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(const 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(const 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].empty() && "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(const 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(const 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 unsigned Idx = (Data.second / NumElts) * NumElts; 3594 unsigned EENumElts = EEVTy->getNumElements(); 3595 if (Idx + NumElts <= EENumElts) { 3596 Cost += 3597 TTIRef.getShuffleCost(TargetTransformInfo::SK_ExtractSubvector, 3598 EEVTy, None, Idx, VecTy); 3599 } else { 3600 // Need to round up the subvector type vectorization factor to avoid a 3601 // crash in cost model functions. Make SubVT so that Idx + VF of SubVT 3602 // <= EENumElts. 3603 auto *SubVT = 3604 FixedVectorType::get(VecTy->getElementType(), EENumElts - Idx); 3605 Cost += 3606 TTIRef.getShuffleCost(TargetTransformInfo::SK_ExtractSubvector, 3607 EEVTy, None, Idx, SubVT); 3608 } 3609 } else { 3610 Cost += TTIRef.getShuffleCost(TargetTransformInfo::SK_InsertSubvector, 3611 VecTy, None, 0, EEVTy); 3612 } 3613 } 3614 }; 3615 if (E->State == TreeEntry::NeedToGather) { 3616 if (allConstant(VL)) 3617 return 0; 3618 if (isSplat(VL)) { 3619 return ReuseShuffleCost + 3620 TTI->getShuffleCost(TargetTransformInfo::SK_Broadcast, VecTy, None, 3621 0); 3622 } 3623 if (E->getOpcode() == Instruction::ExtractElement && 3624 allSameType(VL) && allSameBlock(VL)) { 3625 SmallVector<int> Mask; 3626 Optional<TargetTransformInfo::ShuffleKind> ShuffleKind = 3627 isShuffle(VL, Mask); 3628 if (ShuffleKind.hasValue()) { 3629 InstructionCost Cost = 3630 computeExtractCost(VL, VecTy, *ShuffleKind, Mask, *TTI); 3631 AdjustExtractsCost(Cost, /*IsGather=*/true); 3632 return ReuseShuffleCost + Cost; 3633 } 3634 } 3635 InstructionCost GatherCost = 0; 3636 SmallVector<int> Mask; 3637 SmallVector<const TreeEntry *> Entries; 3638 Optional<TargetTransformInfo::ShuffleKind> Shuffle = 3639 isGatherShuffledEntry(E, Mask, Entries); 3640 if (Shuffle.hasValue()) { 3641 if (ShuffleVectorInst::isIdentityMask(Mask)) { 3642 LLVM_DEBUG( 3643 dbgs() 3644 << "SLP: perfect diamond match for gather bundle that starts with " 3645 << *VL.front() << ".\n"); 3646 } else { 3647 LLVM_DEBUG(dbgs() << "SLP: shuffled " << Entries.size() 3648 << " entries for bundle that starts with " 3649 << *VL.front() << ".\n"); 3650 GatherCost = TTI->getShuffleCost(*Shuffle, VecTy, Mask); 3651 } 3652 } else { 3653 GatherCost = getGatherCost(VL); 3654 } 3655 return ReuseShuffleCost + GatherCost; 3656 } 3657 assert((E->State == TreeEntry::Vectorize || 3658 E->State == TreeEntry::ScatterVectorize) && 3659 "Unhandled state"); 3660 assert(E->getOpcode() && allSameType(VL) && allSameBlock(VL) && "Invalid VL"); 3661 Instruction *VL0 = E->getMainOp(); 3662 unsigned ShuffleOrOp = 3663 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 3664 switch (ShuffleOrOp) { 3665 case Instruction::PHI: 3666 return 0; 3667 3668 case Instruction::ExtractValue: 3669 case Instruction::ExtractElement: { 3670 // The common cost of removal ExtractElement/ExtractValue instructions + 3671 // the cost of shuffles, if required to resuffle the original vector. 3672 InstructionCost CommonCost = 0; 3673 if (NeedToShuffleReuses) { 3674 unsigned Idx = 0; 3675 for (unsigned I : E->ReuseShuffleIndices) { 3676 if (ShuffleOrOp == Instruction::ExtractElement) { 3677 auto *EE = cast<ExtractElementInst>(VL[I]); 3678 ReuseShuffleCost -= TTI->getVectorInstrCost( 3679 Instruction::ExtractElement, EE->getVectorOperandType(), 3680 *getExtractIndex(EE)); 3681 } else { 3682 ReuseShuffleCost -= TTI->getVectorInstrCost( 3683 Instruction::ExtractElement, VecTy, Idx); 3684 ++Idx; 3685 } 3686 } 3687 Idx = ReuseShuffleNumbers; 3688 for (Value *V : VL) { 3689 if (ShuffleOrOp == Instruction::ExtractElement) { 3690 auto *EE = cast<ExtractElementInst>(V); 3691 ReuseShuffleCost += TTI->getVectorInstrCost( 3692 Instruction::ExtractElement, EE->getVectorOperandType(), 3693 *getExtractIndex(EE)); 3694 } else { 3695 --Idx; 3696 ReuseShuffleCost += TTI->getVectorInstrCost( 3697 Instruction::ExtractElement, VecTy, Idx); 3698 } 3699 } 3700 CommonCost = ReuseShuffleCost; 3701 } else if (!E->ReorderIndices.empty()) { 3702 SmallVector<int> NewMask; 3703 inversePermutation(E->ReorderIndices, NewMask); 3704 CommonCost = TTI->getShuffleCost( 3705 TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask); 3706 } 3707 if (ShuffleOrOp == Instruction::ExtractValue) { 3708 for (unsigned I = 0, E = VL.size(); I < E; ++I) { 3709 auto *EI = cast<Instruction>(VL[I]); 3710 // Take credit for instruction that will become dead. 3711 if (EI->hasOneUse()) { 3712 Instruction *Ext = EI->user_back(); 3713 if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) && 3714 all_of(Ext->users(), 3715 [](User *U) { return isa<GetElementPtrInst>(U); })) { 3716 // Use getExtractWithExtendCost() to calculate the cost of 3717 // extractelement/ext pair. 3718 CommonCost -= TTI->getExtractWithExtendCost( 3719 Ext->getOpcode(), Ext->getType(), VecTy, I); 3720 // Add back the cost of s|zext which is subtracted separately. 3721 CommonCost += TTI->getCastInstrCost( 3722 Ext->getOpcode(), Ext->getType(), EI->getType(), 3723 TTI::getCastContextHint(Ext), CostKind, Ext); 3724 continue; 3725 } 3726 } 3727 CommonCost -= 3728 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, I); 3729 } 3730 } else { 3731 AdjustExtractsCost(CommonCost, /*IsGather=*/false); 3732 } 3733 return CommonCost; 3734 } 3735 case Instruction::ZExt: 3736 case Instruction::SExt: 3737 case Instruction::FPToUI: 3738 case Instruction::FPToSI: 3739 case Instruction::FPExt: 3740 case Instruction::PtrToInt: 3741 case Instruction::IntToPtr: 3742 case Instruction::SIToFP: 3743 case Instruction::UIToFP: 3744 case Instruction::Trunc: 3745 case Instruction::FPTrunc: 3746 case Instruction::BitCast: { 3747 Type *SrcTy = VL0->getOperand(0)->getType(); 3748 InstructionCost ScalarEltCost = 3749 TTI->getCastInstrCost(E->getOpcode(), ScalarTy, SrcTy, 3750 TTI::getCastContextHint(VL0), CostKind, VL0); 3751 if (NeedToShuffleReuses) { 3752 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3753 } 3754 3755 // Calculate the cost of this instruction. 3756 InstructionCost ScalarCost = VL.size() * ScalarEltCost; 3757 3758 auto *SrcVecTy = FixedVectorType::get(SrcTy, VL.size()); 3759 InstructionCost VecCost = 0; 3760 // Check if the values are candidates to demote. 3761 if (!MinBWs.count(VL0) || VecTy != SrcVecTy) { 3762 VecCost = 3763 ReuseShuffleCost + 3764 TTI->getCastInstrCost(E->getOpcode(), VecTy, SrcVecTy, 3765 TTI::getCastContextHint(VL0), CostKind, VL0); 3766 } 3767 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3768 return VecCost - ScalarCost; 3769 } 3770 case Instruction::FCmp: 3771 case Instruction::ICmp: 3772 case Instruction::Select: { 3773 // Calculate the cost of this instruction. 3774 InstructionCost ScalarEltCost = 3775 TTI->getCmpSelInstrCost(E->getOpcode(), ScalarTy, Builder.getInt1Ty(), 3776 CmpInst::BAD_ICMP_PREDICATE, CostKind, VL0); 3777 if (NeedToShuffleReuses) { 3778 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3779 } 3780 auto *MaskTy = FixedVectorType::get(Builder.getInt1Ty(), VL.size()); 3781 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3782 3783 // Check if all entries in VL are either compares or selects with compares 3784 // as condition that have the same predicates. 3785 CmpInst::Predicate VecPred = CmpInst::BAD_ICMP_PREDICATE; 3786 bool First = true; 3787 for (auto *V : VL) { 3788 CmpInst::Predicate CurrentPred; 3789 auto MatchCmp = m_Cmp(CurrentPred, m_Value(), m_Value()); 3790 if ((!match(V, m_Select(MatchCmp, m_Value(), m_Value())) && 3791 !match(V, MatchCmp)) || 3792 (!First && VecPred != CurrentPred)) { 3793 VecPred = CmpInst::BAD_ICMP_PREDICATE; 3794 break; 3795 } 3796 First = false; 3797 VecPred = CurrentPred; 3798 } 3799 3800 InstructionCost VecCost = TTI->getCmpSelInstrCost( 3801 E->getOpcode(), VecTy, MaskTy, VecPred, CostKind, VL0); 3802 // Check if it is possible and profitable to use min/max for selects in 3803 // VL. 3804 // 3805 auto IntrinsicAndUse = canConvertToMinOrMaxIntrinsic(VL); 3806 if (IntrinsicAndUse.first != Intrinsic::not_intrinsic) { 3807 IntrinsicCostAttributes CostAttrs(IntrinsicAndUse.first, VecTy, 3808 {VecTy, VecTy}); 3809 InstructionCost IntrinsicCost = 3810 TTI->getIntrinsicInstrCost(CostAttrs, CostKind); 3811 // If the selects are the only uses of the compares, they will be dead 3812 // and we can adjust the cost by removing their cost. 3813 if (IntrinsicAndUse.second) 3814 IntrinsicCost -= 3815 TTI->getCmpSelInstrCost(Instruction::ICmp, VecTy, MaskTy, 3816 CmpInst::BAD_ICMP_PREDICATE, CostKind); 3817 VecCost = std::min(VecCost, IntrinsicCost); 3818 } 3819 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3820 return ReuseShuffleCost + VecCost - ScalarCost; 3821 } 3822 case Instruction::FNeg: 3823 case Instruction::Add: 3824 case Instruction::FAdd: 3825 case Instruction::Sub: 3826 case Instruction::FSub: 3827 case Instruction::Mul: 3828 case Instruction::FMul: 3829 case Instruction::UDiv: 3830 case Instruction::SDiv: 3831 case Instruction::FDiv: 3832 case Instruction::URem: 3833 case Instruction::SRem: 3834 case Instruction::FRem: 3835 case Instruction::Shl: 3836 case Instruction::LShr: 3837 case Instruction::AShr: 3838 case Instruction::And: 3839 case Instruction::Or: 3840 case Instruction::Xor: { 3841 // Certain instructions can be cheaper to vectorize if they have a 3842 // constant second vector operand. 3843 TargetTransformInfo::OperandValueKind Op1VK = 3844 TargetTransformInfo::OK_AnyValue; 3845 TargetTransformInfo::OperandValueKind Op2VK = 3846 TargetTransformInfo::OK_UniformConstantValue; 3847 TargetTransformInfo::OperandValueProperties Op1VP = 3848 TargetTransformInfo::OP_None; 3849 TargetTransformInfo::OperandValueProperties Op2VP = 3850 TargetTransformInfo::OP_PowerOf2; 3851 3852 // If all operands are exactly the same ConstantInt then set the 3853 // operand kind to OK_UniformConstantValue. 3854 // If instead not all operands are constants, then set the operand kind 3855 // to OK_AnyValue. If all operands are constants but not the same, 3856 // then set the operand kind to OK_NonUniformConstantValue. 3857 ConstantInt *CInt0 = nullptr; 3858 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 3859 const Instruction *I = cast<Instruction>(VL[i]); 3860 unsigned OpIdx = isa<BinaryOperator>(I) ? 1 : 0; 3861 ConstantInt *CInt = dyn_cast<ConstantInt>(I->getOperand(OpIdx)); 3862 if (!CInt) { 3863 Op2VK = TargetTransformInfo::OK_AnyValue; 3864 Op2VP = TargetTransformInfo::OP_None; 3865 break; 3866 } 3867 if (Op2VP == TargetTransformInfo::OP_PowerOf2 && 3868 !CInt->getValue().isPowerOf2()) 3869 Op2VP = TargetTransformInfo::OP_None; 3870 if (i == 0) { 3871 CInt0 = CInt; 3872 continue; 3873 } 3874 if (CInt0 != CInt) 3875 Op2VK = TargetTransformInfo::OK_NonUniformConstantValue; 3876 } 3877 3878 SmallVector<const Value *, 4> Operands(VL0->operand_values()); 3879 InstructionCost ScalarEltCost = 3880 TTI->getArithmeticInstrCost(E->getOpcode(), ScalarTy, CostKind, Op1VK, 3881 Op2VK, Op1VP, Op2VP, Operands, VL0); 3882 if (NeedToShuffleReuses) { 3883 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3884 } 3885 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3886 InstructionCost VecCost = 3887 TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind, Op1VK, 3888 Op2VK, Op1VP, Op2VP, Operands, VL0); 3889 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3890 return ReuseShuffleCost + VecCost - ScalarCost; 3891 } 3892 case Instruction::GetElementPtr: { 3893 TargetTransformInfo::OperandValueKind Op1VK = 3894 TargetTransformInfo::OK_AnyValue; 3895 TargetTransformInfo::OperandValueKind Op2VK = 3896 TargetTransformInfo::OK_UniformConstantValue; 3897 3898 InstructionCost ScalarEltCost = TTI->getArithmeticInstrCost( 3899 Instruction::Add, ScalarTy, CostKind, Op1VK, Op2VK); 3900 if (NeedToShuffleReuses) { 3901 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3902 } 3903 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3904 InstructionCost VecCost = TTI->getArithmeticInstrCost( 3905 Instruction::Add, VecTy, CostKind, Op1VK, Op2VK); 3906 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3907 return ReuseShuffleCost + VecCost - ScalarCost; 3908 } 3909 case Instruction::Load: { 3910 // Cost of wide load - cost of scalar loads. 3911 Align alignment = cast<LoadInst>(VL0)->getAlign(); 3912 InstructionCost ScalarEltCost = TTI->getMemoryOpCost( 3913 Instruction::Load, ScalarTy, alignment, 0, CostKind, VL0); 3914 if (NeedToShuffleReuses) { 3915 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3916 } 3917 InstructionCost ScalarLdCost = VecTy->getNumElements() * ScalarEltCost; 3918 InstructionCost VecLdCost; 3919 if (E->State == TreeEntry::Vectorize) { 3920 VecLdCost = TTI->getMemoryOpCost(Instruction::Load, VecTy, alignment, 0, 3921 CostKind, VL0); 3922 } else { 3923 assert(E->State == TreeEntry::ScatterVectorize && "Unknown EntryState"); 3924 VecLdCost = TTI->getGatherScatterOpCost( 3925 Instruction::Load, VecTy, cast<LoadInst>(VL0)->getPointerOperand(), 3926 /*VariableMask=*/false, alignment, CostKind, VL0); 3927 } 3928 if (!NeedToShuffleReuses && !E->ReorderIndices.empty()) { 3929 SmallVector<int> NewMask; 3930 inversePermutation(E->ReorderIndices, NewMask); 3931 VecLdCost += TTI->getShuffleCost( 3932 TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask); 3933 } 3934 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecLdCost, ScalarLdCost)); 3935 return ReuseShuffleCost + VecLdCost - ScalarLdCost; 3936 } 3937 case Instruction::Store: { 3938 // We know that we can merge the stores. Calculate the cost. 3939 bool IsReorder = !E->ReorderIndices.empty(); 3940 auto *SI = 3941 cast<StoreInst>(IsReorder ? VL[E->ReorderIndices.front()] : VL0); 3942 Align Alignment = SI->getAlign(); 3943 InstructionCost ScalarEltCost = TTI->getMemoryOpCost( 3944 Instruction::Store, ScalarTy, Alignment, 0, CostKind, VL0); 3945 InstructionCost ScalarStCost = VecTy->getNumElements() * ScalarEltCost; 3946 InstructionCost VecStCost = TTI->getMemoryOpCost( 3947 Instruction::Store, VecTy, Alignment, 0, CostKind, VL0); 3948 if (IsReorder) { 3949 SmallVector<int> NewMask; 3950 inversePermutation(E->ReorderIndices, NewMask); 3951 VecStCost += TTI->getShuffleCost( 3952 TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask); 3953 } 3954 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecStCost, ScalarStCost)); 3955 return VecStCost - ScalarStCost; 3956 } 3957 case Instruction::Call: { 3958 CallInst *CI = cast<CallInst>(VL0); 3959 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3960 3961 // Calculate the cost of the scalar and vector calls. 3962 IntrinsicCostAttributes CostAttrs(ID, *CI, 1); 3963 InstructionCost ScalarEltCost = 3964 TTI->getIntrinsicInstrCost(CostAttrs, CostKind); 3965 if (NeedToShuffleReuses) { 3966 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3967 } 3968 InstructionCost ScalarCallCost = VecTy->getNumElements() * ScalarEltCost; 3969 3970 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 3971 InstructionCost VecCallCost = 3972 std::min(VecCallCosts.first, VecCallCosts.second); 3973 3974 LLVM_DEBUG(dbgs() << "SLP: Call cost " << VecCallCost - ScalarCallCost 3975 << " (" << VecCallCost << "-" << ScalarCallCost << ")" 3976 << " for " << *CI << "\n"); 3977 3978 return ReuseShuffleCost + VecCallCost - ScalarCallCost; 3979 } 3980 case Instruction::ShuffleVector: { 3981 assert(E->isAltShuffle() && 3982 ((Instruction::isBinaryOp(E->getOpcode()) && 3983 Instruction::isBinaryOp(E->getAltOpcode())) || 3984 (Instruction::isCast(E->getOpcode()) && 3985 Instruction::isCast(E->getAltOpcode()))) && 3986 "Invalid Shuffle Vector Operand"); 3987 InstructionCost ScalarCost = 0; 3988 if (NeedToShuffleReuses) { 3989 for (unsigned Idx : E->ReuseShuffleIndices) { 3990 Instruction *I = cast<Instruction>(VL[Idx]); 3991 ReuseShuffleCost -= TTI->getInstructionCost(I, CostKind); 3992 } 3993 for (Value *V : VL) { 3994 Instruction *I = cast<Instruction>(V); 3995 ReuseShuffleCost += TTI->getInstructionCost(I, CostKind); 3996 } 3997 } 3998 for (Value *V : VL) { 3999 Instruction *I = cast<Instruction>(V); 4000 assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode"); 4001 ScalarCost += TTI->getInstructionCost(I, CostKind); 4002 } 4003 // VecCost is equal to sum of the cost of creating 2 vectors 4004 // and the cost of creating shuffle. 4005 InstructionCost VecCost = 0; 4006 if (Instruction::isBinaryOp(E->getOpcode())) { 4007 VecCost = TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind); 4008 VecCost += TTI->getArithmeticInstrCost(E->getAltOpcode(), VecTy, 4009 CostKind); 4010 } else { 4011 Type *Src0SclTy = E->getMainOp()->getOperand(0)->getType(); 4012 Type *Src1SclTy = E->getAltOp()->getOperand(0)->getType(); 4013 auto *Src0Ty = FixedVectorType::get(Src0SclTy, VL.size()); 4014 auto *Src1Ty = FixedVectorType::get(Src1SclTy, VL.size()); 4015 VecCost = TTI->getCastInstrCost(E->getOpcode(), VecTy, Src0Ty, 4016 TTI::CastContextHint::None, CostKind); 4017 VecCost += TTI->getCastInstrCost(E->getAltOpcode(), VecTy, Src1Ty, 4018 TTI::CastContextHint::None, CostKind); 4019 } 4020 4021 SmallVector<int> Mask(E->Scalars.size()); 4022 for (unsigned I = 0, End = E->Scalars.size(); I < End; ++I) { 4023 auto *OpInst = cast<Instruction>(E->Scalars[I]); 4024 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 4025 Mask[I] = I + (OpInst->getOpcode() == E->getAltOpcode() ? End : 0); 4026 } 4027 VecCost += 4028 TTI->getShuffleCost(TargetTransformInfo::SK_Select, VecTy, Mask, 0); 4029 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 4030 return ReuseShuffleCost + VecCost - ScalarCost; 4031 } 4032 default: 4033 llvm_unreachable("Unknown instruction"); 4034 } 4035 } 4036 4037 bool BoUpSLP::isFullyVectorizableTinyTree() const { 4038 LLVM_DEBUG(dbgs() << "SLP: Check whether the tree with height " 4039 << VectorizableTree.size() << " is fully vectorizable .\n"); 4040 4041 // We only handle trees of heights 1 and 2. 4042 if (VectorizableTree.size() == 1 && 4043 VectorizableTree[0]->State == TreeEntry::Vectorize) 4044 return true; 4045 4046 if (VectorizableTree.size() != 2) 4047 return false; 4048 4049 // Handle splat and all-constants stores. Also try to vectorize tiny trees 4050 // with the second gather nodes if they have less scalar operands rather than 4051 // the initial tree element (may be profitable to shuffle the second gather). 4052 if (VectorizableTree[0]->State == TreeEntry::Vectorize && 4053 (allConstant(VectorizableTree[1]->Scalars) || 4054 isSplat(VectorizableTree[1]->Scalars) || 4055 (VectorizableTree[1]->State == TreeEntry::NeedToGather && 4056 VectorizableTree[1]->Scalars.size() < 4057 VectorizableTree[0]->Scalars.size()))) 4058 return true; 4059 4060 // Gathering cost would be too much for tiny trees. 4061 if (VectorizableTree[0]->State == TreeEntry::NeedToGather || 4062 VectorizableTree[1]->State == TreeEntry::NeedToGather) 4063 return false; 4064 4065 return true; 4066 } 4067 4068 static bool isLoadCombineCandidateImpl(Value *Root, unsigned NumElts, 4069 TargetTransformInfo *TTI, 4070 bool MustMatchOrInst) { 4071 // Look past the root to find a source value. Arbitrarily follow the 4072 // path through operand 0 of any 'or'. Also, peek through optional 4073 // shift-left-by-multiple-of-8-bits. 4074 Value *ZextLoad = Root; 4075 const APInt *ShAmtC; 4076 bool FoundOr = false; 4077 while (!isa<ConstantExpr>(ZextLoad) && 4078 (match(ZextLoad, m_Or(m_Value(), m_Value())) || 4079 (match(ZextLoad, m_Shl(m_Value(), m_APInt(ShAmtC))) && 4080 ShAmtC->urem(8) == 0))) { 4081 auto *BinOp = cast<BinaryOperator>(ZextLoad); 4082 ZextLoad = BinOp->getOperand(0); 4083 if (BinOp->getOpcode() == Instruction::Or) 4084 FoundOr = true; 4085 } 4086 // Check if the input is an extended load of the required or/shift expression. 4087 Value *LoadPtr; 4088 if ((MustMatchOrInst && !FoundOr) || ZextLoad == Root || 4089 !match(ZextLoad, m_ZExt(m_Load(m_Value(LoadPtr))))) 4090 return false; 4091 4092 // Require that the total load bit width is a legal integer type. 4093 // For example, <8 x i8> --> i64 is a legal integer on a 64-bit target. 4094 // But <16 x i8> --> i128 is not, so the backend probably can't reduce it. 4095 Type *SrcTy = LoadPtr->getType()->getPointerElementType(); 4096 unsigned LoadBitWidth = SrcTy->getIntegerBitWidth() * NumElts; 4097 if (!TTI->isTypeLegal(IntegerType::get(Root->getContext(), LoadBitWidth))) 4098 return false; 4099 4100 // Everything matched - assume that we can fold the whole sequence using 4101 // load combining. 4102 LLVM_DEBUG(dbgs() << "SLP: Assume load combining for tree starting at " 4103 << *(cast<Instruction>(Root)) << "\n"); 4104 4105 return true; 4106 } 4107 4108 bool BoUpSLP::isLoadCombineReductionCandidate(RecurKind RdxKind) const { 4109 if (RdxKind != RecurKind::Or) 4110 return false; 4111 4112 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 4113 Value *FirstReduced = VectorizableTree[0]->Scalars[0]; 4114 return isLoadCombineCandidateImpl(FirstReduced, NumElts, TTI, 4115 /* MatchOr */ false); 4116 } 4117 4118 bool BoUpSLP::isLoadCombineCandidate() const { 4119 // Peek through a final sequence of stores and check if all operations are 4120 // likely to be load-combined. 