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 1772 #ifndef NDEBUG 1773 /// Debug printer. 1774 LLVM_DUMP_METHOD void dump() const { 1775 dbgs() << Idx << ".\n"; 1776 for (unsigned OpI = 0, OpE = Operands.size(); OpI != OpE; ++OpI) { 1777 dbgs() << "Operand " << OpI << ":\n"; 1778 for (const Value *V : Operands[OpI]) 1779 dbgs().indent(2) << *V << "\n"; 1780 } 1781 dbgs() << "Scalars: \n"; 1782 for (Value *V : Scalars) 1783 dbgs().indent(2) << *V << "\n"; 1784 dbgs() << "State: "; 1785 switch (State) { 1786 case Vectorize: 1787 dbgs() << "Vectorize\n"; 1788 break; 1789 case ScatterVectorize: 1790 dbgs() << "ScatterVectorize\n"; 1791 break; 1792 case NeedToGather: 1793 dbgs() << "NeedToGather\n"; 1794 break; 1795 } 1796 dbgs() << "MainOp: "; 1797 if (MainOp) 1798 dbgs() << *MainOp << "\n"; 1799 else 1800 dbgs() << "NULL\n"; 1801 dbgs() << "AltOp: "; 1802 if (AltOp) 1803 dbgs() << *AltOp << "\n"; 1804 else 1805 dbgs() << "NULL\n"; 1806 dbgs() << "VectorizedValue: "; 1807 if (VectorizedValue) 1808 dbgs() << *VectorizedValue << "\n"; 1809 else 1810 dbgs() << "NULL\n"; 1811 dbgs() << "ReuseShuffleIndices: "; 1812 if (ReuseShuffleIndices.empty()) 1813 dbgs() << "Empty"; 1814 else 1815 for (unsigned ReuseIdx : ReuseShuffleIndices) 1816 dbgs() << ReuseIdx << ", "; 1817 dbgs() << "\n"; 1818 dbgs() << "ReorderIndices: "; 1819 for (unsigned ReorderIdx : ReorderIndices) 1820 dbgs() << ReorderIdx << ", "; 1821 dbgs() << "\n"; 1822 dbgs() << "UserTreeIndices: "; 1823 for (const auto &EInfo : UserTreeIndices) 1824 dbgs() << EInfo << ", "; 1825 dbgs() << "\n"; 1826 } 1827 #endif 1828 }; 1829 1830 #ifndef NDEBUG 1831 void dumpTreeCosts(const TreeEntry *E, InstructionCost ReuseShuffleCost, 1832 InstructionCost VecCost, 1833 InstructionCost ScalarCost) const { 1834 dbgs() << "SLP: Calculated costs for Tree:\n"; E->dump(); 1835 dbgs() << "SLP: Costs:\n"; 1836 dbgs() << "SLP: ReuseShuffleCost = " << ReuseShuffleCost << "\n"; 1837 dbgs() << "SLP: VectorCost = " << VecCost << "\n"; 1838 dbgs() << "SLP: ScalarCost = " << ScalarCost << "\n"; 1839 dbgs() << "SLP: ReuseShuffleCost + VecCost - ScalarCost = " << 1840 ReuseShuffleCost + VecCost - ScalarCost << "\n"; 1841 } 1842 #endif 1843 1844 /// Create a new VectorizableTree entry. 1845 TreeEntry *newTreeEntry(ArrayRef<Value *> VL, Optional<ScheduleData *> Bundle, 1846 const InstructionsState &S, 1847 const EdgeInfo &UserTreeIdx, 1848 ArrayRef<unsigned> ReuseShuffleIndices = None, 1849 ArrayRef<unsigned> ReorderIndices = None) { 1850 TreeEntry::EntryState EntryState = 1851 Bundle ? TreeEntry::Vectorize : TreeEntry::NeedToGather; 1852 return newTreeEntry(VL, EntryState, Bundle, S, UserTreeIdx, 1853 ReuseShuffleIndices, ReorderIndices); 1854 } 1855 1856 TreeEntry *newTreeEntry(ArrayRef<Value *> VL, 1857 TreeEntry::EntryState EntryState, 1858 Optional<ScheduleData *> Bundle, 1859 const InstructionsState &S, 1860 const EdgeInfo &UserTreeIdx, 1861 ArrayRef<unsigned> ReuseShuffleIndices = None, 1862 ArrayRef<unsigned> ReorderIndices = None) { 1863 assert(((!Bundle && EntryState == TreeEntry::NeedToGather) || 1864 (Bundle && EntryState != TreeEntry::NeedToGather)) && 1865 "Need to vectorize gather entry?"); 1866 VectorizableTree.push_back(std::make_unique<TreeEntry>(VectorizableTree)); 1867 TreeEntry *Last = VectorizableTree.back().get(); 1868 Last->Idx = VectorizableTree.size() - 1; 1869 Last->Scalars.insert(Last->Scalars.begin(), VL.begin(), VL.end()); 1870 Last->State = EntryState; 1871 Last->ReuseShuffleIndices.append(ReuseShuffleIndices.begin(), 1872 ReuseShuffleIndices.end()); 1873 Last->ReorderIndices.append(ReorderIndices.begin(), ReorderIndices.end()); 1874 Last->setOperations(S); 1875 if (Last->State != TreeEntry::NeedToGather) { 1876 for (Value *V : VL) { 1877 assert(!getTreeEntry(V) && "Scalar already in tree!"); 1878 ScalarToTreeEntry[V] = Last; 1879 } 1880 // Update the scheduler bundle to point to this TreeEntry. 1881 unsigned Lane = 0; 1882 for (ScheduleData *BundleMember = Bundle.getValue(); BundleMember; 1883 BundleMember = BundleMember->NextInBundle) { 1884 BundleMember->TE = Last; 1885 BundleMember->Lane = Lane; 1886 ++Lane; 1887 } 1888 assert((!Bundle.getValue() || Lane == VL.size()) && 1889 "Bundle and VL out of sync"); 1890 } else { 1891 MustGather.insert(VL.begin(), VL.end()); 1892 } 1893 1894 if (UserTreeIdx.UserTE) 1895 Last->UserTreeIndices.push_back(UserTreeIdx); 1896 1897 return Last; 1898 } 1899 1900 /// -- Vectorization State -- 1901 /// Holds all of the tree entries. 1902 TreeEntry::VecTreeTy VectorizableTree; 1903 1904 #ifndef NDEBUG 1905 /// Debug printer. 1906 LLVM_DUMP_METHOD void dumpVectorizableTree() const { 1907 for (unsigned Id = 0, IdE = VectorizableTree.size(); Id != IdE; ++Id) { 1908 VectorizableTree[Id]->dump(); 1909 dbgs() << "\n"; 1910 } 1911 } 1912 #endif 1913 1914 TreeEntry *getTreeEntry(Value *V) { return ScalarToTreeEntry.lookup(V); } 1915 1916 const TreeEntry *getTreeEntry(Value *V) const { 1917 return ScalarToTreeEntry.lookup(V); 1918 } 1919 1920 /// Maps a specific scalar to its tree entry. 1921 SmallDenseMap<Value*, TreeEntry *> ScalarToTreeEntry; 1922 1923 /// Maps a value to the proposed vectorizable size. 1924 SmallDenseMap<Value *, unsigned> InstrElementSize; 1925 1926 /// A list of scalars that we found that we need to keep as scalars. 1927 ValueSet MustGather; 1928 1929 /// This POD struct describes one external user in the vectorized tree. 1930 struct ExternalUser { 1931 ExternalUser(Value *S, llvm::User *U, int L) 1932 : Scalar(S), User(U), Lane(L) {} 1933 1934 // Which scalar in our function. 1935 Value *Scalar; 1936 1937 // Which user that uses the scalar. 1938 llvm::User *User; 1939 1940 // Which lane does the scalar belong to. 1941 int Lane; 1942 }; 1943 using UserList = SmallVector<ExternalUser, 16>; 1944 1945 /// Checks if two instructions may access the same memory. 1946 /// 1947 /// \p Loc1 is the location of \p Inst1. It is passed explicitly because it 1948 /// is invariant in the calling loop. 1949 bool isAliased(const MemoryLocation &Loc1, Instruction *Inst1, 1950 Instruction *Inst2) { 1951 // First check if the result is already in the cache. 1952 AliasCacheKey key = std::make_pair(Inst1, Inst2); 1953 Optional<bool> &result = AliasCache[key]; 1954 if (result.hasValue()) { 1955 return result.getValue(); 1956 } 1957 MemoryLocation Loc2 = getLocation(Inst2, AA); 1958 bool aliased = true; 1959 if (Loc1.Ptr && Loc2.Ptr && isSimple(Inst1) && isSimple(Inst2)) { 1960 // Do the alias check. 1961 aliased = !AA->isNoAlias(Loc1, Loc2); 1962 } 1963 // Store the result in the cache. 1964 result = aliased; 1965 return aliased; 1966 } 1967 1968 using AliasCacheKey = std::pair<Instruction *, Instruction *>; 1969 1970 /// Cache for alias results. 1971 /// TODO: consider moving this to the AliasAnalysis itself. 1972 DenseMap<AliasCacheKey, Optional<bool>> AliasCache; 1973 1974 /// Removes an instruction from its block and eventually deletes it. 1975 /// It's like Instruction::eraseFromParent() except that the actual deletion 1976 /// is delayed until BoUpSLP is destructed. 1977 /// This is required to ensure that there are no incorrect collisions in the 1978 /// AliasCache, which can happen if a new instruction is allocated at the 1979 /// same address as a previously deleted instruction. 1980 void eraseInstruction(Instruction *I, bool ReplaceOpsWithUndef = false) { 1981 auto It = DeletedInstructions.try_emplace(I, ReplaceOpsWithUndef).first; 1982 It->getSecond() = It->getSecond() && ReplaceOpsWithUndef; 1983 } 1984 1985 /// Temporary store for deleted instructions. Instructions will be deleted 1986 /// eventually when the BoUpSLP is destructed. 1987 DenseMap<Instruction *, bool> DeletedInstructions; 1988 1989 /// A list of values that need to extracted out of the tree. 1990 /// This list holds pairs of (Internal Scalar : External User). External User 1991 /// can be nullptr, it means that this Internal Scalar will be used later, 1992 /// after vectorization. 1993 UserList ExternalUses; 1994 1995 /// Values used only by @llvm.assume calls. 1996 SmallPtrSet<const Value *, 32> EphValues; 1997 1998 /// Holds all of the instructions that we gathered. 1999 SetVector<Instruction *> GatherSeq; 2000 2001 /// A list of blocks that we are going to CSE. 2002 SetVector<BasicBlock *> CSEBlocks; 2003 2004 /// Contains all scheduling relevant data for an instruction. 2005 /// A ScheduleData either represents a single instruction or a member of an 2006 /// instruction bundle (= a group of instructions which is combined into a 2007 /// vector instruction). 2008 struct ScheduleData { 2009 // The initial value for the dependency counters. It means that the 2010 // dependencies are not calculated yet. 2011 enum { InvalidDeps = -1 }; 2012 2013 ScheduleData() = default; 2014 2015 void init(int BlockSchedulingRegionID, Value *OpVal) { 2016 FirstInBundle = this; 2017 NextInBundle = nullptr; 2018 NextLoadStore = nullptr; 2019 IsScheduled = false; 2020 SchedulingRegionID = BlockSchedulingRegionID; 2021 UnscheduledDepsInBundle = UnscheduledDeps; 2022 clearDependencies(); 2023 OpValue = OpVal; 2024 TE = nullptr; 2025 Lane = -1; 2026 } 2027 2028 /// Returns true if the dependency information has been calculated. 2029 bool hasValidDependencies() const { return Dependencies != InvalidDeps; } 2030 2031 /// Returns true for single instructions and for bundle representatives 2032 /// (= the head of a bundle). 2033 bool isSchedulingEntity() const { return FirstInBundle == this; } 2034 2035 /// Returns true if it represents an instruction bundle and not only a 2036 /// single instruction. 2037 bool isPartOfBundle() const { 2038 return NextInBundle != nullptr || FirstInBundle != this; 2039 } 2040 2041 /// Returns true if it is ready for scheduling, i.e. it has no more 2042 /// unscheduled depending instructions/bundles. 2043 bool isReady() const { 2044 assert(isSchedulingEntity() && 2045 "can't consider non-scheduling entity for ready list"); 2046 return UnscheduledDepsInBundle == 0 && !IsScheduled; 2047 } 2048 2049 /// Modifies the number of unscheduled dependencies, also updating it for 2050 /// the whole bundle. 2051 int incrementUnscheduledDeps(int Incr) { 2052 UnscheduledDeps += Incr; 2053 return FirstInBundle->UnscheduledDepsInBundle += Incr; 2054 } 2055 2056 /// Sets the number of unscheduled dependencies to the number of 2057 /// dependencies. 2058 void resetUnscheduledDeps() { 2059 incrementUnscheduledDeps(Dependencies - UnscheduledDeps); 2060 } 2061 2062 /// Clears all dependency information. 2063 void clearDependencies() { 2064 Dependencies = InvalidDeps; 2065 resetUnscheduledDeps(); 2066 MemoryDependencies.clear(); 2067 } 2068 2069 void dump(raw_ostream &os) const { 2070 if (!isSchedulingEntity()) { 2071 os << "/ " << *Inst; 2072 } else if (NextInBundle) { 2073 os << '[' << *Inst; 2074 ScheduleData *SD = NextInBundle; 2075 while (SD) { 2076 os << ';' << *SD->Inst; 2077 SD = SD->NextInBundle; 2078 } 2079 os << ']'; 2080 } else { 2081 os << *Inst; 2082 } 2083 } 2084 2085 Instruction *Inst = nullptr; 2086 2087 /// Points to the head in an instruction bundle (and always to this for 2088 /// single instructions). 2089 ScheduleData *FirstInBundle = nullptr; 2090 2091 /// Single linked list of all instructions in a bundle. Null if it is a 2092 /// single instruction. 2093 ScheduleData *NextInBundle = nullptr; 2094 2095 /// Single linked list of all memory instructions (e.g. load, store, call) 2096 /// in the block - until the end of the scheduling region. 2097 ScheduleData *NextLoadStore = nullptr; 2098 2099 /// The dependent memory instructions. 2100 /// This list is derived on demand in calculateDependencies(). 2101 SmallVector<ScheduleData *, 4> MemoryDependencies; 2102 2103 /// This ScheduleData is in the current scheduling region if this matches 2104 /// the current SchedulingRegionID of BlockScheduling. 2105 int SchedulingRegionID = 0; 2106 2107 /// Used for getting a "good" final ordering of instructions. 2108 int SchedulingPriority = 0; 2109 2110 /// The number of dependencies. Constitutes of the number of users of the 2111 /// instruction plus the number of dependent memory instructions (if any). 2112 /// This value is calculated on demand. 2113 /// If InvalidDeps, the number of dependencies is not calculated yet. 2114 int Dependencies = InvalidDeps; 2115 2116 /// The number of dependencies minus the number of dependencies of scheduled 2117 /// instructions. As soon as this is zero, the instruction/bundle gets ready 2118 /// for scheduling. 2119 /// Note that this is negative as long as Dependencies is not calculated. 2120 int UnscheduledDeps = InvalidDeps; 2121 2122 /// The sum of UnscheduledDeps in a bundle. Equals to UnscheduledDeps for 2123 /// single instructions. 2124 int UnscheduledDepsInBundle = InvalidDeps; 2125 2126 /// True if this instruction is scheduled (or considered as scheduled in the 2127 /// dry-run). 2128 bool IsScheduled = false; 2129 2130 /// Opcode of the current instruction in the schedule data. 2131 Value *OpValue = nullptr; 2132 2133 /// The TreeEntry that this instruction corresponds to. 2134 TreeEntry *TE = nullptr; 2135 2136 /// The lane of this node in the TreeEntry. 2137 int Lane = -1; 2138 }; 2139 2140 #ifndef NDEBUG 2141 friend inline raw_ostream &operator<<(raw_ostream &os, 2142 const BoUpSLP::ScheduleData &SD) { 2143 SD.dump(os); 2144 return os; 2145 } 2146 #endif 2147 2148 friend struct GraphTraits<BoUpSLP *>; 2149 friend struct DOTGraphTraits<BoUpSLP *>; 2150 2151 /// Contains all scheduling data for a basic block. 2152 struct BlockScheduling { 2153 BlockScheduling(BasicBlock *BB) 2154 : BB(BB), ChunkSize(BB->size()), ChunkPos(ChunkSize) {} 2155 2156 void clear() { 2157 ReadyInsts.clear(); 2158 ScheduleStart = nullptr; 2159 ScheduleEnd = nullptr; 2160 FirstLoadStoreInRegion = nullptr; 2161 LastLoadStoreInRegion = nullptr; 2162 2163 // Reduce the maximum schedule region size by the size of the 2164 // previous scheduling run. 2165 ScheduleRegionSizeLimit -= ScheduleRegionSize; 2166 if (ScheduleRegionSizeLimit < MinScheduleRegionSize) 2167 ScheduleRegionSizeLimit = MinScheduleRegionSize; 2168 ScheduleRegionSize = 0; 2169 2170 // Make a new scheduling region, i.e. all existing ScheduleData is not 2171 // in the new region yet. 2172 ++SchedulingRegionID; 2173 } 2174 2175 ScheduleData *getScheduleData(Value *V) { 2176 ScheduleData *SD = ScheduleDataMap[V]; 2177 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 2178 return SD; 2179 return nullptr; 2180 } 2181 2182 ScheduleData *getScheduleData(Value *V, Value *Key) { 2183 if (V == Key) 2184 return getScheduleData(V); 2185 auto I = ExtraScheduleDataMap.find(V); 2186 if (I != ExtraScheduleDataMap.end()) { 2187 ScheduleData *SD = I->second[Key]; 2188 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 2189 return SD; 2190 } 2191 return nullptr; 2192 } 2193 2194 bool isInSchedulingRegion(ScheduleData *SD) const { 2195 return SD->SchedulingRegionID == SchedulingRegionID; 2196 } 2197 2198 /// Marks an instruction as scheduled and puts all dependent ready 2199 /// instructions into the ready-list. 2200 template <typename ReadyListType> 2201 void schedule(ScheduleData *SD, ReadyListType &ReadyList) { 2202 SD->IsScheduled = true; 2203 LLVM_DEBUG(dbgs() << "SLP: schedule " << *SD << "\n"); 2204 2205 ScheduleData *BundleMember = SD; 2206 while (BundleMember) { 2207 if (BundleMember->Inst != BundleMember->OpValue) { 2208 BundleMember = BundleMember->NextInBundle; 2209 continue; 2210 } 2211 // Handle the def-use chain dependencies. 2212 2213 // Decrement the unscheduled counter and insert to ready list if ready. 2214 auto &&DecrUnsched = [this, &ReadyList](Instruction *I) { 2215 doForAllOpcodes(I, [&ReadyList](ScheduleData *OpDef) { 2216 if (OpDef && OpDef->hasValidDependencies() && 2217 OpDef->incrementUnscheduledDeps(-1) == 0) { 2218 // There are no more unscheduled dependencies after 2219 // decrementing, so we can put the dependent instruction 2220 // into the ready list. 2221 ScheduleData *DepBundle = OpDef->FirstInBundle; 2222 assert(!DepBundle->IsScheduled && 2223 "already scheduled bundle gets ready"); 2224 ReadyList.insert(DepBundle); 2225 LLVM_DEBUG(dbgs() 2226 << "SLP: gets ready (def): " << *DepBundle << "\n"); 2227 } 2228 }); 2229 }; 2230 2231 // If BundleMember is a vector bundle, its operands may have been 2232 // reordered duiring buildTree(). We therefore need to get its operands 2233 // through the TreeEntry. 2234 if (TreeEntry *TE = BundleMember->TE) { 2235 int Lane = BundleMember->Lane; 2236 assert(Lane >= 0 && "Lane not set"); 2237 2238 // Since vectorization tree is being built recursively this assertion 2239 // ensures that the tree entry has all operands set before reaching 2240 // this code. Couple of exceptions known at the moment are extracts 2241 // where their second (immediate) operand is not added. Since 2242 // immediates do not affect scheduler behavior this is considered 2243 // okay. 2244 auto *In = TE->getMainOp(); 2245 assert(In && 2246 (isa<ExtractValueInst>(In) || isa<ExtractElementInst>(In) || 2247 In->getNumOperands() == TE->getNumOperands()) && 2248 "Missed TreeEntry operands?"); 2249 (void)In; // fake use to avoid build failure when assertions disabled 2250 2251 for (unsigned OpIdx = 0, NumOperands = TE->getNumOperands(); 2252 OpIdx != NumOperands; ++OpIdx) 2253 if (auto *I = dyn_cast<Instruction>(TE->getOperand(OpIdx)[Lane])) 2254 DecrUnsched(I); 2255 } else { 2256 // If BundleMember is a stand-alone instruction, no operand reordering 2257 // has taken place, so we directly access its operands. 2258 for (Use &U : BundleMember->Inst->operands()) 2259 if (auto *I = dyn_cast<Instruction>(U.get())) 2260 DecrUnsched(I); 2261 } 2262 // Handle the memory dependencies. 2263 for (ScheduleData *MemoryDepSD : BundleMember->MemoryDependencies) { 2264 if (MemoryDepSD->incrementUnscheduledDeps(-1) == 0) { 2265 // There are no more unscheduled dependencies after decrementing, 2266 // so we can put the dependent instruction into the ready list. 2267 ScheduleData *DepBundle = MemoryDepSD->FirstInBundle; 2268 assert(!DepBundle->IsScheduled && 2269 "already scheduled bundle gets ready"); 2270 ReadyList.insert(DepBundle); 2271 LLVM_DEBUG(dbgs() 2272 << "SLP: gets ready (mem): " << *DepBundle << "\n"); 2273 } 2274 } 2275 BundleMember = BundleMember->NextInBundle; 2276 } 2277 } 2278 2279 void doForAllOpcodes(Value *V, 2280 function_ref<void(ScheduleData *SD)> Action) { 2281 if (ScheduleData *SD = getScheduleData(V)) 2282 Action(SD); 2283 auto I = ExtraScheduleDataMap.find(V); 2284 if (I != ExtraScheduleDataMap.end()) 2285 for (auto &P : I->second) 2286 if (P.second->SchedulingRegionID == SchedulingRegionID) 2287 Action(P.second); 2288 } 2289 2290 /// Put all instructions into the ReadyList which are ready for scheduling. 2291 template <typename ReadyListType> 2292 void initialFillReadyList(ReadyListType &ReadyList) { 2293 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 2294 doForAllOpcodes(I, [&](ScheduleData *SD) { 2295 if (SD->isSchedulingEntity() && SD->isReady()) { 2296 ReadyList.insert(SD); 2297 LLVM_DEBUG(dbgs() 2298 << "SLP: initially in ready list: " << *I << "\n"); 2299 } 2300 }); 2301 } 2302 } 2303 2304 /// Checks if a bundle of instructions can be scheduled, i.e. has no 2305 /// cyclic dependencies. This is only a dry-run, no instructions are 2306 /// actually moved at this stage. 2307 /// \returns the scheduling bundle. The returned Optional value is non-None 2308 /// if \p VL is allowed to be scheduled. 2309 Optional<ScheduleData *> 2310 tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 2311 const InstructionsState &S); 2312 2313 /// Un-bundles a group of instructions. 2314 void cancelScheduling(ArrayRef<Value *> VL, Value *OpValue); 2315 2316 /// Allocates schedule data chunk. 2317 ScheduleData *allocateScheduleDataChunks(); 2318 2319 /// Extends the scheduling region so that V is inside the region. 2320 /// \returns true if the region size is within the limit. 2321 bool extendSchedulingRegion(Value *V, const InstructionsState &S); 2322 2323 /// Initialize the ScheduleData structures for new instructions in the 2324 /// scheduling region. 2325 void initScheduleData(Instruction *FromI, Instruction *ToI, 2326 ScheduleData *PrevLoadStore, 2327 ScheduleData *NextLoadStore); 2328 2329 /// Updates the dependency information of a bundle and of all instructions/ 2330 /// bundles which depend on the original bundle. 2331 void calculateDependencies(ScheduleData *SD, bool InsertInReadyList, 2332 BoUpSLP *SLP); 2333 2334 /// Sets all instruction in the scheduling region to un-scheduled. 2335 void resetSchedule(); 2336 2337 BasicBlock *BB; 2338 2339 /// Simple memory allocation for ScheduleData. 2340 std::vector<std::unique_ptr<ScheduleData[]>> ScheduleDataChunks; 2341 2342 /// The size of a ScheduleData array in ScheduleDataChunks. 2343 int ChunkSize; 2344 2345 /// The allocator position in the current chunk, which is the last entry 2346 /// of ScheduleDataChunks. 2347 int ChunkPos; 2348 2349 /// Attaches ScheduleData to Instruction. 2350 /// Note that the mapping survives during all vectorization iterations, i.e. 2351 /// ScheduleData structures are recycled. 2352 DenseMap<Value *, ScheduleData *> ScheduleDataMap; 2353 2354 /// Attaches ScheduleData to Instruction with the leading key. 2355 DenseMap<Value *, SmallDenseMap<Value *, ScheduleData *>> 2356 ExtraScheduleDataMap; 2357 2358 struct ReadyList : SmallVector<ScheduleData *, 8> { 2359 void insert(ScheduleData *SD) { push_back(SD); } 2360 }; 2361 2362 /// The ready-list for scheduling (only used for the dry-run). 2363 ReadyList ReadyInsts; 2364 2365 /// The first instruction of the scheduling region. 2366 Instruction *ScheduleStart = nullptr; 2367 2368 /// The first instruction _after_ the scheduling region. 2369 Instruction *ScheduleEnd = nullptr; 2370 2371 /// The first memory accessing instruction in the scheduling region 2372 /// (can be null). 2373 ScheduleData *FirstLoadStoreInRegion = nullptr; 2374 2375 /// The last memory accessing instruction in the scheduling region 2376 /// (can be null). 2377 ScheduleData *LastLoadStoreInRegion = nullptr; 2378 2379 /// The current size of the scheduling region. 2380 int ScheduleRegionSize = 0; 2381 2382 /// The maximum size allowed for the scheduling region. 2383 int ScheduleRegionSizeLimit = ScheduleRegionSizeBudget; 2384 2385 /// The ID of the scheduling region. For a new vectorization iteration this 2386 /// is incremented which "removes" all ScheduleData from the region. 2387 // Make sure that the initial SchedulingRegionID is greater than the 2388 // initial SchedulingRegionID in ScheduleData (which is 0). 2389 int SchedulingRegionID = 1; 2390 }; 2391 2392 /// Attaches the BlockScheduling structures to basic blocks. 2393 MapVector<BasicBlock *, std::unique_ptr<BlockScheduling>> BlocksSchedules; 2394 2395 /// Performs the "real" scheduling. Done before vectorization is actually 2396 /// performed in a basic block. 2397 void scheduleBlock(BlockScheduling *BS); 2398 2399 /// List of users to ignore during scheduling and that don't need extracting. 2400 ArrayRef<Value *> UserIgnoreList; 2401 2402 /// A DenseMapInfo implementation for holding DenseMaps and DenseSets of 2403 /// sorted SmallVectors of unsigned. 2404 struct OrdersTypeDenseMapInfo { 2405 static OrdersType getEmptyKey() { 2406 OrdersType V; 2407 V.push_back(~1U); 2408 return V; 2409 } 2410 2411 static OrdersType getTombstoneKey() { 2412 OrdersType V; 2413 V.push_back(~2U); 2414 return V; 2415 } 2416 2417 static unsigned getHashValue(const OrdersType &V) { 2418 return static_cast<unsigned>(hash_combine_range(V.begin(), V.end())); 2419 } 2420 2421 static bool isEqual(const OrdersType &LHS, const OrdersType &RHS) { 2422 return LHS == RHS; 2423 } 2424 }; 2425 2426 /// Contains orders of operations along with the number of bundles that have 2427 /// operations in this order. It stores only those orders that require 2428 /// reordering, if reordering is not required it is counted using \a 2429 /// NumOpsWantToKeepOriginalOrder. 2430 DenseMap<OrdersType, unsigned, OrdersTypeDenseMapInfo> NumOpsWantToKeepOrder; 2431 /// Number of bundles that do not require reordering. 2432 unsigned NumOpsWantToKeepOriginalOrder = 0; 2433 2434 // Analysis and block reference. 2435 Function *F; 2436 ScalarEvolution *SE; 2437 TargetTransformInfo *TTI; 2438 TargetLibraryInfo *TLI; 2439 AAResults *AA; 2440 LoopInfo *LI; 2441 DominatorTree *DT; 2442 AssumptionCache *AC; 2443 DemandedBits *DB; 2444 const DataLayout *DL; 2445 OptimizationRemarkEmitter *ORE; 2446 2447 unsigned MaxVecRegSize; // This is set by TTI or overridden by cl::opt. 2448 unsigned MinVecRegSize; // Set by cl::opt (default: 128). 2449 2450 /// Instruction builder to construct the vectorized tree. 2451 IRBuilder<> Builder; 2452 2453 /// A map of scalar integer values to the smallest bit width with which they 2454 /// can legally be represented. The values map to (width, signed) pairs, 2455 /// where "width" indicates the minimum bit width and "signed" is True if the 2456 /// value must be signed-extended, rather than zero-extended, back to its 2457 /// original width. 2458 MapVector<Value *, std::pair<uint64_t, bool>> MinBWs; 2459 }; 2460 2461 } // end namespace slpvectorizer 2462 2463 template <> struct GraphTraits<BoUpSLP *> { 2464 using TreeEntry = BoUpSLP::TreeEntry; 2465 2466 /// NodeRef has to be a pointer per the GraphWriter. 2467 using NodeRef = TreeEntry *; 2468 2469 using ContainerTy = BoUpSLP::TreeEntry::VecTreeTy; 2470 2471 /// Add the VectorizableTree to the index iterator to be able to return 2472 /// TreeEntry pointers. 2473 struct ChildIteratorType 2474 : public iterator_adaptor_base< 2475 ChildIteratorType, SmallVector<BoUpSLP::EdgeInfo, 1>::iterator> { 2476 ContainerTy &VectorizableTree; 2477 2478 ChildIteratorType(SmallVector<BoUpSLP::EdgeInfo, 1>::iterator W, 2479 ContainerTy &VT) 2480 : ChildIteratorType::iterator_adaptor_base(W), VectorizableTree(VT) {} 2481 2482 NodeRef operator*() { return I->UserTE; } 2483 }; 2484 2485 static NodeRef getEntryNode(BoUpSLP &R) { 2486 return R.VectorizableTree[0].get(); 2487 } 2488 2489 static ChildIteratorType child_begin(NodeRef N) { 2490 return {N->UserTreeIndices.begin(), N->Container}; 2491 } 2492 2493 static ChildIteratorType child_end(NodeRef N) { 2494 return {N->UserTreeIndices.end(), N->Container}; 2495 } 2496 2497 /// For the node iterator we just need to turn the TreeEntry iterator into a 2498 /// TreeEntry* iterator so that it dereferences to NodeRef. 2499 class nodes_iterator { 2500 using ItTy = ContainerTy::iterator; 2501 ItTy It; 2502 2503 public: 2504 nodes_iterator(const ItTy &It2) : It(It2) {} 2505 NodeRef operator*() { return It->get(); } 2506 nodes_iterator operator++() { 2507 ++It; 2508 return *this; 2509 } 2510 bool operator!=(const nodes_iterator &N2) const { return N2.It != It; } 2511 }; 2512 2513 static nodes_iterator nodes_begin(BoUpSLP *R) { 2514 return nodes_iterator(R->VectorizableTree.begin()); 2515 } 2516 2517 static nodes_iterator nodes_end(BoUpSLP *R) { 2518 return nodes_iterator(R->VectorizableTree.end()); 2519 } 2520 2521 static unsigned size(BoUpSLP *R) { return R->VectorizableTree.size(); } 2522 }; 2523 2524 template <> struct DOTGraphTraits<BoUpSLP *> : public DefaultDOTGraphTraits { 2525 using TreeEntry = BoUpSLP::TreeEntry; 2526 2527 DOTGraphTraits(bool isSimple = false) : DefaultDOTGraphTraits(isSimple) {} 2528 2529 std::string getNodeLabel(const TreeEntry *Entry, const BoUpSLP *R) { 2530 std::string Str; 2531 raw_string_ostream OS(Str); 2532 if (isSplat(Entry->Scalars)) { 2533 OS << "<splat> " << *Entry->Scalars[0]; 2534 return Str; 2535 } 2536 for (auto V : Entry->Scalars) { 2537 OS << *V; 2538 if (llvm::any_of(R->ExternalUses, [&](const BoUpSLP::ExternalUser &EU) { 2539 return EU.Scalar == V; 2540 })) 2541 OS << " <extract>"; 2542 OS << "\n"; 2543 } 2544 return Str; 2545 } 2546 2547 static std::string getNodeAttributes(const TreeEntry *Entry, 2548 const BoUpSLP *) { 2549 if (Entry->State == TreeEntry::NeedToGather) 2550 return "color=red"; 2551 return ""; 2552 } 2553 }; 2554 2555 } // end namespace llvm 2556 2557 BoUpSLP::~BoUpSLP() { 2558 for (const auto &Pair : DeletedInstructions) { 2559 // Replace operands of ignored instructions with Undefs in case if they were 2560 // marked for deletion. 2561 if (Pair.getSecond()) { 2562 Value *Undef = UndefValue::get(Pair.getFirst()->getType()); 2563 Pair.getFirst()->replaceAllUsesWith(Undef); 2564 } 2565 Pair.getFirst()->dropAllReferences(); 2566 } 2567 for (const auto &Pair : DeletedInstructions) { 2568 assert(Pair.getFirst()->use_empty() && 2569 "trying to erase instruction with users."); 2570 Pair.getFirst()->eraseFromParent(); 2571 } 2572 #ifdef EXPENSIVE_CHECKS 2573 // If we could guarantee that this call is not extremely slow, we could 2574 // remove the ifdef limitation (see PR47712). 2575 assert(!verifyFunction(*F, &dbgs())); 2576 #endif 2577 } 2578 2579 void BoUpSLP::eraseInstructions(ArrayRef<Value *> AV) { 2580 for (auto *V : AV) { 2581 if (auto *I = dyn_cast<Instruction>(V)) 2582 eraseInstruction(I, /*ReplaceOpsWithUndef=*/true); 2583 }; 2584 } 2585 2586 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2587 ArrayRef<Value *> UserIgnoreLst) { 2588 ExtraValueToDebugLocsMap ExternallyUsedValues; 2589 buildTree(Roots, ExternallyUsedValues, UserIgnoreLst); 2590 } 2591 2592 static int findLaneForValue(ArrayRef<Value *> Scalars, 2593 ArrayRef<int> ReuseShuffleIndices, Value *V) { 2594 unsigned FoundLane = std::distance(Scalars.begin(), find(Scalars, V)); 2595 assert(FoundLane < Scalars.size() && "Couldn't find extract lane"); 2596 if (!ReuseShuffleIndices.empty()) { 2597 FoundLane = std::distance(ReuseShuffleIndices.begin(), 2598 find(ReuseShuffleIndices, FoundLane)); 2599 } 2600 return FoundLane; 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 = 2624 findLaneForValue(Entry->Scalars, Entry->ReuseShuffleIndices, Scalar); 2625 2626 // Check if the scalar is externally used as an extra arg. 2627 auto ExtI = ExternallyUsedValues.find(Scalar); 2628 if (ExtI != ExternallyUsedValues.end()) { 2629 LLVM_DEBUG(dbgs() << "SLP: Need to extract: Extra arg from lane " 2630 << Lane << " from " << *Scalar << ".\n"); 2631 ExternalUses.emplace_back(Scalar, nullptr, FoundLane); 2632 } 2633 for (User *U : Scalar->users()) { 2634 LLVM_DEBUG(dbgs() << "SLP: Checking user:" << *U << ".\n"); 2635 2636 Instruction *UserInst = dyn_cast<Instruction>(U); 2637 if (!UserInst) 2638 continue; 2639 2640 // Skip in-tree scalars that become vectors 2641 if (TreeEntry *UseEntry = getTreeEntry(U)) { 2642 Value *UseScalar = UseEntry->Scalars[0]; 2643 // Some in-tree scalars will remain as scalar in vectorized 2644 // instructions. If that is the case, the one in Lane 0 will 2645 // be used. 2646 if (UseScalar != U || 2647 UseEntry->State == TreeEntry::ScatterVectorize || 2648 !InTreeUserNeedToExtract(Scalar, UserInst, TLI)) { 2649 LLVM_DEBUG(dbgs() << "SLP: \tInternal user will be removed:" << *U 2650 << ".\n"); 2651 assert(UseEntry->State != TreeEntry::NeedToGather && "Bad state"); 2652 continue; 2653 } 2654 } 2655 2656 // Ignore users in the user ignore list. 2657 if (is_contained(UserIgnoreList, UserInst)) 2658 continue; 2659 2660 LLVM_DEBUG(dbgs() << "SLP: Need to extract:" << *U << " from lane " 2661 << Lane << " from " << *Scalar << ".\n"); 2662 ExternalUses.push_back(ExternalUser(Scalar, U, FoundLane)); 2663 } 2664 } 2665 } 2666 } 2667 2668 void BoUpSLP::buildTree_rec(ArrayRef<Value *> VL, unsigned Depth, 2669 const EdgeInfo &UserTreeIdx) { 2670 assert((allConstant(VL) || allSameType(VL)) && "Invalid types!"); 2671 2672 InstructionsState S = getSameOpcode(VL); 2673 if (Depth == RecursionMaxDepth) { 2674 LLVM_DEBUG(dbgs() << "SLP: Gathering due to max recursion depth.\n"); 2675 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2676 return; 2677 } 2678 2679 // Don't handle vectors. 2680 if (S.OpValue->getType()->isVectorTy() && 2681 !isa<InsertElementInst>(S.OpValue)) { 2682 LLVM_DEBUG(dbgs() << "SLP: Gathering due to vector type.\n"); 2683 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2684 return; 2685 } 2686 2687 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) 2688 if (SI->getValueOperand()->getType()->isVectorTy()) { 2689 LLVM_DEBUG(dbgs() << "SLP: Gathering due to store vector type.