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/ArrayRef.h" 21 #include "llvm/ADT/DenseMap.h" 22 #include "llvm/ADT/DenseSet.h" 23 #include "llvm/ADT/MapVector.h" 24 #include "llvm/ADT/None.h" 25 #include "llvm/ADT/Optional.h" 26 #include "llvm/ADT/PostOrderIterator.h" 27 #include "llvm/ADT/STLExtras.h" 28 #include "llvm/ADT/SetVector.h" 29 #include "llvm/ADT/SmallPtrSet.h" 30 #include "llvm/ADT/SmallSet.h" 31 #include "llvm/ADT/SmallVector.h" 32 #include "llvm/ADT/Statistic.h" 33 #include "llvm/ADT/iterator.h" 34 #include "llvm/ADT/iterator_range.h" 35 #include "llvm/Analysis/AliasAnalysis.h" 36 #include "llvm/Analysis/CodeMetrics.h" 37 #include "llvm/Analysis/DemandedBits.h" 38 #include "llvm/Analysis/GlobalsModRef.h" 39 #include "llvm/Analysis/LoopAccessAnalysis.h" 40 #include "llvm/Analysis/LoopInfo.h" 41 #include "llvm/Analysis/MemoryLocation.h" 42 #include "llvm/Analysis/OptimizationRemarkEmitter.h" 43 #include "llvm/Analysis/ScalarEvolution.h" 44 #include "llvm/Analysis/ScalarEvolutionExpressions.h" 45 #include "llvm/Analysis/TargetLibraryInfo.h" 46 #include "llvm/Analysis/TargetTransformInfo.h" 47 #include "llvm/Analysis/ValueTracking.h" 48 #include "llvm/Analysis/VectorUtils.h" 49 #include "llvm/IR/Attributes.h" 50 #include "llvm/IR/BasicBlock.h" 51 #include "llvm/IR/Constant.h" 52 #include "llvm/IR/Constants.h" 53 #include "llvm/IR/DataLayout.h" 54 #include "llvm/IR/DebugLoc.h" 55 #include "llvm/IR/DerivedTypes.h" 56 #include "llvm/IR/Dominators.h" 57 #include "llvm/IR/Function.h" 58 #include "llvm/IR/IRBuilder.h" 59 #include "llvm/IR/InstrTypes.h" 60 #include "llvm/IR/Instruction.h" 61 #include "llvm/IR/Instructions.h" 62 #include "llvm/IR/IntrinsicInst.h" 63 #include "llvm/IR/Intrinsics.h" 64 #include "llvm/IR/Module.h" 65 #include "llvm/IR/NoFolder.h" 66 #include "llvm/IR/Operator.h" 67 #include "llvm/IR/PassManager.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/Pass.h" 76 #include "llvm/Support/Casting.h" 77 #include "llvm/Support/CommandLine.h" 78 #include "llvm/Support/Compiler.h" 79 #include "llvm/Support/DOTGraphTraits.h" 80 #include "llvm/Support/Debug.h" 81 #include "llvm/Support/ErrorHandling.h" 82 #include "llvm/Support/GraphWriter.h" 83 #include "llvm/Support/KnownBits.h" 84 #include "llvm/Support/MathExtras.h" 85 #include "llvm/Support/raw_ostream.h" 86 #include "llvm/Transforms/Utils/LoopUtils.h" 87 #include "llvm/Transforms/Vectorize.h" 88 #include <algorithm> 89 #include <cassert> 90 #include <cstdint> 91 #include <iterator> 92 #include <memory> 93 #include <set> 94 #include <string> 95 #include <tuple> 96 #include <utility> 97 #include <vector> 98 99 using namespace llvm; 100 using namespace llvm::PatternMatch; 101 using namespace slpvectorizer; 102 103 #define SV_NAME "slp-vectorizer" 104 #define DEBUG_TYPE "SLP" 105 106 STATISTIC(NumVectorInstructions, "Number of vector instructions generated"); 107 108 cl::opt<bool> 109 llvm::RunSLPVectorization("vectorize-slp", cl::init(false), cl::Hidden, 110 cl::desc("Run the SLP vectorization passes")); 111 112 static cl::opt<int> 113 SLPCostThreshold("slp-threshold", cl::init(0), cl::Hidden, 114 cl::desc("Only vectorize if you gain more than this " 115 "number ")); 116 117 static cl::opt<bool> 118 ShouldVectorizeHor("slp-vectorize-hor", cl::init(true), cl::Hidden, 119 cl::desc("Attempt to vectorize horizontal reductions")); 120 121 static cl::opt<bool> ShouldStartVectorizeHorAtStore( 122 "slp-vectorize-hor-store", cl::init(false), cl::Hidden, 123 cl::desc( 124 "Attempt to vectorize horizontal reductions feeding into a store")); 125 126 static cl::opt<int> 127 MaxVectorRegSizeOption("slp-max-reg-size", cl::init(128), cl::Hidden, 128 cl::desc("Attempt to vectorize for this register size in bits")); 129 130 /// Limits the size of scheduling regions in a block. 131 /// It avoid long compile times for _very_ large blocks where vector 132 /// instructions are spread over a wide range. 133 /// This limit is way higher than needed by real-world functions. 134 static cl::opt<int> 135 ScheduleRegionSizeBudget("slp-schedule-budget", cl::init(100000), cl::Hidden, 136 cl::desc("Limit the size of the SLP scheduling region per block")); 137 138 static cl::opt<int> MinVectorRegSizeOption( 139 "slp-min-reg-size", cl::init(128), cl::Hidden, 140 cl::desc("Attempt to vectorize for this register size in bits")); 141 142 static cl::opt<unsigned> RecursionMaxDepth( 143 "slp-recursion-max-depth", cl::init(12), cl::Hidden, 144 cl::desc("Limit the recursion depth when building a vectorizable tree")); 145 146 static cl::opt<unsigned> MinTreeSize( 147 "slp-min-tree-size", cl::init(3), cl::Hidden, 148 cl::desc("Only vectorize small trees if they are fully vectorizable")); 149 150 // The maximum depth that the look-ahead score heuristic will explore. 151 // The higher this value, the higher the compilation time overhead. 152 static cl::opt<int> LookAheadMaxDepth( 153 "slp-max-look-ahead-depth", cl::init(2), cl::Hidden, 154 cl::desc("The maximum look-ahead depth for operand reordering scores")); 155 156 // The Look-ahead heuristic goes through the users of the bundle to calculate 157 // the users cost in getExternalUsesCost(). To avoid compilation time increase 158 // we limit the number of users visited to this value. 159 static cl::opt<unsigned> LookAheadUsersBudget( 160 "slp-look-ahead-users-budget", cl::init(2), cl::Hidden, 161 cl::desc("The maximum number of users to visit while visiting the " 162 "predecessors. This prevents compilation time increase.")); 163 164 static cl::opt<bool> 165 ViewSLPTree("view-slp-tree", cl::Hidden, 166 cl::desc("Display the SLP trees with Graphviz")); 167 168 // Limit the number of alias checks. The limit is chosen so that 169 // it has no negative effect on the llvm benchmarks. 170 static const unsigned AliasedCheckLimit = 10; 171 172 // Another limit for the alias checks: The maximum distance between load/store 173 // instructions where alias checks are done. 174 // This limit is useful for very large basic blocks. 175 static const unsigned MaxMemDepDistance = 160; 176 177 /// If the ScheduleRegionSizeBudget is exhausted, we allow small scheduling 178 /// regions to be handled. 179 static const int MinScheduleRegionSize = 16; 180 181 /// Predicate for the element types that the SLP vectorizer supports. 182 /// 183 /// The most important thing to filter here are types which are invalid in LLVM 184 /// vectors. We also filter target specific types which have absolutely no 185 /// meaningful vectorization path such as x86_fp80 and ppc_f128. This just 186 /// avoids spending time checking the cost model and realizing that they will 187 /// be inevitably scalarized. 188 static bool isValidElementType(Type *Ty) { 189 return VectorType::isValidElementType(Ty) && !Ty->isX86_FP80Ty() && 190 !Ty->isPPC_FP128Ty(); 191 } 192 193 /// \returns true if all of the instructions in \p VL are in the same block or 194 /// false otherwise. 195 static bool allSameBlock(ArrayRef<Value *> VL) { 196 Instruction *I0 = dyn_cast<Instruction>(VL[0]); 197 if (!I0) 198 return false; 199 BasicBlock *BB = I0->getParent(); 200 for (int i = 1, e = VL.size(); i < e; i++) { 201 Instruction *I = dyn_cast<Instruction>(VL[i]); 202 if (!I) 203 return false; 204 205 if (BB != I->getParent()) 206 return false; 207 } 208 return true; 209 } 210 211 /// \returns True if all of the values in \p VL are constants. 212 static bool allConstant(ArrayRef<Value *> VL) { 213 for (Value *i : VL) 214 if (!isa<Constant>(i)) 215 return false; 216 return true; 217 } 218 219 /// \returns True if all of the values in \p VL are identical. 220 static bool isSplat(ArrayRef<Value *> VL) { 221 for (unsigned i = 1, e = VL.size(); i < e; ++i) 222 if (VL[i] != VL[0]) 223 return false; 224 return true; 225 } 226 227 /// \returns True if \p I is commutative, handles CmpInst as well as Instruction. 228 static bool isCommutative(Instruction *I) { 229 if (auto *IC = dyn_cast<CmpInst>(I)) 230 return IC->isCommutative(); 231 return I->isCommutative(); 232 } 233 234 /// Checks if the vector of instructions can be represented as a shuffle, like: 235 /// %x0 = extractelement <4 x i8> %x, i32 0 236 /// %x3 = extractelement <4 x i8> %x, i32 3 237 /// %y1 = extractelement <4 x i8> %y, i32 1 238 /// %y2 = extractelement <4 x i8> %y, i32 2 239 /// %x0x0 = mul i8 %x0, %x0 240 /// %x3x3 = mul i8 %x3, %x3 241 /// %y1y1 = mul i8 %y1, %y1 242 /// %y2y2 = mul i8 %y2, %y2 243 /// %ins1 = insertelement <4 x i8> undef, i8 %x0x0, i32 0 244 /// %ins2 = insertelement <4 x i8> %ins1, i8 %x3x3, i32 1 245 /// %ins3 = insertelement <4 x i8> %ins2, i8 %y1y1, i32 2 246 /// %ins4 = insertelement <4 x i8> %ins3, i8 %y2y2, i32 3 247 /// ret <4 x i8> %ins4 248 /// can be transformed into: 249 /// %1 = shufflevector <4 x i8> %x, <4 x i8> %y, <4 x i32> <i32 0, i32 3, i32 5, 250 /// i32 6> 251 /// %2 = mul <4 x i8> %1, %1 252 /// ret <4 x i8> %2 253 /// We convert this initially to something like: 254 /// %x0 = extractelement <4 x i8> %x, i32 0 255 /// %x3 = extractelement <4 x i8> %x, i32 3 256 /// %y1 = extractelement <4 x i8> %y, i32 1 257 /// %y2 = extractelement <4 x i8> %y, i32 2 258 /// %1 = insertelement <4 x i8> undef, i8 %x0, i32 0 259 /// %2 = insertelement <4 x i8> %1, i8 %x3, i32 1 260 /// %3 = insertelement <4 x i8> %2, i8 %y1, i32 2 261 /// %4 = insertelement <4 x i8> %3, i8 %y2, i32 3 262 /// %5 = mul <4 x i8> %4, %4 263 /// %6 = extractelement <4 x i8> %5, i32 0 264 /// %ins1 = insertelement <4 x i8> undef, i8 %6, i32 0 265 /// %7 = extractelement <4 x i8> %5, i32 1 266 /// %ins2 = insertelement <4 x i8> %ins1, i8 %7, i32 1 267 /// %8 = extractelement <4 x i8> %5, i32 2 268 /// %ins3 = insertelement <4 x i8> %ins2, i8 %8, i32 2 269 /// %9 = extractelement <4 x i8> %5, i32 3 270 /// %ins4 = insertelement <4 x i8> %ins3, i8 %9, i32 3 271 /// ret <4 x i8> %ins4 272 /// InstCombiner transforms this into a shuffle and vector mul 273 /// TODO: Can we split off and reuse the shuffle mask detection from 274 /// TargetTransformInfo::getInstructionThroughput? 275 static Optional<TargetTransformInfo::ShuffleKind> 276 isShuffle(ArrayRef<Value *> VL) { 277 auto *EI0 = cast<ExtractElementInst>(VL[0]); 278 unsigned Size = EI0->getVectorOperandType()->getVectorNumElements(); 279 Value *Vec1 = nullptr; 280 Value *Vec2 = nullptr; 281 enum ShuffleMode { Unknown, Select, Permute }; 282 ShuffleMode CommonShuffleMode = Unknown; 283 for (unsigned I = 0, E = VL.size(); I < E; ++I) { 284 auto *EI = cast<ExtractElementInst>(VL[I]); 285 auto *Vec = EI->getVectorOperand(); 286 // All vector operands must have the same number of vector elements. 287 if (Vec->getType()->getVectorNumElements() != Size) 288 return None; 289 auto *Idx = dyn_cast<ConstantInt>(EI->getIndexOperand()); 290 if (!Idx) 291 return None; 292 // Undefined behavior if Idx is negative or >= Size. 293 if (Idx->getValue().uge(Size)) 294 continue; 295 unsigned IntIdx = Idx->getValue().getZExtValue(); 296 // We can extractelement from undef vector. 297 if (isa<UndefValue>(Vec)) 298 continue; 299 // For correct shuffling we have to have at most 2 different vector operands 300 // in all extractelement instructions. 301 if (!Vec1 || Vec1 == Vec) 302 Vec1 = Vec; 303 else if (!Vec2 || Vec2 == Vec) 304 Vec2 = Vec; 305 else 306 return None; 307 if (CommonShuffleMode == Permute) 308 continue; 309 // If the extract index is not the same as the operation number, it is a 310 // permutation. 311 if (IntIdx != I) { 312 CommonShuffleMode = Permute; 313 continue; 314 } 315 CommonShuffleMode = Select; 316 } 317 // If we're not crossing lanes in different vectors, consider it as blending. 318 if (CommonShuffleMode == Select && Vec2) 319 return TargetTransformInfo::SK_Select; 320 // If Vec2 was never used, we have a permutation of a single vector, otherwise 321 // we have permutation of 2 vectors. 322 return Vec2 ? TargetTransformInfo::SK_PermuteTwoSrc 323 : TargetTransformInfo::SK_PermuteSingleSrc; 324 } 325 326 namespace { 327 328 /// Main data required for vectorization of instructions. 329 struct InstructionsState { 330 /// The very first instruction in the list with the main opcode. 331 Value *OpValue = nullptr; 332 333 /// The main/alternate instruction. 334 Instruction *MainOp = nullptr; 335 Instruction *AltOp = nullptr; 336 337 /// The main/alternate opcodes for the list of instructions. 338 unsigned getOpcode() const { 339 return MainOp ? MainOp->getOpcode() : 0; 340 } 341 342 unsigned getAltOpcode() const { 343 return AltOp ? AltOp->getOpcode() : 0; 344 } 345 346 /// Some of the instructions in the list have alternate opcodes. 347 bool isAltShuffle() const { return getOpcode() != getAltOpcode(); } 348 349 bool isOpcodeOrAlt(Instruction *I) const { 350 unsigned CheckedOpcode = I->getOpcode(); 351 return getOpcode() == CheckedOpcode || getAltOpcode() == CheckedOpcode; 352 } 353 354 InstructionsState() = delete; 355 InstructionsState(Value *OpValue, Instruction *MainOp, Instruction *AltOp) 356 : OpValue(OpValue), MainOp(MainOp), AltOp(AltOp) {} 357 }; 358 359 } // end anonymous namespace 360 361 /// Chooses the correct key for scheduling data. If \p Op has the same (or 362 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is \p 363 /// OpValue. 364 static Value *isOneOf(const InstructionsState &S, Value *Op) { 365 auto *I = dyn_cast<Instruction>(Op); 366 if (I && S.isOpcodeOrAlt(I)) 367 return Op; 368 return S.OpValue; 369 } 370 371 /// \returns analysis of the Instructions in \p VL described in 372 /// InstructionsState, the Opcode that we suppose the whole list 373 /// could be vectorized even if its structure is diverse. 374 static InstructionsState getSameOpcode(ArrayRef<Value *> VL, 375 unsigned BaseIndex = 0) { 376 // Make sure these are all Instructions. 377 if (llvm::any_of(VL, [](Value *V) { return !isa<Instruction>(V); })) 378 return InstructionsState(VL[BaseIndex], nullptr, nullptr); 379 380 bool IsCastOp = isa<CastInst>(VL[BaseIndex]); 381 bool IsBinOp = isa<BinaryOperator>(VL[BaseIndex]); 382 unsigned Opcode = cast<Instruction>(VL[BaseIndex])->getOpcode(); 383 unsigned AltOpcode = Opcode; 384 unsigned AltIndex = BaseIndex; 385 386 // Check for one alternate opcode from another BinaryOperator. 387 // TODO - generalize to support all operators (types, calls etc.). 388 for (int Cnt = 0, E = VL.size(); Cnt < E; Cnt++) { 389 unsigned InstOpcode = cast<Instruction>(VL[Cnt])->getOpcode(); 390 if (IsBinOp && isa<BinaryOperator>(VL[Cnt])) { 391 if (InstOpcode == Opcode || InstOpcode == AltOpcode) 392 continue; 393 if (Opcode == AltOpcode) { 394 AltOpcode = InstOpcode; 395 AltIndex = Cnt; 396 continue; 397 } 398 } else if (IsCastOp && isa<CastInst>(VL[Cnt])) { 399 Type *Ty0 = cast<Instruction>(VL[BaseIndex])->getOperand(0)->getType(); 400 Type *Ty1 = cast<Instruction>(VL[Cnt])->getOperand(0)->getType(); 401 if (Ty0 == Ty1) { 402 if (InstOpcode == Opcode || InstOpcode == AltOpcode) 403 continue; 404 if (Opcode == AltOpcode) { 405 AltOpcode = InstOpcode; 406 AltIndex = Cnt; 407 continue; 408 } 409 } 410 } else if (InstOpcode == Opcode || InstOpcode == AltOpcode) 411 continue; 412 return InstructionsState(VL[BaseIndex], nullptr, nullptr); 413 } 414 415 return InstructionsState(VL[BaseIndex], cast<Instruction>(VL[BaseIndex]), 416 cast<Instruction>(VL[AltIndex])); 417 } 418 419 /// \returns true if all of the values in \p VL have the same type or false 420 /// otherwise. 421 static bool allSameType(ArrayRef<Value *> VL) { 422 Type *Ty = VL[0]->getType(); 423 for (int i = 1, e = VL.size(); i < e; i++) 424 if (VL[i]->getType() != Ty) 425 return false; 426 427 return true; 428 } 429 430 /// \returns True if Extract{Value,Element} instruction extracts element Idx. 431 static Optional<unsigned> getExtractIndex(Instruction *E) { 432 unsigned Opcode = E->getOpcode(); 433 assert((Opcode == Instruction::ExtractElement || 434 Opcode == Instruction::ExtractValue) && 435 "Expected extractelement or extractvalue instruction."); 436 if (Opcode == Instruction::ExtractElement) { 437 auto *CI = dyn_cast<ConstantInt>(E->getOperand(1)); 438 if (!CI) 439 return None; 440 return CI->getZExtValue(); 441 } 442 ExtractValueInst *EI = cast<ExtractValueInst>(E); 443 if (EI->getNumIndices() != 1) 444 return None; 445 return *EI->idx_begin(); 446 } 447 448 /// \returns True if in-tree use also needs extract. This refers to 449 /// possible scalar operand in vectorized instruction. 450 static bool InTreeUserNeedToExtract(Value *Scalar, Instruction *UserInst, 451 TargetLibraryInfo *TLI) { 452 unsigned Opcode = UserInst->getOpcode(); 453 switch (Opcode) { 454 case Instruction::Load: { 455 LoadInst *LI = cast<LoadInst>(UserInst); 456 return (LI->getPointerOperand() == Scalar); 457 } 458 case Instruction::Store: { 459 StoreInst *SI = cast<StoreInst>(UserInst); 460 return (SI->getPointerOperand() == Scalar); 461 } 462 case Instruction::Call: { 463 CallInst *CI = cast<CallInst>(UserInst); 464 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 465 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 466 if (hasVectorInstrinsicScalarOpd(ID, i)) 467 return (CI->getArgOperand(i) == Scalar); 468 } 469 LLVM_FALLTHROUGH; 470 } 471 default: 472 return false; 473 } 474 } 475 476 /// \returns the AA location that is being access by the instruction. 477 static MemoryLocation getLocation(Instruction *I, AliasAnalysis *AA) { 478 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 479 return MemoryLocation::get(SI); 480 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 481 return MemoryLocation::get(LI); 482 return MemoryLocation(); 483 } 484 485 /// \returns True if the instruction is not a volatile or atomic load/store. 486 static bool isSimple(Instruction *I) { 487 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 488 return LI->isSimple(); 489 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 490 return SI->isSimple(); 491 if (MemIntrinsic *MI = dyn_cast<MemIntrinsic>(I)) 492 return !MI->isVolatile(); 493 return true; 494 } 495 496 namespace llvm { 497 498 namespace slpvectorizer { 499 500 /// Bottom Up SLP Vectorizer. 501 class BoUpSLP { 502 struct TreeEntry; 503 504 public: 505 using ValueList = SmallVector<Value *, 8>; 506 using InstrList = SmallVector<Instruction *, 16>; 507 using ValueSet = SmallPtrSet<Value *, 16>; 508 using StoreList = SmallVector<StoreInst *, 8>; 509 using ExtraValueToDebugLocsMap = 510 MapVector<Value *, SmallVector<Instruction *, 2>>; 511 512 BoUpSLP(Function *Func, ScalarEvolution *Se, TargetTransformInfo *Tti, 513 TargetLibraryInfo *TLi, AliasAnalysis *Aa, LoopInfo *Li, 514 DominatorTree *Dt, AssumptionCache *AC, DemandedBits *DB, 515 const DataLayout *DL, OptimizationRemarkEmitter *ORE) 516 : F(Func), SE(Se), TTI(Tti), TLI(TLi), AA(Aa), LI(Li), DT(Dt), AC(AC), 517 DB(DB), DL(DL), ORE(ORE), Builder(Se->getContext()) { 518 CodeMetrics::collectEphemeralValues(F, AC, EphValues); 519 // Use the vector register size specified by the target unless overridden 520 // by a command-line option. 521 // TODO: It would be better to limit the vectorization factor based on 522 // data type rather than just register size. For example, x86 AVX has 523 // 256-bit registers, but it does not support integer operations 524 // at that width (that requires AVX2). 525 if (MaxVectorRegSizeOption.getNumOccurrences()) 526 MaxVecRegSize = MaxVectorRegSizeOption; 527 else 528 MaxVecRegSize = TTI->getRegisterBitWidth(true); 529 530 if (MinVectorRegSizeOption.getNumOccurrences()) 531 MinVecRegSize = MinVectorRegSizeOption; 532 else 533 MinVecRegSize = TTI->getMinVectorRegisterBitWidth(); 534 } 535 536 /// Vectorize the tree that starts with the elements in \p VL. 537 /// Returns the vectorized root. 538 Value *vectorizeTree(); 539 540 /// Vectorize the tree but with the list of externally used values \p 541 /// ExternallyUsedValues. Values in this MapVector can be replaced but the 542 /// generated extractvalue instructions. 543 Value *vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues); 544 545 /// \returns the cost incurred by unwanted spills and fills, caused by 546 /// holding live values over call sites. 547 int getSpillCost() const; 548 549 /// \returns the vectorization cost of the subtree that starts at \p VL. 550 /// A negative number means that this is profitable. 551 int getTreeCost(); 552 553 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 554 /// the purpose of scheduling and extraction in the \p UserIgnoreLst. 555 void buildTree(ArrayRef<Value *> Roots, 556 ArrayRef<Value *> UserIgnoreLst = None); 557 558 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 559 /// the purpose of scheduling and extraction in the \p UserIgnoreLst taking 560 /// into account (anf updating it, if required) list of externally used 561 /// values stored in \p ExternallyUsedValues. 562 void buildTree(ArrayRef<Value *> Roots, 563 ExtraValueToDebugLocsMap &ExternallyUsedValues, 564 ArrayRef<Value *> UserIgnoreLst = None); 565 566 /// Clear the internal data structures that are created by 'buildTree'. 567 void deleteTree() { 568 VectorizableTree.clear(); 569 ScalarToTreeEntry.clear(); 570 MustGather.clear(); 571 ExternalUses.clear(); 572 NumOpsWantToKeepOrder.clear(); 573 NumOpsWantToKeepOriginalOrder = 0; 574 for (auto &Iter : BlocksSchedules) { 575 BlockScheduling *BS = Iter.second.get(); 576 BS->clear(); 577 } 578 MinBWs.clear(); 579 } 580 581 unsigned getTreeSize() const { return VectorizableTree.size(); } 582 583 /// Perform LICM and CSE on the newly generated gather sequences. 584 void optimizeGatherSequence(); 585 586 /// \returns The best order of instructions for vectorization. 587 Optional<ArrayRef<unsigned>> bestOrder() const { 588 auto I = std::max_element( 589 NumOpsWantToKeepOrder.begin(), NumOpsWantToKeepOrder.end(), 590 [](const decltype(NumOpsWantToKeepOrder)::value_type &D1, 591 const decltype(NumOpsWantToKeepOrder)::value_type &D2) { 592 return D1.second < D2.second; 593 }); 594 if (I == NumOpsWantToKeepOrder.end() || 595 I->getSecond() <= NumOpsWantToKeepOriginalOrder) 596 return None; 597 598 return makeArrayRef(I->getFirst()); 599 } 600 601 /// \return The vector element size in bits to use when vectorizing the 602 /// expression tree ending at \p V. If V is a store, the size is the width of 603 /// the stored value. Otherwise, the size is the width of the largest loaded 604 /// value reaching V. This method is used by the vectorizer to calculate 605 /// vectorization factors. 606 unsigned getVectorElementSize(Value *V) const; 607 608 /// Compute the minimum type sizes required to represent the entries in a 609 /// vectorizable tree. 610 void computeMinimumValueSizes(); 611 612 // \returns maximum vector register size as set by TTI or overridden by cl::opt. 613 unsigned getMaxVecRegSize() const { 614 return MaxVecRegSize; 615 } 616 617 // \returns minimum vector register size as set by cl::opt. 618 unsigned getMinVecRegSize() const { 619 return MinVecRegSize; 620 } 621 622 /// Check if ArrayType or StructType is isomorphic to some VectorType. 623 /// 624 /// \returns number of elements in vector if isomorphism exists, 0 otherwise. 625 unsigned canMapToVector(Type *T, const DataLayout &DL) const; 626 627 /// \returns True if the VectorizableTree is both tiny and not fully 628 /// vectorizable. We do not vectorize such trees. 629 bool isTreeTinyAndNotFullyVectorizable() const; 630 631 OptimizationRemarkEmitter *getORE() { return ORE; } 632 633 /// This structure holds any data we need about the edges being traversed 634 /// during buildTree_rec(). We keep track of: 635 /// (i) the user TreeEntry index, and 636 /// (ii) the index of the edge. 637 struct EdgeInfo { 638 EdgeInfo() = default; 639 EdgeInfo(TreeEntry *UserTE, unsigned EdgeIdx) 640 : UserTE(UserTE), EdgeIdx(EdgeIdx) {} 641 /// The user TreeEntry. 642 TreeEntry *UserTE = nullptr; 643 /// The operand index of the use. 644 unsigned EdgeIdx = UINT_MAX; 645 #ifndef NDEBUG 646 friend inline raw_ostream &operator<<(raw_ostream &OS, 647 const BoUpSLP::EdgeInfo &EI) { 648 EI.dump(OS); 649 return OS; 650 } 651 /// Debug print. 652 void dump(raw_ostream &OS) const { 653 OS << "{User:" << (UserTE ? std::to_string(UserTE->Idx) : "null") 654 << " EdgeIdx:" << EdgeIdx << "}"; 655 } 656 LLVM_DUMP_METHOD void dump() const { dump(dbgs()); } 657 #endif 658 }; 659 660 /// A helper data structure to hold the operands of a vector of instructions. 661 /// This supports a fixed vector length for all operand vectors. 662 class VLOperands { 663 /// For each operand we need (i) the value, and (ii) the opcode that it 664 /// would be attached to if the expression was in a left-linearized form. 665 /// This is required to avoid illegal operand reordering. 666 /// For example: 667 /// \verbatim 668 /// 0 Op1 669 /// |/ 670 /// Op1 Op2 Linearized + Op2 671 /// \ / ----------> |/ 672 /// - - 673 /// 674 /// Op1 - Op2 (0 + Op1) - Op2 675 /// \endverbatim 676 /// 677 /// Value Op1 is attached to a '+' operation, and Op2 to a '-'. 678 /// 679 /// Another way to think of this is to track all the operations across the 680 /// path from the operand all the way to the root of the tree and to 681 /// calculate the operation that corresponds to this path. For example, the 682 /// path from Op2 to the root crosses the RHS of the '-', therefore the 683 /// corresponding operation is a '-' (which matches the one in the 684 /// linearized tree, as shown above). 685 /// 686 /// For lack of a better term, we refer to this operation as Accumulated 687 /// Path Operation (APO). 688 struct OperandData { 689 OperandData() = default; 690 OperandData(Value *V, bool APO, bool IsUsed) 691 : V(V), APO(APO), IsUsed(IsUsed) {} 692 /// The operand value. 693 Value *V = nullptr; 694 /// TreeEntries only allow a single opcode, or an alternate sequence of 695 /// them (e.g, +, -). Therefore, we can safely use a boolean value for the 696 /// APO. It is set to 'true' if 'V' is attached to an inverse operation 697 /// in the left-linearized form (e.g., Sub/Div), and 'false' otherwise 698 /// (e.g., Add/Mul) 699 bool APO = false; 700 /// Helper data for the reordering function. 701 bool IsUsed = false; 702 }; 703 704 /// During operand reordering, we are trying to select the operand at lane 705 /// that matches best with the operand at the neighboring lane. Our 706 /// selection is based on the type of value we are looking for. For example, 707 /// if the neighboring lane has a load, we need to look for a load that is 708 /// accessing a consecutive address. These strategies are summarized in the 709 /// 'ReorderingMode' enumerator. 710 enum class ReorderingMode { 711 Load, ///< Matching loads to consecutive memory addresses 712 Opcode, ///< Matching instructions based on opcode (same or alternate) 713 Constant, ///< Matching constants 714 Splat, ///< Matching the same instruction multiple times (broadcast) 715 Failed, ///< We failed to create a vectorizable group 716 }; 717 718 using OperandDataVec = SmallVector<OperandData, 2>; 719 720 /// A vector of operand vectors. 721 SmallVector<OperandDataVec, 4> OpsVec; 722 723 const DataLayout &DL; 724 ScalarEvolution &SE; 725 const BoUpSLP &R; 726 727 /// \returns the operand data at \p OpIdx and \p Lane. 728 OperandData &getData(unsigned OpIdx, unsigned Lane) { 729 return OpsVec[OpIdx][Lane]; 730 } 731 732 /// \returns the operand data at \p OpIdx and \p Lane. Const version. 733 const OperandData &getData(unsigned OpIdx, unsigned Lane) const { 734 return OpsVec[OpIdx][Lane]; 735 } 736 737 /// Clears the used flag for all entries. 738 void clearUsed() { 739 for (unsigned OpIdx = 0, NumOperands = getNumOperands(); 740 OpIdx != NumOperands; ++OpIdx) 741 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 742 ++Lane) 743 OpsVec[OpIdx][Lane].IsUsed = false; 744 } 745 746 /// Swap the operand at \p OpIdx1 with that one at \p OpIdx2. 747 void swap(unsigned OpIdx1, unsigned OpIdx2, unsigned Lane) { 748 std::swap(OpsVec[OpIdx1][Lane], OpsVec[OpIdx2][Lane]); 749 } 750 751 // The hard-coded scores listed here are not very important. When computing 752 // the scores of matching one sub-tree with another, we are basically 753 // counting the number of values that are matching. So even if all scores 754 // are set to 1, we would still get a decent matching result. 755 // However, sometimes we have to break ties. For example we may have to 756 // choose between matching loads vs matching opcodes. This is what these 757 // scores are helping us with: they provide the order of preference. 758 759 /// Loads from consecutive memory addresses, e.g. load(A[i]), load(A[i+1]). 760 static const int ScoreConsecutiveLoads = 3; 761 /// Constants. 762 static const int ScoreConstants = 2; 763 /// Instructions with the same opcode. 764 static const int ScoreSameOpcode = 2; 765 /// Instructions with alt opcodes (e.g, add + sub). 766 static const int ScoreAltOpcodes = 1; 767 /// Identical instructions (a.k.a. splat or broadcast). 768 static const int ScoreSplat = 1; 769 /// Matching with an undef is preferable to failing. 770 static const int ScoreUndef = 1; 771 /// Score for failing to find a decent match. 772 static const int ScoreFail = 0; 773 /// User exteranl to the vectorized code. 774 static const int ExternalUseCost = 1; 775 /// The user is internal but in a different lane. 776 static const int UserInDiffLaneCost = ExternalUseCost; 777 778 /// \returns the score of placing \p V1 and \p V2 in consecutive lanes. 779 static int getShallowScore(Value *V1, Value *V2, const DataLayout &DL, 780 ScalarEvolution &SE) { 781 auto *LI1 = dyn_cast<LoadInst>(V1); 782 auto *LI2 = dyn_cast<LoadInst>(V2); 783 if (LI1 && LI2) 784 return isConsecutiveAccess(LI1, LI2, DL, SE) 785 ? VLOperands::ScoreConsecutiveLoads 786 : VLOperands::ScoreFail; 787 788 auto *C1 = dyn_cast<Constant>(V1); 789 auto *C2 = dyn_cast<Constant>(V2); 790 if (C1 && C2) 791 return VLOperands::ScoreConstants; 792 793 auto *I1 = dyn_cast<Instruction>(V1); 794 auto *I2 = dyn_cast<Instruction>(V2); 795 if (I1 && I2) { 796 if (I1 == I2) 797 return VLOperands::ScoreSplat; 798 InstructionsState S = getSameOpcode({I1, I2}); 799 // Note: Only consider instructions with <= 2 operands to avoid 800 // complexity explosion. 801 if (S.getOpcode() && S.MainOp->getNumOperands() <= 2) 802 return S.isAltShuffle() ? VLOperands::ScoreAltOpcodes 803 : VLOperands::ScoreSameOpcode; 804 } 805 806 if (isa<UndefValue>(V2)) 807 return VLOperands::ScoreUndef; 808 809 return VLOperands::ScoreFail; 810 } 811 812 /// Holds the values and their lane that are taking part in the look-ahead 813 /// score calculation. This is used in the external uses cost calculation. 814 SmallDenseMap<Value *, int> InLookAheadValues; 815 816 /// \Returns the additinal cost due to uses of \p LHS and \p RHS that are 817 /// either external to the vectorized code, or require shuffling. 818 int getExternalUsesCost(const std::pair<Value *, int> &LHS, 819 const std::pair<Value *, int> &RHS) { 820 int Cost = 0; 821 SmallVector<std::pair<Value *, int>, 2> Values = {LHS, RHS}; 822 for (int Idx = 0, IdxE = Values.size(); Idx != IdxE; ++Idx) { 823 Value *V = Values[Idx].first; 824 // Calculate the absolute lane, using the minimum relative lane of LHS 825 // and RHS as base and Idx as the offset. 826 int Ln = std::min(LHS.second, RHS.second) + Idx; 827 assert(Ln >= 0 && "Bad lane calculation"); 828 unsigned UsersBudget = LookAheadUsersBudget; 829 for (User *U : V->users()) { 830 if (const TreeEntry *UserTE = R.getTreeEntry(U)) { 831 // The user is in the VectorizableTree. Check if we need to insert. 832 auto It = llvm::find(UserTE->Scalars, U); 833 assert(It != UserTE->Scalars.end() && "U is in UserTE"); 834 int UserLn = std::distance(UserTE->Scalars.begin(), It); 835 assert(UserLn >= 0 && "Bad lane"); 836 if (UserLn != Ln) 837 Cost += UserInDiffLaneCost; 838 } else { 839 // Check if the user is in the look-ahead code. 840 auto It2 = InLookAheadValues.find(U); 841 if (It2 != InLookAheadValues.end()) { 842 // The user is in the look-ahead code. Check the lane. 843 if (It2->second != Ln) 844 Cost += UserInDiffLaneCost; 845 } else { 846 // The user is neither in SLP tree nor in the look-ahead code. 847 Cost += ExternalUseCost; 848 } 849 } 850 // Limit the number of visited uses to cap compilation time. 851 if (--UsersBudget == 0) 852 break; 853 } 854 } 855 return Cost; 856 } 857 858 /// Go through the operands of \p LHS and \p RHS recursively until \p 859 /// MaxLevel, and return the cummulative score. For example: 860 /// \verbatim 861 /// A[0] B[0] A[1] B[1] C[0] D[0] B[1] A[1] 862 /// \ / \ / \ / \ / 863 /// + + + + 864 /// G1 G2 G3 G4 865 /// \endverbatim 866 /// The getScoreAtLevelRec(G1, G2) function will try to match the nodes at 867 /// each level recursively, accumulating the score. It starts from matching 868 /// the additions at level 0, then moves on to the loads (level 1). The 869 /// score of G1 and G2 is higher than G1 and G3, because {A[0],A[1]} and 870 /// {B[0],B[1]} match with VLOperands::ScoreConsecutiveLoads, while 871 /// {A[0],C[0]} has a score of VLOperands::ScoreFail. 