1 //===- SLPVectorizer.cpp - A bottom up SLP Vectorizer ---------------------===// 2 // 3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. 4 // See https://llvm.org/LICENSE.txt for license information. 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 6 // 7 //===----------------------------------------------------------------------===// 8 // 9 // This pass implements the Bottom Up SLP vectorizer. It detects consecutive 10 // stores that can be put together into vector-stores. Next, it attempts to 11 // construct vectorizable tree using the use-def chains. If a profitable tree 12 // was found, the SLP vectorizer performs vectorization on the tree. 13 // 14 // The pass is inspired by the work described in the paper: 15 // "Loop-Aware SLP in GCC" by Ira Rosen, Dorit Nuzman, Ayal Zaks. 16 // 17 //===----------------------------------------------------------------------===// 18 19 #include "llvm/Transforms/Vectorize/SLPVectorizer.h" 20 #include "llvm/ADT/DenseMap.h" 21 #include "llvm/ADT/DenseSet.h" 22 #include "llvm/ADT/Optional.h" 23 #include "llvm/ADT/PostOrderIterator.h" 24 #include "llvm/ADT/STLExtras.h" 25 #include "llvm/ADT/SetVector.h" 26 #include "llvm/ADT/SmallBitVector.h" 27 #include "llvm/ADT/SmallPtrSet.h" 28 #include "llvm/ADT/SmallSet.h" 29 #include "llvm/ADT/SmallString.h" 30 #include "llvm/ADT/Statistic.h" 31 #include "llvm/ADT/iterator.h" 32 #include "llvm/ADT/iterator_range.h" 33 #include "llvm/Analysis/AliasAnalysis.h" 34 #include "llvm/Analysis/AssumptionCache.h" 35 #include "llvm/Analysis/CodeMetrics.h" 36 #include "llvm/Analysis/DemandedBits.h" 37 #include "llvm/Analysis/GlobalsModRef.h" 38 #include "llvm/Analysis/IVDescriptors.h" 39 #include "llvm/Analysis/LoopAccessAnalysis.h" 40 #include "llvm/Analysis/LoopInfo.h" 41 #include "llvm/Analysis/MemoryLocation.h" 42 #include "llvm/Analysis/OptimizationRemarkEmitter.h" 43 #include "llvm/Analysis/ScalarEvolution.h" 44 #include "llvm/Analysis/ScalarEvolutionExpressions.h" 45 #include "llvm/Analysis/TargetLibraryInfo.h" 46 #include "llvm/Analysis/TargetTransformInfo.h" 47 #include "llvm/Analysis/ValueTracking.h" 48 #include "llvm/Analysis/VectorUtils.h" 49 #include "llvm/IR/Attributes.h" 50 #include "llvm/IR/BasicBlock.h" 51 #include "llvm/IR/Constant.h" 52 #include "llvm/IR/Constants.h" 53 #include "llvm/IR/DataLayout.h" 54 #include "llvm/IR/DebugLoc.h" 55 #include "llvm/IR/DerivedTypes.h" 56 #include "llvm/IR/Dominators.h" 57 #include "llvm/IR/Function.h" 58 #include "llvm/IR/IRBuilder.h" 59 #include "llvm/IR/InstrTypes.h" 60 #include "llvm/IR/Instruction.h" 61 #include "llvm/IR/Instructions.h" 62 #include "llvm/IR/IntrinsicInst.h" 63 #include "llvm/IR/Intrinsics.h" 64 #include "llvm/IR/Module.h" 65 #include "llvm/IR/NoFolder.h" 66 #include "llvm/IR/Operator.h" 67 #include "llvm/IR/PatternMatch.h" 68 #include "llvm/IR/Type.h" 69 #include "llvm/IR/Use.h" 70 #include "llvm/IR/User.h" 71 #include "llvm/IR/Value.h" 72 #include "llvm/IR/ValueHandle.h" 73 #include "llvm/IR/Verifier.h" 74 #include "llvm/InitializePasses.h" 75 #include "llvm/Pass.h" 76 #include "llvm/Support/Casting.h" 77 #include "llvm/Support/CommandLine.h" 78 #include "llvm/Support/Compiler.h" 79 #include "llvm/Support/DOTGraphTraits.h" 80 #include "llvm/Support/Debug.h" 81 #include "llvm/Support/ErrorHandling.h" 82 #include "llvm/Support/GraphWriter.h" 83 #include "llvm/Support/InstructionCost.h" 84 #include "llvm/Support/KnownBits.h" 85 #include "llvm/Support/MathExtras.h" 86 #include "llvm/Support/raw_ostream.h" 87 #include "llvm/Transforms/Utils/InjectTLIMappings.h" 88 #include "llvm/Transforms/Utils/LoopUtils.h" 89 #include "llvm/Transforms/Vectorize.h" 90 #include <algorithm> 91 #include <cassert> 92 #include <cstdint> 93 #include <iterator> 94 #include <memory> 95 #include <set> 96 #include <string> 97 #include <tuple> 98 #include <utility> 99 #include <vector> 100 101 using namespace llvm; 102 using namespace llvm::PatternMatch; 103 using namespace slpvectorizer; 104 105 #define SV_NAME "slp-vectorizer" 106 #define DEBUG_TYPE "SLP" 107 108 STATISTIC(NumVectorInstructions, "Number of vector instructions generated"); 109 110 cl::opt<bool> RunSLPVectorization("vectorize-slp", cl::init(true), cl::Hidden, 111 cl::desc("Run the SLP vectorization passes")); 112 113 static cl::opt<int> 114 SLPCostThreshold("slp-threshold", cl::init(0), cl::Hidden, 115 cl::desc("Only vectorize if you gain more than this " 116 "number ")); 117 118 static cl::opt<bool> 119 ShouldVectorizeHor("slp-vectorize-hor", cl::init(true), cl::Hidden, 120 cl::desc("Attempt to vectorize horizontal reductions")); 121 122 static cl::opt<bool> ShouldStartVectorizeHorAtStore( 123 "slp-vectorize-hor-store", cl::init(false), cl::Hidden, 124 cl::desc( 125 "Attempt to vectorize horizontal reductions feeding into a store")); 126 127 static cl::opt<int> 128 MaxVectorRegSizeOption("slp-max-reg-size", cl::init(128), cl::Hidden, 129 cl::desc("Attempt to vectorize for this register size in bits")); 130 131 static cl::opt<unsigned> 132 MaxVFOption("slp-max-vf", cl::init(0), cl::Hidden, 133 cl::desc("Maximum SLP vectorization factor (0=unlimited)")); 134 135 static cl::opt<int> 136 MaxStoreLookup("slp-max-store-lookup", cl::init(32), cl::Hidden, 137 cl::desc("Maximum depth of the lookup for consecutive stores.")); 138 139 /// Limits the size of scheduling regions in a block. 140 /// It avoid long compile times for _very_ large blocks where vector 141 /// instructions are spread over a wide range. 142 /// This limit is way higher than needed by real-world functions. 143 static cl::opt<int> 144 ScheduleRegionSizeBudget("slp-schedule-budget", cl::init(100000), cl::Hidden, 145 cl::desc("Limit the size of the SLP scheduling region per block")); 146 147 static cl::opt<int> MinVectorRegSizeOption( 148 "slp-min-reg-size", cl::init(128), cl::Hidden, 149 cl::desc("Attempt to vectorize for this register size in bits")); 150 151 static cl::opt<unsigned> RecursionMaxDepth( 152 "slp-recursion-max-depth", cl::init(12), cl::Hidden, 153 cl::desc("Limit the recursion depth when building a vectorizable tree")); 154 155 static cl::opt<unsigned> MinTreeSize( 156 "slp-min-tree-size", cl::init(3), cl::Hidden, 157 cl::desc("Only vectorize small trees if they are fully vectorizable")); 158 159 // The maximum depth that the look-ahead score heuristic will explore. 160 // The higher this value, the higher the compilation time overhead. 161 static cl::opt<int> LookAheadMaxDepth( 162 "slp-max-look-ahead-depth", cl::init(2), cl::Hidden, 163 cl::desc("The maximum look-ahead depth for operand reordering scores")); 164 165 // The Look-ahead heuristic goes through the users of the bundle to calculate 166 // the users cost in getExternalUsesCost(). To avoid compilation time increase 167 // we limit the number of users visited to this value. 168 static cl::opt<unsigned> LookAheadUsersBudget( 169 "slp-look-ahead-users-budget", cl::init(2), cl::Hidden, 170 cl::desc("The maximum number of users to visit while visiting the " 171 "predecessors. This prevents compilation time increase.")); 172 173 static cl::opt<bool> 174 ViewSLPTree("view-slp-tree", cl::Hidden, 175 cl::desc("Display the SLP trees with Graphviz")); 176 177 // Limit the number of alias checks. The limit is chosen so that 178 // it has no negative effect on the llvm benchmarks. 179 static const unsigned AliasedCheckLimit = 10; 180 181 // Another limit for the alias checks: The maximum distance between load/store 182 // instructions where alias checks are done. 183 // This limit is useful for very large basic blocks. 184 static const unsigned MaxMemDepDistance = 160; 185 186 /// If the ScheduleRegionSizeBudget is exhausted, we allow small scheduling 187 /// regions to be handled. 188 static const int MinScheduleRegionSize = 16; 189 190 /// Predicate for the element types that the SLP vectorizer supports. 191 /// 192 /// The most important thing to filter here are types which are invalid in LLVM 193 /// vectors. We also filter target specific types which have absolutely no 194 /// meaningful vectorization path such as x86_fp80 and ppc_f128. This just 195 /// avoids spending time checking the cost model and realizing that they will 196 /// be inevitably scalarized. 197 static bool isValidElementType(Type *Ty) { 198 return VectorType::isValidElementType(Ty) && !Ty->isX86_FP80Ty() && 199 !Ty->isPPC_FP128Ty(); 200 } 201 202 /// \returns true if all of the instructions in \p VL are in the same block or 203 /// false otherwise. 204 static bool allSameBlock(ArrayRef<Value *> VL) { 205 Instruction *I0 = dyn_cast<Instruction>(VL[0]); 206 if (!I0) 207 return false; 208 BasicBlock *BB = I0->getParent(); 209 for (int I = 1, E = VL.size(); I < E; I++) { 210 auto *II = dyn_cast<Instruction>(VL[I]); 211 if (!II) 212 return false; 213 214 if (BB != II->getParent()) 215 return false; 216 } 217 return true; 218 } 219 220 /// \returns True if all of the values in \p VL are constants (but not 221 /// globals/constant expressions). 222 static bool allConstant(ArrayRef<Value *> VL) { 223 // Constant expressions and globals can't be vectorized like normal integer/FP 224 // constants. 225 for (Value *i : VL) 226 if (!isa<Constant>(i) || isa<ConstantExpr>(i) || isa<GlobalValue>(i)) 227 return false; 228 return true; 229 } 230 231 /// \returns True if all of the values in \p VL are identical. 232 static bool isSplat(ArrayRef<Value *> VL) { 233 for (unsigned i = 1, e = VL.size(); i < e; ++i) 234 if (VL[i] != VL[0]) 235 return false; 236 return true; 237 } 238 239 /// \returns True if \p I is commutative, handles CmpInst and BinaryOperator. 240 static bool isCommutative(Instruction *I) { 241 if (auto *Cmp = dyn_cast<CmpInst>(I)) 242 return Cmp->isCommutative(); 243 if (auto *BO = dyn_cast<BinaryOperator>(I)) 244 return BO->isCommutative(); 245 // TODO: This should check for generic Instruction::isCommutative(), but 246 // we need to confirm that the caller code correctly handles Intrinsics 247 // for example (does not have 2 operands). 248 return false; 249 } 250 251 /// Checks if the vector of instructions can be represented as a shuffle, like: 252 /// %x0 = extractelement <4 x i8> %x, i32 0 253 /// %x3 = extractelement <4 x i8> %x, i32 3 254 /// %y1 = extractelement <4 x i8> %y, i32 1 255 /// %y2 = extractelement <4 x i8> %y, i32 2 256 /// %x0x0 = mul i8 %x0, %x0 257 /// %x3x3 = mul i8 %x3, %x3 258 /// %y1y1 = mul i8 %y1, %y1 259 /// %y2y2 = mul i8 %y2, %y2 260 /// %ins1 = insertelement <4 x i8> poison, i8 %x0x0, i32 0 261 /// %ins2 = insertelement <4 x i8> %ins1, i8 %x3x3, i32 1 262 /// %ins3 = insertelement <4 x i8> %ins2, i8 %y1y1, i32 2 263 /// %ins4 = insertelement <4 x i8> %ins3, i8 %y2y2, i32 3 264 /// ret <4 x i8> %ins4 265 /// can be transformed into: 266 /// %1 = shufflevector <4 x i8> %x, <4 x i8> %y, <4 x i32> <i32 0, i32 3, i32 5, 267 /// i32 6> 268 /// %2 = mul <4 x i8> %1, %1 269 /// ret <4 x i8> %2 270 /// We convert this initially to something like: 271 /// %x0 = extractelement <4 x i8> %x, i32 0 272 /// %x3 = extractelement <4 x i8> %x, i32 3 273 /// %y1 = extractelement <4 x i8> %y, i32 1 274 /// %y2 = extractelement <4 x i8> %y, i32 2 275 /// %1 = insertelement <4 x i8> poison, i8 %x0, i32 0 276 /// %2 = insertelement <4 x i8> %1, i8 %x3, i32 1 277 /// %3 = insertelement <4 x i8> %2, i8 %y1, i32 2 278 /// %4 = insertelement <4 x i8> %3, i8 %y2, i32 3 279 /// %5 = mul <4 x i8> %4, %4 280 /// %6 = extractelement <4 x i8> %5, i32 0 281 /// %ins1 = insertelement <4 x i8> poison, i8 %6, i32 0 282 /// %7 = extractelement <4 x i8> %5, i32 1 283 /// %ins2 = insertelement <4 x i8> %ins1, i8 %7, i32 1 284 /// %8 = extractelement <4 x i8> %5, i32 2 285 /// %ins3 = insertelement <4 x i8> %ins2, i8 %8, i32 2 286 /// %9 = extractelement <4 x i8> %5, i32 3 287 /// %ins4 = insertelement <4 x i8> %ins3, i8 %9, i32 3 288 /// ret <4 x i8> %ins4 289 /// InstCombiner transforms this into a shuffle and vector mul 290 /// Mask will return the Shuffle Mask equivalent to the extracted elements. 291 /// TODO: Can we split off and reuse the shuffle mask detection from 292 /// TargetTransformInfo::getInstructionThroughput? 293 static Optional<TargetTransformInfo::ShuffleKind> 294 isShuffle(ArrayRef<Value *> VL, SmallVectorImpl<int> &Mask) { 295 auto *EI0 = cast<ExtractElementInst>(VL[0]); 296 unsigned Size = 297 cast<FixedVectorType>(EI0->getVectorOperandType())->getNumElements(); 298 Value *Vec1 = nullptr; 299 Value *Vec2 = nullptr; 300 enum ShuffleMode { Unknown, Select, Permute }; 301 ShuffleMode CommonShuffleMode = Unknown; 302 for (unsigned I = 0, E = VL.size(); I < E; ++I) { 303 auto *EI = cast<ExtractElementInst>(VL[I]); 304 auto *Vec = EI->getVectorOperand(); 305 // All vector operands must have the same number of vector elements. 306 if (cast<FixedVectorType>(Vec->getType())->getNumElements() != Size) 307 return None; 308 auto *Idx = dyn_cast<ConstantInt>(EI->getIndexOperand()); 309 if (!Idx) 310 return None; 311 // Undefined behavior if Idx is negative or >= Size. 312 if (Idx->getValue().uge(Size)) { 313 Mask.push_back(UndefMaskElem); 314 continue; 315 } 316 unsigned IntIdx = Idx->getValue().getZExtValue(); 317 Mask.push_back(IntIdx); 318 // We can extractelement from undef or poison vector. 319 if (isa<UndefValue>(Vec)) 320 continue; 321 // For correct shuffling we have to have at most 2 different vector operands 322 // in all extractelement instructions. 323 if (!Vec1 || Vec1 == Vec) 324 Vec1 = Vec; 325 else if (!Vec2 || Vec2 == Vec) 326 Vec2 = Vec; 327 else 328 return None; 329 if (CommonShuffleMode == Permute) 330 continue; 331 // If the extract index is not the same as the operation number, it is a 332 // permutation. 333 if (IntIdx != I) { 334 CommonShuffleMode = Permute; 335 continue; 336 } 337 CommonShuffleMode = Select; 338 } 339 // If we're not crossing lanes in different vectors, consider it as blending. 340 if (CommonShuffleMode == Select && Vec2) 341 return TargetTransformInfo::SK_Select; 342 // If Vec2 was never used, we have a permutation of a single vector, otherwise 343 // we have permutation of 2 vectors. 344 return Vec2 ? TargetTransformInfo::SK_PermuteTwoSrc 345 : TargetTransformInfo::SK_PermuteSingleSrc; 346 } 347 348 namespace { 349 350 /// Main data required for vectorization of instructions. 351 struct InstructionsState { 352 /// The very first instruction in the list with the main opcode. 353 Value *OpValue = nullptr; 354 355 /// The main/alternate instruction. 356 Instruction *MainOp = nullptr; 357 Instruction *AltOp = nullptr; 358 359 /// The main/alternate opcodes for the list of instructions. 360 unsigned getOpcode() const { 361 return MainOp ? MainOp->getOpcode() : 0; 362 } 363 364 unsigned getAltOpcode() const { 365 return AltOp ? AltOp->getOpcode() : 0; 366 } 367 368 /// Some of the instructions in the list have alternate opcodes. 369 bool isAltShuffle() const { return getOpcode() != getAltOpcode(); } 370 371 bool isOpcodeOrAlt(Instruction *I) const { 372 unsigned CheckedOpcode = I->getOpcode(); 373 return getOpcode() == CheckedOpcode || getAltOpcode() == CheckedOpcode; 374 } 375 376 InstructionsState() = delete; 377 InstructionsState(Value *OpValue, Instruction *MainOp, Instruction *AltOp) 378 : OpValue(OpValue), MainOp(MainOp), AltOp(AltOp) {} 379 }; 380 381 } // end anonymous namespace 382 383 /// Chooses the correct key for scheduling data. If \p Op has the same (or 384 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is \p 385 /// OpValue. 386 static Value *isOneOf(const InstructionsState &S, Value *Op) { 387 auto *I = dyn_cast<Instruction>(Op); 388 if (I && S.isOpcodeOrAlt(I)) 389 return Op; 390 return S.OpValue; 391 } 392 393 /// \returns true if \p Opcode is allowed as part of of the main/alternate 394 /// instruction for SLP vectorization. 395 /// 396 /// Example of unsupported opcode is SDIV that can potentially cause UB if the 397 /// "shuffled out" lane would result in division by zero. 398 static bool isValidForAlternation(unsigned Opcode) { 399 if (Instruction::isIntDivRem(Opcode)) 400 return false; 401 402 return true; 403 } 404 405 /// \returns analysis of the Instructions in \p VL described in 406 /// InstructionsState, the Opcode that we suppose the whole list 407 /// could be vectorized even if its structure is diverse. 408 static InstructionsState getSameOpcode(ArrayRef<Value *> VL, 409 unsigned BaseIndex = 0) { 410 // Make sure these are all Instructions. 411 if (llvm::any_of(VL, [](Value *V) { return !isa<Instruction>(V); })) 412 return InstructionsState(VL[BaseIndex], nullptr, nullptr); 413 414 bool IsCastOp = isa<CastInst>(VL[BaseIndex]); 415 bool IsBinOp = isa<BinaryOperator>(VL[BaseIndex]); 416 unsigned Opcode = cast<Instruction>(VL[BaseIndex])->getOpcode(); 417 unsigned AltOpcode = Opcode; 418 unsigned AltIndex = BaseIndex; 419 420 // Check for one alternate opcode from another BinaryOperator. 421 // TODO - generalize to support all operators (types, calls etc.). 422 for (int Cnt = 0, E = VL.size(); Cnt < E; Cnt++) { 423 unsigned InstOpcode = cast<Instruction>(VL[Cnt])->getOpcode(); 424 if (IsBinOp && isa<BinaryOperator>(VL[Cnt])) { 425 if (InstOpcode == Opcode || InstOpcode == AltOpcode) 426 continue; 427 if (Opcode == AltOpcode && isValidForAlternation(InstOpcode) && 428 isValidForAlternation(Opcode)) { 429 AltOpcode = InstOpcode; 430 AltIndex = Cnt; 431 continue; 432 } 433 } else if (IsCastOp && isa<CastInst>(VL[Cnt])) { 434 Type *Ty0 = cast<Instruction>(VL[BaseIndex])->getOperand(0)->getType(); 435 Type *Ty1 = cast<Instruction>(VL[Cnt])->getOperand(0)->getType(); 436 if (Ty0 == Ty1) { 437 if (InstOpcode == Opcode || InstOpcode == AltOpcode) 438 continue; 439 if (Opcode == AltOpcode) { 440 assert(isValidForAlternation(Opcode) && 441 isValidForAlternation(InstOpcode) && 442 "Cast isn't safe for alternation, logic needs to be updated!"); 443 AltOpcode = InstOpcode; 444 AltIndex = Cnt; 445 continue; 446 } 447 } 448 } else if (InstOpcode == Opcode || InstOpcode == AltOpcode) 449 continue; 450 return InstructionsState(VL[BaseIndex], nullptr, nullptr); 451 } 452 453 return InstructionsState(VL[BaseIndex], cast<Instruction>(VL[BaseIndex]), 454 cast<Instruction>(VL[AltIndex])); 455 } 456 457 /// \returns true if all of the values in \p VL have the same type or false 458 /// otherwise. 459 static bool allSameType(ArrayRef<Value *> VL) { 460 Type *Ty = VL[0]->getType(); 461 for (int i = 1, e = VL.size(); i < e; i++) 462 if (VL[i]->getType() != Ty) 463 return false; 464 465 return true; 466 } 467 468 /// \returns True if Extract{Value,Element} instruction extracts element Idx. 469 static Optional<unsigned> getExtractIndex(Instruction *E) { 470 unsigned Opcode = E->getOpcode(); 471 assert((Opcode == Instruction::ExtractElement || 472 Opcode == Instruction::ExtractValue) && 473 "Expected extractelement or extractvalue instruction."); 474 if (Opcode == Instruction::ExtractElement) { 475 auto *CI = dyn_cast<ConstantInt>(E->getOperand(1)); 476 if (!CI) 477 return None; 478 return CI->getZExtValue(); 479 } 480 ExtractValueInst *EI = cast<ExtractValueInst>(E); 481 if (EI->getNumIndices() != 1) 482 return None; 483 return *EI->idx_begin(); 484 } 485 486 /// \returns True if in-tree use also needs extract. This refers to 487 /// possible scalar operand in vectorized instruction. 488 static bool InTreeUserNeedToExtract(Value *Scalar, Instruction *UserInst, 489 TargetLibraryInfo *TLI) { 490 unsigned Opcode = UserInst->getOpcode(); 491 switch (Opcode) { 492 case Instruction::Load: { 493 LoadInst *LI = cast<LoadInst>(UserInst); 494 return (LI->getPointerOperand() == Scalar); 495 } 496 case Instruction::Store: { 497 StoreInst *SI = cast<StoreInst>(UserInst); 498 return (SI->getPointerOperand() == Scalar); 499 } 500 case Instruction::Call: { 501 CallInst *CI = cast<CallInst>(UserInst); 502 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 503 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 504 if (hasVectorInstrinsicScalarOpd(ID, i)) 505 return (CI->getArgOperand(i) == Scalar); 506 } 507 LLVM_FALLTHROUGH; 508 } 509 default: 510 return false; 511 } 512 } 513 514 /// \returns the AA location that is being access by the instruction. 515 static MemoryLocation getLocation(Instruction *I, AAResults *AA) { 516 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 517 return MemoryLocation::get(SI); 518 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 519 return MemoryLocation::get(LI); 520 return MemoryLocation(); 521 } 522 523 /// \returns True if the instruction is not a volatile or atomic load/store. 524 static bool isSimple(Instruction *I) { 525 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 526 return LI->isSimple(); 527 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 528 return SI->isSimple(); 529 if (MemIntrinsic *MI = dyn_cast<MemIntrinsic>(I)) 530 return !MI->isVolatile(); 531 return true; 532 } 533 534 namespace llvm { 535 536 static void inversePermutation(ArrayRef<unsigned> Indices, 537 SmallVectorImpl<int> &Mask) { 538 Mask.clear(); 539 const unsigned E = Indices.size(); 540 Mask.resize(E, E + 1); 541 for (unsigned I = 0; I < E; ++I) 542 Mask[Indices[I]] = I; 543 } 544 545 namespace slpvectorizer { 546 547 /// Bottom Up SLP Vectorizer. 548 class BoUpSLP { 549 struct TreeEntry; 550 struct ScheduleData; 551 552 public: 553 using ValueList = SmallVector<Value *, 8>; 554 using InstrList = SmallVector<Instruction *, 16>; 555 using ValueSet = SmallPtrSet<Value *, 16>; 556 using StoreList = SmallVector<StoreInst *, 8>; 557 using ExtraValueToDebugLocsMap = 558 MapVector<Value *, SmallVector<Instruction *, 2>>; 559 using OrdersType = SmallVector<unsigned, 4>; 560 561 BoUpSLP(Function *Func, ScalarEvolution *Se, TargetTransformInfo *Tti, 562 TargetLibraryInfo *TLi, AAResults *Aa, LoopInfo *Li, 563 DominatorTree *Dt, AssumptionCache *AC, DemandedBits *DB, 564 const DataLayout *DL, OptimizationRemarkEmitter *ORE) 565 : F(Func), SE(Se), TTI(Tti), TLI(TLi), AA(Aa), LI(Li), DT(Dt), AC(AC), 566 DB(DB), DL(DL), ORE(ORE), Builder(Se->getContext()) { 567 CodeMetrics::collectEphemeralValues(F, AC, EphValues); 568 // Use the vector register size specified by the target unless overridden 569 // by a command-line option. 570 // TODO: It would be better to limit the vectorization factor based on 571 // data type rather than just register size. For example, x86 AVX has 572 // 256-bit registers, but it does not support integer operations 573 // at that width (that requires AVX2). 574 if (MaxVectorRegSizeOption.getNumOccurrences()) 575 MaxVecRegSize = MaxVectorRegSizeOption; 576 else 577 MaxVecRegSize = 578 TTI->getRegisterBitWidth(TargetTransformInfo::RGK_FixedWidthVector) 579 .getFixedSize(); 580 581 if (MinVectorRegSizeOption.getNumOccurrences()) 582 MinVecRegSize = MinVectorRegSizeOption; 583 else 584 MinVecRegSize = TTI->getMinVectorRegisterBitWidth(); 585 } 586 587 /// Vectorize the tree that starts with the elements in \p VL. 588 /// Returns the vectorized root. 589 Value *vectorizeTree(); 590 591 /// Vectorize the tree but with the list of externally used values \p 592 /// ExternallyUsedValues. Values in this MapVector can be replaced but the 593 /// generated extractvalue instructions. 594 Value *vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues); 595 596 /// \returns the cost incurred by unwanted spills and fills, caused by 597 /// holding live values over call sites. 598 InstructionCost getSpillCost() const; 599 600 /// \returns the vectorization cost of the subtree that starts at \p VL. 601 /// A negative number means that this is profitable. 602 InstructionCost getTreeCost(); 603 604 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 605 /// the purpose of scheduling and extraction in the \p UserIgnoreLst. 606 void buildTree(ArrayRef<Value *> Roots, 607 ArrayRef<Value *> UserIgnoreLst = None); 608 609 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 610 /// the purpose of scheduling and extraction in the \p UserIgnoreLst taking 611 /// into account (and updating it, if required) list of externally used 612 /// values stored in \p ExternallyUsedValues. 613 void buildTree(ArrayRef<Value *> Roots, 614 ExtraValueToDebugLocsMap &ExternallyUsedValues, 615 ArrayRef<Value *> UserIgnoreLst = None); 616 617 /// Clear the internal data structures that are created by 'buildTree'. 618 void deleteTree() { 619 VectorizableTree.clear(); 620 ScalarToTreeEntry.clear(); 621 MustGather.clear(); 622 ExternalUses.clear(); 623 NumOpsWantToKeepOrder.clear(); 624 NumOpsWantToKeepOriginalOrder = 0; 625 for (auto &Iter : BlocksSchedules) { 626 BlockScheduling *BS = Iter.second.get(); 627 BS->clear(); 628 } 629 MinBWs.clear(); 630 InstrElementSize.clear(); 631 } 632 633 unsigned getTreeSize() const { return VectorizableTree.size(); } 634 635 /// Perform LICM and CSE on the newly generated gather sequences. 636 void optimizeGatherSequence(); 637 638 /// \returns The best order of instructions for vectorization. 639 Optional<ArrayRef<unsigned>> bestOrder() const { 640 assert(llvm::all_of( 641 NumOpsWantToKeepOrder, 642 [this](const decltype(NumOpsWantToKeepOrder)::value_type &D) { 643 return D.getFirst().size() == 644 VectorizableTree[0]->Scalars.size(); 645 }) && 646 "All orders must have the same size as number of instructions in " 647 "tree node."); 648 auto I = std::max_element( 649 NumOpsWantToKeepOrder.begin(), NumOpsWantToKeepOrder.end(), 650 [](const decltype(NumOpsWantToKeepOrder)::value_type &D1, 651 const decltype(NumOpsWantToKeepOrder)::value_type &D2) { 652 return D1.second < D2.second; 653 }); 654 if (I == NumOpsWantToKeepOrder.end() || 655 I->getSecond() <= NumOpsWantToKeepOriginalOrder) 656 return None; 657 658 return makeArrayRef(I->getFirst()); 659 } 660 661 /// Builds the correct order for root instructions. 662 /// If some leaves have the same instructions to be vectorized, we may 663 /// incorrectly evaluate the best order for the root node (it is built for the 664 /// vector of instructions without repeated instructions and, thus, has less 665 /// elements than the root node). This function builds the correct order for 666 /// the root node. 667 /// For example, if the root node is \<a+b, a+c, a+d, f+e\>, then the leaves 668 /// are \<a, a, a, f\> and \<b, c, d, e\>. When we try to vectorize the first 669 /// leaf, it will be shrink to \<a, b\>. If instructions in this leaf should 670 /// be reordered, the best order will be \<1, 0\>. We need to extend this 671 /// order for the root node. For the root node this order should look like 672 /// \<3, 0, 1, 2\>. This function extends the order for the reused 673 /// instructions. 674 void findRootOrder(OrdersType &Order) { 675 // If the leaf has the same number of instructions to vectorize as the root 676 // - order must be set already. 677 unsigned RootSize = VectorizableTree[0]->Scalars.size(); 678 if (Order.size() == RootSize) 679 return; 680 SmallVector<unsigned, 4> RealOrder(Order.size()); 681 std::swap(Order, RealOrder); 682 SmallVector<int, 4> Mask; 683 inversePermutation(RealOrder, Mask); 684 Order.assign(Mask.begin(), Mask.end()); 685 // The leaf has less number of instructions - need to find the true order of 686 // the root. 687 // Scan the nodes starting from the leaf back to the root. 688 const TreeEntry *PNode = VectorizableTree.back().get(); 689 SmallVector<const TreeEntry *, 4> Nodes(1, PNode); 690 SmallPtrSet<const TreeEntry *, 4> Visited; 691 while (!Nodes.empty() && Order.size() != RootSize) { 692 const TreeEntry *PNode = Nodes.pop_back_val(); 693 if (!Visited.insert(PNode).second) 694 continue; 695 const TreeEntry &Node = *PNode; 696 for (const EdgeInfo &EI : Node.UserTreeIndices) 697 if (EI.UserTE) 698 Nodes.push_back(EI.UserTE); 699 if (Node.ReuseShuffleIndices.empty()) 700 continue; 701 // Build the order for the parent node. 702 OrdersType NewOrder(Node.ReuseShuffleIndices.size(), RootSize); 703 SmallVector<unsigned, 4> OrderCounter(Order.size(), 0); 704 // The algorithm of the order extension is: 705 // 1. Calculate the number of the same instructions for the order. 706 // 2. Calculate the index of the new order: total number of instructions 707 // with order less than the order of the current instruction + reuse 708 // number of the current instruction. 709 // 3. The new order is just the index of the instruction in the original 710 // vector of the instructions. 711 for (unsigned I : Node.ReuseShuffleIndices) 712 ++OrderCounter[Order[I]]; 713 SmallVector<unsigned, 4> CurrentCounter(Order.size(), 0); 714 for (unsigned I = 0, E = Node.ReuseShuffleIndices.size(); I < E; ++I) { 715 unsigned ReusedIdx = Node.ReuseShuffleIndices[I]; 716 unsigned OrderIdx = Order[ReusedIdx]; 717 unsigned NewIdx = 0; 718 for (unsigned J = 0; J < OrderIdx; ++J) 719 NewIdx += OrderCounter[J]; 720 NewIdx += CurrentCounter[OrderIdx]; 721 ++CurrentCounter[OrderIdx]; 722 assert(NewOrder[NewIdx] == RootSize && 723 "The order index should not be written already."); 724 NewOrder[NewIdx] = I; 725 } 726 std::swap(Order, NewOrder); 727 } 728 assert(Order.size() == RootSize && 729 "Root node is expected or the size of the order must be the same as " 730 "the number of elements in the root node."); 731 assert(llvm::all_of(Order, 732 [RootSize](unsigned Val) { return Val != RootSize; }) && 733 "All indices must be initialized"); 734 } 735 736 /// \return The vector element size in bits to use when vectorizing the 737 /// expression tree ending at \p V. If V is a store, the size is the width of 738 /// the stored value. Otherwise, the size is the width of the largest loaded 739 /// value reaching V. This method is used by the vectorizer to calculate 740 /// vectorization factors. 741 unsigned getVectorElementSize(Value *V); 742 743 /// Compute the minimum type sizes required to represent the entries in a 744 /// vectorizable tree. 745 void computeMinimumValueSizes(); 746 747 // \returns maximum vector register size as set by TTI or overridden by cl::opt. 748 unsigned getMaxVecRegSize() const { 749 return MaxVecRegSize; 750 } 751 752 // \returns minimum vector register size as set by cl::opt. 753 unsigned getMinVecRegSize() const { 754 return MinVecRegSize; 755 } 756 757 unsigned getMaximumVF(unsigned ElemWidth, unsigned Opcode) const { 758 unsigned MaxVF = MaxVFOption.getNumOccurrences() ? 759 MaxVFOption : TTI->getMaximumVF(ElemWidth, Opcode); 760 return MaxVF ? MaxVF : UINT_MAX; 761 } 762 763 /// Check if homogeneous aggregate is isomorphic to some VectorType. 764 /// Accepts homogeneous multidimensional aggregate of scalars/vectors like 765 /// {[4 x i16], [4 x i16]}, { <2 x float>, <2 x float> }, 766 /// {{{i16, i16}, {i16, i16}}, {{i16, i16}, {i16, i16}}} and so on. 767 /// 768 /// \returns number of elements in vector if isomorphism exists, 0 otherwise. 769 unsigned canMapToVector(Type *T, const DataLayout &DL) const; 770 771 /// \returns True if the VectorizableTree is both tiny and not fully 772 /// vectorizable. We do not vectorize such trees. 773 bool isTreeTinyAndNotFullyVectorizable() const; 774 775 /// Assume that a legal-sized 'or'-reduction of shifted/zexted loaded values 776 /// can be load combined in the backend. Load combining may not be allowed in 777 /// the IR optimizer, so we do not want to alter the pattern. For example, 778 /// partially transforming a scalar bswap() pattern into vector code is 779 /// effectively impossible for the backend to undo. 780 /// TODO: If load combining is allowed in the IR optimizer, this analysis 781 /// may not be necessary. 782 bool isLoadCombineReductionCandidate(RecurKind RdxKind) const; 783 784 /// Assume that a vector of stores of bitwise-or/shifted/zexted loaded values 785 /// can be load combined in the backend. Load combining may not be allowed in 786 /// the IR optimizer, so we do not want to alter the pattern. For example, 787 /// partially transforming a scalar bswap() pattern into vector code is 788 /// effectively impossible for the backend to undo. 789 /// TODO: If load combining is allowed in the IR optimizer, this analysis 790 /// may not be necessary. 791 bool isLoadCombineCandidate() const; 792 793 OptimizationRemarkEmitter *getORE() { return ORE; } 794 795 /// This structure holds any data we need about the edges being traversed 796 /// during buildTree_rec(). We keep track of: 797 /// (i) the user TreeEntry index, and 798 /// (ii) the index of the edge. 799 struct EdgeInfo { 800 EdgeInfo() = default; 801 EdgeInfo(TreeEntry *UserTE, unsigned EdgeIdx) 802 : UserTE(UserTE), EdgeIdx(EdgeIdx) {} 803 /// The user TreeEntry. 804 TreeEntry *UserTE = nullptr; 805 /// The operand index of the use. 806 unsigned EdgeIdx = UINT_MAX; 807 #ifndef NDEBUG 808 friend inline raw_ostream &operator<<(raw_ostream &OS, 809 const BoUpSLP::EdgeInfo &EI) { 810 EI.dump(OS); 811 return OS; 812 } 813 /// Debug print. 814 void dump(raw_ostream &OS) const { 815 OS << "{User:" << (UserTE ? std::to_string(UserTE->Idx) : "null") 816 << " EdgeIdx:" << EdgeIdx << "}"; 817 } 818 LLVM_DUMP_METHOD void dump() const { dump(dbgs()); } 819 #endif 820 }; 821 822 /// A helper data structure to hold the operands of a vector of instructions. 823 /// This supports a fixed vector length for all operand vectors. 824 class VLOperands { 825 /// For each operand we need (i) the value, and (ii) the opcode that it 826 /// would be attached to if the expression was in a left-linearized form. 827 /// This is required to avoid illegal operand reordering. 828 /// For example: 829 /// \verbatim 830 /// 0 Op1 831 /// |/ 832 /// Op1 Op2 Linearized + Op2 833 /// \ / ----------> |/ 834 /// - - 835 /// 836 /// Op1 - Op2 (0 + Op1) - Op2 837 /// \endverbatim 838 /// 839 /// Value Op1 is attached to a '+' operation, and Op2 to a '-'. 840 /// 841 /// Another way to think of this is to track all the operations across the 842 /// path from the operand all the way to the root of the tree and to 843 /// calculate the operation that corresponds to this path. For example, the 844 /// path from Op2 to the root crosses the RHS of the '-', therefore the 845 /// corresponding operation is a '-' (which matches the one in the 846 /// linearized tree, as shown above). 847 /// 848 /// For lack of a better term, we refer to this operation as Accumulated 849 /// Path Operation (APO). 850 struct OperandData { 851 OperandData() = default; 852 OperandData(Value *V, bool APO, bool IsUsed) 853 : V(V), APO(APO), IsUsed(IsUsed) {} 854 /// The operand value. 855 Value *V = nullptr; 856 /// TreeEntries only allow a single opcode, or an alternate sequence of 857 /// them (e.g, +, -). Therefore, we can safely use a boolean value for the 858 /// APO. It is set to 'true' if 'V' is attached to an inverse operation 859 /// in the left-linearized form (e.g., Sub/Div), and 'false' otherwise 860 /// (e.g., Add/Mul) 861 bool APO = false; 862 /// Helper data for the reordering function. 863 bool IsUsed = false; 864 }; 865 866 /// During operand reordering, we are trying to select the operand at lane 867 /// that matches best with the operand at the neighboring lane. Our 868 /// selection is based on the type of value we are looking for. For example, 869 /// if the neighboring lane has a load, we need to look for a load that is 870 /// accessing a consecutive address. These strategies are summarized in the 871 /// 'ReorderingMode' enumerator. 872 enum class ReorderingMode { 873 Load, ///< Matching loads to consecutive memory addresses 874 Opcode, ///< Matching instructions based on opcode (same or alternate) 875 Constant, ///< Matching constants 876 Splat, ///< Matching the same instruction multiple times (broadcast) 877 Failed, ///< We failed to create a vectorizable group 878 }; 879 880 using OperandDataVec = SmallVector<OperandData, 2>; 881 882 /// A vector of operand vectors. 883 SmallVector<OperandDataVec, 4> OpsVec; 884 885 const DataLayout &DL; 886 ScalarEvolution &SE; 887 const BoUpSLP &R; 888 889 /// \returns the operand data at \p OpIdx and \p Lane. 890 OperandData &getData(unsigned OpIdx, unsigned Lane) { 891 return OpsVec[OpIdx][Lane]; 892 } 893 894 /// \returns the operand data at \p OpIdx and \p Lane. Const version. 895 const OperandData &getData(unsigned OpIdx, unsigned Lane) const { 896 return OpsVec[OpIdx][Lane]; 897 } 898 899 /// Clears the used flag for all entries. 900 void clearUsed() { 901 for (unsigned OpIdx = 0, NumOperands = getNumOperands(); 902 OpIdx != NumOperands; ++OpIdx) 903 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 904 ++Lane) 905 OpsVec[OpIdx][Lane].IsUsed = false; 906 } 907 908 /// Swap the operand at \p OpIdx1 with that one at \p OpIdx2. 909 void swap(unsigned OpIdx1, unsigned OpIdx2, unsigned Lane) { 910 std::swap(OpsVec[OpIdx1][Lane], OpsVec[OpIdx2][Lane]); 911 } 912 913 // The hard-coded scores listed here are not very important. When computing 914 // the scores of matching one sub-tree with another, we are basically 915 // counting the number of values that are matching. So even if all scores 916 // are set to 1, we would still get a decent matching result. 917 // However, sometimes we have to break ties. For example we may have to 918 // choose between matching loads vs matching opcodes. This is what these 919 // scores are helping us with: they provide the order of preference. 920 921 /// Loads from consecutive memory addresses, e.g. load(A[i]), load(A[i+1]). 922 static const int ScoreConsecutiveLoads = 3; 923 /// ExtractElementInst from same vector and consecutive indexes. 924 static const int ScoreConsecutiveExtracts = 3; 925 /// Constants. 926 static const int ScoreConstants = 2; 927 /// Instructions with the same opcode. 928 static const int ScoreSameOpcode = 2; 929 /// Instructions with alt opcodes (e.g, add + sub). 