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->alias(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 return TTI.getShuffleCost(ShuffleKind, VecTy, Mask); 3463 3464 bool AllConsecutive = true; 3465 unsigned EltsPerVector = VecTy->getNumElements() / NumOfParts; 3466 unsigned Idx = -1; 3467 InstructionCost Cost = 0; 3468 3469 // Process extracts in blocks of EltsPerVector to check if the source vector 3470 // operand can be re-used directly. If not, add the cost of creating a shuffle 3471 // to extract the values into a vector register. 3472 for (auto *V : VL) { 3473 ++Idx; 3474 3475 // Reached the start of a new vector registers. 3476 if (Idx % EltsPerVector == 0) { 3477 AllConsecutive = true; 3478 continue; 3479 } 3480 3481 // Check all extracts for a vector register on the target directly 3482 // extract values in order. 3483 unsigned CurrentIdx = *getExtractIndex(cast<Instruction>(V)); 3484 unsigned PrevIdx = *getExtractIndex(cast<Instruction>(VL[Idx - 1])); 3485 AllConsecutive &= PrevIdx + 1 == CurrentIdx && 3486 CurrentIdx % EltsPerVector == Idx % EltsPerVector; 3487 3488 if (AllConsecutive) 3489 continue; 3490 3491 // Skip all indices, except for the last index per vector block. 3492 if ((Idx + 1) % EltsPerVector != 0 && Idx + 1 != VL.size()) 3493 continue; 3494 3495 // If we have a series of extracts which are not consecutive and hence 3496 // cannot re-use the source vector register directly, compute the shuffle 3497 // cost to extract the a vector with EltsPerVector elements. 3498 Cost += TTI.getShuffleCost( 3499 TargetTransformInfo::SK_PermuteSingleSrc, 3500 FixedVectorType::get(VecTy->getElementType(), EltsPerVector)); 3501 } 3502 return Cost; 3503 } 3504 3505 InstructionCost BoUpSLP::getEntryCost(TreeEntry *E) { 3506 ArrayRef<Value*> VL = E->Scalars; 3507 3508 Type *ScalarTy = VL[0]->getType(); 3509 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 3510 ScalarTy = SI->getValueOperand()->getType(); 3511 else if (CmpInst *CI = dyn_cast<CmpInst>(VL[0])) 3512 ScalarTy = CI->getOperand(0)->getType(); 3513 auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); 3514 TTI::TargetCostKind CostKind = TTI::TCK_RecipThroughput; 3515 3516 // If we have computed a smaller type for the expression, update VecTy so 3517 // that the costs will be accurate. 3518 if (MinBWs.count(VL[0])) 3519 VecTy = FixedVectorType::get( 3520 IntegerType::get(F->getContext(), MinBWs[VL[0]].first), VL.size()); 3521 3522 unsigned ReuseShuffleNumbers = E->ReuseShuffleIndices.size(); 3523 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 3524 InstructionCost ReuseShuffleCost = 0; 3525 if (NeedToShuffleReuses) { 3526 ReuseShuffleCost = 3527 TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, VecTy, 3528 E->ReuseShuffleIndices); 3529 } 3530 if (E->State == TreeEntry::NeedToGather) { 3531 if (allConstant(VL)) 3532 return 0; 3533 if (isSplat(VL)) { 3534 return ReuseShuffleCost + 3535 TTI->getShuffleCost(TargetTransformInfo::SK_Broadcast, VecTy, None, 3536 0); 3537 } 3538 if (E->getOpcode() == Instruction::ExtractElement && 3539 allSameType(VL) && allSameBlock(VL)) { 3540 SmallVector<int> Mask; 3541 Optional<TargetTransformInfo::ShuffleKind> ShuffleKind = 3542 isShuffle(VL, Mask); 3543 if (ShuffleKind.hasValue()) { 3544 InstructionCost Cost = 3545 computeExtractCost(VL, VecTy, *ShuffleKind, Mask, *TTI); 3546 for (auto *V : VL) { 3547 // If all users of instruction are going to be vectorized and this 3548 // instruction itself is not going to be vectorized, consider this 3549 // instruction as dead and remove its cost from the final cost of the 3550 // vectorized tree. 3551 if (areAllUsersVectorized(cast<Instruction>(V)) && 3552 !ScalarToTreeEntry.count(V)) { 3553 auto *IO = cast<ConstantInt>( 3554 cast<ExtractElementInst>(V)->getIndexOperand()); 3555 Cost -= TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, 3556 IO->getZExtValue()); 3557 } 3558 } 3559 return ReuseShuffleCost + Cost; 3560 } 3561 } 3562 return ReuseShuffleCost + getGatherCost(VL); 3563 } 3564 assert((E->State == TreeEntry::Vectorize || 3565 E->State == TreeEntry::ScatterVectorize) && 3566 "Unhandled state"); 3567 assert(E->getOpcode() && allSameType(VL) && allSameBlock(VL) && "Invalid VL"); 3568 Instruction *VL0 = E->getMainOp(); 3569 unsigned ShuffleOrOp = 3570 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 3571 switch (ShuffleOrOp) { 3572 case Instruction::PHI: 3573 return 0; 3574 3575 case Instruction::ExtractValue: 3576 case Instruction::ExtractElement: { 3577 // The common cost of removal ExtractElement/ExtractValue instructions + 3578 // the cost of shuffles, if required to resuffle the original vector. 3579 InstructionCost CommonCost = 0; 3580 if (NeedToShuffleReuses) { 3581 unsigned Idx = 0; 3582 for (unsigned I : E->ReuseShuffleIndices) { 3583 if (ShuffleOrOp == Instruction::ExtractElement) { 3584 auto *IO = cast<ConstantInt>( 3585 cast<ExtractElementInst>(VL[I])->getIndexOperand()); 3586 Idx = IO->getZExtValue(); 3587 ReuseShuffleCost -= TTI->getVectorInstrCost( 3588 Instruction::ExtractElement, VecTy, Idx); 3589 } else { 3590 ReuseShuffleCost -= TTI->getVectorInstrCost( 3591 Instruction::ExtractElement, VecTy, Idx); 3592 ++Idx; 3593 } 3594 } 3595 Idx = ReuseShuffleNumbers; 3596 for (Value *V : VL) { 3597 if (ShuffleOrOp == Instruction::ExtractElement) { 3598 auto *IO = cast<ConstantInt>( 3599 cast<ExtractElementInst>(V)->getIndexOperand()); 3600 Idx = IO->getZExtValue(); 3601 } else { 3602 --Idx; 3603 } 3604 ReuseShuffleCost += 3605 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, Idx); 3606 } 3607 CommonCost = ReuseShuffleCost; 3608 } else if (!E->ReorderIndices.empty()) { 3609 SmallVector<int> NewMask; 3610 inversePermutation(E->ReorderIndices, NewMask); 3611 CommonCost = TTI->getShuffleCost( 3612 TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask); 3613 } 3614 for (unsigned I = 0, E = VL.size(); I < E; ++I) { 3615 Instruction *EI = cast<Instruction>(VL[I]); 3616 // If all users are going to be vectorized, instruction can be 3617 // considered as dead. 3618 // The same, if have only one user, it will be vectorized for sure. 3619 if (areAllUsersVectorized(EI)) { 3620 // Take credit for instruction that will become dead. 3621 if (EI->hasOneUse()) { 3622 Instruction *Ext = EI->user_back(); 3623 if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) && 3624 all_of(Ext->users(), 3625 [](User *U) { return isa<GetElementPtrInst>(U); })) { 3626 // Use getExtractWithExtendCost() to calculate the cost of 3627 // extractelement/ext pair. 3628 CommonCost -= TTI->getExtractWithExtendCost( 3629 Ext->getOpcode(), Ext->getType(), VecTy, I); 3630 // Add back the cost of s|zext which is subtracted separately. 3631 CommonCost += TTI->getCastInstrCost( 3632 Ext->getOpcode(), Ext->getType(), EI->getType(), 3633 TTI::getCastContextHint(Ext), CostKind, Ext); 3634 continue; 3635 } 3636 } 3637 CommonCost -= 3638 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, I); 3639 } 3640 } 3641 return CommonCost; 3642 } 3643 case Instruction::ZExt: 3644 case Instruction::SExt: 3645 case Instruction::FPToUI: 3646 case Instruction::FPToSI: 3647 case Instruction::FPExt: 3648 case Instruction::PtrToInt: 3649 case Instruction::IntToPtr: 3650 case Instruction::SIToFP: 3651 case Instruction::UIToFP: 3652 case Instruction::Trunc: 3653 case Instruction::FPTrunc: 3654 case Instruction::BitCast: { 3655 Type *SrcTy = VL0->getOperand(0)->getType(); 3656 InstructionCost ScalarEltCost = 3657 TTI->getCastInstrCost(E->getOpcode(), ScalarTy, SrcTy, 3658 TTI::getCastContextHint(VL0), CostKind, VL0); 3659 if (NeedToShuffleReuses) { 3660 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3661 } 3662 3663 // Calculate the cost of this instruction. 3664 InstructionCost ScalarCost = VL.size() * ScalarEltCost; 3665 3666 auto *SrcVecTy = FixedVectorType::get(SrcTy, VL.size()); 3667 InstructionCost VecCost = 0; 3668 // Check if the values are candidates to demote. 3669 if (!MinBWs.count(VL0) || VecTy != SrcVecTy) { 3670 VecCost = 3671 ReuseShuffleCost + 3672 TTI->getCastInstrCost(E->getOpcode(), VecTy, SrcVecTy, 3673 TTI::getCastContextHint(VL0), CostKind, VL0); 3674 } 3675 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3676 return VecCost - ScalarCost; 3677 } 3678 case Instruction::FCmp: 3679 case Instruction::ICmp: 3680 case Instruction::Select: { 3681 // Calculate the cost of this instruction. 3682 InstructionCost ScalarEltCost = 3683 TTI->getCmpSelInstrCost(E->getOpcode(), ScalarTy, Builder.getInt1Ty(), 3684 CmpInst::BAD_ICMP_PREDICATE, CostKind, VL0); 3685 if (NeedToShuffleReuses) { 3686 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3687 } 3688 auto *MaskTy = FixedVectorType::get(Builder.getInt1Ty(), VL.size()); 3689 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3690 3691 // Check if all entries in VL are either compares or selects with compares 3692 // as condition that have the same predicates. 3693 CmpInst::Predicate VecPred = CmpInst::BAD_ICMP_PREDICATE; 3694 bool First = true; 3695 for (auto *V : VL) { 3696 CmpInst::Predicate CurrentPred; 3697 auto MatchCmp = m_Cmp(CurrentPred, m_Value(), m_Value()); 3698 if ((!match(V, m_Select(MatchCmp, m_Value(), m_Value())) && 3699 !match(V, MatchCmp)) || 3700 (!First && VecPred != CurrentPred)) { 3701 VecPred = CmpInst::BAD_ICMP_PREDICATE; 3702 break; 3703 } 3704 First = false; 3705 VecPred = CurrentPred; 3706 } 3707 3708 InstructionCost VecCost = TTI->getCmpSelInstrCost( 3709 E->getOpcode(), VecTy, MaskTy, VecPred, CostKind, VL0); 3710 // Check if it is possible and profitable to use min/max for selects in 3711 // VL. 3712 // 3713 auto IntrinsicAndUse = canConvertToMinOrMaxIntrinsic(VL); 3714 if (IntrinsicAndUse.first != Intrinsic::not_intrinsic) { 3715 IntrinsicCostAttributes CostAttrs(IntrinsicAndUse.first, VecTy, 3716 {VecTy, VecTy}); 3717 InstructionCost IntrinsicCost = 3718 TTI->getIntrinsicInstrCost(CostAttrs, CostKind); 3719 // If the selects are the only uses of the compares, they will be dead 3720 // and we can adjust the cost by removing their cost. 3721 if (IntrinsicAndUse.second) 3722 IntrinsicCost -= 3723 TTI->getCmpSelInstrCost(Instruction::ICmp, VecTy, MaskTy, 3724 CmpInst::BAD_ICMP_PREDICATE, CostKind); 3725 VecCost = std::min(VecCost, IntrinsicCost); 3726 } 3727 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3728 return ReuseShuffleCost + VecCost - ScalarCost; 3729 } 3730 case Instruction::FNeg: 3731 case Instruction::Add: 3732 case Instruction::FAdd: 3733 case Instruction::Sub: 3734 case Instruction::FSub: 3735 case Instruction::Mul: 3736 case Instruction::FMul: 3737 case Instruction::UDiv: 3738 case Instruction::SDiv: 3739 case Instruction::FDiv: 3740 case Instruction::URem: 3741 case Instruction::SRem: 3742 case Instruction::FRem: 3743 case Instruction::Shl: 3744 case Instruction::LShr: 3745 case Instruction::AShr: 3746 case Instruction::And: 3747 case Instruction::Or: 3748 case Instruction::Xor: { 3749 // Certain instructions can be cheaper to vectorize if they have a 3750 // constant second vector operand. 3751 TargetTransformInfo::OperandValueKind Op1VK = 3752 TargetTransformInfo::OK_AnyValue; 3753 TargetTransformInfo::OperandValueKind Op2VK = 3754 TargetTransformInfo::OK_UniformConstantValue; 3755 TargetTransformInfo::OperandValueProperties Op1VP = 3756 TargetTransformInfo::OP_None; 3757 TargetTransformInfo::OperandValueProperties Op2VP = 3758 TargetTransformInfo::OP_PowerOf2; 3759 3760 // If all operands are exactly the same ConstantInt then set the 3761 // operand kind to OK_UniformConstantValue. 3762 // If instead not all operands are constants, then set the operand kind 3763 // to OK_AnyValue. If all operands are constants but not the same, 3764 // then set the operand kind to OK_NonUniformConstantValue. 3765 ConstantInt *CInt0 = nullptr; 3766 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 3767 const Instruction *I = cast<Instruction>(VL[i]); 3768 unsigned OpIdx = isa<BinaryOperator>(I) ? 1 : 0; 3769 ConstantInt *CInt = dyn_cast<ConstantInt>(I->getOperand(OpIdx)); 3770 if (!CInt) { 3771 Op2VK = TargetTransformInfo::OK_AnyValue; 3772 Op2VP = TargetTransformInfo::OP_None; 3773 break; 3774 } 3775 if (Op2VP == TargetTransformInfo::OP_PowerOf2 && 3776 !CInt->getValue().isPowerOf2()) 3777 Op2VP = TargetTransformInfo::OP_None; 3778 if (i == 0) { 3779 CInt0 = CInt; 3780 continue; 3781 } 3782 if (CInt0 != CInt) 3783 Op2VK = TargetTransformInfo::OK_NonUniformConstantValue; 3784 } 3785 3786 SmallVector<const Value *, 4> Operands(VL0->operand_values()); 3787 InstructionCost ScalarEltCost = 3788 TTI->getArithmeticInstrCost(E->getOpcode(), ScalarTy, CostKind, Op1VK, 3789 Op2VK, Op1VP, Op2VP, Operands, VL0); 3790 if (NeedToShuffleReuses) { 3791 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3792 } 3793 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3794 InstructionCost VecCost = 3795 TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind, Op1VK, 3796 Op2VK, Op1VP, Op2VP, Operands, VL0); 3797 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3798 return ReuseShuffleCost + VecCost - ScalarCost; 3799 } 3800 case Instruction::GetElementPtr: { 3801 TargetTransformInfo::OperandValueKind Op1VK = 3802 TargetTransformInfo::OK_AnyValue; 3803 TargetTransformInfo::OperandValueKind Op2VK = 3804 TargetTransformInfo::OK_UniformConstantValue; 3805 3806 InstructionCost ScalarEltCost = TTI->getArithmeticInstrCost( 3807 Instruction::Add, ScalarTy, CostKind, Op1VK, Op2VK); 3808 if (NeedToShuffleReuses) { 3809 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3810 } 3811 InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3812 InstructionCost VecCost = TTI->getArithmeticInstrCost( 3813 Instruction::Add, VecTy, CostKind, Op1VK, Op2VK); 3814 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3815 return ReuseShuffleCost + VecCost - ScalarCost; 3816 } 3817 case Instruction::Load: { 3818 // Cost of wide load - cost of scalar loads. 3819 Align alignment = cast<LoadInst>(VL0)->getAlign(); 3820 InstructionCost ScalarEltCost = TTI->getMemoryOpCost( 3821 Instruction::Load, ScalarTy, alignment, 0, CostKind, VL0); 3822 if (NeedToShuffleReuses) { 3823 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3824 } 3825 InstructionCost ScalarLdCost = VecTy->getNumElements() * ScalarEltCost; 3826 InstructionCost VecLdCost; 3827 if (E->State == TreeEntry::Vectorize) { 3828 VecLdCost = TTI->getMemoryOpCost(Instruction::Load, VecTy, alignment, 0, 3829 CostKind, VL0); 3830 } else { 3831 assert(E->State == TreeEntry::ScatterVectorize && "Unknown EntryState"); 3832 VecLdCost = TTI->getGatherScatterOpCost( 3833 Instruction::Load, VecTy, cast<LoadInst>(VL0)->getPointerOperand(), 3834 /*VariableMask=*/false, alignment, CostKind, VL0); 3835 } 3836 if (!NeedToShuffleReuses && !E->ReorderIndices.empty()) { 3837 SmallVector<int> NewMask; 3838 inversePermutation(E->ReorderIndices, NewMask); 3839 VecLdCost += TTI->getShuffleCost( 3840 TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask); 3841 } 3842 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecLdCost, ScalarLdCost)); 3843 return ReuseShuffleCost + VecLdCost - ScalarLdCost; 3844 } 3845 case Instruction::Store: { 3846 // We know that we can merge the stores. Calculate the cost. 3847 bool IsReorder = !E->ReorderIndices.empty(); 3848 auto *SI = 3849 cast<StoreInst>(IsReorder ? VL[E->ReorderIndices.front()] : VL0); 3850 Align Alignment = SI->getAlign(); 3851 InstructionCost ScalarEltCost = TTI->getMemoryOpCost( 3852 Instruction::Store, ScalarTy, Alignment, 0, CostKind, VL0); 3853 InstructionCost ScalarStCost = VecTy->getNumElements() * ScalarEltCost; 3854 InstructionCost VecStCost = TTI->getMemoryOpCost( 3855 Instruction::Store, VecTy, Alignment, 0, CostKind, VL0); 3856 if (IsReorder) { 3857 SmallVector<int> NewMask; 3858 inversePermutation(E->ReorderIndices, NewMask); 3859 VecStCost += TTI->getShuffleCost( 3860 TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask); 3861 } 3862 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecStCost, ScalarStCost)); 3863 return VecStCost - ScalarStCost; 3864 } 3865 case Instruction::Call: { 3866 CallInst *CI = cast<CallInst>(VL0); 3867 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3868 3869 // Calculate the cost of the scalar and vector calls. 3870 IntrinsicCostAttributes CostAttrs(ID, *CI, 1); 3871 InstructionCost ScalarEltCost = 3872 TTI->getIntrinsicInstrCost(CostAttrs, CostKind); 3873 if (NeedToShuffleReuses) { 3874 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3875 } 3876 InstructionCost ScalarCallCost = VecTy->getNumElements() * ScalarEltCost; 3877 3878 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 3879 InstructionCost VecCallCost = 3880 std::min(VecCallCosts.first, VecCallCosts.second); 3881 3882 LLVM_DEBUG(dbgs() << "SLP: Call cost " << VecCallCost - ScalarCallCost 3883 << " (" << VecCallCost << "-" << ScalarCallCost << ")" 3884 << " for " << *CI << "\n"); 3885 3886 return ReuseShuffleCost + VecCallCost - ScalarCallCost; 3887 } 3888 case Instruction::ShuffleVector: { 3889 assert(E->isAltShuffle() && 3890 ((Instruction::isBinaryOp(E->getOpcode()) && 3891 Instruction::isBinaryOp(E->getAltOpcode())) || 3892 (Instruction::isCast(E->getOpcode()) && 3893 Instruction::isCast(E->getAltOpcode()))) && 3894 "Invalid Shuffle Vector Operand"); 3895 InstructionCost ScalarCost = 0; 3896 if (NeedToShuffleReuses) { 3897 for (unsigned Idx : E->ReuseShuffleIndices) { 3898 Instruction *I = cast<Instruction>(VL[Idx]); 3899 ReuseShuffleCost -= TTI->getInstructionCost(I, CostKind); 3900 } 3901 for (Value *V : VL) { 3902 Instruction *I = cast<Instruction>(V); 3903 ReuseShuffleCost += TTI->getInstructionCost(I, CostKind); 3904 } 3905 } 3906 for (Value *V : VL) { 3907 Instruction *I = cast<Instruction>(V); 3908 assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode"); 3909 ScalarCost += TTI->getInstructionCost(I, CostKind); 3910 } 3911 // VecCost is equal to sum of the cost of creating 2 vectors 3912 // and the cost of creating shuffle. 3913 InstructionCost VecCost = 0; 3914 if (Instruction::isBinaryOp(E->getOpcode())) { 3915 VecCost = TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind); 3916 VecCost += TTI->getArithmeticInstrCost(E->getAltOpcode(), VecTy, 3917 CostKind); 3918 } else { 3919 Type *Src0SclTy = E->getMainOp()->getOperand(0)->getType(); 3920 Type *Src1SclTy = E->getAltOp()->getOperand(0)->getType(); 3921 auto *Src0Ty = FixedVectorType::get(Src0SclTy, VL.size()); 3922 auto *Src1Ty = FixedVectorType::get(Src1SclTy, VL.size()); 3923 VecCost = TTI->getCastInstrCost(E->getOpcode(), VecTy, Src0Ty, 3924 TTI::CastContextHint::None, CostKind); 3925 VecCost += TTI->getCastInstrCost(E->getAltOpcode(), VecTy, Src1Ty, 3926 TTI::CastContextHint::None, CostKind); 3927 } 3928 3929 SmallVector<int> Mask(E->Scalars.size()); 3930 for (unsigned I = 0, End = E->Scalars.size(); I < End; ++I) { 3931 auto *OpInst = cast<Instruction>(E->Scalars[I]); 3932 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 3933 Mask[I] = I + (OpInst->getOpcode() == E->getAltOpcode() ? End : 0); 3934 } 3935 VecCost += 3936 TTI->getShuffleCost(TargetTransformInfo::SK_Select, VecTy, Mask, 0); 3937 LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost)); 3938 return ReuseShuffleCost + VecCost - ScalarCost; 3939 } 3940 default: 3941 llvm_unreachable("Unknown instruction"); 3942 } 3943 } 3944 3945 bool BoUpSLP::isFullyVectorizableTinyTree() const { 3946 LLVM_DEBUG(dbgs() << "SLP: Check whether the tree with height " 3947 << VectorizableTree.size() << " is fully vectorizable .\n"); 3948 3949 // We only handle trees of heights 1 and 2. 3950 if (VectorizableTree.size() == 1 && 3951 VectorizableTree[0]->State == TreeEntry::Vectorize) 3952 return true; 3953 3954 if (VectorizableTree.size() != 2) 3955 return false; 3956 3957 // Handle splat and all-constants stores. 3958 if (VectorizableTree[0]->State == TreeEntry::Vectorize && 3959 (allConstant(VectorizableTree[1]->Scalars) || 3960 isSplat(VectorizableTree[1]->Scalars))) 3961 return true; 3962 3963 // Gathering cost would be too much for tiny trees. 3964 if (VectorizableTree[0]->State == TreeEntry::NeedToGather || 3965 VectorizableTree[1]->State == TreeEntry::NeedToGather) 3966 return false; 3967 3968 return true; 3969 } 3970 3971 static bool isLoadCombineCandidateImpl(Value *Root, unsigned NumElts, 3972 TargetTransformInfo *TTI) { 3973 // Look past the root to find a source value. Arbitrarily follow the 3974 // path through operand 0 of any 'or'. Also, peek through optional 3975 // shift-left-by-multiple-of-8-bits. 3976 Value *ZextLoad = Root; 3977 const APInt *ShAmtC; 3978 while (!isa<ConstantExpr>(ZextLoad) && 3979 (match(ZextLoad, m_Or(m_Value(), m_Value())) || 3980 (match(ZextLoad, m_Shl(m_Value(), m_APInt(ShAmtC))) && 3981 ShAmtC->urem(8) == 0))) 3982 ZextLoad = cast<BinaryOperator>(ZextLoad)->getOperand(0); 3983 3984 // Check if the input is an extended load of the required or/shift expression. 3985 Value *LoadPtr; 3986 if (ZextLoad == Root || !match(ZextLoad, m_ZExt(m_Load(m_Value(LoadPtr))))) 3987 return false; 3988 3989 // Require that the total load bit width is a legal integer type. 3990 // For example, <8 x i8> --> i64 is a legal integer on a 64-bit target. 