1 //===- SLPVectorizer.cpp - A bottom up SLP Vectorizer ---------------------===// 2 // 3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. 4 // See https://llvm.org/LICENSE.txt for license information. 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 6 // 7 //===----------------------------------------------------------------------===// 8 // 9 // This pass implements the Bottom Up SLP vectorizer. It detects consecutive 10 // stores that can be put together into vector-stores. Next, it attempts to 11 // construct vectorizable tree using the use-def chains. If a profitable tree 12 // was found, the SLP vectorizer performs vectorization on the tree. 13 // 14 // The pass is inspired by the work described in the paper: 15 // "Loop-Aware SLP in GCC" by Ira Rosen, Dorit Nuzman, Ayal Zaks. 16 // 17 //===----------------------------------------------------------------------===// 18 19 #include "llvm/Transforms/Vectorize/SLPVectorizer.h" 20 #include "llvm/ADT/ArrayRef.h" 21 #include "llvm/ADT/DenseMap.h" 22 #include "llvm/ADT/DenseSet.h" 23 #include "llvm/ADT/MapVector.h" 24 #include "llvm/ADT/None.h" 25 #include "llvm/ADT/Optional.h" 26 #include "llvm/ADT/PostOrderIterator.h" 27 #include "llvm/ADT/STLExtras.h" 28 #include "llvm/ADT/SetVector.h" 29 #include "llvm/ADT/SmallBitVector.h" 30 #include "llvm/ADT/SmallPtrSet.h" 31 #include "llvm/ADT/SmallSet.h" 32 #include "llvm/ADT/SmallString.h" 33 #include "llvm/ADT/SmallVector.h" 34 #include "llvm/ADT/Statistic.h" 35 #include "llvm/ADT/iterator.h" 36 #include "llvm/ADT/iterator_range.h" 37 #include "llvm/Analysis/AliasAnalysis.h" 38 #include "llvm/Analysis/CodeMetrics.h" 39 #include "llvm/Analysis/DemandedBits.h" 40 #include "llvm/Analysis/GlobalsModRef.h" 41 #include "llvm/Analysis/LoopAccessAnalysis.h" 42 #include "llvm/Analysis/LoopInfo.h" 43 #include "llvm/Analysis/MemoryLocation.h" 44 #include "llvm/Analysis/OptimizationRemarkEmitter.h" 45 #include "llvm/Analysis/ScalarEvolution.h" 46 #include "llvm/Analysis/ScalarEvolutionExpressions.h" 47 #include "llvm/Analysis/TargetLibraryInfo.h" 48 #include "llvm/Analysis/TargetTransformInfo.h" 49 #include "llvm/Analysis/ValueTracking.h" 50 #include "llvm/Analysis/VectorUtils.h" 51 #include "llvm/Analysis/AssumptionCache.h" 52 #include "llvm/IR/Attributes.h" 53 #include "llvm/IR/BasicBlock.h" 54 #include "llvm/IR/Constant.h" 55 #include "llvm/IR/Constants.h" 56 #include "llvm/IR/DataLayout.h" 57 #include "llvm/IR/DebugLoc.h" 58 #include "llvm/IR/DerivedTypes.h" 59 #include "llvm/IR/Dominators.h" 60 #include "llvm/IR/Function.h" 61 #include "llvm/IR/IRBuilder.h" 62 #include "llvm/IR/InstrTypes.h" 63 #include "llvm/IR/Instruction.h" 64 #include "llvm/IR/Instructions.h" 65 #include "llvm/IR/IntrinsicInst.h" 66 #include "llvm/IR/Intrinsics.h" 67 #include "llvm/IR/Module.h" 68 #include "llvm/IR/NoFolder.h" 69 #include "llvm/IR/Operator.h" 70 #include "llvm/IR/PassManager.h" 71 #include "llvm/IR/PatternMatch.h" 72 #include "llvm/IR/Type.h" 73 #include "llvm/IR/Use.h" 74 #include "llvm/IR/User.h" 75 #include "llvm/IR/Value.h" 76 #include "llvm/IR/ValueHandle.h" 77 #include "llvm/IR/Verifier.h" 78 #include "llvm/InitializePasses.h" 79 #include "llvm/Pass.h" 80 #include "llvm/Support/Casting.h" 81 #include "llvm/Support/CommandLine.h" 82 #include "llvm/Support/Compiler.h" 83 #include "llvm/Support/DOTGraphTraits.h" 84 #include "llvm/Support/Debug.h" 85 #include "llvm/Support/ErrorHandling.h" 86 #include "llvm/Support/GraphWriter.h" 87 #include "llvm/Support/KnownBits.h" 88 #include "llvm/Support/MathExtras.h" 89 #include "llvm/Support/raw_ostream.h" 90 #include "llvm/Transforms/Utils/InjectTLIMappings.h" 91 #include "llvm/Transforms/Utils/LoopUtils.h" 92 #include "llvm/Transforms/Vectorize.h" 93 #include <algorithm> 94 #include <cassert> 95 #include <cstdint> 96 #include <iterator> 97 #include <memory> 98 #include <set> 99 #include <string> 100 #include <tuple> 101 #include <utility> 102 #include <vector> 103 104 using namespace llvm; 105 using namespace llvm::PatternMatch; 106 using namespace slpvectorizer; 107 108 #define SV_NAME "slp-vectorizer" 109 #define DEBUG_TYPE "SLP" 110 111 STATISTIC(NumVectorInstructions, "Number of vector instructions generated"); 112 113 cl::opt<bool> RunSLPVectorization("vectorize-slp", cl::init(true), cl::Hidden, 114 cl::desc("Run the SLP vectorization passes")); 115 116 static cl::opt<int> 117 SLPCostThreshold("slp-threshold", cl::init(0), cl::Hidden, 118 cl::desc("Only vectorize if you gain more than this " 119 "number ")); 120 121 static cl::opt<bool> 122 ShouldVectorizeHor("slp-vectorize-hor", cl::init(true), cl::Hidden, 123 cl::desc("Attempt to vectorize horizontal reductions")); 124 125 static cl::opt<bool> ShouldStartVectorizeHorAtStore( 126 "slp-vectorize-hor-store", cl::init(false), cl::Hidden, 127 cl::desc( 128 "Attempt to vectorize horizontal reductions feeding into a store")); 129 130 static cl::opt<int> 131 MaxVectorRegSizeOption("slp-max-reg-size", cl::init(128), cl::Hidden, 132 cl::desc("Attempt to vectorize for this register size in bits")); 133 134 static cl::opt<int> 135 MaxStoreLookup("slp-max-store-lookup", cl::init(32), cl::Hidden, 136 cl::desc("Maximum depth of the lookup for consecutive stores.")); 137 138 /// Limits the size of scheduling regions in a block. 139 /// It avoid long compile times for _very_ large blocks where vector 140 /// instructions are spread over a wide range. 141 /// This limit is way higher than needed by real-world functions. 142 static cl::opt<int> 143 ScheduleRegionSizeBudget("slp-schedule-budget", cl::init(100000), cl::Hidden, 144 cl::desc("Limit the size of the SLP scheduling region per block")); 145 146 static cl::opt<int> MinVectorRegSizeOption( 147 "slp-min-reg-size", cl::init(128), cl::Hidden, 148 cl::desc("Attempt to vectorize for this register size in bits")); 149 150 static cl::opt<unsigned> RecursionMaxDepth( 151 "slp-recursion-max-depth", cl::init(12), cl::Hidden, 152 cl::desc("Limit the recursion depth when building a vectorizable tree")); 153 154 static cl::opt<unsigned> MinTreeSize( 155 "slp-min-tree-size", cl::init(3), cl::Hidden, 156 cl::desc("Only vectorize small trees if they are fully vectorizable")); 157 158 // The maximum depth that the look-ahead score heuristic will explore. 159 // The higher this value, the higher the compilation time overhead. 160 static cl::opt<int> LookAheadMaxDepth( 161 "slp-max-look-ahead-depth", cl::init(2), cl::Hidden, 162 cl::desc("The maximum look-ahead depth for operand reordering scores")); 163 164 // The Look-ahead heuristic goes through the users of the bundle to calculate 165 // the users cost in getExternalUsesCost(). To avoid compilation time increase 166 // we limit the number of users visited to this value. 167 static cl::opt<unsigned> LookAheadUsersBudget( 168 "slp-look-ahead-users-budget", cl::init(2), cl::Hidden, 169 cl::desc("The maximum number of users to visit while visiting the " 170 "predecessors. This prevents compilation time increase.")); 171 172 static cl::opt<bool> 173 ViewSLPTree("view-slp-tree", cl::Hidden, 174 cl::desc("Display the SLP trees with Graphviz")); 175 176 // Limit the number of alias checks. The limit is chosen so that 177 // it has no negative effect on the llvm benchmarks. 178 static const unsigned AliasedCheckLimit = 10; 179 180 // Another limit for the alias checks: The maximum distance between load/store 181 // instructions where alias checks are done. 182 // This limit is useful for very large basic blocks. 183 static const unsigned MaxMemDepDistance = 160; 184 185 /// If the ScheduleRegionSizeBudget is exhausted, we allow small scheduling 186 /// regions to be handled. 187 static const int MinScheduleRegionSize = 16; 188 189 /// Predicate for the element types that the SLP vectorizer supports. 190 /// 191 /// The most important thing to filter here are types which are invalid in LLVM 192 /// vectors. We also filter target specific types which have absolutely no 193 /// meaningful vectorization path such as x86_fp80 and ppc_f128. This just 194 /// avoids spending time checking the cost model and realizing that they will 195 /// be inevitably scalarized. 196 static bool isValidElementType(Type *Ty) { 197 return VectorType::isValidElementType(Ty) && !Ty->isX86_FP80Ty() && 198 !Ty->isPPC_FP128Ty(); 199 } 200 201 /// \returns true if all of the instructions in \p VL are in the same block or 202 /// false otherwise. 203 static bool allSameBlock(ArrayRef<Value *> VL) { 204 Instruction *I0 = dyn_cast<Instruction>(VL[0]); 205 if (!I0) 206 return false; 207 BasicBlock *BB = I0->getParent(); 208 for (int i = 1, e = VL.size(); i < e; i++) { 209 Instruction *I = dyn_cast<Instruction>(VL[i]); 210 if (!I) 211 return false; 212 213 if (BB != I->getParent()) 214 return false; 215 } 216 return true; 217 } 218 219 /// \returns True if all of the values in \p VL are constants (but not 220 /// globals/constant expressions). 221 static bool allConstant(ArrayRef<Value *> VL) { 222 // Constant expressions and globals can't be vectorized like normal integer/FP 223 // constants. 224 for (Value *i : VL) 225 if (!isa<Constant>(i) || isa<ConstantExpr>(i) || isa<GlobalValue>(i)) 226 return false; 227 return true; 228 } 229 230 /// \returns True if all of the values in \p VL are identical. 231 static bool isSplat(ArrayRef<Value *> VL) { 232 for (unsigned i = 1, e = VL.size(); i < e; ++i) 233 if (VL[i] != VL[0]) 234 return false; 235 return true; 236 } 237 238 /// \returns True if \p I is commutative, handles CmpInst and BinaryOperator. 239 static bool isCommutative(Instruction *I) { 240 if (auto *Cmp = dyn_cast<CmpInst>(I)) 241 return Cmp->isCommutative(); 242 if (auto *BO = dyn_cast<BinaryOperator>(I)) 243 return BO->isCommutative(); 244 // TODO: This should check for generic Instruction::isCommutative(), but 245 // we need to confirm that the caller code correctly handles Intrinsics 246 // for example (does not have 2 operands). 247 return false; 248 } 249 250 /// Checks if the vector of instructions can be represented as a shuffle, like: 251 /// %x0 = extractelement <4 x i8> %x, i32 0 252 /// %x3 = extractelement <4 x i8> %x, i32 3 253 /// %y1 = extractelement <4 x i8> %y, i32 1 254 /// %y2 = extractelement <4 x i8> %y, i32 2 255 /// %x0x0 = mul i8 %x0, %x0 256 /// %x3x3 = mul i8 %x3, %x3 257 /// %y1y1 = mul i8 %y1, %y1 258 /// %y2y2 = mul i8 %y2, %y2 259 /// %ins1 = insertelement <4 x i8> undef, i8 %x0x0, i32 0 260 /// %ins2 = insertelement <4 x i8> %ins1, i8 %x3x3, i32 1 261 /// %ins3 = insertelement <4 x i8> %ins2, i8 %y1y1, i32 2 262 /// %ins4 = insertelement <4 x i8> %ins3, i8 %y2y2, i32 3 263 /// ret <4 x i8> %ins4 264 /// can be transformed into: 265 /// %1 = shufflevector <4 x i8> %x, <4 x i8> %y, <4 x i32> <i32 0, i32 3, i32 5, 266 /// i32 6> 267 /// %2 = mul <4 x i8> %1, %1 268 /// ret <4 x i8> %2 269 /// We convert this initially to something like: 270 /// %x0 = extractelement <4 x i8> %x, i32 0 271 /// %x3 = extractelement <4 x i8> %x, i32 3 272 /// %y1 = extractelement <4 x i8> %y, i32 1 273 /// %y2 = extractelement <4 x i8> %y, i32 2 274 /// %1 = insertelement <4 x i8> undef, i8 %x0, i32 0 275 /// %2 = insertelement <4 x i8> %1, i8 %x3, i32 1 276 /// %3 = insertelement <4 x i8> %2, i8 %y1, i32 2 277 /// %4 = insertelement <4 x i8> %3, i8 %y2, i32 3 278 /// %5 = mul <4 x i8> %4, %4 279 /// %6 = extractelement <4 x i8> %5, i32 0 280 /// %ins1 = insertelement <4 x i8> undef, i8 %6, i32 0 281 /// %7 = extractelement <4 x i8> %5, i32 1 282 /// %ins2 = insertelement <4 x i8> %ins1, i8 %7, i32 1 283 /// %8 = extractelement <4 x i8> %5, i32 2 284 /// %ins3 = insertelement <4 x i8> %ins2, i8 %8, i32 2 285 /// %9 = extractelement <4 x i8> %5, i32 3 286 /// %ins4 = insertelement <4 x i8> %ins3, i8 %9, i32 3 287 /// ret <4 x i8> %ins4 288 /// InstCombiner transforms this into a shuffle and vector mul 289 /// TODO: Can we split off and reuse the shuffle mask detection from 290 /// TargetTransformInfo::getInstructionThroughput? 291 static Optional<TargetTransformInfo::ShuffleKind> 292 isShuffle(ArrayRef<Value *> VL) { 293 auto *EI0 = cast<ExtractElementInst>(VL[0]); 294 unsigned Size = 295 cast<FixedVectorType>(EI0->getVectorOperandType())->getNumElements(); 296 Value *Vec1 = nullptr; 297 Value *Vec2 = nullptr; 298 enum ShuffleMode { Unknown, Select, Permute }; 299 ShuffleMode CommonShuffleMode = Unknown; 300 for (unsigned I = 0, E = VL.size(); I < E; ++I) { 301 auto *EI = cast<ExtractElementInst>(VL[I]); 302 auto *Vec = EI->getVectorOperand(); 303 // All vector operands must have the same number of vector elements. 304 if (cast<FixedVectorType>(Vec->getType())->getNumElements() != Size) 305 return None; 306 auto *Idx = dyn_cast<ConstantInt>(EI->getIndexOperand()); 307 if (!Idx) 308 return None; 309 // Undefined behavior if Idx is negative or >= Size. 310 if (Idx->getValue().uge(Size)) 311 continue; 312 unsigned IntIdx = Idx->getValue().getZExtValue(); 313 // We can extractelement from undef vector. 314 if (isa<UndefValue>(Vec)) 315 continue; 316 // For correct shuffling we have to have at most 2 different vector operands 317 // in all extractelement instructions. 318 if (!Vec1 || Vec1 == Vec) 319 Vec1 = Vec; 320 else if (!Vec2 || Vec2 == Vec) 321 Vec2 = Vec; 322 else 323 return None; 324 if (CommonShuffleMode == Permute) 325 continue; 326 // If the extract index is not the same as the operation number, it is a 327 // permutation. 328 if (IntIdx != I) { 329 CommonShuffleMode = Permute; 330 continue; 331 } 332 CommonShuffleMode = Select; 333 } 334 // If we're not crossing lanes in different vectors, consider it as blending. 335 if (CommonShuffleMode == Select && Vec2) 336 return TargetTransformInfo::SK_Select; 337 // If Vec2 was never used, we have a permutation of a single vector, otherwise 338 // we have permutation of 2 vectors. 339 return Vec2 ? TargetTransformInfo::SK_PermuteTwoSrc 340 : TargetTransformInfo::SK_PermuteSingleSrc; 341 } 342 343 namespace { 344 345 /// Main data required for vectorization of instructions. 346 struct InstructionsState { 347 /// The very first instruction in the list with the main opcode. 348 Value *OpValue = nullptr; 349 350 /// The main/alternate instruction. 351 Instruction *MainOp = nullptr; 352 Instruction *AltOp = nullptr; 353 354 /// The main/alternate opcodes for the list of instructions. 355 unsigned getOpcode() const { 356 return MainOp ? MainOp->getOpcode() : 0; 357 } 358 359 unsigned getAltOpcode() const { 360 return AltOp ? AltOp->getOpcode() : 0; 361 } 362 363 /// Some of the instructions in the list have alternate opcodes. 364 bool isAltShuffle() const { return getOpcode() != getAltOpcode(); } 365 366 bool isOpcodeOrAlt(Instruction *I) const { 367 unsigned CheckedOpcode = I->getOpcode(); 368 return getOpcode() == CheckedOpcode || getAltOpcode() == CheckedOpcode; 369 } 370 371 InstructionsState() = delete; 372 InstructionsState(Value *OpValue, Instruction *MainOp, Instruction *AltOp) 373 : OpValue(OpValue), MainOp(MainOp), AltOp(AltOp) {} 374 }; 375 376 } // end anonymous namespace 377 378 /// Chooses the correct key for scheduling data. If \p Op has the same (or 379 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is \p 380 /// OpValue. 381 static Value *isOneOf(const InstructionsState &S, Value *Op) { 382 auto *I = dyn_cast<Instruction>(Op); 383 if (I && S.isOpcodeOrAlt(I)) 384 return Op; 385 return S.OpValue; 386 } 387 388 /// \returns true if \p Opcode is allowed as part of of the main/alternate 389 /// instruction for SLP vectorization. 390 /// 391 /// Example of unsupported opcode is SDIV that can potentially cause UB if the 392 /// "shuffled out" lane would result in division by zero. 393 static bool isValidForAlternation(unsigned Opcode) { 394 if (Instruction::isIntDivRem(Opcode)) 395 return false; 396 397 return true; 398 } 399 400 /// \returns analysis of the Instructions in \p VL described in 401 /// InstructionsState, the Opcode that we suppose the whole list 402 /// could be vectorized even if its structure is diverse. 403 static InstructionsState getSameOpcode(ArrayRef<Value *> VL, 404 unsigned BaseIndex = 0) { 405 // Make sure these are all Instructions. 406 if (llvm::any_of(VL, [](Value *V) { return !isa<Instruction>(V); })) 407 return InstructionsState(VL[BaseIndex], nullptr, nullptr); 408 409 bool IsCastOp = isa<CastInst>(VL[BaseIndex]); 410 bool IsBinOp = isa<BinaryOperator>(VL[BaseIndex]); 411 unsigned Opcode = cast<Instruction>(VL[BaseIndex])->getOpcode(); 412 unsigned AltOpcode = Opcode; 413 unsigned AltIndex = BaseIndex; 414 415 // Check for one alternate opcode from another BinaryOperator. 416 // TODO - generalize to support all operators (types, calls etc.). 417 for (int Cnt = 0, E = VL.size(); Cnt < E; Cnt++) { 418 unsigned InstOpcode = cast<Instruction>(VL[Cnt])->getOpcode(); 419 if (IsBinOp && isa<BinaryOperator>(VL[Cnt])) { 420 if (InstOpcode == Opcode || InstOpcode == AltOpcode) 421 continue; 422 if (Opcode == AltOpcode && isValidForAlternation(InstOpcode) && 423 isValidForAlternation(Opcode)) { 424 AltOpcode = InstOpcode; 425 AltIndex = Cnt; 426 continue; 427 } 428 } else if (IsCastOp && isa<CastInst>(VL[Cnt])) { 429 Type *Ty0 = cast<Instruction>(VL[BaseIndex])->getOperand(0)->getType(); 430 Type *Ty1 = cast<Instruction>(VL[Cnt])->getOperand(0)->getType(); 431 if (Ty0 == Ty1) { 432 if (InstOpcode == Opcode || InstOpcode == AltOpcode) 433 continue; 434 if (Opcode == AltOpcode) { 435 assert(isValidForAlternation(Opcode) && 436 isValidForAlternation(InstOpcode) && 437 "Cast isn't safe for alternation, logic needs to be updated!"); 438 AltOpcode = InstOpcode; 439 AltIndex = Cnt; 440 continue; 441 } 442 } 443 } else if (InstOpcode == Opcode || InstOpcode == AltOpcode) 444 continue; 445 return InstructionsState(VL[BaseIndex], nullptr, nullptr); 446 } 447 448 return InstructionsState(VL[BaseIndex], cast<Instruction>(VL[BaseIndex]), 449 cast<Instruction>(VL[AltIndex])); 450 } 451 452 /// \returns true if all of the values in \p VL have the same type or false 453 /// otherwise. 454 static bool allSameType(ArrayRef<Value *> VL) { 455 Type *Ty = VL[0]->getType(); 456 for (int i = 1, e = VL.size(); i < e; i++) 457 if (VL[i]->getType() != Ty) 458 return false; 459 460 return true; 461 } 462 463 /// \returns True if Extract{Value,Element} instruction extracts element Idx. 464 static Optional<unsigned> getExtractIndex(Instruction *E) { 465 unsigned Opcode = E->getOpcode(); 466 assert((Opcode == Instruction::ExtractElement || 467 Opcode == Instruction::ExtractValue) && 468 "Expected extractelement or extractvalue instruction."); 469 if (Opcode == Instruction::ExtractElement) { 470 auto *CI = dyn_cast<ConstantInt>(E->getOperand(1)); 471 if (!CI) 472 return None; 473 return CI->getZExtValue(); 474 } 475 ExtractValueInst *EI = cast<ExtractValueInst>(E); 476 if (EI->getNumIndices() != 1) 477 return None; 478 return *EI->idx_begin(); 479 } 480 481 /// \returns True if in-tree use also needs extract. This refers to 482 /// possible scalar operand in vectorized instruction. 483 static bool InTreeUserNeedToExtract(Value *Scalar, Instruction *UserInst, 484 TargetLibraryInfo *TLI) { 485 unsigned Opcode = UserInst->getOpcode(); 486 switch (Opcode) { 487 case Instruction::Load: { 488 LoadInst *LI = cast<LoadInst>(UserInst); 489 return (LI->getPointerOperand() == Scalar); 490 } 491 case Instruction::Store: { 492 StoreInst *SI = cast<StoreInst>(UserInst); 493 return (SI->getPointerOperand() == Scalar); 494 } 495 case Instruction::Call: { 496 CallInst *CI = cast<CallInst>(UserInst); 497 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 498 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 499 if (hasVectorInstrinsicScalarOpd(ID, i)) 500 return (CI->getArgOperand(i) == Scalar); 501 } 502 LLVM_FALLTHROUGH; 503 } 504 default: 505 return false; 506 } 507 } 508 509 /// \returns the AA location that is being access by the instruction. 510 static MemoryLocation getLocation(Instruction *I, AliasAnalysis *AA) { 511 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 512 return MemoryLocation::get(SI); 513 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 514 return MemoryLocation::get(LI); 515 return MemoryLocation(); 516 } 517 518 /// \returns True if the instruction is not a volatile or atomic load/store. 519 static bool isSimple(Instruction *I) { 520 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 521 return LI->isSimple(); 522 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 523 return SI->isSimple(); 524 if (MemIntrinsic *MI = dyn_cast<MemIntrinsic>(I)) 525 return !MI->isVolatile(); 526 return true; 527 } 528 529 namespace llvm { 530 531 namespace slpvectorizer { 532 533 /// Bottom Up SLP Vectorizer. 534 class BoUpSLP { 535 struct TreeEntry; 536 struct ScheduleData; 537 538 public: 539 using ValueList = SmallVector<Value *, 8>; 540 using InstrList = SmallVector<Instruction *, 16>; 541 using ValueSet = SmallPtrSet<Value *, 16>; 542 using StoreList = SmallVector<StoreInst *, 8>; 543 using ExtraValueToDebugLocsMap = 544 MapVector<Value *, SmallVector<Instruction *, 2>>; 545 546 BoUpSLP(Function *Func, ScalarEvolution *Se, TargetTransformInfo *Tti, 547 TargetLibraryInfo *TLi, AliasAnalysis *Aa, LoopInfo *Li, 548 DominatorTree *Dt, AssumptionCache *AC, DemandedBits *DB, 549 const DataLayout *DL, OptimizationRemarkEmitter *ORE) 550 : F(Func), SE(Se), TTI(Tti), TLI(TLi), AA(Aa), LI(Li), DT(Dt), AC(AC), 551 DB(DB), DL(DL), ORE(ORE), Builder(Se->getContext()) { 552 CodeMetrics::collectEphemeralValues(F, AC, EphValues); 553 // Use the vector register size specified by the target unless overridden 554 // by a command-line option. 555 // TODO: It would be better to limit the vectorization factor based on 556 // data type rather than just register size. For example, x86 AVX has 557 // 256-bit registers, but it does not support integer operations 558 // at that width (that requires AVX2). 559 if (MaxVectorRegSizeOption.getNumOccurrences()) 560 MaxVecRegSize = MaxVectorRegSizeOption; 561 else 562 MaxVecRegSize = TTI->getRegisterBitWidth(true); 563 564 if (MinVectorRegSizeOption.getNumOccurrences()) 565 MinVecRegSize = MinVectorRegSizeOption; 566 else 567 MinVecRegSize = TTI->getMinVectorRegisterBitWidth(); 568 } 569 570 /// Vectorize the tree that starts with the elements in \p VL. 571 /// Returns the vectorized root. 572 Value *vectorizeTree(); 573 574 /// Vectorize the tree but with the list of externally used values \p 575 /// ExternallyUsedValues. Values in this MapVector can be replaced but the 576 /// generated extractvalue instructions. 577 Value *vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues); 578 579 /// \returns the cost incurred by unwanted spills and fills, caused by 580 /// holding live values over call sites. 581 int getSpillCost() const; 582 583 /// \returns the vectorization cost of the subtree that starts at \p VL. 584 /// A negative number means that this is profitable. 585 int getTreeCost(); 586 587 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 588 /// the purpose of scheduling and extraction in the \p UserIgnoreLst. 589 void buildTree(ArrayRef<Value *> Roots, 590 ArrayRef<Value *> UserIgnoreLst = None); 591 592 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 593 /// the purpose of scheduling and extraction in the \p UserIgnoreLst taking 594 /// into account (and updating it, if required) list of externally used 595 /// values stored in \p ExternallyUsedValues. 596 void buildTree(ArrayRef<Value *> Roots, 597 ExtraValueToDebugLocsMap &ExternallyUsedValues, 598 ArrayRef<Value *> UserIgnoreLst = None); 599 600 /// Clear the internal data structures that are created by 'buildTree'. 601 void deleteTree() { 602 VectorizableTree.clear(); 603 ScalarToTreeEntry.clear(); 604 MustGather.clear(); 605 ExternalUses.clear(); 606 NumOpsWantToKeepOrder.clear(); 607 NumOpsWantToKeepOriginalOrder = 0; 608 for (auto &Iter : BlocksSchedules) { 609 BlockScheduling *BS = Iter.second.get(); 610 BS->clear(); 611 } 612 MinBWs.clear(); 613 } 614 615 unsigned getTreeSize() const { return VectorizableTree.size(); } 616 617 /// Perform LICM and CSE on the newly generated gather sequences. 618 void optimizeGatherSequence(); 619 620 /// \returns The best order of instructions for vectorization. 621 Optional<ArrayRef<unsigned>> bestOrder() const { 622 auto I = std::max_element( 623 NumOpsWantToKeepOrder.begin(), NumOpsWantToKeepOrder.end(), 624 [](const decltype(NumOpsWantToKeepOrder)::value_type &D1, 625 const decltype(NumOpsWantToKeepOrder)::value_type &D2) { 626 return D1.second < D2.second; 627 }); 628 if (I == NumOpsWantToKeepOrder.end() || 629 I->getSecond() <= NumOpsWantToKeepOriginalOrder) 630 return None; 631 632 return makeArrayRef(I->getFirst()); 633 } 634 635 /// \return The vector element size in bits to use when vectorizing the 636 /// expression tree ending at \p V. If V is a store, the size is the width of 637 /// the stored value. Otherwise, the size is the width of the largest loaded 638 /// value reaching V. This method is used by the vectorizer to calculate 639 /// vectorization factors. 640 unsigned getVectorElementSize(Value *V); 641 642 /// Compute the minimum type sizes required to represent the entries in a 643 /// vectorizable tree. 644 void computeMinimumValueSizes(); 645 646 // \returns maximum vector register size as set by TTI or overridden by cl::opt. 647 unsigned getMaxVecRegSize() const { 648 return MaxVecRegSize; 649 } 650 651 // \returns minimum vector register size as set by cl::opt. 652 unsigned getMinVecRegSize() const { 653 return MinVecRegSize; 654 } 655 656 /// Check if homogeneous aggregate is isomorphic to some VectorType. 657 /// Accepts homogeneous multidimensional aggregate of scalars/vectors like 658 /// {[4 x i16], [4 x i16]}, { <2 x float>, <2 x float> }, 659 /// {{{i16, i16}, {i16, i16}}, {{i16, i16}, {i16, i16}}} and so on. 660 /// 661 /// \returns number of elements in vector if isomorphism exists, 0 otherwise. 662 unsigned canMapToVector(Type *T, const DataLayout &DL) const; 663 664 /// \returns True if the VectorizableTree is both tiny and not fully 665 /// vectorizable. We do not vectorize such trees. 666 bool isTreeTinyAndNotFullyVectorizable() const; 667 668 /// Assume that a legal-sized 'or'-reduction of shifted/zexted loaded values 669 /// can be load combined in the backend. Load combining may not be allowed in 670 /// the IR optimizer, so we do not want to alter the pattern. For example, 671 /// partially transforming a scalar bswap() pattern into vector code is 672 /// effectively impossible for the backend to undo. 673 /// TODO: If load combining is allowed in the IR optimizer, this analysis 674 /// may not be necessary. 675 bool isLoadCombineReductionCandidate(unsigned ReductionOpcode) const; 676 677 /// Assume that a vector of stores of bitwise-or/shifted/zexted loaded values 678 /// can be load combined in the backend. Load combining may not be allowed in 679 /// the IR optimizer, so we do not want to alter the pattern. For example, 680 /// partially transforming a scalar bswap() pattern into vector code is 681 /// effectively impossible for the backend to undo. 682 /// TODO: If load combining is allowed in the IR optimizer, this analysis 683 /// may not be necessary. 684 bool isLoadCombineCandidate() const; 685 686 OptimizationRemarkEmitter *getORE() { return ORE; } 687 688 /// This structure holds any data we need about the edges being traversed 689 /// during buildTree_rec(). We keep track of: 690 /// (i) the user TreeEntry index, and 691 /// (ii) the index of the edge. 692 struct EdgeInfo { 693 EdgeInfo() = default; 694 EdgeInfo(TreeEntry *UserTE, unsigned EdgeIdx) 695 : UserTE(UserTE), EdgeIdx(EdgeIdx) {} 696 /// The user TreeEntry. 697 TreeEntry *UserTE = nullptr; 698 /// The operand index of the use. 699 unsigned EdgeIdx = UINT_MAX; 700 #ifndef NDEBUG 701 friend inline raw_ostream &operator<<(raw_ostream &OS, 702 const BoUpSLP::EdgeInfo &EI) { 703 EI.dump(OS); 704 return OS; 705 } 706 /// Debug print. 707 void dump(raw_ostream &OS) const { 708 OS << "{User:" << (UserTE ? std::to_string(UserTE->Idx) : "null") 709 << " EdgeIdx:" << EdgeIdx << "}"; 710 } 711 LLVM_DUMP_METHOD void dump() const { dump(dbgs()); } 712 #endif 713 }; 714 715 /// A helper data structure to hold the operands of a vector of instructions. 716 /// This supports a fixed vector length for all operand vectors. 717 class VLOperands { 718 /// For each operand we need (i) the value, and (ii) the opcode that it 719 /// would be attached to if the expression was in a left-linearized form. 720 /// This is required to avoid illegal operand reordering. 721 /// For example: 722 /// \verbatim 723 /// 0 Op1 724 /// |/ 725 /// Op1 Op2 Linearized + Op2 726 /// \ / ----------> |/ 727 /// - - 728 /// 729 /// Op1 - Op2 (0 + Op1) - Op2 730 /// \endverbatim 731 /// 732 /// Value Op1 is attached to a '+' operation, and Op2 to a '-'. 733 /// 734 /// Another way to think of this is to track all the operations across the 735 /// path from the operand all the way to the root of the tree and to 736 /// calculate the operation that corresponds to this path. For example, the 737 /// path from Op2 to the root crosses the RHS of the '-', therefore the 738 /// corresponding operation is a '-' (which matches the one in the 739 /// linearized tree, as shown above). 740 /// 741 /// For lack of a better term, we refer to this operation as Accumulated 742 /// Path Operation (APO). 743 struct OperandData { 744 OperandData() = default; 745 OperandData(Value *V, bool APO, bool IsUsed) 746 : V(V), APO(APO), IsUsed(IsUsed) {} 747 /// The operand value. 748 Value *V = nullptr; 749 /// TreeEntries only allow a single opcode, or an alternate sequence of 750 /// them (e.g, +, -). Therefore, we can safely use a boolean value for the 751 /// APO. It is set to 'true' if 'V' is attached to an inverse operation 752 /// in the left-linearized form (e.g., Sub/Div), and 'false' otherwise 753 /// (e.g., Add/Mul) 754 bool APO = false; 755 /// Helper data for the reordering function. 756 bool IsUsed = false; 757 }; 758 759 /// During operand reordering, we are trying to select the operand at lane 760 /// that matches best with the operand at the neighboring lane. Our 761 /// selection is based on the type of value we are looking for. For example, 762 /// if the neighboring lane has a load, we need to look for a load that is 763 /// accessing a consecutive address. These strategies are summarized in the 764 /// 'ReorderingMode' enumerator. 765 enum class ReorderingMode { 766 Load, ///< Matching loads to consecutive memory addresses 767 Opcode, ///< Matching instructions based on opcode (same or alternate) 768 Constant, ///< Matching constants 769 Splat, ///< Matching the same instruction multiple times (broadcast) 770 Failed, ///< We failed to create a vectorizable group 771 }; 772 773 using OperandDataVec = SmallVector<OperandData, 2>; 774 775 /// A vector of operand vectors. 776 SmallVector<OperandDataVec, 4> OpsVec; 777 778 const DataLayout &DL; 779 ScalarEvolution &SE; 780 const BoUpSLP &R; 781 782 /// \returns the operand data at \p OpIdx and \p Lane. 783 OperandData &getData(unsigned OpIdx, unsigned Lane) { 784 return OpsVec[OpIdx][Lane]; 785 } 786 787 /// \returns the operand data at \p OpIdx and \p Lane. Const version. 788 const OperandData &getData(unsigned OpIdx, unsigned Lane) const { 789 return OpsVec[OpIdx][Lane]; 790 } 791 792 /// Clears the used flag for all entries. 793 void clearUsed() { 794 for (unsigned OpIdx = 0, NumOperands = getNumOperands(); 795 OpIdx != NumOperands; ++OpIdx) 796 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 797 ++Lane) 798 OpsVec[OpIdx][Lane].IsUsed = false; 799 } 800 801 /// Swap the operand at \p OpIdx1 with that one at \p OpIdx2. 802 void swap(unsigned OpIdx1, unsigned OpIdx2, unsigned Lane) { 803 std::swap(OpsVec[OpIdx1][Lane], OpsVec[OpIdx2][Lane]); 804 } 805 806 // The hard-coded scores listed here are not very important. When computing 807 // the scores of matching one sub-tree with another, we are basically 808 // counting the number of values that are matching. So even if all scores 809 // are set to 1, we would still get a decent matching result. 810 // However, sometimes we have to break ties. For example we may have to 811 // choose between matching loads vs matching opcodes. This is what these 812 // scores are helping us with: they provide the order of preference. 813 814 /// Loads from consecutive memory addresses, e.g. load(A[i]), load(A[i+1]). 815 static const int ScoreConsecutiveLoads = 3; 816 /// ExtractElementInst from same vector and consecutive indexes. 817 static const int ScoreConsecutiveExtracts = 3; 818 /// Constants. 819 static const int ScoreConstants = 2; 820 /// Instructions with the same opcode. 821 static const int ScoreSameOpcode = 2; 822 /// Instructions with alt opcodes (e.g, add + sub). 823 static const int ScoreAltOpcodes = 1; 824 /// Identical instructions (a.k.a. splat or broadcast). 825 static const int ScoreSplat = 1; 826 /// Matching with an undef is preferable to failing. 827 static const int ScoreUndef = 1; 828 /// Score for failing to find a decent match. 829 static const int ScoreFail = 0; 830 /// User exteranl to the vectorized code. 831 static const int ExternalUseCost = 1; 832 /// The user is internal but in a different lane. 833 static const int UserInDiffLaneCost = ExternalUseCost; 834 835 /// \returns the score of placing \p V1 and \p V2 in consecutive lanes. 836 static int getShallowScore(Value *V1, Value *V2, const DataLayout &DL, 837 ScalarEvolution &SE) { 838 auto *LI1 = dyn_cast<LoadInst>(V1); 839 auto *LI2 = dyn_cast<LoadInst>(V2); 840 if (LI1 && LI2) 841 return isConsecutiveAccess(LI1, LI2, DL, SE) 842 ? VLOperands::ScoreConsecutiveLoads 843 : VLOperands::ScoreFail; 844 845 auto *C1 = dyn_cast<Constant>(V1); 846 auto *C2 = dyn_cast<Constant>(V2); 847 if (C1 && C2) 848 return VLOperands::ScoreConstants; 849 850 // Extracts from consecutive indexes of the same vector better score as 851 // the extracts could be optimized away. 852 Value *EV; 853 ConstantInt *Ex1Idx, *Ex2Idx; 854 if (match(V1, m_ExtractElt(m_Value(EV), m_ConstantInt(Ex1Idx))) && 855 match(V2, m_ExtractElt(m_Deferred(EV), m_ConstantInt(Ex2Idx))) && 856 Ex1Idx->getZExtValue() + 1 == Ex2Idx->getZExtValue()) 857 return VLOperands::ScoreConsecutiveExtracts; 858 859 auto *I1 = dyn_cast<Instruction>(V1); 860 auto *I2 = dyn_cast<Instruction>(V2); 861 if (I1 && I2) { 862 if (I1 == I2) 863 return VLOperands::ScoreSplat; 864 InstructionsState S = getSameOpcode({I1, I2}); 865 // Note: Only consider instructions with <= 2 operands to avoid 866 // complexity explosion. 867 if (S.getOpcode() && S.MainOp->getNumOperands() <= 2) 868 return S.isAltShuffle() ? VLOperands::ScoreAltOpcodes 869 : VLOperands::ScoreSameOpcode; 870 } 871 872 if (isa<UndefValue>(V2)) 873 return VLOperands::ScoreUndef; 874 875 return VLOperands::ScoreFail; 876 } 877 878 /// Holds the values and their lane that are taking part in the look-ahead 879 /// score calculation. This is used in the external uses cost calculation. 880 SmallDenseMap<Value *, int> InLookAheadValues; 881 882 /// \Returns the additinal cost due to uses of \p LHS and \p RHS that are 883 /// either external to the vectorized code, or require shuffling. 884 int getExternalUsesCost(const std::pair<Value *, int> &LHS, 885 const std::pair<Value *, int> &RHS) { 886 int Cost = 0; 887 std::array<std::pair<Value *, int>, 2> Values = {{LHS, RHS}}; 888 for (int Idx = 0, IdxE = Values.size(); Idx != IdxE; ++Idx) { 889 Value *V = Values[Idx].first; 890 // Calculate the absolute lane, using the minimum relative lane of LHS 891 // and RHS as base and Idx as the offset. 892 int Ln = std::min(LHS.second, RHS.second) + Idx; 893 assert(Ln >= 0 && "Bad lane calculation"); 894 unsigned UsersBudget = LookAheadUsersBudget; 895 for (User *U : V->users()) { 896 if (const TreeEntry *UserTE = R.getTreeEntry(U)) { 897 // The user is in the VectorizableTree. Check if we need to insert. 