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 /// Mask will return the Shuffle Mask equivalent to the extracted elements. 291 /// TODO: Can we split off and reuse the shuffle mask detection from 292 /// TargetTransformInfo::getInstructionThroughput? 293 static Optional<TargetTransformInfo::ShuffleKind> 294 isShuffle(ArrayRef<Value *> VL, SmallVectorImpl<int> &Mask) { 295 auto *EI0 = cast<ExtractElementInst>(VL[0]); 296 unsigned Size = 297 cast<FixedVectorType>(EI0->getVectorOperandType())->getNumElements(); 298 Value *Vec1 = nullptr; 299 Value *Vec2 = nullptr; 300 enum ShuffleMode { Unknown, Select, Permute }; 301 ShuffleMode CommonShuffleMode = Unknown; 302 for (unsigned I = 0, E = VL.size(); I < E; ++I) { 303 auto *EI = cast<ExtractElementInst>(VL[I]); 304 auto *Vec = EI->getVectorOperand(); 305 // All vector operands must have the same number of vector elements. 306 if (cast<FixedVectorType>(Vec->getType())->getNumElements() != Size) 307 return None; 308 auto *Idx = dyn_cast<ConstantInt>(EI->getIndexOperand()); 309 if (!Idx) 310 return None; 311 // Undefined behavior if Idx is negative or >= Size. 312 if (Idx->getValue().uge(Size)) { 313 Mask.push_back(UndefMaskElem); 314 continue; 315 } 316 unsigned IntIdx = Idx->getValue().getZExtValue(); 317 Mask.push_back(IntIdx); 318 // We can extractelement from undef or poison vector. 319 if (isa<UndefValue>(Vec)) 320 continue; 321 // For correct shuffling we have to have at most 2 different vector operands 322 // in all extractelement instructions. 323 if (!Vec1 || Vec1 == Vec) 324 Vec1 = Vec; 325 else if (!Vec2 || Vec2 == Vec) 326 Vec2 = Vec; 327 else 328 return None; 329 if (CommonShuffleMode == Permute) 330 continue; 331 // If the extract index is not the same as the operation number, it is a 332 // permutation. 333 if (IntIdx != I) { 334 CommonShuffleMode = Permute; 335 continue; 336 } 337 CommonShuffleMode = Select; 338 } 339 // If we're not crossing lanes in different vectors, consider it as blending. 340 if (CommonShuffleMode == Select && Vec2) 341 return TargetTransformInfo::SK_Select; 342 // If Vec2 was never used, we have a permutation of a single vector, otherwise 343 // we have permutation of 2 vectors. 344 return Vec2 ? TargetTransformInfo::SK_PermuteTwoSrc 345 : TargetTransformInfo::SK_PermuteSingleSrc; 346 } 347 348 namespace { 349 350 /// Main data required for vectorization of instructions. 351 struct InstructionsState { 352 /// The very first instruction in the list with the main opcode. 353 Value *OpValue = nullptr; 354 355 /// The main/alternate instruction. 356 Instruction *MainOp = nullptr; 357 Instruction *AltOp = nullptr; 358 359 /// The main/alternate opcodes for the list of instructions. 360 unsigned getOpcode() const { 361 return MainOp ? MainOp->getOpcode() : 0; 362 } 363 364 unsigned getAltOpcode() const { 365 return AltOp ? AltOp->getOpcode() : 0; 366 } 367 368 /// Some of the instructions in the list have alternate opcodes. 369 bool isAltShuffle() const { return getOpcode() != getAltOpcode(); } 370 371 bool isOpcodeOrAlt(Instruction *I) const { 372 unsigned CheckedOpcode = I->getOpcode(); 373 return getOpcode() == CheckedOpcode || getAltOpcode() == CheckedOpcode; 374 } 375 376 InstructionsState() = delete; 377 InstructionsState(Value *OpValue, Instruction *MainOp, Instruction *AltOp) 378 : OpValue(OpValue), MainOp(MainOp), AltOp(AltOp) {} 379 }; 380 381 } // end anonymous namespace 382 383 /// Chooses the correct key for scheduling data. If \p Op has the same (or 384 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is \p 385 /// OpValue. 386 static Value *isOneOf(const InstructionsState &S, Value *Op) { 387 auto *I = dyn_cast<Instruction>(Op); 388 if (I && S.isOpcodeOrAlt(I)) 389 return Op; 390 return S.OpValue; 391 } 392 393 /// \returns true if \p Opcode is allowed as part of of the main/alternate 394 /// instruction for SLP vectorization. 395 /// 396 /// Example of unsupported opcode is SDIV that can potentially cause UB if the 397 /// "shuffled out" lane would result in division by zero. 398 static bool isValidForAlternation(unsigned Opcode) { 399 if (Instruction::isIntDivRem(Opcode)) 400 return false; 401 402 return true; 403 } 404 405 /// \returns analysis of the Instructions in \p VL described in 406 /// InstructionsState, the Opcode that we suppose the whole list 407 /// could be vectorized even if its structure is diverse. 408 static InstructionsState getSameOpcode(ArrayRef<Value *> VL, 409 unsigned BaseIndex = 0) { 410 // Make sure these are all Instructions. 411 if (llvm::any_of(VL, [](Value *V) { return !isa<Instruction>(V); })) 412 return InstructionsState(VL[BaseIndex], nullptr, nullptr); 413 414 bool IsCastOp = isa<CastInst>(VL[BaseIndex]); 415 bool IsBinOp = isa<BinaryOperator>(VL[BaseIndex]); 416 unsigned Opcode = cast<Instruction>(VL[BaseIndex])->getOpcode(); 417 unsigned AltOpcode = Opcode; 418 unsigned AltIndex = BaseIndex; 419 420 // Check for one alternate opcode from another BinaryOperator. 421 // TODO - generalize to support all operators (types, calls etc.). 422 for (int Cnt = 0, E = VL.size(); Cnt < E; Cnt++) { 423 unsigned InstOpcode = cast<Instruction>(VL[Cnt])->getOpcode(); 424 if (IsBinOp && isa<BinaryOperator>(VL[Cnt])) { 425 if (InstOpcode == Opcode || InstOpcode == AltOpcode) 426 continue; 427 if (Opcode == AltOpcode && isValidForAlternation(InstOpcode) && 428 isValidForAlternation(Opcode)) { 429 AltOpcode = InstOpcode; 430 AltIndex = Cnt; 431 continue; 432 } 433 } else if (IsCastOp && isa<CastInst>(VL[Cnt])) { 434 Type *Ty0 = cast<Instruction>(VL[BaseIndex])->getOperand(0)->getType(); 435 Type *Ty1 = cast<Instruction>(VL[Cnt])->getOperand(0)->getType(); 436 if (Ty0 == Ty1) { 437 if (InstOpcode == Opcode || InstOpcode == AltOpcode) 438 continue; 439 if (Opcode == AltOpcode) { 440 assert(isValidForAlternation(Opcode) && 441 isValidForAlternation(InstOpcode) && 442 "Cast isn't safe for alternation, logic needs to be updated!"); 443 AltOpcode = InstOpcode; 444 AltIndex = Cnt; 445 continue; 446 } 447 } 448 } else if (InstOpcode == Opcode || InstOpcode == AltOpcode) 449 continue; 450 return InstructionsState(VL[BaseIndex], nullptr, nullptr); 451 } 452 453 return InstructionsState(VL[BaseIndex], cast<Instruction>(VL[BaseIndex]), 454 cast<Instruction>(VL[AltIndex])); 455 } 456 457 /// \returns true if all of the values in \p VL have the same type or false 458 /// otherwise. 459 static bool allSameType(ArrayRef<Value *> VL) { 460 Type *Ty = VL[0]->getType(); 461 for (int i = 1, e = VL.size(); i < e; i++) 462 if (VL[i]->getType() != Ty) 463 return false; 464 465 return true; 466 } 467 468 /// \returns True if Extract{Value,Element} instruction extracts element Idx. 469 static Optional<unsigned> getExtractIndex(Instruction *E) { 470 unsigned Opcode = E->getOpcode(); 471 assert((Opcode == Instruction::ExtractElement || 472 Opcode == Instruction::ExtractValue) && 473 "Expected extractelement or extractvalue instruction."); 474 if (Opcode == Instruction::ExtractElement) { 475 auto *CI = dyn_cast<ConstantInt>(E->getOperand(1)); 476 if (!CI) 477 return None; 478 return CI->getZExtValue(); 479 } 480 ExtractValueInst *EI = cast<ExtractValueInst>(E); 481 if (EI->getNumIndices() != 1) 482 return None; 483 return *EI->idx_begin(); 484 } 485 486 /// \returns True if in-tree use also needs extract. This refers to 487 /// possible scalar operand in vectorized instruction. 488 static bool InTreeUserNeedToExtract(Value *Scalar, Instruction *UserInst, 489 TargetLibraryInfo *TLI) { 490 unsigned Opcode = UserInst->getOpcode(); 491 switch (Opcode) { 492 case Instruction::Load: { 493 LoadInst *LI = cast<LoadInst>(UserInst); 494 return (LI->getPointerOperand() == Scalar); 495 } 496 case Instruction::Store: { 497 StoreInst *SI = cast<StoreInst>(UserInst); 498 return (SI->getPointerOperand() == Scalar); 499 } 500 case Instruction::Call: { 501 CallInst *CI = cast<CallInst>(UserInst); 502 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 503 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 504 if (hasVectorInstrinsicScalarOpd(ID, i)) 505 return (CI->getArgOperand(i) == Scalar); 506 } 507 LLVM_FALLTHROUGH; 508 } 509 default: 510 return false; 511 } 512 } 513 514 /// \returns the AA location that is being access by the instruction. 515 static MemoryLocation getLocation(Instruction *I, AAResults *AA) { 516 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 517 return MemoryLocation::get(SI); 518 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 519 return MemoryLocation::get(LI); 520 return MemoryLocation(); 521 } 522 523 /// \returns True if the instruction is not a volatile or atomic load/store. 524 static bool isSimple(Instruction *I) { 525 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 526 return LI->isSimple(); 527 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 528 return SI->isSimple(); 529 if (MemIntrinsic *MI = dyn_cast<MemIntrinsic>(I)) 530 return !MI->isVolatile(); 531 return true; 532 } 533 534 namespace llvm { 535 536 static void inversePermutation(ArrayRef<unsigned> Indices, 537 SmallVectorImpl<int> &Mask) { 538 Mask.clear(); 539 const unsigned E = Indices.size(); 540 Mask.resize(E, E + 1); 541 for (unsigned I = 0; I < E; ++I) 542 Mask[Indices[I]] = I; 543 } 544 545 namespace slpvectorizer { 546 547 /// Bottom Up SLP Vectorizer. 548 class BoUpSLP { 549 struct TreeEntry; 550 struct ScheduleData; 551 552 public: 553 using ValueList = SmallVector<Value *, 8>; 554 using InstrList = SmallVector<Instruction *, 16>; 555 using ValueSet = SmallPtrSet<Value *, 16>; 556 using StoreList = SmallVector<StoreInst *, 8>; 557 using ExtraValueToDebugLocsMap = 558 MapVector<Value *, SmallVector<Instruction *, 2>>; 559 using OrdersType = SmallVector<unsigned, 4>; 560 561 BoUpSLP(Function *Func, ScalarEvolution *Se, TargetTransformInfo *Tti, 562 TargetLibraryInfo *TLi, AAResults *Aa, LoopInfo *Li, 563 DominatorTree *Dt, AssumptionCache *AC, DemandedBits *DB, 564 const DataLayout *DL, OptimizationRemarkEmitter *ORE) 565 : F(Func), SE(Se), TTI(Tti), TLI(TLi), AA(Aa), LI(Li), DT(Dt), AC(AC), 566 DB(DB), DL(DL), ORE(ORE), Builder(Se->getContext()) { 567 CodeMetrics::collectEphemeralValues(F, AC, EphValues); 568 // Use the vector register size specified by the target unless overridden 569 // by a command-line option. 570 // TODO: It would be better to limit the vectorization factor based on 571 // data type rather than just register size. For example, x86 AVX has 572 // 256-bit registers, but it does not support integer operations 573 // at that width (that requires AVX2). 574 if (MaxVectorRegSizeOption.getNumOccurrences()) 575 MaxVecRegSize = MaxVectorRegSizeOption; 576 else 577 MaxVecRegSize = 578 TTI->getRegisterBitWidth(TargetTransformInfo::RGK_FixedWidthVector) 579 .getFixedSize(); 580 581 if (MinVectorRegSizeOption.getNumOccurrences()) 582 MinVecRegSize = MinVectorRegSizeOption; 583 else 584 MinVecRegSize = TTI->getMinVectorRegisterBitWidth(); 585 } 586 587 /// Vectorize the tree that starts with the elements in \p VL. 588 /// Returns the vectorized root. 589 Value *vectorizeTree(); 590 591 /// Vectorize the tree but with the list of externally used values \p 592 /// ExternallyUsedValues. Values in this MapVector can be replaced but the 593 /// generated extractvalue instructions. 594 Value *vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues); 595 596 /// \returns the cost incurred by unwanted spills and fills, caused by 597 /// holding live values over call sites. 598 InstructionCost getSpillCost() const; 599 600 /// \returns the vectorization cost of the subtree that starts at \p VL. 601 /// A negative number means that this is profitable. 602 InstructionCost getTreeCost(); 603 604 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 605 /// the purpose of scheduling and extraction in the \p UserIgnoreLst. 606 void buildTree(ArrayRef<Value *> Roots, 607 ArrayRef<Value *> UserIgnoreLst = None); 608 609 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 610 /// the purpose of scheduling and extraction in the \p UserIgnoreLst taking 611 /// into account (and updating it, if required) list of externally used 612 /// values stored in \p ExternallyUsedValues. 613 void buildTree(ArrayRef<Value *> Roots, 614 ExtraValueToDebugLocsMap &ExternallyUsedValues, 615 ArrayRef<Value *> UserIgnoreLst = None); 616 617 /// Clear the internal data structures that are created by 'buildTree'. 618 void deleteTree() { 619 VectorizableTree.clear(); 620 ScalarToTreeEntry.clear(); 621 MustGather.clear(); 622 ExternalUses.clear(); 623 NumOpsWantToKeepOrder.clear(); 624 NumOpsWantToKeepOriginalOrder = 0; 625 for (auto &Iter : BlocksSchedules) { 626 BlockScheduling *BS = Iter.second.get(); 627 BS->clear(); 628 } 629 MinBWs.clear(); 630 InstrElementSize.clear(); 631 } 632 633 unsigned getTreeSize() const { return VectorizableTree.size(); } 634 635 /// Perform LICM and CSE on the newly generated gather sequences. 636 void optimizeGatherSequence(); 637 638 /// \returns The best order of instructions for vectorization. 639 Optional<ArrayRef<unsigned>> bestOrder() const { 640 assert(llvm::all_of( 641 NumOpsWantToKeepOrder, 642 [this](const decltype(NumOpsWantToKeepOrder)::value_type &D) { 643 return D.getFirst().size() == 644 VectorizableTree[0]->Scalars.size(); 645 }) && 646 "All orders must have the same size as number of instructions in " 647 "tree node."); 648 auto I = std::max_element( 649 NumOpsWantToKeepOrder.begin(), NumOpsWantToKeepOrder.end(), 650 [](const decltype(NumOpsWantToKeepOrder)::value_type &D1, 651 const decltype(NumOpsWantToKeepOrder)::value_type &D2) { 652 return D1.second < D2.second; 653 }); 654 if (I == NumOpsWantToKeepOrder.end() || 655 I->getSecond() <= NumOpsWantToKeepOriginalOrder) 656 return None; 657 658 return makeArrayRef(I->getFirst()); 659 } 660 661 /// Builds the correct order for root instructions. 662 /// If some leaves have the same instructions to be vectorized, we may 663 /// incorrectly evaluate the best order for the root node (it is built for the 664 /// vector of instructions without repeated instructions and, thus, has less 665 /// elements than the root node). This function builds the correct order for 666 /// the root node. 667 /// For example, if the root node is \<a+b, a+c, a+d, f+e\>, then the leaves 668 /// are \<a, a, a, f\> and \<b, c, d, e\>. When we try to vectorize the first 669 /// leaf, it will be shrink to \<a, b\>. If instructions in this leaf should 670 /// be reordered, the best order will be \<1, 0\>. We need to extend this 671 /// order for the root node. For the root node this order should look like 672 /// \<3, 0, 1, 2\>. This function extends the order for the reused 673 /// instructions. 674 void findRootOrder(OrdersType &Order) { 675 // If the leaf has the same number of instructions to vectorize as the root 676 // - order must be set already. 677 unsigned RootSize = VectorizableTree[0]->Scalars.size(); 678 if (Order.size() == RootSize) 679 return; 680 SmallVector<unsigned, 4> RealOrder(Order.size()); 681 std::swap(Order, RealOrder); 682 SmallVector<int, 4> Mask; 683 inversePermutation(RealOrder, Mask); 684 Order.assign(Mask.begin(), Mask.end()); 685 // The leaf has less number of instructions - need to find the true order of 686 // the root. 687 // Scan the nodes starting from the leaf back to the root. 688 const TreeEntry *PNode = VectorizableTree.back().get(); 689 SmallVector<const TreeEntry *, 4> Nodes(1, PNode); 690 SmallPtrSet<const TreeEntry *, 4> Visited; 691 while (!Nodes.empty() && Order.size() != RootSize) { 692 const TreeEntry *PNode = Nodes.pop_back_val(); 693 if (!Visited.insert(PNode).second) 694 continue; 695 const TreeEntry &Node = *PNode; 696 for (const EdgeInfo &EI : Node.UserTreeIndices) 697 if (EI.UserTE) 698 Nodes.push_back(EI.UserTE); 699 if (Node.ReuseShuffleIndices.empty()) 700 continue; 701 // Build the order for the parent node. 702 OrdersType NewOrder(Node.ReuseShuffleIndices.size(), RootSize); 703 SmallVector<unsigned, 4> OrderCounter(Order.size(), 0); 704 // The algorithm of the order extension is: 705 // 1. Calculate the number of the same instructions for the order. 706 // 2. Calculate the index of the new order: total number of instructions 707 // with order less than the order of the current instruction + reuse 708 // number of the current instruction. 709 // 3. The new order is just the index of the instruction in the original 710 // vector of the instructions. 711 for (unsigned I : Node.ReuseShuffleIndices) 712 ++OrderCounter[Order[I]]; 713 SmallVector<unsigned, 4> CurrentCounter(Order.size(), 0); 714 for (unsigned I = 0, E = Node.ReuseShuffleIndices.size(); I < E; ++I) { 715 unsigned ReusedIdx = Node.ReuseShuffleIndices[I]; 716 unsigned OrderIdx = Order[ReusedIdx]; 717 unsigned NewIdx = 0; 718 for (unsigned J = 0; J < OrderIdx; ++J) 719 NewIdx += OrderCounter[J]; 720 NewIdx += CurrentCounter[OrderIdx]; 721 ++CurrentCounter[OrderIdx]; 722 assert(NewOrder[NewIdx] == RootSize && 723 "The order index should not be written already."); 724 NewOrder[NewIdx] = I; 725 } 726 std::swap(Order, NewOrder); 727 } 728 assert(Order.size() == RootSize && 729 "Root node is expected or the size of the order must be the same as " 730 "the number of elements in the root node."); 731 assert(llvm::all_of(Order, 732 [RootSize](unsigned Val) { return Val != RootSize; }) && 733 "All indices must be initialized"); 734 } 735 736 /// \return The vector element size in bits to use when vectorizing the 737 /// expression tree ending at \p V. If V is a store, the size is the width of 738 /// the stored value. Otherwise, the size is the width of the largest loaded 739 /// value reaching V. This method is used by the vectorizer to calculate 740 /// vectorization factors. 741 unsigned getVectorElementSize(Value *V); 742 743 /// Compute the minimum type sizes required to represent the entries in a 744 /// vectorizable tree. 745 void computeMinimumValueSizes(); 746 747 // \returns maximum vector register size as set by TTI or overridden by cl::opt. 748 unsigned getMaxVecRegSize() const { 749 return MaxVecRegSize; 750 } 751 752 // \returns minimum vector register size as set by cl::opt. 753 unsigned getMinVecRegSize() const { 754 return MinVecRegSize; 755 } 756 757 unsigned getMaximumVF(unsigned ElemWidth, unsigned Opcode) const { 758 unsigned MaxVF = MaxVFOption.getNumOccurrences() ? 759 MaxVFOption : TTI->getMaximumVF(ElemWidth, Opcode); 760 return MaxVF ? MaxVF : UINT_MAX; 761 } 762 763 /// Check if homogeneous aggregate is isomorphic to some VectorType. 764 /// Accepts homogeneous multidimensional aggregate of scalars/vectors like 765 /// {[4 x i16], [4 x i16]}, { <2 x float>, <2 x float> }, 766 /// {{{i16, i16}, {i16, i16}}, {{i16, i16}, {i16, i16}}} and so on. 767 /// 768 /// \returns number of elements in vector if isomorphism exists, 0 otherwise. 769 unsigned canMapToVector(Type *T, const DataLayout &DL) const; 770 771 /// \returns True if the VectorizableTree is both tiny and not fully 772 /// vectorizable. We do not vectorize such trees. 773 bool isTreeTinyAndNotFullyVectorizable() const; 774 775 /// Assume that a legal-sized 'or'-reduction of shifted/zexted loaded values 776 /// can be load combined in the backend. Load combining may not be allowed in 777 /// the IR optimizer, so we do not want to alter the pattern. For example, 778 /// partially transforming a scalar bswap() pattern into vector code is 779 /// effectively impossible for the backend to undo. 780 /// TODO: If load combining is allowed in the IR optimizer, this analysis 781 /// may not be necessary. 782 bool isLoadCombineReductionCandidate(RecurKind RdxKind) const; 783 784 /// Assume that a vector of stores of bitwise-or/shifted/zexted loaded values 785 /// can be load combined in the backend. Load combining may not be allowed in 786 /// the IR optimizer, so we do not want to alter the pattern. For example, 787 /// partially transforming a scalar bswap() pattern into vector code is 788 /// effectively impossible for the backend to undo. 789 /// TODO: If load combining is allowed in the IR optimizer, this analysis 790 /// may not be necessary. 791 bool isLoadCombineCandidate() const; 792 793 OptimizationRemarkEmitter *getORE() { return ORE; } 794 795 /// This structure holds any data we need about the edges being traversed 796 /// during buildTree_rec(). We keep track of: 797 /// (i) the user TreeEntry index, and 798 /// (ii) the index of the edge. 799 struct EdgeInfo { 800 EdgeInfo() = default; 801 EdgeInfo(TreeEntry *UserTE, unsigned EdgeIdx) 802 : UserTE(UserTE), EdgeIdx(EdgeIdx) {} 803 /// The user TreeEntry. 804 TreeEntry *UserTE = nullptr; 805 /// The operand index of the use. 806 unsigned EdgeIdx = UINT_MAX; 807 #ifndef NDEBUG 808 friend inline raw_ostream &operator<<(raw_ostream &OS, 809 const BoUpSLP::EdgeInfo &EI) { 810 EI.dump(OS); 811 return OS; 812 } 813 /// Debug print. 814 void dump(raw_ostream &OS) const { 815 OS << "{User:" << (UserTE ? std::to_string(UserTE->Idx) : "null") 816 << " EdgeIdx:" << EdgeIdx << "}"; 817 } 818 LLVM_DUMP_METHOD void dump() const { dump(dbgs()); } 819 #endif 820 }; 821 822 /// A helper data structure to hold the operands of a vector of instructions. 823 /// This supports a fixed vector length for all operand vectors. 824 class VLOperands { 825 /// For each operand we need (i) the value, and (ii) the opcode that it 826 /// would be attached to if the expression was in a left-linearized form. 827 /// This is required to avoid illegal operand reordering. 828 /// For example: 829 /// \verbatim 830 /// 0 Op1 831 /// |/ 832 /// Op1 Op2 Linearized + Op2 833 /// \ / ----------> |/ 834 /// - - 835 /// 836 /// Op1 - Op2 (0 + Op1) - Op2 837 /// \endverbatim 838 /// 839 /// Value Op1 is attached to a '+' operation, and Op2 to a '-'. 840 /// 841 /// Another way to think of this is to track all the operations across the 842 /// path from the operand all the way to the root of the tree and to 843 /// calculate the operation that corresponds to this path. For example, the 844 /// path from Op2 to the root crosses the RHS of the '-', therefore the 845 /// corresponding operation is a '-' (which matches the one in the 846 /// linearized tree, as shown above). 847 /// 848 /// For lack of a better term, we refer to this operation as Accumulated 849 /// Path Operation (APO). 850 struct OperandData { 851 OperandData() = default; 852 OperandData(Value *V, bool APO, bool IsUsed) 853 : V(V), APO(APO), IsUsed(IsUsed) {} 854 /// The operand value. 855 Value *V = nullptr; 856 /// TreeEntries only allow a single opcode, or an alternate sequence of 857 /// them (e.g, +, -). Therefore, we can safely use a boolean value for the 858 /// APO. It is set to 'true' if 'V' is attached to an inverse operation 859 /// in the left-linearized form (e.g., Sub/Div), and 'false' otherwise 860 /// (e.g., Add/Mul) 861 bool APO = false; 862 /// Helper data for the reordering function. 863 bool IsUsed = false; 864 }; 865 866 /// During operand reordering, we are trying to select the operand at lane 867 /// that matches best with the operand at the neighboring lane. Our 868 /// selection is based on the type of value we are looking for. For example, 869 /// if the neighboring lane has a load, we need to look for a load that is 870 /// accessing a consecutive address. These strategies are summarized in the 871 /// 'ReorderingMode' enumerator. 872 enum class ReorderingMode { 873 Load, ///< Matching loads to consecutive memory addresses 874 Opcode, ///< Matching instructions based on opcode (same or alternate) 875 Constant, ///< Matching constants 876 Splat, ///< Matching the same instruction multiple times (broadcast) 877 Failed, ///< We failed to create a vectorizable group 878 }; 879 880 using OperandDataVec = SmallVector<OperandData, 2>; 881 882 /// A vector of operand vectors. 883 SmallVector<OperandDataVec, 4> OpsVec; 884 885 const DataLayout &DL; 886 ScalarEvolution &SE; 887 const BoUpSLP &R; 888 889 /// \returns the operand data at \p OpIdx and \p Lane. 890 OperandData &getData(unsigned OpIdx, unsigned Lane) { 891 return OpsVec[OpIdx][Lane]; 892 } 893 894 /// \returns the operand data at \p OpIdx and \p Lane. Const version. 895 const OperandData &getData(unsigned OpIdx, unsigned Lane) const { 896 return OpsVec[OpIdx][Lane]; 897 } 898 899 /// Clears the used flag for all entries. 900 void clearUsed() { 901 for (unsigned OpIdx = 0, NumOperands = getNumOperands(); 902 OpIdx != NumOperands; ++OpIdx) 903 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 904 ++Lane) 905 OpsVec[OpIdx][Lane].IsUsed = false; 906 } 907 908 /// Swap the operand at \p OpIdx1 with that one at \p OpIdx2. 909 void swap(unsigned OpIdx1, unsigned OpIdx2, unsigned Lane) { 910 std::swap(OpsVec[OpIdx1][Lane], OpsVec[OpIdx2][Lane]); 911 } 912 913 // The hard-coded scores listed here are not very important. When computing 914 // the scores of matching one sub-tree with another, we are basically 915 // counting the number of values that are matching. So even if all scores 916 // are set to 1, we would still get a decent matching result. 917 // However, sometimes we have to break ties. For example we may have to 918 // choose between matching loads vs matching opcodes. This is what these 919 // scores are helping us with: they provide the order of preference. 920 921 /// Loads from consecutive memory addresses, e.g. load(A[i]), load(A[i+1]). 922 static const int ScoreConsecutiveLoads = 3; 923 /// ExtractElementInst from same vector and consecutive indexes. 924 static const int ScoreConsecutiveExtracts = 3; 925 /// Constants. 926 static const int ScoreConstants = 2; 927 /// Instructions with the same opcode. 928 static const int ScoreSameOpcode = 2; 929 /// Instructions with alt opcodes (e.g, add + sub). 930 static const int ScoreAltOpcodes = 1; 931 /// Identical instructions (a.k.a. splat or broadcast). 932 static const int ScoreSplat = 1; 933 /// Matching with an undef is preferable to failing. 934 static const int ScoreUndef = 1; 935 /// Score for failing to find a decent match. 936 static const int ScoreFail = 0; 937 /// User exteranl to the vectorized code. 938 static const int ExternalUseCost = 1; 939 /// The user is internal but in a different lane. 940 static const int UserInDiffLaneCost = ExternalUseCost; 941 942 /// \returns the score of placing \p V1 and \p V2 in consecutive lanes. 943 static int getShallowScore(Value *V1, Value *V2, const DataLayout &DL, 944 ScalarEvolution &SE) { 945 auto *LI1 = dyn_cast<LoadInst>(V1); 946 auto *LI2 = dyn_cast<LoadInst>(V2); 947 if (LI1 && LI2) { 948 if (LI1->getParent() != LI2->getParent()) 949 return VLOperands::ScoreFail; 950 951 Optional<int> Dist = 952 getPointersDiff(LI1->getPointerOperand(), LI2->getPointerOperand(), 953 DL, SE, /*StrictCheck=*/true); 954 return (Dist && *Dist == 1) ? VLOperands::ScoreConsecutiveLoads 955 : VLOperands::ScoreFail; 956 } 957 958 auto *C1 = dyn_cast<Constant>(V1); 959 auto *C2 = dyn_cast<Constant>(V2); 960 if (C1 && C2) 961 return VLOperands::ScoreConstants; 962 963 // Extracts from consecutive indexes of the same vector better score as 964 // the extracts could be optimized away. 965 Value *EV; 966 ConstantInt *Ex1Idx, *Ex2Idx; 967 if (match(V1, m_ExtractElt(m_Value(EV), m_ConstantInt(Ex1Idx))) && 968 match(V2, m_ExtractElt(m_Deferred(EV), m_ConstantInt(Ex2Idx))) && 969 Ex1Idx->getZExtValue() + 1 == Ex2Idx->getZExtValue()) 970 return VLOperands::ScoreConsecutiveExtracts; 971 972 auto *I1 = dyn_cast<Instruction>(V1); 973 auto *I2 = dyn_cast<Instruction>(V2); 974 if (I1 && I2) { 975 if (I1 == I2) 976 return VLOperands::ScoreSplat; 977 InstructionsState S = getSameOpcode({I1, I2}); 978 // Note: Only consider instructions with <= 2 operands to avoid 979 // complexity explosion. 980 if (S.getOpcode() && S.MainOp->getNumOperands() <= 2) 981 return S.isAltShuffle() ? VLOperands::ScoreAltOpcodes 982 : VLOperands::ScoreSameOpcode; 983 } 984 985 if (isa<UndefValue>(V2)) 986 return VLOperands::ScoreUndef; 987 988 return VLOperands::ScoreFail; 989 } 990 991 /// Holds the values and their lane that are taking part in the look-ahead 992 /// score calculation. This is used in the external uses cost calculation. 993 SmallDenseMap<Value *, int> InLookAheadValues; 994 995 /// \Returns the additinal cost due to uses of \p LHS and \p RHS that are 996 /// either external to the vectorized code, or require shuffling. 997 int getExternalUsesCost(const std::pair<Value *, int> &LHS, 998 const std::pair<Value *, int> &RHS) { 999 int Cost = 0; 1000 std::array<std::pair<Value *, int>, 2> Values = {{LHS, RHS}}; 1001 for (int Idx = 0, IdxE = Values.size(); Idx != IdxE; ++Idx) { 1002 Value *V = Values[Idx].first; 1003 if (isa<Constant>(V)) { 1004 // Since this is a function pass, it doesn't make semantic sense to 1005 // walk the users of a subclass of Constant. The users could be in 1006 // another function, or even another module that happens to be in 1007 // the same LLVMContext. 1008 continue; 1009 } 1010 1011 // Calculate the absolute lane, using the minimum relative lane of LHS 1012 // and RHS as base and Idx as the offset. 1013 int Ln = std::min(LHS.second, RHS.second) + Idx; 1014 assert(Ln >= 0 && "Bad lane calculation"); 1015 unsigned UsersBudget = LookAheadUsersBudget; 1016 for (User *U : V->users()) { 1017 if (const TreeEntry *UserTE = R.getTreeEntry(U)) { 1018 // The user is in the VectorizableTree. Check if we need to insert. 1019 auto It = llvm::find(UserTE->Scalars, U); 1020 assert(It != UserTE->Scalars.end() && "U is in UserTE"); 1021 int UserLn = std::distance(UserTE->Scalars.begin(), It); 1022 assert(UserLn >= 0 && "Bad lane"); 1023 if (UserLn != Ln) 1024 Cost += UserInDiffLaneCost; 1025 } else { 1026 // Check if the user is in the look-ahead code. 1027 auto It2 = InLookAheadValues.find(U); 1028 if (It2 != InLookAheadValues.end()) { 1029 // The user is in the look-ahead code. Check the lane. 1030 if (It2->second != Ln) 1031 Cost += UserInDiffLaneCost; 1032 } else { 1033 // The user is neither in SLP tree nor in the look-ahead code. 1034 Cost += ExternalUseCost; 1035 } 1036 } 1037 // Limit the number of visited uses to cap compilation time. 1038 if (--UsersBudget == 0) 1039 break; 1040 } 1041 } 1042 return Cost; 1043 } 1044 1045 /// Go through the operands of \p LHS and \p RHS recursively until \p 1046 /// MaxLevel, and return the cummulative score. For example: 1047 /// \verbatim 1048 /// A[0] B[0] A[1] B[1] C[0] D[0] B[1] A[1] 1049 /// \ / \ / \ / \ / 1050 /// + + + + 1051 /// G1 G2 G3 G4 1052 /// \endverbatim 1053 /// The getScoreAtLevelRec(G1, G2) function will try to match the nodes at 1054 /// each level recursively, accumulating the score. It starts from matching 1055 /// the additions at level 0, then moves on to the loads (level 1). The 1056 /// score of G1 and G2 is higher than G1 and G3, because {A[0],A[1]} and 1057 /// {B[0],B[1]} match with VLOperands::ScoreConsecutiveLoads, while 1058 /// {A[0],C[0]} has a score of VLOperands::ScoreFail. 1059 /// Please note that the order of the operands does not matter, as we 1060 /// evaluate the score of all profitable combinations of operands. In 1061 /// other words the score of G1 and G4 is the same as G1 and G2. This 1062 /// heuristic is based on ideas described in: 1063 /// Look-ahead SLP: Auto-vectorization in the presence of commutative 1064 /// operations, CGO 2018 by Vasileios Porpodas, Rodrigo C. O. Rocha, 1065 /// Luís F. W. Góes 1066 int getScoreAtLevelRec(const std::pair<Value *, int> &LHS, 1067 const std::pair<Value *, int> &RHS, int CurrLevel, 1068 int MaxLevel) { 1069 1070 Value *V1 = LHS.first; 1071 Value *V2 = RHS.first; 1072 // Get the shallow score of V1 and V2. 1073 int ShallowScoreAtThisLevel = 1074 std::max((int)ScoreFail, getShallowScore(V1, V2, DL, SE) - 1075 getExternalUsesCost(LHS, RHS)); 1076 int Lane1 = LHS.second; 1077 int Lane2 = RHS.second; 1078 1079 // If reached MaxLevel, 1080 // or if V1 and V2 are not instructions, 1081 // or if they are SPLAT, 1082 // or if they are not consecutive, early return the current cost. 1083 auto *I1 = dyn_cast<Instruction>(V1); 1084 auto *I2 = dyn_cast<Instruction>(V2); 1085 if (CurrLevel == MaxLevel || !(I1 && I2) || I1 == I2 || 1086 ShallowScoreAtThisLevel == VLOperands::ScoreFail || 1087 (isa<LoadInst>(I1) && isa<LoadInst>(I2) && ShallowScoreAtThisLevel)) 1088 return ShallowScoreAtThisLevel; 1089 assert(I1 && I2 && "Should have early exited."); 1090 1091 // Keep track of in-tree values for determining the external-use cost. 1092 InLookAheadValues[V1] = Lane1; 1093 InLookAheadValues[V2] = Lane2; 1094 1095 // Contains the I2 operand indexes that got matched with I1 operands. 1096 SmallSet<unsigned, 4> Op2Used; 1097 1098 // Recursion towards the operands of I1 and I2. We are trying all possbile 1099 // operand pairs, and keeping track of the best score. 1100 for (unsigned OpIdx1 = 0, NumOperands1 = I1->getNumOperands(); 1101 OpIdx1 != NumOperands1; ++OpIdx1) { 1102 // Try to pair op1I with the best operand of I2. 1103 int MaxTmpScore = 0; 1104 unsigned MaxOpIdx2 = 0; 1105 bool FoundBest = false; 1106 // If I2 is commutative try all combinations. 1107 unsigned FromIdx = isCommutative(I2) ? 0 : OpIdx1; 1108 unsigned ToIdx = isCommutative(I2) 1109 ? I2->getNumOperands() 1110 : std::min(I2->getNumOperands(), OpIdx1 + 1); 1111 assert(FromIdx <= ToIdx && "Bad index"); 1112 for (unsigned OpIdx2 = FromIdx; OpIdx2 != ToIdx; ++OpIdx2) { 1113 // Skip operands already paired with OpIdx1. 1114 if (Op2Used.count(OpIdx2)) 1115 continue; 1116 // Recursively calculate the cost at each level 1117 int TmpScore = getScoreAtLevelRec({I1->getOperand(OpIdx1), Lane1}, 1118 {I2->getOperand(OpIdx2), Lane2}, 1119 CurrLevel + 1, MaxLevel); 1120 // Look for the best score. 1121 if (TmpScore > VLOperands::ScoreFail && TmpScore > MaxTmpScore) { 1122 MaxTmpScore = TmpScore; 1123 MaxOpIdx2 = OpIdx2; 1124 FoundBest = true; 1125 } 1126 } 1127 if (FoundBest) { 1128 // Pair {OpIdx1, MaxOpIdx2} was found to be best. Never revisit it. 1129 Op2Used.insert(MaxOpIdx2); 1130 ShallowScoreAtThisLevel += MaxTmpScore; 1131 } 1132 } 1133 return ShallowScoreAtThisLevel; 1134 } 1135 1136 /// \Returns the look-ahead score, which tells us how much the sub-trees 1137 /// rooted at \p LHS and \p RHS match, the more they match the higher the 1138 /// score. This helps break ties in an informed way when we cannot decide on 1139 /// the order of the operands by just considering the immediate 1140 /// predecessors. 1141 int getLookAheadScore(const std::pair<Value *, int> &LHS, 1142 const std::pair<Value *, int> &RHS) { 1143 InLookAheadValues.clear(); 1144 return getScoreAtLevelRec(LHS, RHS, 1, LookAheadMaxDepth); 1145 } 1146 1147 // Search all operands in Ops[*][Lane] for the one that matches best 1148 // Ops[OpIdx][LastLane] and return its opreand index. 1149 // If no good match can be found, return None. 1150 Optional<unsigned> 1151 getBestOperand(unsigned OpIdx, int Lane, int LastLane, 1152 ArrayRef<ReorderingMode> ReorderingModes) { 1153 unsigned NumOperands = getNumOperands(); 1154 1155 // The operand of the previous lane at OpIdx. 1156 Value *OpLastLane = getData(OpIdx, LastLane).V; 1157 1158 // Our strategy mode for OpIdx. 1159 ReorderingMode RMode = ReorderingModes[OpIdx]; 1160 1161 // The linearized opcode of the operand at OpIdx, Lane. 1162 bool OpIdxAPO = getData(OpIdx, Lane).APO; 1163 1164 // The best operand index and its score. 1165 // Sometimes we have more than one option (e.g., Opcode and Undefs), so we 1166 // are using the score to differentiate between the two. 1167 struct BestOpData { 1168 Optional<unsigned> Idx = None; 1169 unsigned Score = 0; 1170 } BestOp; 1171 1172 // Iterate through all unused operands and look for the best. 1173 for (unsigned Idx = 0; Idx != NumOperands; ++Idx) { 1174 // Get the operand at Idx and Lane. 1175 OperandData &OpData = getData(Idx, Lane); 1176 Value *Op = OpData.V; 1177 bool OpAPO = OpData.APO; 1178 1179 // Skip already selected operands. 1180 if (OpData.IsUsed) 1181 continue; 1182 1183 // Skip if we are trying to move the operand to a position with a 1184 // different opcode in the linearized tree form. This would break the 1185 // semantics. 1186 if (OpAPO != OpIdxAPO) 1187 continue; 1188 1189 // Look for an operand that matches the current mode. 1190 switch (RMode) { 1191 case ReorderingMode::Load: 1192 case ReorderingMode::Constant: 1193 case ReorderingMode::Opcode: { 1194 bool LeftToRight = Lane > LastLane; 1195 Value *OpLeft = (LeftToRight) ? OpLastLane : Op; 1196 Value *OpRight = (LeftToRight) ? Op : OpLastLane; 1197 unsigned Score = 1198 getLookAheadScore({OpLeft, LastLane}, {OpRight, Lane}); 1199 if (Score > BestOp.Score) { 1200 BestOp.Idx = Idx; 1201 BestOp.Score = Score; 1202 } 1203 break; 1204 } 1205 case ReorderingMode::Splat: 1206 if (Op == OpLastLane) 1207 BestOp.Idx = Idx; 1208 break; 1209 case ReorderingMode::Failed: 1210 return None; 1211 } 1212 } 1213 1214 if (BestOp.Idx) { 1215 getData(BestOp.Idx.getValue(), Lane).IsUsed = true; 1216 return BestOp.Idx; 1217 } 1218 // If we could not find a good match return None. 1219 return None; 1220 } 1221 1222 /// Helper for reorderOperandVecs. \Returns the lane that we should start 1223 /// reordering from. This is the one which has the least number of operands 1224 /// that can freely move about. 