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 InstructionCost BoUpSLP::getEntryCost(const TreeEntry *E, 3625 ArrayRef<Value *> VectorizedVals) { 3626 ArrayRef<Value*> VL = E->Scalars; 3627 3628 Type *ScalarTy = VL[0]->getType(); 3629 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 3630 ScalarTy = SI->getValueOperand()->getType(); 3631 else if (CmpInst *CI = dyn_cast<CmpInst>(VL[0])) 3632 ScalarTy = CI->getOperand(0)->getType(); 3633 else if (auto *IE = dyn_cast<InsertElementInst>(VL[0])) 3634 ScalarTy = IE->getOperand(1)->getType(); 3635 auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); 3636 TTI::TargetCostKind CostKind = TTI::TCK_RecipThroughput; 3637 3638 // If we have computed a smaller type for the expression, update VecTy so 3639 // that the costs will be accurate. 3640 if (MinBWs.count(VL[0])) 3641 VecTy = FixedVectorType::get( 3642 IntegerType::get(F->getContext(), MinBWs[VL[0]].first), VL.size()); 3643 3644 unsigned ReuseShuffleNumbers = E->ReuseShuffleIndices.size(); 3645 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 3646 InstructionCost ReuseShuffleCost = 0; 3647 if (NeedToShuffleReuses) { 3648 ReuseShuffleCost = 3649 TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, VecTy, 3650 E->ReuseShuffleIndices); 3651 } 3652 // FIXME: it tries to fix a problem with MSVC buildbots. 3653 TargetTransformInfo &TTIRef = *TTI; 3654 auto &&AdjustExtractsCost = [this, &TTIRef, CostKind, VL, VecTy, 3655 VectorizedVals](InstructionCost &Cost, 3656 bool IsGather) { 3657 DenseMap<Value *, int> ExtractVectorsTys; 3658 for (auto *V : VL) { 3659 // If all users of instruction are going to be vectorized and this 3660 // instruction itself is not going to be vectorized, consider this 3661 // instruction as dead and remove its cost from the final cost of the 3662 // vectorized tree. 3663 if (!areAllUsersVectorized(cast<Instruction>(V), VectorizedVals) || 3664 (IsGather && ScalarToTreeEntry.count(V))) 3665 continue; 3666 auto *EE = cast<ExtractElementInst>(V); 3667 unsigned Idx = *getExtractIndex(EE); 3668 if (TTIRef.getNumberOfParts(VecTy) != 3669 TTIRef.getNumberOfParts(EE->getVectorOperandType())) { 3670 auto It = 3671 ExtractVectorsTys.try_emplace(EE->getVectorOperand(), Idx).first; 3672 It->getSecond() = std::min<int>(It->second, Idx); 3673 } 3674 // Take credit for instruction that will become dead. 3675 if (EE->hasOneUse()) { 3676 Instruction *Ext = EE->user_back(); 3677 if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) && 3678 all_of(Ext->users(), 3679 [](User *U) { return isa<GetElementPtrInst>(U); })) { 3680 // Use getExtractWithExtendCost() to calculate the cost of 3681 // extractelement/ext pair. 3682 Cost -= 3683 TTIRef.getExtractWithExtendCost(Ext->getOpcode(), Ext->getType(), 3684 EE->getVectorOperandType(), Idx); 3685 // Add back the cost of s|zext which is subtracted separately. 3686 Cost += TTIRef.getCastInstrCost( 3687 Ext->getOpcode(), Ext->getType(), EE->getType(), 3688 TTI::getCastContextHint(Ext), CostKind, Ext); 3689 continue; 3690 } 3691 } 3692 Cost -= TTIRef.getVectorInstrCost(Instruction::ExtractElement, 3693 EE->getVectorOperandType(), Idx); 3694 } 3695 // Add a cost for subvector extracts/inserts if required. 3696 for (const auto &Data : ExtractVectorsTys) { 3697 auto *EEVTy = cast<FixedVectorType>(Data.first->getType()); 3698 unsigned NumElts = VecTy->getNumElements(); 3699 if (TTIRef.getNumberOfParts(EEVTy) > TTIRef.getNumberOfParts(VecTy)) { 3700 unsigned Idx = (Data.second / NumElts) * NumElts; 3701 unsigned EENumElts = EEVTy->getNumElements(); 3702 if (Idx + NumElts <= EENumElts) { 3703 Cost += 3704 TTIRef.getShuffleCost(TargetTransformInfo::SK_ExtractSubvector, 3705 EEVTy, None, Idx, VecTy); 3706 } else { 3707 // Need to round up the subvector type vectorization factor to avoid a 3708 // crash in cost model functions. Make SubVT so that Idx + VF of SubVT 3709 // <= EENumElts. 3710 auto *SubVT = 3711 FixedVectorType::get(VecTy->getElementType(), EENumElts - Idx); 3712 Cost += 3713 TTIRef.getShuffleCost(TargetTransformInfo::SK_ExtractSubvector, 3714 EEVTy, None, Idx, SubVT); 3715 } 3716 } else { 3717 Cost += TTIRef.getShuffleCost(TargetTransformInfo::SK_InsertSubvector, 3718 VecTy, None, 0, EEVTy); 3719 } 3720 } 3721 }; 3722 if (E->State == TreeEntry::NeedToGather) { 3723 if (allConstant(VL)) 3724 return 0; 3725 if (isa<InsertElementInst>(VL[0])) 3726 return InstructionCost::getInvalid(); 3727 SmallVector<int> Mask; 3728 SmallVector<const TreeEntry *> Entries; 3729 Optional<TargetTransformInfo::ShuffleKind> Shuffle = 3730 isGatherShuffledEntry(E, Mask, Entries); 3731 if (Shuffle.hasValue()) { 3732 InstructionCost GatherCost = 0; 3733 if (ShuffleVectorInst::isIdentityMask(Mask)) { 3734 // Perfect match in the graph, will reuse the previously vectorized 3735 // node. Cost is 0. 3736 LLVM_DEBUG( 3737 dbgs() 3738 << "SLP: perfect diamond match for gather bundle that starts with " 3739 << *VL.front() << ".\n"); 3740 } else { 3741 LLVM_DEBUG(dbgs() << "SLP: shuffled " << Entries.size() 3742 << " entries for bundle that starts with " 3743 << *VL.front() << ".\n"); 3744 // Detected that instead of gather we can emit a shuffle of single/two 3745 // previously vectorized nodes. Add the cost of the permutation rather 3746 // than gather. 3747 GatherCost = TTI->getShuffleCost(*Shuffle, VecTy, Mask); 3748 } 3749 return ReuseShuffleCost + GatherCost; 3750 } 3751 if (isSplat(VL)) { 3752 // Found the broadcasting of the single scalar, calculate the cost as the 3753 // broadcast. 3754 return ReuseShuffleCost + 3755 TTI->getShuffleCost(TargetTransformInfo::SK_Broadcast, VecTy, None, 3756 0); 3757 } 3758 if (E->getOpcode() == Instruction::ExtractElement && allSameType(VL) && 3759 allSameBlock(VL) && 3760 !isa<ScalableVectorType>( 3761 cast<ExtractElementInst>(E->getMainOp())->getVectorOperandType())) { 3762 // Check that gather of extractelements can be represented as just a 3763 // shuffle of a single/two vectors the scalars are extracted from. 3764 SmallVector<int> Mask; 3765 Optional<TargetTransformInfo::ShuffleKind> ShuffleKind = 3766 isShuffle(VL, Mask); 3767 if (ShuffleKind.hasValue()) { 3768 // Found the bunch of extractelement instructions that must be gathered 3769 // into a vector and can be represented as a permutation elements in a 3770 // single input vector or of 2 input vectors. 3771 InstructionCost Cost = 3772 computeExtractCost(VL, VecTy, *ShuffleKind, Mask, *TTI); 3773 AdjustExtractsCost(Cost, /*IsGather=*/true); 3774 return ReuseShuffleCost + Cost; 3775 } 3776 } 3777 return ReuseShuffleCost + getGatherCost(VL); 3778 } 3779 assert((E->State == TreeEntry::Vectorize || 3780 E->State == TreeEntry::ScatterVectorize) && 3781 "Unhandled state"); 3782 assert(E->getOpcode() && allSameType(VL) && allSameBlock(VL) && "Invalid VL"); 3783 Instruction *VL0 = E->getMainOp(); 3784 unsigned ShuffleOrOp = 3785 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 3786 switch (ShuffleOrOp) { 3787 case Instruction::PHI: 3788 return 0; 3789 3790 case Instruction::ExtractValue: 3791 case Instruction::ExtractElement: { 3792 // The common cost of removal ExtractElement/ExtractValue instructions + 3793 // the cost of shuffles, if required to resuffle the original vector. 3794 InstructionCost CommonCost = 0; 3795 if (NeedToShuffleReuses) { 3796 unsigned Idx = 0; 3797 for (unsigned I : E->ReuseShuffleIndices) { 3798 if (ShuffleOrOp == Instruction::ExtractElement) { 3799 auto *EE = cast<ExtractElementInst>(VL[I]); 3800 ReuseShuffleCost -= TTI->getVectorInstrCost( 3801 Instruction::ExtractElement, EE->getVectorOperandType(), 3802 *getExtractIndex(EE)); 3803 } else { 3804 ReuseShuffleCost -= TTI->getVectorInstrCost( 3805 Instruction::ExtractElement, VecTy, Idx); 3806 ++Idx; 3807 } 3808 } 3809 Idx = ReuseShuffleNumbers; 3810 for (Value *V : VL) { 3811 if (ShuffleOrOp == Instruction::ExtractElement) { 3812 auto *EE = cast<ExtractElementInst>(V); 3813 ReuseShuffleCost += TTI->getVectorInstrCost( 3814 Instruction::ExtractElement, EE->getVectorOperandType(), 3815 *getExtractIndex(EE)); 3816 } else { 3817 --Idx; 3818 ReuseShuffleCost += TTI->getVectorInstrCost( 3819 Instruction::ExtractElement, VecTy, Idx); 3820 } 3821 } 3822 CommonCost = ReuseShuffleCost; 3823 } else if (!E->ReorderIndices.empty()) { 3824 SmallVector<int> NewMask; 3825 inversePermutation(E->ReorderIndices, NewMask); 3826 CommonCost = TTI->getShuffleCost( 3827 TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask); 3828 } 3829 if (ShuffleOrOp == Instruction::ExtractValue) { 3830 for (unsigned I = 0, E = VL.size(); I < E; ++I) { 3831 auto *EI = cast<Instruction>(VL[I]); 3832 // Take credit for instruction that will become dead. 3833 if (EI->hasOneUse()) { 3834 Instruction *Ext = EI->user_back(); 3835 if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) && 3836 all_of(Ext->users(), 3837 [](User *U) { return isa<GetElementPtrInst>(U); })) { 3838 // Use getExtractWithExtendCost() to calculate the cost of 3839 // extractelement/ext pair. 3840 CommonCost -= TTI->getExtractWithExtendCost( 3841 Ext->getOpcode(), Ext->getType(), VecTy, I); 3842 // Add back the cost of s|zext which is subtracted separately. 3843 CommonCost += TTI->getCastInstrCost( 3844 Ext->getOpcode(), Ext->getType(), EI->getType(), 3845 TTI::getCastContextHint(Ext), CostKind, Ext); 3846 continue; 3847 } 3848 } 3849 CommonCost -= 3850 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, I); 3851 } 3852 } else { 3853 AdjustExtractsCost(CommonCost, /*IsGather=*/false); 3854 } 3855 return CommonCost; 3856 } 3857 case Instruction::InsertElement: { 3858 auto *SrcVecTy = cast<FixedVectorType>(VL0->getType()); 3859 3860 unsigned const NumElts = SrcVecTy->getNumElements(); 3861 unsigned const NumScalars = VL.size(); 3862 APInt DemandedElts = APInt::getNullValue(NumElts); 3863 // TODO: Add support for Instruction::InsertValue. 3864 unsigned Offset = UINT_MAX; 3865 bool IsIdentity = true; 3866 SmallVector<int> ShuffleMask(NumElts, UndefMaskElem); 3867 for (unsigned I = 0; I < NumScalars; ++I) { 3868 Optional<int> InsertIdx = getInsertIndex(VL[I], 0); 3869 if (!InsertIdx || *InsertIdx == UndefMaskElem) 3870 continue; 3871 unsigned Idx = *InsertIdx; 3872 DemandedElts.setBit(Idx); 3873 if (Idx < Offset) { 3874 Offset = Idx; 3875 IsIdentity &= I == 0; 3876 } else { 3877 assert(Idx >= Offset && "Failed to find vector index offset"); 3878 IsIdentity &= Idx - Offset == I; 3879 } 3880 ShuffleMask[Idx] = I; 3881 } 3882 assert(Offset < NumElts && "Failed to find vector index offset"); 3883 3884 InstructionCost Cost = 0; 3885 Cost -= TTI->getScalarizationOverhead(SrcVecTy, DemandedElts, 3886 /*Insert*/ true, /*Extract*/ false); 3887 3888 if (IsIdentity && NumElts != NumScalars && Offset % NumScalars != 0) 3889 Cost += TTI->getShuffleCost( 3890 TargetTransformInfo::SK_InsertSubvector, SrcVecTy, /*Mask*/ None, 3891 Offset, 3892 FixedVectorType::get(SrcVecTy->getElementType(), NumScalars)); 3893 else if (!IsIdentity) 3894 Cost += TTI->getShuffleCost(TTI::SK_PermuteSingleSrc, SrcVecTy, 3895 ShuffleMask); 3896 3897 return Cost; 3898 } 3899 case Instruction::ZExt: 3900 case Instruction::SExt: 3901 case Instruction::FPToUI: 3902 case Instruction::FPToSI: 3903 case Instruction::FPExt: 3904 case Instruction::PtrToInt: 3905 case Instruction::IntToPtr: 3906 case Instruction::SIToFP: 3907 case Instruction::UIToFP: 3908 case Instruction::Trunc: 3909 case Instruction::FPTrunc: 3910 case Instruction::BitCast: { 3911 Type *SrcTy = VL0->getOperand(0)->getType(); 3912 InstructionCost ScalarEltCost = 3913 TTI->getCastInstrCost(E->getOpcode(), ScalarTy, SrcTy, 3914 TTI::getCastContextHint(VL0), CostKind, VL0); 3915 if (NeedToShuffleReuses) { 3916 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3917 } 3918 3919 // Calculate the cost of this instruction. 3920 InstructionCost ScalarCost = VL.size() * ScalarEltCost; 3921 3922 auto *SrcVecTy = FixedVectorType::get(SrcTy, VL.size()); 3923 InstructionCost VecCost = 0; 3924 // Check if the values are candidates to demote. 3925 if (!MinBWs.count(VL0) || VecTy != SrcVecTy) { 3926 VecCost = 3927 ReuseShuffleCost + 3928 TTI->getCastInstrCost(E->getOpcode(), VecTy, SrcVecTy, 3929 TTI::getCastContextHint(VL0), CostKind, VL0); 3930 } 3931 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3932 return VecCost - ScalarCost; 3933 } 3934 case Instruction::FCmp: 3935 case Instruction::ICmp: 3936 case Instruction::Select: { 3937 // Calculate the cost of this instruction. 3938 InstructionCost ScalarEltCost = 3939 TTI->getCmpSelInstrCost(E->getOpcode(), ScalarTy, Builder.getInt1Ty(), 3940 CmpInst::BAD_ICMP_PREDICATE, CostKind, VL0); 3941 if (NeedToShuffleReuses) { 3942 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3943 } 3944 auto *MaskTy = FixedVectorType::get(Builder.getInt1Ty(), VL.size()); 3945 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3946 3947 // Check if all entries in VL are either compares or selects with compares 3948 // as condition that have the same predicates. 3949 CmpInst::Predicate VecPred = CmpInst::BAD_ICMP_PREDICATE; 3950 bool First = true; 3951 for (auto *V : VL) { 3952 CmpInst::Predicate CurrentPred; 3953 auto MatchCmp = m_Cmp(CurrentPred, m_Value(), m_Value()); 3954 if ((!match(V, m_Select(MatchCmp, m_Value(), m_Value())) && 3955 !match(V, MatchCmp)) || 3956 (!First && VecPred != CurrentPred)) { 3957 VecPred = CmpInst::BAD_ICMP_PREDICATE; 3958 break; 3959 } 3960 First = false; 3961 VecPred = CurrentPred; 3962 } 3963 3964 InstructionCost VecCost = TTI->getCmpSelInstrCost( 3965 E->getOpcode(), VecTy, MaskTy, VecPred, CostKind, VL0); 3966 // Check if it is possible and profitable to use min/max for selects in 3967 // VL. 3968 // 3969 auto IntrinsicAndUse = canConvertToMinOrMaxIntrinsic(VL); 3970 if (IntrinsicAndUse.first != Intrinsic::not_intrinsic) { 3971 IntrinsicCostAttributes CostAttrs(IntrinsicAndUse.first, VecTy, 3972 {VecTy, VecTy}); 3973 InstructionCost IntrinsicCost = 3974 TTI->getIntrinsicInstrCost(CostAttrs, CostKind); 3975 // If the selects are the only uses of the compares, they will be dead 3976 // and we can adjust the cost by removing their cost. 3977 if (IntrinsicAndUse.second) 3978 IntrinsicCost -= 3979 TTI->getCmpSelInstrCost(Instruction::ICmp, VecTy, MaskTy, 3980 CmpInst::BAD_ICMP_PREDICATE, CostKind); 3981 VecCost = std::min(VecCost, IntrinsicCost); 3982 } 3983 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3984 return ReuseShuffleCost + VecCost - ScalarCost; 3985 } 3986 case Instruction::FNeg: 3987 case Instruction::Add: 3988 case Instruction::FAdd: 3989 case Instruction::Sub: 3990 case Instruction::FSub: 3991 case Instruction::Mul: 3992 case Instruction::FMul: 3993 case Instruction::UDiv: 3994 case Instruction::SDiv: 3995 case Instruction::FDiv: 3996 case Instruction::URem: 3997 case Instruction::SRem: 3998 case Instruction::FRem: 3999 case Instruction::Shl: 4000 case Instruction::LShr: 4001 case Instruction::AShr: 4002 case Instruction::And: 4003 case Instruction::Or: 4004 case Instruction::Xor: { 4005 // Certain instructions can be cheaper to vectorize if they have a 4006 // constant second vector operand. 4007 TargetTransformInfo::OperandValueKind Op1VK = 4008 TargetTransformInfo::OK_AnyValue; 4009 TargetTransformInfo::OperandValueKind Op2VK = 4010 TargetTransformInfo::OK_UniformConstantValue; 4011 TargetTransformInfo::OperandValueProperties Op1VP = 4012 TargetTransformInfo::OP_None; 4013 TargetTransformInfo::OperandValueProperties Op2VP = 4014 TargetTransformInfo::OP_PowerOf2; 4015 4016 // If all operands are exactly the same ConstantInt then set the 4017 // operand kind to OK_UniformConstantValue. 4018 // If instead not all operands are constants, then set the operand kind 4019 // to OK_AnyValue. If all operands are constants but not the same, 4020 // then set the operand kind to OK_NonUniformConstantValue. 4021 ConstantInt *CInt0 = nullptr; 4022 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 4023 const Instruction *I = cast<Instruction>(VL[i]); 4024 unsigned OpIdx = isa<BinaryOperator>(I) ? 1 : 0; 4025 ConstantInt *CInt = dyn_cast<ConstantInt>(I->getOperand(OpIdx)); 4026 if (!CInt) { 4027 Op2VK = TargetTransformInfo::OK_AnyValue; 4028 Op2VP = TargetTransformInfo::OP_None; 4029 break; 4030 } 4031 if (Op2VP == TargetTransformInfo::OP_PowerOf2 && 4032 !CInt->getValue().isPowerOf2()) 4033 Op2VP = TargetTransformInfo::OP_None; 4034 if (i == 0) { 4035 CInt0 = CInt; 4036 continue; 4037 } 4038 if (CInt0 != CInt) 4039 Op2VK = TargetTransformInfo::OK_NonUniformConstantValue; 4040 } 4041 4042 SmallVector<const Value *, 4> Operands(VL0->operand_values()); 4043 InstructionCost ScalarEltCost = 4044 TTI->getArithmeticInstrCost(E->getOpcode(), ScalarTy, CostKind, Op1VK, 4045 Op2VK, Op1VP, Op2VP, Operands, VL0); 4046 if (NeedToShuffleReuses) { 4047 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 4048 } 4049 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 4050 InstructionCost VecCost = 4051 TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind, Op1VK, 4052 Op2VK, Op1VP, Op2VP, Operands, VL0); 4053 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 4054 return ReuseShuffleCost + VecCost - ScalarCost; 4055 } 4056 case Instruction::GetElementPtr: { 4057 TargetTransformInfo::OperandValueKind Op1VK = 4058 TargetTransformInfo::OK_AnyValue; 4059 TargetTransformInfo::OperandValueKind Op2VK = 4060 TargetTransformInfo::OK_UniformConstantValue; 4061 4062 InstructionCost ScalarEltCost = TTI->getArithmeticInstrCost( 4063 Instruction::Add, ScalarTy, CostKind, Op1VK, Op2VK); 4064 if (NeedToShuffleReuses) { 4065 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 4066 } 4067 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 4068 InstructionCost VecCost = TTI->getArithmeticInstrCost( 4069 Instruction::Add, VecTy, CostKind, Op1VK, Op2VK); 4070 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 4071 return ReuseShuffleCost + VecCost - ScalarCost; 4072 } 4073 case Instruction::Load: { 4074 // Cost of wide load - cost of scalar loads. 4075 Align alignment = cast<LoadInst>(VL0)->getAlign(); 4076 InstructionCost ScalarEltCost = TTI->getMemoryOpCost( 4077 Instruction::Load, ScalarTy, alignment, 0, CostKind, VL0); 4078 if (NeedToShuffleReuses) { 4079 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 4080 } 4081 InstructionCost ScalarLdCost = VecTy->getNumElements() * ScalarEltCost; 4082 InstructionCost VecLdCost; 4083 if (E->State == TreeEntry::Vectorize) { 4084 VecLdCost = TTI->getMemoryOpCost(Instruction::Load, VecTy, alignment, 0, 4085 CostKind, VL0); 4086 } else { 4087 assert(E->State == TreeEntry::ScatterVectorize && "Unknown EntryState"); 4088 Align CommonAlignment = alignment; 4089 for (Value *V : VL) 4090 CommonAlignment = 4091 commonAlignment(CommonAlignment, cast<LoadInst>(V)->getAlign()); 4092 VecLdCost = TTI->getGatherScatterOpCost( 4093 Instruction::Load, VecTy, cast<LoadInst>(VL0)->getPointerOperand(), 4094 /*VariableMask=*/false, alignment, CostKind, VL0); 4095 } 4096 if (!NeedToShuffleReuses && !E->ReorderIndices.empty()) { 4097 SmallVector<int> NewMask; 4098 inversePermutation(E->ReorderIndices, NewMask); 4099 VecLdCost += TTI->getShuffleCost( 4100 TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask); 4101 } 4102 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecLdCost, ScalarLdCost)); 4103 return ReuseShuffleCost + VecLdCost - ScalarLdCost; 4104 } 4105 case Instruction::Store: { 4106 // We know that we can merge the stores. Calculate the cost. 4107 bool IsReorder = !E->ReorderIndices.empty(); 4108 auto *SI = 4109 cast<StoreInst>(IsReorder ? VL[E->ReorderIndices.front()] : VL0); 4110 Align Alignment = SI->getAlign(); 4111 InstructionCost ScalarEltCost = TTI->getMemoryOpCost( 4112 Instruction::Store, ScalarTy, Alignment, 0, CostKind, VL0); 4113 InstructionCost ScalarStCost = VecTy->getNumElements() * ScalarEltCost; 4114 InstructionCost VecStCost = TTI->getMemoryOpCost( 4115 Instruction::Store, VecTy, Alignment, 0, CostKind, VL0); 4116 if (IsReorder) { 4117 SmallVector<int> NewMask; 4118 inversePermutation(E->ReorderIndices, NewMask); 4119 VecStCost += TTI->getShuffleCost( 4120 TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask); 4121 } 4122 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecStCost, ScalarStCost)); 4123 return VecStCost - ScalarStCost; 4124 } 4125 case Instruction::Call: { 4126 CallInst *CI = cast<CallInst>(VL0); 4127 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 4128 4129 // Calculate the cost of the scalar and vector calls. 4130 IntrinsicCostAttributes CostAttrs(ID, *CI, 1); 4131 InstructionCost ScalarEltCost = 4132 TTI->getIntrinsicInstrCost(CostAttrs, CostKind); 4133 if (NeedToShuffleReuses) { 4134 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 4135 } 4136 InstructionCost ScalarCallCost = VecTy->getNumElements() * ScalarEltCost; 4137 4138 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 4139 InstructionCost VecCallCost = 4140 std::min(VecCallCosts.first, VecCallCosts.second); 4141 4142 LLVM_DEBUG(dbgs() << "SLP: Call cost " << VecCallCost - ScalarCallCost 4143 << " (" << VecCallCost << "-" << ScalarCallCost << ")" 4144 << " for " << *CI << "\n"); 4145 4146 return ReuseShuffleCost + VecCallCost - ScalarCallCost; 4147 } 4148 case Instruction::ShuffleVector: { 4149 assert(E->isAltShuffle() && 4150 ((Instruction::isBinaryOp(E->getOpcode()) && 4151 Instruction::isBinaryOp(E->getAltOpcode())) || 4152 (Instruction::isCast(E->getOpcode()) && 4153 Instruction::isCast(E->getAltOpcode()))) && 4154 "Invalid Shuffle Vector Operand"); 4155 InstructionCost ScalarCost = 0; 4156 if (NeedToShuffleReuses) { 4157 for (unsigned Idx : E->ReuseShuffleIndices) { 4158 Instruction *I = cast<Instruction>(VL[Idx]); 4159 ReuseShuffleCost -= TTI->getInstructionCost(I, CostKind); 4160 } 4161 for (Value *V : VL) { 4162 Instruction *I = cast<Instruction>(V); 4163 ReuseShuffleCost += TTI->getInstructionCost(I, CostKind); 4164 } 4165 } 4166 for (Value *V : VL) { 4167 Instruction *I = cast<Instruction>(V); 4168 assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode"); 4169 ScalarCost += TTI->getInstructionCost(I, CostKind); 4170 } 4171 // VecCost is equal to sum of the cost of creating 2 vectors 4172 // and the cost of creating shuffle. 4173 InstructionCost VecCost = 0; 4174 if (Instruction::isBinaryOp(E->getOpcode())) { 4175 VecCost = TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind); 4176 VecCost += TTI->getArithmeticInstrCost(E->getAltOpcode(), VecTy, 4177 CostKind); 4178 } else { 4179 Type *Src0SclTy = E->getMainOp()->getOperand(0)->getType(); 4180 Type *Src1SclTy = E->getAltOp()->getOperand(0)->getType(); 4181 auto *Src0Ty = FixedVectorType::get(Src0SclTy, VL.size()); 4182 auto *Src1Ty = FixedVectorType::get(Src1SclTy, VL.size()); 4183 VecCost = TTI->getCastInstrCost(E->getOpcode(), VecTy, Src0Ty, 4184 TTI::CastContextHint::None, CostKind); 4185 VecCost += TTI->getCastInstrCost(E->getAltOpcode(), VecTy, Src1Ty, 4186 TTI::CastContextHint::None, CostKind); 4187 } 4188 4189 SmallVector<int> Mask(E->Scalars.size()); 4190 for (unsigned I = 0, End = E->Scalars.size(); I < End; ++I) { 4191 auto *OpInst = cast<Instruction>(E->Scalars[I]); 4192 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 4193 Mask[I] = I + (OpInst->getOpcode() == E->getAltOpcode() ? End : 0); 4194 } 4195 VecCost += 4196 TTI->getShuffleCost(TargetTransformInfo::SK_Select, VecTy, Mask, 0); 4197 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 4198 return ReuseShuffleCost + VecCost - ScalarCost; 4199 } 4200 default: 4201 llvm_unreachable("Unknown instruction"); 4202 } 4203 } 4204 4205 bool BoUpSLP::isFullyVectorizableTinyTree() const { 4206 LLVM_DEBUG(dbgs() << "SLP: Check whether the tree with height " 4207 << VectorizableTree.size() << " is fully vectorizable .\n"); 4208 4209 // We only handle trees of heights 1 and 2. 4210 if (VectorizableTree.size() == 1 && 4211 VectorizableTree[0]->State == TreeEntry::Vectorize) 4212 return true; 4213 4214 if (VectorizableTree.size() != 2) 4215 return false; 4216 4217 // Handle splat and all-constants stores. Also try to vectorize tiny trees 4218 // with the second gather nodes if they have less scalar operands rather than 4219 // the initial tree element (may be profitable to shuffle the second gather) 4220 // or they are extractelements, which form shuffle. 4221 SmallVector<int> Mask; 4222 if (VectorizableTree[0]->State == TreeEntry::Vectorize && 4223 (allConstant(VectorizableTree[1]->Scalars) || 4224 isSplat(VectorizableTree[1]->Scalars) || 4225 (VectorizableTree[1]->State == TreeEntry::NeedToGather && 4226 VectorizableTree[1]->Scalars.size() < 4227 VectorizableTree[0]->Scalars.size()) || 4228 (VectorizableTree[1]->State == TreeEntry::NeedToGather && 4229 VectorizableTree[1]->getOpcode() == Instruction::ExtractElement && 4230 isShuffle(VectorizableTree[1]->Scalars, Mask)))) 4231 return true; 4232 4233 // Gathering cost would be too much for tiny trees. 