\n"); 2690 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2691 return; 2692 } 2693 2694 // If all of the operands are identical or constant we have a simple solution. 2695 if (allConstant(VL) || isSplat(VL) || !allSameBlock(VL) || !S.getOpcode()) { 2696 LLVM_DEBUG(dbgs() << "SLP: Gathering due to C,S,B,O. \n"); 2697 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2698 return; 2699 } 2700 2701 // We now know that this is a vector of instructions of the same type from 2702 // the same block. 2703 2704 // Don't vectorize ephemeral values. 2705 for (Value *V : VL) { 2706 if (EphValues.count(V)) { 2707 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2708 << ") is ephemeral.\n"); 2709 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2710 return; 2711 } 2712 } 2713 2714 // Check if this is a duplicate of another entry. 2715 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 2716 LLVM_DEBUG(dbgs() << "SLP: \tChecking bundle: " << *S.OpValue << ".\n"); 2717 if (!E->isSame(VL)) { 2718 LLVM_DEBUG(dbgs() << "SLP: Gathering due to partial overlap.\n"); 2719 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2720 return; 2721 } 2722 // Record the reuse of the tree node. FIXME, currently this is only used to 2723 // properly draw the graph rather than for the actual vectorization. 2724 E->UserTreeIndices.push_back(UserTreeIdx); 2725 LLVM_DEBUG(dbgs() << "SLP: Perfect diamond merge at " << *S.OpValue 2726 << ".\n"); 2727 return; 2728 } 2729 2730 // Check that none of the instructions in the bundle are already in the tree. 2731 for (Value *V : VL) { 2732 auto *I = dyn_cast<Instruction>(V); 2733 if (!I) 2734 continue; 2735 if (getTreeEntry(I)) { 2736 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2737 << ") is already in tree.\n"); 2738 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2739 return; 2740 } 2741 } 2742 2743 // If any of the scalars is marked as a value that needs to stay scalar, then 2744 // we need to gather the scalars. 2745 // The reduction nodes (stored in UserIgnoreList) also should stay scalar. 2746 for (Value *V : VL) { 2747 if (MustGather.count(V) || is_contained(UserIgnoreList, V)) { 2748 LLVM_DEBUG(dbgs() << "SLP: Gathering due to gathered scalar.\n"); 2749 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2750 return; 2751 } 2752 } 2753 2754 // Check that all of the users of the scalars that we want to vectorize are 2755 // schedulable. 2756 auto *VL0 = cast<Instruction>(S.OpValue); 2757 BasicBlock *BB = VL0->getParent(); 2758 2759 if (!DT->isReachableFromEntry(BB)) { 2760 // Don't go into unreachable blocks. They may contain instructions with 2761 // dependency cycles which confuse the final scheduling. 2762 LLVM_DEBUG(dbgs() << "SLP: bundle in unreachable block.\n"); 2763 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2764 return; 2765 } 2766 2767 // Check that every instruction appears once in this bundle. 2768 SmallVector<unsigned, 4> ReuseShuffleIndicies; 2769 SmallVector<Value *, 4> UniqueValues; 2770 DenseMap<Value *, unsigned> UniquePositions; 2771 for (Value *V : VL) { 2772 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 2773 ReuseShuffleIndicies.emplace_back(Res.first->second); 2774 if (Res.second) 2775 UniqueValues.emplace_back(V); 2776 } 2777 size_t NumUniqueScalarValues = UniqueValues.size(); 2778 if (NumUniqueScalarValues == VL.size()) { 2779 ReuseShuffleIndicies.clear(); 2780 } else { 2781 LLVM_DEBUG(dbgs() << "SLP: Shuffle for reused scalars.\n"); 2782 if (NumUniqueScalarValues <= 1 || 2783 !llvm::isPowerOf2_32(NumUniqueScalarValues)) { 2784 LLVM_DEBUG(dbgs() << "SLP: Scalar used twice in bundle.\n"); 2785 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2786 return; 2787 } 2788 VL = UniqueValues; 2789 } 2790 2791 auto &BSRef = BlocksSchedules[BB]; 2792 if (!BSRef) 2793 BSRef = std::make_unique<BlockScheduling>(BB); 2794 2795 BlockScheduling &BS = *BSRef.get(); 2796 2797 Optional<ScheduleData *> Bundle = BS.tryScheduleBundle(VL, this, S); 2798 if (!Bundle) { 2799 LLVM_DEBUG(dbgs() << "SLP: We are not able to schedule this bundle!\n"); 2800 assert((!BS.getScheduleData(VL0) || 2801 !BS.getScheduleData(VL0)->isPartOfBundle()) && 2802 "tryScheduleBundle should cancelScheduling on failure"); 2803 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2804 ReuseShuffleIndicies); 2805 return; 2806 } 2807 LLVM_DEBUG(dbgs() << "SLP: We are able to schedule this bundle.\n"); 2808 2809 unsigned ShuffleOrOp = S.isAltShuffle() ? 2810 (unsigned) Instruction::ShuffleVector : S.getOpcode(); 2811 switch (ShuffleOrOp) { 2812 case Instruction::PHI: { 2813 auto *PH = cast<PHINode>(VL0); 2814 2815 // Check for terminator values (e.g. invoke). 2816 for (Value *V : VL) 2817 for (unsigned I = 0, E = PH->getNumIncomingValues(); I < E; ++I) { 2818 Instruction *Term = dyn_cast<Instruction>( 2819 cast<PHINode>(V)->getIncomingValueForBlock( 2820 PH->getIncomingBlock(I))); 2821 if (Term && Term->isTerminator()) { 2822 LLVM_DEBUG(dbgs() 2823 << "SLP: Need to swizzle PHINodes (terminator use).\n"); 2824 BS.cancelScheduling(VL, VL0); 2825 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2826 ReuseShuffleIndicies); 2827 return; 2828 } 2829 } 2830 2831 TreeEntry *TE = 2832 newTreeEntry(VL, Bundle, S, UserTreeIdx, ReuseShuffleIndicies); 2833 LLVM_DEBUG(dbgs() << "SLP: added a vector of PHINodes.\n"); 2834 2835 // Keeps the reordered operands to avoid code duplication. 2836 SmallVector<ValueList, 2> OperandsVec; 2837 for (unsigned I = 0, E = PH->getNumIncomingValues(); I < E; ++I) { 2838 if (!DT->isReachableFromEntry(PH->getIncomingBlock(I))) { 2839 ValueList Operands(VL.size(), PoisonValue::get(PH->getType())); 2840 TE->setOperand(I, Operands); 2841 OperandsVec.push_back(Operands); 2842 continue; 2843 } 2844 ValueList Operands; 2845 // Prepare the operand vector. 2846 for (Value *V : VL) 2847 Operands.push_back(cast<PHINode>(V)->getIncomingValueForBlock( 2848 PH->getIncomingBlock(I))); 2849 TE->setOperand(I, Operands); 2850 OperandsVec.push_back(Operands); 2851 } 2852 for (unsigned OpIdx = 0, OpE = OperandsVec.size(); OpIdx != OpE; ++OpIdx) 2853 buildTree_rec(OperandsVec[OpIdx], Depth + 1, {TE, OpIdx}); 2854 return; 2855 } 2856 case Instruction::ExtractValue: 2857 case Instruction::ExtractElement: { 2858 OrdersType CurrentOrder; 2859 bool Reuse = canReuseExtract(VL, VL0, CurrentOrder); 2860 if (Reuse) { 2861 LLVM_DEBUG(dbgs() << "SLP: Reusing or shuffling extract sequence.\n"); 2862 ++NumOpsWantToKeepOriginalOrder; 2863 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2864 ReuseShuffleIndicies); 2865 // This is a special case, as it does not gather, but at the same time 2866 // we are not extending buildTree_rec() towards the operands. 2867 ValueList Op0; 2868 Op0.assign(VL.size(), VL0->getOperand(0)); 2869 VectorizableTree.back()->setOperand(0, Op0); 2870 return; 2871 } 2872 if (!CurrentOrder.empty()) { 2873 LLVM_DEBUG({ 2874 dbgs() << "SLP: Reusing or shuffling of reordered extract sequence " 2875 "with order"; 2876 for (unsigned Idx : CurrentOrder) 2877 dbgs() << " " << Idx; 2878 dbgs() << "\n"; 2879 }); 2880 // Insert new order with initial value 0, if it does not exist, 2881 // otherwise return the iterator to the existing one. 2882 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2883 ReuseShuffleIndicies, CurrentOrder); 2884 findRootOrder(CurrentOrder); 2885 ++NumOpsWantToKeepOrder[CurrentOrder]; 2886 // This is a special case, as it does not gather, but at the same time 2887 // we are not extending buildTree_rec() towards the operands. 2888 ValueList Op0; 2889 Op0.assign(VL.size(), VL0->getOperand(0)); 2890 VectorizableTree.back()->setOperand(0, Op0); 2891 return; 2892 } 2893 LLVM_DEBUG(dbgs() << "SLP: Gather extract sequence.\n"); 2894 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2895 ReuseShuffleIndicies); 2896 BS.cancelScheduling(VL, VL0); 2897 return; 2898 } 2899 case Instruction::InsertElement: { 2900 assert(ReuseShuffleIndicies.empty() && "All inserts should be unique"); 2901 2902 // Check that we have a buildvector and not a shuffle of 2 or more 2903 // different vectors. 2904 ValueSet SourceVectors; 2905 for (Value *V : VL) 2906 SourceVectors.insert(cast<Instruction>(V)->getOperand(0)); 2907 2908 if (count_if(VL, [&SourceVectors](Value *V) { 2909 return !SourceVectors.contains(V); 2910 }) >= 2) { 2911 // Found 2nd source vector - cancel. 2912 LLVM_DEBUG(dbgs() << "SLP: Gather of insertelement vectors with " 2913 "different source vectors.\n"); 2914 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2915 ReuseShuffleIndicies); 2916 BS.cancelScheduling(VL, VL0); 2917 return; 2918 } 2919 2920 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx); 2921 LLVM_DEBUG(dbgs() << "SLP: added inserts bundle.\n"); 2922 2923 constexpr int NumOps = 2; 2924 ValueList VectorOperands[NumOps]; 2925 for (int I = 0; I < NumOps; ++I) { 2926 for (Value *V : VL) 2927 VectorOperands[I].push_back(cast<Instruction>(V)->getOperand(I)); 2928 2929 TE->setOperand(I, VectorOperands[I]); 2930 } 2931 buildTree_rec(VectorOperands[NumOps - 1], Depth + 1, {TE, 0}); 2932 return; 2933 } 2934 case Instruction::Load: { 2935 // Check that a vectorized load would load the same memory as a scalar 2936 // load. For example, we don't want to vectorize loads that are smaller 2937 // than 8-bit. Even though we have a packed struct {<i2, i2, i2, i2>} LLVM 2938 // treats loading/storing it as an i8 struct. If we vectorize loads/stores 2939 // from such a struct, we read/write packed bits disagreeing with the 2940 // unvectorized version. 2941 Type *ScalarTy = VL0->getType(); 2942 2943 if (DL->getTypeSizeInBits(ScalarTy) != 2944 DL->getTypeAllocSizeInBits(ScalarTy)) { 2945 BS.cancelScheduling(VL, VL0); 2946 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2947 ReuseShuffleIndicies); 2948 LLVM_DEBUG(dbgs() << "SLP: Gathering loads of non-packed type.\n"); 2949 return; 2950 } 2951 2952 // Make sure all loads in the bundle are simple - we can't vectorize 2953 // atomic or volatile loads. 2954 SmallVector<Value *, 4> PointerOps(VL.size()); 2955 auto POIter = PointerOps.begin(); 2956 for (Value *V : VL) { 2957 auto *L = cast<LoadInst>(V); 2958 if (!L->isSimple()) { 2959 BS.cancelScheduling(VL, VL0); 2960 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2961 ReuseShuffleIndicies); 2962 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple loads.\n"); 2963 return; 2964 } 2965 *POIter = L->getPointerOperand(); 2966 ++POIter; 2967 } 2968 2969 OrdersType CurrentOrder; 2970 // Check the order of pointer operands. 2971 if (llvm::sortPtrAccesses(PointerOps, ScalarTy, *DL, *SE, CurrentOrder)) { 2972 Value *Ptr0; 2973 Value *PtrN; 2974 if (CurrentOrder.empty()) { 2975 Ptr0 = PointerOps.front(); 2976 PtrN = PointerOps.back(); 2977 } else { 2978 Ptr0 = PointerOps[CurrentOrder.front()]; 2979 PtrN = PointerOps[CurrentOrder.back()]; 2980 } 2981 Optional<int> Diff = getPointersDiff( 2982 ScalarTy, Ptr0, ScalarTy, PtrN, *DL, *SE); 2983 // Check that the sorted loads are consecutive. 2984 if (static_cast<unsigned>(*Diff) == VL.size() - 1) { 2985 if (CurrentOrder.empty()) { 2986 // Original loads are consecutive and does not require reordering. 2987 ++NumOpsWantToKeepOriginalOrder; 2988 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, 2989 UserTreeIdx, ReuseShuffleIndicies); 2990 TE->setOperandsInOrder(); 2991 LLVM_DEBUG(dbgs() << "SLP: added a vector of loads.\n"); 2992 } else { 2993 // Need to reorder. 2994 TreeEntry *TE = 2995 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2996 ReuseShuffleIndicies, CurrentOrder); 2997 TE->setOperandsInOrder(); 2998 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled loads.\n"); 2999 findRootOrder(CurrentOrder); 3000 ++NumOpsWantToKeepOrder[CurrentOrder]; 3001 } 3002 return; 3003 } 3004 // Vectorizing non-consecutive loads with `llvm.masked.gather`. 3005 TreeEntry *TE = newTreeEntry(VL, TreeEntry::ScatterVectorize, Bundle, S, 3006 UserTreeIdx, ReuseShuffleIndicies); 3007 TE->setOperandsInOrder(); 3008 buildTree_rec(PointerOps, Depth + 1, {TE, 0}); 3009 LLVM_DEBUG(dbgs() << "SLP: added a vector of non-consecutive loads.\n"); 3010 return; 3011 } 3012 3013 LLVM_DEBUG(dbgs() << "SLP: Gathering non-consecutive loads.\n"); 3014 BS.cancelScheduling(VL, VL0); 3015 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3016 ReuseShuffleIndicies); 3017 return; 3018 } 3019 case Instruction::ZExt: 3020 case Instruction::SExt: 3021 case Instruction::FPToUI: 3022 case Instruction::FPToSI: 3023 case Instruction::FPExt: 3024 case Instruction::PtrToInt: 3025 case Instruction::IntToPtr: 3026 case Instruction::SIToFP: 3027 case Instruction::UIToFP: 3028 case Instruction::Trunc: 3029 case Instruction::FPTrunc: 3030 case Instruction::BitCast: { 3031 Type *SrcTy = VL0->getOperand(0)->getType(); 3032 for (Value *V : VL) { 3033 Type *Ty = cast<Instruction>(V)->getOperand(0)->getType(); 3034 if (Ty != SrcTy || !isValidElementType(Ty)) { 3035 BS.cancelScheduling(VL, VL0); 3036 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3037 ReuseShuffleIndicies); 3038 LLVM_DEBUG(dbgs() 3039 << "SLP: Gathering casts with different src types.\n"); 3040 return; 3041 } 3042 } 3043 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3044 ReuseShuffleIndicies); 3045 LLVM_DEBUG(dbgs() << "SLP: added a vector of casts.\n"); 3046 3047 TE->setOperandsInOrder(); 3048 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 3049 ValueList Operands; 3050 // Prepare the operand vector. 3051 for (Value *V : VL) 3052 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3053 3054 buildTree_rec(Operands, Depth + 1, {TE, i}); 3055 } 3056 return; 3057 } 3058 case Instruction::ICmp: 3059 case Instruction::FCmp: { 3060 // Check that all of the compares have the same predicate. 3061 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 3062 CmpInst::Predicate SwapP0 = CmpInst::getSwappedPredicate(P0); 3063 Type *ComparedTy = VL0->getOperand(0)->getType(); 3064 for (Value *V : VL) { 3065 CmpInst *Cmp = cast<CmpInst>(V); 3066 if ((Cmp->getPredicate() != P0 && Cmp->getPredicate() != SwapP0) || 3067 Cmp->getOperand(0)->getType() != ComparedTy) { 3068 BS.cancelScheduling(VL, VL0); 3069 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3070 ReuseShuffleIndicies); 3071 LLVM_DEBUG(dbgs() 3072 << "SLP: Gathering cmp with different predicate.\n"); 3073 return; 3074 } 3075 } 3076 3077 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3078 ReuseShuffleIndicies); 3079 LLVM_DEBUG(dbgs() << "SLP: added a vector of compares.\n"); 3080 3081 ValueList Left, Right; 3082 if (cast<CmpInst>(VL0)->isCommutative()) { 3083 // Commutative predicate - collect + sort operands of the instructions 3084 // so that each side is more likely to have the same opcode. 3085 assert(P0 == SwapP0 && "Commutative Predicate mismatch"); 3086 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 3087 } else { 3088 // Collect operands - commute if it uses the swapped predicate. 3089 for (Value *V : VL) { 3090 auto *Cmp = cast<CmpInst>(V); 3091 Value *LHS = Cmp->getOperand(0); 3092 Value *RHS = Cmp->getOperand(1); 3093 if (Cmp->getPredicate() != P0) 3094 std::swap(LHS, RHS); 3095 Left.push_back(LHS); 3096 Right.push_back(RHS); 3097 } 3098 } 3099 TE->setOperand(0, Left); 3100 TE->setOperand(1, Right); 3101 buildTree_rec(Left, Depth + 1, {TE, 0}); 3102 buildTree_rec(Right, Depth + 1, {TE, 1}); 3103 return; 3104 } 3105 case Instruction::Select: 3106 case Instruction::FNeg: 3107 case Instruction::Add: 3108 case Instruction::FAdd: 3109 case Instruction::Sub: 3110 case Instruction::FSub: 3111 case Instruction::Mul: 3112 case Instruction::FMul: 3113 case Instruction::UDiv: 3114 case Instruction::SDiv: 3115 case Instruction::FDiv: 3116 case Instruction::URem: 3117 case Instruction::SRem: 3118 case Instruction::FRem: 3119 case Instruction::Shl: 3120 case Instruction::LShr: 3121 case Instruction::AShr: 3122 case Instruction::And: 3123 case Instruction::Or: 3124 case Instruction::Xor: { 3125 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3126 ReuseShuffleIndicies); 3127 LLVM_DEBUG(dbgs() << "SLP: added a vector of un/bin op.\n"); 3128 3129 // Sort operands of the instructions so that each side is more likely to 3130 // have the same opcode. 3131 if (isa<BinaryOperator>(VL0) && VL0->isCommutative()) { 3132 ValueList Left, Right; 3133 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 3134 TE->setOperand(0, Left); 3135 TE->setOperand(1, Right); 3136 buildTree_rec(Left, Depth + 1, {TE, 0}); 3137 buildTree_rec(Right, Depth + 1, {TE, 1}); 3138 return; 3139 } 3140 3141 TE->setOperandsInOrder(); 3142 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 3143 ValueList Operands; 3144 // Prepare the operand vector. 3145 for (Value *V : VL) 3146 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3147 3148 buildTree_rec(Operands, Depth + 1, {TE, i}); 3149 } 3150 return; 3151 } 3152 case Instruction::GetElementPtr: { 3153 // We don't combine GEPs with complicated (nested) indexing. 3154 for (Value *V : VL) { 3155 if (cast<Instruction>(V)->getNumOperands() != 2) { 3156 LLVM_DEBUG(dbgs() << "SLP: not-vectorizable GEP (nested indexes).\n"); 3157 BS.cancelScheduling(VL, VL0); 3158 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3159 ReuseShuffleIndicies); 3160 return; 3161 } 3162 } 3163 3164 // We can't combine several GEPs into one vector if they operate on 3165 // different types. 3166 Type *Ty0 = VL0->getOperand(0)->getType(); 3167 for (Value *V : VL) { 3168 Type *CurTy = cast<Instruction>(V)->getOperand(0)->getType(); 3169 if (Ty0 != CurTy) { 3170 LLVM_DEBUG(dbgs() 3171 << "SLP: not-vectorizable GEP (different types).\n"); 3172 BS.cancelScheduling(VL, VL0); 3173 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3174 ReuseShuffleIndicies); 3175 return; 3176 } 3177 } 3178 3179 // We don't combine GEPs with non-constant indexes. 3180 Type *Ty1 = VL0->getOperand(1)->getType(); 3181 for (Value *V : VL) { 3182 auto Op = cast<Instruction>(V)->getOperand(1); 3183 if (!isa<ConstantInt>(Op) || 3184 (Op->getType() != Ty1 && 3185 Op->getType()->getScalarSizeInBits() > 3186 DL->getIndexSizeInBits( 3187 V->getType()->getPointerAddressSpace()))) { 3188 LLVM_DEBUG(dbgs() 3189 << "SLP: not-vectorizable GEP (non-constant indexes).\n"); 3190 BS.cancelScheduling(VL, VL0); 3191 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3192 ReuseShuffleIndicies); 3193 return; 3194 } 3195 } 3196 3197 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3198 ReuseShuffleIndicies); 3199 LLVM_DEBUG(dbgs() << "SLP: added a vector of GEPs.\n"); 3200 TE->setOperandsInOrder(); 3201 for (unsigned i = 0, e = 2; i < e; ++i) { 3202 ValueList Operands; 3203 // Prepare the operand vector. 3204 for (Value *V : VL) 3205 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3206 3207 buildTree_rec(Operands, Depth + 1, {TE, i}); 3208 } 3209 return; 3210 } 3211 case Instruction::Store: { 3212 // Check if the stores are consecutive or if we need to swizzle them. 3213 llvm::Type *ScalarTy = cast<StoreInst>(VL0)->getValueOperand()->getType(); 3214 // Avoid types that are padded when being allocated as scalars, while 3215 // being packed together in a vector (such as i1). 3216 if (DL->getTypeSizeInBits(ScalarTy) != 3217 DL->getTypeAllocSizeInBits(ScalarTy)) { 3218 BS.cancelScheduling(VL, VL0); 3219 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3220 ReuseShuffleIndicies); 3221 LLVM_DEBUG(dbgs() << "SLP: Gathering stores of non-packed type.\n"); 3222 return; 3223 } 3224 // Make sure all stores in the bundle are simple - we can't vectorize 3225 // atomic or volatile stores. 3226 SmallVector<Value *, 4> PointerOps(VL.size()); 3227 ValueList Operands(VL.size()); 3228 auto POIter = PointerOps.begin(); 3229 auto OIter = Operands.begin(); 3230 for (Value *V : VL) { 3231 auto *SI = cast<StoreInst>(V); 3232 if (!SI->isSimple()) { 3233 BS.cancelScheduling(VL, VL0); 3234 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3235 ReuseShuffleIndicies); 3236 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple stores.\n"); 3237 return; 3238 } 3239 *POIter = SI->getPointerOperand(); 3240 *OIter = SI->getValueOperand(); 3241 ++POIter; 3242 ++OIter; 3243 } 3244 3245 OrdersType CurrentOrder; 3246 // Check the order of pointer operands. 3247 if (llvm::sortPtrAccesses(PointerOps, ScalarTy, *DL, *SE, CurrentOrder)) { 3248 Value *Ptr0; 3249 Value *PtrN; 3250 if (CurrentOrder.empty()) { 3251 Ptr0 = PointerOps.front(); 3252 PtrN = PointerOps.back(); 3253 } else { 3254 Ptr0 = PointerOps[CurrentOrder.front()]; 3255 PtrN = PointerOps[CurrentOrder.back()]; 3256 } 3257 Optional<int> Dist = 3258 getPointersDiff(ScalarTy, Ptr0, ScalarTy, PtrN, *DL, *SE); 3259 // Check that the sorted pointer operands are consecutive. 3260 if (static_cast<unsigned>(*Dist) == VL.size() - 1) { 3261 if (CurrentOrder.empty()) { 3262 // Original stores are consecutive and does not require reordering. 3263 ++NumOpsWantToKeepOriginalOrder; 3264 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, 3265 UserTreeIdx, ReuseShuffleIndicies); 3266 TE->setOperandsInOrder(); 3267 buildTree_rec(Operands, Depth + 1, {TE, 0}); 3268 LLVM_DEBUG(dbgs() << "SLP: added a vector of stores.\n"); 3269 } else { 3270 TreeEntry *TE = 3271 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3272 ReuseShuffleIndicies, CurrentOrder); 3273 TE->setOperandsInOrder(); 3274 buildTree_rec(Operands, Depth + 1, {TE, 0}); 3275 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled stores.\n"); 3276 findRootOrder(CurrentOrder); 3277 ++NumOpsWantToKeepOrder[CurrentOrder]; 3278 } 3279 return; 3280 } 3281 } 3282 3283 BS.cancelScheduling(VL, VL0); 3284 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3285 ReuseShuffleIndicies); 3286 LLVM_DEBUG(dbgs() << "SLP: Non-consecutive store.\n"); 3287 return; 3288 } 3289 case Instruction::Call: { 3290 // Check if the calls are all to the same vectorizable intrinsic or 3291 // library function. 3292 CallInst *CI = cast<CallInst>(VL0); 3293 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3294 3295 VFShape Shape = VFShape::get( 3296 *CI, ElementCount::getFixed(static_cast<unsigned int>(VL.size())), 3297 false /*HasGlobalPred*/); 3298 Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape); 3299 3300 if (!VecFunc && !isTriviallyVectorizable(ID)) { 3301 BS.cancelScheduling(VL, VL0); 3302 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3303 ReuseShuffleIndicies); 3304 LLVM_DEBUG(dbgs() << "SLP: Non-vectorizable call.\n"); 3305 return; 3306 } 3307 Function *F = CI->getCalledFunction(); 3308 unsigned NumArgs = CI->getNumArgOperands(); 3309 SmallVector<Value*, 4> ScalarArgs(NumArgs, nullptr); 3310 for (unsigned j = 0; j != NumArgs; ++j) 3311 if (hasVectorInstrinsicScalarOpd(ID, j)) 3312 ScalarArgs[j] = CI->getArgOperand(j); 3313 for (Value *V : VL) { 3314 CallInst *CI2 = dyn_cast<CallInst>(V); 3315 if (!CI2 || CI2->getCalledFunction() != F || 3316 getVectorIntrinsicIDForCall(CI2, TLI) != ID || 3317 (VecFunc && 3318 VecFunc != VFDatabase(*CI2).getVectorizedFunction(Shape)) || 3319 !CI->hasIdenticalOperandBundleSchema(*CI2)) { 3320 BS.cancelScheduling(VL, VL0); 3321 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3322 ReuseShuffleIndicies); 3323 LLVM_DEBUG(dbgs() << "SLP: mismatched calls:" << *CI << "!=" << *V 3324 << "\n"); 3325 return; 3326 } 3327 // Some intrinsics have scalar arguments and should be same in order for 3328 // them to be vectorized. 3329 for (unsigned j = 0; j != NumArgs; ++j) { 3330 if (hasVectorInstrinsicScalarOpd(ID, j)) { 3331 Value *A1J = CI2->getArgOperand(j); 3332 if (ScalarArgs[j] != A1J) { 3333 BS.cancelScheduling(VL, VL0); 3334 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3335 ReuseShuffleIndicies); 3336 LLVM_DEBUG(dbgs() << "SLP: mismatched arguments in call:" << *CI 3337 << " argument " << ScalarArgs[j] << "!=" << A1J 3338 << "\n"); 3339 return; 3340 } 3341 } 3342 } 3343 // Verify that the bundle operands are identical between the two calls. 3344 if (CI->hasOperandBundles() && 3345 !std::equal(CI->op_begin() + CI->getBundleOperandsStartIndex(), 3346 CI->op_begin() + CI->getBundleOperandsEndIndex(), 3347 CI2->op_begin() + CI2->getBundleOperandsStartIndex())) { 3348 BS.cancelScheduling(VL, VL0); 3349 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3350 ReuseShuffleIndicies); 3351 LLVM_DEBUG(dbgs() << "SLP: mismatched bundle operands in calls:" 3352 << *CI << "!=" << *V << '\n'); 3353 return; 3354 } 3355 } 3356 3357 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3358 ReuseShuffleIndicies); 3359 TE->setOperandsInOrder(); 3360 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 3361 ValueList Operands; 3362 // Prepare the operand vector. 3363 for (Value *V : VL) { 3364 auto *CI2 = cast<CallInst>(V); 3365 Operands.push_back(CI2->getArgOperand(i)); 3366 } 3367 buildTree_rec(Operands, Depth + 1, {TE, i}); 3368 } 3369 return; 3370 } 3371 case Instruction::ShuffleVector: { 3372 // If this is not an alternate sequence of opcode like add-sub 3373 // then do not vectorize this instruction. 3374 if (!S.isAltShuffle()) { 3375 BS.cancelScheduling(VL, VL0); 3376 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3377 ReuseShuffleIndicies); 3378 LLVM_DEBUG(dbgs() << "SLP: ShuffleVector are not vectorized.\n"); 3379 return; 3380 } 3381 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3382 ReuseShuffleIndicies); 3383 LLVM_DEBUG(dbgs() << "SLP: added a ShuffleVector op.\n"); 3384 3385 // Reorder operands if reordering would enable vectorization. 3386 if (isa<BinaryOperator>(VL0)) { 3387 ValueList Left, Right; 3388 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 3389 TE->setOperand(0, Left); 3390 TE->setOperand(1, Right); 3391 buildTree_rec(Left, Depth + 1, {TE, 0}); 3392 buildTree_rec(Right, Depth + 1, {TE, 1}); 3393 return; 3394 } 3395 3396 TE->setOperandsInOrder(); 3397 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 3398 ValueList Operands; 3399 // Prepare the operand vector. 3400 for (Value *V : VL) 3401 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3402 3403 buildTree_rec(Operands, Depth + 1, {TE, i}); 3404 } 3405 return; 3406 } 3407 default: 3408 BS.cancelScheduling(VL, VL0); 3409 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3410 ReuseShuffleIndicies); 3411 LLVM_DEBUG(dbgs() << "SLP: Gathering unknown instruction.\n"); 3412 return; 3413 } 3414 } 3415 3416 unsigned BoUpSLP::canMapToVector(Type *T, const DataLayout &DL) const { 3417 unsigned N = 1; 3418 Type *EltTy = T; 3419 3420 while (isa<StructType>(EltTy) || isa<ArrayType>(EltTy) || 3421 isa<VectorType>(EltTy)) { 3422 if (auto *ST = dyn_cast<StructType>(EltTy)) { 3423 // Check that struct is homogeneous. 3424 for (const auto *Ty : ST->elements()) 3425 if (Ty != *ST->element_begin()) 3426 return 0; 3427 N *= ST->getNumElements(); 3428 EltTy = *ST->element_begin(); 3429 } else if (auto *AT = dyn_cast<ArrayType>(EltTy)) { 3430 N *= AT->getNumElements(); 3431 EltTy = AT->getElementType(); 3432 } else { 3433 auto *VT = cast<FixedVectorType>(EltTy); 3434 N *= VT->getNumElements(); 3435 EltTy = VT->getElementType(); 3436 } 3437 } 3438 3439 if (!isValidElementType(EltTy)) 3440 return 0; 3441 uint64_t VTSize = DL.getTypeStoreSizeInBits(FixedVectorType::get(EltTy, N)); 3442 if (VTSize < MinVecRegSize || VTSize > MaxVecRegSize || VTSize != DL.getTypeStoreSizeInBits(T)) 3443 return 0; 3444 return N; 3445 } 3446 3447 bool BoUpSLP::canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 3448 SmallVectorImpl<unsigned> &CurrentOrder) const { 3449 Instruction *E0 = cast<Instruction>(OpValue); 3450 assert(E0->getOpcode() == Instruction::ExtractElement || 3451 E0->getOpcode() == Instruction::ExtractValue); 3452 assert(E0->getOpcode() == getSameOpcode(VL).getOpcode() && "Invalid opcode"); 3453 // Check if all of the extracts come from the same vector and from the 3454 // correct offset. 3455 Value *Vec = E0->getOperand(0); 3456 3457 CurrentOrder.clear(); 3458 3459 // We have to extract from a vector/aggregate with the same number of elements. 3460 unsigned NElts; 3461 if (E0->getOpcode() == Instruction::ExtractValue) { 3462 const DataLayout &DL = E0->getModule()->getDataLayout(); 3463 NElts = canMapToVector(Vec->getType(), DL); 3464 if (!NElts) 3465 return false; 3466 // Check if load can be rewritten as load of vector. 3467 LoadInst *LI = dyn_cast<LoadInst>(Vec); 3468 if (!LI || !LI->isSimple() || !LI->hasNUses(VL.size())) 3469 return false; 3470 } else { 3471 NElts = cast<FixedVectorType>(Vec->getType())->getNumElements(); 3472 } 3473 3474 if (NElts != VL.size()) 3475 return false; 3476 3477 // Check that all of the indices extract from the correct offset. 3478 bool ShouldKeepOrder = true; 3479 unsigned E = VL.size(); 3480 // Assign to all items the initial value E + 1 so we can check if the extract 3481 // instruction index was used already. 3482 // Also, later we can check that all the indices are used and we have a 3483 // consecutive access in the extract instructions, by checking that no 3484 // element of CurrentOrder still has value E + 1. 3485 CurrentOrder.assign(E, E + 1); 3486 unsigned I = 0; 3487 for (; I < E; ++I) { 3488 auto *Inst = cast<Instruction>(VL[I]); 3489 if (Inst->getOperand(0) != Vec) 3490 break; 3491 Optional<unsigned> Idx = getExtractIndex(Inst); 3492 if (!Idx) 3493 break; 3494 const unsigned ExtIdx = *Idx; 3495 if (ExtIdx != I) { 3496 if (ExtIdx >= E || CurrentOrder[ExtIdx] != E + 1) 3497 break; 3498 ShouldKeepOrder = false; 3499 CurrentOrder[ExtIdx] = I; 3500 } else { 3501 if (CurrentOrder[I] != E + 1) 3502 break; 3503 CurrentOrder[I] = I; 3504 } 3505 } 3506 if (I < E) { 3507 CurrentOrder.clear(); 3508 return false; 3509 } 3510 3511 return ShouldKeepOrder; 3512 } 3513 3514 bool BoUpSLP::areAllUsersVectorized(Instruction *I, 3515 ArrayRef<Value *> VectorizedVals) const { 3516 return (I->hasOneUse() && is_contained(VectorizedVals, I)) || 3517 llvm::all_of(I->users(), [this](User *U) { 3518 return ScalarToTreeEntry.count(U) > 0; 3519 }); 3520 } 3521 3522 static std::pair<InstructionCost, InstructionCost> 3523 getVectorCallCosts(CallInst *CI, FixedVectorType *VecTy, 3524 TargetTransformInfo *TTI, TargetLibraryInfo *TLI) { 3525 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3526 3527 // Calculate the cost of the scalar and vector calls. 3528 SmallVector<Type *, 4> VecTys; 3529 for (Use &Arg : CI->args()) 3530 VecTys.push_back( 3531 FixedVectorType::get(Arg->getType(), VecTy->getNumElements())); 3532 FastMathFlags FMF; 3533 if (auto *FPCI = dyn_cast<FPMathOperator>(CI)) 3534 FMF = FPCI->getFastMathFlags(); 3535 SmallVector<const Value *> Arguments(CI->arg_begin(), CI->arg_end()); 3536 IntrinsicCostAttributes CostAttrs(ID, VecTy, Arguments, VecTys, FMF, 3537 dyn_cast<IntrinsicInst>(CI)); 3538 auto IntrinsicCost = 3539 TTI->getIntrinsicInstrCost(CostAttrs, TTI::TCK_RecipThroughput); 3540 3541 auto Shape = VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>( 3542 VecTy->getNumElements())), 3543 false /*HasGlobalPred*/); 3544 Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape); 3545 auto LibCost = IntrinsicCost; 3546 if (!CI->isNoBuiltin() && VecFunc) { 3547 // Calculate the cost of the vector library call. 3548 // If the corresponding vector call is cheaper, return its cost. 3549 LibCost = TTI->getCallInstrCost(nullptr, VecTy, VecTys, 3550 TTI::TCK_RecipThroughput); 3551 } 3552 return {IntrinsicCost, LibCost}; 3553 } 3554 3555 /// Compute the cost of creating a vector of type \p VecTy containing the 3556 /// extracted values from \p VL. 3557 static InstructionCost 3558 computeExtractCost(ArrayRef<Value *> VL, FixedVectorType *VecTy, 3559 TargetTransformInfo::ShuffleKind ShuffleKind, 3560 ArrayRef<int> Mask, TargetTransformInfo &TTI) { 3561 unsigned NumOfParts = TTI.getNumberOfParts(VecTy); 3562 3563 if (ShuffleKind != TargetTransformInfo::SK_PermuteSingleSrc || !NumOfParts || 3564 VecTy->getNumElements() < NumOfParts) 3565 return TTI.getShuffleCost(ShuffleKind, VecTy, Mask); 3566 3567 bool AllConsecutive = true; 3568 unsigned EltsPerVector = VecTy->getNumElements() / NumOfParts; 3569 unsigned Idx = -1; 3570 InstructionCost Cost = 0; 3571 3572 // Process extracts in blocks of EltsPerVector to check if the source vector 3573 // operand can be re-used directly. If not, add the cost of creating a shuffle 3574 // to extract the values into a vector register. 3575 for (auto *V : VL) { 3576 ++Idx; 3577 3578 // Reached the start of a new vector registers. 