1 //===- SLPVectorizer.cpp - A bottom up SLP Vectorizer ---------------------===// 2 // 3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. 4 // See https://llvm.org/LICENSE.txt for license information. 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 6 // 7 //===----------------------------------------------------------------------===// 8 // 9 // This pass implements the Bottom Up SLP vectorizer. It detects consecutive 10 // stores that can be put together into vector-stores. Next, it attempts to 11 // construct vectorizable tree using the use-def chains. If a profitable tree 12 // was found, the SLP vectorizer performs vectorization on the tree. 13 // 14 // The pass is inspired by the work described in the paper: 15 // "Loop-Aware SLP in GCC" by Ira Rosen, Dorit Nuzman, Ayal Zaks. 16 // 17 //===----------------------------------------------------------------------===// 18 19 #include "llvm/Transforms/Vectorize/SLPVectorizer.h" 20 #include "llvm/ADT/DenseMap.h" 21 #include "llvm/ADT/DenseSet.h" 22 #include "llvm/ADT/Optional.h" 23 #include "llvm/ADT/PostOrderIterator.h" 24 #include "llvm/ADT/STLExtras.h" 25 #include "llvm/ADT/SetOperations.h" 26 #include "llvm/ADT/SetVector.h" 27 #include "llvm/ADT/SmallBitVector.h" 28 #include "llvm/ADT/SmallPtrSet.h" 29 #include "llvm/ADT/SmallSet.h" 30 #include "llvm/ADT/SmallString.h" 31 #include "llvm/ADT/Statistic.h" 32 #include "llvm/ADT/iterator.h" 33 #include "llvm/ADT/iterator_range.h" 34 #include "llvm/Analysis/AliasAnalysis.h" 35 #include "llvm/Analysis/AssumptionCache.h" 36 #include "llvm/Analysis/CodeMetrics.h" 37 #include "llvm/Analysis/DemandedBits.h" 38 #include "llvm/Analysis/GlobalsModRef.h" 39 #include "llvm/Analysis/IVDescriptors.h" 40 #include "llvm/Analysis/LoopAccessAnalysis.h" 41 #include "llvm/Analysis/LoopInfo.h" 42 #include "llvm/Analysis/MemoryLocation.h" 43 #include "llvm/Analysis/OptimizationRemarkEmitter.h" 44 #include "llvm/Analysis/ScalarEvolution.h" 45 #include "llvm/Analysis/ScalarEvolutionExpressions.h" 46 #include "llvm/Analysis/TargetLibraryInfo.h" 47 #include "llvm/Analysis/TargetTransformInfo.h" 48 #include "llvm/Analysis/ValueTracking.h" 49 #include "llvm/Analysis/VectorUtils.h" 50 #include "llvm/IR/Attributes.h" 51 #include "llvm/IR/BasicBlock.h" 52 #include "llvm/IR/Constant.h" 53 #include "llvm/IR/Constants.h" 54 #include "llvm/IR/DataLayout.h" 55 #include "llvm/IR/DebugLoc.h" 56 #include "llvm/IR/DerivedTypes.h" 57 #include "llvm/IR/Dominators.h" 58 #include "llvm/IR/Function.h" 59 #include "llvm/IR/IRBuilder.h" 60 #include "llvm/IR/InstrTypes.h" 61 #include "llvm/IR/Instruction.h" 62 #include "llvm/IR/Instructions.h" 63 #include "llvm/IR/IntrinsicInst.h" 64 #include "llvm/IR/Intrinsics.h" 65 #include "llvm/IR/Module.h" 66 #include "llvm/IR/NoFolder.h" 67 #include "llvm/IR/Operator.h" 68 #include "llvm/IR/PatternMatch.h" 69 #include "llvm/IR/Type.h" 70 #include "llvm/IR/Use.h" 71 #include "llvm/IR/User.h" 72 #include "llvm/IR/Value.h" 73 #include "llvm/IR/ValueHandle.h" 74 #include "llvm/IR/Verifier.h" 75 #include "llvm/InitializePasses.h" 76 #include "llvm/Pass.h" 77 #include "llvm/Support/Casting.h" 78 #include "llvm/Support/CommandLine.h" 79 #include "llvm/Support/Compiler.h" 80 #include "llvm/Support/DOTGraphTraits.h" 81 #include "llvm/Support/Debug.h" 82 #include "llvm/Support/ErrorHandling.h" 83 #include "llvm/Support/GraphWriter.h" 84 #include "llvm/Support/InstructionCost.h" 85 #include "llvm/Support/KnownBits.h" 86 #include "llvm/Support/MathExtras.h" 87 #include "llvm/Support/raw_ostream.h" 88 #include "llvm/Transforms/Utils/InjectTLIMappings.h" 89 #include "llvm/Transforms/Utils/LoopUtils.h" 90 #include "llvm/Transforms/Vectorize.h" 91 #include <algorithm> 92 #include <cassert> 93 #include <cstdint> 94 #include <iterator> 95 #include <memory> 96 #include <set> 97 #include <string> 98 #include <tuple> 99 #include <utility> 100 #include <vector> 101 102 using namespace llvm; 103 using namespace llvm::PatternMatch; 104 using namespace slpvectorizer; 105 106 #define SV_NAME "slp-vectorizer" 107 #define DEBUG_TYPE "SLP" 108 109 STATISTIC(NumVectorInstructions, "Number of vector instructions generated"); 110 111 cl::opt<bool> RunSLPVectorization("vectorize-slp", cl::init(true), cl::Hidden, 112 cl::desc("Run the SLP vectorization passes")); 113 114 static cl::opt<int> 115 SLPCostThreshold("slp-threshold", cl::init(0), cl::Hidden, 116 cl::desc("Only vectorize if you gain more than this " 117 "number ")); 118 119 static cl::opt<bool> 120 ShouldVectorizeHor("slp-vectorize-hor", cl::init(true), cl::Hidden, 121 cl::desc("Attempt to vectorize horizontal reductions")); 122 123 static cl::opt<bool> ShouldStartVectorizeHorAtStore( 124 "slp-vectorize-hor-store", cl::init(false), cl::Hidden, 125 cl::desc( 126 "Attempt to vectorize horizontal reductions feeding into a store")); 127 128 static cl::opt<int> 129 MaxVectorRegSizeOption("slp-max-reg-size", cl::init(128), cl::Hidden, 130 cl::desc("Attempt to vectorize for this register size in bits")); 131 132 static cl::opt<unsigned> 133 MaxVFOption("slp-max-vf", cl::init(0), cl::Hidden, 134 cl::desc("Maximum SLP vectorization factor (0=unlimited)")); 135 136 static cl::opt<int> 137 MaxStoreLookup("slp-max-store-lookup", cl::init(32), cl::Hidden, 138 cl::desc("Maximum depth of the lookup for consecutive stores.")); 139 140 /// Limits the size of scheduling regions in a block. 141 /// It avoid long compile times for _very_ large blocks where vector 142 /// instructions are spread over a wide range. 143 /// This limit is way higher than needed by real-world functions. 144 static cl::opt<int> 145 ScheduleRegionSizeBudget("slp-schedule-budget", cl::init(100000), cl::Hidden, 146 cl::desc("Limit the size of the SLP scheduling region per block")); 147 148 static cl::opt<int> MinVectorRegSizeOption( 149 "slp-min-reg-size", cl::init(128), cl::Hidden, 150 cl::desc("Attempt to vectorize for this register size in bits")); 151 152 static cl::opt<unsigned> RecursionMaxDepth( 153 "slp-recursion-max-depth", cl::init(12), cl::Hidden, 154 cl::desc("Limit the recursion depth when building a vectorizable tree")); 155 156 static cl::opt<unsigned> MinTreeSize( 157 "slp-min-tree-size", cl::init(3), cl::Hidden, 158 cl::desc("Only vectorize small trees if they are fully vectorizable")); 159 160 // The maximum depth that the look-ahead score heuristic will explore. 161 // The higher this value, the higher the compilation time overhead. 162 static cl::opt<int> LookAheadMaxDepth( 163 "slp-max-look-ahead-depth", cl::init(2), cl::Hidden, 164 cl::desc("The maximum look-ahead depth for operand reordering scores")); 165 166 // The Look-ahead heuristic goes through the users of the bundle to calculate 167 // the users cost in getExternalUsesCost(). To avoid compilation time increase 168 // we limit the number of users visited to this value. 169 static cl::opt<unsigned> LookAheadUsersBudget( 170 "slp-look-ahead-users-budget", cl::init(2), cl::Hidden, 171 cl::desc("The maximum number of users to visit while visiting the " 172 "predecessors. This prevents compilation time increase.")); 173 174 static cl::opt<bool> 175 ViewSLPTree("view-slp-tree", cl::Hidden, 176 cl::desc("Display the SLP trees with Graphviz")); 177 178 // Limit the number of alias checks. The limit is chosen so that 179 // it has no negative effect on the llvm benchmarks. 180 static const unsigned AliasedCheckLimit = 10; 181 182 // Another limit for the alias checks: The maximum distance between load/store 183 // instructions where alias checks are done. 184 // This limit is useful for very large basic blocks. 185 static const unsigned MaxMemDepDistance = 160; 186 187 /// If the ScheduleRegionSizeBudget is exhausted, we allow small scheduling 188 /// regions to be handled. 189 static const int MinScheduleRegionSize = 16; 190 191 /// Predicate for the element types that the SLP vectorizer supports. 192 /// 193 /// The most important thing to filter here are types which are invalid in LLVM 194 /// vectors. We also filter target specific types which have absolutely no 195 /// meaningful vectorization path such as x86_fp80 and ppc_f128. This just 196 /// avoids spending time checking the cost model and realizing that they will 197 /// be inevitably scalarized. 198 static bool isValidElementType(Type *Ty) { 199 return VectorType::isValidElementType(Ty) && !Ty->isX86_FP80Ty() && 200 !Ty->isPPC_FP128Ty(); 201 } 202 203 /// \returns true if all of the instructions in \p VL are in the same block or 204 /// false otherwise. 205 static bool allSameBlock(ArrayRef<Value *> VL) { 206 Instruction *I0 = dyn_cast<Instruction>(VL[0]); 207 if (!I0) 208 return false; 209 BasicBlock *BB = I0->getParent(); 210 for (int I = 1, E = VL.size(); I < E; I++) { 211 auto *II = dyn_cast<Instruction>(VL[I]); 212 if (!II) 213 return false; 214 215 if (BB != II->getParent()) 216 return false; 217 } 218 return true; 219 } 220 221 /// \returns True if the value is a constant (but not globals/constant 222 /// expressions). 223 static bool isConstant(Value *V) { 224 return isa<Constant>(V) && !isa<ConstantExpr>(V) && !isa<GlobalValue>(V); 225 } 226 227 /// \returns True if all of the values in \p VL are constants (but not 228 /// globals/constant expressions). 229 static bool allConstant(ArrayRef<Value *> VL) { 230 // Constant expressions and globals can't be vectorized like normal integer/FP 231 // constants. 232 return all_of(VL, isConstant); 233 } 234 235 /// \returns True if all of the values in \p VL are identical. 236 static bool isSplat(ArrayRef<Value *> VL) { 237 for (unsigned i = 1, e = VL.size(); i < e; ++i) 238 if (VL[i] != VL[0]) 239 return false; 240 return true; 241 } 242 243 /// \returns True if \p I is commutative, handles CmpInst and BinaryOperator. 244 static bool isCommutative(Instruction *I) { 245 if (auto *Cmp = dyn_cast<CmpInst>(I)) 246 return Cmp->isCommutative(); 247 if (auto *BO = dyn_cast<BinaryOperator>(I)) 248 return BO->isCommutative(); 249 // TODO: This should check for generic Instruction::isCommutative(), but 250 // we need to confirm that the caller code correctly handles Intrinsics 251 // for example (does not have 2 operands). 252 return false; 253 } 254 255 /// Checks if the vector of instructions can be represented as a shuffle, like: 256 /// %x0 = extractelement <4 x i8> %x, i32 0 257 /// %x3 = extractelement <4 x i8> %x, i32 3 258 /// %y1 = extractelement <4 x i8> %y, i32 1 259 /// %y2 = extractelement <4 x i8> %y, i32 2 260 /// %x0x0 = mul i8 %x0, %x0 261 /// %x3x3 = mul i8 %x3, %x3 262 /// %y1y1 = mul i8 %y1, %y1 263 /// %y2y2 = mul i8 %y2, %y2 264 /// %ins1 = insertelement <4 x i8> poison, i8 %x0x0, i32 0 265 /// %ins2 = insertelement <4 x i8> %ins1, i8 %x3x3, i32 1 266 /// %ins3 = insertelement <4 x i8> %ins2, i8 %y1y1, i32 2 267 /// %ins4 = insertelement <4 x i8> %ins3, i8 %y2y2, i32 3 268 /// ret <4 x i8> %ins4 269 /// can be transformed into: 270 /// %1 = shufflevector <4 x i8> %x, <4 x i8> %y, <4 x i32> <i32 0, i32 3, i32 5, 271 /// i32 6> 272 /// %2 = mul <4 x i8> %1, %1 273 /// ret <4 x i8> %2 274 /// We convert this initially to something like: 275 /// %x0 = extractelement <4 x i8> %x, i32 0 276 /// %x3 = extractelement <4 x i8> %x, i32 3 277 /// %y1 = extractelement <4 x i8> %y, i32 1 278 /// %y2 = extractelement <4 x i8> %y, i32 2 279 /// %1 = insertelement <4 x i8> poison, i8 %x0, i32 0 280 /// %2 = insertelement <4 x i8> %1, i8 %x3, i32 1 281 /// %3 = insertelement <4 x i8> %2, i8 %y1, i32 2 282 /// %4 = insertelement <4 x i8> %3, i8 %y2, i32 3 283 /// %5 = mul <4 x i8> %4, %4 284 /// %6 = extractelement <4 x i8> %5, i32 0 285 /// %ins1 = insertelement <4 x i8> poison, i8 %6, i32 0 286 /// %7 = extractelement <4 x i8> %5, i32 1 287 /// %ins2 = insertelement <4 x i8> %ins1, i8 %7, i32 1 288 /// %8 = extractelement <4 x i8> %5, i32 2 289 /// %ins3 = insertelement <4 x i8> %ins2, i8 %8, i32 2 290 /// %9 = extractelement <4 x i8> %5, i32 3 291 /// %ins4 = insertelement <4 x i8> %ins3, i8 %9, i32 3 292 /// ret <4 x i8> %ins4 293 /// InstCombiner transforms this into a shuffle and vector mul 294 /// Mask will return the Shuffle Mask equivalent to the extracted elements. 295 /// TODO: Can we split off and reuse the shuffle mask detection from 296 /// TargetTransformInfo::getInstructionThroughput? 297 static Optional<TargetTransformInfo::ShuffleKind> 298 isShuffle(ArrayRef<Value *> VL, SmallVectorImpl<int> &Mask) { 299 auto *EI0 = cast<ExtractElementInst>(VL[0]); 300 unsigned Size = 301 cast<FixedVectorType>(EI0->getVectorOperandType())->getNumElements(); 302 Value *Vec1 = nullptr; 303 Value *Vec2 = nullptr; 304 enum ShuffleMode { Unknown, Select, Permute }; 305 ShuffleMode CommonShuffleMode = Unknown; 306 for (unsigned I = 0, E = VL.size(); I < E; ++I) { 307 auto *EI = cast<ExtractElementInst>(VL[I]); 308 auto *Vec = EI->getVectorOperand(); 309 // All vector operands must have the same number of vector elements. 310 if (cast<FixedVectorType>(Vec->getType())->getNumElements() != Size) 311 return None; 312 auto *Idx = dyn_cast<ConstantInt>(EI->getIndexOperand()); 313 if (!Idx) 314 return None; 315 // Undefined behavior if Idx is negative or >= Size. 316 if (Idx->getValue().uge(Size)) { 317 Mask.push_back(UndefMaskElem); 318 continue; 319 } 320 unsigned IntIdx = Idx->getValue().getZExtValue(); 321 Mask.push_back(IntIdx); 322 // We can extractelement from undef or poison vector. 323 if (isa<UndefValue>(Vec)) 324 continue; 325 // For correct shuffling we have to have at most 2 different vector operands 326 // in all extractelement instructions. 327 if (!Vec1 || Vec1 == Vec) 328 Vec1 = Vec; 329 else if (!Vec2 || Vec2 == Vec) 330 Vec2 = Vec; 331 else 332 return None; 333 if (CommonShuffleMode == Permute) 334 continue; 335 // If the extract index is not the same as the operation number, it is a 336 // permutation. 337 if (IntIdx != I) { 338 CommonShuffleMode = Permute; 339 continue; 340 } 341 CommonShuffleMode = Select; 342 } 343 // If we're not crossing lanes in different vectors, consider it as blending. 344 if (CommonShuffleMode == Select && Vec2) 345 return TargetTransformInfo::SK_Select; 346 // If Vec2 was never used, we have a permutation of a single vector, otherwise 347 // we have permutation of 2 vectors. 348 return Vec2 ? TargetTransformInfo::SK_PermuteTwoSrc 349 : TargetTransformInfo::SK_PermuteSingleSrc; 350 } 351 352 namespace { 353 354 /// Main data required for vectorization of instructions. 355 struct InstructionsState { 356 /// The very first instruction in the list with the main opcode. 357 Value *OpValue = nullptr; 358 359 /// The main/alternate instruction. 360 Instruction *MainOp = nullptr; 361 Instruction *AltOp = nullptr; 362 363 /// The main/alternate opcodes for the list of instructions. 364 unsigned getOpcode() const { 365 return MainOp ? MainOp->getOpcode() : 0; 366 } 367 368 unsigned getAltOpcode() const { 369 return AltOp ? AltOp->getOpcode() : 0; 370 } 371 372 /// Some of the instructions in the list have alternate opcodes. 373 bool isAltShuffle() const { return getOpcode() != getAltOpcode(); } 374 375 bool isOpcodeOrAlt(Instruction *I) const { 376 unsigned CheckedOpcode = I->getOpcode(); 377 return getOpcode() == CheckedOpcode || getAltOpcode() == CheckedOpcode; 378 } 379 380 InstructionsState() = delete; 381 InstructionsState(Value *OpValue, Instruction *MainOp, Instruction *AltOp) 382 : OpValue(OpValue), MainOp(MainOp), AltOp(AltOp) {} 383 }; 384 385 } // end anonymous namespace 386 387 /// Chooses the correct key for scheduling data. If \p Op has the same (or 388 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is \p 389 /// OpValue. 390 static Value *isOneOf(const InstructionsState &S, Value *Op) { 391 auto *I = dyn_cast<Instruction>(Op); 392 if (I && S.isOpcodeOrAlt(I)) 393 return Op; 394 return S.OpValue; 395 } 396 397 /// \returns true if \p Opcode is allowed as part of of the main/alternate 398 /// instruction for SLP vectorization. 399 /// 400 /// Example of unsupported opcode is SDIV that can potentially cause UB if the 401 /// "shuffled out" lane would result in division by zero. 402 static bool isValidForAlternation(unsigned Opcode) { 403 if (Instruction::isIntDivRem(Opcode)) 404 return false; 405 406 return true; 407 } 408 409 /// \returns analysis of the Instructions in \p VL described in 410 /// InstructionsState, the Opcode that we suppose the whole list 411 /// could be vectorized even if its structure is diverse. 412 static InstructionsState getSameOpcode(ArrayRef<Value *> VL, 413 unsigned BaseIndex = 0) { 414 // Make sure these are all Instructions. 415 if (llvm::any_of(VL, [](Value *V) { return !isa<Instruction>(V); })) 416 return InstructionsState(VL[BaseIndex], nullptr, nullptr); 417 418 bool IsCastOp = isa<CastInst>(VL[BaseIndex]); 419 bool IsBinOp = isa<BinaryOperator>(VL[BaseIndex]); 420 unsigned Opcode = cast<Instruction>(VL[BaseIndex])->getOpcode(); 421 unsigned AltOpcode = Opcode; 422 unsigned AltIndex = BaseIndex; 423 424 // Check for one alternate opcode from another BinaryOperator. 425 // TODO - generalize to support all operators (types, calls etc.). 426 for (int Cnt = 0, E = VL.size(); Cnt < E; Cnt++) { 427 unsigned InstOpcode = cast<Instruction>(VL[Cnt])->getOpcode(); 428 if (IsBinOp && isa<BinaryOperator>(VL[Cnt])) { 429 if (InstOpcode == Opcode || InstOpcode == AltOpcode) 430 continue; 431 if (Opcode == AltOpcode && isValidForAlternation(InstOpcode) && 432 isValidForAlternation(Opcode)) { 433 AltOpcode = InstOpcode; 434 AltIndex = Cnt; 435 continue; 436 } 437 } else if (IsCastOp && isa<CastInst>(VL[Cnt])) { 438 Type *Ty0 = cast<Instruction>(VL[BaseIndex])->getOperand(0)->getType(); 439 Type *Ty1 = cast<Instruction>(VL[Cnt])->getOperand(0)->getType(); 440 if (Ty0 == Ty1) { 441 if (InstOpcode == Opcode || InstOpcode == AltOpcode) 442 continue; 443 if (Opcode == AltOpcode) { 444 assert(isValidForAlternation(Opcode) && 445 isValidForAlternation(InstOpcode) && 446 "Cast isn't safe for alternation, logic needs to be updated!"); 447 AltOpcode = InstOpcode; 448 AltIndex = Cnt; 449 continue; 450 } 451 } 452 } else if (InstOpcode == Opcode || InstOpcode == AltOpcode) 453 continue; 454 return InstructionsState(VL[BaseIndex], nullptr, nullptr); 455 } 456 457 return InstructionsState(VL[BaseIndex], cast<Instruction>(VL[BaseIndex]), 458 cast<Instruction>(VL[AltIndex])); 459 } 460 461 /// \returns true if all of the values in \p VL have the same type or false 462 /// otherwise. 463 static bool allSameType(ArrayRef<Value *> VL) { 464 Type *Ty = VL[0]->getType(); 465 for (int i = 1, e = VL.size(); i < e; i++) 466 if (VL[i]->getType() != Ty) 467 return false; 468 469 return true; 470 } 471 472 /// \returns True if Extract{Value,Element} instruction extracts element Idx. 473 static Optional<unsigned> getExtractIndex(Instruction *E) { 474 unsigned Opcode = E->getOpcode(); 475 assert((Opcode == Instruction::ExtractElement || 476 Opcode == Instruction::ExtractValue) && 477 "Expected extractelement or extractvalue instruction."); 478 if (Opcode == Instruction::ExtractElement) { 479 auto *CI = dyn_cast<ConstantInt>(E->getOperand(1)); 480 if (!CI) 481 return None; 482 return CI->getZExtValue(); 483 } 484 ExtractValueInst *EI = cast<ExtractValueInst>(E); 485 if (EI->getNumIndices() != 1) 486 return None; 487 return *EI->idx_begin(); 488 } 489 490 /// \returns True if in-tree use also needs extract. This refers to 491 /// possible scalar operand in vectorized instruction. 492 static bool InTreeUserNeedToExtract(Value *Scalar, Instruction *UserInst, 493 TargetLibraryInfo *TLI) { 494 unsigned Opcode = UserInst->getOpcode(); 495 switch (Opcode) { 496 case Instruction::Load: { 497 LoadInst *LI = cast<LoadInst>(UserInst); 498 return (LI->getPointerOperand() == Scalar); 499 } 500 case Instruction::Store: { 501 StoreInst *SI = cast<StoreInst>(UserInst); 502 return (SI->getPointerOperand() == Scalar); 503 } 504 case Instruction::Call: { 505 CallInst *CI = cast<CallInst>(UserInst); 506 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 507 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 508 if (hasVectorInstrinsicScalarOpd(ID, i)) 509 return (CI->getArgOperand(i) == Scalar); 510 } 511 LLVM_FALLTHROUGH; 512 } 513 default: 514 return false; 515 } 516 } 517 518 /// \returns the AA location that is being access by the instruction. 519 static MemoryLocation getLocation(Instruction *I, AAResults *AA) { 520 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 521 return MemoryLocation::get(SI); 522 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 523 return MemoryLocation::get(LI); 524 return MemoryLocation(); 525 } 526 527 /// \returns True if the instruction is not a volatile or atomic load/store. 528 static bool isSimple(Instruction *I) { 529 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 530 return LI->isSimple(); 531 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 532 return SI->isSimple(); 533 if (MemIntrinsic *MI = dyn_cast<MemIntrinsic>(I)) 534 return !MI->isVolatile(); 535 return true; 536 } 537 538 namespace llvm { 539 540 static void inversePermutation(ArrayRef<unsigned> Indices, 541 SmallVectorImpl<int> &Mask) { 542 Mask.clear(); 543 const unsigned E = Indices.size(); 544 Mask.resize(E, E + 1); 545 for (unsigned I = 0; I < E; ++I) 546 Mask[Indices[I]] = I; 547 } 548 549 /// \returns inserting index of InsertElement or InsertValue instruction, 550 /// using Offset as base offset for index. 551 static Optional<int> getInsertIndex(Value *InsertInst, unsigned Offset) { 552 int Index = Offset; 553 if (auto *IE = dyn_cast<InsertElementInst>(InsertInst)) { 554 if (auto *CI = dyn_cast<ConstantInt>(IE->getOperand(2))) { 555 auto *VT = cast<FixedVectorType>(IE->getType()); 556 if (CI->getValue().uge(VT->getNumElements())) 557 return UndefMaskElem; 558 Index *= VT->getNumElements(); 559 Index += CI->getZExtValue(); 560 return Index; 561 } 562 if (isa<UndefValue>(IE->getOperand(2))) 563 return UndefMaskElem; 564 return None; 565 } 566 567 auto *IV = cast<InsertValueInst>(InsertInst); 568 Type *CurrentType = IV->getType(); 569 for (unsigned I : IV->indices()) { 570 if (auto *ST = dyn_cast<StructType>(CurrentType)) { 571 Index *= ST->getNumElements(); 572 CurrentType = ST->getElementType(I); 573 } else if (auto *AT = dyn_cast<ArrayType>(CurrentType)) { 574 Index *= AT->getNumElements(); 575 CurrentType = AT->getElementType(); 576 } else { 577 return None; 578 } 579 Index += I; 580 } 581 return Index; 582 } 583 584 namespace slpvectorizer { 585 586 /// Bottom Up SLP Vectorizer. 587 class BoUpSLP { 588 struct TreeEntry; 589 struct ScheduleData; 590 591 public: 592 using ValueList = SmallVector<Value *, 8>; 593 using InstrList = SmallVector<Instruction *, 16>; 594 using ValueSet = SmallPtrSet<Value *, 16>; 595 using StoreList = SmallVector<StoreInst *, 8>; 596 using ExtraValueToDebugLocsMap = 597 MapVector<Value *, SmallVector<Instruction *, 2>>; 598 using OrdersType = SmallVector<unsigned, 4>; 599 600 BoUpSLP(Function *Func, ScalarEvolution *Se, TargetTransformInfo *Tti, 601 TargetLibraryInfo *TLi, AAResults *Aa, LoopInfo *Li, 602 DominatorTree *Dt, AssumptionCache *AC, DemandedBits *DB, 603 const DataLayout *DL, OptimizationRemarkEmitter *ORE) 604 : F(Func), SE(Se), TTI(Tti), TLI(TLi), AA(Aa), LI(Li), DT(Dt), AC(AC), 605 DB(DB), DL(DL), ORE(ORE), Builder(Se->getContext()) { 606 CodeMetrics::collectEphemeralValues(F, AC, EphValues); 607 // Use the vector register size specified by the target unless overridden 608 // by a command-line option. 609 // TODO: It would be better to limit the vectorization factor based on 610 // data type rather than just register size. For example, x86 AVX has 611 // 256-bit registers, but it does not support integer operations 612 // at that width (that requires AVX2). 613 if (MaxVectorRegSizeOption.getNumOccurrences()) 614 MaxVecRegSize = MaxVectorRegSizeOption; 615 else 616 MaxVecRegSize = 617 TTI->getRegisterBitWidth(TargetTransformInfo::RGK_FixedWidthVector) 618 .getFixedSize(); 619 620 if (MinVectorRegSizeOption.getNumOccurrences()) 621 MinVecRegSize = MinVectorRegSizeOption; 622 else 623 MinVecRegSize = TTI->getMinVectorRegisterBitWidth(); 624 } 625 626 /// Vectorize the tree that starts with the elements in \p VL. 627 /// Returns the vectorized root. 628 Value *vectorizeTree(); 629 630 /// Vectorize the tree but with the list of externally used values \p 631 /// ExternallyUsedValues. Values in this MapVector can be replaced but the 632 /// generated extractvalue instructions. 633 Value *vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues); 634 635 /// \returns the cost incurred by unwanted spills and fills, caused by 636 /// holding live values over call sites. 637 InstructionCost getSpillCost() const; 638 639 /// \returns the vectorization cost of the subtree that starts at \p VL. 640 /// A negative number means that this is profitable. 641 InstructionCost getTreeCost(ArrayRef<Value *> VectorizedVals = None); 642 643 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 644 /// the purpose of scheduling and extraction in the \p UserIgnoreLst. 645 void buildTree(ArrayRef<Value *> Roots, 646 ArrayRef<Value *> UserIgnoreLst = None); 647 648 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 649 /// the purpose of scheduling and extraction in the \p UserIgnoreLst taking 650 /// into account (and updating it, if required) list of externally used 651 /// values stored in \p ExternallyUsedValues. 652 void buildTree(ArrayRef<Value *> Roots, 653 ExtraValueToDebugLocsMap &ExternallyUsedValues, 654 ArrayRef<Value *> UserIgnoreLst = None); 655 656 /// Clear the internal data structures that are created by 'buildTree'. 657 void deleteTree() { 658 VectorizableTree.clear(); 659 ScalarToTreeEntry.clear(); 660 MustGather.clear(); 661 ExternalUses.clear(); 662 NumOpsWantToKeepOrder.clear(); 663 NumOpsWantToKeepOriginalOrder = 0; 664 for (auto &Iter : BlocksSchedules) { 665 BlockScheduling *BS = Iter.second.get(); 666 BS->clear(); 667 } 668 MinBWs.clear(); 669 InstrElementSize.clear(); 670 } 671 672 unsigned getTreeSize() const { return VectorizableTree.size(); } 673 674 /// Perform LICM and CSE on the newly generated gather sequences. 675 void optimizeGatherSequence(); 676 677 /// \returns The best order of instructions for vectorization. 678 Optional<ArrayRef<unsigned>> bestOrder() const { 679 assert(llvm::all_of( 680 NumOpsWantToKeepOrder, 681 [this](const decltype(NumOpsWantToKeepOrder)::value_type &D) { 682 return D.getFirst().size() == 683 VectorizableTree[0]->Scalars.size(); 684 }) && 685 "All orders must have the same size as number of instructions in " 686 "tree node."); 687 auto I = std::max_element( 688 NumOpsWantToKeepOrder.begin(), NumOpsWantToKeepOrder.end(), 689 [](const decltype(NumOpsWantToKeepOrder)::value_type &D1, 690 const decltype(NumOpsWantToKeepOrder)::value_type &D2) { 691 return D1.second < D2.second; 692 }); 693 if (I == NumOpsWantToKeepOrder.end() || 694 I->getSecond() <= NumOpsWantToKeepOriginalOrder) 695 return None; 696 697 return makeArrayRef(I->getFirst()); 698 } 699 700 /// Builds the correct order for root instructions. 701 /// If some leaves have the same instructions to be vectorized, we may 702 /// incorrectly evaluate the best order for the root node (it is built for the 703 /// vector of instructions without repeated instructions and, thus, has less 704 /// elements than the root node). This function builds the correct order for 705 /// the root node. 706 /// For example, if the root node is \<a+b, a+c, a+d, f+e\>, then the leaves 707 /// are \<a, a, a, f\> and \<b, c, d, e\>. When we try to vectorize the first 708 /// leaf, it will be shrink to \<a, b\>. If instructions in this leaf should 709 /// be reordered, the best order will be \<1, 0\>. We need to extend this 710 /// order for the root node. For the root node this order should look like 711 /// \<3, 0, 1, 2\>. This function extends the order for the reused 712 /// instructions. 713 void findRootOrder(OrdersType &Order) { 714 // If the leaf has the same number of instructions to vectorize as the root 715 // - order must be set already. 716 unsigned RootSize = VectorizableTree[0]->Scalars.size(); 717 if (Order.size() == RootSize) 718 return; 719 SmallVector<unsigned, 4> RealOrder(Order.size()); 720 std::swap(Order, RealOrder); 721 SmallVector<int, 4> Mask; 722 inversePermutation(RealOrder, Mask); 723 Order.assign(Mask.begin(), Mask.end()); 724 // The leaf has less number of instructions - need to find the true order of 725 // the root. 726 // Scan the nodes starting from the leaf back to the root. 727 const TreeEntry *PNode = VectorizableTree.back().get(); 728 SmallVector<const TreeEntry *, 4> Nodes(1, PNode); 729 SmallPtrSet<const TreeEntry *, 4> Visited; 730 while (!Nodes.empty() && Order.size() != RootSize) { 731 const TreeEntry *PNode = Nodes.pop_back_val(); 732 if (!Visited.insert(PNode).second) 733 continue; 734 const TreeEntry &Node = *PNode; 735 for (const EdgeInfo &EI : Node.UserTreeIndices) 736 if (EI.UserTE) 737 Nodes.push_back(EI.UserTE); 738 if (Node.ReuseShuffleIndices.empty()) 739 continue; 740 // Build the order for the parent node. 741 OrdersType NewOrder(Node.ReuseShuffleIndices.size(), RootSize); 742 SmallVector<unsigned, 4> OrderCounter(Order.size(), 0); 743 // The algorithm of the order extension is: 744 // 1. Calculate the number of the same instructions for the order. 745 // 2. Calculate the index of the new order: total number of instructions 746 // with order less than the order of the current instruction + reuse 747 // number of the current instruction. 748 // 3. The new order is just the index of the instruction in the original 749 // vector of the instructions. 750 for (unsigned I : Node.ReuseShuffleIndices) 751 ++OrderCounter[Order[I]]; 752 SmallVector<unsigned, 4> CurrentCounter(Order.size(), 0); 753 for (unsigned I = 0, E = Node.ReuseShuffleIndices.size(); I < E; ++I) { 754 unsigned ReusedIdx = Node.ReuseShuffleIndices[I]; 755 unsigned OrderIdx = Order[ReusedIdx]; 756 unsigned NewIdx = 0; 757 for (unsigned J = 0; J < OrderIdx; ++J) 758 NewIdx += OrderCounter[J]; 759 NewIdx += CurrentCounter[OrderIdx]; 760 ++CurrentCounter[OrderIdx]; 761 assert(NewOrder[NewIdx] == RootSize && 762 "The order index should not be written already."); 763 NewOrder[NewIdx] = I; 764 } 765 std::swap(Order, NewOrder); 766 } 767 assert(Order.size() == RootSize && 768 "Root node is expected or the size of the order must be the same as " 769 "the number of elements in the root node."); 770 assert(llvm::all_of(Order, 771 [RootSize](unsigned Val) { return Val != RootSize; }) && 772 "All indices must be initialized"); 773 } 774 775 /// \return The vector element size in bits to use when vectorizing the 776 /// expression tree ending at \p V. If V is a store, the size is the width of 777 /// the stored value. Otherwise, the size is the width of the largest loaded 778 /// value reaching V. This method is used by the vectorizer to calculate 779 /// vectorization factors. 780 unsigned getVectorElementSize(Value *V); 781 782 /// Compute the minimum type sizes required to represent the entries in a 783 /// vectorizable tree. 784 void computeMinimumValueSizes(); 785 786 // \returns maximum vector register size as set by TTI or overridden by cl::opt. 787 unsigned getMaxVecRegSize() const { 788 return MaxVecRegSize; 789 } 790 791 // \returns minimum vector register size as set by cl::opt. 792 unsigned getMinVecRegSize() const { 793 return MinVecRegSize; 794 } 795 796 unsigned getMaximumVF(unsigned ElemWidth, unsigned Opcode) const { 797 unsigned MaxVF = MaxVFOption.getNumOccurrences() ? 798 MaxVFOption : TTI->getMaximumVF(ElemWidth, Opcode); 799 return MaxVF ? MaxVF : UINT_MAX; 800 } 801 802 /// Check if homogeneous aggregate is isomorphic to some VectorType. 803 /// Accepts homogeneous multidimensional aggregate of scalars/vectors like 804 /// {[4 x i16], [4 x i16]}, { <2 x float>, <2 x float> }, 805 /// {{{i16, i16}, {i16, i16}}, {{i16, i16}, {i16, i16}}} and so on. 806 /// 807 /// \returns number of elements in vector if isomorphism exists, 0 otherwise. 808 unsigned canMapToVector(Type *T, const DataLayout &DL) const; 809 810 /// \returns True if the VectorizableTree is both tiny and not fully 811 /// vectorizable. We do not vectorize such trees. 812 bool isTreeTinyAndNotFullyVectorizable() const; 813 814 /// Assume that a legal-sized 'or'-reduction of shifted/zexted loaded values 815 /// can be load combined in the backend. Load combining may not be allowed in 816 /// the IR optimizer, so we do not want to alter the pattern. For example, 817 /// partially transforming a scalar bswap() pattern into vector code is 818 /// effectively impossible for the backend to undo. 819 /// TODO: If load combining is allowed in the IR optimizer, this analysis 820 /// may not be necessary. 821 bool isLoadCombineReductionCandidate(RecurKind RdxKind) const; 822 823 /// Assume that a vector of stores of bitwise-or/shifted/zexted loaded values 824 /// can be load combined in the backend. Load combining may not be allowed in 825 /// the IR optimizer, so we do not want to alter the pattern. For example, 826 /// partially transforming a scalar bswap() pattern into vector code is 827 /// effectively impossible for the backend to undo. 828 /// TODO: If load combining is allowed in the IR optimizer, this analysis 829 /// may not be necessary. 830 bool isLoadCombineCandidate() const; 831 832 OptimizationRemarkEmitter *getORE() { return ORE; } 833 834 /// This structure holds any data we need about the edges being traversed 835 /// during buildTree_rec(). We keep track of: 836 /// (i) the user TreeEntry index, and 837 /// (ii) the index of the edge. 838 struct EdgeInfo { 839 EdgeInfo() = default; 840 EdgeInfo(TreeEntry *UserTE, unsigned EdgeIdx) 841 : UserTE(UserTE), EdgeIdx(EdgeIdx) {} 842 /// The user TreeEntry. 843 TreeEntry *UserTE = nullptr; 844 /// The operand index of the use. 845 unsigned EdgeIdx = UINT_MAX; 846 #ifndef NDEBUG 847 friend inline raw_ostream &operator<<(raw_ostream &OS, 848 const BoUpSLP::EdgeInfo &EI) { 849 EI.dump(OS); 850 return OS; 851 } 852 /// Debug print. 853 void dump(raw_ostream &OS) const { 854 OS << "{User:" << (UserTE ? std::to_string(UserTE->Idx) : "null") 855 << " EdgeIdx:" << EdgeIdx << "}"; 856 } 857 LLVM_DUMP_METHOD void dump() const { dump(dbgs()); } 858 #endif 859 }; 860 861 /// A helper data structure to hold the operands of a vector of instructions. 862 /// This supports a fixed vector length for all operand vectors. 863 class VLOperands { 864 /// For each operand we need (i) the value, and (ii) the opcode that it 865 /// would be attached to if the expression was in a left-linearized form. 866 /// This is required to avoid illegal operand reordering. 867 /// For example: 868 /// \verbatim 869 /// 0 Op1 870 /// |/ 871 /// Op1 Op2 Linearized + Op2 872 /// \ / ----------> |/ 873 /// - - 874 /// 875 /// Op1 - Op2 (0 + Op1) - Op2 876 /// \endverbatim 877 /// 878 /// Value Op1 is attached to a '+' operation, and Op2 to a '-'. 879 /// 880 /// Another way to think of this is to track all the operations across the 881 /// path from the operand all the way to the root of the tree and to 882 /// calculate the operation that corresponds to this path. For example, the 883 /// path from Op2 to the root crosses the RHS of the '-', therefore the 884 /// corresponding operation is a '-' (which matches the one in the 885 /// linearized tree, as shown above). 886 /// 887 /// For lack of a better term, we refer to this operation as Accumulated 888 /// Path Operation (APO). 889 struct OperandData { 890 OperandData() = default; 891 OperandData(Value *V, bool APO, bool IsUsed) 892 : V(V), APO(APO), IsUsed(IsUsed) {} 893 /// The operand value. 894 Value *V = nullptr; 895 /// TreeEntries only allow a single opcode, or an alternate sequence of 896 /// them (e.g, +, -). Therefore, we can safely use a boolean value for the 897 /// APO. It is set to 'true' if 'V' is attached to an inverse operation 898 /// in the left-linearized form (e.g., Sub/Div), and 'false' otherwise 899 /// (e.g., Add/Mul) 900 bool APO = false; 901 /// Helper data for the reordering function. 902 bool IsUsed = false; 903 }; 904 905 /// During operand reordering, we are trying to select the operand at lane 906 /// that matches best with the operand at the neighboring lane. Our 907 /// selection is based on the type of value we are looking for. For example, 908 /// if the neighboring lane has a load, we need to look for a load that is 909 /// accessing a consecutive address. These strategies are summarized in the 910 /// 'ReorderingMode' enumerator. 911 enum class ReorderingMode { 912 Load, ///< Matching loads to consecutive memory addresses 913 Opcode, ///< Matching instructions based on opcode (same or alternate) 914 Constant, ///< Matching constants 915 Splat, ///< Matching the same instruction multiple times (broadcast) 916 Failed, ///< We failed to create a vectorizable group 917 }; 918 919 using OperandDataVec = SmallVector<OperandData, 2>; 920 921 /// A vector of operand vectors. 922 SmallVector<OperandDataVec, 4> OpsVec; 923 924 const DataLayout &DL; 925 ScalarEvolution &SE; 926 const BoUpSLP &R; 927 928 /// \returns the operand data at \p OpIdx and \p Lane. 929 OperandData &getData(unsigned OpIdx, unsigned Lane) { 930 return OpsVec[OpIdx][Lane]; 931 } 932 933 /// \returns the operand data at \p OpIdx and \p Lane. Const version. 934 const OperandData &getData(unsigned OpIdx, unsigned Lane) const { 935 return OpsVec[OpIdx][Lane]; 936 } 937 938 /// Clears the used flag for all entries. 939 void clearUsed() { 940 for (unsigned OpIdx = 0, NumOperands = getNumOperands(); 941 OpIdx != NumOperands; ++OpIdx) 942 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 943 ++Lane) 944 OpsVec[OpIdx][Lane].IsUsed = false; 945 } 946 947 /// Swap the operand at \p OpIdx1 with that one at \p OpIdx2. 948 void swap(unsigned OpIdx1, unsigned OpIdx2, unsigned Lane) { 949 std::swap(OpsVec[OpIdx1][Lane], OpsVec[OpIdx2][Lane]); 950 } 951 952 // The hard-coded scores listed here are not very important. When computing 953 // the scores of matching one sub-tree with another, we are basically 954 // counting the number of values that are matching. So even if all scores 955 // are set to 1, we would still get a decent matching result. 956 // However, sometimes we have to break ties. For example we may have to 957 // choose between matching loads vs matching opcodes. This is what these 958 // scores are helping us with: they provide the order of preference. 959 960 /// Loads from consecutive memory addresses, e.g. load(A[i]), load(A[i+1]). 961 static const int ScoreConsecutiveLoads = 3; 962 /// ExtractElementInst from same vector and consecutive indexes. 963 static const int ScoreConsecutiveExtracts = 3; 964 /// Constants. 965 static const int ScoreConstants = 2; 966 /// Instructions with the same opcode. 967 static const int ScoreSameOpcode = 2; 968 /// Instructions with alt opcodes (e.g, add + sub). 969 static const int ScoreAltOpcodes = 1; 970 /// Identical instructions (a.k.a. splat or broadcast). 971 static const int ScoreSplat = 1; 972 /// Matching with an undef is preferable to failing. 973 static const int ScoreUndef = 1; 974 /// Score for failing to find a decent match. 975 static const int ScoreFail = 0; 976 /// User exteranl to the vectorized code. 977 static const int ExternalUseCost = 1; 978 /// The user is internal but in a different lane. 979 static const int UserInDiffLaneCost = ExternalUseCost; 980 981 /// \returns the score of placing \p V1 and \p V2 in consecutive lanes. 982 static int getShallowScore(Value *V1, Value *V2, const DataLayout &DL, 983 ScalarEvolution &SE) { 984 auto *LI1 = dyn_cast<LoadInst>(V1); 985 auto *LI2 = dyn_cast<LoadInst>(V2); 986 if (LI1 && LI2) { 987 if (LI1->getParent() != LI2->getParent()) 988 return VLOperands::ScoreFail; 989 990 Optional<int> Dist = getPointersDiff( 991 LI1->getType(), LI1->getPointerOperand(), LI2->getType(), 992 LI2->getPointerOperand(), DL, SE, /*StrictCheck=*/true); 993 return (Dist && *Dist == 1) ? VLOperands::ScoreConsecutiveLoads 994 : VLOperands::ScoreFail; 995 } 996 997 auto *C1 = dyn_cast<Constant>(V1); 998 auto *C2 = dyn_cast<Constant>(V2); 999 if (C1 && C2) 1000 return VLOperands::ScoreConstants; 1001 1002 // Extracts from consecutive indexes of the same vector better score as 1003 // the extracts could be optimized away. 1004 Value *EV; 1005 ConstantInt *Ex1Idx, *Ex2Idx; 1006 if (match(V1, m_ExtractElt(m_Value(EV), m_ConstantInt(Ex1Idx))) && 1007 match(V2, m_ExtractElt(m_Deferred(EV), m_ConstantInt(Ex2Idx))) && 1008 Ex1Idx->getZExtValue() + 1 == Ex2Idx->getZExtValue()) 1009 return VLOperands::ScoreConsecutiveExtracts; 1010 1011 auto *I1 = dyn_cast<Instruction>(V1); 1012 auto *I2 = dyn_cast<Instruction>(V2); 1013 if (I1 && I2) { 1014 if (I1 == I2) 1015 return VLOperands::ScoreSplat; 1016 InstructionsState S = getSameOpcode({I1, I2}); 1017 // Note: Only consider instructions with <= 2 operands to avoid 1018 // complexity explosion. 1019 if (S.getOpcode() && S.MainOp->getNumOperands() <= 2) 1020 return S.isAltShuffle() ? VLOperands::ScoreAltOpcodes 1021 : VLOperands::ScoreSameOpcode; 1022 } 1023 1024 if (isa<UndefValue>(V2)) 1025 return VLOperands::ScoreUndef; 1026 1027 return VLOperands::ScoreFail; 1028 } 1029 1030 /// Holds the values and their lane that are taking part in the look-ahead 1031 /// score calculation. This is used in the external uses cost calculation. 1032 SmallDenseMap<Value *, int> InLookAheadValues; 1033 1034 /// \Returns the additinal cost due to uses of \p LHS and \p RHS that are 1035 /// either external to the vectorized code, or require shuffling. 1036 int getExternalUsesCost(const std::pair<Value *, int> &LHS, 1037 const std::pair<Value *, int> &RHS) { 1038 int Cost = 0; 1039 std::array<std::pair<Value *, int>, 2> Values = {{LHS, RHS}}; 1040 for (int Idx = 0, IdxE = Values.size(); Idx != IdxE; ++Idx) { 1041 Value *V = Values[Idx].first; 1042 if (isa<Constant>(V)) { 1043 // Since this is a function pass, it doesn't make semantic sense to 1044 // walk the users of a subclass of Constant. The users could be in 1045 // another function, or even another module that happens to be in 1046 // the same LLVMContext. 