4234 if (VectorizableTree[0]->State == TreeEntry::NeedToGather || 4235 VectorizableTree[1]->State == TreeEntry::NeedToGather) 4236 return false; 4237 4238 return true; 4239 } 4240 4241 static bool isLoadCombineCandidateImpl(Value *Root, unsigned NumElts, 4242 TargetTransformInfo *TTI, 4243 bool MustMatchOrInst) { 4244 // Look past the root to find a source value. Arbitrarily follow the 4245 // path through operand 0 of any 'or'. Also, peek through optional 4246 // shift-left-by-multiple-of-8-bits. 4247 Value *ZextLoad = Root; 4248 const APInt *ShAmtC; 4249 bool FoundOr = false; 4250 while (!isa<ConstantExpr>(ZextLoad) && 4251 (match(ZextLoad, m_Or(m_Value(), m_Value())) || 4252 (match(ZextLoad, m_Shl(m_Value(), m_APInt(ShAmtC))) && 4253 ShAmtC->urem(8) == 0))) { 4254 auto *BinOp = cast<BinaryOperator>(ZextLoad); 4255 ZextLoad = BinOp->getOperand(0); 4256 if (BinOp->getOpcode() == Instruction::Or) 4257 FoundOr = true; 4258 } 4259 // Check if the input is an extended load of the required or/shift expression. 4260 Value *LoadPtr; 4261 if ((MustMatchOrInst && !FoundOr) || ZextLoad == Root || 4262 !match(ZextLoad, m_ZExt(m_Load(m_Value(LoadPtr))))) 4263 return false; 4264 4265 // Require that the total load bit width is a legal integer type. 4266 // For example, <8 x i8> --> i64 is a legal integer on a 64-bit target. 4267 // But <16 x i8> --> i128 is not, so the backend probably can't reduce it. 4268 Type *SrcTy = LoadPtr->getType()->getPointerElementType(); 4269 unsigned LoadBitWidth = SrcTy->getIntegerBitWidth() * NumElts; 4270 if (!TTI->isTypeLegal(IntegerType::get(Root->getContext(), LoadBitWidth))) 4271 return false; 4272 4273 // Everything matched - assume that we can fold the whole sequence using 4274 // load combining. 4275 LLVM_DEBUG(dbgs() << "SLP: Assume load combining for tree starting at " 4276 << *(cast<Instruction>(Root)) << "\n"); 4277 4278 return true; 4279 } 4280 4281 bool BoUpSLP::isLoadCombineReductionCandidate(RecurKind RdxKind) const { 4282 if (RdxKind != RecurKind::Or) 4283 return false; 4284 4285 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 4286 Value *FirstReduced = VectorizableTree[0]->Scalars[0]; 4287 return isLoadCombineCandidateImpl(FirstReduced, NumElts, TTI, 4288 /* MatchOr */ false); 4289 } 4290 4291 bool BoUpSLP::isLoadCombineCandidate() const { 4292 // Peek through a final sequence of stores and check if all operations are 4293 // likely to be load-combined. 4294 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 4295 for (Value *Scalar : VectorizableTree[0]->Scalars) { 4296 Value *X; 4297 if (!match(Scalar, m_Store(m_Value(X), m_Value())) || 4298 !isLoadCombineCandidateImpl(X, NumElts, TTI, /* MatchOr */ true)) 4299 return false; 4300 } 4301 return true; 4302 } 4303 4304 bool BoUpSLP::isTreeTinyAndNotFullyVectorizable() const { 4305 // No need to vectorize inserts of gathered values. 4306 if (VectorizableTree.size() == 2 && 4307 isa<InsertElementInst>(VectorizableTree[0]->Scalars[0]) && 4308 VectorizableTree[1]->State == TreeEntry::NeedToGather) 4309 return true; 4310 4311 // We can vectorize the tree if its size is greater than or equal to the 4312 // minimum size specified by the MinTreeSize command line option. 4313 if (VectorizableTree.size() >= MinTreeSize) 4314 return false; 4315 4316 // If we have a tiny tree (a tree whose size is less than MinTreeSize), we 4317 // can vectorize it if we can prove it fully vectorizable. 4318 if (isFullyVectorizableTinyTree()) 4319 return false; 4320 4321 assert(VectorizableTree.empty() 4322 ? ExternalUses.empty() 4323 : true && "We shouldn't have any external users"); 4324 4325 // Otherwise, we can't vectorize the tree. It is both tiny and not fully 4326 // vectorizable. 4327 return true; 4328 } 4329 4330 InstructionCost BoUpSLP::getSpillCost() const { 4331 // Walk from the bottom of the tree to the top, tracking which values are 4332 // live. When we see a call instruction that is not part of our tree, 4333 // query TTI to see if there is a cost to keeping values live over it 4334 // (for example, if spills and fills are required). 4335 unsigned BundleWidth = VectorizableTree.front()->Scalars.size(); 4336 InstructionCost Cost = 0; 4337 4338 SmallPtrSet<Instruction*, 4> LiveValues; 4339 Instruction *PrevInst = nullptr; 4340 4341 // The entries in VectorizableTree are not necessarily ordered by their 4342 // position in basic blocks. Collect them and order them by dominance so later 4343 // instructions are guaranteed to be visited first. For instructions in 4344 // different basic blocks, we only scan to the beginning of the block, so 4345 // their order does not matter, as long as all instructions in a basic block 4346 // are grouped together. Using dominance ensures a deterministic order. 4347 SmallVector<Instruction *, 16> OrderedScalars; 4348 for (const auto &TEPtr : VectorizableTree) { 4349 Instruction *Inst = dyn_cast<Instruction>(TEPtr->Scalars[0]); 4350 if (!Inst) 4351 continue; 4352 OrderedScalars.push_back(Inst); 4353 } 4354 llvm::sort(OrderedScalars, [&](Instruction *A, Instruction *B) { 4355 auto *NodeA = DT->getNode(A->getParent()); 4356 auto *NodeB = DT->getNode(B->getParent()); 4357 assert(NodeA && "Should only process reachable instructions"); 4358 assert(NodeB && "Should only process reachable instructions"); 4359 assert((NodeA == NodeB) == (NodeA->getDFSNumIn() == NodeB->getDFSNumIn()) && 4360 "Different nodes should have different DFS numbers"); 4361 if (NodeA != NodeB) 4362 return NodeA->getDFSNumIn() < NodeB->getDFSNumIn(); 4363 return B->comesBefore(A); 4364 }); 4365 4366 for (Instruction *Inst : OrderedScalars) { 4367 if (!PrevInst) { 4368 PrevInst = Inst; 4369 continue; 4370 } 4371 4372 // Update LiveValues. 4373 LiveValues.erase(PrevInst); 4374 for (auto &J : PrevInst->operands()) { 4375 if (isa<Instruction>(&*J) && getTreeEntry(&*J)) 4376 LiveValues.insert(cast<Instruction>(&*J)); 4377 } 4378 4379 LLVM_DEBUG({ 4380 dbgs() << "SLP: #LV: " << LiveValues.size(); 4381 for (auto *X : LiveValues) 4382 dbgs() << " " << X->getName(); 4383 dbgs() << ", Looking at "; 4384 Inst->dump(); 4385 }); 4386 4387 // Now find the sequence of instructions between PrevInst and Inst. 4388 unsigned NumCalls = 0; 4389 BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(), 4390 PrevInstIt = 4391 PrevInst->getIterator().getReverse(); 4392 while (InstIt != PrevInstIt) { 4393 if (PrevInstIt == PrevInst->getParent()->rend()) { 4394 PrevInstIt = Inst->getParent()->rbegin(); 4395 continue; 4396 } 4397 4398 // Debug information does not impact spill cost. 4399 if ((isa<CallInst>(&*PrevInstIt) && 4400 !isa<DbgInfoIntrinsic>(&*PrevInstIt)) && 4401 &*PrevInstIt != PrevInst) 4402 NumCalls++; 4403 4404 ++PrevInstIt; 4405 } 4406 4407 if (NumCalls) { 4408 SmallVector<Type*, 4> V; 4409 for (auto *II : LiveValues) { 4410 auto *ScalarTy = II->getType(); 4411 if (auto *VectorTy = dyn_cast<FixedVectorType>(ScalarTy)) 4412 ScalarTy = VectorTy->getElementType(); 4413 V.push_back(FixedVectorType::get(ScalarTy, BundleWidth)); 4414 } 4415 Cost += NumCalls * TTI->getCostOfKeepingLiveOverCall(V); 4416 } 4417 4418 PrevInst = Inst; 4419 } 4420 4421 return Cost; 4422 } 4423 4424 InstructionCost BoUpSLP::getTreeCost(ArrayRef<Value *> VectorizedVals) { 4425 InstructionCost Cost = 0; 4426 LLVM_DEBUG(dbgs() << "SLP: Calculating cost for tree of size " 4427 << VectorizableTree.size() << ".\n"); 4428 4429 unsigned BundleWidth = VectorizableTree[0]->Scalars.size(); 4430 4431 for (unsigned I = 0, E = VectorizableTree.size(); I < E; ++I) { 4432 TreeEntry &TE = *VectorizableTree[I].get(); 4433 4434 InstructionCost C = getEntryCost(&TE, VectorizedVals); 4435 Cost += C; 4436 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C 4437 << " for bundle that starts with " << *TE.Scalars[0] 4438 << ".\n" 4439 << "SLP: Current total cost = " << Cost << "\n"); 4440 } 4441 4442 SmallPtrSet<Value *, 16> ExtractCostCalculated; 4443 InstructionCost ExtractCost = 0; 4444 SmallBitVector IsIdentity; 4445 SmallVector<unsigned> VF; 4446 SmallVector<SmallVector<int>> ShuffleMask; 4447 SmallVector<Value *> FirstUsers; 4448 SmallVector<APInt> DemandedElts; 4449 for (ExternalUser &EU : ExternalUses) { 4450 // We only add extract cost once for the same scalar. 4451 if (!ExtractCostCalculated.insert(EU.Scalar).second) 4452 continue; 4453 4454 // Uses by ephemeral values are free (because the ephemeral value will be 4455 // removed prior to code generation, and so the extraction will be 4456 // removed as well). 4457 if (EphValues.count(EU.User)) 4458 continue; 4459 4460 // No extract cost for vector "scalar" 4461 if (isa<FixedVectorType>(EU.Scalar->getType())) 4462 continue; 4463 4464 // Already counted the cost for external uses when tried to adjust the cost 4465 // for extractelements, no need to add it again. 4466 if (isa<ExtractElementInst>(EU.Scalar)) 4467 continue; 4468 4469 // If found user is an insertelement, do not calculate extract cost but try 4470 // to detect it as a final shuffled/identity match. 4471 if (EU.User && isa<InsertElementInst>(EU.User)) { 4472 if (auto *FTy = dyn_cast<FixedVectorType>(EU.User->getType())) { 4473 Optional<int> InsertIdx = getInsertIndex(EU.User, 0); 4474 if (!InsertIdx || *InsertIdx == UndefMaskElem) 4475 continue; 4476 Value *VU = EU.User; 4477 auto *It = find_if(FirstUsers, [VU](Value *V) { 4478 // Checks if 2 insertelements are from the same buildvector. 4479 if (VU->getType() != V->getType()) 4480 return false; 4481 auto *IE1 = cast<InsertElementInst>(VU); 4482 auto *IE2 = cast<InsertElementInst>(V); 4483 // Go though of insertelement instructions trying to find either VU as 4484 // the original vector for IE2 or V as the original vector for IE1. 4485 do { 4486 if (IE1 == VU || IE2 == V) 4487 return true; 4488 if (IE1) 4489 IE1 = dyn_cast<InsertElementInst>(IE1->getOperand(0)); 4490 if (IE2) 4491 IE2 = dyn_cast<InsertElementInst>(IE2->getOperand(0)); 4492 } while (IE1 || IE2); 4493 return false; 4494 }); 4495 int VecId = -1; 4496 if (It == FirstUsers.end()) { 4497 VF.push_back(FTy->getNumElements()); 4498 ShuffleMask.emplace_back(VF.back(), UndefMaskElem); 4499 FirstUsers.push_back(EU.User); 4500 DemandedElts.push_back(APInt::getNullValue(VF.back())); 4501 IsIdentity.push_back(true); 4502 VecId = FirstUsers.size() - 1; 4503 } else { 4504 VecId = std::distance(FirstUsers.begin(), It); 4505 } 4506 int Idx = *InsertIdx; 4507 ShuffleMask[VecId][Idx] = EU.Lane; 4508 IsIdentity.set(IsIdentity.test(VecId) & 4509 (EU.Lane == Idx || EU.Lane == UndefMaskElem)); 4510 DemandedElts[VecId].setBit(Idx); 4511 } 4512 } 4513 4514 // If we plan to rewrite the tree in a smaller type, we will need to sign 4515 // extend the extracted value back to the original type. Here, we account 4516 // for the extract and the added cost of the sign extend if needed. 4517 auto *VecTy = FixedVectorType::get(EU.Scalar->getType(), BundleWidth); 4518 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 4519 if (MinBWs.count(ScalarRoot)) { 4520 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 4521 auto Extend = 4522 MinBWs[ScalarRoot].second ? Instruction::SExt : Instruction::ZExt; 4523 VecTy = FixedVectorType::get(MinTy, BundleWidth); 4524 ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(), 4525 VecTy, EU.Lane); 4526 } else { 4527 ExtractCost += 4528 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, EU.Lane); 4529 } 4530 } 4531 4532 InstructionCost SpillCost = getSpillCost(); 4533 Cost += SpillCost + ExtractCost; 4534 for (int I = 0, E = FirstUsers.size(); I < E; ++I) { 4535 if (!IsIdentity.test(I)) { 4536 InstructionCost C = TTI->getShuffleCost( 4537 TTI::SK_PermuteSingleSrc, 4538 cast<FixedVectorType>(FirstUsers[I]->getType()), ShuffleMask[I]); 4539 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C 4540 << " for final shuffle of insertelement external users " 4541 << *VectorizableTree.front()->Scalars.front() << ".\n" 4542 << "SLP: Current total cost = " << Cost << "\n"); 4543 Cost += C; 4544 } 4545 unsigned VF = ShuffleMask[I].size(); 4546 for (int &Mask : ShuffleMask[I]) 4547 Mask = (Mask == UndefMaskElem ? 0 : VF) + Mask; 4548 InstructionCost C = TTI->getShuffleCost( 4549 TTI::SK_PermuteTwoSrc, cast<FixedVectorType>(FirstUsers[I]->getType()), 4550 ShuffleMask[I]); 4551 LLVM_DEBUG( 4552 dbgs() 4553 << "SLP: Adding cost " << C 4554 << " for final shuffle of vector node and external insertelement users " 4555 << *VectorizableTree.front()->Scalars.front() << ".\n" 4556 << "SLP: Current total cost = " << Cost << "\n"); 4557 Cost += C; 4558 InstructionCost InsertCost = TTI->getScalarizationOverhead( 4559 cast<FixedVectorType>(FirstUsers[I]->getType()), DemandedElts[I], 4560 /*Insert*/ true, 4561 /*Extract*/ false); 4562 Cost -= InsertCost; 4563 LLVM_DEBUG(dbgs() << "SLP: subtracting the cost " << InsertCost 4564 << " for insertelements gather.\n" 4565 << "SLP: Current total cost = " << Cost << "\n"); 4566 } 4567 4568 #ifndef NDEBUG 4569 SmallString<256> Str; 4570 { 4571 raw_svector_ostream OS(Str); 4572 OS << "SLP: Spill Cost = " << SpillCost << ".\n" 4573 << "SLP: Extract Cost = " << ExtractCost << ".\n" 4574 << "SLP: Total Cost = " << Cost << ".\n"; 4575 } 4576 LLVM_DEBUG(dbgs() << Str); 4577 if (ViewSLPTree) 4578 ViewGraph(this, "SLP" + F->getName(), false, Str); 4579 #endif 4580 4581 return Cost; 4582 } 4583 4584 Optional<TargetTransformInfo::ShuffleKind> 4585 BoUpSLP::isGatherShuffledEntry(const TreeEntry *TE, SmallVectorImpl<int> &Mask, 4586 SmallVectorImpl<const TreeEntry *> &Entries) { 4587 // TODO: currently checking only for Scalars in the tree entry, need to count 4588 // reused elements too for better cost estimation. 4589 Mask.assign(TE->Scalars.size(), UndefMaskElem); 4590 Entries.clear(); 4591 // Build a lists of values to tree entries. 4592 DenseMap<Value *, SmallPtrSet<const TreeEntry *, 4>> ValueToTEs; 4593 for (const std::unique_ptr<TreeEntry> &EntryPtr : VectorizableTree) { 4594 if (EntryPtr.get() == TE) 4595 break; 4596 if (EntryPtr->State != TreeEntry::NeedToGather) 4597 continue; 4598 for (Value *V : EntryPtr->Scalars) 4599 ValueToTEs.try_emplace(V).first->getSecond().insert(EntryPtr.get()); 4600 } 4601 // Find all tree entries used by the gathered values. If no common entries 4602 // found - not a shuffle. 4603 // Here we build a set of tree nodes for each gathered value and trying to 4604 // find the intersection between these sets. If we have at least one common 4605 // tree node for each gathered value - we have just a permutation of the 4606 // single vector. If we have 2 different sets, we're in situation where we 4607 // have a permutation of 2 input vectors. 4608 SmallVector<SmallPtrSet<const TreeEntry *, 4>> UsedTEs; 4609 DenseMap<Value *, int> UsedValuesEntry; 4610 for (Value *V : TE->Scalars) { 4611 if (isa<UndefValue>(V)) 4612 continue; 4613 // Build a list of tree entries where V is used. 4614 SmallPtrSet<const TreeEntry *, 4> VToTEs; 4615 auto It = ValueToTEs.find(V); 4616 if (It != ValueToTEs.end()) 4617 VToTEs = It->second; 4618 if (const TreeEntry *VTE = getTreeEntry(V)) 4619 VToTEs.insert(VTE); 4620 if (VToTEs.empty()) 4621 return None; 4622 if (UsedTEs.empty()) { 4623 // The first iteration, just insert the list of nodes to vector. 4624 UsedTEs.push_back(VToTEs); 4625 } else { 4626 // Need to check if there are any previously used tree nodes which use V. 4627 // If there are no such nodes, consider that we have another one input 4628 // vector. 4629 SmallPtrSet<const TreeEntry *, 4> SavedVToTEs(VToTEs); 4630 unsigned Idx = 0; 4631 for (SmallPtrSet<const TreeEntry *, 4> &Set : UsedTEs) { 4632 // Do we have a non-empty intersection of previously listed tree entries 4633 // and tree entries using current V? 4634 set_intersect(VToTEs, Set); 4635 if (!VToTEs.empty()) { 4636 // Yes, write the new subset and continue analysis for the next 4637 // scalar. 4638 Set.swap(VToTEs); 4639 break; 4640 } 4641 VToTEs = SavedVToTEs; 4642 ++Idx; 4643 } 4644 // No non-empty intersection found - need to add a second set of possible 4645 // source vectors. 4646 if (Idx == UsedTEs.size()) { 4647 // If the number of input vectors is greater than 2 - not a permutation, 4648 // fallback to the regular gather. 4649 if (UsedTEs.size() == 2) 4650 return None; 4651 UsedTEs.push_back(SavedVToTEs); 4652 Idx = UsedTEs.size() - 1; 4653 } 4654 UsedValuesEntry.try_emplace(V, Idx); 4655 } 4656 } 4657 4658 unsigned VF = 0; 4659 if (UsedTEs.size() == 1) { 4660 // Try to find the perfect match in another gather node at first. 4661 auto It = find_if(UsedTEs.front(), [TE](const TreeEntry *EntryPtr) { 4662 return EntryPtr->isSame(TE->Scalars); 4663 }); 4664 if (It != UsedTEs.front().end()) { 4665 Entries.push_back(*It); 4666 std::iota(Mask.begin(), Mask.end(), 0); 4667 return TargetTransformInfo::SK_PermuteSingleSrc; 4668 } 4669 // No perfect match, just shuffle, so choose the first tree node. 4670 Entries.push_back(*UsedTEs.front().begin()); 4671 } else { 4672 // Try to find nodes with the same vector factor. 4673 assert(UsedTEs.size() == 2 && "Expected at max 2 permuted entries."); 4674 // FIXME: Shall be replaced by GetVF function once non-power-2 patch is 4675 // landed. 4676 auto &&GetVF = [](const TreeEntry *TE) { 4677 if (!TE->ReuseShuffleIndices.empty()) 4678 return TE->ReuseShuffleIndices.size(); 4679 return TE->Scalars.size(); 4680 }; 4681 DenseMap<int, const TreeEntry *> VFToTE; 4682 for (const TreeEntry *TE : UsedTEs.front()) 4683 VFToTE.try_emplace(GetVF(TE), TE); 4684 for (const TreeEntry *TE : UsedTEs.back()) { 4685 auto It = VFToTE.find(GetVF(TE)); 4686 if (It != VFToTE.end()) { 4687 VF = It->first; 4688 Entries.push_back(It->second); 4689 Entries.push_back(TE); 4690 break; 4691 } 4692 } 4693 // No 2 source vectors with the same vector factor - give up and do regular 4694 // gather. 4695 if (Entries.empty()) 4696 return None; 4697 } 4698 4699 // Build a shuffle mask for better cost estimation and vector emission. 4700 for (int I = 0, E = TE->Scalars.size(); I < E; ++I) { 4701 Value *V = TE->Scalars[I]; 4702 if (isa<UndefValue>(V)) 4703 continue; 4704 unsigned Idx = UsedValuesEntry.lookup(V); 4705 const TreeEntry *VTE = Entries[Idx]; 4706 int FoundLane = VTE->findLaneForValue(V); 4707 Mask[I] = Idx * VF + FoundLane; 4708 // Extra check required by isSingleSourceMaskImpl function (called by 4709 // ShuffleVectorInst::isSingleSourceMask). 4710 if (Mask[I] >= 2 * E) 4711 return None; 4712 } 4713 switch (Entries.size()) { 4714 case 1: 4715 return TargetTransformInfo::SK_PermuteSingleSrc; 4716 case 2: 4717 return TargetTransformInfo::SK_PermuteTwoSrc; 4718 default: 4719 break; 4720 } 4721 return None; 4722 } 4723 4724 InstructionCost 4725 BoUpSLP::getGatherCost(FixedVectorType *Ty, 4726 const DenseSet<unsigned> &ShuffledIndices) const { 4727 unsigned NumElts = Ty->getNumElements(); 4728 APInt DemandedElts = APInt::getNullValue(NumElts); 4729 for (unsigned I = 0; I < NumElts; ++I) 4730 if (!ShuffledIndices.count(I)) 4731 DemandedElts.setBit(I); 4732 InstructionCost Cost = 4733 TTI->getScalarizationOverhead(Ty, DemandedElts, /*Insert*/ true, 4734 /*Extract*/ false); 4735 if (!ShuffledIndices.empty()) 4736 Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, Ty); 4737 return Cost; 4738 } 4739 4740 InstructionCost BoUpSLP::getGatherCost(ArrayRef<Value *> VL) const { 4741 // Find the type of the operands in VL. 4742 Type *ScalarTy = VL[0]->getType(); 4743 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 4744 ScalarTy = SI->getValueOperand()->getType(); 4745 auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); 4746 // Find the cost of inserting/extracting values from the vector. 4747 // Check if the same elements are inserted several times and count them as 4748 // shuffle candidates. 4749 DenseSet<unsigned> ShuffledElements; 4750 DenseSet<Value *> UniqueElements; 4751 // Iterate in reverse order to consider insert elements with the high cost. 4752 for (unsigned I = VL.size(); I > 0; --I) { 4753 unsigned Idx = I - 1; 4754 if (isConstant(VL[Idx])) 4755 continue; 4756 if (!UniqueElements.insert(VL[Idx]).second) 4757 ShuffledElements.insert(Idx); 4758 } 4759 return getGatherCost(VecTy, ShuffledElements); 4760 } 4761 4762 // Perform operand reordering on the instructions in VL and return the reordered 4763 // operands in Left and Right. 4764 void BoUpSLP::reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 4765 SmallVectorImpl<Value *> &Left, 4766 SmallVectorImpl<Value *> &Right, 4767 const DataLayout &DL, 4768 ScalarEvolution &SE, 4769 const BoUpSLP &R) { 4770 if (VL.empty()) 4771 return; 4772 VLOperands Ops(VL, DL, SE, R); 4773 // Reorder the operands in place. 4774 Ops.reorder(); 4775 Left = Ops.getVL(0); 4776 Right = Ops.getVL(1); 4777 } 4778 4779 void BoUpSLP::setInsertPointAfterBundle(const TreeEntry *E) { 4780 // Get the basic block this bundle is in. All instructions in the bundle 4781 // should be in this block. 4782 auto *Front = E->getMainOp(); 4783 auto *BB = Front->getParent(); 4784 assert(llvm::all_of(E->Scalars, [=](Value *V) -> bool { 4785 auto *I = cast<Instruction>(V); 4786 return !E->isOpcodeOrAlt(I) || I->getParent() == BB; 4787 })); 4788 4789 // The last instruction in the bundle in program order. 4790 Instruction *LastInst = nullptr; 4791 4792 // Find the last instruction. The common case should be that BB has been 4793 // scheduled, and the last instruction is VL.back(). So we start with 4794 // VL.back() and iterate over schedule data until we reach the end of the 4795 // bundle. The end of the bundle is marked by null ScheduleData. 4796 if (BlocksSchedules.count(BB)) { 4797 auto *Bundle = 4798 BlocksSchedules[BB]->getScheduleData(E->isOneOf(E->Scalars.back())); 4799 if (Bundle && Bundle->isPartOfBundle()) 4800 for (; Bundle; Bundle = Bundle->NextInBundle) 4801 if (Bundle->OpValue == Bundle->Inst) 4802 LastInst = Bundle->Inst; 4803 } 4804 4805 // LastInst can still be null at this point if there's either not an entry 4806 // for BB in BlocksSchedules or there's no ScheduleData available for 4807 // VL.back(). This can be the case if buildTree_rec aborts for various 4808 // reasons (e.g., the maximum recursion depth is reached, the maximum region 4809 // size is reached, etc.). ScheduleData is initialized in the scheduling 4810 // "dry-run". 4811 // 4812 // If this happens, we can still find the last instruction by brute force. We 4813 // iterate forwards from Front (inclusive) until we either see all 4814 // instructions in the bundle or reach the end of the block. If Front is the 4815 // last instruction in program order, LastInst will be set to Front, and we 4816 // will visit all the remaining instructions in the block. 4817 // 4818 // One of the reasons we exit early from buildTree_rec is to place an upper 4819 // bound on compile-time. Thus, taking an additional compile-time hit here is 4820 // not ideal. However, this should be exceedingly rare since it requires that 4821 // we both exit early from buildTree_rec and that the bundle be out-of-order 4822 // (causing us to iterate all the way to the end of the block). 4823 if (!LastInst) { 4824 SmallPtrSet<Value *, 16> Bundle(E->Scalars.begin(), E->Scalars.end()); 4825 for (auto &I : make_range(BasicBlock::iterator(Front), BB->end())) { 4826 if (Bundle.erase(&I) && E->isOpcodeOrAlt(&I)) 4827 LastInst = &I; 4828 if (Bundle.empty()) 4829 break; 4830 } 4831 } 4832 assert(LastInst && "Failed to find last instruction in bundle"); 4833 4834 // Set the insertion point after the last instruction in the bundle. Set the 4835 // debug location to Front. 4836 Builder.SetInsertPoint(BB, ++LastInst->getIterator()); 4837 Builder.SetCurrentDebugLocation(Front->getDebugLoc()); 4838 } 4839 4840 Value *BoUpSLP::gather(ArrayRef<Value *> VL) { 4841 // List of instructions/lanes from current block and/or the blocks which are 4842 // part of the current loop. These instructions will be inserted at the end to 4843 // make it possible to optimize loops and hoist invariant instructions out of 4844 // the loops body with better chances for success. 