3579 if (Idx % EltsPerVector == 0) { 3580 AllConsecutive = true; 3581 continue; 3582 } 3583 3584 // Check all extracts for a vector register on the target directly 3585 // extract values in order. 3586 unsigned CurrentIdx = *getExtractIndex(cast<Instruction>(V)); 3587 unsigned PrevIdx = *getExtractIndex(cast<Instruction>(VL[Idx - 1])); 3588 AllConsecutive &= PrevIdx + 1 == CurrentIdx && 3589 CurrentIdx % EltsPerVector == Idx % EltsPerVector; 3590 3591 if (AllConsecutive) 3592 continue; 3593 3594 // Skip all indices, except for the last index per vector block. 3595 if ((Idx + 1) % EltsPerVector != 0 && Idx + 1 != VL.size()) 3596 continue; 3597 3598 // If we have a series of extracts which are not consecutive and hence 3599 // cannot re-use the source vector register directly, compute the shuffle 3600 // cost to extract the a vector with EltsPerVector elements. 3601 Cost += TTI.getShuffleCost( 3602 TargetTransformInfo::SK_PermuteSingleSrc, 3603 FixedVectorType::get(VecTy->getElementType(), EltsPerVector)); 3604 } 3605 return Cost; 3606 } 3607 3608 InstructionCost BoUpSLP::getEntryCost(const TreeEntry *E, 3609 ArrayRef<Value *> VectorizedVals) { 3610 ArrayRef<Value*> VL = E->Scalars; 3611 3612 Type *ScalarTy = VL[0]->getType(); 3613 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 3614 ScalarTy = SI->getValueOperand()->getType(); 3615 else if (CmpInst *CI = dyn_cast<CmpInst>(VL[0])) 3616 ScalarTy = CI->getOperand(0)->getType(); 3617 else if (auto *IE = dyn_cast<InsertElementInst>(VL[0])) 3618 ScalarTy = IE->getOperand(1)->getType(); 3619 auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); 3620 TTI::TargetCostKind CostKind = TTI::TCK_RecipThroughput; 3621 3622 // If we have computed a smaller type for the expression, update VecTy so 3623 // that the costs will be accurate. 3624 if (MinBWs.count(VL[0])) 3625 VecTy = FixedVectorType::get( 3626 IntegerType::get(F->getContext(), MinBWs[VL[0]].first), VL.size()); 3627 3628 unsigned ReuseShuffleNumbers = E->ReuseShuffleIndices.size(); 3629 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 3630 InstructionCost ReuseShuffleCost = 0; 3631 if (NeedToShuffleReuses) { 3632 ReuseShuffleCost = 3633 TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, VecTy, 3634 E->ReuseShuffleIndices); 3635 } 3636 // FIXME: it tries to fix a problem with MSVC buildbots. 3637 TargetTransformInfo &TTIRef = *TTI; 3638 auto &&AdjustExtractsCost = [this, &TTIRef, CostKind, VL, VecTy, 3639 VectorizedVals](InstructionCost &Cost, 3640 bool IsGather) { 3641 DenseMap<Value *, int> ExtractVectorsTys; 3642 for (auto *V : VL) { 3643 // If all users of instruction are going to be vectorized and this 3644 // instruction itself is not going to be vectorized, consider this 3645 // instruction as dead and remove its cost from the final cost of the 3646 // vectorized tree. 3647 if (!areAllUsersVectorized(cast<Instruction>(V), VectorizedVals) || 3648 (IsGather && ScalarToTreeEntry.count(V))) 3649 continue; 3650 auto *EE = cast<ExtractElementInst>(V); 3651 unsigned Idx = *getExtractIndex(EE); 3652 if (TTIRef.getNumberOfParts(VecTy) != 3653 TTIRef.getNumberOfParts(EE->getVectorOperandType())) { 3654 auto It = 3655 ExtractVectorsTys.try_emplace(EE->getVectorOperand(), Idx).first; 3656 It->getSecond() = std::min<int>(It->second, Idx); 3657 } 3658 // Take credit for instruction that will become dead. 3659 if (EE->hasOneUse()) { 3660 Instruction *Ext = EE->user_back(); 3661 if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) && 3662 all_of(Ext->users(), 3663 [](User *U) { return isa<GetElementPtrInst>(U); })) { 3664 // Use getExtractWithExtendCost() to calculate the cost of 3665 // extractelement/ext pair. 3666 Cost -= 3667 TTIRef.getExtractWithExtendCost(Ext->getOpcode(), Ext->getType(), 3668 EE->getVectorOperandType(), Idx); 3669 // Add back the cost of s|zext which is subtracted separately. 3670 Cost += TTIRef.getCastInstrCost( 3671 Ext->getOpcode(), Ext->getType(), EE->getType(), 3672 TTI::getCastContextHint(Ext), CostKind, Ext); 3673 continue; 3674 } 3675 } 3676 Cost -= TTIRef.getVectorInstrCost(Instruction::ExtractElement, 3677 EE->getVectorOperandType(), Idx); 3678 } 3679 // Add a cost for subvector extracts/inserts if required. 3680 for (const auto &Data : ExtractVectorsTys) { 3681 auto *EEVTy = cast<FixedVectorType>(Data.first->getType()); 3682 unsigned NumElts = VecTy->getNumElements(); 3683 if (TTIRef.getNumberOfParts(EEVTy) > TTIRef.getNumberOfParts(VecTy)) { 3684 unsigned Idx = (Data.second / NumElts) * NumElts; 3685 unsigned EENumElts = EEVTy->getNumElements(); 3686 if (Idx + NumElts <= EENumElts) { 3687 Cost += 3688 TTIRef.getShuffleCost(TargetTransformInfo::SK_ExtractSubvector, 3689 EEVTy, None, Idx, VecTy); 3690 } else { 3691 // Need to round up the subvector type vectorization factor to avoid a 3692 // crash in cost model functions. Make SubVT so that Idx + VF of SubVT 3693 // <= EENumElts. 3694 auto *SubVT = 3695 FixedVectorType::get(VecTy->getElementType(), EENumElts - Idx); 3696 Cost += 3697 TTIRef.getShuffleCost(TargetTransformInfo::SK_ExtractSubvector, 3698 EEVTy, None, Idx, SubVT); 3699 } 3700 } else { 3701 Cost += TTIRef.getShuffleCost(TargetTransformInfo::SK_InsertSubvector, 3702 VecTy, None, 0, EEVTy); 3703 } 3704 } 3705 }; 3706 if (E->State == TreeEntry::NeedToGather) { 3707 if (allConstant(VL)) 3708 return 0; 3709 if (isa<InsertElementInst>(VL[0])) 3710 return InstructionCost::getInvalid(); 3711 SmallVector<int> Mask; 3712 SmallVector<const TreeEntry *> Entries; 3713 Optional<TargetTransformInfo::ShuffleKind> Shuffle = 3714 isGatherShuffledEntry(E, Mask, Entries); 3715 if (Shuffle.hasValue()) { 3716 InstructionCost GatherCost = 0; 3717 if (ShuffleVectorInst::isIdentityMask(Mask)) { 3718 // Perfect match in the graph, will reuse the previously vectorized 3719 // node. Cost is 0. 3720 LLVM_DEBUG( 3721 dbgs() 3722 << "SLP: perfect diamond match for gather bundle that starts with " 3723 << *VL.front() << ".\n"); 3724 } else { 3725 LLVM_DEBUG(dbgs() << "SLP: shuffled " << Entries.size() 3726 << " entries for bundle that starts with " 3727 << *VL.front() << ".\n"); 3728 // Detected that instead of gather we can emit a shuffle of single/two 3729 // previously vectorized nodes. Add the cost of the permutation rather 3730 // than gather. 3731 GatherCost = TTI->getShuffleCost(*Shuffle, VecTy, Mask); 3732 } 3733 return ReuseShuffleCost + GatherCost; 3734 } 3735 if (isSplat(VL)) { 3736 // Found the broadcasting of the single scalar, calculate the cost as the 3737 // broadcast. 3738 return ReuseShuffleCost + 3739 TTI->getShuffleCost(TargetTransformInfo::SK_Broadcast, VecTy, None, 3740 0); 3741 } 3742 if (E->getOpcode() == Instruction::ExtractElement && allSameType(VL) && 3743 allSameBlock(VL)) { 3744 // Check that gather of extractelements can be represented as just a 3745 // shuffle of a single/two vectors the scalars are extracted from. 3746 SmallVector<int> Mask; 3747 Optional<TargetTransformInfo::ShuffleKind> ShuffleKind = 3748 isShuffle(VL, Mask); 3749 if (ShuffleKind.hasValue()) { 3750 // Found the bunch of extractelement instructions that must be gathered 3751 // into a vector and can be represented as a permutation elements in a 3752 // single input vector or of 2 input vectors. 3753 InstructionCost Cost = 3754 computeExtractCost(VL, VecTy, *ShuffleKind, Mask, *TTI); 3755 AdjustExtractsCost(Cost, /*IsGather=*/true); 3756 return ReuseShuffleCost + Cost; 3757 } 3758 } 3759 return ReuseShuffleCost + getGatherCost(VL); 3760 } 3761 assert((E->State == TreeEntry::Vectorize || 3762 E->State == TreeEntry::ScatterVectorize) && 3763 "Unhandled state"); 3764 assert(E->getOpcode() && allSameType(VL) && allSameBlock(VL) && "Invalid VL"); 3765 Instruction *VL0 = E->getMainOp(); 3766 unsigned ShuffleOrOp = 3767 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 3768 switch (ShuffleOrOp) { 3769 case Instruction::PHI: 3770 return 0; 3771 3772 case Instruction::ExtractValue: 3773 case Instruction::ExtractElement: { 3774 // The common cost of removal ExtractElement/ExtractValue instructions + 3775 // the cost of shuffles, if required to resuffle the original vector. 3776 InstructionCost CommonCost = 0; 3777 if (NeedToShuffleReuses) { 3778 unsigned Idx = 0; 3779 for (unsigned I : E->ReuseShuffleIndices) { 3780 if (ShuffleOrOp == Instruction::ExtractElement) { 3781 auto *EE = cast<ExtractElementInst>(VL[I]); 3782 ReuseShuffleCost -= TTI->getVectorInstrCost( 3783 Instruction::ExtractElement, EE->getVectorOperandType(), 3784 *getExtractIndex(EE)); 3785 } else { 3786 ReuseShuffleCost -= TTI->getVectorInstrCost( 3787 Instruction::ExtractElement, VecTy, Idx); 3788 ++Idx; 3789 } 3790 } 3791 Idx = ReuseShuffleNumbers; 3792 for (Value *V : VL) { 3793 if (ShuffleOrOp == Instruction::ExtractElement) { 3794 auto *EE = cast<ExtractElementInst>(V); 3795 ReuseShuffleCost += TTI->getVectorInstrCost( 3796 Instruction::ExtractElement, EE->getVectorOperandType(), 3797 *getExtractIndex(EE)); 3798 } else { 3799 --Idx; 3800 ReuseShuffleCost += TTI->getVectorInstrCost( 3801 Instruction::ExtractElement, VecTy, Idx); 3802 } 3803 } 3804 CommonCost = ReuseShuffleCost; 3805 } else if (!E->ReorderIndices.empty()) { 3806 SmallVector<int> NewMask; 3807 inversePermutation(E->ReorderIndices, NewMask); 3808 CommonCost = TTI->getShuffleCost( 3809 TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask); 3810 } 3811 if (ShuffleOrOp == Instruction::ExtractValue) { 3812 for (unsigned I = 0, E = VL.size(); I < E; ++I) { 3813 auto *EI = cast<Instruction>(VL[I]); 3814 // Take credit for instruction that will become dead. 3815 if (EI->hasOneUse()) { 3816 Instruction *Ext = EI->user_back(); 3817 if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) && 3818 all_of(Ext->users(), 3819 [](User *U) { return isa<GetElementPtrInst>(U); })) { 3820 // Use getExtractWithExtendCost() to calculate the cost of 3821 // extractelement/ext pair. 3822 CommonCost -= TTI->getExtractWithExtendCost( 3823 Ext->getOpcode(), Ext->getType(), VecTy, I); 3824 // Add back the cost of s|zext which is subtracted separately. 3825 CommonCost += TTI->getCastInstrCost( 3826 Ext->getOpcode(), Ext->getType(), EI->getType(), 3827 TTI::getCastContextHint(Ext), CostKind, Ext); 3828 continue; 3829 } 3830 } 3831 CommonCost -= 3832 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, I); 3833 } 3834 } else { 3835 AdjustExtractsCost(CommonCost, /*IsGather=*/false); 3836 } 3837 return CommonCost; 3838 } 3839 case Instruction::InsertElement: { 3840 auto *SrcVecTy = cast<FixedVectorType>(VL0->getType()); 3841 3842 unsigned const NumElts = SrcVecTy->getNumElements(); 3843 unsigned const NumScalars = VL.size(); 3844 APInt DemandedElts = APInt::getNullValue(NumElts); 3845 // TODO: Add support for Instruction::InsertValue. 3846 unsigned Offset = UINT_MAX; 3847 bool IsIdentity = true; 3848 SmallVector<int> ShuffleMask(NumElts, UndefMaskElem); 3849 for (unsigned I = 0; I < NumScalars; ++I) { 3850 Optional<int> InsertIdx = getInsertIndex(VL[I], 0); 3851 if (!InsertIdx || *InsertIdx == UndefMaskElem) 3852 continue; 3853 unsigned Idx = *InsertIdx; 3854 DemandedElts.setBit(Idx); 3855 if (Idx < Offset) { 3856 Offset = Idx; 3857 IsIdentity &= I == 0; 3858 } else { 3859 assert(Idx >= Offset && "Failed to find vector index offset"); 3860 IsIdentity &= Idx - Offset == I; 3861 } 3862 ShuffleMask[Idx] = I; 3863 } 3864 assert(Offset < NumElts && "Failed to find vector index offset"); 3865 3866 InstructionCost Cost = 0; 3867 Cost -= TTI->getScalarizationOverhead(SrcVecTy, DemandedElts, 3868 /*Insert*/ true, /*Extract*/ false); 3869 3870 if (IsIdentity && NumElts != NumScalars && Offset % NumScalars != 0) 3871 Cost += TTI->getShuffleCost( 3872 TargetTransformInfo::SK_InsertSubvector, SrcVecTy, /*Mask*/ None, 3873 Offset, 3874 FixedVectorType::get(SrcVecTy->getElementType(), NumScalars)); 3875 else if (!IsIdentity) 3876 Cost += TTI->getShuffleCost(TTI::SK_PermuteSingleSrc, SrcVecTy, 3877 ShuffleMask); 3878 3879 return Cost; 3880 } 3881 case Instruction::ZExt: 3882 case Instruction::SExt: 3883 case Instruction::FPToUI: 3884 case Instruction::FPToSI: 3885 case Instruction::FPExt: 3886 case Instruction::PtrToInt: 3887 case Instruction::IntToPtr: 3888 case Instruction::SIToFP: 3889 case Instruction::UIToFP: 3890 case Instruction::Trunc: 3891 case Instruction::FPTrunc: 3892 case Instruction::BitCast: { 3893 Type *SrcTy = VL0->getOperand(0)->getType(); 3894 InstructionCost ScalarEltCost = 3895 TTI->getCastInstrCost(E->getOpcode(), ScalarTy, SrcTy, 3896 TTI::getCastContextHint(VL0), CostKind, VL0); 3897 if (NeedToShuffleReuses) { 3898 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3899 } 3900 3901 // Calculate the cost of this instruction. 3902 InstructionCost ScalarCost = VL.size() * ScalarEltCost; 3903 3904 auto *SrcVecTy = FixedVectorType::get(SrcTy, VL.size()); 3905 InstructionCost VecCost = 0; 3906 // Check if the values are candidates to demote. 3907 if (!MinBWs.count(VL0) || VecTy != SrcVecTy) { 3908 VecCost = 3909 ReuseShuffleCost + 3910 TTI->getCastInstrCost(E->getOpcode(), VecTy, SrcVecTy, 3911 TTI::getCastContextHint(VL0), CostKind, VL0); 3912 } 3913 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3914 return VecCost - ScalarCost; 3915 } 3916 case Instruction::FCmp: 3917 case Instruction::ICmp: 3918 case Instruction::Select: { 3919 // Calculate the cost of this instruction. 3920 InstructionCost ScalarEltCost = 3921 TTI->getCmpSelInstrCost(E->getOpcode(), ScalarTy, Builder.getInt1Ty(), 3922 CmpInst::BAD_ICMP_PREDICATE, CostKind, VL0); 3923 if (NeedToShuffleReuses) { 3924 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3925 } 3926 auto *MaskTy = FixedVectorType::get(Builder.getInt1Ty(), VL.size()); 3927 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3928 3929 // Check if all entries in VL are either compares or selects with compares 3930 // as condition that have the same predicates. 3931 CmpInst::Predicate VecPred = CmpInst::BAD_ICMP_PREDICATE; 3932 bool First = true; 3933 for (auto *V : VL) { 3934 CmpInst::Predicate CurrentPred; 3935 auto MatchCmp = m_Cmp(CurrentPred, m_Value(), m_Value()); 3936 if ((!match(V, m_Select(MatchCmp, m_Value(), m_Value())) && 3937 !match(V, MatchCmp)) || 3938 (!First && VecPred != CurrentPred)) { 3939 VecPred = CmpInst::BAD_ICMP_PREDICATE; 3940 break; 3941 } 3942 First = false; 3943 VecPred = CurrentPred; 3944 } 3945 3946 InstructionCost VecCost = TTI->getCmpSelInstrCost( 3947 E->getOpcode(), VecTy, MaskTy, VecPred, CostKind, VL0); 3948 // Check if it is possible and profitable to use min/max for selects in 3949 // VL. 3950 // 3951 auto IntrinsicAndUse = canConvertToMinOrMaxIntrinsic(VL); 3952 if (IntrinsicAndUse.first != Intrinsic::not_intrinsic) { 3953 IntrinsicCostAttributes CostAttrs(IntrinsicAndUse.first, VecTy, 3954 {VecTy, VecTy}); 3955 InstructionCost IntrinsicCost = 3956 TTI->getIntrinsicInstrCost(CostAttrs, CostKind); 3957 // If the selects are the only uses of the compares, they will be dead 3958 // and we can adjust the cost by removing their cost. 3959 if (IntrinsicAndUse.second) 3960 IntrinsicCost -= 3961 TTI->getCmpSelInstrCost(Instruction::ICmp, VecTy, MaskTy, 3962 CmpInst::BAD_ICMP_PREDICATE, CostKind); 3963 VecCost = std::min(VecCost, IntrinsicCost); 3964 } 3965 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3966 return ReuseShuffleCost + VecCost - ScalarCost; 3967 } 3968 case Instruction::FNeg: 3969 case Instruction::Add: 3970 case Instruction::FAdd: 3971 case Instruction::Sub: 3972 case Instruction::FSub: 3973 case Instruction::Mul: 3974 case Instruction::FMul: 3975 case Instruction::UDiv: 3976 case Instruction::SDiv: 3977 case Instruction::FDiv: 3978 case Instruction::URem: 3979 case Instruction::SRem: 3980 case Instruction::FRem: 3981 case Instruction::Shl: 3982 case Instruction::LShr: 3983 case Instruction::AShr: 3984 case Instruction::And: 3985 case Instruction::Or: 3986 case Instruction::Xor: { 3987 // Certain instructions can be cheaper to vectorize if they have a 3988 // constant second vector operand. 3989 TargetTransformInfo::OperandValueKind Op1VK = 3990 TargetTransformInfo::OK_AnyValue; 3991 TargetTransformInfo::OperandValueKind Op2VK = 3992 TargetTransformInfo::OK_UniformConstantValue; 3993 TargetTransformInfo::OperandValueProperties Op1VP = 3994 TargetTransformInfo::OP_None; 3995 TargetTransformInfo::OperandValueProperties Op2VP = 3996 TargetTransformInfo::OP_PowerOf2; 3997 3998 // If all operands are exactly the same ConstantInt then set the 3999 // operand kind to OK_UniformConstantValue. 4000 // If instead not all operands are constants, then set the operand kind 4001 // to OK_AnyValue. If all operands are constants but not the same, 4002 // then set the operand kind to OK_NonUniformConstantValue. 4003 ConstantInt *CInt0 = nullptr; 4004 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 4005 const Instruction *I = cast<Instruction>(VL[i]); 4006 unsigned OpIdx = isa<BinaryOperator>(I) ? 1 : 0; 4007 ConstantInt *CInt = dyn_cast<ConstantInt>(I->getOperand(OpIdx)); 4008 if (!CInt) { 4009 Op2VK = TargetTransformInfo::OK_AnyValue; 4010 Op2VP = TargetTransformInfo::OP_None; 4011 break; 4012 } 4013 if (Op2VP == TargetTransformInfo::OP_PowerOf2 && 4014 !CInt->getValue().isPowerOf2()) 4015 Op2VP = TargetTransformInfo::OP_None; 4016 if (i == 0) { 4017 CInt0 = CInt; 4018 continue; 4019 } 4020 if (CInt0 != CInt) 4021 Op2VK = TargetTransformInfo::OK_NonUniformConstantValue; 4022 } 4023 4024 SmallVector<const Value *, 4> Operands(VL0->operand_values()); 4025 InstructionCost ScalarEltCost = 4026 TTI->getArithmeticInstrCost(E->getOpcode(), ScalarTy, CostKind, Op1VK, 4027 Op2VK, Op1VP, Op2VP, Operands, VL0); 4028 if (NeedToShuffleReuses) { 4029 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 4030 } 4031 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 4032 InstructionCost VecCost = 4033 TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind, Op1VK, 4034 Op2VK, Op1VP, Op2VP, Operands, VL0); 4035 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 4036 return ReuseShuffleCost + VecCost - ScalarCost; 4037 } 4038 case Instruction::GetElementPtr: { 4039 TargetTransformInfo::OperandValueKind Op1VK = 4040 TargetTransformInfo::OK_AnyValue; 4041 TargetTransformInfo::OperandValueKind Op2VK = 4042 TargetTransformInfo::OK_UniformConstantValue; 4043 4044 InstructionCost ScalarEltCost = TTI->getArithmeticInstrCost( 4045 Instruction::Add, ScalarTy, CostKind, Op1VK, Op2VK); 4046 if (NeedToShuffleReuses) { 4047 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 4048 } 4049 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 4050 InstructionCost VecCost = TTI->getArithmeticInstrCost( 4051 Instruction::Add, VecTy, CostKind, Op1VK, Op2VK); 4052 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 4053 return ReuseShuffleCost + VecCost - ScalarCost; 4054 } 4055 case Instruction::Load: { 4056 // Cost of wide load - cost of scalar loads. 4057 Align alignment = cast<LoadInst>(VL0)->getAlign(); 4058 InstructionCost ScalarEltCost = TTI->getMemoryOpCost( 4059 Instruction::Load, ScalarTy, alignment, 0, CostKind, VL0); 4060 if (NeedToShuffleReuses) { 4061 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 4062 } 4063 InstructionCost ScalarLdCost = VecTy->getNumElements() * ScalarEltCost; 4064 InstructionCost VecLdCost; 4065 if (E->State == TreeEntry::Vectorize) { 4066 VecLdCost = TTI->getMemoryOpCost(Instruction::Load, VecTy, alignment, 0, 4067 CostKind, VL0); 4068 } else { 4069 assert(E->State == TreeEntry::ScatterVectorize && "Unknown EntryState"); 4070 VecLdCost = TTI->getGatherScatterOpCost( 4071 Instruction::Load, VecTy, cast<LoadInst>(VL0)->getPointerOperand(), 4072 /*VariableMask=*/false, alignment, CostKind, VL0); 4073 } 4074 if (!NeedToShuffleReuses && !E->ReorderIndices.empty()) { 4075 SmallVector<int> NewMask; 4076 inversePermutation(E->ReorderIndices, NewMask); 4077 VecLdCost += TTI->getShuffleCost( 4078 TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask); 4079 } 4080 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecLdCost, ScalarLdCost)); 4081 return ReuseShuffleCost + VecLdCost - ScalarLdCost; 4082 } 4083 case Instruction::Store: { 4084 // We know that we can merge the stores. Calculate the cost. 4085 bool IsReorder = !E->ReorderIndices.empty(); 4086 auto *SI = 4087 cast<StoreInst>(IsReorder ? VL[E->ReorderIndices.front()] : VL0); 4088 Align Alignment = SI->getAlign(); 4089 InstructionCost ScalarEltCost = TTI->getMemoryOpCost( 4090 Instruction::Store, ScalarTy, Alignment, 0, CostKind, VL0); 4091 InstructionCost ScalarStCost = VecTy->getNumElements() * ScalarEltCost; 4092 InstructionCost VecStCost = TTI->getMemoryOpCost( 4093 Instruction::Store, VecTy, Alignment, 0, CostKind, VL0); 4094 if (IsReorder) { 4095 SmallVector<int> NewMask; 4096 inversePermutation(E->ReorderIndices, NewMask); 4097 VecStCost += TTI->getShuffleCost( 4098 TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask); 4099 } 4100 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecStCost, ScalarStCost)); 4101 return VecStCost - ScalarStCost; 4102 } 4103 case Instruction::Call: { 4104 CallInst *CI = cast<CallInst>(VL0); 4105 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 4106 4107 // Calculate the cost of the scalar and vector calls. 4108 IntrinsicCostAttributes CostAttrs(ID, *CI, 1); 4109 InstructionCost ScalarEltCost = 4110 TTI->getIntrinsicInstrCost(CostAttrs, CostKind); 4111 if (NeedToShuffleReuses) { 4112 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 4113 } 4114 InstructionCost ScalarCallCost = VecTy->getNumElements() * ScalarEltCost; 4115 4116 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 4117 InstructionCost VecCallCost = 4118 std::min(VecCallCosts.first, VecCallCosts.second); 4119 4120 LLVM_DEBUG(dbgs() << "SLP: Call cost " << VecCallCost - ScalarCallCost 4121 << " (" << VecCallCost << "-" << ScalarCallCost << ")" 4122 << " for " << *CI << "\n"); 4123 4124 return ReuseShuffleCost + VecCallCost - ScalarCallCost; 4125 } 4126 case Instruction::ShuffleVector: { 4127 assert(E->isAltShuffle() && 4128 ((Instruction::isBinaryOp(E->getOpcode()) && 4129 Instruction::isBinaryOp(E->getAltOpcode())) || 4130 (Instruction::isCast(E->getOpcode()) && 4131 Instruction::isCast(E->getAltOpcode()))) && 4132 "Invalid Shuffle Vector Operand"); 4133 InstructionCost ScalarCost = 0; 4134 if (NeedToShuffleReuses) { 4135 for (unsigned Idx : E->ReuseShuffleIndices) { 4136 Instruction *I = cast<Instruction>(VL[Idx]); 4137 ReuseShuffleCost -= TTI->getInstructionCost(I, CostKind); 4138 } 4139 for (Value *V : VL) { 4140 Instruction *I = cast<Instruction>(V); 4141 ReuseShuffleCost += TTI->getInstructionCost(I, CostKind); 4142 } 4143 } 4144 for (Value *V : VL) { 4145 Instruction *I = cast<Instruction>(V); 4146 assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode"); 4147 ScalarCost += TTI->getInstructionCost(I, CostKind); 4148 } 4149 // VecCost is equal to sum of the cost of creating 2 vectors 4150 // and the cost of creating shuffle. 4151 InstructionCost VecCost = 0; 4152 if (Instruction::isBinaryOp(E->getOpcode())) { 4153 VecCost = TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind); 4154 VecCost += TTI->getArithmeticInstrCost(E->getAltOpcode(), VecTy, 4155 CostKind); 4156 } else { 4157 Type *Src0SclTy = E->getMainOp()->getOperand(0)->getType(); 4158 Type *Src1SclTy = E->getAltOp()->getOperand(0)->getType(); 4159 auto *Src0Ty = FixedVectorType::get(Src0SclTy, VL.size()); 4160 auto *Src1Ty = FixedVectorType::get(Src1SclTy, VL.size()); 4161 VecCost = TTI->getCastInstrCost(E->getOpcode(), VecTy, Src0Ty, 4162 TTI::CastContextHint::None, CostKind); 4163 VecCost += TTI->getCastInstrCost(E->getAltOpcode(), VecTy, Src1Ty, 4164 TTI::CastContextHint::None, CostKind); 4165 } 4166 4167 SmallVector<int> Mask(E->Scalars.size()); 4168 for (unsigned I = 0, End = E->Scalars.size(); I < End; ++I) { 4169 auto *OpInst = cast<Instruction>(E->Scalars[I]); 4170 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 4171 Mask[I] = I + (OpInst->getOpcode() == E->getAltOpcode() ? End : 0); 4172 } 4173 VecCost += 4174 TTI->getShuffleCost(TargetTransformInfo::SK_Select, VecTy, Mask, 0); 4175 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 4176 return ReuseShuffleCost + VecCost - ScalarCost; 4177 } 4178 default: 4179 llvm_unreachable("Unknown instruction"); 4180 } 4181 } 4182 4183 bool BoUpSLP::isFullyVectorizableTinyTree() const { 4184 LLVM_DEBUG(dbgs() << "SLP: Check whether the tree with height " 4185 << VectorizableTree.size() << " is fully vectorizable .\n"); 4186 4187 // We only handle trees of heights 1 and 2. 4188 if (VectorizableTree.size() == 1 && 4189 VectorizableTree[0]->State == TreeEntry::Vectorize) 4190 return true; 4191 4192 if (VectorizableTree.size() != 2) 4193 return false; 4194 4195 // Handle splat and all-constants stores. Also try to vectorize tiny trees 4196 // with the second gather nodes if they have less scalar operands rather than 4197 // the initial tree element (may be profitable to shuffle the second gather) 4198 // or they are extractelements, which form shuffle. 4199 SmallVector<int> Mask; 4200 if (VectorizableTree[0]->State == TreeEntry::Vectorize && 4201 (allConstant(VectorizableTree[1]->Scalars) || 4202 isSplat(VectorizableTree[1]->Scalars) || 4203 (VectorizableTree[1]->State == TreeEntry::NeedToGather && 4204 VectorizableTree[1]->Scalars.size() < 4205 VectorizableTree[0]->Scalars.size()) || 4206 (VectorizableTree[1]->State == TreeEntry::NeedToGather && 4207 VectorizableTree[1]->getOpcode() == Instruction::ExtractElement && 4208 isShuffle(VectorizableTree[1]->Scalars, Mask)))) 4209 return true; 4210 4211 // Gathering cost would be too much for tiny trees. 4212 if (VectorizableTree[0]->State == TreeEntry::NeedToGather || 4213 VectorizableTree[1]->State == TreeEntry::NeedToGather) 4214 return false; 4215 4216 return true; 4217 } 4218 4219 static bool isLoadCombineCandidateImpl(Value *Root, unsigned NumElts, 4220 TargetTransformInfo *TTI, 4221 bool MustMatchOrInst) { 4222 // Look past the root to find a source value. Arbitrarily follow the 4223 // path through operand 0 of any 'or'. Also, peek through optional 4224 // shift-left-by-multiple-of-8-bits. 4225 Value *ZextLoad = Root; 4226 const APInt *ShAmtC; 4227 bool FoundOr = false; 4228 while (!isa<ConstantExpr>(ZextLoad) && 4229 (match(ZextLoad, m_Or(m_Value(), m_Value())) || 4230 (match(ZextLoad, m_Shl(m_Value(), m_APInt(ShAmtC))) && 4231 ShAmtC->urem(8) == 0))) { 4232 auto *BinOp = cast<BinaryOperator>(ZextLoad); 4233 ZextLoad = BinOp->getOperand(0); 4234 if (BinOp->getOpcode() == Instruction::Or) 4235 FoundOr = true; 4236 } 4237 // Check if the input is an extended load of the required or/shift expression. 4238 Value *LoadPtr; 4239 if ((MustMatchOrInst && !FoundOr) || ZextLoad == Root || 4240 !match(ZextLoad, m_ZExt(m_Load(m_Value(LoadPtr))))) 4241 return false; 4242 4243 // Require that the total load bit width is a legal integer type. 4244 // For example, <8 x i8> --> i64 is a legal integer on a 64-bit target. 4245 // But <16 x i8> --> i128 is not, so the backend probably can't reduce it. 4246 Type *SrcTy = LoadPtr->getType()->getPointerElementType(); 4247 unsigned LoadBitWidth = SrcTy->getIntegerBitWidth() * NumElts; 4248 if (!TTI->isTypeLegal(IntegerType::get(Root->getContext(), LoadBitWidth))) 4249 return false; 4250 4251 // Everything matched - assume that we can fold the whole sequence using 4252 // load combining. 4253 LLVM_DEBUG(dbgs() << "SLP: Assume load combining for tree starting at " 4254 << *(cast<Instruction>(Root)) << "\n"); 4255 4256 return true; 4257 } 4258 4259 bool BoUpSLP::isLoadCombineReductionCandidate(RecurKind RdxKind) const { 4260 if (RdxKind != RecurKind::Or) 4261 return false; 4262 4263 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 4264 Value *FirstReduced = VectorizableTree[0]->Scalars[0]; 4265 return isLoadCombineCandidateImpl(FirstReduced, NumElts, TTI, 4266 /* MatchOr */ false); 4267 } 4268 4269 bool BoUpSLP::isLoadCombineCandidate() const { 4270 // Peek through a final sequence of stores and check if all operations are 4271 // likely to be load-combined. 4272 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 4273 for (Value *Scalar : VectorizableTree[0]->Scalars) { 4274 Value *X; 4275 if (!match(Scalar, m_Store(m_Value(X), m_Value())) || 4276 !isLoadCombineCandidateImpl(X, NumElts, TTI, /* MatchOr */ true)) 4277 return false; 4278 } 4279 return true; 4280 } 4281 4282 bool BoUpSLP::isTreeTinyAndNotFullyVectorizable() const { 4283 // No need to vectorize inserts of gathered values. 4284 if (VectorizableTree.size() == 2 && 4285 isa<InsertElementInst>(VectorizableTree[0]->Scalars[0]) && 4286 VectorizableTree[1]->State == TreeEntry::NeedToGather) 4287 return true; 4288 4289 // We can vectorize the tree if its size is greater than or equal to the 4290 // minimum size specified by the MinTreeSize command line option. 4291 if (VectorizableTree.size() >= MinTreeSize) 4292 return false; 4293 4294 // If we have a tiny tree (a tree whose size is less than MinTreeSize), we 4295 // can vectorize it if we can prove it fully vectorizable. 4296 if (isFullyVectorizableTinyTree()) 4297 return false; 4298 4299 assert(VectorizableTree.empty() 4300 ? ExternalUses.empty() 4301 : true && "We shouldn't have any external users"); 4302 4303 // Otherwise, we can't vectorize the tree. It is both tiny and not fully 4304 // vectorizable. 4305 return true; 4306 } 4307 4308 InstructionCost BoUpSLP::getSpillCost() const { 4309 // Walk from the bottom of the tree to the top, tracking which values are 4310 // live. When we see a call instruction that is not part of our tree, 4311 // query TTI to see if there is a cost to keeping values live over it 4312 // (for example, if spills and fills are required). 4313 unsigned BundleWidth = VectorizableTree.front()->Scalars.size(); 4314 InstructionCost Cost = 0; 4315 4316 SmallPtrSet<Instruction*, 4> LiveValues; 4317 Instruction *PrevInst = nullptr; 4318 4319 // The entries in VectorizableTree are not necessarily ordered by their 4320 // position in basic blocks. Collect them and order them by dominance so later 4321 // instructions are guaranteed to be visited first. For instructions in 4322 // different basic blocks, we only scan to the beginning of the block, so 4323 // their order does not matter, as long as all instructions in a basic block 4324 // are grouped together. Using dominance ensures a deterministic order. 4325 SmallVector<Instruction *, 16> OrderedScalars; 4326 for (const auto &TEPtr : VectorizableTree) { 4327 Instruction *Inst = dyn_cast<Instruction>(TEPtr->Scalars[0]); 4328 if (!Inst) 4329 continue; 4330 OrderedScalars.push_back(Inst); 4331 } 4332 llvm::sort(OrderedScalars, [&](Instruction *A, Instruction *B) { 4333 auto *NodeA = DT->getNode(A->getParent()); 4334 auto *NodeB = DT->getNode(B->getParent()); 4335 assert(NodeA && "Should only process reachable instructions"); 4336 assert(NodeB && "Should only process reachable instructions"); 4337 assert((NodeA == NodeB) == (NodeA->getDFSNumIn() == NodeB->getDFSNumIn()) && 4338 "Different nodes should have different DFS numbers"); 4339 if (NodeA != NodeB) 4340 return NodeA->getDFSNumIn() < NodeB->getDFSNumIn(); 4341 return B->comesBefore(A); 4342 }); 4343 4344 for (Instruction *Inst : OrderedScalars) { 4345 if (!PrevInst) { 4346 PrevInst = Inst; 4347 continue; 4348 } 4349 4350 // Update LiveValues. 4351 LiveValues.erase(PrevInst); 4352 for (auto &J : PrevInst->operands()) { 4353 if (isa<Instruction>(&*J) && getTreeEntry(&*J)) 4354 LiveValues.insert(cast<Instruction>(&*J)); 4355 } 4356 4357 LLVM_DEBUG({ 4358 dbgs() << "SLP: #LV: " << LiveValues.size(); 4359 for (auto *X : LiveValues) 4360 dbgs() << " " << X->getName(); 4361 dbgs() << ", Looking at "; 4362 Inst->dump(); 4363 }); 4364 4365 // Now find the sequence of instructions between PrevInst and Inst. 4366 unsigned NumCalls = 0; 4367 BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(), 4368 PrevInstIt = 4369 PrevInst->getIterator().getReverse(); 4370 while (InstIt != PrevInstIt) { 4371 if (PrevInstIt == PrevInst->getParent()->rend()) { 4372 PrevInstIt = Inst->getParent()->rbegin(); 4373 continue; 4374 } 4375 4376 // Debug information does not impact spill cost. 4377 if ((isa<CallInst>(&*PrevInstIt) && 4378 !isa<DbgInfoIntrinsic>(&*PrevInstIt)) && 4379 &*PrevInstIt != PrevInst) 4380 NumCalls++; 4381 4382 ++PrevInstIt; 4383 } 4384 4385 if (NumCalls) { 4386 SmallVector<Type*, 4> V; 4387 for (auto *II : LiveValues) { 4388 auto *ScalarTy = II->getType(); 4389 if (auto *VectorTy = dyn_cast<FixedVectorType>(ScalarTy)) 4390 ScalarTy = VectorTy->getElementType(); 4391 V.push_back(FixedVectorType::get(ScalarTy, BundleWidth)); 4392 } 4393 Cost += NumCalls * TTI->getCostOfKeepingLiveOverCall(V); 4394 } 4395 4396 PrevInst = Inst; 4397 } 4398 4399 return Cost; 4400 } 4401 4402 InstructionCost BoUpSLP::getTreeCost(ArrayRef<Value *> VectorizedVals) { 4403 InstructionCost Cost = 0; 4404 LLVM_DEBUG(dbgs() << "SLP: Calculating cost for tree of size " 4405 << VectorizableTree.size() << ".