872 /// Please note that the order of the operands does not matter, as we 873 /// evaluate the score of all profitable combinations of operands. In 874 /// other words the score of G1 and G4 is the same as G1 and G2. This 875 /// heuristic is based on ideas described in: 876 /// Look-ahead SLP: Auto-vectorization in the presence of commutative 877 /// operations, CGO 2018 by Vasileios Porpodas, Rodrigo C. O. Rocha, 878 /// Luís F. W. Góes 879 int getScoreAtLevelRec(const std::pair<Value *, int> &LHS, 880 const std::pair<Value *, int> &RHS, int CurrLevel, 881 int MaxLevel) { 882 883 Value *V1 = LHS.first; 884 Value *V2 = RHS.first; 885 // Get the shallow score of V1 and V2. 886 int ShallowScoreAtThisLevel = 887 std::max((int)ScoreFail, getShallowScore(V1, V2, DL, SE) - 888 getExternalUsesCost(LHS, RHS)); 889 int Lane1 = LHS.second; 890 int Lane2 = RHS.second; 891 892 // If reached MaxLevel, 893 // or if V1 and V2 are not instructions, 894 // or if they are SPLAT, 895 // or if they are not consecutive, early return the current cost. 896 auto *I1 = dyn_cast<Instruction>(V1); 897 auto *I2 = dyn_cast<Instruction>(V2); 898 if (CurrLevel == MaxLevel || !(I1 && I2) || I1 == I2 || 899 ShallowScoreAtThisLevel == VLOperands::ScoreFail || 900 (isa<LoadInst>(I1) && isa<LoadInst>(I2) && ShallowScoreAtThisLevel)) 901 return ShallowScoreAtThisLevel; 902 assert(I1 && I2 && "Should have early exited."); 903 904 // Keep track of in-tree values for determining the external-use cost. 905 InLookAheadValues[V1] = Lane1; 906 InLookAheadValues[V2] = Lane2; 907 908 // Contains the I2 operand indexes that got matched with I1 operands. 909 SmallSet<unsigned, 4> Op2Used; 910 911 // Recursion towards the operands of I1 and I2. We are trying all possbile 912 // operand pairs, and keeping track of the best score. 913 for (unsigned OpIdx1 = 0, NumOperands1 = I1->getNumOperands(); 914 OpIdx1 != NumOperands1; ++OpIdx1) { 915 // Try to pair op1I with the best operand of I2. 916 int MaxTmpScore = 0; 917 unsigned MaxOpIdx2 = 0; 918 bool FoundBest = false; 919 // If I2 is commutative try all combinations. 920 unsigned FromIdx = isCommutative(I2) ? 0 : OpIdx1; 921 unsigned ToIdx = isCommutative(I2) 922 ? I2->getNumOperands() 923 : std::min(I2->getNumOperands(), OpIdx1 + 1); 924 assert(FromIdx <= ToIdx && "Bad index"); 925 for (unsigned OpIdx2 = FromIdx; OpIdx2 != ToIdx; ++OpIdx2) { 926 // Skip operands already paired with OpIdx1. 927 if (Op2Used.count(OpIdx2)) 928 continue; 929 // Recursively calculate the cost at each level 930 int TmpScore = getScoreAtLevelRec({I1->getOperand(OpIdx1), Lane1}, 931 {I2->getOperand(OpIdx2), Lane2}, 932 CurrLevel + 1, MaxLevel); 933 // Look for the best score. 934 if (TmpScore > VLOperands::ScoreFail && TmpScore > MaxTmpScore) { 935 MaxTmpScore = TmpScore; 936 MaxOpIdx2 = OpIdx2; 937 FoundBest = true; 938 } 939 } 940 if (FoundBest) { 941 // Pair {OpIdx1, MaxOpIdx2} was found to be best. Never revisit it. 942 Op2Used.insert(MaxOpIdx2); 943 ShallowScoreAtThisLevel += MaxTmpScore; 944 } 945 } 946 return ShallowScoreAtThisLevel; 947 } 948 949 /// \Returns the look-ahead score, which tells us how much the sub-trees 950 /// rooted at \p LHS and \p RHS match, the more they match the higher the 951 /// score. This helps break ties in an informed way when we cannot decide on 952 /// the order of the operands by just considering the immediate 953 /// predecessors. 954 int getLookAheadScore(const std::pair<Value *, int> &LHS, 955 const std::pair<Value *, int> &RHS) { 956 InLookAheadValues.clear(); 957 return getScoreAtLevelRec(LHS, RHS, 1, LookAheadMaxDepth); 958 } 959 960 // Search all operands in Ops[*][Lane] for the one that matches best 961 // Ops[OpIdx][LastLane] and return its opreand index. 962 // If no good match can be found, return None. 963 Optional<unsigned> 964 getBestOperand(unsigned OpIdx, int Lane, int LastLane, 965 ArrayRef<ReorderingMode> ReorderingModes) { 966 unsigned NumOperands = getNumOperands(); 967 968 // The operand of the previous lane at OpIdx. 969 Value *OpLastLane = getData(OpIdx, LastLane).V; 970 971 // Our strategy mode for OpIdx. 972 ReorderingMode RMode = ReorderingModes[OpIdx]; 973 974 // The linearized opcode of the operand at OpIdx, Lane. 975 bool OpIdxAPO = getData(OpIdx, Lane).APO; 976 977 // The best operand index and its score. 978 // Sometimes we have more than one option (e.g., Opcode and Undefs), so we 979 // are using the score to differentiate between the two. 980 struct BestOpData { 981 Optional<unsigned> Idx = None; 982 unsigned Score = 0; 983 } BestOp; 984 985 // Iterate through all unused operands and look for the best. 986 for (unsigned Idx = 0; Idx != NumOperands; ++Idx) { 987 // Get the operand at Idx and Lane. 988 OperandData &OpData = getData(Idx, Lane); 989 Value *Op = OpData.V; 990 bool OpAPO = OpData.APO; 991 992 // Skip already selected operands. 993 if (OpData.IsUsed) 994 continue; 995 996 // Skip if we are trying to move the operand to a position with a 997 // different opcode in the linearized tree form. This would break the 998 // semantics. 999 if (OpAPO != OpIdxAPO) 1000 continue; 1001 1002 // Look for an operand that matches the current mode. 1003 switch (RMode) { 1004 case ReorderingMode::Load: 1005 case ReorderingMode::Constant: 1006 case ReorderingMode::Opcode: { 1007 bool LeftToRight = Lane > LastLane; 1008 Value *OpLeft = (LeftToRight) ? OpLastLane : Op; 1009 Value *OpRight = (LeftToRight) ? Op : OpLastLane; 1010 unsigned Score = 1011 getLookAheadScore({OpLeft, LastLane}, {OpRight, Lane}); 1012 if (Score > BestOp.Score) { 1013 BestOp.Idx = Idx; 1014 BestOp.Score = Score; 1015 } 1016 break; 1017 } 1018 case ReorderingMode::Splat: 1019 if (Op == OpLastLane) 1020 BestOp.Idx = Idx; 1021 break; 1022 case ReorderingMode::Failed: 1023 return None; 1024 } 1025 } 1026 1027 if (BestOp.Idx) { 1028 getData(BestOp.Idx.getValue(), Lane).IsUsed = true; 1029 return BestOp.Idx; 1030 } 1031 // If we could not find a good match return None. 1032 return None; 1033 } 1034 1035 /// Helper for reorderOperandVecs. \Returns the lane that we should start 1036 /// reordering from. This is the one which has the least number of operands 1037 /// that can freely move about. 1038 unsigned getBestLaneToStartReordering() const { 1039 unsigned BestLane = 0; 1040 unsigned Min = UINT_MAX; 1041 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 1042 ++Lane) { 1043 unsigned NumFreeOps = getMaxNumOperandsThatCanBeReordered(Lane); 1044 if (NumFreeOps < Min) { 1045 Min = NumFreeOps; 1046 BestLane = Lane; 1047 } 1048 } 1049 return BestLane; 1050 } 1051 1052 /// \Returns the maximum number of operands that are allowed to be reordered 1053 /// for \p Lane. This is used as a heuristic for selecting the first lane to 1054 /// start operand reordering. 1055 unsigned getMaxNumOperandsThatCanBeReordered(unsigned Lane) const { 1056 unsigned CntTrue = 0; 1057 unsigned NumOperands = getNumOperands(); 1058 // Operands with the same APO can be reordered. We therefore need to count 1059 // how many of them we have for each APO, like this: Cnt[APO] = x. 1060 // Since we only have two APOs, namely true and false, we can avoid using 1061 // a map. Instead we can simply count the number of operands that 1062 // correspond to one of them (in this case the 'true' APO), and calculate 1063 // the other by subtracting it from the total number of operands. 1064 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) 1065 if (getData(OpIdx, Lane).APO) 1066 ++CntTrue; 1067 unsigned CntFalse = NumOperands - CntTrue; 1068 return std::max(CntTrue, CntFalse); 1069 } 1070 1071 /// Go through the instructions in VL and append their operands. 1072 void appendOperandsOfVL(ArrayRef<Value *> VL) { 1073 assert(!VL.empty() && "Bad VL"); 1074 assert((empty() || VL.size() == getNumLanes()) && 1075 "Expected same number of lanes"); 1076 assert(isa<Instruction>(VL[0]) && "Expected instruction"); 1077 unsigned NumOperands = cast<Instruction>(VL[0])->getNumOperands(); 1078 OpsVec.resize(NumOperands); 1079 unsigned NumLanes = VL.size(); 1080 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1081 OpsVec[OpIdx].resize(NumLanes); 1082 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { 1083 assert(isa<Instruction>(VL[Lane]) && "Expected instruction"); 1084 // Our tree has just 3 nodes: the root and two operands. 1085 // It is therefore trivial to get the APO. We only need to check the 1086 // opcode of VL[Lane] and whether the operand at OpIdx is the LHS or 1087 // RHS operand. The LHS operand of both add and sub is never attached 1088 // to an inversese operation in the linearized form, therefore its APO 1089 // is false. The RHS is true only if VL[Lane] is an inverse operation. 1090 1091 // Since operand reordering is performed on groups of commutative 1092 // operations or alternating sequences (e.g., +, -), we can safely 1093 // tell the inverse operations by checking commutativity. 1094 bool IsInverseOperation = !isCommutative(cast<Instruction>(VL[Lane])); 1095 bool APO = (OpIdx == 0) ? false : IsInverseOperation; 1096 OpsVec[OpIdx][Lane] = {cast<Instruction>(VL[Lane])->getOperand(OpIdx), 1097 APO, false}; 1098 } 1099 } 1100 } 1101 1102 /// \returns the number of operands. 1103 unsigned getNumOperands() const { return OpsVec.size(); } 1104 1105 /// \returns the number of lanes. 1106 unsigned getNumLanes() const { return OpsVec[0].size(); } 1107 1108 /// \returns the operand value at \p OpIdx and \p Lane. 1109 Value *getValue(unsigned OpIdx, unsigned Lane) const { 1110 return getData(OpIdx, Lane).V; 1111 } 1112 1113 /// \returns true if the data structure is empty. 1114 bool empty() const { return OpsVec.empty(); } 1115 1116 /// Clears the data. 1117 void clear() { OpsVec.clear(); } 1118 1119 /// \Returns true if there are enough operands identical to \p Op to fill 1120 /// the whole vector. 1121 /// Note: This modifies the 'IsUsed' flag, so a cleanUsed() must follow. 1122 bool shouldBroadcast(Value *Op, unsigned OpIdx, unsigned Lane) { 1123 bool OpAPO = getData(OpIdx, Lane).APO; 1124 for (unsigned Ln = 0, Lns = getNumLanes(); Ln != Lns; ++Ln) { 1125 if (Ln == Lane) 1126 continue; 1127 // This is set to true if we found a candidate for broadcast at Lane. 1128 bool FoundCandidate = false; 1129 for (unsigned OpI = 0, OpE = getNumOperands(); OpI != OpE; ++OpI) { 1130 OperandData &Data = getData(OpI, Ln); 1131 if (Data.APO != OpAPO || Data.IsUsed) 1132 continue; 1133 if (Data.V == Op) { 1134 FoundCandidate = true; 1135 Data.IsUsed = true; 1136 break; 1137 } 1138 } 1139 if (!FoundCandidate) 1140 return false; 1141 } 1142 return true; 1143 } 1144 1145 public: 1146 /// Initialize with all the operands of the instruction vector \p RootVL. 1147 VLOperands(ArrayRef<Value *> RootVL, const DataLayout &DL, 1148 ScalarEvolution &SE, const BoUpSLP &R) 1149 : DL(DL), SE(SE), R(R) { 1150 // Append all the operands of RootVL. 1151 appendOperandsOfVL(RootVL); 1152 } 1153 1154 /// \Returns a value vector with the operands across all lanes for the 1155 /// opearnd at \p OpIdx. 1156 ValueList getVL(unsigned OpIdx) const { 1157 ValueList OpVL(OpsVec[OpIdx].size()); 1158 assert(OpsVec[OpIdx].size() == getNumLanes() && 1159 "Expected same num of lanes across all operands"); 1160 for (unsigned Lane = 0, Lanes = getNumLanes(); Lane != Lanes; ++Lane) 1161 OpVL[Lane] = OpsVec[OpIdx][Lane].V; 1162 return OpVL; 1163 } 1164 1165 // Performs operand reordering for 2 or more operands. 1166 // The original operands are in OrigOps[OpIdx][Lane]. 1167 // The reordered operands are returned in 'SortedOps[OpIdx][Lane]'. 1168 void reorder() { 1169 unsigned NumOperands = getNumOperands(); 1170 unsigned NumLanes = getNumLanes(); 1171 // Each operand has its own mode. We are using this mode to help us select 1172 // the instructions for each lane, so that they match best with the ones 1173 // we have selected so far. 1174 SmallVector<ReorderingMode, 2> ReorderingModes(NumOperands); 1175 1176 // This is a greedy single-pass algorithm. We are going over each lane 1177 // once and deciding on the best order right away with no back-tracking. 1178 // However, in order to increase its effectiveness, we start with the lane 1179 // that has operands that can move the least. For example, given the 1180 // following lanes: 1181 // Lane 0 : A[0] = B[0] + C[0] // Visited 3rd 1182 // Lane 1 : A[1] = C[1] - B[1] // Visited 1st 1183 // Lane 2 : A[2] = B[2] + C[2] // Visited 2nd 1184 // Lane 3 : A[3] = C[3] - B[3] // Visited 4th 1185 // we will start at Lane 1, since the operands of the subtraction cannot 1186 // be reordered. Then we will visit the rest of the lanes in a circular 1187 // fashion. That is, Lanes 2, then Lane 0, and finally Lane 3. 1188 1189 // Find the first lane that we will start our search from. 1190 unsigned FirstLane = getBestLaneToStartReordering(); 1191 1192 // Initialize the modes. 1193 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1194 Value *OpLane0 = getValue(OpIdx, FirstLane); 1195 // Keep track if we have instructions with all the same opcode on one 1196 // side. 1197 if (isa<LoadInst>(OpLane0)) 1198 ReorderingModes[OpIdx] = ReorderingMode::Load; 1199 else if (isa<Instruction>(OpLane0)) { 1200 // Check if OpLane0 should be broadcast. 1201 if (shouldBroadcast(OpLane0, OpIdx, FirstLane)) 1202 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1203 else 1204 ReorderingModes[OpIdx] = ReorderingMode::Opcode; 1205 } 1206 else if (isa<Constant>(OpLane0)) 1207 ReorderingModes[OpIdx] = ReorderingMode::Constant; 1208 else if (isa<Argument>(OpLane0)) 1209 // Our best hope is a Splat. It may save some cost in some cases. 1210 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1211 else 1212 // NOTE: This should be unreachable. 1213 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1214 } 1215 1216 // If the initial strategy fails for any of the operand indexes, then we 1217 // perform reordering again in a second pass. This helps avoid assigning 1218 // high priority to the failed strategy, and should improve reordering for 1219 // the non-failed operand indexes. 1220 for (int Pass = 0; Pass != 2; ++Pass) { 1221 // Skip the second pass if the first pass did not fail. 1222 bool StrategyFailed = false; 1223 // Mark all operand data as free to use. 1224 clearUsed(); 1225 // We keep the original operand order for the FirstLane, so reorder the 1226 // rest of the lanes. We are visiting the nodes in a circular fashion, 1227 // using FirstLane as the center point and increasing the radius 1228 // distance. 1229 for (unsigned Distance = 1; Distance != NumLanes; ++Distance) { 1230 // Visit the lane on the right and then the lane on the left. 1231 for (int Direction : {+1, -1}) { 1232 int Lane = FirstLane + Direction * Distance; 1233 if (Lane < 0 || Lane >= (int)NumLanes) 1234 continue; 1235 int LastLane = Lane - Direction; 1236 assert(LastLane >= 0 && LastLane < (int)NumLanes && 1237 "Out of bounds"); 1238 // Look for a good match for each operand. 1239 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1240 // Search for the operand that matches SortedOps[OpIdx][Lane-1]. 1241 Optional<unsigned> BestIdx = 1242 getBestOperand(OpIdx, Lane, LastLane, ReorderingModes); 1243 // By not selecting a value, we allow the operands that follow to 1244 // select a better matching value. We will get a non-null value in 1245 // the next run of getBestOperand(). 1246 if (BestIdx) { 1247 // Swap the current operand with the one returned by 1248 // getBestOperand(). 1249 swap(OpIdx, BestIdx.getValue(), Lane); 1250 } else { 1251 // We failed to find a best operand, set mode to 'Failed'. 1252 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1253 // Enable the second pass. 1254 StrategyFailed = true; 1255 } 1256 } 1257 } 1258 } 1259 // Skip second pass if the strategy did not fail. 1260 if (!StrategyFailed) 1261 break; 1262 } 1263 } 1264 1265 #if !defined(NDEBUG) || defined(LLVM_ENABLE_DUMP) 1266 LLVM_DUMP_METHOD static StringRef getModeStr(ReorderingMode RMode) { 1267 switch (RMode) { 1268 case ReorderingMode::Load: 1269 return "Load"; 1270 case ReorderingMode::Opcode: 1271 return "Opcode"; 1272 case ReorderingMode::Constant: 1273 return "Constant"; 1274 case ReorderingMode::Splat: 1275 return "Splat"; 1276 case ReorderingMode::Failed: 1277 return "Failed"; 1278 } 1279 llvm_unreachable("Unimplemented Reordering Type"); 1280 } 1281 1282 LLVM_DUMP_METHOD static raw_ostream &printMode(ReorderingMode RMode, 1283 raw_ostream &OS) { 1284 return OS << getModeStr(RMode); 1285 } 1286 1287 /// Debug print. 1288 LLVM_DUMP_METHOD static void dumpMode(ReorderingMode RMode) { 1289 printMode(RMode, dbgs()); 1290 } 1291 1292 friend raw_ostream &operator<<(raw_ostream &OS, ReorderingMode RMode) { 1293 return printMode(RMode, OS); 1294 } 1295 1296 LLVM_DUMP_METHOD raw_ostream &print(raw_ostream &OS) const { 1297 const unsigned Indent = 2; 1298 unsigned Cnt = 0; 1299 for (const OperandDataVec &OpDataVec : OpsVec) { 1300 OS << "Operand " << Cnt++ << "\n"; 1301 for (const OperandData &OpData : OpDataVec) { 1302 OS.indent(Indent) << "{"; 1303 if (Value *V = OpData.V) 1304 OS << *V; 1305 else 1306 OS << "null"; 1307 OS << ", APO:" << OpData.APO << "}\n"; 1308 } 1309 OS << "\n"; 1310 } 1311 return OS; 1312 } 1313 1314 /// Debug print. 1315 LLVM_DUMP_METHOD void dump() const { print(dbgs()); } 1316 #endif 1317 }; 1318 1319 private: 1320 /// Checks if all users of \p I are the part of the vectorization tree. 1321 bool areAllUsersVectorized(Instruction *I) const; 1322 1323 /// \returns the cost of the vectorizable entry. 1324 int getEntryCost(TreeEntry *E); 1325 1326 /// This is the recursive part of buildTree. 1327 void buildTree_rec(ArrayRef<Value *> Roots, unsigned Depth, 1328 const EdgeInfo &EI); 1329 1330 /// \returns true if the ExtractElement/ExtractValue instructions in \p VL can 1331 /// be vectorized to use the original vector (or aggregate "bitcast" to a 1332 /// vector) and sets \p CurrentOrder to the identity permutation; otherwise 1333 /// returns false, setting \p CurrentOrder to either an empty vector or a 1334 /// non-identity permutation that allows to reuse extract instructions. 1335 bool canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 1336 SmallVectorImpl<unsigned> &CurrentOrder) const; 1337 1338 /// Vectorize a single entry in the tree. 1339 Value *vectorizeTree(TreeEntry *E); 1340 1341 /// Vectorize a single entry in the tree, starting in \p VL. 1342 Value *vectorizeTree(ArrayRef<Value *> VL); 1343 1344 /// \returns the scalarization cost for this type. Scalarization in this 1345 /// context means the creation of vectors from a group of scalars. 1346 int getGatherCost(Type *Ty, const DenseSet<unsigned> &ShuffledIndices) const; 1347 1348 /// \returns the scalarization cost for this list of values. Assuming that 1349 /// this subtree gets vectorized, we may need to extract the values from the 1350 /// roots. This method calculates the cost of extracting the values. 1351 int getGatherCost(ArrayRef<Value *> VL) const; 1352 1353 /// Set the Builder insert point to one after the last instruction in 1354 /// the bundle 1355 void setInsertPointAfterBundle(ArrayRef<Value *> VL, 1356 const InstructionsState &S); 1357 1358 /// \returns a vector from a collection of scalars in \p VL. 1359 Value *Gather(ArrayRef<Value *> VL, VectorType *Ty); 1360 1361 /// \returns whether the VectorizableTree is fully vectorizable and will 1362 /// be beneficial even the tree height is tiny. 1363 bool isFullyVectorizableTinyTree() const; 1364 1365 /// Reorder commutative or alt operands to get better probability of 1366 /// generating vectorized code. 1367 static void reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 1368 SmallVectorImpl<Value *> &Left, 1369 SmallVectorImpl<Value *> &Right, 1370 const DataLayout &DL, 1371 ScalarEvolution &SE, 1372 const BoUpSLP &R); 1373 struct TreeEntry { 1374 using VecTreeTy = SmallVector<std::unique_ptr<TreeEntry>, 8>; 1375 TreeEntry(VecTreeTy &Container) : Container(Container) {} 1376 1377 /// \returns true if the scalars in VL are equal to this entry. 1378 bool isSame(ArrayRef<Value *> VL) const { 1379 if (VL.size() == Scalars.size()) 1380 return std::equal(VL.begin(), VL.end(), Scalars.begin()); 1381 return VL.size() == ReuseShuffleIndices.size() && 1382 std::equal( 1383 VL.begin(), VL.end(), ReuseShuffleIndices.begin(), 1384 [this](Value *V, unsigned Idx) { return V == Scalars[Idx]; }); 1385 } 1386 1387 /// A vector of scalars. 1388 ValueList Scalars; 1389 1390 /// The Scalars are vectorized into this value. It is initialized to Null. 1391 Value *VectorizedValue = nullptr; 1392 1393 /// Do we need to gather this sequence ? 1394 bool NeedToGather = false; 1395 1396 /// Does this sequence require some shuffling? 1397 SmallVector<unsigned, 4> ReuseShuffleIndices; 1398 1399 /// Does this entry require reordering? 1400 ArrayRef<unsigned> ReorderIndices; 1401 1402 /// Points back to the VectorizableTree. 1403 /// 1404 /// Only used for Graphviz right now. Unfortunately GraphTrait::NodeRef has 1405 /// to be a pointer and needs to be able to initialize the child iterator. 1406 /// Thus we need a reference back to the container to translate the indices 1407 /// to entries. 1408 VecTreeTy &Container; 1409 1410 /// The TreeEntry index containing the user of this entry. We can actually 1411 /// have multiple users so the data structure is not truly a tree. 1412 SmallVector<EdgeInfo, 1> UserTreeIndices; 1413 1414 /// The index of this treeEntry in VectorizableTree. 1415 int Idx = -1; 1416 1417 private: 1418 /// The operands of each instruction in each lane Operands[op_index][lane]. 1419 /// Note: This helps avoid the replication of the code that performs the 1420 /// reordering of operands during buildTree_rec() and vectorizeTree(). 1421 SmallVector<ValueList, 2> Operands; 1422 1423 public: 1424 /// Set this bundle's \p OpIdx'th operand to \p OpVL. 1425 void setOperand(unsigned OpIdx, ArrayRef<Value *> OpVL, 1426 ArrayRef<unsigned> ReuseShuffleIndices) { 1427 if (Operands.size() < OpIdx + 1) 1428 Operands.resize(OpIdx + 1); 1429 assert(Operands[OpIdx].size() == 0 && "Already resized?"); 1430 Operands[OpIdx].resize(Scalars.size()); 1431 for (unsigned Lane = 0, E = Scalars.size(); Lane != E; ++Lane) 1432 Operands[OpIdx][Lane] = (!ReuseShuffleIndices.empty()) 1433 ? OpVL[ReuseShuffleIndices[Lane]] 1434 : OpVL[Lane]; 1435 } 1436 1437 /// If there is a user TreeEntry, then set its operand. 1438 void trySetUserTEOperand(const EdgeInfo &UserTreeIdx, 1439 ArrayRef<Value *> OpVL, 1440 ArrayRef<unsigned> ReuseShuffleIndices) { 1441 if (UserTreeIdx.UserTE) 1442 UserTreeIdx.UserTE->setOperand(UserTreeIdx.EdgeIdx, OpVL, 1443 ReuseShuffleIndices); 1444 } 1445 1446 /// \returns the \p OpIdx operand of this TreeEntry. 1447 ValueList &getOperand(unsigned OpIdx) { 1448 assert(OpIdx < Operands.size() && "Off bounds"); 1449 return Operands[OpIdx]; 1450 } 1451 1452 /// \return the single \p OpIdx operand. 1453 Value *getSingleOperand(unsigned OpIdx) const { 1454 assert(OpIdx < Operands.size() && "Off bounds"); 1455 assert(!Operands[OpIdx].empty() && "No operand available"); 1456 return Operands[OpIdx][0]; 1457 } 1458 1459 #ifndef NDEBUG 1460 /// Debug printer. 1461 LLVM_DUMP_METHOD void dump() const { 1462 dbgs() << Idx << ".\n"; 1463 for (unsigned OpI = 0, OpE = Operands.size(); OpI != OpE; ++OpI) { 1464 dbgs() << "Operand " << OpI << ":\n"; 1465 for (const Value *V : Operands[OpI]) 1466 dbgs().indent(2) << *V << "\n"; 1467 } 1468 dbgs() << "Scalars: \n"; 1469 for (Value *V : Scalars) 1470 dbgs().indent(2) << *V << "\n"; 1471 dbgs() << "NeedToGather: " << NeedToGather << "\n"; 1472 dbgs() << "VectorizedValue: "; 1473 if (VectorizedValue) 1474 dbgs() << *VectorizedValue; 1475 else 1476 dbgs() << "NULL"; 1477 dbgs() << "\n"; 1478 dbgs() << "ReuseShuffleIndices: "; 1479 if (ReuseShuffleIndices.empty()) 1480 dbgs() << "Emtpy"; 1481 else 1482 for (unsigned Idx : ReuseShuffleIndices) 1483 dbgs() << Idx << ", "; 1484 dbgs() << "\n"; 1485 dbgs() << "ReorderIndices: "; 1486 for (unsigned Idx : ReorderIndices) 1487 dbgs() << Idx << ", "; 1488 dbgs() << "\n"; 1489 dbgs() << "UserTreeIndices: "; 1490 for (const auto &EInfo : UserTreeIndices) 1491 dbgs() << EInfo << ", "; 1492 dbgs() << "\n"; 1493 } 1494 #endif 1495 }; 1496 1497 /// Create a new VectorizableTree entry. 1498 TreeEntry *newTreeEntry(ArrayRef<Value *> VL, bool Vectorized, 1499 const EdgeInfo &UserTreeIdx, 1500 ArrayRef<unsigned> ReuseShuffleIndices = None, 1501 ArrayRef<unsigned> ReorderIndices = None) { 1502 VectorizableTree.push_back(llvm::make_unique<TreeEntry>(VectorizableTree)); 1503 TreeEntry *Last = VectorizableTree.back().get(); 1504 Last->Idx = VectorizableTree.size() - 1; 1505 Last->Scalars.insert(Last->Scalars.begin(), VL.begin(), VL.end()); 1506 Last->NeedToGather = !Vectorized; 1507 Last->ReuseShuffleIndices.append(ReuseShuffleIndices.begin(), 1508 ReuseShuffleIndices.end()); 1509 Last->ReorderIndices = ReorderIndices; 1510 if (Vectorized) { 1511 for (int i = 0, e = VL.size(); i != e; ++i) { 1512 assert(!getTreeEntry(VL[i]) && "Scalar already in tree!"); 1513 ScalarToTreeEntry[VL[i]] = Last->Idx; 1514 } 1515 } else { 1516 MustGather.insert(VL.begin(), VL.end()); 1517 } 1518 1519 if (UserTreeIdx.UserTE) 1520 Last->UserTreeIndices.push_back(UserTreeIdx); 1521 1522 Last->trySetUserTEOperand(UserTreeIdx, VL, ReuseShuffleIndices); 1523 return Last; 1524 } 1525 1526 /// -- Vectorization State -- 1527 /// Holds all of the tree entries. 1528 TreeEntry::VecTreeTy VectorizableTree; 1529 1530 #ifndef NDEBUG 1531 /// Debug printer. 1532 LLVM_DUMP_METHOD void dumpVectorizableTree() const { 1533 for (unsigned Id = 0, IdE = VectorizableTree.size(); Id != IdE; ++Id) { 1534 VectorizableTree[Id]->dump(); 1535 dbgs() << "\n"; 1536 } 1537 } 1538 #endif 1539 1540 TreeEntry *getTreeEntry(Value *V) { 1541 auto I = ScalarToTreeEntry.find(V); 1542 if (I != ScalarToTreeEntry.end()) 1543 return VectorizableTree[I->second].get(); 1544 return nullptr; 1545 } 1546 1547 const TreeEntry *getTreeEntry(Value *V) const { 1548 auto I = ScalarToTreeEntry.find(V); 1549 if (I != ScalarToTreeEntry.end()) 1550 return VectorizableTree[I->second].get(); 1551 return nullptr; 1552 } 1553 1554 /// Maps a specific scalar to its tree entry. 1555 SmallDenseMap<Value*, int> ScalarToTreeEntry; 1556 1557 /// A list of scalars that we found that we need to keep as scalars. 1558 ValueSet MustGather; 1559 1560 /// This POD struct describes one external user in the vectorized tree. 1561 struct ExternalUser { 1562 ExternalUser(Value *S, llvm::User *U, int L) 1563 : Scalar(S), User(U), Lane(L) {} 1564 1565 // Which scalar in our function. 1566 Value *Scalar; 1567 1568 // Which user that uses the scalar. 1569 llvm::User *User; 1570 1571 // Which lane does the scalar belong to. 1572 int Lane; 1573 }; 1574 using UserList = SmallVector<ExternalUser, 16>; 1575 1576 /// Checks if two instructions may access the same memory. 1577 /// 1578 /// \p Loc1 is the location of \p Inst1. It is passed explicitly because it 1579 /// is invariant in the calling loop. 1580 bool isAliased(const MemoryLocation &Loc1, Instruction *Inst1, 1581 Instruction *Inst2) { 1582 // First check if the result is already in the cache. 1583 AliasCacheKey key = std::make_pair(Inst1, Inst2); 1584 Optional<bool> &result = AliasCache[key]; 1585 if (result.hasValue()) { 1586 return result.getValue(); 1587 } 1588 MemoryLocation Loc2 = getLocation(Inst2, AA); 1589 bool aliased = true; 1590 if (Loc1.Ptr && Loc2.Ptr && isSimple(Inst1) && isSimple(Inst2)) { 1591 // Do the alias check. 1592 aliased = AA->alias(Loc1, Loc2); 1593 } 1594 // Store the result in the cache. 1595 result = aliased; 1596 return aliased; 1597 } 1598 1599 using AliasCacheKey = std::pair<Instruction *, Instruction *>; 1600 1601 /// Cache for alias results. 1602 /// TODO: consider moving this to the AliasAnalysis itself. 1603 DenseMap<AliasCacheKey, Optional<bool>> AliasCache; 1604 1605 /// Removes an instruction from its block and eventually deletes it. 1606 /// It's like Instruction::eraseFromParent() except that the actual deletion 1607 /// is delayed until BoUpSLP is destructed. 1608 /// This is required to ensure that there are no incorrect collisions in the 1609 /// AliasCache, which can happen if a new instruction is allocated at the 1610 /// same address as a previously deleted instruction. 1611 void eraseInstruction(Instruction *I) { 1612 I->removeFromParent(); 1613 I->dropAllReferences(); 1614 DeletedInstructions.emplace_back(I); 1615 } 1616 1617 /// Temporary store for deleted instructions. Instructions will be deleted 1618 /// eventually when the BoUpSLP is destructed. 1619 SmallVector<unique_value, 8> DeletedInstructions; 1620 1621 /// A list of values that need to extracted out of the tree. 1622 /// This list holds pairs of (Internal Scalar : External User). External User 1623 /// can be nullptr, it means that this Internal Scalar will be used later, 1624 /// after vectorization. 1625 UserList ExternalUses; 1626 1627 /// Values used only by @llvm.assume calls. 1628 SmallPtrSet<const Value *, 32> EphValues; 1629 1630 /// Holds all of the instructions that we gathered. 1631 SetVector<Instruction *> GatherSeq; 1632 1633 /// A list of blocks that we are going to CSE. 1634 SetVector<BasicBlock *> CSEBlocks; 1635 1636 /// Contains all scheduling relevant data for an instruction. 1637 /// A ScheduleData either represents a single instruction or a member of an 1638 /// instruction bundle (= a group of instructions which is combined into a 1639 /// vector instruction). 1640 struct ScheduleData { 1641 // The initial value for the dependency counters. It means that the 1642 // dependencies are not calculated yet. 1643 enum { InvalidDeps = -1 }; 1644 1645 ScheduleData() = default; 1646 1647 void init(int BlockSchedulingRegionID, Value *OpVal) { 1648 FirstInBundle = this; 1649 NextInBundle = nullptr; 1650 NextLoadStore = nullptr; 1651 IsScheduled = false; 1652 SchedulingRegionID = BlockSchedulingRegionID; 1653 UnscheduledDepsInBundle = UnscheduledDeps; 1654 clearDependencies(); 1655 OpValue = OpVal; 1656 } 1657 1658 /// Returns true if the dependency information has been calculated. 1659 bool hasValidDependencies() const { return Dependencies != InvalidDeps; } 1660 1661 /// Returns true for single instructions and for bundle representatives 1662 /// (= the head of a bundle). 1663 bool isSchedulingEntity() const { return FirstInBundle == this; } 1664 1665 /// Returns true if it represents an instruction bundle and not only a 1666 /// single instruction. 1667 bool isPartOfBundle() const { 1668 return NextInBundle != nullptr || FirstInBundle != this; 1669 } 1670 1671 /// Returns true if it is ready for scheduling, i.e. it has no more 1672 /// unscheduled depending instructions/bundles. 1673 bool isReady() const { 1674 assert(isSchedulingEntity() && 1675 "can't consider non-scheduling entity for ready list"); 1676 return UnscheduledDepsInBundle == 0 && !IsScheduled; 1677 } 1678 1679 /// Modifies the number of unscheduled dependencies, also updating it for 1680 /// the whole bundle. 1681 int incrementUnscheduledDeps(int Incr) { 1682 UnscheduledDeps += Incr; 1683 return FirstInBundle->UnscheduledDepsInBundle += Incr; 1684 } 1685 1686 /// Sets the number of unscheduled dependencies to the number of 1687 /// dependencies. 1688 void resetUnscheduledDeps() { 1689 incrementUnscheduledDeps(Dependencies - UnscheduledDeps); 1690 } 1691 1692 /// Clears all dependency information. 1693 void clearDependencies() { 1694 Dependencies = InvalidDeps; 1695 resetUnscheduledDeps(); 1696 MemoryDependencies.clear(); 1697 } 1698 1699 void dump(raw_ostream &os) const { 1700 if (!isSchedulingEntity()) { 1701 os << "/ " << *Inst; 1702 } else if (NextInBundle) { 1703 os << '[' << *Inst; 1704 ScheduleData *SD = NextInBundle; 1705 while (SD) { 1706 os << ';' << *SD->Inst; 1707 SD = SD->NextInBundle; 1708 } 1709 os << ']'; 1710 } else { 1711 os << *Inst; 1712 } 1713 } 1714 1715 Instruction *Inst = nullptr; 1716 1717 /// Points to the head in an instruction bundle (and always to this for 1718 /// single instructions). 1719 ScheduleData *FirstInBundle = nullptr; 1720 1721 /// Single linked list of all instructions in a bundle. Null if it is a 1722 /// single instruction. 1723 ScheduleData *NextInBundle = nullptr; 1724 1725 /// Single linked list of all memory instructions (e.g. load, store, call) 1726 /// in the block - until the end of the scheduling region. 1727 ScheduleData *NextLoadStore = nullptr; 1728 1729 /// The dependent memory instructions. 1730 /// This list is derived on demand in calculateDependencies(). 