1225 unsigned getBestLaneToStartReordering() const { 1226 unsigned BestLane = 0; 1227 unsigned Min = UINT_MAX; 1228 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 1229 ++Lane) { 1230 unsigned NumFreeOps = getMaxNumOperandsThatCanBeReordered(Lane); 1231 if (NumFreeOps < Min) { 1232 Min = NumFreeOps; 1233 BestLane = Lane; 1234 } 1235 } 1236 return BestLane; 1237 } 1238 1239 /// \Returns the maximum number of operands that are allowed to be reordered 1240 /// for \p Lane. This is used as a heuristic for selecting the first lane to 1241 /// start operand reordering. 1242 unsigned getMaxNumOperandsThatCanBeReordered(unsigned Lane) const { 1243 unsigned CntTrue = 0; 1244 unsigned NumOperands = getNumOperands(); 1245 // Operands with the same APO can be reordered. We therefore need to count 1246 // how many of them we have for each APO, like this: Cnt[APO] = x. 1247 // Since we only have two APOs, namely true and false, we can avoid using 1248 // a map. Instead we can simply count the number of operands that 1249 // correspond to one of them (in this case the 'true' APO), and calculate 1250 // the other by subtracting it from the total number of operands. 1251 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) 1252 if (getData(OpIdx, Lane).APO) 1253 ++CntTrue; 1254 unsigned CntFalse = NumOperands - CntTrue; 1255 return std::max(CntTrue, CntFalse); 1256 } 1257 1258 /// Go through the instructions in VL and append their operands. 1259 void appendOperandsOfVL(ArrayRef<Value *> VL) { 1260 assert(!VL.empty() && "Bad VL"); 1261 assert((empty() || VL.size() == getNumLanes()) && 1262 "Expected same number of lanes"); 1263 assert(isa<Instruction>(VL[0]) && "Expected instruction"); 1264 unsigned NumOperands = cast<Instruction>(VL[0])->getNumOperands(); 1265 OpsVec.resize(NumOperands); 1266 unsigned NumLanes = VL.size(); 1267 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1268 OpsVec[OpIdx].resize(NumLanes); 1269 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { 1270 assert(isa<Instruction>(VL[Lane]) && "Expected instruction"); 1271 // Our tree has just 3 nodes: the root and two operands. 1272 // It is therefore trivial to get the APO. We only need to check the 1273 // opcode of VL[Lane] and whether the operand at OpIdx is the LHS or 1274 // RHS operand. The LHS operand of both add and sub is never attached 1275 // to an inversese operation in the linearized form, therefore its APO 1276 // is false. The RHS is true only if VL[Lane] is an inverse operation. 1277 1278 // Since operand reordering is performed on groups of commutative 1279 // operations or alternating sequences (e.g., +, -), we can safely 1280 // tell the inverse operations by checking commutativity. 1281 bool IsInverseOperation = !isCommutative(cast<Instruction>(VL[Lane])); 1282 bool APO = (OpIdx == 0) ? false : IsInverseOperation; 1283 OpsVec[OpIdx][Lane] = {cast<Instruction>(VL[Lane])->getOperand(OpIdx), 1284 APO, false}; 1285 } 1286 } 1287 } 1288 1289 /// \returns the number of operands. 1290 unsigned getNumOperands() const { return OpsVec.size(); } 1291 1292 /// \returns the number of lanes. 1293 unsigned getNumLanes() const { return OpsVec[0].size(); } 1294 1295 /// \returns the operand value at \p OpIdx and \p Lane. 1296 Value *getValue(unsigned OpIdx, unsigned Lane) const { 1297 return getData(OpIdx, Lane).V; 1298 } 1299 1300 /// \returns true if the data structure is empty. 1301 bool empty() const { return OpsVec.empty(); } 1302 1303 /// Clears the data. 1304 void clear() { OpsVec.clear(); } 1305 1306 /// \Returns true if there are enough operands identical to \p Op to fill 1307 /// the whole vector. 1308 /// Note: This modifies the 'IsUsed' flag, so a cleanUsed() must follow. 1309 bool shouldBroadcast(Value *Op, unsigned OpIdx, unsigned Lane) { 1310 bool OpAPO = getData(OpIdx, Lane).APO; 1311 for (unsigned Ln = 0, Lns = getNumLanes(); Ln != Lns; ++Ln) { 1312 if (Ln == Lane) 1313 continue; 1314 // This is set to true if we found a candidate for broadcast at Lane. 1315 bool FoundCandidate = false; 1316 for (unsigned OpI = 0, OpE = getNumOperands(); OpI != OpE; ++OpI) { 1317 OperandData &Data = getData(OpI, Ln); 1318 if (Data.APO != OpAPO || Data.IsUsed) 1319 continue; 1320 if (Data.V == Op) { 1321 FoundCandidate = true; 1322 Data.IsUsed = true; 1323 break; 1324 } 1325 } 1326 if (!FoundCandidate) 1327 return false; 1328 } 1329 return true; 1330 } 1331 1332 public: 1333 /// Initialize with all the operands of the instruction vector \p RootVL. 1334 VLOperands(ArrayRef<Value *> RootVL, const DataLayout &DL, 1335 ScalarEvolution &SE, const BoUpSLP &R) 1336 : DL(DL), SE(SE), R(R) { 1337 // Append all the operands of RootVL. 1338 appendOperandsOfVL(RootVL); 1339 } 1340 1341 /// \Returns a value vector with the operands across all lanes for the 1342 /// opearnd at \p OpIdx. 1343 ValueList getVL(unsigned OpIdx) const { 1344 ValueList OpVL(OpsVec[OpIdx].size()); 1345 assert(OpsVec[OpIdx].size() == getNumLanes() && 1346 "Expected same num of lanes across all operands"); 1347 for (unsigned Lane = 0, Lanes = getNumLanes(); Lane != Lanes; ++Lane) 1348 OpVL[Lane] = OpsVec[OpIdx][Lane].V; 1349 return OpVL; 1350 } 1351 1352 // Performs operand reordering for 2 or more operands. 1353 // The original operands are in OrigOps[OpIdx][Lane]. 1354 // The reordered operands are returned in 'SortedOps[OpIdx][Lane]'. 1355 void reorder() { 1356 unsigned NumOperands = getNumOperands(); 1357 unsigned NumLanes = getNumLanes(); 1358 // Each operand has its own mode. We are using this mode to help us select 1359 // the instructions for each lane, so that they match best with the ones 1360 // we have selected so far. 1361 SmallVector<ReorderingMode, 2> ReorderingModes(NumOperands); 1362 1363 // This is a greedy single-pass algorithm. We are going over each lane 1364 // once and deciding on the best order right away with no back-tracking. 1365 // However, in order to increase its effectiveness, we start with the lane 1366 // that has operands that can move the least. For example, given the 1367 // following lanes: 1368 // Lane 0 : A[0] = B[0] + C[0] // Visited 3rd 1369 // Lane 1 : A[1] = C[1] - B[1] // Visited 1st 1370 // Lane 2 : A[2] = B[2] + C[2] // Visited 2nd 1371 // Lane 3 : A[3] = C[3] - B[3] // Visited 4th 1372 // we will start at Lane 1, since the operands of the subtraction cannot 1373 // be reordered. Then we will visit the rest of the lanes in a circular 1374 // fashion. That is, Lanes 2, then Lane 0, and finally Lane 3. 1375 1376 // Find the first lane that we will start our search from. 1377 unsigned FirstLane = getBestLaneToStartReordering(); 1378 1379 // Initialize the modes. 1380 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1381 Value *OpLane0 = getValue(OpIdx, FirstLane); 1382 // Keep track if we have instructions with all the same opcode on one 1383 // side. 1384 if (isa<LoadInst>(OpLane0)) 1385 ReorderingModes[OpIdx] = ReorderingMode::Load; 1386 else if (isa<Instruction>(OpLane0)) { 1387 // Check if OpLane0 should be broadcast. 1388 if (shouldBroadcast(OpLane0, OpIdx, FirstLane)) 1389 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1390 else 1391 ReorderingModes[OpIdx] = ReorderingMode::Opcode; 1392 } 1393 else if (isa<Constant>(OpLane0)) 1394 ReorderingModes[OpIdx] = ReorderingMode::Constant; 1395 else if (isa<Argument>(OpLane0)) 1396 // Our best hope is a Splat. It may save some cost in some cases. 1397 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1398 else 1399 // NOTE: This should be unreachable. 1400 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1401 } 1402 1403 // If the initial strategy fails for any of the operand indexes, then we 1404 // perform reordering again in a second pass. This helps avoid assigning 1405 // high priority to the failed strategy, and should improve reordering for 1406 // the non-failed operand indexes. 1407 for (int Pass = 0; Pass != 2; ++Pass) { 1408 // Skip the second pass if the first pass did not fail. 1409 bool StrategyFailed = false; 1410 // Mark all operand data as free to use. 1411 clearUsed(); 1412 // We keep the original operand order for the FirstLane, so reorder the 1413 // rest of the lanes. We are visiting the nodes in a circular fashion, 1414 // using FirstLane as the center point and increasing the radius 1415 // distance. 1416 for (unsigned Distance = 1; Distance != NumLanes; ++Distance) { 1417 // Visit the lane on the right and then the lane on the left. 1418 for (int Direction : {+1, -1}) { 1419 int Lane = FirstLane + Direction * Distance; 1420 if (Lane < 0 || Lane >= (int)NumLanes) 1421 continue; 1422 int LastLane = Lane - Direction; 1423 assert(LastLane >= 0 && LastLane < (int)NumLanes && 1424 "Out of bounds"); 1425 // Look for a good match for each operand. 1426 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1427 // Search for the operand that matches SortedOps[OpIdx][Lane-1]. 1428 Optional<unsigned> BestIdx = 1429 getBestOperand(OpIdx, Lane, LastLane, ReorderingModes); 1430 // By not selecting a value, we allow the operands that follow to 1431 // select a better matching value. We will get a non-null value in 1432 // the next run of getBestOperand(). 1433 if (BestIdx) { 1434 // Swap the current operand with the one returned by 1435 // getBestOperand(). 1436 swap(OpIdx, BestIdx.getValue(), Lane); 1437 } else { 1438 // We failed to find a best operand, set mode to 'Failed'. 1439 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1440 // Enable the second pass. 1441 StrategyFailed = true; 1442 } 1443 } 1444 } 1445 } 1446 // Skip second pass if the strategy did not fail. 1447 if (!StrategyFailed) 1448 break; 1449 } 1450 } 1451 1452 #if !defined(NDEBUG) || defined(LLVM_ENABLE_DUMP) 1453 LLVM_DUMP_METHOD static StringRef getModeStr(ReorderingMode RMode) { 1454 switch (RMode) { 1455 case ReorderingMode::Load: 1456 return "Load"; 1457 case ReorderingMode::Opcode: 1458 return "Opcode"; 1459 case ReorderingMode::Constant: 1460 return "Constant"; 1461 case ReorderingMode::Splat: 1462 return "Splat"; 1463 case ReorderingMode::Failed: 1464 return "Failed"; 1465 } 1466 llvm_unreachable("Unimplemented Reordering Type"); 1467 } 1468 1469 LLVM_DUMP_METHOD static raw_ostream &printMode(ReorderingMode RMode, 1470 raw_ostream &OS) { 1471 return OS << getModeStr(RMode); 1472 } 1473 1474 /// Debug print. 1475 LLVM_DUMP_METHOD static void dumpMode(ReorderingMode RMode) { 1476 printMode(RMode, dbgs()); 1477 } 1478 1479 friend raw_ostream &operator<<(raw_ostream &OS, ReorderingMode RMode) { 1480 return printMode(RMode, OS); 1481 } 1482 1483 LLVM_DUMP_METHOD raw_ostream &print(raw_ostream &OS) const { 1484 const unsigned Indent = 2; 1485 unsigned Cnt = 0; 1486 for (const OperandDataVec &OpDataVec : OpsVec) { 1487 OS << "Operand " << Cnt++ << "\n"; 1488 for (const OperandData &OpData : OpDataVec) { 1489 OS.indent(Indent) << "{"; 1490 if (Value *V = OpData.V) 1491 OS << *V; 1492 else 1493 OS << "null"; 1494 OS << ", APO:" << OpData.APO << "}\n"; 1495 } 1496 OS << "\n"; 1497 } 1498 return OS; 1499 } 1500 1501 /// Debug print. 1502 LLVM_DUMP_METHOD void dump() const { print(dbgs()); } 1503 #endif 1504 }; 1505 1506 /// Checks if the instruction is marked for deletion. 1507 bool isDeleted(Instruction *I) const { return DeletedInstructions.count(I); } 1508 1509 /// Marks values operands for later deletion by replacing them with Undefs. 1510 void eraseInstructions(ArrayRef<Value *> AV); 1511 1512 ~BoUpSLP(); 1513 1514 private: 1515 /// Checks if all users of \p I are the part of the vectorization tree. 1516 bool areAllUsersVectorized(Instruction *I) const; 1517 1518 /// \returns the cost of the vectorizable entry. 1519 InstructionCost getEntryCost(TreeEntry *E); 1520 1521 /// This is the recursive part of buildTree. 1522 void buildTree_rec(ArrayRef<Value *> Roots, unsigned Depth, 1523 const EdgeInfo &EI); 1524 1525 /// \returns true if the ExtractElement/ExtractValue instructions in \p VL can 1526 /// be vectorized to use the original vector (or aggregate "bitcast" to a 1527 /// vector) and sets \p CurrentOrder to the identity permutation; otherwise 1528 /// returns false, setting \p CurrentOrder to either an empty vector or a 1529 /// non-identity permutation that allows to reuse extract instructions. 1530 bool canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 1531 SmallVectorImpl<unsigned> &CurrentOrder) const; 1532 1533 /// Vectorize a single entry in the tree. 1534 Value *vectorizeTree(TreeEntry *E); 1535 1536 /// Vectorize a single entry in the tree, starting in \p VL. 1537 Value *vectorizeTree(ArrayRef<Value *> VL); 1538 1539 /// \returns the scalarization cost for this type. Scalarization in this 1540 /// context means the creation of vectors from a group of scalars. 1541 InstructionCost 1542 getGatherCost(FixedVectorType *Ty, 1543 const DenseSet<unsigned> &ShuffledIndices) const; 1544 1545 /// Checks if the gathered \p VL can be represented as shuffle(s) of previous 1546 /// tree entries. 1547 /// \returns ShuffleKind, if gathered values can be represented as shuffles of 1548 /// previous tree entries. \p Mask is filled with the shuffle mask. 1549 Optional<TargetTransformInfo::ShuffleKind> 1550 isGatherShuffledEntry(const TreeEntry *TE, SmallVectorImpl<int> &Mask, 1551 SmallVectorImpl<const TreeEntry *> &Entries); 1552 1553 /// \returns the scalarization cost for this list of values. Assuming that 1554 /// this subtree gets vectorized, we may need to extract the values from the 1555 /// roots. This method calculates the cost of extracting the values. 1556 InstructionCost getGatherCost(ArrayRef<Value *> VL) const; 1557 1558 /// Set the Builder insert point to one after the last instruction in 1559 /// the bundle 1560 void setInsertPointAfterBundle(TreeEntry *E); 1561 1562 /// \returns a vector from a collection of scalars in \p VL. 1563 Value *gather(ArrayRef<Value *> VL); 1564 1565 /// \returns whether the VectorizableTree is fully vectorizable and will 1566 /// be beneficial even the tree height is tiny. 1567 bool isFullyVectorizableTinyTree() const; 1568 1569 /// Reorder commutative or alt operands to get better probability of 1570 /// generating vectorized code. 1571 static void reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 1572 SmallVectorImpl<Value *> &Left, 1573 SmallVectorImpl<Value *> &Right, 1574 const DataLayout &DL, 1575 ScalarEvolution &SE, 1576 const BoUpSLP &R); 1577 struct TreeEntry { 1578 using VecTreeTy = SmallVector<std::unique_ptr<TreeEntry>, 8>; 1579 TreeEntry(VecTreeTy &Container) : Container(Container) {} 1580 1581 /// \returns true if the scalars in VL are equal to this entry. 1582 bool isSame(ArrayRef<Value *> VL) const { 1583 if (VL.size() == Scalars.size()) 1584 return std::equal(VL.begin(), VL.end(), Scalars.begin()); 1585 return VL.size() == ReuseShuffleIndices.size() && 1586 std::equal( 1587 VL.begin(), VL.end(), ReuseShuffleIndices.begin(), 1588 [this](Value *V, int Idx) { return V == Scalars[Idx]; }); 1589 } 1590 1591 /// A vector of scalars. 1592 ValueList Scalars; 1593 1594 /// The Scalars are vectorized into this value. It is initialized to Null. 1595 Value *VectorizedValue = nullptr; 1596 1597 /// Do we need to gather this sequence or vectorize it 1598 /// (either with vector instruction or with scatter/gather 1599 /// intrinsics for store/load)? 1600 enum EntryState { Vectorize, ScatterVectorize, NeedToGather }; 1601 EntryState State; 1602 1603 /// Does this sequence require some shuffling? 1604 SmallVector<int, 4> ReuseShuffleIndices; 1605 1606 /// Does this entry require reordering? 1607 SmallVector<unsigned, 4> ReorderIndices; 1608 1609 /// Points back to the VectorizableTree. 1610 /// 1611 /// Only used for Graphviz right now. Unfortunately GraphTrait::NodeRef has 1612 /// to be a pointer and needs to be able to initialize the child iterator. 1613 /// Thus we need a reference back to the container to translate the indices 1614 /// to entries. 1615 VecTreeTy &Container; 1616 1617 /// The TreeEntry index containing the user of this entry. We can actually 1618 /// have multiple users so the data structure is not truly a tree. 1619 SmallVector<EdgeInfo, 1> UserTreeIndices; 1620 1621 /// The index of this treeEntry in VectorizableTree. 1622 int Idx = -1; 1623 1624 private: 1625 /// The operands of each instruction in each lane Operands[op_index][lane]. 1626 /// Note: This helps avoid the replication of the code that performs the 1627 /// reordering of operands during buildTree_rec() and vectorizeTree(). 1628 SmallVector<ValueList, 2> Operands; 1629 1630 /// The main/alternate instruction. 1631 Instruction *MainOp = nullptr; 1632 Instruction *AltOp = nullptr; 1633 1634 public: 1635 /// Set this bundle's \p OpIdx'th operand to \p OpVL. 1636 void setOperand(unsigned OpIdx, ArrayRef<Value *> OpVL) { 1637 if (Operands.size() < OpIdx + 1) 1638 Operands.resize(OpIdx + 1); 1639 assert(Operands[OpIdx].size() == 0 && "Already resized?"); 1640 Operands[OpIdx].resize(Scalars.size()); 1641 for (unsigned Lane = 0, E = Scalars.size(); Lane != E; ++Lane) 1642 Operands[OpIdx][Lane] = OpVL[Lane]; 1643 } 1644 1645 /// Set the operands of this bundle in their original order. 1646 void setOperandsInOrder() { 1647 assert(Operands.empty() && "Already initialized?"); 1648 auto *I0 = cast<Instruction>(Scalars[0]); 1649 Operands.resize(I0->getNumOperands()); 1650 unsigned NumLanes = Scalars.size(); 1651 for (unsigned OpIdx = 0, NumOperands = I0->getNumOperands(); 1652 OpIdx != NumOperands; ++OpIdx) { 1653 Operands[OpIdx].resize(NumLanes); 1654 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { 1655 auto *I = cast<Instruction>(Scalars[Lane]); 1656 assert(I->getNumOperands() == NumOperands && 1657 "Expected same number of operands"); 1658 Operands[OpIdx][Lane] = I->getOperand(OpIdx); 1659 } 1660 } 1661 } 1662 1663 /// \returns the \p OpIdx operand of this TreeEntry. 1664 ValueList &getOperand(unsigned OpIdx) { 1665 assert(OpIdx < Operands.size() && "Off bounds"); 1666 return Operands[OpIdx]; 1667 } 1668 1669 /// \returns the number of operands. 1670 unsigned getNumOperands() const { return Operands.size(); } 1671 1672 /// \return the single \p OpIdx operand. 1673 Value *getSingleOperand(unsigned OpIdx) const { 1674 assert(OpIdx < Operands.size() && "Off bounds"); 1675 assert(!Operands[OpIdx].empty() && "No operand available"); 1676 return Operands[OpIdx][0]; 1677 } 1678 1679 /// Some of the instructions in the list have alternate opcodes. 1680 bool isAltShuffle() const { 1681 return getOpcode() != getAltOpcode(); 1682 } 1683 1684 bool isOpcodeOrAlt(Instruction *I) const { 1685 unsigned CheckedOpcode = I->getOpcode(); 1686 return (getOpcode() == CheckedOpcode || 1687 getAltOpcode() == CheckedOpcode); 1688 } 1689 1690 /// Chooses the correct key for scheduling data. If \p Op has the same (or 1691 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is 1692 /// \p OpValue. 1693 Value *isOneOf(Value *Op) const { 1694 auto *I = dyn_cast<Instruction>(Op); 1695 if (I && isOpcodeOrAlt(I)) 1696 return Op; 1697 return MainOp; 1698 } 1699 1700 void setOperations(const InstructionsState &S) { 1701 MainOp = S.MainOp; 1702 AltOp = S.AltOp; 1703 } 1704 1705 Instruction *getMainOp() const { 1706 return MainOp; 1707 } 1708 1709 Instruction *getAltOp() const { 1710 return AltOp; 1711 } 1712 1713 /// The main/alternate opcodes for the list of instructions. 1714 unsigned getOpcode() const { 1715 return MainOp ? MainOp->getOpcode() : 0; 1716 } 1717 1718 unsigned getAltOpcode() const { 1719 return AltOp ? AltOp->getOpcode() : 0; 1720 } 1721 1722 /// Update operations state of this entry if reorder occurred. 1723 bool updateStateIfReorder() { 1724 if (ReorderIndices.empty()) 1725 return false; 1726 InstructionsState S = getSameOpcode(Scalars, ReorderIndices.front()); 1727 setOperations(S); 1728 return true; 1729 } 1730 1731 #ifndef NDEBUG 1732 /// Debug printer. 1733 LLVM_DUMP_METHOD void dump() const { 1734 dbgs() << Idx << ".\n"; 1735 for (unsigned OpI = 0, OpE = Operands.size(); OpI != OpE; ++OpI) { 1736 dbgs() << "Operand " << OpI << ":\n"; 1737 for (const Value *V : Operands[OpI]) 1738 dbgs().indent(2) << *V << "\n"; 1739 } 1740 dbgs() << "Scalars: \n"; 1741 for (Value *V : Scalars) 1742 dbgs().indent(2) << *V << "\n"; 1743 dbgs() << "State: "; 1744 switch (State) { 1745 case Vectorize: 1746 dbgs() << "Vectorize\n"; 1747 break; 1748 case ScatterVectorize: 1749 dbgs() << "ScatterVectorize\n"; 1750 break; 1751 case NeedToGather: 1752 dbgs() << "NeedToGather\n"; 1753 break; 1754 } 1755 dbgs() << "MainOp: "; 1756 if (MainOp) 1757 dbgs() << *MainOp << "\n"; 1758 else 1759 dbgs() << "NULL\n"; 1760 dbgs() << "AltOp: "; 1761 if (AltOp) 1762 dbgs() << *AltOp << "\n"; 1763 else 1764 dbgs() << "NULL\n"; 1765 dbgs() << "VectorizedValue: "; 1766 if (VectorizedValue) 1767 dbgs() << *VectorizedValue << "\n"; 1768 else 1769 dbgs() << "NULL\n"; 1770 dbgs() << "ReuseShuffleIndices: "; 1771 if (ReuseShuffleIndices.empty()) 1772 dbgs() << "Empty"; 1773 else 1774 for (unsigned ReuseIdx : ReuseShuffleIndices) 1775 dbgs() << ReuseIdx << ", "; 1776 dbgs() << "\n"; 1777 dbgs() << "ReorderIndices: "; 1778 for (unsigned ReorderIdx : ReorderIndices) 1779 dbgs() << ReorderIdx << ", "; 1780 dbgs() << "\n"; 1781 dbgs() << "UserTreeIndices: "; 1782 for (const auto &EInfo : UserTreeIndices) 1783 dbgs() << EInfo << ", "; 1784 dbgs() << "\n"; 1785 } 1786 #endif 1787 }; 1788 1789 #ifndef NDEBUG 1790 void dumpTreeCosts(TreeEntry *E, InstructionCost ReuseShuffleCost, 1791 InstructionCost VecCost, 1792 InstructionCost ScalarCost) const { 1793 dbgs() << "SLP: Calculated costs for Tree:\n"; E->dump(); 1794 dbgs() << "SLP: Costs:\n"; 1795 dbgs() << "SLP: ReuseShuffleCost = " << ReuseShuffleCost << "\n"; 1796 dbgs() << "SLP: VectorCost = " << VecCost << "\n"; 1797 dbgs() << "SLP: ScalarCost = " << ScalarCost << "\n"; 1798 dbgs() << "SLP: ReuseShuffleCost + VecCost - ScalarCost = " << 1799 ReuseShuffleCost + VecCost - ScalarCost << "\n"; 1800 } 1801 #endif 1802 1803 /// Create a new VectorizableTree entry. 1804 TreeEntry *newTreeEntry(ArrayRef<Value *> VL, Optional<ScheduleData *> Bundle, 1805 const InstructionsState &S, 1806 const EdgeInfo &UserTreeIdx, 1807 ArrayRef<unsigned> ReuseShuffleIndices = None, 1808 ArrayRef<unsigned> ReorderIndices = None) { 1809 TreeEntry::EntryState EntryState = 1810 Bundle ? TreeEntry::Vectorize : TreeEntry::NeedToGather; 1811 return newTreeEntry(VL, EntryState, Bundle, S, UserTreeIdx, 1812 ReuseShuffleIndices, ReorderIndices); 1813 } 1814 1815 TreeEntry *newTreeEntry(ArrayRef<Value *> VL, 1816 TreeEntry::EntryState EntryState, 1817 Optional<ScheduleData *> Bundle, 1818 const InstructionsState &S, 1819 const EdgeInfo &UserTreeIdx, 1820 ArrayRef<unsigned> ReuseShuffleIndices = None, 1821 ArrayRef<unsigned> ReorderIndices = None) { 1822 assert(((!Bundle && EntryState == TreeEntry::NeedToGather) || 1823 (Bundle && EntryState != TreeEntry::NeedToGather)) && 1824 "Need to vectorize gather entry?"); 1825 VectorizableTree.push_back(std::make_unique<TreeEntry>(VectorizableTree)); 1826 TreeEntry *Last = VectorizableTree.back().get(); 1827 Last->Idx = VectorizableTree.size() - 1; 1828 Last->Scalars.insert(Last->Scalars.begin(), VL.begin(), VL.end()); 1829 Last->State = EntryState; 1830 Last->ReuseShuffleIndices.append(ReuseShuffleIndices.begin(), 1831 ReuseShuffleIndices.end()); 1832 Last->ReorderIndices.append(ReorderIndices.begin(), ReorderIndices.end()); 1833 Last->setOperations(S); 1834 if (Last->State != TreeEntry::NeedToGather) { 1835 for (Value *V : VL) { 1836 assert(!getTreeEntry(V) && "Scalar already in tree!"); 1837 ScalarToTreeEntry[V] = Last; 1838 } 1839 // Update the scheduler bundle to point to this TreeEntry. 1840 unsigned Lane = 0; 1841 for (ScheduleData *BundleMember = Bundle.getValue(); BundleMember; 1842 BundleMember = BundleMember->NextInBundle) { 1843 BundleMember->TE = Last; 1844 BundleMember->Lane = Lane; 1845 ++Lane; 1846 } 1847 assert((!Bundle.getValue() || Lane == VL.size()) && 1848 "Bundle and VL out of sync"); 1849 } else { 1850 MustGather.insert(VL.begin(), VL.end()); 1851 } 1852 1853 if (UserTreeIdx.UserTE) 1854 Last->UserTreeIndices.push_back(UserTreeIdx); 1855 1856 return Last; 1857 } 1858 1859 /// -- Vectorization State -- 1860 /// Holds all of the tree entries. 1861 TreeEntry::VecTreeTy VectorizableTree; 1862 1863 #ifndef NDEBUG 1864 /// Debug printer. 1865 LLVM_DUMP_METHOD void dumpVectorizableTree() const { 1866 for (unsigned Id = 0, IdE = VectorizableTree.size(); Id != IdE; ++Id) { 1867 VectorizableTree[Id]->dump(); 1868 dbgs() << "\n"; 1869 } 1870 } 1871 #endif 1872 1873 TreeEntry *getTreeEntry(Value *V) { return ScalarToTreeEntry.lookup(V); } 1874 1875 const TreeEntry *getTreeEntry(Value *V) const { 1876 return ScalarToTreeEntry.lookup(V); 1877 } 1878 1879 /// Maps a specific scalar to its tree entry. 1880 SmallDenseMap<Value*, TreeEntry *> ScalarToTreeEntry; 1881 1882 /// Maps a value to the proposed vectorizable size. 1883 SmallDenseMap<Value *, unsigned> InstrElementSize; 1884 1885 /// A list of scalars that we found that we need to keep as scalars. 1886 ValueSet MustGather; 1887 1888 /// This POD struct describes one external user in the vectorized tree. 1889 struct ExternalUser { 1890 ExternalUser(Value *S, llvm::User *U, int L) 1891 : Scalar(S), User(U), Lane(L) {} 1892 1893 // Which scalar in our function. 1894 Value *Scalar; 1895 1896 // Which user that uses the scalar. 1897 llvm::User *User; 1898 1899 // Which lane does the scalar belong to. 1900 int Lane; 1901 }; 1902 using UserList = SmallVector<ExternalUser, 16>; 1903 1904 /// Checks if two instructions may access the same memory. 1905 /// 1906 /// \p Loc1 is the location of \p Inst1. It is passed explicitly because it 1907 /// is invariant in the calling loop. 1908 bool isAliased(const MemoryLocation &Loc1, Instruction *Inst1, 1909 Instruction *Inst2) { 1910 // First check if the result is already in the cache. 1911 AliasCacheKey key = std::make_pair(Inst1, Inst2); 1912 Optional<bool> &result = AliasCache[key]; 1913 if (result.hasValue()) { 1914 return result.getValue(); 1915 } 1916 MemoryLocation Loc2 = getLocation(Inst2, AA); 1917 bool aliased = true; 1918 if (Loc1.Ptr && Loc2.Ptr && isSimple(Inst1) && isSimple(Inst2)) { 1919 // Do the alias check. 1920 aliased = !AA->isNoAlias(Loc1, Loc2); 1921 } 1922 // Store the result in the cache. 1923 result = aliased; 1924 return aliased; 1925 } 1926 1927 using AliasCacheKey = std::pair<Instruction *, Instruction *>; 1928 1929 /// Cache for alias results. 1930 /// TODO: consider moving this to the AliasAnalysis itself. 1931 DenseMap<AliasCacheKey, Optional<bool>> AliasCache; 1932 1933 /// Removes an instruction from its block and eventually deletes it. 1934 /// It's like Instruction::eraseFromParent() except that the actual deletion 1935 /// is delayed until BoUpSLP is destructed. 1936 /// This is required to ensure that there are no incorrect collisions in the 1937 /// AliasCache, which can happen if a new instruction is allocated at the 1938 /// same address as a previously deleted instruction. 1939 void eraseInstruction(Instruction *I, bool ReplaceOpsWithUndef = false) { 1940 auto It = DeletedInstructions.try_emplace(I, ReplaceOpsWithUndef).first; 1941 It->getSecond() = It->getSecond() && ReplaceOpsWithUndef; 1942 } 1943 1944 /// Temporary store for deleted instructions. Instructions will be deleted 1945 /// eventually when the BoUpSLP is destructed. 1946 DenseMap<Instruction *, bool> DeletedInstructions; 1947 1948 /// A list of values that need to extracted out of the tree. 1949 /// This list holds pairs of (Internal Scalar : External User). External User 1950 /// can be nullptr, it means that this Internal Scalar will be used later, 1951 /// after vectorization. 1952 UserList ExternalUses; 1953 1954 /// Values used only by @llvm.assume calls. 1955 SmallPtrSet<const Value *, 32> EphValues; 1956 1957 /// Holds all of the instructions that we gathered. 1958 SetVector<Instruction *> GatherSeq; 1959 1960 /// A list of blocks that we are going to CSE. 1961 SetVector<BasicBlock *> CSEBlocks; 1962 1963 /// Contains all scheduling relevant data for an instruction. 1964 /// A ScheduleData either represents a single instruction or a member of an 1965 /// instruction bundle (= a group of instructions which is combined into a 1966 /// vector instruction). 1967 struct ScheduleData { 1968 // The initial value for the dependency counters. It means that the 1969 // dependencies are not calculated yet. 1970 enum { InvalidDeps = -1 }; 1971 1972 ScheduleData() = default; 1973 1974 void init(int BlockSchedulingRegionID, Value *OpVal) { 1975 FirstInBundle = this; 1976 NextInBundle = nullptr; 1977 NextLoadStore = nullptr; 1978 IsScheduled = false; 1979 SchedulingRegionID = BlockSchedulingRegionID; 1980 UnscheduledDepsInBundle = UnscheduledDeps; 1981 clearDependencies(); 1982 OpValue = OpVal; 1983 TE = nullptr; 1984 Lane = -1; 1985 } 1986 1987 /// Returns true if the dependency information has been calculated. 1988 bool hasValidDependencies() const { return Dependencies != InvalidDeps; } 1989 1990 /// Returns true for single instructions and for bundle representatives 1991 /// (= the head of a bundle). 1992 bool isSchedulingEntity() const { return FirstInBundle == this; } 1993 1994 /// Returns true if it represents an instruction bundle and not only a 1995 /// single instruction. 1996 bool isPartOfBundle() const { 1997 return NextInBundle != nullptr || FirstInBundle != this; 1998 } 1999 2000 /// Returns true if it is ready for scheduling, i.e. it has no more 2001 /// unscheduled depending instructions/bundles. 2002 bool isReady() const { 2003 assert(isSchedulingEntity() && 2004 "can't consider non-scheduling entity for ready list"); 2005 return UnscheduledDepsInBundle == 0 && !IsScheduled; 2006 } 2007 2008 /// Modifies the number of unscheduled dependencies, also updating it for 2009 /// the whole bundle. 2010 int incrementUnscheduledDeps(int Incr) { 2011 UnscheduledDeps += Incr; 2012 return FirstInBundle->UnscheduledDepsInBundle += Incr; 2013 } 2014 2015 /// Sets the number of unscheduled dependencies to the number of 2016 /// dependencies. 2017 void resetUnscheduledDeps() { 2018 incrementUnscheduledDeps(Dependencies - UnscheduledDeps); 2019 } 2020 2021 /// Clears all dependency information. 2022 void clearDependencies() { 2023 Dependencies = InvalidDeps; 2024 resetUnscheduledDeps(); 2025 MemoryDependencies.clear(); 2026 } 2027 2028 void dump(raw_ostream &os) const { 2029 if (!isSchedulingEntity()) { 2030 os << "/ " << *Inst; 2031 } else if (NextInBundle) { 2032 os << '[' << *Inst; 2033 ScheduleData *SD = NextInBundle; 2034 while (SD) { 2035 os << ';' << *SD->Inst; 2036 SD = SD->NextInBundle; 2037 } 2038 os << ']'; 2039 } else { 2040 os << *Inst; 2041 } 2042 } 2043 2044 Instruction *Inst = nullptr; 2045 2046 /// Points to the head in an instruction bundle (and always to this for 2047 /// single instructions). 2048 ScheduleData *FirstInBundle = nullptr; 2049 2050 /// Single linked list of all instructions in a bundle. Null if it is a 2051 /// single instruction. 2052 ScheduleData *NextInBundle = nullptr; 2053 2054 /// Single linked list of all memory instructions (e.g. load, store, call) 2055 /// in the block - until the end of the scheduling region. 2056 ScheduleData *NextLoadStore = nullptr; 2057 2058 /// The dependent memory instructions. 2059 /// This list is derived on demand in calculateDependencies(). 2060 SmallVector<ScheduleData *, 4> MemoryDependencies; 2061 2062 /// This ScheduleData is in the current scheduling region if this matches 2063 /// the current SchedulingRegionID of BlockScheduling. 2064 int SchedulingRegionID = 0; 2065 2066 /// Used for getting a "good" final ordering of instructions. 2067 int SchedulingPriority = 0; 2068 2069 /// The number of dependencies. Constitutes of the number of users of the 2070 /// instruction plus the number of dependent memory instructions (if any). 2071 /// This value is calculated on demand. 2072 /// If InvalidDeps, the number of dependencies is not calculated yet. 2073 int Dependencies = InvalidDeps; 2074 2075 /// The number of dependencies minus the number of dependencies of scheduled 2076 /// instructions. As soon as this is zero, the instruction/bundle gets ready 2077 /// for scheduling. 2078 /// Note that this is negative as long as Dependencies is not calculated. 2079 int UnscheduledDeps = InvalidDeps; 2080 2081 /// The sum of UnscheduledDeps in a bundle. Equals to UnscheduledDeps for 2082 /// single instructions. 2083 int UnscheduledDepsInBundle = InvalidDeps; 2084 2085 /// True if this instruction is scheduled (or considered as scheduled in the 2086 /// dry-run). 2087 bool IsScheduled = false; 2088 2089 /// Opcode of the current instruction in the schedule data. 2090 Value *OpValue = nullptr; 2091 2092 /// The TreeEntry that this instruction corresponds to. 2093 TreeEntry *TE = nullptr; 2094 2095 /// The lane of this node in the TreeEntry. 2096 int Lane = -1; 2097 }; 2098 2099 #ifndef NDEBUG 2100 friend inline raw_ostream &operator<<(raw_ostream &os, 2101 const BoUpSLP::ScheduleData &SD) { 2102 SD.dump(os); 2103 return os; 2104 } 2105 #endif 2106 2107 friend struct GraphTraits<BoUpSLP *>; 2108 friend struct DOTGraphTraits<BoUpSLP *>; 2109 2110 /// Contains all scheduling data for a basic block. 2111 struct BlockScheduling { 2112 BlockScheduling(BasicBlock *BB) 2113 : BB(BB), ChunkSize(BB->size()), ChunkPos(ChunkSize) {} 2114 2115 void clear() { 2116 ReadyInsts.clear(); 2117 ScheduleStart = nullptr; 2118 ScheduleEnd = nullptr; 2119 FirstLoadStoreInRegion = nullptr; 2120 LastLoadStoreInRegion = nullptr; 2121 2122 // Reduce the maximum schedule region size by the size of the 2123 // previous scheduling run. 2124 ScheduleRegionSizeLimit -= ScheduleRegionSize; 2125 if (ScheduleRegionSizeLimit < MinScheduleRegionSize) 2126 ScheduleRegionSizeLimit = MinScheduleRegionSize; 2127 ScheduleRegionSize = 0; 2128 2129 // Make a new scheduling region, i.e. all existing ScheduleData is not 2130 // in the new region yet. 2131 ++SchedulingRegionID; 2132 } 2133 2134 ScheduleData *getScheduleData(Value *V) { 2135 ScheduleData *SD = ScheduleDataMap[V]; 2136 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 2137 return SD; 2138 return nullptr; 2139 } 2140 2141 ScheduleData *getScheduleData(Value *V, Value *Key) { 2142 if (V == Key) 2143 return getScheduleData(V); 2144 auto I = ExtraScheduleDataMap.find(V); 2145 if (I != ExtraScheduleDataMap.end()) { 2146 ScheduleData *SD = I->second[Key]; 2147 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 2148 return SD; 2149 } 2150 return nullptr; 2151 } 2152 2153 bool isInSchedulingRegion(ScheduleData *SD) const { 2154 return SD->SchedulingRegionID == SchedulingRegionID; 2155 } 2156 2157 /// Marks an instruction as scheduled and puts all dependent ready 2158 /// instructions into the ready-list. 2159 template <typename ReadyListType> 2160 void schedule(ScheduleData *SD, ReadyListType &ReadyList) { 2161 SD->IsScheduled = true; 2162 LLVM_DEBUG(dbgs() << "SLP: schedule " << *SD << "\n"); 2163 2164 ScheduleData *BundleMember = SD; 2165 while (BundleMember) { 2166 if (BundleMember->Inst != BundleMember->OpValue) { 2167 BundleMember = BundleMember->NextInBundle; 2168 continue; 2169 } 2170 // Handle the def-use chain dependencies. 2171 2172 // Decrement the unscheduled counter and insert to ready list if ready. 2173 auto &&DecrUnsched = [this, &ReadyList](Instruction *I) { 2174 doForAllOpcodes(I, [&ReadyList](ScheduleData *OpDef) { 2175 if (OpDef && OpDef->hasValidDependencies() && 2176 OpDef->incrementUnscheduledDeps(-1) == 0) { 2177 // There are no more unscheduled dependencies after 2178 // decrementing, so we can put the dependent instruction 2179 // into the ready list. 2180 ScheduleData *DepBundle = OpDef->FirstInBundle; 2181 assert(!DepBundle->IsScheduled && 2182 "already scheduled bundle gets ready"); 2183 ReadyList.insert(DepBundle); 2184 LLVM_DEBUG(dbgs() 2185 << "SLP: gets ready (def): " << *DepBundle << "\n"); 2186 } 2187 }); 2188 }; 2189 2190 // If BundleMember is a vector bundle, its operands may have been 2191 // reordered duiring buildTree(). We therefore need to get its operands 2192 // through the TreeEntry. 