1 //===- SLPVectorizer.cpp - A bottom up SLP Vectorizer ---------------------===// 2 // 3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. 4 // See https://llvm.org/LICENSE.txt for license information. 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 6 // 7 //===----------------------------------------------------------------------===// 8 // 9 // This pass implements the Bottom Up SLP vectorizer. It detects consecutive 10 // stores that can be put together into vector-stores. Next, it attempts to 11 // construct vectorizable tree using the use-def chains. If a profitable tree 12 // was found, the SLP vectorizer performs vectorization on the tree. 13 // 14 // The pass is inspired by the work described in the paper: 15 // "Loop-Aware SLP in GCC" by Ira Rosen, Dorit Nuzman, Ayal Zaks. 16 // 17 //===----------------------------------------------------------------------===// 18 19 #include "llvm/Transforms/Vectorize/SLPVectorizer.h" 20 #include "llvm/ADT/DenseMap.h" 21 #include "llvm/ADT/DenseSet.h" 22 #include "llvm/ADT/Optional.h" 23 #include "llvm/ADT/PostOrderIterator.h" 24 #include "llvm/ADT/STLExtras.h" 25 #include "llvm/ADT/SetVector.h" 26 #include "llvm/ADT/SmallBitVector.h" 27 #include "llvm/ADT/SmallPtrSet.h" 28 #include "llvm/ADT/SmallSet.h" 29 #include "llvm/ADT/SmallString.h" 30 #include "llvm/ADT/Statistic.h" 31 #include "llvm/ADT/iterator.h" 32 #include "llvm/ADT/iterator_range.h" 33 #include "llvm/Analysis/AliasAnalysis.h" 34 #include "llvm/Analysis/AssumptionCache.h" 35 #include "llvm/Analysis/CodeMetrics.h" 36 #include "llvm/Analysis/DemandedBits.h" 37 #include "llvm/Analysis/GlobalsModRef.h" 38 #include "llvm/Analysis/IVDescriptors.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/PatternMatch.h" 68 #include "llvm/IR/Type.h" 69 #include "llvm/IR/Use.h" 70 #include "llvm/IR/User.h" 71 #include "llvm/IR/Value.h" 72 #include "llvm/IR/ValueHandle.h" 73 #include "llvm/IR/Verifier.h" 74 #include "llvm/InitializePasses.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/InstructionCost.h" 84 #include "llvm/Support/KnownBits.h" 85 #include "llvm/Support/MathExtras.h" 86 #include "llvm/Support/raw_ostream.h" 87 #include "llvm/Transforms/Utils/InjectTLIMappings.h" 88 #include "llvm/Transforms/Utils/LoopUtils.h" 89 #include "llvm/Transforms/Vectorize.h" 90 #include <algorithm> 91 #include <cassert> 92 #include <cstdint> 93 #include <iterator> 94 #include <memory> 95 #include <set> 96 #include <string> 97 #include <tuple> 98 #include <utility> 99 #include <vector> 100 101 using namespace llvm; 102 using namespace llvm::PatternMatch; 103 using namespace slpvectorizer; 104 105 #define SV_NAME "slp-vectorizer" 106 #define DEBUG_TYPE "SLP" 107 108 STATISTIC(NumVectorInstructions, "Number of vector instructions generated"); 109 110 cl::opt<bool> RunSLPVectorization("vectorize-slp", cl::init(true), cl::Hidden, 111 cl::desc("Run the SLP vectorization passes")); 112 113 static cl::opt<int> 114 SLPCostThreshold("slp-threshold", cl::init(0), cl::Hidden, 115 cl::desc("Only vectorize if you gain more than this " 116 "number ")); 117 118 static cl::opt<bool> 119 ShouldVectorizeHor("slp-vectorize-hor", cl::init(true), cl::Hidden, 120 cl::desc("Attempt to vectorize horizontal reductions")); 121 122 static cl::opt<bool> ShouldStartVectorizeHorAtStore( 123 "slp-vectorize-hor-store", cl::init(false), cl::Hidden, 124 cl::desc( 125 "Attempt to vectorize horizontal reductions feeding into a store")); 126 127 static cl::opt<int> 128 MaxVectorRegSizeOption("slp-max-reg-size", cl::init(128), cl::Hidden, 129 cl::desc("Attempt to vectorize for this register size in bits")); 130 131 static cl::opt<unsigned> 132 MaxVFOption("slp-max-vf", cl::init(0), cl::Hidden, 133 cl::desc("Maximum SLP vectorization factor (0=unlimited)")); 134 135 static cl::opt<int> 136 MaxStoreLookup("slp-max-store-lookup", cl::init(32), cl::Hidden, 137 cl::desc("Maximum depth of the lookup for consecutive stores.")); 138 139 /// Limits the size of scheduling regions in a block. 140 /// It avoid long compile times for _very_ large blocks where vector 141 /// instructions are spread over a wide range. 142 /// This limit is way higher than needed by real-world functions. 143 static cl::opt<int> 144 ScheduleRegionSizeBudget("slp-schedule-budget", cl::init(100000), cl::Hidden, 145 cl::desc("Limit the size of the SLP scheduling region per block")); 146 147 static cl::opt<int> MinVectorRegSizeOption( 148 "slp-min-reg-size", cl::init(128), cl::Hidden, 149 cl::desc("Attempt to vectorize for this register size in bits")); 150 151 static cl::opt<unsigned> RecursionMaxDepth( 152 "slp-recursion-max-depth", cl::init(12), cl::Hidden, 153 cl::desc("Limit the recursion depth when building a vectorizable tree")); 154 155 static cl::opt<unsigned> MinTreeSize( 156 "slp-min-tree-size", cl::init(3), cl::Hidden, 157 cl::desc("Only vectorize small trees if they are fully vectorizable")); 158 159 // The maximum depth that the look-ahead score heuristic will explore. 160 // The higher this value, the higher the compilation time overhead. 161 static cl::opt<int> LookAheadMaxDepth( 162 "slp-max-look-ahead-depth", cl::init(2), cl::Hidden, 163 cl::desc("The maximum look-ahead depth for operand reordering scores")); 164 165 // The Look-ahead heuristic goes through the users of the bundle to calculate 166 // the users cost in getExternalUsesCost(). To avoid compilation time increase 167 // we limit the number of users visited to this value. 168 static cl::opt<unsigned> LookAheadUsersBudget( 169 "slp-look-ahead-users-budget", cl::init(2), cl::Hidden, 170 cl::desc("The maximum number of users to visit while visiting the " 171 "predecessors. This prevents compilation time increase.")); 172 173 static cl::opt<bool> 174 ViewSLPTree("view-slp-tree", cl::Hidden, 175 cl::desc("Display the SLP trees with Graphviz")); 176 177 // Limit the number of alias checks. The limit is chosen so that 178 // it has no negative effect on the llvm benchmarks. 179 static const unsigned AliasedCheckLimit = 10; 180 181 // Another limit for the alias checks: The maximum distance between load/store 182 // instructions where alias checks are done. 183 // This limit is useful for very large basic blocks. 184 static const unsigned MaxMemDepDistance = 160; 185 186 /// If the ScheduleRegionSizeBudget is exhausted, we allow small scheduling 187 /// regions to be handled. 188 static const int MinScheduleRegionSize = 16; 189 190 /// Predicate for the element types that the SLP vectorizer supports. 191 /// 192 /// The most important thing to filter here are types which are invalid in LLVM 193 /// vectors. We also filter target specific types which have absolutely no 194 /// meaningful vectorization path such as x86_fp80 and ppc_f128. This just 195 /// avoids spending time checking the cost model and realizing that they will 196 /// be inevitably scalarized. 197 static bool isValidElementType(Type *Ty) { 198 return VectorType::isValidElementType(Ty) && !Ty->isX86_FP80Ty() && 199 !Ty->isPPC_FP128Ty(); 200 } 201 202 /// \returns true if all of the instructions in \p VL are in the same block or 203 /// false otherwise. 204 static bool allSameBlock(ArrayRef<Value *> VL) { 205 Instruction *I0 = dyn_cast<Instruction>(VL[0]); 206 if (!I0) 207 return false; 208 BasicBlock *BB = I0->getParent(); 209 for (int I = 1, E = VL.size(); I < E; I++) { 210 auto *II = dyn_cast<Instruction>(VL[I]); 211 if (!II) 212 return false; 213 214 if (BB != II->getParent()) 215 return false; 216 } 217 return true; 218 } 219 220 /// \returns True if all of the values in \p VL are constants (but not 221 /// globals/constant expressions). 222 static bool allConstant(ArrayRef<Value *> VL) { 223 // Constant expressions and globals can't be vectorized like normal integer/FP 224 // constants. 225 for (Value *i : VL) 226 if (!isa<Constant>(i) || isa<ConstantExpr>(i) || isa<GlobalValue>(i)) 227 return false; 228 return true; 229 } 230 231 /// \returns True if all of the values in \p VL are identical. 232 static bool isSplat(ArrayRef<Value *> VL) { 233 for (unsigned i = 1, e = VL.size(); i < e; ++i) 234 if (VL[i] != VL[0]) 235 return false; 236 return true; 237 } 238 239 /// \returns True if \p I is commutative, handles CmpInst and BinaryOperator. 240 static bool isCommutative(Instruction *I) { 241 if (auto *Cmp = dyn_cast<CmpInst>(I)) 242 return Cmp->isCommutative(); 243 if (auto *BO = dyn_cast<BinaryOperator>(I)) 244 return BO->isCommutative(); 245 // TODO: This should check for generic Instruction::isCommutative(), but 246 // we need to confirm that the caller code correctly handles Intrinsics 247 // for example (does not have 2 operands). 248 return false; 249 } 250 251 /// Checks if the vector of instructions can be represented as a shuffle, like: 252 /// %x0 = extractelement <4 x i8> %x, i32 0 253 /// %x3 = extractelement <4 x i8> %x, i32 3 254 /// %y1 = extractelement <4 x i8> %y, i32 1 255 /// %y2 = extractelement <4 x i8> %y, i32 2 256 /// %x0x0 = mul i8 %x0, %x0 257 /// %x3x3 = mul i8 %x3, %x3 258 /// %y1y1 = mul i8 %y1, %y1 259 /// %y2y2 = mul i8 %y2, %y2 260 /// %ins1 = insertelement <4 x i8> poison, i8 %x0x0, i32 0 261 /// %ins2 = insertelement <4 x i8> %ins1, i8 %x3x3, i32 1 262 /// %ins3 = insertelement <4 x i8> %ins2, i8 %y1y1, i32 2 263 /// %ins4 = insertelement <4 x i8> %ins3, i8 %y2y2, i32 3 264 /// ret <4 x i8> %ins4 265 /// can be transformed into: 266 /// %1 = shufflevector <4 x i8> %x, <4 x i8> %y, <4 x i32> <i32 0, i32 3, i32 5, 267 /// i32 6> 268 /// %2 = mul <4 x i8> %1, %1 269 /// ret <4 x i8> %2 270 /// We convert this initially to something like: 271 /// %x0 = extractelement <4 x i8> %x, i32 0 272 /// %x3 = extractelement <4 x i8> %x, i32 3 273 /// %y1 = extractelement <4 x i8> %y, i32 1 274 /// %y2 = extractelement <4 x i8> %y, i32 2 275 /// %1 = insertelement <4 x i8> poison, i8 %x0, i32 0 276 /// %2 = insertelement <4 x i8> %1, i8 %x3, i32 1 277 /// %3 = insertelement <4 x i8> %2, i8 %y1, i32 2 278 /// %4 = insertelement <4 x i8> %3, i8 %y2, i32 3 279 /// %5 = mul <4 x i8> %4, %4 280 /// %6 = extractelement <4 x i8> %5, i32 0 281 /// %ins1 = insertelement <4 x i8> poison, i8 %6, i32 0 282 /// %7 = extractelement <4 x i8> %5, i32 1 283 /// %ins2 = insertelement <4 x i8> %ins1, i8 %7, i32 1 284 /// %8 = extractelement <4 x i8> %5, i32 2 285 /// %ins3 = insertelement <4 x i8> %ins2, i8 %8, i32 2 286 /// %9 = extractelement <4 x i8> %5, i32 3 287 /// %ins4 = insertelement <4 x i8> %ins3, i8 %9, i32 3 288 /// ret <4 x i8> %ins4 289 /// InstCombiner transforms this into a shuffle and vector mul 290 /// TODO: Can we split off and reuse the shuffle mask detection from 291 /// TargetTransformInfo::getInstructionThroughput? 292 static Optional<TargetTransformInfo::ShuffleKind> 293 isShuffle(ArrayRef<Value *> VL) { 294 auto *EI0 = cast<ExtractElementInst>(VL[0]); 295 unsigned Size = 296 cast<FixedVectorType>(EI0->getVectorOperandType())->getNumElements(); 297 Value *Vec1 = nullptr; 298 Value *Vec2 = nullptr; 299 enum ShuffleMode { Unknown, Select, Permute }; 300 ShuffleMode CommonShuffleMode = Unknown; 301 for (unsigned I = 0, E = VL.size(); I < E; ++I) { 302 auto *EI = cast<ExtractElementInst>(VL[I]); 303 auto *Vec = EI->getVectorOperand(); 304 // All vector operands must have the same number of vector elements. 305 if (cast<FixedVectorType>(Vec->getType())->getNumElements() != Size) 306 return None; 307 auto *Idx = dyn_cast<ConstantInt>(EI->getIndexOperand()); 308 if (!Idx) 309 return None; 310 // Undefined behavior if Idx is negative or >= Size. 311 if (Idx->getValue().uge(Size)) 312 continue; 313 unsigned IntIdx = Idx->getValue().getZExtValue(); 314 // We can extractelement from undef or poison vector. 315 if (isa<UndefValue>(Vec)) 316 continue; 317 // For correct shuffling we have to have at most 2 different vector operands 318 // in all extractelement instructions. 319 if (!Vec1 || Vec1 == Vec) 320 Vec1 = Vec; 321 else if (!Vec2 || Vec2 == Vec) 322 Vec2 = Vec; 323 else 324 return None; 325 if (CommonShuffleMode == Permute) 326 continue; 327 // If the extract index is not the same as the operation number, it is a 328 // permutation. 329 if (IntIdx != I) { 330 CommonShuffleMode = Permute; 331 continue; 332 } 333 CommonShuffleMode = Select; 334 } 335 // If we're not crossing lanes in different vectors, consider it as blending. 336 if (CommonShuffleMode == Select && Vec2) 337 return TargetTransformInfo::SK_Select; 338 // If Vec2 was never used, we have a permutation of a single vector, otherwise 339 // we have permutation of 2 vectors. 340 return Vec2 ? TargetTransformInfo::SK_PermuteTwoSrc 341 : TargetTransformInfo::SK_PermuteSingleSrc; 342 } 343 344 namespace { 345 346 /// Main data required for vectorization of instructions. 347 struct InstructionsState { 348 /// The very first instruction in the list with the main opcode. 349 Value *OpValue = nullptr; 350 351 /// The main/alternate instruction. 352 Instruction *MainOp = nullptr; 353 Instruction *AltOp = nullptr; 354 355 /// The main/alternate opcodes for the list of instructions. 356 unsigned getOpcode() const { 357 return MainOp ? MainOp->getOpcode() : 0; 358 } 359 360 unsigned getAltOpcode() const { 361 return AltOp ? AltOp->getOpcode() : 0; 362 } 363 364 /// Some of the instructions in the list have alternate opcodes. 365 bool isAltShuffle() const { return getOpcode() != getAltOpcode(); } 366 367 bool isOpcodeOrAlt(Instruction *I) const { 368 unsigned CheckedOpcode = I->getOpcode(); 369 return getOpcode() == CheckedOpcode || getAltOpcode() == CheckedOpcode; 370 } 371 372 InstructionsState() = delete; 373 InstructionsState(Value *OpValue, Instruction *MainOp, Instruction *AltOp) 374 : OpValue(OpValue), MainOp(MainOp), AltOp(AltOp) {} 375 }; 376 377 } // end anonymous namespace 378 379 /// Chooses the correct key for scheduling data. If \p Op has the same (or 380 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is \p 381 /// OpValue. 382 static Value *isOneOf(const InstructionsState &S, Value *Op) { 383 auto *I = dyn_cast<Instruction>(Op); 384 if (I && S.isOpcodeOrAlt(I)) 385 return Op; 386 return S.OpValue; 387 } 388 389 /// \returns true if \p Opcode is allowed as part of of the main/alternate 390 /// instruction for SLP vectorization. 391 /// 392 /// Example of unsupported opcode is SDIV that can potentially cause UB if the 393 /// "shuffled out" lane would result in division by zero. 394 static bool isValidForAlternation(unsigned Opcode) { 395 if (Instruction::isIntDivRem(Opcode)) 396 return false; 397 398 return true; 399 } 400 401 /// \returns analysis of the Instructions in \p VL described in 402 /// InstructionsState, the Opcode that we suppose the whole list 403 /// could be vectorized even if its structure is diverse. 404 static InstructionsState getSameOpcode(ArrayRef<Value *> VL, 405 unsigned BaseIndex = 0) { 406 // Make sure these are all Instructions. 407 if (llvm::any_of(VL, [](Value *V) { return !isa<Instruction>(V); })) 408 return InstructionsState(VL[BaseIndex], nullptr, nullptr); 409 410 bool IsCastOp = isa<CastInst>(VL[BaseIndex]); 411 bool IsBinOp = isa<BinaryOperator>(VL[BaseIndex]); 412 unsigned Opcode = cast<Instruction>(VL[BaseIndex])->getOpcode(); 413 unsigned AltOpcode = Opcode; 414 unsigned AltIndex = BaseIndex; 415 416 // Check for one alternate opcode from another BinaryOperator. 417 // TODO - generalize to support all operators (types, calls etc.). 418 for (int Cnt = 0, E = VL.size(); Cnt < E; Cnt++) { 419 unsigned InstOpcode = cast<Instruction>(VL[Cnt])->getOpcode(); 420 if (IsBinOp && isa<BinaryOperator>(VL[Cnt])) { 421 if (InstOpcode == Opcode || InstOpcode == AltOpcode) 422 continue; 423 if (Opcode == AltOpcode && isValidForAlternation(InstOpcode) && 424 isValidForAlternation(Opcode)) { 425 AltOpcode = InstOpcode; 426 AltIndex = Cnt; 427 continue; 428 } 429 } else if (IsCastOp && isa<CastInst>(VL[Cnt])) { 430 Type *Ty0 = cast<Instruction>(VL[BaseIndex])->getOperand(0)->getType(); 431 Type *Ty1 = cast<Instruction>(VL[Cnt])->getOperand(0)->getType(); 432 if (Ty0 == Ty1) { 433 if (InstOpcode == Opcode || InstOpcode == AltOpcode) 434 continue; 435 if (Opcode == AltOpcode) { 436 assert(isValidForAlternation(Opcode) && 437 isValidForAlternation(InstOpcode) && 438 "Cast isn't safe for alternation, logic needs to be updated!"); 439 AltOpcode = InstOpcode; 440 AltIndex = Cnt; 441 continue; 442 } 443 } 444 } else if (InstOpcode == Opcode || InstOpcode == AltOpcode) 445 continue; 446 return InstructionsState(VL[BaseIndex], nullptr, nullptr); 447 } 448 449 return InstructionsState(VL[BaseIndex], cast<Instruction>(VL[BaseIndex]), 450 cast<Instruction>(VL[AltIndex])); 451 } 452 453 /// \returns true if all of the values in \p VL have the same type or false 454 /// otherwise. 455 static bool allSameType(ArrayRef<Value *> VL) { 456 Type *Ty = VL[0]->getType(); 457 for (int i = 1, e = VL.size(); i < e; i++) 458 if (VL[i]->getType() != Ty) 459 return false; 460 461 return true; 462 } 463 464 /// \returns True if Extract{Value,Element} instruction extracts element Idx. 465 static Optional<unsigned> getExtractIndex(Instruction *E) { 466 unsigned Opcode = E->getOpcode(); 467 assert((Opcode == Instruction::ExtractElement || 468 Opcode == Instruction::ExtractValue) && 469 "Expected extractelement or extractvalue instruction."); 470 if (Opcode == Instruction::ExtractElement) { 471 auto *CI = dyn_cast<ConstantInt>(E->getOperand(1)); 472 if (!CI) 473 return None; 474 return CI->getZExtValue(); 475 } 476 ExtractValueInst *EI = cast<ExtractValueInst>(E); 477 if (EI->getNumIndices() != 1) 478 return None; 479 return *EI->idx_begin(); 480 } 481 482 /// \returns True if in-tree use also needs extract. This refers to 483 /// possible scalar operand in vectorized instruction. 484 static bool InTreeUserNeedToExtract(Value *Scalar, Instruction *UserInst, 485 TargetLibraryInfo *TLI) { 486 unsigned Opcode = UserInst->getOpcode(); 487 switch (Opcode) { 488 case Instruction::Load: { 489 LoadInst *LI = cast<LoadInst>(UserInst); 490 return (LI->getPointerOperand() == Scalar); 491 } 492 case Instruction::Store: { 493 StoreInst *SI = cast<StoreInst>(UserInst); 494 return (SI->getPointerOperand() == Scalar); 495 } 496 case Instruction::Call: { 497 CallInst *CI = cast<CallInst>(UserInst); 498 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 499 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 500 if (hasVectorInstrinsicScalarOpd(ID, i)) 501 return (CI->getArgOperand(i) == Scalar); 502 } 503 LLVM_FALLTHROUGH; 504 } 505 default: 506 return false; 507 } 508 } 509 510 /// \returns the AA location that is being access by the instruction. 511 static MemoryLocation getLocation(Instruction *I, AAResults *AA) { 512 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 513 return MemoryLocation::get(SI); 514 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 515 return MemoryLocation::get(LI); 516 return MemoryLocation(); 517 } 518 519 /// \returns True if the instruction is not a volatile or atomic load/store. 520 static bool isSimple(Instruction *I) { 521 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 522 return LI->isSimple(); 523 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 524 return SI->isSimple(); 525 if (MemIntrinsic *MI = dyn_cast<MemIntrinsic>(I)) 526 return !MI->isVolatile(); 527 return true; 528 } 529 530 namespace llvm { 531 532 static void inversePermutation(ArrayRef<unsigned> Indices, 533 SmallVectorImpl<int> &Mask) { 534 Mask.clear(); 535 const unsigned E = Indices.size(); 536 Mask.resize(E, E + 1); 537 for (unsigned I = 0; I < E; ++I) 538 Mask[Indices[I]] = I; 539 } 540 541 namespace slpvectorizer { 542 543 /// Bottom Up SLP Vectorizer. 544 class BoUpSLP { 545 struct TreeEntry; 546 struct ScheduleData; 547 548 public: 549 using ValueList = SmallVector<Value *, 8>; 550 using InstrList = SmallVector<Instruction *, 16>; 551 using ValueSet = SmallPtrSet<Value *, 16>; 552 using StoreList = SmallVector<StoreInst *, 8>; 553 using ExtraValueToDebugLocsMap = 554 MapVector<Value *, SmallVector<Instruction *, 2>>; 555 using OrdersType = SmallVector<unsigned, 4>; 556 557 BoUpSLP(Function *Func, ScalarEvolution *Se, TargetTransformInfo *Tti, 558 TargetLibraryInfo *TLi, AAResults *Aa, LoopInfo *Li, 559 DominatorTree *Dt, AssumptionCache *AC, DemandedBits *DB, 560 const DataLayout *DL, OptimizationRemarkEmitter *ORE) 561 : F(Func), SE(Se), TTI(Tti), TLI(TLi), AA(Aa), LI(Li), DT(Dt), AC(AC), 562 DB(DB), DL(DL), ORE(ORE), Builder(Se->getContext()) { 563 CodeMetrics::collectEphemeralValues(F, AC, EphValues); 564 // Use the vector register size specified by the target unless overridden 565 // by a command-line option. 566 // TODO: It would be better to limit the vectorization factor based on 567 // data type rather than just register size. For example, x86 AVX has 568 // 256-bit registers, but it does not support integer operations 569 // at that width (that requires AVX2). 570 if (MaxVectorRegSizeOption.getNumOccurrences()) 571 MaxVecRegSize = MaxVectorRegSizeOption; 572 else 573 MaxVecRegSize = TTI->getRegisterBitWidth(true); 574 575 if (MinVectorRegSizeOption.getNumOccurrences()) 576 MinVecRegSize = MinVectorRegSizeOption; 577 else 578 MinVecRegSize = TTI->getMinVectorRegisterBitWidth(); 579 } 580 581 /// Vectorize the tree that starts with the elements in \p VL. 582 /// Returns the vectorized root. 583 Value *vectorizeTree(); 584 585 /// Vectorize the tree but with the list of externally used values \p 586 /// ExternallyUsedValues. Values in this MapVector can be replaced but the 587 /// generated extractvalue instructions. 588 Value *vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues); 589 590 /// \returns the cost incurred by unwanted spills and fills, caused by 591 /// holding live values over call sites. 592 InstructionCost getSpillCost() const; 593 594 /// \returns the vectorization cost of the subtree that starts at \p VL. 595 /// A negative number means that this is profitable. 596 InstructionCost getTreeCost(); 597 598 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 599 /// the purpose of scheduling and extraction in the \p UserIgnoreLst. 600 void buildTree(ArrayRef<Value *> Roots, 601 ArrayRef<Value *> UserIgnoreLst = None); 602 603 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 604 /// the purpose of scheduling and extraction in the \p UserIgnoreLst taking 605 /// into account (and updating it, if required) list of externally used 606 /// values stored in \p ExternallyUsedValues. 607 void buildTree(ArrayRef<Value *> Roots, 608 ExtraValueToDebugLocsMap &ExternallyUsedValues, 609 ArrayRef<Value *> UserIgnoreLst = None); 610 611 /// Clear the internal data structures that are created by 'buildTree'. 612 void deleteTree() { 613 VectorizableTree.clear(); 614 ScalarToTreeEntry.clear(); 615 MustGather.clear(); 616 ExternalUses.clear(); 617 NumOpsWantToKeepOrder.clear(); 618 NumOpsWantToKeepOriginalOrder = 0; 619 for (auto &Iter : BlocksSchedules) { 620 BlockScheduling *BS = Iter.second.get(); 621 BS->clear(); 622 } 623 MinBWs.clear(); 624 } 625 626 unsigned getTreeSize() const { return VectorizableTree.size(); } 627 628 /// Perform LICM and CSE on the newly generated gather sequences. 629 void optimizeGatherSequence(); 630 631 /// \returns The best order of instructions for vectorization. 632 Optional<ArrayRef<unsigned>> bestOrder() const { 633 assert(llvm::all_of( 634 NumOpsWantToKeepOrder, 635 [this](const decltype(NumOpsWantToKeepOrder)::value_type &D) { 636 return D.getFirst().size() == 637 VectorizableTree[0]->Scalars.size(); 638 }) && 639 "All orders must have the same size as number of instructions in " 640 "tree node."); 641 auto I = std::max_element( 642 NumOpsWantToKeepOrder.begin(), NumOpsWantToKeepOrder.end(), 643 [](const decltype(NumOpsWantToKeepOrder)::value_type &D1, 644 const decltype(NumOpsWantToKeepOrder)::value_type &D2) { 645 return D1.second < D2.second; 646 }); 647 if (I == NumOpsWantToKeepOrder.end() || 648 I->getSecond() <= NumOpsWantToKeepOriginalOrder) 649 return None; 650 651 return makeArrayRef(I->getFirst()); 652 } 653 654 /// Builds the correct order for root instructions. 655 /// If some leaves have the same instructions to be vectorized, we may 656 /// incorrectly evaluate the best order for the root node (it is built for the 657 /// vector of instructions without repeated instructions and, thus, has less 658 /// elements than the root node). This function builds the correct order for 659 /// the root node. 660 /// For example, if the root node is \<a+b, a+c, a+d, f+e\>, then the leaves 661 /// are \<a, a, a, f\> and \<b, c, d, e\>. When we try to vectorize the first 662 /// leaf, it will be shrink to \<a, b\>. If instructions in this leaf should 663 /// be reordered, the best order will be \<1, 0\>. We need to extend this 664 /// order for the root node. For the root node this order should look like 665 /// \<3, 0, 1, 2\>. This function extends the order for the reused 666 /// instructions. 667 void findRootOrder(OrdersType &Order) { 668 // If the leaf has the same number of instructions to vectorize as the root 669 // - order must be set already. 670 unsigned RootSize = VectorizableTree[0]->Scalars.size(); 671 if (Order.size() == RootSize) 672 return; 673 SmallVector<unsigned, 4> RealOrder(Order.size()); 674 std::swap(Order, RealOrder); 675 SmallVector<int, 4> Mask; 676 inversePermutation(RealOrder, Mask); 677 Order.assign(Mask.begin(), Mask.end()); 678 // The leaf has less number of instructions - need to find the true order of 679 // the root. 680 // Scan the nodes starting from the leaf back to the root. 681 const TreeEntry *PNode = VectorizableTree.back().get(); 682 SmallVector<const TreeEntry *, 4> Nodes(1, PNode); 683 SmallPtrSet<const TreeEntry *, 4> Visited; 684 while (!Nodes.empty() && Order.size() != RootSize) { 685 const TreeEntry *PNode = Nodes.pop_back_val(); 686 if (!Visited.insert(PNode).second) 687 continue; 688 const TreeEntry &Node = *PNode; 689 for (const EdgeInfo &EI : Node.UserTreeIndices) 690 if (EI.UserTE) 691 Nodes.push_back(EI.UserTE); 692 if (Node.ReuseShuffleIndices.empty()) 693 continue; 694 // Build the order for the parent node. 695 OrdersType NewOrder(Node.ReuseShuffleIndices.size(), RootSize); 696 SmallVector<unsigned, 4> OrderCounter(Order.size(), 0); 697 // The algorithm of the order extension is: 698 // 1. Calculate the number of the same instructions for the order. 699 // 2. Calculate the index of the new order: total number of instructions 700 // with order less than the order of the current instruction + reuse 701 // number of the current instruction. 702 // 3. The new order is just the index of the instruction in the original 703 // vector of the instructions. 704 for (unsigned I : Node.ReuseShuffleIndices) 705 ++OrderCounter[Order[I]]; 706 SmallVector<unsigned, 4> CurrentCounter(Order.size(), 0); 707 for (unsigned I = 0, E = Node.ReuseShuffleIndices.size(); I < E; ++I) { 708 unsigned ReusedIdx = Node.ReuseShuffleIndices[I]; 709 unsigned OrderIdx = Order[ReusedIdx]; 710 unsigned NewIdx = 0; 711 for (unsigned J = 0; J < OrderIdx; ++J) 712 NewIdx += OrderCounter[J]; 713 NewIdx += CurrentCounter[OrderIdx]; 714 ++CurrentCounter[OrderIdx]; 715 assert(NewOrder[NewIdx] == RootSize && 716 "The order index should not be written already."); 717 NewOrder[NewIdx] = I; 718 } 719 std::swap(Order, NewOrder); 720 } 721 assert(Order.size() == RootSize && 722 "Root node is expected or the size of the order must be the same as " 723 "the number of elements in the root node."); 724 assert(llvm::all_of(Order, 725 [RootSize](unsigned Val) { return Val != RootSize; }) && 726 "All indices must be initialized"); 727 } 728 729 /// \return The vector element size in bits to use when vectorizing the 730 /// expression tree ending at \p V. If V is a store, the size is the width of 731 /// the stored value. Otherwise, the size is the width of the largest loaded 732 /// value reaching V. This method is used by the vectorizer to calculate 733 /// vectorization factors. 734 unsigned getVectorElementSize(Value *V); 735 736 /// Compute the minimum type sizes required to represent the entries in a 737 /// vectorizable tree. 738 void computeMinimumValueSizes(); 739 740 // \returns maximum vector register size as set by TTI or overridden by cl::opt. 741 unsigned getMaxVecRegSize() const { 742 return MaxVecRegSize; 743 } 744 745 // \returns minimum vector register size as set by cl::opt. 746 unsigned getMinVecRegSize() const { 747 return MinVecRegSize; 748 } 749 750 unsigned getMaximumVF(unsigned ElemWidth, unsigned Opcode) const { 751 unsigned MaxVF = MaxVFOption.getNumOccurrences() ? 752 MaxVFOption : TTI->getMaximumVF(ElemWidth, Opcode); 753 return MaxVF ? MaxVF : UINT_MAX; 754 } 755 756 /// Check if homogeneous aggregate is isomorphic to some VectorType. 757 /// Accepts homogeneous multidimensional aggregate of scalars/vectors like 758 /// {[4 x i16], [4 x i16]}, { <2 x float>, <2 x float> }, 759 /// {{{i16, i16}, {i16, i16}}, {{i16, i16}, {i16, i16}}} and so on. 760 /// 761 /// \returns number of elements in vector if isomorphism exists, 0 otherwise. 762 unsigned canMapToVector(Type *T, const DataLayout &DL) const; 763 764 /// \returns True if the VectorizableTree is both tiny and not fully 765 /// vectorizable. We do not vectorize such trees. 766 bool isTreeTinyAndNotFullyVectorizable() const; 767 768 /// Assume that a legal-sized 'or'-reduction of shifted/zexted loaded values 769 /// can be load combined in the backend. Load combining may not be allowed in 770 /// the IR optimizer, so we do not want to alter the pattern. For example, 771 /// partially transforming a scalar bswap() pattern into vector code is 772 /// effectively impossible for the backend to undo. 773 /// TODO: If load combining is allowed in the IR optimizer, this analysis 774 /// may not be necessary. 775 bool isLoadCombineReductionCandidate(RecurKind RdxKind) const; 776 777 /// Assume that a vector of stores of bitwise-or/shifted/zexted loaded values 778 /// can be load combined in the backend. Load combining may not be allowed in 779 /// the IR optimizer, so we do not want to alter the pattern. For example, 780 /// partially transforming a scalar bswap() pattern into vector code is 781 /// effectively impossible for the backend to undo. 782 /// TODO: If load combining is allowed in the IR optimizer, this analysis 783 /// may not be necessary. 784 bool isLoadCombineCandidate() const; 785 786 OptimizationRemarkEmitter *getORE() { return ORE; } 787 788 /// This structure holds any data we need about the edges being traversed 789 /// during buildTree_rec(). We keep track of: 790 /// (i) the user TreeEntry index, and 791 /// (ii) the index of the edge. 792 struct EdgeInfo { 793 EdgeInfo() = default; 794 EdgeInfo(TreeEntry *UserTE, unsigned EdgeIdx) 795 : UserTE(UserTE), EdgeIdx(EdgeIdx) {} 796 /// The user TreeEntry. 797 TreeEntry *UserTE = nullptr; 798 /// The operand index of the use. 799 unsigned EdgeIdx = UINT_MAX; 800 #ifndef NDEBUG 801 friend inline raw_ostream &operator<<(raw_ostream &OS, 802 const BoUpSLP::EdgeInfo &EI) { 803 EI.dump(OS); 804 return OS; 805 } 806 /// Debug print. 807 void dump(raw_ostream &OS) const { 808 OS << "{User:" << (UserTE ? std::to_string(UserTE->Idx) : "null") 809 << " EdgeIdx:" << EdgeIdx << "}"; 810 } 811 LLVM_DUMP_METHOD void dump() const { dump(dbgs()); } 812 #endif 813 }; 814 815 /// A helper data structure to hold the operands of a vector of instructions. 816 /// This supports a fixed vector length for all operand vectors. 817 class VLOperands { 818 /// For each operand we need (i) the value, and (ii) the opcode that it 819 /// would be attached to if the expression was in a left-linearized form. 820 /// This is required to avoid illegal operand reordering. 821 /// For example: 822 /// \verbatim 823 /// 0 Op1 824 /// |/ 825 /// Op1 Op2 Linearized + Op2 826 /// \ / ----------> |/ 827 /// - - 828 /// 829 /// Op1 - Op2 (0 + Op1) - Op2 830 /// \endverbatim 831 /// 832 /// Value Op1 is attached to a '+' operation, and Op2 to a '-'. 833 /// 834 /// Another way to think of this is to track all the operations across the 835 /// path from the operand all the way to the root of the tree and to 836 /// calculate the operation that corresponds to this path. For example, the 837 /// path from Op2 to the root crosses the RHS of the '-', therefore the 838 /// corresponding operation is a '-' (which matches the one in the 839 /// linearized tree, as shown above). 840 /// 841 /// For lack of a better term, we refer to this operation as Accumulated 842 /// Path Operation (APO). 843 struct OperandData { 844 OperandData() = default; 845 OperandData(Value *V, bool APO, bool IsUsed) 846 : V(V), APO(APO), IsUsed(IsUsed) {} 847 /// The operand value. 848 Value *V = nullptr; 849 /// TreeEntries only allow a single opcode, or an alternate sequence of 850 /// them (e.g, +, -). Therefore, we can safely use a boolean value for the 851 /// APO. It is set to 'true' if 'V' is attached to an inverse operation 852 /// in the left-linearized form (e.g., Sub/Div), and 'false' otherwise 853 /// (e.g., Add/Mul) 854 bool APO = false; 855 /// Helper data for the reordering function. 856 bool IsUsed = false; 857 }; 858 859 /// During operand reordering, we are trying to select the operand at lane 860 /// that matches best with the operand at the neighboring lane. Our 861 /// selection is based on the type of value we are looking for. For example, 862 /// if the neighboring lane has a load, we need to look for a load that is 863 /// accessing a consecutive address. These strategies are summarized in the 864 /// 'ReorderingMode' enumerator. 865 enum class ReorderingMode { 866 Load, ///< Matching loads to consecutive memory addresses 867 Opcode, ///< Matching instructions based on opcode (same or alternate) 868 Constant, ///< Matching constants 869 Splat, ///< Matching the same instruction multiple times (broadcast) 870 Failed, ///< We failed to create a vectorizable group 871 }; 872 873 using OperandDataVec = SmallVector<OperandData, 2>; 874 875 /// A vector of operand vectors. 876 SmallVector<OperandDataVec, 4> OpsVec; 877 878 const DataLayout &DL; 879 ScalarEvolution &SE; 880 const BoUpSLP &R; 881 882 /// \returns the operand data at \p OpIdx and \p Lane. 883 OperandData &getData(unsigned OpIdx, unsigned Lane) { 884 return OpsVec[OpIdx][Lane]; 885 } 886 887 /// \returns the operand data at \p OpIdx and \p Lane. Const version. 888 const OperandData &getData(unsigned OpIdx, unsigned Lane) const { 889 return OpsVec[OpIdx][Lane]; 890 } 891 892 /// Clears the used flag for all entries. 893 void clearUsed() { 894 for (unsigned OpIdx = 0, NumOperands = getNumOperands(); 895 OpIdx != NumOperands; ++OpIdx) 896 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 897 ++Lane) 898 OpsVec[OpIdx][Lane].IsUsed = false; 899 } 900 901 /// Swap the operand at \p OpIdx1 with that one at \p OpIdx2. 902 void swap(unsigned OpIdx1, unsigned OpIdx2, unsigned Lane) { 903 std::swap(OpsVec[OpIdx1][Lane], OpsVec[OpIdx2][Lane]); 904 } 905 906 // The hard-coded scores listed here are not very important. When computing 907 // the scores of matching one sub-tree with another, we are basically 908 // counting the number of values that are matching. So even if all scores 909 // are set to 1, we would still get a decent matching result. 910 // However, sometimes we have to break ties. For example we may have to 911 // choose between matching loads vs matching opcodes. This is what these 912 // scores are helping us with: they provide the order of preference. 913 914 /// Loads from consecutive memory addresses, e.g. load(A[i]), load(A[i+1]). 915 static const int ScoreConsecutiveLoads = 3; 916 /// ExtractElementInst from same vector and consecutive indexes. 917 static const int ScoreConsecutiveExtracts = 3; 918 /// Constants. 919 static const int ScoreConstants = 2; 920 /// Instructions with the same opcode. 921 static const int ScoreSameOpcode = 2; 922 /// Instructions with alt opcodes (e.g, add + sub). 923 static const int ScoreAltOpcodes = 1; 924 /// Identical instructions (a.k.a. splat or broadcast). 925 static const int ScoreSplat = 1; 926 /// Matching with an undef is preferable to failing. 927 static const int ScoreUndef = 1; 928 /// Score for failing to find a decent match. 