1731 SmallVector<ScheduleData *, 4> MemoryDependencies; 1732 1733 /// This ScheduleData is in the current scheduling region if this matches 1734 /// the current SchedulingRegionID of BlockScheduling. 1735 int SchedulingRegionID = 0; 1736 1737 /// Used for getting a "good" final ordering of instructions. 1738 int SchedulingPriority = 0; 1739 1740 /// The number of dependencies. Constitutes of the number of users of the 1741 /// instruction plus the number of dependent memory instructions (if any). 1742 /// This value is calculated on demand. 1743 /// If InvalidDeps, the number of dependencies is not calculated yet. 1744 int Dependencies = InvalidDeps; 1745 1746 /// The number of dependencies minus the number of dependencies of scheduled 1747 /// instructions. As soon as this is zero, the instruction/bundle gets ready 1748 /// for scheduling. 1749 /// Note that this is negative as long as Dependencies is not calculated. 1750 int UnscheduledDeps = InvalidDeps; 1751 1752 /// The sum of UnscheduledDeps in a bundle. Equals to UnscheduledDeps for 1753 /// single instructions. 1754 int UnscheduledDepsInBundle = InvalidDeps; 1755 1756 /// True if this instruction is scheduled (or considered as scheduled in the 1757 /// dry-run). 1758 bool IsScheduled = false; 1759 1760 /// Opcode of the current instruction in the schedule data. 1761 Value *OpValue = nullptr; 1762 }; 1763 1764 #ifndef NDEBUG 1765 friend inline raw_ostream &operator<<(raw_ostream &os, 1766 const BoUpSLP::ScheduleData &SD) { 1767 SD.dump(os); 1768 return os; 1769 } 1770 #endif 1771 1772 friend struct GraphTraits<BoUpSLP *>; 1773 friend struct DOTGraphTraits<BoUpSLP *>; 1774 1775 /// Contains all scheduling data for a basic block. 1776 struct BlockScheduling { 1777 BlockScheduling(BasicBlock *BB) 1778 : BB(BB), ChunkSize(BB->size()), ChunkPos(ChunkSize) {} 1779 1780 void clear() { 1781 ReadyInsts.clear(); 1782 ScheduleStart = nullptr; 1783 ScheduleEnd = nullptr; 1784 FirstLoadStoreInRegion = nullptr; 1785 LastLoadStoreInRegion = nullptr; 1786 1787 // Reduce the maximum schedule region size by the size of the 1788 // previous scheduling run. 1789 ScheduleRegionSizeLimit -= ScheduleRegionSize; 1790 if (ScheduleRegionSizeLimit < MinScheduleRegionSize) 1791 ScheduleRegionSizeLimit = MinScheduleRegionSize; 1792 ScheduleRegionSize = 0; 1793 1794 // Make a new scheduling region, i.e. all existing ScheduleData is not 1795 // in the new region yet. 1796 ++SchedulingRegionID; 1797 } 1798 1799 ScheduleData *getScheduleData(Value *V) { 1800 ScheduleData *SD = ScheduleDataMap[V]; 1801 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 1802 return SD; 1803 return nullptr; 1804 } 1805 1806 ScheduleData *getScheduleData(Value *V, Value *Key) { 1807 if (V == Key) 1808 return getScheduleData(V); 1809 auto I = ExtraScheduleDataMap.find(V); 1810 if (I != ExtraScheduleDataMap.end()) { 1811 ScheduleData *SD = I->second[Key]; 1812 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 1813 return SD; 1814 } 1815 return nullptr; 1816 } 1817 1818 bool isInSchedulingRegion(ScheduleData *SD) { 1819 return SD->SchedulingRegionID == SchedulingRegionID; 1820 } 1821 1822 /// Marks an instruction as scheduled and puts all dependent ready 1823 /// instructions into the ready-list. 1824 template <typename ReadyListType> 1825 void schedule(ScheduleData *SD, ReadyListType &ReadyList) { 1826 SD->IsScheduled = true; 1827 LLVM_DEBUG(dbgs() << "SLP: schedule " << *SD << "\n"); 1828 1829 ScheduleData *BundleMember = SD; 1830 while (BundleMember) { 1831 if (BundleMember->Inst != BundleMember->OpValue) { 1832 BundleMember = BundleMember->NextInBundle; 1833 continue; 1834 } 1835 // Handle the def-use chain dependencies. 1836 for (Use &U : BundleMember->Inst->operands()) { 1837 auto *I = dyn_cast<Instruction>(U.get()); 1838 if (!I) 1839 continue; 1840 doForAllOpcodes(I, [&ReadyList](ScheduleData *OpDef) { 1841 if (OpDef && OpDef->hasValidDependencies() && 1842 OpDef->incrementUnscheduledDeps(-1) == 0) { 1843 // There are no more unscheduled dependencies after 1844 // decrementing, so we can put the dependent instruction 1845 // into the ready list. 1846 ScheduleData *DepBundle = OpDef->FirstInBundle; 1847 assert(!DepBundle->IsScheduled && 1848 "already scheduled bundle gets ready"); 1849 ReadyList.insert(DepBundle); 1850 LLVM_DEBUG(dbgs() 1851 << "SLP: gets ready (def): " << *DepBundle << "\n"); 1852 } 1853 }); 1854 } 1855 // Handle the memory dependencies. 1856 for (ScheduleData *MemoryDepSD : BundleMember->MemoryDependencies) { 1857 if (MemoryDepSD->incrementUnscheduledDeps(-1) == 0) { 1858 // There are no more unscheduled dependencies after decrementing, 1859 // so we can put the dependent instruction into the ready list. 1860 ScheduleData *DepBundle = MemoryDepSD->FirstInBundle; 1861 assert(!DepBundle->IsScheduled && 1862 "already scheduled bundle gets ready"); 1863 ReadyList.insert(DepBundle); 1864 LLVM_DEBUG(dbgs() 1865 << "SLP: gets ready (mem): " << *DepBundle << "\n"); 1866 } 1867 } 1868 BundleMember = BundleMember->NextInBundle; 1869 } 1870 } 1871 1872 void doForAllOpcodes(Value *V, 1873 function_ref<void(ScheduleData *SD)> Action) { 1874 if (ScheduleData *SD = getScheduleData(V)) 1875 Action(SD); 1876 auto I = ExtraScheduleDataMap.find(V); 1877 if (I != ExtraScheduleDataMap.end()) 1878 for (auto &P : I->second) 1879 if (P.second->SchedulingRegionID == SchedulingRegionID) 1880 Action(P.second); 1881 } 1882 1883 /// Put all instructions into the ReadyList which are ready for scheduling. 1884 template <typename ReadyListType> 1885 void initialFillReadyList(ReadyListType &ReadyList) { 1886 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 1887 doForAllOpcodes(I, [&](ScheduleData *SD) { 1888 if (SD->isSchedulingEntity() && SD->isReady()) { 1889 ReadyList.insert(SD); 1890 LLVM_DEBUG(dbgs() 1891 << "SLP: initially in ready list: " << *I << "\n"); 1892 } 1893 }); 1894 } 1895 } 1896 1897 /// Checks if a bundle of instructions can be scheduled, i.e. has no 1898 /// cyclic dependencies. This is only a dry-run, no instructions are 1899 /// actually moved at this stage. 1900 bool tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 1901 const InstructionsState &S); 1902 1903 /// Un-bundles a group of instructions. 1904 void cancelScheduling(ArrayRef<Value *> VL, Value *OpValue); 1905 1906 /// Allocates schedule data chunk. 1907 ScheduleData *allocateScheduleDataChunks(); 1908 1909 /// Extends the scheduling region so that V is inside the region. 1910 /// \returns true if the region size is within the limit. 1911 bool extendSchedulingRegion(Value *V, const InstructionsState &S); 1912 1913 /// Initialize the ScheduleData structures for new instructions in the 1914 /// scheduling region. 1915 void initScheduleData(Instruction *FromI, Instruction *ToI, 1916 ScheduleData *PrevLoadStore, 1917 ScheduleData *NextLoadStore); 1918 1919 /// Updates the dependency information of a bundle and of all instructions/ 1920 /// bundles which depend on the original bundle. 1921 void calculateDependencies(ScheduleData *SD, bool InsertInReadyList, 1922 BoUpSLP *SLP); 1923 1924 /// Sets all instruction in the scheduling region to un-scheduled. 1925 void resetSchedule(); 1926 1927 BasicBlock *BB; 1928 1929 /// Simple memory allocation for ScheduleData. 1930 std::vector<std::unique_ptr<ScheduleData[]>> ScheduleDataChunks; 1931 1932 /// The size of a ScheduleData array in ScheduleDataChunks. 1933 int ChunkSize; 1934 1935 /// The allocator position in the current chunk, which is the last entry 1936 /// of ScheduleDataChunks. 1937 int ChunkPos; 1938 1939 /// Attaches ScheduleData to Instruction. 1940 /// Note that the mapping survives during all vectorization iterations, i.e. 1941 /// ScheduleData structures are recycled. 1942 DenseMap<Value *, ScheduleData *> ScheduleDataMap; 1943 1944 /// Attaches ScheduleData to Instruction with the leading key. 1945 DenseMap<Value *, SmallDenseMap<Value *, ScheduleData *>> 1946 ExtraScheduleDataMap; 1947 1948 struct ReadyList : SmallVector<ScheduleData *, 8> { 1949 void insert(ScheduleData *SD) { push_back(SD); } 1950 }; 1951 1952 /// The ready-list for scheduling (only used for the dry-run). 1953 ReadyList ReadyInsts; 1954 1955 /// The first instruction of the scheduling region. 1956 Instruction *ScheduleStart = nullptr; 1957 1958 /// The first instruction _after_ the scheduling region. 1959 Instruction *ScheduleEnd = nullptr; 1960 1961 /// The first memory accessing instruction in the scheduling region 1962 /// (can be null). 1963 ScheduleData *FirstLoadStoreInRegion = nullptr; 1964 1965 /// The last memory accessing instruction in the scheduling region 1966 /// (can be null). 1967 ScheduleData *LastLoadStoreInRegion = nullptr; 1968 1969 /// The current size of the scheduling region. 1970 int ScheduleRegionSize = 0; 1971 1972 /// The maximum size allowed for the scheduling region. 1973 int ScheduleRegionSizeLimit = ScheduleRegionSizeBudget; 1974 1975 /// The ID of the scheduling region. For a new vectorization iteration this 1976 /// is incremented which "removes" all ScheduleData from the region. 1977 // Make sure that the initial SchedulingRegionID is greater than the 1978 // initial SchedulingRegionID in ScheduleData (which is 0). 1979 int SchedulingRegionID = 1; 1980 }; 1981 1982 /// Attaches the BlockScheduling structures to basic blocks. 1983 MapVector<BasicBlock *, std::unique_ptr<BlockScheduling>> BlocksSchedules; 1984 1985 /// Performs the "real" scheduling. Done before vectorization is actually 1986 /// performed in a basic block. 1987 void scheduleBlock(BlockScheduling *BS); 1988 1989 /// List of users to ignore during scheduling and that don't need extracting. 1990 ArrayRef<Value *> UserIgnoreList; 1991 1992 using OrdersType = SmallVector<unsigned, 4>; 1993 /// A DenseMapInfo implementation for holding DenseMaps and DenseSets of 1994 /// sorted SmallVectors of unsigned. 1995 struct OrdersTypeDenseMapInfo { 1996 static OrdersType getEmptyKey() { 1997 OrdersType V; 1998 V.push_back(~1U); 1999 return V; 2000 } 2001 2002 static OrdersType getTombstoneKey() { 2003 OrdersType V; 2004 V.push_back(~2U); 2005 return V; 2006 } 2007 2008 static unsigned getHashValue(const OrdersType &V) { 2009 return static_cast<unsigned>(hash_combine_range(V.begin(), V.end())); 2010 } 2011 2012 static bool isEqual(const OrdersType &LHS, const OrdersType &RHS) { 2013 return LHS == RHS; 2014 } 2015 }; 2016 2017 /// Contains orders of operations along with the number of bundles that have 2018 /// operations in this order. It stores only those orders that require 2019 /// reordering, if reordering is not required it is counted using \a 2020 /// NumOpsWantToKeepOriginalOrder. 2021 DenseMap<OrdersType, unsigned, OrdersTypeDenseMapInfo> NumOpsWantToKeepOrder; 2022 /// Number of bundles that do not require reordering. 2023 unsigned NumOpsWantToKeepOriginalOrder = 0; 2024 2025 // Analysis and block reference. 2026 Function *F; 2027 ScalarEvolution *SE; 2028 TargetTransformInfo *TTI; 2029 TargetLibraryInfo *TLI; 2030 AliasAnalysis *AA; 2031 LoopInfo *LI; 2032 DominatorTree *DT; 2033 AssumptionCache *AC; 2034 DemandedBits *DB; 2035 const DataLayout *DL; 2036 OptimizationRemarkEmitter *ORE; 2037 2038 unsigned MaxVecRegSize; // This is set by TTI or overridden by cl::opt. 2039 unsigned MinVecRegSize; // Set by cl::opt (default: 128). 2040 2041 /// Instruction builder to construct the vectorized tree. 2042 IRBuilder<> Builder; 2043 2044 /// A map of scalar integer values to the smallest bit width with which they 2045 /// can legally be represented. The values map to (width, signed) pairs, 2046 /// where "width" indicates the minimum bit width and "signed" is True if the 2047 /// value must be signed-extended, rather than zero-extended, back to its 2048 /// original width. 2049 MapVector<Value *, std::pair<uint64_t, bool>> MinBWs; 2050 }; 2051 2052 } // end namespace slpvectorizer 2053 2054 template <> struct GraphTraits<BoUpSLP *> { 2055 using TreeEntry = BoUpSLP::TreeEntry; 2056 2057 /// NodeRef has to be a pointer per the GraphWriter. 2058 using NodeRef = TreeEntry *; 2059 2060 using ContainerTy = BoUpSLP::TreeEntry::VecTreeTy; 2061 2062 /// Add the VectorizableTree to the index iterator to be able to return 2063 /// TreeEntry pointers. 2064 struct ChildIteratorType 2065 : public iterator_adaptor_base< 2066 ChildIteratorType, SmallVector<BoUpSLP::EdgeInfo, 1>::iterator> { 2067 ContainerTy &VectorizableTree; 2068 2069 ChildIteratorType(SmallVector<BoUpSLP::EdgeInfo, 1>::iterator W, 2070 ContainerTy &VT) 2071 : ChildIteratorType::iterator_adaptor_base(W), VectorizableTree(VT) {} 2072 2073 NodeRef operator*() { return I->UserTE; } 2074 }; 2075 2076 static NodeRef getEntryNode(BoUpSLP &R) { 2077 return R.VectorizableTree[0].get(); 2078 } 2079 2080 static ChildIteratorType child_begin(NodeRef N) { 2081 return {N->UserTreeIndices.begin(), N->Container}; 2082 } 2083 2084 static ChildIteratorType child_end(NodeRef N) { 2085 return {N->UserTreeIndices.end(), N->Container}; 2086 } 2087 2088 /// For the node iterator we just need to turn the TreeEntry iterator into a 2089 /// TreeEntry* iterator so that it dereferences to NodeRef. 2090 class nodes_iterator { 2091 using ItTy = ContainerTy::iterator; 2092 ItTy It; 2093 2094 public: 2095 nodes_iterator(const ItTy &It2) : It(It2) {} 2096 NodeRef operator*() { return It->get(); } 2097 nodes_iterator operator++() { 2098 ++It; 2099 return *this; 2100 } 2101 bool operator!=(const nodes_iterator &N2) const { return N2.It != It; } 2102 }; 2103 2104 static nodes_iterator nodes_begin(BoUpSLP *R) { 2105 return nodes_iterator(R->VectorizableTree.begin()); 2106 } 2107 2108 static nodes_iterator nodes_end(BoUpSLP *R) { 2109 return nodes_iterator(R->VectorizableTree.end()); 2110 } 2111 2112 static unsigned size(BoUpSLP *R) { return R->VectorizableTree.size(); } 2113 }; 2114 2115 template <> struct DOTGraphTraits<BoUpSLP *> : public DefaultDOTGraphTraits { 2116 using TreeEntry = BoUpSLP::TreeEntry; 2117 2118 DOTGraphTraits(bool isSimple = false) : DefaultDOTGraphTraits(isSimple) {} 2119 2120 std::string getNodeLabel(const TreeEntry *Entry, const BoUpSLP *R) { 2121 std::string Str; 2122 raw_string_ostream OS(Str); 2123 if (isSplat(Entry->Scalars)) { 2124 OS << "<splat> " << *Entry->Scalars[0]; 2125 return Str; 2126 } 2127 for (auto V : Entry->Scalars) { 2128 OS << *V; 2129 if (std::any_of( 2130 R->ExternalUses.begin(), R->ExternalUses.end(), 2131 [&](const BoUpSLP::ExternalUser &EU) { return EU.Scalar == V; })) 2132 OS << " <extract>"; 2133 OS << "\n"; 2134 } 2135 return Str; 2136 } 2137 2138 static std::string getNodeAttributes(const TreeEntry *Entry, 2139 const BoUpSLP *) { 2140 if (Entry->NeedToGather) 2141 return "color=red"; 2142 return ""; 2143 } 2144 }; 2145 2146 } // end namespace llvm 2147 2148 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2149 ArrayRef<Value *> UserIgnoreLst) { 2150 ExtraValueToDebugLocsMap ExternallyUsedValues; 2151 buildTree(Roots, ExternallyUsedValues, UserIgnoreLst); 2152 } 2153 2154 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2155 ExtraValueToDebugLocsMap &ExternallyUsedValues, 2156 ArrayRef<Value *> UserIgnoreLst) { 2157 deleteTree(); 2158 UserIgnoreList = UserIgnoreLst; 2159 if (!allSameType(Roots)) 2160 return; 2161 buildTree_rec(Roots, 0, EdgeInfo()); 2162 2163 // Collect the values that we need to extract from the tree. 2164 for (auto &TEPtr : VectorizableTree) { 2165 TreeEntry *Entry = TEPtr.get(); 2166 2167 // No need to handle users of gathered values. 2168 if (Entry->NeedToGather) 2169 continue; 2170 2171 // For each lane: 2172 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 2173 Value *Scalar = Entry->Scalars[Lane]; 2174 int FoundLane = Lane; 2175 if (!Entry->ReuseShuffleIndices.empty()) { 2176 FoundLane = 2177 std::distance(Entry->ReuseShuffleIndices.begin(), 2178 llvm::find(Entry->ReuseShuffleIndices, FoundLane)); 2179 } 2180 2181 // Check if the scalar is externally used as an extra arg. 2182 auto ExtI = ExternallyUsedValues.find(Scalar); 2183 if (ExtI != ExternallyUsedValues.end()) { 2184 LLVM_DEBUG(dbgs() << "SLP: Need to extract: Extra arg from lane " 2185 << Lane << " from " << *Scalar << ".\n"); 2186 ExternalUses.emplace_back(Scalar, nullptr, FoundLane); 2187 } 2188 for (User *U : Scalar->users()) { 2189 LLVM_DEBUG(dbgs() << "SLP: Checking user:" << *U << ".\n"); 2190 2191 Instruction *UserInst = dyn_cast<Instruction>(U); 2192 if (!UserInst) 2193 continue; 2194 2195 // Skip in-tree scalars that become vectors 2196 if (TreeEntry *UseEntry = getTreeEntry(U)) { 2197 Value *UseScalar = UseEntry->Scalars[0]; 2198 // Some in-tree scalars will remain as scalar in vectorized 2199 // instructions. If that is the case, the one in Lane 0 will 2200 // be used. 2201 if (UseScalar != U || 2202 !InTreeUserNeedToExtract(Scalar, UserInst, TLI)) { 2203 LLVM_DEBUG(dbgs() << "SLP: \tInternal user will be removed:" << *U 2204 << ".\n"); 2205 assert(!UseEntry->NeedToGather && "Bad state"); 2206 continue; 2207 } 2208 } 2209 2210 // Ignore users in the user ignore list. 2211 if (is_contained(UserIgnoreList, UserInst)) 2212 continue; 2213 2214 LLVM_DEBUG(dbgs() << "SLP: Need to extract:" << *U << " from lane " 2215 << Lane << " from " << *Scalar << ".\n"); 2216 ExternalUses.push_back(ExternalUser(Scalar, U, FoundLane)); 2217 } 2218 } 2219 } 2220 } 2221 2222 void BoUpSLP::buildTree_rec(ArrayRef<Value *> VL, unsigned Depth, 2223 const EdgeInfo &UserTreeIdx) { 2224 assert((allConstant(VL) || allSameType(VL)) && "Invalid types!"); 2225 2226 InstructionsState S = getSameOpcode(VL); 2227 if (Depth == RecursionMaxDepth) { 2228 LLVM_DEBUG(dbgs() << "SLP: Gathering due to max recursion depth.\n"); 2229 newTreeEntry(VL, false, UserTreeIdx); 2230 return; 2231 } 2232 2233 // Don't handle vectors. 2234 if (S.OpValue->getType()->isVectorTy()) { 2235 LLVM_DEBUG(dbgs() << "SLP: Gathering due to vector type.\n"); 2236 newTreeEntry(VL, false, UserTreeIdx); 2237 return; 2238 } 2239 2240 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) 2241 if (SI->getValueOperand()->getType()->isVectorTy()) { 2242 LLVM_DEBUG(dbgs() << "SLP: Gathering due to store vector type.\n"); 2243 newTreeEntry(VL, false, UserTreeIdx); 2244 return; 2245 } 2246 2247 // If all of the operands are identical or constant we have a simple solution. 2248 if (allConstant(VL) || isSplat(VL) || !allSameBlock(VL) || !S.getOpcode()) { 2249 LLVM_DEBUG(dbgs() << "SLP: Gathering due to C,S,B,O. \n"); 2250 newTreeEntry(VL, false, UserTreeIdx); 2251 return; 2252 } 2253 2254 // We now know that this is a vector of instructions of the same type from 2255 // the same block. 2256 2257 // Don't vectorize ephemeral values. 2258 for (unsigned i = 0, e = VL.size(); i != e; ++i) { 2259 if (EphValues.count(VL[i])) { 2260 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *VL[i] 2261 << ") is ephemeral.\n"); 2262 newTreeEntry(VL, false, UserTreeIdx); 2263 return; 2264 } 2265 } 2266 2267 // Check if this is a duplicate of another entry. 2268 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 2269 LLVM_DEBUG(dbgs() << "SLP: \tChecking bundle: " << *S.OpValue << ".\n"); 2270 if (!E->isSame(VL)) { 2271 LLVM_DEBUG(dbgs() << "SLP: Gathering due to partial overlap.\n"); 2272 newTreeEntry(VL, false, UserTreeIdx); 2273 return; 2274 } 2275 // Record the reuse of the tree node. FIXME, currently this is only used to 2276 // properly draw the graph rather than for the actual vectorization. 2277 E->UserTreeIndices.push_back(UserTreeIdx); 2278 LLVM_DEBUG(dbgs() << "SLP: Perfect diamond merge at " << *S.OpValue 2279 << ".\n"); 2280 E->trySetUserTEOperand(UserTreeIdx, VL, None); 2281 return; 2282 } 2283 2284 // Check that none of the instructions in the bundle are already in the tree. 2285 for (unsigned i = 0, e = VL.size(); i != e; ++i) { 2286 auto *I = dyn_cast<Instruction>(VL[i]); 2287 if (!I) 2288 continue; 2289 if (getTreeEntry(I)) { 2290 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *VL[i] 2291 << ") is already in tree.\n"); 2292 newTreeEntry(VL, false, UserTreeIdx); 2293 return; 2294 } 2295 } 2296 2297 // If any of the scalars is marked as a value that needs to stay scalar, then 2298 // we need to gather the scalars. 2299 // The reduction nodes (stored in UserIgnoreList) also should stay scalar. 2300 for (unsigned i = 0, e = VL.size(); i != e; ++i) { 2301 if (MustGather.count(VL[i]) || is_contained(UserIgnoreList, VL[i])) { 2302 LLVM_DEBUG(dbgs() << "SLP: Gathering due to gathered scalar.\n"); 2303 newTreeEntry(VL, false, UserTreeIdx); 2304 return; 2305 } 2306 } 2307 2308 // Check that all of the users of the scalars that we want to vectorize are 2309 // schedulable. 2310 auto *VL0 = cast<Instruction>(S.OpValue); 2311 BasicBlock *BB = VL0->getParent(); 2312 2313 if (!DT->isReachableFromEntry(BB)) { 2314 // Don't go into unreachable blocks. They may contain instructions with 2315 // dependency cycles which confuse the final scheduling. 2316 LLVM_DEBUG(dbgs() << "SLP: bundle in unreachable block.\n"); 2317 newTreeEntry(VL, false, UserTreeIdx); 2318 return; 2319 } 2320 2321 // Check that every instruction appears once in this bundle. 2322 SmallVector<unsigned, 4> ReuseShuffleIndicies; 2323 SmallVector<Value *, 4> UniqueValues; 2324 DenseMap<Value *, unsigned> UniquePositions; 2325 for (Value *V : VL) { 2326 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 2327 ReuseShuffleIndicies.emplace_back(Res.first->second); 2328 if (Res.second) 2329 UniqueValues.emplace_back(V); 2330 } 2331 if (UniqueValues.size() == VL.size()) { 2332 ReuseShuffleIndicies.clear(); 2333 } else { 2334 LLVM_DEBUG(dbgs() << "SLP: Shuffle for reused scalars.\n"); 2335 if (UniqueValues.size() <= 1 || !llvm::isPowerOf2_32(UniqueValues.size())) { 2336 LLVM_DEBUG(dbgs() << "SLP: Scalar used twice in bundle.\n"); 2337 newTreeEntry(VL, false, UserTreeIdx); 2338 return; 2339 } 2340 VL = UniqueValues; 2341 } 2342 2343 auto &BSRef = BlocksSchedules[BB]; 2344 if (!BSRef) 2345 BSRef = llvm::make_unique<BlockScheduling>(BB); 2346 2347 BlockScheduling &BS = *BSRef.get(); 2348 2349 if (!BS.tryScheduleBundle(VL, this, S)) { 2350 LLVM_DEBUG(dbgs() << "SLP: We are not able to schedule this bundle!\n"); 2351 assert((!BS.getScheduleData(VL0) || 2352 !BS.getScheduleData(VL0)->isPartOfBundle()) && 2353 "tryScheduleBundle should cancelScheduling on failure"); 2354 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 2355 return; 2356 } 2357 LLVM_DEBUG(dbgs() << "SLP: We are able to schedule this bundle.\n"); 2358 2359 unsigned ShuffleOrOp = S.isAltShuffle() ? 2360 (unsigned) Instruction::ShuffleVector : S.getOpcode(); 2361 switch (ShuffleOrOp) { 2362 case Instruction::PHI: { 2363 PHINode *PH = dyn_cast<PHINode>(VL0); 2364 2365 // Check for terminator values (e.g. invoke). 2366 for (unsigned j = 0; j < VL.size(); ++j) 2367 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 2368 Instruction *Term = dyn_cast<Instruction>( 2369 cast<PHINode>(VL[j])->getIncomingValueForBlock( 2370 PH->getIncomingBlock(i))); 2371 if (Term && Term->isTerminator()) { 2372 LLVM_DEBUG(dbgs() 2373 << "SLP: Need to swizzle PHINodes (terminator use).\n"); 2374 BS.cancelScheduling(VL, VL0); 2375 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 2376 return; 2377 } 2378 } 2379 2380 auto *TE = newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies); 2381 LLVM_DEBUG(dbgs() << "SLP: added a vector of PHINodes.\n"); 2382 2383 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 2384 ValueList Operands; 2385 // Prepare the operand vector. 2386 for (Value *j : VL) 2387 Operands.push_back(cast<PHINode>(j)->getIncomingValueForBlock( 2388 PH->getIncomingBlock(i))); 2389 2390 buildTree_rec(Operands, Depth + 1, {TE, i}); 2391 } 2392 return; 2393 } 2394 case Instruction::ExtractValue: 2395 case Instruction::ExtractElement: { 2396 OrdersType CurrentOrder; 2397 bool Reuse = canReuseExtract(VL, VL0, CurrentOrder); 2398 if (Reuse) { 2399 LLVM_DEBUG(dbgs() << "SLP: Reusing or shuffling extract sequence.\n"); 2400 ++NumOpsWantToKeepOriginalOrder; 2401 newTreeEntry(VL, /*Vectorized=*/true, UserTreeIdx, 2402 ReuseShuffleIndicies); 2403 // This is a special case, as it does not gather, but at the same time 2404 // we are not extending buildTree_rec() towards the operands. 2405 ValueList Op0; 2406 Op0.assign(VL.size(), VL0->getOperand(0)); 2407 VectorizableTree.back()->setOperand(0, Op0, ReuseShuffleIndicies); 2408 return; 2409 } 2410 if (!CurrentOrder.empty()) { 2411 LLVM_DEBUG({ 2412 dbgs() << "SLP: Reusing or shuffling of reordered extract sequence " 2413 "with order"; 2414 for (unsigned Idx : CurrentOrder) 2415 dbgs() << " " << Idx; 2416 dbgs() << "\n"; 2417 }); 2418 // Insert new order with initial value 0, if it does not exist, 2419 // otherwise return the iterator to the existing one. 2420 auto StoredCurrentOrderAndNum = 2421 NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first; 2422 ++StoredCurrentOrderAndNum->getSecond(); 2423 newTreeEntry(VL, /*Vectorized=*/true, UserTreeIdx, ReuseShuffleIndicies, 2424 StoredCurrentOrderAndNum->getFirst()); 2425 // This is a special case, as it does not gather, but at the same time 2426 // we are not extending buildTree_rec() towards the operands. 2427 ValueList Op0; 2428 Op0.assign(VL.size(), VL0->getOperand(0)); 2429 VectorizableTree.back()->setOperand(0, Op0, ReuseShuffleIndicies); 2430 return; 2431 } 2432 LLVM_DEBUG(dbgs() << "SLP: Gather extract sequence.\n"); 2433 newTreeEntry(VL, /*Vectorized=*/false, UserTreeIdx, ReuseShuffleIndicies); 2434 BS.cancelScheduling(VL, VL0); 2435 return; 2436 } 2437 case Instruction::Load: { 2438 // Check that a vectorized load would load the same memory as a scalar 2439 // load. For example, we don't want to vectorize loads that are smaller 2440 // than 8-bit. Even though we have a packed struct {<i2, i2, i2, i2>} LLVM 2441 // treats loading/storing it as an i8 struct. If we vectorize loads/stores 2442 // from such a struct, we read/write packed bits disagreeing with the 2443 // unvectorized version. 2444 Type *ScalarTy = VL0->getType(); 2445 2446 if (DL->getTypeSizeInBits(ScalarTy) != 2447 DL->getTypeAllocSizeInBits(ScalarTy)) { 2448 BS.cancelScheduling(VL, VL0); 2449 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 2450 LLVM_DEBUG(dbgs() << "SLP: Gathering loads of non-packed type.\n"); 2451 return; 2452 } 2453 2454 // Make sure all loads in the bundle are simple - we can't vectorize 2455 // atomic or volatile loads. 2456 SmallVector<Value *, 4> PointerOps(VL.size()); 2457 auto POIter = PointerOps.begin(); 2458 for (Value *V : VL) { 2459 auto *L = cast<LoadInst>(V); 2460 if (!L->isSimple()) { 2461 BS.cancelScheduling(VL, VL0); 2462 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 2463 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple loads.\n"); 2464 return; 2465 } 2466 *POIter = L->getPointerOperand(); 2467 ++POIter; 2468 } 2469 2470 OrdersType CurrentOrder; 2471 // Check the order of pointer operands. 2472 if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) { 2473 Value *Ptr0; 2474 Value *PtrN; 2475 if (CurrentOrder.empty()) { 2476 Ptr0 = PointerOps.front(); 2477 PtrN = PointerOps.back(); 2478 } else { 2479 Ptr0 = PointerOps[CurrentOrder.front()]; 2480 PtrN = PointerOps[CurrentOrder.back()]; 2481 } 2482 const SCEV *Scev0 = SE->getSCEV(Ptr0); 2483 const SCEV *ScevN = SE->getSCEV(PtrN); 2484 const auto *Diff = 2485 dyn_cast<SCEVConstant>(SE->getMinusSCEV(ScevN, Scev0)); 2486 uint64_t Size = DL->getTypeAllocSize(ScalarTy); 2487 // Check that the sorted loads are consecutive. 2488 if (Diff && Diff->getAPInt().getZExtValue() == (VL.size() - 1) * Size) { 2489 if (CurrentOrder.empty()) { 2490 // Original loads are consecutive and does not require reordering. 2491 ++NumOpsWantToKeepOriginalOrder; 2492 newTreeEntry(VL, /*Vectorized=*/true, UserTreeIdx, 2493 ReuseShuffleIndicies); 2494 LLVM_DEBUG(dbgs() << "SLP: added a vector of loads.\n"); 2495 } else { 2496 // Need to reorder. 2497 auto I = NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first; 2498 ++I->getSecond(); 2499 newTreeEntry(VL, /*Vectorized=*/true, UserTreeIdx, 2500 ReuseShuffleIndicies, I->getFirst()); 2501 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled loads.\n"); 2502 } 2503 return; 2504 } 2505 } 2506 2507 LLVM_DEBUG(dbgs() << "SLP: Gathering non-consecutive loads.\n"); 2508 BS.cancelScheduling(VL, VL0); 2509 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 2510 return; 2511 } 2512 case Instruction::ZExt: 2513 case Instruction::SExt: 2514 case Instruction::FPToUI: 2515 case Instruction::FPToSI: 2516 case Instruction::FPExt: 2517 case Instruction::PtrToInt: 2518 case Instruction::IntToPtr: 2519 case Instruction::SIToFP: 2520 case Instruction::UIToFP: 2521 case Instruction::Trunc: 2522 case Instruction::FPTrunc: 2523 case Instruction::BitCast: { 2524 Type *SrcTy = VL0->getOperand(0)->getType(); 2525 for (unsigned i = 0; i < VL.size(); ++i) { 2526 Type *Ty = cast<Instruction>(VL[i])->getOperand(0)->getType(); 2527 if (Ty != SrcTy || !isValidElementType(Ty)) { 2528 BS.cancelScheduling(VL, VL0); 2529 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 2530 LLVM_DEBUG(dbgs() 2531 << "SLP: Gathering casts with different src types.\n"); 2532 return; 2533 } 2534 } 2535 auto *TE = newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies); 2536 LLVM_DEBUG(dbgs() << "SLP: added a vector of casts.\n"); 2537 2538 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 2539 ValueList Operands; 2540 // Prepare the operand vector. 2541 for (Value *j : VL) 2542 Operands.push_back(cast<Instruction>(j)->getOperand(i)); 2543 2544 buildTree_rec(Operands, Depth + 1, {TE, i}); 2545 } 2546 return; 2547 } 2548 case Instruction::ICmp: 2549 case Instruction::FCmp: { 2550 // Check that all of the compares have the same predicate. 2551 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 2552 CmpInst::Predicate SwapP0 = CmpInst::getSwappedPredicate(P0); 2553 Type *ComparedTy = VL0->getOperand(0)->getType(); 2554 for (unsigned i = 1, e = VL.size(); i < e; ++i) { 2555 CmpInst *Cmp = cast<CmpInst>(VL[i]); 2556 if ((Cmp->getPredicate() != P0 && Cmp->getPredicate() != SwapP0) || 2557 Cmp->getOperand(0)->getType() != ComparedTy) { 2558 BS.cancelScheduling(VL, VL0); 2559 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 2560 LLVM_DEBUG(dbgs() 2561 << "SLP: Gathering cmp with different predicate.\n"); 2562 return; 2563 } 2564 } 2565 2566 auto *TE = newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies); 2567 LLVM_DEBUG(dbgs() << "SLP: added a vector of compares.\n"); 2568 2569 ValueList Left, Right; 2570 if (cast<CmpInst>(VL0)->isCommutative()) { 2571 // Commutative predicate - collect + sort operands of the instructions 2572 // so that each side is more likely to have the same opcode. 2573 assert(P0 == SwapP0 && "Commutative Predicate mismatch"); 2574 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 2575 } else { 2576 // Collect operands - commute if it uses the swapped predicate. 2577 for (Value *V : VL) { 2578 auto *Cmp = cast<CmpInst>(V); 2579 Value *LHS = Cmp->getOperand(0); 2580 Value *RHS = Cmp->getOperand(1); 2581 if (Cmp->getPredicate() != P0) 2582 std::swap(LHS, RHS); 2583 Left.push_back(LHS); 2584 Right.push_back(RHS); 2585 } 2586 } 2587 2588 buildTree_rec(Left, Depth + 1, {TE, 0}); 2589 buildTree_rec(Right, Depth + 1, {TE, 1}); 2590 return; 2591 } 2592 case Instruction::Select: 2593 case Instruction::FNeg: 2594 case Instruction::Add: 2595 case Instruction::FAdd: 2596 case Instruction::Sub: 2597 case Instruction::FSub: 2598 case Instruction::Mul: 2599 case Instruction::FMul: 2600 case Instruction::UDiv: 2601 case Instruction::SDiv: 2602 case Instruction::FDiv: 2603 case Instruction::URem: 2604 case Instruction::SRem: 2605 case Instruction::FRem: 2606 case Instruction::Shl: 2607 case Instruction::LShr: 2608 case Instruction::AShr: 2609 case Instruction::And: 2610 case Instruction::Or: 2611 case Instruction::Xor: { 2612 auto *TE = newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies); 2613 LLVM_DEBUG(dbgs() << "SLP: added a vector of un/bin op.\n"); 2614 2615 // Sort operands of the instructions so that each side is more likely to 2616 // have the same opcode. 2617 if (isa<BinaryOperator>(VL0) && VL0->isCommutative()) { 2618 ValueList Left, Right; 2619 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 2620 buildTree_rec(Left, Depth + 1, {TE, 0}); 2621 buildTree_rec(Right, Depth + 1, {TE, 1}); 2622 return; 2623 } 2624 2625 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 2626 ValueList Operands; 2627 // Prepare the operand vector. 2628 for (Value *j : VL) 2629 Operands.push_back(cast<Instruction>(j)->getOperand(i)); 2630 2631 buildTree_rec(Operands, Depth + 1, {TE, i}); 2632 } 2633 return; 2634 } 2635 case Instruction::GetElementPtr: { 2636 // We don't combine GEPs with complicated (nested) indexing. 