1047 continue; 1048 } 1049 1050 // Calculate the absolute lane, using the minimum relative lane of LHS 1051 // and RHS as base and Idx as the offset. 1052 int Ln = std::min(LHS.second, RHS.second) + Idx; 1053 assert(Ln >= 0 && "Bad lane calculation"); 1054 unsigned UsersBudget = LookAheadUsersBudget; 1055 for (User *U : V->users()) { 1056 if (const TreeEntry *UserTE = R.getTreeEntry(U)) { 1057 // The user is in the VectorizableTree. Check if we need to insert. 1058 auto It = llvm::find(UserTE->Scalars, U); 1059 assert(It != UserTE->Scalars.end() && "U is in UserTE"); 1060 int UserLn = std::distance(UserTE->Scalars.begin(), It); 1061 assert(UserLn >= 0 && "Bad lane"); 1062 if (UserLn != Ln) 1063 Cost += UserInDiffLaneCost; 1064 } else { 1065 // Check if the user is in the look-ahead code. 1066 auto It2 = InLookAheadValues.find(U); 1067 if (It2 != InLookAheadValues.end()) { 1068 // The user is in the look-ahead code. Check the lane. 1069 if (It2->second != Ln) 1070 Cost += UserInDiffLaneCost; 1071 } else { 1072 // The user is neither in SLP tree nor in the look-ahead code. 1073 Cost += ExternalUseCost; 1074 } 1075 } 1076 // Limit the number of visited uses to cap compilation time. 1077 if (--UsersBudget == 0) 1078 break; 1079 } 1080 } 1081 return Cost; 1082 } 1083 1084 /// Go through the operands of \p LHS and \p RHS recursively until \p 1085 /// MaxLevel, and return the cummulative score. For example: 1086 /// \verbatim 1087 /// A[0] B[0] A[1] B[1] C[0] D[0] B[1] A[1] 1088 /// \ / \ / \ / \ / 1089 /// + + + + 1090 /// G1 G2 G3 G4 1091 /// \endverbatim 1092 /// The getScoreAtLevelRec(G1, G2) function will try to match the nodes at 1093 /// each level recursively, accumulating the score. It starts from matching 1094 /// the additions at level 0, then moves on to the loads (level 1). The 1095 /// score of G1 and G2 is higher than G1 and G3, because {A[0],A[1]} and 1096 /// {B[0],B[1]} match with VLOperands::ScoreConsecutiveLoads, while 1097 /// {A[0],C[0]} has a score of VLOperands::ScoreFail. 1098 /// Please note that the order of the operands does not matter, as we 1099 /// evaluate the score of all profitable combinations of operands. In 1100 /// other words the score of G1 and G4 is the same as G1 and G2. This 1101 /// heuristic is based on ideas described in: 1102 /// Look-ahead SLP: Auto-vectorization in the presence of commutative 1103 /// operations, CGO 2018 by Vasileios Porpodas, Rodrigo C. O. Rocha, 1104 /// Luís F. W. Góes 1105 int getScoreAtLevelRec(const std::pair<Value *, int> &LHS, 1106 const std::pair<Value *, int> &RHS, int CurrLevel, 1107 int MaxLevel) { 1108 1109 Value *V1 = LHS.first; 1110 Value *V2 = RHS.first; 1111 // Get the shallow score of V1 and V2. 1112 int ShallowScoreAtThisLevel = 1113 std::max((int)ScoreFail, getShallowScore(V1, V2, DL, SE) - 1114 getExternalUsesCost(LHS, RHS)); 1115 int Lane1 = LHS.second; 1116 int Lane2 = RHS.second; 1117 1118 // If reached MaxLevel, 1119 // or if V1 and V2 are not instructions, 1120 // or if they are SPLAT, 1121 // or if they are not consecutive, early return the current cost. 1122 auto *I1 = dyn_cast<Instruction>(V1); 1123 auto *I2 = dyn_cast<Instruction>(V2); 1124 if (CurrLevel == MaxLevel || !(I1 && I2) || I1 == I2 || 1125 ShallowScoreAtThisLevel == VLOperands::ScoreFail || 1126 (isa<LoadInst>(I1) && isa<LoadInst>(I2) && ShallowScoreAtThisLevel)) 1127 return ShallowScoreAtThisLevel; 1128 assert(I1 && I2 && "Should have early exited."); 1129 1130 // Keep track of in-tree values for determining the external-use cost. 1131 InLookAheadValues[V1] = Lane1; 1132 InLookAheadValues[V2] = Lane2; 1133 1134 // Contains the I2 operand indexes that got matched with I1 operands. 1135 SmallSet<unsigned, 4> Op2Used; 1136 1137 // Recursion towards the operands of I1 and I2. We are trying all possbile 1138 // operand pairs, and keeping track of the best score. 1139 for (unsigned OpIdx1 = 0, NumOperands1 = I1->getNumOperands(); 1140 OpIdx1 != NumOperands1; ++OpIdx1) { 1141 // Try to pair op1I with the best operand of I2. 1142 int MaxTmpScore = 0; 1143 unsigned MaxOpIdx2 = 0; 1144 bool FoundBest = false; 1145 // If I2 is commutative try all combinations. 1146 unsigned FromIdx = isCommutative(I2) ? 0 : OpIdx1; 1147 unsigned ToIdx = isCommutative(I2) 1148 ? I2->getNumOperands() 1149 : std::min(I2->getNumOperands(), OpIdx1 + 1); 1150 assert(FromIdx <= ToIdx && "Bad index"); 1151 for (unsigned OpIdx2 = FromIdx; OpIdx2 != ToIdx; ++OpIdx2) { 1152 // Skip operands already paired with OpIdx1. 1153 if (Op2Used.count(OpIdx2)) 1154 continue; 1155 // Recursively calculate the cost at each level 1156 int TmpScore = getScoreAtLevelRec({I1->getOperand(OpIdx1), Lane1}, 1157 {I2->getOperand(OpIdx2), Lane2}, 1158 CurrLevel + 1, MaxLevel); 1159 // Look for the best score. 1160 if (TmpScore > VLOperands::ScoreFail && TmpScore > MaxTmpScore) { 1161 MaxTmpScore = TmpScore; 1162 MaxOpIdx2 = OpIdx2; 1163 FoundBest = true; 1164 } 1165 } 1166 if (FoundBest) { 1167 // Pair {OpIdx1, MaxOpIdx2} was found to be best. Never revisit it. 1168 Op2Used.insert(MaxOpIdx2); 1169 ShallowScoreAtThisLevel += MaxTmpScore; 1170 } 1171 } 1172 return ShallowScoreAtThisLevel; 1173 } 1174 1175 /// \Returns the look-ahead score, which tells us how much the sub-trees 1176 /// rooted at \p LHS and \p RHS match, the more they match the higher the 1177 /// score. This helps break ties in an informed way when we cannot decide on 1178 /// the order of the operands by just considering the immediate 1179 /// predecessors. 1180 int getLookAheadScore(const std::pair<Value *, int> &LHS, 1181 const std::pair<Value *, int> &RHS) { 1182 InLookAheadValues.clear(); 1183 return getScoreAtLevelRec(LHS, RHS, 1, LookAheadMaxDepth); 1184 } 1185 1186 // Search all operands in Ops[*][Lane] for the one that matches best 1187 // Ops[OpIdx][LastLane] and return its opreand index. 1188 // If no good match can be found, return None. 1189 Optional<unsigned> 1190 getBestOperand(unsigned OpIdx, int Lane, int LastLane, 1191 ArrayRef<ReorderingMode> ReorderingModes) { 1192 unsigned NumOperands = getNumOperands(); 1193 1194 // The operand of the previous lane at OpIdx. 1195 Value *OpLastLane = getData(OpIdx, LastLane).V; 1196 1197 // Our strategy mode for OpIdx. 1198 ReorderingMode RMode = ReorderingModes[OpIdx]; 1199 1200 // The linearized opcode of the operand at OpIdx, Lane. 1201 bool OpIdxAPO = getData(OpIdx, Lane).APO; 1202 1203 // The best operand index and its score. 1204 // Sometimes we have more than one option (e.g., Opcode and Undefs), so we 1205 // are using the score to differentiate between the two. 1206 struct BestOpData { 1207 Optional<unsigned> Idx = None; 1208 unsigned Score = 0; 1209 } BestOp; 1210 1211 // Iterate through all unused operands and look for the best. 1212 for (unsigned Idx = 0; Idx != NumOperands; ++Idx) { 1213 // Get the operand at Idx and Lane. 1214 OperandData &OpData = getData(Idx, Lane); 1215 Value *Op = OpData.V; 1216 bool OpAPO = OpData.APO; 1217 1218 // Skip already selected operands. 1219 if (OpData.IsUsed) 1220 continue; 1221 1222 // Skip if we are trying to move the operand to a position with a 1223 // different opcode in the linearized tree form. This would break the 1224 // semantics. 1225 if (OpAPO != OpIdxAPO) 1226 continue; 1227 1228 // Look for an operand that matches the current mode. 1229 switch (RMode) { 1230 case ReorderingMode::Load: 1231 case ReorderingMode::Constant: 1232 case ReorderingMode::Opcode: { 1233 bool LeftToRight = Lane > LastLane; 1234 Value *OpLeft = (LeftToRight) ? OpLastLane : Op; 1235 Value *OpRight = (LeftToRight) ? Op : OpLastLane; 1236 unsigned Score = 1237 getLookAheadScore({OpLeft, LastLane}, {OpRight, Lane}); 1238 if (Score > BestOp.Score) { 1239 BestOp.Idx = Idx; 1240 BestOp.Score = Score; 1241 } 1242 break; 1243 } 1244 case ReorderingMode::Splat: 1245 if (Op == OpLastLane) 1246 BestOp.Idx = Idx; 1247 break; 1248 case ReorderingMode::Failed: 1249 return None; 1250 } 1251 } 1252 1253 if (BestOp.Idx) { 1254 getData(BestOp.Idx.getValue(), Lane).IsUsed = true; 1255 return BestOp.Idx; 1256 } 1257 // If we could not find a good match return None. 1258 return None; 1259 } 1260 1261 /// Helper for reorderOperandVecs. \Returns the lane that we should start 1262 /// reordering from. This is the one which has the least number of operands 1263 /// that can freely move about. 1264 unsigned getBestLaneToStartReordering() const { 1265 unsigned BestLane = 0; 1266 unsigned Min = UINT_MAX; 1267 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 1268 ++Lane) { 1269 unsigned NumFreeOps = getMaxNumOperandsThatCanBeReordered(Lane); 1270 if (NumFreeOps < Min) { 1271 Min = NumFreeOps; 1272 BestLane = Lane; 1273 } 1274 } 1275 return BestLane; 1276 } 1277 1278 /// \Returns the maximum number of operands that are allowed to be reordered 1279 /// for \p Lane. This is used as a heuristic for selecting the first lane to 1280 /// start operand reordering. 1281 unsigned getMaxNumOperandsThatCanBeReordered(unsigned Lane) const { 1282 unsigned CntTrue = 0; 1283 unsigned NumOperands = getNumOperands(); 1284 // Operands with the same APO can be reordered. We therefore need to count 1285 // how many of them we have for each APO, like this: Cnt[APO] = x. 1286 // Since we only have two APOs, namely true and false, we can avoid using 1287 // a map. Instead we can simply count the number of operands that 1288 // correspond to one of them (in this case the 'true' APO), and calculate 1289 // the other by subtracting it from the total number of operands. 1290 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) 1291 if (getData(OpIdx, Lane).APO) 1292 ++CntTrue; 1293 unsigned CntFalse = NumOperands - CntTrue; 1294 return std::max(CntTrue, CntFalse); 1295 } 1296 1297 /// Go through the instructions in VL and append their operands. 1298 void appendOperandsOfVL(ArrayRef<Value *> VL) { 1299 assert(!VL.empty() && "Bad VL"); 1300 assert((empty() || VL.size() == getNumLanes()) && 1301 "Expected same number of lanes"); 1302 assert(isa<Instruction>(VL[0]) && "Expected instruction"); 1303 unsigned NumOperands = cast<Instruction>(VL[0])->getNumOperands(); 1304 OpsVec.resize(NumOperands); 1305 unsigned NumLanes = VL.size(); 1306 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1307 OpsVec[OpIdx].resize(NumLanes); 1308 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { 1309 assert(isa<Instruction>(VL[Lane]) && "Expected instruction"); 1310 // Our tree has just 3 nodes: the root and two operands. 1311 // It is therefore trivial to get the APO. We only need to check the 1312 // opcode of VL[Lane] and whether the operand at OpIdx is the LHS or 1313 // RHS operand. The LHS operand of both add and sub is never attached 1314 // to an inversese operation in the linearized form, therefore its APO 1315 // is false. The RHS is true only if VL[Lane] is an inverse operation. 1316 1317 // Since operand reordering is performed on groups of commutative 1318 // operations or alternating sequences (e.g., +, -), we can safely 1319 // tell the inverse operations by checking commutativity. 1320 bool IsInverseOperation = !isCommutative(cast<Instruction>(VL[Lane])); 1321 bool APO = (OpIdx == 0) ? false : IsInverseOperation; 1322 OpsVec[OpIdx][Lane] = {cast<Instruction>(VL[Lane])->getOperand(OpIdx), 1323 APO, false}; 1324 } 1325 } 1326 } 1327 1328 /// \returns the number of operands. 1329 unsigned getNumOperands() const { return OpsVec.size(); } 1330 1331 /// \returns the number of lanes. 1332 unsigned getNumLanes() const { return OpsVec[0].size(); } 1333 1334 /// \returns the operand value at \p OpIdx and \p Lane. 1335 Value *getValue(unsigned OpIdx, unsigned Lane) const { 1336 return getData(OpIdx, Lane).V; 1337 } 1338 1339 /// \returns true if the data structure is empty. 1340 bool empty() const { return OpsVec.empty(); } 1341 1342 /// Clears the data. 1343 void clear() { OpsVec.clear(); } 1344 1345 /// \Returns true if there are enough operands identical to \p Op to fill 1346 /// the whole vector. 1347 /// Note: This modifies the 'IsUsed' flag, so a cleanUsed() must follow. 1348 bool shouldBroadcast(Value *Op, unsigned OpIdx, unsigned Lane) { 1349 bool OpAPO = getData(OpIdx, Lane).APO; 1350 for (unsigned Ln = 0, Lns = getNumLanes(); Ln != Lns; ++Ln) { 1351 if (Ln == Lane) 1352 continue; 1353 // This is set to true if we found a candidate for broadcast at Lane. 1354 bool FoundCandidate = false; 1355 for (unsigned OpI = 0, OpE = getNumOperands(); OpI != OpE; ++OpI) { 1356 OperandData &Data = getData(OpI, Ln); 1357 if (Data.APO != OpAPO || Data.IsUsed) 1358 continue; 1359 if (Data.V == Op) { 1360 FoundCandidate = true; 1361 Data.IsUsed = true; 1362 break; 1363 } 1364 } 1365 if (!FoundCandidate) 1366 return false; 1367 } 1368 return true; 1369 } 1370 1371 public: 1372 /// Initialize with all the operands of the instruction vector \p RootVL. 1373 VLOperands(ArrayRef<Value *> RootVL, const DataLayout &DL, 1374 ScalarEvolution &SE, const BoUpSLP &R) 1375 : DL(DL), SE(SE), R(R) { 1376 // Append all the operands of RootVL. 1377 appendOperandsOfVL(RootVL); 1378 } 1379 1380 /// \Returns a value vector with the operands across all lanes for the 1381 /// opearnd at \p OpIdx. 1382 ValueList getVL(unsigned OpIdx) const { 1383 ValueList OpVL(OpsVec[OpIdx].size()); 1384 assert(OpsVec[OpIdx].size() == getNumLanes() && 1385 "Expected same num of lanes across all operands"); 1386 for (unsigned Lane = 0, Lanes = getNumLanes(); Lane != Lanes; ++Lane) 1387 OpVL[Lane] = OpsVec[OpIdx][Lane].V; 1388 return OpVL; 1389 } 1390 1391 // Performs operand reordering for 2 or more operands. 1392 // The original operands are in OrigOps[OpIdx][Lane]. 1393 // The reordered operands are returned in 'SortedOps[OpIdx][Lane]'. 1394 void reorder() { 1395 unsigned NumOperands = getNumOperands(); 1396 unsigned NumLanes = getNumLanes(); 1397 // Each operand has its own mode. We are using this mode to help us select 1398 // the instructions for each lane, so that they match best with the ones 1399 // we have selected so far. 1400 SmallVector<ReorderingMode, 2> ReorderingModes(NumOperands); 1401 1402 // This is a greedy single-pass algorithm. We are going over each lane 1403 // once and deciding on the best order right away with no back-tracking. 1404 // However, in order to increase its effectiveness, we start with the lane 1405 // that has operands that can move the least. For example, given the 1406 // following lanes: 1407 // Lane 0 : A[0] = B[0] + C[0] // Visited 3rd 1408 // Lane 1 : A[1] = C[1] - B[1] // Visited 1st 1409 // Lane 2 : A[2] = B[2] + C[2] // Visited 2nd 1410 // Lane 3 : A[3] = C[3] - B[3] // Visited 4th 1411 // we will start at Lane 1, since the operands of the subtraction cannot 1412 // be reordered. Then we will visit the rest of the lanes in a circular 1413 // fashion. That is, Lanes 2, then Lane 0, and finally Lane 3. 1414 1415 // Find the first lane that we will start our search from. 1416 unsigned FirstLane = getBestLaneToStartReordering(); 1417 1418 // Initialize the modes. 1419 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1420 Value *OpLane0 = getValue(OpIdx, FirstLane); 1421 // Keep track if we have instructions with all the same opcode on one 1422 // side. 1423 if (isa<LoadInst>(OpLane0)) 1424 ReorderingModes[OpIdx] = ReorderingMode::Load; 1425 else if (isa<Instruction>(OpLane0)) { 1426 // Check if OpLane0 should be broadcast. 1427 if (shouldBroadcast(OpLane0, OpIdx, FirstLane)) 1428 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1429 else 1430 ReorderingModes[OpIdx] = ReorderingMode::Opcode; 1431 } 1432 else if (isa<Constant>(OpLane0)) 1433 ReorderingModes[OpIdx] = ReorderingMode::Constant; 1434 else if (isa<Argument>(OpLane0)) 1435 // Our best hope is a Splat. It may save some cost in some cases. 1436 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1437 else 1438 // NOTE: This should be unreachable. 1439 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1440 } 1441 1442 // If the initial strategy fails for any of the operand indexes, then we 1443 // perform reordering again in a second pass. This helps avoid assigning 1444 // high priority to the failed strategy, and should improve reordering for 1445 // the non-failed operand indexes. 1446 for (int Pass = 0; Pass != 2; ++Pass) { 1447 // Skip the second pass if the first pass did not fail. 1448 bool StrategyFailed = false; 1449 // Mark all operand data as free to use. 1450 clearUsed(); 1451 // We keep the original operand order for the FirstLane, so reorder the 1452 // rest of the lanes. We are visiting the nodes in a circular fashion, 1453 // using FirstLane as the center point and increasing the radius 1454 // distance. 1455 for (unsigned Distance = 1; Distance != NumLanes; ++Distance) { 1456 // Visit the lane on the right and then the lane on the left. 1457 for (int Direction : {+1, -1}) { 1458 int Lane = FirstLane + Direction * Distance; 1459 if (Lane < 0 || Lane >= (int)NumLanes) 1460 continue; 1461 int LastLane = Lane - Direction; 1462 assert(LastLane >= 0 && LastLane < (int)NumLanes && 1463 "Out of bounds"); 1464 // Look for a good match for each operand. 1465 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1466 // Search for the operand that matches SortedOps[OpIdx][Lane-1]. 1467 Optional<unsigned> BestIdx = 1468 getBestOperand(OpIdx, Lane, LastLane, ReorderingModes); 1469 // By not selecting a value, we allow the operands that follow to 1470 // select a better matching value. We will get a non-null value in 1471 // the next run of getBestOperand(). 1472 if (BestIdx) { 1473 // Swap the current operand with the one returned by 1474 // getBestOperand(). 1475 swap(OpIdx, BestIdx.getValue(), Lane); 1476 } else { 1477 // We failed to find a best operand, set mode to 'Failed'. 1478 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1479 // Enable the second pass. 1480 StrategyFailed = true; 1481 } 1482 } 1483 } 1484 } 1485 // Skip second pass if the strategy did not fail. 1486 if (!StrategyFailed) 1487 break; 1488 } 1489 } 1490 1491 #if !defined(NDEBUG) || defined(LLVM_ENABLE_DUMP) 1492 LLVM_DUMP_METHOD static StringRef getModeStr(ReorderingMode RMode) { 1493 switch (RMode) { 1494 case ReorderingMode::Load: 1495 return "Load"; 1496 case ReorderingMode::Opcode: 1497 return "Opcode"; 1498 case ReorderingMode::Constant: 1499 return "Constant"; 1500 case ReorderingMode::Splat: 1501 return "Splat"; 1502 case ReorderingMode::Failed: 1503 return "Failed"; 1504 } 1505 llvm_unreachable("Unimplemented Reordering Type"); 1506 } 1507 1508 LLVM_DUMP_METHOD static raw_ostream &printMode(ReorderingMode RMode, 1509 raw_ostream &OS) { 1510 return OS << getModeStr(RMode); 1511 } 1512 1513 /// Debug print. 1514 LLVM_DUMP_METHOD static void dumpMode(ReorderingMode RMode) { 1515 printMode(RMode, dbgs()); 1516 } 1517 1518 friend raw_ostream &operator<<(raw_ostream &OS, ReorderingMode RMode) { 1519 return printMode(RMode, OS); 1520 } 1521 1522 LLVM_DUMP_METHOD raw_ostream &print(raw_ostream &OS) const { 1523 const unsigned Indent = 2; 1524 unsigned Cnt = 0; 1525 for (const OperandDataVec &OpDataVec : OpsVec) { 1526 OS << "Operand " << Cnt++ << "\n"; 1527 for (const OperandData &OpData : OpDataVec) { 1528 OS.indent(Indent) << "{"; 1529 if (Value *V = OpData.V) 1530 OS << *V; 1531 else 1532 OS << "null"; 1533 OS << ", APO:" << OpData.APO << "}\n"; 1534 } 1535 OS << "\n"; 1536 } 1537 return OS; 1538 } 1539 1540 /// Debug print. 1541 LLVM_DUMP_METHOD void dump() const { print(dbgs()); } 1542 #endif 1543 }; 1544 1545 /// Checks if the instruction is marked for deletion. 1546 bool isDeleted(Instruction *I) const { return DeletedInstructions.count(I); } 1547 1548 /// Marks values operands for later deletion by replacing them with Undefs. 1549 void eraseInstructions(ArrayRef<Value *> AV); 1550 1551 ~BoUpSLP(); 1552 1553 private: 1554 /// Checks if all users of \p I are the part of the vectorization tree. 1555 bool areAllUsersVectorized(Instruction *I, 1556 ArrayRef<Value *> VectorizedVals) const; 1557 1558 /// \returns the cost of the vectorizable entry. 1559 InstructionCost getEntryCost(const TreeEntry *E, 1560 ArrayRef<Value *> VectorizedVals); 1561 1562 /// This is the recursive part of buildTree. 1563 void buildTree_rec(ArrayRef<Value *> Roots, unsigned Depth, 1564 const EdgeInfo &EI); 1565 1566 /// \returns true if the ExtractElement/ExtractValue instructions in \p VL can 1567 /// be vectorized to use the original vector (or aggregate "bitcast" to a 1568 /// vector) and sets \p CurrentOrder to the identity permutation; otherwise 1569 /// returns false, setting \p CurrentOrder to either an empty vector or a 1570 /// non-identity permutation that allows to reuse extract instructions. 1571 bool canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 1572 SmallVectorImpl<unsigned> &CurrentOrder) const; 1573 1574 /// Vectorize a single entry in the tree. 1575 Value *vectorizeTree(TreeEntry *E); 1576 1577 /// Vectorize a single entry in the tree, starting in \p VL. 1578 Value *vectorizeTree(ArrayRef<Value *> VL); 1579 1580 /// \returns the scalarization cost for this type. Scalarization in this 1581 /// context means the creation of vectors from a group of scalars. 1582 InstructionCost 1583 getGatherCost(FixedVectorType *Ty, 1584 const DenseSet<unsigned> &ShuffledIndices) const; 1585 1586 /// Checks if the gathered \p VL can be represented as shuffle(s) of previous 1587 /// tree entries. 1588 /// \returns ShuffleKind, if gathered values can be represented as shuffles of 1589 /// previous tree entries. \p Mask is filled with the shuffle mask. 1590 Optional<TargetTransformInfo::ShuffleKind> 1591 isGatherShuffledEntry(const TreeEntry *TE, SmallVectorImpl<int> &Mask, 1592 SmallVectorImpl<const TreeEntry *> &Entries); 1593 1594 /// \returns the scalarization cost for this list of values. Assuming that 1595 /// this subtree gets vectorized, we may need to extract the values from the 1596 /// roots. This method calculates the cost of extracting the values. 1597 InstructionCost getGatherCost(ArrayRef<Value *> VL) const; 1598 1599 /// Set the Builder insert point to one after the last instruction in 1600 /// the bundle 1601 void setInsertPointAfterBundle(const TreeEntry *E); 1602 1603 /// \returns a vector from a collection of scalars in \p VL. 1604 Value *gather(ArrayRef<Value *> VL); 1605 1606 /// \returns whether the VectorizableTree is fully vectorizable and will 1607 /// be beneficial even the tree height is tiny. 1608 bool isFullyVectorizableTinyTree() const; 1609 1610 /// Reorder commutative or alt operands to get better probability of 1611 /// generating vectorized code. 1612 static void reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 1613 SmallVectorImpl<Value *> &Left, 1614 SmallVectorImpl<Value *> &Right, 1615 const DataLayout &DL, 1616 ScalarEvolution &SE, 1617 const BoUpSLP &R); 1618 struct TreeEntry { 1619 using VecTreeTy = SmallVector<std::unique_ptr<TreeEntry>, 8>; 1620 TreeEntry(VecTreeTy &Container) : Container(Container) {} 1621 1622 /// \returns true if the scalars in VL are equal to this entry. 1623 bool isSame(ArrayRef<Value *> VL) const { 1624 if (VL.size() == Scalars.size()) 1625 return std::equal(VL.begin(), VL.end(), Scalars.begin()); 1626 return VL.size() == ReuseShuffleIndices.size() && 1627 std::equal( 1628 VL.begin(), VL.end(), ReuseShuffleIndices.begin(), 1629 [this](Value *V, int Idx) { return V == Scalars[Idx]; }); 1630 } 1631 1632 /// A vector of scalars. 1633 ValueList Scalars; 1634 1635 /// The Scalars are vectorized into this value. It is initialized to Null. 1636 Value *VectorizedValue = nullptr; 1637 1638 /// Do we need to gather this sequence or vectorize it 1639 /// (either with vector instruction or with scatter/gather 1640 /// intrinsics for store/load)? 1641 enum EntryState { Vectorize, ScatterVectorize, NeedToGather }; 1642 EntryState State; 1643 1644 /// Does this sequence require some shuffling? 1645 SmallVector<int, 4> ReuseShuffleIndices; 1646 1647 /// Does this entry require reordering? 1648 SmallVector<unsigned, 4> ReorderIndices; 1649 1650 /// Points back to the VectorizableTree. 1651 /// 1652 /// Only used for Graphviz right now. Unfortunately GraphTrait::NodeRef has 1653 /// to be a pointer and needs to be able to initialize the child iterator. 1654 /// Thus we need a reference back to the container to translate the indices 1655 /// to entries. 1656 VecTreeTy &Container; 1657 1658 /// The TreeEntry index containing the user of this entry. We can actually 1659 /// have multiple users so the data structure is not truly a tree. 1660 SmallVector<EdgeInfo, 1> UserTreeIndices; 1661 1662 /// The index of this treeEntry in VectorizableTree. 1663 int Idx = -1; 1664 1665 private: 1666 /// The operands of each instruction in each lane Operands[op_index][lane]. 1667 /// Note: This helps avoid the replication of the code that performs the 1668 /// reordering of operands during buildTree_rec() and vectorizeTree(). 1669 SmallVector<ValueList, 2> Operands; 1670 1671 /// The main/alternate instruction. 1672 Instruction *MainOp = nullptr; 1673 Instruction *AltOp = nullptr; 1674 1675 public: 1676 /// Set this bundle's \p OpIdx'th operand to \p OpVL. 1677 void setOperand(unsigned OpIdx, ArrayRef<Value *> OpVL) { 1678 if (Operands.size() < OpIdx + 1) 1679 Operands.resize(OpIdx + 1); 1680 assert(Operands[OpIdx].empty() && "Already resized?"); 1681 Operands[OpIdx].resize(Scalars.size()); 1682 for (unsigned Lane = 0, E = Scalars.size(); Lane != E; ++Lane) 1683 Operands[OpIdx][Lane] = OpVL[Lane]; 1684 } 1685 1686 /// Set the operands of this bundle in their original order. 1687 void setOperandsInOrder() { 1688 assert(Operands.empty() && "Already initialized?"); 1689 auto *I0 = cast<Instruction>(Scalars[0]); 1690 Operands.resize(I0->getNumOperands()); 1691 unsigned NumLanes = Scalars.size(); 1692 for (unsigned OpIdx = 0, NumOperands = I0->getNumOperands(); 1693 OpIdx != NumOperands; ++OpIdx) { 1694 Operands[OpIdx].resize(NumLanes); 1695 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { 1696 auto *I = cast<Instruction>(Scalars[Lane]); 1697 assert(I->getNumOperands() == NumOperands && 1698 "Expected same number of operands"); 1699 Operands[OpIdx][Lane] = I->getOperand(OpIdx); 1700 } 1701 } 1702 } 1703 1704 /// \returns the \p OpIdx operand of this TreeEntry. 1705 ValueList &getOperand(unsigned OpIdx) { 1706 assert(OpIdx < Operands.size() && "Off bounds"); 1707 return Operands[OpIdx]; 1708 } 1709 1710 /// \returns the number of operands. 1711 unsigned getNumOperands() const { return Operands.size(); } 1712 1713 /// \return the single \p OpIdx operand. 1714 Value *getSingleOperand(unsigned OpIdx) const { 1715 assert(OpIdx < Operands.size() && "Off bounds"); 1716 assert(!Operands[OpIdx].empty() && "No operand available"); 1717 return Operands[OpIdx][0]; 1718 } 1719 1720 /// Some of the instructions in the list have alternate opcodes. 1721 bool isAltShuffle() const { 1722 return getOpcode() != getAltOpcode(); 1723 } 1724 1725 bool isOpcodeOrAlt(Instruction *I) const { 1726 unsigned CheckedOpcode = I->getOpcode(); 1727 return (getOpcode() == CheckedOpcode || 1728 getAltOpcode() == CheckedOpcode); 1729 } 1730 1731 /// Chooses the correct key for scheduling data. If \p Op has the same (or 1732 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is 1733 /// \p OpValue. 1734 Value *isOneOf(Value *Op) const { 1735 auto *I = dyn_cast<Instruction>(Op); 1736 if (I && isOpcodeOrAlt(I)) 1737 return Op; 1738 return MainOp; 1739 } 1740 1741 void setOperations(const InstructionsState &S) { 1742 MainOp = S.MainOp; 1743 AltOp = S.AltOp; 1744 } 1745 1746 Instruction *getMainOp() const { 1747 return MainOp; 1748 } 1749 1750 Instruction *getAltOp() const { 1751 return AltOp; 1752 } 1753 1754 /// The main/alternate opcodes for the list of instructions. 1755 unsigned getOpcode() const { 1756 return MainOp ? MainOp->getOpcode() : 0; 1757 } 1758 1759 unsigned getAltOpcode() const { 1760 return AltOp ? AltOp->getOpcode() : 0; 1761 } 1762 1763 /// Update operations state of this entry if reorder occurred. 1764 bool updateStateIfReorder() { 1765 if (ReorderIndices.empty()) 1766 return false; 1767 InstructionsState S = getSameOpcode(Scalars, ReorderIndices.front()); 1768 setOperations(S); 1769 return true; 1770 } 1771 /// When ReuseShuffleIndices is empty it just returns position of \p V 1772 /// within vector of Scalars. Otherwise, try to remap on its reuse index. 1773 int findLaneForValue(Value *V) const { 1774 unsigned FoundLane = std::distance(Scalars.begin(), find(Scalars, V)); 1775 assert(FoundLane < Scalars.size() && "Couldn't find extract lane"); 1776 if (!ReuseShuffleIndices.empty()) { 1777 FoundLane = std::distance(ReuseShuffleIndices.begin(), 1778 find(ReuseShuffleIndices, FoundLane)); 1779 } 1780 return FoundLane; 1781 } 1782 1783 #ifndef NDEBUG 1784 /// Debug printer. 1785 LLVM_DUMP_METHOD void dump() const { 1786 dbgs() << Idx << ".\n"; 1787 for (unsigned OpI = 0, OpE = Operands.size(); OpI != OpE; ++OpI) { 1788 dbgs() << "Operand " << OpI << ":\n"; 1789 for (const Value *V : Operands[OpI]) 1790 dbgs().indent(2) << *V << "\n"; 1791 } 1792 dbgs() << "Scalars: \n"; 1793 for (Value *V : Scalars) 1794 dbgs().indent(2) << *V << "\n"; 1795 dbgs() << "State: "; 1796 switch (State) { 1797 case Vectorize: 1798 dbgs() << "Vectorize\n"; 1799 break; 1800 case ScatterVectorize: 1801 dbgs() << "ScatterVectorize\n"; 1802 break; 1803 case NeedToGather: 1804 dbgs() << "NeedToGather\n"; 1805 break; 1806 } 1807 dbgs() << "MainOp: "; 1808 if (MainOp) 1809 dbgs() << *MainOp << "\n"; 1810 else 1811 dbgs() << "NULL\n"; 1812 dbgs() << "AltOp: "; 1813 if (AltOp) 1814 dbgs() << *AltOp << "\n"; 1815 else 1816 dbgs() << "NULL\n"; 1817 dbgs() << "VectorizedValue: "; 1818 if (VectorizedValue) 1819 dbgs() << *VectorizedValue << "\n"; 1820 else 1821 dbgs() << "NULL\n"; 1822 dbgs() << "ReuseShuffleIndices: "; 1823 if (ReuseShuffleIndices.empty()) 1824 dbgs() << "Empty"; 1825 else 1826 for (unsigned ReuseIdx : ReuseShuffleIndices) 1827 dbgs() << ReuseIdx << ", "; 1828 dbgs() << "\n"; 1829 dbgs() << "ReorderIndices: "; 1830 for (unsigned ReorderIdx : ReorderIndices) 1831 dbgs() << ReorderIdx << ", "; 1832 dbgs() << "\n"; 1833 dbgs() << "UserTreeIndices: "; 1834 for (const auto &EInfo : UserTreeIndices) 1835 dbgs() << EInfo << ", "; 1836 dbgs() << "\n"; 1837 } 1838 #endif 1839 }; 1840 1841 #ifndef NDEBUG 1842 void dumpTreeCosts(const TreeEntry *E, InstructionCost ReuseShuffleCost, 1843 InstructionCost VecCost, 1844 InstructionCost ScalarCost) const { 1845 dbgs() << "SLP: Calculated costs for Tree:\n"; E->dump(); 1846 dbgs() << "SLP: Costs:\n"; 1847 dbgs() << "SLP: ReuseShuffleCost = " << ReuseShuffleCost << "\n"; 1848 dbgs() << "SLP: VectorCost = " << VecCost << "\n"; 1849 dbgs() << "SLP: ScalarCost = " << ScalarCost << "\n"; 1850 dbgs() << "SLP: ReuseShuffleCost + VecCost - ScalarCost = " << 1851 ReuseShuffleCost + VecCost - ScalarCost << "\n"; 1852 } 1853 #endif 1854 1855 /// Create a new VectorizableTree entry. 1856 TreeEntry *newTreeEntry(ArrayRef<Value *> VL, Optional<ScheduleData *> Bundle, 1857 const InstructionsState &S, 1858 const EdgeInfo &UserTreeIdx, 1859 ArrayRef<unsigned> ReuseShuffleIndices = None, 1860 ArrayRef<unsigned> ReorderIndices = None) { 1861 TreeEntry::EntryState EntryState = 1862 Bundle ? TreeEntry::Vectorize : TreeEntry::NeedToGather; 1863 return newTreeEntry(VL, EntryState, Bundle, S, UserTreeIdx, 1864 ReuseShuffleIndices, ReorderIndices); 1865 } 1866 1867 TreeEntry *newTreeEntry(ArrayRef<Value *> VL, 1868 TreeEntry::EntryState EntryState, 1869 Optional<ScheduleData *> Bundle, 1870 const InstructionsState &S, 1871 const EdgeInfo &UserTreeIdx, 1872 ArrayRef<unsigned> ReuseShuffleIndices = None, 1873 ArrayRef<unsigned> ReorderIndices = None) { 1874 assert(((!Bundle && EntryState == TreeEntry::NeedToGather) || 1875 (Bundle && EntryState != TreeEntry::NeedToGather)) && 1876 "Need to vectorize gather entry?"); 1877 VectorizableTree.push_back(std::make_unique<TreeEntry>(VectorizableTree)); 1878 TreeEntry *Last = VectorizableTree.back().get(); 1879 Last->Idx = VectorizableTree.size() - 1; 1880 Last->Scalars.insert(Last->Scalars.begin(), VL.begin(), VL.end()); 1881 Last->State = EntryState; 1882 Last->ReuseShuffleIndices.append(ReuseShuffleIndices.begin(), 1883 ReuseShuffleIndices.end()); 1884 Last->ReorderIndices.append(ReorderIndices.begin(), ReorderIndices.end()); 1885 Last->setOperations(S); 1886 if (Last->State != TreeEntry::NeedToGather) { 1887 for (Value *V : VL) { 1888 assert(!getTreeEntry(V) && "Scalar already in tree!"); 1889 ScalarToTreeEntry[V] = Last; 1890 } 1891 // Update the scheduler bundle to point to this TreeEntry. 1892 unsigned Lane = 0; 1893 for (ScheduleData *BundleMember = Bundle.getValue(); BundleMember; 1894 BundleMember = BundleMember->NextInBundle) { 1895 BundleMember->TE = Last; 1896 BundleMember->Lane = Lane; 1897 ++Lane; 1898 } 1899 assert((!Bundle.getValue() || Lane == VL.size()) && 1900 "Bundle and VL out of sync"); 1901 } else { 1902 MustGather.insert(VL.begin(), VL.end()); 1903 } 1904 1905 if (UserTreeIdx.UserTE) 1906 Last->UserTreeIndices.push_back(UserTreeIdx); 1907 1908 return Last; 1909 } 1910 1911 /// -- Vectorization State -- 1912 /// Holds all of the tree entries. 1913 TreeEntry::VecTreeTy VectorizableTree; 1914 1915 #ifndef NDEBUG 1916 /// Debug printer. 1917 LLVM_DUMP_METHOD void dumpVectorizableTree() const { 1918 for (unsigned Id = 0, IdE = VectorizableTree.size(); Id != IdE; ++Id) { 1919 VectorizableTree[Id]->dump(); 1920 dbgs() << "\n"; 1921 } 1922 } 1923 #endif 1924 1925 TreeEntry *getTreeEntry(Value *V) { return ScalarToTreeEntry.lookup(V); } 1926 1927 const TreeEntry *getTreeEntry(Value *V) const { 1928 return ScalarToTreeEntry.lookup(V); 1929 } 1930 1931 /// Maps a specific scalar to its tree entry. 1932 SmallDenseMap<Value*, TreeEntry *> ScalarToTreeEntry; 1933 1934 /// Maps a value to the proposed vectorizable size. 1935 SmallDenseMap<Value *, unsigned> InstrElementSize; 1936 1937 /// A list of scalars that we found that we need to keep as scalars. 1938 ValueSet MustGather; 1939 1940 /// This POD struct describes one external user in the vectorized tree. 1941 struct ExternalUser { 1942 ExternalUser(Value *S, llvm::User *U, int L) 1943 : Scalar(S), User(U), Lane(L) {} 1944 1945 // Which scalar in our function. 1946 Value *Scalar; 1947 1948 // Which user that uses the scalar. 1949 llvm::User *User; 1950 1951 // Which lane does the scalar belong to. 1952 int Lane; 1953 }; 1954 using UserList = SmallVector<ExternalUser, 16>; 1955 1956 /// Checks if two instructions may access the same memory. 1957 /// 1958 /// \p Loc1 is the location of \p Inst1. It is passed explicitly because it 1959 /// is invariant in the calling loop. 1960 bool isAliased(const MemoryLocation &Loc1, Instruction *Inst1, 1961 Instruction *Inst2) { 1962 // First check if the result is already in the cache. 1963 AliasCacheKey key = std::make_pair(Inst1, Inst2); 1964 Optional<bool> &result = AliasCache[key]; 1965 if (result.hasValue()) { 1966 return result.getValue(); 1967 } 1968 MemoryLocation Loc2 = getLocation(Inst2, AA); 1969 bool aliased = true; 1970 if (Loc1.Ptr && Loc2.Ptr && isSimple(Inst1) && isSimple(Inst2)) { 1971 // Do the alias check. 1972 aliased = !AA->isNoAlias(Loc1, Loc2); 1973 } 1974 // Store the result in the cache. 1975 result = aliased; 1976 return aliased; 1977 } 1978 1979 using AliasCacheKey = std::pair<Instruction *, Instruction *>; 1980 1981 /// Cache for alias results. 1982 /// TODO: consider moving this to the AliasAnalysis itself. 1983 DenseMap<AliasCacheKey, Optional<bool>> AliasCache; 1984 1985 /// Removes an instruction from its block and eventually deletes it. 1986 /// It's like Instruction::eraseFromParent() except that the actual deletion 1987 /// is delayed until BoUpSLP is destructed. 1988 /// This is required to ensure that there are no incorrect collisions in the 1989 /// AliasCache, which can happen if a new instruction is allocated at the 1990 /// same address as a previously deleted instruction. 1991 void eraseInstruction(Instruction *I, bool ReplaceOpsWithUndef = false) { 1992 auto It = DeletedInstructions.try_emplace(I, ReplaceOpsWithUndef).first; 1993 It->getSecond() = It->getSecond() && ReplaceOpsWithUndef; 1994 } 1995 1996 /// Temporary store for deleted instructions. Instructions will be deleted 1997 /// eventually when the BoUpSLP is destructed. 1998 DenseMap<Instruction *, bool> DeletedInstructions; 1999 2000 /// A list of values that need to extracted out of the tree. 2001 /// This list holds pairs of (Internal Scalar : External User). External User 2002 /// can be nullptr, it means that this Internal Scalar will be used later, 2003 /// after vectorization. 2004 UserList ExternalUses; 2005 2006 /// Values used only by @llvm.assume calls. 2007 SmallPtrSet<const Value *, 32> EphValues; 2008 2009 /// Holds all of the instructions that we gathered. 2010 SetVector<Instruction *> GatherSeq; 2011 2012 /// A list of blocks that we are going to CSE. 2013 SetVector<BasicBlock *> CSEBlocks; 2014 2015 /// Contains all scheduling relevant data for an instruction. 2016 /// A ScheduleData either represents a single instruction or a member of an 2017 /// instruction bundle (= a group of instructions which is combined into a 2018 /// vector instruction). 2019 struct ScheduleData { 2020 // The initial value for the dependency counters. It means that the 2021 // dependencies are not calculated yet. 2022 enum { InvalidDeps = -1 }; 2023 2024 ScheduleData() = default; 2025 2026 void init(int BlockSchedulingRegionID, Value *OpVal) { 2027 FirstInBundle = this; 2028 NextInBundle = nullptr; 2029 NextLoadStore = nullptr; 2030 IsScheduled = false; 2031 SchedulingRegionID = BlockSchedulingRegionID; 2032 UnscheduledDepsInBundle = UnscheduledDeps; 2033 clearDependencies(); 2034 OpValue = OpVal; 2035 TE = nullptr; 2036 Lane = -1; 2037 } 2038 2039 /// Returns true if the dependency information has been calculated. 2040 bool hasValidDependencies() const { return Dependencies != InvalidDeps; } 2041 2042 /// Returns true for single instructions and for bundle representatives 2043 /// (= the head of a bundle). 2044 bool isSchedulingEntity() const { return FirstInBundle == this; } 2045 2046 /// Returns true if it represents an instruction bundle and not only a 2047 /// single instruction. 2048 bool isPartOfBundle() const { 2049 return NextInBundle != nullptr || FirstInBundle != this; 2050 } 2051 2052 /// Returns true if it is ready for scheduling, i.e. it has no more 2053 /// unscheduled depending instructions/bundles. 2054 bool isReady() const { 2055 assert(isSchedulingEntity() && 2056 "can't consider non-scheduling entity for ready list"); 2057 return UnscheduledDepsInBundle == 0 && !IsScheduled; 2058 } 2059 2060 /// Modifies the number of unscheduled dependencies, also updating it for 2061 /// the whole bundle. 2062 int incrementUnscheduledDeps(int Incr) { 2063 UnscheduledDeps += Incr; 2064 return FirstInBundle->UnscheduledDepsInBundle += Incr; 2065 } 2066 2067 /// Sets the number of unscheduled dependencies to the number of 2068 /// dependencies. 2069 void resetUnscheduledDeps() { 2070 incrementUnscheduledDeps(Dependencies - UnscheduledDeps); 2071 } 2072 2073 /// Clears all dependency information. 2074 void clearDependencies() { 2075 Dependencies = InvalidDeps; 2076 resetUnscheduledDeps(); 2077 MemoryDependencies.clear(); 2078 } 2079 2080 void dump(raw_ostream &os) const { 2081 if (!isSchedulingEntity()) { 2082 os << "/ " << *Inst; 2083 } else if (NextInBundle) { 2084 os << '[' << *Inst; 2085 ScheduleData *SD = NextInBundle; 2086 while (SD) { 2087 os << ';' << *SD->Inst; 2088 SD = SD->NextInBundle; 2089 } 2090 os << ']'; 2091 } else { 2092 os << *Inst; 2093 } 2094 } 2095 2096 Instruction *Inst = nullptr; 2097 2098 /// Points to the head in an instruction bundle (and always to this for 2099 /// single instructions). 2100 ScheduleData *FirstInBundle = nullptr; 2101 2102 /// Single linked list of all instructions in a bundle. Null if it is a 2103 /// single instruction. 2104 ScheduleData *NextInBundle = nullptr; 2105 2106 /// Single linked list of all memory instructions (e.g. load, store, call) 2107 /// in the block - until the end of the scheduling region. 2108 ScheduleData *NextLoadStore = nullptr; 2109 2110 /// The dependent memory instructions. 2111 /// This list is derived on demand in calculateDependencies(). 2112 SmallVector<ScheduleData *, 4> MemoryDependencies; 2113 2114 /// This ScheduleData is in the current scheduling region if this matches 2115 /// the current SchedulingRegionID of BlockScheduling. 2116 int SchedulingRegionID = 0; 2117 2118 /// Used for getting a "good" final ordering of instructions. 2119 int SchedulingPriority = 0; 2120 2121 /// The number of dependencies. Constitutes of the number of users of the 2122 /// instruction plus the number of dependent memory instructions (if any). 2123 /// This value is calculated on demand. 2124 /// If InvalidDeps, the number of dependencies is not calculated yet. 2125 int Dependencies = InvalidDeps; 2126 2127 /// The number of dependencies minus the number of dependencies of scheduled 2128 /// instructions. As soon as this is zero, the instruction/bundle gets ready 2129 /// for scheduling. 2130 /// Note that this is negative as long as Dependencies is not calculated. 2131 int UnscheduledDeps = InvalidDeps; 2132 2133 /// The sum of UnscheduledDeps in a bundle. Equals to UnscheduledDeps for 2134 /// single instructions. 2135 int UnscheduledDepsInBundle = InvalidDeps; 2136 2137 /// True if this instruction is scheduled (or considered as scheduled in the 2138 /// dry-run). 2139 bool IsScheduled = false; 2140 2141 /// Opcode of the current instruction in the schedule data. 2142 Value *OpValue = nullptr; 2143 2144 /// The TreeEntry that this instruction corresponds to. 2145 TreeEntry *TE = nullptr; 2146 2147 /// The lane of this node in the TreeEntry. 2148 int Lane = -1; 2149 }; 2150 2151 #ifndef NDEBUG 2152 friend inline raw_ostream &operator<<(raw_ostream &os, 2153 const BoUpSLP::ScheduleData &SD) { 2154 SD.dump(os); 2155 return os; 2156 } 2157 #endif 2158 2159 friend struct GraphTraits<BoUpSLP *>; 2160 friend struct DOTGraphTraits<BoUpSLP *>; 2161 2162 /// Contains all scheduling data for a basic block. 