3991 // But <16 x i8> --> i128 is not, so the backend probably can't reduce it. 3992 Type *SrcTy = LoadPtr->getType()->getPointerElementType(); 3993 unsigned LoadBitWidth = SrcTy->getIntegerBitWidth() * NumElts; 3994 if (!TTI->isTypeLegal(IntegerType::get(Root->getContext(), LoadBitWidth))) 3995 return false; 3996 3997 // Everything matched - assume that we can fold the whole sequence using 3998 // load combining. 3999 LLVM_DEBUG(dbgs() << "SLP: Assume load combining for tree starting at " 4000 << *(cast<Instruction>(Root)) << "\n"); 4001 4002 return true; 4003 } 4004 4005 bool BoUpSLP::isLoadCombineReductionCandidate(RecurKind RdxKind) const { 4006 if (RdxKind != RecurKind::Or) 4007 return false; 4008 4009 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 4010 Value *FirstReduced = VectorizableTree[0]->Scalars[0]; 4011 return isLoadCombineCandidateImpl(FirstReduced, NumElts, TTI); 4012 } 4013 4014 bool BoUpSLP::isLoadCombineCandidate() const { 4015 // Peek through a final sequence of stores and check if all operations are 4016 // likely to be load-combined. 4017 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 4018 for (Value *Scalar : VectorizableTree[0]->Scalars) { 4019 Value *X; 4020 if (!match(Scalar, m_Store(m_Value(X), m_Value())) || 4021 !isLoadCombineCandidateImpl(X, NumElts, TTI)) 4022 return false; 4023 } 4024 return true; 4025 } 4026 4027 bool BoUpSLP::isTreeTinyAndNotFullyVectorizable() const { 4028 // We can vectorize the tree if its size is greater than or equal to the 4029 // minimum size specified by the MinTreeSize command line option. 4030 if (VectorizableTree.size() >= MinTreeSize) 4031 return false; 4032 4033 // If we have a tiny tree (a tree whose size is less than MinTreeSize), we 4034 // can vectorize it if we can prove it fully vectorizable. 4035 if (isFullyVectorizableTinyTree()) 4036 return false; 4037 4038 assert(VectorizableTree.empty() 4039 ? ExternalUses.empty() 4040 : true && "We shouldn't have any external users"); 4041 4042 // Otherwise, we can't vectorize the tree. It is both tiny and not fully 4043 // vectorizable. 4044 return true; 4045 } 4046 4047 InstructionCost BoUpSLP::getSpillCost() const { 4048 // Walk from the bottom of the tree to the top, tracking which values are 4049 // live. When we see a call instruction that is not part of our tree, 4050 // query TTI to see if there is a cost to keeping values live over it 4051 // (for example, if spills and fills are required). 4052 unsigned BundleWidth = VectorizableTree.front()->Scalars.size(); 4053 InstructionCost Cost = 0; 4054 4055 SmallPtrSet<Instruction*, 4> LiveValues; 4056 Instruction *PrevInst = nullptr; 4057 4058 // The entries in VectorizableTree are not necessarily ordered by their 4059 // position in basic blocks. Collect them and order them by dominance so later 4060 // instructions are guaranteed to be visited first. For instructions in 4061 // different basic blocks, we only scan to the beginning of the block, so 4062 // their order does not matter, as long as all instructions in a basic block 4063 // are grouped together. Using dominance ensures a deterministic order. 4064 SmallVector<Instruction *, 16> OrderedScalars; 4065 for (const auto &TEPtr : VectorizableTree) { 4066 Instruction *Inst = dyn_cast<Instruction>(TEPtr->Scalars[0]); 4067 if (!Inst) 4068 continue; 4069 OrderedScalars.push_back(Inst); 4070 } 4071 llvm::stable_sort(OrderedScalars, [this](Instruction *A, Instruction *B) { 4072 return DT->dominates(B, A); 4073 }); 4074 4075 for (Instruction *Inst : OrderedScalars) { 4076 if (!PrevInst) { 4077 PrevInst = Inst; 4078 continue; 4079 } 4080 4081 // Update LiveValues. 4082 LiveValues.erase(PrevInst); 4083 for (auto &J : PrevInst->operands()) { 4084 if (isa<Instruction>(&*J) && getTreeEntry(&*J)) 4085 LiveValues.insert(cast<Instruction>(&*J)); 4086 } 4087 4088 LLVM_DEBUG({ 4089 dbgs() << "SLP: #LV: " << LiveValues.size(); 4090 for (auto *X : LiveValues) 4091 dbgs() << " " << X->getName(); 4092 dbgs() << ", Looking at "; 4093 Inst->dump(); 4094 }); 4095 4096 // Now find the sequence of instructions between PrevInst and Inst. 4097 unsigned NumCalls = 0; 4098 BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(), 4099 PrevInstIt = 4100 PrevInst->getIterator().getReverse(); 4101 while (InstIt != PrevInstIt) { 4102 if (PrevInstIt == PrevInst->getParent()->rend()) { 4103 PrevInstIt = Inst->getParent()->rbegin(); 4104 continue; 4105 } 4106 4107 // Debug information does not impact spill cost. 4108 if ((isa<CallInst>(&*PrevInstIt) && 4109 !isa<DbgInfoIntrinsic>(&*PrevInstIt)) && 4110 &*PrevInstIt != PrevInst) 4111 NumCalls++; 4112 4113 ++PrevInstIt; 4114 } 4115 4116 if (NumCalls) { 4117 SmallVector<Type*, 4> V; 4118 for (auto *II : LiveValues) 4119 V.push_back(FixedVectorType::get(II->getType(), BundleWidth)); 4120 Cost += NumCalls * TTI->getCostOfKeepingLiveOverCall(V); 4121 } 4122 4123 PrevInst = Inst; 4124 } 4125 4126 return Cost; 4127 } 4128 4129 InstructionCost BoUpSLP::getTreeCost() { 4130 InstructionCost Cost = 0; 4131 LLVM_DEBUG(dbgs() << "SLP: Calculating cost for tree of size " 4132 << VectorizableTree.size() << ".\n"); 4133 4134 unsigned BundleWidth = VectorizableTree[0]->Scalars.size(); 4135 4136 for (unsigned I = 0, E = VectorizableTree.size(); I < E; ++I) { 4137 TreeEntry &TE = *VectorizableTree[I].get(); 4138 4139 // We create duplicate tree entries for gather sequences that have multiple 4140 // uses. However, we should not compute the cost of duplicate sequences. 4141 // For example, if we have a build vector (i.e., insertelement sequence) 4142 // that is used by more than one vector instruction, we only need to 4143 // compute the cost of the insertelement instructions once. The redundant 4144 // instructions will be eliminated by CSE. 4145 // 4146 // We should consider not creating duplicate tree entries for gather 4147 // sequences, and instead add additional edges to the tree representing 4148 // their uses. Since such an approach results in fewer total entries, 4149 // existing heuristics based on tree size may yield different results. 4150 // 4151 if (TE.State == TreeEntry::NeedToGather && 4152 std::any_of(std::next(VectorizableTree.begin(), I + 1), 4153 VectorizableTree.end(), 4154 [TE](const std::unique_ptr<TreeEntry> &EntryPtr) { 4155 return EntryPtr->State == TreeEntry::NeedToGather && 4156 EntryPtr->isSame(TE.Scalars); 4157 })) 4158 continue; 4159 4160 InstructionCost C = getEntryCost(&TE); 4161 Cost += C; 4162 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C 4163 << " for bundle that starts with " << *TE.Scalars[0] 4164 << ".\n" 4165 << "SLP: Current total cost = " << Cost << "\n"); 4166 } 4167 4168 SmallPtrSet<Value *, 16> ExtractCostCalculated; 4169 InstructionCost ExtractCost = 0; 4170 for (ExternalUser &EU : ExternalUses) { 4171 // We only add extract cost once for the same scalar. 4172 if (!ExtractCostCalculated.insert(EU.Scalar).second) 4173 continue; 4174 4175 // Uses by ephemeral values are free (because the ephemeral value will be 4176 // removed prior to code generation, and so the extraction will be 4177 // removed as well). 4178 if (EphValues.count(EU.User)) 4179 continue; 4180 4181 // If we plan to rewrite the tree in a smaller type, we will need to sign 4182 // extend the extracted value back to the original type. Here, we account 4183 // for the extract and the added cost of the sign extend if needed. 4184 auto *VecTy = FixedVectorType::get(EU.Scalar->getType(), BundleWidth); 4185 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 4186 if (MinBWs.count(ScalarRoot)) { 4187 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 4188 auto Extend = 4189 MinBWs[ScalarRoot].second ? Instruction::SExt : Instruction::ZExt; 4190 VecTy = FixedVectorType::get(MinTy, BundleWidth); 4191 ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(), 4192 VecTy, EU.Lane); 4193 } else { 4194 ExtractCost += 4195 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, EU.Lane); 4196 } 4197 } 4198 4199 InstructionCost SpillCost = getSpillCost(); 4200 Cost += SpillCost + ExtractCost; 4201 4202 #ifndef NDEBUG 4203 SmallString<256> Str; 4204 { 4205 raw_svector_ostream OS(Str); 4206 OS << "SLP: Spill Cost = " << SpillCost << ".\n" 4207 << "SLP: Extract Cost = " << ExtractCost << ".\n" 4208 << "SLP: Total Cost = " << Cost << ".\n"; 4209 } 4210 LLVM_DEBUG(dbgs() << Str); 4211 if (ViewSLPTree) 4212 ViewGraph(this, "SLP" + F->getName(), false, Str); 4213 #endif 4214 4215 return Cost; 4216 } 4217 4218 InstructionCost 4219 BoUpSLP::getGatherCost(FixedVectorType *Ty, 4220 const DenseSet<unsigned> &ShuffledIndices) const { 4221 unsigned NumElts = Ty->getNumElements(); 4222 APInt DemandedElts = APInt::getNullValue(NumElts); 4223 for (unsigned I = 0; I < NumElts; ++I) 4224 if (!ShuffledIndices.count(I)) 4225 DemandedElts.setBit(I); 4226 InstructionCost Cost = 4227 TTI->getScalarizationOverhead(Ty, DemandedElts, /*Insert*/ true, 4228 /*Extract*/ false); 4229 if (!ShuffledIndices.empty()) 4230 Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, Ty); 4231 return Cost; 4232 } 4233 4234 InstructionCost BoUpSLP::getGatherCost(ArrayRef<Value *> VL) const { 4235 // Find the type of the operands in VL. 4236 Type *ScalarTy = VL[0]->getType(); 4237 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 4238 ScalarTy = SI->getValueOperand()->getType(); 4239 auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); 4240 // Find the cost of inserting/extracting values from the vector. 4241 // Check if the same elements are inserted several times and count them as 4242 // shuffle candidates. 4243 DenseSet<unsigned> ShuffledElements; 4244 DenseSet<Value *> UniqueElements; 4245 // Iterate in reverse order to consider insert elements with the high cost. 4246 for (unsigned I = VL.size(); I > 0; --I) { 4247 unsigned Idx = I - 1; 4248 if (!UniqueElements.insert(VL[Idx]).second) 4249 ShuffledElements.insert(Idx); 4250 } 4251 return getGatherCost(VecTy, ShuffledElements); 4252 } 4253 4254 // Perform operand reordering on the instructions in VL and return the reordered 4255 // operands in Left and Right. 4256 void BoUpSLP::reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 4257 SmallVectorImpl<Value *> &Left, 4258 SmallVectorImpl<Value *> &Right, 4259 const DataLayout &DL, 4260 ScalarEvolution &SE, 4261 const BoUpSLP &R) { 4262 if (VL.empty()) 4263 return; 4264 VLOperands Ops(VL, DL, SE, R); 4265 // Reorder the operands in place. 4266 Ops.reorder(); 4267 Left = Ops.getVL(0); 4268 Right = Ops.getVL(1); 4269 } 4270 4271 void BoUpSLP::setInsertPointAfterBundle(TreeEntry *E) { 4272 // Get the basic block this bundle is in. All instructions in the bundle 4273 // should be in this block. 4274 auto *Front = E->getMainOp(); 4275 auto *BB = Front->getParent(); 4276 assert(llvm::all_of(E->Scalars, [=](Value *V) -> bool { 4277 auto *I = cast<Instruction>(V); 4278 return !E->isOpcodeOrAlt(I) || I->getParent() == BB; 4279 })); 4280 4281 // The last instruction in the bundle in program order. 4282 Instruction *LastInst = nullptr; 4283 4284 // Find the last instruction. The common case should be that BB has been 4285 // scheduled, and the last instruction is VL.back(). So we start with 4286 // VL.back() and iterate over schedule data until we reach the end of the 4287 // bundle. The end of the bundle is marked by null ScheduleData. 4288 if (BlocksSchedules.count(BB)) { 4289 auto *Bundle = 4290 BlocksSchedules[BB]->getScheduleData(E->isOneOf(E->Scalars.back())); 4291 if (Bundle && Bundle->isPartOfBundle()) 4292 for (; Bundle; Bundle = Bundle->NextInBundle) 4293 if (Bundle->OpValue == Bundle->Inst) 4294 LastInst = Bundle->Inst; 4295 } 4296 4297 // LastInst can still be null at this point if there's either not an entry 4298 // for BB in BlocksSchedules or there's no ScheduleData available for 4299 // VL.back(). This can be the case if buildTree_rec aborts for various 4300 // reasons (e.g., the maximum recursion depth is reached, the maximum region 4301 // size is reached, etc.). ScheduleData is initialized in the scheduling 4302 // "dry-run". 4303 // 4304 // If this happens, we can still find the last instruction by brute force. We 4305 // iterate forwards from Front (inclusive) until we either see all 4306 // instructions in the bundle or reach the end of the block. If Front is the 4307 // last instruction in program order, LastInst will be set to Front, and we 4308 // will visit all the remaining instructions in the block. 4309 // 4310 // One of the reasons we exit early from buildTree_rec is to place an upper 4311 // bound on compile-time. Thus, taking an additional compile-time hit here is 4312 // not ideal. However, this should be exceedingly rare since it requires that 4313 // we both exit early from buildTree_rec and that the bundle be out-of-order 4314 // (causing us to iterate all the way to the end of the block). 4315 if (!LastInst) { 4316 SmallPtrSet<Value *, 16> Bundle(E->Scalars.begin(), E->Scalars.end()); 4317 for (auto &I : make_range(BasicBlock::iterator(Front), BB->end())) { 4318 if (Bundle.erase(&I) && E->isOpcodeOrAlt(&I)) 4319 LastInst = &I; 4320 if (Bundle.empty()) 4321 break; 4322 } 4323 } 4324 assert(LastInst && "Failed to find last instruction in bundle"); 4325 4326 // Set the insertion point after the last instruction in the bundle. Set the 4327 // debug location to Front. 4328 Builder.SetInsertPoint(BB, ++LastInst->getIterator()); 4329 Builder.SetCurrentDebugLocation(Front->getDebugLoc()); 4330 } 4331 4332 Value *BoUpSLP::gather(ArrayRef<Value *> VL) { 4333 Value *Val0 = 4334 isa<StoreInst>(VL[0]) ? cast<StoreInst>(VL[0])->getValueOperand() : VL[0]; 4335 FixedVectorType *VecTy = FixedVectorType::get(Val0->getType(), VL.size()); 4336 Value *Vec = PoisonValue::get(VecTy); 4337 unsigned InsIndex = 0; 4338 for (Value *Val : VL) { 4339 Vec = Builder.CreateInsertElement(Vec, Val, Builder.getInt32(InsIndex++)); 4340 auto *InsElt = dyn_cast<InsertElementInst>(Vec); 4341 if (!InsElt) 4342 continue; 4343 GatherSeq.insert(InsElt); 4344 CSEBlocks.insert(InsElt->getParent()); 4345 // Add to our 'need-to-extract' list. 4346 if (TreeEntry *Entry = getTreeEntry(Val)) { 4347 // Find which lane we need to extract. 4348 unsigned FoundLane = std::distance(Entry->Scalars.begin(), 4349 find(Entry->Scalars, Val)); 4350 assert(FoundLane < Entry->Scalars.size() && "Couldn't find extract lane"); 4351 if (!Entry->ReuseShuffleIndices.empty()) { 4352 FoundLane = std::distance(Entry->ReuseShuffleIndices.begin(), 4353 find(Entry->ReuseShuffleIndices, FoundLane)); 4354 } 4355 ExternalUses.push_back(ExternalUser(Val, InsElt, FoundLane)); 4356 } 4357 } 4358 4359 return Vec; 4360 } 4361 4362 Value *BoUpSLP::vectorizeTree(ArrayRef<Value *> VL) { 4363 InstructionsState S = getSameOpcode(VL); 4364 if (S.getOpcode()) { 4365 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 4366 if (E->isSame(VL)) { 4367 Value *V = vectorizeTree(E); 4368 if (VL.size() == E->Scalars.size() && !E->ReuseShuffleIndices.empty()) { 4369 // Reshuffle to get only unique values. 4370 // If some of the scalars are duplicated in the vectorization tree 4371 // entry, we do not vectorize them but instead generate a mask for the 4372 // reuses. But if there are several users of the same entry, they may 4373 // have different vectorization factors. This is especially important 4374 // for PHI nodes. In this case, we need to adapt the resulting 4375 // instruction for the user vectorization factor and have to reshuffle 4376 // it again to take only unique elements of the vector. Without this 4377 // code the function incorrectly returns reduced vector instruction 4378 // with the same elements, not with the unique ones. 4379 // block: 4380 // %phi = phi <2 x > { .., %entry} {%shuffle, %block} 4381 // %2 = shuffle <2 x > %phi, %poison, <4 x > <0, 0, 1, 1> 4382 // ... (use %2) 4383 // %shuffle = shuffle <2 x> %2, poison, <2 x> {0, 2} 4384 // br %block 4385 SmallVector<int, 4> UniqueIdxs; 4386 SmallSet<int, 4> UsedIdxs; 4387 int Pos = 0; 4388 for (int Idx : E->ReuseShuffleIndices) { 4389 if (UsedIdxs.insert(Idx).second) 4390 UniqueIdxs.emplace_back(Pos); 4391 ++Pos; 4392 } 4393 V = Builder.CreateShuffleVector(V, UniqueIdxs, "shrink.shuffle"); 4394 } 4395 return V; 4396 } 4397 } 4398 } 4399 4400 // Check that every instruction appears once in this bundle. 4401 SmallVector<int, 4> ReuseShuffleIndicies; 4402 SmallVector<Value *, 4> UniqueValues; 4403 if (VL.size() > 2) { 4404 DenseMap<Value *, unsigned> UniquePositions; 4405 for (Value *V : VL) { 4406 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 4407 ReuseShuffleIndicies.emplace_back(Res.first->second); 4408 if (Res.second || isa<Constant>(V)) 4409 UniqueValues.emplace_back(V); 4410 } 4411 // Do not shuffle single element or if number of unique values is not power 4412 // of 2. 4413 if (UniqueValues.size() == VL.size() || UniqueValues.size() <= 1 || 4414 !llvm::isPowerOf2_32(UniqueValues.size())) 4415 ReuseShuffleIndicies.clear(); 4416 else 4417 VL = UniqueValues; 4418 } 4419 4420 Value *Vec = gather(VL); 4421 if (!ReuseShuffleIndicies.empty()) { 4422 Vec = Builder.CreateShuffleVector(Vec, ReuseShuffleIndicies, "shuffle"); 4423 if (auto *I = dyn_cast<Instruction>(Vec)) { 4424 GatherSeq.insert(I); 4425 CSEBlocks.insert(I->getParent()); 4426 } 4427 } 4428 return Vec; 4429 } 4430 4431 namespace { 4432 /// Merges shuffle masks and emits final shuffle instruction, if required. 4433 class ShuffleInstructionBuilder { 4434 IRBuilderBase &Builder; 4435 bool IsFinalized = false; 4436 SmallVector<int, 4> Mask; 4437 4438 public: 4439 ShuffleInstructionBuilder(IRBuilderBase &Builder) : Builder(Builder) {} 4440 4441 /// Adds a mask, inverting it before applying. 4442 void addInversedMask(ArrayRef<unsigned> SubMask) { 4443 if (SubMask.empty()) 4444 return; 4445 SmallVector<int, 4> NewMask; 4446 inversePermutation(SubMask, NewMask); 4447 addMask(NewMask); 4448 } 4449 4450 /// Functions adds masks, merging them into single one. 4451 void addMask(ArrayRef<unsigned> SubMask) { 4452 SmallVector<int, 4> NewMask(SubMask.begin(), SubMask.end()); 4453 addMask(NewMask); 4454 } 4455 4456 void addMask(ArrayRef<int> SubMask) { 4457 if (SubMask.empty()) 4458 return; 4459 if (Mask.empty()) { 4460 Mask.append(SubMask.begin(), SubMask.end()); 4461 return; 4462 } 4463 SmallVector<int, 4> NewMask(SubMask.size(), SubMask.size()); 4464 int TermValue = std::min(Mask.size(), SubMask.size()); 4465 for (int I = 0, E = SubMask.size(); I < E; ++I) { 4466 if (SubMask[I] >= TermValue || Mask[SubMask[I]] >= TermValue) { 4467 NewMask[I] = E; 4468 continue; 4469 } 4470 NewMask[I] = Mask[SubMask[I]]; 4471 } 4472 Mask.swap(NewMask); 4473 } 4474 4475 Value *finalize(Value *V) { 4476 IsFinalized = true; 4477 if (Mask.empty()) 4478 return V; 4479 return Builder.CreateShuffleVector(V, Mask, "shuffle"); 4480 } 4481 4482 ~ShuffleInstructionBuilder() { 4483 assert((IsFinalized || Mask.empty()) && 4484 "Shuffle construction must be finalized."); 4485 } 4486 }; 4487 } // namespace 4488 4489 Value *BoUpSLP::vectorizeTree(TreeEntry *E) { 4490 IRBuilder<>::InsertPointGuard Guard(Builder); 4491 4492 if (E->VectorizedValue) { 4493 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *E->Scalars[0] << ".