2637 for (unsigned j = 0; j < VL.size(); ++j) { 2638 if (cast<Instruction>(VL[j])->getNumOperands() != 2) { 2639 LLVM_DEBUG(dbgs() << "SLP: not-vectorizable GEP (nested indexes).\n"); 2640 BS.cancelScheduling(VL, VL0); 2641 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 2642 return; 2643 } 2644 } 2645 2646 // We can't combine several GEPs into one vector if they operate on 2647 // different types. 2648 Type *Ty0 = VL0->getOperand(0)->getType(); 2649 for (unsigned j = 0; j < VL.size(); ++j) { 2650 Type *CurTy = cast<Instruction>(VL[j])->getOperand(0)->getType(); 2651 if (Ty0 != CurTy) { 2652 LLVM_DEBUG(dbgs() 2653 << "SLP: not-vectorizable GEP (different types).\n"); 2654 BS.cancelScheduling(VL, VL0); 2655 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 2656 return; 2657 } 2658 } 2659 2660 // We don't combine GEPs with non-constant indexes. 2661 for (unsigned j = 0; j < VL.size(); ++j) { 2662 auto Op = cast<Instruction>(VL[j])->getOperand(1); 2663 if (!isa<ConstantInt>(Op)) { 2664 LLVM_DEBUG(dbgs() 2665 << "SLP: not-vectorizable GEP (non-constant indexes).\n"); 2666 BS.cancelScheduling(VL, VL0); 2667 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 2668 return; 2669 } 2670 } 2671 2672 auto *TE = newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies); 2673 LLVM_DEBUG(dbgs() << "SLP: added a vector of GEPs.\n"); 2674 for (unsigned i = 0, e = 2; i < e; ++i) { 2675 ValueList Operands; 2676 // Prepare the operand vector. 2677 for (Value *j : VL) 2678 Operands.push_back(cast<Instruction>(j)->getOperand(i)); 2679 2680 buildTree_rec(Operands, Depth + 1, {TE, i}); 2681 } 2682 return; 2683 } 2684 case Instruction::Store: { 2685 // Check if the stores are consecutive or of we need to swizzle them. 2686 for (unsigned i = 0, e = VL.size() - 1; i < e; ++i) 2687 if (!isConsecutiveAccess(VL[i], VL[i + 1], *DL, *SE)) { 2688 BS.cancelScheduling(VL, VL0); 2689 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 2690 LLVM_DEBUG(dbgs() << "SLP: Non-consecutive store.\n"); 2691 return; 2692 } 2693 2694 auto *TE = newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies); 2695 LLVM_DEBUG(dbgs() << "SLP: added a vector of stores.\n"); 2696 2697 ValueList Operands; 2698 for (Value *j : VL) 2699 Operands.push_back(cast<Instruction>(j)->getOperand(0)); 2700 2701 buildTree_rec(Operands, Depth + 1, {TE, 0}); 2702 return; 2703 } 2704 case Instruction::Call: { 2705 // Check if the calls are all to the same vectorizable intrinsic. 2706 CallInst *CI = cast<CallInst>(VL0); 2707 // Check if this is an Intrinsic call or something that can be 2708 // represented by an intrinsic call 2709 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 2710 if (!isTriviallyVectorizable(ID)) { 2711 BS.cancelScheduling(VL, VL0); 2712 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 2713 LLVM_DEBUG(dbgs() << "SLP: Non-vectorizable call.\n"); 2714 return; 2715 } 2716 Function *Int = CI->getCalledFunction(); 2717 unsigned NumArgs = CI->getNumArgOperands(); 2718 SmallVector<Value*, 4> ScalarArgs(NumArgs, nullptr); 2719 for (unsigned j = 0; j != NumArgs; ++j) 2720 if (hasVectorInstrinsicScalarOpd(ID, j)) 2721 ScalarArgs[j] = CI->getArgOperand(j); 2722 for (unsigned i = 1, e = VL.size(); i != e; ++i) { 2723 CallInst *CI2 = dyn_cast<CallInst>(VL[i]); 2724 if (!CI2 || CI2->getCalledFunction() != Int || 2725 getVectorIntrinsicIDForCall(CI2, TLI) != ID || 2726 !CI->hasIdenticalOperandBundleSchema(*CI2)) { 2727 BS.cancelScheduling(VL, VL0); 2728 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 2729 LLVM_DEBUG(dbgs() << "SLP: mismatched calls:" << *CI << "!=" << *VL[i] 2730 << "\n"); 2731 return; 2732 } 2733 // Some intrinsics have scalar arguments and should be same in order for 2734 // them to be vectorized. 2735 for (unsigned j = 0; j != NumArgs; ++j) { 2736 if (hasVectorInstrinsicScalarOpd(ID, j)) { 2737 Value *A1J = CI2->getArgOperand(j); 2738 if (ScalarArgs[j] != A1J) { 2739 BS.cancelScheduling(VL, VL0); 2740 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 2741 LLVM_DEBUG(dbgs() << "SLP: mismatched arguments in call:" << *CI 2742 << " argument " << ScalarArgs[j] << "!=" << A1J 2743 << "\n"); 2744 return; 2745 } 2746 } 2747 } 2748 // Verify that the bundle operands are identical between the two calls. 2749 if (CI->hasOperandBundles() && 2750 !std::equal(CI->op_begin() + CI->getBundleOperandsStartIndex(), 2751 CI->op_begin() + CI->getBundleOperandsEndIndex(), 2752 CI2->op_begin() + CI2->getBundleOperandsStartIndex())) { 2753 BS.cancelScheduling(VL, VL0); 2754 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 2755 LLVM_DEBUG(dbgs() << "SLP: mismatched bundle operands in calls:" 2756 << *CI << "!=" << *VL[i] << '\n'); 2757 return; 2758 } 2759 } 2760 2761 auto *TE = newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies); 2762 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 2763 ValueList Operands; 2764 // Prepare the operand vector. 2765 for (Value *j : VL) { 2766 CallInst *CI2 = dyn_cast<CallInst>(j); 2767 Operands.push_back(CI2->getArgOperand(i)); 2768 } 2769 buildTree_rec(Operands, Depth + 1, {TE, i}); 2770 } 2771 return; 2772 } 2773 case Instruction::ShuffleVector: { 2774 // If this is not an alternate sequence of opcode like add-sub 2775 // then do not vectorize this instruction. 2776 if (!S.isAltShuffle()) { 2777 BS.cancelScheduling(VL, VL0); 2778 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 2779 LLVM_DEBUG(dbgs() << "SLP: ShuffleVector are not vectorized.\n"); 2780 return; 2781 } 2782 auto *TE = newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies); 2783 LLVM_DEBUG(dbgs() << "SLP: added a ShuffleVector op.\n"); 2784 2785 // Reorder operands if reordering would enable vectorization. 2786 if (isa<BinaryOperator>(VL0)) { 2787 ValueList Left, Right; 2788 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 2789 buildTree_rec(Left, Depth + 1, {TE, 0}); 2790 buildTree_rec(Right, Depth + 1, {TE, 1}); 2791 return; 2792 } 2793 2794 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 2795 ValueList Operands; 2796 // Prepare the operand vector. 2797 for (Value *j : VL) 2798 Operands.push_back(cast<Instruction>(j)->getOperand(i)); 2799 2800 buildTree_rec(Operands, Depth + 1, {TE, i}); 2801 } 2802 return; 2803 } 2804 default: 2805 BS.cancelScheduling(VL, VL0); 2806 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 2807 LLVM_DEBUG(dbgs() << "SLP: Gathering unknown instruction.\n"); 2808 return; 2809 } 2810 } 2811 2812 unsigned BoUpSLP::canMapToVector(Type *T, const DataLayout &DL) const { 2813 unsigned N; 2814 Type *EltTy; 2815 auto *ST = dyn_cast<StructType>(T); 2816 if (ST) { 2817 N = ST->getNumElements(); 2818 EltTy = *ST->element_begin(); 2819 } else { 2820 N = cast<ArrayType>(T)->getNumElements(); 2821 EltTy = cast<ArrayType>(T)->getElementType(); 2822 } 2823 if (!isValidElementType(EltTy)) 2824 return 0; 2825 uint64_t VTSize = DL.getTypeStoreSizeInBits(VectorType::get(EltTy, N)); 2826 if (VTSize < MinVecRegSize || VTSize > MaxVecRegSize || VTSize != DL.getTypeStoreSizeInBits(T)) 2827 return 0; 2828 if (ST) { 2829 // Check that struct is homogeneous. 2830 for (const auto *Ty : ST->elements()) 2831 if (Ty != EltTy) 2832 return 0; 2833 } 2834 return N; 2835 } 2836 2837 bool BoUpSLP::canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 2838 SmallVectorImpl<unsigned> &CurrentOrder) const { 2839 Instruction *E0 = cast<Instruction>(OpValue); 2840 assert(E0->getOpcode() == Instruction::ExtractElement || 2841 E0->getOpcode() == Instruction::ExtractValue); 2842 assert(E0->getOpcode() == getSameOpcode(VL).getOpcode() && "Invalid opcode"); 2843 // Check if all of the extracts come from the same vector and from the 2844 // correct offset. 2845 Value *Vec = E0->getOperand(0); 2846 2847 CurrentOrder.clear(); 2848 2849 // We have to extract from a vector/aggregate with the same number of elements. 2850 unsigned NElts; 2851 if (E0->getOpcode() == Instruction::ExtractValue) { 2852 const DataLayout &DL = E0->getModule()->getDataLayout(); 2853 NElts = canMapToVector(Vec->getType(), DL); 2854 if (!NElts) 2855 return false; 2856 // Check if load can be rewritten as load of vector. 2857 LoadInst *LI = dyn_cast<LoadInst>(Vec); 2858 if (!LI || !LI->isSimple() || !LI->hasNUses(VL.size())) 2859 return false; 2860 } else { 2861 NElts = Vec->getType()->getVectorNumElements(); 2862 } 2863 2864 if (NElts != VL.size()) 2865 return false; 2866 2867 // Check that all of the indices extract from the correct offset. 2868 bool ShouldKeepOrder = true; 2869 unsigned E = VL.size(); 2870 // Assign to all items the initial value E + 1 so we can check if the extract 2871 // instruction index was used already. 2872 // Also, later we can check that all the indices are used and we have a 2873 // consecutive access in the extract instructions, by checking that no 2874 // element of CurrentOrder still has value E + 1. 2875 CurrentOrder.assign(E, E + 1); 2876 unsigned I = 0; 2877 for (; I < E; ++I) { 2878 auto *Inst = cast<Instruction>(VL[I]); 2879 if (Inst->getOperand(0) != Vec) 2880 break; 2881 Optional<unsigned> Idx = getExtractIndex(Inst); 2882 if (!Idx) 2883 break; 2884 const unsigned ExtIdx = *Idx; 2885 if (ExtIdx != I) { 2886 if (ExtIdx >= E || CurrentOrder[ExtIdx] != E + 1) 2887 break; 2888 ShouldKeepOrder = false; 2889 CurrentOrder[ExtIdx] = I; 2890 } else { 2891 if (CurrentOrder[I] != E + 1) 2892 break; 2893 CurrentOrder[I] = I; 2894 } 2895 } 2896 if (I < E) { 2897 CurrentOrder.clear(); 2898 return false; 2899 } 2900 2901 return ShouldKeepOrder; 2902 } 2903 2904 bool BoUpSLP::areAllUsersVectorized(Instruction *I) const { 2905 return I->hasOneUse() || 2906 std::all_of(I->user_begin(), I->user_end(), [this](User *U) { 2907 return ScalarToTreeEntry.count(U) > 0; 2908 }); 2909 } 2910 2911 int BoUpSLP::getEntryCost(TreeEntry *E) { 2912 ArrayRef<Value*> VL = E->Scalars; 2913 2914 Type *ScalarTy = VL[0]->getType(); 2915 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 2916 ScalarTy = SI->getValueOperand()->getType(); 2917 else if (CmpInst *CI = dyn_cast<CmpInst>(VL[0])) 2918 ScalarTy = CI->getOperand(0)->getType(); 2919 VectorType *VecTy = VectorType::get(ScalarTy, VL.size()); 2920 2921 // If we have computed a smaller type for the expression, update VecTy so 2922 // that the costs will be accurate. 2923 if (MinBWs.count(VL[0])) 2924 VecTy = VectorType::get( 2925 IntegerType::get(F->getContext(), MinBWs[VL[0]].first), VL.size()); 2926 2927 unsigned ReuseShuffleNumbers = E->ReuseShuffleIndices.size(); 2928 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 2929 int ReuseShuffleCost = 0; 2930 if (NeedToShuffleReuses) { 2931 ReuseShuffleCost = 2932 TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 2933 } 2934 if (E->NeedToGather) { 2935 if (allConstant(VL)) 2936 return 0; 2937 if (isSplat(VL)) { 2938 return ReuseShuffleCost + 2939 TTI->getShuffleCost(TargetTransformInfo::SK_Broadcast, VecTy, 0); 2940 } 2941 if (getSameOpcode(VL).getOpcode() == Instruction::ExtractElement && 2942 allSameType(VL) && allSameBlock(VL)) { 2943 Optional<TargetTransformInfo::ShuffleKind> ShuffleKind = isShuffle(VL); 2944 if (ShuffleKind.hasValue()) { 2945 int Cost = TTI->getShuffleCost(ShuffleKind.getValue(), VecTy); 2946 for (auto *V : VL) { 2947 // If all users of instruction are going to be vectorized and this 2948 // instruction itself is not going to be vectorized, consider this 2949 // instruction as dead and remove its cost from the final cost of the 2950 // vectorized tree. 2951 if (areAllUsersVectorized(cast<Instruction>(V)) && 2952 !ScalarToTreeEntry.count(V)) { 2953 auto *IO = cast<ConstantInt>( 2954 cast<ExtractElementInst>(V)->getIndexOperand()); 2955 Cost -= TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, 2956 IO->getZExtValue()); 2957 } 2958 } 2959 return ReuseShuffleCost + Cost; 2960 } 2961 } 2962 return ReuseShuffleCost + getGatherCost(VL); 2963 } 2964 InstructionsState S = getSameOpcode(VL); 2965 assert(S.getOpcode() && allSameType(VL) && allSameBlock(VL) && "Invalid VL"); 2966 Instruction *VL0 = cast<Instruction>(S.OpValue); 2967 unsigned ShuffleOrOp = S.isAltShuffle() ? 2968 (unsigned) Instruction::ShuffleVector : S.getOpcode(); 2969 switch (ShuffleOrOp) { 2970 case Instruction::PHI: 2971 return 0; 2972 2973 case Instruction::ExtractValue: 2974 case Instruction::ExtractElement: 2975 if (NeedToShuffleReuses) { 2976 unsigned Idx = 0; 2977 for (unsigned I : E->ReuseShuffleIndices) { 2978 if (ShuffleOrOp == Instruction::ExtractElement) { 2979 auto *IO = cast<ConstantInt>( 2980 cast<ExtractElementInst>(VL[I])->getIndexOperand()); 2981 Idx = IO->getZExtValue(); 2982 ReuseShuffleCost -= TTI->getVectorInstrCost( 2983 Instruction::ExtractElement, VecTy, Idx); 2984 } else { 2985 ReuseShuffleCost -= TTI->getVectorInstrCost( 2986 Instruction::ExtractElement, VecTy, Idx); 2987 ++Idx; 2988 } 2989 } 2990 Idx = ReuseShuffleNumbers; 2991 for (Value *V : VL) { 2992 if (ShuffleOrOp == Instruction::ExtractElement) { 2993 auto *IO = cast<ConstantInt>( 2994 cast<ExtractElementInst>(V)->getIndexOperand()); 2995 Idx = IO->getZExtValue(); 2996 } else { 2997 --Idx; 2998 } 2999 ReuseShuffleCost += 3000 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, Idx); 3001 } 3002 } 3003 if (!E->NeedToGather) { 3004 int DeadCost = ReuseShuffleCost; 3005 if (!E->ReorderIndices.empty()) { 3006 // TODO: Merge this shuffle with the ReuseShuffleCost. 3007 DeadCost += TTI->getShuffleCost( 3008 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3009 } 3010 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 3011 Instruction *E = cast<Instruction>(VL[i]); 3012 // If all users are going to be vectorized, instruction can be 3013 // considered as dead. 3014 // The same, if have only one user, it will be vectorized for sure. 3015 if (areAllUsersVectorized(E)) { 3016 // Take credit for instruction that will become dead. 3017 if (E->hasOneUse()) { 3018 Instruction *Ext = E->user_back(); 3019 if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) && 3020 all_of(Ext->users(), 3021 [](User *U) { return isa<GetElementPtrInst>(U); })) { 3022 // Use getExtractWithExtendCost() to calculate the cost of 3023 // extractelement/ext pair. 3024 DeadCost -= TTI->getExtractWithExtendCost( 3025 Ext->getOpcode(), Ext->getType(), VecTy, i); 3026 // Add back the cost of s|zext which is subtracted separately. 3027 DeadCost += TTI->getCastInstrCost( 3028 Ext->getOpcode(), Ext->getType(), E->getType(), Ext); 3029 continue; 3030 } 3031 } 3032 DeadCost -= 3033 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, i); 3034 } 3035 } 3036 return DeadCost; 3037 } 3038 return ReuseShuffleCost + getGatherCost(VL); 3039 3040 case Instruction::ZExt: 3041 case Instruction::SExt: 3042 case Instruction::FPToUI: 3043 case Instruction::FPToSI: 3044 case Instruction::FPExt: 3045 case Instruction::PtrToInt: 3046 case Instruction::IntToPtr: 3047 case Instruction::SIToFP: 3048 case Instruction::UIToFP: 3049 case Instruction::Trunc: 3050 case Instruction::FPTrunc: 3051 case Instruction::BitCast: { 3052 Type *SrcTy = VL0->getOperand(0)->getType(); 3053 int ScalarEltCost = 3054 TTI->getCastInstrCost(S.getOpcode(), ScalarTy, SrcTy, VL0); 3055 if (NeedToShuffleReuses) { 3056 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3057 } 3058 3059 // Calculate the cost of this instruction. 3060 int ScalarCost = VL.size() * ScalarEltCost; 3061 3062 VectorType *SrcVecTy = VectorType::get(SrcTy, VL.size()); 3063 int VecCost = 0; 3064 // Check if the values are candidates to demote. 3065 if (!MinBWs.count(VL0) || VecTy != SrcVecTy) { 3066 VecCost = ReuseShuffleCost + 3067 TTI->getCastInstrCost(S.getOpcode(), VecTy, SrcVecTy, VL0); 3068 } 3069 return VecCost - ScalarCost; 3070 } 3071 case Instruction::FCmp: 3072 case Instruction::ICmp: 3073 case Instruction::Select: { 3074 // Calculate the cost of this instruction. 3075 int ScalarEltCost = TTI->getCmpSelInstrCost(S.getOpcode(), ScalarTy, 3076 Builder.getInt1Ty(), VL0); 3077 if (NeedToShuffleReuses) { 3078 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3079 } 3080 VectorType *MaskTy = VectorType::get(Builder.getInt1Ty(), VL.size()); 3081 int ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3082 int VecCost = TTI->getCmpSelInstrCost(S.getOpcode(), VecTy, MaskTy, VL0); 3083 return ReuseShuffleCost + VecCost - ScalarCost; 3084 } 3085 case Instruction::FNeg: 3086 case Instruction::Add: 3087 case Instruction::FAdd: 3088 case Instruction::Sub: 3089 case Instruction::FSub: 3090 case Instruction::Mul: 3091 case Instruction::FMul: 3092 case Instruction::UDiv: 3093 case Instruction::SDiv: 3094 case Instruction::FDiv: 3095 case Instruction::URem: 3096 case Instruction::SRem: 3097 case Instruction::FRem: 3098 case Instruction::Shl: 3099 case Instruction::LShr: 3100 case Instruction::AShr: 3101 case Instruction::And: 3102 case Instruction::Or: 3103 case Instruction::Xor: { 3104 // Certain instructions can be cheaper to vectorize if they have a 3105 // constant second vector operand. 3106 TargetTransformInfo::OperandValueKind Op1VK = 3107 TargetTransformInfo::OK_AnyValue; 3108 TargetTransformInfo::OperandValueKind Op2VK = 3109 TargetTransformInfo::OK_UniformConstantValue; 3110 TargetTransformInfo::OperandValueProperties Op1VP = 3111 TargetTransformInfo::OP_None; 3112 TargetTransformInfo::OperandValueProperties Op2VP = 3113 TargetTransformInfo::OP_PowerOf2; 3114 3115 // If all operands are exactly the same ConstantInt then set the 3116 // operand kind to OK_UniformConstantValue. 3117 // If instead not all operands are constants, then set the operand kind 3118 // to OK_AnyValue. If all operands are constants but not the same, 3119 // then set the operand kind to OK_NonUniformConstantValue. 3120 ConstantInt *CInt0 = nullptr; 3121 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 3122 const Instruction *I = cast<Instruction>(VL[i]); 3123 unsigned OpIdx = isa<BinaryOperator>(I) ? 1 : 0; 3124 ConstantInt *CInt = dyn_cast<ConstantInt>(I->getOperand(OpIdx)); 3125 if (!CInt) { 3126 Op2VK = TargetTransformInfo::OK_AnyValue; 3127 Op2VP = TargetTransformInfo::OP_None; 3128 break; 3129 } 3130 if (Op2VP == TargetTransformInfo::OP_PowerOf2 && 3131 !CInt->getValue().isPowerOf2()) 3132 Op2VP = TargetTransformInfo::OP_None; 3133 if (i == 0) { 3134 CInt0 = CInt; 3135 continue; 3136 } 3137 if (CInt0 != CInt) 3138 Op2VK = TargetTransformInfo::OK_NonUniformConstantValue; 3139 } 3140 3141 SmallVector<const Value *, 4> Operands(VL0->operand_values()); 3142 int ScalarEltCost = TTI->getArithmeticInstrCost( 3143 S.getOpcode(), ScalarTy, Op1VK, Op2VK, Op1VP, Op2VP, Operands); 3144 if (NeedToShuffleReuses) { 3145 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3146 } 3147 int ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3148 int VecCost = TTI->getArithmeticInstrCost(S.getOpcode(), VecTy, Op1VK, 3149 Op2VK, Op1VP, Op2VP, Operands); 3150 return ReuseShuffleCost + VecCost - ScalarCost; 3151 } 3152 case Instruction::GetElementPtr: { 3153 TargetTransformInfo::OperandValueKind Op1VK = 3154 TargetTransformInfo::OK_AnyValue; 3155 TargetTransformInfo::OperandValueKind Op2VK = 3156 TargetTransformInfo::OK_UniformConstantValue; 3157 3158 int ScalarEltCost = 3159 TTI->getArithmeticInstrCost(Instruction::Add, ScalarTy, Op1VK, Op2VK); 3160 if (NeedToShuffleReuses) { 3161 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3162 } 3163 int ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3164 int VecCost = 3165 TTI->getArithmeticInstrCost(Instruction::Add, VecTy, Op1VK, Op2VK); 3166 return ReuseShuffleCost + VecCost - ScalarCost; 3167 } 3168 case Instruction::Load: { 3169 // Cost of wide load - cost of scalar loads. 3170 unsigned alignment = cast<LoadInst>(VL0)->getAlignment(); 3171 int ScalarEltCost = 3172 TTI->getMemoryOpCost(Instruction::Load, ScalarTy, alignment, 0, VL0); 3173 if (NeedToShuffleReuses) { 3174 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3175 } 3176 int ScalarLdCost = VecTy->getNumElements() * ScalarEltCost; 3177 int VecLdCost = 3178 TTI->getMemoryOpCost(Instruction::Load, VecTy, alignment, 0, VL0); 3179 if (!E->ReorderIndices.empty()) { 3180 // TODO: Merge this shuffle with the ReuseShuffleCost. 3181 VecLdCost += TTI->getShuffleCost( 3182 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3183 } 3184 return ReuseShuffleCost + VecLdCost - ScalarLdCost; 3185 } 3186 case Instruction::Store: { 3187 // We know that we can merge the stores. Calculate the cost. 3188 unsigned alignment = cast<StoreInst>(VL0)->getAlignment(); 3189 int ScalarEltCost = 3190 TTI->getMemoryOpCost(Instruction::Store, ScalarTy, alignment, 0, VL0); 3191 if (NeedToShuffleReuses) { 3192 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3193 } 3194 int ScalarStCost = VecTy->getNumElements() * ScalarEltCost; 3195 int VecStCost = 3196 TTI->getMemoryOpCost(Instruction::Store, VecTy, alignment, 0, VL0); 3197 return ReuseShuffleCost + VecStCost - ScalarStCost; 3198 } 3199 case Instruction::Call: { 3200 CallInst *CI = cast<CallInst>(VL0); 3201 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3202 3203 // Calculate the cost of the scalar and vector calls. 3204 SmallVector<Type *, 4> ScalarTys; 3205 for (unsigned op = 0, opc = CI->getNumArgOperands(); op != opc; ++op) 3206 ScalarTys.push_back(CI->getArgOperand(op)->getType()); 3207 3208 FastMathFlags FMF; 3209 if (auto *FPMO = dyn_cast<FPMathOperator>(CI)) 3210 FMF = FPMO->getFastMathFlags(); 3211 3212 int ScalarEltCost = 3213 TTI->getIntrinsicInstrCost(ID, ScalarTy, ScalarTys, FMF); 3214 if (NeedToShuffleReuses) { 3215 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3216 } 3217 int ScalarCallCost = VecTy->getNumElements() * ScalarEltCost; 3218 3219 SmallVector<Value *, 4> Args(CI->arg_operands()); 3220 int VecCallCost = TTI->getIntrinsicInstrCost(ID, CI->getType(), Args, FMF, 3221 VecTy->getNumElements()); 3222 3223 LLVM_DEBUG(dbgs() << "SLP: Call cost " << VecCallCost - ScalarCallCost 3224 << " (" << VecCallCost << "-" << ScalarCallCost << ")" 3225 << " for " << *CI << "\n"); 3226 3227 return ReuseShuffleCost + VecCallCost - ScalarCallCost; 3228 } 3229 case Instruction::ShuffleVector: { 3230 assert(S.isAltShuffle() && 3231 ((Instruction::isBinaryOp(S.getOpcode()) && 3232 Instruction::isBinaryOp(S.getAltOpcode())) || 3233 (Instruction::isCast(S.getOpcode()) && 3234 Instruction::isCast(S.getAltOpcode()))) && 3235 "Invalid Shuffle Vector Operand"); 3236 int ScalarCost = 0; 3237 if (NeedToShuffleReuses) { 3238 for (unsigned Idx : E->ReuseShuffleIndices) { 3239 Instruction *I = cast<Instruction>(VL[Idx]); 3240 ReuseShuffleCost -= TTI->getInstructionCost( 3241 I, TargetTransformInfo::TCK_RecipThroughput); 3242 } 3243 for (Value *V : VL) { 3244 Instruction *I = cast<Instruction>(V); 3245 ReuseShuffleCost += TTI->getInstructionCost( 3246 I, TargetTransformInfo::TCK_RecipThroughput); 3247 } 3248 } 3249 for (Value *i : VL) { 3250 Instruction *I = cast<Instruction>(i); 3251 assert(S.isOpcodeOrAlt(I) && "Unexpected main/alternate opcode"); 3252 ScalarCost += TTI->getInstructionCost( 3253 I, TargetTransformInfo::TCK_RecipThroughput); 3254 } 3255 // VecCost is equal to sum of the cost of creating 2 vectors 3256 // and the cost of creating shuffle. 3257 int VecCost = 0; 3258 if (Instruction::isBinaryOp(S.getOpcode())) { 3259 VecCost = TTI->getArithmeticInstrCost(S.getOpcode(), VecTy); 3260 VecCost += TTI->getArithmeticInstrCost(S.getAltOpcode(), VecTy); 3261 } else { 3262 Type *Src0SclTy = S.MainOp->getOperand(0)->getType(); 3263 Type *Src1SclTy = S.AltOp->getOperand(0)->getType(); 3264 VectorType *Src0Ty = VectorType::get(Src0SclTy, VL.size()); 3265 VectorType *Src1Ty = VectorType::get(Src1SclTy, VL.size()); 3266 VecCost = TTI->getCastInstrCost(S.getOpcode(), VecTy, Src0Ty); 3267 VecCost += TTI->getCastInstrCost(S.getAltOpcode(), VecTy, Src1Ty); 3268 } 3269 VecCost += TTI->getShuffleCost(TargetTransformInfo::SK_Select, VecTy, 0); 3270 return ReuseShuffleCost + VecCost - ScalarCost; 3271 } 3272 default: 3273 llvm_unreachable("Unknown instruction"); 3274 } 3275 } 3276 3277 bool BoUpSLP::isFullyVectorizableTinyTree() const { 3278 LLVM_DEBUG(dbgs() << "SLP: Check whether the tree with height " 3279 << VectorizableTree.size() << " is fully vectorizable .\n"); 3280 3281 // We only handle trees of heights 1 and 2. 3282 if (VectorizableTree.size() == 1 && !VectorizableTree[0]->NeedToGather) 3283 return true; 3284 3285 if (VectorizableTree.size() != 2) 3286 return false; 3287 3288 // Handle splat and all-constants stores. 3289 if (!VectorizableTree[0]->NeedToGather && 3290 (allConstant(VectorizableTree[1]->Scalars) || 3291 isSplat(VectorizableTree[1]->Scalars))) 3292 return true; 3293 3294 // Gathering cost would be too much for tiny trees. 3295 if (VectorizableTree[0]->NeedToGather || VectorizableTree[1]->NeedToGather) 3296 return false; 3297 3298 return true; 3299 } 3300 3301 bool BoUpSLP::isTreeTinyAndNotFullyVectorizable() const { 3302 // We can vectorize the tree if its size is greater than or equal to the 3303 // minimum size specified by the MinTreeSize command line option. 3304 if (VectorizableTree.size() >= MinTreeSize) 3305 return false; 3306 3307 // If we have a tiny tree (a tree whose size is less than MinTreeSize), we 3308 // can vectorize it if we can prove it fully vectorizable. 3309 if (isFullyVectorizableTinyTree()) 3310 return false; 3311 3312 assert(VectorizableTree.empty() 3313 ? ExternalUses.empty() 3314 : true && "We shouldn't have any external users"); 3315 3316 // Otherwise, we can't vectorize the tree. It is both tiny and not fully 3317 // vectorizable. 3318 return true; 3319 } 3320 3321 int BoUpSLP::getSpillCost() const { 3322 // Walk from the bottom of the tree to the top, tracking which values are 3323 // live. When we see a call instruction that is not part of our tree, 3324 // query TTI to see if there is a cost to keeping values live over it 3325 // (for example, if spills and fills are required). 3326 unsigned BundleWidth = VectorizableTree.front()->Scalars.size(); 3327 int Cost = 0; 3328 3329 SmallPtrSet<Instruction*, 4> LiveValues; 3330 Instruction *PrevInst = nullptr; 3331 3332 for (const auto &TEPtr : VectorizableTree) { 3333 Instruction *Inst = dyn_cast<Instruction>(TEPtr->Scalars[0]); 3334 if (!Inst) 3335 continue; 3336 3337 if (!PrevInst) { 3338 PrevInst = Inst; 3339 continue; 3340 } 3341 3342 // Update LiveValues. 3343 LiveValues.erase(PrevInst); 3344 for (auto &J : PrevInst->operands()) { 3345 if (isa<Instruction>(&*J) && getTreeEntry(&*J)) 3346 LiveValues.insert(cast<Instruction>(&*J)); 3347 } 3348 3349 LLVM_DEBUG({ 3350 dbgs() << "SLP: #LV: " << LiveValues.size(); 3351 for (auto *X : LiveValues) 3352 dbgs() << " " << X->getName(); 3353 dbgs() << ", Looking at "; 3354 Inst->dump(); 3355 }); 3356 3357 // Now find the sequence of instructions between PrevInst and Inst. 3358 unsigned NumCalls = 0; 3359 BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(), 3360 PrevInstIt = 3361 PrevInst->getIterator().getReverse(); 3362 while (InstIt != PrevInstIt) { 3363 if (PrevInstIt == PrevInst->getParent()->rend()) { 3364 PrevInstIt = Inst->getParent()->rbegin(); 3365 continue; 3366 } 3367 3368 // Debug informations don't impact spill cost. 3369 if ((isa<CallInst>(&*PrevInstIt) && 3370 !isa<DbgInfoIntrinsic>(&*PrevInstIt)) && 3371 &*PrevInstIt != PrevInst) 3372 NumCalls++; 3373 3374 ++PrevInstIt; 3375 } 3376 3377 if (NumCalls) { 3378 SmallVector<Type*, 4> V; 3379 for (auto *II : LiveValues) 3380 V.push_back(VectorType::get(II->getType(), BundleWidth)); 3381 Cost += NumCalls * TTI->getCostOfKeepingLiveOverCall(V); 3382 } 3383 3384 PrevInst = Inst; 3385 } 3386 3387 return Cost; 3388 } 3389 3390 int BoUpSLP::getTreeCost() { 3391 int Cost = 0; 3392 LLVM_DEBUG(dbgs() << "SLP: Calculating cost for tree of size " 3393 << VectorizableTree.size() << ".\n"); 3394 3395 unsigned BundleWidth = VectorizableTree[0]->Scalars.size(); 3396 3397 for (unsigned I = 0, E = VectorizableTree.size(); I < E; ++I) { 3398 TreeEntry &TE = *VectorizableTree[I].get(); 3399 3400 // We create duplicate tree entries for gather sequences that have multiple 3401 // uses. However, we should not compute the cost of duplicate sequences. 3402 // For example, if we have a build vector (i.e., insertelement sequence) 3403 // that is used by more than one vector instruction, we only need to 3404 // compute the cost of the insertelement instructions once. The redundant 3405 // instructions will be eliminated by CSE. 3406 // 3407 // We should consider not creating duplicate tree entries for gather 3408 // sequences, and instead add additional edges to the tree representing 3409 // their uses. Since such an approach results in fewer total entries, 3410 // existing heuristics based on tree size may yield different results. 3411 // 3412 if (TE.NeedToGather && 3413 std::any_of( 3414 std::next(VectorizableTree.begin(), I + 1), VectorizableTree.end(), 3415 [TE](const std::unique_ptr<TreeEntry> &EntryPtr) { 3416 return EntryPtr->NeedToGather && EntryPtr->isSame(TE.Scalars); 3417 })) 3418 continue; 3419 3420 int C = getEntryCost(&TE); 3421 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C 3422 << " for bundle that starts with " << *TE.Scalars[0] 3423 << ".\n"); 3424 Cost += C; 3425 } 3426 3427 SmallPtrSet<Value *, 16> ExtractCostCalculated; 3428 int ExtractCost = 0; 3429 for (ExternalUser &EU : ExternalUses) { 3430 // We only add extract cost once for the same scalar. 3431 if (!ExtractCostCalculated.insert(EU.Scalar).second) 3432 continue; 3433 3434 // Uses by ephemeral values are free (because the ephemeral value will be 3435 // removed prior to code generation, and so the extraction will be 3436 // removed as well). 3437 if (EphValues.count(EU.User)) 3438 continue; 3439 3440 // If we plan to rewrite the tree in a smaller type, we will need to sign 3441 // extend the extracted value back to the original type. Here, we account 3442 // for the extract and the added cost of the sign extend if needed. 3443 auto *VecTy = VectorType::get(EU.Scalar->getType(), BundleWidth); 3444 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 3445 if (MinBWs.count(ScalarRoot)) { 3446 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 3447 auto Extend = 3448 MinBWs[ScalarRoot].second ? Instruction::SExt : Instruction::ZExt; 3449 VecTy = VectorType::get(MinTy, BundleWidth); 3450 ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(), 3451 VecTy, EU.Lane); 3452 } else { 3453 ExtractCost += 3454 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, EU.Lane); 3455 } 3456 } 3457 3458 int SpillCost = getSpillCost(); 3459 Cost += SpillCost + ExtractCost; 3460 3461 std::string Str; 3462 { 3463 raw_string_ostream OS(Str); 3464 OS << "SLP: Spill Cost = " << SpillCost << ".\n" 3465 << "SLP: Extract Cost = " << ExtractCost << ".\n" 3466 << "SLP: Total Cost = " << Cost << ".\n"; 3467 } 3468 LLVM_DEBUG(dbgs() << Str); 3469 3470 if (ViewSLPTree) 3471 ViewGraph(this, "SLP" + F->getName(), false, Str); 3472 3473 return Cost; 3474 } 3475 3476 int BoUpSLP::getGatherCost(Type *Ty, 3477 const DenseSet<unsigned> &ShuffledIndices) const { 3478 int Cost = 0; 3479 for (unsigned i = 0, e = cast<VectorType>(Ty)->getNumElements(); i < e; ++i) 3480 if (!ShuffledIndices.count(i)) 3481 Cost += TTI->getVectorInstrCost(Instruction::InsertElement, Ty, i); 3482 if (!ShuffledIndices.empty()) 3483 Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, Ty); 3484 return Cost; 3485 } 3486 3487 int BoUpSLP::getGatherCost(ArrayRef<Value *> VL) const { 3488 // Find the type of the operands in VL. 3489 Type *ScalarTy = VL[0]->getType(); 3490 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 3491 ScalarTy = SI->getValueOperand()->getType(); 3492 VectorType *VecTy = VectorType::get(ScalarTy, VL.size()); 3493 // Find the cost of inserting/extracting values from the vector. 3494 // Check if the same elements are inserted several times and count them as 3495 // shuffle candidates. 3496 DenseSet<unsigned> ShuffledElements; 3497 DenseSet<Value *> UniqueElements; 3498 // Iterate in reverse order to consider insert elements with the high cost. 3499 for (unsigned I = VL.size(); I > 0; --I) { 3500 unsigned Idx = I - 1; 3501 if (!UniqueElements.insert(VL[Idx]).second) 3502 ShuffledElements.insert(Idx); 3503 } 3504 return getGatherCost(VecTy, ShuffledElements); 3505 } 3506 3507 // Perform operand reordering on the instructions in VL and return the reordered 3508 // operands in Left and Right. 3509 void BoUpSLP::reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 3510 SmallVectorImpl<Value *> &Left, 3511 SmallVectorImpl<Value *> &Right, 3512 const DataLayout &DL, 3513 ScalarEvolution &SE, 3514 const BoUpSLP &R) { 3515 if (VL.empty()) 3516 return; 3517 VLOperands Ops(VL, DL, SE, R); 3518 // Reorder the operands in place. 