\n"); 4406 4407 unsigned BundleWidth = VectorizableTree[0]->Scalars.size(); 4408 4409 for (unsigned I = 0, E = VectorizableTree.size(); I < E; ++I) { 4410 TreeEntry &TE = *VectorizableTree[I].get(); 4411 4412 InstructionCost C = getEntryCost(&TE, VectorizedVals); 4413 Cost += C; 4414 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C 4415 << " for bundle that starts with " << *TE.Scalars[0] 4416 << ".\n" 4417 << "SLP: Current total cost = " << Cost << "\n"); 4418 } 4419 4420 SmallPtrSet<Value *, 16> ExtractCostCalculated; 4421 InstructionCost ExtractCost = 0; 4422 SmallBitVector IsIdentity; 4423 SmallVector<unsigned> VF; 4424 SmallVector<SmallVector<int>> ShuffleMask; 4425 SmallVector<Value *> FirstUsers; 4426 SmallVector<APInt> DemandedElts; 4427 for (ExternalUser &EU : ExternalUses) { 4428 // We only add extract cost once for the same scalar. 4429 if (!ExtractCostCalculated.insert(EU.Scalar).second) 4430 continue; 4431 4432 // Uses by ephemeral values are free (because the ephemeral value will be 4433 // removed prior to code generation, and so the extraction will be 4434 // removed as well). 4435 if (EphValues.count(EU.User)) 4436 continue; 4437 4438 // No extract cost for vector "scalar" 4439 if (isa<FixedVectorType>(EU.Scalar->getType())) 4440 continue; 4441 4442 // Already counted the cost for external uses when tried to adjust the cost 4443 // for extractelements, no need to add it again. 4444 if (isa<ExtractElementInst>(EU.Scalar)) 4445 continue; 4446 4447 // If found user is an insertelement, do not calculate extract cost but try 4448 // to detect it as a final shuffled/identity match. 4449 if (EU.User && isa<InsertElementInst>(EU.User)) { 4450 if (auto *FTy = dyn_cast<FixedVectorType>(EU.User->getType())) { 4451 Optional<int> InsertIdx = getInsertIndex(EU.User, 0); 4452 if (!InsertIdx || *InsertIdx == UndefMaskElem) 4453 continue; 4454 Value *VU = EU.User; 4455 auto *It = find_if(FirstUsers, [VU](Value *V) { 4456 // Checks if 2 insertelements are from the same buildvector. 4457 if (VU->getType() != V->getType()) 4458 return false; 4459 auto *IE1 = cast<InsertElementInst>(VU); 4460 auto *IE2 = cast<InsertElementInst>(V); 4461 // Go though of insertelement instructions trying to find either VU as 4462 // the original vector for IE2 or V as the original vector for IE1. 4463 do { 4464 if (IE1 == VU || IE2 == V) 4465 return true; 4466 if (IE1) 4467 IE1 = dyn_cast<InsertElementInst>(IE1->getOperand(0)); 4468 if (IE2) 4469 IE2 = dyn_cast<InsertElementInst>(IE2->getOperand(0)); 4470 } while (IE1 || IE2); 4471 return false; 4472 }); 4473 int VecId = -1; 4474 if (It == FirstUsers.end()) { 4475 VF.push_back(FTy->getNumElements()); 4476 ShuffleMask.emplace_back(VF.back(), UndefMaskElem); 4477 FirstUsers.push_back(EU.User); 4478 DemandedElts.push_back(APInt::getNullValue(VF.back())); 4479 IsIdentity.push_back(true); 4480 VecId = FirstUsers.size() - 1; 4481 } else { 4482 VecId = std::distance(FirstUsers.begin(), It); 4483 } 4484 int Idx = *InsertIdx; 4485 ShuffleMask[VecId][Idx] = EU.Lane; 4486 IsIdentity.set(IsIdentity.test(VecId) & 4487 (EU.Lane == Idx || EU.Lane == UndefMaskElem)); 4488 DemandedElts[VecId].setBit(Idx); 4489 } 4490 } 4491 4492 // If we plan to rewrite the tree in a smaller type, we will need to sign 4493 // extend the extracted value back to the original type. Here, we account 4494 // for the extract and the added cost of the sign extend if needed. 4495 auto *VecTy = FixedVectorType::get(EU.Scalar->getType(), BundleWidth); 4496 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 4497 if (MinBWs.count(ScalarRoot)) { 4498 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 4499 auto Extend = 4500 MinBWs[ScalarRoot].second ? Instruction::SExt : Instruction::ZExt; 4501 VecTy = FixedVectorType::get(MinTy, BundleWidth); 4502 ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(), 4503 VecTy, EU.Lane); 4504 } else { 4505 ExtractCost += 4506 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, EU.Lane); 4507 } 4508 } 4509 4510 InstructionCost SpillCost = getSpillCost(); 4511 Cost += SpillCost + ExtractCost; 4512 for (int I = 0, E = FirstUsers.size(); I < E; ++I) { 4513 if (!IsIdentity.test(I)) { 4514 InstructionCost C = TTI->getShuffleCost( 4515 TTI::SK_PermuteSingleSrc, 4516 cast<FixedVectorType>(FirstUsers[I]->getType()), ShuffleMask[I]); 4517 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C 4518 << " for final shuffle of insertelement external users " 4519 << *VectorizableTree.front()->Scalars.front() << ".\n" 4520 << "SLP: Current total cost = " << Cost << "\n"); 4521 Cost += C; 4522 } 4523 unsigned VF = ShuffleMask[I].size(); 4524 for (int &Mask : ShuffleMask[I]) 4525 Mask = (Mask == UndefMaskElem ? 0 : VF) + Mask; 4526 InstructionCost C = TTI->getShuffleCost( 4527 TTI::SK_PermuteTwoSrc, cast<FixedVectorType>(FirstUsers[I]->getType()), 4528 ShuffleMask[I]); 4529 LLVM_DEBUG( 4530 dbgs() 4531 << "SLP: Adding cost " << C 4532 << " for final shuffle of vector node and external insertelement users " 4533 << *VectorizableTree.front()->Scalars.front() << ".\n" 4534 << "SLP: Current total cost = " << Cost << "\n"); 4535 Cost += C; 4536 InstructionCost InsertCost = TTI->getScalarizationOverhead( 4537 cast<FixedVectorType>(FirstUsers[I]->getType()), DemandedElts[I], 4538 /*Insert*/ true, 4539 /*Extract*/ false); 4540 Cost -= InsertCost; 4541 LLVM_DEBUG(dbgs() << "SLP: subtracting the cost " << InsertCost 4542 << " for insertelements gather.\n" 4543 << "SLP: Current total cost = " << Cost << "\n"); 4544 } 4545 4546 #ifndef NDEBUG 4547 SmallString<256> Str; 4548 { 4549 raw_svector_ostream OS(Str); 4550 OS << "SLP: Spill Cost = " << SpillCost << ".\n" 4551 << "SLP: Extract Cost = " << ExtractCost << ".\n" 4552 << "SLP: Total Cost = " << Cost << ".\n"; 4553 } 4554 LLVM_DEBUG(dbgs() << Str); 4555 if (ViewSLPTree) 4556 ViewGraph(this, "SLP" + F->getName(), false, Str); 4557 #endif 4558 4559 return Cost; 4560 } 4561 4562 Optional<TargetTransformInfo::ShuffleKind> 4563 BoUpSLP::isGatherShuffledEntry(const TreeEntry *TE, SmallVectorImpl<int> &Mask, 4564 SmallVectorImpl<const TreeEntry *> &Entries) { 4565 // TODO: currently checking only for Scalars in the tree entry, need to count 4566 // reused elements too for better cost estimation. 4567 Mask.assign(TE->Scalars.size(), UndefMaskElem); 4568 Entries.clear(); 4569 // Build a lists of values to tree entries. 4570 DenseMap<Value *, SmallPtrSet<const TreeEntry *, 4>> ValueToTEs; 4571 for (const std::unique_ptr<TreeEntry> &EntryPtr : VectorizableTree) { 4572 if (EntryPtr.get() == TE) 4573 break; 4574 if (EntryPtr->State != TreeEntry::NeedToGather) 4575 continue; 4576 for (Value *V : EntryPtr->Scalars) 4577 ValueToTEs.try_emplace(V).first->getSecond().insert(EntryPtr.get()); 4578 } 4579 // Find all tree entries used by the gathered values. If no common entries 4580 // found - not a shuffle. 4581 // Here we build a set of tree nodes for each gathered value and trying to 4582 // find the intersection between these sets. If we have at least one common 4583 // tree node for each gathered value - we have just a permutation of the 4584 // single vector. If we have 2 different sets, we're in situation where we 4585 // have a permutation of 2 input vectors. 4586 SmallVector<SmallPtrSet<const TreeEntry *, 4>> UsedTEs; 4587 DenseMap<Value *, int> UsedValuesEntry; 4588 for (Value *V : TE->Scalars) { 4589 if (isa<UndefValue>(V)) 4590 continue; 4591 // Build a list of tree entries where V is used. 4592 SmallPtrSet<const TreeEntry *, 4> VToTEs; 4593 auto It = ValueToTEs.find(V); 4594 if (It != ValueToTEs.end()) 4595 VToTEs = It->second; 4596 if (const TreeEntry *VTE = getTreeEntry(V)) 4597 VToTEs.insert(VTE); 4598 if (VToTEs.empty()) 4599 return None; 4600 if (UsedTEs.empty()) { 4601 // The first iteration, just insert the list of nodes to vector. 4602 UsedTEs.push_back(VToTEs); 4603 } else { 4604 // Need to check if there are any previously used tree nodes which use V. 4605 // If there are no such nodes, consider that we have another one input 4606 // vector. 4607 SmallPtrSet<const TreeEntry *, 4> SavedVToTEs(VToTEs); 4608 unsigned Idx = 0; 4609 for (SmallPtrSet<const TreeEntry *, 4> &Set : UsedTEs) { 4610 // Do we have a non-empty intersection of previously listed tree entries 4611 // and tree entries using current V? 4612 set_intersect(VToTEs, Set); 4613 if (!VToTEs.empty()) { 4614 // Yes, write the new subset and continue analysis for the next 4615 // scalar. 4616 Set.swap(VToTEs); 4617 break; 4618 } 4619 VToTEs = SavedVToTEs; 4620 ++Idx; 4621 } 4622 // No non-empty intersection found - need to add a second set of possible 4623 // source vectors. 4624 if (Idx == UsedTEs.size()) { 4625 // If the number of input vectors is greater than 2 - not a permutation, 4626 // fallback to the regular gather. 4627 if (UsedTEs.size() == 2) 4628 return None; 4629 UsedTEs.push_back(SavedVToTEs); 4630 Idx = UsedTEs.size() - 1; 4631 } 4632 UsedValuesEntry.try_emplace(V, Idx); 4633 } 4634 } 4635 4636 unsigned VF = 0; 4637 if (UsedTEs.size() == 1) { 4638 // Try to find the perfect match in another gather node at first. 4639 auto It = find_if(UsedTEs.front(), [TE](const TreeEntry *EntryPtr) { 4640 return EntryPtr->isSame(TE->Scalars); 4641 }); 4642 if (It != UsedTEs.front().end()) { 4643 Entries.push_back(*It); 4644 std::iota(Mask.begin(), Mask.end(), 0); 4645 return TargetTransformInfo::SK_PermuteSingleSrc; 4646 } 4647 // No perfect match, just shuffle, so choose the first tree node. 4648 Entries.push_back(*UsedTEs.front().begin()); 4649 } else { 4650 // Try to find nodes with the same vector factor. 4651 assert(UsedTEs.size() == 2 && "Expected at max 2 permuted entries."); 4652 // FIXME: Shall be replaced by GetVF function once non-power-2 patch is 4653 // landed. 4654 auto &&GetVF = [](const TreeEntry *TE) { 4655 if (!TE->ReuseShuffleIndices.empty()) 4656 return TE->ReuseShuffleIndices.size(); 4657 return TE->Scalars.size(); 4658 }; 4659 DenseMap<int, const TreeEntry *> VFToTE; 4660 for (const TreeEntry *TE : UsedTEs.front()) 4661 VFToTE.try_emplace(GetVF(TE), TE); 4662 for (const TreeEntry *TE : UsedTEs.back()) { 4663 auto It = VFToTE.find(GetVF(TE)); 4664 if (It != VFToTE.end()) { 4665 VF = It->first; 4666 Entries.push_back(It->second); 4667 Entries.push_back(TE); 4668 break; 4669 } 4670 } 4671 // No 2 source vectors with the same vector factor - give up and do regular 4672 // gather. 4673 if (Entries.empty()) 4674 return None; 4675 } 4676 4677 // Build a shuffle mask for better cost estimation and vector emission. 4678 for (int I = 0, E = TE->Scalars.size(); I < E; ++I) { 4679 Value *V = TE->Scalars[I]; 4680 if (isa<UndefValue>(V)) 4681 continue; 4682 unsigned Idx = UsedValuesEntry.lookup(V); 4683 const TreeEntry *VTE = Entries[Idx]; 4684 int FoundLane = findLaneForValue(VTE->Scalars, VTE->ReuseShuffleIndices, V); 4685 Mask[I] = Idx * VF + FoundLane; 4686 // Extra check required by isSingleSourceMaskImpl function (called by 4687 // ShuffleVectorInst::isSingleSourceMask). 4688 if (Mask[I] >= 2 * E) 4689 return None; 4690 } 4691 switch (Entries.size()) { 4692 case 1: 4693 return TargetTransformInfo::SK_PermuteSingleSrc; 4694 case 2: 4695 return TargetTransformInfo::SK_PermuteTwoSrc; 4696 default: 4697 break; 4698 } 4699 return None; 4700 } 4701 4702 InstructionCost 4703 BoUpSLP::getGatherCost(FixedVectorType *Ty, 4704 const DenseSet<unsigned> &ShuffledIndices) const { 4705 unsigned NumElts = Ty->getNumElements(); 4706 APInt DemandedElts = APInt::getNullValue(NumElts); 4707 for (unsigned I = 0; I < NumElts; ++I) 4708 if (!ShuffledIndices.count(I)) 4709 DemandedElts.setBit(I); 4710 InstructionCost Cost = 4711 TTI->getScalarizationOverhead(Ty, DemandedElts, /*Insert*/ true, 4712 /*Extract*/ false); 4713 if (!ShuffledIndices.empty()) 4714 Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, Ty); 4715 return Cost; 4716 } 4717 4718 InstructionCost BoUpSLP::getGatherCost(ArrayRef<Value *> VL) const { 4719 // Find the type of the operands in VL. 4720 Type *ScalarTy = VL[0]->getType(); 4721 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 4722 ScalarTy = SI->getValueOperand()->getType(); 4723 auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); 4724 // Find the cost of inserting/extracting values from the vector. 4725 // Check if the same elements are inserted several times and count them as 4726 // shuffle candidates. 4727 DenseSet<unsigned> ShuffledElements; 4728 DenseSet<Value *> UniqueElements; 4729 // Iterate in reverse order to consider insert elements with the high cost. 4730 for (unsigned I = VL.size(); I > 0; --I) { 4731 unsigned Idx = I - 1; 4732 if (isConstant(VL[Idx])) 4733 continue; 4734 if (!UniqueElements.insert(VL[Idx]).second) 4735 ShuffledElements.insert(Idx); 4736 } 4737 return getGatherCost(VecTy, ShuffledElements); 4738 } 4739 4740 // Perform operand reordering on the instructions in VL and return the reordered 4741 // operands in Left and Right. 4742 void BoUpSLP::reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 4743 SmallVectorImpl<Value *> &Left, 4744 SmallVectorImpl<Value *> &Right, 4745 const DataLayout &DL, 4746 ScalarEvolution &SE, 4747 const BoUpSLP &R) { 4748 if (VL.empty()) 4749 return; 4750 VLOperands Ops(VL, DL, SE, R); 4751 // Reorder the operands in place. 4752 Ops.reorder(); 4753 Left = Ops.getVL(0); 4754 Right = Ops.getVL(1); 4755 } 4756 4757 void BoUpSLP::setInsertPointAfterBundle(const TreeEntry *E) { 4758 // Get the basic block this bundle is in. All instructions in the bundle 4759 // should be in this block. 4760 auto *Front = E->getMainOp(); 4761 auto *BB = Front->getParent(); 4762 assert(llvm::all_of(E->Scalars, [=](Value *V) -> bool { 4763 auto *I = cast<Instruction>(V); 4764 return !E->isOpcodeOrAlt(I) || I->getParent() == BB; 4765 })); 4766 4767 // The last instruction in the bundle in program order. 4768 Instruction *LastInst = nullptr; 4769 4770 // Find the last instruction. The common case should be that BB has been 4771 // scheduled, and the last instruction is VL.back(). So we start with 4772 // VL.back() and iterate over schedule data until we reach the end of the 4773 // bundle. The end of the bundle is marked by null ScheduleData. 4774 if (BlocksSchedules.count(BB)) { 4775 auto *Bundle = 4776 BlocksSchedules[BB]->getScheduleData(E->isOneOf(E->Scalars.back())); 4777 if (Bundle && Bundle->isPartOfBundle()) 4778 for (; Bundle; Bundle = Bundle->NextInBundle) 4779 if (Bundle->OpValue == Bundle->Inst) 4780 LastInst = Bundle->Inst; 4781 } 4782 4783 // LastInst can still be null at this point if there's either not an entry 4784 // for BB in BlocksSchedules or there's no ScheduleData available for 4785 // VL.back(). This can be the case if buildTree_rec aborts for various 4786 // reasons (e.g., the maximum recursion depth is reached, the maximum region 4787 // size is reached, etc.). ScheduleData is initialized in the scheduling 4788 // "dry-run". 4789 // 4790 // If this happens, we can still find the last instruction by brute force. We 4791 // iterate forwards from Front (inclusive) until we either see all 4792 // instructions in the bundle or reach the end of the block. If Front is the 4793 // last instruction in program order, LastInst will be set to Front, and we 4794 // will visit all the remaining instructions in the block. 4795 // 4796 // One of the reasons we exit early from buildTree_rec is to place an upper 4797 // bound on compile-time. Thus, taking an additional compile-time hit here is 4798 // not ideal. However, this should be exceedingly rare since it requires that 4799 // we both exit early from buildTree_rec and that the bundle be out-of-order 4800 // (causing us to iterate all the way to the end of the block). 4801 if (!LastInst) { 4802 SmallPtrSet<Value *, 16> Bundle(E->Scalars.begin(), E->Scalars.end()); 4803 for (auto &I : make_range(BasicBlock::iterator(Front), BB->end())) { 4804 if (Bundle.erase(&I) && E->isOpcodeOrAlt(&I)) 4805 LastInst = &I; 4806 if (Bundle.empty()) 4807 break; 4808 } 4809 } 4810 assert(LastInst && "Failed to find last instruction in bundle"); 4811 4812 // Set the insertion point after the last instruction in the bundle. Set the 4813 // debug location to Front. 4814 Builder.SetInsertPoint(BB, ++LastInst->getIterator()); 4815 Builder.SetCurrentDebugLocation(Front->getDebugLoc()); 4816 } 4817 4818 Value *BoUpSLP::gather(ArrayRef<Value *> VL) { 4819 // List of instructions/lanes from current block and/or the blocks which are 4820 // part of the current loop. These instructions will be inserted at the end to 4821 // make it possible to optimize loops and hoist invariant instructions out of 4822 // the loops body with better chances for success. 4823 SmallVector<std::pair<Value *, unsigned>, 4> PostponedInsts; 4824 SmallSet<int, 4> PostponedIndices; 4825 Loop *L = LI->getLoopFor(Builder.GetInsertBlock()); 4826 auto &&CheckPredecessor = [](BasicBlock *InstBB, BasicBlock *InsertBB) { 4827 SmallPtrSet<BasicBlock *, 4> Visited; 4828 while (InsertBB && InsertBB != InstBB && Visited.insert(InsertBB).second) 4829 InsertBB = InsertBB->getSinglePredecessor(); 4830 return InsertBB && InsertBB == InstBB; 4831 }; 4832 for (int I = 0, E = VL.size(); I < E; ++I) { 4833 if (auto *Inst = dyn_cast<Instruction>(VL[I])) 4834 if ((CheckPredecessor(Inst->getParent(), Builder.GetInsertBlock()) || 4835 getTreeEntry(Inst) || (L && (L->contains(Inst)))) && 4836 PostponedIndices.insert(I).second) 4837 PostponedInsts.emplace_back(Inst, I); 4838 } 4839 4840 auto &&CreateInsertElement = [this](Value *Vec, Value *V, unsigned Pos) { 4841 Vec = Builder.CreateInsertElement(Vec, V, Builder.getInt32(Pos)); 4842 auto *InsElt = dyn_cast<InsertElementInst>(Vec); 4843 if (!InsElt) 4844 return Vec; 4845 GatherSeq.insert(InsElt); 4846 CSEBlocks.insert(InsElt->getParent()); 4847 // Add to our 'need-to-extract' list. 4848 if (TreeEntry *Entry = getTreeEntry(V)) { 4849 // Find which lane we need to extract. 4850 unsigned FoundLane = 4851 std::distance(Entry->Scalars.begin(), find(Entry->Scalars, V)); 4852 assert(FoundLane < Entry->Scalars.size() && "Couldn't find extract lane"); 4853 if (!Entry->ReuseShuffleIndices.empty()) { 4854 FoundLane = std::distance(Entry->ReuseShuffleIndices.begin(), 4855 find(Entry->ReuseShuffleIndices, FoundLane)); 4856 } 4857 ExternalUses.emplace_back(V, InsElt, FoundLane); 4858 } 4859 return Vec; 4860 }; 4861 Value *Val0 = 4862 isa<StoreInst>(VL[0]) ? cast<StoreInst>(VL[0])->getValueOperand() : VL[0]; 4863 FixedVectorType *VecTy = FixedVectorType::get(Val0->getType(), VL.size()); 4864 Value *Vec = PoisonValue::get(VecTy); 4865 SmallVector<int> NonConsts; 4866 // Insert constant values at first. 4867 for (int I = 0, E = VL.size(); I < E; ++I) { 4868 if (PostponedIndices.contains(I)) 4869 continue; 4870 if (!isConstant(VL[I])) { 4871 NonConsts.push_back(I); 4872 continue; 4873 } 4874 Vec = CreateInsertElement(Vec, VL[I], I); 4875 } 4876 // Insert non-constant values. 4877 for (int I : NonConsts) 4878 Vec = CreateInsertElement(Vec, VL[I], I); 4879 // Append instructions, which are/may be part of the loop, in the end to make 4880 // it possible to hoist non-loop-based instructions. 4881 for (const std::pair<Value *, unsigned> &Pair : PostponedInsts) 4882 Vec = CreateInsertElement(Vec, Pair.first, Pair.second); 4883 4884 return Vec; 4885 } 4886 4887 namespace { 4888 /// Merges shuffle masks and emits final shuffle instruction, if required. 4889 class ShuffleInstructionBuilder { 4890 IRBuilderBase &Builder; 4891 const unsigned VF = 0; 4892 bool IsFinalized = false; 4893 SmallVector<int, 4> Mask; 4894 4895 public: 4896 ShuffleInstructionBuilder(IRBuilderBase &Builder, unsigned VF) 4897 : Builder(Builder), VF(VF) {} 4898 4899 /// Adds a mask, inverting it before applying. 4900 void addInversedMask(ArrayRef<unsigned> SubMask) { 4901 if (SubMask.empty()) 4902 return; 4903 SmallVector<int, 4> NewMask; 4904 inversePermutation(SubMask, NewMask); 4905 addMask(NewMask); 4906 } 4907 4908 /// Functions adds masks, merging them into single one. 4909 void addMask(ArrayRef<unsigned> SubMask) { 4910 SmallVector<int, 4> NewMask(SubMask.begin(), SubMask.end()); 4911 addMask(NewMask); 4912 } 4913 4914 void addMask(ArrayRef<int> SubMask) { 4915 if (SubMask.empty()) 4916 return; 4917 if (Mask.empty()) { 4918 Mask.append(SubMask.begin(), SubMask.end()); 4919 return; 4920 } 4921 SmallVector<int, 4> NewMask(SubMask.size(), SubMask.size()); 4922 int TermValue = std::min(Mask.size(), SubMask.size()); 4923 for (int I = 0, E = SubMask.size(); I < E; ++I) { 4924 if (SubMask[I] >= TermValue || SubMask[I] == UndefMaskElem || 4925 Mask[SubMask[I]] >= TermValue) { 4926 NewMask[I] = UndefMaskElem; 4927 continue; 4928 } 4929 NewMask[I] = Mask[SubMask[I]]; 4930 } 4931 Mask.swap(NewMask); 4932 } 4933 4934 Value *finalize(Value *V) { 4935 IsFinalized = true; 4936 unsigned ValueVF = cast<FixedVectorType>(V->getType())->getNumElements(); 4937 if (VF == ValueVF && Mask.empty()) 4938 return V; 4939 SmallVector<int, 4> NormalizedMask(VF, UndefMaskElem); 4940 std::iota(NormalizedMask.begin(), NormalizedMask.end(), 0); 4941 addMask(NormalizedMask); 4942 4943 if (VF == ValueVF && ShuffleVectorInst::isIdentityMask(Mask)) 4944 return V; 4945 return Builder.CreateShuffleVector(V, Mask, "shuffle"); 4946 } 4947 4948 ~ShuffleInstructionBuilder() { 4949 assert((IsFinalized || Mask.empty()) && 4950 "Shuffle construction must be finalized."); 4951 } 4952 }; 4953 } // namespace 4954 4955 Value *BoUpSLP::vectorizeTree(ArrayRef<Value *> VL) { 4956 unsigned VF = VL.size(); 4957 InstructionsState S = getSameOpcode(VL); 4958 if (S.getOpcode()) { 4959 if (TreeEntry *E = getTreeEntry(S.OpValue)) 4960 if (E->isSame(VL)) { 4961 Value *V = vectorizeTree(E); 4962 if (VF != cast<FixedVectorType>(V->getType())->getNumElements()) { 4963 if (!E->ReuseShuffleIndices.empty()) { 4964 // Reshuffle to get only unique values. 4965 // If some of the scalars are duplicated in the vectorization tree 4966 // entry, we do not vectorize them but instead generate a mask for 4967 // the reuses. But if there are several users of the same entry, 4968 // they may have different vectorization factors. This is especially 4969 // important for PHI nodes. In this case, we need to adapt the 4970 // resulting instruction for the user vectorization factor and have 4971 // to reshuffle it again to take only unique elements of the vector. 4972 // Without this code the function incorrectly returns reduced vector 4973 // instruction with the same elements, not with the unique ones. 4974 4975 // block: 4976 // %phi = phi <2 x > { .., %entry} {%shuffle, %block} 4977 // %2 = shuffle <2 x > %phi, %poison, <4 x > <0, 0, 1, 1> 4978 // ... (use %2) 4979 // %shuffle = shuffle <2 x> %2, poison, <2 x> {0, 2} 4980 // br %block 4981 SmallVector<int> UniqueIdxs; 4982 SmallSet<int, 4> UsedIdxs; 4983 int Pos = 0; 4984 int Sz = VL.size(); 4985 for (int Idx : E->ReuseShuffleIndices) { 4986 if (Idx != Sz && UsedIdxs.insert(Idx).second) 4987 UniqueIdxs.emplace_back(Pos); 4988 ++Pos; 4989 } 4990 assert(VF >= UsedIdxs.size() && "Expected vectorization factor " 4991 "less than original vector size."); 4992 UniqueIdxs.append(VF - UsedIdxs.size(), UndefMaskElem); 4993 V = Builder.CreateShuffleVector(V, UniqueIdxs, "shrink.shuffle"); 4994 } else { 4995 assert(VF < cast<FixedVectorType>(V->getType())->getNumElements() && 4996 "Expected vectorization factor less " 4997 "than original vector size."); 4998 SmallVector<int> UniformMask(VF, 0); 4999 std::iota(UniformMask.begin(), UniformMask.end(), 0); 5000 V = Builder.CreateShuffleVector(V, UniformMask, "shrink.shuffle"); 5001 } 5002 } 5003 return V; 5004 } 5005 } 5006 5007 // Check that every instruction appears once in this bundle. 5008 SmallVector<int> ReuseShuffleIndicies; 5009 SmallVector<Value *> UniqueValues; 5010 if (VL.size() > 2) { 5011 DenseMap<Value *, unsigned> UniquePositions; 5012 unsigned NumValues = 5013 std::distance(VL.begin(), find_if(reverse(VL), [](Value *V) { 5014 return !isa<UndefValue>(V); 5015 }).base()); 5016 VF = std::max<unsigned>(VF, PowerOf2Ceil(NumValues)); 5017 int UniqueVals = 0; 5018 bool HasUndefs = false; 5019 for (Value *V : VL.drop_back(VL.size() - VF)) { 5020 if (isa<UndefValue>(V)) { 5021 ReuseShuffleIndicies.emplace_back(UndefMaskElem); 5022 HasUndefs = true; 5023 continue; 5024 } 5025 if (isConstant(V)) { 5026 ReuseShuffleIndicies.emplace_back(UniqueValues.size()); 5027 UniqueValues.emplace_back(V); 5028 continue; 5029 } 5030 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 5031 ReuseShuffleIndicies.emplace_back(Res.first->second); 5032 if (Res.second) { 5033 UniqueValues.emplace_back(V); 5034 ++UniqueVals; 5035 } 5036 } 5037 if (HasUndefs && UniqueVals == 1 && UniqueValues.size() == 1) { 5038 // Emit pure splat vector. 5039 // FIXME: why it is not identified as an identity. 5040 unsigned NumUndefs = count(ReuseShuffleIndicies, UndefMaskElem); 5041 if (NumUndefs == ReuseShuffleIndicies.size() - 1) 5042 ReuseShuffleIndicies.append(VF - ReuseShuffleIndicies.size(), 5043 UndefMaskElem); 5044 else 5045 ReuseShuffleIndicies.assign(VF, 0); 5046 } else if (UniqueValues.size() >= VF - 1 || UniqueValues.size() <= 1) { 5047 ReuseShuffleIndicies.clear(); 5048 UniqueValues.clear(); 5049 UniqueValues.append(VL.begin(), std::next(VL.begin(), NumValues)); 5050 } 5051 UniqueValues.append(VF - UniqueValues.size(), 5052 PoisonValue::get(VL[0]->getType())); 5053 VL = UniqueValues; 5054 } 5055 5056 ShuffleInstructionBuilder ShuffleBuilder(Builder, VF); 5057 Value *Vec = gather(VL); 5058 if (!ReuseShuffleIndicies.empty()) { 5059 ShuffleBuilder.addMask(ReuseShuffleIndicies); 5060 Vec = ShuffleBuilder.finalize(Vec); 5061 if (auto *I = dyn_cast<Instruction>(Vec)) { 5062 GatherSeq.insert(I); 5063 CSEBlocks.insert(I->getParent()); 5064 } 5065 } 5066 return Vec; 5067 } 5068 5069 Value *BoUpSLP::vectorizeTree(TreeEntry *E) { 5070 IRBuilder<>::InsertPointGuard Guard(Builder); 5071 5072 if (E->VectorizedValue) { 5073 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *E->Scalars[0] << ".\n"); 5074 return E->VectorizedValue; 5075 } 5076 5077 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 5078 unsigned VF = E->Scalars.size(); 5079 if (NeedToShuffleReuses) 5080 VF = E->ReuseShuffleIndices.size(); 5081 ShuffleInstructionBuilder ShuffleBuilder(Builder, VF); 5082 if (E->State == TreeEntry::NeedToGather) { 5083 setInsertPointAfterBundle(E); 5084 Value *Vec; 5085 SmallVector<int> Mask; 5086 SmallVector<const TreeEntry *> Entries; 5087 Optional<TargetTransformInfo::ShuffleKind> Shuffle = 5088 isGatherShuffledEntry(E, Mask, Entries); 5089 if (Shuffle.hasValue()) { 5090 assert((Entries.size() == 1 || Entries.size() == 2) && 5091 "Expected shuffle of 1 or 2 entries."); 5092 Vec = Builder.CreateShuffleVector(Entries.front()->VectorizedValue, 5093 Entries.back()->VectorizedValue, Mask); 5094 } else { 5095 Vec = gather(E->Scalars); 5096 } 5097 if (NeedToShuffleReuses) { 5098 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5099 Vec = ShuffleBuilder.finalize(Vec); 5100 if (auto *I = dyn_cast<Instruction>(Vec)) { 5101 GatherSeq.insert(I); 5102 CSEBlocks.insert(I->getParent()); 5103 } 5104 } 5105 E->VectorizedValue = Vec; 5106 return Vec; 5107 } 5108 5109 assert((E->State == TreeEntry::Vectorize || 5110 E->State == TreeEntry::ScatterVectorize) && 5111 "Unhandled state"); 5112 unsigned ShuffleOrOp = 5113 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 5114 Instruction *VL0 = E->getMainOp(); 5115 Type *ScalarTy = VL0->getType(); 5116 if (auto *Store = dyn_cast<StoreInst>(VL0)) 5117 ScalarTy = Store->getValueOperand()->getType(); 5118 else if (auto *IE = dyn_cast<InsertElementInst>(VL0)) 5119 ScalarTy = IE->getOperand(1)->getType(); 5120 auto *VecTy = FixedVectorType::get(ScalarTy, E->Scalars.size()); 5121 switch (ShuffleOrOp) { 5122 case Instruction::PHI: { 5123 auto *PH = cast<PHINode>(VL0); 5124 Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI()); 5125 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 5126 PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues()); 5127 Value *V = NewPhi; 5128 if (NeedToShuffleReuses) 5129 V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle"); 5130 5131 E->VectorizedValue = V; 5132 5133 // PHINodes may have multiple entries from the same block. We want to 5134 // visit every block once. 5135 SmallPtrSet<BasicBlock*, 4> VisitedBBs; 5136 5137 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 5138 ValueList Operands; 5139 BasicBlock *IBB = PH->getIncomingBlock(i); 5140 5141 if (!VisitedBBs.insert(IBB).second) { 5142 NewPhi->addIncoming(NewPhi->getIncomingValueForBlock(IBB), IBB); 5143 continue; 5144 } 5145 5146 Builder.SetInsertPoint(IBB->getTerminator()); 5147 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 5148 Value *Vec = vectorizeTree(E->getOperand(i)); 5149 NewPhi->addIncoming(Vec, IBB); 5150 } 5151 5152 assert(NewPhi->getNumIncomingValues() == PH->getNumIncomingValues() && 5153 "Invalid number of incoming values"); 5154 return V; 5155 } 5156 5157 case Instruction::ExtractElement: { 5158 Value *V = E->getSingleOperand(0); 5159 Builder.SetInsertPoint(VL0); 5160 ShuffleBuilder.addInversedMask(E->ReorderIndices); 5161 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5162 V = ShuffleBuilder.finalize(V); 5163 E->VectorizedValue = V; 5164 return V; 5165 } 5166 case Instruction::ExtractValue: { 5167 auto *LI = cast<LoadInst>(E->getSingleOperand(0)); 5168 Builder.SetInsertPoint(LI); 5169 auto *PtrTy = PointerType::get(VecTy, LI->getPointerAddressSpace()); 5170 Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy); 5171 LoadInst *V = Builder.CreateAlignedLoad(VecTy, Ptr, LI->getAlign()); 5172 Value *NewV = propagateMetadata(V, E->Scalars); 5173 ShuffleBuilder.addInversedMask(E->ReorderIndices); 5174 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5175 NewV = ShuffleBuilder.finalize(NewV); 5176 E->VectorizedValue = NewV; 5177 return NewV; 5178 } 5179 case Instruction::InsertElement: { 5180 Builder.SetInsertPoint(VL0); 5181 Value *V = vectorizeTree(E->getOperand(1)); 5182 5183 const unsigned NumElts = 5184 cast<FixedVectorType>(VL0->getType())->getNumElements(); 5185 const unsigned NumScalars = E->Scalars.size(); 5186 5187 // Create InsertVector shuffle if necessary 5188 Instruction *FirstInsert = nullptr; 5189 bool IsIdentity = true; 5190 unsigned Offset = UINT_MAX; 5191 for (unsigned I = 0; I < NumScalars; ++I) { 5192 Value *Scalar = E->Scalars[I]; 5193 if (!FirstInsert && 5194 !is_contained(E->Scalars, cast<Instruction>(Scalar)->getOperand(0))) 5195 FirstInsert = cast<Instruction>(Scalar); 5196 Optional<int> InsertIdx = getInsertIndex(Scalar, 0); 5197 if (!InsertIdx || *InsertIdx == UndefMaskElem) 5198 continue; 5199 unsigned Idx = *InsertIdx; 5200 if (Idx < Offset) { 5201 Offset = Idx; 5202 IsIdentity &= I == 0; 5203 } else { 5204 assert(Idx >= Offset && "Failed to find vector index offset"); 5205 IsIdentity &= Idx - Offset == I; 5206 } 5207 } 5208 assert(Offset < NumElts && "Failed to find vector index offset"); 5209 5210 // Create shuffle to resize vector 5211 SmallVector<int> Mask(NumElts, UndefMaskElem); 5212 if (!IsIdentity) { 5213 for (unsigned I = 0; I < NumScalars; ++I) { 5214 Value *Scalar = E->Scalars[I]; 5215 Optional<int> InsertIdx = getInsertIndex(Scalar, 0); 5216 if (!InsertIdx || *InsertIdx == UndefMaskElem) 5217 continue; 5218 Mask[*InsertIdx - Offset] = I; 5219 } 5220 } else { 5221 std::iota(Mask.begin(), std::next(Mask.begin(), NumScalars), 0); 5222 } 5223 if (!IsIdentity || NumElts != NumScalars) 5224 V = Builder.CreateShuffleVector(V, Mask); 5225 5226 if (NumElts != NumScalars) { 5227 SmallVector<int> InsertMask(NumElts); 5228 std::iota(InsertMask.begin(), InsertMask.end(), 0); 5229 for (unsigned I = 0; I < NumElts; I++) { 5230 if (Mask[I] != UndefMaskElem) 5231 InsertMask[Offset + I] = NumElts + I; 5232 } 5233 5234 V = Builder.CreateShuffleVector( 5235 FirstInsert->getOperand(0), V, InsertMask, 5236 cast<Instruction>(E->Scalars.back())->getName()); 5237 } 5238 5239 ++NumVectorInstructions; 5240 E->VectorizedValue = V; 5241 return V; 5242 } 5243 case Instruction::ZExt: 5244 case Instruction::SExt: 5245 case Instruction::FPToUI: 5246 case Instruction::FPToSI: 5247 case Instruction::FPExt: 5248 case Instruction::PtrToInt: 5249 case Instruction::IntToPtr: 5250 case Instruction::SIToFP: 5251 case Instruction::UIToFP: 5252 case Instruction::Trunc: 5253 case Instruction::FPTrunc: 5254 case Instruction::BitCast: { 5255 setInsertPointAfterBundle(E); 5256 5257 Value *InVec = vectorizeTree(E->getOperand(0)); 5258 5259 if (E->VectorizedValue) { 5260 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5261 return E->VectorizedValue; 5262 } 5263 5264 auto *CI = cast<CastInst>(VL0); 5265 Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy); 5266 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5267 V = ShuffleBuilder.finalize(V); 5268 5269 E->VectorizedValue = V; 5270 ++NumVectorInstructions; 5271 return V; 5272 } 5273 case Instruction::FCmp: 5274 case Instruction::ICmp: { 5275 setInsertPointAfterBundle(E); 5276 5277 Value *L = vectorizeTree(E->getOperand(0)); 5278 Value *R = vectorizeTree(E->getOperand(1)); 5279 5280 if (E->VectorizedValue) { 5281 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5282 return E->VectorizedValue; 5283 } 5284 5285 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 5286 Value *V = Builder.CreateCmp(P0, L, R); 5287 propagateIRFlags(V, E->Scalars, VL0); 5288 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5289 V = ShuffleBuilder.finalize(V); 5290 5291 E->VectorizedValue = V; 5292 ++NumVectorInstructions; 5293 return V; 5294 } 5295 case Instruction::Select: { 5296 setInsertPointAfterBundle(E); 5297 5298 Value *Cond = vectorizeTree(E->getOperand(0)); 5299 Value *True = vectorizeTree(E->getOperand(1)); 5300 Value *False = vectorizeTree(E->getOperand(2)); 5301 5302 if (E->VectorizedValue) { 5303 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5304 return E->VectorizedValue; 5305 } 5306 5307 Value *V = Builder.CreateSelect(Cond, True, False); 5308 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5309 V = ShuffleBuilder.finalize(V); 5310 5311 E->VectorizedValue = V; 5312 ++NumVectorInstructions; 5313 return V; 5314 } 5315 case Instruction::FNeg: { 5316 setInsertPointAfterBundle(E); 5317 5318 Value *Op = vectorizeTree(E->getOperand(0)); 5319 5320 if (E->VectorizedValue) { 5321 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5322 return E->VectorizedValue; 5323 } 5324 5325 Value *V = Builder.CreateUnOp( 5326 static_cast<Instruction::UnaryOps>(E->getOpcode()), Op); 5327 propagateIRFlags(V, E->Scalars, VL0); 5328 if (auto *I = dyn_cast<Instruction>(V)) 5329 V = propagateMetadata(I, E->Scalars); 5330 5331 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5332 V = ShuffleBuilder.finalize(V); 5333 5334 E->VectorizedValue = V; 5335 ++NumVectorInstructions; 5336 5337 return V; 5338 } 5339 case Instruction::Add: 5340 case Instruction::FAdd: 5341 case Instruction::Sub: 5342 case Instruction::FSub: 5343 case Instruction::Mul: 5344 case Instruction::FMul: 5345 case Instruction::UDiv: 5346 case Instruction::SDiv: 5347 case Instruction::FDiv: 5348 case Instruction::URem: 5349 case Instruction::SRem: 5350 case Instruction::FRem: 5351 case Instruction::Shl: 5352 case Instruction::LShr: 5353 case Instruction::AShr: 5354 case Instruction::And: 5355 case Instruction::Or: 5356 case Instruction::Xor: { 5357 setInsertPointAfterBundle(E); 5358 5359 Value *LHS = vectorizeTree(E->getOperand(0)); 5360 Value *RHS = vectorizeTree(E->getOperand(1)); 5361 5362 if (E->VectorizedValue) { 5363 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5364 return E->VectorizedValue; 5365 } 5366 5367 Value *V = Builder.CreateBinOp( 5368 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, 5369 RHS); 5370 propagateIRFlags(V, E->Scalars, VL0); 5371 if (auto *I = dyn_cast<Instruction>(V)) 5372 V = propagateMetadata(I, E->Scalars); 5373 5374 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5375 V = ShuffleBuilder.finalize(V); 5376 5377 E->VectorizedValue = V; 5378 ++NumVectorInstructions; 5379 5380 return V; 5381 } 5382 case Instruction::Load: { 5383 // Loads are inserted at the head of the tree because we don't want to 5384 // sink them all the way down past store instructions. 