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