\n"); 4494 return E->VectorizedValue; 4495 } 4496 4497 ShuffleInstructionBuilder ShuffleBuilder(Builder); 4498 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 4499 if (E->State == TreeEntry::NeedToGather) { 4500 setInsertPointAfterBundle(E); 4501 Value *Vec = gather(E->Scalars); 4502 if (NeedToShuffleReuses) { 4503 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4504 Vec = ShuffleBuilder.finalize(Vec); 4505 if (auto *I = dyn_cast<Instruction>(Vec)) { 4506 GatherSeq.insert(I); 4507 CSEBlocks.insert(I->getParent()); 4508 } 4509 } 4510 E->VectorizedValue = Vec; 4511 return Vec; 4512 } 4513 4514 assert((E->State == TreeEntry::Vectorize || 4515 E->State == TreeEntry::ScatterVectorize) && 4516 "Unhandled state"); 4517 unsigned ShuffleOrOp = 4518 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 4519 Instruction *VL0 = E->getMainOp(); 4520 Type *ScalarTy = VL0->getType(); 4521 if (auto *Store = dyn_cast<StoreInst>(VL0)) 4522 ScalarTy = Store->getValueOperand()->getType(); 4523 auto *VecTy = FixedVectorType::get(ScalarTy, E->Scalars.size()); 4524 switch (ShuffleOrOp) { 4525 case Instruction::PHI: { 4526 auto *PH = cast<PHINode>(VL0); 4527 Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI()); 4528 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 4529 PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues()); 4530 Value *V = NewPhi; 4531 if (NeedToShuffleReuses) 4532 V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle"); 4533 4534 E->VectorizedValue = V; 4535 4536 // PHINodes may have multiple entries from the same block. We want to 4537 // visit every block once. 4538 SmallPtrSet<BasicBlock*, 4> VisitedBBs; 4539 4540 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 4541 ValueList Operands; 4542 BasicBlock *IBB = PH->getIncomingBlock(i); 4543 4544 if (!VisitedBBs.insert(IBB).second) { 4545 NewPhi->addIncoming(NewPhi->getIncomingValueForBlock(IBB), IBB); 4546 continue; 4547 } 4548 4549 Builder.SetInsertPoint(IBB->getTerminator()); 4550 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 4551 Value *Vec = vectorizeTree(E->getOperand(i)); 4552 NewPhi->addIncoming(Vec, IBB); 4553 } 4554 4555 assert(NewPhi->getNumIncomingValues() == PH->getNumIncomingValues() && 4556 "Invalid number of incoming values"); 4557 return V; 4558 } 4559 4560 case Instruction::ExtractElement: { 4561 Value *V = E->getSingleOperand(0); 4562 Builder.SetInsertPoint(VL0); 4563 ShuffleBuilder.addInversedMask(E->ReorderIndices); 4564 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4565 V = ShuffleBuilder.finalize(V); 4566 E->VectorizedValue = V; 4567 return V; 4568 } 4569 case Instruction::ExtractValue: { 4570 auto *LI = cast<LoadInst>(E->getSingleOperand(0)); 4571 Builder.SetInsertPoint(LI); 4572 auto *PtrTy = PointerType::get(VecTy, LI->getPointerAddressSpace()); 4573 Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy); 4574 LoadInst *V = Builder.CreateAlignedLoad(VecTy, Ptr, LI->getAlign()); 4575 Value *NewV = propagateMetadata(V, E->Scalars); 4576 ShuffleBuilder.addInversedMask(E->ReorderIndices); 4577 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4578 NewV = ShuffleBuilder.finalize(NewV); 4579 E->VectorizedValue = NewV; 4580 return NewV; 4581 } 4582 case Instruction::ZExt: 4583 case Instruction::SExt: 4584 case Instruction::FPToUI: 4585 case Instruction::FPToSI: 4586 case Instruction::FPExt: 4587 case Instruction::PtrToInt: 4588 case Instruction::IntToPtr: 4589 case Instruction::SIToFP: 4590 case Instruction::UIToFP: 4591 case Instruction::Trunc: 4592 case Instruction::FPTrunc: 4593 case Instruction::BitCast: { 4594 setInsertPointAfterBundle(E); 4595 4596 Value *InVec = vectorizeTree(E->getOperand(0)); 4597 4598 if (E->VectorizedValue) { 4599 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4600 return E->VectorizedValue; 4601 } 4602 4603 auto *CI = cast<CastInst>(VL0); 4604 Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy); 4605 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4606 V = ShuffleBuilder.finalize(V); 4607 4608 E->VectorizedValue = V; 4609 ++NumVectorInstructions; 4610 return V; 4611 } 4612 case Instruction::FCmp: 4613 case Instruction::ICmp: { 4614 setInsertPointAfterBundle(E); 4615 4616 Value *L = vectorizeTree(E->getOperand(0)); 4617 Value *R = vectorizeTree(E->getOperand(1)); 4618 4619 if (E->VectorizedValue) { 4620 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4621 return E->VectorizedValue; 4622 } 4623 4624 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 4625 Value *V = Builder.CreateCmp(P0, L, R); 4626 propagateIRFlags(V, E->Scalars, VL0); 4627 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4628 V = ShuffleBuilder.finalize(V); 4629 4630 E->VectorizedValue = V; 4631 ++NumVectorInstructions; 4632 return V; 4633 } 4634 case Instruction::Select: { 4635 setInsertPointAfterBundle(E); 4636 4637 Value *Cond = vectorizeTree(E->getOperand(0)); 4638 Value *True = vectorizeTree(E->getOperand(1)); 4639 Value *False = vectorizeTree(E->getOperand(2)); 4640 4641 if (E->VectorizedValue) { 4642 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4643 return E->VectorizedValue; 4644 } 4645 4646 Value *V = Builder.CreateSelect(Cond, True, False); 4647 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4648 V = ShuffleBuilder.finalize(V); 4649 4650 E->VectorizedValue = V; 4651 ++NumVectorInstructions; 4652 return V; 4653 } 4654 case Instruction::FNeg: { 4655 setInsertPointAfterBundle(E); 4656 4657 Value *Op = vectorizeTree(E->getOperand(0)); 4658 4659 if (E->VectorizedValue) { 4660 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4661 return E->VectorizedValue; 4662 } 4663 4664 Value *V = Builder.CreateUnOp( 4665 static_cast<Instruction::UnaryOps>(E->getOpcode()), Op); 4666 propagateIRFlags(V, E->Scalars, VL0); 4667 if (auto *I = dyn_cast<Instruction>(V)) 4668 V = propagateMetadata(I, E->Scalars); 4669 4670 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4671 V = ShuffleBuilder.finalize(V); 4672 4673 E->VectorizedValue = V; 4674 ++NumVectorInstructions; 4675 4676 return V; 4677 } 4678 case Instruction::Add: 4679 case Instruction::FAdd: 4680 case Instruction::Sub: 4681 case Instruction::FSub: 4682 case Instruction::Mul: 4683 case Instruction::FMul: 4684 case Instruction::UDiv: 4685 case Instruction::SDiv: 4686 case Instruction::FDiv: 4687 case Instruction::URem: 4688 case Instruction::SRem: 4689 case Instruction::FRem: 4690 case Instruction::Shl: 4691 case Instruction::LShr: 4692 case Instruction::AShr: 4693 case Instruction::And: 4694 case Instruction::Or: 4695 case Instruction::Xor: { 4696 setInsertPointAfterBundle(E); 4697 4698 Value *LHS = vectorizeTree(E->getOperand(0)); 4699 Value *RHS = vectorizeTree(E->getOperand(1)); 4700 4701 if (E->VectorizedValue) { 4702 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4703 return E->VectorizedValue; 4704 } 4705 4706 Value *V = Builder.CreateBinOp( 4707 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, 4708 RHS); 4709 propagateIRFlags(V, E->Scalars, VL0); 4710 if (auto *I = dyn_cast<Instruction>(V)) 4711 V = propagateMetadata(I, E->Scalars); 4712 4713 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4714 V = ShuffleBuilder.finalize(V); 4715 4716 E->VectorizedValue = V; 4717 ++NumVectorInstructions; 4718 4719 return V; 4720 } 4721 case Instruction::Load: { 4722 // Loads are inserted at the head of the tree because we don't want to 4723 // sink them all the way down past store instructions. 4724 bool IsReorder = E->updateStateIfReorder(); 4725 if (IsReorder) 4726 VL0 = E->getMainOp(); 4727 setInsertPointAfterBundle(E); 4728 4729 LoadInst *LI = cast<LoadInst>(VL0); 4730 Instruction *NewLI; 4731 unsigned AS = LI->getPointerAddressSpace(); 4732 Value *PO = LI->getPointerOperand(); 4733 if (E->State == TreeEntry::Vectorize) { 4734 4735 Value *VecPtr = Builder.CreateBitCast(PO, VecTy->getPointerTo(AS)); 4736 4737 // The pointer operand uses an in-tree scalar so we add the new BitCast 4738 // to ExternalUses list to make sure that an extract will be generated 4739 // in the future. 4740 if (getTreeEntry(PO)) 4741 ExternalUses.emplace_back(PO, cast<User>(VecPtr), 0); 4742 4743 NewLI = Builder.CreateAlignedLoad(VecTy, VecPtr, LI->getAlign()); 4744 } else { 4745 assert(E->State == TreeEntry::ScatterVectorize && "Unhandled state"); 4746 Value *VecPtr = vectorizeTree(E->getOperand(0)); 4747 // Use the minimum alignment of the gathered loads. 4748 Align CommonAlignment = LI->getAlign(); 4749 for (Value *V : E->Scalars) 4750 CommonAlignment = 4751 commonAlignment(CommonAlignment, cast<LoadInst>(V)->getAlign()); 4752 NewLI = Builder.CreateMaskedGather(VecPtr, CommonAlignment); 4753 } 4754 Value *V = propagateMetadata(NewLI, E->Scalars); 4755 4756 ShuffleBuilder.addInversedMask(E->ReorderIndices); 4757 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4758 V = ShuffleBuilder.finalize(V); 4759 E->VectorizedValue = V; 4760 ++NumVectorInstructions; 4761 return V; 4762 } 4763 case Instruction::Store: { 4764 bool IsReorder = !E->ReorderIndices.empty(); 4765 auto *SI = cast<StoreInst>( 4766 IsReorder ? E->Scalars[E->ReorderIndices.front()] : VL0); 4767 unsigned AS = SI->getPointerAddressSpace(); 4768 4769 setInsertPointAfterBundle(E); 4770 4771 Value *VecValue = vectorizeTree(E->getOperand(0)); 4772 ShuffleBuilder.addMask(E->ReorderIndices); 4773 VecValue = ShuffleBuilder.finalize(VecValue); 4774 4775 Value *ScalarPtr = SI->getPointerOperand(); 4776 Value *VecPtr = Builder.CreateBitCast( 4777 ScalarPtr, VecValue->getType()->getPointerTo(AS)); 4778 StoreInst *ST = Builder.CreateAlignedStore(VecValue, VecPtr, 4779 SI->getAlign()); 4780 4781 // The pointer operand uses an in-tree scalar, so add the new BitCast to 4782 // ExternalUses to make sure that an extract will be generated in the 4783 // future. 4784 if (getTreeEntry(ScalarPtr)) 4785 ExternalUses.push_back(ExternalUser(ScalarPtr, cast<User>(VecPtr), 0)); 4786 4787 Value *V = propagateMetadata(ST, E->Scalars); 4788 4789 E->VectorizedValue = V; 4790 ++NumVectorInstructions; 4791 return V; 4792 } 4793 case Instruction::GetElementPtr: { 4794 setInsertPointAfterBundle(E); 4795 4796 Value *Op0 = vectorizeTree(E->getOperand(0)); 4797 4798 std::vector<Value *> OpVecs; 4799 for (int j = 1, e = cast<GetElementPtrInst>(VL0)->getNumOperands(); j < e; 4800 ++j) { 4801 ValueList &VL = E->getOperand(j); 4802 // Need to cast all elements to the same type before vectorization to 4803 // avoid crash. 4804 Type *VL0Ty = VL0->getOperand(j)->getType(); 4805 Type *Ty = llvm::all_of( 4806 VL, [VL0Ty](Value *V) { return VL0Ty == V->getType(); }) 4807 ? VL0Ty 4808 : DL->getIndexType(cast<GetElementPtrInst>(VL0) 4809 ->getPointerOperandType() 4810 ->getScalarType()); 4811 for (Value *&V : VL) { 4812 auto *CI = cast<ConstantInt>(V); 4813 V = ConstantExpr::getIntegerCast(CI, Ty, 4814 CI->getValue().isSignBitSet()); 4815 } 4816 Value *OpVec = vectorizeTree(VL); 4817 OpVecs.push_back(OpVec); 4818 } 4819 4820 Value *V = Builder.CreateGEP( 4821 cast<GetElementPtrInst>(VL0)->getSourceElementType(), Op0, OpVecs); 4822 if (Instruction *I = dyn_cast<Instruction>(V)) 4823 V = propagateMetadata(I, E->Scalars); 4824 4825 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4826 V = ShuffleBuilder.finalize(V); 4827 4828 E->VectorizedValue = V; 4829 ++NumVectorInstructions; 4830 4831 return V; 4832 } 4833 case Instruction::Call: { 4834 CallInst *CI = cast<CallInst>(VL0); 4835 setInsertPointAfterBundle(E); 4836 4837 Intrinsic::ID IID = Intrinsic::not_intrinsic; 4838 if (Function *FI = CI->getCalledFunction()) 4839 IID = FI->getIntrinsicID(); 4840 4841 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 4842 4843 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 4844 bool UseIntrinsic = ID != Intrinsic::not_intrinsic && 4845 VecCallCosts.first <= VecCallCosts.second; 4846 4847 Value *ScalarArg = nullptr; 4848 std::vector<Value *> OpVecs; 4849 for (int j = 0, e = CI->getNumArgOperands(); j < e; ++j) { 4850 ValueList OpVL; 4851 // Some intrinsics have scalar arguments. This argument should not be 4852 // vectorized. 4853 if (UseIntrinsic && hasVectorInstrinsicScalarOpd(IID, j)) { 4854 CallInst *CEI = cast<CallInst>(VL0); 4855 ScalarArg = CEI->getArgOperand(j); 4856 OpVecs.push_back(CEI->getArgOperand(j)); 4857 continue; 4858 } 4859 4860 Value *OpVec = vectorizeTree(E->getOperand(j)); 4861 LLVM_DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n"); 4862 OpVecs.push_back(OpVec); 4863 } 4864 4865 Function *CF; 4866 if (!UseIntrinsic) { 4867 VFShape Shape = 4868 VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>( 4869 VecTy->getNumElements())), 4870 false /*HasGlobalPred*/); 4871 CF = VFDatabase(*CI).getVectorizedFunction(Shape); 4872 } else { 4873 Type *Tys[] = {FixedVectorType::get(CI->getType(), E->Scalars.size())}; 4874 CF = Intrinsic::getDeclaration(F->getParent(), ID, Tys); 4875 } 4876 4877 SmallVector<OperandBundleDef, 1> OpBundles; 4878 CI->getOperandBundlesAsDefs(OpBundles); 4879 Value *V = Builder.CreateCall(CF, OpVecs, OpBundles); 4880 4881 // The scalar argument uses an in-tree scalar so we add the new vectorized 4882 // call to ExternalUses list to make sure that an extract will be 4883 // generated in the future. 4884 if (ScalarArg && getTreeEntry(ScalarArg)) 4885 ExternalUses.push_back(ExternalUser(ScalarArg, cast<User>(V), 0)); 4886 4887 propagateIRFlags(V, E->Scalars, VL0); 4888 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4889 V = ShuffleBuilder.finalize(V); 4890 4891 E->VectorizedValue = V; 4892 ++NumVectorInstructions; 4893 return V; 4894 } 4895 case Instruction::ShuffleVector: { 4896 assert(E->isAltShuffle() && 4897 ((Instruction::isBinaryOp(E->getOpcode()) && 4898 Instruction::isBinaryOp(E->getAltOpcode())) || 4899 (Instruction::isCast(E->getOpcode()) && 4900 Instruction::isCast(E->getAltOpcode()))) && 4901 "Invalid Shuffle Vector Operand"); 4902 4903 Value *LHS = nullptr, *RHS = nullptr; 4904 if (Instruction::isBinaryOp(E->getOpcode())) { 4905 setInsertPointAfterBundle(E); 4906 LHS = vectorizeTree(E->getOperand(0)); 4907 RHS = vectorizeTree(E->getOperand(1)); 4908 } else { 4909 setInsertPointAfterBundle(E); 4910 LHS = vectorizeTree(E->getOperand(0)); 4911 } 4912 4913 if (E->VectorizedValue) { 4914 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4915 return E->VectorizedValue; 4916 } 4917 4918 Value *V0, *V1; 4919 if (Instruction::isBinaryOp(E->getOpcode())) { 4920 V0 = Builder.CreateBinOp( 4921 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, RHS); 4922 V1 = Builder.CreateBinOp( 4923 static_cast<Instruction::BinaryOps>(E->getAltOpcode()), LHS, RHS); 4924 } else { 4925 V0 = Builder.CreateCast( 4926 static_cast<Instruction::CastOps>(E->getOpcode()), LHS, VecTy); 4927 V1 = Builder.CreateCast( 4928 static_cast<Instruction::CastOps>(E->getAltOpcode()), LHS, VecTy); 4929 } 4930 4931 // Create shuffle to take alternate operations from the vector. 4932 // Also, gather up main and alt scalar ops to propagate IR flags to 4933 // each vector operation. 4934 ValueList OpScalars, AltScalars; 4935 unsigned e = E->Scalars.size(); 4936 SmallVector<int, 8> Mask(e); 4937 for (unsigned i = 0; i < e; ++i) { 4938 auto *OpInst = cast<Instruction>(E->Scalars[i]); 4939 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 4940 if (OpInst->getOpcode() == E->getAltOpcode()) { 4941 Mask[i] = e + i; 4942 AltScalars.push_back(E->Scalars[i]); 4943 } else { 4944 Mask[i] = i; 4945 OpScalars.push_back(E->Scalars[i]); 4946 } 4947 } 4948 4949 propagateIRFlags(V0, OpScalars); 4950 propagateIRFlags(V1, AltScalars); 4951 4952 Value *V = Builder.CreateShuffleVector(V0, V1, Mask); 4953 if (Instruction *I = dyn_cast<Instruction>(V)) 4954 V = propagateMetadata(I, E->Scalars); 4955 ShuffleBuilder.addMask(E->ReuseShuffleIndices); 4956 V = ShuffleBuilder.finalize(V); 4957 4958 E->VectorizedValue = V; 4959 ++NumVectorInstructions; 4960 4961 return V; 4962 } 4963 default: 4964 llvm_unreachable("unknown inst"); 4965 } 4966 return nullptr; 4967 } 4968 4969 Value *BoUpSLP::vectorizeTree() { 4970 ExtraValueToDebugLocsMap ExternallyUsedValues; 4971 return vectorizeTree(ExternallyUsedValues); 4972 } 4973 4974 Value * 4975 BoUpSLP::vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues) { 4976 // All blocks must be scheduled before any instructions are inserted. 4977 for (auto &BSIter : BlocksSchedules) { 4978 scheduleBlock(BSIter.second.get()); 4979 } 4980 4981 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4982 auto *VectorRoot = vectorizeTree(VectorizableTree[0].get()); 4983 4984 // If the vectorized tree can be rewritten in a smaller type, we truncate the 4985 // vectorized root. InstCombine will then rewrite the entire expression. We 4986 // sign extend the extracted values below. 4987 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 4988 if (MinBWs.count(ScalarRoot)) { 4989 if (auto *I = dyn_cast<Instruction>(VectorRoot)) { 4990 // If current instr is a phi and not the last phi, insert it after the 4991 // last phi node. 4992 if (isa<PHINode>(I)) 4993 Builder.SetInsertPoint(&*I->getParent()->getFirstInsertionPt()); 4994 else 4995 Builder.SetInsertPoint(&*++BasicBlock::iterator(I)); 4996 } 4997 auto BundleWidth = VectorizableTree[0]->Scalars.size(); 4998 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 4999 auto *VecTy = FixedVectorType::get(MinTy, BundleWidth); 5000 auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy); 5001 VectorizableTree[0]->VectorizedValue = Trunc; 5002 } 5003 5004 LLVM_DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size() 5005 << " values .\n"); 5006 5007 // If necessary, sign-extend or zero-extend ScalarRoot to the larger type 5008 // specified by ScalarType. 5009 auto extend = [&](Value *ScalarRoot, Value *Ex, Type *ScalarType) { 5010 if (!MinBWs.count(ScalarRoot)) 5011 return Ex; 5012 if (MinBWs[ScalarRoot].second) 5013 return Builder.CreateSExt(Ex, ScalarType); 5014 return Builder.CreateZExt(Ex, ScalarType); 5015 }; 5016 5017 // Extract all of the elements with the external uses. 5018 for (const auto &ExternalUse : ExternalUses) { 5019 Value *Scalar = ExternalUse.Scalar; 5020 llvm::User *User = ExternalUse.User; 5021 5022 // Skip users that we already RAUW. This happens when one instruction 5023 // has multiple uses of the same value. 5024 if (User && !is_contained(Scalar->users(), User)) 5025 continue; 5026 TreeEntry *E = getTreeEntry(Scalar); 5027 assert(E && "Invalid scalar"); 5028 assert(E->State != TreeEntry::NeedToGather && 5029 "Extracting from a gather list"); 5030 5031 Value *Vec = E->VectorizedValue; 5032 assert(Vec && "Can't find vectorizable value"); 5033 5034 Value *Lane = Builder.getInt32(ExternalUse.Lane); 5035 // If User == nullptr, the Scalar is used as extra arg. Generate 5036 // ExtractElement instruction and update the record for this scalar in 5037 // ExternallyUsedValues. 5038 if (!User) { 5039 assert(ExternallyUsedValues.count(Scalar) && 5040 "Scalar with nullptr as an external user must be registered in " 5041 "ExternallyUsedValues map"); 5042 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 5043 Builder.SetInsertPoint(VecI->getParent(), 5044 std::next(VecI->getIterator())); 5045 } else { 5046 Builder.SetInsertPoint(&F->getEntryBlock().front()); 5047 } 5048 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 5049 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 5050 CSEBlocks.insert(cast<Instruction>(Scalar)->getParent()); 5051 auto &Locs = ExternallyUsedValues[Scalar]; 5052 ExternallyUsedValues.insert({Ex, Locs}); 5053 ExternallyUsedValues.erase(Scalar); 5054 // Required to update internally referenced instructions. 5055 Scalar->replaceAllUsesWith(Ex); 5056 continue; 5057 } 5058 5059 // Generate extracts for out-of-tree users. 5060 // Find the insertion point for the extractelement lane. 5061 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 5062 if (PHINode *PH = dyn_cast<PHINode>(User)) { 5063 for (int i = 0, e = PH->getNumIncomingValues(); i != e; ++i) { 5064 if (PH->getIncomingValue(i) == Scalar) { 5065 Instruction *IncomingTerminator = 5066 PH->getIncomingBlock(i)->getTerminator(); 5067 if (isa<CatchSwitchInst>(IncomingTerminator)) { 5068 Builder.SetInsertPoint(VecI->getParent(), 5069 std::next(VecI->getIterator())); 5070 } else { 5071 Builder.SetInsertPoint(PH->getIncomingBlock(i)->getTerminator()); 5072 } 5073 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 5074 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 5075 CSEBlocks.insert(PH->getIncomingBlock(i)); 5076 PH->setOperand(i, Ex); 5077 } 5078 } 5079 } else { 5080 Builder.SetInsertPoint(cast<Instruction>(User)); 5081 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 5082 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 5083 CSEBlocks.insert(cast<Instruction>(User)->getParent()); 5084 User->replaceUsesOfWith(Scalar, Ex); 5085 } 5086 } else { 5087 Builder.SetInsertPoint(&F->getEntryBlock().front()); 5088 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 5089 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 5090 CSEBlocks.insert(&F->getEntryBlock()); 5091 User->replaceUsesOfWith(Scalar, Ex); 5092 } 5093 5094 LLVM_DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n"); 5095 } 5096 5097 // For each vectorized value: 5098 for (auto &TEPtr : VectorizableTree) { 5099 TreeEntry *Entry = TEPtr.get(); 5100 5101 // No need to handle users of gathered values. 5102 if (Entry->State == TreeEntry::NeedToGather) 5103 continue; 5104 5105 assert(Entry->VectorizedValue && "Can't find vectorizable value"); 5106 5107 // For each lane: 5108 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 5109 Value *Scalar = Entry->Scalars[Lane]; 5110 5111 #ifndef NDEBUG 5112 Type *Ty = Scalar->getType(); 5113 if (!Ty->isVoidTy()) { 5114 for (User *U : Scalar->users()) { 5115 LLVM_DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n"); 5116 5117 // It is legal to delete users in the ignorelist. 5118 assert((getTreeEntry(U) || is_contained(UserIgnoreList, U)) && 5119 "Deleting out-of-tree value"); 5120 } 5121 } 5122 #endif 5123 LLVM_DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n"); 5124 eraseInstruction(cast<Instruction>(Scalar)); 5125 } 5126 } 5127 5128 Builder.ClearInsertionPoint(); 5129 InstrElementSize.clear(); 5130 5131 return VectorizableTree[0]->VectorizedValue; 5132 } 5133 5134 void BoUpSLP::optimizeGatherSequence() { 5135 LLVM_DEBUG(dbgs() << "SLP: Optimizing " << GatherSeq.size() 5136 << " gather sequences instructions.\n"); 5137 // LICM InsertElementInst sequences. 5138 for (Instruction *I : GatherSeq) { 5139 if (isDeleted(I)) 5140 continue; 5141 5142 // Check if this block is inside a loop. 5143 Loop *L = LI->getLoopFor(I->getParent()); 5144 if (!L) 5145 continue; 5146 5147 // Check if it has a preheader. 5148 BasicBlock *PreHeader = L->getLoopPreheader(); 5149 if (!PreHeader) 5150 continue; 5151 5152 // If the vector or the element that we insert into it are 5153 // instructions that are defined in this basic block then we can't 5154 // hoist this instruction. 