2163 struct BlockScheduling { 2164 BlockScheduling(BasicBlock *BB) 2165 : BB(BB), ChunkSize(BB->size()), ChunkPos(ChunkSize) {} 2166 2167 void clear() { 2168 ReadyInsts.clear(); 2169 ScheduleStart = nullptr; 2170 ScheduleEnd = nullptr; 2171 FirstLoadStoreInRegion = nullptr; 2172 LastLoadStoreInRegion = nullptr; 2173 2174 // Reduce the maximum schedule region size by the size of the 2175 // previous scheduling run. 2176 ScheduleRegionSizeLimit -= ScheduleRegionSize; 2177 if (ScheduleRegionSizeLimit < MinScheduleRegionSize) 2178 ScheduleRegionSizeLimit = MinScheduleRegionSize; 2179 ScheduleRegionSize = 0; 2180 2181 // Make a new scheduling region, i.e. all existing ScheduleData is not 2182 // in the new region yet. 2183 ++SchedulingRegionID; 2184 } 2185 2186 ScheduleData *getScheduleData(Value *V) { 2187 ScheduleData *SD = ScheduleDataMap[V]; 2188 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 2189 return SD; 2190 return nullptr; 2191 } 2192 2193 ScheduleData *getScheduleData(Value *V, Value *Key) { 2194 if (V == Key) 2195 return getScheduleData(V); 2196 auto I = ExtraScheduleDataMap.find(V); 2197 if (I != ExtraScheduleDataMap.end()) { 2198 ScheduleData *SD = I->second[Key]; 2199 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 2200 return SD; 2201 } 2202 return nullptr; 2203 } 2204 2205 bool isInSchedulingRegion(ScheduleData *SD) const { 2206 return SD->SchedulingRegionID == SchedulingRegionID; 2207 } 2208 2209 /// Marks an instruction as scheduled and puts all dependent ready 2210 /// instructions into the ready-list. 2211 template <typename ReadyListType> 2212 void schedule(ScheduleData *SD, ReadyListType &ReadyList) { 2213 SD->IsScheduled = true; 2214 LLVM_DEBUG(dbgs() << "SLP: schedule " << *SD << "\n"); 2215 2216 ScheduleData *BundleMember = SD; 2217 while (BundleMember) { 2218 if (BundleMember->Inst != BundleMember->OpValue) { 2219 BundleMember = BundleMember->NextInBundle; 2220 continue; 2221 } 2222 // Handle the def-use chain dependencies. 2223 2224 // Decrement the unscheduled counter and insert to ready list if ready. 2225 auto &&DecrUnsched = [this, &ReadyList](Instruction *I) { 2226 doForAllOpcodes(I, [&ReadyList](ScheduleData *OpDef) { 2227 if (OpDef && OpDef->hasValidDependencies() && 2228 OpDef->incrementUnscheduledDeps(-1) == 0) { 2229 // There are no more unscheduled dependencies after 2230 // decrementing, so we can put the dependent instruction 2231 // into the ready list. 2232 ScheduleData *DepBundle = OpDef->FirstInBundle; 2233 assert(!DepBundle->IsScheduled && 2234 "already scheduled bundle gets ready"); 2235 ReadyList.insert(DepBundle); 2236 LLVM_DEBUG(dbgs() 2237 << "SLP: gets ready (def): " << *DepBundle << "\n"); 2238 } 2239 }); 2240 }; 2241 2242 // If BundleMember is a vector bundle, its operands may have been 2243 // reordered duiring buildTree(). We therefore need to get its operands 2244 // through the TreeEntry. 2245 if (TreeEntry *TE = BundleMember->TE) { 2246 int Lane = BundleMember->Lane; 2247 assert(Lane >= 0 && "Lane not set"); 2248 2249 // Since vectorization tree is being built recursively this assertion 2250 // ensures that the tree entry has all operands set before reaching 2251 // this code. Couple of exceptions known at the moment are extracts 2252 // where their second (immediate) operand is not added. Since 2253 // immediates do not affect scheduler behavior this is considered 2254 // okay. 2255 auto *In = TE->getMainOp(); 2256 assert(In && 2257 (isa<ExtractValueInst>(In) || isa<ExtractElementInst>(In) || 2258 In->getNumOperands() == TE->getNumOperands()) && 2259 "Missed TreeEntry operands?"); 2260 (void)In; // fake use to avoid build failure when assertions disabled 2261 2262 for (unsigned OpIdx = 0, NumOperands = TE->getNumOperands(); 2263 OpIdx != NumOperands; ++OpIdx) 2264 if (auto *I = dyn_cast<Instruction>(TE->getOperand(OpIdx)[Lane])) 2265 DecrUnsched(I); 2266 } else { 2267 // If BundleMember is a stand-alone instruction, no operand reordering 2268 // has taken place, so we directly access its operands. 2269 for (Use &U : BundleMember->Inst->operands()) 2270 if (auto *I = dyn_cast<Instruction>(U.get())) 2271 DecrUnsched(I); 2272 } 2273 // Handle the memory dependencies. 2274 for (ScheduleData *MemoryDepSD : BundleMember->MemoryDependencies) { 2275 if (MemoryDepSD->incrementUnscheduledDeps(-1) == 0) { 2276 // There are no more unscheduled dependencies after decrementing, 2277 // so we can put the dependent instruction into the ready list. 2278 ScheduleData *DepBundle = MemoryDepSD->FirstInBundle; 2279 assert(!DepBundle->IsScheduled && 2280 "already scheduled bundle gets ready"); 2281 ReadyList.insert(DepBundle); 2282 LLVM_DEBUG(dbgs() 2283 << "SLP: gets ready (mem): " << *DepBundle << "\n"); 2284 } 2285 } 2286 BundleMember = BundleMember->NextInBundle; 2287 } 2288 } 2289 2290 void doForAllOpcodes(Value *V, 2291 function_ref<void(ScheduleData *SD)> Action) { 2292 if (ScheduleData *SD = getScheduleData(V)) 2293 Action(SD); 2294 auto I = ExtraScheduleDataMap.find(V); 2295 if (I != ExtraScheduleDataMap.end()) 2296 for (auto &P : I->second) 2297 if (P.second->SchedulingRegionID == SchedulingRegionID) 2298 Action(P.second); 2299 } 2300 2301 /// Put all instructions into the ReadyList which are ready for scheduling. 2302 template <typename ReadyListType> 2303 void initialFillReadyList(ReadyListType &ReadyList) { 2304 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 2305 doForAllOpcodes(I, [&](ScheduleData *SD) { 2306 if (SD->isSchedulingEntity() && SD->isReady()) { 2307 ReadyList.insert(SD); 2308 LLVM_DEBUG(dbgs() 2309 << "SLP: initially in ready list: " << *I << "\n"); 2310 } 2311 }); 2312 } 2313 } 2314 2315 /// Checks if a bundle of instructions can be scheduled, i.e. has no 2316 /// cyclic dependencies. This is only a dry-run, no instructions are 2317 /// actually moved at this stage. 2318 /// \returns the scheduling bundle. The returned Optional value is non-None 2319 /// if \p VL is allowed to be scheduled. 2320 Optional<ScheduleData *> 2321 tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 2322 const InstructionsState &S); 2323 2324 /// Un-bundles a group of instructions. 2325 void cancelScheduling(ArrayRef<Value *> VL, Value *OpValue); 2326 2327 /// Allocates schedule data chunk. 2328 ScheduleData *allocateScheduleDataChunks(); 2329 2330 /// Extends the scheduling region so that V is inside the region. 2331 /// \returns true if the region size is within the limit. 2332 bool extendSchedulingRegion(Value *V, const InstructionsState &S); 2333 2334 /// Initialize the ScheduleData structures for new instructions in the 2335 /// scheduling region. 2336 void initScheduleData(Instruction *FromI, Instruction *ToI, 2337 ScheduleData *PrevLoadStore, 2338 ScheduleData *NextLoadStore); 2339 2340 /// Updates the dependency information of a bundle and of all instructions/ 2341 /// bundles which depend on the original bundle. 2342 void calculateDependencies(ScheduleData *SD, bool InsertInReadyList, 2343 BoUpSLP *SLP); 2344 2345 /// Sets all instruction in the scheduling region to un-scheduled. 2346 void resetSchedule(); 2347 2348 BasicBlock *BB; 2349 2350 /// Simple memory allocation for ScheduleData. 2351 std::vector<std::unique_ptr<ScheduleData[]>> ScheduleDataChunks; 2352 2353 /// The size of a ScheduleData array in ScheduleDataChunks. 2354 int ChunkSize; 2355 2356 /// The allocator position in the current chunk, which is the last entry 2357 /// of ScheduleDataChunks. 2358 int ChunkPos; 2359 2360 /// Attaches ScheduleData to Instruction. 2361 /// Note that the mapping survives during all vectorization iterations, i.e. 2362 /// ScheduleData structures are recycled. 2363 DenseMap<Value *, ScheduleData *> ScheduleDataMap; 2364 2365 /// Attaches ScheduleData to Instruction with the leading key. 2366 DenseMap<Value *, SmallDenseMap<Value *, ScheduleData *>> 2367 ExtraScheduleDataMap; 2368 2369 struct ReadyList : SmallVector<ScheduleData *, 8> { 2370 void insert(ScheduleData *SD) { push_back(SD); } 2371 }; 2372 2373 /// The ready-list for scheduling (only used for the dry-run). 2374 ReadyList ReadyInsts; 2375 2376 /// The first instruction of the scheduling region. 2377 Instruction *ScheduleStart = nullptr; 2378 2379 /// The first instruction _after_ the scheduling region. 2380 Instruction *ScheduleEnd = nullptr; 2381 2382 /// The first memory accessing instruction in the scheduling region 2383 /// (can be null). 2384 ScheduleData *FirstLoadStoreInRegion = nullptr; 2385 2386 /// The last memory accessing instruction in the scheduling region 2387 /// (can be null). 2388 ScheduleData *LastLoadStoreInRegion = nullptr; 2389 2390 /// The current size of the scheduling region. 2391 int ScheduleRegionSize = 0; 2392 2393 /// The maximum size allowed for the scheduling region. 2394 int ScheduleRegionSizeLimit = ScheduleRegionSizeBudget; 2395 2396 /// The ID of the scheduling region. For a new vectorization iteration this 2397 /// is incremented which "removes" all ScheduleData from the region. 2398 // Make sure that the initial SchedulingRegionID is greater than the 2399 // initial SchedulingRegionID in ScheduleData (which is 0). 2400 int SchedulingRegionID = 1; 2401 }; 2402 2403 /// Attaches the BlockScheduling structures to basic blocks. 2404 MapVector<BasicBlock *, std::unique_ptr<BlockScheduling>> BlocksSchedules; 2405 2406 /// Performs the "real" scheduling. Done before vectorization is actually 2407 /// performed in a basic block. 2408 void scheduleBlock(BlockScheduling *BS); 2409 2410 /// List of users to ignore during scheduling and that don't need extracting. 2411 ArrayRef<Value *> UserIgnoreList; 2412 2413 /// A DenseMapInfo implementation for holding DenseMaps and DenseSets of 2414 /// sorted SmallVectors of unsigned. 2415 struct OrdersTypeDenseMapInfo { 2416 static OrdersType getEmptyKey() { 2417 OrdersType V; 2418 V.push_back(~1U); 2419 return V; 2420 } 2421 2422 static OrdersType getTombstoneKey() { 2423 OrdersType V; 2424 V.push_back(~2U); 2425 return V; 2426 } 2427 2428 static unsigned getHashValue(const OrdersType &V) { 2429 return static_cast<unsigned>(hash_combine_range(V.begin(), V.end())); 2430 } 2431 2432 static bool isEqual(const OrdersType &LHS, const OrdersType &RHS) { 2433 return LHS == RHS; 2434 } 2435 }; 2436 2437 /// Contains orders of operations along with the number of bundles that have 2438 /// operations in this order. It stores only those orders that require 2439 /// reordering, if reordering is not required it is counted using \a 2440 /// NumOpsWantToKeepOriginalOrder. 2441 DenseMap<OrdersType, unsigned, OrdersTypeDenseMapInfo> NumOpsWantToKeepOrder; 2442 /// Number of bundles that do not require reordering. 2443 unsigned NumOpsWantToKeepOriginalOrder = 0; 2444 2445 // Analysis and block reference. 2446 Function *F; 2447 ScalarEvolution *SE; 2448 TargetTransformInfo *TTI; 2449 TargetLibraryInfo *TLI; 2450 AAResults *AA; 2451 LoopInfo *LI; 2452 DominatorTree *DT; 2453 AssumptionCache *AC; 2454 DemandedBits *DB; 2455 const DataLayout *DL; 2456 OptimizationRemarkEmitter *ORE; 2457 2458 unsigned MaxVecRegSize; // This is set by TTI or overridden by cl::opt. 2459 unsigned MinVecRegSize; // Set by cl::opt (default: 128). 2460 2461 /// Instruction builder to construct the vectorized tree. 2462 IRBuilder<> Builder; 2463 2464 /// A map of scalar integer values to the smallest bit width with which they 2465 /// can legally be represented. The values map to (width, signed) pairs, 2466 /// where "width" indicates the minimum bit width and "signed" is True if the 2467 /// value must be signed-extended, rather than zero-extended, back to its 2468 /// original width. 2469 MapVector<Value *, std::pair<uint64_t, bool>> MinBWs; 2470 }; 2471 2472 } // end namespace slpvectorizer 2473 2474 template <> struct GraphTraits<BoUpSLP *> { 2475 using TreeEntry = BoUpSLP::TreeEntry; 2476 2477 /// NodeRef has to be a pointer per the GraphWriter. 2478 using NodeRef = TreeEntry *; 2479 2480 using ContainerTy = BoUpSLP::TreeEntry::VecTreeTy; 2481 2482 /// Add the VectorizableTree to the index iterator to be able to return 2483 /// TreeEntry pointers. 2484 struct ChildIteratorType 2485 : public iterator_adaptor_base< 2486 ChildIteratorType, SmallVector<BoUpSLP::EdgeInfo, 1>::iterator> { 2487 ContainerTy &VectorizableTree; 2488 2489 ChildIteratorType(SmallVector<BoUpSLP::EdgeInfo, 1>::iterator W, 2490 ContainerTy &VT) 2491 : ChildIteratorType::iterator_adaptor_base(W), VectorizableTree(VT) {} 2492 2493 NodeRef operator*() { return I->UserTE; } 2494 }; 2495 2496 static NodeRef getEntryNode(BoUpSLP &R) { 2497 return R.VectorizableTree[0].get(); 2498 } 2499 2500 static ChildIteratorType child_begin(NodeRef N) { 2501 return {N->UserTreeIndices.begin(), N->Container}; 2502 } 2503 2504 static ChildIteratorType child_end(NodeRef N) { 2505 return {N->UserTreeIndices.end(), N->Container}; 2506 } 2507 2508 /// For the node iterator we just need to turn the TreeEntry iterator into a 2509 /// TreeEntry* iterator so that it dereferences to NodeRef. 2510 class nodes_iterator { 2511 using ItTy = ContainerTy::iterator; 2512 ItTy It; 2513 2514 public: 2515 nodes_iterator(const ItTy &It2) : It(It2) {} 2516 NodeRef operator*() { return It->get(); } 2517 nodes_iterator operator++() { 2518 ++It; 2519 return *this; 2520 } 2521 bool operator!=(const nodes_iterator &N2) const { return N2.It != It; } 2522 }; 2523 2524 static nodes_iterator nodes_begin(BoUpSLP *R) { 2525 return nodes_iterator(R->VectorizableTree.begin()); 2526 } 2527 2528 static nodes_iterator nodes_end(BoUpSLP *R) { 2529 return nodes_iterator(R->VectorizableTree.end()); 2530 } 2531 2532 static unsigned size(BoUpSLP *R) { return R->VectorizableTree.size(); } 2533 }; 2534 2535 template <> struct DOTGraphTraits<BoUpSLP *> : public DefaultDOTGraphTraits { 2536 using TreeEntry = BoUpSLP::TreeEntry; 2537 2538 DOTGraphTraits(bool isSimple = false) : DefaultDOTGraphTraits(isSimple) {} 2539 2540 std::string getNodeLabel(const TreeEntry *Entry, const BoUpSLP *R) { 2541 std::string Str; 2542 raw_string_ostream OS(Str); 2543 if (isSplat(Entry->Scalars)) { 2544 OS << "<splat> " << *Entry->Scalars[0]; 2545 return Str; 2546 } 2547 for (auto V : Entry->Scalars) { 2548 OS << *V; 2549 if (llvm::any_of(R->ExternalUses, [&](const BoUpSLP::ExternalUser &EU) { 2550 return EU.Scalar == V; 2551 })) 2552 OS << " <extract>"; 2553 OS << "\n"; 2554 } 2555 return Str; 2556 } 2557 2558 static std::string getNodeAttributes(const TreeEntry *Entry, 2559 const BoUpSLP *) { 2560 if (Entry->State == TreeEntry::NeedToGather) 2561 return "color=red"; 2562 return ""; 2563 } 2564 }; 2565 2566 } // end namespace llvm 2567 2568 BoUpSLP::~BoUpSLP() { 2569 for (const auto &Pair : DeletedInstructions) { 2570 // Replace operands of ignored instructions with Undefs in case if they were 2571 // marked for deletion. 2572 if (Pair.getSecond()) { 2573 Value *Undef = UndefValue::get(Pair.getFirst()->getType()); 2574 Pair.getFirst()->replaceAllUsesWith(Undef); 2575 } 2576 Pair.getFirst()->dropAllReferences(); 2577 } 2578 for (const auto &Pair : DeletedInstructions) { 2579 assert(Pair.getFirst()->use_empty() && 2580 "trying to erase instruction with users."); 2581 Pair.getFirst()->eraseFromParent(); 2582 } 2583 #ifdef EXPENSIVE_CHECKS 2584 // If we could guarantee that this call is not extremely slow, we could 2585 // remove the ifdef limitation (see PR47712). 2586 assert(!verifyFunction(*F, &dbgs())); 2587 #endif 2588 } 2589 2590 void BoUpSLP::eraseInstructions(ArrayRef<Value *> AV) { 2591 for (auto *V : AV) { 2592 if (auto *I = dyn_cast<Instruction>(V)) 2593 eraseInstruction(I, /*ReplaceOpsWithUndef=*/true); 2594 }; 2595 } 2596 2597 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2598 ArrayRef<Value *> UserIgnoreLst) { 2599 ExtraValueToDebugLocsMap ExternallyUsedValues; 2600 buildTree(Roots, ExternallyUsedValues, UserIgnoreLst); 2601 } 2602 2603 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2604 ExtraValueToDebugLocsMap &ExternallyUsedValues, 2605 ArrayRef<Value *> UserIgnoreLst) { 2606 deleteTree(); 2607 UserIgnoreList = UserIgnoreLst; 2608 if (!allSameType(Roots)) 2609 return; 2610 buildTree_rec(Roots, 0, EdgeInfo()); 2611 2612 // Collect the values that we need to extract from the tree. 2613 for (auto &TEPtr : VectorizableTree) { 2614 TreeEntry *Entry = TEPtr.get(); 2615 2616 // No need to handle users of gathered values. 2617 if (Entry->State == TreeEntry::NeedToGather) 2618 continue; 2619 2620 // For each lane: 2621 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 2622 Value *Scalar = Entry->Scalars[Lane]; 2623 int FoundLane = Entry->findLaneForValue(Scalar); 2624 2625 // Check if the scalar is externally used as an extra arg. 2626 auto ExtI = ExternallyUsedValues.find(Scalar); 2627 if (ExtI != ExternallyUsedValues.end()) { 2628 LLVM_DEBUG(dbgs() << "SLP: Need to extract: Extra arg from lane " 2629 << Lane << " from " << *Scalar << ".\n"); 2630 ExternalUses.emplace_back(Scalar, nullptr, FoundLane); 2631 } 2632 for (User *U : Scalar->users()) { 2633 LLVM_DEBUG(dbgs() << "SLP: Checking user:" << *U << ".\n"); 2634 2635 Instruction *UserInst = dyn_cast<Instruction>(U); 2636 if (!UserInst) 2637 continue; 2638 2639 // Skip in-tree scalars that become vectors 2640 if (TreeEntry *UseEntry = getTreeEntry(U)) { 2641 Value *UseScalar = UseEntry->Scalars[0]; 2642 // Some in-tree scalars will remain as scalar in vectorized 2643 // instructions. If that is the case, the one in Lane 0 will 2644 // be used. 2645 if (UseScalar != U || 2646 UseEntry->State == TreeEntry::ScatterVectorize || 2647 !InTreeUserNeedToExtract(Scalar, UserInst, TLI)) { 2648 LLVM_DEBUG(dbgs() << "SLP: \tInternal user will be removed:" << *U 2649 << ".\n"); 2650 assert(UseEntry->State != TreeEntry::NeedToGather && "Bad state"); 2651 continue; 2652 } 2653 } 2654 2655 // Ignore users in the user ignore list. 2656 if (is_contained(UserIgnoreList, UserInst)) 2657 continue; 2658 2659 LLVM_DEBUG(dbgs() << "SLP: Need to extract:" << *U << " from lane " 2660 << Lane << " from " << *Scalar << ".\n"); 2661 ExternalUses.push_back(ExternalUser(Scalar, U, FoundLane)); 2662 } 2663 } 2664 } 2665 } 2666 2667 void BoUpSLP::buildTree_rec(ArrayRef<Value *> VL, unsigned Depth, 2668 const EdgeInfo &UserTreeIdx) { 2669 assert((allConstant(VL) || allSameType(VL)) && "Invalid types!"); 2670 2671 InstructionsState S = getSameOpcode(VL); 2672 if (Depth == RecursionMaxDepth) { 2673 LLVM_DEBUG(dbgs() << "SLP: Gathering due to max recursion depth.\n"); 2674 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2675 return; 2676 } 2677 2678 // Don't handle scalable vectors 2679 if (S.getOpcode() == Instruction::ExtractElement && 2680 isa<ScalableVectorType>( 2681 cast<ExtractElementInst>(S.OpValue)->getVectorOperandType())) { 2682 LLVM_DEBUG(dbgs() << "SLP: Gathering due to scalable vector type.\n"); 2683 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2684 return; 2685 } 2686 2687 // Don't handle vectors. 2688 if (S.OpValue->getType()->isVectorTy() && 2689 !isa<InsertElementInst>(S.OpValue)) { 2690 LLVM_DEBUG(dbgs() << "SLP: Gathering due to vector type.\n"); 2691 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2692 return; 2693 } 2694 2695 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) 2696 if (SI->getValueOperand()->getType()->isVectorTy()) { 2697 LLVM_DEBUG(dbgs() << "SLP: Gathering due to store vector type.\n"); 2698 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2699 return; 2700 } 2701 2702 // If all of the operands are identical or constant we have a simple solution. 2703 if (allConstant(VL) || isSplat(VL) || !allSameBlock(VL) || !S.getOpcode()) { 2704 LLVM_DEBUG(dbgs() << "SLP: Gathering due to C,S,B,O. \n"); 2705 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2706 return; 2707 } 2708 2709 // We now know that this is a vector of instructions of the same type from 2710 // the same block. 2711 2712 // Don't vectorize ephemeral values. 2713 for (Value *V : VL) { 2714 if (EphValues.count(V)) { 2715 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2716 << ") is ephemeral.\n"); 2717 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2718 return; 2719 } 2720 } 2721 2722 // Check if this is a duplicate of another entry. 2723 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 2724 LLVM_DEBUG(dbgs() << "SLP: \tChecking bundle: " << *S.OpValue << ".\n"); 2725 if (!E->isSame(VL)) { 2726 LLVM_DEBUG(dbgs() << "SLP: Gathering due to partial overlap.\n"); 2727 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2728 return; 2729 } 2730 // Record the reuse of the tree node. FIXME, currently this is only used to 2731 // properly draw the graph rather than for the actual vectorization. 2732 E->UserTreeIndices.push_back(UserTreeIdx); 2733 LLVM_DEBUG(dbgs() << "SLP: Perfect diamond merge at " << *S.OpValue 2734 << ".\n"); 2735 return; 2736 } 2737 2738 // Check that none of the instructions in the bundle are already in the tree. 2739 for (Value *V : VL) { 2740 auto *I = dyn_cast<Instruction>(V); 2741 if (!I) 2742 continue; 2743 if (getTreeEntry(I)) { 2744 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2745 << ") is already in tree.\n"); 2746 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2747 return; 2748 } 2749 } 2750 2751 // If any of the scalars is marked as a value that needs to stay scalar, then 2752 // we need to gather the scalars. 2753 // The reduction nodes (stored in UserIgnoreList) also should stay scalar. 2754 for (Value *V : VL) { 2755 if (MustGather.count(V) || is_contained(UserIgnoreList, V)) { 2756 LLVM_DEBUG(dbgs() << "SLP: Gathering due to gathered scalar.\n"); 2757 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2758 return; 2759 } 2760 } 2761 2762 // Check that all of the users of the scalars that we want to vectorize are 2763 // schedulable. 2764 auto *VL0 = cast<Instruction>(S.OpValue); 2765 BasicBlock *BB = VL0->getParent(); 2766 2767 if (!DT->isReachableFromEntry(BB)) { 2768 // Don't go into unreachable blocks. They may contain instructions with 2769 // dependency cycles which confuse the final scheduling. 2770 LLVM_DEBUG(dbgs() << "SLP: bundle in unreachable block.\n"); 2771 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2772 return; 2773 } 2774 2775 // Check that every instruction appears once in this bundle. 2776 SmallVector<unsigned, 4> ReuseShuffleIndicies; 2777 SmallVector<Value *, 4> UniqueValues; 2778 DenseMap<Value *, unsigned> UniquePositions; 2779 for (Value *V : VL) { 2780 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 2781 ReuseShuffleIndicies.emplace_back(Res.first->second); 2782 if (Res.second) 2783 UniqueValues.emplace_back(V); 2784 } 2785 size_t NumUniqueScalarValues = UniqueValues.size(); 2786 if (NumUniqueScalarValues == VL.size()) { 2787 ReuseShuffleIndicies.clear(); 2788 } else { 2789 LLVM_DEBUG(dbgs() << "SLP: Shuffle for reused scalars.\n"); 2790 if (NumUniqueScalarValues <= 1 || 2791 !llvm::isPowerOf2_32(NumUniqueScalarValues)) { 2792 LLVM_DEBUG(dbgs() << "SLP: Scalar used twice in bundle.\n"); 2793 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2794 return; 2795 } 2796 VL = UniqueValues; 2797 } 2798 2799 auto &BSRef = BlocksSchedules[BB]; 2800 if (!BSRef) 2801 BSRef = std::make_unique<BlockScheduling>(BB); 2802 2803 BlockScheduling &BS = *BSRef.get(); 2804 2805 Optional<ScheduleData *> Bundle = BS.tryScheduleBundle(VL, this, S); 2806 if (!Bundle) { 2807 LLVM_DEBUG(dbgs() << "SLP: We are not able to schedule this bundle!\n"); 2808 assert((!BS.getScheduleData(VL0) || 2809 !BS.getScheduleData(VL0)->isPartOfBundle()) && 2810 "tryScheduleBundle should cancelScheduling on failure"); 2811 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2812 ReuseShuffleIndicies); 2813 return; 2814 } 2815 LLVM_DEBUG(dbgs() << "SLP: We are able to schedule this bundle.\n"); 2816 2817 unsigned ShuffleOrOp = S.isAltShuffle() ? 2818 (unsigned) Instruction::ShuffleVector : S.getOpcode(); 2819 switch (ShuffleOrOp) { 2820 case Instruction::PHI: { 2821 auto *PH = cast<PHINode>(VL0); 2822 2823 // Check for terminator values (e.g. invoke). 2824 for (Value *V : VL) 2825 for (unsigned I = 0, E = PH->getNumIncomingValues(); I < E; ++I) { 2826 Instruction *Term = dyn_cast<Instruction>( 2827 cast<PHINode>(V)->getIncomingValueForBlock( 2828 PH->getIncomingBlock(I))); 2829 if (Term && Term->isTerminator()) { 2830 LLVM_DEBUG(dbgs() 2831 << "SLP: Need to swizzle PHINodes (terminator use).\n"); 2832 BS.cancelScheduling(VL, VL0); 2833 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2834 ReuseShuffleIndicies); 2835 return; 2836 } 2837 } 2838 2839 TreeEntry *TE = 2840 newTreeEntry(VL, Bundle, S, UserTreeIdx, ReuseShuffleIndicies); 2841 LLVM_DEBUG(dbgs() << "SLP: added a vector of PHINodes.\n"); 2842 2843 // Keeps the reordered operands to avoid code duplication. 2844 SmallVector<ValueList, 2> OperandsVec; 2845 for (unsigned I = 0, E = PH->getNumIncomingValues(); I < E; ++I) { 2846 if (!DT->isReachableFromEntry(PH->getIncomingBlock(I))) { 2847 ValueList Operands(VL.size(), PoisonValue::get(PH->getType())); 2848 TE->setOperand(I, Operands); 2849 OperandsVec.push_back(Operands); 2850 continue; 2851 } 2852 ValueList Operands; 2853 // Prepare the operand vector. 2854 for (Value *V : VL) 2855 Operands.push_back(cast<PHINode>(V)->getIncomingValueForBlock( 2856 PH->getIncomingBlock(I))); 2857 TE->setOperand(I, Operands); 2858 OperandsVec.push_back(Operands); 2859 } 2860 for (unsigned OpIdx = 0, OpE = OperandsVec.size(); OpIdx != OpE; ++OpIdx) 2861 buildTree_rec(OperandsVec[OpIdx], Depth + 1, {TE, OpIdx}); 2862 return; 2863 } 2864 case Instruction::ExtractValue: 2865 case Instruction::ExtractElement: { 2866 OrdersType CurrentOrder; 2867 bool Reuse = canReuseExtract(VL, VL0, CurrentOrder); 2868 if (Reuse) { 2869 LLVM_DEBUG(dbgs() << "SLP: Reusing or shuffling extract sequence.\n"); 2870 ++NumOpsWantToKeepOriginalOrder; 2871 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2872 ReuseShuffleIndicies); 2873 // This is a special case, as it does not gather, but at the same time 2874 // we are not extending buildTree_rec() towards the operands. 2875 ValueList Op0; 2876 Op0.assign(VL.size(), VL0->getOperand(0)); 2877 VectorizableTree.back()->setOperand(0, Op0); 2878 return; 2879 } 2880 if (!CurrentOrder.empty()) { 2881 LLVM_DEBUG({ 2882 dbgs() << "SLP: Reusing or shuffling of reordered extract sequence " 2883 "with order"; 2884 for (unsigned Idx : CurrentOrder) 2885 dbgs() << " " << Idx; 2886 dbgs() << "\n"; 2887 }); 2888 // Insert new order with initial value 0, if it does not exist, 2889 // otherwise return the iterator to the existing one. 2890 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2891 ReuseShuffleIndicies, CurrentOrder); 2892 findRootOrder(CurrentOrder); 2893 ++NumOpsWantToKeepOrder[CurrentOrder]; 2894 // This is a special case, as it does not gather, but at the same time 2895 // we are not extending buildTree_rec() towards the operands. 2896 ValueList Op0; 2897 Op0.assign(VL.size(), VL0->getOperand(0)); 2898 VectorizableTree.back()->setOperand(0, Op0); 2899 return; 2900 } 2901 LLVM_DEBUG(dbgs() << "SLP: Gather extract sequence.\n"); 2902 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2903 ReuseShuffleIndicies); 2904 BS.cancelScheduling(VL, VL0); 2905 return; 2906 } 2907 case Instruction::InsertElement: { 2908 assert(ReuseShuffleIndicies.empty() && "All inserts should be unique"); 2909 2910 // Check that we have a buildvector and not a shuffle of 2 or more 2911 // different vectors. 2912 ValueSet SourceVectors; 2913 for (Value *V : VL) 2914 SourceVectors.insert(cast<Instruction>(V)->getOperand(0)); 2915 2916 if (count_if(VL, [&SourceVectors](Value *V) { 2917 return !SourceVectors.contains(V); 2918 }) >= 2) { 2919 // Found 2nd source vector - cancel. 2920 LLVM_DEBUG(dbgs() << "SLP: Gather of insertelement vectors with " 2921 "different source vectors.\n"); 2922 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2923 ReuseShuffleIndicies); 2924 BS.cancelScheduling(VL, VL0); 2925 return; 2926 } 2927 2928 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx); 2929 LLVM_DEBUG(dbgs() << "SLP: added inserts bundle.\n"); 2930 2931 constexpr int NumOps = 2; 2932 ValueList VectorOperands[NumOps]; 2933 for (int I = 0; I < NumOps; ++I) { 2934 for (Value *V : VL) 2935 VectorOperands[I].push_back(cast<Instruction>(V)->getOperand(I)); 2936 2937 TE->setOperand(I, VectorOperands[I]); 2938 } 2939 buildTree_rec(VectorOperands[NumOps - 1], Depth + 1, {TE, 0}); 2940 return; 2941 } 2942 case Instruction::Load: { 2943 // Check that a vectorized load would load the same memory as a scalar 2944 // load. For example, we don't want to vectorize loads that are smaller 2945 // than 8-bit. Even though we have a packed struct {<i2, i2, i2, i2>} LLVM 2946 // treats loading/storing it as an i8 struct. If we vectorize loads/stores 2947 // from such a struct, we read/write packed bits disagreeing with the 2948 // unvectorized version. 2949 Type *ScalarTy = VL0->getType(); 2950 2951 if (DL->getTypeSizeInBits(ScalarTy) != 2952 DL->getTypeAllocSizeInBits(ScalarTy)) { 2953 BS.cancelScheduling(VL, VL0); 2954 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2955 ReuseShuffleIndicies); 2956 LLVM_DEBUG(dbgs() << "SLP: Gathering loads of non-packed type.\n"); 2957 return; 2958 } 2959 2960 // Make sure all loads in the bundle are simple - we can't vectorize 2961 // atomic or volatile loads. 2962 SmallVector<Value *, 4> PointerOps(VL.size()); 2963 auto POIter = PointerOps.begin(); 2964 for (Value *V : VL) { 2965 auto *L = cast<LoadInst>(V); 2966 if (!L->isSimple()) { 2967 BS.cancelScheduling(VL, VL0); 2968 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2969 ReuseShuffleIndicies); 2970 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple loads.\n"); 2971 return; 2972 } 2973 *POIter = L->getPointerOperand(); 2974 ++POIter; 2975 } 2976 2977 OrdersType CurrentOrder; 2978 // Check the order of pointer operands. 2979 if (llvm::sortPtrAccesses(PointerOps, ScalarTy, *DL, *SE, CurrentOrder)) { 2980 Value *Ptr0; 2981 Value *PtrN; 2982 if (CurrentOrder.empty()) { 2983 Ptr0 = PointerOps.front(); 2984 PtrN = PointerOps.back(); 2985 } else { 2986 Ptr0 = PointerOps[CurrentOrder.front()]; 2987 PtrN = PointerOps[CurrentOrder.back()]; 2988 } 2989 Optional<int> Diff = getPointersDiff( 2990 ScalarTy, Ptr0, ScalarTy, PtrN, *DL, *SE); 2991 // Check that the sorted loads are consecutive. 2992 if (static_cast<unsigned>(*Diff) == VL.size() - 1) { 2993 if (CurrentOrder.empty()) { 2994 // Original loads are consecutive and does not require reordering. 2995 ++NumOpsWantToKeepOriginalOrder; 2996 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, 2997 UserTreeIdx, ReuseShuffleIndicies); 2998 TE->setOperandsInOrder(); 2999 LLVM_DEBUG(dbgs() << "SLP: added a vector of loads.\n"); 3000 } else { 3001 // Need to reorder. 3002 TreeEntry *TE = 3003 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3004 ReuseShuffleIndicies, CurrentOrder); 3005 TE->setOperandsInOrder(); 3006 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled loads.\n"); 3007 findRootOrder(CurrentOrder); 3008 ++NumOpsWantToKeepOrder[CurrentOrder]; 3009 } 3010 return; 3011 } 3012 Align CommonAlignment = cast<LoadInst>(VL0)->getAlign(); 3013 for (Value *V : VL) 3014 CommonAlignment = 3015 commonAlignment(CommonAlignment, cast<LoadInst>(V)->getAlign()); 3016 if (TTI->isLegalMaskedGather(FixedVectorType::get(ScalarTy, VL.size()), 3017 CommonAlignment)) { 3018 // Vectorizing non-consecutive loads with `llvm.masked.gather`. 3019 TreeEntry *TE = newTreeEntry(VL, TreeEntry::ScatterVectorize, Bundle, 3020 S, UserTreeIdx, ReuseShuffleIndicies); 3021 TE->setOperandsInOrder(); 3022 buildTree_rec(PointerOps, Depth + 1, {TE, 0}); 3023 LLVM_DEBUG(dbgs() 3024 << "SLP: added a vector of non-consecutive loads.\n"); 3025 return; 3026 } 3027 } 3028 3029 LLVM_DEBUG(dbgs() << "SLP: Gathering non-consecutive loads.\n"); 3030 BS.cancelScheduling(VL, VL0); 3031 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3032 ReuseShuffleIndicies); 3033 return; 3034 } 3035 case Instruction::ZExt: 3036 case Instruction::SExt: 3037 case Instruction::FPToUI: 3038 case Instruction::FPToSI: 3039 case Instruction::FPExt: 3040 case Instruction::PtrToInt: 3041 case Instruction::IntToPtr: 3042 case Instruction::SIToFP: 3043 case Instruction::UIToFP: 3044 case Instruction::Trunc: 3045 case Instruction::FPTrunc: 3046 case Instruction::BitCast: { 3047 Type *SrcTy = VL0->getOperand(0)->getType(); 3048 for (Value *V : VL) { 3049 Type *Ty = cast<Instruction>(V)->getOperand(0)->getType(); 3050 if (Ty != SrcTy || !isValidElementType(Ty)) { 3051 BS.cancelScheduling(VL, VL0); 3052 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3053 ReuseShuffleIndicies); 3054 LLVM_DEBUG(dbgs() 3055 << "SLP: Gathering casts with different src types.\n"); 3056 return; 3057 } 3058 } 3059 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3060 ReuseShuffleIndicies); 3061 LLVM_DEBUG(dbgs() << "SLP: added a vector of casts.\n"); 3062 3063 TE->setOperandsInOrder(); 3064 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 3065 ValueList Operands; 3066 // Prepare the operand vector. 3067 for (Value *V : VL) 3068 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3069 3070 buildTree_rec(Operands, Depth + 1, {TE, i}); 3071 } 3072 return; 3073 } 3074 case Instruction::ICmp: 3075 case Instruction::FCmp: { 3076 // Check that all of the compares have the same predicate. 3077 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 3078 CmpInst::Predicate SwapP0 = CmpInst::getSwappedPredicate(P0); 3079 Type *ComparedTy = VL0->getOperand(0)->getType(); 3080 for (Value *V : VL) { 3081 CmpInst *Cmp = cast<CmpInst>(V); 3082 if ((Cmp->getPredicate() != P0 && Cmp->getPredicate() != SwapP0) || 3083 Cmp->getOperand(0)->getType() != ComparedTy) { 3084 BS.cancelScheduling(VL, VL0); 3085 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3086 ReuseShuffleIndicies); 3087 LLVM_DEBUG(dbgs() 3088 << "SLP: Gathering cmp with different predicate.\n"); 3089 return; 3090 } 3091 } 3092 3093 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3094 ReuseShuffleIndicies); 3095 LLVM_DEBUG(dbgs() << "SLP: added a vector of compares.\n"); 3096 3097 ValueList Left, Right; 3098 if (cast<CmpInst>(VL0)->isCommutative()) { 3099 // Commutative predicate - collect + sort operands of the instructions 3100 // so that each side is more likely to have the same opcode. 3101 assert(P0 == SwapP0 && "Commutative Predicate mismatch"); 3102 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 3103 } else { 3104 // Collect operands - commute if it uses the swapped predicate. 3105 for (Value *V : VL) { 3106 auto *Cmp = cast<CmpInst>(V); 3107 Value *LHS = Cmp->getOperand(0); 3108 Value *RHS = Cmp->getOperand(1); 3109 if (Cmp->getPredicate() != P0) 3110 std::swap(LHS, RHS); 3111 Left.push_back(LHS); 3112 Right.push_back(RHS); 3113 } 3114 } 3115 TE->setOperand(0, Left); 3116 TE->setOperand(1, Right); 3117 buildTree_rec(Left, Depth + 1, {TE, 0}); 3118 buildTree_rec(Right, Depth + 1, {TE, 1}); 3119 return; 3120 } 3121 case Instruction::Select: 3122 case Instruction::FNeg: 3123 case Instruction::Add: 3124 case Instruction::FAdd: 3125 case Instruction::Sub: 3126 case Instruction::FSub: 3127 case Instruction::Mul: 3128 case Instruction::FMul: 3129 case Instruction::UDiv: 3130 case Instruction::SDiv: 3131 case Instruction::FDiv: 3132 case Instruction::URem: 3133 case Instruction::SRem: 3134 case Instruction::FRem: 3135 case Instruction::Shl: 3136 case Instruction::LShr: 3137 case Instruction::AShr: 3138 case Instruction::And: 3139 case Instruction::Or: 3140 case Instruction::Xor: { 3141 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3142 ReuseShuffleIndicies); 3143 LLVM_DEBUG(dbgs() << "SLP: added a vector of un/bin op.\n"); 3144 3145 // Sort operands of the instructions so that each side is more likely to 3146 // have the same opcode. 3147 if (isa<BinaryOperator>(VL0) && VL0->isCommutative()) { 3148 ValueList Left, Right; 3149 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 3150 TE->setOperand(0, Left); 3151 TE->setOperand(1, Right); 3152 buildTree_rec(Left, Depth + 1, {TE, 0}); 3153 buildTree_rec(Right, Depth + 1, {TE, 1}); 3154 return; 3155 } 3156 3157 TE->setOperandsInOrder(); 3158 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 3159 ValueList Operands; 3160 // Prepare the operand vector. 3161 for (Value *V : VL) 3162 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3163 3164 buildTree_rec(Operands, Depth + 1, {TE, i}); 3165 } 3166 return; 3167 } 3168 case Instruction::GetElementPtr: { 3169 // We don't combine GEPs with complicated (nested) indexing. 3170 for (Value *V : VL) { 3171 if (cast<Instruction>(V)->getNumOperands() != 2) { 3172 LLVM_DEBUG(dbgs() << "SLP: not-vectorizable GEP (nested indexes).\n"); 3173 BS.cancelScheduling(VL, VL0); 3174 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3175 ReuseShuffleIndicies); 3176 return; 3177 } 3178 } 3179 3180 // We can't combine several GEPs into one vector if they operate on 3181 // different types. 3182 Type *Ty0 = VL0->getOperand(0)->getType(); 3183 for (Value *V : VL) { 3184 Type *CurTy = cast<Instruction>(V)->getOperand(0)->getType(); 3185 if (Ty0 != CurTy) { 3186 LLVM_DEBUG(dbgs() 3187 << "SLP: not-vectorizable GEP (different types).\n"); 3188 BS.cancelScheduling(VL, VL0); 3189 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3190 ReuseShuffleIndicies); 3191 return; 3192 } 3193 } 3194 3195 // We don't combine GEPs with non-constant indexes. 3196 Type *Ty1 = VL0->getOperand(1)->getType(); 3197 for (Value *V : VL) { 3198 auto Op = cast<Instruction>(V)->getOperand(1); 3199 if (!isa<ConstantInt>(Op) || 3200 (Op->getType() != Ty1 && 3201 Op->getType()->getScalarSizeInBits() > 3202 DL->getIndexSizeInBits( 3203 V->getType()->getPointerAddressSpace()))) { 3204 LLVM_DEBUG(dbgs() 3205 << "SLP: not-vectorizable GEP (non-constant indexes).\n"); 3206 BS.cancelScheduling(VL, VL0); 3207 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3208 ReuseShuffleIndicies); 3209 return; 3210 } 3211 } 3212 3213 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3214 ReuseShuffleIndicies); 3215 LLVM_DEBUG(dbgs() << "SLP: added a vector of GEPs.\n"); 3216 TE->setOperandsInOrder(); 3217 for (unsigned i = 0, e = 2; i < e; ++i) { 3218 ValueList Operands; 3219 // Prepare the operand vector. 3220 for (Value *V : VL) 3221 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3222 3223 buildTree_rec(Operands, Depth + 1, {TE, i}); 3224 } 3225 return; 3226 } 3227 case Instruction::Store: { 3228 // Check if the stores are consecutive or if we need to swizzle them. 3229 llvm::Type *ScalarTy = cast<StoreInst>(VL0)->getValueOperand()->getType(); 3230 // Avoid types that are padded when being allocated as scalars, while 3231 // being packed together in a vector (such as i1). 3232 if (DL->getTypeSizeInBits(ScalarTy) != 3233 DL->getTypeAllocSizeInBits(ScalarTy)) { 3234 BS.cancelScheduling(VL, VL0); 3235 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3236 ReuseShuffleIndicies); 3237 LLVM_DEBUG(dbgs() << "SLP: Gathering stores of non-packed type.\n"); 3238 return; 3239 } 3240 // Make sure all stores in the bundle are simple - we can't vectorize 3241 // atomic or volatile stores. 3242 SmallVector<Value *, 4> PointerOps(VL.size()); 3243 ValueList Operands(VL.size()); 3244 auto POIter = PointerOps.begin(); 3245 auto OIter = Operands.begin(); 3246 for (Value *V : VL) { 3247 auto *SI = cast<StoreInst>(V); 3248 if (!SI->isSimple()) { 3249 BS.cancelScheduling(VL, VL0); 3250 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3251 ReuseShuffleIndicies); 3252 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple stores.\n"); 3253 return; 3254 } 3255 *POIter = SI->getPointerOperand(); 3256 *OIter = SI->getValueOperand(); 3257 ++POIter; 3258 ++OIter; 3259 } 3260 3261 OrdersType CurrentOrder; 3262 // Check the order of pointer operands. 3263 if (llvm::sortPtrAccesses(PointerOps, ScalarTy, *DL, *SE, CurrentOrder)) { 3264 Value *Ptr0; 3265 Value *PtrN; 3266 if (CurrentOrder.empty()) { 3267 Ptr0 = PointerOps.front(); 3268 PtrN = PointerOps.back(); 3269 } else { 3270 Ptr0 = PointerOps[CurrentOrder.front()]; 3271 PtrN = PointerOps[CurrentOrder.back()]; 3272 } 3273 Optional<int> Dist = 3274 getPointersDiff(ScalarTy, Ptr0, ScalarTy, PtrN, *DL, *SE); 3275 // Check that the sorted pointer operands are consecutive. 3276 if (static_cast<unsigned>(*Dist) == VL.size() - 1) { 3277 if (CurrentOrder.empty()) { 3278 // Original stores are consecutive and does not require reordering. 3279 ++NumOpsWantToKeepOriginalOrder; 3280 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, 3281 UserTreeIdx, ReuseShuffleIndicies); 3282 TE->setOperandsInOrder(); 3283 buildTree_rec(Operands, Depth + 1, {TE, 0}); 3284 LLVM_DEBUG(dbgs() << "SLP: added a vector of stores.\n"); 3285 } else { 3286 TreeEntry *TE = 3287 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3288 ReuseShuffleIndicies, CurrentOrder); 3289 TE->setOperandsInOrder(); 3290 buildTree_rec(Operands, Depth + 1, {TE, 0}); 3291 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled stores.\n"); 3292 findRootOrder(CurrentOrder); 3293 ++NumOpsWantToKeepOrder[CurrentOrder]; 3294 } 3295 return; 3296 } 3297 } 3298 3299 BS.cancelScheduling(VL, VL0); 3300 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3301 ReuseShuffleIndicies); 3302 LLVM_DEBUG(dbgs() << "SLP: Non-consecutive store.\n"); 3303 return; 3304 } 3305 case Instruction::Call: { 3306 // Check if the calls are all to the same vectorizable intrinsic or 3307 // library function. 3308 CallInst *CI = cast<CallInst>(VL0); 3309 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3310 3311 VFShape Shape = VFShape::get( 3312 *CI, ElementCount::getFixed(static_cast<unsigned int>(VL.size())), 3313 false /*HasGlobalPred*/); 3314 Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape); 3315 3316 if (!VecFunc && !isTriviallyVectorizable(ID)) { 3317 BS.cancelScheduling(VL, VL0); 3318 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3319 ReuseShuffleIndicies); 3320 LLVM_DEBUG(dbgs() << "SLP: Non-vectorizable call.