4121 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 4122 for (Value *Scalar : VectorizableTree[0]->Scalars) { 4123 Value *X; 4124 if (!match(Scalar, m_Store(m_Value(X), m_Value())) || 4125 !isLoadCombineCandidateImpl(X, NumElts, TTI, /* MatchOr */ true)) 4126 return false; 4127 } 4128 return true; 4129 } 4130 4131 bool BoUpSLP::isTreeTinyAndNotFullyVectorizable() const { 4132 // We can vectorize the tree if its size is greater than or equal to the 4133 // minimum size specified by the MinTreeSize command line option. 4134 if (VectorizableTree.size() >= MinTreeSize) 4135 return false; 4136 4137 // If we have a tiny tree (a tree whose size is less than MinTreeSize), we 4138 // can vectorize it if we can prove it fully vectorizable. 4139 if (isFullyVectorizableTinyTree()) 4140 return false; 4141 4142 assert(VectorizableTree.empty() 4143 ? ExternalUses.empty() 4144 : true && "We shouldn't have any external users"); 4145 4146 // Otherwise, we can't vectorize the tree. It is both tiny and not fully 4147 // vectorizable. 4148 return true; 4149 } 4150 4151 InstructionCost BoUpSLP::getSpillCost() const { 4152 // Walk from the bottom of the tree to the top, tracking which values are 4153 // live. When we see a call instruction that is not part of our tree, 4154 // query TTI to see if there is a cost to keeping values live over it 4155 // (for example, if spills and fills are required). 4156 unsigned BundleWidth = VectorizableTree.front()->Scalars.size(); 4157 InstructionCost Cost = 0; 4158 4159 SmallPtrSet<Instruction*, 4> LiveValues; 4160 Instruction *PrevInst = nullptr; 4161 4162 // The entries in VectorizableTree are not necessarily ordered by their 4163 // position in basic blocks. Collect them and order them by dominance so later 4164 // instructions are guaranteed to be visited first. For instructions in 4165 // different basic blocks, we only scan to the beginning of the block, so 4166 // their order does not matter, as long as all instructions in a basic block 4167 // are grouped together. Using dominance ensures a deterministic order. 4168 SmallVector<Instruction *, 16> OrderedScalars; 4169 for (const auto &TEPtr : VectorizableTree) { 4170 Instruction *Inst = dyn_cast<Instruction>(TEPtr->Scalars[0]); 4171 if (!Inst) 4172 continue; 4173 OrderedScalars.push_back(Inst); 4174 } 4175 llvm::stable_sort(OrderedScalars, [this](Instruction *A, Instruction *B) { 4176 return DT->dominates(B, A); 4177 }); 4178 4179 for (Instruction *Inst : OrderedScalars) { 4180 if (!PrevInst) { 4181 PrevInst = Inst; 4182 continue; 4183 } 4184 4185 // Update LiveValues. 4186 LiveValues.erase(PrevInst); 4187 for (auto &J : PrevInst->operands()) { 4188 if (isa<Instruction>(&*J) && getTreeEntry(&*J)) 4189 LiveValues.insert(cast<Instruction>(&*J)); 4190 } 4191 4192 LLVM_DEBUG({ 4193 dbgs() << "SLP: #LV: " << LiveValues.size(); 4194 for (auto *X : LiveValues) 4195 dbgs() << " " << X->getName(); 4196 dbgs() << ", Looking at "; 4197 Inst->dump(); 4198 }); 4199 4200 // Now find the sequence of instructions between PrevInst and Inst. 4201 unsigned NumCalls = 0; 4202 BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(), 4203 PrevInstIt = 4204 PrevInst->getIterator().getReverse(); 4205 while (InstIt != PrevInstIt) { 4206 if (PrevInstIt == PrevInst->getParent()->rend()) { 4207 PrevInstIt = Inst->getParent()->rbegin(); 4208 continue; 4209 } 4210 4211 // Debug information does not impact spill cost. 4212 if ((isa<CallInst>(&*PrevInstIt) && 4213 !isa<DbgInfoIntrinsic>(&*PrevInstIt)) && 4214 &*PrevInstIt != PrevInst) 4215 NumCalls++; 4216 4217 ++PrevInstIt; 4218 } 4219 4220 if (NumCalls) { 4221 SmallVector<Type*, 4> V; 4222 for (auto *II : LiveValues) 4223 V.push_back(FixedVectorType::get(II->getType(), BundleWidth)); 4224 Cost += NumCalls * TTI->getCostOfKeepingLiveOverCall(V); 4225 } 4226 4227 PrevInst = Inst; 4228 } 4229 4230 return Cost; 4231 } 4232 4233 InstructionCost BoUpSLP::getTreeCost() { 4234 InstructionCost Cost = 0; 4235 LLVM_DEBUG(dbgs() << "SLP: Calculating cost for tree of size " 4236 << VectorizableTree.size() << ".\n"); 4237 4238 unsigned BundleWidth = VectorizableTree[0]->Scalars.size(); 4239 4240 for (unsigned I = 0, E = VectorizableTree.size(); I < E; ++I) { 4241 TreeEntry &TE = *VectorizableTree[I].get(); 4242 4243 InstructionCost C = getEntryCost(&TE); 4244 Cost += C; 4245 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C 4246 << " for bundle that starts with " << *TE.Scalars[0] 4247 << ".\n" 4248 << "SLP: Current total cost = " << Cost << "\n"); 4249 } 4250 4251 SmallPtrSet<Value *, 16> ExtractCostCalculated; 4252 InstructionCost ExtractCost = 0; 4253 for (ExternalUser &EU : ExternalUses) { 4254 // We only add extract cost once for the same scalar. 4255 if (!ExtractCostCalculated.insert(EU.Scalar).second) 4256 continue; 4257 4258 // Uses by ephemeral values are free (because the ephemeral value will be 4259 // removed prior to code generation, and so the extraction will be 4260 // removed as well). 4261 if (EphValues.count(EU.User)) 4262 continue; 4263 4264 // If we plan to rewrite the tree in a smaller type, we will need to sign 4265 // extend the extracted value back to the original type. Here, we account 4266 // for the extract and the added cost of the sign extend if needed. 4267 auto *VecTy = FixedVectorType::get(EU.Scalar->getType(), BundleWidth); 4268 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 4269 if (MinBWs.count(ScalarRoot)) { 4270 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 4271 auto Extend = 4272 MinBWs[ScalarRoot].second ? Instruction::SExt : Instruction::ZExt; 4273 VecTy = FixedVectorType::get(MinTy, BundleWidth); 4274 ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(), 4275 VecTy, EU.Lane); 4276 } else { 4277 ExtractCost += 4278 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, EU.Lane); 4279 } 4280 } 4281 4282 InstructionCost SpillCost = getSpillCost(); 4283 Cost += SpillCost + ExtractCost; 4284 4285 #ifndef NDEBUG 4286 SmallString<256> Str; 4287 { 4288 raw_svector_ostream OS(Str); 4289 OS << "SLP: Spill Cost = " << SpillCost << ".\n" 4290 << "SLP: Extract Cost = " << ExtractCost << ".\n" 4291 << "SLP: Total Cost = " << Cost << ".\n"; 4292 } 4293 LLVM_DEBUG(dbgs() << Str); 4294 if (ViewSLPTree) 4295 ViewGraph(this, "SLP" + F->getName(), false, Str); 4296 #endif 4297 4298 return Cost; 4299 } 4300 4301 Optional<TargetTransformInfo::ShuffleKind> 4302 BoUpSLP::isGatherShuffledEntry(const TreeEntry *TE, SmallVectorImpl<int> &Mask, 4303 SmallVectorImpl<const TreeEntry *> &Entries) { 4304 Mask.assign(TE->Scalars.size(), UndefMaskElem); 4305 Entries.clear(); 4306 DenseMap<Value *, const TreeEntry *> UsedValuesEntry; 4307 unsigned VF = 0; 4308 // FIXME: Shall be replaced by GetVF function once non-power-2 patch is 4309 // landed. 4310 auto &&GetVF = [](const TreeEntry *TE) { 4311 if (!TE->ReuseShuffleIndices.empty()) 4312 return TE->ReuseShuffleIndices.size(); 4313 return TE->Scalars.size(); 4314 }; 4315 for (int I = 0, E = TE->Scalars.size(); I < E; ++I) { 4316 Value *V = TE->Scalars[I]; 4317 if (isa<UndefValue>(V)) 4318 continue; 4319 const TreeEntry *VTE = UsedValuesEntry.lookup(V); 4320 if (!VTE) { 4321 if (Entries.size() == 2) 4322 return None; 4323 VTE = getTreeEntry(V); 4324 if (!VTE || find_if( 4325 VectorizableTree, 4326 [VTE, TE](const std::unique_ptr<TreeEntry> &EntryPtr) { 4327 return EntryPtr.get() == VTE || EntryPtr.get() == TE; 4328 })->get() == TE) { 4329 // Check if it is used in one of the gathered entries. 4330 const auto *It = 4331 find_if(VectorizableTree, 4332 [V, TE](const std::unique_ptr<TreeEntry> &EntryPtr) { 4333 return EntryPtr.get() == TE || 4334 (EntryPtr->State == TreeEntry::NeedToGather && 4335 is_contained(EntryPtr->Scalars, V)); 4336 }); 4337 // The vector factor of shuffled entries must be the same. 4338 if (It->get() == TE) 4339 return None; 4340 VTE = It->get(); 4341 } 4342 Entries.push_back(VTE); 4343 if (Entries.size() == 1) { 4344 VF = GetVF(VTE); 4345 } else if (VF != GetVF(VTE)) { 4346 assert(Entries.size() == 2 && "Expected shuffle of 1 or 2 entries."); 4347 assert(VF > 0 && "Expected non-zero vector factor."); 4348 return None; 4349 } 4350 for (Value *SV : VTE->Scalars) 4351 UsedValuesEntry.try_emplace(SV, VTE); 4352 } 4353 int FoundLane = findLaneForValue(VTE->Scalars, VTE->ReuseShuffleIndices, V); 4354 Mask[I] = (Entries.front() == VTE ? 0 : VF) + FoundLane; 4355 // Extra check required by isSingleSourceMaskImpl function (called by 4356 // ShuffleVectorInst::isSingleSourceMask). 4357 if (Mask[I] >= 2 * E) 4358 return None; 4359 } 4360 switch (Entries.size()) { 4361 case 1: 4362 return TargetTransformInfo::SK_PermuteSingleSrc; 4363 case 2: 4364 return TargetTransformInfo::SK_PermuteTwoSrc; 4365 default: 4366 break; 4367 } 4368 return None; 4369 } 4370 4371 InstructionCost 4372 BoUpSLP::getGatherCost(FixedVectorType *Ty, 4373 const DenseSet<unsigned> &ShuffledIndices) const { 4374 unsigned NumElts = Ty->getNumElements(); 4375 APInt DemandedElts = APInt::getNullValue(NumElts); 4376 for (unsigned I = 0; I < NumElts; ++I) 4377 if (!ShuffledIndices.count(I)) 4378 DemandedElts.setBit(I); 4379 InstructionCost Cost = 4380 TTI->getScalarizationOverhead(Ty, DemandedElts, /*Insert*/ true, 4381 /*Extract*/ false); 4382 if (!ShuffledIndices.empty()) 4383 Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, Ty); 4384 return Cost; 4385 } 4386 4387 InstructionCost BoUpSLP::getGatherCost(ArrayRef<Value *> VL) const { 4388 // Find the type of the operands in VL. 4389 Type *ScalarTy = VL[0]->getType(); 4390 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 4391 ScalarTy = SI->getValueOperand()->getType(); 4392 auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); 4393 // Find the cost of inserting/extracting values from the vector. 4394 // Check if the same elements are inserted several times and count them as 4395 // shuffle candidates. 4396 DenseSet<unsigned> ShuffledElements; 4397 DenseSet<Value *> UniqueElements; 4398 // Iterate in reverse order to consider insert elements with the high cost. 4399 for (unsigned I = VL.size(); I > 0; --I) { 4400 unsigned Idx = I - 1; 4401 if (!UniqueElements.insert(VL[Idx]).second) 4402 ShuffledElements.insert(Idx); 4403 } 4404 return getGatherCost(VecTy, ShuffledElements); 4405 } 4406 4407 // Perform operand reordering on the instructions in VL and return the reordered 4408 // operands in Left and Right. 4409 void BoUpSLP::reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 4410 SmallVectorImpl<Value *> &Left, 4411 SmallVectorImpl<Value *> &Right, 4412 const DataLayout &DL, 4413 ScalarEvolution &SE, 4414 const BoUpSLP &R) { 4415 if (VL.empty()) 4416 return; 4417 VLOperands Ops(VL, DL, SE, R); 4418 // Reorder the operands in place. 4419 Ops.reorder(); 4420 Left = Ops.getVL(0); 4421 Right = Ops.getVL(1); 4422 } 4423 4424 void BoUpSLP::setInsertPointAfterBundle(const TreeEntry *E) { 4425 // Get the basic block this bundle is in. All instructions in the bundle 4426 // should be in this block. 4427 auto *Front = E->getMainOp(); 4428 auto *BB = Front->getParent(); 4429 assert(llvm::all_of(E->Scalars, [=](Value *V) -> bool { 4430 auto *I = cast<Instruction>(V); 4431 return !E->isOpcodeOrAlt(I) || I->getParent() == BB; 4432 })); 4433 4434 // The last instruction in the bundle in program order. 4435 Instruction *LastInst = nullptr; 4436 4437 // Find the last instruction. The common case should be that BB has been 4438 // scheduled, and the last instruction is VL.back(). So we start with 4439 // VL.back() and iterate over schedule data until we reach the end of the 4440 // bundle. The end of the bundle is marked by null ScheduleData. 4441 if (BlocksSchedules.count(BB)) { 4442 auto *Bundle = 4443 BlocksSchedules[BB]->getScheduleData(E->isOneOf(E->Scalars.back())); 4444 if (Bundle && Bundle->isPartOfBundle()) 4445 for (; Bundle; Bundle = Bundle->NextInBundle) 4446 if (Bundle->OpValue == Bundle->Inst) 4447 LastInst = Bundle->Inst; 4448 } 4449 4450 // LastInst can still be null at this point if there's either not an entry 4451 // for BB in BlocksSchedules or there's no ScheduleData available for 4452 // VL.back(). This can be the case if buildTree_rec aborts for various 4453 // reasons (e.g., the maximum recursion depth is reached, the maximum region 4454 // size is reached, etc.). ScheduleData is initialized in the scheduling 4455 // "dry-run". 4456 // 4457 // If this happens, we can still find the last instruction by brute force. We 4458 // iterate forwards from Front (inclusive) until we either see all 4459 // instructions in the bundle or reach the end of the block. If Front is the 4460 // last instruction in program order, LastInst will be set to Front, and we 4461 // will visit all the remaining instructions in the block. 4462 // 4463 // One of the reasons we exit early from buildTree_rec is to place an upper 4464 // bound on compile-time. Thus, taking an additional compile-time hit here is 4465 // not ideal. However, this should be exceedingly rare since it requires that 4466 // we both exit early from buildTree_rec and that the bundle be out-of-order 4467 // (causing us to iterate all the way to the end of the block). 4468 if (!LastInst) { 4469 SmallPtrSet<Value *, 16> Bundle(E->Scalars.begin(), E->Scalars.end()); 4470 for (auto &I : make_range(BasicBlock::iterator(Front), BB->end())) { 4471 if (Bundle.erase(&I) && E->isOpcodeOrAlt(&I)) 4472 LastInst = &I; 4473 if (Bundle.empty()) 4474 break; 4475 } 4476 } 4477 assert(LastInst && "Failed to find last instruction in bundle"); 4478 4479 // Set the insertion point after the last instruction in the bundle. Set the 4480 // debug location to Front. 4481 Builder.SetInsertPoint(BB, ++LastInst->getIterator()); 4482 Builder.SetCurrentDebugLocation(Front->getDebugLoc()); 4483 } 4484 4485 Value *BoUpSLP::gather(ArrayRef<Value *> VL) { 4486 Value *Val0 = 4487 isa<StoreInst>(VL[0]) ? cast<StoreInst>(VL[0])->getValueOperand() : VL[0]; 4488 FixedVectorType *VecTy = FixedVectorType::get(Val0->getType(), VL.size()); 4489 Value *Vec = PoisonValue::get(VecTy); 4490 unsigned InsIndex = 0; 4491 for (Value *Val : VL) { 4492 Vec = Builder.CreateInsertElement(Vec, Val, Builder.getInt32(InsIndex++)); 4493 auto *InsElt = dyn_cast<InsertElementInst>(Vec); 4494 if (!InsElt) 4495 continue; 4496 GatherSeq.insert(InsElt); 4497 CSEBlocks.insert(InsElt->getParent()); 4498 // Add to our 'need-to-extract' list. 4499 if (TreeEntry *Entry = getTreeEntry(Val)) { 4500 // Find which lane we need to extract. 4501 int FoundLane = 4502 findLaneForValue(Entry->Scalars, Entry->ReuseShuffleIndices, Val); 4503 ExternalUses.push_back(ExternalUser(Val, InsElt, FoundLane)); 4504 } 4505 } 4506 4507 return Vec; 4508 } 4509 4510 Value *BoUpSLP::vectorizeTree(ArrayRef<Value *> VL) { 4511 InstructionsState S = getSameOpcode(VL); 4512 if (S.getOpcode()) { 4513 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 4514 if (E->isSame(VL)) { 4515 Value *V = vectorizeTree(E); 4516 if (VL.size() == E->Scalars.size() && !E->ReuseShuffleIndices.empty()) { 4517 // Reshuffle to get only unique values. 4518 // If some of the scalars are duplicated in the vectorization tree 4519 // entry, we do not vectorize them but instead generate a mask for the 4520 // reuses. But if there are several users of the same entry, they may 4521 // have different vectorization factors. This is especially important 4522 // for PHI nodes. In this case, we need to adapt the resulting 4523 // instruction for the user vectorization factor and have to reshuffle 4524 // it again to take only unique elements of the vector. Without this 4525 // code the function incorrectly returns reduced vector instruction 4526 // with the same elements, not with the unique ones. 4527 // block: 4528 // %phi = phi <2 x > { .., %entry} {%shuffle, %block} 4529 // %2 = shuffle <2 x > %phi, %poison, <4 x > <0, 0, 1, 1> 4530 // ... (use %2) 4531 // %shuffle = shuffle <2 x> %2, poison, <2 x> {0, 2} 4532 // br %block 4533 SmallVector<int, 4> UniqueIdxs; 4534 SmallSet<int, 4> UsedIdxs; 4535 int Pos = 0; 4536 for (int Idx : E->ReuseShuffleIndices) { 4537 if (UsedIdxs.insert(Idx).second) 4538 UniqueIdxs.emplace_back(Pos); 4539 ++Pos; 4540 } 4541 V = Builder.CreateShuffleVector(V, UniqueIdxs, "shrink.shuffle"); 4542 } 4543 return V; 4544 } 4545 } 4546 } 4547 4548 // Check that every instruction appears once in this bundle. 4549 SmallVector<int, 4> ReuseShuffleIndicies; 4550 SmallVector<Value *, 4> UniqueValues; 4551 if (VL.size() > 2) { 4552 DenseMap<Value *, unsigned> UniquePositions; 4553 for (Value *V : VL) { 4554 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 4555 ReuseShuffleIndicies.emplace_back(Res.first->second); 4556 if (Res.second || isa<Constant>(V)) 4557 UniqueValues.emplace_back(V); 4558 } 4559 // Do not shuffle single element or if number of unique values is not power 4560 // of 2. 4561 if (UniqueValues.size() == VL.size() || UniqueValues.size() <= 1 || 4562 !llvm::isPowerOf2_32(UniqueValues.size())) 4563 ReuseShuffleIndicies.clear(); 4564 else 4565 VL = UniqueValues; 4566 } 4567 4568 Value *Vec = gather(VL); 4569 if (!ReuseShuffleIndicies.empty()) { 4570 Vec = Builder.CreateShuffleVector(Vec, ReuseShuffleIndicies, "shuffle"); 4571 if (auto *I = dyn_cast<Instruction>(Vec)) { 4572 GatherSeq.insert(I); 4573 CSEBlocks.insert(I->getParent()); 4574 } 4575 } 4576 return Vec; 4577 } 4578 4579 namespace { 4580 /// Merges shuffle masks and emits final shuffle instruction, if required. 4581 class ShuffleInstructionBuilder { 4582 IRBuilderBase &Builder; 4583 bool IsFinalized = false; 4584 SmallVector<int, 4> Mask; 4585 4586 public: 4587 ShuffleInstructionBuilder(IRBuilderBase &Builder) : Builder(Builder) {} 4588 4589 /// Adds a mask, inverting it before applying. 4590 void addInversedMask(ArrayRef<unsigned> SubMask) { 4591 if (SubMask.empty()) 4592 return; 4593 SmallVector<int, 4> NewMask; 4594 inversePermutation(SubMask, NewMask); 4595 addMask(NewMask); 4596 } 4597 4598 /// Functions adds masks, merging them into single one. 4599 void addMask(ArrayRef<unsigned> SubMask) { 4600 SmallVector<int, 4> NewMask(SubMask.begin(), SubMask.end()); 4601 addMask(NewMask); 4602 } 4603 4604 void addMask(ArrayRef<int> SubMask) { 4605 if (SubMask.empty()) 4606 return; 4607 if (Mask.empty()) { 4608 Mask.append(SubMask.begin(), SubMask.end()); 4609 return; 4610 } 4611 SmallVector<int, 4> NewMask(SubMask.size(), SubMask.size()); 4612 int TermValue = std::min(Mask.size(), SubMask.size()); 4613 for (int I = 0, E = SubMask.size(); I < E; ++I) { 4614 if (SubMask[I] >= TermValue || Mask[SubMask[I]] >= TermValue) { 4615 NewMask[I] = E; 4616 continue; 4617 } 4618 NewMask[I] = Mask[SubMask[I]]; 4619 } 4620 Mask.swap(NewMask); 4621 } 4622 4623 Value *finalize(Value *V) { 4624 IsFinalized = true; 4625 if (Mask.empty()) 4626 return V; 4627 return Builder.CreateShuffleVector(V, Mask, "shuffle"); 4628 } 4629 4630 ~ShuffleInstructionBuilder() { 4631 assert((IsFinalized || Mask.empty()) && 4632 "Shuffle construction must be finalized."); 4633 } 4634 }; 4635 } // namespace 4636 4637 Value *BoUpSLP::vectorizeTree(TreeEntry *E) { 4638 IRBuilder<>::InsertPointGuard Guard(Builder); 4639 4640 if (E->VectorizedValue) { 4641 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *E->Scalars[0] << ".