5155 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 5156 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 5157 if (Op0 && L->contains(Op0)) 5158 continue; 5159 if (Op1 && L->contains(Op1)) 5160 continue; 5161 5162 // We can hoist this instruction. Move it to the pre-header. 5163 I->moveBefore(PreHeader->getTerminator()); 5164 } 5165 5166 // Make a list of all reachable blocks in our CSE queue. 5167 SmallVector<const DomTreeNode *, 8> CSEWorkList; 5168 CSEWorkList.reserve(CSEBlocks.size()); 5169 for (BasicBlock *BB : CSEBlocks) 5170 if (DomTreeNode *N = DT->getNode(BB)) { 5171 assert(DT->isReachableFromEntry(N)); 5172 CSEWorkList.push_back(N); 5173 } 5174 5175 // Sort blocks by domination. This ensures we visit a block after all blocks 5176 // dominating it are visited. 5177 llvm::stable_sort(CSEWorkList, 5178 [this](const DomTreeNode *A, const DomTreeNode *B) { 5179 return DT->properlyDominates(A, B); 5180 }); 5181 5182 // Perform O(N^2) search over the gather sequences and merge identical 5183 // instructions. TODO: We can further optimize this scan if we split the 5184 // instructions into different buckets based on the insert lane. 5185 SmallVector<Instruction *, 16> Visited; 5186 for (auto I = CSEWorkList.begin(), E = CSEWorkList.end(); I != E; ++I) { 5187 assert(*I && 5188 (I == CSEWorkList.begin() || !DT->dominates(*I, *std::prev(I))) && 5189 "Worklist not sorted properly!"); 5190 BasicBlock *BB = (*I)->getBlock(); 5191 // For all instructions in blocks containing gather sequences: 5192 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e;) { 5193 Instruction *In = &*it++; 5194 if (isDeleted(In)) 5195 continue; 5196 if (!isa<InsertElementInst>(In) && !isa<ExtractElementInst>(In)) 5197 continue; 5198 5199 // Check if we can replace this instruction with any of the 5200 // visited instructions. 5201 for (Instruction *v : Visited) { 5202 if (In->isIdenticalTo(v) && 5203 DT->dominates(v->getParent(), In->getParent())) { 5204 In->replaceAllUsesWith(v); 5205 eraseInstruction(In); 5206 In = nullptr; 5207 break; 5208 } 5209 } 5210 if (In) { 5211 assert(!is_contained(Visited, In)); 5212 Visited.push_back(In); 5213 } 5214 } 5215 } 5216 CSEBlocks.clear(); 5217 GatherSeq.clear(); 5218 } 5219 5220 // Groups the instructions to a bundle (which is then a single scheduling entity) 5221 // and schedules instructions until the bundle gets ready. 5222 Optional<BoUpSLP::ScheduleData *> 5223 BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 5224 const InstructionsState &S) { 5225 if (isa<PHINode>(S.OpValue)) 5226 return nullptr; 5227 5228 // Initialize the instruction bundle. 5229 Instruction *OldScheduleEnd = ScheduleEnd; 5230 ScheduleData *PrevInBundle = nullptr; 5231 ScheduleData *Bundle = nullptr; 5232 bool ReSchedule = false; 5233 LLVM_DEBUG(dbgs() << "SLP: bundle: " << *S.OpValue << "\n"); 5234 5235 auto &&TryScheduleBundle = [this, OldScheduleEnd, SLP](bool ReSchedule, 5236 ScheduleData *Bundle) { 5237 // The scheduling region got new instructions at the lower end (or it is a 5238 // new region for the first bundle). This makes it necessary to 5239 // recalculate all dependencies. 5240 // It is seldom that this needs to be done a second time after adding the 5241 // initial bundle to the region. 5242 if (ScheduleEnd != OldScheduleEnd) { 5243 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) 5244 doForAllOpcodes(I, [](ScheduleData *SD) { SD->clearDependencies(); }); 5245 ReSchedule = true; 5246 } 5247 if (ReSchedule) { 5248 resetSchedule(); 5249 initialFillReadyList(ReadyInsts); 5250 } 5251 if (Bundle) { 5252 LLVM_DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle 5253 << " in block " << BB->getName() << "\n"); 5254 calculateDependencies(Bundle, /*InsertInReadyList=*/true, SLP); 5255 } 5256 5257 // Now try to schedule the new bundle or (if no bundle) just calculate 5258 // dependencies. As soon as the bundle is "ready" it means that there are no 5259 // cyclic dependencies and we can schedule it. Note that's important that we 5260 // don't "schedule" the bundle yet (see cancelScheduling). 5261 while (((!Bundle && ReSchedule) || (Bundle && !Bundle->isReady())) && 5262 !ReadyInsts.empty()) { 5263 ScheduleData *Picked = ReadyInsts.pop_back_val(); 5264 if (Picked->isSchedulingEntity() && Picked->isReady()) 5265 schedule(Picked, ReadyInsts); 5266 } 5267 }; 5268 5269 // Make sure that the scheduling region contains all 5270 // instructions of the bundle. 5271 for (Value *V : VL) { 5272 if (!extendSchedulingRegion(V, S)) { 5273 // If the scheduling region got new instructions at the lower end (or it 5274 // is a new region for the first bundle). This makes it necessary to 5275 // recalculate all dependencies. 5276 // Otherwise the compiler may crash trying to incorrectly calculate 5277 // dependencies and emit instruction in the wrong order at the actual 5278 // scheduling. 5279 TryScheduleBundle(/*ReSchedule=*/false, nullptr); 5280 return None; 5281 } 5282 } 5283 5284 for (Value *V : VL) { 5285 ScheduleData *BundleMember = getScheduleData(V); 5286 assert(BundleMember && 5287 "no ScheduleData for bundle member (maybe not in same basic block)"); 5288 if (BundleMember->IsScheduled) { 5289 // A bundle member was scheduled as single instruction before and now 5290 // needs to be scheduled as part of the bundle. We just get rid of the 5291 // existing schedule. 5292 LLVM_DEBUG(dbgs() << "SLP: reset schedule because " << *BundleMember 5293 << " was already scheduled\n"); 5294 ReSchedule = true; 5295 } 5296 assert(BundleMember->isSchedulingEntity() && 5297 "bundle member already part of other bundle"); 5298 if (PrevInBundle) { 5299 PrevInBundle->NextInBundle = BundleMember; 5300 } else { 5301 Bundle = BundleMember; 5302 } 5303 BundleMember->UnscheduledDepsInBundle = 0; 5304 Bundle->UnscheduledDepsInBundle += BundleMember->UnscheduledDeps; 5305 5306 // Group the instructions to a bundle. 5307 BundleMember->FirstInBundle = Bundle; 5308 PrevInBundle = BundleMember; 5309 } 5310 assert(Bundle && "Failed to find schedule bundle"); 5311 TryScheduleBundle(ReSchedule, Bundle); 5312 if (!Bundle->isReady()) { 5313 cancelScheduling(VL, S.OpValue); 5314 return None; 5315 } 5316 return Bundle; 5317 } 5318 5319 void BoUpSLP::BlockScheduling::cancelScheduling(ArrayRef<Value *> VL, 5320 Value *OpValue) { 5321 if (isa<PHINode>(OpValue)) 5322 return; 5323 5324 ScheduleData *Bundle = getScheduleData(OpValue); 5325 LLVM_DEBUG(dbgs() << "SLP: cancel scheduling of " << *Bundle << "\n"); 5326 assert(!Bundle->IsScheduled && 5327 "Can't cancel bundle which is already scheduled"); 5328 assert(Bundle->isSchedulingEntity() && Bundle->isPartOfBundle() && 5329 "tried to unbundle something which is not a bundle"); 5330 5331 // Un-bundle: make single instructions out of the bundle. 5332 ScheduleData *BundleMember = Bundle; 5333 while (BundleMember) { 5334 assert(BundleMember->FirstInBundle == Bundle && "corrupt bundle links"); 5335 BundleMember->FirstInBundle = BundleMember; 5336 ScheduleData *Next = BundleMember->NextInBundle; 5337 BundleMember->NextInBundle = nullptr; 5338 BundleMember->UnscheduledDepsInBundle = BundleMember->UnscheduledDeps; 5339 if (BundleMember->UnscheduledDepsInBundle == 0) { 5340 ReadyInsts.insert(BundleMember); 5341 } 5342 BundleMember = Next; 5343 } 5344 } 5345 5346 BoUpSLP::ScheduleData *BoUpSLP::BlockScheduling::allocateScheduleDataChunks() { 5347 // Allocate a new ScheduleData for the instruction. 5348 if (ChunkPos >= ChunkSize) { 5349 ScheduleDataChunks.push_back(std::make_unique<ScheduleData[]>(ChunkSize)); 5350 ChunkPos = 0; 5351 } 5352 return &(ScheduleDataChunks.back()[ChunkPos++]); 5353 } 5354 5355 bool BoUpSLP::BlockScheduling::extendSchedulingRegion(Value *V, 5356 const InstructionsState &S) { 5357 if (getScheduleData(V, isOneOf(S, V))) 5358 return true; 5359 Instruction *I = dyn_cast<Instruction>(V); 5360 assert(I && "bundle member must be an instruction"); 5361 assert(!isa<PHINode>(I) && "phi nodes don't need to be scheduled"); 5362 auto &&CheckSheduleForI = [this, &S](Instruction *I) -> bool { 5363 ScheduleData *ISD = getScheduleData(I); 5364 if (!ISD) 5365 return false; 5366 assert(isInSchedulingRegion(ISD) && 5367 "ScheduleData not in scheduling region"); 5368 ScheduleData *SD = allocateScheduleDataChunks(); 5369 SD->Inst = I; 5370 SD->init(SchedulingRegionID, S.OpValue); 5371 ExtraScheduleDataMap[I][S.OpValue] = SD; 5372 return true; 5373 }; 5374 if (CheckSheduleForI(I)) 5375 return true; 5376 if (!ScheduleStart) { 5377 // It's the first instruction in the new region. 5378 initScheduleData(I, I->getNextNode(), nullptr, nullptr); 5379 ScheduleStart = I; 5380 ScheduleEnd = I->getNextNode(); 5381 if (isOneOf(S, I) != I) 5382 CheckSheduleForI(I); 5383 assert(ScheduleEnd && "tried to vectorize a terminator?"); 5384 LLVM_DEBUG(dbgs() << "SLP: initialize schedule region to " << *I << "\n"); 5385 return true; 5386 } 5387 // Search up and down at the same time, because we don't know if the new 5388 // instruction is above or below the existing scheduling region. 5389 BasicBlock::reverse_iterator UpIter = 5390 ++ScheduleStart->getIterator().getReverse(); 5391 BasicBlock::reverse_iterator UpperEnd = BB->rend(); 5392 BasicBlock::iterator DownIter = ScheduleEnd->getIterator(); 5393 BasicBlock::iterator LowerEnd = BB->end(); 5394 while (UpIter != UpperEnd && DownIter != LowerEnd && &*UpIter != I && 5395 &*DownIter != I) { 5396 if (++ScheduleRegionSize > ScheduleRegionSizeLimit) { 5397 LLVM_DEBUG(dbgs() << "SLP: exceeded schedule region size limit\n"); 5398 return false; 5399 } 5400 5401 ++UpIter; 5402 ++DownIter; 5403 } 5404 if (DownIter == LowerEnd || (UpIter != UpperEnd && &*UpIter == I)) { 5405 assert(I->getParent() == ScheduleStart->getParent() && 5406 "Instruction is in wrong basic block."); 5407 initScheduleData(I, ScheduleStart, nullptr, FirstLoadStoreInRegion); 5408 ScheduleStart = I; 5409 if (isOneOf(S, I) != I) 5410 CheckSheduleForI(I); 5411 LLVM_DEBUG(dbgs() << "SLP: extend schedule region start to " << *I 5412 << "\n"); 5413 return true; 5414 } 5415 assert((UpIter == UpperEnd || (DownIter != LowerEnd && &*DownIter == I)) && 5416 "Expected to reach top of the basic block or instruction down the " 5417 "lower end."); 5418 assert(I->getParent() == ScheduleEnd->getParent() && 5419 "Instruction is in wrong basic block."); 5420 initScheduleData(ScheduleEnd, I->getNextNode(), LastLoadStoreInRegion, 5421 nullptr); 5422 ScheduleEnd = I->getNextNode(); 5423 if (isOneOf(S, I) != I) 5424 CheckSheduleForI(I); 5425 assert(ScheduleEnd && "tried to vectorize a terminator?"); 5426 LLVM_DEBUG(dbgs() << "SLP: extend schedule region end to " << *I << "\n"); 5427 return true; 5428 } 5429 5430 void BoUpSLP::BlockScheduling::initScheduleData(Instruction *FromI, 5431 Instruction *ToI, 5432 ScheduleData *PrevLoadStore, 5433 ScheduleData *NextLoadStore) { 5434 ScheduleData *CurrentLoadStore = PrevLoadStore; 5435 for (Instruction *I = FromI; I != ToI; I = I->getNextNode()) { 5436 ScheduleData *SD = ScheduleDataMap[I]; 5437 if (!SD) { 5438 SD = allocateScheduleDataChunks(); 5439 ScheduleDataMap[I] = SD; 5440 SD->Inst = I; 5441 } 5442 assert(!isInSchedulingRegion(SD) && 5443 "new ScheduleData already in scheduling region"); 5444 SD->init(SchedulingRegionID, I); 5445 5446 if (I->mayReadOrWriteMemory() && 5447 (!isa<IntrinsicInst>(I) || 5448 (cast<IntrinsicInst>(I)->getIntrinsicID() != Intrinsic::sideeffect && 5449 cast<IntrinsicInst>(I)->getIntrinsicID() != 5450 Intrinsic::pseudoprobe))) { 5451 // Update the linked list of memory accessing instructions. 5452 if (CurrentLoadStore) { 5453 CurrentLoadStore->NextLoadStore = SD; 5454 } else { 5455 FirstLoadStoreInRegion = SD; 5456 } 5457 CurrentLoadStore = SD; 5458 } 5459 } 5460 if (NextLoadStore) { 5461 if (CurrentLoadStore) 5462 CurrentLoadStore->NextLoadStore = NextLoadStore; 5463 } else { 5464 LastLoadStoreInRegion = CurrentLoadStore; 5465 } 5466 } 5467 5468 void BoUpSLP::BlockScheduling::calculateDependencies(ScheduleData *SD, 5469 bool InsertInReadyList, 5470 BoUpSLP *SLP) { 5471 assert(SD->isSchedulingEntity()); 5472 5473 SmallVector<ScheduleData *, 10> WorkList; 5474 WorkList.push_back(SD); 5475 5476 while (!WorkList.empty()) { 5477 ScheduleData *SD = WorkList.pop_back_val(); 5478 5479 ScheduleData *BundleMember = SD; 5480 while (BundleMember) { 5481 assert(isInSchedulingRegion(BundleMember)); 5482 if (!BundleMember->hasValidDependencies()) { 5483 5484 LLVM_DEBUG(dbgs() << "SLP: update deps of " << *BundleMember 5485 << "\n"); 5486 BundleMember->Dependencies = 0; 5487 BundleMember->resetUnscheduledDeps(); 5488 5489 // Handle def-use chain dependencies. 5490 if (BundleMember->OpValue != BundleMember->Inst) { 5491 ScheduleData *UseSD = getScheduleData(BundleMember->Inst); 5492 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 5493 BundleMember->Dependencies++; 5494 ScheduleData *DestBundle = UseSD->FirstInBundle; 5495 if (!DestBundle->IsScheduled) 5496 BundleMember->incrementUnscheduledDeps(1); 5497 if (!DestBundle->hasValidDependencies()) 5498 WorkList.push_back(DestBundle); 5499 } 5500 } else { 5501 for (User *U : BundleMember->Inst->users()) { 5502 if (isa<Instruction>(U)) { 5503 ScheduleData *UseSD = getScheduleData(U); 5504 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 5505 BundleMember->Dependencies++; 5506 ScheduleData *DestBundle = UseSD->FirstInBundle; 5507 if (!DestBundle->IsScheduled) 5508 BundleMember->incrementUnscheduledDeps(1); 5509 if (!DestBundle->hasValidDependencies()) 5510 WorkList.push_back(DestBundle); 5511 } 5512 } else { 5513 // I'm not sure if this can ever happen. But we need to be safe. 5514 // This lets the instruction/bundle never be scheduled and 5515 // eventually disable vectorization. 5516 BundleMember->Dependencies++; 5517 BundleMember->incrementUnscheduledDeps(1); 5518 } 5519 } 5520 } 5521 5522 // Handle the memory dependencies. 5523 ScheduleData *DepDest = BundleMember->NextLoadStore; 5524 if (DepDest) { 5525 Instruction *SrcInst = BundleMember->Inst; 5526 MemoryLocation SrcLoc = getLocation(SrcInst, SLP->AA); 5527 bool SrcMayWrite = BundleMember->Inst->mayWriteToMemory(); 5528 unsigned numAliased = 0; 5529 unsigned DistToSrc = 1; 5530 5531 while (DepDest) { 5532 assert(isInSchedulingRegion(DepDest)); 5533 5534 // We have two limits to reduce the complexity: 5535 // 1) AliasedCheckLimit: It's a small limit to reduce calls to 5536 // SLP->isAliased (which is the expensive part in this loop). 5537 // 2) MaxMemDepDistance: It's for very large blocks and it aborts 5538 // the whole loop (even if the loop is fast, it's quadratic). 5539 // It's important for the loop break condition (see below) to 5540 // check this limit even between two read-only instructions. 5541 if (DistToSrc >= MaxMemDepDistance || 5542 ((SrcMayWrite || DepDest->Inst->mayWriteToMemory()) && 5543 (numAliased >= AliasedCheckLimit || 5544 SLP->isAliased(SrcLoc, SrcInst, DepDest->Inst)))) { 5545 5546 // We increment the counter only if the locations are aliased 5547 // (instead of counting all alias checks). This gives a better 5548 // balance between reduced runtime and accurate dependencies. 5549 numAliased++; 5550 5551 DepDest->MemoryDependencies.push_back(BundleMember); 5552 BundleMember->Dependencies++; 5553 ScheduleData *DestBundle = DepDest->FirstInBundle; 5554 if (!DestBundle->IsScheduled) { 5555 BundleMember->incrementUnscheduledDeps(1); 5556 } 5557 if (!DestBundle->hasValidDependencies()) { 5558 WorkList.push_back(DestBundle); 5559 } 5560 } 5561 DepDest = DepDest->NextLoadStore; 5562 5563 // Example, explaining the loop break condition: Let's assume our 5564 // starting instruction is i0 and MaxMemDepDistance = 3. 5565 // 5566 // +--------v--v--v 5567 // i0,i1,i2,i3,i4,i5,i6,i7,i8 5568 // +--------^--^--^ 5569 // 5570 // MaxMemDepDistance let us stop alias-checking at i3 and we add 5571 // dependencies from i0 to i3,i4,.. (even if they are not aliased). 5572 // Previously we already added dependencies from i3 to i6,i7,i8 5573 // (because of MaxMemDepDistance). As we added a dependency from 5574 // i0 to i3, we have transitive dependencies from i0 to i6,i7,i8 5575 // and we can abort this loop at i6. 5576 if (DistToSrc >= 2 * MaxMemDepDistance) 5577 break; 5578 DistToSrc++; 5579 } 5580 } 5581 } 5582 BundleMember = BundleMember->NextInBundle; 5583 } 5584 if (InsertInReadyList && SD->isReady()) { 5585 ReadyInsts.push_back(SD); 5586 LLVM_DEBUG(dbgs() << "SLP: gets ready on update: " << *SD->Inst 5587 << "\n"); 5588 } 5589 } 5590 } 5591 5592 void BoUpSLP::BlockScheduling::resetSchedule() { 5593 assert(ScheduleStart && 5594 "tried to reset schedule on block which has not been scheduled"); 5595 for (Instruction *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 5596 doForAllOpcodes(I, [&](ScheduleData *SD) { 5597 assert(isInSchedulingRegion(SD) && 5598 "ScheduleData not in scheduling region"); 5599 SD->IsScheduled = false; 5600 SD->resetUnscheduledDeps(); 5601 }); 5602 } 5603 ReadyInsts.clear(); 5604 } 5605 5606 void BoUpSLP::scheduleBlock(BlockScheduling *BS) { 5607 if (!BS->ScheduleStart) 5608 return; 5609 5610 LLVM_DEBUG(dbgs() << "SLP: schedule block " << BS->BB->getName() << "\n"); 5611 5612 BS->resetSchedule(); 5613 5614 // For the real scheduling we use a more sophisticated ready-list: it is 5615 // sorted by the original instruction location. This lets the final schedule 5616 // be as close as possible to the original instruction order. 5617 struct ScheduleDataCompare { 5618 bool operator()(ScheduleData *SD1, ScheduleData *SD2) const { 5619 return SD2->SchedulingPriority < SD1->SchedulingPriority; 5620 } 5621 }; 5622 std::set<ScheduleData *, ScheduleDataCompare> ReadyInsts; 5623 5624 // Ensure that all dependency data is updated and fill the ready-list with 5625 // initial instructions. 5626 int Idx = 0; 5627 int NumToSchedule = 0; 5628 for (auto *I = BS->ScheduleStart; I != BS->ScheduleEnd; 5629 I = I->getNextNode()) { 5630 BS->doForAllOpcodes(I, [this, &Idx, &NumToSchedule, BS](ScheduleData *SD) { 5631 assert(SD->isPartOfBundle() == 5632 (getTreeEntry(SD->Inst) != nullptr) && 5633 "scheduler and vectorizer bundle mismatch"); 5634 SD->FirstInBundle->SchedulingPriority = Idx++; 5635 if (SD->isSchedulingEntity()) { 5636 BS->calculateDependencies(SD, false, this); 5637 NumToSchedule++; 5638 } 5639 }); 5640 } 5641 BS->initialFillReadyList(ReadyInsts); 5642 5643 Instruction *LastScheduledInst = BS->ScheduleEnd; 5644 5645 // Do the "real" scheduling. 5646 while (!ReadyInsts.empty()) { 5647 ScheduleData *picked = *ReadyInsts.begin(); 5648 ReadyInsts.erase(ReadyInsts.begin()); 5649 5650 // Move the scheduled instruction(s) to their dedicated places, if not 5651 // there yet. 5652 ScheduleData *BundleMember = picked; 5653 while (BundleMember) { 5654 Instruction *pickedInst = BundleMember->Inst; 5655 if (LastScheduledInst->getNextNode() != pickedInst) { 5656 BS->BB->getInstList().remove(pickedInst); 5657 BS->BB->getInstList().insert(LastScheduledInst->getIterator(), 5658 pickedInst); 5659 } 5660 LastScheduledInst = pickedInst; 5661 BundleMember = BundleMember->NextInBundle; 5662 } 5663 5664 BS->schedule(picked, ReadyInsts); 5665 NumToSchedule--; 5666 } 5667 assert(NumToSchedule == 0 && "could not schedule all instructions"); 5668 5669 // Avoid duplicate scheduling of the block. 5670 BS->ScheduleStart = nullptr; 5671 } 5672 5673 unsigned BoUpSLP::getVectorElementSize(Value *V) { 5674 // If V is a store, just return the width of the stored value (or value 5675 // truncated just before storing) without traversing the expression tree. 5676 // This is the common case. 5677 if (auto *Store = dyn_cast<StoreInst>(V)) { 5678 if (auto *Trunc = dyn_cast<TruncInst>(Store->getValueOperand())) 5679 return DL->getTypeSizeInBits(Trunc->getSrcTy()); 5680 return DL->getTypeSizeInBits(Store->getValueOperand()->getType()); 5681 } 5682 5683 auto E = InstrElementSize.find(V); 5684 if (E != InstrElementSize.end()) 5685 return E->second; 5686 5687 // If V is not a store, we can traverse the expression tree to find loads 5688 // that feed it. The type of the loaded value may indicate a more suitable 5689 // width than V's type. We want to base the vector element size on the width 5690 // of memory operations where possible. 5691 SmallVector<std::pair<Instruction *, BasicBlock *>, 16> Worklist; 5692 SmallPtrSet<Instruction *, 16> Visited; 5693 if (auto *I = dyn_cast<Instruction>(V)) { 5694 Worklist.emplace_back(I, I->getParent()); 5695 Visited.insert(I); 5696 } 5697 5698 // Traverse the expression tree in bottom-up order looking for loads. If we 5699 // encounter an instruction we don't yet handle, we give up. 5700 auto Width = 0u; 5701 while (!Worklist.empty()) { 5702 Instruction *I; 5703 BasicBlock *Parent; 5704 std::tie(I, Parent) = Worklist.pop_back_val(); 5705 5706 // We should only be looking at scalar instructions here. If the current 5707 // instruction has a vector type, skip. 5708 auto *Ty = I->getType(); 5709 if (isa<VectorType>(Ty)) 5710 continue; 5711 5712 // If the current instruction is a load, update MaxWidth to reflect the 5713 // width of the loaded value. 