929 static const int ScoreFail = 0; 930 /// User exteranl to the vectorized code. 931 static const int ExternalUseCost = 1; 932 /// The user is internal but in a different lane. 933 static const int UserInDiffLaneCost = ExternalUseCost; 934 935 /// \returns the score of placing \p V1 and \p V2 in consecutive lanes. 936 static int getShallowScore(Value *V1, Value *V2, const DataLayout &DL, 937 ScalarEvolution &SE) { 938 auto *LI1 = dyn_cast<LoadInst>(V1); 939 auto *LI2 = dyn_cast<LoadInst>(V2); 940 if (LI1 && LI2) 941 return isConsecutiveAccess(LI1, LI2, DL, SE) 942 ? VLOperands::ScoreConsecutiveLoads 943 : VLOperands::ScoreFail; 944 945 auto *C1 = dyn_cast<Constant>(V1); 946 auto *C2 = dyn_cast<Constant>(V2); 947 if (C1 && C2) 948 return VLOperands::ScoreConstants; 949 950 // Extracts from consecutive indexes of the same vector better score as 951 // the extracts could be optimized away. 952 Value *EV; 953 ConstantInt *Ex1Idx, *Ex2Idx; 954 if (match(V1, m_ExtractElt(m_Value(EV), m_ConstantInt(Ex1Idx))) && 955 match(V2, m_ExtractElt(m_Deferred(EV), m_ConstantInt(Ex2Idx))) && 956 Ex1Idx->getZExtValue() + 1 == Ex2Idx->getZExtValue()) 957 return VLOperands::ScoreConsecutiveExtracts; 958 959 auto *I1 = dyn_cast<Instruction>(V1); 960 auto *I2 = dyn_cast<Instruction>(V2); 961 if (I1 && I2) { 962 if (I1 == I2) 963 return VLOperands::ScoreSplat; 964 InstructionsState S = getSameOpcode({I1, I2}); 965 // Note: Only consider instructions with <= 2 operands to avoid 966 // complexity explosion. 967 if (S.getOpcode() && S.MainOp->getNumOperands() <= 2) 968 return S.isAltShuffle() ? VLOperands::ScoreAltOpcodes 969 : VLOperands::ScoreSameOpcode; 970 } 971 972 if (isa<UndefValue>(V2)) 973 return VLOperands::ScoreUndef; 974 975 return VLOperands::ScoreFail; 976 } 977 978 /// Holds the values and their lane that are taking part in the look-ahead 979 /// score calculation. This is used in the external uses cost calculation. 980 SmallDenseMap<Value *, int> InLookAheadValues; 981 982 /// \Returns the additinal cost due to uses of \p LHS and \p RHS that are 983 /// either external to the vectorized code, or require shuffling. 984 int getExternalUsesCost(const std::pair<Value *, int> &LHS, 985 const std::pair<Value *, int> &RHS) { 986 int Cost = 0; 987 std::array<std::pair<Value *, int>, 2> Values = {{LHS, RHS}}; 988 for (int Idx = 0, IdxE = Values.size(); Idx != IdxE; ++Idx) { 989 Value *V = Values[Idx].first; 990 if (isa<Constant>(V)) { 991 // Since this is a function pass, it doesn't make semantic sense to 992 // walk the users of a subclass of Constant. The users could be in 993 // another function, or even another module that happens to be in 994 // the same LLVMContext. 995 continue; 996 } 997 998 // Calculate the absolute lane, using the minimum relative lane of LHS 999 // and RHS as base and Idx as the offset. 1000 int Ln = std::min(LHS.second, RHS.second) + Idx; 1001 assert(Ln >= 0 && "Bad lane calculation"); 1002 unsigned UsersBudget = LookAheadUsersBudget; 1003 for (User *U : V->users()) { 1004 if (const TreeEntry *UserTE = R.getTreeEntry(U)) { 1005 // The user is in the VectorizableTree. Check if we need to insert. 1006 auto It = llvm::find(UserTE->Scalars, U); 1007 assert(It != UserTE->Scalars.end() && "U is in UserTE"); 1008 int UserLn = std::distance(UserTE->Scalars.begin(), It); 1009 assert(UserLn >= 0 && "Bad lane"); 1010 if (UserLn != Ln) 1011 Cost += UserInDiffLaneCost; 1012 } else { 1013 // Check if the user is in the look-ahead code. 1014 auto It2 = InLookAheadValues.find(U); 1015 if (It2 != InLookAheadValues.end()) { 1016 // The user is in the look-ahead code. Check the lane. 1017 if (It2->second != Ln) 1018 Cost += UserInDiffLaneCost; 1019 } else { 1020 // The user is neither in SLP tree nor in the look-ahead code. 1021 Cost += ExternalUseCost; 1022 } 1023 } 1024 // Limit the number of visited uses to cap compilation time. 1025 if (--UsersBudget == 0) 1026 break; 1027 } 1028 } 1029 return Cost; 1030 } 1031 1032 /// Go through the operands of \p LHS and \p RHS recursively until \p 1033 /// MaxLevel, and return the cummulative score. For example: 1034 /// \verbatim 1035 /// A[0] B[0] A[1] B[1] C[0] D[0] B[1] A[1] 1036 /// \ / \ / \ / \ / 1037 /// + + + + 1038 /// G1 G2 G3 G4 1039 /// \endverbatim 1040 /// The getScoreAtLevelRec(G1, G2) function will try to match the nodes at 1041 /// each level recursively, accumulating the score. It starts from matching 1042 /// the additions at level 0, then moves on to the loads (level 1). The 1043 /// score of G1 and G2 is higher than G1 and G3, because {A[0],A[1]} and 1044 /// {B[0],B[1]} match with VLOperands::ScoreConsecutiveLoads, while 1045 /// {A[0],C[0]} has a score of VLOperands::ScoreFail. 1046 /// Please note that the order of the operands does not matter, as we 1047 /// evaluate the score of all profitable combinations of operands. In 1048 /// other words the score of G1 and G4 is the same as G1 and G2. This 1049 /// heuristic is based on ideas described in: 1050 /// Look-ahead SLP: Auto-vectorization in the presence of commutative 1051 /// operations, CGO 2018 by Vasileios Porpodas, Rodrigo C. O. Rocha, 1052 /// Luís F. W. Góes 1053 int getScoreAtLevelRec(const std::pair<Value *, int> &LHS, 1054 const std::pair<Value *, int> &RHS, int CurrLevel, 1055 int MaxLevel) { 1056 1057 Value *V1 = LHS.first; 1058 Value *V2 = RHS.first; 1059 // Get the shallow score of V1 and V2. 1060 int ShallowScoreAtThisLevel = 1061 std::max((int)ScoreFail, getShallowScore(V1, V2, DL, SE) - 1062 getExternalUsesCost(LHS, RHS)); 1063 int Lane1 = LHS.second; 1064 int Lane2 = RHS.second; 1065 1066 // If reached MaxLevel, 1067 // or if V1 and V2 are not instructions, 1068 // or if they are SPLAT, 1069 // or if they are not consecutive, early return the current cost. 1070 auto *I1 = dyn_cast<Instruction>(V1); 1071 auto *I2 = dyn_cast<Instruction>(V2); 1072 if (CurrLevel == MaxLevel || !(I1 && I2) || I1 == I2 || 1073 ShallowScoreAtThisLevel == VLOperands::ScoreFail || 1074 (isa<LoadInst>(I1) && isa<LoadInst>(I2) && ShallowScoreAtThisLevel)) 1075 return ShallowScoreAtThisLevel; 1076 assert(I1 && I2 && "Should have early exited."); 1077 1078 // Keep track of in-tree values for determining the external-use cost. 1079 InLookAheadValues[V1] = Lane1; 1080 InLookAheadValues[V2] = Lane2; 1081 1082 // Contains the I2 operand indexes that got matched with I1 operands. 1083 SmallSet<unsigned, 4> Op2Used; 1084 1085 // Recursion towards the operands of I1 and I2. We are trying all possbile 1086 // operand pairs, and keeping track of the best score. 1087 for (unsigned OpIdx1 = 0, NumOperands1 = I1->getNumOperands(); 1088 OpIdx1 != NumOperands1; ++OpIdx1) { 1089 // Try to pair op1I with the best operand of I2. 1090 int MaxTmpScore = 0; 1091 unsigned MaxOpIdx2 = 0; 1092 bool FoundBest = false; 1093 // If I2 is commutative try all combinations. 1094 unsigned FromIdx = isCommutative(I2) ? 0 : OpIdx1; 1095 unsigned ToIdx = isCommutative(I2) 1096 ? I2->getNumOperands() 1097 : std::min(I2->getNumOperands(), OpIdx1 + 1); 1098 assert(FromIdx <= ToIdx && "Bad index"); 1099 for (unsigned OpIdx2 = FromIdx; OpIdx2 != ToIdx; ++OpIdx2) { 1100 // Skip operands already paired with OpIdx1. 1101 if (Op2Used.count(OpIdx2)) 1102 continue; 1103 // Recursively calculate the cost at each level 1104 int TmpScore = getScoreAtLevelRec({I1->getOperand(OpIdx1), Lane1}, 1105 {I2->getOperand(OpIdx2), Lane2}, 1106 CurrLevel + 1, MaxLevel); 1107 // Look for the best score. 1108 if (TmpScore > VLOperands::ScoreFail && TmpScore > MaxTmpScore) { 1109 MaxTmpScore = TmpScore; 1110 MaxOpIdx2 = OpIdx2; 1111 FoundBest = true; 1112 } 1113 } 1114 if (FoundBest) { 1115 // Pair {OpIdx1, MaxOpIdx2} was found to be best. Never revisit it. 1116 Op2Used.insert(MaxOpIdx2); 1117 ShallowScoreAtThisLevel += MaxTmpScore; 1118 } 1119 } 1120 return ShallowScoreAtThisLevel; 1121 } 1122 1123 /// \Returns the look-ahead score, which tells us how much the sub-trees 1124 /// rooted at \p LHS and \p RHS match, the more they match the higher the 1125 /// score. This helps break ties in an informed way when we cannot decide on 1126 /// the order of the operands by just considering the immediate 1127 /// predecessors. 1128 int getLookAheadScore(const std::pair<Value *, int> &LHS, 1129 const std::pair<Value *, int> &RHS) { 1130 InLookAheadValues.clear(); 1131 return getScoreAtLevelRec(LHS, RHS, 1, LookAheadMaxDepth); 1132 } 1133 1134 // Search all operands in Ops[*][Lane] for the one that matches best 1135 // Ops[OpIdx][LastLane] and return its opreand index. 1136 // If no good match can be found, return None. 1137 Optional<unsigned> 1138 getBestOperand(unsigned OpIdx, int Lane, int LastLane, 1139 ArrayRef<ReorderingMode> ReorderingModes) { 1140 unsigned NumOperands = getNumOperands(); 1141 1142 // The operand of the previous lane at OpIdx. 1143 Value *OpLastLane = getData(OpIdx, LastLane).V; 1144 1145 // Our strategy mode for OpIdx. 1146 ReorderingMode RMode = ReorderingModes[OpIdx]; 1147 1148 // The linearized opcode of the operand at OpIdx, Lane. 1149 bool OpIdxAPO = getData(OpIdx, Lane).APO; 1150 1151 // The best operand index and its score. 1152 // Sometimes we have more than one option (e.g., Opcode and Undefs), so we 1153 // are using the score to differentiate between the two. 1154 struct BestOpData { 1155 Optional<unsigned> Idx = None; 1156 unsigned Score = 0; 1157 } BestOp; 1158 1159 // Iterate through all unused operands and look for the best. 1160 for (unsigned Idx = 0; Idx != NumOperands; ++Idx) { 1161 // Get the operand at Idx and Lane. 1162 OperandData &OpData = getData(Idx, Lane); 1163 Value *Op = OpData.V; 1164 bool OpAPO = OpData.APO; 1165 1166 // Skip already selected operands. 1167 if (OpData.IsUsed) 1168 continue; 1169 1170 // Skip if we are trying to move the operand to a position with a 1171 // different opcode in the linearized tree form. This would break the 1172 // semantics. 1173 if (OpAPO != OpIdxAPO) 1174 continue; 1175 1176 // Look for an operand that matches the current mode. 1177 switch (RMode) { 1178 case ReorderingMode::Load: 1179 case ReorderingMode::Constant: 1180 case ReorderingMode::Opcode: { 1181 bool LeftToRight = Lane > LastLane; 1182 Value *OpLeft = (LeftToRight) ? OpLastLane : Op; 1183 Value *OpRight = (LeftToRight) ? Op : OpLastLane; 1184 unsigned Score = 1185 getLookAheadScore({OpLeft, LastLane}, {OpRight, Lane}); 1186 if (Score > BestOp.Score) { 1187 BestOp.Idx = Idx; 1188 BestOp.Score = Score; 1189 } 1190 break; 1191 } 1192 case ReorderingMode::Splat: 1193 if (Op == OpLastLane) 1194 BestOp.Idx = Idx; 1195 break; 1196 case ReorderingMode::Failed: 1197 return None; 1198 } 1199 } 1200 1201 if (BestOp.Idx) { 1202 getData(BestOp.Idx.getValue(), Lane).IsUsed = true; 1203 return BestOp.Idx; 1204 } 1205 // If we could not find a good match return None. 1206 return None; 1207 } 1208 1209 /// Helper for reorderOperandVecs. \Returns the lane that we should start 1210 /// reordering from. This is the one which has the least number of operands 1211 /// that can freely move about. 1212 unsigned getBestLaneToStartReordering() const { 1213 unsigned BestLane = 0; 1214 unsigned Min = UINT_MAX; 1215 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 1216 ++Lane) { 1217 unsigned NumFreeOps = getMaxNumOperandsThatCanBeReordered(Lane); 1218 if (NumFreeOps < Min) { 1219 Min = NumFreeOps; 1220 BestLane = Lane; 1221 } 1222 } 1223 return BestLane; 1224 } 1225 1226 /// \Returns the maximum number of operands that are allowed to be reordered 1227 /// for \p Lane. This is used as a heuristic for selecting the first lane to 1228 /// start operand reordering. 1229 unsigned getMaxNumOperandsThatCanBeReordered(unsigned Lane) const { 1230 unsigned CntTrue = 0; 1231 unsigned NumOperands = getNumOperands(); 1232 // Operands with the same APO can be reordered. We therefore need to count 1233 // how many of them we have for each APO, like this: Cnt[APO] = x. 1234 // Since we only have two APOs, namely true and false, we can avoid using 1235 // a map. Instead we can simply count the number of operands that 1236 // correspond to one of them (in this case the 'true' APO), and calculate 1237 // the other by subtracting it from the total number of operands. 1238 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) 1239 if (getData(OpIdx, Lane).APO) 1240 ++CntTrue; 1241 unsigned CntFalse = NumOperands - CntTrue; 1242 return std::max(CntTrue, CntFalse); 1243 } 1244 1245 /// Go through the instructions in VL and append their operands. 1246 void appendOperandsOfVL(ArrayRef<Value *> VL) { 1247 assert(!VL.empty() && "Bad VL"); 1248 assert((empty() || VL.size() == getNumLanes()) && 1249 "Expected same number of lanes"); 1250 assert(isa<Instruction>(VL[0]) && "Expected instruction"); 1251 unsigned NumOperands = cast<Instruction>(VL[0])->getNumOperands(); 1252 OpsVec.resize(NumOperands); 1253 unsigned NumLanes = VL.size(); 1254 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1255 OpsVec[OpIdx].resize(NumLanes); 1256 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { 1257 assert(isa<Instruction>(VL[Lane]) && "Expected instruction"); 1258 // Our tree has just 3 nodes: the root and two operands. 1259 // It is therefore trivial to get the APO. We only need to check the 1260 // opcode of VL[Lane] and whether the operand at OpIdx is the LHS or 1261 // RHS operand. The LHS operand of both add and sub is never attached 1262 // to an inversese operation in the linearized form, therefore its APO 1263 // is false. The RHS is true only if VL[Lane] is an inverse operation. 1264 1265 // Since operand reordering is performed on groups of commutative 1266 // operations or alternating sequences (e.g., +, -), we can safely 1267 // tell the inverse operations by checking commutativity. 1268 bool IsInverseOperation = !isCommutative(cast<Instruction>(VL[Lane])); 1269 bool APO = (OpIdx == 0) ? false : IsInverseOperation; 1270 OpsVec[OpIdx][Lane] = {cast<Instruction>(VL[Lane])->getOperand(OpIdx), 1271 APO, false}; 1272 } 1273 } 1274 } 1275 1276 /// \returns the number of operands. 1277 unsigned getNumOperands() const { return OpsVec.size(); } 1278 1279 /// \returns the number of lanes. 1280 unsigned getNumLanes() const { return OpsVec[0].size(); } 1281 1282 /// \returns the operand value at \p OpIdx and \p Lane. 1283 Value *getValue(unsigned OpIdx, unsigned Lane) const { 1284 return getData(OpIdx, Lane).V; 1285 } 1286 1287 /// \returns true if the data structure is empty. 1288 bool empty() const { return OpsVec.empty(); } 1289 1290 /// Clears the data. 1291 void clear() { OpsVec.clear(); } 1292 1293 /// \Returns true if there are enough operands identical to \p Op to fill 1294 /// the whole vector. 1295 /// Note: This modifies the 'IsUsed' flag, so a cleanUsed() must follow. 1296 bool shouldBroadcast(Value *Op, unsigned OpIdx, unsigned Lane) { 1297 bool OpAPO = getData(OpIdx, Lane).APO; 1298 for (unsigned Ln = 0, Lns = getNumLanes(); Ln != Lns; ++Ln) { 1299 if (Ln == Lane) 1300 continue; 1301 // This is set to true if we found a candidate for broadcast at Lane. 1302 bool FoundCandidate = false; 1303 for (unsigned OpI = 0, OpE = getNumOperands(); OpI != OpE; ++OpI) { 1304 OperandData &Data = getData(OpI, Ln); 1305 if (Data.APO != OpAPO || Data.IsUsed) 1306 continue; 1307 if (Data.V == Op) { 1308 FoundCandidate = true; 1309 Data.IsUsed = true; 1310 break; 1311 } 1312 } 1313 if (!FoundCandidate) 1314 return false; 1315 } 1316 return true; 1317 } 1318 1319 public: 1320 /// Initialize with all the operands of the instruction vector \p RootVL. 1321 VLOperands(ArrayRef<Value *> RootVL, const DataLayout &DL, 1322 ScalarEvolution &SE, const BoUpSLP &R) 1323 : DL(DL), SE(SE), R(R) { 1324 // Append all the operands of RootVL. 1325 appendOperandsOfVL(RootVL); 1326 } 1327 1328 /// \Returns a value vector with the operands across all lanes for the 1329 /// opearnd at \p OpIdx. 1330 ValueList getVL(unsigned OpIdx) const { 1331 ValueList OpVL(OpsVec[OpIdx].size()); 1332 assert(OpsVec[OpIdx].size() == getNumLanes() && 1333 "Expected same num of lanes across all operands"); 1334 for (unsigned Lane = 0, Lanes = getNumLanes(); Lane != Lanes; ++Lane) 1335 OpVL[Lane] = OpsVec[OpIdx][Lane].V; 1336 return OpVL; 1337 } 1338 1339 // Performs operand reordering for 2 or more operands. 1340 // The original operands are in OrigOps[OpIdx][Lane]. 1341 // The reordered operands are returned in 'SortedOps[OpIdx][Lane]'. 1342 void reorder() { 1343 unsigned NumOperands = getNumOperands(); 1344 unsigned NumLanes = getNumLanes(); 1345 // Each operand has its own mode. We are using this mode to help us select 1346 // the instructions for each lane, so that they match best with the ones 1347 // we have selected so far. 1348 SmallVector<ReorderingMode, 2> ReorderingModes(NumOperands); 1349 1350 // This is a greedy single-pass algorithm. We are going over each lane 1351 // once and deciding on the best order right away with no back-tracking. 1352 // However, in order to increase its effectiveness, we start with the lane 1353 // that has operands that can move the least. For example, given the 1354 // following lanes: 1355 // Lane 0 : A[0] = B[0] + C[0] // Visited 3rd 1356 // Lane 1 : A[1] = C[1] - B[1] // Visited 1st 1357 // Lane 2 : A[2] = B[2] + C[2] // Visited 2nd 1358 // Lane 3 : A[3] = C[3] - B[3] // Visited 4th 1359 // we will start at Lane 1, since the operands of the subtraction cannot 1360 // be reordered. Then we will visit the rest of the lanes in a circular 1361 // fashion. That is, Lanes 2, then Lane 0, and finally Lane 3. 1362 1363 // Find the first lane that we will start our search from. 1364 unsigned FirstLane = getBestLaneToStartReordering(); 1365 1366 // Initialize the modes. 1367 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1368 Value *OpLane0 = getValue(OpIdx, FirstLane); 1369 // Keep track if we have instructions with all the same opcode on one 1370 // side. 1371 if (isa<LoadInst>(OpLane0)) 1372 ReorderingModes[OpIdx] = ReorderingMode::Load; 1373 else if (isa<Instruction>(OpLane0)) { 1374 // Check if OpLane0 should be broadcast. 1375 if (shouldBroadcast(OpLane0, OpIdx, FirstLane)) 1376 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1377 else 1378 ReorderingModes[OpIdx] = ReorderingMode::Opcode; 1379 } 1380 else if (isa<Constant>(OpLane0)) 1381 ReorderingModes[OpIdx] = ReorderingMode::Constant; 1382 else if (isa<Argument>(OpLane0)) 1383 // Our best hope is a Splat. It may save some cost in some cases. 1384 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1385 else 1386 // NOTE: This should be unreachable. 1387 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1388 } 1389 1390 // If the initial strategy fails for any of the operand indexes, then we 1391 // perform reordering again in a second pass. This helps avoid assigning 1392 // high priority to the failed strategy, and should improve reordering for 1393 // the non-failed operand indexes. 1394 for (int Pass = 0; Pass != 2; ++Pass) { 1395 // Skip the second pass if the first pass did not fail. 1396 bool StrategyFailed = false; 1397 // Mark all operand data as free to use. 1398 clearUsed(); 1399 // We keep the original operand order for the FirstLane, so reorder the 1400 // rest of the lanes. We are visiting the nodes in a circular fashion, 1401 // using FirstLane as the center point and increasing the radius 1402 // distance. 1403 for (unsigned Distance = 1; Distance != NumLanes; ++Distance) { 1404 // Visit the lane on the right and then the lane on the left. 1405 for (int Direction : {+1, -1}) { 1406 int Lane = FirstLane + Direction * Distance; 1407 if (Lane < 0 || Lane >= (int)NumLanes) 1408 continue; 1409 int LastLane = Lane - Direction; 1410 assert(LastLane >= 0 && LastLane < (int)NumLanes && 1411 "Out of bounds"); 1412 // Look for a good match for each operand. 1413 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1414 // Search for the operand that matches SortedOps[OpIdx][Lane-1]. 1415 Optional<unsigned> BestIdx = 1416 getBestOperand(OpIdx, Lane, LastLane, ReorderingModes); 1417 // By not selecting a value, we allow the operands that follow to 1418 // select a better matching value. We will get a non-null value in 1419 // the next run of getBestOperand(). 1420 if (BestIdx) { 1421 // Swap the current operand with the one returned by 1422 // getBestOperand(). 1423 swap(OpIdx, BestIdx.getValue(), Lane); 1424 } else { 1425 // We failed to find a best operand, set mode to 'Failed'. 1426 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1427 // Enable the second pass. 1428 StrategyFailed = true; 1429 } 1430 } 1431 } 1432 } 1433 // Skip second pass if the strategy did not fail. 1434 if (!StrategyFailed) 1435 break; 1436 } 1437 } 1438 1439 #if !defined(NDEBUG) || defined(LLVM_ENABLE_DUMP) 1440 LLVM_DUMP_METHOD static StringRef getModeStr(ReorderingMode RMode) { 1441 switch (RMode) { 1442 case ReorderingMode::Load: 1443 return "Load"; 1444 case ReorderingMode::Opcode: 1445 return "Opcode"; 1446 case ReorderingMode::Constant: 1447 return "Constant"; 1448 case ReorderingMode::Splat: 1449 return "Splat"; 1450 case ReorderingMode::Failed: 1451 return "Failed"; 1452 } 1453 llvm_unreachable("Unimplemented Reordering Type"); 1454 } 1455 1456 LLVM_DUMP_METHOD static raw_ostream &printMode(ReorderingMode RMode, 1457 raw_ostream &OS) { 1458 return OS << getModeStr(RMode); 1459 } 1460 1461 /// Debug print. 1462 LLVM_DUMP_METHOD static void dumpMode(ReorderingMode RMode) { 1463 printMode(RMode, dbgs()); 1464 } 1465 1466 friend raw_ostream &operator<<(raw_ostream &OS, ReorderingMode RMode) { 1467 return printMode(RMode, OS); 1468 } 1469 1470 LLVM_DUMP_METHOD raw_ostream &print(raw_ostream &OS) const { 1471 const unsigned Indent = 2; 1472 unsigned Cnt = 0; 1473 for (const OperandDataVec &OpDataVec : OpsVec) { 1474 OS << "Operand " << Cnt++ << "\n"; 1475 for (const OperandData &OpData : OpDataVec) { 1476 OS.indent(Indent) << "{"; 1477 if (Value *V = OpData.V) 1478 OS << *V; 1479 else 1480 OS << "null"; 1481 OS << ", APO:" << OpData.APO << "}\n"; 1482 } 1483 OS << "\n"; 1484 } 1485 return OS; 1486 } 1487 1488 /// Debug print. 1489 LLVM_DUMP_METHOD void dump() const { print(dbgs()); } 1490 #endif 1491 }; 1492 1493 /// Checks if the instruction is marked for deletion. 1494 bool isDeleted(Instruction *I) const { return DeletedInstructions.count(I); } 1495 1496 /// Marks values operands for later deletion by replacing them with Undefs. 1497 void eraseInstructions(ArrayRef<Value *> AV); 1498 1499 ~BoUpSLP(); 1500 1501 private: 1502 /// Checks if all users of \p I are the part of the vectorization tree. 1503 bool areAllUsersVectorized(Instruction *I) const; 1504 1505 /// \returns the cost of the vectorizable entry. 1506 InstructionCost getEntryCost(TreeEntry *E); 1507 1508 /// This is the recursive part of buildTree. 1509 void buildTree_rec(ArrayRef<Value *> Roots, unsigned Depth, 1510 const EdgeInfo &EI); 1511 1512 /// \returns true if the ExtractElement/ExtractValue instructions in \p VL can 1513 /// be vectorized to use the original vector (or aggregate "bitcast" to a 1514 /// vector) and sets \p CurrentOrder to the identity permutation; otherwise 1515 /// returns false, setting \p CurrentOrder to either an empty vector or a 1516 /// non-identity permutation that allows to reuse extract instructions. 1517 bool canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 1518 SmallVectorImpl<unsigned> &CurrentOrder) const; 1519 1520 /// Vectorize a single entry in the tree. 1521 Value *vectorizeTree(TreeEntry *E); 1522 1523 /// Vectorize a single entry in the tree, starting in \p VL. 1524 Value *vectorizeTree(ArrayRef<Value *> VL); 1525 1526 /// \returns the scalarization cost for this type. Scalarization in this 1527 /// context means the creation of vectors from a group of scalars. 1528 InstructionCost 1529 getGatherCost(FixedVectorType *Ty, 1530 const DenseSet<unsigned> &ShuffledIndices) const; 1531 1532 /// \returns the scalarization cost for this list of values. Assuming that 1533 /// this subtree gets vectorized, we may need to extract the values from the 1534 /// roots. This method calculates the cost of extracting the values. 1535 InstructionCost getGatherCost(ArrayRef<Value *> VL) const; 1536 1537 /// Set the Builder insert point to one after the last instruction in 1538 /// the bundle 1539 void setInsertPointAfterBundle(TreeEntry *E); 1540 1541 /// \returns a vector from a collection of scalars in \p VL. 1542 Value *gather(ArrayRef<Value *> VL); 1543 1544 /// \returns whether the VectorizableTree is fully vectorizable and will 1545 /// be beneficial even the tree height is tiny. 1546 bool isFullyVectorizableTinyTree() const; 1547 1548 /// Reorder commutative or alt operands to get better probability of 1549 /// generating vectorized code. 1550 static void reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 1551 SmallVectorImpl<Value *> &Left, 1552 SmallVectorImpl<Value *> &Right, 1553 const DataLayout &DL, 1554 ScalarEvolution &SE, 1555 const BoUpSLP &R); 1556 struct TreeEntry { 1557 using VecTreeTy = SmallVector<std::unique_ptr<TreeEntry>, 8>; 1558 TreeEntry(VecTreeTy &Container) : Container(Container) {} 1559 1560 /// \returns true if the scalars in VL are equal to this entry. 1561 bool isSame(ArrayRef<Value *> VL) const { 1562 if (VL.size() == Scalars.size()) 1563 return std::equal(VL.begin(), VL.end(), Scalars.begin()); 1564 return VL.size() == ReuseShuffleIndices.size() && 1565 std::equal( 1566 VL.begin(), VL.end(), ReuseShuffleIndices.begin(), 1567 [this](Value *V, int Idx) { return V == Scalars[Idx]; }); 1568 } 1569 1570 /// A vector of scalars. 1571 ValueList Scalars; 1572 1573 /// The Scalars are vectorized into this value. It is initialized to Null. 1574 Value *VectorizedValue = nullptr; 1575 1576 /// Do we need to gather this sequence or vectorize it 1577 /// (either with vector instruction or with scatter/gather 1578 /// intrinsics for store/load)? 1579 enum EntryState { Vectorize, ScatterVectorize, NeedToGather }; 1580 EntryState State; 1581 1582 /// Does this sequence require some shuffling? 1583 SmallVector<int, 4> ReuseShuffleIndices; 1584 1585 /// Does this entry require reordering? 1586 SmallVector<unsigned, 4> ReorderIndices; 1587 1588 /// Points back to the VectorizableTree. 1589 /// 1590 /// Only used for Graphviz right now. Unfortunately GraphTrait::NodeRef has 1591 /// to be a pointer and needs to be able to initialize the child iterator. 1592 /// Thus we need a reference back to the container to translate the indices 1593 /// to entries. 1594 VecTreeTy &Container; 1595 1596 /// The TreeEntry index containing the user of this entry. We can actually 1597 /// have multiple users so the data structure is not truly a tree. 1598 SmallVector<EdgeInfo, 1> UserTreeIndices; 1599 1600 /// The index of this treeEntry in VectorizableTree. 1601 int Idx = -1; 1602 1603 private: 1604 /// The operands of each instruction in each lane Operands[op_index][lane]. 1605 /// Note: This helps avoid the replication of the code that performs the 1606 /// reordering of operands during buildTree_rec() and vectorizeTree(). 1607 SmallVector<ValueList, 2> Operands; 1608 1609 /// The main/alternate instruction. 1610 Instruction *MainOp = nullptr; 1611 Instruction *AltOp = nullptr; 1612 1613 public: 1614 /// Set this bundle's \p OpIdx'th operand to \p OpVL. 1615 void setOperand(unsigned OpIdx, ArrayRef<Value *> OpVL) { 1616 if (Operands.size() < OpIdx + 1) 1617 Operands.resize(OpIdx + 1); 1618 assert(Operands[OpIdx].size() == 0 && "Already resized?"); 1619 Operands[OpIdx].resize(Scalars.size()); 1620 for (unsigned Lane = 0, E = Scalars.size(); Lane != E; ++Lane) 1621 Operands[OpIdx][Lane] = OpVL[Lane]; 1622 } 1623 1624 /// Set the operands of this bundle in their original order. 1625 void setOperandsInOrder() { 1626 assert(Operands.empty() && "Already initialized?"); 1627 auto *I0 = cast<Instruction>(Scalars[0]); 1628 Operands.resize(I0->getNumOperands()); 1629 unsigned NumLanes = Scalars.size(); 1630 for (unsigned OpIdx = 0, NumOperands = I0->getNumOperands(); 1631 OpIdx != NumOperands; ++OpIdx) { 1632 Operands[OpIdx].resize(NumLanes); 1633 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { 1634 auto *I = cast<Instruction>(Scalars[Lane]); 1635 assert(I->getNumOperands() == NumOperands && 1636 "Expected same number of operands"); 1637 Operands[OpIdx][Lane] = I->getOperand(OpIdx); 1638 } 1639 } 1640 } 1641 1642 /// \returns the \p OpIdx operand of this TreeEntry. 1643 ValueList &getOperand(unsigned OpIdx) { 1644 assert(OpIdx < Operands.size() && "Off bounds"); 1645 return Operands[OpIdx]; 1646 } 1647 1648 /// \returns the number of operands. 1649 unsigned getNumOperands() const { return Operands.size(); } 1650 1651 /// \return the single \p OpIdx operand. 1652 Value *getSingleOperand(unsigned OpIdx) const { 1653 assert(OpIdx < Operands.size() && "Off bounds"); 1654 assert(!Operands[OpIdx].empty() && "No operand available"); 1655 return Operands[OpIdx][0]; 1656 } 1657 1658 /// Some of the instructions in the list have alternate opcodes. 1659 bool isAltShuffle() const { 1660 return getOpcode() != getAltOpcode(); 1661 } 1662 1663 bool isOpcodeOrAlt(Instruction *I) const { 1664 unsigned CheckedOpcode = I->getOpcode(); 1665 return (getOpcode() == CheckedOpcode || 1666 getAltOpcode() == CheckedOpcode); 1667 } 1668 1669 /// Chooses the correct key for scheduling data. If \p Op has the same (or 1670 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is 1671 /// \p OpValue. 1672 Value *isOneOf(Value *Op) const { 1673 auto *I = dyn_cast<Instruction>(Op); 1674 if (I && isOpcodeOrAlt(I)) 1675 return Op; 1676 return MainOp; 1677 } 1678 1679 void setOperations(const InstructionsState &S) { 1680 MainOp = S.MainOp; 1681 AltOp = S.AltOp; 1682 } 1683 1684 Instruction *getMainOp() const { 1685 return MainOp; 1686 } 1687 1688 Instruction *getAltOp() const { 1689 return AltOp; 1690 } 1691 1692 /// The main/alternate opcodes for the list of instructions. 1693 unsigned getOpcode() const { 1694 return MainOp ? MainOp->getOpcode() : 0; 1695 } 1696 1697 unsigned getAltOpcode() const { 1698 return AltOp ? AltOp->getOpcode() : 0; 1699 } 1700 1701 /// Update operations state of this entry if reorder occurred. 1702 bool updateStateIfReorder() { 1703 if (ReorderIndices.empty()) 1704 return false; 1705 InstructionsState S = getSameOpcode(Scalars, ReorderIndices.front()); 1706 setOperations(S); 1707 return true; 1708 } 1709 1710 #ifndef NDEBUG 1711 /// Debug printer. 1712 LLVM_DUMP_METHOD void dump() const { 1713 dbgs() << Idx << ".\n"; 1714 for (unsigned OpI = 0, OpE = Operands.size(); OpI != OpE; ++OpI) { 1715 dbgs() << "Operand " << OpI << ":\n"; 1716 for (const Value *V : Operands[OpI]) 1717 dbgs().indent(2) << *V << "\n"; 1718 } 1719 dbgs() << "Scalars: \n"; 1720 for (Value *V : Scalars) 1721 dbgs().indent(2) << *V << "\n"; 1722 dbgs() << "State: "; 1723 switch (State) { 1724 case Vectorize: 1725 dbgs() << "Vectorize\n"; 1726 break; 1727 case ScatterVectorize: 1728 dbgs() << "ScatterVectorize\n"; 1729 break; 1730 case NeedToGather: 1731 dbgs() << "NeedToGather\n"; 1732 break; 1733 } 1734 dbgs() << "MainOp: "; 1735 if (MainOp) 1736 dbgs() << *MainOp << "\n"; 1737 else 1738 dbgs() << "NULL\n"; 1739 dbgs() << "AltOp: "; 1740 if (AltOp) 1741 dbgs() << *AltOp << "\n"; 1742 else 1743 dbgs() << "NULL\n"; 1744 dbgs() << "VectorizedValue: "; 1745 if (VectorizedValue) 1746 dbgs() << *VectorizedValue << "\n"; 1747 else 1748 dbgs() << "NULL\n"; 1749 dbgs() << "ReuseShuffleIndices: "; 1750 if (ReuseShuffleIndices.empty()) 1751 dbgs() << "Empty"; 1752 else 1753 for (unsigned ReuseIdx : ReuseShuffleIndices) 1754 dbgs() << ReuseIdx << ", "; 1755 dbgs() << "\n"; 1756 dbgs() << "ReorderIndices: "; 1757 for (unsigned ReorderIdx : ReorderIndices) 1758 dbgs() << ReorderIdx << ", "; 1759 dbgs() << "\n"; 1760 dbgs() << "UserTreeIndices: "; 1761 for (const auto &EInfo : UserTreeIndices) 1762 dbgs() << EInfo << ", "; 1763 dbgs() << "\n"; 1764 } 1765 #endif 1766 }; 1767 1768 #ifndef NDEBUG 1769 void dumpTreeCosts(TreeEntry *E, InstructionCost ReuseShuffleCost, 1770 InstructionCost VecCost, 1771 InstructionCost ScalarCost) const { 1772 dbgs() << "SLP: Calculated costs for Tree:\n"; E->dump(); 1773 dbgs() << "SLP: Costs:\n"; 1774 dbgs() << "SLP: ReuseShuffleCost = " << ReuseShuffleCost << "\n"; 1775 dbgs() << "SLP: VectorCost = " << VecCost << "\n"; 1776 dbgs() << "SLP: ScalarCost = " << ScalarCost << "\n"; 1777 dbgs() << "SLP: ReuseShuffleCost + VecCost - ScalarCost = " << 1778 ReuseShuffleCost + VecCost - ScalarCost << "\n"; 1779 } 1780 #endif 1781 1782 /// Create a new VectorizableTree entry. 1783 TreeEntry *newTreeEntry(ArrayRef<Value *> VL, Optional<ScheduleData *> Bundle, 1784 const InstructionsState &S, 1785 const EdgeInfo &UserTreeIdx, 1786 ArrayRef<unsigned> ReuseShuffleIndices = None, 1787 ArrayRef<unsigned> ReorderIndices = None) { 1788 TreeEntry::EntryState EntryState = 1789 Bundle ? TreeEntry::Vectorize : TreeEntry::NeedToGather; 1790 return newTreeEntry(VL, EntryState, Bundle, S, UserTreeIdx, 1791 ReuseShuffleIndices, ReorderIndices); 1792 } 1793 1794 TreeEntry *newTreeEntry(ArrayRef<Value *> VL, 1795 TreeEntry::EntryState EntryState, 1796 Optional<ScheduleData *> Bundle, 1797 const InstructionsState &S, 1798 const EdgeInfo &UserTreeIdx, 1799 ArrayRef<unsigned> ReuseShuffleIndices = None, 1800 ArrayRef<unsigned> ReorderIndices = None) { 1801 assert(((!Bundle && EntryState == TreeEntry::NeedToGather) || 1802 (Bundle && EntryState != TreeEntry::NeedToGather)) && 1803 "Need to vectorize gather entry?"); 1804 VectorizableTree.push_back(std::make_unique<TreeEntry>(VectorizableTree)); 1805 TreeEntry *Last = VectorizableTree.back().get(); 1806 Last->Idx = VectorizableTree.size() - 1; 1807 Last->Scalars.insert(Last->Scalars.begin(), VL.begin(), VL.end()); 1808 Last->State = EntryState; 1809 Last->ReuseShuffleIndices.append(ReuseShuffleIndices.begin(), 1810 ReuseShuffleIndices.end()); 1811 Last->ReorderIndices.append(ReorderIndices.begin(), ReorderIndices.end()); 1812 Last->setOperations(S); 1813 if (Last->State != TreeEntry::NeedToGather) { 1814 for (Value *V : VL) { 1815 assert(!getTreeEntry(V) && "Scalar already in tree!"); 1816 ScalarToTreeEntry[V] = Last; 1817 } 1818 // Update the scheduler bundle to point to this TreeEntry. 1819 unsigned Lane = 0; 1820 for (ScheduleData *BundleMember = Bundle.getValue(); BundleMember; 1821 BundleMember = BundleMember->NextInBundle) { 1822 BundleMember->TE = Last; 1823 BundleMember->Lane = Lane; 1824 ++Lane; 1825 } 1826 assert((!Bundle.getValue() || Lane == VL.size()) && 1827 "Bundle and VL out of sync"); 1828 } else { 1829 MustGather.insert(VL.begin(), VL.end()); 1830 } 1831 1832 if (UserTreeIdx.UserTE) 1833 Last->UserTreeIndices.push_back(UserTreeIdx); 1834 1835 return Last; 1836 } 1837 1838 /// -- Vectorization State -- 1839 /// Holds all of the tree entries. 1840 TreeEntry::VecTreeTy VectorizableTree; 1841 1842 #ifndef NDEBUG 1843 /// Debug printer. 1844 LLVM_DUMP_METHOD void dumpVectorizableTree() const { 1845 for (unsigned Id = 0, IdE = VectorizableTree.size(); Id != IdE; ++Id) { 1846 VectorizableTree[Id]->dump(); 1847 dbgs() << "\n"; 1848 } 1849 } 1850 #endif 1851 1852 TreeEntry *getTreeEntry(Value *V) { return ScalarToTreeEntry.lookup(V); } 1853 1854 const TreeEntry *getTreeEntry(Value *V) const { 1855 return ScalarToTreeEntry.lookup(V); 1856 } 1857 1858 /// Maps a specific scalar to its tree entry. 1859 SmallDenseMap<Value*, TreeEntry *> ScalarToTreeEntry; 1860 1861 /// Maps a value to the proposed vectorizable size. 1862 SmallDenseMap<Value *, unsigned> InstrElementSize; 1863 1864 /// A list of scalars that we found that we need to keep as scalars. 1865 ValueSet MustGather; 1866 1867 /// This POD struct describes one external user in the vectorized tree. 1868 struct ExternalUser { 1869 ExternalUser(Value *S, llvm::User *U, int L) 1870 : Scalar(S), User(U), Lane(L) {} 1871 1872 // Which scalar in our function. 1873 Value *Scalar; 1874 1875 // Which user that uses the scalar. 1876 llvm::User *User; 1877 1878 // Which lane does the scalar belong to. 1879 int Lane; 1880 }; 1881 using UserList = SmallVector<ExternalUser, 16>; 1882 1883 /// Checks if two instructions may access the same memory. 1884 /// 1885 /// \p Loc1 is the location of \p Inst1. It is passed explicitly because it 1886 /// is invariant in the calling loop. 1887 bool isAliased(const MemoryLocation &Loc1, Instruction *Inst1, 1888 Instruction *Inst2) { 1889 // First check if the result is already in the cache. 