3519 Ops.reorder(); 3520 Left = Ops.getVL(0); 3521 Right = Ops.getVL(1); 3522 } 3523 3524 void BoUpSLP::setInsertPointAfterBundle(ArrayRef<Value *> VL, 3525 const InstructionsState &S) { 3526 // Get the basic block this bundle is in. All instructions in the bundle 3527 // should be in this block. 3528 auto *Front = cast<Instruction>(S.OpValue); 3529 auto *BB = Front->getParent(); 3530 assert(llvm::all_of(make_range(VL.begin(), VL.end()), [=](Value *V) -> bool { 3531 auto *I = cast<Instruction>(V); 3532 return !S.isOpcodeOrAlt(I) || I->getParent() == BB; 3533 })); 3534 3535 // The last instruction in the bundle in program order. 3536 Instruction *LastInst = nullptr; 3537 3538 // Find the last instruction. The common case should be that BB has been 3539 // scheduled, and the last instruction is VL.back(). So we start with 3540 // VL.back() and iterate over schedule data until we reach the end of the 3541 // bundle. The end of the bundle is marked by null ScheduleData. 3542 if (BlocksSchedules.count(BB)) { 3543 auto *Bundle = 3544 BlocksSchedules[BB]->getScheduleData(isOneOf(S, VL.back())); 3545 if (Bundle && Bundle->isPartOfBundle()) 3546 for (; Bundle; Bundle = Bundle->NextInBundle) 3547 if (Bundle->OpValue == Bundle->Inst) 3548 LastInst = Bundle->Inst; 3549 } 3550 3551 // LastInst can still be null at this point if there's either not an entry 3552 // for BB in BlocksSchedules or there's no ScheduleData available for 3553 // VL.back(). This can be the case if buildTree_rec aborts for various 3554 // reasons (e.g., the maximum recursion depth is reached, the maximum region 3555 // size is reached, etc.). ScheduleData is initialized in the scheduling 3556 // "dry-run". 3557 // 3558 // If this happens, we can still find the last instruction by brute force. We 3559 // iterate forwards from Front (inclusive) until we either see all 3560 // instructions in the bundle or reach the end of the block. If Front is the 3561 // last instruction in program order, LastInst will be set to Front, and we 3562 // will visit all the remaining instructions in the block. 3563 // 3564 // One of the reasons we exit early from buildTree_rec is to place an upper 3565 // bound on compile-time. Thus, taking an additional compile-time hit here is 3566 // not ideal. However, this should be exceedingly rare since it requires that 3567 // we both exit early from buildTree_rec and that the bundle be out-of-order 3568 // (causing us to iterate all the way to the end of the block). 3569 if (!LastInst) { 3570 SmallPtrSet<Value *, 16> Bundle(VL.begin(), VL.end()); 3571 for (auto &I : make_range(BasicBlock::iterator(Front), BB->end())) { 3572 if (Bundle.erase(&I) && S.isOpcodeOrAlt(&I)) 3573 LastInst = &I; 3574 if (Bundle.empty()) 3575 break; 3576 } 3577 } 3578 3579 // Set the insertion point after the last instruction in the bundle. Set the 3580 // debug location to Front. 3581 Builder.SetInsertPoint(BB, ++LastInst->getIterator()); 3582 Builder.SetCurrentDebugLocation(Front->getDebugLoc()); 3583 } 3584 3585 Value *BoUpSLP::Gather(ArrayRef<Value *> VL, VectorType *Ty) { 3586 Value *Vec = UndefValue::get(Ty); 3587 // Generate the 'InsertElement' instruction. 3588 for (unsigned i = 0; i < Ty->getNumElements(); ++i) { 3589 Vec = Builder.CreateInsertElement(Vec, VL[i], Builder.getInt32(i)); 3590 if (Instruction *Insrt = dyn_cast<Instruction>(Vec)) { 3591 GatherSeq.insert(Insrt); 3592 CSEBlocks.insert(Insrt->getParent()); 3593 3594 // Add to our 'need-to-extract' list. 3595 if (TreeEntry *E = getTreeEntry(VL[i])) { 3596 // Find which lane we need to extract. 3597 int FoundLane = -1; 3598 for (unsigned Lane = 0, LE = E->Scalars.size(); Lane != LE; ++Lane) { 3599 // Is this the lane of the scalar that we are looking for ? 3600 if (E->Scalars[Lane] == VL[i]) { 3601 FoundLane = Lane; 3602 break; 3603 } 3604 } 3605 assert(FoundLane >= 0 && "Could not find the correct lane"); 3606 if (!E->ReuseShuffleIndices.empty()) { 3607 FoundLane = 3608 std::distance(E->ReuseShuffleIndices.begin(), 3609 llvm::find(E->ReuseShuffleIndices, FoundLane)); 3610 } 3611 ExternalUses.push_back(ExternalUser(VL[i], Insrt, FoundLane)); 3612 } 3613 } 3614 } 3615 3616 return Vec; 3617 } 3618 3619 Value *BoUpSLP::vectorizeTree(ArrayRef<Value *> VL) { 3620 InstructionsState S = getSameOpcode(VL); 3621 if (S.getOpcode()) { 3622 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 3623 if (E->isSame(VL)) { 3624 Value *V = vectorizeTree(E); 3625 if (VL.size() == E->Scalars.size() && !E->ReuseShuffleIndices.empty()) { 3626 // We need to get the vectorized value but without shuffle. 3627 if (auto *SV = dyn_cast<ShuffleVectorInst>(V)) { 3628 V = SV->getOperand(0); 3629 } else { 3630 // Reshuffle to get only unique values. 3631 SmallVector<unsigned, 4> UniqueIdxs; 3632 SmallSet<unsigned, 4> UsedIdxs; 3633 for(unsigned Idx : E->ReuseShuffleIndices) 3634 if (UsedIdxs.insert(Idx).second) 3635 UniqueIdxs.emplace_back(Idx); 3636 V = Builder.CreateShuffleVector(V, UndefValue::get(V->getType()), 3637 UniqueIdxs); 3638 } 3639 } 3640 return V; 3641 } 3642 } 3643 } 3644 3645 Type *ScalarTy = S.OpValue->getType(); 3646 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) 3647 ScalarTy = SI->getValueOperand()->getType(); 3648 3649 // Check that every instruction appears once in this bundle. 3650 SmallVector<unsigned, 4> ReuseShuffleIndicies; 3651 SmallVector<Value *, 4> UniqueValues; 3652 if (VL.size() > 2) { 3653 DenseMap<Value *, unsigned> UniquePositions; 3654 for (Value *V : VL) { 3655 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 3656 ReuseShuffleIndicies.emplace_back(Res.first->second); 3657 if (Res.second || isa<Constant>(V)) 3658 UniqueValues.emplace_back(V); 3659 } 3660 // Do not shuffle single element or if number of unique values is not power 3661 // of 2. 3662 if (UniqueValues.size() == VL.size() || UniqueValues.size() <= 1 || 3663 !llvm::isPowerOf2_32(UniqueValues.size())) 3664 ReuseShuffleIndicies.clear(); 3665 else 3666 VL = UniqueValues; 3667 } 3668 VectorType *VecTy = VectorType::get(ScalarTy, VL.size()); 3669 3670 Value *V = Gather(VL, VecTy); 3671 if (!ReuseShuffleIndicies.empty()) { 3672 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3673 ReuseShuffleIndicies, "shuffle"); 3674 if (auto *I = dyn_cast<Instruction>(V)) { 3675 GatherSeq.insert(I); 3676 CSEBlocks.insert(I->getParent()); 3677 } 3678 } 3679 return V; 3680 } 3681 3682 static void inversePermutation(ArrayRef<unsigned> Indices, 3683 SmallVectorImpl<unsigned> &Mask) { 3684 Mask.clear(); 3685 const unsigned E = Indices.size(); 3686 Mask.resize(E); 3687 for (unsigned I = 0; I < E; ++I) 3688 Mask[Indices[I]] = I; 3689 } 3690 3691 Value *BoUpSLP::vectorizeTree(TreeEntry *E) { 3692 IRBuilder<>::InsertPointGuard Guard(Builder); 3693 3694 if (E->VectorizedValue) { 3695 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *E->Scalars[0] << ".\n"); 3696 return E->VectorizedValue; 3697 } 3698 3699 InstructionsState S = getSameOpcode(E->Scalars); 3700 Instruction *VL0 = cast<Instruction>(S.OpValue); 3701 Type *ScalarTy = VL0->getType(); 3702 if (StoreInst *SI = dyn_cast<StoreInst>(VL0)) 3703 ScalarTy = SI->getValueOperand()->getType(); 3704 VectorType *VecTy = VectorType::get(ScalarTy, E->Scalars.size()); 3705 3706 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 3707 3708 if (E->NeedToGather) { 3709 setInsertPointAfterBundle(E->Scalars, S); 3710 auto *V = Gather(E->Scalars, VecTy); 3711 if (NeedToShuffleReuses) { 3712 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3713 E->ReuseShuffleIndices, "shuffle"); 3714 if (auto *I = dyn_cast<Instruction>(V)) { 3715 GatherSeq.insert(I); 3716 CSEBlocks.insert(I->getParent()); 3717 } 3718 } 3719 E->VectorizedValue = V; 3720 return V; 3721 } 3722 3723 unsigned ShuffleOrOp = S.isAltShuffle() ? 3724 (unsigned) Instruction::ShuffleVector : S.getOpcode(); 3725 switch (ShuffleOrOp) { 3726 case Instruction::PHI: { 3727 PHINode *PH = dyn_cast<PHINode>(VL0); 3728 Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI()); 3729 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 3730 PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues()); 3731 Value *V = NewPhi; 3732 if (NeedToShuffleReuses) { 3733 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3734 E->ReuseShuffleIndices, "shuffle"); 3735 } 3736 E->VectorizedValue = V; 3737 3738 // PHINodes may have multiple entries from the same block. We want to 3739 // visit every block once. 3740 SmallPtrSet<BasicBlock*, 4> VisitedBBs; 3741 3742 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 3743 ValueList Operands; 3744 BasicBlock *IBB = PH->getIncomingBlock(i); 3745 3746 if (!VisitedBBs.insert(IBB).second) { 3747 NewPhi->addIncoming(NewPhi->getIncomingValueForBlock(IBB), IBB); 3748 continue; 3749 } 3750 3751 Builder.SetInsertPoint(IBB->getTerminator()); 3752 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 3753 Value *Vec = vectorizeTree(E->getOperand(i)); 3754 NewPhi->addIncoming(Vec, IBB); 3755 } 3756 3757 assert(NewPhi->getNumIncomingValues() == PH->getNumIncomingValues() && 3758 "Invalid number of incoming values"); 3759 return V; 3760 } 3761 3762 case Instruction::ExtractElement: { 3763 if (!E->NeedToGather) { 3764 Value *V = E->getSingleOperand(0); 3765 if (!E->ReorderIndices.empty()) { 3766 OrdersType Mask; 3767 inversePermutation(E->ReorderIndices, Mask); 3768 Builder.SetInsertPoint(VL0); 3769 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), Mask, 3770 "reorder_shuffle"); 3771 } 3772 if (NeedToShuffleReuses) { 3773 // TODO: Merge this shuffle with the ReorderShuffleMask. 3774 if (E->ReorderIndices.empty()) 3775 Builder.SetInsertPoint(VL0); 3776 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3777 E->ReuseShuffleIndices, "shuffle"); 3778 } 3779 E->VectorizedValue = V; 3780 return V; 3781 } 3782 setInsertPointAfterBundle(E->Scalars, S); 3783 auto *V = Gather(E->Scalars, VecTy); 3784 if (NeedToShuffleReuses) { 3785 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3786 E->ReuseShuffleIndices, "shuffle"); 3787 if (auto *I = dyn_cast<Instruction>(V)) { 3788 GatherSeq.insert(I); 3789 CSEBlocks.insert(I->getParent()); 3790 } 3791 } 3792 E->VectorizedValue = V; 3793 return V; 3794 } 3795 case Instruction::ExtractValue: { 3796 if (!E->NeedToGather) { 3797 LoadInst *LI = cast<LoadInst>(E->getSingleOperand(0)); 3798 Builder.SetInsertPoint(LI); 3799 PointerType *PtrTy = PointerType::get(VecTy, LI->getPointerAddressSpace()); 3800 Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy); 3801 LoadInst *V = Builder.CreateAlignedLoad(VecTy, Ptr, LI->getAlignment()); 3802 Value *NewV = propagateMetadata(V, E->Scalars); 3803 if (!E->ReorderIndices.empty()) { 3804 OrdersType Mask; 3805 inversePermutation(E->ReorderIndices, Mask); 3806 NewV = Builder.CreateShuffleVector(NewV, UndefValue::get(VecTy), Mask, 3807 "reorder_shuffle"); 3808 } 3809 if (NeedToShuffleReuses) { 3810 // TODO: Merge this shuffle with the ReorderShuffleMask. 3811 NewV = Builder.CreateShuffleVector( 3812 NewV, UndefValue::get(VecTy), E->ReuseShuffleIndices, "shuffle"); 3813 } 3814 E->VectorizedValue = NewV; 3815 return NewV; 3816 } 3817 setInsertPointAfterBundle(E->Scalars, S); 3818 auto *V = Gather(E->Scalars, VecTy); 3819 if (NeedToShuffleReuses) { 3820 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3821 E->ReuseShuffleIndices, "shuffle"); 3822 if (auto *I = dyn_cast<Instruction>(V)) { 3823 GatherSeq.insert(I); 3824 CSEBlocks.insert(I->getParent()); 3825 } 3826 } 3827 E->VectorizedValue = V; 3828 return V; 3829 } 3830 case Instruction::ZExt: 3831 case Instruction::SExt: 3832 case Instruction::FPToUI: 3833 case Instruction::FPToSI: 3834 case Instruction::FPExt: 3835 case Instruction::PtrToInt: 3836 case Instruction::IntToPtr: 3837 case Instruction::SIToFP: 3838 case Instruction::UIToFP: 3839 case Instruction::Trunc: 3840 case Instruction::FPTrunc: 3841 case Instruction::BitCast: { 3842 setInsertPointAfterBundle(E->Scalars, S); 3843 3844 Value *InVec = vectorizeTree(E->getOperand(0)); 3845 3846 if (E->VectorizedValue) { 3847 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 3848 return E->VectorizedValue; 3849 } 3850 3851 CastInst *CI = dyn_cast<CastInst>(VL0); 3852 Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy); 3853 if (NeedToShuffleReuses) { 3854 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3855 E->ReuseShuffleIndices, "shuffle"); 3856 } 3857 E->VectorizedValue = V; 3858 ++NumVectorInstructions; 3859 return V; 3860 } 3861 case Instruction::FCmp: 3862 case Instruction::ICmp: { 3863 setInsertPointAfterBundle(E->Scalars, S); 3864 3865 Value *L = vectorizeTree(E->getOperand(0)); 3866 Value *R = vectorizeTree(E->getOperand(1)); 3867 3868 if (E->VectorizedValue) { 3869 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 3870 return E->VectorizedValue; 3871 } 3872 3873 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 3874 Value *V; 3875 if (S.getOpcode() == Instruction::FCmp) 3876 V = Builder.CreateFCmp(P0, L, R); 3877 else 3878 V = Builder.CreateICmp(P0, L, R); 3879 3880 propagateIRFlags(V, E->Scalars, VL0); 3881 if (NeedToShuffleReuses) { 3882 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3883 E->ReuseShuffleIndices, "shuffle"); 3884 } 3885 E->VectorizedValue = V; 3886 ++NumVectorInstructions; 3887 return V; 3888 } 3889 case Instruction::Select: { 3890 setInsertPointAfterBundle(E->Scalars, S); 3891 3892 Value *Cond = vectorizeTree(E->getOperand(0)); 3893 Value *True = vectorizeTree(E->getOperand(1)); 3894 Value *False = vectorizeTree(E->getOperand(2)); 3895 3896 if (E->VectorizedValue) { 3897 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 3898 return E->VectorizedValue; 3899 } 3900 3901 Value *V = Builder.CreateSelect(Cond, True, False); 3902 if (NeedToShuffleReuses) { 3903 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3904 E->ReuseShuffleIndices, "shuffle"); 3905 } 3906 E->VectorizedValue = V; 3907 ++NumVectorInstructions; 3908 return V; 3909 } 3910 case Instruction::FNeg: { 3911 setInsertPointAfterBundle(E->Scalars, S); 3912 3913 Value *Op = vectorizeTree(E->getOperand(0)); 3914 3915 if (E->VectorizedValue) { 3916 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 3917 return E->VectorizedValue; 3918 } 3919 3920 Value *V = Builder.CreateUnOp( 3921 static_cast<Instruction::UnaryOps>(S.getOpcode()), Op); 3922 propagateIRFlags(V, E->Scalars, VL0); 3923 if (auto *I = dyn_cast<Instruction>(V)) 3924 V = propagateMetadata(I, E->Scalars); 3925 3926 if (NeedToShuffleReuses) { 3927 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3928 E->ReuseShuffleIndices, "shuffle"); 3929 } 3930 E->VectorizedValue = V; 3931 ++NumVectorInstructions; 3932 3933 return V; 3934 } 3935 case Instruction::Add: 3936 case Instruction::FAdd: 3937 case Instruction::Sub: 3938 case Instruction::FSub: 3939 case Instruction::Mul: 3940 case Instruction::FMul: 3941 case Instruction::UDiv: 3942 case Instruction::SDiv: 3943 case Instruction::FDiv: 3944 case Instruction::URem: 3945 case Instruction::SRem: 3946 case Instruction::FRem: 3947 case Instruction::Shl: 3948 case Instruction::LShr: 3949 case Instruction::AShr: 3950 case Instruction::And: 3951 case Instruction::Or: 3952 case Instruction::Xor: { 3953 setInsertPointAfterBundle(E->Scalars, S); 3954 3955 Value *LHS = vectorizeTree(E->getOperand(0)); 3956 Value *RHS = vectorizeTree(E->getOperand(1)); 3957 3958 if (E->VectorizedValue) { 3959 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 3960 return E->VectorizedValue; 3961 } 3962 3963 Value *V = Builder.CreateBinOp( 3964 static_cast<Instruction::BinaryOps>(S.getOpcode()), LHS, RHS); 3965 propagateIRFlags(V, E->Scalars, VL0); 3966 if (auto *I = dyn_cast<Instruction>(V)) 3967 V = propagateMetadata(I, E->Scalars); 3968 3969 if (NeedToShuffleReuses) { 3970 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3971 E->ReuseShuffleIndices, "shuffle"); 3972 } 3973 E->VectorizedValue = V; 3974 ++NumVectorInstructions; 3975 3976 return V; 3977 } 3978 case Instruction::Load: { 3979 // Loads are inserted at the head of the tree because we don't want to 3980 // sink them all the way down past store instructions. 3981 bool IsReorder = !E->ReorderIndices.empty(); 3982 if (IsReorder) { 3983 S = getSameOpcode(E->Scalars, E->ReorderIndices.front()); 3984 VL0 = cast<Instruction>(S.OpValue); 3985 } 3986 setInsertPointAfterBundle(E->Scalars, S); 3987 3988 LoadInst *LI = cast<LoadInst>(VL0); 3989 Type *ScalarLoadTy = LI->getType(); 3990 unsigned AS = LI->getPointerAddressSpace(); 3991 3992 Value *VecPtr = Builder.CreateBitCast(LI->getPointerOperand(), 3993 VecTy->getPointerTo(AS)); 3994 3995 // The pointer operand uses an in-tree scalar so we add the new BitCast to 3996 // ExternalUses list to make sure that an extract will be generated in the 3997 // future. 3998 Value *PO = LI->getPointerOperand(); 3999 if (getTreeEntry(PO)) 4000 ExternalUses.push_back(ExternalUser(PO, cast<User>(VecPtr), 0)); 4001 4002 unsigned Alignment = LI->getAlignment(); 4003 LI = Builder.CreateLoad(VecTy, VecPtr); 4004 if (!Alignment) { 4005 Alignment = DL->getABITypeAlignment(ScalarLoadTy); 4006 } 4007 LI->setAlignment(Alignment); 4008 Value *V = propagateMetadata(LI, E->Scalars); 4009 if (IsReorder) { 4010 OrdersType Mask; 4011 inversePermutation(E->ReorderIndices, Mask); 4012 V = Builder.CreateShuffleVector(V, UndefValue::get(V->getType()), 4013 Mask, "reorder_shuffle"); 4014 } 4015 if (NeedToShuffleReuses) { 4016 // TODO: Merge this shuffle with the ReorderShuffleMask. 4017 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4018 E->ReuseShuffleIndices, "shuffle"); 4019 } 4020 E->VectorizedValue = V; 4021 ++NumVectorInstructions; 4022 return V; 4023 } 4024 case Instruction::Store: { 4025 StoreInst *SI = cast<StoreInst>(VL0); 4026 unsigned Alignment = SI->getAlignment(); 4027 unsigned AS = SI->getPointerAddressSpace(); 4028 4029 setInsertPointAfterBundle(E->Scalars, S); 4030 4031 Value *VecValue = vectorizeTree(E->getOperand(0)); 4032 Value *ScalarPtr = SI->getPointerOperand(); 4033 Value *VecPtr = Builder.CreateBitCast(ScalarPtr, VecTy->getPointerTo(AS)); 4034 StoreInst *ST = Builder.CreateStore(VecValue, VecPtr); 4035 4036 // The pointer operand uses an in-tree scalar, so add the new BitCast to 4037 // ExternalUses to make sure that an extract will be generated in the 4038 // future. 4039 if (getTreeEntry(ScalarPtr)) 4040 ExternalUses.push_back(ExternalUser(ScalarPtr, cast<User>(VecPtr), 0)); 4041 4042 if (!Alignment) 4043 Alignment = DL->getABITypeAlignment(SI->getValueOperand()->getType()); 4044 4045 ST->setAlignment(Alignment); 4046 Value *V = propagateMetadata(ST, E->Scalars); 4047 if (NeedToShuffleReuses) { 4048 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4049 E->ReuseShuffleIndices, "shuffle"); 4050 } 4051 E->VectorizedValue = V; 4052 ++NumVectorInstructions; 4053 return V; 4054 } 4055 case Instruction::GetElementPtr: { 4056 setInsertPointAfterBundle(E->Scalars, S); 4057 4058 Value *Op0 = vectorizeTree(E->getOperand(0)); 4059 4060 std::vector<Value *> OpVecs; 4061 for (int j = 1, e = cast<GetElementPtrInst>(VL0)->getNumOperands(); j < e; 4062 ++j) { 4063 Value *OpVec = vectorizeTree(E->getOperand(j)); 4064 OpVecs.push_back(OpVec); 4065 } 4066 4067 Value *V = Builder.CreateGEP( 4068 cast<GetElementPtrInst>(VL0)->getSourceElementType(), Op0, OpVecs); 4069 if (Instruction *I = dyn_cast<Instruction>(V)) 4070 V = propagateMetadata(I, E->Scalars); 4071 4072 if (NeedToShuffleReuses) { 4073 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4074 E->ReuseShuffleIndices, "shuffle"); 4075 } 4076 E->VectorizedValue = V; 4077 ++NumVectorInstructions; 4078 4079 return V; 4080 } 4081 case Instruction::Call: { 4082 CallInst *CI = cast<CallInst>(VL0); 4083 setInsertPointAfterBundle(E->Scalars, S); 4084 Function *FI; 4085 Intrinsic::ID IID = Intrinsic::not_intrinsic; 4086 Value *ScalarArg = nullptr; 4087 if (CI && (FI = CI->getCalledFunction())) { 4088 IID = FI->getIntrinsicID(); 4089 } 4090 std::vector<Value *> OpVecs; 4091 for (int j = 0, e = CI->getNumArgOperands(); j < e; ++j) { 4092 ValueList OpVL; 4093 // Some intrinsics have scalar arguments. This argument should not be 4094 // vectorized. 4095 if (hasVectorInstrinsicScalarOpd(IID, j)) { 4096 CallInst *CEI = cast<CallInst>(VL0); 4097 ScalarArg = CEI->getArgOperand(j); 4098 OpVecs.push_back(CEI->getArgOperand(j)); 4099 continue; 4100 } 4101 4102 Value *OpVec = vectorizeTree(E->getOperand(j)); 4103 LLVM_DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n"); 4104 OpVecs.push_back(OpVec); 4105 } 4106 4107 Module *M = F->getParent(); 4108 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 4109 Type *Tys[] = { VectorType::get(CI->getType(), E->Scalars.size()) }; 4110 Function *CF = Intrinsic::getDeclaration(M, ID, Tys); 4111 SmallVector<OperandBundleDef, 1> OpBundles; 4112 CI->getOperandBundlesAsDefs(OpBundles); 4113 Value *V = Builder.CreateCall(CF, OpVecs, OpBundles); 4114 4115 // The scalar argument uses an in-tree scalar so we add the new vectorized 4116 // call to ExternalUses list to make sure that an extract will be 4117 // generated in the future. 4118 if (ScalarArg && getTreeEntry(ScalarArg)) 4119 ExternalUses.push_back(ExternalUser(ScalarArg, cast<User>(V), 0)); 4120 4121 propagateIRFlags(V, E->Scalars, VL0); 4122 if (NeedToShuffleReuses) { 4123 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4124 E->ReuseShuffleIndices, "shuffle"); 4125 } 4126 E->VectorizedValue = V; 4127 ++NumVectorInstructions; 4128 return V; 4129 } 4130 case Instruction::ShuffleVector: { 4131 assert(S.isAltShuffle() && 4132 ((Instruction::isBinaryOp(S.getOpcode()) && 4133 Instruction::isBinaryOp(S.getAltOpcode())) || 4134 (Instruction::isCast(S.getOpcode()) && 4135 Instruction::isCast(S.getAltOpcode()))) && 4136 "Invalid Shuffle Vector Operand"); 4137 4138 Value *LHS, *RHS; 4139 if (Instruction::isBinaryOp(S.getOpcode())) { 4140 setInsertPointAfterBundle(E->Scalars, S); 4141 LHS = vectorizeTree(E->getOperand(0)); 4142 RHS = vectorizeTree(E->getOperand(1)); 4143 } else { 4144 setInsertPointAfterBundle(E->Scalars, S); 4145 LHS = vectorizeTree(E->getOperand(0)); 4146 } 4147 4148 if (E->VectorizedValue) { 4149 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4150 return E->VectorizedValue; 4151 } 4152 4153 Value *V0, *V1; 4154 if (Instruction::isBinaryOp(S.getOpcode())) { 4155 V0 = Builder.CreateBinOp( 4156 static_cast<Instruction::BinaryOps>(S.getOpcode()), LHS, RHS); 4157 V1 = Builder.CreateBinOp( 4158 static_cast<Instruction::BinaryOps>(S.getAltOpcode()), LHS, RHS); 4159 } else { 4160 V0 = Builder.CreateCast( 4161 static_cast<Instruction::CastOps>(S.getOpcode()), LHS, VecTy); 4162 V1 = Builder.CreateCast( 4163 static_cast<Instruction::CastOps>(S.getAltOpcode()), LHS, VecTy); 4164 } 4165 4166 // Create shuffle to take alternate operations from the vector. 4167 // Also, gather up main and alt scalar ops to propagate IR flags to 4168 // each vector operation. 4169 ValueList OpScalars, AltScalars; 4170 unsigned e = E->Scalars.size(); 4171 SmallVector<Constant *, 8> Mask(e); 4172 for (unsigned i = 0; i < e; ++i) { 4173 auto *OpInst = cast<Instruction>(E->Scalars[i]); 4174 assert(S.isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 4175 if (OpInst->getOpcode() == S.getAltOpcode()) { 4176 Mask[i] = Builder.getInt32(e + i); 4177 AltScalars.push_back(E->Scalars[i]); 4178 } else { 4179 Mask[i] = Builder.getInt32(i); 4180 OpScalars.push_back(E->Scalars[i]); 4181 } 4182 } 4183 4184 Value *ShuffleMask = ConstantVector::get(Mask); 4185 propagateIRFlags(V0, OpScalars); 4186 propagateIRFlags(V1, AltScalars); 4187 4188 Value *V = Builder.CreateShuffleVector(V0, V1, ShuffleMask); 4189 if (Instruction *I = dyn_cast<Instruction>(V)) 4190 V = propagateMetadata(I, E->Scalars); 4191 if (NeedToShuffleReuses) { 4192 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4193 E->ReuseShuffleIndices, "shuffle"); 4194 } 4195 E->VectorizedValue = V; 4196 ++NumVectorInstructions; 4197 4198 return V; 4199 } 4200 default: 4201 llvm_unreachable("unknown inst"); 4202 } 4203 return nullptr; 4204 } 4205 4206 Value *BoUpSLP::vectorizeTree() { 4207 ExtraValueToDebugLocsMap ExternallyUsedValues; 4208 return vectorizeTree(ExternallyUsedValues); 4209 } 4210 4211 Value * 4212 BoUpSLP::vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues) { 4213 // All blocks must be scheduled before any instructions are inserted. 4214 for (auto &BSIter : BlocksSchedules) { 4215 scheduleBlock(BSIter.second.get()); 4216 } 4217 4218 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4219 auto *VectorRoot = vectorizeTree(VectorizableTree[0].get()); 4220 4221 // If the vectorized tree can be rewritten in a smaller type, we truncate the 4222 // vectorized root. InstCombine will then rewrite the entire expression. We 4223 // sign extend the extracted values below. 4224 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 4225 if (MinBWs.count(ScalarRoot)) { 4226 if (auto *I = dyn_cast<Instruction>(VectorRoot)) 4227 Builder.SetInsertPoint(&*++BasicBlock::iterator(I)); 4228 auto BundleWidth = VectorizableTree[0]->Scalars.size(); 4229 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 4230 auto *VecTy = VectorType::get(MinTy, BundleWidth); 4231 auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy); 4232 VectorizableTree[0]->VectorizedValue = Trunc; 4233 } 4234 4235 LLVM_DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size() 4236 << " values .\n"); 4237 4238 // If necessary, sign-extend or zero-extend ScalarRoot to the larger type 4239 // specified by ScalarType. 4240 auto extend = [&](Value *ScalarRoot, Value *Ex, Type *ScalarType) { 4241 if (!MinBWs.count(ScalarRoot)) 4242 return Ex; 4243 if (MinBWs[ScalarRoot].second) 4244 return Builder.CreateSExt(Ex, ScalarType); 4245 return Builder.CreateZExt(Ex, ScalarType); 4246 }; 4247 4248 // Extract all of the elements with the external uses. 4249 for (const auto &ExternalUse : ExternalUses) { 4250 Value *Scalar = ExternalUse.Scalar; 4251 llvm::User *User = ExternalUse.User; 4252 4253 // Skip users that we already RAUW. This happens when one instruction 4254 // has multiple uses of the same value. 4255 if (User && !is_contained(Scalar->users(), User)) 4256 continue; 4257 TreeEntry *E = getTreeEntry(Scalar); 4258 assert(E && "Invalid scalar"); 4259 assert(!E->NeedToGather && "Extracting from a gather list"); 4260 4261 Value *Vec = E->VectorizedValue; 4262 assert(Vec && "Can't find vectorizable value"); 4263 4264 Value *Lane = Builder.getInt32(ExternalUse.Lane); 4265 // If User == nullptr, the Scalar is used as extra arg. Generate 4266 // ExtractElement instruction and update the record for this scalar in 4267 // ExternallyUsedValues. 4268 if (!User) { 4269 assert(ExternallyUsedValues.count(Scalar) && 4270 "Scalar with nullptr as an external user must be registered in " 4271 "ExternallyUsedValues map"); 4272 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 4273 Builder.SetInsertPoint(VecI->getParent(), 4274 std::next(VecI->getIterator())); 4275 } else { 4276 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4277 } 4278 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4279 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4280 CSEBlocks.insert(cast<Instruction>(Scalar)->getParent()); 4281 auto &Locs = ExternallyUsedValues[Scalar]; 4282 ExternallyUsedValues.insert({Ex, Locs}); 4283 ExternallyUsedValues.erase(Scalar); 4284 // Required to update internally referenced instructions. 4285 Scalar->replaceAllUsesWith(Ex); 4286 continue; 4287 } 4288 4289 // Generate extracts for out-of-tree users. 4290 // Find the insertion point for the extractelement lane. 4291 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 4292 if (PHINode *PH = dyn_cast<PHINode>(User)) { 4293 for (int i = 0, e = PH->getNumIncomingValues(); i != e; ++i) { 4294 if (PH->getIncomingValue(i) == Scalar) { 4295 Instruction *IncomingTerminator = 4296 PH->getIncomingBlock(i)->getTerminator(); 4297 if (isa<CatchSwitchInst>(IncomingTerminator)) { 4298 Builder.SetInsertPoint(VecI->getParent(), 4299 std::next(VecI->getIterator())); 4300 } else { 4301 Builder.SetInsertPoint(PH->getIncomingBlock(i)->getTerminator()); 4302 } 4303 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4304 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4305 CSEBlocks.insert(PH->getIncomingBlock(i)); 4306 PH->setOperand(i, Ex); 4307 } 4308 } 4309 } else { 4310 Builder.SetInsertPoint(cast<Instruction>(User)); 4311 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4312 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4313 CSEBlocks.insert(cast<Instruction>(User)->getParent()); 4314 User->replaceUsesOfWith(Scalar, Ex); 4315 } 4316 } else { 4317 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4318 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4319 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4320 CSEBlocks.insert(&F->getEntryBlock()); 4321 User->replaceUsesOfWith(Scalar, Ex); 4322 } 4323 4324 LLVM_DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n"); 4325 } 4326 4327 // For each vectorized value: 4328 for (auto &TEPtr : VectorizableTree) { 4329 TreeEntry *Entry = TEPtr.get(); 4330 4331 // No need to handle users of gathered values. 4332 if (Entry->NeedToGather) 4333 continue; 4334 4335 assert(Entry->VectorizedValue && "Can't find vectorizable value"); 4336 4337 // For each lane: 4338 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 4339 Value *Scalar = Entry->Scalars[Lane]; 4340 4341 Type *Ty = Scalar->getType(); 4342 if (!Ty->isVoidTy()) { 4343 #ifndef NDEBUG 4344 for (User *U : Scalar->users()) { 4345 LLVM_DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n"); 4346 4347 // It is legal to replace users in the ignorelist by undef. 4348 assert((getTreeEntry(U) || is_contained(UserIgnoreList, U)) && 4349 "Replacing out-of-tree value with undef"); 4350 } 4351 #endif 4352 Value *Undef = UndefValue::get(Ty); 4353 Scalar->replaceAllUsesWith(Undef); 4354 } 4355 LLVM_DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n"); 4356 eraseInstruction(cast<Instruction>(Scalar)); 4357 } 4358 } 4359 4360 Builder.ClearInsertionPoint(); 4361 4362 return VectorizableTree[0]->VectorizedValue; 4363 } 4364 4365 void BoUpSLP::optimizeGatherSequence() { 4366 LLVM_DEBUG(dbgs() << "SLP: Optimizing " << GatherSeq.size() 4367 << " gather sequences instructions.\n"); 4368 // LICM InsertElementInst sequences. 4369 for (Instruction *I : GatherSeq) { 4370 if (!isa<InsertElementInst>(I) && !isa<ShuffleVectorInst>(I)) 4371 continue; 4372 4373 // Check if this block is inside a loop. 4374 Loop *L = LI->getLoopFor(I->getParent()); 4375 if (!L) 4376 continue; 4377 4378 // Check if it has a preheader. 4379 BasicBlock *PreHeader = L->getLoopPreheader(); 4380 if (!PreHeader) 4381 continue; 4382 4383 // If the vector or the element that we insert into it are 4384 // instructions that are defined in this basic block then we can't 4385 // hoist this instruction. 4386 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 4387 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 4388 if (Op0 && L->contains(Op0)) 4389 continue; 4390 if (Op1 && L->contains(Op1)) 4391 continue; 4392 4393 // We can hoist this instruction. Move it to the pre-header. 4394 I->moveBefore(PreHeader->getTerminator()); 4395 } 4396 4397 // Make a list of all reachable blocks in our CSE queue. 4398 SmallVector<const DomTreeNode *, 8> CSEWorkList; 4399 CSEWorkList.reserve(CSEBlocks.size()); 4400 for (BasicBlock *BB : CSEBlocks) 4401 if (DomTreeNode *N = DT->getNode(BB)) { 4402 assert(DT->isReachableFromEntry(N)); 4403 CSEWorkList.push_back(N); 4404 } 4405 4406 // Sort blocks by domination. This ensures we visit a block after all blocks 4407 // dominating it are visited. 4408 llvm::stable_sort(CSEWorkList, 4409 [this](const DomTreeNode *A, const DomTreeNode *B) { 4410 return DT->properlyDominates(A, B); 4411 }); 4412 4413 // Perform O(N^2) search over the gather sequences and merge identical 4414 // instructions. TODO: We can further optimize this scan if we split the 4415 // instructions into different buckets based on the insert lane. 4416 SmallVector<Instruction *, 16> Visited; 4417 for (auto I = CSEWorkList.begin(), E = CSEWorkList.end(); I != E; ++I) { 4418 assert((I == CSEWorkList.begin() || !DT->dominates(*I, *std::prev(I))) && 4419 "Worklist not sorted properly!"); 4420 BasicBlock *BB = (*I)->getBlock(); 4421 // For all instructions in blocks containing gather sequences: 4422 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e;) { 4423 Instruction *In = &*it++; 4424 if (!isa<InsertElementInst>(In) && !isa<ExtractElementInst>(In)) 4425 continue; 4426 4427 // Check if we can replace this instruction with any of the 4428 // visited instructions. 