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/SmallPtrSet.h" 30 #include "llvm/ADT/SmallSet.h" 31 #include "llvm/ADT/SmallVector.h" 32 #include "llvm/ADT/Statistic.h" 33 #include "llvm/ADT/iterator.h" 34 #include "llvm/ADT/iterator_range.h" 35 #include "llvm/Analysis/AliasAnalysis.h" 36 #include "llvm/Analysis/CodeMetrics.h" 37 #include "llvm/Analysis/DemandedBits.h" 38 #include "llvm/Analysis/GlobalsModRef.h" 39 #include "llvm/Analysis/LoopAccessAnalysis.h" 40 #include "llvm/Analysis/LoopInfo.h" 41 #include "llvm/Analysis/MemoryLocation.h" 42 #include "llvm/Analysis/OptimizationRemarkEmitter.h" 43 #include "llvm/Analysis/ScalarEvolution.h" 44 #include "llvm/Analysis/ScalarEvolutionExpressions.h" 45 #include "llvm/Analysis/TargetLibraryInfo.h" 46 #include "llvm/Analysis/TargetTransformInfo.h" 47 #include "llvm/Analysis/ValueTracking.h" 48 #include "llvm/Analysis/VectorUtils.h" 49 #include "llvm/IR/Attributes.h" 50 #include "llvm/IR/BasicBlock.h" 51 #include "llvm/IR/Constant.h" 52 #include "llvm/IR/Constants.h" 53 #include "llvm/IR/DataLayout.h" 54 #include "llvm/IR/DebugLoc.h" 55 #include "llvm/IR/DerivedTypes.h" 56 #include "llvm/IR/Dominators.h" 57 #include "llvm/IR/Function.h" 58 #include "llvm/IR/IRBuilder.h" 59 #include "llvm/IR/InstrTypes.h" 60 #include "llvm/IR/Instruction.h" 61 #include "llvm/IR/Instructions.h" 62 #include "llvm/IR/IntrinsicInst.h" 63 #include "llvm/IR/Intrinsics.h" 64 #include "llvm/IR/Module.h" 65 #include "llvm/IR/NoFolder.h" 66 #include "llvm/IR/Operator.h" 67 #include "llvm/IR/PassManager.h" 68 #include "llvm/IR/PatternMatch.h" 69 #include "llvm/IR/Type.h" 70 #include "llvm/IR/Use.h" 71 #include "llvm/IR/User.h" 72 #include "llvm/IR/Value.h" 73 #include "llvm/IR/ValueHandle.h" 74 #include "llvm/IR/Verifier.h" 75 #include "llvm/Pass.h" 76 #include "llvm/Support/Casting.h" 77 #include "llvm/Support/CommandLine.h" 78 #include "llvm/Support/Compiler.h" 79 #include "llvm/Support/DOTGraphTraits.h" 80 #include "llvm/Support/Debug.h" 81 #include "llvm/Support/ErrorHandling.h" 82 #include "llvm/Support/GraphWriter.h" 83 #include "llvm/Support/KnownBits.h" 84 #include "llvm/Support/MathExtras.h" 85 #include "llvm/Support/raw_ostream.h" 86 #include "llvm/Transforms/Utils/LoopUtils.h" 87 #include "llvm/Transforms/Vectorize.h" 88 #include <algorithm> 89 #include <cassert> 90 #include <cstdint> 91 #include <iterator> 92 #include <memory> 93 #include <set> 94 #include <string> 95 #include <tuple> 96 #include <utility> 97 #include <vector> 98 99 using namespace llvm; 100 using namespace llvm::PatternMatch; 101 using namespace slpvectorizer; 102 103 #define SV_NAME "slp-vectorizer" 104 #define DEBUG_TYPE "SLP" 105 106 STATISTIC(NumVectorInstructions, "Number of vector instructions generated"); 107 108 cl::opt<bool> 109 llvm::RunSLPVectorization("vectorize-slp", cl::init(false), cl::Hidden, 110 cl::desc("Run the SLP vectorization passes")); 111 112 static cl::opt<int> 113 SLPCostThreshold("slp-threshold", cl::init(0), cl::Hidden, 114 cl::desc("Only vectorize if you gain more than this " 115 "number ")); 116 117 static cl::opt<bool> 118 ShouldVectorizeHor("slp-vectorize-hor", cl::init(true), cl::Hidden, 119 cl::desc("Attempt to vectorize horizontal reductions")); 120 121 static cl::opt<bool> ShouldStartVectorizeHorAtStore( 122 "slp-vectorize-hor-store", cl::init(false), cl::Hidden, 123 cl::desc( 124 "Attempt to vectorize horizontal reductions feeding into a store")); 125 126 static cl::opt<int> 127 MaxVectorRegSizeOption("slp-max-reg-size", cl::init(128), cl::Hidden, 128 cl::desc("Attempt to vectorize for this register size in bits")); 129 130 /// Limits the size of scheduling regions in a block. 131 /// It avoid long compile times for _very_ large blocks where vector 132 /// instructions are spread over a wide range. 133 /// This limit is way higher than needed by real-world functions. 134 static cl::opt<int> 135 ScheduleRegionSizeBudget("slp-schedule-budget", cl::init(100000), cl::Hidden, 136 cl::desc("Limit the size of the SLP scheduling region per block")); 137 138 static cl::opt<int> MinVectorRegSizeOption( 139 "slp-min-reg-size", cl::init(128), cl::Hidden, 140 cl::desc("Attempt to vectorize for this register size in bits")); 141 142 static cl::opt<unsigned> RecursionMaxDepth( 143 "slp-recursion-max-depth", cl::init(12), cl::Hidden, 144 cl::desc("Limit the recursion depth when building a vectorizable tree")); 145 146 static cl::opt<unsigned> MinTreeSize( 147 "slp-min-tree-size", cl::init(3), cl::Hidden, 148 cl::desc("Only vectorize small trees if they are fully vectorizable")); 149 150 // The maximum depth that the look-ahead score heuristic will explore. 151 // The higher this value, the higher the compilation time overhead. 152 static cl::opt<int> LookAheadMaxDepth( 153 "slp-max-look-ahead-depth", cl::init(2), cl::Hidden, 154 cl::desc("The maximum look-ahead depth for operand reordering scores")); 155 156 // The Look-ahead heuristic goes through the users of the bundle to calculate 157 // the users cost in getExternalUsesCost(). To avoid compilation time increase 158 // we limit the number of users visited to this value. 159 static cl::opt<unsigned> LookAheadUsersBudget( 160 "slp-look-ahead-users-budget", cl::init(2), cl::Hidden, 161 cl::desc("The maximum number of users to visit while visiting the " 162 "predecessors. This prevents compilation time increase.")); 163 164 static cl::opt<bool> 165 ViewSLPTree("view-slp-tree", cl::Hidden, 166 cl::desc("Display the SLP trees with Graphviz")); 167 168 // Limit the number of alias checks. The limit is chosen so that 169 // it has no negative effect on the llvm benchmarks. 170 static const unsigned AliasedCheckLimit = 10; 171 172 // Another limit for the alias checks: The maximum distance between load/store 173 // instructions where alias checks are done. 174 // This limit is useful for very large basic blocks. 175 static const unsigned MaxMemDepDistance = 160; 176 177 /// If the ScheduleRegionSizeBudget is exhausted, we allow small scheduling 178 /// regions to be handled. 179 static const int MinScheduleRegionSize = 16; 180 181 /// Predicate for the element types that the SLP vectorizer supports. 182 /// 183 /// The most important thing to filter here are types which are invalid in LLVM 184 /// vectors. We also filter target specific types which have absolutely no 185 /// meaningful vectorization path such as x86_fp80 and ppc_f128. This just 186 /// avoids spending time checking the cost model and realizing that they will 187 /// be inevitably scalarized. 188 static bool isValidElementType(Type *Ty) { 189 return VectorType::isValidElementType(Ty) && !Ty->isX86_FP80Ty() && 190 !Ty->isPPC_FP128Ty(); 191 } 192 193 /// \returns true if all of the instructions in \p VL are in the same block or 194 /// false otherwise. 195 static bool allSameBlock(ArrayRef<Value *> VL) { 196 Instruction *I0 = dyn_cast<Instruction>(VL[0]); 197 if (!I0) 198 return false; 199 BasicBlock *BB = I0->getParent(); 200 for (int i = 1, e = VL.size(); i < e; i++) { 201 Instruction *I = dyn_cast<Instruction>(VL[i]); 202 if (!I) 203 return false; 204 205 if (BB != I->getParent()) 206 return false; 207 } 208 return true; 209 } 210 211 /// \returns True if all of the values in \p VL are constants (but not 212 /// globals/constant expressions). 213 static bool allConstant(ArrayRef<Value *> VL) { 214 // Constant expressions and globals can't be vectorized like normal integer/FP 215 // constants. 216 for (Value *i : VL) 217 if (!isa<Constant>(i) || isa<ConstantExpr>(i) || isa<GlobalValue>(i)) 218 return false; 219 return true; 220 } 221 222 /// \returns True if all of the values in \p VL are identical. 223 static bool isSplat(ArrayRef<Value *> VL) { 224 for (unsigned i = 1, e = VL.size(); i < e; ++i) 225 if (VL[i] != VL[0]) 226 return false; 227 return true; 228 } 229 230 /// \returns True if \p I is commutative, handles CmpInst as well as Instruction. 231 static bool isCommutative(Instruction *I) { 232 if (auto *IC = dyn_cast<CmpInst>(I)) 233 return IC->isCommutative(); 234 return I->isCommutative(); 235 } 236 237 /// Checks if the vector of instructions can be represented as a shuffle, like: 238 /// %x0 = extractelement <4 x i8> %x, i32 0 239 /// %x3 = extractelement <4 x i8> %x, i32 3 240 /// %y1 = extractelement <4 x i8> %y, i32 1 241 /// %y2 = extractelement <4 x i8> %y, i32 2 242 /// %x0x0 = mul i8 %x0, %x0 243 /// %x3x3 = mul i8 %x3, %x3 244 /// %y1y1 = mul i8 %y1, %y1 245 /// %y2y2 = mul i8 %y2, %y2 246 /// %ins1 = insertelement <4 x i8> undef, i8 %x0x0, i32 0 247 /// %ins2 = insertelement <4 x i8> %ins1, i8 %x3x3, i32 1 248 /// %ins3 = insertelement <4 x i8> %ins2, i8 %y1y1, i32 2 249 /// %ins4 = insertelement <4 x i8> %ins3, i8 %y2y2, i32 3 250 /// ret <4 x i8> %ins4 251 /// can be transformed into: 252 /// %1 = shufflevector <4 x i8> %x, <4 x i8> %y, <4 x i32> <i32 0, i32 3, i32 5, 253 /// i32 6> 254 /// %2 = mul <4 x i8> %1, %1 255 /// ret <4 x i8> %2 256 /// We convert this initially to something like: 257 /// %x0 = extractelement <4 x i8> %x, i32 0 258 /// %x3 = extractelement <4 x i8> %x, i32 3 259 /// %y1 = extractelement <4 x i8> %y, i32 1 260 /// %y2 = extractelement <4 x i8> %y, i32 2 261 /// %1 = insertelement <4 x i8> undef, i8 %x0, i32 0 262 /// %2 = insertelement <4 x i8> %1, i8 %x3, i32 1 263 /// %3 = insertelement <4 x i8> %2, i8 %y1, i32 2 264 /// %4 = insertelement <4 x i8> %3, i8 %y2, i32 3 265 /// %5 = mul <4 x i8> %4, %4 266 /// %6 = extractelement <4 x i8> %5, i32 0 267 /// %ins1 = insertelement <4 x i8> undef, i8 %6, i32 0 268 /// %7 = extractelement <4 x i8> %5, i32 1 269 /// %ins2 = insertelement <4 x i8> %ins1, i8 %7, i32 1 270 /// %8 = extractelement <4 x i8> %5, i32 2 271 /// %ins3 = insertelement <4 x i8> %ins2, i8 %8, i32 2 272 /// %9 = extractelement <4 x i8> %5, i32 3 273 /// %ins4 = insertelement <4 x i8> %ins3, i8 %9, i32 3 274 /// ret <4 x i8> %ins4 275 /// InstCombiner transforms this into a shuffle and vector mul 276 /// TODO: Can we split off and reuse the shuffle mask detection from 277 /// TargetTransformInfo::getInstructionThroughput? 278 static Optional<TargetTransformInfo::ShuffleKind> 279 isShuffle(ArrayRef<Value *> VL) { 280 auto *EI0 = cast<ExtractElementInst>(VL[0]); 281 unsigned Size = EI0->getVectorOperandType()->getVectorNumElements(); 282 Value *Vec1 = nullptr; 283 Value *Vec2 = nullptr; 284 enum ShuffleMode { Unknown, Select, Permute }; 285 ShuffleMode CommonShuffleMode = Unknown; 286 for (unsigned I = 0, E = VL.size(); I < E; ++I) { 287 auto *EI = cast<ExtractElementInst>(VL[I]); 288 auto *Vec = EI->getVectorOperand(); 289 // All vector operands must have the same number of vector elements. 290 if (Vec->getType()->getVectorNumElements() != Size) 291 return None; 292 auto *Idx = dyn_cast<ConstantInt>(EI->getIndexOperand()); 293 if (!Idx) 294 return None; 295 // Undefined behavior if Idx is negative or >= Size. 296 if (Idx->getValue().uge(Size)) 297 continue; 298 unsigned IntIdx = Idx->getValue().getZExtValue(); 299 // We can extractelement from undef vector. 300 if (isa<UndefValue>(Vec)) 301 continue; 302 // For correct shuffling we have to have at most 2 different vector operands 303 // in all extractelement instructions. 304 if (!Vec1 || Vec1 == Vec) 305 Vec1 = Vec; 306 else if (!Vec2 || Vec2 == Vec) 307 Vec2 = Vec; 308 else 309 return None; 310 if (CommonShuffleMode == Permute) 311 continue; 312 // If the extract index is not the same as the operation number, it is a 313 // permutation. 314 if (IntIdx != I) { 315 CommonShuffleMode = Permute; 316 continue; 317 } 318 CommonShuffleMode = Select; 319 } 320 // If we're not crossing lanes in different vectors, consider it as blending. 321 if (CommonShuffleMode == Select && Vec2) 322 return TargetTransformInfo::SK_Select; 323 // If Vec2 was never used, we have a permutation of a single vector, otherwise 324 // we have permutation of 2 vectors. 325 return Vec2 ? TargetTransformInfo::SK_PermuteTwoSrc 326 : TargetTransformInfo::SK_PermuteSingleSrc; 327 } 328 329 namespace { 330 331 /// Main data required for vectorization of instructions. 332 struct InstructionsState { 333 /// The very first instruction in the list with the main opcode. 334 Value *OpValue = nullptr; 335 336 /// The main/alternate instruction. 337 Instruction *MainOp = nullptr; 338 Instruction *AltOp = nullptr; 339 340 /// The main/alternate opcodes for the list of instructions. 341 unsigned getOpcode() const { 342 return MainOp ? MainOp->getOpcode() : 0; 343 } 344 345 unsigned getAltOpcode() const { 346 return AltOp ? AltOp->getOpcode() : 0; 347 } 348 349 /// Some of the instructions in the list have alternate opcodes. 350 bool isAltShuffle() const { return getOpcode() != getAltOpcode(); } 351 352 bool isOpcodeOrAlt(Instruction *I) const { 353 unsigned CheckedOpcode = I->getOpcode(); 354 return getOpcode() == CheckedOpcode || getAltOpcode() == CheckedOpcode; 355 } 356 357 InstructionsState() = delete; 358 InstructionsState(Value *OpValue, Instruction *MainOp, Instruction *AltOp) 359 : OpValue(OpValue), MainOp(MainOp), AltOp(AltOp) {} 360 }; 361 362 } // end anonymous namespace 363 364 /// Chooses the correct key for scheduling data. If \p Op has the same (or 365 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is \p 366 /// OpValue. 367 static Value *isOneOf(const InstructionsState &S, Value *Op) { 368 auto *I = dyn_cast<Instruction>(Op); 369 if (I && S.isOpcodeOrAlt(I)) 370 return Op; 371 return S.OpValue; 372 } 373 374 /// \returns analysis of the Instructions in \p VL described in 375 /// InstructionsState, the Opcode that we suppose the whole list 376 /// could be vectorized even if its structure is diverse. 377 static InstructionsState getSameOpcode(ArrayRef<Value *> VL, 378 unsigned BaseIndex = 0) { 379 // Make sure these are all Instructions. 380 if (llvm::any_of(VL, [](Value *V) { return !isa<Instruction>(V); })) 381 return InstructionsState(VL[BaseIndex], nullptr, nullptr); 382 383 bool IsCastOp = isa<CastInst>(VL[BaseIndex]); 384 bool IsBinOp = isa<BinaryOperator>(VL[BaseIndex]); 385 unsigned Opcode = cast<Instruction>(VL[BaseIndex])->getOpcode(); 386 unsigned AltOpcode = Opcode; 387 unsigned AltIndex = BaseIndex; 388 389 // Check for one alternate opcode from another BinaryOperator. 390 // TODO - generalize to support all operators (types, calls etc.). 391 for (int Cnt = 0, E = VL.size(); Cnt < E; Cnt++) { 392 unsigned InstOpcode = cast<Instruction>(VL[Cnt])->getOpcode(); 393 if (IsBinOp && isa<BinaryOperator>(VL[Cnt])) { 394 if (InstOpcode == Opcode || InstOpcode == AltOpcode) 395 continue; 396 if (Opcode == AltOpcode) { 397 AltOpcode = InstOpcode; 398 AltIndex = Cnt; 399 continue; 400 } 401 } else if (IsCastOp && isa<CastInst>(VL[Cnt])) { 402 Type *Ty0 = cast<Instruction>(VL[BaseIndex])->getOperand(0)->getType(); 403 Type *Ty1 = cast<Instruction>(VL[Cnt])->getOperand(0)->getType(); 404 if (Ty0 == Ty1) { 405 if (InstOpcode == Opcode || InstOpcode == AltOpcode) 406 continue; 407 if (Opcode == AltOpcode) { 408 AltOpcode = InstOpcode; 409 AltIndex = Cnt; 410 continue; 411 } 412 } 413 } else if (InstOpcode == Opcode || InstOpcode == AltOpcode) 414 continue; 415 return InstructionsState(VL[BaseIndex], nullptr, nullptr); 416 } 417 418 return InstructionsState(VL[BaseIndex], cast<Instruction>(VL[BaseIndex]), 419 cast<Instruction>(VL[AltIndex])); 420 } 421 422 /// \returns true if all of the values in \p VL have the same type or false 423 /// otherwise. 424 static bool allSameType(ArrayRef<Value *> VL) { 425 Type *Ty = VL[0]->getType(); 426 for (int i = 1, e = VL.size(); i < e; i++) 427 if (VL[i]->getType() != Ty) 428 return false; 429 430 return true; 431 } 432 433 /// \returns True if Extract{Value,Element} instruction extracts element Idx. 434 static Optional<unsigned> getExtractIndex(Instruction *E) { 435 unsigned Opcode = E->getOpcode(); 436 assert((Opcode == Instruction::ExtractElement || 437 Opcode == Instruction::ExtractValue) && 438 "Expected extractelement or extractvalue instruction."); 439 if (Opcode == Instruction::ExtractElement) { 440 auto *CI = dyn_cast<ConstantInt>(E->getOperand(1)); 441 if (!CI) 442 return None; 443 return CI->getZExtValue(); 444 } 445 ExtractValueInst *EI = cast<ExtractValueInst>(E); 446 if (EI->getNumIndices() != 1) 447 return None; 448 return *EI->idx_begin(); 449 } 450 451 /// \returns True if in-tree use also needs extract. This refers to 452 /// possible scalar operand in vectorized instruction. 453 static bool InTreeUserNeedToExtract(Value *Scalar, Instruction *UserInst, 454 TargetLibraryInfo *TLI) { 455 unsigned Opcode = UserInst->getOpcode(); 456 switch (Opcode) { 457 case Instruction::Load: { 458 LoadInst *LI = cast<LoadInst>(UserInst); 459 return (LI->getPointerOperand() == Scalar); 460 } 461 case Instruction::Store: { 462 StoreInst *SI = cast<StoreInst>(UserInst); 463 return (SI->getPointerOperand() == Scalar); 464 } 465 case Instruction::Call: { 466 CallInst *CI = cast<CallInst>(UserInst); 467 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 468 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 469 if (hasVectorInstrinsicScalarOpd(ID, i)) 470 return (CI->getArgOperand(i) == Scalar); 471 } 472 LLVM_FALLTHROUGH; 473 } 474 default: 475 return false; 476 } 477 } 478 479 /// \returns the AA location that is being access by the instruction. 480 static MemoryLocation getLocation(Instruction *I, AliasAnalysis *AA) { 481 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 482 return MemoryLocation::get(SI); 483 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 484 return MemoryLocation::get(LI); 485 return MemoryLocation(); 486 } 487 488 /// \returns True if the instruction is not a volatile or atomic load/store. 489 static bool isSimple(Instruction *I) { 490 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 491 return LI->isSimple(); 492 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 493 return SI->isSimple(); 494 if (MemIntrinsic *MI = dyn_cast<MemIntrinsic>(I)) 495 return !MI->isVolatile(); 496 return true; 497 } 498 499 namespace llvm { 500 501 namespace slpvectorizer { 502 503 /// Bottom Up SLP Vectorizer. 504 class BoUpSLP { 505 struct TreeEntry; 506 struct ScheduleData; 507 508 public: 509 using ValueList = SmallVector<Value *, 8>; 510 using InstrList = SmallVector<Instruction *, 16>; 511 using ValueSet = SmallPtrSet<Value *, 16>; 512 using StoreList = SmallVector<StoreInst *, 8>; 513 using ExtraValueToDebugLocsMap = 514 MapVector<Value *, SmallVector<Instruction *, 2>>; 515 516 BoUpSLP(Function *Func, ScalarEvolution *Se, TargetTransformInfo *Tti, 517 TargetLibraryInfo *TLi, AliasAnalysis *Aa, LoopInfo *Li, 518 DominatorTree *Dt, AssumptionCache *AC, DemandedBits *DB, 519 const DataLayout *DL, OptimizationRemarkEmitter *ORE) 520 : F(Func), SE(Se), TTI(Tti), TLI(TLi), AA(Aa), LI(Li), DT(Dt), AC(AC), 521 DB(DB), DL(DL), ORE(ORE), Builder(Se->getContext()) { 522 CodeMetrics::collectEphemeralValues(F, AC, EphValues); 523 // Use the vector register size specified by the target unless overridden 524 // by a command-line option. 525 // TODO: It would be better to limit the vectorization factor based on 526 // data type rather than just register size. For example, x86 AVX has 527 // 256-bit registers, but it does not support integer operations 528 // at that width (that requires AVX2). 529 if (MaxVectorRegSizeOption.getNumOccurrences()) 530 MaxVecRegSize = MaxVectorRegSizeOption; 531 else 532 MaxVecRegSize = TTI->getRegisterBitWidth(true); 533 534 if (MinVectorRegSizeOption.getNumOccurrences()) 535 MinVecRegSize = MinVectorRegSizeOption; 536 else 537 MinVecRegSize = TTI->getMinVectorRegisterBitWidth(); 538 } 539 540 /// Vectorize the tree that starts with the elements in \p VL. 541 /// Returns the vectorized root. 542 Value *vectorizeTree(); 543 544 /// Vectorize the tree but with the list of externally used values \p 545 /// ExternallyUsedValues. Values in this MapVector can be replaced but the 546 /// generated extractvalue instructions. 547 Value *vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues); 548 549 /// \returns the cost incurred by unwanted spills and fills, caused by 550 /// holding live values over call sites. 551 int getSpillCost() const; 552 553 /// \returns the vectorization cost of the subtree that starts at \p VL. 554 /// A negative number means that this is profitable. 555 int getTreeCost(); 556 557 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 558 /// the purpose of scheduling and extraction in the \p UserIgnoreLst. 559 void buildTree(ArrayRef<Value *> Roots, 560 ArrayRef<Value *> UserIgnoreLst = None); 561 562 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 563 /// the purpose of scheduling and extraction in the \p UserIgnoreLst taking 564 /// into account (anf updating it, if required) list of externally used 565 /// values stored in \p ExternallyUsedValues. 566 void buildTree(ArrayRef<Value *> Roots, 567 ExtraValueToDebugLocsMap &ExternallyUsedValues, 568 ArrayRef<Value *> UserIgnoreLst = None); 569 570 /// Clear the internal data structures that are created by 'buildTree'. 571 void deleteTree() { 572 VectorizableTree.clear(); 573 ScalarToTreeEntry.clear(); 574 MustGather.clear(); 575 ExternalUses.clear(); 576 NumOpsWantToKeepOrder.clear(); 577 NumOpsWantToKeepOriginalOrder = 0; 578 for (auto &Iter : BlocksSchedules) { 579 BlockScheduling *BS = Iter.second.get(); 580 BS->clear(); 581 } 582 MinBWs.clear(); 583 } 584 585 unsigned getTreeSize() const { return VectorizableTree.size(); } 586 587 /// Perform LICM and CSE on the newly generated gather sequences. 588 void optimizeGatherSequence(); 589 590 /// \returns The best order of instructions for vectorization. 591 Optional<ArrayRef<unsigned>> bestOrder() const { 592 auto I = std::max_element( 593 NumOpsWantToKeepOrder.begin(), NumOpsWantToKeepOrder.end(), 594 [](const decltype(NumOpsWantToKeepOrder)::value_type &D1, 595 const decltype(NumOpsWantToKeepOrder)::value_type &D2) { 596 return D1.second < D2.second; 597 }); 598 if (I == NumOpsWantToKeepOrder.end() || 599 I->getSecond() <= NumOpsWantToKeepOriginalOrder) 600 return None; 601 602 return makeArrayRef(I->getFirst()); 603 } 604 605 /// \return The vector element size in bits to use when vectorizing the 606 /// expression tree ending at \p V. If V is a store, the size is the width of 607 /// the stored value. Otherwise, the size is the width of the largest loaded 608 /// value reaching V. This method is used by the vectorizer to calculate 609 /// vectorization factors. 610 unsigned getVectorElementSize(Value *V) const; 611 612 /// Compute the minimum type sizes required to represent the entries in a 613 /// vectorizable tree. 614 void computeMinimumValueSizes(); 615 616 // \returns maximum vector register size as set by TTI or overridden by cl::opt. 617 unsigned getMaxVecRegSize() const { 618 return MaxVecRegSize; 619 } 620 621 // \returns minimum vector register size as set by cl::opt. 622 unsigned getMinVecRegSize() const { 623 return MinVecRegSize; 624 } 625 626 /// Check if ArrayType or StructType is isomorphic to some VectorType. 627 /// 628 /// \returns number of elements in vector if isomorphism exists, 0 otherwise. 629 unsigned canMapToVector(Type *T, const DataLayout &DL) const; 630 631 /// \returns True if the VectorizableTree is both tiny and not fully 632 /// vectorizable. We do not vectorize such trees. 633 bool isTreeTinyAndNotFullyVectorizable() const; 634 635 /// Assume that a legal-sized 'or'-reduction of shifted/zexted loaded values 636 /// can be load combined in the backend. Load combining may not be allowed in 637 /// the IR optimizer, so we do not want to alter the pattern. For example, 638 /// partially transforming a scalar bswap() pattern into vector code is 639 /// effectively impossible for the backend to undo. 640 /// TODO: If load combining is allowed in the IR optimizer, this analysis 641 /// may not be necessary. 642 bool isLoadCombineReductionCandidate(unsigned ReductionOpcode) const; 643 644 OptimizationRemarkEmitter *getORE() { return ORE; } 645 646 /// This structure holds any data we need about the edges being traversed 647 /// during buildTree_rec(). We keep track of: 648 /// (i) the user TreeEntry index, and 649 /// (ii) the index of the edge. 650 struct EdgeInfo { 651 EdgeInfo() = default; 652 EdgeInfo(TreeEntry *UserTE, unsigned EdgeIdx) 653 : UserTE(UserTE), EdgeIdx(EdgeIdx) {} 654 /// The user TreeEntry. 655 TreeEntry *UserTE = nullptr; 656 /// The operand index of the use. 657 unsigned EdgeIdx = UINT_MAX; 658 #ifndef NDEBUG 659 friend inline raw_ostream &operator<<(raw_ostream &OS, 660 const BoUpSLP::EdgeInfo &EI) { 661 EI.dump(OS); 662 return OS; 663 } 664 /// Debug print. 665 void dump(raw_ostream &OS) const { 666 OS << "{User:" << (UserTE ? std::to_string(UserTE->Idx) : "null") 667 << " EdgeIdx:" << EdgeIdx << "}"; 668 } 669 LLVM_DUMP_METHOD void dump() const { dump(dbgs()); } 670 #endif 671 }; 672 673 /// A helper data structure to hold the operands of a vector of instructions. 674 /// This supports a fixed vector length for all operand vectors. 675 class VLOperands { 676 /// For each operand we need (i) the value, and (ii) the opcode that it 677 /// would be attached to if the expression was in a left-linearized form. 678 /// This is required to avoid illegal operand reordering. 679 /// For example: 680 /// \verbatim 681 /// 0 Op1 682 /// |/ 683 /// Op1 Op2 Linearized + Op2 684 /// \ / ----------> |/ 685 /// - - 686 /// 687 /// Op1 - Op2 (0 + Op1) - Op2 688 /// \endverbatim 689 /// 690 /// Value Op1 is attached to a '+' operation, and Op2 to a '-'. 691 /// 692 /// Another way to think of this is to track all the operations across the 693 /// path from the operand all the way to the root of the tree and to 694 /// calculate the operation that corresponds to this path. For example, the 695 /// path from Op2 to the root crosses the RHS of the '-', therefore the 696 /// corresponding operation is a '-' (which matches the one in the 697 /// linearized tree, as shown above). 698 /// 699 /// For lack of a better term, we refer to this operation as Accumulated 700 /// Path Operation (APO). 701 struct OperandData { 702 OperandData() = default; 703 OperandData(Value *V, bool APO, bool IsUsed) 704 : V(V), APO(APO), IsUsed(IsUsed) {} 705 /// The operand value. 706 Value *V = nullptr; 707 /// TreeEntries only allow a single opcode, or an alternate sequence of 708 /// them (e.g, +, -). Therefore, we can safely use a boolean value for the 709 /// APO. It is set to 'true' if 'V' is attached to an inverse operation 710 /// in the left-linearized form (e.g., Sub/Div), and 'false' otherwise 711 /// (e.g., Add/Mul) 712 bool APO = false; 713 /// Helper data for the reordering function. 714 bool IsUsed = false; 715 }; 716 717 /// During operand reordering, we are trying to select the operand at lane 718 /// that matches best with the operand at the neighboring lane. Our 719 /// selection is based on the type of value we are looking for. For example, 720 /// if the neighboring lane has a load, we need to look for a load that is 721 /// accessing a consecutive address. These strategies are summarized in the 722 /// 'ReorderingMode' enumerator. 723 enum class ReorderingMode { 724 Load, ///< Matching loads to consecutive memory addresses 725 Opcode, ///< Matching instructions based on opcode (same or alternate) 726 Constant, ///< Matching constants 727 Splat, ///< Matching the same instruction multiple times (broadcast) 728 Failed, ///< We failed to create a vectorizable group 729 }; 730 731 using OperandDataVec = SmallVector<OperandData, 2>; 732 733 /// A vector of operand vectors. 734 SmallVector<OperandDataVec, 4> OpsVec; 735 736 const DataLayout &DL; 737 ScalarEvolution &SE; 738 const BoUpSLP &R; 739 740 /// \returns the operand data at \p OpIdx and \p Lane. 741 OperandData &getData(unsigned OpIdx, unsigned Lane) { 742 return OpsVec[OpIdx][Lane]; 743 } 744 745 /// \returns the operand data at \p OpIdx and \p Lane. Const version. 746 const OperandData &getData(unsigned OpIdx, unsigned Lane) const { 747 return OpsVec[OpIdx][Lane]; 748 } 749 750 /// Clears the used flag for all entries. 751 void clearUsed() { 752 for (unsigned OpIdx = 0, NumOperands = getNumOperands(); 753 OpIdx != NumOperands; ++OpIdx) 754 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 755 ++Lane) 756 OpsVec[OpIdx][Lane].IsUsed = false; 757 } 758 759 /// Swap the operand at \p OpIdx1 with that one at \p OpIdx2. 760 void swap(unsigned OpIdx1, unsigned OpIdx2, unsigned Lane) { 761 std::swap(OpsVec[OpIdx1][Lane], OpsVec[OpIdx2][Lane]); 762 } 763 764 // The hard-coded scores listed here are not very important. When computing 765 // the scores of matching one sub-tree with another, we are basically 766 // counting the number of values that are matching. So even if all scores 767 // are set to 1, we would still get a decent matching result. 768 // However, sometimes we have to break ties. For example we may have to 769 // choose between matching loads vs matching opcodes. This is what these 770 // scores are helping us with: they provide the order of preference. 771 772 /// Loads from consecutive memory addresses, e.g. load(A[i]), load(A[i+1]). 773 static const int ScoreConsecutiveLoads = 3; 774 /// ExtractElementInst from same vector and consecutive indexes. 775 static const int ScoreConsecutiveExtracts = 3; 776 /// Constants. 777 static const int ScoreConstants = 2; 778 /// Instructions with the same opcode. 779 static const int ScoreSameOpcode = 2; 780 /// Instructions with alt opcodes (e.g, add + sub). 781 static const int ScoreAltOpcodes = 1; 782 /// Identical instructions (a.k.a. splat or broadcast). 783 static const int ScoreSplat = 1; 784 /// Matching with an undef is preferable to failing. 785 static const int ScoreUndef = 1; 786 /// Score for failing to find a decent match. 787 static const int ScoreFail = 0; 788 /// User exteranl to the vectorized code. 789 static const int ExternalUseCost = 1; 790 /// The user is internal but in a different lane. 791 static const int UserInDiffLaneCost = ExternalUseCost; 792 793 /// \returns the score of placing \p V1 and \p V2 in consecutive lanes. 794 static int getShallowScore(Value *V1, Value *V2, const DataLayout &DL, 795 ScalarEvolution &SE) { 796 auto *LI1 = dyn_cast<LoadInst>(V1); 797 auto *LI2 = dyn_cast<LoadInst>(V2); 798 if (LI1 && LI2) 799 return isConsecutiveAccess(LI1, LI2, DL, SE) 800 ? VLOperands::ScoreConsecutiveLoads 801 : VLOperands::ScoreFail; 802 803 auto *C1 = dyn_cast<Constant>(V1); 804 auto *C2 = dyn_cast<Constant>(V2); 805 if (C1 && C2) 806 return VLOperands::ScoreConstants; 807 808 // Extracts from consecutive indexes of the same vector better score as 809 // the extracts could be optimized away. 810 auto *Ex1 = dyn_cast<ExtractElementInst>(V1); 811 auto *Ex2 = dyn_cast<ExtractElementInst>(V2); 812 if (Ex1 && Ex2 && Ex1->getVectorOperand() == Ex2->getVectorOperand() && 813 cast<ConstantInt>(Ex1->getIndexOperand())->getZExtValue() + 1 == 814 cast<ConstantInt>(Ex2->getIndexOperand())->getZExtValue()) { 815 return VLOperands::ScoreConsecutiveExtracts; 816 } 817 818 auto *I1 = dyn_cast<Instruction>(V1); 819 auto *I2 = dyn_cast<Instruction>(V2); 820 if (I1 && I2) { 821 if (I1 == I2) 822 return VLOperands::ScoreSplat; 823 InstructionsState S = getSameOpcode({I1, I2}); 824 // Note: Only consider instructions with <= 2 operands to avoid 825 // complexity explosion. 826 if (S.getOpcode() && S.MainOp->getNumOperands() <= 2) 827 return S.isAltShuffle() ? VLOperands::ScoreAltOpcodes 828 : VLOperands::ScoreSameOpcode; 829 } 830 831 if (isa<UndefValue>(V2)) 832 return VLOperands::ScoreUndef; 833 834 return VLOperands::ScoreFail; 835 } 836 837 /// Holds the values and their lane that are taking part in the look-ahead 838 /// score calculation. This is used in the external uses cost calculation. 839 SmallDenseMap<Value *, int> InLookAheadValues; 840 841 /// \Returns the additinal cost due to uses of \p LHS and \p RHS that are 842 /// either external to the vectorized code, or require shuffling. 843 int getExternalUsesCost(const std::pair<Value *, int> &LHS, 844 const std::pair<Value *, int> &RHS) { 845 int Cost = 0; 846 SmallVector<std::pair<Value *, int>, 2> Values = {LHS, RHS}; 847 for (int Idx = 0, IdxE = Values.size(); Idx != IdxE; ++Idx) { 848 Value *V = Values[Idx].first; 849 // Calculate the absolute lane, using the minimum relative lane of LHS 850 // and RHS as base and Idx as the offset. 851 int Ln = std::min(LHS.second, RHS.second) + Idx; 852 assert(Ln >= 0 && "Bad lane calculation"); 853 unsigned UsersBudget = LookAheadUsersBudget; 854 for (User *U : V->users()) { 855 if (const TreeEntry *UserTE = R.getTreeEntry(U)) { 856 // The user is in the VectorizableTree. Check if we need to insert. 857 auto It = llvm::find(UserTE->Scalars, U); 858 assert(It != UserTE->Scalars.end() && "U is in UserTE"); 859 int UserLn = std::distance(UserTE->Scalars.begin(), It); 860 assert(UserLn >= 0 && "Bad lane"); 861 if (UserLn != Ln) 862 Cost += UserInDiffLaneCost; 863 } else { 864 // Check if the user is in the look-ahead code. 865 auto It2 = InLookAheadValues.find(U); 866 if (It2 != InLookAheadValues.end()) { 867 // The user is in the look-ahead code. Check the lane. 868 if (It2->second != Ln) 869 Cost += UserInDiffLaneCost; 870 } else { 871 // The user is neither in SLP tree nor in the look-ahead code. 872 Cost += ExternalUseCost; 873 } 874 } 875 // Limit the number of visited uses to cap compilation time. 876 if (--UsersBudget == 0) 877 break; 878 } 879 } 880 return Cost; 881 } 882 883 /// Go through the operands of \p LHS and \p RHS recursively until \p 884 /// MaxLevel, and return the cummulative score. For example: 885 /// \verbatim 886 /// A[0] B[0] A[1] B[1] C[0] D[0] B[1] A[1] 887 /// \ / \ / \ / \ / 888 /// + + + + 889 /// G1 G2 G3 G4 890 /// \endverbatim 891 /// The getScoreAtLevelRec(G1, G2) function will try to match the nodes at 892 /// each level recursively, accumulating the score. It starts from matching 893 /// the additions at level 0, then moves on to the loads (level 1). The 894 /// score of G1 and G2 is higher than G1 and G3, because {A[0],A[1]} and 895 /// {B[0],B[1]} match with VLOperands::ScoreConsecutiveLoads, while 896 /// {A[0],C[0]} has a score of VLOperands::ScoreFail. 