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