898 auto It = llvm::find(UserTE->Scalars, U); 899 assert(It != UserTE->Scalars.end() && "U is in UserTE"); 900 int UserLn = std::distance(UserTE->Scalars.begin(), It); 901 assert(UserLn >= 0 && "Bad lane"); 902 if (UserLn != Ln) 903 Cost += UserInDiffLaneCost; 904 } else { 905 // Check if the user is in the look-ahead code. 906 auto It2 = InLookAheadValues.find(U); 907 if (It2 != InLookAheadValues.end()) { 908 // The user is in the look-ahead code. Check the lane. 909 if (It2->second != Ln) 910 Cost += UserInDiffLaneCost; 911 } else { 912 // The user is neither in SLP tree nor in the look-ahead code. 913 Cost += ExternalUseCost; 914 } 915 } 916 // Limit the number of visited uses to cap compilation time. 917 if (--UsersBudget == 0) 918 break; 919 } 920 } 921 return Cost; 922 } 923 924 /// Go through the operands of \p LHS and \p RHS recursively until \p 925 /// MaxLevel, and return the cummulative score. For example: 926 /// \verbatim 927 /// A[0] B[0] A[1] B[1] C[0] D[0] B[1] A[1] 928 /// \ / \ / \ / \ / 929 /// + + + + 930 /// G1 G2 G3 G4 931 /// \endverbatim 932 /// The getScoreAtLevelRec(G1, G2) function will try to match the nodes at 933 /// each level recursively, accumulating the score. It starts from matching 934 /// the additions at level 0, then moves on to the loads (level 1). The 935 /// score of G1 and G2 is higher than G1 and G3, because {A[0],A[1]} and 936 /// {B[0],B[1]} match with VLOperands::ScoreConsecutiveLoads, while 937 /// {A[0],C[0]} has a score of VLOperands::ScoreFail. 938 /// Please note that the order of the operands does not matter, as we 939 /// evaluate the score of all profitable combinations of operands. In 940 /// other words the score of G1 and G4 is the same as G1 and G2. This 941 /// heuristic is based on ideas described in: 942 /// Look-ahead SLP: Auto-vectorization in the presence of commutative 943 /// operations, CGO 2018 by Vasileios Porpodas, Rodrigo C. O. Rocha, 944 /// Luís F. W. Góes 945 int getScoreAtLevelRec(const std::pair<Value *, int> &LHS, 946 const std::pair<Value *, int> &RHS, int CurrLevel, 947 int MaxLevel) { 948 949 Value *V1 = LHS.first; 950 Value *V2 = RHS.first; 951 // Get the shallow score of V1 and V2. 952 int ShallowScoreAtThisLevel = 953 std::max((int)ScoreFail, getShallowScore(V1, V2, DL, SE) - 954 getExternalUsesCost(LHS, RHS)); 955 int Lane1 = LHS.second; 956 int Lane2 = RHS.second; 957 958 // If reached MaxLevel, 959 // or if V1 and V2 are not instructions, 960 // or if they are SPLAT, 961 // or if they are not consecutive, early return the current cost. 962 auto *I1 = dyn_cast<Instruction>(V1); 963 auto *I2 = dyn_cast<Instruction>(V2); 964 if (CurrLevel == MaxLevel || !(I1 && I2) || I1 == I2 || 965 ShallowScoreAtThisLevel == VLOperands::ScoreFail || 966 (isa<LoadInst>(I1) && isa<LoadInst>(I2) && ShallowScoreAtThisLevel)) 967 return ShallowScoreAtThisLevel; 968 assert(I1 && I2 && "Should have early exited."); 969 970 // Keep track of in-tree values for determining the external-use cost. 971 InLookAheadValues[V1] = Lane1; 972 InLookAheadValues[V2] = Lane2; 973 974 // Contains the I2 operand indexes that got matched with I1 operands. 975 SmallSet<unsigned, 4> Op2Used; 976 977 // Recursion towards the operands of I1 and I2. We are trying all possbile 978 // operand pairs, and keeping track of the best score. 979 for (unsigned OpIdx1 = 0, NumOperands1 = I1->getNumOperands(); 980 OpIdx1 != NumOperands1; ++OpIdx1) { 981 // Try to pair op1I with the best operand of I2. 982 int MaxTmpScore = 0; 983 unsigned MaxOpIdx2 = 0; 984 bool FoundBest = false; 985 // If I2 is commutative try all combinations. 986 unsigned FromIdx = isCommutative(I2) ? 0 : OpIdx1; 987 unsigned ToIdx = isCommutative(I2) 988 ? I2->getNumOperands() 989 : std::min(I2->getNumOperands(), OpIdx1 + 1); 990 assert(FromIdx <= ToIdx && "Bad index"); 991 for (unsigned OpIdx2 = FromIdx; OpIdx2 != ToIdx; ++OpIdx2) { 992 // Skip operands already paired with OpIdx1. 993 if (Op2Used.count(OpIdx2)) 994 continue; 995 // Recursively calculate the cost at each level 996 int TmpScore = getScoreAtLevelRec({I1->getOperand(OpIdx1), Lane1}, 997 {I2->getOperand(OpIdx2), Lane2}, 998 CurrLevel + 1, MaxLevel); 999 // Look for the best score. 1000 if (TmpScore > VLOperands::ScoreFail && TmpScore > MaxTmpScore) { 1001 MaxTmpScore = TmpScore; 1002 MaxOpIdx2 = OpIdx2; 1003 FoundBest = true; 1004 } 1005 } 1006 if (FoundBest) { 1007 // Pair {OpIdx1, MaxOpIdx2} was found to be best. Never revisit it. 1008 Op2Used.insert(MaxOpIdx2); 1009 ShallowScoreAtThisLevel += MaxTmpScore; 1010 } 1011 } 1012 return ShallowScoreAtThisLevel; 1013 } 1014 1015 /// \Returns the look-ahead score, which tells us how much the sub-trees 1016 /// rooted at \p LHS and \p RHS match, the more they match the higher the 1017 /// score. This helps break ties in an informed way when we cannot decide on 1018 /// the order of the operands by just considering the immediate 1019 /// predecessors. 1020 int getLookAheadScore(const std::pair<Value *, int> &LHS, 1021 const std::pair<Value *, int> &RHS) { 1022 InLookAheadValues.clear(); 1023 return getScoreAtLevelRec(LHS, RHS, 1, LookAheadMaxDepth); 1024 } 1025 1026 // Search all operands in Ops[*][Lane] for the one that matches best 1027 // Ops[OpIdx][LastLane] and return its opreand index. 1028 // If no good match can be found, return None. 1029 Optional<unsigned> 1030 getBestOperand(unsigned OpIdx, int Lane, int LastLane, 1031 ArrayRef<ReorderingMode> ReorderingModes) { 1032 unsigned NumOperands = getNumOperands(); 1033 1034 // The operand of the previous lane at OpIdx. 1035 Value *OpLastLane = getData(OpIdx, LastLane).V; 1036 1037 // Our strategy mode for OpIdx. 1038 ReorderingMode RMode = ReorderingModes[OpIdx]; 1039 1040 // The linearized opcode of the operand at OpIdx, Lane. 1041 bool OpIdxAPO = getData(OpIdx, Lane).APO; 1042 1043 // The best operand index and its score. 1044 // Sometimes we have more than one option (e.g., Opcode and Undefs), so we 1045 // are using the score to differentiate between the two. 1046 struct BestOpData { 1047 Optional<unsigned> Idx = None; 1048 unsigned Score = 0; 1049 } BestOp; 1050 1051 // Iterate through all unused operands and look for the best. 1052 for (unsigned Idx = 0; Idx != NumOperands; ++Idx) { 1053 // Get the operand at Idx and Lane. 1054 OperandData &OpData = getData(Idx, Lane); 1055 Value *Op = OpData.V; 1056 bool OpAPO = OpData.APO; 1057 1058 // Skip already selected operands. 1059 if (OpData.IsUsed) 1060 continue; 1061 1062 // Skip if we are trying to move the operand to a position with a 1063 // different opcode in the linearized tree form. This would break the 1064 // semantics. 1065 if (OpAPO != OpIdxAPO) 1066 continue; 1067 1068 // Look for an operand that matches the current mode. 1069 switch (RMode) { 1070 case ReorderingMode::Load: 1071 case ReorderingMode::Constant: 1072 case ReorderingMode::Opcode: { 1073 bool LeftToRight = Lane > LastLane; 1074 Value *OpLeft = (LeftToRight) ? OpLastLane : Op; 1075 Value *OpRight = (LeftToRight) ? Op : OpLastLane; 1076 unsigned Score = 1077 getLookAheadScore({OpLeft, LastLane}, {OpRight, Lane}); 1078 if (Score > BestOp.Score) { 1079 BestOp.Idx = Idx; 1080 BestOp.Score = Score; 1081 } 1082 break; 1083 } 1084 case ReorderingMode::Splat: 1085 if (Op == OpLastLane) 1086 BestOp.Idx = Idx; 1087 break; 1088 case ReorderingMode::Failed: 1089 return None; 1090 } 1091 } 1092 1093 if (BestOp.Idx) { 1094 getData(BestOp.Idx.getValue(), Lane).IsUsed = true; 1095 return BestOp.Idx; 1096 } 1097 // If we could not find a good match return None. 1098 return None; 1099 } 1100 1101 /// Helper for reorderOperandVecs. \Returns the lane that we should start 1102 /// reordering from. This is the one which has the least number of operands 1103 /// that can freely move about. 1104 unsigned getBestLaneToStartReordering() const { 1105 unsigned BestLane = 0; 1106 unsigned Min = UINT_MAX; 1107 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 1108 ++Lane) { 1109 unsigned NumFreeOps = getMaxNumOperandsThatCanBeReordered(Lane); 1110 if (NumFreeOps < Min) { 1111 Min = NumFreeOps; 1112 BestLane = Lane; 1113 } 1114 } 1115 return BestLane; 1116 } 1117 1118 /// \Returns the maximum number of operands that are allowed to be reordered 1119 /// for \p Lane. This is used as a heuristic for selecting the first lane to 1120 /// start operand reordering. 1121 unsigned getMaxNumOperandsThatCanBeReordered(unsigned Lane) const { 1122 unsigned CntTrue = 0; 1123 unsigned NumOperands = getNumOperands(); 1124 // Operands with the same APO can be reordered. We therefore need to count 1125 // how many of them we have for each APO, like this: Cnt[APO] = x. 1126 // Since we only have two APOs, namely true and false, we can avoid using 1127 // a map. Instead we can simply count the number of operands that 1128 // correspond to one of them (in this case the 'true' APO), and calculate 1129 // the other by subtracting it from the total number of operands. 1130 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) 1131 if (getData(OpIdx, Lane).APO) 1132 ++CntTrue; 1133 unsigned CntFalse = NumOperands - CntTrue; 1134 return std::max(CntTrue, CntFalse); 1135 } 1136 1137 /// Go through the instructions in VL and append their operands. 1138 void appendOperandsOfVL(ArrayRef<Value *> VL) { 1139 assert(!VL.empty() && "Bad VL"); 1140 assert((empty() || VL.size() == getNumLanes()) && 1141 "Expected same number of lanes"); 1142 assert(isa<Instruction>(VL[0]) && "Expected instruction"); 1143 unsigned NumOperands = cast<Instruction>(VL[0])->getNumOperands(); 1144 OpsVec.resize(NumOperands); 1145 unsigned NumLanes = VL.size(); 1146 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1147 OpsVec[OpIdx].resize(NumLanes); 1148 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { 1149 assert(isa<Instruction>(VL[Lane]) && "Expected instruction"); 1150 // Our tree has just 3 nodes: the root and two operands. 1151 // It is therefore trivial to get the APO. We only need to check the 1152 // opcode of VL[Lane] and whether the operand at OpIdx is the LHS or 1153 // RHS operand. The LHS operand of both add and sub is never attached 1154 // to an inversese operation in the linearized form, therefore its APO 1155 // is false. The RHS is true only if VL[Lane] is an inverse operation. 1156 1157 // Since operand reordering is performed on groups of commutative 1158 // operations or alternating sequences (e.g., +, -), we can safely 1159 // tell the inverse operations by checking commutativity. 1160 bool IsInverseOperation = !isCommutative(cast<Instruction>(VL[Lane])); 1161 bool APO = (OpIdx == 0) ? false : IsInverseOperation; 1162 OpsVec[OpIdx][Lane] = {cast<Instruction>(VL[Lane])->getOperand(OpIdx), 1163 APO, false}; 1164 } 1165 } 1166 } 1167 1168 /// \returns the number of operands. 1169 unsigned getNumOperands() const { return OpsVec.size(); } 1170 1171 /// \returns the number of lanes. 1172 unsigned getNumLanes() const { return OpsVec[0].size(); } 1173 1174 /// \returns the operand value at \p OpIdx and \p Lane. 1175 Value *getValue(unsigned OpIdx, unsigned Lane) const { 1176 return getData(OpIdx, Lane).V; 1177 } 1178 1179 /// \returns true if the data structure is empty. 1180 bool empty() const { return OpsVec.empty(); } 1181 1182 /// Clears the data. 1183 void clear() { OpsVec.clear(); } 1184 1185 /// \Returns true if there are enough operands identical to \p Op to fill 1186 /// the whole vector. 1187 /// Note: This modifies the 'IsUsed' flag, so a cleanUsed() must follow. 1188 bool shouldBroadcast(Value *Op, unsigned OpIdx, unsigned Lane) { 1189 bool OpAPO = getData(OpIdx, Lane).APO; 1190 for (unsigned Ln = 0, Lns = getNumLanes(); Ln != Lns; ++Ln) { 1191 if (Ln == Lane) 1192 continue; 1193 // This is set to true if we found a candidate for broadcast at Lane. 1194 bool FoundCandidate = false; 1195 for (unsigned OpI = 0, OpE = getNumOperands(); OpI != OpE; ++OpI) { 1196 OperandData &Data = getData(OpI, Ln); 1197 if (Data.APO != OpAPO || Data.IsUsed) 1198 continue; 1199 if (Data.V == Op) { 1200 FoundCandidate = true; 1201 Data.IsUsed = true; 1202 break; 1203 } 1204 } 1205 if (!FoundCandidate) 1206 return false; 1207 } 1208 return true; 1209 } 1210 1211 public: 1212 /// Initialize with all the operands of the instruction vector \p RootVL. 1213 VLOperands(ArrayRef<Value *> RootVL, const DataLayout &DL, 1214 ScalarEvolution &SE, const BoUpSLP &R) 1215 : DL(DL), SE(SE), R(R) { 1216 // Append all the operands of RootVL. 1217 appendOperandsOfVL(RootVL); 1218 } 1219 1220 /// \Returns a value vector with the operands across all lanes for the 1221 /// opearnd at \p OpIdx. 1222 ValueList getVL(unsigned OpIdx) const { 1223 ValueList OpVL(OpsVec[OpIdx].size()); 1224 assert(OpsVec[OpIdx].size() == getNumLanes() && 1225 "Expected same num of lanes across all operands"); 1226 for (unsigned Lane = 0, Lanes = getNumLanes(); Lane != Lanes; ++Lane) 1227 OpVL[Lane] = OpsVec[OpIdx][Lane].V; 1228 return OpVL; 1229 } 1230 1231 // Performs operand reordering for 2 or more operands. 1232 // The original operands are in OrigOps[OpIdx][Lane]. 1233 // The reordered operands are returned in 'SortedOps[OpIdx][Lane]'. 1234 void reorder() { 1235 unsigned NumOperands = getNumOperands(); 1236 unsigned NumLanes = getNumLanes(); 1237 // Each operand has its own mode. We are using this mode to help us select 1238 // the instructions for each lane, so that they match best with the ones 1239 // we have selected so far. 1240 SmallVector<ReorderingMode, 2> ReorderingModes(NumOperands); 1241 1242 // This is a greedy single-pass algorithm. We are going over each lane 1243 // once and deciding on the best order right away with no back-tracking. 1244 // However, in order to increase its effectiveness, we start with the lane 1245 // that has operands that can move the least. For example, given the 1246 // following lanes: 1247 // Lane 0 : A[0] = B[0] + C[0] // Visited 3rd 1248 // Lane 1 : A[1] = C[1] - B[1] // Visited 1st 1249 // Lane 2 : A[2] = B[2] + C[2] // Visited 2nd 1250 // Lane 3 : A[3] = C[3] - B[3] // Visited 4th 1251 // we will start at Lane 1, since the operands of the subtraction cannot 1252 // be reordered. Then we will visit the rest of the lanes in a circular 1253 // fashion. That is, Lanes 2, then Lane 0, and finally Lane 3. 1254 1255 // Find the first lane that we will start our search from. 1256 unsigned FirstLane = getBestLaneToStartReordering(); 1257 1258 // Initialize the modes. 1259 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1260 Value *OpLane0 = getValue(OpIdx, FirstLane); 1261 // Keep track if we have instructions with all the same opcode on one 1262 // side. 1263 if (isa<LoadInst>(OpLane0)) 1264 ReorderingModes[OpIdx] = ReorderingMode::Load; 1265 else if (isa<Instruction>(OpLane0)) { 1266 // Check if OpLane0 should be broadcast. 1267 if (shouldBroadcast(OpLane0, OpIdx, FirstLane)) 1268 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1269 else 1270 ReorderingModes[OpIdx] = ReorderingMode::Opcode; 1271 } 1272 else if (isa<Constant>(OpLane0)) 1273 ReorderingModes[OpIdx] = ReorderingMode::Constant; 1274 else if (isa<Argument>(OpLane0)) 1275 // Our best hope is a Splat. It may save some cost in some cases. 1276 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1277 else 1278 // NOTE: This should be unreachable. 1279 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1280 } 1281 1282 // If the initial strategy fails for any of the operand indexes, then we 1283 // perform reordering again in a second pass. This helps avoid assigning 1284 // high priority to the failed strategy, and should improve reordering for 1285 // the non-failed operand indexes. 1286 for (int Pass = 0; Pass != 2; ++Pass) { 1287 // Skip the second pass if the first pass did not fail. 1288 bool StrategyFailed = false; 1289 // Mark all operand data as free to use. 1290 clearUsed(); 1291 // We keep the original operand order for the FirstLane, so reorder the 1292 // rest of the lanes. We are visiting the nodes in a circular fashion, 1293 // using FirstLane as the center point and increasing the radius 1294 // distance. 1295 for (unsigned Distance = 1; Distance != NumLanes; ++Distance) { 1296 // Visit the lane on the right and then the lane on the left. 1297 for (int Direction : {+1, -1}) { 1298 int Lane = FirstLane + Direction * Distance; 1299 if (Lane < 0 || Lane >= (int)NumLanes) 1300 continue; 1301 int LastLane = Lane - Direction; 1302 assert(LastLane >= 0 && LastLane < (int)NumLanes && 1303 "Out of bounds"); 1304 // Look for a good match for each operand. 1305 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1306 // Search for the operand that matches SortedOps[OpIdx][Lane-1]. 1307 Optional<unsigned> BestIdx = 1308 getBestOperand(OpIdx, Lane, LastLane, ReorderingModes); 1309 // By not selecting a value, we allow the operands that follow to 1310 // select a better matching value. We will get a non-null value in 1311 // the next run of getBestOperand(). 1312 if (BestIdx) { 1313 // Swap the current operand with the one returned by 1314 // getBestOperand(). 1315 swap(OpIdx, BestIdx.getValue(), Lane); 1316 } else { 1317 // We failed to find a best operand, set mode to 'Failed'. 1318 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1319 // Enable the second pass. 1320 StrategyFailed = true; 1321 } 1322 } 1323 } 1324 } 1325 // Skip second pass if the strategy did not fail. 1326 if (!StrategyFailed) 1327 break; 1328 } 1329 } 1330 1331 #if !defined(NDEBUG) || defined(LLVM_ENABLE_DUMP) 1332 LLVM_DUMP_METHOD static StringRef getModeStr(ReorderingMode RMode) { 1333 switch (RMode) { 1334 case ReorderingMode::Load: 1335 return "Load"; 1336 case ReorderingMode::Opcode: 1337 return "Opcode"; 1338 case ReorderingMode::Constant: 1339 return "Constant"; 1340 case ReorderingMode::Splat: 1341 return "Splat"; 1342 case ReorderingMode::Failed: 1343 return "Failed"; 1344 } 1345 llvm_unreachable("Unimplemented Reordering Type"); 1346 } 1347 1348 LLVM_DUMP_METHOD static raw_ostream &printMode(ReorderingMode RMode, 1349 raw_ostream &OS) { 1350 return OS << getModeStr(RMode); 1351 } 1352 1353 /// Debug print. 1354 LLVM_DUMP_METHOD static void dumpMode(ReorderingMode RMode) { 1355 printMode(RMode, dbgs()); 1356 } 1357 1358 friend raw_ostream &operator<<(raw_ostream &OS, ReorderingMode RMode) { 1359 return printMode(RMode, OS); 1360 } 1361 1362 LLVM_DUMP_METHOD raw_ostream &print(raw_ostream &OS) const { 1363 const unsigned Indent = 2; 1364 unsigned Cnt = 0; 1365 for (const OperandDataVec &OpDataVec : OpsVec) { 1366 OS << "Operand " << Cnt++ << "\n"; 1367 for (const OperandData &OpData : OpDataVec) { 1368 OS.indent(Indent) << "{"; 1369 if (Value *V = OpData.V) 1370 OS << *V; 1371 else 1372 OS << "null"; 1373 OS << ", APO:" << OpData.APO << "}\n"; 1374 } 1375 OS << "\n"; 1376 } 1377 return OS; 1378 } 1379 1380 /// Debug print. 1381 LLVM_DUMP_METHOD void dump() const { print(dbgs()); } 1382 #endif 1383 }; 1384 1385 /// Checks if the instruction is marked for deletion. 1386 bool isDeleted(Instruction *I) const { return DeletedInstructions.count(I); } 1387 1388 /// Marks values operands for later deletion by replacing them with Undefs. 1389 void eraseInstructions(ArrayRef<Value *> AV); 1390 1391 ~BoUpSLP(); 1392 1393 private: 1394 /// Checks if all users of \p I are the part of the vectorization tree. 1395 bool areAllUsersVectorized(Instruction *I) const; 1396 1397 /// \returns the cost of the vectorizable entry. 1398 int getEntryCost(TreeEntry *E); 1399 1400 /// This is the recursive part of buildTree. 1401 void buildTree_rec(ArrayRef<Value *> Roots, unsigned Depth, 1402 const EdgeInfo &EI); 1403 1404 /// \returns true if the ExtractElement/ExtractValue instructions in \p VL can 1405 /// be vectorized to use the original vector (or aggregate "bitcast" to a 1406 /// vector) and sets \p CurrentOrder to the identity permutation; otherwise 1407 /// returns false, setting \p CurrentOrder to either an empty vector or a 1408 /// non-identity permutation that allows to reuse extract instructions. 1409 bool canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 1410 SmallVectorImpl<unsigned> &CurrentOrder) const; 1411 1412 /// Vectorize a single entry in the tree. 1413 Value *vectorizeTree(TreeEntry *E); 1414 1415 /// Vectorize a single entry in the tree, starting in \p VL. 1416 Value *vectorizeTree(ArrayRef<Value *> VL); 1417 1418 /// \returns the scalarization cost for this type. Scalarization in this 1419 /// context means the creation of vectors from a group of scalars. 1420 int getGatherCost(FixedVectorType *Ty, 1421 const DenseSet<unsigned> &ShuffledIndices) const; 1422 1423 /// \returns the scalarization cost for this list of values. Assuming that 1424 /// this subtree gets vectorized, we may need to extract the values from the 1425 /// roots. This method calculates the cost of extracting the values. 1426 int getGatherCost(ArrayRef<Value *> VL) const; 1427 1428 /// Set the Builder insert point to one after the last instruction in 1429 /// the bundle 1430 void setInsertPointAfterBundle(TreeEntry *E); 1431 1432 /// \returns a vector from a collection of scalars in \p VL. 1433 Value *Gather(ArrayRef<Value *> VL, FixedVectorType *Ty); 1434 1435 /// \returns whether the VectorizableTree is fully vectorizable and will 1436 /// be beneficial even the tree height is tiny. 1437 bool isFullyVectorizableTinyTree() const; 1438 1439 /// Reorder commutative or alt operands to get better probability of 1440 /// generating vectorized code. 1441 static void reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 1442 SmallVectorImpl<Value *> &Left, 1443 SmallVectorImpl<Value *> &Right, 1444 const DataLayout &DL, 1445 ScalarEvolution &SE, 1446 const BoUpSLP &R); 1447 struct TreeEntry { 1448 using VecTreeTy = SmallVector<std::unique_ptr<TreeEntry>, 8>; 1449 TreeEntry(VecTreeTy &Container) : Container(Container) {} 1450 1451 /// \returns true if the scalars in VL are equal to this entry. 1452 bool isSame(ArrayRef<Value *> VL) const { 1453 if (VL.size() == Scalars.size()) 1454 return std::equal(VL.begin(), VL.end(), Scalars.begin()); 1455 return VL.size() == ReuseShuffleIndices.size() && 1456 std::equal( 1457 VL.begin(), VL.end(), ReuseShuffleIndices.begin(), 1458 [this](Value *V, int Idx) { return V == Scalars[Idx]; }); 1459 } 1460 1461 /// A vector of scalars. 1462 ValueList Scalars; 1463 1464 /// The Scalars are vectorized into this value. It is initialized to Null. 1465 Value *VectorizedValue = nullptr; 1466 1467 /// Do we need to gather this sequence ? 1468 enum EntryState { Vectorize, NeedToGather }; 1469 EntryState State; 1470 1471 /// Does this sequence require some shuffling? 1472 SmallVector<int, 4> ReuseShuffleIndices; 1473 1474 /// Does this entry require reordering? 1475 ArrayRef<unsigned> ReorderIndices; 1476 1477 /// Points back to the VectorizableTree. 1478 /// 1479 /// Only used for Graphviz right now. Unfortunately GraphTrait::NodeRef has 1480 /// to be a pointer and needs to be able to initialize the child iterator. 1481 /// Thus we need a reference back to the container to translate the indices 1482 /// to entries. 1483 VecTreeTy &Container; 1484 1485 /// The TreeEntry index containing the user of this entry. We can actually 1486 /// have multiple users so the data structure is not truly a tree. 1487 SmallVector<EdgeInfo, 1> UserTreeIndices; 1488 1489 /// The index of this treeEntry in VectorizableTree. 1490 int Idx = -1; 1491 1492 private: 1493 /// The operands of each instruction in each lane Operands[op_index][lane]. 1494 /// Note: This helps avoid the replication of the code that performs the 1495 /// reordering of operands during buildTree_rec() and vectorizeTree(). 1496 SmallVector<ValueList, 2> Operands; 1497 1498 /// The main/alternate instruction. 1499 Instruction *MainOp = nullptr; 1500 Instruction *AltOp = nullptr; 1501 1502 public: 1503 /// Set this bundle's \p OpIdx'th operand to \p OpVL. 1504 void setOperand(unsigned OpIdx, ArrayRef<Value *> OpVL) { 1505 if (Operands.size() < OpIdx + 1) 1506 Operands.resize(OpIdx + 1); 1507 assert(Operands[OpIdx].size() == 0 && "Already resized?"); 1508 Operands[OpIdx].resize(Scalars.size()); 1509 for (unsigned Lane = 0, E = Scalars.size(); Lane != E; ++Lane) 1510 Operands[OpIdx][Lane] = OpVL[Lane]; 1511 } 1512 1513 /// Set the operands of this bundle in their original order. 1514 void setOperandsInOrder() { 1515 assert(Operands.empty() && "Already initialized?"); 1516 auto *I0 = cast<Instruction>(Scalars[0]); 1517 Operands.resize(I0->getNumOperands()); 1518 unsigned NumLanes = Scalars.size(); 1519 for (unsigned OpIdx = 0, NumOperands = I0->getNumOperands(); 1520 OpIdx != NumOperands; ++OpIdx) { 1521 Operands[OpIdx].resize(NumLanes); 1522 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { 1523 auto *I = cast<Instruction>(Scalars[Lane]); 1524 assert(I->getNumOperands() == NumOperands && 1525 "Expected same number of operands"); 1526 Operands[OpIdx][Lane] = I->getOperand(OpIdx); 1527 } 1528 } 1529 } 1530 1531 /// \returns the \p OpIdx operand of this TreeEntry. 1532 ValueList &getOperand(unsigned OpIdx) { 1533 assert(OpIdx < Operands.size() && "Off bounds"); 1534 return Operands[OpIdx]; 1535 } 1536 1537 /// \returns the number of operands. 1538 unsigned getNumOperands() const { return Operands.size(); } 1539 1540 /// \return the single \p OpIdx operand. 1541 Value *getSingleOperand(unsigned OpIdx) const { 1542 assert(OpIdx < Operands.size() && "Off bounds"); 1543 assert(!Operands[OpIdx].empty() && "No operand available"); 1544 return Operands[OpIdx][0]; 1545 } 1546 1547 /// Some of the instructions in the list have alternate opcodes. 1548 bool isAltShuffle() const { 1549 return getOpcode() != getAltOpcode(); 1550 } 1551 1552 bool isOpcodeOrAlt(Instruction *I) const { 1553 unsigned CheckedOpcode = I->getOpcode(); 1554 return (getOpcode() == CheckedOpcode || 1555 getAltOpcode() == CheckedOpcode); 1556 } 1557 1558 /// Chooses the correct key for scheduling data. If \p Op has the same (or 1559 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is 1560 /// \p OpValue. 1561 Value *isOneOf(Value *Op) const { 1562 auto *I = dyn_cast<Instruction>(Op); 1563 if (I && isOpcodeOrAlt(I)) 1564 return Op; 1565 return MainOp; 1566 } 1567 1568 void setOperations(const InstructionsState &S) { 1569 MainOp = S.MainOp; 1570 AltOp = S.AltOp; 1571 } 1572 1573 Instruction *getMainOp() const { 1574 return MainOp; 1575 } 1576 1577 Instruction *getAltOp() const { 1578 return AltOp; 1579 } 1580 1581 /// The main/alternate opcodes for the list of instructions. 1582 unsigned getOpcode() const { 1583 return MainOp ? MainOp->getOpcode() : 0; 1584 } 1585 1586 unsigned getAltOpcode() const { 1587 return AltOp ? AltOp->getOpcode() : 0; 1588 } 1589 1590 /// Update operations state of this entry if reorder occurred. 1591 bool updateStateIfReorder() { 1592 if (ReorderIndices.empty()) 1593 return false; 1594 InstructionsState S = getSameOpcode(Scalars, ReorderIndices.front()); 1595 setOperations(S); 1596 return true; 1597 } 1598 1599 #ifndef NDEBUG 1600 /// Debug printer. 1601 LLVM_DUMP_METHOD void dump() const { 1602 dbgs() << Idx << ".\n"; 1603 for (unsigned OpI = 0, OpE = Operands.size(); OpI != OpE; ++OpI) { 1604 dbgs() << "Operand " << OpI << ":\n"; 1605 for (const Value *V : Operands[OpI]) 1606 dbgs().indent(2) << *V << "\n"; 1607 } 1608 dbgs() << "Scalars: \n"; 1609 for (Value *V : Scalars) 1610 dbgs().indent(2) << *V << "\n"; 1611 dbgs() << "State: "; 1612 switch (State) { 1613 case Vectorize: 1614 dbgs() << "Vectorize\n"; 1615 break; 1616 case NeedToGather: 1617 dbgs() << "NeedToGather\n"; 1618 break; 1619 } 1620 dbgs() << "MainOp: "; 1621 if (MainOp) 1622 dbgs() << *MainOp << "\n"; 1623 else 1624 dbgs() << "NULL\n"; 1625 dbgs() << "AltOp: "; 1626 if (AltOp) 1627 dbgs() << *AltOp << "\n"; 1628 else 1629 dbgs() << "NULL\n"; 1630 dbgs() << "VectorizedValue: "; 1631 if (VectorizedValue) 1632 dbgs() << *VectorizedValue << "\n"; 1633 else 1634 dbgs() << "NULL\n"; 1635 dbgs() << "ReuseShuffleIndices: "; 1636 if (ReuseShuffleIndices.empty()) 1637 dbgs() << "Emtpy"; 1638 else 1639 for (unsigned ReuseIdx : ReuseShuffleIndices) 1640 dbgs() << ReuseIdx << ", "; 1641 dbgs() << "\n"; 1642 dbgs() << "ReorderIndices: "; 1643 for (unsigned ReorderIdx : ReorderIndices) 1644 dbgs() << ReorderIdx << ", "; 1645 dbgs() << "\n"; 1646 dbgs() << "UserTreeIndices: "; 1647 for (const auto &EInfo : UserTreeIndices) 1648 dbgs() << EInfo << ", "; 1649 dbgs() << "\n"; 1650 } 1651 #endif 1652 }; 1653 1654 /// Create a new VectorizableTree entry. 1655 TreeEntry *newTreeEntry(ArrayRef<Value *> VL, Optional<ScheduleData *> Bundle, 1656 const InstructionsState &S, 1657 const EdgeInfo &UserTreeIdx, 1658 ArrayRef<unsigned> ReuseShuffleIndices = None, 1659 ArrayRef<unsigned> ReorderIndices = None) { 1660 bool Vectorized = (bool)Bundle; 1661 VectorizableTree.push_back(std::make_unique<TreeEntry>(VectorizableTree)); 1662 TreeEntry *Last = VectorizableTree.back().get(); 1663 Last->Idx = VectorizableTree.size() - 1; 1664 Last->Scalars.insert(Last->Scalars.begin(), VL.begin(), VL.end()); 1665 Last->State = Vectorized ? TreeEntry::Vectorize : TreeEntry::NeedToGather; 1666 Last->ReuseShuffleIndices.append(ReuseShuffleIndices.begin(), 1667 ReuseShuffleIndices.end()); 1668 Last->ReorderIndices = ReorderIndices; 1669 Last->setOperations(S); 1670 if (Vectorized) { 1671 for (int i = 0, e = VL.size(); i != e; ++i) { 1672 assert(!getTreeEntry(VL[i]) && "Scalar already in tree!"); 1673 ScalarToTreeEntry[VL[i]] = Last; 1674 } 1675 // Update the scheduler bundle to point to this TreeEntry. 1676 unsigned Lane = 0; 1677 for (ScheduleData *BundleMember = Bundle.getValue(); BundleMember; 1678 BundleMember = BundleMember->NextInBundle) { 1679 BundleMember->TE = Last; 1680 BundleMember->Lane = Lane; 1681 ++Lane; 1682 } 1683 assert((!Bundle.getValue() || Lane == VL.size()) && 1684 "Bundle and VL out of sync"); 1685 } else { 1686 MustGather.insert(VL.begin(), VL.end()); 1687 } 1688 1689 if (UserTreeIdx.UserTE) 1690 Last->UserTreeIndices.push_back(UserTreeIdx); 1691 1692 return Last; 1693 } 1694 1695 /// -- Vectorization State -- 1696 /// Holds all of the tree entries. 1697 TreeEntry::VecTreeTy VectorizableTree; 1698 1699 #ifndef NDEBUG 1700 /// Debug printer. 1701 LLVM_DUMP_METHOD void dumpVectorizableTree() const { 1702 for (unsigned Id = 0, IdE = VectorizableTree.size(); Id != IdE; ++Id) { 1703 VectorizableTree[Id]->dump(); 1704 dbgs() << "\n"; 1705 } 1706 } 1707 #endif 1708 1709 TreeEntry *getTreeEntry(Value *V) { 1710 auto I = ScalarToTreeEntry.find(V); 1711 if (I != ScalarToTreeEntry.end()) 1712 return I->second; 1713 return nullptr; 1714 } 1715 1716 const TreeEntry *getTreeEntry(Value *V) const { 1717 auto I = ScalarToTreeEntry.find(V); 1718 if (I != ScalarToTreeEntry.end()) 1719 return I->second; 1720 return nullptr; 1721 } 1722 1723 /// Maps a specific scalar to its tree entry. 1724 SmallDenseMap<Value*, TreeEntry *> ScalarToTreeEntry; 1725 1726 /// Maps a value to the proposed vectorizable size. 1727 SmallDenseMap<Value *, unsigned> InstrElementSize; 1728 1729 /// A list of scalars that we found that we need to keep as scalars. 1730 ValueSet MustGather; 1731 1732 /// This POD struct describes one external user in the vectorized tree. 1733 struct ExternalUser { 1734 ExternalUser(Value *S, llvm::User *U, int L) 1735 : Scalar(S), User(U), Lane(L) {} 1736 1737 // Which scalar in our function. 1738 Value *Scalar; 1739 1740 // Which user that uses the scalar. 1741 llvm::User *User; 1742 1743 // Which lane does the scalar belong to. 1744 int Lane; 1745 }; 1746 using UserList = SmallVector<ExternalUser, 16>; 1747 1748 /// Checks if two instructions may access the same memory. 1749 /// 1750 /// \p Loc1 is the location of \p Inst1. It is passed explicitly because it 1751 /// is invariant in the calling loop. 1752 bool isAliased(const MemoryLocation &Loc1, Instruction *Inst1, 1753 Instruction *Inst2) { 1754 // First check if the result is already in the cache. 1755 AliasCacheKey key = std::make_pair(Inst1, Inst2); 1756 Optional<bool> &result = AliasCache[key]; 1757 if (result.hasValue()) { 1758 return result.getValue(); 1759 } 1760 MemoryLocation Loc2 = getLocation(Inst2, AA); 1761 bool aliased = true; 1762 if (Loc1.Ptr && Loc2.Ptr && isSimple(Inst1) && isSimple(Inst2)) { 1763 // Do the alias check. 1764 aliased = AA->alias(Loc1, Loc2); 1765 } 1766 // Store the result in the cache. 1767 result = aliased; 1768 return aliased; 1769 } 1770 1771 using AliasCacheKey = std::pair<Instruction *, Instruction *>; 1772 1773 /// Cache for alias results. 1774 /// TODO: consider moving this to the AliasAnalysis itself. 1775 DenseMap<AliasCacheKey, Optional<bool>> AliasCache; 1776 1777 /// Removes an instruction from its block and eventually deletes it. 1778 /// It's like Instruction::eraseFromParent() except that the actual deletion 1779 /// is delayed until BoUpSLP is destructed. 1780 /// This is required to ensure that there are no incorrect collisions in the 1781 /// AliasCache, which can happen if a new instruction is allocated at the 1782 /// same address as a previously deleted instruction. 1783 void eraseInstruction(Instruction *I, bool ReplaceOpsWithUndef = false) { 1784 auto It = DeletedInstructions.try_emplace(I, ReplaceOpsWithUndef).first; 1785 It->getSecond() = It->getSecond() && ReplaceOpsWithUndef; 1786 } 1787 1788 /// Temporary store for deleted instructions. Instructions will be deleted 1789 /// eventually when the BoUpSLP is destructed. 1790 DenseMap<Instruction *, bool> DeletedInstructions; 1791 1792 /// A list of values that need to extracted out of the tree. 1793 /// This list holds pairs of (Internal Scalar : External User). External User 1794 /// can be nullptr, it means that this Internal Scalar will be used later, 1795 /// after vectorization. 1796 UserList ExternalUses; 1797 1798 /// Values used only by @llvm.assume calls. 1799 SmallPtrSet<const Value *, 32> EphValues; 1800 1801 /// Holds all of the instructions that we gathered. 1802 SetVector<Instruction *> GatherSeq; 1803 1804 /// A list of blocks that we are going to CSE. 1805 SetVector<BasicBlock *> CSEBlocks; 1806 1807 /// Contains all scheduling relevant data for an instruction. 1808 /// A ScheduleData either represents a single instruction or a member of an 1809 /// instruction bundle (= a group of instructions which is combined into a 1810 /// vector instruction). 1811 struct ScheduleData { 1812 // The initial value for the dependency counters. It means that the 1813 // dependencies are not calculated yet. 1814 enum { InvalidDeps = -1 }; 1815 1816 ScheduleData() = default; 1817 1818 void init(int BlockSchedulingRegionID, Value *OpVal) { 1819 FirstInBundle = this; 1820 NextInBundle = nullptr; 1821 NextLoadStore = nullptr; 1822 IsScheduled = false; 1823 SchedulingRegionID = BlockSchedulingRegionID; 1824 UnscheduledDepsInBundle = UnscheduledDeps; 1825 clearDependencies(); 1826 OpValue = OpVal; 1827 TE = nullptr; 1828 Lane = -1; 1829 } 1830 1831 /// Returns true if the dependency information has been calculated. 1832 bool hasValidDependencies() const { return Dependencies != InvalidDeps; } 1833 1834 /// Returns true for single instructions and for bundle representatives 1835 /// (= the head of a bundle). 1836 bool isSchedulingEntity() const { return FirstInBundle == this; } 1837 1838 /// Returns true if it represents an instruction bundle and not only a 1839 /// single instruction. 1840 bool isPartOfBundle() const { 1841 return NextInBundle != nullptr || FirstInBundle != this; 1842 } 1843 1844 /// Returns true if it is ready for scheduling, i.e. it has no more 1845 /// unscheduled depending instructions/bundles. 1846 bool isReady() const { 1847 assert(isSchedulingEntity() && 1848 "can't consider non-scheduling entity for ready list"); 1849 return UnscheduledDepsInBundle == 0 && !IsScheduled; 1850 } 1851 1852 /// Modifies the number of unscheduled dependencies, also updating it for 1853 /// the whole bundle. 1854 int incrementUnscheduledDeps(int Incr) { 1855 UnscheduledDeps += Incr; 1856 return FirstInBundle->UnscheduledDepsInBundle += Incr; 1857 } 1858 1859 /// Sets the number of unscheduled dependencies to the number of 1860 /// dependencies. 1861 void resetUnscheduledDeps() { 1862 incrementUnscheduledDeps(Dependencies - UnscheduledDeps); 1863 } 1864 1865 /// Clears all dependency information. 