897 /// Please note that the order of the operands does not matter, as we 898 /// evaluate the score of all profitable combinations of operands. In 899 /// other words the score of G1 and G4 is the same as G1 and G2. This 900 /// heuristic is based on ideas described in: 901 /// Look-ahead SLP: Auto-vectorization in the presence of commutative 902 /// operations, CGO 2018 by Vasileios Porpodas, Rodrigo C. O. Rocha, 903 /// Luís F. W. Góes 904 int getScoreAtLevelRec(const std::pair<Value *, int> &LHS, 905 const std::pair<Value *, int> &RHS, int CurrLevel, 906 int MaxLevel) { 907 908 Value *V1 = LHS.first; 909 Value *V2 = RHS.first; 910 // Get the shallow score of V1 and V2. 911 int ShallowScoreAtThisLevel = 912 std::max((int)ScoreFail, getShallowScore(V1, V2, DL, SE) - 913 getExternalUsesCost(LHS, RHS)); 914 int Lane1 = LHS.second; 915 int Lane2 = RHS.second; 916 917 // If reached MaxLevel, 918 // or if V1 and V2 are not instructions, 919 // or if they are SPLAT, 920 // or if they are not consecutive, early return the current cost. 921 auto *I1 = dyn_cast<Instruction>(V1); 922 auto *I2 = dyn_cast<Instruction>(V2); 923 if (CurrLevel == MaxLevel || !(I1 && I2) || I1 == I2 || 924 ShallowScoreAtThisLevel == VLOperands::ScoreFail || 925 (isa<LoadInst>(I1) && isa<LoadInst>(I2) && ShallowScoreAtThisLevel)) 926 return ShallowScoreAtThisLevel; 927 assert(I1 && I2 && "Should have early exited."); 928 929 // Keep track of in-tree values for determining the external-use cost. 930 InLookAheadValues[V1] = Lane1; 931 InLookAheadValues[V2] = Lane2; 932 933 // Contains the I2 operand indexes that got matched with I1 operands. 934 SmallSet<unsigned, 4> Op2Used; 935 936 // Recursion towards the operands of I1 and I2. We are trying all possbile 937 // operand pairs, and keeping track of the best score. 938 for (unsigned OpIdx1 = 0, NumOperands1 = I1->getNumOperands(); 939 OpIdx1 != NumOperands1; ++OpIdx1) { 940 // Try to pair op1I with the best operand of I2. 941 int MaxTmpScore = 0; 942 unsigned MaxOpIdx2 = 0; 943 bool FoundBest = false; 944 // If I2 is commutative try all combinations. 945 unsigned FromIdx = isCommutative(I2) ? 0 : OpIdx1; 946 unsigned ToIdx = isCommutative(I2) 947 ? I2->getNumOperands() 948 : std::min(I2->getNumOperands(), OpIdx1 + 1); 949 assert(FromIdx <= ToIdx && "Bad index"); 950 for (unsigned OpIdx2 = FromIdx; OpIdx2 != ToIdx; ++OpIdx2) { 951 // Skip operands already paired with OpIdx1. 952 if (Op2Used.count(OpIdx2)) 953 continue; 954 // Recursively calculate the cost at each level 955 int TmpScore = getScoreAtLevelRec({I1->getOperand(OpIdx1), Lane1}, 956 {I2->getOperand(OpIdx2), Lane2}, 957 CurrLevel + 1, MaxLevel); 958 // Look for the best score. 959 if (TmpScore > VLOperands::ScoreFail && TmpScore > MaxTmpScore) { 960 MaxTmpScore = TmpScore; 961 MaxOpIdx2 = OpIdx2; 962 FoundBest = true; 963 } 964 } 965 if (FoundBest) { 966 // Pair {OpIdx1, MaxOpIdx2} was found to be best. Never revisit it. 967 Op2Used.insert(MaxOpIdx2); 968 ShallowScoreAtThisLevel += MaxTmpScore; 969 } 970 } 971 return ShallowScoreAtThisLevel; 972 } 973 974 /// \Returns the look-ahead score, which tells us how much the sub-trees 975 /// rooted at \p LHS and \p RHS match, the more they match the higher the 976 /// score. This helps break ties in an informed way when we cannot decide on 977 /// the order of the operands by just considering the immediate 978 /// predecessors. 979 int getLookAheadScore(const std::pair<Value *, int> &LHS, 980 const std::pair<Value *, int> &RHS) { 981 InLookAheadValues.clear(); 982 return getScoreAtLevelRec(LHS, RHS, 1, LookAheadMaxDepth); 983 } 984 985 // Search all operands in Ops[*][Lane] for the one that matches best 986 // Ops[OpIdx][LastLane] and return its opreand index. 987 // If no good match can be found, return None. 988 Optional<unsigned> 989 getBestOperand(unsigned OpIdx, int Lane, int LastLane, 990 ArrayRef<ReorderingMode> ReorderingModes) { 991 unsigned NumOperands = getNumOperands(); 992 993 // The operand of the previous lane at OpIdx. 994 Value *OpLastLane = getData(OpIdx, LastLane).V; 995 996 // Our strategy mode for OpIdx. 997 ReorderingMode RMode = ReorderingModes[OpIdx]; 998 999 // The linearized opcode of the operand at OpIdx, Lane. 1000 bool OpIdxAPO = getData(OpIdx, Lane).APO; 1001 1002 // The best operand index and its score. 1003 // Sometimes we have more than one option (e.g., Opcode and Undefs), so we 1004 // are using the score to differentiate between the two. 1005 struct BestOpData { 1006 Optional<unsigned> Idx = None; 1007 unsigned Score = 0; 1008 } BestOp; 1009 1010 // Iterate through all unused operands and look for the best. 1011 for (unsigned Idx = 0; Idx != NumOperands; ++Idx) { 1012 // Get the operand at Idx and Lane. 1013 OperandData &OpData = getData(Idx, Lane); 1014 Value *Op = OpData.V; 1015 bool OpAPO = OpData.APO; 1016 1017 // Skip already selected operands. 1018 if (OpData.IsUsed) 1019 continue; 1020 1021 // Skip if we are trying to move the operand to a position with a 1022 // different opcode in the linearized tree form. This would break the 1023 // semantics. 1024 if (OpAPO != OpIdxAPO) 1025 continue; 1026 1027 // Look for an operand that matches the current mode. 1028 switch (RMode) { 1029 case ReorderingMode::Load: 1030 case ReorderingMode::Constant: 1031 case ReorderingMode::Opcode: { 1032 bool LeftToRight = Lane > LastLane; 1033 Value *OpLeft = (LeftToRight) ? OpLastLane : Op; 1034 Value *OpRight = (LeftToRight) ? Op : OpLastLane; 1035 unsigned Score = 1036 getLookAheadScore({OpLeft, LastLane}, {OpRight, Lane}); 1037 if (Score > BestOp.Score) { 1038 BestOp.Idx = Idx; 1039 BestOp.Score = Score; 1040 } 1041 break; 1042 } 1043 case ReorderingMode::Splat: 1044 if (Op == OpLastLane) 1045 BestOp.Idx = Idx; 1046 break; 1047 case ReorderingMode::Failed: 1048 return None; 1049 } 1050 } 1051 1052 if (BestOp.Idx) { 1053 getData(BestOp.Idx.getValue(), Lane).IsUsed = true; 1054 return BestOp.Idx; 1055 } 1056 // If we could not find a good match return None. 1057 return None; 1058 } 1059 1060 /// Helper for reorderOperandVecs. \Returns the lane that we should start 1061 /// reordering from. This is the one which has the least number of operands 1062 /// that can freely move about. 1063 unsigned getBestLaneToStartReordering() const { 1064 unsigned BestLane = 0; 1065 unsigned Min = UINT_MAX; 1066 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 1067 ++Lane) { 1068 unsigned NumFreeOps = getMaxNumOperandsThatCanBeReordered(Lane); 1069 if (NumFreeOps < Min) { 1070 Min = NumFreeOps; 1071 BestLane = Lane; 1072 } 1073 } 1074 return BestLane; 1075 } 1076 1077 /// \Returns the maximum number of operands that are allowed to be reordered 1078 /// for \p Lane. This is used as a heuristic for selecting the first lane to 1079 /// start operand reordering. 1080 unsigned getMaxNumOperandsThatCanBeReordered(unsigned Lane) const { 1081 unsigned CntTrue = 0; 1082 unsigned NumOperands = getNumOperands(); 1083 // Operands with the same APO can be reordered. We therefore need to count 1084 // how many of them we have for each APO, like this: Cnt[APO] = x. 1085 // Since we only have two APOs, namely true and false, we can avoid using 1086 // a map. Instead we can simply count the number of operands that 1087 // correspond to one of them (in this case the 'true' APO), and calculate 1088 // the other by subtracting it from the total number of operands. 1089 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) 1090 if (getData(OpIdx, Lane).APO) 1091 ++CntTrue; 1092 unsigned CntFalse = NumOperands - CntTrue; 1093 return std::max(CntTrue, CntFalse); 1094 } 1095 1096 /// Go through the instructions in VL and append their operands. 1097 void appendOperandsOfVL(ArrayRef<Value *> VL) { 1098 assert(!VL.empty() && "Bad VL"); 1099 assert((empty() || VL.size() == getNumLanes()) && 1100 "Expected same number of lanes"); 1101 assert(isa<Instruction>(VL[0]) && "Expected instruction"); 1102 unsigned NumOperands = cast<Instruction>(VL[0])->getNumOperands(); 1103 OpsVec.resize(NumOperands); 1104 unsigned NumLanes = VL.size(); 1105 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1106 OpsVec[OpIdx].resize(NumLanes); 1107 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { 1108 assert(isa<Instruction>(VL[Lane]) && "Expected instruction"); 1109 // Our tree has just 3 nodes: the root and two operands. 1110 // It is therefore trivial to get the APO. We only need to check the 1111 // opcode of VL[Lane] and whether the operand at OpIdx is the LHS or 1112 // RHS operand. The LHS operand of both add and sub is never attached 1113 // to an inversese operation in the linearized form, therefore its APO 1114 // is false. The RHS is true only if VL[Lane] is an inverse operation. 1115 1116 // Since operand reordering is performed on groups of commutative 1117 // operations or alternating sequences (e.g., +, -), we can safely 1118 // tell the inverse operations by checking commutativity. 1119 bool IsInverseOperation = !isCommutative(cast<Instruction>(VL[Lane])); 1120 bool APO = (OpIdx == 0) ? false : IsInverseOperation; 1121 OpsVec[OpIdx][Lane] = {cast<Instruction>(VL[Lane])->getOperand(OpIdx), 1122 APO, false}; 1123 } 1124 } 1125 } 1126 1127 /// \returns the number of operands. 1128 unsigned getNumOperands() const { return OpsVec.size(); } 1129 1130 /// \returns the number of lanes. 1131 unsigned getNumLanes() const { return OpsVec[0].size(); } 1132 1133 /// \returns the operand value at \p OpIdx and \p Lane. 1134 Value *getValue(unsigned OpIdx, unsigned Lane) const { 1135 return getData(OpIdx, Lane).V; 1136 } 1137 1138 /// \returns true if the data structure is empty. 1139 bool empty() const { return OpsVec.empty(); } 1140 1141 /// Clears the data. 1142 void clear() { OpsVec.clear(); } 1143 1144 /// \Returns true if there are enough operands identical to \p Op to fill 1145 /// the whole vector. 1146 /// Note: This modifies the 'IsUsed' flag, so a cleanUsed() must follow. 1147 bool shouldBroadcast(Value *Op, unsigned OpIdx, unsigned Lane) { 1148 bool OpAPO = getData(OpIdx, Lane).APO; 1149 for (unsigned Ln = 0, Lns = getNumLanes(); Ln != Lns; ++Ln) { 1150 if (Ln == Lane) 1151 continue; 1152 // This is set to true if we found a candidate for broadcast at Lane. 1153 bool FoundCandidate = false; 1154 for (unsigned OpI = 0, OpE = getNumOperands(); OpI != OpE; ++OpI) { 1155 OperandData &Data = getData(OpI, Ln); 1156 if (Data.APO != OpAPO || Data.IsUsed) 1157 continue; 1158 if (Data.V == Op) { 1159 FoundCandidate = true; 1160 Data.IsUsed = true; 1161 break; 1162 } 1163 } 1164 if (!FoundCandidate) 1165 return false; 1166 } 1167 return true; 1168 } 1169 1170 public: 1171 /// Initialize with all the operands of the instruction vector \p RootVL. 1172 VLOperands(ArrayRef<Value *> RootVL, const DataLayout &DL, 1173 ScalarEvolution &SE, const BoUpSLP &R) 1174 : DL(DL), SE(SE), R(R) { 1175 // Append all the operands of RootVL. 1176 appendOperandsOfVL(RootVL); 1177 } 1178 1179 /// \Returns a value vector with the operands across all lanes for the 1180 /// opearnd at \p OpIdx. 1181 ValueList getVL(unsigned OpIdx) const { 1182 ValueList OpVL(OpsVec[OpIdx].size()); 1183 assert(OpsVec[OpIdx].size() == getNumLanes() && 1184 "Expected same num of lanes across all operands"); 1185 for (unsigned Lane = 0, Lanes = getNumLanes(); Lane != Lanes; ++Lane) 1186 OpVL[Lane] = OpsVec[OpIdx][Lane].V; 1187 return OpVL; 1188 } 1189 1190 // Performs operand reordering for 2 or more operands. 1191 // The original operands are in OrigOps[OpIdx][Lane]. 1192 // The reordered operands are returned in 'SortedOps[OpIdx][Lane]'. 1193 void reorder() { 1194 unsigned NumOperands = getNumOperands(); 1195 unsigned NumLanes = getNumLanes(); 1196 // Each operand has its own mode. We are using this mode to help us select 1197 // the instructions for each lane, so that they match best with the ones 1198 // we have selected so far. 1199 SmallVector<ReorderingMode, 2> ReorderingModes(NumOperands); 1200 1201 // This is a greedy single-pass algorithm. We are going over each lane 1202 // once and deciding on the best order right away with no back-tracking. 1203 // However, in order to increase its effectiveness, we start with the lane 1204 // that has operands that can move the least. For example, given the 1205 // following lanes: 1206 // Lane 0 : A[0] = B[0] + C[0] // Visited 3rd 1207 // Lane 1 : A[1] = C[1] - B[1] // Visited 1st 1208 // Lane 2 : A[2] = B[2] + C[2] // Visited 2nd 1209 // Lane 3 : A[3] = C[3] - B[3] // Visited 4th 1210 // we will start at Lane 1, since the operands of the subtraction cannot 1211 // be reordered. Then we will visit the rest of the lanes in a circular 1212 // fashion. That is, Lanes 2, then Lane 0, and finally Lane 3. 1213 1214 // Find the first lane that we will start our search from. 1215 unsigned FirstLane = getBestLaneToStartReordering(); 1216 1217 // Initialize the modes. 1218 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1219 Value *OpLane0 = getValue(OpIdx, FirstLane); 1220 // Keep track if we have instructions with all the same opcode on one 1221 // side. 1222 if (isa<LoadInst>(OpLane0)) 1223 ReorderingModes[OpIdx] = ReorderingMode::Load; 1224 else if (isa<Instruction>(OpLane0)) { 1225 // Check if OpLane0 should be broadcast. 1226 if (shouldBroadcast(OpLane0, OpIdx, FirstLane)) 1227 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1228 else 1229 ReorderingModes[OpIdx] = ReorderingMode::Opcode; 1230 } 1231 else if (isa<Constant>(OpLane0)) 1232 ReorderingModes[OpIdx] = ReorderingMode::Constant; 1233 else if (isa<Argument>(OpLane0)) 1234 // Our best hope is a Splat. It may save some cost in some cases. 1235 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1236 else 1237 // NOTE: This should be unreachable. 1238 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1239 } 1240 1241 // If the initial strategy fails for any of the operand indexes, then we 1242 // perform reordering again in a second pass. This helps avoid assigning 1243 // high priority to the failed strategy, and should improve reordering for 1244 // the non-failed operand indexes. 1245 for (int Pass = 0; Pass != 2; ++Pass) { 1246 // Skip the second pass if the first pass did not fail. 1247 bool StrategyFailed = false; 1248 // Mark all operand data as free to use. 1249 clearUsed(); 1250 // We keep the original operand order for the FirstLane, so reorder the 1251 // rest of the lanes. We are visiting the nodes in a circular fashion, 1252 // using FirstLane as the center point and increasing the radius 1253 // distance. 1254 for (unsigned Distance = 1; Distance != NumLanes; ++Distance) { 1255 // Visit the lane on the right and then the lane on the left. 1256 for (int Direction : {+1, -1}) { 1257 int Lane = FirstLane + Direction * Distance; 1258 if (Lane < 0 || Lane >= (int)NumLanes) 1259 continue; 1260 int LastLane = Lane - Direction; 1261 assert(LastLane >= 0 && LastLane < (int)NumLanes && 1262 "Out of bounds"); 1263 // Look for a good match for each operand. 1264 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1265 // Search for the operand that matches SortedOps[OpIdx][Lane-1]. 1266 Optional<unsigned> BestIdx = 1267 getBestOperand(OpIdx, Lane, LastLane, ReorderingModes); 1268 // By not selecting a value, we allow the operands that follow to 1269 // select a better matching value. We will get a non-null value in 1270 // the next run of getBestOperand(). 1271 if (BestIdx) { 1272 // Swap the current operand with the one returned by 1273 // getBestOperand(). 1274 swap(OpIdx, BestIdx.getValue(), Lane); 1275 } else { 1276 // We failed to find a best operand, set mode to 'Failed'. 1277 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1278 // Enable the second pass. 1279 StrategyFailed = true; 1280 } 1281 } 1282 } 1283 } 1284 // Skip second pass if the strategy did not fail. 1285 if (!StrategyFailed) 1286 break; 1287 } 1288 } 1289 1290 #if !defined(NDEBUG) || defined(LLVM_ENABLE_DUMP) 1291 LLVM_DUMP_METHOD static StringRef getModeStr(ReorderingMode RMode) { 1292 switch (RMode) { 1293 case ReorderingMode::Load: 1294 return "Load"; 1295 case ReorderingMode::Opcode: 1296 return "Opcode"; 1297 case ReorderingMode::Constant: 1298 return "Constant"; 1299 case ReorderingMode::Splat: 1300 return "Splat"; 1301 case ReorderingMode::Failed: 1302 return "Failed"; 1303 } 1304 llvm_unreachable("Unimplemented Reordering Type"); 1305 } 1306 1307 LLVM_DUMP_METHOD static raw_ostream &printMode(ReorderingMode RMode, 1308 raw_ostream &OS) { 1309 return OS << getModeStr(RMode); 1310 } 1311 1312 /// Debug print. 1313 LLVM_DUMP_METHOD static void dumpMode(ReorderingMode RMode) { 1314 printMode(RMode, dbgs()); 1315 } 1316 1317 friend raw_ostream &operator<<(raw_ostream &OS, ReorderingMode RMode) { 1318 return printMode(RMode, OS); 1319 } 1320 1321 LLVM_DUMP_METHOD raw_ostream &print(raw_ostream &OS) const { 1322 const unsigned Indent = 2; 1323 unsigned Cnt = 0; 1324 for (const OperandDataVec &OpDataVec : OpsVec) { 1325 OS << "Operand " << Cnt++ << "\n"; 1326 for (const OperandData &OpData : OpDataVec) { 1327 OS.indent(Indent) << "{"; 1328 if (Value *V = OpData.V) 1329 OS << *V; 1330 else 1331 OS << "null"; 1332 OS << ", APO:" << OpData.APO << "}\n"; 1333 } 1334 OS << "\n"; 1335 } 1336 return OS; 1337 } 1338 1339 /// Debug print. 1340 LLVM_DUMP_METHOD void dump() const { print(dbgs()); } 1341 #endif 1342 }; 1343 1344 /// Checks if the instruction is marked for deletion. 1345 bool isDeleted(Instruction *I) const { return DeletedInstructions.count(I); } 1346 1347 /// Marks values operands for later deletion by replacing them with Undefs. 1348 void eraseInstructions(ArrayRef<Value *> AV); 1349 1350 ~BoUpSLP(); 1351 1352 private: 1353 /// Checks if all users of \p I are the part of the vectorization tree. 1354 bool areAllUsersVectorized(Instruction *I) const; 1355 1356 /// \returns the cost of the vectorizable entry. 1357 int getEntryCost(TreeEntry *E); 1358 1359 /// This is the recursive part of buildTree. 1360 void buildTree_rec(ArrayRef<Value *> Roots, unsigned Depth, 1361 const EdgeInfo &EI); 1362 1363 /// \returns true if the ExtractElement/ExtractValue instructions in \p VL can 1364 /// be vectorized to use the original vector (or aggregate "bitcast" to a 1365 /// vector) and sets \p CurrentOrder to the identity permutation; otherwise 1366 /// returns false, setting \p CurrentOrder to either an empty vector or a 1367 /// non-identity permutation that allows to reuse extract instructions. 1368 bool canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 1369 SmallVectorImpl<unsigned> &CurrentOrder) const; 1370 1371 /// Vectorize a single entry in the tree. 1372 Value *vectorizeTree(TreeEntry *E); 1373 1374 /// Vectorize a single entry in the tree, starting in \p VL. 1375 Value *vectorizeTree(ArrayRef<Value *> VL); 1376 1377 /// \returns the scalarization cost for this type. Scalarization in this 1378 /// context means the creation of vectors from a group of scalars. 1379 int getGatherCost(Type *Ty, const DenseSet<unsigned> &ShuffledIndices) const; 1380 1381 /// \returns the scalarization cost for this list of values. Assuming that 1382 /// this subtree gets vectorized, we may need to extract the values from the 1383 /// roots. This method calculates the cost of extracting the values. 1384 int getGatherCost(ArrayRef<Value *> VL) const; 1385 1386 /// Set the Builder insert point to one after the last instruction in 1387 /// the bundle 1388 void setInsertPointAfterBundle(TreeEntry *E); 1389 1390 /// \returns a vector from a collection of scalars in \p VL. 1391 Value *Gather(ArrayRef<Value *> VL, VectorType *Ty); 1392 1393 /// \returns whether the VectorizableTree is fully vectorizable and will 1394 /// be beneficial even the tree height is tiny. 1395 bool isFullyVectorizableTinyTree() const; 1396 1397 /// Reorder commutative or alt operands to get better probability of 1398 /// generating vectorized code. 1399 static void reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 1400 SmallVectorImpl<Value *> &Left, 1401 SmallVectorImpl<Value *> &Right, 1402 const DataLayout &DL, 1403 ScalarEvolution &SE, 1404 const BoUpSLP &R); 1405 struct TreeEntry { 1406 using VecTreeTy = SmallVector<std::unique_ptr<TreeEntry>, 8>; 1407 TreeEntry(VecTreeTy &Container) : Container(Container) {} 1408 1409 /// \returns true if the scalars in VL are equal to this entry. 1410 bool isSame(ArrayRef<Value *> VL) const { 1411 if (VL.size() == Scalars.size()) 1412 return std::equal(VL.begin(), VL.end(), Scalars.begin()); 1413 return VL.size() == ReuseShuffleIndices.size() && 1414 std::equal( 1415 VL.begin(), VL.end(), ReuseShuffleIndices.begin(), 1416 [this](Value *V, unsigned Idx) { return V == Scalars[Idx]; }); 1417 } 1418 1419 /// A vector of scalars. 1420 ValueList Scalars; 1421 1422 /// The Scalars are vectorized into this value. It is initialized to Null. 1423 Value *VectorizedValue = nullptr; 1424 1425 /// Do we need to gather this sequence ? 1426 bool NeedToGather = false; 1427 1428 /// Does this sequence require some shuffling? 1429 SmallVector<unsigned, 4> ReuseShuffleIndices; 1430 1431 /// Does this entry require reordering? 1432 ArrayRef<unsigned> ReorderIndices; 1433 1434 /// Points back to the VectorizableTree. 1435 /// 1436 /// Only used for Graphviz right now. Unfortunately GraphTrait::NodeRef has 1437 /// to be a pointer and needs to be able to initialize the child iterator. 1438 /// Thus we need a reference back to the container to translate the indices 1439 /// to entries. 1440 VecTreeTy &Container; 1441 1442 /// The TreeEntry index containing the user of this entry. We can actually 1443 /// have multiple users so the data structure is not truly a tree. 1444 SmallVector<EdgeInfo, 1> UserTreeIndices; 1445 1446 /// The index of this treeEntry in VectorizableTree. 1447 int Idx = -1; 1448 1449 private: 1450 /// The operands of each instruction in each lane Operands[op_index][lane]. 1451 /// Note: This helps avoid the replication of the code that performs the 1452 /// reordering of operands during buildTree_rec() and vectorizeTree(). 1453 SmallVector<ValueList, 2> Operands; 1454 1455 /// The main/alternate instruction. 1456 Instruction *MainOp = nullptr; 1457 Instruction *AltOp = nullptr; 1458 1459 public: 1460 /// Set this bundle's \p OpIdx'th operand to \p OpVL. 1461 void setOperand(unsigned OpIdx, ArrayRef<Value *> OpVL) { 1462 if (Operands.size() < OpIdx + 1) 1463 Operands.resize(OpIdx + 1); 1464 assert(Operands[OpIdx].size() == 0 && "Already resized?"); 1465 Operands[OpIdx].resize(Scalars.size()); 1466 for (unsigned Lane = 0, E = Scalars.size(); Lane != E; ++Lane) 1467 Operands[OpIdx][Lane] = OpVL[Lane]; 1468 } 1469 1470 /// Set the operands of this bundle in their original order. 1471 void setOperandsInOrder() { 1472 assert(Operands.empty() && "Already initialized?"); 1473 auto *I0 = cast<Instruction>(Scalars[0]); 1474 Operands.resize(I0->getNumOperands()); 1475 unsigned NumLanes = Scalars.size(); 1476 for (unsigned OpIdx = 0, NumOperands = I0->getNumOperands(); 1477 OpIdx != NumOperands; ++OpIdx) { 1478 Operands[OpIdx].resize(NumLanes); 1479 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { 1480 auto *I = cast<Instruction>(Scalars[Lane]); 1481 assert(I->getNumOperands() == NumOperands && 1482 "Expected same number of operands"); 1483 Operands[OpIdx][Lane] = I->getOperand(OpIdx); 1484 } 1485 } 1486 } 1487 1488 /// \returns the \p OpIdx operand of this TreeEntry. 1489 ValueList &getOperand(unsigned OpIdx) { 1490 assert(OpIdx < Operands.size() && "Off bounds"); 1491 return Operands[OpIdx]; 1492 } 1493 1494 /// \returns the number of operands. 1495 unsigned getNumOperands() const { return Operands.size(); } 1496 1497 /// \return the single \p OpIdx operand. 1498 Value *getSingleOperand(unsigned OpIdx) const { 1499 assert(OpIdx < Operands.size() && "Off bounds"); 1500 assert(!Operands[OpIdx].empty() && "No operand available"); 1501 return Operands[OpIdx][0]; 1502 } 1503 1504 /// Some of the instructions in the list have alternate opcodes. 1505 bool isAltShuffle() const { 1506 return getOpcode() != getAltOpcode(); 1507 } 1508 1509 bool isOpcodeOrAlt(Instruction *I) const { 1510 unsigned CheckedOpcode = I->getOpcode(); 1511 return (getOpcode() == CheckedOpcode || 1512 getAltOpcode() == CheckedOpcode); 1513 } 1514 1515 /// Chooses the correct key for scheduling data. If \p Op has the same (or 1516 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is 1517 /// \p OpValue. 1518 Value *isOneOf(Value *Op) const { 1519 auto *I = dyn_cast<Instruction>(Op); 1520 if (I && isOpcodeOrAlt(I)) 1521 return Op; 1522 return MainOp; 1523 } 1524 1525 void setOperations(const InstructionsState &S) { 1526 MainOp = S.MainOp; 1527 AltOp = S.AltOp; 1528 } 1529 1530 Instruction *getMainOp() const { 1531 return MainOp; 1532 } 1533 1534 Instruction *getAltOp() const { 1535 return AltOp; 1536 } 1537 1538 /// The main/alternate opcodes for the list of instructions. 1539 unsigned getOpcode() const { 1540 return MainOp ? MainOp->getOpcode() : 0; 1541 } 1542 1543 unsigned getAltOpcode() const { 1544 return AltOp ? AltOp->getOpcode() : 0; 1545 } 1546 1547 /// Update operations state of this entry if reorder occurred. 1548 bool updateStateIfReorder() { 1549 if (ReorderIndices.empty()) 1550 return false; 1551 InstructionsState S = getSameOpcode(Scalars, ReorderIndices.front()); 1552 setOperations(S); 1553 return true; 1554 } 1555 1556 #ifndef NDEBUG 1557 /// Debug printer. 1558 LLVM_DUMP_METHOD void dump() const { 1559 dbgs() << Idx << ".\n"; 1560 for (unsigned OpI = 0, OpE = Operands.size(); OpI != OpE; ++OpI) { 1561 dbgs() << "Operand " << OpI << ":\n"; 1562 for (const Value *V : Operands[OpI]) 1563 dbgs().indent(2) << *V << "\n"; 1564 } 1565 dbgs() << "Scalars: \n"; 1566 for (Value *V : Scalars) 1567 dbgs().indent(2) << *V << "\n"; 1568 dbgs() << "NeedToGather: " << NeedToGather << "\n"; 1569 dbgs() << "MainOp: "; 1570 if (MainOp) 1571 dbgs() << *MainOp << "\n"; 1572 else 1573 dbgs() << "NULL\n"; 1574 dbgs() << "AltOp: "; 1575 if (AltOp) 1576 dbgs() << *AltOp << "\n"; 1577 else 1578 dbgs() << "NULL\n"; 1579 dbgs() << "VectorizedValue: "; 1580 if (VectorizedValue) 1581 dbgs() << *VectorizedValue << "\n"; 1582 else 1583 dbgs() << "NULL\n"; 1584 dbgs() << "ReuseShuffleIndices: "; 1585 if (ReuseShuffleIndices.empty()) 1586 dbgs() << "Emtpy"; 1587 else 1588 for (unsigned ReuseIdx : ReuseShuffleIndices) 1589 dbgs() << ReuseIdx << ", "; 1590 dbgs() << "\n"; 1591 dbgs() << "ReorderIndices: "; 1592 for (unsigned ReorderIdx : ReorderIndices) 1593 dbgs() << ReorderIdx << ", "; 1594 dbgs() << "\n"; 1595 dbgs() << "UserTreeIndices: "; 1596 for (const auto &EInfo : UserTreeIndices) 1597 dbgs() << EInfo << ", "; 1598 dbgs() << "\n"; 1599 } 1600 #endif 1601 }; 1602 1603 /// Create a new VectorizableTree entry. 1604 TreeEntry *newTreeEntry(ArrayRef<Value *> VL, Optional<ScheduleData *> Bundle, 1605 const InstructionsState &S, 1606 const EdgeInfo &UserTreeIdx, 1607 ArrayRef<unsigned> ReuseShuffleIndices = None, 1608 ArrayRef<unsigned> ReorderIndices = None) { 1609 bool Vectorized = (bool)Bundle; 1610 VectorizableTree.push_back(std::make_unique<TreeEntry>(VectorizableTree)); 1611 TreeEntry *Last = VectorizableTree.back().get(); 1612 Last->Idx = VectorizableTree.size() - 1; 1613 Last->Scalars.insert(Last->Scalars.begin(), VL.begin(), VL.end()); 1614 Last->NeedToGather = !Vectorized; 1615 Last->ReuseShuffleIndices.append(ReuseShuffleIndices.begin(), 1616 ReuseShuffleIndices.end()); 1617 Last->ReorderIndices = ReorderIndices; 1618 Last->setOperations(S); 1619 if (Vectorized) { 1620 for (int i = 0, e = VL.size(); i != e; ++i) { 1621 assert(!getTreeEntry(VL[i]) && "Scalar already in tree!"); 1622 ScalarToTreeEntry[VL[i]] = Last; 1623 } 1624 // Update the scheduler bundle to point to this TreeEntry. 1625 unsigned Lane = 0; 1626 for (ScheduleData *BundleMember = Bundle.getValue(); BundleMember; 1627 BundleMember = BundleMember->NextInBundle) { 1628 BundleMember->TE = Last; 1629 BundleMember->Lane = Lane; 1630 ++Lane; 1631 } 1632 assert((!Bundle.getValue() || Lane == VL.size()) && 1633 "Bundle and VL out of sync"); 1634 } else { 1635 MustGather.insert(VL.begin(), VL.end()); 1636 } 1637 1638 if (UserTreeIdx.UserTE) 1639 Last->UserTreeIndices.push_back(UserTreeIdx); 1640 1641 return Last; 1642 } 1643 1644 /// -- Vectorization State -- 1645 /// Holds all of the tree entries. 1646 TreeEntry::VecTreeTy VectorizableTree; 1647 1648 #ifndef NDEBUG 1649 /// Debug printer. 1650 LLVM_DUMP_METHOD void dumpVectorizableTree() const { 1651 for (unsigned Id = 0, IdE = VectorizableTree.size(); Id != IdE; ++Id) { 1652 VectorizableTree[Id]->dump(); 1653 dbgs() << "\n"; 1654 } 1655 } 1656 #endif 1657 1658 TreeEntry *getTreeEntry(Value *V) { 1659 auto I = ScalarToTreeEntry.find(V); 1660 if (I != ScalarToTreeEntry.end()) 1661 return I->second; 1662 return nullptr; 1663 } 1664 1665 const TreeEntry *getTreeEntry(Value *V) const { 1666 auto I = ScalarToTreeEntry.find(V); 1667 if (I != ScalarToTreeEntry.end()) 1668 return I->second; 1669 return nullptr; 1670 } 1671 1672 /// Maps a specific scalar to its tree entry. 1673 SmallDenseMap<Value*, TreeEntry *> ScalarToTreeEntry; 1674 1675 /// A list of scalars that we found that we need to keep as scalars. 1676 ValueSet MustGather; 1677 1678 /// This POD struct describes one external user in the vectorized tree. 1679 struct ExternalUser { 1680 ExternalUser(Value *S, llvm::User *U, int L) 1681 : Scalar(S), User(U), Lane(L) {} 1682 1683 // Which scalar in our function. 1684 Value *Scalar; 1685 1686 // Which user that uses the scalar. 1687 llvm::User *User; 1688 1689 // Which lane does the scalar belong to. 1690 int Lane; 1691 }; 1692 using UserList = SmallVector<ExternalUser, 16>; 1693 1694 /// Checks if two instructions may access the same memory. 1695 /// 1696 /// \p Loc1 is the location of \p Inst1. It is passed explicitly because it 1697 /// is invariant in the calling loop. 1698 bool isAliased(const MemoryLocation &Loc1, Instruction *Inst1, 1699 Instruction *Inst2) { 1700 // First check if the result is already in the cache. 1701 AliasCacheKey key = std::make_pair(Inst1, Inst2); 1702 Optional<bool> &result = AliasCache[key]; 1703 if (result.hasValue()) { 1704 return result.getValue(); 1705 } 1706 MemoryLocation Loc2 = getLocation(Inst2, AA); 1707 bool aliased = true; 1708 if (Loc1.Ptr && Loc2.Ptr && isSimple(Inst1) && isSimple(Inst2)) { 1709 // Do the alias check. 1710 aliased = AA->alias(Loc1, Loc2); 1711 } 1712 // Store the result in the cache. 1713 result = aliased; 1714 return aliased; 1715 } 1716 1717 using AliasCacheKey = std::pair<Instruction *, Instruction *>; 1718 1719 /// Cache for alias results. 1720 /// TODO: consider moving this to the AliasAnalysis itself. 1721 DenseMap<AliasCacheKey, Optional<bool>> AliasCache; 1722 1723 /// Removes an instruction from its block and eventually deletes it. 1724 /// It's like Instruction::eraseFromParent() except that the actual deletion 1725 /// is delayed until BoUpSLP is destructed. 1726 /// This is required to ensure that there are no incorrect collisions in the 1727 /// AliasCache, which can happen if a new instruction is allocated at the 1728 /// same address as a previously deleted instruction. 1729 void eraseInstruction(Instruction *I, bool ReplaceOpsWithUndef = false) { 1730 auto It = DeletedInstructions.try_emplace(I, ReplaceOpsWithUndef).first; 1731 It->getSecond() = It->getSecond() && ReplaceOpsWithUndef; 1732 } 1733 1734 /// Temporary store for deleted instructions. Instructions will be deleted 1735 /// eventually when the BoUpSLP is destructed. 1736 DenseMap<Instruction *, bool> DeletedInstructions; 1737 1738 /// A list of values that need to extracted out of the tree. 1739 /// This list holds pairs of (Internal Scalar : External User). External User 1740 /// can be nullptr, it means that this Internal Scalar will be used later, 1741 /// after vectorization. 1742 UserList ExternalUses; 1743 1744 /// Values used only by @llvm.assume calls. 1745 SmallPtrSet<const Value *, 32> EphValues; 1746 1747 /// Holds all of the instructions that we gathered. 1748 SetVector<Instruction *> GatherSeq; 1749 1750 /// A list of blocks that we are going to CSE. 1751 SetVector<BasicBlock *> CSEBlocks; 1752 1753 /// Contains all scheduling relevant data for an instruction. 1754 /// A ScheduleData either represents a single instruction or a member of an 1755 /// instruction bundle (= a group of instructions which is combined into a 1756 /// vector instruction). 1757 struct ScheduleData { 1758 // The initial value for the dependency counters. It means that the 1759 // dependencies are not calculated yet. 1760 enum { InvalidDeps = -1 }; 1761 1762 ScheduleData() = default; 1763 1764 void init(int BlockSchedulingRegionID, Value *OpVal) { 1765 FirstInBundle = this; 1766 NextInBundle = nullptr; 1767 NextLoadStore = nullptr; 1768 IsScheduled = false; 1769 SchedulingRegionID = BlockSchedulingRegionID; 1770 UnscheduledDepsInBundle = UnscheduledDeps; 1771 clearDependencies(); 1772 OpValue = OpVal; 1773 TE = nullptr; 1774 Lane = -1; 1775 } 1776 1777 /// Returns true if the dependency information has been calculated. 1778 bool hasValidDependencies() const { return Dependencies != InvalidDeps; } 1779 1780 /// Returns true for single instructions and for bundle representatives 1781 /// (= the head of a bundle). 1782 bool isSchedulingEntity() const { return FirstInBundle == this; } 1783 1784 /// Returns true if it represents an instruction bundle and not only a 1785 /// single instruction. 1786 bool isPartOfBundle() const { 1787 return NextInBundle != nullptr || FirstInBundle != this; 1788 } 1789 1790 /// Returns true if it is ready for scheduling, i.e. it has no more 1791 /// unscheduled depending instructions/bundles. 