930 static const int ScoreAltOpcodes = 1; 931 /// Identical instructions (a.k.a. splat or broadcast). 932 static const int ScoreSplat = 1; 933 /// Matching with an undef is preferable to failing. 934 static const int ScoreUndef = 1; 935 /// Score for failing to find a decent match. 936 static const int ScoreFail = 0; 937 /// User exteranl to the vectorized code. 938 static const int ExternalUseCost = 1; 939 /// The user is internal but in a different lane. 940 static const int UserInDiffLaneCost = ExternalUseCost; 941 942 /// \returns the score of placing \p V1 and \p V2 in consecutive lanes. 943 static int getShallowScore(Value *V1, Value *V2, const DataLayout &DL, 944 ScalarEvolution &SE) { 945 auto *LI1 = dyn_cast<LoadInst>(V1); 946 auto *LI2 = dyn_cast<LoadInst>(V2); 947 if (LI1 && LI2) { 948 if (LI1->getParent() != LI2->getParent()) 949 return VLOperands::ScoreFail; 950 951 Optional<int> Dist = 952 getPointersDiff(LI1->getPointerOperand(), LI2->getPointerOperand(), 953 DL, SE, /*StrictCheck=*/true); 954 return (Dist && *Dist == 1) ? VLOperands::ScoreConsecutiveLoads 955 : VLOperands::ScoreFail; 956 } 957 958 auto *C1 = dyn_cast<Constant>(V1); 959 auto *C2 = dyn_cast<Constant>(V2); 960 if (C1 && C2) 961 return VLOperands::ScoreConstants; 962 963 // Extracts from consecutive indexes of the same vector better score as 964 // the extracts could be optimized away. 965 Value *EV; 966 ConstantInt *Ex1Idx, *Ex2Idx; 967 if (match(V1, m_ExtractElt(m_Value(EV), m_ConstantInt(Ex1Idx))) && 968 match(V2, m_ExtractElt(m_Deferred(EV), m_ConstantInt(Ex2Idx))) && 969 Ex1Idx->getZExtValue() + 1 == Ex2Idx->getZExtValue()) 970 return VLOperands::ScoreConsecutiveExtracts; 971 972 auto *I1 = dyn_cast<Instruction>(V1); 973 auto *I2 = dyn_cast<Instruction>(V2); 974 if (I1 && I2) { 975 if (I1 == I2) 976 return VLOperands::ScoreSplat; 977 InstructionsState S = getSameOpcode({I1, I2}); 978 // Note: Only consider instructions with <= 2 operands to avoid 979 // complexity explosion. 980 if (S.getOpcode() && S.MainOp->getNumOperands() <= 2) 981 return S.isAltShuffle() ? VLOperands::ScoreAltOpcodes 982 : VLOperands::ScoreSameOpcode; 983 } 984 985 if (isa<UndefValue>(V2)) 986 return VLOperands::ScoreUndef; 987 988 return VLOperands::ScoreFail; 989 } 990 991 /// Holds the values and their lane that are taking part in the look-ahead 992 /// score calculation. This is used in the external uses cost calculation. 993 SmallDenseMap<Value *, int> InLookAheadValues; 994 995 /// \Returns the additinal cost due to uses of \p LHS and \p RHS that are 996 /// either external to the vectorized code, or require shuffling. 997 int getExternalUsesCost(const std::pair<Value *, int> &LHS, 998 const std::pair<Value *, int> &RHS) { 999 int Cost = 0; 1000 std::array<std::pair<Value *, int>, 2> Values = {{LHS, RHS}}; 1001 for (int Idx = 0, IdxE = Values.size(); Idx != IdxE; ++Idx) { 1002 Value *V = Values[Idx].first; 1003 if (isa<Constant>(V)) { 1004 // Since this is a function pass, it doesn't make semantic sense to 1005 // walk the users of a subclass of Constant. The users could be in 1006 // another function, or even another module that happens to be in 1007 // the same LLVMContext. 1008 continue; 1009 } 1010 1011 // Calculate the absolute lane, using the minimum relative lane of LHS 1012 // and RHS as base and Idx as the offset. 1013 int Ln = std::min(LHS.second, RHS.second) + Idx; 1014 assert(Ln >= 0 && "Bad lane calculation"); 1015 unsigned UsersBudget = LookAheadUsersBudget; 1016 for (User *U : V->users()) { 1017 if (const TreeEntry *UserTE = R.getTreeEntry(U)) { 1018 // The user is in the VectorizableTree. Check if we need to insert. 1019 auto It = llvm::find(UserTE->Scalars, U); 1020 assert(It != UserTE->Scalars.end() && "U is in UserTE"); 1021 int UserLn = std::distance(UserTE->Scalars.begin(), It); 1022 assert(UserLn >= 0 && "Bad lane"); 1023 if (UserLn != Ln) 1024 Cost += UserInDiffLaneCost; 1025 } else { 1026 // Check if the user is in the look-ahead code. 1027 auto It2 = InLookAheadValues.find(U); 1028 if (It2 != InLookAheadValues.end()) { 1029 // The user is in the look-ahead code. Check the lane. 1030 if (It2->second != Ln) 1031 Cost += UserInDiffLaneCost; 1032 } else { 1033 // The user is neither in SLP tree nor in the look-ahead code. 1034 Cost += ExternalUseCost; 1035 } 1036 } 1037 // Limit the number of visited uses to cap compilation time. 1038 if (--UsersBudget == 0) 1039 break; 1040 } 1041 } 1042 return Cost; 1043 } 1044 1045 /// Go through the operands of \p LHS and \p RHS recursively until \p 1046 /// MaxLevel, and return the cummulative score. For example: 1047 /// \verbatim 1048 /// A[0] B[0] A[1] B[1] C[0] D[0] B[1] A[1] 1049 /// \ / \ / \ / \ / 1050 /// + + + + 1051 /// G1 G2 G3 G4 1052 /// \endverbatim 1053 /// The getScoreAtLevelRec(G1, G2) function will try to match the nodes at 1054 /// each level recursively, accumulating the score. It starts from matching 1055 /// the additions at level 0, then moves on to the loads (level 1). The 1056 /// score of G1 and G2 is higher than G1 and G3, because {A[0],A[1]} and 1057 /// {B[0],B[1]} match with VLOperands::ScoreConsecutiveLoads, while 1058 /// {A[0],C[0]} has a score of VLOperands::ScoreFail. 1059 /// Please note that the order of the operands does not matter, as we 1060 /// evaluate the score of all profitable combinations of operands. In 1061 /// other words the score of G1 and G4 is the same as G1 and G2. This 1062 /// heuristic is based on ideas described in: 1063 /// Look-ahead SLP: Auto-vectorization in the presence of commutative 1064 /// operations, CGO 2018 by Vasileios Porpodas, Rodrigo C. O. Rocha, 1065 /// Luís F. W. Góes 1066 int getScoreAtLevelRec(const std::pair<Value *, int> &LHS, 1067 const std::pair<Value *, int> &RHS, int CurrLevel, 1068 int MaxLevel) { 1069 1070 Value *V1 = LHS.first; 1071 Value *V2 = RHS.first; 1072 // Get the shallow score of V1 and V2. 1073 int ShallowScoreAtThisLevel = 1074 std::max((int)ScoreFail, getShallowScore(V1, V2, DL, SE) - 1075 getExternalUsesCost(LHS, RHS)); 1076 int Lane1 = LHS.second; 1077 int Lane2 = RHS.second; 1078 1079 // If reached MaxLevel, 1080 // or if V1 and V2 are not instructions, 1081 // or if they are SPLAT, 1082 // or if they are not consecutive, early return the current cost. 1083 auto *I1 = dyn_cast<Instruction>(V1); 1084 auto *I2 = dyn_cast<Instruction>(V2); 1085 if (CurrLevel == MaxLevel || !(I1 && I2) || I1 == I2 || 1086 ShallowScoreAtThisLevel == VLOperands::ScoreFail || 1087 (isa<LoadInst>(I1) && isa<LoadInst>(I2) && ShallowScoreAtThisLevel)) 1088 return ShallowScoreAtThisLevel; 1089 assert(I1 && I2 && "Should have early exited."); 1090 1091 // Keep track of in-tree values for determining the external-use cost. 1092 InLookAheadValues[V1] = Lane1; 1093 InLookAheadValues[V2] = Lane2; 1094 1095 // Contains the I2 operand indexes that got matched with I1 operands. 1096 SmallSet<unsigned, 4> Op2Used; 1097 1098 // Recursion towards the operands of I1 and I2. We are trying all possbile 1099 // operand pairs, and keeping track of the best score. 1100 for (unsigned OpIdx1 = 0, NumOperands1 = I1->getNumOperands(); 1101 OpIdx1 != NumOperands1; ++OpIdx1) { 1102 // Try to pair op1I with the best operand of I2. 1103 int MaxTmpScore = 0; 1104 unsigned MaxOpIdx2 = 0; 1105 bool FoundBest = false; 1106 // If I2 is commutative try all combinations. 1107 unsigned FromIdx = isCommutative(I2) ? 0 : OpIdx1; 1108 unsigned ToIdx = isCommutative(I2) 1109 ? I2->getNumOperands() 1110 : std::min(I2->getNumOperands(), OpIdx1 + 1); 1111 assert(FromIdx <= ToIdx && "Bad index"); 1112 for (unsigned OpIdx2 = FromIdx; OpIdx2 != ToIdx; ++OpIdx2) { 1113 // Skip operands already paired with OpIdx1. 1114 if (Op2Used.count(OpIdx2)) 1115 continue; 1116 // Recursively calculate the cost at each level 1117 int TmpScore = getScoreAtLevelRec({I1->getOperand(OpIdx1), Lane1}, 1118 {I2->getOperand(OpIdx2), Lane2}, 1119 CurrLevel + 1, MaxLevel); 1120 // Look for the best score. 1121 if (TmpScore > VLOperands::ScoreFail && TmpScore > MaxTmpScore) { 1122 MaxTmpScore = TmpScore; 1123 MaxOpIdx2 = OpIdx2; 1124 FoundBest = true; 1125 } 1126 } 1127 if (FoundBest) { 1128 // Pair {OpIdx1, MaxOpIdx2} was found to be best. Never revisit it. 1129 Op2Used.insert(MaxOpIdx2); 1130 ShallowScoreAtThisLevel += MaxTmpScore; 1131 } 1132 } 1133 return ShallowScoreAtThisLevel; 1134 } 1135 1136 /// \Returns the look-ahead score, which tells us how much the sub-trees 1137 /// rooted at \p LHS and \p RHS match, the more they match the higher the 1138 /// score. This helps break ties in an informed way when we cannot decide on 1139 /// the order of the operands by just considering the immediate 1140 /// predecessors. 1141 int getLookAheadScore(const std::pair<Value *, int> &LHS, 1142 const std::pair<Value *, int> &RHS) { 1143 InLookAheadValues.clear(); 1144 return getScoreAtLevelRec(LHS, RHS, 1, LookAheadMaxDepth); 1145 } 1146 1147 // Search all operands in Ops[*][Lane] for the one that matches best 1148 // Ops[OpIdx][LastLane] and return its opreand index. 1149 // If no good match can be found, return None. 1150 Optional<unsigned> 1151 getBestOperand(unsigned OpIdx, int Lane, int LastLane, 1152 ArrayRef<ReorderingMode> ReorderingModes) { 1153 unsigned NumOperands = getNumOperands(); 1154 1155 // The operand of the previous lane at OpIdx. 1156 Value *OpLastLane = getData(OpIdx, LastLane).V; 1157 1158 // Our strategy mode for OpIdx. 1159 ReorderingMode RMode = ReorderingModes[OpIdx]; 1160 1161 // The linearized opcode of the operand at OpIdx, Lane. 1162 bool OpIdxAPO = getData(OpIdx, Lane).APO; 1163 1164 // The best operand index and its score. 1165 // Sometimes we have more than one option (e.g., Opcode and Undefs), so we 1166 // are using the score to differentiate between the two. 1167 struct BestOpData { 1168 Optional<unsigned> Idx = None; 1169 unsigned Score = 0; 1170 } BestOp; 1171 1172 // Iterate through all unused operands and look for the best. 1173 for (unsigned Idx = 0; Idx != NumOperands; ++Idx) { 1174 // Get the operand at Idx and Lane. 1175 OperandData &OpData = getData(Idx, Lane); 1176 Value *Op = OpData.V; 1177 bool OpAPO = OpData.APO; 1178 1179 // Skip already selected operands. 1180 if (OpData.IsUsed) 1181 continue; 1182 1183 // Skip if we are trying to move the operand to a position with a 1184 // different opcode in the linearized tree form. This would break the 1185 // semantics. 1186 if (OpAPO != OpIdxAPO) 1187 continue; 1188 1189 // Look for an operand that matches the current mode. 1190 switch (RMode) { 1191 case ReorderingMode::Load: 1192 case ReorderingMode::Constant: 1193 case ReorderingMode::Opcode: { 1194 bool LeftToRight = Lane > LastLane; 1195 Value *OpLeft = (LeftToRight) ? OpLastLane : Op; 1196 Value *OpRight = (LeftToRight) ? Op : OpLastLane; 1197 unsigned Score = 1198 getLookAheadScore({OpLeft, LastLane}, {OpRight, Lane}); 1199 if (Score > BestOp.Score) { 1200 BestOp.Idx = Idx; 1201 BestOp.Score = Score; 1202 } 1203 break; 1204 } 1205 case ReorderingMode::Splat: 1206 if (Op == OpLastLane) 1207 BestOp.Idx = Idx; 1208 break; 1209 case ReorderingMode::Failed: 1210 return None; 1211 } 1212 } 1213 1214 if (BestOp.Idx) { 1215 getData(BestOp.Idx.getValue(), Lane).IsUsed = true; 1216 return BestOp.Idx; 1217 } 1218 // If we could not find a good match return None. 1219 return None; 1220 } 1221 1222 /// Helper for reorderOperandVecs. \Returns the lane that we should start 1223 /// reordering from. This is the one which has the least number of operands 1224 /// that can freely move about. 1225 unsigned getBestLaneToStartReordering() const { 1226 unsigned BestLane = 0; 1227 unsigned Min = UINT_MAX; 1228 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 1229 ++Lane) { 1230 unsigned NumFreeOps = getMaxNumOperandsThatCanBeReordered(Lane); 1231 if (NumFreeOps < Min) { 1232 Min = NumFreeOps; 1233 BestLane = Lane; 1234 } 1235 } 1236 return BestLane; 1237 } 1238 1239 /// \Returns the maximum number of operands that are allowed to be reordered 1240 /// for \p Lane. This is used as a heuristic for selecting the first lane to 1241 /// start operand reordering. 1242 unsigned getMaxNumOperandsThatCanBeReordered(unsigned Lane) const { 1243 unsigned CntTrue = 0; 1244 unsigned NumOperands = getNumOperands(); 1245 // Operands with the same APO can be reordered. We therefore need to count 1246 // how many of them we have for each APO, like this: Cnt[APO] = x. 1247 // Since we only have two APOs, namely true and false, we can avoid using 1248 // a map. Instead we can simply count the number of operands that 1249 // correspond to one of them (in this case the 'true' APO), and calculate 1250 // the other by subtracting it from the total number of operands. 1251 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) 1252 if (getData(OpIdx, Lane).APO) 1253 ++CntTrue; 1254 unsigned CntFalse = NumOperands - CntTrue; 1255 return std::max(CntTrue, CntFalse); 1256 } 1257 1258 /// Go through the instructions in VL and append their operands. 1259 void appendOperandsOfVL(ArrayRef<Value *> VL) { 1260 assert(!VL.empty() && "Bad VL"); 1261 assert((empty() || VL.size() == getNumLanes()) && 1262 "Expected same number of lanes"); 1263 assert(isa<Instruction>(VL[0]) && "Expected instruction"); 1264 unsigned NumOperands = cast<Instruction>(VL[0])->getNumOperands(); 1265 OpsVec.resize(NumOperands); 1266 unsigned NumLanes = VL.size(); 1267 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1268 OpsVec[OpIdx].resize(NumLanes); 1269 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { 1270 assert(isa<Instruction>(VL[Lane]) && "Expected instruction"); 1271 // Our tree has just 3 nodes: the root and two operands. 1272 // It is therefore trivial to get the APO. We only need to check the 1273 // opcode of VL[Lane] and whether the operand at OpIdx is the LHS or 1274 // RHS operand. The LHS operand of both add and sub is never attached 1275 // to an inversese operation in the linearized form, therefore its APO 1276 // is false. The RHS is true only if VL[Lane] is an inverse operation. 1277 1278 // Since operand reordering is performed on groups of commutative 1279 // operations or alternating sequences (e.g., +, -), we can safely 1280 // tell the inverse operations by checking commutativity. 1281 bool IsInverseOperation = !isCommutative(cast<Instruction>(VL[Lane])); 1282 bool APO = (OpIdx == 0) ? false : IsInverseOperation; 1283 OpsVec[OpIdx][Lane] = {cast<Instruction>(VL[Lane])->getOperand(OpIdx), 1284 APO, false}; 1285 } 1286 } 1287 } 1288 1289 /// \returns the number of operands. 1290 unsigned getNumOperands() const { return OpsVec.size(); } 1291 1292 /// \returns the number of lanes. 1293 unsigned getNumLanes() const { return OpsVec[0].size(); } 1294 1295 /// \returns the operand value at \p OpIdx and \p Lane. 1296 Value *getValue(unsigned OpIdx, unsigned Lane) const { 1297 return getData(OpIdx, Lane).V; 1298 } 1299 1300 /// \returns true if the data structure is empty. 1301 bool empty() const { return OpsVec.empty(); } 1302 1303 /// Clears the data. 1304 void clear() { OpsVec.clear(); } 1305 1306 /// \Returns true if there are enough operands identical to \p Op to fill 1307 /// the whole vector. 1308 /// Note: This modifies the 'IsUsed' flag, so a cleanUsed() must follow. 1309 bool shouldBroadcast(Value *Op, unsigned OpIdx, unsigned Lane) { 1310 bool OpAPO = getData(OpIdx, Lane).APO; 1311 for (unsigned Ln = 0, Lns = getNumLanes(); Ln != Lns; ++Ln) { 1312 if (Ln == Lane) 1313 continue; 1314 // This is set to true if we found a candidate for broadcast at Lane. 1315 bool FoundCandidate = false; 1316 for (unsigned OpI = 0, OpE = getNumOperands(); OpI != OpE; ++OpI) { 1317 OperandData &Data = getData(OpI, Ln); 1318 if (Data.APO != OpAPO || Data.IsUsed) 1319 continue; 1320 if (Data.V == Op) { 1321 FoundCandidate = true; 1322 Data.IsUsed = true; 1323 break; 1324 } 1325 } 1326 if (!FoundCandidate) 1327 return false; 1328 } 1329 return true; 1330 } 1331 1332 public: 1333 /// Initialize with all the operands of the instruction vector \p RootVL. 1334 VLOperands(ArrayRef<Value *> RootVL, const DataLayout &DL, 1335 ScalarEvolution &SE, const BoUpSLP &R) 1336 : DL(DL), SE(SE), R(R) { 1337 // Append all the operands of RootVL. 1338 appendOperandsOfVL(RootVL); 1339 } 1340 1341 /// \Returns a value vector with the operands across all lanes for the 1342 /// opearnd at \p OpIdx. 1343 ValueList getVL(unsigned OpIdx) const { 1344 ValueList OpVL(OpsVec[OpIdx].size()); 1345 assert(OpsVec[OpIdx].size() == getNumLanes() && 1346 "Expected same num of lanes across all operands"); 1347 for (unsigned Lane = 0, Lanes = getNumLanes(); Lane != Lanes; ++Lane) 1348 OpVL[Lane] = OpsVec[OpIdx][Lane].V; 1349 return OpVL; 1350 } 1351 1352 // Performs operand reordering for 2 or more operands. 1353 // The original operands are in OrigOps[OpIdx][Lane]. 1354 // The reordered operands are returned in 'SortedOps[OpIdx][Lane]'. 1355 void reorder() { 1356 unsigned NumOperands = getNumOperands(); 1357 unsigned NumLanes = getNumLanes(); 1358 // Each operand has its own mode. We are using this mode to help us select 1359 // the instructions for each lane, so that they match best with the ones 1360 // we have selected so far. 1361 SmallVector<ReorderingMode, 2> ReorderingModes(NumOperands); 1362 1363 // This is a greedy single-pass algorithm. We are going over each lane 1364 // once and deciding on the best order right away with no back-tracking. 1365 // However, in order to increase its effectiveness, we start with the lane 1366 // that has operands that can move the least. For example, given the 1367 // following lanes: 1368 // Lane 0 : A[0] = B[0] + C[0] // Visited 3rd 1369 // Lane 1 : A[1] = C[1] - B[1] // Visited 1st 1370 // Lane 2 : A[2] = B[2] + C[2] // Visited 2nd 1371 // Lane 3 : A[3] = C[3] - B[3] // Visited 4th 1372 // we will start at Lane 1, since the operands of the subtraction cannot 1373 // be reordered. Then we will visit the rest of the lanes in a circular 1374 // fashion. That is, Lanes 2, then Lane 0, and finally Lane 3. 1375 1376 // Find the first lane that we will start our search from. 1377 unsigned FirstLane = getBestLaneToStartReordering(); 1378 1379 // Initialize the modes. 1380 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1381 Value *OpLane0 = getValue(OpIdx, FirstLane); 1382 // Keep track if we have instructions with all the same opcode on one 1383 // side. 1384 if (isa<LoadInst>(OpLane0)) 1385 ReorderingModes[OpIdx] = ReorderingMode::Load; 1386 else if (isa<Instruction>(OpLane0)) { 1387 // Check if OpLane0 should be broadcast. 1388 if (shouldBroadcast(OpLane0, OpIdx, FirstLane)) 1389 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1390 else 1391 ReorderingModes[OpIdx] = ReorderingMode::Opcode; 1392 } 1393 else if (isa<Constant>(OpLane0)) 1394 ReorderingModes[OpIdx] = ReorderingMode::Constant; 1395 else if (isa<Argument>(OpLane0)) 1396 // Our best hope is a Splat. It may save some cost in some cases. 1397 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1398 else 1399 // NOTE: This should be unreachable. 1400 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1401 } 1402 1403 // If the initial strategy fails for any of the operand indexes, then we 1404 // perform reordering again in a second pass. This helps avoid assigning 1405 // high priority to the failed strategy, and should improve reordering for 1406 // the non-failed operand indexes. 1407 for (int Pass = 0; Pass != 2; ++Pass) { 1408 // Skip the second pass if the first pass did not fail. 1409 bool StrategyFailed = false; 1410 // Mark all operand data as free to use. 1411 clearUsed(); 1412 // We keep the original operand order for the FirstLane, so reorder the 1413 // rest of the lanes. We are visiting the nodes in a circular fashion, 1414 // using FirstLane as the center point and increasing the radius 1415 // distance. 1416 for (unsigned Distance = 1; Distance != NumLanes; ++Distance) { 1417 // Visit the lane on the right and then the lane on the left. 1418 for (int Direction : {+1, -1}) { 1419 int Lane = FirstLane + Direction * Distance; 1420 if (Lane < 0 || Lane >= (int)NumLanes) 1421 continue; 1422 int LastLane = Lane - Direction; 1423 assert(LastLane >= 0 && LastLane < (int)NumLanes && 1424 "Out of bounds"); 1425 // Look for a good match for each operand. 1426 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1427 // Search for the operand that matches SortedOps[OpIdx][Lane-1]. 1428 Optional<unsigned> BestIdx = 1429 getBestOperand(OpIdx, Lane, LastLane, ReorderingModes); 1430 // By not selecting a value, we allow the operands that follow to 1431 // select a better matching value. We will get a non-null value in 1432 // the next run of getBestOperand(). 1433 if (BestIdx) { 1434 // Swap the current operand with the one returned by 1435 // getBestOperand(). 1436 swap(OpIdx, BestIdx.getValue(), Lane); 1437 } else { 1438 // We failed to find a best operand, set mode to 'Failed'. 1439 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1440 // Enable the second pass. 1441 StrategyFailed = true; 1442 } 1443 } 1444 } 1445 } 1446 // Skip second pass if the strategy did not fail. 1447 if (!StrategyFailed) 1448 break; 1449 } 1450 } 1451 1452 #if !defined(NDEBUG) || defined(LLVM_ENABLE_DUMP) 1453 LLVM_DUMP_METHOD static StringRef getModeStr(ReorderingMode RMode) { 1454 switch (RMode) { 1455 case ReorderingMode::Load: 1456 return "Load"; 1457 case ReorderingMode::Opcode: 1458 return "Opcode"; 1459 case ReorderingMode::Constant: 1460 return "Constant"; 1461 case ReorderingMode::Splat: 1462 return "Splat"; 1463 case ReorderingMode::Failed: 1464 return "Failed"; 1465 } 1466 llvm_unreachable("Unimplemented Reordering Type"); 1467 } 1468 1469 LLVM_DUMP_METHOD static raw_ostream &printMode(ReorderingMode RMode, 1470 raw_ostream &OS) { 1471 return OS << getModeStr(RMode); 1472 } 1473 1474 /// Debug print. 1475 LLVM_DUMP_METHOD static void dumpMode(ReorderingMode RMode) { 1476 printMode(RMode, dbgs()); 1477 } 1478 1479 friend raw_ostream &operator<<(raw_ostream &OS, ReorderingMode RMode) { 1480 return printMode(RMode, OS); 1481 } 1482 1483 LLVM_DUMP_METHOD raw_ostream &print(raw_ostream &OS) const { 1484 const unsigned Indent = 2; 1485 unsigned Cnt = 0; 1486 for (const OperandDataVec &OpDataVec : OpsVec) { 1487 OS << "Operand " << Cnt++ << "\n"; 1488 for (const OperandData &OpData : OpDataVec) { 1489 OS.indent(Indent) << "{"; 1490 if (Value *V = OpData.V) 1491 OS << *V; 1492 else 1493 OS << "null"; 1494 OS << ", APO:" << OpData.APO << "}\n"; 1495 } 1496 OS << "\n"; 1497 } 1498 return OS; 1499 } 1500 1501 /// Debug print. 1502 LLVM_DUMP_METHOD void dump() const { print(dbgs()); } 1503 #endif 1504 }; 1505 1506 /// Checks if the instruction is marked for deletion. 1507 bool isDeleted(Instruction *I) const { return DeletedInstructions.count(I); } 1508 1509 /// Marks values operands for later deletion by replacing them with Undefs. 1510 void eraseInstructions(ArrayRef<Value *> AV); 1511 1512 ~BoUpSLP(); 1513 1514 private: 1515 /// Checks if all users of \p I are the part of the vectorization tree. 1516 bool areAllUsersVectorized(Instruction *I) const; 1517 1518 /// \returns the cost of the vectorizable entry. 1519 InstructionCost getEntryCost(TreeEntry *E); 1520 1521 /// This is the recursive part of buildTree. 1522 void buildTree_rec(ArrayRef<Value *> Roots, unsigned Depth, 1523 const EdgeInfo &EI); 1524 1525 /// \returns true if the ExtractElement/ExtractValue instructions in \p VL can 1526 /// be vectorized to use the original vector (or aggregate "bitcast" to a 1527 /// vector) and sets \p CurrentOrder to the identity permutation; otherwise 1528 /// returns false, setting \p CurrentOrder to either an empty vector or a 1529 /// non-identity permutation that allows to reuse extract instructions. 1530 bool canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 1531 SmallVectorImpl<unsigned> &CurrentOrder) const; 1532 1533 /// Vectorize a single entry in the tree. 1534 Value *vectorizeTree(TreeEntry *E); 1535 1536 /// Vectorize a single entry in the tree, starting in \p VL. 1537 Value *vectorizeTree(ArrayRef<Value *> VL); 1538 1539 /// \returns the scalarization cost for this type. Scalarization in this 1540 /// context means the creation of vectors from a group of scalars. 1541 InstructionCost 1542 getGatherCost(FixedVectorType *Ty, 1543 const DenseSet<unsigned> &ShuffledIndices) const; 1544 1545 /// \returns the scalarization cost for this list of values. Assuming that 1546 /// this subtree gets vectorized, we may need to extract the values from the 1547 /// roots. This method calculates the cost of extracting the values. 1548 InstructionCost getGatherCost(ArrayRef<Value *> VL) const; 1549 1550 /// Set the Builder insert point to one after the last instruction in 1551 /// the bundle 1552 void setInsertPointAfterBundle(TreeEntry *E); 1553 1554 /// \returns a vector from a collection of scalars in \p VL. 1555 Value *gather(ArrayRef<Value *> VL); 1556 1557 /// \returns whether the VectorizableTree is fully vectorizable and will 1558 /// be beneficial even the tree height is tiny. 1559 bool isFullyVectorizableTinyTree() const; 1560 1561 /// Reorder commutative or alt operands to get better probability of 1562 /// generating vectorized code. 1563 static void reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 1564 SmallVectorImpl<Value *> &Left, 1565 SmallVectorImpl<Value *> &Right, 1566 const DataLayout &DL, 1567 ScalarEvolution &SE, 1568 const BoUpSLP &R); 1569 struct TreeEntry { 1570 using VecTreeTy = SmallVector<std::unique_ptr<TreeEntry>, 8>; 1571 TreeEntry(VecTreeTy &Container) : Container(Container) {} 1572 1573 /// \returns true if the scalars in VL are equal to this entry. 1574 bool isSame(ArrayRef<Value *> VL) const { 1575 if (VL.size() == Scalars.size()) 1576 return std::equal(VL.begin(), VL.end(), Scalars.begin()); 1577 return VL.size() == ReuseShuffleIndices.size() && 1578 std::equal( 1579 VL.begin(), VL.end(), ReuseShuffleIndices.begin(), 1580 [this](Value *V, int Idx) { return V == Scalars[Idx]; }); 1581 } 1582 1583 /// A vector of scalars. 1584 ValueList Scalars; 1585 1586 /// The Scalars are vectorized into this value. It is initialized to Null. 1587 Value *VectorizedValue = nullptr; 1588 1589 /// Do we need to gather this sequence or vectorize it 1590 /// (either with vector instruction or with scatter/gather 1591 /// intrinsics for store/load)? 1592 enum EntryState { Vectorize, ScatterVectorize, NeedToGather }; 1593 EntryState State; 1594 1595 /// Does this sequence require some shuffling? 1596 SmallVector<int, 4> ReuseShuffleIndices; 1597 1598 /// Does this entry require reordering? 1599 SmallVector<unsigned, 4> ReorderIndices; 1600 1601 /// Points back to the VectorizableTree. 1602 /// 1603 /// Only used for Graphviz right now. Unfortunately GraphTrait::NodeRef has 1604 /// to be a pointer and needs to be able to initialize the child iterator. 1605 /// Thus we need a reference back to the container to translate the indices 1606 /// to entries. 1607 VecTreeTy &Container; 1608 1609 /// The TreeEntry index containing the user of this entry. We can actually 1610 /// have multiple users so the data structure is not truly a tree. 1611 SmallVector<EdgeInfo, 1> UserTreeIndices; 1612 1613 /// The index of this treeEntry in VectorizableTree. 1614 int Idx = -1; 1615 1616 private: 1617 /// The operands of each instruction in each lane Operands[op_index][lane]. 1618 /// Note: This helps avoid the replication of the code that performs the 1619 /// reordering of operands during buildTree_rec() and vectorizeTree(). 1620 SmallVector<ValueList, 2> Operands; 1621 1622 /// The main/alternate instruction. 1623 Instruction *MainOp = nullptr; 1624 Instruction *AltOp = nullptr; 1625 1626 public: 1627 /// Set this bundle's \p OpIdx'th operand to \p OpVL. 1628 void setOperand(unsigned OpIdx, ArrayRef<Value *> OpVL) { 1629 if (Operands.size() < OpIdx + 1) 1630 Operands.resize(OpIdx + 1); 1631 assert(Operands[OpIdx].size() == 0 && "Already resized?"); 1632 Operands[OpIdx].resize(Scalars.size()); 1633 for (unsigned Lane = 0, E = Scalars.size(); Lane != E; ++Lane) 1634 Operands[OpIdx][Lane] = OpVL[Lane]; 1635 } 1636 1637 /// Set the operands of this bundle in their original order. 1638 void setOperandsInOrder() { 1639 assert(Operands.empty() && "Already initialized?"); 1640 auto *I0 = cast<Instruction>(Scalars[0]); 1641 Operands.resize(I0->getNumOperands()); 1642 unsigned NumLanes = Scalars.size(); 1643 for (unsigned OpIdx = 0, NumOperands = I0->getNumOperands(); 1644 OpIdx != NumOperands; ++OpIdx) { 1645 Operands[OpIdx].resize(NumLanes); 1646 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { 1647 auto *I = cast<Instruction>(Scalars[Lane]); 1648 assert(I->getNumOperands() == NumOperands && 1649 "Expected same number of operands"); 1650 Operands[OpIdx][Lane] = I->getOperand(OpIdx); 1651 } 1652 } 1653 } 1654 1655 /// \returns the \p OpIdx operand of this TreeEntry. 1656 ValueList &getOperand(unsigned OpIdx) { 1657 assert(OpIdx < Operands.size() && "Off bounds"); 1658 return Operands[OpIdx]; 1659 } 1660 1661 /// \returns the number of operands. 1662 unsigned getNumOperands() const { return Operands.size(); } 1663 1664 /// \return the single \p OpIdx operand. 1665 Value *getSingleOperand(unsigned OpIdx) const { 1666 assert(OpIdx < Operands.size() && "Off bounds"); 1667 assert(!Operands[OpIdx].empty() && "No operand available"); 1668 return Operands[OpIdx][0]; 1669 } 1670 1671 /// Some of the instructions in the list have alternate opcodes. 1672 bool isAltShuffle() const { 1673 return getOpcode() != getAltOpcode(); 1674 } 1675 1676 bool isOpcodeOrAlt(Instruction *I) const { 1677 unsigned CheckedOpcode = I->getOpcode(); 1678 return (getOpcode() == CheckedOpcode || 1679 getAltOpcode() == CheckedOpcode); 1680 } 1681 1682 /// Chooses the correct key for scheduling data. If \p Op has the same (or 1683 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is 1684 /// \p OpValue. 1685 Value *isOneOf(Value *Op) const { 1686 auto *I = dyn_cast<Instruction>(Op); 1687 if (I && isOpcodeOrAlt(I)) 1688 return Op; 1689 return MainOp; 1690 } 1691 1692 void setOperations(const InstructionsState &S) { 1693 MainOp = S.MainOp; 1694 AltOp = S.AltOp; 1695 } 1696 1697 Instruction *getMainOp() const { 1698 return MainOp; 1699 } 1700 1701 Instruction *getAltOp() const { 1702 return AltOp; 1703 } 1704 1705 /// The main/alternate opcodes for the list of instructions. 1706 unsigned getOpcode() const { 1707 return MainOp ? MainOp->getOpcode() : 0; 1708 } 1709 1710 unsigned getAltOpcode() const { 1711 return AltOp ? AltOp->getOpcode() : 0; 1712 } 1713 1714 /// Update operations state of this entry if reorder occurred. 1715 bool updateStateIfReorder() { 1716 if (ReorderIndices.empty()) 1717 return false; 1718 InstructionsState S = getSameOpcode(Scalars, ReorderIndices.front()); 1719 setOperations(S); 1720 return true; 1721 } 1722 1723 #ifndef NDEBUG 1724 /// Debug printer. 1725 LLVM_DUMP_METHOD void dump() const { 1726 dbgs() << Idx << ".\n"; 1727 for (unsigned OpI = 0, OpE = Operands.size(); OpI != OpE; ++OpI) { 1728 dbgs() << "Operand " << OpI << ":\n"; 1729 for (const Value *V : Operands[OpI]) 1730 dbgs().indent(2) << *V << "\n"; 1731 } 1732 dbgs() << "Scalars: \n"; 1733 for (Value *V : Scalars) 1734 dbgs().indent(2) << *V << "\n"; 1735 dbgs() << "State: "; 1736 switch (State) { 1737 case Vectorize: 1738 dbgs() << "Vectorize\n"; 1739 break; 1740 case ScatterVectorize: 1741 dbgs() << "ScatterVectorize\n"; 1742 break; 1743 case NeedToGather: 1744 dbgs() << "NeedToGather\n"; 1745 break; 1746 } 1747 dbgs() << "MainOp: "; 1748 if (MainOp) 1749 dbgs() << *MainOp << "\n"; 1750 else 1751 dbgs() << "NULL\n"; 1752 dbgs() << "AltOp: "; 1753 if (AltOp) 1754 dbgs() << *AltOp << "\n"; 1755 else 1756 dbgs() << "NULL\n"; 1757 dbgs() << "VectorizedValue: "; 1758 if (VectorizedValue) 1759 dbgs() << *VectorizedValue << "\n"; 1760 else 1761 dbgs() << "NULL\n"; 1762 dbgs() << "ReuseShuffleIndices: "; 1763 if (ReuseShuffleIndices.empty()) 1764 dbgs() << "Empty"; 1765 else 1766 for (unsigned ReuseIdx : ReuseShuffleIndices) 1767 dbgs() << ReuseIdx << ", "; 1768 dbgs() << "\n"; 1769 dbgs() << "ReorderIndices: "; 1770 for (unsigned ReorderIdx : ReorderIndices) 1771 dbgs() << ReorderIdx << ", "; 1772 dbgs() << "\n"; 1773 dbgs() << "UserTreeIndices: "; 1774 for (const auto &EInfo : UserTreeIndices) 1775 dbgs() << EInfo << ", "; 1776 dbgs() << "\n"; 1777 } 1778 #endif 1779 }; 1780 1781 #ifndef NDEBUG 1782 void dumpTreeCosts(TreeEntry *E, InstructionCost ReuseShuffleCost, 1783 InstructionCost VecCost, 1784 InstructionCost ScalarCost) const { 1785 dbgs() << "SLP: Calculated costs for Tree:\n"; E->dump(); 1786 dbgs() << "SLP: Costs:\n"; 1787 dbgs() << "SLP: ReuseShuffleCost = " << ReuseShuffleCost << "\n"; 1788 dbgs() << "SLP: VectorCost = " << VecCost << "\n"; 1789 dbgs() << "SLP: ScalarCost = " << ScalarCost << "\n"; 1790 dbgs() << "SLP: ReuseShuffleCost + VecCost - ScalarCost = " << 1791 ReuseShuffleCost + VecCost - ScalarCost << "\n"; 1792 } 1793 #endif 1794 1795 /// Create a new VectorizableTree entry. 1796 TreeEntry *newTreeEntry(ArrayRef<Value *> VL, Optional<ScheduleData *> Bundle, 1797 const InstructionsState &S, 1798 const EdgeInfo &UserTreeIdx, 1799 ArrayRef<unsigned> ReuseShuffleIndices = None, 1800 ArrayRef<unsigned> ReorderIndices = None) { 1801 TreeEntry::EntryState EntryState = 1802 Bundle ? TreeEntry::Vectorize : TreeEntry::NeedToGather; 1803 return newTreeEntry(VL, EntryState, Bundle, S, UserTreeIdx, 1804 ReuseShuffleIndices, ReorderIndices); 1805 } 1806 1807 TreeEntry *newTreeEntry(ArrayRef<Value *> VL, 1808 TreeEntry::EntryState EntryState, 1809 Optional<ScheduleData *> Bundle, 1810 const InstructionsState &S, 1811 const EdgeInfo &UserTreeIdx, 1812 ArrayRef<unsigned> ReuseShuffleIndices = None, 1813 ArrayRef<unsigned> ReorderIndices = None) { 1814 assert(((!Bundle && EntryState == TreeEntry::NeedToGather) || 1815 (Bundle && EntryState != TreeEntry::NeedToGather)) && 1816 "Need to vectorize gather entry?"); 1817 VectorizableTree.push_back(std::make_unique<TreeEntry>(VectorizableTree)); 1818 TreeEntry *Last = VectorizableTree.back().get(); 1819 Last->Idx = VectorizableTree.size() - 1; 1820 Last->Scalars.insert(Last->Scalars.begin(), VL.begin(), VL.end()); 1821 Last->State = EntryState; 1822 Last->ReuseShuffleIndices.append(ReuseShuffleIndices.begin(), 1823 ReuseShuffleIndices.end()); 1824 Last->ReorderIndices.append(ReorderIndices.begin(), ReorderIndices.end()); 1825 Last->setOperations(S); 1826 if (Last->State != TreeEntry::NeedToGather) { 1827 for (Value *V : VL) { 1828 assert(!getTreeEntry(V) && "Scalar already in tree!"); 1829 ScalarToTreeEntry[V] = Last; 1830 } 1831 // Update the scheduler bundle to point to this TreeEntry. 1832 unsigned Lane = 0; 1833 for (ScheduleData *BundleMember = Bundle.getValue(); BundleMember; 1834 BundleMember = BundleMember->NextInBundle) { 1835 BundleMember->TE = Last; 1836 BundleMember->Lane = Lane; 1837 ++Lane; 1838 } 1839 assert((!Bundle.getValue() || Lane == VL.size()) && 1840 "Bundle and VL out of sync"); 1841 } else { 1842 MustGather.insert(VL.begin(), VL.end()); 1843 } 1844 1845 if (UserTreeIdx.UserTE) 1846 Last->UserTreeIndices.push_back(UserTreeIdx); 1847 1848 return Last; 1849 } 1850 1851 /// -- Vectorization State -- 1852 /// Holds all of the tree entries. 1853 TreeEntry::VecTreeTy VectorizableTree; 1854 1855 #ifndef NDEBUG 1856 /// Debug printer. 1857 LLVM_DUMP_METHOD void dumpVectorizableTree() const { 1858 for (unsigned Id = 0, IdE = VectorizableTree.size(); Id != IdE; ++Id) { 1859 VectorizableTree[Id]->dump(); 1860 dbgs() << "\n"; 1861 } 1862 } 1863 #endif 1864 1865 TreeEntry *getTreeEntry(Value *V) { return ScalarToTreeEntry.lookup(V); } 1866 1867 const TreeEntry *getTreeEntry(Value *V) const { 1868 return ScalarToTreeEntry.lookup(V); 1869 } 1870 1871 /// Maps a specific scalar to its tree entry. 1872 SmallDenseMap<Value*, TreeEntry *> ScalarToTreeEntry; 1873 1874 /// Maps a value to the proposed vectorizable size. 1875 SmallDenseMap<Value *, unsigned> InstrElementSize; 1876 1877 /// A list of scalars that we found that we need to keep as scalars. 1878 ValueSet MustGather; 1879 1880 /// This POD struct describes one external user in the vectorized tree. 1881 struct ExternalUser { 1882 ExternalUser(Value *S, llvm::User *U, int L) 1883 : Scalar(S), User(U), Lane(L) {} 1884 1885 // Which scalar in our function. 1886 Value *Scalar; 1887 1888 // Which user that uses the scalar. 1889 llvm::User *User; 1890 1891 // Which lane does the scalar belong to. 1892 int Lane; 1893 }; 1894 using UserList = SmallVector<ExternalUser, 16>; 1895 1896 /// Checks if two instructions may access the same memory. 1897 /// 1898 /// \p Loc1 is the location of \p Inst1. It is passed explicitly because it 1899 /// is invariant in the calling loop. 1900 bool isAliased(const MemoryLocation &Loc1, Instruction *Inst1, 1901 Instruction *Inst2) { 1902 // First check if the result is already in the cache. 1903 AliasCacheKey key = std::make_pair(Inst1, Inst2); 1904 Optional<bool> &result = AliasCache[key]; 1905 if (result.hasValue()) { 1906 return result.getValue(); 1907 } 1908 MemoryLocation Loc2 = getLocation(Inst2, AA); 1909 bool aliased = true; 1910 if (Loc1.Ptr && Loc2.Ptr && isSimple(Inst1) && isSimple(Inst2)) { 1911 // Do the alias check. 1912 aliased = !AA->isNoAlias(Loc1, Loc2); 1913 } 1914 // Store the result in the cache. 1915 result = aliased; 1916 return aliased; 1917 } 1918 1919 using AliasCacheKey = std::pair<Instruction *, Instruction *>; 1920 1921 /// Cache for alias results. 