4429 for (Instruction *v : Visited) { 4430 if (In->isIdenticalTo(v) && 4431 DT->dominates(v->getParent(), In->getParent())) { 4432 In->replaceAllUsesWith(v); 4433 eraseInstruction(In); 4434 In = nullptr; 4435 break; 4436 } 4437 } 4438 if (In) { 4439 assert(!is_contained(Visited, In)); 4440 Visited.push_back(In); 4441 } 4442 } 4443 } 4444 CSEBlocks.clear(); 4445 GatherSeq.clear(); 4446 } 4447 4448 // Groups the instructions to a bundle (which is then a single scheduling entity) 4449 // and schedules instructions until the bundle gets ready. 4450 bool BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL, 4451 BoUpSLP *SLP, 4452 const InstructionsState &S) { 4453 if (isa<PHINode>(S.OpValue)) 4454 return true; 4455 4456 // Initialize the instruction bundle. 4457 Instruction *OldScheduleEnd = ScheduleEnd; 4458 ScheduleData *PrevInBundle = nullptr; 4459 ScheduleData *Bundle = nullptr; 4460 bool ReSchedule = false; 4461 LLVM_DEBUG(dbgs() << "SLP: bundle: " << *S.OpValue << "\n"); 4462 4463 // Make sure that the scheduling region contains all 4464 // instructions of the bundle. 4465 for (Value *V : VL) { 4466 if (!extendSchedulingRegion(V, S)) 4467 return false; 4468 } 4469 4470 for (Value *V : VL) { 4471 ScheduleData *BundleMember = getScheduleData(V); 4472 assert(BundleMember && 4473 "no ScheduleData for bundle member (maybe not in same basic block)"); 4474 if (BundleMember->IsScheduled) { 4475 // A bundle member was scheduled as single instruction before and now 4476 // needs to be scheduled as part of the bundle. We just get rid of the 4477 // existing schedule. 4478 LLVM_DEBUG(dbgs() << "SLP: reset schedule because " << *BundleMember 4479 << " was already scheduled\n"); 4480 ReSchedule = true; 4481 } 4482 assert(BundleMember->isSchedulingEntity() && 4483 "bundle member already part of other bundle"); 4484 if (PrevInBundle) { 4485 PrevInBundle->NextInBundle = BundleMember; 4486 } else { 4487 Bundle = BundleMember; 4488 } 4489 BundleMember->UnscheduledDepsInBundle = 0; 4490 Bundle->UnscheduledDepsInBundle += BundleMember->UnscheduledDeps; 4491 4492 // Group the instructions to a bundle. 4493 BundleMember->FirstInBundle = Bundle; 4494 PrevInBundle = BundleMember; 4495 } 4496 if (ScheduleEnd != OldScheduleEnd) { 4497 // The scheduling region got new instructions at the lower end (or it is a 4498 // new region for the first bundle). This makes it necessary to 4499 // recalculate all dependencies. 4500 // It is seldom that this needs to be done a second time after adding the 4501 // initial bundle to the region. 4502 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 4503 doForAllOpcodes(I, [](ScheduleData *SD) { 4504 SD->clearDependencies(); 4505 }); 4506 } 4507 ReSchedule = true; 4508 } 4509 if (ReSchedule) { 4510 resetSchedule(); 4511 initialFillReadyList(ReadyInsts); 4512 } 4513 4514 LLVM_DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle << " in block " 4515 << BB->getName() << "\n"); 4516 4517 calculateDependencies(Bundle, true, SLP); 4518 4519 // Now try to schedule the new bundle. As soon as the bundle is "ready" it 4520 // means that there are no cyclic dependencies and we can schedule it. 4521 // Note that's important that we don't "schedule" the bundle yet (see 4522 // cancelScheduling). 4523 while (!Bundle->isReady() && !ReadyInsts.empty()) { 4524 4525 ScheduleData *pickedSD = ReadyInsts.back(); 4526 ReadyInsts.pop_back(); 4527 4528 if (pickedSD->isSchedulingEntity() && pickedSD->isReady()) { 4529 schedule(pickedSD, ReadyInsts); 4530 } 4531 } 4532 if (!Bundle->isReady()) { 4533 cancelScheduling(VL, S.OpValue); 4534 return false; 4535 } 4536 return true; 4537 } 4538 4539 void BoUpSLP::BlockScheduling::cancelScheduling(ArrayRef<Value *> VL, 4540 Value *OpValue) { 4541 if (isa<PHINode>(OpValue)) 4542 return; 4543 4544 ScheduleData *Bundle = getScheduleData(OpValue); 4545 LLVM_DEBUG(dbgs() << "SLP: cancel scheduling of " << *Bundle << "\n"); 4546 assert(!Bundle->IsScheduled && 4547 "Can't cancel bundle which is already scheduled"); 4548 assert(Bundle->isSchedulingEntity() && Bundle->isPartOfBundle() && 4549 "tried to unbundle something which is not a bundle"); 4550 4551 // Un-bundle: make single instructions out of the bundle. 4552 ScheduleData *BundleMember = Bundle; 4553 while (BundleMember) { 4554 assert(BundleMember->FirstInBundle == Bundle && "corrupt bundle links"); 4555 BundleMember->FirstInBundle = BundleMember; 4556 ScheduleData *Next = BundleMember->NextInBundle; 4557 BundleMember->NextInBundle = nullptr; 4558 BundleMember->UnscheduledDepsInBundle = BundleMember->UnscheduledDeps; 4559 if (BundleMember->UnscheduledDepsInBundle == 0) { 4560 ReadyInsts.insert(BundleMember); 4561 } 4562 BundleMember = Next; 4563 } 4564 } 4565 4566 BoUpSLP::ScheduleData *BoUpSLP::BlockScheduling::allocateScheduleDataChunks() { 4567 // Allocate a new ScheduleData for the instruction. 4568 if (ChunkPos >= ChunkSize) { 4569 ScheduleDataChunks.push_back(llvm::make_unique<ScheduleData[]>(ChunkSize)); 4570 ChunkPos = 0; 4571 } 4572 return &(ScheduleDataChunks.back()[ChunkPos++]); 4573 } 4574 4575 bool BoUpSLP::BlockScheduling::extendSchedulingRegion(Value *V, 4576 const InstructionsState &S) { 4577 if (getScheduleData(V, isOneOf(S, V))) 4578 return true; 4579 Instruction *I = dyn_cast<Instruction>(V); 4580 assert(I && "bundle member must be an instruction"); 4581 assert(!isa<PHINode>(I) && "phi nodes don't need to be scheduled"); 4582 auto &&CheckSheduleForI = [this, &S](Instruction *I) -> bool { 4583 ScheduleData *ISD = getScheduleData(I); 4584 if (!ISD) 4585 return false; 4586 assert(isInSchedulingRegion(ISD) && 4587 "ScheduleData not in scheduling region"); 4588 ScheduleData *SD = allocateScheduleDataChunks(); 4589 SD->Inst = I; 4590 SD->init(SchedulingRegionID, S.OpValue); 4591 ExtraScheduleDataMap[I][S.OpValue] = SD; 4592 return true; 4593 }; 4594 if (CheckSheduleForI(I)) 4595 return true; 4596 if (!ScheduleStart) { 4597 // It's the first instruction in the new region. 4598 initScheduleData(I, I->getNextNode(), nullptr, nullptr); 4599 ScheduleStart = I; 4600 ScheduleEnd = I->getNextNode(); 4601 if (isOneOf(S, I) != I) 4602 CheckSheduleForI(I); 4603 assert(ScheduleEnd && "tried to vectorize a terminator?"); 4604 LLVM_DEBUG(dbgs() << "SLP: initialize schedule region to " << *I << "\n"); 4605 return true; 4606 } 4607 // Search up and down at the same time, because we don't know if the new 4608 // instruction is above or below the existing scheduling region. 4609 BasicBlock::reverse_iterator UpIter = 4610 ++ScheduleStart->getIterator().getReverse(); 4611 BasicBlock::reverse_iterator UpperEnd = BB->rend(); 4612 BasicBlock::iterator DownIter = ScheduleEnd->getIterator(); 4613 BasicBlock::iterator LowerEnd = BB->end(); 4614 while (true) { 4615 if (++ScheduleRegionSize > ScheduleRegionSizeLimit) { 4616 LLVM_DEBUG(dbgs() << "SLP: exceeded schedule region size limit\n"); 4617 return false; 4618 } 4619 4620 if (UpIter != UpperEnd) { 4621 if (&*UpIter == I) { 4622 initScheduleData(I, ScheduleStart, nullptr, FirstLoadStoreInRegion); 4623 ScheduleStart = I; 4624 if (isOneOf(S, I) != I) 4625 CheckSheduleForI(I); 4626 LLVM_DEBUG(dbgs() << "SLP: extend schedule region start to " << *I 4627 << "\n"); 4628 return true; 4629 } 4630 ++UpIter; 4631 } 4632 if (DownIter != LowerEnd) { 4633 if (&*DownIter == I) { 4634 initScheduleData(ScheduleEnd, I->getNextNode(), LastLoadStoreInRegion, 4635 nullptr); 4636 ScheduleEnd = I->getNextNode(); 4637 if (isOneOf(S, I) != I) 4638 CheckSheduleForI(I); 4639 assert(ScheduleEnd && "tried to vectorize a terminator?"); 4640 LLVM_DEBUG(dbgs() << "SLP: extend schedule region end to " << *I 4641 << "\n"); 4642 return true; 4643 } 4644 ++DownIter; 4645 } 4646 assert((UpIter != UpperEnd || DownIter != LowerEnd) && 4647 "instruction not found in block"); 4648 } 4649 return true; 4650 } 4651 4652 void BoUpSLP::BlockScheduling::initScheduleData(Instruction *FromI, 4653 Instruction *ToI, 4654 ScheduleData *PrevLoadStore, 4655 ScheduleData *NextLoadStore) { 4656 ScheduleData *CurrentLoadStore = PrevLoadStore; 4657 for (Instruction *I = FromI; I != ToI; I = I->getNextNode()) { 4658 ScheduleData *SD = ScheduleDataMap[I]; 4659 if (!SD) { 4660 SD = allocateScheduleDataChunks(); 4661 ScheduleDataMap[I] = SD; 4662 SD->Inst = I; 4663 } 4664 assert(!isInSchedulingRegion(SD) && 4665 "new ScheduleData already in scheduling region"); 4666 SD->init(SchedulingRegionID, I); 4667 4668 if (I->mayReadOrWriteMemory() && 4669 (!isa<IntrinsicInst>(I) || 4670 cast<IntrinsicInst>(I)->getIntrinsicID() != Intrinsic::sideeffect)) { 4671 // Update the linked list of memory accessing instructions. 4672 if (CurrentLoadStore) { 4673 CurrentLoadStore->NextLoadStore = SD; 4674 } else { 4675 FirstLoadStoreInRegion = SD; 4676 } 4677 CurrentLoadStore = SD; 4678 } 4679 } 4680 if (NextLoadStore) { 4681 if (CurrentLoadStore) 4682 CurrentLoadStore->NextLoadStore = NextLoadStore; 4683 } else { 4684 LastLoadStoreInRegion = CurrentLoadStore; 4685 } 4686 } 4687 4688 void BoUpSLP::BlockScheduling::calculateDependencies(ScheduleData *SD, 4689 bool InsertInReadyList, 4690 BoUpSLP *SLP) { 4691 assert(SD->isSchedulingEntity()); 4692 4693 SmallVector<ScheduleData *, 10> WorkList; 4694 WorkList.push_back(SD); 4695 4696 while (!WorkList.empty()) { 4697 ScheduleData *SD = WorkList.back(); 4698 WorkList.pop_back(); 4699 4700 ScheduleData *BundleMember = SD; 4701 while (BundleMember) { 4702 assert(isInSchedulingRegion(BundleMember)); 4703 if (!BundleMember->hasValidDependencies()) { 4704 4705 LLVM_DEBUG(dbgs() << "SLP: update deps of " << *BundleMember 4706 << "\n"); 4707 BundleMember->Dependencies = 0; 4708 BundleMember->resetUnscheduledDeps(); 4709 4710 // Handle def-use chain dependencies. 4711 if (BundleMember->OpValue != BundleMember->Inst) { 4712 ScheduleData *UseSD = getScheduleData(BundleMember->Inst); 4713 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 4714 BundleMember->Dependencies++; 4715 ScheduleData *DestBundle = UseSD->FirstInBundle; 4716 if (!DestBundle->IsScheduled) 4717 BundleMember->incrementUnscheduledDeps(1); 4718 if (!DestBundle->hasValidDependencies()) 4719 WorkList.push_back(DestBundle); 4720 } 4721 } else { 4722 for (User *U : BundleMember->Inst->users()) { 4723 if (isa<Instruction>(U)) { 4724 ScheduleData *UseSD = getScheduleData(U); 4725 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 4726 BundleMember->Dependencies++; 4727 ScheduleData *DestBundle = UseSD->FirstInBundle; 4728 if (!DestBundle->IsScheduled) 4729 BundleMember->incrementUnscheduledDeps(1); 4730 if (!DestBundle->hasValidDependencies()) 4731 WorkList.push_back(DestBundle); 4732 } 4733 } else { 4734 // I'm not sure if this can ever happen. But we need to be safe. 4735 // This lets the instruction/bundle never be scheduled and 4736 // eventually disable vectorization. 4737 BundleMember->Dependencies++; 4738 BundleMember->incrementUnscheduledDeps(1); 4739 } 4740 } 4741 } 4742 4743 // Handle the memory dependencies. 4744 ScheduleData *DepDest = BundleMember->NextLoadStore; 4745 if (DepDest) { 4746 Instruction *SrcInst = BundleMember->Inst; 4747 MemoryLocation SrcLoc = getLocation(SrcInst, SLP->AA); 4748 bool SrcMayWrite = BundleMember->Inst->mayWriteToMemory(); 4749 unsigned numAliased = 0; 4750 unsigned DistToSrc = 1; 4751 4752 while (DepDest) { 4753 assert(isInSchedulingRegion(DepDest)); 4754 4755 // We have two limits to reduce the complexity: 4756 // 1) AliasedCheckLimit: It's a small limit to reduce calls to 4757 // SLP->isAliased (which is the expensive part in this loop). 4758 // 2) MaxMemDepDistance: It's for very large blocks and it aborts 4759 // the whole loop (even if the loop is fast, it's quadratic). 4760 // It's important for the loop break condition (see below) to 4761 // check this limit even between two read-only instructions. 4762 if (DistToSrc >= MaxMemDepDistance || 4763 ((SrcMayWrite || DepDest->Inst->mayWriteToMemory()) && 4764 (numAliased >= AliasedCheckLimit || 4765 SLP->isAliased(SrcLoc, SrcInst, DepDest->Inst)))) { 4766 4767 // We increment the counter only if the locations are aliased 4768 // (instead of counting all alias checks). This gives a better 4769 // balance between reduced runtime and accurate dependencies. 4770 numAliased++; 4771 4772 DepDest->MemoryDependencies.push_back(BundleMember); 4773 BundleMember->Dependencies++; 4774 ScheduleData *DestBundle = DepDest->FirstInBundle; 4775 if (!DestBundle->IsScheduled) { 4776 BundleMember->incrementUnscheduledDeps(1); 4777 } 4778 if (!DestBundle->hasValidDependencies()) { 4779 WorkList.push_back(DestBundle); 4780 } 4781 } 4782 DepDest = DepDest->NextLoadStore; 4783 4784 // Example, explaining the loop break condition: Let's assume our 4785 // starting instruction is i0 and MaxMemDepDistance = 3. 4786 // 4787 // +--------v--v--v 4788 // i0,i1,i2,i3,i4,i5,i6,i7,i8 4789 // +--------^--^--^ 4790 // 4791 // MaxMemDepDistance let us stop alias-checking at i3 and we add 4792 // dependencies from i0 to i3,i4,.. (even if they are not aliased). 4793 // Previously we already added dependencies from i3 to i6,i7,i8 4794 // (because of MaxMemDepDistance). As we added a dependency from 4795 // i0 to i3, we have transitive dependencies from i0 to i6,i7,i8 4796 // and we can abort this loop at i6. 4797 if (DistToSrc >= 2 * MaxMemDepDistance) 4798 break; 4799 DistToSrc++; 4800 } 4801 } 4802 } 4803 BundleMember = BundleMember->NextInBundle; 4804 } 4805 if (InsertInReadyList && SD->isReady()) { 4806 ReadyInsts.push_back(SD); 4807 LLVM_DEBUG(dbgs() << "SLP: gets ready on update: " << *SD->Inst 4808 << "\n"); 4809 } 4810 } 4811 } 4812 4813 void BoUpSLP::BlockScheduling::resetSchedule() { 4814 assert(ScheduleStart && 4815 "tried to reset schedule on block which has not been scheduled"); 4816 for (Instruction *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 4817 doForAllOpcodes(I, [&](ScheduleData *SD) { 4818 assert(isInSchedulingRegion(SD) && 4819 "ScheduleData not in scheduling region"); 4820 SD->IsScheduled = false; 4821 SD->resetUnscheduledDeps(); 4822 }); 4823 } 4824 ReadyInsts.clear(); 4825 } 4826 4827 void BoUpSLP::scheduleBlock(BlockScheduling *BS) { 4828 if (!BS->ScheduleStart) 4829 return; 4830 4831 LLVM_DEBUG(dbgs() << "SLP: schedule block " << BS->BB->getName() << "\n"); 4832 4833 BS->resetSchedule(); 4834 4835 // For the real scheduling we use a more sophisticated ready-list: it is 4836 // sorted by the original instruction location. This lets the final schedule 4837 // be as close as possible to the original instruction order. 4838 struct ScheduleDataCompare { 4839 bool operator()(ScheduleData *SD1, ScheduleData *SD2) const { 4840 return SD2->SchedulingPriority < SD1->SchedulingPriority; 4841 } 4842 }; 4843 std::set<ScheduleData *, ScheduleDataCompare> ReadyInsts; 4844 4845 // Ensure that all dependency data is updated and fill the ready-list with 4846 // initial instructions. 4847 int Idx = 0; 4848 int NumToSchedule = 0; 4849 for (auto *I = BS->ScheduleStart; I != BS->ScheduleEnd; 4850 I = I->getNextNode()) { 4851 BS->doForAllOpcodes(I, [this, &Idx, &NumToSchedule, BS](ScheduleData *SD) { 4852 assert(SD->isPartOfBundle() == 4853 (getTreeEntry(SD->Inst) != nullptr) && 4854 "scheduler and vectorizer bundle mismatch"); 4855 SD->FirstInBundle->SchedulingPriority = Idx++; 4856 if (SD->isSchedulingEntity()) { 4857 BS->calculateDependencies(SD, false, this); 4858 NumToSchedule++; 4859 } 4860 }); 4861 } 4862 BS->initialFillReadyList(ReadyInsts); 4863 4864 Instruction *LastScheduledInst = BS->ScheduleEnd; 4865 4866 // Do the "real" scheduling. 4867 while (!ReadyInsts.empty()) { 4868 ScheduleData *picked = *ReadyInsts.begin(); 4869 ReadyInsts.erase(ReadyInsts.begin()); 4870 4871 // Move the scheduled instruction(s) to their dedicated places, if not 4872 // there yet. 4873 ScheduleData *BundleMember = picked; 4874 while (BundleMember) { 4875 Instruction *pickedInst = BundleMember->Inst; 4876 if (LastScheduledInst->getNextNode() != pickedInst) { 4877 BS->BB->getInstList().remove(pickedInst); 4878 BS->BB->getInstList().insert(LastScheduledInst->getIterator(), 4879 pickedInst); 4880 } 4881 LastScheduledInst = pickedInst; 4882 BundleMember = BundleMember->NextInBundle; 4883 } 4884 4885 BS->schedule(picked, ReadyInsts); 4886 NumToSchedule--; 4887 } 4888 assert(NumToSchedule == 0 && "could not schedule all instructions"); 4889 4890 // Avoid duplicate scheduling of the block. 4891 BS->ScheduleStart = nullptr; 4892 } 4893 4894 unsigned BoUpSLP::getVectorElementSize(Value *V) const { 4895 // If V is a store, just return the width of the stored value without 4896 // traversing the expression tree. This is the common case. 4897 if (auto *Store = dyn_cast<StoreInst>(V)) 4898 return DL->getTypeSizeInBits(Store->getValueOperand()->getType()); 4899 4900 // If V is not a store, we can traverse the expression tree to find loads 4901 // that feed it. The type of the loaded value may indicate a more suitable 4902 // width than V's type. We want to base the vector element size on the width 4903 // of memory operations where possible. 4904 SmallVector<Instruction *, 16> Worklist; 4905 SmallPtrSet<Instruction *, 16> Visited; 4906 if (auto *I = dyn_cast<Instruction>(V)) 4907 Worklist.push_back(I); 4908 4909 // Traverse the expression tree in bottom-up order looking for loads. If we 4910 // encounter an instruction we don't yet handle, we give up. 4911 auto MaxWidth = 0u; 4912 auto FoundUnknownInst = false; 4913 while (!Worklist.empty() && !FoundUnknownInst) { 4914 auto *I = Worklist.pop_back_val(); 4915 Visited.insert(I); 4916 4917 // We should only be looking at scalar instructions here. If the current 4918 // instruction has a vector type, give up. 4919 auto *Ty = I->getType(); 4920 if (isa<VectorType>(Ty)) 4921 FoundUnknownInst = true; 4922 4923 // If the current instruction is a load, update MaxWidth to reflect the 4924 // width of the loaded value. 4925 else if (isa<LoadInst>(I)) 4926 MaxWidth = std::max<unsigned>(MaxWidth, DL->getTypeSizeInBits(Ty)); 4927 4928 // Otherwise, we need to visit the operands of the instruction. We only 4929 // handle the interesting cases from buildTree here. If an operand is an 4930 // instruction we haven't yet visited, we add it to the worklist. 4931 else if (isa<PHINode>(I) || isa<CastInst>(I) || isa<GetElementPtrInst>(I) || 4932 isa<CmpInst>(I) || isa<SelectInst>(I) || isa<BinaryOperator>(I)) { 4933 for (Use &U : I->operands()) 4934 if (auto *J = dyn_cast<Instruction>(U.get())) 4935 if (!Visited.count(J)) 4936 Worklist.push_back(J); 4937 } 4938 4939 // If we don't yet handle the instruction, give up. 4940 else 4941 FoundUnknownInst = true; 4942 } 4943 4944 // If we didn't encounter a memory access in the expression tree, or if we 4945 // gave up for some reason, just return the width of V. 4946 if (!MaxWidth || FoundUnknownInst) 4947 return DL->getTypeSizeInBits(V->getType()); 4948 4949 // Otherwise, return the maximum width we found. 4950 return MaxWidth; 4951 } 4952 4953 // Determine if a value V in a vectorizable expression Expr can be demoted to a 4954 // smaller type with a truncation. We collect the values that will be demoted 4955 // in ToDemote and additional roots that require investigating in Roots. 4956 static bool collectValuesToDemote(Value *V, SmallPtrSetImpl<Value *> &Expr, 4957 SmallVectorImpl<Value *> &ToDemote, 4958 SmallVectorImpl<Value *> &Roots) { 4959 // We can always demote constants. 4960 if (isa<Constant>(V)) { 4961 ToDemote.push_back(V); 4962 return true; 4963 } 4964 4965 // If the value is not an instruction in the expression with only one use, it 4966 // cannot be demoted. 4967 auto *I = dyn_cast<Instruction>(V); 4968 if (!I || !I->hasOneUse() || !Expr.count(I)) 4969 return false; 4970 4971 switch (I->getOpcode()) { 4972 4973 // We can always demote truncations and extensions. Since truncations can 4974 // seed additional demotion, we save the truncated value. 4975 case Instruction::Trunc: 4976 Roots.push_back(I->getOperand(0)); 4977 break; 4978 case Instruction::ZExt: 4979 case Instruction::SExt: 4980 break; 4981 4982 // We can demote certain binary operations if we can demote both of their 4983 // operands. 4984 case Instruction::Add: 4985 case Instruction::Sub: 4986 case Instruction::Mul: 4987 case Instruction::And: 4988 case Instruction::Or: 4989 case Instruction::Xor: 4990 if (!collectValuesToDemote(I->getOperand(0), Expr, ToDemote, Roots) || 4991 !collectValuesToDemote(I->getOperand(1), Expr, ToDemote, Roots)) 4992 return false; 4993 break; 4994 4995 // We can demote selects if we can demote their true and false values. 4996 case Instruction::Select: { 4997 SelectInst *SI = cast<SelectInst>(I); 4998 if (!collectValuesToDemote(SI->getTrueValue(), Expr, ToDemote, Roots) || 4999 !collectValuesToDemote(SI->getFalseValue(), Expr, ToDemote, Roots)) 5000 return false; 5001 break; 5002 } 5003 5004 // We can demote phis if we can demote all their incoming operands. Note that 5005 // we don't need to worry about cycles since we ensure single use above. 5006 case Instruction::PHI: { 5007 PHINode *PN = cast<PHINode>(I); 5008 for (Value *IncValue : PN->incoming_values()) 5009 if (!collectValuesToDemote(IncValue, Expr, ToDemote, Roots)) 5010 return false; 5011 break; 5012 } 5013 5014 // Otherwise, conservatively give up. 5015 default: 5016 return false; 5017 } 5018 5019 // Record the value that we can demote. 5020 ToDemote.push_back(V); 5021 return true; 5022 } 5023 5024 void BoUpSLP::computeMinimumValueSizes() { 5025 // If there are no external uses, the expression tree must be rooted by a 5026 // store. We can't demote in-memory values, so there is nothing to do here. 5027 if (ExternalUses.empty()) 5028 return; 5029 5030 // We only attempt to truncate integer expressions. 5031 auto &TreeRoot = VectorizableTree[0]->Scalars; 5032 auto *TreeRootIT = dyn_cast<IntegerType>(TreeRoot[0]->getType()); 5033 if (!TreeRootIT) 5034 return; 5035 5036 // If the expression is not rooted by a store, these roots should have 5037 // external uses. We will rely on InstCombine to rewrite the expression in 5038 // the narrower type. However, InstCombine only rewrites single-use values. 5039 // This means that if a tree entry other than a root is used externally, it 5040 // must have multiple uses and InstCombine will not rewrite it. The code 5041 // below ensures that only the roots are used externally. 5042 SmallPtrSet<Value *, 32> Expr(TreeRoot.begin(), TreeRoot.end()); 5043 for (auto &EU : ExternalUses) 5044 if (!Expr.erase(EU.Scalar)) 5045 return; 5046 if (!Expr.empty()) 5047 return; 5048 5049 // Collect the scalar values of the vectorizable expression. We will use this 5050 // context to determine which values can be demoted. If we see a truncation, 5051 // we mark it as seeding another demotion. 5052 for (auto &EntryPtr : VectorizableTree) 5053 Expr.insert(EntryPtr->Scalars.begin(), EntryPtr->Scalars.end()); 5054 5055 // Ensure the roots of the vectorizable tree don't form a cycle. They must 5056 // have a single external user that is not in the vectorizable tree. 5057 for (auto *Root : TreeRoot) 5058 if (!Root->hasOneUse() || Expr.count(*Root->user_begin())) 5059 return; 5060 5061 // Conservatively determine if we can actually truncate the roots of the 5062 // expression. Collect the values that can be demoted in ToDemote and 5063 // additional roots that require investigating in Roots. 5064 SmallVector<Value *, 32> ToDemote; 5065 SmallVector<Value *, 4> Roots; 5066 for (auto *Root : TreeRoot) 5067 if (!collectValuesToDemote(Root, Expr, ToDemote, Roots)) 5068 return; 5069 5070 // The maximum bit width required to represent all the values that can be 5071 // demoted without loss of precision. It would be safe to truncate the roots 5072 // of the expression to this width. 5073 auto MaxBitWidth = 8u; 5074 5075 // We first check if all the bits of the roots are demanded. If they're not, 5076 // we can truncate the roots to this narrower type. 5077 for (auto *Root : TreeRoot) { 5078 auto Mask = DB->getDemandedBits(cast<Instruction>(Root)); 5079 MaxBitWidth = std::max<unsigned>( 5080 Mask.getBitWidth() - Mask.countLeadingZeros(), MaxBitWidth); 5081 } 5082 5083 // True if the roots can be zero-extended back to their original type, rather 5084 // than sign-extended. We know that if the leading bits are not demanded, we 5085 // can safely zero-extend. So we initialize IsKnownPositive to True. 5086 bool IsKnownPositive = true; 5087 5088 // If all the bits of the roots are demanded, we can try a little harder to 5089 // compute a narrower type. This can happen, for example, if the roots are 5090 // getelementptr indices. InstCombine promotes these indices to the pointer 5091 // width. Thus, all their bits are technically demanded even though the 5092 // address computation might be vectorized in a smaller type. 5093 // 5094 // We start by looking at each entry that can be demoted. We compute the 5095 // maximum bit width required to store the scalar by using ValueTracking to 5096 // compute the number of high-order bits we can truncate. 5097 if (MaxBitWidth == DL->getTypeSizeInBits(TreeRoot[0]->getType()) && 5098 llvm::all_of(TreeRoot, [](Value *R) { 5099 assert(R->hasOneUse() && "Root should have only one use!"); 5100 return isa<GetElementPtrInst>(R->user_back()); 5101 })) { 5102 MaxBitWidth = 8u; 5103 5104 // Determine if the sign bit of all the roots is known to be zero. If not, 5105 // IsKnownPositive is set to False. 5106 IsKnownPositive = llvm::all_of(TreeRoot, [&](Value *R) { 5107 KnownBits Known = computeKnownBits(R, *DL); 5108 return Known.isNonNegative(); 5109 }); 5110 5111 // Determine the maximum number of bits required to store the scalar 5112 // values. 5113 for (auto *Scalar : ToDemote) { 5114 auto NumSignBits = ComputeNumSignBits(Scalar, *DL, 0, AC, nullptr, DT); 5115 auto NumTypeBits = DL->getTypeSizeInBits(Scalar->getType()); 5116 MaxBitWidth = std::max<unsigned>(NumTypeBits - NumSignBits, MaxBitWidth); 5117 } 5118 5119 // If we can't prove that the sign bit is zero, we must add one to the 5120 // maximum bit width to account for the unknown sign bit. This preserves 5121 // the existing sign bit so we can safely sign-extend the root back to the 5122 // original type. Otherwise, if we know the sign bit is zero, we will 5123 // zero-extend the root instead. 5124 // 5125 // FIXME: This is somewhat suboptimal, as there will be cases where adding 5126 // one to the maximum bit width will yield a larger-than-necessary 5127 // type. In general, we need to add an extra bit only if we can't 5128 // prove that the upper bit of the original type is equal to the 5129 // upper bit of the proposed smaller type. If these two bits are the 5130 // same (either zero or one) we know that sign-extending from the 5131 // smaller type will result in the same value. Here, since we can't 5132 // yet prove this, we are just making the proposed smaller type 5133 // larger to ensure correctness. 5134 if (!IsKnownPositive) 5135 ++MaxBitWidth; 5136 } 5137 5138 // Round MaxBitWidth up to the next power-of-two. 5139 if (!isPowerOf2_64(MaxBitWidth)) 5140 MaxBitWidth = NextPowerOf2(MaxBitWidth); 5141 5142 // If the maximum bit width we compute is less than the with of the roots' 5143 // type, we can proceed with the narrowing. Otherwise, do nothing. 5144 if (MaxBitWidth >= TreeRootIT->getBitWidth()) 5145 return; 5146 5147 // If we can truncate the root, we must collect additional values that might 5148 // be demoted as a result. That is, those seeded by truncations we will 5149 // modify. 5150 while (!Roots.empty()) 5151 collectValuesToDemote(Roots.pop_back_val(), Expr, ToDemote, Roots); 5152 5153 // Finally, map the values we can demote to the maximum bit with we computed. 5154 for (auto *Scalar : ToDemote) 5155 MinBWs[Scalar] = std::make_pair(MaxBitWidth, !IsKnownPositive); 5156 } 5157 5158 namespace { 5159 5160 /// The SLPVectorizer Pass. 5161 struct SLPVectorizer : public FunctionPass { 5162 SLPVectorizerPass Impl; 5163 5164 /// Pass identification, replacement for typeid 5165 static char ID; 5166 5167 explicit SLPVectorizer() : FunctionPass(ID) { 5168 initializeSLPVectorizerPass(*PassRegistry::getPassRegistry()); 5169 } 5170 5171 bool doInitialization(Module &M) override { 5172 return false; 5173 } 5174 5175 bool runOnFunction(Function &F) override { 5176 if (skipFunction(F)) 5177 return false; 5178 5179 auto *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 5180 auto *TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F); 5181 auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>(); 5182 auto *TLI = TLIP ? &TLIP->getTLI() : nullptr; 5183 auto *AA = &getAnalysis<AAResultsWrapperPass>().getAAResults(); 5184 auto *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 5185 auto *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 5186 auto *AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F); 5187 auto *DB = &getAnalysis<DemandedBitsWrapperPass>().getDemandedBits(); 5188 auto *ORE = &getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE(); 5189 5190 return Impl.runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 5191 } 5192 5193 void getAnalysisUsage(AnalysisUsage &AU) const override { 5194 FunctionPass::getAnalysisUsage(AU); 5195 AU.addRequired<AssumptionCacheTracker>(); 5196 AU.addRequired<ScalarEvolutionWrapperPass>(); 5197 AU.addRequired<AAResultsWrapperPass>(); 5198 AU.addRequired<TargetTransformInfoWrapperPass>(); 5199 AU.addRequired<LoopInfoWrapperPass>(); 5200 AU.addRequired<DominatorTreeWrapperPass>(); 5201 AU.addRequired<DemandedBitsWrapperPass>(); 5202 AU.addRequired<OptimizationRemarkEmitterWrapperPass>(); 5203 AU.addPreserved<LoopInfoWrapperPass>(); 5204 AU.addPreserved<DominatorTreeWrapperPass>(); 5205 AU.addPreserved<AAResultsWrapperPass>(); 5206 AU.addPreserved<GlobalsAAWrapperPass>(); 5207 AU.setPreservesCFG(); 5208 } 5209 }; 5210 5211 } // end anonymous namespace 5212 5213 PreservedAnalyses SLPVectorizerPass::run(Function &F, FunctionAnalysisManager &AM) { 5214 auto *SE = &AM.getResult<ScalarEvolutionAnalysis>(F); 5215 auto *TTI = &AM.getResult<TargetIRAnalysis>(F); 5216 auto *TLI = AM.getCachedResult<TargetLibraryAnalysis>(F); 5217 auto *AA = &AM.getResult<AAManager>(F); 5218 auto *LI = &AM.getResult<LoopAnalysis>(F); 5219 auto *DT = &AM.getResult<DominatorTreeAnalysis>(F); 5220 auto *AC = &AM.getResult<AssumptionAnalysis>(F); 5221 auto *DB = &AM.getResult<DemandedBitsAnalysis>(F); 5222 auto *ORE = &AM.getResult<OptimizationRemarkEmitterAnalysis>(F); 5223 5224 bool Changed = runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 5225 if (!Changed) 5226 return PreservedAnalyses::all(); 5227 5228 PreservedAnalyses PA; 5229 PA.preserveSet<CFGAnalyses>(); 5230 PA.preserve<AAManager>(); 5231 PA.preserve<GlobalsAA>(); 5232 return PA; 5233 } 5234 5235 bool SLPVectorizerPass::runImpl(Function &F, ScalarEvolution *SE_, 5236 TargetTransformInfo *TTI_, 5237 TargetLibraryInfo *TLI_, AliasAnalysis *AA_, 5238 LoopInfo *LI_, DominatorTree *DT_, 5239 AssumptionCache *AC_, DemandedBits *DB_, 5240 OptimizationRemarkEmitter *ORE_) { 5241 SE = SE_; 5242 TTI = TTI_; 5243 TLI = TLI_; 5244 AA = AA_; 5245 LI = LI_; 5246 DT = DT_; 5247 AC = AC_; 5248 DB = DB_; 5249 DL = &F.getParent()->getDataLayout(); 5250 5251 Stores.clear(); 5252 GEPs.clear(); 5253 bool Changed = false; 5254 5255 // If the target claims to have no vector registers don't attempt 5256 // vectorization. 5257 if (!TTI->getNumberOfRegisters(true)) 5258 return false; 5259 5260 // Don't vectorize when the attribute NoImplicitFloat is used. 5261 if (F.hasFnAttribute(Attribute::NoImplicitFloat)) 5262 return false; 5263 5264 LLVM_DEBUG(dbgs() << "SLP: Analyzing blocks in " << F.getName() << ".\n"); 5265 5266 // Use the bottom up slp vectorizer to construct chains that start with 5267 // store instructions. 5268 BoUpSLP R(&F, SE, TTI, TLI, AA, LI, DT, AC, DB, DL, ORE_); 5269 5270 // A general note: the vectorizer must use BoUpSLP::eraseInstruction() to 5271 // delete instructions. 5272 5273 // Scan the blocks in the function in post order. 5274 for (auto BB : post_order(&F.getEntryBlock())) { 5275 collectSeedInstructions(BB); 5276 5277 // Vectorize trees that end at stores. 5278 if (!Stores.empty()) { 5279 LLVM_DEBUG(dbgs() << "SLP: Found stores for " << Stores.size() 5280 << " underlying objects.\n"); 5281 Changed |= vectorizeStoreChains(R); 5282 } 5283 5284 // Vectorize trees that end at reductions. 5285 Changed |= vectorizeChainsInBlock(BB, R); 5286 5287 // Vectorize the index computations of getelementptr instructions. This 5288 // is primarily intended to catch gather-like idioms ending at 5289 // non-consecutive loads. 5290 if (!GEPs.empty()) { 5291 LLVM_DEBUG(dbgs() << "SLP: Found GEPs for " << GEPs.size() 5292 << " underlying objects.\n"); 5293 Changed |= vectorizeGEPIndices(BB, R); 5294 } 5295 } 5296 5297 if (Changed) { 5298 R.optimizeGatherSequence(); 5299 LLVM_DEBUG(dbgs() << "SLP: vectorized \"" << F.getName() << "\"\n"); 5300 LLVM_DEBUG(verifyFunction(F)); 5301 } 5302 return Changed; 5303 } 5304 5305 /// Check that the Values in the slice in VL array are still existent in 5306 /// the WeakTrackingVH array. 