2193 if (TreeEntry *TE = BundleMember->TE) { 2194 int Lane = BundleMember->Lane; 2195 assert(Lane >= 0 && "Lane not set"); 2196 2197 // Since vectorization tree is being built recursively this assertion 2198 // ensures that the tree entry has all operands set before reaching 2199 // this code. Couple of exceptions known at the moment are extracts 2200 // where their second (immediate) operand is not added. Since 2201 // immediates do not affect scheduler behavior this is considered 2202 // okay. 2203 auto *In = TE->getMainOp(); 2204 assert(In && 2205 (isa<ExtractValueInst>(In) || isa<ExtractElementInst>(In) || 2206 In->getNumOperands() == TE->getNumOperands()) && 2207 "Missed TreeEntry operands?"); 2208 (void)In; // fake use to avoid build failure when assertions disabled 2209 2210 for (unsigned OpIdx = 0, NumOperands = TE->getNumOperands(); 2211 OpIdx != NumOperands; ++OpIdx) 2212 if (auto *I = dyn_cast<Instruction>(TE->getOperand(OpIdx)[Lane])) 2213 DecrUnsched(I); 2214 } else { 2215 // If BundleMember is a stand-alone instruction, no operand reordering 2216 // has taken place, so we directly access its operands. 2217 for (Use &U : BundleMember->Inst->operands()) 2218 if (auto *I = dyn_cast<Instruction>(U.get())) 2219 DecrUnsched(I); 2220 } 2221 // Handle the memory dependencies. 2222 for (ScheduleData *MemoryDepSD : BundleMember->MemoryDependencies) { 2223 if (MemoryDepSD->incrementUnscheduledDeps(-1) == 0) { 2224 // There are no more unscheduled dependencies after decrementing, 2225 // so we can put the dependent instruction into the ready list. 2226 ScheduleData *DepBundle = MemoryDepSD->FirstInBundle; 2227 assert(!DepBundle->IsScheduled && 2228 "already scheduled bundle gets ready"); 2229 ReadyList.insert(DepBundle); 2230 LLVM_DEBUG(dbgs() 2231 << "SLP: gets ready (mem): " << *DepBundle << "\n"); 2232 } 2233 } 2234 BundleMember = BundleMember->NextInBundle; 2235 } 2236 } 2237 2238 void doForAllOpcodes(Value *V, 2239 function_ref<void(ScheduleData *SD)> Action) { 2240 if (ScheduleData *SD = getScheduleData(V)) 2241 Action(SD); 2242 auto I = ExtraScheduleDataMap.find(V); 2243 if (I != ExtraScheduleDataMap.end()) 2244 for (auto &P : I->second) 2245 if (P.second->SchedulingRegionID == SchedulingRegionID) 2246 Action(P.second); 2247 } 2248 2249 /// Put all instructions into the ReadyList which are ready for scheduling. 2250 template <typename ReadyListType> 2251 void initialFillReadyList(ReadyListType &ReadyList) { 2252 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 2253 doForAllOpcodes(I, [&](ScheduleData *SD) { 2254 if (SD->isSchedulingEntity() && SD->isReady()) { 2255 ReadyList.insert(SD); 2256 LLVM_DEBUG(dbgs() 2257 << "SLP: initially in ready list: " << *I << "\n"); 2258 } 2259 }); 2260 } 2261 } 2262 2263 /// Checks if a bundle of instructions can be scheduled, i.e. has no 2264 /// cyclic dependencies. This is only a dry-run, no instructions are 2265 /// actually moved at this stage. 2266 /// \returns the scheduling bundle. The returned Optional value is non-None 2267 /// if \p VL is allowed to be scheduled. 2268 Optional<ScheduleData *> 2269 tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 2270 const InstructionsState &S); 2271 2272 /// Un-bundles a group of instructions. 2273 void cancelScheduling(ArrayRef<Value *> VL, Value *OpValue); 2274 2275 /// Allocates schedule data chunk. 2276 ScheduleData *allocateScheduleDataChunks(); 2277 2278 /// Extends the scheduling region so that V is inside the region. 2279 /// \returns true if the region size is within the limit. 2280 bool extendSchedulingRegion(Value *V, const InstructionsState &S); 2281 2282 /// Initialize the ScheduleData structures for new instructions in the 2283 /// scheduling region. 2284 void initScheduleData(Instruction *FromI, Instruction *ToI, 2285 ScheduleData *PrevLoadStore, 2286 ScheduleData *NextLoadStore); 2287 2288 /// Updates the dependency information of a bundle and of all instructions/ 2289 /// bundles which depend on the original bundle. 2290 void calculateDependencies(ScheduleData *SD, bool InsertInReadyList, 2291 BoUpSLP *SLP); 2292 2293 /// Sets all instruction in the scheduling region to un-scheduled. 2294 void resetSchedule(); 2295 2296 BasicBlock *BB; 2297 2298 /// Simple memory allocation for ScheduleData. 2299 std::vector<std::unique_ptr<ScheduleData[]>> ScheduleDataChunks; 2300 2301 /// The size of a ScheduleData array in ScheduleDataChunks. 2302 int ChunkSize; 2303 2304 /// The allocator position in the current chunk, which is the last entry 2305 /// of ScheduleDataChunks. 2306 int ChunkPos; 2307 2308 /// Attaches ScheduleData to Instruction. 2309 /// Note that the mapping survives during all vectorization iterations, i.e. 2310 /// ScheduleData structures are recycled. 2311 DenseMap<Value *, ScheduleData *> ScheduleDataMap; 2312 2313 /// Attaches ScheduleData to Instruction with the leading key. 2314 DenseMap<Value *, SmallDenseMap<Value *, ScheduleData *>> 2315 ExtraScheduleDataMap; 2316 2317 struct ReadyList : SmallVector<ScheduleData *, 8> { 2318 void insert(ScheduleData *SD) { push_back(SD); } 2319 }; 2320 2321 /// The ready-list for scheduling (only used for the dry-run). 2322 ReadyList ReadyInsts; 2323 2324 /// The first instruction of the scheduling region. 2325 Instruction *ScheduleStart = nullptr; 2326 2327 /// The first instruction _after_ the scheduling region. 2328 Instruction *ScheduleEnd = nullptr; 2329 2330 /// The first memory accessing instruction in the scheduling region 2331 /// (can be null). 2332 ScheduleData *FirstLoadStoreInRegion = nullptr; 2333 2334 /// The last memory accessing instruction in the scheduling region 2335 /// (can be null). 2336 ScheduleData *LastLoadStoreInRegion = nullptr; 2337 2338 /// The current size of the scheduling region. 2339 int ScheduleRegionSize = 0; 2340 2341 /// The maximum size allowed for the scheduling region. 2342 int ScheduleRegionSizeLimit = ScheduleRegionSizeBudget; 2343 2344 /// The ID of the scheduling region. For a new vectorization iteration this 2345 /// is incremented which "removes" all ScheduleData from the region. 2346 // Make sure that the initial SchedulingRegionID is greater than the 2347 // initial SchedulingRegionID in ScheduleData (which is 0). 2348 int SchedulingRegionID = 1; 2349 }; 2350 2351 /// Attaches the BlockScheduling structures to basic blocks. 2352 MapVector<BasicBlock *, std::unique_ptr<BlockScheduling>> BlocksSchedules; 2353 2354 /// Performs the "real" scheduling. Done before vectorization is actually 2355 /// performed in a basic block. 2356 void scheduleBlock(BlockScheduling *BS); 2357 2358 /// List of users to ignore during scheduling and that don't need extracting. 2359 ArrayRef<Value *> UserIgnoreList; 2360 2361 /// A DenseMapInfo implementation for holding DenseMaps and DenseSets of 2362 /// sorted SmallVectors of unsigned. 2363 struct OrdersTypeDenseMapInfo { 2364 static OrdersType getEmptyKey() { 2365 OrdersType V; 2366 V.push_back(~1U); 2367 return V; 2368 } 2369 2370 static OrdersType getTombstoneKey() { 2371 OrdersType V; 2372 V.push_back(~2U); 2373 return V; 2374 } 2375 2376 static unsigned getHashValue(const OrdersType &V) { 2377 return static_cast<unsigned>(hash_combine_range(V.begin(), V.end())); 2378 } 2379 2380 static bool isEqual(const OrdersType &LHS, const OrdersType &RHS) { 2381 return LHS == RHS; 2382 } 2383 }; 2384 2385 /// Contains orders of operations along with the number of bundles that have 2386 /// operations in this order. It stores only those orders that require 2387 /// reordering, if reordering is not required it is counted using \a 2388 /// NumOpsWantToKeepOriginalOrder. 2389 DenseMap<OrdersType, unsigned, OrdersTypeDenseMapInfo> NumOpsWantToKeepOrder; 2390 /// Number of bundles that do not require reordering. 2391 unsigned NumOpsWantToKeepOriginalOrder = 0; 2392 2393 // Analysis and block reference. 2394 Function *F; 2395 ScalarEvolution *SE; 2396 TargetTransformInfo *TTI; 2397 TargetLibraryInfo *TLI; 2398 AAResults *AA; 2399 LoopInfo *LI; 2400 DominatorTree *DT; 2401 AssumptionCache *AC; 2402 DemandedBits *DB; 2403 const DataLayout *DL; 2404 OptimizationRemarkEmitter *ORE; 2405 2406 unsigned MaxVecRegSize; // This is set by TTI or overridden by cl::opt. 2407 unsigned MinVecRegSize; // Set by cl::opt (default: 128). 2408 2409 /// Instruction builder to construct the vectorized tree. 2410 IRBuilder<> Builder; 2411 2412 /// A map of scalar integer values to the smallest bit width with which they 2413 /// can legally be represented. The values map to (width, signed) pairs, 2414 /// where "width" indicates the minimum bit width and "signed" is True if the 2415 /// value must be signed-extended, rather than zero-extended, back to its 2416 /// original width. 2417 MapVector<Value *, std::pair<uint64_t, bool>> MinBWs; 2418 }; 2419 2420 } // end namespace slpvectorizer 2421 2422 template <> struct GraphTraits<BoUpSLP *> { 2423 using TreeEntry = BoUpSLP::TreeEntry; 2424 2425 /// NodeRef has to be a pointer per the GraphWriter. 2426 using NodeRef = TreeEntry *; 2427 2428 using ContainerTy = BoUpSLP::TreeEntry::VecTreeTy; 2429 2430 /// Add the VectorizableTree to the index iterator to be able to return 2431 /// TreeEntry pointers. 2432 struct ChildIteratorType 2433 : public iterator_adaptor_base< 2434 ChildIteratorType, SmallVector<BoUpSLP::EdgeInfo, 1>::iterator> { 2435 ContainerTy &VectorizableTree; 2436 2437 ChildIteratorType(SmallVector<BoUpSLP::EdgeInfo, 1>::iterator W, 2438 ContainerTy &VT) 2439 : ChildIteratorType::iterator_adaptor_base(W), VectorizableTree(VT) {} 2440 2441 NodeRef operator*() { return I->UserTE; } 2442 }; 2443 2444 static NodeRef getEntryNode(BoUpSLP &R) { 2445 return R.VectorizableTree[0].get(); 2446 } 2447 2448 static ChildIteratorType child_begin(NodeRef N) { 2449 return {N->UserTreeIndices.begin(), N->Container}; 2450 } 2451 2452 static ChildIteratorType child_end(NodeRef N) { 2453 return {N->UserTreeIndices.end(), N->Container}; 2454 } 2455 2456 /// For the node iterator we just need to turn the TreeEntry iterator into a 2457 /// TreeEntry* iterator so that it dereferences to NodeRef. 2458 class nodes_iterator { 2459 using ItTy = ContainerTy::iterator; 2460 ItTy It; 2461 2462 public: 2463 nodes_iterator(const ItTy &It2) : It(It2) {} 2464 NodeRef operator*() { return It->get(); } 2465 nodes_iterator operator++() { 2466 ++It; 2467 return *this; 2468 } 2469 bool operator!=(const nodes_iterator &N2) const { return N2.It != It; } 2470 }; 2471 2472 static nodes_iterator nodes_begin(BoUpSLP *R) { 2473 return nodes_iterator(R->VectorizableTree.begin()); 2474 } 2475 2476 static nodes_iterator nodes_end(BoUpSLP *R) { 2477 return nodes_iterator(R->VectorizableTree.end()); 2478 } 2479 2480 static unsigned size(BoUpSLP *R) { return R->VectorizableTree.size(); } 2481 }; 2482 2483 template <> struct DOTGraphTraits<BoUpSLP *> : public DefaultDOTGraphTraits { 2484 using TreeEntry = BoUpSLP::TreeEntry; 2485 2486 DOTGraphTraits(bool isSimple = false) : DefaultDOTGraphTraits(isSimple) {} 2487 2488 std::string getNodeLabel(const TreeEntry *Entry, const BoUpSLP *R) { 2489 std::string Str; 2490 raw_string_ostream OS(Str); 2491 if (isSplat(Entry->Scalars)) { 2492 OS << "<splat> " << *Entry->Scalars[0]; 2493 return Str; 2494 } 2495 for (auto V : Entry->Scalars) { 2496 OS << *V; 2497 if (llvm::any_of(R->ExternalUses, [&](const BoUpSLP::ExternalUser &EU) { 2498 return EU.Scalar == V; 2499 })) 2500 OS << " <extract>"; 2501 OS << "\n"; 2502 } 2503 return Str; 2504 } 2505 2506 static std::string getNodeAttributes(const TreeEntry *Entry, 2507 const BoUpSLP *) { 2508 if (Entry->State == TreeEntry::NeedToGather) 2509 return "color=red"; 2510 return ""; 2511 } 2512 }; 2513 2514 } // end namespace llvm 2515 2516 BoUpSLP::~BoUpSLP() { 2517 for (const auto &Pair : DeletedInstructions) { 2518 // Replace operands of ignored instructions with Undefs in case if they were 2519 // marked for deletion. 2520 if (Pair.getSecond()) { 2521 Value *Undef = UndefValue::get(Pair.getFirst()->getType()); 2522 Pair.getFirst()->replaceAllUsesWith(Undef); 2523 } 2524 Pair.getFirst()->dropAllReferences(); 2525 } 2526 for (const auto &Pair : DeletedInstructions) { 2527 assert(Pair.getFirst()->use_empty() && 2528 "trying to erase instruction with users."); 2529 Pair.getFirst()->eraseFromParent(); 2530 } 2531 #ifdef EXPENSIVE_CHECKS 2532 // If we could guarantee that this call is not extremely slow, we could 2533 // remove the ifdef limitation (see PR47712). 2534 assert(!verifyFunction(*F, &dbgs())); 2535 #endif 2536 } 2537 2538 void BoUpSLP::eraseInstructions(ArrayRef<Value *> AV) { 2539 for (auto *V : AV) { 2540 if (auto *I = dyn_cast<Instruction>(V)) 2541 eraseInstruction(I, /*ReplaceOpsWithUndef=*/true); 2542 }; 2543 } 2544 2545 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2546 ArrayRef<Value *> UserIgnoreLst) { 2547 ExtraValueToDebugLocsMap ExternallyUsedValues; 2548 buildTree(Roots, ExternallyUsedValues, UserIgnoreLst); 2549 } 2550 2551 static int findLaneForValue(ArrayRef<Value *> Scalars, 2552 ArrayRef<int> ReuseShuffleIndices, Value *V) { 2553 unsigned FoundLane = std::distance(Scalars.begin(), find(Scalars, V)); 2554 assert(FoundLane < Scalars.size() && "Couldn't find extract lane"); 2555 if (!ReuseShuffleIndices.empty()) { 2556 FoundLane = std::distance(ReuseShuffleIndices.begin(), 2557 find(ReuseShuffleIndices, FoundLane)); 2558 } 2559 return FoundLane; 2560 } 2561 2562 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2563 ExtraValueToDebugLocsMap &ExternallyUsedValues, 2564 ArrayRef<Value *> UserIgnoreLst) { 2565 deleteTree(); 2566 UserIgnoreList = UserIgnoreLst; 2567 if (!allSameType(Roots)) 2568 return; 2569 buildTree_rec(Roots, 0, EdgeInfo()); 2570 2571 // Collect the values that we need to extract from the tree. 2572 for (auto &TEPtr : VectorizableTree) { 2573 TreeEntry *Entry = TEPtr.get(); 2574 2575 // No need to handle users of gathered values. 2576 if (Entry->State == TreeEntry::NeedToGather) 2577 continue; 2578 2579 // For each lane: 2580 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 2581 Value *Scalar = Entry->Scalars[Lane]; 2582 int FoundLane = 2583 findLaneForValue(Entry->Scalars, Entry->ReuseShuffleIndices, Scalar); 2584 2585 // Check if the scalar is externally used as an extra arg. 2586 auto ExtI = ExternallyUsedValues.find(Scalar); 2587 if (ExtI != ExternallyUsedValues.end()) { 2588 LLVM_DEBUG(dbgs() << "SLP: Need to extract: Extra arg from lane " 2589 << Lane << " from " << *Scalar << ".\n"); 2590 ExternalUses.emplace_back(Scalar, nullptr, FoundLane); 2591 } 2592 for (User *U : Scalar->users()) { 2593 LLVM_DEBUG(dbgs() << "SLP: Checking user:" << *U << ".\n"); 2594 2595 Instruction *UserInst = dyn_cast<Instruction>(U); 2596 if (!UserInst) 2597 continue; 2598 2599 // Skip in-tree scalars that become vectors 2600 if (TreeEntry *UseEntry = getTreeEntry(U)) { 2601 Value *UseScalar = UseEntry->Scalars[0]; 2602 // Some in-tree scalars will remain as scalar in vectorized 2603 // instructions. If that is the case, the one in Lane 0 will 2604 // be used. 2605 if (UseScalar != U || 2606 UseEntry->State == TreeEntry::ScatterVectorize || 2607 !InTreeUserNeedToExtract(Scalar, UserInst, TLI)) { 2608 LLVM_DEBUG(dbgs() << "SLP: \tInternal user will be removed:" << *U 2609 << ".\n"); 2610 assert(UseEntry->State != TreeEntry::NeedToGather && "Bad state"); 2611 continue; 2612 } 2613 } 2614 2615 // Ignore users in the user ignore list. 2616 if (is_contained(UserIgnoreList, UserInst)) 2617 continue; 2618 2619 LLVM_DEBUG(dbgs() << "SLP: Need to extract:" << *U << " from lane " 2620 << Lane << " from " << *Scalar << ".\n"); 2621 ExternalUses.push_back(ExternalUser(Scalar, U, FoundLane)); 2622 } 2623 } 2624 } 2625 } 2626 2627 void BoUpSLP::buildTree_rec(ArrayRef<Value *> VL, unsigned Depth, 2628 const EdgeInfo &UserTreeIdx) { 2629 assert((allConstant(VL) || allSameType(VL)) && "Invalid types!"); 2630 2631 InstructionsState S = getSameOpcode(VL); 2632 if (Depth == RecursionMaxDepth) { 2633 LLVM_DEBUG(dbgs() << "SLP: Gathering due to max recursion depth.\n"); 2634 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2635 return; 2636 } 2637 2638 // Don't handle vectors. 2639 if (S.OpValue->getType()->isVectorTy()) { 2640 LLVM_DEBUG(dbgs() << "SLP: Gathering due to vector type.\n"); 2641 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2642 return; 2643 } 2644 2645 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) 2646 if (SI->getValueOperand()->getType()->isVectorTy()) { 2647 LLVM_DEBUG(dbgs() << "SLP: Gathering due to store vector type.\n"); 2648 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2649 return; 2650 } 2651 2652 // If all of the operands are identical or constant we have a simple solution. 2653 if (allConstant(VL) || isSplat(VL) || !allSameBlock(VL) || !S.getOpcode()) { 2654 LLVM_DEBUG(dbgs() << "SLP: Gathering due to C,S,B,O. \n"); 2655 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2656 return; 2657 } 2658 2659 // We now know that this is a vector of instructions of the same type from 2660 // the same block. 2661 2662 // Don't vectorize ephemeral values. 2663 for (Value *V : VL) { 2664 if (EphValues.count(V)) { 2665 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2666 << ") is ephemeral.\n"); 2667 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2668 return; 2669 } 2670 } 2671 2672 // Check if this is a duplicate of another entry. 2673 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 2674 LLVM_DEBUG(dbgs() << "SLP: \tChecking bundle: " << *S.OpValue << ".\n"); 2675 if (!E->isSame(VL)) { 2676 LLVM_DEBUG(dbgs() << "SLP: Gathering due to partial overlap.\n"); 2677 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2678 return; 2679 } 2680 // Record the reuse of the tree node. FIXME, currently this is only used to 2681 // properly draw the graph rather than for the actual vectorization. 2682 E->UserTreeIndices.push_back(UserTreeIdx); 2683 LLVM_DEBUG(dbgs() << "SLP: Perfect diamond merge at " << *S.OpValue 2684 << ".\n"); 2685 return; 2686 } 2687 2688 // Check that none of the instructions in the bundle are already in the tree. 2689 for (Value *V : VL) { 2690 auto *I = dyn_cast<Instruction>(V); 2691 if (!I) 2692 continue; 2693 if (getTreeEntry(I)) { 2694 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2695 << ") is already in tree.\n"); 2696 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2697 return; 2698 } 2699 } 2700 2701 // If any of the scalars is marked as a value that needs to stay scalar, then 2702 // we need to gather the scalars. 2703 // The reduction nodes (stored in UserIgnoreList) also should stay scalar. 2704 for (Value *V : VL) { 2705 if (MustGather.count(V) || is_contained(UserIgnoreList, V)) { 2706 LLVM_DEBUG(dbgs() << "SLP: Gathering due to gathered scalar.\n"); 2707 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2708 return; 2709 } 2710 } 2711 2712 // Check that all of the users of the scalars that we want to vectorize are 2713 // schedulable. 2714 auto *VL0 = cast<Instruction>(S.OpValue); 2715 BasicBlock *BB = VL0->getParent(); 2716 2717 if (!DT->isReachableFromEntry(BB)) { 2718 // Don't go into unreachable blocks. They may contain instructions with 2719 // dependency cycles which confuse the final scheduling. 2720 LLVM_DEBUG(dbgs() << "SLP: bundle in unreachable block.\n"); 2721 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2722 return; 2723 } 2724 2725 // Check that every instruction appears once in this bundle. 2726 SmallVector<unsigned, 4> ReuseShuffleIndicies; 2727 SmallVector<Value *, 4> UniqueValues; 2728 DenseMap<Value *, unsigned> UniquePositions; 2729 for (Value *V : VL) { 2730 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 2731 ReuseShuffleIndicies.emplace_back(Res.first->second); 2732 if (Res.second) 2733 UniqueValues.emplace_back(V); 2734 } 2735 size_t NumUniqueScalarValues = UniqueValues.size(); 2736 if (NumUniqueScalarValues == VL.size()) { 2737 ReuseShuffleIndicies.clear(); 2738 } else { 2739 LLVM_DEBUG(dbgs() << "SLP: Shuffle for reused scalars.\n"); 2740 if (NumUniqueScalarValues <= 1 || 2741 !llvm::isPowerOf2_32(NumUniqueScalarValues)) { 2742 LLVM_DEBUG(dbgs() << "SLP: Scalar used twice in bundle.\n"); 2743 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2744 return; 2745 } 2746 VL = UniqueValues; 2747 } 2748 2749 auto &BSRef = BlocksSchedules[BB]; 2750 if (!BSRef) 2751 BSRef = std::make_unique<BlockScheduling>(BB); 2752 2753 BlockScheduling &BS = *BSRef.get(); 2754 2755 Optional<ScheduleData *> Bundle = BS.tryScheduleBundle(VL, this, S); 2756 if (!Bundle) { 2757 LLVM_DEBUG(dbgs() << "SLP: We are not able to schedule this bundle!\n"); 2758 assert((!BS.getScheduleData(VL0) || 2759 !BS.getScheduleData(VL0)->isPartOfBundle()) && 2760 "tryScheduleBundle should cancelScheduling on failure"); 2761 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2762 ReuseShuffleIndicies); 2763 return; 2764 } 2765 LLVM_DEBUG(dbgs() << "SLP: We are able to schedule this bundle.\n"); 2766 2767 unsigned ShuffleOrOp = S.isAltShuffle() ? 2768 (unsigned) Instruction::ShuffleVector : S.getOpcode(); 2769 switch (ShuffleOrOp) { 2770 case Instruction::PHI: { 2771 auto *PH = cast<PHINode>(VL0); 2772 2773 // Check for terminator values (e.g. invoke). 2774 for (Value *V : VL) 2775 for (unsigned I = 0, E = PH->getNumIncomingValues(); I < E; ++I) { 2776 Instruction *Term = dyn_cast<Instruction>( 2777 cast<PHINode>(V)->getIncomingValueForBlock( 2778 PH->getIncomingBlock(I))); 2779 if (Term && Term->isTerminator()) { 2780 LLVM_DEBUG(dbgs() 2781 << "SLP: Need to swizzle PHINodes (terminator use).\n"); 2782 BS.cancelScheduling(VL, VL0); 2783 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2784 ReuseShuffleIndicies); 2785 return; 2786 } 2787 } 2788 2789 TreeEntry *TE = 2790 newTreeEntry(VL, Bundle, S, UserTreeIdx, ReuseShuffleIndicies); 2791 LLVM_DEBUG(dbgs() << "SLP: added a vector of PHINodes.\n"); 2792 2793 // Keeps the reordered operands to avoid code duplication. 2794 SmallVector<ValueList, 2> OperandsVec; 2795 for (unsigned I = 0, E = PH->getNumIncomingValues(); I < E; ++I) { 2796 ValueList Operands; 2797 // Prepare the operand vector. 2798 for (Value *V : VL) 2799 Operands.push_back(cast<PHINode>(V)->getIncomingValueForBlock( 2800 PH->getIncomingBlock(I))); 2801 TE->setOperand(I, Operands); 2802 OperandsVec.push_back(Operands); 2803 } 2804 for (unsigned OpIdx = 0, OpE = OperandsVec.size(); OpIdx != OpE; ++OpIdx) 2805 buildTree_rec(OperandsVec[OpIdx], Depth + 1, {TE, OpIdx}); 2806 return; 2807 } 2808 case Instruction::ExtractValue: 2809 case Instruction::ExtractElement: { 2810 OrdersType CurrentOrder; 2811 bool Reuse = canReuseExtract(VL, VL0, CurrentOrder); 2812 if (Reuse) { 2813 LLVM_DEBUG(dbgs() << "SLP: Reusing or shuffling extract sequence.\n"); 2814 ++NumOpsWantToKeepOriginalOrder; 2815 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2816 ReuseShuffleIndicies); 2817 // This is a special case, as it does not gather, but at the same time 2818 // we are not extending buildTree_rec() towards the operands. 2819 ValueList Op0; 2820 Op0.assign(VL.size(), VL0->getOperand(0)); 2821 VectorizableTree.back()->setOperand(0, Op0); 2822 return; 2823 } 2824 if (!CurrentOrder.empty()) { 2825 LLVM_DEBUG({ 2826 dbgs() << "SLP: Reusing or shuffling of reordered extract sequence " 2827 "with order"; 2828 for (unsigned Idx : CurrentOrder) 2829 dbgs() << " " << Idx; 2830 dbgs() << "\n"; 2831 }); 2832 // Insert new order with initial value 0, if it does not exist, 2833 // otherwise return the iterator to the existing one. 2834 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2835 ReuseShuffleIndicies, CurrentOrder); 2836 findRootOrder(CurrentOrder); 2837 ++NumOpsWantToKeepOrder[CurrentOrder]; 2838 // This is a special case, as it does not gather, but at the same time 2839 // we are not extending buildTree_rec() towards the operands. 2840 ValueList Op0; 2841 Op0.assign(VL.size(), VL0->getOperand(0)); 2842 VectorizableTree.back()->setOperand(0, Op0); 2843 return; 2844 } 2845 LLVM_DEBUG(dbgs() << "SLP: Gather extract sequence.\n"); 2846 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2847 ReuseShuffleIndicies); 2848 BS.cancelScheduling(VL, VL0); 2849 return; 2850 } 2851 case Instruction::Load: { 2852 // Check that a vectorized load would load the same memory as a scalar 2853 // load. For example, we don't want to vectorize loads that are smaller 2854 // than 8-bit. Even though we have a packed struct {<i2, i2, i2, i2>} LLVM 2855 // treats loading/storing it as an i8 struct. If we vectorize loads/stores 2856 // from such a struct, we read/write packed bits disagreeing with the 2857 // unvectorized version. 2858 Type *ScalarTy = VL0->getType(); 2859 2860 if (DL->getTypeSizeInBits(ScalarTy) != 2861 DL->getTypeAllocSizeInBits(ScalarTy)) { 2862 BS.cancelScheduling(VL, VL0); 2863 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2864 ReuseShuffleIndicies); 2865 LLVM_DEBUG(dbgs() << "SLP: Gathering loads of non-packed type.\n"); 2866 return; 2867 } 2868 2869 // Make sure all loads in the bundle are simple - we can't vectorize 2870 // atomic or volatile loads. 2871 SmallVector<Value *, 4> PointerOps(VL.size()); 2872 auto POIter = PointerOps.begin(); 2873 for (Value *V : VL) { 2874 auto *L = cast<LoadInst>(V); 2875 if (!L->isSimple()) { 2876 BS.cancelScheduling(VL, VL0); 2877 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2878 ReuseShuffleIndicies); 2879 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple loads.\n"); 2880 return; 2881 } 2882 *POIter = L->getPointerOperand(); 2883 ++POIter; 2884 } 2885 2886 OrdersType CurrentOrder; 2887 // Check the order of pointer operands. 2888 if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) { 2889 Value *Ptr0; 2890 Value *PtrN; 2891 if (CurrentOrder.empty()) { 2892 Ptr0 = PointerOps.front(); 2893 PtrN = PointerOps.back(); 2894 } else { 2895 Ptr0 = PointerOps[CurrentOrder.front()]; 2896 PtrN = PointerOps[CurrentOrder.back()]; 2897 } 2898 Optional<int> Diff = getPointersDiff(Ptr0, PtrN, *DL, *SE); 2899 // Check that the sorted loads are consecutive. 2900 if (static_cast<unsigned>(*Diff) == VL.size() - 1) { 2901 if (CurrentOrder.empty()) { 2902 // Original loads are consecutive and does not require reordering. 2903 ++NumOpsWantToKeepOriginalOrder; 2904 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, 2905 UserTreeIdx, ReuseShuffleIndicies); 2906 TE->setOperandsInOrder(); 2907 LLVM_DEBUG(dbgs() << "SLP: added a vector of loads.\n"); 2908 } else { 2909 // Need to reorder. 2910 TreeEntry *TE = 2911 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2912 ReuseShuffleIndicies, CurrentOrder); 2913 TE->setOperandsInOrder(); 2914 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled loads.\n"); 2915 findRootOrder(CurrentOrder); 2916 ++NumOpsWantToKeepOrder[CurrentOrder]; 2917 } 2918 return; 2919 } 2920 // Vectorizing non-consecutive loads with `llvm.masked.gather`. 2921 TreeEntry *TE = newTreeEntry(VL, TreeEntry::ScatterVectorize, Bundle, S, 2922 UserTreeIdx, ReuseShuffleIndicies); 2923 TE->setOperandsInOrder(); 2924 buildTree_rec(PointerOps, Depth + 1, {TE, 0}); 2925 LLVM_DEBUG(dbgs() << "SLP: added a vector of non-consecutive loads.\n"); 2926 return; 2927 } 2928 2929 LLVM_DEBUG(dbgs() << "SLP: Gathering non-consecutive loads.\n"); 2930 BS.cancelScheduling(VL, VL0); 2931 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2932 ReuseShuffleIndicies); 2933 return; 2934 } 2935 case Instruction::ZExt: 2936 case Instruction::SExt: 2937 case Instruction::FPToUI: 2938 case Instruction::FPToSI: 2939 case Instruction::FPExt: 2940 case Instruction::PtrToInt: 2941 case Instruction::IntToPtr: 2942 case Instruction::SIToFP: 2943 case Instruction::UIToFP: 2944 case Instruction::Trunc: 2945 case Instruction::FPTrunc: 2946 case Instruction::BitCast: { 2947 Type *SrcTy = VL0->getOperand(0)->getType(); 2948 for (Value *V : VL) { 2949 Type *Ty = cast<Instruction>(V)->getOperand(0)->getType(); 2950 if (Ty != SrcTy || !isValidElementType(Ty)) { 2951 BS.cancelScheduling(VL, VL0); 2952 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2953 ReuseShuffleIndicies); 2954 LLVM_DEBUG(dbgs() 2955 << "SLP: Gathering casts with different src types.\n"); 2956 return; 2957 } 2958 } 2959 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2960 ReuseShuffleIndicies); 2961 LLVM_DEBUG(dbgs() << "SLP: added a vector of casts.\n"); 2962 2963 TE->setOperandsInOrder(); 2964 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 2965 ValueList Operands; 2966 // Prepare the operand vector. 2967 for (Value *V : VL) 2968 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 2969 2970 buildTree_rec(Operands, Depth + 1, {TE, i}); 2971 } 2972 return; 2973 } 2974 case Instruction::ICmp: 2975 case Instruction::FCmp: { 2976 // Check that all of the compares have the same predicate. 2977 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 2978 CmpInst::Predicate SwapP0 = CmpInst::getSwappedPredicate(P0); 2979 Type *ComparedTy = VL0->getOperand(0)->getType(); 2980 for (Value *V : VL) { 2981 CmpInst *Cmp = cast<CmpInst>(V); 2982 if ((Cmp->getPredicate() != P0 && Cmp->getPredicate() != SwapP0) || 2983 Cmp->getOperand(0)->getType() != ComparedTy) { 2984 BS.cancelScheduling(VL, VL0); 2985 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2986 ReuseShuffleIndicies); 2987 LLVM_DEBUG(dbgs() 2988 << "SLP: Gathering cmp with different predicate.\n"); 2989 return; 2990 } 2991 } 2992 2993 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2994 ReuseShuffleIndicies); 2995 LLVM_DEBUG(dbgs() << "SLP: added a vector of compares.\n"); 2996 2997 ValueList Left, Right; 2998 if (cast<CmpInst>(VL0)->isCommutative()) { 2999 // Commutative predicate - collect + sort operands of the instructions 3000 // so that each side is more likely to have the same opcode. 3001 assert(P0 == SwapP0 && "Commutative Predicate mismatch"); 3002 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 3003 } else { 3004 // Collect operands - commute if it uses the swapped predicate. 3005 for (Value *V : VL) { 3006 auto *Cmp = cast<CmpInst>(V); 3007 Value *LHS = Cmp->getOperand(0); 3008 Value *RHS = Cmp->getOperand(1); 3009 if (Cmp->getPredicate() != P0) 3010 std::swap(LHS, RHS); 3011 Left.push_back(LHS); 3012 Right.push_back(RHS); 3013 } 3014 } 3015 TE->setOperand(0, Left); 3016 TE->setOperand(1, Right); 3017 buildTree_rec(Left, Depth + 1, {TE, 0}); 3018 buildTree_rec(Right, Depth + 1, {TE, 1}); 3019 return; 3020 } 3021 case Instruction::Select: 3022 case Instruction::FNeg: 3023 case Instruction::Add: 3024 case Instruction::FAdd: 3025 case Instruction::Sub: 3026 case Instruction::FSub: 3027 case Instruction::Mul: 3028 case Instruction::FMul: 3029 case Instruction::UDiv: 3030 case Instruction::SDiv: 3031 case Instruction::FDiv: 3032 case Instruction::URem: 3033 case Instruction::SRem: 3034 case Instruction::FRem: 3035 case Instruction::Shl: 3036 case Instruction::LShr: 3037 case Instruction::AShr: 3038 case Instruction::And: 3039 case Instruction::Or: 3040 case Instruction::Xor: { 3041 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3042 ReuseShuffleIndicies); 3043 LLVM_DEBUG(dbgs() << "SLP: added a vector of un/bin op.\n"); 3044 3045 // Sort operands of the instructions so that each side is more likely to 3046 // have the same opcode. 3047 if (isa<BinaryOperator>(VL0) && VL0->isCommutative()) { 3048 ValueList Left, Right; 3049 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 3050 TE->setOperand(0, Left); 3051 TE->setOperand(1, Right); 3052 buildTree_rec(Left, Depth + 1, {TE, 0}); 3053 buildTree_rec(Right, Depth + 1, {TE, 1}); 3054 return; 3055 } 3056 3057 TE->setOperandsInOrder(); 3058 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 3059 ValueList Operands; 3060 // Prepare the operand vector. 3061 for (Value *V : VL) 3062 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3063 3064 buildTree_rec(Operands, Depth + 1, {TE, i}); 3065 } 3066 return; 3067 } 3068 case Instruction::GetElementPtr: { 3069 // We don't combine GEPs with complicated (nested) indexing. 3070 for (Value *V : VL) { 3071 if (cast<Instruction>(V)->getNumOperands() != 2) { 3072 LLVM_DEBUG(dbgs() << "SLP: not-vectorizable GEP (nested indexes).\n"); 3073 BS.cancelScheduling(VL, VL0); 3074 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3075 ReuseShuffleIndicies); 3076 return; 3077 } 3078 } 3079 3080 // We can't combine several GEPs into one vector if they operate on 3081 // different types. 3082 Type *Ty0 = VL0->getOperand(0)->getType(); 3083 for (Value *V : VL) { 3084 Type *CurTy = cast<Instruction>(V)->getOperand(0)->getType(); 3085 if (Ty0 != CurTy) { 3086 LLVM_DEBUG(dbgs() 3087 << "SLP: not-vectorizable GEP (different types).\n"); 3088 BS.cancelScheduling(VL, VL0); 3089 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3090 ReuseShuffleIndicies); 3091 return; 3092 } 3093 } 3094 3095 // We don't combine GEPs with non-constant indexes. 3096 Type *Ty1 = VL0->getOperand(1)->getType(); 3097 for (Value *V : VL) { 3098 auto Op = cast<Instruction>(V)->getOperand(1); 3099 if (!isa<ConstantInt>(Op) || 3100 (Op->getType() != Ty1 && 3101 Op->getType()->getScalarSizeInBits() > 3102 DL->getIndexSizeInBits( 3103 V->getType()->getPointerAddressSpace()))) { 3104 LLVM_DEBUG(dbgs() 3105 << "SLP: not-vectorizable GEP (non-constant indexes).\n"); 3106 BS.cancelScheduling(VL, VL0); 3107 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3108 ReuseShuffleIndicies); 3109 return; 3110 } 3111 } 3112 3113 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3114 ReuseShuffleIndicies); 3115 LLVM_DEBUG(dbgs() << "SLP: added a vector of GEPs.\n"); 3116 TE->setOperandsInOrder(); 3117 for (unsigned i = 0, e = 2; i < e; ++i) { 3118 ValueList Operands; 3119 // Prepare the operand vector. 3120 for (Value *V : VL) 3121 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3122 3123 buildTree_rec(Operands, Depth + 1, {TE, i}); 3124 } 3125 return; 3126 } 3127 case Instruction::Store: { 3128 // Check if the stores are consecutive or if we need to swizzle them. 3129 llvm::Type *ScalarTy = cast<StoreInst>(VL0)->getValueOperand()->getType(); 3130 // Avoid types that are padded when being allocated as scalars, while 3131 // being packed together in a vector (such as i1). 3132 if (DL->getTypeSizeInBits(ScalarTy) != 3133 DL->getTypeAllocSizeInBits(ScalarTy)) { 3134 BS.cancelScheduling(VL, VL0); 3135 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3136 ReuseShuffleIndicies); 3137 LLVM_DEBUG(dbgs() << "SLP: Gathering stores of non-packed type.\n"); 3138 return; 3139 } 3140 // Make sure all stores in the bundle are simple - we can't vectorize 3141 // atomic or volatile stores. 3142 SmallVector<Value *, 4> PointerOps(VL.size()); 3143 ValueList Operands(VL.size()); 3144 auto POIter = PointerOps.begin(); 3145 auto OIter = Operands.begin(); 3146 for (Value *V : VL) { 3147 auto *SI = cast<StoreInst>(V); 3148 if (!SI->isSimple()) { 3149 BS.cancelScheduling(VL, VL0); 3150 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3151 ReuseShuffleIndicies); 3152 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple stores.\n"); 3153 return; 3154 } 3155 *POIter = SI->getPointerOperand(); 3156 *OIter = SI->getValueOperand(); 3157 ++POIter; 3158 ++OIter; 3159 } 3160 3161 OrdersType CurrentOrder; 3162 // Check the order of pointer operands. 3163 if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) { 3164 Value *Ptr0; 3165 Value *PtrN; 3166 if (CurrentOrder.empty()) { 3167 Ptr0 = PointerOps.front(); 3168 PtrN = PointerOps.back(); 3169 } else { 3170 Ptr0 = PointerOps[CurrentOrder.front()]; 3171 PtrN = PointerOps[CurrentOrder.back()]; 3172 } 3173 Optional<int> Dist = getPointersDiff(Ptr0, PtrN, *DL, *SE); 3174 // Check that the sorted pointer operands are consecutive. 3175 if (static_cast<unsigned>(*Dist) == VL.size() - 1) { 3176 if (CurrentOrder.empty()) { 3177 // Original stores are consecutive and does not require reordering. 3178 ++NumOpsWantToKeepOriginalOrder; 3179 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, 3180 UserTreeIdx, ReuseShuffleIndicies); 3181 TE->setOperandsInOrder(); 3182 buildTree_rec(Operands, Depth + 1, {TE, 0}); 3183 LLVM_DEBUG(dbgs() << "SLP: added a vector of stores.\n"); 3184 } else { 3185 TreeEntry *TE = 3186 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3187 ReuseShuffleIndicies, CurrentOrder); 3188 TE->setOperandsInOrder(); 3189 buildTree_rec(Operands, Depth + 1, {TE, 0}); 3190 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled stores.\n"); 3191 findRootOrder(CurrentOrder); 3192 ++NumOpsWantToKeepOrder[CurrentOrder]; 3193 } 3194 return; 3195 } 3196 } 3197 3198 BS.cancelScheduling(VL, VL0); 3199 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3200 ReuseShuffleIndicies); 3201 LLVM_DEBUG(dbgs() << "SLP: Non-consecutive store.\n"); 3202 return; 3203 } 3204 case Instruction::Call: { 3205 // Check if the calls are all to the same vectorizable intrinsic or 3206 // library function. 3207 CallInst *CI = cast<CallInst>(VL0); 3208 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3209 3210 VFShape Shape = VFShape::get( 3211 *CI, ElementCount::getFixed(static_cast<unsigned int>(VL.size())), 3212 false /*HasGlobalPred*/); 3213 Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape); 3214 3215 if (!VecFunc && !isTriviallyVectorizable(ID)) { 3216 BS.cancelScheduling(VL, VL0); 3217 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3218 ReuseShuffleIndicies); 3219 LLVM_DEBUG(dbgs() << "SLP: Non-vectorizable call.