1922 /// TODO: consider moving this to the AliasAnalysis itself. 1923 DenseMap<AliasCacheKey, Optional<bool>> AliasCache; 1924 1925 /// Removes an instruction from its block and eventually deletes it. 1926 /// It's like Instruction::eraseFromParent() except that the actual deletion 1927 /// is delayed until BoUpSLP is destructed. 1928 /// This is required to ensure that there are no incorrect collisions in the 1929 /// AliasCache, which can happen if a new instruction is allocated at the 1930 /// same address as a previously deleted instruction. 1931 void eraseInstruction(Instruction *I, bool ReplaceOpsWithUndef = false) { 1932 auto It = DeletedInstructions.try_emplace(I, ReplaceOpsWithUndef).first; 1933 It->getSecond() = It->getSecond() && ReplaceOpsWithUndef; 1934 } 1935 1936 /// Temporary store for deleted instructions. Instructions will be deleted 1937 /// eventually when the BoUpSLP is destructed. 1938 DenseMap<Instruction *, bool> DeletedInstructions; 1939 1940 /// A list of values that need to extracted out of the tree. 1941 /// This list holds pairs of (Internal Scalar : External User). External User 1942 /// can be nullptr, it means that this Internal Scalar will be used later, 1943 /// after vectorization. 1944 UserList ExternalUses; 1945 1946 /// Values used only by @llvm.assume calls. 1947 SmallPtrSet<const Value *, 32> EphValues; 1948 1949 /// Holds all of the instructions that we gathered. 1950 SetVector<Instruction *> GatherSeq; 1951 1952 /// A list of blocks that we are going to CSE. 1953 SetVector<BasicBlock *> CSEBlocks; 1954 1955 /// Contains all scheduling relevant data for an instruction. 1956 /// A ScheduleData either represents a single instruction or a member of an 1957 /// instruction bundle (= a group of instructions which is combined into a 1958 /// vector instruction). 1959 struct ScheduleData { 1960 // The initial value for the dependency counters. It means that the 1961 // dependencies are not calculated yet. 1962 enum { InvalidDeps = -1 }; 1963 1964 ScheduleData() = default; 1965 1966 void init(int BlockSchedulingRegionID, Value *OpVal) { 1967 FirstInBundle = this; 1968 NextInBundle = nullptr; 1969 NextLoadStore = nullptr; 1970 IsScheduled = false; 1971 SchedulingRegionID = BlockSchedulingRegionID; 1972 UnscheduledDepsInBundle = UnscheduledDeps; 1973 clearDependencies(); 1974 OpValue = OpVal; 1975 TE = nullptr; 1976 Lane = -1; 1977 } 1978 1979 /// Returns true if the dependency information has been calculated. 1980 bool hasValidDependencies() const { return Dependencies != InvalidDeps; } 1981 1982 /// Returns true for single instructions and for bundle representatives 1983 /// (= the head of a bundle). 1984 bool isSchedulingEntity() const { return FirstInBundle == this; } 1985 1986 /// Returns true if it represents an instruction bundle and not only a 1987 /// single instruction. 1988 bool isPartOfBundle() const { 1989 return NextInBundle != nullptr || FirstInBundle != this; 1990 } 1991 1992 /// Returns true if it is ready for scheduling, i.e. it has no more 1993 /// unscheduled depending instructions/bundles. 1994 bool isReady() const { 1995 assert(isSchedulingEntity() && 1996 "can't consider non-scheduling entity for ready list"); 1997 return UnscheduledDepsInBundle == 0 && !IsScheduled; 1998 } 1999 2000 /// Modifies the number of unscheduled dependencies, also updating it for 2001 /// the whole bundle. 2002 int incrementUnscheduledDeps(int Incr) { 2003 UnscheduledDeps += Incr; 2004 return FirstInBundle->UnscheduledDepsInBundle += Incr; 2005 } 2006 2007 /// Sets the number of unscheduled dependencies to the number of 2008 /// dependencies. 2009 void resetUnscheduledDeps() { 2010 incrementUnscheduledDeps(Dependencies - UnscheduledDeps); 2011 } 2012 2013 /// Clears all dependency information. 2014 void clearDependencies() { 2015 Dependencies = InvalidDeps; 2016 resetUnscheduledDeps(); 2017 MemoryDependencies.clear(); 2018 } 2019 2020 void dump(raw_ostream &os) const { 2021 if (!isSchedulingEntity()) { 2022 os << "/ " << *Inst; 2023 } else if (NextInBundle) { 2024 os << '[' << *Inst; 2025 ScheduleData *SD = NextInBundle; 2026 while (SD) { 2027 os << ';' << *SD->Inst; 2028 SD = SD->NextInBundle; 2029 } 2030 os << ']'; 2031 } else { 2032 os << *Inst; 2033 } 2034 } 2035 2036 Instruction *Inst = nullptr; 2037 2038 /// Points to the head in an instruction bundle (and always to this for 2039 /// single instructions). 2040 ScheduleData *FirstInBundle = nullptr; 2041 2042 /// Single linked list of all instructions in a bundle. Null if it is a 2043 /// single instruction. 2044 ScheduleData *NextInBundle = nullptr; 2045 2046 /// Single linked list of all memory instructions (e.g. load, store, call) 2047 /// in the block - until the end of the scheduling region. 2048 ScheduleData *NextLoadStore = nullptr; 2049 2050 /// The dependent memory instructions. 2051 /// This list is derived on demand in calculateDependencies(). 2052 SmallVector<ScheduleData *, 4> MemoryDependencies; 2053 2054 /// This ScheduleData is in the current scheduling region if this matches 2055 /// the current SchedulingRegionID of BlockScheduling. 2056 int SchedulingRegionID = 0; 2057 2058 /// Used for getting a "good" final ordering of instructions. 2059 int SchedulingPriority = 0; 2060 2061 /// The number of dependencies. Constitutes of the number of users of the 2062 /// instruction plus the number of dependent memory instructions (if any). 2063 /// This value is calculated on demand. 2064 /// If InvalidDeps, the number of dependencies is not calculated yet. 2065 int Dependencies = InvalidDeps; 2066 2067 /// The number of dependencies minus the number of dependencies of scheduled 2068 /// instructions. As soon as this is zero, the instruction/bundle gets ready 2069 /// for scheduling. 2070 /// Note that this is negative as long as Dependencies is not calculated. 2071 int UnscheduledDeps = InvalidDeps; 2072 2073 /// The sum of UnscheduledDeps in a bundle. Equals to UnscheduledDeps for 2074 /// single instructions. 2075 int UnscheduledDepsInBundle = InvalidDeps; 2076 2077 /// True if this instruction is scheduled (or considered as scheduled in the 2078 /// dry-run). 2079 bool IsScheduled = false; 2080 2081 /// Opcode of the current instruction in the schedule data. 2082 Value *OpValue = nullptr; 2083 2084 /// The TreeEntry that this instruction corresponds to. 2085 TreeEntry *TE = nullptr; 2086 2087 /// The lane of this node in the TreeEntry. 2088 int Lane = -1; 2089 }; 2090 2091 #ifndef NDEBUG 2092 friend inline raw_ostream &operator<<(raw_ostream &os, 2093 const BoUpSLP::ScheduleData &SD) { 2094 SD.dump(os); 2095 return os; 2096 } 2097 #endif 2098 2099 friend struct GraphTraits<BoUpSLP *>; 2100 friend struct DOTGraphTraits<BoUpSLP *>; 2101 2102 /// Contains all scheduling data for a basic block. 2103 struct BlockScheduling { 2104 BlockScheduling(BasicBlock *BB) 2105 : BB(BB), ChunkSize(BB->size()), ChunkPos(ChunkSize) {} 2106 2107 void clear() { 2108 ReadyInsts.clear(); 2109 ScheduleStart = nullptr; 2110 ScheduleEnd = nullptr; 2111 FirstLoadStoreInRegion = nullptr; 2112 LastLoadStoreInRegion = nullptr; 2113 2114 // Reduce the maximum schedule region size by the size of the 2115 // previous scheduling run. 2116 ScheduleRegionSizeLimit -= ScheduleRegionSize; 2117 if (ScheduleRegionSizeLimit < MinScheduleRegionSize) 2118 ScheduleRegionSizeLimit = MinScheduleRegionSize; 2119 ScheduleRegionSize = 0; 2120 2121 // Make a new scheduling region, i.e. all existing ScheduleData is not 2122 // in the new region yet. 2123 ++SchedulingRegionID; 2124 } 2125 2126 ScheduleData *getScheduleData(Value *V) { 2127 ScheduleData *SD = ScheduleDataMap[V]; 2128 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 2129 return SD; 2130 return nullptr; 2131 } 2132 2133 ScheduleData *getScheduleData(Value *V, Value *Key) { 2134 if (V == Key) 2135 return getScheduleData(V); 2136 auto I = ExtraScheduleDataMap.find(V); 2137 if (I != ExtraScheduleDataMap.end()) { 2138 ScheduleData *SD = I->second[Key]; 2139 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 2140 return SD; 2141 } 2142 return nullptr; 2143 } 2144 2145 bool isInSchedulingRegion(ScheduleData *SD) const { 2146 return SD->SchedulingRegionID == SchedulingRegionID; 2147 } 2148 2149 /// Marks an instruction as scheduled and puts all dependent ready 2150 /// instructions into the ready-list. 2151 template <typename ReadyListType> 2152 void schedule(ScheduleData *SD, ReadyListType &ReadyList) { 2153 SD->IsScheduled = true; 2154 LLVM_DEBUG(dbgs() << "SLP: schedule " << *SD << "\n"); 2155 2156 ScheduleData *BundleMember = SD; 2157 while (BundleMember) { 2158 if (BundleMember->Inst != BundleMember->OpValue) { 2159 BundleMember = BundleMember->NextInBundle; 2160 continue; 2161 } 2162 // Handle the def-use chain dependencies. 2163 2164 // Decrement the unscheduled counter and insert to ready list if ready. 2165 auto &&DecrUnsched = [this, &ReadyList](Instruction *I) { 2166 doForAllOpcodes(I, [&ReadyList](ScheduleData *OpDef) { 2167 if (OpDef && OpDef->hasValidDependencies() && 2168 OpDef->incrementUnscheduledDeps(-1) == 0) { 2169 // There are no more unscheduled dependencies after 2170 // decrementing, so we can put the dependent instruction 2171 // into the ready list. 2172 ScheduleData *DepBundle = OpDef->FirstInBundle; 2173 assert(!DepBundle->IsScheduled && 2174 "already scheduled bundle gets ready"); 2175 ReadyList.insert(DepBundle); 2176 LLVM_DEBUG(dbgs() 2177 << "SLP: gets ready (def): " << *DepBundle << "\n"); 2178 } 2179 }); 2180 }; 2181 2182 // If BundleMember is a vector bundle, its operands may have been 2183 // reordered duiring buildTree(). We therefore need to get its operands 2184 // through the TreeEntry. 2185 if (TreeEntry *TE = BundleMember->TE) { 2186 int Lane = BundleMember->Lane; 2187 assert(Lane >= 0 && "Lane not set"); 2188 2189 // Since vectorization tree is being built recursively this assertion 2190 // ensures that the tree entry has all operands set before reaching 2191 // this code. Couple of exceptions known at the moment are extracts 2192 // where their second (immediate) operand is not added. Since 2193 // immediates do not affect scheduler behavior this is considered 2194 // okay. 2195 auto *In = TE->getMainOp(); 2196 assert(In && 2197 (isa<ExtractValueInst>(In) || isa<ExtractElementInst>(In) || 2198 In->getNumOperands() == TE->getNumOperands()) && 2199 "Missed TreeEntry operands?"); 2200 (void)In; // fake use to avoid build failure when assertions disabled 2201 2202 for (unsigned OpIdx = 0, NumOperands = TE->getNumOperands(); 2203 OpIdx != NumOperands; ++OpIdx) 2204 if (auto *I = dyn_cast<Instruction>(TE->getOperand(OpIdx)[Lane])) 2205 DecrUnsched(I); 2206 } else { 2207 // If BundleMember is a stand-alone instruction, no operand reordering 2208 // has taken place, so we directly access its operands. 2209 for (Use &U : BundleMember->Inst->operands()) 2210 if (auto *I = dyn_cast<Instruction>(U.get())) 2211 DecrUnsched(I); 2212 } 2213 // Handle the memory dependencies. 2214 for (ScheduleData *MemoryDepSD : BundleMember->MemoryDependencies) { 2215 if (MemoryDepSD->incrementUnscheduledDeps(-1) == 0) { 2216 // There are no more unscheduled dependencies after decrementing, 2217 // so we can put the dependent instruction into the ready list. 2218 ScheduleData *DepBundle = MemoryDepSD->FirstInBundle; 2219 assert(!DepBundle->IsScheduled && 2220 "already scheduled bundle gets ready"); 2221 ReadyList.insert(DepBundle); 2222 LLVM_DEBUG(dbgs() 2223 << "SLP: gets ready (mem): " << *DepBundle << "\n"); 2224 } 2225 } 2226 BundleMember = BundleMember->NextInBundle; 2227 } 2228 } 2229 2230 void doForAllOpcodes(Value *V, 2231 function_ref<void(ScheduleData *SD)> Action) { 2232 if (ScheduleData *SD = getScheduleData(V)) 2233 Action(SD); 2234 auto I = ExtraScheduleDataMap.find(V); 2235 if (I != ExtraScheduleDataMap.end()) 2236 for (auto &P : I->second) 2237 if (P.second->SchedulingRegionID == SchedulingRegionID) 2238 Action(P.second); 2239 } 2240 2241 /// Put all instructions into the ReadyList which are ready for scheduling. 2242 template <typename ReadyListType> 2243 void initialFillReadyList(ReadyListType &ReadyList) { 2244 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 2245 doForAllOpcodes(I, [&](ScheduleData *SD) { 2246 if (SD->isSchedulingEntity() && SD->isReady()) { 2247 ReadyList.insert(SD); 2248 LLVM_DEBUG(dbgs() 2249 << "SLP: initially in ready list: " << *I << "\n"); 2250 } 2251 }); 2252 } 2253 } 2254 2255 /// Checks if a bundle of instructions can be scheduled, i.e. has no 2256 /// cyclic dependencies. This is only a dry-run, no instructions are 2257 /// actually moved at this stage. 2258 /// \returns the scheduling bundle. The returned Optional value is non-None 2259 /// if \p VL is allowed to be scheduled. 2260 Optional<ScheduleData *> 2261 tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 2262 const InstructionsState &S); 2263 2264 /// Un-bundles a group of instructions. 2265 void cancelScheduling(ArrayRef<Value *> VL, Value *OpValue); 2266 2267 /// Allocates schedule data chunk. 2268 ScheduleData *allocateScheduleDataChunks(); 2269 2270 /// Extends the scheduling region so that V is inside the region. 2271 /// \returns true if the region size is within the limit. 2272 bool extendSchedulingRegion(Value *V, const InstructionsState &S); 2273 2274 /// Initialize the ScheduleData structures for new instructions in the 2275 /// scheduling region. 2276 void initScheduleData(Instruction *FromI, Instruction *ToI, 2277 ScheduleData *PrevLoadStore, 2278 ScheduleData *NextLoadStore); 2279 2280 /// Updates the dependency information of a bundle and of all instructions/ 2281 /// bundles which depend on the original bundle. 2282 void calculateDependencies(ScheduleData *SD, bool InsertInReadyList, 2283 BoUpSLP *SLP); 2284 2285 /// Sets all instruction in the scheduling region to un-scheduled. 2286 void resetSchedule(); 2287 2288 BasicBlock *BB; 2289 2290 /// Simple memory allocation for ScheduleData. 2291 std::vector<std::unique_ptr<ScheduleData[]>> ScheduleDataChunks; 2292 2293 /// The size of a ScheduleData array in ScheduleDataChunks. 2294 int ChunkSize; 2295 2296 /// The allocator position in the current chunk, which is the last entry 2297 /// of ScheduleDataChunks. 2298 int ChunkPos; 2299 2300 /// Attaches ScheduleData to Instruction. 2301 /// Note that the mapping survives during all vectorization iterations, i.e. 2302 /// ScheduleData structures are recycled. 2303 DenseMap<Value *, ScheduleData *> ScheduleDataMap; 2304 2305 /// Attaches ScheduleData to Instruction with the leading key. 2306 DenseMap<Value *, SmallDenseMap<Value *, ScheduleData *>> 2307 ExtraScheduleDataMap; 2308 2309 struct ReadyList : SmallVector<ScheduleData *, 8> { 2310 void insert(ScheduleData *SD) { push_back(SD); } 2311 }; 2312 2313 /// The ready-list for scheduling (only used for the dry-run). 2314 ReadyList ReadyInsts; 2315 2316 /// The first instruction of the scheduling region. 2317 Instruction *ScheduleStart = nullptr; 2318 2319 /// The first instruction _after_ the scheduling region. 2320 Instruction *ScheduleEnd = nullptr; 2321 2322 /// The first memory accessing instruction in the scheduling region 2323 /// (can be null). 2324 ScheduleData *FirstLoadStoreInRegion = nullptr; 2325 2326 /// The last memory accessing instruction in the scheduling region 2327 /// (can be null). 2328 ScheduleData *LastLoadStoreInRegion = nullptr; 2329 2330 /// The current size of the scheduling region. 2331 int ScheduleRegionSize = 0; 2332 2333 /// The maximum size allowed for the scheduling region. 2334 int ScheduleRegionSizeLimit = ScheduleRegionSizeBudget; 2335 2336 /// The ID of the scheduling region. For a new vectorization iteration this 2337 /// is incremented which "removes" all ScheduleData from the region. 2338 // Make sure that the initial SchedulingRegionID is greater than the 2339 // initial SchedulingRegionID in ScheduleData (which is 0). 2340 int SchedulingRegionID = 1; 2341 }; 2342 2343 /// Attaches the BlockScheduling structures to basic blocks. 2344 MapVector<BasicBlock *, std::unique_ptr<BlockScheduling>> BlocksSchedules; 2345 2346 /// Performs the "real" scheduling. Done before vectorization is actually 2347 /// performed in a basic block. 2348 void scheduleBlock(BlockScheduling *BS); 2349 2350 /// List of users to ignore during scheduling and that don't need extracting. 2351 ArrayRef<Value *> UserIgnoreList; 2352 2353 /// A DenseMapInfo implementation for holding DenseMaps and DenseSets of 2354 /// sorted SmallVectors of unsigned. 2355 struct OrdersTypeDenseMapInfo { 2356 static OrdersType getEmptyKey() { 2357 OrdersType V; 2358 V.push_back(~1U); 2359 return V; 2360 } 2361 2362 static OrdersType getTombstoneKey() { 2363 OrdersType V; 2364 V.push_back(~2U); 2365 return V; 2366 } 2367 2368 static unsigned getHashValue(const OrdersType &V) { 2369 return static_cast<unsigned>(hash_combine_range(V.begin(), V.end())); 2370 } 2371 2372 static bool isEqual(const OrdersType &LHS, const OrdersType &RHS) { 2373 return LHS == RHS; 2374 } 2375 }; 2376 2377 /// Contains orders of operations along with the number of bundles that have 2378 /// operations in this order. It stores only those orders that require 2379 /// reordering, if reordering is not required it is counted using \a 2380 /// NumOpsWantToKeepOriginalOrder. 2381 DenseMap<OrdersType, unsigned, OrdersTypeDenseMapInfo> NumOpsWantToKeepOrder; 2382 /// Number of bundles that do not require reordering. 2383 unsigned NumOpsWantToKeepOriginalOrder = 0; 2384 2385 // Analysis and block reference. 2386 Function *F; 2387 ScalarEvolution *SE; 2388 TargetTransformInfo *TTI; 2389 TargetLibraryInfo *TLI; 2390 AAResults *AA; 2391 LoopInfo *LI; 2392 DominatorTree *DT; 2393 AssumptionCache *AC; 2394 DemandedBits *DB; 2395 const DataLayout *DL; 2396 OptimizationRemarkEmitter *ORE; 2397 2398 unsigned MaxVecRegSize; // This is set by TTI or overridden by cl::opt. 2399 unsigned MinVecRegSize; // Set by cl::opt (default: 128). 2400 2401 /// Instruction builder to construct the vectorized tree. 2402 IRBuilder<> Builder; 2403 2404 /// A map of scalar integer values to the smallest bit width with which they 2405 /// can legally be represented. The values map to (width, signed) pairs, 2406 /// where "width" indicates the minimum bit width and "signed" is True if the 2407 /// value must be signed-extended, rather than zero-extended, back to its 2408 /// original width. 2409 MapVector<Value *, std::pair<uint64_t, bool>> MinBWs; 2410 }; 2411 2412 } // end namespace slpvectorizer 2413 2414 template <> struct GraphTraits<BoUpSLP *> { 2415 using TreeEntry = BoUpSLP::TreeEntry; 2416 2417 /// NodeRef has to be a pointer per the GraphWriter. 2418 using NodeRef = TreeEntry *; 2419 2420 using ContainerTy = BoUpSLP::TreeEntry::VecTreeTy; 2421 2422 /// Add the VectorizableTree to the index iterator to be able to return 2423 /// TreeEntry pointers. 2424 struct ChildIteratorType 2425 : public iterator_adaptor_base< 2426 ChildIteratorType, SmallVector<BoUpSLP::EdgeInfo, 1>::iterator> { 2427 ContainerTy &VectorizableTree; 2428 2429 ChildIteratorType(SmallVector<BoUpSLP::EdgeInfo, 1>::iterator W, 2430 ContainerTy &VT) 2431 : ChildIteratorType::iterator_adaptor_base(W), VectorizableTree(VT) {} 2432 2433 NodeRef operator*() { return I->UserTE; } 2434 }; 2435 2436 static NodeRef getEntryNode(BoUpSLP &R) { 2437 return R.VectorizableTree[0].get(); 2438 } 2439 2440 static ChildIteratorType child_begin(NodeRef N) { 2441 return {N->UserTreeIndices.begin(), N->Container}; 2442 } 2443 2444 static ChildIteratorType child_end(NodeRef N) { 2445 return {N->UserTreeIndices.end(), N->Container}; 2446 } 2447 2448 /// For the node iterator we just need to turn the TreeEntry iterator into a 2449 /// TreeEntry* iterator so that it dereferences to NodeRef. 2450 class nodes_iterator { 2451 using ItTy = ContainerTy::iterator; 2452 ItTy It; 2453 2454 public: 2455 nodes_iterator(const ItTy &It2) : It(It2) {} 2456 NodeRef operator*() { return It->get(); } 2457 nodes_iterator operator++() { 2458 ++It; 2459 return *this; 2460 } 2461 bool operator!=(const nodes_iterator &N2) const { return N2.It != It; } 2462 }; 2463 2464 static nodes_iterator nodes_begin(BoUpSLP *R) { 2465 return nodes_iterator(R->VectorizableTree.begin()); 2466 } 2467 2468 static nodes_iterator nodes_end(BoUpSLP *R) { 2469 return nodes_iterator(R->VectorizableTree.end()); 2470 } 2471 2472 static unsigned size(BoUpSLP *R) { return R->VectorizableTree.size(); } 2473 }; 2474 2475 template <> struct DOTGraphTraits<BoUpSLP *> : public DefaultDOTGraphTraits { 2476 using TreeEntry = BoUpSLP::TreeEntry; 2477 2478 DOTGraphTraits(bool isSimple = false) : DefaultDOTGraphTraits(isSimple) {} 2479 2480 std::string getNodeLabel(const TreeEntry *Entry, const BoUpSLP *R) { 2481 std::string Str; 2482 raw_string_ostream OS(Str); 2483 if (isSplat(Entry->Scalars)) { 2484 OS << "<splat> " << *Entry->Scalars[0]; 2485 return Str; 2486 } 2487 for (auto V : Entry->Scalars) { 2488 OS << *V; 2489 if (llvm::any_of(R->ExternalUses, [&](const BoUpSLP::ExternalUser &EU) { 2490 return EU.Scalar == V; 2491 })) 2492 OS << " <extract>"; 2493 OS << "\n"; 2494 } 2495 return Str; 2496 } 2497 2498 static std::string getNodeAttributes(const TreeEntry *Entry, 2499 const BoUpSLP *) { 2500 if (Entry->State == TreeEntry::NeedToGather) 2501 return "color=red"; 2502 return ""; 2503 } 2504 }; 2505 2506 } // end namespace llvm 2507 2508 BoUpSLP::~BoUpSLP() { 2509 for (const auto &Pair : DeletedInstructions) { 2510 // Replace operands of ignored instructions with Undefs in case if they were 2511 // marked for deletion. 2512 if (Pair.getSecond()) { 2513 Value *Undef = UndefValue::get(Pair.getFirst()->getType()); 2514 Pair.getFirst()->replaceAllUsesWith(Undef); 2515 } 2516 Pair.getFirst()->dropAllReferences(); 2517 } 2518 for (const auto &Pair : DeletedInstructions) { 2519 assert(Pair.getFirst()->use_empty() && 2520 "trying to erase instruction with users."); 2521 Pair.getFirst()->eraseFromParent(); 2522 } 2523 #ifdef EXPENSIVE_CHECKS 2524 // If we could guarantee that this call is not extremely slow, we could 2525 // remove the ifdef limitation (see PR47712). 2526 assert(!verifyFunction(*F, &dbgs())); 2527 #endif 2528 } 2529 2530 void BoUpSLP::eraseInstructions(ArrayRef<Value *> AV) { 2531 for (auto *V : AV) { 2532 if (auto *I = dyn_cast<Instruction>(V)) 2533 eraseInstruction(I, /*ReplaceOpsWithUndef=*/true); 2534 }; 2535 } 2536 2537 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2538 ArrayRef<Value *> UserIgnoreLst) { 2539 ExtraValueToDebugLocsMap ExternallyUsedValues; 2540 buildTree(Roots, ExternallyUsedValues, UserIgnoreLst); 2541 } 2542 2543 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2544 ExtraValueToDebugLocsMap &ExternallyUsedValues, 2545 ArrayRef<Value *> UserIgnoreLst) { 2546 deleteTree(); 2547 UserIgnoreList = UserIgnoreLst; 2548 if (!allSameType(Roots)) 2549 return; 2550 buildTree_rec(Roots, 0, EdgeInfo()); 2551 2552 // Collect the values that we need to extract from the tree. 2553 for (auto &TEPtr : VectorizableTree) { 2554 TreeEntry *Entry = TEPtr.get(); 2555 2556 // No need to handle users of gathered values. 2557 if (Entry->State == TreeEntry::NeedToGather) 2558 continue; 2559 2560 // For each lane: 2561 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 2562 Value *Scalar = Entry->Scalars[Lane]; 2563 int FoundLane = Lane; 2564 if (!Entry->ReuseShuffleIndices.empty()) { 2565 FoundLane = 2566 std::distance(Entry->ReuseShuffleIndices.begin(), 2567 llvm::find(Entry->ReuseShuffleIndices, FoundLane)); 2568 } 2569 2570 // Check if the scalar is externally used as an extra arg. 2571 auto ExtI = ExternallyUsedValues.find(Scalar); 2572 if (ExtI != ExternallyUsedValues.end()) { 2573 LLVM_DEBUG(dbgs() << "SLP: Need to extract: Extra arg from lane " 2574 << Lane << " from " << *Scalar << ".\n"); 2575 ExternalUses.emplace_back(Scalar, nullptr, FoundLane); 2576 } 2577 for (User *U : Scalar->users()) { 2578 LLVM_DEBUG(dbgs() << "SLP: Checking user:" << *U << ".\n"); 2579 2580 Instruction *UserInst = dyn_cast<Instruction>(U); 2581 if (!UserInst) 2582 continue; 2583 2584 // Skip in-tree scalars that become vectors 2585 if (TreeEntry *UseEntry = getTreeEntry(U)) { 2586 Value *UseScalar = UseEntry->Scalars[0]; 2587 // Some in-tree scalars will remain as scalar in vectorized 2588 // instructions. If that is the case, the one in Lane 0 will 2589 // be used. 2590 if (UseScalar != U || 2591 UseEntry->State == TreeEntry::ScatterVectorize || 2592 !InTreeUserNeedToExtract(Scalar, UserInst, TLI)) { 2593 LLVM_DEBUG(dbgs() << "SLP: \tInternal user will be removed:" << *U 2594 << ".\n"); 2595 assert(UseEntry->State != TreeEntry::NeedToGather && "Bad state"); 2596 continue; 2597 } 2598 } 2599 2600 // Ignore users in the user ignore list. 2601 if (is_contained(UserIgnoreList, UserInst)) 2602 continue; 2603 2604 LLVM_DEBUG(dbgs() << "SLP: Need to extract:" << *U << " from lane " 2605 << Lane << " from " << *Scalar << ".\n"); 2606 ExternalUses.push_back(ExternalUser(Scalar, U, FoundLane)); 2607 } 2608 } 2609 } 2610 } 2611 2612 void BoUpSLP::buildTree_rec(ArrayRef<Value *> VL, unsigned Depth, 2613 const EdgeInfo &UserTreeIdx) { 2614 assert((allConstant(VL) || allSameType(VL)) && "Invalid types!"); 2615 2616 InstructionsState S = getSameOpcode(VL); 2617 if (Depth == RecursionMaxDepth) { 2618 LLVM_DEBUG(dbgs() << "SLP: Gathering due to max recursion depth.\n"); 2619 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2620 return; 2621 } 2622 2623 // Don't handle vectors. 2624 if (S.OpValue->getType()->isVectorTy()) { 2625 LLVM_DEBUG(dbgs() << "SLP: Gathering due to vector type.\n"); 2626 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2627 return; 2628 } 2629 2630 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) 2631 if (SI->getValueOperand()->getType()->isVectorTy()) { 2632 LLVM_DEBUG(dbgs() << "SLP: Gathering due to store vector type.\n"); 2633 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2634 return; 2635 } 2636 2637 // If all of the operands are identical or constant we have a simple solution. 2638 if (allConstant(VL) || isSplat(VL) || !allSameBlock(VL) || !S.getOpcode()) { 2639 LLVM_DEBUG(dbgs() << "SLP: Gathering due to C,S,B,O. \n"); 2640 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2641 return; 2642 } 2643 2644 // We now know that this is a vector of instructions of the same type from 2645 // the same block. 2646 2647 // Don't vectorize ephemeral values. 2648 for (Value *V : VL) { 2649 if (EphValues.count(V)) { 2650 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2651 << ") is ephemeral.\n"); 2652 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2653 return; 2654 } 2655 } 2656 2657 // Check if this is a duplicate of another entry. 2658 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 2659 LLVM_DEBUG(dbgs() << "SLP: \tChecking bundle: " << *S.OpValue << ".\n"); 2660 if (!E->isSame(VL)) { 2661 LLVM_DEBUG(dbgs() << "SLP: Gathering due to partial overlap.\n"); 2662 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2663 return; 2664 } 2665 // Record the reuse of the tree node. FIXME, currently this is only used to 2666 // properly draw the graph rather than for the actual vectorization. 2667 E->UserTreeIndices.push_back(UserTreeIdx); 2668 LLVM_DEBUG(dbgs() << "SLP: Perfect diamond merge at " << *S.OpValue 2669 << ".\n"); 2670 return; 2671 } 2672 2673 // Check that none of the instructions in the bundle are already in the tree. 2674 for (Value *V : VL) { 2675 auto *I = dyn_cast<Instruction>(V); 2676 if (!I) 2677 continue; 2678 if (getTreeEntry(I)) { 2679 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2680 << ") is already in tree.\n"); 2681 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2682 return; 2683 } 2684 } 2685 2686 // If any of the scalars is marked as a value that needs to stay scalar, then 2687 // we need to gather the scalars. 2688 // The reduction nodes (stored in UserIgnoreList) also should stay scalar. 2689 for (Value *V : VL) { 2690 if (MustGather.count(V) || is_contained(UserIgnoreList, V)) { 2691 LLVM_DEBUG(dbgs() << "SLP: Gathering due to gathered scalar.\n"); 2692 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2693 return; 2694 } 2695 } 2696 2697 // Check that all of the users of the scalars that we want to vectorize are 2698 // schedulable. 2699 auto *VL0 = cast<Instruction>(S.OpValue); 2700 BasicBlock *BB = VL0->getParent(); 2701 2702 if (!DT->isReachableFromEntry(BB)) { 2703 // Don't go into unreachable blocks. They may contain instructions with 2704 // dependency cycles which confuse the final scheduling. 2705 LLVM_DEBUG(dbgs() << "SLP: bundle in unreachable block.\n"); 2706 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2707 return; 2708 } 2709 2710 // Check that every instruction appears once in this bundle. 2711 SmallVector<unsigned, 4> ReuseShuffleIndicies; 2712 SmallVector<Value *, 4> UniqueValues; 2713 DenseMap<Value *, unsigned> UniquePositions; 2714 for (Value *V : VL) { 2715 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 2716 ReuseShuffleIndicies.emplace_back(Res.first->second); 2717 if (Res.second) 2718 UniqueValues.emplace_back(V); 2719 } 2720 size_t NumUniqueScalarValues = UniqueValues.size(); 2721 if (NumUniqueScalarValues == VL.size()) { 2722 ReuseShuffleIndicies.clear(); 2723 } else { 2724 LLVM_DEBUG(dbgs() << "SLP: Shuffle for reused scalars.\n"); 2725 if (NumUniqueScalarValues <= 1 || 2726 !llvm::isPowerOf2_32(NumUniqueScalarValues)) { 2727 LLVM_DEBUG(dbgs() << "SLP: Scalar used twice in bundle.\n"); 2728 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2729 return; 2730 } 2731 VL = UniqueValues; 2732 } 2733 2734 auto &BSRef = BlocksSchedules[BB]; 2735 if (!BSRef) 2736 BSRef = std::make_unique<BlockScheduling>(BB); 2737 2738 BlockScheduling &BS = *BSRef.get(); 2739 2740 Optional<ScheduleData *> Bundle = BS.tryScheduleBundle(VL, this, S); 2741 if (!Bundle) { 2742 LLVM_DEBUG(dbgs() << "SLP: We are not able to schedule this bundle!\n"); 2743 assert((!BS.getScheduleData(VL0) || 2744 !BS.getScheduleData(VL0)->isPartOfBundle()) && 2745 "tryScheduleBundle should cancelScheduling on failure"); 2746 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2747 ReuseShuffleIndicies); 2748 return; 2749 } 2750 LLVM_DEBUG(dbgs() << "SLP: We are able to schedule this bundle.\n"); 2751 2752 unsigned ShuffleOrOp = S.isAltShuffle() ? 2753 (unsigned) Instruction::ShuffleVector : S.getOpcode(); 2754 switch (ShuffleOrOp) { 2755 case Instruction::PHI: { 2756 auto *PH = cast<PHINode>(VL0); 2757 2758 // Check for terminator values (e.g. invoke). 2759 for (Value *V : VL) 2760 for (unsigned I = 0, E = PH->getNumIncomingValues(); I < E; ++I) { 2761 Instruction *Term = dyn_cast<Instruction>( 2762 cast<PHINode>(V)->getIncomingValueForBlock( 2763 PH->getIncomingBlock(I))); 2764 if (Term && Term->isTerminator()) { 2765 LLVM_DEBUG(dbgs() 2766 << "SLP: Need to swizzle PHINodes (terminator use).\n"); 2767 BS.cancelScheduling(VL, VL0); 2768 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2769 ReuseShuffleIndicies); 2770 return; 2771 } 2772 } 2773 2774 TreeEntry *TE = 2775 newTreeEntry(VL, Bundle, S, UserTreeIdx, ReuseShuffleIndicies); 2776 LLVM_DEBUG(dbgs() << "SLP: added a vector of PHINodes.\n"); 2777 2778 // Keeps the reordered operands to avoid code duplication. 2779 SmallVector<ValueList, 2> OperandsVec; 2780 for (unsigned I = 0, E = PH->getNumIncomingValues(); I < E; ++I) { 2781 ValueList Operands; 2782 // Prepare the operand vector. 2783 for (Value *V : VL) 2784 Operands.push_back(cast<PHINode>(V)->getIncomingValueForBlock( 2785 PH->getIncomingBlock(I))); 2786 TE->setOperand(I, Operands); 2787 OperandsVec.push_back(Operands); 2788 } 2789 for (unsigned OpIdx = 0, OpE = OperandsVec.size(); OpIdx != OpE; ++OpIdx) 2790 buildTree_rec(OperandsVec[OpIdx], Depth + 1, {TE, OpIdx}); 2791 return; 2792 } 2793 case Instruction::ExtractValue: 2794 case Instruction::ExtractElement: { 2795 OrdersType CurrentOrder; 2796 bool Reuse = canReuseExtract(VL, VL0, CurrentOrder); 2797 if (Reuse) { 2798 LLVM_DEBUG(dbgs() << "SLP: Reusing or shuffling extract sequence.\n"); 2799 ++NumOpsWantToKeepOriginalOrder; 2800 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2801 ReuseShuffleIndicies); 2802 // This is a special case, as it does not gather, but at the same time 2803 // we are not extending buildTree_rec() towards the operands. 2804 ValueList Op0; 2805 Op0.assign(VL.size(), VL0->getOperand(0)); 2806 VectorizableTree.back()->setOperand(0, Op0); 2807 return; 2808 } 2809 if (!CurrentOrder.empty()) { 2810 LLVM_DEBUG({ 2811 dbgs() << "SLP: Reusing or shuffling of reordered extract sequence " 2812 "with order"; 2813 for (unsigned Idx : CurrentOrder) 2814 dbgs() << " " << Idx; 2815 dbgs() << "\n"; 2816 }); 2817 // Insert new order with initial value 0, if it does not exist, 2818 // otherwise return the iterator to the existing one. 2819 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2820 ReuseShuffleIndicies, CurrentOrder); 2821 findRootOrder(CurrentOrder); 2822 ++NumOpsWantToKeepOrder[CurrentOrder]; 2823 // This is a special case, as it does not gather, but at the same time 2824 // we are not extending buildTree_rec() towards the operands. 2825 ValueList Op0; 2826 Op0.assign(VL.size(), VL0->getOperand(0)); 2827 VectorizableTree.back()->setOperand(0, Op0); 2828 return; 2829 } 2830 LLVM_DEBUG(dbgs() << "SLP: Gather extract sequence.\n"); 2831 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2832 ReuseShuffleIndicies); 2833 BS.cancelScheduling(VL, VL0); 2834 return; 2835 } 2836 case Instruction::Load: { 2837 // Check that a vectorized load would load the same memory as a scalar 2838 // load. For example, we don't want to vectorize loads that are smaller 2839 // than 8-bit. Even though we have a packed struct {<i2, i2, i2, i2>} LLVM 2840 // treats loading/storing it as an i8 struct. If we vectorize loads/stores 2841 // from such a struct, we read/write packed bits disagreeing with the 2842 // unvectorized version. 2843 Type *ScalarTy = VL0->getType(); 2844 2845 if (DL->getTypeSizeInBits(ScalarTy) != 2846 DL->getTypeAllocSizeInBits(ScalarTy)) { 2847 BS.cancelScheduling(VL, VL0); 2848 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2849 ReuseShuffleIndicies); 2850 LLVM_DEBUG(dbgs() << "SLP: Gathering loads of non-packed type.\n"); 2851 return; 2852 } 2853 2854 // Make sure all loads in the bundle are simple - we can't vectorize 2855 // atomic or volatile loads. 2856 SmallVector<Value *, 4> PointerOps(VL.size()); 2857 auto POIter = PointerOps.begin(); 2858 for (Value *V : VL) { 2859 auto *L = cast<LoadInst>(V); 2860 if (!L->isSimple()) { 2861 BS.cancelScheduling(VL, VL0); 2862 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2863 ReuseShuffleIndicies); 2864 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple loads.\n"); 2865 return; 2866 } 2867 *POIter = L->getPointerOperand(); 2868 ++POIter; 2869 } 2870 2871 OrdersType CurrentOrder; 2872 // Check the order of pointer operands. 2873 if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) { 2874 Value *Ptr0; 2875 Value *PtrN; 2876 if (CurrentOrder.empty()) { 2877 Ptr0 = PointerOps.front(); 2878 PtrN = PointerOps.back(); 2879 } else { 2880 Ptr0 = PointerOps[CurrentOrder.front()]; 2881 PtrN = PointerOps[CurrentOrder.back()]; 2882 } 2883 Optional<int> Diff = getPointersDiff(Ptr0, PtrN, *DL, *SE); 2884 // Check that the sorted loads are consecutive. 2885 if (static_cast<unsigned>(*Diff) == VL.size() - 1) { 2886 if (CurrentOrder.empty()) { 2887 // Original loads are consecutive and does not require reordering. 2888 ++NumOpsWantToKeepOriginalOrder; 2889 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, 2890 UserTreeIdx, ReuseShuffleIndicies); 2891 TE->setOperandsInOrder(); 2892 LLVM_DEBUG(dbgs() << "SLP: added a vector of loads.\n"); 2893 } else { 2894 // Need to reorder. 2895 TreeEntry *TE = 2896 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2897 ReuseShuffleIndicies, CurrentOrder); 2898 TE->setOperandsInOrder(); 2899 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled loads.\n"); 2900 findRootOrder(CurrentOrder); 2901 ++NumOpsWantToKeepOrder[CurrentOrder]; 2902 } 2903 return; 2904 } 2905 // Vectorizing non-consecutive loads with `llvm.masked.gather`. 2906 TreeEntry *TE = newTreeEntry(VL, TreeEntry::ScatterVectorize, Bundle, S, 2907 UserTreeIdx, ReuseShuffleIndicies); 2908 TE->setOperandsInOrder(); 2909 buildTree_rec(PointerOps, Depth + 1, {TE, 0}); 2910 LLVM_DEBUG(dbgs() << "SLP: added a vector of non-consecutive loads.\n"); 2911 return; 2912 } 2913 2914 LLVM_DEBUG(dbgs() << "SLP: Gathering non-consecutive loads.\n"); 2915 BS.cancelScheduling(VL, VL0); 2916 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2917 ReuseShuffleIndicies); 2918 return; 2919 } 2920 case Instruction::ZExt: 2921 case Instruction::SExt: 2922 case Instruction::FPToUI: 2923 case Instruction::FPToSI: 2924 case Instruction::FPExt: 2925 case Instruction::PtrToInt: 2926 case Instruction::IntToPtr: 2927 case Instruction::SIToFP: 2928 case Instruction::UIToFP: 2929 case Instruction::Trunc: 2930 case Instruction::FPTrunc: 2931 case Instruction::BitCast: { 2932 Type *SrcTy = VL0->getOperand(0)->getType(); 2933 for (Value *V : VL) { 2934 Type *Ty = cast<Instruction>(V)->getOperand(0)->getType(); 2935 if (Ty != SrcTy || !isValidElementType(Ty)) { 2936 BS.cancelScheduling(VL, VL0); 2937 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2938 ReuseShuffleIndicies); 2939 LLVM_DEBUG(dbgs() 2940 << "SLP: Gathering casts with different src types.\n"); 2941 return; 2942 } 2943 } 2944 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2945 ReuseShuffleIndicies); 2946 LLVM_DEBUG(dbgs() << "SLP: added a vector of casts.