1792 bool isReady() const { 1793 assert(isSchedulingEntity() && 1794 "can't consider non-scheduling entity for ready list"); 1795 return UnscheduledDepsInBundle == 0 && !IsScheduled; 1796 } 1797 1798 /// Modifies the number of unscheduled dependencies, also updating it for 1799 /// the whole bundle. 1800 int incrementUnscheduledDeps(int Incr) { 1801 UnscheduledDeps += Incr; 1802 return FirstInBundle->UnscheduledDepsInBundle += Incr; 1803 } 1804 1805 /// Sets the number of unscheduled dependencies to the number of 1806 /// dependencies. 1807 void resetUnscheduledDeps() { 1808 incrementUnscheduledDeps(Dependencies - UnscheduledDeps); 1809 } 1810 1811 /// Clears all dependency information. 1812 void clearDependencies() { 1813 Dependencies = InvalidDeps; 1814 resetUnscheduledDeps(); 1815 MemoryDependencies.clear(); 1816 } 1817 1818 void dump(raw_ostream &os) const { 1819 if (!isSchedulingEntity()) { 1820 os << "/ " << *Inst; 1821 } else if (NextInBundle) { 1822 os << '[' << *Inst; 1823 ScheduleData *SD = NextInBundle; 1824 while (SD) { 1825 os << ';' << *SD->Inst; 1826 SD = SD->NextInBundle; 1827 } 1828 os << ']'; 1829 } else { 1830 os << *Inst; 1831 } 1832 } 1833 1834 Instruction *Inst = nullptr; 1835 1836 /// Points to the head in an instruction bundle (and always to this for 1837 /// single instructions). 1838 ScheduleData *FirstInBundle = nullptr; 1839 1840 /// Single linked list of all instructions in a bundle. Null if it is a 1841 /// single instruction. 1842 ScheduleData *NextInBundle = nullptr; 1843 1844 /// Single linked list of all memory instructions (e.g. load, store, call) 1845 /// in the block - until the end of the scheduling region. 1846 ScheduleData *NextLoadStore = nullptr; 1847 1848 /// The dependent memory instructions. 1849 /// This list is derived on demand in calculateDependencies(). 1850 SmallVector<ScheduleData *, 4> MemoryDependencies; 1851 1852 /// This ScheduleData is in the current scheduling region if this matches 1853 /// the current SchedulingRegionID of BlockScheduling. 1854 int SchedulingRegionID = 0; 1855 1856 /// Used for getting a "good" final ordering of instructions. 1857 int SchedulingPriority = 0; 1858 1859 /// The number of dependencies. Constitutes of the number of users of the 1860 /// instruction plus the number of dependent memory instructions (if any). 1861 /// This value is calculated on demand. 1862 /// If InvalidDeps, the number of dependencies is not calculated yet. 1863 int Dependencies = InvalidDeps; 1864 1865 /// The number of dependencies minus the number of dependencies of scheduled 1866 /// instructions. As soon as this is zero, the instruction/bundle gets ready 1867 /// for scheduling. 1868 /// Note that this is negative as long as Dependencies is not calculated. 1869 int UnscheduledDeps = InvalidDeps; 1870 1871 /// The sum of UnscheduledDeps in a bundle. Equals to UnscheduledDeps for 1872 /// single instructions. 1873 int UnscheduledDepsInBundle = InvalidDeps; 1874 1875 /// True if this instruction is scheduled (or considered as scheduled in the 1876 /// dry-run). 1877 bool IsScheduled = false; 1878 1879 /// Opcode of the current instruction in the schedule data. 1880 Value *OpValue = nullptr; 1881 1882 /// The TreeEntry that this instruction corresponds to. 1883 TreeEntry *TE = nullptr; 1884 1885 /// The lane of this node in the TreeEntry. 1886 int Lane = -1; 1887 }; 1888 1889 #ifndef NDEBUG 1890 friend inline raw_ostream &operator<<(raw_ostream &os, 1891 const BoUpSLP::ScheduleData &SD) { 1892 SD.dump(os); 1893 return os; 1894 } 1895 #endif 1896 1897 friend struct GraphTraits<BoUpSLP *>; 1898 friend struct DOTGraphTraits<BoUpSLP *>; 1899 1900 /// Contains all scheduling data for a basic block. 1901 struct BlockScheduling { 1902 BlockScheduling(BasicBlock *BB) 1903 : BB(BB), ChunkSize(BB->size()), ChunkPos(ChunkSize) {} 1904 1905 void clear() { 1906 ReadyInsts.clear(); 1907 ScheduleStart = nullptr; 1908 ScheduleEnd = nullptr; 1909 FirstLoadStoreInRegion = nullptr; 1910 LastLoadStoreInRegion = nullptr; 1911 1912 // Reduce the maximum schedule region size by the size of the 1913 // previous scheduling run. 1914 ScheduleRegionSizeLimit -= ScheduleRegionSize; 1915 if (ScheduleRegionSizeLimit < MinScheduleRegionSize) 1916 ScheduleRegionSizeLimit = MinScheduleRegionSize; 1917 ScheduleRegionSize = 0; 1918 1919 // Make a new scheduling region, i.e. all existing ScheduleData is not 1920 // in the new region yet. 1921 ++SchedulingRegionID; 1922 } 1923 1924 ScheduleData *getScheduleData(Value *V) { 1925 ScheduleData *SD = ScheduleDataMap[V]; 1926 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 1927 return SD; 1928 return nullptr; 1929 } 1930 1931 ScheduleData *getScheduleData(Value *V, Value *Key) { 1932 if (V == Key) 1933 return getScheduleData(V); 1934 auto I = ExtraScheduleDataMap.find(V); 1935 if (I != ExtraScheduleDataMap.end()) { 1936 ScheduleData *SD = I->second[Key]; 1937 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 1938 return SD; 1939 } 1940 return nullptr; 1941 } 1942 1943 bool isInSchedulingRegion(ScheduleData *SD) { 1944 return SD->SchedulingRegionID == SchedulingRegionID; 1945 } 1946 1947 /// Marks an instruction as scheduled and puts all dependent ready 1948 /// instructions into the ready-list. 1949 template <typename ReadyListType> 1950 void schedule(ScheduleData *SD, ReadyListType &ReadyList) { 1951 SD->IsScheduled = true; 1952 LLVM_DEBUG(dbgs() << "SLP: schedule " << *SD << "\n"); 1953 1954 ScheduleData *BundleMember = SD; 1955 while (BundleMember) { 1956 if (BundleMember->Inst != BundleMember->OpValue) { 1957 BundleMember = BundleMember->NextInBundle; 1958 continue; 1959 } 1960 // Handle the def-use chain dependencies. 1961 1962 // Decrement the unscheduled counter and insert to ready list if ready. 1963 auto &&DecrUnsched = [this, &ReadyList](Instruction *I) { 1964 doForAllOpcodes(I, [&ReadyList](ScheduleData *OpDef) { 1965 if (OpDef && OpDef->hasValidDependencies() && 1966 OpDef->incrementUnscheduledDeps(-1) == 0) { 1967 // There are no more unscheduled dependencies after 1968 // decrementing, so we can put the dependent instruction 1969 // into the ready list. 1970 ScheduleData *DepBundle = OpDef->FirstInBundle; 1971 assert(!DepBundle->IsScheduled && 1972 "already scheduled bundle gets ready"); 1973 ReadyList.insert(DepBundle); 1974 LLVM_DEBUG(dbgs() 1975 << "SLP: gets ready (def): " << *DepBundle << "\n"); 1976 } 1977 }); 1978 }; 1979 1980 // If BundleMember is a vector bundle, its operands may have been 1981 // reordered duiring buildTree(). We therefore need to get its operands 1982 // through the TreeEntry. 1983 if (TreeEntry *TE = BundleMember->TE) { 1984 int Lane = BundleMember->Lane; 1985 assert(Lane >= 0 && "Lane not set"); 1986 for (unsigned OpIdx = 0, NumOperands = TE->getNumOperands(); 1987 OpIdx != NumOperands; ++OpIdx) 1988 if (auto *I = dyn_cast<Instruction>(TE->getOperand(OpIdx)[Lane])) 1989 DecrUnsched(I); 1990 } else { 1991 // If BundleMember is a stand-alone instruction, no operand reordering 1992 // has taken place, so we directly access its operands. 1993 for (Use &U : BundleMember->Inst->operands()) 1994 if (auto *I = dyn_cast<Instruction>(U.get())) 1995 DecrUnsched(I); 1996 } 1997 // Handle the memory dependencies. 1998 for (ScheduleData *MemoryDepSD : BundleMember->MemoryDependencies) { 1999 if (MemoryDepSD->incrementUnscheduledDeps(-1) == 0) { 2000 // There are no more unscheduled dependencies after decrementing, 2001 // so we can put the dependent instruction into the ready list. 2002 ScheduleData *DepBundle = MemoryDepSD->FirstInBundle; 2003 assert(!DepBundle->IsScheduled && 2004 "already scheduled bundle gets ready"); 2005 ReadyList.insert(DepBundle); 2006 LLVM_DEBUG(dbgs() 2007 << "SLP: gets ready (mem): " << *DepBundle << "\n"); 2008 } 2009 } 2010 BundleMember = BundleMember->NextInBundle; 2011 } 2012 } 2013 2014 void doForAllOpcodes(Value *V, 2015 function_ref<void(ScheduleData *SD)> Action) { 2016 if (ScheduleData *SD = getScheduleData(V)) 2017 Action(SD); 2018 auto I = ExtraScheduleDataMap.find(V); 2019 if (I != ExtraScheduleDataMap.end()) 2020 for (auto &P : I->second) 2021 if (P.second->SchedulingRegionID == SchedulingRegionID) 2022 Action(P.second); 2023 } 2024 2025 /// Put all instructions into the ReadyList which are ready for scheduling. 2026 template <typename ReadyListType> 2027 void initialFillReadyList(ReadyListType &ReadyList) { 2028 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 2029 doForAllOpcodes(I, [&](ScheduleData *SD) { 2030 if (SD->isSchedulingEntity() && SD->isReady()) { 2031 ReadyList.insert(SD); 2032 LLVM_DEBUG(dbgs() 2033 << "SLP: initially in ready list: " << *I << "\n"); 2034 } 2035 }); 2036 } 2037 } 2038 2039 /// Checks if a bundle of instructions can be scheduled, i.e. has no 2040 /// cyclic dependencies. This is only a dry-run, no instructions are 2041 /// actually moved at this stage. 2042 /// \returns the scheduling bundle. The returned Optional value is non-None 2043 /// if \p VL is allowed to be scheduled. 2044 Optional<ScheduleData *> 2045 tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 2046 const InstructionsState &S); 2047 2048 /// Un-bundles a group of instructions. 2049 void cancelScheduling(ArrayRef<Value *> VL, Value *OpValue); 2050 2051 /// Allocates schedule data chunk. 2052 ScheduleData *allocateScheduleDataChunks(); 2053 2054 /// Extends the scheduling region so that V is inside the region. 2055 /// \returns true if the region size is within the limit. 2056 bool extendSchedulingRegion(Value *V, const InstructionsState &S); 2057 2058 /// Initialize the ScheduleData structures for new instructions in the 2059 /// scheduling region. 2060 void initScheduleData(Instruction *FromI, Instruction *ToI, 2061 ScheduleData *PrevLoadStore, 2062 ScheduleData *NextLoadStore); 2063 2064 /// Updates the dependency information of a bundle and of all instructions/ 2065 /// bundles which depend on the original bundle. 2066 void calculateDependencies(ScheduleData *SD, bool InsertInReadyList, 2067 BoUpSLP *SLP); 2068 2069 /// Sets all instruction in the scheduling region to un-scheduled. 2070 void resetSchedule(); 2071 2072 BasicBlock *BB; 2073 2074 /// Simple memory allocation for ScheduleData. 2075 std::vector<std::unique_ptr<ScheduleData[]>> ScheduleDataChunks; 2076 2077 /// The size of a ScheduleData array in ScheduleDataChunks. 2078 int ChunkSize; 2079 2080 /// The allocator position in the current chunk, which is the last entry 2081 /// of ScheduleDataChunks. 2082 int ChunkPos; 2083 2084 /// Attaches ScheduleData to Instruction. 2085 /// Note that the mapping survives during all vectorization iterations, i.e. 2086 /// ScheduleData structures are recycled. 2087 DenseMap<Value *, ScheduleData *> ScheduleDataMap; 2088 2089 /// Attaches ScheduleData to Instruction with the leading key. 2090 DenseMap<Value *, SmallDenseMap<Value *, ScheduleData *>> 2091 ExtraScheduleDataMap; 2092 2093 struct ReadyList : SmallVector<ScheduleData *, 8> { 2094 void insert(ScheduleData *SD) { push_back(SD); } 2095 }; 2096 2097 /// The ready-list for scheduling (only used for the dry-run). 2098 ReadyList ReadyInsts; 2099 2100 /// The first instruction of the scheduling region. 2101 Instruction *ScheduleStart = nullptr; 2102 2103 /// The first instruction _after_ the scheduling region. 2104 Instruction *ScheduleEnd = nullptr; 2105 2106 /// The first memory accessing instruction in the scheduling region 2107 /// (can be null). 2108 ScheduleData *FirstLoadStoreInRegion = nullptr; 2109 2110 /// The last memory accessing instruction in the scheduling region 2111 /// (can be null). 2112 ScheduleData *LastLoadStoreInRegion = nullptr; 2113 2114 /// The current size of the scheduling region. 2115 int ScheduleRegionSize = 0; 2116 2117 /// The maximum size allowed for the scheduling region. 2118 int ScheduleRegionSizeLimit = ScheduleRegionSizeBudget; 2119 2120 /// The ID of the scheduling region. For a new vectorization iteration this 2121 /// is incremented which "removes" all ScheduleData from the region. 2122 // Make sure that the initial SchedulingRegionID is greater than the 2123 // initial SchedulingRegionID in ScheduleData (which is 0). 2124 int SchedulingRegionID = 1; 2125 }; 2126 2127 /// Attaches the BlockScheduling structures to basic blocks. 2128 MapVector<BasicBlock *, std::unique_ptr<BlockScheduling>> BlocksSchedules; 2129 2130 /// Performs the "real" scheduling. Done before vectorization is actually 2131 /// performed in a basic block. 2132 void scheduleBlock(BlockScheduling *BS); 2133 2134 /// List of users to ignore during scheduling and that don't need extracting. 2135 ArrayRef<Value *> UserIgnoreList; 2136 2137 using OrdersType = SmallVector<unsigned, 4>; 2138 /// A DenseMapInfo implementation for holding DenseMaps and DenseSets of 2139 /// sorted SmallVectors of unsigned. 2140 struct OrdersTypeDenseMapInfo { 2141 static OrdersType getEmptyKey() { 2142 OrdersType V; 2143 V.push_back(~1U); 2144 return V; 2145 } 2146 2147 static OrdersType getTombstoneKey() { 2148 OrdersType V; 2149 V.push_back(~2U); 2150 return V; 2151 } 2152 2153 static unsigned getHashValue(const OrdersType &V) { 2154 return static_cast<unsigned>(hash_combine_range(V.begin(), V.end())); 2155 } 2156 2157 static bool isEqual(const OrdersType &LHS, const OrdersType &RHS) { 2158 return LHS == RHS; 2159 } 2160 }; 2161 2162 /// Contains orders of operations along with the number of bundles that have 2163 /// operations in this order. It stores only those orders that require 2164 /// reordering, if reordering is not required it is counted using \a 2165 /// NumOpsWantToKeepOriginalOrder. 2166 DenseMap<OrdersType, unsigned, OrdersTypeDenseMapInfo> NumOpsWantToKeepOrder; 2167 /// Number of bundles that do not require reordering. 2168 unsigned NumOpsWantToKeepOriginalOrder = 0; 2169 2170 // Analysis and block reference. 2171 Function *F; 2172 ScalarEvolution *SE; 2173 TargetTransformInfo *TTI; 2174 TargetLibraryInfo *TLI; 2175 AliasAnalysis *AA; 2176 LoopInfo *LI; 2177 DominatorTree *DT; 2178 AssumptionCache *AC; 2179 DemandedBits *DB; 2180 const DataLayout *DL; 2181 OptimizationRemarkEmitter *ORE; 2182 2183 unsigned MaxVecRegSize; // This is set by TTI or overridden by cl::opt. 2184 unsigned MinVecRegSize; // Set by cl::opt (default: 128). 2185 2186 /// Instruction builder to construct the vectorized tree. 2187 IRBuilder<> Builder; 2188 2189 /// A map of scalar integer values to the smallest bit width with which they 2190 /// can legally be represented. The values map to (width, signed) pairs, 2191 /// where "width" indicates the minimum bit width and "signed" is True if the 2192 /// value must be signed-extended, rather than zero-extended, back to its 2193 /// original width. 2194 MapVector<Value *, std::pair<uint64_t, bool>> MinBWs; 2195 }; 2196 2197 } // end namespace slpvectorizer 2198 2199 template <> struct GraphTraits<BoUpSLP *> { 2200 using TreeEntry = BoUpSLP::TreeEntry; 2201 2202 /// NodeRef has to be a pointer per the GraphWriter. 2203 using NodeRef = TreeEntry *; 2204 2205 using ContainerTy = BoUpSLP::TreeEntry::VecTreeTy; 2206 2207 /// Add the VectorizableTree to the index iterator to be able to return 2208 /// TreeEntry pointers. 2209 struct ChildIteratorType 2210 : public iterator_adaptor_base< 2211 ChildIteratorType, SmallVector<BoUpSLP::EdgeInfo, 1>::iterator> { 2212 ContainerTy &VectorizableTree; 2213 2214 ChildIteratorType(SmallVector<BoUpSLP::EdgeInfo, 1>::iterator W, 2215 ContainerTy &VT) 2216 : ChildIteratorType::iterator_adaptor_base(W), VectorizableTree(VT) {} 2217 2218 NodeRef operator*() { return I->UserTE; } 2219 }; 2220 2221 static NodeRef getEntryNode(BoUpSLP &R) { 2222 return R.VectorizableTree[0].get(); 2223 } 2224 2225 static ChildIteratorType child_begin(NodeRef N) { 2226 return {N->UserTreeIndices.begin(), N->Container}; 2227 } 2228 2229 static ChildIteratorType child_end(NodeRef N) { 2230 return {N->UserTreeIndices.end(), N->Container}; 2231 } 2232 2233 /// For the node iterator we just need to turn the TreeEntry iterator into a 2234 /// TreeEntry* iterator so that it dereferences to NodeRef. 2235 class nodes_iterator { 2236 using ItTy = ContainerTy::iterator; 2237 ItTy It; 2238 2239 public: 2240 nodes_iterator(const ItTy &It2) : It(It2) {} 2241 NodeRef operator*() { return It->get(); } 2242 nodes_iterator operator++() { 2243 ++It; 2244 return *this; 2245 } 2246 bool operator!=(const nodes_iterator &N2) const { return N2.It != It; } 2247 }; 2248 2249 static nodes_iterator nodes_begin(BoUpSLP *R) { 2250 return nodes_iterator(R->VectorizableTree.begin()); 2251 } 2252 2253 static nodes_iterator nodes_end(BoUpSLP *R) { 2254 return nodes_iterator(R->VectorizableTree.end()); 2255 } 2256 2257 static unsigned size(BoUpSLP *R) { return R->VectorizableTree.size(); } 2258 }; 2259 2260 template <> struct DOTGraphTraits<BoUpSLP *> : public DefaultDOTGraphTraits { 2261 using TreeEntry = BoUpSLP::TreeEntry; 2262 2263 DOTGraphTraits(bool isSimple = false) : DefaultDOTGraphTraits(isSimple) {} 2264 2265 std::string getNodeLabel(const TreeEntry *Entry, const BoUpSLP *R) { 2266 std::string Str; 2267 raw_string_ostream OS(Str); 2268 if (isSplat(Entry->Scalars)) { 2269 OS << "<splat> " << *Entry->Scalars[0]; 2270 return Str; 2271 } 2272 for (auto V : Entry->Scalars) { 2273 OS << *V; 2274 if (std::any_of( 2275 R->ExternalUses.begin(), R->ExternalUses.end(), 2276 [&](const BoUpSLP::ExternalUser &EU) { return EU.Scalar == V; })) 2277 OS << " <extract>"; 2278 OS << "\n"; 2279 } 2280 return Str; 2281 } 2282 2283 static std::string getNodeAttributes(const TreeEntry *Entry, 2284 const BoUpSLP *) { 2285 if (Entry->NeedToGather) 2286 return "color=red"; 2287 return ""; 2288 } 2289 }; 2290 2291 } // end namespace llvm 2292 2293 BoUpSLP::~BoUpSLP() { 2294 for (const auto &Pair : DeletedInstructions) { 2295 // Replace operands of ignored instructions with Undefs in case if they were 2296 // marked for deletion. 2297 if (Pair.getSecond()) { 2298 Value *Undef = UndefValue::get(Pair.getFirst()->getType()); 2299 Pair.getFirst()->replaceAllUsesWith(Undef); 2300 } 2301 Pair.getFirst()->dropAllReferences(); 2302 } 2303 for (const auto &Pair : DeletedInstructions) { 2304 assert(Pair.getFirst()->use_empty() && 2305 "trying to erase instruction with users."); 2306 Pair.getFirst()->eraseFromParent(); 2307 } 2308 } 2309 2310 void BoUpSLP::eraseInstructions(ArrayRef<Value *> AV) { 2311 for (auto *V : AV) { 2312 if (auto *I = dyn_cast<Instruction>(V)) 2313 eraseInstruction(I, /*ReplaceWithUndef=*/true); 2314 }; 2315 } 2316 2317 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2318 ArrayRef<Value *> UserIgnoreLst) { 2319 ExtraValueToDebugLocsMap ExternallyUsedValues; 2320 buildTree(Roots, ExternallyUsedValues, UserIgnoreLst); 2321 } 2322 2323 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2324 ExtraValueToDebugLocsMap &ExternallyUsedValues, 2325 ArrayRef<Value *> UserIgnoreLst) { 2326 deleteTree(); 2327 UserIgnoreList = UserIgnoreLst; 2328 if (!allSameType(Roots)) 2329 return; 2330 buildTree_rec(Roots, 0, EdgeInfo()); 2331 2332 // Collect the values that we need to extract from the tree. 2333 for (auto &TEPtr : VectorizableTree) { 2334 TreeEntry *Entry = TEPtr.get(); 2335 2336 // No need to handle users of gathered values. 2337 if (Entry->NeedToGather) 2338 continue; 2339 2340 // For each lane: 2341 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 2342 Value *Scalar = Entry->Scalars[Lane]; 2343 int FoundLane = Lane; 2344 if (!Entry->ReuseShuffleIndices.empty()) { 2345 FoundLane = 2346 std::distance(Entry->ReuseShuffleIndices.begin(), 2347 llvm::find(Entry->ReuseShuffleIndices, FoundLane)); 2348 } 2349 2350 // Check if the scalar is externally used as an extra arg. 2351 auto ExtI = ExternallyUsedValues.find(Scalar); 2352 if (ExtI != ExternallyUsedValues.end()) { 2353 LLVM_DEBUG(dbgs() << "SLP: Need to extract: Extra arg from lane " 2354 << Lane << " from " << *Scalar << ".\n"); 2355 ExternalUses.emplace_back(Scalar, nullptr, FoundLane); 2356 } 2357 for (User *U : Scalar->users()) { 2358 LLVM_DEBUG(dbgs() << "SLP: Checking user:" << *U << ".\n"); 2359 2360 Instruction *UserInst = dyn_cast<Instruction>(U); 2361 if (!UserInst) 2362 continue; 2363 2364 // Skip in-tree scalars that become vectors 2365 if (TreeEntry *UseEntry = getTreeEntry(U)) { 2366 Value *UseScalar = UseEntry->Scalars[0]; 2367 // Some in-tree scalars will remain as scalar in vectorized 2368 // instructions. If that is the case, the one in Lane 0 will 2369 // be used. 2370 if (UseScalar != U || 2371 !InTreeUserNeedToExtract(Scalar, UserInst, TLI)) { 2372 LLVM_DEBUG(dbgs() << "SLP: \tInternal user will be removed:" << *U 2373 << ".\n"); 2374 assert(!UseEntry->NeedToGather && "Bad state"); 2375 continue; 2376 } 2377 } 2378 2379 // Ignore users in the user ignore list. 2380 if (is_contained(UserIgnoreList, UserInst)) 2381 continue; 2382 2383 LLVM_DEBUG(dbgs() << "SLP: Need to extract:" << *U << " from lane " 2384 << Lane << " from " << *Scalar << ".\n"); 2385 ExternalUses.push_back(ExternalUser(Scalar, U, FoundLane)); 2386 } 2387 } 2388 } 2389 } 2390 2391 void BoUpSLP::buildTree_rec(ArrayRef<Value *> VL, unsigned Depth, 2392 const EdgeInfo &UserTreeIdx) { 2393 assert((allConstant(VL) || allSameType(VL)) && "Invalid types!"); 2394 2395 InstructionsState S = getSameOpcode(VL); 2396 if (Depth == RecursionMaxDepth) { 2397 LLVM_DEBUG(dbgs() << "SLP: Gathering due to max recursion depth.\n"); 2398 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2399 return; 2400 } 2401 2402 // Don't handle vectors. 2403 if (S.OpValue->getType()->isVectorTy()) { 2404 LLVM_DEBUG(dbgs() << "SLP: Gathering due to vector type.\n"); 2405 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2406 return; 2407 } 2408 2409 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) 2410 if (SI->getValueOperand()->getType()->isVectorTy()) { 2411 LLVM_DEBUG(dbgs() << "SLP: Gathering due to store vector type.\n"); 2412 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2413 return; 2414 } 2415 2416 // If all of the operands are identical or constant we have a simple solution. 2417 if (allConstant(VL) || isSplat(VL) || !allSameBlock(VL) || !S.getOpcode()) { 2418 LLVM_DEBUG(dbgs() << "SLP: Gathering due to C,S,B,O. \n"); 2419 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2420 return; 2421 } 2422 2423 // We now know that this is a vector of instructions of the same type from 2424 // the same block. 2425 2426 // Don't vectorize ephemeral values. 2427 for (Value *V : VL) { 2428 if (EphValues.count(V)) { 2429 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2430 << ") is ephemeral.\n"); 2431 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2432 return; 2433 } 2434 } 2435 2436 // Check if this is a duplicate of another entry. 2437 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 2438 LLVM_DEBUG(dbgs() << "SLP: \tChecking bundle: " << *S.OpValue << ".\n"); 2439 if (!E->isSame(VL)) { 2440 LLVM_DEBUG(dbgs() << "SLP: Gathering due to partial overlap.\n"); 2441 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2442 return; 2443 } 2444 // Record the reuse of the tree node. FIXME, currently this is only used to 2445 // properly draw the graph rather than for the actual vectorization. 2446 E->UserTreeIndices.push_back(UserTreeIdx); 2447 LLVM_DEBUG(dbgs() << "SLP: Perfect diamond merge at " << *S.OpValue 2448 << ".\n"); 2449 return; 2450 } 2451 2452 // Check that none of the instructions in the bundle are already in the tree. 2453 for (Value *V : VL) { 2454 auto *I = dyn_cast<Instruction>(V); 2455 if (!I) 2456 continue; 2457 if (getTreeEntry(I)) { 2458 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2459 << ") is already in tree.\n"); 2460 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2461 return; 2462 } 2463 } 2464 2465 // If any of the scalars is marked as a value that needs to stay scalar, then 2466 // we need to gather the scalars. 2467 // The reduction nodes (stored in UserIgnoreList) also should stay scalar. 2468 for (Value *V : VL) { 2469 if (MustGather.count(V) || is_contained(UserIgnoreList, V)) { 2470 LLVM_DEBUG(dbgs() << "SLP: Gathering due to gathered scalar.\n"); 2471 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2472 return; 2473 } 2474 } 2475 2476 // Check that all of the users of the scalars that we want to vectorize are 2477 // schedulable. 2478 auto *VL0 = cast<Instruction>(S.OpValue); 2479 BasicBlock *BB = VL0->getParent(); 2480 2481 if (!DT->isReachableFromEntry(BB)) { 2482 // Don't go into unreachable blocks. They may contain instructions with 2483 // dependency cycles which confuse the final scheduling. 2484 LLVM_DEBUG(dbgs() << "SLP: bundle in unreachable block.\n"); 2485 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2486 return; 2487 } 2488 2489 // Check that every instruction appears once in this bundle. 2490 SmallVector<unsigned, 4> ReuseShuffleIndicies; 2491 SmallVector<Value *, 4> UniqueValues; 2492 DenseMap<Value *, unsigned> UniquePositions; 2493 for (Value *V : VL) { 2494 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 2495 ReuseShuffleIndicies.emplace_back(Res.first->second); 2496 if (Res.second) 2497 UniqueValues.emplace_back(V); 2498 } 2499 size_t NumUniqueScalarValues = UniqueValues.size(); 2500 if (NumUniqueScalarValues == VL.size()) { 2501 ReuseShuffleIndicies.clear(); 2502 } else { 2503 LLVM_DEBUG(dbgs() << "SLP: Shuffle for reused scalars.\n"); 2504 if (NumUniqueScalarValues <= 1 || 2505 !llvm::isPowerOf2_32(NumUniqueScalarValues)) { 2506 LLVM_DEBUG(dbgs() << "SLP: Scalar used twice in bundle.\n"); 2507 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2508 return; 2509 } 2510 VL = UniqueValues; 2511 } 2512 2513 auto &BSRef = BlocksSchedules[BB]; 2514 if (!BSRef) 2515 BSRef = std::make_unique<BlockScheduling>(BB); 2516 2517 BlockScheduling &BS = *BSRef.get(); 2518 2519 Optional<ScheduleData *> Bundle = BS.tryScheduleBundle(VL, this, S); 2520 if (!Bundle) { 2521 LLVM_DEBUG(dbgs() << "SLP: We are not able to schedule this bundle!\n"); 2522 assert((!BS.getScheduleData(VL0) || 2523 !BS.getScheduleData(VL0)->isPartOfBundle()) && 2524 "tryScheduleBundle should cancelScheduling on failure"); 2525 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2526 ReuseShuffleIndicies); 2527 return; 2528 } 2529 LLVM_DEBUG(dbgs() << "SLP: We are able to schedule this bundle.\n"); 2530 2531 unsigned ShuffleOrOp = S.isAltShuffle() ? 2532 (unsigned) Instruction::ShuffleVector : S.getOpcode(); 2533 switch (ShuffleOrOp) { 2534 case Instruction::PHI: { 2535 auto *PH = cast<PHINode>(VL0); 2536 2537 // Check for terminator values (e.g. invoke). 2538 for (unsigned j = 0; j < VL.size(); ++j) 2539 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 2540 Instruction *Term = dyn_cast<Instruction>( 2541 cast<PHINode>(VL[j])->getIncomingValueForBlock( 2542 PH->getIncomingBlock(i))); 2543 if (Term && Term->isTerminator()) { 2544 LLVM_DEBUG(dbgs() 2545 << "SLP: Need to swizzle PHINodes (terminator use).\n"); 2546 BS.cancelScheduling(VL, VL0); 2547 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2548 ReuseShuffleIndicies); 2549 return; 2550 } 2551 } 2552 2553 TreeEntry *TE = 2554 newTreeEntry(VL, Bundle, S, UserTreeIdx, ReuseShuffleIndicies); 2555 LLVM_DEBUG(dbgs() << "SLP: added a vector of PHINodes.\n"); 2556 2557 // Keeps the reordered operands to avoid code duplication. 2558 SmallVector<ValueList, 2> OperandsVec; 2559 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 2560 ValueList Operands; 2561 // Prepare the operand vector. 2562 for (Value *j : VL) 2563 Operands.push_back(cast<PHINode>(j)->getIncomingValueForBlock( 2564 PH->getIncomingBlock(i))); 2565 TE->setOperand(i, Operands); 2566 OperandsVec.push_back(Operands); 2567 } 2568 for (unsigned OpIdx = 0, OpE = OperandsVec.size(); OpIdx != OpE; ++OpIdx) 2569 buildTree_rec(OperandsVec[OpIdx], Depth + 1, {TE, OpIdx}); 2570 return; 2571 } 2572 case Instruction::ExtractValue: 2573 case Instruction::ExtractElement: { 2574 OrdersType CurrentOrder; 2575 bool Reuse = canReuseExtract(VL, VL0, CurrentOrder); 2576 if (Reuse) { 2577 LLVM_DEBUG(dbgs() << "SLP: Reusing or shuffling extract sequence.\n"); 2578 ++NumOpsWantToKeepOriginalOrder; 2579 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2580 ReuseShuffleIndicies); 2581 // This is a special case, as it does not gather, but at the same time 2582 // we are not extending buildTree_rec() towards the operands. 2583 ValueList Op0; 2584 Op0.assign(VL.size(), VL0->getOperand(0)); 2585 VectorizableTree.back()->setOperand(0, Op0); 2586 return; 2587 } 2588 if (!CurrentOrder.empty()) { 2589 LLVM_DEBUG({ 2590 dbgs() << "SLP: Reusing or shuffling of reordered extract sequence " 2591 "with order"; 2592 for (unsigned Idx : CurrentOrder) 2593 dbgs() << " " << Idx; 2594 dbgs() << "\n"; 2595 }); 2596 // Insert new order with initial value 0, if it does not exist, 2597 // otherwise return the iterator to the existing one. 2598 auto StoredCurrentOrderAndNum = 2599 NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first; 2600 ++StoredCurrentOrderAndNum->getSecond(); 2601 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2602 ReuseShuffleIndicies, 2603 StoredCurrentOrderAndNum->getFirst()); 2604 // This is a special case, as it does not gather, but at the same time 2605 // we are not extending buildTree_rec() towards the operands. 2606 ValueList Op0; 2607 Op0.assign(VL.size(), VL0->getOperand(0)); 2608 VectorizableTree.back()->setOperand(0, Op0); 2609 return; 2610 } 2611 LLVM_DEBUG(dbgs() << "SLP: Gather extract sequence.\n"); 2612 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2613 ReuseShuffleIndicies); 2614 BS.cancelScheduling(VL, VL0); 2615 return; 2616 } 2617 case Instruction::Load: { 2618 // Check that a vectorized load would load the same memory as a scalar 2619 // load. For example, we don't want to vectorize loads that are smaller 2620 // than 8-bit. Even though we have a packed struct {<i2, i2, i2, i2>} LLVM 2621 // treats loading/storing it as an i8 struct. If we vectorize loads/stores 2622 // from such a struct, we read/write packed bits disagreeing with the 2623 // unvectorized version. 2624 Type *ScalarTy = VL0->getType(); 2625 2626 if (DL->getTypeSizeInBits(ScalarTy) != 2627 DL->getTypeAllocSizeInBits(ScalarTy)) { 2628 BS.cancelScheduling(VL, VL0); 2629 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2630 ReuseShuffleIndicies); 2631 LLVM_DEBUG(dbgs() << "SLP: Gathering loads of non-packed type.\n"); 2632 return; 2633 } 2634 2635 // Make sure all loads in the bundle are simple - we can't vectorize 2636 // atomic or volatile loads. 2637 SmallVector<Value *, 4> PointerOps(VL.size()); 2638 auto POIter = PointerOps.begin(); 2639 for (Value *V : VL) { 2640 auto *L = cast<LoadInst>(V); 2641 if (!L->isSimple()) { 2642 BS.cancelScheduling(VL, VL0); 2643 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2644 ReuseShuffleIndicies); 2645 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple loads.\n"); 2646 return; 2647 } 2648 *POIter = L->getPointerOperand(); 2649 ++POIter; 2650 } 2651 2652 OrdersType CurrentOrder; 2653 // Check the order of pointer operands. 2654 if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) { 2655 Value *Ptr0; 2656 Value *PtrN; 2657 if (CurrentOrder.empty()) { 2658 Ptr0 = PointerOps.front(); 2659 PtrN = PointerOps.back(); 2660 } else { 2661 Ptr0 = PointerOps[CurrentOrder.front()]; 2662 PtrN = PointerOps[CurrentOrder.back()]; 2663 } 2664 const SCEV *Scev0 = SE->getSCEV(Ptr0); 2665 const SCEV *ScevN = SE->getSCEV(PtrN); 2666 const auto *Diff = 2667 dyn_cast<SCEVConstant>(SE->getMinusSCEV(ScevN, Scev0)); 2668 uint64_t Size = DL->getTypeAllocSize(ScalarTy); 2669 // Check that the sorted loads are consecutive. 2670 if (Diff && Diff->getAPInt() == (VL.size() - 1) * Size) { 2671 if (CurrentOrder.empty()) { 2672 // Original loads are consecutive and does not require reordering. 2673 ++NumOpsWantToKeepOriginalOrder; 2674 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, 2675 UserTreeIdx, ReuseShuffleIndicies); 2676 TE->setOperandsInOrder(); 2677 LLVM_DEBUG(dbgs() << "SLP: added a vector of loads.\n"); 2678 } else { 2679 // Need to reorder. 2680 auto I = NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first; 2681 ++I->getSecond(); 2682 TreeEntry *TE = 2683 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2684 ReuseShuffleIndicies, I->getFirst()); 2685 TE->setOperandsInOrder(); 2686 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled loads.\n"); 2687 } 2688 return; 2689 } 2690 } 2691 2692 LLVM_DEBUG(dbgs() << "SLP: Gathering non-consecutive loads.\n"); 2693 BS.cancelScheduling(VL, VL0); 2694 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2695 ReuseShuffleIndicies); 2696 return; 2697 } 2698 case Instruction::ZExt: 2699 case Instruction::SExt: 2700 case Instruction::FPToUI: 2701 case Instruction::FPToSI: 2702 case Instruction::FPExt: 2703 case Instruction::PtrToInt: 2704 case Instruction::IntToPtr: 2705 case Instruction::SIToFP: 2706 case Instruction::UIToFP: 2707 case Instruction::Trunc: 2708 case Instruction::FPTrunc: 2709 case Instruction::BitCast: { 2710 Type *SrcTy = VL0->getOperand(0)->getType(); 2711 for (Value *V : VL) { 2712 Type *Ty = cast<Instruction>(V)->getOperand(0)->getType(); 2713 if (Ty != SrcTy || !isValidElementType(Ty)) { 2714 BS.cancelScheduling(VL, VL0); 2715 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2716 ReuseShuffleIndicies); 2717 LLVM_DEBUG(dbgs() 2718 << "SLP: Gathering casts with different src types.\n"); 2719 return; 2720 } 2721 } 2722 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2723 ReuseShuffleIndicies); 2724 LLVM_DEBUG(dbgs() << "SLP: added a vector of casts.\n"); 2725 2726 TE->setOperandsInOrder(); 2727 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 2728 ValueList Operands; 2729 // Prepare the operand vector. 2730 for (Value *V : VL) 2731 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 2732 2733 buildTree_rec(Operands, Depth + 1, {TE, i}); 2734 } 2735 return; 2736 } 2737 case Instruction::ICmp: 2738 case Instruction::FCmp: { 2739 // Check that all of the compares have the same predicate. 