\n"); 3220 return; 3221 } 3222 Function *F = CI->getCalledFunction(); 3223 unsigned NumArgs = CI->getNumArgOperands(); 3224 SmallVector<Value*, 4> ScalarArgs(NumArgs, nullptr); 3225 for (unsigned j = 0; j != NumArgs; ++j) 3226 if (hasVectorInstrinsicScalarOpd(ID, j)) 3227 ScalarArgs[j] = CI->getArgOperand(j); 3228 for (Value *V : VL) { 3229 CallInst *CI2 = dyn_cast<CallInst>(V); 3230 if (!CI2 || CI2->getCalledFunction() != F || 3231 getVectorIntrinsicIDForCall(CI2, TLI) != ID || 3232 (VecFunc && 3233 VecFunc != VFDatabase(*CI2).getVectorizedFunction(Shape)) || 3234 !CI->hasIdenticalOperandBundleSchema(*CI2)) { 3235 BS.cancelScheduling(VL, VL0); 3236 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3237 ReuseShuffleIndicies); 3238 LLVM_DEBUG(dbgs() << "SLP: mismatched calls:" << *CI << "!=" << *V 3239 << "\n"); 3240 return; 3241 } 3242 // Some intrinsics have scalar arguments and should be same in order for 3243 // them to be vectorized. 3244 for (unsigned j = 0; j != NumArgs; ++j) { 3245 if (hasVectorInstrinsicScalarOpd(ID, j)) { 3246 Value *A1J = CI2->getArgOperand(j); 3247 if (ScalarArgs[j] != A1J) { 3248 BS.cancelScheduling(VL, VL0); 3249 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3250 ReuseShuffleIndicies); 3251 LLVM_DEBUG(dbgs() << "SLP: mismatched arguments in call:" << *CI 3252 << " argument " << ScalarArgs[j] << "!=" << A1J 3253 << "\n"); 3254 return; 3255 } 3256 } 3257 } 3258 // Verify that the bundle operands are identical between the two calls. 3259 if (CI->hasOperandBundles() && 3260 !std::equal(CI->op_begin() + CI->getBundleOperandsStartIndex(), 3261 CI->op_begin() + CI->getBundleOperandsEndIndex(), 3262 CI2->op_begin() + CI2->getBundleOperandsStartIndex())) { 3263 BS.cancelScheduling(VL, VL0); 3264 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3265 ReuseShuffleIndicies); 3266 LLVM_DEBUG(dbgs() << "SLP: mismatched bundle operands in calls:" 3267 << *CI << "!=" << *V << '\n'); 3268 return; 3269 } 3270 } 3271 3272 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3273 ReuseShuffleIndicies); 3274 TE->setOperandsInOrder(); 3275 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 3276 ValueList Operands; 3277 // Prepare the operand vector. 3278 for (Value *V : VL) { 3279 auto *CI2 = cast<CallInst>(V); 3280 Operands.push_back(CI2->getArgOperand(i)); 3281 } 3282 buildTree_rec(Operands, Depth + 1, {TE, i}); 3283 } 3284 return; 3285 } 3286 case Instruction::ShuffleVector: { 3287 // If this is not an alternate sequence of opcode like add-sub 3288 // then do not vectorize this instruction. 3289 if (!S.isAltShuffle()) { 3290 BS.cancelScheduling(VL, VL0); 3291 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3292 ReuseShuffleIndicies); 3293 LLVM_DEBUG(dbgs() << "SLP: ShuffleVector are not vectorized.\n"); 3294 return; 3295 } 3296 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3297 ReuseShuffleIndicies); 3298 LLVM_DEBUG(dbgs() << "SLP: added a ShuffleVector op.\n"); 3299 3300 // Reorder operands if reordering would enable vectorization. 3301 if (isa<BinaryOperator>(VL0)) { 3302 ValueList Left, Right; 3303 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 3304 TE->setOperand(0, Left); 3305 TE->setOperand(1, Right); 3306 buildTree_rec(Left, Depth + 1, {TE, 0}); 3307 buildTree_rec(Right, Depth + 1, {TE, 1}); 3308 return; 3309 } 3310 3311 TE->setOperandsInOrder(); 3312 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 3313 ValueList Operands; 3314 // Prepare the operand vector. 3315 for (Value *V : VL) 3316 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3317 3318 buildTree_rec(Operands, Depth + 1, {TE, i}); 3319 } 3320 return; 3321 } 3322 default: 3323 BS.cancelScheduling(VL, VL0); 3324 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3325 ReuseShuffleIndicies); 3326 LLVM_DEBUG(dbgs() << "SLP: Gathering unknown instruction.\n"); 3327 return; 3328 } 3329 } 3330 3331 unsigned BoUpSLP::canMapToVector(Type *T, const DataLayout &DL) const { 3332 unsigned N = 1; 3333 Type *EltTy = T; 3334 3335 while (isa<StructType>(EltTy) || isa<ArrayType>(EltTy) || 3336 isa<VectorType>(EltTy)) { 3337 if (auto *ST = dyn_cast<StructType>(EltTy)) { 3338 // Check that struct is homogeneous. 3339 for (const auto *Ty : ST->elements()) 3340 if (Ty != *ST->element_begin()) 3341 return 0; 3342 N *= ST->getNumElements(); 3343 EltTy = *ST->element_begin(); 3344 } else if (auto *AT = dyn_cast<ArrayType>(EltTy)) { 3345 N *= AT->getNumElements(); 3346 EltTy = AT->getElementType(); 3347 } else { 3348 auto *VT = cast<FixedVectorType>(EltTy); 3349 N *= VT->getNumElements(); 3350 EltTy = VT->getElementType(); 3351 } 3352 } 3353 3354 if (!isValidElementType(EltTy)) 3355 return 0; 3356 uint64_t VTSize = DL.getTypeStoreSizeInBits(FixedVectorType::get(EltTy, N)); 3357 if (VTSize < MinVecRegSize || VTSize > MaxVecRegSize || VTSize != DL.getTypeStoreSizeInBits(T)) 3358 return 0; 3359 return N; 3360 } 3361 3362 bool BoUpSLP::canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 3363 SmallVectorImpl<unsigned> &CurrentOrder) const { 3364 Instruction *E0 = cast<Instruction>(OpValue); 3365 assert(E0->getOpcode() == Instruction::ExtractElement || 3366 E0->getOpcode() == Instruction::ExtractValue); 3367 assert(E0->getOpcode() == getSameOpcode(VL).getOpcode() && "Invalid opcode"); 3368 // Check if all of the extracts come from the same vector and from the 3369 // correct offset. 3370 Value *Vec = E0->getOperand(0); 3371 3372 CurrentOrder.clear(); 3373 3374 // We have to extract from a vector/aggregate with the same number of elements. 3375 unsigned NElts; 3376 if (E0->getOpcode() == Instruction::ExtractValue) { 3377 const DataLayout &DL = E0->getModule()->getDataLayout(); 3378 NElts = canMapToVector(Vec->getType(), DL); 3379 if (!NElts) 3380 return false; 3381 // Check if load can be rewritten as load of vector. 3382 LoadInst *LI = dyn_cast<LoadInst>(Vec); 3383 if (!LI || !LI->isSimple() || !LI->hasNUses(VL.size())) 3384 return false; 3385 } else { 3386 NElts = cast<FixedVectorType>(Vec->getType())->getNumElements(); 3387 } 3388 3389 if (NElts != VL.size()) 3390 return false; 3391 3392 // Check that all of the indices extract from the correct offset. 3393 bool ShouldKeepOrder = true; 3394 unsigned E = VL.size(); 3395 // Assign to all items the initial value E + 1 so we can check if the extract 3396 // instruction index was used already. 3397 // Also, later we can check that all the indices are used and we have a 3398 // consecutive access in the extract instructions, by checking that no 3399 // element of CurrentOrder still has value E + 1. 3400 CurrentOrder.assign(E, E + 1); 3401 unsigned I = 0; 3402 for (; I < E; ++I) { 3403 auto *Inst = cast<Instruction>(VL[I]); 3404 if (Inst->getOperand(0) != Vec) 3405 break; 3406 Optional<unsigned> Idx = getExtractIndex(Inst); 3407 if (!Idx) 3408 break; 3409 const unsigned ExtIdx = *Idx; 3410 if (ExtIdx != I) { 3411 if (ExtIdx >= E || CurrentOrder[ExtIdx] != E + 1) 3412 break; 3413 ShouldKeepOrder = false; 3414 CurrentOrder[ExtIdx] = I; 3415 } else { 3416 if (CurrentOrder[I] != E + 1) 3417 break; 3418 CurrentOrder[I] = I; 3419 } 3420 } 3421 if (I < E) { 3422 CurrentOrder.clear(); 3423 return false; 3424 } 3425 3426 return ShouldKeepOrder; 3427 } 3428 3429 bool BoUpSLP::areAllUsersVectorized(Instruction *I) const { 3430 return I->hasOneUse() || llvm::all_of(I->users(), [this](User *U) { 3431 return ScalarToTreeEntry.count(U) > 0; 3432 }); 3433 } 3434 3435 static std::pair<InstructionCost, InstructionCost> 3436 getVectorCallCosts(CallInst *CI, FixedVectorType *VecTy, 3437 TargetTransformInfo *TTI, TargetLibraryInfo *TLI) { 3438 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3439 3440 // Calculate the cost of the scalar and vector calls. 3441 SmallVector<Type *, 4> VecTys; 3442 for (Use &Arg : CI->args()) 3443 VecTys.push_back( 3444 FixedVectorType::get(Arg->getType(), VecTy->getNumElements())); 3445 FastMathFlags FMF; 3446 if (auto *FPCI = dyn_cast<FPMathOperator>(CI)) 3447 FMF = FPCI->getFastMathFlags(); 3448 SmallVector<const Value *> Arguments(CI->arg_begin(), CI->arg_end()); 3449 IntrinsicCostAttributes CostAttrs(ID, VecTy, Arguments, VecTys, FMF, 3450 dyn_cast<IntrinsicInst>(CI)); 3451 auto IntrinsicCost = 3452 TTI->getIntrinsicInstrCost(CostAttrs, TTI::TCK_RecipThroughput); 3453 3454 auto Shape = VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>( 3455 VecTy->getNumElements())), 3456 false /*HasGlobalPred*/); 3457 Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape); 3458 auto LibCost = IntrinsicCost; 3459 if (!CI->isNoBuiltin() && VecFunc) { 3460 // Calculate the cost of the vector library call. 3461 // If the corresponding vector call is cheaper, return its cost. 3462 LibCost = TTI->getCallInstrCost(nullptr, VecTy, VecTys, 3463 TTI::TCK_RecipThroughput); 3464 } 3465 return {IntrinsicCost, LibCost}; 3466 } 3467 3468 /// Compute the cost of creating a vector of type \p VecTy containing the 3469 /// extracted values from \p VL. 3470 static InstructionCost 3471 computeExtractCost(ArrayRef<Value *> VL, FixedVectorType *VecTy, 3472 TargetTransformInfo::ShuffleKind ShuffleKind, 3473 ArrayRef<int> Mask, TargetTransformInfo &TTI) { 3474 unsigned NumOfParts = TTI.getNumberOfParts(VecTy); 3475 3476 if (ShuffleKind != TargetTransformInfo::SK_PermuteSingleSrc || !NumOfParts || 3477 VecTy->getNumElements() < NumOfParts) 3478 return TTI.getShuffleCost(ShuffleKind, VecTy, Mask); 3479 3480 bool AllConsecutive = true; 3481 unsigned EltsPerVector = VecTy->getNumElements() / NumOfParts; 3482 unsigned Idx = -1; 3483 InstructionCost Cost = 0; 3484 3485 // Process extracts in blocks of EltsPerVector to check if the source vector 3486 // operand can be re-used directly. If not, add the cost of creating a shuffle 3487 // to extract the values into a vector register. 3488 for (auto *V : VL) { 3489 ++Idx; 3490 3491 // Reached the start of a new vector registers. 3492 if (Idx % EltsPerVector == 0) { 3493 AllConsecutive = true; 3494 continue; 3495 } 3496 3497 // Check all extracts for a vector register on the target directly 3498 // extract values in order. 3499 unsigned CurrentIdx = *getExtractIndex(cast<Instruction>(V)); 3500 unsigned PrevIdx = *getExtractIndex(cast<Instruction>(VL[Idx - 1])); 3501 AllConsecutive &= PrevIdx + 1 == CurrentIdx && 3502 CurrentIdx % EltsPerVector == Idx % EltsPerVector; 3503 3504 if (AllConsecutive) 3505 continue; 3506 3507 // Skip all indices, except for the last index per vector block. 3508 if ((Idx + 1) % EltsPerVector != 0 && Idx + 1 != VL.size()) 3509 continue; 3510 3511 // If we have a series of extracts which are not consecutive and hence 3512 // cannot re-use the source vector register directly, compute the shuffle 3513 // cost to extract the a vector with EltsPerVector elements. 3514 Cost += TTI.getShuffleCost( 3515 TargetTransformInfo::SK_PermuteSingleSrc, 3516 FixedVectorType::get(VecTy->getElementType(), EltsPerVector)); 3517 } 3518 return Cost; 3519 } 3520 3521 InstructionCost BoUpSLP::getEntryCost(TreeEntry *E) { 3522 ArrayRef<Value*> VL = E->Scalars; 3523 3524 Type *ScalarTy = VL[0]->getType(); 3525 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 3526 ScalarTy = SI->getValueOperand()->getType(); 3527 else if (CmpInst *CI = dyn_cast<CmpInst>(VL[0])) 3528 ScalarTy = CI->getOperand(0)->getType(); 3529 auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); 3530 TTI::TargetCostKind CostKind = TTI::TCK_RecipThroughput; 3531 3532 // If we have computed a smaller type for the expression, update VecTy so 3533 // that the costs will be accurate. 3534 if (MinBWs.count(VL[0])) 3535 VecTy = FixedVectorType::get( 3536 IntegerType::get(F->getContext(), MinBWs[VL[0]].first), VL.size()); 3537 3538 unsigned ReuseShuffleNumbers = E->ReuseShuffleIndices.size(); 3539 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 3540 InstructionCost ReuseShuffleCost = 0; 3541 if (NeedToShuffleReuses) { 3542 ReuseShuffleCost = 3543 TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, VecTy, 3544 E->ReuseShuffleIndices); 3545 } 3546 // FIXME: it tries to fix a problem with MSVC buildbots. 3547 TargetTransformInfo &TTIRef = *TTI; 3548 auto &&AdjustExtractsCost = [this, &TTIRef, CostKind, VL, 3549 VecTy](InstructionCost &Cost, bool IsGather) { 3550 DenseMap<Value *, int> ExtractVectorsTys; 3551 for (auto *V : VL) { 3552 // If all users of instruction are going to be vectorized and this 3553 // instruction itself is not going to be vectorized, consider this 3554 // instruction as dead and remove its cost from the final cost of the 3555 // vectorized tree. 3556 if (IsGather && (!areAllUsersVectorized(cast<Instruction>(V)) || 3557 ScalarToTreeEntry.count(V))) 3558 continue; 3559 auto *EE = cast<ExtractElementInst>(V); 3560 unsigned Idx = *getExtractIndex(EE); 3561 if (TTIRef.getNumberOfParts(VecTy) != 3562 TTIRef.getNumberOfParts(EE->getVectorOperandType())) { 3563 auto It = 3564 ExtractVectorsTys.try_emplace(EE->getVectorOperand(), Idx).first; 3565 It->getSecond() = std::min<int>(It->second, Idx); 3566 } 3567 // Take credit for instruction that will become dead. 3568 if (EE->hasOneUse()) { 3569 Instruction *Ext = EE->user_back(); 3570 if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) && 3571 all_of(Ext->users(), 3572 [](User *U) { return isa<GetElementPtrInst>(U); })) { 3573 // Use getExtractWithExtendCost() to calculate the cost of 3574 // extractelement/ext pair. 3575 Cost -= 3576 TTIRef.getExtractWithExtendCost(Ext->getOpcode(), Ext->getType(), 3577 EE->getVectorOperandType(), Idx); 3578 // Add back the cost of s|zext which is subtracted separately. 3579 Cost += TTIRef.getCastInstrCost( 3580 Ext->getOpcode(), Ext->getType(), EE->getType(), 3581 TTI::getCastContextHint(Ext), CostKind, Ext); 3582 continue; 3583 } 3584 } 3585 Cost -= TTIRef.getVectorInstrCost(Instruction::ExtractElement, 3586 EE->getVectorOperandType(), Idx); 3587 } 3588 // Add a cost for subvector extracts/inserts if required. 3589 for (const auto &Data : ExtractVectorsTys) { 3590 auto *EEVTy = cast<FixedVectorType>(Data.first->getType()); 3591 unsigned NumElts = VecTy->getNumElements(); 3592 if (TTIRef.getNumberOfParts(EEVTy) > TTIRef.getNumberOfParts(VecTy)) 3593 Cost += TTIRef.getShuffleCost(TargetTransformInfo::SK_ExtractSubvector, 3594 EEVTy, None, 3595 (Data.second / NumElts) * NumElts, VecTy); 3596 else 3597 Cost += TTIRef.getShuffleCost(TargetTransformInfo::SK_InsertSubvector, 3598 VecTy, None, 0, EEVTy); 3599 } 3600 }; 3601 if (E->State == TreeEntry::NeedToGather) { 3602 if (allConstant(VL)) 3603 return 0; 3604 if (isSplat(VL)) { 3605 return ReuseShuffleCost + 3606 TTI->getShuffleCost(TargetTransformInfo::SK_Broadcast, VecTy, None, 3607 0); 3608 } 3609 if (E->getOpcode() == Instruction::ExtractElement && 3610 allSameType(VL) && allSameBlock(VL)) { 3611 SmallVector<int> Mask; 3612 Optional<TargetTransformInfo::ShuffleKind> ShuffleKind = 3613 isShuffle(VL, Mask); 3614 if (ShuffleKind.hasValue()) { 3615 InstructionCost Cost = 3616 computeExtractCost(VL, VecTy, *ShuffleKind, Mask, *TTI); 3617 AdjustExtractsCost(Cost, /*IsGather=*/true); 3618 return ReuseShuffleCost + Cost; 3619 } 3620 } 3621 InstructionCost GatherCost = 0; 3622 SmallVector<int> Mask; 3623 SmallVector<const TreeEntry *> Entries; 3624 Optional<TargetTransformInfo::ShuffleKind> Shuffle = 3625 isGatherShuffledEntry(E, Mask, Entries); 3626 if (Shuffle.hasValue()) { 3627 if (ShuffleVectorInst::isIdentityMask(Mask)) { 3628 LLVM_DEBUG( 3629 dbgs() 3630 << "SLP: perfect diamond match for gather bundle that starts with " 3631 << *VL.front() << ".\n"); 3632 } else { 3633 LLVM_DEBUG(dbgs() << "SLP: shuffled " << Entries.size() 3634 << " entries for bundle that starts with " 3635 << *VL.front() << ".\n"); 3636 GatherCost = TTI->getShuffleCost(*Shuffle, VecTy, Mask); 3637 } 3638 } else { 3639 GatherCost = getGatherCost(VL); 3640 } 3641 return ReuseShuffleCost + GatherCost; 3642 } 3643 assert((E->State == TreeEntry::Vectorize || 3644 E->State == TreeEntry::ScatterVectorize) && 3645 "Unhandled state"); 3646 assert(E->getOpcode() && allSameType(VL) && allSameBlock(VL) && "Invalid VL"); 3647 Instruction *VL0 = E->getMainOp(); 3648 unsigned ShuffleOrOp = 3649 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 3650 switch (ShuffleOrOp) { 3651 case Instruction::PHI: 3652 return 0; 3653 3654 case Instruction::ExtractValue: 3655 case Instruction::ExtractElement: { 3656 // The common cost of removal ExtractElement/ExtractValue instructions + 3657 // the cost of shuffles, if required to resuffle the original vector. 3658 InstructionCost CommonCost = 0; 3659 if (NeedToShuffleReuses) { 3660 unsigned Idx = 0; 3661 for (unsigned I : E->ReuseShuffleIndices) { 3662 if (ShuffleOrOp == Instruction::ExtractElement) { 3663 auto *EE = cast<ExtractElementInst>(VL[I]); 3664 ReuseShuffleCost -= TTI->getVectorInstrCost( 3665 Instruction::ExtractElement, EE->getVectorOperandType(), 3666 *getExtractIndex(EE)); 3667 } else { 3668 ReuseShuffleCost -= TTI->getVectorInstrCost( 3669 Instruction::ExtractElement, VecTy, Idx); 3670 ++Idx; 3671 } 3672 } 3673 Idx = ReuseShuffleNumbers; 3674 for (Value *V : VL) { 3675 if (ShuffleOrOp == Instruction::ExtractElement) { 3676 auto *EE = cast<ExtractElementInst>(V); 3677 ReuseShuffleCost += TTI->getVectorInstrCost( 3678 Instruction::ExtractElement, EE->getVectorOperandType(), 3679 *getExtractIndex(EE)); 3680 } else { 3681 --Idx; 3682 ReuseShuffleCost += TTI->getVectorInstrCost( 3683 Instruction::ExtractElement, VecTy, Idx); 3684 } 3685 } 3686 CommonCost = ReuseShuffleCost; 3687 } else if (!E->ReorderIndices.empty()) { 3688 SmallVector<int> NewMask; 3689 inversePermutation(E->ReorderIndices, NewMask); 3690 CommonCost = TTI->getShuffleCost( 3691 TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask); 3692 } 3693 if (ShuffleOrOp == Instruction::ExtractValue) { 3694 for (unsigned I = 0, E = VL.size(); I < E; ++I) { 3695 auto *EI = cast<Instruction>(VL[I]); 3696 // Take credit for instruction that will become dead. 3697 if (EI->hasOneUse()) { 3698 Instruction *Ext = EI->user_back(); 3699 if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) && 3700 all_of(Ext->users(), 3701 [](User *U) { return isa<GetElementPtrInst>(U); })) { 3702 // Use getExtractWithExtendCost() to calculate the cost of 3703 // extractelement/ext pair. 3704 CommonCost -= TTI->getExtractWithExtendCost( 3705 Ext->getOpcode(), Ext->getType(), VecTy, I); 3706 // Add back the cost of s|zext which is subtracted separately. 3707 CommonCost += TTI->getCastInstrCost( 3708 Ext->getOpcode(), Ext->getType(), EI->getType(), 3709 TTI::getCastContextHint(Ext), CostKind, Ext); 3710 continue; 3711 } 3712 } 3713 CommonCost -= 3714 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, I); 3715 } 3716 } else { 3717 AdjustExtractsCost(CommonCost, /*IsGather=*/false); 3718 } 3719 return CommonCost; 3720 } 3721 case Instruction::ZExt: 3722 case Instruction::SExt: 3723 case Instruction::FPToUI: 3724 case Instruction::FPToSI: 3725 case Instruction::FPExt: 3726 case Instruction::PtrToInt: 3727 case Instruction::IntToPtr: 3728 case Instruction::SIToFP: 3729 case Instruction::UIToFP: 3730 case Instruction::Trunc: 3731 case Instruction::FPTrunc: 3732 case Instruction::BitCast: { 3733 Type *SrcTy = VL0->getOperand(0)->getType(); 3734 InstructionCost ScalarEltCost = 3735 TTI->getCastInstrCost(E->getOpcode(), ScalarTy, SrcTy, 3736 TTI::getCastContextHint(VL0), CostKind, VL0); 3737 if (NeedToShuffleReuses) { 3738 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3739 } 3740 3741 // Calculate the cost of this instruction. 3742 InstructionCost ScalarCost = VL.size() * ScalarEltCost; 3743 3744 auto *SrcVecTy = FixedVectorType::get(SrcTy, VL.size()); 3745 InstructionCost VecCost = 0; 3746 // Check if the values are candidates to demote. 3747 if (!MinBWs.count(VL0) || VecTy != SrcVecTy) { 3748 VecCost = 3749 ReuseShuffleCost + 3750 TTI->getCastInstrCost(E->getOpcode(), VecTy, SrcVecTy, 3751 TTI::getCastContextHint(VL0), CostKind, VL0); 3752 } 3753 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3754 return VecCost - ScalarCost; 3755 } 3756 case Instruction::FCmp: 3757 case Instruction::ICmp: 3758 case Instruction::Select: { 3759 // Calculate the cost of this instruction. 3760 InstructionCost ScalarEltCost = 3761 TTI->getCmpSelInstrCost(E->getOpcode(), ScalarTy, Builder.getInt1Ty(), 3762 CmpInst::BAD_ICMP_PREDICATE, CostKind, VL0); 3763 if (NeedToShuffleReuses) { 3764 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3765 } 3766 auto *MaskTy = FixedVectorType::get(Builder.getInt1Ty(), VL.size()); 3767 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3768 3769 // Check if all entries in VL are either compares or selects with compares 3770 // as condition that have the same predicates. 3771 CmpInst::Predicate VecPred = CmpInst::BAD_ICMP_PREDICATE; 3772 bool First = true; 3773 for (auto *V : VL) { 3774 CmpInst::Predicate CurrentPred; 3775 auto MatchCmp = m_Cmp(CurrentPred, m_Value(), m_Value()); 3776 if ((!match(V, m_Select(MatchCmp, m_Value(), m_Value())) && 3777 !match(V, MatchCmp)) || 3778 (!First && VecPred != CurrentPred)) { 3779 VecPred = CmpInst::BAD_ICMP_PREDICATE; 3780 break; 3781 } 3782 First = false; 3783 VecPred = CurrentPred; 3784 } 3785 3786 InstructionCost VecCost = TTI->getCmpSelInstrCost( 3787 E->getOpcode(), VecTy, MaskTy, VecPred, CostKind, VL0); 3788 // Check if it is possible and profitable to use min/max for selects in 3789 // VL. 3790 // 3791 auto IntrinsicAndUse = canConvertToMinOrMaxIntrinsic(VL); 3792 if (IntrinsicAndUse.first != Intrinsic::not_intrinsic) { 3793 IntrinsicCostAttributes CostAttrs(IntrinsicAndUse.first, VecTy, 3794 {VecTy, VecTy}); 3795 InstructionCost IntrinsicCost = 3796 TTI->getIntrinsicInstrCost(CostAttrs, CostKind); 3797 // If the selects are the only uses of the compares, they will be dead 3798 // and we can adjust the cost by removing their cost. 3799 if (IntrinsicAndUse.second) 3800 IntrinsicCost -= 3801 TTI->getCmpSelInstrCost(Instruction::ICmp, VecTy, MaskTy, 3802 CmpInst::BAD_ICMP_PREDICATE, CostKind); 3803 VecCost = std::min(VecCost, IntrinsicCost); 3804 } 3805 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3806 return ReuseShuffleCost + VecCost - ScalarCost; 3807 } 3808 case Instruction::FNeg: 3809 case Instruction::Add: 3810 case Instruction::FAdd: 3811 case Instruction::Sub: 3812 case Instruction::FSub: 3813 case Instruction::Mul: 3814 case Instruction::FMul: 3815 case Instruction::UDiv: 3816 case Instruction::SDiv: 3817 case Instruction::FDiv: 3818 case Instruction::URem: 3819 case Instruction::SRem: 3820 case Instruction::FRem: 3821 case Instruction::Shl: 3822 case Instruction::LShr: 3823 case Instruction::AShr: 3824 case Instruction::And: 3825 case Instruction::Or: 3826 case Instruction::Xor: { 3827 // Certain instructions can be cheaper to vectorize if they have a 3828 // constant second vector operand. 3829 TargetTransformInfo::OperandValueKind Op1VK = 3830 TargetTransformInfo::OK_AnyValue; 3831 TargetTransformInfo::OperandValueKind Op2VK = 3832 TargetTransformInfo::OK_UniformConstantValue; 3833 TargetTransformInfo::OperandValueProperties Op1VP = 3834 TargetTransformInfo::OP_None; 3835 TargetTransformInfo::OperandValueProperties Op2VP = 3836 TargetTransformInfo::OP_PowerOf2; 3837 3838 // If all operands are exactly the same ConstantInt then set the 3839 // operand kind to OK_UniformConstantValue. 3840 // If instead not all operands are constants, then set the operand kind 3841 // to OK_AnyValue. If all operands are constants but not the same, 3842 // then set the operand kind to OK_NonUniformConstantValue. 3843 ConstantInt *CInt0 = nullptr; 3844 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 3845 const Instruction *I = cast<Instruction>(VL[i]); 3846 unsigned OpIdx = isa<BinaryOperator>(I) ? 1 : 0; 3847 ConstantInt *CInt = dyn_cast<ConstantInt>(I->getOperand(OpIdx)); 3848 if (!CInt) { 3849 Op2VK = TargetTransformInfo::OK_AnyValue; 3850 Op2VP = TargetTransformInfo::OP_None; 3851 break; 3852 } 3853 if (Op2VP == TargetTransformInfo::OP_PowerOf2 && 3854 !CInt->getValue().isPowerOf2()) 3855 Op2VP = TargetTransformInfo::OP_None; 3856 if (i == 0) { 3857 CInt0 = CInt; 3858 continue; 3859 } 3860 if (CInt0 != CInt) 3861 Op2VK = TargetTransformInfo::OK_NonUniformConstantValue; 3862 } 3863 3864 SmallVector<const Value *, 4> Operands(VL0->operand_values()); 3865 InstructionCost ScalarEltCost = 3866 TTI->getArithmeticInstrCost(E->getOpcode(), ScalarTy, CostKind, Op1VK, 3867 Op2VK, Op1VP, Op2VP, Operands, VL0); 3868 if (NeedToShuffleReuses) { 3869 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3870 } 3871 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3872 InstructionCost VecCost = 3873 TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind, Op1VK, 3874 Op2VK, Op1VP, Op2VP, Operands, VL0); 3875 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3876 return ReuseShuffleCost + VecCost - ScalarCost; 3877 } 3878 case Instruction::GetElementPtr: { 3879 TargetTransformInfo::OperandValueKind Op1VK = 3880 TargetTransformInfo::OK_AnyValue; 3881 TargetTransformInfo::OperandValueKind Op2VK = 3882 TargetTransformInfo::OK_UniformConstantValue; 3883 3884 InstructionCost ScalarEltCost = TTI->getArithmeticInstrCost( 3885 Instruction::Add, ScalarTy, CostKind, Op1VK, Op2VK); 3886 if (NeedToShuffleReuses) { 3887 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3888 } 3889 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3890 InstructionCost VecCost = TTI->getArithmeticInstrCost( 3891 Instruction::Add, VecTy, CostKind, Op1VK, Op2VK); 3892 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3893 return ReuseShuffleCost + VecCost - ScalarCost; 3894 } 3895 case Instruction::Load: { 3896 // Cost of wide load - cost of scalar loads. 3897 Align alignment = cast<LoadInst>(VL0)->getAlign(); 3898 InstructionCost ScalarEltCost = TTI->getMemoryOpCost( 3899 Instruction::Load, ScalarTy, alignment, 0, CostKind, VL0); 3900 if (NeedToShuffleReuses) { 3901 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3902 } 3903 InstructionCost ScalarLdCost = VecTy->getNumElements() * ScalarEltCost; 3904 InstructionCost VecLdCost; 3905 if (E->State == TreeEntry::Vectorize) { 3906 VecLdCost = TTI->getMemoryOpCost(Instruction::Load, VecTy, alignment, 0, 3907 CostKind, VL0); 3908 } else { 3909 assert(E->State == TreeEntry::ScatterVectorize && "Unknown EntryState"); 3910 VecLdCost = TTI->getGatherScatterOpCost( 3911 Instruction::Load, VecTy, cast<LoadInst>(VL0)->getPointerOperand(), 3912 /*VariableMask=*/false, alignment, CostKind, VL0); 3913 } 3914 if (!NeedToShuffleReuses && !E->ReorderIndices.empty()) { 3915 SmallVector<int> NewMask; 3916 inversePermutation(E->ReorderIndices, NewMask); 3917 VecLdCost += TTI->getShuffleCost( 3918 TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask); 3919 } 3920 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecLdCost, ScalarLdCost)); 3921 return ReuseShuffleCost + VecLdCost - ScalarLdCost; 3922 } 3923 case Instruction::Store: { 3924 // We know that we can merge the stores. Calculate the cost. 3925 bool IsReorder = !E->ReorderIndices.empty(); 3926 auto *SI = 3927 cast<StoreInst>(IsReorder ? VL[E->ReorderIndices.front()] : VL0); 3928 Align Alignment = SI->getAlign(); 3929 InstructionCost ScalarEltCost = TTI->getMemoryOpCost( 3930 Instruction::Store, ScalarTy, Alignment, 0, CostKind, VL0); 3931 InstructionCost ScalarStCost = VecTy->getNumElements() * ScalarEltCost; 3932 InstructionCost VecStCost = TTI->getMemoryOpCost( 3933 Instruction::Store, VecTy, Alignment, 0, CostKind, VL0); 3934 if (IsReorder) { 3935 SmallVector<int> NewMask; 3936 inversePermutation(E->ReorderIndices, NewMask); 3937 VecStCost += TTI->getShuffleCost( 3938 TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask); 3939 } 3940 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecStCost, ScalarStCost)); 3941 return VecStCost - ScalarStCost; 3942 } 3943 case Instruction::Call: { 3944 CallInst *CI = cast<CallInst>(VL0); 3945 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3946 3947 // Calculate the cost of the scalar and vector calls. 3948 IntrinsicCostAttributes CostAttrs(ID, *CI, 1); 3949 InstructionCost ScalarEltCost = 3950 TTI->getIntrinsicInstrCost(CostAttrs, CostKind); 3951 if (NeedToShuffleReuses) { 3952 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3953 } 3954 InstructionCost ScalarCallCost = VecTy->getNumElements() * ScalarEltCost; 3955 3956 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 3957 InstructionCost VecCallCost = 3958 std::min(VecCallCosts.first, VecCallCosts.second); 3959 3960 LLVM_DEBUG(dbgs() << "SLP: Call cost " << VecCallCost - ScalarCallCost 3961 << " (" << VecCallCost << "-" << ScalarCallCost << ")" 3962 << " for " << *CI << "\n"); 3963 3964 return ReuseShuffleCost + VecCallCost - ScalarCallCost; 3965 } 3966 case Instruction::ShuffleVector: { 3967 assert(E->isAltShuffle() && 3968 ((Instruction::isBinaryOp(E->getOpcode()) && 3969 Instruction::isBinaryOp(E->getAltOpcode())) || 3970 (Instruction::isCast(E->getOpcode()) && 3971 Instruction::isCast(E->getAltOpcode()))) && 3972 "Invalid Shuffle Vector Operand"); 3973 InstructionCost ScalarCost = 0; 3974 if (NeedToShuffleReuses) { 3975 for (unsigned Idx : E->ReuseShuffleIndices) { 3976 Instruction *I = cast<Instruction>(VL[Idx]); 3977 ReuseShuffleCost -= TTI->getInstructionCost(I, CostKind); 3978 } 3979 for (Value *V : VL) { 3980 Instruction *I = cast<Instruction>(V); 3981 ReuseShuffleCost += TTI->getInstructionCost(I, CostKind); 3982 } 3983 } 3984 for (Value *V : VL) { 3985 Instruction *I = cast<Instruction>(V); 3986 assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode"); 3987 ScalarCost += TTI->getInstructionCost(I, CostKind); 3988 } 3989 // VecCost is equal to sum of the cost of creating 2 vectors 3990 // and the cost of creating shuffle. 3991 InstructionCost VecCost = 0; 3992 if (Instruction::isBinaryOp(E->getOpcode())) { 3993 VecCost = TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind); 3994 VecCost += TTI->getArithmeticInstrCost(E->getAltOpcode(), VecTy, 3995 CostKind); 3996 } else { 3997 Type *Src0SclTy = E->getMainOp()->getOperand(0)->getType(); 3998 Type *Src1SclTy = E->getAltOp()->getOperand(0)->getType(); 3999 auto *Src0Ty = FixedVectorType::get(Src0SclTy, VL.size()); 4000 auto *Src1Ty = FixedVectorType::get(Src1SclTy, VL.size()); 4001 VecCost = TTI->getCastInstrCost(E->getOpcode(), VecTy, Src0Ty, 4002 TTI::CastContextHint::None, CostKind); 4003 VecCost += TTI->getCastInstrCost(E->getAltOpcode(), VecTy, Src1Ty, 4004 TTI::CastContextHint::None, CostKind); 4005 } 4006 4007 SmallVector<int> Mask(E->Scalars.size()); 4008 for (unsigned I = 0, End = E->Scalars.size(); I < End; ++I) { 4009 auto *OpInst = cast<Instruction>(E->Scalars[I]); 4010 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 4011 Mask[I] = I + (OpInst->getOpcode() == E->getAltOpcode() ? End : 0); 4012 } 4013 VecCost += 4014 TTI->getShuffleCost(TargetTransformInfo::SK_Select, VecTy, Mask, 0); 4015 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 4016 return ReuseShuffleCost + VecCost - ScalarCost; 4017 } 4018 default: 4019 llvm_unreachable("Unknown instruction"); 4020 } 4021 } 4022 4023 bool BoUpSLP::isFullyVectorizableTinyTree() const { 4024 LLVM_DEBUG(dbgs() << "SLP: Check whether the tree with height " 4025 << VectorizableTree.size() << " is fully vectorizable .\n"); 4026 4027 // We only handle trees of heights 1 and 2. 4028 if (VectorizableTree.size() == 1 && 4029 VectorizableTree[0]->State == TreeEntry::Vectorize) 4030 return true; 4031 4032 if (VectorizableTree.size() != 2) 4033 return false; 4034 4035 // Handle splat and all-constants stores. 4036 if (VectorizableTree[0]->State == TreeEntry::Vectorize && 4037 (allConstant(VectorizableTree[1]->Scalars) || 4038 isSplat(VectorizableTree[1]->Scalars))) 4039 return true; 4040 4041 // Gathering cost would be too much for tiny trees. 4042 if (VectorizableTree[0]->State == TreeEntry::NeedToGather || 4043 VectorizableTree[1]->State == TreeEntry::NeedToGather) 4044 return false; 4045 4046 return true; 4047 } 4048 4049 static bool isLoadCombineCandidateImpl(Value *Root, unsigned NumElts, 4050 TargetTransformInfo *TTI) { 4051 // Look past the root to find a source value. Arbitrarily follow the 4052 // path through operand 0 of any 'or'. Also, peek through optional 4053 // shift-left-by-multiple-of-8-bits. 4054 Value *ZextLoad = Root; 4055 const APInt *ShAmtC; 4056 while (!isa<ConstantExpr>(ZextLoad) && 4057 (match(ZextLoad, m_Or(m_Value(), m_Value())) || 4058 (match(ZextLoad, m_Shl(m_Value(), m_APInt(ShAmtC))) && 4059 ShAmtC->urem(8) == 0))) 4060 ZextLoad = cast<BinaryOperator>(ZextLoad)->getOperand(0); 4061 4062 // Check if the input is an extended load of the required or/shift expression. 4063 Value *LoadPtr; 4064 if (ZextLoad == Root || !match(ZextLoad, m_ZExt(m_Load(m_Value(LoadPtr))))) 4065 return false; 4066 4067 // Require that the total load bit width is a legal integer type. 4068 // For example, <8 x i8> --> i64 is a legal integer on a 64-bit target. 4069 // But <16 x i8> --> i128 is not, so the backend probably can't reduce it. 4070 Type *SrcTy = LoadPtr->getType()->getPointerElementType(); 4071 unsigned LoadBitWidth = SrcTy->getIntegerBitWidth() * NumElts; 4072 if (!TTI->isTypeLegal(IntegerType::get(Root->getContext(), LoadBitWidth))) 4073 return false; 4074 4075 // Everything matched - assume that we can fold the whole sequence using 4076 // load combining. 4077 LLVM_DEBUG(dbgs() << "SLP: Assume load combining for tree starting at " 4078 << *(cast<Instruction>(Root)) << "\n"); 4079 4080 return true; 4081 } 4082 4083 bool BoUpSLP::isLoadCombineReductionCandidate(RecurKind RdxKind) const { 4084 if (RdxKind != RecurKind::Or) 4085 return false; 4086 4087 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 4088 Value *FirstReduced = VectorizableTree[0]->Scalars[0]; 4089 return isLoadCombineCandidateImpl(FirstReduced, NumElts, TTI); 4090 } 4091 4092 bool BoUpSLP::isLoadCombineCandidate() const { 4093 // Peek through a final sequence of stores and check if all operations are 4094 // likely to be load-combined. 4095 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 4096 for (Value *Scalar : VectorizableTree[0]->Scalars) { 4097 Value *X; 4098 if (!match(Scalar, m_Store(m_Value(X), m_Value())) || 4099 !isLoadCombineCandidateImpl(X, NumElts, TTI)) 4100 return false; 4101 } 4102 return true; 4103 } 4104 4105 bool BoUpSLP::isTreeTinyAndNotFullyVectorizable() const { 4106 // We can vectorize the tree if its size is greater than or equal to the 4107 // minimum size specified by the MinTreeSize command line option. 4108 if (VectorizableTree.size() >= MinTreeSize) 4109 return false; 4110 4111 // If we have a tiny tree (a tree whose size is less than MinTreeSize), we 4112 // can vectorize it if we can prove it fully vectorizable. 4113 if (isFullyVectorizableTinyTree()) 4114 return false; 4115 4116 assert(VectorizableTree.empty() 4117 ? ExternalUses.empty() 4118 : true && "We shouldn't have any external users"); 4119 4120 // Otherwise, we can't vectorize the tree. It is both tiny and not fully 4121 // vectorizable. 4122 return true; 4123 } 4124 4125 InstructionCost BoUpSLP::getSpillCost() const { 4126 // Walk from the bottom of the tree to the top, tracking which values are 4127 // live. When we see a call instruction that is not part of our tree, 4128 // query TTI to see if there is a cost to keeping values live over it 4129 // (for example, if spills and fills are required). 4130 unsigned BundleWidth = VectorizableTree.front()->Scalars.size(); 4131 InstructionCost Cost = 0; 4132 4133 SmallPtrSet<Instruction*, 4> LiveValues; 4134 Instruction *PrevInst = nullptr; 4135 4136 // The entries in VectorizableTree are not necessarily ordered by their 4137 // position in basic blocks. Collect them and order them by dominance so later 4138 // instructions are guaranteed to be visited first. For instructions in 4139 // different basic blocks, we only scan to the beginning of the block, so 4140 // their order does not matter, as long as all instructions in a basic block 4141 // are grouped together. Using dominance ensures a deterministic order. 4142 SmallVector<Instruction *, 16> OrderedScalars; 4143 for (const auto &TEPtr : VectorizableTree) { 4144 Instruction *Inst = dyn_cast<Instruction>(TEPtr->Scalars[0]); 4145 if (!Inst) 4146 continue; 4147 OrderedScalars.push_back(Inst); 4148 } 4149 llvm::stable_sort(OrderedScalars, [this](Instruction *A, Instruction *B) { 4150 return DT->dominates(B, A); 4151 }); 4152 4153 for (Instruction *Inst : OrderedScalars) { 4154 if (!PrevInst) { 4155 PrevInst = Inst; 4156 continue; 4157 } 4158 4159 // Update LiveValues. 