1890 AliasCacheKey key = std::make_pair(Inst1, Inst2); 1891 Optional<bool> &result = AliasCache[key]; 1892 if (result.hasValue()) { 1893 return result.getValue(); 1894 } 1895 MemoryLocation Loc2 = getLocation(Inst2, AA); 1896 bool aliased = true; 1897 if (Loc1.Ptr && Loc2.Ptr && isSimple(Inst1) && isSimple(Inst2)) { 1898 // Do the alias check. 1899 aliased = AA->alias(Loc1, Loc2); 1900 } 1901 // Store the result in the cache. 1902 result = aliased; 1903 return aliased; 1904 } 1905 1906 using AliasCacheKey = std::pair<Instruction *, Instruction *>; 1907 1908 /// Cache for alias results. 1909 /// TODO: consider moving this to the AliasAnalysis itself. 1910 DenseMap<AliasCacheKey, Optional<bool>> AliasCache; 1911 1912 /// Removes an instruction from its block and eventually deletes it. 1913 /// It's like Instruction::eraseFromParent() except that the actual deletion 1914 /// is delayed until BoUpSLP is destructed. 1915 /// This is required to ensure that there are no incorrect collisions in the 1916 /// AliasCache, which can happen if a new instruction is allocated at the 1917 /// same address as a previously deleted instruction. 1918 void eraseInstruction(Instruction *I, bool ReplaceOpsWithUndef = false) { 1919 auto It = DeletedInstructions.try_emplace(I, ReplaceOpsWithUndef).first; 1920 It->getSecond() = It->getSecond() && ReplaceOpsWithUndef; 1921 } 1922 1923 /// Temporary store for deleted instructions. Instructions will be deleted 1924 /// eventually when the BoUpSLP is destructed. 1925 DenseMap<Instruction *, bool> DeletedInstructions; 1926 1927 /// A list of values that need to extracted out of the tree. 1928 /// This list holds pairs of (Internal Scalar : External User). External User 1929 /// can be nullptr, it means that this Internal Scalar will be used later, 1930 /// after vectorization. 1931 UserList ExternalUses; 1932 1933 /// Values used only by @llvm.assume calls. 1934 SmallPtrSet<const Value *, 32> EphValues; 1935 1936 /// Holds all of the instructions that we gathered. 1937 SetVector<Instruction *> GatherSeq; 1938 1939 /// A list of blocks that we are going to CSE. 1940 SetVector<BasicBlock *> CSEBlocks; 1941 1942 /// Contains all scheduling relevant data for an instruction. 1943 /// A ScheduleData either represents a single instruction or a member of an 1944 /// instruction bundle (= a group of instructions which is combined into a 1945 /// vector instruction). 1946 struct ScheduleData { 1947 // The initial value for the dependency counters. It means that the 1948 // dependencies are not calculated yet. 1949 enum { InvalidDeps = -1 }; 1950 1951 ScheduleData() = default; 1952 1953 void init(int BlockSchedulingRegionID, Value *OpVal) { 1954 FirstInBundle = this; 1955 NextInBundle = nullptr; 1956 NextLoadStore = nullptr; 1957 IsScheduled = false; 1958 SchedulingRegionID = BlockSchedulingRegionID; 1959 UnscheduledDepsInBundle = UnscheduledDeps; 1960 clearDependencies(); 1961 OpValue = OpVal; 1962 TE = nullptr; 1963 Lane = -1; 1964 } 1965 1966 /// Returns true if the dependency information has been calculated. 1967 bool hasValidDependencies() const { return Dependencies != InvalidDeps; } 1968 1969 /// Returns true for single instructions and for bundle representatives 1970 /// (= the head of a bundle). 1971 bool isSchedulingEntity() const { return FirstInBundle == this; } 1972 1973 /// Returns true if it represents an instruction bundle and not only a 1974 /// single instruction. 1975 bool isPartOfBundle() const { 1976 return NextInBundle != nullptr || FirstInBundle != this; 1977 } 1978 1979 /// Returns true if it is ready for scheduling, i.e. it has no more 1980 /// unscheduled depending instructions/bundles. 1981 bool isReady() const { 1982 assert(isSchedulingEntity() && 1983 "can't consider non-scheduling entity for ready list"); 1984 return UnscheduledDepsInBundle == 0 && !IsScheduled; 1985 } 1986 1987 /// Modifies the number of unscheduled dependencies, also updating it for 1988 /// the whole bundle. 1989 int incrementUnscheduledDeps(int Incr) { 1990 UnscheduledDeps += Incr; 1991 return FirstInBundle->UnscheduledDepsInBundle += Incr; 1992 } 1993 1994 /// Sets the number of unscheduled dependencies to the number of 1995 /// dependencies. 1996 void resetUnscheduledDeps() { 1997 incrementUnscheduledDeps(Dependencies - UnscheduledDeps); 1998 } 1999 2000 /// Clears all dependency information. 2001 void clearDependencies() { 2002 Dependencies = InvalidDeps; 2003 resetUnscheduledDeps(); 2004 MemoryDependencies.clear(); 2005 } 2006 2007 void dump(raw_ostream &os) const { 2008 if (!isSchedulingEntity()) { 2009 os << "/ " << *Inst; 2010 } else if (NextInBundle) { 2011 os << '[' << *Inst; 2012 ScheduleData *SD = NextInBundle; 2013 while (SD) { 2014 os << ';' << *SD->Inst; 2015 SD = SD->NextInBundle; 2016 } 2017 os << ']'; 2018 } else { 2019 os << *Inst; 2020 } 2021 } 2022 2023 Instruction *Inst = nullptr; 2024 2025 /// Points to the head in an instruction bundle (and always to this for 2026 /// single instructions). 2027 ScheduleData *FirstInBundle = nullptr; 2028 2029 /// Single linked list of all instructions in a bundle. Null if it is a 2030 /// single instruction. 2031 ScheduleData *NextInBundle = nullptr; 2032 2033 /// Single linked list of all memory instructions (e.g. load, store, call) 2034 /// in the block - until the end of the scheduling region. 2035 ScheduleData *NextLoadStore = nullptr; 2036 2037 /// The dependent memory instructions. 2038 /// This list is derived on demand in calculateDependencies(). 2039 SmallVector<ScheduleData *, 4> MemoryDependencies; 2040 2041 /// This ScheduleData is in the current scheduling region if this matches 2042 /// the current SchedulingRegionID of BlockScheduling. 2043 int SchedulingRegionID = 0; 2044 2045 /// Used for getting a "good" final ordering of instructions. 2046 int SchedulingPriority = 0; 2047 2048 /// The number of dependencies. Constitutes of the number of users of the 2049 /// instruction plus the number of dependent memory instructions (if any). 2050 /// This value is calculated on demand. 2051 /// If InvalidDeps, the number of dependencies is not calculated yet. 2052 int Dependencies = InvalidDeps; 2053 2054 /// The number of dependencies minus the number of dependencies of scheduled 2055 /// instructions. As soon as this is zero, the instruction/bundle gets ready 2056 /// for scheduling. 2057 /// Note that this is negative as long as Dependencies is not calculated. 2058 int UnscheduledDeps = InvalidDeps; 2059 2060 /// The sum of UnscheduledDeps in a bundle. Equals to UnscheduledDeps for 2061 /// single instructions. 2062 int UnscheduledDepsInBundle = InvalidDeps; 2063 2064 /// True if this instruction is scheduled (or considered as scheduled in the 2065 /// dry-run). 2066 bool IsScheduled = false; 2067 2068 /// Opcode of the current instruction in the schedule data. 2069 Value *OpValue = nullptr; 2070 2071 /// The TreeEntry that this instruction corresponds to. 2072 TreeEntry *TE = nullptr; 2073 2074 /// The lane of this node in the TreeEntry. 2075 int Lane = -1; 2076 }; 2077 2078 #ifndef NDEBUG 2079 friend inline raw_ostream &operator<<(raw_ostream &os, 2080 const BoUpSLP::ScheduleData &SD) { 2081 SD.dump(os); 2082 return os; 2083 } 2084 #endif 2085 2086 friend struct GraphTraits<BoUpSLP *>; 2087 friend struct DOTGraphTraits<BoUpSLP *>; 2088 2089 /// Contains all scheduling data for a basic block. 2090 struct BlockScheduling { 2091 BlockScheduling(BasicBlock *BB) 2092 : BB(BB), ChunkSize(BB->size()), ChunkPos(ChunkSize) {} 2093 2094 void clear() { 2095 ReadyInsts.clear(); 2096 ScheduleStart = nullptr; 2097 ScheduleEnd = nullptr; 2098 FirstLoadStoreInRegion = nullptr; 2099 LastLoadStoreInRegion = nullptr; 2100 2101 // Reduce the maximum schedule region size by the size of the 2102 // previous scheduling run. 2103 ScheduleRegionSizeLimit -= ScheduleRegionSize; 2104 if (ScheduleRegionSizeLimit < MinScheduleRegionSize) 2105 ScheduleRegionSizeLimit = MinScheduleRegionSize; 2106 ScheduleRegionSize = 0; 2107 2108 // Make a new scheduling region, i.e. all existing ScheduleData is not 2109 // in the new region yet. 2110 ++SchedulingRegionID; 2111 } 2112 2113 ScheduleData *getScheduleData(Value *V) { 2114 ScheduleData *SD = ScheduleDataMap[V]; 2115 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 2116 return SD; 2117 return nullptr; 2118 } 2119 2120 ScheduleData *getScheduleData(Value *V, Value *Key) { 2121 if (V == Key) 2122 return getScheduleData(V); 2123 auto I = ExtraScheduleDataMap.find(V); 2124 if (I != ExtraScheduleDataMap.end()) { 2125 ScheduleData *SD = I->second[Key]; 2126 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 2127 return SD; 2128 } 2129 return nullptr; 2130 } 2131 2132 bool isInSchedulingRegion(ScheduleData *SD) const { 2133 return SD->SchedulingRegionID == SchedulingRegionID; 2134 } 2135 2136 /// Marks an instruction as scheduled and puts all dependent ready 2137 /// instructions into the ready-list. 2138 template <typename ReadyListType> 2139 void schedule(ScheduleData *SD, ReadyListType &ReadyList) { 2140 SD->IsScheduled = true; 2141 LLVM_DEBUG(dbgs() << "SLP: schedule " << *SD << "\n"); 2142 2143 ScheduleData *BundleMember = SD; 2144 while (BundleMember) { 2145 if (BundleMember->Inst != BundleMember->OpValue) { 2146 BundleMember = BundleMember->NextInBundle; 2147 continue; 2148 } 2149 // Handle the def-use chain dependencies. 2150 2151 // Decrement the unscheduled counter and insert to ready list if ready. 2152 auto &&DecrUnsched = [this, &ReadyList](Instruction *I) { 2153 doForAllOpcodes(I, [&ReadyList](ScheduleData *OpDef) { 2154 if (OpDef && OpDef->hasValidDependencies() && 2155 OpDef->incrementUnscheduledDeps(-1) == 0) { 2156 // There are no more unscheduled dependencies after 2157 // decrementing, so we can put the dependent instruction 2158 // into the ready list. 2159 ScheduleData *DepBundle = OpDef->FirstInBundle; 2160 assert(!DepBundle->IsScheduled && 2161 "already scheduled bundle gets ready"); 2162 ReadyList.insert(DepBundle); 2163 LLVM_DEBUG(dbgs() 2164 << "SLP: gets ready (def): " << *DepBundle << "\n"); 2165 } 2166 }); 2167 }; 2168 2169 // If BundleMember is a vector bundle, its operands may have been 2170 // reordered duiring buildTree(). We therefore need to get its operands 2171 // through the TreeEntry. 2172 if (TreeEntry *TE = BundleMember->TE) { 2173 int Lane = BundleMember->Lane; 2174 assert(Lane >= 0 && "Lane not set"); 2175 2176 // Since vectorization tree is being built recursively this assertion 2177 // ensures that the tree entry has all operands set before reaching 2178 // this code. Couple of exceptions known at the moment are extracts 2179 // where their second (immediate) operand is not added. Since 2180 // immediates do not affect scheduler behavior this is considered 2181 // okay. 2182 auto *In = TE->getMainOp(); 2183 assert(In && 2184 (isa<ExtractValueInst>(In) || isa<ExtractElementInst>(In) || 2185 In->getNumOperands() == TE->getNumOperands()) && 2186 "Missed TreeEntry operands?"); 2187 (void)In; // fake use to avoid build failure when assertions disabled 2188 2189 for (unsigned OpIdx = 0, NumOperands = TE->getNumOperands(); 2190 OpIdx != NumOperands; ++OpIdx) 2191 if (auto *I = dyn_cast<Instruction>(TE->getOperand(OpIdx)[Lane])) 2192 DecrUnsched(I); 2193 } else { 2194 // If BundleMember is a stand-alone instruction, no operand reordering 2195 // has taken place, so we directly access its operands. 2196 for (Use &U : BundleMember->Inst->operands()) 2197 if (auto *I = dyn_cast<Instruction>(U.get())) 2198 DecrUnsched(I); 2199 } 2200 // Handle the memory dependencies. 2201 for (ScheduleData *MemoryDepSD : BundleMember->MemoryDependencies) { 2202 if (MemoryDepSD->incrementUnscheduledDeps(-1) == 0) { 2203 // There are no more unscheduled dependencies after decrementing, 2204 // so we can put the dependent instruction into the ready list. 2205 ScheduleData *DepBundle = MemoryDepSD->FirstInBundle; 2206 assert(!DepBundle->IsScheduled && 2207 "already scheduled bundle gets ready"); 2208 ReadyList.insert(DepBundle); 2209 LLVM_DEBUG(dbgs() 2210 << "SLP: gets ready (mem): " << *DepBundle << "\n"); 2211 } 2212 } 2213 BundleMember = BundleMember->NextInBundle; 2214 } 2215 } 2216 2217 void doForAllOpcodes(Value *V, 2218 function_ref<void(ScheduleData *SD)> Action) { 2219 if (ScheduleData *SD = getScheduleData(V)) 2220 Action(SD); 2221 auto I = ExtraScheduleDataMap.find(V); 2222 if (I != ExtraScheduleDataMap.end()) 2223 for (auto &P : I->second) 2224 if (P.second->SchedulingRegionID == SchedulingRegionID) 2225 Action(P.second); 2226 } 2227 2228 /// Put all instructions into the ReadyList which are ready for scheduling. 2229 template <typename ReadyListType> 2230 void initialFillReadyList(ReadyListType &ReadyList) { 2231 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 2232 doForAllOpcodes(I, [&](ScheduleData *SD) { 2233 if (SD->isSchedulingEntity() && SD->isReady()) { 2234 ReadyList.insert(SD); 2235 LLVM_DEBUG(dbgs() 2236 << "SLP: initially in ready list: " << *I << "\n"); 2237 } 2238 }); 2239 } 2240 } 2241 2242 /// Checks if a bundle of instructions can be scheduled, i.e. has no 2243 /// cyclic dependencies. This is only a dry-run, no instructions are 2244 /// actually moved at this stage. 2245 /// \returns the scheduling bundle. The returned Optional value is non-None 2246 /// if \p VL is allowed to be scheduled. 2247 Optional<ScheduleData *> 2248 tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 2249 const InstructionsState &S); 2250 2251 /// Un-bundles a group of instructions. 2252 void cancelScheduling(ArrayRef<Value *> VL, Value *OpValue); 2253 2254 /// Allocates schedule data chunk. 2255 ScheduleData *allocateScheduleDataChunks(); 2256 2257 /// Extends the scheduling region so that V is inside the region. 2258 /// \returns true if the region size is within the limit. 2259 bool extendSchedulingRegion(Value *V, const InstructionsState &S); 2260 2261 /// Initialize the ScheduleData structures for new instructions in the 2262 /// scheduling region. 2263 void initScheduleData(Instruction *FromI, Instruction *ToI, 2264 ScheduleData *PrevLoadStore, 2265 ScheduleData *NextLoadStore); 2266 2267 /// Updates the dependency information of a bundle and of all instructions/ 2268 /// bundles which depend on the original bundle. 2269 void calculateDependencies(ScheduleData *SD, bool InsertInReadyList, 2270 BoUpSLP *SLP); 2271 2272 /// Sets all instruction in the scheduling region to un-scheduled. 2273 void resetSchedule(); 2274 2275 BasicBlock *BB; 2276 2277 /// Simple memory allocation for ScheduleData. 2278 std::vector<std::unique_ptr<ScheduleData[]>> ScheduleDataChunks; 2279 2280 /// The size of a ScheduleData array in ScheduleDataChunks. 2281 int ChunkSize; 2282 2283 /// The allocator position in the current chunk, which is the last entry 2284 /// of ScheduleDataChunks. 2285 int ChunkPos; 2286 2287 /// Attaches ScheduleData to Instruction. 2288 /// Note that the mapping survives during all vectorization iterations, i.e. 2289 /// ScheduleData structures are recycled. 2290 DenseMap<Value *, ScheduleData *> ScheduleDataMap; 2291 2292 /// Attaches ScheduleData to Instruction with the leading key. 2293 DenseMap<Value *, SmallDenseMap<Value *, ScheduleData *>> 2294 ExtraScheduleDataMap; 2295 2296 struct ReadyList : SmallVector<ScheduleData *, 8> { 2297 void insert(ScheduleData *SD) { push_back(SD); } 2298 }; 2299 2300 /// The ready-list for scheduling (only used for the dry-run). 2301 ReadyList ReadyInsts; 2302 2303 /// The first instruction of the scheduling region. 2304 Instruction *ScheduleStart = nullptr; 2305 2306 /// The first instruction _after_ the scheduling region. 2307 Instruction *ScheduleEnd = nullptr; 2308 2309 /// The first memory accessing instruction in the scheduling region 2310 /// (can be null). 2311 ScheduleData *FirstLoadStoreInRegion = nullptr; 2312 2313 /// The last memory accessing instruction in the scheduling region 2314 /// (can be null). 2315 ScheduleData *LastLoadStoreInRegion = nullptr; 2316 2317 /// The current size of the scheduling region. 2318 int ScheduleRegionSize = 0; 2319 2320 /// The maximum size allowed for the scheduling region. 2321 int ScheduleRegionSizeLimit = ScheduleRegionSizeBudget; 2322 2323 /// The ID of the scheduling region. For a new vectorization iteration this 2324 /// is incremented which "removes" all ScheduleData from the region. 2325 // Make sure that the initial SchedulingRegionID is greater than the 2326 // initial SchedulingRegionID in ScheduleData (which is 0). 2327 int SchedulingRegionID = 1; 2328 }; 2329 2330 /// Attaches the BlockScheduling structures to basic blocks. 2331 MapVector<BasicBlock *, std::unique_ptr<BlockScheduling>> BlocksSchedules; 2332 2333 /// Performs the "real" scheduling. Done before vectorization is actually 2334 /// performed in a basic block. 2335 void scheduleBlock(BlockScheduling *BS); 2336 2337 /// List of users to ignore during scheduling and that don't need extracting. 2338 ArrayRef<Value *> UserIgnoreList; 2339 2340 /// A DenseMapInfo implementation for holding DenseMaps and DenseSets of 2341 /// sorted SmallVectors of unsigned. 2342 struct OrdersTypeDenseMapInfo { 2343 static OrdersType getEmptyKey() { 2344 OrdersType V; 2345 V.push_back(~1U); 2346 return V; 2347 } 2348 2349 static OrdersType getTombstoneKey() { 2350 OrdersType V; 2351 V.push_back(~2U); 2352 return V; 2353 } 2354 2355 static unsigned getHashValue(const OrdersType &V) { 2356 return static_cast<unsigned>(hash_combine_range(V.begin(), V.end())); 2357 } 2358 2359 static bool isEqual(const OrdersType &LHS, const OrdersType &RHS) { 2360 return LHS == RHS; 2361 } 2362 }; 2363 2364 /// Contains orders of operations along with the number of bundles that have 2365 /// operations in this order. It stores only those orders that require 2366 /// reordering, if reordering is not required it is counted using \a 2367 /// NumOpsWantToKeepOriginalOrder. 2368 DenseMap<OrdersType, unsigned, OrdersTypeDenseMapInfo> NumOpsWantToKeepOrder; 2369 /// Number of bundles that do not require reordering. 2370 unsigned NumOpsWantToKeepOriginalOrder = 0; 2371 2372 // Analysis and block reference. 2373 Function *F; 2374 ScalarEvolution *SE; 2375 TargetTransformInfo *TTI; 2376 TargetLibraryInfo *TLI; 2377 AAResults *AA; 2378 LoopInfo *LI; 2379 DominatorTree *DT; 2380 AssumptionCache *AC; 2381 DemandedBits *DB; 2382 const DataLayout *DL; 2383 OptimizationRemarkEmitter *ORE; 2384 2385 unsigned MaxVecRegSize; // This is set by TTI or overridden by cl::opt. 2386 unsigned MinVecRegSize; // Set by cl::opt (default: 128). 2387 2388 /// Instruction builder to construct the vectorized tree. 2389 IRBuilder<> Builder; 2390 2391 /// A map of scalar integer values to the smallest bit width with which they 2392 /// can legally be represented. The values map to (width, signed) pairs, 2393 /// where "width" indicates the minimum bit width and "signed" is True if the 2394 /// value must be signed-extended, rather than zero-extended, back to its 2395 /// original width. 2396 MapVector<Value *, std::pair<uint64_t, bool>> MinBWs; 2397 }; 2398 2399 } // end namespace slpvectorizer 2400 2401 template <> struct GraphTraits<BoUpSLP *> { 2402 using TreeEntry = BoUpSLP::TreeEntry; 2403 2404 /// NodeRef has to be a pointer per the GraphWriter. 2405 using NodeRef = TreeEntry *; 2406 2407 using ContainerTy = BoUpSLP::TreeEntry::VecTreeTy; 2408 2409 /// Add the VectorizableTree to the index iterator to be able to return 2410 /// TreeEntry pointers. 2411 struct ChildIteratorType 2412 : public iterator_adaptor_base< 2413 ChildIteratorType, SmallVector<BoUpSLP::EdgeInfo, 1>::iterator> { 2414 ContainerTy &VectorizableTree; 2415 2416 ChildIteratorType(SmallVector<BoUpSLP::EdgeInfo, 1>::iterator W, 2417 ContainerTy &VT) 2418 : ChildIteratorType::iterator_adaptor_base(W), VectorizableTree(VT) {} 2419 2420 NodeRef operator*() { return I->UserTE; } 2421 }; 2422 2423 static NodeRef getEntryNode(BoUpSLP &R) { 2424 return R.VectorizableTree[0].get(); 2425 } 2426 2427 static ChildIteratorType child_begin(NodeRef N) { 2428 return {N->UserTreeIndices.begin(), N->Container}; 2429 } 2430 2431 static ChildIteratorType child_end(NodeRef N) { 2432 return {N->UserTreeIndices.end(), N->Container}; 2433 } 2434 2435 /// For the node iterator we just need to turn the TreeEntry iterator into a 2436 /// TreeEntry* iterator so that it dereferences to NodeRef. 2437 class nodes_iterator { 2438 using ItTy = ContainerTy::iterator; 2439 ItTy It; 2440 2441 public: 2442 nodes_iterator(const ItTy &It2) : It(It2) {} 2443 NodeRef operator*() { return It->get(); } 2444 nodes_iterator operator++() { 2445 ++It; 2446 return *this; 2447 } 2448 bool operator!=(const nodes_iterator &N2) const { return N2.It != It; } 2449 }; 2450 2451 static nodes_iterator nodes_begin(BoUpSLP *R) { 2452 return nodes_iterator(R->VectorizableTree.begin()); 2453 } 2454 2455 static nodes_iterator nodes_end(BoUpSLP *R) { 2456 return nodes_iterator(R->VectorizableTree.end()); 2457 } 2458 2459 static unsigned size(BoUpSLP *R) { return R->VectorizableTree.size(); } 2460 }; 2461 2462 template <> struct DOTGraphTraits<BoUpSLP *> : public DefaultDOTGraphTraits { 2463 using TreeEntry = BoUpSLP::TreeEntry; 2464 2465 DOTGraphTraits(bool isSimple = false) : DefaultDOTGraphTraits(isSimple) {} 2466 2467 std::string getNodeLabel(const TreeEntry *Entry, const BoUpSLP *R) { 2468 std::string Str; 2469 raw_string_ostream OS(Str); 2470 if (isSplat(Entry->Scalars)) { 2471 OS << "<splat> " << *Entry->Scalars[0]; 2472 return Str; 2473 } 2474 for (auto V : Entry->Scalars) { 2475 OS << *V; 2476 if (llvm::any_of(R->ExternalUses, [&](const BoUpSLP::ExternalUser &EU) { 2477 return EU.Scalar == V; 2478 })) 2479 OS << " <extract>"; 2480 OS << "\n"; 2481 } 2482 return Str; 2483 } 2484 2485 static std::string getNodeAttributes(const TreeEntry *Entry, 2486 const BoUpSLP *) { 2487 if (Entry->State == TreeEntry::NeedToGather) 2488 return "color=red"; 2489 return ""; 2490 } 2491 }; 2492 2493 } // end namespace llvm 2494 2495 BoUpSLP::~BoUpSLP() { 2496 for (const auto &Pair : DeletedInstructions) { 2497 // Replace operands of ignored instructions with Undefs in case if they were 2498 // marked for deletion. 2499 if (Pair.getSecond()) { 2500 Value *Undef = UndefValue::get(Pair.getFirst()->getType()); 2501 Pair.getFirst()->replaceAllUsesWith(Undef); 2502 } 2503 Pair.getFirst()->dropAllReferences(); 2504 } 2505 for (const auto &Pair : DeletedInstructions) { 2506 assert(Pair.getFirst()->use_empty() && 2507 "trying to erase instruction with users."); 2508 Pair.getFirst()->eraseFromParent(); 2509 } 2510 #ifdef EXPENSIVE_CHECKS 2511 // If we could guarantee that this call is not extremely slow, we could 2512 // remove the ifdef limitation (see PR47712). 2513 assert(!verifyFunction(*F, &dbgs())); 2514 #endif 2515 } 2516 2517 void BoUpSLP::eraseInstructions(ArrayRef<Value *> AV) { 2518 for (auto *V : AV) { 2519 if (auto *I = dyn_cast<Instruction>(V)) 2520 eraseInstruction(I, /*ReplaceOpsWithUndef=*/true); 2521 }; 2522 } 2523 2524 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2525 ArrayRef<Value *> UserIgnoreLst) { 2526 ExtraValueToDebugLocsMap ExternallyUsedValues; 2527 buildTree(Roots, ExternallyUsedValues, UserIgnoreLst); 2528 } 2529 2530 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2531 ExtraValueToDebugLocsMap &ExternallyUsedValues, 2532 ArrayRef<Value *> UserIgnoreLst) { 2533 deleteTree(); 2534 UserIgnoreList = UserIgnoreLst; 2535 if (!allSameType(Roots)) 2536 return; 2537 buildTree_rec(Roots, 0, EdgeInfo()); 2538 2539 // Collect the values that we need to extract from the tree. 2540 for (auto &TEPtr : VectorizableTree) { 2541 TreeEntry *Entry = TEPtr.get(); 2542 2543 // No need to handle users of gathered values. 2544 if (Entry->State == TreeEntry::NeedToGather) 2545 continue; 2546 2547 // For each lane: 2548 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 2549 Value *Scalar = Entry->Scalars[Lane]; 2550 int FoundLane = Lane; 2551 if (!Entry->ReuseShuffleIndices.empty()) { 2552 FoundLane = 2553 std::distance(Entry->ReuseShuffleIndices.begin(), 2554 llvm::find(Entry->ReuseShuffleIndices, FoundLane)); 2555 } 2556 2557 // Check if the scalar is externally used as an extra arg. 2558 auto ExtI = ExternallyUsedValues.find(Scalar); 2559 if (ExtI != ExternallyUsedValues.end()) { 2560 LLVM_DEBUG(dbgs() << "SLP: Need to extract: Extra arg from lane " 2561 << Lane << " from " << *Scalar << ".\n"); 2562 ExternalUses.emplace_back(Scalar, nullptr, FoundLane); 2563 } 2564 for (User *U : Scalar->users()) { 2565 LLVM_DEBUG(dbgs() << "SLP: Checking user:" << *U << ".\n"); 2566 2567 Instruction *UserInst = dyn_cast<Instruction>(U); 2568 if (!UserInst) 2569 continue; 2570 2571 // Skip in-tree scalars that become vectors 2572 if (TreeEntry *UseEntry = getTreeEntry(U)) { 2573 Value *UseScalar = UseEntry->Scalars[0]; 2574 // Some in-tree scalars will remain as scalar in vectorized 2575 // instructions. If that is the case, the one in Lane 0 will 2576 // be used. 2577 if (UseScalar != U || 2578 UseEntry->State == TreeEntry::ScatterVectorize || 2579 !InTreeUserNeedToExtract(Scalar, UserInst, TLI)) { 2580 LLVM_DEBUG(dbgs() << "SLP: \tInternal user will be removed:" << *U 2581 << ".\n"); 2582 assert(UseEntry->State != TreeEntry::NeedToGather && "Bad state"); 2583 continue; 2584 } 2585 } 2586 2587 // Ignore users in the user ignore list. 2588 if (is_contained(UserIgnoreList, UserInst)) 2589 continue; 2590 2591 LLVM_DEBUG(dbgs() << "SLP: Need to extract:" << *U << " from lane " 2592 << Lane << " from " << *Scalar << ".\n"); 2593 ExternalUses.push_back(ExternalUser(Scalar, U, FoundLane)); 2594 } 2595 } 2596 } 2597 } 2598 2599 void BoUpSLP::buildTree_rec(ArrayRef<Value *> VL, unsigned Depth, 2600 const EdgeInfo &UserTreeIdx) { 2601 assert((allConstant(VL) || allSameType(VL)) && "Invalid types!"); 2602 2603 InstructionsState S = getSameOpcode(VL); 2604 if (Depth == RecursionMaxDepth) { 2605 LLVM_DEBUG(dbgs() << "SLP: Gathering due to max recursion depth.\n"); 2606 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2607 return; 2608 } 2609 2610 // Don't handle vectors. 2611 if (S.OpValue->getType()->isVectorTy()) { 2612 LLVM_DEBUG(dbgs() << "SLP: Gathering due to vector type.\n"); 2613 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2614 return; 2615 } 2616 2617 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) 2618 if (SI->getValueOperand()->getType()->isVectorTy()) { 2619 LLVM_DEBUG(dbgs() << "SLP: Gathering due to store vector type.\n"); 2620 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2621 return; 2622 } 2623 2624 // If all of the operands are identical or constant we have a simple solution. 2625 if (allConstant(VL) || isSplat(VL) || !allSameBlock(VL) || !S.getOpcode()) { 2626 LLVM_DEBUG(dbgs() << "SLP: Gathering due to C,S,B,O. \n"); 2627 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2628 return; 2629 } 2630 2631 // We now know that this is a vector of instructions of the same type from 2632 // the same block. 2633 2634 // Don't vectorize ephemeral values. 2635 for (Value *V : VL) { 2636 if (EphValues.count(V)) { 2637 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2638 << ") is ephemeral.\n"); 2639 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2640 return; 2641 } 2642 } 2643 2644 // Check if this is a duplicate of another entry. 2645 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 2646 LLVM_DEBUG(dbgs() << "SLP: \tChecking bundle: " << *S.OpValue << ".\n"); 2647 if (!E->isSame(VL)) { 2648 LLVM_DEBUG(dbgs() << "SLP: Gathering due to partial overlap.\n"); 2649 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2650 return; 2651 } 2652 // Record the reuse of the tree node. FIXME, currently this is only used to 2653 // properly draw the graph rather than for the actual vectorization. 2654 E->UserTreeIndices.push_back(UserTreeIdx); 2655 LLVM_DEBUG(dbgs() << "SLP: Perfect diamond merge at " << *S.OpValue 2656 << ".\n"); 2657 return; 2658 } 2659 2660 // Check that none of the instructions in the bundle are already in the tree. 2661 for (Value *V : VL) { 2662 auto *I = dyn_cast<Instruction>(V); 2663 if (!I) 2664 continue; 2665 if (getTreeEntry(I)) { 2666 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2667 << ") is already in tree.\n"); 2668 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2669 return; 2670 } 2671 } 2672 2673 // If any of the scalars is marked as a value that needs to stay scalar, then 2674 // we need to gather the scalars. 2675 // The reduction nodes (stored in UserIgnoreList) also should stay scalar. 2676 for (Value *V : VL) { 2677 if (MustGather.count(V) || is_contained(UserIgnoreList, V)) { 2678 LLVM_DEBUG(dbgs() << "SLP: Gathering due to gathered scalar.\n"); 2679 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2680 return; 2681 } 2682 } 2683 2684 // Check that all of the users of the scalars that we want to vectorize are 2685 // schedulable. 2686 auto *VL0 = cast<Instruction>(S.OpValue); 2687 BasicBlock *BB = VL0->getParent(); 2688 2689 if (!DT->isReachableFromEntry(BB)) { 2690 // Don't go into unreachable blocks. They may contain instructions with 2691 // dependency cycles which confuse the final scheduling. 2692 LLVM_DEBUG(dbgs() << "SLP: bundle in unreachable block.\n"); 2693 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2694 return; 2695 } 2696 2697 // Check that every instruction appears once in this bundle. 2698 SmallVector<unsigned, 4> ReuseShuffleIndicies; 2699 SmallVector<Value *, 4> UniqueValues; 2700 DenseMap<Value *, unsigned> UniquePositions; 2701 for (Value *V : VL) { 2702 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 2703 ReuseShuffleIndicies.emplace_back(Res.first->second); 2704 if (Res.second) 2705 UniqueValues.emplace_back(V); 2706 } 2707 size_t NumUniqueScalarValues = UniqueValues.size(); 2708 if (NumUniqueScalarValues == VL.size()) { 2709 ReuseShuffleIndicies.clear(); 2710 } else { 2711 LLVM_DEBUG(dbgs() << "SLP: Shuffle for reused scalars.\n"); 2712 if (NumUniqueScalarValues <= 1 || 2713 !llvm::isPowerOf2_32(NumUniqueScalarValues)) { 2714 LLVM_DEBUG(dbgs() << "SLP: Scalar used twice in bundle.\n"); 2715 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2716 return; 2717 } 2718 VL = UniqueValues; 2719 } 2720 2721 auto &BSRef = BlocksSchedules[BB]; 2722 if (!BSRef) 2723 BSRef = std::make_unique<BlockScheduling>(BB); 2724 2725 BlockScheduling &BS = *BSRef.get(); 2726 2727 Optional<ScheduleData *> Bundle = BS.tryScheduleBundle(VL, this, S); 2728 if (!Bundle) { 2729 LLVM_DEBUG(dbgs() << "SLP: We are not able to schedule this bundle!\n"); 2730 assert((!BS.getScheduleData(VL0) || 2731 !BS.getScheduleData(VL0)->isPartOfBundle()) && 2732 "tryScheduleBundle should cancelScheduling on failure"); 2733 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2734 ReuseShuffleIndicies); 2735 return; 2736 } 2737 LLVM_DEBUG(dbgs() << "SLP: We are able to schedule this bundle.\n"); 2738 2739 unsigned ShuffleOrOp = S.isAltShuffle() ? 2740 (unsigned) Instruction::ShuffleVector : S.getOpcode(); 2741 switch (ShuffleOrOp) { 2742 case Instruction::PHI: { 2743 auto *PH = cast<PHINode>(VL0); 2744 2745 // Check for terminator values (e.g. invoke). 2746 for (Value *V : VL) 2747 for (unsigned I = 0, E = PH->getNumIncomingValues(); I < E; ++I) { 2748 Instruction *Term = dyn_cast<Instruction>( 2749 cast<PHINode>(V)->getIncomingValueForBlock( 2750 PH->getIncomingBlock(I))); 2751 if (Term && Term->isTerminator()) { 2752 LLVM_DEBUG(dbgs() 2753 << "SLP: Need to swizzle PHINodes (terminator use).\n"); 2754 BS.cancelScheduling(VL, VL0); 2755 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2756 ReuseShuffleIndicies); 2757 return; 2758 } 2759 } 2760 2761 TreeEntry *TE = 2762 newTreeEntry(VL, Bundle, S, UserTreeIdx, ReuseShuffleIndicies); 2763 LLVM_DEBUG(dbgs() << "SLP: added a vector of PHINodes.\n"); 2764 2765 // Keeps the reordered operands to avoid code duplication. 2766 SmallVector<ValueList, 2> OperandsVec; 2767 for (unsigned I = 0, E = PH->getNumIncomingValues(); I < E; ++I) { 2768 ValueList Operands; 2769 // Prepare the operand vector. 2770 for (Value *V : VL) 2771 Operands.push_back(cast<PHINode>(V)->getIncomingValueForBlock( 2772 PH->getIncomingBlock(I))); 2773 TE->setOperand(I, Operands); 2774 OperandsVec.push_back(Operands); 2775 } 2776 for (unsigned OpIdx = 0, OpE = OperandsVec.size(); OpIdx != OpE; ++OpIdx) 2777 buildTree_rec(OperandsVec[OpIdx], Depth + 1, {TE, OpIdx}); 2778 return; 2779 } 2780 case Instruction::ExtractValue: 2781 case Instruction::ExtractElement: { 2782 OrdersType CurrentOrder; 2783 bool Reuse = canReuseExtract(VL, VL0, CurrentOrder); 2784 if (Reuse) { 2785 LLVM_DEBUG(dbgs() << "SLP: Reusing or shuffling extract sequence.\n"); 2786 ++NumOpsWantToKeepOriginalOrder; 2787 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2788 ReuseShuffleIndicies); 2789 // This is a special case, as it does not gather, but at the same time 2790 // we are not extending buildTree_rec() towards the operands. 2791 ValueList Op0; 2792 Op0.assign(VL.size(), VL0->getOperand(0)); 2793 VectorizableTree.back()->setOperand(0, Op0); 2794 return; 2795 } 2796 if (!CurrentOrder.empty()) { 2797 LLVM_DEBUG({ 2798 dbgs() << "SLP: Reusing or shuffling of reordered extract sequence " 2799 "with order"; 2800 for (unsigned Idx : CurrentOrder) 2801 dbgs() << " " << Idx; 2802 dbgs() << "\n"; 2803 }); 2804 // Insert new order with initial value 0, if it does not exist, 2805 // otherwise return the iterator to the existing one. 2806 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2807 ReuseShuffleIndicies, CurrentOrder); 2808 findRootOrder(CurrentOrder); 2809 ++NumOpsWantToKeepOrder[CurrentOrder]; 2810 // This is a special case, as it does not gather, but at the same time 2811 // we are not extending buildTree_rec() towards the operands. 2812 ValueList Op0; 2813 Op0.assign(VL.size(), VL0->getOperand(0)); 2814 VectorizableTree.back()->setOperand(0, Op0); 2815 return; 2816 } 2817 LLVM_DEBUG(dbgs() << "SLP: Gather extract sequence.\n"); 2818 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2819 ReuseShuffleIndicies); 2820 BS.cancelScheduling(VL, VL0); 2821 return; 2822 } 2823 case Instruction::Load: { 2824 // Check that a vectorized load would load the same memory as a scalar 2825 // load. For example, we don't want to vectorize loads that are smaller 2826 // than 8-bit. Even though we have a packed struct {<i2, i2, i2, i2>} LLVM 2827 // treats loading/storing it as an i8 struct. If we vectorize loads/stores 2828 // from such a struct, we read/write packed bits disagreeing with the 2829 // unvectorized version. 2830 Type *ScalarTy = VL0->getType(); 2831 2832 if (DL->getTypeSizeInBits(ScalarTy) != 2833 DL->getTypeAllocSizeInBits(ScalarTy)) { 2834 BS.cancelScheduling(VL, VL0); 2835 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2836 ReuseShuffleIndicies); 2837 LLVM_DEBUG(dbgs() << "SLP: Gathering loads of non-packed type.\n"); 2838 return; 2839 } 2840 2841 // Make sure all loads in the bundle are simple - we can't vectorize 2842 // atomic or volatile loads. 2843 SmallVector<Value *, 4> PointerOps(VL.size()); 2844 auto POIter = PointerOps.begin(); 2845 for (Value *V : VL) { 2846 auto *L = cast<LoadInst>(V); 2847 if (!L->isSimple()) { 2848 BS.cancelScheduling(VL, VL0); 2849 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2850 ReuseShuffleIndicies); 2851 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple loads.\n"); 2852 return; 2853 } 2854 *POIter = L->getPointerOperand(); 2855 ++POIter; 2856 } 2857 2858 OrdersType CurrentOrder; 2859 // Check the order of pointer operands. 2860 if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) { 2861 Value *Ptr0; 2862 Value *PtrN; 2863 if (CurrentOrder.empty()) { 2864 Ptr0 = PointerOps.front(); 2865 PtrN = PointerOps.back(); 2866 } else { 2867 Ptr0 = PointerOps[CurrentOrder.front()]; 2868 PtrN = PointerOps[CurrentOrder.back()]; 2869 } 2870 const SCEV *Scev0 = SE->getSCEV(Ptr0); 2871 const SCEV *ScevN = SE->getSCEV(PtrN); 2872 const auto *Diff = 2873 dyn_cast<SCEVConstant>(SE->getMinusSCEV(ScevN, Scev0)); 2874 uint64_t Size = DL->getTypeAllocSize(ScalarTy); 2875 // Check that the sorted loads are consecutive. 2876 if (Diff && Diff->getAPInt() == (VL.size() - 1) * Size) { 2877 if (CurrentOrder.empty()) { 2878 // Original loads are consecutive and does not require reordering. 