4845 SmallVector<std::pair<Value *, unsigned>, 4> PostponedInsts; 4846 SmallSet<int, 4> PostponedIndices; 4847 Loop *L = LI->getLoopFor(Builder.GetInsertBlock()); 4848 auto &&CheckPredecessor = [](BasicBlock *InstBB, BasicBlock *InsertBB) { 4849 SmallPtrSet<BasicBlock *, 4> Visited; 4850 while (InsertBB && InsertBB != InstBB && Visited.insert(InsertBB).second) 4851 InsertBB = InsertBB->getSinglePredecessor(); 4852 return InsertBB && InsertBB == InstBB; 4853 }; 4854 for (int I = 0, E = VL.size(); I < E; ++I) { 4855 if (auto *Inst = dyn_cast<Instruction>(VL[I])) 4856 if ((CheckPredecessor(Inst->getParent(), Builder.GetInsertBlock()) || 4857 getTreeEntry(Inst) || (L && (L->contains(Inst)))) && 4858 PostponedIndices.insert(I).second) 4859 PostponedInsts.emplace_back(Inst, I); 4860 } 4861 4862 auto &&CreateInsertElement = [this](Value *Vec, Value *V, unsigned Pos) { 4863 Vec = Builder.CreateInsertElement(Vec, V, Builder.getInt32(Pos)); 4864 auto *InsElt = dyn_cast<InsertElementInst>(Vec); 4865 if (!InsElt) 4866 return Vec; 4867 GatherSeq.insert(InsElt); 4868 CSEBlocks.insert(InsElt->getParent()); 4869 // Add to our 'need-to-extract' list. 4870 if (TreeEntry *Entry = getTreeEntry(V)) { 4871 // Find which lane we need to extract. 4872 unsigned FoundLane = Entry->findLaneForValue(V); 4873 ExternalUses.emplace_back(V, InsElt, FoundLane); 4874 } 4875 return Vec; 4876 }; 4877 Value *Val0 = 4878 isa<StoreInst>(VL[0]) ? cast<StoreInst>(VL[0])->getValueOperand() : VL[0]; 4879 FixedVectorType *VecTy = FixedVectorType::get(Val0->getType(), VL.size()); 4880 Value *Vec = PoisonValue::get(VecTy); 4881 SmallVector<int> NonConsts; 4882 // Insert constant values at first. 4883 for (int I = 0, E = VL.size(); I < E; ++I) { 4884 if (PostponedIndices.contains(I)) 4885 continue; 4886 if (!isConstant(VL[I])) { 4887 NonConsts.push_back(I); 4888 continue; 4889 } 4890 Vec = CreateInsertElement(Vec, VL[I], I); 4891 } 4892 // Insert non-constant values. 4893 for (int I : NonConsts) 4894 Vec = CreateInsertElement(Vec, VL[I], I); 4895 // Append instructions, which are/may be part of the loop, in the end to make 4896 // it possible to hoist non-loop-based instructions. 4897 for (const std::pair<Value *, unsigned> &Pair : PostponedInsts) 4898 Vec = CreateInsertElement(Vec, Pair.first, Pair.second); 4899 4900 return Vec; 4901 } 4902 4903 namespace { 4904 /// Merges shuffle masks and emits final shuffle instruction, if required. 4905 class ShuffleInstructionBuilder { 4906 IRBuilderBase &Builder; 4907 const unsigned VF = 0; 4908 bool IsFinalized = false; 4909 SmallVector<int, 4> Mask; 4910 4911 public: 4912 ShuffleInstructionBuilder(IRBuilderBase &Builder, unsigned VF) 4913 : Builder(Builder), VF(VF) {} 4914 4915 /// Adds a mask, inverting it before applying. 4916 void addInversedMask(ArrayRef<unsigned> SubMask) { 4917 if (SubMask.empty()) 4918 return; 4919 SmallVector<int, 4> NewMask; 4920 inversePermutation(SubMask, NewMask); 4921 addMask(NewMask); 4922 } 4923 4924 /// Functions adds masks, merging them into single one. 4925 void addMask(ArrayRef<unsigned> SubMask) { 4926 SmallVector<int, 4> NewMask(SubMask.begin(), SubMask.end()); 4927 addMask(NewMask); 4928 } 4929 4930 void addMask(ArrayRef<int> SubMask) { 4931 if (SubMask.empty()) 4932 return; 4933 if (Mask.empty()) { 4934 Mask.append(SubMask.begin(), SubMask.end()); 4935 return; 4936 } 4937 SmallVector<int, 4> NewMask(SubMask.size(), SubMask.size()); 4938 int TermValue = std::min(Mask.size(), SubMask.size()); 4939 for (int I = 0, E = SubMask.size(); I < E; ++I) { 4940 if (SubMask[I] >= TermValue || SubMask[I] == UndefMaskElem || 4941 Mask[SubMask[I]] >= TermValue) { 4942 NewMask[I] = UndefMaskElem; 4943 continue; 4944 } 4945 NewMask[I] = Mask[SubMask[I]]; 4946 } 4947 Mask.swap(NewMask); 4948 } 4949 4950 Value *finalize(Value *V) { 4951 IsFinalized = true; 4952 unsigned ValueVF = cast<FixedVectorType>(V->getType())->getNumElements(); 4953 if (VF == ValueVF && Mask.empty()) 4954 return V; 4955 SmallVector<int, 4> NormalizedMask(VF, UndefMaskElem); 4956 std::iota(NormalizedMask.begin(), NormalizedMask.end(), 0); 4957 addMask(NormalizedMask); 4958 4959 if (VF == ValueVF && ShuffleVectorInst::isIdentityMask(Mask)) 4960 return V; 4961 return Builder.CreateShuffleVector(V, Mask, "shuffle"); 4962 } 4963 4964 ~ShuffleInstructionBuilder() { 4965 assert((IsFinalized || Mask.empty()) && 4966 "Shuffle construction must be finalized."); 4967 } 4968 }; 4969 } // namespace 4970 4971 Value *BoUpSLP::vectorizeTree(ArrayRef<Value *> VL) { 4972 unsigned VF = VL.size(); 4973 InstructionsState S = getSameOpcode(VL); 4974 if (S.getOpcode()) { 4975 if (TreeEntry *E = getTreeEntry(S.OpValue)) 4976 if (E->isSame(VL)) { 4977 Value *V = vectorizeTree(E); 4978 if (VF != cast<FixedVectorType>(V->getType())->getNumElements()) { 4979 if (!E->ReuseShuffleIndices.empty()) { 4980 // Reshuffle to get only unique values. 4981 // If some of the scalars are duplicated in the vectorization tree 4982 // entry, we do not vectorize them but instead generate a mask for 4983 // the reuses. But if there are several users of the same entry, 4984 // they may have different vectorization factors. This is especially 4985 // important for PHI nodes. In this case, we need to adapt the 4986 // resulting instruction for the user vectorization factor and have 4987 // to reshuffle it again to take only unique elements of the vector. 4988 // Without this code the function incorrectly returns reduced vector 4989 // instruction with the same elements, not with the unique ones. 4990 4991 // block: 4992 // %phi = phi <2 x > { .., %entry} {%shuffle, %block} 4993 // %2 = shuffle <2 x > %phi, %poison, <4 x > <0, 0, 1, 1> 4994 // ... (use %2) 4995 // %shuffle = shuffle <2 x> %2, poison, <2 x> {0, 2} 4996 // br %block 4997 SmallVector<int> UniqueIdxs; 4998 SmallSet<int, 4> UsedIdxs; 4999 int Pos = 0; 5000 int Sz = VL.size(); 5001 for (int Idx : E->ReuseShuffleIndices) { 5002 if (Idx != Sz && UsedIdxs.insert(Idx).second) 5003 UniqueIdxs.emplace_back(Pos); 5004 ++Pos; 5005 } 5006 assert(VF >= UsedIdxs.size() && "Expected vectorization factor " 5007 "less than original vector size."); 5008 UniqueIdxs.append(VF - UsedIdxs.size(), UndefMaskElem); 5009 V = Builder.CreateShuffleVector(V, UniqueIdxs, "shrink.shuffle"); 5010 } else { 5011 assert(VF < cast<FixedVectorType>(V->getType())->getNumElements() && 5012 "Expected vectorization factor less " 5013 "than original vector size."); 5014 SmallVector<int> UniformMask(VF, 0); 5015 std::iota(UniformMask.begin(), UniformMask.end(), 0); 5016 V = Builder.CreateShuffleVector(V, UniformMask, "shrink.shuffle"); 5017 } 5018 } 5019 return V; 5020 } 5021 } 5022 5023 // Check that every instruction appears once in this bundle. 5024 SmallVector<int> ReuseShuffleIndicies; 5025 SmallVector<Value *> UniqueValues; 5026 if (VL.size() > 2) { 5027 DenseMap<Value *, unsigned> UniquePositions; 5028 unsigned NumValues = 5029 std::distance(VL.begin(), find_if(reverse(VL), [](Value *V) { 5030 return !isa<UndefValue>(V); 5031 }).base()); 5032 VF = std::max<unsigned>(VF, PowerOf2Ceil(NumValues)); 5033 int UniqueVals = 0; 5034 bool HasUndefs = false; 5035 for (Value *V : VL.drop_back(VL.size() - VF)) { 5036 if (isa<UndefValue>(V)) { 5037 ReuseShuffleIndicies.emplace_back(UndefMaskElem); 5038 HasUndefs = true; 5039 continue; 5040 } 5041 if (isConstant(V)) { 5042 ReuseShuffleIndicies.emplace_back(UniqueValues.size()); 5043 UniqueValues.emplace_back(V); 5044 continue; 5045 } 5046 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 5047 ReuseShuffleIndicies.emplace_back(Res.first->second); 5048 if (Res.second) { 5049 UniqueValues.emplace_back(V); 5050 ++UniqueVals; 5051 } 5052 } 5053 if (HasUndefs && UniqueVals == 1 && UniqueValues.size() == 1) { 5054 // Emit pure splat vector. 5055 // FIXME: why it is not identified as an identity. 5056 unsigned NumUndefs = count(ReuseShuffleIndicies, UndefMaskElem); 5057 if (NumUndefs == ReuseShuffleIndicies.size() - 1) 5058 ReuseShuffleIndicies.append(VF - ReuseShuffleIndicies.size(), 5059 UndefMaskElem); 5060 else 5061 ReuseShuffleIndicies.assign(VF, 0); 5062 } else if (UniqueValues.size() >= VF - 1 || UniqueValues.size() <= 1) { 5063 ReuseShuffleIndicies.clear(); 5064 UniqueValues.clear(); 5065 UniqueValues.append(VL.begin(), std::next(VL.begin(), NumValues)); 5066 } 5067 UniqueValues.append(VF - UniqueValues.size(), 5068 PoisonValue::get(VL[0]->getType())); 5069 VL = UniqueValues; 5070 } 5071 5072 ShuffleInstructionBuilder ShuffleBuilder(Builder, VF); 5073 Value *Vec = gather(VL); 5074 if (!ReuseShuffleIndicies.empty()) { 5075 ShuffleBuilder.addMask(ReuseShuffleIndicies); 5076 Vec = ShuffleBuilder.finalize(Vec); 5077 if (auto *I = dyn_cast<Instruction>(Vec)) { 5078 GatherSeq.insert(I); 5079 CSEBlocks.insert(I->getParent()); 5080 } 5081 } 5082 return Vec; 5083 } 5084 5085 Value *BoUpSLP::vectorizeTree(TreeEntry *E) { 5086 IRBuilder<>::InsertPointGuard Guard(Builder); 5087 5088 if (E->VectorizedValue) { 5089 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *E->Scalars[0] << ".\n"); 5090 return E->VectorizedValue; 5091 } 5092 5093 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 5094 unsigned VF = E->Scalars.size(); 5095 if (NeedToShuffleReuses) 5096 VF = E->ReuseShuffleIndices.size(); 5097 ShuffleInstructionBuilder ShuffleBuilder(Builder, VF); 5098 if (E->State == TreeEntry::NeedToGather) { 5099 setInsertPointAfterBundle(E); 5100 Value *Vec; 5101 SmallVector<int> Mask; 5102 SmallVector<const TreeEntry *> Entries; 5103 Optional<TargetTransformInfo::ShuffleKind> Shuffle = 5104 isGatherShuffledEntry(E, Mask, Entries); 5105 if (Shuffle.hasValue()) { 5106 assert((Entries.size() == 1 || Entries.size() == 2) && 5107 "Expected shuffle of 1 or 2 entries."); 5108 Vec = Builder.CreateShuffleVector(Entries.front()->VectorizedValue, 5109 Entries.back()->VectorizedValue, Mask); 5110 } else { 5111 Vec = gather(E->Scalars); 5112 } 5113 if (NeedToShuffleReuses) { 5114 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5115 Vec = ShuffleBuilder.finalize(Vec); 5116 if (auto *I = dyn_cast<Instruction>(Vec)) { 5117 GatherSeq.insert(I); 5118 CSEBlocks.insert(I->getParent()); 5119 } 5120 } 5121 E->VectorizedValue = Vec; 5122 return Vec; 5123 } 5124 5125 assert((E->State == TreeEntry::Vectorize || 5126 E->State == TreeEntry::ScatterVectorize) && 5127 "Unhandled state"); 5128 unsigned ShuffleOrOp = 5129 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 5130 Instruction *VL0 = E->getMainOp(); 5131 Type *ScalarTy = VL0->getType(); 5132 if (auto *Store = dyn_cast<StoreInst>(VL0)) 5133 ScalarTy = Store->getValueOperand()->getType(); 5134 else if (auto *IE = dyn_cast<InsertElementInst>(VL0)) 5135 ScalarTy = IE->getOperand(1)->getType(); 5136 auto *VecTy = FixedVectorType::get(ScalarTy, E->Scalars.size()); 5137 switch (ShuffleOrOp) { 5138 case Instruction::PHI: { 5139 auto *PH = cast<PHINode>(VL0); 5140 Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI()); 5141 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 5142 PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues()); 5143 Value *V = NewPhi; 5144 if (NeedToShuffleReuses) 5145 V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle"); 5146 5147 E->VectorizedValue = V; 5148 5149 // PHINodes may have multiple entries from the same block. We want to 5150 // visit every block once. 5151 SmallPtrSet<BasicBlock*, 4> VisitedBBs; 5152 5153 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 5154 ValueList Operands; 5155 BasicBlock *IBB = PH->getIncomingBlock(i); 5156 5157 if (!VisitedBBs.insert(IBB).second) { 5158 NewPhi->addIncoming(NewPhi->getIncomingValueForBlock(IBB), IBB); 5159 continue; 5160 } 5161 5162 Builder.SetInsertPoint(IBB->getTerminator()); 5163 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 5164 Value *Vec = vectorizeTree(E->getOperand(i)); 5165 NewPhi->addIncoming(Vec, IBB); 5166 } 5167 5168 assert(NewPhi->getNumIncomingValues() == PH->getNumIncomingValues() && 5169 "Invalid number of incoming values"); 5170 return V; 5171 } 5172 5173 case Instruction::ExtractElement: { 5174 Value *V = E->getSingleOperand(0); 5175 Builder.SetInsertPoint(VL0); 5176 ShuffleBuilder.addInversedMask(E->ReorderIndices); 5177 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5178 V = ShuffleBuilder.finalize(V); 5179 E->VectorizedValue = V; 5180 return V; 5181 } 5182 case Instruction::ExtractValue: { 5183 auto *LI = cast<LoadInst>(E->getSingleOperand(0)); 5184 Builder.SetInsertPoint(LI); 5185 auto *PtrTy = PointerType::get(VecTy, LI->getPointerAddressSpace()); 5186 Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy); 5187 LoadInst *V = Builder.CreateAlignedLoad(VecTy, Ptr, LI->getAlign()); 5188 Value *NewV = propagateMetadata(V, E->Scalars); 5189 ShuffleBuilder.addInversedMask(E->ReorderIndices); 5190 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5191 NewV = ShuffleBuilder.finalize(NewV); 5192 E->VectorizedValue = NewV; 5193 return NewV; 5194 } 5195 case Instruction::InsertElement: { 5196 Builder.SetInsertPoint(VL0); 5197 Value *V = vectorizeTree(E->getOperand(1)); 5198 5199 const unsigned NumElts = 5200 cast<FixedVectorType>(VL0->getType())->getNumElements(); 5201 const unsigned NumScalars = E->Scalars.size(); 5202 5203 // Create InsertVector shuffle if necessary 5204 Instruction *FirstInsert = nullptr; 5205 bool IsIdentity = true; 5206 unsigned Offset = UINT_MAX; 5207 for (unsigned I = 0; I < NumScalars; ++I) { 5208 Value *Scalar = E->Scalars[I]; 5209 if (!FirstInsert && 5210 !is_contained(E->Scalars, cast<Instruction>(Scalar)->getOperand(0))) 5211 FirstInsert = cast<Instruction>(Scalar); 5212 Optional<int> InsertIdx = getInsertIndex(Scalar, 0); 5213 if (!InsertIdx || *InsertIdx == UndefMaskElem) 5214 continue; 5215 unsigned Idx = *InsertIdx; 5216 if (Idx < Offset) { 5217 Offset = Idx; 5218 IsIdentity &= I == 0; 5219 } else { 5220 assert(Idx >= Offset && "Failed to find vector index offset"); 5221 IsIdentity &= Idx - Offset == I; 5222 } 5223 } 5224 assert(Offset < NumElts && "Failed to find vector index offset"); 5225 5226 // Create shuffle to resize vector 5227 SmallVector<int> Mask(NumElts, UndefMaskElem); 5228 if (!IsIdentity) { 5229 for (unsigned I = 0; I < NumScalars; ++I) { 5230 Value *Scalar = E->Scalars[I]; 5231 Optional<int> InsertIdx = getInsertIndex(Scalar, 0); 5232 if (!InsertIdx || *InsertIdx == UndefMaskElem) 5233 continue; 5234 Mask[*InsertIdx - Offset] = I; 5235 } 5236 } else { 5237 std::iota(Mask.begin(), std::next(Mask.begin(), NumScalars), 0); 5238 } 5239 if (!IsIdentity || NumElts != NumScalars) 5240 V = Builder.CreateShuffleVector(V, Mask); 5241 5242 if (NumElts != NumScalars) { 5243 SmallVector<int> InsertMask(NumElts); 5244 std::iota(InsertMask.begin(), InsertMask.end(), 0); 5245 for (unsigned I = 0; I < NumElts; I++) { 5246 if (Mask[I] != UndefMaskElem) 5247 InsertMask[Offset + I] = NumElts + I; 5248 } 5249 5250 V = Builder.CreateShuffleVector( 5251 FirstInsert->getOperand(0), V, InsertMask, 5252 cast<Instruction>(E->Scalars.back())->getName()); 5253 } 5254 5255 ++NumVectorInstructions; 5256 E->VectorizedValue = V; 5257 return V; 5258 } 5259 case Instruction::ZExt: 5260 case Instruction::SExt: 5261 case Instruction::FPToUI: 5262 case Instruction::FPToSI: 5263 case Instruction::FPExt: 5264 case Instruction::PtrToInt: 5265 case Instruction::IntToPtr: 5266 case Instruction::SIToFP: 5267 case Instruction::UIToFP: 5268 case Instruction::Trunc: 5269 case Instruction::FPTrunc: 5270 case Instruction::BitCast: { 5271 setInsertPointAfterBundle(E); 5272 5273 Value *InVec = vectorizeTree(E->getOperand(0)); 5274 5275 if (E->VectorizedValue) { 5276 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5277 return E->VectorizedValue; 5278 } 5279 5280 auto *CI = cast<CastInst>(VL0); 5281 Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy); 5282 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5283 V = ShuffleBuilder.finalize(V); 5284 5285 E->VectorizedValue = V; 5286 ++NumVectorInstructions; 5287 return V; 5288 } 5289 case Instruction::FCmp: 5290 case Instruction::ICmp: { 5291 setInsertPointAfterBundle(E); 5292 5293 Value *L = vectorizeTree(E->getOperand(0)); 5294 Value *R = vectorizeTree(E->getOperand(1)); 5295 5296 if (E->VectorizedValue) { 5297 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5298 return E->VectorizedValue; 5299 } 5300 5301 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 5302 Value *V = Builder.CreateCmp(P0, L, R); 5303 propagateIRFlags(V, E->Scalars, VL0); 5304 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5305 V = ShuffleBuilder.finalize(V); 5306 5307 E->VectorizedValue = V; 5308 ++NumVectorInstructions; 5309 return V; 5310 } 5311 case Instruction::Select: { 5312 setInsertPointAfterBundle(E); 5313 5314 Value *Cond = vectorizeTree(E->getOperand(0)); 5315 Value *True = vectorizeTree(E->getOperand(1)); 5316 Value *False = vectorizeTree(E->getOperand(2)); 5317 5318 if (E->VectorizedValue) { 5319 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5320 return E->VectorizedValue; 5321 } 5322 5323 Value *V = Builder.CreateSelect(Cond, True, False); 5324 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5325 V = ShuffleBuilder.finalize(V); 5326 5327 E->VectorizedValue = V; 5328 ++NumVectorInstructions; 5329 return V; 5330 } 5331 case Instruction::FNeg: { 5332 setInsertPointAfterBundle(E); 5333 5334 Value *Op = vectorizeTree(E->getOperand(0)); 5335 5336 if (E->VectorizedValue) { 5337 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5338 return E->VectorizedValue; 5339 } 5340 5341 Value *V = Builder.CreateUnOp( 5342 static_cast<Instruction::UnaryOps>(E->getOpcode()), Op); 5343 propagateIRFlags(V, E->Scalars, VL0); 5344 if (auto *I = dyn_cast<Instruction>(V)) 5345 V = propagateMetadata(I, E->Scalars); 5346 5347 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5348 V = ShuffleBuilder.finalize(V); 5349 5350 E->VectorizedValue = V; 5351 ++NumVectorInstructions; 5352 5353 return V; 5354 } 5355 case Instruction::Add: 5356 case Instruction::FAdd: 5357 case Instruction::Sub: 5358 case Instruction::FSub: 5359 case Instruction::Mul: 5360 case Instruction::FMul: 5361 case Instruction::UDiv: 5362 case Instruction::SDiv: 5363 case Instruction::FDiv: 5364 case Instruction::URem: 5365 case Instruction::SRem: 5366 case Instruction::FRem: 5367 case Instruction::Shl: 5368 case Instruction::LShr: 5369 case Instruction::AShr: 5370 case Instruction::And: 5371 case Instruction::Or: 5372 case Instruction::Xor: { 5373 setInsertPointAfterBundle(E); 5374 5375 Value *LHS = vectorizeTree(E->getOperand(0)); 5376 Value *RHS = vectorizeTree(E->getOperand(1)); 5377 5378 if (E->VectorizedValue) { 5379 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5380 return E->VectorizedValue; 5381 } 5382 5383 Value *V = Builder.CreateBinOp( 5384 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, 5385 RHS); 5386 propagateIRFlags(V, E->Scalars, VL0); 5387 if (auto *I = dyn_cast<Instruction>(V)) 5388 V = propagateMetadata(I, E->Scalars); 5389 5390 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5391 V = ShuffleBuilder.finalize(V); 5392 5393 E->VectorizedValue = V; 5394 ++NumVectorInstructions; 5395 5396 return V; 5397 } 5398 case Instruction::Load: { 5399 // Loads are inserted at the head of the tree because we don't want to 5400 // sink them all the way down past store instructions. 5401 bool IsReorder = E->updateStateIfReorder(); 5402 if (IsReorder) 5403 VL0 = E->getMainOp(); 5404 setInsertPointAfterBundle(E); 5405 5406 LoadInst *LI = cast<LoadInst>(VL0); 5407 Instruction *NewLI; 5408 unsigned AS = LI->getPointerAddressSpace(); 5409 Value *PO = LI->getPointerOperand(); 5410 if (E->State == TreeEntry::Vectorize) { 5411 5412 Value *VecPtr = Builder.CreateBitCast(PO, VecTy->getPointerTo(AS)); 5413 5414 // The pointer operand uses an in-tree scalar so we add the new BitCast 5415 // to ExternalUses list to make sure that an extract will be generated 5416 // in the future. 5417 if (getTreeEntry(PO)) 5418 ExternalUses.emplace_back(PO, cast<User>(VecPtr), 0); 5419 5420 NewLI = Builder.CreateAlignedLoad(VecTy, VecPtr, LI->getAlign()); 5421 } else { 5422 assert(E->State == TreeEntry::ScatterVectorize && "Unhandled state"); 5423 Value *VecPtr = vectorizeTree(E->getOperand(0)); 5424 // Use the minimum alignment of the gathered loads. 5425 Align CommonAlignment = LI->getAlign(); 5426 for (Value *V : E->Scalars) 5427 CommonAlignment = 5428 commonAlignment(CommonAlignment, cast<LoadInst>(V)->getAlign()); 5429 NewLI = Builder.CreateMaskedGather(VecTy, VecPtr, CommonAlignment); 5430 } 5431 Value *V = propagateMetadata(NewLI, E->Scalars); 5432 5433 ShuffleBuilder.addInversedMask(E->ReorderIndices); 5434 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5435 V = ShuffleBuilder.finalize(V); 5436 E->VectorizedValue = V; 5437 ++NumVectorInstructions; 5438 return V; 5439 } 5440 case Instruction::Store: { 5441 bool IsReorder = !E->ReorderIndices.empty(); 5442 auto *SI = cast<StoreInst>( 5443 IsReorder ? E->Scalars[E->ReorderIndices.front()] : VL0); 5444 unsigned AS = SI->getPointerAddressSpace(); 5445 5446 setInsertPointAfterBundle(E); 5447 5448 Value *VecValue = vectorizeTree(E->getOperand(0)); 5449 ShuffleBuilder.addMask(E->ReorderIndices); 5450 VecValue = ShuffleBuilder.finalize(VecValue); 5451 5452 Value *ScalarPtr = SI->getPointerOperand(); 5453 Value *VecPtr = Builder.CreateBitCast( 5454 ScalarPtr, VecValue->getType()->getPointerTo(AS)); 5455 StoreInst *ST = Builder.CreateAlignedStore(VecValue, VecPtr, 5456 SI->getAlign()); 5457 5458 // The pointer operand uses an in-tree scalar, so add the new BitCast to 5459 // ExternalUses to make sure that an extract will be generated in the 5460 // future. 5461 if (getTreeEntry(ScalarPtr)) 5462 ExternalUses.push_back(ExternalUser(ScalarPtr, cast<User>(VecPtr), 0)); 5463 5464 Value *V = propagateMetadata(ST, E->Scalars); 5465 5466 E->VectorizedValue = V; 5467 ++NumVectorInstructions; 5468 return V; 5469 } 5470 case Instruction::GetElementPtr: { 5471 setInsertPointAfterBundle(E); 5472 5473 Value *Op0 = vectorizeTree(E->getOperand(0)); 5474 5475 std::vector<Value *> OpVecs; 5476 for (int j = 1, e = cast<GetElementPtrInst>(VL0)->getNumOperands(); j < e; 5477 ++j) { 5478 ValueList &VL = E->getOperand(j); 5479 // Need to cast all elements to the same type before vectorization to 5480 // avoid crash. 5481 Type *VL0Ty = VL0->getOperand(j)->getType(); 5482 Type *Ty = llvm::all_of( 5483 VL, [VL0Ty](Value *V) { return VL0Ty == V->getType(); }) 5484 ? VL0Ty 5485 : DL->getIndexType(cast<GetElementPtrInst>(VL0) 5486 ->getPointerOperandType() 5487 ->getScalarType()); 5488 for (Value *&V : VL) { 5489 auto *CI = cast<ConstantInt>(V); 5490 V = ConstantExpr::getIntegerCast(CI, Ty, 5491 CI->getValue().isSignBitSet()); 5492 } 5493 Value *OpVec = vectorizeTree(VL); 5494 OpVecs.push_back(OpVec); 5495 } 5496 5497 Value *V = Builder.CreateGEP( 5498 cast<GetElementPtrInst>(VL0)->getSourceElementType(), Op0, OpVecs); 5499 if (Instruction *I = dyn_cast<Instruction>(V)) 5500 V = propagateMetadata(I, E->Scalars); 5501 5502 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5503 V = ShuffleBuilder.finalize(V); 5504 5505 E->VectorizedValue = V; 5506 ++NumVectorInstructions; 5507 5508 return V; 5509 } 5510 case Instruction::Call: { 5511 CallInst *CI = cast<CallInst>(VL0); 5512 setInsertPointAfterBundle(E); 5513 5514 Intrinsic::ID IID = Intrinsic::not_intrinsic; 5515 if (Function *FI = CI->getCalledFunction()) 5516 IID = FI->getIntrinsicID(); 5517 5518 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 5519 5520 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 5521 bool UseIntrinsic = ID != Intrinsic::not_intrinsic && 5522 VecCallCosts.first <= VecCallCosts.second; 5523 5524 Value *ScalarArg = nullptr; 5525 std::vector<Value *> OpVecs; 5526 SmallVector<Type *, 2> TysForDecl = 5527 {FixedVectorType::get(CI->getType(), E->Scalars.size())}; 5528 for (int j = 0, e = CI->getNumArgOperands(); j < e; ++j) { 5529 ValueList OpVL; 5530 // Some intrinsics have scalar arguments. This argument should not be 5531 // vectorized. 5532 if (UseIntrinsic && hasVectorInstrinsicScalarOpd(IID, j)) { 5533 CallInst *CEI = cast<CallInst>(VL0); 5534 ScalarArg = CEI->getArgOperand(j); 5535 OpVecs.push_back(CEI->getArgOperand(j)); 5536 if (hasVectorInstrinsicOverloadedScalarOpd(IID, j)) 5537 TysForDecl.push_back(ScalarArg->getType()); 5538 continue; 5539 } 5540 5541 Value *OpVec = vectorizeTree(E->getOperand(j)); 5542 LLVM_DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n"); 5543 OpVecs.push_back(OpVec); 5544 } 5545 5546 Function *CF; 5547 if (!UseIntrinsic) { 5548 VFShape Shape = 5549 VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>( 5550 VecTy->getNumElements())), 5551 false /*HasGlobalPred*/); 5552 CF = VFDatabase(*CI).getVectorizedFunction(Shape); 5553 } else { 5554 CF = Intrinsic::getDeclaration(F->getParent(), ID, TysForDecl); 5555 } 5556 5557 SmallVector<OperandBundleDef, 1> OpBundles; 5558 CI->getOperandBundlesAsDefs(OpBundles); 5559 Value *V = Builder.CreateCall(CF, OpVecs, OpBundles); 5560 5561 // The scalar argument uses an in-tree scalar so we add the new vectorized 5562 // call to ExternalUses list to make sure that an extract will be 5563 // generated in the future. 