\n"); 3321 return; 3322 } 3323 Function *F = CI->getCalledFunction(); 3324 unsigned NumArgs = CI->getNumArgOperands(); 3325 SmallVector<Value*, 4> ScalarArgs(NumArgs, nullptr); 3326 for (unsigned j = 0; j != NumArgs; ++j) 3327 if (hasVectorInstrinsicScalarOpd(ID, j)) 3328 ScalarArgs[j] = CI->getArgOperand(j); 3329 for (Value *V : VL) { 3330 CallInst *CI2 = dyn_cast<CallInst>(V); 3331 if (!CI2 || CI2->getCalledFunction() != F || 3332 getVectorIntrinsicIDForCall(CI2, TLI) != ID || 3333 (VecFunc && 3334 VecFunc != VFDatabase(*CI2).getVectorizedFunction(Shape)) || 3335 !CI->hasIdenticalOperandBundleSchema(*CI2)) { 3336 BS.cancelScheduling(VL, VL0); 3337 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3338 ReuseShuffleIndicies); 3339 LLVM_DEBUG(dbgs() << "SLP: mismatched calls:" << *CI << "!=" << *V 3340 << "\n"); 3341 return; 3342 } 3343 // Some intrinsics have scalar arguments and should be same in order for 3344 // them to be vectorized. 3345 for (unsigned j = 0; j != NumArgs; ++j) { 3346 if (hasVectorInstrinsicScalarOpd(ID, j)) { 3347 Value *A1J = CI2->getArgOperand(j); 3348 if (ScalarArgs[j] != A1J) { 3349 BS.cancelScheduling(VL, VL0); 3350 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3351 ReuseShuffleIndicies); 3352 LLVM_DEBUG(dbgs() << "SLP: mismatched arguments in call:" << *CI 3353 << " argument " << ScalarArgs[j] << "!=" << A1J 3354 << "\n"); 3355 return; 3356 } 3357 } 3358 } 3359 // Verify that the bundle operands are identical between the two calls. 3360 if (CI->hasOperandBundles() && 3361 !std::equal(CI->op_begin() + CI->getBundleOperandsStartIndex(), 3362 CI->op_begin() + CI->getBundleOperandsEndIndex(), 3363 CI2->op_begin() + CI2->getBundleOperandsStartIndex())) { 3364 BS.cancelScheduling(VL, VL0); 3365 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3366 ReuseShuffleIndicies); 3367 LLVM_DEBUG(dbgs() << "SLP: mismatched bundle operands in calls:" 3368 << *CI << "!=" << *V << '\n'); 3369 return; 3370 } 3371 } 3372 3373 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3374 ReuseShuffleIndicies); 3375 TE->setOperandsInOrder(); 3376 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 3377 ValueList Operands; 3378 // Prepare the operand vector. 3379 for (Value *V : VL) { 3380 auto *CI2 = cast<CallInst>(V); 3381 Operands.push_back(CI2->getArgOperand(i)); 3382 } 3383 buildTree_rec(Operands, Depth + 1, {TE, i}); 3384 } 3385 return; 3386 } 3387 case Instruction::ShuffleVector: { 3388 // If this is not an alternate sequence of opcode like add-sub 3389 // then do not vectorize this instruction. 3390 if (!S.isAltShuffle()) { 3391 BS.cancelScheduling(VL, VL0); 3392 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3393 ReuseShuffleIndicies); 3394 LLVM_DEBUG(dbgs() << "SLP: ShuffleVector are not vectorized.\n"); 3395 return; 3396 } 3397 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3398 ReuseShuffleIndicies); 3399 LLVM_DEBUG(dbgs() << "SLP: added a ShuffleVector op.\n"); 3400 3401 // Reorder operands if reordering would enable vectorization. 3402 if (isa<BinaryOperator>(VL0)) { 3403 ValueList Left, Right; 3404 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 3405 TE->setOperand(0, Left); 3406 TE->setOperand(1, Right); 3407 buildTree_rec(Left, Depth + 1, {TE, 0}); 3408 buildTree_rec(Right, Depth + 1, {TE, 1}); 3409 return; 3410 } 3411 3412 TE->setOperandsInOrder(); 3413 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 3414 ValueList Operands; 3415 // Prepare the operand vector. 3416 for (Value *V : VL) 3417 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3418 3419 buildTree_rec(Operands, Depth + 1, {TE, i}); 3420 } 3421 return; 3422 } 3423 default: 3424 BS.cancelScheduling(VL, VL0); 3425 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3426 ReuseShuffleIndicies); 3427 LLVM_DEBUG(dbgs() << "SLP: Gathering unknown instruction.\n"); 3428 return; 3429 } 3430 } 3431 3432 unsigned BoUpSLP::canMapToVector(Type *T, const DataLayout &DL) const { 3433 unsigned N = 1; 3434 Type *EltTy = T; 3435 3436 while (isa<StructType>(EltTy) || isa<ArrayType>(EltTy) || 3437 isa<VectorType>(EltTy)) { 3438 if (auto *ST = dyn_cast<StructType>(EltTy)) { 3439 // Check that struct is homogeneous. 3440 for (const auto *Ty : ST->elements()) 3441 if (Ty != *ST->element_begin()) 3442 return 0; 3443 N *= ST->getNumElements(); 3444 EltTy = *ST->element_begin(); 3445 } else if (auto *AT = dyn_cast<ArrayType>(EltTy)) { 3446 N *= AT->getNumElements(); 3447 EltTy = AT->getElementType(); 3448 } else { 3449 auto *VT = cast<FixedVectorType>(EltTy); 3450 N *= VT->getNumElements(); 3451 EltTy = VT->getElementType(); 3452 } 3453 } 3454 3455 if (!isValidElementType(EltTy)) 3456 return 0; 3457 uint64_t VTSize = DL.getTypeStoreSizeInBits(FixedVectorType::get(EltTy, N)); 3458 if (VTSize < MinVecRegSize || VTSize > MaxVecRegSize || VTSize != DL.getTypeStoreSizeInBits(T)) 3459 return 0; 3460 return N; 3461 } 3462 3463 bool BoUpSLP::canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 3464 SmallVectorImpl<unsigned> &CurrentOrder) const { 3465 Instruction *E0 = cast<Instruction>(OpValue); 3466 assert(E0->getOpcode() == Instruction::ExtractElement || 3467 E0->getOpcode() == Instruction::ExtractValue); 3468 assert(E0->getOpcode() == getSameOpcode(VL).getOpcode() && "Invalid opcode"); 3469 // Check if all of the extracts come from the same vector and from the 3470 // correct offset. 3471 Value *Vec = E0->getOperand(0); 3472 3473 CurrentOrder.clear(); 3474 3475 // We have to extract from a vector/aggregate with the same number of elements. 3476 unsigned NElts; 3477 if (E0->getOpcode() == Instruction::ExtractValue) { 3478 const DataLayout &DL = E0->getModule()->getDataLayout(); 3479 NElts = canMapToVector(Vec->getType(), DL); 3480 if (!NElts) 3481 return false; 3482 // Check if load can be rewritten as load of vector. 3483 LoadInst *LI = dyn_cast<LoadInst>(Vec); 3484 if (!LI || !LI->isSimple() || !LI->hasNUses(VL.size())) 3485 return false; 3486 } else { 3487 NElts = cast<FixedVectorType>(Vec->getType())->getNumElements(); 3488 } 3489 3490 if (NElts != VL.size()) 3491 return false; 3492 3493 // Check that all of the indices extract from the correct offset. 3494 bool ShouldKeepOrder = true; 3495 unsigned E = VL.size(); 3496 // Assign to all items the initial value E + 1 so we can check if the extract 3497 // instruction index was used already. 3498 // Also, later we can check that all the indices are used and we have a 3499 // consecutive access in the extract instructions, by checking that no 3500 // element of CurrentOrder still has value E + 1. 3501 CurrentOrder.assign(E, E + 1); 3502 unsigned I = 0; 3503 for (; I < E; ++I) { 3504 auto *Inst = cast<Instruction>(VL[I]); 3505 if (Inst->getOperand(0) != Vec) 3506 break; 3507 Optional<unsigned> Idx = getExtractIndex(Inst); 3508 if (!Idx) 3509 break; 3510 const unsigned ExtIdx = *Idx; 3511 if (ExtIdx != I) { 3512 if (ExtIdx >= E || CurrentOrder[ExtIdx] != E + 1) 3513 break; 3514 ShouldKeepOrder = false; 3515 CurrentOrder[ExtIdx] = I; 3516 } else { 3517 if (CurrentOrder[I] != E + 1) 3518 break; 3519 CurrentOrder[I] = I; 3520 } 3521 } 3522 if (I < E) { 3523 CurrentOrder.clear(); 3524 return false; 3525 } 3526 3527 return ShouldKeepOrder; 3528 } 3529 3530 bool BoUpSLP::areAllUsersVectorized(Instruction *I, 3531 ArrayRef<Value *> VectorizedVals) const { 3532 return (I->hasOneUse() && is_contained(VectorizedVals, I)) || 3533 llvm::all_of(I->users(), [this](User *U) { 3534 return ScalarToTreeEntry.count(U) > 0; 3535 }); 3536 } 3537 3538 static std::pair<InstructionCost, InstructionCost> 3539 getVectorCallCosts(CallInst *CI, FixedVectorType *VecTy, 3540 TargetTransformInfo *TTI, TargetLibraryInfo *TLI) { 3541 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3542 3543 // Calculate the cost of the scalar and vector calls. 3544 SmallVector<Type *, 4> VecTys; 3545 for (Use &Arg : CI->args()) 3546 VecTys.push_back( 3547 FixedVectorType::get(Arg->getType(), VecTy->getNumElements())); 3548 FastMathFlags FMF; 3549 if (auto *FPCI = dyn_cast<FPMathOperator>(CI)) 3550 FMF = FPCI->getFastMathFlags(); 3551 SmallVector<const Value *> Arguments(CI->arg_begin(), CI->arg_end()); 3552 IntrinsicCostAttributes CostAttrs(ID, VecTy, Arguments, VecTys, FMF, 3553 dyn_cast<IntrinsicInst>(CI)); 3554 auto IntrinsicCost = 3555 TTI->getIntrinsicInstrCost(CostAttrs, TTI::TCK_RecipThroughput); 3556 3557 auto Shape = VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>( 3558 VecTy->getNumElements())), 3559 false /*HasGlobalPred*/); 3560 Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape); 3561 auto LibCost = IntrinsicCost; 3562 if (!CI->isNoBuiltin() && VecFunc) { 3563 // Calculate the cost of the vector library call. 3564 // If the corresponding vector call is cheaper, return its cost. 3565 LibCost = TTI->getCallInstrCost(nullptr, VecTy, VecTys, 3566 TTI::TCK_RecipThroughput); 3567 } 3568 return {IntrinsicCost, LibCost}; 3569 } 3570 3571 /// Compute the cost of creating a vector of type \p VecTy containing the 3572 /// extracted values from \p VL. 3573 static InstructionCost 3574 computeExtractCost(ArrayRef<Value *> VL, FixedVectorType *VecTy, 3575 TargetTransformInfo::ShuffleKind ShuffleKind, 3576 ArrayRef<int> Mask, TargetTransformInfo &TTI) { 3577 unsigned NumOfParts = TTI.getNumberOfParts(VecTy); 3578 3579 if (ShuffleKind != TargetTransformInfo::SK_PermuteSingleSrc || !NumOfParts || 3580 VecTy->getNumElements() < NumOfParts) 3581 return TTI.getShuffleCost(ShuffleKind, VecTy, Mask); 3582 3583 bool AllConsecutive = true; 3584 unsigned EltsPerVector = VecTy->getNumElements() / NumOfParts; 3585 unsigned Idx = -1; 3586 InstructionCost Cost = 0; 3587 3588 // Process extracts in blocks of EltsPerVector to check if the source vector 3589 // operand can be re-used directly. If not, add the cost of creating a shuffle 3590 // to extract the values into a vector register. 3591 for (auto *V : VL) { 3592 ++Idx; 3593 3594 // Reached the start of a new vector registers. 3595 if (Idx % EltsPerVector == 0) { 3596 AllConsecutive = true; 3597 continue; 3598 } 3599 3600 // Check all extracts for a vector register on the target directly 3601 // extract values in order. 3602 unsigned CurrentIdx = *getExtractIndex(cast<Instruction>(V)); 3603 unsigned PrevIdx = *getExtractIndex(cast<Instruction>(VL[Idx - 1])); 3604 AllConsecutive &= PrevIdx + 1 == CurrentIdx && 3605 CurrentIdx % EltsPerVector == Idx % EltsPerVector; 3606 3607 if (AllConsecutive) 3608 continue; 3609 3610 // Skip all indices, except for the last index per vector block. 3611 if ((Idx + 1) % EltsPerVector != 0 && Idx + 1 != VL.size()) 3612 continue; 3613 3614 // If we have a series of extracts which are not consecutive and hence 3615 // cannot re-use the source vector register directly, compute the shuffle 3616 // cost to extract the a vector with EltsPerVector elements. 3617 Cost += TTI.getShuffleCost( 3618 TargetTransformInfo::SK_PermuteSingleSrc, 3619 FixedVectorType::get(VecTy->getElementType(), EltsPerVector)); 3620 } 3621 return Cost; 3622 } 3623 3624 /// Shuffles \p Mask in accordance with the given \p SubMask. 3625 static void addMask(SmallVectorImpl<int> &Mask, ArrayRef<int> SubMask) { 3626 if (SubMask.empty()) 3627 return; 3628 if (Mask.empty()) { 3629 Mask.append(SubMask.begin(), SubMask.end()); 3630 return; 3631 } 3632 SmallVector<int, 4> NewMask(SubMask.size(), SubMask.size()); 3633 int TermValue = std::min(Mask.size(), SubMask.size()); 3634 for (int I = 0, E = SubMask.size(); I < E; ++I) { 3635 if (SubMask[I] >= TermValue || SubMask[I] == UndefMaskElem || 3636 Mask[SubMask[I]] >= TermValue) { 3637 NewMask[I] = UndefMaskElem; 3638 continue; 3639 } 3640 NewMask[I] = Mask[SubMask[I]]; 3641 } 3642 Mask.swap(NewMask); 3643 } 3644 3645 InstructionCost BoUpSLP::getEntryCost(const TreeEntry *E, 3646 ArrayRef<Value *> VectorizedVals) { 3647 ArrayRef<Value*> VL = E->Scalars; 3648 3649 Type *ScalarTy = VL[0]->getType(); 3650 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 3651 ScalarTy = SI->getValueOperand()->getType(); 3652 else if (CmpInst *CI = dyn_cast<CmpInst>(VL[0])) 3653 ScalarTy = CI->getOperand(0)->getType(); 3654 else if (auto *IE = dyn_cast<InsertElementInst>(VL[0])) 3655 ScalarTy = IE->getOperand(1)->getType(); 3656 auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); 3657 auto *FinalVecTy = VecTy; 3658 TTI::TargetCostKind CostKind = TTI::TCK_RecipThroughput; 3659 3660 // If we have computed a smaller type for the expression, update VecTy so 3661 // that the costs will be accurate. 3662 if (MinBWs.count(VL[0])) 3663 VecTy = FixedVectorType::get( 3664 IntegerType::get(F->getContext(), MinBWs[VL[0]].first), VL.size()); 3665 3666 unsigned ReuseShuffleNumbers = E->ReuseShuffleIndices.size(); 3667 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 3668 if (NeedToShuffleReuses) 3669 FinalVecTy = 3670 FixedVectorType::get(VecTy->getElementType(), ReuseShuffleNumbers); 3671 // FIXME: it tries to fix a problem with MSVC buildbots. 3672 TargetTransformInfo &TTIRef = *TTI; 3673 auto &&AdjustExtractsCost = [this, &TTIRef, CostKind, VL, VecTy, 3674 VectorizedVals](InstructionCost &Cost, 3675 bool IsGather) { 3676 DenseMap<Value *, int> ExtractVectorsTys; 3677 for (auto *V : VL) { 3678 // If all users of instruction are going to be vectorized and this 3679 // instruction itself is not going to be vectorized, consider this 3680 // instruction as dead and remove its cost from the final cost of the 3681 // vectorized tree. 3682 if (!areAllUsersVectorized(cast<Instruction>(V), VectorizedVals) || 3683 (IsGather && ScalarToTreeEntry.count(V))) 3684 continue; 3685 auto *EE = cast<ExtractElementInst>(V); 3686 unsigned Idx = *getExtractIndex(EE); 3687 if (TTIRef.getNumberOfParts(VecTy) != 3688 TTIRef.getNumberOfParts(EE->getVectorOperandType())) { 3689 auto It = 3690 ExtractVectorsTys.try_emplace(EE->getVectorOperand(), Idx).first; 3691 It->getSecond() = std::min<int>(It->second, Idx); 3692 } 3693 // Take credit for instruction that will become dead. 3694 if (EE->hasOneUse()) { 3695 Instruction *Ext = EE->user_back(); 3696 if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) && 3697 all_of(Ext->users(), 3698 [](User *U) { return isa<GetElementPtrInst>(U); })) { 3699 // Use getExtractWithExtendCost() to calculate the cost of 3700 // extractelement/ext pair. 3701 Cost -= 3702 TTIRef.getExtractWithExtendCost(Ext->getOpcode(), Ext->getType(), 3703 EE->getVectorOperandType(), Idx); 3704 // Add back the cost of s|zext which is subtracted separately. 3705 Cost += TTIRef.getCastInstrCost( 3706 Ext->getOpcode(), Ext->getType(), EE->getType(), 3707 TTI::getCastContextHint(Ext), CostKind, Ext); 3708 continue; 3709 } 3710 } 3711 Cost -= TTIRef.getVectorInstrCost(Instruction::ExtractElement, 3712 EE->getVectorOperandType(), Idx); 3713 } 3714 // Add a cost for subvector extracts/inserts if required. 3715 for (const auto &Data : ExtractVectorsTys) { 3716 auto *EEVTy = cast<FixedVectorType>(Data.first->getType()); 3717 unsigned NumElts = VecTy->getNumElements(); 3718 if (TTIRef.getNumberOfParts(EEVTy) > TTIRef.getNumberOfParts(VecTy)) { 3719 unsigned Idx = (Data.second / NumElts) * NumElts; 3720 unsigned EENumElts = EEVTy->getNumElements(); 3721 if (Idx + NumElts <= EENumElts) { 3722 Cost += 3723 TTIRef.getShuffleCost(TargetTransformInfo::SK_ExtractSubvector, 3724 EEVTy, None, Idx, VecTy); 3725 } else { 3726 // Need to round up the subvector type vectorization factor to avoid a 3727 // crash in cost model functions. Make SubVT so that Idx + VF of SubVT 3728 // <= EENumElts. 3729 auto *SubVT = 3730 FixedVectorType::get(VecTy->getElementType(), EENumElts - Idx); 3731 Cost += 3732 TTIRef.getShuffleCost(TargetTransformInfo::SK_ExtractSubvector, 3733 EEVTy, None, Idx, SubVT); 3734 } 3735 } else { 3736 Cost += TTIRef.getShuffleCost(TargetTransformInfo::SK_InsertSubvector, 3737 VecTy, None, 0, EEVTy); 3738 } 3739 } 3740 }; 3741 if (E->State == TreeEntry::NeedToGather) { 3742 if (allConstant(VL)) 3743 return 0; 3744 if (isa<InsertElementInst>(VL[0])) 3745 return InstructionCost::getInvalid(); 3746 SmallVector<int> Mask; 3747 SmallVector<const TreeEntry *> Entries; 3748 Optional<TargetTransformInfo::ShuffleKind> Shuffle = 3749 isGatherShuffledEntry(E, Mask, Entries); 3750 if (Shuffle.hasValue()) { 3751 InstructionCost GatherCost = 0; 3752 if (ShuffleVectorInst::isIdentityMask(Mask)) { 3753 // Perfect match in the graph, will reuse the previously vectorized 3754 // node. Cost is 0. 3755 LLVM_DEBUG( 3756 dbgs() 3757 << "SLP: perfect diamond match for gather bundle that starts with " 3758 << *VL.front() << ".\n"); 3759 if (NeedToShuffleReuses) 3760 GatherCost = 3761 TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, 3762 FinalVecTy, E->ReuseShuffleIndices); 3763 } else { 3764 LLVM_DEBUG(dbgs() << "SLP: shuffled " << Entries.size() 3765 << " entries for bundle that starts with " 3766 << *VL.front() << ".\n"); 3767 // Detected that instead of gather we can emit a shuffle of single/two 3768 // previously vectorized nodes. Add the cost of the permutation rather 3769 // than gather. 3770 ::addMask(Mask, E->ReuseShuffleIndices); 3771 GatherCost = TTI->getShuffleCost(*Shuffle, FinalVecTy, Mask); 3772 } 3773 return GatherCost; 3774 } 3775 if (isSplat(VL)) { 3776 // Found the broadcasting of the single scalar, calculate the cost as the 3777 // broadcast. 3778 return TTI->getShuffleCost(TargetTransformInfo::SK_Broadcast, VecTy); 3779 } 3780 if (E->getOpcode() == Instruction::ExtractElement && allSameType(VL) && 3781 allSameBlock(VL) && 3782 !isa<ScalableVectorType>( 3783 cast<ExtractElementInst>(E->getMainOp())->getVectorOperandType())) { 3784 // Check that gather of extractelements can be represented as just a 3785 // shuffle of a single/two vectors the scalars are extracted from. 3786 SmallVector<int> Mask; 3787 Optional<TargetTransformInfo::ShuffleKind> ShuffleKind = 3788 isShuffle(VL, Mask); 3789 if (ShuffleKind.hasValue()) { 3790 // Found the bunch of extractelement instructions that must be gathered 3791 // into a vector and can be represented as a permutation elements in a 3792 // single input vector or of 2 input vectors. 3793 InstructionCost Cost = 3794 computeExtractCost(VL, VecTy, *ShuffleKind, Mask, *TTI); 3795 AdjustExtractsCost(Cost, /*IsGather=*/true); 3796 if (NeedToShuffleReuses) 3797 Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, 3798 FinalVecTy, E->ReuseShuffleIndices); 3799 return Cost; 3800 } 3801 } 3802 InstructionCost ReuseShuffleCost = 0; 3803 if (NeedToShuffleReuses) 3804 ReuseShuffleCost = TTI->getShuffleCost( 3805 TTI::SK_PermuteSingleSrc, FinalVecTy, E->ReuseShuffleIndices); 3806 return ReuseShuffleCost + getGatherCost(VL); 3807 } 3808 InstructionCost CommonCost = 0; 3809 SmallVector<int> Mask; 3810 if (!E->ReorderIndices.empty()) { 3811 SmallVector<int> NewMask; 3812 if (E->getOpcode() == Instruction::Store) { 3813 // For stores the order is actually a mask. 3814 NewMask.resize(E->ReorderIndices.size()); 3815 copy(E->ReorderIndices, NewMask.begin()); 3816 } else { 3817 inversePermutation(E->ReorderIndices, NewMask); 3818 } 3819 ::addMask(Mask, NewMask); 3820 } 3821 if (NeedToShuffleReuses) 3822 ::addMask(Mask, E->ReuseShuffleIndices); 3823 if (!Mask.empty() && !ShuffleVectorInst::isIdentityMask(Mask)) 3824 CommonCost = 3825 TTI->getShuffleCost(TTI::SK_PermuteSingleSrc, FinalVecTy, Mask); 3826 assert((E->State == TreeEntry::Vectorize || 3827 E->State == TreeEntry::ScatterVectorize) && 3828 "Unhandled state"); 3829 assert(E->getOpcode() && allSameType(VL) && allSameBlock(VL) && "Invalid VL"); 3830 Instruction *VL0 = E->getMainOp(); 3831 unsigned ShuffleOrOp = 3832 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 3833 switch (ShuffleOrOp) { 3834 case Instruction::PHI: 3835 return 0; 3836 3837 case Instruction::ExtractValue: 3838 case Instruction::ExtractElement: { 3839 // The common cost of removal ExtractElement/ExtractValue instructions + 3840 // the cost of shuffles, if required to resuffle the original vector. 3841 InstructionCost CommonCost = 0; 3842 if (NeedToShuffleReuses) { 3843 unsigned Idx = 0; 3844 for (unsigned I : E->ReuseShuffleIndices) { 3845 if (ShuffleOrOp == Instruction::ExtractElement) { 3846 auto *EE = cast<ExtractElementInst>(VL[I]); 3847 CommonCost -= TTI->getVectorInstrCost(Instruction::ExtractElement, 3848 EE->getVectorOperandType(), 3849 *getExtractIndex(EE)); 3850 } else { 3851 CommonCost -= TTI->getVectorInstrCost(Instruction::ExtractElement, 3852 VecTy, Idx); 3853 ++Idx; 3854 } 3855 } 3856 Idx = ReuseShuffleNumbers; 3857 for (Value *V : VL) { 3858 if (ShuffleOrOp == Instruction::ExtractElement) { 3859 auto *EE = cast<ExtractElementInst>(V); 3860 CommonCost += TTI->getVectorInstrCost(Instruction::ExtractElement, 3861 EE->getVectorOperandType(), 3862 *getExtractIndex(EE)); 3863 } else { 3864 --Idx; 3865 CommonCost += TTI->getVectorInstrCost(Instruction::ExtractElement, 3866 VecTy, Idx); 3867 } 3868 } 3869 } 3870 if (ShuffleOrOp == Instruction::ExtractValue) { 3871 for (unsigned I = 0, E = VL.size(); I < E; ++I) { 3872 auto *EI = cast<Instruction>(VL[I]); 3873 // Take credit for instruction that will become dead. 3874 if (EI->hasOneUse()) { 3875 Instruction *Ext = EI->user_back(); 3876 if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) && 3877 all_of(Ext->users(), 3878 [](User *U) { return isa<GetElementPtrInst>(U); })) { 3879 // Use getExtractWithExtendCost() to calculate the cost of 3880 // extractelement/ext pair. 3881 CommonCost -= TTI->getExtractWithExtendCost( 3882 Ext->getOpcode(), Ext->getType(), VecTy, I); 3883 // Add back the cost of s|zext which is subtracted separately. 3884 CommonCost += TTI->getCastInstrCost( 3885 Ext->getOpcode(), Ext->getType(), EI->getType(), 3886 TTI::getCastContextHint(Ext), CostKind, Ext); 3887 continue; 3888 } 3889 } 3890 CommonCost -= 3891 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, I); 3892 } 3893 } else { 3894 AdjustExtractsCost(CommonCost, /*IsGather=*/false); 3895 } 3896 return CommonCost; 3897 } 3898 case Instruction::InsertElement: { 3899 auto *SrcVecTy = cast<FixedVectorType>(VL0->getType()); 3900 3901 unsigned const NumElts = SrcVecTy->getNumElements(); 3902 unsigned const NumScalars = VL.size(); 3903 APInt DemandedElts = APInt::getNullValue(NumElts); 3904 // TODO: Add support for Instruction::InsertValue. 3905 unsigned Offset = UINT_MAX; 3906 bool IsIdentity = true; 3907 SmallVector<int> ShuffleMask(NumElts, UndefMaskElem); 3908 for (unsigned I = 0; I < NumScalars; ++I) { 3909 Optional<int> InsertIdx = getInsertIndex(VL[I], 0); 3910 if (!InsertIdx || *InsertIdx == UndefMaskElem) 3911 continue; 3912 unsigned Idx = *InsertIdx; 3913 DemandedElts.setBit(Idx); 3914 if (Idx < Offset) { 3915 Offset = Idx; 3916 IsIdentity &= I == 0; 3917 } else { 3918 assert(Idx >= Offset && "Failed to find vector index offset"); 3919 IsIdentity &= Idx - Offset == I; 3920 } 3921 ShuffleMask[Idx] = I; 3922 } 3923 assert(Offset < NumElts && "Failed to find vector index offset"); 3924 3925 InstructionCost Cost = 0; 3926 Cost -= TTI->getScalarizationOverhead(SrcVecTy, DemandedElts, 3927 /*Insert*/ true, /*Extract*/ false); 3928 3929 if (IsIdentity && NumElts != NumScalars && Offset % NumScalars != 0) { 3930 // FIXME: Replace with SK_InsertSubvector once it is properly supported. 3931 unsigned Sz = PowerOf2Ceil(Offset + NumScalars); 3932 Cost += TTI->getShuffleCost( 3933 TargetTransformInfo::SK_PermuteSingleSrc, 3934 FixedVectorType::get(SrcVecTy->getElementType(), Sz)); 3935 } else if (!IsIdentity) { 3936 Cost += TTI->getShuffleCost(TTI::SK_PermuteSingleSrc, SrcVecTy, 3937 ShuffleMask); 3938 } 3939 3940 return Cost; 3941 } 3942 case Instruction::ZExt: 3943 case Instruction::SExt: 3944 case Instruction::FPToUI: 3945 case Instruction::FPToSI: 3946 case Instruction::FPExt: 3947 case Instruction::PtrToInt: 3948 case Instruction::IntToPtr: 3949 case Instruction::SIToFP: 3950 case Instruction::UIToFP: 3951 case Instruction::Trunc: 3952 case Instruction::FPTrunc: 3953 case Instruction::BitCast: { 3954 Type *SrcTy = VL0->getOperand(0)->getType(); 3955 InstructionCost ScalarEltCost = 3956 TTI->getCastInstrCost(E->getOpcode(), ScalarTy, SrcTy, 3957 TTI::getCastContextHint(VL0), CostKind, VL0); 3958 if (NeedToShuffleReuses) { 3959 CommonCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3960 } 3961 3962 // Calculate the cost of this instruction. 3963 InstructionCost ScalarCost = VL.size() * ScalarEltCost; 3964 3965 auto *SrcVecTy = FixedVectorType::get(SrcTy, VL.size()); 3966 InstructionCost VecCost = 0; 3967 // Check if the values are candidates to demote. 3968 if (!MinBWs.count(VL0) || VecTy != SrcVecTy) { 3969 VecCost = CommonCost + TTI->getCastInstrCost( 3970 E->getOpcode(), VecTy, SrcVecTy, 3971 TTI::getCastContextHint(VL0), CostKind, VL0); 3972 } 3973 LLVM_DEBUG(dumpTreeCosts(E, CommonCost, VecCost, ScalarCost)); 3974 return VecCost - ScalarCost; 3975 } 3976 case Instruction::FCmp: 3977 case Instruction::ICmp: 3978 case Instruction::Select: { 3979 // Calculate the cost of this instruction. 3980 InstructionCost ScalarEltCost = 3981 TTI->getCmpSelInstrCost(E->getOpcode(), ScalarTy, Builder.getInt1Ty(), 3982 CmpInst::BAD_ICMP_PREDICATE, CostKind, VL0); 3983 if (NeedToShuffleReuses) { 3984 CommonCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3985 } 3986 auto *MaskTy = FixedVectorType::get(Builder.getInt1Ty(), VL.size()); 3987 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3988 3989 // Check if all entries in VL are either compares or selects with compares 3990 // as condition that have the same predicates. 3991 CmpInst::Predicate VecPred = CmpInst::BAD_ICMP_PREDICATE; 3992 bool First = true; 3993 for (auto *V : VL) { 3994 CmpInst::Predicate CurrentPred; 3995 auto MatchCmp = m_Cmp(CurrentPred, m_Value(), m_Value()); 3996 if ((!match(V, m_Select(MatchCmp, m_Value(), m_Value())) && 3997 !match(V, MatchCmp)) || 3998 (!First && VecPred != CurrentPred)) { 3999 VecPred = CmpInst::BAD_ICMP_PREDICATE; 4000 break; 4001 } 4002 First = false; 4003 VecPred = CurrentPred; 4004 } 4005 4006 InstructionCost VecCost = TTI->getCmpSelInstrCost( 4007 E->getOpcode(), VecTy, MaskTy, VecPred, CostKind, VL0); 4008 // Check if it is possible and profitable to use min/max for selects in 4009 // VL. 4010 // 4011 auto IntrinsicAndUse = canConvertToMinOrMaxIntrinsic(VL); 4012 if (IntrinsicAndUse.first != Intrinsic::not_intrinsic) { 4013 IntrinsicCostAttributes CostAttrs(IntrinsicAndUse.first, VecTy, 4014 {VecTy, VecTy}); 4015 InstructionCost IntrinsicCost = 4016 TTI->getIntrinsicInstrCost(CostAttrs, CostKind); 4017 // If the selects are the only uses of the compares, they will be dead 4018 // and we can adjust the cost by removing their cost. 4019 if (IntrinsicAndUse.second) 4020 IntrinsicCost -= 4021 TTI->getCmpSelInstrCost(Instruction::ICmp, VecTy, MaskTy, 4022 CmpInst::BAD_ICMP_PREDICATE, CostKind); 4023 VecCost = std::min(VecCost, IntrinsicCost); 4024 } 4025 LLVM_DEBUG(dumpTreeCosts(E, CommonCost, VecCost, ScalarCost)); 4026 return CommonCost + VecCost - ScalarCost; 4027 } 4028 case Instruction::FNeg: 4029 case Instruction::Add: 4030 case Instruction::FAdd: 4031 case Instruction::Sub: 4032 case Instruction::FSub: 4033 case Instruction::Mul: 4034 case Instruction::FMul: 4035 case Instruction::UDiv: 4036 case Instruction::SDiv: 4037 case Instruction::FDiv: 4038 case Instruction::URem: 4039 case Instruction::SRem: 4040 case Instruction::FRem: 4041 case Instruction::Shl: 4042 case Instruction::LShr: 4043 case Instruction::AShr: 4044 case Instruction::And: 4045 case Instruction::Or: 4046 case Instruction::Xor: { 4047 // Certain instructions can be cheaper to vectorize if they have a 4048 // constant second vector operand. 4049 TargetTransformInfo::OperandValueKind Op1VK = 4050 TargetTransformInfo::OK_AnyValue; 4051 TargetTransformInfo::OperandValueKind Op2VK = 4052 TargetTransformInfo::OK_UniformConstantValue; 4053 TargetTransformInfo::OperandValueProperties Op1VP = 4054 TargetTransformInfo::OP_None; 4055 TargetTransformInfo::OperandValueProperties Op2VP = 4056 TargetTransformInfo::OP_PowerOf2; 4057 4058 // If all operands are exactly the same ConstantInt then set the 4059 // operand kind to OK_UniformConstantValue. 4060 // If instead not all operands are constants, then set the operand kind 4061 // to OK_AnyValue. If all operands are constants but not the same, 4062 // then set the operand kind to OK_NonUniformConstantValue. 4063 ConstantInt *CInt0 = nullptr; 4064 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 4065 const Instruction *I = cast<Instruction>(VL[i]); 4066 unsigned OpIdx = isa<BinaryOperator>(I) ? 1 : 0; 4067 ConstantInt *CInt = dyn_cast<ConstantInt>(I->getOperand(OpIdx)); 4068 if (!CInt) { 4069 Op2VK = TargetTransformInfo::OK_AnyValue; 4070 Op2VP = TargetTransformInfo::OP_None; 4071 break; 4072 } 4073 if (Op2VP == TargetTransformInfo::OP_PowerOf2 && 4074 !CInt->getValue().isPowerOf2()) 4075 Op2VP = TargetTransformInfo::OP_None; 4076 if (i == 0) { 4077 CInt0 = CInt; 4078 continue; 4079 } 4080 if (CInt0 != CInt) 4081 Op2VK = TargetTransformInfo::OK_NonUniformConstantValue; 4082 } 4083 4084 SmallVector<const Value *, 4> Operands(VL0->operand_values()); 4085 InstructionCost ScalarEltCost = 4086 TTI->getArithmeticInstrCost(E->getOpcode(), ScalarTy, CostKind, Op1VK, 4087 Op2VK, Op1VP, Op2VP, Operands, VL0); 4088 if (NeedToShuffleReuses) { 4089 CommonCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 4090 } 4091 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 4092 InstructionCost VecCost = 4093 TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind, Op1VK, 4094 Op2VK, Op1VP, Op2VP, Operands, VL0); 4095 LLVM_DEBUG(dumpTreeCosts(E, CommonCost, VecCost, ScalarCost)); 4096 return CommonCost + VecCost - ScalarCost; 4097 } 4098 case Instruction::GetElementPtr: { 4099 TargetTransformInfo::OperandValueKind Op1VK = 4100 TargetTransformInfo::OK_AnyValue; 4101 TargetTransformInfo::OperandValueKind Op2VK = 4102 TargetTransformInfo::OK_UniformConstantValue; 4103 4104 InstructionCost ScalarEltCost = TTI->getArithmeticInstrCost( 4105 Instruction::Add, ScalarTy, CostKind, Op1VK, Op2VK); 4106 if (NeedToShuffleReuses) { 4107 CommonCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 4108 } 4109 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 4110 InstructionCost VecCost = TTI->getArithmeticInstrCost( 4111 Instruction::Add, VecTy, CostKind, Op1VK, Op2VK); 4112 LLVM_DEBUG(dumpTreeCosts(E, CommonCost, VecCost, ScalarCost)); 4113 return CommonCost + VecCost - ScalarCost; 4114 } 4115 case Instruction::Load: { 4116 // Cost of wide load - cost of scalar loads. 4117 Align Alignment = cast<LoadInst>(VL0)->getAlign(); 4118 InstructionCost ScalarEltCost = TTI->getMemoryOpCost( 4119 Instruction::Load, ScalarTy, Alignment, 0, CostKind, VL0); 4120 if (NeedToShuffleReuses) { 4121 CommonCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 4122 } 4123 InstructionCost ScalarLdCost = VecTy->getNumElements() * ScalarEltCost; 4124 InstructionCost VecLdCost; 4125 if (E->State == TreeEntry::Vectorize) { 4126 VecLdCost = TTI->getMemoryOpCost(Instruction::Load, VecTy, Alignment, 0, 4127 CostKind, VL0); 4128 } else { 4129 assert(E->State == TreeEntry::ScatterVectorize && "Unknown EntryState"); 4130 Align CommonAlignment = Alignment; 4131 for (Value *V : VL) 4132 CommonAlignment = 4133 commonAlignment(CommonAlignment, cast<LoadInst>(V)->getAlign()); 4134 VecLdCost = TTI->getGatherScatterOpCost( 4135 Instruction::Load, VecTy, cast<LoadInst>(VL0)->getPointerOperand(), 4136 /*VariableMask=*/false, Alignment, CostKind, VL0); 4137 } 4138 LLVM_DEBUG(dumpTreeCosts(E, CommonCost, VecLdCost, ScalarLdCost)); 4139 return CommonCost + VecLdCost - ScalarLdCost; 4140 } 4141 case Instruction::Store: { 4142 // We know that we can merge the stores. Calculate the cost. 4143 bool IsReorder = !E->ReorderIndices.empty(); 4144 auto *SI = 4145 cast<StoreInst>(IsReorder ? VL[E->ReorderIndices.front()] : VL0); 4146 Align Alignment = SI->getAlign(); 4147 InstructionCost ScalarEltCost = TTI->getMemoryOpCost( 4148 Instruction::Store, ScalarTy, Alignment, 0, CostKind, VL0); 4149 InstructionCost ScalarStCost = VecTy->getNumElements() * ScalarEltCost; 4150 InstructionCost VecStCost = TTI->getMemoryOpCost( 4151 Instruction::Store, VecTy, Alignment, 0, CostKind, VL0); 4152 LLVM_DEBUG(dumpTreeCosts(E, CommonCost, VecStCost, ScalarStCost)); 4153 return CommonCost + VecStCost - ScalarStCost; 4154 } 4155 case Instruction::Call: { 4156 CallInst *CI = cast<CallInst>(VL0); 4157 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 4158 4159 // Calculate the cost of the scalar and vector calls. 4160 IntrinsicCostAttributes CostAttrs(ID, *CI, 1); 4161 InstructionCost ScalarEltCost = 4162 TTI->getIntrinsicInstrCost(CostAttrs, CostKind); 4163 if (NeedToShuffleReuses) { 4164 CommonCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 4165 } 4166 InstructionCost ScalarCallCost = VecTy->getNumElements() * ScalarEltCost; 4167 4168 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 4169 InstructionCost VecCallCost = 4170 std::min(VecCallCosts.first, VecCallCosts.second); 4171 4172 LLVM_DEBUG(dbgs() << "SLP: Call cost " << VecCallCost - ScalarCallCost 4173 << " (" << VecCallCost << "-" << ScalarCallCost << ")" 4174 << " for " << *CI << "\n"); 4175 4176 return CommonCost + VecCallCost - ScalarCallCost; 4177 } 4178 case Instruction::ShuffleVector: { 4179 assert(E->isAltShuffle() && 4180 ((Instruction::isBinaryOp(E->getOpcode()) && 4181 Instruction::isBinaryOp(E->getAltOpcode())) || 4182 (Instruction::isCast(E->getOpcode()) && 4183 Instruction::isCast(E->getAltOpcode()))) && 4184 "Invalid Shuffle Vector Operand"); 4185 InstructionCost ScalarCost = 0; 4186 if (NeedToShuffleReuses) { 4187 for (unsigned Idx : E->ReuseShuffleIndices) { 4188 Instruction *I = cast<Instruction>(VL[Idx]); 4189 CommonCost -= TTI->getInstructionCost(I, CostKind); 4190 } 4191 for (Value *V : VL) { 4192 Instruction *I = cast<Instruction>(V); 4193 CommonCost += TTI->getInstructionCost(I, CostKind); 4194 } 4195 } 4196 for (Value *V : VL) { 4197 Instruction *I = cast<Instruction>(V); 4198 assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode"); 4199 ScalarCost += TTI->getInstructionCost(I, CostKind); 4200 } 4201 // VecCost is equal to sum of the cost of creating 2 vectors 4202 // and the cost of creating shuffle. 4203 InstructionCost VecCost = 0; 4204 if (Instruction::isBinaryOp(E->getOpcode())) { 4205 VecCost = TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind); 4206 VecCost += TTI->getArithmeticInstrCost(E->getAltOpcode(), VecTy, 4207 CostKind); 4208 } else { 4209 Type *Src0SclTy = E->getMainOp()->getOperand(0)->getType(); 4210 Type *Src1SclTy = E->getAltOp()->getOperand(0)->getType(); 4211 auto *Src0Ty = FixedVectorType::get(Src0SclTy, VL.size()); 4212 auto *Src1Ty = FixedVectorType::get(Src1SclTy, VL.size()); 4213 VecCost = TTI->getCastInstrCost(E->getOpcode(), VecTy, Src0Ty, 4214 TTI::CastContextHint::None, CostKind); 4215 VecCost += TTI->getCastInstrCost(E->getAltOpcode(), VecTy, Src1Ty, 4216 TTI::CastContextHint::None, CostKind); 4217 } 4218 4219 SmallVector<int> Mask(E->Scalars.size()); 4220 for (unsigned I = 0, End = E->Scalars.size(); I < End; ++I) { 4221 auto *OpInst = cast<Instruction>(E->Scalars[I]); 4222 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 4223 Mask[I] = I + (OpInst->getOpcode() == E->getAltOpcode() ? End : 0); 4224 } 4225 VecCost += 4226 TTI->getShuffleCost(TargetTransformInfo::SK_Select, VecTy, Mask, 0); 4227 LLVM_DEBUG(dumpTreeCosts(E, CommonCost, VecCost, ScalarCost)); 4228 return CommonCost + VecCost - ScalarCost; 4229 } 4230 default: 4231 llvm_unreachable("Unknown instruction"); 4232 } 4233 } 4234 4235 bool BoUpSLP::isFullyVectorizableTinyTree() const { 4236 LLVM_DEBUG(dbgs() << "SLP: Check whether the tree with height " 4237 << VectorizableTree.size() << " is fully vectorizable .\n"); 4238 4239 // We only handle trees of heights 1 and 2. 4240 if (VectorizableTree.size() == 1 && 4241 VectorizableTree[0]->State == TreeEntry::Vectorize) 4242 return true; 4243 4244 if (VectorizableTree.size() != 2) 4245 return false; 4246 4247 // Handle splat and all-constants stores. Also try to vectorize tiny trees 4248 // with the second gather nodes if they have less scalar operands rather than 4249 // the initial tree element (may be profitable to shuffle the second gather) 4250 // or they are extractelements, which form shuffle. 4251 SmallVector<int> Mask; 4252 if (VectorizableTree[0]->State == TreeEntry::Vectorize && 4253 (allConstant(VectorizableTree[1]->Scalars) || 4254 isSplat(VectorizableTree[1]->Scalars) || 4255 (VectorizableTree[1]->State == TreeEntry::NeedToGather && 4256 VectorizableTree[1]->Scalars.size() < 4257 VectorizableTree[0]->Scalars.size()) || 4258 (VectorizableTree[1]->State == TreeEntry::NeedToGather && 4259 VectorizableTree[1]->getOpcode() == Instruction::ExtractElement && 4260 isShuffle(VectorizableTree[1]->Scalars, Mask)))) 4261 return true; 4262 4263 // Gathering cost would be too much for tiny trees. 4264 if (VectorizableTree[0]->State == TreeEntry::NeedToGather || 4265 VectorizableTree[1]->State == TreeEntry::NeedToGather) 4266 return false; 4267 4268 return true; 4269 } 4270 4271 static bool isLoadCombineCandidateImpl(Value *Root, unsigned NumElts, 4272 TargetTransformInfo *TTI, 4273 bool MustMatchOrInst) { 4274 // Look past the root to find a source value. Arbitrarily follow the 4275 // path through operand 0 of any 'or'. Also, peek through optional 4276 // shift-left-by-multiple-of-8-bits. 4277 Value *ZextLoad = Root; 4278 const APInt *ShAmtC; 4279 bool FoundOr = false; 4280 while (!isa<ConstantExpr>(ZextLoad) && 4281 (match(ZextLoad, m_Or(m_Value(), m_Value())) || 4282 (match(ZextLoad, m_Shl(m_Value(), m_APInt(ShAmtC))) && 4283 ShAmtC->urem(8) == 0))) { 4284 auto *BinOp = cast<BinaryOperator>(ZextLoad); 4285 ZextLoad = BinOp->getOperand(0); 4286 if (BinOp->getOpcode() == Instruction::Or) 4287 FoundOr = true; 4288 } 4289 // Check if the input is an extended load of the required or/shift expression. 4290 Value *LoadPtr; 4291 if ((MustMatchOrInst && !FoundOr) || ZextLoad == Root || 4292 !match(ZextLoad, m_ZExt(m_Load(m_Value(LoadPtr))))) 4293 return false; 4294 4295 // Require that the total load bit width is a legal integer type. 4296 // For example, <8 x i8> --> i64 is a legal integer on a 64-bit target. 4297 // But <16 x i8> --> i128 is not, so the backend probably can't reduce it. 4298 Type *SrcTy = LoadPtr->getType()->getPointerElementType(); 4299 unsigned LoadBitWidth = SrcTy->getIntegerBitWidth() * NumElts; 4300 if (!TTI->isTypeLegal(IntegerType::get(Root->getContext(), LoadBitWidth))) 4301 return false; 4302 4303 // Everything matched - assume that we can fold the whole sequence using 4304 // load combining. 4305 LLVM_DEBUG(dbgs() << "SLP: Assume load combining for tree starting at " 4306 << *(cast<Instruction>(Root)) << "\n"); 4307 4308 return true; 4309 } 4310 4311 bool BoUpSLP::isLoadCombineReductionCandidate(RecurKind RdxKind) const { 4312 if (RdxKind != RecurKind::Or) 4313 return false; 4314 4315 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 4316 Value *FirstReduced = VectorizableTree[0]->Scalars[0]; 4317 return isLoadCombineCandidateImpl(FirstReduced, NumElts, TTI, 4318 /* MatchOr */ false); 4319 } 4320 4321 bool BoUpSLP::isLoadCombineCandidate() const { 4322 // Peek through a final sequence of stores and check if all operations are 4323 // likely to be load-combined. 4324 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 4325 for (Value *Scalar : VectorizableTree[0]->Scalars) { 4326 Value *X; 4327 if (!match(Scalar, m_Store(m_Value(X), m_Value())) || 4328 !isLoadCombineCandidateImpl(X, NumElts, TTI, /* MatchOr */ true)) 4329 return false; 4330 } 4331 return true; 4332 } 4333 4334 bool BoUpSLP::isTreeTinyAndNotFullyVectorizable() const { 4335 // No need to vectorize inserts of gathered values. 4336 if (VectorizableTree.size() == 2 && 4337 isa<InsertElementInst>(VectorizableTree[0]->Scalars[0]) && 4338 VectorizableTree[1]->State == TreeEntry::NeedToGather) 4339 return true; 4340 4341 // We can vectorize the tree if its size is greater than or equal to the 4342 // minimum size specified by the MinTreeSize command line option. 4343 if (VectorizableTree.size() >= MinTreeSize) 4344 return false; 4345 4346 // If we have a tiny tree (a tree whose size is less than MinTreeSize), we 4347 // can vectorize it if we can prove it fully vectorizable. 4348 if (isFullyVectorizableTinyTree()) 4349 return false; 4350 4351 assert(VectorizableTree.empty() 4352 ? ExternalUses.empty() 4353 : true && "We shouldn't have any external users"); 4354 4355 // Otherwise, we can't vectorize the tree. It is both tiny and not fully 4356 // vectorizable. 4357 return true; 4358 } 4359 4360 InstructionCost BoUpSLP::getSpillCost() const { 4361 // Walk from the bottom of the tree to the top, tracking which values are 4362 // live. When we see a call instruction that is not part of our tree, 4363 // query TTI to see if there is a cost to keeping values live over it 4364 // (for example, if spills and fills are required). 4365 unsigned BundleWidth = VectorizableTree.front()->Scalars.size(); 4366 InstructionCost Cost = 0; 4367 4368 SmallPtrSet<Instruction*, 4> LiveValues; 4369 Instruction *PrevInst = nullptr; 4370 4371 // The entries in VectorizableTree are not necessarily ordered by their 4372 // position in basic blocks. Collect them and order them by dominance so later 4373 // instructions are guaranteed to be visited first. For instructions in 4374 // different basic blocks, we only scan to the beginning of the block, so 4375 // their order does not matter, as long as all instructions in a basic block 4376 // are grouped together. Using dominance ensures a deterministic order. 4377 SmallVector<Instruction *, 16> OrderedScalars; 4378 for (const auto &TEPtr : VectorizableTree) { 4379 Instruction *Inst = dyn_cast<Instruction>(TEPtr->Scalars[0]); 4380 if (!Inst) 4381 continue; 4382 OrderedScalars.push_back(Inst); 4383 } 4384 llvm::sort(OrderedScalars, [&](Instruction *A, Instruction *B) { 4385 auto *NodeA = DT->getNode(A->getParent()); 4386 auto *NodeB = DT->getNode(B->getParent()); 4387 assert(NodeA && "Should only process reachable instructions"); 4388 assert(NodeB && "Should only process reachable instructions"); 4389 assert((NodeA == NodeB) == (NodeA->getDFSNumIn() == NodeB->getDFSNumIn()) && 4390 "Different nodes should have different DFS numbers"); 4391 if (NodeA != NodeB) 4392 return NodeA->getDFSNumIn() < NodeB->getDFSNumIn(); 4393 return B->comesBefore(A); 4394 }); 4395 4396 for (Instruction *Inst : OrderedScalars) { 4397 if (!PrevInst) { 4398 PrevInst = Inst; 4399 continue; 4400 } 4401 4402 // Update LiveValues. 