5714 if (isa<LoadInst>(I) || isa<ExtractElementInst>(I) || 5715 isa<ExtractValueInst>(I)) 5716 Width = std::max<unsigned>(Width, DL->getTypeSizeInBits(Ty)); 5717 5718 // Otherwise, we need to visit the operands of the instruction. We only 5719 // handle the interesting cases from buildTree here. If an operand is an 5720 // instruction we haven't yet visited and from the same basic block as the 5721 // user or the use is a PHI node, we add it to the worklist. 5722 else if (isa<PHINode>(I) || isa<CastInst>(I) || isa<GetElementPtrInst>(I) || 5723 isa<CmpInst>(I) || isa<SelectInst>(I) || isa<BinaryOperator>(I) || 5724 isa<UnaryOperator>(I)) { 5725 for (Use &U : I->operands()) 5726 if (auto *J = dyn_cast<Instruction>(U.get())) 5727 if (Visited.insert(J).second && 5728 (isa<PHINode>(I) || J->getParent() == Parent)) 5729 Worklist.emplace_back(J, J->getParent()); 5730 } else { 5731 break; 5732 } 5733 } 5734 5735 // If we didn't encounter a memory access in the expression tree, or if we 5736 // gave up for some reason, just return the width of V. Otherwise, return the 5737 // maximum width we found. 5738 if (!Width) { 5739 if (auto *CI = dyn_cast<CmpInst>(V)) 5740 V = CI->getOperand(0); 5741 Width = DL->getTypeSizeInBits(V->getType()); 5742 } 5743 5744 for (Instruction *I : Visited) 5745 InstrElementSize[I] = Width; 5746 5747 return Width; 5748 } 5749 5750 // Determine if a value V in a vectorizable expression Expr can be demoted to a 5751 // smaller type with a truncation. We collect the values that will be demoted 5752 // in ToDemote and additional roots that require investigating in Roots. 5753 static bool collectValuesToDemote(Value *V, SmallPtrSetImpl<Value *> &Expr, 5754 SmallVectorImpl<Value *> &ToDemote, 5755 SmallVectorImpl<Value *> &Roots) { 5756 // We can always demote constants. 5757 if (isa<Constant>(V)) { 5758 ToDemote.push_back(V); 5759 return true; 5760 } 5761 5762 // If the value is not an instruction in the expression with only one use, it 5763 // cannot be demoted. 5764 auto *I = dyn_cast<Instruction>(V); 5765 if (!I || !I->hasOneUse() || !Expr.count(I)) 5766 return false; 5767 5768 switch (I->getOpcode()) { 5769 5770 // We can always demote truncations and extensions. Since truncations can 5771 // seed additional demotion, we save the truncated value. 5772 case Instruction::Trunc: 5773 Roots.push_back(I->getOperand(0)); 5774 break; 5775 case Instruction::ZExt: 5776 case Instruction::SExt: 5777 break; 5778 5779 // We can demote certain binary operations if we can demote both of their 5780 // operands. 5781 case Instruction::Add: 5782 case Instruction::Sub: 5783 case Instruction::Mul: 5784 case Instruction::And: 5785 case Instruction::Or: 5786 case Instruction::Xor: 5787 if (!collectValuesToDemote(I->getOperand(0), Expr, ToDemote, Roots) || 5788 !collectValuesToDemote(I->getOperand(1), Expr, ToDemote, Roots)) 5789 return false; 5790 break; 5791 5792 // We can demote selects if we can demote their true and false values. 5793 case Instruction::Select: { 5794 SelectInst *SI = cast<SelectInst>(I); 5795 if (!collectValuesToDemote(SI->getTrueValue(), Expr, ToDemote, Roots) || 5796 !collectValuesToDemote(SI->getFalseValue(), Expr, ToDemote, Roots)) 5797 return false; 5798 break; 5799 } 5800 5801 // We can demote phis if we can demote all their incoming operands. Note that 5802 // we don't need to worry about cycles since we ensure single use above. 5803 case Instruction::PHI: { 5804 PHINode *PN = cast<PHINode>(I); 5805 for (Value *IncValue : PN->incoming_values()) 5806 if (!collectValuesToDemote(IncValue, Expr, ToDemote, Roots)) 5807 return false; 5808 break; 5809 } 5810 5811 // Otherwise, conservatively give up. 5812 default: 5813 return false; 5814 } 5815 5816 // Record the value that we can demote. 5817 ToDemote.push_back(V); 5818 return true; 5819 } 5820 5821 void BoUpSLP::computeMinimumValueSizes() { 5822 // If there are no external uses, the expression tree must be rooted by a 5823 // store. We can't demote in-memory values, so there is nothing to do here. 5824 if (ExternalUses.empty()) 5825 return; 5826 5827 // We only attempt to truncate integer expressions. 5828 auto &TreeRoot = VectorizableTree[0]->Scalars; 5829 auto *TreeRootIT = dyn_cast<IntegerType>(TreeRoot[0]->getType()); 5830 if (!TreeRootIT) 5831 return; 5832 5833 // If the expression is not rooted by a store, these roots should have 5834 // external uses. We will rely on InstCombine to rewrite the expression in 5835 // the narrower type. However, InstCombine only rewrites single-use values. 5836 // This means that if a tree entry other than a root is used externally, it 5837 // must have multiple uses and InstCombine will not rewrite it. The code 5838 // below ensures that only the roots are used externally. 5839 SmallPtrSet<Value *, 32> Expr(TreeRoot.begin(), TreeRoot.end()); 5840 for (auto &EU : ExternalUses) 5841 if (!Expr.erase(EU.Scalar)) 5842 return; 5843 if (!Expr.empty()) 5844 return; 5845 5846 // Collect the scalar values of the vectorizable expression. We will use this 5847 // context to determine which values can be demoted. If we see a truncation, 5848 // we mark it as seeding another demotion. 5849 for (auto &EntryPtr : VectorizableTree) 5850 Expr.insert(EntryPtr->Scalars.begin(), EntryPtr->Scalars.end()); 5851 5852 // Ensure the roots of the vectorizable tree don't form a cycle. They must 5853 // have a single external user that is not in the vectorizable tree. 5854 for (auto *Root : TreeRoot) 5855 if (!Root->hasOneUse() || Expr.count(*Root->user_begin())) 5856 return; 5857 5858 // Conservatively determine if we can actually truncate the roots of the 5859 // expression. Collect the values that can be demoted in ToDemote and 5860 // additional roots that require investigating in Roots. 5861 SmallVector<Value *, 32> ToDemote; 5862 SmallVector<Value *, 4> Roots; 5863 for (auto *Root : TreeRoot) 5864 if (!collectValuesToDemote(Root, Expr, ToDemote, Roots)) 5865 return; 5866 5867 // The maximum bit width required to represent all the values that can be 5868 // demoted without loss of precision. It would be safe to truncate the roots 5869 // of the expression to this width. 5870 auto MaxBitWidth = 8u; 5871 5872 // We first check if all the bits of the roots are demanded. If they're not, 5873 // we can truncate the roots to this narrower type. 5874 for (auto *Root : TreeRoot) { 5875 auto Mask = DB->getDemandedBits(cast<Instruction>(Root)); 5876 MaxBitWidth = std::max<unsigned>( 5877 Mask.getBitWidth() - Mask.countLeadingZeros(), MaxBitWidth); 5878 } 5879 5880 // True if the roots can be zero-extended back to their original type, rather 5881 // than sign-extended. We know that if the leading bits are not demanded, we 5882 // can safely zero-extend. So we initialize IsKnownPositive to True. 5883 bool IsKnownPositive = true; 5884 5885 // If all the bits of the roots are demanded, we can try a little harder to 5886 // compute a narrower type. This can happen, for example, if the roots are 5887 // getelementptr indices. InstCombine promotes these indices to the pointer 5888 // width. Thus, all their bits are technically demanded even though the 5889 // address computation might be vectorized in a smaller type. 5890 // 5891 // We start by looking at each entry that can be demoted. We compute the 5892 // maximum bit width required to store the scalar by using ValueTracking to 5893 // compute the number of high-order bits we can truncate. 5894 if (MaxBitWidth == DL->getTypeSizeInBits(TreeRoot[0]->getType()) && 5895 llvm::all_of(TreeRoot, [](Value *R) { 5896 assert(R->hasOneUse() && "Root should have only one use!"); 5897 return isa<GetElementPtrInst>(R->user_back()); 5898 })) { 5899 MaxBitWidth = 8u; 5900 5901 // Determine if the sign bit of all the roots is known to be zero. If not, 5902 // IsKnownPositive is set to False. 5903 IsKnownPositive = llvm::all_of(TreeRoot, [&](Value *R) { 5904 KnownBits Known = computeKnownBits(R, *DL); 5905 return Known.isNonNegative(); 5906 }); 5907 5908 // Determine the maximum number of bits required to store the scalar 5909 // values. 5910 for (auto *Scalar : ToDemote) { 5911 auto NumSignBits = ComputeNumSignBits(Scalar, *DL, 0, AC, nullptr, DT); 5912 auto NumTypeBits = DL->getTypeSizeInBits(Scalar->getType()); 5913 MaxBitWidth = std::max<unsigned>(NumTypeBits - NumSignBits, MaxBitWidth); 5914 } 5915 5916 // If we can't prove that the sign bit is zero, we must add one to the 5917 // maximum bit width to account for the unknown sign bit. This preserves 5918 // the existing sign bit so we can safely sign-extend the root back to the 5919 // original type. Otherwise, if we know the sign bit is zero, we will 5920 // zero-extend the root instead. 5921 // 5922 // FIXME: This is somewhat suboptimal, as there will be cases where adding 5923 // one to the maximum bit width will yield a larger-than-necessary 5924 // type. In general, we need to add an extra bit only if we can't 5925 // prove that the upper bit of the original type is equal to the 5926 // upper bit of the proposed smaller type. If these two bits are the 5927 // same (either zero or one) we know that sign-extending from the 5928 // smaller type will result in the same value. Here, since we can't 5929 // yet prove this, we are just making the proposed smaller type 5930 // larger to ensure correctness. 5931 if (!IsKnownPositive) 5932 ++MaxBitWidth; 5933 } 5934 5935 // Round MaxBitWidth up to the next power-of-two. 5936 if (!isPowerOf2_64(MaxBitWidth)) 5937 MaxBitWidth = NextPowerOf2(MaxBitWidth); 5938 5939 // If the maximum bit width we compute is less than the with of the roots' 5940 // type, we can proceed with the narrowing. Otherwise, do nothing. 5941 if (MaxBitWidth >= TreeRootIT->getBitWidth()) 5942 return; 5943 5944 // If we can truncate the root, we must collect additional values that might 5945 // be demoted as a result. That is, those seeded by truncations we will 5946 // modify. 5947 while (!Roots.empty()) 5948 collectValuesToDemote(Roots.pop_back_val(), Expr, ToDemote, Roots); 5949 5950 // Finally, map the values we can demote to the maximum bit with we computed. 5951 for (auto *Scalar : ToDemote) 5952 MinBWs[Scalar] = std::make_pair(MaxBitWidth, !IsKnownPositive); 5953 } 5954 5955 namespace { 5956 5957 /// The SLPVectorizer Pass. 5958 struct SLPVectorizer : public FunctionPass { 5959 SLPVectorizerPass Impl; 5960 5961 /// Pass identification, replacement for typeid 5962 static char ID; 5963 5964 explicit SLPVectorizer() : FunctionPass(ID) { 5965 initializeSLPVectorizerPass(*PassRegistry::getPassRegistry()); 5966 } 5967 5968 bool doInitialization(Module &M) override { 5969 return false; 5970 } 5971 5972 bool runOnFunction(Function &F) override { 5973 if (skipFunction(F)) 5974 return false; 5975 5976 auto *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 5977 auto *TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F); 5978 auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>(); 5979 auto *TLI = TLIP ? &TLIP->getTLI(F) : nullptr; 5980 auto *AA = &getAnalysis<AAResultsWrapperPass>().getAAResults(); 5981 auto *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 5982 auto *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 5983 auto *AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F); 5984 auto *DB = &getAnalysis<DemandedBitsWrapperPass>().getDemandedBits(); 5985 auto *ORE = &getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE(); 5986 5987 return Impl.runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 5988 } 5989 5990 void getAnalysisUsage(AnalysisUsage &AU) const override { 5991 FunctionPass::getAnalysisUsage(AU); 5992 AU.addRequired<AssumptionCacheTracker>(); 5993 AU.addRequired<ScalarEvolutionWrapperPass>(); 5994 AU.addRequired<AAResultsWrapperPass>(); 5995 AU.addRequired<TargetTransformInfoWrapperPass>(); 5996 AU.addRequired<LoopInfoWrapperPass>(); 5997 AU.addRequired<DominatorTreeWrapperPass>(); 5998 AU.addRequired<DemandedBitsWrapperPass>(); 5999 AU.addRequired<OptimizationRemarkEmitterWrapperPass>(); 6000 AU.addRequired<InjectTLIMappingsLegacy>(); 6001 AU.addPreserved<LoopInfoWrapperPass>(); 6002 AU.addPreserved<DominatorTreeWrapperPass>(); 6003 AU.addPreserved<AAResultsWrapperPass>(); 6004 AU.addPreserved<GlobalsAAWrapperPass>(); 6005 AU.setPreservesCFG(); 6006 } 6007 }; 6008 6009 } // end anonymous namespace 6010 6011 PreservedAnalyses SLPVectorizerPass::run(Function &F, FunctionAnalysisManager &AM) { 6012 auto *SE = &AM.getResult<ScalarEvolutionAnalysis>(F); 6013 auto *TTI = &AM.getResult<TargetIRAnalysis>(F); 6014 auto *TLI = AM.getCachedResult<TargetLibraryAnalysis>(F); 6015 auto *AA = &AM.getResult<AAManager>(F); 6016 auto *LI = &AM.getResult<LoopAnalysis>(F); 6017 auto *DT = &AM.getResult<DominatorTreeAnalysis>(F); 6018 auto *AC = &AM.getResult<AssumptionAnalysis>(F); 6019 auto *DB = &AM.getResult<DemandedBitsAnalysis>(F); 6020 auto *ORE = &AM.getResult<OptimizationRemarkEmitterAnalysis>(F); 6021 6022 bool Changed = runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 6023 if (!Changed) 6024 return PreservedAnalyses::all(); 6025 6026 PreservedAnalyses PA; 6027 PA.preserveSet<CFGAnalyses>(); 6028 PA.preserve<AAManager>(); 6029 PA.preserve<GlobalsAA>(); 6030 return PA; 6031 } 6032 6033 bool SLPVectorizerPass::runImpl(Function &F, ScalarEvolution *SE_, 6034 TargetTransformInfo *TTI_, 6035 TargetLibraryInfo *TLI_, AAResults *AA_, 6036 LoopInfo *LI_, DominatorTree *DT_, 6037 AssumptionCache *AC_, DemandedBits *DB_, 6038 OptimizationRemarkEmitter *ORE_) { 6039 if (!RunSLPVectorization) 6040 return false; 6041 SE = SE_; 6042 TTI = TTI_; 6043 TLI = TLI_; 6044 AA = AA_; 6045 LI = LI_; 6046 DT = DT_; 6047 AC = AC_; 6048 DB = DB_; 6049 DL = &F.getParent()->getDataLayout(); 6050 6051 Stores.clear(); 6052 GEPs.clear(); 6053 bool Changed = false; 6054 6055 // If the target claims to have no vector registers don't attempt 6056 // vectorization. 6057 if (!TTI->getNumberOfRegisters(TTI->getRegisterClassForType(true))) 6058 return false; 6059 6060 // Don't vectorize when the attribute NoImplicitFloat is used. 6061 if (F.hasFnAttribute(Attribute::NoImplicitFloat)) 6062 return false; 6063 6064 LLVM_DEBUG(dbgs() << "SLP: Analyzing blocks in " << F.getName() << ".\n"); 6065 6066 // Use the bottom up slp vectorizer to construct chains that start with 6067 // store instructions. 6068 BoUpSLP R(&F, SE, TTI, TLI, AA, LI, DT, AC, DB, DL, ORE_); 6069 6070 // A general note: the vectorizer must use BoUpSLP::eraseInstruction() to 6071 // delete instructions. 6072 6073 // Scan the blocks in the function in post order. 6074 for (auto BB : post_order(&F.getEntryBlock())) { 6075 collectSeedInstructions(BB); 6076 6077 // Vectorize trees that end at stores. 6078 if (!Stores.empty()) { 6079 LLVM_DEBUG(dbgs() << "SLP: Found stores for " << Stores.size() 6080 << " underlying objects.\n"); 6081 Changed |= vectorizeStoreChains(R); 6082 } 6083 6084 // Vectorize trees that end at reductions. 6085 Changed |= vectorizeChainsInBlock(BB, R); 6086 6087 // Vectorize the index computations of getelementptr instructions. This 6088 // is primarily intended to catch gather-like idioms ending at 6089 // non-consecutive loads. 6090 if (!GEPs.empty()) { 6091 LLVM_DEBUG(dbgs() << "SLP: Found GEPs for " << GEPs.size() 6092 << " underlying objects.\n"); 6093 Changed |= vectorizeGEPIndices(BB, R); 6094 } 6095 } 6096 6097 if (Changed) { 6098 R.optimizeGatherSequence(); 6099 LLVM_DEBUG(dbgs() << "SLP: vectorized \"" << F.getName() << "\"\n"); 6100 } 6101 return Changed; 6102 } 6103 6104 bool SLPVectorizerPass::vectorizeStoreChain(ArrayRef<Value *> Chain, BoUpSLP &R, 6105 unsigned Idx) { 6106 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " << Chain.size() 6107 << "\n"); 6108 const unsigned Sz = R.getVectorElementSize(Chain[0]); 6109 const unsigned MinVF = R.getMinVecRegSize() / Sz; 6110 unsigned VF = Chain.size(); 6111 6112 if (!isPowerOf2_32(Sz) || !isPowerOf2_32(VF) || VF < 2 || VF < MinVF) 6113 return false; 6114 6115 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << VF << " stores at offset " << Idx 6116 << "\n"); 6117 6118 R.buildTree(Chain); 6119 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 6120 // TODO: Handle orders of size less than number of elements in the vector. 6121 if (Order && Order->size() == Chain.size()) { 6122 // TODO: reorder tree nodes without tree rebuilding. 6123 SmallVector<Value *, 4> ReorderedOps(Chain.rbegin(), Chain.rend()); 6124 llvm::transform(*Order, ReorderedOps.begin(), 6125 [Chain](const unsigned Idx) { return Chain[Idx]; }); 6126 R.buildTree(ReorderedOps); 6127 } 6128 if (R.isTreeTinyAndNotFullyVectorizable()) 6129 return false; 6130 if (R.isLoadCombineCandidate()) 6131 return false; 6132 6133 R.computeMinimumValueSizes(); 6134 6135 InstructionCost Cost = R.getTreeCost(); 6136 6137 LLVM_DEBUG(dbgs() << "SLP: Found cost = " << Cost << " for VF =" << VF << "\n"); 6138 if (Cost < -SLPCostThreshold) { 6139 LLVM_DEBUG(dbgs() << "SLP: Decided to vectorize cost = " << Cost << "\n"); 6140 6141 using namespace ore; 6142 6143 R.getORE()->emit(OptimizationRemark(SV_NAME, "StoresVectorized", 6144 cast<StoreInst>(Chain[0])) 6145 << "Stores SLP vectorized with cost " << NV("Cost", Cost) 6146 << " and with tree size " 6147 << NV("TreeSize", R.getTreeSize())); 6148 6149 R.vectorizeTree(); 6150 return true; 6151 } 6152 6153 return false; 6154 } 6155 6156 bool SLPVectorizerPass::vectorizeStores(ArrayRef<StoreInst *> Stores, 6157 BoUpSLP &R) { 6158 // We may run into multiple chains that merge into a single chain. We mark the 6159 // stores that we vectorized so that we don't visit the same store twice. 6160 BoUpSLP::ValueSet VectorizedStores; 6161 bool Changed = false; 6162 6163 int E = Stores.size(); 6164 SmallBitVector Tails(E, false); 6165 int MaxIter = MaxStoreLookup.getValue(); 6166 SmallVector<std::pair<int, int>, 16> ConsecutiveChain( 6167 E, std::make_pair(E, INT_MAX)); 6168 SmallVector<SmallBitVector, 4> CheckedPairs(E, SmallBitVector(E, false)); 6169 int IterCnt; 6170 auto &&FindConsecutiveAccess = [this, &Stores, &Tails, &IterCnt, MaxIter, 6171 &CheckedPairs, 6172 &ConsecutiveChain](int K, int Idx) { 6173 if (IterCnt >= MaxIter) 6174 return true; 6175 if (CheckedPairs[Idx].test(K)) 6176 return ConsecutiveChain[K].second == 1 && 6177 ConsecutiveChain[K].first == Idx; 6178 ++IterCnt; 6179 CheckedPairs[Idx].set(K); 6180 CheckedPairs[K].set(Idx); 6181 Optional<int> Diff = getPointersDiff(Stores[K]->getPointerOperand(), 6182 Stores[Idx]->getPointerOperand(), *DL, 6183 *SE, /*StrictCheck=*/true); 6184 if (!Diff || *Diff == 0) 6185 return false; 6186 int Val = *Diff; 6187 if (Val < 0) { 6188 if (ConsecutiveChain[Idx].second > -Val) { 6189 Tails.set(K); 6190 ConsecutiveChain[Idx] = std::make_pair(K, -Val); 6191 } 6192 return false; 6193 } 6194 if (ConsecutiveChain[K].second <= Val) 6195 return false; 6196 6197 Tails.set(Idx); 6198 ConsecutiveChain[K] = std::make_pair(Idx, Val); 6199 return Val == 1; 6200 }; 6201 // Do a quadratic search on all of the given stores in reverse order and find 6202 // all of the pairs of stores that follow each other. 6203 for (int Idx = E - 1; Idx >= 0; --Idx) { 6204 // If a store has multiple consecutive store candidates, search according 6205 // to the sequence: Idx-1, Idx+1, Idx-2, Idx+2, ... 6206 // This is because usually pairing with immediate succeeding or preceding 6207 // candidate create the best chance to find slp vectorization opportunity. 6208 const int MaxLookDepth = std::max(E - Idx, Idx + 1); 6209 IterCnt = 0; 6210 for (int Offset = 1, F = MaxLookDepth; Offset < F; ++Offset) 6211 if ((Idx >= Offset && FindConsecutiveAccess(Idx - Offset, Idx)) || 6212 (Idx + Offset < E && FindConsecutiveAccess(Idx + Offset, Idx))) 6213 break; 6214 } 6215 6216 // For stores that start but don't end a link in the chain: 6217 for (int Cnt = E; Cnt > 0; --Cnt) { 6218 int I = Cnt - 1; 6219 if (ConsecutiveChain[I].first == E || Tails.test(I)) 6220 continue; 6221 // We found a store instr that starts a chain. Now follow the chain and try 6222 // to vectorize it. 6223 BoUpSLP::ValueList Operands; 6224 // Collect the chain into a list. 6225 while (I != E && !VectorizedStores.count(Stores[I])) { 6226 Operands.push_back(Stores[I]); 6227 Tails.set(I); 6228 if (ConsecutiveChain[I].second != 1) { 6229 // Mark the new end in the chain and go back, if required. It might be 6230 // required if the original stores come in reversed order, for example. 6231 if (ConsecutiveChain[I].first != E && 6232 Tails.test(ConsecutiveChain[I].first) && 6233 !VectorizedStores.count(Stores[ConsecutiveChain[I].first])) { 6234 Tails.reset(ConsecutiveChain[I].first); 6235 if (Cnt < ConsecutiveChain[I].first + 2) 6236 Cnt = ConsecutiveChain[I].first + 2; 6237 } 6238 break; 6239 } 6240 // Move to the next value in the chain. 6241 I = ConsecutiveChain[I].first; 6242 } 6243 assert(!Operands.empty() && "Expected non-empty list of stores."); 6244 6245 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 6246 unsigned EltSize = R.getVectorElementSize(Operands[0]); 6247 unsigned MaxElts = llvm::PowerOf2Floor(MaxVecRegSize / EltSize); 6248 6249 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / EltSize); 6250 unsigned MaxVF = std::min(R.getMaximumVF(EltSize, Instruction::Store), 6251 MaxElts); 6252 6253 // FIXME: Is division-by-2 the correct step? Should we assert that the 6254 // register size is a power-of-2? 