\n"); 4642 return E->VectorizedValue; 4643 } 4644 4645 ShuffleInstructionBuilder ShuffleBuilder(Builder); 4646 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 4647 if (E->State == TreeEntry::NeedToGather) { 4648 setInsertPointAfterBundle(E); 4649 Value *Vec; 4650 SmallVector<int> Mask; 4651 SmallVector<const TreeEntry *> Entries; 4652 Optional<TargetTransformInfo::ShuffleKind> Shuffle = 4653 isGatherShuffledEntry(E, Mask, Entries); 4654 if (Shuffle.hasValue()) { 4655 assert((Entries.size() == 1 || Entries.size() == 2) && 4656 "Expected shuffle of 1 or 2 entries."); 4657 Vec = Builder.CreateShuffleVector(Entries.front()->VectorizedValue, 4658 Entries.back()->VectorizedValue, Mask); 4659 } else { 4660 Vec = gather(E->Scalars); 4661 } 4662 if (NeedToShuffleReuses) { 4663 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4664 Vec = ShuffleBuilder.finalize(Vec); 4665 if (auto *I = dyn_cast<Instruction>(Vec)) { 4666 GatherSeq.insert(I); 4667 CSEBlocks.insert(I->getParent()); 4668 } 4669 } 4670 E->VectorizedValue = Vec; 4671 return Vec; 4672 } 4673 4674 assert((E->State == TreeEntry::Vectorize || 4675 E->State == TreeEntry::ScatterVectorize) && 4676 "Unhandled state"); 4677 unsigned ShuffleOrOp = 4678 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 4679 Instruction *VL0 = E->getMainOp(); 4680 Type *ScalarTy = VL0->getType(); 4681 if (auto *Store = dyn_cast<StoreInst>(VL0)) 4682 ScalarTy = Store->getValueOperand()->getType(); 4683 auto *VecTy = FixedVectorType::get(ScalarTy, E->Scalars.size()); 4684 switch (ShuffleOrOp) { 4685 case Instruction::PHI: { 4686 auto *PH = cast<PHINode>(VL0); 4687 Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI()); 4688 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 4689 PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues()); 4690 Value *V = NewPhi; 4691 if (NeedToShuffleReuses) 4692 V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle"); 4693 4694 E->VectorizedValue = V; 4695 4696 // PHINodes may have multiple entries from the same block. We want to 4697 // visit every block once. 4698 SmallPtrSet<BasicBlock*, 4> VisitedBBs; 4699 4700 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 4701 ValueList Operands; 4702 BasicBlock *IBB = PH->getIncomingBlock(i); 4703 4704 if (!VisitedBBs.insert(IBB).second) { 4705 NewPhi->addIncoming(NewPhi->getIncomingValueForBlock(IBB), IBB); 4706 continue; 4707 } 4708 4709 Builder.SetInsertPoint(IBB->getTerminator()); 4710 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 4711 Value *Vec = vectorizeTree(E->getOperand(i)); 4712 NewPhi->addIncoming(Vec, IBB); 4713 } 4714 4715 assert(NewPhi->getNumIncomingValues() == PH->getNumIncomingValues() && 4716 "Invalid number of incoming values"); 4717 return V; 4718 } 4719 4720 case Instruction::ExtractElement: { 4721 Value *V = E->getSingleOperand(0); 4722 Builder.SetInsertPoint(VL0); 4723 ShuffleBuilder.addInversedMask(E->ReorderIndices); 4724 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4725 V = ShuffleBuilder.finalize(V); 4726 E->VectorizedValue = V; 4727 return V; 4728 } 4729 case Instruction::ExtractValue: { 4730 auto *LI = cast<LoadInst>(E->getSingleOperand(0)); 4731 Builder.SetInsertPoint(LI); 4732 auto *PtrTy = PointerType::get(VecTy, LI->getPointerAddressSpace()); 4733 Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy); 4734 LoadInst *V = Builder.CreateAlignedLoad(VecTy, Ptr, LI->getAlign()); 4735 Value *NewV = propagateMetadata(V, E->Scalars); 4736 ShuffleBuilder.addInversedMask(E->ReorderIndices); 4737 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4738 NewV = ShuffleBuilder.finalize(NewV); 4739 E->VectorizedValue = NewV; 4740 return NewV; 4741 } 4742 case Instruction::ZExt: 4743 case Instruction::SExt: 4744 case Instruction::FPToUI: 4745 case Instruction::FPToSI: 4746 case Instruction::FPExt: 4747 case Instruction::PtrToInt: 4748 case Instruction::IntToPtr: 4749 case Instruction::SIToFP: 4750 case Instruction::UIToFP: 4751 case Instruction::Trunc: 4752 case Instruction::FPTrunc: 4753 case Instruction::BitCast: { 4754 setInsertPointAfterBundle(E); 4755 4756 Value *InVec = vectorizeTree(E->getOperand(0)); 4757 4758 if (E->VectorizedValue) { 4759 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4760 return E->VectorizedValue; 4761 } 4762 4763 auto *CI = cast<CastInst>(VL0); 4764 Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy); 4765 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4766 V = ShuffleBuilder.finalize(V); 4767 4768 E->VectorizedValue = V; 4769 ++NumVectorInstructions; 4770 return V; 4771 } 4772 case Instruction::FCmp: 4773 case Instruction::ICmp: { 4774 setInsertPointAfterBundle(E); 4775 4776 Value *L = vectorizeTree(E->getOperand(0)); 4777 Value *R = vectorizeTree(E->getOperand(1)); 4778 4779 if (E->VectorizedValue) { 4780 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4781 return E->VectorizedValue; 4782 } 4783 4784 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 4785 Value *V = Builder.CreateCmp(P0, L, R); 4786 propagateIRFlags(V, E->Scalars, VL0); 4787 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4788 V = ShuffleBuilder.finalize(V); 4789 4790 E->VectorizedValue = V; 4791 ++NumVectorInstructions; 4792 return V; 4793 } 4794 case Instruction::Select: { 4795 setInsertPointAfterBundle(E); 4796 4797 Value *Cond = vectorizeTree(E->getOperand(0)); 4798 Value *True = vectorizeTree(E->getOperand(1)); 4799 Value *False = vectorizeTree(E->getOperand(2)); 4800 4801 if (E->VectorizedValue) { 4802 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4803 return E->VectorizedValue; 4804 } 4805 4806 Value *V = Builder.CreateSelect(Cond, True, False); 4807 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4808 V = ShuffleBuilder.finalize(V); 4809 4810 E->VectorizedValue = V; 4811 ++NumVectorInstructions; 4812 return V; 4813 } 4814 case Instruction::FNeg: { 4815 setInsertPointAfterBundle(E); 4816 4817 Value *Op = vectorizeTree(E->getOperand(0)); 4818 4819 if (E->VectorizedValue) { 4820 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4821 return E->VectorizedValue; 4822 } 4823 4824 Value *V = Builder.CreateUnOp( 4825 static_cast<Instruction::UnaryOps>(E->getOpcode()), Op); 4826 propagateIRFlags(V, E->Scalars, VL0); 4827 if (auto *I = dyn_cast<Instruction>(V)) 4828 V = propagateMetadata(I, E->Scalars); 4829 4830 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4831 V = ShuffleBuilder.finalize(V); 4832 4833 E->VectorizedValue = V; 4834 ++NumVectorInstructions; 4835 4836 return V; 4837 } 4838 case Instruction::Add: 4839 case Instruction::FAdd: 4840 case Instruction::Sub: 4841 case Instruction::FSub: 4842 case Instruction::Mul: 4843 case Instruction::FMul: 4844 case Instruction::UDiv: 4845 case Instruction::SDiv: 4846 case Instruction::FDiv: 4847 case Instruction::URem: 4848 case Instruction::SRem: 4849 case Instruction::FRem: 4850 case Instruction::Shl: 4851 case Instruction::LShr: 4852 case Instruction::AShr: 4853 case Instruction::And: 4854 case Instruction::Or: 4855 case Instruction::Xor: { 4856 setInsertPointAfterBundle(E); 4857 4858 Value *LHS = vectorizeTree(E->getOperand(0)); 4859 Value *RHS = vectorizeTree(E->getOperand(1)); 4860 4861 if (E->VectorizedValue) { 4862 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4863 return E->VectorizedValue; 4864 } 4865 4866 Value *V = Builder.CreateBinOp( 4867 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, 4868 RHS); 4869 propagateIRFlags(V, E->Scalars, VL0); 4870 if (auto *I = dyn_cast<Instruction>(V)) 4871 V = propagateMetadata(I, E->Scalars); 4872 4873 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4874 V = ShuffleBuilder.finalize(V); 4875 4876 E->VectorizedValue = V; 4877 ++NumVectorInstructions; 4878 4879 return V; 4880 } 4881 case Instruction::Load: { 4882 // Loads are inserted at the head of the tree because we don't want to 4883 // sink them all the way down past store instructions. 4884 bool IsReorder = E->updateStateIfReorder(); 4885 if (IsReorder) 4886 VL0 = E->getMainOp(); 4887 setInsertPointAfterBundle(E); 4888 4889 LoadInst *LI = cast<LoadInst>(VL0); 4890 Instruction *NewLI; 4891 unsigned AS = LI->getPointerAddressSpace(); 4892 Value *PO = LI->getPointerOperand(); 4893 if (E->State == TreeEntry::Vectorize) { 4894 4895 Value *VecPtr = Builder.CreateBitCast(PO, VecTy->getPointerTo(AS)); 4896 4897 // The pointer operand uses an in-tree scalar so we add the new BitCast 4898 // to ExternalUses list to make sure that an extract will be generated 4899 // in the future. 4900 if (getTreeEntry(PO)) 4901 ExternalUses.emplace_back(PO, cast<User>(VecPtr), 0); 4902 4903 NewLI = Builder.CreateAlignedLoad(VecTy, VecPtr, LI->getAlign()); 4904 } else { 4905 assert(E->State == TreeEntry::ScatterVectorize && "Unhandled state"); 4906 Value *VecPtr = vectorizeTree(E->getOperand(0)); 4907 // Use the minimum alignment of the gathered loads. 4908 Align CommonAlignment = LI->getAlign(); 4909 for (Value *V : E->Scalars) 4910 CommonAlignment = 4911 commonAlignment(CommonAlignment, cast<LoadInst>(V)->getAlign()); 4912 NewLI = Builder.CreateMaskedGather(VecPtr, CommonAlignment); 4913 } 4914 Value *V = propagateMetadata(NewLI, E->Scalars); 4915 4916 ShuffleBuilder.addInversedMask(E->ReorderIndices); 4917 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4918 V = ShuffleBuilder.finalize(V); 4919 E->VectorizedValue = V; 4920 ++NumVectorInstructions; 4921 return V; 4922 } 4923 case Instruction::Store: { 4924 bool IsReorder = !E->ReorderIndices.empty(); 4925 auto *SI = cast<StoreInst>( 4926 IsReorder ? E->Scalars[E->ReorderIndices.front()] : VL0); 4927 unsigned AS = SI->getPointerAddressSpace(); 4928 4929 setInsertPointAfterBundle(E); 4930 4931 Value *VecValue = vectorizeTree(E->getOperand(0)); 4932 ShuffleBuilder.addMask(E->ReorderIndices); 4933 VecValue = ShuffleBuilder.finalize(VecValue); 4934 4935 Value *ScalarPtr = SI->getPointerOperand(); 4936 Value *VecPtr = Builder.CreateBitCast( 4937 ScalarPtr, VecValue->getType()->getPointerTo(AS)); 4938 StoreInst *ST = Builder.CreateAlignedStore(VecValue, VecPtr, 4939 SI->getAlign()); 4940 4941 // The pointer operand uses an in-tree scalar, so add the new BitCast to 4942 // ExternalUses to make sure that an extract will be generated in the 4943 // future. 4944 if (getTreeEntry(ScalarPtr)) 4945 ExternalUses.push_back(ExternalUser(ScalarPtr, cast<User>(VecPtr), 0)); 4946 4947 Value *V = propagateMetadata(ST, E->Scalars); 4948 4949 E->VectorizedValue = V; 4950 ++NumVectorInstructions; 4951 return V; 4952 } 4953 case Instruction::GetElementPtr: { 4954 setInsertPointAfterBundle(E); 4955 4956 Value *Op0 = vectorizeTree(E->getOperand(0)); 4957 4958 std::vector<Value *> OpVecs; 4959 for (int j = 1, e = cast<GetElementPtrInst>(VL0)->getNumOperands(); j < e; 4960 ++j) { 4961 ValueList &VL = E->getOperand(j); 4962 // Need to cast all elements to the same type before vectorization to 4963 // avoid crash. 4964 Type *VL0Ty = VL0->getOperand(j)->getType(); 4965 Type *Ty = llvm::all_of( 4966 VL, [VL0Ty](Value *V) { return VL0Ty == V->getType(); }) 4967 ? VL0Ty 4968 : DL->getIndexType(cast<GetElementPtrInst>(VL0) 4969 ->getPointerOperandType() 4970 ->getScalarType()); 4971 for (Value *&V : VL) { 4972 auto *CI = cast<ConstantInt>(V); 4973 V = ConstantExpr::getIntegerCast(CI, Ty, 4974 CI->getValue().isSignBitSet()); 4975 } 4976 Value *OpVec = vectorizeTree(VL); 4977 OpVecs.push_back(OpVec); 4978 } 4979 4980 Value *V = Builder.CreateGEP( 4981 cast<GetElementPtrInst>(VL0)->getSourceElementType(), Op0, OpVecs); 4982 if (Instruction *I = dyn_cast<Instruction>(V)) 4983 V = propagateMetadata(I, E->Scalars); 4984 4985 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4986 V = ShuffleBuilder.finalize(V); 4987 4988 E->VectorizedValue = V; 4989 ++NumVectorInstructions; 4990 4991 return V; 4992 } 4993 case Instruction::Call: { 4994 CallInst *CI = cast<CallInst>(VL0); 4995 setInsertPointAfterBundle(E); 4996 4997 Intrinsic::ID IID = Intrinsic::not_intrinsic; 4998 if (Function *FI = CI->getCalledFunction()) 4999 IID = FI->getIntrinsicID(); 5000 5001 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 5002 5003 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 5004 bool UseIntrinsic = ID != Intrinsic::not_intrinsic && 5005 VecCallCosts.first <= VecCallCosts.second; 5006 5007 Value *ScalarArg = nullptr; 5008 std::vector<Value *> OpVecs; 5009 for (int j = 0, e = CI->getNumArgOperands(); j < e; ++j) { 5010 ValueList OpVL; 5011 // Some intrinsics have scalar arguments. This argument should not be 5012 // vectorized. 5013 if (UseIntrinsic && hasVectorInstrinsicScalarOpd(IID, j)) { 5014 CallInst *CEI = cast<CallInst>(VL0); 5015 ScalarArg = CEI->getArgOperand(j); 5016 OpVecs.push_back(CEI->getArgOperand(j)); 5017 continue; 5018 } 5019 5020 Value *OpVec = vectorizeTree(E->getOperand(j)); 5021 LLVM_DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n"); 5022 OpVecs.push_back(OpVec); 5023 } 5024 5025 Function *CF; 5026 if (!UseIntrinsic) { 5027 VFShape Shape = 5028 VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>( 5029 VecTy->getNumElements())), 5030 false /*HasGlobalPred*/); 5031 CF = VFDatabase(*CI).getVectorizedFunction(Shape); 5032 } else { 5033 Type *Tys[] = {FixedVectorType::get(CI->getType(), E->Scalars.size())}; 5034 CF = Intrinsic::getDeclaration(F->getParent(), ID, Tys); 5035 } 5036 5037 SmallVector<OperandBundleDef, 1> OpBundles; 5038 CI->getOperandBundlesAsDefs(OpBundles); 5039 Value *V = Builder.CreateCall(CF, OpVecs, OpBundles); 5040 5041 // The scalar argument uses an in-tree scalar so we add the new vectorized 5042 // call to ExternalUses list to make sure that an extract will be 5043 // generated in the future. 5044 if (ScalarArg && getTreeEntry(ScalarArg)) 5045 ExternalUses.push_back(ExternalUser(ScalarArg, cast<User>(V), 0)); 5046 5047 propagateIRFlags(V, E->Scalars, VL0); 5048 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5049 V = ShuffleBuilder.finalize(V); 5050 5051 E->VectorizedValue = V; 5052 ++NumVectorInstructions; 5053 return V; 5054 } 5055 case Instruction::ShuffleVector: { 5056 assert(E->isAltShuffle() && 5057 ((Instruction::isBinaryOp(E->getOpcode()) && 5058 Instruction::isBinaryOp(E->getAltOpcode())) || 5059 (Instruction::isCast(E->getOpcode()) && 5060 Instruction::isCast(E->getAltOpcode()))) && 5061 "Invalid Shuffle Vector Operand"); 5062 5063 Value *LHS = nullptr, *RHS = nullptr; 5064 if (Instruction::isBinaryOp(E->getOpcode())) { 5065 setInsertPointAfterBundle(E); 5066 LHS = vectorizeTree(E->getOperand(0)); 5067 RHS = vectorizeTree(E->getOperand(1)); 5068 } else { 5069 setInsertPointAfterBundle(E); 5070 LHS = vectorizeTree(E->getOperand(0)); 5071 } 5072 5073 if (E->VectorizedValue) { 5074 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 5075 return E->VectorizedValue; 5076 } 5077 5078 Value *V0, *V1; 5079 if (Instruction::isBinaryOp(E->getOpcode())) { 5080 V0 = Builder.CreateBinOp( 5081 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, RHS); 5082 V1 = Builder.CreateBinOp( 5083 static_cast<Instruction::BinaryOps>(E->getAltOpcode()), LHS, RHS); 5084 } else { 5085 V0 = Builder.CreateCast( 5086 static_cast<Instruction::CastOps>(E->getOpcode()), LHS, VecTy); 5087 V1 = Builder.CreateCast( 5088 static_cast<Instruction::CastOps>(E->getAltOpcode()), LHS, VecTy); 5089 } 5090 5091 // Create shuffle to take alternate operations from the vector. 5092 // Also, gather up main and alt scalar ops to propagate IR flags to 5093 // each vector operation. 5094 ValueList OpScalars, AltScalars; 5095 unsigned e = E->Scalars.size(); 5096 SmallVector<int, 8> Mask(e); 5097 for (unsigned i = 0; i < e; ++i) { 5098 auto *OpInst = cast<Instruction>(E->Scalars[i]); 5099 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 5100 if (OpInst->getOpcode() == E->getAltOpcode()) { 5101 Mask[i] = e + i; 5102 AltScalars.push_back(E->Scalars[i]); 5103 } else { 5104 Mask[i] = i; 5105 OpScalars.push_back(E->Scalars[i]); 5106 } 5107 } 5108 5109 propagateIRFlags(V0, OpScalars); 5110 propagateIRFlags(V1, AltScalars); 5111 5112 Value *V = Builder.CreateShuffleVector(V0, V1, Mask); 5113 if (Instruction *I = dyn_cast<Instruction>(V)) 5114 V = propagateMetadata(I, E->Scalars); 5115 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 5116 V = ShuffleBuilder.finalize(V); 5117 5118 E->VectorizedValue = V; 5119 ++NumVectorInstructions; 5120 5121 return V; 5122 } 5123 default: 5124 llvm_unreachable("unknown inst"); 5125 } 5126 return nullptr; 5127 } 5128 5129 Value *BoUpSLP::vectorizeTree() { 5130 ExtraValueToDebugLocsMap ExternallyUsedValues; 5131 return vectorizeTree(ExternallyUsedValues); 5132 } 5133 5134 Value * 5135 BoUpSLP::vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues) { 5136 // All blocks must be scheduled before any instructions are inserted. 5137 for (auto &BSIter : BlocksSchedules) { 5138 scheduleBlock(BSIter.second.get()); 5139 } 5140 5141 Builder.SetInsertPoint(&F->getEntryBlock().front()); 5142 auto *VectorRoot = vectorizeTree(VectorizableTree[0].get()); 5143 5144 // If the vectorized tree can be rewritten in a smaller type, we truncate the 5145 // vectorized root. InstCombine will then rewrite the entire expression. We 5146 // sign extend the extracted values below. 5147 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 5148 if (MinBWs.count(ScalarRoot)) { 5149 if (auto *I = dyn_cast<Instruction>(VectorRoot)) { 5150 // If current instr is a phi and not the last phi, insert it after the 5151 // last phi node. 5152 if (isa<PHINode>(I)) 5153 Builder.SetInsertPoint(&*I->getParent()->getFirstInsertionPt()); 5154 else 5155 Builder.SetInsertPoint(&*++BasicBlock::iterator(I)); 5156 } 5157 auto BundleWidth = VectorizableTree[0]->Scalars.size(); 5158 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 5159 auto *VecTy = FixedVectorType::get(MinTy, BundleWidth); 5160 auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy); 5161 VectorizableTree[0]->VectorizedValue = Trunc; 5162 } 5163 5164 LLVM_DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size() 5165 << " values .\n"); 5166 5167 // If necessary, sign-extend or zero-extend ScalarRoot to the larger type 5168 // specified by ScalarType. 5169 auto extend = [&](Value *ScalarRoot, Value *Ex, Type *ScalarType) { 5170 if (!MinBWs.count(ScalarRoot)) 5171 return Ex; 5172 if (MinBWs[ScalarRoot].second) 5173 return Builder.CreateSExt(Ex, ScalarType); 5174 return Builder.CreateZExt(Ex, ScalarType); 5175 }; 5176 5177 // Extract all of the elements with the external uses. 5178 for (const auto &ExternalUse : ExternalUses) { 5179 Value *Scalar = ExternalUse.Scalar; 5180 llvm::User *User = ExternalUse.User; 5181 5182 // Skip users that we already RAUW. This happens when one instruction 5183 // has multiple uses of the same value. 5184 if (User && !is_contained(Scalar->users(), User)) 5185 continue; 5186 TreeEntry *E = getTreeEntry(Scalar); 5187 assert(E && "Invalid scalar"); 5188 assert(E->State != TreeEntry::NeedToGather && 5189 "Extracting from a gather list"); 5190 5191 Value *Vec = E->VectorizedValue; 5192 assert(Vec && "Can't find vectorizable value"); 5193 5194 Value *Lane = Builder.getInt32(ExternalUse.Lane); 5195 // If User == nullptr, the Scalar is used as extra arg. Generate 5196 // ExtractElement instruction and update the record for this scalar in 5197 // ExternallyUsedValues. 5198 if (!User) { 5199 assert(ExternallyUsedValues.count(Scalar) && 5200 "Scalar with nullptr as an external user must be registered in " 5201 "ExternallyUsedValues map"); 5202 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 5203 Builder.SetInsertPoint(VecI->getParent(), 5204 std::next(VecI->getIterator())); 5205 } else { 5206 Builder.SetInsertPoint(&F->getEntryBlock().front()); 5207 } 5208 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 5209 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 5210 CSEBlocks.insert(cast<Instruction>(Scalar)->getParent()); 5211 auto &Locs = ExternallyUsedValues[Scalar]; 5212 ExternallyUsedValues.insert({Ex, Locs}); 5213 ExternallyUsedValues.erase(Scalar); 5214 // Required to update internally referenced instructions. 5215 Scalar->replaceAllUsesWith(Ex); 5216 continue; 5217 } 5218 5219 // Generate extracts for out-of-tree users. 5220 // Find the insertion point for the extractelement lane. 5221 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 5222 if (PHINode *PH = dyn_cast<PHINode>(User)) { 5223 for (int i = 0, e = PH->getNumIncomingValues(); i != e; ++i) { 5224 if (PH->getIncomingValue(i) == Scalar) { 5225 Instruction *IncomingTerminator = 5226 PH->getIncomingBlock(i)->getTerminator(); 5227 if (isa<CatchSwitchInst>(IncomingTerminator)) { 5228 Builder.SetInsertPoint(VecI->getParent(), 5229 std::next(VecI->getIterator())); 5230 } else { 5231 Builder.SetInsertPoint(PH->getIncomingBlock(i)->getTerminator()); 5232 } 5233 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 5234 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 5235 CSEBlocks.insert(PH->getIncomingBlock(i)); 5236 PH->setOperand(i, Ex); 5237 } 5238 } 5239 } else { 5240 Builder.SetInsertPoint(cast<Instruction>(User)); 5241 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 5242 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 5243 CSEBlocks.insert(cast<Instruction>(User)->getParent()); 5244 User->replaceUsesOfWith(Scalar, Ex); 5245 } 5246 } else { 5247 Builder.SetInsertPoint(&F->getEntryBlock().front()); 5248 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 5249 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 5250 CSEBlocks.insert(&F->getEntryBlock()); 5251 User->replaceUsesOfWith(Scalar, Ex); 5252 } 5253 5254 LLVM_DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n"); 5255 } 5256 5257 // For each vectorized value: 5258 for (auto &TEPtr : VectorizableTree) { 5259 TreeEntry *Entry = TEPtr.get(); 5260 5261 // No need to handle users of gathered values. 5262 if (Entry->State == TreeEntry::NeedToGather) 5263 continue; 5264 5265 assert(Entry->VectorizedValue && "Can't find vectorizable value"); 5266 5267 // For each lane: 5268 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 5269 Value *Scalar = Entry->Scalars[Lane]; 5270 5271 #ifndef NDEBUG 5272 Type *Ty = Scalar->getType(); 5273 if (!Ty->isVoidTy()) { 5274 for (User *U : Scalar->users()) { 5275 LLVM_DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n"); 5276 5277 // It is legal to delete users in the ignorelist. 5278 assert((getTreeEntry(U) || is_contained(UserIgnoreList, U)) && 5279 "Deleting out-of-tree value"); 5280 } 5281 } 5282 #endif 5283 LLVM_DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n"); 5284 eraseInstruction(cast<Instruction>(Scalar)); 5285 } 5286 } 5287 5288 Builder.ClearInsertionPoint(); 5289 InstrElementSize.clear(); 5290 5291 return VectorizableTree[0]->VectorizedValue; 5292 } 5293 5294 void BoUpSLP::optimizeGatherSequence() { 5295 LLVM_DEBUG(dbgs() << "SLP: Optimizing " << GatherSeq.size() 5296 << " gather sequences instructions.\n"); 5297 // LICM InsertElementInst sequences. 5298 for (Instruction *I : GatherSeq) { 5299 if (isDeleted(I)) 5300 continue; 5301 5302 // Check if this block is inside a loop. 5303 Loop *L = LI->getLoopFor(I->getParent()); 5304 if (!L) 5305 continue; 5306 5307 // Check if it has a preheader. 