5385 bool IsReorder = E->updateStateIfReorder(); 5386 if (IsReorder) 5387 VL0 = E->getMainOp(); 5388 setInsertPointAfterBundle(E); 5389 5390 LoadInst *LI = cast<LoadInst>(VL0); 5391 Instruction *NewLI; 5392 unsigned AS = LI->getPointerAddressSpace(); 5393 Value *PO = LI->getPointerOperand(); 5394 if (E->State == TreeEntry::Vectorize) { 5395 5396 Value *VecPtr = Builder.CreateBitCast(PO, VecTy->getPointerTo(AS)); 5397 5398 // The pointer operand uses an in-tree scalar so we add the new BitCast 5399 // to ExternalUses list to make sure that an extract will be generated 5400 // in the future. 5401 if (getTreeEntry(PO)) 5402 ExternalUses.emplace_back(PO, cast<User>(VecPtr), 0); 5403 5404 NewLI = Builder.CreateAlignedLoad(VecTy, VecPtr, LI->getAlign()); 5405 } else { 5406 assert(E->State == TreeEntry::ScatterVectorize && "Unhandled state"); 5407 Value *VecPtr = vectorizeTree(E->getOperand(0)); 5408 // Use the minimum alignment of the gathered loads. 5409 Align CommonAlignment = LI->getAlign(); 5410 for (Value *V : E->Scalars) 5411 CommonAlignment = 5412 commonAlignment(CommonAlignment, cast<LoadInst>(V)->getAlign()); 5413 NewLI = Builder.CreateMaskedGather(VecPtr, CommonAlignment); 5414 } 5415 Value *V = propagateMetadata(NewLI, E->Scalars); 5416 5417 ShuffleBuilder.addInversedMask(E->ReorderIndices); 5418 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5419 V = ShuffleBuilder.finalize(V); 5420 E->VectorizedValue = V; 5421 ++NumVectorInstructions; 5422 return V; 5423 } 5424 case Instruction::Store: { 5425 bool IsReorder = !E->ReorderIndices.empty(); 5426 auto *SI = cast<StoreInst>( 5427 IsReorder ? E->Scalars[E->ReorderIndices.front()] : VL0); 5428 unsigned AS = SI->getPointerAddressSpace(); 5429 5430 setInsertPointAfterBundle(E); 5431 5432 Value *VecValue = vectorizeTree(E->getOperand(0)); 5433 ShuffleBuilder.addMask(E->ReorderIndices); 5434 VecValue = ShuffleBuilder.finalize(VecValue); 5435 5436 Value *ScalarPtr = SI->getPointerOperand(); 5437 Value *VecPtr = Builder.CreateBitCast( 5438 ScalarPtr, VecValue->getType()->getPointerTo(AS)); 5439 StoreInst *ST = Builder.CreateAlignedStore(VecValue, VecPtr, 5440 SI->getAlign()); 5441 5442 // The pointer operand uses an in-tree scalar, so add the new BitCast to 5443 // ExternalUses to make sure that an extract will be generated in the 5444 // future. 5445 if (getTreeEntry(ScalarPtr)) 5446 ExternalUses.push_back(ExternalUser(ScalarPtr, cast<User>(VecPtr), 0)); 5447 5448 Value *V = propagateMetadata(ST, E->Scalars); 5449 5450 E->VectorizedValue = V; 5451 ++NumVectorInstructions; 5452 return V; 5453 } 5454 case Instruction::GetElementPtr: { 5455 setInsertPointAfterBundle(E); 5456 5457 Value *Op0 = vectorizeTree(E->getOperand(0)); 5458 5459 std::vector<Value *> OpVecs; 5460 for (int j = 1, e = cast<GetElementPtrInst>(VL0)->getNumOperands(); j < e; 5461 ++j) { 5462 ValueList &VL = E->getOperand(j); 5463 // Need to cast all elements to the same type before vectorization to 5464 // avoid crash. 5465 Type *VL0Ty = VL0->getOperand(j)->getType(); 5466 Type *Ty = llvm::all_of( 5467 VL, [VL0Ty](Value *V) { return VL0Ty == V->getType(); }) 5468 ? VL0Ty 5469 : DL->getIndexType(cast<GetElementPtrInst>(VL0) 5470 ->getPointerOperandType() 5471 ->getScalarType()); 5472 for (Value *&V : VL) { 5473 auto *CI = cast<ConstantInt>(V); 5474 V = ConstantExpr::getIntegerCast(CI, Ty, 5475 CI->getValue().isSignBitSet()); 5476 } 5477 Value *OpVec = vectorizeTree(VL); 5478 OpVecs.push_back(OpVec); 5479 } 5480 5481 Value *V = Builder.CreateGEP( 5482 cast<GetElementPtrInst>(VL0)->getSourceElementType(), Op0, OpVecs); 5483 if (Instruction *I = dyn_cast<Instruction>(V)) 5484 V = propagateMetadata(I, E->Scalars); 5485 5486 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5487 V = ShuffleBuilder.finalize(V); 5488 5489 E->VectorizedValue = V; 5490 ++NumVectorInstructions; 5491 5492 return V; 5493 } 5494 case Instruction::Call: { 5495 CallInst *CI = cast<CallInst>(VL0); 5496 setInsertPointAfterBundle(E); 5497 5498 Intrinsic::ID IID = Intrinsic::not_intrinsic; 5499 if (Function *FI = CI->getCalledFunction()) 5500 IID = FI->getIntrinsicID(); 5501 5502 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 5503 5504 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 5505 bool UseIntrinsic = ID != Intrinsic::not_intrinsic && 5506 VecCallCosts.first <= VecCallCosts.second; 5507 5508 Value *ScalarArg = nullptr; 5509 std::vector<Value *> OpVecs; 5510 SmallVector<Type *, 2> TysForDecl = 5511 {FixedVectorType::get(CI->getType(), E->Scalars.size())}; 5512 for (int j = 0, e = CI->getNumArgOperands(); j < e; ++j) { 5513 ValueList OpVL; 5514 // Some intrinsics have scalar arguments. This argument should not be 5515 // vectorized. 5516 if (UseIntrinsic && hasVectorInstrinsicScalarOpd(IID, j)) { 5517 CallInst *CEI = cast<CallInst>(VL0); 5518 ScalarArg = CEI->getArgOperand(j); 5519 OpVecs.push_back(CEI->getArgOperand(j)); 5520 if (hasVectorInstrinsicOverloadedScalarOpd(IID, j)) 5521 TysForDecl.push_back(ScalarArg->getType()); 5522 continue; 5523 } 5524 5525 Value *OpVec = vectorizeTree(E->getOperand(j)); 5526 LLVM_DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n"); 5527 OpVecs.push_back(OpVec); 5528 } 5529 5530 Function *CF; 5531 if (!UseIntrinsic) { 5532 VFShape Shape = 5533 VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>( 5534 VecTy->getNumElements())), 5535 false /*HasGlobalPred*/); 5536 CF = VFDatabase(*CI).getVectorizedFunction(Shape); 5537 } else { 5538 CF = Intrinsic::getDeclaration(F->getParent(), ID, TysForDecl); 5539 } 5540 5541 SmallVector<OperandBundleDef, 1> OpBundles; 5542 CI->getOperandBundlesAsDefs(OpBundles); 5543 Value *V = Builder.CreateCall(CF, OpVecs, OpBundles); 5544 5545 // The scalar argument uses an in-tree scalar so we add the new vectorized 5546 // call to ExternalUses list to make sure that an extract will be 5547 // generated in the future. 5548 if (ScalarArg && getTreeEntry(ScalarArg)) 5549 ExternalUses.push_back(ExternalUser(ScalarArg, cast<User>(V), 0)); 5550 5551 propagateIRFlags(V, E->Scalars, VL0); 5552 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5553 V = ShuffleBuilder.finalize(V); 5554 5555 E->VectorizedValue = V; 5556 ++NumVectorInstructions; 5557 return V; 5558 } 5559 case Instruction::ShuffleVector: { 5560 assert(E->isAltShuffle() && 5561 ((Instruction::isBinaryOp(E->getOpcode()) && 5562 Instruction::isBinaryOp(E->getAltOpcode())) || 5563 (Instruction::isCast(E->getOpcode()) && 5564 Instruction::isCast(E->getAltOpcode()))) && 5565 "Invalid Shuffle Vector Operand"); 5566 5567 Value *LHS = nullptr, *RHS = nullptr; 5568 if (Instruction::isBinaryOp(E->getOpcode())) { 5569 setInsertPointAfterBundle(E); 5570 LHS = vectorizeTree(E->getOperand(0)); 5571 RHS = vectorizeTree(E->getOperand(1)); 5572 } else { 5573 setInsertPointAfterBundle(E); 5574 LHS = vectorizeTree(E->getOperand(0)); 5575 } 5576 5577 if (E->VectorizedValue) { 5578 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5579 return E->VectorizedValue; 5580 } 5581 5582 Value *V0, *V1; 5583 if (Instruction::isBinaryOp(E->getOpcode())) { 5584 V0 = Builder.CreateBinOp( 5585 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, RHS); 5586 V1 = Builder.CreateBinOp( 5587 static_cast<Instruction::BinaryOps>(E->getAltOpcode()), LHS, RHS); 5588 } else { 5589 V0 = Builder.CreateCast( 5590 static_cast<Instruction::CastOps>(E->getOpcode()), LHS, VecTy); 5591 V1 = Builder.CreateCast( 5592 static_cast<Instruction::CastOps>(E->getAltOpcode()), LHS, VecTy); 5593 } 5594 5595 // Create shuffle to take alternate operations from the vector. 5596 // Also, gather up main and alt scalar ops to propagate IR flags to 5597 // each vector operation. 5598 ValueList OpScalars, AltScalars; 5599 unsigned e = E->Scalars.size(); 5600 SmallVector<int, 8> Mask(e); 5601 for (unsigned i = 0; i < e; ++i) { 5602 auto *OpInst = cast<Instruction>(E->Scalars[i]); 5603 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 5604 if (OpInst->getOpcode() == E->getAltOpcode()) { 5605 Mask[i] = e + i; 5606 AltScalars.push_back(E->Scalars[i]); 5607 } else { 5608 Mask[i] = i; 5609 OpScalars.push_back(E->Scalars[i]); 5610 } 5611 } 5612 5613 propagateIRFlags(V0, OpScalars); 5614 propagateIRFlags(V1, AltScalars); 5615 5616 Value *V = Builder.CreateShuffleVector(V0, V1, Mask); 5617 if (Instruction *I = dyn_cast<Instruction>(V)) 5618 V = propagateMetadata(I, E->Scalars); 5619 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5620 V = ShuffleBuilder.finalize(V); 5621 5622 E->VectorizedValue = V; 5623 ++NumVectorInstructions; 5624 5625 return V; 5626 } 5627 default: 5628 llvm_unreachable("unknown inst"); 5629 } 5630 return nullptr; 5631 } 5632 5633 Value *BoUpSLP::vectorizeTree() { 5634 ExtraValueToDebugLocsMap ExternallyUsedValues; 5635 return vectorizeTree(ExternallyUsedValues); 5636 } 5637 5638 Value * 5639 BoUpSLP::vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues) { 5640 // All blocks must be scheduled before any instructions are inserted. 5641 for (auto &BSIter : BlocksSchedules) { 5642 scheduleBlock(BSIter.second.get()); 5643 } 5644 5645 Builder.SetInsertPoint(&F->getEntryBlock().front()); 5646 auto *VectorRoot = vectorizeTree(VectorizableTree[0].get()); 5647 5648 // If the vectorized tree can be rewritten in a smaller type, we truncate the 5649 // vectorized root. InstCombine will then rewrite the entire expression. We 5650 // sign extend the extracted values below. 5651 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 5652 if (MinBWs.count(ScalarRoot)) { 5653 if (auto *I = dyn_cast<Instruction>(VectorRoot)) { 5654 // If current instr is a phi and not the last phi, insert it after the 5655 // last phi node. 5656 if (isa<PHINode>(I)) 5657 Builder.SetInsertPoint(&*I->getParent()->getFirstInsertionPt()); 5658 else 5659 Builder.SetInsertPoint(&*++BasicBlock::iterator(I)); 5660 } 5661 auto BundleWidth = VectorizableTree[0]->Scalars.size(); 5662 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 5663 auto *VecTy = FixedVectorType::get(MinTy, BundleWidth); 5664 auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy); 5665 VectorizableTree[0]->VectorizedValue = Trunc; 5666 } 5667 5668 LLVM_DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size() 5669 << " values .\n"); 5670 5671 // Extract all of the elements with the external uses. 5672 for (const auto &ExternalUse : ExternalUses) { 5673 Value *Scalar = ExternalUse.Scalar; 5674 llvm::User *User = ExternalUse.User; 5675 5676 // Skip users that we already RAUW. This happens when one instruction 5677 // has multiple uses of the same value. 5678 if (User && !is_contained(Scalar->users(), User)) 5679 continue; 5680 TreeEntry *E = getTreeEntry(Scalar); 5681 assert(E && "Invalid scalar"); 5682 assert(E->State != TreeEntry::NeedToGather && 5683 "Extracting from a gather list"); 5684 5685 Value *Vec = E->VectorizedValue; 5686 assert(Vec && "Can't find vectorizable value"); 5687 5688 Value *Lane = Builder.getInt32(ExternalUse.Lane); 5689 auto ExtractAndExtendIfNeeded = [&](Value *Vec) { 5690 if (Scalar->getType() != Vec->getType()) { 5691 Value *Ex; 5692 // "Reuse" the existing extract to improve final codegen. 5693 if (auto *ES = dyn_cast<ExtractElementInst>(Scalar)) { 5694 Ex = Builder.CreateExtractElement(ES->getOperand(0), 5695 ES->getOperand(1)); 5696 } else { 5697 Ex = Builder.CreateExtractElement(Vec, Lane); 5698 } 5699 // If necessary, sign-extend or zero-extend ScalarRoot 5700 // to the larger type. 5701 if (!MinBWs.count(ScalarRoot)) 5702 return Ex; 5703 if (MinBWs[ScalarRoot].second) 5704 return Builder.CreateSExt(Ex, Scalar->getType()); 5705 return Builder.CreateZExt(Ex, Scalar->getType()); 5706 } 5707 assert(isa<FixedVectorType>(Scalar->getType()) && 5708 isa<InsertElementInst>(Scalar) && 5709 "In-tree scalar of vector type is not insertelement?"); 5710 return Vec; 5711 }; 5712 // If User == nullptr, the Scalar is used as extra arg. Generate 5713 // ExtractElement instruction and update the record for this scalar in 5714 // ExternallyUsedValues. 5715 if (!User) { 5716 assert(ExternallyUsedValues.count(Scalar) && 5717 "Scalar with nullptr as an external user must be registered in " 5718 "ExternallyUsedValues map"); 5719 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 5720 Builder.SetInsertPoint(VecI->getParent(), 5721 std::next(VecI->getIterator())); 5722 } else { 5723 Builder.SetInsertPoint(&F->getEntryBlock().front()); 5724 } 5725 Value *NewInst = ExtractAndExtendIfNeeded(Vec); 5726 CSEBlocks.insert(cast<Instruction>(Scalar)->getParent()); 5727 auto &NewInstLocs = ExternallyUsedValues[NewInst]; 5728 auto It = ExternallyUsedValues.find(Scalar); 5729 assert(It != ExternallyUsedValues.end() && 5730 "Externally used scalar is not found in ExternallyUsedValues"); 5731 NewInstLocs.append(It->second); 5732 ExternallyUsedValues.erase(Scalar); 5733 // Required to update internally referenced instructions. 5734 Scalar->replaceAllUsesWith(NewInst); 5735 continue; 5736 } 5737 5738 // Generate extracts for out-of-tree users. 5739 // Find the insertion point for the extractelement lane. 5740 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 5741 if (PHINode *PH = dyn_cast<PHINode>(User)) { 5742 for (int i = 0, e = PH->getNumIncomingValues(); i != e; ++i) { 5743 if (PH->getIncomingValue(i) == Scalar) { 5744 Instruction *IncomingTerminator = 5745 PH->getIncomingBlock(i)->getTerminator(); 5746 if (isa<CatchSwitchInst>(IncomingTerminator)) { 5747 Builder.SetInsertPoint(VecI->getParent(), 5748 std::next(VecI->getIterator())); 5749 } else { 5750 Builder.SetInsertPoint(PH->getIncomingBlock(i)->getTerminator()); 5751 } 5752 Value *NewInst = ExtractAndExtendIfNeeded(Vec); 5753 CSEBlocks.insert(PH->getIncomingBlock(i)); 5754 PH->setOperand(i, NewInst); 5755 } 5756 } 5757 } else { 5758 Builder.SetInsertPoint(cast<Instruction>(User)); 5759 Value *NewInst = ExtractAndExtendIfNeeded(Vec); 5760 CSEBlocks.insert(cast<Instruction>(User)->getParent()); 5761 User->replaceUsesOfWith(Scalar, NewInst); 5762 } 5763 } else { 5764 Builder.SetInsertPoint(&F->getEntryBlock().front()); 5765 Value *NewInst = ExtractAndExtendIfNeeded(Vec); 5766 CSEBlocks.insert(&F->getEntryBlock()); 5767 User->replaceUsesOfWith(Scalar, NewInst); 5768 } 5769 5770 LLVM_DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n"); 5771 } 5772 5773 // For each vectorized value: 5774 for (auto &TEPtr : VectorizableTree) { 5775 TreeEntry *Entry = TEPtr.get(); 5776 5777 // No need to handle users of gathered values. 5778 if (Entry->State == TreeEntry::NeedToGather) 5779 continue; 5780 5781 assert(Entry->VectorizedValue && "Can't find vectorizable value"); 5782 5783 // For each lane: 5784 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 5785 Value *Scalar = Entry->Scalars[Lane]; 5786 5787 #ifndef NDEBUG 5788 Type *Ty = Scalar->getType(); 5789 if (!Ty->isVoidTy()) { 5790 for (User *U : Scalar->users()) { 5791 LLVM_DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n"); 5792 5793 // It is legal to delete users in the ignorelist. 5794 assert((getTreeEntry(U) || is_contained(UserIgnoreList, U)) && 5795 "Deleting out-of-tree value"); 5796 } 5797 } 5798 #endif 5799 LLVM_DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n"); 5800 eraseInstruction(cast<Instruction>(Scalar)); 5801 } 5802 } 5803 5804 Builder.ClearInsertionPoint(); 5805 InstrElementSize.clear(); 5806 5807 return VectorizableTree[0]->VectorizedValue; 5808 } 5809 5810 void BoUpSLP::optimizeGatherSequence() { 5811 LLVM_DEBUG(dbgs() << "SLP: Optimizing " << GatherSeq.size() 5812 << " gather sequences instructions.\n"); 5813 // LICM InsertElementInst sequences. 5814 for (Instruction *I : GatherSeq) { 5815 if (isDeleted(I)) 5816 continue; 5817 5818 // Check if this block is inside a loop. 5819 Loop *L = LI->getLoopFor(I->getParent()); 5820 if (!L) 5821 continue; 5822 5823 // Check if it has a preheader. 5824 BasicBlock *PreHeader = L->getLoopPreheader(); 5825 if (!PreHeader) 5826 continue; 5827 5828 // If the vector or the element that we insert into it are 5829 // instructions that are defined in this basic block then we can't 5830 // hoist this instruction. 5831 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 5832 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 5833 if (Op0 && L->contains(Op0)) 5834 continue; 5835 if (Op1 && L->contains(Op1)) 5836 continue; 5837 5838 // We can hoist this instruction. Move it to the pre-header. 5839 I->moveBefore(PreHeader->getTerminator()); 5840 } 5841 5842 // Make a list of all reachable blocks in our CSE queue. 5843 SmallVector<const DomTreeNode *, 8> CSEWorkList; 5844 CSEWorkList.reserve(CSEBlocks.size()); 5845 for (BasicBlock *BB : CSEBlocks) 5846 if (DomTreeNode *N = DT->getNode(BB)) { 5847 assert(DT->isReachableFromEntry(N)); 5848 CSEWorkList.push_back(N); 5849 } 5850 5851 // Sort blocks by domination. This ensures we visit a block after all blocks 5852 // dominating it are visited. 5853 llvm::sort(CSEWorkList, [](const DomTreeNode *A, const DomTreeNode *B) { 5854 assert((A == B) == (A->getDFSNumIn() == B->getDFSNumIn()) && 5855 "Different nodes should have different DFS numbers"); 5856 return A->getDFSNumIn() < B->getDFSNumIn(); 5857 }); 5858 5859 // Perform O(N^2) search over the gather sequences and merge identical 5860 // instructions. TODO: We can further optimize this scan if we split the 5861 // instructions into different buckets based on the insert lane. 5862 SmallVector<Instruction *, 16> Visited; 5863 for (auto I = CSEWorkList.begin(), E = CSEWorkList.end(); I != E; ++I) { 5864 assert(*I && 5865 (I == CSEWorkList.begin() || !DT->dominates(*I, *std::prev(I))) && 5866 "Worklist not sorted properly!"); 5867 BasicBlock *BB = (*I)->getBlock(); 5868 // For all instructions in blocks containing gather sequences: 5869 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e;) { 5870 Instruction *In = &*it++; 5871 if (isDeleted(In)) 5872 continue; 5873 if (!isa<InsertElementInst>(In) && !isa<ExtractElementInst>(In)) 5874 continue; 5875 5876 // Check if we can replace this instruction with any of the 5877 // visited instructions. 5878 for (Instruction *v : Visited) { 5879 if (In->isIdenticalTo(v) && 5880 DT->dominates(v->getParent(), In->getParent())) { 5881 In->replaceAllUsesWith(v); 5882 eraseInstruction(In); 5883 In = nullptr; 5884 break; 5885 } 5886 } 5887 if (In) { 5888 assert(!is_contained(Visited, In)); 5889 Visited.push_back(In); 5890 } 5891 } 5892 } 5893 CSEBlocks.clear(); 5894 GatherSeq.clear(); 5895 } 5896 5897 // Groups the instructions to a bundle (which is then a single scheduling entity) 5898 // and schedules instructions until the bundle gets ready. 5899 Optional<BoUpSLP::ScheduleData *> 5900 BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 5901 const InstructionsState &S) { 5902 if (isa<PHINode>(S.OpValue) || isa<InsertElementInst>(S.OpValue)) 5903 return nullptr; 5904 5905 // Initialize the instruction bundle. 5906 Instruction *OldScheduleEnd = ScheduleEnd; 5907 ScheduleData *PrevInBundle = nullptr; 5908 ScheduleData *Bundle = nullptr; 5909 bool ReSchedule = false; 5910 LLVM_DEBUG(dbgs() << "SLP: bundle: " << *S.OpValue << "\n"); 5911 5912 auto &&TryScheduleBundle = [this, OldScheduleEnd, SLP](bool ReSchedule, 5913 ScheduleData *Bundle) { 5914 // The scheduling region got new instructions at the lower end (or it is a 5915 // new region for the first bundle). This makes it necessary to 5916 // recalculate all dependencies. 5917 // It is seldom that this needs to be done a second time after adding the 5918 // initial bundle to the region. 5919 if (ScheduleEnd != OldScheduleEnd) { 5920 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) 5921 doForAllOpcodes(I, [](ScheduleData *SD) { SD->clearDependencies(); }); 5922 ReSchedule = true; 5923 } 5924 if (ReSchedule) { 5925 resetSchedule(); 5926 initialFillReadyList(ReadyInsts); 5927 } 5928 if (Bundle) { 5929 LLVM_DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle 5930 << " in block " << BB->getName() << "\n"); 5931 calculateDependencies(Bundle, /*InsertInReadyList=*/true, SLP); 5932 } 5933 5934 // Now try to schedule the new bundle or (if no bundle) just calculate 5935 // dependencies. As soon as the bundle is "ready" it means that there are no 5936 // cyclic dependencies and we can schedule it. Note that's important that we 5937 // don't "schedule" the bundle yet (see cancelScheduling). 5938 while (((!Bundle && ReSchedule) || (Bundle && !Bundle->isReady())) && 5939 !ReadyInsts.empty()) { 5940 ScheduleData *Picked = ReadyInsts.pop_back_val(); 5941 if (Picked->isSchedulingEntity() && Picked->isReady()) 5942 schedule(Picked, ReadyInsts); 5943 } 5944 }; 5945 5946 // Make sure that the scheduling region contains all 5947 // instructions of the bundle. 5948 for (Value *V : VL) { 5949 if (!extendSchedulingRegion(V, S)) { 5950 // If the scheduling region got new instructions at the lower end (or it 5951 // is a new region for the first bundle). This makes it necessary to 5952 // recalculate all dependencies. 5953 // Otherwise the compiler may crash trying to incorrectly calculate 5954 // dependencies and emit instruction in the wrong order at the actual 5955 // scheduling. 5956 TryScheduleBundle(/*ReSchedule=*/false, nullptr); 5957 return None; 5958 } 5959 } 5960 5961 for (Value *V : VL) { 5962 ScheduleData *BundleMember = getScheduleData(V); 5963 assert(BundleMember && 5964 "no ScheduleData for bundle member (maybe not in same basic block)"); 5965 if (BundleMember->IsScheduled) { 5966 // A bundle member was scheduled as single instruction before and now 5967 // needs to be scheduled as part of the bundle. We just get rid of the 5968 // existing schedule. 5969 LLVM_DEBUG(dbgs() << "SLP: reset schedule because " << *BundleMember 5970 << " was already scheduled\n"); 5971 ReSchedule = true; 5972 } 5973 assert(BundleMember->isSchedulingEntity() && 5974 "bundle member already part of other bundle"); 5975 if (PrevInBundle) { 5976 PrevInBundle->NextInBundle = BundleMember; 5977 } else { 5978 Bundle = BundleMember; 5979 } 5980 BundleMember->UnscheduledDepsInBundle = 0; 5981 Bundle->UnscheduledDepsInBundle += BundleMember->UnscheduledDeps; 5982 5983 // Group the instructions to a bundle. 5984 BundleMember->FirstInBundle = Bundle; 5985 PrevInBundle = BundleMember; 5986 } 5987 assert(Bundle && "Failed to find schedule bundle"); 5988 TryScheduleBundle(ReSchedule, Bundle); 5989 if (!Bundle->isReady()) { 5990 cancelScheduling(VL, S.OpValue); 5991 return None; 5992 } 5993 return Bundle; 5994 } 5995 5996 void BoUpSLP::BlockScheduling::cancelScheduling(ArrayRef<Value *> VL, 5997 Value *OpValue) { 5998 if (isa<PHINode>(OpValue) || isa<InsertElementInst>(OpValue)) 5999 return; 6000 6001 ScheduleData *Bundle = getScheduleData(OpValue); 6002 LLVM_DEBUG(dbgs() << "SLP: cancel scheduling of " << *Bundle << "\n"); 6003 assert(!Bundle->IsScheduled && 6004 "Can't cancel bundle which is already scheduled"); 6005 assert(Bundle->isSchedulingEntity() && Bundle->isPartOfBundle() && 6006 "tried to unbundle something which is not a bundle"); 6007 6008 // Un-bundle: make single instructions out of the bundle. 6009 ScheduleData *BundleMember = Bundle; 6010 while (BundleMember) { 6011 assert(BundleMember->FirstInBundle == Bundle && "corrupt bundle links"); 6012 BundleMember->FirstInBundle = BundleMember; 6013 ScheduleData *Next = BundleMember->NextInBundle; 6014 BundleMember->NextInBundle = nullptr; 6015 BundleMember->UnscheduledDepsInBundle = BundleMember->UnscheduledDeps; 6016 if (BundleMember->UnscheduledDepsInBundle == 0) { 6017 ReadyInsts.insert(BundleMember); 6018 } 6019 BundleMember = Next; 6020 } 6021 } 6022 6023 BoUpSLP::ScheduleData *BoUpSLP::BlockScheduling::allocateScheduleDataChunks() { 6024 // Allocate a new ScheduleData for the instruction. 6025 if (ChunkPos >= ChunkSize) { 6026 ScheduleDataChunks.push_back(std::make_unique<ScheduleData[]>(ChunkSize)); 6027 ChunkPos = 0; 6028 } 6029 return &(ScheduleDataChunks.back()[ChunkPos++]); 6030 } 6031 6032 bool BoUpSLP::BlockScheduling::extendSchedulingRegion(Value *V, 6033 const InstructionsState &S) { 6034 if (getScheduleData(V, isOneOf(S, V))) 6035 return true; 6036 Instruction *I = dyn_cast<Instruction>(V); 6037 assert(I && "bundle member must be an instruction"); 6038 assert(!isa<PHINode>(I) && !isa<InsertElementInst>(I) && 6039 "phi nodes/insertelements don't need to be scheduled"); 6040 auto &&CheckSheduleForI = [this, &S](Instruction *I) -> bool { 6041 ScheduleData *ISD = getScheduleData(I); 6042 if (!ISD) 6043 return false; 6044 assert(isInSchedulingRegion(ISD) && 6045 "ScheduleData not in scheduling region"); 6046 ScheduleData *SD = allocateScheduleDataChunks(); 6047 SD->Inst = I; 6048 SD->init(SchedulingRegionID, S.OpValue); 6049 ExtraScheduleDataMap[I][S.OpValue] = SD; 6050 return true; 6051 }; 6052 if (CheckSheduleForI(I)) 6053 return true; 6054 if (!ScheduleStart) { 6055 // It's the first instruction in the new region. 6056 initScheduleData(I, I->getNextNode(), nullptr, nullptr); 6057 ScheduleStart = I; 6058 ScheduleEnd = I->getNextNode(); 6059 if (isOneOf(S, I) != I) 6060 CheckSheduleForI(I); 6061 assert(ScheduleEnd && "tried to vectorize a terminator?"); 6062 LLVM_DEBUG(dbgs() << "SLP: initialize schedule region to " << *I << "\n"); 6063 return true; 6064 } 6065 // Search up and down at the same time, because we don't know if the new 6066 // instruction is above or below the existing scheduling region. 6067 BasicBlock::reverse_iterator UpIter = 6068 ++ScheduleStart->getIterator().getReverse(); 6069 BasicBlock::reverse_iterator UpperEnd = BB->rend(); 6070 BasicBlock::iterator DownIter = ScheduleEnd->getIterator(); 6071 BasicBlock::iterator LowerEnd = BB->end(); 6072 while (UpIter != UpperEnd && DownIter != LowerEnd && &*UpIter != I && 6073 &*DownIter != I) { 6074 if (++ScheduleRegionSize > ScheduleRegionSizeLimit) { 6075 LLVM_DEBUG(dbgs() << "SLP: exceeded schedule region size limit\n"); 6076 return false; 6077 } 6078 6079 ++UpIter; 6080 ++DownIter; 6081 } 6082 if (DownIter == LowerEnd || (UpIter != UpperEnd && &*UpIter == I)) { 6083 assert(I->getParent() == ScheduleStart->getParent() && 6084 "Instruction is in wrong basic block."); 6085 initScheduleData(I, ScheduleStart, nullptr, FirstLoadStoreInRegion); 6086 ScheduleStart = I; 6087 if (isOneOf(S, I) != I) 6088 CheckSheduleForI(I); 6089 LLVM_DEBUG(dbgs() << "SLP: extend schedule region start to " << *I 6090 << "\n"); 6091 return true; 6092 } 6093 assert((UpIter == UpperEnd || (DownIter != LowerEnd && &*DownIter == I)) && 6094 "Expected to reach top of the basic block or instruction down the " 6095 "lower end."); 6096 assert(I->getParent() == ScheduleEnd->getParent() && 6097 "Instruction is in wrong basic block."); 6098 initScheduleData(ScheduleEnd, I->getNextNode(), LastLoadStoreInRegion, 6099 nullptr); 6100 ScheduleEnd = I->getNextNode(); 6101 if (isOneOf(S, I) != I) 6102 CheckSheduleForI(I); 6103 assert(ScheduleEnd && "tried to vectorize a terminator?"); 6104 LLVM_DEBUG(dbgs() << "SLP: extend schedule region end to " << *I << "\n"); 6105 return true; 6106 } 6107 6108 void BoUpSLP::BlockScheduling::initScheduleData(Instruction *FromI, 6109 Instruction *ToI, 6110 ScheduleData *PrevLoadStore, 6111 ScheduleData *NextLoadStore) { 6112 ScheduleData *CurrentLoadStore = PrevLoadStore; 6113 for (Instruction *I = FromI; I != ToI; I = I->getNextNode()) { 6114 ScheduleData *SD = ScheduleDataMap[I]; 6115 if (!SD) { 6116 SD = allocateScheduleDataChunks(); 6117 ScheduleDataMap[I] = SD; 6118 SD->Inst = I; 6119 } 6120 assert(!isInSchedulingRegion(SD) && 6121 "new ScheduleData already in scheduling region"); 6122 SD->init(SchedulingRegionID, I); 6123 6124 if (I->mayReadOrWriteMemory() && 6125 (!isa<IntrinsicInst>(I) || 6126 (cast<IntrinsicInst>(I)->getIntrinsicID() != Intrinsic::sideeffect && 6127 cast<IntrinsicInst>(I)->getIntrinsicID() != 6128 Intrinsic::pseudoprobe))) { 6129 // Update the linked list of memory accessing instructions. 