1866 void clearDependencies() { 1867 Dependencies = InvalidDeps; 1868 resetUnscheduledDeps(); 1869 MemoryDependencies.clear(); 1870 } 1871 1872 void dump(raw_ostream &os) const { 1873 if (!isSchedulingEntity()) { 1874 os << "/ " << *Inst; 1875 } else if (NextInBundle) { 1876 os << '[' << *Inst; 1877 ScheduleData *SD = NextInBundle; 1878 while (SD) { 1879 os << ';' << *SD->Inst; 1880 SD = SD->NextInBundle; 1881 } 1882 os << ']'; 1883 } else { 1884 os << *Inst; 1885 } 1886 } 1887 1888 Instruction *Inst = nullptr; 1889 1890 /// Points to the head in an instruction bundle (and always to this for 1891 /// single instructions). 1892 ScheduleData *FirstInBundle = nullptr; 1893 1894 /// Single linked list of all instructions in a bundle. Null if it is a 1895 /// single instruction. 1896 ScheduleData *NextInBundle = nullptr; 1897 1898 /// Single linked list of all memory instructions (e.g. load, store, call) 1899 /// in the block - until the end of the scheduling region. 1900 ScheduleData *NextLoadStore = nullptr; 1901 1902 /// The dependent memory instructions. 1903 /// This list is derived on demand in calculateDependencies(). 1904 SmallVector<ScheduleData *, 4> MemoryDependencies; 1905 1906 /// This ScheduleData is in the current scheduling region if this matches 1907 /// the current SchedulingRegionID of BlockScheduling. 1908 int SchedulingRegionID = 0; 1909 1910 /// Used for getting a "good" final ordering of instructions. 1911 int SchedulingPriority = 0; 1912 1913 /// The number of dependencies. Constitutes of the number of users of the 1914 /// instruction plus the number of dependent memory instructions (if any). 1915 /// This value is calculated on demand. 1916 /// If InvalidDeps, the number of dependencies is not calculated yet. 1917 int Dependencies = InvalidDeps; 1918 1919 /// The number of dependencies minus the number of dependencies of scheduled 1920 /// instructions. As soon as this is zero, the instruction/bundle gets ready 1921 /// for scheduling. 1922 /// Note that this is negative as long as Dependencies is not calculated. 1923 int UnscheduledDeps = InvalidDeps; 1924 1925 /// The sum of UnscheduledDeps in a bundle. Equals to UnscheduledDeps for 1926 /// single instructions. 1927 int UnscheduledDepsInBundle = InvalidDeps; 1928 1929 /// True if this instruction is scheduled (or considered as scheduled in the 1930 /// dry-run). 1931 bool IsScheduled = false; 1932 1933 /// Opcode of the current instruction in the schedule data. 1934 Value *OpValue = nullptr; 1935 1936 /// The TreeEntry that this instruction corresponds to. 1937 TreeEntry *TE = nullptr; 1938 1939 /// The lane of this node in the TreeEntry. 1940 int Lane = -1; 1941 }; 1942 1943 #ifndef NDEBUG 1944 friend inline raw_ostream &operator<<(raw_ostream &os, 1945 const BoUpSLP::ScheduleData &SD) { 1946 SD.dump(os); 1947 return os; 1948 } 1949 #endif 1950 1951 friend struct GraphTraits<BoUpSLP *>; 1952 friend struct DOTGraphTraits<BoUpSLP *>; 1953 1954 /// Contains all scheduling data for a basic block. 1955 struct BlockScheduling { 1956 BlockScheduling(BasicBlock *BB) 1957 : BB(BB), ChunkSize(BB->size()), ChunkPos(ChunkSize) {} 1958 1959 void clear() { 1960 ReadyInsts.clear(); 1961 ScheduleStart = nullptr; 1962 ScheduleEnd = nullptr; 1963 FirstLoadStoreInRegion = nullptr; 1964 LastLoadStoreInRegion = nullptr; 1965 1966 // Reduce the maximum schedule region size by the size of the 1967 // previous scheduling run. 1968 ScheduleRegionSizeLimit -= ScheduleRegionSize; 1969 if (ScheduleRegionSizeLimit < MinScheduleRegionSize) 1970 ScheduleRegionSizeLimit = MinScheduleRegionSize; 1971 ScheduleRegionSize = 0; 1972 1973 // Make a new scheduling region, i.e. all existing ScheduleData is not 1974 // in the new region yet. 1975 ++SchedulingRegionID; 1976 } 1977 1978 ScheduleData *getScheduleData(Value *V) { 1979 ScheduleData *SD = ScheduleDataMap[V]; 1980 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 1981 return SD; 1982 return nullptr; 1983 } 1984 1985 ScheduleData *getScheduleData(Value *V, Value *Key) { 1986 if (V == Key) 1987 return getScheduleData(V); 1988 auto I = ExtraScheduleDataMap.find(V); 1989 if (I != ExtraScheduleDataMap.end()) { 1990 ScheduleData *SD = I->second[Key]; 1991 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 1992 return SD; 1993 } 1994 return nullptr; 1995 } 1996 1997 bool isInSchedulingRegion(ScheduleData *SD) const { 1998 return SD->SchedulingRegionID == SchedulingRegionID; 1999 } 2000 2001 /// Marks an instruction as scheduled and puts all dependent ready 2002 /// instructions into the ready-list. 2003 template <typename ReadyListType> 2004 void schedule(ScheduleData *SD, ReadyListType &ReadyList) { 2005 SD->IsScheduled = true; 2006 LLVM_DEBUG(dbgs() << "SLP: schedule " << *SD << "\n"); 2007 2008 ScheduleData *BundleMember = SD; 2009 while (BundleMember) { 2010 if (BundleMember->Inst != BundleMember->OpValue) { 2011 BundleMember = BundleMember->NextInBundle; 2012 continue; 2013 } 2014 // Handle the def-use chain dependencies. 2015 2016 // Decrement the unscheduled counter and insert to ready list if ready. 2017 auto &&DecrUnsched = [this, &ReadyList](Instruction *I) { 2018 doForAllOpcodes(I, [&ReadyList](ScheduleData *OpDef) { 2019 if (OpDef && OpDef->hasValidDependencies() && 2020 OpDef->incrementUnscheduledDeps(-1) == 0) { 2021 // There are no more unscheduled dependencies after 2022 // decrementing, so we can put the dependent instruction 2023 // into the ready list. 2024 ScheduleData *DepBundle = OpDef->FirstInBundle; 2025 assert(!DepBundle->IsScheduled && 2026 "already scheduled bundle gets ready"); 2027 ReadyList.insert(DepBundle); 2028 LLVM_DEBUG(dbgs() 2029 << "SLP: gets ready (def): " << *DepBundle << "\n"); 2030 } 2031 }); 2032 }; 2033 2034 // If BundleMember is a vector bundle, its operands may have been 2035 // reordered duiring buildTree(). We therefore need to get its operands 2036 // through the TreeEntry. 2037 if (TreeEntry *TE = BundleMember->TE) { 2038 int Lane = BundleMember->Lane; 2039 assert(Lane >= 0 && "Lane not set"); 2040 2041 // Since vectorization tree is being built recursively this assertion 2042 // ensures that the tree entry has all operands set before reaching 2043 // this code. Couple of exceptions known at the moment are extracts 2044 // where their second (immediate) operand is not added. Since 2045 // immediates do not affect scheduler behavior this is considered 2046 // okay. 2047 auto *In = TE->getMainOp(); 2048 assert(In && 2049 (isa<ExtractValueInst>(In) || isa<ExtractElementInst>(In) || 2050 In->getNumOperands() == TE->getNumOperands()) && 2051 "Missed TreeEntry operands?"); 2052 (void)In; // fake use to avoid build failure when assertions disabled 2053 2054 for (unsigned OpIdx = 0, NumOperands = TE->getNumOperands(); 2055 OpIdx != NumOperands; ++OpIdx) 2056 if (auto *I = dyn_cast<Instruction>(TE->getOperand(OpIdx)[Lane])) 2057 DecrUnsched(I); 2058 } else { 2059 // If BundleMember is a stand-alone instruction, no operand reordering 2060 // has taken place, so we directly access its operands. 2061 for (Use &U : BundleMember->Inst->operands()) 2062 if (auto *I = dyn_cast<Instruction>(U.get())) 2063 DecrUnsched(I); 2064 } 2065 // Handle the memory dependencies. 2066 for (ScheduleData *MemoryDepSD : BundleMember->MemoryDependencies) { 2067 if (MemoryDepSD->incrementUnscheduledDeps(-1) == 0) { 2068 // There are no more unscheduled dependencies after decrementing, 2069 // so we can put the dependent instruction into the ready list. 2070 ScheduleData *DepBundle = MemoryDepSD->FirstInBundle; 2071 assert(!DepBundle->IsScheduled && 2072 "already scheduled bundle gets ready"); 2073 ReadyList.insert(DepBundle); 2074 LLVM_DEBUG(dbgs() 2075 << "SLP: gets ready (mem): " << *DepBundle << "\n"); 2076 } 2077 } 2078 BundleMember = BundleMember->NextInBundle; 2079 } 2080 } 2081 2082 void doForAllOpcodes(Value *V, 2083 function_ref<void(ScheduleData *SD)> Action) { 2084 if (ScheduleData *SD = getScheduleData(V)) 2085 Action(SD); 2086 auto I = ExtraScheduleDataMap.find(V); 2087 if (I != ExtraScheduleDataMap.end()) 2088 for (auto &P : I->second) 2089 if (P.second->SchedulingRegionID == SchedulingRegionID) 2090 Action(P.second); 2091 } 2092 2093 /// Put all instructions into the ReadyList which are ready for scheduling. 2094 template <typename ReadyListType> 2095 void initialFillReadyList(ReadyListType &ReadyList) { 2096 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 2097 doForAllOpcodes(I, [&](ScheduleData *SD) { 2098 if (SD->isSchedulingEntity() && SD->isReady()) { 2099 ReadyList.insert(SD); 2100 LLVM_DEBUG(dbgs() 2101 << "SLP: initially in ready list: " << *I << "\n"); 2102 } 2103 }); 2104 } 2105 } 2106 2107 /// Checks if a bundle of instructions can be scheduled, i.e. has no 2108 /// cyclic dependencies. This is only a dry-run, no instructions are 2109 /// actually moved at this stage. 2110 /// \returns the scheduling bundle. The returned Optional value is non-None 2111 /// if \p VL is allowed to be scheduled. 2112 Optional<ScheduleData *> 2113 tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 2114 const InstructionsState &S); 2115 2116 /// Un-bundles a group of instructions. 2117 void cancelScheduling(ArrayRef<Value *> VL, Value *OpValue); 2118 2119 /// Allocates schedule data chunk. 2120 ScheduleData *allocateScheduleDataChunks(); 2121 2122 /// Extends the scheduling region so that V is inside the region. 2123 /// \returns true if the region size is within the limit. 2124 bool extendSchedulingRegion(Value *V, const InstructionsState &S); 2125 2126 /// Initialize the ScheduleData structures for new instructions in the 2127 /// scheduling region. 2128 void initScheduleData(Instruction *FromI, Instruction *ToI, 2129 ScheduleData *PrevLoadStore, 2130 ScheduleData *NextLoadStore); 2131 2132 /// Updates the dependency information of a bundle and of all instructions/ 2133 /// bundles which depend on the original bundle. 2134 void calculateDependencies(ScheduleData *SD, bool InsertInReadyList, 2135 BoUpSLP *SLP); 2136 2137 /// Sets all instruction in the scheduling region to un-scheduled. 2138 void resetSchedule(); 2139 2140 BasicBlock *BB; 2141 2142 /// Simple memory allocation for ScheduleData. 2143 std::vector<std::unique_ptr<ScheduleData[]>> ScheduleDataChunks; 2144 2145 /// The size of a ScheduleData array in ScheduleDataChunks. 2146 int ChunkSize; 2147 2148 /// The allocator position in the current chunk, which is the last entry 2149 /// of ScheduleDataChunks. 2150 int ChunkPos; 2151 2152 /// Attaches ScheduleData to Instruction. 2153 /// Note that the mapping survives during all vectorization iterations, i.e. 2154 /// ScheduleData structures are recycled. 2155 DenseMap<Value *, ScheduleData *> ScheduleDataMap; 2156 2157 /// Attaches ScheduleData to Instruction with the leading key. 2158 DenseMap<Value *, SmallDenseMap<Value *, ScheduleData *>> 2159 ExtraScheduleDataMap; 2160 2161 struct ReadyList : SmallVector<ScheduleData *, 8> { 2162 void insert(ScheduleData *SD) { push_back(SD); } 2163 }; 2164 2165 /// The ready-list for scheduling (only used for the dry-run). 2166 ReadyList ReadyInsts; 2167 2168 /// The first instruction of the scheduling region. 2169 Instruction *ScheduleStart = nullptr; 2170 2171 /// The first instruction _after_ the scheduling region. 2172 Instruction *ScheduleEnd = nullptr; 2173 2174 /// The first memory accessing instruction in the scheduling region 2175 /// (can be null). 2176 ScheduleData *FirstLoadStoreInRegion = nullptr; 2177 2178 /// The last memory accessing instruction in the scheduling region 2179 /// (can be null). 2180 ScheduleData *LastLoadStoreInRegion = nullptr; 2181 2182 /// The current size of the scheduling region. 2183 int ScheduleRegionSize = 0; 2184 2185 /// The maximum size allowed for the scheduling region. 2186 int ScheduleRegionSizeLimit = ScheduleRegionSizeBudget; 2187 2188 /// The ID of the scheduling region. For a new vectorization iteration this 2189 /// is incremented which "removes" all ScheduleData from the region. 2190 // Make sure that the initial SchedulingRegionID is greater than the 2191 // initial SchedulingRegionID in ScheduleData (which is 0). 2192 int SchedulingRegionID = 1; 2193 }; 2194 2195 /// Attaches the BlockScheduling structures to basic blocks. 2196 MapVector<BasicBlock *, std::unique_ptr<BlockScheduling>> BlocksSchedules; 2197 2198 /// Performs the "real" scheduling. Done before vectorization is actually 2199 /// performed in a basic block. 2200 void scheduleBlock(BlockScheduling *BS); 2201 2202 /// List of users to ignore during scheduling and that don't need extracting. 2203 ArrayRef<Value *> UserIgnoreList; 2204 2205 using OrdersType = SmallVector<unsigned, 4>; 2206 /// A DenseMapInfo implementation for holding DenseMaps and DenseSets of 2207 /// sorted SmallVectors of unsigned. 2208 struct OrdersTypeDenseMapInfo { 2209 static OrdersType getEmptyKey() { 2210 OrdersType V; 2211 V.push_back(~1U); 2212 return V; 2213 } 2214 2215 static OrdersType getTombstoneKey() { 2216 OrdersType V; 2217 V.push_back(~2U); 2218 return V; 2219 } 2220 2221 static unsigned getHashValue(const OrdersType &V) { 2222 return static_cast<unsigned>(hash_combine_range(V.begin(), V.end())); 2223 } 2224 2225 static bool isEqual(const OrdersType &LHS, const OrdersType &RHS) { 2226 return LHS == RHS; 2227 } 2228 }; 2229 2230 /// Contains orders of operations along with the number of bundles that have 2231 /// operations in this order. It stores only those orders that require 2232 /// reordering, if reordering is not required it is counted using \a 2233 /// NumOpsWantToKeepOriginalOrder. 2234 DenseMap<OrdersType, unsigned, OrdersTypeDenseMapInfo> NumOpsWantToKeepOrder; 2235 /// Number of bundles that do not require reordering. 2236 unsigned NumOpsWantToKeepOriginalOrder = 0; 2237 2238 // Analysis and block reference. 2239 Function *F; 2240 ScalarEvolution *SE; 2241 TargetTransformInfo *TTI; 2242 TargetLibraryInfo *TLI; 2243 AliasAnalysis *AA; 2244 LoopInfo *LI; 2245 DominatorTree *DT; 2246 AssumptionCache *AC; 2247 DemandedBits *DB; 2248 const DataLayout *DL; 2249 OptimizationRemarkEmitter *ORE; 2250 2251 unsigned MaxVecRegSize; // This is set by TTI or overridden by cl::opt. 2252 unsigned MinVecRegSize; // Set by cl::opt (default: 128). 2253 2254 /// Instruction builder to construct the vectorized tree. 2255 IRBuilder<> Builder; 2256 2257 /// A map of scalar integer values to the smallest bit width with which they 2258 /// can legally be represented. The values map to (width, signed) pairs, 2259 /// where "width" indicates the minimum bit width and "signed" is True if the 2260 /// value must be signed-extended, rather than zero-extended, back to its 2261 /// original width. 2262 MapVector<Value *, std::pair<uint64_t, bool>> MinBWs; 2263 }; 2264 2265 } // end namespace slpvectorizer 2266 2267 template <> struct GraphTraits<BoUpSLP *> { 2268 using TreeEntry = BoUpSLP::TreeEntry; 2269 2270 /// NodeRef has to be a pointer per the GraphWriter. 2271 using NodeRef = TreeEntry *; 2272 2273 using ContainerTy = BoUpSLP::TreeEntry::VecTreeTy; 2274 2275 /// Add the VectorizableTree to the index iterator to be able to return 2276 /// TreeEntry pointers. 2277 struct ChildIteratorType 2278 : public iterator_adaptor_base< 2279 ChildIteratorType, SmallVector<BoUpSLP::EdgeInfo, 1>::iterator> { 2280 ContainerTy &VectorizableTree; 2281 2282 ChildIteratorType(SmallVector<BoUpSLP::EdgeInfo, 1>::iterator W, 2283 ContainerTy &VT) 2284 : ChildIteratorType::iterator_adaptor_base(W), VectorizableTree(VT) {} 2285 2286 NodeRef operator*() { return I->UserTE; } 2287 }; 2288 2289 static NodeRef getEntryNode(BoUpSLP &R) { 2290 return R.VectorizableTree[0].get(); 2291 } 2292 2293 static ChildIteratorType child_begin(NodeRef N) { 2294 return {N->UserTreeIndices.begin(), N->Container}; 2295 } 2296 2297 static ChildIteratorType child_end(NodeRef N) { 2298 return {N->UserTreeIndices.end(), N->Container}; 2299 } 2300 2301 /// For the node iterator we just need to turn the TreeEntry iterator into a 2302 /// TreeEntry* iterator so that it dereferences to NodeRef. 2303 class nodes_iterator { 2304 using ItTy = ContainerTy::iterator; 2305 ItTy It; 2306 2307 public: 2308 nodes_iterator(const ItTy &It2) : It(It2) {} 2309 NodeRef operator*() { return It->get(); } 2310 nodes_iterator operator++() { 2311 ++It; 2312 return *this; 2313 } 2314 bool operator!=(const nodes_iterator &N2) const { return N2.It != It; } 2315 }; 2316 2317 static nodes_iterator nodes_begin(BoUpSLP *R) { 2318 return nodes_iterator(R->VectorizableTree.begin()); 2319 } 2320 2321 static nodes_iterator nodes_end(BoUpSLP *R) { 2322 return nodes_iterator(R->VectorizableTree.end()); 2323 } 2324 2325 static unsigned size(BoUpSLP *R) { return R->VectorizableTree.size(); } 2326 }; 2327 2328 template <> struct DOTGraphTraits<BoUpSLP *> : public DefaultDOTGraphTraits { 2329 using TreeEntry = BoUpSLP::TreeEntry; 2330 2331 DOTGraphTraits(bool isSimple = false) : DefaultDOTGraphTraits(isSimple) {} 2332 2333 std::string getNodeLabel(const TreeEntry *Entry, const BoUpSLP *R) { 2334 std::string Str; 2335 raw_string_ostream OS(Str); 2336 if (isSplat(Entry->Scalars)) { 2337 OS << "<splat> " << *Entry->Scalars[0]; 2338 return Str; 2339 } 2340 for (auto V : Entry->Scalars) { 2341 OS << *V; 2342 if (std::any_of( 2343 R->ExternalUses.begin(), R->ExternalUses.end(), 2344 [&](const BoUpSLP::ExternalUser &EU) { return EU.Scalar == V; })) 2345 OS << " <extract>"; 2346 OS << "\n"; 2347 } 2348 return Str; 2349 } 2350 2351 static std::string getNodeAttributes(const TreeEntry *Entry, 2352 const BoUpSLP *) { 2353 if (Entry->State == TreeEntry::NeedToGather) 2354 return "color=red"; 2355 return ""; 2356 } 2357 }; 2358 2359 } // end namespace llvm 2360 2361 BoUpSLP::~BoUpSLP() { 2362 for (const auto &Pair : DeletedInstructions) { 2363 // Replace operands of ignored instructions with Undefs in case if they were 2364 // marked for deletion. 2365 if (Pair.getSecond()) { 2366 Value *Undef = UndefValue::get(Pair.getFirst()->getType()); 2367 Pair.getFirst()->replaceAllUsesWith(Undef); 2368 } 2369 Pair.getFirst()->dropAllReferences(); 2370 } 2371 for (const auto &Pair : DeletedInstructions) { 2372 assert(Pair.getFirst()->use_empty() && 2373 "trying to erase instruction with users."); 2374 Pair.getFirst()->eraseFromParent(); 2375 } 2376 assert(!verifyFunction(*F, &dbgs())); 2377 } 2378 2379 void BoUpSLP::eraseInstructions(ArrayRef<Value *> AV) { 2380 for (auto *V : AV) { 2381 if (auto *I = dyn_cast<Instruction>(V)) 2382 eraseInstruction(I, /*ReplaceWithUndef=*/true); 2383 }; 2384 } 2385 2386 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2387 ArrayRef<Value *> UserIgnoreLst) { 2388 ExtraValueToDebugLocsMap ExternallyUsedValues; 2389 buildTree(Roots, ExternallyUsedValues, UserIgnoreLst); 2390 } 2391 2392 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2393 ExtraValueToDebugLocsMap &ExternallyUsedValues, 2394 ArrayRef<Value *> UserIgnoreLst) { 2395 deleteTree(); 2396 UserIgnoreList = UserIgnoreLst; 2397 if (!allSameType(Roots)) 2398 return; 2399 buildTree_rec(Roots, 0, EdgeInfo()); 2400 2401 // Collect the values that we need to extract from the tree. 2402 for (auto &TEPtr : VectorizableTree) { 2403 TreeEntry *Entry = TEPtr.get(); 2404 2405 // No need to handle users of gathered values. 2406 if (Entry->State == TreeEntry::NeedToGather) 2407 continue; 2408 2409 // For each lane: 2410 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 2411 Value *Scalar = Entry->Scalars[Lane]; 2412 int FoundLane = Lane; 2413 if (!Entry->ReuseShuffleIndices.empty()) { 2414 FoundLane = 2415 std::distance(Entry->ReuseShuffleIndices.begin(), 2416 llvm::find(Entry->ReuseShuffleIndices, FoundLane)); 2417 } 2418 2419 // Check if the scalar is externally used as an extra arg. 2420 auto ExtI = ExternallyUsedValues.find(Scalar); 2421 if (ExtI != ExternallyUsedValues.end()) { 2422 LLVM_DEBUG(dbgs() << "SLP: Need to extract: Extra arg from lane " 2423 << Lane << " from " << *Scalar << ".\n"); 2424 ExternalUses.emplace_back(Scalar, nullptr, FoundLane); 2425 } 2426 for (User *U : Scalar->users()) { 2427 LLVM_DEBUG(dbgs() << "SLP: Checking user:" << *U << ".\n"); 2428 2429 Instruction *UserInst = dyn_cast<Instruction>(U); 2430 if (!UserInst) 2431 continue; 2432 2433 // Skip in-tree scalars that become vectors 2434 if (TreeEntry *UseEntry = getTreeEntry(U)) { 2435 Value *UseScalar = UseEntry->Scalars[0]; 2436 // Some in-tree scalars will remain as scalar in vectorized 2437 // instructions. If that is the case, the one in Lane 0 will 2438 // be used. 2439 if (UseScalar != U || 2440 !InTreeUserNeedToExtract(Scalar, UserInst, TLI)) { 2441 LLVM_DEBUG(dbgs() << "SLP: \tInternal user will be removed:" << *U 2442 << ".\n"); 2443 assert(UseEntry->State != TreeEntry::NeedToGather && "Bad state"); 2444 continue; 2445 } 2446 } 2447 2448 // Ignore users in the user ignore list. 2449 if (is_contained(UserIgnoreList, UserInst)) 2450 continue; 2451 2452 LLVM_DEBUG(dbgs() << "SLP: Need to extract:" << *U << " from lane " 2453 << Lane << " from " << *Scalar << ".\n"); 2454 ExternalUses.push_back(ExternalUser(Scalar, U, FoundLane)); 2455 } 2456 } 2457 } 2458 } 2459 2460 void BoUpSLP::buildTree_rec(ArrayRef<Value *> VL, unsigned Depth, 2461 const EdgeInfo &UserTreeIdx) { 2462 assert((allConstant(VL) || allSameType(VL)) && "Invalid types!"); 2463 2464 InstructionsState S = getSameOpcode(VL); 2465 if (Depth == RecursionMaxDepth) { 2466 LLVM_DEBUG(dbgs() << "SLP: Gathering due to max recursion depth.\n"); 2467 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2468 return; 2469 } 2470 2471 // Don't handle vectors. 2472 if (S.OpValue->getType()->isVectorTy()) { 2473 LLVM_DEBUG(dbgs() << "SLP: Gathering due to vector type.\n"); 2474 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2475 return; 2476 } 2477 2478 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) 2479 if (SI->getValueOperand()->getType()->isVectorTy()) { 2480 LLVM_DEBUG(dbgs() << "SLP: Gathering due to store vector type.\n"); 2481 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2482 return; 2483 } 2484 2485 // If all of the operands are identical or constant we have a simple solution. 2486 if (allConstant(VL) || isSplat(VL) || !allSameBlock(VL) || !S.getOpcode()) { 2487 LLVM_DEBUG(dbgs() << "SLP: Gathering due to C,S,B,O. \n"); 2488 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2489 return; 2490 } 2491 2492 // We now know that this is a vector of instructions of the same type from 2493 // the same block. 2494 2495 // Don't vectorize ephemeral values. 2496 for (Value *V : VL) { 2497 if (EphValues.count(V)) { 2498 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2499 << ") is ephemeral.\n"); 2500 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2501 return; 2502 } 2503 } 2504 2505 // Check if this is a duplicate of another entry. 2506 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 2507 LLVM_DEBUG(dbgs() << "SLP: \tChecking bundle: " << *S.OpValue << ".\n"); 2508 if (!E->isSame(VL)) { 2509 LLVM_DEBUG(dbgs() << "SLP: Gathering due to partial overlap.\n"); 2510 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2511 return; 2512 } 2513 // Record the reuse of the tree node. FIXME, currently this is only used to 2514 // properly draw the graph rather than for the actual vectorization. 2515 E->UserTreeIndices.push_back(UserTreeIdx); 2516 LLVM_DEBUG(dbgs() << "SLP: Perfect diamond merge at " << *S.OpValue 2517 << ".\n"); 2518 return; 2519 } 2520 2521 // Check that none of the instructions in the bundle are already in the tree. 2522 for (Value *V : VL) { 2523 auto *I = dyn_cast<Instruction>(V); 2524 if (!I) 2525 continue; 2526 if (getTreeEntry(I)) { 2527 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2528 << ") is already in tree.\n"); 2529 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2530 return; 2531 } 2532 } 2533 2534 // If any of the scalars is marked as a value that needs to stay scalar, then 2535 // we need to gather the scalars. 2536 // The reduction nodes (stored in UserIgnoreList) also should stay scalar. 2537 for (Value *V : VL) { 2538 if (MustGather.count(V) || is_contained(UserIgnoreList, V)) { 2539 LLVM_DEBUG(dbgs() << "SLP: Gathering due to gathered scalar.\n"); 2540 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2541 return; 2542 } 2543 } 2544 2545 // Check that all of the users of the scalars that we want to vectorize are 2546 // schedulable. 2547 auto *VL0 = cast<Instruction>(S.OpValue); 2548 BasicBlock *BB = VL0->getParent(); 2549 2550 if (!DT->isReachableFromEntry(BB)) { 2551 // Don't go into unreachable blocks. They may contain instructions with 2552 // dependency cycles which confuse the final scheduling. 2553 LLVM_DEBUG(dbgs() << "SLP: bundle in unreachable block.\n"); 2554 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2555 return; 2556 } 2557 2558 // Check that every instruction appears once in this bundle. 2559 SmallVector<unsigned, 4> ReuseShuffleIndicies; 2560 SmallVector<Value *, 4> UniqueValues; 2561 DenseMap<Value *, unsigned> UniquePositions; 2562 for (Value *V : VL) { 2563 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 2564 ReuseShuffleIndicies.emplace_back(Res.first->second); 2565 if (Res.second) 2566 UniqueValues.emplace_back(V); 2567 } 2568 size_t NumUniqueScalarValues = UniqueValues.size(); 2569 if (NumUniqueScalarValues == VL.size()) { 2570 ReuseShuffleIndicies.clear(); 2571 } else { 2572 LLVM_DEBUG(dbgs() << "SLP: Shuffle for reused scalars.\n"); 2573 if (NumUniqueScalarValues <= 1 || 2574 !llvm::isPowerOf2_32(NumUniqueScalarValues)) { 2575 LLVM_DEBUG(dbgs() << "SLP: Scalar used twice in bundle.\n"); 2576 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2577 return; 2578 } 2579 VL = UniqueValues; 2580 } 2581 2582 auto &BSRef = BlocksSchedules[BB]; 2583 if (!BSRef) 2584 BSRef = std::make_unique<BlockScheduling>(BB); 2585 2586 BlockScheduling &BS = *BSRef.get(); 2587 2588 Optional<ScheduleData *> Bundle = BS.tryScheduleBundle(VL, this, S); 2589 if (!Bundle) { 2590 LLVM_DEBUG(dbgs() << "SLP: We are not able to schedule this bundle!\n"); 2591 assert((!BS.getScheduleData(VL0) || 2592 !BS.getScheduleData(VL0)->isPartOfBundle()) && 2593 "tryScheduleBundle should cancelScheduling on failure"); 2594 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2595 ReuseShuffleIndicies); 2596 return; 2597 } 2598 LLVM_DEBUG(dbgs() << "SLP: We are able to schedule this bundle.\n"); 2599 2600 unsigned ShuffleOrOp = S.isAltShuffle() ? 2601 (unsigned) Instruction::ShuffleVector : S.getOpcode(); 2602 switch (ShuffleOrOp) { 2603 case Instruction::PHI: { 2604 auto *PH = cast<PHINode>(VL0); 2605 2606 // Check for terminator values (e.g. invoke). 2607 for (unsigned j = 0; j < VL.size(); ++j) 2608 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 2609 Instruction *Term = dyn_cast<Instruction>( 2610 cast<PHINode>(VL[j])->getIncomingValueForBlock( 2611 PH->getIncomingBlock(i))); 2612 if (Term && Term->isTerminator()) { 2613 LLVM_DEBUG(dbgs() 2614 << "SLP: Need to swizzle PHINodes (terminator use).\n"); 2615 BS.cancelScheduling(VL, VL0); 2616 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2617 ReuseShuffleIndicies); 2618 return; 2619 } 2620 } 2621 2622 TreeEntry *TE = 2623 newTreeEntry(VL, Bundle, S, UserTreeIdx, ReuseShuffleIndicies); 2624 LLVM_DEBUG(dbgs() << "SLP: added a vector of PHINodes.\n"); 2625 2626 // Keeps the reordered operands to avoid code duplication. 2627 SmallVector<ValueList, 2> OperandsVec; 2628 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 2629 ValueList Operands; 2630 // Prepare the operand vector. 2631 for (Value *j : VL) 2632 Operands.push_back(cast<PHINode>(j)->getIncomingValueForBlock( 2633 PH->getIncomingBlock(i))); 2634 TE->setOperand(i, Operands); 2635 OperandsVec.push_back(Operands); 2636 } 2637 for (unsigned OpIdx = 0, OpE = OperandsVec.size(); OpIdx != OpE; ++OpIdx) 2638 buildTree_rec(OperandsVec[OpIdx], Depth + 1, {TE, OpIdx}); 2639 return; 2640 } 2641 case Instruction::ExtractValue: 2642 case Instruction::ExtractElement: { 2643 OrdersType CurrentOrder; 2644 bool Reuse = canReuseExtract(VL, VL0, CurrentOrder); 2645 if (Reuse) { 2646 LLVM_DEBUG(dbgs() << "SLP: Reusing or shuffling extract sequence.\n"); 2647 ++NumOpsWantToKeepOriginalOrder; 2648 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2649 ReuseShuffleIndicies); 2650 // This is a special case, as it does not gather, but at the same time 2651 // we are not extending buildTree_rec() towards the operands. 2652 ValueList Op0; 2653 Op0.assign(VL.size(), VL0->getOperand(0)); 2654 VectorizableTree.back()->setOperand(0, Op0); 2655 return; 2656 } 2657 if (!CurrentOrder.empty()) { 2658 LLVM_DEBUG({ 2659 dbgs() << "SLP: Reusing or shuffling of reordered extract sequence " 2660 "with order"; 2661 for (unsigned Idx : CurrentOrder) 2662 dbgs() << " " << Idx; 2663 dbgs() << "\n"; 2664 }); 2665 // Insert new order with initial value 0, if it does not exist, 2666 // otherwise return the iterator to the existing one. 2667 auto StoredCurrentOrderAndNum = 2668 NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first; 2669 ++StoredCurrentOrderAndNum->getSecond(); 2670 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2671 ReuseShuffleIndicies, 2672 StoredCurrentOrderAndNum->getFirst()); 2673 // This is a special case, as it does not gather, but at the same time 2674 // we are not extending buildTree_rec() towards the operands. 2675 ValueList Op0; 2676 Op0.assign(VL.size(), VL0->getOperand(0)); 2677 VectorizableTree.back()->setOperand(0, Op0); 2678 return; 2679 } 2680 LLVM_DEBUG(dbgs() << "SLP: Gather extract sequence.\n"); 2681 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2682 ReuseShuffleIndicies); 2683 BS.cancelScheduling(VL, VL0); 2684 return; 2685 } 2686 case Instruction::Load: { 2687 // Check that a vectorized load would load the same memory as a scalar 2688 // load. For example, we don't want to vectorize loads that are smaller 2689 // than 8-bit. Even though we have a packed struct {<i2, i2, i2, i2>} LLVM 2690 // treats loading/storing it as an i8 struct. If we vectorize loads/stores 2691 // from such a struct, we read/write packed bits disagreeing with the 2692 // unvectorized version. 2693 Type *ScalarTy = VL0->getType(); 2694 2695 if (DL->getTypeSizeInBits(ScalarTy) != 2696 DL->getTypeAllocSizeInBits(ScalarTy)) { 2697 BS.cancelScheduling(VL, VL0); 2698 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2699 ReuseShuffleIndicies); 2700 LLVM_DEBUG(dbgs() << "SLP: Gathering loads of non-packed type.\n"); 2701 return; 2702 } 2703 2704 // Make sure all loads in the bundle are simple - we can't vectorize 2705 // atomic or volatile loads. 2706 SmallVector<Value *, 4> PointerOps(VL.size()); 2707 auto POIter = PointerOps.begin(); 2708 for (Value *V : VL) { 2709 auto *L = cast<LoadInst>(V); 2710 if (!L->isSimple()) { 2711 BS.cancelScheduling(VL, VL0); 2712 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2713 ReuseShuffleIndicies); 2714 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple loads.\n"); 2715 return; 2716 } 2717 *POIter = L->getPointerOperand(); 2718 ++POIter; 2719 } 2720 2721 OrdersType CurrentOrder; 2722 // Check the order of pointer operands. 2723 if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) { 2724 Value *Ptr0; 2725 Value *PtrN; 2726 if (CurrentOrder.empty()) { 2727 Ptr0 = PointerOps.front(); 2728 PtrN = PointerOps.back(); 2729 } else { 2730 Ptr0 = PointerOps[CurrentOrder.front()]; 2731 PtrN = PointerOps[CurrentOrder.back()]; 2732 } 2733 const SCEV *Scev0 = SE->getSCEV(Ptr0); 2734 const SCEV *ScevN = SE->getSCEV(PtrN); 2735 const auto *Diff = 2736 dyn_cast<SCEVConstant>(SE->getMinusSCEV(ScevN, Scev0)); 2737 uint64_t Size = DL->getTypeAllocSize(ScalarTy); 2738 // Check that the sorted loads are consecutive. 2739 if (Diff && Diff->getAPInt() == (VL.size() - 1) * Size) { 2740 if (CurrentOrder.empty()) { 2741 // Original loads are consecutive and does not require reordering. 2742 ++NumOpsWantToKeepOriginalOrder; 2743 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, 2744 UserTreeIdx, ReuseShuffleIndicies); 2745 TE->setOperandsInOrder(); 2746 LLVM_DEBUG(dbgs() << "SLP: added a vector of loads.\n"); 2747 } else { 2748 // Need to reorder. 2749 auto I = NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first; 2750 ++I->getSecond(); 2751 TreeEntry *TE = 2752 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2753 ReuseShuffleIndicies, I->getFirst()); 2754 TE->setOperandsInOrder(); 2755 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled loads.\n"); 2756 } 2757 return; 2758 } 2759 } 2760 2761 LLVM_DEBUG(dbgs() << "SLP: Gathering non-consecutive loads.\n"); 2762 BS.cancelScheduling(VL, VL0); 2763 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2764 ReuseShuffleIndicies); 2765 return; 2766 } 2767 case Instruction::ZExt: 2768 case Instruction::SExt: 2769 case Instruction::FPToUI: 2770 case Instruction::FPToSI: 2771 case Instruction::FPExt: 2772 case Instruction::PtrToInt: 2773 case Instruction::IntToPtr: 2774 case Instruction::SIToFP: 2775 case Instruction::UIToFP: 2776 case Instruction::Trunc: 2777 case Instruction::FPTrunc: 2778 case Instruction::BitCast: { 2779 Type *SrcTy = VL0->getOperand(0)->getType(); 2780 for (Value *V : VL) { 2781 Type *Ty = cast<Instruction>(V)->getOperand(0)->getType(); 2782 if (Ty != SrcTy || !isValidElementType(Ty)) { 2783 BS.cancelScheduling(VL, VL0); 2784 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2785 ReuseShuffleIndicies); 2786 LLVM_DEBUG(dbgs() 2787 << "SLP: Gathering casts with different src types.\n"); 2788 return; 2789 } 2790 } 2791 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2792 ReuseShuffleIndicies); 2793 LLVM_DEBUG(dbgs() << "SLP: added a vector of casts.\n"); 2794 2795 TE->setOperandsInOrder(); 2796 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 2797 ValueList Operands; 2798 // Prepare the operand vector. 2799 for (Value *V : VL) 2800 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 2801 2802 buildTree_rec(Operands, Depth + 1, {TE, i}); 2803 } 2804 return; 2805 } 2806 case Instruction::ICmp: 2807 case Instruction::FCmp: { 2808 // Check that all of the compares have the same predicate. 2809 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 2810 CmpInst::Predicate SwapP0 = CmpInst::getSwappedPredicate(P0); 2811 Type *ComparedTy = VL0->getOperand(0)->getType(); 2812 for (Value *V : VL) { 2813 CmpInst *Cmp = cast<CmpInst>(V); 2814 if ((Cmp->getPredicate() != P0 && Cmp->getPredicate() != SwapP0) || 2815 Cmp->getOperand(0)->getType() != ComparedTy) { 2816 BS.cancelScheduling(VL, VL0); 2817 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2818 ReuseShuffleIndicies); 2819 LLVM_DEBUG(dbgs() 2820 << "SLP: Gathering cmp with different predicate.\n"); 2821 return; 2822 } 2823 } 2824 2825 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2826 ReuseShuffleIndicies); 2827 LLVM_DEBUG(dbgs() << "SLP: added a vector of compares.\n"); 2828 2829 ValueList Left, Right; 2830 if (cast<CmpInst>(VL0)->isCommutative()) { 2831 // Commutative predicate - collect + sort operands of the instructions 2832 // so that each side is more likely to have the same opcode. 2833 assert(P0 == SwapP0 && "Commutative Predicate mismatch"); 2834 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 2835 } else { 2836 // Collect operands - commute if it uses the swapped predicate. 2837 for (Value *V : VL) { 2838 auto *Cmp = cast<CmpInst>(V); 2839 Value *LHS = Cmp->getOperand(0); 2840 Value *RHS = Cmp->getOperand(1); 2841 if (Cmp->getPredicate() != P0) 2842 std::swap(LHS, RHS); 2843 Left.push_back(LHS); 2844 Right.push_back(RHS); 2845 } 2846 } 2847 TE->setOperand(0, Left); 2848 TE->setOperand(1, Right); 2849 buildTree_rec(Left, Depth + 1, {TE, 0}); 2850 buildTree_rec(Right, Depth + 1, {TE, 1}); 2851 return; 2852 } 2853 case Instruction::Select: 2854 case Instruction::FNeg: 2855 case Instruction::Add: 2856 case Instruction::FAdd: 2857 case Instruction::Sub: 2858 case Instruction::FSub: 2859 case Instruction::Mul: 2860 case Instruction::FMul: 2861 case Instruction::UDiv: 2862 case Instruction::SDiv: 2863 case Instruction::FDiv: 2864 case Instruction::URem: 2865 case Instruction::SRem: 2866 case Instruction::FRem: 2867 case Instruction::Shl: 2868 case Instruction::LShr: 2869 case Instruction::AShr: 2870 case Instruction::And: 2871 case Instruction::Or: 2872 case Instruction::Xor: { 2873 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2874 ReuseShuffleIndicies); 2875 LLVM_DEBUG(dbgs() << "SLP: added a vector of un/bin op.