2879 ++NumOpsWantToKeepOriginalOrder; 2880 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, 2881 UserTreeIdx, ReuseShuffleIndicies); 2882 TE->setOperandsInOrder(); 2883 LLVM_DEBUG(dbgs() << "SLP: added a vector of loads.\n"); 2884 } else { 2885 // Need to reorder. 2886 TreeEntry *TE = 2887 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2888 ReuseShuffleIndicies, CurrentOrder); 2889 TE->setOperandsInOrder(); 2890 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled loads.\n"); 2891 findRootOrder(CurrentOrder); 2892 ++NumOpsWantToKeepOrder[CurrentOrder]; 2893 } 2894 return; 2895 } 2896 // Vectorizing non-consecutive loads with `llvm.masked.gather`. 2897 TreeEntry *TE = newTreeEntry(VL, TreeEntry::ScatterVectorize, Bundle, S, 2898 UserTreeIdx, ReuseShuffleIndicies); 2899 TE->setOperandsInOrder(); 2900 buildTree_rec(PointerOps, Depth + 1, {TE, 0}); 2901 LLVM_DEBUG(dbgs() << "SLP: added a vector of non-consecutive loads.\n"); 2902 return; 2903 } 2904 2905 LLVM_DEBUG(dbgs() << "SLP: Gathering non-consecutive loads.\n"); 2906 BS.cancelScheduling(VL, VL0); 2907 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2908 ReuseShuffleIndicies); 2909 return; 2910 } 2911 case Instruction::ZExt: 2912 case Instruction::SExt: 2913 case Instruction::FPToUI: 2914 case Instruction::FPToSI: 2915 case Instruction::FPExt: 2916 case Instruction::PtrToInt: 2917 case Instruction::IntToPtr: 2918 case Instruction::SIToFP: 2919 case Instruction::UIToFP: 2920 case Instruction::Trunc: 2921 case Instruction::FPTrunc: 2922 case Instruction::BitCast: { 2923 Type *SrcTy = VL0->getOperand(0)->getType(); 2924 for (Value *V : VL) { 2925 Type *Ty = cast<Instruction>(V)->getOperand(0)->getType(); 2926 if (Ty != SrcTy || !isValidElementType(Ty)) { 2927 BS.cancelScheduling(VL, VL0); 2928 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2929 ReuseShuffleIndicies); 2930 LLVM_DEBUG(dbgs() 2931 << "SLP: Gathering casts with different src types.\n"); 2932 return; 2933 } 2934 } 2935 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2936 ReuseShuffleIndicies); 2937 LLVM_DEBUG(dbgs() << "SLP: added a vector of casts.\n"); 2938 2939 TE->setOperandsInOrder(); 2940 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 2941 ValueList Operands; 2942 // Prepare the operand vector. 2943 for (Value *V : VL) 2944 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 2945 2946 buildTree_rec(Operands, Depth + 1, {TE, i}); 2947 } 2948 return; 2949 } 2950 case Instruction::ICmp: 2951 case Instruction::FCmp: { 2952 // Check that all of the compares have the same predicate. 2953 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 2954 CmpInst::Predicate SwapP0 = CmpInst::getSwappedPredicate(P0); 2955 Type *ComparedTy = VL0->getOperand(0)->getType(); 2956 for (Value *V : VL) { 2957 CmpInst *Cmp = cast<CmpInst>(V); 2958 if ((Cmp->getPredicate() != P0 && Cmp->getPredicate() != SwapP0) || 2959 Cmp->getOperand(0)->getType() != ComparedTy) { 2960 BS.cancelScheduling(VL, VL0); 2961 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2962 ReuseShuffleIndicies); 2963 LLVM_DEBUG(dbgs() 2964 << "SLP: Gathering cmp with different predicate.\n"); 2965 return; 2966 } 2967 } 2968 2969 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2970 ReuseShuffleIndicies); 2971 LLVM_DEBUG(dbgs() << "SLP: added a vector of compares.\n"); 2972 2973 ValueList Left, Right; 2974 if (cast<CmpInst>(VL0)->isCommutative()) { 2975 // Commutative predicate - collect + sort operands of the instructions 2976 // so that each side is more likely to have the same opcode. 2977 assert(P0 == SwapP0 && "Commutative Predicate mismatch"); 2978 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 2979 } else { 2980 // Collect operands - commute if it uses the swapped predicate. 2981 for (Value *V : VL) { 2982 auto *Cmp = cast<CmpInst>(V); 2983 Value *LHS = Cmp->getOperand(0); 2984 Value *RHS = Cmp->getOperand(1); 2985 if (Cmp->getPredicate() != P0) 2986 std::swap(LHS, RHS); 2987 Left.push_back(LHS); 2988 Right.push_back(RHS); 2989 } 2990 } 2991 TE->setOperand(0, Left); 2992 TE->setOperand(1, Right); 2993 buildTree_rec(Left, Depth + 1, {TE, 0}); 2994 buildTree_rec(Right, Depth + 1, {TE, 1}); 2995 return; 2996 } 2997 case Instruction::Select: 2998 case Instruction::FNeg: 2999 case Instruction::Add: 3000 case Instruction::FAdd: 3001 case Instruction::Sub: 3002 case Instruction::FSub: 3003 case Instruction::Mul: 3004 case Instruction::FMul: 3005 case Instruction::UDiv: 3006 case Instruction::SDiv: 3007 case Instruction::FDiv: 3008 case Instruction::URem: 3009 case Instruction::SRem: 3010 case Instruction::FRem: 3011 case Instruction::Shl: 3012 case Instruction::LShr: 3013 case Instruction::AShr: 3014 case Instruction::And: 3015 case Instruction::Or: 3016 case Instruction::Xor: { 3017 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3018 ReuseShuffleIndicies); 3019 LLVM_DEBUG(dbgs() << "SLP: added a vector of un/bin op.\n"); 3020 3021 // Sort operands of the instructions so that each side is more likely to 3022 // have the same opcode. 3023 if (isa<BinaryOperator>(VL0) && VL0->isCommutative()) { 3024 ValueList Left, Right; 3025 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 3026 TE->setOperand(0, Left); 3027 TE->setOperand(1, Right); 3028 buildTree_rec(Left, Depth + 1, {TE, 0}); 3029 buildTree_rec(Right, Depth + 1, {TE, 1}); 3030 return; 3031 } 3032 3033 TE->setOperandsInOrder(); 3034 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 3035 ValueList Operands; 3036 // Prepare the operand vector. 3037 for (Value *V : VL) 3038 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3039 3040 buildTree_rec(Operands, Depth + 1, {TE, i}); 3041 } 3042 return; 3043 } 3044 case Instruction::GetElementPtr: { 3045 // We don't combine GEPs with complicated (nested) indexing. 3046 for (Value *V : VL) { 3047 if (cast<Instruction>(V)->getNumOperands() != 2) { 3048 LLVM_DEBUG(dbgs() << "SLP: not-vectorizable GEP (nested indexes).\n"); 3049 BS.cancelScheduling(VL, VL0); 3050 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3051 ReuseShuffleIndicies); 3052 return; 3053 } 3054 } 3055 3056 // We can't combine several GEPs into one vector if they operate on 3057 // different types. 3058 Type *Ty0 = VL0->getOperand(0)->getType(); 3059 for (Value *V : VL) { 3060 Type *CurTy = cast<Instruction>(V)->getOperand(0)->getType(); 3061 if (Ty0 != CurTy) { 3062 LLVM_DEBUG(dbgs() 3063 << "SLP: not-vectorizable GEP (different types).\n"); 3064 BS.cancelScheduling(VL, VL0); 3065 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3066 ReuseShuffleIndicies); 3067 return; 3068 } 3069 } 3070 3071 // We don't combine GEPs with non-constant indexes. 3072 Type *Ty1 = VL0->getOperand(1)->getType(); 3073 for (Value *V : VL) { 3074 auto Op = cast<Instruction>(V)->getOperand(1); 3075 if (!isa<ConstantInt>(Op) || 3076 (Op->getType() != Ty1 && 3077 Op->getType()->getScalarSizeInBits() > 3078 DL->getIndexSizeInBits( 3079 V->getType()->getPointerAddressSpace()))) { 3080 LLVM_DEBUG(dbgs() 3081 << "SLP: not-vectorizable GEP (non-constant indexes).\n"); 3082 BS.cancelScheduling(VL, VL0); 3083 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3084 ReuseShuffleIndicies); 3085 return; 3086 } 3087 } 3088 3089 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3090 ReuseShuffleIndicies); 3091 LLVM_DEBUG(dbgs() << "SLP: added a vector of GEPs.\n"); 3092 TE->setOperandsInOrder(); 3093 for (unsigned i = 0, e = 2; i < e; ++i) { 3094 ValueList Operands; 3095 // Prepare the operand vector. 3096 for (Value *V : VL) 3097 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3098 3099 buildTree_rec(Operands, Depth + 1, {TE, i}); 3100 } 3101 return; 3102 } 3103 case Instruction::Store: { 3104 // Check if the stores are consecutive or if we need to swizzle them. 3105 llvm::Type *ScalarTy = cast<StoreInst>(VL0)->getValueOperand()->getType(); 3106 // Avoid types that are padded when being allocated as scalars, while 3107 // being packed together in a vector (such as i1). 3108 if (DL->getTypeSizeInBits(ScalarTy) != 3109 DL->getTypeAllocSizeInBits(ScalarTy)) { 3110 BS.cancelScheduling(VL, VL0); 3111 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3112 ReuseShuffleIndicies); 3113 LLVM_DEBUG(dbgs() << "SLP: Gathering stores of non-packed type.\n"); 3114 return; 3115 } 3116 // Make sure all stores in the bundle are simple - we can't vectorize 3117 // atomic or volatile stores. 3118 SmallVector<Value *, 4> PointerOps(VL.size()); 3119 ValueList Operands(VL.size()); 3120 auto POIter = PointerOps.begin(); 3121 auto OIter = Operands.begin(); 3122 for (Value *V : VL) { 3123 auto *SI = cast<StoreInst>(V); 3124 if (!SI->isSimple()) { 3125 BS.cancelScheduling(VL, VL0); 3126 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3127 ReuseShuffleIndicies); 3128 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple stores.\n"); 3129 return; 3130 } 3131 *POIter = SI->getPointerOperand(); 3132 *OIter = SI->getValueOperand(); 3133 ++POIter; 3134 ++OIter; 3135 } 3136 3137 OrdersType CurrentOrder; 3138 // Check the order of pointer operands. 3139 if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) { 3140 Value *Ptr0; 3141 Value *PtrN; 3142 if (CurrentOrder.empty()) { 3143 Ptr0 = PointerOps.front(); 3144 PtrN = PointerOps.back(); 3145 } else { 3146 Ptr0 = PointerOps[CurrentOrder.front()]; 3147 PtrN = PointerOps[CurrentOrder.back()]; 3148 } 3149 const SCEV *Scev0 = SE->getSCEV(Ptr0); 3150 const SCEV *ScevN = SE->getSCEV(PtrN); 3151 const auto *Diff = 3152 dyn_cast<SCEVConstant>(SE->getMinusSCEV(ScevN, Scev0)); 3153 uint64_t Size = DL->getTypeAllocSize(ScalarTy); 3154 // Check that the sorted pointer operands are consecutive. 3155 if (Diff && Diff->getAPInt() == (VL.size() - 1) * Size) { 3156 if (CurrentOrder.empty()) { 3157 // Original stores are consecutive and does not require reordering. 3158 ++NumOpsWantToKeepOriginalOrder; 3159 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, 3160 UserTreeIdx, ReuseShuffleIndicies); 3161 TE->setOperandsInOrder(); 3162 buildTree_rec(Operands, Depth + 1, {TE, 0}); 3163 LLVM_DEBUG(dbgs() << "SLP: added a vector of stores.\n"); 3164 } else { 3165 TreeEntry *TE = 3166 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3167 ReuseShuffleIndicies, CurrentOrder); 3168 TE->setOperandsInOrder(); 3169 buildTree_rec(Operands, Depth + 1, {TE, 0}); 3170 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled stores.\n"); 3171 findRootOrder(CurrentOrder); 3172 ++NumOpsWantToKeepOrder[CurrentOrder]; 3173 } 3174 return; 3175 } 3176 } 3177 3178 BS.cancelScheduling(VL, VL0); 3179 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3180 ReuseShuffleIndicies); 3181 LLVM_DEBUG(dbgs() << "SLP: Non-consecutive store.\n"); 3182 return; 3183 } 3184 case Instruction::Call: { 3185 // Check if the calls are all to the same vectorizable intrinsic or 3186 // library function. 3187 CallInst *CI = cast<CallInst>(VL0); 3188 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3189 3190 VFShape Shape = VFShape::get( 3191 *CI, ElementCount::getFixed(static_cast<unsigned int>(VL.size())), 3192 false /*HasGlobalPred*/); 3193 Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape); 3194 3195 if (!VecFunc && !isTriviallyVectorizable(ID)) { 3196 BS.cancelScheduling(VL, VL0); 3197 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3198 ReuseShuffleIndicies); 3199 LLVM_DEBUG(dbgs() << "SLP: Non-vectorizable call.\n"); 3200 return; 3201 } 3202 Function *F = CI->getCalledFunction(); 3203 unsigned NumArgs = CI->getNumArgOperands(); 3204 SmallVector<Value*, 4> ScalarArgs(NumArgs, nullptr); 3205 for (unsigned j = 0; j != NumArgs; ++j) 3206 if (hasVectorInstrinsicScalarOpd(ID, j)) 3207 ScalarArgs[j] = CI->getArgOperand(j); 3208 for (Value *V : VL) { 3209 CallInst *CI2 = dyn_cast<CallInst>(V); 3210 if (!CI2 || CI2->getCalledFunction() != F || 3211 getVectorIntrinsicIDForCall(CI2, TLI) != ID || 3212 (VecFunc && 3213 VecFunc != VFDatabase(*CI2).getVectorizedFunction(Shape)) || 3214 !CI->hasIdenticalOperandBundleSchema(*CI2)) { 3215 BS.cancelScheduling(VL, VL0); 3216 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3217 ReuseShuffleIndicies); 3218 LLVM_DEBUG(dbgs() << "SLP: mismatched calls:" << *CI << "!=" << *V 3219 << "\n"); 3220 return; 3221 } 3222 // Some intrinsics have scalar arguments and should be same in order for 3223 // them to be vectorized. 3224 for (unsigned j = 0; j != NumArgs; ++j) { 3225 if (hasVectorInstrinsicScalarOpd(ID, j)) { 3226 Value *A1J = CI2->getArgOperand(j); 3227 if (ScalarArgs[j] != A1J) { 3228 BS.cancelScheduling(VL, VL0); 3229 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3230 ReuseShuffleIndicies); 3231 LLVM_DEBUG(dbgs() << "SLP: mismatched arguments in call:" << *CI 3232 << " argument " << ScalarArgs[j] << "!=" << A1J 3233 << "\n"); 3234 return; 3235 } 3236 } 3237 } 3238 // Verify that the bundle operands are identical between the two calls. 3239 if (CI->hasOperandBundles() && 3240 !std::equal(CI->op_begin() + CI->getBundleOperandsStartIndex(), 3241 CI->op_begin() + CI->getBundleOperandsEndIndex(), 3242 CI2->op_begin() + CI2->getBundleOperandsStartIndex())) { 3243 BS.cancelScheduling(VL, VL0); 3244 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3245 ReuseShuffleIndicies); 3246 LLVM_DEBUG(dbgs() << "SLP: mismatched bundle operands in calls:" 3247 << *CI << "!=" << *V << '\n'); 3248 return; 3249 } 3250 } 3251 3252 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3253 ReuseShuffleIndicies); 3254 TE->setOperandsInOrder(); 3255 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 3256 ValueList Operands; 3257 // Prepare the operand vector. 3258 for (Value *V : VL) { 3259 auto *CI2 = cast<CallInst>(V); 3260 Operands.push_back(CI2->getArgOperand(i)); 3261 } 3262 buildTree_rec(Operands, Depth + 1, {TE, i}); 3263 } 3264 return; 3265 } 3266 case Instruction::ShuffleVector: { 3267 // If this is not an alternate sequence of opcode like add-sub 3268 // then do not vectorize this instruction. 3269 if (!S.isAltShuffle()) { 3270 BS.cancelScheduling(VL, VL0); 3271 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3272 ReuseShuffleIndicies); 3273 LLVM_DEBUG(dbgs() << "SLP: ShuffleVector are not vectorized.\n"); 3274 return; 3275 } 3276 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3277 ReuseShuffleIndicies); 3278 LLVM_DEBUG(dbgs() << "SLP: added a ShuffleVector op.\n"); 3279 3280 // Reorder operands if reordering would enable vectorization. 3281 if (isa<BinaryOperator>(VL0)) { 3282 ValueList Left, Right; 3283 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 3284 TE->setOperand(0, Left); 3285 TE->setOperand(1, Right); 3286 buildTree_rec(Left, Depth + 1, {TE, 0}); 3287 buildTree_rec(Right, Depth + 1, {TE, 1}); 3288 return; 3289 } 3290 3291 TE->setOperandsInOrder(); 3292 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 3293 ValueList Operands; 3294 // Prepare the operand vector. 3295 for (Value *V : VL) 3296 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3297 3298 buildTree_rec(Operands, Depth + 1, {TE, i}); 3299 } 3300 return; 3301 } 3302 default: 3303 BS.cancelScheduling(VL, VL0); 3304 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3305 ReuseShuffleIndicies); 3306 LLVM_DEBUG(dbgs() << "SLP: Gathering unknown instruction.\n"); 3307 return; 3308 } 3309 } 3310 3311 unsigned BoUpSLP::canMapToVector(Type *T, const DataLayout &DL) const { 3312 unsigned N = 1; 3313 Type *EltTy = T; 3314 3315 while (isa<StructType>(EltTy) || isa<ArrayType>(EltTy) || 3316 isa<VectorType>(EltTy)) { 3317 if (auto *ST = dyn_cast<StructType>(EltTy)) { 3318 // Check that struct is homogeneous. 3319 for (const auto *Ty : ST->elements()) 3320 if (Ty != *ST->element_begin()) 3321 return 0; 3322 N *= ST->getNumElements(); 3323 EltTy = *ST->element_begin(); 3324 } else if (auto *AT = dyn_cast<ArrayType>(EltTy)) { 3325 N *= AT->getNumElements(); 3326 EltTy = AT->getElementType(); 3327 } else { 3328 auto *VT = cast<FixedVectorType>(EltTy); 3329 N *= VT->getNumElements(); 3330 EltTy = VT->getElementType(); 3331 } 3332 } 3333 3334 if (!isValidElementType(EltTy)) 3335 return 0; 3336 uint64_t VTSize = DL.getTypeStoreSizeInBits(FixedVectorType::get(EltTy, N)); 3337 if (VTSize < MinVecRegSize || VTSize > MaxVecRegSize || VTSize != DL.getTypeStoreSizeInBits(T)) 3338 return 0; 3339 return N; 3340 } 3341 3342 bool BoUpSLP::canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 3343 SmallVectorImpl<unsigned> &CurrentOrder) const { 3344 Instruction *E0 = cast<Instruction>(OpValue); 3345 assert(E0->getOpcode() == Instruction::ExtractElement || 3346 E0->getOpcode() == Instruction::ExtractValue); 3347 assert(E0->getOpcode() == getSameOpcode(VL).getOpcode() && "Invalid opcode"); 3348 // Check if all of the extracts come from the same vector and from the 3349 // correct offset. 3350 Value *Vec = E0->getOperand(0); 3351 3352 CurrentOrder.clear(); 3353 3354 // We have to extract from a vector/aggregate with the same number of elements. 3355 unsigned NElts; 3356 if (E0->getOpcode() == Instruction::ExtractValue) { 3357 const DataLayout &DL = E0->getModule()->getDataLayout(); 3358 NElts = canMapToVector(Vec->getType(), DL); 3359 if (!NElts) 3360 return false; 3361 // Check if load can be rewritten as load of vector. 3362 LoadInst *LI = dyn_cast<LoadInst>(Vec); 3363 if (!LI || !LI->isSimple() || !LI->hasNUses(VL.size())) 3364 return false; 3365 } else { 3366 NElts = cast<FixedVectorType>(Vec->getType())->getNumElements(); 3367 } 3368 3369 if (NElts != VL.size()) 3370 return false; 3371 3372 // Check that all of the indices extract from the correct offset. 3373 bool ShouldKeepOrder = true; 3374 unsigned E = VL.size(); 3375 // Assign to all items the initial value E + 1 so we can check if the extract 3376 // instruction index was used already. 3377 // Also, later we can check that all the indices are used and we have a 3378 // consecutive access in the extract instructions, by checking that no 3379 // element of CurrentOrder still has value E + 1. 3380 CurrentOrder.assign(E, E + 1); 3381 unsigned I = 0; 3382 for (; I < E; ++I) { 3383 auto *Inst = cast<Instruction>(VL[I]); 3384 if (Inst->getOperand(0) != Vec) 3385 break; 3386 Optional<unsigned> Idx = getExtractIndex(Inst); 3387 if (!Idx) 3388 break; 3389 const unsigned ExtIdx = *Idx; 3390 if (ExtIdx != I) { 3391 if (ExtIdx >= E || CurrentOrder[ExtIdx] != E + 1) 3392 break; 3393 ShouldKeepOrder = false; 3394 CurrentOrder[ExtIdx] = I; 3395 } else { 3396 if (CurrentOrder[I] != E + 1) 3397 break; 3398 CurrentOrder[I] = I; 3399 } 3400 } 3401 if (I < E) { 3402 CurrentOrder.clear(); 3403 return false; 3404 } 3405 3406 return ShouldKeepOrder; 3407 } 3408 3409 bool BoUpSLP::areAllUsersVectorized(Instruction *I) const { 3410 return I->hasOneUse() || llvm::all_of(I->users(), [this](User *U) { 3411 return ScalarToTreeEntry.count(U) > 0; 3412 }); 3413 } 3414 3415 static std::pair<InstructionCost, InstructionCost> 3416 getVectorCallCosts(CallInst *CI, FixedVectorType *VecTy, 3417 TargetTransformInfo *TTI, TargetLibraryInfo *TLI) { 3418 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3419 3420 // Calculate the cost of the scalar and vector calls. 3421 SmallVector<Type *, 4> VecTys; 3422 for (Use &Arg : CI->args()) 3423 VecTys.push_back( 3424 FixedVectorType::get(Arg->getType(), VecTy->getNumElements())); 3425 FastMathFlags FMF; 3426 if (auto *FPCI = dyn_cast<FPMathOperator>(CI)) 3427 FMF = FPCI->getFastMathFlags(); 3428 SmallVector<const Value *> Arguments(CI->arg_begin(), CI->arg_end()); 3429 IntrinsicCostAttributes CostAttrs(ID, VecTy, Arguments, VecTys, FMF, 3430 dyn_cast<IntrinsicInst>(CI)); 3431 auto IntrinsicCost = 3432 TTI->getIntrinsicInstrCost(CostAttrs, TTI::TCK_RecipThroughput); 3433 3434 auto Shape = VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>( 3435 VecTy->getNumElements())), 3436 false /*HasGlobalPred*/); 3437 Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape); 3438 auto LibCost = IntrinsicCost; 3439 if (!CI->isNoBuiltin() && VecFunc) { 3440 // Calculate the cost of the vector library call. 3441 // If the corresponding vector call is cheaper, return its cost. 3442 LibCost = TTI->getCallInstrCost(nullptr, VecTy, VecTys, 3443 TTI::TCK_RecipThroughput); 3444 } 3445 return {IntrinsicCost, LibCost}; 3446 } 3447 3448 InstructionCost BoUpSLP::getEntryCost(TreeEntry *E) { 3449 ArrayRef<Value*> VL = E->Scalars; 3450 3451 Type *ScalarTy = VL[0]->getType(); 3452 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 3453 ScalarTy = SI->getValueOperand()->getType(); 3454 else if (CmpInst *CI = dyn_cast<CmpInst>(VL[0])) 3455 ScalarTy = CI->getOperand(0)->getType(); 3456 auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); 3457 TTI::TargetCostKind CostKind = TTI::TCK_RecipThroughput; 3458 3459 // If we have computed a smaller type for the expression, update VecTy so 3460 // that the costs will be accurate. 3461 if (MinBWs.count(VL[0])) 3462 VecTy = FixedVectorType::get( 3463 IntegerType::get(F->getContext(), MinBWs[VL[0]].first), VL.size()); 3464 3465 unsigned ReuseShuffleNumbers = E->ReuseShuffleIndices.size(); 3466 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 3467 InstructionCost ReuseShuffleCost = 0; 3468 if (NeedToShuffleReuses) { 3469 ReuseShuffleCost = 3470 TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3471 } 3472 if (E->State == TreeEntry::NeedToGather) { 3473 if (allConstant(VL)) 3474 return 0; 3475 if (isSplat(VL)) { 3476 return ReuseShuffleCost + 3477 TTI->getShuffleCost(TargetTransformInfo::SK_Broadcast, VecTy, 0); 3478 } 3479 if (E->getOpcode() == Instruction::ExtractElement && 3480 allSameType(VL) && allSameBlock(VL)) { 3481 Optional<TargetTransformInfo::ShuffleKind> ShuffleKind = isShuffle(VL); 3482 if (ShuffleKind.hasValue()) { 3483 InstructionCost Cost = 3484 TTI->getShuffleCost(ShuffleKind.getValue(), VecTy); 3485 for (auto *V : VL) { 3486 // If all users of instruction are going to be vectorized and this 3487 // instruction itself is not going to be vectorized, consider this 3488 // instruction as dead and remove its cost from the final cost of the 3489 // vectorized tree. 3490 if (areAllUsersVectorized(cast<Instruction>(V)) && 3491 !ScalarToTreeEntry.count(V)) { 3492 auto *IO = cast<ConstantInt>( 3493 cast<ExtractElementInst>(V)->getIndexOperand()); 3494 Cost -= TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, 3495 IO->getZExtValue()); 3496 } 3497 } 3498 return ReuseShuffleCost + Cost; 3499 } 3500 } 3501 return ReuseShuffleCost + getGatherCost(VL); 3502 } 3503 assert((E->State == TreeEntry::Vectorize || 3504 E->State == TreeEntry::ScatterVectorize) && 3505 "Unhandled state"); 3506 assert(E->getOpcode() && allSameType(VL) && allSameBlock(VL) && "Invalid VL"); 3507 Instruction *VL0 = E->getMainOp(); 3508 unsigned ShuffleOrOp = 3509 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 3510 switch (ShuffleOrOp) { 3511 case Instruction::PHI: 3512 return 0; 3513 3514 case Instruction::ExtractValue: 3515 case Instruction::ExtractElement: { 3516 if (NeedToShuffleReuses) { 3517 unsigned Idx = 0; 3518 for (unsigned I : E->ReuseShuffleIndices) { 3519 if (ShuffleOrOp == Instruction::ExtractElement) { 3520 auto *IO = cast<ConstantInt>( 3521 cast<ExtractElementInst>(VL[I])->getIndexOperand()); 3522 Idx = IO->getZExtValue(); 3523 ReuseShuffleCost -= TTI->getVectorInstrCost( 3524 Instruction::ExtractElement, VecTy, Idx); 3525 } else { 3526 ReuseShuffleCost -= TTI->getVectorInstrCost( 3527 Instruction::ExtractElement, VecTy, Idx); 3528 ++Idx; 3529 } 3530 } 3531 Idx = ReuseShuffleNumbers; 3532 for (Value *V : VL) { 3533 if (ShuffleOrOp == Instruction::ExtractElement) { 3534 auto *IO = cast<ConstantInt>( 3535 cast<ExtractElementInst>(V)->getIndexOperand()); 3536 Idx = IO->getZExtValue(); 3537 } else { 3538 --Idx; 3539 } 3540 ReuseShuffleCost += 3541 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, Idx); 3542 } 3543 } 3544 InstructionCost DeadCost = ReuseShuffleCost; 3545 if (!E->ReorderIndices.empty()) { 3546 // TODO: Merge this shuffle with the ReuseShuffleCost. 3547 DeadCost += TTI->getShuffleCost( 3548 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3549 } 3550 for (unsigned I = 0, E = VL.size(); I < E; ++I) { 3551 Instruction *EI = cast<Instruction>(VL[I]); 3552 // If all users are going to be vectorized, instruction can be 3553 // considered as dead. 3554 // The same, if have only one user, it will be vectorized for sure. 3555 if (areAllUsersVectorized(EI)) { 3556 // Take credit for instruction that will become dead. 3557 if (EI->hasOneUse()) { 3558 Instruction *Ext = EI->user_back(); 3559 if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) && 3560 all_of(Ext->users(), 3561 [](User *U) { return isa<GetElementPtrInst>(U); })) { 3562 // Use getExtractWithExtendCost() to calculate the cost of 3563 // extractelement/ext pair. 3564 DeadCost -= TTI->getExtractWithExtendCost( 3565 Ext->getOpcode(), Ext->getType(), VecTy, I); 3566 // Add back the cost of s|zext which is subtracted separately. 3567 DeadCost += TTI->getCastInstrCost( 3568 Ext->getOpcode(), Ext->getType(), EI->getType(), 3569 TTI::getCastContextHint(Ext), CostKind, Ext); 3570 continue; 3571 } 3572 } 3573 DeadCost -= 3574 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, I); 3575 } 3576 } 3577 return DeadCost; 3578 } 3579 case Instruction::ZExt: 3580 case Instruction::SExt: 3581 case Instruction::FPToUI: 3582 case Instruction::FPToSI: 3583 case Instruction::FPExt: 3584 case Instruction::PtrToInt: 3585 case Instruction::IntToPtr: 3586 case Instruction::SIToFP: 3587 case Instruction::UIToFP: 3588 case Instruction::Trunc: 3589 case Instruction::FPTrunc: 3590 case Instruction::BitCast: { 3591 Type *SrcTy = VL0->getOperand(0)->getType(); 3592 InstructionCost ScalarEltCost = 3593 TTI->getCastInstrCost(E->getOpcode(), ScalarTy, SrcTy, 3594 TTI::getCastContextHint(VL0), CostKind, VL0); 3595 if (NeedToShuffleReuses) { 3596 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3597 } 3598 3599 // Calculate the cost of this instruction. 3600 InstructionCost ScalarCost = VL.size() * ScalarEltCost; 3601 3602 auto *SrcVecTy = FixedVectorType::get(SrcTy, VL.size()); 3603 InstructionCost VecCost = 0; 3604 // Check if the values are candidates to demote. 3605 if (!MinBWs.count(VL0) || VecTy != SrcVecTy) { 3606 VecCost = 3607 ReuseShuffleCost + 3608 TTI->getCastInstrCost(E->getOpcode(), VecTy, SrcVecTy, 3609 TTI::getCastContextHint(VL0), CostKind, VL0); 3610 } 3611 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3612 return VecCost - ScalarCost; 3613 } 3614 case Instruction::FCmp: 3615 case Instruction::ICmp: 3616 case Instruction::Select: { 3617 // Calculate the cost of this instruction. 3618 InstructionCost ScalarEltCost = 3619 TTI->getCmpSelInstrCost(E->getOpcode(), ScalarTy, Builder.getInt1Ty(), 3620 CmpInst::BAD_ICMP_PREDICATE, CostKind, VL0); 3621 if (NeedToShuffleReuses) { 3622 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3623 } 3624 auto *MaskTy = FixedVectorType::get(Builder.getInt1Ty(), VL.size()); 3625 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3626 3627 // Check if all entries in VL are either compares or selects with compares 3628 // as condition that have the same predicates. 3629 CmpInst::Predicate VecPred = CmpInst::BAD_ICMP_PREDICATE; 3630 bool First = true; 3631 for (auto *V : VL) { 3632 CmpInst::Predicate CurrentPred; 3633 auto MatchCmp = m_Cmp(CurrentPred, m_Value(), m_Value()); 3634 if ((!match(V, m_Select(MatchCmp, m_Value(), m_Value())) && 3635 !match(V, MatchCmp)) || 3636 (!First && VecPred != CurrentPred)) { 3637 VecPred = CmpInst::BAD_ICMP_PREDICATE; 3638 break; 3639 } 3640 First = false; 3641 VecPred = CurrentPred; 3642 } 3643 3644 InstructionCost VecCost = TTI->getCmpSelInstrCost( 3645 E->getOpcode(), VecTy, MaskTy, VecPred, CostKind, VL0); 3646 // Check if it is possible and profitable to use min/max for selects in 3647 // VL. 3648 // 3649 auto IntrinsicAndUse = canConvertToMinOrMaxIntrinsic(VL); 3650 if (IntrinsicAndUse.first != Intrinsic::not_intrinsic) { 3651 IntrinsicCostAttributes CostAttrs(IntrinsicAndUse.first, VecTy, 3652 {VecTy, VecTy}); 3653 InstructionCost IntrinsicCost = 3654 TTI->getIntrinsicInstrCost(CostAttrs, CostKind); 3655 // If the selects are the only uses of the compares, they will be dead 3656 // and we can adjust the cost by removing their cost. 3657 if (IntrinsicAndUse.second) 3658 IntrinsicCost -= 3659 TTI->getCmpSelInstrCost(Instruction::ICmp, VecTy, MaskTy, 3660 CmpInst::BAD_ICMP_PREDICATE, CostKind); 3661 VecCost = std::min(VecCost, IntrinsicCost); 3662 } 3663 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3664 return ReuseShuffleCost + VecCost - ScalarCost; 3665 } 3666 case Instruction::FNeg: 3667 case Instruction::Add: 3668 case Instruction::FAdd: 3669 case Instruction::Sub: 3670 case Instruction::FSub: 3671 case Instruction::Mul: 3672 case Instruction::FMul: 3673 case Instruction::UDiv: 3674 case Instruction::SDiv: 3675 case Instruction::FDiv: 3676 case Instruction::URem: 3677 case Instruction::SRem: 3678 case Instruction::FRem: 3679 case Instruction::Shl: 3680 case Instruction::LShr: 3681 case Instruction::AShr: 3682 case Instruction::And: 3683 case Instruction::Or: 3684 case Instruction::Xor: { 3685 // Certain instructions can be cheaper to vectorize if they have a 3686 // constant second vector operand. 3687 TargetTransformInfo::OperandValueKind Op1VK = 3688 TargetTransformInfo::OK_AnyValue; 3689 TargetTransformInfo::OperandValueKind Op2VK = 3690 TargetTransformInfo::OK_UniformConstantValue; 3691 TargetTransformInfo::OperandValueProperties Op1VP = 3692 TargetTransformInfo::OP_None; 3693 TargetTransformInfo::OperandValueProperties Op2VP = 3694 TargetTransformInfo::OP_PowerOf2; 3695 3696 // If all operands are exactly the same ConstantInt then set the 3697 // operand kind to OK_UniformConstantValue. 3698 // If instead not all operands are constants, then set the operand kind 3699 // to OK_AnyValue. If all operands are constants but not the same, 3700 // then set the operand kind to OK_NonUniformConstantValue. 3701 ConstantInt *CInt0 = nullptr; 3702 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 3703 const Instruction *I = cast<Instruction>(VL[i]); 3704 unsigned OpIdx = isa<BinaryOperator>(I) ? 1 : 0; 3705 ConstantInt *CInt = dyn_cast<ConstantInt>(I->getOperand(OpIdx)); 3706 if (!CInt) { 3707 Op2VK = TargetTransformInfo::OK_AnyValue; 3708 Op2VP = TargetTransformInfo::OP_None; 3709 break; 3710 } 3711 if (Op2VP == TargetTransformInfo::OP_PowerOf2 && 3712 !CInt->getValue().isPowerOf2()) 3713 Op2VP = TargetTransformInfo::OP_None; 3714 if (i == 0) { 3715 CInt0 = CInt; 3716 continue; 3717 } 3718 if (CInt0 != CInt) 3719 Op2VK = TargetTransformInfo::OK_NonUniformConstantValue; 3720 } 3721 3722 SmallVector<const Value *, 4> Operands(VL0->operand_values()); 3723 InstructionCost ScalarEltCost = 3724 TTI->getArithmeticInstrCost(E->getOpcode(), ScalarTy, CostKind, Op1VK, 3725 Op2VK, Op1VP, Op2VP, Operands, VL0); 3726 if (NeedToShuffleReuses) { 3727 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3728 } 3729 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3730 InstructionCost VecCost = 3731 TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind, Op1VK, 3732 Op2VK, Op1VP, Op2VP, Operands, VL0); 3733 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3734 return ReuseShuffleCost + VecCost - ScalarCost; 3735 } 3736 case Instruction::GetElementPtr: { 3737 TargetTransformInfo::OperandValueKind Op1VK = 3738 TargetTransformInfo::OK_AnyValue; 3739 TargetTransformInfo::OperandValueKind Op2VK = 3740 TargetTransformInfo::OK_UniformConstantValue; 3741 3742 InstructionCost ScalarEltCost = TTI->getArithmeticInstrCost( 3743 Instruction::Add, ScalarTy, CostKind, Op1VK, Op2VK); 3744 if (NeedToShuffleReuses) { 3745 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3746 } 3747 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3748 InstructionCost VecCost = TTI->getArithmeticInstrCost( 3749 Instruction::Add, VecTy, CostKind, Op1VK, Op2VK); 3750 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3751 return ReuseShuffleCost + VecCost - ScalarCost; 3752 } 3753 case Instruction::Load: { 3754 // Cost of wide load - cost of scalar loads. 3755 Align alignment = cast<LoadInst>(VL0)->getAlign(); 3756 InstructionCost ScalarEltCost = TTI->getMemoryOpCost( 3757 Instruction::Load, ScalarTy, alignment, 0, CostKind, VL0); 3758 if (NeedToShuffleReuses) { 3759 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3760 } 3761 InstructionCost ScalarLdCost = VecTy->getNumElements() * ScalarEltCost; 3762 InstructionCost VecLdCost; 3763 if (E->State == TreeEntry::Vectorize) { 3764 VecLdCost = TTI->getMemoryOpCost(Instruction::Load, VecTy, alignment, 0, 3765 CostKind, VL0); 3766 } else { 3767 assert(E->State == TreeEntry::ScatterVectorize && "Unknown EntryState"); 3768 VecLdCost = TTI->getGatherScatterOpCost( 3769 Instruction::Load, VecTy, cast<LoadInst>(VL0)->getPointerOperand(), 3770 /*VariableMask=*/false, alignment, CostKind, VL0); 3771 } 3772 if (!E->ReorderIndices.empty()) { 3773 // TODO: Merge this shuffle with the ReuseShuffleCost. 3774 VecLdCost += TTI->getShuffleCost( 3775 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3776 } 3777 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecLdCost, ScalarLdCost)); 3778 return ReuseShuffleCost + VecLdCost - ScalarLdCost; 3779 } 3780 case Instruction::Store: { 3781 // We know that we can merge the stores. Calculate the cost. 3782 bool IsReorder = !E->ReorderIndices.empty(); 3783 auto *SI = 3784 cast<StoreInst>(IsReorder ? VL[E->ReorderIndices.front()] : VL0); 3785 Align Alignment = SI->getAlign(); 3786 InstructionCost ScalarEltCost = TTI->getMemoryOpCost( 3787 Instruction::Store, ScalarTy, Alignment, 0, CostKind, VL0); 3788 if (NeedToShuffleReuses) 3789 ReuseShuffleCost = -(ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3790 InstructionCost ScalarStCost = VecTy->getNumElements() * ScalarEltCost; 3791 InstructionCost VecStCost = TTI->getMemoryOpCost( 3792 Instruction::Store, VecTy, Alignment, 0, CostKind, VL0); 3793 if (IsReorder) { 3794 // TODO: Merge this shuffle with the ReuseShuffleCost. 3795 VecStCost += TTI->getShuffleCost( 3796 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3797 } 3798 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecStCost, ScalarStCost)); 3799 return ReuseShuffleCost + VecStCost - ScalarStCost; 3800 } 3801 case Instruction::Call: { 3802 CallInst *CI = cast<CallInst>(VL0); 3803 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3804 3805 // Calculate the cost of the scalar and vector calls. 3806 IntrinsicCostAttributes CostAttrs(ID, *CI, 1); 3807 InstructionCost ScalarEltCost = 3808 TTI->getIntrinsicInstrCost(CostAttrs, CostKind); 3809 if (NeedToShuffleReuses) { 3810 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3811 } 3812 InstructionCost ScalarCallCost = VecTy->getNumElements() * ScalarEltCost; 3813 3814 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 3815 InstructionCost VecCallCost = 3816 std::min(VecCallCosts.first, VecCallCosts.second); 3817 3818 LLVM_DEBUG(dbgs() << "SLP: Call cost " << VecCallCost - ScalarCallCost 3819 << " (" << VecCallCost << "-" << ScalarCallCost << ")" 3820 << " for " << *CI << "\n"); 3821 3822 return ReuseShuffleCost + VecCallCost - ScalarCallCost; 3823 } 3824 case Instruction::ShuffleVector: { 3825 assert(E->isAltShuffle() && 3826 ((Instruction::isBinaryOp(E->getOpcode()) && 3827 Instruction::isBinaryOp(E->getAltOpcode())) || 3828 (Instruction::isCast(E->getOpcode()) && 3829 Instruction::isCast(E->getAltOpcode()))) && 3830 "Invalid Shuffle Vector Operand"); 3831 InstructionCost ScalarCost = 0; 3832 if (NeedToShuffleReuses) { 3833 for (unsigned Idx : E->ReuseShuffleIndices) { 3834 Instruction *I = cast<Instruction>(VL[Idx]); 3835 ReuseShuffleCost -= TTI->getInstructionCost(I, CostKind); 3836 } 3837 for (Value *V : VL) { 3838 Instruction *I = cast<Instruction>(V); 3839 ReuseShuffleCost += TTI->getInstructionCost(I, CostKind); 3840 } 3841 } 3842 for (Value *V : VL) { 3843 Instruction *I = cast<Instruction>(V); 3844 assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode"); 3845 ScalarCost += TTI->getInstructionCost(I, CostKind); 3846 } 3847 // VecCost is equal to sum of the cost of creating 2 vectors 3848 // and the cost of creating shuffle. 