6255 unsigned StartIdx = 0; 6256 for (unsigned Size = MaxVF; Size >= MinVF; Size /= 2) { 6257 for (unsigned Cnt = StartIdx, E = Operands.size(); Cnt + Size <= E;) { 6258 ArrayRef<Value *> Slice = makeArrayRef(Operands).slice(Cnt, Size); 6259 if (!VectorizedStores.count(Slice.front()) && 6260 !VectorizedStores.count(Slice.back()) && 6261 vectorizeStoreChain(Slice, R, Cnt)) { 6262 // Mark the vectorized stores so that we don't vectorize them again. 6263 VectorizedStores.insert(Slice.begin(), Slice.end()); 6264 Changed = true; 6265 // If we vectorized initial block, no need to try to vectorize it 6266 // again. 6267 if (Cnt == StartIdx) 6268 StartIdx += Size; 6269 Cnt += Size; 6270 continue; 6271 } 6272 ++Cnt; 6273 } 6274 // Check if the whole array was vectorized already - exit. 6275 if (StartIdx >= Operands.size()) 6276 break; 6277 } 6278 } 6279 6280 return Changed; 6281 } 6282 6283 void SLPVectorizerPass::collectSeedInstructions(BasicBlock *BB) { 6284 // Initialize the collections. We will make a single pass over the block. 6285 Stores.clear(); 6286 GEPs.clear(); 6287 6288 // Visit the store and getelementptr instructions in BB and organize them in 6289 // Stores and GEPs according to the underlying objects of their pointer 6290 // operands. 6291 for (Instruction &I : *BB) { 6292 // Ignore store instructions that are volatile or have a pointer operand 6293 // that doesn't point to a scalar type. 6294 if (auto *SI = dyn_cast<StoreInst>(&I)) { 6295 if (!SI->isSimple()) 6296 continue; 6297 if (!isValidElementType(SI->getValueOperand()->getType())) 6298 continue; 6299 Stores[getUnderlyingObject(SI->getPointerOperand())].push_back(SI); 6300 } 6301 6302 // Ignore getelementptr instructions that have more than one index, a 6303 // constant index, or a pointer operand that doesn't point to a scalar 6304 // type. 6305 else if (auto *GEP = dyn_cast<GetElementPtrInst>(&I)) { 6306 auto Idx = GEP->idx_begin()->get(); 6307 if (GEP->getNumIndices() > 1 || isa<Constant>(Idx)) 6308 continue; 6309 if (!isValidElementType(Idx->getType())) 6310 continue; 6311 if (GEP->getType()->isVectorTy()) 6312 continue; 6313 GEPs[GEP->getPointerOperand()].push_back(GEP); 6314 } 6315 } 6316 } 6317 6318 bool SLPVectorizerPass::tryToVectorizePair(Value *A, Value *B, BoUpSLP &R) { 6319 if (!A || !B) 6320 return false; 6321 Value *VL[] = {A, B}; 6322 return tryToVectorizeList(VL, R, /*AllowReorder=*/true); 6323 } 6324 6325 bool SLPVectorizerPass::tryToVectorizeList(ArrayRef<Value *> VL, BoUpSLP &R, 6326 bool AllowReorder, 6327 ArrayRef<Value *> InsertUses) { 6328 if (VL.size() < 2) 6329 return false; 6330 6331 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize a list of length = " 6332 << VL.size() << ".\n"); 6333 6334 // Check that all of the parts are instructions of the same type, 6335 // we permit an alternate opcode via InstructionsState. 6336 InstructionsState S = getSameOpcode(VL); 6337 if (!S.getOpcode()) 6338 return false; 6339 6340 Instruction *I0 = cast<Instruction>(S.OpValue); 6341 // Make sure invalid types (including vector type) are rejected before 6342 // determining vectorization factor for scalar instructions. 6343 for (Value *V : VL) { 6344 Type *Ty = V->getType(); 6345 if (!isValidElementType(Ty)) { 6346 // NOTE: the following will give user internal llvm type name, which may 6347 // not be useful. 6348 R.getORE()->emit([&]() { 6349 std::string type_str; 6350 llvm::raw_string_ostream rso(type_str); 6351 Ty->print(rso); 6352 return OptimizationRemarkMissed(SV_NAME, "UnsupportedType", I0) 6353 << "Cannot SLP vectorize list: type " 6354 << rso.str() + " is unsupported by vectorizer"; 6355 }); 6356 return false; 6357 } 6358 } 6359 6360 unsigned Sz = R.getVectorElementSize(I0); 6361 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / Sz); 6362 unsigned MaxVF = std::max<unsigned>(PowerOf2Floor(VL.size()), MinVF); 6363 MaxVF = std::min(R.getMaximumVF(Sz, S.getOpcode()), MaxVF); 6364 if (MaxVF < 2) { 6365 R.getORE()->emit([&]() { 6366 return OptimizationRemarkMissed(SV_NAME, "SmallVF", I0) 6367 << "Cannot SLP vectorize list: vectorization factor " 6368 << "less than 2 is not supported"; 6369 }); 6370 return false; 6371 } 6372 6373 bool Changed = false; 6374 bool CandidateFound = false; 6375 InstructionCost MinCost = SLPCostThreshold.getValue(); 6376 6377 bool CompensateUseCost = 6378 !InsertUses.empty() && llvm::all_of(InsertUses, [](const Value *V) { 6379 return V && isa<InsertElementInst>(V); 6380 }); 6381 assert((!CompensateUseCost || InsertUses.size() == VL.size()) && 6382 "Each scalar expected to have an associated InsertElement user."); 6383 6384 unsigned NextInst = 0, MaxInst = VL.size(); 6385 for (unsigned VF = MaxVF; NextInst + 1 < MaxInst && VF >= MinVF; VF /= 2) { 6386 // No actual vectorization should happen, if number of parts is the same as 6387 // provided vectorization factor (i.e. the scalar type is used for vector 6388 // code during codegen). 6389 auto *VecTy = FixedVectorType::get(VL[0]->getType(), VF); 6390 if (TTI->getNumberOfParts(VecTy) == VF) 6391 continue; 6392 for (unsigned I = NextInst; I < MaxInst; ++I) { 6393 unsigned OpsWidth = 0; 6394 6395 if (I + VF > MaxInst) 6396 OpsWidth = MaxInst - I; 6397 else 6398 OpsWidth = VF; 6399 6400 if (!isPowerOf2_32(OpsWidth) || OpsWidth < 2) 6401 break; 6402 6403 ArrayRef<Value *> Ops = VL.slice(I, OpsWidth); 6404 // Check that a previous iteration of this loop did not delete the Value. 6405 if (llvm::any_of(Ops, [&R](Value *V) { 6406 auto *I = dyn_cast<Instruction>(V); 6407 return I && R.isDeleted(I); 6408 })) 6409 continue; 6410 6411 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << OpsWidth << " operations " 6412 << "\n"); 6413 6414 R.buildTree(Ops); 6415 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 6416 // TODO: check if we can allow reordering for more cases. 6417 if (AllowReorder && Order) { 6418 // TODO: reorder tree nodes without tree rebuilding. 6419 // Conceptually, there is nothing actually preventing us from trying to 6420 // reorder a larger list. In fact, we do exactly this when vectorizing 6421 // reductions. However, at this point, we only expect to get here when 6422 // there are exactly two operations. 6423 assert(Ops.size() == 2); 6424 Value *ReorderedOps[] = {Ops[1], Ops[0]}; 6425 R.buildTree(ReorderedOps, None); 6426 } 6427 if (R.isTreeTinyAndNotFullyVectorizable()) 6428 continue; 6429 6430 R.computeMinimumValueSizes(); 6431 InstructionCost Cost = R.getTreeCost(); 6432 CandidateFound = true; 6433 if (CompensateUseCost) { 6434 // TODO: Use TTI's getScalarizationOverhead for sequence of inserts 6435 // rather than sum of single inserts as the latter may overestimate 6436 // cost. This work should imply improving cost estimation for extracts 6437 // that added in for external (for vectorization tree) users,i.e. that 6438 // part should also switch to same interface. 6439 // For example, the following case is projected code after SLP: 6440 // %4 = extractelement <4 x i64> %3, i32 0 6441 // %v0 = insertelement <4 x i64> poison, i64 %4, i32 0 6442 // %5 = extractelement <4 x i64> %3, i32 1 6443 // %v1 = insertelement <4 x i64> %v0, i64 %5, i32 1 6444 // %6 = extractelement <4 x i64> %3, i32 2 6445 // %v2 = insertelement <4 x i64> %v1, i64 %6, i32 2 6446 // %7 = extractelement <4 x i64> %3, i32 3 6447 // %v3 = insertelement <4 x i64> %v2, i64 %7, i32 3 6448 // 6449 // Extracts here added by SLP in order to feed users (the inserts) of 6450 // original scalars and contribute to "ExtractCost" at cost evaluation. 6451 // The inserts in turn form sequence to build an aggregate that 6452 // detected by findBuildAggregate routine. 6453 // SLP makes an assumption that such sequence will be optimized away 6454 // later (instcombine) so it tries to compensate ExctractCost with 6455 // cost of insert sequence. 6456 // Current per element cost calculation approach is not quite accurate 6457 // and tends to create bias toward favoring vectorization. 6458 // Switching to the TTI interface might help a bit. 6459 // Alternative solution could be pattern-match to detect a no-op or 6460 // shuffle. 6461 InstructionCost UserCost = 0; 6462 for (unsigned Lane = 0; Lane < OpsWidth; Lane++) { 6463 auto *IE = cast<InsertElementInst>(InsertUses[I + Lane]); 6464 if (auto *CI = dyn_cast<ConstantInt>(IE->getOperand(2))) 6465 UserCost += TTI->getVectorInstrCost( 6466 Instruction::InsertElement, IE->getType(), CI->getZExtValue()); 6467 } 6468 LLVM_DEBUG(dbgs() << "SLP: Compensate cost of users by: " << UserCost 6469 << ".\n"); 6470 Cost -= UserCost; 6471 } 6472 6473 MinCost = std::min(MinCost, Cost); 6474 6475 if (Cost < -SLPCostThreshold) { 6476 LLVM_DEBUG(dbgs() << "SLP: Vectorizing list at cost:" << Cost << ".\n"); 6477 R.getORE()->emit(OptimizationRemark(SV_NAME, "VectorizedList", 6478 cast<Instruction>(Ops[0])) 6479 << "SLP vectorized with cost " << ore::NV("Cost", Cost) 6480 << " and with tree size " 6481 << ore::NV("TreeSize", R.getTreeSize())); 6482 6483 R.vectorizeTree(); 6484 // Move to the next bundle. 6485 I += VF - 1; 6486 NextInst = I + 1; 6487 Changed = true; 6488 } 6489 } 6490 } 6491 6492 if (!Changed && CandidateFound) { 6493 R.getORE()->emit([&]() { 6494 return OptimizationRemarkMissed(SV_NAME, "NotBeneficial", I0) 6495 << "List vectorization was possible but not beneficial with cost " 6496 << ore::NV("Cost", MinCost) << " >= " 6497 << ore::NV("Treshold", -SLPCostThreshold); 6498 }); 6499 } else if (!Changed) { 6500 R.getORE()->emit([&]() { 6501 return OptimizationRemarkMissed(SV_NAME, "NotPossible", I0) 6502 << "Cannot SLP vectorize list: vectorization was impossible" 6503 << " with available vectorization factors"; 6504 }); 6505 } 6506 return Changed; 6507 } 6508 6509 bool SLPVectorizerPass::tryToVectorize(Instruction *I, BoUpSLP &R) { 6510 if (!I) 6511 return false; 6512 6513 if (!isa<BinaryOperator>(I) && !isa<CmpInst>(I)) 6514 return false; 6515 6516 Value *P = I->getParent(); 6517 6518 // Vectorize in current basic block only. 6519 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 6520 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 6521 if (!Op0 || !Op1 || Op0->getParent() != P || Op1->getParent() != P) 6522 return false; 6523 6524 // Try to vectorize V. 6525 if (tryToVectorizePair(Op0, Op1, R)) 6526 return true; 6527 6528 auto *A = dyn_cast<BinaryOperator>(Op0); 6529 auto *B = dyn_cast<BinaryOperator>(Op1); 6530 // Try to skip B. 6531 if (B && B->hasOneUse()) { 6532 auto *B0 = dyn_cast<BinaryOperator>(B->getOperand(0)); 6533 auto *B1 = dyn_cast<BinaryOperator>(B->getOperand(1)); 6534 if (B0 && B0->getParent() == P && tryToVectorizePair(A, B0, R)) 6535 return true; 6536 if (B1 && B1->getParent() == P && tryToVectorizePair(A, B1, R)) 6537 return true; 6538 } 6539 6540 // Try to skip A. 6541 if (A && A->hasOneUse()) { 6542 auto *A0 = dyn_cast<BinaryOperator>(A->getOperand(0)); 6543 auto *A1 = dyn_cast<BinaryOperator>(A->getOperand(1)); 6544 if (A0 && A0->getParent() == P && tryToVectorizePair(A0, B, R)) 6545 return true; 6546 if (A1 && A1->getParent() == P && tryToVectorizePair(A1, B, R)) 6547 return true; 6548 } 6549 return false; 6550 } 6551 6552 namespace { 6553 6554 /// Model horizontal reductions. 6555 /// 6556 /// A horizontal reduction is a tree of reduction instructions that has values 6557 /// that can be put into a vector as its leaves. For example: 6558 /// 6559 /// mul mul mul mul 6560 /// \ / \ / 6561 /// + + 6562 /// \ / 6563 /// + 6564 /// This tree has "mul" as its leaf values and "+" as its reduction 6565 /// instructions. A reduction can feed into a store or a binary operation 6566 /// feeding a phi. 6567 /// ... 6568 /// \ / 6569 /// + 6570 /// | 6571 /// phi += 6572 /// 6573 /// Or: 6574 /// ... 6575 /// \ / 6576 /// + 6577 /// | 6578 /// *p = 6579 /// 6580 class HorizontalReduction { 6581 using ReductionOpsType = SmallVector<Value *, 16>; 6582 using ReductionOpsListType = SmallVector<ReductionOpsType, 2>; 6583 ReductionOpsListType ReductionOps; 6584 SmallVector<Value *, 32> ReducedVals; 6585 // Use map vector to make stable output. 6586 MapVector<Instruction *, Value *> ExtraArgs; 6587 WeakTrackingVH ReductionRoot; 6588 /// The type of reduction operation. 6589 RecurKind RdxKind; 6590 6591 /// Checks if instruction is associative and can be vectorized. 6592 static bool isVectorizable(RecurKind Kind, Instruction *I) { 6593 if (Kind == RecurKind::None) 6594 return false; 6595 if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(Kind)) 6596 return true; 6597 6598 if (Kind == RecurKind::FMax || Kind == RecurKind::FMin) { 6599 // FP min/max are associative except for NaN and -0.0. We do not 6600 // have to rule out -0.0 here because the intrinsic semantics do not 6601 // specify a fixed result for it. 6602 return I->getFastMathFlags().noNaNs(); 6603 } 6604 6605 return I->isAssociative(); 6606 } 6607 6608 /// Checks if the ParentStackElem.first should be marked as a reduction 6609 /// operation with an extra argument or as extra argument itself. 6610 void markExtraArg(std::pair<Instruction *, unsigned> &ParentStackElem, 6611 Value *ExtraArg) { 6612 if (ExtraArgs.count(ParentStackElem.first)) { 6613 ExtraArgs[ParentStackElem.first] = nullptr; 6614 // We ran into something like: 6615 // ParentStackElem.first = ExtraArgs[ParentStackElem.first] + ExtraArg. 6616 // The whole ParentStackElem.first should be considered as an extra value 6617 // in this case. 6618 // Do not perform analysis of remaining operands of ParentStackElem.first 6619 // instruction, this whole instruction is an extra argument. 6620 ParentStackElem.second = getNumberOfOperands(ParentStackElem.first); 6621 } else { 6622 // We ran into something like: 6623 // ParentStackElem.first += ... + ExtraArg + ... 6624 ExtraArgs[ParentStackElem.first] = ExtraArg; 6625 } 6626 } 6627 6628 /// Creates reduction operation with the current opcode. 6629 static Value *createOp(IRBuilder<> &Builder, RecurKind Kind, Value *LHS, 6630 Value *RHS, const Twine &Name, bool UseSelect) { 6631 unsigned RdxOpcode = RecurrenceDescriptor::getOpcode(Kind); 6632 switch (Kind) { 6633 case RecurKind::Add: 6634 case RecurKind::Mul: 6635 case RecurKind::Or: 6636 case RecurKind::And: 6637 case RecurKind::Xor: 6638 case RecurKind::FAdd: 6639 case RecurKind::FMul: 6640 return Builder.CreateBinOp((Instruction::BinaryOps)RdxOpcode, LHS, RHS, 6641 Name); 6642 case RecurKind::FMax: 6643 return Builder.CreateBinaryIntrinsic(Intrinsic::maxnum, LHS, RHS); 6644 case RecurKind::FMin: 6645 return Builder.CreateBinaryIntrinsic(Intrinsic::minnum, LHS, RHS); 6646 case RecurKind::SMax: 6647 if (UseSelect) { 6648 Value *Cmp = Builder.CreateICmpSGT(LHS, RHS, Name); 6649 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6650 } 6651 return Builder.CreateBinaryIntrinsic(Intrinsic::smax, LHS, RHS); 6652 case RecurKind::SMin: 6653 if (UseSelect) { 6654 Value *Cmp = Builder.CreateICmpSLT(LHS, RHS, Name); 6655 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6656 } 6657 return Builder.CreateBinaryIntrinsic(Intrinsic::smin, LHS, RHS); 6658 case RecurKind::UMax: 6659 if (UseSelect) { 6660 Value *Cmp = Builder.CreateICmpUGT(LHS, RHS, Name); 6661 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6662 } 6663 return Builder.CreateBinaryIntrinsic(Intrinsic::umax, LHS, RHS); 6664 case RecurKind::UMin: 6665 if (UseSelect) { 6666 Value *Cmp = Builder.CreateICmpULT(LHS, RHS, Name); 6667 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6668 } 6669 return Builder.CreateBinaryIntrinsic(Intrinsic::umin, LHS, RHS); 6670 default: 6671 llvm_unreachable("Unknown reduction operation."); 6672 } 6673 } 6674 6675 /// Creates reduction operation with the current opcode with the IR flags 6676 /// from \p ReductionOps. 6677 static Value *createOp(IRBuilder<> &Builder, RecurKind RdxKind, Value *LHS, 6678 Value *RHS, const Twine &Name, 6679 const ReductionOpsListType &ReductionOps) { 6680 bool UseSelect = ReductionOps.size() == 2; 6681 assert((!UseSelect || isa<SelectInst>(ReductionOps[1][0])) && 6682 "Expected cmp + select pairs for reduction"); 6683 Value *Op = createOp(Builder, RdxKind, LHS, RHS, Name, UseSelect); 6684 if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(RdxKind)) { 6685 if (auto *Sel = dyn_cast<SelectInst>(Op)) { 6686 propagateIRFlags(Sel->getCondition(), ReductionOps[0]); 6687 propagateIRFlags(Op, ReductionOps[1]); 6688 return Op; 6689 } 6690 } 6691 propagateIRFlags(Op, ReductionOps[0]); 6692 return Op; 6693 } 6694 /// Creates reduction operation with the current opcode with the IR flags 6695 /// from \p I. 6696 static Value *createOp(IRBuilder<> &Builder, RecurKind RdxKind, Value *LHS, 6697 Value *RHS, const Twine &Name, Instruction *I) { 6698 auto *SelI = dyn_cast<SelectInst>(I); 6699 Value *Op = createOp(Builder, RdxKind, LHS, RHS, Name, SelI != nullptr); 6700 if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(RdxKind)) { 6701 if (auto *Sel = dyn_cast<SelectInst>(Op)) 6702 propagateIRFlags(Sel->getCondition(), SelI->getCondition()); 6703 } 6704 propagateIRFlags(Op, I); 6705 return Op; 6706 } 6707 6708 static RecurKind getRdxKind(Instruction *I) { 6709 assert(I && "Expected instruction for reduction matching"); 6710 TargetTransformInfo::ReductionFlags RdxFlags; 6711 if (match(I, m_Add(m_Value(), m_Value()))) 6712 return RecurKind::Add; 6713 if (match(I, m_Mul(m_Value(), m_Value()))) 6714 return RecurKind::Mul; 6715 if (match(I, m_And(m_Value(), m_Value()))) 6716 return RecurKind::And; 6717 if (match(I, m_Or(m_Value(), m_Value()))) 6718 return RecurKind::Or; 6719 if (match(I, m_Xor(m_Value(), m_Value()))) 6720 return RecurKind::Xor; 6721 if (match(I, m_FAdd(m_Value(), m_Value()))) 6722 return RecurKind::FAdd; 6723 if (match(I, m_FMul(m_Value(), m_Value()))) 6724 return RecurKind::FMul; 6725 6726 if (match(I, m_Intrinsic<Intrinsic::maxnum>(m_Value(), m_Value()))) 6727 return RecurKind::FMax; 6728 if (match(I, m_Intrinsic<Intrinsic::minnum>(m_Value(), m_Value()))) 6729 return RecurKind::FMin; 6730 6731 // This matches either cmp+select or intrinsics. SLP is expected to handle 6732 // either form. 6733 // TODO: If we are canonicalizing to intrinsics, we can remove several 6734 // special-case paths that deal with selects. 6735 if (match(I, m_SMax(m_Value(), m_Value()))) 6736 return RecurKind::SMax; 6737 if (match(I, m_SMin(m_Value(), m_Value()))) 6738 return RecurKind::SMin; 6739 if (match(I, m_UMax(m_Value(), m_Value()))) 6740 return RecurKind::UMax; 6741 if (match(I, m_UMin(m_Value(), m_Value()))) 6742 return RecurKind::UMin; 6743 6744 if (auto *Select = dyn_cast<SelectInst>(I)) { 6745 // Try harder: look for min/max pattern based on instructions producing 6746 // same values such as: select ((cmp Inst1, Inst2), Inst1, Inst2). 6747 // During the intermediate stages of SLP, it's very common to have 6748 // pattern like this (since optimizeGatherSequence is run only once 6749 // at the end): 6750 // %1 = extractelement <2 x i32> %a, i32 0 6751 // %2 = extractelement <2 x i32> %a, i32 1 6752 // %cond = icmp sgt i32 %1, %2 6753 // %3 = extractelement <2 x i32> %a, i32 0 6754 // %4 = extractelement <2 x i32> %a, i32 1 6755 // %select = select i1 %cond, i32 %3, i32 %4 6756 CmpInst::Predicate Pred; 6757 Instruction *L1; 6758 Instruction *L2; 6759 6760 Value *LHS = Select->getTrueValue(); 6761 Value *RHS = Select->getFalseValue(); 6762 Value *Cond = Select->getCondition(); 6763 6764 // TODO: Support inverse predicates. 6765 if (match(Cond, m_Cmp(Pred, m_Specific(LHS), m_Instruction(L2)))) { 6766 if (!isa<ExtractElementInst>(RHS) || 6767 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6768 return RecurKind::None; 6769 } else if (match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Specific(RHS)))) { 6770 if (!isa<ExtractElementInst>(LHS) || 6771 !L1->isIdenticalTo(cast<Instruction>(LHS))) 6772 return RecurKind::None; 6773 } else { 6774 if (!isa<ExtractElementInst>(LHS) || !isa<ExtractElementInst>(RHS)) 6775 return RecurKind::None; 6776 if (!match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Instruction(L2))) || 6777 !L1->isIdenticalTo(cast<Instruction>(LHS)) || 6778 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6779 return RecurKind::None; 6780 } 6781 6782 TargetTransformInfo::ReductionFlags RdxFlags; 6783 switch (Pred) { 6784 default: 6785 return RecurKind::None; 6786 case CmpInst::ICMP_SGT: 6787 case CmpInst::ICMP_SGE: 6788 return RecurKind::SMax; 6789 case CmpInst::ICMP_SLT: 6790 case CmpInst::ICMP_SLE: 6791 return RecurKind::SMin; 6792 case CmpInst::ICMP_UGT: 6793 case CmpInst::ICMP_UGE: 6794 return RecurKind::UMax; 6795 case CmpInst::ICMP_ULT: 6796 case CmpInst::ICMP_ULE: 6797 return RecurKind::UMin; 6798 } 6799 } 6800 return RecurKind::None; 6801 } 6802 6803 /// Get the index of the first operand. 6804 static unsigned getFirstOperandIndex(Instruction *I) { 6805 return isa<SelectInst>(I) ? 1 : 0; 6806 } 6807 6808 /// Total number of operands in the reduction operation. 6809 static unsigned getNumberOfOperands(Instruction *I) { 6810 return isa<SelectInst>(I) ? 