2740 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 2741 CmpInst::Predicate SwapP0 = CmpInst::getSwappedPredicate(P0); 2742 Type *ComparedTy = VL0->getOperand(0)->getType(); 2743 for (Value *V : VL) { 2744 CmpInst *Cmp = cast<CmpInst>(V); 2745 if ((Cmp->getPredicate() != P0 && Cmp->getPredicate() != SwapP0) || 2746 Cmp->getOperand(0)->getType() != ComparedTy) { 2747 BS.cancelScheduling(VL, VL0); 2748 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2749 ReuseShuffleIndicies); 2750 LLVM_DEBUG(dbgs() 2751 << "SLP: Gathering cmp with different predicate.\n"); 2752 return; 2753 } 2754 } 2755 2756 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2757 ReuseShuffleIndicies); 2758 LLVM_DEBUG(dbgs() << "SLP: added a vector of compares.\n"); 2759 2760 ValueList Left, Right; 2761 if (cast<CmpInst>(VL0)->isCommutative()) { 2762 // Commutative predicate - collect + sort operands of the instructions 2763 // so that each side is more likely to have the same opcode. 2764 assert(P0 == SwapP0 && "Commutative Predicate mismatch"); 2765 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 2766 } else { 2767 // Collect operands - commute if it uses the swapped predicate. 2768 for (Value *V : VL) { 2769 auto *Cmp = cast<CmpInst>(V); 2770 Value *LHS = Cmp->getOperand(0); 2771 Value *RHS = Cmp->getOperand(1); 2772 if (Cmp->getPredicate() != P0) 2773 std::swap(LHS, RHS); 2774 Left.push_back(LHS); 2775 Right.push_back(RHS); 2776 } 2777 } 2778 TE->setOperand(0, Left); 2779 TE->setOperand(1, Right); 2780 buildTree_rec(Left, Depth + 1, {TE, 0}); 2781 buildTree_rec(Right, Depth + 1, {TE, 1}); 2782 return; 2783 } 2784 case Instruction::Select: 2785 case Instruction::FNeg: 2786 case Instruction::Add: 2787 case Instruction::FAdd: 2788 case Instruction::Sub: 2789 case Instruction::FSub: 2790 case Instruction::Mul: 2791 case Instruction::FMul: 2792 case Instruction::UDiv: 2793 case Instruction::SDiv: 2794 case Instruction::FDiv: 2795 case Instruction::URem: 2796 case Instruction::SRem: 2797 case Instruction::FRem: 2798 case Instruction::Shl: 2799 case Instruction::LShr: 2800 case Instruction::AShr: 2801 case Instruction::And: 2802 case Instruction::Or: 2803 case Instruction::Xor: { 2804 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2805 ReuseShuffleIndicies); 2806 LLVM_DEBUG(dbgs() << "SLP: added a vector of un/bin op.\n"); 2807 2808 // Sort operands of the instructions so that each side is more likely to 2809 // have the same opcode. 2810 if (isa<BinaryOperator>(VL0) && VL0->isCommutative()) { 2811 ValueList Left, Right; 2812 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 2813 TE->setOperand(0, Left); 2814 TE->setOperand(1, Right); 2815 buildTree_rec(Left, Depth + 1, {TE, 0}); 2816 buildTree_rec(Right, Depth + 1, {TE, 1}); 2817 return; 2818 } 2819 2820 TE->setOperandsInOrder(); 2821 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 2822 ValueList Operands; 2823 // Prepare the operand vector. 2824 for (Value *j : VL) 2825 Operands.push_back(cast<Instruction>(j)->getOperand(i)); 2826 2827 buildTree_rec(Operands, Depth + 1, {TE, i}); 2828 } 2829 return; 2830 } 2831 case Instruction::GetElementPtr: { 2832 // We don't combine GEPs with complicated (nested) indexing. 2833 for (Value *V : VL) { 2834 if (cast<Instruction>(V)->getNumOperands() != 2) { 2835 LLVM_DEBUG(dbgs() << "SLP: not-vectorizable GEP (nested indexes).\n"); 2836 BS.cancelScheduling(VL, VL0); 2837 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2838 ReuseShuffleIndicies); 2839 return; 2840 } 2841 } 2842 2843 // We can't combine several GEPs into one vector if they operate on 2844 // different types. 2845 Type *Ty0 = VL0->getOperand(0)->getType(); 2846 for (Value *V : VL) { 2847 Type *CurTy = cast<Instruction>(V)->getOperand(0)->getType(); 2848 if (Ty0 != CurTy) { 2849 LLVM_DEBUG(dbgs() 2850 << "SLP: not-vectorizable GEP (different types).\n"); 2851 BS.cancelScheduling(VL, VL0); 2852 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2853 ReuseShuffleIndicies); 2854 return; 2855 } 2856 } 2857 2858 // We don't combine GEPs with non-constant indexes. 2859 Type *Ty1 = VL0->getOperand(1)->getType(); 2860 for (Value *V : VL) { 2861 auto Op = cast<Instruction>(V)->getOperand(1); 2862 if (!isa<ConstantInt>(Op) || 2863 (Op->getType() != Ty1 && 2864 Op->getType()->getScalarSizeInBits() > 2865 DL->getIndexSizeInBits( 2866 V->getType()->getPointerAddressSpace()))) { 2867 LLVM_DEBUG(dbgs() 2868 << "SLP: not-vectorizable GEP (non-constant indexes).\n"); 2869 BS.cancelScheduling(VL, VL0); 2870 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2871 ReuseShuffleIndicies); 2872 return; 2873 } 2874 } 2875 2876 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2877 ReuseShuffleIndicies); 2878 LLVM_DEBUG(dbgs() << "SLP: added a vector of GEPs.\n"); 2879 TE->setOperandsInOrder(); 2880 for (unsigned i = 0, e = 2; i < e; ++i) { 2881 ValueList Operands; 2882 // Prepare the operand vector. 2883 for (Value *V : VL) 2884 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 2885 2886 buildTree_rec(Operands, Depth + 1, {TE, i}); 2887 } 2888 return; 2889 } 2890 case Instruction::Store: { 2891 // Check if the stores are consecutive or if we need to swizzle them. 2892 for (unsigned i = 0, e = VL.size() - 1; i < e; ++i) 2893 if (!isConsecutiveAccess(VL[i], VL[i + 1], *DL, *SE)) { 2894 BS.cancelScheduling(VL, VL0); 2895 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2896 ReuseShuffleIndicies); 2897 LLVM_DEBUG(dbgs() << "SLP: Non-consecutive store.\n"); 2898 return; 2899 } 2900 2901 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2902 ReuseShuffleIndicies); 2903 LLVM_DEBUG(dbgs() << "SLP: added a vector of stores.\n"); 2904 2905 ValueList Operands; 2906 for (Value *V : VL) 2907 Operands.push_back(cast<Instruction>(V)->getOperand(0)); 2908 TE->setOperandsInOrder(); 2909 buildTree_rec(Operands, Depth + 1, {TE, 0}); 2910 return; 2911 } 2912 case Instruction::Call: { 2913 // Check if the calls are all to the same vectorizable intrinsic. 2914 CallInst *CI = cast<CallInst>(VL0); 2915 // Check if this is an Intrinsic call or something that can be 2916 // represented by an intrinsic call 2917 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 2918 if (!isTriviallyVectorizable(ID)) { 2919 BS.cancelScheduling(VL, VL0); 2920 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2921 ReuseShuffleIndicies); 2922 LLVM_DEBUG(dbgs() << "SLP: Non-vectorizable call.\n"); 2923 return; 2924 } 2925 Function *Int = CI->getCalledFunction(); 2926 unsigned NumArgs = CI->getNumArgOperands(); 2927 SmallVector<Value*, 4> ScalarArgs(NumArgs, nullptr); 2928 for (unsigned j = 0; j != NumArgs; ++j) 2929 if (hasVectorInstrinsicScalarOpd(ID, j)) 2930 ScalarArgs[j] = CI->getArgOperand(j); 2931 for (Value *V : VL) { 2932 CallInst *CI2 = dyn_cast<CallInst>(V); 2933 if (!CI2 || CI2->getCalledFunction() != Int || 2934 getVectorIntrinsicIDForCall(CI2, TLI) != ID || 2935 !CI->hasIdenticalOperandBundleSchema(*CI2)) { 2936 BS.cancelScheduling(VL, VL0); 2937 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2938 ReuseShuffleIndicies); 2939 LLVM_DEBUG(dbgs() << "SLP: mismatched calls:" << *CI << "!=" << *V 2940 << "\n"); 2941 return; 2942 } 2943 // Some intrinsics have scalar arguments and should be same in order for 2944 // them to be vectorized. 2945 for (unsigned j = 0; j != NumArgs; ++j) { 2946 if (hasVectorInstrinsicScalarOpd(ID, j)) { 2947 Value *A1J = CI2->getArgOperand(j); 2948 if (ScalarArgs[j] != A1J) { 2949 BS.cancelScheduling(VL, VL0); 2950 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2951 ReuseShuffleIndicies); 2952 LLVM_DEBUG(dbgs() << "SLP: mismatched arguments in call:" << *CI 2953 << " argument " << ScalarArgs[j] << "!=" << A1J 2954 << "\n"); 2955 return; 2956 } 2957 } 2958 } 2959 // Verify that the bundle operands are identical between the two calls. 2960 if (CI->hasOperandBundles() && 2961 !std::equal(CI->op_begin() + CI->getBundleOperandsStartIndex(), 2962 CI->op_begin() + CI->getBundleOperandsEndIndex(), 2963 CI2->op_begin() + CI2->getBundleOperandsStartIndex())) { 2964 BS.cancelScheduling(VL, VL0); 2965 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2966 ReuseShuffleIndicies); 2967 LLVM_DEBUG(dbgs() << "SLP: mismatched bundle operands in calls:" 2968 << *CI << "!=" << *V << '\n'); 2969 return; 2970 } 2971 } 2972 2973 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2974 ReuseShuffleIndicies); 2975 TE->setOperandsInOrder(); 2976 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 2977 ValueList Operands; 2978 // Prepare the operand vector. 2979 for (Value *V : VL) { 2980 auto *CI2 = cast<CallInst>(V); 2981 Operands.push_back(CI2->getArgOperand(i)); 2982 } 2983 buildTree_rec(Operands, Depth + 1, {TE, i}); 2984 } 2985 return; 2986 } 2987 case Instruction::ShuffleVector: { 2988 // If this is not an alternate sequence of opcode like add-sub 2989 // then do not vectorize this instruction. 2990 if (!S.isAltShuffle()) { 2991 BS.cancelScheduling(VL, VL0); 2992 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2993 ReuseShuffleIndicies); 2994 LLVM_DEBUG(dbgs() << "SLP: ShuffleVector are not vectorized.\n"); 2995 return; 2996 } 2997 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2998 ReuseShuffleIndicies); 2999 LLVM_DEBUG(dbgs() << "SLP: added a ShuffleVector op.\n"); 3000 3001 // Reorder operands if reordering would enable vectorization. 3002 if (isa<BinaryOperator>(VL0)) { 3003 ValueList Left, Right; 3004 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 3005 TE->setOperand(0, Left); 3006 TE->setOperand(1, Right); 3007 buildTree_rec(Left, Depth + 1, {TE, 0}); 3008 buildTree_rec(Right, Depth + 1, {TE, 1}); 3009 return; 3010 } 3011 3012 TE->setOperandsInOrder(); 3013 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 3014 ValueList Operands; 3015 // Prepare the operand vector. 3016 for (Value *V : VL) 3017 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3018 3019 buildTree_rec(Operands, Depth + 1, {TE, i}); 3020 } 3021 return; 3022 } 3023 default: 3024 BS.cancelScheduling(VL, VL0); 3025 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3026 ReuseShuffleIndicies); 3027 LLVM_DEBUG(dbgs() << "SLP: Gathering unknown instruction.\n"); 3028 return; 3029 } 3030 } 3031 3032 unsigned BoUpSLP::canMapToVector(Type *T, const DataLayout &DL) const { 3033 unsigned N; 3034 Type *EltTy; 3035 auto *ST = dyn_cast<StructType>(T); 3036 if (ST) { 3037 N = ST->getNumElements(); 3038 EltTy = *ST->element_begin(); 3039 } else { 3040 N = cast<ArrayType>(T)->getNumElements(); 3041 EltTy = cast<ArrayType>(T)->getElementType(); 3042 } 3043 if (!isValidElementType(EltTy)) 3044 return 0; 3045 uint64_t VTSize = DL.getTypeStoreSizeInBits(VectorType::get(EltTy, N)); 3046 if (VTSize < MinVecRegSize || VTSize > MaxVecRegSize || VTSize != DL.getTypeStoreSizeInBits(T)) 3047 return 0; 3048 if (ST) { 3049 // Check that struct is homogeneous. 3050 for (const auto *Ty : ST->elements()) 3051 if (Ty != EltTy) 3052 return 0; 3053 } 3054 return N; 3055 } 3056 3057 bool BoUpSLP::canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 3058 SmallVectorImpl<unsigned> &CurrentOrder) const { 3059 Instruction *E0 = cast<Instruction>(OpValue); 3060 assert(E0->getOpcode() == Instruction::ExtractElement || 3061 E0->getOpcode() == Instruction::ExtractValue); 3062 assert(E0->getOpcode() == getSameOpcode(VL).getOpcode() && "Invalid opcode"); 3063 // Check if all of the extracts come from the same vector and from the 3064 // correct offset. 3065 Value *Vec = E0->getOperand(0); 3066 3067 CurrentOrder.clear(); 3068 3069 // We have to extract from a vector/aggregate with the same number of elements. 3070 unsigned NElts; 3071 if (E0->getOpcode() == Instruction::ExtractValue) { 3072 const DataLayout &DL = E0->getModule()->getDataLayout(); 3073 NElts = canMapToVector(Vec->getType(), DL); 3074 if (!NElts) 3075 return false; 3076 // Check if load can be rewritten as load of vector. 3077 LoadInst *LI = dyn_cast<LoadInst>(Vec); 3078 if (!LI || !LI->isSimple() || !LI->hasNUses(VL.size())) 3079 return false; 3080 } else { 3081 NElts = Vec->getType()->getVectorNumElements(); 3082 } 3083 3084 if (NElts != VL.size()) 3085 return false; 3086 3087 // Check that all of the indices extract from the correct offset. 3088 bool ShouldKeepOrder = true; 3089 unsigned E = VL.size(); 3090 // Assign to all items the initial value E + 1 so we can check if the extract 3091 // instruction index was used already. 3092 // Also, later we can check that all the indices are used and we have a 3093 // consecutive access in the extract instructions, by checking that no 3094 // element of CurrentOrder still has value E + 1. 3095 CurrentOrder.assign(E, E + 1); 3096 unsigned I = 0; 3097 for (; I < E; ++I) { 3098 auto *Inst = cast<Instruction>(VL[I]); 3099 if (Inst->getOperand(0) != Vec) 3100 break; 3101 Optional<unsigned> Idx = getExtractIndex(Inst); 3102 if (!Idx) 3103 break; 3104 const unsigned ExtIdx = *Idx; 3105 if (ExtIdx != I) { 3106 if (ExtIdx >= E || CurrentOrder[ExtIdx] != E + 1) 3107 break; 3108 ShouldKeepOrder = false; 3109 CurrentOrder[ExtIdx] = I; 3110 } else { 3111 if (CurrentOrder[I] != E + 1) 3112 break; 3113 CurrentOrder[I] = I; 3114 } 3115 } 3116 if (I < E) { 3117 CurrentOrder.clear(); 3118 return false; 3119 } 3120 3121 return ShouldKeepOrder; 3122 } 3123 3124 bool BoUpSLP::areAllUsersVectorized(Instruction *I) const { 3125 return I->hasOneUse() || 3126 std::all_of(I->user_begin(), I->user_end(), [this](User *U) { 3127 return ScalarToTreeEntry.count(U) > 0; 3128 }); 3129 } 3130 3131 int BoUpSLP::getEntryCost(TreeEntry *E) { 3132 ArrayRef<Value*> VL = E->Scalars; 3133 3134 Type *ScalarTy = VL[0]->getType(); 3135 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 3136 ScalarTy = SI->getValueOperand()->getType(); 3137 else if (CmpInst *CI = dyn_cast<CmpInst>(VL[0])) 3138 ScalarTy = CI->getOperand(0)->getType(); 3139 VectorType *VecTy = VectorType::get(ScalarTy, VL.size()); 3140 3141 // If we have computed a smaller type for the expression, update VecTy so 3142 // that the costs will be accurate. 3143 if (MinBWs.count(VL[0])) 3144 VecTy = VectorType::get( 3145 IntegerType::get(F->getContext(), MinBWs[VL[0]].first), VL.size()); 3146 3147 unsigned ReuseShuffleNumbers = E->ReuseShuffleIndices.size(); 3148 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 3149 int ReuseShuffleCost = 0; 3150 if (NeedToShuffleReuses) { 3151 ReuseShuffleCost = 3152 TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3153 } 3154 if (E->NeedToGather) { 3155 if (allConstant(VL)) 3156 return 0; 3157 if (isSplat(VL)) { 3158 return ReuseShuffleCost + 3159 TTI->getShuffleCost(TargetTransformInfo::SK_Broadcast, VecTy, 0); 3160 } 3161 if (E->getOpcode() == Instruction::ExtractElement && 3162 allSameType(VL) && allSameBlock(VL)) { 3163 Optional<TargetTransformInfo::ShuffleKind> ShuffleKind = isShuffle(VL); 3164 if (ShuffleKind.hasValue()) { 3165 int Cost = TTI->getShuffleCost(ShuffleKind.getValue(), VecTy); 3166 for (auto *V : VL) { 3167 // If all users of instruction are going to be vectorized and this 3168 // instruction itself is not going to be vectorized, consider this 3169 // instruction as dead and remove its cost from the final cost of the 3170 // vectorized tree. 3171 if (areAllUsersVectorized(cast<Instruction>(V)) && 3172 !ScalarToTreeEntry.count(V)) { 3173 auto *IO = cast<ConstantInt>( 3174 cast<ExtractElementInst>(V)->getIndexOperand()); 3175 Cost -= TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, 3176 IO->getZExtValue()); 3177 } 3178 } 3179 return ReuseShuffleCost + Cost; 3180 } 3181 } 3182 return ReuseShuffleCost + getGatherCost(VL); 3183 } 3184 assert(E->getOpcode() && allSameType(VL) && allSameBlock(VL) && "Invalid VL"); 3185 Instruction *VL0 = E->getMainOp(); 3186 unsigned ShuffleOrOp = 3187 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 3188 switch (ShuffleOrOp) { 3189 case Instruction::PHI: 3190 return 0; 3191 3192 case Instruction::ExtractValue: 3193 case Instruction::ExtractElement: 3194 if (NeedToShuffleReuses) { 3195 unsigned Idx = 0; 3196 for (unsigned I : E->ReuseShuffleIndices) { 3197 if (ShuffleOrOp == Instruction::ExtractElement) { 3198 auto *IO = cast<ConstantInt>( 3199 cast<ExtractElementInst>(VL[I])->getIndexOperand()); 3200 Idx = IO->getZExtValue(); 3201 ReuseShuffleCost -= TTI->getVectorInstrCost( 3202 Instruction::ExtractElement, VecTy, Idx); 3203 } else { 3204 ReuseShuffleCost -= TTI->getVectorInstrCost( 3205 Instruction::ExtractElement, VecTy, Idx); 3206 ++Idx; 3207 } 3208 } 3209 Idx = ReuseShuffleNumbers; 3210 for (Value *V : VL) { 3211 if (ShuffleOrOp == Instruction::ExtractElement) { 3212 auto *IO = cast<ConstantInt>( 3213 cast<ExtractElementInst>(V)->getIndexOperand()); 3214 Idx = IO->getZExtValue(); 3215 } else { 3216 --Idx; 3217 } 3218 ReuseShuffleCost += 3219 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, Idx); 3220 } 3221 } 3222 if (!E->NeedToGather) { 3223 int DeadCost = ReuseShuffleCost; 3224 if (!E->ReorderIndices.empty()) { 3225 // TODO: Merge this shuffle with the ReuseShuffleCost. 3226 DeadCost += TTI->getShuffleCost( 3227 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3228 } 3229 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 3230 Instruction *E = cast<Instruction>(VL[i]); 3231 // If all users are going to be vectorized, instruction can be 3232 // considered as dead. 3233 // The same, if have only one user, it will be vectorized for sure. 3234 if (areAllUsersVectorized(E)) { 3235 // Take credit for instruction that will become dead. 3236 if (E->hasOneUse()) { 3237 Instruction *Ext = E->user_back(); 3238 if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) && 3239 all_of(Ext->users(), 3240 [](User *U) { return isa<GetElementPtrInst>(U); })) { 3241 // Use getExtractWithExtendCost() to calculate the cost of 3242 // extractelement/ext pair. 3243 DeadCost -= TTI->getExtractWithExtendCost( 3244 Ext->getOpcode(), Ext->getType(), VecTy, i); 3245 // Add back the cost of s|zext which is subtracted separately. 3246 DeadCost += TTI->getCastInstrCost( 3247 Ext->getOpcode(), Ext->getType(), E->getType(), Ext); 3248 continue; 3249 } 3250 } 3251 DeadCost -= 3252 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, i); 3253 } 3254 } 3255 return DeadCost; 3256 } 3257 return ReuseShuffleCost + getGatherCost(VL); 3258 3259 case Instruction::ZExt: 3260 case Instruction::SExt: 3261 case Instruction::FPToUI: 3262 case Instruction::FPToSI: 3263 case Instruction::FPExt: 3264 case Instruction::PtrToInt: 3265 case Instruction::IntToPtr: 3266 case Instruction::SIToFP: 3267 case Instruction::UIToFP: 3268 case Instruction::Trunc: 3269 case Instruction::FPTrunc: 3270 case Instruction::BitCast: { 3271 Type *SrcTy = VL0->getOperand(0)->getType(); 3272 int ScalarEltCost = 3273 TTI->getCastInstrCost(E->getOpcode(), ScalarTy, SrcTy, VL0); 3274 if (NeedToShuffleReuses) { 3275 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3276 } 3277 3278 // Calculate the cost of this instruction. 3279 int ScalarCost = VL.size() * ScalarEltCost; 3280 3281 VectorType *SrcVecTy = VectorType::get(SrcTy, VL.size()); 3282 int VecCost = 0; 3283 // Check if the values are candidates to demote. 3284 if (!MinBWs.count(VL0) || VecTy != SrcVecTy) { 3285 VecCost = ReuseShuffleCost + 3286 TTI->getCastInstrCost(E->getOpcode(), VecTy, SrcVecTy, VL0); 3287 } 3288 return VecCost - ScalarCost; 3289 } 3290 case Instruction::FCmp: 3291 case Instruction::ICmp: 3292 case Instruction::Select: { 3293 // Calculate the cost of this instruction. 3294 int ScalarEltCost = TTI->getCmpSelInstrCost(E->getOpcode(), ScalarTy, 3295 Builder.getInt1Ty(), VL0); 3296 if (NeedToShuffleReuses) { 3297 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3298 } 3299 VectorType *MaskTy = VectorType::get(Builder.getInt1Ty(), VL.size()); 3300 int ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3301 int VecCost = TTI->getCmpSelInstrCost(E->getOpcode(), VecTy, MaskTy, VL0); 3302 return ReuseShuffleCost + VecCost - ScalarCost; 3303 } 3304 case Instruction::FNeg: 3305 case Instruction::Add: 3306 case Instruction::FAdd: 3307 case Instruction::Sub: 3308 case Instruction::FSub: 3309 case Instruction::Mul: 3310 case Instruction::FMul: 3311 case Instruction::UDiv: 3312 case Instruction::SDiv: 3313 case Instruction::FDiv: 3314 case Instruction::URem: 3315 case Instruction::SRem: 3316 case Instruction::FRem: 3317 case Instruction::Shl: 3318 case Instruction::LShr: 3319 case Instruction::AShr: 3320 case Instruction::And: 3321 case Instruction::Or: 3322 case Instruction::Xor: { 3323 // Certain instructions can be cheaper to vectorize if they have a 3324 // constant second vector operand. 3325 TargetTransformInfo::OperandValueKind Op1VK = 3326 TargetTransformInfo::OK_AnyValue; 3327 TargetTransformInfo::OperandValueKind Op2VK = 3328 TargetTransformInfo::OK_UniformConstantValue; 3329 TargetTransformInfo::OperandValueProperties Op1VP = 3330 TargetTransformInfo::OP_None; 3331 TargetTransformInfo::OperandValueProperties Op2VP = 3332 TargetTransformInfo::OP_PowerOf2; 3333 3334 // If all operands are exactly the same ConstantInt then set the 3335 // operand kind to OK_UniformConstantValue. 3336 // If instead not all operands are constants, then set the operand kind 3337 // to OK_AnyValue. If all operands are constants but not the same, 3338 // then set the operand kind to OK_NonUniformConstantValue. 3339 ConstantInt *CInt0 = nullptr; 3340 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 3341 const Instruction *I = cast<Instruction>(VL[i]); 3342 unsigned OpIdx = isa<BinaryOperator>(I) ? 1 : 0; 3343 ConstantInt *CInt = dyn_cast<ConstantInt>(I->getOperand(OpIdx)); 3344 if (!CInt) { 3345 Op2VK = TargetTransformInfo::OK_AnyValue; 3346 Op2VP = TargetTransformInfo::OP_None; 3347 break; 3348 } 3349 if (Op2VP == TargetTransformInfo::OP_PowerOf2 && 3350 !CInt->getValue().isPowerOf2()) 3351 Op2VP = TargetTransformInfo::OP_None; 3352 if (i == 0) { 3353 CInt0 = CInt; 3354 continue; 3355 } 3356 if (CInt0 != CInt) 3357 Op2VK = TargetTransformInfo::OK_NonUniformConstantValue; 3358 } 3359 3360 SmallVector<const Value *, 4> Operands(VL0->operand_values()); 3361 int ScalarEltCost = TTI->getArithmeticInstrCost( 3362 E->getOpcode(), ScalarTy, Op1VK, Op2VK, Op1VP, Op2VP, Operands); 3363 if (NeedToShuffleReuses) { 3364 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3365 } 3366 int ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3367 int VecCost = TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, Op1VK, 3368 Op2VK, Op1VP, Op2VP, Operands); 3369 return ReuseShuffleCost + VecCost - ScalarCost; 3370 } 3371 case Instruction::GetElementPtr: { 3372 TargetTransformInfo::OperandValueKind Op1VK = 3373 TargetTransformInfo::OK_AnyValue; 3374 TargetTransformInfo::OperandValueKind Op2VK = 3375 TargetTransformInfo::OK_UniformConstantValue; 3376 3377 int ScalarEltCost = 3378 TTI->getArithmeticInstrCost(Instruction::Add, ScalarTy, Op1VK, Op2VK); 3379 if (NeedToShuffleReuses) { 3380 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3381 } 3382 int ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3383 int VecCost = 3384 TTI->getArithmeticInstrCost(Instruction::Add, VecTy, Op1VK, Op2VK); 3385 return ReuseShuffleCost + VecCost - ScalarCost; 3386 } 3387 case Instruction::Load: { 3388 // Cost of wide load - cost of scalar loads. 3389 MaybeAlign alignment(cast<LoadInst>(VL0)->getAlignment()); 3390 int ScalarEltCost = 3391 TTI->getMemoryOpCost(Instruction::Load, ScalarTy, alignment, 0, VL0); 3392 if (NeedToShuffleReuses) { 3393 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3394 } 3395 int ScalarLdCost = VecTy->getNumElements() * ScalarEltCost; 3396 int VecLdCost = 3397 TTI->getMemoryOpCost(Instruction::Load, VecTy, alignment, 0, VL0); 3398 if (!E->ReorderIndices.empty()) { 3399 // TODO: Merge this shuffle with the ReuseShuffleCost. 3400 VecLdCost += TTI->getShuffleCost( 3401 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3402 } 3403 return ReuseShuffleCost + VecLdCost - ScalarLdCost; 3404 } 3405 case Instruction::Store: { 3406 // We know that we can merge the stores. Calculate the cost. 3407 MaybeAlign alignment(cast<StoreInst>(VL0)->getAlignment()); 3408 int ScalarEltCost = 3409 TTI->getMemoryOpCost(Instruction::Store, ScalarTy, alignment, 0, VL0); 3410 if (NeedToShuffleReuses) { 3411 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3412 } 3413 int ScalarStCost = VecTy->getNumElements() * ScalarEltCost; 3414 int VecStCost = 3415 TTI->getMemoryOpCost(Instruction::Store, VecTy, alignment, 0, VL0); 3416 return ReuseShuffleCost + VecStCost - ScalarStCost; 3417 } 3418 case Instruction::Call: { 3419 CallInst *CI = cast<CallInst>(VL0); 3420 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3421 3422 // Calculate the cost of the scalar and vector calls. 3423 SmallVector<Type *, 4> ScalarTys; 3424 for (unsigned op = 0, opc = CI->getNumArgOperands(); op != opc; ++op) 3425 ScalarTys.push_back(CI->getArgOperand(op)->getType()); 3426 3427 FastMathFlags FMF; 3428 if (auto *FPMO = dyn_cast<FPMathOperator>(CI)) 3429 FMF = FPMO->getFastMathFlags(); 3430 3431 int ScalarEltCost = 3432 TTI->getIntrinsicInstrCost(ID, ScalarTy, ScalarTys, FMF); 3433 if (NeedToShuffleReuses) { 3434 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3435 } 3436 int ScalarCallCost = VecTy->getNumElements() * ScalarEltCost; 3437 3438 SmallVector<Value *, 4> Args(CI->arg_operands()); 3439 int VecCallCost = TTI->getIntrinsicInstrCost(ID, CI->getType(), Args, FMF, 3440 VecTy->getNumElements()); 3441 3442 LLVM_DEBUG(dbgs() << "SLP: Call cost " << VecCallCost - ScalarCallCost 3443 << " (" << VecCallCost << "-" << ScalarCallCost << ")" 3444 << " for " << *CI << "\n"); 3445 3446 return ReuseShuffleCost + VecCallCost - ScalarCallCost; 3447 } 3448 case Instruction::ShuffleVector: { 3449 assert(E->isAltShuffle() && 3450 ((Instruction::isBinaryOp(E->getOpcode()) && 3451 Instruction::isBinaryOp(E->getAltOpcode())) || 3452 (Instruction::isCast(E->getOpcode()) && 3453 Instruction::isCast(E->getAltOpcode()))) && 3454 "Invalid Shuffle Vector Operand"); 3455 int ScalarCost = 0; 3456 if (NeedToShuffleReuses) { 3457 for (unsigned Idx : E->ReuseShuffleIndices) { 3458 Instruction *I = cast<Instruction>(VL[Idx]); 3459 ReuseShuffleCost -= TTI->getInstructionCost( 3460 I, TargetTransformInfo::TCK_RecipThroughput); 3461 } 3462 for (Value *V : VL) { 3463 Instruction *I = cast<Instruction>(V); 3464 ReuseShuffleCost += TTI->getInstructionCost( 3465 I, TargetTransformInfo::TCK_RecipThroughput); 3466 } 3467 } 3468 for (Value *V : VL) { 3469 Instruction *I = cast<Instruction>(V); 3470 assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode"); 3471 ScalarCost += TTI->getInstructionCost( 3472 I, TargetTransformInfo::TCK_RecipThroughput); 3473 } 3474 // VecCost is equal to sum of the cost of creating 2 vectors 3475 // and the cost of creating shuffle. 3476 int VecCost = 0; 3477 if (Instruction::isBinaryOp(E->getOpcode())) { 3478 VecCost = TTI->getArithmeticInstrCost(E->getOpcode(), VecTy); 3479 VecCost += TTI->getArithmeticInstrCost(E->getAltOpcode(), VecTy); 3480 } else { 3481 Type *Src0SclTy = E->getMainOp()->getOperand(0)->getType(); 3482 Type *Src1SclTy = E->getAltOp()->getOperand(0)->getType(); 3483 VectorType *Src0Ty = VectorType::get(Src0SclTy, VL.size()); 3484 VectorType *Src1Ty = VectorType::get(Src1SclTy, VL.size()); 3485 VecCost = TTI->getCastInstrCost(E->getOpcode(), VecTy, Src0Ty); 3486 VecCost += TTI->getCastInstrCost(E->getAltOpcode(), VecTy, Src1Ty); 3487 } 3488 VecCost += TTI->getShuffleCost(TargetTransformInfo::SK_Select, VecTy, 0); 3489 return ReuseShuffleCost + VecCost - ScalarCost; 3490 } 3491 default: 3492 llvm_unreachable("Unknown instruction"); 3493 } 3494 } 3495 3496 bool BoUpSLP::isFullyVectorizableTinyTree() const { 3497 LLVM_DEBUG(dbgs() << "SLP: Check whether the tree with height " 3498 << VectorizableTree.size() << " is fully vectorizable .\n"); 3499 3500 // We only handle trees of heights 1 and 2. 3501 if (VectorizableTree.size() == 1 && !VectorizableTree[0]->NeedToGather) 3502 return true; 3503 3504 if (VectorizableTree.size() != 2) 3505 return false; 3506 3507 // Handle splat and all-constants stores. 3508 if (!VectorizableTree[0]->NeedToGather && 3509 (allConstant(VectorizableTree[1]->Scalars) || 3510 isSplat(VectorizableTree[1]->Scalars))) 3511 return true; 3512 3513 // Gathering cost would be too much for tiny trees. 3514 if (VectorizableTree[0]->NeedToGather || VectorizableTree[1]->NeedToGather) 3515 return false; 3516 3517 return true; 3518 } 3519 3520 bool BoUpSLP::isLoadCombineReductionCandidate(unsigned RdxOpcode) const { 3521 if (RdxOpcode != Instruction::Or) 3522 return false; 3523 3524 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 3525 Value *FirstReduced = VectorizableTree[0]->Scalars[0]; 3526 3527 // Look past the reduction to find a source value. Arbitrarily follow the 3528 // path through operand 0 of any 'or'. Also, peek through optional 3529 // shift-left-by-constant. 3530 Value *ZextLoad = FirstReduced; 3531 while (match(ZextLoad, m_Or(m_Value(), m_Value())) || 3532 match(ZextLoad, m_Shl(m_Value(), m_Constant()))) 3533 ZextLoad = cast<BinaryOperator>(ZextLoad)->getOperand(0); 3534 3535 // Check if the input to the reduction is an extended load. 3536 Value *LoadPtr; 3537 if (!match(ZextLoad, m_ZExt(m_Load(m_Value(LoadPtr))))) 3538 return false; 3539 3540 // Require that the total load bit width is a legal integer type. 3541 // For example, <8 x i8> --> i64 is a legal integer on a 64-bit target. 3542 // But <16 x i8> --> i128 is not, so the backend probably can't reduce it. 3543 Type *SrcTy = LoadPtr->getType()->getPointerElementType(); 3544 unsigned LoadBitWidth = SrcTy->getIntegerBitWidth() * NumElts; 3545 LLVMContext &Context = FirstReduced->getContext(); 3546 if (!TTI->isTypeLegal(IntegerType::get(Context, LoadBitWidth))) 3547 return false; 3548 3549 // Everything matched - assume that we can fold the whole sequence using 3550 // load combining. 3551 LLVM_DEBUG(dbgs() << "SLP: Assume load combining for scalar reduction of " 3552 << *(cast<Instruction>(FirstReduced)) << "\n"); 3553 3554 return true; 3555 } 3556 3557 bool BoUpSLP::isTreeTinyAndNotFullyVectorizable() const { 3558 // We can vectorize the tree if its size is greater than or equal to the 3559 // minimum size specified by the MinTreeSize command line option. 3560 if (VectorizableTree.size() >= MinTreeSize) 3561 return false; 3562 3563 // If we have a tiny tree (a tree whose size is less than MinTreeSize), we 3564 // can vectorize it if we can prove it fully vectorizable. 3565 if (isFullyVectorizableTinyTree()) 3566 return false; 3567 3568 assert(VectorizableTree.empty() 3569 ? ExternalUses.empty() 3570 : true && "We shouldn't have any external users"); 3571 3572 // Otherwise, we can't vectorize the tree. It is both tiny and not fully 3573 // vectorizable. 3574 return true; 3575 } 3576 3577 int BoUpSLP::getSpillCost() const { 3578 // Walk from the bottom of the tree to the top, tracking which values are 3579 // live. When we see a call instruction that is not part of our tree, 3580 // query TTI to see if there is a cost to keeping values live over it 3581 // (for example, if spills and fills are required). 3582 unsigned BundleWidth = VectorizableTree.front()->Scalars.size(); 3583 int Cost = 0; 3584 3585 SmallPtrSet<Instruction*, 4> LiveValues; 3586 Instruction *PrevInst = nullptr; 3587 3588 for (const auto &TEPtr : VectorizableTree) { 3589 Instruction *Inst = dyn_cast<Instruction>(TEPtr->Scalars[0]); 3590 if (!Inst) 3591 continue; 3592 3593 if (!PrevInst) { 3594 PrevInst = Inst; 3595 continue; 3596 } 3597 3598 // Update LiveValues. 3599 LiveValues.erase(PrevInst); 3600 for (auto &J : PrevInst->operands()) { 3601 if (isa<Instruction>(&*J) && getTreeEntry(&*J)) 3602 LiveValues.insert(cast<Instruction>(&*J)); 3603 } 3604 3605 LLVM_DEBUG({ 3606 dbgs() << "SLP: #LV: " << LiveValues.size(); 3607 for (auto *X : LiveValues) 3608 dbgs() << " " << X->getName(); 3609 dbgs() << ", Looking at "; 3610 Inst->dump(); 3611 }); 3612 3613 // Now find the sequence of instructions between PrevInst and Inst. 3614 unsigned NumCalls = 0; 3615 BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(), 3616 PrevInstIt = 3617 PrevInst->getIterator().getReverse(); 3618 while (InstIt != PrevInstIt) { 3619 if (PrevInstIt == PrevInst->getParent()->rend()) { 3620 PrevInstIt = Inst->getParent()->rbegin(); 3621 continue; 3622 } 3623 3624 // Debug information does not impact spill cost. 3625 if ((isa<CallInst>(&*PrevInstIt) && 3626 !isa<DbgInfoIntrinsic>(&*PrevInstIt)) && 3627 &*PrevInstIt != PrevInst) 3628 NumCalls++; 3629 3630 ++PrevInstIt; 3631 } 3632 3633 if (NumCalls) { 3634 SmallVector<Type*, 4> V; 3635 for (auto *II : LiveValues) 3636 V.push_back(VectorType::get(II->getType(), BundleWidth)); 3637 Cost += NumCalls * TTI->getCostOfKeepingLiveOverCall(V); 3638 } 3639 3640 PrevInst = Inst; 3641 } 3642 3643 return Cost; 3644 } 3645 3646 int BoUpSLP::getTreeCost() { 3647 int Cost = 0; 3648 LLVM_DEBUG(dbgs() << "SLP: Calculating cost for tree of size " 3649 << VectorizableTree.size() << ".\n"); 3650 3651 unsigned BundleWidth = VectorizableTree[0]->Scalars.size(); 3652 3653 for (unsigned I = 0, E = VectorizableTree.size(); I < E; ++I) { 3654 TreeEntry &TE = *VectorizableTree[I].get(); 3655 3656 // We create duplicate tree entries for gather sequences that have multiple 3657 // uses. However, we should not compute the cost of duplicate sequences. 3658 // For example, if we have a build vector (i.e., insertelement sequence) 3659 // that is used by more than one vector instruction, we only need to 3660 // compute the cost of the insertelement instructions once. The redundant 3661 // instructions will be eliminated by CSE. 3662 // 3663 // We should consider not creating duplicate tree entries for gather 3664 // sequences, and instead add additional edges to the tree representing 3665 // their uses. Since such an approach results in fewer total entries, 3666 // existing heuristics based on tree size may yield different results. 