\n"); 2876 2877 // Sort operands of the instructions so that each side is more likely to 2878 // have the same opcode. 2879 if (isa<BinaryOperator>(VL0) && VL0->isCommutative()) { 2880 ValueList Left, Right; 2881 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 2882 TE->setOperand(0, Left); 2883 TE->setOperand(1, Right); 2884 buildTree_rec(Left, Depth + 1, {TE, 0}); 2885 buildTree_rec(Right, Depth + 1, {TE, 1}); 2886 return; 2887 } 2888 2889 TE->setOperandsInOrder(); 2890 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 2891 ValueList Operands; 2892 // Prepare the operand vector. 2893 for (Value *j : VL) 2894 Operands.push_back(cast<Instruction>(j)->getOperand(i)); 2895 2896 buildTree_rec(Operands, Depth + 1, {TE, i}); 2897 } 2898 return; 2899 } 2900 case Instruction::GetElementPtr: { 2901 // We don't combine GEPs with complicated (nested) indexing. 2902 for (Value *V : VL) { 2903 if (cast<Instruction>(V)->getNumOperands() != 2) { 2904 LLVM_DEBUG(dbgs() << "SLP: not-vectorizable GEP (nested indexes).\n"); 2905 BS.cancelScheduling(VL, VL0); 2906 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2907 ReuseShuffleIndicies); 2908 return; 2909 } 2910 } 2911 2912 // We can't combine several GEPs into one vector if they operate on 2913 // different types. 2914 Type *Ty0 = VL0->getOperand(0)->getType(); 2915 for (Value *V : VL) { 2916 Type *CurTy = cast<Instruction>(V)->getOperand(0)->getType(); 2917 if (Ty0 != CurTy) { 2918 LLVM_DEBUG(dbgs() 2919 << "SLP: not-vectorizable GEP (different types).\n"); 2920 BS.cancelScheduling(VL, VL0); 2921 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2922 ReuseShuffleIndicies); 2923 return; 2924 } 2925 } 2926 2927 // We don't combine GEPs with non-constant indexes. 2928 Type *Ty1 = VL0->getOperand(1)->getType(); 2929 for (Value *V : VL) { 2930 auto Op = cast<Instruction>(V)->getOperand(1); 2931 if (!isa<ConstantInt>(Op) || 2932 (Op->getType() != Ty1 && 2933 Op->getType()->getScalarSizeInBits() > 2934 DL->getIndexSizeInBits( 2935 V->getType()->getPointerAddressSpace()))) { 2936 LLVM_DEBUG(dbgs() 2937 << "SLP: not-vectorizable GEP (non-constant indexes).\n"); 2938 BS.cancelScheduling(VL, VL0); 2939 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2940 ReuseShuffleIndicies); 2941 return; 2942 } 2943 } 2944 2945 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2946 ReuseShuffleIndicies); 2947 LLVM_DEBUG(dbgs() << "SLP: added a vector of GEPs.\n"); 2948 TE->setOperandsInOrder(); 2949 for (unsigned i = 0, e = 2; i < e; ++i) { 2950 ValueList Operands; 2951 // Prepare the operand vector. 2952 for (Value *V : VL) 2953 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 2954 2955 buildTree_rec(Operands, Depth + 1, {TE, i}); 2956 } 2957 return; 2958 } 2959 case Instruction::Store: { 2960 // Check if the stores are consecutive or if we need to swizzle them. 2961 llvm::Type *ScalarTy = cast<StoreInst>(VL0)->getValueOperand()->getType(); 2962 // Make sure all stores in the bundle are simple - we can't vectorize 2963 // atomic or volatile stores. 2964 SmallVector<Value *, 4> PointerOps(VL.size()); 2965 ValueList Operands(VL.size()); 2966 auto POIter = PointerOps.begin(); 2967 auto OIter = Operands.begin(); 2968 for (Value *V : VL) { 2969 auto *SI = cast<StoreInst>(V); 2970 if (!SI->isSimple()) { 2971 BS.cancelScheduling(VL, VL0); 2972 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2973 ReuseShuffleIndicies); 2974 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple stores.\n"); 2975 return; 2976 } 2977 *POIter = SI->getPointerOperand(); 2978 *OIter = SI->getValueOperand(); 2979 ++POIter; 2980 ++OIter; 2981 } 2982 2983 OrdersType CurrentOrder; 2984 // Check the order of pointer operands. 2985 if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) { 2986 Value *Ptr0; 2987 Value *PtrN; 2988 if (CurrentOrder.empty()) { 2989 Ptr0 = PointerOps.front(); 2990 PtrN = PointerOps.back(); 2991 } else { 2992 Ptr0 = PointerOps[CurrentOrder.front()]; 2993 PtrN = PointerOps[CurrentOrder.back()]; 2994 } 2995 const SCEV *Scev0 = SE->getSCEV(Ptr0); 2996 const SCEV *ScevN = SE->getSCEV(PtrN); 2997 const auto *Diff = 2998 dyn_cast<SCEVConstant>(SE->getMinusSCEV(ScevN, Scev0)); 2999 uint64_t Size = DL->getTypeAllocSize(ScalarTy); 3000 // Check that the sorted pointer operands are consecutive. 3001 if (Diff && Diff->getAPInt() == (VL.size() - 1) * Size) { 3002 if (CurrentOrder.empty()) { 3003 // Original stores are consecutive and does not require reordering. 3004 ++NumOpsWantToKeepOriginalOrder; 3005 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, 3006 UserTreeIdx, ReuseShuffleIndicies); 3007 TE->setOperandsInOrder(); 3008 buildTree_rec(Operands, Depth + 1, {TE, 0}); 3009 LLVM_DEBUG(dbgs() << "SLP: added a vector of stores.\n"); 3010 } else { 3011 // Need to reorder. 3012 auto I = NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first; 3013 ++(I->getSecond()); 3014 TreeEntry *TE = 3015 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3016 ReuseShuffleIndicies, I->getFirst()); 3017 TE->setOperandsInOrder(); 3018 buildTree_rec(Operands, Depth + 1, {TE, 0}); 3019 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled stores.\n"); 3020 } 3021 return; 3022 } 3023 } 3024 3025 BS.cancelScheduling(VL, VL0); 3026 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3027 ReuseShuffleIndicies); 3028 LLVM_DEBUG(dbgs() << "SLP: Non-consecutive store.\n"); 3029 return; 3030 } 3031 case Instruction::Call: { 3032 // Check if the calls are all to the same vectorizable intrinsic or 3033 // library function. 3034 CallInst *CI = cast<CallInst>(VL0); 3035 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3036 3037 VFShape Shape = VFShape::get( 3038 *CI, ElementCount::getFixed(static_cast<unsigned int>(VL.size())), 3039 false /*HasGlobalPred*/); 3040 Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape); 3041 3042 if (!VecFunc && !isTriviallyVectorizable(ID)) { 3043 BS.cancelScheduling(VL, VL0); 3044 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3045 ReuseShuffleIndicies); 3046 LLVM_DEBUG(dbgs() << "SLP: Non-vectorizable call.\n"); 3047 return; 3048 } 3049 Function *F = CI->getCalledFunction(); 3050 unsigned NumArgs = CI->getNumArgOperands(); 3051 SmallVector<Value*, 4> ScalarArgs(NumArgs, nullptr); 3052 for (unsigned j = 0; j != NumArgs; ++j) 3053 if (hasVectorInstrinsicScalarOpd(ID, j)) 3054 ScalarArgs[j] = CI->getArgOperand(j); 3055 for (Value *V : VL) { 3056 CallInst *CI2 = dyn_cast<CallInst>(V); 3057 if (!CI2 || CI2->getCalledFunction() != F || 3058 getVectorIntrinsicIDForCall(CI2, TLI) != ID || 3059 (VecFunc && 3060 VecFunc != VFDatabase(*CI2).getVectorizedFunction(Shape)) || 3061 !CI->hasIdenticalOperandBundleSchema(*CI2)) { 3062 BS.cancelScheduling(VL, VL0); 3063 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3064 ReuseShuffleIndicies); 3065 LLVM_DEBUG(dbgs() << "SLP: mismatched calls:" << *CI << "!=" << *V 3066 << "\n"); 3067 return; 3068 } 3069 // Some intrinsics have scalar arguments and should be same in order for 3070 // them to be vectorized. 3071 for (unsigned j = 0; j != NumArgs; ++j) { 3072 if (hasVectorInstrinsicScalarOpd(ID, j)) { 3073 Value *A1J = CI2->getArgOperand(j); 3074 if (ScalarArgs[j] != A1J) { 3075 BS.cancelScheduling(VL, VL0); 3076 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3077 ReuseShuffleIndicies); 3078 LLVM_DEBUG(dbgs() << "SLP: mismatched arguments in call:" << *CI 3079 << " argument " << ScalarArgs[j] << "!=" << A1J 3080 << "\n"); 3081 return; 3082 } 3083 } 3084 } 3085 // Verify that the bundle operands are identical between the two calls. 3086 if (CI->hasOperandBundles() && 3087 !std::equal(CI->op_begin() + CI->getBundleOperandsStartIndex(), 3088 CI->op_begin() + CI->getBundleOperandsEndIndex(), 3089 CI2->op_begin() + CI2->getBundleOperandsStartIndex())) { 3090 BS.cancelScheduling(VL, VL0); 3091 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3092 ReuseShuffleIndicies); 3093 LLVM_DEBUG(dbgs() << "SLP: mismatched bundle operands in calls:" 3094 << *CI << "!=" << *V << '\n'); 3095 return; 3096 } 3097 } 3098 3099 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3100 ReuseShuffleIndicies); 3101 TE->setOperandsInOrder(); 3102 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 3103 ValueList Operands; 3104 // Prepare the operand vector. 3105 for (Value *V : VL) { 3106 auto *CI2 = cast<CallInst>(V); 3107 Operands.push_back(CI2->getArgOperand(i)); 3108 } 3109 buildTree_rec(Operands, Depth + 1, {TE, i}); 3110 } 3111 return; 3112 } 3113 case Instruction::ShuffleVector: { 3114 // If this is not an alternate sequence of opcode like add-sub 3115 // then do not vectorize this instruction. 3116 if (!S.isAltShuffle()) { 3117 BS.cancelScheduling(VL, VL0); 3118 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3119 ReuseShuffleIndicies); 3120 LLVM_DEBUG(dbgs() << "SLP: ShuffleVector are not vectorized.\n"); 3121 return; 3122 } 3123 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3124 ReuseShuffleIndicies); 3125 LLVM_DEBUG(dbgs() << "SLP: added a ShuffleVector op.\n"); 3126 3127 // Reorder operands if reordering would enable vectorization. 3128 if (isa<BinaryOperator>(VL0)) { 3129 ValueList Left, Right; 3130 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 3131 TE->setOperand(0, Left); 3132 TE->setOperand(1, Right); 3133 buildTree_rec(Left, Depth + 1, {TE, 0}); 3134 buildTree_rec(Right, Depth + 1, {TE, 1}); 3135 return; 3136 } 3137 3138 TE->setOperandsInOrder(); 3139 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 3140 ValueList Operands; 3141 // Prepare the operand vector. 3142 for (Value *V : VL) 3143 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3144 3145 buildTree_rec(Operands, Depth + 1, {TE, i}); 3146 } 3147 return; 3148 } 3149 default: 3150 BS.cancelScheduling(VL, VL0); 3151 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3152 ReuseShuffleIndicies); 3153 LLVM_DEBUG(dbgs() << "SLP: Gathering unknown instruction.\n"); 3154 return; 3155 } 3156 } 3157 3158 unsigned BoUpSLP::canMapToVector(Type *T, const DataLayout &DL) const { 3159 unsigned N = 1; 3160 Type *EltTy = T; 3161 3162 while (isa<StructType>(EltTy) || isa<ArrayType>(EltTy) || 3163 isa<VectorType>(EltTy)) { 3164 if (auto *ST = dyn_cast<StructType>(EltTy)) { 3165 // Check that struct is homogeneous. 3166 for (const auto *Ty : ST->elements()) 3167 if (Ty != *ST->element_begin()) 3168 return 0; 3169 N *= ST->getNumElements(); 3170 EltTy = *ST->element_begin(); 3171 } else if (auto *AT = dyn_cast<ArrayType>(EltTy)) { 3172 N *= AT->getNumElements(); 3173 EltTy = AT->getElementType(); 3174 } else { 3175 auto *VT = cast<FixedVectorType>(EltTy); 3176 N *= VT->getNumElements(); 3177 EltTy = VT->getElementType(); 3178 } 3179 } 3180 3181 if (!isValidElementType(EltTy)) 3182 return 0; 3183 uint64_t VTSize = DL.getTypeStoreSizeInBits(FixedVectorType::get(EltTy, N)); 3184 if (VTSize < MinVecRegSize || VTSize > MaxVecRegSize || VTSize != DL.getTypeStoreSizeInBits(T)) 3185 return 0; 3186 return N; 3187 } 3188 3189 bool BoUpSLP::canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 3190 SmallVectorImpl<unsigned> &CurrentOrder) const { 3191 Instruction *E0 = cast<Instruction>(OpValue); 3192 assert(E0->getOpcode() == Instruction::ExtractElement || 3193 E0->getOpcode() == Instruction::ExtractValue); 3194 assert(E0->getOpcode() == getSameOpcode(VL).getOpcode() && "Invalid opcode"); 3195 // Check if all of the extracts come from the same vector and from the 3196 // correct offset. 3197 Value *Vec = E0->getOperand(0); 3198 3199 CurrentOrder.clear(); 3200 3201 // We have to extract from a vector/aggregate with the same number of elements. 3202 unsigned NElts; 3203 if (E0->getOpcode() == Instruction::ExtractValue) { 3204 const DataLayout &DL = E0->getModule()->getDataLayout(); 3205 NElts = canMapToVector(Vec->getType(), DL); 3206 if (!NElts) 3207 return false; 3208 // Check if load can be rewritten as load of vector. 3209 LoadInst *LI = dyn_cast<LoadInst>(Vec); 3210 if (!LI || !LI->isSimple() || !LI->hasNUses(VL.size())) 3211 return false; 3212 } else { 3213 NElts = cast<FixedVectorType>(Vec->getType())->getNumElements(); 3214 } 3215 3216 if (NElts != VL.size()) 3217 return false; 3218 3219 // Check that all of the indices extract from the correct offset. 3220 bool ShouldKeepOrder = true; 3221 unsigned E = VL.size(); 3222 // Assign to all items the initial value E + 1 so we can check if the extract 3223 // instruction index was used already. 3224 // Also, later we can check that all the indices are used and we have a 3225 // consecutive access in the extract instructions, by checking that no 3226 // element of CurrentOrder still has value E + 1. 3227 CurrentOrder.assign(E, E + 1); 3228 unsigned I = 0; 3229 for (; I < E; ++I) { 3230 auto *Inst = cast<Instruction>(VL[I]); 3231 if (Inst->getOperand(0) != Vec) 3232 break; 3233 Optional<unsigned> Idx = getExtractIndex(Inst); 3234 if (!Idx) 3235 break; 3236 const unsigned ExtIdx = *Idx; 3237 if (ExtIdx != I) { 3238 if (ExtIdx >= E || CurrentOrder[ExtIdx] != E + 1) 3239 break; 3240 ShouldKeepOrder = false; 3241 CurrentOrder[ExtIdx] = I; 3242 } else { 3243 if (CurrentOrder[I] != E + 1) 3244 break; 3245 CurrentOrder[I] = I; 3246 } 3247 } 3248 if (I < E) { 3249 CurrentOrder.clear(); 3250 return false; 3251 } 3252 3253 return ShouldKeepOrder; 3254 } 3255 3256 bool BoUpSLP::areAllUsersVectorized(Instruction *I) const { 3257 return I->hasOneUse() || 3258 std::all_of(I->user_begin(), I->user_end(), [this](User *U) { 3259 return ScalarToTreeEntry.count(U) > 0; 3260 }); 3261 } 3262 3263 static std::pair<unsigned, unsigned> 3264 getVectorCallCosts(CallInst *CI, FixedVectorType *VecTy, 3265 TargetTransformInfo *TTI, TargetLibraryInfo *TLI) { 3266 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3267 3268 // Calculate the cost of the scalar and vector calls. 3269 IntrinsicCostAttributes CostAttrs(ID, *CI, VecTy->getNumElements()); 3270 int IntrinsicCost = 3271 TTI->getIntrinsicInstrCost(CostAttrs, TTI::TCK_RecipThroughput); 3272 3273 auto Shape = VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>( 3274 VecTy->getNumElements())), 3275 false /*HasGlobalPred*/); 3276 Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape); 3277 int LibCost = IntrinsicCost; 3278 if (!CI->isNoBuiltin() && VecFunc) { 3279 // Calculate the cost of the vector library call. 3280 SmallVector<Type *, 4> VecTys; 3281 for (Use &Arg : CI->args()) 3282 VecTys.push_back( 3283 FixedVectorType::get(Arg->getType(), VecTy->getNumElements())); 3284 3285 // If the corresponding vector call is cheaper, return its cost. 3286 LibCost = TTI->getCallInstrCost(nullptr, VecTy, VecTys, 3287 TTI::TCK_RecipThroughput); 3288 } 3289 return {IntrinsicCost, LibCost}; 3290 } 3291 3292 int BoUpSLP::getEntryCost(TreeEntry *E) { 3293 ArrayRef<Value*> VL = E->Scalars; 3294 3295 Type *ScalarTy = VL[0]->getType(); 3296 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 3297 ScalarTy = SI->getValueOperand()->getType(); 3298 else if (CmpInst *CI = dyn_cast<CmpInst>(VL[0])) 3299 ScalarTy = CI->getOperand(0)->getType(); 3300 auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); 3301 TTI::TargetCostKind CostKind = TTI::TCK_RecipThroughput; 3302 3303 // If we have computed a smaller type for the expression, update VecTy so 3304 // that the costs will be accurate. 3305 if (MinBWs.count(VL[0])) 3306 VecTy = FixedVectorType::get( 3307 IntegerType::get(F->getContext(), MinBWs[VL[0]].first), VL.size()); 3308 3309 unsigned ReuseShuffleNumbers = E->ReuseShuffleIndices.size(); 3310 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 3311 int ReuseShuffleCost = 0; 3312 if (NeedToShuffleReuses) { 3313 ReuseShuffleCost = 3314 TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3315 } 3316 if (E->State == TreeEntry::NeedToGather) { 3317 if (allConstant(VL)) 3318 return 0; 3319 if (isSplat(VL)) { 3320 return ReuseShuffleCost + 3321 TTI->getShuffleCost(TargetTransformInfo::SK_Broadcast, VecTy, 0); 3322 } 3323 if (E->getOpcode() == Instruction::ExtractElement && 3324 allSameType(VL) && allSameBlock(VL)) { 3325 Optional<TargetTransformInfo::ShuffleKind> ShuffleKind = isShuffle(VL); 3326 if (ShuffleKind.hasValue()) { 3327 int Cost = TTI->getShuffleCost(ShuffleKind.getValue(), VecTy); 3328 for (auto *V : VL) { 3329 // If all users of instruction are going to be vectorized and this 3330 // instruction itself is not going to be vectorized, consider this 3331 // instruction as dead and remove its cost from the final cost of the 3332 // vectorized tree. 3333 if (areAllUsersVectorized(cast<Instruction>(V)) && 3334 !ScalarToTreeEntry.count(V)) { 3335 auto *IO = cast<ConstantInt>( 3336 cast<ExtractElementInst>(V)->getIndexOperand()); 3337 Cost -= TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, 3338 IO->getZExtValue()); 3339 } 3340 } 3341 return ReuseShuffleCost + Cost; 3342 } 3343 } 3344 return ReuseShuffleCost + getGatherCost(VL); 3345 } 3346 assert(E->State == TreeEntry::Vectorize && "Unhandled state"); 3347 assert(E->getOpcode() && allSameType(VL) && allSameBlock(VL) && "Invalid VL"); 3348 Instruction *VL0 = E->getMainOp(); 3349 unsigned ShuffleOrOp = 3350 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 3351 switch (ShuffleOrOp) { 3352 case Instruction::PHI: 3353 return 0; 3354 3355 case Instruction::ExtractValue: 3356 case Instruction::ExtractElement: { 3357 if (NeedToShuffleReuses) { 3358 unsigned Idx = 0; 3359 for (unsigned I : E->ReuseShuffleIndices) { 3360 if (ShuffleOrOp == Instruction::ExtractElement) { 3361 auto *IO = cast<ConstantInt>( 3362 cast<ExtractElementInst>(VL[I])->getIndexOperand()); 3363 Idx = IO->getZExtValue(); 3364 ReuseShuffleCost -= TTI->getVectorInstrCost( 3365 Instruction::ExtractElement, VecTy, Idx); 3366 } else { 3367 ReuseShuffleCost -= TTI->getVectorInstrCost( 3368 Instruction::ExtractElement, VecTy, Idx); 3369 ++Idx; 3370 } 3371 } 3372 Idx = ReuseShuffleNumbers; 3373 for (Value *V : VL) { 3374 if (ShuffleOrOp == Instruction::ExtractElement) { 3375 auto *IO = cast<ConstantInt>( 3376 cast<ExtractElementInst>(V)->getIndexOperand()); 3377 Idx = IO->getZExtValue(); 3378 } else { 3379 --Idx; 3380 } 3381 ReuseShuffleCost += 3382 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, Idx); 3383 } 3384 } 3385 int DeadCost = ReuseShuffleCost; 3386 if (!E->ReorderIndices.empty()) { 3387 // TODO: Merge this shuffle with the ReuseShuffleCost. 3388 DeadCost += TTI->getShuffleCost( 3389 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3390 } 3391 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 3392 Instruction *E = cast<Instruction>(VL[i]); 3393 // If all users are going to be vectorized, instruction can be 3394 // considered as dead. 3395 // The same, if have only one user, it will be vectorized for sure. 3396 if (areAllUsersVectorized(E)) { 3397 // Take credit for instruction that will become dead. 3398 if (E->hasOneUse()) { 3399 Instruction *Ext = E->user_back(); 3400 if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) && 3401 all_of(Ext->users(), 3402 [](User *U) { return isa<GetElementPtrInst>(U); })) { 3403 // Use getExtractWithExtendCost() to calculate the cost of 3404 // extractelement/ext pair. 3405 DeadCost -= TTI->getExtractWithExtendCost( 3406 Ext->getOpcode(), Ext->getType(), VecTy, i); 3407 // Add back the cost of s|zext which is subtracted separately. 3408 DeadCost += TTI->getCastInstrCost( 3409 Ext->getOpcode(), Ext->getType(), E->getType(), 3410 TTI::getCastContextHint(Ext), CostKind, Ext); 3411 continue; 3412 } 3413 } 3414 DeadCost -= 3415 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, i); 3416 } 3417 } 3418 return DeadCost; 3419 } 3420 case Instruction::ZExt: 3421 case Instruction::SExt: 3422 case Instruction::FPToUI: 3423 case Instruction::FPToSI: 3424 case Instruction::FPExt: 3425 case Instruction::PtrToInt: 3426 case Instruction::IntToPtr: 3427 case Instruction::SIToFP: 3428 case Instruction::UIToFP: 3429 case Instruction::Trunc: 3430 case Instruction::FPTrunc: 3431 case Instruction::BitCast: { 3432 Type *SrcTy = VL0->getOperand(0)->getType(); 3433 int ScalarEltCost = 3434 TTI->getCastInstrCost(E->getOpcode(), ScalarTy, SrcTy, 3435 TTI::getCastContextHint(VL0), CostKind, VL0); 3436 if (NeedToShuffleReuses) { 3437 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3438 } 3439 3440 // Calculate the cost of this instruction. 3441 int ScalarCost = VL.size() * ScalarEltCost; 3442 3443 auto *SrcVecTy = FixedVectorType::get(SrcTy, VL.size()); 3444 int VecCost = 0; 3445 // Check if the values are candidates to demote. 3446 if (!MinBWs.count(VL0) || VecTy != SrcVecTy) { 3447 VecCost = 3448 ReuseShuffleCost + 3449 TTI->getCastInstrCost(E->getOpcode(), VecTy, SrcVecTy, 3450 TTI::getCastContextHint(VL0), CostKind, VL0); 3451 } 3452 return VecCost - ScalarCost; 3453 } 3454 case Instruction::FCmp: 3455 case Instruction::ICmp: 3456 case Instruction::Select: { 3457 // Calculate the cost of this instruction. 3458 int ScalarEltCost = TTI->getCmpSelInstrCost(E->getOpcode(), ScalarTy, 3459 Builder.getInt1Ty(), 3460 CostKind, VL0); 3461 if (NeedToShuffleReuses) { 3462 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3463 } 3464 auto *MaskTy = FixedVectorType::get(Builder.getInt1Ty(), VL.size()); 3465 int ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3466 int VecCost = TTI->getCmpSelInstrCost(E->getOpcode(), VecTy, MaskTy, 3467 CostKind, VL0); 3468 return ReuseShuffleCost + VecCost - ScalarCost; 3469 } 3470 case Instruction::FNeg: 3471 case Instruction::Add: 3472 case Instruction::FAdd: 3473 case Instruction::Sub: 3474 case Instruction::FSub: 3475 case Instruction::Mul: 3476 case Instruction::FMul: 3477 case Instruction::UDiv: 3478 case Instruction::SDiv: 3479 case Instruction::FDiv: 3480 case Instruction::URem: 3481 case Instruction::SRem: 3482 case Instruction::FRem: 3483 case Instruction::Shl: 3484 case Instruction::LShr: 3485 case Instruction::AShr: 3486 case Instruction::And: 3487 case Instruction::Or: 3488 case Instruction::Xor: { 3489 // Certain instructions can be cheaper to vectorize if they have a 3490 // constant second vector operand. 3491 TargetTransformInfo::OperandValueKind Op1VK = 3492 TargetTransformInfo::OK_AnyValue; 3493 TargetTransformInfo::OperandValueKind Op2VK = 3494 TargetTransformInfo::OK_UniformConstantValue; 3495 TargetTransformInfo::OperandValueProperties Op1VP = 3496 TargetTransformInfo::OP_None; 3497 TargetTransformInfo::OperandValueProperties Op2VP = 3498 TargetTransformInfo::OP_PowerOf2; 3499 3500 // If all operands are exactly the same ConstantInt then set the 3501 // operand kind to OK_UniformConstantValue. 3502 // If instead not all operands are constants, then set the operand kind 3503 // to OK_AnyValue. If all operands are constants but not the same, 3504 // then set the operand kind to OK_NonUniformConstantValue. 3505 ConstantInt *CInt0 = nullptr; 3506 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 3507 const Instruction *I = cast<Instruction>(VL[i]); 3508 unsigned OpIdx = isa<BinaryOperator>(I) ? 1 : 0; 3509 ConstantInt *CInt = dyn_cast<ConstantInt>(I->getOperand(OpIdx)); 3510 if (!CInt) { 3511 Op2VK = TargetTransformInfo::OK_AnyValue; 3512 Op2VP = TargetTransformInfo::OP_None; 3513 break; 3514 } 3515 if (Op2VP == TargetTransformInfo::OP_PowerOf2 && 3516 !CInt->getValue().isPowerOf2()) 3517 Op2VP = TargetTransformInfo::OP_None; 3518 if (i == 0) { 3519 CInt0 = CInt; 3520 continue; 3521 } 3522 if (CInt0 != CInt) 3523 Op2VK = TargetTransformInfo::OK_NonUniformConstantValue; 3524 } 3525 3526 SmallVector<const Value *, 4> Operands(VL0->operand_values()); 3527 int ScalarEltCost = TTI->getArithmeticInstrCost( 3528 E->getOpcode(), ScalarTy, CostKind, Op1VK, Op2VK, Op1VP, Op2VP, 3529 Operands, VL0); 3530 if (NeedToShuffleReuses) { 3531 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3532 } 3533 int ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3534 int VecCost = TTI->getArithmeticInstrCost( 3535 E->getOpcode(), VecTy, CostKind, Op1VK, Op2VK, Op1VP, Op2VP, 3536 Operands, VL0); 3537 return ReuseShuffleCost + VecCost - ScalarCost; 3538 } 3539 case Instruction::GetElementPtr: { 3540 TargetTransformInfo::OperandValueKind Op1VK = 3541 TargetTransformInfo::OK_AnyValue; 3542 TargetTransformInfo::OperandValueKind Op2VK = 3543 TargetTransformInfo::OK_UniformConstantValue; 3544 3545 int ScalarEltCost = 3546 TTI->getArithmeticInstrCost(Instruction::Add, ScalarTy, CostKind, 3547 Op1VK, Op2VK); 3548 if (NeedToShuffleReuses) { 3549 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3550 } 3551 int ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3552 int VecCost = 3553 TTI->getArithmeticInstrCost(Instruction::Add, VecTy, CostKind, 3554 Op1VK, Op2VK); 3555 return ReuseShuffleCost + VecCost - ScalarCost; 3556 } 3557 case Instruction::Load: { 3558 // Cost of wide load - cost of scalar loads. 3559 Align alignment = cast<LoadInst>(VL0)->getAlign(); 3560 int ScalarEltCost = 3561 TTI->getMemoryOpCost(Instruction::Load, ScalarTy, alignment, 0, 3562 CostKind, VL0); 3563 if (NeedToShuffleReuses) { 3564 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3565 } 3566 int ScalarLdCost = VecTy->getNumElements() * ScalarEltCost; 3567 int VecLdCost = 3568 TTI->getMemoryOpCost(Instruction::Load, VecTy, alignment, 0, 3569 CostKind, VL0); 3570 if (!E->ReorderIndices.empty()) { 3571 // TODO: Merge this shuffle with the ReuseShuffleCost. 3572 VecLdCost += TTI->getShuffleCost( 3573 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3574 } 3575 return ReuseShuffleCost + VecLdCost - ScalarLdCost; 3576 } 3577 case Instruction::Store: { 3578 // We know that we can merge the stores. Calculate the cost. 3579 bool IsReorder = !E->ReorderIndices.empty(); 3580 auto *SI = 3581 cast<StoreInst>(IsReorder ? VL[E->ReorderIndices.front()] : VL0); 3582 Align Alignment = SI->getAlign(); 3583 int ScalarEltCost = 3584 TTI->getMemoryOpCost(Instruction::Store, ScalarTy, Alignment, 0, 3585 CostKind, VL0); 3586 if (NeedToShuffleReuses) 3587 ReuseShuffleCost = -(ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3588 int ScalarStCost = VecTy->getNumElements() * ScalarEltCost; 3589 int VecStCost = TTI->getMemoryOpCost(Instruction::Store, 3590 VecTy, Alignment, 0, CostKind, VL0); 3591 if (IsReorder) { 3592 // TODO: Merge this shuffle with the ReuseShuffleCost. 3593 VecStCost += TTI->getShuffleCost( 3594 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3595 } 3596 return ReuseShuffleCost + VecStCost - ScalarStCost; 3597 } 3598 case Instruction::Call: { 3599 CallInst *CI = cast<CallInst>(VL0); 3600 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3601 3602 // Calculate the cost of the scalar and vector calls. 3603 IntrinsicCostAttributes CostAttrs(ID, *CI, 1, 1); 3604 int ScalarEltCost = TTI->getIntrinsicInstrCost(CostAttrs, CostKind); 3605 if (NeedToShuffleReuses) { 3606 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3607 } 3608 int ScalarCallCost = VecTy->getNumElements() * ScalarEltCost; 3609 3610 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 3611 int VecCallCost = std::min(VecCallCosts.first, VecCallCosts.second); 3612 3613 LLVM_DEBUG(dbgs() << "SLP: Call cost " << VecCallCost - ScalarCallCost 3614 << " (" << VecCallCost << "-" << ScalarCallCost << ")" 3615 << " for " << *CI << "\n"); 3616 3617 return ReuseShuffleCost + VecCallCost - ScalarCallCost; 3618 } 3619 case Instruction::ShuffleVector: { 3620 assert(E->isAltShuffle() && 3621 ((Instruction::isBinaryOp(E->getOpcode()) && 3622 Instruction::isBinaryOp(E->getAltOpcode())) || 3623 (Instruction::isCast(E->getOpcode()) && 3624 Instruction::isCast(E->getAltOpcode()))) && 3625 "Invalid Shuffle Vector Operand"); 3626 int ScalarCost = 0; 3627 if (NeedToShuffleReuses) { 3628 for (unsigned Idx : E->ReuseShuffleIndices) { 3629 Instruction *I = cast<Instruction>(VL[Idx]); 3630 ReuseShuffleCost -= TTI->getInstructionCost(I, CostKind); 3631 } 3632 for (Value *V : VL) { 3633 Instruction *I = cast<Instruction>(V); 3634 ReuseShuffleCost += TTI->getInstructionCost(I, CostKind); 3635 } 3636 } 3637 for (Value *V : VL) { 3638 Instruction *I = cast<Instruction>(V); 3639 assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode"); 3640 ScalarCost += TTI->getInstructionCost(I, CostKind); 3641 } 3642 // VecCost is equal to sum of the cost of creating 2 vectors 3643 // and the cost of creating shuffle. 3644 int VecCost = 0; 3645 if (Instruction::isBinaryOp(E->getOpcode())) { 3646 VecCost = TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind); 3647 VecCost += TTI->getArithmeticInstrCost(E->getAltOpcode(), VecTy, 3648 CostKind); 3649 } else { 3650 Type *Src0SclTy = E->getMainOp()->getOperand(0)->getType(); 3651 Type *Src1SclTy = E->getAltOp()->getOperand(0)->getType(); 3652 auto *Src0Ty = FixedVectorType::get(Src0SclTy, VL.size()); 3653 auto *Src1Ty = FixedVectorType::get(Src1SclTy, VL.size()); 3654 VecCost = TTI->getCastInstrCost(E->getOpcode(), VecTy, Src0Ty, 3655 TTI::CastContextHint::None, CostKind); 3656 VecCost += TTI->getCastInstrCost(E->getAltOpcode(), VecTy, Src1Ty, 3657 TTI::CastContextHint::None, CostKind); 3658 } 3659 VecCost += TTI->getShuffleCost(TargetTransformInfo::SK_Select, VecTy, 0); 3660 return ReuseShuffleCost + VecCost - ScalarCost; 3661 } 3662 default: 3663 llvm_unreachable("Unknown instruction"); 3664 } 3665 } 3666 3667 bool BoUpSLP::isFullyVectorizableTinyTree() const { 3668 LLVM_DEBUG(dbgs() << "SLP: Check whether the tree with height " 3669 << VectorizableTree.size() << " is fully vectorizable .\n"); 3670 3671 // We only handle trees of heights 1 and 2. 3672 if (VectorizableTree.size() == 1 && 3673 VectorizableTree[0]->State == TreeEntry::Vectorize) 3674 return true; 3675 3676 if (VectorizableTree.size() != 2) 3677 return false; 3678 3679 // Handle splat and all-constants stores. 3680 if (VectorizableTree[0]->State == TreeEntry::Vectorize && 3681 (allConstant(VectorizableTree[1]->Scalars) || 3682 isSplat(VectorizableTree[1]->Scalars))) 3683 return true; 3684 3685 // Gathering cost would be too much for tiny trees. 3686 if (VectorizableTree[0]->State == TreeEntry::NeedToGather || 3687 VectorizableTree[1]->State == TreeEntry::NeedToGather) 3688 return false; 3689 3690 return true; 3691 } 3692 3693 static bool isLoadCombineCandidateImpl(Value *Root, unsigned NumElts, 3694 TargetTransformInfo *TTI) { 3695 // Look past the root to find a source value. Arbitrarily follow the 3696 // path through operand 0 of any 'or'. Also, peek through optional 3697 // shift-left-by-constant. 3698 Value *ZextLoad = Root; 3699 while (!isa<ConstantExpr>(ZextLoad) && 3700 (match(ZextLoad, m_Or(m_Value(), m_Value())) || 3701 match(ZextLoad, m_Shl(m_Value(), m_Constant())))) 3702 ZextLoad = cast<BinaryOperator>(ZextLoad)->getOperand(0); 3703 3704 // Check if the input is an extended load of the required or/shift expression. 3705 Value *LoadPtr; 3706 if (ZextLoad == Root || !match(ZextLoad, m_ZExt(m_Load(m_Value(LoadPtr))))) 3707 return false; 3708 3709 // Require that the total load bit width is a legal integer type. 3710 // For example, <8 x i8> --> i64 is a legal integer on a 64-bit target. 3711 // But <16 x i8> --> i128 is not, so the backend probably can't reduce it. 3712 Type *SrcTy = LoadPtr->getType()->getPointerElementType(); 3713 unsigned LoadBitWidth = SrcTy->getIntegerBitWidth() * NumElts; 3714 if (!TTI->isTypeLegal(IntegerType::get(Root->getContext(), LoadBitWidth))) 3715 return false; 3716 3717 // Everything matched - assume that we can fold the whole sequence using 3718 // load combining. 3719 LLVM_DEBUG(dbgs() << "SLP: Assume load combining for tree starting at " 3720 << *(cast<Instruction>(Root)) << "\n"); 3721 3722 return true; 3723 } 3724 3725 bool BoUpSLP::isLoadCombineReductionCandidate(unsigned RdxOpcode) const { 3726 if (RdxOpcode != Instruction::Or) 3727 return false; 3728 3729 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 3730 Value *FirstReduced = VectorizableTree[0]->Scalars[0]; 3731 return isLoadCombineCandidateImpl(FirstReduced, NumElts, TTI); 3732 } 3733 3734 bool BoUpSLP::isLoadCombineCandidate() const { 3735 // Peek through a final sequence of stores and check if all operations are 3736 // likely to be load-combined. 3737 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 3738 for (Value *Scalar : VectorizableTree[0]->Scalars) { 3739 Value *X; 3740 if (!match(Scalar, m_Store(m_Value(X), m_Value())) || 3741 !isLoadCombineCandidateImpl(X, NumElts, TTI)) 3742 return false; 3743 } 3744 return true; 3745 } 3746 3747 bool BoUpSLP::isTreeTinyAndNotFullyVectorizable() const { 3748 // We can vectorize the tree if its size is greater than or equal to the 3749 // minimum size specified by the MinTreeSize command line option. 3750 if (VectorizableTree.size() >= MinTreeSize) 3751 return false; 3752 3753 // If we have a tiny tree (a tree whose size is less than MinTreeSize), we 3754 // can vectorize it if we can prove it fully vectorizable. 3755 if (isFullyVectorizableTinyTree()) 3756 return false; 3757 3758 assert(VectorizableTree.empty() 3759 ? ExternalUses.empty() 3760 : true && "We shouldn't have any external users"); 3761 3762 // Otherwise, we can't vectorize the tree. It is both tiny and not fully 3763 // vectorizable. 3764 return true; 3765 } 3766 3767 int BoUpSLP::getSpillCost() const { 3768 // Walk from the bottom of the tree to the top, tracking which values are 3769 // live. When we see a call instruction that is not part of our tree, 3770 // query TTI to see if there is a cost to keeping values live over it 3771 // (for example, if spills and fills are required). 3772 unsigned BundleWidth = VectorizableTree.front()->Scalars.size(); 3773 int Cost = 0; 3774 3775 SmallPtrSet<Instruction*, 4> LiveValues; 3776 Instruction *PrevInst = nullptr; 3777 3778 // The entries in VectorizableTree are not necessarily ordered by their 3779 // position in basic blocks. Collect them and order them by dominance so later 3780 // instructions are guaranteed to be visited first. For instructions in 3781 // different basic blocks, we only scan to the beginning of the block, so 3782 // their order does not matter, as long as all instructions in a basic block 3783 // are grouped together. Using dominance ensures a deterministic order. 3784 SmallVector<Instruction *, 16> OrderedScalars; 3785 for (const auto &TEPtr : VectorizableTree) { 3786 Instruction *Inst = dyn_cast<Instruction>(TEPtr->Scalars[0]); 3787 if (!Inst) 3788 continue; 3789 OrderedScalars.push_back(Inst); 3790 } 3791 llvm::stable_sort(OrderedScalars, [this](Instruction *A, Instruction *B) { 3792 return DT->dominates(B, A); 3793 }); 3794 3795 for (Instruction *Inst : OrderedScalars) { 3796 if (!PrevInst) { 3797 PrevInst = Inst; 3798 continue; 3799 } 3800 3801 // Update LiveValues. 3802 LiveValues.erase(PrevInst); 3803 for (auto &J : PrevInst->operands()) { 3804 if (isa<Instruction>(&*J) && getTreeEntry(&*J)) 3805 LiveValues.insert(cast<Instruction>(&*J)); 3806 } 3807 3808 LLVM_DEBUG({ 3809 dbgs() << "SLP: #LV: " << LiveValues.size(); 3810 for (auto *X : LiveValues) 3811 dbgs() << " " << X->getName(); 3812 dbgs() << ", Looking at "; 3813 Inst->dump(); 3814 }); 3815 3816 // Now find the sequence of instructions between PrevInst and Inst. 3817 unsigned NumCalls = 0; 3818 BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(), 3819 PrevInstIt = 3820 PrevInst->getIterator().getReverse(); 3821 while (InstIt != PrevInstIt) { 3822 if (PrevInstIt == PrevInst->getParent()->rend()) { 3823 PrevInstIt = Inst->getParent()->rbegin(); 3824 continue; 3825 } 3826 3827 // Debug information does not impact spill cost. 3828 if ((isa<CallInst>(&*PrevInstIt) && 3829 !isa<DbgInfoIntrinsic>(&*PrevInstIt)) && 3830 &*PrevInstIt != PrevInst) 3831 NumCalls++; 3832 3833 ++PrevInstIt; 3834 } 3835 3836 if (NumCalls) { 3837 SmallVector<Type*, 4> V; 3838 for (auto *II : LiveValues) 3839 V.push_back(FixedVectorType::get(II->getType(), BundleWidth)); 3840 Cost += NumCalls * TTI->getCostOfKeepingLiveOverCall(V); 3841 } 3842 3843 PrevInst = Inst; 3844 } 3845 3846 return Cost; 3847 } 3848 3849 int BoUpSLP::getTreeCost() { 3850 int Cost = 0; 3851 LLVM_DEBUG(dbgs() << "SLP: Calculating cost for tree of size " 3852 << VectorizableTree.size() << ".