\n"); 2947 2948 TE->setOperandsInOrder(); 2949 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 2950 ValueList Operands; 2951 // Prepare the operand vector. 2952 for (Value *V : VL) 2953 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 2954 2955 buildTree_rec(Operands, Depth + 1, {TE, i}); 2956 } 2957 return; 2958 } 2959 case Instruction::ICmp: 2960 case Instruction::FCmp: { 2961 // Check that all of the compares have the same predicate. 2962 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 2963 CmpInst::Predicate SwapP0 = CmpInst::getSwappedPredicate(P0); 2964 Type *ComparedTy = VL0->getOperand(0)->getType(); 2965 for (Value *V : VL) { 2966 CmpInst *Cmp = cast<CmpInst>(V); 2967 if ((Cmp->getPredicate() != P0 && Cmp->getPredicate() != SwapP0) || 2968 Cmp->getOperand(0)->getType() != ComparedTy) { 2969 BS.cancelScheduling(VL, VL0); 2970 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2971 ReuseShuffleIndicies); 2972 LLVM_DEBUG(dbgs() 2973 << "SLP: Gathering cmp with different predicate.\n"); 2974 return; 2975 } 2976 } 2977 2978 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2979 ReuseShuffleIndicies); 2980 LLVM_DEBUG(dbgs() << "SLP: added a vector of compares.\n"); 2981 2982 ValueList Left, Right; 2983 if (cast<CmpInst>(VL0)->isCommutative()) { 2984 // Commutative predicate - collect + sort operands of the instructions 2985 // so that each side is more likely to have the same opcode. 2986 assert(P0 == SwapP0 && "Commutative Predicate mismatch"); 2987 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 2988 } else { 2989 // Collect operands - commute if it uses the swapped predicate. 2990 for (Value *V : VL) { 2991 auto *Cmp = cast<CmpInst>(V); 2992 Value *LHS = Cmp->getOperand(0); 2993 Value *RHS = Cmp->getOperand(1); 2994 if (Cmp->getPredicate() != P0) 2995 std::swap(LHS, RHS); 2996 Left.push_back(LHS); 2997 Right.push_back(RHS); 2998 } 2999 } 3000 TE->setOperand(0, Left); 3001 TE->setOperand(1, Right); 3002 buildTree_rec(Left, Depth + 1, {TE, 0}); 3003 buildTree_rec(Right, Depth + 1, {TE, 1}); 3004 return; 3005 } 3006 case Instruction::Select: 3007 case Instruction::FNeg: 3008 case Instruction::Add: 3009 case Instruction::FAdd: 3010 case Instruction::Sub: 3011 case Instruction::FSub: 3012 case Instruction::Mul: 3013 case Instruction::FMul: 3014 case Instruction::UDiv: 3015 case Instruction::SDiv: 3016 case Instruction::FDiv: 3017 case Instruction::URem: 3018 case Instruction::SRem: 3019 case Instruction::FRem: 3020 case Instruction::Shl: 3021 case Instruction::LShr: 3022 case Instruction::AShr: 3023 case Instruction::And: 3024 case Instruction::Or: 3025 case Instruction::Xor: { 3026 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3027 ReuseShuffleIndicies); 3028 LLVM_DEBUG(dbgs() << "SLP: added a vector of un/bin op.\n"); 3029 3030 // Sort operands of the instructions so that each side is more likely to 3031 // have the same opcode. 3032 if (isa<BinaryOperator>(VL0) && VL0->isCommutative()) { 3033 ValueList Left, Right; 3034 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 3035 TE->setOperand(0, Left); 3036 TE->setOperand(1, Right); 3037 buildTree_rec(Left, Depth + 1, {TE, 0}); 3038 buildTree_rec(Right, Depth + 1, {TE, 1}); 3039 return; 3040 } 3041 3042 TE->setOperandsInOrder(); 3043 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 3044 ValueList Operands; 3045 // Prepare the operand vector. 3046 for (Value *V : VL) 3047 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3048 3049 buildTree_rec(Operands, Depth + 1, {TE, i}); 3050 } 3051 return; 3052 } 3053 case Instruction::GetElementPtr: { 3054 // We don't combine GEPs with complicated (nested) indexing. 3055 for (Value *V : VL) { 3056 if (cast<Instruction>(V)->getNumOperands() != 2) { 3057 LLVM_DEBUG(dbgs() << "SLP: not-vectorizable GEP (nested indexes).\n"); 3058 BS.cancelScheduling(VL, VL0); 3059 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3060 ReuseShuffleIndicies); 3061 return; 3062 } 3063 } 3064 3065 // We can't combine several GEPs into one vector if they operate on 3066 // different types. 3067 Type *Ty0 = VL0->getOperand(0)->getType(); 3068 for (Value *V : VL) { 3069 Type *CurTy = cast<Instruction>(V)->getOperand(0)->getType(); 3070 if (Ty0 != CurTy) { 3071 LLVM_DEBUG(dbgs() 3072 << "SLP: not-vectorizable GEP (different types).\n"); 3073 BS.cancelScheduling(VL, VL0); 3074 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3075 ReuseShuffleIndicies); 3076 return; 3077 } 3078 } 3079 3080 // We don't combine GEPs with non-constant indexes. 3081 Type *Ty1 = VL0->getOperand(1)->getType(); 3082 for (Value *V : VL) { 3083 auto Op = cast<Instruction>(V)->getOperand(1); 3084 if (!isa<ConstantInt>(Op) || 3085 (Op->getType() != Ty1 && 3086 Op->getType()->getScalarSizeInBits() > 3087 DL->getIndexSizeInBits( 3088 V->getType()->getPointerAddressSpace()))) { 3089 LLVM_DEBUG(dbgs() 3090 << "SLP: not-vectorizable GEP (non-constant indexes).\n"); 3091 BS.cancelScheduling(VL, VL0); 3092 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3093 ReuseShuffleIndicies); 3094 return; 3095 } 3096 } 3097 3098 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3099 ReuseShuffleIndicies); 3100 LLVM_DEBUG(dbgs() << "SLP: added a vector of GEPs.\n"); 3101 TE->setOperandsInOrder(); 3102 for (unsigned i = 0, e = 2; i < e; ++i) { 3103 ValueList Operands; 3104 // Prepare the operand vector. 3105 for (Value *V : VL) 3106 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3107 3108 buildTree_rec(Operands, Depth + 1, {TE, i}); 3109 } 3110 return; 3111 } 3112 case Instruction::Store: { 3113 // Check if the stores are consecutive or if we need to swizzle them. 3114 llvm::Type *ScalarTy = cast<StoreInst>(VL0)->getValueOperand()->getType(); 3115 // Avoid types that are padded when being allocated as scalars, while 3116 // being packed together in a vector (such as i1). 3117 if (DL->getTypeSizeInBits(ScalarTy) != 3118 DL->getTypeAllocSizeInBits(ScalarTy)) { 3119 BS.cancelScheduling(VL, VL0); 3120 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3121 ReuseShuffleIndicies); 3122 LLVM_DEBUG(dbgs() << "SLP: Gathering stores of non-packed type.\n"); 3123 return; 3124 } 3125 // Make sure all stores in the bundle are simple - we can't vectorize 3126 // atomic or volatile stores. 3127 SmallVector<Value *, 4> PointerOps(VL.size()); 3128 ValueList Operands(VL.size()); 3129 auto POIter = PointerOps.begin(); 3130 auto OIter = Operands.begin(); 3131 for (Value *V : VL) { 3132 auto *SI = cast<StoreInst>(V); 3133 if (!SI->isSimple()) { 3134 BS.cancelScheduling(VL, VL0); 3135 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3136 ReuseShuffleIndicies); 3137 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple stores.\n"); 3138 return; 3139 } 3140 *POIter = SI->getPointerOperand(); 3141 *OIter = SI->getValueOperand(); 3142 ++POIter; 3143 ++OIter; 3144 } 3145 3146 OrdersType CurrentOrder; 3147 // Check the order of pointer operands. 3148 if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) { 3149 Value *Ptr0; 3150 Value *PtrN; 3151 if (CurrentOrder.empty()) { 3152 Ptr0 = PointerOps.front(); 3153 PtrN = PointerOps.back(); 3154 } else { 3155 Ptr0 = PointerOps[CurrentOrder.front()]; 3156 PtrN = PointerOps[CurrentOrder.back()]; 3157 } 3158 Optional<int> Dist = getPointersDiff(Ptr0, PtrN, *DL, *SE); 3159 // Check that the sorted pointer operands are consecutive. 3160 if (static_cast<unsigned>(*Dist) == VL.size() - 1) { 3161 if (CurrentOrder.empty()) { 3162 // Original stores are consecutive and does not require reordering. 3163 ++NumOpsWantToKeepOriginalOrder; 3164 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, 3165 UserTreeIdx, ReuseShuffleIndicies); 3166 TE->setOperandsInOrder(); 3167 buildTree_rec(Operands, Depth + 1, {TE, 0}); 3168 LLVM_DEBUG(dbgs() << "SLP: added a vector of stores.\n"); 3169 } else { 3170 TreeEntry *TE = 3171 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3172 ReuseShuffleIndicies, CurrentOrder); 3173 TE->setOperandsInOrder(); 3174 buildTree_rec(Operands, Depth + 1, {TE, 0}); 3175 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled stores.\n"); 3176 findRootOrder(CurrentOrder); 3177 ++NumOpsWantToKeepOrder[CurrentOrder]; 3178 } 3179 return; 3180 } 3181 } 3182 3183 BS.cancelScheduling(VL, VL0); 3184 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3185 ReuseShuffleIndicies); 3186 LLVM_DEBUG(dbgs() << "SLP: Non-consecutive store.\n"); 3187 return; 3188 } 3189 case Instruction::Call: { 3190 // Check if the calls are all to the same vectorizable intrinsic or 3191 // library function. 3192 CallInst *CI = cast<CallInst>(VL0); 3193 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3194 3195 VFShape Shape = VFShape::get( 3196 *CI, ElementCount::getFixed(static_cast<unsigned int>(VL.size())), 3197 false /*HasGlobalPred*/); 3198 Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape); 3199 3200 if (!VecFunc && !isTriviallyVectorizable(ID)) { 3201 BS.cancelScheduling(VL, VL0); 3202 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3203 ReuseShuffleIndicies); 3204 LLVM_DEBUG(dbgs() << "SLP: Non-vectorizable call.\n"); 3205 return; 3206 } 3207 Function *F = CI->getCalledFunction(); 3208 unsigned NumArgs = CI->getNumArgOperands(); 3209 SmallVector<Value*, 4> ScalarArgs(NumArgs, nullptr); 3210 for (unsigned j = 0; j != NumArgs; ++j) 3211 if (hasVectorInstrinsicScalarOpd(ID, j)) 3212 ScalarArgs[j] = CI->getArgOperand(j); 3213 for (Value *V : VL) { 3214 CallInst *CI2 = dyn_cast<CallInst>(V); 3215 if (!CI2 || CI2->getCalledFunction() != F || 3216 getVectorIntrinsicIDForCall(CI2, TLI) != ID || 3217 (VecFunc && 3218 VecFunc != VFDatabase(*CI2).getVectorizedFunction(Shape)) || 3219 !CI->hasIdenticalOperandBundleSchema(*CI2)) { 3220 BS.cancelScheduling(VL, VL0); 3221 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3222 ReuseShuffleIndicies); 3223 LLVM_DEBUG(dbgs() << "SLP: mismatched calls:" << *CI << "!=" << *V 3224 << "\n"); 3225 return; 3226 } 3227 // Some intrinsics have scalar arguments and should be same in order for 3228 // them to be vectorized. 3229 for (unsigned j = 0; j != NumArgs; ++j) { 3230 if (hasVectorInstrinsicScalarOpd(ID, j)) { 3231 Value *A1J = CI2->getArgOperand(j); 3232 if (ScalarArgs[j] != A1J) { 3233 BS.cancelScheduling(VL, VL0); 3234 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3235 ReuseShuffleIndicies); 3236 LLVM_DEBUG(dbgs() << "SLP: mismatched arguments in call:" << *CI 3237 << " argument " << ScalarArgs[j] << "!=" << A1J 3238 << "\n"); 3239 return; 3240 } 3241 } 3242 } 3243 // Verify that the bundle operands are identical between the two calls. 3244 if (CI->hasOperandBundles() && 3245 !std::equal(CI->op_begin() + CI->getBundleOperandsStartIndex(), 3246 CI->op_begin() + CI->getBundleOperandsEndIndex(), 3247 CI2->op_begin() + CI2->getBundleOperandsStartIndex())) { 3248 BS.cancelScheduling(VL, VL0); 3249 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3250 ReuseShuffleIndicies); 3251 LLVM_DEBUG(dbgs() << "SLP: mismatched bundle operands in calls:" 3252 << *CI << "!=" << *V << '\n'); 3253 return; 3254 } 3255 } 3256 3257 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3258 ReuseShuffleIndicies); 3259 TE->setOperandsInOrder(); 3260 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 3261 ValueList Operands; 3262 // Prepare the operand vector. 3263 for (Value *V : VL) { 3264 auto *CI2 = cast<CallInst>(V); 3265 Operands.push_back(CI2->getArgOperand(i)); 3266 } 3267 buildTree_rec(Operands, Depth + 1, {TE, i}); 3268 } 3269 return; 3270 } 3271 case Instruction::ShuffleVector: { 3272 // If this is not an alternate sequence of opcode like add-sub 3273 // then do not vectorize this instruction. 3274 if (!S.isAltShuffle()) { 3275 BS.cancelScheduling(VL, VL0); 3276 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3277 ReuseShuffleIndicies); 3278 LLVM_DEBUG(dbgs() << "SLP: ShuffleVector are not vectorized.\n"); 3279 return; 3280 } 3281 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3282 ReuseShuffleIndicies); 3283 LLVM_DEBUG(dbgs() << "SLP: added a ShuffleVector op.\n"); 3284 3285 // Reorder operands if reordering would enable vectorization. 3286 if (isa<BinaryOperator>(VL0)) { 3287 ValueList Left, Right; 3288 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 3289 TE->setOperand(0, Left); 3290 TE->setOperand(1, Right); 3291 buildTree_rec(Left, Depth + 1, {TE, 0}); 3292 buildTree_rec(Right, Depth + 1, {TE, 1}); 3293 return; 3294 } 3295 3296 TE->setOperandsInOrder(); 3297 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 3298 ValueList Operands; 3299 // Prepare the operand vector. 3300 for (Value *V : VL) 3301 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3302 3303 buildTree_rec(Operands, Depth + 1, {TE, i}); 3304 } 3305 return; 3306 } 3307 default: 3308 BS.cancelScheduling(VL, VL0); 3309 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3310 ReuseShuffleIndicies); 3311 LLVM_DEBUG(dbgs() << "SLP: Gathering unknown instruction.\n"); 3312 return; 3313 } 3314 } 3315 3316 unsigned BoUpSLP::canMapToVector(Type *T, const DataLayout &DL) const { 3317 unsigned N = 1; 3318 Type *EltTy = T; 3319 3320 while (isa<StructType>(EltTy) || isa<ArrayType>(EltTy) || 3321 isa<VectorType>(EltTy)) { 3322 if (auto *ST = dyn_cast<StructType>(EltTy)) { 3323 // Check that struct is homogeneous. 3324 for (const auto *Ty : ST->elements()) 3325 if (Ty != *ST->element_begin()) 3326 return 0; 3327 N *= ST->getNumElements(); 3328 EltTy = *ST->element_begin(); 3329 } else if (auto *AT = dyn_cast<ArrayType>(EltTy)) { 3330 N *= AT->getNumElements(); 3331 EltTy = AT->getElementType(); 3332 } else { 3333 auto *VT = cast<FixedVectorType>(EltTy); 3334 N *= VT->getNumElements(); 3335 EltTy = VT->getElementType(); 3336 } 3337 } 3338 3339 if (!isValidElementType(EltTy)) 3340 return 0; 3341 uint64_t VTSize = DL.getTypeStoreSizeInBits(FixedVectorType::get(EltTy, N)); 3342 if (VTSize < MinVecRegSize || VTSize > MaxVecRegSize || VTSize != DL.getTypeStoreSizeInBits(T)) 3343 return 0; 3344 return N; 3345 } 3346 3347 bool BoUpSLP::canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 3348 SmallVectorImpl<unsigned> &CurrentOrder) const { 3349 Instruction *E0 = cast<Instruction>(OpValue); 3350 assert(E0->getOpcode() == Instruction::ExtractElement || 3351 E0->getOpcode() == Instruction::ExtractValue); 3352 assert(E0->getOpcode() == getSameOpcode(VL).getOpcode() && "Invalid opcode"); 3353 // Check if all of the extracts come from the same vector and from the 3354 // correct offset. 3355 Value *Vec = E0->getOperand(0); 3356 3357 CurrentOrder.clear(); 3358 3359 // We have to extract from a vector/aggregate with the same number of elements. 3360 unsigned NElts; 3361 if (E0->getOpcode() == Instruction::ExtractValue) { 3362 const DataLayout &DL = E0->getModule()->getDataLayout(); 3363 NElts = canMapToVector(Vec->getType(), DL); 3364 if (!NElts) 3365 return false; 3366 // Check if load can be rewritten as load of vector. 3367 LoadInst *LI = dyn_cast<LoadInst>(Vec); 3368 if (!LI || !LI->isSimple() || !LI->hasNUses(VL.size())) 3369 return false; 3370 } else { 3371 NElts = cast<FixedVectorType>(Vec->getType())->getNumElements(); 3372 } 3373 3374 if (NElts != VL.size()) 3375 return false; 3376 3377 // Check that all of the indices extract from the correct offset. 3378 bool ShouldKeepOrder = true; 3379 unsigned E = VL.size(); 3380 // Assign to all items the initial value E + 1 so we can check if the extract 3381 // instruction index was used already. 3382 // Also, later we can check that all the indices are used and we have a 3383 // consecutive access in the extract instructions, by checking that no 3384 // element of CurrentOrder still has value E + 1. 3385 CurrentOrder.assign(E, E + 1); 3386 unsigned I = 0; 3387 for (; I < E; ++I) { 3388 auto *Inst = cast<Instruction>(VL[I]); 3389 if (Inst->getOperand(0) != Vec) 3390 break; 3391 Optional<unsigned> Idx = getExtractIndex(Inst); 3392 if (!Idx) 3393 break; 3394 const unsigned ExtIdx = *Idx; 3395 if (ExtIdx != I) { 3396 if (ExtIdx >= E || CurrentOrder[ExtIdx] != E + 1) 3397 break; 3398 ShouldKeepOrder = false; 3399 CurrentOrder[ExtIdx] = I; 3400 } else { 3401 if (CurrentOrder[I] != E + 1) 3402 break; 3403 CurrentOrder[I] = I; 3404 } 3405 } 3406 if (I < E) { 3407 CurrentOrder.clear(); 3408 return false; 3409 } 3410 3411 return ShouldKeepOrder; 3412 } 3413 3414 bool BoUpSLP::areAllUsersVectorized(Instruction *I) const { 3415 return I->hasOneUse() || llvm::all_of(I->users(), [this](User *U) { 3416 return ScalarToTreeEntry.count(U) > 0; 3417 }); 3418 } 3419 3420 static std::pair<InstructionCost, InstructionCost> 3421 getVectorCallCosts(CallInst *CI, FixedVectorType *VecTy, 3422 TargetTransformInfo *TTI, TargetLibraryInfo *TLI) { 3423 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3424 3425 // Calculate the cost of the scalar and vector calls. 3426 SmallVector<Type *, 4> VecTys; 3427 for (Use &Arg : CI->args()) 3428 VecTys.push_back( 3429 FixedVectorType::get(Arg->getType(), VecTy->getNumElements())); 3430 FastMathFlags FMF; 3431 if (auto *FPCI = dyn_cast<FPMathOperator>(CI)) 3432 FMF = FPCI->getFastMathFlags(); 3433 SmallVector<const Value *> Arguments(CI->arg_begin(), CI->arg_end()); 3434 IntrinsicCostAttributes CostAttrs(ID, VecTy, Arguments, VecTys, FMF, 3435 dyn_cast<IntrinsicInst>(CI)); 3436 auto IntrinsicCost = 3437 TTI->getIntrinsicInstrCost(CostAttrs, TTI::TCK_RecipThroughput); 3438 3439 auto Shape = VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>( 3440 VecTy->getNumElements())), 3441 false /*HasGlobalPred*/); 3442 Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape); 3443 auto LibCost = IntrinsicCost; 3444 if (!CI->isNoBuiltin() && VecFunc) { 3445 // Calculate the cost of the vector library call. 3446 // If the corresponding vector call is cheaper, return its cost. 3447 LibCost = TTI->getCallInstrCost(nullptr, VecTy, VecTys, 3448 TTI::TCK_RecipThroughput); 3449 } 3450 return {IntrinsicCost, LibCost}; 3451 } 3452 3453 /// Compute the cost of creating a vector of type \p VecTy containing the 3454 /// extracted values from \p VL. 3455 static InstructionCost 3456 computeExtractCost(ArrayRef<Value *> VL, FixedVectorType *VecTy, 3457 TargetTransformInfo::ShuffleKind ShuffleKind, 3458 ArrayRef<int> Mask, TargetTransformInfo &TTI) { 3459 unsigned NumOfParts = TTI.getNumberOfParts(VecTy); 3460 3461 if (ShuffleKind != TargetTransformInfo::SK_PermuteSingleSrc || !NumOfParts || 3462 VecTy->getNumElements() < NumOfParts) 3463 return TTI.getShuffleCost(ShuffleKind, VecTy, Mask); 3464 3465 bool AllConsecutive = true; 3466 unsigned EltsPerVector = VecTy->getNumElements() / NumOfParts; 3467 unsigned Idx = -1; 3468 InstructionCost Cost = 0; 3469 3470 // Process extracts in blocks of EltsPerVector to check if the source vector 3471 // operand can be re-used directly. If not, add the cost of creating a shuffle 3472 // to extract the values into a vector register. 3473 for (auto *V : VL) { 3474 ++Idx; 3475 3476 // Reached the start of a new vector registers. 3477 if (Idx % EltsPerVector == 0) { 3478 AllConsecutive = true; 3479 continue; 3480 } 3481 3482 // Check all extracts for a vector register on the target directly 3483 // extract values in order. 3484 unsigned CurrentIdx = *getExtractIndex(cast<Instruction>(V)); 3485 unsigned PrevIdx = *getExtractIndex(cast<Instruction>(VL[Idx - 1])); 3486 AllConsecutive &= PrevIdx + 1 == CurrentIdx && 3487 CurrentIdx % EltsPerVector == Idx % EltsPerVector; 3488 3489 if (AllConsecutive) 3490 continue; 3491 3492 // Skip all indices, except for the last index per vector block. 3493 if ((Idx + 1) % EltsPerVector != 0 && Idx + 1 != VL.size()) 3494 continue; 3495 3496 // If we have a series of extracts which are not consecutive and hence 3497 // cannot re-use the source vector register directly, compute the shuffle 3498 // cost to extract the a vector with EltsPerVector elements. 3499 Cost += TTI.getShuffleCost( 3500 TargetTransformInfo::SK_PermuteSingleSrc, 3501 FixedVectorType::get(VecTy->getElementType(), EltsPerVector)); 3502 } 3503 return Cost; 3504 } 3505 3506 InstructionCost BoUpSLP::getEntryCost(TreeEntry *E) { 3507 ArrayRef<Value*> VL = E->Scalars; 3508 3509 Type *ScalarTy = VL[0]->getType(); 3510 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 3511 ScalarTy = SI->getValueOperand()->getType(); 3512 else if (CmpInst *CI = dyn_cast<CmpInst>(VL[0])) 3513 ScalarTy = CI->getOperand(0)->getType(); 3514 auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); 3515 TTI::TargetCostKind CostKind = TTI::TCK_RecipThroughput; 3516 3517 // If we have computed a smaller type for the expression, update VecTy so 3518 // that the costs will be accurate. 3519 if (MinBWs.count(VL[0])) 3520 VecTy = FixedVectorType::get( 3521 IntegerType::get(F->getContext(), MinBWs[VL[0]].first), VL.size()); 3522 3523 unsigned ReuseShuffleNumbers = E->ReuseShuffleIndices.size(); 3524 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 3525 InstructionCost ReuseShuffleCost = 0; 3526 if (NeedToShuffleReuses) { 3527 ReuseShuffleCost = 3528 TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, VecTy, 3529 E->ReuseShuffleIndices); 3530 } 3531 if (E->State == TreeEntry::NeedToGather) { 3532 if (allConstant(VL)) 3533 return 0; 3534 if (isSplat(VL)) { 3535 return ReuseShuffleCost + 3536 TTI->getShuffleCost(TargetTransformInfo::SK_Broadcast, VecTy, None, 3537 0); 3538 } 3539 if (E->getOpcode() == Instruction::ExtractElement && 3540 allSameType(VL) && allSameBlock(VL)) { 3541 SmallVector<int> Mask; 3542 Optional<TargetTransformInfo::ShuffleKind> ShuffleKind = 3543 isShuffle(VL, Mask); 3544 if (ShuffleKind.hasValue()) { 3545 InstructionCost Cost = 3546 computeExtractCost(VL, VecTy, *ShuffleKind, Mask, *TTI); 3547 for (auto *V : VL) { 3548 // If all users of instruction are going to be vectorized and this 3549 // instruction itself is not going to be vectorized, consider this 3550 // instruction as dead and remove its cost from the final cost of the 3551 // vectorized tree. 3552 if (areAllUsersVectorized(cast<Instruction>(V)) && 3553 !ScalarToTreeEntry.count(V)) { 3554 auto *IO = cast<ConstantInt>( 3555 cast<ExtractElementInst>(V)->getIndexOperand()); 3556 Cost -= TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, 3557 IO->getZExtValue()); 3558 } 3559 } 3560 return ReuseShuffleCost + Cost; 3561 } 3562 } 3563 return ReuseShuffleCost + getGatherCost(VL); 3564 } 3565 assert((E->State == TreeEntry::Vectorize || 3566 E->State == TreeEntry::ScatterVectorize) && 3567 "Unhandled state"); 3568 assert(E->getOpcode() && allSameType(VL) && allSameBlock(VL) && "Invalid VL"); 3569 Instruction *VL0 = E->getMainOp(); 3570 unsigned ShuffleOrOp = 3571 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 3572 switch (ShuffleOrOp) { 3573 case Instruction::PHI: 3574 return 0; 3575 3576 case Instruction::ExtractValue: 3577 case Instruction::ExtractElement: { 3578 // The common cost of removal ExtractElement/ExtractValue instructions + 3579 // the cost of shuffles, if required to resuffle the original vector. 3580 InstructionCost CommonCost = 0; 3581 if (NeedToShuffleReuses) { 3582 unsigned Idx = 0; 3583 for (unsigned I : E->ReuseShuffleIndices) { 3584 if (ShuffleOrOp == Instruction::ExtractElement) { 3585 auto *IO = cast<ConstantInt>( 3586 cast<ExtractElementInst>(VL[I])->getIndexOperand()); 3587 Idx = IO->getZExtValue(); 3588 ReuseShuffleCost -= TTI->getVectorInstrCost( 3589 Instruction::ExtractElement, VecTy, Idx); 3590 } else { 3591 ReuseShuffleCost -= TTI->getVectorInstrCost( 3592 Instruction::ExtractElement, VecTy, Idx); 3593 ++Idx; 3594 } 3595 } 3596 Idx = ReuseShuffleNumbers; 3597 for (Value *V : VL) { 3598 if (ShuffleOrOp == Instruction::ExtractElement) { 3599 auto *IO = cast<ConstantInt>( 3600 cast<ExtractElementInst>(V)->getIndexOperand()); 3601 Idx = IO->getZExtValue(); 3602 } else { 3603 --Idx; 3604 } 3605 ReuseShuffleCost += 3606 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, Idx); 3607 } 3608 CommonCost = ReuseShuffleCost; 3609 } else if (!E->ReorderIndices.empty()) { 3610 SmallVector<int> NewMask; 3611 inversePermutation(E->ReorderIndices, NewMask); 3612 CommonCost = TTI->getShuffleCost( 3613 TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask); 3614 } 3615 for (unsigned I = 0, E = VL.size(); I < E; ++I) { 3616 Instruction *EI = cast<Instruction>(VL[I]); 3617 // If all users are going to be vectorized, instruction can be 3618 // considered as dead. 3619 // The same, if have only one user, it will be vectorized for sure. 3620 if (areAllUsersVectorized(EI)) { 3621 // Take credit for instruction that will become dead. 3622 if (EI->hasOneUse()) { 3623 Instruction *Ext = EI->user_back(); 3624 if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) && 3625 all_of(Ext->users(), 3626 [](User *U) { return isa<GetElementPtrInst>(U); })) { 3627 // Use getExtractWithExtendCost() to calculate the cost of 3628 // extractelement/ext pair. 3629 CommonCost -= TTI->getExtractWithExtendCost( 3630 Ext->getOpcode(), Ext->getType(), VecTy, I); 3631 // Add back the cost of s|zext which is subtracted separately. 3632 CommonCost += TTI->getCastInstrCost( 3633 Ext->getOpcode(), Ext->getType(), EI->getType(), 3634 TTI::getCastContextHint(Ext), CostKind, Ext); 3635 continue; 3636 } 3637 } 3638 CommonCost -= 3639 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, I); 3640 } 3641 } 3642 return CommonCost; 3643 } 3644 case Instruction::ZExt: 3645 case Instruction::SExt: 3646 case Instruction::FPToUI: 3647 case Instruction::FPToSI: 3648 case Instruction::FPExt: 3649 case Instruction::PtrToInt: 3650 case Instruction::IntToPtr: 3651 case Instruction::SIToFP: 3652 case Instruction::UIToFP: 3653 case Instruction::Trunc: 3654 case Instruction::FPTrunc: 3655 case Instruction::BitCast: { 3656 Type *SrcTy = VL0->getOperand(0)->getType(); 3657 InstructionCost ScalarEltCost = 3658 TTI->getCastInstrCost(E->getOpcode(), ScalarTy, SrcTy, 3659 TTI::getCastContextHint(VL0), CostKind, VL0); 3660 if (NeedToShuffleReuses) { 3661 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3662 } 3663 3664 // Calculate the cost of this instruction. 3665 InstructionCost ScalarCost = VL.size() * ScalarEltCost; 3666 3667 auto *SrcVecTy = FixedVectorType::get(SrcTy, VL.size()); 3668 InstructionCost VecCost = 0; 3669 // Check if the values are candidates to demote. 3670 if (!MinBWs.count(VL0) || VecTy != SrcVecTy) { 3671 VecCost = 3672 ReuseShuffleCost + 3673 TTI->getCastInstrCost(E->getOpcode(), VecTy, SrcVecTy, 3674 TTI::getCastContextHint(VL0), CostKind, VL0); 3675 } 3676 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3677 return VecCost - ScalarCost; 3678 } 3679 case Instruction::FCmp: 3680 case Instruction::ICmp: 3681 case Instruction::Select: { 3682 // Calculate the cost of this instruction. 3683 InstructionCost ScalarEltCost = 3684 TTI->getCmpSelInstrCost(E->getOpcode(), ScalarTy, Builder.getInt1Ty(), 3685 CmpInst::BAD_ICMP_PREDICATE, CostKind, VL0); 3686 if (NeedToShuffleReuses) { 3687 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3688 } 3689 auto *MaskTy = FixedVectorType::get(Builder.getInt1Ty(), VL.size()); 3690 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3691 3692 // Check if all entries in VL are either compares or selects with compares 3693 // as condition that have the same predicates. 3694 CmpInst::Predicate VecPred = CmpInst::BAD_ICMP_PREDICATE; 3695 bool First = true; 3696 for (auto *V : VL) { 3697 CmpInst::Predicate CurrentPred; 3698 auto MatchCmp = m_Cmp(CurrentPred, m_Value(), m_Value()); 3699 if ((!match(V, m_Select(MatchCmp, m_Value(), m_Value())) && 3700 !match(V, MatchCmp)) || 3701 (!First && VecPred != CurrentPred)) { 3702 VecPred = CmpInst::BAD_ICMP_PREDICATE; 3703 break; 3704 } 3705 First = false; 3706 VecPred = CurrentPred; 3707 } 3708 3709 InstructionCost VecCost = TTI->getCmpSelInstrCost( 3710 E->getOpcode(), VecTy, MaskTy, VecPred, CostKind, VL0); 3711 // Check if it is possible and profitable to use min/max for selects in 3712 // VL. 3713 // 3714 auto IntrinsicAndUse = canConvertToMinOrMaxIntrinsic(VL); 3715 if (IntrinsicAndUse.first != Intrinsic::not_intrinsic) { 3716 IntrinsicCostAttributes CostAttrs(IntrinsicAndUse.first, VecTy, 3717 {VecTy, VecTy}); 3718 InstructionCost IntrinsicCost = 3719 TTI->getIntrinsicInstrCost(CostAttrs, CostKind); 3720 // If the selects are the only uses of the compares, they will be dead 3721 // and we can adjust the cost by removing their cost. 3722 if (IntrinsicAndUse.second) 3723 IntrinsicCost -= 3724 TTI->getCmpSelInstrCost(Instruction::ICmp, VecTy, MaskTy, 3725 CmpInst::BAD_ICMP_PREDICATE, CostKind); 3726 VecCost = std::min(VecCost, IntrinsicCost); 3727 } 3728 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3729 return ReuseShuffleCost + VecCost - ScalarCost; 3730 } 3731 case Instruction::FNeg: 3732 case Instruction::Add: 3733 case Instruction::FAdd: 3734 case Instruction::Sub: 3735 case Instruction::FSub: 3736 case Instruction::Mul: 3737 case Instruction::FMul: 3738 case Instruction::UDiv: 3739 case Instruction::SDiv: 3740 case Instruction::FDiv: 3741 case Instruction::URem: 3742 case Instruction::SRem: 3743 case Instruction::FRem: 3744 case Instruction::Shl: 3745 case Instruction::LShr: 3746 case Instruction::AShr: 3747 case Instruction::And: 3748 case Instruction::Or: 3749 case Instruction::Xor: { 3750 // Certain instructions can be cheaper to vectorize if they have a 3751 // constant second vector operand. 3752 TargetTransformInfo::OperandValueKind Op1VK = 3753 TargetTransformInfo::OK_AnyValue; 3754 TargetTransformInfo::OperandValueKind Op2VK = 3755 TargetTransformInfo::OK_UniformConstantValue; 3756 TargetTransformInfo::OperandValueProperties Op1VP = 3757 TargetTransformInfo::OP_None; 3758 TargetTransformInfo::OperandValueProperties Op2VP = 3759 TargetTransformInfo::OP_PowerOf2; 3760 3761 // If all operands are exactly the same ConstantInt then set the 3762 // operand kind to OK_UniformConstantValue. 3763 // If instead not all operands are constants, then set the operand kind 3764 // to OK_AnyValue. If all operands are constants but not the same, 3765 // then set the operand kind to OK_NonUniformConstantValue. 3766 ConstantInt *CInt0 = nullptr; 3767 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 3768 const Instruction *I = cast<Instruction>(VL[i]); 3769 unsigned OpIdx = isa<BinaryOperator>(I) ? 1 : 0; 3770 ConstantInt *CInt = dyn_cast<ConstantInt>(I->getOperand(OpIdx)); 3771 if (!CInt) { 3772 Op2VK = TargetTransformInfo::OK_AnyValue; 3773 Op2VP = TargetTransformInfo::OP_None; 3774 break; 3775 } 3776 if (Op2VP == TargetTransformInfo::OP_PowerOf2 && 3777 !CInt->getValue().isPowerOf2()) 3778 Op2VP = TargetTransformInfo::OP_None; 3779 if (i == 0) { 3780 CInt0 = CInt; 3781 continue; 3782 } 3783 if (CInt0 != CInt) 3784 Op2VK = TargetTransformInfo::OK_NonUniformConstantValue; 3785 } 3786 3787 SmallVector<const Value *, 4> Operands(VL0->operand_values()); 3788 InstructionCost ScalarEltCost = 3789 TTI->getArithmeticInstrCost(E->getOpcode(), ScalarTy, CostKind, Op1VK, 3790 Op2VK, Op1VP, Op2VP, Operands, VL0); 3791 if (NeedToShuffleReuses) { 3792 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3793 } 3794 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3795 InstructionCost VecCost = 3796 TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind, Op1VK, 3797 Op2VK, Op1VP, Op2VP, Operands, VL0); 3798 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3799 return ReuseShuffleCost + VecCost - ScalarCost; 3800 } 3801 case Instruction::GetElementPtr: { 3802 TargetTransformInfo::OperandValueKind Op1VK = 3803 TargetTransformInfo::OK_AnyValue; 3804 TargetTransformInfo::OperandValueKind Op2VK = 3805 TargetTransformInfo::OK_UniformConstantValue; 3806 3807 InstructionCost ScalarEltCost = TTI->getArithmeticInstrCost( 3808 Instruction::Add, ScalarTy, CostKind, Op1VK, Op2VK); 3809 if (NeedToShuffleReuses) { 3810 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3811 } 3812 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3813 InstructionCost VecCost = TTI->getArithmeticInstrCost( 3814 Instruction::Add, VecTy, CostKind, Op1VK, Op2VK); 3815 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3816 return ReuseShuffleCost + VecCost - ScalarCost; 3817 } 3818 case Instruction::Load: { 3819 // Cost of wide load - cost of scalar loads. 3820 Align alignment = cast<LoadInst>(VL0)->getAlign(); 3821 InstructionCost ScalarEltCost = TTI->getMemoryOpCost( 3822 Instruction::Load, ScalarTy, alignment, 0, CostKind, VL0); 3823 if (NeedToShuffleReuses) { 3824 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3825 } 3826 InstructionCost ScalarLdCost = VecTy->getNumElements() * ScalarEltCost; 3827 InstructionCost VecLdCost; 3828 if (E->State == TreeEntry::Vectorize) { 3829 VecLdCost = TTI->getMemoryOpCost(Instruction::Load, VecTy, alignment, 0, 3830 CostKind, VL0); 3831 } else { 3832 assert(E->State == TreeEntry::ScatterVectorize && "Unknown EntryState"); 3833 VecLdCost = TTI->getGatherScatterOpCost( 3834 Instruction::Load, VecTy, cast<LoadInst>(VL0)->getPointerOperand(), 3835 /*VariableMask=*/false, alignment, CostKind, VL0); 3836 } 3837 if (!NeedToShuffleReuses && !E->ReorderIndices.empty()) { 3838 SmallVector<int> NewMask; 3839 inversePermutation(E->ReorderIndices, NewMask); 3840 VecLdCost += TTI->getShuffleCost( 3841 TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask); 3842 } 3843 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecLdCost, ScalarLdCost)); 3844 return ReuseShuffleCost + VecLdCost - ScalarLdCost; 3845 } 3846 case Instruction::Store: { 3847 // We know that we can merge the stores. Calculate the cost. 3848 bool IsReorder = !E->ReorderIndices.empty(); 3849 auto *SI = 3850 cast<StoreInst>(IsReorder ? VL[E->ReorderIndices.front()] : VL0); 3851 Align Alignment = SI->getAlign(); 3852 InstructionCost ScalarEltCost = TTI->getMemoryOpCost( 3853 Instruction::Store, ScalarTy, Alignment, 0, CostKind, VL0); 3854 InstructionCost ScalarStCost = VecTy->getNumElements() * ScalarEltCost; 3855 InstructionCost VecStCost = TTI->getMemoryOpCost( 3856 Instruction::Store, VecTy, Alignment, 0, CostKind, VL0); 3857 if (IsReorder) { 3858 SmallVector<int> NewMask; 3859 inversePermutation(E->ReorderIndices, NewMask); 3860 VecStCost += TTI->getShuffleCost( 3861 TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask); 3862 } 3863 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecStCost, ScalarStCost)); 3864 return VecStCost - ScalarStCost; 3865 } 3866 case Instruction::Call: { 3867 CallInst *CI = cast<CallInst>(VL0); 3868 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3869 3870 // Calculate the cost of the scalar and vector calls. 3871 IntrinsicCostAttributes CostAttrs(ID, *CI, 1); 3872 InstructionCost ScalarEltCost = 3873 TTI->getIntrinsicInstrCost(CostAttrs, CostKind); 3874 if (NeedToShuffleReuses) { 3875 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3876 } 3877 InstructionCost ScalarCallCost = VecTy->getNumElements() * ScalarEltCost; 3878 3879 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 3880 InstructionCost VecCallCost = 3881 std::min(VecCallCosts.first, VecCallCosts.second); 3882 3883 LLVM_DEBUG(dbgs() << "SLP: Call cost " << VecCallCost - ScalarCallCost 3884 << " (" << VecCallCost << "-" << ScalarCallCost << ")" 3885 << " for " << *CI << "\n"); 3886 3887 return ReuseShuffleCost + VecCallCost - ScalarCallCost; 3888 } 3889 case Instruction::ShuffleVector: { 3890 assert(E->isAltShuffle() && 3891 ((Instruction::isBinaryOp(E->getOpcode()) && 3892 Instruction::isBinaryOp(E->getAltOpcode())) || 3893 (Instruction::isCast(E->getOpcode()) && 3894 Instruction::isCast(E->getAltOpcode()))) && 3895 "Invalid Shuffle Vector Operand"); 3896 InstructionCost ScalarCost = 0; 3897 if (NeedToShuffleReuses) { 3898 for (unsigned Idx : E->ReuseShuffleIndices) { 3899 Instruction *I = cast<Instruction>(VL[Idx]); 3900 ReuseShuffleCost -= TTI->getInstructionCost(I, CostKind); 3901 } 3902 for (Value *V : VL) { 3903 Instruction *I = cast<Instruction>(V); 3904 ReuseShuffleCost += TTI->getInstructionCost(I, CostKind); 3905 } 3906 } 3907 for (Value *V : VL) { 3908 Instruction *I = cast<Instruction>(V); 3909 assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode"); 3910 ScalarCost += TTI->getInstructionCost(I, CostKind); 3911 } 3912 // VecCost is equal to sum of the cost of creating 2 vectors 3913 // and the cost of creating shuffle. 3914 InstructionCost VecCost = 0; 3915 if (Instruction::isBinaryOp(E->getOpcode())) { 3916 VecCost = TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind); 3917 VecCost += TTI->getArithmeticInstrCost(E->getAltOpcode(), VecTy, 3918 CostKind); 3919 } else { 3920 Type *Src0SclTy = E->getMainOp()->getOperand(0)->getType(); 3921 Type *Src1SclTy = E->getAltOp()->getOperand(0)->getType(); 3922 auto *Src0Ty = FixedVectorType::get(Src0SclTy, VL.size()); 3923 auto *Src1Ty = FixedVectorType::get(Src1SclTy, VL.size()); 3924 VecCost = TTI->getCastInstrCost(E->getOpcode(), VecTy, Src0Ty, 3925 TTI::CastContextHint::None, CostKind); 3926 VecCost += TTI->getCastInstrCost(E->getAltOpcode(), VecTy, Src1Ty, 3927 TTI::CastContextHint::None, CostKind); 3928 } 3929 3930 SmallVector<int> Mask(E->Scalars.size()); 3931 for (unsigned I = 0, End = E->Scalars.size(); I < End; ++I) { 3932 auto *OpInst = cast<Instruction>(E->Scalars[I]); 3933 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 3934 Mask[I] = I + (OpInst->getOpcode() == E->getAltOpcode() ? End : 0); 3935 } 3936 VecCost += 3937 TTI->getShuffleCost(TargetTransformInfo::SK_Select, VecTy, Mask, 0); 3938 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3939 return ReuseShuffleCost + VecCost - ScalarCost; 3940 } 3941 default: 3942 llvm_unreachable("Unknown instruction"); 3943 } 3944 } 3945 3946 bool BoUpSLP::isFullyVectorizableTinyTree() const { 3947 LLVM_DEBUG(dbgs() << "SLP: Check whether the tree with height " 3948 << VectorizableTree.size() << " is fully vectorizable .