3667 // 3668 if (TE.NeedToGather && 3669 std::any_of( 3670 std::next(VectorizableTree.begin(), I + 1), VectorizableTree.end(), 3671 [TE](const std::unique_ptr<TreeEntry> &EntryPtr) { 3672 return EntryPtr->NeedToGather && EntryPtr->isSame(TE.Scalars); 3673 })) 3674 continue; 3675 3676 int C = getEntryCost(&TE); 3677 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C 3678 << " for bundle that starts with " << *TE.Scalars[0] 3679 << ".\n"); 3680 Cost += C; 3681 } 3682 3683 SmallPtrSet<Value *, 16> ExtractCostCalculated; 3684 int ExtractCost = 0; 3685 for (ExternalUser &EU : ExternalUses) { 3686 // We only add extract cost once for the same scalar. 3687 if (!ExtractCostCalculated.insert(EU.Scalar).second) 3688 continue; 3689 3690 // Uses by ephemeral values are free (because the ephemeral value will be 3691 // removed prior to code generation, and so the extraction will be 3692 // removed as well). 3693 if (EphValues.count(EU.User)) 3694 continue; 3695 3696 // If we plan to rewrite the tree in a smaller type, we will need to sign 3697 // extend the extracted value back to the original type. Here, we account 3698 // for the extract and the added cost of the sign extend if needed. 3699 auto *VecTy = VectorType::get(EU.Scalar->getType(), BundleWidth); 3700 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 3701 if (MinBWs.count(ScalarRoot)) { 3702 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 3703 auto Extend = 3704 MinBWs[ScalarRoot].second ? Instruction::SExt : Instruction::ZExt; 3705 VecTy = VectorType::get(MinTy, BundleWidth); 3706 ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(), 3707 VecTy, EU.Lane); 3708 } else { 3709 ExtractCost += 3710 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, EU.Lane); 3711 } 3712 } 3713 3714 int SpillCost = getSpillCost(); 3715 Cost += SpillCost + ExtractCost; 3716 3717 std::string Str; 3718 { 3719 raw_string_ostream OS(Str); 3720 OS << "SLP: Spill Cost = " << SpillCost << ".\n" 3721 << "SLP: Extract Cost = " << ExtractCost << ".\n" 3722 << "SLP: Total Cost = " << Cost << ".\n"; 3723 } 3724 LLVM_DEBUG(dbgs() << Str); 3725 3726 if (ViewSLPTree) 3727 ViewGraph(this, "SLP" + F->getName(), false, Str); 3728 3729 return Cost; 3730 } 3731 3732 int BoUpSLP::getGatherCost(Type *Ty, 3733 const DenseSet<unsigned> &ShuffledIndices) const { 3734 int Cost = 0; 3735 for (unsigned i = 0, e = cast<VectorType>(Ty)->getNumElements(); i < e; ++i) 3736 if (!ShuffledIndices.count(i)) 3737 Cost += TTI->getVectorInstrCost(Instruction::InsertElement, Ty, i); 3738 if (!ShuffledIndices.empty()) 3739 Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, Ty); 3740 return Cost; 3741 } 3742 3743 int BoUpSLP::getGatherCost(ArrayRef<Value *> VL) const { 3744 // Find the type of the operands in VL. 3745 Type *ScalarTy = VL[0]->getType(); 3746 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 3747 ScalarTy = SI->getValueOperand()->getType(); 3748 VectorType *VecTy = VectorType::get(ScalarTy, VL.size()); 3749 // Find the cost of inserting/extracting values from the vector. 3750 // Check if the same elements are inserted several times and count them as 3751 // shuffle candidates. 3752 DenseSet<unsigned> ShuffledElements; 3753 DenseSet<Value *> UniqueElements; 3754 // Iterate in reverse order to consider insert elements with the high cost. 3755 for (unsigned I = VL.size(); I > 0; --I) { 3756 unsigned Idx = I - 1; 3757 if (!UniqueElements.insert(VL[Idx]).second) 3758 ShuffledElements.insert(Idx); 3759 } 3760 return getGatherCost(VecTy, ShuffledElements); 3761 } 3762 3763 // Perform operand reordering on the instructions in VL and return the reordered 3764 // operands in Left and Right. 3765 void BoUpSLP::reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 3766 SmallVectorImpl<Value *> &Left, 3767 SmallVectorImpl<Value *> &Right, 3768 const DataLayout &DL, 3769 ScalarEvolution &SE, 3770 const BoUpSLP &R) { 3771 if (VL.empty()) 3772 return; 3773 VLOperands Ops(VL, DL, SE, R); 3774 // Reorder the operands in place. 3775 Ops.reorder(); 3776 Left = Ops.getVL(0); 3777 Right = Ops.getVL(1); 3778 } 3779 3780 void BoUpSLP::setInsertPointAfterBundle(TreeEntry *E) { 3781 // Get the basic block this bundle is in. All instructions in the bundle 3782 // should be in this block. 3783 auto *Front = E->getMainOp(); 3784 auto *BB = Front->getParent(); 3785 assert(llvm::all_of(make_range(E->Scalars.begin(), E->Scalars.end()), 3786 [=](Value *V) -> bool { 3787 auto *I = cast<Instruction>(V); 3788 return !E->isOpcodeOrAlt(I) || I->getParent() == BB; 3789 })); 3790 3791 // The last instruction in the bundle in program order. 3792 Instruction *LastInst = nullptr; 3793 3794 // Find the last instruction. The common case should be that BB has been 3795 // scheduled, and the last instruction is VL.back(). So we start with 3796 // VL.back() and iterate over schedule data until we reach the end of the 3797 // bundle. The end of the bundle is marked by null ScheduleData. 3798 if (BlocksSchedules.count(BB)) { 3799 auto *Bundle = 3800 BlocksSchedules[BB]->getScheduleData(E->isOneOf(E->Scalars.back())); 3801 if (Bundle && Bundle->isPartOfBundle()) 3802 for (; Bundle; Bundle = Bundle->NextInBundle) 3803 if (Bundle->OpValue == Bundle->Inst) 3804 LastInst = Bundle->Inst; 3805 } 3806 3807 // LastInst can still be null at this point if there's either not an entry 3808 // for BB in BlocksSchedules or there's no ScheduleData available for 3809 // VL.back(). This can be the case if buildTree_rec aborts for various 3810 // reasons (e.g., the maximum recursion depth is reached, the maximum region 3811 // size is reached, etc.). ScheduleData is initialized in the scheduling 3812 // "dry-run". 3813 // 3814 // If this happens, we can still find the last instruction by brute force. We 3815 // iterate forwards from Front (inclusive) until we either see all 3816 // instructions in the bundle or reach the end of the block. If Front is the 3817 // last instruction in program order, LastInst will be set to Front, and we 3818 // will visit all the remaining instructions in the block. 3819 // 3820 // One of the reasons we exit early from buildTree_rec is to place an upper 3821 // bound on compile-time. Thus, taking an additional compile-time hit here is 3822 // not ideal. However, this should be exceedingly rare since it requires that 3823 // we both exit early from buildTree_rec and that the bundle be out-of-order 3824 // (causing us to iterate all the way to the end of the block). 3825 if (!LastInst) { 3826 SmallPtrSet<Value *, 16> Bundle(E->Scalars.begin(), E->Scalars.end()); 3827 for (auto &I : make_range(BasicBlock::iterator(Front), BB->end())) { 3828 if (Bundle.erase(&I) && E->isOpcodeOrAlt(&I)) 3829 LastInst = &I; 3830 if (Bundle.empty()) 3831 break; 3832 } 3833 } 3834 assert(LastInst && "Failed to find last instruction in bundle"); 3835 3836 // Set the insertion point after the last instruction in the bundle. Set the 3837 // debug location to Front. 3838 Builder.SetInsertPoint(BB, ++LastInst->getIterator()); 3839 Builder.SetCurrentDebugLocation(Front->getDebugLoc()); 3840 } 3841 3842 Value *BoUpSLP::Gather(ArrayRef<Value *> VL, VectorType *Ty) { 3843 Value *Vec = UndefValue::get(Ty); 3844 // Generate the 'InsertElement' instruction. 3845 for (unsigned i = 0; i < Ty->getNumElements(); ++i) { 3846 Vec = Builder.CreateInsertElement(Vec, VL[i], Builder.getInt32(i)); 3847 if (auto *Insrt = dyn_cast<InsertElementInst>(Vec)) { 3848 GatherSeq.insert(Insrt); 3849 CSEBlocks.insert(Insrt->getParent()); 3850 3851 // Add to our 'need-to-extract' list. 3852 if (TreeEntry *E = getTreeEntry(VL[i])) { 3853 // Find which lane we need to extract. 3854 int FoundLane = -1; 3855 for (unsigned Lane = 0, LE = E->Scalars.size(); Lane != LE; ++Lane) { 3856 // Is this the lane of the scalar that we are looking for ? 3857 if (E->Scalars[Lane] == VL[i]) { 3858 FoundLane = Lane; 3859 break; 3860 } 3861 } 3862 assert(FoundLane >= 0 && "Could not find the correct lane"); 3863 if (!E->ReuseShuffleIndices.empty()) { 3864 FoundLane = 3865 std::distance(E->ReuseShuffleIndices.begin(), 3866 llvm::find(E->ReuseShuffleIndices, FoundLane)); 3867 } 3868 ExternalUses.push_back(ExternalUser(VL[i], Insrt, FoundLane)); 3869 } 3870 } 3871 } 3872 3873 return Vec; 3874 } 3875 3876 Value *BoUpSLP::vectorizeTree(ArrayRef<Value *> VL) { 3877 InstructionsState S = getSameOpcode(VL); 3878 if (S.getOpcode()) { 3879 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 3880 if (E->isSame(VL)) { 3881 Value *V = vectorizeTree(E); 3882 if (VL.size() == E->Scalars.size() && !E->ReuseShuffleIndices.empty()) { 3883 // We need to get the vectorized value but without shuffle. 3884 if (auto *SV = dyn_cast<ShuffleVectorInst>(V)) { 3885 V = SV->getOperand(0); 3886 } else { 3887 // Reshuffle to get only unique values. 3888 SmallVector<unsigned, 4> UniqueIdxs; 3889 SmallSet<unsigned, 4> UsedIdxs; 3890 for(unsigned Idx : E->ReuseShuffleIndices) 3891 if (UsedIdxs.insert(Idx).second) 3892 UniqueIdxs.emplace_back(Idx); 3893 V = Builder.CreateShuffleVector(V, UndefValue::get(V->getType()), 3894 UniqueIdxs); 3895 } 3896 } 3897 return V; 3898 } 3899 } 3900 } 3901 3902 Type *ScalarTy = S.OpValue->getType(); 3903 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) 3904 ScalarTy = SI->getValueOperand()->getType(); 3905 3906 // Check that every instruction appears once in this bundle. 3907 SmallVector<unsigned, 4> ReuseShuffleIndicies; 3908 SmallVector<Value *, 4> UniqueValues; 3909 if (VL.size() > 2) { 3910 DenseMap<Value *, unsigned> UniquePositions; 3911 for (Value *V : VL) { 3912 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 3913 ReuseShuffleIndicies.emplace_back(Res.first->second); 3914 if (Res.second || isa<Constant>(V)) 3915 UniqueValues.emplace_back(V); 3916 } 3917 // Do not shuffle single element or if number of unique values is not power 3918 // of 2. 3919 if (UniqueValues.size() == VL.size() || UniqueValues.size() <= 1 || 3920 !llvm::isPowerOf2_32(UniqueValues.size())) 3921 ReuseShuffleIndicies.clear(); 3922 else 3923 VL = UniqueValues; 3924 } 3925 VectorType *VecTy = VectorType::get(ScalarTy, VL.size()); 3926 3927 Value *V = Gather(VL, VecTy); 3928 if (!ReuseShuffleIndicies.empty()) { 3929 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3930 ReuseShuffleIndicies, "shuffle"); 3931 if (auto *I = dyn_cast<Instruction>(V)) { 3932 GatherSeq.insert(I); 3933 CSEBlocks.insert(I->getParent()); 3934 } 3935 } 3936 return V; 3937 } 3938 3939 static void inversePermutation(ArrayRef<unsigned> Indices, 3940 SmallVectorImpl<unsigned> &Mask) { 3941 Mask.clear(); 3942 const unsigned E = Indices.size(); 3943 Mask.resize(E); 3944 for (unsigned I = 0; I < E; ++I) 3945 Mask[Indices[I]] = I; 3946 } 3947 3948 Value *BoUpSLP::vectorizeTree(TreeEntry *E) { 3949 IRBuilder<>::InsertPointGuard Guard(Builder); 3950 3951 if (E->VectorizedValue) { 3952 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *E->Scalars[0] << ".\n"); 3953 return E->VectorizedValue; 3954 } 3955 3956 Instruction *VL0 = E->getMainOp(); 3957 Type *ScalarTy = VL0->getType(); 3958 if (StoreInst *SI = dyn_cast<StoreInst>(VL0)) 3959 ScalarTy = SI->getValueOperand()->getType(); 3960 VectorType *VecTy = VectorType::get(ScalarTy, E->Scalars.size()); 3961 3962 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 3963 3964 if (E->NeedToGather) { 3965 setInsertPointAfterBundle(E); 3966 auto *V = Gather(E->Scalars, VecTy); 3967 if (NeedToShuffleReuses) { 3968 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3969 E->ReuseShuffleIndices, "shuffle"); 3970 if (auto *I = dyn_cast<Instruction>(V)) { 3971 GatherSeq.insert(I); 3972 CSEBlocks.insert(I->getParent()); 3973 } 3974 } 3975 E->VectorizedValue = V; 3976 return V; 3977 } 3978 3979 unsigned ShuffleOrOp = 3980 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 3981 switch (ShuffleOrOp) { 3982 case Instruction::PHI: { 3983 auto *PH = cast<PHINode>(VL0); 3984 Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI()); 3985 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 3986 PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues()); 3987 Value *V = NewPhi; 3988 if (NeedToShuffleReuses) { 3989 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3990 E->ReuseShuffleIndices, "shuffle"); 3991 } 3992 E->VectorizedValue = V; 3993 3994 // PHINodes may have multiple entries from the same block. We want to 3995 // visit every block once. 3996 SmallPtrSet<BasicBlock*, 4> VisitedBBs; 3997 3998 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 3999 ValueList Operands; 4000 BasicBlock *IBB = PH->getIncomingBlock(i); 4001 4002 if (!VisitedBBs.insert(IBB).second) { 4003 NewPhi->addIncoming(NewPhi->getIncomingValueForBlock(IBB), IBB); 4004 continue; 4005 } 4006 4007 Builder.SetInsertPoint(IBB->getTerminator()); 4008 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 4009 Value *Vec = vectorizeTree(E->getOperand(i)); 4010 NewPhi->addIncoming(Vec, IBB); 4011 } 4012 4013 assert(NewPhi->getNumIncomingValues() == PH->getNumIncomingValues() && 4014 "Invalid number of incoming values"); 4015 return V; 4016 } 4017 4018 case Instruction::ExtractElement: { 4019 if (!E->NeedToGather) { 4020 Value *V = E->getSingleOperand(0); 4021 if (!E->ReorderIndices.empty()) { 4022 OrdersType Mask; 4023 inversePermutation(E->ReorderIndices, Mask); 4024 Builder.SetInsertPoint(VL0); 4025 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), Mask, 4026 "reorder_shuffle"); 4027 } 4028 if (NeedToShuffleReuses) { 4029 // TODO: Merge this shuffle with the ReorderShuffleMask. 4030 if (E->ReorderIndices.empty()) 4031 Builder.SetInsertPoint(VL0); 4032 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4033 E->ReuseShuffleIndices, "shuffle"); 4034 } 4035 E->VectorizedValue = V; 4036 return V; 4037 } 4038 setInsertPointAfterBundle(E); 4039 auto *V = Gather(E->Scalars, VecTy); 4040 if (NeedToShuffleReuses) { 4041 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4042 E->ReuseShuffleIndices, "shuffle"); 4043 if (auto *I = dyn_cast<Instruction>(V)) { 4044 GatherSeq.insert(I); 4045 CSEBlocks.insert(I->getParent()); 4046 } 4047 } 4048 E->VectorizedValue = V; 4049 return V; 4050 } 4051 case Instruction::ExtractValue: { 4052 if (!E->NeedToGather) { 4053 LoadInst *LI = cast<LoadInst>(E->getSingleOperand(0)); 4054 Builder.SetInsertPoint(LI); 4055 PointerType *PtrTy = PointerType::get(VecTy, LI->getPointerAddressSpace()); 4056 Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy); 4057 LoadInst *V = Builder.CreateAlignedLoad(VecTy, Ptr, LI->getAlignment()); 4058 Value *NewV = propagateMetadata(V, E->Scalars); 4059 if (!E->ReorderIndices.empty()) { 4060 OrdersType Mask; 4061 inversePermutation(E->ReorderIndices, Mask); 4062 NewV = Builder.CreateShuffleVector(NewV, UndefValue::get(VecTy), Mask, 4063 "reorder_shuffle"); 4064 } 4065 if (NeedToShuffleReuses) { 4066 // TODO: Merge this shuffle with the ReorderShuffleMask. 4067 NewV = Builder.CreateShuffleVector( 4068 NewV, UndefValue::get(VecTy), E->ReuseShuffleIndices, "shuffle"); 4069 } 4070 E->VectorizedValue = NewV; 4071 return NewV; 4072 } 4073 setInsertPointAfterBundle(E); 4074 auto *V = Gather(E->Scalars, VecTy); 4075 if (NeedToShuffleReuses) { 4076 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4077 E->ReuseShuffleIndices, "shuffle"); 4078 if (auto *I = dyn_cast<Instruction>(V)) { 4079 GatherSeq.insert(I); 4080 CSEBlocks.insert(I->getParent()); 4081 } 4082 } 4083 E->VectorizedValue = V; 4084 return V; 4085 } 4086 case Instruction::ZExt: 4087 case Instruction::SExt: 4088 case Instruction::FPToUI: 4089 case Instruction::FPToSI: 4090 case Instruction::FPExt: 4091 case Instruction::PtrToInt: 4092 case Instruction::IntToPtr: 4093 case Instruction::SIToFP: 4094 case Instruction::UIToFP: 4095 case Instruction::Trunc: 4096 case Instruction::FPTrunc: 4097 case Instruction::BitCast: { 4098 setInsertPointAfterBundle(E); 4099 4100 Value *InVec = vectorizeTree(E->getOperand(0)); 4101 4102 if (E->VectorizedValue) { 4103 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4104 return E->VectorizedValue; 4105 } 4106 4107 auto *CI = cast<CastInst>(VL0); 4108 Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy); 4109 if (NeedToShuffleReuses) { 4110 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4111 E->ReuseShuffleIndices, "shuffle"); 4112 } 4113 E->VectorizedValue = V; 4114 ++NumVectorInstructions; 4115 return V; 4116 } 4117 case Instruction::FCmp: 4118 case Instruction::ICmp: { 4119 setInsertPointAfterBundle(E); 4120 4121 Value *L = vectorizeTree(E->getOperand(0)); 4122 Value *R = vectorizeTree(E->getOperand(1)); 4123 4124 if (E->VectorizedValue) { 4125 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4126 return E->VectorizedValue; 4127 } 4128 4129 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 4130 Value *V; 4131 if (E->getOpcode() == Instruction::FCmp) 4132 V = Builder.CreateFCmp(P0, L, R); 4133 else 4134 V = Builder.CreateICmp(P0, L, R); 4135 4136 propagateIRFlags(V, E->Scalars, VL0); 4137 if (NeedToShuffleReuses) { 4138 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4139 E->ReuseShuffleIndices, "shuffle"); 4140 } 4141 E->VectorizedValue = V; 4142 ++NumVectorInstructions; 4143 return V; 4144 } 4145 case Instruction::Select: { 4146 setInsertPointAfterBundle(E); 4147 4148 Value *Cond = vectorizeTree(E->getOperand(0)); 4149 Value *True = vectorizeTree(E->getOperand(1)); 4150 Value *False = vectorizeTree(E->getOperand(2)); 4151 4152 if (E->VectorizedValue) { 4153 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4154 return E->VectorizedValue; 4155 } 4156 4157 Value *V = Builder.CreateSelect(Cond, True, False); 4158 if (NeedToShuffleReuses) { 4159 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4160 E->ReuseShuffleIndices, "shuffle"); 4161 } 4162 E->VectorizedValue = V; 4163 ++NumVectorInstructions; 4164 return V; 4165 } 4166 case Instruction::FNeg: { 4167 setInsertPointAfterBundle(E); 4168 4169 Value *Op = vectorizeTree(E->getOperand(0)); 4170 4171 if (E->VectorizedValue) { 4172 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4173 return E->VectorizedValue; 4174 } 4175 4176 Value *V = Builder.CreateUnOp( 4177 static_cast<Instruction::UnaryOps>(E->getOpcode()), Op); 4178 propagateIRFlags(V, E->Scalars, VL0); 4179 if (auto *I = dyn_cast<Instruction>(V)) 4180 V = propagateMetadata(I, E->Scalars); 4181 4182 if (NeedToShuffleReuses) { 4183 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4184 E->ReuseShuffleIndices, "shuffle"); 4185 } 4186 E->VectorizedValue = V; 4187 ++NumVectorInstructions; 4188 4189 return V; 4190 } 4191 case Instruction::Add: 4192 case Instruction::FAdd: 4193 case Instruction::Sub: 4194 case Instruction::FSub: 4195 case Instruction::Mul: 4196 case Instruction::FMul: 4197 case Instruction::UDiv: 4198 case Instruction::SDiv: 4199 case Instruction::FDiv: 4200 case Instruction::URem: 4201 case Instruction::SRem: 4202 case Instruction::FRem: 4203 case Instruction::Shl: 4204 case Instruction::LShr: 4205 case Instruction::AShr: 4206 case Instruction::And: 4207 case Instruction::Or: 4208 case Instruction::Xor: { 4209 setInsertPointAfterBundle(E); 4210 4211 Value *LHS = vectorizeTree(E->getOperand(0)); 4212 Value *RHS = vectorizeTree(E->getOperand(1)); 4213 4214 if (E->VectorizedValue) { 4215 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4216 return E->VectorizedValue; 4217 } 4218 4219 Value *V = Builder.CreateBinOp( 4220 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, 4221 RHS); 4222 propagateIRFlags(V, E->Scalars, VL0); 4223 if (auto *I = dyn_cast<Instruction>(V)) 4224 V = propagateMetadata(I, E->Scalars); 4225 4226 if (NeedToShuffleReuses) { 4227 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4228 E->ReuseShuffleIndices, "shuffle"); 4229 } 4230 E->VectorizedValue = V; 4231 ++NumVectorInstructions; 4232 4233 return V; 4234 } 4235 case Instruction::Load: { 4236 // Loads are inserted at the head of the tree because we don't want to 4237 // sink them all the way down past store instructions. 4238 bool IsReorder = E->updateStateIfReorder(); 4239 if (IsReorder) 4240 VL0 = E->getMainOp(); 4241 setInsertPointAfterBundle(E); 4242 4243 LoadInst *LI = cast<LoadInst>(VL0); 4244 Type *ScalarLoadTy = LI->getType(); 4245 unsigned AS = LI->getPointerAddressSpace(); 4246 4247 Value *VecPtr = Builder.CreateBitCast(LI->getPointerOperand(), 4248 VecTy->getPointerTo(AS)); 4249 4250 // The pointer operand uses an in-tree scalar so we add the new BitCast to 4251 // ExternalUses list to make sure that an extract will be generated in the 4252 // future. 4253 Value *PO = LI->getPointerOperand(); 4254 if (getTreeEntry(PO)) 4255 ExternalUses.push_back(ExternalUser(PO, cast<User>(VecPtr), 0)); 4256 4257 MaybeAlign Alignment = MaybeAlign(LI->getAlignment()); 4258 LI = Builder.CreateLoad(VecTy, VecPtr); 4259 if (!Alignment) 4260 Alignment = MaybeAlign(DL->getABITypeAlignment(ScalarLoadTy)); 4261 LI->setAlignment(Alignment); 4262 Value *V = propagateMetadata(LI, E->Scalars); 4263 if (IsReorder) { 4264 OrdersType Mask; 4265 inversePermutation(E->ReorderIndices, Mask); 4266 V = Builder.CreateShuffleVector(V, UndefValue::get(V->getType()), 4267 Mask, "reorder_shuffle"); 4268 } 4269 if (NeedToShuffleReuses) { 4270 // TODO: Merge this shuffle with the ReorderShuffleMask. 4271 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4272 E->ReuseShuffleIndices, "shuffle"); 4273 } 4274 E->VectorizedValue = V; 4275 ++NumVectorInstructions; 4276 return V; 4277 } 4278 case Instruction::Store: { 4279 StoreInst *SI = cast<StoreInst>(VL0); 4280 unsigned Alignment = SI->getAlignment(); 4281 unsigned AS = SI->getPointerAddressSpace(); 4282 4283 setInsertPointAfterBundle(E); 4284 4285 Value *VecValue = vectorizeTree(E->getOperand(0)); 4286 Value *ScalarPtr = SI->getPointerOperand(); 4287 Value *VecPtr = Builder.CreateBitCast(ScalarPtr, VecTy->getPointerTo(AS)); 4288 StoreInst *ST = Builder.CreateStore(VecValue, VecPtr); 4289 4290 // The pointer operand uses an in-tree scalar, so add the new BitCast to 4291 // ExternalUses to make sure that an extract will be generated in the 4292 // future. 4293 if (getTreeEntry(ScalarPtr)) 4294 ExternalUses.push_back(ExternalUser(ScalarPtr, cast<User>(VecPtr), 0)); 4295 4296 if (!Alignment) 4297 Alignment = DL->getABITypeAlignment(SI->getValueOperand()->getType()); 4298 4299 ST->setAlignment(Align(Alignment)); 4300 Value *V = propagateMetadata(ST, E->Scalars); 4301 if (NeedToShuffleReuses) { 4302 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4303 E->ReuseShuffleIndices, "shuffle"); 4304 } 4305 E->VectorizedValue = V; 4306 ++NumVectorInstructions; 4307 return V; 4308 } 4309 case Instruction::GetElementPtr: { 4310 setInsertPointAfterBundle(E); 4311 4312 Value *Op0 = vectorizeTree(E->getOperand(0)); 4313 4314 std::vector<Value *> OpVecs; 4315 for (int j = 1, e = cast<GetElementPtrInst>(VL0)->getNumOperands(); j < e; 4316 ++j) { 4317 ValueList &VL = E->getOperand(j); 4318 // Need to cast all elements to the same type before vectorization to 4319 // avoid crash. 4320 Type *VL0Ty = VL0->getOperand(j)->getType(); 4321 Type *Ty = llvm::all_of( 4322 VL, [VL0Ty](Value *V) { return VL0Ty == V->getType(); }) 4323 ? VL0Ty 4324 : DL->getIndexType(cast<GetElementPtrInst>(VL0) 4325 ->getPointerOperandType() 4326 ->getScalarType()); 4327 for (Value *&V : VL) { 4328 auto *CI = cast<ConstantInt>(V); 4329 V = ConstantExpr::getIntegerCast(CI, Ty, 4330 CI->getValue().isSignBitSet()); 4331 } 4332 Value *OpVec = vectorizeTree(VL); 4333 OpVecs.push_back(OpVec); 4334 } 4335 4336 Value *V = Builder.CreateGEP( 4337 cast<GetElementPtrInst>(VL0)->getSourceElementType(), Op0, OpVecs); 4338 if (Instruction *I = dyn_cast<Instruction>(V)) 4339 V = propagateMetadata(I, E->Scalars); 4340 4341 if (NeedToShuffleReuses) { 4342 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4343 E->ReuseShuffleIndices, "shuffle"); 4344 } 4345 E->VectorizedValue = V; 4346 ++NumVectorInstructions; 4347 4348 return V; 4349 } 4350 case Instruction::Call: { 4351 CallInst *CI = cast<CallInst>(VL0); 4352 setInsertPointAfterBundle(E); 4353 4354 Intrinsic::ID IID = Intrinsic::not_intrinsic; 4355 if (Function *FI = CI->getCalledFunction()) 4356 IID = FI->getIntrinsicID(); 4357 4358 Value *ScalarArg = nullptr; 4359 std::vector<Value *> OpVecs; 4360 for (int j = 0, e = CI->getNumArgOperands(); j < e; ++j) { 4361 ValueList OpVL; 4362 // Some intrinsics have scalar arguments. This argument should not be 4363 // vectorized. 4364 if (hasVectorInstrinsicScalarOpd(IID, j)) { 4365 CallInst *CEI = cast<CallInst>(VL0); 4366 ScalarArg = CEI->getArgOperand(j); 4367 OpVecs.push_back(CEI->getArgOperand(j)); 4368 continue; 4369 } 4370 4371 Value *OpVec = vectorizeTree(E->getOperand(j)); 4372 LLVM_DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n"); 4373 OpVecs.push_back(OpVec); 4374 } 4375 4376 Module *M = F->getParent(); 4377 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 4378 Type *Tys[] = { VectorType::get(CI->getType(), E->Scalars.size()) }; 4379 Function *CF = Intrinsic::getDeclaration(M, ID, Tys); 4380 SmallVector<OperandBundleDef, 1> OpBundles; 4381 CI->getOperandBundlesAsDefs(OpBundles); 4382 Value *V = Builder.CreateCall(CF, OpVecs, OpBundles); 4383 4384 // The scalar argument uses an in-tree scalar so we add the new vectorized 4385 // call to ExternalUses list to make sure that an extract will be 4386 // generated in the future. 4387 if (ScalarArg && getTreeEntry(ScalarArg)) 4388 ExternalUses.push_back(ExternalUser(ScalarArg, cast<User>(V), 0)); 4389 4390 propagateIRFlags(V, E->Scalars, VL0); 4391 if (NeedToShuffleReuses) { 4392 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4393 E->ReuseShuffleIndices, "shuffle"); 4394 } 4395 E->VectorizedValue = V; 4396 ++NumVectorInstructions; 4397 return V; 4398 } 4399 case Instruction::ShuffleVector: { 4400 assert(E->isAltShuffle() && 4401 ((Instruction::isBinaryOp(E->getOpcode()) && 4402 Instruction::isBinaryOp(E->getAltOpcode())) || 4403 (Instruction::isCast(E->getOpcode()) && 4404 Instruction::isCast(E->getAltOpcode()))) && 4405 "Invalid Shuffle Vector Operand"); 4406 4407 Value *LHS = nullptr, *RHS = nullptr; 4408 if (Instruction::isBinaryOp(E->getOpcode())) { 4409 setInsertPointAfterBundle(E); 4410 LHS = vectorizeTree(E->getOperand(0)); 4411 RHS = vectorizeTree(E->getOperand(1)); 4412 } else { 4413 setInsertPointAfterBundle(E); 4414 LHS = vectorizeTree(E->getOperand(0)); 4415 } 4416 4417 if (E->VectorizedValue) { 4418 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4419 return E->VectorizedValue; 4420 } 4421 4422 Value *V0, *V1; 4423 if (Instruction::isBinaryOp(E->getOpcode())) { 4424 V0 = Builder.CreateBinOp( 4425 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, RHS); 4426 V1 = Builder.CreateBinOp( 4427 static_cast<Instruction::BinaryOps>(E->getAltOpcode()), LHS, RHS); 4428 } else { 4429 V0 = Builder.CreateCast( 4430 static_cast<Instruction::CastOps>(E->getOpcode()), LHS, VecTy); 4431 V1 = Builder.CreateCast( 4432 static_cast<Instruction::CastOps>(E->getAltOpcode()), LHS, VecTy); 4433 } 4434 4435 // Create shuffle to take alternate operations from the vector. 4436 // Also, gather up main and alt scalar ops to propagate IR flags to 4437 // each vector operation. 4438 ValueList OpScalars, AltScalars; 4439 unsigned e = E->Scalars.size(); 4440 SmallVector<Constant *, 8> Mask(e); 4441 for (unsigned i = 0; i < e; ++i) { 4442 auto *OpInst = cast<Instruction>(E->Scalars[i]); 4443 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 4444 if (OpInst->getOpcode() == E->getAltOpcode()) { 4445 Mask[i] = Builder.getInt32(e + i); 4446 AltScalars.push_back(E->Scalars[i]); 4447 } else { 4448 Mask[i] = Builder.getInt32(i); 4449 OpScalars.push_back(E->Scalars[i]); 4450 } 4451 } 4452 4453 Value *ShuffleMask = ConstantVector::get(Mask); 4454 propagateIRFlags(V0, OpScalars); 4455 propagateIRFlags(V1, AltScalars); 4456 4457 Value *V = Builder.CreateShuffleVector(V0, V1, ShuffleMask); 4458 if (Instruction *I = dyn_cast<Instruction>(V)) 4459 V = propagateMetadata(I, E->Scalars); 4460 if (NeedToShuffleReuses) { 4461 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4462 E->ReuseShuffleIndices, "shuffle"); 4463 } 4464 E->VectorizedValue = V; 4465 ++NumVectorInstructions; 4466 4467 return V; 4468 } 4469 default: 4470 llvm_unreachable("unknown inst"); 4471 } 4472 return nullptr; 4473 } 4474 4475 Value *BoUpSLP::vectorizeTree() { 4476 ExtraValueToDebugLocsMap ExternallyUsedValues; 4477 return vectorizeTree(ExternallyUsedValues); 4478 } 4479 4480 Value * 4481 BoUpSLP::vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues) { 4482 // All blocks must be scheduled before any instructions are inserted. 4483 for (auto &BSIter : BlocksSchedules) { 4484 scheduleBlock(BSIter.second.get()); 4485 } 4486 4487 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4488 auto *VectorRoot = vectorizeTree(VectorizableTree[0].get()); 4489 4490 // If the vectorized tree can be rewritten in a smaller type, we truncate the 4491 // vectorized root. InstCombine will then rewrite the entire expression. We 4492 // sign extend the extracted values below. 4493 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 4494 if (MinBWs.count(ScalarRoot)) { 4495 if (auto *I = dyn_cast<Instruction>(VectorRoot)) 4496 Builder.SetInsertPoint(&*++BasicBlock::iterator(I)); 4497 auto BundleWidth = VectorizableTree[0]->Scalars.size(); 4498 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 4499 auto *VecTy = VectorType::get(MinTy, BundleWidth); 4500 auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy); 4501 VectorizableTree[0]->VectorizedValue = Trunc; 4502 } 4503 4504 LLVM_DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size() 4505 << " values .\n"); 4506 4507 // If necessary, sign-extend or zero-extend ScalarRoot to the larger type 4508 // specified by ScalarType. 4509 auto extend = [&](Value *ScalarRoot, Value *Ex, Type *ScalarType) { 4510 if (!MinBWs.count(ScalarRoot)) 4511 return Ex; 4512 if (MinBWs[ScalarRoot].second) 4513 return Builder.CreateSExt(Ex, ScalarType); 4514 return Builder.CreateZExt(Ex, ScalarType); 4515 }; 4516 4517 // Extract all of the elements with the external uses. 4518 for (const auto &ExternalUse : ExternalUses) { 4519 Value *Scalar = ExternalUse.Scalar; 4520 llvm::User *User = ExternalUse.User; 4521 4522 // Skip users that we already RAUW. This happens when one instruction 4523 // has multiple uses of the same value. 4524 if (User && !is_contained(Scalar->users(), User)) 4525 continue; 4526 TreeEntry *E = getTreeEntry(Scalar); 4527 assert(E && "Invalid scalar"); 4528 assert(!E->NeedToGather && "Extracting from a gather list"); 4529 4530 Value *Vec = E->VectorizedValue; 4531 assert(Vec && "Can't find vectorizable value"); 4532 4533 Value *Lane = Builder.getInt32(ExternalUse.Lane); 4534 // If User == nullptr, the Scalar is used as extra arg. Generate 4535 // ExtractElement instruction and update the record for this scalar in 4536 // ExternallyUsedValues. 4537 if (!User) { 4538 assert(ExternallyUsedValues.count(Scalar) && 4539 "Scalar with nullptr as an external user must be registered in " 4540 "ExternallyUsedValues map"); 4541 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 4542 Builder.SetInsertPoint(VecI->getParent(), 4543 std::next(VecI->getIterator())); 4544 } else { 4545 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4546 } 4547 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4548 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4549 CSEBlocks.insert(cast<Instruction>(Scalar)->getParent()); 4550 auto &Locs = ExternallyUsedValues[Scalar]; 4551 ExternallyUsedValues.insert({Ex, Locs}); 4552 ExternallyUsedValues.erase(Scalar); 4553 // Required to update internally referenced instructions. 4554 Scalar->replaceAllUsesWith(Ex); 4555 continue; 4556 } 4557 4558 // Generate extracts for out-of-tree users. 4559 // Find the insertion point for the extractelement lane. 4560 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 4561 if (PHINode *PH = dyn_cast<PHINode>(User)) { 4562 for (int i = 0, e = PH->getNumIncomingValues(); i != e; ++i) { 4563 if (PH->getIncomingValue(i) == Scalar) { 4564 Instruction *IncomingTerminator = 4565 PH->getIncomingBlock(i)->getTerminator(); 4566 if (isa<CatchSwitchInst>(IncomingTerminator)) { 4567 Builder.SetInsertPoint(VecI->getParent(), 4568 std::next(VecI->getIterator())); 4569 } else { 4570 Builder.SetInsertPoint(PH->getIncomingBlock(i)->getTerminator()); 4571 } 4572 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4573 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4574 CSEBlocks.insert(PH->getIncomingBlock(i)); 4575 PH->setOperand(i, Ex); 4576 } 4577 } 4578 } else { 4579 Builder.SetInsertPoint(cast<Instruction>(User)); 4580 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4581 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4582 CSEBlocks.insert(cast<Instruction>(User)->getParent()); 4583 User->replaceUsesOfWith(Scalar, Ex); 4584 } 4585 } else { 4586 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4587 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4588 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4589 CSEBlocks.insert(&F->getEntryBlock()); 4590 User->replaceUsesOfWith(Scalar, Ex); 4591 } 4592 4593 LLVM_DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n"); 4594 } 4595 4596 // For each vectorized value: 4597 for (auto &TEPtr : VectorizableTree) { 4598 TreeEntry *Entry = TEPtr.get(); 4599 4600 // No need to handle users of gathered values. 4601 if (Entry->NeedToGather) 4602 continue; 4603 4604 assert(Entry->VectorizedValue && "Can't find vectorizable value"); 4605 4606 // For each lane: 4607 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 4608 Value *Scalar = Entry->Scalars[Lane]; 4609 4610 #ifndef NDEBUG 4611 Type *Ty = Scalar->getType(); 4612 if (!Ty->isVoidTy()) { 4613 for (User *U : Scalar->users()) { 4614 LLVM_DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n"); 4615 4616 // It is legal to delete users in the ignorelist. 4617 assert((getTreeEntry(U) || is_contained(UserIgnoreList, U)) && 4618 "Deleting out-of-tree value"); 4619 } 4620 } 4621 #endif 4622 LLVM_DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n"); 4623 eraseInstruction(cast<Instruction>(Scalar)); 4624 } 4625 } 4626 4627 Builder.ClearInsertionPoint(); 4628 4629 return VectorizableTree[0]->VectorizedValue; 4630 } 4631 4632 void BoUpSLP::optimizeGatherSequence() { 4633 LLVM_DEBUG(dbgs() << "SLP: Optimizing " << GatherSeq.size() 4634 << " gather sequences instructions.