4403 LiveValues.erase(PrevInst); 4404 for (auto &J : PrevInst->operands()) { 4405 if (isa<Instruction>(&*J) && getTreeEntry(&*J)) 4406 LiveValues.insert(cast<Instruction>(&*J)); 4407 } 4408 4409 LLVM_DEBUG({ 4410 dbgs() << "SLP: #LV: " << LiveValues.size(); 4411 for (auto *X : LiveValues) 4412 dbgs() << " " << X->getName(); 4413 dbgs() << ", Looking at "; 4414 Inst->dump(); 4415 }); 4416 4417 // Now find the sequence of instructions between PrevInst and Inst. 4418 unsigned NumCalls = 0; 4419 BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(), 4420 PrevInstIt = 4421 PrevInst->getIterator().getReverse(); 4422 while (InstIt != PrevInstIt) { 4423 if (PrevInstIt == PrevInst->getParent()->rend()) { 4424 PrevInstIt = Inst->getParent()->rbegin(); 4425 continue; 4426 } 4427 4428 // Debug information does not impact spill cost. 4429 if ((isa<CallInst>(&*PrevInstIt) && 4430 !isa<DbgInfoIntrinsic>(&*PrevInstIt)) && 4431 &*PrevInstIt != PrevInst) 4432 NumCalls++; 4433 4434 ++PrevInstIt; 4435 } 4436 4437 if (NumCalls) { 4438 SmallVector<Type*, 4> V; 4439 for (auto *II : LiveValues) { 4440 auto *ScalarTy = II->getType(); 4441 if (auto *VectorTy = dyn_cast<FixedVectorType>(ScalarTy)) 4442 ScalarTy = VectorTy->getElementType(); 4443 V.push_back(FixedVectorType::get(ScalarTy, BundleWidth)); 4444 } 4445 Cost += NumCalls * TTI->getCostOfKeepingLiveOverCall(V); 4446 } 4447 4448 PrevInst = Inst; 4449 } 4450 4451 return Cost; 4452 } 4453 4454 InstructionCost BoUpSLP::getTreeCost(ArrayRef<Value *> VectorizedVals) { 4455 InstructionCost Cost = 0; 4456 LLVM_DEBUG(dbgs() << "SLP: Calculating cost for tree of size " 4457 << VectorizableTree.size() << ".\n"); 4458 4459 unsigned BundleWidth = VectorizableTree[0]->Scalars.size(); 4460 4461 for (unsigned I = 0, E = VectorizableTree.size(); I < E; ++I) { 4462 TreeEntry &TE = *VectorizableTree[I].get(); 4463 4464 InstructionCost C = getEntryCost(&TE, VectorizedVals); 4465 Cost += C; 4466 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C 4467 << " for bundle that starts with " << *TE.Scalars[0] 4468 << ".\n" 4469 << "SLP: Current total cost = " << Cost << "\n"); 4470 } 4471 4472 SmallPtrSet<Value *, 16> ExtractCostCalculated; 4473 InstructionCost ExtractCost = 0; 4474 SmallBitVector IsIdentity; 4475 SmallVector<unsigned> VF; 4476 SmallVector<SmallVector<int>> ShuffleMask; 4477 SmallVector<Value *> FirstUsers; 4478 SmallVector<APInt> DemandedElts; 4479 for (ExternalUser &EU : ExternalUses) { 4480 // We only add extract cost once for the same scalar. 4481 if (!ExtractCostCalculated.insert(EU.Scalar).second) 4482 continue; 4483 4484 // Uses by ephemeral values are free (because the ephemeral value will be 4485 // removed prior to code generation, and so the extraction will be 4486 // removed as well). 4487 if (EphValues.count(EU.User)) 4488 continue; 4489 4490 // No extract cost for vector "scalar" 4491 if (isa<FixedVectorType>(EU.Scalar->getType())) 4492 continue; 4493 4494 // Already counted the cost for external uses when tried to adjust the cost 4495 // for extractelements, no need to add it again. 4496 if (isa<ExtractElementInst>(EU.Scalar)) 4497 continue; 4498 4499 // If found user is an insertelement, do not calculate extract cost but try 4500 // to detect it as a final shuffled/identity match. 4501 if (EU.User && isa<InsertElementInst>(EU.User)) { 4502 if (auto *FTy = dyn_cast<FixedVectorType>(EU.User->getType())) { 4503 Optional<int> InsertIdx = getInsertIndex(EU.User, 0); 4504 if (!InsertIdx || *InsertIdx == UndefMaskElem) 4505 continue; 4506 Value *VU = EU.User; 4507 auto *It = find_if(FirstUsers, [VU](Value *V) { 4508 // Checks if 2 insertelements are from the same buildvector. 4509 if (VU->getType() != V->getType()) 4510 return false; 4511 auto *IE1 = cast<InsertElementInst>(VU); 4512 auto *IE2 = cast<InsertElementInst>(V); 4513 // Go though of insertelement instructions trying to find either VU as 4514 // the original vector for IE2 or V as the original vector for IE1. 4515 do { 4516 if (IE1 == VU || IE2 == V) 4517 return true; 4518 if (IE1) 4519 IE1 = dyn_cast<InsertElementInst>(IE1->getOperand(0)); 4520 if (IE2) 4521 IE2 = dyn_cast<InsertElementInst>(IE2->getOperand(0)); 4522 } while (IE1 || IE2); 4523 return false; 4524 }); 4525 int VecId = -1; 4526 if (It == FirstUsers.end()) { 4527 VF.push_back(FTy->getNumElements()); 4528 ShuffleMask.emplace_back(VF.back(), UndefMaskElem); 4529 FirstUsers.push_back(EU.User); 4530 DemandedElts.push_back(APInt::getNullValue(VF.back())); 4531 IsIdentity.push_back(true); 4532 VecId = FirstUsers.size() - 1; 4533 } else { 4534 VecId = std::distance(FirstUsers.begin(), It); 4535 } 4536 int Idx = *InsertIdx; 4537 ShuffleMask[VecId][Idx] = EU.Lane; 4538 IsIdentity.set(IsIdentity.test(VecId) & 4539 (EU.Lane == Idx || EU.Lane == UndefMaskElem)); 4540 DemandedElts[VecId].setBit(Idx); 4541 } 4542 } 4543 4544 // If we plan to rewrite the tree in a smaller type, we will need to sign 4545 // extend the extracted value back to the original type. Here, we account 4546 // for the extract and the added cost of the sign extend if needed. 4547 auto *VecTy = FixedVectorType::get(EU.Scalar->getType(), BundleWidth); 4548 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 4549 if (MinBWs.count(ScalarRoot)) { 4550 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 4551 auto Extend = 4552 MinBWs[ScalarRoot].second ? Instruction::SExt : Instruction::ZExt; 4553 VecTy = FixedVectorType::get(MinTy, BundleWidth); 4554 ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(), 4555 VecTy, EU.Lane); 4556 } else { 4557 ExtractCost += 4558 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, EU.Lane); 4559 } 4560 } 4561 4562 InstructionCost SpillCost = getSpillCost(); 4563 Cost += SpillCost + ExtractCost; 4564 for (int I = 0, E = FirstUsers.size(); I < E; ++I) { 4565 if (!IsIdentity.test(I)) { 4566 InstructionCost C = TTI->getShuffleCost( 4567 TTI::SK_PermuteSingleSrc, 4568 cast<FixedVectorType>(FirstUsers[I]->getType()), ShuffleMask[I]); 4569 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C 4570 << " for final shuffle of insertelement external users " 4571 << *VectorizableTree.front()->Scalars.front() << ".\n" 4572 << "SLP: Current total cost = " << Cost << "\n"); 4573 Cost += C; 4574 } 4575 unsigned VF = ShuffleMask[I].size(); 4576 for (int &Mask : ShuffleMask[I]) 4577 Mask = (Mask == UndefMaskElem ? 0 : VF) + Mask; 4578 InstructionCost C = TTI->getShuffleCost( 4579 TTI::SK_PermuteTwoSrc, cast<FixedVectorType>(FirstUsers[I]->getType()), 4580 ShuffleMask[I]); 4581 LLVM_DEBUG( 4582 dbgs() 4583 << "SLP: Adding cost " << C 4584 << " for final shuffle of vector node and external insertelement users " 4585 << *VectorizableTree.front()->Scalars.front() << ".\n" 4586 << "SLP: Current total cost = " << Cost << "\n"); 4587 Cost += C; 4588 InstructionCost InsertCost = TTI->getScalarizationOverhead( 4589 cast<FixedVectorType>(FirstUsers[I]->getType()), DemandedElts[I], 4590 /*Insert*/ true, 4591 /*Extract*/ false); 4592 Cost -= InsertCost; 4593 LLVM_DEBUG(dbgs() << "SLP: subtracting the cost " << InsertCost 4594 << " for insertelements gather.\n" 4595 << "SLP: Current total cost = " << Cost << "\n"); 4596 } 4597 4598 #ifndef NDEBUG 4599 SmallString<256> Str; 4600 { 4601 raw_svector_ostream OS(Str); 4602 OS << "SLP: Spill Cost = " << SpillCost << ".\n" 4603 << "SLP: Extract Cost = " << ExtractCost << ".\n" 4604 << "SLP: Total Cost = " << Cost << ".\n"; 4605 } 4606 LLVM_DEBUG(dbgs() << Str); 4607 if (ViewSLPTree) 4608 ViewGraph(this, "SLP" + F->getName(), false, Str); 4609 #endif 4610 4611 return Cost; 4612 } 4613 4614 Optional<TargetTransformInfo::ShuffleKind> 4615 BoUpSLP::isGatherShuffledEntry(const TreeEntry *TE, SmallVectorImpl<int> &Mask, 4616 SmallVectorImpl<const TreeEntry *> &Entries) { 4617 // TODO: currently checking only for Scalars in the tree entry, need to count 4618 // reused elements too for better cost estimation. 4619 Mask.assign(TE->Scalars.size(), UndefMaskElem); 4620 Entries.clear(); 4621 // Build a lists of values to tree entries. 4622 DenseMap<Value *, SmallPtrSet<const TreeEntry *, 4>> ValueToTEs; 4623 for (const std::unique_ptr<TreeEntry> &EntryPtr : VectorizableTree) { 4624 if (EntryPtr.get() == TE) 4625 break; 4626 if (EntryPtr->State != TreeEntry::NeedToGather) 4627 continue; 4628 for (Value *V : EntryPtr->Scalars) 4629 ValueToTEs.try_emplace(V).first->getSecond().insert(EntryPtr.get()); 4630 } 4631 // Find all tree entries used by the gathered values. If no common entries 4632 // found - not a shuffle. 4633 // Here we build a set of tree nodes for each gathered value and trying to 4634 // find the intersection between these sets. If we have at least one common 4635 // tree node for each gathered value - we have just a permutation of the 4636 // single vector. If we have 2 different sets, we're in situation where we 4637 // have a permutation of 2 input vectors. 4638 SmallVector<SmallPtrSet<const TreeEntry *, 4>> UsedTEs; 4639 DenseMap<Value *, int> UsedValuesEntry; 4640 for (Value *V : TE->Scalars) { 4641 if (isa<UndefValue>(V)) 4642 continue; 4643 // Build a list of tree entries where V is used. 4644 SmallPtrSet<const TreeEntry *, 4> VToTEs; 4645 auto It = ValueToTEs.find(V); 4646 if (It != ValueToTEs.end()) 4647 VToTEs = It->second; 4648 if (const TreeEntry *VTE = getTreeEntry(V)) 4649 VToTEs.insert(VTE); 4650 if (VToTEs.empty()) 4651 return None; 4652 if (UsedTEs.empty()) { 4653 // The first iteration, just insert the list of nodes to vector. 4654 UsedTEs.push_back(VToTEs); 4655 } else { 4656 // Need to check if there are any previously used tree nodes which use V. 4657 // If there are no such nodes, consider that we have another one input 4658 // vector. 4659 SmallPtrSet<const TreeEntry *, 4> SavedVToTEs(VToTEs); 4660 unsigned Idx = 0; 4661 for (SmallPtrSet<const TreeEntry *, 4> &Set : UsedTEs) { 4662 // Do we have a non-empty intersection of previously listed tree entries 4663 // and tree entries using current V? 4664 set_intersect(VToTEs, Set); 4665 if (!VToTEs.empty()) { 4666 // Yes, write the new subset and continue analysis for the next 4667 // scalar. 4668 Set.swap(VToTEs); 4669 break; 4670 } 4671 VToTEs = SavedVToTEs; 4672 ++Idx; 4673 } 4674 // No non-empty intersection found - need to add a second set of possible 4675 // source vectors. 4676 if (Idx == UsedTEs.size()) { 4677 // If the number of input vectors is greater than 2 - not a permutation, 4678 // fallback to the regular gather. 4679 if (UsedTEs.size() == 2) 4680 return None; 4681 UsedTEs.push_back(SavedVToTEs); 4682 Idx = UsedTEs.size() - 1; 4683 } 4684 UsedValuesEntry.try_emplace(V, Idx); 4685 } 4686 } 4687 4688 unsigned VF = 0; 4689 if (UsedTEs.size() == 1) { 4690 // Try to find the perfect match in another gather node at first. 4691 auto It = find_if(UsedTEs.front(), [TE](const TreeEntry *EntryPtr) { 4692 return EntryPtr->isSame(TE->Scalars); 4693 }); 4694 if (It != UsedTEs.front().end()) { 4695 Entries.push_back(*It); 4696 std::iota(Mask.begin(), Mask.end(), 0); 4697 return TargetTransformInfo::SK_PermuteSingleSrc; 4698 } 4699 // No perfect match, just shuffle, so choose the first tree node. 4700 Entries.push_back(*UsedTEs.front().begin()); 4701 } else { 4702 // Try to find nodes with the same vector factor. 4703 assert(UsedTEs.size() == 2 && "Expected at max 2 permuted entries."); 4704 // FIXME: Shall be replaced by GetVF function once non-power-2 patch is 4705 // landed. 4706 auto &&GetVF = [](const TreeEntry *TE) { 4707 if (!TE->ReuseShuffleIndices.empty()) 4708 return TE->ReuseShuffleIndices.size(); 4709 return TE->Scalars.size(); 4710 }; 4711 DenseMap<int, const TreeEntry *> VFToTE; 4712 for (const TreeEntry *TE : UsedTEs.front()) 4713 VFToTE.try_emplace(GetVF(TE), TE); 4714 for (const TreeEntry *TE : UsedTEs.back()) { 4715 auto It = VFToTE.find(GetVF(TE)); 4716 if (It != VFToTE.end()) { 4717 VF = It->first; 4718 Entries.push_back(It->second); 4719 Entries.push_back(TE); 4720 break; 4721 } 4722 } 4723 // No 2 source vectors with the same vector factor - give up and do regular 4724 // gather. 4725 if (Entries.empty()) 4726 return None; 4727 } 4728 4729 // Build a shuffle mask for better cost estimation and vector emission. 4730 for (int I = 0, E = TE->Scalars.size(); I < E; ++I) { 4731 Value *V = TE->Scalars[I]; 4732 if (isa<UndefValue>(V)) 4733 continue; 4734 unsigned Idx = UsedValuesEntry.lookup(V); 4735 const TreeEntry *VTE = Entries[Idx]; 4736 int FoundLane = VTE->findLaneForValue(V); 4737 Mask[I] = Idx * VF + FoundLane; 4738 // Extra check required by isSingleSourceMaskImpl function (called by 4739 // ShuffleVectorInst::isSingleSourceMask). 4740 if (Mask[I] >= 2 * E) 4741 return None; 4742 } 4743 switch (Entries.size()) { 4744 case 1: 4745 return TargetTransformInfo::SK_PermuteSingleSrc; 4746 case 2: 4747 return TargetTransformInfo::SK_PermuteTwoSrc; 4748 default: 4749 break; 4750 } 4751 return None; 4752 } 4753 4754 InstructionCost 4755 BoUpSLP::getGatherCost(FixedVectorType *Ty, 4756 const DenseSet<unsigned> &ShuffledIndices) const { 4757 unsigned NumElts = Ty->getNumElements(); 4758 APInt DemandedElts = APInt::getNullValue(NumElts); 4759 for (unsigned I = 0; I < NumElts; ++I) 4760 if (!ShuffledIndices.count(I)) 4761 DemandedElts.setBit(I); 4762 InstructionCost Cost = 4763 TTI->getScalarizationOverhead(Ty, DemandedElts, /*Insert*/ true, 4764 /*Extract*/ false); 4765 if (!ShuffledIndices.empty()) 4766 Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, Ty); 4767 return Cost; 4768 } 4769 4770 InstructionCost BoUpSLP::getGatherCost(ArrayRef<Value *> VL) const { 4771 // Find the type of the operands in VL. 4772 Type *ScalarTy = VL[0]->getType(); 4773 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 4774 ScalarTy = SI->getValueOperand()->getType(); 4775 auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); 4776 // Find the cost of inserting/extracting values from the vector. 4777 // Check if the same elements are inserted several times and count them as 4778 // shuffle candidates. 4779 DenseSet<unsigned> ShuffledElements; 4780 DenseSet<Value *> UniqueElements; 4781 // Iterate in reverse order to consider insert elements with the high cost. 4782 for (unsigned I = VL.size(); I > 0; --I) { 4783 unsigned Idx = I - 1; 4784 if (isConstant(VL[Idx])) 4785 continue; 4786 if (!UniqueElements.insert(VL[Idx]).second) 4787 ShuffledElements.insert(Idx); 4788 } 4789 return getGatherCost(VecTy, ShuffledElements); 4790 } 4791 4792 // Perform operand reordering on the instructions in VL and return the reordered 4793 // operands in Left and Right. 4794 void BoUpSLP::reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 4795 SmallVectorImpl<Value *> &Left, 4796 SmallVectorImpl<Value *> &Right, 4797 const DataLayout &DL, 4798 ScalarEvolution &SE, 4799 const BoUpSLP &R) { 4800 if (VL.empty()) 4801 return; 4802 VLOperands Ops(VL, DL, SE, R); 4803 // Reorder the operands in place. 4804 Ops.reorder(); 4805 Left = Ops.getVL(0); 4806 Right = Ops.getVL(1); 4807 } 4808 4809 void BoUpSLP::setInsertPointAfterBundle(const TreeEntry *E) { 4810 // Get the basic block this bundle is in. All instructions in the bundle 4811 // should be in this block. 4812 auto *Front = E->getMainOp(); 4813 auto *BB = Front->getParent(); 4814 assert(llvm::all_of(E->Scalars, [=](Value *V) -> bool { 4815 auto *I = cast<Instruction>(V); 4816 return !E->isOpcodeOrAlt(I) || I->getParent() == BB; 4817 })); 4818 4819 // The last instruction in the bundle in program order. 4820 Instruction *LastInst = nullptr; 4821 4822 // Find the last instruction. The common case should be that BB has been 4823 // scheduled, and the last instruction is VL.back(). So we start with 4824 // VL.back() and iterate over schedule data until we reach the end of the 4825 // bundle. The end of the bundle is marked by null ScheduleData. 4826 if (BlocksSchedules.count(BB)) { 4827 auto *Bundle = 4828 BlocksSchedules[BB]->getScheduleData(E->isOneOf(E->Scalars.back())); 4829 if (Bundle && Bundle->isPartOfBundle()) 4830 for (; Bundle; Bundle = Bundle->NextInBundle) 4831 if (Bundle->OpValue == Bundle->Inst) 4832 LastInst = Bundle->Inst; 4833 } 4834 4835 // LastInst can still be null at this point if there's either not an entry 4836 // for BB in BlocksSchedules or there's no ScheduleData available for 4837 // VL.back(). This can be the case if buildTree_rec aborts for various 4838 // reasons (e.g., the maximum recursion depth is reached, the maximum region 4839 // size is reached, etc.). ScheduleData is initialized in the scheduling 4840 // "dry-run". 4841 // 4842 // If this happens, we can still find the last instruction by brute force. We 4843 // iterate forwards from Front (inclusive) until we either see all 4844 // instructions in the bundle or reach the end of the block. If Front is the 4845 // last instruction in program order, LastInst will be set to Front, and we 4846 // will visit all the remaining instructions in the block. 4847 // 4848 // One of the reasons we exit early from buildTree_rec is to place an upper 4849 // bound on compile-time. Thus, taking an additional compile-time hit here is 4850 // not ideal. However, this should be exceedingly rare since it requires that 4851 // we both exit early from buildTree_rec and that the bundle be out-of-order 4852 // (causing us to iterate all the way to the end of the block). 4853 if (!LastInst) { 4854 SmallPtrSet<Value *, 16> Bundle(E->Scalars.begin(), E->Scalars.end()); 4855 for (auto &I : make_range(BasicBlock::iterator(Front), BB->end())) { 4856 if (Bundle.erase(&I) && E->isOpcodeOrAlt(&I)) 4857 LastInst = &I; 4858 if (Bundle.empty()) 4859 break; 4860 } 4861 } 4862 assert(LastInst && "Failed to find last instruction in bundle"); 4863 4864 // Set the insertion point after the last instruction in the bundle. Set the 4865 // debug location to Front. 4866 Builder.SetInsertPoint(BB, ++LastInst->getIterator()); 4867 Builder.SetCurrentDebugLocation(Front->getDebugLoc()); 4868 } 4869 4870 Value *BoUpSLP::gather(ArrayRef<Value *> VL) { 4871 // List of instructions/lanes from current block and/or the blocks which are 4872 // part of the current loop. These instructions will be inserted at the end to 4873 // make it possible to optimize loops and hoist invariant instructions out of 4874 // the loops body with better chances for success. 4875 SmallVector<std::pair<Value *, unsigned>, 4> PostponedInsts; 4876 SmallSet<int, 4> PostponedIndices; 4877 Loop *L = LI->getLoopFor(Builder.GetInsertBlock()); 4878 auto &&CheckPredecessor = [](BasicBlock *InstBB, BasicBlock *InsertBB) { 4879 SmallPtrSet<BasicBlock *, 4> Visited; 4880 while (InsertBB && InsertBB != InstBB && Visited.insert(InsertBB).second) 4881 InsertBB = InsertBB->getSinglePredecessor(); 4882 return InsertBB && InsertBB == InstBB; 4883 }; 4884 for (int I = 0, E = VL.size(); I < E; ++I) { 4885 if (auto *Inst = dyn_cast<Instruction>(VL[I])) 4886 if ((CheckPredecessor(Inst->getParent(), Builder.GetInsertBlock()) || 4887 getTreeEntry(Inst) || (L && (L->contains(Inst)))) && 4888 PostponedIndices.insert(I).second) 4889 PostponedInsts.emplace_back(Inst, I); 4890 } 4891 4892 auto &&CreateInsertElement = [this](Value *Vec, Value *V, unsigned Pos) { 4893 Vec = Builder.CreateInsertElement(Vec, V, Builder.getInt32(Pos)); 4894 auto *InsElt = dyn_cast<InsertElementInst>(Vec); 4895 if (!InsElt) 4896 return Vec; 4897 GatherSeq.insert(InsElt); 4898 CSEBlocks.insert(InsElt->getParent()); 4899 // Add to our 'need-to-extract' list. 4900 if (TreeEntry *Entry = getTreeEntry(V)) { 4901 // Find which lane we need to extract. 4902 unsigned FoundLane = Entry->findLaneForValue(V); 4903 ExternalUses.emplace_back(V, InsElt, FoundLane); 4904 } 4905 return Vec; 4906 }; 4907 Value *Val0 = 4908 isa<StoreInst>(VL[0]) ? cast<StoreInst>(VL[0])->getValueOperand() : VL[0]; 4909 FixedVectorType *VecTy = FixedVectorType::get(Val0->getType(), VL.size()); 4910 Value *Vec = PoisonValue::get(VecTy); 4911 SmallVector<int> NonConsts; 4912 // Insert constant values at first. 4913 for (int I = 0, E = VL.size(); I < E; ++I) { 4914 if (PostponedIndices.contains(I)) 4915 continue; 4916 if (!isConstant(VL[I])) { 4917 NonConsts.push_back(I); 4918 continue; 4919 } 4920 Vec = CreateInsertElement(Vec, VL[I], I); 4921 } 4922 // Insert non-constant values. 4923 for (int I : NonConsts) 4924 Vec = CreateInsertElement(Vec, VL[I], I); 4925 // Append instructions, which are/may be part of the loop, in the end to make 4926 // it possible to hoist non-loop-based instructions. 4927 for (const std::pair<Value *, unsigned> &Pair : PostponedInsts) 4928 Vec = CreateInsertElement(Vec, Pair.first, Pair.second); 4929 4930 return Vec; 4931 } 4932 4933 namespace { 4934 /// Merges shuffle masks and emits final shuffle instruction, if required. 4935 class ShuffleInstructionBuilder { 4936 IRBuilderBase &Builder; 4937 const unsigned VF = 0; 4938 bool IsFinalized = false; 4939 SmallVector<int, 4> Mask; 4940 4941 public: 4942 ShuffleInstructionBuilder(IRBuilderBase &Builder, unsigned VF) 4943 : Builder(Builder), VF(VF) {} 4944 4945 /// Adds a mask, inverting it before applying. 4946 void addInversedMask(ArrayRef<unsigned> SubMask) { 4947 if (SubMask.empty()) 4948 return; 4949 SmallVector<int, 4> NewMask; 4950 inversePermutation(SubMask, NewMask); 4951 addMask(NewMask); 4952 } 4953 4954 /// Functions adds masks, merging them into single one. 4955 void addMask(ArrayRef<unsigned> SubMask) { 4956 SmallVector<int, 4> NewMask(SubMask.begin(), SubMask.end()); 4957 addMask(NewMask); 4958 } 4959 4960 void addMask(ArrayRef<int> SubMask) { ::addMask(Mask, SubMask); } 4961 4962 Value *finalize(Value *V) { 4963 IsFinalized = true; 4964 unsigned ValueVF = cast<FixedVectorType>(V->getType())->getNumElements(); 4965 if (VF == ValueVF && Mask.empty()) 4966 return V; 4967 SmallVector<int, 4> NormalizedMask(VF, UndefMaskElem); 4968 std::iota(NormalizedMask.begin(), NormalizedMask.end(), 0); 4969 addMask(NormalizedMask); 4970 4971 if (VF == ValueVF && ShuffleVectorInst::isIdentityMask(Mask)) 4972 return V; 4973 return Builder.CreateShuffleVector(V, Mask, "shuffle"); 4974 } 4975 4976 ~ShuffleInstructionBuilder() { 4977 assert((IsFinalized || Mask.empty()) && 4978 "Shuffle construction must be finalized."); 4979 } 4980 }; 4981 } // namespace 4982 4983 Value *BoUpSLP::vectorizeTree(ArrayRef<Value *> VL) { 4984 unsigned VF = VL.size(); 4985 InstructionsState S = getSameOpcode(VL); 4986 if (S.getOpcode()) { 4987 if (TreeEntry *E = getTreeEntry(S.OpValue)) 4988 if (E->isSame(VL)) { 4989 Value *V = vectorizeTree(E); 4990 if (VF != cast<FixedVectorType>(V->getType())->getNumElements()) { 4991 if (!E->ReuseShuffleIndices.empty()) { 4992 // Reshuffle to get only unique values. 4993 // If some of the scalars are duplicated in the vectorization tree 4994 // entry, we do not vectorize them but instead generate a mask for 4995 // the reuses. But if there are several users of the same entry, 4996 // they may have different vectorization factors. This is especially 4997 // important for PHI nodes. In this case, we need to adapt the 4998 // resulting instruction for the user vectorization factor and have 4999 // to reshuffle it again to take only unique elements of the vector. 5000 // Without this code the function incorrectly returns reduced vector 5001 // instruction with the same elements, not with the unique ones. 5002 5003 // block: 5004 // %phi = phi <2 x > { .., %entry} {%shuffle, %block} 5005 // %2 = shuffle <2 x > %phi, %poison, <4 x > <0, 0, 1, 1> 5006 // ... (use %2) 5007 // %shuffle = shuffle <2 x> %2, poison, <2 x> {0, 2} 5008 // br %block 5009 SmallVector<int> UniqueIdxs; 5010 SmallSet<int, 4> UsedIdxs; 5011 int Pos = 0; 5012 int Sz = VL.size(); 5013 for (int Idx : E->ReuseShuffleIndices) { 5014 if (Idx != Sz && UsedIdxs.insert(Idx).second) 5015 UniqueIdxs.emplace_back(Pos); 5016 ++Pos; 5017 } 5018 assert(VF >= UsedIdxs.size() && "Expected vectorization factor " 5019 "less than original vector size."); 5020 UniqueIdxs.append(VF - UsedIdxs.size(), UndefMaskElem); 5021 V = Builder.CreateShuffleVector(V, UniqueIdxs, "shrink.shuffle"); 5022 } else { 5023 assert(VF < cast<FixedVectorType>(V->getType())->getNumElements() && 5024 "Expected vectorization factor less " 5025 "than original vector size."); 5026 SmallVector<int> UniformMask(VF, 0); 5027 std::iota(UniformMask.begin(), UniformMask.end(), 0); 5028 V = Builder.CreateShuffleVector(V, UniformMask, "shrink.shuffle"); 5029 } 5030 } 5031 return V; 5032 } 5033 } 5034 5035 // Check that every instruction appears once in this bundle. 5036 SmallVector<int> ReuseShuffleIndicies; 5037 SmallVector<Value *> UniqueValues; 5038 if (VL.size() > 2) { 5039 DenseMap<Value *, unsigned> UniquePositions; 5040 unsigned NumValues = 5041 std::distance(VL.begin(), find_if(reverse(VL), [](Value *V) { 5042 return !isa<UndefValue>(V); 5043 }).base()); 5044 VF = std::max<unsigned>(VF, PowerOf2Ceil(NumValues)); 5045 int UniqueVals = 0; 5046 bool HasUndefs = false; 5047 for (Value *V : VL.drop_back(VL.size() - VF)) { 5048 if (isa<UndefValue>(V)) { 5049 ReuseShuffleIndicies.emplace_back(UndefMaskElem); 5050 HasUndefs = true; 5051 continue; 5052 } 5053 if (isConstant(V)) { 5054 ReuseShuffleIndicies.emplace_back(UniqueValues.size()); 5055 UniqueValues.emplace_back(V); 5056 continue; 5057 } 5058 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 5059 ReuseShuffleIndicies.emplace_back(Res.first->second); 5060 if (Res.second) { 5061 UniqueValues.emplace_back(V); 5062 ++UniqueVals; 5063 } 5064 } 5065 if (HasUndefs && UniqueVals == 1 && UniqueValues.size() == 1) { 5066 // Emit pure splat vector. 5067 // FIXME: why it is not identified as an identity. 5068 unsigned NumUndefs = count(ReuseShuffleIndicies, UndefMaskElem); 5069 if (NumUndefs == ReuseShuffleIndicies.size() - 1) 5070 ReuseShuffleIndicies.append(VF - ReuseShuffleIndicies.size(), 5071 UndefMaskElem); 5072 else 5073 ReuseShuffleIndicies.assign(VF, 0); 5074 } else if (UniqueValues.size() >= VF - 1 || UniqueValues.size() <= 1) { 5075 ReuseShuffleIndicies.clear(); 5076 UniqueValues.clear(); 5077 UniqueValues.append(VL.begin(), std::next(VL.begin(), NumValues)); 5078 } 5079 UniqueValues.append(VF - UniqueValues.size(), 5080 PoisonValue::get(VL[0]->getType())); 5081 VL = UniqueValues; 5082 } 5083 5084 ShuffleInstructionBuilder ShuffleBuilder(Builder, VF); 5085 Value *Vec = gather(VL); 5086 if (!ReuseShuffleIndicies.empty()) { 5087 ShuffleBuilder.addMask(ReuseShuffleIndicies); 5088 Vec = ShuffleBuilder.finalize(Vec); 5089 if (auto *I = dyn_cast<Instruction>(Vec)) { 5090 GatherSeq.insert(I); 5091 CSEBlocks.insert(I->getParent()); 5092 } 5093 } 5094 return Vec; 5095 } 5096 5097 Value *BoUpSLP::vectorizeTree(TreeEntry *E) { 5098 IRBuilder<>::InsertPointGuard Guard(Builder); 5099 5100 if (E->VectorizedValue) { 5101 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *E->Scalars[0] << ".\n"); 5102 return E->VectorizedValue; 5103 } 5104 5105 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 5106 unsigned VF = E->Scalars.size(); 5107 if (NeedToShuffleReuses) 5108 VF = E->ReuseShuffleIndices.size(); 5109 ShuffleInstructionBuilder ShuffleBuilder(Builder, VF); 5110 if (E->State == TreeEntry::NeedToGather) { 5111 setInsertPointAfterBundle(E); 5112 Value *Vec; 5113 SmallVector<int> Mask; 5114 SmallVector<const TreeEntry *> Entries; 5115 Optional<TargetTransformInfo::ShuffleKind> Shuffle = 5116 isGatherShuffledEntry(E, Mask, Entries); 5117 if (Shuffle.hasValue()) { 5118 assert((Entries.size() == 1 || Entries.size() == 2) && 5119 "Expected shuffle of 1 or 2 entries."); 5120 Vec = Builder.CreateShuffleVector(Entries.front()->VectorizedValue, 5121 Entries.back()->VectorizedValue, Mask); 5122 } else { 5123 Vec = gather(E->Scalars); 5124 } 5125 if (NeedToShuffleReuses) { 5126 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5127 Vec = ShuffleBuilder.finalize(Vec); 5128 if (auto *I = dyn_cast<Instruction>(Vec)) { 5129 GatherSeq.insert(I); 5130 CSEBlocks.insert(I->getParent()); 5131 } 5132 } 5133 E->VectorizedValue = Vec; 5134 return Vec; 5135 } 5136 5137 assert((E->State == TreeEntry::Vectorize || 5138 E->State == TreeEntry::ScatterVectorize) && 5139 "Unhandled state"); 5140 unsigned ShuffleOrOp = 5141 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 5142 Instruction *VL0 = E->getMainOp(); 5143 Type *ScalarTy = VL0->getType(); 5144 if (auto *Store = dyn_cast<StoreInst>(VL0)) 5145 ScalarTy = Store->getValueOperand()->getType(); 5146 else if (auto *IE = dyn_cast<InsertElementInst>(VL0)) 5147 ScalarTy = IE->getOperand(1)->getType(); 5148 auto *VecTy = FixedVectorType::get(ScalarTy, E->Scalars.size()); 5149 switch (ShuffleOrOp) { 5150 case Instruction::PHI: { 5151 auto *PH = cast<PHINode>(VL0); 5152 Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI()); 5153 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 5154 PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues()); 5155 Value *V = NewPhi; 5156 if (NeedToShuffleReuses) 5157 V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle"); 5158 5159 E->VectorizedValue = V; 5160 5161 // PHINodes may have multiple entries from the same block. We want to 5162 // visit every block once. 5163 SmallPtrSet<BasicBlock*, 4> VisitedBBs; 5164 5165 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 5166 ValueList Operands; 5167 BasicBlock *IBB = PH->getIncomingBlock(i); 5168 5169 if (!VisitedBBs.insert(IBB).second) { 5170 NewPhi->addIncoming(NewPhi->getIncomingValueForBlock(IBB), IBB); 5171 continue; 5172 } 5173 5174 Builder.SetInsertPoint(IBB->getTerminator()); 5175 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 5176 Value *Vec = vectorizeTree(E->getOperand(i)); 5177 NewPhi->addIncoming(Vec, IBB); 5178 } 5179 5180 assert(NewPhi->getNumIncomingValues() == PH->getNumIncomingValues() && 5181 "Invalid number of incoming values"); 5182 return V; 5183 } 5184 5185 case Instruction::ExtractElement: { 5186 Value *V = E->getSingleOperand(0); 5187 Builder.SetInsertPoint(VL0); 5188 ShuffleBuilder.addInversedMask(E->ReorderIndices); 5189 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5190 V = ShuffleBuilder.finalize(V); 5191 E->VectorizedValue = V; 5192 return V; 5193 } 5194 case Instruction::ExtractValue: { 5195 auto *LI = cast<LoadInst>(E->getSingleOperand(0)); 5196 Builder.SetInsertPoint(LI); 5197 auto *PtrTy = PointerType::get(VecTy, LI->getPointerAddressSpace()); 5198 Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy); 5199 LoadInst *V = Builder.CreateAlignedLoad(VecTy, Ptr, LI->getAlign()); 5200 Value *NewV = propagateMetadata(V, E->Scalars); 5201 ShuffleBuilder.addInversedMask(E->ReorderIndices); 5202 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5203 NewV = ShuffleBuilder.finalize(NewV); 5204 E->VectorizedValue = NewV; 5205 return NewV; 5206 } 5207 case Instruction::InsertElement: { 5208 Builder.SetInsertPoint(VL0); 5209 Value *V = vectorizeTree(E->getOperand(1)); 5210 5211 const unsigned NumElts = 5212 cast<FixedVectorType>(VL0->getType())->getNumElements(); 5213 const unsigned NumScalars = E->Scalars.size(); 5214 5215 // Create InsertVector shuffle if necessary 5216 Instruction *FirstInsert = nullptr; 5217 bool IsIdentity = true; 5218 unsigned Offset = UINT_MAX; 5219 for (unsigned I = 0; I < NumScalars; ++I) { 5220 Value *Scalar = E->Scalars[I]; 5221 if (!FirstInsert && 5222 !is_contained(E->Scalars, cast<Instruction>(Scalar)->getOperand(0))) 5223 FirstInsert = cast<Instruction>(Scalar); 5224 Optional<int> InsertIdx = getInsertIndex(Scalar, 0); 5225 if (!InsertIdx || *InsertIdx == UndefMaskElem) 5226 continue; 5227 unsigned Idx = *InsertIdx; 5228 if (Idx < Offset) { 5229 Offset = Idx; 5230 IsIdentity &= I == 0; 5231 } else { 5232 assert(Idx >= Offset && "Failed to find vector index offset"); 5233 IsIdentity &= Idx - Offset == I; 5234 } 5235 } 5236 assert(Offset < NumElts && "Failed to find vector index offset"); 5237 5238 // Create shuffle to resize vector 5239 SmallVector<int> Mask(NumElts, UndefMaskElem); 5240 if (!IsIdentity) { 5241 for (unsigned I = 0; I < NumScalars; ++I) { 5242 Value *Scalar = E->Scalars[I]; 5243 Optional<int> InsertIdx = getInsertIndex(Scalar, 0); 5244 if (!InsertIdx || *InsertIdx == UndefMaskElem) 5245 continue; 5246 Mask[*InsertIdx - Offset] = I; 5247 } 5248 } else { 5249 std::iota(Mask.begin(), std::next(Mask.begin(), NumScalars), 0); 5250 } 5251 if (!IsIdentity || NumElts != NumScalars) 5252 V = Builder.CreateShuffleVector(V, Mask); 5253 5254 if (NumElts != NumScalars) { 5255 SmallVector<int> InsertMask(NumElts); 5256 std::iota(InsertMask.begin(), InsertMask.end(), 0); 5257 for (unsigned I = 0; I < NumElts; I++) { 5258 if (Mask[I] != UndefMaskElem) 5259 InsertMask[Offset + I] = NumElts + I; 5260 } 5261 5262 V = Builder.CreateShuffleVector( 5263 FirstInsert->getOperand(0), V, InsertMask, 5264 cast<Instruction>(E->Scalars.back())->getName()); 5265 } 5266 5267 ++NumVectorInstructions; 5268 E->VectorizedValue = V; 5269 return V; 5270 } 5271 case Instruction::ZExt: 5272 case Instruction::SExt: 5273 case Instruction::FPToUI: 5274 case Instruction::FPToSI: 5275 case Instruction::FPExt: 5276 case Instruction::PtrToInt: 5277 case Instruction::IntToPtr: 5278 case Instruction::SIToFP: 5279 case Instruction::UIToFP: 5280 case Instruction::Trunc: 5281 case Instruction::FPTrunc: 5282 case Instruction::BitCast: { 5283 setInsertPointAfterBundle(E); 5284 5285 Value *InVec = vectorizeTree(E->getOperand(0)); 5286 5287 if (E->VectorizedValue) { 5288 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5289 return E->VectorizedValue; 5290 } 5291 5292 auto *CI = cast<CastInst>(VL0); 5293 Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy); 5294 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5295 V = ShuffleBuilder.finalize(V); 5296 5297 E->VectorizedValue = V; 5298 ++NumVectorInstructions; 5299 return V; 5300 } 5301 case Instruction::FCmp: 5302 case Instruction::ICmp: { 5303 setInsertPointAfterBundle(E); 5304 5305 Value *L = vectorizeTree(E->getOperand(0)); 5306 Value *R = vectorizeTree(E->getOperand(1)); 5307 5308 if (E->VectorizedValue) { 5309 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5310 return E->VectorizedValue; 5311 } 5312 5313 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 5314 Value *V = Builder.CreateCmp(P0, L, R); 5315 propagateIRFlags(V, E->Scalars, VL0); 5316 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5317 V = ShuffleBuilder.finalize(V); 5318 5319 E->VectorizedValue = V; 5320 ++NumVectorInstructions; 5321 return V; 5322 } 5323 case Instruction::Select: { 5324 setInsertPointAfterBundle(E); 5325 5326 Value *Cond = vectorizeTree(E->getOperand(0)); 5327 Value *True = vectorizeTree(E->getOperand(1)); 5328 Value *False = vectorizeTree(E->getOperand(2)); 5329 5330 if (E->VectorizedValue) { 5331 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5332 return E->VectorizedValue; 5333 } 5334 5335 Value *V = Builder.CreateSelect(Cond, True, False); 5336 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5337 V = ShuffleBuilder.finalize(V); 5338 5339 E->VectorizedValue = V; 5340 ++NumVectorInstructions; 5341 return V; 5342 } 5343 case Instruction::FNeg: { 5344 setInsertPointAfterBundle(E); 5345 5346 Value *Op = vectorizeTree(E->getOperand(0)); 5347 5348 if (E->VectorizedValue) { 5349 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5350 return E->VectorizedValue; 5351 } 5352 5353 Value *V = Builder.CreateUnOp( 5354 static_cast<Instruction::UnaryOps>(E->getOpcode()), Op); 5355 propagateIRFlags(V, E->Scalars, VL0); 5356 if (auto *I = dyn_cast<Instruction>(V)) 5357 V = propagateMetadata(I, E->Scalars); 5358 5359 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5360 V = ShuffleBuilder.finalize(V); 5361 5362 E->VectorizedValue = V; 5363 ++NumVectorInstructions; 5364 5365 return V; 5366 } 5367 case Instruction::Add: 5368 case Instruction::FAdd: 5369 case Instruction::Sub: 5370 case Instruction::FSub: 5371 case Instruction::Mul: 5372 case Instruction::FMul: 5373 case Instruction::UDiv: 5374 case Instruction::SDiv: 5375 case Instruction::FDiv: 5376 case Instruction::URem: 5377 case Instruction::SRem: 5378 case Instruction::FRem: 5379 case Instruction::Shl: 5380 case Instruction::LShr: 5381 case Instruction::AShr: 5382 case Instruction::And: 5383 case Instruction::Or: 5384 case Instruction::Xor: { 5385 setInsertPointAfterBundle(E); 5386 5387 Value *LHS = vectorizeTree(E->getOperand(0)); 5388 Value *RHS = vectorizeTree(E->getOperand(1)); 5389 5390 if (E->VectorizedValue) { 5391 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5392 return E->VectorizedValue; 5393 } 5394 5395 Value *V = Builder.CreateBinOp( 5396 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, 5397 RHS); 5398 propagateIRFlags(V, E->Scalars, VL0); 5399 if (auto *I = dyn_cast<Instruction>(V)) 5400 V = propagateMetadata(I, E->Scalars); 5401 5402 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5403 V = ShuffleBuilder.finalize(V); 5404 5405 E->VectorizedValue = V; 5406 ++NumVectorInstructions; 5407 5408 return V; 5409 } 5410 case Instruction::Load: { 5411 // Loads are inserted at the head of the tree because we don't want to 5412 // sink them all the way down past store instructions. 5413 bool IsReorder = E->updateStateIfReorder(); 5414 if (IsReorder) 5415 VL0 = E->getMainOp(); 5416 setInsertPointAfterBundle(E); 5417 5418 LoadInst *LI = cast<LoadInst>(VL0); 5419 Instruction *NewLI; 5420 unsigned AS = LI->getPointerAddressSpace(); 5421 Value *PO = LI->getPointerOperand(); 5422 if (E->State == TreeEntry::Vectorize) { 5423 5424 Value *VecPtr = Builder.CreateBitCast(PO, VecTy->getPointerTo(AS)); 5425 5426 // The pointer operand uses an in-tree scalar so we add the new BitCast 5427 // to ExternalUses list to make sure that an extract will be generated 5428 // in the future. 5429 if (getTreeEntry(PO)) 5430 ExternalUses.emplace_back(PO, cast<User>(VecPtr), 0); 5431 5432 NewLI = Builder.CreateAlignedLoad(VecTy, VecPtr, LI->getAlign()); 5433 } else { 5434 assert(E->State == TreeEntry::ScatterVectorize && "Unhandled state"); 5435 Value *VecPtr = vectorizeTree(E->getOperand(0)); 5436 // Use the minimum alignment of the gathered loads. 5437 Align CommonAlignment = LI->getAlign(); 5438 for (Value *V : E->Scalars) 5439 CommonAlignment = 5440 commonAlignment(CommonAlignment, cast<LoadInst>(V)->getAlign()); 5441 NewLI = Builder.CreateMaskedGather(VecTy, VecPtr, CommonAlignment); 5442 } 5443 Value *V = propagateMetadata(NewLI, E->Scalars); 5444 5445 ShuffleBuilder.addInversedMask(E->ReorderIndices); 5446 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5447 V = ShuffleBuilder.finalize(V); 5448 E->VectorizedValue = V; 5449 ++NumVectorInstructions; 5450 return V; 5451 } 5452 case Instruction::Store: { 5453 bool IsReorder = !E->ReorderIndices.empty(); 5454 auto *SI = cast<StoreInst>( 5455 IsReorder ? E->Scalars[E->ReorderIndices.front()] : VL0); 5456 unsigned AS = SI->getPointerAddressSpace(); 5457 5458 setInsertPointAfterBundle(E); 5459 5460 Value *VecValue = vectorizeTree(E->getOperand(0)); 5461 ShuffleBuilder.addMask(E->ReorderIndices); 5462 VecValue = ShuffleBuilder.finalize(VecValue); 5463 5464 Value *ScalarPtr = SI->getPointerOperand(); 5465 Value *VecPtr = Builder.CreateBitCast( 5466 ScalarPtr, VecValue->getType()->getPointerTo(AS)); 5467 StoreInst *ST = Builder.CreateAlignedStore(VecValue, VecPtr, 5468 SI->getAlign()); 5469 5470 // The pointer operand uses an in-tree scalar, so add the new BitCast to 5471 // ExternalUses to make sure that an extract will be generated in the 5472 // future. 5473 if (getTreeEntry(ScalarPtr)) 5474 ExternalUses.push_back(ExternalUser(ScalarPtr, cast<User>(VecPtr), 0)); 5475 5476 Value *V = propagateMetadata(ST, E->Scalars); 5477 5478 E->VectorizedValue = V; 5479 ++NumVectorInstructions; 5480 return V; 5481 } 5482 case Instruction::GetElementPtr: { 5483 setInsertPointAfterBundle(E); 5484 5485 Value *Op0 = vectorizeTree(E->getOperand(0)); 5486 5487 std::vector<Value *> OpVecs; 5488 for (int j = 1, e = cast<GetElementPtrInst>(VL0)->getNumOperands(); j < e; 5489 ++j) { 5490 ValueList &VL = E->getOperand(j); 5491 // Need to cast all elements to the same type before vectorization to 5492 // avoid crash. 5493 Type *VL0Ty = VL0->getOperand(j)->getType(); 5494 Type *Ty = llvm::all_of( 5495 VL, [VL0Ty](Value *V) { return VL0Ty == V->getType(); }) 5496 ? VL0Ty 5497 : DL->getIndexType(cast<GetElementPtrInst>(VL0) 5498 ->getPointerOperandType() 5499 ->getScalarType()); 5500 for (Value *&V : VL) { 5501 auto *CI = cast<ConstantInt>(V); 5502 V = ConstantExpr::getIntegerCast(CI, Ty, 5503 CI->getValue().isSignBitSet()); 5504 } 5505 Value *OpVec = vectorizeTree(VL); 5506 OpVecs.push_back(OpVec); 5507 } 5508 5509 Value *V = Builder.CreateGEP( 5510 cast<GetElementPtrInst>(VL0)->getSourceElementType(), Op0, OpVecs); 5511 if (Instruction *I = dyn_cast<Instruction>(V)) 5512 V = propagateMetadata(I, E->Scalars); 5513 5514 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5515 V = ShuffleBuilder.finalize(V); 5516 5517 E->VectorizedValue = V; 5518 ++NumVectorInstructions; 5519 5520 return V; 5521 } 5522 case Instruction::Call: { 5523 CallInst *CI = cast<CallInst>(VL0); 5524 setInsertPointAfterBundle(E); 5525 5526 Intrinsic::ID IID = Intrinsic::not_intrinsic; 5527 if (Function *FI = CI->getCalledFunction()) 5528 IID = FI->getIntrinsicID(); 5529 5530 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 5531 5532 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 5533 bool UseIntrinsic = ID != Intrinsic::not_intrinsic && 5534 VecCallCosts.first <= VecCallCosts.second; 5535 5536 Value *ScalarArg = nullptr; 5537 std::vector<Value *> OpVecs; 5538 SmallVector<Type *, 2> TysForDecl = 5539 {FixedVectorType::get(CI->getType(), E->Scalars.size())}; 5540 for (int j = 0, e = CI->getNumArgOperands(); j < e; ++j) { 5541 ValueList OpVL; 5542 // Some intrinsics have scalar arguments. This argument should not be 5543 // vectorized. 