\n"); 3949 3950 // We only handle trees of heights 1 and 2. 3951 if (VectorizableTree.size() == 1 && 3952 VectorizableTree[0]->State == TreeEntry::Vectorize) 3953 return true; 3954 3955 if (VectorizableTree.size() != 2) 3956 return false; 3957 3958 // Handle splat and all-constants stores. 3959 if (VectorizableTree[0]->State == TreeEntry::Vectorize && 3960 (allConstant(VectorizableTree[1]->Scalars) || 3961 isSplat(VectorizableTree[1]->Scalars))) 3962 return true; 3963 3964 // Gathering cost would be too much for tiny trees. 3965 if (VectorizableTree[0]->State == TreeEntry::NeedToGather || 3966 VectorizableTree[1]->State == TreeEntry::NeedToGather) 3967 return false; 3968 3969 return true; 3970 } 3971 3972 static bool isLoadCombineCandidateImpl(Value *Root, unsigned NumElts, 3973 TargetTransformInfo *TTI) { 3974 // Look past the root to find a source value. Arbitrarily follow the 3975 // path through operand 0 of any 'or'. Also, peek through optional 3976 // shift-left-by-multiple-of-8-bits. 3977 Value *ZextLoad = Root; 3978 const APInt *ShAmtC; 3979 while (!isa<ConstantExpr>(ZextLoad) && 3980 (match(ZextLoad, m_Or(m_Value(), m_Value())) || 3981 (match(ZextLoad, m_Shl(m_Value(), m_APInt(ShAmtC))) && 3982 ShAmtC->urem(8) == 0))) 3983 ZextLoad = cast<BinaryOperator>(ZextLoad)->getOperand(0); 3984 3985 // Check if the input is an extended load of the required or/shift expression. 3986 Value *LoadPtr; 3987 if (ZextLoad == Root || !match(ZextLoad, m_ZExt(m_Load(m_Value(LoadPtr))))) 3988 return false; 3989 3990 // Require that the total load bit width is a legal integer type. 3991 // For example, <8 x i8> --> i64 is a legal integer on a 64-bit target. 3992 // But <16 x i8> --> i128 is not, so the backend probably can't reduce it. 3993 Type *SrcTy = LoadPtr->getType()->getPointerElementType(); 3994 unsigned LoadBitWidth = SrcTy->getIntegerBitWidth() * NumElts; 3995 if (!TTI->isTypeLegal(IntegerType::get(Root->getContext(), LoadBitWidth))) 3996 return false; 3997 3998 // Everything matched - assume that we can fold the whole sequence using 3999 // load combining. 4000 LLVM_DEBUG(dbgs() << "SLP: Assume load combining for tree starting at " 4001 << *(cast<Instruction>(Root)) << "\n"); 4002 4003 return true; 4004 } 4005 4006 bool BoUpSLP::isLoadCombineReductionCandidate(RecurKind RdxKind) const { 4007 if (RdxKind != RecurKind::Or) 4008 return false; 4009 4010 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 4011 Value *FirstReduced = VectorizableTree[0]->Scalars[0]; 4012 return isLoadCombineCandidateImpl(FirstReduced, NumElts, TTI); 4013 } 4014 4015 bool BoUpSLP::isLoadCombineCandidate() const { 4016 // Peek through a final sequence of stores and check if all operations are 4017 // likely to be load-combined. 4018 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 4019 for (Value *Scalar : VectorizableTree[0]->Scalars) { 4020 Value *X; 4021 if (!match(Scalar, m_Store(m_Value(X), m_Value())) || 4022 !isLoadCombineCandidateImpl(X, NumElts, TTI)) 4023 return false; 4024 } 4025 return true; 4026 } 4027 4028 bool BoUpSLP::isTreeTinyAndNotFullyVectorizable() const { 4029 // We can vectorize the tree if its size is greater than or equal to the 4030 // minimum size specified by the MinTreeSize command line option. 4031 if (VectorizableTree.size() >= MinTreeSize) 4032 return false; 4033 4034 // If we have a tiny tree (a tree whose size is less than MinTreeSize), we 4035 // can vectorize it if we can prove it fully vectorizable. 4036 if (isFullyVectorizableTinyTree()) 4037 return false; 4038 4039 assert(VectorizableTree.empty() 4040 ? ExternalUses.empty() 4041 : true && "We shouldn't have any external users"); 4042 4043 // Otherwise, we can't vectorize the tree. It is both tiny and not fully 4044 // vectorizable. 4045 return true; 4046 } 4047 4048 InstructionCost BoUpSLP::getSpillCost() const { 4049 // Walk from the bottom of the tree to the top, tracking which values are 4050 // live. When we see a call instruction that is not part of our tree, 4051 // query TTI to see if there is a cost to keeping values live over it 4052 // (for example, if spills and fills are required). 4053 unsigned BundleWidth = VectorizableTree.front()->Scalars.size(); 4054 InstructionCost Cost = 0; 4055 4056 SmallPtrSet<Instruction*, 4> LiveValues; 4057 Instruction *PrevInst = nullptr; 4058 4059 // The entries in VectorizableTree are not necessarily ordered by their 4060 // position in basic blocks. Collect them and order them by dominance so later 4061 // instructions are guaranteed to be visited first. For instructions in 4062 // different basic blocks, we only scan to the beginning of the block, so 4063 // their order does not matter, as long as all instructions in a basic block 4064 // are grouped together. Using dominance ensures a deterministic order. 4065 SmallVector<Instruction *, 16> OrderedScalars; 4066 for (const auto &TEPtr : VectorizableTree) { 4067 Instruction *Inst = dyn_cast<Instruction>(TEPtr->Scalars[0]); 4068 if (!Inst) 4069 continue; 4070 OrderedScalars.push_back(Inst); 4071 } 4072 llvm::stable_sort(OrderedScalars, [this](Instruction *A, Instruction *B) { 4073 return DT->dominates(B, A); 4074 }); 4075 4076 for (Instruction *Inst : OrderedScalars) { 4077 if (!PrevInst) { 4078 PrevInst = Inst; 4079 continue; 4080 } 4081 4082 // Update LiveValues. 4083 LiveValues.erase(PrevInst); 4084 for (auto &J : PrevInst->operands()) { 4085 if (isa<Instruction>(&*J) && getTreeEntry(&*J)) 4086 LiveValues.insert(cast<Instruction>(&*J)); 4087 } 4088 4089 LLVM_DEBUG({ 4090 dbgs() << "SLP: #LV: " << LiveValues.size(); 4091 for (auto *X : LiveValues) 4092 dbgs() << " " << X->getName(); 4093 dbgs() << ", Looking at "; 4094 Inst->dump(); 4095 }); 4096 4097 // Now find the sequence of instructions between PrevInst and Inst. 4098 unsigned NumCalls = 0; 4099 BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(), 4100 PrevInstIt = 4101 PrevInst->getIterator().getReverse(); 4102 while (InstIt != PrevInstIt) { 4103 if (PrevInstIt == PrevInst->getParent()->rend()) { 4104 PrevInstIt = Inst->getParent()->rbegin(); 4105 continue; 4106 } 4107 4108 // Debug information does not impact spill cost. 4109 if ((isa<CallInst>(&*PrevInstIt) && 4110 !isa<DbgInfoIntrinsic>(&*PrevInstIt)) && 4111 &*PrevInstIt != PrevInst) 4112 NumCalls++; 4113 4114 ++PrevInstIt; 4115 } 4116 4117 if (NumCalls) { 4118 SmallVector<Type*, 4> V; 4119 for (auto *II : LiveValues) 4120 V.push_back(FixedVectorType::get(II->getType(), BundleWidth)); 4121 Cost += NumCalls * TTI->getCostOfKeepingLiveOverCall(V); 4122 } 4123 4124 PrevInst = Inst; 4125 } 4126 4127 return Cost; 4128 } 4129 4130 InstructionCost BoUpSLP::getTreeCost() { 4131 InstructionCost Cost = 0; 4132 LLVM_DEBUG(dbgs() << "SLP: Calculating cost for tree of size " 4133 << VectorizableTree.size() << ".\n"); 4134 4135 unsigned BundleWidth = VectorizableTree[0]->Scalars.size(); 4136 4137 for (unsigned I = 0, E = VectorizableTree.size(); I < E; ++I) { 4138 TreeEntry &TE = *VectorizableTree[I].get(); 4139 4140 // We create duplicate tree entries for gather sequences that have multiple 4141 // uses. However, we should not compute the cost of duplicate sequences. 4142 // For example, if we have a build vector (i.e., insertelement sequence) 4143 // that is used by more than one vector instruction, we only need to 4144 // compute the cost of the insertelement instructions once. The redundant 4145 // instructions will be eliminated by CSE. 4146 // 4147 // We should consider not creating duplicate tree entries for gather 4148 // sequences, and instead add additional edges to the tree representing 4149 // their uses. Since such an approach results in fewer total entries, 4150 // existing heuristics based on tree size may yield different results. 4151 // 4152 if (TE.State == TreeEntry::NeedToGather && 4153 std::any_of(std::next(VectorizableTree.begin(), I + 1), 4154 VectorizableTree.end(), 4155 [TE](const std::unique_ptr<TreeEntry> &EntryPtr) { 4156 return EntryPtr->State == TreeEntry::NeedToGather && 4157 EntryPtr->isSame(TE.Scalars); 4158 })) 4159 continue; 4160 4161 InstructionCost C = getEntryCost(&TE); 4162 Cost += C; 4163 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C 4164 << " for bundle that starts with " << *TE.Scalars[0] 4165 << ".\n" 4166 << "SLP: Current total cost = " << Cost << "\n"); 4167 } 4168 4169 SmallPtrSet<Value *, 16> ExtractCostCalculated; 4170 InstructionCost ExtractCost = 0; 4171 for (ExternalUser &EU : ExternalUses) { 4172 // We only add extract cost once for the same scalar. 4173 if (!ExtractCostCalculated.insert(EU.Scalar).second) 4174 continue; 4175 4176 // Uses by ephemeral values are free (because the ephemeral value will be 4177 // removed prior to code generation, and so the extraction will be 4178 // removed as well). 4179 if (EphValues.count(EU.User)) 4180 continue; 4181 4182 // If we plan to rewrite the tree in a smaller type, we will need to sign 4183 // extend the extracted value back to the original type. Here, we account 4184 // for the extract and the added cost of the sign extend if needed. 4185 auto *VecTy = FixedVectorType::get(EU.Scalar->getType(), BundleWidth); 4186 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 4187 if (MinBWs.count(ScalarRoot)) { 4188 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 4189 auto Extend = 4190 MinBWs[ScalarRoot].second ? Instruction::SExt : Instruction::ZExt; 4191 VecTy = FixedVectorType::get(MinTy, BundleWidth); 4192 ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(), 4193 VecTy, EU.Lane); 4194 } else { 4195 ExtractCost += 4196 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, EU.Lane); 4197 } 4198 } 4199 4200 InstructionCost SpillCost = getSpillCost(); 4201 Cost += SpillCost + ExtractCost; 4202 4203 #ifndef NDEBUG 4204 SmallString<256> Str; 4205 { 4206 raw_svector_ostream OS(Str); 4207 OS << "SLP: Spill Cost = " << SpillCost << ".\n" 4208 << "SLP: Extract Cost = " << ExtractCost << ".\n" 4209 << "SLP: Total Cost = " << Cost << ".\n"; 4210 } 4211 LLVM_DEBUG(dbgs() << Str); 4212 if (ViewSLPTree) 4213 ViewGraph(this, "SLP" + F->getName(), false, Str); 4214 #endif 4215 4216 return Cost; 4217 } 4218 4219 InstructionCost 4220 BoUpSLP::getGatherCost(FixedVectorType *Ty, 4221 const DenseSet<unsigned> &ShuffledIndices) const { 4222 unsigned NumElts = Ty->getNumElements(); 4223 APInt DemandedElts = APInt::getNullValue(NumElts); 4224 for (unsigned I = 0; I < NumElts; ++I) 4225 if (!ShuffledIndices.count(I)) 4226 DemandedElts.setBit(I); 4227 InstructionCost Cost = 4228 TTI->getScalarizationOverhead(Ty, DemandedElts, /*Insert*/ true, 4229 /*Extract*/ false); 4230 if (!ShuffledIndices.empty()) 4231 Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, Ty); 4232 return Cost; 4233 } 4234 4235 InstructionCost BoUpSLP::getGatherCost(ArrayRef<Value *> VL) const { 4236 // Find the type of the operands in VL. 4237 Type *ScalarTy = VL[0]->getType(); 4238 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 4239 ScalarTy = SI->getValueOperand()->getType(); 4240 auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); 4241 // Find the cost of inserting/extracting values from the vector. 4242 // Check if the same elements are inserted several times and count them as 4243 // shuffle candidates. 4244 DenseSet<unsigned> ShuffledElements; 4245 DenseSet<Value *> UniqueElements; 4246 // Iterate in reverse order to consider insert elements with the high cost. 4247 for (unsigned I = VL.size(); I > 0; --I) { 4248 unsigned Idx = I - 1; 4249 if (!UniqueElements.insert(VL[Idx]).second) 4250 ShuffledElements.insert(Idx); 4251 } 4252 return getGatherCost(VecTy, ShuffledElements); 4253 } 4254 4255 // Perform operand reordering on the instructions in VL and return the reordered 4256 // operands in Left and Right. 4257 void BoUpSLP::reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 4258 SmallVectorImpl<Value *> &Left, 4259 SmallVectorImpl<Value *> &Right, 4260 const DataLayout &DL, 4261 ScalarEvolution &SE, 4262 const BoUpSLP &R) { 4263 if (VL.empty()) 4264 return; 4265 VLOperands Ops(VL, DL, SE, R); 4266 // Reorder the operands in place. 4267 Ops.reorder(); 4268 Left = Ops.getVL(0); 4269 Right = Ops.getVL(1); 4270 } 4271 4272 void BoUpSLP::setInsertPointAfterBundle(TreeEntry *E) { 4273 // Get the basic block this bundle is in. All instructions in the bundle 4274 // should be in this block. 4275 auto *Front = E->getMainOp(); 4276 auto *BB = Front->getParent(); 4277 assert(llvm::all_of(E->Scalars, [=](Value *V) -> bool { 4278 auto *I = cast<Instruction>(V); 4279 return !E->isOpcodeOrAlt(I) || I->getParent() == BB; 4280 })); 4281 4282 // The last instruction in the bundle in program order. 4283 Instruction *LastInst = nullptr; 4284 4285 // Find the last instruction. The common case should be that BB has been 4286 // scheduled, and the last instruction is VL.back(). So we start with 4287 // VL.back() and iterate over schedule data until we reach the end of the 4288 // bundle. The end of the bundle is marked by null ScheduleData. 4289 if (BlocksSchedules.count(BB)) { 4290 auto *Bundle = 4291 BlocksSchedules[BB]->getScheduleData(E->isOneOf(E->Scalars.back())); 4292 if (Bundle && Bundle->isPartOfBundle()) 4293 for (; Bundle; Bundle = Bundle->NextInBundle) 4294 if (Bundle->OpValue == Bundle->Inst) 4295 LastInst = Bundle->Inst; 4296 } 4297 4298 // LastInst can still be null at this point if there's either not an entry 4299 // for BB in BlocksSchedules or there's no ScheduleData available for 4300 // VL.back(). This can be the case if buildTree_rec aborts for various 4301 // reasons (e.g., the maximum recursion depth is reached, the maximum region 4302 // size is reached, etc.). ScheduleData is initialized in the scheduling 4303 // "dry-run". 4304 // 4305 // If this happens, we can still find the last instruction by brute force. We 4306 // iterate forwards from Front (inclusive) until we either see all 4307 // instructions in the bundle or reach the end of the block. If Front is the 4308 // last instruction in program order, LastInst will be set to Front, and we 4309 // will visit all the remaining instructions in the block. 4310 // 4311 // One of the reasons we exit early from buildTree_rec is to place an upper 4312 // bound on compile-time. Thus, taking an additional compile-time hit here is 4313 // not ideal. However, this should be exceedingly rare since it requires that 4314 // we both exit early from buildTree_rec and that the bundle be out-of-order 4315 // (causing us to iterate all the way to the end of the block). 4316 if (!LastInst) { 4317 SmallPtrSet<Value *, 16> Bundle(E->Scalars.begin(), E->Scalars.end()); 4318 for (auto &I : make_range(BasicBlock::iterator(Front), BB->end())) { 4319 if (Bundle.erase(&I) && E->isOpcodeOrAlt(&I)) 4320 LastInst = &I; 4321 if (Bundle.empty()) 4322 break; 4323 } 4324 } 4325 assert(LastInst && "Failed to find last instruction in bundle"); 4326 4327 // Set the insertion point after the last instruction in the bundle. Set the 4328 // debug location to Front. 4329 Builder.SetInsertPoint(BB, ++LastInst->getIterator()); 4330 Builder.SetCurrentDebugLocation(Front->getDebugLoc()); 4331 } 4332 4333 Value *BoUpSLP::gather(ArrayRef<Value *> VL) { 4334 Value *Val0 = 4335 isa<StoreInst>(VL[0]) ? cast<StoreInst>(VL[0])->getValueOperand() : VL[0]; 4336 FixedVectorType *VecTy = FixedVectorType::get(Val0->getType(), VL.size()); 4337 Value *Vec = PoisonValue::get(VecTy); 4338 unsigned InsIndex = 0; 4339 for (Value *Val : VL) { 4340 Vec = Builder.CreateInsertElement(Vec, Val, Builder.getInt32(InsIndex++)); 4341 auto *InsElt = dyn_cast<InsertElementInst>(Vec); 4342 if (!InsElt) 4343 continue; 4344 GatherSeq.insert(InsElt); 4345 CSEBlocks.insert(InsElt->getParent()); 4346 // Add to our 'need-to-extract' list. 4347 if (TreeEntry *Entry = getTreeEntry(Val)) { 4348 // Find which lane we need to extract. 4349 unsigned FoundLane = std::distance(Entry->Scalars.begin(), 4350 find(Entry->Scalars, Val)); 4351 assert(FoundLane < Entry->Scalars.size() && "Couldn't find extract lane"); 4352 if (!Entry->ReuseShuffleIndices.empty()) { 4353 FoundLane = std::distance(Entry->ReuseShuffleIndices.begin(), 4354 find(Entry->ReuseShuffleIndices, FoundLane)); 4355 } 4356 ExternalUses.push_back(ExternalUser(Val, InsElt, FoundLane)); 4357 } 4358 } 4359 4360 return Vec; 4361 } 4362 4363 Value *BoUpSLP::vectorizeTree(ArrayRef<Value *> VL) { 4364 InstructionsState S = getSameOpcode(VL); 4365 if (S.getOpcode()) { 4366 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 4367 if (E->isSame(VL)) { 4368 Value *V = vectorizeTree(E); 4369 if (VL.size() == E->Scalars.size() && !E->ReuseShuffleIndices.empty()) { 4370 // Reshuffle to get only unique values. 4371 // If some of the scalars are duplicated in the vectorization tree 4372 // entry, we do not vectorize them but instead generate a mask for the 4373 // reuses. But if there are several users of the same entry, they may 4374 // have different vectorization factors. This is especially important 4375 // for PHI nodes. In this case, we need to adapt the resulting 4376 // instruction for the user vectorization factor and have to reshuffle 4377 // it again to take only unique elements of the vector. Without this 4378 // code the function incorrectly returns reduced vector instruction 4379 // with the same elements, not with the unique ones. 4380 // block: 4381 // %phi = phi <2 x > { .., %entry} {%shuffle, %block} 4382 // %2 = shuffle <2 x > %phi, %poison, <4 x > <0, 0, 1, 1> 4383 // ... (use %2) 4384 // %shuffle = shuffle <2 x> %2, poison, <2 x> {0, 2} 4385 // br %block 4386 SmallVector<int, 4> UniqueIdxs; 4387 SmallSet<int, 4> UsedIdxs; 4388 int Pos = 0; 4389 for (int Idx : E->ReuseShuffleIndices) { 4390 if (UsedIdxs.insert(Idx).second) 4391 UniqueIdxs.emplace_back(Pos); 4392 ++Pos; 4393 } 4394 V = Builder.CreateShuffleVector(V, UniqueIdxs, "shrink.shuffle"); 4395 } 4396 return V; 4397 } 4398 } 4399 } 4400 4401 // Check that every instruction appears once in this bundle. 4402 SmallVector<int, 4> ReuseShuffleIndicies; 4403 SmallVector<Value *, 4> UniqueValues; 4404 if (VL.size() > 2) { 4405 DenseMap<Value *, unsigned> UniquePositions; 4406 for (Value *V : VL) { 4407 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 4408 ReuseShuffleIndicies.emplace_back(Res.first->second); 4409 if (Res.second || isa<Constant>(V)) 4410 UniqueValues.emplace_back(V); 4411 } 4412 // Do not shuffle single element or if number of unique values is not power 4413 // of 2. 4414 if (UniqueValues.size() == VL.size() || UniqueValues.size() <= 1 || 4415 !llvm::isPowerOf2_32(UniqueValues.size())) 4416 ReuseShuffleIndicies.clear(); 4417 else 4418 VL = UniqueValues; 4419 } 4420 4421 Value *Vec = gather(VL); 4422 if (!ReuseShuffleIndicies.empty()) { 4423 Vec = Builder.CreateShuffleVector(Vec, ReuseShuffleIndicies, "shuffle"); 4424 if (auto *I = dyn_cast<Instruction>(Vec)) { 4425 GatherSeq.insert(I); 4426 CSEBlocks.insert(I->getParent()); 4427 } 4428 } 4429 return Vec; 4430 } 4431 4432 namespace { 4433 /// Merges shuffle masks and emits final shuffle instruction, if required. 4434 class ShuffleInstructionBuilder { 4435 IRBuilderBase &Builder; 4436 bool IsFinalized = false; 4437 SmallVector<int, 4> Mask; 4438 4439 public: 4440 ShuffleInstructionBuilder(IRBuilderBase &Builder) : Builder(Builder) {} 4441 4442 /// Adds a mask, inverting it before applying. 4443 void addInversedMask(ArrayRef<unsigned> SubMask) { 4444 if (SubMask.empty()) 4445 return; 4446 SmallVector<int, 4> NewMask; 4447 inversePermutation(SubMask, NewMask); 4448 addMask(NewMask); 4449 } 4450 4451 /// Functions adds masks, merging them into single one. 4452 void addMask(ArrayRef<unsigned> SubMask) { 4453 SmallVector<int, 4> NewMask(SubMask.begin(), SubMask.end()); 4454 addMask(NewMask); 4455 } 4456 4457 void addMask(ArrayRef<int> SubMask) { 4458 if (SubMask.empty()) 4459 return; 4460 if (Mask.empty()) { 4461 Mask.append(SubMask.begin(), SubMask.end()); 4462 return; 4463 } 4464 SmallVector<int, 4> NewMask(SubMask.size(), SubMask.size()); 4465 int TermValue = std::min(Mask.size(), SubMask.size()); 4466 for (int I = 0, E = SubMask.size(); I < E; ++I) { 4467 if (SubMask[I] >= TermValue || Mask[SubMask[I]] >= TermValue) { 4468 NewMask[I] = E; 4469 continue; 4470 } 4471 NewMask[I] = Mask[SubMask[I]]; 4472 } 4473 Mask.swap(NewMask); 4474 } 4475 4476 Value *finalize(Value *V) { 4477 IsFinalized = true; 4478 if (Mask.empty()) 4479 return V; 4480 return Builder.CreateShuffleVector(V, Mask, "shuffle"); 4481 } 4482 4483 ~ShuffleInstructionBuilder() { 4484 assert((IsFinalized || Mask.empty()) && 4485 "Shuffle construction must be finalized."); 4486 } 4487 }; 4488 } // namespace 4489 4490 Value *BoUpSLP::vectorizeTree(TreeEntry *E) { 4491 IRBuilder<>::InsertPointGuard Guard(Builder); 4492 4493 if (E->VectorizedValue) { 4494 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *E->Scalars[0] << ".\n"); 4495 return E->VectorizedValue; 4496 } 4497 4498 ShuffleInstructionBuilder ShuffleBuilder(Builder); 4499 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 4500 if (E->State == TreeEntry::NeedToGather) { 4501 setInsertPointAfterBundle(E); 4502 Value *Vec = gather(E->Scalars); 4503 if (NeedToShuffleReuses) { 4504 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4505 Vec = ShuffleBuilder.finalize(Vec); 4506 if (auto *I = dyn_cast<Instruction>(Vec)) { 4507 GatherSeq.insert(I); 4508 CSEBlocks.insert(I->getParent()); 4509 } 4510 } 4511 E->VectorizedValue = Vec; 4512 return Vec; 4513 } 4514 4515 assert((E->State == TreeEntry::Vectorize || 4516 E->State == TreeEntry::ScatterVectorize) && 4517 "Unhandled state"); 4518 unsigned ShuffleOrOp = 4519 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 4520 Instruction *VL0 = E->getMainOp(); 4521 Type *ScalarTy = VL0->getType(); 4522 if (auto *Store = dyn_cast<StoreInst>(VL0)) 4523 ScalarTy = Store->getValueOperand()->getType(); 4524 auto *VecTy = FixedVectorType::get(ScalarTy, E->Scalars.size()); 4525 switch (ShuffleOrOp) { 4526 case Instruction::PHI: { 4527 auto *PH = cast<PHINode>(VL0); 4528 Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI()); 4529 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 4530 PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues()); 4531 Value *V = NewPhi; 4532 if (NeedToShuffleReuses) 4533 V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle"); 4534 4535 E->VectorizedValue = V; 4536 4537 // PHINodes may have multiple entries from the same block. We want to 4538 // visit every block once. 4539 SmallPtrSet<BasicBlock*, 4> VisitedBBs; 4540 4541 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 4542 ValueList Operands; 4543 BasicBlock *IBB = PH->getIncomingBlock(i); 4544 4545 if (!VisitedBBs.insert(IBB).second) { 4546 NewPhi->addIncoming(NewPhi->getIncomingValueForBlock(IBB), IBB); 4547 continue; 4548 } 4549 4550 Builder.SetInsertPoint(IBB->getTerminator()); 4551 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 4552 Value *Vec = vectorizeTree(E->getOperand(i)); 4553 NewPhi->addIncoming(Vec, IBB); 4554 } 4555 4556 assert(NewPhi->getNumIncomingValues() == PH->getNumIncomingValues() && 4557 "Invalid number of incoming values"); 4558 return V; 4559 } 4560 4561 case Instruction::ExtractElement: { 4562 Value *V = E->getSingleOperand(0); 4563 Builder.SetInsertPoint(VL0); 4564 ShuffleBuilder.addInversedMask(E->ReorderIndices); 4565 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4566 V = ShuffleBuilder.finalize(V); 4567 E->VectorizedValue = V; 4568 return V; 4569 } 4570 case Instruction::ExtractValue: { 4571 auto *LI = cast<LoadInst>(E->getSingleOperand(0)); 4572 Builder.SetInsertPoint(LI); 4573 auto *PtrTy = PointerType::get(VecTy, LI->getPointerAddressSpace()); 4574 Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy); 4575 LoadInst *V = Builder.CreateAlignedLoad(VecTy, Ptr, LI->getAlign()); 4576 Value *NewV = propagateMetadata(V, E->Scalars); 4577 ShuffleBuilder.addInversedMask(E->ReorderIndices); 4578 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4579 NewV = ShuffleBuilder.finalize(NewV); 4580 E->VectorizedValue = NewV; 4581 return NewV; 4582 } 4583 case Instruction::ZExt: 4584 case Instruction::SExt: 4585 case Instruction::FPToUI: 4586 case Instruction::FPToSI: 4587 case Instruction::FPExt: 4588 case Instruction::PtrToInt: 4589 case Instruction::IntToPtr: 4590 case Instruction::SIToFP: 4591 case Instruction::UIToFP: 4592 case Instruction::Trunc: 4593 case Instruction::FPTrunc: 4594 case Instruction::BitCast: { 4595 setInsertPointAfterBundle(E); 4596 4597 Value *InVec = vectorizeTree(E->getOperand(0)); 4598 4599 if (E->VectorizedValue) { 4600 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4601 return E->VectorizedValue; 4602 } 4603 4604 auto *CI = cast<CastInst>(VL0); 4605 Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy); 4606 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4607 V = ShuffleBuilder.finalize(V); 4608 4609 E->VectorizedValue = V; 4610 ++NumVectorInstructions; 4611 return V; 4612 } 4613 case Instruction::FCmp: 4614 case Instruction::ICmp: { 4615 setInsertPointAfterBundle(E); 4616 4617 Value *L = vectorizeTree(E->getOperand(0)); 4618 Value *R = vectorizeTree(E->getOperand(1)); 4619 4620 if (E->VectorizedValue) { 4621 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4622 return E->VectorizedValue; 4623 } 4624 4625 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 4626 Value *V = Builder.CreateCmp(P0, L, R); 4627 propagateIRFlags(V, E->Scalars, VL0); 4628 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4629 V = ShuffleBuilder.finalize(V); 4630 4631 E->VectorizedValue = V; 4632 ++NumVectorInstructions; 4633 return V; 4634 } 4635 case Instruction::Select: { 4636 setInsertPointAfterBundle(E); 4637 4638 Value *Cond = vectorizeTree(E->getOperand(0)); 4639 Value *True = vectorizeTree(E->getOperand(1)); 4640 Value *False = vectorizeTree(E->getOperand(2)); 4641 4642 if (E->VectorizedValue) { 4643 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4644 return E->VectorizedValue; 4645 } 4646 4647 Value *V = Builder.CreateSelect(Cond, True, False); 4648 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4649 V = ShuffleBuilder.finalize(V); 4650 4651 E->VectorizedValue = V; 4652 ++NumVectorInstructions; 4653 return V; 4654 } 4655 case Instruction::FNeg: { 4656 setInsertPointAfterBundle(E); 4657 4658 Value *Op = vectorizeTree(E->getOperand(0)); 4659 4660 if (E->VectorizedValue) { 4661 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4662 return E->VectorizedValue; 4663 } 4664 4665 Value *V = Builder.CreateUnOp( 4666 static_cast<Instruction::UnaryOps>(E->getOpcode()), Op); 4667 propagateIRFlags(V, E->Scalars, VL0); 4668 if (auto *I = dyn_cast<Instruction>(V)) 4669 V = propagateMetadata(I, E->Scalars); 4670 4671 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4672 V = ShuffleBuilder.finalize(V); 4673 4674 E->VectorizedValue = V; 4675 ++NumVectorInstructions; 4676 4677 return V; 4678 } 4679 case Instruction::Add: 4680 case Instruction::FAdd: 4681 case Instruction::Sub: 4682 case Instruction::FSub: 4683 case Instruction::Mul: 4684 case Instruction::FMul: 4685 case Instruction::UDiv: 4686 case Instruction::SDiv: 4687 case Instruction::FDiv: 4688 case Instruction::URem: 4689 case Instruction::SRem: 4690 case Instruction::FRem: 4691 case Instruction::Shl: 4692 case Instruction::LShr: 4693 case Instruction::AShr: 4694 case Instruction::And: 4695 case Instruction::Or: 4696 case Instruction::Xor: { 4697 setInsertPointAfterBundle(E); 4698 4699 Value *LHS = vectorizeTree(E->getOperand(0)); 4700 Value *RHS = vectorizeTree(E->getOperand(1)); 4701 4702 if (E->VectorizedValue) { 4703 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4704 return E->VectorizedValue; 4705 } 4706 4707 Value *V = Builder.CreateBinOp( 4708 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, 4709 RHS); 4710 propagateIRFlags(V, E->Scalars, VL0); 4711 if (auto *I = dyn_cast<Instruction>(V)) 4712 V = propagateMetadata(I, E->Scalars); 4713 4714 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4715 V = ShuffleBuilder.finalize(V); 4716 4717 E->VectorizedValue = V; 4718 ++NumVectorInstructions; 4719 4720 return V; 4721 } 4722 case Instruction::Load: { 4723 // Loads are inserted at the head of the tree because we don't want to 4724 // sink them all the way down past store instructions. 4725 bool IsReorder = E->updateStateIfReorder(); 4726 if (IsReorder) 4727 VL0 = E->getMainOp(); 4728 setInsertPointAfterBundle(E); 4729 4730 LoadInst *LI = cast<LoadInst>(VL0); 4731 Instruction *NewLI; 4732 unsigned AS = LI->getPointerAddressSpace(); 4733 Value *PO = LI->getPointerOperand(); 4734 if (E->State == TreeEntry::Vectorize) { 4735 4736 Value *VecPtr = Builder.CreateBitCast(PO, VecTy->getPointerTo(AS)); 4737 4738 // The pointer operand uses an in-tree scalar so we add the new BitCast 4739 // to ExternalUses list to make sure that an extract will be generated 4740 // in the future. 4741 if (getTreeEntry(PO)) 4742 ExternalUses.emplace_back(PO, cast<User>(VecPtr), 0); 4743 4744 NewLI = Builder.CreateAlignedLoad(VecTy, VecPtr, LI->getAlign()); 4745 } else { 4746 assert(E->State == TreeEntry::ScatterVectorize && "Unhandled state"); 4747 Value *VecPtr = vectorizeTree(E->getOperand(0)); 4748 // Use the minimum alignment of the gathered loads. 4749 Align CommonAlignment = LI->getAlign(); 4750 for (Value *V : E->Scalars) 4751 CommonAlignment = 4752 commonAlignment(CommonAlignment, cast<LoadInst>(V)->getAlign()); 4753 NewLI = Builder.CreateMaskedGather(VecPtr, CommonAlignment); 4754 } 4755 Value *V = propagateMetadata(NewLI, E->Scalars); 4756 4757 ShuffleBuilder.addInversedMask(E->ReorderIndices); 4758 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4759 V = ShuffleBuilder.finalize(V); 4760 E->VectorizedValue = V; 4761 ++NumVectorInstructions; 4762 return V; 4763 } 4764 case Instruction::Store: { 4765 bool IsReorder = !E->ReorderIndices.empty(); 4766 auto *SI = cast<StoreInst>( 4767 IsReorder ? E->Scalars[E->ReorderIndices.front()] : VL0); 4768 unsigned AS = SI->getPointerAddressSpace(); 4769 4770 setInsertPointAfterBundle(E); 4771 4772 Value *VecValue = vectorizeTree(E->getOperand(0)); 4773 ShuffleBuilder.addMask(E->ReorderIndices); 4774 VecValue = ShuffleBuilder.finalize(VecValue); 4775 4776 Value *ScalarPtr = SI->getPointerOperand(); 4777 Value *VecPtr = Builder.CreateBitCast( 4778 ScalarPtr, VecValue->getType()->getPointerTo(AS)); 4779 StoreInst *ST = Builder.CreateAlignedStore(VecValue, VecPtr, 4780 SI->getAlign()); 4781 4782 // The pointer operand uses an in-tree scalar, so add the new BitCast to 4783 // ExternalUses to make sure that an extract will be generated in the 4784 // future. 4785 if (getTreeEntry(ScalarPtr)) 4786 ExternalUses.push_back(ExternalUser(ScalarPtr, cast<User>(VecPtr), 0)); 4787 4788 Value *V = propagateMetadata(ST, E->Scalars); 4789 4790 E->VectorizedValue = V; 4791 ++NumVectorInstructions; 4792 return V; 4793 } 4794 case Instruction::GetElementPtr: { 4795 setInsertPointAfterBundle(E); 4796 4797 Value *Op0 = vectorizeTree(E->getOperand(0)); 4798 4799 std::vector<Value *> OpVecs; 4800 for (int j = 1, e = cast<GetElementPtrInst>(VL0)->getNumOperands(); j < e; 4801 ++j) { 4802 ValueList &VL = E->getOperand(j); 4803 // Need to cast all elements to the same type before vectorization to 4804 // avoid crash. 4805 Type *VL0Ty = VL0->getOperand(j)->getType(); 4806 Type *Ty = llvm::all_of( 4807 VL, [VL0Ty](Value *V) { return VL0Ty == V->getType(); }) 4808 ? VL0Ty 4809 : DL->getIndexType(cast<GetElementPtrInst>(VL0) 4810 ->getPointerOperandType() 4811 ->getScalarType()); 4812 for (Value *&V : VL) { 4813 auto *CI = cast<ConstantInt>(V); 4814 V = ConstantExpr::getIntegerCast(CI, Ty, 4815 CI->getValue().isSignBitSet()); 4816 } 4817 Value *OpVec = vectorizeTree(VL); 4818 OpVecs.push_back(OpVec); 4819 } 4820 4821 Value *V = Builder.CreateGEP( 4822 cast<GetElementPtrInst>(VL0)->getSourceElementType(), Op0, OpVecs); 4823 if (Instruction *I = dyn_cast<Instruction>(V)) 4824 V = propagateMetadata(I, E->Scalars); 4825 4826 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4827 V = ShuffleBuilder.finalize(V); 4828 4829 E->VectorizedValue = V; 4830 ++NumVectorInstructions; 4831 4832 return V; 4833 } 4834 case Instruction::Call: { 4835 CallInst *CI = cast<CallInst>(VL0); 4836 setInsertPointAfterBundle(E); 4837 4838 Intrinsic::ID IID = Intrinsic::not_intrinsic; 4839 if (Function *FI = CI->getCalledFunction()) 4840 IID = FI->getIntrinsicID(); 4841 4842 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 4843 4844 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 4845 bool UseIntrinsic = ID != Intrinsic::not_intrinsic && 4846 VecCallCosts.first <= VecCallCosts.second; 4847 4848 Value *ScalarArg = nullptr; 4849 std::vector<Value *> OpVecs; 4850 for (int j = 0, e = CI->getNumArgOperands(); j < e; ++j) { 4851 ValueList OpVL; 4852 // Some intrinsics have scalar arguments. This argument should not be 4853 // vectorized. 4854 if (UseIntrinsic && hasVectorInstrinsicScalarOpd(IID, j)) { 4855 CallInst *CEI = cast<CallInst>(VL0); 4856 ScalarArg = CEI->getArgOperand(j); 4857 OpVecs.push_back(CEI->getArgOperand(j)); 4858 continue; 4859 } 4860 4861 Value *OpVec = vectorizeTree(E->getOperand(j)); 4862 LLVM_DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n"); 4863 OpVecs.push_back(OpVec); 4864 } 4865 4866 Function *CF; 4867 if (!UseIntrinsic) { 4868 VFShape Shape = 4869 VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>( 4870 VecTy->getNumElements())), 4871 false /*HasGlobalPred*/); 4872 CF = VFDatabase(*CI).getVectorizedFunction(Shape); 4873 } else { 4874 Type *Tys[] = {FixedVectorType::get(CI->getType(), E->Scalars.size())}; 4875 CF = Intrinsic::getDeclaration(F->getParent(), ID, Tys); 4876 } 4877 4878 SmallVector<OperandBundleDef, 1> OpBundles; 4879 CI->getOperandBundlesAsDefs(OpBundles); 4880 Value *V = Builder.CreateCall(CF, OpVecs, OpBundles); 4881 4882 // The scalar argument uses an in-tree scalar so we add the new vectorized 4883 // call to ExternalUses list to make sure that an extract will be 4884 // generated in the future. 4885 if (ScalarArg && getTreeEntry(ScalarArg)) 4886 ExternalUses.push_back(ExternalUser(ScalarArg, cast<User>(V), 0)); 4887 4888 propagateIRFlags(V, E->Scalars, VL0); 4889 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4890 V = ShuffleBuilder.finalize(V); 4891 4892 E->VectorizedValue = V; 4893 ++NumVectorInstructions; 4894 return V; 4895 } 4896 case Instruction::ShuffleVector: { 4897 assert(E->isAltShuffle() && 4898 ((Instruction::isBinaryOp(E->getOpcode()) && 4899 Instruction::isBinaryOp(E->getAltOpcode())) || 4900 (Instruction::isCast(E->getOpcode()) && 4901 Instruction::isCast(E->getAltOpcode()))) && 4902 "Invalid Shuffle Vector Operand"); 4903 4904 Value *LHS = nullptr, *RHS = nullptr; 4905 if (Instruction::isBinaryOp(E->getOpcode())) { 4906 setInsertPointAfterBundle(E); 4907 LHS = vectorizeTree(E->getOperand(0)); 4908 RHS = vectorizeTree(E->getOperand(1)); 4909 } else { 4910 setInsertPointAfterBundle(E); 4911 LHS = vectorizeTree(E->getOperand(0)); 4912 } 4913 4914 if (E->VectorizedValue) { 4915 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4916 return E->VectorizedValue; 4917 } 4918 4919 Value *V0, *V1; 4920 if (Instruction::isBinaryOp(E->getOpcode())) { 4921 V0 = Builder.CreateBinOp( 4922 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, RHS); 4923 V1 = Builder.CreateBinOp( 4924 static_cast<Instruction::BinaryOps>(E->getAltOpcode()), LHS, RHS); 4925 } else { 4926 V0 = Builder.CreateCast( 4927 static_cast<Instruction::CastOps>(E->getOpcode()), LHS, VecTy); 4928 V1 = Builder.CreateCast( 4929 static_cast<Instruction::CastOps>(E->getAltOpcode()), LHS, VecTy); 4930 } 4931 4932 // Create shuffle to take alternate operations from the vector. 4933 // Also, gather up main and alt scalar ops to propagate IR flags to 4934 // each vector operation. 4935 ValueList OpScalars, AltScalars; 4936 unsigned e = E->Scalars.size(); 4937 SmallVector<int, 8> Mask(e); 4938 for (unsigned i = 0; i < e; ++i) { 4939 auto *OpInst = cast<Instruction>(E->Scalars[i]); 4940 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 4941 if (OpInst->getOpcode() == E->getAltOpcode()) { 4942 Mask[i] = e + i; 4943 AltScalars.push_back(E->Scalars[i]); 4944 } else { 4945 Mask[i] = i; 4946 OpScalars.push_back(E->Scalars[i]); 4947 } 4948 } 4949 4950 propagateIRFlags(V0, OpScalars); 4951 propagateIRFlags(V1, AltScalars); 4952 4953 Value *V = Builder.CreateShuffleVector(V0, V1, Mask); 4954 if (Instruction *I = dyn_cast<Instruction>(V)) 4955 V = propagateMetadata(I, E->Scalars); 4956 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4957 V = ShuffleBuilder.finalize(V); 4958 4959 E->VectorizedValue = V; 4960 ++NumVectorInstructions; 4961 4962 return V; 4963 } 4964 default: 4965 llvm_unreachable("unknown inst"); 4966 } 4967 return nullptr; 4968 } 4969 4970 Value *BoUpSLP::vectorizeTree() { 4971 ExtraValueToDebugLocsMap ExternallyUsedValues; 4972 return vectorizeTree(ExternallyUsedValues); 4973 } 4974 4975 Value * 4976 BoUpSLP::vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues) { 4977 // All blocks must be scheduled before any instructions are inserted. 