\n"); 3853 3854 unsigned BundleWidth = VectorizableTree[0]->Scalars.size(); 3855 3856 for (unsigned I = 0, E = VectorizableTree.size(); I < E; ++I) { 3857 TreeEntry &TE = *VectorizableTree[I].get(); 3858 3859 // We create duplicate tree entries for gather sequences that have multiple 3860 // uses. However, we should not compute the cost of duplicate sequences. 3861 // For example, if we have a build vector (i.e., insertelement sequence) 3862 // that is used by more than one vector instruction, we only need to 3863 // compute the cost of the insertelement instructions once. The redundant 3864 // instructions will be eliminated by CSE. 3865 // 3866 // We should consider not creating duplicate tree entries for gather 3867 // sequences, and instead add additional edges to the tree representing 3868 // their uses. Since such an approach results in fewer total entries, 3869 // existing heuristics based on tree size may yield different results. 3870 // 3871 if (TE.State == TreeEntry::NeedToGather && 3872 std::any_of(std::next(VectorizableTree.begin(), I + 1), 3873 VectorizableTree.end(), 3874 [TE](const std::unique_ptr<TreeEntry> &EntryPtr) { 3875 return EntryPtr->State == TreeEntry::NeedToGather && 3876 EntryPtr->isSame(TE.Scalars); 3877 })) 3878 continue; 3879 3880 int C = getEntryCost(&TE); 3881 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C 3882 << " for bundle that starts with " << *TE.Scalars[0] 3883 << ".\n"); 3884 Cost += C; 3885 } 3886 3887 SmallPtrSet<Value *, 16> ExtractCostCalculated; 3888 int ExtractCost = 0; 3889 for (ExternalUser &EU : ExternalUses) { 3890 // We only add extract cost once for the same scalar. 3891 if (!ExtractCostCalculated.insert(EU.Scalar).second) 3892 continue; 3893 3894 // Uses by ephemeral values are free (because the ephemeral value will be 3895 // removed prior to code generation, and so the extraction will be 3896 // removed as well). 3897 if (EphValues.count(EU.User)) 3898 continue; 3899 3900 // If we plan to rewrite the tree in a smaller type, we will need to sign 3901 // extend the extracted value back to the original type. Here, we account 3902 // for the extract and the added cost of the sign extend if needed. 3903 auto *VecTy = FixedVectorType::get(EU.Scalar->getType(), BundleWidth); 3904 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 3905 if (MinBWs.count(ScalarRoot)) { 3906 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 3907 auto Extend = 3908 MinBWs[ScalarRoot].second ? Instruction::SExt : Instruction::ZExt; 3909 VecTy = FixedVectorType::get(MinTy, BundleWidth); 3910 ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(), 3911 VecTy, EU.Lane); 3912 } else { 3913 ExtractCost += 3914 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, EU.Lane); 3915 } 3916 } 3917 3918 int SpillCost = getSpillCost(); 3919 Cost += SpillCost + ExtractCost; 3920 3921 #ifndef NDEBUG 3922 SmallString<256> Str; 3923 { 3924 raw_svector_ostream OS(Str); 3925 OS << "SLP: Spill Cost = " << SpillCost << ".\n" 3926 << "SLP: Extract Cost = " << ExtractCost << ".\n" 3927 << "SLP: Total Cost = " << Cost << ".\n"; 3928 } 3929 LLVM_DEBUG(dbgs() << Str); 3930 if (ViewSLPTree) 3931 ViewGraph(this, "SLP" + F->getName(), false, Str); 3932 #endif 3933 3934 return Cost; 3935 } 3936 3937 int BoUpSLP::getGatherCost(FixedVectorType *Ty, 3938 const DenseSet<unsigned> &ShuffledIndices) const { 3939 unsigned NumElts = Ty->getNumElements(); 3940 APInt DemandedElts = APInt::getNullValue(NumElts); 3941 for (unsigned i = 0; i < NumElts; ++i) 3942 if (!ShuffledIndices.count(i)) 3943 DemandedElts.setBit(i); 3944 int Cost = TTI->getScalarizationOverhead(Ty, DemandedElts, /*Insert*/ true, 3945 /*Extract*/ false); 3946 if (!ShuffledIndices.empty()) 3947 Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, Ty); 3948 return Cost; 3949 } 3950 3951 int BoUpSLP::getGatherCost(ArrayRef<Value *> VL) const { 3952 // Find the type of the operands in VL. 3953 Type *ScalarTy = VL[0]->getType(); 3954 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 3955 ScalarTy = SI->getValueOperand()->getType(); 3956 auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); 3957 // Find the cost of inserting/extracting values from the vector. 3958 // Check if the same elements are inserted several times and count them as 3959 // shuffle candidates. 3960 DenseSet<unsigned> ShuffledElements; 3961 DenseSet<Value *> UniqueElements; 3962 // Iterate in reverse order to consider insert elements with the high cost. 3963 for (unsigned I = VL.size(); I > 0; --I) { 3964 unsigned Idx = I - 1; 3965 if (!UniqueElements.insert(VL[Idx]).second) 3966 ShuffledElements.insert(Idx); 3967 } 3968 return getGatherCost(VecTy, ShuffledElements); 3969 } 3970 3971 // Perform operand reordering on the instructions in VL and return the reordered 3972 // operands in Left and Right. 3973 void BoUpSLP::reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 3974 SmallVectorImpl<Value *> &Left, 3975 SmallVectorImpl<Value *> &Right, 3976 const DataLayout &DL, 3977 ScalarEvolution &SE, 3978 const BoUpSLP &R) { 3979 if (VL.empty()) 3980 return; 3981 VLOperands Ops(VL, DL, SE, R); 3982 // Reorder the operands in place. 3983 Ops.reorder(); 3984 Left = Ops.getVL(0); 3985 Right = Ops.getVL(1); 3986 } 3987 3988 void BoUpSLP::setInsertPointAfterBundle(TreeEntry *E) { 3989 // Get the basic block this bundle is in. All instructions in the bundle 3990 // should be in this block. 3991 auto *Front = E->getMainOp(); 3992 auto *BB = Front->getParent(); 3993 assert(llvm::all_of(make_range(E->Scalars.begin(), E->Scalars.end()), 3994 [=](Value *V) -> bool { 3995 auto *I = cast<Instruction>(V); 3996 return !E->isOpcodeOrAlt(I) || I->getParent() == BB; 3997 })); 3998 3999 // The last instruction in the bundle in program order. 4000 Instruction *LastInst = nullptr; 4001 4002 // Find the last instruction. The common case should be that BB has been 4003 // scheduled, and the last instruction is VL.back(). So we start with 4004 // VL.back() and iterate over schedule data until we reach the end of the 4005 // bundle. The end of the bundle is marked by null ScheduleData. 4006 if (BlocksSchedules.count(BB)) { 4007 auto *Bundle = 4008 BlocksSchedules[BB]->getScheduleData(E->isOneOf(E->Scalars.back())); 4009 if (Bundle && Bundle->isPartOfBundle()) 4010 for (; Bundle; Bundle = Bundle->NextInBundle) 4011 if (Bundle->OpValue == Bundle->Inst) 4012 LastInst = Bundle->Inst; 4013 } 4014 4015 // LastInst can still be null at this point if there's either not an entry 4016 // for BB in BlocksSchedules or there's no ScheduleData available for 4017 // VL.back(). This can be the case if buildTree_rec aborts for various 4018 // reasons (e.g., the maximum recursion depth is reached, the maximum region 4019 // size is reached, etc.). ScheduleData is initialized in the scheduling 4020 // "dry-run". 4021 // 4022 // If this happens, we can still find the last instruction by brute force. We 4023 // iterate forwards from Front (inclusive) until we either see all 4024 // instructions in the bundle or reach the end of the block. If Front is the 4025 // last instruction in program order, LastInst will be set to Front, and we 4026 // will visit all the remaining instructions in the block. 4027 // 4028 // One of the reasons we exit early from buildTree_rec is to place an upper 4029 // bound on compile-time. Thus, taking an additional compile-time hit here is 4030 // not ideal. However, this should be exceedingly rare since it requires that 4031 // we both exit early from buildTree_rec and that the bundle be out-of-order 4032 // (causing us to iterate all the way to the end of the block). 4033 if (!LastInst) { 4034 SmallPtrSet<Value *, 16> Bundle(E->Scalars.begin(), E->Scalars.end()); 4035 for (auto &I : make_range(BasicBlock::iterator(Front), BB->end())) { 4036 if (Bundle.erase(&I) && E->isOpcodeOrAlt(&I)) 4037 LastInst = &I; 4038 if (Bundle.empty()) 4039 break; 4040 } 4041 } 4042 assert(LastInst && "Failed to find last instruction in bundle"); 4043 4044 // Set the insertion point after the last instruction in the bundle. Set the 4045 // debug location to Front. 4046 Builder.SetInsertPoint(BB, ++LastInst->getIterator()); 4047 Builder.SetCurrentDebugLocation(Front->getDebugLoc()); 4048 } 4049 4050 Value *BoUpSLP::Gather(ArrayRef<Value *> VL, FixedVectorType *Ty) { 4051 Value *Vec = UndefValue::get(Ty); 4052 // Generate the 'InsertElement' instruction. 4053 for (unsigned i = 0; i < Ty->getNumElements(); ++i) { 4054 Vec = Builder.CreateInsertElement(Vec, VL[i], Builder.getInt32(i)); 4055 if (auto *Insrt = dyn_cast<InsertElementInst>(Vec)) { 4056 GatherSeq.insert(Insrt); 4057 CSEBlocks.insert(Insrt->getParent()); 4058 4059 // Add to our 'need-to-extract' list. 4060 if (TreeEntry *E = getTreeEntry(VL[i])) { 4061 // Find which lane we need to extract. 4062 int FoundLane = -1; 4063 for (unsigned Lane = 0, LE = E->Scalars.size(); Lane != LE; ++Lane) { 4064 // Is this the lane of the scalar that we are looking for ? 4065 if (E->Scalars[Lane] == VL[i]) { 4066 FoundLane = Lane; 4067 break; 4068 } 4069 } 4070 assert(FoundLane >= 0 && "Could not find the correct lane"); 4071 if (!E->ReuseShuffleIndices.empty()) { 4072 FoundLane = 4073 std::distance(E->ReuseShuffleIndices.begin(), 4074 llvm::find(E->ReuseShuffleIndices, FoundLane)); 4075 } 4076 ExternalUses.push_back(ExternalUser(VL[i], Insrt, FoundLane)); 4077 } 4078 } 4079 } 4080 4081 return Vec; 4082 } 4083 4084 Value *BoUpSLP::vectorizeTree(ArrayRef<Value *> VL) { 4085 InstructionsState S = getSameOpcode(VL); 4086 if (S.getOpcode()) { 4087 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 4088 if (E->isSame(VL)) { 4089 Value *V = vectorizeTree(E); 4090 if (VL.size() == E->Scalars.size() && !E->ReuseShuffleIndices.empty()) { 4091 // We need to get the vectorized value but without shuffle. 4092 if (auto *SV = dyn_cast<ShuffleVectorInst>(V)) { 4093 V = SV->getOperand(0); 4094 } else { 4095 // Reshuffle to get only unique values. 4096 SmallVector<int, 4> UniqueIdxs; 4097 SmallSet<int, 4> UsedIdxs; 4098 for (int Idx : E->ReuseShuffleIndices) 4099 if (UsedIdxs.insert(Idx).second) 4100 UniqueIdxs.emplace_back(Idx); 4101 V = Builder.CreateShuffleVector(V, UndefValue::get(V->getType()), 4102 UniqueIdxs); 4103 } 4104 } 4105 return V; 4106 } 4107 } 4108 } 4109 4110 Type *ScalarTy = S.OpValue->getType(); 4111 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) 4112 ScalarTy = SI->getValueOperand()->getType(); 4113 4114 // Check that every instruction appears once in this bundle. 4115 SmallVector<int, 4> ReuseShuffleIndicies; 4116 SmallVector<Value *, 4> UniqueValues; 4117 if (VL.size() > 2) { 4118 DenseMap<Value *, unsigned> UniquePositions; 4119 for (Value *V : VL) { 4120 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 4121 ReuseShuffleIndicies.emplace_back(Res.first->second); 4122 if (Res.second || isa<Constant>(V)) 4123 UniqueValues.emplace_back(V); 4124 } 4125 // Do not shuffle single element or if number of unique values is not power 4126 // of 2. 4127 if (UniqueValues.size() == VL.size() || UniqueValues.size() <= 1 || 4128 !llvm::isPowerOf2_32(UniqueValues.size())) 4129 ReuseShuffleIndicies.clear(); 4130 else 4131 VL = UniqueValues; 4132 } 4133 auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); 4134 4135 Value *V = Gather(VL, VecTy); 4136 if (!ReuseShuffleIndicies.empty()) { 4137 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4138 ReuseShuffleIndicies, "shuffle"); 4139 if (auto *I = dyn_cast<Instruction>(V)) { 4140 GatherSeq.insert(I); 4141 CSEBlocks.insert(I->getParent()); 4142 } 4143 } 4144 return V; 4145 } 4146 4147 static void inversePermutation(ArrayRef<unsigned> Indices, 4148 SmallVectorImpl<int> &Mask) { 4149 Mask.clear(); 4150 const unsigned E = Indices.size(); 4151 Mask.resize(E); 4152 for (unsigned I = 0; I < E; ++I) 4153 Mask[Indices[I]] = I; 4154 } 4155 4156 Value *BoUpSLP::vectorizeTree(TreeEntry *E) { 4157 IRBuilder<>::InsertPointGuard Guard(Builder); 4158 4159 if (E->VectorizedValue) { 4160 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *E->Scalars[0] << ".\n"); 4161 return E->VectorizedValue; 4162 } 4163 4164 Instruction *VL0 = E->getMainOp(); 4165 Type *ScalarTy = VL0->getType(); 4166 if (StoreInst *SI = dyn_cast<StoreInst>(VL0)) 4167 ScalarTy = SI->getValueOperand()->getType(); 4168 auto *VecTy = FixedVectorType::get(ScalarTy, E->Scalars.size()); 4169 4170 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 4171 4172 if (E->State == TreeEntry::NeedToGather) { 4173 setInsertPointAfterBundle(E); 4174 auto *V = Gather(E->Scalars, VecTy); 4175 if (NeedToShuffleReuses) { 4176 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4177 E->ReuseShuffleIndices, "shuffle"); 4178 if (auto *I = dyn_cast<Instruction>(V)) { 4179 GatherSeq.insert(I); 4180 CSEBlocks.insert(I->getParent()); 4181 } 4182 } 4183 E->VectorizedValue = V; 4184 return V; 4185 } 4186 4187 assert(E->State == TreeEntry::Vectorize && "Unhandled state"); 4188 unsigned ShuffleOrOp = 4189 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 4190 switch (ShuffleOrOp) { 4191 case Instruction::PHI: { 4192 auto *PH = cast<PHINode>(VL0); 4193 Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI()); 4194 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 4195 PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues()); 4196 Value *V = NewPhi; 4197 if (NeedToShuffleReuses) { 4198 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4199 E->ReuseShuffleIndices, "shuffle"); 4200 } 4201 E->VectorizedValue = V; 4202 4203 // PHINodes may have multiple entries from the same block. We want to 4204 // visit every block once. 4205 SmallPtrSet<BasicBlock*, 4> VisitedBBs; 4206 4207 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 4208 ValueList Operands; 4209 BasicBlock *IBB = PH->getIncomingBlock(i); 4210 4211 if (!VisitedBBs.insert(IBB).second) { 4212 NewPhi->addIncoming(NewPhi->getIncomingValueForBlock(IBB), IBB); 4213 continue; 4214 } 4215 4216 Builder.SetInsertPoint(IBB->getTerminator()); 4217 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 4218 Value *Vec = vectorizeTree(E->getOperand(i)); 4219 NewPhi->addIncoming(Vec, IBB); 4220 } 4221 4222 assert(NewPhi->getNumIncomingValues() == PH->getNumIncomingValues() && 4223 "Invalid number of incoming values"); 4224 return V; 4225 } 4226 4227 case Instruction::ExtractElement: { 4228 Value *V = E->getSingleOperand(0); 4229 if (!E->ReorderIndices.empty()) { 4230 SmallVector<int, 4> Mask; 4231 inversePermutation(E->ReorderIndices, Mask); 4232 Builder.SetInsertPoint(VL0); 4233 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), Mask, 4234 "reorder_shuffle"); 4235 } 4236 if (NeedToShuffleReuses) { 4237 // TODO: Merge this shuffle with the ReorderShuffleMask. 4238 if (E->ReorderIndices.empty()) 4239 Builder.SetInsertPoint(VL0); 4240 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4241 E->ReuseShuffleIndices, "shuffle"); 4242 } 4243 E->VectorizedValue = V; 4244 return V; 4245 } 4246 case Instruction::ExtractValue: { 4247 LoadInst *LI = cast<LoadInst>(E->getSingleOperand(0)); 4248 Builder.SetInsertPoint(LI); 4249 PointerType *PtrTy = 4250 PointerType::get(VecTy, LI->getPointerAddressSpace()); 4251 Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy); 4252 LoadInst *V = Builder.CreateAlignedLoad(VecTy, Ptr, LI->getAlign()); 4253 Value *NewV = propagateMetadata(V, E->Scalars); 4254 if (!E->ReorderIndices.empty()) { 4255 SmallVector<int, 4> Mask; 4256 inversePermutation(E->ReorderIndices, Mask); 4257 NewV = Builder.CreateShuffleVector(NewV, UndefValue::get(VecTy), Mask, 4258 "reorder_shuffle"); 4259 } 4260 if (NeedToShuffleReuses) { 4261 // TODO: Merge this shuffle with the ReorderShuffleMask. 4262 NewV = Builder.CreateShuffleVector(NewV, UndefValue::get(VecTy), 4263 E->ReuseShuffleIndices, "shuffle"); 4264 } 4265 E->VectorizedValue = NewV; 4266 return NewV; 4267 } 4268 case Instruction::ZExt: 4269 case Instruction::SExt: 4270 case Instruction::FPToUI: 4271 case Instruction::FPToSI: 4272 case Instruction::FPExt: 4273 case Instruction::PtrToInt: 4274 case Instruction::IntToPtr: 4275 case Instruction::SIToFP: 4276 case Instruction::UIToFP: 4277 case Instruction::Trunc: 4278 case Instruction::FPTrunc: 4279 case Instruction::BitCast: { 4280 setInsertPointAfterBundle(E); 4281 4282 Value *InVec = vectorizeTree(E->getOperand(0)); 4283 4284 if (E->VectorizedValue) { 4285 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4286 return E->VectorizedValue; 4287 } 4288 4289 auto *CI = cast<CastInst>(VL0); 4290 Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy); 4291 if (NeedToShuffleReuses) { 4292 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4293 E->ReuseShuffleIndices, "shuffle"); 4294 } 4295 E->VectorizedValue = V; 4296 ++NumVectorInstructions; 4297 return V; 4298 } 4299 case Instruction::FCmp: 4300 case Instruction::ICmp: { 4301 setInsertPointAfterBundle(E); 4302 4303 Value *L = vectorizeTree(E->getOperand(0)); 4304 Value *R = vectorizeTree(E->getOperand(1)); 4305 4306 if (E->VectorizedValue) { 4307 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4308 return E->VectorizedValue; 4309 } 4310 4311 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 4312 Value *V = Builder.CreateCmp(P0, L, R); 4313 propagateIRFlags(V, E->Scalars, VL0); 4314 if (NeedToShuffleReuses) { 4315 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4316 E->ReuseShuffleIndices, "shuffle"); 4317 } 4318 E->VectorizedValue = V; 4319 ++NumVectorInstructions; 4320 return V; 4321 } 4322 case Instruction::Select: { 4323 setInsertPointAfterBundle(E); 4324 4325 Value *Cond = vectorizeTree(E->getOperand(0)); 4326 Value *True = vectorizeTree(E->getOperand(1)); 4327 Value *False = vectorizeTree(E->getOperand(2)); 4328 4329 if (E->VectorizedValue) { 4330 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4331 return E->VectorizedValue; 4332 } 4333 4334 Value *V = Builder.CreateSelect(Cond, True, False); 4335 if (NeedToShuffleReuses) { 4336 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4337 E->ReuseShuffleIndices, "shuffle"); 4338 } 4339 E->VectorizedValue = V; 4340 ++NumVectorInstructions; 4341 return V; 4342 } 4343 case Instruction::FNeg: { 4344 setInsertPointAfterBundle(E); 4345 4346 Value *Op = vectorizeTree(E->getOperand(0)); 4347 4348 if (E->VectorizedValue) { 4349 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4350 return E->VectorizedValue; 4351 } 4352 4353 Value *V = Builder.CreateUnOp( 4354 static_cast<Instruction::UnaryOps>(E->getOpcode()), Op); 4355 propagateIRFlags(V, E->Scalars, VL0); 4356 if (auto *I = dyn_cast<Instruction>(V)) 4357 V = propagateMetadata(I, E->Scalars); 4358 4359 if (NeedToShuffleReuses) { 4360 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4361 E->ReuseShuffleIndices, "shuffle"); 4362 } 4363 E->VectorizedValue = V; 4364 ++NumVectorInstructions; 4365 4366 return V; 4367 } 4368 case Instruction::Add: 4369 case Instruction::FAdd: 4370 case Instruction::Sub: 4371 case Instruction::FSub: 4372 case Instruction::Mul: 4373 case Instruction::FMul: 4374 case Instruction::UDiv: 4375 case Instruction::SDiv: 4376 case Instruction::FDiv: 4377 case Instruction::URem: 4378 case Instruction::SRem: 4379 case Instruction::FRem: 4380 case Instruction::Shl: 4381 case Instruction::LShr: 4382 case Instruction::AShr: 4383 case Instruction::And: 4384 case Instruction::Or: 4385 case Instruction::Xor: { 4386 setInsertPointAfterBundle(E); 4387 4388 Value *LHS = vectorizeTree(E->getOperand(0)); 4389 Value *RHS = vectorizeTree(E->getOperand(1)); 4390 4391 if (E->VectorizedValue) { 4392 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4393 return E->VectorizedValue; 4394 } 4395 4396 Value *V = Builder.CreateBinOp( 4397 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, 4398 RHS); 4399 propagateIRFlags(V, E->Scalars, VL0); 4400 if (auto *I = dyn_cast<Instruction>(V)) 4401 V = propagateMetadata(I, E->Scalars); 4402 4403 if (NeedToShuffleReuses) { 4404 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4405 E->ReuseShuffleIndices, "shuffle"); 4406 } 4407 E->VectorizedValue = V; 4408 ++NumVectorInstructions; 4409 4410 return V; 4411 } 4412 case Instruction::Load: { 4413 // Loads are inserted at the head of the tree because we don't want to 4414 // sink them all the way down past store instructions. 4415 bool IsReorder = E->updateStateIfReorder(); 4416 if (IsReorder) 4417 VL0 = E->getMainOp(); 4418 setInsertPointAfterBundle(E); 4419 4420 LoadInst *LI = cast<LoadInst>(VL0); 4421 unsigned AS = LI->getPointerAddressSpace(); 4422 4423 Value *VecPtr = Builder.CreateBitCast(LI->getPointerOperand(), 4424 VecTy->getPointerTo(AS)); 4425 4426 // The pointer operand uses an in-tree scalar so we add the new BitCast to 4427 // ExternalUses list to make sure that an extract will be generated in the 4428 // future. 4429 Value *PO = LI->getPointerOperand(); 4430 if (getTreeEntry(PO)) 4431 ExternalUses.push_back(ExternalUser(PO, cast<User>(VecPtr), 0)); 4432 4433 LI = Builder.CreateAlignedLoad(VecTy, VecPtr, LI->getAlign()); 4434 Value *V = propagateMetadata(LI, E->Scalars); 4435 if (IsReorder) { 4436 SmallVector<int, 4> Mask; 4437 inversePermutation(E->ReorderIndices, Mask); 4438 V = Builder.CreateShuffleVector(V, UndefValue::get(V->getType()), 4439 Mask, "reorder_shuffle"); 4440 } 4441 if (NeedToShuffleReuses) { 4442 // TODO: Merge this shuffle with the ReorderShuffleMask. 4443 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4444 E->ReuseShuffleIndices, "shuffle"); 4445 } 4446 E->VectorizedValue = V; 4447 ++NumVectorInstructions; 4448 return V; 4449 } 4450 case Instruction::Store: { 4451 bool IsReorder = !E->ReorderIndices.empty(); 4452 auto *SI = cast<StoreInst>( 4453 IsReorder ? E->Scalars[E->ReorderIndices.front()] : VL0); 4454 unsigned AS = SI->getPointerAddressSpace(); 4455 4456 setInsertPointAfterBundle(E); 4457 4458 Value *VecValue = vectorizeTree(E->getOperand(0)); 4459 if (IsReorder) { 4460 SmallVector<int, 4> Mask(E->ReorderIndices.begin(), 4461 E->ReorderIndices.end()); 4462 VecValue = Builder.CreateShuffleVector( 4463 VecValue, UndefValue::get(VecValue->getType()), Mask, 4464 "reorder_shuffle"); 4465 } 4466 Value *ScalarPtr = SI->getPointerOperand(); 4467 Value *VecPtr = Builder.CreateBitCast( 4468 ScalarPtr, VecValue->getType()->getPointerTo(AS)); 4469 StoreInst *ST = Builder.CreateAlignedStore(VecValue, VecPtr, 4470 SI->getAlign()); 4471 4472 // The pointer operand uses an in-tree scalar, so add the new BitCast to 4473 // ExternalUses to make sure that an extract will be generated in the 4474 // future. 4475 if (getTreeEntry(ScalarPtr)) 4476 ExternalUses.push_back(ExternalUser(ScalarPtr, cast<User>(VecPtr), 0)); 4477 4478 Value *V = propagateMetadata(ST, E->Scalars); 4479 if (NeedToShuffleReuses) { 4480 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4481 E->ReuseShuffleIndices, "shuffle"); 4482 } 4483 E->VectorizedValue = V; 4484 ++NumVectorInstructions; 4485 return V; 4486 } 4487 case Instruction::GetElementPtr: { 4488 setInsertPointAfterBundle(E); 4489 4490 Value *Op0 = vectorizeTree(E->getOperand(0)); 4491 4492 std::vector<Value *> OpVecs; 4493 for (int j = 1, e = cast<GetElementPtrInst>(VL0)->getNumOperands(); j < e; 4494 ++j) { 4495 ValueList &VL = E->getOperand(j); 4496 // Need to cast all elements to the same type before vectorization to 4497 // avoid crash. 4498 Type *VL0Ty = VL0->getOperand(j)->getType(); 4499 Type *Ty = llvm::all_of( 4500 VL, [VL0Ty](Value *V) { return VL0Ty == V->getType(); }) 4501 ? VL0Ty 4502 : DL->getIndexType(cast<GetElementPtrInst>(VL0) 4503 ->getPointerOperandType() 4504 ->getScalarType()); 4505 for (Value *&V : VL) { 4506 auto *CI = cast<ConstantInt>(V); 4507 V = ConstantExpr::getIntegerCast(CI, Ty, 4508 CI->getValue().isSignBitSet()); 4509 } 4510 Value *OpVec = vectorizeTree(VL); 4511 OpVecs.push_back(OpVec); 4512 } 4513 4514 Value *V = Builder.CreateGEP( 4515 cast<GetElementPtrInst>(VL0)->getSourceElementType(), Op0, OpVecs); 4516 if (Instruction *I = dyn_cast<Instruction>(V)) 4517 V = propagateMetadata(I, E->Scalars); 4518 4519 if (NeedToShuffleReuses) { 4520 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4521 E->ReuseShuffleIndices, "shuffle"); 4522 } 4523 E->VectorizedValue = V; 4524 ++NumVectorInstructions; 4525 4526 return V; 4527 } 4528 case Instruction::Call: { 4529 CallInst *CI = cast<CallInst>(VL0); 4530 setInsertPointAfterBundle(E); 4531 4532 Intrinsic::ID IID = Intrinsic::not_intrinsic; 4533 if (Function *FI = CI->getCalledFunction()) 4534 IID = FI->getIntrinsicID(); 4535 4536 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 4537 4538 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 4539 bool UseIntrinsic = ID != Intrinsic::not_intrinsic && 4540 VecCallCosts.first <= VecCallCosts.second; 4541 4542 Value *ScalarArg = nullptr; 4543 std::vector<Value *> OpVecs; 4544 for (int j = 0, e = CI->getNumArgOperands(); j < e; ++j) { 4545 ValueList OpVL; 4546 // Some intrinsics have scalar arguments. This argument should not be 4547 // vectorized. 4548 if (UseIntrinsic && hasVectorInstrinsicScalarOpd(IID, j)) { 4549 CallInst *CEI = cast<CallInst>(VL0); 4550 ScalarArg = CEI->getArgOperand(j); 4551 OpVecs.push_back(CEI->getArgOperand(j)); 4552 continue; 4553 } 4554 4555 Value *OpVec = vectorizeTree(E->getOperand(j)); 4556 LLVM_DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n"); 4557 OpVecs.push_back(OpVec); 4558 } 4559 4560 Function *CF; 4561 if (!UseIntrinsic) { 4562 VFShape Shape = 4563 VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>( 4564 VecTy->getNumElements())), 4565 false /*HasGlobalPred*/); 4566 CF = VFDatabase(*CI).getVectorizedFunction(Shape); 4567 } else { 4568 Type *Tys[] = {FixedVectorType::get(CI->getType(), E->Scalars.size())}; 4569 CF = Intrinsic::getDeclaration(F->getParent(), ID, Tys); 4570 } 4571 4572 SmallVector<OperandBundleDef, 1> OpBundles; 4573 CI->getOperandBundlesAsDefs(OpBundles); 4574 Value *V = Builder.CreateCall(CF, OpVecs, OpBundles); 4575 4576 // The scalar argument uses an in-tree scalar so we add the new vectorized 4577 // call to ExternalUses list to make sure that an extract will be 4578 // generated in the future. 4579 if (ScalarArg && getTreeEntry(ScalarArg)) 4580 ExternalUses.push_back(ExternalUser(ScalarArg, cast<User>(V), 0)); 4581 4582 propagateIRFlags(V, E->Scalars, VL0); 4583 if (NeedToShuffleReuses) { 4584 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4585 E->ReuseShuffleIndices, "shuffle"); 4586 } 4587 E->VectorizedValue = V; 4588 ++NumVectorInstructions; 4589 return V; 4590 } 4591 case Instruction::ShuffleVector: { 4592 assert(E->isAltShuffle() && 4593 ((Instruction::isBinaryOp(E->getOpcode()) && 4594 Instruction::isBinaryOp(E->getAltOpcode())) || 4595 (Instruction::isCast(E->getOpcode()) && 4596 Instruction::isCast(E->getAltOpcode()))) && 4597 "Invalid Shuffle Vector Operand"); 4598 4599 Value *LHS = nullptr, *RHS = nullptr; 4600 if (Instruction::isBinaryOp(E->getOpcode())) { 4601 setInsertPointAfterBundle(E); 4602 LHS = vectorizeTree(E->getOperand(0)); 4603 RHS = vectorizeTree(E->getOperand(1)); 4604 } else { 4605 setInsertPointAfterBundle(E); 4606 LHS = vectorizeTree(E->getOperand(0)); 4607 } 4608 4609 if (E->VectorizedValue) { 4610 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4611 return E->VectorizedValue; 4612 } 4613 4614 Value *V0, *V1; 4615 if (Instruction::isBinaryOp(E->getOpcode())) { 4616 V0 = Builder.CreateBinOp( 4617 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, RHS); 4618 V1 = Builder.CreateBinOp( 4619 static_cast<Instruction::BinaryOps>(E->getAltOpcode()), LHS, RHS); 4620 } else { 4621 V0 = Builder.CreateCast( 4622 static_cast<Instruction::CastOps>(E->getOpcode()), LHS, VecTy); 4623 V1 = Builder.CreateCast( 4624 static_cast<Instruction::CastOps>(E->getAltOpcode()), LHS, VecTy); 4625 } 4626 4627 // Create shuffle to take alternate operations from the vector. 4628 // Also, gather up main and alt scalar ops to propagate IR flags to 4629 // each vector operation. 4630 ValueList OpScalars, AltScalars; 4631 unsigned e = E->Scalars.size(); 4632 SmallVector<int, 8> Mask(e); 4633 for (unsigned i = 0; i < e; ++i) { 4634 auto *OpInst = cast<Instruction>(E->Scalars[i]); 4635 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 4636 if (OpInst->getOpcode() == E->getAltOpcode()) { 4637 Mask[i] = e + i; 4638 AltScalars.push_back(E->Scalars[i]); 4639 } else { 4640 Mask[i] = i; 4641 OpScalars.push_back(E->Scalars[i]); 4642 } 4643 } 4644 4645 propagateIRFlags(V0, OpScalars); 4646 propagateIRFlags(V1, AltScalars); 4647 4648 Value *V = Builder.CreateShuffleVector(V0, V1, Mask); 4649 if (Instruction *I = dyn_cast<Instruction>(V)) 4650 V = propagateMetadata(I, E->Scalars); 4651 if (NeedToShuffleReuses) { 4652 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4653 E->ReuseShuffleIndices, "shuffle"); 4654 } 4655 E->VectorizedValue = V; 4656 ++NumVectorInstructions; 4657 4658 return V; 4659 } 4660 default: 4661 llvm_unreachable("unknown inst"); 4662 } 4663 return nullptr; 4664 } 4665 4666 Value *BoUpSLP::vectorizeTree() { 4667 ExtraValueToDebugLocsMap ExternallyUsedValues; 4668 return vectorizeTree(ExternallyUsedValues); 4669 } 4670 4671 Value * 4672 BoUpSLP::vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues) { 4673 // All blocks must be scheduled before any instructions are inserted. 4674 for (auto &BSIter : BlocksSchedules) { 4675 scheduleBlock(BSIter.second.get()); 4676 } 4677 4678 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4679 auto *VectorRoot = vectorizeTree(VectorizableTree[0].get()); 4680 4681 // If the vectorized tree can be rewritten in a smaller type, we truncate the 4682 // vectorized root. InstCombine will then rewrite the entire expression. We 4683 // sign extend the extracted values below. 4684 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 4685 if (MinBWs.count(ScalarRoot)) { 4686 if (auto *I = dyn_cast<Instruction>(VectorRoot)) 4687 Builder.SetInsertPoint(&*++BasicBlock::iterator(I)); 4688 auto BundleWidth = VectorizableTree[0]->Scalars.size(); 4689 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 4690 auto *VecTy = FixedVectorType::get(MinTy, BundleWidth); 4691 auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy); 4692 VectorizableTree[0]->VectorizedValue = Trunc; 4693 } 4694 4695 LLVM_DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size() 4696 << " values .\n"); 4697 4698 // If necessary, sign-extend or zero-extend ScalarRoot to the larger type 4699 // specified by ScalarType. 4700 auto extend = [&](Value *ScalarRoot, Value *Ex, Type *ScalarType) { 4701 if (!MinBWs.count(ScalarRoot)) 4702 return Ex; 4703 if (MinBWs[ScalarRoot].second) 4704 return Builder.CreateSExt(Ex, ScalarType); 4705 return Builder.CreateZExt(Ex, ScalarType); 4706 }; 4707 4708 // Extract all of the elements with the external uses. 4709 for (const auto &ExternalUse : ExternalUses) { 4710 Value *Scalar = ExternalUse.Scalar; 4711 llvm::User *User = ExternalUse.User; 4712 4713 // Skip users that we already RAUW. This happens when one instruction 4714 // has multiple uses of the same value. 4715 if (User && !is_contained(Scalar->users(), User)) 4716 continue; 4717 TreeEntry *E = getTreeEntry(Scalar); 4718 assert(E && "Invalid scalar"); 4719 assert(E->State == TreeEntry::Vectorize && "Extracting from a gather list"); 4720 4721 Value *Vec = E->VectorizedValue; 4722 assert(Vec && "Can't find vectorizable value"); 4723 4724 Value *Lane = Builder.getInt32(ExternalUse.Lane); 4725 // If User == nullptr, the Scalar is used as extra arg. Generate 4726 // ExtractElement instruction and update the record for this scalar in 4727 // ExternallyUsedValues. 4728 if (!User) { 4729 assert(ExternallyUsedValues.count(Scalar) && 4730 "Scalar with nullptr as an external user must be registered in " 4731 "ExternallyUsedValues map"); 4732 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 4733 Builder.SetInsertPoint(VecI->getParent(), 4734 std::next(VecI->getIterator())); 4735 } else { 4736 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4737 } 4738 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4739 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4740 CSEBlocks.insert(cast<Instruction>(Scalar)->getParent()); 4741 auto &Locs = ExternallyUsedValues[Scalar]; 4742 ExternallyUsedValues.insert({Ex, Locs}); 4743 ExternallyUsedValues.erase(Scalar); 4744 // Required to update internally referenced instructions. 4745 Scalar->replaceAllUsesWith(Ex); 4746 continue; 4747 } 4748 4749 // Generate extracts for out-of-tree users. 4750 // Find the insertion point for the extractelement lane. 4751 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 4752 if (PHINode *PH = dyn_cast<PHINode>(User)) { 4753 for (int i = 0, e = PH->getNumIncomingValues(); i != e; ++i) { 4754 if (PH->getIncomingValue(i) == Scalar) { 4755 Instruction *IncomingTerminator = 4756 PH->getIncomingBlock(i)->getTerminator(); 4757 if (isa<CatchSwitchInst>(IncomingTerminator)) { 4758 Builder.SetInsertPoint(VecI->getParent(), 4759 std::next(VecI->getIterator())); 4760 } else { 4761 Builder.SetInsertPoint(PH->getIncomingBlock(i)->getTerminator()); 4762 } 4763 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4764 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4765 CSEBlocks.insert(PH->getIncomingBlock(i)); 4766 PH->setOperand(i, Ex); 4767 } 4768 } 4769 } else { 4770 Builder.SetInsertPoint(cast<Instruction>(User)); 4771 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4772 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4773 CSEBlocks.insert(cast<Instruction>(User)->getParent()); 4774 User->replaceUsesOfWith(Scalar, Ex); 4775 } 4776 } else { 4777 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4778 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4779 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4780 CSEBlocks.insert(&F->getEntryBlock()); 4781 User->replaceUsesOfWith(Scalar, Ex); 4782 } 4783 4784 LLVM_DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n"); 4785 } 4786 4787 // For each vectorized value: 4788 for (auto &TEPtr : VectorizableTree) { 4789 TreeEntry *Entry = TEPtr.get(); 4790 4791 // No need to handle users of gathered values. 4792 if (Entry->State == TreeEntry::NeedToGather) 4793 continue; 4794 4795 assert(Entry->VectorizedValue && "Can't find vectorizable value"); 4796 4797 // For each lane: 4798 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 4799 Value *Scalar = Entry->Scalars[Lane]; 4800 4801 #ifndef NDEBUG 4802 Type *Ty = Scalar->getType(); 4803 if (!Ty->isVoidTy()) { 4804 for (User *U : Scalar->users()) { 4805 LLVM_DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n"); 4806 4807 // It is legal to delete users in the ignorelist. 4808 assert((getTreeEntry(U) || is_contained(UserIgnoreList, U)) && 4809 "Deleting out-of-tree value"); 4810 } 4811 } 4812 #endif 4813 LLVM_DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n"); 4814 eraseInstruction(cast<Instruction>(Scalar)); 4815 } 4816 } 4817 4818 Builder.ClearInsertionPoint(); 4819 InstrElementSize.clear(); 4820 4821 return VectorizableTree[0]->VectorizedValue; 4822 } 4823 4824 void BoUpSLP::optimizeGatherSequence() { 4825 LLVM_DEBUG(dbgs() << "SLP: Optimizing " << GatherSeq.size() 4826 << " gather sequences instructions.\n"); 4827 // LICM InsertElementInst sequences. 4828 for (Instruction *I : GatherSeq) { 4829 if (isDeleted(I)) 4830 continue; 4831 4832 // Check if this block is inside a loop. 4833 Loop *L = LI->getLoopFor(I->getParent()); 4834 if (!L) 4835 continue; 4836 4837 // Check if it has a preheader. 4838 BasicBlock *PreHeader = L->getLoopPreheader(); 4839 if (!PreHeader) 4840 continue; 4841 4842 // If the vector or the element that we insert into it are 4843 // instructions that are defined in this basic block then we can't 4844 // hoist this instruction. 