3849 InstructionCost VecCost = 0; 3850 if (Instruction::isBinaryOp(E->getOpcode())) { 3851 VecCost = TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind); 3852 VecCost += TTI->getArithmeticInstrCost(E->getAltOpcode(), VecTy, 3853 CostKind); 3854 } else { 3855 Type *Src0SclTy = E->getMainOp()->getOperand(0)->getType(); 3856 Type *Src1SclTy = E->getAltOp()->getOperand(0)->getType(); 3857 auto *Src0Ty = FixedVectorType::get(Src0SclTy, VL.size()); 3858 auto *Src1Ty = FixedVectorType::get(Src1SclTy, VL.size()); 3859 VecCost = TTI->getCastInstrCost(E->getOpcode(), VecTy, Src0Ty, 3860 TTI::CastContextHint::None, CostKind); 3861 VecCost += TTI->getCastInstrCost(E->getAltOpcode(), VecTy, Src1Ty, 3862 TTI::CastContextHint::None, CostKind); 3863 } 3864 VecCost += TTI->getShuffleCost(TargetTransformInfo::SK_Select, VecTy, 0); 3865 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3866 return ReuseShuffleCost + VecCost - ScalarCost; 3867 } 3868 default: 3869 llvm_unreachable("Unknown instruction"); 3870 } 3871 } 3872 3873 bool BoUpSLP::isFullyVectorizableTinyTree() const { 3874 LLVM_DEBUG(dbgs() << "SLP: Check whether the tree with height " 3875 << VectorizableTree.size() << " is fully vectorizable .\n"); 3876 3877 // We only handle trees of heights 1 and 2. 3878 if (VectorizableTree.size() == 1 && 3879 VectorizableTree[0]->State == TreeEntry::Vectorize) 3880 return true; 3881 3882 if (VectorizableTree.size() != 2) 3883 return false; 3884 3885 // Handle splat and all-constants stores. 3886 if (VectorizableTree[0]->State == TreeEntry::Vectorize && 3887 (allConstant(VectorizableTree[1]->Scalars) || 3888 isSplat(VectorizableTree[1]->Scalars))) 3889 return true; 3890 3891 // Gathering cost would be too much for tiny trees. 3892 if (VectorizableTree[0]->State == TreeEntry::NeedToGather || 3893 VectorizableTree[1]->State == TreeEntry::NeedToGather) 3894 return false; 3895 3896 return true; 3897 } 3898 3899 static bool isLoadCombineCandidateImpl(Value *Root, unsigned NumElts, 3900 TargetTransformInfo *TTI) { 3901 // Look past the root to find a source value. Arbitrarily follow the 3902 // path through operand 0 of any 'or'. Also, peek through optional 3903 // shift-left-by-multiple-of-8-bits. 3904 Value *ZextLoad = Root; 3905 const APInt *ShAmtC; 3906 while (!isa<ConstantExpr>(ZextLoad) && 3907 (match(ZextLoad, m_Or(m_Value(), m_Value())) || 3908 (match(ZextLoad, m_Shl(m_Value(), m_APInt(ShAmtC))) && 3909 ShAmtC->urem(8) == 0))) 3910 ZextLoad = cast<BinaryOperator>(ZextLoad)->getOperand(0); 3911 3912 // Check if the input is an extended load of the required or/shift expression. 3913 Value *LoadPtr; 3914 if (ZextLoad == Root || !match(ZextLoad, m_ZExt(m_Load(m_Value(LoadPtr))))) 3915 return false; 3916 3917 // Require that the total load bit width is a legal integer type. 3918 // For example, <8 x i8> --> i64 is a legal integer on a 64-bit target. 3919 // But <16 x i8> --> i128 is not, so the backend probably can't reduce it. 3920 Type *SrcTy = LoadPtr->getType()->getPointerElementType(); 3921 unsigned LoadBitWidth = SrcTy->getIntegerBitWidth() * NumElts; 3922 if (!TTI->isTypeLegal(IntegerType::get(Root->getContext(), LoadBitWidth))) 3923 return false; 3924 3925 // Everything matched - assume that we can fold the whole sequence using 3926 // load combining. 3927 LLVM_DEBUG(dbgs() << "SLP: Assume load combining for tree starting at " 3928 << *(cast<Instruction>(Root)) << "\n"); 3929 3930 return true; 3931 } 3932 3933 bool BoUpSLP::isLoadCombineReductionCandidate(RecurKind RdxKind) const { 3934 if (RdxKind != RecurKind::Or) 3935 return false; 3936 3937 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 3938 Value *FirstReduced = VectorizableTree[0]->Scalars[0]; 3939 return isLoadCombineCandidateImpl(FirstReduced, NumElts, TTI); 3940 } 3941 3942 bool BoUpSLP::isLoadCombineCandidate() const { 3943 // Peek through a final sequence of stores and check if all operations are 3944 // likely to be load-combined. 3945 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 3946 for (Value *Scalar : VectorizableTree[0]->Scalars) { 3947 Value *X; 3948 if (!match(Scalar, m_Store(m_Value(X), m_Value())) || 3949 !isLoadCombineCandidateImpl(X, NumElts, TTI)) 3950 return false; 3951 } 3952 return true; 3953 } 3954 3955 bool BoUpSLP::isTreeTinyAndNotFullyVectorizable() const { 3956 // We can vectorize the tree if its size is greater than or equal to the 3957 // minimum size specified by the MinTreeSize command line option. 3958 if (VectorizableTree.size() >= MinTreeSize) 3959 return false; 3960 3961 // If we have a tiny tree (a tree whose size is less than MinTreeSize), we 3962 // can vectorize it if we can prove it fully vectorizable. 3963 if (isFullyVectorizableTinyTree()) 3964 return false; 3965 3966 assert(VectorizableTree.empty() 3967 ? ExternalUses.empty() 3968 : true && "We shouldn't have any external users"); 3969 3970 // Otherwise, we can't vectorize the tree. It is both tiny and not fully 3971 // vectorizable. 3972 return true; 3973 } 3974 3975 InstructionCost BoUpSLP::getSpillCost() const { 3976 // Walk from the bottom of the tree to the top, tracking which values are 3977 // live. When we see a call instruction that is not part of our tree, 3978 // query TTI to see if there is a cost to keeping values live over it 3979 // (for example, if spills and fills are required). 3980 unsigned BundleWidth = VectorizableTree.front()->Scalars.size(); 3981 InstructionCost Cost = 0; 3982 3983 SmallPtrSet<Instruction*, 4> LiveValues; 3984 Instruction *PrevInst = nullptr; 3985 3986 // The entries in VectorizableTree are not necessarily ordered by their 3987 // position in basic blocks. Collect them and order them by dominance so later 3988 // instructions are guaranteed to be visited first. For instructions in 3989 // different basic blocks, we only scan to the beginning of the block, so 3990 // their order does not matter, as long as all instructions in a basic block 3991 // are grouped together. Using dominance ensures a deterministic order. 3992 SmallVector<Instruction *, 16> OrderedScalars; 3993 for (const auto &TEPtr : VectorizableTree) { 3994 Instruction *Inst = dyn_cast<Instruction>(TEPtr->Scalars[0]); 3995 if (!Inst) 3996 continue; 3997 OrderedScalars.push_back(Inst); 3998 } 3999 llvm::stable_sort(OrderedScalars, [this](Instruction *A, Instruction *B) { 4000 return DT->dominates(B, A); 4001 }); 4002 4003 for (Instruction *Inst : OrderedScalars) { 4004 if (!PrevInst) { 4005 PrevInst = Inst; 4006 continue; 4007 } 4008 4009 // Update LiveValues. 4010 LiveValues.erase(PrevInst); 4011 for (auto &J : PrevInst->operands()) { 4012 if (isa<Instruction>(&*J) && getTreeEntry(&*J)) 4013 LiveValues.insert(cast<Instruction>(&*J)); 4014 } 4015 4016 LLVM_DEBUG({ 4017 dbgs() << "SLP: #LV: " << LiveValues.size(); 4018 for (auto *X : LiveValues) 4019 dbgs() << " " << X->getName(); 4020 dbgs() << ", Looking at "; 4021 Inst->dump(); 4022 }); 4023 4024 // Now find the sequence of instructions between PrevInst and Inst. 4025 unsigned NumCalls = 0; 4026 BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(), 4027 PrevInstIt = 4028 PrevInst->getIterator().getReverse(); 4029 while (InstIt != PrevInstIt) { 4030 if (PrevInstIt == PrevInst->getParent()->rend()) { 4031 PrevInstIt = Inst->getParent()->rbegin(); 4032 continue; 4033 } 4034 4035 // Debug information does not impact spill cost. 4036 if ((isa<CallInst>(&*PrevInstIt) && 4037 !isa<DbgInfoIntrinsic>(&*PrevInstIt)) && 4038 &*PrevInstIt != PrevInst) 4039 NumCalls++; 4040 4041 ++PrevInstIt; 4042 } 4043 4044 if (NumCalls) { 4045 SmallVector<Type*, 4> V; 4046 for (auto *II : LiveValues) 4047 V.push_back(FixedVectorType::get(II->getType(), BundleWidth)); 4048 Cost += NumCalls * TTI->getCostOfKeepingLiveOverCall(V); 4049 } 4050 4051 PrevInst = Inst; 4052 } 4053 4054 return Cost; 4055 } 4056 4057 InstructionCost BoUpSLP::getTreeCost() { 4058 InstructionCost Cost = 0; 4059 LLVM_DEBUG(dbgs() << "SLP: Calculating cost for tree of size " 4060 << VectorizableTree.size() << ".\n"); 4061 4062 unsigned BundleWidth = VectorizableTree[0]->Scalars.size(); 4063 4064 for (unsigned I = 0, E = VectorizableTree.size(); I < E; ++I) { 4065 TreeEntry &TE = *VectorizableTree[I].get(); 4066 4067 // We create duplicate tree entries for gather sequences that have multiple 4068 // uses. However, we should not compute the cost of duplicate sequences. 4069 // For example, if we have a build vector (i.e., insertelement sequence) 4070 // that is used by more than one vector instruction, we only need to 4071 // compute the cost of the insertelement instructions once. The redundant 4072 // instructions will be eliminated by CSE. 4073 // 4074 // We should consider not creating duplicate tree entries for gather 4075 // sequences, and instead add additional edges to the tree representing 4076 // their uses. Since such an approach results in fewer total entries, 4077 // existing heuristics based on tree size may yield different results. 4078 // 4079 if (TE.State == TreeEntry::NeedToGather && 4080 std::any_of(std::next(VectorizableTree.begin(), I + 1), 4081 VectorizableTree.end(), 4082 [TE](const std::unique_ptr<TreeEntry> &EntryPtr) { 4083 return EntryPtr->State == TreeEntry::NeedToGather && 4084 EntryPtr->isSame(TE.Scalars); 4085 })) 4086 continue; 4087 4088 InstructionCost C = getEntryCost(&TE); 4089 Cost += C; 4090 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C 4091 << " for bundle that starts with " << *TE.Scalars[0] 4092 << ".\n" 4093 << "SLP: Current total cost = " << Cost << "\n"); 4094 } 4095 4096 SmallPtrSet<Value *, 16> ExtractCostCalculated; 4097 InstructionCost ExtractCost = 0; 4098 for (ExternalUser &EU : ExternalUses) { 4099 // We only add extract cost once for the same scalar. 4100 if (!ExtractCostCalculated.insert(EU.Scalar).second) 4101 continue; 4102 4103 // Uses by ephemeral values are free (because the ephemeral value will be 4104 // removed prior to code generation, and so the extraction will be 4105 // removed as well). 4106 if (EphValues.count(EU.User)) 4107 continue; 4108 4109 // If we plan to rewrite the tree in a smaller type, we will need to sign 4110 // extend the extracted value back to the original type. Here, we account 4111 // for the extract and the added cost of the sign extend if needed. 4112 auto *VecTy = FixedVectorType::get(EU.Scalar->getType(), BundleWidth); 4113 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 4114 if (MinBWs.count(ScalarRoot)) { 4115 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 4116 auto Extend = 4117 MinBWs[ScalarRoot].second ? Instruction::SExt : Instruction::ZExt; 4118 VecTy = FixedVectorType::get(MinTy, BundleWidth); 4119 ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(), 4120 VecTy, EU.Lane); 4121 } else { 4122 ExtractCost += 4123 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, EU.Lane); 4124 } 4125 } 4126 4127 InstructionCost SpillCost = getSpillCost(); 4128 Cost += SpillCost + ExtractCost; 4129 4130 #ifndef NDEBUG 4131 SmallString<256> Str; 4132 { 4133 raw_svector_ostream OS(Str); 4134 OS << "SLP: Spill Cost = " << SpillCost << ".\n" 4135 << "SLP: Extract Cost = " << ExtractCost << ".\n" 4136 << "SLP: Total Cost = " << Cost << ".\n"; 4137 } 4138 LLVM_DEBUG(dbgs() << Str); 4139 if (ViewSLPTree) 4140 ViewGraph(this, "SLP" + F->getName(), false, Str); 4141 #endif 4142 4143 return Cost; 4144 } 4145 4146 InstructionCost 4147 BoUpSLP::getGatherCost(FixedVectorType *Ty, 4148 const DenseSet<unsigned> &ShuffledIndices) const { 4149 unsigned NumElts = Ty->getNumElements(); 4150 APInt DemandedElts = APInt::getNullValue(NumElts); 4151 for (unsigned I = 0; I < NumElts; ++I) 4152 if (!ShuffledIndices.count(I)) 4153 DemandedElts.setBit(I); 4154 InstructionCost Cost = 4155 TTI->getScalarizationOverhead(Ty, DemandedElts, /*Insert*/ true, 4156 /*Extract*/ false); 4157 if (!ShuffledIndices.empty()) 4158 Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, Ty); 4159 return Cost; 4160 } 4161 4162 InstructionCost BoUpSLP::getGatherCost(ArrayRef<Value *> VL) const { 4163 // Find the type of the operands in VL. 4164 Type *ScalarTy = VL[0]->getType(); 4165 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 4166 ScalarTy = SI->getValueOperand()->getType(); 4167 auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); 4168 // Find the cost of inserting/extracting values from the vector. 4169 // Check if the same elements are inserted several times and count them as 4170 // shuffle candidates. 4171 DenseSet<unsigned> ShuffledElements; 4172 DenseSet<Value *> UniqueElements; 4173 // Iterate in reverse order to consider insert elements with the high cost. 4174 for (unsigned I = VL.size(); I > 0; --I) { 4175 unsigned Idx = I - 1; 4176 if (!UniqueElements.insert(VL[Idx]).second) 4177 ShuffledElements.insert(Idx); 4178 } 4179 return getGatherCost(VecTy, ShuffledElements); 4180 } 4181 4182 // Perform operand reordering on the instructions in VL and return the reordered 4183 // operands in Left and Right. 4184 void BoUpSLP::reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 4185 SmallVectorImpl<Value *> &Left, 4186 SmallVectorImpl<Value *> &Right, 4187 const DataLayout &DL, 4188 ScalarEvolution &SE, 4189 const BoUpSLP &R) { 4190 if (VL.empty()) 4191 return; 4192 VLOperands Ops(VL, DL, SE, R); 4193 // Reorder the operands in place. 4194 Ops.reorder(); 4195 Left = Ops.getVL(0); 4196 Right = Ops.getVL(1); 4197 } 4198 4199 void BoUpSLP::setInsertPointAfterBundle(TreeEntry *E) { 4200 // Get the basic block this bundle is in. All instructions in the bundle 4201 // should be in this block. 4202 auto *Front = E->getMainOp(); 4203 auto *BB = Front->getParent(); 4204 assert(llvm::all_of(E->Scalars, [=](Value *V) -> bool { 4205 auto *I = cast<Instruction>(V); 4206 return !E->isOpcodeOrAlt(I) || I->getParent() == BB; 4207 })); 4208 4209 // The last instruction in the bundle in program order. 4210 Instruction *LastInst = nullptr; 4211 4212 // Find the last instruction. The common case should be that BB has been 4213 // scheduled, and the last instruction is VL.back(). So we start with 4214 // VL.back() and iterate over schedule data until we reach the end of the 4215 // bundle. The end of the bundle is marked by null ScheduleData. 4216 if (BlocksSchedules.count(BB)) { 4217 auto *Bundle = 4218 BlocksSchedules[BB]->getScheduleData(E->isOneOf(E->Scalars.back())); 4219 if (Bundle && Bundle->isPartOfBundle()) 4220 for (; Bundle; Bundle = Bundle->NextInBundle) 4221 if (Bundle->OpValue == Bundle->Inst) 4222 LastInst = Bundle->Inst; 4223 } 4224 4225 // LastInst can still be null at this point if there's either not an entry 4226 // for BB in BlocksSchedules or there's no ScheduleData available for 4227 // VL.back(). This can be the case if buildTree_rec aborts for various 4228 // reasons (e.g., the maximum recursion depth is reached, the maximum region 4229 // size is reached, etc.). ScheduleData is initialized in the scheduling 4230 // "dry-run". 4231 // 4232 // If this happens, we can still find the last instruction by brute force. We 4233 // iterate forwards from Front (inclusive) until we either see all 4234 // instructions in the bundle or reach the end of the block. If Front is the 4235 // last instruction in program order, LastInst will be set to Front, and we 4236 // will visit all the remaining instructions in the block. 4237 // 4238 // One of the reasons we exit early from buildTree_rec is to place an upper 4239 // bound on compile-time. Thus, taking an additional compile-time hit here is 4240 // not ideal. However, this should be exceedingly rare since it requires that 4241 // we both exit early from buildTree_rec and that the bundle be out-of-order 4242 // (causing us to iterate all the way to the end of the block). 4243 if (!LastInst) { 4244 SmallPtrSet<Value *, 16> Bundle(E->Scalars.begin(), E->Scalars.end()); 4245 for (auto &I : make_range(BasicBlock::iterator(Front), BB->end())) { 4246 if (Bundle.erase(&I) && E->isOpcodeOrAlt(&I)) 4247 LastInst = &I; 4248 if (Bundle.empty()) 4249 break; 4250 } 4251 } 4252 assert(LastInst && "Failed to find last instruction in bundle"); 4253 4254 // Set the insertion point after the last instruction in the bundle. Set the 4255 // debug location to Front. 4256 Builder.SetInsertPoint(BB, ++LastInst->getIterator()); 4257 Builder.SetCurrentDebugLocation(Front->getDebugLoc()); 4258 } 4259 4260 Value *BoUpSLP::gather(ArrayRef<Value *> VL) { 4261 Value *Val0 = 4262 isa<StoreInst>(VL[0]) ? cast<StoreInst>(VL[0])->getValueOperand() : VL[0]; 4263 FixedVectorType *VecTy = FixedVectorType::get(Val0->getType(), VL.size()); 4264 Value *Vec = PoisonValue::get(VecTy); 4265 unsigned InsIndex = 0; 4266 for (Value *Val : VL) { 4267 Vec = Builder.CreateInsertElement(Vec, Val, Builder.getInt32(InsIndex++)); 4268 auto *InsElt = dyn_cast<InsertElementInst>(Vec); 4269 if (!InsElt) 4270 continue; 4271 GatherSeq.insert(InsElt); 4272 CSEBlocks.insert(InsElt->getParent()); 4273 // Add to our 'need-to-extract' list. 4274 if (TreeEntry *Entry = getTreeEntry(Val)) { 4275 // Find which lane we need to extract. 4276 unsigned FoundLane = std::distance(Entry->Scalars.begin(), 4277 find(Entry->Scalars, Val)); 4278 assert(FoundLane < Entry->Scalars.size() && "Couldn't find extract lane"); 4279 if (!Entry->ReuseShuffleIndices.empty()) { 4280 FoundLane = std::distance(Entry->ReuseShuffleIndices.begin(), 4281 find(Entry->ReuseShuffleIndices, FoundLane)); 4282 } 4283 ExternalUses.push_back(ExternalUser(Val, InsElt, FoundLane)); 4284 } 4285 } 4286 4287 return Vec; 4288 } 4289 4290 Value *BoUpSLP::vectorizeTree(ArrayRef<Value *> VL) { 4291 InstructionsState S = getSameOpcode(VL); 4292 if (S.getOpcode()) { 4293 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 4294 if (E->isSame(VL)) { 4295 Value *V = vectorizeTree(E); 4296 if (VL.size() == E->Scalars.size() && !E->ReuseShuffleIndices.empty()) { 4297 // We need to get the vectorized value but without shuffle. 4298 if (auto *SV = dyn_cast<ShuffleVectorInst>(V)) { 4299 V = SV->getOperand(0); 4300 } else { 4301 // Reshuffle to get only unique values. 4302 SmallVector<int, 4> UniqueIdxs; 4303 SmallSet<int, 4> UsedIdxs; 4304 for (int Idx : E->ReuseShuffleIndices) 4305 if (UsedIdxs.insert(Idx).second) 4306 UniqueIdxs.emplace_back(Idx); 4307 V = Builder.CreateShuffleVector(V, UniqueIdxs); 4308 } 4309 } 4310 return V; 4311 } 4312 } 4313 } 4314 4315 // Check that every instruction appears once in this bundle. 4316 SmallVector<int, 4> ReuseShuffleIndicies; 4317 SmallVector<Value *, 4> UniqueValues; 4318 if (VL.size() > 2) { 4319 DenseMap<Value *, unsigned> UniquePositions; 4320 for (Value *V : VL) { 4321 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 4322 ReuseShuffleIndicies.emplace_back(Res.first->second); 4323 if (Res.second || isa<Constant>(V)) 4324 UniqueValues.emplace_back(V); 4325 } 4326 // Do not shuffle single element or if number of unique values is not power 4327 // of 2. 4328 if (UniqueValues.size() == VL.size() || UniqueValues.size() <= 1 || 4329 !llvm::isPowerOf2_32(UniqueValues.size())) 4330 ReuseShuffleIndicies.clear(); 4331 else 4332 VL = UniqueValues; 4333 } 4334 4335 Value *Vec = gather(VL); 4336 if (!ReuseShuffleIndicies.empty()) { 4337 Vec = Builder.CreateShuffleVector(Vec, ReuseShuffleIndicies, "shuffle"); 4338 if (auto *I = dyn_cast<Instruction>(Vec)) { 4339 GatherSeq.insert(I); 4340 CSEBlocks.insert(I->getParent()); 4341 } 4342 } 4343 return Vec; 4344 } 4345 4346 Value *BoUpSLP::vectorizeTree(TreeEntry *E) { 4347 IRBuilder<>::InsertPointGuard Guard(Builder); 4348 4349 if (E->VectorizedValue) { 4350 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *E->Scalars[0] << ".\n"); 4351 return E->VectorizedValue; 4352 } 4353 4354 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 4355 if (E->State == TreeEntry::NeedToGather) { 4356 setInsertPointAfterBundle(E); 4357 Value *Vec = gather(E->Scalars); 4358 if (NeedToShuffleReuses) { 4359 Vec = Builder.CreateShuffleVector(Vec, E->ReuseShuffleIndices, "shuffle"); 4360 if (auto *I = dyn_cast<Instruction>(Vec)) { 4361 GatherSeq.insert(I); 4362 CSEBlocks.insert(I->getParent()); 4363 } 4364 } 4365 E->VectorizedValue = Vec; 4366 return Vec; 4367 } 4368 4369 assert((E->State == TreeEntry::Vectorize || 4370 E->State == TreeEntry::ScatterVectorize) && 4371 "Unhandled state"); 4372 unsigned ShuffleOrOp = 4373 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 4374 Instruction *VL0 = E->getMainOp(); 4375 Type *ScalarTy = VL0->getType(); 4376 if (auto *Store = dyn_cast<StoreInst>(VL0)) 4377 ScalarTy = Store->getValueOperand()->getType(); 4378 auto *VecTy = FixedVectorType::get(ScalarTy, E->Scalars.size()); 4379 switch (ShuffleOrOp) { 4380 case Instruction::PHI: { 4381 auto *PH = cast<PHINode>(VL0); 4382 Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI()); 4383 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 4384 PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues()); 4385 Value *V = NewPhi; 4386 if (NeedToShuffleReuses) 4387 V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle"); 4388 4389 E->VectorizedValue = V; 4390 4391 // PHINodes may have multiple entries from the same block. We want to 4392 // visit every block once. 4393 SmallPtrSet<BasicBlock*, 4> VisitedBBs; 4394 4395 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 4396 ValueList Operands; 4397 BasicBlock *IBB = PH->getIncomingBlock(i); 4398 4399 if (!VisitedBBs.insert(IBB).second) { 4400 NewPhi->addIncoming(NewPhi->getIncomingValueForBlock(IBB), IBB); 4401 continue; 4402 } 4403 4404 Builder.SetInsertPoint(IBB->getTerminator()); 4405 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 4406 Value *Vec = vectorizeTree(E->getOperand(i)); 4407 NewPhi->addIncoming(Vec, IBB); 4408 } 4409 4410 assert(NewPhi->getNumIncomingValues() == PH->getNumIncomingValues() && 4411 "Invalid number of incoming values"); 4412 return V; 4413 } 4414 4415 case Instruction::ExtractElement: { 4416 Value *V = E->getSingleOperand(0); 4417 if (!E->ReorderIndices.empty()) { 4418 SmallVector<int, 4> Mask; 4419 inversePermutation(E->ReorderIndices, Mask); 4420 Builder.SetInsertPoint(VL0); 4421 V = Builder.CreateShuffleVector(V, Mask, "reorder_shuffle"); 4422 } 4423 if (NeedToShuffleReuses) { 4424 // TODO: Merge this shuffle with the ReorderShuffleMask. 4425 if (E->ReorderIndices.empty()) 4426 Builder.SetInsertPoint(VL0); 4427 V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle"); 4428 } 4429 E->VectorizedValue = V; 4430 return V; 4431 } 4432 case Instruction::ExtractValue: { 4433 auto *LI = cast<LoadInst>(E->getSingleOperand(0)); 4434 Builder.SetInsertPoint(LI); 4435 auto *PtrTy = PointerType::get(VecTy, LI->getPointerAddressSpace()); 4436 Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy); 4437 LoadInst *V = Builder.CreateAlignedLoad(VecTy, Ptr, LI->getAlign()); 4438 Value *NewV = propagateMetadata(V, E->Scalars); 4439 if (!E->ReorderIndices.empty()) { 4440 SmallVector<int, 4> Mask; 4441 inversePermutation(E->ReorderIndices, Mask); 4442 NewV = Builder.CreateShuffleVector(NewV, Mask, "reorder_shuffle"); 4443 } 4444 if (NeedToShuffleReuses) { 4445 // TODO: Merge this shuffle with the ReorderShuffleMask. 4446 NewV = Builder.CreateShuffleVector(NewV, E->ReuseShuffleIndices, 4447 "shuffle"); 4448 } 4449 E->VectorizedValue = NewV; 4450 return NewV; 4451 } 4452 case Instruction::ZExt: 4453 case Instruction::SExt: 4454 case Instruction::FPToUI: 4455 case Instruction::FPToSI: 4456 case Instruction::FPExt: 4457 case Instruction::PtrToInt: 4458 case Instruction::IntToPtr: 4459 case Instruction::SIToFP: 4460 case Instruction::UIToFP: 4461 case Instruction::Trunc: 4462 case Instruction::FPTrunc: 4463 case Instruction::BitCast: { 4464 setInsertPointAfterBundle(E); 4465 4466 Value *InVec = vectorizeTree(E->getOperand(0)); 4467 4468 if (E->VectorizedValue) { 4469 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4470 return E->VectorizedValue; 4471 } 4472 4473 auto *CI = cast<CastInst>(VL0); 4474 Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy); 4475 if (NeedToShuffleReuses) 4476 V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle"); 4477 4478 E->VectorizedValue = V; 4479 ++NumVectorInstructions; 4480 return V; 4481 } 4482 case Instruction::FCmp: 4483 case Instruction::ICmp: { 4484 setInsertPointAfterBundle(E); 4485 4486 Value *L = vectorizeTree(E->getOperand(0)); 4487 Value *R = vectorizeTree(E->getOperand(1)); 4488 4489 if (E->VectorizedValue) { 4490 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4491 return E->VectorizedValue; 4492 } 4493 4494 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 4495 Value *V = Builder.CreateCmp(P0, L, R); 4496 propagateIRFlags(V, E->Scalars, VL0); 4497 if (NeedToShuffleReuses) 4498 V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle"); 4499 4500 E->VectorizedValue = V; 4501 ++NumVectorInstructions; 4502 return V; 4503 } 4504 case Instruction::Select: { 4505 setInsertPointAfterBundle(E); 4506 4507 Value *Cond = vectorizeTree(E->getOperand(0)); 4508 Value *True = vectorizeTree(E->getOperand(1)); 4509 Value *False = vectorizeTree(E->getOperand(2)); 4510 4511 if (E->VectorizedValue) { 4512 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4513 return E->VectorizedValue; 4514 } 4515 4516 Value *V = Builder.CreateSelect(Cond, True, False); 4517 if (NeedToShuffleReuses) 4518 V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle"); 4519 4520 E->VectorizedValue = V; 4521 ++NumVectorInstructions; 4522 return V; 4523 } 4524 case Instruction::FNeg: { 4525 setInsertPointAfterBundle(E); 4526 4527 Value *Op = vectorizeTree(E->getOperand(0)); 4528 4529 if (E->VectorizedValue) { 4530 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4531 return E->VectorizedValue; 4532 } 4533 4534 Value *V = Builder.CreateUnOp( 4535 static_cast<Instruction::UnaryOps>(E->getOpcode()), Op); 4536 propagateIRFlags(V, E->Scalars, VL0); 4537 if (auto *I = dyn_cast<Instruction>(V)) 4538 V = propagateMetadata(I, E->Scalars); 4539 4540 if (NeedToShuffleReuses) 4541 V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle"); 4542 4543 E->VectorizedValue = V; 4544 ++NumVectorInstructions; 4545 4546 return V; 4547 } 4548 case Instruction::Add: 4549 case Instruction::FAdd: 4550 case Instruction::Sub: 4551 case Instruction::FSub: 4552 case Instruction::Mul: 4553 case Instruction::FMul: 4554 case Instruction::UDiv: 4555 case Instruction::SDiv: 4556 case Instruction::FDiv: 4557 case Instruction::URem: 4558 case Instruction::SRem: 4559 case Instruction::FRem: 4560 case Instruction::Shl: 4561 case Instruction::LShr: 4562 case Instruction::AShr: 4563 case Instruction::And: 4564 case Instruction::Or: 4565 case Instruction::Xor: { 4566 setInsertPointAfterBundle(E); 4567 4568 Value *LHS = vectorizeTree(E->getOperand(0)); 4569 Value *RHS = vectorizeTree(E->getOperand(1)); 4570 4571 if (E->VectorizedValue) { 4572 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4573 return E->VectorizedValue; 4574 } 4575 4576 Value *V = Builder.CreateBinOp( 4577 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, 4578 RHS); 4579 propagateIRFlags(V, E->Scalars, VL0); 4580 if (auto *I = dyn_cast<Instruction>(V)) 4581 V = propagateMetadata(I, E->Scalars); 4582 4583 if (NeedToShuffleReuses) 4584 V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle"); 4585 4586 E->VectorizedValue = V; 4587 ++NumVectorInstructions; 4588 4589 return V; 4590 } 4591 case Instruction::Load: { 4592 // Loads are inserted at the head of the tree because we don't want to 4593 // sink them all the way down past store instructions. 4594 bool IsReorder = E->updateStateIfReorder(); 4595 if (IsReorder) 4596 VL0 = E->getMainOp(); 4597 setInsertPointAfterBundle(E); 4598 4599 LoadInst *LI = cast<LoadInst>(VL0); 4600 Instruction *NewLI; 4601 unsigned AS = LI->getPointerAddressSpace(); 4602 Value *PO = LI->getPointerOperand(); 4603 if (E->State == TreeEntry::Vectorize) { 4604 4605 Value *VecPtr = Builder.CreateBitCast(PO, VecTy->getPointerTo(AS)); 4606 4607 // The pointer operand uses an in-tree scalar so we add the new BitCast 4608 // to ExternalUses list to make sure that an extract will be generated 4609 // in the future. 4610 if (getTreeEntry(PO)) 4611 ExternalUses.emplace_back(PO, cast<User>(VecPtr), 0); 4612 4613 NewLI = Builder.CreateAlignedLoad(VecTy, VecPtr, LI->getAlign()); 4614 } else { 4615 assert(E->State == TreeEntry::ScatterVectorize && "Unhandled state"); 4616 Value *VecPtr = vectorizeTree(E->getOperand(0)); 4617 // Use the minimum alignment of the gathered loads. 4618 Align CommonAlignment = LI->getAlign(); 4619 for (Value *V : E->Scalars) 4620 CommonAlignment = 4621 commonAlignment(CommonAlignment, cast<LoadInst>(V)->getAlign()); 4622 NewLI = Builder.CreateMaskedGather(VecPtr, CommonAlignment); 4623 } 4624 Value *V = propagateMetadata(NewLI, E->Scalars); 4625 4626 if (IsReorder) { 4627 SmallVector<int, 4> Mask; 4628 inversePermutation(E->ReorderIndices, Mask); 4629 V = Builder.CreateShuffleVector(V, Mask, "reorder_shuffle"); 4630 } 4631 if (NeedToShuffleReuses) { 4632 // TODO: Merge this shuffle with the ReorderShuffleMask. 4633 V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle"); 4634 } 4635 E->VectorizedValue = V; 4636 ++NumVectorInstructions; 4637 return V; 4638 } 4639 case Instruction::Store: { 4640 bool IsReorder = !E->ReorderIndices.empty(); 4641 auto *SI = cast<StoreInst>( 4642 IsReorder ? E->Scalars[E->ReorderIndices.front()] : VL0); 4643 unsigned AS = SI->getPointerAddressSpace(); 4644 4645 setInsertPointAfterBundle(E); 4646 4647 Value *VecValue = vectorizeTree(E->getOperand(0)); 4648 if (IsReorder) { 4649 SmallVector<int, 4> Mask(E->ReorderIndices.begin(), 4650 E->ReorderIndices.end()); 4651 VecValue = Builder.CreateShuffleVector(VecValue, Mask, "reorder_shuf"); 4652 } 4653 Value *ScalarPtr = SI->getPointerOperand(); 4654 Value *VecPtr = Builder.CreateBitCast( 4655 ScalarPtr, VecValue->getType()->getPointerTo(AS)); 4656 StoreInst *ST = Builder.CreateAlignedStore(VecValue, VecPtr, 4657 SI->getAlign()); 4658 4659 // The pointer operand uses an in-tree scalar, so add the new BitCast to 4660 // ExternalUses to make sure that an extract will be generated in the 4661 // future. 4662 if (getTreeEntry(ScalarPtr)) 4663 ExternalUses.push_back(ExternalUser(ScalarPtr, cast<User>(VecPtr), 0)); 4664 4665 Value *V = propagateMetadata(ST, E->Scalars); 4666 if (NeedToShuffleReuses) 4667 V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle"); 4668 4669 E->VectorizedValue = V; 4670 ++NumVectorInstructions; 4671 return V; 4672 } 4673 case Instruction::GetElementPtr: { 4674 setInsertPointAfterBundle(E); 4675 4676 Value *Op0 = vectorizeTree(E->getOperand(0)); 4677 4678 std::vector<Value *> OpVecs; 4679 for (int j = 1, e = cast<GetElementPtrInst>(VL0)->getNumOperands(); j < e; 4680 ++j) { 4681 ValueList &VL = E->getOperand(j); 4682 // Need to cast all elements to the same type before vectorization to 4683 // avoid crash. 4684 Type *VL0Ty = VL0->getOperand(j)->getType(); 4685 Type *Ty = llvm::all_of( 4686 VL, [VL0Ty](Value *V) { return VL0Ty == V->getType(); }) 4687 ? VL0Ty 4688 : DL->getIndexType(cast<GetElementPtrInst>(VL0) 4689 ->getPointerOperandType() 4690 ->getScalarType()); 4691 for (Value *&V : VL) { 4692 auto *CI = cast<ConstantInt>(V); 4693 V = ConstantExpr::getIntegerCast(CI, Ty, 4694 CI->getValue().isSignBitSet()); 4695 } 4696 Value *OpVec = vectorizeTree(VL); 4697 OpVecs.push_back(OpVec); 4698 } 4699 4700 Value *V = Builder.CreateGEP( 4701 cast<GetElementPtrInst>(VL0)->getSourceElementType(), Op0, OpVecs); 4702 if (Instruction *I = dyn_cast<Instruction>(V)) 4703 V = propagateMetadata(I, E->Scalars); 4704 4705 if (NeedToShuffleReuses) 4706 V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle"); 4707 4708 E->VectorizedValue = V; 4709 ++NumVectorInstructions; 4710 4711 return V; 4712 } 4713 case Instruction::Call: { 4714 CallInst *CI = cast<CallInst>(VL0); 4715 setInsertPointAfterBundle(E); 4716 4717 Intrinsic::ID IID = Intrinsic::not_intrinsic; 4718 if (Function *FI = CI->getCalledFunction()) 4719 IID = FI->getIntrinsicID(); 4720 4721 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 4722 4723 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 4724 bool UseIntrinsic = ID != Intrinsic::not_intrinsic && 4725 VecCallCosts.first <= VecCallCosts.second; 4726 4727 Value *ScalarArg = nullptr; 4728 std::vector<Value *> OpVecs; 4729 for (int j = 0, e = CI->getNumArgOperands(); j < e; ++j) { 4730 ValueList OpVL; 4731 // Some intrinsics have scalar arguments. This argument should not be 4732 // vectorized. 4733 if (UseIntrinsic && hasVectorInstrinsicScalarOpd(IID, j)) { 4734 CallInst *CEI = cast<CallInst>(VL0); 4735 ScalarArg = CEI->getArgOperand(j); 4736 OpVecs.push_back(CEI->getArgOperand(j)); 4737 continue; 4738 } 4739 4740 Value *OpVec = vectorizeTree(E->getOperand(j)); 4741 LLVM_DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n"); 4742 OpVecs.push_back(OpVec); 4743 } 4744 4745 Function *CF; 4746 if (!UseIntrinsic) { 4747 VFShape Shape = 4748 VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>( 4749 VecTy->getNumElements())), 4750 false /*HasGlobalPred*/); 4751 CF = VFDatabase(*CI).getVectorizedFunction(Shape); 4752 } else { 4753 Type *Tys[] = {FixedVectorType::get(CI->getType(), E->Scalars.size())}; 4754 CF = Intrinsic::getDeclaration(F->getParent(), ID, Tys); 4755 } 4756 4757 SmallVector<OperandBundleDef, 1> OpBundles; 4758 CI->getOperandBundlesAsDefs(OpBundles); 4759 Value *V = Builder.CreateCall(CF, OpVecs, OpBundles); 4760 4761 // The scalar argument uses an in-tree scalar so we add the new vectorized 4762 // call to ExternalUses list to make sure that an extract will be 4763 // generated in the future. 4764 if (ScalarArg && getTreeEntry(ScalarArg)) 4765 ExternalUses.push_back(ExternalUser(ScalarArg, cast<User>(V), 0)); 4766 4767 propagateIRFlags(V, E->Scalars, VL0); 4768 if (NeedToShuffleReuses) 4769 V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle"); 4770 4771 E->VectorizedValue = V; 4772 ++NumVectorInstructions; 4773 return V; 4774 } 4775 case Instruction::ShuffleVector: { 4776 assert(E->isAltShuffle() && 4777 ((Instruction::isBinaryOp(E->getOpcode()) && 4778 Instruction::isBinaryOp(E->getAltOpcode())) || 4779 (Instruction::isCast(E->getOpcode()) && 4780 Instruction::isCast(E->getAltOpcode()))) && 4781 "Invalid Shuffle Vector Operand"); 4782 4783 Value *LHS = nullptr, *RHS = nullptr; 4784 if (Instruction::isBinaryOp(E->getOpcode())) { 4785 setInsertPointAfterBundle(E); 4786 LHS = vectorizeTree(E->getOperand(0)); 4787 RHS = vectorizeTree(E->getOperand(1)); 4788 } else { 4789 setInsertPointAfterBundle(E); 4790 LHS = vectorizeTree(E->getOperand(0)); 4791 } 4792 4793 if (E->VectorizedValue) { 4794 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4795 return E->VectorizedValue; 4796 } 4797 4798 Value *V0, *V1; 4799 if (Instruction::isBinaryOp(E->getOpcode())) { 4800 V0 = Builder.CreateBinOp( 4801 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, RHS); 4802 V1 = Builder.CreateBinOp( 4803 static_cast<Instruction::BinaryOps>(E->getAltOpcode()), LHS, RHS); 4804 } else { 4805 V0 = Builder.CreateCast( 4806 static_cast<Instruction::CastOps>(E->getOpcode()), LHS, VecTy); 4807 V1 = Builder.CreateCast( 4808 static_cast<Instruction::CastOps>(E->getAltOpcode()), LHS, VecTy); 4809 } 4810 4811 // Create shuffle to take alternate operations from the vector. 4812 // Also, gather up main and alt scalar ops to propagate IR flags to 4813 // each vector operation. 4814 ValueList OpScalars, AltScalars; 4815 unsigned e = E->Scalars.size(); 4816 SmallVector<int, 8> Mask(e); 4817 for (unsigned i = 0; i < e; ++i) { 4818 auto *OpInst = cast<Instruction>(E->Scalars[i]); 4819 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 4820 if (OpInst->getOpcode() == E->getAltOpcode()) { 4821 Mask[i] = e + i; 4822 AltScalars.push_back(E->Scalars[i]); 4823 } else { 4824 Mask[i] = i; 4825 OpScalars.push_back(E->Scalars[i]); 4826 } 4827 } 4828 4829 propagateIRFlags(V0, OpScalars); 4830 propagateIRFlags(V1, AltScalars); 4831 4832 Value *V = Builder.CreateShuffleVector(V0, V1, Mask); 4833 if (Instruction *I = dyn_cast<Instruction>(V)) 4834 V = propagateMetadata(I, E->Scalars); 4835 if (NeedToShuffleReuses) 4836 V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle"); 4837 4838 E->VectorizedValue = V; 4839 ++NumVectorInstructions; 4840 4841 return V; 4842 } 4843 default: 4844 llvm_unreachable("unknown inst"); 4845 } 4846 return nullptr; 4847 } 4848 4849 Value *BoUpSLP::vectorizeTree() { 4850 ExtraValueToDebugLocsMap ExternallyUsedValues; 4851 return vectorizeTree(ExternallyUsedValues); 4852 } 4853 4854 Value * 4855 BoUpSLP::vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues) { 4856 // All blocks must be scheduled before any instructions are inserted. 