4978 for (auto &BSIter : BlocksSchedules) { 4979 scheduleBlock(BSIter.second.get()); 4980 } 4981 4982 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4983 auto *VectorRoot = vectorizeTree(VectorizableTree[0].get()); 4984 4985 // If the vectorized tree can be rewritten in a smaller type, we truncate the 4986 // vectorized root. InstCombine will then rewrite the entire expression. We 4987 // sign extend the extracted values below. 4988 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 4989 if (MinBWs.count(ScalarRoot)) { 4990 if (auto *I = dyn_cast<Instruction>(VectorRoot)) { 4991 // If current instr is a phi and not the last phi, insert it after the 4992 // last phi node. 4993 if (isa<PHINode>(I)) 4994 Builder.SetInsertPoint(&*I->getParent()->getFirstInsertionPt()); 4995 else 4996 Builder.SetInsertPoint(&*++BasicBlock::iterator(I)); 4997 } 4998 auto BundleWidth = VectorizableTree[0]->Scalars.size(); 4999 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 5000 auto *VecTy = FixedVectorType::get(MinTy, BundleWidth); 5001 auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy); 5002 VectorizableTree[0]->VectorizedValue = Trunc; 5003 } 5004 5005 LLVM_DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size() 5006 << " values .\n"); 5007 5008 // If necessary, sign-extend or zero-extend ScalarRoot to the larger type 5009 // specified by ScalarType. 5010 auto extend = [&](Value *ScalarRoot, Value *Ex, Type *ScalarType) { 5011 if (!MinBWs.count(ScalarRoot)) 5012 return Ex; 5013 if (MinBWs[ScalarRoot].second) 5014 return Builder.CreateSExt(Ex, ScalarType); 5015 return Builder.CreateZExt(Ex, ScalarType); 5016 }; 5017 5018 // Extract all of the elements with the external uses. 5019 for (const auto &ExternalUse : ExternalUses) { 5020 Value *Scalar = ExternalUse.Scalar; 5021 llvm::User *User = ExternalUse.User; 5022 5023 // Skip users that we already RAUW. This happens when one instruction 5024 // has multiple uses of the same value. 5025 if (User && !is_contained(Scalar->users(), User)) 5026 continue; 5027 TreeEntry *E = getTreeEntry(Scalar); 5028 assert(E && "Invalid scalar"); 5029 assert(E->State != TreeEntry::NeedToGather && 5030 "Extracting from a gather list"); 5031 5032 Value *Vec = E->VectorizedValue; 5033 assert(Vec && "Can't find vectorizable value"); 5034 5035 Value *Lane = Builder.getInt32(ExternalUse.Lane); 5036 // If User == nullptr, the Scalar is used as extra arg. Generate 5037 // ExtractElement instruction and update the record for this scalar in 5038 // ExternallyUsedValues. 5039 if (!User) { 5040 assert(ExternallyUsedValues.count(Scalar) && 5041 "Scalar with nullptr as an external user must be registered in " 5042 "ExternallyUsedValues map"); 5043 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 5044 Builder.SetInsertPoint(VecI->getParent(), 5045 std::next(VecI->getIterator())); 5046 } else { 5047 Builder.SetInsertPoint(&F->getEntryBlock().front()); 5048 } 5049 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 5050 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 5051 CSEBlocks.insert(cast<Instruction>(Scalar)->getParent()); 5052 auto &Locs = ExternallyUsedValues[Scalar]; 5053 ExternallyUsedValues.insert({Ex, Locs}); 5054 ExternallyUsedValues.erase(Scalar); 5055 // Required to update internally referenced instructions. 5056 Scalar->replaceAllUsesWith(Ex); 5057 continue; 5058 } 5059 5060 // Generate extracts for out-of-tree users. 5061 // Find the insertion point for the extractelement lane. 5062 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 5063 if (PHINode *PH = dyn_cast<PHINode>(User)) { 5064 for (int i = 0, e = PH->getNumIncomingValues(); i != e; ++i) { 5065 if (PH->getIncomingValue(i) == Scalar) { 5066 Instruction *IncomingTerminator = 5067 PH->getIncomingBlock(i)->getTerminator(); 5068 if (isa<CatchSwitchInst>(IncomingTerminator)) { 5069 Builder.SetInsertPoint(VecI->getParent(), 5070 std::next(VecI->getIterator())); 5071 } else { 5072 Builder.SetInsertPoint(PH->getIncomingBlock(i)->getTerminator()); 5073 } 5074 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 5075 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 5076 CSEBlocks.insert(PH->getIncomingBlock(i)); 5077 PH->setOperand(i, Ex); 5078 } 5079 } 5080 } else { 5081 Builder.SetInsertPoint(cast<Instruction>(User)); 5082 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 5083 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 5084 CSEBlocks.insert(cast<Instruction>(User)->getParent()); 5085 User->replaceUsesOfWith(Scalar, Ex); 5086 } 5087 } else { 5088 Builder.SetInsertPoint(&F->getEntryBlock().front()); 5089 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 5090 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 5091 CSEBlocks.insert(&F->getEntryBlock()); 5092 User->replaceUsesOfWith(Scalar, Ex); 5093 } 5094 5095 LLVM_DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n"); 5096 } 5097 5098 // For each vectorized value: 5099 for (auto &TEPtr : VectorizableTree) { 5100 TreeEntry *Entry = TEPtr.get(); 5101 5102 // No need to handle users of gathered values. 5103 if (Entry->State == TreeEntry::NeedToGather) 5104 continue; 5105 5106 assert(Entry->VectorizedValue && "Can't find vectorizable value"); 5107 5108 // For each lane: 5109 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 5110 Value *Scalar = Entry->Scalars[Lane]; 5111 5112 #ifndef NDEBUG 5113 Type *Ty = Scalar->getType(); 5114 if (!Ty->isVoidTy()) { 5115 for (User *U : Scalar->users()) { 5116 LLVM_DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n"); 5117 5118 // It is legal to delete users in the ignorelist. 5119 assert((getTreeEntry(U) || is_contained(UserIgnoreList, U)) && 5120 "Deleting out-of-tree value"); 5121 } 5122 } 5123 #endif 5124 LLVM_DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n"); 5125 eraseInstruction(cast<Instruction>(Scalar)); 5126 } 5127 } 5128 5129 Builder.ClearInsertionPoint(); 5130 InstrElementSize.clear(); 5131 5132 return VectorizableTree[0]->VectorizedValue; 5133 } 5134 5135 void BoUpSLP::optimizeGatherSequence() { 5136 LLVM_DEBUG(dbgs() << "SLP: Optimizing " << GatherSeq.size() 5137 << " gather sequences instructions.\n"); 5138 // LICM InsertElementInst sequences. 5139 for (Instruction *I : GatherSeq) { 5140 if (isDeleted(I)) 5141 continue; 5142 5143 // Check if this block is inside a loop. 5144 Loop *L = LI->getLoopFor(I->getParent()); 5145 if (!L) 5146 continue; 5147 5148 // Check if it has a preheader. 5149 BasicBlock *PreHeader = L->getLoopPreheader(); 5150 if (!PreHeader) 5151 continue; 5152 5153 // If the vector or the element that we insert into it are 5154 // instructions that are defined in this basic block then we can't 5155 // hoist this instruction. 5156 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 5157 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 5158 if (Op0 && L->contains(Op0)) 5159 continue; 5160 if (Op1 && L->contains(Op1)) 5161 continue; 5162 5163 // We can hoist this instruction. Move it to the pre-header. 5164 I->moveBefore(PreHeader->getTerminator()); 5165 } 5166 5167 // Make a list of all reachable blocks in our CSE queue. 5168 SmallVector<const DomTreeNode *, 8> CSEWorkList; 5169 CSEWorkList.reserve(CSEBlocks.size()); 5170 for (BasicBlock *BB : CSEBlocks) 5171 if (DomTreeNode *N = DT->getNode(BB)) { 5172 assert(DT->isReachableFromEntry(N)); 5173 CSEWorkList.push_back(N); 5174 } 5175 5176 // Sort blocks by domination. This ensures we visit a block after all blocks 5177 // dominating it are visited. 5178 llvm::stable_sort(CSEWorkList, 5179 [this](const DomTreeNode *A, const DomTreeNode *B) { 5180 return DT->properlyDominates(A, B); 5181 }); 5182 5183 // Perform O(N^2) search over the gather sequences and merge identical 5184 // instructions. TODO: We can further optimize this scan if we split the 5185 // instructions into different buckets based on the insert lane. 5186 SmallVector<Instruction *, 16> Visited; 5187 for (auto I = CSEWorkList.begin(), E = CSEWorkList.end(); I != E; ++I) { 5188 assert(*I && 5189 (I == CSEWorkList.begin() || !DT->dominates(*I, *std::prev(I))) && 5190 "Worklist not sorted properly!"); 5191 BasicBlock *BB = (*I)->getBlock(); 5192 // For all instructions in blocks containing gather sequences: 5193 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e;) { 5194 Instruction *In = &*it++; 5195 if (isDeleted(In)) 5196 continue; 5197 if (!isa<InsertElementInst>(In) && !isa<ExtractElementInst>(In)) 5198 continue; 5199 5200 // Check if we can replace this instruction with any of the 5201 // visited instructions. 5202 for (Instruction *v : Visited) { 5203 if (In->isIdenticalTo(v) && 5204 DT->dominates(v->getParent(), In->getParent())) { 5205 In->replaceAllUsesWith(v); 5206 eraseInstruction(In); 5207 In = nullptr; 5208 break; 5209 } 5210 } 5211 if (In) { 5212 assert(!is_contained(Visited, In)); 5213 Visited.push_back(In); 5214 } 5215 } 5216 } 5217 CSEBlocks.clear(); 5218 GatherSeq.clear(); 5219 } 5220 5221 // Groups the instructions to a bundle (which is then a single scheduling entity) 5222 // and schedules instructions until the bundle gets ready. 5223 Optional<BoUpSLP::ScheduleData *> 5224 BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 5225 const InstructionsState &S) { 5226 if (isa<PHINode>(S.OpValue)) 5227 return nullptr; 5228 5229 // Initialize the instruction bundle. 5230 Instruction *OldScheduleEnd = ScheduleEnd; 5231 ScheduleData *PrevInBundle = nullptr; 5232 ScheduleData *Bundle = nullptr; 5233 bool ReSchedule = false; 5234 LLVM_DEBUG(dbgs() << "SLP: bundle: " << *S.OpValue << "\n"); 5235 5236 auto &&TryScheduleBundle = [this, OldScheduleEnd, SLP](bool ReSchedule, 5237 ScheduleData *Bundle) { 5238 // The scheduling region got new instructions at the lower end (or it is a 5239 // new region for the first bundle). This makes it necessary to 5240 // recalculate all dependencies. 5241 // It is seldom that this needs to be done a second time after adding the 5242 // initial bundle to the region. 5243 if (ScheduleEnd != OldScheduleEnd) { 5244 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) 5245 doForAllOpcodes(I, [](ScheduleData *SD) { SD->clearDependencies(); }); 5246 ReSchedule = true; 5247 } 5248 if (ReSchedule) { 5249 resetSchedule(); 5250 initialFillReadyList(ReadyInsts); 5251 } 5252 if (Bundle) { 5253 LLVM_DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle 5254 << " in block " << BB->getName() << "\n"); 5255 calculateDependencies(Bundle, /*InsertInReadyList=*/true, SLP); 5256 } 5257 5258 // Now try to schedule the new bundle or (if no bundle) just calculate 5259 // dependencies. As soon as the bundle is "ready" it means that there are no 5260 // cyclic dependencies and we can schedule it. Note that's important that we 5261 // don't "schedule" the bundle yet (see cancelScheduling). 5262 while (((!Bundle && ReSchedule) || (Bundle && !Bundle->isReady())) && 5263 !ReadyInsts.empty()) { 5264 ScheduleData *Picked = ReadyInsts.pop_back_val(); 5265 if (Picked->isSchedulingEntity() && Picked->isReady()) 5266 schedule(Picked, ReadyInsts); 5267 } 5268 }; 5269 5270 // Make sure that the scheduling region contains all 5271 // instructions of the bundle. 5272 for (Value *V : VL) { 5273 if (!extendSchedulingRegion(V, S)) { 5274 // If the scheduling region got new instructions at the lower end (or it 5275 // is a new region for the first bundle). This makes it necessary to 5276 // recalculate all dependencies. 5277 // Otherwise the compiler may crash trying to incorrectly calculate 5278 // dependencies and emit instruction in the wrong order at the actual 5279 // scheduling. 5280 TryScheduleBundle(/*ReSchedule=*/false, nullptr); 5281 return None; 5282 } 5283 } 5284 5285 for (Value *V : VL) { 5286 ScheduleData *BundleMember = getScheduleData(V); 5287 assert(BundleMember && 5288 "no ScheduleData for bundle member (maybe not in same basic block)"); 5289 if (BundleMember->IsScheduled) { 5290 // A bundle member was scheduled as single instruction before and now 5291 // needs to be scheduled as part of the bundle. We just get rid of the 5292 // existing schedule. 5293 LLVM_DEBUG(dbgs() << "SLP: reset schedule because " << *BundleMember 5294 << " was already scheduled\n"); 5295 ReSchedule = true; 5296 } 5297 assert(BundleMember->isSchedulingEntity() && 5298 "bundle member already part of other bundle"); 5299 if (PrevInBundle) { 5300 PrevInBundle->NextInBundle = BundleMember; 5301 } else { 5302 Bundle = BundleMember; 5303 } 5304 BundleMember->UnscheduledDepsInBundle = 0; 5305 Bundle->UnscheduledDepsInBundle += BundleMember->UnscheduledDeps; 5306 5307 // Group the instructions to a bundle. 5308 BundleMember->FirstInBundle = Bundle; 5309 PrevInBundle = BundleMember; 5310 } 5311 assert(Bundle && "Failed to find schedule bundle"); 5312 TryScheduleBundle(ReSchedule, Bundle); 5313 if (!Bundle->isReady()) { 5314 cancelScheduling(VL, S.OpValue); 5315 return None; 5316 } 5317 return Bundle; 5318 } 5319 5320 void BoUpSLP::BlockScheduling::cancelScheduling(ArrayRef<Value *> VL, 5321 Value *OpValue) { 5322 if (isa<PHINode>(OpValue)) 5323 return; 5324 5325 ScheduleData *Bundle = getScheduleData(OpValue); 5326 LLVM_DEBUG(dbgs() << "SLP: cancel scheduling of " << *Bundle << "\n"); 5327 assert(!Bundle->IsScheduled && 5328 "Can't cancel bundle which is already scheduled"); 5329 assert(Bundle->isSchedulingEntity() && Bundle->isPartOfBundle() && 5330 "tried to unbundle something which is not a bundle"); 5331 5332 // Un-bundle: make single instructions out of the bundle. 5333 ScheduleData *BundleMember = Bundle; 5334 while (BundleMember) { 5335 assert(BundleMember->FirstInBundle == Bundle && "corrupt bundle links"); 5336 BundleMember->FirstInBundle = BundleMember; 5337 ScheduleData *Next = BundleMember->NextInBundle; 5338 BundleMember->NextInBundle = nullptr; 5339 BundleMember->UnscheduledDepsInBundle = BundleMember->UnscheduledDeps; 5340 if (BundleMember->UnscheduledDepsInBundle == 0) { 5341 ReadyInsts.insert(BundleMember); 5342 } 5343 BundleMember = Next; 5344 } 5345 } 5346 5347 BoUpSLP::ScheduleData *BoUpSLP::BlockScheduling::allocateScheduleDataChunks() { 5348 // Allocate a new ScheduleData for the instruction. 5349 if (ChunkPos >= ChunkSize) { 5350 ScheduleDataChunks.push_back(std::make_unique<ScheduleData[]>(ChunkSize)); 5351 ChunkPos = 0; 5352 } 5353 return &(ScheduleDataChunks.back()[ChunkPos++]); 5354 } 5355 5356 bool BoUpSLP::BlockScheduling::extendSchedulingRegion(Value *V, 5357 const InstructionsState &S) { 5358 if (getScheduleData(V, isOneOf(S, V))) 5359 return true; 5360 Instruction *I = dyn_cast<Instruction>(V); 5361 assert(I && "bundle member must be an instruction"); 5362 assert(!isa<PHINode>(I) && "phi nodes don't need to be scheduled"); 5363 auto &&CheckSheduleForI = [this, &S](Instruction *I) -> bool { 5364 ScheduleData *ISD = getScheduleData(I); 5365 if (!ISD) 5366 return false; 5367 assert(isInSchedulingRegion(ISD) && 5368 "ScheduleData not in scheduling region"); 5369 ScheduleData *SD = allocateScheduleDataChunks(); 5370 SD->Inst = I; 5371 SD->init(SchedulingRegionID, S.OpValue); 5372 ExtraScheduleDataMap[I][S.OpValue] = SD; 5373 return true; 5374 }; 5375 if (CheckSheduleForI(I)) 5376 return true; 5377 if (!ScheduleStart) { 5378 // It's the first instruction in the new region. 5379 initScheduleData(I, I->getNextNode(), nullptr, nullptr); 5380 ScheduleStart = I; 5381 ScheduleEnd = I->getNextNode(); 5382 if (isOneOf(S, I) != I) 5383 CheckSheduleForI(I); 5384 assert(ScheduleEnd && "tried to vectorize a terminator?"); 5385 LLVM_DEBUG(dbgs() << "SLP: initialize schedule region to " << *I << "\n"); 5386 return true; 5387 } 5388 // Search up and down at the same time, because we don't know if the new 5389 // instruction is above or below the existing scheduling region. 5390 BasicBlock::reverse_iterator UpIter = 5391 ++ScheduleStart->getIterator().getReverse(); 5392 BasicBlock::reverse_iterator UpperEnd = BB->rend(); 5393 BasicBlock::iterator DownIter = ScheduleEnd->getIterator(); 5394 BasicBlock::iterator LowerEnd = BB->end(); 5395 while (UpIter != UpperEnd && DownIter != LowerEnd && &*UpIter != I && 5396 &*DownIter != I) { 5397 if (++ScheduleRegionSize > ScheduleRegionSizeLimit) { 5398 LLVM_DEBUG(dbgs() << "SLP: exceeded schedule region size limit\n"); 5399 return false; 5400 } 5401 5402 ++UpIter; 5403 ++DownIter; 5404 } 5405 if (DownIter == LowerEnd || (UpIter != UpperEnd && &*UpIter == I)) { 5406 assert(I->getParent() == ScheduleStart->getParent() && 5407 "Instruction is in wrong basic block."); 5408 initScheduleData(I, ScheduleStart, nullptr, FirstLoadStoreInRegion); 5409 ScheduleStart = I; 5410 if (isOneOf(S, I) != I) 5411 CheckSheduleForI(I); 5412 LLVM_DEBUG(dbgs() << "SLP: extend schedule region start to " << *I 5413 << "\n"); 5414 return true; 5415 } 5416 assert((UpIter == UpperEnd || (DownIter != LowerEnd && &*DownIter == I)) && 5417 "Expected to reach top of the basic block or instruction down the " 5418 "lower end."); 5419 assert(I->getParent() == ScheduleEnd->getParent() && 5420 "Instruction is in wrong basic block."); 5421 initScheduleData(ScheduleEnd, I->getNextNode(), LastLoadStoreInRegion, 5422 nullptr); 5423 ScheduleEnd = I->getNextNode(); 5424 if (isOneOf(S, I) != I) 5425 CheckSheduleForI(I); 5426 assert(ScheduleEnd && "tried to vectorize a terminator?"); 5427 LLVM_DEBUG(dbgs() << "SLP: extend schedule region end to " << *I << "\n"); 5428 return true; 5429 } 5430 5431 void BoUpSLP::BlockScheduling::initScheduleData(Instruction *FromI, 5432 Instruction *ToI, 5433 ScheduleData *PrevLoadStore, 5434 ScheduleData *NextLoadStore) { 5435 ScheduleData *CurrentLoadStore = PrevLoadStore; 5436 for (Instruction *I = FromI; I != ToI; I = I->getNextNode()) { 5437 ScheduleData *SD = ScheduleDataMap[I]; 5438 if (!SD) { 5439 SD = allocateScheduleDataChunks(); 5440 ScheduleDataMap[I] = SD; 5441 SD->Inst = I; 5442 } 5443 assert(!isInSchedulingRegion(SD) && 5444 "new ScheduleData already in scheduling region"); 5445 SD->init(SchedulingRegionID, I); 5446 5447 if (I->mayReadOrWriteMemory() && 5448 (!isa<IntrinsicInst>(I) || 5449 (cast<IntrinsicInst>(I)->getIntrinsicID() != Intrinsic::sideeffect && 5450 cast<IntrinsicInst>(I)->getIntrinsicID() != 5451 Intrinsic::pseudoprobe))) { 5452 // Update the linked list of memory accessing instructions. 5453 if (CurrentLoadStore) { 5454 CurrentLoadStore->NextLoadStore = SD; 5455 } else { 5456 FirstLoadStoreInRegion = SD; 5457 } 5458 CurrentLoadStore = SD; 5459 } 5460 } 5461 if (NextLoadStore) { 5462 if (CurrentLoadStore) 5463 CurrentLoadStore->NextLoadStore = NextLoadStore; 5464 } else { 5465 LastLoadStoreInRegion = CurrentLoadStore; 5466 } 5467 } 5468 5469 void BoUpSLP::BlockScheduling::calculateDependencies(ScheduleData *SD, 5470 bool InsertInReadyList, 5471 BoUpSLP *SLP) { 5472 assert(SD->isSchedulingEntity()); 5473 5474 SmallVector<ScheduleData *, 10> WorkList; 5475 WorkList.push_back(SD); 5476 5477 while (!WorkList.empty()) { 5478 ScheduleData *SD = WorkList.pop_back_val(); 5479 5480 ScheduleData *BundleMember = SD; 5481 while (BundleMember) { 5482 assert(isInSchedulingRegion(BundleMember)); 5483 if (!BundleMember->hasValidDependencies()) { 5484 5485 LLVM_DEBUG(dbgs() << "SLP: update deps of " << *BundleMember 5486 << "\n"); 5487 BundleMember->Dependencies = 0; 5488 BundleMember->resetUnscheduledDeps(); 5489 5490 // Handle def-use chain dependencies. 5491 if (BundleMember->OpValue != BundleMember->Inst) { 5492 ScheduleData *UseSD = getScheduleData(BundleMember->Inst); 5493 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 5494 BundleMember->Dependencies++; 5495 ScheduleData *DestBundle = UseSD->FirstInBundle; 5496 if (!DestBundle->IsScheduled) 5497 BundleMember->incrementUnscheduledDeps(1); 5498 if (!DestBundle->hasValidDependencies()) 5499 WorkList.push_back(DestBundle); 5500 } 5501 } else { 5502 for (User *U : BundleMember->Inst->users()) { 5503 if (isa<Instruction>(U)) { 5504 ScheduleData *UseSD = getScheduleData(U); 5505 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 5506 BundleMember->Dependencies++; 5507 ScheduleData *DestBundle = UseSD->FirstInBundle; 5508 if (!DestBundle->IsScheduled) 5509 BundleMember->incrementUnscheduledDeps(1); 5510 if (!DestBundle->hasValidDependencies()) 5511 WorkList.push_back(DestBundle); 5512 } 5513 } else { 5514 // I'm not sure if this can ever happen. But we need to be safe. 5515 // This lets the instruction/bundle never be scheduled and 5516 // eventually disable vectorization. 5517 BundleMember->Dependencies++; 5518 BundleMember->incrementUnscheduledDeps(1); 5519 } 5520 } 5521 } 5522 5523 // Handle the memory dependencies. 5524 ScheduleData *DepDest = BundleMember->NextLoadStore; 5525 if (DepDest) { 5526 Instruction *SrcInst = BundleMember->Inst; 5527 MemoryLocation SrcLoc = getLocation(SrcInst, SLP->AA); 5528 bool SrcMayWrite = BundleMember->Inst->mayWriteToMemory(); 5529 unsigned numAliased = 0; 5530 unsigned DistToSrc = 1; 5531 5532 while (DepDest) { 5533 assert(isInSchedulingRegion(DepDest)); 5534 5535 // We have two limits to reduce the complexity: 5536 // 1) AliasedCheckLimit: It's a small limit to reduce calls to 5537 // SLP->isAliased (which is the expensive part in this loop). 5538 // 2) MaxMemDepDistance: It's for very large blocks and it aborts 5539 // the whole loop (even if the loop is fast, it's quadratic). 5540 // It's important for the loop break condition (see below) to 5541 // check this limit even between two read-only instructions. 5542 if (DistToSrc >= MaxMemDepDistance || 5543 ((SrcMayWrite || DepDest->Inst->mayWriteToMemory()) && 5544 (numAliased >= AliasedCheckLimit || 5545 SLP->isAliased(SrcLoc, SrcInst, DepDest->Inst)))) { 5546 5547 // We increment the counter only if the locations are aliased 5548 // (instead of counting all alias checks). This gives a better 5549 // balance between reduced runtime and accurate dependencies. 5550 numAliased++; 5551 5552 DepDest->MemoryDependencies.push_back(BundleMember); 5553 BundleMember->Dependencies++; 5554 ScheduleData *DestBundle = DepDest->FirstInBundle; 5555 if (!DestBundle->IsScheduled) { 5556 BundleMember->incrementUnscheduledDeps(1); 5557 } 5558 if (!DestBundle->hasValidDependencies()) { 5559 WorkList.push_back(DestBundle); 5560 } 5561 } 5562 DepDest = DepDest->NextLoadStore; 5563 5564 // Example, explaining the loop break condition: Let's assume our 5565 // starting instruction is i0 and MaxMemDepDistance = 3. 5566 // 5567 // +--------v--v--v 5568 // i0,i1,i2,i3,i4,i5,i6,i7,i8 5569 // +--------^--^--^ 5570 // 5571 // MaxMemDepDistance let us stop alias-checking at i3 and we add 5572 // dependencies from i0 to i3,i4,.. (even if they are not aliased). 5573 // Previously we already added dependencies from i3 to i6,i7,i8 5574 // (because of MaxMemDepDistance). As we added a dependency from 5575 // i0 to i3, we have transitive dependencies from i0 to i6,i7,i8 5576 // and we can abort this loop at i6. 5577 if (DistToSrc >= 2 * MaxMemDepDistance) 5578 break; 5579 DistToSrc++; 5580 } 5581 } 5582 } 5583 BundleMember = BundleMember->NextInBundle; 5584 } 5585 if (InsertInReadyList && SD->isReady()) { 5586 ReadyInsts.push_back(SD); 5587 LLVM_DEBUG(dbgs() << "SLP: gets ready on update: " << *SD->Inst 5588 << "\n"); 5589 } 5590 } 5591 } 5592 5593 void BoUpSLP::BlockScheduling::resetSchedule() { 5594 assert(ScheduleStart && 5595 "tried to reset schedule on block which has not been scheduled"); 5596 for (Instruction *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 5597 doForAllOpcodes(I, [&](ScheduleData *SD) { 5598 assert(isInSchedulingRegion(SD) && 5599 "ScheduleData not in scheduling region"); 5600 SD->IsScheduled = false; 5601 SD->resetUnscheduledDeps(); 5602 }); 5603 } 5604 ReadyInsts.clear(); 5605 } 5606 5607 void BoUpSLP::scheduleBlock(BlockScheduling *BS) { 5608 if (!BS->ScheduleStart) 5609 return; 5610 5611 LLVM_DEBUG(dbgs() << "SLP: schedule block " << BS->BB->getName() << "\n"); 5612 5613 BS->resetSchedule(); 5614 5615 // For the real scheduling we use a more sophisticated ready-list: it is 5616 // sorted by the original instruction location. This lets the final schedule 5617 // be as close as possible to the original instruction order. 5618 struct ScheduleDataCompare { 5619 bool operator()(ScheduleData *SD1, ScheduleData *SD2) const { 5620 return SD2->SchedulingPriority < SD1->SchedulingPriority; 5621 } 5622 }; 5623 std::set<ScheduleData *, ScheduleDataCompare> ReadyInsts; 5624 5625 // Ensure that all dependency data is updated and fill the ready-list with 5626 // initial instructions. 5627 int Idx = 0; 5628 int NumToSchedule = 0; 5629 for (auto *I = BS->ScheduleStart; I != BS->ScheduleEnd; 5630 I = I->getNextNode()) { 5631 BS->doForAllOpcodes(I, [this, &Idx, &NumToSchedule, BS](ScheduleData *SD) { 5632 assert(SD->isPartOfBundle() == 5633 (getTreeEntry(SD->Inst) != nullptr) && 5634 "scheduler and vectorizer bundle mismatch"); 5635 SD->FirstInBundle->SchedulingPriority = Idx++; 5636 if (SD->isSchedulingEntity()) { 5637 BS->calculateDependencies(SD, false, this); 5638 NumToSchedule++; 5639 } 5640 }); 5641 } 5642 BS->initialFillReadyList(ReadyInsts); 5643 5644 Instruction *LastScheduledInst = BS->ScheduleEnd; 5645 5646 // Do the "real" scheduling. 5647 while (!ReadyInsts.empty()) { 5648 ScheduleData *picked = *ReadyInsts.begin(); 5649 ReadyInsts.erase(ReadyInsts.begin()); 5650 5651 // Move the scheduled instruction(s) to their dedicated places, if not 5652 // there yet. 5653 ScheduleData *BundleMember = picked; 5654 while (BundleMember) { 5655 Instruction *pickedInst = BundleMember->Inst; 5656 if (LastScheduledInst->getNextNode() != pickedInst) { 5657 BS->BB->getInstList().remove(pickedInst); 5658 BS->BB->getInstList().insert(LastScheduledInst->getIterator(), 5659 pickedInst); 5660 } 5661 LastScheduledInst = pickedInst; 5662 BundleMember = BundleMember->NextInBundle; 5663 } 5664 5665 BS->schedule(picked, ReadyInsts); 5666 NumToSchedule--; 5667 } 5668 assert(NumToSchedule == 0 && "could not schedule all instructions"); 5669 5670 // Avoid duplicate scheduling of the block. 5671 BS->ScheduleStart = nullptr; 5672 } 5673 5674 unsigned BoUpSLP::getVectorElementSize(Value *V) { 5675 // If V is a store, just return the width of the stored value (or value 5676 // truncated just before storing) without traversing the expression tree. 5677 // This is the common case. 5678 if (auto *Store = dyn_cast<StoreInst>(V)) { 5679 if (auto *Trunc = dyn_cast<TruncInst>(Store->getValueOperand())) 5680 return DL->getTypeSizeInBits(Trunc->getSrcTy()); 5681 return DL->getTypeSizeInBits(Store->getValueOperand()->getType()); 5682 } 5683 5684 auto E = InstrElementSize.find(V); 5685 if (E != InstrElementSize.end()) 5686 return E->second; 5687 5688 // If V is not a store, we can traverse the expression tree to find loads 5689 // that feed it. The type of the loaded value may indicate a more suitable 5690 // width than V's type. We want to base the vector element size on the width 5691 // of memory operations where possible. 5692 SmallVector<std::pair<Instruction *, BasicBlock *>, 16> Worklist; 5693 SmallPtrSet<Instruction *, 16> Visited; 5694 if (auto *I = dyn_cast<Instruction>(V)) { 5695 Worklist.emplace_back(I, I->getParent()); 5696 Visited.insert(I); 5697 } 5698 5699 // Traverse the expression tree in bottom-up order looking for loads. If we 5700 // encounter an instruction we don't yet handle, we give up. 5701 auto Width = 0u; 5702 while (!Worklist.empty()) { 5703 Instruction *I; 5704 BasicBlock *Parent; 5705 std::tie(I, Parent) = Worklist.pop_back_val(); 5706 5707 // We should only be looking at scalar instructions here. If the current 5708 // instruction has a vector type, skip. 5709 auto *Ty = I->getType(); 5710 if (isa<VectorType>(Ty)) 5711 continue; 5712 5713 // If the current instruction is a load, update MaxWidth to reflect the 5714 // width of the loaded value. 5715 if (isa<LoadInst>(I) || isa<ExtractElementInst>(I) || 5716 isa<ExtractValueInst>(I)) 5717 Width = std::max<unsigned>(Width, DL->getTypeSizeInBits(Ty)); 5718 5719 // Otherwise, we need to visit the operands of the instruction. We only 5720 // handle the interesting cases from buildTree here. If an operand is an 5721 // instruction we haven't yet visited and from the same basic block as the 5722 // user or the use is a PHI node, we add it to the worklist. 5723 else if (isa<PHINode>(I) || isa<CastInst>(I) || isa<GetElementPtrInst>(I) || 5724 isa<CmpInst>(I) || isa<SelectInst>(I) || isa<BinaryOperator>(I) || 5725 isa<UnaryOperator>(I)) { 5726 for (Use &U : I->operands()) 5727 if (auto *J = dyn_cast<Instruction>(U.get())) 5728 if (Visited.insert(J).second && 5729 (isa<PHINode>(I) || J->getParent() == Parent)) 5730 Worklist.emplace_back(J, J->getParent()); 5731 } else { 5732 break; 5733 } 5734 } 5735 5736 // If we didn't encounter a memory access in the expression tree, or if we 5737 // gave up for some reason, just return the width of V. Otherwise, return the 5738 // maximum width we found. 5739 if (!Width) { 5740 if (auto *CI = dyn_cast<CmpInst>(V)) 5741 V = CI->getOperand(0); 5742 Width = DL->getTypeSizeInBits(V->getType()); 5743 } 5744 5745 for (Instruction *I : Visited) 5746 InstrElementSize[I] = Width; 5747 5748 return Width; 5749 } 5750 5751 // Determine if a value V in a vectorizable expression Expr can be demoted to a 5752 // smaller type with a truncation. We collect the values that will be demoted 5753 // in ToDemote and additional roots that require investigating in Roots. 5754 static bool collectValuesToDemote(Value *V, SmallPtrSetImpl<Value *> &Expr, 5755 SmallVectorImpl<Value *> &ToDemote, 5756 SmallVectorImpl<Value *> &Roots) { 5757 // We can always demote constants. 5758 if (isa<Constant>(V)) { 5759 ToDemote.push_back(V); 5760 return true; 5761 } 5762 5763 // If the value is not an instruction in the expression with only one use, it 5764 // cannot be demoted. 5765 auto *I = dyn_cast<Instruction>(V); 5766 if (!I || !I->hasOneUse() || !Expr.count(I)) 5767 return false; 5768 5769 switch (I->getOpcode()) { 5770 5771 // We can always demote truncations and extensions. Since truncations can 5772 // seed additional demotion, we save the truncated value. 5773 case Instruction::Trunc: 5774 Roots.push_back(I->getOperand(0)); 5775 break; 5776 case Instruction::ZExt: 5777 case Instruction::SExt: 5778 break; 5779 5780 // We can demote certain binary operations if we can demote both of their 5781 // operands. 5782 case Instruction::Add: 5783 case Instruction::Sub: 5784 case Instruction::Mul: 5785 case Instruction::And: 5786 case Instruction::Or: 5787 case Instruction::Xor: 5788 if (!collectValuesToDemote(I->getOperand(0), Expr, ToDemote, Roots) || 5789 !collectValuesToDemote(I->getOperand(1), Expr, ToDemote, Roots)) 5790 return false; 5791 break; 5792 5793 // We can demote selects if we can demote their true and false values. 5794 case Instruction::Select: { 5795 SelectInst *SI = cast<SelectInst>(I); 5796 if (!collectValuesToDemote(SI->getTrueValue(), Expr, ToDemote, Roots) || 5797 !collectValuesToDemote(SI->getFalseValue(), Expr, ToDemote, Roots)) 5798 return false; 5799 break; 5800 } 5801 5802 // We can demote phis if we can demote all their incoming operands. Note that 5803 // we don't need to worry about cycles since we ensure single use above. 5804 case Instruction::PHI: { 5805 PHINode *PN = cast<PHINode>(I); 5806 for (Value *IncValue : PN->incoming_values()) 5807 if (!collectValuesToDemote(IncValue, Expr, ToDemote, Roots)) 5808 return false; 5809 break; 5810 } 5811 5812 // Otherwise, conservatively give up. 5813 default: 5814 return false; 5815 } 5816 5817 // Record the value that we can demote. 5818 ToDemote.push_back(V); 5819 return true; 5820 } 5821 5822 void BoUpSLP::computeMinimumValueSizes() { 5823 // If there are no external uses, the expression tree must be rooted by a 5824 // store. We can't demote in-memory values, so there is nothing to do here. 5825 if (ExternalUses.empty()) 5826 return; 5827 5828 // We only attempt to truncate integer expressions. 5829 auto &TreeRoot = VectorizableTree[0]->Scalars; 5830 auto *TreeRootIT = dyn_cast<IntegerType>(TreeRoot[0]->getType()); 5831 if (!TreeRootIT) 5832 return; 5833 5834 // If the expression is not rooted by a store, these roots should have 5835 // external uses. We will rely on InstCombine to rewrite the expression in 5836 // the narrower type. However, InstCombine only rewrites single-use values. 5837 // This means that if a tree entry other than a root is used externally, it 5838 // must have multiple uses and InstCombine will not rewrite it. The code 5839 // below ensures that only the roots are used externally. 5840 SmallPtrSet<Value *, 32> Expr(TreeRoot.begin(), TreeRoot.end()); 5841 for (auto &EU : ExternalUses) 5842 if (!Expr.erase(EU.Scalar)) 5843 return; 5844 if (!Expr.empty()) 5845 return; 5846 5847 // Collect the scalar values of the vectorizable expression. We will use this 5848 // context to determine which values can be demoted. If we see a truncation, 5849 // we mark it as seeding another demotion. 5850 for (auto &EntryPtr : VectorizableTree) 5851 Expr.insert(EntryPtr->Scalars.begin(), EntryPtr->Scalars.end()); 5852 5853 // Ensure the roots of the vectorizable tree don't form a cycle. They must 5854 // have a single external user that is not in the vectorizable tree. 5855 for (auto *Root : TreeRoot) 5856 if (!Root->hasOneUse() || Expr.count(*Root->user_begin())) 5857 return; 5858 5859 // Conservatively determine if we can actually truncate the roots of the 5860 // expression. Collect the values that can be demoted in ToDemote and 5861 // additional roots that require investigating in Roots. 5862 SmallVector<Value *, 32> ToDemote; 5863 SmallVector<Value *, 4> Roots; 5864 for (auto *Root : TreeRoot) 5865 if (!collectValuesToDemote(Root, Expr, ToDemote, Roots)) 5866 return; 5867 5868 // The maximum bit width required to represent all the values that can be 5869 // demoted without loss of precision. It would be safe to truncate the roots 5870 // of the expression to this width. 5871 auto MaxBitWidth = 8u; 5872 5873 // We first check if all the bits of the roots are demanded. If they're not, 5874 // we can truncate the roots to this narrower type. 5875 for (auto *Root : TreeRoot) { 5876 auto Mask = DB->getDemandedBits(cast<Instruction>(Root)); 5877 MaxBitWidth = std::max<unsigned>( 5878 Mask.getBitWidth() - Mask.countLeadingZeros(), MaxBitWidth); 5879 } 5880 5881 // True if the roots can be zero-extended back to their original type, rather 5882 // than sign-extended. We know that if the leading bits are not demanded, we 5883 // can safely zero-extend. So we initialize IsKnownPositive to True. 5884 bool IsKnownPositive = true; 5885 5886 // If all the bits of the roots are demanded, we can try a little harder to 5887 // compute a narrower type. This can happen, for example, if the roots are 5888 // getelementptr indices. InstCombine promotes these indices to the pointer 5889 // width. Thus, all their bits are technically demanded even though the 5890 // address computation might be vectorized in a smaller type. 5891 // 5892 // We start by looking at each entry that can be demoted. We compute the 5893 // maximum bit width required to store the scalar by using ValueTracking to 5894 // compute the number of high-order bits we can truncate. 5895 if (MaxBitWidth == DL->getTypeSizeInBits(TreeRoot[0]->getType()) && 5896 llvm::all_of(TreeRoot, [](Value *R) { 5897 assert(R->hasOneUse() && "Root should have only one use!"); 5898 return isa<GetElementPtrInst>(R->user_back()); 5899 })) { 5900 MaxBitWidth = 8u; 5901 5902 // Determine if the sign bit of all the roots is known to be zero. If not, 5903 // IsKnownPositive is set to False. 5904 IsKnownPositive = llvm::all_of(TreeRoot, [&](Value *R) { 5905 KnownBits Known = computeKnownBits(R, *DL); 5906 return Known.isNonNegative(); 5907 }); 5908 5909 // Determine the maximum number of bits required to store the scalar 5910 // values. 5911 for (auto *Scalar : ToDemote) { 5912 auto NumSignBits = ComputeNumSignBits(Scalar, *DL, 0, AC, nullptr, DT); 5913 auto NumTypeBits = DL->getTypeSizeInBits(Scalar->getType()); 5914 MaxBitWidth = std::max<unsigned>(NumTypeBits - NumSignBits, MaxBitWidth); 5915 } 5916 5917 // If we can't prove that the sign bit is zero, we must add one to the 5918 // maximum bit width to account for the unknown sign bit. This preserves 5919 // the existing sign bit so we can safely sign-extend the root back to the 5920 // original type. Otherwise, if we know the sign bit is zero, we will 5921 // zero-extend the root instead. 5922 // 5923 // FIXME: This is somewhat suboptimal, as there will be cases where adding 5924 // one to the maximum bit width will yield a larger-than-necessary 5925 // type. In general, we need to add an extra bit only if we can't 5926 // prove that the upper bit of the original type is equal to the 5927 // upper bit of the proposed smaller type. If these two bits are the 5928 // same (either zero or one) we know that sign-extending from the 5929 // smaller type will result in the same value. Here, since we can't 5930 // yet prove this, we are just making the proposed smaller type 5931 // larger to ensure correctness. 5932 if (!IsKnownPositive) 5933 ++MaxBitWidth; 5934 } 5935 5936 // Round MaxBitWidth up to the next power-of-two. 5937 if (!isPowerOf2_64(MaxBitWidth)) 5938 MaxBitWidth = NextPowerOf2(MaxBitWidth); 5939 5940 // If the maximum bit width we compute is less than the with of the roots' 5941 // type, we can proceed with the narrowing. Otherwise, do nothing. 5942 if (MaxBitWidth >= TreeRootIT->getBitWidth()) 5943 return; 5944 5945 // If we can truncate the root, we must collect additional values that might 5946 // be demoted as a result. That is, those seeded by truncations we will 5947 // modify. 5948 while (!Roots.empty()) 5949 collectValuesToDemote(Roots.pop_back_val(), Expr, ToDemote, Roots); 5950 5951 // Finally, map the values we can demote to the maximum bit with we computed. 