4845 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 4846 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 4847 if (Op0 && L->contains(Op0)) 4848 continue; 4849 if (Op1 && L->contains(Op1)) 4850 continue; 4851 4852 // We can hoist this instruction. Move it to the pre-header. 4853 I->moveBefore(PreHeader->getTerminator()); 4854 } 4855 4856 // Make a list of all reachable blocks in our CSE queue. 4857 SmallVector<const DomTreeNode *, 8> CSEWorkList; 4858 CSEWorkList.reserve(CSEBlocks.size()); 4859 for (BasicBlock *BB : CSEBlocks) 4860 if (DomTreeNode *N = DT->getNode(BB)) { 4861 assert(DT->isReachableFromEntry(N)); 4862 CSEWorkList.push_back(N); 4863 } 4864 4865 // Sort blocks by domination. This ensures we visit a block after all blocks 4866 // dominating it are visited. 4867 llvm::stable_sort(CSEWorkList, 4868 [this](const DomTreeNode *A, const DomTreeNode *B) { 4869 return DT->properlyDominates(A, B); 4870 }); 4871 4872 // Perform O(N^2) search over the gather sequences and merge identical 4873 // instructions. TODO: We can further optimize this scan if we split the 4874 // instructions into different buckets based on the insert lane. 4875 SmallVector<Instruction *, 16> Visited; 4876 for (auto I = CSEWorkList.begin(), E = CSEWorkList.end(); I != E; ++I) { 4877 assert((I == CSEWorkList.begin() || !DT->dominates(*I, *std::prev(I))) && 4878 "Worklist not sorted properly!"); 4879 BasicBlock *BB = (*I)->getBlock(); 4880 // For all instructions in blocks containing gather sequences: 4881 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e;) { 4882 Instruction *In = &*it++; 4883 if (isDeleted(In)) 4884 continue; 4885 if (!isa<InsertElementInst>(In) && !isa<ExtractElementInst>(In)) 4886 continue; 4887 4888 // Check if we can replace this instruction with any of the 4889 // visited instructions. 4890 for (Instruction *v : Visited) { 4891 if (In->isIdenticalTo(v) && 4892 DT->dominates(v->getParent(), In->getParent())) { 4893 In->replaceAllUsesWith(v); 4894 eraseInstruction(In); 4895 In = nullptr; 4896 break; 4897 } 4898 } 4899 if (In) { 4900 assert(!is_contained(Visited, In)); 4901 Visited.push_back(In); 4902 } 4903 } 4904 } 4905 CSEBlocks.clear(); 4906 GatherSeq.clear(); 4907 } 4908 4909 // Groups the instructions to a bundle (which is then a single scheduling entity) 4910 // and schedules instructions until the bundle gets ready. 4911 Optional<BoUpSLP::ScheduleData *> 4912 BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 4913 const InstructionsState &S) { 4914 if (isa<PHINode>(S.OpValue)) 4915 return nullptr; 4916 4917 // Initialize the instruction bundle. 4918 Instruction *OldScheduleEnd = ScheduleEnd; 4919 ScheduleData *PrevInBundle = nullptr; 4920 ScheduleData *Bundle = nullptr; 4921 bool ReSchedule = false; 4922 LLVM_DEBUG(dbgs() << "SLP: bundle: " << *S.OpValue << "\n"); 4923 4924 // Make sure that the scheduling region contains all 4925 // instructions of the bundle. 4926 for (Value *V : VL) { 4927 if (!extendSchedulingRegion(V, S)) 4928 return None; 4929 } 4930 4931 for (Value *V : VL) { 4932 ScheduleData *BundleMember = getScheduleData(V); 4933 assert(BundleMember && 4934 "no ScheduleData for bundle member (maybe not in same basic block)"); 4935 if (BundleMember->IsScheduled) { 4936 // A bundle member was scheduled as single instruction before and now 4937 // needs to be scheduled as part of the bundle. We just get rid of the 4938 // existing schedule. 4939 LLVM_DEBUG(dbgs() << "SLP: reset schedule because " << *BundleMember 4940 << " was already scheduled\n"); 4941 ReSchedule = true; 4942 } 4943 assert(BundleMember->isSchedulingEntity() && 4944 "bundle member already part of other bundle"); 4945 if (PrevInBundle) { 4946 PrevInBundle->NextInBundle = BundleMember; 4947 } else { 4948 Bundle = BundleMember; 4949 } 4950 BundleMember->UnscheduledDepsInBundle = 0; 4951 Bundle->UnscheduledDepsInBundle += BundleMember->UnscheduledDeps; 4952 4953 // Group the instructions to a bundle. 4954 BundleMember->FirstInBundle = Bundle; 4955 PrevInBundle = BundleMember; 4956 } 4957 if (ScheduleEnd != OldScheduleEnd) { 4958 // The scheduling region got new instructions at the lower end (or it is a 4959 // new region for the first bundle). This makes it necessary to 4960 // recalculate all dependencies. 4961 // It is seldom that this needs to be done a second time after adding the 4962 // initial bundle to the region. 4963 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 4964 doForAllOpcodes(I, [](ScheduleData *SD) { 4965 SD->clearDependencies(); 4966 }); 4967 } 4968 ReSchedule = true; 4969 } 4970 if (ReSchedule) { 4971 resetSchedule(); 4972 initialFillReadyList(ReadyInsts); 4973 } 4974 assert(Bundle && "Failed to find schedule bundle"); 4975 4976 LLVM_DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle << " in block " 4977 << BB->getName() << "\n"); 4978 4979 calculateDependencies(Bundle, true, SLP); 4980 4981 // Now try to schedule the new bundle. As soon as the bundle is "ready" it 4982 // means that there are no cyclic dependencies and we can schedule it. 4983 // Note that's important that we don't "schedule" the bundle yet (see 4984 // cancelScheduling). 4985 while (!Bundle->isReady() && !ReadyInsts.empty()) { 4986 4987 ScheduleData *pickedSD = ReadyInsts.back(); 4988 ReadyInsts.pop_back(); 4989 4990 if (pickedSD->isSchedulingEntity() && pickedSD->isReady()) { 4991 schedule(pickedSD, ReadyInsts); 4992 } 4993 } 4994 if (!Bundle->isReady()) { 4995 cancelScheduling(VL, S.OpValue); 4996 return None; 4997 } 4998 return Bundle; 4999 } 5000 5001 void BoUpSLP::BlockScheduling::cancelScheduling(ArrayRef<Value *> VL, 5002 Value *OpValue) { 5003 if (isa<PHINode>(OpValue)) 5004 return; 5005 5006 ScheduleData *Bundle = getScheduleData(OpValue); 5007 LLVM_DEBUG(dbgs() << "SLP: cancel scheduling of " << *Bundle << "\n"); 5008 assert(!Bundle->IsScheduled && 5009 "Can't cancel bundle which is already scheduled"); 5010 assert(Bundle->isSchedulingEntity() && Bundle->isPartOfBundle() && 5011 "tried to unbundle something which is not a bundle"); 5012 5013 // Un-bundle: make single instructions out of the bundle. 5014 ScheduleData *BundleMember = Bundle; 5015 while (BundleMember) { 5016 assert(BundleMember->FirstInBundle == Bundle && "corrupt bundle links"); 5017 BundleMember->FirstInBundle = BundleMember; 5018 ScheduleData *Next = BundleMember->NextInBundle; 5019 BundleMember->NextInBundle = nullptr; 5020 BundleMember->UnscheduledDepsInBundle = BundleMember->UnscheduledDeps; 5021 if (BundleMember->UnscheduledDepsInBundle == 0) { 5022 ReadyInsts.insert(BundleMember); 5023 } 5024 BundleMember = Next; 5025 } 5026 } 5027 5028 BoUpSLP::ScheduleData *BoUpSLP::BlockScheduling::allocateScheduleDataChunks() { 5029 // Allocate a new ScheduleData for the instruction. 5030 if (ChunkPos >= ChunkSize) { 5031 ScheduleDataChunks.push_back(std::make_unique<ScheduleData[]>(ChunkSize)); 5032 ChunkPos = 0; 5033 } 5034 return &(ScheduleDataChunks.back()[ChunkPos++]); 5035 } 5036 5037 bool BoUpSLP::BlockScheduling::extendSchedulingRegion(Value *V, 5038 const InstructionsState &S) { 5039 if (getScheduleData(V, isOneOf(S, V))) 5040 return true; 5041 Instruction *I = dyn_cast<Instruction>(V); 5042 assert(I && "bundle member must be an instruction"); 5043 assert(!isa<PHINode>(I) && "phi nodes don't need to be scheduled"); 5044 auto &&CheckSheduleForI = [this, &S](Instruction *I) -> bool { 5045 ScheduleData *ISD = getScheduleData(I); 5046 if (!ISD) 5047 return false; 5048 assert(isInSchedulingRegion(ISD) && 5049 "ScheduleData not in scheduling region"); 5050 ScheduleData *SD = allocateScheduleDataChunks(); 5051 SD->Inst = I; 5052 SD->init(SchedulingRegionID, S.OpValue); 5053 ExtraScheduleDataMap[I][S.OpValue] = SD; 5054 return true; 5055 }; 5056 if (CheckSheduleForI(I)) 5057 return true; 5058 if (!ScheduleStart) { 5059 // It's the first instruction in the new region. 5060 initScheduleData(I, I->getNextNode(), nullptr, nullptr); 5061 ScheduleStart = I; 5062 ScheduleEnd = I->getNextNode(); 5063 if (isOneOf(S, I) != I) 5064 CheckSheduleForI(I); 5065 assert(ScheduleEnd && "tried to vectorize a terminator?"); 5066 LLVM_DEBUG(dbgs() << "SLP: initialize schedule region to " << *I << "\n"); 5067 return true; 5068 } 5069 // Search up and down at the same time, because we don't know if the new 5070 // instruction is above or below the existing scheduling region. 5071 BasicBlock::reverse_iterator UpIter = 5072 ++ScheduleStart->getIterator().getReverse(); 5073 BasicBlock::reverse_iterator UpperEnd = BB->rend(); 5074 BasicBlock::iterator DownIter = ScheduleEnd->getIterator(); 5075 BasicBlock::iterator LowerEnd = BB->end(); 5076 while (true) { 5077 if (++ScheduleRegionSize > ScheduleRegionSizeLimit) { 5078 LLVM_DEBUG(dbgs() << "SLP: exceeded schedule region size limit\n"); 5079 return false; 5080 } 5081 5082 if (UpIter != UpperEnd) { 5083 if (&*UpIter == I) { 5084 initScheduleData(I, ScheduleStart, nullptr, FirstLoadStoreInRegion); 5085 ScheduleStart = I; 5086 if (isOneOf(S, I) != I) 5087 CheckSheduleForI(I); 5088 LLVM_DEBUG(dbgs() << "SLP: extend schedule region start to " << *I 5089 << "\n"); 5090 return true; 5091 } 5092 ++UpIter; 5093 } 5094 if (DownIter != LowerEnd) { 5095 if (&*DownIter == I) { 5096 initScheduleData(ScheduleEnd, I->getNextNode(), LastLoadStoreInRegion, 5097 nullptr); 5098 ScheduleEnd = I->getNextNode(); 5099 if (isOneOf(S, I) != I) 5100 CheckSheduleForI(I); 5101 assert(ScheduleEnd && "tried to vectorize a terminator?"); 5102 LLVM_DEBUG(dbgs() << "SLP: extend schedule region end to " << *I 5103 << "\n"); 5104 return true; 5105 } 5106 ++DownIter; 5107 } 5108 assert((UpIter != UpperEnd || DownIter != LowerEnd) && 5109 "instruction not found in block"); 5110 } 5111 return true; 5112 } 5113 5114 void BoUpSLP::BlockScheduling::initScheduleData(Instruction *FromI, 5115 Instruction *ToI, 5116 ScheduleData *PrevLoadStore, 5117 ScheduleData *NextLoadStore) { 5118 ScheduleData *CurrentLoadStore = PrevLoadStore; 5119 for (Instruction *I = FromI; I != ToI; I = I->getNextNode()) { 5120 ScheduleData *SD = ScheduleDataMap[I]; 5121 if (!SD) { 5122 SD = allocateScheduleDataChunks(); 5123 ScheduleDataMap[I] = SD; 5124 SD->Inst = I; 5125 } 5126 assert(!isInSchedulingRegion(SD) && 5127 "new ScheduleData already in scheduling region"); 5128 SD->init(SchedulingRegionID, I); 5129 5130 if (I->mayReadOrWriteMemory() && 5131 (!isa<IntrinsicInst>(I) || 5132 cast<IntrinsicInst>(I)->getIntrinsicID() != Intrinsic::sideeffect)) { 5133 // Update the linked list of memory accessing instructions. 5134 if (CurrentLoadStore) { 5135 CurrentLoadStore->NextLoadStore = SD; 5136 } else { 5137 FirstLoadStoreInRegion = SD; 5138 } 5139 CurrentLoadStore = SD; 5140 } 5141 } 5142 if (NextLoadStore) { 5143 if (CurrentLoadStore) 5144 CurrentLoadStore->NextLoadStore = NextLoadStore; 5145 } else { 5146 LastLoadStoreInRegion = CurrentLoadStore; 5147 } 5148 } 5149 5150 void BoUpSLP::BlockScheduling::calculateDependencies(ScheduleData *SD, 5151 bool InsertInReadyList, 5152 BoUpSLP *SLP) { 5153 assert(SD->isSchedulingEntity()); 5154 5155 SmallVector<ScheduleData *, 10> WorkList; 5156 WorkList.push_back(SD); 5157 5158 while (!WorkList.empty()) { 5159 ScheduleData *SD = WorkList.back(); 5160 WorkList.pop_back(); 5161 5162 ScheduleData *BundleMember = SD; 5163 while (BundleMember) { 5164 assert(isInSchedulingRegion(BundleMember)); 5165 if (!BundleMember->hasValidDependencies()) { 5166 5167 LLVM_DEBUG(dbgs() << "SLP: update deps of " << *BundleMember 5168 << "\n"); 5169 BundleMember->Dependencies = 0; 5170 BundleMember->resetUnscheduledDeps(); 5171 5172 // Handle def-use chain dependencies. 5173 if (BundleMember->OpValue != BundleMember->Inst) { 5174 ScheduleData *UseSD = getScheduleData(BundleMember->Inst); 5175 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 5176 BundleMember->Dependencies++; 5177 ScheduleData *DestBundle = UseSD->FirstInBundle; 5178 if (!DestBundle->IsScheduled) 5179 BundleMember->incrementUnscheduledDeps(1); 5180 if (!DestBundle->hasValidDependencies()) 5181 WorkList.push_back(DestBundle); 5182 } 5183 } else { 5184 for (User *U : BundleMember->Inst->users()) { 5185 if (isa<Instruction>(U)) { 5186 ScheduleData *UseSD = getScheduleData(U); 5187 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 5188 BundleMember->Dependencies++; 5189 ScheduleData *DestBundle = UseSD->FirstInBundle; 5190 if (!DestBundle->IsScheduled) 5191 BundleMember->incrementUnscheduledDeps(1); 5192 if (!DestBundle->hasValidDependencies()) 5193 WorkList.push_back(DestBundle); 5194 } 5195 } else { 5196 // I'm not sure if this can ever happen. But we need to be safe. 5197 // This lets the instruction/bundle never be scheduled and 5198 // eventually disable vectorization. 5199 BundleMember->Dependencies++; 5200 BundleMember->incrementUnscheduledDeps(1); 5201 } 5202 } 5203 } 5204 5205 // Handle the memory dependencies. 5206 ScheduleData *DepDest = BundleMember->NextLoadStore; 5207 if (DepDest) { 5208 Instruction *SrcInst = BundleMember->Inst; 5209 MemoryLocation SrcLoc = getLocation(SrcInst, SLP->AA); 5210 bool SrcMayWrite = BundleMember->Inst->mayWriteToMemory(); 5211 unsigned numAliased = 0; 5212 unsigned DistToSrc = 1; 5213 5214 while (DepDest) { 5215 assert(isInSchedulingRegion(DepDest)); 5216 5217 // We have two limits to reduce the complexity: 5218 // 1) AliasedCheckLimit: It's a small limit to reduce calls to 5219 // SLP->isAliased (which is the expensive part in this loop). 5220 // 2) MaxMemDepDistance: It's for very large blocks and it aborts 5221 // the whole loop (even if the loop is fast, it's quadratic). 5222 // It's important for the loop break condition (see below) to 5223 // check this limit even between two read-only instructions. 5224 if (DistToSrc >= MaxMemDepDistance || 5225 ((SrcMayWrite || DepDest->Inst->mayWriteToMemory()) && 5226 (numAliased >= AliasedCheckLimit || 5227 SLP->isAliased(SrcLoc, SrcInst, DepDest->Inst)))) { 5228 5229 // We increment the counter only if the locations are aliased 5230 // (instead of counting all alias checks). This gives a better 5231 // balance between reduced runtime and accurate dependencies. 5232 numAliased++; 5233 5234 DepDest->MemoryDependencies.push_back(BundleMember); 5235 BundleMember->Dependencies++; 5236 ScheduleData *DestBundle = DepDest->FirstInBundle; 5237 if (!DestBundle->IsScheduled) { 5238 BundleMember->incrementUnscheduledDeps(1); 5239 } 5240 if (!DestBundle->hasValidDependencies()) { 5241 WorkList.push_back(DestBundle); 5242 } 5243 } 5244 DepDest = DepDest->NextLoadStore; 5245 5246 // Example, explaining the loop break condition: Let's assume our 5247 // starting instruction is i0 and MaxMemDepDistance = 3. 5248 // 5249 // +--------v--v--v 5250 // i0,i1,i2,i3,i4,i5,i6,i7,i8 5251 // +--------^--^--^ 5252 // 5253 // MaxMemDepDistance let us stop alias-checking at i3 and we add 5254 // dependencies from i0 to i3,i4,.. (even if they are not aliased). 5255 // Previously we already added dependencies from i3 to i6,i7,i8 5256 // (because of MaxMemDepDistance). As we added a dependency from 5257 // i0 to i3, we have transitive dependencies from i0 to i6,i7,i8 5258 // and we can abort this loop at i6. 5259 if (DistToSrc >= 2 * MaxMemDepDistance) 5260 break; 5261 DistToSrc++; 5262 } 5263 } 5264 } 5265 BundleMember = BundleMember->NextInBundle; 5266 } 5267 if (InsertInReadyList && SD->isReady()) { 5268 ReadyInsts.push_back(SD); 5269 LLVM_DEBUG(dbgs() << "SLP: gets ready on update: " << *SD->Inst 5270 << "\n"); 5271 } 5272 } 5273 } 5274 5275 void BoUpSLP::BlockScheduling::resetSchedule() { 5276 assert(ScheduleStart && 5277 "tried to reset schedule on block which has not been scheduled"); 5278 for (Instruction *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 5279 doForAllOpcodes(I, [&](ScheduleData *SD) { 5280 assert(isInSchedulingRegion(SD) && 5281 "ScheduleData not in scheduling region"); 5282 SD->IsScheduled = false; 5283 SD->resetUnscheduledDeps(); 5284 }); 5285 } 5286 ReadyInsts.clear(); 5287 } 5288 5289 void BoUpSLP::scheduleBlock(BlockScheduling *BS) { 5290 if (!BS->ScheduleStart) 5291 return; 5292 5293 LLVM_DEBUG(dbgs() << "SLP: schedule block " << BS->BB->getName() << "\n"); 5294 5295 BS->resetSchedule(); 5296 5297 // For the real scheduling we use a more sophisticated ready-list: it is 5298 // sorted by the original instruction location. This lets the final schedule 5299 // be as close as possible to the original instruction order. 5300 struct ScheduleDataCompare { 5301 bool operator()(ScheduleData *SD1, ScheduleData *SD2) const { 5302 return SD2->SchedulingPriority < SD1->SchedulingPriority; 5303 } 5304 }; 5305 std::set<ScheduleData *, ScheduleDataCompare> ReadyInsts; 5306 5307 // Ensure that all dependency data is updated and fill the ready-list with 5308 // initial instructions. 5309 int Idx = 0; 5310 int NumToSchedule = 0; 5311 for (auto *I = BS->ScheduleStart; I != BS->ScheduleEnd; 5312 I = I->getNextNode()) { 5313 BS->doForAllOpcodes(I, [this, &Idx, &NumToSchedule, BS](ScheduleData *SD) { 5314 assert(SD->isPartOfBundle() == 5315 (getTreeEntry(SD->Inst) != nullptr) && 5316 "scheduler and vectorizer bundle mismatch"); 5317 SD->FirstInBundle->SchedulingPriority = Idx++; 5318 if (SD->isSchedulingEntity()) { 5319 BS->calculateDependencies(SD, false, this); 5320 NumToSchedule++; 5321 } 5322 }); 5323 } 5324 BS->initialFillReadyList(ReadyInsts); 5325 5326 Instruction *LastScheduledInst = BS->ScheduleEnd; 5327 5328 // Do the "real" scheduling. 5329 while (!ReadyInsts.empty()) { 5330 ScheduleData *picked = *ReadyInsts.begin(); 5331 ReadyInsts.erase(ReadyInsts.begin()); 5332 5333 // Move the scheduled instruction(s) to their dedicated places, if not 5334 // there yet. 5335 ScheduleData *BundleMember = picked; 5336 while (BundleMember) { 5337 Instruction *pickedInst = BundleMember->Inst; 5338 if (LastScheduledInst->getNextNode() != pickedInst) { 5339 BS->BB->getInstList().remove(pickedInst); 5340 BS->BB->getInstList().insert(LastScheduledInst->getIterator(), 5341 pickedInst); 5342 } 5343 LastScheduledInst = pickedInst; 5344 BundleMember = BundleMember->NextInBundle; 5345 } 5346 5347 BS->schedule(picked, ReadyInsts); 5348 NumToSchedule--; 5349 } 5350 assert(NumToSchedule == 0 && "could not schedule all instructions"); 5351 5352 // Avoid duplicate scheduling of the block. 5353 BS->ScheduleStart = nullptr; 5354 } 5355 5356 unsigned BoUpSLP::getVectorElementSize(Value *V) { 5357 // If V is a store, just return the width of the stored value without 5358 // traversing the expression tree. This is the common case. 5359 if (auto *Store = dyn_cast<StoreInst>(V)) 5360 return DL->getTypeSizeInBits(Store->getValueOperand()->getType()); 5361 5362 auto E = InstrElementSize.find(V); 5363 if (E != InstrElementSize.end()) 5364 return E->second; 5365 5366 // If V is not a store, we can traverse the expression tree to find loads 5367 // that feed it. The type of the loaded value may indicate a more suitable 5368 // width than V's type. We want to base the vector element size on the width 5369 // of memory operations where possible. 5370 SmallVector<Instruction *, 16> Worklist; 5371 SmallPtrSet<Instruction *, 16> Visited; 5372 if (auto *I = dyn_cast<Instruction>(V)) { 5373 Worklist.push_back(I); 5374 Visited.insert(I); 5375 } 5376 5377 // Traverse the expression tree in bottom-up order looking for loads. If we 5378 // encounter an instruction we don't yet handle, we give up. 5379 auto MaxWidth = 0u; 5380 auto FoundUnknownInst = false; 5381 while (!Worklist.empty() && !FoundUnknownInst) { 5382 auto *I = Worklist.pop_back_val(); 5383 5384 // We should only be looking at scalar instructions here. If the current 5385 // instruction has a vector type, give up. 5386 auto *Ty = I->getType(); 5387 if (isa<VectorType>(Ty)) 5388 FoundUnknownInst = true; 5389 5390 // If the current instruction is a load, update MaxWidth to reflect the 5391 // width of the loaded value. 5392 else if (isa<LoadInst>(I)) 5393 MaxWidth = std::max<unsigned>(MaxWidth, DL->getTypeSizeInBits(Ty)); 5394 5395 // Otherwise, we need to visit the operands of the instruction. We only 5396 // handle the interesting cases from buildTree here. If an operand is an 5397 // instruction we haven't yet visited, we add it to the worklist. 5398 else if (isa<PHINode>(I) || isa<CastInst>(I) || isa<GetElementPtrInst>(I) || 5399 isa<CmpInst>(I) || isa<SelectInst>(I) || isa<BinaryOperator>(I)) { 5400 for (Use &U : I->operands()) 5401 if (auto *J = dyn_cast<Instruction>(U.get())) 5402 if (Visited.insert(J).second) 5403 Worklist.push_back(J); 5404 } 5405 5406 // If we don't yet handle the instruction, give up. 5407 else 5408 FoundUnknownInst = true; 5409 } 5410 5411 int Width = MaxWidth; 5412 // If we didn't encounter a memory access in the expression tree, or if we 5413 // gave up for some reason, just return the width of V. Otherwise, return the 5414 // maximum width we found. 5415 if (!MaxWidth || FoundUnknownInst) 5416 Width = DL->getTypeSizeInBits(V->getType()); 5417 5418 for (Instruction *I : Visited) 5419 InstrElementSize[I] = Width; 5420 5421 return Width; 5422 } 5423 5424 // Determine if a value V in a vectorizable expression Expr can be demoted to a 5425 // smaller type with a truncation. We collect the values that will be demoted 5426 // in ToDemote and additional roots that require investigating in Roots. 5427 static bool collectValuesToDemote(Value *V, SmallPtrSetImpl<Value *> &Expr, 5428 SmallVectorImpl<Value *> &ToDemote, 5429 SmallVectorImpl<Value *> &Roots) { 5430 // We can always demote constants. 5431 if (isa<Constant>(V)) { 5432 ToDemote.push_back(V); 5433 return true; 5434 } 5435 5436 // If the value is not an instruction in the expression with only one use, it 5437 // cannot be demoted. 5438 auto *I = dyn_cast<Instruction>(V); 5439 if (!I || !I->hasOneUse() || !Expr.count(I)) 5440 return false; 5441 5442 switch (I->getOpcode()) { 5443 5444 // We can always demote truncations and extensions. Since truncations can 5445 // seed additional demotion, we save the truncated value. 5446 case Instruction::Trunc: 5447 Roots.push_back(I->getOperand(0)); 5448 break; 5449 case Instruction::ZExt: 5450 case Instruction::SExt: 5451 break; 5452 5453 // We can demote certain binary operations if we can demote both of their 5454 // operands. 5455 case Instruction::Add: 5456 case Instruction::Sub: 5457 case Instruction::Mul: 5458 case Instruction::And: 5459 case Instruction::Or: 5460 case Instruction::Xor: 5461 if (!collectValuesToDemote(I->getOperand(0), Expr, ToDemote, Roots) || 5462 !collectValuesToDemote(I->getOperand(1), Expr, ToDemote, Roots)) 5463 return false; 5464 break; 5465 5466 // We can demote selects if we can demote their true and false values. 5467 case Instruction::Select: { 5468 SelectInst *SI = cast<SelectInst>(I); 5469 if (!collectValuesToDemote(SI->getTrueValue(), Expr, ToDemote, Roots) || 5470 !collectValuesToDemote(SI->getFalseValue(), Expr, ToDemote, Roots)) 5471 return false; 5472 break; 5473 } 5474 5475 // We can demote phis if we can demote all their incoming operands. Note that 5476 // we don't need to worry about cycles since we ensure single use above. 5477 case Instruction::PHI: { 5478 PHINode *PN = cast<PHINode>(I); 5479 for (Value *IncValue : PN->incoming_values()) 5480 if (!collectValuesToDemote(IncValue, Expr, ToDemote, Roots)) 5481 return false; 5482 break; 5483 } 5484 5485 // Otherwise, conservatively give up. 5486 default: 5487 return false; 5488 } 5489 5490 // Record the value that we can demote. 5491 ToDemote.push_back(V); 5492 return true; 5493 } 5494 5495 void BoUpSLP::computeMinimumValueSizes() { 5496 // If there are no external uses, the expression tree must be rooted by a 5497 // store. We can't demote in-memory values, so there is nothing to do here. 5498 if (ExternalUses.empty()) 5499 return; 5500 5501 // We only attempt to truncate integer expressions. 5502 auto &TreeRoot = VectorizableTree[0]->Scalars; 5503 auto *TreeRootIT = dyn_cast<IntegerType>(TreeRoot[0]->getType()); 5504 if (!TreeRootIT) 5505 return; 5506 5507 // If the expression is not rooted by a store, these roots should have 5508 // external uses. We will rely on InstCombine to rewrite the expression in 5509 // the narrower type. However, InstCombine only rewrites single-use values. 5510 // This means that if a tree entry other than a root is used externally, it 5511 // must have multiple uses and InstCombine will not rewrite it. The code 5512 // below ensures that only the roots are used externally. 5513 SmallPtrSet<Value *, 32> Expr(TreeRoot.begin(), TreeRoot.end()); 5514 for (auto &EU : ExternalUses) 5515 if (!Expr.erase(EU.Scalar)) 5516 return; 5517 if (!Expr.empty()) 5518 return; 5519 5520 // Collect the scalar values of the vectorizable expression. We will use this 5521 // context to determine which values can be demoted. If we see a truncation, 5522 // we mark it as seeding another demotion. 5523 for (auto &EntryPtr : VectorizableTree) 5524 Expr.insert(EntryPtr->Scalars.begin(), EntryPtr->Scalars.end()); 5525 5526 // Ensure the roots of the vectorizable tree don't form a cycle. They must 5527 // have a single external user that is not in the vectorizable tree. 5528 for (auto *Root : TreeRoot) 5529 if (!Root->hasOneUse() || Expr.count(*Root->user_begin())) 5530 return; 5531 5532 // Conservatively determine if we can actually truncate the roots of the 5533 // expression. Collect the values that can be demoted in ToDemote and 5534 // additional roots that require investigating in Roots. 5535 SmallVector<Value *, 32> ToDemote; 5536 SmallVector<Value *, 4> Roots; 5537 for (auto *Root : TreeRoot) 5538 if (!collectValuesToDemote(Root, Expr, ToDemote, Roots)) 5539 return; 5540 5541 // The maximum bit width required to represent all the values that can be 5542 // demoted without loss of precision. It would be safe to truncate the roots 5543 // of the expression to this width. 5544 auto MaxBitWidth = 8u; 5545 5546 // We first check if all the bits of the roots are demanded. If they're not, 5547 // we can truncate the roots to this narrower type. 5548 for (auto *Root : TreeRoot) { 5549 auto Mask = DB->getDemandedBits(cast<Instruction>(Root)); 5550 MaxBitWidth = std::max<unsigned>( 5551 Mask.getBitWidth() - Mask.countLeadingZeros(), MaxBitWidth); 5552 } 5553 5554 // True if the roots can be zero-extended back to their original type, rather 5555 // than sign-extended. We know that if the leading bits are not demanded, we 5556 // can safely zero-extend. So we initialize IsKnownPositive to True. 5557 bool IsKnownPositive = true; 5558 5559 // If all the bits of the roots are demanded, we can try a little harder to 5560 // compute a narrower type. This can happen, for example, if the roots are 5561 // getelementptr indices. InstCombine promotes these indices to the pointer 5562 // width. Thus, all their bits are technically demanded even though the 5563 // address computation might be vectorized in a smaller type. 5564 // 5565 // We start by looking at each entry that can be demoted. We compute the 5566 // maximum bit width required to store the scalar by using ValueTracking to 5567 // compute the number of high-order bits we can truncate. 5568 if (MaxBitWidth == DL->getTypeSizeInBits(TreeRoot[0]->getType()) && 5569 llvm::all_of(TreeRoot, [](Value *R) { 5570 assert(R->hasOneUse() && "Root should have only one use!"); 5571 return isa<GetElementPtrInst>(R->user_back()); 5572 })) { 5573 MaxBitWidth = 8u; 5574 5575 // Determine if the sign bit of all the roots is known to be zero. If not, 5576 // IsKnownPositive is set to False. 5577 IsKnownPositive = llvm::all_of(TreeRoot, [&](Value *R) { 5578 KnownBits Known = computeKnownBits(R, *DL); 5579 return Known.isNonNegative(); 5580 }); 5581 5582 // Determine the maximum number of bits required to store the scalar 5583 // values. 5584 for (auto *Scalar : ToDemote) { 5585 auto NumSignBits = ComputeNumSignBits(Scalar, *DL, 0, AC, nullptr, DT); 5586 auto NumTypeBits = DL->getTypeSizeInBits(Scalar->getType()); 5587 MaxBitWidth = std::max<unsigned>(NumTypeBits - NumSignBits, MaxBitWidth); 5588 } 5589 5590 // If we can't prove that the sign bit is zero, we must add one to the 5591 // maximum bit width to account for the unknown sign bit. This preserves 5592 // the existing sign bit so we can safely sign-extend the root back to the 5593 // original type. Otherwise, if we know the sign bit is zero, we will 5594 // zero-extend the root instead. 5595 // 5596 // FIXME: This is somewhat suboptimal, as there will be cases where adding 5597 // one to the maximum bit width will yield a larger-than-necessary 5598 // type. In general, we need to add an extra bit only if we can't 5599 // prove that the upper bit of the original type is equal to the 5600 // upper bit of the proposed smaller type. If these two bits are the 5601 // same (either zero or one) we know that sign-extending from the 5602 // smaller type will result in the same value. Here, since we can't 5603 // yet prove this, we are just making the proposed smaller type 5604 // larger to ensure correctness. 5605 if (!IsKnownPositive) 5606 ++MaxBitWidth; 5607 } 5608 5609 // Round MaxBitWidth up to the next power-of-two. 5610 if (!isPowerOf2_64(MaxBitWidth)) 5611 MaxBitWidth = NextPowerOf2(MaxBitWidth); 5612 5613 // If the maximum bit width we compute is less than the with of the roots' 5614 // type, we can proceed with the narrowing. Otherwise, do nothing. 5615 if (MaxBitWidth >= TreeRootIT->getBitWidth()) 5616 return; 5617 5618 // If we can truncate the root, we must collect additional values that might 5619 // be demoted as a result. That is, those seeded by truncations we will 5620 // modify. 5621 while (!Roots.empty()) 5622 collectValuesToDemote(Roots.pop_back_val(), Expr, ToDemote, Roots); 5623 5624 // Finally, map the values we can demote to the maximum bit with we computed. 5625 for (auto *Scalar : ToDemote) 5626 MinBWs[Scalar] = std::make_pair(MaxBitWidth, !IsKnownPositive); 5627 } 5628 5629 namespace { 5630 5631 /// The SLPVectorizer Pass. 5632 struct SLPVectorizer : public FunctionPass { 5633 SLPVectorizerPass Impl; 5634 5635 /// Pass identification, replacement for typeid 5636 static char ID; 5637 5638 explicit SLPVectorizer() : FunctionPass(ID) { 5639 initializeSLPVectorizerPass(*PassRegistry::getPassRegistry()); 5640 } 5641 5642 bool doInitialization(Module &M) override { 5643 return false; 5644 } 5645 5646 bool runOnFunction(Function &F) override { 5647 if (skipFunction(F)) 5648 return false; 5649 5650 auto *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 5651 auto *TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F); 5652 auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>(); 5653 auto *TLI = TLIP ? &TLIP->getTLI(F) : nullptr; 5654 auto *AA = &getAnalysis<AAResultsWrapperPass>().getAAResults(); 5655 auto *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 5656 auto *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 5657 auto *AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F); 5658 auto *DB = &getAnalysis<DemandedBitsWrapperPass>().getDemandedBits(); 5659 auto *ORE = &getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE(); 5660 5661 return Impl.runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 5662 } 5663 5664 void getAnalysisUsage(AnalysisUsage &AU) const override { 5665 FunctionPass::getAnalysisUsage(AU); 5666 AU.addRequired<AssumptionCacheTracker>(); 5667 AU.addRequired<ScalarEvolutionWrapperPass>(); 5668 AU.addRequired<AAResultsWrapperPass>(); 5669 AU.addRequired<TargetTransformInfoWrapperPass>(); 5670 AU.addRequired<LoopInfoWrapperPass>(); 5671 AU.addRequired<DominatorTreeWrapperPass>(); 5672 AU.addRequired<DemandedBitsWrapperPass>(); 5673 AU.addRequired<OptimizationRemarkEmitterWrapperPass>(); 5674 AU.addRequired<InjectTLIMappingsLegacy>(); 5675 AU.addPreserved<LoopInfoWrapperPass>(); 5676 AU.addPreserved<DominatorTreeWrapperPass>(); 5677 AU.addPreserved<AAResultsWrapperPass>(); 5678 AU.addPreserved<GlobalsAAWrapperPass>(); 5679 AU.setPreservesCFG(); 5680 } 5681 }; 5682 5683 } // end anonymous namespace 5684 5685 PreservedAnalyses SLPVectorizerPass::run(Function &F, FunctionAnalysisManager &AM) { 5686 auto *SE = &AM.getResult<ScalarEvolutionAnalysis>(F); 5687 auto *TTI = &AM.getResult<TargetIRAnalysis>(F); 5688 auto *TLI = AM.getCachedResult<TargetLibraryAnalysis>(F); 5689 auto *AA = &AM.getResult<AAManager>(F); 5690 auto *LI = &AM.getResult<LoopAnalysis>(F); 5691 auto *DT = &AM.getResult<DominatorTreeAnalysis>(F); 5692 auto *AC = &AM.getResult<AssumptionAnalysis>(F); 5693 auto *DB = &AM.getResult<DemandedBitsAnalysis>(F); 5694 auto *ORE = &AM.getResult<OptimizationRemarkEmitterAnalysis>(F); 5695 5696 bool Changed = runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 5697 if (!Changed) 5698 return PreservedAnalyses::all(); 5699 5700 PreservedAnalyses PA; 5701 PA.preserveSet<CFGAnalyses>(); 5702 PA.preserve<AAManager>(); 5703 PA.preserve<GlobalsAA>(); 5704 return PA; 5705 } 5706 5707 bool SLPVectorizerPass::runImpl(Function &F, ScalarEvolution *SE_, 5708 TargetTransformInfo *TTI_, 5709 TargetLibraryInfo *TLI_, AliasAnalysis *AA_, 5710 LoopInfo *LI_, DominatorTree *DT_, 5711 AssumptionCache *AC_, DemandedBits *DB_, 5712 OptimizationRemarkEmitter *ORE_) { 5713 if (!RunSLPVectorization) 5714 return false; 5715 SE = SE_; 5716 TTI = TTI_; 5717 TLI = TLI_; 5718 AA = AA_; 5719 LI = LI_; 5720 DT = DT_; 5721 AC = AC_; 5722 DB = DB_; 5723 DL = &F.getParent()->getDataLayout(); 5724 5725 Stores.clear(); 5726 GEPs.clear(); 5727 bool Changed = false; 5728 5729 // If the target claims to have no vector registers don't attempt 5730 // vectorization. 5731 if (!TTI->getNumberOfRegisters(TTI->getRegisterClassForType(true))) 5732 return false; 5733 5734 // Don't vectorize when the attribute NoImplicitFloat is used. 5735 if (F.hasFnAttribute(Attribute::NoImplicitFloat)) 5736 return false; 5737 5738 LLVM_DEBUG(dbgs() << "SLP: Analyzing blocks in " << F.getName() << ".\n"); 5739 5740 // Use the bottom up slp vectorizer to construct chains that start with 5741 // store instructions. 5742 BoUpSLP R(&F, SE, TTI, TLI, AA, LI, DT, AC, DB, DL, ORE_); 5743 5744 // A general note: the vectorizer must use BoUpSLP::eraseInstruction() to 5745 // delete instructions. 5746 5747 // Scan the blocks in the function in post order. 5748 for (auto BB : post_order(&F.getEntryBlock())) { 5749 collectSeedInstructions(BB); 5750 5751 // Vectorize trees that end at stores. 5752 if (!Stores.empty()) { 5753 LLVM_DEBUG(dbgs() << "SLP: Found stores for " << Stores.size() 5754 << " underlying objects.\n"); 5755 Changed |= vectorizeStoreChains(R); 5756 } 5757 5758 // Vectorize trees that end at reductions. 5759 Changed |= vectorizeChainsInBlock(BB, R); 5760 5761 // Vectorize the index computations of getelementptr instructions. This 5762 // is primarily intended to catch gather-like idioms ending at 5763 // non-consecutive loads. 5764 if (!GEPs.empty()) { 5765 LLVM_DEBUG(dbgs() << "SLP: Found GEPs for " << GEPs.size() 5766 << " underlying objects.\n"); 5767 Changed |= vectorizeGEPIndices(BB, R); 5768 } 5769 } 5770 5771 if (Changed) { 5772 R.optimizeGatherSequence(); 5773 LLVM_DEBUG(dbgs() << "SLP: vectorized \"" << F.getName() << "\"\n"); 5774 } 5775 return Changed; 5776 } 5777 5778 bool SLPVectorizerPass::vectorizeStoreChain(ArrayRef<Value *> Chain, BoUpSLP &R, 5779 unsigned Idx) { 5780 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " << Chain.size() 5781 << "\n"); 5782 const unsigned Sz = R.getVectorElementSize(Chain[0]); 5783 const unsigned MinVF = R.getMinVecRegSize() / Sz; 5784 unsigned VF = Chain.size(); 5785 5786 if (!isPowerOf2_32(Sz) || !isPowerOf2_32(VF) || VF < 2 || VF < MinVF) 5787 return false; 5788 5789 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << VF << " stores at offset " << Idx 5790 << "\n"); 5791 5792 R.buildTree(Chain); 5793 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 5794 // TODO: Handle orders of size less than number of elements in the vector. 5795 if (Order && Order->size() == Chain.size()) { 5796 // TODO: reorder tree nodes without tree rebuilding. 