\n"); 4635 // LICM InsertElementInst sequences. 4636 for (Instruction *I : GatherSeq) { 4637 if (isDeleted(I)) 4638 continue; 4639 4640 // Check if this block is inside a loop. 4641 Loop *L = LI->getLoopFor(I->getParent()); 4642 if (!L) 4643 continue; 4644 4645 // Check if it has a preheader. 4646 BasicBlock *PreHeader = L->getLoopPreheader(); 4647 if (!PreHeader) 4648 continue; 4649 4650 // If the vector or the element that we insert into it are 4651 // instructions that are defined in this basic block then we can't 4652 // hoist this instruction. 4653 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 4654 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 4655 if (Op0 && L->contains(Op0)) 4656 continue; 4657 if (Op1 && L->contains(Op1)) 4658 continue; 4659 4660 // We can hoist this instruction. Move it to the pre-header. 4661 I->moveBefore(PreHeader->getTerminator()); 4662 } 4663 4664 // Make a list of all reachable blocks in our CSE queue. 4665 SmallVector<const DomTreeNode *, 8> CSEWorkList; 4666 CSEWorkList.reserve(CSEBlocks.size()); 4667 for (BasicBlock *BB : CSEBlocks) 4668 if (DomTreeNode *N = DT->getNode(BB)) { 4669 assert(DT->isReachableFromEntry(N)); 4670 CSEWorkList.push_back(N); 4671 } 4672 4673 // Sort blocks by domination. This ensures we visit a block after all blocks 4674 // dominating it are visited. 4675 llvm::stable_sort(CSEWorkList, 4676 [this](const DomTreeNode *A, const DomTreeNode *B) { 4677 return DT->properlyDominates(A, B); 4678 }); 4679 4680 // Perform O(N^2) search over the gather sequences and merge identical 4681 // instructions. TODO: We can further optimize this scan if we split the 4682 // instructions into different buckets based on the insert lane. 4683 SmallVector<Instruction *, 16> Visited; 4684 for (auto I = CSEWorkList.begin(), E = CSEWorkList.end(); I != E; ++I) { 4685 assert((I == CSEWorkList.begin() || !DT->dominates(*I, *std::prev(I))) && 4686 "Worklist not sorted properly!"); 4687 BasicBlock *BB = (*I)->getBlock(); 4688 // For all instructions in blocks containing gather sequences: 4689 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e;) { 4690 Instruction *In = &*it++; 4691 if (isDeleted(In)) 4692 continue; 4693 if (!isa<InsertElementInst>(In) && !isa<ExtractElementInst>(In)) 4694 continue; 4695 4696 // Check if we can replace this instruction with any of the 4697 // visited instructions. 4698 for (Instruction *v : Visited) { 4699 if (In->isIdenticalTo(v) && 4700 DT->dominates(v->getParent(), In->getParent())) { 4701 In->replaceAllUsesWith(v); 4702 eraseInstruction(In); 4703 In = nullptr; 4704 break; 4705 } 4706 } 4707 if (In) { 4708 assert(!is_contained(Visited, In)); 4709 Visited.push_back(In); 4710 } 4711 } 4712 } 4713 CSEBlocks.clear(); 4714 GatherSeq.clear(); 4715 } 4716 4717 // Groups the instructions to a bundle (which is then a single scheduling entity) 4718 // and schedules instructions until the bundle gets ready. 4719 Optional<BoUpSLP::ScheduleData *> 4720 BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 4721 const InstructionsState &S) { 4722 if (isa<PHINode>(S.OpValue)) 4723 return nullptr; 4724 4725 // Initialize the instruction bundle. 4726 Instruction *OldScheduleEnd = ScheduleEnd; 4727 ScheduleData *PrevInBundle = nullptr; 4728 ScheduleData *Bundle = nullptr; 4729 bool ReSchedule = false; 4730 LLVM_DEBUG(dbgs() << "SLP: bundle: " << *S.OpValue << "\n"); 4731 4732 // Make sure that the scheduling region contains all 4733 // instructions of the bundle. 4734 for (Value *V : VL) { 4735 if (!extendSchedulingRegion(V, S)) 4736 return None; 4737 } 4738 4739 for (Value *V : VL) { 4740 ScheduleData *BundleMember = getScheduleData(V); 4741 assert(BundleMember && 4742 "no ScheduleData for bundle member (maybe not in same basic block)"); 4743 if (BundleMember->IsScheduled) { 4744 // A bundle member was scheduled as single instruction before and now 4745 // needs to be scheduled as part of the bundle. We just get rid of the 4746 // existing schedule. 4747 LLVM_DEBUG(dbgs() << "SLP: reset schedule because " << *BundleMember 4748 << " was already scheduled\n"); 4749 ReSchedule = true; 4750 } 4751 assert(BundleMember->isSchedulingEntity() && 4752 "bundle member already part of other bundle"); 4753 if (PrevInBundle) { 4754 PrevInBundle->NextInBundle = BundleMember; 4755 } else { 4756 Bundle = BundleMember; 4757 } 4758 BundleMember->UnscheduledDepsInBundle = 0; 4759 Bundle->UnscheduledDepsInBundle += BundleMember->UnscheduledDeps; 4760 4761 // Group the instructions to a bundle. 4762 BundleMember->FirstInBundle = Bundle; 4763 PrevInBundle = BundleMember; 4764 } 4765 if (ScheduleEnd != OldScheduleEnd) { 4766 // The scheduling region got new instructions at the lower end (or it is a 4767 // new region for the first bundle). This makes it necessary to 4768 // recalculate all dependencies. 4769 // It is seldom that this needs to be done a second time after adding the 4770 // initial bundle to the region. 4771 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 4772 doForAllOpcodes(I, [](ScheduleData *SD) { 4773 SD->clearDependencies(); 4774 }); 4775 } 4776 ReSchedule = true; 4777 } 4778 if (ReSchedule) { 4779 resetSchedule(); 4780 initialFillReadyList(ReadyInsts); 4781 } 4782 assert(Bundle && "Failed to find schedule bundle"); 4783 4784 LLVM_DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle << " in block " 4785 << BB->getName() << "\n"); 4786 4787 calculateDependencies(Bundle, true, SLP); 4788 4789 // Now try to schedule the new bundle. As soon as the bundle is "ready" it 4790 // means that there are no cyclic dependencies and we can schedule it. 4791 // Note that's important that we don't "schedule" the bundle yet (see 4792 // cancelScheduling). 4793 while (!Bundle->isReady() && !ReadyInsts.empty()) { 4794 4795 ScheduleData *pickedSD = ReadyInsts.back(); 4796 ReadyInsts.pop_back(); 4797 4798 if (pickedSD->isSchedulingEntity() && pickedSD->isReady()) { 4799 schedule(pickedSD, ReadyInsts); 4800 } 4801 } 4802 if (!Bundle->isReady()) { 4803 cancelScheduling(VL, S.OpValue); 4804 return None; 4805 } 4806 return Bundle; 4807 } 4808 4809 void BoUpSLP::BlockScheduling::cancelScheduling(ArrayRef<Value *> VL, 4810 Value *OpValue) { 4811 if (isa<PHINode>(OpValue)) 4812 return; 4813 4814 ScheduleData *Bundle = getScheduleData(OpValue); 4815 LLVM_DEBUG(dbgs() << "SLP: cancel scheduling of " << *Bundle << "\n"); 4816 assert(!Bundle->IsScheduled && 4817 "Can't cancel bundle which is already scheduled"); 4818 assert(Bundle->isSchedulingEntity() && Bundle->isPartOfBundle() && 4819 "tried to unbundle something which is not a bundle"); 4820 4821 // Un-bundle: make single instructions out of the bundle. 4822 ScheduleData *BundleMember = Bundle; 4823 while (BundleMember) { 4824 assert(BundleMember->FirstInBundle == Bundle && "corrupt bundle links"); 4825 BundleMember->FirstInBundle = BundleMember; 4826 ScheduleData *Next = BundleMember->NextInBundle; 4827 BundleMember->NextInBundle = nullptr; 4828 BundleMember->UnscheduledDepsInBundle = BundleMember->UnscheduledDeps; 4829 if (BundleMember->UnscheduledDepsInBundle == 0) { 4830 ReadyInsts.insert(BundleMember); 4831 } 4832 BundleMember = Next; 4833 } 4834 } 4835 4836 BoUpSLP::ScheduleData *BoUpSLP::BlockScheduling::allocateScheduleDataChunks() { 4837 // Allocate a new ScheduleData for the instruction. 4838 if (ChunkPos >= ChunkSize) { 4839 ScheduleDataChunks.push_back(std::make_unique<ScheduleData[]>(ChunkSize)); 4840 ChunkPos = 0; 4841 } 4842 return &(ScheduleDataChunks.back()[ChunkPos++]); 4843 } 4844 4845 bool BoUpSLP::BlockScheduling::extendSchedulingRegion(Value *V, 4846 const InstructionsState &S) { 4847 if (getScheduleData(V, isOneOf(S, V))) 4848 return true; 4849 Instruction *I = dyn_cast<Instruction>(V); 4850 assert(I && "bundle member must be an instruction"); 4851 assert(!isa<PHINode>(I) && "phi nodes don't need to be scheduled"); 4852 auto &&CheckSheduleForI = [this, &S](Instruction *I) -> bool { 4853 ScheduleData *ISD = getScheduleData(I); 4854 if (!ISD) 4855 return false; 4856 assert(isInSchedulingRegion(ISD) && 4857 "ScheduleData not in scheduling region"); 4858 ScheduleData *SD = allocateScheduleDataChunks(); 4859 SD->Inst = I; 4860 SD->init(SchedulingRegionID, S.OpValue); 4861 ExtraScheduleDataMap[I][S.OpValue] = SD; 4862 return true; 4863 }; 4864 if (CheckSheduleForI(I)) 4865 return true; 4866 if (!ScheduleStart) { 4867 // It's the first instruction in the new region. 4868 initScheduleData(I, I->getNextNode(), nullptr, nullptr); 4869 ScheduleStart = I; 4870 ScheduleEnd = I->getNextNode(); 4871 if (isOneOf(S, I) != I) 4872 CheckSheduleForI(I); 4873 assert(ScheduleEnd && "tried to vectorize a terminator?"); 4874 LLVM_DEBUG(dbgs() << "SLP: initialize schedule region to " << *I << "\n"); 4875 return true; 4876 } 4877 // Search up and down at the same time, because we don't know if the new 4878 // instruction is above or below the existing scheduling region. 4879 BasicBlock::reverse_iterator UpIter = 4880 ++ScheduleStart->getIterator().getReverse(); 4881 BasicBlock::reverse_iterator UpperEnd = BB->rend(); 4882 BasicBlock::iterator DownIter = ScheduleEnd->getIterator(); 4883 BasicBlock::iterator LowerEnd = BB->end(); 4884 while (true) { 4885 if (++ScheduleRegionSize > ScheduleRegionSizeLimit) { 4886 LLVM_DEBUG(dbgs() << "SLP: exceeded schedule region size limit\n"); 4887 return false; 4888 } 4889 4890 if (UpIter != UpperEnd) { 4891 if (&*UpIter == I) { 4892 initScheduleData(I, ScheduleStart, nullptr, FirstLoadStoreInRegion); 4893 ScheduleStart = I; 4894 if (isOneOf(S, I) != I) 4895 CheckSheduleForI(I); 4896 LLVM_DEBUG(dbgs() << "SLP: extend schedule region start to " << *I 4897 << "\n"); 4898 return true; 4899 } 4900 ++UpIter; 4901 } 4902 if (DownIter != LowerEnd) { 4903 if (&*DownIter == I) { 4904 initScheduleData(ScheduleEnd, I->getNextNode(), LastLoadStoreInRegion, 4905 nullptr); 4906 ScheduleEnd = I->getNextNode(); 4907 if (isOneOf(S, I) != I) 4908 CheckSheduleForI(I); 4909 assert(ScheduleEnd && "tried to vectorize a terminator?"); 4910 LLVM_DEBUG(dbgs() << "SLP: extend schedule region end to " << *I 4911 << "\n"); 4912 return true; 4913 } 4914 ++DownIter; 4915 } 4916 assert((UpIter != UpperEnd || DownIter != LowerEnd) && 4917 "instruction not found in block"); 4918 } 4919 return true; 4920 } 4921 4922 void BoUpSLP::BlockScheduling::initScheduleData(Instruction *FromI, 4923 Instruction *ToI, 4924 ScheduleData *PrevLoadStore, 4925 ScheduleData *NextLoadStore) { 4926 ScheduleData *CurrentLoadStore = PrevLoadStore; 4927 for (Instruction *I = FromI; I != ToI; I = I->getNextNode()) { 4928 ScheduleData *SD = ScheduleDataMap[I]; 4929 if (!SD) { 4930 SD = allocateScheduleDataChunks(); 4931 ScheduleDataMap[I] = SD; 4932 SD->Inst = I; 4933 } 4934 assert(!isInSchedulingRegion(SD) && 4935 "new ScheduleData already in scheduling region"); 4936 SD->init(SchedulingRegionID, I); 4937 4938 if (I->mayReadOrWriteMemory() && 4939 (!isa<IntrinsicInst>(I) || 4940 cast<IntrinsicInst>(I)->getIntrinsicID() != Intrinsic::sideeffect)) { 4941 // Update the linked list of memory accessing instructions. 4942 if (CurrentLoadStore) { 4943 CurrentLoadStore->NextLoadStore = SD; 4944 } else { 4945 FirstLoadStoreInRegion = SD; 4946 } 4947 CurrentLoadStore = SD; 4948 } 4949 } 4950 if (NextLoadStore) { 4951 if (CurrentLoadStore) 4952 CurrentLoadStore->NextLoadStore = NextLoadStore; 4953 } else { 4954 LastLoadStoreInRegion = CurrentLoadStore; 4955 } 4956 } 4957 4958 void BoUpSLP::BlockScheduling::calculateDependencies(ScheduleData *SD, 4959 bool InsertInReadyList, 4960 BoUpSLP *SLP) { 4961 assert(SD->isSchedulingEntity()); 4962 4963 SmallVector<ScheduleData *, 10> WorkList; 4964 WorkList.push_back(SD); 4965 4966 while (!WorkList.empty()) { 4967 ScheduleData *SD = WorkList.back(); 4968 WorkList.pop_back(); 4969 4970 ScheduleData *BundleMember = SD; 4971 while (BundleMember) { 4972 assert(isInSchedulingRegion(BundleMember)); 4973 if (!BundleMember->hasValidDependencies()) { 4974 4975 LLVM_DEBUG(dbgs() << "SLP: update deps of " << *BundleMember 4976 << "\n"); 4977 BundleMember->Dependencies = 0; 4978 BundleMember->resetUnscheduledDeps(); 4979 4980 // Handle def-use chain dependencies. 4981 if (BundleMember->OpValue != BundleMember->Inst) { 4982 ScheduleData *UseSD = getScheduleData(BundleMember->Inst); 4983 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 4984 BundleMember->Dependencies++; 4985 ScheduleData *DestBundle = UseSD->FirstInBundle; 4986 if (!DestBundle->IsScheduled) 4987 BundleMember->incrementUnscheduledDeps(1); 4988 if (!DestBundle->hasValidDependencies()) 4989 WorkList.push_back(DestBundle); 4990 } 4991 } else { 4992 for (User *U : BundleMember->Inst->users()) { 4993 if (isa<Instruction>(U)) { 4994 ScheduleData *UseSD = getScheduleData(U); 4995 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 4996 BundleMember->Dependencies++; 4997 ScheduleData *DestBundle = UseSD->FirstInBundle; 4998 if (!DestBundle->IsScheduled) 4999 BundleMember->incrementUnscheduledDeps(1); 5000 if (!DestBundle->hasValidDependencies()) 5001 WorkList.push_back(DestBundle); 5002 } 5003 } else { 5004 // I'm not sure if this can ever happen. But we need to be safe. 5005 // This lets the instruction/bundle never be scheduled and 5006 // eventually disable vectorization. 5007 BundleMember->Dependencies++; 5008 BundleMember->incrementUnscheduledDeps(1); 5009 } 5010 } 5011 } 5012 5013 // Handle the memory dependencies. 5014 ScheduleData *DepDest = BundleMember->NextLoadStore; 5015 if (DepDest) { 5016 Instruction *SrcInst = BundleMember->Inst; 5017 MemoryLocation SrcLoc = getLocation(SrcInst, SLP->AA); 5018 bool SrcMayWrite = BundleMember->Inst->mayWriteToMemory(); 5019 unsigned numAliased = 0; 5020 unsigned DistToSrc = 1; 5021 5022 while (DepDest) { 5023 assert(isInSchedulingRegion(DepDest)); 5024 5025 // We have two limits to reduce the complexity: 5026 // 1) AliasedCheckLimit: It's a small limit to reduce calls to 5027 // SLP->isAliased (which is the expensive part in this loop). 5028 // 2) MaxMemDepDistance: It's for very large blocks and it aborts 5029 // the whole loop (even if the loop is fast, it's quadratic). 5030 // It's important for the loop break condition (see below) to 5031 // check this limit even between two read-only instructions. 5032 if (DistToSrc >= MaxMemDepDistance || 5033 ((SrcMayWrite || DepDest->Inst->mayWriteToMemory()) && 5034 (numAliased >= AliasedCheckLimit || 5035 SLP->isAliased(SrcLoc, SrcInst, DepDest->Inst)))) { 5036 5037 // We increment the counter only if the locations are aliased 5038 // (instead of counting all alias checks). This gives a better 5039 // balance between reduced runtime and accurate dependencies. 5040 numAliased++; 5041 5042 DepDest->MemoryDependencies.push_back(BundleMember); 5043 BundleMember->Dependencies++; 5044 ScheduleData *DestBundle = DepDest->FirstInBundle; 5045 if (!DestBundle->IsScheduled) { 5046 BundleMember->incrementUnscheduledDeps(1); 5047 } 5048 if (!DestBundle->hasValidDependencies()) { 5049 WorkList.push_back(DestBundle); 5050 } 5051 } 5052 DepDest = DepDest->NextLoadStore; 5053 5054 // Example, explaining the loop break condition: Let's assume our 5055 // starting instruction is i0 and MaxMemDepDistance = 3. 5056 // 5057 // +--------v--v--v 5058 // i0,i1,i2,i3,i4,i5,i6,i7,i8 5059 // +--------^--^--^ 5060 // 5061 // MaxMemDepDistance let us stop alias-checking at i3 and we add 5062 // dependencies from i0 to i3,i4,.. (even if they are not aliased). 5063 // Previously we already added dependencies from i3 to i6,i7,i8 5064 // (because of MaxMemDepDistance). As we added a dependency from 5065 // i0 to i3, we have transitive dependencies from i0 to i6,i7,i8 5066 // and we can abort this loop at i6. 5067 if (DistToSrc >= 2 * MaxMemDepDistance) 5068 break; 5069 DistToSrc++; 5070 } 5071 } 5072 } 5073 BundleMember = BundleMember->NextInBundle; 5074 } 5075 if (InsertInReadyList && SD->isReady()) { 5076 ReadyInsts.push_back(SD); 5077 LLVM_DEBUG(dbgs() << "SLP: gets ready on update: " << *SD->Inst 5078 << "\n"); 5079 } 5080 } 5081 } 5082 5083 void BoUpSLP::BlockScheduling::resetSchedule() { 5084 assert(ScheduleStart && 5085 "tried to reset schedule on block which has not been scheduled"); 5086 for (Instruction *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 5087 doForAllOpcodes(I, [&](ScheduleData *SD) { 5088 assert(isInSchedulingRegion(SD) && 5089 "ScheduleData not in scheduling region"); 5090 SD->IsScheduled = false; 5091 SD->resetUnscheduledDeps(); 5092 }); 5093 } 5094 ReadyInsts.clear(); 5095 } 5096 5097 void BoUpSLP::scheduleBlock(BlockScheduling *BS) { 5098 if (!BS->ScheduleStart) 5099 return; 5100 5101 LLVM_DEBUG(dbgs() << "SLP: schedule block " << BS->BB->getName() << "\n"); 5102 5103 BS->resetSchedule(); 5104 5105 // For the real scheduling we use a more sophisticated ready-list: it is 5106 // sorted by the original instruction location. This lets the final schedule 5107 // be as close as possible to the original instruction order. 5108 struct ScheduleDataCompare { 5109 bool operator()(ScheduleData *SD1, ScheduleData *SD2) const { 5110 return SD2->SchedulingPriority < SD1->SchedulingPriority; 5111 } 5112 }; 5113 std::set<ScheduleData *, ScheduleDataCompare> ReadyInsts; 5114 5115 // Ensure that all dependency data is updated and fill the ready-list with 5116 // initial instructions. 5117 int Idx = 0; 5118 int NumToSchedule = 0; 5119 for (auto *I = BS->ScheduleStart; I != BS->ScheduleEnd; 5120 I = I->getNextNode()) { 5121 BS->doForAllOpcodes(I, [this, &Idx, &NumToSchedule, BS](ScheduleData *SD) { 5122 assert(SD->isPartOfBundle() == 5123 (getTreeEntry(SD->Inst) != nullptr) && 5124 "scheduler and vectorizer bundle mismatch"); 5125 SD->FirstInBundle->SchedulingPriority = Idx++; 5126 if (SD->isSchedulingEntity()) { 5127 BS->calculateDependencies(SD, false, this); 5128 NumToSchedule++; 5129 } 5130 }); 5131 } 5132 BS->initialFillReadyList(ReadyInsts); 5133 5134 Instruction *LastScheduledInst = BS->ScheduleEnd; 5135 5136 // Do the "real" scheduling. 5137 while (!ReadyInsts.empty()) { 5138 ScheduleData *picked = *ReadyInsts.begin(); 5139 ReadyInsts.erase(ReadyInsts.begin()); 5140 5141 // Move the scheduled instruction(s) to their dedicated places, if not 5142 // there yet. 5143 ScheduleData *BundleMember = picked; 5144 while (BundleMember) { 5145 Instruction *pickedInst = BundleMember->Inst; 5146 if (LastScheduledInst->getNextNode() != pickedInst) { 5147 BS->BB->getInstList().remove(pickedInst); 5148 BS->BB->getInstList().insert(LastScheduledInst->getIterator(), 5149 pickedInst); 5150 } 5151 LastScheduledInst = pickedInst; 5152 BundleMember = BundleMember->NextInBundle; 5153 } 5154 5155 BS->schedule(picked, ReadyInsts); 5156 NumToSchedule--; 5157 } 5158 assert(NumToSchedule == 0 && "could not schedule all instructions"); 5159 5160 // Avoid duplicate scheduling of the block. 5161 BS->ScheduleStart = nullptr; 5162 } 5163 5164 unsigned BoUpSLP::getVectorElementSize(Value *V) const { 5165 // If V is a store, just return the width of the stored value without 5166 // traversing the expression tree. This is the common case. 5167 if (auto *Store = dyn_cast<StoreInst>(V)) 5168 return DL->getTypeSizeInBits(Store->getValueOperand()->getType()); 5169 5170 // If V is not a store, we can traverse the expression tree to find loads 5171 // that feed it. The type of the loaded value may indicate a more suitable 5172 // width than V's type. We want to base the vector element size on the width 5173 // of memory operations where possible. 5174 SmallVector<Instruction *, 16> Worklist; 5175 SmallPtrSet<Instruction *, 16> Visited; 5176 if (auto *I = dyn_cast<Instruction>(V)) 5177 Worklist.push_back(I); 5178 5179 // Traverse the expression tree in bottom-up order looking for loads. If we 5180 // encounter an instruction we don't yet handle, we give up. 5181 auto MaxWidth = 0u; 5182 auto FoundUnknownInst = false; 5183 while (!Worklist.empty() && !FoundUnknownInst) { 5184 auto *I = Worklist.pop_back_val(); 5185 Visited.insert(I); 5186 5187 // We should only be looking at scalar instructions here. If the current 5188 // instruction has a vector type, give up. 5189 auto *Ty = I->getType(); 5190 if (isa<VectorType>(Ty)) 5191 FoundUnknownInst = true; 5192 5193 // If the current instruction is a load, update MaxWidth to reflect the 5194 // width of the loaded value. 5195 else if (isa<LoadInst>(I)) 5196 MaxWidth = std::max<unsigned>(MaxWidth, DL->getTypeSizeInBits(Ty)); 5197 5198 // Otherwise, we need to visit the operands of the instruction. We only 5199 // handle the interesting cases from buildTree here. If an operand is an 5200 // instruction we haven't yet visited, we add it to the worklist. 5201 else if (isa<PHINode>(I) || isa<CastInst>(I) || isa<GetElementPtrInst>(I) || 5202 isa<CmpInst>(I) || isa<SelectInst>(I) || isa<BinaryOperator>(I)) { 5203 for (Use &U : I->operands()) 5204 if (auto *J = dyn_cast<Instruction>(U.get())) 5205 if (!Visited.count(J)) 5206 Worklist.push_back(J); 5207 } 5208 5209 // If we don't yet handle the instruction, give up. 5210 else 5211 FoundUnknownInst = true; 5212 } 5213 5214 // If we didn't encounter a memory access in the expression tree, or if we 5215 // gave up for some reason, just return the width of V. 5216 if (!MaxWidth || FoundUnknownInst) 5217 return DL->getTypeSizeInBits(V->getType()); 5218 5219 // Otherwise, return the maximum width we found. 5220 return MaxWidth; 5221 } 5222 5223 // Determine if a value V in a vectorizable expression Expr can be demoted to a 5224 // smaller type with a truncation. We collect the values that will be demoted 5225 // in ToDemote and additional roots that require investigating in Roots. 5226 static bool collectValuesToDemote(Value *V, SmallPtrSetImpl<Value *> &Expr, 5227 SmallVectorImpl<Value *> &ToDemote, 5228 SmallVectorImpl<Value *> &Roots) { 5229 // We can always demote constants. 5230 if (isa<Constant>(V)) { 5231 ToDemote.push_back(V); 5232 return true; 5233 } 5234 5235 // If the value is not an instruction in the expression with only one use, it 5236 // cannot be demoted. 5237 auto *I = dyn_cast<Instruction>(V); 5238 if (!I || !I->hasOneUse() || !Expr.count(I)) 5239 return false; 5240 5241 switch (I->getOpcode()) { 5242 5243 // We can always demote truncations and extensions. Since truncations can 5244 // seed additional demotion, we save the truncated value. 5245 case Instruction::Trunc: 5246 Roots.push_back(I->getOperand(0)); 5247 break; 5248 case Instruction::ZExt: 5249 case Instruction::SExt: 5250 break; 5251 5252 // We can demote certain binary operations if we can demote both of their 5253 // operands. 5254 case Instruction::Add: 5255 case Instruction::Sub: 5256 case Instruction::Mul: 5257 case Instruction::And: 5258 case Instruction::Or: 5259 case Instruction::Xor: 5260 if (!collectValuesToDemote(I->getOperand(0), Expr, ToDemote, Roots) || 5261 !collectValuesToDemote(I->getOperand(1), Expr, ToDemote, Roots)) 5262 return false; 5263 break; 5264 5265 // We can demote selects if we can demote their true and false values. 5266 case Instruction::Select: { 5267 SelectInst *SI = cast<SelectInst>(I); 5268 if (!collectValuesToDemote(SI->getTrueValue(), Expr, ToDemote, Roots) || 5269 !collectValuesToDemote(SI->getFalseValue(), Expr, ToDemote, Roots)) 5270 return false; 5271 break; 5272 } 5273 5274 // We can demote phis if we can demote all their incoming operands. Note that 5275 // we don't need to worry about cycles since we ensure single use above. 5276 case Instruction::PHI: { 5277 PHINode *PN = cast<PHINode>(I); 5278 for (Value *IncValue : PN->incoming_values()) 5279 if (!collectValuesToDemote(IncValue, Expr, ToDemote, Roots)) 5280 return false; 5281 break; 5282 } 5283 5284 // Otherwise, conservatively give up. 5285 default: 5286 return false; 5287 } 5288 5289 // Record the value that we can demote. 5290 ToDemote.push_back(V); 5291 return true; 5292 } 5293 5294 void BoUpSLP::computeMinimumValueSizes() { 5295 // If there are no external uses, the expression tree must be rooted by a 5296 // store. We can't demote in-memory values, so there is nothing to do here. 5297 if (ExternalUses.empty()) 5298 return; 5299 5300 // We only attempt to truncate integer expressions. 5301 auto &TreeRoot = VectorizableTree[0]->Scalars; 5302 auto *TreeRootIT = dyn_cast<IntegerType>(TreeRoot[0]->getType()); 5303 if (!TreeRootIT) 5304 return; 5305 5306 // If the expression is not rooted by a store, these roots should have 5307 // external uses. We will rely on InstCombine to rewrite the expression in 5308 // the narrower type. However, InstCombine only rewrites single-use values. 5309 // This means that if a tree entry other than a root is used externally, it 5310 // must have multiple uses and InstCombine will not rewrite it. The code 5311 // below ensures that only the roots are used externally. 5312 SmallPtrSet<Value *, 32> Expr(TreeRoot.begin(), TreeRoot.end()); 5313 for (auto &EU : ExternalUses) 5314 if (!Expr.erase(EU.Scalar)) 5315 return; 5316 if (!Expr.empty()) 5317 return; 5318 5319 // Collect the scalar values of the vectorizable expression. We will use this 5320 // context to determine which values can be demoted. If we see a truncation, 5321 // we mark it as seeding another demotion. 5322 for (auto &EntryPtr : VectorizableTree) 5323 Expr.insert(EntryPtr->Scalars.begin(), EntryPtr->Scalars.end()); 5324 5325 // Ensure the roots of the vectorizable tree don't form a cycle. They must 5326 // have a single external user that is not in the vectorizable tree. 5327 for (auto *Root : TreeRoot) 5328 if (!Root->hasOneUse() || Expr.count(*Root->user_begin())) 5329 return; 5330 5331 // Conservatively determine if we can actually truncate the roots of the 5332 // expression. Collect the values that can be demoted in ToDemote and 5333 // additional roots that require investigating in Roots. 5334 SmallVector<Value *, 32> ToDemote; 5335 SmallVector<Value *, 4> Roots; 5336 for (auto *Root : TreeRoot) 5337 if (!collectValuesToDemote(Root, Expr, ToDemote, Roots)) 5338 return; 5339 5340 // The maximum bit width required to represent all the values that can be 5341 // demoted without loss of precision. It would be safe to truncate the roots 5342 // of the expression to this width. 5343 auto MaxBitWidth = 8u; 5344 5345 // We first check if all the bits of the roots are demanded. If they're not, 5346 // we can truncate the roots to this narrower type. 5347 for (auto *Root : TreeRoot) { 5348 auto Mask = DB->getDemandedBits(cast<Instruction>(Root)); 5349 MaxBitWidth = std::max<unsigned>( 5350 Mask.getBitWidth() - Mask.countLeadingZeros(), MaxBitWidth); 5351 } 5352 5353 // True if the roots can be zero-extended back to their original type, rather 5354 // than sign-extended. We know that if the leading bits are not demanded, we 5355 // can safely zero-extend. So we initialize IsKnownPositive to True. 5356 bool IsKnownPositive = true; 5357 5358 // If all the bits of the roots are demanded, we can try a little harder to 5359 // compute a narrower type. This can happen, for example, if the roots are 5360 // getelementptr indices. InstCombine promotes these indices to the pointer 5361 // width. Thus, all their bits are technically demanded even though the 5362 // address computation might be vectorized in a smaller type. 5363 // 5364 // We start by looking at each entry that can be demoted. We compute the 5365 // maximum bit width required to store the scalar by using ValueTracking to 5366 // compute the number of high-order bits we can truncate. 5367 if (MaxBitWidth == DL->getTypeSizeInBits(TreeRoot[0]->getType()) && 5368 llvm::all_of(TreeRoot, [](Value *R) { 5369 assert(R->hasOneUse() && "Root should have only one use!"); 5370 return isa<GetElementPtrInst>(R->user_back()); 5371 })) { 5372 MaxBitWidth = 8u; 5373 5374 // Determine if the sign bit of all the roots is known to be zero. If not, 5375 // IsKnownPositive is set to False. 5376 IsKnownPositive = llvm::all_of(TreeRoot, [&](Value *R) { 5377 KnownBits Known = computeKnownBits(R, *DL); 5378 return Known.isNonNegative(); 5379 }); 5380 5381 // Determine the maximum number of bits required to store the scalar 5382 // values. 5383 for (auto *Scalar : ToDemote) { 5384 auto NumSignBits = ComputeNumSignBits(Scalar, *DL, 0, AC, nullptr, DT); 5385 auto NumTypeBits = DL->getTypeSizeInBits(Scalar->getType()); 5386 MaxBitWidth = std::max<unsigned>(NumTypeBits - NumSignBits, MaxBitWidth); 5387 } 5388 5389 // If we can't prove that the sign bit is zero, we must add one to the 5390 // maximum bit width to account for the unknown sign bit. This preserves 5391 // the existing sign bit so we can safely sign-extend the root back to the 5392 // original type. Otherwise, if we know the sign bit is zero, we will 5393 // zero-extend the root instead. 5394 // 5395 // FIXME: This is somewhat suboptimal, as there will be cases where adding 5396 // one to the maximum bit width will yield a larger-than-necessary 5397 // type. In general, we need to add an extra bit only if we can't 5398 // prove that the upper bit of the original type is equal to the 5399 // upper bit of the proposed smaller type. If these two bits are the 5400 // same (either zero or one) we know that sign-extending from the 5401 // smaller type will result in the same value. Here, since we can't 5402 // yet prove this, we are just making the proposed smaller type 5403 // larger to ensure correctness. 5404 if (!IsKnownPositive) 5405 ++MaxBitWidth; 5406 } 5407 5408 // Round MaxBitWidth up to the next power-of-two. 5409 if (!isPowerOf2_64(MaxBitWidth)) 5410 MaxBitWidth = NextPowerOf2(MaxBitWidth); 5411 5412 // If the maximum bit width we compute is less than the with of the roots' 5413 // type, we can proceed with the narrowing. Otherwise, do nothing. 5414 if (MaxBitWidth >= TreeRootIT->getBitWidth()) 5415 return; 5416 5417 // If we can truncate the root, we must collect additional values that might 5418 // be demoted as a result. That is, those seeded by truncations we will 5419 // modify. 5420 while (!Roots.empty()) 5421 collectValuesToDemote(Roots.pop_back_val(), Expr, ToDemote, Roots); 5422 5423 // Finally, map the values we can demote to the maximum bit with we computed. 5424 for (auto *Scalar : ToDemote) 5425 MinBWs[Scalar] = std::make_pair(MaxBitWidth, !IsKnownPositive); 5426 } 5427 5428 namespace { 5429 5430 /// The SLPVectorizer Pass. 5431 struct SLPVectorizer : public FunctionPass { 5432 SLPVectorizerPass Impl; 5433 5434 /// Pass identification, replacement for typeid 5435 static char ID; 5436 5437 explicit SLPVectorizer() : FunctionPass(ID) { 5438 initializeSLPVectorizerPass(*PassRegistry::getPassRegistry()); 5439 } 5440 5441 bool doInitialization(Module &M) override { 5442 return false; 5443 } 5444 5445 bool runOnFunction(Function &F) override { 5446 if (skipFunction(F)) 5447 return false; 5448 5449 auto *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 5450 auto *TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F); 5451 auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>(); 5452 auto *TLI = TLIP ? &TLIP->getTLI(F) : nullptr; 5453 auto *AA = &getAnalysis<AAResultsWrapperPass>().getAAResults(); 5454 auto *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 5455 auto *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 5456 auto *AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F); 5457 auto *DB = &getAnalysis<DemandedBitsWrapperPass>().getDemandedBits(); 5458 auto *ORE = &getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE(); 5459 5460 return Impl.runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 5461 } 5462 5463 void getAnalysisUsage(AnalysisUsage &AU) const override { 5464 FunctionPass::getAnalysisUsage(AU); 5465 AU.addRequired<AssumptionCacheTracker>(); 5466 AU.addRequired<ScalarEvolutionWrapperPass>(); 5467 AU.addRequired<AAResultsWrapperPass>(); 5468 AU.addRequired<TargetTransformInfoWrapperPass>(); 5469 AU.addRequired<LoopInfoWrapperPass>(); 5470 AU.addRequired<DominatorTreeWrapperPass>(); 5471 AU.addRequired<DemandedBitsWrapperPass>(); 5472 AU.addRequired<OptimizationRemarkEmitterWrapperPass>(); 5473 AU.addPreserved<LoopInfoWrapperPass>(); 5474 AU.addPreserved<DominatorTreeWrapperPass>(); 5475 AU.addPreserved<AAResultsWrapperPass>(); 5476 AU.addPreserved<GlobalsAAWrapperPass>(); 5477 AU.setPreservesCFG(); 5478 } 5479 }; 5480 5481 } // end anonymous namespace 5482 5483 PreservedAnalyses SLPVectorizerPass::run(Function &F, FunctionAnalysisManager &AM) { 5484 auto *SE = &AM.getResult<ScalarEvolutionAnalysis>(F); 5485 auto *TTI = &AM.getResult<TargetIRAnalysis>(F); 5486 auto *TLI = AM.getCachedResult<TargetLibraryAnalysis>(F); 5487 auto *AA = &AM.getResult<AAManager>(F); 5488 auto *LI = &AM.getResult<LoopAnalysis>(F); 5489 auto *DT = &AM.getResult<DominatorTreeAnalysis>(F); 5490 auto *AC = &AM.getResult<AssumptionAnalysis>(F); 5491 auto *DB = &AM.getResult<DemandedBitsAnalysis>(F); 5492 auto *ORE = &AM.getResult<OptimizationRemarkEmitterAnalysis>(F); 5493 5494 bool Changed = runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 5495 if (!Changed) 5496 return PreservedAnalyses::all(); 5497 5498 PreservedAnalyses PA; 5499 PA.preserveSet<CFGAnalyses>(); 5500 PA.preserve<AAManager>(); 5501 PA.preserve<GlobalsAA>(); 5502 return PA; 5503 } 5504 5505 bool SLPVectorizerPass::runImpl(Function &F, ScalarEvolution *SE_, 5506 TargetTransformInfo *TTI_, 5507 TargetLibraryInfo *TLI_, AliasAnalysis *AA_, 5508 LoopInfo *LI_, DominatorTree *DT_, 5509 AssumptionCache *AC_, DemandedBits *DB_, 5510 OptimizationRemarkEmitter *ORE_) { 5511 SE = SE_; 5512 TTI = TTI_; 5513 TLI = TLI_; 5514 AA = AA_; 5515 LI = LI_; 5516 DT = DT_; 5517 AC = AC_; 5518 DB = DB_; 5519 DL = &F.getParent()->getDataLayout(); 5520 5521 Stores.clear(); 5522 GEPs.clear(); 5523 bool Changed = false; 5524 5525 // If the target claims to have no vector registers don't attempt 5526 // vectorization. 