5952 for (auto *Scalar : ToDemote) 5953 MinBWs[Scalar] = std::make_pair(MaxBitWidth, !IsKnownPositive); 5954 } 5955 5956 namespace { 5957 5958 /// The SLPVectorizer Pass. 5959 struct SLPVectorizer : public FunctionPass { 5960 SLPVectorizerPass Impl; 5961 5962 /// Pass identification, replacement for typeid 5963 static char ID; 5964 5965 explicit SLPVectorizer() : FunctionPass(ID) { 5966 initializeSLPVectorizerPass(*PassRegistry::getPassRegistry()); 5967 } 5968 5969 bool doInitialization(Module &M) override { 5970 return false; 5971 } 5972 5973 bool runOnFunction(Function &F) override { 5974 if (skipFunction(F)) 5975 return false; 5976 5977 auto *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 5978 auto *TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F); 5979 auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>(); 5980 auto *TLI = TLIP ? &TLIP->getTLI(F) : nullptr; 5981 auto *AA = &getAnalysis<AAResultsWrapperPass>().getAAResults(); 5982 auto *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 5983 auto *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 5984 auto *AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F); 5985 auto *DB = &getAnalysis<DemandedBitsWrapperPass>().getDemandedBits(); 5986 auto *ORE = &getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE(); 5987 5988 return Impl.runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 5989 } 5990 5991 void getAnalysisUsage(AnalysisUsage &AU) const override { 5992 FunctionPass::getAnalysisUsage(AU); 5993 AU.addRequired<AssumptionCacheTracker>(); 5994 AU.addRequired<ScalarEvolutionWrapperPass>(); 5995 AU.addRequired<AAResultsWrapperPass>(); 5996 AU.addRequired<TargetTransformInfoWrapperPass>(); 5997 AU.addRequired<LoopInfoWrapperPass>(); 5998 AU.addRequired<DominatorTreeWrapperPass>(); 5999 AU.addRequired<DemandedBitsWrapperPass>(); 6000 AU.addRequired<OptimizationRemarkEmitterWrapperPass>(); 6001 AU.addRequired<InjectTLIMappingsLegacy>(); 6002 AU.addPreserved<LoopInfoWrapperPass>(); 6003 AU.addPreserved<DominatorTreeWrapperPass>(); 6004 AU.addPreserved<AAResultsWrapperPass>(); 6005 AU.addPreserved<GlobalsAAWrapperPass>(); 6006 AU.setPreservesCFG(); 6007 } 6008 }; 6009 6010 } // end anonymous namespace 6011 6012 PreservedAnalyses SLPVectorizerPass::run(Function &F, FunctionAnalysisManager &AM) { 6013 auto *SE = &AM.getResult<ScalarEvolutionAnalysis>(F); 6014 auto *TTI = &AM.getResult<TargetIRAnalysis>(F); 6015 auto *TLI = AM.getCachedResult<TargetLibraryAnalysis>(F); 6016 auto *AA = &AM.getResult<AAManager>(F); 6017 auto *LI = &AM.getResult<LoopAnalysis>(F); 6018 auto *DT = &AM.getResult<DominatorTreeAnalysis>(F); 6019 auto *AC = &AM.getResult<AssumptionAnalysis>(F); 6020 auto *DB = &AM.getResult<DemandedBitsAnalysis>(F); 6021 auto *ORE = &AM.getResult<OptimizationRemarkEmitterAnalysis>(F); 6022 6023 bool Changed = runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 6024 if (!Changed) 6025 return PreservedAnalyses::all(); 6026 6027 PreservedAnalyses PA; 6028 PA.preserveSet<CFGAnalyses>(); 6029 PA.preserve<AAManager>(); 6030 PA.preserve<GlobalsAA>(); 6031 return PA; 6032 } 6033 6034 bool SLPVectorizerPass::runImpl(Function &F, ScalarEvolution *SE_, 6035 TargetTransformInfo *TTI_, 6036 TargetLibraryInfo *TLI_, AAResults *AA_, 6037 LoopInfo *LI_, DominatorTree *DT_, 6038 AssumptionCache *AC_, DemandedBits *DB_, 6039 OptimizationRemarkEmitter *ORE_) { 6040 if (!RunSLPVectorization) 6041 return false; 6042 SE = SE_; 6043 TTI = TTI_; 6044 TLI = TLI_; 6045 AA = AA_; 6046 LI = LI_; 6047 DT = DT_; 6048 AC = AC_; 6049 DB = DB_; 6050 DL = &F.getParent()->getDataLayout(); 6051 6052 Stores.clear(); 6053 GEPs.clear(); 6054 bool Changed = false; 6055 6056 // If the target claims to have no vector registers don't attempt 6057 // vectorization. 6058 if (!TTI->getNumberOfRegisters(TTI->getRegisterClassForType(true))) 6059 return false; 6060 6061 // Don't vectorize when the attribute NoImplicitFloat is used. 6062 if (F.hasFnAttribute(Attribute::NoImplicitFloat)) 6063 return false; 6064 6065 LLVM_DEBUG(dbgs() << "SLP: Analyzing blocks in " << F.getName() << ".\n"); 6066 6067 // Use the bottom up slp vectorizer to construct chains that start with 6068 // store instructions. 6069 BoUpSLP R(&F, SE, TTI, TLI, AA, LI, DT, AC, DB, DL, ORE_); 6070 6071 // A general note: the vectorizer must use BoUpSLP::eraseInstruction() to 6072 // delete instructions. 6073 6074 // Scan the blocks in the function in post order. 6075 for (auto BB : post_order(&F.getEntryBlock())) { 6076 collectSeedInstructions(BB); 6077 6078 // Vectorize trees that end at stores. 6079 if (!Stores.empty()) { 6080 LLVM_DEBUG(dbgs() << "SLP: Found stores for " << Stores.size() 6081 << " underlying objects.\n"); 6082 Changed |= vectorizeStoreChains(R); 6083 } 6084 6085 // Vectorize trees that end at reductions. 6086 Changed |= vectorizeChainsInBlock(BB, R); 6087 6088 // Vectorize the index computations of getelementptr instructions. This 6089 // is primarily intended to catch gather-like idioms ending at 6090 // non-consecutive loads. 6091 if (!GEPs.empty()) { 6092 LLVM_DEBUG(dbgs() << "SLP: Found GEPs for " << GEPs.size() 6093 << " underlying objects.\n"); 6094 Changed |= vectorizeGEPIndices(BB, R); 6095 } 6096 } 6097 6098 if (Changed) { 6099 R.optimizeGatherSequence(); 6100 LLVM_DEBUG(dbgs() << "SLP: vectorized \"" << F.getName() << "\"\n"); 6101 } 6102 return Changed; 6103 } 6104 6105 bool SLPVectorizerPass::vectorizeStoreChain(ArrayRef<Value *> Chain, BoUpSLP &R, 6106 unsigned Idx) { 6107 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " << Chain.size() 6108 << "\n"); 6109 const unsigned Sz = R.getVectorElementSize(Chain[0]); 6110 const unsigned MinVF = R.getMinVecRegSize() / Sz; 6111 unsigned VF = Chain.size(); 6112 6113 if (!isPowerOf2_32(Sz) || !isPowerOf2_32(VF) || VF < 2 || VF < MinVF) 6114 return false; 6115 6116 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << VF << " stores at offset " << Idx 6117 << "\n"); 6118 6119 R.buildTree(Chain); 6120 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 6121 // TODO: Handle orders of size less than number of elements in the vector. 6122 if (Order && Order->size() == Chain.size()) { 6123 // TODO: reorder tree nodes without tree rebuilding. 6124 SmallVector<Value *, 4> ReorderedOps(Chain.rbegin(), Chain.rend()); 6125 llvm::transform(*Order, ReorderedOps.begin(), 6126 [Chain](const unsigned Idx) { return Chain[Idx]; }); 6127 R.buildTree(ReorderedOps); 6128 } 6129 if (R.isTreeTinyAndNotFullyVectorizable()) 6130 return false; 6131 if (R.isLoadCombineCandidate()) 6132 return false; 6133 6134 R.computeMinimumValueSizes(); 6135 6136 InstructionCost Cost = R.getTreeCost(); 6137 6138 LLVM_DEBUG(dbgs() << "SLP: Found cost = " << Cost << " for VF =" << VF << "\n"); 6139 if (Cost < -SLPCostThreshold) { 6140 LLVM_DEBUG(dbgs() << "SLP: Decided to vectorize cost = " << Cost << "\n"); 6141 6142 using namespace ore; 6143 6144 R.getORE()->emit(OptimizationRemark(SV_NAME, "StoresVectorized", 6145 cast<StoreInst>(Chain[0])) 6146 << "Stores SLP vectorized with cost " << NV("Cost", Cost) 6147 << " and with tree size " 6148 << NV("TreeSize", R.getTreeSize())); 6149 6150 R.vectorizeTree(); 6151 return true; 6152 } 6153 6154 return false; 6155 } 6156 6157 bool SLPVectorizerPass::vectorizeStores(ArrayRef<StoreInst *> Stores, 6158 BoUpSLP &R) { 6159 // We may run into multiple chains that merge into a single chain. We mark the 6160 // stores that we vectorized so that we don't visit the same store twice. 6161 BoUpSLP::ValueSet VectorizedStores; 6162 bool Changed = false; 6163 6164 int E = Stores.size(); 6165 SmallBitVector Tails(E, false); 6166 int MaxIter = MaxStoreLookup.getValue(); 6167 SmallVector<std::pair<int, int>, 16> ConsecutiveChain( 6168 E, std::make_pair(E, INT_MAX)); 6169 SmallVector<SmallBitVector, 4> CheckedPairs(E, SmallBitVector(E, false)); 6170 int IterCnt; 6171 auto &&FindConsecutiveAccess = [this, &Stores, &Tails, &IterCnt, MaxIter, 6172 &CheckedPairs, 6173 &ConsecutiveChain](int K, int Idx) { 6174 if (IterCnt >= MaxIter) 6175 return true; 6176 if (CheckedPairs[Idx].test(K)) 6177 return ConsecutiveChain[K].second == 1 && 6178 ConsecutiveChain[K].first == Idx; 6179 ++IterCnt; 6180 CheckedPairs[Idx].set(K); 6181 CheckedPairs[K].set(Idx); 6182 Optional<int> Diff = getPointersDiff(Stores[K]->getPointerOperand(), 6183 Stores[Idx]->getPointerOperand(), *DL, 6184 *SE, /*StrictCheck=*/true); 6185 if (!Diff || *Diff == 0) 6186 return false; 6187 int Val = *Diff; 6188 if (Val < 0) { 6189 if (ConsecutiveChain[Idx].second > -Val) { 6190 Tails.set(K); 6191 ConsecutiveChain[Idx] = std::make_pair(K, -Val); 6192 } 6193 return false; 6194 } 6195 if (ConsecutiveChain[K].second <= Val) 6196 return false; 6197 6198 Tails.set(Idx); 6199 ConsecutiveChain[K] = std::make_pair(Idx, Val); 6200 return Val == 1; 6201 }; 6202 // Do a quadratic search on all of the given stores in reverse order and find 6203 // all of the pairs of stores that follow each other. 6204 for (int Idx = E - 1; Idx >= 0; --Idx) { 6205 // If a store has multiple consecutive store candidates, search according 6206 // to the sequence: Idx-1, Idx+1, Idx-2, Idx+2, ... 6207 // This is because usually pairing with immediate succeeding or preceding 6208 // candidate create the best chance to find slp vectorization opportunity. 6209 const int MaxLookDepth = std::max(E - Idx, Idx + 1); 6210 IterCnt = 0; 6211 for (int Offset = 1, F = MaxLookDepth; Offset < F; ++Offset) 6212 if ((Idx >= Offset && FindConsecutiveAccess(Idx - Offset, Idx)) || 6213 (Idx + Offset < E && FindConsecutiveAccess(Idx + Offset, Idx))) 6214 break; 6215 } 6216 6217 // Tracks if we tried to vectorize stores starting from the given tail 6218 // already. 6219 SmallBitVector TriedTails(E, false); 6220 // For stores that start but don't end a link in the chain: 6221 for (int Cnt = E; Cnt > 0; --Cnt) { 6222 int I = Cnt - 1; 6223 if (ConsecutiveChain[I].first == E || Tails.test(I)) 6224 continue; 6225 // We found a store instr that starts a chain. Now follow the chain and try 6226 // to vectorize it. 6227 BoUpSLP::ValueList Operands; 6228 // Collect the chain into a list. 6229 while (I != E && !VectorizedStores.count(Stores[I])) { 6230 Operands.push_back(Stores[I]); 6231 Tails.set(I); 6232 if (ConsecutiveChain[I].second != 1) { 6233 // Mark the new end in the chain and go back, if required. It might be 6234 // required if the original stores come in reversed order, for example. 6235 if (ConsecutiveChain[I].first != E && 6236 Tails.test(ConsecutiveChain[I].first) && !TriedTails.test(I) && 6237 !VectorizedStores.count(Stores[ConsecutiveChain[I].first])) { 6238 TriedTails.set(I); 6239 Tails.reset(ConsecutiveChain[I].first); 6240 if (Cnt < ConsecutiveChain[I].first + 2) 6241 Cnt = ConsecutiveChain[I].first + 2; 6242 } 6243 break; 6244 } 6245 // Move to the next value in the chain. 6246 I = ConsecutiveChain[I].first; 6247 } 6248 assert(!Operands.empty() && "Expected non-empty list of stores."); 6249 6250 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 6251 unsigned EltSize = R.getVectorElementSize(Operands[0]); 6252 unsigned MaxElts = llvm::PowerOf2Floor(MaxVecRegSize / EltSize); 6253 6254 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / EltSize); 6255 unsigned MaxVF = std::min(R.getMaximumVF(EltSize, Instruction::Store), 6256 MaxElts); 6257 6258 // FIXME: Is division-by-2 the correct step? Should we assert that the 6259 // register size is a power-of-2? 6260 unsigned StartIdx = 0; 6261 for (unsigned Size = MaxVF; Size >= MinVF; Size /= 2) { 6262 for (unsigned Cnt = StartIdx, E = Operands.size(); Cnt + Size <= E;) { 6263 ArrayRef<Value *> Slice = makeArrayRef(Operands).slice(Cnt, Size); 6264 if (!VectorizedStores.count(Slice.front()) && 6265 !VectorizedStores.count(Slice.back()) && 6266 vectorizeStoreChain(Slice, R, Cnt)) { 6267 // Mark the vectorized stores so that we don't vectorize them again. 6268 VectorizedStores.insert(Slice.begin(), Slice.end()); 6269 Changed = true; 6270 // If we vectorized initial block, no need to try to vectorize it 6271 // again. 6272 if (Cnt == StartIdx) 6273 StartIdx += Size; 6274 Cnt += Size; 6275 continue; 6276 } 6277 ++Cnt; 6278 } 6279 // Check if the whole array was vectorized already - exit. 6280 if (StartIdx >= Operands.size()) 6281 break; 6282 } 6283 } 6284 6285 return Changed; 6286 } 6287 6288 void SLPVectorizerPass::collectSeedInstructions(BasicBlock *BB) { 6289 // Initialize the collections. We will make a single pass over the block. 6290 Stores.clear(); 6291 GEPs.clear(); 6292 6293 // Visit the store and getelementptr instructions in BB and organize them in 6294 // Stores and GEPs according to the underlying objects of their pointer 6295 // operands. 6296 for (Instruction &I : *BB) { 6297 // Ignore store instructions that are volatile or have a pointer operand 6298 // that doesn't point to a scalar type. 6299 if (auto *SI = dyn_cast<StoreInst>(&I)) { 6300 if (!SI->isSimple()) 6301 continue; 6302 if (!isValidElementType(SI->getValueOperand()->getType())) 6303 continue; 6304 Stores[getUnderlyingObject(SI->getPointerOperand())].push_back(SI); 6305 } 6306 6307 // Ignore getelementptr instructions that have more than one index, a 6308 // constant index, or a pointer operand that doesn't point to a scalar 6309 // type. 6310 else if (auto *GEP = dyn_cast<GetElementPtrInst>(&I)) { 6311 auto Idx = GEP->idx_begin()->get(); 6312 if (GEP->getNumIndices() > 1 || isa<Constant>(Idx)) 6313 continue; 6314 if (!isValidElementType(Idx->getType())) 6315 continue; 6316 if (GEP->getType()->isVectorTy()) 6317 continue; 6318 GEPs[GEP->getPointerOperand()].push_back(GEP); 6319 } 6320 } 6321 } 6322 6323 bool SLPVectorizerPass::tryToVectorizePair(Value *A, Value *B, BoUpSLP &R) { 6324 if (!A || !B) 6325 return false; 6326 Value *VL[] = {A, B}; 6327 return tryToVectorizeList(VL, R, /*AllowReorder=*/true); 6328 } 6329 6330 bool SLPVectorizerPass::tryToVectorizeList(ArrayRef<Value *> VL, BoUpSLP &R, 6331 bool AllowReorder, 6332 ArrayRef<Value *> InsertUses) { 6333 if (VL.size() < 2) 6334 return false; 6335 6336 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize a list of length = " 6337 << VL.size() << ".\n"); 6338 6339 // Check that all of the parts are instructions of the same type, 6340 // we permit an alternate opcode via InstructionsState. 6341 InstructionsState S = getSameOpcode(VL); 6342 if (!S.getOpcode()) 6343 return false; 6344 6345 Instruction *I0 = cast<Instruction>(S.OpValue); 6346 // Make sure invalid types (including vector type) are rejected before 6347 // determining vectorization factor for scalar instructions. 6348 for (Value *V : VL) { 6349 Type *Ty = V->getType(); 6350 if (!isValidElementType(Ty)) { 6351 // NOTE: the following will give user internal llvm type name, which may 6352 // not be useful. 6353 R.getORE()->emit([&]() { 6354 std::string type_str; 6355 llvm::raw_string_ostream rso(type_str); 6356 Ty->print(rso); 6357 return OptimizationRemarkMissed(SV_NAME, "UnsupportedType", I0) 6358 << "Cannot SLP vectorize list: type " 6359 << rso.str() + " is unsupported by vectorizer"; 6360 }); 6361 return false; 6362 } 6363 } 6364 6365 unsigned Sz = R.getVectorElementSize(I0); 6366 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / Sz); 6367 unsigned MaxVF = std::max<unsigned>(PowerOf2Floor(VL.size()), MinVF); 6368 MaxVF = std::min(R.getMaximumVF(Sz, S.getOpcode()), MaxVF); 6369 if (MaxVF < 2) { 6370 R.getORE()->emit([&]() { 6371 return OptimizationRemarkMissed(SV_NAME, "SmallVF", I0) 6372 << "Cannot SLP vectorize list: vectorization factor " 6373 << "less than 2 is not supported"; 6374 }); 6375 return false; 6376 } 6377 6378 bool Changed = false; 6379 bool CandidateFound = false; 6380 InstructionCost MinCost = SLPCostThreshold.getValue(); 6381 6382 bool CompensateUseCost = 6383 !InsertUses.empty() && llvm::all_of(InsertUses, [](const Value *V) { 6384 return V && isa<InsertElementInst>(V); 6385 }); 6386 assert((!CompensateUseCost || InsertUses.size() == VL.size()) && 6387 "Each scalar expected to have an associated InsertElement user."); 6388 6389 unsigned NextInst = 0, MaxInst = VL.size(); 6390 for (unsigned VF = MaxVF; NextInst + 1 < MaxInst && VF >= MinVF; VF /= 2) { 6391 // No actual vectorization should happen, if number of parts is the same as 6392 // provided vectorization factor (i.e. the scalar type is used for vector 6393 // code during codegen). 6394 auto *VecTy = FixedVectorType::get(VL[0]->getType(), VF); 6395 if (TTI->getNumberOfParts(VecTy) == VF) 6396 continue; 6397 for (unsigned I = NextInst; I < MaxInst; ++I) { 6398 unsigned OpsWidth = 0; 6399 6400 if (I + VF > MaxInst) 6401 OpsWidth = MaxInst - I; 6402 else 6403 OpsWidth = VF; 6404 6405 if (!isPowerOf2_32(OpsWidth) || OpsWidth < 2) 6406 break; 6407 6408 ArrayRef<Value *> Ops = VL.slice(I, OpsWidth); 6409 // Check that a previous iteration of this loop did not delete the Value. 6410 if (llvm::any_of(Ops, [&R](Value *V) { 6411 auto *I = dyn_cast<Instruction>(V); 6412 return I && R.isDeleted(I); 6413 })) 6414 continue; 6415 6416 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << OpsWidth << " operations " 6417 << "\n"); 6418 6419 R.buildTree(Ops); 6420 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 6421 // TODO: check if we can allow reordering for more cases. 6422 if (AllowReorder && Order) { 6423 // TODO: reorder tree nodes without tree rebuilding. 6424 // Conceptually, there is nothing actually preventing us from trying to 6425 // reorder a larger list. In fact, we do exactly this when vectorizing 6426 // reductions. However, at this point, we only expect to get here when 6427 // there are exactly two operations. 6428 assert(Ops.size() == 2); 6429 Value *ReorderedOps[] = {Ops[1], Ops[0]}; 6430 R.buildTree(ReorderedOps, None); 6431 } 6432 if (R.isTreeTinyAndNotFullyVectorizable()) 6433 continue; 6434 6435 R.computeMinimumValueSizes(); 6436 InstructionCost Cost = R.getTreeCost(); 6437 CandidateFound = true; 6438 if (CompensateUseCost) { 6439 // TODO: Use TTI's getScalarizationOverhead for sequence of inserts 6440 // rather than sum of single inserts as the latter may overestimate 6441 // cost. This work should imply improving cost estimation for extracts 6442 // that added in for external (for vectorization tree) users,i.e. that 6443 // part should also switch to same interface. 6444 // For example, the following case is projected code after SLP: 6445 // %4 = extractelement <4 x i64> %3, i32 0 6446 // %v0 = insertelement <4 x i64> poison, i64 %4, i32 0 6447 // %5 = extractelement <4 x i64> %3, i32 1 6448 // %v1 = insertelement <4 x i64> %v0, i64 %5, i32 1 6449 // %6 = extractelement <4 x i64> %3, i32 2 6450 // %v2 = insertelement <4 x i64> %v1, i64 %6, i32 2 6451 // %7 = extractelement <4 x i64> %3, i32 3 6452 // %v3 = insertelement <4 x i64> %v2, i64 %7, i32 3 6453 // 6454 // Extracts here added by SLP in order to feed users (the inserts) of 6455 // original scalars and contribute to "ExtractCost" at cost evaluation. 6456 // The inserts in turn form sequence to build an aggregate that 6457 // detected by findBuildAggregate routine. 6458 // SLP makes an assumption that such sequence will be optimized away 6459 // later (instcombine) so it tries to compensate ExctractCost with 6460 // cost of insert sequence. 6461 // Current per element cost calculation approach is not quite accurate 6462 // and tends to create bias toward favoring vectorization. 6463 // Switching to the TTI interface might help a bit. 6464 // Alternative solution could be pattern-match to detect a no-op or 6465 // shuffle. 6466 InstructionCost UserCost = 0; 6467 for (unsigned Lane = 0; Lane < OpsWidth; Lane++) { 6468 auto *IE = cast<InsertElementInst>(InsertUses[I + Lane]); 6469 if (auto *CI = dyn_cast<ConstantInt>(IE->getOperand(2))) 6470 UserCost += TTI->getVectorInstrCost( 6471 Instruction::InsertElement, IE->getType(), CI->getZExtValue()); 6472 } 6473 LLVM_DEBUG(dbgs() << "SLP: Compensate cost of users by: " << UserCost 6474 << ".\n"); 6475 Cost -= UserCost; 6476 } 6477 6478 MinCost = std::min(MinCost, Cost); 6479 6480 if (Cost < -SLPCostThreshold) { 6481 LLVM_DEBUG(dbgs() << "SLP: Vectorizing list at cost:" << Cost << ".\n"); 6482 R.getORE()->emit(OptimizationRemark(SV_NAME, "VectorizedList", 6483 cast<Instruction>(Ops[0])) 6484 << "SLP vectorized with cost " << ore::NV("Cost", Cost) 6485 << " and with tree size " 6486 << ore::NV("TreeSize", R.getTreeSize())); 6487 6488 R.vectorizeTree(); 6489 // Move to the next bundle. 6490 I += VF - 1; 6491 NextInst = I + 1; 6492 Changed = true; 6493 } 6494 } 6495 } 6496 6497 if (!Changed && CandidateFound) { 6498 R.getORE()->emit([&]() { 6499 return OptimizationRemarkMissed(SV_NAME, "NotBeneficial", I0) 6500 << "List vectorization was possible but not beneficial with cost " 6501 << ore::NV("Cost", MinCost) << " >= " 6502 << ore::NV("Treshold", -SLPCostThreshold); 6503 }); 6504 } else if (!Changed) { 6505 R.getORE()->emit([&]() { 6506 return OptimizationRemarkMissed(SV_NAME, "NotPossible", I0) 6507 << "Cannot SLP vectorize list: vectorization was impossible" 6508 << " with available vectorization factors"; 6509 }); 6510 } 6511 return Changed; 6512 } 6513 6514 bool SLPVectorizerPass::tryToVectorize(Instruction *I, BoUpSLP &R) { 6515 if (!I) 6516 return false; 6517 6518 if (!isa<BinaryOperator>(I) && !isa<CmpInst>(I)) 6519 return false; 6520 6521 Value *P = I->getParent(); 6522 6523 // Vectorize in current basic block only. 6524 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 6525 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 6526 if (!Op0 || !Op1 || Op0->getParent() != P || Op1->getParent() != P) 6527 return false; 6528 6529 // Try to vectorize V. 6530 if (tryToVectorizePair(Op0, Op1, R)) 6531 return true; 6532 6533 auto *A = dyn_cast<BinaryOperator>(Op0); 6534 auto *B = dyn_cast<BinaryOperator>(Op1); 6535 // Try to skip B. 6536 if (B && B->hasOneUse()) { 6537 auto *B0 = dyn_cast<BinaryOperator>(B->getOperand(0)); 6538 auto *B1 = dyn_cast<BinaryOperator>(B->getOperand(1)); 6539 if (B0 && B0->getParent() == P && tryToVectorizePair(A, B0, R)) 6540 return true; 6541 if (B1 && B1->getParent() == P && tryToVectorizePair(A, B1, R)) 6542 return true; 6543 } 6544 6545 // Try to skip A. 6546 if (A && A->hasOneUse()) { 6547 auto *A0 = dyn_cast<BinaryOperator>(A->getOperand(0)); 6548 auto *A1 = dyn_cast<BinaryOperator>(A->getOperand(1)); 6549 if (A0 && A0->getParent() == P && tryToVectorizePair(A0, B, R)) 6550 return true; 6551 if (A1 && A1->getParent() == P && tryToVectorizePair(A1, B, R)) 6552 return true; 6553 } 6554 return false; 6555 } 6556 6557 namespace { 6558 6559 /// Model horizontal reductions. 6560 /// 6561 /// A horizontal reduction is a tree of reduction instructions that has values 6562 /// that can be put into a vector as its leaves. For example: 6563 /// 6564 /// mul mul mul mul 6565 /// \ / \ / 6566 /// + + 6567 /// \ / 6568 /// + 6569 /// This tree has "mul" as its leaf values and "+" as its reduction 6570 /// instructions. A reduction can feed into a store or a binary operation 6571 /// feeding a phi. 6572 /// ... 6573 /// \ / 6574 /// + 6575 /// | 6576 /// phi += 6577 /// 6578 /// Or: 6579 /// ... 6580 /// \ / 6581 /// + 6582 /// | 6583 /// *p = 6584 /// 6585 class HorizontalReduction { 6586 using ReductionOpsType = SmallVector<Value *, 16>; 6587 using ReductionOpsListType = SmallVector<ReductionOpsType, 2>; 6588 ReductionOpsListType ReductionOps; 6589 SmallVector<Value *, 32> ReducedVals; 6590 // Use map vector to make stable output. 6591 MapVector<Instruction *, Value *> ExtraArgs; 6592 WeakTrackingVH ReductionRoot; 6593 /// The type of reduction operation. 6594 RecurKind RdxKind; 6595 6596 /// Checks if instruction is associative and can be vectorized. 6597 static bool isVectorizable(RecurKind Kind, Instruction *I) { 6598 if (Kind == RecurKind::None) 6599 return false; 6600 if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(Kind)) 6601 return true; 6602 6603 if (Kind == RecurKind::FMax || Kind == RecurKind::FMin) { 6604 // FP min/max are associative except for NaN and -0.0. We do not 6605 // have to rule out -0.0 here because the intrinsic semantics do not 6606 // specify a fixed result for it. 6607 return I->getFastMathFlags().noNaNs(); 6608 } 6609 6610 return I->isAssociative(); 6611 } 6612 6613 /// Checks if the ParentStackElem.first should be marked as a reduction 6614 /// operation with an extra argument or as extra argument itself. 6615 void markExtraArg(std::pair<Instruction *, unsigned> &ParentStackElem, 6616 Value *ExtraArg) { 6617 if (ExtraArgs.count(ParentStackElem.first)) { 6618 ExtraArgs[ParentStackElem.first] = nullptr; 6619 // We ran into something like: 6620 // ParentStackElem.first = ExtraArgs[ParentStackElem.first] + ExtraArg. 6621 // The whole ParentStackElem.first should be considered as an extra value 6622 // in this case. 6623 // Do not perform analysis of remaining operands of ParentStackElem.first 6624 // instruction, this whole instruction is an extra argument. 6625 ParentStackElem.second = getNumberOfOperands(ParentStackElem.first); 6626 } else { 6627 // We ran into something like: 6628 // ParentStackElem.first += ... + ExtraArg + ... 6629 ExtraArgs[ParentStackElem.first] = ExtraArg; 6630 } 6631 } 6632 6633 /// Creates reduction operation with the current opcode. 6634 static Value *createOp(IRBuilder<> &Builder, RecurKind Kind, Value *LHS, 6635 Value *RHS, const Twine &Name, bool UseSelect) { 6636 unsigned RdxOpcode = RecurrenceDescriptor::getOpcode(Kind); 6637 switch (Kind) { 6638 case RecurKind::Add: 6639 case RecurKind::Mul: 6640 case RecurKind::Or: 6641 case RecurKind::And: 6642 case RecurKind::Xor: 6643 case RecurKind::FAdd: 6644 case RecurKind::FMul: 6645 return Builder.CreateBinOp((Instruction::BinaryOps)RdxOpcode, LHS, RHS, 6646 Name); 6647 case RecurKind::FMax: 6648 return Builder.CreateBinaryIntrinsic(Intrinsic::maxnum, LHS, RHS); 6649 case RecurKind::FMin: 6650 return Builder.CreateBinaryIntrinsic(Intrinsic::minnum, LHS, RHS); 6651 case RecurKind::SMax: 6652 if (UseSelect) { 6653 Value *Cmp = Builder.CreateICmpSGT(LHS, RHS, Name); 6654 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6655 } 6656 return Builder.CreateBinaryIntrinsic(Intrinsic::smax, LHS, RHS); 6657 case RecurKind::SMin: 6658 if (UseSelect) { 6659 Value *Cmp = Builder.CreateICmpSLT(LHS, RHS, Name); 6660 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6661 } 6662 return Builder.CreateBinaryIntrinsic(Intrinsic::smin, LHS, RHS); 6663 case RecurKind::UMax: 6664 if (UseSelect) { 6665 Value *Cmp = Builder.CreateICmpUGT(LHS, RHS, Name); 6666 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6667 } 6668 return Builder.CreateBinaryIntrinsic(Intrinsic::umax, LHS, RHS); 6669 case RecurKind::UMin: 6670 if (UseSelect) { 6671 Value *Cmp = Builder.CreateICmpULT(LHS, RHS, Name); 6672 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6673 } 6674 return Builder.CreateBinaryIntrinsic(Intrinsic::umin, LHS, RHS); 6675 default: 6676 llvm_unreachable("Unknown reduction operation."); 6677 } 6678 } 6679 6680 /// Creates reduction operation with the current opcode with the IR flags 6681 /// from \p ReductionOps. 6682 static Value *createOp(IRBuilder<> &Builder, RecurKind RdxKind, Value *LHS, 6683 Value *RHS, const Twine &Name, 6684 const ReductionOpsListType &ReductionOps) { 6685 bool UseSelect = ReductionOps.size() == 2; 6686 assert((!UseSelect || isa<SelectInst>(ReductionOps[1][0])) && 6687 "Expected cmp + select pairs for reduction"); 6688 Value *Op = createOp(Builder, RdxKind, LHS, RHS, Name, UseSelect); 6689 if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(RdxKind)) { 6690 if (auto *Sel = dyn_cast<SelectInst>(Op)) { 6691 propagateIRFlags(Sel->getCondition(), ReductionOps[0]); 6692 propagateIRFlags(Op, ReductionOps[1]); 6693 return Op; 6694 } 6695 } 6696 propagateIRFlags(Op, ReductionOps[0]); 6697 return Op; 6698 } 6699 6700 /// Creates reduction operation with the current opcode with the IR flags 6701 /// from \p I. 6702 static Value *createOp(IRBuilder<> &Builder, RecurKind RdxKind, Value *LHS, 6703 Value *RHS, const Twine &Name, Instruction *I) { 6704 auto *SelI = dyn_cast<SelectInst>(I); 6705 Value *Op = createOp(Builder, RdxKind, LHS, RHS, Name, SelI != nullptr); 6706 if (SelI && RecurrenceDescriptor::isIntMinMaxRecurrenceKind(RdxKind)) { 6707 if (auto *Sel = dyn_cast<SelectInst>(Op)) 6708 propagateIRFlags(Sel->getCondition(), SelI->getCondition()); 6709 } 6710 propagateIRFlags(Op, I); 6711 return Op; 6712 } 6713 6714 static RecurKind getRdxKind(Instruction *I) { 6715 assert(I && "Expected instruction for reduction matching"); 6716 TargetTransformInfo::ReductionFlags RdxFlags; 6717 if (match(I, m_Add(m_Value(), m_Value()))) 6718 return RecurKind::Add; 6719 if (match(I, m_Mul(m_Value(), m_Value()))) 6720 return RecurKind::Mul; 6721 if (match(I, m_And(m_Value(), m_Value()))) 6722 return RecurKind::And; 6723 if (match(I, m_Or(m_Value(), m_Value()))) 6724 return RecurKind::Or; 6725 if (match(I, m_Xor(m_Value(), m_Value()))) 6726 return RecurKind::Xor; 6727 if (match(I, m_FAdd(m_Value(), m_Value()))) 6728 return RecurKind::FAdd; 6729 if (match(I, m_FMul(m_Value(), m_Value()))) 6730 return RecurKind::FMul; 6731 6732 if (match(I, m_Intrinsic<Intrinsic::maxnum>(m_Value(), m_Value()))) 6733 return RecurKind::FMax; 6734 if (match(I, m_Intrinsic<Intrinsic::minnum>(m_Value(), m_Value()))) 6735 return RecurKind::FMin; 6736 6737 // This matches either cmp+select or intrinsics. SLP is expected to handle 6738 // either form. 6739 // TODO: If we are canonicalizing to intrinsics, we can remove several 6740 // special-case paths that deal with selects. 6741 if (match(I, m_SMax(m_Value(), m_Value()))) 6742 return RecurKind::SMax; 6743 if (match(I, m_SMin(m_Value(), m_Value()))) 6744 return RecurKind::SMin; 6745 if (match(I, m_UMax(m_Value(), m_Value()))) 6746 return RecurKind::UMax; 6747 if (match(I, m_UMin(m_Value(), m_Value()))) 6748 return RecurKind::UMin; 6749 6750 if (auto *Select = dyn_cast<SelectInst>(I)) { 6751 // Try harder: look for min/max pattern based on instructions producing 6752 // same values such as: select ((cmp Inst1, Inst2), Inst1, Inst2). 6753 // During the intermediate stages of SLP, it's very common to have 6754 // pattern like this (since optimizeGatherSequence is run only once 6755 // at the end): 6756 // %1 = extractelement <2 x i32> %a, i32 0 6757 // %2 = extractelement <2 x i32> %a, i32 1 6758 // %cond = icmp sgt i32 %1, %2 6759 // %3 = extractelement <2 x i32> %a, i32 0 6760 // %4 = extractelement <2 x i32> %a, i32 1 6761 // %select = select i1 %cond, i32 %3, i32 %4 6762 CmpInst::Predicate Pred; 6763 Instruction *L1; 6764 Instruction *L2; 6765 6766 Value *LHS = Select->getTrueValue(); 6767 Value *RHS = Select->getFalseValue(); 6768 Value *Cond = Select->getCondition(); 6769 6770 // TODO: Support inverse predicates. 6771 if (match(Cond, m_Cmp(Pred, m_Specific(LHS), m_Instruction(L2)))) { 6772 if (!isa<ExtractElementInst>(RHS) || 6773 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6774 return RecurKind::None; 6775 } else if (match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Specific(RHS)))) { 6776 if (!isa<ExtractElementInst>(LHS) || 6777 !L1->isIdenticalTo(cast<Instruction>(LHS))) 6778 return RecurKind::None; 6779 } else { 6780 if (!isa<ExtractElementInst>(LHS) || !isa<ExtractElementInst>(RHS)) 6781 return RecurKind::None; 6782 if (!match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Instruction(L2))) || 6783 !L1->isIdenticalTo(cast<Instruction>(LHS)) || 6784 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6785 return RecurKind::None; 6786 } 6787 6788 TargetTransformInfo::ReductionFlags RdxFlags; 6789 switch (Pred) { 6790 default: 6791 return RecurKind::None; 6792 case CmpInst::ICMP_SGT: 6793 case CmpInst::ICMP_SGE: 6794 return RecurKind::SMax; 6795 case CmpInst::ICMP_SLT: 6796 case CmpInst::ICMP_SLE: 6797 return RecurKind::SMin; 6798 case CmpInst::ICMP_UGT: 6799 case CmpInst::ICMP_UGE: 6800 return RecurKind::UMax; 6801 case CmpInst::ICMP_ULT: 6802 case CmpInst::ICMP_ULE: 6803 return RecurKind::UMin; 6804 } 6805 } 6806 return RecurKind::None; 6807 } 6808 6809 /// Get the index of the first operand. 6810 static unsigned getFirstOperandIndex(Instruction *I) { 6811 return isa<SelectInst>(I) ? 1 : 0; 6812 } 6813 6814 /// Total number of operands in the reduction operation. 6815 static unsigned getNumberOfOperands(Instruction *I) { 6816 return isa<SelectInst>(I) ? 3 : 2; 6817 } 6818 6819 /// Checks if the instruction is in basic block \p BB. 6820 /// For a min/max reduction check that both compare and select are in \p BB. 6821 static bool hasSameParent(Instruction *I, BasicBlock *BB, bool IsRedOp) { 6822 auto *Sel = dyn_cast<SelectInst>(I); 6823 if (IsRedOp && Sel) { 6824 auto *Cmp = cast<Instruction>(Sel->getCondition()); 6825 return Sel->getParent() == BB && Cmp->getParent() == BB; 6826 } 6827 return I->getParent() == BB; 6828 } 6829 6830 /// Expected number of uses for reduction operations/reduced values. 6831 static bool hasRequiredNumberOfUses(bool MatchCmpSel, Instruction *I) { 6832 // SelectInst must be used twice while the condition op must have single 6833 // use only. 6834 if (MatchCmpSel) { 6835 if (auto *Sel = dyn_cast<SelectInst>(I)) 6836 return Sel->hasNUses(2) && Sel->getCondition()->hasOneUse(); 6837 return I->hasNUses(2); 6838 } 6839 6840 // Arithmetic reduction operation must be used once only. 6841 return I->hasOneUse(); 6842 } 6843 6844 /// Initializes the list of reduction operations. 6845 void initReductionOps(Instruction *I) { 6846 if (isa<SelectInst>(I)) 6847 ReductionOps.assign(2, ReductionOpsType()); 6848 else 6849 ReductionOps.assign(1, ReductionOpsType()); 6850 } 6851 6852 /// Add all reduction operations for the reduction instruction \p I. 6853 void addReductionOps(Instruction *I) { 6854 if (auto *Sel = dyn_cast<SelectInst>(I)) { 6855 ReductionOps[0].emplace_back(Sel->getCondition()); 6856 ReductionOps[1].emplace_back(Sel); 6857 } else { 6858 ReductionOps[0].emplace_back(I); 6859 } 6860 } 6861 6862 static Value *getLHS(RecurKind Kind, Instruction *I) { 6863 if (Kind == RecurKind::None) 6864 return nullptr; 6865 return I->getOperand(getFirstOperandIndex(I)); 6866 } 6867 static Value *getRHS(RecurKind Kind, Instruction *I) { 6868 if (Kind == RecurKind::None) 6869 return nullptr; 6870 return I->getOperand(getFirstOperandIndex(I) + 1); 6871 } 6872 6873 public: 6874 HorizontalReduction() = default; 6875 6876 /// Try to find a reduction tree. 6877 bool matchAssociativeReduction(PHINode *Phi, Instruction *B) { 6878 assert((!Phi || is_contained(Phi->operands(), B)) && 6879 "Phi needs to use the binary operator"); 6880 6881 RdxKind = getRdxKind(B); 6882 6883 // We could have a initial reductions that is not an add. 6884 // r *= v1 + v2 + v3 + v4 6885 // In such a case start looking for a tree rooted in the first '+'. 6886 if (Phi) { 6887 if (getLHS(RdxKind, B) == Phi) { 6888 Phi = nullptr; 6889 B = dyn_cast<Instruction>(getRHS(RdxKind, B)); 6890 if (!B) 6891 return false; 6892 RdxKind = getRdxKind(B); 6893 } else if (getRHS(RdxKind, B) == Phi) { 6894 Phi = nullptr; 6895 B = dyn_cast<Instruction>(getLHS(RdxKind, B)); 6896 if (!B) 6897 return false; 6898 RdxKind = getRdxKind(B); 6899 } 6900 } 6901 6902 if (!isVectorizable(RdxKind, B)) 6903 return false; 6904 6905 // Analyze "regular" integer/FP types for reductions - no target-specific 6906 // types or pointers. 6907 Type *Ty = B->getType(); 6908 if (!isValidElementType(Ty) || Ty->isPointerTy()) 6909 return false; 6910 6911 // Though the ultimate reduction may have multiple uses, its condition must 6912 // have only single use. 6913 if (auto *SI = dyn_cast<SelectInst>(B)) 6914 if (!SI->getCondition()->hasOneUse()) 6915 return false; 6916 6917 ReductionRoot = B; 6918 6919 // The opcode for leaf values that we perform a reduction on. 6920 // For example: load(x) + load(y) + load(z) + fptoui(w) 6921 // The leaf opcode for 'w' does not match, so we don't include it as a 6922 // potential candidate for the reduction. 6923 unsigned LeafOpcode = 0; 6924 6925 // Post order traverse the reduction tree starting at B. We only handle true 6926 // trees containing only binary operators. 6927 SmallVector<std::pair<Instruction *, unsigned>, 32> Stack; 6928 Stack.push_back(std::make_pair(B, getFirstOperandIndex(B))); 6929 initReductionOps(B); 6930 while (!Stack.empty()) { 6931 Instruction *TreeN = Stack.back().first; 6932 unsigned EdgeToVisit = Stack.back().second++; 6933 const RecurKind TreeRdxKind = getRdxKind(TreeN); 6934 bool IsReducedValue = TreeRdxKind != RdxKind; 6935 6936 // Postorder visit. 6937 if (IsReducedValue || EdgeToVisit == getNumberOfOperands(TreeN)) { 6938 if (IsReducedValue) 6939 ReducedVals.push_back(TreeN); 6940 else { 6941 auto ExtraArgsIter = ExtraArgs.find(TreeN); 6942 if (ExtraArgsIter != ExtraArgs.end() && !ExtraArgsIter->second) { 6943 // Check if TreeN is an extra argument of its parent operation. 6944 if (Stack.size() <= 1) { 6945 // TreeN can't be an extra argument as it is a root reduction 6946 // operation. 6947 return false; 6948 } 6949 // Yes, TreeN is an extra argument, do not add it to a list of 6950 // reduction operations. 6951 // Stack[Stack.size() - 2] always points to the parent operation. 6952 markExtraArg(Stack[Stack.size() - 2], TreeN); 6953 ExtraArgs.erase(TreeN); 6954 } else 6955 addReductionOps(TreeN); 6956 } 6957 // Retract. 6958 Stack.pop_back(); 6959 continue; 6960 } 6961 6962 // Visit left or right. 