4160 LiveValues.erase(PrevInst); 4161 for (auto &J : PrevInst->operands()) { 4162 if (isa<Instruction>(&*J) && getTreeEntry(&*J)) 4163 LiveValues.insert(cast<Instruction>(&*J)); 4164 } 4165 4166 LLVM_DEBUG({ 4167 dbgs() << "SLP: #LV: " << LiveValues.size(); 4168 for (auto *X : LiveValues) 4169 dbgs() << " " << X->getName(); 4170 dbgs() << ", Looking at "; 4171 Inst->dump(); 4172 }); 4173 4174 // Now find the sequence of instructions between PrevInst and Inst. 4175 unsigned NumCalls = 0; 4176 BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(), 4177 PrevInstIt = 4178 PrevInst->getIterator().getReverse(); 4179 while (InstIt != PrevInstIt) { 4180 if (PrevInstIt == PrevInst->getParent()->rend()) { 4181 PrevInstIt = Inst->getParent()->rbegin(); 4182 continue; 4183 } 4184 4185 // Debug information does not impact spill cost. 4186 if ((isa<CallInst>(&*PrevInstIt) && 4187 !isa<DbgInfoIntrinsic>(&*PrevInstIt)) && 4188 &*PrevInstIt != PrevInst) 4189 NumCalls++; 4190 4191 ++PrevInstIt; 4192 } 4193 4194 if (NumCalls) { 4195 SmallVector<Type*, 4> V; 4196 for (auto *II : LiveValues) 4197 V.push_back(FixedVectorType::get(II->getType(), BundleWidth)); 4198 Cost += NumCalls * TTI->getCostOfKeepingLiveOverCall(V); 4199 } 4200 4201 PrevInst = Inst; 4202 } 4203 4204 return Cost; 4205 } 4206 4207 InstructionCost BoUpSLP::getTreeCost() { 4208 InstructionCost Cost = 0; 4209 LLVM_DEBUG(dbgs() << "SLP: Calculating cost for tree of size " 4210 << VectorizableTree.size() << ".\n"); 4211 4212 unsigned BundleWidth = VectorizableTree[0]->Scalars.size(); 4213 4214 for (unsigned I = 0, E = VectorizableTree.size(); I < E; ++I) { 4215 TreeEntry &TE = *VectorizableTree[I].get(); 4216 4217 // We create duplicate tree entries for gather sequences that have multiple 4218 // uses. However, we should not compute the cost of duplicate sequences. 4219 // For example, if we have a build vector (i.e., insertelement sequence) 4220 // that is used by more than one vector instruction, we only need to 4221 // compute the cost of the insertelement instructions once. The redundant 4222 // instructions will be eliminated by CSE. 4223 // 4224 // We should consider not creating duplicate tree entries for gather 4225 // sequences, and instead add additional edges to the tree representing 4226 // their uses. Since such an approach results in fewer total entries, 4227 // existing heuristics based on tree size may yield different results. 4228 // 4229 if (TE.State == TreeEntry::NeedToGather && 4230 std::any_of(std::next(VectorizableTree.begin(), I + 1), 4231 VectorizableTree.end(), 4232 [TE](const std::unique_ptr<TreeEntry> &EntryPtr) { 4233 return EntryPtr->State == TreeEntry::NeedToGather && 4234 EntryPtr->isSame(TE.Scalars); 4235 })) 4236 continue; 4237 4238 InstructionCost C = getEntryCost(&TE); 4239 Cost += C; 4240 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C 4241 << " for bundle that starts with " << *TE.Scalars[0] 4242 << ".\n" 4243 << "SLP: Current total cost = " << Cost << "\n"); 4244 } 4245 4246 SmallPtrSet<Value *, 16> ExtractCostCalculated; 4247 InstructionCost ExtractCost = 0; 4248 for (ExternalUser &EU : ExternalUses) { 4249 // We only add extract cost once for the same scalar. 4250 if (!ExtractCostCalculated.insert(EU.Scalar).second) 4251 continue; 4252 4253 // Uses by ephemeral values are free (because the ephemeral value will be 4254 // removed prior to code generation, and so the extraction will be 4255 // removed as well). 4256 if (EphValues.count(EU.User)) 4257 continue; 4258 4259 // If we plan to rewrite the tree in a smaller type, we will need to sign 4260 // extend the extracted value back to the original type. Here, we account 4261 // for the extract and the added cost of the sign extend if needed. 4262 auto *VecTy = FixedVectorType::get(EU.Scalar->getType(), BundleWidth); 4263 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 4264 if (MinBWs.count(ScalarRoot)) { 4265 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 4266 auto Extend = 4267 MinBWs[ScalarRoot].second ? Instruction::SExt : Instruction::ZExt; 4268 VecTy = FixedVectorType::get(MinTy, BundleWidth); 4269 ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(), 4270 VecTy, EU.Lane); 4271 } else { 4272 ExtractCost += 4273 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, EU.Lane); 4274 } 4275 } 4276 4277 InstructionCost SpillCost = getSpillCost(); 4278 Cost += SpillCost + ExtractCost; 4279 4280 #ifndef NDEBUG 4281 SmallString<256> Str; 4282 { 4283 raw_svector_ostream OS(Str); 4284 OS << "SLP: Spill Cost = " << SpillCost << ".\n" 4285 << "SLP: Extract Cost = " << ExtractCost << ".\n" 4286 << "SLP: Total Cost = " << Cost << ".\n"; 4287 } 4288 LLVM_DEBUG(dbgs() << Str); 4289 if (ViewSLPTree) 4290 ViewGraph(this, "SLP" + F->getName(), false, Str); 4291 #endif 4292 4293 return Cost; 4294 } 4295 4296 Optional<TargetTransformInfo::ShuffleKind> 4297 BoUpSLP::isGatherShuffledEntry(const TreeEntry *TE, SmallVectorImpl<int> &Mask, 4298 SmallVectorImpl<const TreeEntry *> &Entries) { 4299 auto *VLIt = find_if(VectorizableTree, 4300 [TE](const std::unique_ptr<TreeEntry> &EntryPtr) { 4301 return EntryPtr.get() == TE; 4302 }); 4303 assert(VLIt != VectorizableTree.end() && 4304 "Gathered values should be in the tree."); 4305 Mask.assign(TE->Scalars.size(), UndefMaskElem); 4306 Entries.clear(); 4307 DenseMap<const TreeEntry *, int> Used; 4308 int NumShuffles = 0; 4309 for (int I = 0, E = TE->Scalars.size(); I < E; ++I) { 4310 Value *V = TE->Scalars[I]; 4311 const TreeEntry *VTE = getTreeEntry(V); 4312 if (!VTE) { 4313 // Check if it is used in one of the gathered entries. 4314 const auto *It = 4315 find_if(make_range(VectorizableTree.begin(), VLIt), 4316 [V](const std::unique_ptr<TreeEntry> &EntryPtr) { 4317 return EntryPtr->State == TreeEntry::NeedToGather && 4318 is_contained(EntryPtr->Scalars, V); 4319 }); 4320 if (It != VLIt) 4321 VTE = It->get(); 4322 } 4323 if (VTE) { 4324 auto Res = Used.try_emplace(VTE, NumShuffles); 4325 if (Res.second) { 4326 Entries.push_back(VTE); 4327 ++NumShuffles; 4328 if (NumShuffles > 2) 4329 return None; 4330 if (NumShuffles == 2) { 4331 unsigned FirstSz = Entries.front()->Scalars.size(); 4332 if (!Entries.front()->ReuseShuffleIndices.empty()) 4333 FirstSz = Entries.front()->ReuseShuffleIndices.size(); 4334 unsigned SecondSz = Entries.back()->Scalars.size(); 4335 if (!Entries.back()->ReuseShuffleIndices.empty()) 4336 SecondSz = Entries.back()->ReuseShuffleIndices.size(); 4337 if (FirstSz != SecondSz) 4338 return None; 4339 } 4340 } 4341 int FoundLane = 4342 findLaneForValue(VTE->Scalars, VTE->ReuseShuffleIndices, V); 4343 unsigned Sz = VTE->Scalars.size(); 4344 if (!VTE->ReuseShuffleIndices.empty()) 4345 Sz = VTE->ReuseShuffleIndices.size(); 4346 Mask[I] = Res.first->second * Sz + FoundLane; 4347 // Extra check required by isSingleSourceMaskImpl function (called by 4348 // ShuffleVectorInst::isSingleSourceMask). 4349 if (Mask[I] >= 2 * E) 4350 return None; 4351 continue; 4352 } 4353 return None; 4354 } 4355 if (NumShuffles == 1) { 4356 if (ShuffleVectorInst::isReverseMask(Mask)) 4357 return TargetTransformInfo::SK_Reverse; 4358 return TargetTransformInfo::SK_PermuteSingleSrc; 4359 } 4360 if (NumShuffles == 2) { 4361 if (ShuffleVectorInst::isSelectMask(Mask)) 4362 return TargetTransformInfo::SK_Select; 4363 if (ShuffleVectorInst::isTransposeMask(Mask)) 4364 return TargetTransformInfo::SK_Transpose; 4365 return TargetTransformInfo::SK_PermuteTwoSrc; 4366 } 4367 return None; 4368 } 4369 4370 InstructionCost 4371 BoUpSLP::getGatherCost(FixedVectorType *Ty, 4372 const DenseSet<unsigned> &ShuffledIndices) const { 4373 unsigned NumElts = Ty->getNumElements(); 4374 APInt DemandedElts = APInt::getNullValue(NumElts); 4375 for (unsigned I = 0; I < NumElts; ++I) 4376 if (!ShuffledIndices.count(I)) 4377 DemandedElts.setBit(I); 4378 InstructionCost Cost = 4379 TTI->getScalarizationOverhead(Ty, DemandedElts, /*Insert*/ true, 4380 /*Extract*/ false); 4381 if (!ShuffledIndices.empty()) 4382 Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, Ty); 4383 return Cost; 4384 } 4385 4386 InstructionCost BoUpSLP::getGatherCost(ArrayRef<Value *> VL) const { 4387 // Find the type of the operands in VL. 4388 Type *ScalarTy = VL[0]->getType(); 4389 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 4390 ScalarTy = SI->getValueOperand()->getType(); 4391 auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); 4392 // Find the cost of inserting/extracting values from the vector. 4393 // Check if the same elements are inserted several times and count them as 4394 // shuffle candidates. 4395 DenseSet<unsigned> ShuffledElements; 4396 DenseSet<Value *> UniqueElements; 4397 // Iterate in reverse order to consider insert elements with the high cost. 4398 for (unsigned I = VL.size(); I > 0; --I) { 4399 unsigned Idx = I - 1; 4400 if (!UniqueElements.insert(VL[Idx]).second) 4401 ShuffledElements.insert(Idx); 4402 } 4403 return getGatherCost(VecTy, ShuffledElements); 4404 } 4405 4406 // Perform operand reordering on the instructions in VL and return the reordered 4407 // operands in Left and Right. 4408 void BoUpSLP::reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 4409 SmallVectorImpl<Value *> &Left, 4410 SmallVectorImpl<Value *> &Right, 4411 const DataLayout &DL, 4412 ScalarEvolution &SE, 4413 const BoUpSLP &R) { 4414 if (VL.empty()) 4415 return; 4416 VLOperands Ops(VL, DL, SE, R); 4417 // Reorder the operands in place. 4418 Ops.reorder(); 4419 Left = Ops.getVL(0); 4420 Right = Ops.getVL(1); 4421 } 4422 4423 void BoUpSLP::setInsertPointAfterBundle(TreeEntry *E) { 4424 // Get the basic block this bundle is in. All instructions in the bundle 4425 // should be in this block. 4426 auto *Front = E->getMainOp(); 4427 auto *BB = Front->getParent(); 4428 assert(llvm::all_of(E->Scalars, [=](Value *V) -> bool { 4429 auto *I = cast<Instruction>(V); 4430 return !E->isOpcodeOrAlt(I) || I->getParent() == BB; 4431 })); 4432 4433 // The last instruction in the bundle in program order. 4434 Instruction *LastInst = nullptr; 4435 4436 // Find the last instruction. The common case should be that BB has been 4437 // scheduled, and the last instruction is VL.back(). So we start with 4438 // VL.back() and iterate over schedule data until we reach the end of the 4439 // bundle. The end of the bundle is marked by null ScheduleData. 4440 if (BlocksSchedules.count(BB)) { 4441 auto *Bundle = 4442 BlocksSchedules[BB]->getScheduleData(E->isOneOf(E->Scalars.back())); 4443 if (Bundle && Bundle->isPartOfBundle()) 4444 for (; Bundle; Bundle = Bundle->NextInBundle) 4445 if (Bundle->OpValue == Bundle->Inst) 4446 LastInst = Bundle->Inst; 4447 } 4448 4449 // LastInst can still be null at this point if there's either not an entry 4450 // for BB in BlocksSchedules or there's no ScheduleData available for 4451 // VL.back(). This can be the case if buildTree_rec aborts for various 4452 // reasons (e.g., the maximum recursion depth is reached, the maximum region 4453 // size is reached, etc.). ScheduleData is initialized in the scheduling 4454 // "dry-run". 4455 // 4456 // If this happens, we can still find the last instruction by brute force. We 4457 // iterate forwards from Front (inclusive) until we either see all 4458 // instructions in the bundle or reach the end of the block. If Front is the 4459 // last instruction in program order, LastInst will be set to Front, and we 4460 // will visit all the remaining instructions in the block. 4461 // 4462 // One of the reasons we exit early from buildTree_rec is to place an upper 4463 // bound on compile-time. Thus, taking an additional compile-time hit here is 4464 // not ideal. However, this should be exceedingly rare since it requires that 4465 // we both exit early from buildTree_rec and that the bundle be out-of-order 4466 // (causing us to iterate all the way to the end of the block). 4467 if (!LastInst) { 4468 SmallPtrSet<Value *, 16> Bundle(E->Scalars.begin(), E->Scalars.end()); 4469 for (auto &I : make_range(BasicBlock::iterator(Front), BB->end())) { 4470 if (Bundle.erase(&I) && E->isOpcodeOrAlt(&I)) 4471 LastInst = &I; 4472 if (Bundle.empty()) 4473 break; 4474 } 4475 } 4476 assert(LastInst && "Failed to find last instruction in bundle"); 4477 4478 // Set the insertion point after the last instruction in the bundle. Set the 4479 // debug location to Front. 4480 Builder.SetInsertPoint(BB, ++LastInst->getIterator()); 4481 Builder.SetCurrentDebugLocation(Front->getDebugLoc()); 4482 } 4483 4484 Value *BoUpSLP::gather(ArrayRef<Value *> VL) { 4485 Value *Val0 = 4486 isa<StoreInst>(VL[0]) ? cast<StoreInst>(VL[0])->getValueOperand() : VL[0]; 4487 FixedVectorType *VecTy = FixedVectorType::get(Val0->getType(), VL.size()); 4488 Value *Vec = PoisonValue::get(VecTy); 4489 unsigned InsIndex = 0; 4490 for (Value *Val : VL) { 4491 Vec = Builder.CreateInsertElement(Vec, Val, Builder.getInt32(InsIndex++)); 4492 auto *InsElt = dyn_cast<InsertElementInst>(Vec); 4493 if (!InsElt) 4494 continue; 4495 GatherSeq.insert(InsElt); 4496 CSEBlocks.insert(InsElt->getParent()); 4497 // Add to our 'need-to-extract' list. 4498 if (TreeEntry *Entry = getTreeEntry(Val)) { 4499 // Find which lane we need to extract. 4500 int FoundLane = 4501 findLaneForValue(Entry->Scalars, Entry->ReuseShuffleIndices, Val); 4502 ExternalUses.push_back(ExternalUser(Val, InsElt, FoundLane)); 4503 } 4504 } 4505 4506 return Vec; 4507 } 4508 4509 Value *BoUpSLP::vectorizeTree(ArrayRef<Value *> VL) { 4510 InstructionsState S = getSameOpcode(VL); 4511 if (S.getOpcode()) { 4512 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 4513 if (E->isSame(VL)) { 4514 Value *V = vectorizeTree(E); 4515 if (VL.size() == E->Scalars.size() && !E->ReuseShuffleIndices.empty()) { 4516 // Reshuffle to get only unique values. 4517 // If some of the scalars are duplicated in the vectorization tree 4518 // entry, we do not vectorize them but instead generate a mask for the 4519 // reuses. But if there are several users of the same entry, they may 4520 // have different vectorization factors. This is especially important 4521 // for PHI nodes. In this case, we need to adapt the resulting 4522 // instruction for the user vectorization factor and have to reshuffle 4523 // it again to take only unique elements of the vector. Without this 4524 // code the function incorrectly returns reduced vector instruction 4525 // with the same elements, not with the unique ones. 4526 // block: 4527 // %phi = phi <2 x > { .., %entry} {%shuffle, %block} 4528 // %2 = shuffle <2 x > %phi, %poison, <4 x > <0, 0, 1, 1> 4529 // ... (use %2) 4530 // %shuffle = shuffle <2 x> %2, poison, <2 x> {0, 2} 4531 // br %block 4532 SmallVector<int, 4> UniqueIdxs; 4533 SmallSet<int, 4> UsedIdxs; 4534 int Pos = 0; 4535 for (int Idx : E->ReuseShuffleIndices) { 4536 if (UsedIdxs.insert(Idx).second) 4537 UniqueIdxs.emplace_back(Pos); 4538 ++Pos; 4539 } 4540 V = Builder.CreateShuffleVector(V, UniqueIdxs, "shrink.shuffle"); 4541 } 4542 return V; 4543 } 4544 } 4545 } 4546 4547 // Check that every instruction appears once in this bundle. 4548 SmallVector<int, 4> ReuseShuffleIndicies; 4549 SmallVector<Value *, 4> UniqueValues; 4550 if (VL.size() > 2) { 4551 DenseMap<Value *, unsigned> UniquePositions; 4552 for (Value *V : VL) { 4553 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 4554 ReuseShuffleIndicies.emplace_back(Res.first->second); 4555 if (Res.second || isa<Constant>(V)) 4556 UniqueValues.emplace_back(V); 4557 } 4558 // Do not shuffle single element or if number of unique values is not power 4559 // of 2. 4560 if (UniqueValues.size() == VL.size() || UniqueValues.size() <= 1 || 4561 !llvm::isPowerOf2_32(UniqueValues.size())) 4562 ReuseShuffleIndicies.clear(); 4563 else 4564 VL = UniqueValues; 4565 } 4566 4567 Value *Vec = gather(VL); 4568 if (!ReuseShuffleIndicies.empty()) { 4569 Vec = Builder.CreateShuffleVector(Vec, ReuseShuffleIndicies, "shuffle"); 4570 if (auto *I = dyn_cast<Instruction>(Vec)) { 4571 GatherSeq.insert(I); 4572 CSEBlocks.insert(I->getParent()); 4573 } 4574 } 4575 return Vec; 4576 } 4577 4578 namespace { 4579 /// Merges shuffle masks and emits final shuffle instruction, if required. 4580 class ShuffleInstructionBuilder { 4581 IRBuilderBase &Builder; 4582 bool IsFinalized = false; 4583 SmallVector<int, 4> Mask; 4584 4585 public: 4586 ShuffleInstructionBuilder(IRBuilderBase &Builder) : Builder(Builder) {} 4587 4588 /// Adds a mask, inverting it before applying. 4589 void addInversedMask(ArrayRef<unsigned> SubMask) { 4590 if (SubMask.empty()) 4591 return; 4592 SmallVector<int, 4> NewMask; 4593 inversePermutation(SubMask, NewMask); 4594 addMask(NewMask); 4595 } 4596 4597 /// Functions adds masks, merging them into single one. 4598 void addMask(ArrayRef<unsigned> SubMask) { 4599 SmallVector<int, 4> NewMask(SubMask.begin(), SubMask.end()); 4600 addMask(NewMask); 4601 } 4602 4603 void addMask(ArrayRef<int> SubMask) { 4604 if (SubMask.empty()) 4605 return; 4606 if (Mask.empty()) { 4607 Mask.append(SubMask.begin(), SubMask.end()); 4608 return; 4609 } 4610 SmallVector<int, 4> NewMask(SubMask.size(), SubMask.size()); 4611 int TermValue = std::min(Mask.size(), SubMask.size()); 4612 for (int I = 0, E = SubMask.size(); I < E; ++I) { 4613 if (SubMask[I] >= TermValue || Mask[SubMask[I]] >= TermValue) { 4614 NewMask[I] = E; 4615 continue; 4616 } 4617 NewMask[I] = Mask[SubMask[I]]; 4618 } 4619 Mask.swap(NewMask); 4620 } 4621 4622 Value *finalize(Value *V) { 4623 IsFinalized = true; 4624 if (Mask.empty()) 4625 return V; 4626 return Builder.CreateShuffleVector(V, Mask, "shuffle"); 4627 } 4628 4629 ~ShuffleInstructionBuilder() { 4630 assert((IsFinalized || Mask.empty()) && 4631 "Shuffle construction must be finalized."); 4632 } 4633 }; 4634 } // namespace 4635 4636 Value *BoUpSLP::vectorizeTree(TreeEntry *E) { 4637 IRBuilder<>::InsertPointGuard Guard(Builder); 4638 4639 if (E->VectorizedValue) { 4640 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *E->Scalars[0] << ".\n"); 4641 return E->VectorizedValue; 4642 } 4643 4644 ShuffleInstructionBuilder ShuffleBuilder(Builder); 4645 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 4646 if (E->State == TreeEntry::NeedToGather) { 4647 setInsertPointAfterBundle(E); 4648 Value *Vec; 4649 SmallVector<int> Mask; 4650 SmallVector<const TreeEntry *> Entries; 4651 Optional<TargetTransformInfo::ShuffleKind> Shuffle = 4652 isGatherShuffledEntry(E, Mask, Entries); 4653 if (Shuffle.hasValue()) { 4654 assert((Entries.size() == 1 || Entries.size() == 2) && 4655 "Expected shuffle of 1 or 2 entries."); 4656 Vec = Builder.CreateShuffleVector(Entries.front()->VectorizedValue, 4657 Entries.back()->VectorizedValue, Mask); 4658 } else { 4659 Vec = gather(E->Scalars); 4660 } 4661 if (NeedToShuffleReuses) { 4662 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4663 Vec = ShuffleBuilder.finalize(Vec); 4664 if (auto *I = dyn_cast<Instruction>(Vec)) { 4665 GatherSeq.insert(I); 4666 CSEBlocks.insert(I->getParent()); 4667 } 4668 } 4669 E->VectorizedValue = Vec; 4670 return Vec; 4671 } 4672 4673 assert((E->State == TreeEntry::Vectorize || 4674 E->State == TreeEntry::ScatterVectorize) && 4675 "Unhandled state"); 4676 unsigned ShuffleOrOp = 4677 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 4678 Instruction *VL0 = E->getMainOp(); 4679 Type *ScalarTy = VL0->getType(); 4680 if (auto *Store = dyn_cast<StoreInst>(VL0)) 4681 ScalarTy = Store->getValueOperand()->getType(); 4682 auto *VecTy = FixedVectorType::get(ScalarTy, E->Scalars.size()); 4683 switch (ShuffleOrOp) { 4684 case Instruction::PHI: { 4685 auto *PH = cast<PHINode>(VL0); 4686 Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI()); 4687 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 4688 PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues()); 4689 Value *V = NewPhi; 4690 if (NeedToShuffleReuses) 4691 V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle"); 4692 4693 E->VectorizedValue = V; 4694 4695 // PHINodes may have multiple entries from the same block. We want to 4696 // visit every block once. 4697 SmallPtrSet<BasicBlock*, 4> VisitedBBs; 4698 4699 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 4700 ValueList Operands; 4701 BasicBlock *IBB = PH->getIncomingBlock(i); 4702 4703 if (!VisitedBBs.insert(IBB).second) { 4704 NewPhi->addIncoming(NewPhi->getIncomingValueForBlock(IBB), IBB); 4705 continue; 4706 } 4707 4708 Builder.SetInsertPoint(IBB->getTerminator()); 4709 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 4710 Value *Vec = vectorizeTree(E->getOperand(i)); 4711 NewPhi->addIncoming(Vec, IBB); 4712 } 4713 4714 assert(NewPhi->getNumIncomingValues() == PH->getNumIncomingValues() && 4715 "Invalid number of incoming values"); 4716 return V; 4717 } 4718 4719 case Instruction::ExtractElement: { 4720 Value *V = E->getSingleOperand(0); 4721 Builder.SetInsertPoint(VL0); 4722 ShuffleBuilder.addInversedMask(E->ReorderIndices); 4723 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4724 V = ShuffleBuilder.finalize(V); 4725 E->VectorizedValue = V; 4726 return V; 4727 } 4728 case Instruction::ExtractValue: { 4729 auto *LI = cast<LoadInst>(E->getSingleOperand(0)); 4730 Builder.SetInsertPoint(LI); 4731 auto *PtrTy = PointerType::get(VecTy, LI->getPointerAddressSpace()); 4732 Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy); 4733 LoadInst *V = Builder.CreateAlignedLoad(VecTy, Ptr, LI->getAlign()); 4734 Value *NewV = propagateMetadata(V, E->Scalars); 4735 ShuffleBuilder.addInversedMask(E->ReorderIndices); 4736 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4737 NewV = ShuffleBuilder.finalize(NewV); 4738 E->VectorizedValue = NewV; 4739 return NewV; 4740 } 4741 case Instruction::ZExt: 4742 case Instruction::SExt: 4743 case Instruction::FPToUI: 4744 case Instruction::FPToSI: 4745 case Instruction::FPExt: 4746 case Instruction::PtrToInt: 4747 case Instruction::IntToPtr: 4748 case Instruction::SIToFP: 4749 case Instruction::UIToFP: 4750 case Instruction::Trunc: 4751 case Instruction::FPTrunc: 4752 case Instruction::BitCast: { 4753 setInsertPointAfterBundle(E); 4754 4755 Value *InVec = vectorizeTree(E->getOperand(0)); 4756 4757 if (E->VectorizedValue) { 4758 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4759 return E->VectorizedValue; 4760 } 4761 4762 auto *CI = cast<CastInst>(VL0); 4763 Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy); 4764 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4765 V = ShuffleBuilder.finalize(V); 4766 4767 E->VectorizedValue = V; 4768 ++NumVectorInstructions; 4769 return V; 4770 } 4771 case Instruction::FCmp: 4772 case Instruction::ICmp: { 4773 setInsertPointAfterBundle(E); 4774 4775 Value *L = vectorizeTree(E->getOperand(0)); 4776 Value *R = vectorizeTree(E->getOperand(1)); 4777 4778 if (E->VectorizedValue) { 4779 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4780 return E->VectorizedValue; 4781 } 4782 4783 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 4784 Value *V = Builder.CreateCmp(P0, L, R); 4785 propagateIRFlags(V, E->Scalars, VL0); 4786 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4787 V = ShuffleBuilder.finalize(V); 4788 4789 E->VectorizedValue = V; 4790 ++NumVectorInstructions; 4791 return V; 4792 } 4793 case Instruction::Select: { 4794 setInsertPointAfterBundle(E); 4795 4796 Value *Cond = vectorizeTree(E->getOperand(0)); 4797 Value *True = vectorizeTree(E->getOperand(1)); 4798 Value *False = vectorizeTree(E->getOperand(2)); 4799 4800 if (E->VectorizedValue) { 4801 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4802 return E->VectorizedValue; 4803 } 4804 4805 Value *V = Builder.CreateSelect(Cond, True, False); 4806 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4807 V = ShuffleBuilder.finalize(V); 4808 4809 E->VectorizedValue = V; 4810 ++NumVectorInstructions; 4811 return V; 4812 } 4813 case Instruction::FNeg: { 4814 setInsertPointAfterBundle(E); 4815 4816 Value *Op = vectorizeTree(E->getOperand(0)); 4817 4818 if (E->VectorizedValue) { 4819 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4820 return E->VectorizedValue; 4821 } 4822 4823 Value *V = Builder.CreateUnOp( 4824 static_cast<Instruction::UnaryOps>(E->getOpcode()), Op); 4825 propagateIRFlags(V, E->Scalars, VL0); 4826 if (auto *I = dyn_cast<Instruction>(V)) 4827 V = propagateMetadata(I, E->Scalars); 4828 4829 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4830 V = ShuffleBuilder.finalize(V); 4831 4832 E->VectorizedValue = V; 4833 ++NumVectorInstructions; 4834 4835 return V; 4836 } 4837 case Instruction::Add: 4838 case Instruction::FAdd: 4839 case Instruction::Sub: 4840 case Instruction::FSub: 4841 case Instruction::Mul: 4842 case Instruction::FMul: 4843 case Instruction::UDiv: 4844 case Instruction::SDiv: 4845 case Instruction::FDiv: 4846 case Instruction::URem: 4847 case Instruction::SRem: 4848 case Instruction::FRem: 4849 case Instruction::Shl: 4850 case Instruction::LShr: 4851 case Instruction::AShr: 4852 case Instruction::And: 4853 case Instruction::Or: 4854 case Instruction::Xor: { 4855 setInsertPointAfterBundle(E); 4856 4857 Value *LHS = vectorizeTree(E->getOperand(0)); 4858 Value *RHS = vectorizeTree(E->getOperand(1)); 4859 4860 if (E->VectorizedValue) { 4861 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4862 return E->VectorizedValue; 4863 } 4864 4865 Value *V = Builder.CreateBinOp( 4866 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, 4867 RHS); 4868 propagateIRFlags(V, E->Scalars, VL0); 4869 if (auto *I = dyn_cast<Instruction>(V)) 4870 V = propagateMetadata(I, E->Scalars); 4871 4872 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4873 V = ShuffleBuilder.finalize(V); 4874 4875 E->VectorizedValue = V; 4876 ++NumVectorInstructions; 4877 4878 return V; 4879 } 4880 case Instruction::Load: { 4881 // Loads are inserted at the head of the tree because we don't want to 4882 // sink them all the way down past store instructions. 4883 bool IsReorder = E->updateStateIfReorder(); 4884 if (IsReorder) 4885 VL0 = E->getMainOp(); 4886 setInsertPointAfterBundle(E); 4887 4888 LoadInst *LI = cast<LoadInst>(VL0); 4889 Instruction *NewLI; 4890 unsigned AS = LI->getPointerAddressSpace(); 4891 Value *PO = LI->getPointerOperand(); 4892 if (E->State == TreeEntry::Vectorize) { 4893 4894 Value *VecPtr = Builder.CreateBitCast(PO, VecTy->getPointerTo(AS)); 4895 4896 // The pointer operand uses an in-tree scalar so we add the new BitCast 4897 // to ExternalUses list to make sure that an extract will be generated 4898 // in the future. 4899 if (getTreeEntry(PO)) 4900 ExternalUses.emplace_back(PO, cast<User>(VecPtr), 0); 4901 4902 NewLI = Builder.CreateAlignedLoad(VecTy, VecPtr, LI->getAlign()); 4903 } else { 4904 assert(E->State == TreeEntry::ScatterVectorize && "Unhandled state"); 4905 Value *VecPtr = vectorizeTree(E->getOperand(0)); 4906 // Use the minimum alignment of the gathered loads. 4907 Align CommonAlignment = LI->getAlign(); 4908 for (Value *V : E->Scalars) 4909 CommonAlignment = 4910 commonAlignment(CommonAlignment, cast<LoadInst>(V)->getAlign()); 4911 NewLI = Builder.CreateMaskedGather(VecPtr, CommonAlignment); 4912 } 4913 Value *V = propagateMetadata(NewLI, E->Scalars); 4914 4915 ShuffleBuilder.addInversedMask(E->ReorderIndices); 4916 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4917 V = ShuffleBuilder.finalize(V); 4918 E->VectorizedValue = V; 4919 ++NumVectorInstructions; 4920 return V; 4921 } 4922 case Instruction::Store: { 4923 bool IsReorder = !E->ReorderIndices.empty(); 4924 auto *SI = cast<StoreInst>( 4925 IsReorder ? E->Scalars[E->ReorderIndices.front()] : VL0); 4926 unsigned AS = SI->getPointerAddressSpace(); 4927 4928 setInsertPointAfterBundle(E); 4929 4930 Value *VecValue = vectorizeTree(E->getOperand(0)); 4931 ShuffleBuilder.addMask(E->ReorderIndices); 4932 VecValue = ShuffleBuilder.finalize(VecValue); 4933 4934 Value *ScalarPtr = SI->getPointerOperand(); 4935 Value *VecPtr = Builder.CreateBitCast( 4936 ScalarPtr, VecValue->getType()->getPointerTo(AS)); 4937 StoreInst *ST = Builder.CreateAlignedStore(VecValue, VecPtr, 4938 SI->getAlign()); 4939 4940 // The pointer operand uses an in-tree scalar, so add the new BitCast to 4941 // ExternalUses to make sure that an extract will be generated in the 4942 // future. 4943 if (getTreeEntry(ScalarPtr)) 4944 ExternalUses.push_back(ExternalUser(ScalarPtr, cast<User>(VecPtr), 0)); 4945 4946 Value *V = propagateMetadata(ST, E->Scalars); 4947 4948 E->VectorizedValue = V; 4949 ++NumVectorInstructions; 4950 return V; 4951 } 4952 case Instruction::GetElementPtr: { 4953 setInsertPointAfterBundle(E); 4954 4955 Value *Op0 = vectorizeTree(E->getOperand(0)); 4956 4957 std::vector<Value *> OpVecs; 4958 for (int j = 1, e = cast<GetElementPtrInst>(VL0)->getNumOperands(); j < e; 4959 ++j) { 4960 ValueList &VL = E->getOperand(j); 4961 // Need to cast all elements to the same type before vectorization to 4962 // avoid crash. 4963 Type *VL0Ty = VL0->getOperand(j)->getType(); 4964 Type *Ty = llvm::all_of( 4965 VL, [VL0Ty](Value *V) { return VL0Ty == V->getType(); }) 4966 ? VL0Ty 4967 : DL->getIndexType(cast<GetElementPtrInst>(VL0) 4968 ->getPointerOperandType() 4969 ->getScalarType()); 4970 for (Value *&V : VL) { 4971 auto *CI = cast<ConstantInt>(V); 4972 V = ConstantExpr::getIntegerCast(CI, Ty, 4973 CI->getValue().isSignBitSet()); 4974 } 4975 Value *OpVec = vectorizeTree(VL); 4976 OpVecs.push_back(OpVec); 4977 } 4978 4979 Value *V = Builder.CreateGEP( 4980 cast<GetElementPtrInst>(VL0)->getSourceElementType(), Op0, OpVecs); 4981 if (Instruction *I = dyn_cast<Instruction>(V)) 4982 V = propagateMetadata(I, E->Scalars); 4983 4984 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4985 V = ShuffleBuilder.finalize(V); 4986 4987 E->VectorizedValue = V; 4988 ++NumVectorInstructions; 4989 4990 return V; 4991 } 4992 case Instruction::Call: { 4993 CallInst *CI = cast<CallInst>(VL0); 4994 setInsertPointAfterBundle(E); 4995 4996 Intrinsic::ID IID = Intrinsic::not_intrinsic; 4997 if (Function *FI = CI->getCalledFunction()) 4998 IID = FI->getIntrinsicID(); 4999 5000 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 5001 5002 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 5003 bool UseIntrinsic = ID != Intrinsic::not_intrinsic && 5004 VecCallCosts.first <= VecCallCosts.second; 5005 5006 Value *ScalarArg = nullptr; 5007 std::vector<Value *> OpVecs; 5008 for (int j = 0, e = CI->getNumArgOperands(); j < e; ++j) { 5009 ValueList OpVL; 5010 // Some intrinsics have scalar arguments. This argument should not be 5011 // vectorized. 5012 if (UseIntrinsic && hasVectorInstrinsicScalarOpd(IID, j)) { 5013 CallInst *CEI = cast<CallInst>(VL0); 5014 ScalarArg = CEI->getArgOperand(j); 5015 OpVecs.push_back(CEI->getArgOperand(j)); 5016 continue; 5017 } 5018 5019 Value *OpVec = vectorizeTree(E->getOperand(j)); 5020 LLVM_DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n"); 5021 OpVecs.push_back(OpVec); 5022 } 5023 5024 Function *CF; 5025 if (!UseIntrinsic) { 5026 VFShape Shape = 5027 VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>( 5028 VecTy->getNumElements())), 5029 false /*HasGlobalPred*/); 5030 CF = VFDatabase(*CI).getVectorizedFunction(Shape); 5031 } else { 5032 Type *Tys[] = {FixedVectorType::get(CI->getType(), E->Scalars.size())}; 5033 CF = Intrinsic::getDeclaration(F->getParent(), ID, Tys); 5034 } 5035 5036 SmallVector<OperandBundleDef, 1> OpBundles; 5037 CI->getOperandBundlesAsDefs(OpBundles); 5038 Value *V = Builder.CreateCall(CF, OpVecs, OpBundles); 5039 5040 // The scalar argument uses an in-tree scalar so we add the new vectorized 5041 // call to ExternalUses list to make sure that an extract will be 5042 // generated in the future. 5043 if (ScalarArg && getTreeEntry(ScalarArg)) 5044 ExternalUses.push_back(ExternalUser(ScalarArg, cast<User>(V), 0)); 5045 5046 propagateIRFlags(V, E->Scalars, VL0); 5047 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5048 V = ShuffleBuilder.finalize(V); 5049 5050 E->VectorizedValue = V; 5051 ++NumVectorInstructions; 5052 return V; 5053 } 5054 case Instruction::ShuffleVector: { 5055 assert(E->isAltShuffle() && 5056 ((Instruction::isBinaryOp(E->getOpcode()) && 5057 Instruction::isBinaryOp(E->getAltOpcode())) || 5058 (Instruction::isCast(E->getOpcode()) && 5059 Instruction::isCast(E->getAltOpcode()))) && 5060 "Invalid Shuffle Vector Operand"); 5061 5062 Value *LHS = nullptr, *RHS = nullptr; 5063 if (Instruction::isBinaryOp(E->getOpcode())) { 5064 setInsertPointAfterBundle(E); 5065 LHS = vectorizeTree(E->getOperand(0)); 5066 RHS = vectorizeTree(E->getOperand(1)); 5067 } else { 5068 setInsertPointAfterBundle(E); 5069 LHS = vectorizeTree(E->getOperand(0)); 5070 } 5071 5072 if (E->VectorizedValue) { 5073 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5074 return E->VectorizedValue; 5075 } 5076 5077 Value *V0, *V1; 5078 if (Instruction::isBinaryOp(E->getOpcode())) { 5079 V0 = Builder.CreateBinOp( 5080 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, RHS); 5081 V1 = Builder.CreateBinOp( 5082 static_cast<Instruction::BinaryOps>(E->getAltOpcode()), LHS, RHS); 5083 } else { 5084 V0 = Builder.CreateCast( 5085 static_cast<Instruction::CastOps>(E->getOpcode()), LHS, VecTy); 5086 V1 = Builder.CreateCast( 5087 static_cast<Instruction::CastOps>(E->getAltOpcode()), LHS, VecTy); 5088 } 5089 5090 // Create shuffle to take alternate operations from the vector. 5091 // Also, gather up main and alt scalar ops to propagate IR flags to 5092 // each vector operation. 5093 ValueList OpScalars, AltScalars; 5094 unsigned e = E->Scalars.size(); 5095 SmallVector<int, 8> Mask(e); 5096 for (unsigned i = 0; i < e; ++i) { 5097 auto *OpInst = cast<Instruction>(E->Scalars[i]); 5098 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 5099 if (OpInst->getOpcode() == E->getAltOpcode()) { 5100 Mask[i] = e + i; 5101 AltScalars.push_back(E->Scalars[i]); 5102 } else { 5103 Mask[i] = i; 5104 OpScalars.push_back(E->Scalars[i]); 5105 } 5106 } 5107 5108 propagateIRFlags(V0, OpScalars); 5109 propagateIRFlags(V1, AltScalars); 5110 5111 Value *V = Builder.CreateShuffleVector(V0, V1, Mask); 5112 if (Instruction *I = dyn_cast<Instruction>(V)) 5113 V = propagateMetadata(I, E->Scalars); 5114 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5115 V = ShuffleBuilder.finalize(V); 5116 5117 E->VectorizedValue = V; 5118 ++NumVectorInstructions; 5119 5120 return V; 5121 } 5122 default: 5123 llvm_unreachable("unknown inst"); 5124 } 5125 return nullptr; 5126 } 5127 5128 Value *BoUpSLP::vectorizeTree() { 5129 ExtraValueToDebugLocsMap ExternallyUsedValues; 5130 return vectorizeTree(ExternallyUsedValues); 5131 } 5132 5133 Value * 5134 BoUpSLP::vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues) { 5135 // All blocks must be scheduled before any instructions are inserted. 5136 for (auto &BSIter : BlocksSchedules) { 5137 scheduleBlock(BSIter.second.get()); 5138 } 5139 5140 Builder.SetInsertPoint(&F->getEntryBlock().front()); 5141 auto *VectorRoot = vectorizeTree(VectorizableTree[0].get()); 5142 5143 // If the vectorized tree can be rewritten in a smaller type, we truncate the 5144 // vectorized root. InstCombine will then rewrite the entire expression. We 5145 // sign extend the extracted values below. 5146 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 5147 if (MinBWs.count(ScalarRoot)) { 5148 if (auto *I = dyn_cast<Instruction>(VectorRoot)) { 5149 // If current instr is a phi and not the last phi, insert it after the 5150 // last phi node. 5151 if (isa<PHINode>(I)) 5152 Builder.SetInsertPoint(&*I->getParent()->getFirstInsertionPt()); 5153 else 5154 Builder.SetInsertPoint(&*++BasicBlock::iterator(I)); 5155 } 5156 auto BundleWidth = VectorizableTree[0]->Scalars.size(); 5157 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 5158 auto *VecTy = FixedVectorType::get(MinTy, BundleWidth); 5159 auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy); 5160 VectorizableTree[0]->VectorizedValue = Trunc; 5161 } 5162 5163 LLVM_DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size() 5164 << " values .\n"); 5165 5166 // If necessary, sign-extend or zero-extend ScalarRoot to the larger type 5167 // specified by ScalarType. 5168 auto extend = [&](Value *ScalarRoot, Value *Ex, Type *ScalarType) { 5169 if (!MinBWs.count(ScalarRoot)) 5170 return Ex; 5171 if (MinBWs[ScalarRoot].second) 5172 return Builder.CreateSExt(Ex, ScalarType); 5173 return Builder.CreateZExt(Ex, ScalarType); 5174 }; 5175 5176 // Extract all of the elements with the external uses. 5177 for (const auto &ExternalUse : ExternalUses) { 5178 Value *Scalar = ExternalUse.Scalar; 5179 llvm::User *User = ExternalUse.User; 5180 5181 // Skip users that we already RAUW. This happens when one instruction 5182 // has multiple uses of the same value. 5183 if (User && !is_contained(Scalar->users(), User)) 5184 continue; 5185 TreeEntry *E = getTreeEntry(Scalar); 5186 assert(E && "Invalid scalar"); 5187 assert(E->State != TreeEntry::NeedToGather && 5188 "Extracting from a gather list"); 5189 5190 Value *Vec = E->VectorizedValue; 5191 assert(Vec && "Can't find vectorizable value"); 5192 5193 Value *Lane = Builder.getInt32(ExternalUse.Lane); 5194 // If User == nullptr, the Scalar is used as extra arg. Generate 5195 // ExtractElement instruction and update the record for this scalar in 5196 // ExternallyUsedValues. 