5797 SmallVector<Value *, 4> ReorderedOps(Chain.rbegin(), Chain.rend()); 5798 llvm::transform(*Order, ReorderedOps.begin(), 5799 [Chain](const unsigned Idx) { return Chain[Idx]; }); 5800 R.buildTree(ReorderedOps); 5801 } 5802 if (R.isTreeTinyAndNotFullyVectorizable()) 5803 return false; 5804 if (R.isLoadCombineCandidate()) 5805 return false; 5806 5807 R.computeMinimumValueSizes(); 5808 5809 int Cost = R.getTreeCost(); 5810 5811 LLVM_DEBUG(dbgs() << "SLP: Found cost=" << Cost << " for VF=" << VF << "\n"); 5812 if (Cost < -SLPCostThreshold) { 5813 LLVM_DEBUG(dbgs() << "SLP: Decided to vectorize cost=" << Cost << "\n"); 5814 5815 using namespace ore; 5816 5817 R.getORE()->emit(OptimizationRemark(SV_NAME, "StoresVectorized", 5818 cast<StoreInst>(Chain[0])) 5819 << "Stores SLP vectorized with cost " << NV("Cost", Cost) 5820 << " and with tree size " 5821 << NV("TreeSize", R.getTreeSize())); 5822 5823 R.vectorizeTree(); 5824 return true; 5825 } 5826 5827 return false; 5828 } 5829 5830 bool SLPVectorizerPass::vectorizeStores(ArrayRef<StoreInst *> Stores, 5831 BoUpSLP &R) { 5832 // We may run into multiple chains that merge into a single chain. We mark the 5833 // stores that we vectorized so that we don't visit the same store twice. 5834 BoUpSLP::ValueSet VectorizedStores; 5835 bool Changed = false; 5836 5837 int E = Stores.size(); 5838 SmallBitVector Tails(E, false); 5839 SmallVector<int, 16> ConsecutiveChain(E, E + 1); 5840 int MaxIter = MaxStoreLookup.getValue(); 5841 int IterCnt; 5842 auto &&FindConsecutiveAccess = [this, &Stores, &Tails, &IterCnt, MaxIter, 5843 &ConsecutiveChain](int K, int Idx) { 5844 if (IterCnt >= MaxIter) 5845 return true; 5846 ++IterCnt; 5847 if (!isConsecutiveAccess(Stores[K], Stores[Idx], *DL, *SE)) 5848 return false; 5849 5850 Tails.set(Idx); 5851 ConsecutiveChain[K] = Idx; 5852 return true; 5853 }; 5854 // Do a quadratic search on all of the given stores in reverse order and find 5855 // all of the pairs of stores that follow each other. 5856 for (int Idx = E - 1; Idx >= 0; --Idx) { 5857 // If a store has multiple consecutive store candidates, search according 5858 // to the sequence: Idx-1, Idx+1, Idx-2, Idx+2, ... 5859 // This is because usually pairing with immediate succeeding or preceding 5860 // candidate create the best chance to find slp vectorization opportunity. 5861 const int MaxLookDepth = std::max(E - Idx, Idx + 1); 5862 IterCnt = 0; 5863 for (int Offset = 1, F = MaxLookDepth; Offset < F; ++Offset) 5864 if ((Idx >= Offset && FindConsecutiveAccess(Idx - Offset, Idx)) || 5865 (Idx + Offset < E && FindConsecutiveAccess(Idx + Offset, Idx))) 5866 break; 5867 } 5868 5869 // For stores that start but don't end a link in the chain: 5870 for (int Cnt = E; Cnt > 0; --Cnt) { 5871 int I = Cnt - 1; 5872 if (ConsecutiveChain[I] == E + 1 || Tails.test(I)) 5873 continue; 5874 // We found a store instr that starts a chain. Now follow the chain and try 5875 // to vectorize it. 5876 BoUpSLP::ValueList Operands; 5877 // Collect the chain into a list. 5878 while (I != E + 1 && !VectorizedStores.count(Stores[I])) { 5879 Operands.push_back(Stores[I]); 5880 // Move to the next value in the chain. 5881 I = ConsecutiveChain[I]; 5882 } 5883 5884 // If a vector register can't hold 1 element, we are done. 5885 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 5886 unsigned EltSize = R.getVectorElementSize(Stores[0]); 5887 if (MaxVecRegSize % EltSize != 0) 5888 continue; 5889 5890 unsigned MaxElts = MaxVecRegSize / EltSize; 5891 // FIXME: Is division-by-2 the correct step? Should we assert that the 5892 // register size is a power-of-2? 5893 unsigned StartIdx = 0; 5894 for (unsigned Size = llvm::PowerOf2Ceil(MaxElts); Size >= 2; Size /= 2) { 5895 for (unsigned Cnt = StartIdx, E = Operands.size(); Cnt + Size <= E;) { 5896 ArrayRef<Value *> Slice = makeArrayRef(Operands).slice(Cnt, Size); 5897 if (!VectorizedStores.count(Slice.front()) && 5898 !VectorizedStores.count(Slice.back()) && 5899 vectorizeStoreChain(Slice, R, Cnt)) { 5900 // Mark the vectorized stores so that we don't vectorize them again. 5901 VectorizedStores.insert(Slice.begin(), Slice.end()); 5902 Changed = true; 5903 // If we vectorized initial block, no need to try to vectorize it 5904 // again. 5905 if (Cnt == StartIdx) 5906 StartIdx += Size; 5907 Cnt += Size; 5908 continue; 5909 } 5910 ++Cnt; 5911 } 5912 // Check if the whole array was vectorized already - exit. 5913 if (StartIdx >= Operands.size()) 5914 break; 5915 } 5916 } 5917 5918 return Changed; 5919 } 5920 5921 void SLPVectorizerPass::collectSeedInstructions(BasicBlock *BB) { 5922 // Initialize the collections. We will make a single pass over the block. 5923 Stores.clear(); 5924 GEPs.clear(); 5925 5926 // Visit the store and getelementptr instructions in BB and organize them in 5927 // Stores and GEPs according to the underlying objects of their pointer 5928 // operands. 5929 for (Instruction &I : *BB) { 5930 // Ignore store instructions that are volatile or have a pointer operand 5931 // that doesn't point to a scalar type. 5932 if (auto *SI = dyn_cast<StoreInst>(&I)) { 5933 if (!SI->isSimple()) 5934 continue; 5935 if (!isValidElementType(SI->getValueOperand()->getType())) 5936 continue; 5937 Stores[getUnderlyingObject(SI->getPointerOperand())].push_back(SI); 5938 } 5939 5940 // Ignore getelementptr instructions that have more than one index, a 5941 // constant index, or a pointer operand that doesn't point to a scalar 5942 // type. 5943 else if (auto *GEP = dyn_cast<GetElementPtrInst>(&I)) { 5944 auto Idx = GEP->idx_begin()->get(); 5945 if (GEP->getNumIndices() > 1 || isa<Constant>(Idx)) 5946 continue; 5947 if (!isValidElementType(Idx->getType())) 5948 continue; 5949 if (GEP->getType()->isVectorTy()) 5950 continue; 5951 GEPs[GEP->getPointerOperand()].push_back(GEP); 5952 } 5953 } 5954 } 5955 5956 bool SLPVectorizerPass::tryToVectorizePair(Value *A, Value *B, BoUpSLP &R) { 5957 if (!A || !B) 5958 return false; 5959 Value *VL[] = {A, B}; 5960 return tryToVectorizeList(VL, R, /*AllowReorder=*/true); 5961 } 5962 5963 bool SLPVectorizerPass::tryToVectorizeList(ArrayRef<Value *> VL, BoUpSLP &R, 5964 bool AllowReorder, 5965 ArrayRef<Value *> InsertUses) { 5966 if (VL.size() < 2) 5967 return false; 5968 5969 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize a list of length = " 5970 << VL.size() << ".\n"); 5971 5972 // Check that all of the parts are instructions of the same type, 5973 // we permit an alternate opcode via InstructionsState. 5974 InstructionsState S = getSameOpcode(VL); 5975 if (!S.getOpcode()) 5976 return false; 5977 5978 Instruction *I0 = cast<Instruction>(S.OpValue); 5979 // Make sure invalid types (including vector type) are rejected before 5980 // determining vectorization factor for scalar instructions. 5981 for (Value *V : VL) { 5982 Type *Ty = V->getType(); 5983 if (!isValidElementType(Ty)) { 5984 // NOTE: the following will give user internal llvm type name, which may 5985 // not be useful. 5986 R.getORE()->emit([&]() { 5987 std::string type_str; 5988 llvm::raw_string_ostream rso(type_str); 5989 Ty->print(rso); 5990 return OptimizationRemarkMissed(SV_NAME, "UnsupportedType", I0) 5991 << "Cannot SLP vectorize list: type " 5992 << rso.str() + " is unsupported by vectorizer"; 5993 }); 5994 return false; 5995 } 5996 } 5997 5998 unsigned Sz = R.getVectorElementSize(I0); 5999 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / Sz); 6000 unsigned MaxVF = std::max<unsigned>(PowerOf2Floor(VL.size()), MinVF); 6001 if (MaxVF < 2) { 6002 R.getORE()->emit([&]() { 6003 return OptimizationRemarkMissed(SV_NAME, "SmallVF", I0) 6004 << "Cannot SLP vectorize list: vectorization factor " 6005 << "less than 2 is not supported"; 6006 }); 6007 return false; 6008 } 6009 6010 bool Changed = false; 6011 bool CandidateFound = false; 6012 int MinCost = SLPCostThreshold; 6013 6014 bool CompensateUseCost = 6015 !InsertUses.empty() && llvm::all_of(InsertUses, [](const Value *V) { 6016 return V && isa<InsertElementInst>(V); 6017 }); 6018 assert((!CompensateUseCost || InsertUses.size() == VL.size()) && 6019 "Each scalar expected to have an associated InsertElement user."); 6020 6021 unsigned NextInst = 0, MaxInst = VL.size(); 6022 for (unsigned VF = MaxVF; NextInst + 1 < MaxInst && VF >= MinVF; VF /= 2) { 6023 // No actual vectorization should happen, if number of parts is the same as 6024 // provided vectorization factor (i.e. the scalar type is used for vector 6025 // code during codegen). 6026 auto *VecTy = FixedVectorType::get(VL[0]->getType(), VF); 6027 if (TTI->getNumberOfParts(VecTy) == VF) 6028 continue; 6029 for (unsigned I = NextInst; I < MaxInst; ++I) { 6030 unsigned OpsWidth = 0; 6031 6032 if (I + VF > MaxInst) 6033 OpsWidth = MaxInst - I; 6034 else 6035 OpsWidth = VF; 6036 6037 if (!isPowerOf2_32(OpsWidth) || OpsWidth < 2) 6038 break; 6039 6040 ArrayRef<Value *> Ops = VL.slice(I, OpsWidth); 6041 // Check that a previous iteration of this loop did not delete the Value. 6042 if (llvm::any_of(Ops, [&R](Value *V) { 6043 auto *I = dyn_cast<Instruction>(V); 6044 return I && R.isDeleted(I); 6045 })) 6046 continue; 6047 6048 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << OpsWidth << " operations " 6049 << "\n"); 6050 6051 R.buildTree(Ops); 6052 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 6053 // TODO: check if we can allow reordering for more cases. 6054 if (AllowReorder && Order) { 6055 // TODO: reorder tree nodes without tree rebuilding. 6056 // Conceptually, there is nothing actually preventing us from trying to 6057 // reorder a larger list. In fact, we do exactly this when vectorizing 6058 // reductions. However, at this point, we only expect to get here when 6059 // there are exactly two operations. 6060 assert(Ops.size() == 2); 6061 Value *ReorderedOps[] = {Ops[1], Ops[0]}; 6062 R.buildTree(ReorderedOps, None); 6063 } 6064 if (R.isTreeTinyAndNotFullyVectorizable()) 6065 continue; 6066 6067 R.computeMinimumValueSizes(); 6068 int Cost = R.getTreeCost(); 6069 CandidateFound = true; 6070 if (CompensateUseCost) { 6071 // TODO: Use TTI's getScalarizationOverhead for sequence of inserts 6072 // rather than sum of single inserts as the latter may overestimate 6073 // cost. This work should imply improving cost estimation for extracts 6074 // that added in for external (for vectorization tree) users,i.e. that 6075 // part should also switch to same interface. 6076 // For example, the following case is projected code after SLP: 6077 // %4 = extractelement <4 x i64> %3, i32 0 6078 // %v0 = insertelement <4 x i64> undef, i64 %4, i32 0 6079 // %5 = extractelement <4 x i64> %3, i32 1 6080 // %v1 = insertelement <4 x i64> %v0, i64 %5, i32 1 6081 // %6 = extractelement <4 x i64> %3, i32 2 6082 // %v2 = insertelement <4 x i64> %v1, i64 %6, i32 2 6083 // %7 = extractelement <4 x i64> %3, i32 3 6084 // %v3 = insertelement <4 x i64> %v2, i64 %7, i32 3 6085 // 6086 // Extracts here added by SLP in order to feed users (the inserts) of 6087 // original scalars and contribute to "ExtractCost" at cost evaluation. 6088 // The inserts in turn form sequence to build an aggregate that 6089 // detected by findBuildAggregate routine. 6090 // SLP makes an assumption that such sequence will be optimized away 6091 // later (instcombine) so it tries to compensate ExctractCost with 6092 // cost of insert sequence. 6093 // Current per element cost calculation approach is not quite accurate 6094 // and tends to create bias toward favoring vectorization. 6095 // Switching to the TTI interface might help a bit. 6096 // Alternative solution could be pattern-match to detect a no-op or 6097 // shuffle. 6098 unsigned UserCost = 0; 6099 for (unsigned Lane = 0; Lane < OpsWidth; Lane++) { 6100 auto *IE = cast<InsertElementInst>(InsertUses[I + Lane]); 6101 if (auto *CI = dyn_cast<ConstantInt>(IE->getOperand(2))) 6102 UserCost += TTI->getVectorInstrCost( 6103 Instruction::InsertElement, IE->getType(), CI->getZExtValue()); 6104 } 6105 LLVM_DEBUG(dbgs() << "SLP: Compensate cost of users by: " << UserCost 6106 << ".\n"); 6107 Cost -= UserCost; 6108 } 6109 6110 MinCost = std::min(MinCost, Cost); 6111 6112 if (Cost < -SLPCostThreshold) { 6113 LLVM_DEBUG(dbgs() << "SLP: Vectorizing list at cost:" << Cost << ".\n"); 6114 R.getORE()->emit(OptimizationRemark(SV_NAME, "VectorizedList", 6115 cast<Instruction>(Ops[0])) 6116 << "SLP vectorized with cost " << ore::NV("Cost", Cost) 6117 << " and with tree size " 6118 << ore::NV("TreeSize", R.getTreeSize())); 6119 6120 R.vectorizeTree(); 6121 // Move to the next bundle. 6122 I += VF - 1; 6123 NextInst = I + 1; 6124 Changed = true; 6125 } 6126 } 6127 } 6128 6129 if (!Changed && CandidateFound) { 6130 R.getORE()->emit([&]() { 6131 return OptimizationRemarkMissed(SV_NAME, "NotBeneficial", I0) 6132 << "List vectorization was possible but not beneficial with cost " 6133 << ore::NV("Cost", MinCost) << " >= " 6134 << ore::NV("Treshold", -SLPCostThreshold); 6135 }); 6136 } else if (!Changed) { 6137 R.getORE()->emit([&]() { 6138 return OptimizationRemarkMissed(SV_NAME, "NotPossible", I0) 6139 << "Cannot SLP vectorize list: vectorization was impossible" 6140 << " with available vectorization factors"; 6141 }); 6142 } 6143 return Changed; 6144 } 6145 6146 bool SLPVectorizerPass::tryToVectorize(Instruction *I, BoUpSLP &R) { 6147 if (!I) 6148 return false; 6149 6150 if (!isa<BinaryOperator>(I) && !isa<CmpInst>(I)) 6151 return false; 6152 6153 Value *P = I->getParent(); 6154 6155 // Vectorize in current basic block only. 6156 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 6157 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 6158 if (!Op0 || !Op1 || Op0->getParent() != P || Op1->getParent() != P) 6159 return false; 6160 6161 // Try to vectorize V. 6162 if (tryToVectorizePair(Op0, Op1, R)) 6163 return true; 6164 6165 auto *A = dyn_cast<BinaryOperator>(Op0); 6166 auto *B = dyn_cast<BinaryOperator>(Op1); 6167 // Try to skip B. 6168 if (B && B->hasOneUse()) { 6169 auto *B0 = dyn_cast<BinaryOperator>(B->getOperand(0)); 6170 auto *B1 = dyn_cast<BinaryOperator>(B->getOperand(1)); 6171 if (B0 && B0->getParent() == P && tryToVectorizePair(A, B0, R)) 6172 return true; 6173 if (B1 && B1->getParent() == P && tryToVectorizePair(A, B1, R)) 6174 return true; 6175 } 6176 6177 // Try to skip A. 6178 if (A && A->hasOneUse()) { 6179 auto *A0 = dyn_cast<BinaryOperator>(A->getOperand(0)); 6180 auto *A1 = dyn_cast<BinaryOperator>(A->getOperand(1)); 6181 if (A0 && A0->getParent() == P && tryToVectorizePair(A0, B, R)) 6182 return true; 6183 if (A1 && A1->getParent() == P && tryToVectorizePair(A1, B, R)) 6184 return true; 6185 } 6186 return false; 6187 } 6188 6189 /// Generate a shuffle mask to be used in a reduction tree. 6190 /// 6191 /// \param VecLen The length of the vector to be reduced. 6192 /// \param NumEltsToRdx The number of elements that should be reduced in the 6193 /// vector. 6194 /// \param IsPairwise Whether the reduction is a pairwise or splitting 6195 /// reduction. A pairwise reduction will generate a mask of 6196 /// <0,2,...> or <1,3,..> while a splitting reduction will generate 6197 /// <2,3, undef,undef> for a vector of 4 and NumElts = 2. 6198 /// \param IsLeft True will generate a mask of even elements, odd otherwise. 6199 static SmallVector<int, 32> createRdxShuffleMask(unsigned VecLen, 6200 unsigned NumEltsToRdx, 6201 bool IsPairwise, bool IsLeft) { 6202 assert((IsPairwise || !IsLeft) && "Don't support a <0,1,undef,...> mask"); 6203 6204 SmallVector<int, 32> ShuffleMask(VecLen, -1); 6205 6206 if (IsPairwise) 6207 // Build a mask of 0, 2, ... (left) or 1, 3, ... (right). 6208 for (unsigned i = 0; i != NumEltsToRdx; ++i) 6209 ShuffleMask[i] = 2 * i + !IsLeft; 6210 else 6211 // Move the upper half of the vector to the lower half. 6212 for (unsigned i = 0; i != NumEltsToRdx; ++i) 6213 ShuffleMask[i] = NumEltsToRdx + i; 6214 6215 return ShuffleMask; 6216 } 6217 6218 namespace { 6219 6220 /// Model horizontal reductions. 6221 /// 6222 /// A horizontal reduction is a tree of reduction operations (currently add and 6223 /// fadd) that has operations that can be put into a vector as its leaf. 6224 /// For example, this tree: 6225 /// 6226 /// mul mul mul mul 6227 /// \ / \ / 6228 /// + + 6229 /// \ / 6230 /// + 6231 /// This tree has "mul" as its reduced values and "+" as its reduction 6232 /// operations. A reduction might be feeding into a store or a binary operation 6233 /// feeding a phi. 6234 /// ... 6235 /// \ / 6236 /// + 6237 /// | 6238 /// phi += 6239 /// 6240 /// Or: 6241 /// ... 6242 /// \ / 6243 /// + 6244 /// | 6245 /// *p = 6246 /// 6247 class HorizontalReduction { 6248 using ReductionOpsType = SmallVector<Value *, 16>; 6249 using ReductionOpsListType = SmallVector<ReductionOpsType, 2>; 6250 ReductionOpsListType ReductionOps; 6251 SmallVector<Value *, 32> ReducedVals; 6252 // Use map vector to make stable output. 6253 MapVector<Instruction *, Value *> ExtraArgs; 6254 6255 /// Kind of the reduction data. 6256 enum ReductionKind { 6257 RK_None, /// Not a reduction. 6258 RK_Arithmetic, /// Binary reduction data. 6259 RK_Min, /// Minimum reduction data. 6260 RK_UMin, /// Unsigned minimum reduction data. 6261 RK_Max, /// Maximum reduction data. 6262 RK_UMax, /// Unsigned maximum reduction data. 6263 }; 6264 6265 /// Contains info about operation, like its opcode, left and right operands. 6266 class OperationData { 6267 /// Opcode of the instruction. 6268 unsigned Opcode = 0; 6269 6270 /// Left operand of the reduction operation. 6271 Value *LHS = nullptr; 6272 6273 /// Right operand of the reduction operation. 6274 Value *RHS = nullptr; 6275 6276 /// Kind of the reduction operation. 6277 ReductionKind Kind = RK_None; 6278 6279 /// True if float point min/max reduction has no NaNs. 6280 bool NoNaN = false; 6281 6282 /// Checks if the reduction operation can be vectorized. 6283 bool isVectorizable() const { 6284 return LHS && RHS && 6285 // We currently only support add/mul/logical && min/max reductions. 6286 ((Kind == RK_Arithmetic && 6287 (Opcode == Instruction::Add || Opcode == Instruction::FAdd || 6288 Opcode == Instruction::Mul || Opcode == Instruction::FMul || 6289 Opcode == Instruction::And || Opcode == Instruction::Or || 6290 Opcode == Instruction::Xor)) || 6291 ((Opcode == Instruction::ICmp || Opcode == Instruction::FCmp) && 6292 (Kind == RK_Min || Kind == RK_Max)) || 6293 (Opcode == Instruction::ICmp && 6294 (Kind == RK_UMin || Kind == RK_UMax))); 6295 } 6296 6297 /// Creates reduction operation with the current opcode. 6298 Value *createOp(IRBuilder<> &Builder, const Twine &Name) const { 6299 assert(isVectorizable() && 6300 "Expected add|fadd or min/max reduction operation."); 6301 Value *Cmp = nullptr; 6302 switch (Kind) { 6303 case RK_Arithmetic: 6304 return Builder.CreateBinOp((Instruction::BinaryOps)Opcode, LHS, RHS, 6305 Name); 6306 case RK_Min: 6307 Cmp = Opcode == Instruction::ICmp ? Builder.CreateICmpSLT(LHS, RHS) 6308 : Builder.CreateFCmpOLT(LHS, RHS); 6309 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6310 case RK_Max: 6311 Cmp = Opcode == Instruction::ICmp ? Builder.CreateICmpSGT(LHS, RHS) 6312 : Builder.CreateFCmpOGT(LHS, RHS); 6313 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6314 case RK_UMin: 6315 assert(Opcode == Instruction::ICmp && "Expected integer types."); 6316 Cmp = Builder.CreateICmpULT(LHS, RHS); 6317 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6318 case RK_UMax: 6319 assert(Opcode == Instruction::ICmp && "Expected integer types."); 6320 Cmp = Builder.CreateICmpUGT(LHS, RHS); 6321 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6322 case RK_None: 6323 break; 6324 } 6325 llvm_unreachable("Unknown reduction operation."); 6326 } 6327 6328 public: 6329 explicit OperationData() = default; 6330 6331 /// Construction for reduced values. They are identified by opcode only and 6332 /// don't have associated LHS/RHS values. 6333 explicit OperationData(Value *V) { 6334 if (auto *I = dyn_cast<Instruction>(V)) 6335 Opcode = I->getOpcode(); 6336 } 6337 6338 /// Constructor for reduction operations with opcode and its left and 6339 /// right operands. 6340 OperationData(unsigned Opcode, Value *LHS, Value *RHS, ReductionKind Kind, 6341 bool NoNaN = false) 6342 : Opcode(Opcode), LHS(LHS), RHS(RHS), Kind(Kind), NoNaN(NoNaN) { 6343 assert(Kind != RK_None && "One of the reduction operations is expected."); 6344 } 6345 6346 explicit operator bool() const { return Opcode; } 6347 6348 /// Return true if this operation is any kind of minimum or maximum. 6349 bool isMinMax() const { 6350 switch (Kind) { 6351 case RK_Arithmetic: 6352 return false; 6353 case RK_Min: 6354 case RK_Max: 6355 case RK_UMin: 6356 case RK_UMax: 6357 return true; 6358 case RK_None: 6359 break; 6360 } 6361 llvm_unreachable("Reduction kind is not set"); 6362 } 6363 6364 /// Get the index of the first operand. 6365 unsigned getFirstOperandIndex() const { 6366 assert(!!*this && "The opcode is not set."); 6367 // We allow calling this before 'Kind' is set, so handle that specially. 6368 if (Kind == RK_None) 6369 return 0; 6370 return isMinMax() ? 1 : 0; 6371 } 6372 6373 /// Total number of operands in the reduction operation. 6374 unsigned getNumberOfOperands() const { 6375 assert(Kind != RK_None && !!*this && LHS && RHS && 6376 "Expected reduction operation."); 6377 return isMinMax() ? 3 : 2; 6378 } 6379 6380 /// Checks if the operation has the same parent as \p P. 6381 bool hasSameParent(Instruction *I, Value *P, bool IsRedOp) const { 6382 assert(Kind != RK_None && !!*this && LHS && RHS && 6383 "Expected reduction operation."); 6384 if (!IsRedOp) 6385 return I->getParent() == P; 6386 if (isMinMax()) { 6387 // SelectInst must be used twice while the condition op must have single 6388 // use only. 6389 auto *Cmp = cast<Instruction>(cast<SelectInst>(I)->getCondition()); 6390 return I->getParent() == P && Cmp && Cmp->getParent() == P; 6391 } 6392 // Arithmetic reduction operation must be used once only. 6393 return I->getParent() == P; 6394 } 6395 6396 /// Expected number of uses for reduction operations/reduced values. 6397 bool hasRequiredNumberOfUses(Instruction *I, bool IsReductionOp) const { 6398 assert(Kind != RK_None && !!*this && LHS && RHS && 6399 "Expected reduction operation."); 6400 if (isMinMax()) 6401 return I->hasNUses(2) && 6402 (!IsReductionOp || 6403 cast<SelectInst>(I)->getCondition()->hasOneUse()); 6404 return I->hasOneUse(); 6405 } 6406 6407 /// Initializes the list of reduction operations. 6408 void initReductionOps(ReductionOpsListType &ReductionOps) { 6409 assert(Kind != RK_None && !!*this && LHS && RHS && 6410 "Expected reduction operation."); 6411 if (isMinMax()) 6412 ReductionOps.assign(2, ReductionOpsType()); 6413 else 6414 ReductionOps.assign(1, ReductionOpsType()); 6415 } 6416 6417 /// Add all reduction operations for the reduction instruction \p I. 6418 void addReductionOps(Instruction *I, ReductionOpsListType &ReductionOps) { 6419 assert(Kind != RK_None && !!*this && LHS && RHS && 6420 "Expected reduction operation."); 6421 if (isMinMax()) { 6422 ReductionOps[0].emplace_back(cast<SelectInst>(I)->getCondition()); 6423 ReductionOps[1].emplace_back(I); 6424 } else { 6425 ReductionOps[0].emplace_back(I); 6426 } 6427 } 6428 6429 /// Checks if instruction is associative and can be vectorized. 6430 bool isAssociative(Instruction *I) const { 6431 assert(Kind != RK_None && *this && LHS && RHS && 6432 "Expected reduction operation."); 6433 switch (Kind) { 6434 case RK_Arithmetic: 6435 return I->isAssociative(); 6436 case RK_Min: 6437 case RK_Max: 6438 return Opcode == Instruction::ICmp || 6439 cast<Instruction>(I->getOperand(0))->isFast(); 6440 case RK_UMin: 6441 case RK_UMax: 6442 assert(Opcode == Instruction::ICmp && 6443 "Only integer compare operation is expected."); 6444 return true; 6445 case RK_None: 6446 break; 6447 } 6448 llvm_unreachable("Reduction kind is not set"); 6449 } 6450 6451 /// Checks if the reduction operation can be vectorized. 6452 bool isVectorizable(Instruction *I) const { 6453 return isVectorizable() && isAssociative(I); 6454 } 6455 6456 /// Checks if two operation data are both a reduction op or both a reduced 6457 /// value. 6458 bool operator==(const OperationData &OD) const { 6459 assert(((Kind != OD.Kind) || ((!LHS == !OD.LHS) && (!RHS == !OD.RHS))) && 6460 "One of the comparing operations is incorrect."); 6461 return this == &OD || (Kind == OD.Kind && Opcode == OD.Opcode); 6462 } 6463 bool operator!=(const OperationData &OD) const { return !(*this == OD); } 6464 void clear() { 6465 Opcode = 0; 6466 LHS = nullptr; 6467 RHS = nullptr; 6468 Kind = RK_None; 6469 NoNaN = false; 6470 } 6471 6472 /// Get the opcode of the reduction operation. 6473 unsigned getOpcode() const { 6474 assert(isVectorizable() && "Expected vectorizable operation."); 6475 return Opcode; 6476 } 6477 6478 /// Get kind of reduction data. 6479 ReductionKind getKind() const { return Kind; } 6480 Value *getLHS() const { return LHS; } 6481 Value *getRHS() const { return RHS; } 6482 Type *getConditionType() const { 6483 return isMinMax() ? CmpInst::makeCmpResultType(LHS->getType()) : nullptr; 6484 } 6485 6486 /// Creates reduction operation with the current opcode with the IR flags 6487 /// from \p ReductionOps. 6488 Value *createOp(IRBuilder<> &Builder, const Twine &Name, 6489 const ReductionOpsListType &ReductionOps) const { 6490 assert(isVectorizable() && 6491 "Expected add|fadd or min/max reduction operation."); 6492 auto *Op = createOp(Builder, Name); 6493 switch (Kind) { 6494 case RK_Arithmetic: 6495 propagateIRFlags(Op, ReductionOps[0]); 6496 return Op; 6497 case RK_Min: 6498 case RK_Max: 6499 case RK_UMin: 6500 case RK_UMax: 6501 if (auto *SI = dyn_cast<SelectInst>(Op)) 6502 propagateIRFlags(SI->getCondition(), ReductionOps[0]); 6503 propagateIRFlags(Op, ReductionOps[1]); 6504 return Op; 6505 case RK_None: 6506 break; 6507 } 6508 llvm_unreachable("Unknown reduction operation."); 6509 } 6510 /// Creates reduction operation with the current opcode with the IR flags 6511 /// from \p I. 6512 Value *createOp(IRBuilder<> &Builder, const Twine &Name, 6513 Instruction *I) const { 6514 assert(isVectorizable() && 6515 "Expected add|fadd or min/max reduction operation."); 6516 auto *Op = createOp(Builder, Name); 6517 switch (Kind) { 6518 case RK_Arithmetic: 6519 propagateIRFlags(Op, I); 6520 return Op; 6521 case RK_Min: 6522 case RK_Max: 6523 case RK_UMin: 6524 case RK_UMax: 6525 if (auto *SI = dyn_cast<SelectInst>(Op)) { 6526 propagateIRFlags(SI->getCondition(), 6527 cast<SelectInst>(I)->getCondition()); 6528 } 6529 propagateIRFlags(Op, I); 6530 return Op; 6531 case RK_None: 6532 break; 6533 } 6534 llvm_unreachable("Unknown reduction operation."); 6535 } 6536 6537 TargetTransformInfo::ReductionFlags getFlags() const { 6538 TargetTransformInfo::ReductionFlags Flags; 6539 Flags.NoNaN = NoNaN; 6540 switch (Kind) { 6541 case RK_Arithmetic: 6542 break; 6543 case RK_Min: 6544 Flags.IsSigned = Opcode == Instruction::ICmp; 6545 Flags.IsMaxOp = false; 6546 break; 6547 case RK_Max: 6548 Flags.IsSigned = Opcode == Instruction::ICmp; 6549 Flags.IsMaxOp = true; 6550 break; 6551 case RK_UMin: 6552 Flags.IsSigned = false; 6553 Flags.IsMaxOp = false; 6554 break; 6555 case RK_UMax: 6556 Flags.IsSigned = false; 6557 Flags.IsMaxOp = true; 6558 break; 6559 case RK_None: 6560 llvm_unreachable("Reduction kind is not set"); 6561 } 6562 return Flags; 6563 } 6564 }; 6565 6566 WeakTrackingVH ReductionRoot; 6567 6568 /// The operation data of the reduction operation. 6569 OperationData ReductionData; 6570 6571 /// The operation data of the values we perform a reduction on. 6572 OperationData ReducedValueData; 6573 6574 /// Should we model this reduction as a pairwise reduction tree or a tree that 6575 /// splits the vector in halves and adds those halves. 6576 bool IsPairwiseReduction = false; 6577 6578 /// Checks if the ParentStackElem.first should be marked as a reduction 6579 /// operation with an extra argument or as extra argument itself. 6580 void markExtraArg(std::pair<Instruction *, unsigned> &ParentStackElem, 6581 Value *ExtraArg) { 6582 if (ExtraArgs.count(ParentStackElem.first)) { 6583 ExtraArgs[ParentStackElem.first] = nullptr; 6584 // We ran into something like: 6585 // ParentStackElem.first = ExtraArgs[ParentStackElem.first] + ExtraArg. 6586 // The whole ParentStackElem.first should be considered as an extra value 6587 // in this case. 6588 // Do not perform analysis of remaining operands of ParentStackElem.first 6589 // instruction, this whole instruction is an extra argument. 6590 ParentStackElem.second = ParentStackElem.first->getNumOperands(); 6591 } else { 6592 // We ran into something like: 6593 // ParentStackElem.first += ... + ExtraArg + ... 6594 ExtraArgs[ParentStackElem.first] = ExtraArg; 6595 } 6596 } 6597 6598 static OperationData getOperationData(Value *V) { 6599 if (!V) 6600 return OperationData(); 6601 6602 Value *LHS; 6603 Value *RHS; 6604 if (m_BinOp(m_Value(LHS), m_Value(RHS)).match(V)) { 6605 return OperationData(cast<BinaryOperator>(V)->getOpcode(), LHS, RHS, 6606 RK_Arithmetic); 6607 } 6608 if (auto *Select = dyn_cast<SelectInst>(V)) { 6609 // Look for a min/max pattern. 6610 if (m_UMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 6611 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMin); 6612 } else if (m_SMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 6613 return OperationData(Instruction::ICmp, LHS, RHS, RK_Min); 6614 } else if (m_OrdFMin(m_Value(LHS), m_Value(RHS)).match(Select) || 6615 m_UnordFMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 6616 return OperationData( 6617 Instruction::FCmp, LHS, RHS, RK_Min, 6618 cast<Instruction>(Select->getCondition())->hasNoNaNs()); 6619 } else if (m_UMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 6620 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMax); 6621 } else if (m_SMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 6622 return OperationData(Instruction::ICmp, LHS, RHS, RK_Max); 6623 } else if (m_OrdFMax(m_Value(LHS), m_Value(RHS)).match(Select) || 6624 m_UnordFMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 6625 return OperationData( 6626 Instruction::FCmp, LHS, RHS, RK_Max, 6627 cast<Instruction>(Select->getCondition())->hasNoNaNs()); 6628 } else { 6629 // Try harder: look for min/max pattern based on instructions producing 6630 // same values such as: select ((cmp Inst1, Inst2), Inst1, Inst2). 6631 // During the intermediate stages of SLP, it's very common to have 6632 // pattern like this (since optimizeGatherSequence is run only once 6633 // at the end): 6634 // %1 = extractelement <2 x i32> %a, i32 0 6635 // %2 = extractelement <2 x i32> %a, i32 1 6636 // %cond = icmp sgt i32 %1, %2 6637 // %3 = extractelement <2 x i32> %a, i32 0 6638 // %4 = extractelement <2 x i32> %a, i32 1 6639 // %select = select i1 %cond, i32 %3, i32 %4 6640 CmpInst::Predicate Pred; 6641 Instruction *L1; 6642 Instruction *L2; 6643 6644 LHS = Select->getTrueValue(); 6645 RHS = Select->getFalseValue(); 6646 Value *Cond = Select->getCondition(); 6647 6648 // TODO: Support inverse predicates. 6649 if (match(Cond, m_Cmp(Pred, m_Specific(LHS), m_Instruction(L2)))) { 6650 if (!isa<ExtractElementInst>(RHS) || 6651 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6652 return OperationData(V); 6653 } else if (match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Specific(RHS)))) { 6654 if (!isa<ExtractElementInst>(LHS) || 6655 !L1->isIdenticalTo(cast<Instruction>(LHS))) 6656 return OperationData(V); 6657 } else { 6658 if (!isa<ExtractElementInst>(LHS) || !isa<ExtractElementInst>(RHS)) 6659 return OperationData(V); 6660 if (!match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Instruction(L2))) || 6661 !L1->isIdenticalTo(cast<Instruction>(LHS)) || 6662 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6663 return OperationData(V); 6664 } 6665 switch (Pred) { 6666 default: 6667 return OperationData(V); 6668 6669 case CmpInst::ICMP_ULT: 6670 case CmpInst::ICMP_ULE: 6671 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMin); 6672 6673 case CmpInst::ICMP_SLT: 6674 case CmpInst::ICMP_SLE: 6675 return OperationData(Instruction::ICmp, LHS, RHS, RK_Min); 6676 6677 case CmpInst::FCMP_OLT: 6678 case CmpInst::FCMP_OLE: 6679 case CmpInst::FCMP_ULT: 6680 case CmpInst::FCMP_ULE: 6681 return OperationData(Instruction::FCmp, LHS, RHS, RK_Min, 6682 cast<Instruction>(Cond)->hasNoNaNs()); 6683 6684 case CmpInst::ICMP_UGT: 6685 case CmpInst::ICMP_UGE: 6686 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMax); 6687 6688 case CmpInst::ICMP_SGT: 6689 case CmpInst::ICMP_SGE: 6690 return OperationData(Instruction::ICmp, LHS, RHS, RK_Max); 6691 6692 case CmpInst::FCMP_OGT: 6693 case CmpInst::FCMP_OGE: 6694 case CmpInst::FCMP_UGT: 6695 case CmpInst::FCMP_UGE: 6696 return OperationData(Instruction::FCmp, LHS, RHS, RK_Max, 6697 cast<Instruction>(Cond)->hasNoNaNs()); 6698 } 6699 } 6700 } 6701 return OperationData(V); 6702 } 6703 6704 public: 6705 HorizontalReduction() = default; 6706 6707 /// Try to find a reduction tree. 6708 bool matchAssociativeReduction(PHINode *Phi, Instruction *B) { 6709 assert((!Phi || is_contained(Phi->operands(), B)) && 6710 "Thi phi needs to use the binary operator"); 6711 6712 ReductionData = getOperationData(B); 6713 6714 // We could have a initial reductions that is not an add. 6715 // r *= v1 + v2 + v3 + v4 6716 // In such a case start looking for a tree rooted in the first '+'. 6717 if (Phi) { 6718 if (ReductionData.getLHS() == Phi) { 6719 Phi = nullptr; 6720 B = dyn_cast<Instruction>(ReductionData.getRHS()); 6721 ReductionData = getOperationData(B); 6722 } else if (ReductionData.getRHS() == Phi) { 6723 Phi = nullptr; 6724 B = dyn_cast<Instruction>(ReductionData.getLHS()); 6725 ReductionData = getOperationData(B); 6726 } 6727 } 6728 6729 if (!ReductionData.isVectorizable(B)) 6730 return false; 6731 6732 Type *Ty = B->getType(); 6733 if (!isValidElementType(Ty)) 6734 return false; 6735 if (!Ty->isIntOrIntVectorTy() && !Ty->isFPOrFPVectorTy()) 6736 return false; 6737 6738 ReducedValueData.clear(); 6739 ReductionRoot = B; 6740 6741 // Post order traverse the reduction tree starting at B. We only handle true 6742 // trees containing only binary operators. 6743 SmallVector<std::pair<Instruction *, unsigned>, 32> Stack; 6744 Stack.push_back(std::make_pair(B, ReductionData.getFirstOperandIndex())); 6745 ReductionData.initReductionOps(ReductionOps); 6746 while (!Stack.empty()) { 6747 Instruction *TreeN = Stack.back().first; 6748 unsigned EdgeToVist = Stack.back().second++; 6749 OperationData OpData = getOperationData(TreeN); 6750 bool IsReducedValue = OpData != ReductionData; 6751 6752 // Postorder vist. 6753 if (IsReducedValue || EdgeToVist == OpData.getNumberOfOperands()) { 6754 if (IsReducedValue) 6755 ReducedVals.push_back(TreeN); 6756 else { 6757 auto I = ExtraArgs.find(TreeN); 6758 if (I != ExtraArgs.end() && !I->second) { 6759 // Check if TreeN is an extra argument of its parent operation. 6760 if (Stack.size() <= 1) { 6761 // TreeN can't be an extra argument as it is a root reduction 6762 // operation. 6763 return false; 6764 } 6765 // Yes, TreeN is an extra argument, do not add it to a list of 6766 // reduction operations. 6767 // Stack[Stack.size() - 2] always points to the parent operation. 6768 markExtraArg(Stack[Stack.size() - 2], TreeN); 6769 ExtraArgs.erase(TreeN); 6770 } else 6771 ReductionData.addReductionOps(TreeN, ReductionOps); 6772 } 6773 // Retract. 6774 Stack.pop_back(); 6775 continue; 6776 } 6777 6778 // Visit left or right. 6779 Value *NextV = TreeN->getOperand(EdgeToVist); 6780 if (NextV != Phi) { 6781 auto *I = dyn_cast<Instruction>(NextV); 6782 OpData = getOperationData(I); 6783 // Continue analysis if the next operand is a reduction operation or 6784 // (possibly) a reduced value. If the reduced value opcode is not set, 6785 // the first met operation != reduction operation is considered as the 6786 // reduced value class. 6787 if (I && (!ReducedValueData || OpData == ReducedValueData || 6788 OpData == ReductionData)) { 6789 const bool IsReductionOperation = OpData == ReductionData; 6790 // Only handle trees in the current basic block. 6791 if (!ReductionData.hasSameParent(I, B->getParent(), 6792 IsReductionOperation)) { 6793 // I is an extra argument for TreeN (its parent operation). 