5307 /// Vectorization of part of the VL array may cause later values in the VL array 5308 /// to become invalid. We track when this has happened in the WeakTrackingVH 5309 /// array. 5310 static bool hasValueBeenRAUWed(ArrayRef<Value *> VL, 5311 ArrayRef<WeakTrackingVH> VH, unsigned SliceBegin, 5312 unsigned SliceSize) { 5313 VL = VL.slice(SliceBegin, SliceSize); 5314 VH = VH.slice(SliceBegin, SliceSize); 5315 return !std::equal(VL.begin(), VL.end(), VH.begin()); 5316 } 5317 5318 bool SLPVectorizerPass::vectorizeStoreChain(ArrayRef<Value *> Chain, BoUpSLP &R, 5319 unsigned VecRegSize) { 5320 const unsigned ChainLen = Chain.size(); 5321 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " << ChainLen 5322 << "\n"); 5323 const unsigned Sz = R.getVectorElementSize(Chain[0]); 5324 const unsigned VF = VecRegSize / Sz; 5325 5326 if (!isPowerOf2_32(Sz) || VF < 2) 5327 return false; 5328 5329 // Keep track of values that were deleted by vectorizing in the loop below. 5330 const SmallVector<WeakTrackingVH, 8> TrackValues(Chain.begin(), Chain.end()); 5331 5332 bool Changed = false; 5333 // Look for profitable vectorizable trees at all offsets, starting at zero. 5334 for (unsigned i = 0, e = ChainLen; i + VF <= e; ++i) { 5335 5336 // Check that a previous iteration of this loop did not delete the Value. 5337 if (hasValueBeenRAUWed(Chain, TrackValues, i, VF)) 5338 continue; 5339 5340 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << VF << " stores at offset " << i 5341 << "\n"); 5342 ArrayRef<Value *> Operands = Chain.slice(i, VF); 5343 5344 R.buildTree(Operands); 5345 if (R.isTreeTinyAndNotFullyVectorizable()) 5346 continue; 5347 5348 R.computeMinimumValueSizes(); 5349 5350 int Cost = R.getTreeCost(); 5351 5352 LLVM_DEBUG(dbgs() << "SLP: Found cost=" << Cost << " for VF=" << VF 5353 << "\n"); 5354 if (Cost < -SLPCostThreshold) { 5355 LLVM_DEBUG(dbgs() << "SLP: Decided to vectorize cost=" << Cost << "\n"); 5356 5357 using namespace ore; 5358 5359 R.getORE()->emit(OptimizationRemark(SV_NAME, "StoresVectorized", 5360 cast<StoreInst>(Chain[i])) 5361 << "Stores SLP vectorized with cost " << NV("Cost", Cost) 5362 << " and with tree size " 5363 << NV("TreeSize", R.getTreeSize())); 5364 5365 R.vectorizeTree(); 5366 5367 // Move to the next bundle. 5368 i += VF - 1; 5369 Changed = true; 5370 } 5371 } 5372 5373 return Changed; 5374 } 5375 5376 bool SLPVectorizerPass::vectorizeStores(ArrayRef<StoreInst *> Stores, 5377 BoUpSLP &R) { 5378 SetVector<StoreInst *> Heads; 5379 SmallDenseSet<StoreInst *> Tails; 5380 SmallDenseMap<StoreInst *, StoreInst *> ConsecutiveChain; 5381 5382 // We may run into multiple chains that merge into a single chain. We mark the 5383 // stores that we vectorized so that we don't visit the same store twice. 5384 BoUpSLP::ValueSet VectorizedStores; 5385 bool Changed = false; 5386 5387 auto &&FindConsecutiveAccess = 5388 [this, &Stores, &Heads, &Tails, &ConsecutiveChain] (int K, int Idx) { 5389 if (!isConsecutiveAccess(Stores[K], Stores[Idx], *DL, *SE)) 5390 return false; 5391 5392 Tails.insert(Stores[Idx]); 5393 Heads.insert(Stores[K]); 5394 ConsecutiveChain[Stores[K]] = Stores[Idx]; 5395 return true; 5396 }; 5397 5398 // Do a quadratic search on all of the given stores in reverse order and find 5399 // all of the pairs of stores that follow each other. 5400 int E = Stores.size(); 5401 for (int Idx = E - 1; Idx >= 0; --Idx) { 5402 // If a store has multiple consecutive store candidates, search according 5403 // to the sequence: Idx-1, Idx+1, Idx-2, Idx+2, ... 5404 // This is because usually pairing with immediate succeeding or preceding 5405 // candidate create the best chance to find slp vectorization opportunity. 5406 for (int Offset = 1, F = std::max(E - Idx, Idx + 1); Offset < F; ++Offset) 5407 if ((Idx >= Offset && FindConsecutiveAccess(Idx - Offset, Idx)) || 5408 (Idx + Offset < E && FindConsecutiveAccess(Idx + Offset, Idx))) 5409 break; 5410 } 5411 5412 // For stores that start but don't end a link in the chain: 5413 for (auto *SI : llvm::reverse(Heads)) { 5414 if (Tails.count(SI)) 5415 continue; 5416 5417 // We found a store instr that starts a chain. Now follow the chain and try 5418 // to vectorize it. 5419 BoUpSLP::ValueList Operands; 5420 StoreInst *I = SI; 5421 // Collect the chain into a list. 5422 while ((Tails.count(I) || Heads.count(I)) && !VectorizedStores.count(I)) { 5423 Operands.push_back(I); 5424 // Move to the next value in the chain. 5425 I = ConsecutiveChain[I]; 5426 } 5427 5428 // FIXME: Is division-by-2 the correct step? Should we assert that the 5429 // register size is a power-of-2? 5430 for (unsigned Size = R.getMaxVecRegSize(); Size >= R.getMinVecRegSize(); 5431 Size /= 2) { 5432 if (vectorizeStoreChain(Operands, R, Size)) { 5433 // Mark the vectorized stores so that we don't vectorize them again. 5434 VectorizedStores.insert(Operands.begin(), Operands.end()); 5435 Changed = true; 5436 break; 5437 } 5438 } 5439 } 5440 5441 return Changed; 5442 } 5443 5444 void SLPVectorizerPass::collectSeedInstructions(BasicBlock *BB) { 5445 // Initialize the collections. We will make a single pass over the block. 5446 Stores.clear(); 5447 GEPs.clear(); 5448 5449 // Visit the store and getelementptr instructions in BB and organize them in 5450 // Stores and GEPs according to the underlying objects of their pointer 5451 // operands. 5452 for (Instruction &I : *BB) { 5453 // Ignore store instructions that are volatile or have a pointer operand 5454 // that doesn't point to a scalar type. 5455 if (auto *SI = dyn_cast<StoreInst>(&I)) { 5456 if (!SI->isSimple()) 5457 continue; 5458 if (!isValidElementType(SI->getValueOperand()->getType())) 5459 continue; 5460 Stores[GetUnderlyingObject(SI->getPointerOperand(), *DL)].push_back(SI); 5461 } 5462 5463 // Ignore getelementptr instructions that have more than one index, a 5464 // constant index, or a pointer operand that doesn't point to a scalar 5465 // type. 5466 else if (auto *GEP = dyn_cast<GetElementPtrInst>(&I)) { 5467 auto Idx = GEP->idx_begin()->get(); 5468 if (GEP->getNumIndices() > 1 || isa<Constant>(Idx)) 5469 continue; 5470 if (!isValidElementType(Idx->getType())) 5471 continue; 5472 if (GEP->getType()->isVectorTy()) 5473 continue; 5474 GEPs[GEP->getPointerOperand()].push_back(GEP); 5475 } 5476 } 5477 } 5478 5479 bool SLPVectorizerPass::tryToVectorizePair(Value *A, Value *B, BoUpSLP &R) { 5480 if (!A || !B) 5481 return false; 5482 Value *VL[] = { A, B }; 5483 return tryToVectorizeList(VL, R, /*UserCost=*/0, true); 5484 } 5485 5486 bool SLPVectorizerPass::tryToVectorizeList(ArrayRef<Value *> VL, BoUpSLP &R, 5487 int UserCost, bool AllowReorder) { 5488 if (VL.size() < 2) 5489 return false; 5490 5491 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize a list of length = " 5492 << VL.size() << ".\n"); 5493 5494 // Check that all of the parts are scalar instructions of the same type, 5495 // we permit an alternate opcode via InstructionsState. 5496 InstructionsState S = getSameOpcode(VL); 5497 if (!S.getOpcode()) 5498 return false; 5499 5500 Instruction *I0 = cast<Instruction>(S.OpValue); 5501 unsigned Sz = R.getVectorElementSize(I0); 5502 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / Sz); 5503 unsigned MaxVF = std::max<unsigned>(PowerOf2Floor(VL.size()), MinVF); 5504 if (MaxVF < 2) { 5505 R.getORE()->emit([&]() { 5506 return OptimizationRemarkMissed(SV_NAME, "SmallVF", I0) 5507 << "Cannot SLP vectorize list: vectorization factor " 5508 << "less than 2 is not supported"; 5509 }); 5510 return false; 5511 } 5512 5513 for (Value *V : VL) { 5514 Type *Ty = V->getType(); 5515 if (!isValidElementType(Ty)) { 5516 // NOTE: the following will give user internal llvm type name, which may 5517 // not be useful. 5518 R.getORE()->emit([&]() { 5519 std::string type_str; 5520 llvm::raw_string_ostream rso(type_str); 5521 Ty->print(rso); 5522 return OptimizationRemarkMissed(SV_NAME, "UnsupportedType", I0) 5523 << "Cannot SLP vectorize list: type " 5524 << rso.str() + " is unsupported by vectorizer"; 5525 }); 5526 return false; 5527 } 5528 } 5529 5530 bool Changed = false; 5531 bool CandidateFound = false; 5532 int MinCost = SLPCostThreshold; 5533 5534 // Keep track of values that were deleted by vectorizing in the loop below. 5535 SmallVector<WeakTrackingVH, 8> TrackValues(VL.begin(), VL.end()); 5536 5537 unsigned NextInst = 0, MaxInst = VL.size(); 5538 for (unsigned VF = MaxVF; NextInst + 1 < MaxInst && VF >= MinVF; 5539 VF /= 2) { 5540 // No actual vectorization should happen, if number of parts is the same as 5541 // provided vectorization factor (i.e. the scalar type is used for vector 5542 // code during codegen). 5543 auto *VecTy = VectorType::get(VL[0]->getType(), VF); 5544 if (TTI->getNumberOfParts(VecTy) == VF) 5545 continue; 5546 for (unsigned I = NextInst; I < MaxInst; ++I) { 5547 unsigned OpsWidth = 0; 5548 5549 if (I + VF > MaxInst) 5550 OpsWidth = MaxInst - I; 5551 else 5552 OpsWidth = VF; 5553 5554 if (!isPowerOf2_32(OpsWidth) || OpsWidth < 2) 5555 break; 5556 5557 // Check that a previous iteration of this loop did not delete the Value. 5558 if (hasValueBeenRAUWed(VL, TrackValues, I, OpsWidth)) 5559 continue; 5560 5561 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << OpsWidth << " operations " 5562 << "\n"); 5563 ArrayRef<Value *> Ops = VL.slice(I, OpsWidth); 5564 5565 R.buildTree(Ops); 5566 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 5567 // TODO: check if we can allow reordering for more cases. 5568 if (AllowReorder && Order) { 5569 // TODO: reorder tree nodes without tree rebuilding. 5570 // Conceptually, there is nothing actually preventing us from trying to 5571 // reorder a larger list. In fact, we do exactly this when vectorizing 5572 // reductions. However, at this point, we only expect to get here when 5573 // there are exactly two operations. 5574 assert(Ops.size() == 2); 5575 Value *ReorderedOps[] = {Ops[1], Ops[0]}; 5576 R.buildTree(ReorderedOps, None); 5577 } 5578 if (R.isTreeTinyAndNotFullyVectorizable()) 5579 continue; 5580 5581 R.computeMinimumValueSizes(); 5582 int Cost = R.getTreeCost() - UserCost; 5583 CandidateFound = true; 5584 MinCost = std::min(MinCost, Cost); 5585 5586 if (Cost < -SLPCostThreshold) { 5587 LLVM_DEBUG(dbgs() << "SLP: Vectorizing list at cost:" << Cost << ".\n"); 5588 R.getORE()->emit(OptimizationRemark(SV_NAME, "VectorizedList", 5589 cast<Instruction>(Ops[0])) 5590 << "SLP vectorized with cost " << ore::NV("Cost", Cost) 5591 << " and with tree size " 5592 << ore::NV("TreeSize", R.getTreeSize())); 5593 5594 R.vectorizeTree(); 5595 // Move to the next bundle. 5596 I += VF - 1; 5597 NextInst = I + 1; 5598 Changed = true; 5599 } 5600 } 5601 } 5602 5603 if (!Changed && CandidateFound) { 5604 R.getORE()->emit([&]() { 5605 return OptimizationRemarkMissed(SV_NAME, "NotBeneficial", I0) 5606 << "List vectorization was possible but not beneficial with cost " 5607 << ore::NV("Cost", MinCost) << " >= " 5608 << ore::NV("Treshold", -SLPCostThreshold); 5609 }); 5610 } else if (!Changed) { 5611 R.getORE()->emit([&]() { 5612 return OptimizationRemarkMissed(SV_NAME, "NotPossible", I0) 5613 << "Cannot SLP vectorize list: vectorization was impossible" 5614 << " with available vectorization factors"; 5615 }); 5616 } 5617 return Changed; 5618 } 5619 5620 bool SLPVectorizerPass::tryToVectorize(Instruction *I, BoUpSLP &R) { 5621 if (!I) 5622 return false; 5623 5624 if (!isa<BinaryOperator>(I) && !isa<CmpInst>(I)) 5625 return false; 5626 5627 Value *P = I->getParent(); 5628 5629 // Vectorize in current basic block only. 5630 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 5631 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 5632 if (!Op0 || !Op1 || Op0->getParent() != P || Op1->getParent() != P) 5633 return false; 5634 5635 // Try to vectorize V. 5636 if (tryToVectorizePair(Op0, Op1, R)) 5637 return true; 5638 5639 auto *A = dyn_cast<BinaryOperator>(Op0); 5640 auto *B = dyn_cast<BinaryOperator>(Op1); 5641 // Try to skip B. 5642 if (B && B->hasOneUse()) { 5643 auto *B0 = dyn_cast<BinaryOperator>(B->getOperand(0)); 5644 auto *B1 = dyn_cast<BinaryOperator>(B->getOperand(1)); 5645 if (B0 && B0->getParent() == P && tryToVectorizePair(A, B0, R)) 5646 return true; 5647 if (B1 && B1->getParent() == P && tryToVectorizePair(A, B1, R)) 5648 return true; 5649 } 5650 5651 // Try to skip A. 5652 if (A && A->hasOneUse()) { 5653 auto *A0 = dyn_cast<BinaryOperator>(A->getOperand(0)); 5654 auto *A1 = dyn_cast<BinaryOperator>(A->getOperand(1)); 5655 if (A0 && A0->getParent() == P && tryToVectorizePair(A0, B, R)) 5656 return true; 5657 if (A1 && A1->getParent() == P && tryToVectorizePair(A1, B, R)) 5658 return true; 5659 } 5660 return false; 5661 } 5662 5663 /// Generate a shuffle mask to be used in a reduction tree. 5664 /// 5665 /// \param VecLen The length of the vector to be reduced. 5666 /// \param NumEltsToRdx The number of elements that should be reduced in the 5667 /// vector. 5668 /// \param IsPairwise Whether the reduction is a pairwise or splitting 5669 /// reduction. A pairwise reduction will generate a mask of 5670 /// <0,2,...> or <1,3,..> while a splitting reduction will generate 5671 /// <2,3, undef,undef> for a vector of 4 and NumElts = 2. 5672 /// \param IsLeft True will generate a mask of even elements, odd otherwise. 5673 static Value *createRdxShuffleMask(unsigned VecLen, unsigned NumEltsToRdx, 5674 bool IsPairwise, bool IsLeft, 5675 IRBuilder<> &Builder) { 5676 assert((IsPairwise || !IsLeft) && "Don't support a <0,1,undef,...> mask"); 5677 5678 SmallVector<Constant *, 32> ShuffleMask( 5679 VecLen, UndefValue::get(Builder.getInt32Ty())); 5680 5681 if (IsPairwise) 5682 // Build a mask of 0, 2, ... (left) or 1, 3, ... (right). 5683 for (unsigned i = 0; i != NumEltsToRdx; ++i) 5684 ShuffleMask[i] = Builder.getInt32(2 * i + !IsLeft); 5685 else 5686 // Move the upper half of the vector to the lower half. 5687 for (unsigned i = 0; i != NumEltsToRdx; ++i) 5688 ShuffleMask[i] = Builder.getInt32(NumEltsToRdx + i); 5689 5690 return ConstantVector::get(ShuffleMask); 5691 } 5692 5693 namespace { 5694 5695 /// Model horizontal reductions. 5696 /// 5697 /// A horizontal reduction is a tree of reduction operations (currently add and 5698 /// fadd) that has operations that can be put into a vector as its leaf. 5699 /// For example, this tree: 5700 /// 5701 /// mul mul mul mul 5702 /// \ / \ / 5703 /// + + 5704 /// \ / 5705 /// + 5706 /// This tree has "mul" as its reduced values and "+" as its reduction 5707 /// operations. A reduction might be feeding into a store or a binary operation 5708 /// feeding a phi. 5709 /// ... 5710 /// \ / 5711 /// + 5712 /// | 5713 /// phi += 5714 /// 5715 /// Or: 5716 /// ... 5717 /// \ / 5718 /// + 5719 /// | 5720 /// *p = 5721 /// 5722 class HorizontalReduction { 5723 using ReductionOpsType = SmallVector<Value *, 16>; 5724 using ReductionOpsListType = SmallVector<ReductionOpsType, 2>; 5725 ReductionOpsListType ReductionOps; 5726 SmallVector<Value *, 32> ReducedVals; 5727 // Use map vector to make stable output. 5728 MapVector<Instruction *, Value *> ExtraArgs; 5729 5730 /// Kind of the reduction data. 5731 enum ReductionKind { 5732 RK_None, /// Not a reduction. 5733 RK_Arithmetic, /// Binary reduction data. 5734 RK_Min, /// Minimum reduction data. 5735 RK_UMin, /// Unsigned minimum reduction data. 5736 RK_Max, /// Maximum reduction data. 5737 RK_UMax, /// Unsigned maximum reduction data. 5738 }; 5739 5740 /// Contains info about operation, like its opcode, left and right operands. 5741 class OperationData { 5742 /// Opcode of the instruction. 5743 unsigned Opcode = 0; 5744 5745 /// Left operand of the reduction operation. 5746 Value *LHS = nullptr; 5747 5748 /// Right operand of the reduction operation. 5749 Value *RHS = nullptr; 5750 5751 /// Kind of the reduction operation. 5752 ReductionKind Kind = RK_None; 5753 5754 /// True if float point min/max reduction has no NaNs. 5755 bool NoNaN = false; 5756 5757 /// Checks if the reduction operation can be vectorized. 5758 bool isVectorizable() const { 5759 return LHS && RHS && 5760 // We currently only support add/mul/logical && min/max reductions. 5761 ((Kind == RK_Arithmetic && 5762 (Opcode == Instruction::Add || Opcode == Instruction::FAdd || 5763 Opcode == Instruction::Mul || Opcode == Instruction::FMul || 5764 Opcode == Instruction::And || Opcode == Instruction::Or || 5765 Opcode == Instruction::Xor)) || 5766 ((Opcode == Instruction::ICmp || Opcode == Instruction::FCmp) && 5767 (Kind == RK_Min || Kind == RK_Max)) || 5768 (Opcode == Instruction::ICmp && 5769 (Kind == RK_UMin || Kind == RK_UMax))); 5770 } 5771 5772 /// Creates reduction operation with the current opcode. 5773 Value *createOp(IRBuilder<> &Builder, const Twine &Name) const { 5774 assert(isVectorizable() && 5775 "Expected add|fadd or min/max reduction operation."); 5776 Value *Cmp; 5777 switch (Kind) { 5778 case RK_Arithmetic: 5779 return Builder.CreateBinOp((Instruction::BinaryOps)Opcode, LHS, RHS, 5780 Name); 5781 case RK_Min: 5782 Cmp = Opcode == Instruction::ICmp ? Builder.CreateICmpSLT(LHS, RHS) 5783 : Builder.CreateFCmpOLT(LHS, RHS); 5784 break; 5785 case RK_Max: 5786 Cmp = Opcode == Instruction::ICmp ? Builder.CreateICmpSGT(LHS, RHS) 5787 : Builder.CreateFCmpOGT(LHS, RHS); 5788 break; 5789 case RK_UMin: 5790 assert(Opcode == Instruction::ICmp && "Expected integer types."); 5791 Cmp = Builder.CreateICmpULT(LHS, RHS); 5792 break; 5793 case RK_UMax: 5794 assert(Opcode == Instruction::ICmp && "Expected integer types."); 5795 Cmp = Builder.CreateICmpUGT(LHS, RHS); 5796 break; 5797 case RK_None: 5798 llvm_unreachable("Unknown reduction operation."); 5799 } 5800 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 5801 } 5802 5803 public: 5804 explicit OperationData() = default; 5805 5806 /// Construction for reduced values. They are identified by opcode only and 5807 /// don't have associated LHS/RHS values. 5808 explicit OperationData(Value *V) { 5809 if (auto *I = dyn_cast<Instruction>(V)) 5810 Opcode = I->getOpcode(); 5811 } 5812 5813 /// Constructor for reduction operations with opcode and its left and 5814 /// right operands. 5815 OperationData(unsigned Opcode, Value *LHS, Value *RHS, ReductionKind Kind, 5816 bool NoNaN = false) 5817 : Opcode(Opcode), LHS(LHS), RHS(RHS), Kind(Kind), NoNaN(NoNaN) { 5818 assert(Kind != RK_None && "One of the reduction operations is expected."); 5819 } 5820 5821 explicit operator bool() const { return Opcode; } 5822 5823 /// Get the index of the first operand. 5824 unsigned getFirstOperandIndex() const { 5825 assert(!!*this && "The opcode is not set."); 5826 switch (Kind) { 5827 case RK_Min: 5828 case RK_UMin: 5829 case RK_Max: 5830 case RK_UMax: 5831 return 1; 5832 case RK_Arithmetic: 5833 case RK_None: 5834 break; 5835 } 5836 return 0; 5837 } 5838 5839 /// Total number of operands in the reduction operation. 5840 unsigned getNumberOfOperands() const { 5841 assert(Kind != RK_None && !!*this && LHS && RHS && 5842 "Expected reduction operation."); 5843 switch (Kind) { 5844 case RK_Arithmetic: 5845 return 2; 5846 case RK_Min: 5847 case RK_UMin: 5848 case RK_Max: 5849 case RK_UMax: 5850 return 3; 5851 case RK_None: 5852 break; 5853 } 5854 llvm_unreachable("Reduction kind is not set"); 5855 } 5856 5857 /// Checks if the operation has the same parent as \p P. 5858 bool hasSameParent(Instruction *I, Value *P, bool IsRedOp) const { 5859 assert(Kind != RK_None && !!*this && LHS && RHS && 5860 "Expected reduction operation."); 5861 if (!IsRedOp) 5862 return I->getParent() == P; 5863 switch (Kind) { 5864 case RK_Arithmetic: 5865 // Arithmetic reduction operation must be used once only. 5866 return I->getParent() == P; 5867 case RK_Min: 5868 case RK_UMin: 5869 case RK_Max: 5870 case RK_UMax: { 5871 // SelectInst must be used twice while the condition op must have single 5872 // use only. 5873 auto *Cmp = cast<Instruction>(cast<SelectInst>(I)->getCondition()); 5874 return I->getParent() == P && Cmp && Cmp->getParent() == P; 5875 } 5876 case RK_None: 5877 break; 5878 } 5879 llvm_unreachable("Reduction kind is not set"); 5880 } 5881 /// Expected number of uses for reduction operations/reduced values. 5882 bool hasRequiredNumberOfUses(Instruction *I, bool IsReductionOp) const { 5883 assert(Kind != RK_None && !!*this && LHS && RHS && 5884 "Expected reduction operation."); 5885 switch (Kind) { 5886 case RK_Arithmetic: 5887 return I->hasOneUse(); 5888 case RK_Min: 5889 case RK_UMin: 5890 case RK_Max: 5891 case RK_UMax: 5892 return I->hasNUses(2) && 5893 (!IsReductionOp || 5894 cast<SelectInst>(I)->getCondition()->hasOneUse()); 5895 case RK_None: 5896 break; 5897 } 5898 llvm_unreachable("Reduction kind is not set"); 5899 } 5900 5901 /// Initializes the list of reduction operations. 5902 void initReductionOps(ReductionOpsListType &ReductionOps) { 5903 assert(Kind != RK_None && !!*this && LHS && RHS && 5904 "Expected reduction operation."); 5905 switch (Kind) { 5906 case RK_Arithmetic: 5907 ReductionOps.assign(1, ReductionOpsType()); 5908 break; 5909 case RK_Min: 5910 case RK_UMin: 5911 case RK_Max: 5912 case RK_UMax: 5913 ReductionOps.assign(2, ReductionOpsType()); 5914 break; 5915 case RK_None: 5916 llvm_unreachable("Reduction kind is not set"); 5917 } 5918 } 5919 /// Add all reduction operations for the reduction instruction \p I. 5920 void addReductionOps(Instruction *I, ReductionOpsListType &ReductionOps) { 5921 assert(Kind != RK_None && !!*this && LHS && RHS && 5922 "Expected reduction operation."); 5923 switch (Kind) { 5924 case RK_Arithmetic: 5925 ReductionOps[0].emplace_back(I); 5926 break; 5927 case RK_Min: 5928 case RK_UMin: 5929 case RK_Max: 5930 case RK_UMax: 5931 ReductionOps[0].emplace_back(cast<SelectInst>(I)->getCondition()); 5932 ReductionOps[1].emplace_back(I); 5933 break; 5934 case RK_None: 5935 llvm_unreachable("Reduction kind is not set"); 5936 } 5937 } 5938 5939 /// Checks if instruction is associative and can be vectorized. 5940 bool isAssociative(Instruction *I) const { 5941 assert(Kind != RK_None && *this && LHS && RHS && 5942 "Expected reduction operation."); 5943 switch (Kind) { 5944 case RK_Arithmetic: 5945 return I->isAssociative(); 5946 case RK_Min: 5947 case RK_Max: 5948 return Opcode == Instruction::ICmp || 5949 cast<Instruction>(I->getOperand(0))->isFast(); 5950 case RK_UMin: 5951 case RK_UMax: 5952 assert(Opcode == Instruction::ICmp && 5953 "Only integer compare operation is expected."); 5954 return true; 5955 case RK_None: 5956 break; 5957 } 5958 llvm_unreachable("Reduction kind is not set"); 5959 } 5960 5961 /// Checks if the reduction operation can be vectorized. 5962 bool isVectorizable(Instruction *I) const { 5963 return isVectorizable() && isAssociative(I); 5964 } 5965 5966 /// Checks if two operation data are both a reduction op or both a reduced 5967 /// value. 5968 bool operator==(const OperationData &OD) { 5969 assert(((Kind != OD.Kind) || ((!LHS == !OD.LHS) && (!RHS == !OD.RHS))) && 5970 "One of the comparing operations is incorrect."); 5971 return this == &OD || (Kind == OD.Kind && Opcode == OD.Opcode); 5972 } 5973 bool operator!=(const OperationData &OD) { return !(*this == OD); } 5974 void clear() { 5975 Opcode = 0; 5976 LHS = nullptr; 5977 RHS = nullptr; 5978 Kind = RK_None; 5979 NoNaN = false; 5980 } 5981 5982 /// Get the opcode of the reduction operation. 5983 unsigned getOpcode() const { 5984 assert(isVectorizable() && "Expected vectorizable operation."); 5985 return Opcode; 5986 } 5987 5988 /// Get kind of reduction data. 5989 ReductionKind getKind() const { return Kind; } 5990 Value *getLHS() const { return LHS; } 5991 Value *getRHS() const { return RHS; } 5992 Type *getConditionType() const { 5993 switch (Kind) { 5994 case RK_Arithmetic: 5995 return nullptr; 5996 case RK_Min: 5997 case RK_Max: 5998 case RK_UMin: 5999 case RK_UMax: 6000 return CmpInst::makeCmpResultType(LHS->getType()); 6001 case RK_None: 6002 break; 6003 } 6004 llvm_unreachable("Reduction kind is not set"); 6005 } 6006 6007 /// Creates reduction operation with the current opcode with the IR flags 6008 /// from \p ReductionOps. 6009 Value *createOp(IRBuilder<> &Builder, const Twine &Name, 6010 const ReductionOpsListType &ReductionOps) const { 6011 assert(isVectorizable() && 6012 "Expected add|fadd or min/max reduction operation."); 6013 auto *Op = createOp(Builder, Name); 6014 switch (Kind) { 6015 case RK_Arithmetic: 6016 propagateIRFlags(Op, ReductionOps[0]); 6017 return Op; 6018 case RK_Min: 6019 case RK_Max: 6020 case RK_UMin: 6021 case RK_UMax: 6022 if (auto *SI = dyn_cast<SelectInst>(Op)) 6023 propagateIRFlags(SI->getCondition(), ReductionOps[0]); 6024 propagateIRFlags(Op, ReductionOps[1]); 6025 return Op; 6026 case RK_None: 6027 break; 6028 } 6029 llvm_unreachable("Unknown reduction operation."); 6030 } 6031 /// Creates reduction operation with the current opcode with the IR flags 6032 /// from \p I. 6033 Value *createOp(IRBuilder<> &Builder, const Twine &Name, 6034 Instruction *I) const { 6035 assert(isVectorizable() && 6036 "Expected add|fadd or min/max reduction operation."); 6037 auto *Op = createOp(Builder, Name); 6038 switch (Kind) { 6039 case RK_Arithmetic: 6040 propagateIRFlags(Op, I); 6041 return Op; 6042 case RK_Min: 6043 case RK_Max: 6044 case RK_UMin: 6045 case RK_UMax: 6046 if (auto *SI = dyn_cast<SelectInst>(Op)) { 6047 propagateIRFlags(SI->getCondition(), 6048 cast<SelectInst>(I)->getCondition()); 6049 } 6050 propagateIRFlags(Op, I); 6051 return Op; 6052 case RK_None: 6053 break; 6054 } 6055 llvm_unreachable("Unknown reduction operation."); 6056 } 6057 6058 TargetTransformInfo::ReductionFlags getFlags() const { 6059 TargetTransformInfo::ReductionFlags Flags; 6060 Flags.NoNaN = NoNaN; 6061 switch (Kind) { 6062 case RK_Arithmetic: 6063 break; 6064 case RK_Min: 6065 Flags.IsSigned = Opcode == Instruction::ICmp; 6066 Flags.IsMaxOp = false; 6067 break; 6068 case RK_Max: 6069 Flags.IsSigned = Opcode == Instruction::ICmp; 6070 Flags.IsMaxOp = true; 6071 break; 6072 case RK_UMin: 6073 Flags.IsSigned = false; 6074 Flags.IsMaxOp = false; 6075 break; 6076 case RK_UMax: 6077 Flags.IsSigned = false; 6078 Flags.IsMaxOp = true; 6079 break; 6080 case RK_None: 6081 llvm_unreachable("Reduction kind is not set"); 6082 } 6083 return Flags; 6084 } 6085 }; 6086 6087 WeakTrackingVH ReductionRoot; 6088 6089 /// The operation data of the reduction operation. 6090 OperationData ReductionData; 6091 6092 /// The operation data of the values we perform a reduction on. 6093 OperationData ReducedValueData; 6094 6095 /// Should we model this reduction as a pairwise reduction tree or a tree that 6096 /// splits the vector in halves and adds those halves. 6097 bool IsPairwiseReduction = false; 6098 6099 /// Checks if the ParentStackElem.first should be marked as a reduction 6100 /// operation with an extra argument or as extra argument itself. 6101 void markExtraArg(std::pair<Instruction *, unsigned> &ParentStackElem, 6102 Value *ExtraArg) { 6103 if (ExtraArgs.count(ParentStackElem.first)) { 6104 ExtraArgs[ParentStackElem.first] = nullptr; 6105 // We ran into something like: 6106 // ParentStackElem.first = ExtraArgs[ParentStackElem.first] + ExtraArg. 6107 // The whole ParentStackElem.first should be considered as an extra value 6108 // in this case. 6109 // Do not perform analysis of remaining operands of ParentStackElem.first 6110 // instruction, this whole instruction is an extra argument. 6111 ParentStackElem.second = ParentStackElem.first->getNumOperands(); 6112 } else { 6113 // We ran into something like: 6114 // ParentStackElem.first += ... + ExtraArg + ... 6115 ExtraArgs[ParentStackElem.first] = ExtraArg; 6116 } 6117 } 6118 6119 static OperationData getOperationData(Value *V) { 6120 if (!V) 6121 return OperationData(); 6122 6123 Value *LHS; 6124 Value *RHS; 6125 if (m_BinOp(m_Value(LHS), m_Value(RHS)).match(V)) { 6126 return OperationData(cast<BinaryOperator>(V)->getOpcode(), LHS, RHS, 6127 RK_Arithmetic); 6128 } 6129 if (auto *Select = dyn_cast<SelectInst>(V)) { 6130 // Look for a min/max pattern. 6131 if (m_UMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 6132 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMin); 6133 } else if (m_SMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 6134 return OperationData(Instruction::ICmp, LHS, RHS, RK_Min); 6135 } else if (m_OrdFMin(m_Value(LHS), m_Value(RHS)).match(Select) || 6136 m_UnordFMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 6137 return OperationData( 6138 Instruction::FCmp, LHS, RHS, RK_Min, 6139 cast<Instruction>(Select->getCondition())->hasNoNaNs()); 6140 } else if (m_UMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 6141 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMax); 6142 } else if (m_SMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 6143 return OperationData(Instruction::ICmp, LHS, RHS, RK_Max); 6144 } else if (m_OrdFMax(m_Value(LHS), m_Value(RHS)).match(Select) || 6145 m_UnordFMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 6146 return OperationData( 6147 Instruction::FCmp, LHS, RHS, RK_Max, 6148 cast<Instruction>(Select->getCondition())->hasNoNaNs()); 6149 } else { 6150 // Try harder: look for min/max pattern based on instructions producing 6151 // same values such as: select ((cmp Inst1, Inst2), Inst1, Inst2). 6152 // During the intermediate stages of SLP, it's very common to have 6153 // pattern like this (since optimizeGatherSequence is run only once 6154 // at the end): 6155 // %1 = extractelement <2 x i32> %a, i32 0 6156 // %2 = extractelement <2 x i32> %a, i32 1 6157 // %cond = icmp sgt i32 %1, %2 6158 // %3 = extractelement <2 x i32> %a, i32 0 6159 // %4 = extractelement <2 x i32> %a, i32 1 6160 // %select = select i1 %cond, i32 %3, i32 %4 6161 CmpInst::Predicate Pred; 6162 Instruction *L1; 6163 Instruction *L2; 6164 6165 LHS = Select->getTrueValue(); 6166 RHS = Select->getFalseValue(); 6167 Value *Cond = Select->getCondition(); 6168 6169 // TODO: Support inverse predicates. 6170 if (match(Cond, m_Cmp(Pred, m_Specific(LHS), m_Instruction(L2)))) { 6171 if (!isa<ExtractElementInst>(RHS) || 6172 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6173 return OperationData(V); 6174 } else if (match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Specific(RHS)))) { 6175 if (!isa<ExtractElementInst>(LHS) || 6176 !L1->isIdenticalTo(cast<Instruction>(LHS))) 6177 return OperationData(V); 6178 } else { 6179 if (!isa<ExtractElementInst>(LHS) || !isa<ExtractElementInst>(RHS)) 6180 return OperationData(V); 6181 if (!match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Instruction(L2))) || 6182 !L1->isIdenticalTo(cast<Instruction>(LHS)) || 6183 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6184 return OperationData(V); 6185 } 6186 switch (Pred) { 6187 default: 6188 return OperationData(V); 6189 6190 case CmpInst::ICMP_ULT: 6191 case CmpInst::ICMP_ULE: 6192 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMin); 6193 6194 case CmpInst::ICMP_SLT: 6195 case CmpInst::ICMP_SLE: 6196 return OperationData(Instruction::ICmp, LHS, RHS, RK_Min); 6197 6198 case CmpInst::FCMP_OLT: 6199 case CmpInst::FCMP_OLE: 6200 case CmpInst::FCMP_ULT: 6201 case CmpInst::FCMP_ULE: 6202 return OperationData(Instruction::FCmp, LHS, RHS, RK_Min, 6203 cast<Instruction>(Cond)->hasNoNaNs()); 6204 6205 case CmpInst::ICMP_UGT: 6206 case CmpInst::ICMP_UGE: 6207 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMax); 6208 6209 case CmpInst::ICMP_SGT: 6210 case CmpInst::ICMP_SGE: 6211 return OperationData(Instruction::ICmp, LHS, RHS, RK_Max); 6212 6213 case CmpInst::FCMP_OGT: 6214 case CmpInst::FCMP_OGE: 6215 case CmpInst::FCMP_UGT: 6216 case CmpInst::FCMP_UGE: 6217 return OperationData(Instruction::FCmp, LHS, RHS, RK_Max, 6218 cast<Instruction>(Cond)->hasNoNaNs()); 6219 } 6220 } 6221 } 6222 return OperationData(V); 6223 } 6224 6225 public: 6226 HorizontalReduction() = default; 6227 6228 /// Try to find a reduction tree. 6229 bool matchAssociativeReduction(PHINode *Phi, Instruction *B) { 6230 assert((!Phi || is_contained(Phi->operands(), B)) && 6231 "Thi phi needs to use the binary operator"); 6232 6233 ReductionData = getOperationData(B); 6234 6235 // We could have a initial reductions that is not an add. 6236 // r *= v1 + v2 + v3 + v4 6237 // In such a case start looking for a tree rooted in the first '+'. 6238 if (Phi) { 6239 if (ReductionData.getLHS() == Phi) { 6240 Phi = nullptr; 6241 B = dyn_cast<Instruction>(ReductionData.getRHS()); 6242 ReductionData = getOperationData(B); 6243 } else if (ReductionData.getRHS() == Phi) { 6244 Phi = nullptr; 6245 B = dyn_cast<Instruction>(ReductionData.getLHS()); 6246 ReductionData = getOperationData(B); 6247 } 6248 } 6249 6250 if (!ReductionData.isVectorizable(B)) 6251 return false; 6252 6253 Type *Ty = B->getType(); 6254 if (!isValidElementType(Ty)) 6255 return false; 6256 if (!Ty->isIntOrIntVectorTy() && !Ty->isFPOrFPVectorTy()) 6257 return false; 6258 6259 ReducedValueData.clear(); 6260 ReductionRoot = B; 6261 6262 // Post order traverse the reduction tree starting at B. We only handle true 6263 // trees containing only binary operators. 