3 : 2; 6811 } 6812 6813 /// Checks if the instruction is in basic block \p BB. 6814 /// For a min/max reduction check that both compare and select are in \p BB. 6815 static bool hasSameParent(Instruction *I, BasicBlock *BB, bool IsRedOp) { 6816 auto *Sel = dyn_cast<SelectInst>(I); 6817 if (IsRedOp && Sel) { 6818 auto *Cmp = cast<Instruction>(Sel->getCondition()); 6819 return Sel->getParent() == BB && Cmp->getParent() == BB; 6820 } 6821 return I->getParent() == BB; 6822 } 6823 6824 /// Expected number of uses for reduction operations/reduced values. 6825 static bool hasRequiredNumberOfUses(bool MatchCmpSel, Instruction *I) { 6826 // SelectInst must be used twice while the condition op must have single 6827 // use only. 6828 if (MatchCmpSel) { 6829 if (auto *Sel = dyn_cast<SelectInst>(I)) 6830 return Sel->hasNUses(2) && Sel->getCondition()->hasOneUse(); 6831 return I->hasNUses(2); 6832 } 6833 6834 // Arithmetic reduction operation must be used once only. 6835 return I->hasOneUse(); 6836 } 6837 6838 /// Initializes the list of reduction operations. 6839 void initReductionOps(Instruction *I) { 6840 if (isa<SelectInst>(I)) 6841 ReductionOps.assign(2, ReductionOpsType()); 6842 else 6843 ReductionOps.assign(1, ReductionOpsType()); 6844 } 6845 6846 /// Add all reduction operations for the reduction instruction \p I. 6847 void addReductionOps(Instruction *I) { 6848 if (auto *Sel = dyn_cast<SelectInst>(I)) { 6849 ReductionOps[0].emplace_back(Sel->getCondition()); 6850 ReductionOps[1].emplace_back(Sel); 6851 } else { 6852 ReductionOps[0].emplace_back(I); 6853 } 6854 } 6855 6856 static Value *getLHS(RecurKind Kind, Instruction *I) { 6857 if (Kind == RecurKind::None) 6858 return nullptr; 6859 return I->getOperand(getFirstOperandIndex(I)); 6860 } 6861 static Value *getRHS(RecurKind Kind, Instruction *I) { 6862 if (Kind == RecurKind::None) 6863 return nullptr; 6864 return I->getOperand(getFirstOperandIndex(I) + 1); 6865 } 6866 6867 public: 6868 HorizontalReduction() = default; 6869 6870 /// Try to find a reduction tree. 6871 bool matchAssociativeReduction(PHINode *Phi, Instruction *B) { 6872 assert((!Phi || is_contained(Phi->operands(), B)) && 6873 "Phi needs to use the binary operator"); 6874 6875 RdxKind = getRdxKind(B); 6876 6877 // We could have a initial reductions that is not an add. 6878 // r *= v1 + v2 + v3 + v4 6879 // In such a case start looking for a tree rooted in the first '+'. 6880 if (Phi) { 6881 if (getLHS(RdxKind, B) == Phi) { 6882 Phi = nullptr; 6883 B = dyn_cast<Instruction>(getRHS(RdxKind, B)); 6884 if (!B) 6885 return false; 6886 RdxKind = getRdxKind(B); 6887 } else if (getRHS(RdxKind, B) == Phi) { 6888 Phi = nullptr; 6889 B = dyn_cast<Instruction>(getLHS(RdxKind, B)); 6890 if (!B) 6891 return false; 6892 RdxKind = getRdxKind(B); 6893 } 6894 } 6895 6896 if (!isVectorizable(RdxKind, B)) 6897 return false; 6898 6899 // Analyze "regular" integer/FP types for reductions - no target-specific 6900 // types or pointers. 6901 Type *Ty = B->getType(); 6902 if (!isValidElementType(Ty) || Ty->isPointerTy()) 6903 return false; 6904 6905 ReductionRoot = B; 6906 6907 // The opcode for leaf values that we perform a reduction on. 6908 // For example: load(x) + load(y) + load(z) + fptoui(w) 6909 // The leaf opcode for 'w' does not match, so we don't include it as a 6910 // potential candidate for the reduction. 6911 unsigned LeafOpcode = 0; 6912 6913 // Post order traverse the reduction tree starting at B. We only handle true 6914 // trees containing only binary operators. 6915 SmallVector<std::pair<Instruction *, unsigned>, 32> Stack; 6916 Stack.push_back(std::make_pair(B, getFirstOperandIndex(B))); 6917 initReductionOps(B); 6918 while (!Stack.empty()) { 6919 Instruction *TreeN = Stack.back().first; 6920 unsigned EdgeToVisit = Stack.back().second++; 6921 const RecurKind TreeRdxKind = getRdxKind(TreeN); 6922 bool IsReducedValue = TreeRdxKind != RdxKind; 6923 6924 // Postorder visit. 6925 if (IsReducedValue || EdgeToVisit == getNumberOfOperands(TreeN)) { 6926 if (IsReducedValue) 6927 ReducedVals.push_back(TreeN); 6928 else { 6929 auto ExtraArgsIter = ExtraArgs.find(TreeN); 6930 if (ExtraArgsIter != ExtraArgs.end() && !ExtraArgsIter->second) { 6931 // Check if TreeN is an extra argument of its parent operation. 6932 if (Stack.size() <= 1) { 6933 // TreeN can't be an extra argument as it is a root reduction 6934 // operation. 6935 return false; 6936 } 6937 // Yes, TreeN is an extra argument, do not add it to a list of 6938 // reduction operations. 6939 // Stack[Stack.size() - 2] always points to the parent operation. 6940 markExtraArg(Stack[Stack.size() - 2], TreeN); 6941 ExtraArgs.erase(TreeN); 6942 } else 6943 addReductionOps(TreeN); 6944 } 6945 // Retract. 6946 Stack.pop_back(); 6947 continue; 6948 } 6949 6950 // Visit left or right. 6951 Value *EdgeVal = TreeN->getOperand(EdgeToVisit); 6952 auto *EdgeInst = dyn_cast<Instruction>(EdgeVal); 6953 if (!EdgeInst) { 6954 // Edge value is not a reduction instruction or a leaf instruction. 6955 // (It may be a constant, function argument, or something else.) 6956 markExtraArg(Stack.back(), EdgeVal); 6957 continue; 6958 } 6959 RecurKind EdgeRdxKind = getRdxKind(EdgeInst); 6960 // Continue analysis if the next operand is a reduction operation or 6961 // (possibly) a leaf value. If the leaf value opcode is not set, 6962 // the first met operation != reduction operation is considered as the 6963 // leaf opcode. 6964 // Only handle trees in the current basic block. 6965 // Each tree node needs to have minimal number of users except for the 6966 // ultimate reduction. 6967 const bool IsRdxInst = EdgeRdxKind == RdxKind; 6968 if (EdgeInst != Phi && EdgeInst != B && 6969 hasSameParent(EdgeInst, B->getParent(), IsRdxInst) && 6970 hasRequiredNumberOfUses(isa<SelectInst>(B), EdgeInst) && 6971 (!LeafOpcode || LeafOpcode == EdgeInst->getOpcode() || IsRdxInst)) { 6972 if (IsRdxInst) { 6973 // We need to be able to reassociate the reduction operations. 6974 if (!isVectorizable(EdgeRdxKind, EdgeInst)) { 6975 // I is an extra argument for TreeN (its parent operation). 6976 markExtraArg(Stack.back(), EdgeInst); 6977 continue; 6978 } 6979 } else if (!LeafOpcode) { 6980 LeafOpcode = EdgeInst->getOpcode(); 6981 } 6982 Stack.push_back( 6983 std::make_pair(EdgeInst, getFirstOperandIndex(EdgeInst))); 6984 continue; 6985 } 6986 // I is an extra argument for TreeN (its parent operation). 6987 markExtraArg(Stack.back(), EdgeInst); 6988 } 6989 return true; 6990 } 6991 6992 /// Attempt to vectorize the tree found by matchAssociativeReduction. 6993 bool tryToReduce(BoUpSLP &V, TargetTransformInfo *TTI) { 6994 // If there are a sufficient number of reduction values, reduce 6995 // to a nearby power-of-2. We can safely generate oversized 6996 // vectors and rely on the backend to split them to legal sizes. 6997 unsigned NumReducedVals = ReducedVals.size(); 6998 if (NumReducedVals < 4) 6999 return false; 7000 7001 // Intersect the fast-math-flags from all reduction operations. 7002 FastMathFlags RdxFMF; 7003 RdxFMF.set(); 7004 for (ReductionOpsType &RdxOp : ReductionOps) { 7005 for (Value *RdxVal : RdxOp) { 7006 if (auto *FPMO = dyn_cast<FPMathOperator>(RdxVal)) 7007 RdxFMF &= FPMO->getFastMathFlags(); 7008 } 7009 } 7010 7011 IRBuilder<> Builder(cast<Instruction>(ReductionRoot)); 7012 Builder.setFastMathFlags(RdxFMF); 7013 7014 BoUpSLP::ExtraValueToDebugLocsMap ExternallyUsedValues; 7015 // The same extra argument may be used several times, so log each attempt 7016 // to use it. 7017 for (const std::pair<Instruction *, Value *> &Pair : ExtraArgs) { 7018 assert(Pair.first && "DebugLoc must be set."); 7019 ExternallyUsedValues[Pair.second].push_back(Pair.first); 7020 } 7021 7022 // The compare instruction of a min/max is the insertion point for new 7023 // instructions and may be replaced with a new compare instruction. 7024 auto getCmpForMinMaxReduction = [](Instruction *RdxRootInst) { 7025 assert(isa<SelectInst>(RdxRootInst) && 7026 "Expected min/max reduction to have select root instruction"); 7027 Value *ScalarCond = cast<SelectInst>(RdxRootInst)->getCondition(); 7028 assert(isa<Instruction>(ScalarCond) && 7029 "Expected min/max reduction to have compare condition"); 7030 return cast<Instruction>(ScalarCond); 7031 }; 7032 7033 // The reduction root is used as the insertion point for new instructions, 7034 // so set it as externally used to prevent it from being deleted. 7035 ExternallyUsedValues[ReductionRoot]; 7036 SmallVector<Value *, 16> IgnoreList; 7037 for (ReductionOpsType &RdxOp : ReductionOps) 7038 IgnoreList.append(RdxOp.begin(), RdxOp.end()); 7039 7040 unsigned ReduxWidth = PowerOf2Floor(NumReducedVals); 7041 if (NumReducedVals > ReduxWidth) { 7042 // In the loop below, we are building a tree based on a window of 7043 // 'ReduxWidth' values. 7044 // If the operands of those values have common traits (compare predicate, 7045 // constant operand, etc), then we want to group those together to 7046 // minimize the cost of the reduction. 7047 7048 // TODO: This should be extended to count common operands for 7049 // compares and binops. 7050 7051 // Step 1: Count the number of times each compare predicate occurs. 7052 SmallDenseMap<unsigned, unsigned> PredCountMap; 7053 for (Value *RdxVal : ReducedVals) { 7054 CmpInst::Predicate Pred; 7055 if (match(RdxVal, m_Cmp(Pred, m_Value(), m_Value()))) 7056 ++PredCountMap[Pred]; 7057 } 7058 // Step 2: Sort the values so the most common predicates come first. 7059 stable_sort(ReducedVals, [&PredCountMap](Value *A, Value *B) { 7060 CmpInst::Predicate PredA, PredB; 7061 if (match(A, m_Cmp(PredA, m_Value(), m_Value())) && 7062 match(B, m_Cmp(PredB, m_Value(), m_Value()))) { 7063 return PredCountMap[PredA] > PredCountMap[PredB]; 7064 } 7065 return false; 7066 }); 7067 } 7068 7069 Value *VectorizedTree = nullptr; 7070 unsigned i = 0; 7071 while (i < NumReducedVals - ReduxWidth + 1 && ReduxWidth > 2) { 7072 ArrayRef<Value *> VL(&ReducedVals[i], ReduxWidth); 7073 V.buildTree(VL, ExternallyUsedValues, IgnoreList); 7074 Optional<ArrayRef<unsigned>> Order = V.bestOrder(); 7075 if (Order) { 7076 assert(Order->size() == VL.size() && 7077 "Order size must be the same as number of vectorized " 7078 "instructions."); 7079 // TODO: reorder tree nodes without tree rebuilding. 7080 SmallVector<Value *, 4> ReorderedOps(VL.size()); 7081 llvm::transform(*Order, ReorderedOps.begin(), 7082 [VL](const unsigned Idx) { return VL[Idx]; }); 7083 V.buildTree(ReorderedOps, ExternallyUsedValues, IgnoreList); 7084 } 7085 if (V.isTreeTinyAndNotFullyVectorizable()) 7086 break; 7087 if (V.isLoadCombineReductionCandidate(RdxKind)) 7088 break; 7089 7090 V.computeMinimumValueSizes(); 7091 7092 // Estimate cost. 7093 InstructionCost TreeCost = V.getTreeCost(); 7094 InstructionCost ReductionCost = 7095 getReductionCost(TTI, ReducedVals[i], ReduxWidth); 7096 InstructionCost Cost = TreeCost + ReductionCost; 7097 if (!Cost.isValid()) { 7098 LLVM_DEBUG(dbgs() << "Encountered invalid baseline cost.\n"); 7099 return false; 7100 } 7101 if (Cost >= -SLPCostThreshold) { 7102 V.getORE()->emit([&]() { 7103 return OptimizationRemarkMissed(SV_NAME, "HorSLPNotBeneficial", 7104 cast<Instruction>(VL[0])) 7105 << "Vectorizing horizontal reduction is possible" 7106 << "but not beneficial with cost " << ore::NV("Cost", Cost) 7107 << " and threshold " 7108 << ore::NV("Threshold", -SLPCostThreshold); 7109 }); 7110 break; 7111 } 7112 7113 LLVM_DEBUG(dbgs() << "SLP: Vectorizing horizontal reduction at cost:" 7114 << Cost << ". (HorRdx)\n"); 7115 V.getORE()->emit([&]() { 7116 return OptimizationRemark(SV_NAME, "VectorizedHorizontalReduction", 7117 cast<Instruction>(VL[0])) 7118 << "Vectorized horizontal reduction with cost " 7119 << ore::NV("Cost", Cost) << " and with tree size " 7120 << ore::NV("TreeSize", V.getTreeSize()); 7121 }); 7122 7123 // Vectorize a tree. 7124 DebugLoc Loc = cast<Instruction>(ReducedVals[i])->getDebugLoc(); 7125 Value *VectorizedRoot = V.vectorizeTree(ExternallyUsedValues); 7126 7127 // Emit a reduction. If the root is a select (min/max idiom), the insert 7128 // point is the compare condition of that select. 7129 Instruction *RdxRootInst = cast<Instruction>(ReductionRoot); 7130 if (isa<SelectInst>(RdxRootInst)) 7131 Builder.SetInsertPoint(getCmpForMinMaxReduction(RdxRootInst)); 7132 else 7133 Builder.SetInsertPoint(RdxRootInst); 7134 7135 Value *ReducedSubTree = 7136 emitReduction(VectorizedRoot, Builder, ReduxWidth, TTI); 7137 7138 if (!VectorizedTree) { 7139 // Initialize the final value in the reduction. 7140 VectorizedTree = ReducedSubTree; 7141 } else { 7142 // Update the final value in the reduction. 7143 Builder.SetCurrentDebugLocation(Loc); 7144 VectorizedTree = createOp(Builder, RdxKind, VectorizedTree, 7145 ReducedSubTree, "op.rdx", ReductionOps); 7146 } 7147 i += ReduxWidth; 7148 ReduxWidth = PowerOf2Floor(NumReducedVals - i); 7149 } 7150 7151 if (VectorizedTree) { 7152 // Finish the reduction. 7153 for (; i < NumReducedVals; ++i) { 7154 auto *I = cast<Instruction>(ReducedVals[i]); 7155 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 7156 VectorizedTree = 7157 createOp(Builder, RdxKind, VectorizedTree, I, "", ReductionOps); 7158 } 7159 for (auto &Pair : ExternallyUsedValues) { 7160 // Add each externally used value to the final reduction. 7161 for (auto *I : Pair.second) { 7162 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 7163 VectorizedTree = createOp(Builder, RdxKind, VectorizedTree, 7164 Pair.first, "op.extra", I); 7165 } 7166 } 7167 7168 // Update users. For a min/max reduction that ends with a compare and 7169 // select, we also have to RAUW for the compare instruction feeding the 7170 // reduction root. That's because the original compare may have extra uses 7171 // besides the final select of the reduction. 7172 if (auto *ScalarSelect = dyn_cast<SelectInst>(ReductionRoot)) { 7173 if (auto *VecSelect = dyn_cast<SelectInst>(VectorizedTree)) { 7174 Instruction *ScalarCmp = getCmpForMinMaxReduction(ScalarSelect); 7175 ScalarCmp->replaceAllUsesWith(VecSelect->getCondition()); 7176 } 7177 } 7178 ReductionRoot->replaceAllUsesWith(VectorizedTree); 7179 7180 // Mark all scalar reduction ops for deletion, they are replaced by the 7181 // vector reductions. 7182 V.eraseInstructions(IgnoreList); 7183 } 7184 return VectorizedTree != nullptr; 7185 } 7186 7187 unsigned numReductionValues() const { return ReducedVals.size(); } 7188 7189 private: 7190 /// Calculate the cost of a reduction. 7191 InstructionCost getReductionCost(TargetTransformInfo *TTI, 7192 Value *FirstReducedVal, 7193 unsigned ReduxWidth) { 7194 Type *ScalarTy = FirstReducedVal->getType(); 7195 FixedVectorType *VectorTy = FixedVectorType::get(ScalarTy, ReduxWidth); 7196 InstructionCost VectorCost, ScalarCost; 7197 switch (RdxKind) { 7198 case RecurKind::Add: 7199 case RecurKind::Mul: 7200 case RecurKind::Or: 7201 case RecurKind::And: 7202 case RecurKind::Xor: 7203 case RecurKind::FAdd: 7204 case RecurKind::FMul: { 7205 unsigned RdxOpcode = RecurrenceDescriptor::getOpcode(RdxKind); 7206 VectorCost = TTI->getArithmeticReductionCost(RdxOpcode, VectorTy, 7207 /*IsPairwiseForm=*/false); 7208 ScalarCost = TTI->getArithmeticInstrCost(RdxOpcode, ScalarTy); 7209 break; 7210 } 7211 case RecurKind::FMax: 7212 case RecurKind::FMin: { 7213 auto *VecCondTy = cast<VectorType>(CmpInst::makeCmpResultType(VectorTy)); 7214 VectorCost = 7215 TTI->getMinMaxReductionCost(VectorTy, VecCondTy, 7216 /*pairwise=*/false, /*unsigned=*/false); 7217 ScalarCost = 7218 TTI->getCmpSelInstrCost(Instruction::FCmp, ScalarTy) + 7219 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 7220 CmpInst::makeCmpResultType(ScalarTy)); 7221 break; 7222 } 7223 case RecurKind::SMax: 7224 case RecurKind::SMin: 7225 case RecurKind::UMax: 7226 case RecurKind::UMin: { 7227 auto *VecCondTy = cast<VectorType>(CmpInst::makeCmpResultType(VectorTy)); 7228 bool IsUnsigned = 7229 RdxKind == RecurKind::UMax || RdxKind == RecurKind::UMin; 7230 VectorCost = 7231 TTI->getMinMaxReductionCost(VectorTy, VecCondTy, 7232 /*IsPairwiseForm=*/false, IsUnsigned); 7233 ScalarCost = 7234 TTI->getCmpSelInstrCost(Instruction::ICmp, ScalarTy) + 7235 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 7236 CmpInst::makeCmpResultType(ScalarTy)); 7237 break; 7238 } 7239 default: 7240 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 7241 } 7242 7243 // Scalar cost is repeated for N-1 elements. 7244 ScalarCost *= (ReduxWidth - 1); 7245 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << VectorCost - ScalarCost 7246 << " for reduction that starts with " << *FirstReducedVal 7247 << " (It is a splitting reduction)\n"); 7248 return VectorCost - ScalarCost; 7249 } 7250 7251 /// Emit a horizontal reduction of the vectorized value. 7252 Value *emitReduction(Value *VectorizedValue, IRBuilder<> &Builder, 7253 unsigned ReduxWidth, const TargetTransformInfo *TTI) { 7254 assert(VectorizedValue && "Need to have a vectorized tree node"); 7255 assert(isPowerOf2_32(ReduxWidth) && 7256 "We only handle power-of-two reductions for now"); 7257 7258 return createSimpleTargetReduction(Builder, TTI, VectorizedValue, RdxKind, 7259 ReductionOps.back()); 7260 } 7261 }; 7262 7263 } // end anonymous namespace 7264 7265 static Optional<unsigned> getAggregateSize(Instruction *InsertInst) { 7266 if (auto *IE = dyn_cast<InsertElementInst>(InsertInst)) 7267 return cast<FixedVectorType>(IE->getType())->getNumElements(); 7268 7269 unsigned AggregateSize = 1; 7270 auto *IV = cast<InsertValueInst>(InsertInst); 7271 Type *CurrentType = IV->getType(); 7272 do { 7273 if (auto *ST = dyn_cast<StructType>(CurrentType)) { 7274 for (auto *Elt : ST->elements()) 7275 if (Elt != ST->getElementType(0)) // check homogeneity 7276 return None; 7277 AggregateSize *= ST->getNumElements(); 7278 CurrentType = ST->getElementType(0); 7279 } else if (auto *AT = dyn_cast<ArrayType>(CurrentType)) { 7280 AggregateSize *= AT->getNumElements(); 7281 CurrentType = AT->getElementType(); 7282 } else if (auto *VT = dyn_cast<FixedVectorType>(CurrentType)) { 7283 AggregateSize *= VT->getNumElements(); 7284 return AggregateSize; 7285 } else if (CurrentType->isSingleValueType()) { 7286 return AggregateSize; 7287 } else { 7288 return None; 7289 } 7290 } while (true); 7291 } 7292 7293 static Optional<unsigned> getOperandIndex(Instruction *InsertInst, 7294 unsigned OperandOffset) { 7295 unsigned OperandIndex = OperandOffset; 7296 if (auto *IE = dyn_cast<InsertElementInst>(InsertInst)) { 7297 if (auto *CI = dyn_cast<ConstantInt>(IE->getOperand(2))) { 7298 auto *VT = cast<FixedVectorType>(IE->getType()); 7299 OperandIndex *= VT->getNumElements(); 7300 OperandIndex += CI->getZExtValue(); 7301 return OperandIndex; 7302 } 7303 return None; 7304 } 7305 7306 auto *IV = cast<InsertValueInst>(InsertInst); 7307 Type *CurrentType = IV->getType(); 7308 for (unsigned int Index : IV->indices()) { 7309 if (auto *ST = dyn_cast<StructType>(CurrentType)) { 7310 OperandIndex *= ST->getNumElements(); 7311 CurrentType = ST->getElementType(Index); 7312 } else if (auto *AT = dyn_cast<ArrayType>(CurrentType)) { 7313 OperandIndex *= AT->getNumElements(); 7314 CurrentType = AT->getElementType(); 7315 } else { 7316 return None; 7317 } 7318 OperandIndex += Index; 7319 } 7320 return OperandIndex; 7321 } 7322 7323 static bool findBuildAggregate_rec(Instruction *LastInsertInst, 7324 TargetTransformInfo *TTI, 7325 SmallVectorImpl<Value *> &BuildVectorOpds, 7326 SmallVectorImpl<Value *> &InsertElts, 7327 unsigned OperandOffset) { 7328 do { 7329 Value *InsertedOperand = LastInsertInst->getOperand(1); 7330 Optional<unsigned> OperandIndex = 7331 getOperandIndex(LastInsertInst, OperandOffset); 7332 if (!OperandIndex) 7333 return false; 7334 if (isa<InsertElementInst>(InsertedOperand) || 7335 isa<InsertValueInst>(InsertedOperand)) { 7336 if (!findBuildAggregate_rec(cast<Instruction>(InsertedOperand), TTI, 7337 BuildVectorOpds, InsertElts, *OperandIndex)) 7338 return false; 7339 } else { 7340 BuildVectorOpds[*OperandIndex] = InsertedOperand; 7341 InsertElts[*OperandIndex] = LastInsertInst; 7342 } 7343 if (isa<UndefValue>(LastInsertInst->getOperand(0))) 7344 return true; 7345 LastInsertInst = dyn_cast<Instruction>(LastInsertInst->getOperand(0)); 7346 } while (LastInsertInst != nullptr && 7347 (isa<InsertValueInst>(LastInsertInst) || 7348 isa<InsertElementInst>(LastInsertInst)) && 7349 LastInsertInst->hasOneUse()); 7350 return false; 7351 } 7352 7353 /// Recognize construction of vectors like 7354 /// %ra = insertelement <4 x float> poison, float %s0, i32 0 7355 /// %rb = insertelement <4 x float> %ra, float %s1, i32 1 7356 /// %rc = insertelement <4 x float> %rb, float %s2, i32 2 7357 /// %rd = insertelement <4 x float> %rc, float %s3, i32 3 7358 /// starting from the last insertelement or insertvalue instruction. 7359 /// 7360 /// Also recognize homogeneous aggregates like {<2 x float>, <2 x float>}, 7361 /// {{float, float}, {float, float}}, [2 x {float, float}] and so on. 7362 /// See llvm/test/Transforms/SLPVectorizer/X86/pr42022.ll for examples. 7363 /// 7364 /// Assume LastInsertInst is of InsertElementInst or InsertValueInst type. 7365 /// 7366 /// \return true if it matches. 