5197 if (!User) { 5198 assert(ExternallyUsedValues.count(Scalar) && 5199 "Scalar with nullptr as an external user must be registered in " 5200 "ExternallyUsedValues map"); 5201 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 5202 Builder.SetInsertPoint(VecI->getParent(), 5203 std::next(VecI->getIterator())); 5204 } else { 5205 Builder.SetInsertPoint(&F->getEntryBlock().front()); 5206 } 5207 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 5208 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 5209 CSEBlocks.insert(cast<Instruction>(Scalar)->getParent()); 5210 auto &Locs = ExternallyUsedValues[Scalar]; 5211 ExternallyUsedValues.insert({Ex, Locs}); 5212 ExternallyUsedValues.erase(Scalar); 5213 // Required to update internally referenced instructions. 5214 Scalar->replaceAllUsesWith(Ex); 5215 continue; 5216 } 5217 5218 // Generate extracts for out-of-tree users. 5219 // Find the insertion point for the extractelement lane. 5220 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 5221 if (PHINode *PH = dyn_cast<PHINode>(User)) { 5222 for (int i = 0, e = PH->getNumIncomingValues(); i != e; ++i) { 5223 if (PH->getIncomingValue(i) == Scalar) { 5224 Instruction *IncomingTerminator = 5225 PH->getIncomingBlock(i)->getTerminator(); 5226 if (isa<CatchSwitchInst>(IncomingTerminator)) { 5227 Builder.SetInsertPoint(VecI->getParent(), 5228 std::next(VecI->getIterator())); 5229 } else { 5230 Builder.SetInsertPoint(PH->getIncomingBlock(i)->getTerminator()); 5231 } 5232 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 5233 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 5234 CSEBlocks.insert(PH->getIncomingBlock(i)); 5235 PH->setOperand(i, Ex); 5236 } 5237 } 5238 } else { 5239 Builder.SetInsertPoint(cast<Instruction>(User)); 5240 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 5241 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 5242 CSEBlocks.insert(cast<Instruction>(User)->getParent()); 5243 User->replaceUsesOfWith(Scalar, Ex); 5244 } 5245 } else { 5246 Builder.SetInsertPoint(&F->getEntryBlock().front()); 5247 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 5248 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 5249 CSEBlocks.insert(&F->getEntryBlock()); 5250 User->replaceUsesOfWith(Scalar, Ex); 5251 } 5252 5253 LLVM_DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n"); 5254 } 5255 5256 // For each vectorized value: 5257 for (auto &TEPtr : VectorizableTree) { 5258 TreeEntry *Entry = TEPtr.get(); 5259 5260 // No need to handle users of gathered values. 5261 if (Entry->State == TreeEntry::NeedToGather) 5262 continue; 5263 5264 assert(Entry->VectorizedValue && "Can't find vectorizable value"); 5265 5266 // For each lane: 5267 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 5268 Value *Scalar = Entry->Scalars[Lane]; 5269 5270 #ifndef NDEBUG 5271 Type *Ty = Scalar->getType(); 5272 if (!Ty->isVoidTy()) { 5273 for (User *U : Scalar->users()) { 5274 LLVM_DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n"); 5275 5276 // It is legal to delete users in the ignorelist. 5277 assert((getTreeEntry(U) || is_contained(UserIgnoreList, U)) && 5278 "Deleting out-of-tree value"); 5279 } 5280 } 5281 #endif 5282 LLVM_DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n"); 5283 eraseInstruction(cast<Instruction>(Scalar)); 5284 } 5285 } 5286 5287 Builder.ClearInsertionPoint(); 5288 InstrElementSize.clear(); 5289 5290 return VectorizableTree[0]->VectorizedValue; 5291 } 5292 5293 void BoUpSLP::optimizeGatherSequence() { 5294 LLVM_DEBUG(dbgs() << "SLP: Optimizing " << GatherSeq.size() 5295 << " gather sequences instructions.\n"); 5296 // LICM InsertElementInst sequences. 5297 for (Instruction *I : GatherSeq) { 5298 if (isDeleted(I)) 5299 continue; 5300 5301 // Check if this block is inside a loop. 5302 Loop *L = LI->getLoopFor(I->getParent()); 5303 if (!L) 5304 continue; 5305 5306 // Check if it has a preheader. 5307 BasicBlock *PreHeader = L->getLoopPreheader(); 5308 if (!PreHeader) 5309 continue; 5310 5311 // If the vector or the element that we insert into it are 5312 // instructions that are defined in this basic block then we can't 5313 // hoist this instruction. 5314 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 5315 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 5316 if (Op0 && L->contains(Op0)) 5317 continue; 5318 if (Op1 && L->contains(Op1)) 5319 continue; 5320 5321 // We can hoist this instruction. Move it to the pre-header. 5322 I->moveBefore(PreHeader->getTerminator()); 5323 } 5324 5325 // Make a list of all reachable blocks in our CSE queue. 5326 SmallVector<const DomTreeNode *, 8> CSEWorkList; 5327 CSEWorkList.reserve(CSEBlocks.size()); 5328 for (BasicBlock *BB : CSEBlocks) 5329 if (DomTreeNode *N = DT->getNode(BB)) { 5330 assert(DT->isReachableFromEntry(N)); 5331 CSEWorkList.push_back(N); 5332 } 5333 5334 // Sort blocks by domination. This ensures we visit a block after all blocks 5335 // dominating it are visited. 5336 llvm::stable_sort(CSEWorkList, 5337 [this](const DomTreeNode *A, const DomTreeNode *B) { 5338 return DT->properlyDominates(A, B); 5339 }); 5340 5341 // Perform O(N^2) search over the gather sequences and merge identical 5342 // instructions. TODO: We can further optimize this scan if we split the 5343 // instructions into different buckets based on the insert lane. 5344 SmallVector<Instruction *, 16> Visited; 5345 for (auto I = CSEWorkList.begin(), E = CSEWorkList.end(); I != E; ++I) { 5346 assert(*I && 5347 (I == CSEWorkList.begin() || !DT->dominates(*I, *std::prev(I))) && 5348 "Worklist not sorted properly!"); 5349 BasicBlock *BB = (*I)->getBlock(); 5350 // For all instructions in blocks containing gather sequences: 5351 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e;) { 5352 Instruction *In = &*it++; 5353 if (isDeleted(In)) 5354 continue; 5355 if (!isa<InsertElementInst>(In) && !isa<ExtractElementInst>(In)) 5356 continue; 5357 5358 // Check if we can replace this instruction with any of the 5359 // visited instructions. 5360 for (Instruction *v : Visited) { 5361 if (In->isIdenticalTo(v) && 5362 DT->dominates(v->getParent(), In->getParent())) { 5363 In->replaceAllUsesWith(v); 5364 eraseInstruction(In); 5365 In = nullptr; 5366 break; 5367 } 5368 } 5369 if (In) { 5370 assert(!is_contained(Visited, In)); 5371 Visited.push_back(In); 5372 } 5373 } 5374 } 5375 CSEBlocks.clear(); 5376 GatherSeq.clear(); 5377 } 5378 5379 // Groups the instructions to a bundle (which is then a single scheduling entity) 5380 // and schedules instructions until the bundle gets ready. 5381 Optional<BoUpSLP::ScheduleData *> 5382 BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 5383 const InstructionsState &S) { 5384 if (isa<PHINode>(S.OpValue)) 5385 return nullptr; 5386 5387 // Initialize the instruction bundle. 5388 Instruction *OldScheduleEnd = ScheduleEnd; 5389 ScheduleData *PrevInBundle = nullptr; 5390 ScheduleData *Bundle = nullptr; 5391 bool ReSchedule = false; 5392 LLVM_DEBUG(dbgs() << "SLP: bundle: " << *S.OpValue << "\n"); 5393 5394 auto &&TryScheduleBundle = [this, OldScheduleEnd, SLP](bool ReSchedule, 5395 ScheduleData *Bundle) { 5396 // The scheduling region got new instructions at the lower end (or it is a 5397 // new region for the first bundle). This makes it necessary to 5398 // recalculate all dependencies. 5399 // It is seldom that this needs to be done a second time after adding the 5400 // initial bundle to the region. 5401 if (ScheduleEnd != OldScheduleEnd) { 5402 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) 5403 doForAllOpcodes(I, [](ScheduleData *SD) { SD->clearDependencies(); }); 5404 ReSchedule = true; 5405 } 5406 if (ReSchedule) { 5407 resetSchedule(); 5408 initialFillReadyList(ReadyInsts); 5409 } 5410 if (Bundle) { 5411 LLVM_DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle 5412 << " in block " << BB->getName() << "\n"); 5413 calculateDependencies(Bundle, /*InsertInReadyList=*/true, SLP); 5414 } 5415 5416 // Now try to schedule the new bundle or (if no bundle) just calculate 5417 // dependencies. As soon as the bundle is "ready" it means that there are no 5418 // cyclic dependencies and we can schedule it. Note that's important that we 5419 // don't "schedule" the bundle yet (see cancelScheduling). 5420 while (((!Bundle && ReSchedule) || (Bundle && !Bundle->isReady())) && 5421 !ReadyInsts.empty()) { 5422 ScheduleData *Picked = ReadyInsts.pop_back_val(); 5423 if (Picked->isSchedulingEntity() && Picked->isReady()) 5424 schedule(Picked, ReadyInsts); 5425 } 5426 }; 5427 5428 // Make sure that the scheduling region contains all 5429 // instructions of the bundle. 5430 for (Value *V : VL) { 5431 if (!extendSchedulingRegion(V, S)) { 5432 // If the scheduling region got new instructions at the lower end (or it 5433 // is a new region for the first bundle). This makes it necessary to 5434 // recalculate all dependencies. 5435 // Otherwise the compiler may crash trying to incorrectly calculate 5436 // dependencies and emit instruction in the wrong order at the actual 5437 // scheduling. 5438 TryScheduleBundle(/*ReSchedule=*/false, nullptr); 5439 return None; 5440 } 5441 } 5442 5443 for (Value *V : VL) { 5444 ScheduleData *BundleMember = getScheduleData(V); 5445 assert(BundleMember && 5446 "no ScheduleData for bundle member (maybe not in same basic block)"); 5447 if (BundleMember->IsScheduled) { 5448 // A bundle member was scheduled as single instruction before and now 5449 // needs to be scheduled as part of the bundle. We just get rid of the 5450 // existing schedule. 5451 LLVM_DEBUG(dbgs() << "SLP: reset schedule because " << *BundleMember 5452 << " was already scheduled\n"); 5453 ReSchedule = true; 5454 } 5455 assert(BundleMember->isSchedulingEntity() && 5456 "bundle member already part of other bundle"); 5457 if (PrevInBundle) { 5458 PrevInBundle->NextInBundle = BundleMember; 5459 } else { 5460 Bundle = BundleMember; 5461 } 5462 BundleMember->UnscheduledDepsInBundle = 0; 5463 Bundle->UnscheduledDepsInBundle += BundleMember->UnscheduledDeps; 5464 5465 // Group the instructions to a bundle. 5466 BundleMember->FirstInBundle = Bundle; 5467 PrevInBundle = BundleMember; 5468 } 5469 assert(Bundle && "Failed to find schedule bundle"); 5470 TryScheduleBundle(ReSchedule, Bundle); 5471 if (!Bundle->isReady()) { 5472 cancelScheduling(VL, S.OpValue); 5473 return None; 5474 } 5475 return Bundle; 5476 } 5477 5478 void BoUpSLP::BlockScheduling::cancelScheduling(ArrayRef<Value *> VL, 5479 Value *OpValue) { 5480 if (isa<PHINode>(OpValue)) 5481 return; 5482 5483 ScheduleData *Bundle = getScheduleData(OpValue); 5484 LLVM_DEBUG(dbgs() << "SLP: cancel scheduling of " << *Bundle << "\n"); 5485 assert(!Bundle->IsScheduled && 5486 "Can't cancel bundle which is already scheduled"); 5487 assert(Bundle->isSchedulingEntity() && Bundle->isPartOfBundle() && 5488 "tried to unbundle something which is not a bundle"); 5489 5490 // Un-bundle: make single instructions out of the bundle. 5491 ScheduleData *BundleMember = Bundle; 5492 while (BundleMember) { 5493 assert(BundleMember->FirstInBundle == Bundle && "corrupt bundle links"); 5494 BundleMember->FirstInBundle = BundleMember; 5495 ScheduleData *Next = BundleMember->NextInBundle; 5496 BundleMember->NextInBundle = nullptr; 5497 BundleMember->UnscheduledDepsInBundle = BundleMember->UnscheduledDeps; 5498 if (BundleMember->UnscheduledDepsInBundle == 0) { 5499 ReadyInsts.insert(BundleMember); 5500 } 5501 BundleMember = Next; 5502 } 5503 } 5504 5505 BoUpSLP::ScheduleData *BoUpSLP::BlockScheduling::allocateScheduleDataChunks() { 5506 // Allocate a new ScheduleData for the instruction. 5507 if (ChunkPos >= ChunkSize) { 5508 ScheduleDataChunks.push_back(std::make_unique<ScheduleData[]>(ChunkSize)); 5509 ChunkPos = 0; 5510 } 5511 return &(ScheduleDataChunks.back()[ChunkPos++]); 5512 } 5513 5514 bool BoUpSLP::BlockScheduling::extendSchedulingRegion(Value *V, 5515 const InstructionsState &S) { 5516 if (getScheduleData(V, isOneOf(S, V))) 5517 return true; 5518 Instruction *I = dyn_cast<Instruction>(V); 5519 assert(I && "bundle member must be an instruction"); 5520 assert(!isa<PHINode>(I) && "phi nodes don't need to be scheduled"); 5521 auto &&CheckSheduleForI = [this, &S](Instruction *I) -> bool { 5522 ScheduleData *ISD = getScheduleData(I); 5523 if (!ISD) 5524 return false; 5525 assert(isInSchedulingRegion(ISD) && 5526 "ScheduleData not in scheduling region"); 5527 ScheduleData *SD = allocateScheduleDataChunks(); 5528 SD->Inst = I; 5529 SD->init(SchedulingRegionID, S.OpValue); 5530 ExtraScheduleDataMap[I][S.OpValue] = SD; 5531 return true; 5532 }; 5533 if (CheckSheduleForI(I)) 5534 return true; 5535 if (!ScheduleStart) { 5536 // It's the first instruction in the new region. 5537 initScheduleData(I, I->getNextNode(), nullptr, nullptr); 5538 ScheduleStart = I; 5539 ScheduleEnd = I->getNextNode(); 5540 if (isOneOf(S, I) != I) 5541 CheckSheduleForI(I); 5542 assert(ScheduleEnd && "tried to vectorize a terminator?"); 5543 LLVM_DEBUG(dbgs() << "SLP: initialize schedule region to " << *I << "\n"); 5544 return true; 5545 } 5546 // Search up and down at the same time, because we don't know if the new 5547 // instruction is above or below the existing scheduling region. 5548 BasicBlock::reverse_iterator UpIter = 5549 ++ScheduleStart->getIterator().getReverse(); 5550 BasicBlock::reverse_iterator UpperEnd = BB->rend(); 5551 BasicBlock::iterator DownIter = ScheduleEnd->getIterator(); 5552 BasicBlock::iterator LowerEnd = BB->end(); 5553 while (UpIter != UpperEnd && DownIter != LowerEnd && &*UpIter != I && 5554 &*DownIter != I) { 5555 if (++ScheduleRegionSize > ScheduleRegionSizeLimit) { 5556 LLVM_DEBUG(dbgs() << "SLP: exceeded schedule region size limit\n"); 5557 return false; 5558 } 5559 5560 ++UpIter; 5561 ++DownIter; 5562 } 5563 if (DownIter == LowerEnd || (UpIter != UpperEnd && &*UpIter == I)) { 5564 assert(I->getParent() == ScheduleStart->getParent() && 5565 "Instruction is in wrong basic block."); 5566 initScheduleData(I, ScheduleStart, nullptr, FirstLoadStoreInRegion); 5567 ScheduleStart = I; 5568 if (isOneOf(S, I) != I) 5569 CheckSheduleForI(I); 5570 LLVM_DEBUG(dbgs() << "SLP: extend schedule region start to " << *I 5571 << "\n"); 5572 return true; 5573 } 5574 assert((UpIter == UpperEnd || (DownIter != LowerEnd && &*DownIter == I)) && 5575 "Expected to reach top of the basic block or instruction down the " 5576 "lower end."); 5577 assert(I->getParent() == ScheduleEnd->getParent() && 5578 "Instruction is in wrong basic block."); 5579 initScheduleData(ScheduleEnd, I->getNextNode(), LastLoadStoreInRegion, 5580 nullptr); 5581 ScheduleEnd = I->getNextNode(); 5582 if (isOneOf(S, I) != I) 5583 CheckSheduleForI(I); 5584 assert(ScheduleEnd && "tried to vectorize a terminator?"); 5585 LLVM_DEBUG(dbgs() << "SLP: extend schedule region end to " << *I << "\n"); 5586 return true; 5587 } 5588 5589 void BoUpSLP::BlockScheduling::initScheduleData(Instruction *FromI, 5590 Instruction *ToI, 5591 ScheduleData *PrevLoadStore, 5592 ScheduleData *NextLoadStore) { 5593 ScheduleData *CurrentLoadStore = PrevLoadStore; 5594 for (Instruction *I = FromI; I != ToI; I = I->getNextNode()) { 5595 ScheduleData *SD = ScheduleDataMap[I]; 5596 if (!SD) { 5597 SD = allocateScheduleDataChunks(); 5598 ScheduleDataMap[I] = SD; 5599 SD->Inst = I; 5600 } 5601 assert(!isInSchedulingRegion(SD) && 5602 "new ScheduleData already in scheduling region"); 5603 SD->init(SchedulingRegionID, I); 5604 5605 if (I->mayReadOrWriteMemory() && 5606 (!isa<IntrinsicInst>(I) || 5607 (cast<IntrinsicInst>(I)->getIntrinsicID() != Intrinsic::sideeffect && 5608 cast<IntrinsicInst>(I)->getIntrinsicID() != 5609 Intrinsic::pseudoprobe))) { 5610 // Update the linked list of memory accessing instructions. 5611 if (CurrentLoadStore) { 5612 CurrentLoadStore->NextLoadStore = SD; 5613 } else { 5614 FirstLoadStoreInRegion = SD; 5615 } 5616 CurrentLoadStore = SD; 5617 } 5618 } 5619 if (NextLoadStore) { 5620 if (CurrentLoadStore) 5621 CurrentLoadStore->NextLoadStore = NextLoadStore; 5622 } else { 5623 LastLoadStoreInRegion = CurrentLoadStore; 5624 } 5625 } 5626 5627 void BoUpSLP::BlockScheduling::calculateDependencies(ScheduleData *SD, 5628 bool InsertInReadyList, 5629 BoUpSLP *SLP) { 5630 assert(SD->isSchedulingEntity()); 5631 5632 SmallVector<ScheduleData *, 10> WorkList; 5633 WorkList.push_back(SD); 5634 5635 while (!WorkList.empty()) { 5636 ScheduleData *SD = WorkList.pop_back_val(); 5637 5638 ScheduleData *BundleMember = SD; 5639 while (BundleMember) { 5640 assert(isInSchedulingRegion(BundleMember)); 5641 if (!BundleMember->hasValidDependencies()) { 5642 5643 LLVM_DEBUG(dbgs() << "SLP: update deps of " << *BundleMember 5644 << "\n"); 5645 BundleMember->Dependencies = 0; 5646 BundleMember->resetUnscheduledDeps(); 5647 5648 // Handle def-use chain dependencies. 5649 if (BundleMember->OpValue != BundleMember->Inst) { 5650 ScheduleData *UseSD = getScheduleData(BundleMember->Inst); 5651 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 5652 BundleMember->Dependencies++; 5653 ScheduleData *DestBundle = UseSD->FirstInBundle; 5654 if (!DestBundle->IsScheduled) 5655 BundleMember->incrementUnscheduledDeps(1); 5656 if (!DestBundle->hasValidDependencies()) 5657 WorkList.push_back(DestBundle); 5658 } 5659 } else { 5660 for (User *U : BundleMember->Inst->users()) { 5661 if (isa<Instruction>(U)) { 5662 ScheduleData *UseSD = getScheduleData(U); 5663 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 5664 BundleMember->Dependencies++; 5665 ScheduleData *DestBundle = UseSD->FirstInBundle; 5666 if (!DestBundle->IsScheduled) 5667 BundleMember->incrementUnscheduledDeps(1); 5668 if (!DestBundle->hasValidDependencies()) 5669 WorkList.push_back(DestBundle); 5670 } 5671 } else { 5672 // I'm not sure if this can ever happen. But we need to be safe. 5673 // This lets the instruction/bundle never be scheduled and 5674 // eventually disable vectorization. 5675 BundleMember->Dependencies++; 5676 BundleMember->incrementUnscheduledDeps(1); 5677 } 5678 } 5679 } 5680 5681 // Handle the memory dependencies. 5682 ScheduleData *DepDest = BundleMember->NextLoadStore; 5683 if (DepDest) { 5684 Instruction *SrcInst = BundleMember->Inst; 5685 MemoryLocation SrcLoc = getLocation(SrcInst, SLP->AA); 5686 bool SrcMayWrite = BundleMember->Inst->mayWriteToMemory(); 5687 unsigned numAliased = 0; 5688 unsigned DistToSrc = 1; 5689 5690 while (DepDest) { 5691 assert(isInSchedulingRegion(DepDest)); 5692 5693 // We have two limits to reduce the complexity: 5694 // 1) AliasedCheckLimit: It's a small limit to reduce calls to 5695 // SLP->isAliased (which is the expensive part in this loop). 5696 // 2) MaxMemDepDistance: It's for very large blocks and it aborts 5697 // the whole loop (even if the loop is fast, it's quadratic). 5698 // It's important for the loop break condition (see below) to 5699 // check this limit even between two read-only instructions. 5700 if (DistToSrc >= MaxMemDepDistance || 5701 ((SrcMayWrite || DepDest->Inst->mayWriteToMemory()) && 5702 (numAliased >= AliasedCheckLimit || 5703 SLP->isAliased(SrcLoc, SrcInst, DepDest->Inst)))) { 5704 5705 // We increment the counter only if the locations are aliased 5706 // (instead of counting all alias checks). This gives a better 5707 // balance between reduced runtime and accurate dependencies. 5708 numAliased++; 5709 5710 DepDest->MemoryDependencies.push_back(BundleMember); 5711 BundleMember->Dependencies++; 5712 ScheduleData *DestBundle = DepDest->FirstInBundle; 5713 if (!DestBundle->IsScheduled) { 5714 BundleMember->incrementUnscheduledDeps(1); 5715 } 5716 if (!DestBundle->hasValidDependencies()) { 5717 WorkList.push_back(DestBundle); 5718 } 5719 } 5720 DepDest = DepDest->NextLoadStore; 5721 5722 // Example, explaining the loop break condition: Let's assume our 5723 // starting instruction is i0 and MaxMemDepDistance = 3. 5724 // 5725 // +--------v--v--v 5726 // i0,i1,i2,i3,i4,i5,i6,i7,i8 5727 // +--------^--^--^ 5728 // 5729 // MaxMemDepDistance let us stop alias-checking at i3 and we add 5730 // dependencies from i0 to i3,i4,.. (even if they are not aliased). 5731 // Previously we already added dependencies from i3 to i6,i7,i8 5732 // (because of MaxMemDepDistance). As we added a dependency from 5733 // i0 to i3, we have transitive dependencies from i0 to i6,i7,i8 5734 // and we can abort this loop at i6. 5735 if (DistToSrc >= 2 * MaxMemDepDistance) 5736 break; 5737 DistToSrc++; 5738 } 5739 } 5740 } 5741 BundleMember = BundleMember->NextInBundle; 5742 } 5743 if (InsertInReadyList && SD->isReady()) { 5744 ReadyInsts.push_back(SD); 5745 LLVM_DEBUG(dbgs() << "SLP: gets ready on update: " << *SD->Inst 5746 << "\n"); 5747 } 5748 } 5749 } 5750 5751 void BoUpSLP::BlockScheduling::resetSchedule() { 5752 assert(ScheduleStart && 5753 "tried to reset schedule on block which has not been scheduled"); 5754 for (Instruction *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 5755 doForAllOpcodes(I, [&](ScheduleData *SD) { 5756 assert(isInSchedulingRegion(SD) && 5757 "ScheduleData not in scheduling region"); 5758 SD->IsScheduled = false; 5759 SD->resetUnscheduledDeps(); 5760 }); 5761 } 5762 ReadyInsts.clear(); 5763 } 5764 5765 void BoUpSLP::scheduleBlock(BlockScheduling *BS) { 5766 if (!BS->ScheduleStart) 5767 return; 5768 5769 LLVM_DEBUG(dbgs() << "SLP: schedule block " << BS->BB->getName() << "\n"); 5770 5771 BS->resetSchedule(); 5772 5773 // For the real scheduling we use a more sophisticated ready-list: it is 5774 // sorted by the original instruction location. This lets the final schedule 5775 // be as close as possible to the original instruction order. 5776 struct ScheduleDataCompare { 5777 bool operator()(ScheduleData *SD1, ScheduleData *SD2) const { 5778 return SD2->SchedulingPriority < SD1->SchedulingPriority; 5779 } 5780 }; 5781 std::set<ScheduleData *, ScheduleDataCompare> ReadyInsts; 5782 5783 // Ensure that all dependency data is updated and fill the ready-list with 5784 // initial instructions. 5785 int Idx = 0; 5786 int NumToSchedule = 0; 5787 for (auto *I = BS->ScheduleStart; I != BS->ScheduleEnd; 5788 I = I->getNextNode()) { 5789 BS->doForAllOpcodes(I, [this, &Idx, &NumToSchedule, BS](ScheduleData *SD) { 5790 assert(SD->isPartOfBundle() == 5791 (getTreeEntry(SD->Inst) != nullptr) && 5792 "scheduler and vectorizer bundle mismatch"); 5793 SD->FirstInBundle->SchedulingPriority = Idx++; 5794 if (SD->isSchedulingEntity()) { 5795 BS->calculateDependencies(SD, false, this); 5796 NumToSchedule++; 5797 } 5798 }); 5799 } 5800 BS->initialFillReadyList(ReadyInsts); 5801 5802 Instruction *LastScheduledInst = BS->ScheduleEnd; 5803 5804 // Do the "real" scheduling. 5805 while (!ReadyInsts.empty()) { 5806 ScheduleData *picked = *ReadyInsts.begin(); 5807 ReadyInsts.erase(ReadyInsts.begin()); 5808 5809 // Move the scheduled instruction(s) to their dedicated places, if not 5810 // there yet. 5811 ScheduleData *BundleMember = picked; 5812 while (BundleMember) { 5813 Instruction *pickedInst = BundleMember->Inst; 5814 if (LastScheduledInst->getNextNode() != pickedInst) { 5815 BS->BB->getInstList().remove(pickedInst); 5816 BS->BB->getInstList().insert(LastScheduledInst->getIterator(), 5817 pickedInst); 5818 } 5819 LastScheduledInst = pickedInst; 5820 BundleMember = BundleMember->NextInBundle; 5821 } 5822 5823 BS->schedule(picked, ReadyInsts); 5824 NumToSchedule--; 5825 } 5826 assert(NumToSchedule == 0 && "could not schedule all instructions"); 5827 5828 // Avoid duplicate scheduling of the block. 5829 BS->ScheduleStart = nullptr; 5830 } 5831 5832 unsigned BoUpSLP::getVectorElementSize(Value *V) { 5833 // If V is a store, just return the width of the stored value (or value 5834 // truncated just before storing) without traversing the expression tree. 5835 // This is the common case. 5836 if (auto *Store = dyn_cast<StoreInst>(V)) { 5837 if (auto *Trunc = dyn_cast<TruncInst>(Store->getValueOperand())) 5838 return DL->getTypeSizeInBits(Trunc->getSrcTy()); 5839 return DL->getTypeSizeInBits(Store->getValueOperand()->getType()); 5840 } 5841 5842 auto E = InstrElementSize.find(V); 5843 if (E != InstrElementSize.end()) 5844 return E->second; 5845 5846 // If V is not a store, we can traverse the expression tree to find loads 5847 // that feed it. The type of the loaded value may indicate a more suitable 5848 // width than V's type. We want to base the vector element size on the width 5849 // of memory operations where possible. 5850 SmallVector<std::pair<Instruction *, BasicBlock *>, 16> Worklist; 5851 SmallPtrSet<Instruction *, 16> Visited; 5852 if (auto *I = dyn_cast<Instruction>(V)) { 5853 Worklist.emplace_back(I, I->getParent()); 5854 Visited.insert(I); 5855 } 5856 5857 // Traverse the expression tree in bottom-up order looking for loads. If we 5858 // encounter an instruction we don't yet handle, we give up. 5859 auto Width = 0u; 5860 while (!Worklist.empty()) { 5861 Instruction *I; 5862 BasicBlock *Parent; 5863 std::tie(I, Parent) = Worklist.pop_back_val(); 5864 5865 // We should only be looking at scalar instructions here. If the current 5866 // instruction has a vector type, skip. 5867 auto *Ty = I->getType(); 5868 if (isa<VectorType>(Ty)) 5869 continue; 5870 5871 // If the current instruction is a load, update MaxWidth to reflect the 5872 // width of the loaded value. 5873 if (isa<LoadInst>(I) || isa<ExtractElementInst>(I) || 5874 isa<ExtractValueInst>(I)) 5875 Width = std::max<unsigned>(Width, DL->getTypeSizeInBits(Ty)); 5876 5877 // Otherwise, we need to visit the operands of the instruction. We only 5878 // handle the interesting cases from buildTree here. If an operand is an 5879 // instruction we haven't yet visited and from the same basic block as the 5880 // user or the use is a PHI node, we add it to the worklist. 5881 else if (isa<PHINode>(I) || isa<CastInst>(I) || isa<GetElementPtrInst>(I) || 5882 isa<CmpInst>(I) || isa<SelectInst>(I) || isa<BinaryOperator>(I) || 5883 isa<UnaryOperator>(I)) { 5884 for (Use &U : I->operands()) 5885 if (auto *J = dyn_cast<Instruction>(U.get())) 5886 if (Visited.insert(J).second && 5887 (isa<PHINode>(I) || J->getParent() == Parent)) 5888 Worklist.emplace_back(J, J->getParent()); 5889 } else { 5890 break; 5891 } 5892 } 5893 5894 // If we didn't encounter a memory access in the expression tree, or if we 5895 // gave up for some reason, just return the width of V. Otherwise, return the 5896 // maximum width we found. 5897 if (!Width) { 5898 if (auto *CI = dyn_cast<CmpInst>(V)) 5899 V = CI->getOperand(0); 5900 Width = DL->getTypeSizeInBits(V->getType()); 5901 } 5902 5903 for (Instruction *I : Visited) 5904 InstrElementSize[I] = Width; 5905 5906 return Width; 5907 } 5908 5909 // Determine if a value V in a vectorizable expression Expr can be demoted to a 5910 // smaller type with a truncation. We collect the values that will be demoted 5911 // in ToDemote and additional roots that require investigating in Roots. 5912 static bool collectValuesToDemote(Value *V, SmallPtrSetImpl<Value *> &Expr, 5913 SmallVectorImpl<Value *> &ToDemote, 5914 SmallVectorImpl<Value *> &Roots) { 5915 // We can always demote constants. 5916 if (isa<Constant>(V)) { 5917 ToDemote.push_back(V); 5918 return true; 5919 } 5920 5921 // If the value is not an instruction in the expression with only one use, it 5922 // cannot be demoted. 5923 auto *I = dyn_cast<Instruction>(V); 5924 if (!I || !I->hasOneUse() || !Expr.count(I)) 5925 return false; 5926 5927 switch (I->getOpcode()) { 5928 5929 // We can always demote truncations and extensions. Since truncations can 5930 // seed additional demotion, we save the truncated value. 5931 case Instruction::Trunc: 5932 Roots.push_back(I->getOperand(0)); 5933 break; 5934 case Instruction::ZExt: 5935 case Instruction::SExt: 5936 break; 5937 5938 // We can demote certain binary operations if we can demote both of their 5939 // operands. 5940 case Instruction::Add: 5941 case Instruction::Sub: 5942 case Instruction::Mul: 5943 case Instruction::And: 5944 case Instruction::Or: 5945 case Instruction::Xor: 5946 if (!collectValuesToDemote(I->getOperand(0), Expr, ToDemote, Roots) || 5947 !collectValuesToDemote(I->getOperand(1), Expr, ToDemote, Roots)) 5948 return false; 5949 break; 5950 5951 // We can demote selects if we can demote their true and false values. 5952 case Instruction::Select: { 5953 SelectInst *SI = cast<SelectInst>(I); 5954 if (!collectValuesToDemote(SI->getTrueValue(), Expr, ToDemote, Roots) || 5955 !collectValuesToDemote(SI->getFalseValue(), Expr, ToDemote, Roots)) 5956 return false; 5957 break; 5958 } 5959 5960 // We can demote phis if we can demote all their incoming operands. Note that 5961 // we don't need to worry about cycles since we ensure single use above. 5962 case Instruction::PHI: { 5963 PHINode *PN = cast<PHINode>(I); 5964 for (Value *IncValue : PN->incoming_values()) 5965 if (!collectValuesToDemote(IncValue, Expr, ToDemote, Roots)) 5966 return false; 5967 break; 5968 } 5969 5970 // Otherwise, conservatively give up. 5971 default: 5972 return false; 5973 } 5974 5975 // Record the value that we can demote. 5976 ToDemote.push_back(V); 5977 return true; 5978 } 5979 5980 void BoUpSLP::computeMinimumValueSizes() { 5981 // If there are no external uses, the expression tree must be rooted by a 5982 // store. We can't demote in-memory values, so there is nothing to do here. 5983 if (ExternalUses.empty()) 5984 return; 5985 5986 // We only attempt to truncate integer expressions. 5987 auto &TreeRoot = VectorizableTree[0]->Scalars; 5988 auto *TreeRootIT = dyn_cast<IntegerType>(TreeRoot[0]->getType()); 5989 if (!TreeRootIT) 5990 return; 5991 5992 // If the expression is not rooted by a store, these roots should have 5993 // external uses. We will rely on InstCombine to rewrite the expression in 5994 // the narrower type. However, InstCombine only rewrites single-use values. 5995 // This means that if a tree entry other than a root is used externally, it 5996 // must have multiple uses and InstCombine will not rewrite it. The code 5997 // below ensures that only the roots are used externally. 5998 SmallPtrSet<Value *, 32> Expr(TreeRoot.begin(), TreeRoot.end()); 5999 for (auto &EU : ExternalUses) 6000 if (!Expr.erase(EU.Scalar)) 6001 return; 6002 if (!Expr.empty()) 6003 return; 6004 6005 // Collect the scalar values of the vectorizable expression. We will use this 6006 // context to determine which values can be demoted. If we see a truncation, 6007 // we mark it as seeding another demotion. 6008 for (auto &EntryPtr : VectorizableTree) 6009 Expr.insert(EntryPtr->Scalars.begin(), EntryPtr->Scalars.end()); 6010 6011 // Ensure the roots of the vectorizable tree don't form a cycle. They must 6012 // have a single external user that is not in the vectorizable tree. 6013 for (auto *Root : TreeRoot) 6014 if (!Root->hasOneUse() || Expr.count(*Root->user_begin())) 6015 return; 6016 6017 // Conservatively determine if we can actually truncate the roots of the 6018 // expression. Collect the values that can be demoted in ToDemote and 6019 // additional roots that require investigating in Roots. 6020 SmallVector<Value *, 32> ToDemote; 6021 SmallVector<Value *, 4> Roots; 6022 for (auto *Root : TreeRoot) 6023 if (!collectValuesToDemote(Root, Expr, ToDemote, Roots)) 6024 return; 6025 6026 // The maximum bit width required to represent all the values that can be 6027 // demoted without loss of precision. It would be safe to truncate the roots 6028 // of the expression to this width. 6029 auto MaxBitWidth = 8u; 6030 6031 // We first check if all the bits of the roots are demanded. If they're not, 6032 // we can truncate the roots to this narrower type. 6033 for (auto *Root : TreeRoot) { 6034 auto Mask = DB->getDemandedBits(cast<Instruction>(Root)); 6035 MaxBitWidth = std::max<unsigned>( 6036 Mask.getBitWidth() - Mask.countLeadingZeros(), MaxBitWidth); 6037 } 6038 6039 // True if the roots can be zero-extended back to their original type, rather 6040 // than sign-extended. We know that if the leading bits are not demanded, we 6041 // can safely zero-extend. So we initialize IsKnownPositive to True. 6042 bool IsKnownPositive = true; 6043 6044 // If all the bits of the roots are demanded, we can try a little harder to 6045 // compute a narrower type. This can happen, for example, if the roots are 6046 // getelementptr indices. InstCombine promotes these indices to the pointer 6047 // width. Thus, all their bits are technically demanded even though the 6048 // address computation might be vectorized in a smaller type. 6049 // 6050 // We start by looking at each entry that can be demoted. We compute the 6051 // maximum bit width required to store the scalar by using ValueTracking to 6052 // compute the number of high-order bits we can truncate. 6053 if (MaxBitWidth == DL->getTypeSizeInBits(TreeRoot[0]->getType()) && 6054 llvm::all_of(TreeRoot, [](Value *R) { 6055 assert(R->hasOneUse() && "Root should have only one use!"); 6056 return isa<GetElementPtrInst>(R->user_back()); 6057 })) { 6058 MaxBitWidth = 8u; 6059 6060 // Determine if the sign bit of all the roots is known to be zero. If not, 6061 // IsKnownPositive is set to False. 6062 IsKnownPositive = llvm::all_of(TreeRoot, [&](Value *R) { 6063 KnownBits Known = computeKnownBits(R, *DL); 6064 return Known.isNonNegative(); 6065 }); 6066 6067 // Determine the maximum number of bits required to store the scalar 6068 // values. 6069 for (auto *Scalar : ToDemote) { 6070 auto NumSignBits = ComputeNumSignBits(Scalar, *DL, 0, AC, nullptr, DT); 6071 auto NumTypeBits = DL->getTypeSizeInBits(Scalar->getType()); 6072 MaxBitWidth = std::max<unsigned>(NumTypeBits - NumSignBits, MaxBitWidth); 6073 } 6074 6075 // If we can't prove that the sign bit is zero, we must add one to the 6076 // maximum bit width to account for the unknown sign bit. This preserves 6077 // the existing sign bit so we can safely sign-extend the root back to the 6078 // original type. Otherwise, if we know the sign bit is zero, we will 6079 // zero-extend the root instead. 6080 // 6081 // FIXME: This is somewhat suboptimal, as there will be cases where adding 6082 // one to the maximum bit width will yield a larger-than-necessary 6083 // type. In general, we need to add an extra bit only if we can't 6084 // prove that the upper bit of the original type is equal to the 6085 // upper bit of the proposed smaller type. If these two bits are the 6086 // same (either zero or one) we know that sign-extending from the 6087 // smaller type will result in the same value. Here, since we can't 6088 // yet prove this, we are just making the proposed smaller type 6089 // larger to ensure correctness. 6090 if (!IsKnownPositive) 6091 ++MaxBitWidth; 6092 } 6093 6094 // Round MaxBitWidth up to the next power-of-two. 6095 if (!isPowerOf2_64(MaxBitWidth)) 6096 MaxBitWidth = NextPowerOf2(MaxBitWidth); 6097 6098 // If the maximum bit width we compute is less than the with of the roots' 6099 // type, we can proceed with the narrowing. Otherwise, do nothing. 6100 if (MaxBitWidth >= TreeRootIT->getBitWidth()) 6101 return; 6102 6103 // If we can truncate the root, we must collect additional values that might 6104 // be demoted as a result. That is, those seeded by truncations we will 6105 // modify. 6106 while (!Roots.empty()) 6107 collectValuesToDemote(Roots.pop_back_val(), Expr, ToDemote, Roots); 6108 6109 // Finally, map the values we can demote to the maximum bit with we computed. 