6130 if (CurrentLoadStore) { 6131 CurrentLoadStore->NextLoadStore = SD; 6132 } else { 6133 FirstLoadStoreInRegion = SD; 6134 } 6135 CurrentLoadStore = SD; 6136 } 6137 } 6138 if (NextLoadStore) { 6139 if (CurrentLoadStore) 6140 CurrentLoadStore->NextLoadStore = NextLoadStore; 6141 } else { 6142 LastLoadStoreInRegion = CurrentLoadStore; 6143 } 6144 } 6145 6146 void BoUpSLP::BlockScheduling::calculateDependencies(ScheduleData *SD, 6147 bool InsertInReadyList, 6148 BoUpSLP *SLP) { 6149 assert(SD->isSchedulingEntity()); 6150 6151 SmallVector<ScheduleData *, 10> WorkList; 6152 WorkList.push_back(SD); 6153 6154 while (!WorkList.empty()) { 6155 ScheduleData *SD = WorkList.pop_back_val(); 6156 6157 ScheduleData *BundleMember = SD; 6158 while (BundleMember) { 6159 assert(isInSchedulingRegion(BundleMember)); 6160 if (!BundleMember->hasValidDependencies()) { 6161 6162 LLVM_DEBUG(dbgs() << "SLP: update deps of " << *BundleMember 6163 << "\n"); 6164 BundleMember->Dependencies = 0; 6165 BundleMember->resetUnscheduledDeps(); 6166 6167 // Handle def-use chain dependencies. 6168 if (BundleMember->OpValue != BundleMember->Inst) { 6169 ScheduleData *UseSD = getScheduleData(BundleMember->Inst); 6170 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 6171 BundleMember->Dependencies++; 6172 ScheduleData *DestBundle = UseSD->FirstInBundle; 6173 if (!DestBundle->IsScheduled) 6174 BundleMember->incrementUnscheduledDeps(1); 6175 if (!DestBundle->hasValidDependencies()) 6176 WorkList.push_back(DestBundle); 6177 } 6178 } else { 6179 for (User *U : BundleMember->Inst->users()) { 6180 if (isa<Instruction>(U)) { 6181 ScheduleData *UseSD = getScheduleData(U); 6182 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 6183 BundleMember->Dependencies++; 6184 ScheduleData *DestBundle = UseSD->FirstInBundle; 6185 if (!DestBundle->IsScheduled) 6186 BundleMember->incrementUnscheduledDeps(1); 6187 if (!DestBundle->hasValidDependencies()) 6188 WorkList.push_back(DestBundle); 6189 } 6190 } else { 6191 // I'm not sure if this can ever happen. But we need to be safe. 6192 // This lets the instruction/bundle never be scheduled and 6193 // eventually disable vectorization. 6194 BundleMember->Dependencies++; 6195 BundleMember->incrementUnscheduledDeps(1); 6196 } 6197 } 6198 } 6199 6200 // Handle the memory dependencies. 6201 ScheduleData *DepDest = BundleMember->NextLoadStore; 6202 if (DepDest) { 6203 Instruction *SrcInst = BundleMember->Inst; 6204 MemoryLocation SrcLoc = getLocation(SrcInst, SLP->AA); 6205 bool SrcMayWrite = BundleMember->Inst->mayWriteToMemory(); 6206 unsigned numAliased = 0; 6207 unsigned DistToSrc = 1; 6208 6209 while (DepDest) { 6210 assert(isInSchedulingRegion(DepDest)); 6211 6212 // We have two limits to reduce the complexity: 6213 // 1) AliasedCheckLimit: It's a small limit to reduce calls to 6214 // SLP->isAliased (which is the expensive part in this loop). 6215 // 2) MaxMemDepDistance: It's for very large blocks and it aborts 6216 // the whole loop (even if the loop is fast, it's quadratic). 6217 // It's important for the loop break condition (see below) to 6218 // check this limit even between two read-only instructions. 6219 if (DistToSrc >= MaxMemDepDistance || 6220 ((SrcMayWrite || DepDest->Inst->mayWriteToMemory()) && 6221 (numAliased >= AliasedCheckLimit || 6222 SLP->isAliased(SrcLoc, SrcInst, DepDest->Inst)))) { 6223 6224 // We increment the counter only if the locations are aliased 6225 // (instead of counting all alias checks). This gives a better 6226 // balance between reduced runtime and accurate dependencies. 6227 numAliased++; 6228 6229 DepDest->MemoryDependencies.push_back(BundleMember); 6230 BundleMember->Dependencies++; 6231 ScheduleData *DestBundle = DepDest->FirstInBundle; 6232 if (!DestBundle->IsScheduled) { 6233 BundleMember->incrementUnscheduledDeps(1); 6234 } 6235 if (!DestBundle->hasValidDependencies()) { 6236 WorkList.push_back(DestBundle); 6237 } 6238 } 6239 DepDest = DepDest->NextLoadStore; 6240 6241 // Example, explaining the loop break condition: Let's assume our 6242 // starting instruction is i0 and MaxMemDepDistance = 3. 6243 // 6244 // +--------v--v--v 6245 // i0,i1,i2,i3,i4,i5,i6,i7,i8 6246 // +--------^--^--^ 6247 // 6248 // MaxMemDepDistance let us stop alias-checking at i3 and we add 6249 // dependencies from i0 to i3,i4,.. (even if they are not aliased). 6250 // Previously we already added dependencies from i3 to i6,i7,i8 6251 // (because of MaxMemDepDistance). As we added a dependency from 6252 // i0 to i3, we have transitive dependencies from i0 to i6,i7,i8 6253 // and we can abort this loop at i6. 6254 if (DistToSrc >= 2 * MaxMemDepDistance) 6255 break; 6256 DistToSrc++; 6257 } 6258 } 6259 } 6260 BundleMember = BundleMember->NextInBundle; 6261 } 6262 if (InsertInReadyList && SD->isReady()) { 6263 ReadyInsts.push_back(SD); 6264 LLVM_DEBUG(dbgs() << "SLP: gets ready on update: " << *SD->Inst 6265 << "\n"); 6266 } 6267 } 6268 } 6269 6270 void BoUpSLP::BlockScheduling::resetSchedule() { 6271 assert(ScheduleStart && 6272 "tried to reset schedule on block which has not been scheduled"); 6273 for (Instruction *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 6274 doForAllOpcodes(I, [&](ScheduleData *SD) { 6275 assert(isInSchedulingRegion(SD) && 6276 "ScheduleData not in scheduling region"); 6277 SD->IsScheduled = false; 6278 SD->resetUnscheduledDeps(); 6279 }); 6280 } 6281 ReadyInsts.clear(); 6282 } 6283 6284 void BoUpSLP::scheduleBlock(BlockScheduling *BS) { 6285 if (!BS->ScheduleStart) 6286 return; 6287 6288 LLVM_DEBUG(dbgs() << "SLP: schedule block " << BS->BB->getName() << "\n"); 6289 6290 BS->resetSchedule(); 6291 6292 // For the real scheduling we use a more sophisticated ready-list: it is 6293 // sorted by the original instruction location. This lets the final schedule 6294 // be as close as possible to the original instruction order. 6295 struct ScheduleDataCompare { 6296 bool operator()(ScheduleData *SD1, ScheduleData *SD2) const { 6297 return SD2->SchedulingPriority < SD1->SchedulingPriority; 6298 } 6299 }; 6300 std::set<ScheduleData *, ScheduleDataCompare> ReadyInsts; 6301 6302 // Ensure that all dependency data is updated and fill the ready-list with 6303 // initial instructions. 6304 int Idx = 0; 6305 int NumToSchedule = 0; 6306 for (auto *I = BS->ScheduleStart; I != BS->ScheduleEnd; 6307 I = I->getNextNode()) { 6308 BS->doForAllOpcodes(I, [this, &Idx, &NumToSchedule, BS](ScheduleData *SD) { 6309 assert((isa<InsertElementInst>(SD->Inst) || 6310 SD->isPartOfBundle() == (getTreeEntry(SD->Inst) != nullptr)) && 6311 "scheduler and vectorizer bundle mismatch"); 6312 SD->FirstInBundle->SchedulingPriority = Idx++; 6313 if (SD->isSchedulingEntity()) { 6314 BS->calculateDependencies(SD, false, this); 6315 NumToSchedule++; 6316 } 6317 }); 6318 } 6319 BS->initialFillReadyList(ReadyInsts); 6320 6321 Instruction *LastScheduledInst = BS->ScheduleEnd; 6322 6323 // Do the "real" scheduling. 6324 while (!ReadyInsts.empty()) { 6325 ScheduleData *picked = *ReadyInsts.begin(); 6326 ReadyInsts.erase(ReadyInsts.begin()); 6327 6328 // Move the scheduled instruction(s) to their dedicated places, if not 6329 // there yet. 6330 ScheduleData *BundleMember = picked; 6331 while (BundleMember) { 6332 Instruction *pickedInst = BundleMember->Inst; 6333 if (pickedInst->getNextNode() != LastScheduledInst) { 6334 BS->BB->getInstList().remove(pickedInst); 6335 BS->BB->getInstList().insert(LastScheduledInst->getIterator(), 6336 pickedInst); 6337 } 6338 LastScheduledInst = pickedInst; 6339 BundleMember = BundleMember->NextInBundle; 6340 } 6341 6342 BS->schedule(picked, ReadyInsts); 6343 NumToSchedule--; 6344 } 6345 assert(NumToSchedule == 0 && "could not schedule all instructions"); 6346 6347 // Avoid duplicate scheduling of the block. 6348 BS->ScheduleStart = nullptr; 6349 } 6350 6351 unsigned BoUpSLP::getVectorElementSize(Value *V) { 6352 // If V is a store, just return the width of the stored value (or value 6353 // truncated just before storing) without traversing the expression tree. 6354 // This is the common case. 6355 if (auto *Store = dyn_cast<StoreInst>(V)) { 6356 if (auto *Trunc = dyn_cast<TruncInst>(Store->getValueOperand())) 6357 return DL->getTypeSizeInBits(Trunc->getSrcTy()); 6358 return DL->getTypeSizeInBits(Store->getValueOperand()->getType()); 6359 } 6360 6361 if (auto *IEI = dyn_cast<InsertElementInst>(V)) 6362 return getVectorElementSize(IEI->getOperand(1)); 6363 6364 auto E = InstrElementSize.find(V); 6365 if (E != InstrElementSize.end()) 6366 return E->second; 6367 6368 // If V is not a store, we can traverse the expression tree to find loads 6369 // that feed it. The type of the loaded value may indicate a more suitable 6370 // width than V's type. We want to base the vector element size on the width 6371 // of memory operations where possible. 6372 SmallVector<std::pair<Instruction *, BasicBlock *>, 16> Worklist; 6373 SmallPtrSet<Instruction *, 16> Visited; 6374 if (auto *I = dyn_cast<Instruction>(V)) { 6375 Worklist.emplace_back(I, I->getParent()); 6376 Visited.insert(I); 6377 } 6378 6379 // Traverse the expression tree in bottom-up order looking for loads. If we 6380 // encounter an instruction we don't yet handle, we give up. 6381 auto Width = 0u; 6382 while (!Worklist.empty()) { 6383 Instruction *I; 6384 BasicBlock *Parent; 6385 std::tie(I, Parent) = Worklist.pop_back_val(); 6386 6387 // We should only be looking at scalar instructions here. If the current 6388 // instruction has a vector type, skip. 6389 auto *Ty = I->getType(); 6390 if (isa<VectorType>(Ty)) 6391 continue; 6392 6393 // If the current instruction is a load, update MaxWidth to reflect the 6394 // width of the loaded value. 6395 if (isa<LoadInst>(I) || isa<ExtractElementInst>(I) || 6396 isa<ExtractValueInst>(I)) 6397 Width = std::max<unsigned>(Width, DL->getTypeSizeInBits(Ty)); 6398 6399 // Otherwise, we need to visit the operands of the instruction. We only 6400 // handle the interesting cases from buildTree here. If an operand is an 6401 // instruction we haven't yet visited and from the same basic block as the 6402 // user or the use is a PHI node, we add it to the worklist. 6403 else if (isa<PHINode>(I) || isa<CastInst>(I) || isa<GetElementPtrInst>(I) || 6404 isa<CmpInst>(I) || isa<SelectInst>(I) || isa<BinaryOperator>(I) || 6405 isa<UnaryOperator>(I)) { 6406 for (Use &U : I->operands()) 6407 if (auto *J = dyn_cast<Instruction>(U.get())) 6408 if (Visited.insert(J).second && 6409 (isa<PHINode>(I) || J->getParent() == Parent)) 6410 Worklist.emplace_back(J, J->getParent()); 6411 } else { 6412 break; 6413 } 6414 } 6415 6416 // If we didn't encounter a memory access in the expression tree, or if we 6417 // gave up for some reason, just return the width of V. Otherwise, return the 6418 // maximum width we found. 6419 if (!Width) { 6420 if (auto *CI = dyn_cast<CmpInst>(V)) 6421 V = CI->getOperand(0); 6422 Width = DL->getTypeSizeInBits(V->getType()); 6423 } 6424 6425 for (Instruction *I : Visited) 6426 InstrElementSize[I] = Width; 6427 6428 return Width; 6429 } 6430 6431 // Determine if a value V in a vectorizable expression Expr can be demoted to a 6432 // smaller type with a truncation. We collect the values that will be demoted 6433 // in ToDemote and additional roots that require investigating in Roots. 6434 static bool collectValuesToDemote(Value *V, SmallPtrSetImpl<Value *> &Expr, 6435 SmallVectorImpl<Value *> &ToDemote, 6436 SmallVectorImpl<Value *> &Roots) { 6437 // We can always demote constants. 6438 if (isa<Constant>(V)) { 6439 ToDemote.push_back(V); 6440 return true; 6441 } 6442 6443 // If the value is not an instruction in the expression with only one use, it 6444 // cannot be demoted. 6445 auto *I = dyn_cast<Instruction>(V); 6446 if (!I || !I->hasOneUse() || !Expr.count(I)) 6447 return false; 6448 6449 switch (I->getOpcode()) { 6450 6451 // We can always demote truncations and extensions. Since truncations can 6452 // seed additional demotion, we save the truncated value. 6453 case Instruction::Trunc: 6454 Roots.push_back(I->getOperand(0)); 6455 break; 6456 case Instruction::ZExt: 6457 case Instruction::SExt: 6458 if (isa<ExtractElementInst>(I->getOperand(0)) || 6459 isa<InsertElementInst>(I->getOperand(0))) 6460 return false; 6461 break; 6462 6463 // We can demote certain binary operations if we can demote both of their 6464 // operands. 6465 case Instruction::Add: 6466 case Instruction::Sub: 6467 case Instruction::Mul: 6468 case Instruction::And: 6469 case Instruction::Or: 6470 case Instruction::Xor: 6471 if (!collectValuesToDemote(I->getOperand(0), Expr, ToDemote, Roots) || 6472 !collectValuesToDemote(I->getOperand(1), Expr, ToDemote, Roots)) 6473 return false; 6474 break; 6475 6476 // We can demote selects if we can demote their true and false values. 6477 case Instruction::Select: { 6478 SelectInst *SI = cast<SelectInst>(I); 6479 if (!collectValuesToDemote(SI->getTrueValue(), Expr, ToDemote, Roots) || 6480 !collectValuesToDemote(SI->getFalseValue(), Expr, ToDemote, Roots)) 6481 return false; 6482 break; 6483 } 6484 6485 // We can demote phis if we can demote all their incoming operands. Note that 6486 // we don't need to worry about cycles since we ensure single use above. 6487 case Instruction::PHI: { 6488 PHINode *PN = cast<PHINode>(I); 6489 for (Value *IncValue : PN->incoming_values()) 6490 if (!collectValuesToDemote(IncValue, Expr, ToDemote, Roots)) 6491 return false; 6492 break; 6493 } 6494 6495 // Otherwise, conservatively give up. 6496 default: 6497 return false; 6498 } 6499 6500 // Record the value that we can demote. 6501 ToDemote.push_back(V); 6502 return true; 6503 } 6504 6505 void BoUpSLP::computeMinimumValueSizes() { 6506 // If there are no external uses, the expression tree must be rooted by a 6507 // store. We can't demote in-memory values, so there is nothing to do here. 6508 if (ExternalUses.empty()) 6509 return; 6510 6511 // We only attempt to truncate integer expressions. 6512 auto &TreeRoot = VectorizableTree[0]->Scalars; 6513 auto *TreeRootIT = dyn_cast<IntegerType>(TreeRoot[0]->getType()); 6514 if (!TreeRootIT) 6515 return; 6516 6517 // If the expression is not rooted by a store, these roots should have 6518 // external uses. We will rely on InstCombine to rewrite the expression in 6519 // the narrower type. However, InstCombine only rewrites single-use values. 6520 // This means that if a tree entry other than a root is used externally, it 6521 // must have multiple uses and InstCombine will not rewrite it. The code 6522 // below ensures that only the roots are used externally. 6523 SmallPtrSet<Value *, 32> Expr(TreeRoot.begin(), TreeRoot.end()); 6524 for (auto &EU : ExternalUses) 6525 if (!Expr.erase(EU.Scalar)) 6526 return; 6527 if (!Expr.empty()) 6528 return; 6529 6530 // Collect the scalar values of the vectorizable expression. We will use this 6531 // context to determine which values can be demoted. If we see a truncation, 6532 // we mark it as seeding another demotion. 6533 for (auto &EntryPtr : VectorizableTree) 6534 Expr.insert(EntryPtr->Scalars.begin(), EntryPtr->Scalars.end()); 6535 6536 // Ensure the roots of the vectorizable tree don't form a cycle. They must 6537 // have a single external user that is not in the vectorizable tree. 6538 for (auto *Root : TreeRoot) 6539 if (!Root->hasOneUse() || Expr.count(*Root->user_begin())) 6540 return; 6541 6542 // Conservatively determine if we can actually truncate the roots of the 6543 // expression. Collect the values that can be demoted in ToDemote and 6544 // additional roots that require investigating in Roots. 6545 SmallVector<Value *, 32> ToDemote; 6546 SmallVector<Value *, 4> Roots; 6547 for (auto *Root : TreeRoot) 6548 if (!collectValuesToDemote(Root, Expr, ToDemote, Roots)) 6549 return; 6550 6551 // The maximum bit width required to represent all the values that can be 6552 // demoted without loss of precision. It would be safe to truncate the roots 6553 // of the expression to this width. 6554 auto MaxBitWidth = 8u; 6555 6556 // We first check if all the bits of the roots are demanded. If they're not, 6557 // we can truncate the roots to this narrower type. 6558 for (auto *Root : TreeRoot) { 6559 auto Mask = DB->getDemandedBits(cast<Instruction>(Root)); 6560 MaxBitWidth = std::max<unsigned>( 6561 Mask.getBitWidth() - Mask.countLeadingZeros(), MaxBitWidth); 6562 } 6563 6564 // True if the roots can be zero-extended back to their original type, rather 6565 // than sign-extended. We know that if the leading bits are not demanded, we 6566 // can safely zero-extend. So we initialize IsKnownPositive to True. 6567 bool IsKnownPositive = true; 6568 6569 // If all the bits of the roots are demanded, we can try a little harder to 6570 // compute a narrower type. This can happen, for example, if the roots are 6571 // getelementptr indices. InstCombine promotes these indices to the pointer 6572 // width. Thus, all their bits are technically demanded even though the 6573 // address computation might be vectorized in a smaller type. 6574 // 6575 // We start by looking at each entry that can be demoted. We compute the 6576 // maximum bit width required to store the scalar by using ValueTracking to 6577 // compute the number of high-order bits we can truncate. 6578 if (MaxBitWidth == DL->getTypeSizeInBits(TreeRoot[0]->getType()) && 6579 llvm::all_of(TreeRoot, [](Value *R) { 6580 assert(R->hasOneUse() && "Root should have only one use!"); 6581 return isa<GetElementPtrInst>(R->user_back()); 6582 })) { 6583 MaxBitWidth = 8u; 6584 6585 // Determine if the sign bit of all the roots is known to be zero. If not, 6586 // IsKnownPositive is set to False. 6587 IsKnownPositive = llvm::all_of(TreeRoot, [&](Value *R) { 6588 KnownBits Known = computeKnownBits(R, *DL); 6589 return Known.isNonNegative(); 6590 }); 6591 6592 // Determine the maximum number of bits required to store the scalar 6593 // values. 6594 for (auto *Scalar : ToDemote) { 6595 auto NumSignBits = ComputeNumSignBits(Scalar, *DL, 0, AC, nullptr, DT); 6596 auto NumTypeBits = DL->getTypeSizeInBits(Scalar->getType()); 6597 MaxBitWidth = std::max<unsigned>(NumTypeBits - NumSignBits, MaxBitWidth); 6598 } 6599 6600 // If we can't prove that the sign bit is zero, we must add one to the 6601 // maximum bit width to account for the unknown sign bit. This preserves 6602 // the existing sign bit so we can safely sign-extend the root back to the 6603 // original type. Otherwise, if we know the sign bit is zero, we will 6604 // zero-extend the root instead. 6605 // 6606 // FIXME: This is somewhat suboptimal, as there will be cases where adding 6607 // one to the maximum bit width will yield a larger-than-necessary 6608 // type. In general, we need to add an extra bit only if we can't 6609 // prove that the upper bit of the original type is equal to the 6610 // upper bit of the proposed smaller type. If these two bits are the 6611 // same (either zero or one) we know that sign-extending from the 6612 // smaller type will result in the same value. Here, since we can't 6613 // yet prove this, we are just making the proposed smaller type 6614 // larger to ensure correctness. 6615 if (!IsKnownPositive) 6616 ++MaxBitWidth; 6617 } 6618 6619 // Round MaxBitWidth up to the next power-of-two. 6620 if (!isPowerOf2_64(MaxBitWidth)) 6621 MaxBitWidth = NextPowerOf2(MaxBitWidth); 6622 6623 // If the maximum bit width we compute is less than the with of the roots' 6624 // type, we can proceed with the narrowing. Otherwise, do nothing. 6625 if (MaxBitWidth >= TreeRootIT->getBitWidth()) 6626 return; 6627 6628 // If we can truncate the root, we must collect additional values that might 6629 // be demoted as a result. That is, those seeded by truncations we will 6630 // modify. 6631 while (!Roots.empty()) 6632 collectValuesToDemote(Roots.pop_back_val(), Expr, ToDemote, Roots); 6633 6634 // Finally, map the values we can demote to the maximum bit with we computed. 6635 for (auto *Scalar : ToDemote) 6636 MinBWs[Scalar] = std::make_pair(MaxBitWidth, !IsKnownPositive); 6637 } 6638 6639 namespace { 6640 6641 /// The SLPVectorizer Pass. 6642 struct SLPVectorizer : public FunctionPass { 6643 SLPVectorizerPass Impl; 6644 6645 /// Pass identification, replacement for typeid 6646 static char ID; 6647 6648 explicit SLPVectorizer() : FunctionPass(ID) { 6649 initializeSLPVectorizerPass(*PassRegistry::getPassRegistry()); 6650 } 6651 6652 bool doInitialization(Module &M) override { 6653 return false; 6654 } 6655 6656 bool runOnFunction(Function &F) override { 6657 if (skipFunction(F)) 6658 return false; 6659 6660 auto *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 6661 auto *TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F); 6662 auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>(); 6663 auto *TLI = TLIP ? &TLIP->getTLI(F) : nullptr; 6664 auto *AA = &getAnalysis<AAResultsWrapperPass>().getAAResults(); 6665 auto *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 6666 auto *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 6667 auto *AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F); 6668 auto *DB = &getAnalysis<DemandedBitsWrapperPass>().getDemandedBits(); 6669 auto *ORE = &getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE(); 6670 6671 return Impl.runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 6672 } 6673 6674 void getAnalysisUsage(AnalysisUsage &AU) const override { 6675 FunctionPass::getAnalysisUsage(AU); 6676 AU.addRequired<AssumptionCacheTracker>(); 6677 AU.addRequired<ScalarEvolutionWrapperPass>(); 6678 AU.addRequired<AAResultsWrapperPass>(); 6679 AU.addRequired<TargetTransformInfoWrapperPass>(); 6680 AU.addRequired<LoopInfoWrapperPass>(); 6681 AU.addRequired<DominatorTreeWrapperPass>(); 6682 AU.addRequired<DemandedBitsWrapperPass>(); 6683 AU.addRequired<OptimizationRemarkEmitterWrapperPass>(); 6684 AU.addRequired<InjectTLIMappingsLegacy>(); 6685 AU.addPreserved<LoopInfoWrapperPass>(); 6686 AU.addPreserved<DominatorTreeWrapperPass>(); 6687 AU.addPreserved<AAResultsWrapperPass>(); 6688 AU.addPreserved<GlobalsAAWrapperPass>(); 6689 AU.setPreservesCFG(); 6690 } 6691 }; 6692 6693 } // end anonymous namespace 6694 6695 PreservedAnalyses SLPVectorizerPass::run(Function &F, FunctionAnalysisManager &AM) { 6696 auto *SE = &AM.getResult<ScalarEvolutionAnalysis>(F); 6697 auto *TTI = &AM.getResult<TargetIRAnalysis>(F); 6698 auto *TLI = AM.getCachedResult<TargetLibraryAnalysis>(F); 6699 auto *AA = &AM.getResult<AAManager>(F); 6700 auto *LI = &AM.getResult<LoopAnalysis>(F); 6701 auto *DT = &AM.getResult<DominatorTreeAnalysis>(F); 6702 auto *AC = &AM.getResult<AssumptionAnalysis>(F); 6703 auto *DB = &AM.getResult<DemandedBitsAnalysis>(F); 6704 auto *ORE = &AM.getResult<OptimizationRemarkEmitterAnalysis>(F); 6705 6706 bool Changed = runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 6707 if (!Changed) 6708 return PreservedAnalyses::all(); 6709 6710 PreservedAnalyses PA; 6711 PA.preserveSet<CFGAnalyses>(); 6712 return PA; 6713 } 6714 6715 bool SLPVectorizerPass::runImpl(Function &F, ScalarEvolution *SE_, 6716 TargetTransformInfo *TTI_, 6717 TargetLibraryInfo *TLI_, AAResults *AA_, 6718 LoopInfo *LI_, DominatorTree *DT_, 6719 AssumptionCache *AC_, DemandedBits *DB_, 6720 OptimizationRemarkEmitter *ORE_) { 6721 if (!RunSLPVectorization) 6722 return false; 6723 SE = SE_; 6724 TTI = TTI_; 6725 TLI = TLI_; 6726 AA = AA_; 6727 LI = LI_; 6728 DT = DT_; 6729 AC = AC_; 6730 DB = DB_; 6731 DL = &F.getParent()->getDataLayout(); 6732 6733 Stores.clear(); 6734 GEPs.clear(); 6735 bool Changed = false; 6736 6737 // If the target claims to have no vector registers don't attempt 6738 // vectorization. 6739 if (!TTI->getNumberOfRegisters(TTI->getRegisterClassForType(true))) 6740 return false; 6741 6742 // Don't vectorize when the attribute NoImplicitFloat is used. 6743 if (F.hasFnAttribute(Attribute::NoImplicitFloat)) 6744 return false; 6745 6746 LLVM_DEBUG(dbgs() << "SLP: Analyzing blocks in " << F.getName() << ".\n"); 6747 6748 // Use the bottom up slp vectorizer to construct chains that start with 6749 // store instructions. 6750 BoUpSLP R(&F, SE, TTI, TLI, AA, LI, DT, AC, DB, DL, ORE_); 6751 6752 // A general note: the vectorizer must use BoUpSLP::eraseInstruction() to 6753 // delete instructions. 6754 6755 // Update DFS numbers now so that we can use them for ordering. 6756 DT->updateDFSNumbers(); 6757 6758 // Scan the blocks in the function in post order. 6759 for (auto BB : post_order(&F.getEntryBlock())) { 6760 collectSeedInstructions(BB); 6761 6762 // Vectorize trees that end at stores. 6763 if (!Stores.empty()) { 6764 LLVM_DEBUG(dbgs() << "SLP: Found stores for " << Stores.size() 6765 << " underlying objects.\n"); 6766 Changed |= vectorizeStoreChains(R); 6767 } 6768 6769 // Vectorize trees that end at reductions. 6770 Changed |= vectorizeChainsInBlock(BB, R); 6771 6772 // Vectorize the index computations of getelementptr instructions. This 6773 // is primarily intended to catch gather-like idioms ending at 6774 // non-consecutive loads. 6775 if (!GEPs.empty()) { 6776 LLVM_DEBUG(dbgs() << "SLP: Found GEPs for " << GEPs.size() 6777 << " underlying objects.\n"); 6778 Changed |= vectorizeGEPIndices(BB, R); 6779 } 6780 } 6781 6782 if (Changed) { 6783 R.optimizeGatherSequence(); 6784 LLVM_DEBUG(dbgs() << "SLP: vectorized \"" << F.getName() << "\"\n"); 6785 } 6786 return Changed; 6787 } 6788 6789 /// Order may have elements assigned special value (size) which is out of 6790 /// bounds. Such indices only appear on places which correspond to undef values 6791 /// (see canReuseExtract for details) and used in order to avoid undef values 6792 /// have effect on operands ordering. 6793 /// The first loop below simply finds all unused indices and then the next loop 6794 /// nest assigns these indices for undef values positions. 6795 /// As an example below Order has two undef positions and they have assigned 6796 /// values 3 and 7 respectively: 6797 /// before: 6 9 5 4 9 2 1 0 6798 /// after: 6 3 5 4 7 2 1 0 6799 /// \returns Fixed ordering. 6800 static BoUpSLP::OrdersType fixupOrderingIndices(ArrayRef<unsigned> Order) { 6801 BoUpSLP::OrdersType NewOrder(Order.begin(), Order.end()); 6802 const unsigned Sz = NewOrder.size(); 6803 SmallBitVector UsedIndices(Sz); 6804 SmallVector<int> MaskedIndices; 6805 for (int I = 0, E = NewOrder.size(); I < E; ++I) { 6806 if (NewOrder[I] < Sz) 6807 UsedIndices.set(NewOrder[I]); 6808 else 6809 MaskedIndices.push_back(I); 6810 } 6811 if (MaskedIndices.empty()) 6812 return NewOrder; 6813 SmallVector<int> AvailableIndices(MaskedIndices.size()); 6814 unsigned Cnt = 0; 6815 int Idx = UsedIndices.find_first(); 6816 do { 6817 AvailableIndices[Cnt] = Idx; 6818 Idx = UsedIndices.find_next(Idx); 6819 ++Cnt; 6820 } while (Idx > 0); 6821 assert(Cnt == MaskedIndices.size() && "Non-synced masked/available indices."); 6822 for (int I = 0, E = MaskedIndices.size(); I < E; ++I) 6823 NewOrder[MaskedIndices[I]] = AvailableIndices[I]; 6824 return NewOrder; 6825 } 6826 6827 bool SLPVectorizerPass::vectorizeStoreChain(ArrayRef<Value *> Chain, BoUpSLP &R, 6828 unsigned Idx) { 6829 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " << Chain.size() 6830 << "\n"); 6831 const unsigned Sz = R.getVectorElementSize(Chain[0]); 6832 const unsigned MinVF = R.getMinVecRegSize() / Sz; 6833 unsigned VF = Chain.size(); 6834 6835 if (!isPowerOf2_32(Sz) || !isPowerOf2_32(VF) || VF < 2 || VF < MinVF) 6836 return false; 6837 6838 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << VF << " stores at offset " << Idx 6839 << "\n"); 6840 6841 R.buildTree(Chain); 6842 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 6843 // TODO: Handle orders of size less than number of elements in the vector. 6844 if (Order && Order->size() == Chain.size()) { 6845 // TODO: reorder tree nodes without tree rebuilding. 6846 SmallVector<Value *, 4> ReorderedOps(Chain.size()); 6847 transform(fixupOrderingIndices(*Order), ReorderedOps.begin(), 6848 [Chain](const unsigned Idx) { return Chain[Idx]; }); 6849 R.buildTree(ReorderedOps); 6850 } 6851 if (R.isTreeTinyAndNotFullyVectorizable()) 6852 return false; 6853 if (R.isLoadCombineCandidate()) 6854 return false; 6855 6856 R.computeMinimumValueSizes(); 6857 6858 InstructionCost Cost = R.getTreeCost(); 6859 6860 LLVM_DEBUG(dbgs() << "SLP: Found cost = " << Cost << " for VF =" << VF << "\n"); 6861 if (Cost < -SLPCostThreshold) { 6862 LLVM_DEBUG(dbgs() << "SLP: Decided to vectorize cost = " << Cost << "\n"); 6863 6864 using namespace ore; 6865 6866 R.getORE()->emit(OptimizationRemark(SV_NAME, "StoresVectorized", 6867 cast<StoreInst>(Chain[0])) 6868 << "Stores SLP vectorized with cost " << NV("Cost", Cost) 6869 << " and with tree size " 6870 << NV("TreeSize", R.getTreeSize())); 6871 6872 R.vectorizeTree(); 6873 return true; 6874 } 6875 6876 return false; 6877 } 6878 6879 bool SLPVectorizerPass::vectorizeStores(ArrayRef<StoreInst *> Stores, 6880 BoUpSLP &R) { 6881 // We may run into multiple chains that merge into a single chain. We mark the 6882 // stores that we vectorized so that we don't visit the same store twice. 6883 BoUpSLP::ValueSet VectorizedStores; 6884 bool Changed = false; 6885 6886 int E = Stores.size(); 6887 SmallBitVector Tails(E, false); 6888 int MaxIter = MaxStoreLookup.getValue(); 6889 SmallVector<std::pair<int, int>, 16> ConsecutiveChain( 6890 E, std::make_pair(E, INT_MAX)); 6891 SmallVector<SmallBitVector, 4> CheckedPairs(E, SmallBitVector(E, false)); 6892 int IterCnt; 6893 auto &&FindConsecutiveAccess = [this, &Stores, &Tails, &IterCnt, MaxIter, 6894 &CheckedPairs, 6895 &ConsecutiveChain](int K, int Idx) { 6896 if (IterCnt >= MaxIter) 6897 return true; 6898 if (CheckedPairs[Idx].test(K)) 6899 return ConsecutiveChain[K].second == 1 && 6900 ConsecutiveChain[K].first == Idx; 6901 ++IterCnt; 6902 CheckedPairs[Idx].set(K); 6903 CheckedPairs[K].set(Idx); 6904 Optional<int> Diff = getPointersDiff( 6905 Stores[K]->getValueOperand()->getType(), Stores[K]->getPointerOperand(), 6906 Stores[Idx]->getValueOperand()->getType(), 6907 Stores[Idx]->getPointerOperand(), *DL, *SE, /*StrictCheck=*/true); 6908 if (!Diff || *Diff == 0) 6909 return false; 6910 int Val = *Diff; 6911 if (Val < 0) { 6912 if (ConsecutiveChain[Idx].second > -Val) { 6913 Tails.set(K); 6914 ConsecutiveChain[Idx] = std::make_pair(K, -Val); 6915 } 6916 return false; 6917 } 6918 if (ConsecutiveChain[K].second <= Val) 6919 return false; 6920 6921 Tails.set(Idx); 6922 ConsecutiveChain[K] = std::make_pair(Idx, Val); 6923 return Val == 1; 6924 }; 6925 // Do a quadratic search on all of the given stores in reverse order and find 6926 // all of the pairs of stores that follow each other. 6927 for (int Idx = E - 1; Idx >= 0; --Idx) { 6928 // If a store has multiple consecutive store candidates, search according 6929 // to the sequence: Idx-1, Idx+1, Idx-2, Idx+2, ... 6930 // This is because usually pairing with immediate succeeding or preceding 6931 // candidate create the best chance to find slp vectorization opportunity. 6932 const int MaxLookDepth = std::max(E - Idx, Idx + 1); 6933 IterCnt = 0; 6934 for (int Offset = 1, F = MaxLookDepth; Offset < F; ++Offset) 6935 if ((Idx >= Offset && FindConsecutiveAccess(Idx - Offset, Idx)) || 6936 (Idx + Offset < E && FindConsecutiveAccess(Idx + Offset, Idx))) 6937 break; 6938 } 6939 6940 // Tracks if we tried to vectorize stores starting from the given tail 6941 // already. 6942 SmallBitVector TriedTails(E, false); 6943 // For stores that start but don't end a link in the chain: 6944 for (int Cnt = E; Cnt > 0; --Cnt) { 6945 int I = Cnt - 1; 6946 if (ConsecutiveChain[I].first == E || Tails.test(I)) 6947 continue; 6948 // We found a store instr that starts a chain. Now follow the chain and try 6949 // to vectorize it. 6950 BoUpSLP::ValueList Operands; 6951 // Collect the chain into a list. 6952 while (I != E && !VectorizedStores.count(Stores[I])) { 6953 Operands.push_back(Stores[I]); 6954 Tails.set(I); 6955 if (ConsecutiveChain[I].second != 1) { 6956 // Mark the new end in the chain and go back, if required. It might be 6957 // required if the original stores come in reversed order, for example. 6958 if (ConsecutiveChain[I].first != E && 6959 Tails.test(ConsecutiveChain[I].first) && !TriedTails.test(I) && 6960 !VectorizedStores.count(Stores[ConsecutiveChain[I].first])) { 6961 TriedTails.set(I); 6962 Tails.reset(ConsecutiveChain[I].first); 6963 if (Cnt < ConsecutiveChain[I].first + 2) 6964 Cnt = ConsecutiveChain[I].first + 2; 6965 } 6966 break; 6967 } 6968 // Move to the next value in the chain. 