5527 if (!TTI->getNumberOfRegisters(TTI->getRegisterClassForType(true))) 5528 return false; 5529 5530 // Don't vectorize when the attribute NoImplicitFloat is used. 5531 if (F.hasFnAttribute(Attribute::NoImplicitFloat)) 5532 return false; 5533 5534 LLVM_DEBUG(dbgs() << "SLP: Analyzing blocks in " << F.getName() << ".\n"); 5535 5536 // Use the bottom up slp vectorizer to construct chains that start with 5537 // store instructions. 5538 BoUpSLP R(&F, SE, TTI, TLI, AA, LI, DT, AC, DB, DL, ORE_); 5539 5540 // A general note: the vectorizer must use BoUpSLP::eraseInstruction() to 5541 // delete instructions. 5542 5543 // Scan the blocks in the function in post order. 5544 for (auto BB : post_order(&F.getEntryBlock())) { 5545 collectSeedInstructions(BB); 5546 5547 // Vectorize trees that end at stores. 5548 if (!Stores.empty()) { 5549 LLVM_DEBUG(dbgs() << "SLP: Found stores for " << Stores.size() 5550 << " underlying objects.\n"); 5551 Changed |= vectorizeStoreChains(R); 5552 } 5553 5554 // Vectorize trees that end at reductions. 5555 Changed |= vectorizeChainsInBlock(BB, R); 5556 5557 // Vectorize the index computations of getelementptr instructions. This 5558 // is primarily intended to catch gather-like idioms ending at 5559 // non-consecutive loads. 5560 if (!GEPs.empty()) { 5561 LLVM_DEBUG(dbgs() << "SLP: Found GEPs for " << GEPs.size() 5562 << " underlying objects.\n"); 5563 Changed |= vectorizeGEPIndices(BB, R); 5564 } 5565 } 5566 5567 if (Changed) { 5568 R.optimizeGatherSequence(); 5569 LLVM_DEBUG(dbgs() << "SLP: vectorized \"" << F.getName() << "\"\n"); 5570 LLVM_DEBUG(verifyFunction(F)); 5571 } 5572 return Changed; 5573 } 5574 5575 bool SLPVectorizerPass::vectorizeStoreChain(ArrayRef<Value *> Chain, BoUpSLP &R, 5576 unsigned VecRegSize) { 5577 const unsigned ChainLen = Chain.size(); 5578 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " << ChainLen 5579 << "\n"); 5580 const unsigned Sz = R.getVectorElementSize(Chain[0]); 5581 const unsigned VF = VecRegSize / Sz; 5582 5583 if (!isPowerOf2_32(Sz) || VF < 2) 5584 return false; 5585 5586 bool Changed = false; 5587 // Look for profitable vectorizable trees at all offsets, starting at zero. 5588 for (unsigned i = 0, e = ChainLen; i + VF <= e; ++i) { 5589 5590 ArrayRef<Value *> Operands = Chain.slice(i, VF); 5591 // Check that a previous iteration of this loop did not delete the Value. 5592 if (llvm::any_of(Operands, [&R](Value *V) { 5593 auto *I = dyn_cast<Instruction>(V); 5594 return I && R.isDeleted(I); 5595 })) 5596 continue; 5597 5598 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << VF << " stores at offset " << i 5599 << "\n"); 5600 5601 R.buildTree(Operands); 5602 if (R.isTreeTinyAndNotFullyVectorizable()) 5603 continue; 5604 5605 R.computeMinimumValueSizes(); 5606 5607 int Cost = R.getTreeCost(); 5608 5609 LLVM_DEBUG(dbgs() << "SLP: Found cost=" << Cost << " for VF=" << VF 5610 << "\n"); 5611 if (Cost < -SLPCostThreshold) { 5612 LLVM_DEBUG(dbgs() << "SLP: Decided to vectorize cost=" << Cost << "\n"); 5613 5614 using namespace ore; 5615 5616 R.getORE()->emit(OptimizationRemark(SV_NAME, "StoresVectorized", 5617 cast<StoreInst>(Chain[i])) 5618 << "Stores SLP vectorized with cost " << NV("Cost", Cost) 5619 << " and with tree size " 5620 << NV("TreeSize", R.getTreeSize())); 5621 5622 R.vectorizeTree(); 5623 5624 // Move to the next bundle. 5625 i += VF - 1; 5626 Changed = true; 5627 } 5628 } 5629 5630 return Changed; 5631 } 5632 5633 bool SLPVectorizerPass::vectorizeStores(ArrayRef<StoreInst *> Stores, 5634 BoUpSLP &R) { 5635 SetVector<StoreInst *> Heads; 5636 SmallDenseSet<StoreInst *> Tails; 5637 SmallDenseMap<StoreInst *, StoreInst *> ConsecutiveChain; 5638 5639 // We may run into multiple chains that merge into a single chain. We mark the 5640 // stores that we vectorized so that we don't visit the same store twice. 5641 BoUpSLP::ValueSet VectorizedStores; 5642 bool Changed = false; 5643 5644 auto &&FindConsecutiveAccess = 5645 [this, &Stores, &Heads, &Tails, &ConsecutiveChain] (int K, int Idx) { 5646 if (!isConsecutiveAccess(Stores[K], Stores[Idx], *DL, *SE)) 5647 return false; 5648 5649 Tails.insert(Stores[Idx]); 5650 Heads.insert(Stores[K]); 5651 ConsecutiveChain[Stores[K]] = Stores[Idx]; 5652 return true; 5653 }; 5654 5655 // Do a quadratic search on all of the given stores in reverse order and find 5656 // all of the pairs of stores that follow each other. 5657 int E = Stores.size(); 5658 for (int Idx = E - 1; Idx >= 0; --Idx) { 5659 // If a store has multiple consecutive store candidates, search according 5660 // to the sequence: Idx-1, Idx+1, Idx-2, Idx+2, ... 5661 // This is because usually pairing with immediate succeeding or preceding 5662 // candidate create the best chance to find slp vectorization opportunity. 5663 for (int Offset = 1, F = std::max(E - Idx, Idx + 1); Offset < F; ++Offset) 5664 if ((Idx >= Offset && FindConsecutiveAccess(Idx - Offset, Idx)) || 5665 (Idx + Offset < E && FindConsecutiveAccess(Idx + Offset, Idx))) 5666 break; 5667 } 5668 5669 // For stores that start but don't end a link in the chain: 5670 for (auto *SI : llvm::reverse(Heads)) { 5671 if (Tails.count(SI)) 5672 continue; 5673 5674 // We found a store instr that starts a chain. Now follow the chain and try 5675 // to vectorize it. 5676 BoUpSLP::ValueList Operands; 5677 StoreInst *I = SI; 5678 // Collect the chain into a list. 5679 while ((Tails.count(I) || Heads.count(I)) && !VectorizedStores.count(I)) { 5680 Operands.push_back(I); 5681 // Move to the next value in the chain. 5682 I = ConsecutiveChain[I]; 5683 } 5684 5685 // FIXME: Is division-by-2 the correct step? Should we assert that the 5686 // register size is a power-of-2? 5687 for (unsigned Size = R.getMaxVecRegSize(); Size >= R.getMinVecRegSize(); 5688 Size /= 2) { 5689 if (vectorizeStoreChain(Operands, R, Size)) { 5690 // Mark the vectorized stores so that we don't vectorize them again. 5691 VectorizedStores.insert(Operands.begin(), Operands.end()); 5692 Changed = true; 5693 break; 5694 } 5695 } 5696 } 5697 5698 return Changed; 5699 } 5700 5701 void SLPVectorizerPass::collectSeedInstructions(BasicBlock *BB) { 5702 // Initialize the collections. We will make a single pass over the block. 5703 Stores.clear(); 5704 GEPs.clear(); 5705 5706 // Visit the store and getelementptr instructions in BB and organize them in 5707 // Stores and GEPs according to the underlying objects of their pointer 5708 // operands. 5709 for (Instruction &I : *BB) { 5710 // Ignore store instructions that are volatile or have a pointer operand 5711 // that doesn't point to a scalar type. 5712 if (auto *SI = dyn_cast<StoreInst>(&I)) { 5713 if (!SI->isSimple()) 5714 continue; 5715 if (!isValidElementType(SI->getValueOperand()->getType())) 5716 continue; 5717 Stores[GetUnderlyingObject(SI->getPointerOperand(), *DL)].push_back(SI); 5718 } 5719 5720 // Ignore getelementptr instructions that have more than one index, a 5721 // constant index, or a pointer operand that doesn't point to a scalar 5722 // type. 5723 else if (auto *GEP = dyn_cast<GetElementPtrInst>(&I)) { 5724 auto Idx = GEP->idx_begin()->get(); 5725 if (GEP->getNumIndices() > 1 || isa<Constant>(Idx)) 5726 continue; 5727 if (!isValidElementType(Idx->getType())) 5728 continue; 5729 if (GEP->getType()->isVectorTy()) 5730 continue; 5731 GEPs[GEP->getPointerOperand()].push_back(GEP); 5732 } 5733 } 5734 } 5735 5736 bool SLPVectorizerPass::tryToVectorizePair(Value *A, Value *B, BoUpSLP &R) { 5737 if (!A || !B) 5738 return false; 5739 Value *VL[] = { A, B }; 5740 return tryToVectorizeList(VL, R, /*UserCost=*/0, true); 5741 } 5742 5743 bool SLPVectorizerPass::tryToVectorizeList(ArrayRef<Value *> VL, BoUpSLP &R, 5744 int UserCost, bool AllowReorder) { 5745 if (VL.size() < 2) 5746 return false; 5747 5748 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize a list of length = " 5749 << VL.size() << ".\n"); 5750 5751 // Check that all of the parts are scalar instructions of the same type, 5752 // we permit an alternate opcode via InstructionsState. 5753 InstructionsState S = getSameOpcode(VL); 5754 if (!S.getOpcode()) 5755 return false; 5756 5757 Instruction *I0 = cast<Instruction>(S.OpValue); 5758 unsigned Sz = R.getVectorElementSize(I0); 5759 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / Sz); 5760 unsigned MaxVF = std::max<unsigned>(PowerOf2Floor(VL.size()), MinVF); 5761 if (MaxVF < 2) { 5762 R.getORE()->emit([&]() { 5763 return OptimizationRemarkMissed(SV_NAME, "SmallVF", I0) 5764 << "Cannot SLP vectorize list: vectorization factor " 5765 << "less than 2 is not supported"; 5766 }); 5767 return false; 5768 } 5769 5770 for (Value *V : VL) { 5771 Type *Ty = V->getType(); 5772 if (!isValidElementType(Ty)) { 5773 // NOTE: the following will give user internal llvm type name, which may 5774 // not be useful. 5775 R.getORE()->emit([&]() { 5776 std::string type_str; 5777 llvm::raw_string_ostream rso(type_str); 5778 Ty->print(rso); 5779 return OptimizationRemarkMissed(SV_NAME, "UnsupportedType", I0) 5780 << "Cannot SLP vectorize list: type " 5781 << rso.str() + " is unsupported by vectorizer"; 5782 }); 5783 return false; 5784 } 5785 } 5786 5787 bool Changed = false; 5788 bool CandidateFound = false; 5789 int MinCost = SLPCostThreshold; 5790 5791 unsigned NextInst = 0, MaxInst = VL.size(); 5792 for (unsigned VF = MaxVF; NextInst + 1 < MaxInst && VF >= MinVF; VF /= 2) { 5793 // No actual vectorization should happen, if number of parts is the same as 5794 // provided vectorization factor (i.e. the scalar type is used for vector 5795 // code during codegen). 5796 auto *VecTy = VectorType::get(VL[0]->getType(), VF); 5797 if (TTI->getNumberOfParts(VecTy) == VF) 5798 continue; 5799 for (unsigned I = NextInst; I < MaxInst; ++I) { 5800 unsigned OpsWidth = 0; 5801 5802 if (I + VF > MaxInst) 5803 OpsWidth = MaxInst - I; 5804 else 5805 OpsWidth = VF; 5806 5807 if (!isPowerOf2_32(OpsWidth) || OpsWidth < 2) 5808 break; 5809 5810 ArrayRef<Value *> Ops = VL.slice(I, OpsWidth); 5811 // Check that a previous iteration of this loop did not delete the Value. 5812 if (llvm::any_of(Ops, [&R](Value *V) { 5813 auto *I = dyn_cast<Instruction>(V); 5814 return I && R.isDeleted(I); 5815 })) 5816 continue; 5817 5818 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << OpsWidth << " operations " 5819 << "\n"); 5820 5821 R.buildTree(Ops); 5822 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 5823 // TODO: check if we can allow reordering for more cases. 5824 if (AllowReorder && Order) { 5825 // TODO: reorder tree nodes without tree rebuilding. 5826 // Conceptually, there is nothing actually preventing us from trying to 5827 // reorder a larger list. In fact, we do exactly this when vectorizing 5828 // reductions. However, at this point, we only expect to get here when 5829 // there are exactly two operations. 5830 assert(Ops.size() == 2); 5831 Value *ReorderedOps[] = {Ops[1], Ops[0]}; 5832 R.buildTree(ReorderedOps, None); 5833 } 5834 if (R.isTreeTinyAndNotFullyVectorizable()) 5835 continue; 5836 5837 R.computeMinimumValueSizes(); 5838 int Cost = R.getTreeCost() - UserCost; 5839 CandidateFound = true; 5840 MinCost = std::min(MinCost, Cost); 5841 5842 if (Cost < -SLPCostThreshold) { 5843 LLVM_DEBUG(dbgs() << "SLP: Vectorizing list at cost:" << Cost << ".\n"); 5844 R.getORE()->emit(OptimizationRemark(SV_NAME, "VectorizedList", 5845 cast<Instruction>(Ops[0])) 5846 << "SLP vectorized with cost " << ore::NV("Cost", Cost) 5847 << " and with tree size " 5848 << ore::NV("TreeSize", R.getTreeSize())); 5849 5850 R.vectorizeTree(); 5851 // Move to the next bundle. 5852 I += VF - 1; 5853 NextInst = I + 1; 5854 Changed = true; 5855 } 5856 } 5857 } 5858 5859 if (!Changed && CandidateFound) { 5860 R.getORE()->emit([&]() { 5861 return OptimizationRemarkMissed(SV_NAME, "NotBeneficial", I0) 5862 << "List vectorization was possible but not beneficial with cost " 5863 << ore::NV("Cost", MinCost) << " >= " 5864 << ore::NV("Treshold", -SLPCostThreshold); 5865 }); 5866 } else if (!Changed) { 5867 R.getORE()->emit([&]() { 5868 return OptimizationRemarkMissed(SV_NAME, "NotPossible", I0) 5869 << "Cannot SLP vectorize list: vectorization was impossible" 5870 << " with available vectorization factors"; 5871 }); 5872 } 5873 return Changed; 5874 } 5875 5876 bool SLPVectorizerPass::tryToVectorize(Instruction *I, BoUpSLP &R) { 5877 if (!I) 5878 return false; 5879 5880 if (!isa<BinaryOperator>(I) && !isa<CmpInst>(I)) 5881 return false; 5882 5883 Value *P = I->getParent(); 5884 5885 // Vectorize in current basic block only. 5886 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 5887 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 5888 if (!Op0 || !Op1 || Op0->getParent() != P || Op1->getParent() != P) 5889 return false; 5890 5891 // Try to vectorize V. 5892 if (tryToVectorizePair(Op0, Op1, R)) 5893 return true; 5894 5895 auto *A = dyn_cast<BinaryOperator>(Op0); 5896 auto *B = dyn_cast<BinaryOperator>(Op1); 5897 // Try to skip B. 5898 if (B && B->hasOneUse()) { 5899 auto *B0 = dyn_cast<BinaryOperator>(B->getOperand(0)); 5900 auto *B1 = dyn_cast<BinaryOperator>(B->getOperand(1)); 5901 if (B0 && B0->getParent() == P && tryToVectorizePair(A, B0, R)) 5902 return true; 5903 if (B1 && B1->getParent() == P && tryToVectorizePair(A, B1, R)) 5904 return true; 5905 } 5906 5907 // Try to skip A. 5908 if (A && A->hasOneUse()) { 5909 auto *A0 = dyn_cast<BinaryOperator>(A->getOperand(0)); 5910 auto *A1 = dyn_cast<BinaryOperator>(A->getOperand(1)); 5911 if (A0 && A0->getParent() == P && tryToVectorizePair(A0, B, R)) 5912 return true; 5913 if (A1 && A1->getParent() == P && tryToVectorizePair(A1, B, R)) 5914 return true; 5915 } 5916 return false; 5917 } 5918 5919 /// Generate a shuffle mask to be used in a reduction tree. 5920 /// 5921 /// \param VecLen The length of the vector to be reduced. 5922 /// \param NumEltsToRdx The number of elements that should be reduced in the 5923 /// vector. 5924 /// \param IsPairwise Whether the reduction is a pairwise or splitting 5925 /// reduction. A pairwise reduction will generate a mask of 5926 /// <0,2,...> or <1,3,..> while a splitting reduction will generate 5927 /// <2,3, undef,undef> for a vector of 4 and NumElts = 2. 5928 /// \param IsLeft True will generate a mask of even elements, odd otherwise. 5929 static Value *createRdxShuffleMask(unsigned VecLen, unsigned NumEltsToRdx, 5930 bool IsPairwise, bool IsLeft, 5931 IRBuilder<> &Builder) { 5932 assert((IsPairwise || !IsLeft) && "Don't support a <0,1,undef,...> mask"); 5933 5934 SmallVector<Constant *, 32> ShuffleMask( 5935 VecLen, UndefValue::get(Builder.getInt32Ty())); 5936 5937 if (IsPairwise) 5938 // Build a mask of 0, 2, ... (left) or 1, 3, ... (right). 5939 for (unsigned i = 0; i != NumEltsToRdx; ++i) 5940 ShuffleMask[i] = Builder.getInt32(2 * i + !IsLeft); 5941 else 5942 // Move the upper half of the vector to the lower half. 5943 for (unsigned i = 0; i != NumEltsToRdx; ++i) 5944 ShuffleMask[i] = Builder.getInt32(NumEltsToRdx + i); 5945 5946 return ConstantVector::get(ShuffleMask); 5947 } 5948 5949 namespace { 5950 5951 /// Model horizontal reductions. 5952 /// 5953 /// A horizontal reduction is a tree of reduction operations (currently add and 5954 /// fadd) that has operations that can be put into a vector as its leaf. 5955 /// For example, this tree: 5956 /// 5957 /// mul mul mul mul 5958 /// \ / \ / 5959 /// + + 5960 /// \ / 5961 /// + 5962 /// This tree has "mul" as its reduced values and "+" as its reduction 5963 /// operations. A reduction might be feeding into a store or a binary operation 5964 /// feeding a phi. 5965 /// ... 5966 /// \ / 5967 /// + 5968 /// | 5969 /// phi += 5970 /// 5971 /// Or: 5972 /// ... 5973 /// \ / 5974 /// + 5975 /// | 5976 /// *p = 5977 /// 5978 class HorizontalReduction { 5979 using ReductionOpsType = SmallVector<Value *, 16>; 5980 using ReductionOpsListType = SmallVector<ReductionOpsType, 2>; 5981 ReductionOpsListType ReductionOps; 5982 SmallVector<Value *, 32> ReducedVals; 5983 // Use map vector to make stable output. 5984 MapVector<Instruction *, Value *> ExtraArgs; 5985 5986 /// Kind of the reduction data. 5987 enum ReductionKind { 5988 RK_None, /// Not a reduction. 5989 RK_Arithmetic, /// Binary reduction data. 5990 RK_Min, /// Minimum reduction data. 5991 RK_UMin, /// Unsigned minimum reduction data. 5992 RK_Max, /// Maximum reduction data. 5993 RK_UMax, /// Unsigned maximum reduction data. 5994 }; 5995 5996 /// Contains info about operation, like its opcode, left and right operands. 5997 class OperationData { 5998 /// Opcode of the instruction. 5999 unsigned Opcode = 0; 6000 6001 /// Left operand of the reduction operation. 6002 Value *LHS = nullptr; 6003 6004 /// Right operand of the reduction operation. 6005 Value *RHS = nullptr; 6006 6007 /// Kind of the reduction operation. 6008 ReductionKind Kind = RK_None; 6009 6010 /// True if float point min/max reduction has no NaNs. 6011 bool NoNaN = false; 6012 6013 /// Checks if the reduction operation can be vectorized. 6014 bool isVectorizable() const { 6015 return LHS && RHS && 6016 // We currently only support add/mul/logical && min/max reductions. 6017 ((Kind == RK_Arithmetic && 6018 (Opcode == Instruction::Add || Opcode == Instruction::FAdd || 6019 Opcode == Instruction::Mul || Opcode == Instruction::FMul || 6020 Opcode == Instruction::And || Opcode == Instruction::Or || 6021 Opcode == Instruction::Xor)) || 6022 ((Opcode == Instruction::ICmp || Opcode == Instruction::FCmp) && 6023 (Kind == RK_Min || Kind == RK_Max)) || 6024 (Opcode == Instruction::ICmp && 6025 (Kind == RK_UMin || Kind == RK_UMax))); 6026 } 6027 6028 /// Creates reduction operation with the current opcode. 6029 Value *createOp(IRBuilder<> &Builder, const Twine &Name) const { 6030 assert(isVectorizable() && 6031 "Expected add|fadd or min/max reduction operation."); 6032 Value *Cmp = nullptr; 6033 switch (Kind) { 6034 case RK_Arithmetic: 6035 return Builder.CreateBinOp((Instruction::BinaryOps)Opcode, LHS, RHS, 6036 Name); 6037 case RK_Min: 6038 Cmp = Opcode == Instruction::ICmp ? Builder.CreateICmpSLT(LHS, RHS) 6039 : Builder.CreateFCmpOLT(LHS, RHS); 6040 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6041 case RK_Max: 6042 Cmp = Opcode == Instruction::ICmp ? Builder.CreateICmpSGT(LHS, RHS) 6043 : Builder.CreateFCmpOGT(LHS, RHS); 6044 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6045 case RK_UMin: 6046 assert(Opcode == Instruction::ICmp && "Expected integer types."); 6047 Cmp = Builder.CreateICmpULT(LHS, RHS); 6048 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6049 case RK_UMax: 6050 assert(Opcode == Instruction::ICmp && "Expected integer types."); 6051 Cmp = Builder.CreateICmpUGT(LHS, RHS); 6052 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6053 case RK_None: 6054 break; 6055 } 6056 llvm_unreachable("Unknown reduction operation."); 6057 } 6058 6059 public: 6060 explicit OperationData() = default; 6061 6062 /// Construction for reduced values. They are identified by opcode only and 6063 /// don't have associated LHS/RHS values. 6064 explicit OperationData(Value *V) { 6065 if (auto *I = dyn_cast<Instruction>(V)) 6066 Opcode = I->getOpcode(); 6067 } 6068 6069 /// Constructor for reduction operations with opcode and its left and 6070 /// right operands. 6071 OperationData(unsigned Opcode, Value *LHS, Value *RHS, ReductionKind Kind, 6072 bool NoNaN = false) 6073 : Opcode(Opcode), LHS(LHS), RHS(RHS), Kind(Kind), NoNaN(NoNaN) { 6074 assert(Kind != RK_None && "One of the reduction operations is expected."); 6075 } 6076 6077 explicit operator bool() const { return Opcode; } 6078 6079 /// Get the index of the first operand. 6080 unsigned getFirstOperandIndex() const { 6081 assert(!!*this && "The opcode is not set."); 6082 switch (Kind) { 6083 case RK_Min: 6084 case RK_UMin: 6085 case RK_Max: 6086 case RK_UMax: 6087 return 1; 6088 case RK_Arithmetic: 6089 case RK_None: 6090 break; 6091 } 6092 return 0; 6093 } 6094 6095 /// Total number of operands in the reduction operation. 6096 unsigned getNumberOfOperands() const { 6097 assert(Kind != RK_None && !!*this && LHS && RHS && 6098 "Expected reduction operation."); 6099 switch (Kind) { 6100 case RK_Arithmetic: 6101 return 2; 6102 case RK_Min: 6103 case RK_UMin: 6104 case RK_Max: 6105 case RK_UMax: 6106 return 3; 6107 case RK_None: 6108 break; 6109 } 6110 llvm_unreachable("Reduction kind is not set"); 6111 } 6112 6113 /// Checks if the operation has the same parent as \p P. 6114 bool hasSameParent(Instruction *I, Value *P, bool IsRedOp) const { 6115 assert(Kind != RK_None && !!*this && LHS && RHS && 6116 "Expected reduction operation."); 6117 if (!IsRedOp) 6118 return I->getParent() == P; 6119 switch (Kind) { 6120 case RK_Arithmetic: 6121 // Arithmetic reduction operation must be used once only. 6122 return I->getParent() == P; 6123 case RK_Min: 6124 case RK_UMin: 6125 case RK_Max: 6126 case RK_UMax: { 6127 // SelectInst must be used twice while the condition op must have single 6128 // use only. 6129 auto *Cmp = cast<Instruction>(cast<SelectInst>(I)->getCondition()); 6130 return I->getParent() == P && Cmp && Cmp->getParent() == P; 6131 } 6132 case RK_None: 6133 break; 6134 } 6135 llvm_unreachable("Reduction kind is not set"); 6136 } 6137 /// Expected number of uses for reduction operations/reduced values. 6138 bool hasRequiredNumberOfUses(Instruction *I, bool IsReductionOp) const { 6139 assert(Kind != RK_None && !!*this && LHS && RHS && 6140 "Expected reduction operation."); 6141 switch (Kind) { 6142 case RK_Arithmetic: 6143 return I->hasOneUse(); 6144 case RK_Min: 6145 case RK_UMin: 6146 case RK_Max: 6147 case RK_UMax: 6148 return I->hasNUses(2) && 6149 (!IsReductionOp || 6150 cast<SelectInst>(I)->getCondition()->hasOneUse()); 6151 case RK_None: 6152 break; 6153 } 6154 llvm_unreachable("Reduction kind is not set"); 6155 } 6156 6157 /// Initializes the list of reduction operations. 6158 void initReductionOps(ReductionOpsListType &ReductionOps) { 6159 assert(Kind != RK_None && !!*this && LHS && RHS && 6160 "Expected reduction operation."); 6161 switch (Kind) { 6162 case RK_Arithmetic: 6163 ReductionOps.assign(1, ReductionOpsType()); 6164 break; 6165 case RK_Min: 6166 case RK_UMin: 6167 case RK_Max: 6168 case RK_UMax: 6169 ReductionOps.assign(2, ReductionOpsType()); 6170 break; 6171 case RK_None: 6172 llvm_unreachable("Reduction kind is not set"); 6173 } 6174 } 6175 /// Add all reduction operations for the reduction instruction \p I. 6176 void addReductionOps(Instruction *I, ReductionOpsListType &ReductionOps) { 6177 assert(Kind != RK_None && !!*this && LHS && RHS && 6178 "Expected reduction operation."); 6179 switch (Kind) { 6180 case RK_Arithmetic: 6181 ReductionOps[0].emplace_back(I); 6182 break; 6183 case RK_Min: 6184 case RK_UMin: 6185 case RK_Max: 6186 case RK_UMax: 6187 ReductionOps[0].emplace_back(cast<SelectInst>(I)->getCondition()); 6188 ReductionOps[1].emplace_back(I); 6189 break; 6190 case RK_None: 6191 llvm_unreachable("Reduction kind is not set"); 6192 } 6193 } 6194 6195 /// Checks if instruction is associative and can be vectorized. 6196 bool isAssociative(Instruction *I) const { 6197 assert(Kind != RK_None && *this && LHS && RHS && 6198 "Expected reduction operation."); 6199 switch (Kind) { 6200 case RK_Arithmetic: 6201 return I->isAssociative(); 6202 case RK_Min: 6203 case RK_Max: 6204 return Opcode == Instruction::ICmp || 6205 cast<Instruction>(I->getOperand(0))->isFast(); 6206 case RK_UMin: 6207 case RK_UMax: 6208 assert(Opcode == Instruction::ICmp && 6209 "Only integer compare operation is expected."); 6210 return true; 6211 case RK_None: 6212 break; 6213 } 6214 llvm_unreachable("Reduction kind is not set"); 6215 } 6216 6217 /// Checks if the reduction operation can be vectorized. 6218 bool isVectorizable(Instruction *I) const { 6219 return isVectorizable() && isAssociative(I); 6220 } 6221 6222 /// Checks if two operation data are both a reduction op or both a reduced 6223 /// value. 6224 bool operator==(const OperationData &OD) { 6225 assert(((Kind != OD.Kind) || ((!LHS == !OD.LHS) && (!RHS == !OD.RHS))) && 6226 "One of the comparing operations is incorrect."); 6227 return this == &OD || (Kind == OD.Kind && Opcode == OD.Opcode); 6228 } 6229 bool operator!=(const OperationData &OD) { return !(*this == OD); } 6230 void clear() { 6231 Opcode = 0; 6232 LHS = nullptr; 6233 RHS = nullptr; 6234 Kind = RK_None; 6235 NoNaN = false; 6236 } 6237 6238 /// Get the opcode of the reduction operation. 6239 unsigned getOpcode() const { 6240 assert(isVectorizable() && "Expected vectorizable operation."); 6241 return Opcode; 6242 } 6243 6244 /// Get kind of reduction data. 6245 ReductionKind getKind() const { return Kind; } 6246 Value *getLHS() const { return LHS; } 6247 Value *getRHS() const { return RHS; } 6248 Type *getConditionType() const { 6249 switch (Kind) { 6250 case RK_Arithmetic: 6251 return nullptr; 6252 case RK_Min: 6253 case RK_Max: 6254 case RK_UMin: 6255 case RK_UMax: 6256 return CmpInst::makeCmpResultType(LHS->getType()); 6257 case RK_None: 6258 break; 6259 } 6260 llvm_unreachable("Reduction kind is not set"); 6261 } 6262 6263 /// Creates reduction operation with the current opcode with the IR flags 6264 /// from \p ReductionOps. 6265 Value *createOp(IRBuilder<> &Builder, const Twine &Name, 6266 const ReductionOpsListType &ReductionOps) const { 6267 assert(isVectorizable() && 6268 "Expected add|fadd or min/max reduction operation."); 6269 auto *Op = createOp(Builder, Name); 6270 switch (Kind) { 6271 case RK_Arithmetic: 6272 propagateIRFlags(Op, ReductionOps[0]); 6273 return Op; 6274 case RK_Min: 6275 case RK_Max: 6276 case RK_UMin: 6277 case RK_UMax: 6278 if (auto *SI = dyn_cast<SelectInst>(Op)) 6279 propagateIRFlags(SI->getCondition(), ReductionOps[0]); 6280 propagateIRFlags(Op, ReductionOps[1]); 6281 return Op; 6282 case RK_None: 6283 break; 6284 } 6285 llvm_unreachable("Unknown reduction operation."); 6286 } 6287 /// Creates reduction operation with the current opcode with the IR flags 6288 /// from \p I. 6289 Value *createOp(IRBuilder<> &Builder, const Twine &Name, 6290 Instruction *I) const { 6291 assert(isVectorizable() && 6292 "Expected add|fadd or min/max reduction operation."); 6293 auto *Op = createOp(Builder, Name); 6294 switch (Kind) { 6295 case RK_Arithmetic: 6296 propagateIRFlags(Op, I); 6297 return Op; 6298 case RK_Min: 6299 case RK_Max: 6300 case RK_UMin: 6301 case RK_UMax: 6302 if (auto *SI = dyn_cast<SelectInst>(Op)) { 6303 propagateIRFlags(SI->getCondition(), 6304 cast<SelectInst>(I)->getCondition()); 6305 } 6306 propagateIRFlags(Op, I); 6307 return Op; 6308 case RK_None: 6309 break; 6310 } 6311 llvm_unreachable("Unknown reduction operation."); 6312 } 6313 6314 TargetTransformInfo::ReductionFlags getFlags() const { 6315 TargetTransformInfo::ReductionFlags Flags; 6316 Flags.NoNaN = NoNaN; 6317 switch (Kind) { 6318 case RK_Arithmetic: 6319 break; 6320 case RK_Min: 6321 Flags.IsSigned = Opcode == Instruction::ICmp; 6322 Flags.IsMaxOp = false; 6323 break; 6324 case RK_Max: 6325 Flags.IsSigned = Opcode == Instruction::ICmp; 6326 Flags.IsMaxOp = true; 6327 break; 6328 case RK_UMin: 6329 Flags.IsSigned = false; 6330 Flags.IsMaxOp = false; 6331 break; 6332 case RK_UMax: 6333 Flags.IsSigned = false; 6334 Flags.IsMaxOp = true; 6335 break; 6336 case RK_None: 6337 llvm_unreachable("Reduction kind is not set"); 6338 } 6339 return Flags; 6340 } 6341 }; 6342 6343 WeakTrackingVH ReductionRoot; 6344 6345 /// The operation data of the reduction operation. 6346 OperationData ReductionData; 6347 6348 /// The operation data of the values we perform a reduction on. 6349 OperationData ReducedValueData; 6350 6351 /// Should we model this reduction as a pairwise reduction tree or a tree that 6352 /// splits the vector in halves and adds those halves. 6353 bool IsPairwiseReduction = false; 6354 6355 /// Checks if the ParentStackElem.first should be marked as a reduction 6356 /// operation with an extra argument or as extra argument itself. 6357 void markExtraArg(std::pair<Instruction *, unsigned> &ParentStackElem, 6358 Value *ExtraArg) { 6359 if (ExtraArgs.count(ParentStackElem.first)) { 6360 ExtraArgs[ParentStackElem.first] = nullptr; 6361 // We ran into something like: 6362 // ParentStackElem.first = ExtraArgs[ParentStackElem.first] + ExtraArg. 6363 // The whole ParentStackElem.first should be considered as an extra value 6364 // in this case. 6365 // Do not perform analysis of remaining operands of ParentStackElem.first 6366 // instruction, this whole instruction is an extra argument. 6367 ParentStackElem.second = ParentStackElem.first->getNumOperands(); 6368 } else { 6369 // We ran into something like: 6370 // ParentStackElem.first += ... + ExtraArg + ... 6371 ExtraArgs[ParentStackElem.first] = ExtraArg; 6372 } 6373 } 6374 6375 static OperationData getOperationData(Value *V) { 6376 if (!V) 6377 return OperationData(); 6378 6379 Value *LHS; 6380 Value *RHS; 6381 if (m_BinOp(m_Value(LHS), m_Value(RHS)).match(V)) { 6382 return OperationData(cast<BinaryOperator>(V)->getOpcode(), LHS, RHS, 6383 RK_Arithmetic); 6384 } 6385 if (auto *Select = dyn_cast<SelectInst>(V)) { 6386 // Look for a min/max pattern. 6387 if (m_UMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 6388 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMin); 6389 } else if (m_SMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 6390 return OperationData(Instruction::ICmp, LHS, RHS, RK_Min); 6391 } else if (m_OrdFMin(m_Value(LHS), m_Value(RHS)).match(Select) || 6392 m_UnordFMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 6393 return OperationData( 6394 Instruction::FCmp, LHS, RHS, RK_Min, 6395 cast<Instruction>(Select->getCondition())->hasNoNaNs()); 6396 } else if (m_UMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 6397 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMax); 6398 } else if (m_SMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 6399 return OperationData(Instruction::ICmp, LHS, RHS, RK_Max); 6400 } else if (m_OrdFMax(m_Value(LHS), m_Value(RHS)).match(Select) || 6401 m_UnordFMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 6402 return OperationData( 6403 Instruction::FCmp, LHS, RHS, RK_Max, 6404 cast<Instruction>(Select->getCondition())->hasNoNaNs()); 6405 } else { 6406 // Try harder: look for min/max pattern based on instructions producing 6407 // same values such as: select ((cmp Inst1, Inst2), Inst1, Inst2). 6408 // During the intermediate stages of SLP, it's very common to have 6409 // pattern like this (since optimizeGatherSequence is run only once 6410 // at the end): 6411 // %1 = extractelement <2 x i32> %a, i32 0 6412 // %2 = extractelement <2 x i32> %a, i32 1 6413 // %cond = icmp sgt i32 %1, %2 6414 // %3 = extractelement <2 x i32> %a, i32 0 6415 // %4 = extractelement <2 x i32> %a, i32 1 6416 // %select = select i1 %cond, i32 %3, i32 %4 6417 CmpInst::Predicate Pred; 6418 Instruction *L1; 6419 Instruction *L2; 6420 6421 LHS = Select->getTrueValue(); 6422 RHS = Select->getFalseValue(); 6423 Value *Cond = Select->getCondition(); 6424 6425 // TODO: Support inverse predicates. 6426 if (match(Cond, m_Cmp(Pred, m_Specific(LHS), m_Instruction(L2)))) { 6427 if (!isa<ExtractElementInst>(RHS) || 6428 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6429 return OperationData(V); 6430 } else if (match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Specific(RHS)))) { 6431 if (!isa<ExtractElementInst>(LHS) || 6432 !L1->isIdenticalTo(cast<Instruction>(LHS))) 6433 return OperationData(V); 6434 } else { 6435 if (!isa<ExtractElementInst>(LHS) || !isa<ExtractElementInst>(RHS)) 6436 return OperationData(V); 6437 if (!match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Instruction(L2))) || 6438 !L1->isIdenticalTo(cast<Instruction>(LHS)) || 6439 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6440 return OperationData(V); 6441 } 6442 switch (Pred) { 6443 default: 6444 return OperationData(V); 6445 6446 case CmpInst::ICMP_ULT: 6447 case CmpInst::ICMP_ULE: 6448 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMin); 6449 6450 case CmpInst::ICMP_SLT: 6451 case CmpInst::ICMP_SLE: 6452 return OperationData(Instruction::ICmp, LHS, RHS, RK_Min); 6453 6454 case CmpInst::FCMP_OLT: 6455 case CmpInst::FCMP_OLE: 6456 case CmpInst::FCMP_ULT: 6457 case CmpInst::FCMP_ULE: 6458 return OperationData(Instruction::FCmp, LHS, RHS, RK_Min, 6459 cast<Instruction>(Cond)->hasNoNaNs()); 6460 6461 case CmpInst::ICMP_UGT: 6462 case CmpInst::ICMP_UGE: 6463 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMax); 6464 6465 case CmpInst::ICMP_SGT: 6466 case CmpInst::ICMP_SGE: 6467 return OperationData(Instruction::ICmp, LHS, RHS, RK_Max); 6468 6469 case CmpInst::FCMP_OGT: 6470 case CmpInst::FCMP_OGE: 6471 case CmpInst::FCMP_UGT: 6472 case CmpInst::FCMP_UGE: 6473 return OperationData(Instruction::FCmp, LHS, RHS, RK_Max, 6474 cast<Instruction>(Cond)->hasNoNaNs()); 6475 } 6476 } 6477 } 6478 return OperationData(V); 6479 } 6480 6481 public: 6482 HorizontalReduction() = default; 6483 6484 /// Try to find a reduction tree. 6485 bool matchAssociativeReduction(PHINode *Phi, Instruction *B) { 6486 assert((!Phi || is_contained(Phi->operands(), B)) && 6487 "Thi phi needs to use the binary operator"); 6488 6489 ReductionData = getOperationData(B); 6490 6491 // We could have a initial reductions that is not an add. 6492 // r *= v1 + v2 + v3 + v4 6493 // In such a case start looking for a tree rooted in the first '+'. 6494 if (Phi) { 6495 if (ReductionData.getLHS() == Phi) { 6496 Phi = nullptr; 6497 B = dyn_cast<Instruction>(ReductionData.getRHS()); 6498 ReductionData = getOperationData(B); 6499 } else if (ReductionData.getRHS() == Phi) { 6500 Phi = nullptr; 6501 B = dyn_cast<Instruction>(ReductionData.getLHS()); 6502 ReductionData = getOperationData(B); 6503 } 6504 } 6505 6506 if (!ReductionData.isVectorizable(B)) 6507 return false; 6508 6509 Type *Ty = B->getType(); 6510 if (!isValidElementType(Ty)) 6511 return false; 6512 if (!Ty->isIntOrIntVectorTy() && !Ty->isFPOrFPVectorTy()) 6513 return false; 6514 6515 ReducedValueData.clear(); 6516 ReductionRoot = B; 6517 6518 // Post order traverse the reduction tree starting at B. We only handle true 6519 // trees containing only binary operators. 