6963 Value *EdgeVal = TreeN->getOperand(EdgeToVisit); 6964 auto *EdgeInst = dyn_cast<Instruction>(EdgeVal); 6965 if (!EdgeInst) { 6966 // Edge value is not a reduction instruction or a leaf instruction. 6967 // (It may be a constant, function argument, or something else.) 6968 markExtraArg(Stack.back(), EdgeVal); 6969 continue; 6970 } 6971 RecurKind EdgeRdxKind = getRdxKind(EdgeInst); 6972 // Continue analysis if the next operand is a reduction operation or 6973 // (possibly) a leaf value. If the leaf value opcode is not set, 6974 // the first met operation != reduction operation is considered as the 6975 // leaf opcode. 6976 // Only handle trees in the current basic block. 6977 // Each tree node needs to have minimal number of users except for the 6978 // ultimate reduction. 6979 const bool IsRdxInst = EdgeRdxKind == RdxKind; 6980 if (EdgeInst != Phi && EdgeInst != B && 6981 hasSameParent(EdgeInst, B->getParent(), IsRdxInst) && 6982 hasRequiredNumberOfUses(isa<SelectInst>(B), EdgeInst) && 6983 (!LeafOpcode || LeafOpcode == EdgeInst->getOpcode() || IsRdxInst)) { 6984 if (IsRdxInst) { 6985 // We need to be able to reassociate the reduction operations. 6986 if (!isVectorizable(EdgeRdxKind, EdgeInst)) { 6987 // I is an extra argument for TreeN (its parent operation). 6988 markExtraArg(Stack.back(), EdgeInst); 6989 continue; 6990 } 6991 } else if (!LeafOpcode) { 6992 LeafOpcode = EdgeInst->getOpcode(); 6993 } 6994 Stack.push_back( 6995 std::make_pair(EdgeInst, getFirstOperandIndex(EdgeInst))); 6996 continue; 6997 } 6998 // I is an extra argument for TreeN (its parent operation). 6999 markExtraArg(Stack.back(), EdgeInst); 7000 } 7001 return true; 7002 } 7003 7004 /// Attempt to vectorize the tree found by matchAssociativeReduction. 7005 bool tryToReduce(BoUpSLP &V, TargetTransformInfo *TTI) { 7006 // If there are a sufficient number of reduction values, reduce 7007 // to a nearby power-of-2. We can safely generate oversized 7008 // vectors and rely on the backend to split them to legal sizes. 7009 unsigned NumReducedVals = ReducedVals.size(); 7010 if (NumReducedVals < 4) 7011 return false; 7012 7013 // Intersect the fast-math-flags from all reduction operations. 7014 FastMathFlags RdxFMF; 7015 RdxFMF.set(); 7016 for (ReductionOpsType &RdxOp : ReductionOps) { 7017 for (Value *RdxVal : RdxOp) { 7018 if (auto *FPMO = dyn_cast<FPMathOperator>(RdxVal)) 7019 RdxFMF &= FPMO->getFastMathFlags(); 7020 } 7021 } 7022 7023 IRBuilder<> Builder(cast<Instruction>(ReductionRoot)); 7024 Builder.setFastMathFlags(RdxFMF); 7025 7026 BoUpSLP::ExtraValueToDebugLocsMap ExternallyUsedValues; 7027 // The same extra argument may be used several times, so log each attempt 7028 // to use it. 7029 for (const std::pair<Instruction *, Value *> &Pair : ExtraArgs) { 7030 assert(Pair.first && "DebugLoc must be set."); 7031 ExternallyUsedValues[Pair.second].push_back(Pair.first); 7032 } 7033 7034 // The compare instruction of a min/max is the insertion point for new 7035 // instructions and may be replaced with a new compare instruction. 7036 auto getCmpForMinMaxReduction = [](Instruction *RdxRootInst) { 7037 assert(isa<SelectInst>(RdxRootInst) && 7038 "Expected min/max reduction to have select root instruction"); 7039 Value *ScalarCond = cast<SelectInst>(RdxRootInst)->getCondition(); 7040 assert(isa<Instruction>(ScalarCond) && 7041 "Expected min/max reduction to have compare condition"); 7042 return cast<Instruction>(ScalarCond); 7043 }; 7044 7045 // The reduction root is used as the insertion point for new instructions, 7046 // so set it as externally used to prevent it from being deleted. 7047 ExternallyUsedValues[ReductionRoot]; 7048 SmallVector<Value *, 16> IgnoreList; 7049 for (ReductionOpsType &RdxOp : ReductionOps) 7050 IgnoreList.append(RdxOp.begin(), RdxOp.end()); 7051 7052 unsigned ReduxWidth = PowerOf2Floor(NumReducedVals); 7053 if (NumReducedVals > ReduxWidth) { 7054 // In the loop below, we are building a tree based on a window of 7055 // 'ReduxWidth' values. 7056 // If the operands of those values have common traits (compare predicate, 7057 // constant operand, etc), then we want to group those together to 7058 // minimize the cost of the reduction. 7059 7060 // TODO: This should be extended to count common operands for 7061 // compares and binops. 7062 7063 // Step 1: Count the number of times each compare predicate occurs. 7064 SmallDenseMap<unsigned, unsigned> PredCountMap; 7065 for (Value *RdxVal : ReducedVals) { 7066 CmpInst::Predicate Pred; 7067 if (match(RdxVal, m_Cmp(Pred, m_Value(), m_Value()))) 7068 ++PredCountMap[Pred]; 7069 } 7070 // Step 2: Sort the values so the most common predicates come first. 7071 stable_sort(ReducedVals, [&PredCountMap](Value *A, Value *B) { 7072 CmpInst::Predicate PredA, PredB; 7073 if (match(A, m_Cmp(PredA, m_Value(), m_Value())) && 7074 match(B, m_Cmp(PredB, m_Value(), m_Value()))) { 7075 return PredCountMap[PredA] > PredCountMap[PredB]; 7076 } 7077 return false; 7078 }); 7079 } 7080 7081 Value *VectorizedTree = nullptr; 7082 unsigned i = 0; 7083 while (i < NumReducedVals - ReduxWidth + 1 && ReduxWidth > 2) { 7084 ArrayRef<Value *> VL(&ReducedVals[i], ReduxWidth); 7085 V.buildTree(VL, ExternallyUsedValues, IgnoreList); 7086 Optional<ArrayRef<unsigned>> Order = V.bestOrder(); 7087 if (Order) { 7088 assert(Order->size() == VL.size() && 7089 "Order size must be the same as number of vectorized " 7090 "instructions."); 7091 // TODO: reorder tree nodes without tree rebuilding. 7092 SmallVector<Value *, 4> ReorderedOps(VL.size()); 7093 llvm::transform(*Order, ReorderedOps.begin(), 7094 [VL](const unsigned Idx) { return VL[Idx]; }); 7095 V.buildTree(ReorderedOps, ExternallyUsedValues, IgnoreList); 7096 } 7097 if (V.isTreeTinyAndNotFullyVectorizable()) 7098 break; 7099 if (V.isLoadCombineReductionCandidate(RdxKind)) 7100 break; 7101 7102 V.computeMinimumValueSizes(); 7103 7104 // Estimate cost. 7105 InstructionCost TreeCost = V.getTreeCost(); 7106 InstructionCost ReductionCost = 7107 getReductionCost(TTI, ReducedVals[i], ReduxWidth); 7108 InstructionCost Cost = TreeCost + ReductionCost; 7109 if (!Cost.isValid()) { 7110 LLVM_DEBUG(dbgs() << "Encountered invalid baseline cost.\n"); 7111 return false; 7112 } 7113 if (Cost >= -SLPCostThreshold) { 7114 V.getORE()->emit([&]() { 7115 return OptimizationRemarkMissed(SV_NAME, "HorSLPNotBeneficial", 7116 cast<Instruction>(VL[0])) 7117 << "Vectorizing horizontal reduction is possible" 7118 << "but not beneficial with cost " << ore::NV("Cost", Cost) 7119 << " and threshold " 7120 << ore::NV("Threshold", -SLPCostThreshold); 7121 }); 7122 break; 7123 } 7124 7125 LLVM_DEBUG(dbgs() << "SLP: Vectorizing horizontal reduction at cost:" 7126 << Cost << ". (HorRdx)\n"); 7127 V.getORE()->emit([&]() { 7128 return OptimizationRemark(SV_NAME, "VectorizedHorizontalReduction", 7129 cast<Instruction>(VL[0])) 7130 << "Vectorized horizontal reduction with cost " 7131 << ore::NV("Cost", Cost) << " and with tree size " 7132 << ore::NV("TreeSize", V.getTreeSize()); 7133 }); 7134 7135 // Vectorize a tree. 7136 DebugLoc Loc = cast<Instruction>(ReducedVals[i])->getDebugLoc(); 7137 Value *VectorizedRoot = V.vectorizeTree(ExternallyUsedValues); 7138 7139 // Emit a reduction. If the root is a select (min/max idiom), the insert 7140 // point is the compare condition of that select. 7141 Instruction *RdxRootInst = cast<Instruction>(ReductionRoot); 7142 if (isa<SelectInst>(RdxRootInst)) 7143 Builder.SetInsertPoint(getCmpForMinMaxReduction(RdxRootInst)); 7144 else 7145 Builder.SetInsertPoint(RdxRootInst); 7146 7147 Value *ReducedSubTree = 7148 emitReduction(VectorizedRoot, Builder, ReduxWidth, TTI); 7149 7150 if (!VectorizedTree) { 7151 // Initialize the final value in the reduction. 7152 VectorizedTree = ReducedSubTree; 7153 } else { 7154 // Update the final value in the reduction. 7155 Builder.SetCurrentDebugLocation(Loc); 7156 VectorizedTree = createOp(Builder, RdxKind, VectorizedTree, 7157 ReducedSubTree, "op.rdx", ReductionOps); 7158 } 7159 i += ReduxWidth; 7160 ReduxWidth = PowerOf2Floor(NumReducedVals - i); 7161 } 7162 7163 if (VectorizedTree) { 7164 // Finish the reduction. 7165 for (; i < NumReducedVals; ++i) { 7166 auto *I = cast<Instruction>(ReducedVals[i]); 7167 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 7168 VectorizedTree = 7169 createOp(Builder, RdxKind, VectorizedTree, I, "", ReductionOps); 7170 } 7171 for (auto &Pair : ExternallyUsedValues) { 7172 // Add each externally used value to the final reduction. 7173 for (auto *I : Pair.second) { 7174 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 7175 VectorizedTree = createOp(Builder, RdxKind, VectorizedTree, 7176 Pair.first, "op.extra", I); 7177 } 7178 } 7179 7180 ReductionRoot->replaceAllUsesWith(VectorizedTree); 7181 7182 // Mark all scalar reduction ops for deletion, they are replaced by the 7183 // vector reductions. 7184 V.eraseInstructions(IgnoreList); 7185 } 7186 return VectorizedTree != nullptr; 7187 } 7188 7189 unsigned numReductionValues() const { return ReducedVals.size(); } 7190 7191 private: 7192 /// Calculate the cost of a reduction. 7193 InstructionCost getReductionCost(TargetTransformInfo *TTI, 7194 Value *FirstReducedVal, 7195 unsigned ReduxWidth) { 7196 Type *ScalarTy = FirstReducedVal->getType(); 7197 FixedVectorType *VectorTy = FixedVectorType::get(ScalarTy, ReduxWidth); 7198 InstructionCost VectorCost, ScalarCost; 7199 switch (RdxKind) { 7200 case RecurKind::Add: 7201 case RecurKind::Mul: 7202 case RecurKind::Or: 7203 case RecurKind::And: 7204 case RecurKind::Xor: 7205 case RecurKind::FAdd: 7206 case RecurKind::FMul: { 7207 unsigned RdxOpcode = RecurrenceDescriptor::getOpcode(RdxKind); 7208 VectorCost = TTI->getArithmeticReductionCost(RdxOpcode, VectorTy, 7209 /*IsPairwiseForm=*/false); 7210 ScalarCost = TTI->getArithmeticInstrCost(RdxOpcode, ScalarTy); 7211 break; 7212 } 7213 case RecurKind::FMax: 7214 case RecurKind::FMin: { 7215 auto *VecCondTy = cast<VectorType>(CmpInst::makeCmpResultType(VectorTy)); 7216 VectorCost = 7217 TTI->getMinMaxReductionCost(VectorTy, VecCondTy, 7218 /*pairwise=*/false, /*unsigned=*/false); 7219 ScalarCost = 7220 TTI->getCmpSelInstrCost(Instruction::FCmp, ScalarTy) + 7221 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 7222 CmpInst::makeCmpResultType(ScalarTy)); 7223 break; 7224 } 7225 case RecurKind::SMax: 7226 case RecurKind::SMin: 7227 case RecurKind::UMax: 7228 case RecurKind::UMin: { 7229 auto *VecCondTy = cast<VectorType>(CmpInst::makeCmpResultType(VectorTy)); 7230 bool IsUnsigned = 7231 RdxKind == RecurKind::UMax || RdxKind == RecurKind::UMin; 7232 VectorCost = 7233 TTI->getMinMaxReductionCost(VectorTy, VecCondTy, 7234 /*IsPairwiseForm=*/false, IsUnsigned); 7235 ScalarCost = 7236 TTI->getCmpSelInstrCost(Instruction::ICmp, ScalarTy) + 7237 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 7238 CmpInst::makeCmpResultType(ScalarTy)); 7239 break; 7240 } 7241 default: 7242 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 7243 } 7244 7245 // Scalar cost is repeated for N-1 elements. 7246 ScalarCost *= (ReduxWidth - 1); 7247 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << VectorCost - ScalarCost 7248 << " for reduction that starts with " << *FirstReducedVal 7249 << " (It is a splitting reduction)\n"); 7250 return VectorCost - ScalarCost; 7251 } 7252 7253 /// Emit a horizontal reduction of the vectorized value. 7254 Value *emitReduction(Value *VectorizedValue, IRBuilder<> &Builder, 7255 unsigned ReduxWidth, const TargetTransformInfo *TTI) { 7256 assert(VectorizedValue && "Need to have a vectorized tree node"); 7257 assert(isPowerOf2_32(ReduxWidth) && 7258 "We only handle power-of-two reductions for now"); 7259 7260 return createSimpleTargetReduction(Builder, TTI, VectorizedValue, RdxKind, 7261 ReductionOps.back()); 7262 } 7263 }; 7264 7265 } // end anonymous namespace 7266 7267 static Optional<unsigned> getAggregateSize(Instruction *InsertInst) { 7268 if (auto *IE = dyn_cast<InsertElementInst>(InsertInst)) 7269 return cast<FixedVectorType>(IE->getType())->getNumElements(); 7270 7271 unsigned AggregateSize = 1; 7272 auto *IV = cast<InsertValueInst>(InsertInst); 7273 Type *CurrentType = IV->getType(); 7274 do { 7275 if (auto *ST = dyn_cast<StructType>(CurrentType)) { 7276 for (auto *Elt : ST->elements()) 7277 if (Elt != ST->getElementType(0)) // check homogeneity 7278 return None; 7279 AggregateSize *= ST->getNumElements(); 7280 CurrentType = ST->getElementType(0); 7281 } else if (auto *AT = dyn_cast<ArrayType>(CurrentType)) { 7282 AggregateSize *= AT->getNumElements(); 7283 CurrentType = AT->getElementType(); 7284 } else if (auto *VT = dyn_cast<FixedVectorType>(CurrentType)) { 7285 AggregateSize *= VT->getNumElements(); 7286 return AggregateSize; 7287 } else if (CurrentType->isSingleValueType()) { 7288 return AggregateSize; 7289 } else { 7290 return None; 7291 } 7292 } while (true); 7293 } 7294 7295 static Optional<unsigned> getOperandIndex(Instruction *InsertInst, 7296 unsigned OperandOffset) { 7297 unsigned OperandIndex = OperandOffset; 7298 if (auto *IE = dyn_cast<InsertElementInst>(InsertInst)) { 7299 if (auto *CI = dyn_cast<ConstantInt>(IE->getOperand(2))) { 7300 auto *VT = cast<FixedVectorType>(IE->getType()); 7301 OperandIndex *= VT->getNumElements(); 7302 OperandIndex += CI->getZExtValue(); 7303 return OperandIndex; 7304 } 7305 return None; 7306 } 7307 7308 auto *IV = cast<InsertValueInst>(InsertInst); 7309 Type *CurrentType = IV->getType(); 7310 for (unsigned int Index : IV->indices()) { 7311 if (auto *ST = dyn_cast<StructType>(CurrentType)) { 7312 OperandIndex *= ST->getNumElements(); 7313 CurrentType = ST->getElementType(Index); 7314 } else if (auto *AT = dyn_cast<ArrayType>(CurrentType)) { 7315 OperandIndex *= AT->getNumElements(); 7316 CurrentType = AT->getElementType(); 7317 } else { 7318 return None; 7319 } 7320 OperandIndex += Index; 7321 } 7322 return OperandIndex; 7323 } 7324 7325 static bool findBuildAggregate_rec(Instruction *LastInsertInst, 7326 TargetTransformInfo *TTI, 7327 SmallVectorImpl<Value *> &BuildVectorOpds, 7328 SmallVectorImpl<Value *> &InsertElts, 7329 unsigned OperandOffset) { 7330 do { 7331 Value *InsertedOperand = LastInsertInst->getOperand(1); 7332 Optional<unsigned> OperandIndex = 7333 getOperandIndex(LastInsertInst, OperandOffset); 7334 if (!OperandIndex) 7335 return false; 7336 if (isa<InsertElementInst>(InsertedOperand) || 7337 isa<InsertValueInst>(InsertedOperand)) { 7338 if (!findBuildAggregate_rec(cast<Instruction>(InsertedOperand), TTI, 7339 BuildVectorOpds, InsertElts, *OperandIndex)) 7340 return false; 7341 } else { 7342 BuildVectorOpds[*OperandIndex] = InsertedOperand; 7343 InsertElts[*OperandIndex] = LastInsertInst; 7344 } 7345 if (isa<UndefValue>(LastInsertInst->getOperand(0))) 7346 return true; 7347 LastInsertInst = dyn_cast<Instruction>(LastInsertInst->getOperand(0)); 7348 } while (LastInsertInst != nullptr && 7349 (isa<InsertValueInst>(LastInsertInst) || 7350 isa<InsertElementInst>(LastInsertInst)) && 7351 LastInsertInst->hasOneUse()); 7352 return false; 7353 } 7354 7355 /// Recognize construction of vectors like 7356 /// %ra = insertelement <4 x float> poison, float %s0, i32 0 7357 /// %rb = insertelement <4 x float> %ra, float %s1, i32 1 7358 /// %rc = insertelement <4 x float> %rb, float %s2, i32 2 7359 /// %rd = insertelement <4 x float> %rc, float %s3, i32 3 7360 /// starting from the last insertelement or insertvalue instruction. 7361 /// 7362 /// Also recognize homogeneous aggregates like {<2 x float>, <2 x float>}, 7363 /// {{float, float}, {float, float}}, [2 x {float, float}] and so on. 7364 /// See llvm/test/Transforms/SLPVectorizer/X86/pr42022.ll for examples. 7365 /// 7366 /// Assume LastInsertInst is of InsertElementInst or InsertValueInst type. 7367 /// 7368 /// \return true if it matches. 7369 static bool findBuildAggregate(Instruction *LastInsertInst, 7370 TargetTransformInfo *TTI, 7371 SmallVectorImpl<Value *> &BuildVectorOpds, 7372 SmallVectorImpl<Value *> &InsertElts) { 7373 7374 assert((isa<InsertElementInst>(LastInsertInst) || 7375 isa<InsertValueInst>(LastInsertInst)) && 7376 "Expected insertelement or insertvalue instruction!"); 7377 7378 assert((BuildVectorOpds.empty() && InsertElts.empty()) && 7379 "Expected empty result vectors!"); 7380 7381 Optional<unsigned> AggregateSize = getAggregateSize(LastInsertInst); 7382 if (!AggregateSize) 7383 return false; 7384 BuildVectorOpds.resize(*AggregateSize); 7385 InsertElts.resize(*AggregateSize); 7386 7387 if (findBuildAggregate_rec(LastInsertInst, TTI, BuildVectorOpds, InsertElts, 7388 0)) { 7389 llvm::erase_value(BuildVectorOpds, nullptr); 7390 llvm::erase_value(InsertElts, nullptr); 7391 if (BuildVectorOpds.size() >= 2) 7392 return true; 7393 } 7394 7395 return false; 7396 } 7397 7398 static bool PhiTypeSorterFunc(Value *V, Value *V2) { 7399 return V->getType() < V2->getType(); 7400 } 7401 7402 /// Try and get a reduction value from a phi node. 7403 /// 7404 /// Given a phi node \p P in a block \p ParentBB, consider possible reductions 7405 /// if they come from either \p ParentBB or a containing loop latch. 7406 /// 7407 /// \returns A candidate reduction value if possible, or \code nullptr \endcode 7408 /// if not possible. 7409 static Value *getReductionValue(const DominatorTree *DT, PHINode *P, 7410 BasicBlock *ParentBB, LoopInfo *LI) { 7411 // There are situations where the reduction value is not dominated by the 7412 // reduction phi. Vectorizing such cases has been reported to cause 7413 // miscompiles. See PR25787. 7414 auto DominatedReduxValue = [&](Value *R) { 7415 return isa<Instruction>(R) && 7416 DT->dominates(P->getParent(), cast<Instruction>(R)->getParent()); 7417 }; 7418 7419 Value *Rdx = nullptr; 7420 7421 // Return the incoming value if it comes from the same BB as the phi node. 7422 if (P->getIncomingBlock(0) == ParentBB) { 7423 Rdx = P->getIncomingValue(0); 7424 } else if (P->getIncomingBlock(1) == ParentBB) { 7425 Rdx = P->getIncomingValue(1); 7426 } 7427 7428 if (Rdx && DominatedReduxValue(Rdx)) 7429 return Rdx; 7430 7431 // Otherwise, check whether we have a loop latch to look at. 7432 Loop *BBL = LI->getLoopFor(ParentBB); 7433 if (!BBL) 7434 return nullptr; 7435 BasicBlock *BBLatch = BBL->getLoopLatch(); 7436 if (!BBLatch) 7437 return nullptr; 7438 7439 // There is a loop latch, return the incoming value if it comes from 7440 // that. This reduction pattern occasionally turns up. 7441 if (P->getIncomingBlock(0) == BBLatch) { 7442 Rdx = P->getIncomingValue(0); 7443 } else if (P->getIncomingBlock(1) == BBLatch) { 7444 Rdx = P->getIncomingValue(1); 7445 } 7446 7447 if (Rdx && DominatedReduxValue(Rdx)) 7448 return Rdx; 7449 7450 return nullptr; 7451 } 7452 7453 static bool matchRdxBop(Instruction *I, Value *&V0, Value *&V1) { 7454 if (match(I, m_BinOp(m_Value(V0), m_Value(V1)))) 7455 return true; 7456 if (match(I, m_Intrinsic<Intrinsic::maxnum>(m_Value(V0), m_Value(V1)))) 7457 return true; 7458 if (match(I, m_Intrinsic<Intrinsic::minnum>(m_Value(V0), m_Value(V1)))) 7459 return true; 7460 if (match(I, m_Intrinsic<Intrinsic::smax>(m_Value(V0), m_Value(V1)))) 7461 return true; 7462 if (match(I, m_Intrinsic<Intrinsic::smin>(m_Value(V0), m_Value(V1)))) 7463 return true; 7464 if (match(I, m_Intrinsic<Intrinsic::umax>(m_Value(V0), m_Value(V1)))) 7465 return true; 7466 if (match(I, m_Intrinsic<Intrinsic::umin>(m_Value(V0), m_Value(V1)))) 7467 return true; 7468 return false; 7469 } 7470 7471 /// Attempt to reduce a horizontal reduction. 7472 /// If it is legal to match a horizontal reduction feeding the phi node \a P 7473 /// with reduction operators \a Root (or one of its operands) in a basic block 7474 /// \a BB, then check if it can be done. If horizontal reduction is not found 7475 /// and root instruction is a binary operation, vectorization of the operands is 7476 /// attempted. 7477 /// \returns true if a horizontal reduction was matched and reduced or operands 7478 /// of one of the binary instruction were vectorized. 7479 /// \returns false if a horizontal reduction was not matched (or not possible) 7480 /// or no vectorization of any binary operation feeding \a Root instruction was 7481 /// performed. 7482 static bool tryToVectorizeHorReductionOrInstOperands( 7483 PHINode *P, Instruction *Root, BasicBlock *BB, BoUpSLP &R, 7484 TargetTransformInfo *TTI, 7485 const function_ref<bool(Instruction *, BoUpSLP &)> Vectorize) { 7486 if (!ShouldVectorizeHor) 7487 return false; 7488 7489 if (!Root) 7490 return false; 7491 7492 if (Root->getParent() != BB || isa<PHINode>(Root)) 7493 return false; 7494 // Start analysis starting from Root instruction. If horizontal reduction is 7495 // found, try to vectorize it. If it is not a horizontal reduction or 7496 // vectorization is not possible or not effective, and currently analyzed 7497 // instruction is a binary operation, try to vectorize the operands, using 7498 // pre-order DFS traversal order. If the operands were not vectorized, repeat 7499 // the same procedure considering each operand as a possible root of the 7500 // horizontal reduction. 7501 // Interrupt the process if the Root instruction itself was vectorized or all 7502 // sub-trees not higher that RecursionMaxDepth were analyzed/vectorized. 7503 // Skip the analysis of CmpInsts.Compiler implements postanalysis of the 7504 // CmpInsts so we can skip extra attempts in 7505 // tryToVectorizeHorReductionOrInstOperands and save compile time. 7506 SmallVector<std::pair<Instruction *, unsigned>, 8> Stack(1, {Root, 0}); 7507 SmallPtrSet<Value *, 8> VisitedInstrs; 7508 bool Res = false; 7509 while (!Stack.empty()) { 7510 Instruction *Inst; 7511 unsigned Level; 7512 std::tie(Inst, Level) = Stack.pop_back_val(); 7513 Value *B0, *B1; 7514 bool IsBinop = matchRdxBop(Inst, B0, B1); 7515 bool IsSelect = match(Inst, m_Select(m_Value(), m_Value(), m_Value())); 7516 if (IsBinop || IsSelect) { 7517 HorizontalReduction HorRdx; 7518 if (HorRdx.matchAssociativeReduction(P, Inst)) { 7519 if (HorRdx.tryToReduce(R, TTI)) { 7520 Res = true; 7521 // Set P to nullptr to avoid re-analysis of phi node in 7522 // matchAssociativeReduction function unless this is the root node. 7523 P = nullptr; 7524 continue; 7525 } 7526 } 7527 if (P && IsBinop) { 7528 Inst = dyn_cast<Instruction>(B0); 7529 if (Inst == P) 7530 Inst = dyn_cast<Instruction>(B1); 7531 if (!Inst) { 7532 // Set P to nullptr to avoid re-analysis of phi node in 7533 // matchAssociativeReduction function unless this is the root node. 7534 P = nullptr; 7535 continue; 7536 } 7537 } 7538 } 7539 // Set P to nullptr to avoid re-analysis of phi node in 7540 // matchAssociativeReduction function unless this is the root node. 7541 P = nullptr; 7542 // Do not try to vectorize CmpInst operands, this is done separately. 7543 if (!isa<CmpInst>(Inst) && Vectorize(Inst, R)) { 7544 Res = true; 7545 continue; 7546 } 7547 7548 // Try to vectorize operands. 7549 // Continue analysis for the instruction from the same basic block only to 7550 // save compile time. 7551 if (++Level < RecursionMaxDepth) 7552 for (auto *Op : Inst->operand_values()) 7553 if (VisitedInstrs.insert(Op).second) 7554 if (auto *I = dyn_cast<Instruction>(Op)) 7555 // Do not try to vectorize CmpInst operands, this is done 7556 // separately. 7557 if (!isa<PHINode>(I) && !isa<CmpInst>(I) && !R.isDeleted(I) && 7558 I->getParent() == BB) 7559 Stack.emplace_back(I, Level); 7560 } 7561 return Res; 7562 } 7563 7564 bool SLPVectorizerPass::vectorizeRootInstruction(PHINode *P, Value *V, 7565 BasicBlock *BB, BoUpSLP &R, 7566 TargetTransformInfo *TTI) { 7567 auto *I = dyn_cast_or_null<Instruction>(V); 7568 if (!I) 7569 return false; 7570 7571 if (!isa<BinaryOperator>(I)) 7572 P = nullptr; 7573 // Try to match and vectorize a horizontal reduction. 7574 auto &&ExtraVectorization = [this](Instruction *I, BoUpSLP &R) -> bool { 7575 return tryToVectorize(I, R); 7576 }; 7577 return tryToVectorizeHorReductionOrInstOperands(P, I, BB, R, TTI, 7578 ExtraVectorization); 7579 } 7580 7581 bool SLPVectorizerPass::vectorizeInsertValueInst(InsertValueInst *IVI, 7582 BasicBlock *BB, BoUpSLP &R) { 7583 const DataLayout &DL = BB->getModule()->getDataLayout(); 7584 if (!R.canMapToVector(IVI->getType(), DL)) 7585 return false; 7586 7587 SmallVector<Value *, 16> BuildVectorOpds; 7588 SmallVector<Value *, 16> BuildVectorInsts; 7589 if (!findBuildAggregate(IVI, TTI, BuildVectorOpds, BuildVectorInsts)) 7590 return false; 7591 7592 LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IVI << "\n"); 7593 // Aggregate value is unlikely to be processed in vector register, we need to 7594 // extract scalars into scalar registers, so NeedExtraction is set true. 7595 return tryToVectorizeList(BuildVectorOpds, R, /*AllowReorder=*/false, 7596 BuildVectorInsts); 7597 } 7598 7599 bool SLPVectorizerPass::vectorizeInsertElementInst(InsertElementInst *IEI, 7600 BasicBlock *BB, BoUpSLP &R) { 7601 SmallVector<Value *, 16> BuildVectorInsts; 7602 SmallVector<Value *, 16> BuildVectorOpds; 7603 SmallVector<int> Mask; 7604 if (!findBuildAggregate(IEI, TTI, BuildVectorOpds, BuildVectorInsts) || 7605 (llvm::all_of(BuildVectorOpds, 7606 [](Value *V) { return isa<ExtractElementInst>(V); }) && 7607 isShuffle(BuildVectorOpds, Mask))) 7608 return false; 7609 7610 // Vectorize starting with the build vector operands ignoring the BuildVector 7611 // instructions for the purpose of scheduling and user extraction. 7612 return tryToVectorizeList(BuildVectorOpds, R, /*AllowReorder=*/false, 7613 BuildVectorInsts); 7614 } 7615 7616 bool SLPVectorizerPass::vectorizeSimpleInstructions( 7617 SmallVectorImpl<Instruction *> &Instructions, BasicBlock *BB, BoUpSLP &R, 7618 bool AtTerminator) { 7619 bool OpsChanged = false; 7620 SmallVector<Instruction *, 4> PostponedCmps; 7621 for (auto *I : reverse(Instructions)) { 7622 if (R.isDeleted(I)) 7623 continue; 7624 if (auto *LastInsertValue = dyn_cast<InsertValueInst>(I)) 7625 OpsChanged |= vectorizeInsertValueInst(LastInsertValue, BB, R); 7626 else if (auto *LastInsertElem = dyn_cast<InsertElementInst>(I)) 7627 OpsChanged |= vectorizeInsertElementInst(LastInsertElem, BB, R); 7628 else if (isa<CmpInst>(I)) 7629 PostponedCmps.push_back(I); 7630 } 7631 if (AtTerminator) { 7632 // Try to find reductions first. 7633 for (Instruction *I : PostponedCmps) { 7634 if (R.isDeleted(I)) 7635 continue; 7636 for (Value *Op : I->operands()) 7637 OpsChanged |= vectorizeRootInstruction(nullptr, Op, BB, R, TTI); 7638 } 7639 // Try to vectorize operands as vector bundles. 7640 for (Instruction *I : PostponedCmps) { 7641 if (R.isDeleted(I)) 7642 continue; 7643 OpsChanged |= tryToVectorize(I, R); 7644 } 7645 Instructions.clear(); 7646 } else { 7647 // Insert in reverse order since the PostponedCmps vector was filled in 7648 // reverse order. 7649 Instructions.assign(PostponedCmps.rbegin(), PostponedCmps.rend()); 7650 } 7651 return OpsChanged; 7652 } 7653 7654 bool SLPVectorizerPass::vectorizeChainsInBlock(BasicBlock *BB, BoUpSLP &R) { 7655 bool Changed = false; 7656 SmallVector<Value *, 4> Incoming; 7657 SmallPtrSet<Value *, 16> VisitedInstrs; 7658 7659 bool HaveVectorizedPhiNodes = true; 7660 while (HaveVectorizedPhiNodes) { 7661 HaveVectorizedPhiNodes = false; 7662 7663 // Collect the incoming values from the PHIs. 7664 Incoming.clear(); 7665 for (Instruction &I : *BB) { 7666 PHINode *P = dyn_cast<PHINode>(&I); 7667 if (!P) 7668 break; 7669 7670 if (!VisitedInstrs.count(P) && !R.isDeleted(P)) 7671 Incoming.push_back(P); 7672 } 7673 7674 // Sort by type. 7675 llvm::stable_sort(Incoming, PhiTypeSorterFunc); 7676 7677 // Try to vectorize elements base on their type. 7678 for (SmallVector<Value *, 4>::iterator IncIt = Incoming.begin(), 7679 E = Incoming.end(); 7680 IncIt != E;) { 7681 7682 // Look for the next elements with the same type. 7683 SmallVector<Value *, 4>::iterator SameTypeIt = IncIt; 7684 while (SameTypeIt != E && 7685 (*SameTypeIt)->getType() == (*IncIt)->getType()) { 7686 VisitedInstrs.insert(*SameTypeIt); 7687 ++SameTypeIt; 7688 } 7689 7690 // Try to vectorize them. 7691 unsigned NumElts = (SameTypeIt - IncIt); 7692 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize starting at PHIs (" 7693 << NumElts << ")\n"); 7694 // The order in which the phi nodes appear in the program does not matter. 7695 // So allow tryToVectorizeList to reorder them if it is beneficial. This 7696 // is done when there are exactly two elements since tryToVectorizeList 7697 // asserts that there are only two values when AllowReorder is true. 7698 bool AllowReorder = NumElts == 2; 7699 if (NumElts > 1 && 7700 tryToVectorizeList(makeArrayRef(IncIt, NumElts), R, AllowReorder)) { 7701 // Success start over because instructions might have been changed. 7702 HaveVectorizedPhiNodes = true; 7703 Changed = true; 7704 break; 7705 } 7706 7707 // Start over at the next instruction of a different type (or the end). 7708 IncIt = SameTypeIt; 7709 } 7710 } 7711 7712 VisitedInstrs.clear(); 7713 7714 SmallVector<Instruction *, 8> PostProcessInstructions; 7715 SmallDenseSet<Instruction *, 4> KeyNodes; 7716 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 7717 // Skip instructions with scalable type. The num of elements is unknown at 7718 // compile-time for scalable type. 7719 if (isa<ScalableVectorType>(it->getType())) 7720 continue; 7721 7722 // Skip instructions marked for the deletion. 7723 if (R.isDeleted(&*it)) 7724 continue; 7725 // We may go through BB multiple times so skip the one we have checked. 7726 if (!VisitedInstrs.insert(&*it).second) { 7727 if (it->use_empty() && KeyNodes.contains(&*it) && 7728 vectorizeSimpleInstructions(PostProcessInstructions, BB, R, 7729 it->isTerminator())) { 7730 // We would like to start over since some instructions are deleted 7731 // and the iterator may become invalid value. 7732 Changed = true; 7733 it = BB->begin(); 7734 e = BB->end(); 7735 } 7736 continue; 7737 } 7738 7739 if (isa<DbgInfoIntrinsic>(it)) 7740 continue; 7741 7742 // Try to vectorize reductions that use PHINodes. 7743 if (PHINode *P = dyn_cast<PHINode>(it)) { 7744 // Check that the PHI is a reduction PHI. 7745 if (P->getNumIncomingValues() == 2) { 7746 // Try to match and vectorize a horizontal reduction. 7747 if (vectorizeRootInstruction(P, getReductionValue(DT, P, BB, LI), BB, R, 7748 TTI)) { 7749 Changed = true; 7750 it = BB->begin(); 7751 e = BB->end(); 7752 continue; 7753 } 7754 } 7755 // Try to vectorize the incoming values of the PHI, to catch reductions 7756 // that feed into PHIs. 7757 for (unsigned I = 0, E = P->getNumIncomingValues(); I != E; I++) { 7758 // Skip if the incoming block is the current BB for now. Also, bypass 7759 // unreachable IR for efficiency and to avoid crashing. 7760 // TODO: Collect the skipped incoming values and try to vectorize them 7761 // after processing BB. 7762 if (BB == P->getIncomingBlock(I) || 7763 !DT->isReachableFromEntry(P->getIncomingBlock(I))) 7764 continue; 7765 7766 Changed |= vectorizeRootInstruction(nullptr, P->getIncomingValue(I), 7767 P->getIncomingBlock(I), R, TTI); 7768 } 7769 continue; 7770 } 7771 7772 // Ran into an instruction without users, like terminator, or function call 7773 // with ignored return value, store. Ignore unused instructions (basing on 7774 // instruction type, except for CallInst and InvokeInst). 7775 if (it->use_empty() && (it->getType()->isVoidTy() || isa<CallInst>(it) || 7776 isa<InvokeInst>(it))) { 7777 KeyNodes.insert(&*it); 7778 bool OpsChanged = false; 7779 if (ShouldStartVectorizeHorAtStore || !isa<StoreInst>(it)) { 7780 for (auto *V : it->operand_values()) { 7781 // Try to match and vectorize a horizontal reduction. 7782 OpsChanged |= vectorizeRootInstruction(nullptr, V, BB, R, TTI); 7783 } 7784 } 7785 // Start vectorization of post-process list of instructions from the 7786 // top-tree instructions to try to vectorize as many instructions as 7787 // possible. 7788 OpsChanged |= vectorizeSimpleInstructions(PostProcessInstructions, BB, R, 7789 it->isTerminator()); 7790 if (OpsChanged) { 7791 // We would like to start over since some instructions are deleted 7792 // and the iterator may become invalid value. 7793 Changed = true; 7794 it = BB->begin(); 7795 e = BB->end(); 7796 continue; 7797 } 7798 } 7799 7800 if (isa<InsertElementInst>(it) || isa<CmpInst>(it) || 7801 isa<InsertValueInst>(it)) 7802 PostProcessInstructions.push_back(&*it); 7803 } 7804 7805 return Changed; 7806 } 7807 7808 bool SLPVectorizerPass::vectorizeGEPIndices(BasicBlock *BB, BoUpSLP &R) { 7809 auto Changed = false; 7810 for (auto &Entry : GEPs) { 7811 // If the getelementptr list has fewer than two elements, there's nothing 7812 // to do. 7813 if (Entry.second.size() < 2) 7814 continue; 7815 7816 LLVM_DEBUG(dbgs() << "SLP: Analyzing a getelementptr list of length " 7817 << Entry.second.size() << ".\n"); 7818 7819 // Process the GEP list in chunks suitable for the target's supported 7820 // vector size. If a vector register can't hold 1 element, we are done. We 7821 // are trying to vectorize the index computations, so the maximum number of 7822 // elements is based on the size of the index expression, rather than the 7823 // size of the GEP itself (the target's pointer size). 7824 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 7825 unsigned EltSize = R.getVectorElementSize(*Entry.second[0]->idx_begin()); 7826 if (MaxVecRegSize < EltSize) 7827 continue; 7828 7829 unsigned MaxElts = MaxVecRegSize / EltSize; 7830 for (unsigned BI = 0, BE = Entry.second.size(); BI < BE; BI += MaxElts) { 7831 auto Len = std::min<unsigned>(BE - BI, MaxElts); 7832 ArrayRef<GetElementPtrInst *> GEPList(&Entry.second[BI], Len); 7833 7834 // Initialize a set a candidate getelementptrs. Note that we use a 7835 // SetVector here to preserve program order. If the index computations 7836 // are vectorizable and begin with loads, we want to minimize the chance 7837 // of having to reorder them later. 7838 SetVector<Value *> Candidates(GEPList.begin(), GEPList.end()); 7839 7840 // Some of the candidates may have already been vectorized after we 7841 // initially collected them. If so, they are marked as deleted, so remove 7842 // them from the set of candidates. 7843 Candidates.remove_if( 7844 [&R](Value *I) { return R.isDeleted(cast<Instruction>(I)); }); 7845 7846 // Remove from the set of candidates all pairs of getelementptrs with 7847 // constant differences. Such getelementptrs are likely not good 7848 // candidates for vectorization in a bottom-up phase since one can be 7849 // computed from the other. We also ensure all candidate getelementptr 7850 // indices are unique. 7851 for (int I = 0, E = GEPList.size(); I < E && Candidates.size() > 1; ++I) { 7852 auto *GEPI = GEPList[I]; 7853 if (!Candidates.count(GEPI)) 7854 continue; 7855 auto *SCEVI = SE->getSCEV(GEPList[I]); 7856 for (int J = I + 1; J < E && Candidates.size() > 1; ++J) { 7857 auto *GEPJ = GEPList[J]; 7858 auto *SCEVJ = SE->getSCEV(GEPList[J]); 7859 if (isa<SCEVConstant>(SE->getMinusSCEV(SCEVI, SCEVJ))) { 7860 Candidates.remove(GEPI); 7861 Candidates.remove(GEPJ); 7862 } else if (GEPI->idx_begin()->get() == GEPJ->idx_begin()->get()) { 7863 Candidates.remove(GEPJ); 7864 } 7865 } 7866 } 7867 7868 // We break out of the above computation as soon as we know there are 7869 // fewer than two candidates remaining. 7870 if (Candidates.size() < 2) 7871 continue; 7872 7873 // Add the single, non-constant index of each candidate to the bundle. We 7874 // ensured the indices met these constraints when we originally collected 7875 // the getelementptrs. 7876 SmallVector<Value *, 16> Bundle(Candidates.size()); 7877 auto BundleIndex = 0u; 7878 for (auto *V : Candidates) { 7879 auto *GEP = cast<GetElementPtrInst>(V); 7880 auto *GEPIdx = GEP->idx_begin()->get(); 7881 assert(GEP->getNumIndices() == 1 || !isa<Constant>(GEPIdx)); 7882 Bundle[BundleIndex++] = GEPIdx; 7883 } 7884 7885 // Try and vectorize the indices. We are currently only interested in 7886 // gather-like cases of the form: 7887 // 7888 // ... = g[a[0] - b[0]] + g[a[1] - b[1]] + ... 7889 // 7890 // where the loads of "a", the loads of "b", and the subtractions can be 7891 // performed in parallel. It's likely that detecting this pattern in a 7892 // bottom-up phase will be simpler and less costly than building a 7893 // full-blown top-down phase beginning at the consecutive loads. 7894 Changed |= tryToVectorizeList(Bundle, R); 7895 } 7896 } 7897 return Changed; 7898 } 7899 7900 bool SLPVectorizerPass::vectorizeStoreChains(BoUpSLP &R) { 7901 bool Changed = false; 7902 // Attempt to sort and vectorize each of the store-groups. 7903 for (StoreListMap::iterator it = Stores.begin(), e = Stores.end(); it != e; 7904 ++it) { 7905 if (it->second.size() < 2) 7906 continue; 7907 7908 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " 7909 << it->second.size() << ".\n"); 7910 7911 Changed |= vectorizeStores(it->second, R); 7912 } 7913 return Changed; 7914 } 7915 7916 char SLPVectorizer::ID = 0; 7917 7918 static const char lv_name[] = "SLP Vectorizer"; 7919 7920 INITIALIZE_PASS_BEGIN(SLPVectorizer, SV_NAME, lv_name, false, false) 7921 INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass) 7922 INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass) 7923 INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker) 7924 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass) 7925 INITIALIZE_PASS_DEPENDENCY(LoopSimplify) 7926 INITIALIZE_PASS_DEPENDENCY(DemandedBitsWrapperPass) 7927 INITIALIZE_PASS_DEPENDENCY(OptimizationRemarkEmitterWrapperPass) 7928 INITIALIZE_PASS_DEPENDENCY(InjectTLIMappingsLegacy) 7929 INITIALIZE_PASS_END(SLPVectorizer, SV_NAME, lv_name, false, false) 7930 7931 Pass *llvm::createSLPVectorizerPass() { return new SLPVectorizer(); } 7932