5308 BasicBlock *PreHeader = L->getLoopPreheader(); 5309 if (!PreHeader) 5310 continue; 5311 5312 // If the vector or the element that we insert into it are 5313 // instructions that are defined in this basic block then we can't 5314 // hoist this instruction. 5315 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 5316 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 5317 if (Op0 && L->contains(Op0)) 5318 continue; 5319 if (Op1 && L->contains(Op1)) 5320 continue; 5321 5322 // We can hoist this instruction. Move it to the pre-header. 5323 I->moveBefore(PreHeader->getTerminator()); 5324 } 5325 5326 // Make a list of all reachable blocks in our CSE queue. 5327 SmallVector<const DomTreeNode *, 8> CSEWorkList; 5328 CSEWorkList.reserve(CSEBlocks.size()); 5329 for (BasicBlock *BB : CSEBlocks) 5330 if (DomTreeNode *N = DT->getNode(BB)) { 5331 assert(DT->isReachableFromEntry(N)); 5332 CSEWorkList.push_back(N); 5333 } 5334 5335 // Sort blocks by domination. This ensures we visit a block after all blocks 5336 // dominating it are visited. 5337 llvm::stable_sort(CSEWorkList, 5338 [this](const DomTreeNode *A, const DomTreeNode *B) { 5339 return DT->properlyDominates(A, B); 5340 }); 5341 5342 // Perform O(N^2) search over the gather sequences and merge identical 5343 // instructions. TODO: We can further optimize this scan if we split the 5344 // instructions into different buckets based on the insert lane. 5345 SmallVector<Instruction *, 16> Visited; 5346 for (auto I = CSEWorkList.begin(), E = CSEWorkList.end(); I != E; ++I) { 5347 assert(*I && 5348 (I == CSEWorkList.begin() || !DT->dominates(*I, *std::prev(I))) && 5349 "Worklist not sorted properly!"); 5350 BasicBlock *BB = (*I)->getBlock(); 5351 // For all instructions in blocks containing gather sequences: 5352 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e;) { 5353 Instruction *In = &*it++; 5354 if (isDeleted(In)) 5355 continue; 5356 if (!isa<InsertElementInst>(In) && !isa<ExtractElementInst>(In)) 5357 continue; 5358 5359 // Check if we can replace this instruction with any of the 5360 // visited instructions. 5361 for (Instruction *v : Visited) { 5362 if (In->isIdenticalTo(v) && 5363 DT->dominates(v->getParent(), In->getParent())) { 5364 In->replaceAllUsesWith(v); 5365 eraseInstruction(In); 5366 In = nullptr; 5367 break; 5368 } 5369 } 5370 if (In) { 5371 assert(!is_contained(Visited, In)); 5372 Visited.push_back(In); 5373 } 5374 } 5375 } 5376 CSEBlocks.clear(); 5377 GatherSeq.clear(); 5378 } 5379 5380 // Groups the instructions to a bundle (which is then a single scheduling entity) 5381 // and schedules instructions until the bundle gets ready. 5382 Optional<BoUpSLP::ScheduleData *> 5383 BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 5384 const InstructionsState &S) { 5385 if (isa<PHINode>(S.OpValue)) 5386 return nullptr; 5387 5388 // Initialize the instruction bundle. 5389 Instruction *OldScheduleEnd = ScheduleEnd; 5390 ScheduleData *PrevInBundle = nullptr; 5391 ScheduleData *Bundle = nullptr; 5392 bool ReSchedule = false; 5393 LLVM_DEBUG(dbgs() << "SLP: bundle: " << *S.OpValue << "\n"); 5394 5395 auto &&TryScheduleBundle = [this, OldScheduleEnd, SLP](bool ReSchedule, 5396 ScheduleData *Bundle) { 5397 // The scheduling region got new instructions at the lower end (or it is a 5398 // new region for the first bundle). This makes it necessary to 5399 // recalculate all dependencies. 5400 // It is seldom that this needs to be done a second time after adding the 5401 // initial bundle to the region. 5402 if (ScheduleEnd != OldScheduleEnd) { 5403 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) 5404 doForAllOpcodes(I, [](ScheduleData *SD) { SD->clearDependencies(); }); 5405 ReSchedule = true; 5406 } 5407 if (ReSchedule) { 5408 resetSchedule(); 5409 initialFillReadyList(ReadyInsts); 5410 } 5411 if (Bundle) { 5412 LLVM_DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle 5413 << " in block " << BB->getName() << "\n"); 5414 calculateDependencies(Bundle, /*InsertInReadyList=*/true, SLP); 5415 } 5416 5417 // Now try to schedule the new bundle or (if no bundle) just calculate 5418 // dependencies. As soon as the bundle is "ready" it means that there are no 5419 // cyclic dependencies and we can schedule it. Note that's important that we 5420 // don't "schedule" the bundle yet (see cancelScheduling). 5421 while (((!Bundle && ReSchedule) || (Bundle && !Bundle->isReady())) && 5422 !ReadyInsts.empty()) { 5423 ScheduleData *Picked = ReadyInsts.pop_back_val(); 5424 if (Picked->isSchedulingEntity() && Picked->isReady()) 5425 schedule(Picked, ReadyInsts); 5426 } 5427 }; 5428 5429 // Make sure that the scheduling region contains all 5430 // instructions of the bundle. 5431 for (Value *V : VL) { 5432 if (!extendSchedulingRegion(V, S)) { 5433 // If the scheduling region got new instructions at the lower end (or it 5434 // is a new region for the first bundle). This makes it necessary to 5435 // recalculate all dependencies. 5436 // Otherwise the compiler may crash trying to incorrectly calculate 5437 // dependencies and emit instruction in the wrong order at the actual 5438 // scheduling. 5439 TryScheduleBundle(/*ReSchedule=*/false, nullptr); 5440 return None; 5441 } 5442 } 5443 5444 for (Value *V : VL) { 5445 ScheduleData *BundleMember = getScheduleData(V); 5446 assert(BundleMember && 5447 "no ScheduleData for bundle member (maybe not in same basic block)"); 5448 if (BundleMember->IsScheduled) { 5449 // A bundle member was scheduled as single instruction before and now 5450 // needs to be scheduled as part of the bundle. We just get rid of the 5451 // existing schedule. 5452 LLVM_DEBUG(dbgs() << "SLP: reset schedule because " << *BundleMember 5453 << " was already scheduled\n"); 5454 ReSchedule = true; 5455 } 5456 assert(BundleMember->isSchedulingEntity() && 5457 "bundle member already part of other bundle"); 5458 if (PrevInBundle) { 5459 PrevInBundle->NextInBundle = BundleMember; 5460 } else { 5461 Bundle = BundleMember; 5462 } 5463 BundleMember->UnscheduledDepsInBundle = 0; 5464 Bundle->UnscheduledDepsInBundle += BundleMember->UnscheduledDeps; 5465 5466 // Group the instructions to a bundle. 5467 BundleMember->FirstInBundle = Bundle; 5468 PrevInBundle = BundleMember; 5469 } 5470 assert(Bundle && "Failed to find schedule bundle"); 5471 TryScheduleBundle(ReSchedule, Bundle); 5472 if (!Bundle->isReady()) { 5473 cancelScheduling(VL, S.OpValue); 5474 return None; 5475 } 5476 return Bundle; 5477 } 5478 5479 void BoUpSLP::BlockScheduling::cancelScheduling(ArrayRef<Value *> VL, 5480 Value *OpValue) { 5481 if (isa<PHINode>(OpValue)) 5482 return; 5483 5484 ScheduleData *Bundle = getScheduleData(OpValue); 5485 LLVM_DEBUG(dbgs() << "SLP: cancel scheduling of " << *Bundle << "\n"); 5486 assert(!Bundle->IsScheduled && 5487 "Can't cancel bundle which is already scheduled"); 5488 assert(Bundle->isSchedulingEntity() && Bundle->isPartOfBundle() && 5489 "tried to unbundle something which is not a bundle"); 5490 5491 // Un-bundle: make single instructions out of the bundle. 5492 ScheduleData *BundleMember = Bundle; 5493 while (BundleMember) { 5494 assert(BundleMember->FirstInBundle == Bundle && "corrupt bundle links"); 5495 BundleMember->FirstInBundle = BundleMember; 5496 ScheduleData *Next = BundleMember->NextInBundle; 5497 BundleMember->NextInBundle = nullptr; 5498 BundleMember->UnscheduledDepsInBundle = BundleMember->UnscheduledDeps; 5499 if (BundleMember->UnscheduledDepsInBundle == 0) { 5500 ReadyInsts.insert(BundleMember); 5501 } 5502 BundleMember = Next; 5503 } 5504 } 5505 5506 BoUpSLP::ScheduleData *BoUpSLP::BlockScheduling::allocateScheduleDataChunks() { 5507 // Allocate a new ScheduleData for the instruction. 5508 if (ChunkPos >= ChunkSize) { 5509 ScheduleDataChunks.push_back(std::make_unique<ScheduleData[]>(ChunkSize)); 5510 ChunkPos = 0; 5511 } 5512 return &(ScheduleDataChunks.back()[ChunkPos++]); 5513 } 5514 5515 bool BoUpSLP::BlockScheduling::extendSchedulingRegion(Value *V, 5516 const InstructionsState &S) { 5517 if (getScheduleData(V, isOneOf(S, V))) 5518 return true; 5519 Instruction *I = dyn_cast<Instruction>(V); 5520 assert(I && "bundle member must be an instruction"); 5521 assert(!isa<PHINode>(I) && "phi nodes don't need to be scheduled"); 5522 auto &&CheckSheduleForI = [this, &S](Instruction *I) -> bool { 5523 ScheduleData *ISD = getScheduleData(I); 5524 if (!ISD) 5525 return false; 5526 assert(isInSchedulingRegion(ISD) && 5527 "ScheduleData not in scheduling region"); 5528 ScheduleData *SD = allocateScheduleDataChunks(); 5529 SD->Inst = I; 5530 SD->init(SchedulingRegionID, S.OpValue); 5531 ExtraScheduleDataMap[I][S.OpValue] = SD; 5532 return true; 5533 }; 5534 if (CheckSheduleForI(I)) 5535 return true; 5536 if (!ScheduleStart) { 5537 // It's the first instruction in the new region. 5538 initScheduleData(I, I->getNextNode(), nullptr, nullptr); 5539 ScheduleStart = I; 5540 ScheduleEnd = I->getNextNode(); 5541 if (isOneOf(S, I) != I) 5542 CheckSheduleForI(I); 5543 assert(ScheduleEnd && "tried to vectorize a terminator?"); 5544 LLVM_DEBUG(dbgs() << "SLP: initialize schedule region to " << *I << "\n"); 5545 return true; 5546 } 5547 // Search up and down at the same time, because we don't know if the new 5548 // instruction is above or below the existing scheduling region. 5549 BasicBlock::reverse_iterator UpIter = 5550 ++ScheduleStart->getIterator().getReverse(); 5551 BasicBlock::reverse_iterator UpperEnd = BB->rend(); 5552 BasicBlock::iterator DownIter = ScheduleEnd->getIterator(); 5553 BasicBlock::iterator LowerEnd = BB->end(); 5554 while (UpIter != UpperEnd && DownIter != LowerEnd && &*UpIter != I && 5555 &*DownIter != I) { 5556 if (++ScheduleRegionSize > ScheduleRegionSizeLimit) { 5557 LLVM_DEBUG(dbgs() << "SLP: exceeded schedule region size limit\n"); 5558 return false; 5559 } 5560 5561 ++UpIter; 5562 ++DownIter; 5563 } 5564 if (DownIter == LowerEnd || (UpIter != UpperEnd && &*UpIter == I)) { 5565 assert(I->getParent() == ScheduleStart->getParent() && 5566 "Instruction is in wrong basic block."); 5567 initScheduleData(I, ScheduleStart, nullptr, FirstLoadStoreInRegion); 5568 ScheduleStart = I; 5569 if (isOneOf(S, I) != I) 5570 CheckSheduleForI(I); 5571 LLVM_DEBUG(dbgs() << "SLP: extend schedule region start to " << *I 5572 << "\n"); 5573 return true; 5574 } 5575 assert((UpIter == UpperEnd || (DownIter != LowerEnd && &*DownIter == I)) && 5576 "Expected to reach top of the basic block or instruction down the " 5577 "lower end."); 5578 assert(I->getParent() == ScheduleEnd->getParent() && 5579 "Instruction is in wrong basic block."); 5580 initScheduleData(ScheduleEnd, I->getNextNode(), LastLoadStoreInRegion, 5581 nullptr); 5582 ScheduleEnd = I->getNextNode(); 5583 if (isOneOf(S, I) != I) 5584 CheckSheduleForI(I); 5585 assert(ScheduleEnd && "tried to vectorize a terminator?"); 5586 LLVM_DEBUG(dbgs() << "SLP: extend schedule region end to " << *I << "\n"); 5587 return true; 5588 } 5589 5590 void BoUpSLP::BlockScheduling::initScheduleData(Instruction *FromI, 5591 Instruction *ToI, 5592 ScheduleData *PrevLoadStore, 5593 ScheduleData *NextLoadStore) { 5594 ScheduleData *CurrentLoadStore = PrevLoadStore; 5595 for (Instruction *I = FromI; I != ToI; I = I->getNextNode()) { 5596 ScheduleData *SD = ScheduleDataMap[I]; 5597 if (!SD) { 5598 SD = allocateScheduleDataChunks(); 5599 ScheduleDataMap[I] = SD; 5600 SD->Inst = I; 5601 } 5602 assert(!isInSchedulingRegion(SD) && 5603 "new ScheduleData already in scheduling region"); 5604 SD->init(SchedulingRegionID, I); 5605 5606 if (I->mayReadOrWriteMemory() && 5607 (!isa<IntrinsicInst>(I) || 5608 (cast<IntrinsicInst>(I)->getIntrinsicID() != Intrinsic::sideeffect && 5609 cast<IntrinsicInst>(I)->getIntrinsicID() != 5610 Intrinsic::pseudoprobe))) { 5611 // Update the linked list of memory accessing instructions. 5612 if (CurrentLoadStore) { 5613 CurrentLoadStore->NextLoadStore = SD; 5614 } else { 5615 FirstLoadStoreInRegion = SD; 5616 } 5617 CurrentLoadStore = SD; 5618 } 5619 } 5620 if (NextLoadStore) { 5621 if (CurrentLoadStore) 5622 CurrentLoadStore->NextLoadStore = NextLoadStore; 5623 } else { 5624 LastLoadStoreInRegion = CurrentLoadStore; 5625 } 5626 } 5627 5628 void BoUpSLP::BlockScheduling::calculateDependencies(ScheduleData *SD, 5629 bool InsertInReadyList, 5630 BoUpSLP *SLP) { 5631 assert(SD->isSchedulingEntity()); 5632 5633 SmallVector<ScheduleData *, 10> WorkList; 5634 WorkList.push_back(SD); 5635 5636 while (!WorkList.empty()) { 5637 ScheduleData *SD = WorkList.pop_back_val(); 5638 5639 ScheduleData *BundleMember = SD; 5640 while (BundleMember) { 5641 assert(isInSchedulingRegion(BundleMember)); 5642 if (!BundleMember->hasValidDependencies()) { 5643 5644 LLVM_DEBUG(dbgs() << "SLP: update deps of " << *BundleMember 5645 << "\n"); 5646 BundleMember->Dependencies = 0; 5647 BundleMember->resetUnscheduledDeps(); 5648 5649 // Handle def-use chain dependencies. 5650 if (BundleMember->OpValue != BundleMember->Inst) { 5651 ScheduleData *UseSD = getScheduleData(BundleMember->Inst); 5652 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 5653 BundleMember->Dependencies++; 5654 ScheduleData *DestBundle = UseSD->FirstInBundle; 5655 if (!DestBundle->IsScheduled) 5656 BundleMember->incrementUnscheduledDeps(1); 5657 if (!DestBundle->hasValidDependencies()) 5658 WorkList.push_back(DestBundle); 5659 } 5660 } else { 5661 for (User *U : BundleMember->Inst->users()) { 5662 if (isa<Instruction>(U)) { 5663 ScheduleData *UseSD = getScheduleData(U); 5664 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 5665 BundleMember->Dependencies++; 5666 ScheduleData *DestBundle = UseSD->FirstInBundle; 5667 if (!DestBundle->IsScheduled) 5668 BundleMember->incrementUnscheduledDeps(1); 5669 if (!DestBundle->hasValidDependencies()) 5670 WorkList.push_back(DestBundle); 5671 } 5672 } else { 5673 // I'm not sure if this can ever happen. But we need to be safe. 5674 // This lets the instruction/bundle never be scheduled and 5675 // eventually disable vectorization. 5676 BundleMember->Dependencies++; 5677 BundleMember->incrementUnscheduledDeps(1); 5678 } 5679 } 5680 } 5681 5682 // Handle the memory dependencies. 5683 ScheduleData *DepDest = BundleMember->NextLoadStore; 5684 if (DepDest) { 5685 Instruction *SrcInst = BundleMember->Inst; 5686 MemoryLocation SrcLoc = getLocation(SrcInst, SLP->AA); 5687 bool SrcMayWrite = BundleMember->Inst->mayWriteToMemory(); 5688 unsigned numAliased = 0; 5689 unsigned DistToSrc = 1; 5690 5691 while (DepDest) { 5692 assert(isInSchedulingRegion(DepDest)); 5693 5694 // We have two limits to reduce the complexity: 5695 // 1) AliasedCheckLimit: It's a small limit to reduce calls to 5696 // SLP->isAliased (which is the expensive part in this loop). 5697 // 2) MaxMemDepDistance: It's for very large blocks and it aborts 5698 // the whole loop (even if the loop is fast, it's quadratic). 5699 // It's important for the loop break condition (see below) to 5700 // check this limit even between two read-only instructions. 5701 if (DistToSrc >= MaxMemDepDistance || 5702 ((SrcMayWrite || DepDest->Inst->mayWriteToMemory()) && 5703 (numAliased >= AliasedCheckLimit || 5704 SLP->isAliased(SrcLoc, SrcInst, DepDest->Inst)))) { 5705 5706 // We increment the counter only if the locations are aliased 5707 // (instead of counting all alias checks). This gives a better 5708 // balance between reduced runtime and accurate dependencies. 5709 numAliased++; 5710 5711 DepDest->MemoryDependencies.push_back(BundleMember); 5712 BundleMember->Dependencies++; 5713 ScheduleData *DestBundle = DepDest->FirstInBundle; 5714 if (!DestBundle->IsScheduled) { 5715 BundleMember->incrementUnscheduledDeps(1); 5716 } 5717 if (!DestBundle->hasValidDependencies()) { 5718 WorkList.push_back(DestBundle); 5719 } 5720 } 5721 DepDest = DepDest->NextLoadStore; 5722 5723 // Example, explaining the loop break condition: Let's assume our 5724 // starting instruction is i0 and MaxMemDepDistance = 3. 5725 // 5726 // +--------v--v--v 5727 // i0,i1,i2,i3,i4,i5,i6,i7,i8 5728 // +--------^--^--^ 5729 // 5730 // MaxMemDepDistance let us stop alias-checking at i3 and we add 5731 // dependencies from i0 to i3,i4,.. (even if they are not aliased). 5732 // Previously we already added dependencies from i3 to i6,i7,i8 5733 // (because of MaxMemDepDistance). As we added a dependency from 5734 // i0 to i3, we have transitive dependencies from i0 to i6,i7,i8 5735 // and we can abort this loop at i6. 5736 if (DistToSrc >= 2 * MaxMemDepDistance) 5737 break; 5738 DistToSrc++; 5739 } 5740 } 5741 } 5742 BundleMember = BundleMember->NextInBundle; 5743 } 5744 if (InsertInReadyList && SD->isReady()) { 5745 ReadyInsts.push_back(SD); 5746 LLVM_DEBUG(dbgs() << "SLP: gets ready on update: " << *SD->Inst 5747 << "\n"); 5748 } 5749 } 5750 } 5751 5752 void BoUpSLP::BlockScheduling::resetSchedule() { 5753 assert(ScheduleStart && 5754 "tried to reset schedule on block which has not been scheduled"); 5755 for (Instruction *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 5756 doForAllOpcodes(I, [&](ScheduleData *SD) { 5757 assert(isInSchedulingRegion(SD) && 5758 "ScheduleData not in scheduling region"); 5759 SD->IsScheduled = false; 5760 SD->resetUnscheduledDeps(); 5761 }); 5762 } 5763 ReadyInsts.clear(); 5764 } 5765 5766 void BoUpSLP::scheduleBlock(BlockScheduling *BS) { 5767 if (!BS->ScheduleStart) 5768 return; 5769 5770 LLVM_DEBUG(dbgs() << "SLP: schedule block " << BS->BB->getName() << "\n"); 5771 5772 BS->resetSchedule(); 5773 5774 // For the real scheduling we use a more sophisticated ready-list: it is 5775 // sorted by the original instruction location. This lets the final schedule 5776 // be as close as possible to the original instruction order. 5777 struct ScheduleDataCompare { 5778 bool operator()(ScheduleData *SD1, ScheduleData *SD2) const { 5779 return SD2->SchedulingPriority < SD1->SchedulingPriority; 5780 } 5781 }; 5782 std::set<ScheduleData *, ScheduleDataCompare> ReadyInsts; 5783 5784 // Ensure that all dependency data is updated and fill the ready-list with 5785 // initial instructions. 5786 int Idx = 0; 5787 int NumToSchedule = 0; 5788 for (auto *I = BS->ScheduleStart; I != BS->ScheduleEnd; 5789 I = I->getNextNode()) { 5790 BS->doForAllOpcodes(I, [this, &Idx, &NumToSchedule, BS](ScheduleData *SD) { 5791 assert(SD->isPartOfBundle() == 5792 (getTreeEntry(SD->Inst) != nullptr) && 5793 "scheduler and vectorizer bundle mismatch"); 5794 SD->FirstInBundle->SchedulingPriority = Idx++; 5795 if (SD->isSchedulingEntity()) { 5796 BS->calculateDependencies(SD, false, this); 5797 NumToSchedule++; 5798 } 5799 }); 5800 } 5801 BS->initialFillReadyList(ReadyInsts); 5802 5803 Instruction *LastScheduledInst = BS->ScheduleEnd; 5804 5805 // Do the "real" scheduling. 5806 while (!ReadyInsts.empty()) { 5807 ScheduleData *picked = *ReadyInsts.begin(); 5808 ReadyInsts.erase(ReadyInsts.begin()); 5809 5810 // Move the scheduled instruction(s) to their dedicated places, if not 5811 // there yet. 5812 ScheduleData *BundleMember = picked; 5813 while (BundleMember) { 5814 Instruction *pickedInst = BundleMember->Inst; 5815 if (LastScheduledInst->getNextNode() != pickedInst) { 5816 BS->BB->getInstList().remove(pickedInst); 5817 BS->BB->getInstList().insert(LastScheduledInst->getIterator(), 5818 pickedInst); 5819 } 5820 LastScheduledInst = pickedInst; 5821 BundleMember = BundleMember->NextInBundle; 5822 } 5823 5824 BS->schedule(picked, ReadyInsts); 5825 NumToSchedule--; 5826 } 5827 assert(NumToSchedule == 0 && "could not schedule all instructions"); 5828 5829 // Avoid duplicate scheduling of the block. 5830 BS->ScheduleStart = nullptr; 5831 } 5832 5833 unsigned BoUpSLP::getVectorElementSize(Value *V) { 5834 // If V is a store, just return the width of the stored value (or value 5835 // truncated just before storing) without traversing the expression tree. 5836 // This is the common case. 5837 if (auto *Store = dyn_cast<StoreInst>(V)) { 5838 if (auto *Trunc = dyn_cast<TruncInst>(Store->getValueOperand())) 5839 return DL->getTypeSizeInBits(Trunc->getSrcTy()); 5840 return DL->getTypeSizeInBits(Store->getValueOperand()->getType()); 5841 } 5842 5843 auto E = InstrElementSize.find(V); 5844 if (E != InstrElementSize.end()) 5845 return E->second; 5846 5847 // If V is not a store, we can traverse the expression tree to find loads 5848 // that feed it. The type of the loaded value may indicate a more suitable 5849 // width than V's type. We want to base the vector element size on the width 5850 // of memory operations where possible. 5851 SmallVector<std::pair<Instruction *, BasicBlock *>, 16> Worklist; 5852 SmallPtrSet<Instruction *, 16> Visited; 5853 if (auto *I = dyn_cast<Instruction>(V)) { 5854 Worklist.emplace_back(I, I->getParent()); 5855 Visited.insert(I); 5856 } 5857 5858 // Traverse the expression tree in bottom-up order looking for loads. If we 5859 // encounter an instruction we don't yet handle, we give up. 5860 auto Width = 0u; 5861 while (!Worklist.empty()) { 5862 Instruction *I; 5863 BasicBlock *Parent; 5864 std::tie(I, Parent) = Worklist.pop_back_val(); 5865 5866 // We should only be looking at scalar instructions here. If the current 5867 // instruction has a vector type, skip. 5868 auto *Ty = I->getType(); 5869 if (isa<VectorType>(Ty)) 5870 continue; 5871 5872 // If the current instruction is a load, update MaxWidth to reflect the 5873 // width of the loaded value. 