6110 for (auto *Scalar : ToDemote) 6111 MinBWs[Scalar] = std::make_pair(MaxBitWidth, !IsKnownPositive); 6112 } 6113 6114 namespace { 6115 6116 /// The SLPVectorizer Pass. 6117 struct SLPVectorizer : public FunctionPass { 6118 SLPVectorizerPass Impl; 6119 6120 /// Pass identification, replacement for typeid 6121 static char ID; 6122 6123 explicit SLPVectorizer() : FunctionPass(ID) { 6124 initializeSLPVectorizerPass(*PassRegistry::getPassRegistry()); 6125 } 6126 6127 bool doInitialization(Module &M) override { 6128 return false; 6129 } 6130 6131 bool runOnFunction(Function &F) override { 6132 if (skipFunction(F)) 6133 return false; 6134 6135 auto *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 6136 auto *TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F); 6137 auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>(); 6138 auto *TLI = TLIP ? &TLIP->getTLI(F) : nullptr; 6139 auto *AA = &getAnalysis<AAResultsWrapperPass>().getAAResults(); 6140 auto *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 6141 auto *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 6142 auto *AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F); 6143 auto *DB = &getAnalysis<DemandedBitsWrapperPass>().getDemandedBits(); 6144 auto *ORE = &getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE(); 6145 6146 return Impl.runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 6147 } 6148 6149 void getAnalysisUsage(AnalysisUsage &AU) const override { 6150 FunctionPass::getAnalysisUsage(AU); 6151 AU.addRequired<AssumptionCacheTracker>(); 6152 AU.addRequired<ScalarEvolutionWrapperPass>(); 6153 AU.addRequired<AAResultsWrapperPass>(); 6154 AU.addRequired<TargetTransformInfoWrapperPass>(); 6155 AU.addRequired<LoopInfoWrapperPass>(); 6156 AU.addRequired<DominatorTreeWrapperPass>(); 6157 AU.addRequired<DemandedBitsWrapperPass>(); 6158 AU.addRequired<OptimizationRemarkEmitterWrapperPass>(); 6159 AU.addRequired<InjectTLIMappingsLegacy>(); 6160 AU.addPreserved<LoopInfoWrapperPass>(); 6161 AU.addPreserved<DominatorTreeWrapperPass>(); 6162 AU.addPreserved<AAResultsWrapperPass>(); 6163 AU.addPreserved<GlobalsAAWrapperPass>(); 6164 AU.setPreservesCFG(); 6165 } 6166 }; 6167 6168 } // end anonymous namespace 6169 6170 PreservedAnalyses SLPVectorizerPass::run(Function &F, FunctionAnalysisManager &AM) { 6171 auto *SE = &AM.getResult<ScalarEvolutionAnalysis>(F); 6172 auto *TTI = &AM.getResult<TargetIRAnalysis>(F); 6173 auto *TLI = AM.getCachedResult<TargetLibraryAnalysis>(F); 6174 auto *AA = &AM.getResult<AAManager>(F); 6175 auto *LI = &AM.getResult<LoopAnalysis>(F); 6176 auto *DT = &AM.getResult<DominatorTreeAnalysis>(F); 6177 auto *AC = &AM.getResult<AssumptionAnalysis>(F); 6178 auto *DB = &AM.getResult<DemandedBitsAnalysis>(F); 6179 auto *ORE = &AM.getResult<OptimizationRemarkEmitterAnalysis>(F); 6180 6181 bool Changed = runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 6182 if (!Changed) 6183 return PreservedAnalyses::all(); 6184 6185 PreservedAnalyses PA; 6186 PA.preserveSet<CFGAnalyses>(); 6187 PA.preserve<AAManager>(); 6188 PA.preserve<GlobalsAA>(); 6189 return PA; 6190 } 6191 6192 bool SLPVectorizerPass::runImpl(Function &F, ScalarEvolution *SE_, 6193 TargetTransformInfo *TTI_, 6194 TargetLibraryInfo *TLI_, AAResults *AA_, 6195 LoopInfo *LI_, DominatorTree *DT_, 6196 AssumptionCache *AC_, DemandedBits *DB_, 6197 OptimizationRemarkEmitter *ORE_) { 6198 if (!RunSLPVectorization) 6199 return false; 6200 SE = SE_; 6201 TTI = TTI_; 6202 TLI = TLI_; 6203 AA = AA_; 6204 LI = LI_; 6205 DT = DT_; 6206 AC = AC_; 6207 DB = DB_; 6208 DL = &F.getParent()->getDataLayout(); 6209 6210 Stores.clear(); 6211 GEPs.clear(); 6212 bool Changed = false; 6213 6214 // If the target claims to have no vector registers don't attempt 6215 // vectorization. 6216 if (!TTI->getNumberOfRegisters(TTI->getRegisterClassForType(true))) 6217 return false; 6218 6219 // Don't vectorize when the attribute NoImplicitFloat is used. 6220 if (F.hasFnAttribute(Attribute::NoImplicitFloat)) 6221 return false; 6222 6223 LLVM_DEBUG(dbgs() << "SLP: Analyzing blocks in " << F.getName() << ".\n"); 6224 6225 // Use the bottom up slp vectorizer to construct chains that start with 6226 // store instructions. 6227 BoUpSLP R(&F, SE, TTI, TLI, AA, LI, DT, AC, DB, DL, ORE_); 6228 6229 // A general note: the vectorizer must use BoUpSLP::eraseInstruction() to 6230 // delete instructions. 6231 6232 // Scan the blocks in the function in post order. 6233 for (auto BB : post_order(&F.getEntryBlock())) { 6234 collectSeedInstructions(BB); 6235 6236 // Vectorize trees that end at stores. 6237 if (!Stores.empty()) { 6238 LLVM_DEBUG(dbgs() << "SLP: Found stores for " << Stores.size() 6239 << " underlying objects.\n"); 6240 Changed |= vectorizeStoreChains(R); 6241 } 6242 6243 // Vectorize trees that end at reductions. 6244 Changed |= vectorizeChainsInBlock(BB, R); 6245 6246 // Vectorize the index computations of getelementptr instructions. This 6247 // is primarily intended to catch gather-like idioms ending at 6248 // non-consecutive loads. 6249 if (!GEPs.empty()) { 6250 LLVM_DEBUG(dbgs() << "SLP: Found GEPs for " << GEPs.size() 6251 << " underlying objects.\n"); 6252 Changed |= vectorizeGEPIndices(BB, R); 6253 } 6254 } 6255 6256 if (Changed) { 6257 R.optimizeGatherSequence(); 6258 LLVM_DEBUG(dbgs() << "SLP: vectorized \"" << F.getName() << "\"\n"); 6259 } 6260 return Changed; 6261 } 6262 6263 bool SLPVectorizerPass::vectorizeStoreChain(ArrayRef<Value *> Chain, BoUpSLP &R, 6264 unsigned Idx) { 6265 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " << Chain.size() 6266 << "\n"); 6267 const unsigned Sz = R.getVectorElementSize(Chain[0]); 6268 const unsigned MinVF = R.getMinVecRegSize() / Sz; 6269 unsigned VF = Chain.size(); 6270 6271 if (!isPowerOf2_32(Sz) || !isPowerOf2_32(VF) || VF < 2 || VF < MinVF) 6272 return false; 6273 6274 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << VF << " stores at offset " << Idx 6275 << "\n"); 6276 6277 R.buildTree(Chain); 6278 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 6279 // TODO: Handle orders of size less than number of elements in the vector. 6280 if (Order && Order->size() == Chain.size()) { 6281 // TODO: reorder tree nodes without tree rebuilding. 6282 SmallVector<Value *, 4> ReorderedOps(Chain.rbegin(), Chain.rend()); 6283 llvm::transform(*Order, ReorderedOps.begin(), 6284 [Chain](const unsigned Idx) { return Chain[Idx]; }); 6285 R.buildTree(ReorderedOps); 6286 } 6287 if (R.isTreeTinyAndNotFullyVectorizable()) 6288 return false; 6289 if (R.isLoadCombineCandidate()) 6290 return false; 6291 6292 R.computeMinimumValueSizes(); 6293 6294 InstructionCost Cost = R.getTreeCost(); 6295 6296 LLVM_DEBUG(dbgs() << "SLP: Found cost = " << Cost << " for VF =" << VF << "\n"); 6297 if (Cost < -SLPCostThreshold) { 6298 LLVM_DEBUG(dbgs() << "SLP: Decided to vectorize cost = " << Cost << "\n"); 6299 6300 using namespace ore; 6301 6302 R.getORE()->emit(OptimizationRemark(SV_NAME, "StoresVectorized", 6303 cast<StoreInst>(Chain[0])) 6304 << "Stores SLP vectorized with cost " << NV("Cost", Cost) 6305 << " and with tree size " 6306 << NV("TreeSize", R.getTreeSize())); 6307 6308 R.vectorizeTree(); 6309 return true; 6310 } 6311 6312 return false; 6313 } 6314 6315 bool SLPVectorizerPass::vectorizeStores(ArrayRef<StoreInst *> Stores, 6316 BoUpSLP &R) { 6317 // We may run into multiple chains that merge into a single chain. We mark the 6318 // stores that we vectorized so that we don't visit the same store twice. 6319 BoUpSLP::ValueSet VectorizedStores; 6320 bool Changed = false; 6321 6322 int E = Stores.size(); 6323 SmallBitVector Tails(E, false); 6324 int MaxIter = MaxStoreLookup.getValue(); 6325 SmallVector<std::pair<int, int>, 16> ConsecutiveChain( 6326 E, std::make_pair(E, INT_MAX)); 6327 SmallVector<SmallBitVector, 4> CheckedPairs(E, SmallBitVector(E, false)); 6328 int IterCnt; 6329 auto &&FindConsecutiveAccess = [this, &Stores, &Tails, &IterCnt, MaxIter, 6330 &CheckedPairs, 6331 &ConsecutiveChain](int K, int Idx) { 6332 if (IterCnt >= MaxIter) 6333 return true; 6334 if (CheckedPairs[Idx].test(K)) 6335 return ConsecutiveChain[K].second == 1 && 6336 ConsecutiveChain[K].first == Idx; 6337 ++IterCnt; 6338 CheckedPairs[Idx].set(K); 6339 CheckedPairs[K].set(Idx); 6340 Optional<int> Diff = getPointersDiff(Stores[K]->getPointerOperand(), 6341 Stores[Idx]->getPointerOperand(), *DL, 6342 *SE, /*StrictCheck=*/true); 6343 if (!Diff || *Diff == 0) 6344 return false; 6345 int Val = *Diff; 6346 if (Val < 0) { 6347 if (ConsecutiveChain[Idx].second > -Val) { 6348 Tails.set(K); 6349 ConsecutiveChain[Idx] = std::make_pair(K, -Val); 6350 } 6351 return false; 6352 } 6353 if (ConsecutiveChain[K].second <= Val) 6354 return false; 6355 6356 Tails.set(Idx); 6357 ConsecutiveChain[K] = std::make_pair(Idx, Val); 6358 return Val == 1; 6359 }; 6360 // Do a quadratic search on all of the given stores in reverse order and find 6361 // all of the pairs of stores that follow each other. 6362 for (int Idx = E - 1; Idx >= 0; --Idx) { 6363 // If a store has multiple consecutive store candidates, search according 6364 // to the sequence: Idx-1, Idx+1, Idx-2, Idx+2, ... 6365 // This is because usually pairing with immediate succeeding or preceding 6366 // candidate create the best chance to find slp vectorization opportunity. 6367 const int MaxLookDepth = std::max(E - Idx, Idx + 1); 6368 IterCnt = 0; 6369 for (int Offset = 1, F = MaxLookDepth; Offset < F; ++Offset) 6370 if ((Idx >= Offset && FindConsecutiveAccess(Idx - Offset, Idx)) || 6371 (Idx + Offset < E && FindConsecutiveAccess(Idx + Offset, Idx))) 6372 break; 6373 } 6374 6375 // Tracks if we tried to vectorize stores starting from the given tail 6376 // already. 6377 SmallBitVector TriedTails(E, false); 6378 // For stores that start but don't end a link in the chain: 6379 for (int Cnt = E; Cnt > 0; --Cnt) { 6380 int I = Cnt - 1; 6381 if (ConsecutiveChain[I].first == E || Tails.test(I)) 6382 continue; 6383 // We found a store instr that starts a chain. Now follow the chain and try 6384 // to vectorize it. 6385 BoUpSLP::ValueList Operands; 6386 // Collect the chain into a list. 6387 while (I != E && !VectorizedStores.count(Stores[I])) { 6388 Operands.push_back(Stores[I]); 6389 Tails.set(I); 6390 if (ConsecutiveChain[I].second != 1) { 6391 // Mark the new end in the chain and go back, if required. It might be 6392 // required if the original stores come in reversed order, for example. 6393 if (ConsecutiveChain[I].first != E && 6394 Tails.test(ConsecutiveChain[I].first) && !TriedTails.test(I) && 6395 !VectorizedStores.count(Stores[ConsecutiveChain[I].first])) { 6396 TriedTails.set(I); 6397 Tails.reset(ConsecutiveChain[I].first); 6398 if (Cnt < ConsecutiveChain[I].first + 2) 6399 Cnt = ConsecutiveChain[I].first + 2; 6400 } 6401 break; 6402 } 6403 // Move to the next value in the chain. 6404 I = ConsecutiveChain[I].first; 6405 } 6406 assert(!Operands.empty() && "Expected non-empty list of stores."); 6407 6408 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 6409 unsigned EltSize = R.getVectorElementSize(Operands[0]); 6410 unsigned MaxElts = llvm::PowerOf2Floor(MaxVecRegSize / EltSize); 6411 6412 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / EltSize); 6413 unsigned MaxVF = std::min(R.getMaximumVF(EltSize, Instruction::Store), 6414 MaxElts); 6415 6416 // FIXME: Is division-by-2 the correct step? Should we assert that the 6417 // register size is a power-of-2? 6418 unsigned StartIdx = 0; 6419 for (unsigned Size = MaxVF; Size >= MinVF; Size /= 2) { 6420 for (unsigned Cnt = StartIdx, E = Operands.size(); Cnt + Size <= E;) { 6421 ArrayRef<Value *> Slice = makeArrayRef(Operands).slice(Cnt, Size); 6422 if (!VectorizedStores.count(Slice.front()) && 6423 !VectorizedStores.count(Slice.back()) && 6424 vectorizeStoreChain(Slice, R, Cnt)) { 6425 // Mark the vectorized stores so that we don't vectorize them again. 6426 VectorizedStores.insert(Slice.begin(), Slice.end()); 6427 Changed = true; 6428 // If we vectorized initial block, no need to try to vectorize it 6429 // again. 6430 if (Cnt == StartIdx) 6431 StartIdx += Size; 6432 Cnt += Size; 6433 continue; 6434 } 6435 ++Cnt; 6436 } 6437 // Check if the whole array was vectorized already - exit. 6438 if (StartIdx >= Operands.size()) 6439 break; 6440 } 6441 } 6442 6443 return Changed; 6444 } 6445 6446 void SLPVectorizerPass::collectSeedInstructions(BasicBlock *BB) { 6447 // Initialize the collections. We will make a single pass over the block. 6448 Stores.clear(); 6449 GEPs.clear(); 6450 6451 // Visit the store and getelementptr instructions in BB and organize them in 6452 // Stores and GEPs according to the underlying objects of their pointer 6453 // operands. 6454 for (Instruction &I : *BB) { 6455 // Ignore store instructions that are volatile or have a pointer operand 6456 // that doesn't point to a scalar type. 6457 if (auto *SI = dyn_cast<StoreInst>(&I)) { 6458 if (!SI->isSimple()) 6459 continue; 6460 if (!isValidElementType(SI->getValueOperand()->getType())) 6461 continue; 6462 Stores[getUnderlyingObject(SI->getPointerOperand())].push_back(SI); 6463 } 6464 6465 // Ignore getelementptr instructions that have more than one index, a 6466 // constant index, or a pointer operand that doesn't point to a scalar 6467 // type. 6468 else if (auto *GEP = dyn_cast<GetElementPtrInst>(&I)) { 6469 auto Idx = GEP->idx_begin()->get(); 6470 if (GEP->getNumIndices() > 1 || isa<Constant>(Idx)) 6471 continue; 6472 if (!isValidElementType(Idx->getType())) 6473 continue; 6474 if (GEP->getType()->isVectorTy()) 6475 continue; 6476 GEPs[GEP->getPointerOperand()].push_back(GEP); 6477 } 6478 } 6479 } 6480 6481 bool SLPVectorizerPass::tryToVectorizePair(Value *A, Value *B, BoUpSLP &R) { 6482 if (!A || !B) 6483 return false; 6484 Value *VL[] = {A, B}; 6485 return tryToVectorizeList(VL, R, /*AllowReorder=*/true); 6486 } 6487 6488 bool SLPVectorizerPass::tryToVectorizeList(ArrayRef<Value *> VL, BoUpSLP &R, 6489 bool AllowReorder, 6490 ArrayRef<Value *> InsertUses) { 6491 if (VL.size() < 2) 6492 return false; 6493 6494 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize a list of length = " 6495 << VL.size() << ".\n"); 6496 6497 // Check that all of the parts are instructions of the same type, 6498 // we permit an alternate opcode via InstructionsState. 6499 InstructionsState S = getSameOpcode(VL); 6500 if (!S.getOpcode()) 6501 return false; 6502 6503 Instruction *I0 = cast<Instruction>(S.OpValue); 6504 // Make sure invalid types (including vector type) are rejected before 6505 // determining vectorization factor for scalar instructions. 6506 for (Value *V : VL) { 6507 Type *Ty = V->getType(); 6508 if (!isValidElementType(Ty)) { 6509 // NOTE: the following will give user internal llvm type name, which may 6510 // not be useful. 6511 R.getORE()->emit([&]() { 6512 std::string type_str; 6513 llvm::raw_string_ostream rso(type_str); 6514 Ty->print(rso); 6515 return OptimizationRemarkMissed(SV_NAME, "UnsupportedType", I0) 6516 << "Cannot SLP vectorize list: type " 6517 << rso.str() + " is unsupported by vectorizer"; 6518 }); 6519 return false; 6520 } 6521 } 6522 6523 unsigned Sz = R.getVectorElementSize(I0); 6524 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / Sz); 6525 unsigned MaxVF = std::max<unsigned>(PowerOf2Floor(VL.size()), MinVF); 6526 MaxVF = std::min(R.getMaximumVF(Sz, S.getOpcode()), MaxVF); 6527 if (MaxVF < 2) { 6528 R.getORE()->emit([&]() { 6529 return OptimizationRemarkMissed(SV_NAME, "SmallVF", I0) 6530 << "Cannot SLP vectorize list: vectorization factor " 6531 << "less than 2 is not supported"; 6532 }); 6533 return false; 6534 } 6535 6536 bool Changed = false; 6537 bool CandidateFound = false; 6538 InstructionCost MinCost = SLPCostThreshold.getValue(); 6539 6540 bool CompensateUseCost = 6541 !InsertUses.empty() && llvm::all_of(InsertUses, [](const Value *V) { 6542 return V && isa<InsertElementInst>(V); 6543 }); 6544 assert((!CompensateUseCost || InsertUses.size() == VL.size()) && 6545 "Each scalar expected to have an associated InsertElement user."); 6546 6547 unsigned NextInst = 0, MaxInst = VL.size(); 6548 for (unsigned VF = MaxVF; NextInst + 1 < MaxInst && VF >= MinVF; VF /= 2) { 6549 // No actual vectorization should happen, if number of parts is the same as 6550 // provided vectorization factor (i.e. the scalar type is used for vector 6551 // code during codegen). 6552 auto *VecTy = FixedVectorType::get(VL[0]->getType(), VF); 6553 if (TTI->getNumberOfParts(VecTy) == VF) 6554 continue; 6555 for (unsigned I = NextInst; I < MaxInst; ++I) { 6556 unsigned OpsWidth = 0; 6557 6558 if (I + VF > MaxInst) 6559 OpsWidth = MaxInst - I; 6560 else 6561 OpsWidth = VF; 6562 6563 if (!isPowerOf2_32(OpsWidth) || OpsWidth < 2) 6564 break; 6565 6566 ArrayRef<Value *> Ops = VL.slice(I, OpsWidth); 6567 // Check that a previous iteration of this loop did not delete the Value. 6568 if (llvm::any_of(Ops, [&R](Value *V) { 6569 auto *I = dyn_cast<Instruction>(V); 6570 return I && R.isDeleted(I); 6571 })) 6572 continue; 6573 6574 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << OpsWidth << " operations " 6575 << "\n"); 6576 6577 R.buildTree(Ops); 6578 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 6579 // TODO: check if we can allow reordering for more cases. 6580 if (AllowReorder && Order) { 6581 // TODO: reorder tree nodes without tree rebuilding. 6582 // Conceptually, there is nothing actually preventing us from trying to 6583 // reorder a larger list. In fact, we do exactly this when vectorizing 6584 // reductions. However, at this point, we only expect to get here when 6585 // there are exactly two operations. 6586 assert(Ops.size() == 2); 6587 Value *ReorderedOps[] = {Ops[1], Ops[0]}; 6588 R.buildTree(ReorderedOps, None); 6589 } 6590 if (R.isTreeTinyAndNotFullyVectorizable()) 6591 continue; 6592 6593 R.computeMinimumValueSizes(); 6594 InstructionCost Cost = R.getTreeCost(); 6595 CandidateFound = true; 6596 if (CompensateUseCost) { 6597 // TODO: Use TTI's getScalarizationOverhead for sequence of inserts 6598 // rather than sum of single inserts as the latter may overestimate 6599 // cost. This work should imply improving cost estimation for extracts 6600 // that added in for external (for vectorization tree) users,i.e. that 6601 // part should also switch to same interface. 6602 // For example, the following case is projected code after SLP: 6603 // %4 = extractelement <4 x i64> %3, i32 0 6604 // %v0 = insertelement <4 x i64> poison, i64 %4, i32 0 6605 // %5 = extractelement <4 x i64> %3, i32 1 6606 // %v1 = insertelement <4 x i64> %v0, i64 %5, i32 1 6607 // %6 = extractelement <4 x i64> %3, i32 2 6608 // %v2 = insertelement <4 x i64> %v1, i64 %6, i32 2 6609 // %7 = extractelement <4 x i64> %3, i32 3 6610 // %v3 = insertelement <4 x i64> %v2, i64 %7, i32 3 6611 // 6612 // Extracts here added by SLP in order to feed users (the inserts) of 6613 // original scalars and contribute to "ExtractCost" at cost evaluation. 6614 // The inserts in turn form sequence to build an aggregate that 6615 // detected by findBuildAggregate routine. 6616 // SLP makes an assumption that such sequence will be optimized away 6617 // later (instcombine) so it tries to compensate ExctractCost with 6618 // cost of insert sequence. 6619 // Current per element cost calculation approach is not quite accurate 6620 // and tends to create bias toward favoring vectorization. 6621 // Switching to the TTI interface might help a bit. 6622 // Alternative solution could be pattern-match to detect a no-op or 6623 // shuffle. 6624 InstructionCost UserCost = 0; 6625 for (unsigned Lane = 0; Lane < OpsWidth; Lane++) { 6626 auto *IE = cast<InsertElementInst>(InsertUses[I + Lane]); 6627 if (auto *CI = dyn_cast<ConstantInt>(IE->getOperand(2))) 6628 UserCost += TTI->getVectorInstrCost( 6629 Instruction::InsertElement, IE->getType(), CI->getZExtValue()); 6630 } 6631 LLVM_DEBUG(dbgs() << "SLP: Compensate cost of users by: " << UserCost 6632 << ".\n"); 6633 Cost -= UserCost; 6634 } 6635 6636 MinCost = std::min(MinCost, Cost); 6637 6638 if (Cost < -SLPCostThreshold) { 6639 LLVM_DEBUG(dbgs() << "SLP: Vectorizing list at cost:" << Cost << ".\n"); 6640 R.getORE()->emit(OptimizationRemark(SV_NAME, "VectorizedList", 6641 cast<Instruction>(Ops[0])) 6642 << "SLP vectorized with cost " << ore::NV("Cost", Cost) 6643 << " and with tree size " 6644 << ore::NV("TreeSize", R.getTreeSize())); 6645 6646 R.vectorizeTree(); 6647 // Move to the next bundle. 6648 I += VF - 1; 6649 NextInst = I + 1; 6650 Changed = true; 6651 } 6652 } 6653 } 6654 6655 if (!Changed && CandidateFound) { 6656 R.getORE()->emit([&]() { 6657 return OptimizationRemarkMissed(SV_NAME, "NotBeneficial", I0) 6658 << "List vectorization was possible but not beneficial with cost " 6659 << ore::NV("Cost", MinCost) << " >= " 6660 << ore::NV("Treshold", -SLPCostThreshold); 6661 }); 6662 } else if (!Changed) { 6663 R.getORE()->emit([&]() { 6664 return OptimizationRemarkMissed(SV_NAME, "NotPossible", I0) 6665 << "Cannot SLP vectorize list: vectorization was impossible" 6666 << " with available vectorization factors"; 6667 }); 6668 } 6669 return Changed; 6670 } 6671 6672 bool SLPVectorizerPass::tryToVectorize(Instruction *I, BoUpSLP &R) { 6673 if (!I) 6674 return false; 6675 6676 if (!isa<BinaryOperator>(I) && !isa<CmpInst>(I)) 6677 return false; 6678 6679 Value *P = I->getParent(); 6680 6681 // Vectorize in current basic block only. 6682 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 6683 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 6684 if (!Op0 || !Op1 || Op0->getParent() != P || Op1->getParent() != P) 6685 return false; 6686 6687 // Try to vectorize V. 6688 if (tryToVectorizePair(Op0, Op1, R)) 6689 return true; 6690 6691 auto *A = dyn_cast<BinaryOperator>(Op0); 6692 auto *B = dyn_cast<BinaryOperator>(Op1); 6693 // Try to skip B. 6694 if (B && B->hasOneUse()) { 6695 auto *B0 = dyn_cast<BinaryOperator>(B->getOperand(0)); 6696 auto *B1 = dyn_cast<BinaryOperator>(B->getOperand(1)); 6697 if (B0 && B0->getParent() == P && tryToVectorizePair(A, B0, R)) 6698 return true; 6699 if (B1 && B1->getParent() == P && tryToVectorizePair(A, B1, R)) 6700 return true; 6701 } 6702 6703 // Try to skip A. 6704 if (A && A->hasOneUse()) { 6705 auto *A0 = dyn_cast<BinaryOperator>(A->getOperand(0)); 6706 auto *A1 = dyn_cast<BinaryOperator>(A->getOperand(1)); 6707 if (A0 && A0->getParent() == P && tryToVectorizePair(A0, B, R)) 6708 return true; 6709 if (A1 && A1->getParent() == P && tryToVectorizePair(A1, B, R)) 6710 return true; 6711 } 6712 return false; 6713 } 6714 6715 namespace { 6716 6717 /// Model horizontal reductions. 6718 /// 6719 /// A horizontal reduction is a tree of reduction instructions that has values 6720 /// that can be put into a vector as its leaves. For example: 6721 /// 6722 /// mul mul mul mul 6723 /// \ / \ / 6724 /// + + 6725 /// \ / 6726 /// + 6727 /// This tree has "mul" as its leaf values and "+" as its reduction 6728 /// instructions. A reduction can feed into a store or a binary operation 6729 /// feeding a phi. 6730 /// ... 6731 /// \ / 6732 /// + 6733 /// | 6734 /// phi += 6735 /// 6736 /// Or: 6737 /// ... 6738 /// \ / 6739 /// + 6740 /// | 6741 /// *p = 6742 /// 6743 class HorizontalReduction { 6744 using ReductionOpsType = SmallVector<Value *, 16>; 6745 using ReductionOpsListType = SmallVector<ReductionOpsType, 2>; 6746 ReductionOpsListType ReductionOps; 6747 SmallVector<Value *, 32> ReducedVals; 6748 // Use map vector to make stable output. 6749 MapVector<Instruction *, Value *> ExtraArgs; 6750 WeakTrackingVH ReductionRoot; 6751 /// The type of reduction operation. 6752 RecurKind RdxKind; 6753 6754 /// Checks if instruction is associative and can be vectorized. 6755 static bool isVectorizable(RecurKind Kind, Instruction *I) { 6756 if (Kind == RecurKind::None) 6757 return false; 6758 if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(Kind)) 6759 return true; 6760 6761 if (Kind == RecurKind::FMax || Kind == RecurKind::FMin) { 6762 // FP min/max are associative except for NaN and -0.0. We do not 6763 // have to rule out -0.0 here because the intrinsic semantics do not 6764 // specify a fixed result for it. 6765 return I->getFastMathFlags().noNaNs(); 6766 } 6767 6768 return I->isAssociative(); 6769 } 6770 6771 /// Checks if the ParentStackElem.first should be marked as a reduction 6772 /// operation with an extra argument or as extra argument itself. 6773 void markExtraArg(std::pair<Instruction *, unsigned> &ParentStackElem, 6774 Value *ExtraArg) { 6775 if (ExtraArgs.count(ParentStackElem.first)) { 6776 ExtraArgs[ParentStackElem.first] = nullptr; 6777 // We ran into something like: 6778 // ParentStackElem.first = ExtraArgs[ParentStackElem.first] + ExtraArg. 6779 // The whole ParentStackElem.first should be considered as an extra value 6780 // in this case. 6781 // Do not perform analysis of remaining operands of ParentStackElem.first 6782 // instruction, this whole instruction is an extra argument. 6783 ParentStackElem.second = getNumberOfOperands(ParentStackElem.first); 6784 } else { 6785 // We ran into something like: 6786 // ParentStackElem.first += ... + ExtraArg + ... 6787 ExtraArgs[ParentStackElem.first] = ExtraArg; 6788 } 6789 } 6790 6791 /// Creates reduction operation with the current opcode. 6792 static Value *createOp(IRBuilder<> &Builder, RecurKind Kind, Value *LHS, 6793 Value *RHS, const Twine &Name, bool UseSelect) { 6794 unsigned RdxOpcode = RecurrenceDescriptor::getOpcode(Kind); 6795 switch (Kind) { 6796 case RecurKind::Add: 6797 case RecurKind::Mul: 6798 case RecurKind::Or: 6799 case RecurKind::And: 6800 case RecurKind::Xor: 6801 case RecurKind::FAdd: 6802 case RecurKind::FMul: 6803 return Builder.CreateBinOp((Instruction::BinaryOps)RdxOpcode, LHS, RHS, 6804 Name); 6805 case RecurKind::FMax: 6806 return Builder.CreateBinaryIntrinsic(Intrinsic::maxnum, LHS, RHS); 6807 case RecurKind::FMin: 6808 return Builder.CreateBinaryIntrinsic(Intrinsic::minnum, LHS, RHS); 6809 case RecurKind::SMax: 6810 if (UseSelect) { 6811 Value *Cmp = Builder.CreateICmpSGT(LHS, RHS, Name); 6812 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6813 } 6814 return Builder.CreateBinaryIntrinsic(Intrinsic::smax, LHS, RHS); 6815 case RecurKind::SMin: 6816 if (UseSelect) { 6817 Value *Cmp = Builder.CreateICmpSLT(LHS, RHS, Name); 6818 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6819 } 6820 return Builder.CreateBinaryIntrinsic(Intrinsic::smin, LHS, RHS); 6821 case RecurKind::UMax: 6822 if (UseSelect) { 6823 Value *Cmp = Builder.CreateICmpUGT(LHS, RHS, Name); 6824 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6825 } 6826 return Builder.CreateBinaryIntrinsic(Intrinsic::umax, LHS, RHS); 6827 case RecurKind::UMin: 6828 if (UseSelect) { 6829 Value *Cmp = Builder.CreateICmpULT(LHS, RHS, Name); 6830 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6831 } 6832 return Builder.CreateBinaryIntrinsic(Intrinsic::umin, LHS, RHS); 6833 default: 6834 llvm_unreachable("Unknown reduction operation."); 6835 } 6836 } 6837 6838 /// Creates reduction operation with the current opcode with the IR flags 6839 /// from \p ReductionOps. 6840 static Value *createOp(IRBuilder<> &Builder, RecurKind RdxKind, Value *LHS, 6841 Value *RHS, const Twine &Name, 6842 const ReductionOpsListType &ReductionOps) { 6843 bool UseSelect = ReductionOps.size() == 2; 6844 assert((!UseSelect || isa<SelectInst>(ReductionOps[1][0])) && 6845 "Expected cmp + select pairs for reduction"); 6846 Value *Op = createOp(Builder, RdxKind, LHS, RHS, Name, UseSelect); 6847 if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(RdxKind)) { 6848 if (auto *Sel = dyn_cast<SelectInst>(Op)) { 6849 propagateIRFlags(Sel->getCondition(), ReductionOps[0]); 6850 propagateIRFlags(Op, ReductionOps[1]); 6851 return Op; 6852 } 6853 } 6854 propagateIRFlags(Op, ReductionOps[0]); 6855 return Op; 6856 } 6857 6858 /// Creates reduction operation with the current opcode with the IR flags 6859 /// from \p I. 6860 static Value *createOp(IRBuilder<> &Builder, RecurKind RdxKind, Value *LHS, 6861 Value *RHS, const Twine &Name, Instruction *I) { 6862 auto *SelI = dyn_cast<SelectInst>(I); 6863 Value *Op = createOp(Builder, RdxKind, LHS, RHS, Name, SelI != nullptr); 6864 if (SelI && RecurrenceDescriptor::isIntMinMaxRecurrenceKind(RdxKind)) { 6865 if (auto *Sel = dyn_cast<SelectInst>(Op)) 6866 propagateIRFlags(Sel->getCondition(), SelI->getCondition()); 6867 } 6868 propagateIRFlags(Op, I); 6869 return Op; 6870 } 6871 6872 static RecurKind getRdxKind(Instruction *I) { 6873 assert(I && "Expected instruction for reduction matching"); 6874 TargetTransformInfo::ReductionFlags RdxFlags; 6875 if (match(I, m_Add(m_Value(), m_Value()))) 6876 return RecurKind::Add; 6877 if (match(I, m_Mul(m_Value(), m_Value()))) 6878 return RecurKind::Mul; 6879 if (match(I, m_And(m_Value(), m_Value()))) 6880 return RecurKind::And; 6881 if (match(I, m_Or(m_Value(), m_Value()))) 6882 return RecurKind::Or; 6883 if (match(I, m_Xor(m_Value(), m_Value()))) 6884 return RecurKind::Xor; 6885 if (match(I, m_FAdd(m_Value(), m_Value()))) 6886 return RecurKind::FAdd; 6887 if (match(I, m_FMul(m_Value(), m_Value()))) 6888 return RecurKind::FMul; 6889 6890 if (match(I, m_Intrinsic<Intrinsic::maxnum>(m_Value(), m_Value()))) 6891 return RecurKind::FMax; 6892 if (match(I, m_Intrinsic<Intrinsic::minnum>(m_Value(), m_Value()))) 6893 return RecurKind::FMin; 6894 6895 // This matches either cmp+select or intrinsics. SLP is expected to handle 6896 // either form. 6897 // TODO: If we are canonicalizing to intrinsics, we can remove several 6898 // special-case paths that deal with selects. 6899 if (match(I, m_SMax(m_Value(), m_Value()))) 6900 return RecurKind::SMax; 6901 if (match(I, m_SMin(m_Value(), m_Value()))) 6902 return RecurKind::SMin; 6903 if (match(I, m_UMax(m_Value(), m_Value()))) 6904 return RecurKind::UMax; 6905 if (match(I, m_UMin(m_Value(), m_Value()))) 6906 return RecurKind::UMin; 6907 6908 if (auto *Select = dyn_cast<SelectInst>(I)) { 6909 // Try harder: look for min/max pattern based on instructions producing 6910 // same values such as: select ((cmp Inst1, Inst2), Inst1, Inst2). 6911 // During the intermediate stages of SLP, it's very common to have 6912 // pattern like this (since optimizeGatherSequence is run only once 6913 // at the end): 6914 // %1 = extractelement <2 x i32> %a, i32 0 6915 // %2 = extractelement <2 x i32> %a, i32 1 6916 // %cond = icmp sgt i32 %1, %2 6917 // %3 = extractelement <2 x i32> %a, i32 0 6918 // %4 = extractelement <2 x i32> %a, i32 1 6919 // %select = select i1 %cond, i32 %3, i32 %4 6920 CmpInst::Predicate Pred; 6921 Instruction *L1; 6922 Instruction *L2; 6923 6924 Value *LHS = Select->getTrueValue(); 6925 Value *RHS = Select->getFalseValue(); 6926 Value *Cond = Select->getCondition(); 6927 6928 // TODO: Support inverse predicates. 6929 if (match(Cond, m_Cmp(Pred, m_Specific(LHS), m_Instruction(L2)))) { 6930 if (!isa<ExtractElementInst>(RHS) || 6931 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6932 return RecurKind::None; 6933 } else if (match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Specific(RHS)))) { 6934 if (!isa<ExtractElementInst>(LHS) || 6935 !L1->isIdenticalTo(cast<Instruction>(LHS))) 6936 return RecurKind::None; 6937 } else { 6938 if (!isa<ExtractElementInst>(LHS) || !isa<ExtractElementInst>(RHS)) 6939 return RecurKind::None; 6940 if (!match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Instruction(L2))) || 6941 !L1->isIdenticalTo(cast<Instruction>(LHS)) || 6942 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6943 return RecurKind::None; 6944 } 6945 6946 TargetTransformInfo::ReductionFlags RdxFlags; 6947 switch (Pred) { 6948 default: 6949 return RecurKind::None; 6950 case CmpInst::ICMP_SGT: 6951 case CmpInst::ICMP_SGE: 6952 return RecurKind::SMax; 6953 case CmpInst::ICMP_SLT: 6954 case CmpInst::ICMP_SLE: 6955 return RecurKind::SMin; 6956 case CmpInst::ICMP_UGT: 6957 case CmpInst::ICMP_UGE: 6958 return RecurKind::UMax; 6959 case CmpInst::ICMP_ULT: 6960 case CmpInst::ICMP_ULE: 6961 return RecurKind::UMin; 6962 } 6963 } 6964 return RecurKind::None; 6965 } 6966 6967 /// Get the index of the first operand. 6968 static unsigned getFirstOperandIndex(Instruction *I) { 6969 return isa<SelectInst>(I) ? 1 : 0; 6970 } 6971 6972 /// Total number of operands in the reduction operation. 6973 static unsigned getNumberOfOperands(Instruction *I) { 6974 return isa<SelectInst>(I) ? 3 : 2; 6975 } 6976 6977 /// Checks if the instruction is in basic block \p BB. 6978 /// For a min/max reduction check that both compare and select are in \p BB. 6979 static bool hasSameParent(Instruction *I, BasicBlock *BB, bool IsRedOp) { 6980 auto *Sel = dyn_cast<SelectInst>(I); 6981 if (IsRedOp && Sel) { 6982 auto *Cmp = cast<Instruction>(Sel->getCondition()); 6983 return Sel->getParent() == BB && Cmp->getParent() == BB; 6984 } 6985 return I->getParent() == BB; 6986 } 6987 6988 /// Expected number of uses for reduction operations/reduced values. 6989 static bool hasRequiredNumberOfUses(bool MatchCmpSel, Instruction *I) { 6990 // SelectInst must be used twice while the condition op must have single 6991 // use only. 6992 if (MatchCmpSel) { 6993 if (auto *Sel = dyn_cast<SelectInst>(I)) 6994 return Sel->hasNUses(2) && Sel->getCondition()->hasOneUse(); 6995 return I->hasNUses(2); 6996 } 6997 6998 // Arithmetic reduction operation must be used once only. 6999 return I->hasOneUse(); 7000 } 7001 7002 /// Initializes the list of reduction operations. 7003 void initReductionOps(Instruction *I) { 7004 if (isa<SelectInst>(I)) 7005 ReductionOps.assign(2, ReductionOpsType()); 7006 else 7007 ReductionOps.assign(1, ReductionOpsType()); 7008 } 7009 7010 /// Add all reduction operations for the reduction instruction \p I. 7011 void addReductionOps(Instruction *I) { 7012 if (auto *Sel = dyn_cast<SelectInst>(I)) { 7013 ReductionOps[0].emplace_back(Sel->getCondition()); 7014 ReductionOps[1].emplace_back(Sel); 7015 } else { 7016 ReductionOps[0].emplace_back(I); 7017 } 7018 } 7019 7020 static Value *getLHS(RecurKind Kind, Instruction *I) { 7021 if (Kind == RecurKind::None) 7022 return nullptr; 7023 return I->getOperand(getFirstOperandIndex(I)); 7024 } 7025 static Value *getRHS(RecurKind Kind, Instruction *I) { 7026 if (Kind == RecurKind::None) 7027 return nullptr; 7028 return I->getOperand(getFirstOperandIndex(I) + 1); 7029 } 7030 7031 public: 7032 HorizontalReduction() = default; 7033 7034 /// Try to find a reduction tree. 7035 bool matchAssociativeReduction(PHINode *Phi, Instruction *B) { 7036 assert((!Phi || is_contained(Phi->operands(), B)) && 7037 "Phi needs to use the binary operator"); 7038 7039 RdxKind = getRdxKind(B); 7040 7041 // We could have a initial reductions that is not an add. 7042 // r *= v1 + v2 + v3 + v4 7043 // In such a case start looking for a tree rooted in the first '+'. 7044 if (Phi) { 7045 if (getLHS(RdxKind, B) == Phi) { 7046 Phi = nullptr; 7047 B = dyn_cast<Instruction>(getRHS(RdxKind, B)); 7048 if (!B) 7049 return false; 7050 RdxKind = getRdxKind(B); 7051 } else if (getRHS(RdxKind, B) == Phi) { 7052 Phi = nullptr; 7053 B = dyn_cast<Instruction>(getLHS(RdxKind, B)); 7054 if (!B) 7055 return false; 7056 RdxKind = getRdxKind(B); 7057 } 7058 } 7059 7060 if (!isVectorizable(RdxKind, B)) 7061 return false; 7062 7063 // Analyze "regular" integer/FP types for reductions - no target-specific 7064 // types or pointers. 7065 Type *Ty = B->getType(); 7066 if (!isValidElementType(Ty) || Ty->isPointerTy()) 7067 return false; 7068 7069 // Though the ultimate reduction may have multiple uses, its condition must 7070 // have only single use. 7071 if (auto *SI = dyn_cast<SelectInst>(B)) 7072 if (!SI->getCondition()->hasOneUse()) 7073 return false; 7074 7075 ReductionRoot = B; 7076 7077 // The opcode for leaf values that we perform a reduction on. 7078 // For example: load(x) + load(y) + load(z) + fptoui(w) 7079 // The leaf opcode for 'w' does not match, so we don't include it as a 7080 // potential candidate for the reduction. 7081 unsigned LeafOpcode = 0; 7082 7083 // Post order traverse the reduction tree starting at B. We only handle true 7084 // trees containing only binary operators. 7085 SmallVector<std::pair<Instruction *, unsigned>, 32> Stack; 7086 Stack.push_back(std::make_pair(B, getFirstOperandIndex(B))); 7087 initReductionOps(B); 7088 while (!Stack.empty()) { 7089 Instruction *TreeN = Stack.back().first; 7090 unsigned EdgeToVisit = Stack.back().second++; 7091 const RecurKind TreeRdxKind = getRdxKind(TreeN); 7092 bool IsReducedValue = TreeRdxKind != RdxKind; 7093 7094 // Postorder visit. 7095 if (IsReducedValue || EdgeToVisit == getNumberOfOperands(TreeN)) { 7096 if (IsReducedValue) 7097 ReducedVals.push_back(TreeN); 7098 else { 7099 auto ExtraArgsIter = ExtraArgs.find(TreeN); 7100 if (ExtraArgsIter != ExtraArgs.end() && !ExtraArgsIter->second) { 7101 // Check if TreeN is an extra argument of its parent operation. 7102 if (Stack.size() <= 1) { 7103 // TreeN can't be an extra argument as it is a root reduction 7104 // operation. 7105 return false; 7106 } 7107 // Yes, TreeN is an extra argument, do not add it to a list of 7108 // reduction operations. 7109 // Stack[Stack.size() - 2] always points to the parent operation. 7110 markExtraArg(Stack[Stack.size() - 2], TreeN); 7111 ExtraArgs.erase(TreeN); 7112 } else 7113 addReductionOps(TreeN); 7114 } 7115 // Retract. 7116 Stack.pop_back(); 7117 continue; 7118 } 7119 7120 // Visit left or right. 7121 Value *EdgeVal = TreeN->getOperand(EdgeToVisit); 7122 auto *EdgeInst = dyn_cast<Instruction>(EdgeVal); 7123 if (!EdgeInst) { 7124 // Edge value is not a reduction instruction or a leaf instruction. 7125 // (It may be a constant, function argument, or something else.) 7126 markExtraArg(Stack.back(), EdgeVal); 7127 continue; 7128 } 7129 RecurKind EdgeRdxKind = getRdxKind(EdgeInst); 7130 // Continue analysis if the next operand is a reduction operation or 7131 // (possibly) a leaf value. If the leaf value opcode is not set, 7132 // the first met operation != reduction operation is considered as the 7133 // leaf opcode. 7134 // Only handle trees in the current basic block. 7135 // Each tree node needs to have minimal number of users except for the 7136 // ultimate reduction. 