4857 for (auto &BSIter : BlocksSchedules) { 4858 scheduleBlock(BSIter.second.get()); 4859 } 4860 4861 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4862 auto *VectorRoot = vectorizeTree(VectorizableTree[0].get()); 4863 4864 // If the vectorized tree can be rewritten in a smaller type, we truncate the 4865 // vectorized root. InstCombine will then rewrite the entire expression. We 4866 // sign extend the extracted values below. 4867 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 4868 if (MinBWs.count(ScalarRoot)) { 4869 if (auto *I = dyn_cast<Instruction>(VectorRoot)) 4870 Builder.SetInsertPoint(&*++BasicBlock::iterator(I)); 4871 auto BundleWidth = VectorizableTree[0]->Scalars.size(); 4872 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 4873 auto *VecTy = FixedVectorType::get(MinTy, BundleWidth); 4874 auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy); 4875 VectorizableTree[0]->VectorizedValue = Trunc; 4876 } 4877 4878 LLVM_DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size() 4879 << " values .\n"); 4880 4881 // If necessary, sign-extend or zero-extend ScalarRoot to the larger type 4882 // specified by ScalarType. 4883 auto extend = [&](Value *ScalarRoot, Value *Ex, Type *ScalarType) { 4884 if (!MinBWs.count(ScalarRoot)) 4885 return Ex; 4886 if (MinBWs[ScalarRoot].second) 4887 return Builder.CreateSExt(Ex, ScalarType); 4888 return Builder.CreateZExt(Ex, ScalarType); 4889 }; 4890 4891 // Extract all of the elements with the external uses. 4892 for (const auto &ExternalUse : ExternalUses) { 4893 Value *Scalar = ExternalUse.Scalar; 4894 llvm::User *User = ExternalUse.User; 4895 4896 // Skip users that we already RAUW. This happens when one instruction 4897 // has multiple uses of the same value. 4898 if (User && !is_contained(Scalar->users(), User)) 4899 continue; 4900 TreeEntry *E = getTreeEntry(Scalar); 4901 assert(E && "Invalid scalar"); 4902 assert(E->State != TreeEntry::NeedToGather && 4903 "Extracting from a gather list"); 4904 4905 Value *Vec = E->VectorizedValue; 4906 assert(Vec && "Can't find vectorizable value"); 4907 4908 Value *Lane = Builder.getInt32(ExternalUse.Lane); 4909 // If User == nullptr, the Scalar is used as extra arg. Generate 4910 // ExtractElement instruction and update the record for this scalar in 4911 // ExternallyUsedValues. 4912 if (!User) { 4913 assert(ExternallyUsedValues.count(Scalar) && 4914 "Scalar with nullptr as an external user must be registered in " 4915 "ExternallyUsedValues map"); 4916 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 4917 Builder.SetInsertPoint(VecI->getParent(), 4918 std::next(VecI->getIterator())); 4919 } else { 4920 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4921 } 4922 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4923 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4924 CSEBlocks.insert(cast<Instruction>(Scalar)->getParent()); 4925 auto &Locs = ExternallyUsedValues[Scalar]; 4926 ExternallyUsedValues.insert({Ex, Locs}); 4927 ExternallyUsedValues.erase(Scalar); 4928 // Required to update internally referenced instructions. 4929 Scalar->replaceAllUsesWith(Ex); 4930 continue; 4931 } 4932 4933 // Generate extracts for out-of-tree users. 4934 // Find the insertion point for the extractelement lane. 4935 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 4936 if (PHINode *PH = dyn_cast<PHINode>(User)) { 4937 for (int i = 0, e = PH->getNumIncomingValues(); i != e; ++i) { 4938 if (PH->getIncomingValue(i) == Scalar) { 4939 Instruction *IncomingTerminator = 4940 PH->getIncomingBlock(i)->getTerminator(); 4941 if (isa<CatchSwitchInst>(IncomingTerminator)) { 4942 Builder.SetInsertPoint(VecI->getParent(), 4943 std::next(VecI->getIterator())); 4944 } else { 4945 Builder.SetInsertPoint(PH->getIncomingBlock(i)->getTerminator()); 4946 } 4947 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4948 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4949 CSEBlocks.insert(PH->getIncomingBlock(i)); 4950 PH->setOperand(i, Ex); 4951 } 4952 } 4953 } else { 4954 Builder.SetInsertPoint(cast<Instruction>(User)); 4955 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4956 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4957 CSEBlocks.insert(cast<Instruction>(User)->getParent()); 4958 User->replaceUsesOfWith(Scalar, Ex); 4959 } 4960 } else { 4961 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4962 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4963 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4964 CSEBlocks.insert(&F->getEntryBlock()); 4965 User->replaceUsesOfWith(Scalar, Ex); 4966 } 4967 4968 LLVM_DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n"); 4969 } 4970 4971 // For each vectorized value: 4972 for (auto &TEPtr : VectorizableTree) { 4973 TreeEntry *Entry = TEPtr.get(); 4974 4975 // No need to handle users of gathered values. 4976 if (Entry->State == TreeEntry::NeedToGather) 4977 continue; 4978 4979 assert(Entry->VectorizedValue && "Can't find vectorizable value"); 4980 4981 // For each lane: 4982 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 4983 Value *Scalar = Entry->Scalars[Lane]; 4984 4985 #ifndef NDEBUG 4986 Type *Ty = Scalar->getType(); 4987 if (!Ty->isVoidTy()) { 4988 for (User *U : Scalar->users()) { 4989 LLVM_DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n"); 4990 4991 // It is legal to delete users in the ignorelist. 4992 assert((getTreeEntry(U) || is_contained(UserIgnoreList, U)) && 4993 "Deleting out-of-tree value"); 4994 } 4995 } 4996 #endif 4997 LLVM_DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n"); 4998 eraseInstruction(cast<Instruction>(Scalar)); 4999 } 5000 } 5001 5002 Builder.ClearInsertionPoint(); 5003 InstrElementSize.clear(); 5004 5005 return VectorizableTree[0]->VectorizedValue; 5006 } 5007 5008 void BoUpSLP::optimizeGatherSequence() { 5009 LLVM_DEBUG(dbgs() << "SLP: Optimizing " << GatherSeq.size() 5010 << " gather sequences instructions.\n"); 5011 // LICM InsertElementInst sequences. 5012 for (Instruction *I : GatherSeq) { 5013 if (isDeleted(I)) 5014 continue; 5015 5016 // Check if this block is inside a loop. 5017 Loop *L = LI->getLoopFor(I->getParent()); 5018 if (!L) 5019 continue; 5020 5021 // Check if it has a preheader. 5022 BasicBlock *PreHeader = L->getLoopPreheader(); 5023 if (!PreHeader) 5024 continue; 5025 5026 // If the vector or the element that we insert into it are 5027 // instructions that are defined in this basic block then we can't 5028 // hoist this instruction. 5029 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 5030 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 5031 if (Op0 && L->contains(Op0)) 5032 continue; 5033 if (Op1 && L->contains(Op1)) 5034 continue; 5035 5036 // We can hoist this instruction. Move it to the pre-header. 5037 I->moveBefore(PreHeader->getTerminator()); 5038 } 5039 5040 // Make a list of all reachable blocks in our CSE queue. 5041 SmallVector<const DomTreeNode *, 8> CSEWorkList; 5042 CSEWorkList.reserve(CSEBlocks.size()); 5043 for (BasicBlock *BB : CSEBlocks) 5044 if (DomTreeNode *N = DT->getNode(BB)) { 5045 assert(DT->isReachableFromEntry(N)); 5046 CSEWorkList.push_back(N); 5047 } 5048 5049 // Sort blocks by domination. This ensures we visit a block after all blocks 5050 // dominating it are visited. 5051 llvm::stable_sort(CSEWorkList, 5052 [this](const DomTreeNode *A, const DomTreeNode *B) { 5053 return DT->properlyDominates(A, B); 5054 }); 5055 5056 // Perform O(N^2) search over the gather sequences and merge identical 5057 // instructions. TODO: We can further optimize this scan if we split the 5058 // instructions into different buckets based on the insert lane. 5059 SmallVector<Instruction *, 16> Visited; 5060 for (auto I = CSEWorkList.begin(), E = CSEWorkList.end(); I != E; ++I) { 5061 assert(*I && 5062 (I == CSEWorkList.begin() || !DT->dominates(*I, *std::prev(I))) && 5063 "Worklist not sorted properly!"); 5064 BasicBlock *BB = (*I)->getBlock(); 5065 // For all instructions in blocks containing gather sequences: 5066 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e;) { 5067 Instruction *In = &*it++; 5068 if (isDeleted(In)) 5069 continue; 5070 if (!isa<InsertElementInst>(In) && !isa<ExtractElementInst>(In)) 5071 continue; 5072 5073 // Check if we can replace this instruction with any of the 5074 // visited instructions. 5075 for (Instruction *v : Visited) { 5076 if (In->isIdenticalTo(v) && 5077 DT->dominates(v->getParent(), In->getParent())) { 5078 In->replaceAllUsesWith(v); 5079 eraseInstruction(In); 5080 In = nullptr; 5081 break; 5082 } 5083 } 5084 if (In) { 5085 assert(!is_contained(Visited, In)); 5086 Visited.push_back(In); 5087 } 5088 } 5089 } 5090 CSEBlocks.clear(); 5091 GatherSeq.clear(); 5092 } 5093 5094 // Groups the instructions to a bundle (which is then a single scheduling entity) 5095 // and schedules instructions until the bundle gets ready. 5096 Optional<BoUpSLP::ScheduleData *> 5097 BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 5098 const InstructionsState &S) { 5099 if (isa<PHINode>(S.OpValue)) 5100 return nullptr; 5101 5102 // Initialize the instruction bundle. 5103 Instruction *OldScheduleEnd = ScheduleEnd; 5104 ScheduleData *PrevInBundle = nullptr; 5105 ScheduleData *Bundle = nullptr; 5106 bool ReSchedule = false; 5107 LLVM_DEBUG(dbgs() << "SLP: bundle: " << *S.OpValue << "\n"); 5108 5109 // Make sure that the scheduling region contains all 5110 // instructions of the bundle. 5111 for (Value *V : VL) { 5112 if (!extendSchedulingRegion(V, S)) 5113 return None; 5114 } 5115 5116 for (Value *V : VL) { 5117 ScheduleData *BundleMember = getScheduleData(V); 5118 assert(BundleMember && 5119 "no ScheduleData for bundle member (maybe not in same basic block)"); 5120 if (BundleMember->IsScheduled) { 5121 // A bundle member was scheduled as single instruction before and now 5122 // needs to be scheduled as part of the bundle. We just get rid of the 5123 // existing schedule. 5124 LLVM_DEBUG(dbgs() << "SLP: reset schedule because " << *BundleMember 5125 << " was already scheduled\n"); 5126 ReSchedule = true; 5127 } 5128 assert(BundleMember->isSchedulingEntity() && 5129 "bundle member already part of other bundle"); 5130 if (PrevInBundle) { 5131 PrevInBundle->NextInBundle = BundleMember; 5132 } else { 5133 Bundle = BundleMember; 5134 } 5135 BundleMember->UnscheduledDepsInBundle = 0; 5136 Bundle->UnscheduledDepsInBundle += BundleMember->UnscheduledDeps; 5137 5138 // Group the instructions to a bundle. 5139 BundleMember->FirstInBundle = Bundle; 5140 PrevInBundle = BundleMember; 5141 } 5142 if (ScheduleEnd != OldScheduleEnd) { 5143 // The scheduling region got new instructions at the lower end (or it is a 5144 // new region for the first bundle). This makes it necessary to 5145 // recalculate all dependencies. 5146 // It is seldom that this needs to be done a second time after adding the 5147 // initial bundle to the region. 5148 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 5149 doForAllOpcodes(I, [](ScheduleData *SD) { 5150 SD->clearDependencies(); 5151 }); 5152 } 5153 ReSchedule = true; 5154 } 5155 if (ReSchedule) { 5156 resetSchedule(); 5157 initialFillReadyList(ReadyInsts); 5158 } 5159 assert(Bundle && "Failed to find schedule bundle"); 5160 5161 LLVM_DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle << " in block " 5162 << BB->getName() << "\n"); 5163 5164 calculateDependencies(Bundle, true, SLP); 5165 5166 // Now try to schedule the new bundle. As soon as the bundle is "ready" it 5167 // means that there are no cyclic dependencies and we can schedule it. 5168 // Note that's important that we don't "schedule" the bundle yet (see 5169 // cancelScheduling). 5170 while (!Bundle->isReady() && !ReadyInsts.empty()) { 5171 5172 ScheduleData *pickedSD = ReadyInsts.pop_back_val(); 5173 5174 if (pickedSD->isSchedulingEntity() && pickedSD->isReady()) { 5175 schedule(pickedSD, ReadyInsts); 5176 } 5177 } 5178 if (!Bundle->isReady()) { 5179 cancelScheduling(VL, S.OpValue); 5180 return None; 5181 } 5182 return Bundle; 5183 } 5184 5185 void BoUpSLP::BlockScheduling::cancelScheduling(ArrayRef<Value *> VL, 5186 Value *OpValue) { 5187 if (isa<PHINode>(OpValue)) 5188 return; 5189 5190 ScheduleData *Bundle = getScheduleData(OpValue); 5191 LLVM_DEBUG(dbgs() << "SLP: cancel scheduling of " << *Bundle << "\n"); 5192 assert(!Bundle->IsScheduled && 5193 "Can't cancel bundle which is already scheduled"); 5194 assert(Bundle->isSchedulingEntity() && Bundle->isPartOfBundle() && 5195 "tried to unbundle something which is not a bundle"); 5196 5197 // Un-bundle: make single instructions out of the bundle. 5198 ScheduleData *BundleMember = Bundle; 5199 while (BundleMember) { 5200 assert(BundleMember->FirstInBundle == Bundle && "corrupt bundle links"); 5201 BundleMember->FirstInBundle = BundleMember; 5202 ScheduleData *Next = BundleMember->NextInBundle; 5203 BundleMember->NextInBundle = nullptr; 5204 BundleMember->UnscheduledDepsInBundle = BundleMember->UnscheduledDeps; 5205 if (BundleMember->UnscheduledDepsInBundle == 0) { 5206 ReadyInsts.insert(BundleMember); 5207 } 5208 BundleMember = Next; 5209 } 5210 } 5211 5212 BoUpSLP::ScheduleData *BoUpSLP::BlockScheduling::allocateScheduleDataChunks() { 5213 // Allocate a new ScheduleData for the instruction. 5214 if (ChunkPos >= ChunkSize) { 5215 ScheduleDataChunks.push_back(std::make_unique<ScheduleData[]>(ChunkSize)); 5216 ChunkPos = 0; 5217 } 5218 return &(ScheduleDataChunks.back()[ChunkPos++]); 5219 } 5220 5221 bool BoUpSLP::BlockScheduling::extendSchedulingRegion(Value *V, 5222 const InstructionsState &S) { 5223 if (getScheduleData(V, isOneOf(S, V))) 5224 return true; 5225 Instruction *I = dyn_cast<Instruction>(V); 5226 assert(I && "bundle member must be an instruction"); 5227 assert(!isa<PHINode>(I) && "phi nodes don't need to be scheduled"); 5228 auto &&CheckSheduleForI = [this, &S](Instruction *I) -> bool { 5229 ScheduleData *ISD = getScheduleData(I); 5230 if (!ISD) 5231 return false; 5232 assert(isInSchedulingRegion(ISD) && 5233 "ScheduleData not in scheduling region"); 5234 ScheduleData *SD = allocateScheduleDataChunks(); 5235 SD->Inst = I; 5236 SD->init(SchedulingRegionID, S.OpValue); 5237 ExtraScheduleDataMap[I][S.OpValue] = SD; 5238 return true; 5239 }; 5240 if (CheckSheduleForI(I)) 5241 return true; 5242 if (!ScheduleStart) { 5243 // It's the first instruction in the new region. 5244 initScheduleData(I, I->getNextNode(), nullptr, nullptr); 5245 ScheduleStart = I; 5246 ScheduleEnd = I->getNextNode(); 5247 if (isOneOf(S, I) != I) 5248 CheckSheduleForI(I); 5249 assert(ScheduleEnd && "tried to vectorize a terminator?"); 5250 LLVM_DEBUG(dbgs() << "SLP: initialize schedule region to " << *I << "\n"); 5251 return true; 5252 } 5253 // Search up and down at the same time, because we don't know if the new 5254 // instruction is above or below the existing scheduling region. 5255 BasicBlock::reverse_iterator UpIter = 5256 ++ScheduleStart->getIterator().getReverse(); 5257 BasicBlock::reverse_iterator UpperEnd = BB->rend(); 5258 BasicBlock::iterator DownIter = ScheduleEnd->getIterator(); 5259 BasicBlock::iterator LowerEnd = BB->end(); 5260 while (true) { 5261 if (++ScheduleRegionSize > ScheduleRegionSizeLimit) { 5262 LLVM_DEBUG(dbgs() << "SLP: exceeded schedule region size limit\n"); 5263 return false; 5264 } 5265 5266 if (UpIter != UpperEnd) { 5267 if (&*UpIter == I) { 5268 initScheduleData(I, ScheduleStart, nullptr, FirstLoadStoreInRegion); 5269 ScheduleStart = I; 5270 if (isOneOf(S, I) != I) 5271 CheckSheduleForI(I); 5272 LLVM_DEBUG(dbgs() << "SLP: extend schedule region start to " << *I 5273 << "\n"); 5274 return true; 5275 } 5276 ++UpIter; 5277 } 5278 if (DownIter != LowerEnd) { 5279 if (&*DownIter == I) { 5280 initScheduleData(ScheduleEnd, I->getNextNode(), LastLoadStoreInRegion, 5281 nullptr); 5282 ScheduleEnd = I->getNextNode(); 5283 if (isOneOf(S, I) != I) 5284 CheckSheduleForI(I); 5285 assert(ScheduleEnd && "tried to vectorize a terminator?"); 5286 LLVM_DEBUG(dbgs() << "SLP: extend schedule region end to " << *I 5287 << "\n"); 5288 return true; 5289 } 5290 ++DownIter; 5291 } 5292 assert((UpIter != UpperEnd || DownIter != LowerEnd) && 5293 "instruction not found in block"); 5294 } 5295 return true; 5296 } 5297 5298 void BoUpSLP::BlockScheduling::initScheduleData(Instruction *FromI, 5299 Instruction *ToI, 5300 ScheduleData *PrevLoadStore, 5301 ScheduleData *NextLoadStore) { 5302 ScheduleData *CurrentLoadStore = PrevLoadStore; 5303 for (Instruction *I = FromI; I != ToI; I = I->getNextNode()) { 5304 ScheduleData *SD = ScheduleDataMap[I]; 5305 if (!SD) { 5306 SD = allocateScheduleDataChunks(); 5307 ScheduleDataMap[I] = SD; 5308 SD->Inst = I; 5309 } 5310 assert(!isInSchedulingRegion(SD) && 5311 "new ScheduleData already in scheduling region"); 5312 SD->init(SchedulingRegionID, I); 5313 5314 if (I->mayReadOrWriteMemory() && 5315 (!isa<IntrinsicInst>(I) || 5316 (cast<IntrinsicInst>(I)->getIntrinsicID() != Intrinsic::sideeffect && 5317 cast<IntrinsicInst>(I)->getIntrinsicID() != 5318 Intrinsic::pseudoprobe))) { 5319 // Update the linked list of memory accessing instructions. 5320 if (CurrentLoadStore) { 5321 CurrentLoadStore->NextLoadStore = SD; 5322 } else { 5323 FirstLoadStoreInRegion = SD; 5324 } 5325 CurrentLoadStore = SD; 5326 } 5327 } 5328 if (NextLoadStore) { 5329 if (CurrentLoadStore) 5330 CurrentLoadStore->NextLoadStore = NextLoadStore; 5331 } else { 5332 LastLoadStoreInRegion = CurrentLoadStore; 5333 } 5334 } 5335 5336 void BoUpSLP::BlockScheduling::calculateDependencies(ScheduleData *SD, 5337 bool InsertInReadyList, 5338 BoUpSLP *SLP) { 5339 assert(SD->isSchedulingEntity()); 5340 5341 SmallVector<ScheduleData *, 10> WorkList; 5342 WorkList.push_back(SD); 5343 5344 while (!WorkList.empty()) { 5345 ScheduleData *SD = WorkList.pop_back_val(); 5346 5347 ScheduleData *BundleMember = SD; 5348 while (BundleMember) { 5349 assert(isInSchedulingRegion(BundleMember)); 5350 if (!BundleMember->hasValidDependencies()) { 5351 5352 LLVM_DEBUG(dbgs() << "SLP: update deps of " << *BundleMember 5353 << "\n"); 5354 BundleMember->Dependencies = 0; 5355 BundleMember->resetUnscheduledDeps(); 5356 5357 // Handle def-use chain dependencies. 5358 if (BundleMember->OpValue != BundleMember->Inst) { 5359 ScheduleData *UseSD = getScheduleData(BundleMember->Inst); 5360 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 5361 BundleMember->Dependencies++; 5362 ScheduleData *DestBundle = UseSD->FirstInBundle; 5363 if (!DestBundle->IsScheduled) 5364 BundleMember->incrementUnscheduledDeps(1); 5365 if (!DestBundle->hasValidDependencies()) 5366 WorkList.push_back(DestBundle); 5367 } 5368 } else { 5369 for (User *U : BundleMember->Inst->users()) { 5370 if (isa<Instruction>(U)) { 5371 ScheduleData *UseSD = getScheduleData(U); 5372 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 5373 BundleMember->Dependencies++; 5374 ScheduleData *DestBundle = UseSD->FirstInBundle; 5375 if (!DestBundle->IsScheduled) 5376 BundleMember->incrementUnscheduledDeps(1); 5377 if (!DestBundle->hasValidDependencies()) 5378 WorkList.push_back(DestBundle); 5379 } 5380 } else { 5381 // I'm not sure if this can ever happen. But we need to be safe. 5382 // This lets the instruction/bundle never be scheduled and 5383 // eventually disable vectorization. 5384 BundleMember->Dependencies++; 5385 BundleMember->incrementUnscheduledDeps(1); 5386 } 5387 } 5388 } 5389 5390 // Handle the memory dependencies. 5391 ScheduleData *DepDest = BundleMember->NextLoadStore; 5392 if (DepDest) { 5393 Instruction *SrcInst = BundleMember->Inst; 5394 MemoryLocation SrcLoc = getLocation(SrcInst, SLP->AA); 5395 bool SrcMayWrite = BundleMember->Inst->mayWriteToMemory(); 5396 unsigned numAliased = 0; 5397 unsigned DistToSrc = 1; 5398 5399 while (DepDest) { 5400 assert(isInSchedulingRegion(DepDest)); 5401 5402 // We have two limits to reduce the complexity: 5403 // 1) AliasedCheckLimit: It's a small limit to reduce calls to 5404 // SLP->isAliased (which is the expensive part in this loop). 5405 // 2) MaxMemDepDistance: It's for very large blocks and it aborts 5406 // the whole loop (even if the loop is fast, it's quadratic). 5407 // It's important for the loop break condition (see below) to 5408 // check this limit even between two read-only instructions. 5409 if (DistToSrc >= MaxMemDepDistance || 5410 ((SrcMayWrite || DepDest->Inst->mayWriteToMemory()) && 5411 (numAliased >= AliasedCheckLimit || 5412 SLP->isAliased(SrcLoc, SrcInst, DepDest->Inst)))) { 5413 5414 // We increment the counter only if the locations are aliased 5415 // (instead of counting all alias checks). This gives a better 5416 // balance between reduced runtime and accurate dependencies. 5417 numAliased++; 5418 5419 DepDest->MemoryDependencies.push_back(BundleMember); 5420 BundleMember->Dependencies++; 5421 ScheduleData *DestBundle = DepDest->FirstInBundle; 5422 if (!DestBundle->IsScheduled) { 5423 BundleMember->incrementUnscheduledDeps(1); 5424 } 5425 if (!DestBundle->hasValidDependencies()) { 5426 WorkList.push_back(DestBundle); 5427 } 5428 } 5429 DepDest = DepDest->NextLoadStore; 5430 5431 // Example, explaining the loop break condition: Let's assume our 5432 // starting instruction is i0 and MaxMemDepDistance = 3. 5433 // 5434 // +--------v--v--v 5435 // i0,i1,i2,i3,i4,i5,i6,i7,i8 5436 // +--------^--^--^ 5437 // 5438 // MaxMemDepDistance let us stop alias-checking at i3 and we add 5439 // dependencies from i0 to i3,i4,.. (even if they are not aliased). 5440 // Previously we already added dependencies from i3 to i6,i7,i8 5441 // (because of MaxMemDepDistance). As we added a dependency from 5442 // i0 to i3, we have transitive dependencies from i0 to i6,i7,i8 5443 // and we can abort this loop at i6. 5444 if (DistToSrc >= 2 * MaxMemDepDistance) 5445 break; 5446 DistToSrc++; 5447 } 5448 } 5449 } 5450 BundleMember = BundleMember->NextInBundle; 5451 } 5452 if (InsertInReadyList && SD->isReady()) { 5453 ReadyInsts.push_back(SD); 5454 LLVM_DEBUG(dbgs() << "SLP: gets ready on update: " << *SD->Inst 5455 << "\n"); 5456 } 5457 } 5458 } 5459 5460 void BoUpSLP::BlockScheduling::resetSchedule() { 5461 assert(ScheduleStart && 5462 "tried to reset schedule on block which has not been scheduled"); 5463 for (Instruction *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 5464 doForAllOpcodes(I, [&](ScheduleData *SD) { 5465 assert(isInSchedulingRegion(SD) && 5466 "ScheduleData not in scheduling region"); 5467 SD->IsScheduled = false; 5468 SD->resetUnscheduledDeps(); 5469 }); 5470 } 5471 ReadyInsts.clear(); 5472 } 5473 5474 void BoUpSLP::scheduleBlock(BlockScheduling *BS) { 5475 if (!BS->ScheduleStart) 5476 return; 5477 5478 LLVM_DEBUG(dbgs() << "SLP: schedule block " << BS->BB->getName() << "\n"); 5479 5480 BS->resetSchedule(); 5481 5482 // For the real scheduling we use a more sophisticated ready-list: it is 5483 // sorted by the original instruction location. This lets the final schedule 5484 // be as close as possible to the original instruction order. 5485 struct ScheduleDataCompare { 5486 bool operator()(ScheduleData *SD1, ScheduleData *SD2) const { 5487 return SD2->SchedulingPriority < SD1->SchedulingPriority; 5488 } 5489 }; 5490 std::set<ScheduleData *, ScheduleDataCompare> ReadyInsts; 5491 5492 // Ensure that all dependency data is updated and fill the ready-list with 5493 // initial instructions. 5494 int Idx = 0; 5495 int NumToSchedule = 0; 5496 for (auto *I = BS->ScheduleStart; I != BS->ScheduleEnd; 5497 I = I->getNextNode()) { 5498 BS->doForAllOpcodes(I, [this, &Idx, &NumToSchedule, BS](ScheduleData *SD) { 5499 assert(SD->isPartOfBundle() == 5500 (getTreeEntry(SD->Inst) != nullptr) && 5501 "scheduler and vectorizer bundle mismatch"); 5502 SD->FirstInBundle->SchedulingPriority = Idx++; 5503 if (SD->isSchedulingEntity()) { 5504 BS->calculateDependencies(SD, false, this); 5505 NumToSchedule++; 5506 } 5507 }); 5508 } 5509 BS->initialFillReadyList(ReadyInsts); 5510 5511 Instruction *LastScheduledInst = BS->ScheduleEnd; 5512 5513 // Do the "real" scheduling. 5514 while (!ReadyInsts.empty()) { 5515 ScheduleData *picked = *ReadyInsts.begin(); 5516 ReadyInsts.erase(ReadyInsts.begin()); 5517 5518 // Move the scheduled instruction(s) to their dedicated places, if not 5519 // there yet. 5520 ScheduleData *BundleMember = picked; 5521 while (BundleMember) { 5522 Instruction *pickedInst = BundleMember->Inst; 5523 if (LastScheduledInst->getNextNode() != pickedInst) { 5524 BS->BB->getInstList().remove(pickedInst); 5525 BS->BB->getInstList().insert(LastScheduledInst->getIterator(), 5526 pickedInst); 5527 } 5528 LastScheduledInst = pickedInst; 5529 BundleMember = BundleMember->NextInBundle; 5530 } 5531 5532 BS->schedule(picked, ReadyInsts); 5533 NumToSchedule--; 5534 } 5535 assert(NumToSchedule == 0 && "could not schedule all instructions"); 5536 5537 // Avoid duplicate scheduling of the block. 5538 BS->ScheduleStart = nullptr; 5539 } 5540 5541 unsigned BoUpSLP::getVectorElementSize(Value *V) { 5542 // If V is a store, just return the width of the stored value (or value 5543 // truncated just before storing) without traversing the expression tree. 5544 // This is the common case. 5545 if (auto *Store = dyn_cast<StoreInst>(V)) { 5546 if (auto *Trunc = dyn_cast<TruncInst>(Store->getValueOperand())) 5547 return DL->getTypeSizeInBits(Trunc->getSrcTy()); 5548 else 5549 return DL->getTypeSizeInBits(Store->getValueOperand()->getType()); 5550 } 5551 5552 auto E = InstrElementSize.find(V); 5553 if (E != InstrElementSize.end()) 5554 return E->second; 5555 5556 // If V is not a store, we can traverse the expression tree to find loads 5557 // that feed it. The type of the loaded value may indicate a more suitable 5558 // width than V's type. We want to base the vector element size on the width 5559 // of memory operations where possible. 5560 SmallVector<Instruction *, 16> Worklist; 5561 SmallPtrSet<Instruction *, 16> Visited; 5562 if (auto *I = dyn_cast<Instruction>(V)) { 5563 Worklist.push_back(I); 5564 Visited.insert(I); 5565 } 5566 5567 // Traverse the expression tree in bottom-up order looking for loads. If we 5568 // encounter an instruction we don't yet handle, we give up. 5569 auto MaxWidth = 0u; 5570 auto FoundUnknownInst = false; 5571 while (!Worklist.empty() && !FoundUnknownInst) { 5572 auto *I = Worklist.pop_back_val(); 5573 5574 // We should only be looking at scalar instructions here. If the current 5575 // instruction has a vector type, give up. 5576 auto *Ty = I->getType(); 5577 if (isa<VectorType>(Ty)) 5578 FoundUnknownInst = true; 5579 5580 // If the current instruction is a load, update MaxWidth to reflect the 5581 // width of the loaded value. 5582 else if (isa<LoadInst>(I)) 5583 MaxWidth = std::max<unsigned>(MaxWidth, DL->getTypeSizeInBits(Ty)); 5584 5585 // Otherwise, we need to visit the operands of the instruction. We only 5586 // handle the interesting cases from buildTree here. If an operand is an 5587 // instruction we haven't yet visited, we add it to the worklist. 5588 else if (isa<PHINode>(I) || isa<CastInst>(I) || isa<GetElementPtrInst>(I) || 5589 isa<CmpInst>(I) || isa<SelectInst>(I) || isa<BinaryOperator>(I)) { 5590 for (Use &U : I->operands()) 5591 if (auto *J = dyn_cast<Instruction>(U.get())) 5592 if (Visited.insert(J).second) 5593 Worklist.push_back(J); 5594 } 5595 5596 // If we don't yet handle the instruction, give up. 5597 else 5598 FoundUnknownInst = true; 5599 } 5600 5601 int Width = MaxWidth; 5602 // If we didn't encounter a memory access in the expression tree, or if we 5603 // gave up for some reason, just return the width of V. Otherwise, return the 5604 // maximum width we found. 5605 if (!MaxWidth || FoundUnknownInst) 5606 Width = DL->getTypeSizeInBits(V->getType()); 5607 5608 for (Instruction *I : Visited) 5609 InstrElementSize[I] = Width; 5610 5611 return Width; 5612 } 5613 5614 // Determine if a value V in a vectorizable expression Expr can be demoted to a 5615 // smaller type with a truncation. We collect the values that will be demoted 5616 // in ToDemote and additional roots that require investigating in Roots. 5617 static bool collectValuesToDemote(Value *V, SmallPtrSetImpl<Value *> &Expr, 5618 SmallVectorImpl<Value *> &ToDemote, 5619 SmallVectorImpl<Value *> &Roots) { 5620 // We can always demote constants. 5621 if (isa<Constant>(V)) { 5622 ToDemote.push_back(V); 5623 return true; 5624 } 5625 5626 // If the value is not an instruction in the expression with only one use, it 5627 // cannot be demoted. 5628 auto *I = dyn_cast<Instruction>(V); 5629 if (!I || !I->hasOneUse() || !Expr.count(I)) 5630 return false; 5631 5632 switch (I->getOpcode()) { 5633 5634 // We can always demote truncations and extensions. Since truncations can 5635 // seed additional demotion, we save the truncated value. 5636 case Instruction::Trunc: 5637 Roots.push_back(I->getOperand(0)); 5638 break; 5639 case Instruction::ZExt: 5640 case Instruction::SExt: 5641 break; 5642 5643 // We can demote certain binary operations if we can demote both of their 5644 // operands. 5645 case Instruction::Add: 5646 case Instruction::Sub: 5647 case Instruction::Mul: 5648 case Instruction::And: 5649 case Instruction::Or: 5650 case Instruction::Xor: 5651 if (!collectValuesToDemote(I->getOperand(0), Expr, ToDemote, Roots) || 5652 !collectValuesToDemote(I->getOperand(1), Expr, ToDemote, Roots)) 5653 return false; 5654 break; 5655 5656 // We can demote selects if we can demote their true and false values. 5657 case Instruction::Select: { 5658 SelectInst *SI = cast<SelectInst>(I); 5659 if (!collectValuesToDemote(SI->getTrueValue(), Expr, ToDemote, Roots) || 5660 !collectValuesToDemote(SI->getFalseValue(), Expr, ToDemote, Roots)) 5661 return false; 5662 break; 5663 } 5664 5665 // We can demote phis if we can demote all their incoming operands. Note that 5666 // we don't need to worry about cycles since we ensure single use above. 5667 case Instruction::PHI: { 5668 PHINode *PN = cast<PHINode>(I); 5669 for (Value *IncValue : PN->incoming_values()) 5670 if (!collectValuesToDemote(IncValue, Expr, ToDemote, Roots)) 5671 return false; 5672 break; 5673 } 5674 5675 // Otherwise, conservatively give up. 5676 default: 5677 return false; 5678 } 5679 5680 // Record the value that we can demote. 5681 ToDemote.push_back(V); 5682 return true; 5683 } 5684 5685 void BoUpSLP::computeMinimumValueSizes() { 5686 // If there are no external uses, the expression tree must be rooted by a 5687 // store. We can't demote in-memory values, so there is nothing to do here. 5688 if (ExternalUses.empty()) 5689 return; 5690 5691 // We only attempt to truncate integer expressions. 5692 auto &TreeRoot = VectorizableTree[0]->Scalars; 5693 auto *TreeRootIT = dyn_cast<IntegerType>(TreeRoot[0]->getType()); 5694 if (!TreeRootIT) 5695 return; 5696 5697 // If the expression is not rooted by a store, these roots should have 5698 // external uses. We will rely on InstCombine to rewrite the expression in 5699 // the narrower type. However, InstCombine only rewrites single-use values. 5700 // This means that if a tree entry other than a root is used externally, it 5701 // must have multiple uses and InstCombine will not rewrite it. The code 5702 // below ensures that only the roots are used externally. 5703 SmallPtrSet<Value *, 32> Expr(TreeRoot.begin(), TreeRoot.end()); 5704 for (auto &EU : ExternalUses) 5705 if (!Expr.erase(EU.Scalar)) 5706 return; 5707 if (!Expr.empty()) 5708 return; 5709 5710 // Collect the scalar values of the vectorizable expression. We will use this 5711 // context to determine which values can be demoted. If we see a truncation, 5712 // we mark it as seeding another demotion. 5713 for (auto &EntryPtr : VectorizableTree) 5714 Expr.insert(EntryPtr->Scalars.begin(), EntryPtr->Scalars.end()); 5715 5716 // Ensure the roots of the vectorizable tree don't form a cycle. They must 5717 // have a single external user that is not in the vectorizable tree. 5718 for (auto *Root : TreeRoot) 5719 if (!Root->hasOneUse() || Expr.count(*Root->user_begin())) 5720 return; 5721 5722 // Conservatively determine if we can actually truncate the roots of the 5723 // expression. Collect the values that can be demoted in ToDemote and 5724 // additional roots that require investigating in Roots. 5725 SmallVector<Value *, 32> ToDemote; 5726 SmallVector<Value *, 4> Roots; 5727 for (auto *Root : TreeRoot) 5728 if (!collectValuesToDemote(Root, Expr, ToDemote, Roots)) 5729 return; 5730 5731 // The maximum bit width required to represent all the values that can be 5732 // demoted without loss of precision. It would be safe to truncate the roots 5733 // of the expression to this width. 5734 auto MaxBitWidth = 8u; 5735 5736 // We first check if all the bits of the roots are demanded. If they're not, 5737 // we can truncate the roots to this narrower type. 5738 for (auto *Root : TreeRoot) { 5739 auto Mask = DB->getDemandedBits(cast<Instruction>(Root)); 5740 MaxBitWidth = std::max<unsigned>( 5741 Mask.getBitWidth() - Mask.countLeadingZeros(), MaxBitWidth); 5742 } 5743 5744 // True if the roots can be zero-extended back to their original type, rather 5745 // than sign-extended. We know that if the leading bits are not demanded, we 5746 // can safely zero-extend. So we initialize IsKnownPositive to True. 5747 bool IsKnownPositive = true; 5748 5749 // If all the bits of the roots are demanded, we can try a little harder to 5750 // compute a narrower type. This can happen, for example, if the roots are 5751 // getelementptr indices. InstCombine promotes these indices to the pointer 5752 // width. Thus, all their bits are technically demanded even though the 5753 // address computation might be vectorized in a smaller type. 5754 // 5755 // We start by looking at each entry that can be demoted. We compute the 5756 // maximum bit width required to store the scalar by using ValueTracking to 5757 // compute the number of high-order bits we can truncate. 5758 if (MaxBitWidth == DL->getTypeSizeInBits(TreeRoot[0]->getType()) && 5759 llvm::all_of(TreeRoot, [](Value *R) { 5760 assert(R->hasOneUse() && "Root should have only one use!"); 5761 return isa<GetElementPtrInst>(R->user_back()); 5762 })) { 5763 MaxBitWidth = 8u; 5764 5765 // Determine if the sign bit of all the roots is known to be zero. If not, 5766 // IsKnownPositive is set to False. 5767 IsKnownPositive = llvm::all_of(TreeRoot, [&](Value *R) { 5768 KnownBits Known = computeKnownBits(R, *DL); 5769 return Known.isNonNegative(); 5770 }); 5771 5772 // Determine the maximum number of bits required to store the scalar 5773 // values. 5774 for (auto *Scalar : ToDemote) { 5775 auto NumSignBits = ComputeNumSignBits(Scalar, *DL, 0, AC, nullptr, DT); 5776 auto NumTypeBits = DL->getTypeSizeInBits(Scalar->getType()); 5777 MaxBitWidth = std::max<unsigned>(NumTypeBits - NumSignBits, MaxBitWidth); 5778 } 5779 5780 // If we can't prove that the sign bit is zero, we must add one to the 5781 // maximum bit width to account for the unknown sign bit. This preserves 5782 // the existing sign bit so we can safely sign-extend the root back to the 5783 // original type. Otherwise, if we know the sign bit is zero, we will 5784 // zero-extend the root instead. 5785 // 5786 // FIXME: This is somewhat suboptimal, as there will be cases where adding 5787 // one to the maximum bit width will yield a larger-than-necessary 5788 // type. In general, we need to add an extra bit only if we can't 5789 // prove that the upper bit of the original type is equal to the 5790 // upper bit of the proposed smaller type. If these two bits are the 5791 // same (either zero or one) we know that sign-extending from the 5792 // smaller type will result in the same value. Here, since we can't 5793 // yet prove this, we are just making the proposed smaller type 5794 // larger to ensure correctness. 5795 if (!IsKnownPositive) 5796 ++MaxBitWidth; 5797 } 5798 5799 // Round MaxBitWidth up to the next power-of-two. 5800 if (!isPowerOf2_64(MaxBitWidth)) 5801 MaxBitWidth = NextPowerOf2(MaxBitWidth); 5802 5803 // If the maximum bit width we compute is less than the with of the roots' 5804 // type, we can proceed with the narrowing. Otherwise, do nothing. 