6520 SmallVector<std::pair<Instruction *, unsigned>, 32> Stack; 6521 Stack.push_back(std::make_pair(B, ReductionData.getFirstOperandIndex())); 6522 ReductionData.initReductionOps(ReductionOps); 6523 while (!Stack.empty()) { 6524 Instruction *TreeN = Stack.back().first; 6525 unsigned EdgeToVist = Stack.back().second++; 6526 OperationData OpData = getOperationData(TreeN); 6527 bool IsReducedValue = OpData != ReductionData; 6528 6529 // Postorder vist. 6530 if (IsReducedValue || EdgeToVist == OpData.getNumberOfOperands()) { 6531 if (IsReducedValue) 6532 ReducedVals.push_back(TreeN); 6533 else { 6534 auto I = ExtraArgs.find(TreeN); 6535 if (I != ExtraArgs.end() && !I->second) { 6536 // Check if TreeN is an extra argument of its parent operation. 6537 if (Stack.size() <= 1) { 6538 // TreeN can't be an extra argument as it is a root reduction 6539 // operation. 6540 return false; 6541 } 6542 // Yes, TreeN is an extra argument, do not add it to a list of 6543 // reduction operations. 6544 // Stack[Stack.size() - 2] always points to the parent operation. 6545 markExtraArg(Stack[Stack.size() - 2], TreeN); 6546 ExtraArgs.erase(TreeN); 6547 } else 6548 ReductionData.addReductionOps(TreeN, ReductionOps); 6549 } 6550 // Retract. 6551 Stack.pop_back(); 6552 continue; 6553 } 6554 6555 // Visit left or right. 6556 Value *NextV = TreeN->getOperand(EdgeToVist); 6557 if (NextV != Phi) { 6558 auto *I = dyn_cast<Instruction>(NextV); 6559 OpData = getOperationData(I); 6560 // Continue analysis if the next operand is a reduction operation or 6561 // (possibly) a reduced value. If the reduced value opcode is not set, 6562 // the first met operation != reduction operation is considered as the 6563 // reduced value class. 6564 if (I && (!ReducedValueData || OpData == ReducedValueData || 6565 OpData == ReductionData)) { 6566 const bool IsReductionOperation = OpData == ReductionData; 6567 // Only handle trees in the current basic block. 6568 if (!ReductionData.hasSameParent(I, B->getParent(), 6569 IsReductionOperation)) { 6570 // I is an extra argument for TreeN (its parent operation). 6571 markExtraArg(Stack.back(), I); 6572 continue; 6573 } 6574 6575 // Each tree node needs to have minimal number of users except for the 6576 // ultimate reduction. 6577 if (!ReductionData.hasRequiredNumberOfUses(I, 6578 OpData == ReductionData) && 6579 I != B) { 6580 // I is an extra argument for TreeN (its parent operation). 6581 markExtraArg(Stack.back(), I); 6582 continue; 6583 } 6584 6585 if (IsReductionOperation) { 6586 // We need to be able to reassociate the reduction operations. 6587 if (!OpData.isAssociative(I)) { 6588 // I is an extra argument for TreeN (its parent operation). 6589 markExtraArg(Stack.back(), I); 6590 continue; 6591 } 6592 } else if (ReducedValueData && 6593 ReducedValueData != OpData) { 6594 // Make sure that the opcodes of the operations that we are going to 6595 // reduce match. 6596 // I is an extra argument for TreeN (its parent operation). 6597 markExtraArg(Stack.back(), I); 6598 continue; 6599 } else if (!ReducedValueData) 6600 ReducedValueData = OpData; 6601 6602 Stack.push_back(std::make_pair(I, OpData.getFirstOperandIndex())); 6603 continue; 6604 } 6605 } 6606 // NextV is an extra argument for TreeN (its parent operation). 6607 markExtraArg(Stack.back(), NextV); 6608 } 6609 return true; 6610 } 6611 6612 /// Attempt to vectorize the tree found by 6613 /// matchAssociativeReduction. 6614 bool tryToReduce(BoUpSLP &V, TargetTransformInfo *TTI, bool Try2WayRdx) { 6615 if (ReducedVals.empty()) 6616 return false; 6617 6618 // If there is a sufficient number of reduction values, reduce 6619 // to a nearby power-of-2. Can safely generate oversized 6620 // vectors and rely on the backend to split them to legal sizes. 6621 unsigned NumReducedVals = ReducedVals.size(); 6622 if (Try2WayRdx && NumReducedVals != 2) 6623 return false; 6624 unsigned MinRdxVals = Try2WayRdx ? 2 : 4; 6625 if (NumReducedVals < MinRdxVals) 6626 return false; 6627 6628 unsigned ReduxWidth = PowerOf2Floor(NumReducedVals); 6629 unsigned MinRdxWidth = Log2_32(MinRdxVals); 6630 Value *VectorizedTree = nullptr; 6631 6632 // FIXME: Fast-math-flags should be set based on the instructions in the 6633 // reduction (not all of 'fast' are required). 6634 IRBuilder<> Builder(cast<Instruction>(ReductionRoot)); 6635 FastMathFlags Unsafe; 6636 Unsafe.setFast(); 6637 Builder.setFastMathFlags(Unsafe); 6638 unsigned i = 0; 6639 6640 BoUpSLP::ExtraValueToDebugLocsMap ExternallyUsedValues; 6641 // The same extra argument may be used several time, so log each attempt 6642 // to use it. 6643 for (auto &Pair : ExtraArgs) { 6644 assert(Pair.first && "DebugLoc must be set."); 6645 ExternallyUsedValues[Pair.second].push_back(Pair.first); 6646 } 6647 // The reduction root is used as the insertion point for new instructions, 6648 // so set it as externally used to prevent it from being deleted. 6649 ExternallyUsedValues[ReductionRoot]; 6650 SmallVector<Value *, 16> IgnoreList; 6651 for (auto &V : ReductionOps) 6652 IgnoreList.append(V.begin(), V.end()); 6653 while (i < NumReducedVals - ReduxWidth + 1 && ReduxWidth > MinRdxWidth) { 6654 auto VL = makeArrayRef(&ReducedVals[i], ReduxWidth); 6655 V.buildTree(VL, ExternallyUsedValues, IgnoreList); 6656 Optional<ArrayRef<unsigned>> Order = V.bestOrder(); 6657 // TODO: Handle orders of size less than number of elements in the vector. 6658 if (Order && Order->size() == VL.size()) { 6659 // TODO: reorder tree nodes without tree rebuilding. 6660 SmallVector<Value *, 4> ReorderedOps(VL.size()); 6661 llvm::transform(*Order, ReorderedOps.begin(), 6662 [VL](const unsigned Idx) { return VL[Idx]; }); 6663 V.buildTree(ReorderedOps, ExternallyUsedValues, IgnoreList); 6664 } 6665 if (V.isTreeTinyAndNotFullyVectorizable()) 6666 break; 6667 if (V.isLoadCombineReductionCandidate(ReductionData.getOpcode())) 6668 break; 6669 6670 V.computeMinimumValueSizes(); 6671 6672 // Estimate cost. 6673 int TreeCost = V.getTreeCost(); 6674 int ReductionCost = getReductionCost(TTI, ReducedVals[i], ReduxWidth); 6675 int Cost = TreeCost + ReductionCost; 6676 if (Cost >= -SLPCostThreshold) { 6677 V.getORE()->emit([&]() { 6678 return OptimizationRemarkMissed( 6679 SV_NAME, "HorSLPNotBeneficial", cast<Instruction>(VL[0])) 6680 << "Vectorizing horizontal reduction is possible" 6681 << "but not beneficial with cost " 6682 << ore::NV("Cost", Cost) << " and threshold " 6683 << ore::NV("Threshold", -SLPCostThreshold); 6684 }); 6685 break; 6686 } 6687 6688 LLVM_DEBUG(dbgs() << "SLP: Vectorizing horizontal reduction at cost:" 6689 << Cost << ". (HorRdx)\n"); 6690 V.getORE()->emit([&]() { 6691 return OptimizationRemark( 6692 SV_NAME, "VectorizedHorizontalReduction", cast<Instruction>(VL[0])) 6693 << "Vectorized horizontal reduction with cost " 6694 << ore::NV("Cost", Cost) << " and with tree size " 6695 << ore::NV("TreeSize", V.getTreeSize()); 6696 }); 6697 6698 // Vectorize a tree. 6699 DebugLoc Loc = cast<Instruction>(ReducedVals[i])->getDebugLoc(); 6700 Value *VectorizedRoot = V.vectorizeTree(ExternallyUsedValues); 6701 6702 // Emit a reduction. 6703 Builder.SetInsertPoint(cast<Instruction>(ReductionRoot)); 6704 Value *ReducedSubTree = 6705 emitReduction(VectorizedRoot, Builder, ReduxWidth, TTI); 6706 if (VectorizedTree) { 6707 Builder.SetCurrentDebugLocation(Loc); 6708 OperationData VectReductionData(ReductionData.getOpcode(), 6709 VectorizedTree, ReducedSubTree, 6710 ReductionData.getKind()); 6711 VectorizedTree = 6712 VectReductionData.createOp(Builder, "op.rdx", ReductionOps); 6713 } else 6714 VectorizedTree = ReducedSubTree; 6715 i += ReduxWidth; 6716 ReduxWidth = PowerOf2Floor(NumReducedVals - i); 6717 } 6718 6719 if (VectorizedTree) { 6720 // Finish the reduction. 6721 for (; i < NumReducedVals; ++i) { 6722 auto *I = cast<Instruction>(ReducedVals[i]); 6723 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 6724 OperationData VectReductionData(ReductionData.getOpcode(), 6725 VectorizedTree, I, 6726 ReductionData.getKind()); 6727 VectorizedTree = VectReductionData.createOp(Builder, "", ReductionOps); 6728 } 6729 for (auto &Pair : ExternallyUsedValues) { 6730 // Add each externally used value to the final reduction. 6731 for (auto *I : Pair.second) { 6732 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 6733 OperationData VectReductionData(ReductionData.getOpcode(), 6734 VectorizedTree, Pair.first, 6735 ReductionData.getKind()); 6736 VectorizedTree = VectReductionData.createOp(Builder, "op.extra", I); 6737 } 6738 } 6739 // Update users. 6740 ReductionRoot->replaceAllUsesWith(VectorizedTree); 6741 // Mark all scalar reduction ops for deletion, they are replaced by the 6742 // vector reductions. 6743 V.eraseInstructions(IgnoreList); 6744 } 6745 return VectorizedTree != nullptr; 6746 } 6747 6748 unsigned numReductionValues() const { 6749 return ReducedVals.size(); 6750 } 6751 6752 private: 6753 /// Calculate the cost of a reduction. 6754 int getReductionCost(TargetTransformInfo *TTI, Value *FirstReducedVal, 6755 unsigned ReduxWidth) { 6756 Type *ScalarTy = FirstReducedVal->getType(); 6757 Type *VecTy = VectorType::get(ScalarTy, ReduxWidth); 6758 6759 int PairwiseRdxCost; 6760 int SplittingRdxCost; 6761 switch (ReductionData.getKind()) { 6762 case RK_Arithmetic: 6763 PairwiseRdxCost = 6764 TTI->getArithmeticReductionCost(ReductionData.getOpcode(), VecTy, 6765 /*IsPairwiseForm=*/true); 6766 SplittingRdxCost = 6767 TTI->getArithmeticReductionCost(ReductionData.getOpcode(), VecTy, 6768 /*IsPairwiseForm=*/false); 6769 break; 6770 case RK_Min: 6771 case RK_Max: 6772 case RK_UMin: 6773 case RK_UMax: { 6774 Type *VecCondTy = CmpInst::makeCmpResultType(VecTy); 6775 bool IsUnsigned = ReductionData.getKind() == RK_UMin || 6776 ReductionData.getKind() == RK_UMax; 6777 PairwiseRdxCost = 6778 TTI->getMinMaxReductionCost(VecTy, VecCondTy, 6779 /*IsPairwiseForm=*/true, IsUnsigned); 6780 SplittingRdxCost = 6781 TTI->getMinMaxReductionCost(VecTy, VecCondTy, 6782 /*IsPairwiseForm=*/false, IsUnsigned); 6783 break; 6784 } 6785 case RK_None: 6786 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 6787 } 6788 6789 IsPairwiseReduction = PairwiseRdxCost < SplittingRdxCost; 6790 int VecReduxCost = IsPairwiseReduction ? PairwiseRdxCost : SplittingRdxCost; 6791 6792 int ScalarReduxCost = 0; 6793 switch (ReductionData.getKind()) { 6794 case RK_Arithmetic: 6795 ScalarReduxCost = 6796 TTI->getArithmeticInstrCost(ReductionData.getOpcode(), ScalarTy); 6797 break; 6798 case RK_Min: 6799 case RK_Max: 6800 case RK_UMin: 6801 case RK_UMax: 6802 ScalarReduxCost = 6803 TTI->getCmpSelInstrCost(ReductionData.getOpcode(), ScalarTy) + 6804 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 6805 CmpInst::makeCmpResultType(ScalarTy)); 6806 break; 6807 case RK_None: 6808 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 6809 } 6810 ScalarReduxCost *= (ReduxWidth - 1); 6811 6812 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << VecReduxCost - ScalarReduxCost 6813 << " for reduction that starts with " << *FirstReducedVal 6814 << " (It is a " 6815 << (IsPairwiseReduction ? "pairwise" : "splitting") 6816 << " reduction)\n"); 6817 6818 return VecReduxCost - ScalarReduxCost; 6819 } 6820 6821 /// Emit a horizontal reduction of the vectorized value. 6822 Value *emitReduction(Value *VectorizedValue, IRBuilder<> &Builder, 6823 unsigned ReduxWidth, const TargetTransformInfo *TTI) { 6824 assert(VectorizedValue && "Need to have a vectorized tree node"); 6825 assert(isPowerOf2_32(ReduxWidth) && 6826 "We only handle power-of-two reductions for now"); 6827 6828 if (!IsPairwiseReduction) { 6829 // FIXME: The builder should use an FMF guard. It should not be hard-coded 6830 // to 'fast'. 6831 assert(Builder.getFastMathFlags().isFast() && "Expected 'fast' FMF"); 6832 return createSimpleTargetReduction( 6833 Builder, TTI, ReductionData.getOpcode(), VectorizedValue, 6834 ReductionData.getFlags(), ReductionOps.back()); 6835 } 6836 6837 Value *TmpVec = VectorizedValue; 6838 for (unsigned i = ReduxWidth / 2; i != 0; i >>= 1) { 6839 Value *LeftMask = 6840 createRdxShuffleMask(ReduxWidth, i, true, true, Builder); 6841 Value *RightMask = 6842 createRdxShuffleMask(ReduxWidth, i, true, false, Builder); 6843 6844 Value *LeftShuf = Builder.CreateShuffleVector( 6845 TmpVec, UndefValue::get(TmpVec->getType()), LeftMask, "rdx.shuf.l"); 6846 Value *RightShuf = Builder.CreateShuffleVector( 6847 TmpVec, UndefValue::get(TmpVec->getType()), (RightMask), 6848 "rdx.shuf.r"); 6849 OperationData VectReductionData(ReductionData.getOpcode(), LeftShuf, 6850 RightShuf, ReductionData.getKind()); 6851 TmpVec = VectReductionData.createOp(Builder, "op.rdx", ReductionOps); 6852 } 6853 6854 // The result is in the first element of the vector. 6855 return Builder.CreateExtractElement(TmpVec, Builder.getInt32(0)); 6856 } 6857 }; 6858 6859 } // end anonymous namespace 6860 6861 /// Recognize construction of vectors like 6862 /// %ra = insertelement <4 x float> undef, float %s0, i32 0 6863 /// %rb = insertelement <4 x float> %ra, float %s1, i32 1 6864 /// %rc = insertelement <4 x float> %rb, float %s2, i32 2 6865 /// %rd = insertelement <4 x float> %rc, float %s3, i32 3 6866 /// starting from the last insertelement instruction. 6867 /// 6868 /// Returns true if it matches 6869 static bool findBuildVector(InsertElementInst *LastInsertElem, 6870 TargetTransformInfo *TTI, 6871 SmallVectorImpl<Value *> &BuildVectorOpds, 6872 int &UserCost) { 6873 UserCost = 0; 6874 Value *V = nullptr; 6875 do { 6876 if (auto *CI = dyn_cast<ConstantInt>(LastInsertElem->getOperand(2))) { 6877 UserCost += TTI->getVectorInstrCost(Instruction::InsertElement, 6878 LastInsertElem->getType(), 6879 CI->getZExtValue()); 6880 } 6881 BuildVectorOpds.push_back(LastInsertElem->getOperand(1)); 6882 V = LastInsertElem->getOperand(0); 6883 if (isa<UndefValue>(V)) 6884 break; 6885 LastInsertElem = dyn_cast<InsertElementInst>(V); 6886 if (!LastInsertElem || !LastInsertElem->hasOneUse()) 6887 return false; 6888 } while (true); 6889 std::reverse(BuildVectorOpds.begin(), BuildVectorOpds.end()); 6890 return true; 6891 } 6892 6893 /// Like findBuildVector, but looks for construction of aggregate. 6894 /// 6895 /// \return true if it matches. 6896 static bool findBuildAggregate(InsertValueInst *IV, 6897 SmallVectorImpl<Value *> &BuildVectorOpds) { 6898 do { 6899 BuildVectorOpds.push_back(IV->getInsertedValueOperand()); 6900 Value *V = IV->getAggregateOperand(); 6901 if (isa<UndefValue>(V)) 6902 break; 6903 IV = dyn_cast<InsertValueInst>(V); 6904 if (!IV || !IV->hasOneUse()) 6905 return false; 6906 } while (true); 6907 std::reverse(BuildVectorOpds.begin(), BuildVectorOpds.end()); 6908 return true; 6909 } 6910 6911 static bool PhiTypeSorterFunc(Value *V, Value *V2) { 6912 return V->getType() < V2->getType(); 6913 } 6914 6915 /// Try and get a reduction value from a phi node. 6916 /// 6917 /// Given a phi node \p P in a block \p ParentBB, consider possible reductions 6918 /// if they come from either \p ParentBB or a containing loop latch. 6919 /// 6920 /// \returns A candidate reduction value if possible, or \code nullptr \endcode 6921 /// if not possible. 6922 static Value *getReductionValue(const DominatorTree *DT, PHINode *P, 6923 BasicBlock *ParentBB, LoopInfo *LI) { 6924 // There are situations where the reduction value is not dominated by the 6925 // reduction phi. Vectorizing such cases has been reported to cause 6926 // miscompiles. See PR25787. 6927 auto DominatedReduxValue = [&](Value *R) { 6928 return isa<Instruction>(R) && 6929 DT->dominates(P->getParent(), cast<Instruction>(R)->getParent()); 6930 }; 6931 6932 Value *Rdx = nullptr; 6933 6934 // Return the incoming value if it comes from the same BB as the phi node. 6935 if (P->getIncomingBlock(0) == ParentBB) { 6936 Rdx = P->getIncomingValue(0); 6937 } else if (P->getIncomingBlock(1) == ParentBB) { 6938 Rdx = P->getIncomingValue(1); 6939 } 6940 6941 if (Rdx && DominatedReduxValue(Rdx)) 6942 return Rdx; 6943 6944 // Otherwise, check whether we have a loop latch to look at. 6945 Loop *BBL = LI->getLoopFor(ParentBB); 6946 if (!BBL) 6947 return nullptr; 6948 BasicBlock *BBLatch = BBL->getLoopLatch(); 6949 if (!BBLatch) 6950 return nullptr; 6951 6952 // There is a loop latch, return the incoming value if it comes from 6953 // that. This reduction pattern occasionally turns up. 6954 if (P->getIncomingBlock(0) == BBLatch) { 6955 Rdx = P->getIncomingValue(0); 6956 } else if (P->getIncomingBlock(1) == BBLatch) { 6957 Rdx = P->getIncomingValue(1); 6958 } 6959 6960 if (Rdx && DominatedReduxValue(Rdx)) 6961 return Rdx; 6962 6963 return nullptr; 6964 } 6965 6966 /// Attempt to reduce a horizontal reduction. 6967 /// If it is legal to match a horizontal reduction feeding the phi node \a P 6968 /// with reduction operators \a Root (or one of its operands) in a basic block 6969 /// \a BB, then check if it can be done. If horizontal reduction is not found 6970 /// and root instruction is a binary operation, vectorization of the operands is 6971 /// attempted. 6972 /// \returns true if a horizontal reduction was matched and reduced or operands 6973 /// of one of the binary instruction were vectorized. 6974 /// \returns false if a horizontal reduction was not matched (or not possible) 6975 /// or no vectorization of any binary operation feeding \a Root instruction was 6976 /// performed. 6977 static bool tryToVectorizeHorReductionOrInstOperands( 6978 PHINode *P, Instruction *Root, BasicBlock *BB, BoUpSLP &R, 6979 TargetTransformInfo *TTI, bool Try2WayRdx, 6980 const function_ref<bool(Instruction *, BoUpSLP &)> Vectorize) { 6981 if (!ShouldVectorizeHor) 6982 return false; 6983 6984 if (!Root) 6985 return false; 6986 6987 if (Root->getParent() != BB || isa<PHINode>(Root)) 6988 return false; 6989 // Start analysis starting from Root instruction. If horizontal reduction is 6990 // found, try to vectorize it. If it is not a horizontal reduction or 6991 // vectorization is not possible or not effective, and currently analyzed 6992 // instruction is a binary operation, try to vectorize the operands, using 6993 // pre-order DFS traversal order. If the operands were not vectorized, repeat 6994 // the same procedure considering each operand as a possible root of the 6995 // horizontal reduction. 6996 // Interrupt the process if the Root instruction itself was vectorized or all 6997 // sub-trees not higher that RecursionMaxDepth were analyzed/vectorized. 6998 SmallVector<std::pair<Instruction *, unsigned>, 8> Stack(1, {Root, 0}); 6999 SmallPtrSet<Value *, 8> VisitedInstrs; 7000 bool Res = false; 7001 while (!Stack.empty()) { 7002 Instruction *Inst; 7003 unsigned Level; 7004 std::tie(Inst, Level) = Stack.pop_back_val(); 7005 auto *BI = dyn_cast<BinaryOperator>(Inst); 7006 auto *SI = dyn_cast<SelectInst>(Inst); 7007 if (BI || SI) { 7008 HorizontalReduction HorRdx; 7009 if (HorRdx.matchAssociativeReduction(P, Inst)) { 7010 if (HorRdx.tryToReduce(R, TTI, Try2WayRdx)) { 7011 Res = true; 7012 // Set P to nullptr to avoid re-analysis of phi node in 7013 // matchAssociativeReduction function unless this is the root node. 7014 P = nullptr; 7015 continue; 7016 } 7017 } 7018 if (P && BI) { 7019 Inst = dyn_cast<Instruction>(BI->getOperand(0)); 7020 if (Inst == P) 7021 Inst = dyn_cast<Instruction>(BI->getOperand(1)); 7022 if (!Inst) { 7023 // Set P to nullptr to avoid re-analysis of phi node in 7024 // matchAssociativeReduction function unless this is the root node. 7025 P = nullptr; 7026 continue; 7027 } 7028 } 7029 } 7030 // Set P to nullptr to avoid re-analysis of phi node in 7031 // matchAssociativeReduction function unless this is the root node. 7032 P = nullptr; 7033 if (Vectorize(Inst, R)) { 7034 Res = true; 7035 continue; 7036 } 7037 7038 // Try to vectorize operands. 7039 // Continue analysis for the instruction from the same basic block only to 7040 // save compile time. 7041 if (++Level < RecursionMaxDepth) 7042 for (auto *Op : Inst->operand_values()) 7043 if (VisitedInstrs.insert(Op).second) 7044 if (auto *I = dyn_cast<Instruction>(Op)) 7045 if (!isa<PHINode>(I) && !R.isDeleted(I) && I->getParent() == BB) 7046 Stack.emplace_back(I, Level); 7047 } 7048 return Res; 7049 } 7050 7051 bool SLPVectorizerPass::vectorizeRootInstruction(PHINode *P, Value *V, 7052 BasicBlock *BB, BoUpSLP &R, 7053 TargetTransformInfo *TTI, 7054 bool Try2WayRdx) { 7055 if (!V) 7056 return false; 7057 auto *I = dyn_cast<Instruction>(V); 7058 if (!I) 7059 return false; 7060 7061 if (!isa<BinaryOperator>(I)) 7062 P = nullptr; 7063 // Try to match and vectorize a horizontal reduction. 7064 auto &&ExtraVectorization = [this](Instruction *I, BoUpSLP &R) -> bool { 7065 return tryToVectorize(I, R); 7066 }; 7067 return tryToVectorizeHorReductionOrInstOperands(P, I, BB, R, TTI, Try2WayRdx, 7068 ExtraVectorization); 7069 } 7070 7071 bool SLPVectorizerPass::vectorizeInsertValueInst(InsertValueInst *IVI, 7072 BasicBlock *BB, BoUpSLP &R) { 7073 const DataLayout &DL = BB->getModule()->getDataLayout(); 7074 if (!R.canMapToVector(IVI->getType(), DL)) 7075 return false; 7076 7077 SmallVector<Value *, 16> BuildVectorOpds; 7078 if (!findBuildAggregate(IVI, BuildVectorOpds)) 7079 return false; 7080 7081 LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IVI << "\n"); 7082 // Aggregate value is unlikely to be processed in vector register, we need to 7083 // extract scalars into scalar registers, so NeedExtraction is set true. 7084 return tryToVectorizeList(BuildVectorOpds, R); 7085 } 7086 7087 bool SLPVectorizerPass::vectorizeInsertElementInst(InsertElementInst *IEI, 7088 BasicBlock *BB, BoUpSLP &R) { 7089 int UserCost; 7090 SmallVector<Value *, 16> BuildVectorOpds; 7091 if (!findBuildVector(IEI, TTI, BuildVectorOpds, UserCost) || 7092 (llvm::all_of(BuildVectorOpds, 7093 [](Value *V) { return isa<ExtractElementInst>(V); }) && 7094 isShuffle(BuildVectorOpds))) 7095 return false; 7096 7097 // Vectorize starting with the build vector operands ignoring the BuildVector 7098 // instructions for the purpose of scheduling and user extraction. 7099 return tryToVectorizeList(BuildVectorOpds, R, UserCost); 7100 } 7101 7102 bool SLPVectorizerPass::vectorizeCmpInst(CmpInst *CI, BasicBlock *BB, 7103 BoUpSLP &R) { 7104 if (tryToVectorizePair(CI->getOperand(0), CI->getOperand(1), R)) 7105 return true; 7106 7107 bool OpsChanged = false; 7108 for (int Idx = 0; Idx < 2; ++Idx) { 7109 OpsChanged |= 7110 vectorizeRootInstruction(nullptr, CI->getOperand(Idx), BB, R, TTI); 7111 } 7112 return OpsChanged; 7113 } 7114 7115 bool SLPVectorizerPass::vectorizeSimpleInstructions( 7116 SmallVectorImpl<Instruction *> &Instructions, BasicBlock *BB, BoUpSLP &R) { 7117 bool OpsChanged = false; 7118 for (auto *I : reverse(Instructions)) { 7119 if (R.isDeleted(I)) 7120 continue; 7121 if (auto *LastInsertValue = dyn_cast<InsertValueInst>(I)) 7122 OpsChanged |= vectorizeInsertValueInst(LastInsertValue, BB, R); 7123 else if (auto *LastInsertElem = dyn_cast<InsertElementInst>(I)) 7124 OpsChanged |= vectorizeInsertElementInst(LastInsertElem, BB, R); 7125 else if (auto *CI = dyn_cast<CmpInst>(I)) 7126 OpsChanged |= vectorizeCmpInst(CI, BB, R); 7127 } 7128 Instructions.clear(); 7129 return OpsChanged; 7130 } 7131 7132 bool SLPVectorizerPass::vectorizeChainsInBlock(BasicBlock *BB, BoUpSLP &R) { 7133 bool Changed = false; 7134 SmallVector<Value *, 4> Incoming; 7135 SmallPtrSet<Value *, 16> VisitedInstrs; 7136 7137 bool HaveVectorizedPhiNodes = true; 7138 while (HaveVectorizedPhiNodes) { 7139 HaveVectorizedPhiNodes = false; 7140 7141 // Collect the incoming values from the PHIs. 7142 Incoming.clear(); 7143 for (Instruction &I : *BB) { 7144 PHINode *P = dyn_cast<PHINode>(&I); 7145 if (!P) 7146 break; 7147 7148 if (!VisitedInstrs.count(P) && !R.isDeleted(P)) 7149 Incoming.push_back(P); 7150 } 7151 7152 // Sort by type. 7153 llvm::stable_sort(Incoming, PhiTypeSorterFunc); 7154 7155 // Try to vectorize elements base on their type. 7156 for (SmallVector<Value *, 4>::iterator IncIt = Incoming.begin(), 7157 E = Incoming.end(); 7158 IncIt != E;) { 7159 7160 // Look for the next elements with the same type. 7161 SmallVector<Value *, 4>::iterator SameTypeIt = IncIt; 7162 while (SameTypeIt != E && 7163 (*SameTypeIt)->getType() == (*IncIt)->getType()) { 7164 VisitedInstrs.insert(*SameTypeIt); 7165 ++SameTypeIt; 7166 } 7167 7168 // Try to vectorize them. 7169 unsigned NumElts = (SameTypeIt - IncIt); 7170 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize starting at PHIs (" 7171 << NumElts << ")\n"); 7172 // The order in which the phi nodes appear in the program does not matter. 7173 // So allow tryToVectorizeList to reorder them if it is beneficial. This 7174 // is done when there are exactly two elements since tryToVectorizeList 7175 // asserts that there are only two values when AllowReorder is true. 7176 bool AllowReorder = NumElts == 2; 7177 if (NumElts > 1 && tryToVectorizeList(makeArrayRef(IncIt, NumElts), R, 7178 /*UserCost=*/0, AllowReorder)) { 7179 // Success start over because instructions might have been changed. 7180 HaveVectorizedPhiNodes = true; 7181 Changed = true; 7182 break; 7183 } 7184 7185 // Start over at the next instruction of a different type (or the end). 7186 IncIt = SameTypeIt; 7187 } 7188 } 7189 7190 VisitedInstrs.clear(); 7191 7192 SmallVector<Instruction *, 8> PostProcessInstructions; 7193 SmallDenseSet<Instruction *, 4> KeyNodes; 7194 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 7195 // Skip instructions marked for the deletion. 7196 if (R.isDeleted(&*it)) 7197 continue; 7198 // We may go through BB multiple times so skip the one we have checked. 7199 if (!VisitedInstrs.insert(&*it).second) { 7200 if (it->use_empty() && KeyNodes.count(&*it) > 0 && 7201 vectorizeSimpleInstructions(PostProcessInstructions, BB, R)) { 7202 // We would like to start over since some instructions are deleted 7203 // and the iterator may become invalid value. 7204 Changed = true; 7205 it = BB->begin(); 7206 e = BB->end(); 7207 } 7208 continue; 7209 } 7210 7211 if (isa<DbgInfoIntrinsic>(it)) 7212 continue; 7213 7214 // Try to vectorize reductions that use PHINodes. 7215 if (PHINode *P = dyn_cast<PHINode>(it)) { 7216 // Check that the PHI is a reduction PHI. 7217 if (P->getNumIncomingValues() != 2) 7218 return Changed; 7219 7220 // Try to match and vectorize a horizontal reduction. 7221 if (vectorizeRootInstruction(P, getReductionValue(DT, P, BB, LI), BB, R, 7222 TTI)) { 7223 Changed = true; 7224 it = BB->begin(); 7225 e = BB->end(); 7226 continue; 7227 } 7228 continue; 7229 } 7230 7231 // Ran into an instruction without users, like terminator, or function call 7232 // with ignored return value, store. Ignore unused instructions (basing on 7233 // instruction type, except for CallInst and InvokeInst). 7234 if (it->use_empty() && (it->getType()->isVoidTy() || isa<CallInst>(it) || 7235 isa<InvokeInst>(it))) { 7236 KeyNodes.insert(&*it); 7237 bool OpsChanged = false; 7238 if (ShouldStartVectorizeHorAtStore || !isa<StoreInst>(it)) { 7239 for (auto *V : it->operand_values()) { 7240 // Try to match and vectorize a horizontal reduction. 7241 OpsChanged |= vectorizeRootInstruction(nullptr, V, BB, R, TTI); 7242 } 7243 } 7244 // Start vectorization of post-process list of instructions from the 7245 // top-tree instructions to try to vectorize as many instructions as 7246 // possible. 7247 OpsChanged |= vectorizeSimpleInstructions(PostProcessInstructions, BB, R); 7248 if (OpsChanged) { 7249 // We would like to start over since some instructions are deleted 7250 // and the iterator may become invalid value. 7251 Changed = true; 7252 it = BB->begin(); 7253 e = BB->end(); 7254 continue; 7255 } 7256 } 7257 7258 if (isa<InsertElementInst>(it) || isa<CmpInst>(it) || 7259 isa<InsertValueInst>(it)) 7260 PostProcessInstructions.push_back(&*it); 7261 } 7262 7263 // Make a final attempt to match a 2-way reduction if nothing else worked. 7264 // We do not try this above because it may interfere with other vectorization 7265 // attempts. 7266 // TODO: The constraints are copied from the above call to 7267 // vectorizeRootInstruction(), but that might be too restrictive? 7268 BasicBlock::iterator LastInst = --BB->end(); 7269 if (!Changed && LastInst->use_empty() && 7270 (LastInst->getType()->isVoidTy() || isa<CallInst>(LastInst) || 7271 isa<InvokeInst>(LastInst))) { 7272 if (ShouldStartVectorizeHorAtStore || !isa<StoreInst>(LastInst)) { 7273 for (auto *V : LastInst->operand_values()) { 7274 Changed |= vectorizeRootInstruction(nullptr, V, BB, R, TTI, 7275 /* Try2WayRdx */ true); 7276 } 7277 } 7278 } 7279 7280 return Changed; 7281 } 7282 7283 bool SLPVectorizerPass::vectorizeGEPIndices(BasicBlock *BB, BoUpSLP &R) { 7284 auto Changed = false; 7285 for (auto &Entry : GEPs) { 7286 // If the getelementptr list has fewer than two elements, there's nothing 7287 // to do. 7288 if (Entry.second.size() < 2) 7289 continue; 7290 7291 LLVM_DEBUG(dbgs() << "SLP: Analyzing a getelementptr list of length " 7292 << Entry.second.size() << ".\n"); 7293 7294 // Process the GEP list in chunks suitable for the target's supported 7295 // vector size. If a vector register can't hold 1 element, we are done. 7296 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 7297 unsigned EltSize = R.getVectorElementSize(Entry.second[0]); 7298 if (MaxVecRegSize < EltSize) 7299 continue; 7300 7301 unsigned MaxElts = MaxVecRegSize / EltSize; 7302 for (unsigned BI = 0, BE = Entry.second.size(); BI < BE; BI += MaxElts) { 7303 auto Len = std::min<unsigned>(BE - BI, MaxElts); 7304 auto GEPList = makeArrayRef(&Entry.second[BI], Len); 7305 7306 // Initialize a set a candidate getelementptrs. Note that we use a 7307 // SetVector here to preserve program order. If the index computations 7308 // are vectorizable and begin with loads, we want to minimize the chance 7309 // of having to reorder them later. 7310 SetVector<Value *> Candidates(GEPList.begin(), GEPList.end()); 7311 7312 // Some of the candidates may have already been vectorized after we 7313 // initially collected them. If so, they are marked as deleted, so remove 7314 // them from the set of candidates. 7315 Candidates.remove_if( 7316 [&R](Value *I) { return R.isDeleted(cast<Instruction>(I)); }); 7317 7318 // Remove from the set of candidates all pairs of getelementptrs with 7319 // constant differences. Such getelementptrs are likely not good 7320 // candidates for vectorization in a bottom-up phase since one can be 7321 // computed from the other. We also ensure all candidate getelementptr 7322 // indices are unique. 7323 for (int I = 0, E = GEPList.size(); I < E && Candidates.size() > 1; ++I) { 7324 auto *GEPI = GEPList[I]; 7325 if (!Candidates.count(GEPI)) 7326 continue; 7327 auto *SCEVI = SE->getSCEV(GEPList[I]); 7328 for (int J = I + 1; J < E && Candidates.size() > 1; ++J) { 7329 auto *GEPJ = GEPList[J]; 7330 auto *SCEVJ = SE->getSCEV(GEPList[J]); 7331 if (isa<SCEVConstant>(SE->getMinusSCEV(SCEVI, SCEVJ))) { 7332 Candidates.remove(GEPI); 7333 Candidates.remove(GEPJ); 7334 } else if (GEPI->idx_begin()->get() == GEPJ->idx_begin()->get()) { 7335 Candidates.remove(GEPJ); 7336 } 7337 } 7338 } 7339 7340 // We break out of the above computation as soon as we know there are 7341 // fewer than two candidates remaining. 7342 if (Candidates.size() < 2) 7343 continue; 7344 7345 // Add the single, non-constant index of each candidate to the bundle. We 7346 // ensured the indices met these constraints when we originally collected 7347 // the getelementptrs. 7348 SmallVector<Value *, 16> Bundle(Candidates.size()); 7349 auto BundleIndex = 0u; 7350 for (auto *V : Candidates) { 7351 auto *GEP = cast<GetElementPtrInst>(V); 7352 auto *GEPIdx = GEP->idx_begin()->get(); 7353 assert(GEP->getNumIndices() == 1 || !isa<Constant>(GEPIdx)); 7354 Bundle[BundleIndex++] = GEPIdx; 7355 } 7356 7357 // Try and vectorize the indices. We are currently only interested in 7358 // gather-like cases of the form: 7359 // 7360 // ... = g[a[0] - b[0]] + g[a[1] - b[1]] + ... 7361 // 7362 // where the loads of "a", the loads of "b", and the subtractions can be 7363 // performed in parallel. It's likely that detecting this pattern in a 7364 // bottom-up phase will be simpler and less costly than building a 7365 // full-blown top-down phase beginning at the consecutive loads. 7366 Changed |= tryToVectorizeList(Bundle, R); 7367 } 7368 } 7369 return Changed; 7370 } 7371 7372 bool SLPVectorizerPass::vectorizeStoreChains(BoUpSLP &R) { 7373 bool Changed = false; 7374 // Attempt to sort and vectorize each of the store-groups. 7375 for (StoreListMap::iterator it = Stores.begin(), e = Stores.end(); it != e; 7376 ++it) { 7377 if (it->second.size() < 2) 7378 continue; 7379 7380 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " 7381 << it->second.size() << ".\n"); 7382 7383 // Process the stores in chunks of 16. 7384 // TODO: The limit of 16 inhibits greater vectorization factors. 7385 // For example, AVX2 supports v32i8. Increasing this limit, however, 7386 // may cause a significant compile-time increase. 7387 for (unsigned CI = 0, CE = it->second.size(); CI < CE; CI += 16) { 7388 unsigned Len = std::min<unsigned>(CE - CI, 16); 7389 Changed |= vectorizeStores(makeArrayRef(&it->second[CI], Len), R); 7390 } 7391 } 7392 return Changed; 7393 } 7394 7395 char SLPVectorizer::ID = 0; 7396 7397 static const char lv_name[] = "SLP Vectorizer"; 7398 7399 INITIALIZE_PASS_BEGIN(SLPVectorizer, SV_NAME, lv_name, false, false) 7400 INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass) 7401 INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass) 7402 INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker) 7403 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass) 7404 INITIALIZE_PASS_DEPENDENCY(LoopSimplify) 7405 INITIALIZE_PASS_DEPENDENCY(DemandedBitsWrapperPass) 7406 INITIALIZE_PASS_DEPENDENCY(OptimizationRemarkEmitterWrapperPass) 7407 INITIALIZE_PASS_END(SLPVectorizer, SV_NAME, lv_name, false, false) 7408 7409 Pass *llvm::createSLPVectorizerPass() { return new SLPVectorizer(); } 7410