5564 if (ScalarArg && getTreeEntry(ScalarArg)) 5565 ExternalUses.push_back(ExternalUser(ScalarArg, cast<User>(V), 0)); 5566 5567 propagateIRFlags(V, E->Scalars, VL0); 5568 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5569 V = ShuffleBuilder.finalize(V); 5570 5571 E->VectorizedValue = V; 5572 ++NumVectorInstructions; 5573 return V; 5574 } 5575 case Instruction::ShuffleVector: { 5576 assert(E->isAltShuffle() && 5577 ((Instruction::isBinaryOp(E->getOpcode()) && 5578 Instruction::isBinaryOp(E->getAltOpcode())) || 5579 (Instruction::isCast(E->getOpcode()) && 5580 Instruction::isCast(E->getAltOpcode()))) && 5581 "Invalid Shuffle Vector Operand"); 5582 5583 Value *LHS = nullptr, *RHS = nullptr; 5584 if (Instruction::isBinaryOp(E->getOpcode())) { 5585 setInsertPointAfterBundle(E); 5586 LHS = vectorizeTree(E->getOperand(0)); 5587 RHS = vectorizeTree(E->getOperand(1)); 5588 } else { 5589 setInsertPointAfterBundle(E); 5590 LHS = vectorizeTree(E->getOperand(0)); 5591 } 5592 5593 if (E->VectorizedValue) { 5594 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5595 return E->VectorizedValue; 5596 } 5597 5598 Value *V0, *V1; 5599 if (Instruction::isBinaryOp(E->getOpcode())) { 5600 V0 = Builder.CreateBinOp( 5601 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, RHS); 5602 V1 = Builder.CreateBinOp( 5603 static_cast<Instruction::BinaryOps>(E->getAltOpcode()), LHS, RHS); 5604 } else { 5605 V0 = Builder.CreateCast( 5606 static_cast<Instruction::CastOps>(E->getOpcode()), LHS, VecTy); 5607 V1 = Builder.CreateCast( 5608 static_cast<Instruction::CastOps>(E->getAltOpcode()), LHS, VecTy); 5609 } 5610 5611 // Create shuffle to take alternate operations from the vector. 5612 // Also, gather up main and alt scalar ops to propagate IR flags to 5613 // each vector operation. 5614 ValueList OpScalars, AltScalars; 5615 unsigned e = E->Scalars.size(); 5616 SmallVector<int, 8> Mask(e); 5617 for (unsigned i = 0; i < e; ++i) { 5618 auto *OpInst = cast<Instruction>(E->Scalars[i]); 5619 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 5620 if (OpInst->getOpcode() == E->getAltOpcode()) { 5621 Mask[i] = e + i; 5622 AltScalars.push_back(E->Scalars[i]); 5623 } else { 5624 Mask[i] = i; 5625 OpScalars.push_back(E->Scalars[i]); 5626 } 5627 } 5628 5629 propagateIRFlags(V0, OpScalars); 5630 propagateIRFlags(V1, AltScalars); 5631 5632 Value *V = Builder.CreateShuffleVector(V0, V1, Mask); 5633 if (Instruction *I = dyn_cast<Instruction>(V)) 5634 V = propagateMetadata(I, E->Scalars); 5635 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5636 V = ShuffleBuilder.finalize(V); 5637 5638 E->VectorizedValue = V; 5639 ++NumVectorInstructions; 5640 5641 return V; 5642 } 5643 default: 5644 llvm_unreachable("unknown inst"); 5645 } 5646 return nullptr; 5647 } 5648 5649 Value *BoUpSLP::vectorizeTree() { 5650 ExtraValueToDebugLocsMap ExternallyUsedValues; 5651 return vectorizeTree(ExternallyUsedValues); 5652 } 5653 5654 Value * 5655 BoUpSLP::vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues) { 5656 // All blocks must be scheduled before any instructions are inserted. 5657 for (auto &BSIter : BlocksSchedules) { 5658 scheduleBlock(BSIter.second.get()); 5659 } 5660 5661 Builder.SetInsertPoint(&F->getEntryBlock().front()); 5662 auto *VectorRoot = vectorizeTree(VectorizableTree[0].get()); 5663 5664 // If the vectorized tree can be rewritten in a smaller type, we truncate the 5665 // vectorized root. InstCombine will then rewrite the entire expression. We 5666 // sign extend the extracted values below. 5667 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 5668 if (MinBWs.count(ScalarRoot)) { 5669 if (auto *I = dyn_cast<Instruction>(VectorRoot)) { 5670 // If current instr is a phi and not the last phi, insert it after the 5671 // last phi node. 5672 if (isa<PHINode>(I)) 5673 Builder.SetInsertPoint(&*I->getParent()->getFirstInsertionPt()); 5674 else 5675 Builder.SetInsertPoint(&*++BasicBlock::iterator(I)); 5676 } 5677 auto BundleWidth = VectorizableTree[0]->Scalars.size(); 5678 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 5679 auto *VecTy = FixedVectorType::get(MinTy, BundleWidth); 5680 auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy); 5681 VectorizableTree[0]->VectorizedValue = Trunc; 5682 } 5683 5684 LLVM_DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size() 5685 << " values .\n"); 5686 5687 // Extract all of the elements with the external uses. 5688 for (const auto &ExternalUse : ExternalUses) { 5689 Value *Scalar = ExternalUse.Scalar; 5690 llvm::User *User = ExternalUse.User; 5691 5692 // Skip users that we already RAUW. This happens when one instruction 5693 // has multiple uses of the same value. 5694 if (User && !is_contained(Scalar->users(), User)) 5695 continue; 5696 TreeEntry *E = getTreeEntry(Scalar); 5697 assert(E && "Invalid scalar"); 5698 assert(E->State != TreeEntry::NeedToGather && 5699 "Extracting from a gather list"); 5700 5701 Value *Vec = E->VectorizedValue; 5702 assert(Vec && "Can't find vectorizable value"); 5703 5704 Value *Lane = Builder.getInt32(ExternalUse.Lane); 5705 auto ExtractAndExtendIfNeeded = [&](Value *Vec) { 5706 if (Scalar->getType() != Vec->getType()) { 5707 Value *Ex; 5708 // "Reuse" the existing extract to improve final codegen. 5709 if (auto *ES = dyn_cast<ExtractElementInst>(Scalar)) { 5710 Ex = Builder.CreateExtractElement(ES->getOperand(0), 5711 ES->getOperand(1)); 5712 } else { 5713 Ex = Builder.CreateExtractElement(Vec, Lane); 5714 } 5715 // If necessary, sign-extend or zero-extend ScalarRoot 5716 // to the larger type. 5717 if (!MinBWs.count(ScalarRoot)) 5718 return Ex; 5719 if (MinBWs[ScalarRoot].second) 5720 return Builder.CreateSExt(Ex, Scalar->getType()); 5721 return Builder.CreateZExt(Ex, Scalar->getType()); 5722 } 5723 assert(isa<FixedVectorType>(Scalar->getType()) && 5724 isa<InsertElementInst>(Scalar) && 5725 "In-tree scalar of vector type is not insertelement?"); 5726 return Vec; 5727 }; 5728 // If User == nullptr, the Scalar is used as extra arg. Generate 5729 // ExtractElement instruction and update the record for this scalar in 5730 // ExternallyUsedValues. 5731 if (!User) { 5732 assert(ExternallyUsedValues.count(Scalar) && 5733 "Scalar with nullptr as an external user must be registered in " 5734 "ExternallyUsedValues map"); 5735 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 5736 Builder.SetInsertPoint(VecI->getParent(), 5737 std::next(VecI->getIterator())); 5738 } else { 5739 Builder.SetInsertPoint(&F->getEntryBlock().front()); 5740 } 5741 Value *NewInst = ExtractAndExtendIfNeeded(Vec); 5742 CSEBlocks.insert(cast<Instruction>(Scalar)->getParent()); 5743 auto &NewInstLocs = ExternallyUsedValues[NewInst]; 5744 auto It = ExternallyUsedValues.find(Scalar); 5745 assert(It != ExternallyUsedValues.end() && 5746 "Externally used scalar is not found in ExternallyUsedValues"); 5747 NewInstLocs.append(It->second); 5748 ExternallyUsedValues.erase(Scalar); 5749 // Required to update internally referenced instructions. 5750 Scalar->replaceAllUsesWith(NewInst); 5751 continue; 5752 } 5753 5754 // Generate extracts for out-of-tree users. 5755 // Find the insertion point for the extractelement lane. 5756 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 5757 if (PHINode *PH = dyn_cast<PHINode>(User)) { 5758 for (int i = 0, e = PH->getNumIncomingValues(); i != e; ++i) { 5759 if (PH->getIncomingValue(i) == Scalar) { 5760 Instruction *IncomingTerminator = 5761 PH->getIncomingBlock(i)->getTerminator(); 5762 if (isa<CatchSwitchInst>(IncomingTerminator)) { 5763 Builder.SetInsertPoint(VecI->getParent(), 5764 std::next(VecI->getIterator())); 5765 } else { 5766 Builder.SetInsertPoint(PH->getIncomingBlock(i)->getTerminator()); 5767 } 5768 Value *NewInst = ExtractAndExtendIfNeeded(Vec); 5769 CSEBlocks.insert(PH->getIncomingBlock(i)); 5770 PH->setOperand(i, NewInst); 5771 } 5772 } 5773 } else { 5774 Builder.SetInsertPoint(cast<Instruction>(User)); 5775 Value *NewInst = ExtractAndExtendIfNeeded(Vec); 5776 CSEBlocks.insert(cast<Instruction>(User)->getParent()); 5777 User->replaceUsesOfWith(Scalar, NewInst); 5778 } 5779 } else { 5780 Builder.SetInsertPoint(&F->getEntryBlock().front()); 5781 Value *NewInst = ExtractAndExtendIfNeeded(Vec); 5782 CSEBlocks.insert(&F->getEntryBlock()); 5783 User->replaceUsesOfWith(Scalar, NewInst); 5784 } 5785 5786 LLVM_DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n"); 5787 } 5788 5789 // For each vectorized value: 5790 for (auto &TEPtr : VectorizableTree) { 5791 TreeEntry *Entry = TEPtr.get(); 5792 5793 // No need to handle users of gathered values. 5794 if (Entry->State == TreeEntry::NeedToGather) 5795 continue; 5796 5797 assert(Entry->VectorizedValue && "Can't find vectorizable value"); 5798 5799 // For each lane: 5800 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 5801 Value *Scalar = Entry->Scalars[Lane]; 5802 5803 #ifndef NDEBUG 5804 Type *Ty = Scalar->getType(); 5805 if (!Ty->isVoidTy()) { 5806 for (User *U : Scalar->users()) { 5807 LLVM_DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n"); 5808 5809 // It is legal to delete users in the ignorelist. 5810 assert((getTreeEntry(U) || is_contained(UserIgnoreList, U)) && 5811 "Deleting out-of-tree value"); 5812 } 5813 } 5814 #endif 5815 LLVM_DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n"); 5816 eraseInstruction(cast<Instruction>(Scalar)); 5817 } 5818 } 5819 5820 Builder.ClearInsertionPoint(); 5821 InstrElementSize.clear(); 5822 5823 return VectorizableTree[0]->VectorizedValue; 5824 } 5825 5826 void BoUpSLP::optimizeGatherSequence() { 5827 LLVM_DEBUG(dbgs() << "SLP: Optimizing " << GatherSeq.size() 5828 << " gather sequences instructions.\n"); 5829 // LICM InsertElementInst sequences. 5830 for (Instruction *I : GatherSeq) { 5831 if (isDeleted(I)) 5832 continue; 5833 5834 // Check if this block is inside a loop. 5835 Loop *L = LI->getLoopFor(I->getParent()); 5836 if (!L) 5837 continue; 5838 5839 // Check if it has a preheader. 5840 BasicBlock *PreHeader = L->getLoopPreheader(); 5841 if (!PreHeader) 5842 continue; 5843 5844 // If the vector or the element that we insert into it are 5845 // instructions that are defined in this basic block then we can't 5846 // hoist this instruction. 5847 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 5848 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 5849 if (Op0 && L->contains(Op0)) 5850 continue; 5851 if (Op1 && L->contains(Op1)) 5852 continue; 5853 5854 // We can hoist this instruction. Move it to the pre-header. 5855 I->moveBefore(PreHeader->getTerminator()); 5856 } 5857 5858 // Make a list of all reachable blocks in our CSE queue. 5859 SmallVector<const DomTreeNode *, 8> CSEWorkList; 5860 CSEWorkList.reserve(CSEBlocks.size()); 5861 for (BasicBlock *BB : CSEBlocks) 5862 if (DomTreeNode *N = DT->getNode(BB)) { 5863 assert(DT->isReachableFromEntry(N)); 5864 CSEWorkList.push_back(N); 5865 } 5866 5867 // Sort blocks by domination. This ensures we visit a block after all blocks 5868 // dominating it are visited. 5869 llvm::sort(CSEWorkList, [](const DomTreeNode *A, const DomTreeNode *B) { 5870 assert((A == B) == (A->getDFSNumIn() == B->getDFSNumIn()) && 5871 "Different nodes should have different DFS numbers"); 5872 return A->getDFSNumIn() < B->getDFSNumIn(); 5873 }); 5874 5875 // Perform O(N^2) search over the gather sequences and merge identical 5876 // instructions. TODO: We can further optimize this scan if we split the 5877 // instructions into different buckets based on the insert lane. 5878 SmallVector<Instruction *, 16> Visited; 5879 for (auto I = CSEWorkList.begin(), E = CSEWorkList.end(); I != E; ++I) { 5880 assert(*I && 5881 (I == CSEWorkList.begin() || !DT->dominates(*I, *std::prev(I))) && 5882 "Worklist not sorted properly!"); 5883 BasicBlock *BB = (*I)->getBlock(); 5884 // For all instructions in blocks containing gather sequences: 5885 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e;) { 5886 Instruction *In = &*it++; 5887 if (isDeleted(In)) 5888 continue; 5889 if (!isa<InsertElementInst>(In) && !isa<ExtractElementInst>(In)) 5890 continue; 5891 5892 // Check if we can replace this instruction with any of the 5893 // visited instructions. 5894 for (Instruction *v : Visited) { 5895 if (In->isIdenticalTo(v) && 5896 DT->dominates(v->getParent(), In->getParent())) { 5897 In->replaceAllUsesWith(v); 5898 eraseInstruction(In); 5899 In = nullptr; 5900 break; 5901 } 5902 } 5903 if (In) { 5904 assert(!is_contained(Visited, In)); 5905 Visited.push_back(In); 5906 } 5907 } 5908 } 5909 CSEBlocks.clear(); 5910 GatherSeq.clear(); 5911 } 5912 5913 // Groups the instructions to a bundle (which is then a single scheduling entity) 5914 // and schedules instructions until the bundle gets ready. 5915 Optional<BoUpSLP::ScheduleData *> 5916 BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 5917 const InstructionsState &S) { 5918 if (isa<PHINode>(S.OpValue) || isa<InsertElementInst>(S.OpValue)) 5919 return nullptr; 5920 5921 // Initialize the instruction bundle. 5922 Instruction *OldScheduleEnd = ScheduleEnd; 5923 ScheduleData *PrevInBundle = nullptr; 5924 ScheduleData *Bundle = nullptr; 5925 bool ReSchedule = false; 5926 LLVM_DEBUG(dbgs() << "SLP: bundle: " << *S.OpValue << "\n"); 5927 5928 auto &&TryScheduleBundle = [this, OldScheduleEnd, SLP](bool ReSchedule, 5929 ScheduleData *Bundle) { 5930 // The scheduling region got new instructions at the lower end (or it is a 5931 // new region for the first bundle). This makes it necessary to 5932 // recalculate all dependencies. 5933 // It is seldom that this needs to be done a second time after adding the 5934 // initial bundle to the region. 5935 if (ScheduleEnd != OldScheduleEnd) { 5936 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) 5937 doForAllOpcodes(I, [](ScheduleData *SD) { SD->clearDependencies(); }); 5938 ReSchedule = true; 5939 } 5940 if (ReSchedule) { 5941 resetSchedule(); 5942 initialFillReadyList(ReadyInsts); 5943 } 5944 if (Bundle) { 5945 LLVM_DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle 5946 << " in block " << BB->getName() << "\n"); 5947 calculateDependencies(Bundle, /*InsertInReadyList=*/true, SLP); 5948 } 5949 5950 // Now try to schedule the new bundle or (if no bundle) just calculate 5951 // dependencies. As soon as the bundle is "ready" it means that there are no 5952 // cyclic dependencies and we can schedule it. Note that's important that we 5953 // don't "schedule" the bundle yet (see cancelScheduling). 5954 while (((!Bundle && ReSchedule) || (Bundle && !Bundle->isReady())) && 5955 !ReadyInsts.empty()) { 5956 ScheduleData *Picked = ReadyInsts.pop_back_val(); 5957 if (Picked->isSchedulingEntity() && Picked->isReady()) 5958 schedule(Picked, ReadyInsts); 5959 } 5960 }; 5961 5962 // Make sure that the scheduling region contains all 5963 // instructions of the bundle. 5964 for (Value *V : VL) { 5965 if (!extendSchedulingRegion(V, S)) { 5966 // If the scheduling region got new instructions at the lower end (or it 5967 // is a new region for the first bundle). This makes it necessary to 5968 // recalculate all dependencies. 5969 // Otherwise the compiler may crash trying to incorrectly calculate 5970 // dependencies and emit instruction in the wrong order at the actual 5971 // scheduling. 5972 TryScheduleBundle(/*ReSchedule=*/false, nullptr); 5973 return None; 5974 } 5975 } 5976 5977 for (Value *V : VL) { 5978 ScheduleData *BundleMember = getScheduleData(V); 5979 assert(BundleMember && 5980 "no ScheduleData for bundle member (maybe not in same basic block)"); 5981 if (BundleMember->IsScheduled) { 5982 // A bundle member was scheduled as single instruction before and now 5983 // needs to be scheduled as part of the bundle. We just get rid of the 5984 // existing schedule. 5985 LLVM_DEBUG(dbgs() << "SLP: reset schedule because " << *BundleMember 5986 << " was already scheduled\n"); 5987 ReSchedule = true; 5988 } 5989 assert(BundleMember->isSchedulingEntity() && 5990 "bundle member already part of other bundle"); 5991 if (PrevInBundle) { 5992 PrevInBundle->NextInBundle = BundleMember; 5993 } else { 5994 Bundle = BundleMember; 5995 } 5996 BundleMember->UnscheduledDepsInBundle = 0; 5997 Bundle->UnscheduledDepsInBundle += BundleMember->UnscheduledDeps; 5998 5999 // Group the instructions to a bundle. 6000 BundleMember->FirstInBundle = Bundle; 6001 PrevInBundle = BundleMember; 6002 } 6003 assert(Bundle && "Failed to find schedule bundle"); 6004 TryScheduleBundle(ReSchedule, Bundle); 6005 if (!Bundle->isReady()) { 6006 cancelScheduling(VL, S.OpValue); 6007 return None; 6008 } 6009 return Bundle; 6010 } 6011 6012 void BoUpSLP::BlockScheduling::cancelScheduling(ArrayRef<Value *> VL, 6013 Value *OpValue) { 6014 if (isa<PHINode>(OpValue) || isa<InsertElementInst>(OpValue)) 6015 return; 6016 6017 ScheduleData *Bundle = getScheduleData(OpValue); 6018 LLVM_DEBUG(dbgs() << "SLP: cancel scheduling of " << *Bundle << "\n"); 6019 assert(!Bundle->IsScheduled && 6020 "Can't cancel bundle which is already scheduled"); 6021 assert(Bundle->isSchedulingEntity() && Bundle->isPartOfBundle() && 6022 "tried to unbundle something which is not a bundle"); 6023 6024 // Un-bundle: make single instructions out of the bundle. 6025 ScheduleData *BundleMember = Bundle; 6026 while (BundleMember) { 6027 assert(BundleMember->FirstInBundle == Bundle && "corrupt bundle links"); 6028 BundleMember->FirstInBundle = BundleMember; 6029 ScheduleData *Next = BundleMember->NextInBundle; 6030 BundleMember->NextInBundle = nullptr; 6031 BundleMember->UnscheduledDepsInBundle = BundleMember->UnscheduledDeps; 6032 if (BundleMember->UnscheduledDepsInBundle == 0) { 6033 ReadyInsts.insert(BundleMember); 6034 } 6035 BundleMember = Next; 6036 } 6037 } 6038 6039 BoUpSLP::ScheduleData *BoUpSLP::BlockScheduling::allocateScheduleDataChunks() { 6040 // Allocate a new ScheduleData for the instruction. 6041 if (ChunkPos >= ChunkSize) { 6042 ScheduleDataChunks.push_back(std::make_unique<ScheduleData[]>(ChunkSize)); 6043 ChunkPos = 0; 6044 } 6045 return &(ScheduleDataChunks.back()[ChunkPos++]); 6046 } 6047 6048 bool BoUpSLP::BlockScheduling::extendSchedulingRegion(Value *V, 6049 const InstructionsState &S) { 6050 if (getScheduleData(V, isOneOf(S, V))) 6051 return true; 6052 Instruction *I = dyn_cast<Instruction>(V); 6053 assert(I && "bundle member must be an instruction"); 6054 assert(!isa<PHINode>(I) && !isa<InsertElementInst>(I) && 6055 "phi nodes/insertelements don't need to be scheduled"); 6056 auto &&CheckSheduleForI = [this, &S](Instruction *I) -> bool { 6057 ScheduleData *ISD = getScheduleData(I); 6058 if (!ISD) 6059 return false; 6060 assert(isInSchedulingRegion(ISD) && 6061 "ScheduleData not in scheduling region"); 6062 ScheduleData *SD = allocateScheduleDataChunks(); 6063 SD->Inst = I; 6064 SD->init(SchedulingRegionID, S.OpValue); 6065 ExtraScheduleDataMap[I][S.OpValue] = SD; 6066 return true; 6067 }; 6068 if (CheckSheduleForI(I)) 6069 return true; 6070 if (!ScheduleStart) { 6071 // It's the first instruction in the new region. 6072 initScheduleData(I, I->getNextNode(), nullptr, nullptr); 6073 ScheduleStart = I; 6074 ScheduleEnd = I->getNextNode(); 6075 if (isOneOf(S, I) != I) 6076 CheckSheduleForI(I); 6077 assert(ScheduleEnd && "tried to vectorize a terminator?"); 6078 LLVM_DEBUG(dbgs() << "SLP: initialize schedule region to " << *I << "\n"); 6079 return true; 6080 } 6081 // Search up and down at the same time, because we don't know if the new 6082 // instruction is above or below the existing scheduling region. 6083 BasicBlock::reverse_iterator UpIter = 6084 ++ScheduleStart->getIterator().getReverse(); 6085 BasicBlock::reverse_iterator UpperEnd = BB->rend(); 6086 BasicBlock::iterator DownIter = ScheduleEnd->getIterator(); 6087 BasicBlock::iterator LowerEnd = BB->end(); 6088 while (UpIter != UpperEnd && DownIter != LowerEnd && &*UpIter != I && 6089 &*DownIter != I) { 6090 if (++ScheduleRegionSize > ScheduleRegionSizeLimit) { 6091 LLVM_DEBUG(dbgs() << "SLP: exceeded schedule region size limit\n"); 6092 return false; 6093 } 6094 6095 ++UpIter; 6096 ++DownIter; 6097 } 6098 if (DownIter == LowerEnd || (UpIter != UpperEnd && &*UpIter == I)) { 6099 assert(I->getParent() == ScheduleStart->getParent() && 6100 "Instruction is in wrong basic block."); 6101 initScheduleData(I, ScheduleStart, nullptr, FirstLoadStoreInRegion); 6102 ScheduleStart = I; 6103 if (isOneOf(S, I) != I) 6104 CheckSheduleForI(I); 6105 LLVM_DEBUG(dbgs() << "SLP: extend schedule region start to " << *I 6106 << "\n"); 6107 return true; 6108 } 6109 assert((UpIter == UpperEnd || (DownIter != LowerEnd && &*DownIter == I)) && 6110 "Expected to reach top of the basic block or instruction down the " 6111 "lower end."); 6112 assert(I->getParent() == ScheduleEnd->getParent() && 6113 "Instruction is in wrong basic block."); 6114 initScheduleData(ScheduleEnd, I->getNextNode(), LastLoadStoreInRegion, 6115 nullptr); 6116 ScheduleEnd = I->getNextNode(); 6117 if (isOneOf(S, I) != I) 6118 CheckSheduleForI(I); 6119 assert(ScheduleEnd && "tried to vectorize a terminator?"); 6120 LLVM_DEBUG(dbgs() << "SLP: extend schedule region end to " << *I << "\n"); 6121 return true; 6122 } 6123 6124 void BoUpSLP::BlockScheduling::initScheduleData(Instruction *FromI, 6125 Instruction *ToI, 6126 ScheduleData *PrevLoadStore, 6127 ScheduleData *NextLoadStore) { 6128 ScheduleData *CurrentLoadStore = PrevLoadStore; 6129 for (Instruction *I = FromI; I != ToI; I = I->getNextNode()) { 6130 ScheduleData *SD = ScheduleDataMap[I]; 6131 if (!SD) { 6132 SD = allocateScheduleDataChunks(); 6133 ScheduleDataMap[I] = SD; 6134 SD->Inst = I; 6135 } 6136 assert(!isInSchedulingRegion(SD) && 6137 "new ScheduleData already in scheduling region"); 6138 SD->init(SchedulingRegionID, I); 6139 6140 if (I->mayReadOrWriteMemory() && 6141 (!isa<IntrinsicInst>(I) || 6142 (cast<IntrinsicInst>(I)->getIntrinsicID() != Intrinsic::sideeffect && 6143 cast<IntrinsicInst>(I)->getIntrinsicID() != 6144 Intrinsic::pseudoprobe))) { 6145 // Update the linked list of memory accessing instructions. 6146 if (CurrentLoadStore) { 6147 CurrentLoadStore->NextLoadStore = SD; 6148 } else { 6149 FirstLoadStoreInRegion = SD; 6150 } 6151 CurrentLoadStore = SD; 6152 } 6153 } 6154 if (NextLoadStore) { 6155 if (CurrentLoadStore) 6156 CurrentLoadStore->NextLoadStore = NextLoadStore; 6157 } else { 6158 LastLoadStoreInRegion = CurrentLoadStore; 6159 } 6160 } 6161 6162 void BoUpSLP::BlockScheduling::calculateDependencies(ScheduleData *SD, 6163 bool InsertInReadyList, 6164 BoUpSLP *SLP) { 6165 assert(SD->isSchedulingEntity()); 6166 6167 SmallVector<ScheduleData *, 10> WorkList; 6168 WorkList.push_back(SD); 6169 6170 while (!WorkList.empty()) { 6171 ScheduleData *SD = WorkList.pop_back_val(); 6172 6173 ScheduleData *BundleMember = SD; 6174 while (BundleMember) { 6175 assert(isInSchedulingRegion(BundleMember)); 6176 if (!BundleMember->hasValidDependencies()) { 6177 6178 LLVM_DEBUG(dbgs() << "SLP: update deps of " << *BundleMember 6179 << "\n"); 6180 BundleMember->Dependencies = 0; 6181 BundleMember->resetUnscheduledDeps(); 6182 6183 // Handle def-use chain dependencies. 6184 if (BundleMember->OpValue != BundleMember->Inst) { 6185 ScheduleData *UseSD = getScheduleData(BundleMember->Inst); 6186 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 6187 BundleMember->Dependencies++; 6188 ScheduleData *DestBundle = UseSD->FirstInBundle; 6189 if (!DestBundle->IsScheduled) 6190 BundleMember->incrementUnscheduledDeps(1); 6191 if (!DestBundle->hasValidDependencies()) 6192 WorkList.push_back(DestBundle); 6193 } 6194 } else { 6195 for (User *U : BundleMember->Inst->users()) { 6196 if (isa<Instruction>(U)) { 6197 ScheduleData *UseSD = getScheduleData(U); 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 // I'm not sure if this can ever happen. But we need to be safe. 6208 // This lets the instruction/bundle never be scheduled and 6209 // eventually disable vectorization. 6210 BundleMember->Dependencies++; 6211 BundleMember->incrementUnscheduledDeps(1); 6212 } 6213 } 6214 } 6215 6216 // Handle the memory dependencies. 6217 ScheduleData *DepDest = BundleMember->NextLoadStore; 6218 if (DepDest) { 6219 Instruction *SrcInst = BundleMember->Inst; 6220 MemoryLocation SrcLoc = getLocation(SrcInst, SLP->AA); 6221 bool SrcMayWrite = BundleMember->Inst->mayWriteToMemory(); 6222 unsigned numAliased = 0; 6223 unsigned DistToSrc = 1; 6224 6225 while (DepDest) { 6226 assert(isInSchedulingRegion(DepDest)); 6227 6228 // We have two limits to reduce the complexity: 6229 // 1) AliasedCheckLimit: It's a small limit to reduce calls to 6230 // SLP->isAliased (which is the expensive part in this loop). 