5544 if (UseIntrinsic && hasVectorInstrinsicScalarOpd(IID, j)) { 5545 CallInst *CEI = cast<CallInst>(VL0); 5546 ScalarArg = CEI->getArgOperand(j); 5547 OpVecs.push_back(CEI->getArgOperand(j)); 5548 if (hasVectorInstrinsicOverloadedScalarOpd(IID, j)) 5549 TysForDecl.push_back(ScalarArg->getType()); 5550 continue; 5551 } 5552 5553 Value *OpVec = vectorizeTree(E->getOperand(j)); 5554 LLVM_DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n"); 5555 OpVecs.push_back(OpVec); 5556 } 5557 5558 Function *CF; 5559 if (!UseIntrinsic) { 5560 VFShape Shape = 5561 VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>( 5562 VecTy->getNumElements())), 5563 false /*HasGlobalPred*/); 5564 CF = VFDatabase(*CI).getVectorizedFunction(Shape); 5565 } else { 5566 CF = Intrinsic::getDeclaration(F->getParent(), ID, TysForDecl); 5567 } 5568 5569 SmallVector<OperandBundleDef, 1> OpBundles; 5570 CI->getOperandBundlesAsDefs(OpBundles); 5571 Value *V = Builder.CreateCall(CF, OpVecs, OpBundles); 5572 5573 // The scalar argument uses an in-tree scalar so we add the new vectorized 5574 // call to ExternalUses list to make sure that an extract will be 5575 // generated in the future. 5576 if (ScalarArg && getTreeEntry(ScalarArg)) 5577 ExternalUses.push_back(ExternalUser(ScalarArg, cast<User>(V), 0)); 5578 5579 propagateIRFlags(V, E->Scalars, VL0); 5580 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5581 V = ShuffleBuilder.finalize(V); 5582 5583 E->VectorizedValue = V; 5584 ++NumVectorInstructions; 5585 return V; 5586 } 5587 case Instruction::ShuffleVector: { 5588 assert(E->isAltShuffle() && 5589 ((Instruction::isBinaryOp(E->getOpcode()) && 5590 Instruction::isBinaryOp(E->getAltOpcode())) || 5591 (Instruction::isCast(E->getOpcode()) && 5592 Instruction::isCast(E->getAltOpcode()))) && 5593 "Invalid Shuffle Vector Operand"); 5594 5595 Value *LHS = nullptr, *RHS = nullptr; 5596 if (Instruction::isBinaryOp(E->getOpcode())) { 5597 setInsertPointAfterBundle(E); 5598 LHS = vectorizeTree(E->getOperand(0)); 5599 RHS = vectorizeTree(E->getOperand(1)); 5600 } else { 5601 setInsertPointAfterBundle(E); 5602 LHS = vectorizeTree(E->getOperand(0)); 5603 } 5604 5605 if (E->VectorizedValue) { 5606 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5607 return E->VectorizedValue; 5608 } 5609 5610 Value *V0, *V1; 5611 if (Instruction::isBinaryOp(E->getOpcode())) { 5612 V0 = Builder.CreateBinOp( 5613 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, RHS); 5614 V1 = Builder.CreateBinOp( 5615 static_cast<Instruction::BinaryOps>(E->getAltOpcode()), LHS, RHS); 5616 } else { 5617 V0 = Builder.CreateCast( 5618 static_cast<Instruction::CastOps>(E->getOpcode()), LHS, VecTy); 5619 V1 = Builder.CreateCast( 5620 static_cast<Instruction::CastOps>(E->getAltOpcode()), LHS, VecTy); 5621 } 5622 5623 // Create shuffle to take alternate operations from the vector. 5624 // Also, gather up main and alt scalar ops to propagate IR flags to 5625 // each vector operation. 5626 ValueList OpScalars, AltScalars; 5627 unsigned Sz = E->Scalars.size(); 5628 SmallVector<int> Mask(Sz); 5629 for (unsigned I = 0; I < Sz; ++I) { 5630 auto *OpInst = cast<Instruction>(E->Scalars[I]); 5631 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 5632 if (OpInst->getOpcode() == E->getAltOpcode()) { 5633 Mask[I] = Sz + I; 5634 AltScalars.push_back(E->Scalars[I]); 5635 } else { 5636 Mask[I] = I; 5637 OpScalars.push_back(E->Scalars[I]); 5638 } 5639 } 5640 5641 propagateIRFlags(V0, OpScalars); 5642 propagateIRFlags(V1, AltScalars); 5643 5644 Value *V = Builder.CreateShuffleVector(V0, V1, Mask); 5645 if (Instruction *I = dyn_cast<Instruction>(V)) 5646 V = propagateMetadata(I, E->Scalars); 5647 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5648 V = ShuffleBuilder.finalize(V); 5649 5650 E->VectorizedValue = V; 5651 ++NumVectorInstructions; 5652 5653 return V; 5654 } 5655 default: 5656 llvm_unreachable("unknown inst"); 5657 } 5658 return nullptr; 5659 } 5660 5661 Value *BoUpSLP::vectorizeTree() { 5662 ExtraValueToDebugLocsMap ExternallyUsedValues; 5663 return vectorizeTree(ExternallyUsedValues); 5664 } 5665 5666 Value * 5667 BoUpSLP::vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues) { 5668 // All blocks must be scheduled before any instructions are inserted. 5669 for (auto &BSIter : BlocksSchedules) { 5670 scheduleBlock(BSIter.second.get()); 5671 } 5672 5673 Builder.SetInsertPoint(&F->getEntryBlock().front()); 5674 auto *VectorRoot = vectorizeTree(VectorizableTree[0].get()); 5675 5676 // If the vectorized tree can be rewritten in a smaller type, we truncate the 5677 // vectorized root. InstCombine will then rewrite the entire expression. We 5678 // sign extend the extracted values below. 5679 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 5680 if (MinBWs.count(ScalarRoot)) { 5681 if (auto *I = dyn_cast<Instruction>(VectorRoot)) { 5682 // If current instr is a phi and not the last phi, insert it after the 5683 // last phi node. 5684 if (isa<PHINode>(I)) 5685 Builder.SetInsertPoint(&*I->getParent()->getFirstInsertionPt()); 5686 else 5687 Builder.SetInsertPoint(&*++BasicBlock::iterator(I)); 5688 } 5689 auto BundleWidth = VectorizableTree[0]->Scalars.size(); 5690 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 5691 auto *VecTy = FixedVectorType::get(MinTy, BundleWidth); 5692 auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy); 5693 VectorizableTree[0]->VectorizedValue = Trunc; 5694 } 5695 5696 LLVM_DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size() 5697 << " values .\n"); 5698 5699 // Extract all of the elements with the external uses. 5700 for (const auto &ExternalUse : ExternalUses) { 5701 Value *Scalar = ExternalUse.Scalar; 5702 llvm::User *User = ExternalUse.User; 5703 5704 // Skip users that we already RAUW. This happens when one instruction 5705 // has multiple uses of the same value. 5706 if (User && !is_contained(Scalar->users(), User)) 5707 continue; 5708 TreeEntry *E = getTreeEntry(Scalar); 5709 assert(E && "Invalid scalar"); 5710 assert(E->State != TreeEntry::NeedToGather && 5711 "Extracting from a gather list"); 5712 5713 Value *Vec = E->VectorizedValue; 5714 assert(Vec && "Can't find vectorizable value"); 5715 5716 Value *Lane = Builder.getInt32(ExternalUse.Lane); 5717 auto ExtractAndExtendIfNeeded = [&](Value *Vec) { 5718 if (Scalar->getType() != Vec->getType()) { 5719 Value *Ex; 5720 // "Reuse" the existing extract to improve final codegen. 5721 if (auto *ES = dyn_cast<ExtractElementInst>(Scalar)) { 5722 Ex = Builder.CreateExtractElement(ES->getOperand(0), 5723 ES->getOperand(1)); 5724 } else { 5725 Ex = Builder.CreateExtractElement(Vec, Lane); 5726 } 5727 // If necessary, sign-extend or zero-extend ScalarRoot 5728 // to the larger type. 5729 if (!MinBWs.count(ScalarRoot)) 5730 return Ex; 5731 if (MinBWs[ScalarRoot].second) 5732 return Builder.CreateSExt(Ex, Scalar->getType()); 5733 return Builder.CreateZExt(Ex, Scalar->getType()); 5734 } 5735 assert(isa<FixedVectorType>(Scalar->getType()) && 5736 isa<InsertElementInst>(Scalar) && 5737 "In-tree scalar of vector type is not insertelement?"); 5738 return Vec; 5739 }; 5740 // If User == nullptr, the Scalar is used as extra arg. Generate 5741 // ExtractElement instruction and update the record for this scalar in 5742 // ExternallyUsedValues. 5743 if (!User) { 5744 assert(ExternallyUsedValues.count(Scalar) && 5745 "Scalar with nullptr as an external user must be registered in " 5746 "ExternallyUsedValues map"); 5747 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 5748 Builder.SetInsertPoint(VecI->getParent(), 5749 std::next(VecI->getIterator())); 5750 } else { 5751 Builder.SetInsertPoint(&F->getEntryBlock().front()); 5752 } 5753 Value *NewInst = ExtractAndExtendIfNeeded(Vec); 5754 CSEBlocks.insert(cast<Instruction>(Scalar)->getParent()); 5755 auto &NewInstLocs = ExternallyUsedValues[NewInst]; 5756 auto It = ExternallyUsedValues.find(Scalar); 5757 assert(It != ExternallyUsedValues.end() && 5758 "Externally used scalar is not found in ExternallyUsedValues"); 5759 NewInstLocs.append(It->second); 5760 ExternallyUsedValues.erase(Scalar); 5761 // Required to update internally referenced instructions. 5762 Scalar->replaceAllUsesWith(NewInst); 5763 continue; 5764 } 5765 5766 // Generate extracts for out-of-tree users. 5767 // Find the insertion point for the extractelement lane. 5768 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 5769 if (PHINode *PH = dyn_cast<PHINode>(User)) { 5770 for (int i = 0, e = PH->getNumIncomingValues(); i != e; ++i) { 5771 if (PH->getIncomingValue(i) == Scalar) { 5772 Instruction *IncomingTerminator = 5773 PH->getIncomingBlock(i)->getTerminator(); 5774 if (isa<CatchSwitchInst>(IncomingTerminator)) { 5775 Builder.SetInsertPoint(VecI->getParent(), 5776 std::next(VecI->getIterator())); 5777 } else { 5778 Builder.SetInsertPoint(PH->getIncomingBlock(i)->getTerminator()); 5779 } 5780 Value *NewInst = ExtractAndExtendIfNeeded(Vec); 5781 CSEBlocks.insert(PH->getIncomingBlock(i)); 5782 PH->setOperand(i, NewInst); 5783 } 5784 } 5785 } else { 5786 Builder.SetInsertPoint(cast<Instruction>(User)); 5787 Value *NewInst = ExtractAndExtendIfNeeded(Vec); 5788 CSEBlocks.insert(cast<Instruction>(User)->getParent()); 5789 User->replaceUsesOfWith(Scalar, NewInst); 5790 } 5791 } else { 5792 Builder.SetInsertPoint(&F->getEntryBlock().front()); 5793 Value *NewInst = ExtractAndExtendIfNeeded(Vec); 5794 CSEBlocks.insert(&F->getEntryBlock()); 5795 User->replaceUsesOfWith(Scalar, NewInst); 5796 } 5797 5798 LLVM_DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n"); 5799 } 5800 5801 // For each vectorized value: 5802 for (auto &TEPtr : VectorizableTree) { 5803 TreeEntry *Entry = TEPtr.get(); 5804 5805 // No need to handle users of gathered values. 5806 if (Entry->State == TreeEntry::NeedToGather) 5807 continue; 5808 5809 assert(Entry->VectorizedValue && "Can't find vectorizable value"); 5810 5811 // For each lane: 5812 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 5813 Value *Scalar = Entry->Scalars[Lane]; 5814 5815 #ifndef NDEBUG 5816 Type *Ty = Scalar->getType(); 5817 if (!Ty->isVoidTy()) { 5818 for (User *U : Scalar->users()) { 5819 LLVM_DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n"); 5820 5821 // It is legal to delete users in the ignorelist. 5822 assert((getTreeEntry(U) || is_contained(UserIgnoreList, U)) && 5823 "Deleting out-of-tree value"); 5824 } 5825 } 5826 #endif 5827 LLVM_DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n"); 5828 eraseInstruction(cast<Instruction>(Scalar)); 5829 } 5830 } 5831 5832 Builder.ClearInsertionPoint(); 5833 InstrElementSize.clear(); 5834 5835 return VectorizableTree[0]->VectorizedValue; 5836 } 5837 5838 void BoUpSLP::optimizeGatherSequence() { 5839 LLVM_DEBUG(dbgs() << "SLP: Optimizing " << GatherSeq.size() 5840 << " gather sequences instructions.\n"); 5841 // LICM InsertElementInst sequences. 5842 for (Instruction *I : GatherSeq) { 5843 if (isDeleted(I)) 5844 continue; 5845 5846 // Check if this block is inside a loop. 5847 Loop *L = LI->getLoopFor(I->getParent()); 5848 if (!L) 5849 continue; 5850 5851 // Check if it has a preheader. 5852 BasicBlock *PreHeader = L->getLoopPreheader(); 5853 if (!PreHeader) 5854 continue; 5855 5856 // If the vector or the element that we insert into it are 5857 // instructions that are defined in this basic block then we can't 5858 // hoist this instruction. 5859 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 5860 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 5861 if (Op0 && L->contains(Op0)) 5862 continue; 5863 if (Op1 && L->contains(Op1)) 5864 continue; 5865 5866 // We can hoist this instruction. Move it to the pre-header. 5867 I->moveBefore(PreHeader->getTerminator()); 5868 } 5869 5870 // Make a list of all reachable blocks in our CSE queue. 5871 SmallVector<const DomTreeNode *, 8> CSEWorkList; 5872 CSEWorkList.reserve(CSEBlocks.size()); 5873 for (BasicBlock *BB : CSEBlocks) 5874 if (DomTreeNode *N = DT->getNode(BB)) { 5875 assert(DT->isReachableFromEntry(N)); 5876 CSEWorkList.push_back(N); 5877 } 5878 5879 // Sort blocks by domination. This ensures we visit a block after all blocks 5880 // dominating it are visited. 5881 llvm::sort(CSEWorkList, [](const DomTreeNode *A, const DomTreeNode *B) { 5882 assert((A == B) == (A->getDFSNumIn() == B->getDFSNumIn()) && 5883 "Different nodes should have different DFS numbers"); 5884 return A->getDFSNumIn() < B->getDFSNumIn(); 5885 }); 5886 5887 // Perform O(N^2) search over the gather sequences and merge identical 5888 // instructions. TODO: We can further optimize this scan if we split the 5889 // instructions into different buckets based on the insert lane. 5890 SmallVector<Instruction *, 16> Visited; 5891 for (auto I = CSEWorkList.begin(), E = CSEWorkList.end(); I != E; ++I) { 5892 assert(*I && 5893 (I == CSEWorkList.begin() || !DT->dominates(*I, *std::prev(I))) && 5894 "Worklist not sorted properly!"); 5895 BasicBlock *BB = (*I)->getBlock(); 5896 // For all instructions in blocks containing gather sequences: 5897 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e;) { 5898 Instruction *In = &*it++; 5899 if (isDeleted(In)) 5900 continue; 5901 if (!isa<InsertElementInst>(In) && !isa<ExtractElementInst>(In)) 5902 continue; 5903 5904 // Check if we can replace this instruction with any of the 5905 // visited instructions. 5906 for (Instruction *v : Visited) { 5907 if (In->isIdenticalTo(v) && 5908 DT->dominates(v->getParent(), In->getParent())) { 5909 In->replaceAllUsesWith(v); 5910 eraseInstruction(In); 5911 In = nullptr; 5912 break; 5913 } 5914 } 5915 if (In) { 5916 assert(!is_contained(Visited, In)); 5917 Visited.push_back(In); 5918 } 5919 } 5920 } 5921 CSEBlocks.clear(); 5922 GatherSeq.clear(); 5923 } 5924 5925 // Groups the instructions to a bundle (which is then a single scheduling entity) 5926 // and schedules instructions until the bundle gets ready. 5927 Optional<BoUpSLP::ScheduleData *> 5928 BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 5929 const InstructionsState &S) { 5930 if (isa<PHINode>(S.OpValue) || isa<InsertElementInst>(S.OpValue)) 5931 return nullptr; 5932 5933 // Initialize the instruction bundle. 5934 Instruction *OldScheduleEnd = ScheduleEnd; 5935 ScheduleData *PrevInBundle = nullptr; 5936 ScheduleData *Bundle = nullptr; 5937 bool ReSchedule = false; 5938 LLVM_DEBUG(dbgs() << "SLP: bundle: " << *S.OpValue << "\n"); 5939 5940 auto &&TryScheduleBundle = [this, OldScheduleEnd, SLP](bool ReSchedule, 5941 ScheduleData *Bundle) { 5942 // The scheduling region got new instructions at the lower end (or it is a 5943 // new region for the first bundle). This makes it necessary to 5944 // recalculate all dependencies. 5945 // It is seldom that this needs to be done a second time after adding the 5946 // initial bundle to the region. 5947 if (ScheduleEnd != OldScheduleEnd) { 5948 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) 5949 doForAllOpcodes(I, [](ScheduleData *SD) { SD->clearDependencies(); }); 5950 ReSchedule = true; 5951 } 5952 if (ReSchedule) { 5953 resetSchedule(); 5954 initialFillReadyList(ReadyInsts); 5955 } 5956 if (Bundle) { 5957 LLVM_DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle 5958 << " in block " << BB->getName() << "\n"); 5959 calculateDependencies(Bundle, /*InsertInReadyList=*/true, SLP); 5960 } 5961 5962 // Now try to schedule the new bundle or (if no bundle) just calculate 5963 // dependencies. As soon as the bundle is "ready" it means that there are no 5964 // cyclic dependencies and we can schedule it. Note that's important that we 5965 // don't "schedule" the bundle yet (see cancelScheduling). 5966 while (((!Bundle && ReSchedule) || (Bundle && !Bundle->isReady())) && 5967 !ReadyInsts.empty()) { 5968 ScheduleData *Picked = ReadyInsts.pop_back_val(); 5969 if (Picked->isSchedulingEntity() && Picked->isReady()) 5970 schedule(Picked, ReadyInsts); 5971 } 5972 }; 5973 5974 // Make sure that the scheduling region contains all 5975 // instructions of the bundle. 5976 for (Value *V : VL) { 5977 if (!extendSchedulingRegion(V, S)) { 5978 // If the scheduling region got new instructions at the lower end (or it 5979 // is a new region for the first bundle). This makes it necessary to 5980 // recalculate all dependencies. 5981 // Otherwise the compiler may crash trying to incorrectly calculate 5982 // dependencies and emit instruction in the wrong order at the actual 5983 // scheduling. 5984 TryScheduleBundle(/*ReSchedule=*/false, nullptr); 5985 return None; 5986 } 5987 } 5988 5989 for (Value *V : VL) { 5990 ScheduleData *BundleMember = getScheduleData(V); 5991 assert(BundleMember && 5992 "no ScheduleData for bundle member (maybe not in same basic block)"); 5993 if (BundleMember->IsScheduled) { 5994 // A bundle member was scheduled as single instruction before and now 5995 // needs to be scheduled as part of the bundle. We just get rid of the 5996 // existing schedule. 5997 LLVM_DEBUG(dbgs() << "SLP: reset schedule because " << *BundleMember 5998 << " was already scheduled\n"); 5999 ReSchedule = true; 6000 } 6001 assert(BundleMember->isSchedulingEntity() && 6002 "bundle member already part of other bundle"); 6003 if (PrevInBundle) { 6004 PrevInBundle->NextInBundle = BundleMember; 6005 } else { 6006 Bundle = BundleMember; 6007 } 6008 BundleMember->UnscheduledDepsInBundle = 0; 6009 Bundle->UnscheduledDepsInBundle += BundleMember->UnscheduledDeps; 6010 6011 // Group the instructions to a bundle. 6012 BundleMember->FirstInBundle = Bundle; 6013 PrevInBundle = BundleMember; 6014 } 6015 assert(Bundle && "Failed to find schedule bundle"); 6016 TryScheduleBundle(ReSchedule, Bundle); 6017 if (!Bundle->isReady()) { 6018 cancelScheduling(VL, S.OpValue); 6019 return None; 6020 } 6021 return Bundle; 6022 } 6023 6024 void BoUpSLP::BlockScheduling::cancelScheduling(ArrayRef<Value *> VL, 6025 Value *OpValue) { 6026 if (isa<PHINode>(OpValue) || isa<InsertElementInst>(OpValue)) 6027 return; 6028 6029 ScheduleData *Bundle = getScheduleData(OpValue); 6030 LLVM_DEBUG(dbgs() << "SLP: cancel scheduling of " << *Bundle << "\n"); 6031 assert(!Bundle->IsScheduled && 6032 "Can't cancel bundle which is already scheduled"); 6033 assert(Bundle->isSchedulingEntity() && Bundle->isPartOfBundle() && 6034 "tried to unbundle something which is not a bundle"); 6035 6036 // Un-bundle: make single instructions out of the bundle. 6037 ScheduleData *BundleMember = Bundle; 6038 while (BundleMember) { 6039 assert(BundleMember->FirstInBundle == Bundle && "corrupt bundle links"); 6040 BundleMember->FirstInBundle = BundleMember; 6041 ScheduleData *Next = BundleMember->NextInBundle; 6042 BundleMember->NextInBundle = nullptr; 6043 BundleMember->UnscheduledDepsInBundle = BundleMember->UnscheduledDeps; 6044 if (BundleMember->UnscheduledDepsInBundle == 0) { 6045 ReadyInsts.insert(BundleMember); 6046 } 6047 BundleMember = Next; 6048 } 6049 } 6050 6051 BoUpSLP::ScheduleData *BoUpSLP::BlockScheduling::allocateScheduleDataChunks() { 6052 // Allocate a new ScheduleData for the instruction. 6053 if (ChunkPos >= ChunkSize) { 6054 ScheduleDataChunks.push_back(std::make_unique<ScheduleData[]>(ChunkSize)); 6055 ChunkPos = 0; 6056 } 6057 return &(ScheduleDataChunks.back()[ChunkPos++]); 6058 } 6059 6060 bool BoUpSLP::BlockScheduling::extendSchedulingRegion(Value *V, 6061 const InstructionsState &S) { 6062 if (getScheduleData(V, isOneOf(S, V))) 6063 return true; 6064 Instruction *I = dyn_cast<Instruction>(V); 6065 assert(I && "bundle member must be an instruction"); 6066 assert(!isa<PHINode>(I) && !isa<InsertElementInst>(I) && 6067 "phi nodes/insertelements don't need to be scheduled"); 6068 auto &&CheckSheduleForI = [this, &S](Instruction *I) -> bool { 6069 ScheduleData *ISD = getScheduleData(I); 6070 if (!ISD) 6071 return false; 6072 assert(isInSchedulingRegion(ISD) && 6073 "ScheduleData not in scheduling region"); 6074 ScheduleData *SD = allocateScheduleDataChunks(); 6075 SD->Inst = I; 6076 SD->init(SchedulingRegionID, S.OpValue); 6077 ExtraScheduleDataMap[I][S.OpValue] = SD; 6078 return true; 6079 }; 6080 if (CheckSheduleForI(I)) 6081 return true; 6082 if (!ScheduleStart) { 6083 // It's the first instruction in the new region. 6084 initScheduleData(I, I->getNextNode(), nullptr, nullptr); 6085 ScheduleStart = I; 6086 ScheduleEnd = I->getNextNode(); 6087 if (isOneOf(S, I) != I) 6088 CheckSheduleForI(I); 6089 assert(ScheduleEnd && "tried to vectorize a terminator?"); 6090 LLVM_DEBUG(dbgs() << "SLP: initialize schedule region to " << *I << "\n"); 6091 return true; 6092 } 6093 // Search up and down at the same time, because we don't know if the new 6094 // instruction is above or below the existing scheduling region. 6095 BasicBlock::reverse_iterator UpIter = 6096 ++ScheduleStart->getIterator().getReverse(); 6097 BasicBlock::reverse_iterator UpperEnd = BB->rend(); 6098 BasicBlock::iterator DownIter = ScheduleEnd->getIterator(); 6099 BasicBlock::iterator LowerEnd = BB->end(); 6100 while (UpIter != UpperEnd && DownIter != LowerEnd && &*UpIter != I && 6101 &*DownIter != I) { 6102 if (++ScheduleRegionSize > ScheduleRegionSizeLimit) { 6103 LLVM_DEBUG(dbgs() << "SLP: exceeded schedule region size limit\n"); 6104 return false; 6105 } 6106 6107 ++UpIter; 6108 ++DownIter; 6109 } 6110 if (DownIter == LowerEnd || (UpIter != UpperEnd && &*UpIter == I)) { 6111 assert(I->getParent() == ScheduleStart->getParent() && 6112 "Instruction is in wrong basic block."); 6113 initScheduleData(I, ScheduleStart, nullptr, FirstLoadStoreInRegion); 6114 ScheduleStart = I; 6115 if (isOneOf(S, I) != I) 6116 CheckSheduleForI(I); 6117 LLVM_DEBUG(dbgs() << "SLP: extend schedule region start to " << *I 6118 << "\n"); 6119 return true; 6120 } 6121 assert((UpIter == UpperEnd || (DownIter != LowerEnd && &*DownIter == I)) && 6122 "Expected to reach top of the basic block or instruction down the " 6123 "lower end."); 6124 assert(I->getParent() == ScheduleEnd->getParent() && 6125 "Instruction is in wrong basic block."); 6126 initScheduleData(ScheduleEnd, I->getNextNode(), LastLoadStoreInRegion, 6127 nullptr); 6128 ScheduleEnd = I->getNextNode(); 6129 if (isOneOf(S, I) != I) 6130 CheckSheduleForI(I); 6131 assert(ScheduleEnd && "tried to vectorize a terminator?"); 6132 LLVM_DEBUG(dbgs() << "SLP: extend schedule region end to " << *I << "\n"); 6133 return true; 6134 } 6135 6136 void BoUpSLP::BlockScheduling::initScheduleData(Instruction *FromI, 6137 Instruction *ToI, 6138 ScheduleData *PrevLoadStore, 6139 ScheduleData *NextLoadStore) { 6140 ScheduleData *CurrentLoadStore = PrevLoadStore; 6141 for (Instruction *I = FromI; I != ToI; I = I->getNextNode()) { 6142 ScheduleData *SD = ScheduleDataMap[I]; 6143 if (!SD) { 6144 SD = allocateScheduleDataChunks(); 6145 ScheduleDataMap[I] = SD; 6146 SD->Inst = I; 6147 } 6148 assert(!isInSchedulingRegion(SD) && 6149 "new ScheduleData already in scheduling region"); 6150 SD->init(SchedulingRegionID, I); 6151 6152 if (I->mayReadOrWriteMemory() && 6153 (!isa<IntrinsicInst>(I) || 6154 (cast<IntrinsicInst>(I)->getIntrinsicID() != Intrinsic::sideeffect && 6155 cast<IntrinsicInst>(I)->getIntrinsicID() != 6156 Intrinsic::pseudoprobe))) { 6157 // Update the linked list of memory accessing instructions. 6158 if (CurrentLoadStore) { 6159 CurrentLoadStore->NextLoadStore = SD; 6160 } else { 6161 FirstLoadStoreInRegion = SD; 6162 } 6163 CurrentLoadStore = SD; 6164 } 6165 } 6166 if (NextLoadStore) { 6167 if (CurrentLoadStore) 6168 CurrentLoadStore->NextLoadStore = NextLoadStore; 6169 } else { 6170 LastLoadStoreInRegion = CurrentLoadStore; 6171 } 6172 } 6173 6174 void BoUpSLP::BlockScheduling::calculateDependencies(ScheduleData *SD, 6175 bool InsertInReadyList, 6176 BoUpSLP *SLP) { 6177 assert(SD->isSchedulingEntity()); 6178 6179 SmallVector<ScheduleData *, 10> WorkList; 6180 WorkList.push_back(SD); 6181 6182 while (!WorkList.empty()) { 6183 ScheduleData *SD = WorkList.pop_back_val(); 6184 6185 ScheduleData *BundleMember = SD; 6186 while (BundleMember) { 6187 assert(isInSchedulingRegion(BundleMember)); 6188 if (!BundleMember->hasValidDependencies()) { 6189 6190 LLVM_DEBUG(dbgs() << "SLP: update deps of " << *BundleMember 6191 << "\n"); 6192 BundleMember->Dependencies = 0; 6193 BundleMember->resetUnscheduledDeps(); 6194 6195 // Handle def-use chain dependencies. 6196 if (BundleMember->OpValue != BundleMember->Inst) { 6197 ScheduleData *UseSD = getScheduleData(BundleMember->Inst); 6198 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 6199 BundleMember->Dependencies++; 6200 ScheduleData *DestBundle = UseSD->FirstInBundle; 6201 if (!DestBundle->IsScheduled) 6202 BundleMember->incrementUnscheduledDeps(1); 6203 if (!DestBundle->hasValidDependencies()) 6204 WorkList.push_back(DestBundle); 6205 } 6206 } else { 6207 for (User *U : BundleMember->Inst->users()) { 6208 if (isa<Instruction>(U)) { 6209 ScheduleData *UseSD = getScheduleData(U); 6210 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 6211 BundleMember->Dependencies++; 6212 ScheduleData *DestBundle = UseSD->FirstInBundle; 6213 if (!DestBundle->IsScheduled) 6214 BundleMember->incrementUnscheduledDeps(1); 6215 if (!DestBundle->hasValidDependencies()) 6216 WorkList.push_back(DestBundle); 6217 } 6218 } else { 6219 // I'm not sure if this can ever happen. But we need to be safe. 6220 // This lets the instruction/bundle never be scheduled and 6221 // eventually disable vectorization. 6222 BundleMember->Dependencies++; 6223 BundleMember->incrementUnscheduledDeps(1); 6224 } 6225 } 6226 } 6227 6228 // Handle the memory dependencies. 6229 ScheduleData *DepDest = BundleMember->NextLoadStore; 6230 if (DepDest) { 6231 Instruction *SrcInst = BundleMember->Inst; 6232 MemoryLocation SrcLoc = getLocation(SrcInst, SLP->AA); 6233 bool SrcMayWrite = BundleMember->Inst->mayWriteToMemory(); 6234 unsigned numAliased = 0; 6235 unsigned DistToSrc = 1; 6236 6237 while (DepDest) { 6238 assert(isInSchedulingRegion(DepDest)); 6239 6240 // We have two limits to reduce the complexity: 6241 // 1) AliasedCheckLimit: It's a small limit to reduce calls to 6242 // SLP->isAliased (which is the expensive part in this loop). 6243 // 2) MaxMemDepDistance: It's for very large blocks and it aborts 6244 // the whole loop (even if the loop is fast, it's quadratic). 6245 // It's important for the loop break condition (see below) to 6246 // check this limit even between two read-only instructions. 6247 if (DistToSrc >= MaxMemDepDistance || 6248 ((SrcMayWrite || DepDest->Inst->mayWriteToMemory()) && 6249 (numAliased >= AliasedCheckLimit || 6250 SLP->isAliased(SrcLoc, SrcInst, DepDest->Inst)))) { 6251 6252 // We increment the counter only if the locations are aliased 6253 // (instead of counting all alias checks). This gives a better 6254 // balance between reduced runtime and accurate dependencies. 6255 numAliased++; 6256 6257 DepDest->MemoryDependencies.push_back(BundleMember); 6258 BundleMember->Dependencies++; 6259 ScheduleData *DestBundle = DepDest->FirstInBundle; 6260 if (!DestBundle->IsScheduled) { 6261 BundleMember->incrementUnscheduledDeps(1); 6262 } 6263 if (!DestBundle->hasValidDependencies()) { 6264 WorkList.push_back(DestBundle); 6265 } 6266 } 6267 DepDest = DepDest->NextLoadStore; 6268 6269 // Example, explaining the loop break condition: Let's assume our 6270 // starting instruction is i0 and MaxMemDepDistance = 3. 6271 // 6272 // +--------v--v--v 6273 // i0,i1,i2,i3,i4,i5,i6,i7,i8 6274 // +--------^--^--^ 6275 // 6276 // MaxMemDepDistance let us stop alias-checking at i3 and we add 6277 // dependencies from i0 to i3,i4,.. (even if they are not aliased). 6278 // Previously we already added dependencies from i3 to i6,i7,i8 6279 // (because of MaxMemDepDistance). As we added a dependency from 6280 // i0 to i3, we have transitive dependencies from i0 to i6,i7,i8 6281 // and we can abort this loop at i6. 6282 if (DistToSrc >= 2 * MaxMemDepDistance) 6283 break; 6284 DistToSrc++; 6285 } 6286 } 6287 } 6288 BundleMember = BundleMember->NextInBundle; 6289 } 6290 if (InsertInReadyList && SD->isReady()) { 6291 ReadyInsts.push_back(SD); 6292 LLVM_DEBUG(dbgs() << "SLP: gets ready on update: " << *SD->Inst 6293 << "\n"); 6294 } 6295 } 6296 } 6297 6298 void BoUpSLP::BlockScheduling::resetSchedule() { 6299 assert(ScheduleStart && 6300 "tried to reset schedule on block which has not been scheduled"); 6301 for (Instruction *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 6302 doForAllOpcodes(I, [&](ScheduleData *SD) { 6303 assert(isInSchedulingRegion(SD) && 6304 "ScheduleData not in scheduling region"); 6305 SD->IsScheduled = false; 6306 SD->resetUnscheduledDeps(); 6307 }); 6308 } 6309 ReadyInsts.clear(); 6310 } 6311 6312 void BoUpSLP::scheduleBlock(BlockScheduling *BS) { 6313 if (!BS->ScheduleStart) 6314 return; 6315 6316 LLVM_DEBUG(dbgs() << "SLP: schedule block " << BS->BB->getName() << "\n"); 6317 6318 BS->resetSchedule(); 6319 6320 // For the real scheduling we use a more sophisticated ready-list: it is 6321 // sorted by the original instruction location. This lets the final schedule 6322 // be as close as possible to the original instruction order. 6323 struct ScheduleDataCompare { 6324 bool operator()(ScheduleData *SD1, ScheduleData *SD2) const { 6325 return SD2->SchedulingPriority < SD1->SchedulingPriority; 6326 } 6327 }; 6328 std::set<ScheduleData *, ScheduleDataCompare> ReadyInsts; 6329 6330 // Ensure that all dependency data is updated and fill the ready-list with 6331 // initial instructions. 6332 int Idx = 0; 6333 int NumToSchedule = 0; 6334 for (auto *I = BS->ScheduleStart; I != BS->ScheduleEnd; 6335 I = I->getNextNode()) { 6336 BS->doForAllOpcodes(I, [this, &Idx, &NumToSchedule, BS](ScheduleData *SD) { 6337 assert((isa<InsertElementInst>(SD->Inst) || 6338 SD->isPartOfBundle() == (getTreeEntry(SD->Inst) != nullptr)) && 6339 "scheduler and vectorizer bundle mismatch"); 6340 SD->FirstInBundle->SchedulingPriority = Idx++; 6341 if (SD->isSchedulingEntity()) { 6342 BS->calculateDependencies(SD, false, this); 6343 NumToSchedule++; 6344 } 6345 }); 6346 } 6347 BS->initialFillReadyList(ReadyInsts); 6348 6349 Instruction *LastScheduledInst = BS->ScheduleEnd; 6350 6351 // Do the "real" scheduling. 6352 while (!ReadyInsts.empty()) { 6353 ScheduleData *picked = *ReadyInsts.begin(); 6354 ReadyInsts.erase(ReadyInsts.begin()); 6355 6356 // Move the scheduled instruction(s) to their dedicated places, if not 6357 // there yet. 6358 ScheduleData *BundleMember = picked; 6359 while (BundleMember) { 6360 Instruction *pickedInst = BundleMember->Inst; 6361 if (pickedInst->getNextNode() != LastScheduledInst) { 6362 BS->BB->getInstList().remove(pickedInst); 6363 BS->BB->getInstList().insert(LastScheduledInst->getIterator(), 6364 pickedInst); 6365 } 6366 LastScheduledInst = pickedInst; 6367 BundleMember = BundleMember->NextInBundle; 6368 } 6369 6370 BS->schedule(picked, ReadyInsts); 6371 NumToSchedule--; 6372 } 6373 assert(NumToSchedule == 0 && "could not schedule all instructions"); 6374 6375 // Avoid duplicate scheduling of the block. 6376 BS->ScheduleStart = nullptr; 6377 } 6378 6379 unsigned BoUpSLP::getVectorElementSize(Value *V) { 6380 // If V is a store, just return the width of the stored value (or value 6381 // truncated just before storing) without traversing the expression tree. 6382 // This is the common case. 6383 if (auto *Store = dyn_cast<StoreInst>(V)) { 6384 if (auto *Trunc = dyn_cast<TruncInst>(Store->getValueOperand())) 6385 return DL->getTypeSizeInBits(Trunc->getSrcTy()); 6386 return DL->getTypeSizeInBits(Store->getValueOperand()->getType()); 6387 } 6388 6389 if (auto *IEI = dyn_cast<InsertElementInst>(V)) 6390 return getVectorElementSize(IEI->getOperand(1)); 6391 6392 auto E = InstrElementSize.find(V); 6393 if (E != InstrElementSize.end()) 6394 return E->second; 6395 6396 // If V is not a store, we can traverse the expression tree to find loads 6397 // that feed it. The type of the loaded value may indicate a more suitable 6398 // width than V's type. We want to base the vector element size on the width 6399 // of memory operations where possible. 6400 SmallVector<std::pair<Instruction *, BasicBlock *>, 16> Worklist; 6401 SmallPtrSet<Instruction *, 16> Visited; 6402 if (auto *I = dyn_cast<Instruction>(V)) { 6403 Worklist.emplace_back(I, I->getParent()); 6404 Visited.insert(I); 6405 } 6406 6407 // Traverse the expression tree in bottom-up order looking for loads. If we 6408 // encounter an instruction we don't yet handle, we give up. 6409 auto Width = 0u; 6410 while (!Worklist.empty()) { 6411 Instruction *I; 6412 BasicBlock *Parent; 6413 std::tie(I, Parent) = Worklist.pop_back_val(); 6414 6415 // We should only be looking at scalar instructions here. If the current 6416 // instruction has a vector type, skip. 6417 auto *Ty = I->getType(); 6418 if (isa<VectorType>(Ty)) 6419 continue; 6420 6421 // If the current instruction is a load, update MaxWidth to reflect the 6422 // width of the loaded value. 6423 if (isa<LoadInst>(I) || isa<ExtractElementInst>(I) || 6424 isa<ExtractValueInst>(I)) 6425 Width = std::max<unsigned>(Width, DL->getTypeSizeInBits(Ty)); 6426 6427 // Otherwise, we need to visit the operands of the instruction. We only 6428 // handle the interesting cases from buildTree here. If an operand is an 6429 // instruction we haven't yet visited and from the same basic block as the 6430 // user or the use is a PHI node, we add it to the worklist. 6431 else if (isa<PHINode>(I) || isa<CastInst>(I) || isa<GetElementPtrInst>(I) || 6432 isa<CmpInst>(I) || isa<SelectInst>(I) || isa<BinaryOperator>(I) || 6433 isa<UnaryOperator>(I)) { 6434 for (Use &U : I->operands()) 6435 if (auto *J = dyn_cast<Instruction>(U.get())) 6436 if (Visited.insert(J).second && 6437 (isa<PHINode>(I) || J->getParent() == Parent)) 6438 Worklist.emplace_back(J, J->getParent()); 6439 } else { 6440 break; 6441 } 6442 } 6443 6444 // If we didn't encounter a memory access in the expression tree, or if we 6445 // gave up for some reason, just return the width of V. Otherwise, return the 6446 // maximum width we found. 6447 if (!Width) { 6448 if (auto *CI = dyn_cast<CmpInst>(V)) 6449 V = CI->getOperand(0); 6450 Width = DL->getTypeSizeInBits(V->getType()); 6451 } 6452 6453 for (Instruction *I : Visited) 6454 InstrElementSize[I] = Width; 6455 6456 return Width; 6457 } 6458 6459 // Determine if a value V in a vectorizable expression Expr can be demoted to a 6460 // smaller type with a truncation. We collect the values that will be demoted 6461 // in ToDemote and additional roots that require investigating in Roots. 6462 static bool collectValuesToDemote(Value *V, SmallPtrSetImpl<Value *> &Expr, 6463 SmallVectorImpl<Value *> &ToDemote, 6464 SmallVectorImpl<Value *> &Roots) { 6465 // We can always demote constants. 6466 if (isa<Constant>(V)) { 6467 ToDemote.push_back(V); 6468 return true; 6469 } 6470 6471 // If the value is not an instruction in the expression with only one use, it 6472 // cannot be demoted. 6473 auto *I = dyn_cast<Instruction>(V); 6474 if (!I || !I->hasOneUse() || !Expr.count(I)) 6475 return false; 6476 6477 switch (I->getOpcode()) { 6478 6479 // We can always demote truncations and extensions. Since truncations can 6480 // seed additional demotion, we save the truncated value. 6481 case Instruction::Trunc: 6482 Roots.push_back(I->getOperand(0)); 6483 break; 6484 case Instruction::ZExt: 6485 case Instruction::SExt: 6486 if (isa<ExtractElementInst>(I->getOperand(0)) || 6487 isa<InsertElementInst>(I->getOperand(0))) 6488 return false; 6489 break; 6490 6491 // We can demote certain binary operations if we can demote both of their 6492 // operands. 6493 case Instruction::Add: 6494 case Instruction::Sub: 6495 case Instruction::Mul: 6496 case Instruction::And: 6497 case Instruction::Or: 6498 case Instruction::Xor: 6499 if (!collectValuesToDemote(I->getOperand(0), Expr, ToDemote, Roots) || 6500 !collectValuesToDemote(I->getOperand(1), Expr, ToDemote, Roots)) 6501 return false; 6502 break; 6503 6504 // We can demote selects if we can demote their true and false values. 6505 case Instruction::Select: { 6506 SelectInst *SI = cast<SelectInst>(I); 6507 if (!collectValuesToDemote(SI->getTrueValue(), Expr, ToDemote, Roots) || 6508 !collectValuesToDemote(SI->getFalseValue(), Expr, ToDemote, Roots)) 6509 return false; 6510 break; 6511 } 6512 6513 // We can demote phis if we can demote all their incoming operands. Note that 6514 // we don't need to worry about cycles since we ensure single use above. 6515 case Instruction::PHI: { 6516 PHINode *PN = cast<PHINode>(I); 6517 for (Value *IncValue : PN->incoming_values()) 6518 if (!collectValuesToDemote(IncValue, Expr, ToDemote, Roots)) 6519 return false; 6520 break; 6521 } 6522 6523 // Otherwise, conservatively give up. 6524 default: 6525 return false; 6526 } 6527 6528 // Record the value that we can demote. 6529 ToDemote.push_back(V); 6530 return true; 6531 } 6532 6533 void BoUpSLP::computeMinimumValueSizes() { 6534 // If there are no external uses, the expression tree must be rooted by a 6535 // store. We can't demote in-memory values, so there is nothing to do here. 6536 if (ExternalUses.empty()) 6537 return; 6538 6539 // We only attempt to truncate integer expressions. 6540 auto &TreeRoot = VectorizableTree[0]->Scalars; 6541 auto *TreeRootIT = dyn_cast<IntegerType>(TreeRoot[0]->getType()); 6542 if (!TreeRootIT) 6543 return; 6544 6545 // If the expression is not rooted by a store, these roots should have 6546 // external uses. We will rely on InstCombine to rewrite the expression in 6547 // the narrower type. However, InstCombine only rewrites single-use values. 6548 // This means that if a tree entry other than a root is used externally, it 6549 // must have multiple uses and InstCombine will not rewrite it. The code 6550 // below ensures that only the roots are used externally. 6551 SmallPtrSet<Value *, 32> Expr(TreeRoot.begin(), TreeRoot.end()); 6552 for (auto &EU : ExternalUses) 6553 if (!Expr.erase(EU.Scalar)) 6554 return; 6555 if (!Expr.empty()) 6556 return; 6557 6558 // Collect the scalar values of the vectorizable expression. We will use this 6559 // context to determine which values can be demoted. If we see a truncation, 6560 // we mark it as seeding another demotion. 6561 for (auto &EntryPtr : VectorizableTree) 6562 Expr.insert(EntryPtr->Scalars.begin(), EntryPtr->Scalars.end()); 6563 6564 // Ensure the roots of the vectorizable tree don't form a cycle. They must 6565 // have a single external user that is not in the vectorizable tree. 6566 for (auto *Root : TreeRoot) 6567 if (!Root->hasOneUse() || Expr.count(*Root->user_begin())) 6568 return; 6569 6570 // Conservatively determine if we can actually truncate the roots of the 6571 // expression. Collect the values that can be demoted in ToDemote and 6572 // additional roots that require investigating in Roots. 6573 SmallVector<Value *, 32> ToDemote; 6574 SmallVector<Value *, 4> Roots; 6575 for (auto *Root : TreeRoot) 6576 if (!collectValuesToDemote(Root, Expr, ToDemote, Roots)) 6577 return; 6578 6579 // The maximum bit width required to represent all the values that can be 6580 // demoted without loss of precision. It would be safe to truncate the roots 6581 // of the expression to this width. 6582 auto MaxBitWidth = 8u; 6583 6584 // We first check if all the bits of the roots are demanded. If they're not, 6585 // we can truncate the roots to this narrower type. 6586 for (auto *Root : TreeRoot) { 6587 auto Mask = DB->getDemandedBits(cast<Instruction>(Root)); 6588 MaxBitWidth = std::max<unsigned>( 6589 Mask.getBitWidth() - Mask.countLeadingZeros(), MaxBitWidth); 6590 } 6591 6592 // True if the roots can be zero-extended back to their original type, rather 6593 // than sign-extended. We know that if the leading bits are not demanded, we 6594 // can safely zero-extend. So we initialize IsKnownPositive to True. 6595 bool IsKnownPositive = true; 6596 6597 // If all the bits of the roots are demanded, we can try a little harder to 6598 // compute a narrower type. This can happen, for example, if the roots are 6599 // getelementptr indices. InstCombine promotes these indices to the pointer 6600 // width. Thus, all their bits are technically demanded even though the 6601 // address computation might be vectorized in a smaller type. 6602 // 6603 // We start by looking at each entry that can be demoted. We compute the 6604 // maximum bit width required to store the scalar by using ValueTracking to 6605 // compute the number of high-order bits we can truncate. 6606 if (MaxBitWidth == DL->getTypeSizeInBits(TreeRoot[0]->getType()) && 6607 llvm::all_of(TreeRoot, [](Value *R) { 6608 assert(R->hasOneUse() && "Root should have only one use!"); 6609 return isa<GetElementPtrInst>(R->user_back()); 6610 })) { 6611 MaxBitWidth = 8u; 6612 6613 // Determine if the sign bit of all the roots is known to be zero. If not, 6614 // IsKnownPositive is set to False. 6615 IsKnownPositive = llvm::all_of(TreeRoot, [&](Value *R) { 6616 KnownBits Known = computeKnownBits(R, *DL); 6617 return Known.isNonNegative(); 6618 }); 6619 6620 // Determine the maximum number of bits required to store the scalar 6621 // values. 6622 for (auto *Scalar : ToDemote) { 6623 auto NumSignBits = ComputeNumSignBits(Scalar, *DL, 0, AC, nullptr, DT); 6624 auto NumTypeBits = DL->getTypeSizeInBits(Scalar->getType()); 6625 MaxBitWidth = std::max<unsigned>(NumTypeBits - NumSignBits, MaxBitWidth); 6626 } 6627 6628 // If we can't prove that the sign bit is zero, we must add one to the 6629 // maximum bit width to account for the unknown sign bit. This preserves 6630 // the existing sign bit so we can safely sign-extend the root back to the 6631 // original type. Otherwise, if we know the sign bit is zero, we will 6632 // zero-extend the root instead. 6633 // 6634 // FIXME: This is somewhat suboptimal, as there will be cases where adding 6635 // one to the maximum bit width will yield a larger-than-necessary 6636 // type. In general, we need to add an extra bit only if we can't 6637 // prove that the upper bit of the original type is equal to the 6638 // upper bit of the proposed smaller type. If these two bits are the 6639 // same (either zero or one) we know that sign-extending from the 6640 // smaller type will result in the same value. Here, since we can't 6641 // yet prove this, we are just making the proposed smaller type 6642 // larger to ensure correctness. 