5874 if (isa<LoadInst>(I) || isa<ExtractElementInst>(I) || 5875 isa<ExtractValueInst>(I)) 5876 Width = std::max<unsigned>(Width, DL->getTypeSizeInBits(Ty)); 5877 5878 // Otherwise, we need to visit the operands of the instruction. We only 5879 // handle the interesting cases from buildTree here. If an operand is an 5880 // instruction we haven't yet visited and from the same basic block as the 5881 // user or the use is a PHI node, we add it to the worklist. 5882 else if (isa<PHINode>(I) || isa<CastInst>(I) || isa<GetElementPtrInst>(I) || 5883 isa<CmpInst>(I) || isa<SelectInst>(I) || isa<BinaryOperator>(I) || 5884 isa<UnaryOperator>(I)) { 5885 for (Use &U : I->operands()) 5886 if (auto *J = dyn_cast<Instruction>(U.get())) 5887 if (Visited.insert(J).second && 5888 (isa<PHINode>(I) || J->getParent() == Parent)) 5889 Worklist.emplace_back(J, J->getParent()); 5890 } else { 5891 break; 5892 } 5893 } 5894 5895 // If we didn't encounter a memory access in the expression tree, or if we 5896 // gave up for some reason, just return the width of V. Otherwise, return the 5897 // maximum width we found. 5898 if (!Width) { 5899 if (auto *CI = dyn_cast<CmpInst>(V)) 5900 V = CI->getOperand(0); 5901 Width = DL->getTypeSizeInBits(V->getType()); 5902 } 5903 5904 for (Instruction *I : Visited) 5905 InstrElementSize[I] = Width; 5906 5907 return Width; 5908 } 5909 5910 // Determine if a value V in a vectorizable expression Expr can be demoted to a 5911 // smaller type with a truncation. We collect the values that will be demoted 5912 // in ToDemote and additional roots that require investigating in Roots. 5913 static bool collectValuesToDemote(Value *V, SmallPtrSetImpl<Value *> &Expr, 5914 SmallVectorImpl<Value *> &ToDemote, 5915 SmallVectorImpl<Value *> &Roots) { 5916 // We can always demote constants. 5917 if (isa<Constant>(V)) { 5918 ToDemote.push_back(V); 5919 return true; 5920 } 5921 5922 // If the value is not an instruction in the expression with only one use, it 5923 // cannot be demoted. 5924 auto *I = dyn_cast<Instruction>(V); 5925 if (!I || !I->hasOneUse() || !Expr.count(I)) 5926 return false; 5927 5928 switch (I->getOpcode()) { 5929 5930 // We can always demote truncations and extensions. Since truncations can 5931 // seed additional demotion, we save the truncated value. 5932 case Instruction::Trunc: 5933 Roots.push_back(I->getOperand(0)); 5934 break; 5935 case Instruction::ZExt: 5936 case Instruction::SExt: 5937 break; 5938 5939 // We can demote certain binary operations if we can demote both of their 5940 // operands. 5941 case Instruction::Add: 5942 case Instruction::Sub: 5943 case Instruction::Mul: 5944 case Instruction::And: 5945 case Instruction::Or: 5946 case Instruction::Xor: 5947 if (!collectValuesToDemote(I->getOperand(0), Expr, ToDemote, Roots) || 5948 !collectValuesToDemote(I->getOperand(1), Expr, ToDemote, Roots)) 5949 return false; 5950 break; 5951 5952 // We can demote selects if we can demote their true and false values. 5953 case Instruction::Select: { 5954 SelectInst *SI = cast<SelectInst>(I); 5955 if (!collectValuesToDemote(SI->getTrueValue(), Expr, ToDemote, Roots) || 5956 !collectValuesToDemote(SI->getFalseValue(), Expr, ToDemote, Roots)) 5957 return false; 5958 break; 5959 } 5960 5961 // We can demote phis if we can demote all their incoming operands. Note that 5962 // we don't need to worry about cycles since we ensure single use above. 5963 case Instruction::PHI: { 5964 PHINode *PN = cast<PHINode>(I); 5965 for (Value *IncValue : PN->incoming_values()) 5966 if (!collectValuesToDemote(IncValue, Expr, ToDemote, Roots)) 5967 return false; 5968 break; 5969 } 5970 5971 // Otherwise, conservatively give up. 5972 default: 5973 return false; 5974 } 5975 5976 // Record the value that we can demote. 5977 ToDemote.push_back(V); 5978 return true; 5979 } 5980 5981 void BoUpSLP::computeMinimumValueSizes() { 5982 // If there are no external uses, the expression tree must be rooted by a 5983 // store. We can't demote in-memory values, so there is nothing to do here. 5984 if (ExternalUses.empty()) 5985 return; 5986 5987 // We only attempt to truncate integer expressions. 5988 auto &TreeRoot = VectorizableTree[0]->Scalars; 5989 auto *TreeRootIT = dyn_cast<IntegerType>(TreeRoot[0]->getType()); 5990 if (!TreeRootIT) 5991 return; 5992 5993 // If the expression is not rooted by a store, these roots should have 5994 // external uses. We will rely on InstCombine to rewrite the expression in 5995 // the narrower type. However, InstCombine only rewrites single-use values. 5996 // This means that if a tree entry other than a root is used externally, it 5997 // must have multiple uses and InstCombine will not rewrite it. The code 5998 // below ensures that only the roots are used externally. 5999 SmallPtrSet<Value *, 32> Expr(TreeRoot.begin(), TreeRoot.end()); 6000 for (auto &EU : ExternalUses) 6001 if (!Expr.erase(EU.Scalar)) 6002 return; 6003 if (!Expr.empty()) 6004 return; 6005 6006 // Collect the scalar values of the vectorizable expression. We will use this 6007 // context to determine which values can be demoted. If we see a truncation, 6008 // we mark it as seeding another demotion. 6009 for (auto &EntryPtr : VectorizableTree) 6010 Expr.insert(EntryPtr->Scalars.begin(), EntryPtr->Scalars.end()); 6011 6012 // Ensure the roots of the vectorizable tree don't form a cycle. They must 6013 // have a single external user that is not in the vectorizable tree. 6014 for (auto *Root : TreeRoot) 6015 if (!Root->hasOneUse() || Expr.count(*Root->user_begin())) 6016 return; 6017 6018 // Conservatively determine if we can actually truncate the roots of the 6019 // expression. Collect the values that can be demoted in ToDemote and 6020 // additional roots that require investigating in Roots. 6021 SmallVector<Value *, 32> ToDemote; 6022 SmallVector<Value *, 4> Roots; 6023 for (auto *Root : TreeRoot) 6024 if (!collectValuesToDemote(Root, Expr, ToDemote, Roots)) 6025 return; 6026 6027 // The maximum bit width required to represent all the values that can be 6028 // demoted without loss of precision. It would be safe to truncate the roots 6029 // of the expression to this width. 6030 auto MaxBitWidth = 8u; 6031 6032 // We first check if all the bits of the roots are demanded. If they're not, 6033 // we can truncate the roots to this narrower type. 6034 for (auto *Root : TreeRoot) { 6035 auto Mask = DB->getDemandedBits(cast<Instruction>(Root)); 6036 MaxBitWidth = std::max<unsigned>( 6037 Mask.getBitWidth() - Mask.countLeadingZeros(), MaxBitWidth); 6038 } 6039 6040 // True if the roots can be zero-extended back to their original type, rather 6041 // than sign-extended. We know that if the leading bits are not demanded, we 6042 // can safely zero-extend. So we initialize IsKnownPositive to True. 6043 bool IsKnownPositive = true; 6044 6045 // If all the bits of the roots are demanded, we can try a little harder to 6046 // compute a narrower type. This can happen, for example, if the roots are 6047 // getelementptr indices. InstCombine promotes these indices to the pointer 6048 // width. Thus, all their bits are technically demanded even though the 6049 // address computation might be vectorized in a smaller type. 6050 // 6051 // We start by looking at each entry that can be demoted. We compute the 6052 // maximum bit width required to store the scalar by using ValueTracking to 6053 // compute the number of high-order bits we can truncate. 6054 if (MaxBitWidth == DL->getTypeSizeInBits(TreeRoot[0]->getType()) && 6055 llvm::all_of(TreeRoot, [](Value *R) { 6056 assert(R->hasOneUse() && "Root should have only one use!"); 6057 return isa<GetElementPtrInst>(R->user_back()); 6058 })) { 6059 MaxBitWidth = 8u; 6060 6061 // Determine if the sign bit of all the roots is known to be zero. If not, 6062 // IsKnownPositive is set to False. 6063 IsKnownPositive = llvm::all_of(TreeRoot, [&](Value *R) { 6064 KnownBits Known = computeKnownBits(R, *DL); 6065 return Known.isNonNegative(); 6066 }); 6067 6068 // Determine the maximum number of bits required to store the scalar 6069 // values. 6070 for (auto *Scalar : ToDemote) { 6071 auto NumSignBits = ComputeNumSignBits(Scalar, *DL, 0, AC, nullptr, DT); 6072 auto NumTypeBits = DL->getTypeSizeInBits(Scalar->getType()); 6073 MaxBitWidth = std::max<unsigned>(NumTypeBits - NumSignBits, MaxBitWidth); 6074 } 6075 6076 // If we can't prove that the sign bit is zero, we must add one to the 6077 // maximum bit width to account for the unknown sign bit. This preserves 6078 // the existing sign bit so we can safely sign-extend the root back to the 6079 // original type. Otherwise, if we know the sign bit is zero, we will 6080 // zero-extend the root instead. 6081 // 6082 // FIXME: This is somewhat suboptimal, as there will be cases where adding 6083 // one to the maximum bit width will yield a larger-than-necessary 6084 // type. In general, we need to add an extra bit only if we can't 6085 // prove that the upper bit of the original type is equal to the 6086 // upper bit of the proposed smaller type. If these two bits are the 6087 // same (either zero or one) we know that sign-extending from the 6088 // smaller type will result in the same value. Here, since we can't 6089 // yet prove this, we are just making the proposed smaller type 6090 // larger to ensure correctness. 6091 if (!IsKnownPositive) 6092 ++MaxBitWidth; 6093 } 6094 6095 // Round MaxBitWidth up to the next power-of-two. 6096 if (!isPowerOf2_64(MaxBitWidth)) 6097 MaxBitWidth = NextPowerOf2(MaxBitWidth); 6098 6099 // If the maximum bit width we compute is less than the with of the roots' 6100 // type, we can proceed with the narrowing. Otherwise, do nothing. 6101 if (MaxBitWidth >= TreeRootIT->getBitWidth()) 6102 return; 6103 6104 // If we can truncate the root, we must collect additional values that might 6105 // be demoted as a result. That is, those seeded by truncations we will 6106 // modify. 6107 while (!Roots.empty()) 6108 collectValuesToDemote(Roots.pop_back_val(), Expr, ToDemote, Roots); 6109 6110 // Finally, map the values we can demote to the maximum bit with we computed. 6111 for (auto *Scalar : ToDemote) 6112 MinBWs[Scalar] = std::make_pair(MaxBitWidth, !IsKnownPositive); 6113 } 6114 6115 namespace { 6116 6117 /// The SLPVectorizer Pass. 6118 struct SLPVectorizer : public FunctionPass { 6119 SLPVectorizerPass Impl; 6120 6121 /// Pass identification, replacement for typeid 6122 static char ID; 6123 6124 explicit SLPVectorizer() : FunctionPass(ID) { 6125 initializeSLPVectorizerPass(*PassRegistry::getPassRegistry()); 6126 } 6127 6128 bool doInitialization(Module &M) override { 6129 return false; 6130 } 6131 6132 bool runOnFunction(Function &F) override { 6133 if (skipFunction(F)) 6134 return false; 6135 6136 auto *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 6137 auto *TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F); 6138 auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>(); 6139 auto *TLI = TLIP ? &TLIP->getTLI(F) : nullptr; 6140 auto *AA = &getAnalysis<AAResultsWrapperPass>().getAAResults(); 6141 auto *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 6142 auto *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 6143 auto *AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F); 6144 auto *DB = &getAnalysis<DemandedBitsWrapperPass>().getDemandedBits(); 6145 auto *ORE = &getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE(); 6146 6147 return Impl.runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 6148 } 6149 6150 void getAnalysisUsage(AnalysisUsage &AU) const override { 6151 FunctionPass::getAnalysisUsage(AU); 6152 AU.addRequired<AssumptionCacheTracker>(); 6153 AU.addRequired<ScalarEvolutionWrapperPass>(); 6154 AU.addRequired<AAResultsWrapperPass>(); 6155 AU.addRequired<TargetTransformInfoWrapperPass>(); 6156 AU.addRequired<LoopInfoWrapperPass>(); 6157 AU.addRequired<DominatorTreeWrapperPass>(); 6158 AU.addRequired<DemandedBitsWrapperPass>(); 6159 AU.addRequired<OptimizationRemarkEmitterWrapperPass>(); 6160 AU.addRequired<InjectTLIMappingsLegacy>(); 6161 AU.addPreserved<LoopInfoWrapperPass>(); 6162 AU.addPreserved<DominatorTreeWrapperPass>(); 6163 AU.addPreserved<AAResultsWrapperPass>(); 6164 AU.addPreserved<GlobalsAAWrapperPass>(); 6165 AU.setPreservesCFG(); 6166 } 6167 }; 6168 6169 } // end anonymous namespace 6170 6171 PreservedAnalyses SLPVectorizerPass::run(Function &F, FunctionAnalysisManager &AM) { 6172 auto *SE = &AM.getResult<ScalarEvolutionAnalysis>(F); 6173 auto *TTI = &AM.getResult<TargetIRAnalysis>(F); 6174 auto *TLI = AM.getCachedResult<TargetLibraryAnalysis>(F); 6175 auto *AA = &AM.getResult<AAManager>(F); 6176 auto *LI = &AM.getResult<LoopAnalysis>(F); 6177 auto *DT = &AM.getResult<DominatorTreeAnalysis>(F); 6178 auto *AC = &AM.getResult<AssumptionAnalysis>(F); 6179 auto *DB = &AM.getResult<DemandedBitsAnalysis>(F); 6180 auto *ORE = &AM.getResult<OptimizationRemarkEmitterAnalysis>(F); 6181 6182 bool Changed = runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 6183 if (!Changed) 6184 return PreservedAnalyses::all(); 6185 6186 PreservedAnalyses PA; 6187 PA.preserveSet<CFGAnalyses>(); 6188 PA.preserve<AAManager>(); 6189 PA.preserve<GlobalsAA>(); 6190 return PA; 6191 } 6192 6193 bool SLPVectorizerPass::runImpl(Function &F, ScalarEvolution *SE_, 6194 TargetTransformInfo *TTI_, 6195 TargetLibraryInfo *TLI_, AAResults *AA_, 6196 LoopInfo *LI_, DominatorTree *DT_, 6197 AssumptionCache *AC_, DemandedBits *DB_, 6198 OptimizationRemarkEmitter *ORE_) { 6199 if (!RunSLPVectorization) 6200 return false; 6201 SE = SE_; 6202 TTI = TTI_; 6203 TLI = TLI_; 6204 AA = AA_; 6205 LI = LI_; 6206 DT = DT_; 6207 AC = AC_; 6208 DB = DB_; 6209 DL = &F.getParent()->getDataLayout(); 6210 6211 Stores.clear(); 6212 GEPs.clear(); 6213 bool Changed = false; 6214 6215 // If the target claims to have no vector registers don't attempt 6216 // vectorization. 6217 if (!TTI->getNumberOfRegisters(TTI->getRegisterClassForType(true))) 6218 return false; 6219 6220 // Don't vectorize when the attribute NoImplicitFloat is used. 6221 if (F.hasFnAttribute(Attribute::NoImplicitFloat)) 6222 return false; 6223 6224 LLVM_DEBUG(dbgs() << "SLP: Analyzing blocks in " << F.getName() << ".\n"); 6225 6226 // Use the bottom up slp vectorizer to construct chains that start with 6227 // store instructions. 6228 BoUpSLP R(&F, SE, TTI, TLI, AA, LI, DT, AC, DB, DL, ORE_); 6229 6230 // A general note: the vectorizer must use BoUpSLP::eraseInstruction() to 6231 // delete instructions. 6232 6233 // Scan the blocks in the function in post order. 6234 for (auto BB : post_order(&F.getEntryBlock())) { 6235 collectSeedInstructions(BB); 6236 6237 // Vectorize trees that end at stores. 6238 if (!Stores.empty()) { 6239 LLVM_DEBUG(dbgs() << "SLP: Found stores for " << Stores.size() 6240 << " underlying objects.\n"); 6241 Changed |= vectorizeStoreChains(R); 6242 } 6243 6244 // Vectorize trees that end at reductions. 6245 Changed |= vectorizeChainsInBlock(BB, R); 6246 6247 // Vectorize the index computations of getelementptr instructions. This 6248 // is primarily intended to catch gather-like idioms ending at 6249 // non-consecutive loads. 6250 if (!GEPs.empty()) { 6251 LLVM_DEBUG(dbgs() << "SLP: Found GEPs for " << GEPs.size() 6252 << " underlying objects.\n"); 6253 Changed |= vectorizeGEPIndices(BB, R); 6254 } 6255 } 6256 6257 if (Changed) { 6258 R.optimizeGatherSequence(); 6259 LLVM_DEBUG(dbgs() << "SLP: vectorized \"" << F.getName() << "\"\n"); 6260 } 6261 return Changed; 6262 } 6263 6264 bool SLPVectorizerPass::vectorizeStoreChain(ArrayRef<Value *> Chain, BoUpSLP &R, 6265 unsigned Idx) { 6266 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " << Chain.size() 6267 << "\n"); 6268 const unsigned Sz = R.getVectorElementSize(Chain[0]); 6269 const unsigned MinVF = R.getMinVecRegSize() / Sz; 6270 unsigned VF = Chain.size(); 6271 6272 if (!isPowerOf2_32(Sz) || !isPowerOf2_32(VF) || VF < 2 || VF < MinVF) 6273 return false; 6274 6275 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << VF << " stores at offset " << Idx 6276 << "\n"); 6277 6278 R.buildTree(Chain); 6279 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 6280 // TODO: Handle orders of size less than number of elements in the vector. 6281 if (Order && Order->size() == Chain.size()) { 6282 // TODO: reorder tree nodes without tree rebuilding. 6283 SmallVector<Value *, 4> ReorderedOps(Chain.rbegin(), Chain.rend()); 6284 llvm::transform(*Order, ReorderedOps.begin(), 6285 [Chain](const unsigned Idx) { return Chain[Idx]; }); 6286 R.buildTree(ReorderedOps); 6287 } 6288 if (R.isTreeTinyAndNotFullyVectorizable()) 6289 return false; 6290 if (R.isLoadCombineCandidate()) 6291 return false; 6292 6293 R.computeMinimumValueSizes(); 6294 6295 InstructionCost Cost = R.getTreeCost(); 6296 6297 LLVM_DEBUG(dbgs() << "SLP: Found cost = " << Cost << " for VF =" << VF << "\n"); 6298 if (Cost < -SLPCostThreshold) { 6299 LLVM_DEBUG(dbgs() << "SLP: Decided to vectorize cost = " << Cost << "\n"); 6300 6301 using namespace ore; 6302 6303 R.getORE()->emit(OptimizationRemark(SV_NAME, "StoresVectorized", 6304 cast<StoreInst>(Chain[0])) 6305 << "Stores SLP vectorized with cost " << NV("Cost", Cost) 6306 << " and with tree size " 6307 << NV("TreeSize", R.getTreeSize())); 6308 6309 R.vectorizeTree(); 6310 return true; 6311 } 6312 6313 return false; 6314 } 6315 6316 bool SLPVectorizerPass::vectorizeStores(ArrayRef<StoreInst *> Stores, 6317 BoUpSLP &R) { 6318 // We may run into multiple chains that merge into a single chain. We mark the 6319 // stores that we vectorized so that we don't visit the same store twice. 6320 BoUpSLP::ValueSet VectorizedStores; 6321 bool Changed = false; 6322 6323 int E = Stores.size(); 6324 SmallBitVector Tails(E, false); 6325 int MaxIter = MaxStoreLookup.getValue(); 6326 SmallVector<std::pair<int, int>, 16> ConsecutiveChain( 6327 E, std::make_pair(E, INT_MAX)); 6328 SmallVector<SmallBitVector, 4> CheckedPairs(E, SmallBitVector(E, false)); 6329 int IterCnt; 6330 auto &&FindConsecutiveAccess = [this, &Stores, &Tails, &IterCnt, MaxIter, 6331 &CheckedPairs, 6332 &ConsecutiveChain](int K, int Idx) { 6333 if (IterCnt >= MaxIter) 6334 return true; 6335 if (CheckedPairs[Idx].test(K)) 6336 return ConsecutiveChain[K].second == 1 && 6337 ConsecutiveChain[K].first == Idx; 6338 ++IterCnt; 6339 CheckedPairs[Idx].set(K); 6340 CheckedPairs[K].set(Idx); 6341 Optional<int> Diff = getPointersDiff(Stores[K]->getPointerOperand(), 6342 Stores[Idx]->getPointerOperand(), *DL, 6343 *SE, /*StrictCheck=*/true); 6344 if (!Diff || *Diff == 0) 6345 return false; 6346 int Val = *Diff; 6347 if (Val < 0) { 6348 if (ConsecutiveChain[Idx].second > -Val) { 6349 Tails.set(K); 6350 ConsecutiveChain[Idx] = std::make_pair(K, -Val); 6351 } 6352 return false; 6353 } 6354 if (ConsecutiveChain[K].second <= Val) 6355 return false; 6356 6357 Tails.set(Idx); 6358 ConsecutiveChain[K] = std::make_pair(Idx, Val); 6359 return Val == 1; 6360 }; 6361 // Do a quadratic search on all of the given stores in reverse order and find 6362 // all of the pairs of stores that follow each other. 6363 for (int Idx = E - 1; Idx >= 0; --Idx) { 6364 // If a store has multiple consecutive store candidates, search according 6365 // to the sequence: Idx-1, Idx+1, Idx-2, Idx+2, ... 6366 // This is because usually pairing with immediate succeeding or preceding 6367 // candidate create the best chance to find slp vectorization opportunity. 6368 const int MaxLookDepth = std::max(E - Idx, Idx + 1); 6369 IterCnt = 0; 6370 for (int Offset = 1, F = MaxLookDepth; Offset < F; ++Offset) 6371 if ((Idx >= Offset && FindConsecutiveAccess(Idx - Offset, Idx)) || 6372 (Idx + Offset < E && FindConsecutiveAccess(Idx + Offset, Idx))) 6373 break; 6374 } 6375 6376 // Tracks if we tried to vectorize stores starting from the given tail 6377 // already. 6378 SmallBitVector TriedTails(E, false); 6379 // For stores that start but don't end a link in the chain: 6380 for (int Cnt = E; Cnt > 0; --Cnt) { 6381 int I = Cnt - 1; 6382 if (ConsecutiveChain[I].first == E || Tails.test(I)) 6383 continue; 6384 // We found a store instr that starts a chain. Now follow the chain and try 6385 // to vectorize it. 6386 BoUpSLP::ValueList Operands; 6387 // Collect the chain into a list. 6388 while (I != E && !VectorizedStores.count(Stores[I])) { 6389 Operands.push_back(Stores[I]); 6390 Tails.set(I); 6391 if (ConsecutiveChain[I].second != 1) { 6392 // Mark the new end in the chain and go back, if required. It might be 6393 // required if the original stores come in reversed order, for example. 6394 if (ConsecutiveChain[I].first != E && 6395 Tails.test(ConsecutiveChain[I].first) && !TriedTails.test(I) && 6396 !VectorizedStores.count(Stores[ConsecutiveChain[I].first])) { 6397 TriedTails.set(I); 6398 Tails.reset(ConsecutiveChain[I].first); 6399 if (Cnt < ConsecutiveChain[I].first + 2) 6400 Cnt = ConsecutiveChain[I].first + 2; 6401 } 6402 break; 6403 } 6404 // Move to the next value in the chain. 6405 I = ConsecutiveChain[I].first; 6406 } 6407 assert(!Operands.empty() && "Expected non-empty list of stores."); 6408 6409 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 6410 unsigned EltSize = R.getVectorElementSize(Operands[0]); 6411 unsigned MaxElts = llvm::PowerOf2Floor(MaxVecRegSize / EltSize); 6412 6413 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / EltSize); 6414 unsigned MaxVF = std::min(R.getMaximumVF(EltSize, Instruction::Store), 6415 MaxElts); 6416 6417 // FIXME: Is division-by-2 the correct step? Should we assert that the 6418 // register size is a power-of-2? 