6231 // 2) MaxMemDepDistance: It's for very large blocks and it aborts 6232 // the whole loop (even if the loop is fast, it's quadratic). 6233 // It's important for the loop break condition (see below) to 6234 // check this limit even between two read-only instructions. 6235 if (DistToSrc >= MaxMemDepDistance || 6236 ((SrcMayWrite || DepDest->Inst->mayWriteToMemory()) && 6237 (numAliased >= AliasedCheckLimit || 6238 SLP->isAliased(SrcLoc, SrcInst, DepDest->Inst)))) { 6239 6240 // We increment the counter only if the locations are aliased 6241 // (instead of counting all alias checks). This gives a better 6242 // balance between reduced runtime and accurate dependencies. 6243 numAliased++; 6244 6245 DepDest->MemoryDependencies.push_back(BundleMember); 6246 BundleMember->Dependencies++; 6247 ScheduleData *DestBundle = DepDest->FirstInBundle; 6248 if (!DestBundle->IsScheduled) { 6249 BundleMember->incrementUnscheduledDeps(1); 6250 } 6251 if (!DestBundle->hasValidDependencies()) { 6252 WorkList.push_back(DestBundle); 6253 } 6254 } 6255 DepDest = DepDest->NextLoadStore; 6256 6257 // Example, explaining the loop break condition: Let's assume our 6258 // starting instruction is i0 and MaxMemDepDistance = 3. 6259 // 6260 // +--------v--v--v 6261 // i0,i1,i2,i3,i4,i5,i6,i7,i8 6262 // +--------^--^--^ 6263 // 6264 // MaxMemDepDistance let us stop alias-checking at i3 and we add 6265 // dependencies from i0 to i3,i4,.. (even if they are not aliased). 6266 // Previously we already added dependencies from i3 to i6,i7,i8 6267 // (because of MaxMemDepDistance). As we added a dependency from 6268 // i0 to i3, we have transitive dependencies from i0 to i6,i7,i8 6269 // and we can abort this loop at i6. 6270 if (DistToSrc >= 2 * MaxMemDepDistance) 6271 break; 6272 DistToSrc++; 6273 } 6274 } 6275 } 6276 BundleMember = BundleMember->NextInBundle; 6277 } 6278 if (InsertInReadyList && SD->isReady()) { 6279 ReadyInsts.push_back(SD); 6280 LLVM_DEBUG(dbgs() << "SLP: gets ready on update: " << *SD->Inst 6281 << "\n"); 6282 } 6283 } 6284 } 6285 6286 void BoUpSLP::BlockScheduling::resetSchedule() { 6287 assert(ScheduleStart && 6288 "tried to reset schedule on block which has not been scheduled"); 6289 for (Instruction *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 6290 doForAllOpcodes(I, [&](ScheduleData *SD) { 6291 assert(isInSchedulingRegion(SD) && 6292 "ScheduleData not in scheduling region"); 6293 SD->IsScheduled = false; 6294 SD->resetUnscheduledDeps(); 6295 }); 6296 } 6297 ReadyInsts.clear(); 6298 } 6299 6300 void BoUpSLP::scheduleBlock(BlockScheduling *BS) { 6301 if (!BS->ScheduleStart) 6302 return; 6303 6304 LLVM_DEBUG(dbgs() << "SLP: schedule block " << BS->BB->getName() << "\n"); 6305 6306 BS->resetSchedule(); 6307 6308 // For the real scheduling we use a more sophisticated ready-list: it is 6309 // sorted by the original instruction location. This lets the final schedule 6310 // be as close as possible to the original instruction order. 6311 struct ScheduleDataCompare { 6312 bool operator()(ScheduleData *SD1, ScheduleData *SD2) const { 6313 return SD2->SchedulingPriority < SD1->SchedulingPriority; 6314 } 6315 }; 6316 std::set<ScheduleData *, ScheduleDataCompare> ReadyInsts; 6317 6318 // Ensure that all dependency data is updated and fill the ready-list with 6319 // initial instructions. 6320 int Idx = 0; 6321 int NumToSchedule = 0; 6322 for (auto *I = BS->ScheduleStart; I != BS->ScheduleEnd; 6323 I = I->getNextNode()) { 6324 BS->doForAllOpcodes(I, [this, &Idx, &NumToSchedule, BS](ScheduleData *SD) { 6325 assert((isa<InsertElementInst>(SD->Inst) || 6326 SD->isPartOfBundle() == (getTreeEntry(SD->Inst) != nullptr)) && 6327 "scheduler and vectorizer bundle mismatch"); 6328 SD->FirstInBundle->SchedulingPriority = Idx++; 6329 if (SD->isSchedulingEntity()) { 6330 BS->calculateDependencies(SD, false, this); 6331 NumToSchedule++; 6332 } 6333 }); 6334 } 6335 BS->initialFillReadyList(ReadyInsts); 6336 6337 Instruction *LastScheduledInst = BS->ScheduleEnd; 6338 6339 // Do the "real" scheduling. 6340 while (!ReadyInsts.empty()) { 6341 ScheduleData *picked = *ReadyInsts.begin(); 6342 ReadyInsts.erase(ReadyInsts.begin()); 6343 6344 // Move the scheduled instruction(s) to their dedicated places, if not 6345 // there yet. 6346 ScheduleData *BundleMember = picked; 6347 while (BundleMember) { 6348 Instruction *pickedInst = BundleMember->Inst; 6349 if (pickedInst->getNextNode() != LastScheduledInst) { 6350 BS->BB->getInstList().remove(pickedInst); 6351 BS->BB->getInstList().insert(LastScheduledInst->getIterator(), 6352 pickedInst); 6353 } 6354 LastScheduledInst = pickedInst; 6355 BundleMember = BundleMember->NextInBundle; 6356 } 6357 6358 BS->schedule(picked, ReadyInsts); 6359 NumToSchedule--; 6360 } 6361 assert(NumToSchedule == 0 && "could not schedule all instructions"); 6362 6363 // Avoid duplicate scheduling of the block. 6364 BS->ScheduleStart = nullptr; 6365 } 6366 6367 unsigned BoUpSLP::getVectorElementSize(Value *V) { 6368 // If V is a store, just return the width of the stored value (or value 6369 // truncated just before storing) without traversing the expression tree. 6370 // This is the common case. 6371 if (auto *Store = dyn_cast<StoreInst>(V)) { 6372 if (auto *Trunc = dyn_cast<TruncInst>(Store->getValueOperand())) 6373 return DL->getTypeSizeInBits(Trunc->getSrcTy()); 6374 return DL->getTypeSizeInBits(Store->getValueOperand()->getType()); 6375 } 6376 6377 if (auto *IEI = dyn_cast<InsertElementInst>(V)) 6378 return getVectorElementSize(IEI->getOperand(1)); 6379 6380 auto E = InstrElementSize.find(V); 6381 if (E != InstrElementSize.end()) 6382 return E->second; 6383 6384 // If V is not a store, we can traverse the expression tree to find loads 6385 // that feed it. The type of the loaded value may indicate a more suitable 6386 // width than V's type. We want to base the vector element size on the width 6387 // of memory operations where possible. 6388 SmallVector<std::pair<Instruction *, BasicBlock *>, 16> Worklist; 6389 SmallPtrSet<Instruction *, 16> Visited; 6390 if (auto *I = dyn_cast<Instruction>(V)) { 6391 Worklist.emplace_back(I, I->getParent()); 6392 Visited.insert(I); 6393 } 6394 6395 // Traverse the expression tree in bottom-up order looking for loads. If we 6396 // encounter an instruction we don't yet handle, we give up. 6397 auto Width = 0u; 6398 while (!Worklist.empty()) { 6399 Instruction *I; 6400 BasicBlock *Parent; 6401 std::tie(I, Parent) = Worklist.pop_back_val(); 6402 6403 // We should only be looking at scalar instructions here. If the current 6404 // instruction has a vector type, skip. 6405 auto *Ty = I->getType(); 6406 if (isa<VectorType>(Ty)) 6407 continue; 6408 6409 // If the current instruction is a load, update MaxWidth to reflect the 6410 // width of the loaded value. 6411 if (isa<LoadInst>(I) || isa<ExtractElementInst>(I) || 6412 isa<ExtractValueInst>(I)) 6413 Width = std::max<unsigned>(Width, DL->getTypeSizeInBits(Ty)); 6414 6415 // Otherwise, we need to visit the operands of the instruction. We only 6416 // handle the interesting cases from buildTree here. If an operand is an 6417 // instruction we haven't yet visited and from the same basic block as the 6418 // user or the use is a PHI node, we add it to the worklist. 6419 else if (isa<PHINode>(I) || isa<CastInst>(I) || isa<GetElementPtrInst>(I) || 6420 isa<CmpInst>(I) || isa<SelectInst>(I) || isa<BinaryOperator>(I) || 6421 isa<UnaryOperator>(I)) { 6422 for (Use &U : I->operands()) 6423 if (auto *J = dyn_cast<Instruction>(U.get())) 6424 if (Visited.insert(J).second && 6425 (isa<PHINode>(I) || J->getParent() == Parent)) 6426 Worklist.emplace_back(J, J->getParent()); 6427 } else { 6428 break; 6429 } 6430 } 6431 6432 // If we didn't encounter a memory access in the expression tree, or if we 6433 // gave up for some reason, just return the width of V. Otherwise, return the 6434 // maximum width we found. 6435 if (!Width) { 6436 if (auto *CI = dyn_cast<CmpInst>(V)) 6437 V = CI->getOperand(0); 6438 Width = DL->getTypeSizeInBits(V->getType()); 6439 } 6440 6441 for (Instruction *I : Visited) 6442 InstrElementSize[I] = Width; 6443 6444 return Width; 6445 } 6446 6447 // Determine if a value V in a vectorizable expression Expr can be demoted to a 6448 // smaller type with a truncation. We collect the values that will be demoted 6449 // in ToDemote and additional roots that require investigating in Roots. 6450 static bool collectValuesToDemote(Value *V, SmallPtrSetImpl<Value *> &Expr, 6451 SmallVectorImpl<Value *> &ToDemote, 6452 SmallVectorImpl<Value *> &Roots) { 6453 // We can always demote constants. 6454 if (isa<Constant>(V)) { 6455 ToDemote.push_back(V); 6456 return true; 6457 } 6458 6459 // If the value is not an instruction in the expression with only one use, it 6460 // cannot be demoted. 6461 auto *I = dyn_cast<Instruction>(V); 6462 if (!I || !I->hasOneUse() || !Expr.count(I)) 6463 return false; 6464 6465 switch (I->getOpcode()) { 6466 6467 // We can always demote truncations and extensions. Since truncations can 6468 // seed additional demotion, we save the truncated value. 6469 case Instruction::Trunc: 6470 Roots.push_back(I->getOperand(0)); 6471 break; 6472 case Instruction::ZExt: 6473 case Instruction::SExt: 6474 if (isa<ExtractElementInst>(I->getOperand(0)) || 6475 isa<InsertElementInst>(I->getOperand(0))) 6476 return false; 6477 break; 6478 6479 // We can demote certain binary operations if we can demote both of their 6480 // operands. 6481 case Instruction::Add: 6482 case Instruction::Sub: 6483 case Instruction::Mul: 6484 case Instruction::And: 6485 case Instruction::Or: 6486 case Instruction::Xor: 6487 if (!collectValuesToDemote(I->getOperand(0), Expr, ToDemote, Roots) || 6488 !collectValuesToDemote(I->getOperand(1), Expr, ToDemote, Roots)) 6489 return false; 6490 break; 6491 6492 // We can demote selects if we can demote their true and false values. 6493 case Instruction::Select: { 6494 SelectInst *SI = cast<SelectInst>(I); 6495 if (!collectValuesToDemote(SI->getTrueValue(), Expr, ToDemote, Roots) || 6496 !collectValuesToDemote(SI->getFalseValue(), Expr, ToDemote, Roots)) 6497 return false; 6498 break; 6499 } 6500 6501 // We can demote phis if we can demote all their incoming operands. Note that 6502 // we don't need to worry about cycles since we ensure single use above. 6503 case Instruction::PHI: { 6504 PHINode *PN = cast<PHINode>(I); 6505 for (Value *IncValue : PN->incoming_values()) 6506 if (!collectValuesToDemote(IncValue, Expr, ToDemote, Roots)) 6507 return false; 6508 break; 6509 } 6510 6511 // Otherwise, conservatively give up. 6512 default: 6513 return false; 6514 } 6515 6516 // Record the value that we can demote. 6517 ToDemote.push_back(V); 6518 return true; 6519 } 6520 6521 void BoUpSLP::computeMinimumValueSizes() { 6522 // If there are no external uses, the expression tree must be rooted by a 6523 // store. We can't demote in-memory values, so there is nothing to do here. 6524 if (ExternalUses.empty()) 6525 return; 6526 6527 // We only attempt to truncate integer expressions. 6528 auto &TreeRoot = VectorizableTree[0]->Scalars; 6529 auto *TreeRootIT = dyn_cast<IntegerType>(TreeRoot[0]->getType()); 6530 if (!TreeRootIT) 6531 return; 6532 6533 // If the expression is not rooted by a store, these roots should have 6534 // external uses. We will rely on InstCombine to rewrite the expression in 6535 // the narrower type. However, InstCombine only rewrites single-use values. 6536 // This means that if a tree entry other than a root is used externally, it 6537 // must have multiple uses and InstCombine will not rewrite it. The code 6538 // below ensures that only the roots are used externally. 6539 SmallPtrSet<Value *, 32> Expr(TreeRoot.begin(), TreeRoot.end()); 6540 for (auto &EU : ExternalUses) 6541 if (!Expr.erase(EU.Scalar)) 6542 return; 6543 if (!Expr.empty()) 6544 return; 6545 6546 // Collect the scalar values of the vectorizable expression. We will use this 6547 // context to determine which values can be demoted. If we see a truncation, 6548 // we mark it as seeding another demotion. 6549 for (auto &EntryPtr : VectorizableTree) 6550 Expr.insert(EntryPtr->Scalars.begin(), EntryPtr->Scalars.end()); 6551 6552 // Ensure the roots of the vectorizable tree don't form a cycle. They must 6553 // have a single external user that is not in the vectorizable tree. 6554 for (auto *Root : TreeRoot) 6555 if (!Root->hasOneUse() || Expr.count(*Root->user_begin())) 6556 return; 6557 6558 // Conservatively determine if we can actually truncate the roots of the 6559 // expression. Collect the values that can be demoted in ToDemote and 6560 // additional roots that require investigating in Roots. 6561 SmallVector<Value *, 32> ToDemote; 6562 SmallVector<Value *, 4> Roots; 6563 for (auto *Root : TreeRoot) 6564 if (!collectValuesToDemote(Root, Expr, ToDemote, Roots)) 6565 return; 6566 6567 // The maximum bit width required to represent all the values that can be 6568 // demoted without loss of precision. It would be safe to truncate the roots 6569 // of the expression to this width. 6570 auto MaxBitWidth = 8u; 6571 6572 // We first check if all the bits of the roots are demanded. If they're not, 6573 // we can truncate the roots to this narrower type. 6574 for (auto *Root : TreeRoot) { 6575 auto Mask = DB->getDemandedBits(cast<Instruction>(Root)); 6576 MaxBitWidth = std::max<unsigned>( 6577 Mask.getBitWidth() - Mask.countLeadingZeros(), MaxBitWidth); 6578 } 6579 6580 // True if the roots can be zero-extended back to their original type, rather 6581 // than sign-extended. We know that if the leading bits are not demanded, we 6582 // can safely zero-extend. So we initialize IsKnownPositive to True. 6583 bool IsKnownPositive = true; 6584 6585 // If all the bits of the roots are demanded, we can try a little harder to 6586 // compute a narrower type. This can happen, for example, if the roots are 6587 // getelementptr indices. InstCombine promotes these indices to the pointer 6588 // width. Thus, all their bits are technically demanded even though the 6589 // address computation might be vectorized in a smaller type. 6590 // 6591 // We start by looking at each entry that can be demoted. We compute the 6592 // maximum bit width required to store the scalar by using ValueTracking to 6593 // compute the number of high-order bits we can truncate. 6594 if (MaxBitWidth == DL->getTypeSizeInBits(TreeRoot[0]->getType()) && 6595 llvm::all_of(TreeRoot, [](Value *R) { 6596 assert(R->hasOneUse() && "Root should have only one use!"); 6597 return isa<GetElementPtrInst>(R->user_back()); 6598 })) { 6599 MaxBitWidth = 8u; 6600 6601 // Determine if the sign bit of all the roots is known to be zero. If not, 6602 // IsKnownPositive is set to False. 6603 IsKnownPositive = llvm::all_of(TreeRoot, [&](Value *R) { 6604 KnownBits Known = computeKnownBits(R, *DL); 6605 return Known.isNonNegative(); 6606 }); 6607 6608 // Determine the maximum number of bits required to store the scalar 6609 // values. 6610 for (auto *Scalar : ToDemote) { 6611 auto NumSignBits = ComputeNumSignBits(Scalar, *DL, 0, AC, nullptr, DT); 6612 auto NumTypeBits = DL->getTypeSizeInBits(Scalar->getType()); 6613 MaxBitWidth = std::max<unsigned>(NumTypeBits - NumSignBits, MaxBitWidth); 6614 } 6615 6616 // If we can't prove that the sign bit is zero, we must add one to the 6617 // maximum bit width to account for the unknown sign bit. This preserves 6618 // the existing sign bit so we can safely sign-extend the root back to the 6619 // original type. Otherwise, if we know the sign bit is zero, we will 6620 // zero-extend the root instead. 6621 // 6622 // FIXME: This is somewhat suboptimal, as there will be cases where adding 6623 // one to the maximum bit width will yield a larger-than-necessary 6624 // type. In general, we need to add an extra bit only if we can't 6625 // prove that the upper bit of the original type is equal to the 6626 // upper bit of the proposed smaller type. If these two bits are the 6627 // same (either zero or one) we know that sign-extending from the 6628 // smaller type will result in the same value. Here, since we can't 6629 // yet prove this, we are just making the proposed smaller type 6630 // larger to ensure correctness. 6631 if (!IsKnownPositive) 6632 ++MaxBitWidth; 6633 } 6634 6635 // Round MaxBitWidth up to the next power-of-two. 6636 if (!isPowerOf2_64(MaxBitWidth)) 6637 MaxBitWidth = NextPowerOf2(MaxBitWidth); 6638 6639 // If the maximum bit width we compute is less than the with of the roots' 6640 // type, we can proceed with the narrowing. Otherwise, do nothing. 6641 if (MaxBitWidth >= TreeRootIT->getBitWidth()) 6642 return; 6643 6644 // If we can truncate the root, we must collect additional values that might 6645 // be demoted as a result. That is, those seeded by truncations we will 6646 // modify. 6647 while (!Roots.empty()) 6648 collectValuesToDemote(Roots.pop_back_val(), Expr, ToDemote, Roots); 6649 6650 // Finally, map the values we can demote to the maximum bit with we computed. 6651 for (auto *Scalar : ToDemote) 6652 MinBWs[Scalar] = std::make_pair(MaxBitWidth, !IsKnownPositive); 6653 } 6654 6655 namespace { 6656 6657 /// The SLPVectorizer Pass. 6658 struct SLPVectorizer : public FunctionPass { 6659 SLPVectorizerPass Impl; 6660 6661 /// Pass identification, replacement for typeid 6662 static char ID; 6663 6664 explicit SLPVectorizer() : FunctionPass(ID) { 6665 initializeSLPVectorizerPass(*PassRegistry::getPassRegistry()); 6666 } 6667 6668 bool doInitialization(Module &M) override { 6669 return false; 6670 } 6671 6672 bool runOnFunction(Function &F) override { 6673 if (skipFunction(F)) 6674 return false; 6675 6676 auto *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 6677 auto *TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F); 6678 auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>(); 6679 auto *TLI = TLIP ? &TLIP->getTLI(F) : nullptr; 6680 auto *AA = &getAnalysis<AAResultsWrapperPass>().getAAResults(); 6681 auto *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 6682 auto *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 6683 auto *AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F); 6684 auto *DB = &getAnalysis<DemandedBitsWrapperPass>().getDemandedBits(); 6685 auto *ORE = &getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE(); 6686 6687 return Impl.runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 6688 } 6689 6690 void getAnalysisUsage(AnalysisUsage &AU) const override { 6691 FunctionPass::getAnalysisUsage(AU); 6692 AU.addRequired<AssumptionCacheTracker>(); 6693 AU.addRequired<ScalarEvolutionWrapperPass>(); 6694 AU.addRequired<AAResultsWrapperPass>(); 6695 AU.addRequired<TargetTransformInfoWrapperPass>(); 6696 AU.addRequired<LoopInfoWrapperPass>(); 6697 AU.addRequired<DominatorTreeWrapperPass>(); 6698 AU.addRequired<DemandedBitsWrapperPass>(); 6699 AU.addRequired<OptimizationRemarkEmitterWrapperPass>(); 6700 AU.addRequired<InjectTLIMappingsLegacy>(); 6701 AU.addPreserved<LoopInfoWrapperPass>(); 6702 AU.addPreserved<DominatorTreeWrapperPass>(); 6703 AU.addPreserved<AAResultsWrapperPass>(); 6704 AU.addPreserved<GlobalsAAWrapperPass>(); 6705 AU.setPreservesCFG(); 6706 } 6707 }; 6708 6709 } // end anonymous namespace 6710 6711 PreservedAnalyses SLPVectorizerPass::run(Function &F, FunctionAnalysisManager &AM) { 6712 auto *SE = &AM.getResult<ScalarEvolutionAnalysis>(F); 6713 auto *TTI = &AM.getResult<TargetIRAnalysis>(F); 6714 auto *TLI = AM.getCachedResult<TargetLibraryAnalysis>(F); 6715 auto *AA = &AM.getResult<AAManager>(F); 6716 auto *LI = &AM.getResult<LoopAnalysis>(F); 6717 auto *DT = &AM.getResult<DominatorTreeAnalysis>(F); 6718 auto *AC = &AM.getResult<AssumptionAnalysis>(F); 6719 auto *DB = &AM.getResult<DemandedBitsAnalysis>(F); 6720 auto *ORE = &AM.getResult<OptimizationRemarkEmitterAnalysis>(F); 6721 6722 bool Changed = runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 6723 if (!Changed) 6724 return PreservedAnalyses::all(); 6725 6726 PreservedAnalyses PA; 6727 PA.preserveSet<CFGAnalyses>(); 6728 return PA; 6729 } 6730 6731 bool SLPVectorizerPass::runImpl(Function &F, ScalarEvolution *SE_, 6732 TargetTransformInfo *TTI_, 6733 TargetLibraryInfo *TLI_, AAResults *AA_, 6734 LoopInfo *LI_, DominatorTree *DT_, 6735 AssumptionCache *AC_, DemandedBits *DB_, 6736 OptimizationRemarkEmitter *ORE_) { 6737 if (!RunSLPVectorization) 6738 return false; 6739 SE = SE_; 6740 TTI = TTI_; 6741 TLI = TLI_; 6742 AA = AA_; 6743 LI = LI_; 6744 DT = DT_; 6745 AC = AC_; 6746 DB = DB_; 6747 DL = &F.getParent()->getDataLayout(); 6748 6749 Stores.clear(); 6750 GEPs.clear(); 6751 bool Changed = false; 6752 6753 // If the target claims to have no vector registers don't attempt 6754 // vectorization. 6755 if (!TTI->getNumberOfRegisters(TTI->getRegisterClassForType(true))) 6756 return false; 6757 6758 // Don't vectorize when the attribute NoImplicitFloat is used. 6759 if (F.hasFnAttribute(Attribute::NoImplicitFloat)) 6760 return false; 6761 6762 LLVM_DEBUG(dbgs() << "SLP: Analyzing blocks in " << F.getName() << ".\n"); 6763 6764 // Use the bottom up slp vectorizer to construct chains that start with 6765 // store instructions. 6766 BoUpSLP R(&F, SE, TTI, TLI, AA, LI, DT, AC, DB, DL, ORE_); 6767 6768 // A general note: the vectorizer must use BoUpSLP::eraseInstruction() to 6769 // delete instructions. 6770 6771 // Update DFS numbers now so that we can use them for ordering. 6772 DT->updateDFSNumbers(); 6773 6774 // Scan the blocks in the function in post order. 6775 for (auto BB : post_order(&F.getEntryBlock())) { 6776 collectSeedInstructions(BB); 6777 6778 // Vectorize trees that end at stores. 6779 if (!Stores.empty()) { 6780 LLVM_DEBUG(dbgs() << "SLP: Found stores for " << Stores.size() 6781 << " underlying objects.\n"); 6782 Changed |= vectorizeStoreChains(R); 6783 } 6784 6785 // Vectorize trees that end at reductions. 6786 Changed |= vectorizeChainsInBlock(BB, R); 6787 6788 // Vectorize the index computations of getelementptr instructions. This 6789 // is primarily intended to catch gather-like idioms ending at 6790 // non-consecutive loads. 6791 if (!GEPs.empty()) { 6792 LLVM_DEBUG(dbgs() << "SLP: Found GEPs for " << GEPs.size() 6793 << " underlying objects.\n"); 6794 Changed |= vectorizeGEPIndices(BB, R); 6795 } 6796 } 6797 6798 if (Changed) { 6799 R.optimizeGatherSequence(); 6800 LLVM_DEBUG(dbgs() << "SLP: vectorized \"" << F.getName() << "\"\n"); 6801 } 6802 return Changed; 6803 } 6804 6805 /// Order may have elements assigned special value (size) which is out of 6806 /// bounds. Such indices only appear on places which correspond to undef values 6807 /// (see canReuseExtract for details) and used in order to avoid undef values 6808 /// have effect on operands ordering. 6809 /// The first loop below simply finds all unused indices and then the next loop 6810 /// nest assigns these indices for undef values positions. 6811 /// As an example below Order has two undef positions and they have assigned 6812 /// values 3 and 7 respectively: 6813 /// before: 6 9 5 4 9 2 1 0 6814 /// after: 6 3 5 4 7 2 1 0 6815 /// \returns Fixed ordering. 6816 static BoUpSLP::OrdersType fixupOrderingIndices(ArrayRef<unsigned> Order) { 6817 BoUpSLP::OrdersType NewOrder(Order.begin(), Order.end()); 6818 const unsigned Sz = NewOrder.size(); 6819 SmallBitVector UsedIndices(Sz); 6820 SmallVector<int> MaskedIndices; 6821 for (int I = 0, E = NewOrder.size(); I < E; ++I) { 6822 if (NewOrder[I] < Sz) 6823 UsedIndices.set(NewOrder[I]); 6824 else 6825 MaskedIndices.push_back(I); 6826 } 6827 if (MaskedIndices.empty()) 6828 return NewOrder; 6829 SmallVector<int> AvailableIndices(MaskedIndices.size()); 6830 unsigned Cnt = 0; 6831 int Idx = UsedIndices.find_first(); 6832 do { 6833 AvailableIndices[Cnt] = Idx; 6834 Idx = UsedIndices.find_next(Idx); 6835 ++Cnt; 6836 } while (Idx > 0); 6837 assert(Cnt == MaskedIndices.size() && "Non-synced masked/available indices."); 6838 for (int I = 0, E = MaskedIndices.size(); I < E; ++I) 6839 NewOrder[MaskedIndices[I]] = AvailableIndices[I]; 6840 return NewOrder; 6841 } 6842 6843 bool SLPVectorizerPass::vectorizeStoreChain(ArrayRef<Value *> Chain, BoUpSLP &R, 6844 unsigned Idx) { 6845 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " << Chain.size() 6846 << "\n"); 6847 const unsigned Sz = R.getVectorElementSize(Chain[0]); 6848 const unsigned MinVF = R.getMinVecRegSize() / Sz; 6849 unsigned VF = Chain.size(); 6850 6851 if (!isPowerOf2_32(Sz) || !isPowerOf2_32(VF) || VF < 2 || VF < MinVF) 6852 return false; 6853 6854 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << VF << " stores at offset " << Idx 6855 << "\n"); 6856 6857 R.buildTree(Chain); 6858 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 6859 // TODO: Handle orders of size less than number of elements in the vector. 