5805 if (MaxBitWidth >= TreeRootIT->getBitWidth()) 5806 return; 5807 5808 // If we can truncate the root, we must collect additional values that might 5809 // be demoted as a result. That is, those seeded by truncations we will 5810 // modify. 5811 while (!Roots.empty()) 5812 collectValuesToDemote(Roots.pop_back_val(), Expr, ToDemote, Roots); 5813 5814 // Finally, map the values we can demote to the maximum bit with we computed. 5815 for (auto *Scalar : ToDemote) 5816 MinBWs[Scalar] = std::make_pair(MaxBitWidth, !IsKnownPositive); 5817 } 5818 5819 namespace { 5820 5821 /// The SLPVectorizer Pass. 5822 struct SLPVectorizer : public FunctionPass { 5823 SLPVectorizerPass Impl; 5824 5825 /// Pass identification, replacement for typeid 5826 static char ID; 5827 5828 explicit SLPVectorizer() : FunctionPass(ID) { 5829 initializeSLPVectorizerPass(*PassRegistry::getPassRegistry()); 5830 } 5831 5832 bool doInitialization(Module &M) override { 5833 return false; 5834 } 5835 5836 bool runOnFunction(Function &F) override { 5837 if (skipFunction(F)) 5838 return false; 5839 5840 auto *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 5841 auto *TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F); 5842 auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>(); 5843 auto *TLI = TLIP ? &TLIP->getTLI(F) : nullptr; 5844 auto *AA = &getAnalysis<AAResultsWrapperPass>().getAAResults(); 5845 auto *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 5846 auto *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 5847 auto *AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F); 5848 auto *DB = &getAnalysis<DemandedBitsWrapperPass>().getDemandedBits(); 5849 auto *ORE = &getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE(); 5850 5851 return Impl.runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 5852 } 5853 5854 void getAnalysisUsage(AnalysisUsage &AU) const override { 5855 FunctionPass::getAnalysisUsage(AU); 5856 AU.addRequired<AssumptionCacheTracker>(); 5857 AU.addRequired<ScalarEvolutionWrapperPass>(); 5858 AU.addRequired<AAResultsWrapperPass>(); 5859 AU.addRequired<TargetTransformInfoWrapperPass>(); 5860 AU.addRequired<LoopInfoWrapperPass>(); 5861 AU.addRequired<DominatorTreeWrapperPass>(); 5862 AU.addRequired<DemandedBitsWrapperPass>(); 5863 AU.addRequired<OptimizationRemarkEmitterWrapperPass>(); 5864 AU.addRequired<InjectTLIMappingsLegacy>(); 5865 AU.addPreserved<LoopInfoWrapperPass>(); 5866 AU.addPreserved<DominatorTreeWrapperPass>(); 5867 AU.addPreserved<AAResultsWrapperPass>(); 5868 AU.addPreserved<GlobalsAAWrapperPass>(); 5869 AU.setPreservesCFG(); 5870 } 5871 }; 5872 5873 } // end anonymous namespace 5874 5875 PreservedAnalyses SLPVectorizerPass::run(Function &F, FunctionAnalysisManager &AM) { 5876 auto *SE = &AM.getResult<ScalarEvolutionAnalysis>(F); 5877 auto *TTI = &AM.getResult<TargetIRAnalysis>(F); 5878 auto *TLI = AM.getCachedResult<TargetLibraryAnalysis>(F); 5879 auto *AA = &AM.getResult<AAManager>(F); 5880 auto *LI = &AM.getResult<LoopAnalysis>(F); 5881 auto *DT = &AM.getResult<DominatorTreeAnalysis>(F); 5882 auto *AC = &AM.getResult<AssumptionAnalysis>(F); 5883 auto *DB = &AM.getResult<DemandedBitsAnalysis>(F); 5884 auto *ORE = &AM.getResult<OptimizationRemarkEmitterAnalysis>(F); 5885 5886 bool Changed = runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 5887 if (!Changed) 5888 return PreservedAnalyses::all(); 5889 5890 PreservedAnalyses PA; 5891 PA.preserveSet<CFGAnalyses>(); 5892 PA.preserve<AAManager>(); 5893 PA.preserve<GlobalsAA>(); 5894 return PA; 5895 } 5896 5897 bool SLPVectorizerPass::runImpl(Function &F, ScalarEvolution *SE_, 5898 TargetTransformInfo *TTI_, 5899 TargetLibraryInfo *TLI_, AAResults *AA_, 5900 LoopInfo *LI_, DominatorTree *DT_, 5901 AssumptionCache *AC_, DemandedBits *DB_, 5902 OptimizationRemarkEmitter *ORE_) { 5903 if (!RunSLPVectorization) 5904 return false; 5905 SE = SE_; 5906 TTI = TTI_; 5907 TLI = TLI_; 5908 AA = AA_; 5909 LI = LI_; 5910 DT = DT_; 5911 AC = AC_; 5912 DB = DB_; 5913 DL = &F.getParent()->getDataLayout(); 5914 5915 Stores.clear(); 5916 GEPs.clear(); 5917 bool Changed = false; 5918 5919 // If the target claims to have no vector registers don't attempt 5920 // vectorization. 5921 if (!TTI->getNumberOfRegisters(TTI->getRegisterClassForType(true))) 5922 return false; 5923 5924 // Don't vectorize when the attribute NoImplicitFloat is used. 5925 if (F.hasFnAttribute(Attribute::NoImplicitFloat)) 5926 return false; 5927 5928 LLVM_DEBUG(dbgs() << "SLP: Analyzing blocks in " << F.getName() << ".\n"); 5929 5930 // Use the bottom up slp vectorizer to construct chains that start with 5931 // store instructions. 5932 BoUpSLP R(&F, SE, TTI, TLI, AA, LI, DT, AC, DB, DL, ORE_); 5933 5934 // A general note: the vectorizer must use BoUpSLP::eraseInstruction() to 5935 // delete instructions. 5936 5937 // Scan the blocks in the function in post order. 5938 for (auto BB : post_order(&F.getEntryBlock())) { 5939 collectSeedInstructions(BB); 5940 5941 // Vectorize trees that end at stores. 5942 if (!Stores.empty()) { 5943 LLVM_DEBUG(dbgs() << "SLP: Found stores for " << Stores.size() 5944 << " underlying objects.\n"); 5945 Changed |= vectorizeStoreChains(R); 5946 } 5947 5948 // Vectorize trees that end at reductions. 5949 Changed |= vectorizeChainsInBlock(BB, R); 5950 5951 // Vectorize the index computations of getelementptr instructions. This 5952 // is primarily intended to catch gather-like idioms ending at 5953 // non-consecutive loads. 5954 if (!GEPs.empty()) { 5955 LLVM_DEBUG(dbgs() << "SLP: Found GEPs for " << GEPs.size() 5956 << " underlying objects.\n"); 5957 Changed |= vectorizeGEPIndices(BB, R); 5958 } 5959 } 5960 5961 if (Changed) { 5962 R.optimizeGatherSequence(); 5963 LLVM_DEBUG(dbgs() << "SLP: vectorized \"" << F.getName() << "\"\n"); 5964 } 5965 return Changed; 5966 } 5967 5968 bool SLPVectorizerPass::vectorizeStoreChain(ArrayRef<Value *> Chain, BoUpSLP &R, 5969 unsigned Idx) { 5970 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " << Chain.size() 5971 << "\n"); 5972 const unsigned Sz = R.getVectorElementSize(Chain[0]); 5973 const unsigned MinVF = R.getMinVecRegSize() / Sz; 5974 unsigned VF = Chain.size(); 5975 5976 if (!isPowerOf2_32(Sz) || !isPowerOf2_32(VF) || VF < 2 || VF < MinVF) 5977 return false; 5978 5979 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << VF << " stores at offset " << Idx 5980 << "\n"); 5981 5982 R.buildTree(Chain); 5983 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 5984 // TODO: Handle orders of size less than number of elements in the vector. 5985 if (Order && Order->size() == Chain.size()) { 5986 // TODO: reorder tree nodes without tree rebuilding. 5987 SmallVector<Value *, 4> ReorderedOps(Chain.rbegin(), Chain.rend()); 5988 llvm::transform(*Order, ReorderedOps.begin(), 5989 [Chain](const unsigned Idx) { return Chain[Idx]; }); 5990 R.buildTree(ReorderedOps); 5991 } 5992 if (R.isTreeTinyAndNotFullyVectorizable()) 5993 return false; 5994 if (R.isLoadCombineCandidate()) 5995 return false; 5996 5997 R.computeMinimumValueSizes(); 5998 5999 InstructionCost Cost = R.getTreeCost(); 6000 6001 LLVM_DEBUG(dbgs() << "SLP: Found cost = " << Cost << " for VF =" << VF << "\n"); 6002 if (Cost < -SLPCostThreshold) { 6003 LLVM_DEBUG(dbgs() << "SLP: Decided to vectorize cost = " << Cost << "\n"); 6004 6005 using namespace ore; 6006 6007 R.getORE()->emit(OptimizationRemark(SV_NAME, "StoresVectorized", 6008 cast<StoreInst>(Chain[0])) 6009 << "Stores SLP vectorized with cost " << NV("Cost", Cost) 6010 << " and with tree size " 6011 << NV("TreeSize", R.getTreeSize())); 6012 6013 R.vectorizeTree(); 6014 return true; 6015 } 6016 6017 return false; 6018 } 6019 6020 bool SLPVectorizerPass::vectorizeStores(ArrayRef<StoreInst *> Stores, 6021 BoUpSLP &R) { 6022 // We may run into multiple chains that merge into a single chain. We mark the 6023 // stores that we vectorized so that we don't visit the same store twice. 6024 BoUpSLP::ValueSet VectorizedStores; 6025 bool Changed = false; 6026 6027 int E = Stores.size(); 6028 SmallBitVector Tails(E, false); 6029 SmallVector<int, 16> ConsecutiveChain(E, E + 1); 6030 int MaxIter = MaxStoreLookup.getValue(); 6031 int IterCnt; 6032 auto &&FindConsecutiveAccess = [this, &Stores, &Tails, &IterCnt, MaxIter, 6033 &ConsecutiveChain](int K, int Idx) { 6034 if (IterCnt >= MaxIter) 6035 return true; 6036 ++IterCnt; 6037 if (!isConsecutiveAccess(Stores[K], Stores[Idx], *DL, *SE)) 6038 return false; 6039 6040 Tails.set(Idx); 6041 ConsecutiveChain[K] = Idx; 6042 return true; 6043 }; 6044 // Do a quadratic search on all of the given stores in reverse order and find 6045 // all of the pairs of stores that follow each other. 6046 for (int Idx = E - 1; Idx >= 0; --Idx) { 6047 // If a store has multiple consecutive store candidates, search according 6048 // to the sequence: Idx-1, Idx+1, Idx-2, Idx+2, ... 6049 // This is because usually pairing with immediate succeeding or preceding 6050 // candidate create the best chance to find slp vectorization opportunity. 6051 const int MaxLookDepth = std::max(E - Idx, Idx + 1); 6052 IterCnt = 0; 6053 for (int Offset = 1, F = MaxLookDepth; Offset < F; ++Offset) 6054 if ((Idx >= Offset && FindConsecutiveAccess(Idx - Offset, Idx)) || 6055 (Idx + Offset < E && FindConsecutiveAccess(Idx + Offset, Idx))) 6056 break; 6057 } 6058 6059 // For stores that start but don't end a link in the chain: 6060 for (int Cnt = E; Cnt > 0; --Cnt) { 6061 int I = Cnt - 1; 6062 if (ConsecutiveChain[I] == E + 1 || Tails.test(I)) 6063 continue; 6064 // We found a store instr that starts a chain. Now follow the chain and try 6065 // to vectorize it. 6066 BoUpSLP::ValueList Operands; 6067 // Collect the chain into a list. 6068 while (I != E + 1 && !VectorizedStores.count(Stores[I])) { 6069 Operands.push_back(Stores[I]); 6070 // Move to the next value in the chain. 6071 I = ConsecutiveChain[I]; 6072 } 6073 6074 // If a vector register can't hold 1 element, we are done. 6075 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 6076 unsigned EltSize = R.getVectorElementSize(Operands[0]); 6077 if (MaxVecRegSize % EltSize != 0) 6078 continue; 6079 6080 unsigned MaxElts = MaxVecRegSize / EltSize; 6081 // FIXME: Is division-by-2 the correct step? Should we assert that the 6082 // register size is a power-of-2? 6083 unsigned StartIdx = 0; 6084 for (unsigned Size = llvm::PowerOf2Ceil(MaxElts); Size >= 2; Size /= 2) { 6085 for (unsigned Cnt = StartIdx, E = Operands.size(); Cnt + Size <= E;) { 6086 ArrayRef<Value *> Slice = makeArrayRef(Operands).slice(Cnt, Size); 6087 if (!VectorizedStores.count(Slice.front()) && 6088 !VectorizedStores.count(Slice.back()) && 6089 vectorizeStoreChain(Slice, R, Cnt)) { 6090 // Mark the vectorized stores so that we don't vectorize them again. 6091 VectorizedStores.insert(Slice.begin(), Slice.end()); 6092 Changed = true; 6093 // If we vectorized initial block, no need to try to vectorize it 6094 // again. 6095 if (Cnt == StartIdx) 6096 StartIdx += Size; 6097 Cnt += Size; 6098 continue; 6099 } 6100 ++Cnt; 6101 } 6102 // Check if the whole array was vectorized already - exit. 6103 if (StartIdx >= Operands.size()) 6104 break; 6105 } 6106 } 6107 6108 return Changed; 6109 } 6110 6111 void SLPVectorizerPass::collectSeedInstructions(BasicBlock *BB) { 6112 // Initialize the collections. We will make a single pass over the block. 6113 Stores.clear(); 6114 GEPs.clear(); 6115 6116 // Visit the store and getelementptr instructions in BB and organize them in 6117 // Stores and GEPs according to the underlying objects of their pointer 6118 // operands. 6119 for (Instruction &I : *BB) { 6120 // Ignore store instructions that are volatile or have a pointer operand 6121 // that doesn't point to a scalar type. 6122 if (auto *SI = dyn_cast<StoreInst>(&I)) { 6123 if (!SI->isSimple()) 6124 continue; 6125 if (!isValidElementType(SI->getValueOperand()->getType())) 6126 continue; 6127 Stores[getUnderlyingObject(SI->getPointerOperand())].push_back(SI); 6128 } 6129 6130 // Ignore getelementptr instructions that have more than one index, a 6131 // constant index, or a pointer operand that doesn't point to a scalar 6132 // type. 6133 else if (auto *GEP = dyn_cast<GetElementPtrInst>(&I)) { 6134 auto Idx = GEP->idx_begin()->get(); 6135 if (GEP->getNumIndices() > 1 || isa<Constant>(Idx)) 6136 continue; 6137 if (!isValidElementType(Idx->getType())) 6138 continue; 6139 if (GEP->getType()->isVectorTy()) 6140 continue; 6141 GEPs[GEP->getPointerOperand()].push_back(GEP); 6142 } 6143 } 6144 } 6145 6146 bool SLPVectorizerPass::tryToVectorizePair(Value *A, Value *B, BoUpSLP &R) { 6147 if (!A || !B) 6148 return false; 6149 Value *VL[] = {A, B}; 6150 return tryToVectorizeList(VL, R, /*AllowReorder=*/true); 6151 } 6152 6153 bool SLPVectorizerPass::tryToVectorizeList(ArrayRef<Value *> VL, BoUpSLP &R, 6154 bool AllowReorder, 6155 ArrayRef<Value *> InsertUses) { 6156 if (VL.size() < 2) 6157 return false; 6158 6159 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize a list of length = " 6160 << VL.size() << ".\n"); 6161 6162 // Check that all of the parts are instructions of the same type, 6163 // we permit an alternate opcode via InstructionsState. 6164 InstructionsState S = getSameOpcode(VL); 6165 if (!S.getOpcode()) 6166 return false; 6167 6168 Instruction *I0 = cast<Instruction>(S.OpValue); 6169 // Make sure invalid types (including vector type) are rejected before 6170 // determining vectorization factor for scalar instructions. 6171 for (Value *V : VL) { 6172 Type *Ty = V->getType(); 6173 if (!isValidElementType(Ty)) { 6174 // NOTE: the following will give user internal llvm type name, which may 6175 // not be useful. 6176 R.getORE()->emit([&]() { 6177 std::string type_str; 6178 llvm::raw_string_ostream rso(type_str); 6179 Ty->print(rso); 6180 return OptimizationRemarkMissed(SV_NAME, "UnsupportedType", I0) 6181 << "Cannot SLP vectorize list: type " 6182 << rso.str() + " is unsupported by vectorizer"; 6183 }); 6184 return false; 6185 } 6186 } 6187 6188 unsigned Sz = R.getVectorElementSize(I0); 6189 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / Sz); 6190 unsigned MaxVF = std::max<unsigned>(PowerOf2Floor(VL.size()), MinVF); 6191 MaxVF = std::min(R.getMaximumVF(Sz, S.getOpcode()), MaxVF); 6192 if (MaxVF < 2) { 6193 R.getORE()->emit([&]() { 6194 return OptimizationRemarkMissed(SV_NAME, "SmallVF", I0) 6195 << "Cannot SLP vectorize list: vectorization factor " 6196 << "less than 2 is not supported"; 6197 }); 6198 return false; 6199 } 6200 6201 bool Changed = false; 6202 bool CandidateFound = false; 6203 InstructionCost MinCost = SLPCostThreshold.getValue(); 6204 6205 bool CompensateUseCost = 6206 !InsertUses.empty() && llvm::all_of(InsertUses, [](const Value *V) { 6207 return V && isa<InsertElementInst>(V); 6208 }); 6209 assert((!CompensateUseCost || InsertUses.size() == VL.size()) && 6210 "Each scalar expected to have an associated InsertElement user."); 6211 6212 unsigned NextInst = 0, MaxInst = VL.size(); 6213 for (unsigned VF = MaxVF; NextInst + 1 < MaxInst && VF >= MinVF; VF /= 2) { 6214 // No actual vectorization should happen, if number of parts is the same as 6215 // provided vectorization factor (i.e. the scalar type is used for vector 6216 // code during codegen). 6217 auto *VecTy = FixedVectorType::get(VL[0]->getType(), VF); 6218 if (TTI->getNumberOfParts(VecTy) == VF) 6219 continue; 6220 for (unsigned I = NextInst; I < MaxInst; ++I) { 6221 unsigned OpsWidth = 0; 6222 6223 if (I + VF > MaxInst) 6224 OpsWidth = MaxInst - I; 6225 else 6226 OpsWidth = VF; 6227 6228 if (!isPowerOf2_32(OpsWidth) || OpsWidth < 2) 6229 break; 6230 6231 ArrayRef<Value *> Ops = VL.slice(I, OpsWidth); 6232 // Check that a previous iteration of this loop did not delete the Value. 6233 if (llvm::any_of(Ops, [&R](Value *V) { 6234 auto *I = dyn_cast<Instruction>(V); 6235 return I && R.isDeleted(I); 6236 })) 6237 continue; 6238 6239 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << OpsWidth << " operations " 6240 << "\n"); 6241 6242 R.buildTree(Ops); 6243 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 6244 // TODO: check if we can allow reordering for more cases. 6245 if (AllowReorder && Order) { 6246 // TODO: reorder tree nodes without tree rebuilding. 6247 // Conceptually, there is nothing actually preventing us from trying to 6248 // reorder a larger list. In fact, we do exactly this when vectorizing 6249 // reductions. However, at this point, we only expect to get here when 6250 // there are exactly two operations. 6251 assert(Ops.size() == 2); 6252 Value *ReorderedOps[] = {Ops[1], Ops[0]}; 6253 R.buildTree(ReorderedOps, None); 6254 } 6255 if (R.isTreeTinyAndNotFullyVectorizable()) 6256 continue; 6257 6258 R.computeMinimumValueSizes(); 6259 InstructionCost Cost = R.getTreeCost(); 6260 CandidateFound = true; 6261 if (CompensateUseCost) { 6262 // TODO: Use TTI's getScalarizationOverhead for sequence of inserts 6263 // rather than sum of single inserts as the latter may overestimate 6264 // cost. This work should imply improving cost estimation for extracts 6265 // that added in for external (for vectorization tree) users,i.e. that 6266 // part should also switch to same interface. 6267 // For example, the following case is projected code after SLP: 6268 // %4 = extractelement <4 x i64> %3, i32 0 6269 // %v0 = insertelement <4 x i64> poison, i64 %4, i32 0 6270 // %5 = extractelement <4 x i64> %3, i32 1 6271 // %v1 = insertelement <4 x i64> %v0, i64 %5, i32 1 6272 // %6 = extractelement <4 x i64> %3, i32 2 6273 // %v2 = insertelement <4 x i64> %v1, i64 %6, i32 2 6274 // %7 = extractelement <4 x i64> %3, i32 3 6275 // %v3 = insertelement <4 x i64> %v2, i64 %7, i32 3 6276 // 6277 // Extracts here added by SLP in order to feed users (the inserts) of 6278 // original scalars and contribute to "ExtractCost" at cost evaluation. 6279 // The inserts in turn form sequence to build an aggregate that 6280 // detected by findBuildAggregate routine. 6281 // SLP makes an assumption that such sequence will be optimized away 6282 // later (instcombine) so it tries to compensate ExctractCost with 6283 // cost of insert sequence. 6284 // Current per element cost calculation approach is not quite accurate 6285 // and tends to create bias toward favoring vectorization. 6286 // Switching to the TTI interface might help a bit. 6287 // Alternative solution could be pattern-match to detect a no-op or 6288 // shuffle. 6289 InstructionCost UserCost = 0; 6290 for (unsigned Lane = 0; Lane < OpsWidth; Lane++) { 6291 auto *IE = cast<InsertElementInst>(InsertUses[I + Lane]); 6292 if (auto *CI = dyn_cast<ConstantInt>(IE->getOperand(2))) 6293 UserCost += TTI->getVectorInstrCost( 6294 Instruction::InsertElement, IE->getType(), CI->getZExtValue()); 6295 } 6296 LLVM_DEBUG(dbgs() << "SLP: Compensate cost of users by: " << UserCost 6297 << ".\n"); 6298 Cost -= UserCost; 6299 } 6300 6301 MinCost = std::min(MinCost, Cost); 6302 6303 if (Cost < -SLPCostThreshold) { 6304 LLVM_DEBUG(dbgs() << "SLP: Vectorizing list at cost:" << Cost << ".\n"); 6305 R.getORE()->emit(OptimizationRemark(SV_NAME, "VectorizedList", 6306 cast<Instruction>(Ops[0])) 6307 << "SLP vectorized with cost " << ore::NV("Cost", Cost) 6308 << " and with tree size " 6309 << ore::NV("TreeSize", R.getTreeSize())); 6310 6311 R.vectorizeTree(); 6312 // Move to the next bundle. 6313 I += VF - 1; 6314 NextInst = I + 1; 6315 Changed = true; 6316 } 6317 } 6318 } 6319 6320 if (!Changed && CandidateFound) { 6321 R.getORE()->emit([&]() { 6322 return OptimizationRemarkMissed(SV_NAME, "NotBeneficial", I0) 6323 << "List vectorization was possible but not beneficial with cost " 6324 << ore::NV("Cost", MinCost) << " >= " 6325 << ore::NV("Treshold", -SLPCostThreshold); 6326 }); 6327 } else if (!Changed) { 6328 R.getORE()->emit([&]() { 6329 return OptimizationRemarkMissed(SV_NAME, "NotPossible", I0) 6330 << "Cannot SLP vectorize list: vectorization was impossible" 6331 << " with available vectorization factors"; 6332 }); 6333 } 6334 return Changed; 6335 } 6336 6337 bool SLPVectorizerPass::tryToVectorize(Instruction *I, BoUpSLP &R) { 6338 if (!I) 6339 return false; 6340 6341 if (!isa<BinaryOperator>(I) && !isa<CmpInst>(I)) 6342 return false; 6343 6344 Value *P = I->getParent(); 6345 6346 // Vectorize in current basic block only. 6347 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 6348 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 6349 if (!Op0 || !Op1 || Op0->getParent() != P || Op1->getParent() != P) 6350 return false; 6351 6352 // Try to vectorize V. 6353 if (tryToVectorizePair(Op0, Op1, R)) 6354 return true; 6355 6356 auto *A = dyn_cast<BinaryOperator>(Op0); 6357 auto *B = dyn_cast<BinaryOperator>(Op1); 6358 // Try to skip B. 6359 if (B && B->hasOneUse()) { 6360 auto *B0 = dyn_cast<BinaryOperator>(B->getOperand(0)); 6361 auto *B1 = dyn_cast<BinaryOperator>(B->getOperand(1)); 6362 if (B0 && B0->getParent() == P && tryToVectorizePair(A, B0, R)) 6363 return true; 6364 if (B1 && B1->getParent() == P && tryToVectorizePair(A, B1, R)) 6365 return true; 6366 } 6367 6368 // Try to skip A. 6369 if (A && A->hasOneUse()) { 6370 auto *A0 = dyn_cast<BinaryOperator>(A->getOperand(0)); 6371 auto *A1 = dyn_cast<BinaryOperator>(A->getOperand(1)); 6372 if (A0 && A0->getParent() == P && tryToVectorizePair(A0, B, R)) 6373 return true; 6374 if (A1 && A1->getParent() == P && tryToVectorizePair(A1, B, R)) 6375 return true; 6376 } 6377 return false; 6378 } 6379 6380 namespace { 6381 6382 /// Model horizontal reductions. 6383 /// 6384 /// A horizontal reduction is a tree of reduction instructions that has values 6385 /// that can be put into a vector as its leaves. For example: 6386 /// 6387 /// mul mul mul mul 6388 /// \ / \ / 6389 /// + + 6390 /// \ / 6391 /// + 6392 /// This tree has "mul" as its leaf values and "+" as its reduction 6393 /// instructions. A reduction can feed into a store or a binary operation 6394 /// feeding a phi. 6395 /// ... 6396 /// \ / 6397 /// + 6398 /// | 6399 /// phi += 6400 /// 6401 /// Or: 6402 /// ... 6403 /// \ / 6404 /// + 6405 /// | 6406 /// *p = 6407 /// 6408 class HorizontalReduction { 6409 using ReductionOpsType = SmallVector<Value *, 16>; 6410 using ReductionOpsListType = SmallVector<ReductionOpsType, 2>; 6411 ReductionOpsListType ReductionOps; 6412 SmallVector<Value *, 32> ReducedVals; 6413 // Use map vector to make stable output. 6414 MapVector<Instruction *, Value *> ExtraArgs; 6415 WeakTrackingVH ReductionRoot; 6416 /// The type of reduction operation. 6417 RecurKind RdxKind; 6418 6419 /// Checks if instruction is associative and can be vectorized. 6420 static bool isVectorizable(RecurKind Kind, Instruction *I) { 6421 if (Kind == RecurKind::None) 6422 return false; 6423 if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(Kind)) 6424 return true; 6425 6426 if (Kind == RecurKind::FMax || Kind == RecurKind::FMin) { 6427 // FP min/max are associative except for NaN and -0.0. We do not 6428 // have to rule out -0.0 here because the intrinsic semantics do not 6429 // specify a fixed result for it. 6430 return I->getFastMathFlags().noNaNs(); 6431 } 6432 6433 return I->isAssociative(); 6434 } 6435 6436 /// Checks if the ParentStackElem.first should be marked as a reduction 6437 /// operation with an extra argument or as extra argument itself. 6438 void markExtraArg(std::pair<Instruction *, unsigned> &ParentStackElem, 6439 Value *ExtraArg) { 6440 if (ExtraArgs.count(ParentStackElem.first)) { 6441 ExtraArgs[ParentStackElem.first] = nullptr; 6442 // We ran into something like: 6443 // ParentStackElem.first = ExtraArgs[ParentStackElem.first] + ExtraArg. 6444 // The whole ParentStackElem.first should be considered as an extra value 6445 // in this case. 6446 // Do not perform analysis of remaining operands of ParentStackElem.first 6447 // instruction, this whole instruction is an extra argument. 6448 RecurKind ParentRdxKind = getRdxKind(ParentStackElem.first); 6449 ParentStackElem.second = getNumberOfOperands(ParentRdxKind); 6450 } else { 6451 // We ran into something like: 6452 // ParentStackElem.first += ... + ExtraArg + ... 6453 ExtraArgs[ParentStackElem.first] = ExtraArg; 6454 } 6455 } 6456 6457 /// Creates reduction operation with the current opcode. 6458 static Value *createOp(IRBuilder<> &Builder, RecurKind Kind, Value *LHS, 6459 Value *RHS, const Twine &Name) { 6460 unsigned RdxOpcode = RecurrenceDescriptor::getOpcode(Kind); 6461 switch (Kind) { 6462 case RecurKind::Add: 6463 case RecurKind::Mul: 6464 case RecurKind::Or: 6465 case RecurKind::And: 6466 case RecurKind::Xor: 6467 case RecurKind::FAdd: 6468 case RecurKind::FMul: 6469 return Builder.CreateBinOp((Instruction::BinaryOps)RdxOpcode, LHS, RHS, 6470 Name); 6471 case RecurKind::FMax: 6472 return Builder.CreateBinaryIntrinsic(Intrinsic::maxnum, LHS, RHS); 6473 case RecurKind::FMin: 6474 return Builder.CreateBinaryIntrinsic(Intrinsic::minnum, LHS, RHS); 6475 6476 case RecurKind::SMax: { 6477 Value *Cmp = Builder.CreateICmpSGT(LHS, RHS, Name); 6478 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6479 } 6480 case RecurKind::SMin: { 6481 Value *Cmp = Builder.CreateICmpSLT(LHS, RHS, Name); 6482 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6483 } 6484 case RecurKind::UMax: { 6485 Value *Cmp = Builder.CreateICmpUGT(LHS, RHS, Name); 6486 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6487 } 6488 case RecurKind::UMin: { 6489 Value *Cmp = Builder.CreateICmpULT(LHS, RHS, Name); 6490 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6491 } 6492 default: 6493 llvm_unreachable("Unknown reduction operation."); 6494 } 6495 } 6496 6497 /// Creates reduction operation with the current opcode with the IR flags 6498 /// from \p ReductionOps. 6499 static Value *createOp(IRBuilder<> &Builder, RecurKind RdxKind, Value *LHS, 6500 Value *RHS, const Twine &Name, 6501 const ReductionOpsListType &ReductionOps) { 6502 Value *Op = createOp(Builder, RdxKind, LHS, RHS, Name); 6503 if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(RdxKind)) { 6504 if (auto *Sel = dyn_cast<SelectInst>(Op)) 6505 propagateIRFlags(Sel->getCondition(), ReductionOps[0]); 6506 propagateIRFlags(Op, ReductionOps[1]); 6507 return Op; 6508 } 6509 propagateIRFlags(Op, ReductionOps[0]); 6510 return Op; 6511 } 6512 /// Creates reduction operation with the current opcode with the IR flags 6513 /// from \p I. 6514 static Value *createOp(IRBuilder<> &Builder, RecurKind RdxKind, Value *LHS, 6515 Value *RHS, const Twine &Name, Instruction *I) { 6516 Value *Op = createOp(Builder, RdxKind, LHS, RHS, Name); 6517 if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(RdxKind)) { 6518 if (auto *Sel = dyn_cast<SelectInst>(Op)) { 6519 propagateIRFlags(Sel->getCondition(), 6520 cast<SelectInst>(I)->getCondition()); 6521 } 6522 } 6523 propagateIRFlags(Op, I); 6524 return Op; 6525 } 6526 6527 static RecurKind getRdxKind(Instruction *I) { 6528 assert(I && "Expected instruction for reduction matching"); 6529 TargetTransformInfo::ReductionFlags RdxFlags; 6530 if (match(I, m_Add(m_Value(), m_Value()))) 6531 return RecurKind::Add; 6532 if (match(I, m_Mul(m_Value(), m_Value()))) 6533 return RecurKind::Mul; 6534 if (match(I, m_And(m_Value(), m_Value()))) 6535 return RecurKind::And; 6536 if (match(I, m_Or(m_Value(), m_Value()))) 6537 return RecurKind::Or; 6538 if (match(I, m_Xor(m_Value(), m_Value()))) 6539 return RecurKind::Xor; 6540 if (match(I, m_FAdd(m_Value(), m_Value()))) 6541 return RecurKind::FAdd; 6542 if (match(I, m_FMul(m_Value(), m_Value()))) 6543 return RecurKind::FMul; 6544 6545 if (match(I, m_Intrinsic<Intrinsic::maxnum>(m_Value(), m_Value()))) 6546 return RecurKind::FMax; 6547 if (match(I, m_Intrinsic<Intrinsic::minnum>(m_Value(), m_Value()))) 6548 return RecurKind::FMin; 6549 6550 if (match(I, m_SMax(m_Value(), m_Value()))) 6551 return RecurKind::SMax; 6552 if (match(I, m_SMin(m_Value(), m_Value()))) 6553 return RecurKind::SMin; 6554 if (match(I, m_UMax(m_Value(), m_Value()))) 6555 return RecurKind::UMax; 6556 if (match(I, m_UMin(m_Value(), m_Value()))) 6557 return RecurKind::UMin; 6558 6559 if (auto *Select = dyn_cast<SelectInst>(I)) { 6560 // Try harder: look for min/max pattern based on instructions producing 6561 // same values such as: select ((cmp Inst1, Inst2), Inst1, Inst2). 6562 // During the intermediate stages of SLP, it's very common to have 6563 // pattern like this (since optimizeGatherSequence is run only once 6564 // at the end): 6565 // %1 = extractelement <2 x i32> %a, i32 0 6566 // %2 = extractelement <2 x i32> %a, i32 1 6567 // %cond = icmp sgt i32 %1, %2 6568 // %3 = extractelement <2 x i32> %a, i32 0 6569 // %4 = extractelement <2 x i32> %a, i32 1 6570 // %select = select i1 %cond, i32 %3, i32 %4 6571 CmpInst::Predicate Pred; 6572 Instruction *L1; 6573 Instruction *L2; 6574 6575 Value *LHS = Select->getTrueValue(); 6576 Value *RHS = Select->getFalseValue(); 6577 Value *Cond = Select->getCondition(); 6578 6579 // TODO: Support inverse predicates. 6580 if (match(Cond, m_Cmp(Pred, m_Specific(LHS), m_Instruction(L2)))) { 6581 if (!isa<ExtractElementInst>(RHS) || 6582 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6583 return RecurKind::None; 6584 } else if (match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Specific(RHS)))) { 6585 if (!isa<ExtractElementInst>(LHS) || 6586 !L1->isIdenticalTo(cast<Instruction>(LHS))) 6587 return RecurKind::None; 6588 } else { 6589 if (!isa<ExtractElementInst>(LHS) || !isa<ExtractElementInst>(RHS)) 6590 return RecurKind::None; 6591 if (!match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Instruction(L2))) || 6592 !L1->isIdenticalTo(cast<Instruction>(LHS)) || 6593 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6594 return RecurKind::None; 6595 } 6596 6597 TargetTransformInfo::ReductionFlags RdxFlags; 6598 switch (Pred) { 6599 default: 6600 return RecurKind::None; 6601 case CmpInst::ICMP_SGT: 6602 case CmpInst::ICMP_SGE: 6603 return RecurKind::SMax; 6604 case CmpInst::ICMP_SLT: 6605 case CmpInst::ICMP_SLE: 6606 return RecurKind::SMin; 6607 case CmpInst::ICMP_UGT: 6608 case CmpInst::ICMP_UGE: 6609 return RecurKind::UMax; 6610 case CmpInst::ICMP_ULT: 6611 case CmpInst::ICMP_ULE: 6612 return RecurKind::UMin; 6613 } 6614 } 6615 return RecurKind::None; 6616 } 6617 6618 /// Return true if this operation is a cmp+select idiom. 6619 static bool isCmpSel(RecurKind Kind) { 6620 return RecurrenceDescriptor::isIntMinMaxRecurrenceKind(Kind); 6621 } 6622 6623 /// Get the index of the first operand. 6624 static unsigned getFirstOperandIndex(RecurKind Kind) { 6625 // We allow calling this before 'Kind' is set, so handle that specially. 6626 if (Kind == RecurKind::None) 6627 return 0; 6628 return isCmpSel(Kind) ? 1 : 0; 6629 } 6630 6631 /// Total number of operands in the reduction operation. 6632 static unsigned getNumberOfOperands(RecurKind Kind) { 6633 return isCmpSel(Kind) ? 3 : 2; 6634 } 6635 6636 /// Checks if the instruction is in basic block \p BB. 6637 /// For a min/max reduction check that both compare and select are in \p BB. 6638 static bool hasSameParent(RecurKind Kind, Instruction *I, BasicBlock *BB, 6639 bool IsRedOp) { 6640 if (IsRedOp && isCmpSel(Kind)) { 6641 auto *Cmp = cast<Instruction>(cast<SelectInst>(I)->getCondition()); 6642 return I->getParent() == BB && Cmp && Cmp->getParent() == BB; 6643 } 6644 return I->getParent() == BB; 6645 } 6646 6647 /// Expected number of uses for reduction operations/reduced values. 6648 static bool hasRequiredNumberOfUses(RecurKind Kind, Instruction *I, 6649 bool IsReductionOp) { 6650 // SelectInst must be used twice while the condition op must have single 6651 // use only. 6652 if (isCmpSel(Kind)) 6653 return I->hasNUses(2) && 6654 (!IsReductionOp || 6655 cast<SelectInst>(I)->getCondition()->hasOneUse()); 6656 6657 // Arithmetic reduction operation must be used once only. 6658 return I->hasOneUse(); 6659 } 6660 6661 /// Initializes the list of reduction operations. 6662 void initReductionOps(RecurKind Kind) { 6663 if (isCmpSel(Kind)) 6664 ReductionOps.assign(2, ReductionOpsType()); 6665 else 6666 ReductionOps.assign(1, ReductionOpsType()); 6667 } 6668 6669 /// Add all reduction operations for the reduction instruction \p I. 6670 void addReductionOps(RecurKind Kind, Instruction *I) { 6671 assert(Kind != RecurKind::None && "Expected reduction operation."); 6672 if (isCmpSel(Kind)) { 6673 ReductionOps[0].emplace_back(cast<SelectInst>(I)->getCondition()); 6674 ReductionOps[1].emplace_back(I); 6675 } else { 6676 ReductionOps[0].emplace_back(I); 6677 } 6678 } 6679 6680 static Value *getLHS(RecurKind Kind, Instruction *I) { 6681 if (Kind == RecurKind::None) 6682 return nullptr; 6683 return I->getOperand(getFirstOperandIndex(Kind)); 6684 } 6685 static Value *getRHS(RecurKind Kind, Instruction *I) { 6686 if (Kind == RecurKind::None) 6687 return nullptr; 6688 return I->getOperand(getFirstOperandIndex(Kind) + 1); 6689 } 6690 6691 public: 6692 HorizontalReduction() = default; 6693 6694 /// Try to find a reduction tree. 6695 bool matchAssociativeReduction(PHINode *Phi, Instruction *B) { 6696 assert((!Phi || is_contained(Phi->operands(), B)) && 6697 "Phi needs to use the binary operator"); 6698 6699 RdxKind = getRdxKind(B); 6700 6701 // We could have a initial reductions that is not an add. 6702 // r *= v1 + v2 + v3 + v4 6703 // In such a case start looking for a tree rooted in the first '+'. 6704 if (Phi) { 6705 if (getLHS(RdxKind, B) == Phi) { 6706 Phi = nullptr; 6707 B = dyn_cast<Instruction>(getRHS(RdxKind, B)); 6708 if (!B) 6709 return false; 6710 RdxKind = getRdxKind(B); 6711 } else if (getRHS(RdxKind, B) == Phi) { 6712 Phi = nullptr; 6713 B = dyn_cast<Instruction>(getLHS(RdxKind, B)); 6714 if (!B) 6715 return false; 6716 RdxKind = getRdxKind(B); 6717 } 6718 } 6719 6720 if (!isVectorizable(RdxKind, B)) 6721 return false; 6722 6723 // Analyze "regular" integer/FP types for reductions - no target-specific 6724 // types or pointers. 6725 Type *Ty = B->getType(); 6726 if (!isValidElementType(Ty) || Ty->isPointerTy()) 6727 return false; 6728 6729 ReductionRoot = B; 6730 6731 // The opcode for leaf values that we perform a reduction on. 6732 // For example: load(x) + load(y) + load(z) + fptoui(w) 6733 // The leaf opcode for 'w' does not match, so we don't include it as a 6734 // potential candidate for the reduction. 6735 unsigned LeafOpcode = 0; 6736 6737 // Post order traverse the reduction tree starting at B. We only handle true 6738 // trees containing only binary operators. 6739 SmallVector<std::pair<Instruction *, unsigned>, 32> Stack; 6740 Stack.push_back(std::make_pair(B, getFirstOperandIndex(RdxKind))); 6741 initReductionOps(RdxKind); 6742 while (!Stack.empty()) { 6743 Instruction *TreeN = Stack.back().first; 6744 unsigned EdgeToVisit = Stack.back().second++; 6745 const RecurKind TreeRdxKind = getRdxKind(TreeN); 6746 bool IsReducedValue = TreeRdxKind != RdxKind; 6747 6748 // Postorder visit. 6749 if (IsReducedValue || EdgeToVisit == getNumberOfOperands(TreeRdxKind)) { 6750 if (IsReducedValue) 6751 ReducedVals.push_back(TreeN); 6752 else { 6753 auto I = ExtraArgs.find(TreeN); 6754 if (I != ExtraArgs.end() && !I->second) { 6755 // Check if TreeN is an extra argument of its parent operation. 6756 if (Stack.size() <= 1) { 6757 // TreeN can't be an extra argument as it is a root reduction 6758 // operation. 6759 return false; 6760 } 6761 // Yes, TreeN is an extra argument, do not add it to a list of 6762 // reduction operations. 6763 // Stack[Stack.size() - 2] always points to the parent operation. 6764 markExtraArg(Stack[Stack.size() - 2], TreeN); 6765 ExtraArgs.erase(TreeN); 6766 } else 6767 addReductionOps(RdxKind, TreeN); 6768 } 6769 // Retract. 6770 Stack.pop_back(); 6771 continue; 6772 } 6773 6774 // Visit left or right. 6775 Value *EdgeVal = TreeN->getOperand(EdgeToVisit); 6776 auto *I = dyn_cast<Instruction>(EdgeVal); 6777 if (!I) { 6778 // Edge value is not a reduction instruction or a leaf instruction. 6779 // (It may be a constant, function argument, or something else.) 6780 markExtraArg(Stack.back(), EdgeVal); 6781 continue; 6782 } 6783 RecurKind EdgeRdxKind = getRdxKind(I); 6784 // Continue analysis if the next operand is a reduction operation or 6785 // (possibly) a leaf value. If the leaf value opcode is not set, 6786 // the first met operation != reduction operation is considered as the 6787 // leaf opcode. 6788 // Only handle trees in the current basic block. 