7367 static bool findBuildAggregate(Instruction *LastInsertInst, 7368 TargetTransformInfo *TTI, 7369 SmallVectorImpl<Value *> &BuildVectorOpds, 7370 SmallVectorImpl<Value *> &InsertElts) { 7371 7372 assert((isa<InsertElementInst>(LastInsertInst) || 7373 isa<InsertValueInst>(LastInsertInst)) && 7374 "Expected insertelement or insertvalue instruction!"); 7375 7376 assert((BuildVectorOpds.empty() && InsertElts.empty()) && 7377 "Expected empty result vectors!"); 7378 7379 Optional<unsigned> AggregateSize = getAggregateSize(LastInsertInst); 7380 if (!AggregateSize) 7381 return false; 7382 BuildVectorOpds.resize(*AggregateSize); 7383 InsertElts.resize(*AggregateSize); 7384 7385 if (findBuildAggregate_rec(LastInsertInst, TTI, BuildVectorOpds, InsertElts, 7386 0)) { 7387 llvm::erase_value(BuildVectorOpds, nullptr); 7388 llvm::erase_value(InsertElts, nullptr); 7389 if (BuildVectorOpds.size() >= 2) 7390 return true; 7391 } 7392 7393 return false; 7394 } 7395 7396 static bool PhiTypeSorterFunc(Value *V, Value *V2) { 7397 return V->getType() < V2->getType(); 7398 } 7399 7400 /// Try and get a reduction value from a phi node. 7401 /// 7402 /// Given a phi node \p P in a block \p ParentBB, consider possible reductions 7403 /// if they come from either \p ParentBB or a containing loop latch. 7404 /// 7405 /// \returns A candidate reduction value if possible, or \code nullptr \endcode 7406 /// if not possible. 7407 static Value *getReductionValue(const DominatorTree *DT, PHINode *P, 7408 BasicBlock *ParentBB, LoopInfo *LI) { 7409 // There are situations where the reduction value is not dominated by the 7410 // reduction phi. Vectorizing such cases has been reported to cause 7411 // miscompiles. See PR25787. 7412 auto DominatedReduxValue = [&](Value *R) { 7413 return isa<Instruction>(R) && 7414 DT->dominates(P->getParent(), cast<Instruction>(R)->getParent()); 7415 }; 7416 7417 Value *Rdx = nullptr; 7418 7419 // Return the incoming value if it comes from the same BB as the phi node. 7420 if (P->getIncomingBlock(0) == ParentBB) { 7421 Rdx = P->getIncomingValue(0); 7422 } else if (P->getIncomingBlock(1) == ParentBB) { 7423 Rdx = P->getIncomingValue(1); 7424 } 7425 7426 if (Rdx && DominatedReduxValue(Rdx)) 7427 return Rdx; 7428 7429 // Otherwise, check whether we have a loop latch to look at. 7430 Loop *BBL = LI->getLoopFor(ParentBB); 7431 if (!BBL) 7432 return nullptr; 7433 BasicBlock *BBLatch = BBL->getLoopLatch(); 7434 if (!BBLatch) 7435 return nullptr; 7436 7437 // There is a loop latch, return the incoming value if it comes from 7438 // that. This reduction pattern occasionally turns up. 7439 if (P->getIncomingBlock(0) == BBLatch) { 7440 Rdx = P->getIncomingValue(0); 7441 } else if (P->getIncomingBlock(1) == BBLatch) { 7442 Rdx = P->getIncomingValue(1); 7443 } 7444 7445 if (Rdx && DominatedReduxValue(Rdx)) 7446 return Rdx; 7447 7448 return nullptr; 7449 } 7450 7451 static bool matchRdxBop(Instruction *I, Value *&V0, Value *&V1) { 7452 if (match(I, m_BinOp(m_Value(V0), m_Value(V1)))) 7453 return true; 7454 if (match(I, m_Intrinsic<Intrinsic::maxnum>(m_Value(V0), m_Value(V1)))) 7455 return true; 7456 if (match(I, m_Intrinsic<Intrinsic::minnum>(m_Value(V0), m_Value(V1)))) 7457 return true; 7458 if (match(I, m_Intrinsic<Intrinsic::smax>(m_Value(V0), m_Value(V1)))) 7459 return true; 7460 if (match(I, m_Intrinsic<Intrinsic::smin>(m_Value(V0), m_Value(V1)))) 7461 return true; 7462 if (match(I, m_Intrinsic<Intrinsic::umax>(m_Value(V0), m_Value(V1)))) 7463 return true; 7464 if (match(I, m_Intrinsic<Intrinsic::umin>(m_Value(V0), m_Value(V1)))) 7465 return true; 7466 return false; 7467 } 7468 7469 /// Attempt to reduce a horizontal reduction. 7470 /// If it is legal to match a horizontal reduction feeding the phi node \a P 7471 /// with reduction operators \a Root (or one of its operands) in a basic block 7472 /// \a BB, then check if it can be done. If horizontal reduction is not found 7473 /// and root instruction is a binary operation, vectorization of the operands is 7474 /// attempted. 7475 /// \returns true if a horizontal reduction was matched and reduced or operands 7476 /// of one of the binary instruction were vectorized. 7477 /// \returns false if a horizontal reduction was not matched (or not possible) 7478 /// or no vectorization of any binary operation feeding \a Root instruction was 7479 /// performed. 7480 static bool tryToVectorizeHorReductionOrInstOperands( 7481 PHINode *P, Instruction *Root, BasicBlock *BB, BoUpSLP &R, 7482 TargetTransformInfo *TTI, 7483 const function_ref<bool(Instruction *, BoUpSLP &)> Vectorize) { 7484 if (!ShouldVectorizeHor) 7485 return false; 7486 7487 if (!Root) 7488 return false; 7489 7490 if (Root->getParent() != BB || isa<PHINode>(Root)) 7491 return false; 7492 // Start analysis starting from Root instruction. If horizontal reduction is 7493 // found, try to vectorize it. If it is not a horizontal reduction or 7494 // vectorization is not possible or not effective, and currently analyzed 7495 // instruction is a binary operation, try to vectorize the operands, using 7496 // pre-order DFS traversal order. If the operands were not vectorized, repeat 7497 // the same procedure considering each operand as a possible root of the 7498 // horizontal reduction. 7499 // Interrupt the process if the Root instruction itself was vectorized or all 7500 // sub-trees not higher that RecursionMaxDepth were analyzed/vectorized. 7501 SmallVector<std::pair<Instruction *, unsigned>, 8> Stack(1, {Root, 0}); 7502 SmallPtrSet<Value *, 8> VisitedInstrs; 7503 bool Res = false; 7504 while (!Stack.empty()) { 7505 Instruction *Inst; 7506 unsigned Level; 7507 std::tie(Inst, Level) = Stack.pop_back_val(); 7508 Value *B0, *B1; 7509 bool IsBinop = matchRdxBop(Inst, B0, B1); 7510 bool IsSelect = match(Inst, m_Select(m_Value(), m_Value(), m_Value())); 7511 if (IsBinop || IsSelect) { 7512 HorizontalReduction HorRdx; 7513 if (HorRdx.matchAssociativeReduction(P, Inst)) { 7514 if (HorRdx.tryToReduce(R, TTI)) { 7515 Res = true; 7516 // Set P to nullptr to avoid re-analysis of phi node in 7517 // matchAssociativeReduction function unless this is the root node. 7518 P = nullptr; 7519 continue; 7520 } 7521 } 7522 if (P && IsBinop) { 7523 Inst = dyn_cast<Instruction>(B0); 7524 if (Inst == P) 7525 Inst = dyn_cast<Instruction>(B1); 7526 if (!Inst) { 7527 // Set P to nullptr to avoid re-analysis of phi node in 7528 // matchAssociativeReduction function unless this is the root node. 7529 P = nullptr; 7530 continue; 7531 } 7532 } 7533 } 7534 // Set P to nullptr to avoid re-analysis of phi node in 7535 // matchAssociativeReduction function unless this is the root node. 7536 P = nullptr; 7537 if (Vectorize(Inst, R)) { 7538 Res = true; 7539 continue; 7540 } 7541 7542 // Try to vectorize operands. 7543 // Continue analysis for the instruction from the same basic block only to 7544 // save compile time. 7545 if (++Level < RecursionMaxDepth) 7546 for (auto *Op : Inst->operand_values()) 7547 if (VisitedInstrs.insert(Op).second) 7548 if (auto *I = dyn_cast<Instruction>(Op)) 7549 if (!isa<PHINode>(I) && !R.isDeleted(I) && I->getParent() == BB) 7550 Stack.emplace_back(I, Level); 7551 } 7552 return Res; 7553 } 7554 7555 bool SLPVectorizerPass::vectorizeRootInstruction(PHINode *P, Value *V, 7556 BasicBlock *BB, BoUpSLP &R, 7557 TargetTransformInfo *TTI) { 7558 auto *I = dyn_cast_or_null<Instruction>(V); 7559 if (!I) 7560 return false; 7561 7562 if (!isa<BinaryOperator>(I)) 7563 P = nullptr; 7564 // Try to match and vectorize a horizontal reduction. 7565 auto &&ExtraVectorization = [this](Instruction *I, BoUpSLP &R) -> bool { 7566 return tryToVectorize(I, R); 7567 }; 7568 return tryToVectorizeHorReductionOrInstOperands(P, I, BB, R, TTI, 7569 ExtraVectorization); 7570 } 7571 7572 bool SLPVectorizerPass::vectorizeInsertValueInst(InsertValueInst *IVI, 7573 BasicBlock *BB, BoUpSLP &R) { 7574 const DataLayout &DL = BB->getModule()->getDataLayout(); 7575 if (!R.canMapToVector(IVI->getType(), DL)) 7576 return false; 7577 7578 SmallVector<Value *, 16> BuildVectorOpds; 7579 SmallVector<Value *, 16> BuildVectorInsts; 7580 if (!findBuildAggregate(IVI, TTI, BuildVectorOpds, BuildVectorInsts)) 7581 return false; 7582 7583 LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IVI << "\n"); 7584 // Aggregate value is unlikely to be processed in vector register, we need to 7585 // extract scalars into scalar registers, so NeedExtraction is set true. 7586 return tryToVectorizeList(BuildVectorOpds, R, /*AllowReorder=*/false, 7587 BuildVectorInsts); 7588 } 7589 7590 bool SLPVectorizerPass::vectorizeInsertElementInst(InsertElementInst *IEI, 7591 BasicBlock *BB, BoUpSLP &R) { 7592 SmallVector<Value *, 16> BuildVectorInsts; 7593 SmallVector<Value *, 16> BuildVectorOpds; 7594 SmallVector<int> Mask; 7595 if (!findBuildAggregate(IEI, TTI, BuildVectorOpds, BuildVectorInsts) || 7596 (llvm::all_of(BuildVectorOpds, 7597 [](Value *V) { return isa<ExtractElementInst>(V); }) && 7598 isShuffle(BuildVectorOpds, Mask))) 7599 return false; 7600 7601 // Vectorize starting with the build vector operands ignoring the BuildVector 7602 // instructions for the purpose of scheduling and user extraction. 7603 return tryToVectorizeList(BuildVectorOpds, R, /*AllowReorder=*/false, 7604 BuildVectorInsts); 7605 } 7606 7607 bool SLPVectorizerPass::vectorizeCmpInst(CmpInst *CI, BasicBlock *BB, 7608 BoUpSLP &R) { 7609 if (tryToVectorizePair(CI->getOperand(0), CI->getOperand(1), R)) 7610 return true; 7611 7612 bool OpsChanged = false; 7613 for (int Idx = 0; Idx < 2; ++Idx) { 7614 OpsChanged |= 7615 vectorizeRootInstruction(nullptr, CI->getOperand(Idx), BB, R, TTI); 7616 } 7617 return OpsChanged; 7618 } 7619 7620 bool SLPVectorizerPass::vectorizeSimpleInstructions( 7621 SmallVectorImpl<Instruction *> &Instructions, BasicBlock *BB, BoUpSLP &R) { 7622 bool OpsChanged = false; 7623 for (auto *I : reverse(Instructions)) { 7624 if (R.isDeleted(I)) 7625 continue; 7626 if (auto *LastInsertValue = dyn_cast<InsertValueInst>(I)) 7627 OpsChanged |= vectorizeInsertValueInst(LastInsertValue, BB, R); 7628 else if (auto *LastInsertElem = dyn_cast<InsertElementInst>(I)) 7629 OpsChanged |= vectorizeInsertElementInst(LastInsertElem, BB, R); 7630 else if (auto *CI = dyn_cast<CmpInst>(I)) 7631 OpsChanged |= vectorizeCmpInst(CI, BB, R); 7632 } 7633 Instructions.clear(); 7634 return OpsChanged; 7635 } 7636 7637 bool SLPVectorizerPass::vectorizeChainsInBlock(BasicBlock *BB, BoUpSLP &R) { 7638 bool Changed = false; 7639 SmallVector<Value *, 4> Incoming; 7640 SmallPtrSet<Value *, 16> VisitedInstrs; 7641 7642 bool HaveVectorizedPhiNodes = true; 7643 while (HaveVectorizedPhiNodes) { 7644 HaveVectorizedPhiNodes = false; 7645 7646 // Collect the incoming values from the PHIs. 7647 Incoming.clear(); 7648 for (Instruction &I : *BB) { 7649 PHINode *P = dyn_cast<PHINode>(&I); 7650 if (!P) 7651 break; 7652 7653 if (!VisitedInstrs.count(P) && !R.isDeleted(P)) 7654 Incoming.push_back(P); 7655 } 7656 7657 // Sort by type. 7658 llvm::stable_sort(Incoming, PhiTypeSorterFunc); 7659 7660 // Try to vectorize elements base on their type. 7661 for (SmallVector<Value *, 4>::iterator IncIt = Incoming.begin(), 7662 E = Incoming.end(); 7663 IncIt != E;) { 7664 7665 // Look for the next elements with the same type. 7666 SmallVector<Value *, 4>::iterator SameTypeIt = IncIt; 7667 while (SameTypeIt != E && 7668 (*SameTypeIt)->getType() == (*IncIt)->getType()) { 7669 VisitedInstrs.insert(*SameTypeIt); 7670 ++SameTypeIt; 7671 } 7672 7673 // Try to vectorize them. 7674 unsigned NumElts = (SameTypeIt - IncIt); 7675 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize starting at PHIs (" 7676 << NumElts << ")\n"); 7677 // The order in which the phi nodes appear in the program does not matter. 7678 // So allow tryToVectorizeList to reorder them if it is beneficial. This 7679 // is done when there are exactly two elements since tryToVectorizeList 7680 // asserts that there are only two values when AllowReorder is true. 7681 bool AllowReorder = NumElts == 2; 7682 if (NumElts > 1 && 7683 tryToVectorizeList(makeArrayRef(IncIt, NumElts), R, AllowReorder)) { 7684 // Success start over because instructions might have been changed. 7685 HaveVectorizedPhiNodes = true; 7686 Changed = true; 7687 break; 7688 } 7689 7690 // Start over at the next instruction of a different type (or the end). 7691 IncIt = SameTypeIt; 7692 } 7693 } 7694 7695 VisitedInstrs.clear(); 7696 7697 SmallVector<Instruction *, 8> PostProcessInstructions; 7698 SmallDenseSet<Instruction *, 4> KeyNodes; 7699 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 7700 // Skip instructions with scalable type. The num of elements is unknown at 7701 // compile-time for scalable type. 7702 if (isa<ScalableVectorType>(it->getType())) 7703 continue; 7704 7705 // Skip instructions marked for the deletion. 7706 if (R.isDeleted(&*it)) 7707 continue; 7708 // We may go through BB multiple times so skip the one we have checked. 7709 if (!VisitedInstrs.insert(&*it).second) { 7710 if (it->use_empty() && KeyNodes.contains(&*it) && 7711 vectorizeSimpleInstructions(PostProcessInstructions, BB, R)) { 7712 // We would like to start over since some instructions are deleted 7713 // and the iterator may become invalid value. 7714 Changed = true; 7715 it = BB->begin(); 7716 e = BB->end(); 7717 } 7718 continue; 7719 } 7720 7721 if (isa<DbgInfoIntrinsic>(it)) 7722 continue; 7723 7724 // Try to vectorize reductions that use PHINodes. 7725 if (PHINode *P = dyn_cast<PHINode>(it)) { 7726 // Check that the PHI is a reduction PHI. 7727 if (P->getNumIncomingValues() == 2) { 7728 // Try to match and vectorize a horizontal reduction. 7729 if (vectorizeRootInstruction(P, getReductionValue(DT, P, BB, LI), BB, R, 7730 TTI)) { 7731 Changed = true; 7732 it = BB->begin(); 7733 e = BB->end(); 7734 continue; 7735 } 7736 } 7737 // Try to vectorize the incoming values of the PHI, to catch reductions 7738 // that feed into PHIs. 7739 for (unsigned I = 0, E = P->getNumIncomingValues(); I != E; I++) { 7740 // Skip if the incoming block is the current BB for now. Also, bypass 7741 // unreachable IR for efficiency and to avoid crashing. 7742 // TODO: Collect the skipped incoming values and try to vectorize them 7743 // after processing BB. 7744 if (BB == P->getIncomingBlock(I) || 7745 !DT->isReachableFromEntry(P->getIncomingBlock(I))) 7746 continue; 7747 7748 Changed |= vectorizeRootInstruction(nullptr, P->getIncomingValue(I), 7749 P->getIncomingBlock(I), R, TTI); 7750 } 7751 continue; 7752 } 7753 7754 // Ran into an instruction without users, like terminator, or function call 7755 // with ignored return value, store. Ignore unused instructions (basing on 7756 // instruction type, except for CallInst and InvokeInst). 7757 if (it->use_empty() && (it->getType()->isVoidTy() || isa<CallInst>(it) || 7758 isa<InvokeInst>(it))) { 7759 KeyNodes.insert(&*it); 7760 bool OpsChanged = false; 7761 if (ShouldStartVectorizeHorAtStore || !isa<StoreInst>(it)) { 7762 for (auto *V : it->operand_values()) { 7763 // Try to match and vectorize a horizontal reduction. 7764 OpsChanged |= vectorizeRootInstruction(nullptr, V, BB, R, TTI); 7765 } 7766 } 7767 // Start vectorization of post-process list of instructions from the 7768 // top-tree instructions to try to vectorize as many instructions as 7769 // possible. 7770 OpsChanged |= vectorizeSimpleInstructions(PostProcessInstructions, BB, R); 7771 if (OpsChanged) { 7772 // We would like to start over since some instructions are deleted 7773 // and the iterator may become invalid value. 7774 Changed = true; 7775 it = BB->begin(); 7776 e = BB->end(); 7777 continue; 7778 } 7779 } 7780 7781 if (isa<InsertElementInst>(it) || isa<CmpInst>(it) || 7782 isa<InsertValueInst>(it)) 7783 PostProcessInstructions.push_back(&*it); 7784 } 7785 7786 return Changed; 7787 } 7788 7789 bool SLPVectorizerPass::vectorizeGEPIndices(BasicBlock *BB, BoUpSLP &R) { 7790 auto Changed = false; 7791 for (auto &Entry : GEPs) { 7792 // If the getelementptr list has fewer than two elements, there's nothing 7793 // to do. 7794 if (Entry.second.size() < 2) 7795 continue; 7796 7797 LLVM_DEBUG(dbgs() << "SLP: Analyzing a getelementptr list of length " 7798 << Entry.second.size() << ".\n"); 7799 7800 // Process the GEP list in chunks suitable for the target's supported 7801 // vector size. If a vector register can't hold 1 element, we are done. We 7802 // are trying to vectorize the index computations, so the maximum number of 7803 // elements is based on the size of the index expression, rather than the 7804 // size of the GEP itself (the target's pointer size). 7805 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 7806 unsigned EltSize = R.getVectorElementSize(*Entry.second[0]->idx_begin()); 7807 if (MaxVecRegSize < EltSize) 7808 continue; 7809 7810 unsigned MaxElts = MaxVecRegSize / EltSize; 7811 for (unsigned BI = 0, BE = Entry.second.size(); BI < BE; BI += MaxElts) { 7812 auto Len = std::min<unsigned>(BE - BI, MaxElts); 7813 ArrayRef<GetElementPtrInst *> GEPList(&Entry.second[BI], Len); 7814 7815 // Initialize a set a candidate getelementptrs. Note that we use a 7816 // SetVector here to preserve program order. If the index computations 7817 // are vectorizable and begin with loads, we want to minimize the chance 7818 // of having to reorder them later. 7819 SetVector<Value *> Candidates(GEPList.begin(), GEPList.end()); 7820 7821 // Some of the candidates may have already been vectorized after we 7822 // initially collected them. If so, they are marked as deleted, so remove 7823 // them from the set of candidates. 7824 Candidates.remove_if( 7825 [&R](Value *I) { return R.isDeleted(cast<Instruction>(I)); }); 7826 7827 // Remove from the set of candidates all pairs of getelementptrs with 7828 // constant differences. Such getelementptrs are likely not good 7829 // candidates for vectorization in a bottom-up phase since one can be 7830 // computed from the other. We also ensure all candidate getelementptr 7831 // indices are unique. 7832 for (int I = 0, E = GEPList.size(); I < E && Candidates.size() > 1; ++I) { 7833 auto *GEPI = GEPList[I]; 7834 if (!Candidates.count(GEPI)) 7835 continue; 7836 auto *SCEVI = SE->getSCEV(GEPList[I]); 7837 for (int J = I + 1; J < E && Candidates.size() > 1; ++J) { 7838 auto *GEPJ = GEPList[J]; 7839 auto *SCEVJ = SE->getSCEV(GEPList[J]); 7840 if (isa<SCEVConstant>(SE->getMinusSCEV(SCEVI, SCEVJ))) { 7841 Candidates.remove(GEPI); 7842 Candidates.remove(GEPJ); 7843 } else if (GEPI->idx_begin()->get() == GEPJ->idx_begin()->get()) { 7844 Candidates.remove(GEPJ); 7845 } 7846 } 7847 } 7848 7849 // We break out of the above computation as soon as we know there are 7850 // fewer than two candidates remaining. 7851 if (Candidates.size() < 2) 7852 continue; 7853 7854 // Add the single, non-constant index of each candidate to the bundle. We 7855 // ensured the indices met these constraints when we originally collected 7856 // the getelementptrs. 7857 SmallVector<Value *, 16> Bundle(Candidates.size()); 7858 auto BundleIndex = 0u; 7859 for (auto *V : Candidates) { 7860 auto *GEP = cast<GetElementPtrInst>(V); 7861 auto *GEPIdx = GEP->idx_begin()->get(); 7862 assert(GEP->getNumIndices() == 1 || !isa<Constant>(GEPIdx)); 7863 Bundle[BundleIndex++] = GEPIdx; 7864 } 7865 7866 // Try and vectorize the indices. We are currently only interested in 7867 // gather-like cases of the form: 7868 // 7869 // ... = g[a[0] - b[0]] + g[a[1] - b[1]] + ... 7870 // 7871 // where the loads of "a", the loads of "b", and the subtractions can be 7872 // performed in parallel. It's likely that detecting this pattern in a 7873 // bottom-up phase will be simpler and less costly than building a 7874 // full-blown top-down phase beginning at the consecutive loads. 7875 Changed |= tryToVectorizeList(Bundle, R); 7876 } 7877 } 7878 return Changed; 7879 } 7880 7881 bool SLPVectorizerPass::vectorizeStoreChains(BoUpSLP &R) { 7882 bool Changed = false; 7883 // Attempt to sort and vectorize each of the store-groups. 7884 for (StoreListMap::iterator it = Stores.begin(), e = Stores.end(); it != e; 7885 ++it) { 7886 if (it->second.size() < 2) 7887 continue; 7888 7889 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " 7890 << it->second.size() << ".\n"); 7891 7892 Changed |= vectorizeStores(it->second, R); 7893 } 7894 return Changed; 7895 } 7896 7897 char SLPVectorizer::ID = 0; 7898 7899 static const char lv_name[] = "SLP Vectorizer"; 7900 7901 INITIALIZE_PASS_BEGIN(SLPVectorizer, SV_NAME, lv_name, false, false) 7902 INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass) 7903 INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass) 7904 INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker) 7905 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass) 7906 INITIALIZE_PASS_DEPENDENCY(LoopSimplify) 7907 INITIALIZE_PASS_DEPENDENCY(DemandedBitsWrapperPass) 7908 INITIALIZE_PASS_DEPENDENCY(OptimizationRemarkEmitterWrapperPass) 7909 INITIALIZE_PASS_DEPENDENCY(InjectTLIMappingsLegacy) 7910 INITIALIZE_PASS_END(SLPVectorizer, SV_NAME, lv_name, false, false) 7911 7912 Pass *llvm::createSLPVectorizerPass() { return new SLPVectorizer(); } 7913