6264 SmallVector<std::pair<Instruction *, unsigned>, 32> Stack; 6265 Stack.push_back(std::make_pair(B, ReductionData.getFirstOperandIndex())); 6266 ReductionData.initReductionOps(ReductionOps); 6267 while (!Stack.empty()) { 6268 Instruction *TreeN = Stack.back().first; 6269 unsigned EdgeToVist = Stack.back().second++; 6270 OperationData OpData = getOperationData(TreeN); 6271 bool IsReducedValue = OpData != ReductionData; 6272 6273 // Postorder vist. 6274 if (IsReducedValue || EdgeToVist == OpData.getNumberOfOperands()) { 6275 if (IsReducedValue) 6276 ReducedVals.push_back(TreeN); 6277 else { 6278 auto I = ExtraArgs.find(TreeN); 6279 if (I != ExtraArgs.end() && !I->second) { 6280 // Check if TreeN is an extra argument of its parent operation. 6281 if (Stack.size() <= 1) { 6282 // TreeN can't be an extra argument as it is a root reduction 6283 // operation. 6284 return false; 6285 } 6286 // Yes, TreeN is an extra argument, do not add it to a list of 6287 // reduction operations. 6288 // Stack[Stack.size() - 2] always points to the parent operation. 6289 markExtraArg(Stack[Stack.size() - 2], TreeN); 6290 ExtraArgs.erase(TreeN); 6291 } else 6292 ReductionData.addReductionOps(TreeN, ReductionOps); 6293 } 6294 // Retract. 6295 Stack.pop_back(); 6296 continue; 6297 } 6298 6299 // Visit left or right. 6300 Value *NextV = TreeN->getOperand(EdgeToVist); 6301 if (NextV != Phi) { 6302 auto *I = dyn_cast<Instruction>(NextV); 6303 OpData = getOperationData(I); 6304 // Continue analysis if the next operand is a reduction operation or 6305 // (possibly) a reduced value. If the reduced value opcode is not set, 6306 // the first met operation != reduction operation is considered as the 6307 // reduced value class. 6308 if (I && (!ReducedValueData || OpData == ReducedValueData || 6309 OpData == ReductionData)) { 6310 const bool IsReductionOperation = OpData == ReductionData; 6311 // Only handle trees in the current basic block. 6312 if (!ReductionData.hasSameParent(I, B->getParent(), 6313 IsReductionOperation)) { 6314 // I is an extra argument for TreeN (its parent operation). 6315 markExtraArg(Stack.back(), I); 6316 continue; 6317 } 6318 6319 // Each tree node needs to have minimal number of users except for the 6320 // ultimate reduction. 6321 if (!ReductionData.hasRequiredNumberOfUses(I, 6322 OpData == ReductionData) && 6323 I != B) { 6324 // I is an extra argument for TreeN (its parent operation). 6325 markExtraArg(Stack.back(), I); 6326 continue; 6327 } 6328 6329 if (IsReductionOperation) { 6330 // We need to be able to reassociate the reduction operations. 6331 if (!OpData.isAssociative(I)) { 6332 // I is an extra argument for TreeN (its parent operation). 6333 markExtraArg(Stack.back(), I); 6334 continue; 6335 } 6336 } else if (ReducedValueData && 6337 ReducedValueData != OpData) { 6338 // Make sure that the opcodes of the operations that we are going to 6339 // reduce match. 6340 // I is an extra argument for TreeN (its parent operation). 6341 markExtraArg(Stack.back(), I); 6342 continue; 6343 } else if (!ReducedValueData) 6344 ReducedValueData = OpData; 6345 6346 Stack.push_back(std::make_pair(I, OpData.getFirstOperandIndex())); 6347 continue; 6348 } 6349 } 6350 // NextV is an extra argument for TreeN (its parent operation). 6351 markExtraArg(Stack.back(), NextV); 6352 } 6353 return true; 6354 } 6355 6356 /// Attempt to vectorize the tree found by 6357 /// matchAssociativeReduction. 6358 bool tryToReduce(BoUpSLP &V, TargetTransformInfo *TTI) { 6359 if (ReducedVals.empty()) 6360 return false; 6361 6362 // If there is a sufficient number of reduction values, reduce 6363 // to a nearby power-of-2. Can safely generate oversized 6364 // vectors and rely on the backend to split them to legal sizes. 6365 unsigned NumReducedVals = ReducedVals.size(); 6366 if (NumReducedVals < 4) 6367 return false; 6368 6369 unsigned ReduxWidth = PowerOf2Floor(NumReducedVals); 6370 6371 Value *VectorizedTree = nullptr; 6372 6373 // FIXME: Fast-math-flags should be set based on the instructions in the 6374 // reduction (not all of 'fast' are required). 6375 IRBuilder<> Builder(cast<Instruction>(ReductionRoot)); 6376 FastMathFlags Unsafe; 6377 Unsafe.setFast(); 6378 Builder.setFastMathFlags(Unsafe); 6379 unsigned i = 0; 6380 6381 BoUpSLP::ExtraValueToDebugLocsMap ExternallyUsedValues; 6382 // The same extra argument may be used several time, so log each attempt 6383 // to use it. 6384 for (auto &Pair : ExtraArgs) { 6385 assert(Pair.first && "DebugLoc must be set."); 6386 ExternallyUsedValues[Pair.second].push_back(Pair.first); 6387 } 6388 // The reduction root is used as the insertion point for new instructions, 6389 // so set it as externally used to prevent it from being deleted. 6390 ExternallyUsedValues[ReductionRoot]; 6391 SmallVector<Value *, 16> IgnoreList; 6392 for (auto &V : ReductionOps) 6393 IgnoreList.append(V.begin(), V.end()); 6394 while (i < NumReducedVals - ReduxWidth + 1 && ReduxWidth > 2) { 6395 auto VL = makeArrayRef(&ReducedVals[i], ReduxWidth); 6396 V.buildTree(VL, ExternallyUsedValues, IgnoreList); 6397 Optional<ArrayRef<unsigned>> Order = V.bestOrder(); 6398 // TODO: Handle orders of size less than number of elements in the vector. 6399 if (Order && Order->size() == VL.size()) { 6400 // TODO: reorder tree nodes without tree rebuilding. 6401 SmallVector<Value *, 4> ReorderedOps(VL.size()); 6402 llvm::transform(*Order, ReorderedOps.begin(), 6403 [VL](const unsigned Idx) { return VL[Idx]; }); 6404 V.buildTree(ReorderedOps, ExternallyUsedValues, IgnoreList); 6405 } 6406 if (V.isTreeTinyAndNotFullyVectorizable()) 6407 break; 6408 6409 V.computeMinimumValueSizes(); 6410 6411 // Estimate cost. 6412 int TreeCost = V.getTreeCost(); 6413 int ReductionCost = getReductionCost(TTI, ReducedVals[i], ReduxWidth); 6414 int Cost = TreeCost + ReductionCost; 6415 if (Cost >= -SLPCostThreshold) { 6416 V.getORE()->emit([&]() { 6417 return OptimizationRemarkMissed( 6418 SV_NAME, "HorSLPNotBeneficial", cast<Instruction>(VL[0])) 6419 << "Vectorizing horizontal reduction is possible" 6420 << "but not beneficial with cost " 6421 << ore::NV("Cost", Cost) << " and threshold " 6422 << ore::NV("Threshold", -SLPCostThreshold); 6423 }); 6424 break; 6425 } 6426 6427 LLVM_DEBUG(dbgs() << "SLP: Vectorizing horizontal reduction at cost:" 6428 << Cost << ". (HorRdx)\n"); 6429 V.getORE()->emit([&]() { 6430 return OptimizationRemark( 6431 SV_NAME, "VectorizedHorizontalReduction", cast<Instruction>(VL[0])) 6432 << "Vectorized horizontal reduction with cost " 6433 << ore::NV("Cost", Cost) << " and with tree size " 6434 << ore::NV("TreeSize", V.getTreeSize()); 6435 }); 6436 6437 // Vectorize a tree. 6438 DebugLoc Loc = cast<Instruction>(ReducedVals[i])->getDebugLoc(); 6439 Value *VectorizedRoot = V.vectorizeTree(ExternallyUsedValues); 6440 6441 // Emit a reduction. 6442 Builder.SetInsertPoint(cast<Instruction>(ReductionRoot)); 6443 Value *ReducedSubTree = 6444 emitReduction(VectorizedRoot, Builder, ReduxWidth, TTI); 6445 if (VectorizedTree) { 6446 Builder.SetCurrentDebugLocation(Loc); 6447 OperationData VectReductionData(ReductionData.getOpcode(), 6448 VectorizedTree, ReducedSubTree, 6449 ReductionData.getKind()); 6450 VectorizedTree = 6451 VectReductionData.createOp(Builder, "op.rdx", ReductionOps); 6452 } else 6453 VectorizedTree = ReducedSubTree; 6454 i += ReduxWidth; 6455 ReduxWidth = PowerOf2Floor(NumReducedVals - i); 6456 } 6457 6458 if (VectorizedTree) { 6459 // Finish the reduction. 6460 for (; i < NumReducedVals; ++i) { 6461 auto *I = cast<Instruction>(ReducedVals[i]); 6462 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 6463 OperationData VectReductionData(ReductionData.getOpcode(), 6464 VectorizedTree, I, 6465 ReductionData.getKind()); 6466 VectorizedTree = VectReductionData.createOp(Builder, "", ReductionOps); 6467 } 6468 for (auto &Pair : ExternallyUsedValues) { 6469 // Add each externally used value to the final reduction. 6470 for (auto *I : Pair.second) { 6471 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 6472 OperationData VectReductionData(ReductionData.getOpcode(), 6473 VectorizedTree, Pair.first, 6474 ReductionData.getKind()); 6475 VectorizedTree = VectReductionData.createOp(Builder, "op.extra", I); 6476 } 6477 } 6478 // Update users. 6479 ReductionRoot->replaceAllUsesWith(VectorizedTree); 6480 } 6481 return VectorizedTree != nullptr; 6482 } 6483 6484 unsigned numReductionValues() const { 6485 return ReducedVals.size(); 6486 } 6487 6488 private: 6489 /// Calculate the cost of a reduction. 6490 int getReductionCost(TargetTransformInfo *TTI, Value *FirstReducedVal, 6491 unsigned ReduxWidth) { 6492 Type *ScalarTy = FirstReducedVal->getType(); 6493 Type *VecTy = VectorType::get(ScalarTy, ReduxWidth); 6494 6495 int PairwiseRdxCost; 6496 int SplittingRdxCost; 6497 switch (ReductionData.getKind()) { 6498 case RK_Arithmetic: 6499 PairwiseRdxCost = 6500 TTI->getArithmeticReductionCost(ReductionData.getOpcode(), VecTy, 6501 /*IsPairwiseForm=*/true); 6502 SplittingRdxCost = 6503 TTI->getArithmeticReductionCost(ReductionData.getOpcode(), VecTy, 6504 /*IsPairwiseForm=*/false); 6505 break; 6506 case RK_Min: 6507 case RK_Max: 6508 case RK_UMin: 6509 case RK_UMax: { 6510 Type *VecCondTy = CmpInst::makeCmpResultType(VecTy); 6511 bool IsUnsigned = ReductionData.getKind() == RK_UMin || 6512 ReductionData.getKind() == RK_UMax; 6513 PairwiseRdxCost = 6514 TTI->getMinMaxReductionCost(VecTy, VecCondTy, 6515 /*IsPairwiseForm=*/true, IsUnsigned); 6516 SplittingRdxCost = 6517 TTI->getMinMaxReductionCost(VecTy, VecCondTy, 6518 /*IsPairwiseForm=*/false, IsUnsigned); 6519 break; 6520 } 6521 case RK_None: 6522 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 6523 } 6524 6525 IsPairwiseReduction = PairwiseRdxCost < SplittingRdxCost; 6526 int VecReduxCost = IsPairwiseReduction ? PairwiseRdxCost : SplittingRdxCost; 6527 6528 int ScalarReduxCost; 6529 switch (ReductionData.getKind()) { 6530 case RK_Arithmetic: 6531 ScalarReduxCost = 6532 TTI->getArithmeticInstrCost(ReductionData.getOpcode(), ScalarTy); 6533 break; 6534 case RK_Min: 6535 case RK_Max: 6536 case RK_UMin: 6537 case RK_UMax: 6538 ScalarReduxCost = 6539 TTI->getCmpSelInstrCost(ReductionData.getOpcode(), ScalarTy) + 6540 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 6541 CmpInst::makeCmpResultType(ScalarTy)); 6542 break; 6543 case RK_None: 6544 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 6545 } 6546 ScalarReduxCost *= (ReduxWidth - 1); 6547 6548 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << VecReduxCost - ScalarReduxCost 6549 << " for reduction that starts with " << *FirstReducedVal 6550 << " (It is a " 6551 << (IsPairwiseReduction ? "pairwise" : "splitting") 6552 << " reduction)\n"); 6553 6554 return VecReduxCost - ScalarReduxCost; 6555 } 6556 6557 /// Emit a horizontal reduction of the vectorized value. 6558 Value *emitReduction(Value *VectorizedValue, IRBuilder<> &Builder, 6559 unsigned ReduxWidth, const TargetTransformInfo *TTI) { 6560 assert(VectorizedValue && "Need to have a vectorized tree node"); 6561 assert(isPowerOf2_32(ReduxWidth) && 6562 "We only handle power-of-two reductions for now"); 6563 6564 if (!IsPairwiseReduction) { 6565 // FIXME: The builder should use an FMF guard. It should not be hard-coded 6566 // to 'fast'. 6567 assert(Builder.getFastMathFlags().isFast() && "Expected 'fast' FMF"); 6568 return createSimpleTargetReduction( 6569 Builder, TTI, ReductionData.getOpcode(), VectorizedValue, 6570 ReductionData.getFlags(), ReductionOps.back()); 6571 } 6572 6573 Value *TmpVec = VectorizedValue; 6574 for (unsigned i = ReduxWidth / 2; i != 0; i >>= 1) { 6575 Value *LeftMask = 6576 createRdxShuffleMask(ReduxWidth, i, true, true, Builder); 6577 Value *RightMask = 6578 createRdxShuffleMask(ReduxWidth, i, true, false, Builder); 6579 6580 Value *LeftShuf = Builder.CreateShuffleVector( 6581 TmpVec, UndefValue::get(TmpVec->getType()), LeftMask, "rdx.shuf.l"); 6582 Value *RightShuf = Builder.CreateShuffleVector( 6583 TmpVec, UndefValue::get(TmpVec->getType()), (RightMask), 6584 "rdx.shuf.r"); 6585 OperationData VectReductionData(ReductionData.getOpcode(), LeftShuf, 6586 RightShuf, ReductionData.getKind()); 6587 TmpVec = VectReductionData.createOp(Builder, "op.rdx", ReductionOps); 6588 } 6589 6590 // The result is in the first element of the vector. 6591 return Builder.CreateExtractElement(TmpVec, Builder.getInt32(0)); 6592 } 6593 }; 6594 6595 } // end anonymous namespace 6596 6597 /// Recognize construction of vectors like 6598 /// %ra = insertelement <4 x float> undef, float %s0, i32 0 6599 /// %rb = insertelement <4 x float> %ra, float %s1, i32 1 6600 /// %rc = insertelement <4 x float> %rb, float %s2, i32 2 6601 /// %rd = insertelement <4 x float> %rc, float %s3, i32 3 6602 /// starting from the last insertelement instruction. 6603 /// 6604 /// Returns true if it matches 6605 static bool findBuildVector(InsertElementInst *LastInsertElem, 6606 TargetTransformInfo *TTI, 6607 SmallVectorImpl<Value *> &BuildVectorOpds, 6608 int &UserCost) { 6609 UserCost = 0; 6610 Value *V = nullptr; 6611 do { 6612 if (auto *CI = dyn_cast<ConstantInt>(LastInsertElem->getOperand(2))) { 6613 UserCost += TTI->getVectorInstrCost(Instruction::InsertElement, 6614 LastInsertElem->getType(), 6615 CI->getZExtValue()); 6616 } 6617 BuildVectorOpds.push_back(LastInsertElem->getOperand(1)); 6618 V = LastInsertElem->getOperand(0); 6619 if (isa<UndefValue>(V)) 6620 break; 6621 LastInsertElem = dyn_cast<InsertElementInst>(V); 6622 if (!LastInsertElem || !LastInsertElem->hasOneUse()) 6623 return false; 6624 } while (true); 6625 std::reverse(BuildVectorOpds.begin(), BuildVectorOpds.end()); 6626 return true; 6627 } 6628 6629 /// Like findBuildVector, but looks for construction of aggregate. 6630 /// 6631 /// \return true if it matches. 6632 static bool findBuildAggregate(InsertValueInst *IV, 6633 SmallVectorImpl<Value *> &BuildVectorOpds) { 6634 Value *V; 6635 do { 6636 BuildVectorOpds.push_back(IV->getInsertedValueOperand()); 6637 V = IV->getAggregateOperand(); 6638 if (isa<UndefValue>(V)) 6639 break; 6640 IV = dyn_cast<InsertValueInst>(V); 6641 if (!IV || !IV->hasOneUse()) 6642 return false; 6643 } while (true); 6644 std::reverse(BuildVectorOpds.begin(), BuildVectorOpds.end()); 6645 return true; 6646 } 6647 6648 static bool PhiTypeSorterFunc(Value *V, Value *V2) { 6649 return V->getType() < V2->getType(); 6650 } 6651 6652 /// Try and get a reduction value from a phi node. 6653 /// 6654 /// Given a phi node \p P in a block \p ParentBB, consider possible reductions 6655 /// if they come from either \p ParentBB or a containing loop latch. 6656 /// 6657 /// \returns A candidate reduction value if possible, or \code nullptr \endcode 6658 /// if not possible. 6659 static Value *getReductionValue(const DominatorTree *DT, PHINode *P, 6660 BasicBlock *ParentBB, LoopInfo *LI) { 6661 // There are situations where the reduction value is not dominated by the 6662 // reduction phi. Vectorizing such cases has been reported to cause 6663 // miscompiles. See PR25787. 6664 auto DominatedReduxValue = [&](Value *R) { 6665 return isa<Instruction>(R) && 6666 DT->dominates(P->getParent(), cast<Instruction>(R)->getParent()); 6667 }; 6668 6669 Value *Rdx = nullptr; 6670 6671 // Return the incoming value if it comes from the same BB as the phi node. 6672 if (P->getIncomingBlock(0) == ParentBB) { 6673 Rdx = P->getIncomingValue(0); 6674 } else if (P->getIncomingBlock(1) == ParentBB) { 6675 Rdx = P->getIncomingValue(1); 6676 } 6677 6678 if (Rdx && DominatedReduxValue(Rdx)) 6679 return Rdx; 6680 6681 // Otherwise, check whether we have a loop latch to look at. 6682 Loop *BBL = LI->getLoopFor(ParentBB); 6683 if (!BBL) 6684 return nullptr; 6685 BasicBlock *BBLatch = BBL->getLoopLatch(); 6686 if (!BBLatch) 6687 return nullptr; 6688 6689 // There is a loop latch, return the incoming value if it comes from 6690 // that. This reduction pattern occasionally turns up. 6691 if (P->getIncomingBlock(0) == BBLatch) { 6692 Rdx = P->getIncomingValue(0); 6693 } else if (P->getIncomingBlock(1) == BBLatch) { 6694 Rdx = P->getIncomingValue(1); 6695 } 6696 6697 if (Rdx && DominatedReduxValue(Rdx)) 6698 return Rdx; 6699 6700 return nullptr; 6701 } 6702 6703 /// Attempt to reduce a horizontal reduction. 6704 /// If it is legal to match a horizontal reduction feeding the phi node \a P 6705 /// with reduction operators \a Root (or one of its operands) in a basic block 6706 /// \a BB, then check if it can be done. If horizontal reduction is not found 6707 /// and root instruction is a binary operation, vectorization of the operands is 6708 /// attempted. 6709 /// \returns true if a horizontal reduction was matched and reduced or operands 6710 /// of one of the binary instruction were vectorized. 6711 /// \returns false if a horizontal reduction was not matched (or not possible) 6712 /// or no vectorization of any binary operation feeding \a Root instruction was 6713 /// performed. 6714 static bool tryToVectorizeHorReductionOrInstOperands( 6715 PHINode *P, Instruction *Root, BasicBlock *BB, BoUpSLP &R, 6716 TargetTransformInfo *TTI, 6717 const function_ref<bool(Instruction *, BoUpSLP &)> Vectorize) { 6718 if (!ShouldVectorizeHor) 6719 return false; 6720 6721 if (!Root) 6722 return false; 6723 6724 if (Root->getParent() != BB || isa<PHINode>(Root)) 6725 return false; 6726 // Start analysis starting from Root instruction. If horizontal reduction is 6727 // found, try to vectorize it. If it is not a horizontal reduction or 6728 // vectorization is not possible or not effective, and currently analyzed 6729 // instruction is a binary operation, try to vectorize the operands, using 6730 // pre-order DFS traversal order. If the operands were not vectorized, repeat 6731 // the same procedure considering each operand as a possible root of the 6732 // horizontal reduction. 6733 // Interrupt the process if the Root instruction itself was vectorized or all 6734 // sub-trees not higher that RecursionMaxDepth were analyzed/vectorized. 6735 SmallVector<std::pair<WeakTrackingVH, unsigned>, 8> Stack(1, {Root, 0}); 6736 SmallPtrSet<Value *, 8> VisitedInstrs; 6737 bool Res = false; 6738 while (!Stack.empty()) { 6739 Value *V; 6740 unsigned Level; 6741 std::tie(V, Level) = Stack.pop_back_val(); 6742 if (!V) 6743 continue; 6744 auto *Inst = dyn_cast<Instruction>(V); 6745 if (!Inst) 6746 continue; 6747 auto *BI = dyn_cast<BinaryOperator>(Inst); 6748 auto *SI = dyn_cast<SelectInst>(Inst); 6749 if (BI || SI) { 6750 HorizontalReduction HorRdx; 6751 if (HorRdx.matchAssociativeReduction(P, Inst)) { 6752 if (HorRdx.tryToReduce(R, TTI)) { 6753 Res = true; 6754 // Set P to nullptr to avoid re-analysis of phi node in 6755 // matchAssociativeReduction function unless this is the root node. 6756 P = nullptr; 6757 continue; 6758 } 6759 } 6760 if (P && BI) { 6761 Inst = dyn_cast<Instruction>(BI->getOperand(0)); 6762 if (Inst == P) 6763 Inst = dyn_cast<Instruction>(BI->getOperand(1)); 6764 if (!Inst) { 6765 // Set P to nullptr to avoid re-analysis of phi node in 6766 // matchAssociativeReduction function unless this is the root node. 6767 P = nullptr; 6768 continue; 6769 } 6770 } 6771 } 6772 // Set P to nullptr to avoid re-analysis of phi node in 6773 // matchAssociativeReduction function unless this is the root node. 6774 P = nullptr; 6775 if (Vectorize(Inst, R)) { 6776 Res = true; 6777 continue; 6778 } 6779 6780 // Try to vectorize operands. 6781 // Continue analysis for the instruction from the same basic block only to 6782 // save compile time. 6783 if (++Level < RecursionMaxDepth) 6784 for (auto *Op : Inst->operand_values()) 6785 if (VisitedInstrs.insert(Op).second) 6786 if (auto *I = dyn_cast<Instruction>(Op)) 6787 if (!isa<PHINode>(I) && I->getParent() == BB) 6788 Stack.emplace_back(Op, Level); 6789 } 6790 return Res; 6791 } 6792 6793 bool SLPVectorizerPass::vectorizeRootInstruction(PHINode *P, Value *V, 6794 BasicBlock *BB, BoUpSLP &R, 6795 TargetTransformInfo *TTI) { 6796 if (!V) 6797 return false; 6798 auto *I = dyn_cast<Instruction>(V); 6799 if (!I) 6800 return false; 6801 6802 if (!isa<BinaryOperator>(I)) 6803 P = nullptr; 6804 // Try to match and vectorize a horizontal reduction. 6805 auto &&ExtraVectorization = [this](Instruction *I, BoUpSLP &R) -> bool { 6806 return tryToVectorize(I, R); 6807 }; 6808 return tryToVectorizeHorReductionOrInstOperands(P, I, BB, R, TTI, 6809 ExtraVectorization); 6810 } 6811 6812 bool SLPVectorizerPass::vectorizeInsertValueInst(InsertValueInst *IVI, 6813 BasicBlock *BB, BoUpSLP &R) { 6814 const DataLayout &DL = BB->getModule()->getDataLayout(); 6815 if (!R.canMapToVector(IVI->getType(), DL)) 6816 return false; 6817 6818 SmallVector<Value *, 16> BuildVectorOpds; 6819 if (!findBuildAggregate(IVI, BuildVectorOpds)) 6820 return false; 6821 6822 LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IVI << "\n"); 6823 // Aggregate value is unlikely to be processed in vector register, we need to 6824 // extract scalars into scalar registers, so NeedExtraction is set true. 6825 return tryToVectorizeList(BuildVectorOpds, R); 6826 } 6827 6828 bool SLPVectorizerPass::vectorizeInsertElementInst(InsertElementInst *IEI, 6829 BasicBlock *BB, BoUpSLP &R) { 6830 int UserCost; 6831 SmallVector<Value *, 16> BuildVectorOpds; 6832 if (!findBuildVector(IEI, TTI, BuildVectorOpds, UserCost) || 6833 (llvm::all_of(BuildVectorOpds, 6834 [](Value *V) { return isa<ExtractElementInst>(V); }) && 6835 isShuffle(BuildVectorOpds))) 6836 return false; 6837 6838 // Vectorize starting with the build vector operands ignoring the BuildVector 6839 // instructions for the purpose of scheduling and user extraction. 6840 return tryToVectorizeList(BuildVectorOpds, R, UserCost); 6841 } 6842 6843 bool SLPVectorizerPass::vectorizeCmpInst(CmpInst *CI, BasicBlock *BB, 6844 BoUpSLP &R) { 6845 if (tryToVectorizePair(CI->getOperand(0), CI->getOperand(1), R)) 6846 return true; 6847 6848 bool OpsChanged = false; 6849 for (int Idx = 0; Idx < 2; ++Idx) { 6850 OpsChanged |= 6851 vectorizeRootInstruction(nullptr, CI->getOperand(Idx), BB, R, TTI); 6852 } 6853 return OpsChanged; 6854 } 6855 6856 bool SLPVectorizerPass::vectorizeSimpleInstructions( 6857 SmallVectorImpl<WeakVH> &Instructions, BasicBlock *BB, BoUpSLP &R) { 6858 bool OpsChanged = false; 6859 for (auto &VH : reverse(Instructions)) { 6860 auto *I = dyn_cast_or_null<Instruction>(VH); 6861 if (!I) 6862 continue; 6863 if (auto *LastInsertValue = dyn_cast<InsertValueInst>(I)) 6864 OpsChanged |= vectorizeInsertValueInst(LastInsertValue, BB, R); 6865 else if (auto *LastInsertElem = dyn_cast<InsertElementInst>(I)) 6866 OpsChanged |= vectorizeInsertElementInst(LastInsertElem, BB, R); 6867 else if (auto *CI = dyn_cast<CmpInst>(I)) 6868 OpsChanged |= vectorizeCmpInst(CI, BB, R); 6869 } 6870 Instructions.clear(); 6871 return OpsChanged; 6872 } 6873 6874 bool SLPVectorizerPass::vectorizeChainsInBlock(BasicBlock *BB, BoUpSLP &R) { 6875 bool Changed = false; 6876 SmallVector<Value *, 4> Incoming; 6877 SmallPtrSet<Value *, 16> VisitedInstrs; 6878 6879 bool HaveVectorizedPhiNodes = true; 6880 while (HaveVectorizedPhiNodes) { 6881 HaveVectorizedPhiNodes = false; 6882 6883 // Collect the incoming values from the PHIs. 6884 Incoming.clear(); 6885 for (Instruction &I : *BB) { 6886 PHINode *P = dyn_cast<PHINode>(&I); 6887 if (!P) 6888 break; 6889 6890 if (!VisitedInstrs.count(P)) 6891 Incoming.push_back(P); 6892 } 6893 6894 // Sort by type. 6895 llvm::stable_sort(Incoming, PhiTypeSorterFunc); 6896 6897 // Try to vectorize elements base on their type. 6898 for (SmallVector<Value *, 4>::iterator IncIt = Incoming.begin(), 6899 E = Incoming.end(); 6900 IncIt != E;) { 6901 6902 // Look for the next elements with the same type. 6903 SmallVector<Value *, 4>::iterator SameTypeIt = IncIt; 6904 while (SameTypeIt != E && 6905 (*SameTypeIt)->getType() == (*IncIt)->getType()) { 6906 VisitedInstrs.insert(*SameTypeIt); 6907 ++SameTypeIt; 6908 } 6909 6910 // Try to vectorize them. 6911 unsigned NumElts = (SameTypeIt - IncIt); 6912 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize starting at PHIs (" 6913 << NumElts << ")\n"); 6914 // The order in which the phi nodes appear in the program does not matter. 6915 // So allow tryToVectorizeList to reorder them if it is beneficial. This 6916 // is done when there are exactly two elements since tryToVectorizeList 6917 // asserts that there are only two values when AllowReorder is true. 6918 bool AllowReorder = NumElts == 2; 6919 if (NumElts > 1 && tryToVectorizeList(makeArrayRef(IncIt, NumElts), R, 6920 /*UserCost=*/0, AllowReorder)) { 6921 // Success start over because instructions might have been changed. 6922 HaveVectorizedPhiNodes = true; 6923 Changed = true; 6924 break; 6925 } 6926 6927 // Start over at the next instruction of a different type (or the end). 6928 IncIt = SameTypeIt; 6929 } 6930 } 6931 6932 VisitedInstrs.clear(); 6933 6934 SmallVector<WeakVH, 8> PostProcessInstructions; 6935 SmallDenseSet<Instruction *, 4> KeyNodes; 6936 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 6937 // We may go through BB multiple times so skip the one we have checked. 6938 if (!VisitedInstrs.insert(&*it).second) { 6939 if (it->use_empty() && KeyNodes.count(&*it) > 0 && 6940 vectorizeSimpleInstructions(PostProcessInstructions, BB, R)) { 6941 // We would like to start over since some instructions are deleted 6942 // and the iterator may become invalid value. 6943 Changed = true; 6944 it = BB->begin(); 6945 e = BB->end(); 6946 } 6947 continue; 6948 } 6949 6950 if (isa<DbgInfoIntrinsic>(it)) 6951 continue; 6952 6953 // Try to vectorize reductions that use PHINodes. 6954 if (PHINode *P = dyn_cast<PHINode>(it)) { 6955 // Check that the PHI is a reduction PHI. 6956 if (P->getNumIncomingValues() != 2) 6957 return Changed; 6958 6959 // Try to match and vectorize a horizontal reduction. 6960 if (vectorizeRootInstruction(P, getReductionValue(DT, P, BB, LI), BB, R, 6961 TTI)) { 6962 Changed = true; 6963 it = BB->begin(); 6964 e = BB->end(); 6965 continue; 6966 } 6967 continue; 6968 } 6969 6970 // Ran into an instruction without users, like terminator, or function call 6971 // with ignored return value, store. Ignore unused instructions (basing on 6972 // instruction type, except for CallInst and InvokeInst). 6973 if (it->use_empty() && (it->getType()->isVoidTy() || isa<CallInst>(it) || 6974 isa<InvokeInst>(it))) { 6975 KeyNodes.insert(&*it); 6976 bool OpsChanged = false; 6977 if (ShouldStartVectorizeHorAtStore || !isa<StoreInst>(it)) { 6978 for (auto *V : it->operand_values()) { 6979 // Try to match and vectorize a horizontal reduction. 6980 OpsChanged |= vectorizeRootInstruction(nullptr, V, BB, R, TTI); 6981 } 6982 } 6983 // Start vectorization of post-process list of instructions from the 6984 // top-tree instructions to try to vectorize as many instructions as 6985 // possible. 6986 OpsChanged |= vectorizeSimpleInstructions(PostProcessInstructions, BB, R); 6987 if (OpsChanged) { 6988 // We would like to start over since some instructions are deleted 6989 // and the iterator may become invalid value. 6990 Changed = true; 6991 it = BB->begin(); 6992 e = BB->end(); 6993 continue; 6994 } 6995 } 6996 6997 if (isa<InsertElementInst>(it) || isa<CmpInst>(it) || 6998 isa<InsertValueInst>(it)) 6999 PostProcessInstructions.push_back(&*it); 7000 } 7001 7002 return Changed; 7003 } 7004 7005 bool SLPVectorizerPass::vectorizeGEPIndices(BasicBlock *BB, BoUpSLP &R) { 7006 auto Changed = false; 7007 for (auto &Entry : GEPs) { 7008 // If the getelementptr list has fewer than two elements, there's nothing 7009 // to do. 7010 if (Entry.second.size() < 2) 7011 continue; 7012 7013 LLVM_DEBUG(dbgs() << "SLP: Analyzing a getelementptr list of length " 7014 << Entry.second.size() << ".\n"); 7015 7016 // We process the getelementptr list in chunks of 16 (like we do for 7017 // stores) to minimize compile-time. 7018 for (unsigned BI = 0, BE = Entry.second.size(); BI < BE; BI += 16) { 7019 auto Len = std::min<unsigned>(BE - BI, 16); 7020 auto GEPList = makeArrayRef(&Entry.second[BI], Len); 7021 7022 // Initialize a set a candidate getelementptrs. Note that we use a 7023 // SetVector here to preserve program order. If the index computations 7024 // are vectorizable and begin with loads, we want to minimize the chance 7025 // of having to reorder them later. 7026 SetVector<Value *> Candidates(GEPList.begin(), GEPList.end()); 7027 7028 // Some of the candidates may have already been vectorized after we 7029 // initially collected them. If so, the WeakTrackingVHs will have 7030 // nullified the 7031 // values, so remove them from the set of candidates. 7032 Candidates.remove(nullptr); 7033 7034 // Remove from the set of candidates all pairs of getelementptrs with 7035 // constant differences. Such getelementptrs are likely not good 7036 // candidates for vectorization in a bottom-up phase since one can be 7037 // computed from the other. We also ensure all candidate getelementptr 7038 // indices are unique. 7039 for (int I = 0, E = GEPList.size(); I < E && Candidates.size() > 1; ++I) { 7040 auto *GEPI = cast<GetElementPtrInst>(GEPList[I]); 7041 if (!Candidates.count(GEPI)) 7042 continue; 7043 auto *SCEVI = SE->getSCEV(GEPList[I]); 7044 for (int J = I + 1; J < E && Candidates.size() > 1; ++J) { 7045 auto *GEPJ = cast<GetElementPtrInst>(GEPList[J]); 7046 auto *SCEVJ = SE->getSCEV(GEPList[J]); 7047 if (isa<SCEVConstant>(SE->getMinusSCEV(SCEVI, SCEVJ))) { 7048 Candidates.remove(GEPList[I]); 7049 Candidates.remove(GEPList[J]); 7050 } else if (GEPI->idx_begin()->get() == GEPJ->idx_begin()->get()) { 7051 Candidates.remove(GEPList[J]); 7052 } 7053 } 7054 } 7055 7056 // We break out of the above computation as soon as we know there are 7057 // fewer than two candidates remaining. 7058 if (Candidates.size() < 2) 7059 continue; 7060 7061 // Add the single, non-constant index of each candidate to the bundle. We 7062 // ensured the indices met these constraints when we originally collected 7063 // the getelementptrs. 7064 SmallVector<Value *, 16> Bundle(Candidates.size()); 7065 auto BundleIndex = 0u; 7066 for (auto *V : Candidates) { 7067 auto *GEP = cast<GetElementPtrInst>(V); 7068 auto *GEPIdx = GEP->idx_begin()->get(); 7069 assert(GEP->getNumIndices() == 1 || !isa<Constant>(GEPIdx)); 7070 Bundle[BundleIndex++] = GEPIdx; 7071 } 7072 7073 // Try and vectorize the indices. We are currently only interested in 7074 // gather-like cases of the form: 7075 // 7076 // ... = g[a[0] - b[0]] + g[a[1] - b[1]] + ... 7077 // 7078 // where the loads of "a", the loads of "b", and the subtractions can be 7079 // performed in parallel. It's likely that detecting this pattern in a 7080 // bottom-up phase will be simpler and less costly than building a 7081 // full-blown top-down phase beginning at the consecutive loads. 7082 Changed |= tryToVectorizeList(Bundle, R); 7083 } 7084 } 7085 return Changed; 7086 } 7087 7088 bool SLPVectorizerPass::vectorizeStoreChains(BoUpSLP &R) { 7089 bool Changed = false; 7090 // Attempt to sort and vectorize each of the store-groups. 7091 for (StoreListMap::iterator it = Stores.begin(), e = Stores.end(); it != e; 7092 ++it) { 7093 if (it->second.size() < 2) 7094 continue; 7095 7096 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " 7097 << it->second.size() << ".\n"); 7098 7099 // Process the stores in chunks of 16. 7100 // TODO: The limit of 16 inhibits greater vectorization factors. 7101 // For example, AVX2 supports v32i8. Increasing this limit, however, 7102 // may cause a significant compile-time increase. 7103 for (unsigned CI = 0, CE = it->second.size(); CI < CE; CI += 16) { 7104 unsigned Len = std::min<unsigned>(CE - CI, 16); 7105 Changed |= vectorizeStores(makeArrayRef(&it->second[CI], Len), R); 7106 } 7107 } 7108 return Changed; 7109 } 7110 7111 char SLPVectorizer::ID = 0; 7112 7113 static const char lv_name[] = "SLP Vectorizer"; 7114 7115 INITIALIZE_PASS_BEGIN(SLPVectorizer, SV_NAME, lv_name, false, false) 7116 INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass) 7117 INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass) 7118 INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker) 7119 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass) 7120 INITIALIZE_PASS_DEPENDENCY(LoopSimplify) 7121 INITIALIZE_PASS_DEPENDENCY(DemandedBitsWrapperPass) 7122 INITIALIZE_PASS_DEPENDENCY(OptimizationRemarkEmitterWrapperPass) 7123 INITIALIZE_PASS_END(SLPVectorizer, SV_NAME, lv_name, false, false) 7124 7125 Pass *llvm::createSLPVectorizerPass() { return new SLPVectorizer(); } 7126