6789 // Each tree node needs to have minimal number of users except for the 6790 // ultimate reduction. 6791 const bool IsRdxInst = EdgeRdxKind == RdxKind; 6792 if (I != Phi && I != B && 6793 hasSameParent(RdxKind, I, B->getParent(), IsRdxInst) && 6794 hasRequiredNumberOfUses(RdxKind, I, IsRdxInst) && 6795 (!LeafOpcode || LeafOpcode == I->getOpcode() || IsRdxInst)) { 6796 if (IsRdxInst) { 6797 // We need to be able to reassociate the reduction operations. 6798 if (!isVectorizable(EdgeRdxKind, I)) { 6799 // I is an extra argument for TreeN (its parent operation). 6800 markExtraArg(Stack.back(), I); 6801 continue; 6802 } 6803 } else if (!LeafOpcode) { 6804 LeafOpcode = I->getOpcode(); 6805 } 6806 Stack.push_back(std::make_pair(I, getFirstOperandIndex(EdgeRdxKind))); 6807 continue; 6808 } 6809 // I is an extra argument for TreeN (its parent operation). 6810 markExtraArg(Stack.back(), I); 6811 } 6812 return true; 6813 } 6814 6815 /// Attempt to vectorize the tree found by matchAssociativeReduction. 6816 bool tryToReduce(BoUpSLP &V, TargetTransformInfo *TTI) { 6817 // If there are a sufficient number of reduction values, reduce 6818 // to a nearby power-of-2. We can safely generate oversized 6819 // vectors and rely on the backend to split them to legal sizes. 6820 unsigned NumReducedVals = ReducedVals.size(); 6821 if (NumReducedVals < 4) 6822 return false; 6823 6824 // Intersect the fast-math-flags from all reduction operations. 6825 FastMathFlags RdxFMF; 6826 RdxFMF.set(); 6827 for (ReductionOpsType &RdxOp : ReductionOps) { 6828 for (Value *RdxVal : RdxOp) { 6829 if (auto *FPMO = dyn_cast<FPMathOperator>(RdxVal)) 6830 RdxFMF &= FPMO->getFastMathFlags(); 6831 } 6832 } 6833 6834 IRBuilder<> Builder(cast<Instruction>(ReductionRoot)); 6835 Builder.setFastMathFlags(RdxFMF); 6836 6837 BoUpSLP::ExtraValueToDebugLocsMap ExternallyUsedValues; 6838 // The same extra argument may be used several times, so log each attempt 6839 // to use it. 6840 for (const std::pair<Instruction *, Value *> &Pair : ExtraArgs) { 6841 assert(Pair.first && "DebugLoc must be set."); 6842 ExternallyUsedValues[Pair.second].push_back(Pair.first); 6843 } 6844 6845 // The compare instruction of a min/max is the insertion point for new 6846 // instructions and may be replaced with a new compare instruction. 6847 auto getCmpForMinMaxReduction = [](Instruction *RdxRootInst) { 6848 assert(isa<SelectInst>(RdxRootInst) && 6849 "Expected min/max reduction to have select root instruction"); 6850 Value *ScalarCond = cast<SelectInst>(RdxRootInst)->getCondition(); 6851 assert(isa<Instruction>(ScalarCond) && 6852 "Expected min/max reduction to have compare condition"); 6853 return cast<Instruction>(ScalarCond); 6854 }; 6855 6856 // The reduction root is used as the insertion point for new instructions, 6857 // so set it as externally used to prevent it from being deleted. 6858 ExternallyUsedValues[ReductionRoot]; 6859 SmallVector<Value *, 16> IgnoreList; 6860 for (ReductionOpsType &RdxOp : ReductionOps) 6861 IgnoreList.append(RdxOp.begin(), RdxOp.end()); 6862 6863 unsigned ReduxWidth = PowerOf2Floor(NumReducedVals); 6864 if (NumReducedVals > ReduxWidth) { 6865 // In the loop below, we are building a tree based on a window of 6866 // 'ReduxWidth' values. 6867 // If the operands of those values have common traits (compare predicate, 6868 // constant operand, etc), then we want to group those together to 6869 // minimize the cost of the reduction. 6870 6871 // TODO: This should be extended to count common operands for 6872 // compares and binops. 6873 6874 // Step 1: Count the number of times each compare predicate occurs. 6875 SmallDenseMap<unsigned, unsigned> PredCountMap; 6876 for (Value *RdxVal : ReducedVals) { 6877 CmpInst::Predicate Pred; 6878 if (match(RdxVal, m_Cmp(Pred, m_Value(), m_Value()))) 6879 ++PredCountMap[Pred]; 6880 } 6881 // Step 2: Sort the values so the most common predicates come first. 6882 stable_sort(ReducedVals, [&PredCountMap](Value *A, Value *B) { 6883 CmpInst::Predicate PredA, PredB; 6884 if (match(A, m_Cmp(PredA, m_Value(), m_Value())) && 6885 match(B, m_Cmp(PredB, m_Value(), m_Value()))) { 6886 return PredCountMap[PredA] > PredCountMap[PredB]; 6887 } 6888 return false; 6889 }); 6890 } 6891 6892 Value *VectorizedTree = nullptr; 6893 unsigned i = 0; 6894 while (i < NumReducedVals - ReduxWidth + 1 && ReduxWidth > 2) { 6895 ArrayRef<Value *> VL(&ReducedVals[i], ReduxWidth); 6896 V.buildTree(VL, ExternallyUsedValues, IgnoreList); 6897 Optional<ArrayRef<unsigned>> Order = V.bestOrder(); 6898 if (Order) { 6899 assert(Order->size() == VL.size() && 6900 "Order size must be the same as number of vectorized " 6901 "instructions."); 6902 // TODO: reorder tree nodes without tree rebuilding. 6903 SmallVector<Value *, 4> ReorderedOps(VL.size()); 6904 llvm::transform(*Order, ReorderedOps.begin(), 6905 [VL](const unsigned Idx) { return VL[Idx]; }); 6906 V.buildTree(ReorderedOps, ExternallyUsedValues, IgnoreList); 6907 } 6908 if (V.isTreeTinyAndNotFullyVectorizable()) 6909 break; 6910 if (V.isLoadCombineReductionCandidate(RdxKind)) 6911 break; 6912 6913 V.computeMinimumValueSizes(); 6914 6915 // Estimate cost. 6916 InstructionCost TreeCost = V.getTreeCost(); 6917 InstructionCost ReductionCost = 6918 getReductionCost(TTI, ReducedVals[i], ReduxWidth); 6919 InstructionCost Cost = TreeCost + ReductionCost; 6920 if (!Cost.isValid()) { 6921 LLVM_DEBUG(dbgs() << "Encountered invalid baseline cost.\n"); 6922 return false; 6923 } 6924 if (Cost >= -SLPCostThreshold) { 6925 V.getORE()->emit([&]() { 6926 return OptimizationRemarkMissed(SV_NAME, "HorSLPNotBeneficial", 6927 cast<Instruction>(VL[0])) 6928 << "Vectorizing horizontal reduction is possible" 6929 << "but not beneficial with cost " << ore::NV("Cost", Cost) 6930 << " and threshold " 6931 << ore::NV("Threshold", -SLPCostThreshold); 6932 }); 6933 break; 6934 } 6935 6936 LLVM_DEBUG(dbgs() << "SLP: Vectorizing horizontal reduction at cost:" 6937 << Cost << ". (HorRdx)\n"); 6938 V.getORE()->emit([&]() { 6939 return OptimizationRemark(SV_NAME, "VectorizedHorizontalReduction", 6940 cast<Instruction>(VL[0])) 6941 << "Vectorized horizontal reduction with cost " 6942 << ore::NV("Cost", Cost) << " and with tree size " 6943 << ore::NV("TreeSize", V.getTreeSize()); 6944 }); 6945 6946 // Vectorize a tree. 6947 DebugLoc Loc = cast<Instruction>(ReducedVals[i])->getDebugLoc(); 6948 Value *VectorizedRoot = V.vectorizeTree(ExternallyUsedValues); 6949 6950 // Emit a reduction. If the root is a select (min/max idiom), the insert 6951 // point is the compare condition of that select. 6952 Instruction *RdxRootInst = cast<Instruction>(ReductionRoot); 6953 if (isCmpSel(RdxKind)) 6954 Builder.SetInsertPoint(getCmpForMinMaxReduction(RdxRootInst)); 6955 else 6956 Builder.SetInsertPoint(RdxRootInst); 6957 6958 Value *ReducedSubTree = 6959 emitReduction(VectorizedRoot, Builder, ReduxWidth, TTI); 6960 6961 if (!VectorizedTree) { 6962 // Initialize the final value in the reduction. 6963 VectorizedTree = ReducedSubTree; 6964 } else { 6965 // Update the final value in the reduction. 6966 Builder.SetCurrentDebugLocation(Loc); 6967 VectorizedTree = createOp(Builder, RdxKind, VectorizedTree, 6968 ReducedSubTree, "op.rdx", ReductionOps); 6969 } 6970 i += ReduxWidth; 6971 ReduxWidth = PowerOf2Floor(NumReducedVals - i); 6972 } 6973 6974 if (VectorizedTree) { 6975 // Finish the reduction. 6976 for (; i < NumReducedVals; ++i) { 6977 auto *I = cast<Instruction>(ReducedVals[i]); 6978 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 6979 VectorizedTree = 6980 createOp(Builder, RdxKind, VectorizedTree, I, "", ReductionOps); 6981 } 6982 for (auto &Pair : ExternallyUsedValues) { 6983 // Add each externally used value to the final reduction. 6984 for (auto *I : Pair.second) { 6985 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 6986 VectorizedTree = createOp(Builder, RdxKind, VectorizedTree, 6987 Pair.first, "op.extra", I); 6988 } 6989 } 6990 6991 // Update users. For a min/max reduction that ends with a compare and 6992 // select, we also have to RAUW for the compare instruction feeding the 6993 // reduction root. That's because the original compare may have extra uses 6994 // besides the final select of the reduction. 6995 if (isCmpSel(RdxKind)) { 6996 if (auto *VecSelect = dyn_cast<SelectInst>(VectorizedTree)) { 6997 Instruction *ScalarCmp = 6998 getCmpForMinMaxReduction(cast<Instruction>(ReductionRoot)); 6999 ScalarCmp->replaceAllUsesWith(VecSelect->getCondition()); 7000 } 7001 } 7002 ReductionRoot->replaceAllUsesWith(VectorizedTree); 7003 7004 // Mark all scalar reduction ops for deletion, they are replaced by the 7005 // vector reductions. 7006 V.eraseInstructions(IgnoreList); 7007 } 7008 return VectorizedTree != nullptr; 7009 } 7010 7011 unsigned numReductionValues() const { return ReducedVals.size(); } 7012 7013 private: 7014 /// Calculate the cost of a reduction. 7015 InstructionCost getReductionCost(TargetTransformInfo *TTI, 7016 Value *FirstReducedVal, 7017 unsigned ReduxWidth) { 7018 Type *ScalarTy = FirstReducedVal->getType(); 7019 FixedVectorType *VectorTy = FixedVectorType::get(ScalarTy, ReduxWidth); 7020 InstructionCost VectorCost, ScalarCost; 7021 switch (RdxKind) { 7022 case RecurKind::Add: 7023 case RecurKind::Mul: 7024 case RecurKind::Or: 7025 case RecurKind::And: 7026 case RecurKind::Xor: 7027 case RecurKind::FAdd: 7028 case RecurKind::FMul: { 7029 unsigned RdxOpcode = RecurrenceDescriptor::getOpcode(RdxKind); 7030 VectorCost = TTI->getArithmeticReductionCost(RdxOpcode, VectorTy, 7031 /*IsPairwiseForm=*/false); 7032 ScalarCost = TTI->getArithmeticInstrCost(RdxOpcode, ScalarTy); 7033 break; 7034 } 7035 case RecurKind::FMax: 7036 case RecurKind::FMin: { 7037 auto *VecCondTy = cast<VectorType>(CmpInst::makeCmpResultType(VectorTy)); 7038 VectorCost = 7039 TTI->getMinMaxReductionCost(VectorTy, VecCondTy, 7040 /*pairwise=*/false, /*unsigned=*/false); 7041 ScalarCost = 7042 TTI->getCmpSelInstrCost(Instruction::FCmp, ScalarTy) + 7043 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 7044 CmpInst::makeCmpResultType(ScalarTy)); 7045 break; 7046 } 7047 case RecurKind::SMax: 7048 case RecurKind::SMin: 7049 case RecurKind::UMax: 7050 case RecurKind::UMin: { 7051 auto *VecCondTy = cast<VectorType>(CmpInst::makeCmpResultType(VectorTy)); 7052 bool IsUnsigned = 7053 RdxKind == RecurKind::UMax || RdxKind == RecurKind::UMin; 7054 VectorCost = 7055 TTI->getMinMaxReductionCost(VectorTy, VecCondTy, 7056 /*IsPairwiseForm=*/false, IsUnsigned); 7057 ScalarCost = 7058 TTI->getCmpSelInstrCost(Instruction::ICmp, ScalarTy) + 7059 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 7060 CmpInst::makeCmpResultType(ScalarTy)); 7061 break; 7062 } 7063 default: 7064 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 7065 } 7066 7067 // Scalar cost is repeated for N-1 elements. 7068 ScalarCost *= (ReduxWidth - 1); 7069 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << VectorCost - ScalarCost 7070 << " for reduction that starts with " << *FirstReducedVal 7071 << " (It is a splitting reduction)\n"); 7072 return VectorCost - ScalarCost; 7073 } 7074 7075 /// Emit a horizontal reduction of the vectorized value. 7076 Value *emitReduction(Value *VectorizedValue, IRBuilder<> &Builder, 7077 unsigned ReduxWidth, const TargetTransformInfo *TTI) { 7078 assert(VectorizedValue && "Need to have a vectorized tree node"); 7079 assert(isPowerOf2_32(ReduxWidth) && 7080 "We only handle power-of-two reductions for now"); 7081 7082 return createSimpleTargetReduction(Builder, TTI, VectorizedValue, RdxKind, 7083 ReductionOps.back()); 7084 } 7085 }; 7086 7087 } // end anonymous namespace 7088 7089 static Optional<unsigned> getAggregateSize(Instruction *InsertInst) { 7090 if (auto *IE = dyn_cast<InsertElementInst>(InsertInst)) 7091 return cast<FixedVectorType>(IE->getType())->getNumElements(); 7092 7093 unsigned AggregateSize = 1; 7094 auto *IV = cast<InsertValueInst>(InsertInst); 7095 Type *CurrentType = IV->getType(); 7096 do { 7097 if (auto *ST = dyn_cast<StructType>(CurrentType)) { 7098 for (auto *Elt : ST->elements()) 7099 if (Elt != ST->getElementType(0)) // check homogeneity 7100 return None; 7101 AggregateSize *= ST->getNumElements(); 7102 CurrentType = ST->getElementType(0); 7103 } else if (auto *AT = dyn_cast<ArrayType>(CurrentType)) { 7104 AggregateSize *= AT->getNumElements(); 7105 CurrentType = AT->getElementType(); 7106 } else if (auto *VT = dyn_cast<FixedVectorType>(CurrentType)) { 7107 AggregateSize *= VT->getNumElements(); 7108 return AggregateSize; 7109 } else if (CurrentType->isSingleValueType()) { 7110 return AggregateSize; 7111 } else { 7112 return None; 7113 } 7114 } while (true); 7115 } 7116 7117 static Optional<unsigned> getOperandIndex(Instruction *InsertInst, 7118 unsigned OperandOffset) { 7119 unsigned OperandIndex = OperandOffset; 7120 if (auto *IE = dyn_cast<InsertElementInst>(InsertInst)) { 7121 if (auto *CI = dyn_cast<ConstantInt>(IE->getOperand(2))) { 7122 auto *VT = cast<FixedVectorType>(IE->getType()); 7123 OperandIndex *= VT->getNumElements(); 7124 OperandIndex += CI->getZExtValue(); 7125 return OperandIndex; 7126 } 7127 return None; 7128 } 7129 7130 auto *IV = cast<InsertValueInst>(InsertInst); 7131 Type *CurrentType = IV->getType(); 7132 for (unsigned int Index : IV->indices()) { 7133 if (auto *ST = dyn_cast<StructType>(CurrentType)) { 7134 OperandIndex *= ST->getNumElements(); 7135 CurrentType = ST->getElementType(Index); 7136 } else if (auto *AT = dyn_cast<ArrayType>(CurrentType)) { 7137 OperandIndex *= AT->getNumElements(); 7138 CurrentType = AT->getElementType(); 7139 } else { 7140 return None; 7141 } 7142 OperandIndex += Index; 7143 } 7144 return OperandIndex; 7145 } 7146 7147 static bool findBuildAggregate_rec(Instruction *LastInsertInst, 7148 TargetTransformInfo *TTI, 7149 SmallVectorImpl<Value *> &BuildVectorOpds, 7150 SmallVectorImpl<Value *> &InsertElts, 7151 unsigned OperandOffset) { 7152 do { 7153 Value *InsertedOperand = LastInsertInst->getOperand(1); 7154 Optional<unsigned> OperandIndex = 7155 getOperandIndex(LastInsertInst, OperandOffset); 7156 if (!OperandIndex) 7157 return false; 7158 if (isa<InsertElementInst>(InsertedOperand) || 7159 isa<InsertValueInst>(InsertedOperand)) { 7160 if (!findBuildAggregate_rec(cast<Instruction>(InsertedOperand), TTI, 7161 BuildVectorOpds, InsertElts, *OperandIndex)) 7162 return false; 7163 } else { 7164 BuildVectorOpds[*OperandIndex] = InsertedOperand; 7165 InsertElts[*OperandIndex] = LastInsertInst; 7166 } 7167 if (isa<UndefValue>(LastInsertInst->getOperand(0))) 7168 return true; 7169 LastInsertInst = dyn_cast<Instruction>(LastInsertInst->getOperand(0)); 7170 } while (LastInsertInst != nullptr && 7171 (isa<InsertValueInst>(LastInsertInst) || 7172 isa<InsertElementInst>(LastInsertInst)) && 7173 LastInsertInst->hasOneUse()); 7174 return false; 7175 } 7176 7177 /// Recognize construction of vectors like 7178 /// %ra = insertelement <4 x float> poison, float %s0, i32 0 7179 /// %rb = insertelement <4 x float> %ra, float %s1, i32 1 7180 /// %rc = insertelement <4 x float> %rb, float %s2, i32 2 7181 /// %rd = insertelement <4 x float> %rc, float %s3, i32 3 7182 /// starting from the last insertelement or insertvalue instruction. 7183 /// 7184 /// Also recognize homogeneous aggregates like {<2 x float>, <2 x float>}, 7185 /// {{float, float}, {float, float}}, [2 x {float, float}] and so on. 7186 /// See llvm/test/Transforms/SLPVectorizer/X86/pr42022.ll for examples. 7187 /// 7188 /// Assume LastInsertInst is of InsertElementInst or InsertValueInst type. 7189 /// 7190 /// \return true if it matches. 7191 static bool findBuildAggregate(Instruction *LastInsertInst, 7192 TargetTransformInfo *TTI, 7193 SmallVectorImpl<Value *> &BuildVectorOpds, 7194 SmallVectorImpl<Value *> &InsertElts) { 7195 7196 assert((isa<InsertElementInst>(LastInsertInst) || 7197 isa<InsertValueInst>(LastInsertInst)) && 7198 "Expected insertelement or insertvalue instruction!"); 7199 7200 assert((BuildVectorOpds.empty() && InsertElts.empty()) && 7201 "Expected empty result vectors!"); 7202 7203 Optional<unsigned> AggregateSize = getAggregateSize(LastInsertInst); 7204 if (!AggregateSize) 7205 return false; 7206 BuildVectorOpds.resize(*AggregateSize); 7207 InsertElts.resize(*AggregateSize); 7208 7209 if (findBuildAggregate_rec(LastInsertInst, TTI, BuildVectorOpds, InsertElts, 7210 0)) { 7211 llvm::erase_value(BuildVectorOpds, nullptr); 7212 llvm::erase_value(InsertElts, nullptr); 7213 if (BuildVectorOpds.size() >= 2) 7214 return true; 7215 } 7216 7217 return false; 7218 } 7219 7220 static bool PhiTypeSorterFunc(Value *V, Value *V2) { 7221 return V->getType() < V2->getType(); 7222 } 7223 7224 /// Try and get a reduction value from a phi node. 7225 /// 7226 /// Given a phi node \p P in a block \p ParentBB, consider possible reductions 7227 /// if they come from either \p ParentBB or a containing loop latch. 7228 /// 7229 /// \returns A candidate reduction value if possible, or \code nullptr \endcode 7230 /// if not possible. 7231 static Value *getReductionValue(const DominatorTree *DT, PHINode *P, 7232 BasicBlock *ParentBB, LoopInfo *LI) { 7233 // There are situations where the reduction value is not dominated by the 7234 // reduction phi. Vectorizing such cases has been reported to cause 7235 // miscompiles. See PR25787. 7236 auto DominatedReduxValue = [&](Value *R) { 7237 return isa<Instruction>(R) && 7238 DT->dominates(P->getParent(), cast<Instruction>(R)->getParent()); 7239 }; 7240 7241 Value *Rdx = nullptr; 7242 7243 // Return the incoming value if it comes from the same BB as the phi node. 7244 if (P->getIncomingBlock(0) == ParentBB) { 7245 Rdx = P->getIncomingValue(0); 7246 } else if (P->getIncomingBlock(1) == ParentBB) { 7247 Rdx = P->getIncomingValue(1); 7248 } 7249 7250 if (Rdx && DominatedReduxValue(Rdx)) 7251 return Rdx; 7252 7253 // Otherwise, check whether we have a loop latch to look at. 7254 Loop *BBL = LI->getLoopFor(ParentBB); 7255 if (!BBL) 7256 return nullptr; 7257 BasicBlock *BBLatch = BBL->getLoopLatch(); 7258 if (!BBLatch) 7259 return nullptr; 7260 7261 // There is a loop latch, return the incoming value if it comes from 7262 // that. This reduction pattern occasionally turns up. 7263 if (P->getIncomingBlock(0) == BBLatch) { 7264 Rdx = P->getIncomingValue(0); 7265 } else if (P->getIncomingBlock(1) == BBLatch) { 7266 Rdx = P->getIncomingValue(1); 7267 } 7268 7269 if (Rdx && DominatedReduxValue(Rdx)) 7270 return Rdx; 7271 7272 return nullptr; 7273 } 7274 7275 static bool matchRdxBop(Instruction *I, Value *&V0, Value *&V1) { 7276 if (match(I, m_BinOp(m_Value(V0), m_Value(V1)))) 7277 return true; 7278 if (match(I, m_Intrinsic<Intrinsic::maxnum>(m_Value(V0), m_Value(V1)))) 7279 return true; 7280 if (match(I, m_Intrinsic<Intrinsic::minnum>(m_Value(V0), m_Value(V1)))) 7281 return true; 7282 return false; 7283 } 7284 7285 /// Attempt to reduce a horizontal reduction. 7286 /// If it is legal to match a horizontal reduction feeding the phi node \a P 7287 /// with reduction operators \a Root (or one of its operands) in a basic block 7288 /// \a BB, then check if it can be done. If horizontal reduction is not found 7289 /// and root instruction is a binary operation, vectorization of the operands is 7290 /// attempted. 7291 /// \returns true if a horizontal reduction was matched and reduced or operands 7292 /// of one of the binary instruction were vectorized. 7293 /// \returns false if a horizontal reduction was not matched (or not possible) 7294 /// or no vectorization of any binary operation feeding \a Root instruction was 7295 /// performed. 7296 static bool tryToVectorizeHorReductionOrInstOperands( 7297 PHINode *P, Instruction *Root, BasicBlock *BB, BoUpSLP &R, 7298 TargetTransformInfo *TTI, 7299 const function_ref<bool(Instruction *, BoUpSLP &)> Vectorize) { 7300 if (!ShouldVectorizeHor) 7301 return false; 7302 7303 if (!Root) 7304 return false; 7305 7306 if (Root->getParent() != BB || isa<PHINode>(Root)) 7307 return false; 7308 // Start analysis starting from Root instruction. If horizontal reduction is 7309 // found, try to vectorize it. If it is not a horizontal reduction or 7310 // vectorization is not possible or not effective, and currently analyzed 7311 // instruction is a binary operation, try to vectorize the operands, using 7312 // pre-order DFS traversal order. If the operands were not vectorized, repeat 7313 // the same procedure considering each operand as a possible root of the 7314 // horizontal reduction. 7315 // Interrupt the process if the Root instruction itself was vectorized or all 7316 // sub-trees not higher that RecursionMaxDepth were analyzed/vectorized. 7317 SmallVector<std::pair<Instruction *, unsigned>, 8> Stack(1, {Root, 0}); 7318 SmallPtrSet<Value *, 8> VisitedInstrs; 7319 bool Res = false; 7320 while (!Stack.empty()) { 7321 Instruction *Inst; 7322 unsigned Level; 7323 std::tie(Inst, Level) = Stack.pop_back_val(); 7324 Value *B0, *B1; 7325 bool IsBinop = matchRdxBop(Inst, B0, B1); 7326 bool IsSelect = match(Inst, m_Select(m_Value(), m_Value(), m_Value())); 7327 if (IsBinop || IsSelect) { 7328 HorizontalReduction HorRdx; 7329 if (HorRdx.matchAssociativeReduction(P, Inst)) { 7330 if (HorRdx.tryToReduce(R, TTI)) { 7331 Res = true; 7332 // Set P to nullptr to avoid re-analysis of phi node in 7333 // matchAssociativeReduction function unless this is the root node. 7334 P = nullptr; 7335 continue; 7336 } 7337 } 7338 if (P && IsBinop) { 7339 Inst = dyn_cast<Instruction>(B0); 7340 if (Inst == P) 7341 Inst = dyn_cast<Instruction>(B1); 7342 if (!Inst) { 7343 // Set P to nullptr to avoid re-analysis of phi node in 7344 // matchAssociativeReduction function unless this is the root node. 7345 P = nullptr; 7346 continue; 7347 } 7348 } 7349 } 7350 // Set P to nullptr to avoid re-analysis of phi node in 7351 // matchAssociativeReduction function unless this is the root node. 7352 P = nullptr; 7353 if (Vectorize(Inst, R)) { 7354 Res = true; 7355 continue; 7356 } 7357 7358 // Try to vectorize operands. 7359 // Continue analysis for the instruction from the same basic block only to 7360 // save compile time. 7361 if (++Level < RecursionMaxDepth) 7362 for (auto *Op : Inst->operand_values()) 7363 if (VisitedInstrs.insert(Op).second) 7364 if (auto *I = dyn_cast<Instruction>(Op)) 7365 if (!isa<PHINode>(I) && !R.isDeleted(I) && I->getParent() == BB) 7366 Stack.emplace_back(I, Level); 7367 } 7368 return Res; 7369 } 7370 7371 bool SLPVectorizerPass::vectorizeRootInstruction(PHINode *P, Value *V, 7372 BasicBlock *BB, BoUpSLP &R, 7373 TargetTransformInfo *TTI) { 7374 auto *I = dyn_cast_or_null<Instruction>(V); 7375 if (!I) 7376 return false; 7377 7378 if (!isa<BinaryOperator>(I)) 7379 P = nullptr; 7380 // Try to match and vectorize a horizontal reduction. 7381 auto &&ExtraVectorization = [this](Instruction *I, BoUpSLP &R) -> bool { 7382 return tryToVectorize(I, R); 7383 }; 7384 return tryToVectorizeHorReductionOrInstOperands(P, I, BB, R, TTI, 7385 ExtraVectorization); 7386 } 7387 7388 bool SLPVectorizerPass::vectorizeInsertValueInst(InsertValueInst *IVI, 7389 BasicBlock *BB, BoUpSLP &R) { 7390 const DataLayout &DL = BB->getModule()->getDataLayout(); 7391 if (!R.canMapToVector(IVI->getType(), DL)) 7392 return false; 7393 7394 SmallVector<Value *, 16> BuildVectorOpds; 7395 SmallVector<Value *, 16> BuildVectorInsts; 7396 if (!findBuildAggregate(IVI, TTI, BuildVectorOpds, BuildVectorInsts)) 7397 return false; 7398 7399 LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IVI << "\n"); 7400 // Aggregate value is unlikely to be processed in vector register, we need to 7401 // extract scalars into scalar registers, so NeedExtraction is set true. 7402 return tryToVectorizeList(BuildVectorOpds, R, /*AllowReorder=*/false, 7403 BuildVectorInsts); 7404 } 7405 7406 bool SLPVectorizerPass::vectorizeInsertElementInst(InsertElementInst *IEI, 7407 BasicBlock *BB, BoUpSLP &R) { 7408 SmallVector<Value *, 16> BuildVectorInsts; 7409 SmallVector<Value *, 16> BuildVectorOpds; 7410 if (!findBuildAggregate(IEI, TTI, BuildVectorOpds, BuildVectorInsts) || 7411 (llvm::all_of(BuildVectorOpds, 7412 [](Value *V) { return isa<ExtractElementInst>(V); }) && 7413 isShuffle(BuildVectorOpds))) 7414 return false; 7415 7416 // Vectorize starting with the build vector operands ignoring the BuildVector 7417 // instructions for the purpose of scheduling and user extraction. 7418 return tryToVectorizeList(BuildVectorOpds, R, /*AllowReorder=*/false, 7419 BuildVectorInsts); 7420 } 7421 7422 bool SLPVectorizerPass::vectorizeCmpInst(CmpInst *CI, BasicBlock *BB, 7423 BoUpSLP &R) { 7424 if (tryToVectorizePair(CI->getOperand(0), CI->getOperand(1), R)) 7425 return true; 7426 7427 bool OpsChanged = false; 7428 for (int Idx = 0; Idx < 2; ++Idx) { 7429 OpsChanged |= 7430 vectorizeRootInstruction(nullptr, CI->getOperand(Idx), BB, R, TTI); 7431 } 7432 return OpsChanged; 7433 } 7434 7435 bool SLPVectorizerPass::vectorizeSimpleInstructions( 7436 SmallVectorImpl<Instruction *> &Instructions, BasicBlock *BB, BoUpSLP &R) { 7437 bool OpsChanged = false; 7438 for (auto *I : reverse(Instructions)) { 7439 if (R.isDeleted(I)) 7440 continue; 7441 if (auto *LastInsertValue = dyn_cast<InsertValueInst>(I)) 7442 OpsChanged |= vectorizeInsertValueInst(LastInsertValue, BB, R); 7443 else if (auto *LastInsertElem = dyn_cast<InsertElementInst>(I)) 7444 OpsChanged |= vectorizeInsertElementInst(LastInsertElem, BB, R); 7445 else if (auto *CI = dyn_cast<CmpInst>(I)) 7446 OpsChanged |= vectorizeCmpInst(CI, BB, R); 7447 } 7448 Instructions.clear(); 7449 return OpsChanged; 7450 } 7451 7452 bool SLPVectorizerPass::vectorizeChainsInBlock(BasicBlock *BB, BoUpSLP &R) { 7453 bool Changed = false; 7454 SmallVector<Value *, 4> Incoming; 7455 SmallPtrSet<Value *, 16> VisitedInstrs; 7456 7457 bool HaveVectorizedPhiNodes = true; 7458 while (HaveVectorizedPhiNodes) { 7459 HaveVectorizedPhiNodes = false; 7460 7461 // Collect the incoming values from the PHIs. 7462 Incoming.clear(); 7463 for (Instruction &I : *BB) { 7464 PHINode *P = dyn_cast<PHINode>(&I); 7465 if (!P) 7466 break; 7467 7468 if (!VisitedInstrs.count(P) && !R.isDeleted(P)) 7469 Incoming.push_back(P); 7470 } 7471 7472 // Sort by type. 7473 llvm::stable_sort(Incoming, PhiTypeSorterFunc); 7474 7475 // Try to vectorize elements base on their type. 7476 for (SmallVector<Value *, 4>::iterator IncIt = Incoming.begin(), 7477 E = Incoming.end(); 7478 IncIt != E;) { 7479 7480 // Look for the next elements with the same type. 7481 SmallVector<Value *, 4>::iterator SameTypeIt = IncIt; 7482 while (SameTypeIt != E && 7483 (*SameTypeIt)->getType() == (*IncIt)->getType()) { 7484 VisitedInstrs.insert(*SameTypeIt); 7485 ++SameTypeIt; 7486 } 7487 7488 // Try to vectorize them. 7489 unsigned NumElts = (SameTypeIt - IncIt); 7490 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize starting at PHIs (" 7491 << NumElts << ")\n"); 7492 // The order in which the phi nodes appear in the program does not matter. 7493 // So allow tryToVectorizeList to reorder them if it is beneficial. This 7494 // is done when there are exactly two elements since tryToVectorizeList 7495 // asserts that there are only two values when AllowReorder is true. 7496 bool AllowReorder = NumElts == 2; 7497 if (NumElts > 1 && 7498 tryToVectorizeList(makeArrayRef(IncIt, NumElts), R, AllowReorder)) { 7499 // Success start over because instructions might have been changed. 7500 HaveVectorizedPhiNodes = true; 7501 Changed = true; 7502 break; 7503 } 7504 7505 // Start over at the next instruction of a different type (or the end). 7506 IncIt = SameTypeIt; 7507 } 7508 } 7509 7510 VisitedInstrs.clear(); 7511 7512 SmallVector<Instruction *, 8> PostProcessInstructions; 7513 SmallDenseSet<Instruction *, 4> KeyNodes; 7514 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 7515 // Skip instructions with scalable type. The num of elements is unknown at 7516 // compile-time for scalable type. 7517 if (isa<ScalableVectorType>(it->getType())) 7518 continue; 7519 7520 // Skip instructions marked for the deletion. 7521 if (R.isDeleted(&*it)) 7522 continue; 7523 // We may go through BB multiple times so skip the one we have checked. 7524 if (!VisitedInstrs.insert(&*it).second) { 7525 if (it->use_empty() && KeyNodes.contains(&*it) && 7526 vectorizeSimpleInstructions(PostProcessInstructions, BB, R)) { 7527 // We would like to start over since some instructions are deleted 7528 // and the iterator may become invalid value. 7529 Changed = true; 7530 it = BB->begin(); 7531 e = BB->end(); 7532 } 7533 continue; 7534 } 7535 7536 if (isa<DbgInfoIntrinsic>(it)) 7537 continue; 7538 7539 // Try to vectorize reductions that use PHINodes. 7540 if (PHINode *P = dyn_cast<PHINode>(it)) { 7541 // Check that the PHI is a reduction PHI. 7542 if (P->getNumIncomingValues() == 2) { 7543 // Try to match and vectorize a horizontal reduction. 7544 if (vectorizeRootInstruction(P, getReductionValue(DT, P, BB, LI), BB, R, 7545 TTI)) { 7546 Changed = true; 7547 it = BB->begin(); 7548 e = BB->end(); 7549 continue; 7550 } 7551 } 7552 // Try to vectorize the incoming values of the PHI, to catch reductions 7553 // that feed into PHIs. 7554 for (unsigned I = 0, E = P->getNumIncomingValues(); I != E; I++) { 7555 // Skip if the incoming block is the current BB for now. Also, bypass 7556 // unreachable IR for efficiency and to avoid crashing. 7557 // TODO: Collect the skipped incoming values and try to vectorize them 7558 // after processing BB. 7559 if (BB == P->getIncomingBlock(I) || 7560 !DT->isReachableFromEntry(P->getIncomingBlock(I))) 7561 continue; 7562 7563 Changed |= vectorizeRootInstruction(nullptr, P->getIncomingValue(I), 7564 P->getIncomingBlock(I), R, TTI); 7565 } 7566 continue; 7567 } 7568 7569 // Ran into an instruction without users, like terminator, or function call 7570 // with ignored return value, store. Ignore unused instructions (basing on 7571 // instruction type, except for CallInst and InvokeInst). 7572 if (it->use_empty() && (it->getType()->isVoidTy() || isa<CallInst>(it) || 7573 isa<InvokeInst>(it))) { 7574 KeyNodes.insert(&*it); 7575 bool OpsChanged = false; 7576 if (ShouldStartVectorizeHorAtStore || !isa<StoreInst>(it)) { 7577 for (auto *V : it->operand_values()) { 7578 // Try to match and vectorize a horizontal reduction. 7579 OpsChanged |= vectorizeRootInstruction(nullptr, V, BB, R, TTI); 7580 } 7581 } 7582 // Start vectorization of post-process list of instructions from the 7583 // top-tree instructions to try to vectorize as many instructions as 7584 // possible. 7585 OpsChanged |= vectorizeSimpleInstructions(PostProcessInstructions, BB, R); 7586 if (OpsChanged) { 7587 // We would like to start over since some instructions are deleted 7588 // and the iterator may become invalid value. 7589 Changed = true; 7590 it = BB->begin(); 7591 e = BB->end(); 7592 continue; 7593 } 7594 } 7595 7596 if (isa<InsertElementInst>(it) || isa<CmpInst>(it) || 7597 isa<InsertValueInst>(it)) 7598 PostProcessInstructions.push_back(&*it); 7599 } 7600 7601 return Changed; 7602 } 7603 7604 bool SLPVectorizerPass::vectorizeGEPIndices(BasicBlock *BB, BoUpSLP &R) { 7605 auto Changed = false; 7606 for (auto &Entry : GEPs) { 7607 // If the getelementptr list has fewer than two elements, there's nothing 7608 // to do. 7609 if (Entry.second.size() < 2) 7610 continue; 7611 7612 LLVM_DEBUG(dbgs() << "SLP: Analyzing a getelementptr list of length " 7613 << Entry.second.size() << ".\n"); 7614 7615 // Process the GEP list in chunks suitable for the target's supported 7616 // vector size. If a vector register can't hold 1 element, we are done. We 7617 // are trying to vectorize the index computations, so the maximum number of 7618 // elements is based on the size of the index expression, rather than the 7619 // size of the GEP itself (the target's pointer size). 7620 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 7621 unsigned EltSize = R.getVectorElementSize(*Entry.second[0]->idx_begin()); 7622 if (MaxVecRegSize < EltSize) 7623 continue; 7624 7625 unsigned MaxElts = MaxVecRegSize / EltSize; 7626 for (unsigned BI = 0, BE = Entry.second.size(); BI < BE; BI += MaxElts) { 7627 auto Len = std::min<unsigned>(BE - BI, MaxElts); 7628 ArrayRef<GetElementPtrInst *> GEPList(&Entry.second[BI], Len); 7629 7630 // Initialize a set a candidate getelementptrs. Note that we use a 7631 // SetVector here to preserve program order. If the index computations 7632 // are vectorizable and begin with loads, we want to minimize the chance 7633 // of having to reorder them later. 7634 SetVector<Value *> Candidates(GEPList.begin(), GEPList.end()); 7635 7636 // Some of the candidates may have already been vectorized after we 7637 // initially collected them. If so, they are marked as deleted, so remove 7638 // them from the set of candidates. 7639 Candidates.remove_if( 7640 [&R](Value *I) { return R.isDeleted(cast<Instruction>(I)); }); 7641 7642 // Remove from the set of candidates all pairs of getelementptrs with 7643 // constant differences. Such getelementptrs are likely not good 7644 // candidates for vectorization in a bottom-up phase since one can be 7645 // computed from the other. We also ensure all candidate getelementptr 7646 // indices are unique. 7647 for (int I = 0, E = GEPList.size(); I < E && Candidates.size() > 1; ++I) { 7648 auto *GEPI = GEPList[I]; 7649 if (!Candidates.count(GEPI)) 7650 continue; 7651 auto *SCEVI = SE->getSCEV(GEPList[I]); 7652 for (int J = I + 1; J < E && Candidates.size() > 1; ++J) { 7653 auto *GEPJ = GEPList[J]; 7654 auto *SCEVJ = SE->getSCEV(GEPList[J]); 7655 if (isa<SCEVConstant>(SE->getMinusSCEV(SCEVI, SCEVJ))) { 7656 Candidates.remove(GEPI); 7657 Candidates.remove(GEPJ); 7658 } else if (GEPI->idx_begin()->get() == GEPJ->idx_begin()->get()) { 7659 Candidates.remove(GEPJ); 7660 } 7661 } 7662 } 7663 7664 // We break out of the above computation as soon as we know there are 7665 // fewer than two candidates remaining. 7666 if (Candidates.size() < 2) 7667 continue; 7668 7669 // Add the single, non-constant index of each candidate to the bundle. We 7670 // ensured the indices met these constraints when we originally collected 7671 // the getelementptrs. 7672 SmallVector<Value *, 16> Bundle(Candidates.size()); 7673 auto BundleIndex = 0u; 7674 for (auto *V : Candidates) { 7675 auto *GEP = cast<GetElementPtrInst>(V); 7676 auto *GEPIdx = GEP->idx_begin()->get(); 7677 assert(GEP->getNumIndices() == 1 || !isa<Constant>(GEPIdx)); 7678 Bundle[BundleIndex++] = GEPIdx; 7679 } 7680 7681 // Try and vectorize the indices. We are currently only interested in 7682 // gather-like cases of the form: 7683 // 7684 // ... = g[a[0] - b[0]] + g[a[1] - b[1]] + ... 7685 // 7686 // where the loads of "a", the loads of "b", and the subtractions can be 7687 // performed in parallel. It's likely that detecting this pattern in a 7688 // bottom-up phase will be simpler and less costly than building a 7689 // full-blown top-down phase beginning at the consecutive loads. 7690 Changed |= tryToVectorizeList(Bundle, R); 7691 } 7692 } 7693 return Changed; 7694 } 7695 7696 bool SLPVectorizerPass::vectorizeStoreChains(BoUpSLP &R) { 7697 bool Changed = false; 7698 // Attempt to sort and vectorize each of the store-groups. 7699 for (StoreListMap::iterator it = Stores.begin(), e = Stores.end(); it != e; 7700 ++it) { 7701 if (it->second.size() < 2) 7702 continue; 7703 7704 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " 7705 << it->second.size() << ".\n"); 7706 7707 Changed |= vectorizeStores(it->second, R); 7708 } 7709 return Changed; 7710 } 7711 7712 char SLPVectorizer::ID = 0; 7713 7714 static const char lv_name[] = "SLP Vectorizer"; 7715 7716 INITIALIZE_PASS_BEGIN(SLPVectorizer, SV_NAME, lv_name, false, false) 7717 INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass) 7718 INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass) 7719 INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker) 7720 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass) 7721 INITIALIZE_PASS_DEPENDENCY(LoopSimplify) 7722 INITIALIZE_PASS_DEPENDENCY(DemandedBitsWrapperPass) 7723 INITIALIZE_PASS_DEPENDENCY(OptimizationRemarkEmitterWrapperPass) 7724 INITIALIZE_PASS_DEPENDENCY(InjectTLIMappingsLegacy) 7725 INITIALIZE_PASS_END(SLPVectorizer, SV_NAME, lv_name, false, false) 7726 7727 Pass *llvm::createSLPVectorizerPass() { return new SLPVectorizer(); } 7728