6643 if (!IsKnownPositive) 6644 ++MaxBitWidth; 6645 } 6646 6647 // Round MaxBitWidth up to the next power-of-two. 6648 if (!isPowerOf2_64(MaxBitWidth)) 6649 MaxBitWidth = NextPowerOf2(MaxBitWidth); 6650 6651 // If the maximum bit width we compute is less than the with of the roots' 6652 // type, we can proceed with the narrowing. Otherwise, do nothing. 6653 if (MaxBitWidth >= TreeRootIT->getBitWidth()) 6654 return; 6655 6656 // If we can truncate the root, we must collect additional values that might 6657 // be demoted as a result. That is, those seeded by truncations we will 6658 // modify. 6659 while (!Roots.empty()) 6660 collectValuesToDemote(Roots.pop_back_val(), Expr, ToDemote, Roots); 6661 6662 // Finally, map the values we can demote to the maximum bit with we computed. 6663 for (auto *Scalar : ToDemote) 6664 MinBWs[Scalar] = std::make_pair(MaxBitWidth, !IsKnownPositive); 6665 } 6666 6667 namespace { 6668 6669 /// The SLPVectorizer Pass. 6670 struct SLPVectorizer : public FunctionPass { 6671 SLPVectorizerPass Impl; 6672 6673 /// Pass identification, replacement for typeid 6674 static char ID; 6675 6676 explicit SLPVectorizer() : FunctionPass(ID) { 6677 initializeSLPVectorizerPass(*PassRegistry::getPassRegistry()); 6678 } 6679 6680 bool doInitialization(Module &M) override { 6681 return false; 6682 } 6683 6684 bool runOnFunction(Function &F) override { 6685 if (skipFunction(F)) 6686 return false; 6687 6688 auto *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 6689 auto *TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F); 6690 auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>(); 6691 auto *TLI = TLIP ? &TLIP->getTLI(F) : nullptr; 6692 auto *AA = &getAnalysis<AAResultsWrapperPass>().getAAResults(); 6693 auto *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 6694 auto *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 6695 auto *AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F); 6696 auto *DB = &getAnalysis<DemandedBitsWrapperPass>().getDemandedBits(); 6697 auto *ORE = &getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE(); 6698 6699 return Impl.runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 6700 } 6701 6702 void getAnalysisUsage(AnalysisUsage &AU) const override { 6703 FunctionPass::getAnalysisUsage(AU); 6704 AU.addRequired<AssumptionCacheTracker>(); 6705 AU.addRequired<ScalarEvolutionWrapperPass>(); 6706 AU.addRequired<AAResultsWrapperPass>(); 6707 AU.addRequired<TargetTransformInfoWrapperPass>(); 6708 AU.addRequired<LoopInfoWrapperPass>(); 6709 AU.addRequired<DominatorTreeWrapperPass>(); 6710 AU.addRequired<DemandedBitsWrapperPass>(); 6711 AU.addRequired<OptimizationRemarkEmitterWrapperPass>(); 6712 AU.addRequired<InjectTLIMappingsLegacy>(); 6713 AU.addPreserved<LoopInfoWrapperPass>(); 6714 AU.addPreserved<DominatorTreeWrapperPass>(); 6715 AU.addPreserved<AAResultsWrapperPass>(); 6716 AU.addPreserved<GlobalsAAWrapperPass>(); 6717 AU.setPreservesCFG(); 6718 } 6719 }; 6720 6721 } // end anonymous namespace 6722 6723 PreservedAnalyses SLPVectorizerPass::run(Function &F, FunctionAnalysisManager &AM) { 6724 auto *SE = &AM.getResult<ScalarEvolutionAnalysis>(F); 6725 auto *TTI = &AM.getResult<TargetIRAnalysis>(F); 6726 auto *TLI = AM.getCachedResult<TargetLibraryAnalysis>(F); 6727 auto *AA = &AM.getResult<AAManager>(F); 6728 auto *LI = &AM.getResult<LoopAnalysis>(F); 6729 auto *DT = &AM.getResult<DominatorTreeAnalysis>(F); 6730 auto *AC = &AM.getResult<AssumptionAnalysis>(F); 6731 auto *DB = &AM.getResult<DemandedBitsAnalysis>(F); 6732 auto *ORE = &AM.getResult<OptimizationRemarkEmitterAnalysis>(F); 6733 6734 bool Changed = runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 6735 if (!Changed) 6736 return PreservedAnalyses::all(); 6737 6738 PreservedAnalyses PA; 6739 PA.preserveSet<CFGAnalyses>(); 6740 return PA; 6741 } 6742 6743 bool SLPVectorizerPass::runImpl(Function &F, ScalarEvolution *SE_, 6744 TargetTransformInfo *TTI_, 6745 TargetLibraryInfo *TLI_, AAResults *AA_, 6746 LoopInfo *LI_, DominatorTree *DT_, 6747 AssumptionCache *AC_, DemandedBits *DB_, 6748 OptimizationRemarkEmitter *ORE_) { 6749 if (!RunSLPVectorization) 6750 return false; 6751 SE = SE_; 6752 TTI = TTI_; 6753 TLI = TLI_; 6754 AA = AA_; 6755 LI = LI_; 6756 DT = DT_; 6757 AC = AC_; 6758 DB = DB_; 6759 DL = &F.getParent()->getDataLayout(); 6760 6761 Stores.clear(); 6762 GEPs.clear(); 6763 bool Changed = false; 6764 6765 // If the target claims to have no vector registers don't attempt 6766 // vectorization. 6767 if (!TTI->getNumberOfRegisters(TTI->getRegisterClassForType(true))) 6768 return false; 6769 6770 // Don't vectorize when the attribute NoImplicitFloat is used. 6771 if (F.hasFnAttribute(Attribute::NoImplicitFloat)) 6772 return false; 6773 6774 LLVM_DEBUG(dbgs() << "SLP: Analyzing blocks in " << F.getName() << ".\n"); 6775 6776 // Use the bottom up slp vectorizer to construct chains that start with 6777 // store instructions. 6778 BoUpSLP R(&F, SE, TTI, TLI, AA, LI, DT, AC, DB, DL, ORE_); 6779 6780 // A general note: the vectorizer must use BoUpSLP::eraseInstruction() to 6781 // delete instructions. 6782 6783 // Update DFS numbers now so that we can use them for ordering. 6784 DT->updateDFSNumbers(); 6785 6786 // Scan the blocks in the function in post order. 6787 for (auto BB : post_order(&F.getEntryBlock())) { 6788 collectSeedInstructions(BB); 6789 6790 // Vectorize trees that end at stores. 6791 if (!Stores.empty()) { 6792 LLVM_DEBUG(dbgs() << "SLP: Found stores for " << Stores.size() 6793 << " underlying objects.\n"); 6794 Changed |= vectorizeStoreChains(R); 6795 } 6796 6797 // Vectorize trees that end at reductions. 6798 Changed |= vectorizeChainsInBlock(BB, R); 6799 6800 // Vectorize the index computations of getelementptr instructions. This 6801 // is primarily intended to catch gather-like idioms ending at 6802 // non-consecutive loads. 6803 if (!GEPs.empty()) { 6804 LLVM_DEBUG(dbgs() << "SLP: Found GEPs for " << GEPs.size() 6805 << " underlying objects.\n"); 6806 Changed |= vectorizeGEPIndices(BB, R); 6807 } 6808 } 6809 6810 if (Changed) { 6811 R.optimizeGatherSequence(); 6812 LLVM_DEBUG(dbgs() << "SLP: vectorized \"" << F.getName() << "\"\n"); 6813 } 6814 return Changed; 6815 } 6816 6817 /// Order may have elements assigned special value (size) which is out of 6818 /// bounds. Such indices only appear on places which correspond to undef values 6819 /// (see canReuseExtract for details) and used in order to avoid undef values 6820 /// have effect on operands ordering. 6821 /// The first loop below simply finds all unused indices and then the next loop 6822 /// nest assigns these indices for undef values positions. 6823 /// As an example below Order has two undef positions and they have assigned 6824 /// values 3 and 7 respectively: 6825 /// before: 6 9 5 4 9 2 1 0 6826 /// after: 6 3 5 4 7 2 1 0 6827 /// \returns Fixed ordering. 6828 static BoUpSLP::OrdersType fixupOrderingIndices(ArrayRef<unsigned> Order) { 6829 BoUpSLP::OrdersType NewOrder(Order.begin(), Order.end()); 6830 const unsigned Sz = NewOrder.size(); 6831 SmallBitVector UsedIndices(Sz); 6832 SmallVector<int> MaskedIndices; 6833 for (int I = 0, E = NewOrder.size(); I < E; ++I) { 6834 if (NewOrder[I] < Sz) 6835 UsedIndices.set(NewOrder[I]); 6836 else 6837 MaskedIndices.push_back(I); 6838 } 6839 if (MaskedIndices.empty()) 6840 return NewOrder; 6841 SmallVector<int> AvailableIndices(MaskedIndices.size()); 6842 unsigned Cnt = 0; 6843 int Idx = UsedIndices.find_first(); 6844 do { 6845 AvailableIndices[Cnt] = Idx; 6846 Idx = UsedIndices.find_next(Idx); 6847 ++Cnt; 6848 } while (Idx > 0); 6849 assert(Cnt == MaskedIndices.size() && "Non-synced masked/available indices."); 6850 for (int I = 0, E = MaskedIndices.size(); I < E; ++I) 6851 NewOrder[MaskedIndices[I]] = AvailableIndices[I]; 6852 return NewOrder; 6853 } 6854 6855 bool SLPVectorizerPass::vectorizeStoreChain(ArrayRef<Value *> Chain, BoUpSLP &R, 6856 unsigned Idx) { 6857 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " << Chain.size() 6858 << "\n"); 6859 const unsigned Sz = R.getVectorElementSize(Chain[0]); 6860 const unsigned MinVF = R.getMinVecRegSize() / Sz; 6861 unsigned VF = Chain.size(); 6862 6863 if (!isPowerOf2_32(Sz) || !isPowerOf2_32(VF) || VF < 2 || VF < MinVF) 6864 return false; 6865 6866 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << VF << " stores at offset " << Idx 6867 << "\n"); 6868 6869 R.buildTree(Chain); 6870 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 6871 // TODO: Handle orders of size less than number of elements in the vector. 6872 if (Order && Order->size() == Chain.size()) { 6873 // TODO: reorder tree nodes without tree rebuilding. 6874 SmallVector<Value *, 4> ReorderedOps(Chain.size()); 6875 transform(fixupOrderingIndices(*Order), ReorderedOps.begin(), 6876 [Chain](const unsigned Idx) { return Chain[Idx]; }); 6877 R.buildTree(ReorderedOps); 6878 } 6879 if (R.isTreeTinyAndNotFullyVectorizable()) 6880 return false; 6881 if (R.isLoadCombineCandidate()) 6882 return false; 6883 6884 R.computeMinimumValueSizes(); 6885 6886 InstructionCost Cost = R.getTreeCost(); 6887 6888 LLVM_DEBUG(dbgs() << "SLP: Found cost = " << Cost << " for VF =" << VF << "\n"); 6889 if (Cost < -SLPCostThreshold) { 6890 LLVM_DEBUG(dbgs() << "SLP: Decided to vectorize cost = " << Cost << "\n"); 6891 6892 using namespace ore; 6893 6894 R.getORE()->emit(OptimizationRemark(SV_NAME, "StoresVectorized", 6895 cast<StoreInst>(Chain[0])) 6896 << "Stores SLP vectorized with cost " << NV("Cost", Cost) 6897 << " and with tree size " 6898 << NV("TreeSize", R.getTreeSize())); 6899 6900 R.vectorizeTree(); 6901 return true; 6902 } 6903 6904 return false; 6905 } 6906 6907 bool SLPVectorizerPass::vectorizeStores(ArrayRef<StoreInst *> Stores, 6908 BoUpSLP &R) { 6909 // We may run into multiple chains that merge into a single chain. We mark the 6910 // stores that we vectorized so that we don't visit the same store twice. 6911 BoUpSLP::ValueSet VectorizedStores; 6912 bool Changed = false; 6913 6914 int E = Stores.size(); 6915 SmallBitVector Tails(E, false); 6916 int MaxIter = MaxStoreLookup.getValue(); 6917 SmallVector<std::pair<int, int>, 16> ConsecutiveChain( 6918 E, std::make_pair(E, INT_MAX)); 6919 SmallVector<SmallBitVector, 4> CheckedPairs(E, SmallBitVector(E, false)); 6920 int IterCnt; 6921 auto &&FindConsecutiveAccess = [this, &Stores, &Tails, &IterCnt, MaxIter, 6922 &CheckedPairs, 6923 &ConsecutiveChain](int K, int Idx) { 6924 if (IterCnt >= MaxIter) 6925 return true; 6926 if (CheckedPairs[Idx].test(K)) 6927 return ConsecutiveChain[K].second == 1 && 6928 ConsecutiveChain[K].first == Idx; 6929 ++IterCnt; 6930 CheckedPairs[Idx].set(K); 6931 CheckedPairs[K].set(Idx); 6932 Optional<int> Diff = getPointersDiff( 6933 Stores[K]->getValueOperand()->getType(), Stores[K]->getPointerOperand(), 6934 Stores[Idx]->getValueOperand()->getType(), 6935 Stores[Idx]->getPointerOperand(), *DL, *SE, /*StrictCheck=*/true); 6936 if (!Diff || *Diff == 0) 6937 return false; 6938 int Val = *Diff; 6939 if (Val < 0) { 6940 if (ConsecutiveChain[Idx].second > -Val) { 6941 Tails.set(K); 6942 ConsecutiveChain[Idx] = std::make_pair(K, -Val); 6943 } 6944 return false; 6945 } 6946 if (ConsecutiveChain[K].second <= Val) 6947 return false; 6948 6949 Tails.set(Idx); 6950 ConsecutiveChain[K] = std::make_pair(Idx, Val); 6951 return Val == 1; 6952 }; 6953 // Do a quadratic search on all of the given stores in reverse order and find 6954 // all of the pairs of stores that follow each other. 6955 for (int Idx = E - 1; Idx >= 0; --Idx) { 6956 // If a store has multiple consecutive store candidates, search according 6957 // to the sequence: Idx-1, Idx+1, Idx-2, Idx+2, ... 6958 // This is because usually pairing with immediate succeeding or preceding 6959 // candidate create the best chance to find slp vectorization opportunity. 6960 const int MaxLookDepth = std::max(E - Idx, Idx + 1); 6961 IterCnt = 0; 6962 for (int Offset = 1, F = MaxLookDepth; Offset < F; ++Offset) 6963 if ((Idx >= Offset && FindConsecutiveAccess(Idx - Offset, Idx)) || 6964 (Idx + Offset < E && FindConsecutiveAccess(Idx + Offset, Idx))) 6965 break; 6966 } 6967 6968 // Tracks if we tried to vectorize stores starting from the given tail 6969 // already. 6970 SmallBitVector TriedTails(E, false); 6971 // For stores that start but don't end a link in the chain: 6972 for (int Cnt = E; Cnt > 0; --Cnt) { 6973 int I = Cnt - 1; 6974 if (ConsecutiveChain[I].first == E || Tails.test(I)) 6975 continue; 6976 // We found a store instr that starts a chain. Now follow the chain and try 6977 // to vectorize it. 6978 BoUpSLP::ValueList Operands; 6979 // Collect the chain into a list. 6980 while (I != E && !VectorizedStores.count(Stores[I])) { 6981 Operands.push_back(Stores[I]); 6982 Tails.set(I); 6983 if (ConsecutiveChain[I].second != 1) { 6984 // Mark the new end in the chain and go back, if required. It might be 6985 // required if the original stores come in reversed order, for example. 6986 if (ConsecutiveChain[I].first != E && 6987 Tails.test(ConsecutiveChain[I].first) && !TriedTails.test(I) && 6988 !VectorizedStores.count(Stores[ConsecutiveChain[I].first])) { 6989 TriedTails.set(I); 6990 Tails.reset(ConsecutiveChain[I].first); 6991 if (Cnt < ConsecutiveChain[I].first + 2) 6992 Cnt = ConsecutiveChain[I].first + 2; 6993 } 6994 break; 6995 } 6996 // Move to the next value in the chain. 6997 I = ConsecutiveChain[I].first; 6998 } 6999 assert(!Operands.empty() && "Expected non-empty list of stores."); 7000 7001 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 7002 unsigned EltSize = R.getVectorElementSize(Operands[0]); 7003 unsigned MaxElts = llvm::PowerOf2Floor(MaxVecRegSize / EltSize); 7004 7005 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / EltSize); 7006 unsigned MaxVF = std::min(R.getMaximumVF(EltSize, Instruction::Store), 7007 MaxElts); 7008 7009 // FIXME: Is division-by-2 the correct step? Should we assert that the 7010 // register size is a power-of-2? 7011 unsigned StartIdx = 0; 7012 for (unsigned Size = MaxVF; Size >= MinVF; Size /= 2) { 7013 for (unsigned Cnt = StartIdx, E = Operands.size(); Cnt + Size <= E;) { 7014 ArrayRef<Value *> Slice = makeArrayRef(Operands).slice(Cnt, Size); 7015 if (!VectorizedStores.count(Slice.front()) && 7016 !VectorizedStores.count(Slice.back()) && 7017 vectorizeStoreChain(Slice, R, Cnt)) { 7018 // Mark the vectorized stores so that we don't vectorize them again. 7019 VectorizedStores.insert(Slice.begin(), Slice.end()); 7020 Changed = true; 7021 // If we vectorized initial block, no need to try to vectorize it 7022 // again. 7023 if (Cnt == StartIdx) 7024 StartIdx += Size; 7025 Cnt += Size; 7026 continue; 7027 } 7028 ++Cnt; 7029 } 7030 // Check if the whole array was vectorized already - exit. 7031 if (StartIdx >= Operands.size()) 7032 break; 7033 } 7034 } 7035 7036 return Changed; 7037 } 7038 7039 void SLPVectorizerPass::collectSeedInstructions(BasicBlock *BB) { 7040 // Initialize the collections. We will make a single pass over the block. 7041 Stores.clear(); 7042 GEPs.clear(); 7043 7044 // Visit the store and getelementptr instructions in BB and organize them in 7045 // Stores and GEPs according to the underlying objects of their pointer 7046 // operands. 7047 for (Instruction &I : *BB) { 7048 // Ignore store instructions that are volatile or have a pointer operand 7049 // that doesn't point to a scalar type. 7050 if (auto *SI = dyn_cast<StoreInst>(&I)) { 7051 if (!SI->isSimple()) 7052 continue; 7053 if (!isValidElementType(SI->getValueOperand()->getType())) 7054 continue; 7055 Stores[getUnderlyingObject(SI->getPointerOperand())].push_back(SI); 7056 } 7057 7058 // Ignore getelementptr instructions that have more than one index, a 7059 // constant index, or a pointer operand that doesn't point to a scalar 7060 // type. 7061 else if (auto *GEP = dyn_cast<GetElementPtrInst>(&I)) { 7062 auto Idx = GEP->idx_begin()->get(); 7063 if (GEP->getNumIndices() > 1 || isa<Constant>(Idx)) 7064 continue; 7065 if (!isValidElementType(Idx->getType())) 7066 continue; 7067 if (GEP->getType()->isVectorTy()) 7068 continue; 7069 GEPs[GEP->getPointerOperand()].push_back(GEP); 7070 } 7071 } 7072 } 7073 7074 bool SLPVectorizerPass::tryToVectorizePair(Value *A, Value *B, BoUpSLP &R) { 7075 if (!A || !B) 7076 return false; 7077 Value *VL[] = {A, B}; 7078 return tryToVectorizeList(VL, R, /*AllowReorder=*/true); 7079 } 7080 7081 bool SLPVectorizerPass::tryToVectorizeList(ArrayRef<Value *> VL, BoUpSLP &R, 7082 bool AllowReorder) { 7083 if (VL.size() < 2) 7084 return false; 7085 7086 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize a list of length = " 7087 << VL.size() << ".\n"); 7088 7089 // Check that all of the parts are instructions of the same type, 7090 // we permit an alternate opcode via InstructionsState. 7091 InstructionsState S = getSameOpcode(VL); 7092 if (!S.getOpcode()) 7093 return false; 7094 7095 Instruction *I0 = cast<Instruction>(S.OpValue); 7096 // Make sure invalid types (including vector type) are rejected before 7097 // determining vectorization factor for scalar instructions. 7098 for (Value *V : VL) { 7099 Type *Ty = V->getType(); 7100 if (!isa<InsertElementInst>(V) && !isValidElementType(Ty)) { 7101 // NOTE: the following will give user internal llvm type name, which may 7102 // not be useful. 7103 R.getORE()->emit([&]() { 7104 std::string type_str; 7105 llvm::raw_string_ostream rso(type_str); 7106 Ty->print(rso); 7107 return OptimizationRemarkMissed(SV_NAME, "UnsupportedType", I0) 7108 << "Cannot SLP vectorize list: type " 7109 << rso.str() + " is unsupported by vectorizer"; 7110 }); 7111 return false; 7112 } 7113 } 7114 7115 unsigned Sz = R.getVectorElementSize(I0); 7116 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / Sz); 7117 unsigned MaxVF = std::max<unsigned>(PowerOf2Floor(VL.size()), MinVF); 7118 MaxVF = std::min(R.getMaximumVF(Sz, S.getOpcode()), MaxVF); 7119 if (MaxVF < 2) { 7120 R.getORE()->emit([&]() { 7121 return OptimizationRemarkMissed(SV_NAME, "SmallVF", I0) 7122 << "Cannot SLP vectorize list: vectorization factor " 7123 << "less than 2 is not supported"; 7124 }); 7125 return false; 7126 } 7127 7128 bool Changed = false; 7129 bool CandidateFound = false; 7130 InstructionCost MinCost = SLPCostThreshold.getValue(); 7131 Type *ScalarTy = VL[0]->getType(); 7132 if (auto *IE = dyn_cast<InsertElementInst>(VL[0])) 7133 ScalarTy = IE->getOperand(1)->getType(); 7134 7135 unsigned NextInst = 0, MaxInst = VL.size(); 7136 for (unsigned VF = MaxVF; NextInst + 1 < MaxInst && VF >= MinVF; VF /= 2) { 7137 // No actual vectorization should happen, if number of parts is the same as 7138 // provided vectorization factor (i.e. the scalar type is used for vector 7139 // code during codegen). 7140 auto *VecTy = FixedVectorType::get(ScalarTy, VF); 7141 if (TTI->getNumberOfParts(VecTy) == VF) 7142 continue; 7143 for (unsigned I = NextInst; I < MaxInst; ++I) { 7144 unsigned OpsWidth = 0; 7145 7146 if (I + VF > MaxInst) 7147 OpsWidth = MaxInst - I; 7148 else 7149 OpsWidth = VF; 7150 7151 if (!isPowerOf2_32(OpsWidth)) 7152 continue; 7153 7154 if ((VF > MinVF && OpsWidth <= VF / 2) || (VF == MinVF && OpsWidth < 2)) 7155 break; 7156 7157 ArrayRef<Value *> Ops = VL.slice(I, OpsWidth); 7158 // Check that a previous iteration of this loop did not delete the Value. 7159 if (llvm::any_of(Ops, [&R](Value *V) { 7160 auto *I = dyn_cast<Instruction>(V); 7161 return I && R.isDeleted(I); 7162 })) 7163 continue; 7164 7165 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << OpsWidth << " operations " 7166 << "\n"); 7167 7168 R.buildTree(Ops); 7169 if (AllowReorder) { 7170 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 7171 if (Order) { 7172 // TODO: reorder tree nodes without tree rebuilding. 7173 SmallVector<Value *, 4> ReorderedOps(Ops.size()); 7174 transform(fixupOrderingIndices(*Order), ReorderedOps.begin(), 7175 [Ops](const unsigned Idx) { return Ops[Idx]; }); 7176 R.buildTree(ReorderedOps); 7177 } 7178 } 7179 if (R.isTreeTinyAndNotFullyVectorizable()) 7180 continue; 7181 7182 R.computeMinimumValueSizes(); 7183 InstructionCost Cost = R.getTreeCost(); 7184 CandidateFound = true; 7185 MinCost = std::min(MinCost, Cost); 7186 7187 if (Cost < -SLPCostThreshold) { 7188 LLVM_DEBUG(dbgs() << "SLP: Vectorizing list at cost:" << Cost << ".\n"); 7189 R.getORE()->emit(OptimizationRemark(SV_NAME, "VectorizedList", 7190 cast<Instruction>(Ops[0])) 7191 << "SLP vectorized with cost " << ore::NV("Cost", Cost) 7192 << " and with tree size " 7193 << ore::NV("TreeSize", R.getTreeSize())); 7194 7195 R.vectorizeTree(); 7196 // Move to the next bundle. 7197 I += VF - 1; 7198 NextInst = I + 1; 7199 Changed = true; 7200 } 7201 } 7202 } 7203 7204 if (!Changed && CandidateFound) { 7205 R.getORE()->emit([&]() { 7206 return OptimizationRemarkMissed(SV_NAME, "NotBeneficial", I0) 7207 << "List vectorization was possible but not beneficial with cost " 7208 << ore::NV("Cost", MinCost) << " >= " 7209 << ore::NV("Treshold", -SLPCostThreshold); 7210 }); 7211 } else if (!Changed) { 7212 R.getORE()->emit([&]() { 7213 return OptimizationRemarkMissed(SV_NAME, "NotPossible", I0) 7214 << "Cannot SLP vectorize list: vectorization was impossible" 7215 << " with available vectorization factors"; 7216 }); 7217 } 7218 return Changed; 7219 } 7220 7221 bool SLPVectorizerPass::tryToVectorize(Instruction *I, BoUpSLP &R) { 7222 if (!I) 7223 return false; 7224 7225 if (!isa<BinaryOperator>(I) && !isa<CmpInst>(I)) 7226 return false; 7227 7228 Value *P = I->getParent(); 7229 7230 // Vectorize in current basic block only. 7231 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 7232 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 7233 if (!Op0 || !Op1 || Op0->getParent() != P || Op1->getParent() != P) 7234 return false; 7235 7236 // Try to vectorize V. 7237 if (tryToVectorizePair(Op0, Op1, R)) 7238 return true; 7239 7240 auto *A = dyn_cast<BinaryOperator>(Op0); 7241 auto *B = dyn_cast<BinaryOperator>(Op1); 7242 // Try to skip B. 7243 if (B && B->hasOneUse()) { 7244 auto *B0 = dyn_cast<BinaryOperator>(B->getOperand(0)); 7245 auto *B1 = dyn_cast<BinaryOperator>(B->getOperand(1)); 7246 if (B0 && B0->getParent() == P && tryToVectorizePair(A, B0, R)) 7247 return true; 7248 if (B1 && B1->getParent() == P && tryToVectorizePair(A, B1, R)) 7249 return true; 7250 } 7251 7252 // Try to skip A. 7253 if (A && A->hasOneUse()) { 7254 auto *A0 = dyn_cast<BinaryOperator>(A->getOperand(0)); 7255 auto *A1 = dyn_cast<BinaryOperator>(A->getOperand(1)); 7256 if (A0 && A0->getParent() == P && tryToVectorizePair(A0, B, R)) 7257 return true; 7258 if (A1 && A1->getParent() == P && tryToVectorizePair(A1, B, R)) 7259 return true; 7260 } 7261 return false; 7262 } 7263 7264 namespace { 7265 7266 /// Model horizontal reductions. 7267 /// 7268 /// A horizontal reduction is a tree of reduction instructions that has values 7269 /// that can be put into a vector as its leaves. For example: 7270 /// 7271 /// mul mul mul mul 7272 /// \ / \ / 7273 /// + + 7274 /// \ / 7275 /// + 7276 /// This tree has "mul" as its leaf values and "+" as its reduction 7277 /// instructions. A reduction can feed into a store or a binary operation 7278 /// feeding a phi. 7279 /// ... 7280 /// \ / 7281 /// + 7282 /// | 7283 /// phi += 7284 /// 7285 /// Or: 7286 /// ... 7287 /// \ / 7288 /// + 7289 /// | 7290 /// *p = 7291 /// 7292 class HorizontalReduction { 7293 using ReductionOpsType = SmallVector<Value *, 16>; 7294 using ReductionOpsListType = SmallVector<ReductionOpsType, 2>; 7295 ReductionOpsListType ReductionOps; 7296 SmallVector<Value *, 32> ReducedVals; 7297 // Use map vector to make stable output. 7298 MapVector<Instruction *, Value *> ExtraArgs; 7299 WeakTrackingVH ReductionRoot; 7300 /// The type of reduction operation. 7301 RecurKind RdxKind; 7302 7303 const unsigned INVALID_OPERAND_INDEX = std::numeric_limits<unsigned>::max(); 7304 7305 static bool isCmpSelMinMax(Instruction *I) { 7306 return match(I, m_Select(m_Cmp(), m_Value(), m_Value())) && 7307 RecurrenceDescriptor::isMinMaxRecurrenceKind(getRdxKind(I)); 7308 } 7309 7310 // And/or are potentially poison-safe logical patterns like: 7311 // select x, y, false 7312 // select x, true, y 7313 static bool isBoolLogicOp(Instruction *I) { 7314 return match(I, m_LogicalAnd(m_Value(), m_Value())) || 7315 match(I, m_LogicalOr(m_Value(), m_Value())); 7316 } 7317 7318 /// Checks if instruction is associative and can be vectorized. 7319 static bool isVectorizable(RecurKind Kind, Instruction *I) { 7320 if (Kind == RecurKind::None) 7321 return false; 7322 7323 // Integer ops that map to select instructions or intrinsics are fine. 7324 if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(Kind) || 7325 isBoolLogicOp(I)) 7326 return true; 7327 7328 if (Kind == RecurKind::FMax || Kind == RecurKind::FMin) { 7329 // FP min/max are associative except for NaN and -0.0. We do not 7330 // have to rule out -0.0 here because the intrinsic semantics do not 7331 // specify a fixed result for it. 7332 return I->getFastMathFlags().noNaNs(); 7333 } 7334 7335 return I->isAssociative(); 7336 } 7337 7338 static Value *getRdxOperand(Instruction *I, unsigned Index) { 7339 // Poison-safe 'or' takes the form: select X, true, Y 7340 // To make that work with the normal operand processing, we skip the 7341 // true value operand. 7342 // TODO: Change the code and data structures to handle this without a hack. 7343 if (getRdxKind(I) == RecurKind::Or && isa<SelectInst>(I) && Index == 1) 7344 return I->getOperand(2); 7345 return I->getOperand(Index); 7346 } 7347 7348 /// Checks if the ParentStackElem.first should be marked as a reduction 7349 /// operation with an extra argument or as extra argument itself. 7350 void markExtraArg(std::pair<Instruction *, unsigned> &ParentStackElem, 7351 Value *ExtraArg) { 7352 if (ExtraArgs.count(ParentStackElem.first)) { 7353 ExtraArgs[ParentStackElem.first] = nullptr; 7354 // We ran into something like: 7355 // ParentStackElem.first = ExtraArgs[ParentStackElem.first] + ExtraArg. 7356 // The whole ParentStackElem.first should be considered as an extra value 7357 // in this case. 7358 // Do not perform analysis of remaining operands of ParentStackElem.first 7359 // instruction, this whole instruction is an extra argument. 7360 ParentStackElem.second = INVALID_OPERAND_INDEX; 7361 } else { 7362 // We ran into something like: 7363 // ParentStackElem.first += ... + ExtraArg + ... 7364 ExtraArgs[ParentStackElem.first] = ExtraArg; 7365 } 7366 } 7367 7368 /// Creates reduction operation with the current opcode. 7369 static Value *createOp(IRBuilder<> &Builder, RecurKind Kind, Value *LHS, 7370 Value *RHS, const Twine &Name, bool UseSelect) { 7371 unsigned RdxOpcode = RecurrenceDescriptor::getOpcode(Kind); 7372 switch (Kind) { 7373 case RecurKind::Add: 7374 case RecurKind::Mul: 7375 case RecurKind::Or: 7376 case RecurKind::And: 7377 case RecurKind::Xor: 7378 case RecurKind::FAdd: 7379 case RecurKind::FMul: 7380 return Builder.CreateBinOp((Instruction::BinaryOps)RdxOpcode, LHS, RHS, 7381 Name); 7382 case RecurKind::FMax: 7383 return Builder.CreateBinaryIntrinsic(Intrinsic::maxnum, LHS, RHS); 7384 case RecurKind::FMin: 7385 return Builder.CreateBinaryIntrinsic(Intrinsic::minnum, LHS, RHS); 7386 case RecurKind::SMax: 7387 if (UseSelect) { 7388 Value *Cmp = Builder.CreateICmpSGT(LHS, RHS, Name); 7389 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 7390 } 7391 return Builder.CreateBinaryIntrinsic(Intrinsic::smax, LHS, RHS); 7392 case RecurKind::SMin: 7393 if (UseSelect) { 7394 Value *Cmp = Builder.CreateICmpSLT(LHS, RHS, Name); 7395 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 7396 } 7397 return Builder.CreateBinaryIntrinsic(Intrinsic::smin, LHS, RHS); 7398 case RecurKind::UMax: 7399 if (UseSelect) { 7400 Value *Cmp = Builder.CreateICmpUGT(LHS, RHS, Name); 7401 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 7402 } 7403 return Builder.CreateBinaryIntrinsic(Intrinsic::umax, LHS, RHS); 7404 case RecurKind::UMin: 7405 if (UseSelect) { 7406 Value *Cmp = Builder.CreateICmpULT(LHS, RHS, Name); 7407 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 7408 } 7409 return Builder.CreateBinaryIntrinsic(Intrinsic::umin, LHS, RHS); 7410 default: 7411 llvm_unreachable("Unknown reduction operation."); 7412 } 7413 } 7414 7415 /// Creates reduction operation with the current opcode with the IR flags 7416 /// from \p ReductionOps. 7417 static Value *createOp(IRBuilder<> &Builder, RecurKind RdxKind, Value *LHS, 7418 Value *RHS, const Twine &Name, 7419 const ReductionOpsListType &ReductionOps) { 7420 bool UseSelect = ReductionOps.size() == 2; 7421 assert((!UseSelect || isa<SelectInst>(ReductionOps[1][0])) && 7422 "Expected cmp + select pairs for reduction"); 7423 Value *Op = createOp(Builder, RdxKind, LHS, RHS, Name, UseSelect); 7424 if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(RdxKind)) { 7425 if (auto *Sel = dyn_cast<SelectInst>(Op)) { 7426 propagateIRFlags(Sel->getCondition(), ReductionOps[0]); 7427 propagateIRFlags(Op, ReductionOps[1]); 7428 return Op; 7429 } 7430 } 7431 propagateIRFlags(Op, ReductionOps[0]); 7432 return Op; 7433 } 7434 7435 /// Creates reduction operation with the current opcode with the IR flags 7436 /// from \p I. 7437 static Value *createOp(IRBuilder<> &Builder, RecurKind RdxKind, Value *LHS, 7438 Value *RHS, const Twine &Name, Instruction *I) { 7439 auto *SelI = dyn_cast<SelectInst>(I); 7440 Value *Op = createOp(Builder, RdxKind, LHS, RHS, Name, SelI != nullptr); 7441 if (SelI && RecurrenceDescriptor::isIntMinMaxRecurrenceKind(RdxKind)) { 7442 if (auto *Sel = dyn_cast<SelectInst>(Op)) 7443 propagateIRFlags(Sel->getCondition(), SelI->getCondition()); 7444 } 7445 propagateIRFlags(Op, I); 7446 return Op; 7447 } 7448 7449 static RecurKind getRdxKind(Instruction *I) { 7450 assert(I && "Expected instruction for reduction matching"); 7451 TargetTransformInfo::ReductionFlags RdxFlags; 7452 if (match(I, m_Add(m_Value(), m_Value()))) 7453 return RecurKind::Add; 7454 if (match(I, m_Mul(m_Value(), m_Value()))) 7455 return RecurKind::Mul; 7456 if (match(I, m_And(m_Value(), m_Value())) || 7457 match(I, m_LogicalAnd(m_Value(), m_Value()))) 7458 return RecurKind::And; 7459 if (match(I, m_Or(m_Value(), m_Value())) || 7460 match(I, m_LogicalOr(m_Value(), m_Value()))) 7461 return RecurKind::Or; 7462 if (match(I, m_Xor(m_Value(), m_Value()))) 7463 return RecurKind::Xor; 7464 if (match(I, m_FAdd(m_Value(), m_Value()))) 7465 return RecurKind::FAdd; 7466 if (match(I, m_FMul(m_Value(), m_Value()))) 7467 return RecurKind::FMul; 7468 7469 if (match(I, m_Intrinsic<Intrinsic::maxnum>(m_Value(), m_Value()))) 7470 return RecurKind::FMax; 7471 if (match(I, m_Intrinsic<Intrinsic::minnum>(m_Value(), m_Value()))) 7472 return RecurKind::FMin; 7473 7474 // This matches either cmp+select or intrinsics. SLP is expected to handle 7475 // either form. 7476 // TODO: If we are canonicalizing to intrinsics, we can remove several 7477 // special-case paths that deal with selects. 7478 if (match(I, m_SMax(m_Value(), m_Value()))) 7479 return RecurKind::SMax; 7480 if (match(I, m_SMin(m_Value(), m_Value()))) 7481 return RecurKind::SMin; 7482 if (match(I, m_UMax(m_Value(), m_Value()))) 7483 return RecurKind::UMax; 7484 if (match(I, m_UMin(m_Value(), m_Value()))) 7485 return RecurKind::UMin; 7486 7487 if (auto *Select = dyn_cast<SelectInst>(I)) { 7488 // Try harder: look for min/max pattern based on instructions producing 7489 // same values such as: select ((cmp Inst1, Inst2), Inst1, Inst2). 7490 // During the intermediate stages of SLP, it's very common to have 7491 // pattern like this (since optimizeGatherSequence is run only once 7492 // at the end): 7493 // %1 = extractelement <2 x i32> %a, i32 0 7494 // %2 = extractelement <2 x i32> %a, i32 1 7495 // %cond = icmp sgt i32 %1, %2 7496 // %3 = extractelement <2 x i32> %a, i32 0 7497 // %4 = extractelement <2 x i32> %a, i32 1 7498 // %select = select i1 %cond, i32 %3, i32 %4 7499 CmpInst::Predicate Pred; 7500 Instruction *L1; 7501 Instruction *L2; 7502 7503 Value *LHS = Select->getTrueValue(); 7504 Value *RHS = Select->getFalseValue(); 7505 Value *Cond = Select->getCondition(); 7506 7507 // TODO: Support inverse predicates. 7508 if (match(Cond, m_Cmp(Pred, m_Specific(LHS), m_Instruction(L2)))) { 7509 if (!isa<ExtractElementInst>(RHS) || 7510 !L2->isIdenticalTo(cast<Instruction>(RHS))) 7511 return RecurKind::None; 7512 } else if (match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Specific(RHS)))) { 7513 if (!isa<ExtractElementInst>(LHS) || 7514 !L1->isIdenticalTo(cast<Instruction>(LHS))) 7515 return RecurKind::None; 7516 } else { 7517 if (!isa<ExtractElementInst>(LHS) || !isa<ExtractElementInst>(RHS)) 7518 return RecurKind::None; 7519 if (!match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Instruction(L2))) || 7520 !L1->isIdenticalTo(cast<Instruction>(LHS)) || 7521 !L2->isIdenticalTo(cast<Instruction>(RHS))) 7522 return RecurKind::None; 7523 } 7524 7525 TargetTransformInfo::ReductionFlags RdxFlags; 7526 switch (Pred) { 7527 default: 7528 return RecurKind::None; 7529 case CmpInst::ICMP_SGT: 7530 case CmpInst::ICMP_SGE: 7531 return RecurKind::SMax; 7532 case CmpInst::ICMP_SLT: 7533 case CmpInst::ICMP_SLE: 7534 return RecurKind::SMin; 7535 case CmpInst::ICMP_UGT: 7536 case CmpInst::ICMP_UGE: 7537 return RecurKind::UMax; 7538 case CmpInst::ICMP_ULT: 7539 case CmpInst::ICMP_ULE: 7540 return RecurKind::UMin; 7541 } 7542 } 7543 return RecurKind::None; 7544 } 7545 7546 /// Get the index of the first operand. 7547 static unsigned getFirstOperandIndex(Instruction *I) { 7548 return isCmpSelMinMax(I) ? 1 : 0; 7549 } 7550 7551 /// Total number of operands in the reduction operation. 7552 static unsigned getNumberOfOperands(Instruction *I) { 7553 return isCmpSelMinMax(I) ? 3 : 2; 7554 } 7555 7556 /// Checks if the instruction is in basic block \p BB. 7557 /// For a cmp+sel min/max reduction check that both ops are in \p BB. 7558 static bool hasSameParent(Instruction *I, BasicBlock *BB) { 7559 if (isCmpSelMinMax(I)) { 7560 auto *Sel = cast<SelectInst>(I); 7561 auto *Cmp = cast<Instruction>(Sel->getCondition()); 7562 return Sel->getParent() == BB && Cmp->getParent() == BB; 7563 } 7564 return I->getParent() == BB; 7565 } 7566 7567 /// Expected number of uses for reduction operations/reduced values. 7568 static bool hasRequiredNumberOfUses(bool IsCmpSelMinMax, Instruction *I) { 7569 if (IsCmpSelMinMax) { 7570 // SelectInst must be used twice while the condition op must have single 7571 // use only. 7572 if (auto *Sel = dyn_cast<SelectInst>(I)) 7573 return Sel->hasNUses(2) && Sel->getCondition()->hasOneUse(); 7574 return I->hasNUses(2); 7575 } 7576 7577 // Arithmetic reduction operation must be used once only. 7578 return I->hasOneUse(); 7579 } 7580 7581 /// Initializes the list of reduction operations. 7582 void initReductionOps(Instruction *I) { 7583 if (isCmpSelMinMax(I)) 7584 ReductionOps.assign(2, ReductionOpsType()); 7585 else 7586 ReductionOps.assign(1, ReductionOpsType()); 7587 } 7588 7589 /// Add all reduction operations for the reduction instruction \p I. 7590 void addReductionOps(Instruction *I) { 7591 if (isCmpSelMinMax(I)) { 7592 ReductionOps[0].emplace_back(cast<SelectInst>(I)->getCondition()); 7593 ReductionOps[1].emplace_back(I); 7594 } else { 7595 ReductionOps[0].emplace_back(I); 7596 } 7597 } 7598 7599 static Value *getLHS(RecurKind Kind, Instruction *I) { 7600 if (Kind == RecurKind::None) 7601 return nullptr; 7602 return I->getOperand(getFirstOperandIndex(I)); 7603 } 7604 static Value *getRHS(RecurKind Kind, Instruction *I) { 7605 if (Kind == RecurKind::None) 7606 return nullptr; 7607 return I->getOperand(getFirstOperandIndex(I) + 1); 7608 } 7609 7610 public: 7611 HorizontalReduction() = default; 7612 7613 /// Try to find a reduction tree. 7614 bool matchAssociativeReduction(PHINode *Phi, Instruction *Inst) { 7615 assert((!Phi || is_contained(Phi->operands(), Inst)) && 7616 "Phi needs to use the binary operator"); 7617 assert((isa<BinaryOperator>(Inst) || isa<SelectInst>(Inst) || 7618 isa<IntrinsicInst>(Inst)) && 7619 "Expected binop, select, or intrinsic for reduction matching"); 7620 RdxKind = getRdxKind(Inst); 7621 7622 // We could have a initial reductions that is not an add. 7623 // r *= v1 + v2 + v3 + v4 7624 // In such a case start looking for a tree rooted in the first '+'. 7625 if (Phi) { 7626 if (getLHS(RdxKind, Inst) == Phi) { 7627 Phi = nullptr; 7628 Inst = dyn_cast<Instruction>(getRHS(RdxKind, Inst)); 7629 if (!Inst) 7630 return false; 7631 RdxKind = getRdxKind(Inst); 7632 } else if (getRHS(RdxKind, Inst) == Phi) { 7633 Phi = nullptr; 7634 Inst = dyn_cast<Instruction>(getLHS(RdxKind, Inst)); 7635 if (!Inst) 7636 return false; 7637 RdxKind = getRdxKind(Inst); 7638 } 7639 } 7640 7641 if (!isVectorizable(RdxKind, Inst)) 7642 return false; 7643 7644 // Analyze "regular" integer/FP types for reductions - no target-specific 7645 // types or pointers. 7646 Type *Ty = Inst->getType(); 7647 if (!isValidElementType(Ty) || Ty->isPointerTy()) 7648 return false; 7649 7650 // Though the ultimate reduction may have multiple uses, its condition must 7651 // have only single use. 7652 if (auto *Sel = dyn_cast<SelectInst>(Inst)) 7653 if (!Sel->getCondition()->hasOneUse()) 7654 return false; 7655 7656 ReductionRoot = Inst; 7657 7658 // The opcode for leaf values that we perform a reduction on. 7659 // For example: load(x) + load(y) + load(z) + fptoui(w) 7660 // The leaf opcode for 'w' does not match, so we don't include it as a 7661 // potential candidate for the reduction. 7662 unsigned LeafOpcode = 0; 7663 7664 // Post-order traverse the reduction tree starting at Inst. We only handle 7665 // true trees containing binary operators or selects. 7666 SmallVector<std::pair<Instruction *, unsigned>, 32> Stack; 7667 Stack.push_back(std::make_pair(Inst, getFirstOperandIndex(Inst))); 7668 initReductionOps(Inst); 7669 while (!Stack.empty()) { 7670 Instruction *TreeN = Stack.back().first; 7671 unsigned EdgeToVisit = Stack.back().second++; 7672 const RecurKind TreeRdxKind = getRdxKind(TreeN); 7673 bool IsReducedValue = TreeRdxKind != RdxKind; 7674 7675 // Postorder visit. 7676 if (IsReducedValue || EdgeToVisit >= getNumberOfOperands(TreeN)) { 7677 if (IsReducedValue) 7678 ReducedVals.push_back(TreeN); 7679 else { 7680 auto ExtraArgsIter = ExtraArgs.find(TreeN); 7681 if (ExtraArgsIter != ExtraArgs.end() && !ExtraArgsIter->second) { 7682 // Check if TreeN is an extra argument of its parent operation. 7683 if (Stack.size() <= 1) { 7684 // TreeN can't be an extra argument as it is a root reduction 7685 // operation. 7686 return false; 7687 } 7688 // Yes, TreeN is an extra argument, do not add it to a list of 7689 // reduction operations. 7690 // Stack[Stack.size() - 2] always points to the parent operation. 7691 markExtraArg(Stack[Stack.size() - 2], TreeN); 7692 ExtraArgs.erase(TreeN); 7693 } else 7694 addReductionOps(TreeN); 7695 } 7696 // Retract. 7697 Stack.pop_back(); 7698 continue; 7699 } 7700 7701 // Visit operands. 7702 Value *EdgeVal = getRdxOperand(TreeN, EdgeToVisit); 7703 auto *EdgeInst = dyn_cast<Instruction>(EdgeVal); 7704 if (!EdgeInst) { 7705 // Edge value is not a reduction instruction or a leaf instruction. 7706 // (It may be a constant, function argument, or something else.) 7707 markExtraArg(Stack.back(), EdgeVal); 7708 continue; 7709 } 7710 RecurKind EdgeRdxKind = getRdxKind(EdgeInst); 7711 // Continue analysis if the next operand is a reduction operation or 7712 // (possibly) a leaf value. If the leaf value opcode is not set, 7713 // the first met operation != reduction operation is considered as the 7714 // leaf opcode. 7715 // Only handle trees in the current basic block. 7716 // Each tree node needs to have minimal number of users except for the 7717 // ultimate reduction. 7718 const bool IsRdxInst = EdgeRdxKind == RdxKind; 7719 if (EdgeInst != Phi && EdgeInst != Inst && 7720 hasSameParent(EdgeInst, Inst->getParent()) && 7721 hasRequiredNumberOfUses(isCmpSelMinMax(Inst), EdgeInst) && 7722 (!LeafOpcode || LeafOpcode == EdgeInst->getOpcode() || IsRdxInst)) { 7723 if (IsRdxInst) { 7724 // We need to be able to reassociate the reduction operations. 7725 if (!isVectorizable(EdgeRdxKind, EdgeInst)) { 7726 // I is an extra argument for TreeN (its parent operation). 7727 markExtraArg(Stack.back(), EdgeInst); 7728 continue; 7729 } 7730 } else if (!LeafOpcode) { 7731 LeafOpcode = EdgeInst->getOpcode(); 7732 } 7733 Stack.push_back( 7734 std::make_pair(EdgeInst, getFirstOperandIndex(EdgeInst))); 7735 continue; 7736 } 7737 // I is an extra argument for TreeN (its parent operation). 7738 markExtraArg(Stack.back(), EdgeInst); 7739 } 7740 return true; 7741 } 7742 7743 /// Attempt to vectorize the tree found by matchAssociativeReduction. 7744 bool tryToReduce(BoUpSLP &V, TargetTransformInfo *TTI) { 7745 // If there are a sufficient number of reduction values, reduce 7746 // to a nearby power-of-2. We can safely generate oversized 7747 // vectors and rely on the backend to split them to legal sizes. 7748 unsigned NumReducedVals = ReducedVals.size(); 7749 if (NumReducedVals < 4) 7750 return false; 7751 7752 // Intersect the fast-math-flags from all reduction operations. 7753 FastMathFlags RdxFMF; 7754 RdxFMF.set(); 7755 for (ReductionOpsType &RdxOp : ReductionOps) { 7756 for (Value *RdxVal : RdxOp) { 7757 if (auto *FPMO = dyn_cast<FPMathOperator>(RdxVal)) 7758 RdxFMF &= FPMO->getFastMathFlags(); 7759 } 7760 } 7761 7762 IRBuilder<> Builder(cast<Instruction>(ReductionRoot)); 7763 Builder.setFastMathFlags(RdxFMF); 7764 7765 BoUpSLP::ExtraValueToDebugLocsMap ExternallyUsedValues; 7766 // The same extra argument may be used several times, so log each attempt 7767 // to use it. 7768 for (const std::pair<Instruction *, Value *> &Pair : ExtraArgs) { 7769 assert(Pair.first && "DebugLoc must be set."); 7770 ExternallyUsedValues[Pair.second].push_back(Pair.first); 7771 } 7772 7773 // The compare instruction of a min/max is the insertion point for new 7774 // instructions and may be replaced with a new compare instruction. 