6419 unsigned StartIdx = 0; 6420 for (unsigned Size = MaxVF; Size >= MinVF; Size /= 2) { 6421 for (unsigned Cnt = StartIdx, E = Operands.size(); Cnt + Size <= E;) { 6422 ArrayRef<Value *> Slice = makeArrayRef(Operands).slice(Cnt, Size); 6423 if (!VectorizedStores.count(Slice.front()) && 6424 !VectorizedStores.count(Slice.back()) && 6425 vectorizeStoreChain(Slice, R, Cnt)) { 6426 // Mark the vectorized stores so that we don't vectorize them again. 6427 VectorizedStores.insert(Slice.begin(), Slice.end()); 6428 Changed = true; 6429 // If we vectorized initial block, no need to try to vectorize it 6430 // again. 6431 if (Cnt == StartIdx) 6432 StartIdx += Size; 6433 Cnt += Size; 6434 continue; 6435 } 6436 ++Cnt; 6437 } 6438 // Check if the whole array was vectorized already - exit. 6439 if (StartIdx >= Operands.size()) 6440 break; 6441 } 6442 } 6443 6444 return Changed; 6445 } 6446 6447 void SLPVectorizerPass::collectSeedInstructions(BasicBlock *BB) { 6448 // Initialize the collections. We will make a single pass over the block. 6449 Stores.clear(); 6450 GEPs.clear(); 6451 6452 // Visit the store and getelementptr instructions in BB and organize them in 6453 // Stores and GEPs according to the underlying objects of their pointer 6454 // operands. 6455 for (Instruction &I : *BB) { 6456 // Ignore store instructions that are volatile or have a pointer operand 6457 // that doesn't point to a scalar type. 6458 if (auto *SI = dyn_cast<StoreInst>(&I)) { 6459 if (!SI->isSimple()) 6460 continue; 6461 if (!isValidElementType(SI->getValueOperand()->getType())) 6462 continue; 6463 Stores[getUnderlyingObject(SI->getPointerOperand())].push_back(SI); 6464 } 6465 6466 // Ignore getelementptr instructions that have more than one index, a 6467 // constant index, or a pointer operand that doesn't point to a scalar 6468 // type. 6469 else if (auto *GEP = dyn_cast<GetElementPtrInst>(&I)) { 6470 auto Idx = GEP->idx_begin()->get(); 6471 if (GEP->getNumIndices() > 1 || isa<Constant>(Idx)) 6472 continue; 6473 if (!isValidElementType(Idx->getType())) 6474 continue; 6475 if (GEP->getType()->isVectorTy()) 6476 continue; 6477 GEPs[GEP->getPointerOperand()].push_back(GEP); 6478 } 6479 } 6480 } 6481 6482 bool SLPVectorizerPass::tryToVectorizePair(Value *A, Value *B, BoUpSLP &R) { 6483 if (!A || !B) 6484 return false; 6485 Value *VL[] = {A, B}; 6486 return tryToVectorizeList(VL, R, /*AllowReorder=*/true); 6487 } 6488 6489 bool SLPVectorizerPass::tryToVectorizeList(ArrayRef<Value *> VL, BoUpSLP &R, 6490 bool AllowReorder, 6491 ArrayRef<Value *> InsertUses) { 6492 if (VL.size() < 2) 6493 return false; 6494 6495 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize a list of length = " 6496 << VL.size() << ".\n"); 6497 6498 // Check that all of the parts are instructions of the same type, 6499 // we permit an alternate opcode via InstructionsState. 6500 InstructionsState S = getSameOpcode(VL); 6501 if (!S.getOpcode()) 6502 return false; 6503 6504 Instruction *I0 = cast<Instruction>(S.OpValue); 6505 // Make sure invalid types (including vector type) are rejected before 6506 // determining vectorization factor for scalar instructions. 6507 for (Value *V : VL) { 6508 Type *Ty = V->getType(); 6509 if (!isValidElementType(Ty)) { 6510 // NOTE: the following will give user internal llvm type name, which may 6511 // not be useful. 6512 R.getORE()->emit([&]() { 6513 std::string type_str; 6514 llvm::raw_string_ostream rso(type_str); 6515 Ty->print(rso); 6516 return OptimizationRemarkMissed(SV_NAME, "UnsupportedType", I0) 6517 << "Cannot SLP vectorize list: type " 6518 << rso.str() + " is unsupported by vectorizer"; 6519 }); 6520 return false; 6521 } 6522 } 6523 6524 unsigned Sz = R.getVectorElementSize(I0); 6525 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / Sz); 6526 unsigned MaxVF = std::max<unsigned>(PowerOf2Floor(VL.size()), MinVF); 6527 MaxVF = std::min(R.getMaximumVF(Sz, S.getOpcode()), MaxVF); 6528 if (MaxVF < 2) { 6529 R.getORE()->emit([&]() { 6530 return OptimizationRemarkMissed(SV_NAME, "SmallVF", I0) 6531 << "Cannot SLP vectorize list: vectorization factor " 6532 << "less than 2 is not supported"; 6533 }); 6534 return false; 6535 } 6536 6537 bool Changed = false; 6538 bool CandidateFound = false; 6539 InstructionCost MinCost = SLPCostThreshold.getValue(); 6540 6541 bool CompensateUseCost = 6542 !InsertUses.empty() && llvm::all_of(InsertUses, [](const Value *V) { 6543 return V && isa<InsertElementInst>(V); 6544 }); 6545 assert((!CompensateUseCost || InsertUses.size() == VL.size()) && 6546 "Each scalar expected to have an associated InsertElement user."); 6547 6548 unsigned NextInst = 0, MaxInst = VL.size(); 6549 for (unsigned VF = MaxVF; NextInst + 1 < MaxInst && VF >= MinVF; VF /= 2) { 6550 // No actual vectorization should happen, if number of parts is the same as 6551 // provided vectorization factor (i.e. the scalar type is used for vector 6552 // code during codegen). 6553 auto *VecTy = FixedVectorType::get(VL[0]->getType(), VF); 6554 if (TTI->getNumberOfParts(VecTy) == VF) 6555 continue; 6556 for (unsigned I = NextInst; I < MaxInst; ++I) { 6557 unsigned OpsWidth = 0; 6558 6559 if (I + VF > MaxInst) 6560 OpsWidth = MaxInst - I; 6561 else 6562 OpsWidth = VF; 6563 6564 if (!isPowerOf2_32(OpsWidth) || OpsWidth < 2) 6565 break; 6566 6567 ArrayRef<Value *> Ops = VL.slice(I, OpsWidth); 6568 // Check that a previous iteration of this loop did not delete the Value. 6569 if (llvm::any_of(Ops, [&R](Value *V) { 6570 auto *I = dyn_cast<Instruction>(V); 6571 return I && R.isDeleted(I); 6572 })) 6573 continue; 6574 6575 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << OpsWidth << " operations " 6576 << "\n"); 6577 6578 R.buildTree(Ops); 6579 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 6580 // TODO: check if we can allow reordering for more cases. 6581 if (AllowReorder && Order) { 6582 // TODO: reorder tree nodes without tree rebuilding. 6583 // Conceptually, there is nothing actually preventing us from trying to 6584 // reorder a larger list. In fact, we do exactly this when vectorizing 6585 // reductions. However, at this point, we only expect to get here when 6586 // there are exactly two operations. 6587 assert(Ops.size() == 2); 6588 Value *ReorderedOps[] = {Ops[1], Ops[0]}; 6589 R.buildTree(ReorderedOps, None); 6590 } 6591 if (R.isTreeTinyAndNotFullyVectorizable()) 6592 continue; 6593 6594 R.computeMinimumValueSizes(); 6595 InstructionCost Cost = R.getTreeCost(); 6596 CandidateFound = true; 6597 if (CompensateUseCost) { 6598 // TODO: Use TTI's getScalarizationOverhead for sequence of inserts 6599 // rather than sum of single inserts as the latter may overestimate 6600 // cost. This work should imply improving cost estimation for extracts 6601 // that added in for external (for vectorization tree) users,i.e. that 6602 // part should also switch to same interface. 6603 // For example, the following case is projected code after SLP: 6604 // %4 = extractelement <4 x i64> %3, i32 0 6605 // %v0 = insertelement <4 x i64> poison, i64 %4, i32 0 6606 // %5 = extractelement <4 x i64> %3, i32 1 6607 // %v1 = insertelement <4 x i64> %v0, i64 %5, i32 1 6608 // %6 = extractelement <4 x i64> %3, i32 2 6609 // %v2 = insertelement <4 x i64> %v1, i64 %6, i32 2 6610 // %7 = extractelement <4 x i64> %3, i32 3 6611 // %v3 = insertelement <4 x i64> %v2, i64 %7, i32 3 6612 // 6613 // Extracts here added by SLP in order to feed users (the inserts) of 6614 // original scalars and contribute to "ExtractCost" at cost evaluation. 6615 // The inserts in turn form sequence to build an aggregate that 6616 // detected by findBuildAggregate routine. 6617 // SLP makes an assumption that such sequence will be optimized away 6618 // later (instcombine) so it tries to compensate ExctractCost with 6619 // cost of insert sequence. 6620 // Current per element cost calculation approach is not quite accurate 6621 // and tends to create bias toward favoring vectorization. 6622 // Switching to the TTI interface might help a bit. 6623 // Alternative solution could be pattern-match to detect a no-op or 6624 // shuffle. 6625 InstructionCost UserCost = 0; 6626 for (unsigned Lane = 0; Lane < OpsWidth; Lane++) { 6627 auto *IE = cast<InsertElementInst>(InsertUses[I + Lane]); 6628 if (auto *CI = dyn_cast<ConstantInt>(IE->getOperand(2))) 6629 UserCost += TTI->getVectorInstrCost( 6630 Instruction::InsertElement, IE->getType(), CI->getZExtValue()); 6631 } 6632 LLVM_DEBUG(dbgs() << "SLP: Compensate cost of users by: " << UserCost 6633 << ".\n"); 6634 Cost -= UserCost; 6635 } 6636 6637 MinCost = std::min(MinCost, Cost); 6638 6639 if (Cost < -SLPCostThreshold) { 6640 LLVM_DEBUG(dbgs() << "SLP: Vectorizing list at cost:" << Cost << ".\n"); 6641 R.getORE()->emit(OptimizationRemark(SV_NAME, "VectorizedList", 6642 cast<Instruction>(Ops[0])) 6643 << "SLP vectorized with cost " << ore::NV("Cost", Cost) 6644 << " and with tree size " 6645 << ore::NV("TreeSize", R.getTreeSize())); 6646 6647 R.vectorizeTree(); 6648 // Move to the next bundle. 6649 I += VF - 1; 6650 NextInst = I + 1; 6651 Changed = true; 6652 } 6653 } 6654 } 6655 6656 if (!Changed && CandidateFound) { 6657 R.getORE()->emit([&]() { 6658 return OptimizationRemarkMissed(SV_NAME, "NotBeneficial", I0) 6659 << "List vectorization was possible but not beneficial with cost " 6660 << ore::NV("Cost", MinCost) << " >= " 6661 << ore::NV("Treshold", -SLPCostThreshold); 6662 }); 6663 } else if (!Changed) { 6664 R.getORE()->emit([&]() { 6665 return OptimizationRemarkMissed(SV_NAME, "NotPossible", I0) 6666 << "Cannot SLP vectorize list: vectorization was impossible" 6667 << " with available vectorization factors"; 6668 }); 6669 } 6670 return Changed; 6671 } 6672 6673 bool SLPVectorizerPass::tryToVectorize(Instruction *I, BoUpSLP &R) { 6674 if (!I) 6675 return false; 6676 6677 if (!isa<BinaryOperator>(I) && !isa<CmpInst>(I)) 6678 return false; 6679 6680 Value *P = I->getParent(); 6681 6682 // Vectorize in current basic block only. 6683 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 6684 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 6685 if (!Op0 || !Op1 || Op0->getParent() != P || Op1->getParent() != P) 6686 return false; 6687 6688 // Try to vectorize V. 6689 if (tryToVectorizePair(Op0, Op1, R)) 6690 return true; 6691 6692 auto *A = dyn_cast<BinaryOperator>(Op0); 6693 auto *B = dyn_cast<BinaryOperator>(Op1); 6694 // Try to skip B. 6695 if (B && B->hasOneUse()) { 6696 auto *B0 = dyn_cast<BinaryOperator>(B->getOperand(0)); 6697 auto *B1 = dyn_cast<BinaryOperator>(B->getOperand(1)); 6698 if (B0 && B0->getParent() == P && tryToVectorizePair(A, B0, R)) 6699 return true; 6700 if (B1 && B1->getParent() == P && tryToVectorizePair(A, B1, R)) 6701 return true; 6702 } 6703 6704 // Try to skip A. 6705 if (A && A->hasOneUse()) { 6706 auto *A0 = dyn_cast<BinaryOperator>(A->getOperand(0)); 6707 auto *A1 = dyn_cast<BinaryOperator>(A->getOperand(1)); 6708 if (A0 && A0->getParent() == P && tryToVectorizePair(A0, B, R)) 6709 return true; 6710 if (A1 && A1->getParent() == P && tryToVectorizePair(A1, B, R)) 6711 return true; 6712 } 6713 return false; 6714 } 6715 6716 namespace { 6717 6718 /// Model horizontal reductions. 6719 /// 6720 /// A horizontal reduction is a tree of reduction instructions that has values 6721 /// that can be put into a vector as its leaves. For example: 6722 /// 6723 /// mul mul mul mul 6724 /// \ / \ / 6725 /// + + 6726 /// \ / 6727 /// + 6728 /// This tree has "mul" as its leaf values and "+" as its reduction 6729 /// instructions. A reduction can feed into a store or a binary operation 6730 /// feeding a phi. 6731 /// ... 6732 /// \ / 6733 /// + 6734 /// | 6735 /// phi += 6736 /// 6737 /// Or: 6738 /// ... 6739 /// \ / 6740 /// + 6741 /// | 6742 /// *p = 6743 /// 6744 class HorizontalReduction { 6745 using ReductionOpsType = SmallVector<Value *, 16>; 6746 using ReductionOpsListType = SmallVector<ReductionOpsType, 2>; 6747 ReductionOpsListType ReductionOps; 6748 SmallVector<Value *, 32> ReducedVals; 6749 // Use map vector to make stable output. 6750 MapVector<Instruction *, Value *> ExtraArgs; 6751 WeakTrackingVH ReductionRoot; 6752 /// The type of reduction operation. 6753 RecurKind RdxKind; 6754 6755 /// Checks if instruction is associative and can be vectorized. 6756 static bool isVectorizable(RecurKind Kind, Instruction *I) { 6757 if (Kind == RecurKind::None) 6758 return false; 6759 if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(Kind)) 6760 return true; 6761 6762 if (Kind == RecurKind::FMax || Kind == RecurKind::FMin) { 6763 // FP min/max are associative except for NaN and -0.0. We do not 6764 // have to rule out -0.0 here because the intrinsic semantics do not 6765 // specify a fixed result for it. 6766 return I->getFastMathFlags().noNaNs(); 6767 } 6768 6769 return I->isAssociative(); 6770 } 6771 6772 /// Checks if the ParentStackElem.first should be marked as a reduction 6773 /// operation with an extra argument or as extra argument itself. 6774 void markExtraArg(std::pair<Instruction *, unsigned> &ParentStackElem, 6775 Value *ExtraArg) { 6776 if (ExtraArgs.count(ParentStackElem.first)) { 6777 ExtraArgs[ParentStackElem.first] = nullptr; 6778 // We ran into something like: 6779 // ParentStackElem.first = ExtraArgs[ParentStackElem.first] + ExtraArg. 6780 // The whole ParentStackElem.first should be considered as an extra value 6781 // in this case. 6782 // Do not perform analysis of remaining operands of ParentStackElem.first 6783 // instruction, this whole instruction is an extra argument. 6784 ParentStackElem.second = getNumberOfOperands(ParentStackElem.first); 6785 } else { 6786 // We ran into something like: 6787 // ParentStackElem.first += ... + ExtraArg + ... 6788 ExtraArgs[ParentStackElem.first] = ExtraArg; 6789 } 6790 } 6791 6792 /// Creates reduction operation with the current opcode. 6793 static Value *createOp(IRBuilder<> &Builder, RecurKind Kind, Value *LHS, 6794 Value *RHS, const Twine &Name, bool UseSelect) { 6795 unsigned RdxOpcode = RecurrenceDescriptor::getOpcode(Kind); 6796 switch (Kind) { 6797 case RecurKind::Add: 6798 case RecurKind::Mul: 6799 case RecurKind::Or: 6800 case RecurKind::And: 6801 case RecurKind::Xor: 6802 case RecurKind::FAdd: 6803 case RecurKind::FMul: 6804 return Builder.CreateBinOp((Instruction::BinaryOps)RdxOpcode, LHS, RHS, 6805 Name); 6806 case RecurKind::FMax: 6807 return Builder.CreateBinaryIntrinsic(Intrinsic::maxnum, LHS, RHS); 6808 case RecurKind::FMin: 6809 return Builder.CreateBinaryIntrinsic(Intrinsic::minnum, LHS, RHS); 6810 case RecurKind::SMax: 6811 if (UseSelect) { 6812 Value *Cmp = Builder.CreateICmpSGT(LHS, RHS, Name); 6813 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6814 } 6815 return Builder.CreateBinaryIntrinsic(Intrinsic::smax, LHS, RHS); 6816 case RecurKind::SMin: 6817 if (UseSelect) { 6818 Value *Cmp = Builder.CreateICmpSLT(LHS, RHS, Name); 6819 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6820 } 6821 return Builder.CreateBinaryIntrinsic(Intrinsic::smin, LHS, RHS); 6822 case RecurKind::UMax: 6823 if (UseSelect) { 6824 Value *Cmp = Builder.CreateICmpUGT(LHS, RHS, Name); 6825 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6826 } 6827 return Builder.CreateBinaryIntrinsic(Intrinsic::umax, LHS, RHS); 6828 case RecurKind::UMin: 6829 if (UseSelect) { 6830 Value *Cmp = Builder.CreateICmpULT(LHS, RHS, Name); 6831 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6832 } 6833 return Builder.CreateBinaryIntrinsic(Intrinsic::umin, LHS, RHS); 6834 default: 6835 llvm_unreachable("Unknown reduction operation."); 6836 } 6837 } 6838 6839 /// Creates reduction operation with the current opcode with the IR flags 6840 /// from \p ReductionOps. 6841 static Value *createOp(IRBuilder<> &Builder, RecurKind RdxKind, Value *LHS, 6842 Value *RHS, const Twine &Name, 6843 const ReductionOpsListType &ReductionOps) { 6844 bool UseSelect = ReductionOps.size() == 2; 6845 assert((!UseSelect || isa<SelectInst>(ReductionOps[1][0])) && 6846 "Expected cmp + select pairs for reduction"); 6847 Value *Op = createOp(Builder, RdxKind, LHS, RHS, Name, UseSelect); 6848 if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(RdxKind)) { 6849 if (auto *Sel = dyn_cast<SelectInst>(Op)) { 6850 propagateIRFlags(Sel->getCondition(), ReductionOps[0]); 6851 propagateIRFlags(Op, ReductionOps[1]); 6852 return Op; 6853 } 6854 } 6855 propagateIRFlags(Op, ReductionOps[0]); 6856 return Op; 6857 } 6858 6859 /// Creates reduction operation with the current opcode with the IR flags 6860 /// from \p I. 6861 static Value *createOp(IRBuilder<> &Builder, RecurKind RdxKind, Value *LHS, 6862 Value *RHS, const Twine &Name, Instruction *I) { 6863 auto *SelI = dyn_cast<SelectInst>(I); 6864 Value *Op = createOp(Builder, RdxKind, LHS, RHS, Name, SelI != nullptr); 6865 if (SelI && RecurrenceDescriptor::isIntMinMaxRecurrenceKind(RdxKind)) { 6866 if (auto *Sel = dyn_cast<SelectInst>(Op)) 6867 propagateIRFlags(Sel->getCondition(), SelI->getCondition()); 6868 } 6869 propagateIRFlags(Op, I); 6870 return Op; 6871 } 6872 6873 static RecurKind getRdxKind(Instruction *I) { 6874 assert(I && "Expected instruction for reduction matching"); 6875 TargetTransformInfo::ReductionFlags RdxFlags; 6876 if (match(I, m_Add(m_Value(), m_Value()))) 6877 return RecurKind::Add; 6878 if (match(I, m_Mul(m_Value(), m_Value()))) 6879 return RecurKind::Mul; 6880 if (match(I, m_And(m_Value(), m_Value()))) 6881 return RecurKind::And; 6882 if (match(I, m_Or(m_Value(), m_Value()))) 6883 return RecurKind::Or; 6884 if (match(I, m_Xor(m_Value(), m_Value()))) 6885 return RecurKind::Xor; 6886 if (match(I, m_FAdd(m_Value(), m_Value()))) 6887 return RecurKind::FAdd; 6888 if (match(I, m_FMul(m_Value(), m_Value()))) 6889 return RecurKind::FMul; 6890 6891 if (match(I, m_Intrinsic<Intrinsic::maxnum>(m_Value(), m_Value()))) 6892 return RecurKind::FMax; 6893 if (match(I, m_Intrinsic<Intrinsic::minnum>(m_Value(), m_Value()))) 6894 return RecurKind::FMin; 6895 6896 // This matches either cmp+select or intrinsics. SLP is expected to handle 6897 // either form. 6898 // TODO: If we are canonicalizing to intrinsics, we can remove several 6899 // special-case paths that deal with selects. 6900 if (match(I, m_SMax(m_Value(), m_Value()))) 6901 return RecurKind::SMax; 6902 if (match(I, m_SMin(m_Value(), m_Value()))) 6903 return RecurKind::SMin; 6904 if (match(I, m_UMax(m_Value(), m_Value()))) 6905 return RecurKind::UMax; 6906 if (match(I, m_UMin(m_Value(), m_Value()))) 6907 return RecurKind::UMin; 6908 6909 if (auto *Select = dyn_cast<SelectInst>(I)) { 6910 // Try harder: look for min/max pattern based on instructions producing 6911 // same values such as: select ((cmp Inst1, Inst2), Inst1, Inst2). 6912 // During the intermediate stages of SLP, it's very common to have 6913 // pattern like this (since optimizeGatherSequence is run only once 6914 // at the end): 6915 // %1 = extractelement <2 x i32> %a, i32 0 6916 // %2 = extractelement <2 x i32> %a, i32 1 6917 // %cond = icmp sgt i32 %1, %2 6918 // %3 = extractelement <2 x i32> %a, i32 0 6919 // %4 = extractelement <2 x i32> %a, i32 1 6920 // %select = select i1 %cond, i32 %3, i32 %4 6921 CmpInst::Predicate Pred; 6922 Instruction *L1; 6923 Instruction *L2; 6924 6925 Value *LHS = Select->getTrueValue(); 6926 Value *RHS = Select->getFalseValue(); 6927 Value *Cond = Select->getCondition(); 6928 6929 // TODO: Support inverse predicates. 6930 if (match(Cond, m_Cmp(Pred, m_Specific(LHS), m_Instruction(L2)))) { 6931 if (!isa<ExtractElementInst>(RHS) || 6932 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6933 return RecurKind::None; 6934 } else if (match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Specific(RHS)))) { 6935 if (!isa<ExtractElementInst>(LHS) || 6936 !L1->isIdenticalTo(cast<Instruction>(LHS))) 6937 return RecurKind::None; 6938 } else { 6939 if (!isa<ExtractElementInst>(LHS) || !isa<ExtractElementInst>(RHS)) 6940 return RecurKind::None; 6941 if (!match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Instruction(L2))) || 6942 !L1->isIdenticalTo(cast<Instruction>(LHS)) || 6943 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6944 return RecurKind::None; 6945 } 6946 6947 TargetTransformInfo::ReductionFlags RdxFlags; 6948 switch (Pred) { 6949 default: 6950 return RecurKind::None; 6951 case CmpInst::ICMP_SGT: 6952 case CmpInst::ICMP_SGE: 6953 return RecurKind::SMax; 6954 case CmpInst::ICMP_SLT: 6955 case CmpInst::ICMP_SLE: 6956 return RecurKind::SMin; 6957 case CmpInst::ICMP_UGT: 6958 case CmpInst::ICMP_UGE: 6959 return RecurKind::UMax; 6960 case CmpInst::ICMP_ULT: 6961 case CmpInst::ICMP_ULE: 6962 return RecurKind::UMin; 6963 } 6964 } 6965 return RecurKind::None; 6966 } 6967 6968 /// Get the index of the first operand. 6969 static unsigned getFirstOperandIndex(Instruction *I) { 6970 return isa<SelectInst>(I) ? 1 : 0; 6971 } 6972 6973 /// Total number of operands in the reduction operation. 6974 static unsigned getNumberOfOperands(Instruction *I) { 6975 return isa<SelectInst>(I) ? 