6969 I = ConsecutiveChain[I].first; 6970 } 6971 assert(!Operands.empty() && "Expected non-empty list of stores."); 6972 6973 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 6974 unsigned EltSize = R.getVectorElementSize(Operands[0]); 6975 unsigned MaxElts = llvm::PowerOf2Floor(MaxVecRegSize / EltSize); 6976 6977 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / EltSize); 6978 unsigned MaxVF = std::min(R.getMaximumVF(EltSize, Instruction::Store), 6979 MaxElts); 6980 6981 // FIXME: Is division-by-2 the correct step? Should we assert that the 6982 // register size is a power-of-2? 6983 unsigned StartIdx = 0; 6984 for (unsigned Size = MaxVF; Size >= MinVF; Size /= 2) { 6985 for (unsigned Cnt = StartIdx, E = Operands.size(); Cnt + Size <= E;) { 6986 ArrayRef<Value *> Slice = makeArrayRef(Operands).slice(Cnt, Size); 6987 if (!VectorizedStores.count(Slice.front()) && 6988 !VectorizedStores.count(Slice.back()) && 6989 vectorizeStoreChain(Slice, R, Cnt)) { 6990 // Mark the vectorized stores so that we don't vectorize them again. 6991 VectorizedStores.insert(Slice.begin(), Slice.end()); 6992 Changed = true; 6993 // If we vectorized initial block, no need to try to vectorize it 6994 // again. 6995 if (Cnt == StartIdx) 6996 StartIdx += Size; 6997 Cnt += Size; 6998 continue; 6999 } 7000 ++Cnt; 7001 } 7002 // Check if the whole array was vectorized already - exit. 7003 if (StartIdx >= Operands.size()) 7004 break; 7005 } 7006 } 7007 7008 return Changed; 7009 } 7010 7011 void SLPVectorizerPass::collectSeedInstructions(BasicBlock *BB) { 7012 // Initialize the collections. We will make a single pass over the block. 7013 Stores.clear(); 7014 GEPs.clear(); 7015 7016 // Visit the store and getelementptr instructions in BB and organize them in 7017 // Stores and GEPs according to the underlying objects of their pointer 7018 // operands. 7019 for (Instruction &I : *BB) { 7020 // Ignore store instructions that are volatile or have a pointer operand 7021 // that doesn't point to a scalar type. 7022 if (auto *SI = dyn_cast<StoreInst>(&I)) { 7023 if (!SI->isSimple()) 7024 continue; 7025 if (!isValidElementType(SI->getValueOperand()->getType())) 7026 continue; 7027 Stores[getUnderlyingObject(SI->getPointerOperand())].push_back(SI); 7028 } 7029 7030 // Ignore getelementptr instructions that have more than one index, a 7031 // constant index, or a pointer operand that doesn't point to a scalar 7032 // type. 7033 else if (auto *GEP = dyn_cast<GetElementPtrInst>(&I)) { 7034 auto Idx = GEP->idx_begin()->get(); 7035 if (GEP->getNumIndices() > 1 || isa<Constant>(Idx)) 7036 continue; 7037 if (!isValidElementType(Idx->getType())) 7038 continue; 7039 if (GEP->getType()->isVectorTy()) 7040 continue; 7041 GEPs[GEP->getPointerOperand()].push_back(GEP); 7042 } 7043 } 7044 } 7045 7046 bool SLPVectorizerPass::tryToVectorizePair(Value *A, Value *B, BoUpSLP &R) { 7047 if (!A || !B) 7048 return false; 7049 Value *VL[] = {A, B}; 7050 return tryToVectorizeList(VL, R, /*AllowReorder=*/true); 7051 } 7052 7053 bool SLPVectorizerPass::tryToVectorizeList(ArrayRef<Value *> VL, BoUpSLP &R, 7054 bool AllowReorder) { 7055 if (VL.size() < 2) 7056 return false; 7057 7058 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize a list of length = " 7059 << VL.size() << ".\n"); 7060 7061 // Check that all of the parts are instructions of the same type, 7062 // we permit an alternate opcode via InstructionsState. 7063 InstructionsState S = getSameOpcode(VL); 7064 if (!S.getOpcode()) 7065 return false; 7066 7067 Instruction *I0 = cast<Instruction>(S.OpValue); 7068 // Make sure invalid types (including vector type) are rejected before 7069 // determining vectorization factor for scalar instructions. 7070 for (Value *V : VL) { 7071 Type *Ty = V->getType(); 7072 if (!isa<InsertElementInst>(V) && !isValidElementType(Ty)) { 7073 // NOTE: the following will give user internal llvm type name, which may 7074 // not be useful. 7075 R.getORE()->emit([&]() { 7076 std::string type_str; 7077 llvm::raw_string_ostream rso(type_str); 7078 Ty->print(rso); 7079 return OptimizationRemarkMissed(SV_NAME, "UnsupportedType", I0) 7080 << "Cannot SLP vectorize list: type " 7081 << rso.str() + " is unsupported by vectorizer"; 7082 }); 7083 return false; 7084 } 7085 } 7086 7087 unsigned Sz = R.getVectorElementSize(I0); 7088 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / Sz); 7089 unsigned MaxVF = std::max<unsigned>(PowerOf2Floor(VL.size()), MinVF); 7090 MaxVF = std::min(R.getMaximumVF(Sz, S.getOpcode()), MaxVF); 7091 if (MaxVF < 2) { 7092 R.getORE()->emit([&]() { 7093 return OptimizationRemarkMissed(SV_NAME, "SmallVF", I0) 7094 << "Cannot SLP vectorize list: vectorization factor " 7095 << "less than 2 is not supported"; 7096 }); 7097 return false; 7098 } 7099 7100 bool Changed = false; 7101 bool CandidateFound = false; 7102 InstructionCost MinCost = SLPCostThreshold.getValue(); 7103 Type *ScalarTy = VL[0]->getType(); 7104 if (auto *IE = dyn_cast<InsertElementInst>(VL[0])) 7105 ScalarTy = IE->getOperand(1)->getType(); 7106 7107 unsigned NextInst = 0, MaxInst = VL.size(); 7108 for (unsigned VF = MaxVF; NextInst + 1 < MaxInst && VF >= MinVF; VF /= 2) { 7109 // No actual vectorization should happen, if number of parts is the same as 7110 // provided vectorization factor (i.e. the scalar type is used for vector 7111 // code during codegen). 7112 auto *VecTy = FixedVectorType::get(ScalarTy, VF); 7113 if (TTI->getNumberOfParts(VecTy) == VF) 7114 continue; 7115 for (unsigned I = NextInst; I < MaxInst; ++I) { 7116 unsigned OpsWidth = 0; 7117 7118 if (I + VF > MaxInst) 7119 OpsWidth = MaxInst - I; 7120 else 7121 OpsWidth = VF; 7122 7123 if (!isPowerOf2_32(OpsWidth)) 7124 continue; 7125 7126 if ((VF > MinVF && OpsWidth <= VF / 2) || (VF == MinVF && OpsWidth < 2)) 7127 break; 7128 7129 ArrayRef<Value *> Ops = VL.slice(I, OpsWidth); 7130 // Check that a previous iteration of this loop did not delete the Value. 7131 if (llvm::any_of(Ops, [&R](Value *V) { 7132 auto *I = dyn_cast<Instruction>(V); 7133 return I && R.isDeleted(I); 7134 })) 7135 continue; 7136 7137 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << OpsWidth << " operations " 7138 << "\n"); 7139 7140 R.buildTree(Ops); 7141 if (AllowReorder) { 7142 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 7143 if (Order) { 7144 // TODO: reorder tree nodes without tree rebuilding. 7145 SmallVector<Value *, 4> ReorderedOps(Ops.size()); 7146 transform(fixupOrderingIndices(*Order), ReorderedOps.begin(), 7147 [Ops](const unsigned Idx) { return Ops[Idx]; }); 7148 R.buildTree(ReorderedOps); 7149 } 7150 } 7151 if (R.isTreeTinyAndNotFullyVectorizable()) 7152 continue; 7153 7154 R.computeMinimumValueSizes(); 7155 InstructionCost Cost = R.getTreeCost(); 7156 CandidateFound = true; 7157 MinCost = std::min(MinCost, Cost); 7158 7159 if (Cost < -SLPCostThreshold) { 7160 LLVM_DEBUG(dbgs() << "SLP: Vectorizing list at cost:" << Cost << ".\n"); 7161 R.getORE()->emit(OptimizationRemark(SV_NAME, "VectorizedList", 7162 cast<Instruction>(Ops[0])) 7163 << "SLP vectorized with cost " << ore::NV("Cost", Cost) 7164 << " and with tree size " 7165 << ore::NV("TreeSize", R.getTreeSize())); 7166 7167 R.vectorizeTree(); 7168 // Move to the next bundle. 7169 I += VF - 1; 7170 NextInst = I + 1; 7171 Changed = true; 7172 } 7173 } 7174 } 7175 7176 if (!Changed && CandidateFound) { 7177 R.getORE()->emit([&]() { 7178 return OptimizationRemarkMissed(SV_NAME, "NotBeneficial", I0) 7179 << "List vectorization was possible but not beneficial with cost " 7180 << ore::NV("Cost", MinCost) << " >= " 7181 << ore::NV("Treshold", -SLPCostThreshold); 7182 }); 7183 } else if (!Changed) { 7184 R.getORE()->emit([&]() { 7185 return OptimizationRemarkMissed(SV_NAME, "NotPossible", I0) 7186 << "Cannot SLP vectorize list: vectorization was impossible" 7187 << " with available vectorization factors"; 7188 }); 7189 } 7190 return Changed; 7191 } 7192 7193 bool SLPVectorizerPass::tryToVectorize(Instruction *I, BoUpSLP &R) { 7194 if (!I) 7195 return false; 7196 7197 if (!isa<BinaryOperator>(I) && !isa<CmpInst>(I)) 7198 return false; 7199 7200 Value *P = I->getParent(); 7201 7202 // Vectorize in current basic block only. 7203 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 7204 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 7205 if (!Op0 || !Op1 || Op0->getParent() != P || Op1->getParent() != P) 7206 return false; 7207 7208 // Try to vectorize V. 7209 if (tryToVectorizePair(Op0, Op1, R)) 7210 return true; 7211 7212 auto *A = dyn_cast<BinaryOperator>(Op0); 7213 auto *B = dyn_cast<BinaryOperator>(Op1); 7214 // Try to skip B. 7215 if (B && B->hasOneUse()) { 7216 auto *B0 = dyn_cast<BinaryOperator>(B->getOperand(0)); 7217 auto *B1 = dyn_cast<BinaryOperator>(B->getOperand(1)); 7218 if (B0 && B0->getParent() == P && tryToVectorizePair(A, B0, R)) 7219 return true; 7220 if (B1 && B1->getParent() == P && tryToVectorizePair(A, B1, R)) 7221 return true; 7222 } 7223 7224 // Try to skip A. 7225 if (A && A->hasOneUse()) { 7226 auto *A0 = dyn_cast<BinaryOperator>(A->getOperand(0)); 7227 auto *A1 = dyn_cast<BinaryOperator>(A->getOperand(1)); 7228 if (A0 && A0->getParent() == P && tryToVectorizePair(A0, B, R)) 7229 return true; 7230 if (A1 && A1->getParent() == P && tryToVectorizePair(A1, B, R)) 7231 return true; 7232 } 7233 return false; 7234 } 7235 7236 namespace { 7237 7238 /// Model horizontal reductions. 7239 /// 7240 /// A horizontal reduction is a tree of reduction instructions that has values 7241 /// that can be put into a vector as its leaves. For example: 7242 /// 7243 /// mul mul mul mul 7244 /// \ / \ / 7245 /// + + 7246 /// \ / 7247 /// + 7248 /// This tree has "mul" as its leaf values and "+" as its reduction 7249 /// instructions. A reduction can feed into a store or a binary operation 7250 /// feeding a phi. 7251 /// ... 7252 /// \ / 7253 /// + 7254 /// | 7255 /// phi += 7256 /// 7257 /// Or: 7258 /// ... 7259 /// \ / 7260 /// + 7261 /// | 7262 /// *p = 7263 /// 7264 class HorizontalReduction { 7265 using ReductionOpsType = SmallVector<Value *, 16>; 7266 using ReductionOpsListType = SmallVector<ReductionOpsType, 2>; 7267 ReductionOpsListType ReductionOps; 7268 SmallVector<Value *, 32> ReducedVals; 7269 // Use map vector to make stable output. 7270 MapVector<Instruction *, Value *> ExtraArgs; 7271 WeakTrackingVH ReductionRoot; 7272 /// The type of reduction operation. 7273 RecurKind RdxKind; 7274 7275 /// Checks if instruction is associative and can be vectorized. 7276 static bool isVectorizable(RecurKind Kind, Instruction *I) { 7277 if (Kind == RecurKind::None) 7278 return false; 7279 if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(Kind)) 7280 return true; 7281 7282 if (Kind == RecurKind::FMax || Kind == RecurKind::FMin) { 7283 // FP min/max are associative except for NaN and -0.0. We do not 7284 // have to rule out -0.0 here because the intrinsic semantics do not 7285 // specify a fixed result for it. 7286 return I->getFastMathFlags().noNaNs(); 7287 } 7288 7289 return I->isAssociative(); 7290 } 7291 7292 /// Checks if the ParentStackElem.first should be marked as a reduction 7293 /// operation with an extra argument or as extra argument itself. 7294 void markExtraArg(std::pair<Instruction *, unsigned> &ParentStackElem, 7295 Value *ExtraArg) { 7296 if (ExtraArgs.count(ParentStackElem.first)) { 7297 ExtraArgs[ParentStackElem.first] = nullptr; 7298 // We ran into something like: 7299 // ParentStackElem.first = ExtraArgs[ParentStackElem.first] + ExtraArg. 7300 // The whole ParentStackElem.first should be considered as an extra value 7301 // in this case. 7302 // Do not perform analysis of remaining operands of ParentStackElem.first 7303 // instruction, this whole instruction is an extra argument. 7304 ParentStackElem.second = getNumberOfOperands(ParentStackElem.first); 7305 } else { 7306 // We ran into something like: 7307 // ParentStackElem.first += ... + ExtraArg + ... 7308 ExtraArgs[ParentStackElem.first] = ExtraArg; 7309 } 7310 } 7311 7312 /// Creates reduction operation with the current opcode. 7313 static Value *createOp(IRBuilder<> &Builder, RecurKind Kind, Value *LHS, 7314 Value *RHS, const Twine &Name, bool UseSelect) { 7315 unsigned RdxOpcode = RecurrenceDescriptor::getOpcode(Kind); 7316 switch (Kind) { 7317 case RecurKind::Add: 7318 case RecurKind::Mul: 7319 case RecurKind::Or: 7320 case RecurKind::And: 7321 case RecurKind::Xor: 7322 case RecurKind::FAdd: 7323 case RecurKind::FMul: 7324 return Builder.CreateBinOp((Instruction::BinaryOps)RdxOpcode, LHS, RHS, 7325 Name); 7326 case RecurKind::FMax: 7327 return Builder.CreateBinaryIntrinsic(Intrinsic::maxnum, LHS, RHS); 7328 case RecurKind::FMin: 7329 return Builder.CreateBinaryIntrinsic(Intrinsic::minnum, LHS, RHS); 7330 case RecurKind::SMax: 7331 if (UseSelect) { 7332 Value *Cmp = Builder.CreateICmpSGT(LHS, RHS, Name); 7333 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 7334 } 7335 return Builder.CreateBinaryIntrinsic(Intrinsic::smax, LHS, RHS); 7336 case RecurKind::SMin: 7337 if (UseSelect) { 7338 Value *Cmp = Builder.CreateICmpSLT(LHS, RHS, Name); 7339 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 7340 } 7341 return Builder.CreateBinaryIntrinsic(Intrinsic::smin, LHS, RHS); 7342 case RecurKind::UMax: 7343 if (UseSelect) { 7344 Value *Cmp = Builder.CreateICmpUGT(LHS, RHS, Name); 7345 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 7346 } 7347 return Builder.CreateBinaryIntrinsic(Intrinsic::umax, LHS, RHS); 7348 case RecurKind::UMin: 7349 if (UseSelect) { 7350 Value *Cmp = Builder.CreateICmpULT(LHS, RHS, Name); 7351 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 7352 } 7353 return Builder.CreateBinaryIntrinsic(Intrinsic::umin, LHS, RHS); 7354 default: 7355 llvm_unreachable("Unknown reduction operation."); 7356 } 7357 } 7358 7359 /// Creates reduction operation with the current opcode with the IR flags 7360 /// from \p ReductionOps. 7361 static Value *createOp(IRBuilder<> &Builder, RecurKind RdxKind, Value *LHS, 7362 Value *RHS, const Twine &Name, 7363 const ReductionOpsListType &ReductionOps) { 7364 bool UseSelect = ReductionOps.size() == 2; 7365 assert((!UseSelect || isa<SelectInst>(ReductionOps[1][0])) && 7366 "Expected cmp + select pairs for reduction"); 7367 Value *Op = createOp(Builder, RdxKind, LHS, RHS, Name, UseSelect); 7368 if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(RdxKind)) { 7369 if (auto *Sel = dyn_cast<SelectInst>(Op)) { 7370 propagateIRFlags(Sel->getCondition(), ReductionOps[0]); 7371 propagateIRFlags(Op, ReductionOps[1]); 7372 return Op; 7373 } 7374 } 7375 propagateIRFlags(Op, ReductionOps[0]); 7376 return Op; 7377 } 7378 7379 /// Creates reduction operation with the current opcode with the IR flags 7380 /// from \p I. 7381 static Value *createOp(IRBuilder<> &Builder, RecurKind RdxKind, Value *LHS, 7382 Value *RHS, const Twine &Name, Instruction *I) { 7383 auto *SelI = dyn_cast<SelectInst>(I); 7384 Value *Op = createOp(Builder, RdxKind, LHS, RHS, Name, SelI != nullptr); 7385 if (SelI && RecurrenceDescriptor::isIntMinMaxRecurrenceKind(RdxKind)) { 7386 if (auto *Sel = dyn_cast<SelectInst>(Op)) 7387 propagateIRFlags(Sel->getCondition(), SelI->getCondition()); 7388 } 7389 propagateIRFlags(Op, I); 7390 return Op; 7391 } 7392 7393 static RecurKind getRdxKind(Instruction *I) { 7394 assert(I && "Expected instruction for reduction matching"); 7395 TargetTransformInfo::ReductionFlags RdxFlags; 7396 if (match(I, m_Add(m_Value(), m_Value()))) 7397 return RecurKind::Add; 7398 if (match(I, m_Mul(m_Value(), m_Value()))) 7399 return RecurKind::Mul; 7400 if (match(I, m_And(m_Value(), m_Value()))) 7401 return RecurKind::And; 7402 if (match(I, m_Or(m_Value(), m_Value()))) 7403 return RecurKind::Or; 7404 if (match(I, m_Xor(m_Value(), m_Value()))) 7405 return RecurKind::Xor; 7406 if (match(I, m_FAdd(m_Value(), m_Value()))) 7407 return RecurKind::FAdd; 7408 if (match(I, m_FMul(m_Value(), m_Value()))) 7409 return RecurKind::FMul; 7410 7411 if (match(I, m_Intrinsic<Intrinsic::maxnum>(m_Value(), m_Value()))) 7412 return RecurKind::FMax; 7413 if (match(I, m_Intrinsic<Intrinsic::minnum>(m_Value(), m_Value()))) 7414 return RecurKind::FMin; 7415 7416 // This matches either cmp+select or intrinsics. SLP is expected to handle 7417 // either form. 7418 // TODO: If we are canonicalizing to intrinsics, we can remove several 7419 // special-case paths that deal with selects. 7420 if (match(I, m_SMax(m_Value(), m_Value()))) 7421 return RecurKind::SMax; 7422 if (match(I, m_SMin(m_Value(), m_Value()))) 7423 return RecurKind::SMin; 7424 if (match(I, m_UMax(m_Value(), m_Value()))) 7425 return RecurKind::UMax; 7426 if (match(I, m_UMin(m_Value(), m_Value()))) 7427 return RecurKind::UMin; 7428 7429 if (auto *Select = dyn_cast<SelectInst>(I)) { 7430 // Try harder: look for min/max pattern based on instructions producing 7431 // same values such as: select ((cmp Inst1, Inst2), Inst1, Inst2). 7432 // During the intermediate stages of SLP, it's very common to have 7433 // pattern like this (since optimizeGatherSequence is run only once 7434 // at the end): 7435 // %1 = extractelement <2 x i32> %a, i32 0 7436 // %2 = extractelement <2 x i32> %a, i32 1 7437 // %cond = icmp sgt i32 %1, %2 7438 // %3 = extractelement <2 x i32> %a, i32 0 7439 // %4 = extractelement <2 x i32> %a, i32 1 7440 // %select = select i1 %cond, i32 %3, i32 %4 7441 CmpInst::Predicate Pred; 7442 Instruction *L1; 7443 Instruction *L2; 7444 7445 Value *LHS = Select->getTrueValue(); 7446 Value *RHS = Select->getFalseValue(); 7447 Value *Cond = Select->getCondition(); 7448 7449 // TODO: Support inverse predicates. 7450 if (match(Cond, m_Cmp(Pred, m_Specific(LHS), m_Instruction(L2)))) { 7451 if (!isa<ExtractElementInst>(RHS) || 7452 !L2->isIdenticalTo(cast<Instruction>(RHS))) 7453 return RecurKind::None; 7454 } else if (match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Specific(RHS)))) { 7455 if (!isa<ExtractElementInst>(LHS) || 7456 !L1->isIdenticalTo(cast<Instruction>(LHS))) 7457 return RecurKind::None; 7458 } else { 7459 if (!isa<ExtractElementInst>(LHS) || !isa<ExtractElementInst>(RHS)) 7460 return RecurKind::None; 7461 if (!match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Instruction(L2))) || 7462 !L1->isIdenticalTo(cast<Instruction>(LHS)) || 7463 !L2->isIdenticalTo(cast<Instruction>(RHS))) 7464 return RecurKind::None; 7465 } 7466 7467 TargetTransformInfo::ReductionFlags RdxFlags; 7468 switch (Pred) { 7469 default: 7470 return RecurKind::None; 7471 case CmpInst::ICMP_SGT: 7472 case CmpInst::ICMP_SGE: 7473 return RecurKind::SMax; 7474 case CmpInst::ICMP_SLT: 7475 case CmpInst::ICMP_SLE: 7476 return RecurKind::SMin; 7477 case CmpInst::ICMP_UGT: 7478 case CmpInst::ICMP_UGE: 7479 return RecurKind::UMax; 7480 case CmpInst::ICMP_ULT: 7481 case CmpInst::ICMP_ULE: 7482 return RecurKind::UMin; 7483 } 7484 } 7485 return RecurKind::None; 7486 } 7487 7488 /// Get the index of the first operand. 7489 static unsigned getFirstOperandIndex(Instruction *I) { 7490 return isa<SelectInst>(I) ? 1 : 0; 7491 } 7492 7493 /// Total number of operands in the reduction operation. 7494 static unsigned getNumberOfOperands(Instruction *I) { 7495 return isa<SelectInst>(I) ? 3 : 2; 7496 } 7497 7498 /// Checks if the instruction is in basic block \p BB. 7499 /// For a min/max reduction check that both compare and select are in \p BB. 7500 static bool hasSameParent(Instruction *I, BasicBlock *BB, bool IsRedOp) { 7501 auto *Sel = dyn_cast<SelectInst>(I); 7502 if (IsRedOp && Sel) { 7503 auto *Cmp = cast<Instruction>(Sel->getCondition()); 7504 return Sel->getParent() == BB && Cmp->getParent() == BB; 7505 } 7506 return I->getParent() == BB; 7507 } 7508 7509 /// Expected number of uses for reduction operations/reduced values. 7510 static bool hasRequiredNumberOfUses(bool MatchCmpSel, Instruction *I) { 7511 // SelectInst must be used twice while the condition op must have single 7512 // use only. 7513 if (MatchCmpSel) { 7514 if (auto *Sel = dyn_cast<SelectInst>(I)) 7515 return Sel->hasNUses(2) && Sel->getCondition()->hasOneUse(); 7516 return I->hasNUses(2); 7517 } 7518 7519 // Arithmetic reduction operation must be used once only. 7520 return I->hasOneUse(); 7521 } 7522 7523 /// Initializes the list of reduction operations. 7524 void initReductionOps(Instruction *I) { 7525 if (isa<SelectInst>(I)) 7526 ReductionOps.assign(2, ReductionOpsType()); 7527 else 7528 ReductionOps.assign(1, ReductionOpsType()); 7529 } 7530 7531 /// Add all reduction operations for the reduction instruction \p I. 7532 void addReductionOps(Instruction *I) { 7533 if (auto *Sel = dyn_cast<SelectInst>(I)) { 7534 ReductionOps[0].emplace_back(Sel->getCondition()); 7535 ReductionOps[1].emplace_back(Sel); 7536 } else { 7537 ReductionOps[0].emplace_back(I); 7538 } 7539 } 7540 7541 static Value *getLHS(RecurKind Kind, Instruction *I) { 7542 if (Kind == RecurKind::None) 7543 return nullptr; 7544 return I->getOperand(getFirstOperandIndex(I)); 7545 } 7546 static Value *getRHS(RecurKind Kind, Instruction *I) { 7547 if (Kind == RecurKind::None) 7548 return nullptr; 7549 return I->getOperand(getFirstOperandIndex(I) + 1); 7550 } 7551 7552 public: 7553 HorizontalReduction() = default; 7554 7555 /// Try to find a reduction tree. 7556 bool matchAssociativeReduction(PHINode *Phi, Instruction *B) { 7557 assert((!Phi || is_contained(Phi->operands(), B)) && 7558 "Phi needs to use the binary operator"); 7559 7560 RdxKind = getRdxKind(B); 7561 7562 // We could have a initial reductions that is not an add. 7563 // r *= v1 + v2 + v3 + v4 7564 // In such a case start looking for a tree rooted in the first '+'. 7565 if (Phi) { 7566 if (getLHS(RdxKind, B) == Phi) { 7567 Phi = nullptr; 7568 B = dyn_cast<Instruction>(getRHS(RdxKind, B)); 7569 if (!B) 7570 return false; 7571 RdxKind = getRdxKind(B); 7572 } else if (getRHS(RdxKind, B) == Phi) { 7573 Phi = nullptr; 7574 B = dyn_cast<Instruction>(getLHS(RdxKind, B)); 7575 if (!B) 7576 return false; 7577 RdxKind = getRdxKind(B); 7578 } 7579 } 7580 7581 if (!isVectorizable(RdxKind, B)) 7582 return false; 7583 7584 // Analyze "regular" integer/FP types for reductions - no target-specific 7585 // types or pointers. 7586 Type *Ty = B->getType(); 7587 if (!isValidElementType(Ty) || Ty->isPointerTy()) 7588 return false; 7589 7590 // Though the ultimate reduction may have multiple uses, its condition must 7591 // have only single use. 7592 if (auto *SI = dyn_cast<SelectInst>(B)) 7593 if (!SI->getCondition()->hasOneUse()) 7594 return false; 7595 7596 ReductionRoot = B; 7597 7598 // The opcode for leaf values that we perform a reduction on. 7599 // For example: load(x) + load(y) + load(z) + fptoui(w) 7600 // The leaf opcode for 'w' does not match, so we don't include it as a 7601 // potential candidate for the reduction. 7602 unsigned LeafOpcode = 0; 7603 7604 // Post order traverse the reduction tree starting at B. We only handle true 7605 // trees containing only binary operators. 7606 SmallVector<std::pair<Instruction *, unsigned>, 32> Stack; 7607 Stack.push_back(std::make_pair(B, getFirstOperandIndex(B))); 7608 initReductionOps(B); 7609 while (!Stack.empty()) { 7610 Instruction *TreeN = Stack.back().first; 7611 unsigned EdgeToVisit = Stack.back().second++; 7612 const RecurKind TreeRdxKind = getRdxKind(TreeN); 7613 bool IsReducedValue = TreeRdxKind != RdxKind; 7614 7615 // Postorder visit. 7616 if (IsReducedValue || EdgeToVisit == getNumberOfOperands(TreeN)) { 7617 if (IsReducedValue) 7618 ReducedVals.push_back(TreeN); 7619 else { 7620 auto ExtraArgsIter = ExtraArgs.find(TreeN); 7621 if (ExtraArgsIter != ExtraArgs.end() && !ExtraArgsIter->second) { 7622 // Check if TreeN is an extra argument of its parent operation. 7623 if (Stack.size() <= 1) { 7624 // TreeN can't be an extra argument as it is a root reduction 7625 // operation. 7626 return false; 7627 } 7628 // Yes, TreeN is an extra argument, do not add it to a list of 7629 // reduction operations. 7630 // Stack[Stack.size() - 2] always points to the parent operation. 7631 markExtraArg(Stack[Stack.size() - 2], TreeN); 7632 ExtraArgs.erase(TreeN); 7633 } else 7634 addReductionOps(TreeN); 7635 } 7636 // Retract. 7637 Stack.pop_back(); 7638 continue; 7639 } 7640 7641 // Visit left or right. 7642 Value *EdgeVal = TreeN->getOperand(EdgeToVisit); 7643 auto *EdgeInst = dyn_cast<Instruction>(EdgeVal); 7644 if (!EdgeInst) { 7645 // Edge value is not a reduction instruction or a leaf instruction. 7646 // (It may be a constant, function argument, or something else.) 7647 markExtraArg(Stack.back(), EdgeVal); 7648 continue; 7649 } 7650 RecurKind EdgeRdxKind = getRdxKind(EdgeInst); 7651 // Continue analysis if the next operand is a reduction operation or 7652 // (possibly) a leaf value. If the leaf value opcode is not set, 7653 // the first met operation != reduction operation is considered as the 7654 // leaf opcode. 7655 // Only handle trees in the current basic block. 7656 // Each tree node needs to have minimal number of users except for the 7657 // ultimate reduction. 7658 const bool IsRdxInst = EdgeRdxKind == RdxKind; 7659 if (EdgeInst != Phi && EdgeInst != B && 7660 hasSameParent(EdgeInst, B->getParent(), IsRdxInst) && 7661 hasRequiredNumberOfUses(isa<SelectInst>(B), EdgeInst) && 7662 (!LeafOpcode || LeafOpcode == EdgeInst->getOpcode() || IsRdxInst)) { 7663 if (IsRdxInst) { 7664 // We need to be able to reassociate the reduction operations. 7665 if (!isVectorizable(EdgeRdxKind, EdgeInst)) { 7666 // I is an extra argument for TreeN (its parent operation). 7667 markExtraArg(Stack.back(), EdgeInst); 7668 continue; 7669 } 7670 } else if (!LeafOpcode) { 7671 LeafOpcode = EdgeInst->getOpcode(); 7672 } 7673 Stack.push_back( 7674 std::make_pair(EdgeInst, getFirstOperandIndex(EdgeInst))); 7675 continue; 7676 } 7677 // I is an extra argument for TreeN (its parent operation). 7678 markExtraArg(Stack.back(), EdgeInst); 7679 } 7680 return true; 7681 } 7682 7683 /// Attempt to vectorize the tree found by matchAssociativeReduction. 7684 bool tryToReduce(BoUpSLP &V, TargetTransformInfo *TTI) { 7685 // If there are a sufficient number of reduction values, reduce 7686 // to a nearby power-of-2. We can safely generate oversized 7687 // vectors and rely on the backend to split them to legal sizes. 7688 unsigned NumReducedVals = ReducedVals.size(); 7689 if (NumReducedVals < 4) 7690 return false; 7691 7692 // Intersect the fast-math-flags from all reduction operations. 7693 FastMathFlags RdxFMF; 7694 RdxFMF.set(); 7695 for (ReductionOpsType &RdxOp : ReductionOps) { 7696 for (Value *RdxVal : RdxOp) { 7697 if (auto *FPMO = dyn_cast<FPMathOperator>(RdxVal)) 7698 RdxFMF &= FPMO->getFastMathFlags(); 7699 } 7700 } 7701 7702 IRBuilder<> Builder(cast<Instruction>(ReductionRoot)); 7703 Builder.setFastMathFlags(RdxFMF); 7704 7705 BoUpSLP::ExtraValueToDebugLocsMap ExternallyUsedValues; 7706 // The same extra argument may be used several times, so log each attempt 7707 // to use it. 7708 for (const std::pair<Instruction *, Value *> &Pair : ExtraArgs) { 7709 assert(Pair.first && "DebugLoc must be set."); 7710 ExternallyUsedValues[Pair.second].push_back(Pair.first); 7711 } 7712 7713 // The compare instruction of a min/max is the insertion point for new 7714 // instructions and may be replaced with a new compare instruction. 7715 auto getCmpForMinMaxReduction = [](Instruction *RdxRootInst) { 7716 assert(isa<SelectInst>(RdxRootInst) && 7717 "Expected min/max reduction to have select root instruction"); 7718 Value *ScalarCond = cast<SelectInst>(RdxRootInst)->getCondition(); 7719 assert(isa<Instruction>(ScalarCond) && 7720 "Expected min/max reduction to have compare condition"); 7721 return cast<Instruction>(ScalarCond); 7722 }; 7723 7724 // The reduction root is used as the insertion point for new instructions, 7725 // so set it as externally used to prevent it from being deleted. 7726 ExternallyUsedValues[ReductionRoot]; 7727 SmallVector<Value *, 16> IgnoreList; 7728 for (ReductionOpsType &RdxOp : ReductionOps) 7729 IgnoreList.append(RdxOp.begin(), RdxOp.end()); 7730 7731 unsigned ReduxWidth = PowerOf2Floor(NumReducedVals); 7732 if (NumReducedVals > ReduxWidth) { 7733 // In the loop below, we are building a tree based on a window of 7734 // 'ReduxWidth' values. 7735 // If the operands of those values have common traits (compare predicate, 7736 // constant operand, etc), then we want to group those together to 7737 // minimize the cost of the reduction. 7738 7739 // TODO: This should be extended to count common operands for 7740 // compares and binops. 7741 7742 // Step 1: Count the number of times each compare predicate occurs. 7743 SmallDenseMap<unsigned, unsigned> PredCountMap; 7744 for (Value *RdxVal : ReducedVals) { 7745 CmpInst::Predicate Pred; 7746 if (match(RdxVal, m_Cmp(Pred, m_Value(), m_Value()))) 7747 ++PredCountMap[Pred]; 7748 } 7749 // Step 2: Sort the values so the most common predicates come first. 7750 stable_sort(ReducedVals, [&PredCountMap](Value *A, Value *B) { 7751 CmpInst::Predicate PredA, PredB; 7752 if (match(A, m_Cmp(PredA, m_Value(), m_Value())) && 7753 match(B, m_Cmp(PredB, m_Value(), m_Value()))) { 7754 return PredCountMap[PredA] > PredCountMap[PredB]; 7755 } 7756 return false; 7757 }); 7758 } 7759 7760 Value *VectorizedTree = nullptr; 7761 unsigned i = 0; 7762 while (i < NumReducedVals - ReduxWidth + 1 && ReduxWidth > 2) { 7763 ArrayRef<Value *> VL(&ReducedVals[i], ReduxWidth); 7764 V.buildTree(VL, ExternallyUsedValues, IgnoreList); 7765 Optional<ArrayRef<unsigned>> Order = V.bestOrder(); 7766 if (Order) { 7767 assert(Order->size() == VL.size() && 7768 "Order size must be the same as number of vectorized " 7769 "instructions."); 7770 // TODO: reorder tree nodes without tree rebuilding. 7771 SmallVector<Value *, 4> ReorderedOps(VL.size()); 7772 transform(fixupOrderingIndices(*Order), ReorderedOps.begin(), 7773 [VL](const unsigned Idx) { return VL[Idx]; }); 7774 V.buildTree(ReorderedOps, ExternallyUsedValues, IgnoreList); 7775 } 7776 if (V.isTreeTinyAndNotFullyVectorizable()) 7777 break; 7778 if (V.isLoadCombineReductionCandidate(RdxKind)) 7779 break; 7780 7781 V.computeMinimumValueSizes(); 7782 7783 // Estimate cost. 7784 InstructionCost TreeCost = 7785 V.getTreeCost(makeArrayRef(&ReducedVals[i], ReduxWidth)); 7786 InstructionCost ReductionCost = 7787 getReductionCost(TTI, ReducedVals[i], ReduxWidth); 7788 InstructionCost Cost = TreeCost + ReductionCost; 7789 if (!Cost.isValid()) { 7790 LLVM_DEBUG(dbgs() << "Encountered invalid baseline cost.\n"); 7791 return false; 7792 } 7793 if (Cost >= -SLPCostThreshold) { 7794 V.getORE()->emit([&]() { 7795 return OptimizationRemarkMissed(SV_NAME, "HorSLPNotBeneficial", 7796 cast<Instruction>(VL[0])) 7797 << "Vectorizing horizontal reduction is possible" 7798 << "but not beneficial with cost " << ore::NV("Cost", Cost) 7799 << " and threshold " 7800 << ore::NV("Threshold", -SLPCostThreshold); 7801 }); 7802 break; 7803 } 7804 7805 LLVM_DEBUG(dbgs() << "SLP: Vectorizing horizontal reduction at cost:" 7806 << Cost << ". (HorRdx)\n"); 7807 V.getORE()->emit([&]() { 7808 return OptimizationRemark(SV_NAME, "VectorizedHorizontalReduction", 7809 cast<Instruction>(VL[0])) 7810 << "Vectorized horizontal reduction with cost " 7811 << ore::NV("Cost", Cost) << " and with tree size " 7812 << ore::NV("TreeSize", V.getTreeSize()); 7813 }); 7814 7815 // Vectorize a tree. 7816 DebugLoc Loc = cast<Instruction>(ReducedVals[i])->getDebugLoc(); 7817 Value *VectorizedRoot = V.vectorizeTree(ExternallyUsedValues); 7818 7819 // Emit a reduction. If the root is a select (min/max idiom), the insert 7820 // point is the compare condition of that select. 7821 Instruction *RdxRootInst = cast<Instruction>(ReductionRoot); 7822 if (isa<SelectInst>(RdxRootInst)) 7823 Builder.SetInsertPoint(getCmpForMinMaxReduction(RdxRootInst)); 7824 else 7825 Builder.SetInsertPoint(RdxRootInst); 7826 7827 Value *ReducedSubTree = 7828 emitReduction(VectorizedRoot, Builder, ReduxWidth, TTI); 7829 7830 if (!VectorizedTree) { 7831 // Initialize the final value in the reduction. 7832 VectorizedTree = ReducedSubTree; 7833 } else { 7834 // Update the final value in the reduction. 