7775 auto getCmpForMinMaxReduction = [](Instruction *RdxRootInst) { 7776 assert(isa<SelectInst>(RdxRootInst) && 7777 "Expected min/max reduction to have select root instruction"); 7778 Value *ScalarCond = cast<SelectInst>(RdxRootInst)->getCondition(); 7779 assert(isa<Instruction>(ScalarCond) && 7780 "Expected min/max reduction to have compare condition"); 7781 return cast<Instruction>(ScalarCond); 7782 }; 7783 7784 // The reduction root is used as the insertion point for new instructions, 7785 // so set it as externally used to prevent it from being deleted. 7786 ExternallyUsedValues[ReductionRoot]; 7787 SmallVector<Value *, 16> IgnoreList; 7788 for (ReductionOpsType &RdxOp : ReductionOps) 7789 IgnoreList.append(RdxOp.begin(), RdxOp.end()); 7790 7791 unsigned ReduxWidth = PowerOf2Floor(NumReducedVals); 7792 if (NumReducedVals > ReduxWidth) { 7793 // In the loop below, we are building a tree based on a window of 7794 // 'ReduxWidth' values. 7795 // If the operands of those values have common traits (compare predicate, 7796 // constant operand, etc), then we want to group those together to 7797 // minimize the cost of the reduction. 7798 7799 // TODO: This should be extended to count common operands for 7800 // compares and binops. 7801 7802 // Step 1: Count the number of times each compare predicate occurs. 7803 SmallDenseMap<unsigned, unsigned> PredCountMap; 7804 for (Value *RdxVal : ReducedVals) { 7805 CmpInst::Predicate Pred; 7806 if (match(RdxVal, m_Cmp(Pred, m_Value(), m_Value()))) 7807 ++PredCountMap[Pred]; 7808 } 7809 // Step 2: Sort the values so the most common predicates come first. 7810 stable_sort(ReducedVals, [&PredCountMap](Value *A, Value *B) { 7811 CmpInst::Predicate PredA, PredB; 7812 if (match(A, m_Cmp(PredA, m_Value(), m_Value())) && 7813 match(B, m_Cmp(PredB, m_Value(), m_Value()))) { 7814 return PredCountMap[PredA] > PredCountMap[PredB]; 7815 } 7816 return false; 7817 }); 7818 } 7819 7820 Value *VectorizedTree = nullptr; 7821 unsigned i = 0; 7822 while (i < NumReducedVals - ReduxWidth + 1 && ReduxWidth > 2) { 7823 ArrayRef<Value *> VL(&ReducedVals[i], ReduxWidth); 7824 V.buildTree(VL, ExternallyUsedValues, IgnoreList); 7825 Optional<ArrayRef<unsigned>> Order = V.bestOrder(); 7826 if (Order) { 7827 assert(Order->size() == VL.size() && 7828 "Order size must be the same as number of vectorized " 7829 "instructions."); 7830 // TODO: reorder tree nodes without tree rebuilding. 7831 SmallVector<Value *, 4> ReorderedOps(VL.size()); 7832 transform(fixupOrderingIndices(*Order), ReorderedOps.begin(), 7833 [VL](const unsigned Idx) { return VL[Idx]; }); 7834 V.buildTree(ReorderedOps, ExternallyUsedValues, IgnoreList); 7835 } 7836 if (V.isTreeTinyAndNotFullyVectorizable()) 7837 break; 7838 if (V.isLoadCombineReductionCandidate(RdxKind)) 7839 break; 7840 7841 // For a poison-safe boolean logic reduction, do not replace select 7842 // instructions with logic ops. All reduced values will be frozen (see 7843 // below) to prevent leaking poison. 7844 if (isa<SelectInst>(ReductionRoot) && 7845 isBoolLogicOp(cast<Instruction>(ReductionRoot)) && 7846 NumReducedVals != ReduxWidth) 7847 break; 7848 7849 V.computeMinimumValueSizes(); 7850 7851 // Estimate cost. 7852 InstructionCost TreeCost = 7853 V.getTreeCost(makeArrayRef(&ReducedVals[i], ReduxWidth)); 7854 InstructionCost ReductionCost = 7855 getReductionCost(TTI, ReducedVals[i], ReduxWidth); 7856 InstructionCost Cost = TreeCost + ReductionCost; 7857 if (!Cost.isValid()) { 7858 LLVM_DEBUG(dbgs() << "Encountered invalid baseline cost.\n"); 7859 return false; 7860 } 7861 if (Cost >= -SLPCostThreshold) { 7862 V.getORE()->emit([&]() { 7863 return OptimizationRemarkMissed(SV_NAME, "HorSLPNotBeneficial", 7864 cast<Instruction>(VL[0])) 7865 << "Vectorizing horizontal reduction is possible" 7866 << "but not beneficial with cost " << ore::NV("Cost", Cost) 7867 << " and threshold " 7868 << ore::NV("Threshold", -SLPCostThreshold); 7869 }); 7870 break; 7871 } 7872 7873 LLVM_DEBUG(dbgs() << "SLP: Vectorizing horizontal reduction at cost:" 7874 << Cost << ". (HorRdx)\n"); 7875 V.getORE()->emit([&]() { 7876 return OptimizationRemark(SV_NAME, "VectorizedHorizontalReduction", 7877 cast<Instruction>(VL[0])) 7878 << "Vectorized horizontal reduction with cost " 7879 << ore::NV("Cost", Cost) << " and with tree size " 7880 << ore::NV("TreeSize", V.getTreeSize()); 7881 }); 7882 7883 // Vectorize a tree. 7884 DebugLoc Loc = cast<Instruction>(ReducedVals[i])->getDebugLoc(); 7885 Value *VectorizedRoot = V.vectorizeTree(ExternallyUsedValues); 7886 7887 // Emit a reduction. If the root is a select (min/max idiom), the insert 7888 // point is the compare condition of that select. 7889 Instruction *RdxRootInst = cast<Instruction>(ReductionRoot); 7890 if (isCmpSelMinMax(RdxRootInst)) 7891 Builder.SetInsertPoint(getCmpForMinMaxReduction(RdxRootInst)); 7892 else 7893 Builder.SetInsertPoint(RdxRootInst); 7894 7895 // To prevent poison from leaking across what used to be sequential, safe, 7896 // scalar boolean logic operations, the reduction operand must be frozen. 7897 if (isa<SelectInst>(RdxRootInst) && isBoolLogicOp(RdxRootInst)) 7898 VectorizedRoot = Builder.CreateFreeze(VectorizedRoot); 7899 7900 Value *ReducedSubTree = 7901 emitReduction(VectorizedRoot, Builder, ReduxWidth, TTI); 7902 7903 if (!VectorizedTree) { 7904 // Initialize the final value in the reduction. 7905 VectorizedTree = ReducedSubTree; 7906 } else { 7907 // Update the final value in the reduction. 7908 Builder.SetCurrentDebugLocation(Loc); 7909 VectorizedTree = createOp(Builder, RdxKind, VectorizedTree, 7910 ReducedSubTree, "op.rdx", ReductionOps); 7911 } 7912 i += ReduxWidth; 7913 ReduxWidth = PowerOf2Floor(NumReducedVals - i); 7914 } 7915 7916 if (VectorizedTree) { 7917 // Finish the reduction. 7918 for (; i < NumReducedVals; ++i) { 7919 auto *I = cast<Instruction>(ReducedVals[i]); 7920 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 7921 VectorizedTree = 7922 createOp(Builder, RdxKind, VectorizedTree, I, "", ReductionOps); 7923 } 7924 for (auto &Pair : ExternallyUsedValues) { 7925 // Add each externally used value to the final reduction. 7926 for (auto *I : Pair.second) { 7927 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 7928 VectorizedTree = createOp(Builder, RdxKind, VectorizedTree, 7929 Pair.first, "op.extra", I); 7930 } 7931 } 7932 7933 ReductionRoot->replaceAllUsesWith(VectorizedTree); 7934 7935 // Mark all scalar reduction ops for deletion, they are replaced by the 7936 // vector reductions. 7937 V.eraseInstructions(IgnoreList); 7938 } 7939 return VectorizedTree != nullptr; 7940 } 7941 7942 unsigned numReductionValues() const { return ReducedVals.size(); } 7943 7944 private: 7945 /// Calculate the cost of a reduction. 7946 InstructionCost getReductionCost(TargetTransformInfo *TTI, 7947 Value *FirstReducedVal, 7948 unsigned ReduxWidth) { 7949 Type *ScalarTy = FirstReducedVal->getType(); 7950 FixedVectorType *VectorTy = FixedVectorType::get(ScalarTy, ReduxWidth); 7951 InstructionCost VectorCost, ScalarCost; 7952 switch (RdxKind) { 7953 case RecurKind::Add: 7954 case RecurKind::Mul: 7955 case RecurKind::Or: 7956 case RecurKind::And: 7957 case RecurKind::Xor: 7958 case RecurKind::FAdd: 7959 case RecurKind::FMul: { 7960 unsigned RdxOpcode = RecurrenceDescriptor::getOpcode(RdxKind); 7961 VectorCost = TTI->getArithmeticReductionCost(RdxOpcode, VectorTy); 7962 ScalarCost = TTI->getArithmeticInstrCost(RdxOpcode, ScalarTy); 7963 break; 7964 } 7965 case RecurKind::FMax: 7966 case RecurKind::FMin: { 7967 auto *VecCondTy = cast<VectorType>(CmpInst::makeCmpResultType(VectorTy)); 7968 VectorCost = TTI->getMinMaxReductionCost(VectorTy, VecCondTy, 7969 /*unsigned=*/false); 7970 ScalarCost = 7971 TTI->getCmpSelInstrCost(Instruction::FCmp, ScalarTy) + 7972 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 7973 CmpInst::makeCmpResultType(ScalarTy)); 7974 break; 7975 } 7976 case RecurKind::SMax: 7977 case RecurKind::SMin: 7978 case RecurKind::UMax: 7979 case RecurKind::UMin: { 7980 auto *VecCondTy = cast<VectorType>(CmpInst::makeCmpResultType(VectorTy)); 7981 bool IsUnsigned = 7982 RdxKind == RecurKind::UMax || RdxKind == RecurKind::UMin; 7983 VectorCost = TTI->getMinMaxReductionCost(VectorTy, VecCondTy, IsUnsigned); 7984 ScalarCost = 7985 TTI->getCmpSelInstrCost(Instruction::ICmp, ScalarTy) + 7986 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 7987 CmpInst::makeCmpResultType(ScalarTy)); 7988 break; 7989 } 7990 default: 7991 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 7992 } 7993 7994 // Scalar cost is repeated for N-1 elements. 7995 ScalarCost *= (ReduxWidth - 1); 7996 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << VectorCost - ScalarCost 7997 << " for reduction that starts with " << *FirstReducedVal 7998 << " (It is a splitting reduction)\n"); 7999 return VectorCost - ScalarCost; 8000 } 8001 8002 /// Emit a horizontal reduction of the vectorized value. 8003 Value *emitReduction(Value *VectorizedValue, IRBuilder<> &Builder, 8004 unsigned ReduxWidth, const TargetTransformInfo *TTI) { 8005 assert(VectorizedValue && "Need to have a vectorized tree node"); 8006 assert(isPowerOf2_32(ReduxWidth) && 8007 "We only handle power-of-two reductions for now"); 8008 8009 return createSimpleTargetReduction(Builder, TTI, VectorizedValue, RdxKind, 8010 ReductionOps.back()); 8011 } 8012 }; 8013 8014 } // end anonymous namespace 8015 8016 static Optional<unsigned> getAggregateSize(Instruction *InsertInst) { 8017 if (auto *IE = dyn_cast<InsertElementInst>(InsertInst)) 8018 return cast<FixedVectorType>(IE->getType())->getNumElements(); 8019 8020 unsigned AggregateSize = 1; 8021 auto *IV = cast<InsertValueInst>(InsertInst); 8022 Type *CurrentType = IV->getType(); 8023 do { 8024 if (auto *ST = dyn_cast<StructType>(CurrentType)) { 8025 for (auto *Elt : ST->elements()) 8026 if (Elt != ST->getElementType(0)) // check homogeneity 8027 return None; 8028 AggregateSize *= ST->getNumElements(); 8029 CurrentType = ST->getElementType(0); 8030 } else if (auto *AT = dyn_cast<ArrayType>(CurrentType)) { 8031 AggregateSize *= AT->getNumElements(); 8032 CurrentType = AT->getElementType(); 8033 } else if (auto *VT = dyn_cast<FixedVectorType>(CurrentType)) { 8034 AggregateSize *= VT->getNumElements(); 8035 return AggregateSize; 8036 } else if (CurrentType->isSingleValueType()) { 8037 return AggregateSize; 8038 } else { 8039 return None; 8040 } 8041 } while (true); 8042 } 8043 8044 static bool findBuildAggregate_rec(Instruction *LastInsertInst, 8045 TargetTransformInfo *TTI, 8046 SmallVectorImpl<Value *> &BuildVectorOpds, 8047 SmallVectorImpl<Value *> &InsertElts, 8048 unsigned OperandOffset) { 8049 do { 8050 Value *InsertedOperand = LastInsertInst->getOperand(1); 8051 Optional<int> OperandIndex = getInsertIndex(LastInsertInst, OperandOffset); 8052 if (!OperandIndex) 8053 return false; 8054 if (isa<InsertElementInst>(InsertedOperand) || 8055 isa<InsertValueInst>(InsertedOperand)) { 8056 if (!findBuildAggregate_rec(cast<Instruction>(InsertedOperand), TTI, 8057 BuildVectorOpds, InsertElts, *OperandIndex)) 8058 return false; 8059 } else { 8060 BuildVectorOpds[*OperandIndex] = InsertedOperand; 8061 InsertElts[*OperandIndex] = LastInsertInst; 8062 } 8063 LastInsertInst = dyn_cast<Instruction>(LastInsertInst->getOperand(0)); 8064 } while (LastInsertInst != nullptr && 8065 (isa<InsertValueInst>(LastInsertInst) || 8066 isa<InsertElementInst>(LastInsertInst)) && 8067 LastInsertInst->hasOneUse()); 8068 return true; 8069 } 8070 8071 /// Recognize construction of vectors like 8072 /// %ra = insertelement <4 x float> poison, float %s0, i32 0 8073 /// %rb = insertelement <4 x float> %ra, float %s1, i32 1 8074 /// %rc = insertelement <4 x float> %rb, float %s2, i32 2 8075 /// %rd = insertelement <4 x float> %rc, float %s3, i32 3 8076 /// starting from the last insertelement or insertvalue instruction. 8077 /// 8078 /// Also recognize homogeneous aggregates like {<2 x float>, <2 x float>}, 8079 /// {{float, float}, {float, float}}, [2 x {float, float}] and so on. 8080 /// See llvm/test/Transforms/SLPVectorizer/X86/pr42022.ll for examples. 8081 /// 8082 /// Assume LastInsertInst is of InsertElementInst or InsertValueInst type. 8083 /// 8084 /// \return true if it matches. 8085 static bool findBuildAggregate(Instruction *LastInsertInst, 8086 TargetTransformInfo *TTI, 8087 SmallVectorImpl<Value *> &BuildVectorOpds, 8088 SmallVectorImpl<Value *> &InsertElts) { 8089 8090 assert((isa<InsertElementInst>(LastInsertInst) || 8091 isa<InsertValueInst>(LastInsertInst)) && 8092 "Expected insertelement or insertvalue instruction!"); 8093 8094 assert((BuildVectorOpds.empty() && InsertElts.empty()) && 8095 "Expected empty result vectors!"); 8096 8097 Optional<unsigned> AggregateSize = getAggregateSize(LastInsertInst); 8098 if (!AggregateSize) 8099 return false; 8100 BuildVectorOpds.resize(*AggregateSize); 8101 InsertElts.resize(*AggregateSize); 8102 8103 if (findBuildAggregate_rec(LastInsertInst, TTI, BuildVectorOpds, InsertElts, 8104 0)) { 8105 llvm::erase_value(BuildVectorOpds, nullptr); 8106 llvm::erase_value(InsertElts, nullptr); 8107 if (BuildVectorOpds.size() >= 2) 8108 return true; 8109 } 8110 8111 return false; 8112 } 8113 8114 /// Try and get a reduction value from a phi node. 8115 /// 8116 /// Given a phi node \p P in a block \p ParentBB, consider possible reductions 8117 /// if they come from either \p ParentBB or a containing loop latch. 8118 /// 8119 /// \returns A candidate reduction value if possible, or \code nullptr \endcode 8120 /// if not possible. 8121 static Value *getReductionValue(const DominatorTree *DT, PHINode *P, 8122 BasicBlock *ParentBB, LoopInfo *LI) { 8123 // There are situations where the reduction value is not dominated by the 8124 // reduction phi. Vectorizing such cases has been reported to cause 8125 // miscompiles. See PR25787. 8126 auto DominatedReduxValue = [&](Value *R) { 8127 return isa<Instruction>(R) && 8128 DT->dominates(P->getParent(), cast<Instruction>(R)->getParent()); 8129 }; 8130 8131 Value *Rdx = nullptr; 8132 8133 // Return the incoming value if it comes from the same BB as the phi node. 8134 if (P->getIncomingBlock(0) == ParentBB) { 8135 Rdx = P->getIncomingValue(0); 8136 } else if (P->getIncomingBlock(1) == ParentBB) { 8137 Rdx = P->getIncomingValue(1); 8138 } 8139 8140 if (Rdx && DominatedReduxValue(Rdx)) 8141 return Rdx; 8142 8143 // Otherwise, check whether we have a loop latch to look at. 8144 Loop *BBL = LI->getLoopFor(ParentBB); 8145 if (!BBL) 8146 return nullptr; 8147 BasicBlock *BBLatch = BBL->getLoopLatch(); 8148 if (!BBLatch) 8149 return nullptr; 8150 8151 // There is a loop latch, return the incoming value if it comes from 8152 // that. This reduction pattern occasionally turns up. 8153 if (P->getIncomingBlock(0) == BBLatch) { 8154 Rdx = P->getIncomingValue(0); 8155 } else if (P->getIncomingBlock(1) == BBLatch) { 8156 Rdx = P->getIncomingValue(1); 8157 } 8158 8159 if (Rdx && DominatedReduxValue(Rdx)) 8160 return Rdx; 8161 8162 return nullptr; 8163 } 8164 8165 static bool matchRdxBop(Instruction *I, Value *&V0, Value *&V1) { 8166 if (match(I, m_BinOp(m_Value(V0), m_Value(V1)))) 8167 return true; 8168 if (match(I, m_Intrinsic<Intrinsic::maxnum>(m_Value(V0), m_Value(V1)))) 8169 return true; 8170 if (match(I, m_Intrinsic<Intrinsic::minnum>(m_Value(V0), m_Value(V1)))) 8171 return true; 8172 if (match(I, m_Intrinsic<Intrinsic::smax>(m_Value(V0), m_Value(V1)))) 8173 return true; 8174 if (match(I, m_Intrinsic<Intrinsic::smin>(m_Value(V0), m_Value(V1)))) 8175 return true; 8176 if (match(I, m_Intrinsic<Intrinsic::umax>(m_Value(V0), m_Value(V1)))) 8177 return true; 8178 if (match(I, m_Intrinsic<Intrinsic::umin>(m_Value(V0), m_Value(V1)))) 8179 return true; 8180 return false; 8181 } 8182 8183 /// Attempt to reduce a horizontal reduction. 8184 /// If it is legal to match a horizontal reduction feeding the phi node \a P 8185 /// with reduction operators \a Root (or one of its operands) in a basic block 8186 /// \a BB, then check if it can be done. If horizontal reduction is not found 8187 /// and root instruction is a binary operation, vectorization of the operands is 8188 /// attempted. 8189 /// \returns true if a horizontal reduction was matched and reduced or operands 8190 /// of one of the binary instruction were vectorized. 8191 /// \returns false if a horizontal reduction was not matched (or not possible) 8192 /// or no vectorization of any binary operation feeding \a Root instruction was 8193 /// performed. 8194 static bool tryToVectorizeHorReductionOrInstOperands( 8195 PHINode *P, Instruction *Root, BasicBlock *BB, BoUpSLP &R, 8196 TargetTransformInfo *TTI, 8197 const function_ref<bool(Instruction *, BoUpSLP &)> Vectorize) { 8198 if (!ShouldVectorizeHor) 8199 return false; 8200 8201 if (!Root) 8202 return false; 8203 8204 if (Root->getParent() != BB || isa<PHINode>(Root)) 8205 return false; 8206 // Start analysis starting from Root instruction. If horizontal reduction is 8207 // found, try to vectorize it. If it is not a horizontal reduction or 8208 // vectorization is not possible or not effective, and currently analyzed 8209 // instruction is a binary operation, try to vectorize the operands, using 8210 // pre-order DFS traversal order. If the operands were not vectorized, repeat 8211 // the same procedure considering each operand as a possible root of the 8212 // horizontal reduction. 8213 // Interrupt the process if the Root instruction itself was vectorized or all 8214 // sub-trees not higher that RecursionMaxDepth were analyzed/vectorized. 8215 // Skip the analysis of CmpInsts.Compiler implements postanalysis of the 8216 // CmpInsts so we can skip extra attempts in 8217 // tryToVectorizeHorReductionOrInstOperands and save compile time. 8218 SmallVector<std::pair<Instruction *, unsigned>, 8> Stack(1, {Root, 0}); 8219 SmallPtrSet<Value *, 8> VisitedInstrs; 8220 bool Res = false; 8221 while (!Stack.empty()) { 8222 Instruction *Inst; 8223 unsigned Level; 8224 std::tie(Inst, Level) = Stack.pop_back_val(); 8225 // Do not try to analyze instruction that has already been vectorized. 8226 // This may happen when we vectorize instruction operands on a previous 8227 // iteration while stack was populated before that happened. 8228 if (R.isDeleted(Inst)) 8229 continue; 8230 Value *B0, *B1; 8231 bool IsBinop = matchRdxBop(Inst, B0, B1); 8232 bool IsSelect = match(Inst, m_Select(m_Value(), m_Value(), m_Value())); 8233 if (IsBinop || IsSelect) { 8234 HorizontalReduction HorRdx; 8235 if (HorRdx.matchAssociativeReduction(P, Inst)) { 8236 if (HorRdx.tryToReduce(R, TTI)) { 8237 Res = true; 8238 // Set P to nullptr to avoid re-analysis of phi node in 8239 // matchAssociativeReduction function unless this is the root node. 8240 P = nullptr; 8241 continue; 8242 } 8243 } 8244 if (P && IsBinop) { 8245 Inst = dyn_cast<Instruction>(B0); 8246 if (Inst == P) 8247 Inst = dyn_cast<Instruction>(B1); 8248 if (!Inst) { 8249 // Set P to nullptr to avoid re-analysis of phi node in 8250 // matchAssociativeReduction function unless this is the root node. 8251 P = nullptr; 8252 continue; 8253 } 8254 } 8255 } 8256 // Set P to nullptr to avoid re-analysis of phi node in 8257 // matchAssociativeReduction function unless this is the root node. 8258 P = nullptr; 8259 // Do not try to vectorize CmpInst operands, this is done separately. 8260 if (!isa<CmpInst>(Inst) && Vectorize(Inst, R)) { 8261 Res = true; 8262 continue; 8263 } 8264 8265 // Try to vectorize operands. 8266 // Continue analysis for the instruction from the same basic block only to 8267 // save compile time. 8268 if (++Level < RecursionMaxDepth) 8269 for (auto *Op : Inst->operand_values()) 8270 if (VisitedInstrs.insert(Op).second) 8271 if (auto *I = dyn_cast<Instruction>(Op)) 8272 // Do not try to vectorize CmpInst operands, this is done 8273 // separately. 8274 if (!isa<PHINode>(I) && !isa<CmpInst>(I) && !R.isDeleted(I) && 8275 I->getParent() == BB) 8276 Stack.emplace_back(I, Level); 8277 } 8278 return Res; 8279 } 8280 8281 bool SLPVectorizerPass::vectorizeRootInstruction(PHINode *P, Value *V, 8282 BasicBlock *BB, BoUpSLP &R, 8283 TargetTransformInfo *TTI) { 8284 auto *I = dyn_cast_or_null<Instruction>(V); 8285 if (!I) 8286 return false; 8287 8288 if (!isa<BinaryOperator>(I)) 8289 P = nullptr; 8290 // Try to match and vectorize a horizontal reduction. 8291 auto &&ExtraVectorization = [this](Instruction *I, BoUpSLP &R) -> bool { 8292 return tryToVectorize(I, R); 8293 }; 8294 return tryToVectorizeHorReductionOrInstOperands(P, I, BB, R, TTI, 8295 ExtraVectorization); 8296 } 8297 8298 bool SLPVectorizerPass::vectorizeInsertValueInst(InsertValueInst *IVI, 8299 BasicBlock *BB, BoUpSLP &R) { 8300 const DataLayout &DL = BB->getModule()->getDataLayout(); 8301 if (!R.canMapToVector(IVI->getType(), DL)) 8302 return false; 8303 8304 SmallVector<Value *, 16> BuildVectorOpds; 8305 SmallVector<Value *, 16> BuildVectorInsts; 8306 if (!findBuildAggregate(IVI, TTI, BuildVectorOpds, BuildVectorInsts)) 8307 return false; 8308 8309 LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IVI << "\n"); 8310 // Aggregate value is unlikely to be processed in vector register, we need to 8311 // extract scalars into scalar registers, so NeedExtraction is set true. 8312 return tryToVectorizeList(BuildVectorOpds, R, /*AllowReorder=*/false); 8313 } 8314 8315 bool SLPVectorizerPass::vectorizeInsertElementInst(InsertElementInst *IEI, 8316 BasicBlock *BB, BoUpSLP &R) { 8317 SmallVector<Value *, 16> BuildVectorInsts; 8318 SmallVector<Value *, 16> BuildVectorOpds; 8319 SmallVector<int> Mask; 8320 if (!findBuildAggregate(IEI, TTI, BuildVectorOpds, BuildVectorInsts) || 8321 (llvm::all_of(BuildVectorOpds, 8322 [](Value *V) { return isa<ExtractElementInst>(V); }) && 8323 isShuffle(BuildVectorOpds, Mask))) 8324 return false; 8325 8326 LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IEI << "\n"); 8327 return tryToVectorizeList(BuildVectorInsts, R, /*AllowReorder=*/true); 8328 } 8329 8330 bool SLPVectorizerPass::vectorizeSimpleInstructions( 8331 SmallVectorImpl<Instruction *> &Instructions, BasicBlock *BB, BoUpSLP &R, 8332 bool AtTerminator) { 8333 bool OpsChanged = false; 8334 SmallVector<Instruction *, 4> PostponedCmps; 8335 for (auto *I : reverse(Instructions)) { 8336 if (R.isDeleted(I)) 8337 continue; 8338 if (auto *LastInsertValue = dyn_cast<InsertValueInst>(I)) 8339 OpsChanged |= vectorizeInsertValueInst(LastInsertValue, BB, R); 8340 else if (auto *LastInsertElem = dyn_cast<InsertElementInst>(I)) 8341 OpsChanged |= vectorizeInsertElementInst(LastInsertElem, BB, R); 8342 else if (isa<CmpInst>(I)) 8343 PostponedCmps.push_back(I); 8344 } 8345 if (AtTerminator) { 8346 // Try to find reductions first. 8347 for (Instruction *I : PostponedCmps) { 8348 if (R.isDeleted(I)) 8349 continue; 8350 for (Value *Op : I->operands()) 8351 OpsChanged |= vectorizeRootInstruction(nullptr, Op, BB, R, TTI); 8352 } 8353 // Try to vectorize operands as vector bundles. 8354 for (Instruction *I : PostponedCmps) { 8355 if (R.isDeleted(I)) 8356 continue; 8357 OpsChanged |= tryToVectorize(I, R); 8358 } 8359 Instructions.clear(); 8360 } else { 8361 // Insert in reverse order since the PostponedCmps vector was filled in 8362 // reverse order. 8363 Instructions.assign(PostponedCmps.rbegin(), PostponedCmps.rend()); 8364 } 8365 return OpsChanged; 8366 } 8367 8368 bool SLPVectorizerPass::vectorizeChainsInBlock(BasicBlock *BB, BoUpSLP &R) { 8369 bool Changed = false; 8370 SmallVector<Value *, 4> Incoming; 8371 SmallPtrSet<Value *, 16> VisitedInstrs; 8372 // Maps phi nodes to the non-phi nodes found in the use tree for each phi 8373 // node. Allows better to identify the chains that can be vectorized in the 8374 // better way. 8375 DenseMap<Value *, SmallVector<Value *, 4>> PHIToOpcodes; 8376 8377 bool HaveVectorizedPhiNodes = true; 8378 while (HaveVectorizedPhiNodes) { 8379 HaveVectorizedPhiNodes = false; 8380 8381 // Collect the incoming values from the PHIs. 8382 Incoming.clear(); 8383 for (Instruction &I : *BB) { 8384 PHINode *P = dyn_cast<PHINode>(&I); 8385 if (!P) 8386 break; 8387 8388 // No need to analyze deleted, vectorized and non-vectorizable 8389 // instructions. 8390 if (!VisitedInstrs.count(P) && !R.isDeleted(P) && 8391 isValidElementType(P->getType())) 8392 Incoming.push_back(P); 8393 } 8394 8395 // Find the corresponding non-phi nodes for better matching when trying to 8396 // build the tree. 8397 for (Value *V : Incoming) { 8398 SmallVectorImpl<Value *> &Opcodes = 8399 PHIToOpcodes.try_emplace(V).first->getSecond(); 8400 if (!Opcodes.empty()) 8401 continue; 8402 SmallVector<Value *, 4> Nodes(1, V); 8403 SmallPtrSet<Value *, 4> Visited; 8404 while (!Nodes.empty()) { 8405 auto *PHI = cast<PHINode>(Nodes.pop_back_val()); 8406 if (!Visited.insert(PHI).second) 8407 continue; 8408 for (Value *V : PHI->incoming_values()) { 8409 if (auto *PHI1 = dyn_cast<PHINode>((V))) { 8410 Nodes.push_back(PHI1); 8411 continue; 8412 } 8413 Opcodes.emplace_back(V); 8414 } 8415 } 8416 } 8417 8418 // Sort by type, parent, operands. 8419 stable_sort(Incoming, [this, &PHIToOpcodes](Value *V1, Value *V2) { 8420 assert(isValidElementType(V1->getType()) && 8421 isValidElementType(V2->getType()) && 8422 "Expected vectorizable types only."); 8423 // It is fine to compare type IDs here, since we expect only vectorizable 8424 // types, like ints, floats and pointers, we don't care about other type. 8425 if (V1->getType()->getTypeID() < V2->getType()->getTypeID()) 8426 return true; 8427 if (V1->getType()->getTypeID() > V2->getType()->getTypeID()) 8428 return false; 8429 ArrayRef<Value *> Opcodes1 = PHIToOpcodes[V1]; 8430 ArrayRef<Value *> Opcodes2 = PHIToOpcodes[V2]; 8431 if (Opcodes1.size() < Opcodes2.size()) 8432 return true; 8433 if (Opcodes1.size() > Opcodes2.size()) 8434 return false; 8435 for (int I = 0, E = Opcodes1.size(); I < E; ++I) { 8436 // Undefs are compatible with any other value. 8437 if (isa<UndefValue>(Opcodes1[I]) || isa<UndefValue>(Opcodes2[I])) 8438 continue; 8439 if (auto *I1 = dyn_cast<Instruction>(Opcodes1[I])) 8440 if (auto *I2 = dyn_cast<Instruction>(Opcodes2[I])) { 8441 DomTreeNodeBase<BasicBlock> *NodeI1 = DT->getNode(I1->getParent()); 8442 DomTreeNodeBase<BasicBlock> *NodeI2 = DT->getNode(I2->getParent()); 8443 if (!NodeI1) 8444 return NodeI2 != nullptr; 8445 if (!NodeI2) 8446 return false; 8447 assert((NodeI1 == NodeI2) == 8448 (NodeI1->getDFSNumIn() == NodeI2->getDFSNumIn()) && 8449 "Different nodes should have different DFS numbers"); 8450 if (NodeI1 != NodeI2) 8451 return NodeI1->getDFSNumIn() < NodeI2->getDFSNumIn(); 8452 InstructionsState S = getSameOpcode({I1, I2}); 8453 if (S.getOpcode()) 8454 continue; 8455 return I1->getOpcode() < I2->getOpcode(); 8456 } 8457 if (isa<Constant>(Opcodes1[I]) && isa<Constant>(Opcodes2[I])) 8458 continue; 8459 if (Opcodes1[I]->getValueID() < Opcodes2[I]->getValueID()) 8460 return true; 8461 if (Opcodes1[I]->getValueID() > Opcodes2[I]->getValueID()) 8462 return false; 8463 } 8464 return false; 8465 }); 8466 8467 auto &&AreCompatiblePHIs = [&PHIToOpcodes](Value *V1, Value *V2) { 8468 if (V1 == V2) 8469 return true; 8470 if (V1->getType() != V2->getType()) 8471 return false; 8472 ArrayRef<Value *> Opcodes1 = PHIToOpcodes[V1]; 8473 ArrayRef<Value *> Opcodes2 = PHIToOpcodes[V2]; 8474 if (Opcodes1.size() != Opcodes2.size()) 8475 return false; 8476 for (int I = 0, E = Opcodes1.size(); I < E; ++I) { 8477 // Undefs are compatible with any other value. 8478 if (isa<UndefValue>(Opcodes1[I]) || isa<UndefValue>(Opcodes2[I])) 8479 continue; 8480 if (auto *I1 = dyn_cast<Instruction>(Opcodes1[I])) 8481 if (auto *I2 = dyn_cast<Instruction>(Opcodes2[I])) { 8482 if (I1->getParent() != I2->getParent()) 8483 return false; 8484 InstructionsState S = getSameOpcode({I1, I2}); 8485 if (S.getOpcode()) 8486 continue; 8487 return false; 8488 } 8489 if (isa<Constant>(Opcodes1[I]) && isa<Constant>(Opcodes2[I])) 8490 continue; 8491 if (Opcodes1[I]->getValueID() != Opcodes2[I]->getValueID()) 8492 return false; 8493 } 8494 return true; 8495 }; 8496 8497 // Try to vectorize elements base on their type. 8498 SmallVector<Value *, 4> Candidates; 8499 for (SmallVector<Value *, 4>::iterator IncIt = Incoming.begin(), 8500 E = Incoming.end(); 8501 IncIt != E;) { 8502 8503 // Look for the next elements with the same type, parent and operand 8504 // kinds. 8505 SmallVector<Value *, 4>::iterator SameTypeIt = IncIt; 8506 while (SameTypeIt != E && AreCompatiblePHIs(*SameTypeIt, *IncIt)) { 8507 VisitedInstrs.insert(*SameTypeIt); 8508 ++SameTypeIt; 8509 } 8510 8511 // Try to vectorize them. 8512 unsigned NumElts = (SameTypeIt - IncIt); 8513 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize starting at PHIs (" 8514 << NumElts << ")\n"); 8515 // The order in which the phi nodes appear in the program does not matter. 8516 // So allow tryToVectorizeList to reorder them if it is beneficial. This 8517 // is done when there are exactly two elements since tryToVectorizeList 8518 // asserts that there are only two values when AllowReorder is true. 8519 if (NumElts > 1 && tryToVectorizeList(makeArrayRef(IncIt, NumElts), R, 8520 /*AllowReorder=*/true)) { 8521 // Success start over because instructions might have been changed. 8522 HaveVectorizedPhiNodes = true; 8523 Changed = true; 8524 } else if (NumElts < 4 && 8525 (Candidates.empty() || 8526 Candidates.front()->getType() == (*IncIt)->getType())) { 8527 Candidates.append(IncIt, std::next(IncIt, NumElts)); 8528 } 8529 // Final attempt to vectorize phis with the same types. 8530 if (SameTypeIt == E || (*SameTypeIt)->getType() != (*IncIt)->getType()) { 8531 if (Candidates.size() > 1 && 8532 tryToVectorizeList(Candidates, R, /*AllowReorder=*/true)) { 8533 // Success start over because instructions might have been changed. 8534 HaveVectorizedPhiNodes = true; 8535 Changed = true; 8536 } 8537 Candidates.clear(); 8538 } 8539 8540 // Start over at the next instruction of a different type (or the end). 8541 IncIt = SameTypeIt; 8542 } 8543 } 8544 8545 VisitedInstrs.clear(); 8546 8547 SmallVector<Instruction *, 8> PostProcessInstructions; 8548 SmallDenseSet<Instruction *, 4> KeyNodes; 8549 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 8550 // Skip instructions with scalable type. The num of elements is unknown at 8551 // compile-time for scalable type. 8552 if (isa<ScalableVectorType>(it->getType())) 8553 continue; 8554 8555 // Skip instructions marked for the deletion. 8556 if (R.isDeleted(&*it)) 8557 continue; 8558 // We may go through BB multiple times so skip the one we have checked. 8559 if (!VisitedInstrs.insert(&*it).second) { 8560 if (it->use_empty() && KeyNodes.contains(&*it) && 8561 vectorizeSimpleInstructions(PostProcessInstructions, BB, R, 8562 it->isTerminator())) { 8563 // We would like to start over since some instructions are deleted 8564 // and the iterator may become invalid value. 8565 Changed = true; 8566 it = BB->begin(); 8567 e = BB->end(); 8568 } 8569 continue; 8570 } 8571 8572 if (isa<DbgInfoIntrinsic>(it)) 8573 continue; 8574 8575 // Try to vectorize reductions that use PHINodes. 8576 if (PHINode *P = dyn_cast<PHINode>(it)) { 8577 // Check that the PHI is a reduction PHI. 8578 if (P->getNumIncomingValues() == 2) { 8579 // Try to match and vectorize a horizontal reduction. 8580 if (vectorizeRootInstruction(P, getReductionValue(DT, P, BB, LI), BB, R, 8581 TTI)) { 8582 Changed = true; 8583 it = BB->begin(); 8584 e = BB->end(); 8585 continue; 8586 } 8587 } 8588 // Try to vectorize the incoming values of the PHI, to catch reductions 8589 // that feed into PHIs. 8590 for (unsigned I = 0, E = P->getNumIncomingValues(); I != E; I++) { 8591 // Skip if the incoming block is the current BB for now. Also, bypass 8592 // unreachable IR for efficiency and to avoid crashing. 8593 // TODO: Collect the skipped incoming values and try to vectorize them 8594 // after processing BB. 8595 if (BB == P->getIncomingBlock(I) || 8596 !DT->isReachableFromEntry(P->getIncomingBlock(I))) 8597 continue; 8598 8599 Changed |= vectorizeRootInstruction(nullptr, P->getIncomingValue(I), 8600 P->getIncomingBlock(I), R, TTI); 8601 } 8602 continue; 8603 } 8604 8605 // Ran into an instruction without users, like terminator, or function call 8606 // with ignored return value, store. Ignore unused instructions (basing on 8607 // instruction type, except for CallInst and InvokeInst). 8608 if (it->use_empty() && (it->getType()->isVoidTy() || isa<CallInst>(it) || 8609 isa<InvokeInst>(it))) { 8610 KeyNodes.insert(&*it); 8611 bool OpsChanged = false; 8612 if (ShouldStartVectorizeHorAtStore || !isa<StoreInst>(it)) { 8613 for (auto *V : it->operand_values()) { 8614 // Try to match and vectorize a horizontal reduction. 8615 OpsChanged |= vectorizeRootInstruction(nullptr, V, BB, R, TTI); 8616 } 8617 } 8618 // Start vectorization of post-process list of instructions from the 8619 // top-tree instructions to try to vectorize as many instructions as 8620 // possible. 8621 OpsChanged |= vectorizeSimpleInstructions(PostProcessInstructions, BB, R, 8622 it->isTerminator()); 8623 if (OpsChanged) { 8624 // We would like to start over since some instructions are deleted 8625 // and the iterator may become invalid value. 8626 Changed = true; 8627 it = BB->begin(); 8628 e = BB->end(); 8629 continue; 8630 } 8631 } 8632 8633 if (isa<InsertElementInst>(it) || isa<CmpInst>(it) || 8634 isa<InsertValueInst>(it)) 8635 PostProcessInstructions.push_back(&*it); 8636 } 8637 8638 return Changed; 8639 } 8640 8641 bool SLPVectorizerPass::vectorizeGEPIndices(BasicBlock *BB, BoUpSLP &R) { 8642 auto Changed = false; 8643 for (auto &Entry : GEPs) { 8644 // If the getelementptr list has fewer than two elements, there's nothing 8645 // to do. 8646 if (Entry.second.size() < 2) 8647 continue; 8648 8649 LLVM_DEBUG(dbgs() << "SLP: Analyzing a getelementptr list of length " 8650 << Entry.second.size() << ".\n"); 8651 8652 // Process the GEP list in chunks suitable for the target's supported 8653 // vector size. If a vector register can't hold 1 element, we are done. We 8654 // are trying to vectorize the index computations, so the maximum number of 8655 // elements is based on the size of the index expression, rather than the 8656 // size of the GEP itself (the target's pointer size). 8657 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 8658 unsigned EltSize = R.getVectorElementSize(*Entry.second[0]->idx_begin()); 8659 if (MaxVecRegSize < EltSize) 8660 continue; 8661 8662 unsigned MaxElts = MaxVecRegSize / EltSize; 8663 for (unsigned BI = 0, BE = Entry.second.size(); BI < BE; BI += MaxElts) { 8664 auto Len = std::min<unsigned>(BE - BI, MaxElts); 8665 ArrayRef<GetElementPtrInst *> GEPList(&Entry.second[BI], Len); 8666 8667 // Initialize a set a candidate getelementptrs. Note that we use a 8668 // SetVector here to preserve program order. If the index computations 8669 // are vectorizable and begin with loads, we want to minimize the chance 8670 // of having to reorder them later. 8671 SetVector<Value *> Candidates(GEPList.begin(), GEPList.end()); 8672 8673 // Some of the candidates may have already been vectorized after we 8674 // initially collected them. If so, they are marked as deleted, so remove 8675 // them from the set of candidates. 8676 Candidates.remove_if( 8677 [&R](Value *I) { return R.isDeleted(cast<Instruction>(I)); }); 8678 8679 // Remove from the set of candidates all pairs of getelementptrs with 8680 // constant differences. Such getelementptrs are likely not good 8681 // candidates for vectorization in a bottom-up phase since one can be 8682 // computed from the other. We also ensure all candidate getelementptr 8683 // indices are unique. 8684 for (int I = 0, E = GEPList.size(); I < E && Candidates.size() > 1; ++I) { 8685 auto *GEPI = GEPList[I]; 8686 if (!Candidates.count(GEPI)) 8687 continue; 8688 auto *SCEVI = SE->getSCEV(GEPList[I]); 8689 for (int J = I + 1; J < E && Candidates.size() > 1; ++J) { 8690 auto *GEPJ = GEPList[J]; 8691 auto *SCEVJ = SE->getSCEV(GEPList[J]); 8692 if (isa<SCEVConstant>(SE->getMinusSCEV(SCEVI, SCEVJ))) { 8693 Candidates.remove(GEPI); 8694 Candidates.remove(GEPJ); 8695 } else if (GEPI->idx_begin()->get() == GEPJ->idx_begin()->get()) { 8696 Candidates.remove(GEPJ); 8697 } 8698 } 8699 } 8700 8701 // We break out of the above computation as soon as we know there are 8702 // fewer than two candidates remaining. 8703 if (Candidates.size() < 2) 8704 continue; 8705 8706 // Add the single, non-constant index of each candidate to the bundle. We 8707 // ensured the indices met these constraints when we originally collected 8708 // the getelementptrs. 8709 SmallVector<Value *, 16> Bundle(Candidates.size()); 8710 auto BundleIndex = 0u; 8711 for (auto *V : Candidates) { 8712 auto *GEP = cast<GetElementPtrInst>(V); 8713 auto *GEPIdx = GEP->idx_begin()->get(); 8714 assert(GEP->getNumIndices() == 1 || !isa<Constant>(GEPIdx)); 8715 Bundle[BundleIndex++] = GEPIdx; 8716 } 8717 8718 // Try and vectorize the indices. We are currently only interested in 8719 // gather-like cases of the form: 8720 // 8721 // ... = g[a[0] - b[0]] + g[a[1] - b[1]] + ... 8722 // 8723 // where the loads of "a", the loads of "b", and the subtractions can be 8724 // performed in parallel. It's likely that detecting this pattern in a 8725 // bottom-up phase will be simpler and less costly than building a 8726 // full-blown top-down phase beginning at the consecutive loads. 8727 Changed |= tryToVectorizeList(Bundle, R); 8728 } 8729 } 8730 return Changed; 8731 } 8732 8733 bool SLPVectorizerPass::vectorizeStoreChains(BoUpSLP &R) { 8734 bool Changed = false; 8735 // Sort by type, base pointers and values operand. Value operands must be 8736 // compatible (have the same opcode, same parent), otherwise it is 8737 // definitely not profitable to try to vectorize them. 8738 auto &&StoreSorter = [this](StoreInst *V, StoreInst *V2) { 8739 if (V->getPointerOperandType()->getTypeID() < 8740 V2->getPointerOperandType()->getTypeID()) 8741 return true; 8742 if (V->getPointerOperandType()->getTypeID() > 8743 V2->getPointerOperandType()->getTypeID()) 8744 return false; 8745 // UndefValues are compatible with all other values. 8746 if (isa<UndefValue>(V->getValueOperand()) || 8747 isa<UndefValue>(V2->getValueOperand())) 8748 return false; 8749 if (auto *I1 = dyn_cast<Instruction>(V->getValueOperand())) 8750 if (auto *I2 = dyn_cast<Instruction>(V2->getValueOperand())) { 8751 DomTreeNodeBase<llvm::BasicBlock> *NodeI1 = 8752 DT->getNode(I1->getParent()); 8753 DomTreeNodeBase<llvm::BasicBlock> *NodeI2 = 8754 DT->getNode(I2->getParent()); 8755 assert(NodeI1 && "Should only process reachable instructions"); 8756 assert(NodeI1 && "Should only process reachable instructions"); 8757 assert((NodeI1 == NodeI2) == 8758 (NodeI1->getDFSNumIn() == NodeI2->getDFSNumIn()) && 8759 "Different nodes should have different DFS numbers"); 8760 if (NodeI1 != NodeI2) 8761 return NodeI1->getDFSNumIn() < NodeI2->getDFSNumIn(); 8762 InstructionsState S = getSameOpcode({I1, I2}); 8763 if (S.getOpcode()) 8764 return false; 8765 return I1->getOpcode() < I2->getOpcode(); 8766 } 8767 if (isa<Constant>(V->getValueOperand()) && 8768 isa<Constant>(V2->getValueOperand())) 8769 return false; 8770 return V->getValueOperand()->getValueID() < 8771 V2->getValueOperand()->getValueID(); 8772 }; 8773 8774 auto &&AreCompatibleStores = [](StoreInst *V1, StoreInst *V2) { 8775 if (V1 == V2) 8776 return true; 8777 if (V1->getPointerOperandType() != V2->getPointerOperandType()) 8778 return false; 8779 // Undefs are compatible with any other value. 8780 if (isa<UndefValue>(V1->getValueOperand()) || 8781 isa<UndefValue>(V2->getValueOperand())) 8782 return true; 8783 if (auto *I1 = dyn_cast<Instruction>(V1->getValueOperand())) 8784 if (auto *I2 = dyn_cast<Instruction>(V2->getValueOperand())) { 8785 if (I1->getParent() != I2->getParent()) 8786 return false; 8787 InstructionsState S = getSameOpcode({I1, I2}); 8788 return S.getOpcode() > 0; 8789 } 8790 if (isa<Constant>(V1->getValueOperand()) && 8791 isa<Constant>(V2->getValueOperand())) 8792 return true; 8793 return V1->getValueOperand()->getValueID() == 8794 V2->getValueOperand()->getValueID(); 8795 }; 8796 8797 // Attempt to sort and vectorize each of the store-groups. 8798 for (auto &Pair : Stores) { 8799 if (Pair.second.size() < 2) 8800 continue; 8801 8802 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " 8803 << Pair.second.size() << ".\n"); 8804 8805 stable_sort(Pair.second, StoreSorter); 8806 8807 // Try to vectorize elements based on their compatibility. 8808 for (ArrayRef<StoreInst *>::iterator IncIt = Pair.second.begin(), 8809 E = Pair.second.end(); 8810 IncIt != E;) { 8811 8812 // Look for the next elements with the same type. 8813 ArrayRef<StoreInst *>::iterator SameTypeIt = IncIt; 8814 Type *EltTy = (*IncIt)->getPointerOperand()->getType(); 8815 8816 while (SameTypeIt != E && AreCompatibleStores(*SameTypeIt, *IncIt)) 8817 ++SameTypeIt; 8818 8819 // Try to vectorize them. 8820 unsigned NumElts = (SameTypeIt - IncIt); 8821 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize starting at stores (" 8822 << NumElts << ")\n"); 8823 if (NumElts > 1 && !EltTy->getPointerElementType()->isVectorTy() && 8824 vectorizeStores(makeArrayRef(IncIt, NumElts), R)) { 8825 // Success start over because instructions might have been changed. 8826 Changed = true; 8827 } 8828 8829 // Start over at the next instruction of a different type (or the end). 8830 IncIt = SameTypeIt; 8831 } 8832 } 8833 return Changed; 8834 } 8835 8836 char SLPVectorizer::ID = 0; 8837 8838 static const char lv_name[] = "SLP Vectorizer"; 8839 8840 INITIALIZE_PASS_BEGIN(SLPVectorizer, SV_NAME, lv_name, false, false) 8841 INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass) 8842 INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass) 8843 INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker) 8844 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass) 8845 INITIALIZE_PASS_DEPENDENCY(LoopSimplify) 8846 INITIALIZE_PASS_DEPENDENCY(DemandedBitsWrapperPass) 8847 INITIALIZE_PASS_DEPENDENCY(OptimizationRemarkEmitterWrapperPass) 8848 INITIALIZE_PASS_DEPENDENCY(InjectTLIMappingsLegacy) 8849 INITIALIZE_PASS_END(SLPVectorizer, SV_NAME, lv_name, false, false) 8850 8851 Pass *llvm::createSLPVectorizerPass() { return new SLPVectorizer(); } 8852