6794 markExtraArg(Stack.back(), I); 6795 continue; 6796 } 6797 6798 // Each tree node needs to have minimal number of users except for the 6799 // ultimate reduction. 6800 if (!ReductionData.hasRequiredNumberOfUses(I, 6801 OpData == ReductionData) && 6802 I != B) { 6803 // I is an extra argument for TreeN (its parent operation). 6804 markExtraArg(Stack.back(), I); 6805 continue; 6806 } 6807 6808 if (IsReductionOperation) { 6809 // We need to be able to reassociate the reduction operations. 6810 if (!OpData.isAssociative(I)) { 6811 // I is an extra argument for TreeN (its parent operation). 6812 markExtraArg(Stack.back(), I); 6813 continue; 6814 } 6815 } else if (ReducedValueData && 6816 ReducedValueData != OpData) { 6817 // Make sure that the opcodes of the operations that we are going to 6818 // reduce match. 6819 // I is an extra argument for TreeN (its parent operation). 6820 markExtraArg(Stack.back(), I); 6821 continue; 6822 } else if (!ReducedValueData) 6823 ReducedValueData = OpData; 6824 6825 Stack.push_back(std::make_pair(I, OpData.getFirstOperandIndex())); 6826 continue; 6827 } 6828 } 6829 // NextV is an extra argument for TreeN (its parent operation). 6830 markExtraArg(Stack.back(), NextV); 6831 } 6832 return true; 6833 } 6834 6835 /// Attempt to vectorize the tree found by 6836 /// matchAssociativeReduction. 6837 bool tryToReduce(BoUpSLP &V, TargetTransformInfo *TTI) { 6838 if (ReducedVals.empty()) 6839 return false; 6840 6841 // If there is a sufficient number of reduction values, reduce 6842 // to a nearby power-of-2. Can safely generate oversized 6843 // vectors and rely on the backend to split them to legal sizes. 6844 unsigned NumReducedVals = ReducedVals.size(); 6845 if (NumReducedVals < 4) 6846 return false; 6847 6848 unsigned ReduxWidth = PowerOf2Floor(NumReducedVals); 6849 6850 Value *VectorizedTree = nullptr; 6851 6852 // FIXME: Fast-math-flags should be set based on the instructions in the 6853 // reduction (not all of 'fast' are required). 6854 IRBuilder<> Builder(cast<Instruction>(ReductionRoot)); 6855 FastMathFlags Unsafe; 6856 Unsafe.setFast(); 6857 Builder.setFastMathFlags(Unsafe); 6858 unsigned i = 0; 6859 6860 BoUpSLP::ExtraValueToDebugLocsMap ExternallyUsedValues; 6861 // The same extra argument may be used several time, so log each attempt 6862 // to use it. 6863 for (auto &Pair : ExtraArgs) { 6864 assert(Pair.first && "DebugLoc must be set."); 6865 ExternallyUsedValues[Pair.second].push_back(Pair.first); 6866 } 6867 6868 // The compare instruction of a min/max is the insertion point for new 6869 // instructions and may be replaced with a new compare instruction. 6870 auto getCmpForMinMaxReduction = [](Instruction *RdxRootInst) { 6871 assert(isa<SelectInst>(RdxRootInst) && 6872 "Expected min/max reduction to have select root instruction"); 6873 Value *ScalarCond = cast<SelectInst>(RdxRootInst)->getCondition(); 6874 assert(isa<Instruction>(ScalarCond) && 6875 "Expected min/max reduction to have compare condition"); 6876 return cast<Instruction>(ScalarCond); 6877 }; 6878 6879 // The reduction root is used as the insertion point for new instructions, 6880 // so set it as externally used to prevent it from being deleted. 6881 ExternallyUsedValues[ReductionRoot]; 6882 SmallVector<Value *, 16> IgnoreList; 6883 for (auto &V : ReductionOps) 6884 IgnoreList.append(V.begin(), V.end()); 6885 while (i < NumReducedVals - ReduxWidth + 1 && ReduxWidth > 2) { 6886 auto VL = makeArrayRef(&ReducedVals[i], ReduxWidth); 6887 V.buildTree(VL, ExternallyUsedValues, IgnoreList); 6888 Optional<ArrayRef<unsigned>> Order = V.bestOrder(); 6889 // TODO: Handle orders of size less than number of elements in the vector. 6890 if (Order && Order->size() == VL.size()) { 6891 // TODO: reorder tree nodes without tree rebuilding. 6892 SmallVector<Value *, 4> ReorderedOps(VL.size()); 6893 llvm::transform(*Order, ReorderedOps.begin(), 6894 [VL](const unsigned Idx) { return VL[Idx]; }); 6895 V.buildTree(ReorderedOps, ExternallyUsedValues, IgnoreList); 6896 } 6897 if (V.isTreeTinyAndNotFullyVectorizable()) 6898 break; 6899 if (V.isLoadCombineReductionCandidate(ReductionData.getOpcode())) 6900 break; 6901 6902 V.computeMinimumValueSizes(); 6903 6904 // Estimate cost. 6905 int TreeCost = V.getTreeCost(); 6906 int ReductionCost = getReductionCost(TTI, ReducedVals[i], ReduxWidth); 6907 int Cost = TreeCost + ReductionCost; 6908 if (Cost >= -SLPCostThreshold) { 6909 V.getORE()->emit([&]() { 6910 return OptimizationRemarkMissed( 6911 SV_NAME, "HorSLPNotBeneficial", cast<Instruction>(VL[0])) 6912 << "Vectorizing horizontal reduction is possible" 6913 << "but not beneficial with cost " 6914 << ore::NV("Cost", Cost) << " and threshold " 6915 << ore::NV("Threshold", -SLPCostThreshold); 6916 }); 6917 break; 6918 } 6919 6920 LLVM_DEBUG(dbgs() << "SLP: Vectorizing horizontal reduction at cost:" 6921 << Cost << ". (HorRdx)\n"); 6922 V.getORE()->emit([&]() { 6923 return OptimizationRemark( 6924 SV_NAME, "VectorizedHorizontalReduction", cast<Instruction>(VL[0])) 6925 << "Vectorized horizontal reduction with cost " 6926 << ore::NV("Cost", Cost) << " and with tree size " 6927 << ore::NV("TreeSize", V.getTreeSize()); 6928 }); 6929 6930 // Vectorize a tree. 6931 DebugLoc Loc = cast<Instruction>(ReducedVals[i])->getDebugLoc(); 6932 Value *VectorizedRoot = V.vectorizeTree(ExternallyUsedValues); 6933 6934 // Emit a reduction. For min/max, the root is a select, but the insertion 6935 // point is the compare condition of that select. 6936 Instruction *RdxRootInst = cast<Instruction>(ReductionRoot); 6937 if (ReductionData.isMinMax()) 6938 Builder.SetInsertPoint(getCmpForMinMaxReduction(RdxRootInst)); 6939 else 6940 Builder.SetInsertPoint(RdxRootInst); 6941 6942 Value *ReducedSubTree = 6943 emitReduction(VectorizedRoot, Builder, ReduxWidth, TTI); 6944 if (VectorizedTree) { 6945 Builder.SetCurrentDebugLocation(Loc); 6946 OperationData VectReductionData(ReductionData.getOpcode(), 6947 VectorizedTree, ReducedSubTree, 6948 ReductionData.getKind()); 6949 VectorizedTree = 6950 VectReductionData.createOp(Builder, "op.rdx", ReductionOps); 6951 } else 6952 VectorizedTree = ReducedSubTree; 6953 i += ReduxWidth; 6954 ReduxWidth = PowerOf2Floor(NumReducedVals - i); 6955 } 6956 6957 if (VectorizedTree) { 6958 // Finish the reduction. 6959 for (; i < NumReducedVals; ++i) { 6960 auto *I = cast<Instruction>(ReducedVals[i]); 6961 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 6962 OperationData VectReductionData(ReductionData.getOpcode(), 6963 VectorizedTree, I, 6964 ReductionData.getKind()); 6965 VectorizedTree = VectReductionData.createOp(Builder, "", ReductionOps); 6966 } 6967 for (auto &Pair : ExternallyUsedValues) { 6968 // Add each externally used value to the final reduction. 6969 for (auto *I : Pair.second) { 6970 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 6971 OperationData VectReductionData(ReductionData.getOpcode(), 6972 VectorizedTree, Pair.first, 6973 ReductionData.getKind()); 6974 VectorizedTree = VectReductionData.createOp(Builder, "op.extra", I); 6975 } 6976 } 6977 6978 // Update users. For a min/max reduction that ends with a compare and 6979 // select, we also have to RAUW for the compare instruction feeding the 6980 // reduction root. That's because the original compare may have extra uses 6981 // besides the final select of the reduction. 6982 if (ReductionData.isMinMax()) { 6983 if (auto *VecSelect = dyn_cast<SelectInst>(VectorizedTree)) { 6984 Instruction *ScalarCmp = 6985 getCmpForMinMaxReduction(cast<Instruction>(ReductionRoot)); 6986 ScalarCmp->replaceAllUsesWith(VecSelect->getCondition()); 6987 } 6988 } 6989 ReductionRoot->replaceAllUsesWith(VectorizedTree); 6990 6991 // Mark all scalar reduction ops for deletion, they are replaced by the 6992 // vector reductions. 6993 V.eraseInstructions(IgnoreList); 6994 } 6995 return VectorizedTree != nullptr; 6996 } 6997 6998 unsigned numReductionValues() const { 6999 return ReducedVals.size(); 7000 } 7001 7002 private: 7003 /// Calculate the cost of a reduction. 7004 int getReductionCost(TargetTransformInfo *TTI, Value *FirstReducedVal, 7005 unsigned ReduxWidth) { 7006 Type *ScalarTy = FirstReducedVal->getType(); 7007 auto *VecTy = FixedVectorType::get(ScalarTy, ReduxWidth); 7008 7009 int PairwiseRdxCost; 7010 int SplittingRdxCost; 7011 switch (ReductionData.getKind()) { 7012 case RK_Arithmetic: 7013 PairwiseRdxCost = 7014 TTI->getArithmeticReductionCost(ReductionData.getOpcode(), VecTy, 7015 /*IsPairwiseForm=*/true); 7016 SplittingRdxCost = 7017 TTI->getArithmeticReductionCost(ReductionData.getOpcode(), VecTy, 7018 /*IsPairwiseForm=*/false); 7019 break; 7020 case RK_Min: 7021 case RK_Max: 7022 case RK_UMin: 7023 case RK_UMax: { 7024 auto *VecCondTy = cast<VectorType>(CmpInst::makeCmpResultType(VecTy)); 7025 bool IsUnsigned = ReductionData.getKind() == RK_UMin || 7026 ReductionData.getKind() == RK_UMax; 7027 PairwiseRdxCost = 7028 TTI->getMinMaxReductionCost(VecTy, VecCondTy, 7029 /*IsPairwiseForm=*/true, IsUnsigned); 7030 SplittingRdxCost = 7031 TTI->getMinMaxReductionCost(VecTy, VecCondTy, 7032 /*IsPairwiseForm=*/false, IsUnsigned); 7033 break; 7034 } 7035 case RK_None: 7036 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 7037 } 7038 7039 IsPairwiseReduction = PairwiseRdxCost < SplittingRdxCost; 7040 int VecReduxCost = IsPairwiseReduction ? PairwiseRdxCost : SplittingRdxCost; 7041 7042 int ScalarReduxCost = 0; 7043 switch (ReductionData.getKind()) { 7044 case RK_Arithmetic: 7045 ScalarReduxCost = 7046 TTI->getArithmeticInstrCost(ReductionData.getOpcode(), ScalarTy); 7047 break; 7048 case RK_Min: 7049 case RK_Max: 7050 case RK_UMin: 7051 case RK_UMax: 7052 ScalarReduxCost = 7053 TTI->getCmpSelInstrCost(ReductionData.getOpcode(), ScalarTy) + 7054 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 7055 CmpInst::makeCmpResultType(ScalarTy)); 7056 break; 7057 case RK_None: 7058 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 7059 } 7060 ScalarReduxCost *= (ReduxWidth - 1); 7061 7062 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << VecReduxCost - ScalarReduxCost 7063 << " for reduction that starts with " << *FirstReducedVal 7064 << " (It is a " 7065 << (IsPairwiseReduction ? "pairwise" : "splitting") 7066 << " reduction)\n"); 7067 7068 return VecReduxCost - ScalarReduxCost; 7069 } 7070 7071 /// Emit a horizontal reduction of the vectorized value. 7072 Value *emitReduction(Value *VectorizedValue, IRBuilder<> &Builder, 7073 unsigned ReduxWidth, const TargetTransformInfo *TTI) { 7074 assert(VectorizedValue && "Need to have a vectorized tree node"); 7075 assert(isPowerOf2_32(ReduxWidth) && 7076 "We only handle power-of-two reductions for now"); 7077 7078 if (!IsPairwiseReduction) { 7079 // FIXME: The builder should use an FMF guard. It should not be hard-coded 7080 // to 'fast'. 7081 assert(Builder.getFastMathFlags().isFast() && "Expected 'fast' FMF"); 7082 return createSimpleTargetReduction( 7083 Builder, TTI, ReductionData.getOpcode(), VectorizedValue, 7084 ReductionData.getFlags(), ReductionOps.back()); 7085 } 7086 7087 Value *TmpVec = VectorizedValue; 7088 for (unsigned i = ReduxWidth / 2; i != 0; i >>= 1) { 7089 auto LeftMask = createRdxShuffleMask(ReduxWidth, i, true, true); 7090 auto RightMask = createRdxShuffleMask(ReduxWidth, i, true, false); 7091 7092 Value *LeftShuf = Builder.CreateShuffleVector( 7093 TmpVec, UndefValue::get(TmpVec->getType()), LeftMask, "rdx.shuf.l"); 7094 Value *RightShuf = Builder.CreateShuffleVector( 7095 TmpVec, UndefValue::get(TmpVec->getType()), (RightMask), 7096 "rdx.shuf.r"); 7097 OperationData VectReductionData(ReductionData.getOpcode(), LeftShuf, 7098 RightShuf, ReductionData.getKind()); 7099 TmpVec = VectReductionData.createOp(Builder, "op.rdx", ReductionOps); 7100 } 7101 7102 // The result is in the first element of the vector. 7103 return Builder.CreateExtractElement(TmpVec, Builder.getInt32(0)); 7104 } 7105 }; 7106 7107 } // end anonymous namespace 7108 7109 static Optional<unsigned> getAggregateSize(Instruction *InsertInst) { 7110 if (auto *IE = dyn_cast<InsertElementInst>(InsertInst)) 7111 return cast<FixedVectorType>(IE->getType())->getNumElements(); 7112 7113 unsigned AggregateSize = 1; 7114 auto *IV = cast<InsertValueInst>(InsertInst); 7115 Type *CurrentType = IV->getType(); 7116 do { 7117 if (auto *ST = dyn_cast<StructType>(CurrentType)) { 7118 for (auto *Elt : ST->elements()) 7119 if (Elt != ST->getElementType(0)) // check homogeneity 7120 return None; 7121 AggregateSize *= ST->getNumElements(); 7122 CurrentType = ST->getElementType(0); 7123 } else if (auto *AT = dyn_cast<ArrayType>(CurrentType)) { 7124 AggregateSize *= AT->getNumElements(); 7125 CurrentType = AT->getElementType(); 7126 } else if (auto *VT = dyn_cast<FixedVectorType>(CurrentType)) { 7127 AggregateSize *= VT->getNumElements(); 7128 return AggregateSize; 7129 } else if (CurrentType->isSingleValueType()) { 7130 return AggregateSize; 7131 } else { 7132 return None; 7133 } 7134 } while (true); 7135 } 7136 7137 static Optional<unsigned> getOperandIndex(Instruction *InsertInst, 7138 unsigned OperandOffset) { 7139 unsigned OperandIndex = OperandOffset; 7140 if (auto *IE = dyn_cast<InsertElementInst>(InsertInst)) { 7141 if (auto *CI = dyn_cast<ConstantInt>(IE->getOperand(2))) { 7142 auto *VT = cast<FixedVectorType>(IE->getType()); 7143 OperandIndex *= VT->getNumElements(); 7144 OperandIndex += CI->getZExtValue(); 7145 return OperandIndex; 7146 } 7147 return None; 7148 } 7149 7150 auto *IV = cast<InsertValueInst>(InsertInst); 7151 Type *CurrentType = IV->getType(); 7152 for (unsigned int Index : IV->indices()) { 7153 if (auto *ST = dyn_cast<StructType>(CurrentType)) { 7154 OperandIndex *= ST->getNumElements(); 7155 CurrentType = ST->getElementType(Index); 7156 } else if (auto *AT = dyn_cast<ArrayType>(CurrentType)) { 7157 OperandIndex *= AT->getNumElements(); 7158 CurrentType = AT->getElementType(); 7159 } else { 7160 return None; 7161 } 7162 OperandIndex += Index; 7163 } 7164 return OperandIndex; 7165 } 7166 7167 static bool findBuildAggregate_rec(Instruction *LastInsertInst, 7168 TargetTransformInfo *TTI, 7169 SmallVectorImpl<Value *> &BuildVectorOpds, 7170 SmallVectorImpl<Value *> &InsertElts, 7171 unsigned OperandOffset) { 7172 do { 7173 Value *InsertedOperand = LastInsertInst->getOperand(1); 7174 Optional<unsigned> OperandIndex = 7175 getOperandIndex(LastInsertInst, OperandOffset); 7176 if (!OperandIndex) 7177 return false; 7178 if (isa<InsertElementInst>(InsertedOperand) || 7179 isa<InsertValueInst>(InsertedOperand)) { 7180 if (!findBuildAggregate_rec(cast<Instruction>(InsertedOperand), TTI, 7181 BuildVectorOpds, InsertElts, *OperandIndex)) 7182 return false; 7183 } else { 7184 BuildVectorOpds[*OperandIndex] = InsertedOperand; 7185 InsertElts[*OperandIndex] = LastInsertInst; 7186 } 7187 if (isa<UndefValue>(LastInsertInst->getOperand(0))) 7188 return true; 7189 LastInsertInst = dyn_cast<Instruction>(LastInsertInst->getOperand(0)); 7190 } while (LastInsertInst != nullptr && 7191 (isa<InsertValueInst>(LastInsertInst) || 7192 isa<InsertElementInst>(LastInsertInst)) && 7193 LastInsertInst->hasOneUse()); 7194 return false; 7195 } 7196 7197 /// Recognize construction of vectors like 7198 /// %ra = insertelement <4 x float> undef, float %s0, i32 0 7199 /// %rb = insertelement <4 x float> %ra, float %s1, i32 1 7200 /// %rc = insertelement <4 x float> %rb, float %s2, i32 2 7201 /// %rd = insertelement <4 x float> %rc, float %s3, i32 3 7202 /// starting from the last insertelement or insertvalue instruction. 7203 /// 7204 /// Also recognize homogeneous aggregates like {<2 x float>, <2 x float>}, 7205 /// {{float, float}, {float, float}}, [2 x {float, float}] and so on. 7206 /// See llvm/test/Transforms/SLPVectorizer/X86/pr42022.ll for examples. 7207 /// 7208 /// Assume LastInsertInst is of InsertElementInst or InsertValueInst type. 7209 /// 7210 /// \return true if it matches. 7211 static bool findBuildAggregate(Instruction *LastInsertInst, 7212 TargetTransformInfo *TTI, 7213 SmallVectorImpl<Value *> &BuildVectorOpds, 7214 SmallVectorImpl<Value *> &InsertElts) { 7215 7216 assert((isa<InsertElementInst>(LastInsertInst) || 7217 isa<InsertValueInst>(LastInsertInst)) && 7218 "Expected insertelement or insertvalue instruction!"); 7219 7220 assert((BuildVectorOpds.empty() && InsertElts.empty()) && 7221 "Expected empty result vectors!"); 7222 7223 Optional<unsigned> AggregateSize = getAggregateSize(LastInsertInst); 7224 if (!AggregateSize) 7225 return false; 7226 BuildVectorOpds.resize(*AggregateSize); 7227 InsertElts.resize(*AggregateSize); 7228 7229 if (findBuildAggregate_rec(LastInsertInst, TTI, BuildVectorOpds, InsertElts, 7230 0)) { 7231 llvm::erase_if(BuildVectorOpds, 7232 [](const Value *V) { return V == nullptr; }); 7233 llvm::erase_if(InsertElts, [](const Value *V) { return V == nullptr; }); 7234 if (BuildVectorOpds.size() >= 2) 7235 return true; 7236 } 7237 7238 return false; 7239 } 7240 7241 static bool PhiTypeSorterFunc(Value *V, Value *V2) { 7242 return V->getType() < V2->getType(); 7243 } 7244 7245 /// Try and get a reduction value from a phi node. 7246 /// 7247 /// Given a phi node \p P in a block \p ParentBB, consider possible reductions 7248 /// if they come from either \p ParentBB or a containing loop latch. 7249 /// 7250 /// \returns A candidate reduction value if possible, or \code nullptr \endcode 7251 /// if not possible. 7252 static Value *getReductionValue(const DominatorTree *DT, PHINode *P, 7253 BasicBlock *ParentBB, LoopInfo *LI) { 7254 // There are situations where the reduction value is not dominated by the 7255 // reduction phi. Vectorizing such cases has been reported to cause 7256 // miscompiles. See PR25787. 7257 auto DominatedReduxValue = [&](Value *R) { 7258 return isa<Instruction>(R) && 7259 DT->dominates(P->getParent(), cast<Instruction>(R)->getParent()); 7260 }; 7261 7262 Value *Rdx = nullptr; 7263 7264 // Return the incoming value if it comes from the same BB as the phi node. 7265 if (P->getIncomingBlock(0) == ParentBB) { 7266 Rdx = P->getIncomingValue(0); 7267 } else if (P->getIncomingBlock(1) == ParentBB) { 7268 Rdx = P->getIncomingValue(1); 7269 } 7270 7271 if (Rdx && DominatedReduxValue(Rdx)) 7272 return Rdx; 7273 7274 // Otherwise, check whether we have a loop latch to look at. 7275 Loop *BBL = LI->getLoopFor(ParentBB); 7276 if (!BBL) 7277 return nullptr; 7278 BasicBlock *BBLatch = BBL->getLoopLatch(); 7279 if (!BBLatch) 7280 return nullptr; 7281 7282 // There is a loop latch, return the incoming value if it comes from 7283 // that. This reduction pattern occasionally turns up. 7284 if (P->getIncomingBlock(0) == BBLatch) { 7285 Rdx = P->getIncomingValue(0); 7286 } else if (P->getIncomingBlock(1) == BBLatch) { 7287 Rdx = P->getIncomingValue(1); 7288 } 7289 7290 if (Rdx && DominatedReduxValue(Rdx)) 7291 return Rdx; 7292 7293 return nullptr; 7294 } 7295 7296 /// Attempt to reduce a horizontal reduction. 7297 /// If it is legal to match a horizontal reduction feeding the phi node \a P 7298 /// with reduction operators \a Root (or one of its operands) in a basic block 7299 /// \a BB, then check if it can be done. If horizontal reduction is not found 7300 /// and root instruction is a binary operation, vectorization of the operands is 7301 /// attempted. 7302 /// \returns true if a horizontal reduction was matched and reduced or operands 7303 /// of one of the binary instruction were vectorized. 7304 /// \returns false if a horizontal reduction was not matched (or not possible) 7305 /// or no vectorization of any binary operation feeding \a Root instruction was 7306 /// performed. 7307 static bool tryToVectorizeHorReductionOrInstOperands( 7308 PHINode *P, Instruction *Root, BasicBlock *BB, BoUpSLP &R, 7309 TargetTransformInfo *TTI, 7310 const function_ref<bool(Instruction *, BoUpSLP &)> Vectorize) { 7311 if (!ShouldVectorizeHor) 7312 return false; 7313 7314 if (!Root) 7315 return false; 7316 7317 if (Root->getParent() != BB || isa<PHINode>(Root)) 7318 return false; 7319 // Start analysis starting from Root instruction. If horizontal reduction is 7320 // found, try to vectorize it. If it is not a horizontal reduction or 7321 // vectorization is not possible or not effective, and currently analyzed 7322 // instruction is a binary operation, try to vectorize the operands, using 7323 // pre-order DFS traversal order. If the operands were not vectorized, repeat 7324 // the same procedure considering each operand as a possible root of the 7325 // horizontal reduction. 7326 // Interrupt the process if the Root instruction itself was vectorized or all 7327 // sub-trees not higher that RecursionMaxDepth were analyzed/vectorized. 7328 SmallVector<std::pair<Instruction *, unsigned>, 8> Stack(1, {Root, 0}); 7329 SmallPtrSet<Value *, 8> VisitedInstrs; 7330 bool Res = false; 7331 while (!Stack.empty()) { 7332 Instruction *Inst; 7333 unsigned Level; 7334 std::tie(Inst, Level) = Stack.pop_back_val(); 7335 auto *BI = dyn_cast<BinaryOperator>(Inst); 7336 auto *SI = dyn_cast<SelectInst>(Inst); 7337 if (BI || SI) { 7338 HorizontalReduction HorRdx; 7339 if (HorRdx.matchAssociativeReduction(P, Inst)) { 7340 if (HorRdx.tryToReduce(R, TTI)) { 7341 Res = true; 7342 // Set P to nullptr to avoid re-analysis of phi node in 7343 // matchAssociativeReduction function unless this is the root node. 7344 P = nullptr; 7345 continue; 7346 } 7347 } 7348 if (P && BI) { 7349 Inst = dyn_cast<Instruction>(BI->getOperand(0)); 7350 if (Inst == P) 7351 Inst = dyn_cast<Instruction>(BI->getOperand(1)); 7352 if (!Inst) { 7353 // Set P to nullptr to avoid re-analysis of phi node in 7354 // matchAssociativeReduction function unless this is the root node. 7355 P = nullptr; 7356 continue; 7357 } 7358 } 7359 } 7360 // Set P to nullptr to avoid re-analysis of phi node in 7361 // matchAssociativeReduction function unless this is the root node. 7362 P = nullptr; 7363 if (Vectorize(Inst, R)) { 7364 Res = true; 7365 continue; 7366 } 7367 7368 // Try to vectorize operands. 7369 // Continue analysis for the instruction from the same basic block only to 7370 // save compile time. 7371 if (++Level < RecursionMaxDepth) 7372 for (auto *Op : Inst->operand_values()) 7373 if (VisitedInstrs.insert(Op).second) 7374 if (auto *I = dyn_cast<Instruction>(Op)) 7375 if (!isa<PHINode>(I) && !R.isDeleted(I) && I->getParent() == BB) 7376 Stack.emplace_back(I, Level); 7377 } 7378 return Res; 7379 } 7380 7381 bool SLPVectorizerPass::vectorizeRootInstruction(PHINode *P, Value *V, 7382 BasicBlock *BB, BoUpSLP &R, 7383 TargetTransformInfo *TTI) { 7384 if (!V) 7385 return false; 7386 auto *I = dyn_cast<Instruction>(V); 7387 if (!I) 7388 return false; 7389 7390 if (!isa<BinaryOperator>(I)) 7391 P = nullptr; 7392 // Try to match and vectorize a horizontal reduction. 7393 auto &&ExtraVectorization = [this](Instruction *I, BoUpSLP &R) -> bool { 7394 return tryToVectorize(I, R); 7395 }; 7396 return tryToVectorizeHorReductionOrInstOperands(P, I, BB, R, TTI, 7397 ExtraVectorization); 7398 } 7399 7400 bool SLPVectorizerPass::vectorizeInsertValueInst(InsertValueInst *IVI, 7401 BasicBlock *BB, BoUpSLP &R) { 7402 const DataLayout &DL = BB->getModule()->getDataLayout(); 7403 if (!R.canMapToVector(IVI->getType(), DL)) 7404 return false; 7405 7406 SmallVector<Value *, 16> BuildVectorOpds; 7407 SmallVector<Value *, 16> BuildVectorInsts; 7408 if (!findBuildAggregate(IVI, TTI, BuildVectorOpds, BuildVectorInsts)) 7409 return false; 7410 7411 LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IVI << "\n"); 7412 // Aggregate value is unlikely to be processed in vector register, we need to 7413 // extract scalars into scalar registers, so NeedExtraction is set true. 7414 return tryToVectorizeList(BuildVectorOpds, R, /*AllowReorder=*/false, 7415 BuildVectorInsts); 7416 } 7417 7418 bool SLPVectorizerPass::vectorizeInsertElementInst(InsertElementInst *IEI, 7419 BasicBlock *BB, BoUpSLP &R) { 7420 SmallVector<Value *, 16> BuildVectorInsts; 7421 SmallVector<Value *, 16> BuildVectorOpds; 7422 if (!findBuildAggregate(IEI, TTI, BuildVectorOpds, BuildVectorInsts) || 7423 (llvm::all_of(BuildVectorOpds, 7424 [](Value *V) { return isa<ExtractElementInst>(V); }) && 7425 isShuffle(BuildVectorOpds))) 7426 return false; 7427 7428 // Vectorize starting with the build vector operands ignoring the BuildVector 7429 // instructions for the purpose of scheduling and user extraction. 7430 return tryToVectorizeList(BuildVectorOpds, R, /*AllowReorder=*/false, 7431 BuildVectorInsts); 7432 } 7433 7434 bool SLPVectorizerPass::vectorizeCmpInst(CmpInst *CI, BasicBlock *BB, 7435 BoUpSLP &R) { 7436 if (tryToVectorizePair(CI->getOperand(0), CI->getOperand(1), R)) 7437 return true; 7438 7439 bool OpsChanged = false; 7440 for (int Idx = 0; Idx < 2; ++Idx) { 7441 OpsChanged |= 7442 vectorizeRootInstruction(nullptr, CI->getOperand(Idx), BB, R, TTI); 7443 } 7444 return OpsChanged; 7445 } 7446 7447 bool SLPVectorizerPass::vectorizeSimpleInstructions( 7448 SmallVectorImpl<Instruction *> &Instructions, BasicBlock *BB, BoUpSLP &R) { 7449 bool OpsChanged = false; 7450 for (auto *I : reverse(Instructions)) { 7451 if (R.isDeleted(I)) 7452 continue; 7453 if (auto *LastInsertValue = dyn_cast<InsertValueInst>(I)) 7454 OpsChanged |= vectorizeInsertValueInst(LastInsertValue, BB, R); 7455 else if (auto *LastInsertElem = dyn_cast<InsertElementInst>(I)) 7456 OpsChanged |= vectorizeInsertElementInst(LastInsertElem, BB, R); 7457 else if (auto *CI = dyn_cast<CmpInst>(I)) 7458 OpsChanged |= vectorizeCmpInst(CI, BB, R); 7459 } 7460 Instructions.clear(); 7461 return OpsChanged; 7462 } 7463 7464 bool SLPVectorizerPass::vectorizeChainsInBlock(BasicBlock *BB, BoUpSLP &R) { 7465 bool Changed = false; 7466 SmallVector<Value *, 4> Incoming; 7467 SmallPtrSet<Value *, 16> VisitedInstrs; 7468 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 7469 7470 bool HaveVectorizedPhiNodes = true; 7471 while (HaveVectorizedPhiNodes) { 7472 HaveVectorizedPhiNodes = false; 7473 7474 // Collect the incoming values from the PHIs. 7475 Incoming.clear(); 7476 for (Instruction &I : *BB) { 7477 PHINode *P = dyn_cast<PHINode>(&I); 7478 if (!P) 7479 break; 7480 7481 if (!VisitedInstrs.count(P) && !R.isDeleted(P)) 7482 Incoming.push_back(P); 7483 } 7484 7485 // Sort by type. 7486 llvm::stable_sort(Incoming, PhiTypeSorterFunc); 7487 7488 // Try to vectorize elements base on their type. 7489 for (SmallVector<Value *, 4>::iterator IncIt = Incoming.begin(), 7490 E = Incoming.end(); 7491 IncIt != E;) { 7492 7493 // Look for the next elements with the same type. 7494 SmallVector<Value *, 4>::iterator SameTypeIt = IncIt; 7495 Type *EltTy = (*IncIt)->getType(); 7496 7497 assert(EltTy->isSized() && 7498 "Instructions should all be sized at this point"); 7499 TypeSize EltTS = DL->getTypeSizeInBits(EltTy); 7500 if (EltTS.isScalable()) { 7501 // For now, just ignore vectorizing scalable types. 7502 ++IncIt; 7503 continue; 7504 } 7505 7506 unsigned EltSize = EltTS.getFixedSize(); 7507 unsigned MaxNumElts = MaxVecRegSize / EltSize; 7508 if (MaxNumElts < 2) { 7509 ++IncIt; 7510 continue; 7511 } 7512 7513 while (SameTypeIt != E && 7514 (*SameTypeIt)->getType() == EltTy && 7515 static_cast<unsigned>(SameTypeIt - IncIt) < MaxNumElts) { 7516 VisitedInstrs.insert(*SameTypeIt); 7517 ++SameTypeIt; 7518 } 7519 7520 // Try to vectorize them. 7521 unsigned NumElts = (SameTypeIt - IncIt); 7522 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize starting at PHIs (" 7523 << NumElts << ")\n"); 7524 // The order in which the phi nodes appear in the program does not matter. 7525 // So allow tryToVectorizeList to reorder them if it is beneficial. This 7526 // is done when there are exactly two elements since tryToVectorizeList 7527 // asserts that there are only two values when AllowReorder is true. 7528 bool AllowReorder = NumElts == 2; 7529 if (NumElts > 1 && 7530 tryToVectorizeList(makeArrayRef(IncIt, NumElts), R, AllowReorder)) { 7531 // Success start over because instructions might have been changed. 7532 HaveVectorizedPhiNodes = true; 7533 Changed = true; 7534 break; 7535 } 7536 7537 // Start over at the next instruction of a different type (or the end). 7538 IncIt = SameTypeIt; 7539 } 7540 } 7541 7542 VisitedInstrs.clear(); 7543 7544 SmallVector<Instruction *, 8> PostProcessInstructions; 7545 SmallDenseSet<Instruction *, 4> KeyNodes; 7546 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 7547 // Skip instructions marked for the deletion. 7548 if (R.isDeleted(&*it)) 7549 continue; 7550 // We may go through BB multiple times so skip the one we have checked. 7551 if (!VisitedInstrs.insert(&*it).second) { 7552 if (it->use_empty() && KeyNodes.count(&*it) > 0 && 7553 vectorizeSimpleInstructions(PostProcessInstructions, BB, R)) { 7554 // We would like to start over since some instructions are deleted 7555 // and the iterator may become invalid value. 7556 Changed = true; 7557 it = BB->begin(); 7558 e = BB->end(); 7559 } 7560 continue; 7561 } 7562 7563 if (isa<DbgInfoIntrinsic>(it)) 7564 continue; 7565 7566 // Try to vectorize reductions that use PHINodes. 7567 if (PHINode *P = dyn_cast<PHINode>(it)) { 7568 // Check that the PHI is a reduction PHI. 7569 if (P->getNumIncomingValues() != 2) 7570 return Changed; 7571 7572 // Try to match and vectorize a horizontal reduction. 7573 if (vectorizeRootInstruction(P, getReductionValue(DT, P, BB, LI), BB, R, 7574 TTI)) { 7575 Changed = true; 7576 it = BB->begin(); 7577 e = BB->end(); 7578 continue; 7579 } 7580 continue; 7581 } 7582 7583 // Ran into an instruction without users, like terminator, or function call 7584 // with ignored return value, store. Ignore unused instructions (basing on 7585 // instruction type, except for CallInst and InvokeInst). 7586 if (it->use_empty() && (it->getType()->isVoidTy() || isa<CallInst>(it) || 7587 isa<InvokeInst>(it))) { 7588 KeyNodes.insert(&*it); 7589 bool OpsChanged = false; 7590 if (ShouldStartVectorizeHorAtStore || !isa<StoreInst>(it)) { 7591 for (auto *V : it->operand_values()) { 7592 // Try to match and vectorize a horizontal reduction. 7593 OpsChanged |= vectorizeRootInstruction(nullptr, V, BB, R, TTI); 7594 } 7595 } 7596 // Start vectorization of post-process list of instructions from the 7597 // top-tree instructions to try to vectorize as many instructions as 7598 // possible. 7599 OpsChanged |= vectorizeSimpleInstructions(PostProcessInstructions, BB, R); 7600 if (OpsChanged) { 7601 // We would like to start over since some instructions are deleted 7602 // and the iterator may become invalid value. 7603 Changed = true; 7604 it = BB->begin(); 7605 e = BB->end(); 7606 continue; 7607 } 7608 } 7609 7610 if (isa<InsertElementInst>(it) || isa<CmpInst>(it) || 7611 isa<InsertValueInst>(it)) 7612 PostProcessInstructions.push_back(&*it); 7613 } 7614 7615 return Changed; 7616 } 7617 7618 bool SLPVectorizerPass::vectorizeGEPIndices(BasicBlock *BB, BoUpSLP &R) { 7619 auto Changed = false; 7620 for (auto &Entry : GEPs) { 7621 // If the getelementptr list has fewer than two elements, there's nothing 7622 // to do. 7623 if (Entry.second.size() < 2) 7624 continue; 7625 7626 LLVM_DEBUG(dbgs() << "SLP: Analyzing a getelementptr list of length " 7627 << Entry.second.size() << ".\n"); 7628 7629 // Process the GEP list in chunks suitable for the target's supported 7630 // vector size. If a vector register can't hold 1 element, we are done. We 7631 // are trying to vectorize the index computations, so the maximum number of 7632 // elements is based on the size of the index expression, rather than the 7633 // size of the GEP itself (the target's pointer size). 7634 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 7635 unsigned EltSize = R.getVectorElementSize(*Entry.second[0]->idx_begin()); 7636 if (MaxVecRegSize < EltSize) 7637 continue; 7638 7639 unsigned MaxElts = MaxVecRegSize / EltSize; 7640 for (unsigned BI = 0, BE = Entry.second.size(); BI < BE; BI += MaxElts) { 7641 auto Len = std::min<unsigned>(BE - BI, MaxElts); 7642 auto GEPList = makeArrayRef(&Entry.second[BI], Len); 7643 7644 // Initialize a set a candidate getelementptrs. Note that we use a 7645 // SetVector here to preserve program order. If the index computations 7646 // are vectorizable and begin with loads, we want to minimize the chance 7647 // of having to reorder them later. 7648 SetVector<Value *> Candidates(GEPList.begin(), GEPList.end()); 7649 7650 // Some of the candidates may have already been vectorized after we 7651 // initially collected them. If so, they are marked as deleted, so remove 7652 // them from the set of candidates. 7653 Candidates.remove_if( 7654 [&R](Value *I) { return R.isDeleted(cast<Instruction>(I)); }); 7655 7656 // Remove from the set of candidates all pairs of getelementptrs with 7657 // constant differences. Such getelementptrs are likely not good 7658 // candidates for vectorization in a bottom-up phase since one can be 7659 // computed from the other. We also ensure all candidate getelementptr 7660 // indices are unique. 7661 for (int I = 0, E = GEPList.size(); I < E && Candidates.size() > 1; ++I) { 7662 auto *GEPI = GEPList[I]; 7663 if (!Candidates.count(GEPI)) 7664 continue; 7665 auto *SCEVI = SE->getSCEV(GEPList[I]); 7666 for (int J = I + 1; J < E && Candidates.size() > 1; ++J) { 7667 auto *GEPJ = GEPList[J]; 7668 auto *SCEVJ = SE->getSCEV(GEPList[J]); 7669 if (isa<SCEVConstant>(SE->getMinusSCEV(SCEVI, SCEVJ))) { 7670 Candidates.remove(GEPI); 7671 Candidates.remove(GEPJ); 7672 } else if (GEPI->idx_begin()->get() == GEPJ->idx_begin()->get()) { 7673 Candidates.remove(GEPJ); 7674 } 7675 } 7676 } 7677 7678 // We break out of the above computation as soon as we know there are 7679 // fewer than two candidates remaining. 7680 if (Candidates.size() < 2) 7681 continue; 7682 7683 // Add the single, non-constant index of each candidate to the bundle. We 7684 // ensured the indices met these constraints when we originally collected 7685 // the getelementptrs. 7686 SmallVector<Value *, 16> Bundle(Candidates.size()); 7687 auto BundleIndex = 0u; 7688 for (auto *V : Candidates) { 7689 auto *GEP = cast<GetElementPtrInst>(V); 7690 auto *GEPIdx = GEP->idx_begin()->get(); 7691 assert(GEP->getNumIndices() == 1 || !isa<Constant>(GEPIdx)); 7692 Bundle[BundleIndex++] = GEPIdx; 7693 } 7694 7695 // Try and vectorize the indices. We are currently only interested in 7696 // gather-like cases of the form: 7697 // 7698 // ... = g[a[0] - b[0]] + g[a[1] - b[1]] + ... 7699 // 7700 // where the loads of "a", the loads of "b", and the subtractions can be 7701 // performed in parallel. It's likely that detecting this pattern in a 7702 // bottom-up phase will be simpler and less costly than building a 7703 // full-blown top-down phase beginning at the consecutive loads. 7704 Changed |= tryToVectorizeList(Bundle, R); 7705 } 7706 } 7707 return Changed; 7708 } 7709 7710 bool SLPVectorizerPass::vectorizeStoreChains(BoUpSLP &R) { 7711 bool Changed = false; 7712 // Attempt to sort and vectorize each of the store-groups. 7713 for (StoreListMap::iterator it = Stores.begin(), e = Stores.end(); it != e; 7714 ++it) { 7715 if (it->second.size() < 2) 7716 continue; 7717 7718 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " 7719 << it->second.size() << ".\n"); 7720 7721 Changed |= vectorizeStores(it->second, R); 7722 } 7723 return Changed; 7724 } 7725 7726 char SLPVectorizer::ID = 0; 7727 7728 static const char lv_name[] = "SLP Vectorizer"; 7729 7730 INITIALIZE_PASS_BEGIN(SLPVectorizer, SV_NAME, lv_name, false, false) 7731 INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass) 7732 INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass) 7733 INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker) 7734 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass) 7735 INITIALIZE_PASS_DEPENDENCY(LoopSimplify) 7736 INITIALIZE_PASS_DEPENDENCY(DemandedBitsWrapperPass) 7737 INITIALIZE_PASS_DEPENDENCY(OptimizationRemarkEmitterWrapperPass) 7738 INITIALIZE_PASS_DEPENDENCY(InjectTLIMappingsLegacy) 7739 INITIALIZE_PASS_END(SLPVectorizer, SV_NAME, lv_name, false, false) 7740 7741 Pass *llvm::createSLPVectorizerPass() { return new SLPVectorizer(); } 7742