7835 Builder.SetCurrentDebugLocation(Loc); 7836 VectorizedTree = createOp(Builder, RdxKind, VectorizedTree, 7837 ReducedSubTree, "op.rdx", ReductionOps); 7838 } 7839 i += ReduxWidth; 7840 ReduxWidth = PowerOf2Floor(NumReducedVals - i); 7841 } 7842 7843 if (VectorizedTree) { 7844 // Finish the reduction. 7845 for (; i < NumReducedVals; ++i) { 7846 auto *I = cast<Instruction>(ReducedVals[i]); 7847 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 7848 VectorizedTree = 7849 createOp(Builder, RdxKind, VectorizedTree, I, "", ReductionOps); 7850 } 7851 for (auto &Pair : ExternallyUsedValues) { 7852 // Add each externally used value to the final reduction. 7853 for (auto *I : Pair.second) { 7854 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 7855 VectorizedTree = createOp(Builder, RdxKind, VectorizedTree, 7856 Pair.first, "op.extra", I); 7857 } 7858 } 7859 7860 ReductionRoot->replaceAllUsesWith(VectorizedTree); 7861 7862 // Mark all scalar reduction ops for deletion, they are replaced by the 7863 // vector reductions. 7864 V.eraseInstructions(IgnoreList); 7865 } 7866 return VectorizedTree != nullptr; 7867 } 7868 7869 unsigned numReductionValues() const { return ReducedVals.size(); } 7870 7871 private: 7872 /// Calculate the cost of a reduction. 7873 InstructionCost getReductionCost(TargetTransformInfo *TTI, 7874 Value *FirstReducedVal, 7875 unsigned ReduxWidth) { 7876 Type *ScalarTy = FirstReducedVal->getType(); 7877 FixedVectorType *VectorTy = FixedVectorType::get(ScalarTy, ReduxWidth); 7878 InstructionCost VectorCost, ScalarCost; 7879 switch (RdxKind) { 7880 case RecurKind::Add: 7881 case RecurKind::Mul: 7882 case RecurKind::Or: 7883 case RecurKind::And: 7884 case RecurKind::Xor: 7885 case RecurKind::FAdd: 7886 case RecurKind::FMul: { 7887 unsigned RdxOpcode = RecurrenceDescriptor::getOpcode(RdxKind); 7888 VectorCost = TTI->getArithmeticReductionCost(RdxOpcode, VectorTy, 7889 /*IsPairwiseForm=*/false); 7890 ScalarCost = TTI->getArithmeticInstrCost(RdxOpcode, ScalarTy); 7891 break; 7892 } 7893 case RecurKind::FMax: 7894 case RecurKind::FMin: { 7895 auto *VecCondTy = cast<VectorType>(CmpInst::makeCmpResultType(VectorTy)); 7896 VectorCost = 7897 TTI->getMinMaxReductionCost(VectorTy, VecCondTy, 7898 /*pairwise=*/false, /*unsigned=*/false); 7899 ScalarCost = 7900 TTI->getCmpSelInstrCost(Instruction::FCmp, ScalarTy) + 7901 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 7902 CmpInst::makeCmpResultType(ScalarTy)); 7903 break; 7904 } 7905 case RecurKind::SMax: 7906 case RecurKind::SMin: 7907 case RecurKind::UMax: 7908 case RecurKind::UMin: { 7909 auto *VecCondTy = cast<VectorType>(CmpInst::makeCmpResultType(VectorTy)); 7910 bool IsUnsigned = 7911 RdxKind == RecurKind::UMax || RdxKind == RecurKind::UMin; 7912 VectorCost = 7913 TTI->getMinMaxReductionCost(VectorTy, VecCondTy, 7914 /*IsPairwiseForm=*/false, IsUnsigned); 7915 ScalarCost = 7916 TTI->getCmpSelInstrCost(Instruction::ICmp, ScalarTy) + 7917 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 7918 CmpInst::makeCmpResultType(ScalarTy)); 7919 break; 7920 } 7921 default: 7922 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 7923 } 7924 7925 // Scalar cost is repeated for N-1 elements. 7926 ScalarCost *= (ReduxWidth - 1); 7927 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << VectorCost - ScalarCost 7928 << " for reduction that starts with " << *FirstReducedVal 7929 << " (It is a splitting reduction)\n"); 7930 return VectorCost - ScalarCost; 7931 } 7932 7933 /// Emit a horizontal reduction of the vectorized value. 7934 Value *emitReduction(Value *VectorizedValue, IRBuilder<> &Builder, 7935 unsigned ReduxWidth, const TargetTransformInfo *TTI) { 7936 assert(VectorizedValue && "Need to have a vectorized tree node"); 7937 assert(isPowerOf2_32(ReduxWidth) && 7938 "We only handle power-of-two reductions for now"); 7939 7940 return createSimpleTargetReduction(Builder, TTI, VectorizedValue, RdxKind, 7941 ReductionOps.back()); 7942 } 7943 }; 7944 7945 } // end anonymous namespace 7946 7947 static Optional<unsigned> getAggregateSize(Instruction *InsertInst) { 7948 if (auto *IE = dyn_cast<InsertElementInst>(InsertInst)) 7949 return cast<FixedVectorType>(IE->getType())->getNumElements(); 7950 7951 unsigned AggregateSize = 1; 7952 auto *IV = cast<InsertValueInst>(InsertInst); 7953 Type *CurrentType = IV->getType(); 7954 do { 7955 if (auto *ST = dyn_cast<StructType>(CurrentType)) { 7956 for (auto *Elt : ST->elements()) 7957 if (Elt != ST->getElementType(0)) // check homogeneity 7958 return None; 7959 AggregateSize *= ST->getNumElements(); 7960 CurrentType = ST->getElementType(0); 7961 } else if (auto *AT = dyn_cast<ArrayType>(CurrentType)) { 7962 AggregateSize *= AT->getNumElements(); 7963 CurrentType = AT->getElementType(); 7964 } else if (auto *VT = dyn_cast<FixedVectorType>(CurrentType)) { 7965 AggregateSize *= VT->getNumElements(); 7966 return AggregateSize; 7967 } else if (CurrentType->isSingleValueType()) { 7968 return AggregateSize; 7969 } else { 7970 return None; 7971 } 7972 } while (true); 7973 } 7974 7975 static bool findBuildAggregate_rec(Instruction *LastInsertInst, 7976 TargetTransformInfo *TTI, 7977 SmallVectorImpl<Value *> &BuildVectorOpds, 7978 SmallVectorImpl<Value *> &InsertElts, 7979 unsigned OperandOffset) { 7980 do { 7981 Value *InsertedOperand = LastInsertInst->getOperand(1); 7982 Optional<int> OperandIndex = getInsertIndex(LastInsertInst, OperandOffset); 7983 if (!OperandIndex) 7984 return false; 7985 if (isa<InsertElementInst>(InsertedOperand) || 7986 isa<InsertValueInst>(InsertedOperand)) { 7987 if (!findBuildAggregate_rec(cast<Instruction>(InsertedOperand), TTI, 7988 BuildVectorOpds, InsertElts, *OperandIndex)) 7989 return false; 7990 } else { 7991 BuildVectorOpds[*OperandIndex] = InsertedOperand; 7992 InsertElts[*OperandIndex] = LastInsertInst; 7993 } 7994 LastInsertInst = dyn_cast<Instruction>(LastInsertInst->getOperand(0)); 7995 } while (LastInsertInst != nullptr && 7996 (isa<InsertValueInst>(LastInsertInst) || 7997 isa<InsertElementInst>(LastInsertInst)) && 7998 LastInsertInst->hasOneUse()); 7999 return true; 8000 } 8001 8002 /// Recognize construction of vectors like 8003 /// %ra = insertelement <4 x float> poison, float %s0, i32 0 8004 /// %rb = insertelement <4 x float> %ra, float %s1, i32 1 8005 /// %rc = insertelement <4 x float> %rb, float %s2, i32 2 8006 /// %rd = insertelement <4 x float> %rc, float %s3, i32 3 8007 /// starting from the last insertelement or insertvalue instruction. 8008 /// 8009 /// Also recognize homogeneous aggregates like {<2 x float>, <2 x float>}, 8010 /// {{float, float}, {float, float}}, [2 x {float, float}] and so on. 8011 /// See llvm/test/Transforms/SLPVectorizer/X86/pr42022.ll for examples. 8012 /// 8013 /// Assume LastInsertInst is of InsertElementInst or InsertValueInst type. 8014 /// 8015 /// \return true if it matches. 8016 static bool findBuildAggregate(Instruction *LastInsertInst, 8017 TargetTransformInfo *TTI, 8018 SmallVectorImpl<Value *> &BuildVectorOpds, 8019 SmallVectorImpl<Value *> &InsertElts) { 8020 8021 assert((isa<InsertElementInst>(LastInsertInst) || 8022 isa<InsertValueInst>(LastInsertInst)) && 8023 "Expected insertelement or insertvalue instruction!"); 8024 8025 assert((BuildVectorOpds.empty() && InsertElts.empty()) && 8026 "Expected empty result vectors!"); 8027 8028 Optional<unsigned> AggregateSize = getAggregateSize(LastInsertInst); 8029 if (!AggregateSize) 8030 return false; 8031 BuildVectorOpds.resize(*AggregateSize); 8032 InsertElts.resize(*AggregateSize); 8033 8034 if (findBuildAggregate_rec(LastInsertInst, TTI, BuildVectorOpds, InsertElts, 8035 0)) { 8036 llvm::erase_value(BuildVectorOpds, nullptr); 8037 llvm::erase_value(InsertElts, nullptr); 8038 if (BuildVectorOpds.size() >= 2) 8039 return true; 8040 } 8041 8042 return false; 8043 } 8044 8045 /// Try and get a reduction value from a phi node. 8046 /// 8047 /// Given a phi node \p P in a block \p ParentBB, consider possible reductions 8048 /// if they come from either \p ParentBB or a containing loop latch. 8049 /// 8050 /// \returns A candidate reduction value if possible, or \code nullptr \endcode 8051 /// if not possible. 8052 static Value *getReductionValue(const DominatorTree *DT, PHINode *P, 8053 BasicBlock *ParentBB, LoopInfo *LI) { 8054 // There are situations where the reduction value is not dominated by the 8055 // reduction phi. Vectorizing such cases has been reported to cause 8056 // miscompiles. See PR25787. 8057 auto DominatedReduxValue = [&](Value *R) { 8058 return isa<Instruction>(R) && 8059 DT->dominates(P->getParent(), cast<Instruction>(R)->getParent()); 8060 }; 8061 8062 Value *Rdx = nullptr; 8063 8064 // Return the incoming value if it comes from the same BB as the phi node. 8065 if (P->getIncomingBlock(0) == ParentBB) { 8066 Rdx = P->getIncomingValue(0); 8067 } else if (P->getIncomingBlock(1) == ParentBB) { 8068 Rdx = P->getIncomingValue(1); 8069 } 8070 8071 if (Rdx && DominatedReduxValue(Rdx)) 8072 return Rdx; 8073 8074 // Otherwise, check whether we have a loop latch to look at. 8075 Loop *BBL = LI->getLoopFor(ParentBB); 8076 if (!BBL) 8077 return nullptr; 8078 BasicBlock *BBLatch = BBL->getLoopLatch(); 8079 if (!BBLatch) 8080 return nullptr; 8081 8082 // There is a loop latch, return the incoming value if it comes from 8083 // that. This reduction pattern occasionally turns up. 8084 if (P->getIncomingBlock(0) == BBLatch) { 8085 Rdx = P->getIncomingValue(0); 8086 } else if (P->getIncomingBlock(1) == BBLatch) { 8087 Rdx = P->getIncomingValue(1); 8088 } 8089 8090 if (Rdx && DominatedReduxValue(Rdx)) 8091 return Rdx; 8092 8093 return nullptr; 8094 } 8095 8096 static bool matchRdxBop(Instruction *I, Value *&V0, Value *&V1) { 8097 if (match(I, m_BinOp(m_Value(V0), m_Value(V1)))) 8098 return true; 8099 if (match(I, m_Intrinsic<Intrinsic::maxnum>(m_Value(V0), m_Value(V1)))) 8100 return true; 8101 if (match(I, m_Intrinsic<Intrinsic::minnum>(m_Value(V0), m_Value(V1)))) 8102 return true; 8103 if (match(I, m_Intrinsic<Intrinsic::smax>(m_Value(V0), m_Value(V1)))) 8104 return true; 8105 if (match(I, m_Intrinsic<Intrinsic::smin>(m_Value(V0), m_Value(V1)))) 8106 return true; 8107 if (match(I, m_Intrinsic<Intrinsic::umax>(m_Value(V0), m_Value(V1)))) 8108 return true; 8109 if (match(I, m_Intrinsic<Intrinsic::umin>(m_Value(V0), m_Value(V1)))) 8110 return true; 8111 return false; 8112 } 8113 8114 /// Attempt to reduce a horizontal reduction. 8115 /// If it is legal to match a horizontal reduction feeding the phi node \a P 8116 /// with reduction operators \a Root (or one of its operands) in a basic block 8117 /// \a BB, then check if it can be done. If horizontal reduction is not found 8118 /// and root instruction is a binary operation, vectorization of the operands is 8119 /// attempted. 8120 /// \returns true if a horizontal reduction was matched and reduced or operands 8121 /// of one of the binary instruction were vectorized. 8122 /// \returns false if a horizontal reduction was not matched (or not possible) 8123 /// or no vectorization of any binary operation feeding \a Root instruction was 8124 /// performed. 8125 static bool tryToVectorizeHorReductionOrInstOperands( 8126 PHINode *P, Instruction *Root, BasicBlock *BB, BoUpSLP &R, 8127 TargetTransformInfo *TTI, 8128 const function_ref<bool(Instruction *, BoUpSLP &)> Vectorize) { 8129 if (!ShouldVectorizeHor) 8130 return false; 8131 8132 if (!Root) 8133 return false; 8134 8135 if (Root->getParent() != BB || isa<PHINode>(Root)) 8136 return false; 8137 // Start analysis starting from Root instruction. If horizontal reduction is 8138 // found, try to vectorize it. If it is not a horizontal reduction or 8139 // vectorization is not possible or not effective, and currently analyzed 8140 // instruction is a binary operation, try to vectorize the operands, using 8141 // pre-order DFS traversal order. If the operands were not vectorized, repeat 8142 // the same procedure considering each operand as a possible root of the 8143 // horizontal reduction. 8144 // Interrupt the process if the Root instruction itself was vectorized or all 8145 // sub-trees not higher that RecursionMaxDepth were analyzed/vectorized. 8146 // Skip the analysis of CmpInsts.Compiler implements postanalysis of the 8147 // CmpInsts so we can skip extra attempts in 8148 // tryToVectorizeHorReductionOrInstOperands and save compile time. 8149 SmallVector<std::pair<Instruction *, unsigned>, 8> Stack(1, {Root, 0}); 8150 SmallPtrSet<Value *, 8> VisitedInstrs; 8151 bool Res = false; 8152 while (!Stack.empty()) { 8153 Instruction *Inst; 8154 unsigned Level; 8155 std::tie(Inst, Level) = Stack.pop_back_val(); 8156 Value *B0, *B1; 8157 bool IsBinop = matchRdxBop(Inst, B0, B1); 8158 bool IsSelect = match(Inst, m_Select(m_Value(), m_Value(), m_Value())); 8159 if (IsBinop || IsSelect) { 8160 HorizontalReduction HorRdx; 8161 if (HorRdx.matchAssociativeReduction(P, Inst)) { 8162 if (HorRdx.tryToReduce(R, TTI)) { 8163 Res = true; 8164 // Set P to nullptr to avoid re-analysis of phi node in 8165 // matchAssociativeReduction function unless this is the root node. 8166 P = nullptr; 8167 continue; 8168 } 8169 } 8170 if (P && IsBinop) { 8171 Inst = dyn_cast<Instruction>(B0); 8172 if (Inst == P) 8173 Inst = dyn_cast<Instruction>(B1); 8174 if (!Inst) { 8175 // Set P to nullptr to avoid re-analysis of phi node in 8176 // matchAssociativeReduction function unless this is the root node. 8177 P = nullptr; 8178 continue; 8179 } 8180 } 8181 } 8182 // Set P to nullptr to avoid re-analysis of phi node in 8183 // matchAssociativeReduction function unless this is the root node. 8184 P = nullptr; 8185 // Do not try to vectorize CmpInst operands, this is done separately. 8186 if (!isa<CmpInst>(Inst) && Vectorize(Inst, R)) { 8187 Res = true; 8188 continue; 8189 } 8190 8191 // Try to vectorize operands. 8192 // Continue analysis for the instruction from the same basic block only to 8193 // save compile time. 8194 if (++Level < RecursionMaxDepth) 8195 for (auto *Op : Inst->operand_values()) 8196 if (VisitedInstrs.insert(Op).second) 8197 if (auto *I = dyn_cast<Instruction>(Op)) 8198 // Do not try to vectorize CmpInst operands, this is done 8199 // separately. 8200 if (!isa<PHINode>(I) && !isa<CmpInst>(I) && !R.isDeleted(I) && 8201 I->getParent() == BB) 8202 Stack.emplace_back(I, Level); 8203 } 8204 return Res; 8205 } 8206 8207 bool SLPVectorizerPass::vectorizeRootInstruction(PHINode *P, Value *V, 8208 BasicBlock *BB, BoUpSLP &R, 8209 TargetTransformInfo *TTI) { 8210 auto *I = dyn_cast_or_null<Instruction>(V); 8211 if (!I) 8212 return false; 8213 8214 if (!isa<BinaryOperator>(I)) 8215 P = nullptr; 8216 // Try to match and vectorize a horizontal reduction. 8217 auto &&ExtraVectorization = [this](Instruction *I, BoUpSLP &R) -> bool { 8218 return tryToVectorize(I, R); 8219 }; 8220 return tryToVectorizeHorReductionOrInstOperands(P, I, BB, R, TTI, 8221 ExtraVectorization); 8222 } 8223 8224 bool SLPVectorizerPass::vectorizeInsertValueInst(InsertValueInst *IVI, 8225 BasicBlock *BB, BoUpSLP &R) { 8226 const DataLayout &DL = BB->getModule()->getDataLayout(); 8227 if (!R.canMapToVector(IVI->getType(), DL)) 8228 return false; 8229 8230 SmallVector<Value *, 16> BuildVectorOpds; 8231 SmallVector<Value *, 16> BuildVectorInsts; 8232 if (!findBuildAggregate(IVI, TTI, BuildVectorOpds, BuildVectorInsts)) 8233 return false; 8234 8235 LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IVI << "\n"); 8236 // Aggregate value is unlikely to be processed in vector register, we need to 8237 // extract scalars into scalar registers, so NeedExtraction is set true. 8238 return tryToVectorizeList(BuildVectorOpds, R, /*AllowReorder=*/false); 8239 } 8240 8241 bool SLPVectorizerPass::vectorizeInsertElementInst(InsertElementInst *IEI, 8242 BasicBlock *BB, BoUpSLP &R) { 8243 SmallVector<Value *, 16> BuildVectorInsts; 8244 SmallVector<Value *, 16> BuildVectorOpds; 8245 SmallVector<int> Mask; 8246 if (!findBuildAggregate(IEI, TTI, BuildVectorOpds, BuildVectorInsts) || 8247 (llvm::all_of(BuildVectorOpds, 8248 [](Value *V) { return isa<ExtractElementInst>(V); }) && 8249 isShuffle(BuildVectorOpds, Mask))) 8250 return false; 8251 8252 LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IEI << "\n"); 8253 return tryToVectorizeList(BuildVectorInsts, R, /*AllowReorder=*/true); 8254 } 8255 8256 bool SLPVectorizerPass::vectorizeSimpleInstructions( 8257 SmallVectorImpl<Instruction *> &Instructions, BasicBlock *BB, BoUpSLP &R, 8258 bool AtTerminator) { 8259 bool OpsChanged = false; 8260 SmallVector<Instruction *, 4> PostponedCmps; 8261 for (auto *I : reverse(Instructions)) { 8262 if (R.isDeleted(I)) 8263 continue; 8264 if (auto *LastInsertValue = dyn_cast<InsertValueInst>(I)) 8265 OpsChanged |= vectorizeInsertValueInst(LastInsertValue, BB, R); 8266 else if (auto *LastInsertElem = dyn_cast<InsertElementInst>(I)) 8267 OpsChanged |= vectorizeInsertElementInst(LastInsertElem, BB, R); 8268 else if (isa<CmpInst>(I)) 8269 PostponedCmps.push_back(I); 8270 } 8271 if (AtTerminator) { 8272 // Try to find reductions first. 8273 for (Instruction *I : PostponedCmps) { 8274 if (R.isDeleted(I)) 8275 continue; 8276 for (Value *Op : I->operands()) 8277 OpsChanged |= vectorizeRootInstruction(nullptr, Op, BB, R, TTI); 8278 } 8279 // Try to vectorize operands as vector bundles. 8280 for (Instruction *I : PostponedCmps) { 8281 if (R.isDeleted(I)) 8282 continue; 8283 OpsChanged |= tryToVectorize(I, R); 8284 } 8285 Instructions.clear(); 8286 } else { 8287 // Insert in reverse order since the PostponedCmps vector was filled in 8288 // reverse order. 8289 Instructions.assign(PostponedCmps.rbegin(), PostponedCmps.rend()); 8290 } 8291 return OpsChanged; 8292 } 8293 8294 bool SLPVectorizerPass::vectorizeChainsInBlock(BasicBlock *BB, BoUpSLP &R) { 8295 bool Changed = false; 8296 SmallVector<Value *, 4> Incoming; 8297 SmallPtrSet<Value *, 16> VisitedInstrs; 8298 // Maps phi nodes to the non-phi nodes found in the use tree for each phi 8299 // node. Allows better to identify the chains that can be vectorized in the 8300 // better way. 8301 DenseMap<Value *, SmallVector<Value *, 4>> PHIToOpcodes; 8302 8303 bool HaveVectorizedPhiNodes = true; 8304 while (HaveVectorizedPhiNodes) { 8305 HaveVectorizedPhiNodes = false; 8306 8307 // Collect the incoming values from the PHIs. 8308 Incoming.clear(); 8309 for (Instruction &I : *BB) { 8310 PHINode *P = dyn_cast<PHINode>(&I); 8311 if (!P) 8312 break; 8313 8314 // No need to analyze deleted, vectorized and non-vectorizable 8315 // instructions. 8316 if (!VisitedInstrs.count(P) && !R.isDeleted(P) && 8317 !P->getType()->isVectorTy()) 8318 Incoming.push_back(P); 8319 } 8320 8321 // Find the corresponding non-phi nodes for better matching when trying to 8322 // build the tree. 8323 for (Value *V : Incoming) { 8324 SmallVectorImpl<Value *> &Opcodes = 8325 PHIToOpcodes.try_emplace(V).first->getSecond(); 8326 if (!Opcodes.empty()) 8327 continue; 8328 SmallVector<Value *, 4> Nodes(1, V); 8329 SmallPtrSet<Value *, 4> Visited; 8330 while (!Nodes.empty()) { 8331 auto *PHI = cast<PHINode>(Nodes.pop_back_val()); 8332 if (!Visited.insert(PHI).second) 8333 continue; 8334 for (Value *V : PHI->incoming_values()) { 8335 if (auto *PHI1 = dyn_cast<PHINode>((V))) { 8336 Nodes.push_back(PHI1); 8337 continue; 8338 } 8339 Opcodes.emplace_back(V); 8340 } 8341 } 8342 } 8343 8344 // Sort by type, parent, operands. 8345 stable_sort(Incoming, [&PHIToOpcodes](Value *V1, Value *V2) { 8346 if (V1->getType() < V2->getType()) 8347 return true; 8348 if (V1->getType() > V2->getType()) 8349 return false; 8350 ArrayRef<Value *> Opcodes1 = PHIToOpcodes[V1]; 8351 ArrayRef<Value *> Opcodes2 = PHIToOpcodes[V2]; 8352 if (Opcodes1.size() < Opcodes2.size()) 8353 return true; 8354 if (Opcodes1.size() > Opcodes2.size()) 8355 return false; 8356 for (int I = 0, E = Opcodes1.size(); I < E; ++I) { 8357 // Undefs are compatible with any other value. 8358 if (isa<UndefValue>(Opcodes1[I]) || isa<UndefValue>(Opcodes2[I])) 8359 continue; 8360 if (auto *I1 = dyn_cast<Instruction>(Opcodes1[I])) 8361 if (auto *I2 = dyn_cast<Instruction>(Opcodes2[I])) { 8362 if (I1->getParent() < I2->getParent()) 8363 return true; 8364 if (I1->getParent() > I2->getParent()) 8365 return false; 8366 InstructionsState S = getSameOpcode({I1, I2}); 8367 if (S.getOpcode()) 8368 continue; 8369 return I1->getOpcode() < I2->getOpcode(); 8370 } 8371 if (isa<Constant>(Opcodes1[I]) && isa<Constant>(Opcodes2[I])) 8372 continue; 8373 if (Opcodes1[I]->getValueID() < Opcodes2[I]->getValueID()) 8374 return true; 8375 if (Opcodes1[I]->getValueID() > Opcodes2[I]->getValueID()) 8376 return false; 8377 } 8378 return false; 8379 }); 8380 8381 auto &&AreCompatiblePHIs = [&PHIToOpcodes](Value *V1, Value *V2) { 8382 if (V1 == V2) 8383 return true; 8384 if (V1->getType() != V2->getType()) 8385 return false; 8386 ArrayRef<Value *> Opcodes1 = PHIToOpcodes[V1]; 8387 ArrayRef<Value *> Opcodes2 = PHIToOpcodes[V2]; 8388 if (Opcodes1.size() != Opcodes2.size()) 8389 return false; 8390 for (int I = 0, E = Opcodes1.size(); I < E; ++I) { 8391 // Undefs are compatible with any other value. 8392 if (isa<UndefValue>(Opcodes1[I]) || isa<UndefValue>(Opcodes2[I])) 8393 continue; 8394 if (auto *I1 = dyn_cast<Instruction>(Opcodes1[I])) 8395 if (auto *I2 = dyn_cast<Instruction>(Opcodes2[I])) { 8396 if (I1->getParent() != I2->getParent()) 8397 return false; 8398 InstructionsState S = getSameOpcode({I1, I2}); 8399 if (S.getOpcode()) 8400 continue; 8401 return false; 8402 } 8403 if (isa<Constant>(Opcodes1[I]) && isa<Constant>(Opcodes2[I])) 8404 continue; 8405 if (Opcodes1[I]->getValueID() != Opcodes2[I]->getValueID()) 8406 return false; 8407 } 8408 return true; 8409 }; 8410 8411 // Try to vectorize elements base on their type. 8412 SmallVector<Value *, 4> Candidates; 8413 for (SmallVector<Value *, 4>::iterator IncIt = Incoming.begin(), 8414 E = Incoming.end(); 8415 IncIt != E;) { 8416 8417 // Look for the next elements with the same type, parent and operand 8418 // kinds. 8419 SmallVector<Value *, 4>::iterator SameTypeIt = IncIt; 8420 while (SameTypeIt != E && AreCompatiblePHIs(*SameTypeIt, *IncIt)) { 8421 VisitedInstrs.insert(*SameTypeIt); 8422 ++SameTypeIt; 8423 } 8424 8425 // Try to vectorize them. 8426 unsigned NumElts = (SameTypeIt - IncIt); 8427 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize starting at PHIs (" 8428 << NumElts << ")\n"); 8429 // The order in which the phi nodes appear in the program does not matter. 8430 // So allow tryToVectorizeList to reorder them if it is beneficial. This 8431 // is done when there are exactly two elements since tryToVectorizeList 8432 // asserts that there are only two values when AllowReorder is true. 8433 if (NumElts > 1 && tryToVectorizeList(makeArrayRef(IncIt, NumElts), R, 8434 /*AllowReorder=*/true)) { 8435 // Success start over because instructions might have been changed. 8436 HaveVectorizedPhiNodes = true; 8437 Changed = true; 8438 } else if (NumElts < 4 && 8439 (Candidates.empty() || 8440 Candidates.front()->getType() == (*IncIt)->getType())) { 8441 Candidates.append(IncIt, std::next(IncIt, NumElts)); 8442 } 8443 // Final attempt to vectorize phis with the same types. 8444 if (SameTypeIt == E || (*SameTypeIt)->getType() != (*IncIt)->getType()) { 8445 if (Candidates.size() > 1 && 8446 tryToVectorizeList(Candidates, R, /*AllowReorder=*/true)) { 8447 // Success start over because instructions might have been changed. 8448 HaveVectorizedPhiNodes = true; 8449 Changed = true; 8450 } 8451 Candidates.clear(); 8452 } 8453 8454 // Start over at the next instruction of a different type (or the end). 8455 IncIt = SameTypeIt; 8456 } 8457 } 8458 8459 VisitedInstrs.clear(); 8460 8461 SmallVector<Instruction *, 8> PostProcessInstructions; 8462 SmallDenseSet<Instruction *, 4> KeyNodes; 8463 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 8464 // Skip instructions with scalable type. The num of elements is unknown at 8465 // compile-time for scalable type. 8466 if (isa<ScalableVectorType>(it->getType())) 8467 continue; 8468 8469 // Skip instructions marked for the deletion. 8470 if (R.isDeleted(&*it)) 8471 continue; 8472 // We may go through BB multiple times so skip the one we have checked. 8473 if (!VisitedInstrs.insert(&*it).second) { 8474 if (it->use_empty() && KeyNodes.contains(&*it) && 8475 vectorizeSimpleInstructions(PostProcessInstructions, BB, R, 8476 it->isTerminator())) { 8477 // We would like to start over since some instructions are deleted 8478 // and the iterator may become invalid value. 8479 Changed = true; 8480 it = BB->begin(); 8481 e = BB->end(); 8482 } 8483 continue; 8484 } 8485 8486 if (isa<DbgInfoIntrinsic>(it)) 8487 continue; 8488 8489 // Try to vectorize reductions that use PHINodes. 8490 if (PHINode *P = dyn_cast<PHINode>(it)) { 8491 // Check that the PHI is a reduction PHI. 8492 if (P->getNumIncomingValues() == 2) { 8493 // Try to match and vectorize a horizontal reduction. 8494 if (vectorizeRootInstruction(P, getReductionValue(DT, P, BB, LI), BB, R, 8495 TTI)) { 8496 Changed = true; 8497 it = BB->begin(); 8498 e = BB->end(); 8499 continue; 8500 } 8501 } 8502 // Try to vectorize the incoming values of the PHI, to catch reductions 8503 // that feed into PHIs. 8504 for (unsigned I = 0, E = P->getNumIncomingValues(); I != E; I++) { 8505 // Skip if the incoming block is the current BB for now. Also, bypass 8506 // unreachable IR for efficiency and to avoid crashing. 8507 // TODO: Collect the skipped incoming values and try to vectorize them 8508 // after processing BB. 8509 if (BB == P->getIncomingBlock(I) || 8510 !DT->isReachableFromEntry(P->getIncomingBlock(I))) 8511 continue; 8512 8513 Changed |= vectorizeRootInstruction(nullptr, P->getIncomingValue(I), 8514 P->getIncomingBlock(I), R, TTI); 8515 } 8516 continue; 8517 } 8518 8519 // Ran into an instruction without users, like terminator, or function call 8520 // with ignored return value, store. Ignore unused instructions (basing on 8521 // instruction type, except for CallInst and InvokeInst). 8522 if (it->use_empty() && (it->getType()->isVoidTy() || isa<CallInst>(it) || 8523 isa<InvokeInst>(it))) { 8524 KeyNodes.insert(&*it); 8525 bool OpsChanged = false; 8526 if (ShouldStartVectorizeHorAtStore || !isa<StoreInst>(it)) { 8527 for (auto *V : it->operand_values()) { 8528 // Try to match and vectorize a horizontal reduction. 8529 OpsChanged |= vectorizeRootInstruction(nullptr, V, BB, R, TTI); 8530 } 8531 } 8532 // Start vectorization of post-process list of instructions from the 8533 // top-tree instructions to try to vectorize as many instructions as 8534 // possible. 8535 OpsChanged |= vectorizeSimpleInstructions(PostProcessInstructions, BB, R, 8536 it->isTerminator()); 8537 if (OpsChanged) { 8538 // We would like to start over since some instructions are deleted 8539 // and the iterator may become invalid value. 8540 Changed = true; 8541 it = BB->begin(); 8542 e = BB->end(); 8543 continue; 8544 } 8545 } 8546 8547 if (isa<InsertElementInst>(it) || isa<CmpInst>(it) || 8548 isa<InsertValueInst>(it)) 8549 PostProcessInstructions.push_back(&*it); 8550 } 8551 8552 return Changed; 8553 } 8554 8555 bool SLPVectorizerPass::vectorizeGEPIndices(BasicBlock *BB, BoUpSLP &R) { 8556 auto Changed = false; 8557 for (auto &Entry : GEPs) { 8558 // If the getelementptr list has fewer than two elements, there's nothing 8559 // to do. 8560 if (Entry.second.size() < 2) 8561 continue; 8562 8563 LLVM_DEBUG(dbgs() << "SLP: Analyzing a getelementptr list of length " 8564 << Entry.second.size() << ".\n"); 8565 8566 // Process the GEP list in chunks suitable for the target's supported 8567 // vector size. If a vector register can't hold 1 element, we are done. We 8568 // are trying to vectorize the index computations, so the maximum number of 8569 // elements is based on the size of the index expression, rather than the 8570 // size of the GEP itself (the target's pointer size). 8571 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 8572 unsigned EltSize = R.getVectorElementSize(*Entry.second[0]->idx_begin()); 8573 if (MaxVecRegSize < EltSize) 8574 continue; 8575 8576 unsigned MaxElts = MaxVecRegSize / EltSize; 8577 for (unsigned BI = 0, BE = Entry.second.size(); BI < BE; BI += MaxElts) { 8578 auto Len = std::min<unsigned>(BE - BI, MaxElts); 8579 ArrayRef<GetElementPtrInst *> GEPList(&Entry.second[BI], Len); 8580 8581 // Initialize a set a candidate getelementptrs. Note that we use a 8582 // SetVector here to preserve program order. If the index computations 8583 // are vectorizable and begin with loads, we want to minimize the chance 8584 // of having to reorder them later. 8585 SetVector<Value *> Candidates(GEPList.begin(), GEPList.end()); 8586 8587 // Some of the candidates may have already been vectorized after we 8588 // initially collected them. If so, they are marked as deleted, so remove 8589 // them from the set of candidates. 8590 Candidates.remove_if( 8591 [&R](Value *I) { return R.isDeleted(cast<Instruction>(I)); }); 8592 8593 // Remove from the set of candidates all pairs of getelementptrs with 8594 // constant differences. Such getelementptrs are likely not good 8595 // candidates for vectorization in a bottom-up phase since one can be 8596 // computed from the other. We also ensure all candidate getelementptr 8597 // indices are unique. 8598 for (int I = 0, E = GEPList.size(); I < E && Candidates.size() > 1; ++I) { 8599 auto *GEPI = GEPList[I]; 8600 if (!Candidates.count(GEPI)) 8601 continue; 8602 auto *SCEVI = SE->getSCEV(GEPList[I]); 8603 for (int J = I + 1; J < E && Candidates.size() > 1; ++J) { 8604 auto *GEPJ = GEPList[J]; 8605 auto *SCEVJ = SE->getSCEV(GEPList[J]); 8606 if (isa<SCEVConstant>(SE->getMinusSCEV(SCEVI, SCEVJ))) { 8607 Candidates.remove(GEPI); 8608 Candidates.remove(GEPJ); 8609 } else if (GEPI->idx_begin()->get() == GEPJ->idx_begin()->get()) { 8610 Candidates.remove(GEPJ); 8611 } 8612 } 8613 } 8614 8615 // We break out of the above computation as soon as we know there are 8616 // fewer than two candidates remaining. 8617 if (Candidates.size() < 2) 8618 continue; 8619 8620 // Add the single, non-constant index of each candidate to the bundle. We 8621 // ensured the indices met these constraints when we originally collected 8622 // the getelementptrs. 8623 SmallVector<Value *, 16> Bundle(Candidates.size()); 8624 auto BundleIndex = 0u; 8625 for (auto *V : Candidates) { 8626 auto *GEP = cast<GetElementPtrInst>(V); 8627 auto *GEPIdx = GEP->idx_begin()->get(); 8628 assert(GEP->getNumIndices() == 1 || !isa<Constant>(GEPIdx)); 8629 Bundle[BundleIndex++] = GEPIdx; 8630 } 8631 8632 // Try and vectorize the indices. We are currently only interested in 8633 // gather-like cases of the form: 8634 // 8635 // ... = g[a[0] - b[0]] + g[a[1] - b[1]] + ... 8636 // 8637 // where the loads of "a", the loads of "b", and the subtractions can be 8638 // performed in parallel. It's likely that detecting this pattern in a 8639 // bottom-up phase will be simpler and less costly than building a 8640 // full-blown top-down phase beginning at the consecutive loads. 8641 Changed |= tryToVectorizeList(Bundle, R); 8642 } 8643 } 8644 return Changed; 8645 } 8646 8647 bool SLPVectorizerPass::vectorizeStoreChains(BoUpSLP &R) { 8648 bool Changed = false; 8649 // Attempt to sort and vectorize each of the store-groups. 8650 for (StoreListMap::iterator it = Stores.begin(), e = Stores.end(); it != e; 8651 ++it) { 8652 if (it->second.size() < 2) 8653 continue; 8654 8655 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " 8656 << it->second.size() << ".\n"); 8657 8658 Changed |= vectorizeStores(it->second, R); 8659 } 8660 return Changed; 8661 } 8662 8663 char SLPVectorizer::ID = 0; 8664 8665 static const char lv_name[] = "SLP Vectorizer"; 8666 8667 INITIALIZE_PASS_BEGIN(SLPVectorizer, SV_NAME, lv_name, false, false) 8668 INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass) 8669 INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass) 8670 INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker) 8671 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass) 8672 INITIALIZE_PASS_DEPENDENCY(LoopSimplify) 8673 INITIALIZE_PASS_DEPENDENCY(DemandedBitsWrapperPass) 8674 INITIALIZE_PASS_DEPENDENCY(OptimizationRemarkEmitterWrapperPass) 8675 INITIALIZE_PASS_DEPENDENCY(InjectTLIMappingsLegacy) 8676 INITIALIZE_PASS_END(SLPVectorizer, SV_NAME, lv_name, false, false) 8677 8678 Pass *llvm::createSLPVectorizerPass() { return new SLPVectorizer(); } 8679