3 : 2; 6976 } 6977 6978 /// Checks if the instruction is in basic block \p BB. 6979 /// For a min/max reduction check that both compare and select are in \p BB. 6980 static bool hasSameParent(Instruction *I, BasicBlock *BB, bool IsRedOp) { 6981 auto *Sel = dyn_cast<SelectInst>(I); 6982 if (IsRedOp && Sel) { 6983 auto *Cmp = cast<Instruction>(Sel->getCondition()); 6984 return Sel->getParent() == BB && Cmp->getParent() == BB; 6985 } 6986 return I->getParent() == BB; 6987 } 6988 6989 /// Expected number of uses for reduction operations/reduced values. 6990 static bool hasRequiredNumberOfUses(bool MatchCmpSel, Instruction *I) { 6991 // SelectInst must be used twice while the condition op must have single 6992 // use only. 6993 if (MatchCmpSel) { 6994 if (auto *Sel = dyn_cast<SelectInst>(I)) 6995 return Sel->hasNUses(2) && Sel->getCondition()->hasOneUse(); 6996 return I->hasNUses(2); 6997 } 6998 6999 // Arithmetic reduction operation must be used once only. 7000 return I->hasOneUse(); 7001 } 7002 7003 /// Initializes the list of reduction operations. 7004 void initReductionOps(Instruction *I) { 7005 if (isa<SelectInst>(I)) 7006 ReductionOps.assign(2, ReductionOpsType()); 7007 else 7008 ReductionOps.assign(1, ReductionOpsType()); 7009 } 7010 7011 /// Add all reduction operations for the reduction instruction \p I. 7012 void addReductionOps(Instruction *I) { 7013 if (auto *Sel = dyn_cast<SelectInst>(I)) { 7014 ReductionOps[0].emplace_back(Sel->getCondition()); 7015 ReductionOps[1].emplace_back(Sel); 7016 } else { 7017 ReductionOps[0].emplace_back(I); 7018 } 7019 } 7020 7021 static Value *getLHS(RecurKind Kind, Instruction *I) { 7022 if (Kind == RecurKind::None) 7023 return nullptr; 7024 return I->getOperand(getFirstOperandIndex(I)); 7025 } 7026 static Value *getRHS(RecurKind Kind, Instruction *I) { 7027 if (Kind == RecurKind::None) 7028 return nullptr; 7029 return I->getOperand(getFirstOperandIndex(I) + 1); 7030 } 7031 7032 public: 7033 HorizontalReduction() = default; 7034 7035 /// Try to find a reduction tree. 7036 bool matchAssociativeReduction(PHINode *Phi, Instruction *B) { 7037 assert((!Phi || is_contained(Phi->operands(), B)) && 7038 "Phi needs to use the binary operator"); 7039 7040 RdxKind = getRdxKind(B); 7041 7042 // We could have a initial reductions that is not an add. 7043 // r *= v1 + v2 + v3 + v4 7044 // In such a case start looking for a tree rooted in the first '+'. 7045 if (Phi) { 7046 if (getLHS(RdxKind, B) == Phi) { 7047 Phi = nullptr; 7048 B = dyn_cast<Instruction>(getRHS(RdxKind, B)); 7049 if (!B) 7050 return false; 7051 RdxKind = getRdxKind(B); 7052 } else if (getRHS(RdxKind, B) == Phi) { 7053 Phi = nullptr; 7054 B = dyn_cast<Instruction>(getLHS(RdxKind, B)); 7055 if (!B) 7056 return false; 7057 RdxKind = getRdxKind(B); 7058 } 7059 } 7060 7061 if (!isVectorizable(RdxKind, B)) 7062 return false; 7063 7064 // Analyze "regular" integer/FP types for reductions - no target-specific 7065 // types or pointers. 7066 Type *Ty = B->getType(); 7067 if (!isValidElementType(Ty) || Ty->isPointerTy()) 7068 return false; 7069 7070 // Though the ultimate reduction may have multiple uses, its condition must 7071 // have only single use. 7072 if (auto *SI = dyn_cast<SelectInst>(B)) 7073 if (!SI->getCondition()->hasOneUse()) 7074 return false; 7075 7076 ReductionRoot = B; 7077 7078 // The opcode for leaf values that we perform a reduction on. 7079 // For example: load(x) + load(y) + load(z) + fptoui(w) 7080 // The leaf opcode for 'w' does not match, so we don't include it as a 7081 // potential candidate for the reduction. 7082 unsigned LeafOpcode = 0; 7083 7084 // Post order traverse the reduction tree starting at B. We only handle true 7085 // trees containing only binary operators. 7086 SmallVector<std::pair<Instruction *, unsigned>, 32> Stack; 7087 Stack.push_back(std::make_pair(B, getFirstOperandIndex(B))); 7088 initReductionOps(B); 7089 while (!Stack.empty()) { 7090 Instruction *TreeN = Stack.back().first; 7091 unsigned EdgeToVisit = Stack.back().second++; 7092 const RecurKind TreeRdxKind = getRdxKind(TreeN); 7093 bool IsReducedValue = TreeRdxKind != RdxKind; 7094 7095 // Postorder visit. 7096 if (IsReducedValue || EdgeToVisit == getNumberOfOperands(TreeN)) { 7097 if (IsReducedValue) 7098 ReducedVals.push_back(TreeN); 7099 else { 7100 auto ExtraArgsIter = ExtraArgs.find(TreeN); 7101 if (ExtraArgsIter != ExtraArgs.end() && !ExtraArgsIter->second) { 7102 // Check if TreeN is an extra argument of its parent operation. 7103 if (Stack.size() <= 1) { 7104 // TreeN can't be an extra argument as it is a root reduction 7105 // operation. 7106 return false; 7107 } 7108 // Yes, TreeN is an extra argument, do not add it to a list of 7109 // reduction operations. 7110 // Stack[Stack.size() - 2] always points to the parent operation. 7111 markExtraArg(Stack[Stack.size() - 2], TreeN); 7112 ExtraArgs.erase(TreeN); 7113 } else 7114 addReductionOps(TreeN); 7115 } 7116 // Retract. 7117 Stack.pop_back(); 7118 continue; 7119 } 7120 7121 // Visit left or right. 7122 Value *EdgeVal = TreeN->getOperand(EdgeToVisit); 7123 auto *EdgeInst = dyn_cast<Instruction>(EdgeVal); 7124 if (!EdgeInst) { 7125 // Edge value is not a reduction instruction or a leaf instruction. 7126 // (It may be a constant, function argument, or something else.) 7127 markExtraArg(Stack.back(), EdgeVal); 7128 continue; 7129 } 7130 RecurKind EdgeRdxKind = getRdxKind(EdgeInst); 7131 // Continue analysis if the next operand is a reduction operation or 7132 // (possibly) a leaf value. If the leaf value opcode is not set, 7133 // the first met operation != reduction operation is considered as the 7134 // leaf opcode. 7135 // Only handle trees in the current basic block. 7136 // Each tree node needs to have minimal number of users except for the 7137 // ultimate reduction. 7138 const bool IsRdxInst = EdgeRdxKind == RdxKind; 7139 if (EdgeInst != Phi && EdgeInst != B && 7140 hasSameParent(EdgeInst, B->getParent(), IsRdxInst) && 7141 hasRequiredNumberOfUses(isa<SelectInst>(B), EdgeInst) && 7142 (!LeafOpcode || LeafOpcode == EdgeInst->getOpcode() || IsRdxInst)) { 7143 if (IsRdxInst) { 7144 // We need to be able to reassociate the reduction operations. 7145 if (!isVectorizable(EdgeRdxKind, EdgeInst)) { 7146 // I is an extra argument for TreeN (its parent operation). 7147 markExtraArg(Stack.back(), EdgeInst); 7148 continue; 7149 } 7150 } else if (!LeafOpcode) { 7151 LeafOpcode = EdgeInst->getOpcode(); 7152 } 7153 Stack.push_back( 7154 std::make_pair(EdgeInst, getFirstOperandIndex(EdgeInst))); 7155 continue; 7156 } 7157 // I is an extra argument for TreeN (its parent operation). 7158 markExtraArg(Stack.back(), EdgeInst); 7159 } 7160 return true; 7161 } 7162 7163 /// Attempt to vectorize the tree found by matchAssociativeReduction. 7164 bool tryToReduce(BoUpSLP &V, TargetTransformInfo *TTI) { 7165 // If there are a sufficient number of reduction values, reduce 7166 // to a nearby power-of-2. We can safely generate oversized 7167 // vectors and rely on the backend to split them to legal sizes. 7168 unsigned NumReducedVals = ReducedVals.size(); 7169 if (NumReducedVals < 4) 7170 return false; 7171 7172 // Intersect the fast-math-flags from all reduction operations. 7173 FastMathFlags RdxFMF; 7174 RdxFMF.set(); 7175 for (ReductionOpsType &RdxOp : ReductionOps) { 7176 for (Value *RdxVal : RdxOp) { 7177 if (auto *FPMO = dyn_cast<FPMathOperator>(RdxVal)) 7178 RdxFMF &= FPMO->getFastMathFlags(); 7179 } 7180 } 7181 7182 IRBuilder<> Builder(cast<Instruction>(ReductionRoot)); 7183 Builder.setFastMathFlags(RdxFMF); 7184 7185 BoUpSLP::ExtraValueToDebugLocsMap ExternallyUsedValues; 7186 // The same extra argument may be used several times, so log each attempt 7187 // to use it. 7188 for (const std::pair<Instruction *, Value *> &Pair : ExtraArgs) { 7189 assert(Pair.first && "DebugLoc must be set."); 7190 ExternallyUsedValues[Pair.second].push_back(Pair.first); 7191 } 7192 7193 // The compare instruction of a min/max is the insertion point for new 7194 // instructions and may be replaced with a new compare instruction. 7195 auto getCmpForMinMaxReduction = [](Instruction *RdxRootInst) { 7196 assert(isa<SelectInst>(RdxRootInst) && 7197 "Expected min/max reduction to have select root instruction"); 7198 Value *ScalarCond = cast<SelectInst>(RdxRootInst)->getCondition(); 7199 assert(isa<Instruction>(ScalarCond) && 7200 "Expected min/max reduction to have compare condition"); 7201 return cast<Instruction>(ScalarCond); 7202 }; 7203 7204 // The reduction root is used as the insertion point for new instructions, 7205 // so set it as externally used to prevent it from being deleted. 7206 ExternallyUsedValues[ReductionRoot]; 7207 SmallVector<Value *, 16> IgnoreList; 7208 for (ReductionOpsType &RdxOp : ReductionOps) 7209 IgnoreList.append(RdxOp.begin(), RdxOp.end()); 7210 7211 unsigned ReduxWidth = PowerOf2Floor(NumReducedVals); 7212 if (NumReducedVals > ReduxWidth) { 7213 // In the loop below, we are building a tree based on a window of 7214 // 'ReduxWidth' values. 7215 // If the operands of those values have common traits (compare predicate, 7216 // constant operand, etc), then we want to group those together to 7217 // minimize the cost of the reduction. 7218 7219 // TODO: This should be extended to count common operands for 7220 // compares and binops. 7221 7222 // Step 1: Count the number of times each compare predicate occurs. 7223 SmallDenseMap<unsigned, unsigned> PredCountMap; 7224 for (Value *RdxVal : ReducedVals) { 7225 CmpInst::Predicate Pred; 7226 if (match(RdxVal, m_Cmp(Pred, m_Value(), m_Value()))) 7227 ++PredCountMap[Pred]; 7228 } 7229 // Step 2: Sort the values so the most common predicates come first. 7230 stable_sort(ReducedVals, [&PredCountMap](Value *A, Value *B) { 7231 CmpInst::Predicate PredA, PredB; 7232 if (match(A, m_Cmp(PredA, m_Value(), m_Value())) && 7233 match(B, m_Cmp(PredB, m_Value(), m_Value()))) { 7234 return PredCountMap[PredA] > PredCountMap[PredB]; 7235 } 7236 return false; 7237 }); 7238 } 7239 7240 Value *VectorizedTree = nullptr; 7241 unsigned i = 0; 7242 while (i < NumReducedVals - ReduxWidth + 1 && ReduxWidth > 2) { 7243 ArrayRef<Value *> VL(&ReducedVals[i], ReduxWidth); 7244 V.buildTree(VL, ExternallyUsedValues, IgnoreList); 7245 Optional<ArrayRef<unsigned>> Order = V.bestOrder(); 7246 if (Order) { 7247 assert(Order->size() == VL.size() && 7248 "Order size must be the same as number of vectorized " 7249 "instructions."); 7250 // TODO: reorder tree nodes without tree rebuilding. 7251 SmallVector<Value *, 4> ReorderedOps(VL.size()); 7252 llvm::transform(*Order, ReorderedOps.begin(), 7253 [VL](const unsigned Idx) { return VL[Idx]; }); 7254 V.buildTree(ReorderedOps, ExternallyUsedValues, IgnoreList); 7255 } 7256 if (V.isTreeTinyAndNotFullyVectorizable()) 7257 break; 7258 if (V.isLoadCombineReductionCandidate(RdxKind)) 7259 break; 7260 7261 V.computeMinimumValueSizes(); 7262 7263 // Estimate cost. 7264 InstructionCost TreeCost = V.getTreeCost(); 7265 InstructionCost ReductionCost = 7266 getReductionCost(TTI, ReducedVals[i], ReduxWidth); 7267 InstructionCost Cost = TreeCost + ReductionCost; 7268 if (!Cost.isValid()) { 7269 LLVM_DEBUG(dbgs() << "Encountered invalid baseline cost.\n"); 7270 return false; 7271 } 7272 if (Cost >= -SLPCostThreshold) { 7273 V.getORE()->emit([&]() { 7274 return OptimizationRemarkMissed(SV_NAME, "HorSLPNotBeneficial", 7275 cast<Instruction>(VL[0])) 7276 << "Vectorizing horizontal reduction is possible" 7277 << "but not beneficial with cost " << ore::NV("Cost", Cost) 7278 << " and threshold " 7279 << ore::NV("Threshold", -SLPCostThreshold); 7280 }); 7281 break; 7282 } 7283 7284 LLVM_DEBUG(dbgs() << "SLP: Vectorizing horizontal reduction at cost:" 7285 << Cost << ". (HorRdx)\n"); 7286 V.getORE()->emit([&]() { 7287 return OptimizationRemark(SV_NAME, "VectorizedHorizontalReduction", 7288 cast<Instruction>(VL[0])) 7289 << "Vectorized horizontal reduction with cost " 7290 << ore::NV("Cost", Cost) << " and with tree size " 7291 << ore::NV("TreeSize", V.getTreeSize()); 7292 }); 7293 7294 // Vectorize a tree. 7295 DebugLoc Loc = cast<Instruction>(ReducedVals[i])->getDebugLoc(); 7296 Value *VectorizedRoot = V.vectorizeTree(ExternallyUsedValues); 7297 7298 // Emit a reduction. If the root is a select (min/max idiom), the insert 7299 // point is the compare condition of that select. 7300 Instruction *RdxRootInst = cast<Instruction>(ReductionRoot); 7301 if (isa<SelectInst>(RdxRootInst)) 7302 Builder.SetInsertPoint(getCmpForMinMaxReduction(RdxRootInst)); 7303 else 7304 Builder.SetInsertPoint(RdxRootInst); 7305 7306 Value *ReducedSubTree = 7307 emitReduction(VectorizedRoot, Builder, ReduxWidth, TTI); 7308 7309 if (!VectorizedTree) { 7310 // Initialize the final value in the reduction. 7311 VectorizedTree = ReducedSubTree; 7312 } else { 7313 // Update the final value in the reduction. 7314 Builder.SetCurrentDebugLocation(Loc); 7315 VectorizedTree = createOp(Builder, RdxKind, VectorizedTree, 7316 ReducedSubTree, "op.rdx", ReductionOps); 7317 } 7318 i += ReduxWidth; 7319 ReduxWidth = PowerOf2Floor(NumReducedVals - i); 7320 } 7321 7322 if (VectorizedTree) { 7323 // Finish the reduction. 7324 for (; i < NumReducedVals; ++i) { 7325 auto *I = cast<Instruction>(ReducedVals[i]); 7326 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 7327 VectorizedTree = 7328 createOp(Builder, RdxKind, VectorizedTree, I, "", ReductionOps); 7329 } 7330 for (auto &Pair : ExternallyUsedValues) { 7331 // Add each externally used value to the final reduction. 7332 for (auto *I : Pair.second) { 7333 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 7334 VectorizedTree = createOp(Builder, RdxKind, VectorizedTree, 7335 Pair.first, "op.extra", I); 7336 } 7337 } 7338 7339 ReductionRoot->replaceAllUsesWith(VectorizedTree); 7340 7341 // Mark all scalar reduction ops for deletion, they are replaced by the 7342 // vector reductions. 7343 V.eraseInstructions(IgnoreList); 7344 } 7345 return VectorizedTree != nullptr; 7346 } 7347 7348 unsigned numReductionValues() const { return ReducedVals.size(); } 7349 7350 private: 7351 /// Calculate the cost of a reduction. 7352 InstructionCost getReductionCost(TargetTransformInfo *TTI, 7353 Value *FirstReducedVal, 7354 unsigned ReduxWidth) { 7355 Type *ScalarTy = FirstReducedVal->getType(); 7356 FixedVectorType *VectorTy = FixedVectorType::get(ScalarTy, ReduxWidth); 7357 InstructionCost VectorCost, ScalarCost; 7358 switch (RdxKind) { 7359 case RecurKind::Add: 7360 case RecurKind::Mul: 7361 case RecurKind::Or: 7362 case RecurKind::And: 7363 case RecurKind::Xor: 7364 case RecurKind::FAdd: 7365 case RecurKind::FMul: { 7366 unsigned RdxOpcode = RecurrenceDescriptor::getOpcode(RdxKind); 7367 VectorCost = TTI->getArithmeticReductionCost(RdxOpcode, VectorTy, 7368 /*IsPairwiseForm=*/false); 7369 ScalarCost = TTI->getArithmeticInstrCost(RdxOpcode, ScalarTy); 7370 break; 7371 } 7372 case RecurKind::FMax: 7373 case RecurKind::FMin: { 7374 auto *VecCondTy = cast<VectorType>(CmpInst::makeCmpResultType(VectorTy)); 7375 VectorCost = 7376 TTI->getMinMaxReductionCost(VectorTy, VecCondTy, 7377 /*pairwise=*/false, /*unsigned=*/false); 7378 ScalarCost = 7379 TTI->getCmpSelInstrCost(Instruction::FCmp, ScalarTy) + 7380 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 7381 CmpInst::makeCmpResultType(ScalarTy)); 7382 break; 7383 } 7384 case RecurKind::SMax: 7385 case RecurKind::SMin: 7386 case RecurKind::UMax: 7387 case RecurKind::UMin: { 7388 auto *VecCondTy = cast<VectorType>(CmpInst::makeCmpResultType(VectorTy)); 7389 bool IsUnsigned = 7390 RdxKind == RecurKind::UMax || RdxKind == RecurKind::UMin; 7391 VectorCost = 7392 TTI->getMinMaxReductionCost(VectorTy, VecCondTy, 7393 /*IsPairwiseForm=*/false, IsUnsigned); 7394 ScalarCost = 7395 TTI->getCmpSelInstrCost(Instruction::ICmp, ScalarTy) + 7396 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 7397 CmpInst::makeCmpResultType(ScalarTy)); 7398 break; 7399 } 7400 default: 7401 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 7402 } 7403 7404 // Scalar cost is repeated for N-1 elements. 7405 ScalarCost *= (ReduxWidth - 1); 7406 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << VectorCost - ScalarCost 7407 << " for reduction that starts with " << *FirstReducedVal 7408 << " (It is a splitting reduction)\n"); 7409 return VectorCost - ScalarCost; 7410 } 7411 7412 /// Emit a horizontal reduction of the vectorized value. 7413 Value *emitReduction(Value *VectorizedValue, IRBuilder<> &Builder, 7414 unsigned ReduxWidth, const TargetTransformInfo *TTI) { 7415 assert(VectorizedValue && "Need to have a vectorized tree node"); 7416 assert(isPowerOf2_32(ReduxWidth) && 7417 "We only handle power-of-two reductions for now"); 7418 7419 return createSimpleTargetReduction(Builder, TTI, VectorizedValue, RdxKind, 7420 ReductionOps.back()); 7421 } 7422 }; 7423 7424 } // end anonymous namespace 7425 7426 static Optional<unsigned> getAggregateSize(Instruction *InsertInst) { 7427 if (auto *IE = dyn_cast<InsertElementInst>(InsertInst)) 7428 return cast<FixedVectorType>(IE->getType())->getNumElements(); 7429 7430 unsigned AggregateSize = 1; 7431 auto *IV = cast<InsertValueInst>(InsertInst); 7432 Type *CurrentType = IV->getType(); 7433 do { 7434 if (auto *ST = dyn_cast<StructType>(CurrentType)) { 7435 for (auto *Elt : ST->elements()) 7436 if (Elt != ST->getElementType(0)) // check homogeneity 7437 return None; 7438 AggregateSize *= ST->getNumElements(); 7439 CurrentType = ST->getElementType(0); 7440 } else if (auto *AT = dyn_cast<ArrayType>(CurrentType)) { 7441 AggregateSize *= AT->getNumElements(); 7442 CurrentType = AT->getElementType(); 7443 } else if (auto *VT = dyn_cast<FixedVectorType>(CurrentType)) { 7444 AggregateSize *= VT->getNumElements(); 7445 return AggregateSize; 7446 } else if (CurrentType->isSingleValueType()) { 7447 return AggregateSize; 7448 } else { 7449 return None; 7450 } 7451 } while (true); 7452 } 7453 7454 static Optional<unsigned> getOperandIndex(Instruction *InsertInst, 7455 unsigned OperandOffset) { 7456 unsigned OperandIndex = OperandOffset; 7457 if (auto *IE = dyn_cast<InsertElementInst>(InsertInst)) { 7458 if (auto *CI = dyn_cast<ConstantInt>(IE->getOperand(2))) { 7459 auto *VT = cast<FixedVectorType>(IE->getType()); 7460 OperandIndex *= VT->getNumElements(); 7461 OperandIndex += CI->getZExtValue(); 7462 return OperandIndex; 7463 } 7464 return None; 7465 } 7466 7467 auto *IV = cast<InsertValueInst>(InsertInst); 7468 Type *CurrentType = IV->getType(); 7469 for (unsigned int Index : IV->indices()) { 7470 if (auto *ST = dyn_cast<StructType>(CurrentType)) { 7471 OperandIndex *= ST->getNumElements(); 7472 CurrentType = ST->getElementType(Index); 7473 } else if (auto *AT = dyn_cast<ArrayType>(CurrentType)) { 7474 OperandIndex *= AT->getNumElements(); 7475 CurrentType = AT->getElementType(); 7476 } else { 7477 return None; 7478 } 7479 OperandIndex += Index; 7480 } 7481 return OperandIndex; 7482 } 7483 7484 static bool findBuildAggregate_rec(Instruction *LastInsertInst, 7485 TargetTransformInfo *TTI, 7486 SmallVectorImpl<Value *> &BuildVectorOpds, 7487 SmallVectorImpl<Value *> &InsertElts, 7488 unsigned OperandOffset) { 7489 do { 7490 Value *InsertedOperand = LastInsertInst->getOperand(1); 7491 Optional<unsigned> OperandIndex = 7492 getOperandIndex(LastInsertInst, OperandOffset); 7493 if (!OperandIndex) 7494 return false; 7495 if (isa<InsertElementInst>(InsertedOperand) || 7496 isa<InsertValueInst>(InsertedOperand)) { 7497 if (!findBuildAggregate_rec(cast<Instruction>(InsertedOperand), TTI, 7498 BuildVectorOpds, InsertElts, *OperandIndex)) 7499 return false; 7500 } else { 7501 BuildVectorOpds[*OperandIndex] = InsertedOperand; 7502 InsertElts[*OperandIndex] = LastInsertInst; 7503 } 7504 if (isa<UndefValue>(LastInsertInst->getOperand(0))) 7505 return true; 7506 LastInsertInst = dyn_cast<Instruction>(LastInsertInst->getOperand(0)); 7507 } while (LastInsertInst != nullptr && 7508 (isa<InsertValueInst>(LastInsertInst) || 7509 isa<InsertElementInst>(LastInsertInst)) && 7510 LastInsertInst->hasOneUse()); 7511 return false; 7512 } 7513 7514 /// Recognize construction of vectors like 7515 /// %ra = insertelement <4 x float> poison, float %s0, i32 0 7516 /// %rb = insertelement <4 x float> %ra, float %s1, i32 1 7517 /// %rc = insertelement <4 x float> %rb, float %s2, i32 2 7518 /// %rd = insertelement <4 x float> %rc, float %s3, i32 3 7519 /// starting from the last insertelement or insertvalue instruction. 7520 /// 7521 /// Also recognize homogeneous aggregates like {<2 x float>, <2 x float>}, 7522 /// {{float, float}, {float, float}}, [2 x {float, float}] and so on. 7523 /// See llvm/test/Transforms/SLPVectorizer/X86/pr42022.ll for examples. 7524 /// 7525 /// Assume LastInsertInst is of InsertElementInst or InsertValueInst type. 7526 /// 7527 /// \return true if it matches. 