7137 const bool IsRdxInst = EdgeRdxKind == RdxKind; 7138 if (EdgeInst != Phi && EdgeInst != B && 7139 hasSameParent(EdgeInst, B->getParent(), IsRdxInst) && 7140 hasRequiredNumberOfUses(isa<SelectInst>(B), EdgeInst) && 7141 (!LeafOpcode || LeafOpcode == EdgeInst->getOpcode() || IsRdxInst)) { 7142 if (IsRdxInst) { 7143 // We need to be able to reassociate the reduction operations. 7144 if (!isVectorizable(EdgeRdxKind, EdgeInst)) { 7145 // I is an extra argument for TreeN (its parent operation). 7146 markExtraArg(Stack.back(), EdgeInst); 7147 continue; 7148 } 7149 } else if (!LeafOpcode) { 7150 LeafOpcode = EdgeInst->getOpcode(); 7151 } 7152 Stack.push_back( 7153 std::make_pair(EdgeInst, getFirstOperandIndex(EdgeInst))); 7154 continue; 7155 } 7156 // I is an extra argument for TreeN (its parent operation). 7157 markExtraArg(Stack.back(), EdgeInst); 7158 } 7159 return true; 7160 } 7161 7162 /// Attempt to vectorize the tree found by matchAssociativeReduction. 7163 bool tryToReduce(BoUpSLP &V, TargetTransformInfo *TTI) { 7164 // If there are a sufficient number of reduction values, reduce 7165 // to a nearby power-of-2. We can safely generate oversized 7166 // vectors and rely on the backend to split them to legal sizes. 7167 unsigned NumReducedVals = ReducedVals.size(); 7168 if (NumReducedVals < 4) 7169 return false; 7170 7171 // Intersect the fast-math-flags from all reduction operations. 7172 FastMathFlags RdxFMF; 7173 RdxFMF.set(); 7174 for (ReductionOpsType &RdxOp : ReductionOps) { 7175 for (Value *RdxVal : RdxOp) { 7176 if (auto *FPMO = dyn_cast<FPMathOperator>(RdxVal)) 7177 RdxFMF &= FPMO->getFastMathFlags(); 7178 } 7179 } 7180 7181 IRBuilder<> Builder(cast<Instruction>(ReductionRoot)); 7182 Builder.setFastMathFlags(RdxFMF); 7183 7184 BoUpSLP::ExtraValueToDebugLocsMap ExternallyUsedValues; 7185 // The same extra argument may be used several times, so log each attempt 7186 // to use it. 7187 for (const std::pair<Instruction *, Value *> &Pair : ExtraArgs) { 7188 assert(Pair.first && "DebugLoc must be set."); 7189 ExternallyUsedValues[Pair.second].push_back(Pair.first); 7190 } 7191 7192 // The compare instruction of a min/max is the insertion point for new 7193 // instructions and may be replaced with a new compare instruction. 7194 auto getCmpForMinMaxReduction = [](Instruction *RdxRootInst) { 7195 assert(isa<SelectInst>(RdxRootInst) && 7196 "Expected min/max reduction to have select root instruction"); 7197 Value *ScalarCond = cast<SelectInst>(RdxRootInst)->getCondition(); 7198 assert(isa<Instruction>(ScalarCond) && 7199 "Expected min/max reduction to have compare condition"); 7200 return cast<Instruction>(ScalarCond); 7201 }; 7202 7203 // The reduction root is used as the insertion point for new instructions, 7204 // so set it as externally used to prevent it from being deleted. 7205 ExternallyUsedValues[ReductionRoot]; 7206 SmallVector<Value *, 16> IgnoreList; 7207 for (ReductionOpsType &RdxOp : ReductionOps) 7208 IgnoreList.append(RdxOp.begin(), RdxOp.end()); 7209 7210 unsigned ReduxWidth = PowerOf2Floor(NumReducedVals); 7211 if (NumReducedVals > ReduxWidth) { 7212 // In the loop below, we are building a tree based on a window of 7213 // 'ReduxWidth' values. 7214 // If the operands of those values have common traits (compare predicate, 7215 // constant operand, etc), then we want to group those together to 7216 // minimize the cost of the reduction. 7217 7218 // TODO: This should be extended to count common operands for 7219 // compares and binops. 7220 7221 // Step 1: Count the number of times each compare predicate occurs. 7222 SmallDenseMap<unsigned, unsigned> PredCountMap; 7223 for (Value *RdxVal : ReducedVals) { 7224 CmpInst::Predicate Pred; 7225 if (match(RdxVal, m_Cmp(Pred, m_Value(), m_Value()))) 7226 ++PredCountMap[Pred]; 7227 } 7228 // Step 2: Sort the values so the most common predicates come first. 7229 stable_sort(ReducedVals, [&PredCountMap](Value *A, Value *B) { 7230 CmpInst::Predicate PredA, PredB; 7231 if (match(A, m_Cmp(PredA, m_Value(), m_Value())) && 7232 match(B, m_Cmp(PredB, m_Value(), m_Value()))) { 7233 return PredCountMap[PredA] > PredCountMap[PredB]; 7234 } 7235 return false; 7236 }); 7237 } 7238 7239 Value *VectorizedTree = nullptr; 7240 unsigned i = 0; 7241 while (i < NumReducedVals - ReduxWidth + 1 && ReduxWidth > 2) { 7242 ArrayRef<Value *> VL(&ReducedVals[i], ReduxWidth); 7243 V.buildTree(VL, ExternallyUsedValues, IgnoreList); 7244 Optional<ArrayRef<unsigned>> Order = V.bestOrder(); 7245 if (Order) { 7246 assert(Order->size() == VL.size() && 7247 "Order size must be the same as number of vectorized " 7248 "instructions."); 7249 // TODO: reorder tree nodes without tree rebuilding. 7250 SmallVector<Value *, 4> ReorderedOps(VL.size()); 7251 llvm::transform(*Order, ReorderedOps.begin(), 7252 [VL](const unsigned Idx) { return VL[Idx]; }); 7253 V.buildTree(ReorderedOps, ExternallyUsedValues, IgnoreList); 7254 } 7255 if (V.isTreeTinyAndNotFullyVectorizable()) 7256 break; 7257 if (V.isLoadCombineReductionCandidate(RdxKind)) 7258 break; 7259 7260 V.computeMinimumValueSizes(); 7261 7262 // Estimate cost. 7263 InstructionCost TreeCost = V.getTreeCost(); 7264 InstructionCost ReductionCost = 7265 getReductionCost(TTI, ReducedVals[i], ReduxWidth); 7266 InstructionCost Cost = TreeCost + ReductionCost; 7267 if (!Cost.isValid()) { 7268 LLVM_DEBUG(dbgs() << "Encountered invalid baseline cost.\n"); 7269 return false; 7270 } 7271 if (Cost >= -SLPCostThreshold) { 7272 V.getORE()->emit([&]() { 7273 return OptimizationRemarkMissed(SV_NAME, "HorSLPNotBeneficial", 7274 cast<Instruction>(VL[0])) 7275 << "Vectorizing horizontal reduction is possible" 7276 << "but not beneficial with cost " << ore::NV("Cost", Cost) 7277 << " and threshold " 7278 << ore::NV("Threshold", -SLPCostThreshold); 7279 }); 7280 break; 7281 } 7282 7283 LLVM_DEBUG(dbgs() << "SLP: Vectorizing horizontal reduction at cost:" 7284 << Cost << ". (HorRdx)\n"); 7285 V.getORE()->emit([&]() { 7286 return OptimizationRemark(SV_NAME, "VectorizedHorizontalReduction", 7287 cast<Instruction>(VL[0])) 7288 << "Vectorized horizontal reduction with cost " 7289 << ore::NV("Cost", Cost) << " and with tree size " 7290 << ore::NV("TreeSize", V.getTreeSize()); 7291 }); 7292 7293 // Vectorize a tree. 7294 DebugLoc Loc = cast<Instruction>(ReducedVals[i])->getDebugLoc(); 7295 Value *VectorizedRoot = V.vectorizeTree(ExternallyUsedValues); 7296 7297 // Emit a reduction. If the root is a select (min/max idiom), the insert 7298 // point is the compare condition of that select. 7299 Instruction *RdxRootInst = cast<Instruction>(ReductionRoot); 7300 if (isa<SelectInst>(RdxRootInst)) 7301 Builder.SetInsertPoint(getCmpForMinMaxReduction(RdxRootInst)); 7302 else 7303 Builder.SetInsertPoint(RdxRootInst); 7304 7305 Value *ReducedSubTree = 7306 emitReduction(VectorizedRoot, Builder, ReduxWidth, TTI); 7307 7308 if (!VectorizedTree) { 7309 // Initialize the final value in the reduction. 7310 VectorizedTree = ReducedSubTree; 7311 } else { 7312 // Update the final value in the reduction. 7313 Builder.SetCurrentDebugLocation(Loc); 7314 VectorizedTree = createOp(Builder, RdxKind, VectorizedTree, 7315 ReducedSubTree, "op.rdx", ReductionOps); 7316 } 7317 i += ReduxWidth; 7318 ReduxWidth = PowerOf2Floor(NumReducedVals - i); 7319 } 7320 7321 if (VectorizedTree) { 7322 // Finish the reduction. 7323 for (; i < NumReducedVals; ++i) { 7324 auto *I = cast<Instruction>(ReducedVals[i]); 7325 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 7326 VectorizedTree = 7327 createOp(Builder, RdxKind, VectorizedTree, I, "", ReductionOps); 7328 } 7329 for (auto &Pair : ExternallyUsedValues) { 7330 // Add each externally used value to the final reduction. 7331 for (auto *I : Pair.second) { 7332 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 7333 VectorizedTree = createOp(Builder, RdxKind, VectorizedTree, 7334 Pair.first, "op.extra", I); 7335 } 7336 } 7337 7338 ReductionRoot->replaceAllUsesWith(VectorizedTree); 7339 7340 // Mark all scalar reduction ops for deletion, they are replaced by the 7341 // vector reductions. 7342 V.eraseInstructions(IgnoreList); 7343 } 7344 return VectorizedTree != nullptr; 7345 } 7346 7347 unsigned numReductionValues() const { return ReducedVals.size(); } 7348 7349 private: 7350 /// Calculate the cost of a reduction. 7351 InstructionCost getReductionCost(TargetTransformInfo *TTI, 7352 Value *FirstReducedVal, 7353 unsigned ReduxWidth) { 7354 Type *ScalarTy = FirstReducedVal->getType(); 7355 FixedVectorType *VectorTy = FixedVectorType::get(ScalarTy, ReduxWidth); 7356 InstructionCost VectorCost, ScalarCost; 7357 switch (RdxKind) { 7358 case RecurKind::Add: 7359 case RecurKind::Mul: 7360 case RecurKind::Or: 7361 case RecurKind::And: 7362 case RecurKind::Xor: 7363 case RecurKind::FAdd: 7364 case RecurKind::FMul: { 7365 unsigned RdxOpcode = RecurrenceDescriptor::getOpcode(RdxKind); 7366 VectorCost = TTI->getArithmeticReductionCost(RdxOpcode, VectorTy, 7367 /*IsPairwiseForm=*/false); 7368 ScalarCost = TTI->getArithmeticInstrCost(RdxOpcode, ScalarTy); 7369 break; 7370 } 7371 case RecurKind::FMax: 7372 case RecurKind::FMin: { 7373 auto *VecCondTy = cast<VectorType>(CmpInst::makeCmpResultType(VectorTy)); 7374 VectorCost = 7375 TTI->getMinMaxReductionCost(VectorTy, VecCondTy, 7376 /*pairwise=*/false, /*unsigned=*/false); 7377 ScalarCost = 7378 TTI->getCmpSelInstrCost(Instruction::FCmp, ScalarTy) + 7379 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 7380 CmpInst::makeCmpResultType(ScalarTy)); 7381 break; 7382 } 7383 case RecurKind::SMax: 7384 case RecurKind::SMin: 7385 case RecurKind::UMax: 7386 case RecurKind::UMin: { 7387 auto *VecCondTy = cast<VectorType>(CmpInst::makeCmpResultType(VectorTy)); 7388 bool IsUnsigned = 7389 RdxKind == RecurKind::UMax || RdxKind == RecurKind::UMin; 7390 VectorCost = 7391 TTI->getMinMaxReductionCost(VectorTy, VecCondTy, 7392 /*IsPairwiseForm=*/false, IsUnsigned); 7393 ScalarCost = 7394 TTI->getCmpSelInstrCost(Instruction::ICmp, ScalarTy) + 7395 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 7396 CmpInst::makeCmpResultType(ScalarTy)); 7397 break; 7398 } 7399 default: 7400 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 7401 } 7402 7403 // Scalar cost is repeated for N-1 elements. 7404 ScalarCost *= (ReduxWidth - 1); 7405 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << VectorCost - ScalarCost 7406 << " for reduction that starts with " << *FirstReducedVal 7407 << " (It is a splitting reduction)\n"); 7408 return VectorCost - ScalarCost; 7409 } 7410 7411 /// Emit a horizontal reduction of the vectorized value. 7412 Value *emitReduction(Value *VectorizedValue, IRBuilder<> &Builder, 7413 unsigned ReduxWidth, const TargetTransformInfo *TTI) { 7414 assert(VectorizedValue && "Need to have a vectorized tree node"); 7415 assert(isPowerOf2_32(ReduxWidth) && 7416 "We only handle power-of-two reductions for now"); 7417 7418 return createSimpleTargetReduction(Builder, TTI, VectorizedValue, RdxKind, 7419 ReductionOps.back()); 7420 } 7421 }; 7422 7423 } // end anonymous namespace 7424 7425 static Optional<unsigned> getAggregateSize(Instruction *InsertInst) { 7426 if (auto *IE = dyn_cast<InsertElementInst>(InsertInst)) 7427 return cast<FixedVectorType>(IE->getType())->getNumElements(); 7428 7429 unsigned AggregateSize = 1; 7430 auto *IV = cast<InsertValueInst>(InsertInst); 7431 Type *CurrentType = IV->getType(); 7432 do { 7433 if (auto *ST = dyn_cast<StructType>(CurrentType)) { 7434 for (auto *Elt : ST->elements()) 7435 if (Elt != ST->getElementType(0)) // check homogeneity 7436 return None; 7437 AggregateSize *= ST->getNumElements(); 7438 CurrentType = ST->getElementType(0); 7439 } else if (auto *AT = dyn_cast<ArrayType>(CurrentType)) { 7440 AggregateSize *= AT->getNumElements(); 7441 CurrentType = AT->getElementType(); 7442 } else if (auto *VT = dyn_cast<FixedVectorType>(CurrentType)) { 7443 AggregateSize *= VT->getNumElements(); 7444 return AggregateSize; 7445 } else if (CurrentType->isSingleValueType()) { 7446 return AggregateSize; 7447 } else { 7448 return None; 7449 } 7450 } while (true); 7451 } 7452 7453 static Optional<unsigned> getOperandIndex(Instruction *InsertInst, 7454 unsigned OperandOffset) { 7455 unsigned OperandIndex = OperandOffset; 7456 if (auto *IE = dyn_cast<InsertElementInst>(InsertInst)) { 7457 if (auto *CI = dyn_cast<ConstantInt>(IE->getOperand(2))) { 7458 auto *VT = cast<FixedVectorType>(IE->getType()); 7459 OperandIndex *= VT->getNumElements(); 7460 OperandIndex += CI->getZExtValue(); 7461 return OperandIndex; 7462 } 7463 return None; 7464 } 7465 7466 auto *IV = cast<InsertValueInst>(InsertInst); 7467 Type *CurrentType = IV->getType(); 7468 for (unsigned int Index : IV->indices()) { 7469 if (auto *ST = dyn_cast<StructType>(CurrentType)) { 7470 OperandIndex *= ST->getNumElements(); 7471 CurrentType = ST->getElementType(Index); 7472 } else if (auto *AT = dyn_cast<ArrayType>(CurrentType)) { 7473 OperandIndex *= AT->getNumElements(); 7474 CurrentType = AT->getElementType(); 7475 } else { 7476 return None; 7477 } 7478 OperandIndex += Index; 7479 } 7480 return OperandIndex; 7481 } 7482 7483 static bool findBuildAggregate_rec(Instruction *LastInsertInst, 7484 TargetTransformInfo *TTI, 7485 SmallVectorImpl<Value *> &BuildVectorOpds, 7486 SmallVectorImpl<Value *> &InsertElts, 7487 unsigned OperandOffset) { 7488 do { 7489 Value *InsertedOperand = LastInsertInst->getOperand(1); 7490 Optional<unsigned> OperandIndex = 7491 getOperandIndex(LastInsertInst, OperandOffset); 7492 if (!OperandIndex) 7493 return false; 7494 if (isa<InsertElementInst>(InsertedOperand) || 7495 isa<InsertValueInst>(InsertedOperand)) { 7496 if (!findBuildAggregate_rec(cast<Instruction>(InsertedOperand), TTI, 7497 BuildVectorOpds, InsertElts, *OperandIndex)) 7498 return false; 7499 } else { 7500 BuildVectorOpds[*OperandIndex] = InsertedOperand; 7501 InsertElts[*OperandIndex] = LastInsertInst; 7502 } 7503 if (isa<UndefValue>(LastInsertInst->getOperand(0))) 7504 return true; 7505 LastInsertInst = dyn_cast<Instruction>(LastInsertInst->getOperand(0)); 7506 } while (LastInsertInst != nullptr && 7507 (isa<InsertValueInst>(LastInsertInst) || 7508 isa<InsertElementInst>(LastInsertInst)) && 7509 LastInsertInst->hasOneUse()); 7510 return false; 7511 } 7512 7513 /// Recognize construction of vectors like 7514 /// %ra = insertelement <4 x float> poison, float %s0, i32 0 7515 /// %rb = insertelement <4 x float> %ra, float %s1, i32 1 7516 /// %rc = insertelement <4 x float> %rb, float %s2, i32 2 7517 /// %rd = insertelement <4 x float> %rc, float %s3, i32 3 7518 /// starting from the last insertelement or insertvalue instruction. 7519 /// 7520 /// Also recognize homogeneous aggregates like {<2 x float>, <2 x float>}, 7521 /// {{float, float}, {float, float}}, [2 x {float, float}] and so on. 7522 /// See llvm/test/Transforms/SLPVectorizer/X86/pr42022.ll for examples. 7523 /// 7524 /// Assume LastInsertInst is of InsertElementInst or InsertValueInst type. 7525 /// 7526 /// \return true if it matches. 7527 static bool findBuildAggregate(Instruction *LastInsertInst, 7528 TargetTransformInfo *TTI, 7529 SmallVectorImpl<Value *> &BuildVectorOpds, 7530 SmallVectorImpl<Value *> &InsertElts) { 7531 7532 assert((isa<InsertElementInst>(LastInsertInst) || 7533 isa<InsertValueInst>(LastInsertInst)) && 7534 "Expected insertelement or insertvalue instruction!"); 7535 7536 assert((BuildVectorOpds.empty() && InsertElts.empty()) && 7537 "Expected empty result vectors!"); 7538 7539 Optional<unsigned> AggregateSize = getAggregateSize(LastInsertInst); 7540 if (!AggregateSize) 7541 return false; 7542 BuildVectorOpds.resize(*AggregateSize); 7543 InsertElts.resize(*AggregateSize); 7544 7545 if (findBuildAggregate_rec(LastInsertInst, TTI, BuildVectorOpds, InsertElts, 7546 0)) { 7547 llvm::erase_value(BuildVectorOpds, nullptr); 7548 llvm::erase_value(InsertElts, nullptr); 7549 if (BuildVectorOpds.size() >= 2) 7550 return true; 7551 } 7552 7553 return false; 7554 } 7555 7556 static bool PhiTypeSorterFunc(Value *V, Value *V2) { 7557 return V->getType() < V2->getType(); 7558 } 7559 7560 /// Try and get a reduction value from a phi node. 7561 /// 7562 /// Given a phi node \p P in a block \p ParentBB, consider possible reductions 7563 /// if they come from either \p ParentBB or a containing loop latch. 7564 /// 7565 /// \returns A candidate reduction value if possible, or \code nullptr \endcode 7566 /// if not possible. 7567 static Value *getReductionValue(const DominatorTree *DT, PHINode *P, 7568 BasicBlock *ParentBB, LoopInfo *LI) { 7569 // There are situations where the reduction value is not dominated by the 7570 // reduction phi. Vectorizing such cases has been reported to cause 7571 // miscompiles. See PR25787. 7572 auto DominatedReduxValue = [&](Value *R) { 7573 return isa<Instruction>(R) && 7574 DT->dominates(P->getParent(), cast<Instruction>(R)->getParent()); 7575 }; 7576 7577 Value *Rdx = nullptr; 7578 7579 // Return the incoming value if it comes from the same BB as the phi node. 7580 if (P->getIncomingBlock(0) == ParentBB) { 7581 Rdx = P->getIncomingValue(0); 7582 } else if (P->getIncomingBlock(1) == ParentBB) { 7583 Rdx = P->getIncomingValue(1); 7584 } 7585 7586 if (Rdx && DominatedReduxValue(Rdx)) 7587 return Rdx; 7588 7589 // Otherwise, check whether we have a loop latch to look at. 7590 Loop *BBL = LI->getLoopFor(ParentBB); 7591 if (!BBL) 7592 return nullptr; 7593 BasicBlock *BBLatch = BBL->getLoopLatch(); 7594 if (!BBLatch) 7595 return nullptr; 7596 7597 // There is a loop latch, return the incoming value if it comes from 7598 // that. This reduction pattern occasionally turns up. 7599 if (P->getIncomingBlock(0) == BBLatch) { 7600 Rdx = P->getIncomingValue(0); 7601 } else if (P->getIncomingBlock(1) == BBLatch) { 7602 Rdx = P->getIncomingValue(1); 7603 } 7604 7605 if (Rdx && DominatedReduxValue(Rdx)) 7606 return Rdx; 7607 7608 return nullptr; 7609 } 7610 7611 static bool matchRdxBop(Instruction *I, Value *&V0, Value *&V1) { 7612 if (match(I, m_BinOp(m_Value(V0), m_Value(V1)))) 7613 return true; 7614 if (match(I, m_Intrinsic<Intrinsic::maxnum>(m_Value(V0), m_Value(V1)))) 7615 return true; 7616 if (match(I, m_Intrinsic<Intrinsic::minnum>(m_Value(V0), m_Value(V1)))) 7617 return true; 7618 if (match(I, m_Intrinsic<Intrinsic::smax>(m_Value(V0), m_Value(V1)))) 7619 return true; 7620 if (match(I, m_Intrinsic<Intrinsic::smin>(m_Value(V0), m_Value(V1)))) 7621 return true; 7622 if (match(I, m_Intrinsic<Intrinsic::umax>(m_Value(V0), m_Value(V1)))) 7623 return true; 7624 if (match(I, m_Intrinsic<Intrinsic::umin>(m_Value(V0), m_Value(V1)))) 7625 return true; 7626 return false; 7627 } 7628 7629 /// Attempt to reduce a horizontal reduction. 7630 /// If it is legal to match a horizontal reduction feeding the phi node \a P 7631 /// with reduction operators \a Root (or one of its operands) in a basic block 7632 /// \a BB, then check if it can be done. If horizontal reduction is not found 7633 /// and root instruction is a binary operation, vectorization of the operands is 7634 /// attempted. 7635 /// \returns true if a horizontal reduction was matched and reduced or operands 7636 /// of one of the binary instruction were vectorized. 7637 /// \returns false if a horizontal reduction was not matched (or not possible) 7638 /// or no vectorization of any binary operation feeding \a Root instruction was 7639 /// performed. 7640 static bool tryToVectorizeHorReductionOrInstOperands( 7641 PHINode *P, Instruction *Root, BasicBlock *BB, BoUpSLP &R, 7642 TargetTransformInfo *TTI, 7643 const function_ref<bool(Instruction *, BoUpSLP &)> Vectorize) { 7644 if (!ShouldVectorizeHor) 7645 return false; 7646 7647 if (!Root) 7648 return false; 7649 7650 if (Root->getParent() != BB || isa<PHINode>(Root)) 7651 return false; 7652 // Start analysis starting from Root instruction. If horizontal reduction is 7653 // found, try to vectorize it. If it is not a horizontal reduction or 7654 // vectorization is not possible or not effective, and currently analyzed 7655 // instruction is a binary operation, try to vectorize the operands, using 7656 // pre-order DFS traversal order. If the operands were not vectorized, repeat 7657 // the same procedure considering each operand as a possible root of the 7658 // horizontal reduction. 7659 // Interrupt the process if the Root instruction itself was vectorized or all 7660 // sub-trees not higher that RecursionMaxDepth were analyzed/vectorized. 7661 // Skip the analysis of CmpInsts.Compiler implements postanalysis of the 7662 // CmpInsts so we can skip extra attempts in 7663 // tryToVectorizeHorReductionOrInstOperands and save compile time. 7664 SmallVector<std::pair<Instruction *, unsigned>, 8> Stack(1, {Root, 0}); 7665 SmallPtrSet<Value *, 8> VisitedInstrs; 7666 bool Res = false; 7667 while (!Stack.empty()) { 7668 Instruction *Inst; 7669 unsigned Level; 7670 std::tie(Inst, Level) = Stack.pop_back_val(); 7671 Value *B0, *B1; 7672 bool IsBinop = matchRdxBop(Inst, B0, B1); 7673 bool IsSelect = match(Inst, m_Select(m_Value(), m_Value(), m_Value())); 7674 if (IsBinop || IsSelect) { 7675 HorizontalReduction HorRdx; 7676 if (HorRdx.matchAssociativeReduction(P, Inst)) { 7677 if (HorRdx.tryToReduce(R, TTI)) { 7678 Res = true; 7679 // Set P to nullptr to avoid re-analysis of phi node in 7680 // matchAssociativeReduction function unless this is the root node. 7681 P = nullptr; 7682 continue; 7683 } 7684 } 7685 if (P && IsBinop) { 7686 Inst = dyn_cast<Instruction>(B0); 7687 if (Inst == P) 7688 Inst = dyn_cast<Instruction>(B1); 7689 if (!Inst) { 7690 // Set P to nullptr to avoid re-analysis of phi node in 7691 // matchAssociativeReduction function unless this is the root node. 7692 P = nullptr; 7693 continue; 7694 } 7695 } 7696 } 7697 // Set P to nullptr to avoid re-analysis of phi node in 7698 // matchAssociativeReduction function unless this is the root node. 7699 P = nullptr; 7700 // Do not try to vectorize CmpInst operands, this is done separately. 7701 if (!isa<CmpInst>(Inst) && Vectorize(Inst, R)) { 7702 Res = true; 7703 continue; 7704 } 7705 7706 // Try to vectorize operands. 7707 // Continue analysis for the instruction from the same basic block only to 7708 // save compile time. 7709 if (++Level < RecursionMaxDepth) 7710 for (auto *Op : Inst->operand_values()) 7711 if (VisitedInstrs.insert(Op).second) 7712 if (auto *I = dyn_cast<Instruction>(Op)) 7713 // Do not try to vectorize CmpInst operands, this is done 7714 // separately. 7715 if (!isa<PHINode>(I) && !isa<CmpInst>(I) && !R.isDeleted(I) && 7716 I->getParent() == BB) 7717 Stack.emplace_back(I, Level); 7718 } 7719 return Res; 7720 } 7721 7722 bool SLPVectorizerPass::vectorizeRootInstruction(PHINode *P, Value *V, 7723 BasicBlock *BB, BoUpSLP &R, 7724 TargetTransformInfo *TTI) { 7725 auto *I = dyn_cast_or_null<Instruction>(V); 7726 if (!I) 7727 return false; 7728 7729 if (!isa<BinaryOperator>(I)) 7730 P = nullptr; 7731 // Try to match and vectorize a horizontal reduction. 7732 auto &&ExtraVectorization = [this](Instruction *I, BoUpSLP &R) -> bool { 7733 return tryToVectorize(I, R); 7734 }; 7735 return tryToVectorizeHorReductionOrInstOperands(P, I, BB, R, TTI, 7736 ExtraVectorization); 7737 } 7738 7739 bool SLPVectorizerPass::vectorizeInsertValueInst(InsertValueInst *IVI, 7740 BasicBlock *BB, BoUpSLP &R) { 7741 const DataLayout &DL = BB->getModule()->getDataLayout(); 7742 if (!R.canMapToVector(IVI->getType(), DL)) 7743 return false; 7744 7745 SmallVector<Value *, 16> BuildVectorOpds; 7746 SmallVector<Value *, 16> BuildVectorInsts; 7747 if (!findBuildAggregate(IVI, TTI, BuildVectorOpds, BuildVectorInsts)) 7748 return false; 7749 7750 LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IVI << "\n"); 7751 // Aggregate value is unlikely to be processed in vector register, we need to 7752 // extract scalars into scalar registers, so NeedExtraction is set true. 7753 return tryToVectorizeList(BuildVectorOpds, R, /*AllowReorder=*/false, 7754 BuildVectorInsts); 7755 } 7756 7757 bool SLPVectorizerPass::vectorizeInsertElementInst(InsertElementInst *IEI, 7758 BasicBlock *BB, BoUpSLP &R) { 7759 SmallVector<Value *, 16> BuildVectorInsts; 7760 SmallVector<Value *, 16> BuildVectorOpds; 7761 SmallVector<int> Mask; 7762 if (!findBuildAggregate(IEI, TTI, BuildVectorOpds, BuildVectorInsts) || 7763 (llvm::all_of(BuildVectorOpds, 7764 [](Value *V) { return isa<ExtractElementInst>(V); }) && 7765 isShuffle(BuildVectorOpds, Mask))) 7766 return false; 7767 7768 // Vectorize starting with the build vector operands ignoring the BuildVector 7769 // instructions for the purpose of scheduling and user extraction. 7770 return tryToVectorizeList(BuildVectorOpds, R, /*AllowReorder=*/false, 7771 BuildVectorInsts); 7772 } 7773 7774 bool SLPVectorizerPass::vectorizeSimpleInstructions( 7775 SmallVectorImpl<Instruction *> &Instructions, BasicBlock *BB, BoUpSLP &R, 7776 bool AtTerminator) { 7777 bool OpsChanged = false; 7778 SmallVector<Instruction *, 4> PostponedCmps; 7779 for (auto *I : reverse(Instructions)) { 7780 if (R.isDeleted(I)) 7781 continue; 7782 if (auto *LastInsertValue = dyn_cast<InsertValueInst>(I)) 7783 OpsChanged |= vectorizeInsertValueInst(LastInsertValue, BB, R); 7784 else if (auto *LastInsertElem = dyn_cast<InsertElementInst>(I)) 7785 OpsChanged |= vectorizeInsertElementInst(LastInsertElem, BB, R); 7786 else if (isa<CmpInst>(I)) 7787 PostponedCmps.push_back(I); 7788 } 7789 if (AtTerminator) { 7790 // Try to find reductions first. 7791 for (Instruction *I : PostponedCmps) { 7792 if (R.isDeleted(I)) 7793 continue; 7794 for (Value *Op : I->operands()) 7795 OpsChanged |= vectorizeRootInstruction(nullptr, Op, BB, R, TTI); 7796 } 7797 // Try to vectorize operands as vector bundles. 7798 for (Instruction *I : PostponedCmps) { 7799 if (R.isDeleted(I)) 7800 continue; 7801 OpsChanged |= tryToVectorize(I, R); 7802 } 7803 Instructions.clear(); 7804 } else { 7805 // Insert in reverse order since the PostponedCmps vector was filled in 7806 // reverse order. 7807 Instructions.assign(PostponedCmps.rbegin(), PostponedCmps.rend()); 7808 } 7809 return OpsChanged; 7810 } 7811 7812 bool SLPVectorizerPass::vectorizeChainsInBlock(BasicBlock *BB, BoUpSLP &R) { 7813 bool Changed = false; 7814 SmallVector<Value *, 4> Incoming; 7815 SmallPtrSet<Value *, 16> VisitedInstrs; 7816 7817 bool HaveVectorizedPhiNodes = true; 7818 while (HaveVectorizedPhiNodes) { 7819 HaveVectorizedPhiNodes = false; 7820 7821 // Collect the incoming values from the PHIs. 7822 Incoming.clear(); 7823 for (Instruction &I : *BB) { 7824 PHINode *P = dyn_cast<PHINode>(&I); 7825 if (!P) 7826 break; 7827 7828 if (!VisitedInstrs.count(P) && !R.isDeleted(P)) 7829 Incoming.push_back(P); 7830 } 7831 7832 // Sort by type. 7833 llvm::stable_sort(Incoming, PhiTypeSorterFunc); 7834 7835 // Try to vectorize elements base on their type. 7836 for (SmallVector<Value *, 4>::iterator IncIt = Incoming.begin(), 7837 E = Incoming.end(); 7838 IncIt != E;) { 7839 7840 // Look for the next elements with the same type. 7841 SmallVector<Value *, 4>::iterator SameTypeIt = IncIt; 7842 while (SameTypeIt != E && 7843 (*SameTypeIt)->getType() == (*IncIt)->getType()) { 7844 VisitedInstrs.insert(*SameTypeIt); 7845 ++SameTypeIt; 7846 } 7847 7848 // Try to vectorize them. 7849 unsigned NumElts = (SameTypeIt - IncIt); 7850 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize starting at PHIs (" 7851 << NumElts << ")\n"); 7852 // The order in which the phi nodes appear in the program does not matter. 7853 // So allow tryToVectorizeList to reorder them if it is beneficial. This 7854 // is done when there are exactly two elements since tryToVectorizeList 7855 // asserts that there are only two values when AllowReorder is true. 7856 bool AllowReorder = NumElts == 2; 7857 if (NumElts > 1 && 7858 tryToVectorizeList(makeArrayRef(IncIt, NumElts), R, AllowReorder)) { 7859 // Success start over because instructions might have been changed. 7860 HaveVectorizedPhiNodes = true; 7861 Changed = true; 7862 break; 7863 } 7864 7865 // Start over at the next instruction of a different type (or the end). 7866 IncIt = SameTypeIt; 7867 } 7868 } 7869 7870 VisitedInstrs.clear(); 7871 7872 SmallVector<Instruction *, 8> PostProcessInstructions; 7873 SmallDenseSet<Instruction *, 4> KeyNodes; 7874 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 7875 // Skip instructions with scalable type. The num of elements is unknown at 7876 // compile-time for scalable type. 7877 if (isa<ScalableVectorType>(it->getType())) 7878 continue; 7879 7880 // Skip instructions marked for the deletion. 7881 if (R.isDeleted(&*it)) 7882 continue; 7883 // We may go through BB multiple times so skip the one we have checked. 7884 if (!VisitedInstrs.insert(&*it).second) { 7885 if (it->use_empty() && KeyNodes.contains(&*it) && 7886 vectorizeSimpleInstructions(PostProcessInstructions, BB, R, 7887 it->isTerminator())) { 7888 // We would like to start over since some instructions are deleted 7889 // and the iterator may become invalid value. 7890 Changed = true; 7891 it = BB->begin(); 7892 e = BB->end(); 7893 } 7894 continue; 7895 } 7896 7897 if (isa<DbgInfoIntrinsic>(it)) 7898 continue; 7899 7900 // Try to vectorize reductions that use PHINodes. 7901 if (PHINode *P = dyn_cast<PHINode>(it)) { 7902 // Check that the PHI is a reduction PHI. 7903 if (P->getNumIncomingValues() == 2) { 7904 // Try to match and vectorize a horizontal reduction. 7905 if (vectorizeRootInstruction(P, getReductionValue(DT, P, BB, LI), BB, R, 7906 TTI)) { 7907 Changed = true; 7908 it = BB->begin(); 7909 e = BB->end(); 7910 continue; 7911 } 7912 } 7913 // Try to vectorize the incoming values of the PHI, to catch reductions 7914 // that feed into PHIs. 7915 for (unsigned I = 0, E = P->getNumIncomingValues(); I != E; I++) { 7916 // Skip if the incoming block is the current BB for now. Also, bypass 7917 // unreachable IR for efficiency and to avoid crashing. 7918 // TODO: Collect the skipped incoming values and try to vectorize them 7919 // after processing BB. 7920 if (BB == P->getIncomingBlock(I) || 7921 !DT->isReachableFromEntry(P->getIncomingBlock(I))) 7922 continue; 7923 7924 Changed |= vectorizeRootInstruction(nullptr, P->getIncomingValue(I), 7925 P->getIncomingBlock(I), R, TTI); 7926 } 7927 continue; 7928 } 7929 7930 // Ran into an instruction without users, like terminator, or function call 7931 // with ignored return value, store. Ignore unused instructions (basing on 7932 // instruction type, except for CallInst and InvokeInst). 7933 if (it->use_empty() && (it->getType()->isVoidTy() || isa<CallInst>(it) || 7934 isa<InvokeInst>(it))) { 7935 KeyNodes.insert(&*it); 7936 bool OpsChanged = false; 7937 if (ShouldStartVectorizeHorAtStore || !isa<StoreInst>(it)) { 7938 for (auto *V : it->operand_values()) { 7939 // Try to match and vectorize a horizontal reduction. 7940 OpsChanged |= vectorizeRootInstruction(nullptr, V, BB, R, TTI); 7941 } 7942 } 7943 // Start vectorization of post-process list of instructions from the 7944 // top-tree instructions to try to vectorize as many instructions as 7945 // possible. 7946 OpsChanged |= vectorizeSimpleInstructions(PostProcessInstructions, BB, R, 7947 it->isTerminator()); 7948 if (OpsChanged) { 7949 // We would like to start over since some instructions are deleted 7950 // and the iterator may become invalid value. 7951 Changed = true; 7952 it = BB->begin(); 7953 e = BB->end(); 7954 continue; 7955 } 7956 } 7957 7958 if (isa<InsertElementInst>(it) || isa<CmpInst>(it) || 7959 isa<InsertValueInst>(it)) 7960 PostProcessInstructions.push_back(&*it); 7961 } 7962 7963 return Changed; 7964 } 7965 7966 bool SLPVectorizerPass::vectorizeGEPIndices(BasicBlock *BB, BoUpSLP &R) { 7967 auto Changed = false; 7968 for (auto &Entry : GEPs) { 7969 // If the getelementptr list has fewer than two elements, there's nothing 7970 // to do. 7971 if (Entry.second.size() < 2) 7972 continue; 7973 7974 LLVM_DEBUG(dbgs() << "SLP: Analyzing a getelementptr list of length " 7975 << Entry.second.size() << ".\n"); 7976 7977 // Process the GEP list in chunks suitable for the target's supported 7978 // vector size. If a vector register can't hold 1 element, we are done. We 7979 // are trying to vectorize the index computations, so the maximum number of 7980 // elements is based on the size of the index expression, rather than the 7981 // size of the GEP itself (the target's pointer size). 7982 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 7983 unsigned EltSize = R.getVectorElementSize(*Entry.second[0]->idx_begin()); 7984 if (MaxVecRegSize < EltSize) 7985 continue; 7986 7987 unsigned MaxElts = MaxVecRegSize / EltSize; 7988 for (unsigned BI = 0, BE = Entry.second.size(); BI < BE; BI += MaxElts) { 7989 auto Len = std::min<unsigned>(BE - BI, MaxElts); 7990 ArrayRef<GetElementPtrInst *> GEPList(&Entry.second[BI], Len); 7991 7992 // Initialize a set a candidate getelementptrs. Note that we use a 7993 // SetVector here to preserve program order. If the index computations 7994 // are vectorizable and begin with loads, we want to minimize the chance 7995 // of having to reorder them later. 7996 SetVector<Value *> Candidates(GEPList.begin(), GEPList.end()); 7997 7998 // Some of the candidates may have already been vectorized after we 7999 // initially collected them. If so, they are marked as deleted, so remove 8000 // them from the set of candidates. 8001 Candidates.remove_if( 8002 [&R](Value *I) { return R.isDeleted(cast<Instruction>(I)); }); 8003 8004 // Remove from the set of candidates all pairs of getelementptrs with 8005 // constant differences. Such getelementptrs are likely not good 8006 // candidates for vectorization in a bottom-up phase since one can be 8007 // computed from the other. We also ensure all candidate getelementptr 8008 // indices are unique. 8009 for (int I = 0, E = GEPList.size(); I < E && Candidates.size() > 1; ++I) { 8010 auto *GEPI = GEPList[I]; 8011 if (!Candidates.count(GEPI)) 8012 continue; 8013 auto *SCEVI = SE->getSCEV(GEPList[I]); 8014 for (int J = I + 1; J < E && Candidates.size() > 1; ++J) { 8015 auto *GEPJ = GEPList[J]; 8016 auto *SCEVJ = SE->getSCEV(GEPList[J]); 8017 if (isa<SCEVConstant>(SE->getMinusSCEV(SCEVI, SCEVJ))) { 8018 Candidates.remove(GEPI); 8019 Candidates.remove(GEPJ); 8020 } else if (GEPI->idx_begin()->get() == GEPJ->idx_begin()->get()) { 8021 Candidates.remove(GEPJ); 8022 } 8023 } 8024 } 8025 8026 // We break out of the above computation as soon as we know there are 8027 // fewer than two candidates remaining. 8028 if (Candidates.size() < 2) 8029 continue; 8030 8031 // Add the single, non-constant index of each candidate to the bundle. We 8032 // ensured the indices met these constraints when we originally collected 8033 // the getelementptrs. 8034 SmallVector<Value *, 16> Bundle(Candidates.size()); 8035 auto BundleIndex = 0u; 8036 for (auto *V : Candidates) { 8037 auto *GEP = cast<GetElementPtrInst>(V); 8038 auto *GEPIdx = GEP->idx_begin()->get(); 8039 assert(GEP->getNumIndices() == 1 || !isa<Constant>(GEPIdx)); 8040 Bundle[BundleIndex++] = GEPIdx; 8041 } 8042 8043 // Try and vectorize the indices. We are currently only interested in 8044 // gather-like cases of the form: 8045 // 8046 // ... = g[a[0] - b[0]] + g[a[1] - b[1]] + ... 8047 // 8048 // where the loads of "a", the loads of "b", and the subtractions can be 8049 // performed in parallel. It's likely that detecting this pattern in a 8050 // bottom-up phase will be simpler and less costly than building a 8051 // full-blown top-down phase beginning at the consecutive loads. 8052 Changed |= tryToVectorizeList(Bundle, R); 8053 } 8054 } 8055 return Changed; 8056 } 8057 8058 bool SLPVectorizerPass::vectorizeStoreChains(BoUpSLP &R) { 8059 bool Changed = false; 8060 // Attempt to sort and vectorize each of the store-groups. 8061 for (StoreListMap::iterator it = Stores.begin(), e = Stores.end(); it != e; 8062 ++it) { 8063 if (it->second.size() < 2) 8064 continue; 8065 8066 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " 8067 << it->second.size() << ".\n"); 8068 8069 Changed |= vectorizeStores(it->second, R); 8070 } 8071 return Changed; 8072 } 8073 8074 char SLPVectorizer::ID = 0; 8075 8076 static const char lv_name[] = "SLP Vectorizer"; 8077 8078 INITIALIZE_PASS_BEGIN(SLPVectorizer, SV_NAME, lv_name, false, false) 8079 INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass) 8080 INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass) 8081 INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker) 8082 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass) 8083 INITIALIZE_PASS_DEPENDENCY(LoopSimplify) 8084 INITIALIZE_PASS_DEPENDENCY(DemandedBitsWrapperPass) 8085 INITIALIZE_PASS_DEPENDENCY(OptimizationRemarkEmitterWrapperPass) 8086 INITIALIZE_PASS_DEPENDENCY(InjectTLIMappingsLegacy) 8087 INITIALIZE_PASS_END(SLPVectorizer, SV_NAME, lv_name, false, false) 8088 8089 Pass *llvm::createSLPVectorizerPass() { return new SLPVectorizer(); } 8090