6860 if (Order && Order->size() == Chain.size()) { 6861 // TODO: reorder tree nodes without tree rebuilding. 6862 SmallVector<Value *, 4> ReorderedOps(Chain.size()); 6863 transform(fixupOrderingIndices(*Order), ReorderedOps.begin(), 6864 [Chain](const unsigned Idx) { return Chain[Idx]; }); 6865 R.buildTree(ReorderedOps); 6866 } 6867 if (R.isTreeTinyAndNotFullyVectorizable()) 6868 return false; 6869 if (R.isLoadCombineCandidate()) 6870 return false; 6871 6872 R.computeMinimumValueSizes(); 6873 6874 InstructionCost Cost = R.getTreeCost(); 6875 6876 LLVM_DEBUG(dbgs() << "SLP: Found cost = " << Cost << " for VF =" << VF << "\n"); 6877 if (Cost < -SLPCostThreshold) { 6878 LLVM_DEBUG(dbgs() << "SLP: Decided to vectorize cost = " << Cost << "\n"); 6879 6880 using namespace ore; 6881 6882 R.getORE()->emit(OptimizationRemark(SV_NAME, "StoresVectorized", 6883 cast<StoreInst>(Chain[0])) 6884 << "Stores SLP vectorized with cost " << NV("Cost", Cost) 6885 << " and with tree size " 6886 << NV("TreeSize", R.getTreeSize())); 6887 6888 R.vectorizeTree(); 6889 return true; 6890 } 6891 6892 return false; 6893 } 6894 6895 bool SLPVectorizerPass::vectorizeStores(ArrayRef<StoreInst *> Stores, 6896 BoUpSLP &R) { 6897 // We may run into multiple chains that merge into a single chain. We mark the 6898 // stores that we vectorized so that we don't visit the same store twice. 6899 BoUpSLP::ValueSet VectorizedStores; 6900 bool Changed = false; 6901 6902 int E = Stores.size(); 6903 SmallBitVector Tails(E, false); 6904 int MaxIter = MaxStoreLookup.getValue(); 6905 SmallVector<std::pair<int, int>, 16> ConsecutiveChain( 6906 E, std::make_pair(E, INT_MAX)); 6907 SmallVector<SmallBitVector, 4> CheckedPairs(E, SmallBitVector(E, false)); 6908 int IterCnt; 6909 auto &&FindConsecutiveAccess = [this, &Stores, &Tails, &IterCnt, MaxIter, 6910 &CheckedPairs, 6911 &ConsecutiveChain](int K, int Idx) { 6912 if (IterCnt >= MaxIter) 6913 return true; 6914 if (CheckedPairs[Idx].test(K)) 6915 return ConsecutiveChain[K].second == 1 && 6916 ConsecutiveChain[K].first == Idx; 6917 ++IterCnt; 6918 CheckedPairs[Idx].set(K); 6919 CheckedPairs[K].set(Idx); 6920 Optional<int> Diff = getPointersDiff( 6921 Stores[K]->getValueOperand()->getType(), Stores[K]->getPointerOperand(), 6922 Stores[Idx]->getValueOperand()->getType(), 6923 Stores[Idx]->getPointerOperand(), *DL, *SE, /*StrictCheck=*/true); 6924 if (!Diff || *Diff == 0) 6925 return false; 6926 int Val = *Diff; 6927 if (Val < 0) { 6928 if (ConsecutiveChain[Idx].second > -Val) { 6929 Tails.set(K); 6930 ConsecutiveChain[Idx] = std::make_pair(K, -Val); 6931 } 6932 return false; 6933 } 6934 if (ConsecutiveChain[K].second <= Val) 6935 return false; 6936 6937 Tails.set(Idx); 6938 ConsecutiveChain[K] = std::make_pair(Idx, Val); 6939 return Val == 1; 6940 }; 6941 // Do a quadratic search on all of the given stores in reverse order and find 6942 // all of the pairs of stores that follow each other. 6943 for (int Idx = E - 1; Idx >= 0; --Idx) { 6944 // If a store has multiple consecutive store candidates, search according 6945 // to the sequence: Idx-1, Idx+1, Idx-2, Idx+2, ... 6946 // This is because usually pairing with immediate succeeding or preceding 6947 // candidate create the best chance to find slp vectorization opportunity. 6948 const int MaxLookDepth = std::max(E - Idx, Idx + 1); 6949 IterCnt = 0; 6950 for (int Offset = 1, F = MaxLookDepth; Offset < F; ++Offset) 6951 if ((Idx >= Offset && FindConsecutiveAccess(Idx - Offset, Idx)) || 6952 (Idx + Offset < E && FindConsecutiveAccess(Idx + Offset, Idx))) 6953 break; 6954 } 6955 6956 // Tracks if we tried to vectorize stores starting from the given tail 6957 // already. 6958 SmallBitVector TriedTails(E, false); 6959 // For stores that start but don't end a link in the chain: 6960 for (int Cnt = E; Cnt > 0; --Cnt) { 6961 int I = Cnt - 1; 6962 if (ConsecutiveChain[I].first == E || Tails.test(I)) 6963 continue; 6964 // We found a store instr that starts a chain. Now follow the chain and try 6965 // to vectorize it. 6966 BoUpSLP::ValueList Operands; 6967 // Collect the chain into a list. 6968 while (I != E && !VectorizedStores.count(Stores[I])) { 6969 Operands.push_back(Stores[I]); 6970 Tails.set(I); 6971 if (ConsecutiveChain[I].second != 1) { 6972 // Mark the new end in the chain and go back, if required. It might be 6973 // required if the original stores come in reversed order, for example. 6974 if (ConsecutiveChain[I].first != E && 6975 Tails.test(ConsecutiveChain[I].first) && !TriedTails.test(I) && 6976 !VectorizedStores.count(Stores[ConsecutiveChain[I].first])) { 6977 TriedTails.set(I); 6978 Tails.reset(ConsecutiveChain[I].first); 6979 if (Cnt < ConsecutiveChain[I].first + 2) 6980 Cnt = ConsecutiveChain[I].first + 2; 6981 } 6982 break; 6983 } 6984 // Move to the next value in the chain. 6985 I = ConsecutiveChain[I].first; 6986 } 6987 assert(!Operands.empty() && "Expected non-empty list of stores."); 6988 6989 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 6990 unsigned EltSize = R.getVectorElementSize(Operands[0]); 6991 unsigned MaxElts = llvm::PowerOf2Floor(MaxVecRegSize / EltSize); 6992 6993 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / EltSize); 6994 unsigned MaxVF = std::min(R.getMaximumVF(EltSize, Instruction::Store), 6995 MaxElts); 6996 6997 // FIXME: Is division-by-2 the correct step? Should we assert that the 6998 // register size is a power-of-2? 6999 unsigned StartIdx = 0; 7000 for (unsigned Size = MaxVF; Size >= MinVF; Size /= 2) { 7001 for (unsigned Cnt = StartIdx, E = Operands.size(); Cnt + Size <= E;) { 7002 ArrayRef<Value *> Slice = makeArrayRef(Operands).slice(Cnt, Size); 7003 if (!VectorizedStores.count(Slice.front()) && 7004 !VectorizedStores.count(Slice.back()) && 7005 vectorizeStoreChain(Slice, R, Cnt)) { 7006 // Mark the vectorized stores so that we don't vectorize them again. 7007 VectorizedStores.insert(Slice.begin(), Slice.end()); 7008 Changed = true; 7009 // If we vectorized initial block, no need to try to vectorize it 7010 // again. 7011 if (Cnt == StartIdx) 7012 StartIdx += Size; 7013 Cnt += Size; 7014 continue; 7015 } 7016 ++Cnt; 7017 } 7018 // Check if the whole array was vectorized already - exit. 7019 if (StartIdx >= Operands.size()) 7020 break; 7021 } 7022 } 7023 7024 return Changed; 7025 } 7026 7027 void SLPVectorizerPass::collectSeedInstructions(BasicBlock *BB) { 7028 // Initialize the collections. We will make a single pass over the block. 7029 Stores.clear(); 7030 GEPs.clear(); 7031 7032 // Visit the store and getelementptr instructions in BB and organize them in 7033 // Stores and GEPs according to the underlying objects of their pointer 7034 // operands. 7035 for (Instruction &I : *BB) { 7036 // Ignore store instructions that are volatile or have a pointer operand 7037 // that doesn't point to a scalar type. 7038 if (auto *SI = dyn_cast<StoreInst>(&I)) { 7039 if (!SI->isSimple()) 7040 continue; 7041 if (!isValidElementType(SI->getValueOperand()->getType())) 7042 continue; 7043 Stores[getUnderlyingObject(SI->getPointerOperand())].push_back(SI); 7044 } 7045 7046 // Ignore getelementptr instructions that have more than one index, a 7047 // constant index, or a pointer operand that doesn't point to a scalar 7048 // type. 7049 else if (auto *GEP = dyn_cast<GetElementPtrInst>(&I)) { 7050 auto Idx = GEP->idx_begin()->get(); 7051 if (GEP->getNumIndices() > 1 || isa<Constant>(Idx)) 7052 continue; 7053 if (!isValidElementType(Idx->getType())) 7054 continue; 7055 if (GEP->getType()->isVectorTy()) 7056 continue; 7057 GEPs[GEP->getPointerOperand()].push_back(GEP); 7058 } 7059 } 7060 } 7061 7062 bool SLPVectorizerPass::tryToVectorizePair(Value *A, Value *B, BoUpSLP &R) { 7063 if (!A || !B) 7064 return false; 7065 Value *VL[] = {A, B}; 7066 return tryToVectorizeList(VL, R, /*AllowReorder=*/true); 7067 } 7068 7069 bool SLPVectorizerPass::tryToVectorizeList(ArrayRef<Value *> VL, BoUpSLP &R, 7070 bool AllowReorder) { 7071 if (VL.size() < 2) 7072 return false; 7073 7074 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize a list of length = " 7075 << VL.size() << ".\n"); 7076 7077 // Check that all of the parts are instructions of the same type, 7078 // we permit an alternate opcode via InstructionsState. 7079 InstructionsState S = getSameOpcode(VL); 7080 if (!S.getOpcode()) 7081 return false; 7082 7083 Instruction *I0 = cast<Instruction>(S.OpValue); 7084 // Make sure invalid types (including vector type) are rejected before 7085 // determining vectorization factor for scalar instructions. 7086 for (Value *V : VL) { 7087 Type *Ty = V->getType(); 7088 if (!isa<InsertElementInst>(V) && !isValidElementType(Ty)) { 7089 // NOTE: the following will give user internal llvm type name, which may 7090 // not be useful. 7091 R.getORE()->emit([&]() { 7092 std::string type_str; 7093 llvm::raw_string_ostream rso(type_str); 7094 Ty->print(rso); 7095 return OptimizationRemarkMissed(SV_NAME, "UnsupportedType", I0) 7096 << "Cannot SLP vectorize list: type " 7097 << rso.str() + " is unsupported by vectorizer"; 7098 }); 7099 return false; 7100 } 7101 } 7102 7103 unsigned Sz = R.getVectorElementSize(I0); 7104 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / Sz); 7105 unsigned MaxVF = std::max<unsigned>(PowerOf2Floor(VL.size()), MinVF); 7106 MaxVF = std::min(R.getMaximumVF(Sz, S.getOpcode()), MaxVF); 7107 if (MaxVF < 2) { 7108 R.getORE()->emit([&]() { 7109 return OptimizationRemarkMissed(SV_NAME, "SmallVF", I0) 7110 << "Cannot SLP vectorize list: vectorization factor " 7111 << "less than 2 is not supported"; 7112 }); 7113 return false; 7114 } 7115 7116 bool Changed = false; 7117 bool CandidateFound = false; 7118 InstructionCost MinCost = SLPCostThreshold.getValue(); 7119 Type *ScalarTy = VL[0]->getType(); 7120 if (auto *IE = dyn_cast<InsertElementInst>(VL[0])) 7121 ScalarTy = IE->getOperand(1)->getType(); 7122 7123 unsigned NextInst = 0, MaxInst = VL.size(); 7124 for (unsigned VF = MaxVF; NextInst + 1 < MaxInst && VF >= MinVF; VF /= 2) { 7125 // No actual vectorization should happen, if number of parts is the same as 7126 // provided vectorization factor (i.e. the scalar type is used for vector 7127 // code during codegen). 7128 auto *VecTy = FixedVectorType::get(ScalarTy, VF); 7129 if (TTI->getNumberOfParts(VecTy) == VF) 7130 continue; 7131 for (unsigned I = NextInst; I < MaxInst; ++I) { 7132 unsigned OpsWidth = 0; 7133 7134 if (I + VF > MaxInst) 7135 OpsWidth = MaxInst - I; 7136 else 7137 OpsWidth = VF; 7138 7139 if (!isPowerOf2_32(OpsWidth)) 7140 continue; 7141 7142 if ((VF > MinVF && OpsWidth <= VF / 2) || (VF == MinVF && OpsWidth < 2)) 7143 break; 7144 7145 ArrayRef<Value *> Ops = VL.slice(I, OpsWidth); 7146 // Check that a previous iteration of this loop did not delete the Value. 7147 if (llvm::any_of(Ops, [&R](Value *V) { 7148 auto *I = dyn_cast<Instruction>(V); 7149 return I && R.isDeleted(I); 7150 })) 7151 continue; 7152 7153 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << OpsWidth << " operations " 7154 << "\n"); 7155 7156 R.buildTree(Ops); 7157 if (AllowReorder) { 7158 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 7159 if (Order) { 7160 // TODO: reorder tree nodes without tree rebuilding. 7161 SmallVector<Value *, 4> ReorderedOps(Ops.size()); 7162 transform(fixupOrderingIndices(*Order), ReorderedOps.begin(), 7163 [Ops](const unsigned Idx) { return Ops[Idx]; }); 7164 R.buildTree(ReorderedOps); 7165 } 7166 } 7167 if (R.isTreeTinyAndNotFullyVectorizable()) 7168 continue; 7169 7170 R.computeMinimumValueSizes(); 7171 InstructionCost Cost = R.getTreeCost(); 7172 CandidateFound = true; 7173 MinCost = std::min(MinCost, Cost); 7174 7175 if (Cost < -SLPCostThreshold) { 7176 LLVM_DEBUG(dbgs() << "SLP: Vectorizing list at cost:" << Cost << ".\n"); 7177 R.getORE()->emit(OptimizationRemark(SV_NAME, "VectorizedList", 7178 cast<Instruction>(Ops[0])) 7179 << "SLP vectorized with cost " << ore::NV("Cost", Cost) 7180 << " and with tree size " 7181 << ore::NV("TreeSize", R.getTreeSize())); 7182 7183 R.vectorizeTree(); 7184 // Move to the next bundle. 7185 I += VF - 1; 7186 NextInst = I + 1; 7187 Changed = true; 7188 } 7189 } 7190 } 7191 7192 if (!Changed && CandidateFound) { 7193 R.getORE()->emit([&]() { 7194 return OptimizationRemarkMissed(SV_NAME, "NotBeneficial", I0) 7195 << "List vectorization was possible but not beneficial with cost " 7196 << ore::NV("Cost", MinCost) << " >= " 7197 << ore::NV("Treshold", -SLPCostThreshold); 7198 }); 7199 } else if (!Changed) { 7200 R.getORE()->emit([&]() { 7201 return OptimizationRemarkMissed(SV_NAME, "NotPossible", I0) 7202 << "Cannot SLP vectorize list: vectorization was impossible" 7203 << " with available vectorization factors"; 7204 }); 7205 } 7206 return Changed; 7207 } 7208 7209 bool SLPVectorizerPass::tryToVectorize(Instruction *I, BoUpSLP &R) { 7210 if (!I) 7211 return false; 7212 7213 if (!isa<BinaryOperator>(I) && !isa<CmpInst>(I)) 7214 return false; 7215 7216 Value *P = I->getParent(); 7217 7218 // Vectorize in current basic block only. 7219 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 7220 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 7221 if (!Op0 || !Op1 || Op0->getParent() != P || Op1->getParent() != P) 7222 return false; 7223 7224 // Try to vectorize V. 7225 if (tryToVectorizePair(Op0, Op1, R)) 7226 return true; 7227 7228 auto *A = dyn_cast<BinaryOperator>(Op0); 7229 auto *B = dyn_cast<BinaryOperator>(Op1); 7230 // Try to skip B. 7231 if (B && B->hasOneUse()) { 7232 auto *B0 = dyn_cast<BinaryOperator>(B->getOperand(0)); 7233 auto *B1 = dyn_cast<BinaryOperator>(B->getOperand(1)); 7234 if (B0 && B0->getParent() == P && tryToVectorizePair(A, B0, R)) 7235 return true; 7236 if (B1 && B1->getParent() == P && tryToVectorizePair(A, B1, R)) 7237 return true; 7238 } 7239 7240 // Try to skip A. 7241 if (A && A->hasOneUse()) { 7242 auto *A0 = dyn_cast<BinaryOperator>(A->getOperand(0)); 7243 auto *A1 = dyn_cast<BinaryOperator>(A->getOperand(1)); 7244 if (A0 && A0->getParent() == P && tryToVectorizePair(A0, B, R)) 7245 return true; 7246 if (A1 && A1->getParent() == P && tryToVectorizePair(A1, B, R)) 7247 return true; 7248 } 7249 return false; 7250 } 7251 7252 namespace { 7253 7254 /// Model horizontal reductions. 7255 /// 7256 /// A horizontal reduction is a tree of reduction instructions that has values 7257 /// that can be put into a vector as its leaves. For example: 7258 /// 7259 /// mul mul mul mul 7260 /// \ / \ / 7261 /// + + 7262 /// \ / 7263 /// + 7264 /// This tree has "mul" as its leaf values and "+" as its reduction 7265 /// instructions. A reduction can feed into a store or a binary operation 7266 /// feeding a phi. 7267 /// ... 7268 /// \ / 7269 /// + 7270 /// | 7271 /// phi += 7272 /// 7273 /// Or: 7274 /// ... 7275 /// \ / 7276 /// + 7277 /// | 7278 /// *p = 7279 /// 7280 class HorizontalReduction { 7281 using ReductionOpsType = SmallVector<Value *, 16>; 7282 using ReductionOpsListType = SmallVector<ReductionOpsType, 2>; 7283 ReductionOpsListType ReductionOps; 7284 SmallVector<Value *, 32> ReducedVals; 7285 // Use map vector to make stable output. 7286 MapVector<Instruction *, Value *> ExtraArgs; 7287 WeakTrackingVH ReductionRoot; 7288 /// The type of reduction operation. 7289 RecurKind RdxKind; 7290 7291 /// Checks if instruction is associative and can be vectorized. 7292 static bool isVectorizable(RecurKind Kind, Instruction *I) { 7293 if (Kind == RecurKind::None) 7294 return false; 7295 if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(Kind)) 7296 return true; 7297 7298 if (Kind == RecurKind::FMax || Kind == RecurKind::FMin) { 7299 // FP min/max are associative except for NaN and -0.0. We do not 7300 // have to rule out -0.0 here because the intrinsic semantics do not 7301 // specify a fixed result for it. 7302 return I->getFastMathFlags().noNaNs(); 7303 } 7304 7305 return I->isAssociative(); 7306 } 7307 7308 /// Checks if the ParentStackElem.first should be marked as a reduction 7309 /// operation with an extra argument or as extra argument itself. 7310 void markExtraArg(std::pair<Instruction *, unsigned> &ParentStackElem, 7311 Value *ExtraArg) { 7312 if (ExtraArgs.count(ParentStackElem.first)) { 7313 ExtraArgs[ParentStackElem.first] = nullptr; 7314 // We ran into something like: 7315 // ParentStackElem.first = ExtraArgs[ParentStackElem.first] + ExtraArg. 7316 // The whole ParentStackElem.first should be considered as an extra value 7317 // in this case. 7318 // Do not perform analysis of remaining operands of ParentStackElem.first 7319 // instruction, this whole instruction is an extra argument. 7320 ParentStackElem.second = getNumberOfOperands(ParentStackElem.first); 7321 } else { 7322 // We ran into something like: 7323 // ParentStackElem.first += ... + ExtraArg + ... 7324 ExtraArgs[ParentStackElem.first] = ExtraArg; 7325 } 7326 } 7327 7328 /// Creates reduction operation with the current opcode. 7329 static Value *createOp(IRBuilder<> &Builder, RecurKind Kind, Value *LHS, 7330 Value *RHS, const Twine &Name, bool UseSelect) { 7331 unsigned RdxOpcode = RecurrenceDescriptor::getOpcode(Kind); 7332 switch (Kind) { 7333 case RecurKind::Add: 7334 case RecurKind::Mul: 7335 case RecurKind::Or: 7336 case RecurKind::And: 7337 case RecurKind::Xor: 7338 case RecurKind::FAdd: 7339 case RecurKind::FMul: 7340 return Builder.CreateBinOp((Instruction::BinaryOps)RdxOpcode, LHS, RHS, 7341 Name); 7342 case RecurKind::FMax: 7343 return Builder.CreateBinaryIntrinsic(Intrinsic::maxnum, LHS, RHS); 7344 case RecurKind::FMin: 7345 return Builder.CreateBinaryIntrinsic(Intrinsic::minnum, LHS, RHS); 7346 case RecurKind::SMax: 7347 if (UseSelect) { 7348 Value *Cmp = Builder.CreateICmpSGT(LHS, RHS, Name); 7349 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 7350 } 7351 return Builder.CreateBinaryIntrinsic(Intrinsic::smax, LHS, RHS); 7352 case RecurKind::SMin: 7353 if (UseSelect) { 7354 Value *Cmp = Builder.CreateICmpSLT(LHS, RHS, Name); 7355 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 7356 } 7357 return Builder.CreateBinaryIntrinsic(Intrinsic::smin, LHS, RHS); 7358 case RecurKind::UMax: 7359 if (UseSelect) { 7360 Value *Cmp = Builder.CreateICmpUGT(LHS, RHS, Name); 7361 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 7362 } 7363 return Builder.CreateBinaryIntrinsic(Intrinsic::umax, LHS, RHS); 7364 case RecurKind::UMin: 7365 if (UseSelect) { 7366 Value *Cmp = Builder.CreateICmpULT(LHS, RHS, Name); 7367 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 7368 } 7369 return Builder.CreateBinaryIntrinsic(Intrinsic::umin, LHS, RHS); 7370 default: 7371 llvm_unreachable("Unknown reduction operation."); 7372 } 7373 } 7374 7375 /// Creates reduction operation with the current opcode with the IR flags 7376 /// from \p ReductionOps. 7377 static Value *createOp(IRBuilder<> &Builder, RecurKind RdxKind, Value *LHS, 7378 Value *RHS, const Twine &Name, 7379 const ReductionOpsListType &ReductionOps) { 7380 bool UseSelect = ReductionOps.size() == 2; 7381 assert((!UseSelect || isa<SelectInst>(ReductionOps[1][0])) && 7382 "Expected cmp + select pairs for reduction"); 7383 Value *Op = createOp(Builder, RdxKind, LHS, RHS, Name, UseSelect); 7384 if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(RdxKind)) { 7385 if (auto *Sel = dyn_cast<SelectInst>(Op)) { 7386 propagateIRFlags(Sel->getCondition(), ReductionOps[0]); 7387 propagateIRFlags(Op, ReductionOps[1]); 7388 return Op; 7389 } 7390 } 7391 propagateIRFlags(Op, ReductionOps[0]); 7392 return Op; 7393 } 7394 7395 /// Creates reduction operation with the current opcode with the IR flags 7396 /// from \p I. 7397 static Value *createOp(IRBuilder<> &Builder, RecurKind RdxKind, Value *LHS, 7398 Value *RHS, const Twine &Name, Instruction *I) { 7399 auto *SelI = dyn_cast<SelectInst>(I); 7400 Value *Op = createOp(Builder, RdxKind, LHS, RHS, Name, SelI != nullptr); 7401 if (SelI && RecurrenceDescriptor::isIntMinMaxRecurrenceKind(RdxKind)) { 7402 if (auto *Sel = dyn_cast<SelectInst>(Op)) 7403 propagateIRFlags(Sel->getCondition(), SelI->getCondition()); 7404 } 7405 propagateIRFlags(Op, I); 7406 return Op; 7407 } 7408 7409 static RecurKind getRdxKind(Instruction *I) { 7410 assert(I && "Expected instruction for reduction matching"); 7411 TargetTransformInfo::ReductionFlags RdxFlags; 7412 if (match(I, m_Add(m_Value(), m_Value()))) 7413 return RecurKind::Add; 7414 if (match(I, m_Mul(m_Value(), m_Value()))) 7415 return RecurKind::Mul; 7416 if (match(I, m_And(m_Value(), m_Value()))) 7417 return RecurKind::And; 7418 if (match(I, m_Or(m_Value(), m_Value()))) 7419 return RecurKind::Or; 7420 if (match(I, m_Xor(m_Value(), m_Value()))) 7421 return RecurKind::Xor; 7422 if (match(I, m_FAdd(m_Value(), m_Value()))) 7423 return RecurKind::FAdd; 7424 if (match(I, m_FMul(m_Value(), m_Value()))) 7425 return RecurKind::FMul; 7426 7427 if (match(I, m_Intrinsic<Intrinsic::maxnum>(m_Value(), m_Value()))) 7428 return RecurKind::FMax; 7429 if (match(I, m_Intrinsic<Intrinsic::minnum>(m_Value(), m_Value()))) 7430 return RecurKind::FMin; 7431 7432 // This matches either cmp+select or intrinsics. SLP is expected to handle 7433 // either form. 7434 // TODO: If we are canonicalizing to intrinsics, we can remove several 7435 // special-case paths that deal with selects. 7436 if (match(I, m_SMax(m_Value(), m_Value()))) 7437 return RecurKind::SMax; 7438 if (match(I, m_SMin(m_Value(), m_Value()))) 7439 return RecurKind::SMin; 7440 if (match(I, m_UMax(m_Value(), m_Value()))) 7441 return RecurKind::UMax; 7442 if (match(I, m_UMin(m_Value(), m_Value()))) 7443 return RecurKind::UMin; 7444 7445 if (auto *Select = dyn_cast<SelectInst>(I)) { 7446 // Try harder: look for min/max pattern based on instructions producing 7447 // same values such as: select ((cmp Inst1, Inst2), Inst1, Inst2). 7448 // During the intermediate stages of SLP, it's very common to have 7449 // pattern like this (since optimizeGatherSequence is run only once 7450 // at the end): 7451 // %1 = extractelement <2 x i32> %a, i32 0 7452 // %2 = extractelement <2 x i32> %a, i32 1 7453 // %cond = icmp sgt i32 %1, %2 7454 // %3 = extractelement <2 x i32> %a, i32 0 7455 // %4 = extractelement <2 x i32> %a, i32 1 7456 // %select = select i1 %cond, i32 %3, i32 %4 7457 CmpInst::Predicate Pred; 7458 Instruction *L1; 7459 Instruction *L2; 7460 7461 Value *LHS = Select->getTrueValue(); 7462 Value *RHS = Select->getFalseValue(); 7463 Value *Cond = Select->getCondition(); 7464 7465 // TODO: Support inverse predicates. 7466 if (match(Cond, m_Cmp(Pred, m_Specific(LHS), m_Instruction(L2)))) { 7467 if (!isa<ExtractElementInst>(RHS) || 7468 !L2->isIdenticalTo(cast<Instruction>(RHS))) 7469 return RecurKind::None; 7470 } else if (match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Specific(RHS)))) { 7471 if (!isa<ExtractElementInst>(LHS) || 7472 !L1->isIdenticalTo(cast<Instruction>(LHS))) 7473 return RecurKind::None; 7474 } else { 7475 if (!isa<ExtractElementInst>(LHS) || !isa<ExtractElementInst>(RHS)) 7476 return RecurKind::None; 7477 if (!match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Instruction(L2))) || 7478 !L1->isIdenticalTo(cast<Instruction>(LHS)) || 7479 !L2->isIdenticalTo(cast<Instruction>(RHS))) 7480 return RecurKind::None; 7481 } 7482 7483 TargetTransformInfo::ReductionFlags RdxFlags; 7484 switch (Pred) { 7485 default: 7486 return RecurKind::None; 7487 case CmpInst::ICMP_SGT: 7488 case CmpInst::ICMP_SGE: 7489 return RecurKind::SMax; 7490 case CmpInst::ICMP_SLT: 7491 case CmpInst::ICMP_SLE: 7492 return RecurKind::SMin; 7493 case CmpInst::ICMP_UGT: 7494 case CmpInst::ICMP_UGE: 7495 return RecurKind::UMax; 7496 case CmpInst::ICMP_ULT: 7497 case CmpInst::ICMP_ULE: 7498 return RecurKind::UMin; 7499 } 7500 } 7501 return RecurKind::None; 7502 } 7503 7504 /// Get the index of the first operand. 7505 static unsigned getFirstOperandIndex(Instruction *I) { 7506 return isa<SelectInst>(I) ? 1 : 0; 7507 } 7508 7509 /// Total number of operands in the reduction operation. 7510 static unsigned getNumberOfOperands(Instruction *I) { 7511 return isa<SelectInst>(I) ? 3 : 2; 7512 } 7513 7514 /// Checks if the instruction is in basic block \p BB. 7515 /// For a min/max reduction check that both compare and select are in \p BB. 7516 static bool hasSameParent(Instruction *I, BasicBlock *BB, bool IsRedOp) { 7517 auto *Sel = dyn_cast<SelectInst>(I); 7518 if (IsRedOp && Sel) { 7519 auto *Cmp = cast<Instruction>(Sel->getCondition()); 7520 return Sel->getParent() == BB && Cmp->getParent() == BB; 7521 } 7522 return I->getParent() == BB; 7523 } 7524 7525 /// Expected number of uses for reduction operations/reduced values. 