7528 static bool findBuildAggregate(Instruction *LastInsertInst, 7529 TargetTransformInfo *TTI, 7530 SmallVectorImpl<Value *> &BuildVectorOpds, 7531 SmallVectorImpl<Value *> &InsertElts) { 7532 7533 assert((isa<InsertElementInst>(LastInsertInst) || 7534 isa<InsertValueInst>(LastInsertInst)) && 7535 "Expected insertelement or insertvalue instruction!"); 7536 7537 assert((BuildVectorOpds.empty() && InsertElts.empty()) && 7538 "Expected empty result vectors!"); 7539 7540 Optional<unsigned> AggregateSize = getAggregateSize(LastInsertInst); 7541 if (!AggregateSize) 7542 return false; 7543 BuildVectorOpds.resize(*AggregateSize); 7544 InsertElts.resize(*AggregateSize); 7545 7546 if (findBuildAggregate_rec(LastInsertInst, TTI, BuildVectorOpds, InsertElts, 7547 0)) { 7548 llvm::erase_value(BuildVectorOpds, nullptr); 7549 llvm::erase_value(InsertElts, nullptr); 7550 if (BuildVectorOpds.size() >= 2) 7551 return true; 7552 } 7553 7554 return false; 7555 } 7556 7557 static bool PhiTypeSorterFunc(Value *V, Value *V2) { 7558 return V->getType() < V2->getType(); 7559 } 7560 7561 /// Try and get a reduction value from a phi node. 7562 /// 7563 /// Given a phi node \p P in a block \p ParentBB, consider possible reductions 7564 /// if they come from either \p ParentBB or a containing loop latch. 7565 /// 7566 /// \returns A candidate reduction value if possible, or \code nullptr \endcode 7567 /// if not possible. 7568 static Value *getReductionValue(const DominatorTree *DT, PHINode *P, 7569 BasicBlock *ParentBB, LoopInfo *LI) { 7570 // There are situations where the reduction value is not dominated by the 7571 // reduction phi. Vectorizing such cases has been reported to cause 7572 // miscompiles. See PR25787. 7573 auto DominatedReduxValue = [&](Value *R) { 7574 return isa<Instruction>(R) && 7575 DT->dominates(P->getParent(), cast<Instruction>(R)->getParent()); 7576 }; 7577 7578 Value *Rdx = nullptr; 7579 7580 // Return the incoming value if it comes from the same BB as the phi node. 7581 if (P->getIncomingBlock(0) == ParentBB) { 7582 Rdx = P->getIncomingValue(0); 7583 } else if (P->getIncomingBlock(1) == ParentBB) { 7584 Rdx = P->getIncomingValue(1); 7585 } 7586 7587 if (Rdx && DominatedReduxValue(Rdx)) 7588 return Rdx; 7589 7590 // Otherwise, check whether we have a loop latch to look at. 7591 Loop *BBL = LI->getLoopFor(ParentBB); 7592 if (!BBL) 7593 return nullptr; 7594 BasicBlock *BBLatch = BBL->getLoopLatch(); 7595 if (!BBLatch) 7596 return nullptr; 7597 7598 // There is a loop latch, return the incoming value if it comes from 7599 // that. This reduction pattern occasionally turns up. 7600 if (P->getIncomingBlock(0) == BBLatch) { 7601 Rdx = P->getIncomingValue(0); 7602 } else if (P->getIncomingBlock(1) == BBLatch) { 7603 Rdx = P->getIncomingValue(1); 7604 } 7605 7606 if (Rdx && DominatedReduxValue(Rdx)) 7607 return Rdx; 7608 7609 return nullptr; 7610 } 7611 7612 static bool matchRdxBop(Instruction *I, Value *&V0, Value *&V1) { 7613 if (match(I, m_BinOp(m_Value(V0), m_Value(V1)))) 7614 return true; 7615 if (match(I, m_Intrinsic<Intrinsic::maxnum>(m_Value(V0), m_Value(V1)))) 7616 return true; 7617 if (match(I, m_Intrinsic<Intrinsic::minnum>(m_Value(V0), m_Value(V1)))) 7618 return true; 7619 if (match(I, m_Intrinsic<Intrinsic::smax>(m_Value(V0), m_Value(V1)))) 7620 return true; 7621 if (match(I, m_Intrinsic<Intrinsic::smin>(m_Value(V0), m_Value(V1)))) 7622 return true; 7623 if (match(I, m_Intrinsic<Intrinsic::umax>(m_Value(V0), m_Value(V1)))) 7624 return true; 7625 if (match(I, m_Intrinsic<Intrinsic::umin>(m_Value(V0), m_Value(V1)))) 7626 return true; 7627 return false; 7628 } 7629 7630 /// Attempt to reduce a horizontal reduction. 7631 /// If it is legal to match a horizontal reduction feeding the phi node \a P 7632 /// with reduction operators \a Root (or one of its operands) in a basic block 7633 /// \a BB, then check if it can be done. If horizontal reduction is not found 7634 /// and root instruction is a binary operation, vectorization of the operands is 7635 /// attempted. 7636 /// \returns true if a horizontal reduction was matched and reduced or operands 7637 /// of one of the binary instruction were vectorized. 7638 /// \returns false if a horizontal reduction was not matched (or not possible) 7639 /// or no vectorization of any binary operation feeding \a Root instruction was 7640 /// performed. 7641 static bool tryToVectorizeHorReductionOrInstOperands( 7642 PHINode *P, Instruction *Root, BasicBlock *BB, BoUpSLP &R, 7643 TargetTransformInfo *TTI, 7644 const function_ref<bool(Instruction *, BoUpSLP &)> Vectorize) { 7645 if (!ShouldVectorizeHor) 7646 return false; 7647 7648 if (!Root) 7649 return false; 7650 7651 if (Root->getParent() != BB || isa<PHINode>(Root)) 7652 return false; 7653 // Start analysis starting from Root instruction. If horizontal reduction is 7654 // found, try to vectorize it. If it is not a horizontal reduction or 7655 // vectorization is not possible or not effective, and currently analyzed 7656 // instruction is a binary operation, try to vectorize the operands, using 7657 // pre-order DFS traversal order. If the operands were not vectorized, repeat 7658 // the same procedure considering each operand as a possible root of the 7659 // horizontal reduction. 7660 // Interrupt the process if the Root instruction itself was vectorized or all 7661 // sub-trees not higher that RecursionMaxDepth were analyzed/vectorized. 7662 // Skip the analysis of CmpInsts.Compiler implements postanalysis of the 7663 // CmpInsts so we can skip extra attempts in 7664 // tryToVectorizeHorReductionOrInstOperands and save compile time. 7665 SmallVector<std::pair<Instruction *, unsigned>, 8> Stack(1, {Root, 0}); 7666 SmallPtrSet<Value *, 8> VisitedInstrs; 7667 bool Res = false; 7668 while (!Stack.empty()) { 7669 Instruction *Inst; 7670 unsigned Level; 7671 std::tie(Inst, Level) = Stack.pop_back_val(); 7672 Value *B0, *B1; 7673 bool IsBinop = matchRdxBop(Inst, B0, B1); 7674 bool IsSelect = match(Inst, m_Select(m_Value(), m_Value(), m_Value())); 7675 if (IsBinop || IsSelect) { 7676 HorizontalReduction HorRdx; 7677 if (HorRdx.matchAssociativeReduction(P, Inst)) { 7678 if (HorRdx.tryToReduce(R, TTI)) { 7679 Res = true; 7680 // Set P to nullptr to avoid re-analysis of phi node in 7681 // matchAssociativeReduction function unless this is the root node. 7682 P = nullptr; 7683 continue; 7684 } 7685 } 7686 if (P && IsBinop) { 7687 Inst = dyn_cast<Instruction>(B0); 7688 if (Inst == P) 7689 Inst = dyn_cast<Instruction>(B1); 7690 if (!Inst) { 7691 // Set P to nullptr to avoid re-analysis of phi node in 7692 // matchAssociativeReduction function unless this is the root node. 7693 P = nullptr; 7694 continue; 7695 } 7696 } 7697 } 7698 // Set P to nullptr to avoid re-analysis of phi node in 7699 // matchAssociativeReduction function unless this is the root node. 7700 P = nullptr; 7701 // Do not try to vectorize CmpInst operands, this is done separately. 7702 if (!isa<CmpInst>(Inst) && Vectorize(Inst, R)) { 7703 Res = true; 7704 continue; 7705 } 7706 7707 // Try to vectorize operands. 7708 // Continue analysis for the instruction from the same basic block only to 7709 // save compile time. 7710 if (++Level < RecursionMaxDepth) 7711 for (auto *Op : Inst->operand_values()) 7712 if (VisitedInstrs.insert(Op).second) 7713 if (auto *I = dyn_cast<Instruction>(Op)) 7714 // Do not try to vectorize CmpInst operands, this is done 7715 // separately. 7716 if (!isa<PHINode>(I) && !isa<CmpInst>(I) && !R.isDeleted(I) && 7717 I->getParent() == BB) 7718 Stack.emplace_back(I, Level); 7719 } 7720 return Res; 7721 } 7722 7723 bool SLPVectorizerPass::vectorizeRootInstruction(PHINode *P, Value *V, 7724 BasicBlock *BB, BoUpSLP &R, 7725 TargetTransformInfo *TTI) { 7726 auto *I = dyn_cast_or_null<Instruction>(V); 7727 if (!I) 7728 return false; 7729 7730 if (!isa<BinaryOperator>(I)) 7731 P = nullptr; 7732 // Try to match and vectorize a horizontal reduction. 7733 auto &&ExtraVectorization = [this](Instruction *I, BoUpSLP &R) -> bool { 7734 return tryToVectorize(I, R); 7735 }; 7736 return tryToVectorizeHorReductionOrInstOperands(P, I, BB, R, TTI, 7737 ExtraVectorization); 7738 } 7739 7740 bool SLPVectorizerPass::vectorizeInsertValueInst(InsertValueInst *IVI, 7741 BasicBlock *BB, BoUpSLP &R) { 7742 const DataLayout &DL = BB->getModule()->getDataLayout(); 7743 if (!R.canMapToVector(IVI->getType(), DL)) 7744 return false; 7745 7746 SmallVector<Value *, 16> BuildVectorOpds; 7747 SmallVector<Value *, 16> BuildVectorInsts; 7748 if (!findBuildAggregate(IVI, TTI, BuildVectorOpds, BuildVectorInsts)) 7749 return false; 7750 7751 LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IVI << "\n"); 7752 // Aggregate value is unlikely to be processed in vector register, we need to 7753 // extract scalars into scalar registers, so NeedExtraction is set true. 7754 return tryToVectorizeList(BuildVectorOpds, R, /*AllowReorder=*/false, 7755 BuildVectorInsts); 7756 } 7757 7758 bool SLPVectorizerPass::vectorizeInsertElementInst(InsertElementInst *IEI, 7759 BasicBlock *BB, BoUpSLP &R) { 7760 SmallVector<Value *, 16> BuildVectorInsts; 7761 SmallVector<Value *, 16> BuildVectorOpds; 7762 SmallVector<int> Mask; 7763 if (!findBuildAggregate(IEI, TTI, BuildVectorOpds, BuildVectorInsts) || 7764 (llvm::all_of(BuildVectorOpds, 7765 [](Value *V) { return isa<ExtractElementInst>(V); }) && 7766 isShuffle(BuildVectorOpds, Mask))) 7767 return false; 7768 7769 // Vectorize starting with the build vector operands ignoring the BuildVector 7770 // instructions for the purpose of scheduling and user extraction. 7771 return tryToVectorizeList(BuildVectorOpds, R, /*AllowReorder=*/false, 7772 BuildVectorInsts); 7773 } 7774 7775 bool SLPVectorizerPass::vectorizeSimpleInstructions( 7776 SmallVectorImpl<Instruction *> &Instructions, BasicBlock *BB, BoUpSLP &R, 7777 bool AtTerminator) { 7778 bool OpsChanged = false; 7779 SmallVector<Instruction *, 4> PostponedCmps; 7780 for (auto *I : reverse(Instructions)) { 7781 if (R.isDeleted(I)) 7782 continue; 7783 if (auto *LastInsertValue = dyn_cast<InsertValueInst>(I)) 7784 OpsChanged |= vectorizeInsertValueInst(LastInsertValue, BB, R); 7785 else if (auto *LastInsertElem = dyn_cast<InsertElementInst>(I)) 7786 OpsChanged |= vectorizeInsertElementInst(LastInsertElem, BB, R); 7787 else if (isa<CmpInst>(I)) 7788 PostponedCmps.push_back(I); 7789 } 7790 if (AtTerminator) { 7791 // Try to find reductions first. 7792 for (Instruction *I : PostponedCmps) { 7793 if (R.isDeleted(I)) 7794 continue; 7795 for (Value *Op : I->operands()) 7796 OpsChanged |= vectorizeRootInstruction(nullptr, Op, BB, R, TTI); 7797 } 7798 // Try to vectorize operands as vector bundles. 7799 for (Instruction *I : PostponedCmps) { 7800 if (R.isDeleted(I)) 7801 continue; 7802 OpsChanged |= tryToVectorize(I, R); 7803 } 7804 Instructions.clear(); 7805 } else { 7806 // Insert in reverse order since the PostponedCmps vector was filled in 7807 // reverse order. 7808 Instructions.assign(PostponedCmps.rbegin(), PostponedCmps.rend()); 7809 } 7810 return OpsChanged; 7811 } 7812 7813 bool SLPVectorizerPass::vectorizeChainsInBlock(BasicBlock *BB, BoUpSLP &R) { 7814 bool Changed = false; 7815 SmallVector<Value *, 4> Incoming; 7816 SmallPtrSet<Value *, 16> VisitedInstrs; 7817 7818 bool HaveVectorizedPhiNodes = true; 7819 while (HaveVectorizedPhiNodes) { 7820 HaveVectorizedPhiNodes = false; 7821 7822 // Collect the incoming values from the PHIs. 7823 Incoming.clear(); 7824 for (Instruction &I : *BB) { 7825 PHINode *P = dyn_cast<PHINode>(&I); 7826 if (!P) 7827 break; 7828 7829 if (!VisitedInstrs.count(P) && !R.isDeleted(P)) 7830 Incoming.push_back(P); 7831 } 7832 7833 // Sort by type. 7834 llvm::stable_sort(Incoming, PhiTypeSorterFunc); 7835 7836 // Try to vectorize elements base on their type. 7837 for (SmallVector<Value *, 4>::iterator IncIt = Incoming.begin(), 7838 E = Incoming.end(); 7839 IncIt != E;) { 7840 7841 // Look for the next elements with the same type. 7842 SmallVector<Value *, 4>::iterator SameTypeIt = IncIt; 7843 while (SameTypeIt != E && 7844 (*SameTypeIt)->getType() == (*IncIt)->getType()) { 7845 VisitedInstrs.insert(*SameTypeIt); 7846 ++SameTypeIt; 7847 } 7848 7849 // Try to vectorize them. 7850 unsigned NumElts = (SameTypeIt - IncIt); 7851 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize starting at PHIs (" 7852 << NumElts << ")\n"); 7853 // The order in which the phi nodes appear in the program does not matter. 7854 // So allow tryToVectorizeList to reorder them if it is beneficial. This 7855 // is done when there are exactly two elements since tryToVectorizeList 7856 // asserts that there are only two values when AllowReorder is true. 7857 bool AllowReorder = NumElts == 2; 7858 if (NumElts > 1 && 7859 tryToVectorizeList(makeArrayRef(IncIt, NumElts), R, AllowReorder)) { 7860 // Success start over because instructions might have been changed. 7861 HaveVectorizedPhiNodes = true; 7862 Changed = true; 7863 break; 7864 } 7865 7866 // Start over at the next instruction of a different type (or the end). 7867 IncIt = SameTypeIt; 7868 } 7869 } 7870 7871 VisitedInstrs.clear(); 7872 7873 SmallVector<Instruction *, 8> PostProcessInstructions; 7874 SmallDenseSet<Instruction *, 4> KeyNodes; 7875 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 7876 // Skip instructions with scalable type. The num of elements is unknown at 7877 // compile-time for scalable type. 7878 if (isa<ScalableVectorType>(it->getType())) 7879 continue; 7880 7881 // Skip instructions marked for the deletion. 7882 if (R.isDeleted(&*it)) 7883 continue; 7884 // We may go through BB multiple times so skip the one we have checked. 7885 if (!VisitedInstrs.insert(&*it).second) { 7886 if (it->use_empty() && KeyNodes.contains(&*it) && 7887 vectorizeSimpleInstructions(PostProcessInstructions, BB, R, 7888 it->isTerminator())) { 7889 // We would like to start over since some instructions are deleted 7890 // and the iterator may become invalid value. 7891 Changed = true; 7892 it = BB->begin(); 7893 e = BB->end(); 7894 } 7895 continue; 7896 } 7897 7898 if (isa<DbgInfoIntrinsic>(it)) 7899 continue; 7900 7901 // Try to vectorize reductions that use PHINodes. 7902 if (PHINode *P = dyn_cast<PHINode>(it)) { 7903 // Check that the PHI is a reduction PHI. 7904 if (P->getNumIncomingValues() == 2) { 7905 // Try to match and vectorize a horizontal reduction. 7906 if (vectorizeRootInstruction(P, getReductionValue(DT, P, BB, LI), BB, R, 7907 TTI)) { 7908 Changed = true; 7909 it = BB->begin(); 7910 e = BB->end(); 7911 continue; 7912 } 7913 } 7914 // Try to vectorize the incoming values of the PHI, to catch reductions 7915 // that feed into PHIs. 7916 for (unsigned I = 0, E = P->getNumIncomingValues(); I != E; I++) { 7917 // Skip if the incoming block is the current BB for now. Also, bypass 7918 // unreachable IR for efficiency and to avoid crashing. 7919 // TODO: Collect the skipped incoming values and try to vectorize them 7920 // after processing BB. 7921 if (BB == P->getIncomingBlock(I) || 7922 !DT->isReachableFromEntry(P->getIncomingBlock(I))) 7923 continue; 7924 7925 Changed |= vectorizeRootInstruction(nullptr, P->getIncomingValue(I), 7926 P->getIncomingBlock(I), R, TTI); 7927 } 7928 continue; 7929 } 7930 7931 // Ran into an instruction without users, like terminator, or function call 7932 // with ignored return value, store. Ignore unused instructions (basing on 7933 // instruction type, except for CallInst and InvokeInst). 7934 if (it->use_empty() && (it->getType()->isVoidTy() || isa<CallInst>(it) || 7935 isa<InvokeInst>(it))) { 7936 KeyNodes.insert(&*it); 7937 bool OpsChanged = false; 7938 if (ShouldStartVectorizeHorAtStore || !isa<StoreInst>(it)) { 7939 for (auto *V : it->operand_values()) { 7940 // Try to match and vectorize a horizontal reduction. 7941 OpsChanged |= vectorizeRootInstruction(nullptr, V, BB, R, TTI); 7942 } 7943 } 7944 // Start vectorization of post-process list of instructions from the 7945 // top-tree instructions to try to vectorize as many instructions as 7946 // possible. 7947 OpsChanged |= vectorizeSimpleInstructions(PostProcessInstructions, BB, R, 7948 it->isTerminator()); 7949 if (OpsChanged) { 7950 // We would like to start over since some instructions are deleted 7951 // and the iterator may become invalid value. 7952 Changed = true; 7953 it = BB->begin(); 7954 e = BB->end(); 7955 continue; 7956 } 7957 } 7958 7959 if (isa<InsertElementInst>(it) || isa<CmpInst>(it) || 7960 isa<InsertValueInst>(it)) 7961 PostProcessInstructions.push_back(&*it); 7962 } 7963 7964 return Changed; 7965 } 7966 7967 bool SLPVectorizerPass::vectorizeGEPIndices(BasicBlock *BB, BoUpSLP &R) { 7968 auto Changed = false; 7969 for (auto &Entry : GEPs) { 7970 // If the getelementptr list has fewer than two elements, there's nothing 7971 // to do. 7972 if (Entry.second.size() < 2) 7973 continue; 7974 7975 LLVM_DEBUG(dbgs() << "SLP: Analyzing a getelementptr list of length " 7976 << Entry.second.size() << ".\n"); 7977 7978 // Process the GEP list in chunks suitable for the target's supported 7979 // vector size. If a vector register can't hold 1 element, we are done. We 7980 // are trying to vectorize the index computations, so the maximum number of 7981 // elements is based on the size of the index expression, rather than the 7982 // size of the GEP itself (the target's pointer size). 7983 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 7984 unsigned EltSize = R.getVectorElementSize(*Entry.second[0]->idx_begin()); 7985 if (MaxVecRegSize < EltSize) 7986 continue; 7987 7988 unsigned MaxElts = MaxVecRegSize / EltSize; 7989 for (unsigned BI = 0, BE = Entry.second.size(); BI < BE; BI += MaxElts) { 7990 auto Len = std::min<unsigned>(BE - BI, MaxElts); 7991 ArrayRef<GetElementPtrInst *> GEPList(&Entry.second[BI], Len); 7992 7993 // Initialize a set a candidate getelementptrs. Note that we use a 7994 // SetVector here to preserve program order. If the index computations 7995 // are vectorizable and begin with loads, we want to minimize the chance 7996 // of having to reorder them later. 7997 SetVector<Value *> Candidates(GEPList.begin(), GEPList.end()); 7998 7999 // Some of the candidates may have already been vectorized after we 8000 // initially collected them. If so, they are marked as deleted, so remove 8001 // them from the set of candidates. 8002 Candidates.remove_if( 8003 [&R](Value *I) { return R.isDeleted(cast<Instruction>(I)); }); 8004 8005 // Remove from the set of candidates all pairs of getelementptrs with 8006 // constant differences. Such getelementptrs are likely not good 8007 // candidates for vectorization in a bottom-up phase since one can be 8008 // computed from the other. We also ensure all candidate getelementptr 8009 // indices are unique. 8010 for (int I = 0, E = GEPList.size(); I < E && Candidates.size() > 1; ++I) { 8011 auto *GEPI = GEPList[I]; 8012 if (!Candidates.count(GEPI)) 8013 continue; 8014 auto *SCEVI = SE->getSCEV(GEPList[I]); 8015 for (int J = I + 1; J < E && Candidates.size() > 1; ++J) { 8016 auto *GEPJ = GEPList[J]; 8017 auto *SCEVJ = SE->getSCEV(GEPList[J]); 8018 if (isa<SCEVConstant>(SE->getMinusSCEV(SCEVI, SCEVJ))) { 8019 Candidates.remove(GEPI); 8020 Candidates.remove(GEPJ); 8021 } else if (GEPI->idx_begin()->get() == GEPJ->idx_begin()->get()) { 8022 Candidates.remove(GEPJ); 8023 } 8024 } 8025 } 8026 8027 // We break out of the above computation as soon as we know there are 8028 // fewer than two candidates remaining. 8029 if (Candidates.size() < 2) 8030 continue; 8031 8032 // Add the single, non-constant index of each candidate to the bundle. We 8033 // ensured the indices met these constraints when we originally collected 8034 // the getelementptrs. 8035 SmallVector<Value *, 16> Bundle(Candidates.size()); 8036 auto BundleIndex = 0u; 8037 for (auto *V : Candidates) { 8038 auto *GEP = cast<GetElementPtrInst>(V); 8039 auto *GEPIdx = GEP->idx_begin()->get(); 8040 assert(GEP->getNumIndices() == 1 || !isa<Constant>(GEPIdx)); 8041 Bundle[BundleIndex++] = GEPIdx; 8042 } 8043 8044 // Try and vectorize the indices. We are currently only interested in 8045 // gather-like cases of the form: 8046 // 8047 // ... = g[a[0] - b[0]] + g[a[1] - b[1]] + ... 8048 // 8049 // where the loads of "a", the loads of "b", and the subtractions can be 8050 // performed in parallel. It's likely that detecting this pattern in a 8051 // bottom-up phase will be simpler and less costly than building a 8052 // full-blown top-down phase beginning at the consecutive loads. 8053 Changed |= tryToVectorizeList(Bundle, R); 8054 } 8055 } 8056 return Changed; 8057 } 8058 8059 bool SLPVectorizerPass::vectorizeStoreChains(BoUpSLP &R) { 8060 bool Changed = false; 8061 // Attempt to sort and vectorize each of the store-groups. 8062 for (StoreListMap::iterator it = Stores.begin(), e = Stores.end(); it != e; 8063 ++it) { 8064 if (it->second.size() < 2) 8065 continue; 8066 8067 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " 8068 << it->second.size() << ".\n"); 8069 8070 Changed |= vectorizeStores(it->second, R); 8071 } 8072 return Changed; 8073 } 8074 8075 char SLPVectorizer::ID = 0; 8076 8077 static const char lv_name[] = "SLP Vectorizer"; 8078 8079 INITIALIZE_PASS_BEGIN(SLPVectorizer, SV_NAME, lv_name, false, false) 8080 INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass) 8081 INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass) 8082 INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker) 8083 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass) 8084 INITIALIZE_PASS_DEPENDENCY(LoopSimplify) 8085 INITIALIZE_PASS_DEPENDENCY(DemandedBitsWrapperPass) 8086 INITIALIZE_PASS_DEPENDENCY(OptimizationRemarkEmitterWrapperPass) 8087 INITIALIZE_PASS_DEPENDENCY(InjectTLIMappingsLegacy) 8088 INITIALIZE_PASS_END(SLPVectorizer, SV_NAME, lv_name, false, false) 8089 8090 Pass *llvm::createSLPVectorizerPass() { return new SLPVectorizer(); } 8091