7526 static bool hasRequiredNumberOfUses(bool MatchCmpSel, Instruction *I) { 7527 // SelectInst must be used twice while the condition op must have single 7528 // use only. 7529 if (MatchCmpSel) { 7530 if (auto *Sel = dyn_cast<SelectInst>(I)) 7531 return Sel->hasNUses(2) && Sel->getCondition()->hasOneUse(); 7532 return I->hasNUses(2); 7533 } 7534 7535 // Arithmetic reduction operation must be used once only. 7536 return I->hasOneUse(); 7537 } 7538 7539 /// Initializes the list of reduction operations. 7540 void initReductionOps(Instruction *I) { 7541 if (isa<SelectInst>(I)) 7542 ReductionOps.assign(2, ReductionOpsType()); 7543 else 7544 ReductionOps.assign(1, ReductionOpsType()); 7545 } 7546 7547 /// Add all reduction operations for the reduction instruction \p I. 7548 void addReductionOps(Instruction *I) { 7549 if (auto *Sel = dyn_cast<SelectInst>(I)) { 7550 ReductionOps[0].emplace_back(Sel->getCondition()); 7551 ReductionOps[1].emplace_back(Sel); 7552 } else { 7553 ReductionOps[0].emplace_back(I); 7554 } 7555 } 7556 7557 static Value *getLHS(RecurKind Kind, Instruction *I) { 7558 if (Kind == RecurKind::None) 7559 return nullptr; 7560 return I->getOperand(getFirstOperandIndex(I)); 7561 } 7562 static Value *getRHS(RecurKind Kind, Instruction *I) { 7563 if (Kind == RecurKind::None) 7564 return nullptr; 7565 return I->getOperand(getFirstOperandIndex(I) + 1); 7566 } 7567 7568 public: 7569 HorizontalReduction() = default; 7570 7571 /// Try to find a reduction tree. 7572 bool matchAssociativeReduction(PHINode *Phi, Instruction *Inst) { 7573 assert((!Phi || is_contained(Phi->operands(), Inst)) && 7574 "Phi needs to use the binary operator"); 7575 assert((isa<BinaryOperator>(Inst) || isa<SelectInst>(Inst) || 7576 isa<IntrinsicInst>(Inst)) && 7577 "Expected binop, select, or intrinsic for reduction matching"); 7578 RdxKind = getRdxKind(Inst); 7579 7580 // We could have a initial reductions that is not an add. 7581 // r *= v1 + v2 + v3 + v4 7582 // In such a case start looking for a tree rooted in the first '+'. 7583 if (Phi) { 7584 if (getLHS(RdxKind, Inst) == Phi) { 7585 Phi = nullptr; 7586 Inst = dyn_cast<Instruction>(getRHS(RdxKind, Inst)); 7587 if (!Inst) 7588 return false; 7589 RdxKind = getRdxKind(Inst); 7590 } else if (getRHS(RdxKind, Inst) == Phi) { 7591 Phi = nullptr; 7592 Inst = dyn_cast<Instruction>(getLHS(RdxKind, Inst)); 7593 if (!Inst) 7594 return false; 7595 RdxKind = getRdxKind(Inst); 7596 } 7597 } 7598 7599 if (!isVectorizable(RdxKind, Inst)) 7600 return false; 7601 7602 // Analyze "regular" integer/FP types for reductions - no target-specific 7603 // types or pointers. 7604 Type *Ty = Inst->getType(); 7605 if (!isValidElementType(Ty) || Ty->isPointerTy()) 7606 return false; 7607 7608 // Though the ultimate reduction may have multiple uses, its condition must 7609 // have only single use. 7610 if (auto *Sel = dyn_cast<SelectInst>(Inst)) 7611 if (!Sel->getCondition()->hasOneUse()) 7612 return false; 7613 7614 ReductionRoot = Inst; 7615 7616 // The opcode for leaf values that we perform a reduction on. 7617 // For example: load(x) + load(y) + load(z) + fptoui(w) 7618 // The leaf opcode for 'w' does not match, so we don't include it as a 7619 // potential candidate for the reduction. 7620 unsigned LeafOpcode = 0; 7621 7622 // Post order traverse the reduction tree starting at B. We only handle true 7623 // trees containing only binary operators. 7624 SmallVector<std::pair<Instruction *, unsigned>, 32> Stack; 7625 Stack.push_back(std::make_pair(Inst, getFirstOperandIndex(Inst))); 7626 initReductionOps(Inst); 7627 while (!Stack.empty()) { 7628 Instruction *TreeN = Stack.back().first; 7629 unsigned EdgeToVisit = Stack.back().second++; 7630 const RecurKind TreeRdxKind = getRdxKind(TreeN); 7631 bool IsReducedValue = TreeRdxKind != RdxKind; 7632 7633 // Postorder visit. 7634 if (IsReducedValue || EdgeToVisit == getNumberOfOperands(TreeN)) { 7635 if (IsReducedValue) 7636 ReducedVals.push_back(TreeN); 7637 else { 7638 auto ExtraArgsIter = ExtraArgs.find(TreeN); 7639 if (ExtraArgsIter != ExtraArgs.end() && !ExtraArgsIter->second) { 7640 // Check if TreeN is an extra argument of its parent operation. 7641 if (Stack.size() <= 1) { 7642 // TreeN can't be an extra argument as it is a root reduction 7643 // operation. 7644 return false; 7645 } 7646 // Yes, TreeN is an extra argument, do not add it to a list of 7647 // reduction operations. 7648 // Stack[Stack.size() - 2] always points to the parent operation. 7649 markExtraArg(Stack[Stack.size() - 2], TreeN); 7650 ExtraArgs.erase(TreeN); 7651 } else 7652 addReductionOps(TreeN); 7653 } 7654 // Retract. 7655 Stack.pop_back(); 7656 continue; 7657 } 7658 7659 // Visit left or right. 7660 Value *EdgeVal = TreeN->getOperand(EdgeToVisit); 7661 auto *EdgeInst = dyn_cast<Instruction>(EdgeVal); 7662 if (!EdgeInst) { 7663 // Edge value is not a reduction instruction or a leaf instruction. 7664 // (It may be a constant, function argument, or something else.) 7665 markExtraArg(Stack.back(), EdgeVal); 7666 continue; 7667 } 7668 RecurKind EdgeRdxKind = getRdxKind(EdgeInst); 7669 // Continue analysis if the next operand is a reduction operation or 7670 // (possibly) a leaf value. If the leaf value opcode is not set, 7671 // the first met operation != reduction operation is considered as the 7672 // leaf opcode. 7673 // Only handle trees in the current basic block. 7674 // Each tree node needs to have minimal number of users except for the 7675 // ultimate reduction. 7676 const bool IsRdxInst = EdgeRdxKind == RdxKind; 7677 if (EdgeInst != Phi && EdgeInst != Inst && 7678 hasSameParent(EdgeInst, Inst->getParent(), IsRdxInst) && 7679 hasRequiredNumberOfUses(isa<SelectInst>(Inst), EdgeInst) && 7680 (!LeafOpcode || LeafOpcode == EdgeInst->getOpcode() || IsRdxInst)) { 7681 if (IsRdxInst) { 7682 // We need to be able to reassociate the reduction operations. 7683 if (!isVectorizable(EdgeRdxKind, EdgeInst)) { 7684 // I is an extra argument for TreeN (its parent operation). 7685 markExtraArg(Stack.back(), EdgeInst); 7686 continue; 7687 } 7688 } else if (!LeafOpcode) { 7689 LeafOpcode = EdgeInst->getOpcode(); 7690 } 7691 Stack.push_back( 7692 std::make_pair(EdgeInst, getFirstOperandIndex(EdgeInst))); 7693 continue; 7694 } 7695 // I is an extra argument for TreeN (its parent operation). 7696 markExtraArg(Stack.back(), EdgeInst); 7697 } 7698 return true; 7699 } 7700 7701 /// Attempt to vectorize the tree found by matchAssociativeReduction. 7702 bool tryToReduce(BoUpSLP &V, TargetTransformInfo *TTI) { 7703 // If there are a sufficient number of reduction values, reduce 7704 // to a nearby power-of-2. We can safely generate oversized 7705 // vectors and rely on the backend to split them to legal sizes. 7706 unsigned NumReducedVals = ReducedVals.size(); 7707 if (NumReducedVals < 4) 7708 return false; 7709 7710 // Intersect the fast-math-flags from all reduction operations. 7711 FastMathFlags RdxFMF; 7712 RdxFMF.set(); 7713 for (ReductionOpsType &RdxOp : ReductionOps) { 7714 for (Value *RdxVal : RdxOp) { 7715 if (auto *FPMO = dyn_cast<FPMathOperator>(RdxVal)) 7716 RdxFMF &= FPMO->getFastMathFlags(); 7717 } 7718 } 7719 7720 IRBuilder<> Builder(cast<Instruction>(ReductionRoot)); 7721 Builder.setFastMathFlags(RdxFMF); 7722 7723 BoUpSLP::ExtraValueToDebugLocsMap ExternallyUsedValues; 7724 // The same extra argument may be used several times, so log each attempt 7725 // to use it. 7726 for (const std::pair<Instruction *, Value *> &Pair : ExtraArgs) { 7727 assert(Pair.first && "DebugLoc must be set."); 7728 ExternallyUsedValues[Pair.second].push_back(Pair.first); 7729 } 7730 7731 // The compare instruction of a min/max is the insertion point for new 7732 // instructions and may be replaced with a new compare instruction. 7733 auto getCmpForMinMaxReduction = [](Instruction *RdxRootInst) { 7734 assert(isa<SelectInst>(RdxRootInst) && 7735 "Expected min/max reduction to have select root instruction"); 7736 Value *ScalarCond = cast<SelectInst>(RdxRootInst)->getCondition(); 7737 assert(isa<Instruction>(ScalarCond) && 7738 "Expected min/max reduction to have compare condition"); 7739 return cast<Instruction>(ScalarCond); 7740 }; 7741 7742 // The reduction root is used as the insertion point for new instructions, 7743 // so set it as externally used to prevent it from being deleted. 7744 ExternallyUsedValues[ReductionRoot]; 7745 SmallVector<Value *, 16> IgnoreList; 7746 for (ReductionOpsType &RdxOp : ReductionOps) 7747 IgnoreList.append(RdxOp.begin(), RdxOp.end()); 7748 7749 unsigned ReduxWidth = PowerOf2Floor(NumReducedVals); 7750 if (NumReducedVals > ReduxWidth) { 7751 // In the loop below, we are building a tree based on a window of 7752 // 'ReduxWidth' values. 7753 // If the operands of those values have common traits (compare predicate, 7754 // constant operand, etc), then we want to group those together to 7755 // minimize the cost of the reduction. 7756 7757 // TODO: This should be extended to count common operands for 7758 // compares and binops. 7759 7760 // Step 1: Count the number of times each compare predicate occurs. 7761 SmallDenseMap<unsigned, unsigned> PredCountMap; 7762 for (Value *RdxVal : ReducedVals) { 7763 CmpInst::Predicate Pred; 7764 if (match(RdxVal, m_Cmp(Pred, m_Value(), m_Value()))) 7765 ++PredCountMap[Pred]; 7766 } 7767 // Step 2: Sort the values so the most common predicates come first. 7768 stable_sort(ReducedVals, [&PredCountMap](Value *A, Value *B) { 7769 CmpInst::Predicate PredA, PredB; 7770 if (match(A, m_Cmp(PredA, m_Value(), m_Value())) && 7771 match(B, m_Cmp(PredB, m_Value(), m_Value()))) { 7772 return PredCountMap[PredA] > PredCountMap[PredB]; 7773 } 7774 return false; 7775 }); 7776 } 7777 7778 Value *VectorizedTree = nullptr; 7779 unsigned i = 0; 7780 while (i < NumReducedVals - ReduxWidth + 1 && ReduxWidth > 2) { 7781 ArrayRef<Value *> VL(&ReducedVals[i], ReduxWidth); 7782 V.buildTree(VL, ExternallyUsedValues, IgnoreList); 7783 Optional<ArrayRef<unsigned>> Order = V.bestOrder(); 7784 if (Order) { 7785 assert(Order->size() == VL.size() && 7786 "Order size must be the same as number of vectorized " 7787 "instructions."); 7788 // TODO: reorder tree nodes without tree rebuilding. 7789 SmallVector<Value *, 4> ReorderedOps(VL.size()); 7790 transform(fixupOrderingIndices(*Order), ReorderedOps.begin(), 7791 [VL](const unsigned Idx) { return VL[Idx]; }); 7792 V.buildTree(ReorderedOps, ExternallyUsedValues, IgnoreList); 7793 } 7794 if (V.isTreeTinyAndNotFullyVectorizable()) 7795 break; 7796 if (V.isLoadCombineReductionCandidate(RdxKind)) 7797 break; 7798 7799 V.computeMinimumValueSizes(); 7800 7801 // Estimate cost. 7802 InstructionCost TreeCost = 7803 V.getTreeCost(makeArrayRef(&ReducedVals[i], ReduxWidth)); 7804 InstructionCost ReductionCost = 7805 getReductionCost(TTI, ReducedVals[i], ReduxWidth); 7806 InstructionCost Cost = TreeCost + ReductionCost; 7807 if (!Cost.isValid()) { 7808 LLVM_DEBUG(dbgs() << "Encountered invalid baseline cost.\n"); 7809 return false; 7810 } 7811 if (Cost >= -SLPCostThreshold) { 7812 V.getORE()->emit([&]() { 7813 return OptimizationRemarkMissed(SV_NAME, "HorSLPNotBeneficial", 7814 cast<Instruction>(VL[0])) 7815 << "Vectorizing horizontal reduction is possible" 7816 << "but not beneficial with cost " << ore::NV("Cost", Cost) 7817 << " and threshold " 7818 << ore::NV("Threshold", -SLPCostThreshold); 7819 }); 7820 break; 7821 } 7822 7823 LLVM_DEBUG(dbgs() << "SLP: Vectorizing horizontal reduction at cost:" 7824 << Cost << ". (HorRdx)\n"); 7825 V.getORE()->emit([&]() { 7826 return OptimizationRemark(SV_NAME, "VectorizedHorizontalReduction", 7827 cast<Instruction>(VL[0])) 7828 << "Vectorized horizontal reduction with cost " 7829 << ore::NV("Cost", Cost) << " and with tree size " 7830 << ore::NV("TreeSize", V.getTreeSize()); 7831 }); 7832 7833 // Vectorize a tree. 7834 DebugLoc Loc = cast<Instruction>(ReducedVals[i])->getDebugLoc(); 7835 Value *VectorizedRoot = V.vectorizeTree(ExternallyUsedValues); 7836 7837 // Emit a reduction. If the root is a select (min/max idiom), the insert 7838 // point is the compare condition of that select. 7839 Instruction *RdxRootInst = cast<Instruction>(ReductionRoot); 7840 if (isa<SelectInst>(RdxRootInst)) 7841 Builder.SetInsertPoint(getCmpForMinMaxReduction(RdxRootInst)); 7842 else 7843 Builder.SetInsertPoint(RdxRootInst); 7844 7845 Value *ReducedSubTree = 7846 emitReduction(VectorizedRoot, Builder, ReduxWidth, TTI); 7847 7848 if (!VectorizedTree) { 7849 // Initialize the final value in the reduction. 7850 VectorizedTree = ReducedSubTree; 7851 } else { 7852 // Update the final value in the reduction. 7853 Builder.SetCurrentDebugLocation(Loc); 7854 VectorizedTree = createOp(Builder, RdxKind, VectorizedTree, 7855 ReducedSubTree, "op.rdx", ReductionOps); 7856 } 7857 i += ReduxWidth; 7858 ReduxWidth = PowerOf2Floor(NumReducedVals - i); 7859 } 7860 7861 if (VectorizedTree) { 7862 // Finish the reduction. 7863 for (; i < NumReducedVals; ++i) { 7864 auto *I = cast<Instruction>(ReducedVals[i]); 7865 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 7866 VectorizedTree = 7867 createOp(Builder, RdxKind, VectorizedTree, I, "", ReductionOps); 7868 } 7869 for (auto &Pair : ExternallyUsedValues) { 7870 // Add each externally used value to the final reduction. 7871 for (auto *I : Pair.second) { 7872 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 7873 VectorizedTree = createOp(Builder, RdxKind, VectorizedTree, 7874 Pair.first, "op.extra", I); 7875 } 7876 } 7877 7878 ReductionRoot->replaceAllUsesWith(VectorizedTree); 7879 7880 // Mark all scalar reduction ops for deletion, they are replaced by the 7881 // vector reductions. 7882 V.eraseInstructions(IgnoreList); 7883 } 7884 return VectorizedTree != nullptr; 7885 } 7886 7887 unsigned numReductionValues() const { return ReducedVals.size(); } 7888 7889 private: 7890 /// Calculate the cost of a reduction. 7891 InstructionCost getReductionCost(TargetTransformInfo *TTI, 7892 Value *FirstReducedVal, 7893 unsigned ReduxWidth) { 7894 Type *ScalarTy = FirstReducedVal->getType(); 7895 FixedVectorType *VectorTy = FixedVectorType::get(ScalarTy, ReduxWidth); 7896 InstructionCost VectorCost, ScalarCost; 7897 switch (RdxKind) { 7898 case RecurKind::Add: 7899 case RecurKind::Mul: 7900 case RecurKind::Or: 7901 case RecurKind::And: 7902 case RecurKind::Xor: 7903 case RecurKind::FAdd: 7904 case RecurKind::FMul: { 7905 unsigned RdxOpcode = RecurrenceDescriptor::getOpcode(RdxKind); 7906 VectorCost = TTI->getArithmeticReductionCost(RdxOpcode, VectorTy); 7907 ScalarCost = TTI->getArithmeticInstrCost(RdxOpcode, ScalarTy); 7908 break; 7909 } 7910 case RecurKind::FMax: 7911 case RecurKind::FMin: { 7912 auto *VecCondTy = cast<VectorType>(CmpInst::makeCmpResultType(VectorTy)); 7913 VectorCost = TTI->getMinMaxReductionCost(VectorTy, VecCondTy, 7914 /*unsigned=*/false); 7915 ScalarCost = 7916 TTI->getCmpSelInstrCost(Instruction::FCmp, ScalarTy) + 7917 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 7918 CmpInst::makeCmpResultType(ScalarTy)); 7919 break; 7920 } 7921 case RecurKind::SMax: 7922 case RecurKind::SMin: 7923 case RecurKind::UMax: 7924 case RecurKind::UMin: { 7925 auto *VecCondTy = cast<VectorType>(CmpInst::makeCmpResultType(VectorTy)); 7926 bool IsUnsigned = 7927 RdxKind == RecurKind::UMax || RdxKind == RecurKind::UMin; 7928 VectorCost = TTI->getMinMaxReductionCost(VectorTy, VecCondTy, IsUnsigned); 7929 ScalarCost = 7930 TTI->getCmpSelInstrCost(Instruction::ICmp, ScalarTy) + 7931 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 7932 CmpInst::makeCmpResultType(ScalarTy)); 7933 break; 7934 } 7935 default: 7936 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 7937 } 7938 7939 // Scalar cost is repeated for N-1 elements. 7940 ScalarCost *= (ReduxWidth - 1); 7941 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << VectorCost - ScalarCost 7942 << " for reduction that starts with " << *FirstReducedVal 7943 << " (It is a splitting reduction)\n"); 7944 return VectorCost - ScalarCost; 7945 } 7946 7947 /// Emit a horizontal reduction of the vectorized value. 7948 Value *emitReduction(Value *VectorizedValue, IRBuilder<> &Builder, 7949 unsigned ReduxWidth, const TargetTransformInfo *TTI) { 7950 assert(VectorizedValue && "Need to have a vectorized tree node"); 7951 assert(isPowerOf2_32(ReduxWidth) && 7952 "We only handle power-of-two reductions for now"); 7953 7954 return createSimpleTargetReduction(Builder, TTI, VectorizedValue, RdxKind, 7955 ReductionOps.back()); 7956 } 7957 }; 7958 7959 } // end anonymous namespace 7960 7961 static Optional<unsigned> getAggregateSize(Instruction *InsertInst) { 7962 if (auto *IE = dyn_cast<InsertElementInst>(InsertInst)) 7963 return cast<FixedVectorType>(IE->getType())->getNumElements(); 7964 7965 unsigned AggregateSize = 1; 7966 auto *IV = cast<InsertValueInst>(InsertInst); 7967 Type *CurrentType = IV->getType(); 7968 do { 7969 if (auto *ST = dyn_cast<StructType>(CurrentType)) { 7970 for (auto *Elt : ST->elements()) 7971 if (Elt != ST->getElementType(0)) // check homogeneity 7972 return None; 7973 AggregateSize *= ST->getNumElements(); 7974 CurrentType = ST->getElementType(0); 7975 } else if (auto *AT = dyn_cast<ArrayType>(CurrentType)) { 7976 AggregateSize *= AT->getNumElements(); 7977 CurrentType = AT->getElementType(); 7978 } else if (auto *VT = dyn_cast<FixedVectorType>(CurrentType)) { 7979 AggregateSize *= VT->getNumElements(); 7980 return AggregateSize; 7981 } else if (CurrentType->isSingleValueType()) { 7982 return AggregateSize; 7983 } else { 7984 return None; 7985 } 7986 } while (true); 7987 } 7988 7989 static bool findBuildAggregate_rec(Instruction *LastInsertInst, 7990 TargetTransformInfo *TTI, 7991 SmallVectorImpl<Value *> &BuildVectorOpds, 7992 SmallVectorImpl<Value *> &InsertElts, 7993 unsigned OperandOffset) { 7994 do { 7995 Value *InsertedOperand = LastInsertInst->getOperand(1); 7996 Optional<int> OperandIndex = getInsertIndex(LastInsertInst, OperandOffset); 7997 if (!OperandIndex) 7998 return false; 7999 if (isa<InsertElementInst>(InsertedOperand) || 8000 isa<InsertValueInst>(InsertedOperand)) { 8001 if (!findBuildAggregate_rec(cast<Instruction>(InsertedOperand), TTI, 8002 BuildVectorOpds, InsertElts, *OperandIndex)) 8003 return false; 8004 } else { 8005 BuildVectorOpds[*OperandIndex] = InsertedOperand; 8006 InsertElts[*OperandIndex] = LastInsertInst; 8007 } 8008 LastInsertInst = dyn_cast<Instruction>(LastInsertInst->getOperand(0)); 8009 } while (LastInsertInst != nullptr && 8010 (isa<InsertValueInst>(LastInsertInst) || 8011 isa<InsertElementInst>(LastInsertInst)) && 8012 LastInsertInst->hasOneUse()); 8013 return true; 8014 } 8015 8016 /// Recognize construction of vectors like 8017 /// %ra = insertelement <4 x float> poison, float %s0, i32 0 8018 /// %rb = insertelement <4 x float> %ra, float %s1, i32 1 8019 /// %rc = insertelement <4 x float> %rb, float %s2, i32 2 8020 /// %rd = insertelement <4 x float> %rc, float %s3, i32 3 8021 /// starting from the last insertelement or insertvalue instruction. 8022 /// 8023 /// Also recognize homogeneous aggregates like {<2 x float>, <2 x float>}, 8024 /// {{float, float}, {float, float}}, [2 x {float, float}] and so on. 8025 /// See llvm/test/Transforms/SLPVectorizer/X86/pr42022.ll for examples. 8026 /// 8027 /// Assume LastInsertInst is of InsertElementInst or InsertValueInst type. 8028 /// 8029 /// \return true if it matches. 8030 static bool findBuildAggregate(Instruction *LastInsertInst, 8031 TargetTransformInfo *TTI, 8032 SmallVectorImpl<Value *> &BuildVectorOpds, 8033 SmallVectorImpl<Value *> &InsertElts) { 8034 8035 assert((isa<InsertElementInst>(LastInsertInst) || 8036 isa<InsertValueInst>(LastInsertInst)) && 8037 "Expected insertelement or insertvalue instruction!"); 8038 8039 assert((BuildVectorOpds.empty() && InsertElts.empty()) && 8040 "Expected empty result vectors!"); 8041 8042 Optional<unsigned> AggregateSize = getAggregateSize(LastInsertInst); 8043 if (!AggregateSize) 8044 return false; 8045 BuildVectorOpds.resize(*AggregateSize); 8046 InsertElts.resize(*AggregateSize); 8047 8048 if (findBuildAggregate_rec(LastInsertInst, TTI, BuildVectorOpds, InsertElts, 8049 0)) { 8050 llvm::erase_value(BuildVectorOpds, nullptr); 8051 llvm::erase_value(InsertElts, nullptr); 8052 if (BuildVectorOpds.size() >= 2) 8053 return true; 8054 } 8055 8056 return false; 8057 } 8058 8059 /// Try and get a reduction value from a phi node. 8060 /// 8061 /// Given a phi node \p P in a block \p ParentBB, consider possible reductions 8062 /// if they come from either \p ParentBB or a containing loop latch. 8063 /// 8064 /// \returns A candidate reduction value if possible, or \code nullptr \endcode 8065 /// if not possible. 8066 static Value *getReductionValue(const DominatorTree *DT, PHINode *P, 8067 BasicBlock *ParentBB, LoopInfo *LI) { 8068 // There are situations where the reduction value is not dominated by the 8069 // reduction phi. Vectorizing such cases has been reported to cause 8070 // miscompiles. See PR25787. 8071 auto DominatedReduxValue = [&](Value *R) { 8072 return isa<Instruction>(R) && 8073 DT->dominates(P->getParent(), cast<Instruction>(R)->getParent()); 8074 }; 8075 8076 Value *Rdx = nullptr; 8077 8078 // Return the incoming value if it comes from the same BB as the phi node. 8079 if (P->getIncomingBlock(0) == ParentBB) { 8080 Rdx = P->getIncomingValue(0); 8081 } else if (P->getIncomingBlock(1) == ParentBB) { 8082 Rdx = P->getIncomingValue(1); 8083 } 8084 8085 if (Rdx && DominatedReduxValue(Rdx)) 8086 return Rdx; 8087 8088 // Otherwise, check whether we have a loop latch to look at. 8089 Loop *BBL = LI->getLoopFor(ParentBB); 8090 if (!BBL) 8091 return nullptr; 8092 BasicBlock *BBLatch = BBL->getLoopLatch(); 8093 if (!BBLatch) 8094 return nullptr; 8095 8096 // There is a loop latch, return the incoming value if it comes from 8097 // that. This reduction pattern occasionally turns up. 8098 if (P->getIncomingBlock(0) == BBLatch) { 8099 Rdx = P->getIncomingValue(0); 8100 } else if (P->getIncomingBlock(1) == BBLatch) { 8101 Rdx = P->getIncomingValue(1); 8102 } 8103 8104 if (Rdx && DominatedReduxValue(Rdx)) 8105 return Rdx; 8106 8107 return nullptr; 8108 } 8109 8110 static bool matchRdxBop(Instruction *I, Value *&V0, Value *&V1) { 8111 if (match(I, m_BinOp(m_Value(V0), m_Value(V1)))) 8112 return true; 8113 if (match(I, m_Intrinsic<Intrinsic::maxnum>(m_Value(V0), m_Value(V1)))) 8114 return true; 8115 if (match(I, m_Intrinsic<Intrinsic::minnum>(m_Value(V0), m_Value(V1)))) 8116 return true; 8117 if (match(I, m_Intrinsic<Intrinsic::smax>(m_Value(V0), m_Value(V1)))) 8118 return true; 8119 if (match(I, m_Intrinsic<Intrinsic::smin>(m_Value(V0), m_Value(V1)))) 8120 return true; 8121 if (match(I, m_Intrinsic<Intrinsic::umax>(m_Value(V0), m_Value(V1)))) 8122 return true; 8123 if (match(I, m_Intrinsic<Intrinsic::umin>(m_Value(V0), m_Value(V1)))) 8124 return true; 8125 return false; 8126 } 8127 8128 /// Attempt to reduce a horizontal reduction. 8129 /// If it is legal to match a horizontal reduction feeding the phi node \a P 8130 /// with reduction operators \a Root (or one of its operands) in a basic block 8131 /// \a BB, then check if it can be done. If horizontal reduction is not found 8132 /// and root instruction is a binary operation, vectorization of the operands is 8133 /// attempted. 8134 /// \returns true if a horizontal reduction was matched and reduced or operands 8135 /// of one of the binary instruction were vectorized. 8136 /// \returns false if a horizontal reduction was not matched (or not possible) 8137 /// or no vectorization of any binary operation feeding \a Root instruction was 8138 /// performed. 8139 static bool tryToVectorizeHorReductionOrInstOperands( 8140 PHINode *P, Instruction *Root, BasicBlock *BB, BoUpSLP &R, 8141 TargetTransformInfo *TTI, 8142 const function_ref<bool(Instruction *, BoUpSLP &)> Vectorize) { 8143 if (!ShouldVectorizeHor) 8144 return false; 8145 8146 if (!Root) 8147 return false; 8148 8149 if (Root->getParent() != BB || isa<PHINode>(Root)) 8150 return false; 8151 // Start analysis starting from Root instruction. If horizontal reduction is 8152 // found, try to vectorize it. If it is not a horizontal reduction or 8153 // vectorization is not possible or not effective, and currently analyzed 8154 // instruction is a binary operation, try to vectorize the operands, using 8155 // pre-order DFS traversal order. If the operands were not vectorized, repeat 8156 // the same procedure considering each operand as a possible root of the 8157 // horizontal reduction. 8158 // Interrupt the process if the Root instruction itself was vectorized or all 8159 // sub-trees not higher that RecursionMaxDepth were analyzed/vectorized. 8160 // Skip the analysis of CmpInsts.Compiler implements postanalysis of the 8161 // CmpInsts so we can skip extra attempts in 8162 // tryToVectorizeHorReductionOrInstOperands and save compile time. 8163 SmallVector<std::pair<Instruction *, unsigned>, 8> Stack(1, {Root, 0}); 8164 SmallPtrSet<Value *, 8> VisitedInstrs; 8165 bool Res = false; 8166 while (!Stack.empty()) { 8167 Instruction *Inst; 8168 unsigned Level; 8169 std::tie(Inst, Level) = Stack.pop_back_val(); 8170 Value *B0, *B1; 8171 bool IsBinop = matchRdxBop(Inst, B0, B1); 8172 bool IsSelect = match(Inst, m_Select(m_Value(), m_Value(), m_Value())); 8173 if (IsBinop || IsSelect) { 8174 HorizontalReduction HorRdx; 8175 if (HorRdx.matchAssociativeReduction(P, Inst)) { 8176 if (HorRdx.tryToReduce(R, TTI)) { 8177 Res = true; 8178 // Set P to nullptr to avoid re-analysis of phi node in 8179 // matchAssociativeReduction function unless this is the root node. 8180 P = nullptr; 8181 continue; 8182 } 8183 } 8184 if (P && IsBinop) { 8185 Inst = dyn_cast<Instruction>(B0); 8186 if (Inst == P) 8187 Inst = dyn_cast<Instruction>(B1); 8188 if (!Inst) { 8189 // Set P to nullptr to avoid re-analysis of phi node in 8190 // matchAssociativeReduction function unless this is the root node. 8191 P = nullptr; 8192 continue; 8193 } 8194 } 8195 } 8196 // Set P to nullptr to avoid re-analysis of phi node in 8197 // matchAssociativeReduction function unless this is the root node. 8198 P = nullptr; 8199 // Do not try to vectorize CmpInst operands, this is done separately. 8200 if (!isa<CmpInst>(Inst) && Vectorize(Inst, R)) { 8201 Res = true; 8202 continue; 8203 } 8204 8205 // Try to vectorize operands. 8206 // Continue analysis for the instruction from the same basic block only to 8207 // save compile time. 8208 if (++Level < RecursionMaxDepth) 8209 for (auto *Op : Inst->operand_values()) 8210 if (VisitedInstrs.insert(Op).second) 8211 if (auto *I = dyn_cast<Instruction>(Op)) 8212 // Do not try to vectorize CmpInst operands, this is done 8213 // separately. 8214 if (!isa<PHINode>(I) && !isa<CmpInst>(I) && !R.isDeleted(I) && 8215 I->getParent() == BB) 8216 Stack.emplace_back(I, Level); 8217 } 8218 return Res; 8219 } 8220 8221 bool SLPVectorizerPass::vectorizeRootInstruction(PHINode *P, Value *V, 8222 BasicBlock *BB, BoUpSLP &R, 8223 TargetTransformInfo *TTI) { 8224 auto *I = dyn_cast_or_null<Instruction>(V); 8225 if (!I) 8226 return false; 8227 8228 if (!isa<BinaryOperator>(I)) 8229 P = nullptr; 8230 // Try to match and vectorize a horizontal reduction. 8231 auto &&ExtraVectorization = [this](Instruction *I, BoUpSLP &R) -> bool { 8232 return tryToVectorize(I, R); 8233 }; 8234 return tryToVectorizeHorReductionOrInstOperands(P, I, BB, R, TTI, 8235 ExtraVectorization); 8236 } 8237 8238 bool SLPVectorizerPass::vectorizeInsertValueInst(InsertValueInst *IVI, 8239 BasicBlock *BB, BoUpSLP &R) { 8240 const DataLayout &DL = BB->getModule()->getDataLayout(); 8241 if (!R.canMapToVector(IVI->getType(), DL)) 8242 return false; 8243 8244 SmallVector<Value *, 16> BuildVectorOpds; 8245 SmallVector<Value *, 16> BuildVectorInsts; 8246 if (!findBuildAggregate(IVI, TTI, BuildVectorOpds, BuildVectorInsts)) 8247 return false; 8248 8249 LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IVI << "\n"); 8250 // Aggregate value is unlikely to be processed in vector register, we need to 8251 // extract scalars into scalar registers, so NeedExtraction is set true. 8252 return tryToVectorizeList(BuildVectorOpds, R, /*AllowReorder=*/false); 8253 } 8254 8255 bool SLPVectorizerPass::vectorizeInsertElementInst(InsertElementInst *IEI, 8256 BasicBlock *BB, BoUpSLP &R) { 8257 SmallVector<Value *, 16> BuildVectorInsts; 8258 SmallVector<Value *, 16> BuildVectorOpds; 8259 SmallVector<int> Mask; 8260 if (!findBuildAggregate(IEI, TTI, BuildVectorOpds, BuildVectorInsts) || 8261 (llvm::all_of(BuildVectorOpds, 8262 [](Value *V) { return isa<ExtractElementInst>(V); }) && 8263 isShuffle(BuildVectorOpds, Mask))) 8264 return false; 8265 8266 LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IEI << "\n"); 8267 return tryToVectorizeList(BuildVectorInsts, R, /*AllowReorder=*/true); 8268 } 8269 8270 bool SLPVectorizerPass::vectorizeSimpleInstructions( 8271 SmallVectorImpl<Instruction *> &Instructions, BasicBlock *BB, BoUpSLP &R, 8272 bool AtTerminator) { 8273 bool OpsChanged = false; 8274 SmallVector<Instruction *, 4> PostponedCmps; 8275 for (auto *I : reverse(Instructions)) { 8276 if (R.isDeleted(I)) 8277 continue; 8278 if (auto *LastInsertValue = dyn_cast<InsertValueInst>(I)) 8279 OpsChanged |= vectorizeInsertValueInst(LastInsertValue, BB, R); 8280 else if (auto *LastInsertElem = dyn_cast<InsertElementInst>(I)) 8281 OpsChanged |= vectorizeInsertElementInst(LastInsertElem, BB, R); 8282 else if (isa<CmpInst>(I)) 8283 PostponedCmps.push_back(I); 8284 } 8285 if (AtTerminator) { 8286 // Try to find reductions first. 8287 for (Instruction *I : PostponedCmps) { 8288 if (R.isDeleted(I)) 8289 continue; 8290 for (Value *Op : I->operands()) 8291 OpsChanged |= vectorizeRootInstruction(nullptr, Op, BB, R, TTI); 8292 } 8293 // Try to vectorize operands as vector bundles. 8294 for (Instruction *I : PostponedCmps) { 8295 if (R.isDeleted(I)) 8296 continue; 8297 OpsChanged |= tryToVectorize(I, R); 8298 } 8299 Instructions.clear(); 8300 } else { 8301 // Insert in reverse order since the PostponedCmps vector was filled in 8302 // reverse order. 8303 Instructions.assign(PostponedCmps.rbegin(), PostponedCmps.rend()); 8304 } 8305 return OpsChanged; 8306 } 8307 8308 bool SLPVectorizerPass::vectorizeChainsInBlock(BasicBlock *BB, BoUpSLP &R) { 8309 bool Changed = false; 8310 SmallVector<Value *, 4> Incoming; 8311 SmallPtrSet<Value *, 16> VisitedInstrs; 8312 // Maps phi nodes to the non-phi nodes found in the use tree for each phi 8313 // node. Allows better to identify the chains that can be vectorized in the 8314 // better way. 8315 DenseMap<Value *, SmallVector<Value *, 4>> PHIToOpcodes; 8316 8317 bool HaveVectorizedPhiNodes = true; 8318 while (HaveVectorizedPhiNodes) { 8319 HaveVectorizedPhiNodes = false; 8320 8321 // Collect the incoming values from the PHIs. 8322 Incoming.clear(); 8323 for (Instruction &I : *BB) { 8324 PHINode *P = dyn_cast<PHINode>(&I); 8325 if (!P) 8326 break; 8327 8328 // No need to analyze deleted, vectorized and non-vectorizable 8329 // instructions. 8330 if (!VisitedInstrs.count(P) && !R.isDeleted(P) && 8331 isValidElementType(P->getType())) 8332 Incoming.push_back(P); 8333 } 8334 8335 // Find the corresponding non-phi nodes for better matching when trying to 8336 // build the tree. 8337 for (Value *V : Incoming) { 8338 SmallVectorImpl<Value *> &Opcodes = 8339 PHIToOpcodes.try_emplace(V).first->getSecond(); 8340 if (!Opcodes.empty()) 8341 continue; 8342 SmallVector<Value *, 4> Nodes(1, V); 8343 SmallPtrSet<Value *, 4> Visited; 8344 while (!Nodes.empty()) { 8345 auto *PHI = cast<PHINode>(Nodes.pop_back_val()); 8346 if (!Visited.insert(PHI).second) 8347 continue; 8348 for (Value *V : PHI->incoming_values()) { 8349 if (auto *PHI1 = dyn_cast<PHINode>((V))) { 8350 Nodes.push_back(PHI1); 8351 continue; 8352 } 8353 Opcodes.emplace_back(V); 8354 } 8355 } 8356 } 8357 8358 // Sort by type, parent, operands. 8359 stable_sort(Incoming, [this, &PHIToOpcodes](Value *V1, Value *V2) { 8360 assert(isValidElementType(V1->getType()) && 8361 isValidElementType(V2->getType()) && 8362 "Expected vectorizable types only."); 8363 // It is fine to compare type IDs here, since we expect only vectorizable 8364 // types, like ints, floats and pointers, we don't care about other type. 8365 if (V1->getType()->getTypeID() < V2->getType()->getTypeID()) 8366 return true; 8367 if (V1->getType()->getTypeID() > V2->getType()->getTypeID()) 8368 return false; 8369 ArrayRef<Value *> Opcodes1 = PHIToOpcodes[V1]; 8370 ArrayRef<Value *> Opcodes2 = PHIToOpcodes[V2]; 8371 if (Opcodes1.size() < Opcodes2.size()) 8372 return true; 8373 if (Opcodes1.size() > Opcodes2.size()) 8374 return false; 8375 for (int I = 0, E = Opcodes1.size(); I < E; ++I) { 8376 // Undefs are compatible with any other value. 8377 if (isa<UndefValue>(Opcodes1[I]) || isa<UndefValue>(Opcodes2[I])) 8378 continue; 8379 if (auto *I1 = dyn_cast<Instruction>(Opcodes1[I])) 8380 if (auto *I2 = dyn_cast<Instruction>(Opcodes2[I])) { 8381 DomTreeNodeBase<BasicBlock> *NodeI1 = DT->getNode(I1->getParent()); 8382 DomTreeNodeBase<BasicBlock> *NodeI2 = DT->getNode(I2->getParent()); 8383 assert(NodeI1 && "Should only process reachable instructions"); 8384 assert(NodeI2 && "Should only process reachable instructions"); 8385 assert((NodeI1 == NodeI2) == 8386 (NodeI1->getDFSNumIn() == NodeI2->getDFSNumIn()) && 8387 "Different nodes should have different DFS numbers"); 8388 if (NodeI1 != NodeI2) 8389 return NodeI1->getDFSNumIn() < NodeI2->getDFSNumIn(); 8390 InstructionsState S = getSameOpcode({I1, I2}); 8391 if (S.getOpcode()) 8392 continue; 8393 return I1->getOpcode() < I2->getOpcode(); 8394 } 8395 if (isa<Constant>(Opcodes1[I]) && isa<Constant>(Opcodes2[I])) 8396 continue; 8397 if (Opcodes1[I]->getValueID() < Opcodes2[I]->getValueID()) 8398 return true; 8399 if (Opcodes1[I]->getValueID() > Opcodes2[I]->getValueID()) 8400 return false; 8401 } 8402 return false; 8403 }); 8404 8405 auto &&AreCompatiblePHIs = [&PHIToOpcodes](Value *V1, Value *V2) { 8406 if (V1 == V2) 8407 return true; 8408 if (V1->getType() != V2->getType()) 8409 return false; 8410 ArrayRef<Value *> Opcodes1 = PHIToOpcodes[V1]; 8411 ArrayRef<Value *> Opcodes2 = PHIToOpcodes[V2]; 8412 if (Opcodes1.size() != Opcodes2.size()) 8413 return false; 8414 for (int I = 0, E = Opcodes1.size(); I < E; ++I) { 8415 // Undefs are compatible with any other value. 8416 if (isa<UndefValue>(Opcodes1[I]) || isa<UndefValue>(Opcodes2[I])) 8417 continue; 8418 if (auto *I1 = dyn_cast<Instruction>(Opcodes1[I])) 8419 if (auto *I2 = dyn_cast<Instruction>(Opcodes2[I])) { 8420 if (I1->getParent() != I2->getParent()) 8421 return false; 8422 InstructionsState S = getSameOpcode({I1, I2}); 8423 if (S.getOpcode()) 8424 continue; 8425 return false; 8426 } 8427 if (isa<Constant>(Opcodes1[I]) && isa<Constant>(Opcodes2[I])) 8428 continue; 8429 if (Opcodes1[I]->getValueID() != Opcodes2[I]->getValueID()) 8430 return false; 8431 } 8432 return true; 8433 }; 8434 8435 // Try to vectorize elements base on their type. 8436 SmallVector<Value *, 4> Candidates; 8437 for (SmallVector<Value *, 4>::iterator IncIt = Incoming.begin(), 8438 E = Incoming.end(); 8439 IncIt != E;) { 8440 8441 // Look for the next elements with the same type, parent and operand 8442 // kinds. 8443 SmallVector<Value *, 4>::iterator SameTypeIt = IncIt; 8444 while (SameTypeIt != E && AreCompatiblePHIs(*SameTypeIt, *IncIt)) { 8445 VisitedInstrs.insert(*SameTypeIt); 8446 ++SameTypeIt; 8447 } 8448 8449 // Try to vectorize them. 8450 unsigned NumElts = (SameTypeIt - IncIt); 8451 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize starting at PHIs (" 8452 << NumElts << ")\n"); 8453 // The order in which the phi nodes appear in the program does not matter. 8454 // So allow tryToVectorizeList to reorder them if it is beneficial. This 8455 // is done when there are exactly two elements since tryToVectorizeList 8456 // asserts that there are only two values when AllowReorder is true. 8457 if (NumElts > 1 && tryToVectorizeList(makeArrayRef(IncIt, NumElts), R, 8458 /*AllowReorder=*/true)) { 8459 // Success start over because instructions might have been changed. 8460 HaveVectorizedPhiNodes = true; 8461 Changed = true; 8462 } else if (NumElts < 4 && 8463 (Candidates.empty() || 8464 Candidates.front()->getType() == (*IncIt)->getType())) { 8465 Candidates.append(IncIt, std::next(IncIt, NumElts)); 8466 } 8467 // Final attempt to vectorize phis with the same types. 8468 if (SameTypeIt == E || (*SameTypeIt)->getType() != (*IncIt)->getType()) { 8469 if (Candidates.size() > 1 && 8470 tryToVectorizeList(Candidates, R, /*AllowReorder=*/true)) { 8471 // Success start over because instructions might have been changed. 8472 HaveVectorizedPhiNodes = true; 8473 Changed = true; 8474 } 8475 Candidates.clear(); 8476 } 8477 8478 // Start over at the next instruction of a different type (or the end). 8479 IncIt = SameTypeIt; 8480 } 8481 } 8482 8483 VisitedInstrs.clear(); 8484 8485 SmallVector<Instruction *, 8> PostProcessInstructions; 8486 SmallDenseSet<Instruction *, 4> KeyNodes; 8487 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 8488 // Skip instructions with scalable type. The num of elements is unknown at 8489 // compile-time for scalable type. 8490 if (isa<ScalableVectorType>(it->getType())) 8491 continue; 8492 8493 // Skip instructions marked for the deletion. 8494 if (R.isDeleted(&*it)) 8495 continue; 8496 // We may go through BB multiple times so skip the one we have checked. 8497 if (!VisitedInstrs.insert(&*it).second) { 8498 if (it->use_empty() && KeyNodes.contains(&*it) && 8499 vectorizeSimpleInstructions(PostProcessInstructions, BB, R, 8500 it->isTerminator())) { 8501 // We would like to start over since some instructions are deleted 8502 // and the iterator may become invalid value. 8503 Changed = true; 8504 it = BB->begin(); 8505 e = BB->end(); 8506 } 8507 continue; 8508 } 8509 8510 if (isa<DbgInfoIntrinsic>(it)) 8511 continue; 8512 8513 // Try to vectorize reductions that use PHINodes. 8514 if (PHINode *P = dyn_cast<PHINode>(it)) { 8515 // Check that the PHI is a reduction PHI. 8516 if (P->getNumIncomingValues() == 2) { 8517 // Try to match and vectorize a horizontal reduction. 8518 if (vectorizeRootInstruction(P, getReductionValue(DT, P, BB, LI), BB, R, 8519 TTI)) { 8520 Changed = true; 8521 it = BB->begin(); 8522 e = BB->end(); 8523 continue; 8524 } 8525 } 8526 // Try to vectorize the incoming values of the PHI, to catch reductions 8527 // that feed into PHIs. 8528 for (unsigned I = 0, E = P->getNumIncomingValues(); I != E; I++) { 8529 // Skip if the incoming block is the current BB for now. Also, bypass 8530 // unreachable IR for efficiency and to avoid crashing. 8531 // TODO: Collect the skipped incoming values and try to vectorize them 8532 // after processing BB. 8533 if (BB == P->getIncomingBlock(I) || 8534 !DT->isReachableFromEntry(P->getIncomingBlock(I))) 8535 continue; 8536 8537 Changed |= vectorizeRootInstruction(nullptr, P->getIncomingValue(I), 8538 P->getIncomingBlock(I), R, TTI); 8539 } 8540 continue; 8541 } 8542 8543 // Ran into an instruction without users, like terminator, or function call 8544 // with ignored return value, store. Ignore unused instructions (basing on 8545 // instruction type, except for CallInst and InvokeInst). 8546 if (it->use_empty() && (it->getType()->isVoidTy() || isa<CallInst>(it) || 8547 isa<InvokeInst>(it))) { 8548 KeyNodes.insert(&*it); 8549 bool OpsChanged = false; 8550 if (ShouldStartVectorizeHorAtStore || !isa<StoreInst>(it)) { 8551 for (auto *V : it->operand_values()) { 8552 // Try to match and vectorize a horizontal reduction. 8553 OpsChanged |= vectorizeRootInstruction(nullptr, V, BB, R, TTI); 8554 } 8555 } 8556 // Start vectorization of post-process list of instructions from the 8557 // top-tree instructions to try to vectorize as many instructions as 8558 // possible. 8559 OpsChanged |= vectorizeSimpleInstructions(PostProcessInstructions, BB, R, 8560 it->isTerminator()); 8561 if (OpsChanged) { 8562 // We would like to start over since some instructions are deleted 8563 // and the iterator may become invalid value. 8564 Changed = true; 8565 it = BB->begin(); 8566 e = BB->end(); 8567 continue; 8568 } 8569 } 8570 8571 if (isa<InsertElementInst>(it) || isa<CmpInst>(it) || 8572 isa<InsertValueInst>(it)) 8573 PostProcessInstructions.push_back(&*it); 8574 } 8575 8576 return Changed; 8577 } 8578 8579 bool SLPVectorizerPass::vectorizeGEPIndices(BasicBlock *BB, BoUpSLP &R) { 8580 auto Changed = false; 8581 for (auto &Entry : GEPs) { 8582 // If the getelementptr list has fewer than two elements, there's nothing 8583 // to do. 8584 if (Entry.second.size() < 2) 8585 continue; 8586 8587 LLVM_DEBUG(dbgs() << "SLP: Analyzing a getelementptr list of length " 8588 << Entry.second.size() << ".\n"); 8589 8590 // Process the GEP list in chunks suitable for the target's supported 8591 // vector size. If a vector register can't hold 1 element, we are done. We 8592 // are trying to vectorize the index computations, so the maximum number of 8593 // elements is based on the size of the index expression, rather than the 8594 // size of the GEP itself (the target's pointer size). 8595 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 8596 unsigned EltSize = R.getVectorElementSize(*Entry.second[0]->idx_begin()); 8597 if (MaxVecRegSize < EltSize) 8598 continue; 8599 8600 unsigned MaxElts = MaxVecRegSize / EltSize; 8601 for (unsigned BI = 0, BE = Entry.second.size(); BI < BE; BI += MaxElts) { 8602 auto Len = std::min<unsigned>(BE - BI, MaxElts); 8603 ArrayRef<GetElementPtrInst *> GEPList(&Entry.second[BI], Len); 8604 8605 // Initialize a set a candidate getelementptrs. Note that we use a 8606 // SetVector here to preserve program order. If the index computations 8607 // are vectorizable and begin with loads, we want to minimize the chance 8608 // of having to reorder them later. 8609 SetVector<Value *> Candidates(GEPList.begin(), GEPList.end()); 8610 8611 // Some of the candidates may have already been vectorized after we 8612 // initially collected them. If so, they are marked as deleted, so remove 8613 // them from the set of candidates. 8614 Candidates.remove_if( 8615 [&R](Value *I) { return R.isDeleted(cast<Instruction>(I)); }); 8616 8617 // Remove from the set of candidates all pairs of getelementptrs with 8618 // constant differences. Such getelementptrs are likely not good 8619 // candidates for vectorization in a bottom-up phase since one can be 8620 // computed from the other. We also ensure all candidate getelementptr 8621 // indices are unique. 8622 for (int I = 0, E = GEPList.size(); I < E && Candidates.size() > 1; ++I) { 8623 auto *GEPI = GEPList[I]; 8624 if (!Candidates.count(GEPI)) 8625 continue; 8626 auto *SCEVI = SE->getSCEV(GEPList[I]); 8627 for (int J = I + 1; J < E && Candidates.size() > 1; ++J) { 8628 auto *GEPJ = GEPList[J]; 8629 auto *SCEVJ = SE->getSCEV(GEPList[J]); 8630 if (isa<SCEVConstant>(SE->getMinusSCEV(SCEVI, SCEVJ))) { 8631 Candidates.remove(GEPI); 8632 Candidates.remove(GEPJ); 8633 } else if (GEPI->idx_begin()->get() == GEPJ->idx_begin()->get()) { 8634 Candidates.remove(GEPJ); 8635 } 8636 } 8637 } 8638 8639 // We break out of the above computation as soon as we know there are 8640 // fewer than two candidates remaining. 8641 if (Candidates.size() < 2) 8642 continue; 8643 8644 // Add the single, non-constant index of each candidate to the bundle. We 8645 // ensured the indices met these constraints when we originally collected 8646 // the getelementptrs. 8647 SmallVector<Value *, 16> Bundle(Candidates.size()); 8648 auto BundleIndex = 0u; 8649 for (auto *V : Candidates) { 8650 auto *GEP = cast<GetElementPtrInst>(V); 8651 auto *GEPIdx = GEP->idx_begin()->get(); 8652 assert(GEP->getNumIndices() == 1 || !isa<Constant>(GEPIdx)); 8653 Bundle[BundleIndex++] = GEPIdx; 8654 } 8655 8656 // Try and vectorize the indices. We are currently only interested in 8657 // gather-like cases of the form: 8658 // 8659 // ... = g[a[0] - b[0]] + g[a[1] - b[1]] + ... 8660 // 8661 // where the loads of "a", the loads of "b", and the subtractions can be 8662 // performed in parallel. It's likely that detecting this pattern in a 8663 // bottom-up phase will be simpler and less costly than building a 8664 // full-blown top-down phase beginning at the consecutive loads. 8665 Changed |= tryToVectorizeList(Bundle, R); 8666 } 8667 } 8668 return Changed; 8669 } 8670 8671 bool SLPVectorizerPass::vectorizeStoreChains(BoUpSLP &R) { 8672 bool Changed = false; 8673 // Sort by type, base pointers and values operand. Value operands must be 8674 // compatible (have the same opcode, same parent), otherwise it is 8675 // definitely not profitable to try to vectorize them. 8676 auto &&StoreSorter = [this](StoreInst *V, StoreInst *V2) { 8677 if (V->getPointerOperandType()->getTypeID() < 8678 V2->getPointerOperandType()->getTypeID()) 8679 return true; 8680 if (V->getPointerOperandType()->getTypeID() > 8681 V2->getPointerOperandType()->getTypeID()) 8682 return false; 8683 // UndefValues are compatible with all other values. 8684 if (isa<UndefValue>(V->getValueOperand()) || 8685 isa<UndefValue>(V2->getValueOperand())) 8686 return false; 8687 if (auto *I1 = dyn_cast<Instruction>(V->getValueOperand())) 8688 if (auto *I2 = dyn_cast<Instruction>(V2->getValueOperand())) { 8689 DomTreeNodeBase<llvm::BasicBlock> *NodeI1 = 8690 DT->getNode(I1->getParent()); 8691 DomTreeNodeBase<llvm::BasicBlock> *NodeI2 = 8692 DT->getNode(I2->getParent()); 8693 assert(NodeI1 && "Should only process reachable instructions"); 8694 assert(NodeI1 && "Should only process reachable instructions"); 8695 assert((NodeI1 == NodeI2) == 8696 (NodeI1->getDFSNumIn() == NodeI2->getDFSNumIn()) && 8697 "Different nodes should have different DFS numbers"); 8698 if (NodeI1 != NodeI2) 8699 return NodeI1->getDFSNumIn() < NodeI2->getDFSNumIn(); 8700 InstructionsState S = getSameOpcode({I1, I2}); 8701 if (S.getOpcode()) 8702 return false; 8703 return I1->getOpcode() < I2->getOpcode(); 8704 } 8705 if (isa<Constant>(V->getValueOperand()) && 8706 isa<Constant>(V2->getValueOperand())) 8707 return false; 8708 return V->getValueOperand()->getValueID() < 8709 V2->getValueOperand()->getValueID(); 8710 }; 8711 8712 auto &&AreCompatibleStores = [](StoreInst *V1, StoreInst *V2) { 8713 if (V1 == V2) 8714 return true; 8715 if (V1->getPointerOperandType() != V2->getPointerOperandType()) 8716 return false; 8717 // Undefs are compatible with any other value. 8718 if (isa<UndefValue>(V1->getValueOperand()) || 8719 isa<UndefValue>(V2->getValueOperand())) 8720 return true; 8721 if (auto *I1 = dyn_cast<Instruction>(V1->getValueOperand())) 8722 if (auto *I2 = dyn_cast<Instruction>(V2->getValueOperand())) { 8723 if (I1->getParent() != I2->getParent()) 8724 return false; 8725 InstructionsState S = getSameOpcode({I1, I2}); 8726 return S.getOpcode() > 0; 8727 } 8728 if (isa<Constant>(V1->getValueOperand()) && 8729 isa<Constant>(V2->getValueOperand())) 8730 return true; 8731 return V1->getValueOperand()->getValueID() == 8732 V2->getValueOperand()->getValueID(); 8733 }; 8734 8735 // Attempt to sort and vectorize each of the store-groups. 8736 for (auto &Pair : Stores) { 8737 if (Pair.second.size() < 2) 8738 continue; 8739 8740 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " 8741 << Pair.second.size() << ".\n"); 8742 8743 stable_sort(Pair.second, StoreSorter); 8744 8745 // Try to vectorize elements based on their compatibility. 8746 for (ArrayRef<StoreInst *>::iterator IncIt = Pair.second.begin(), 8747 E = Pair.second.end(); 8748 IncIt != E;) { 8749 8750 // Look for the next elements with the same type. 8751 ArrayRef<StoreInst *>::iterator SameTypeIt = IncIt; 8752 Type *EltTy = (*IncIt)->getPointerOperand()->getType(); 8753 8754 while (SameTypeIt != E && AreCompatibleStores(*SameTypeIt, *IncIt)) 8755 ++SameTypeIt; 8756 8757 // Try to vectorize them. 8758 unsigned NumElts = (SameTypeIt - IncIt); 8759 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize starting at stores (" 8760 << NumElts << ")\n"); 8761 if (NumElts > 1 && !EltTy->getPointerElementType()->isVectorTy() && 8762 vectorizeStores(makeArrayRef(IncIt, NumElts), R)) { 8763 // Success start over because instructions might have been changed. 8764 Changed = true; 8765 } 8766 8767 // Start over at the next instruction of a different type (or the end). 8768 IncIt = SameTypeIt; 8769 } 8770 } 8771 return Changed; 8772 } 8773 8774 char SLPVectorizer::ID = 0; 8775 8776 static const char lv_name[] = "SLP Vectorizer"; 8777 8778 INITIALIZE_PASS_BEGIN(SLPVectorizer, SV_NAME, lv_name, false, false) 8779 INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass) 8780 INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass) 8781 INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker) 8782 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass) 8783 INITIALIZE_PASS_DEPENDENCY(LoopSimplify) 8784 INITIALIZE_PASS_DEPENDENCY(DemandedBitsWrapperPass) 8785 INITIALIZE_PASS_DEPENDENCY(OptimizationRemarkEmitterWrapperPass) 8786 INITIALIZE_PASS_DEPENDENCY(InjectTLIMappingsLegacy) 8787 INITIALIZE_PASS_END(SLPVectorizer, SV_NAME, lv_name, false, false) 8788 8789 Pass *llvm::createSLPVectorizerPass() { return new SLPVectorizer(); } 8790