1 //===- SLPVectorizer.cpp - A bottom up SLP Vectorizer ---------------------===// 2 // 3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. 4 // See https://llvm.org/LICENSE.txt for license information. 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 6 // 7 //===----------------------------------------------------------------------===// 8 // 9 // This pass implements the Bottom Up SLP vectorizer. It detects consecutive 10 // stores that can be put together into vector-stores. Next, it attempts to 11 // construct vectorizable tree using the use-def chains. If a profitable tree 12 // was found, the SLP vectorizer performs vectorization on the tree. 13 // 14 // The pass is inspired by the work described in the paper: 15 // "Loop-Aware SLP in GCC" by Ira Rosen, Dorit Nuzman, Ayal Zaks. 16 // 17 //===----------------------------------------------------------------------===// 18 19 #include "llvm/Transforms/Vectorize/SLPVectorizer.h" 20 #include "llvm/ADT/ArrayRef.h" 21 #include "llvm/ADT/DenseMap.h" 22 #include "llvm/ADT/DenseSet.h" 23 #include "llvm/ADT/MapVector.h" 24 #include "llvm/ADT/None.h" 25 #include "llvm/ADT/Optional.h" 26 #include "llvm/ADT/PostOrderIterator.h" 27 #include "llvm/ADT/STLExtras.h" 28 #include "llvm/ADT/SetVector.h" 29 #include "llvm/ADT/SmallBitVector.h" 30 #include "llvm/ADT/SmallPtrSet.h" 31 #include "llvm/ADT/SmallSet.h" 32 #include "llvm/ADT/SmallVector.h" 33 #include "llvm/ADT/Statistic.h" 34 #include "llvm/ADT/iterator.h" 35 #include "llvm/ADT/iterator_range.h" 36 #include "llvm/Analysis/AliasAnalysis.h" 37 #include "llvm/Analysis/CodeMetrics.h" 38 #include "llvm/Analysis/DemandedBits.h" 39 #include "llvm/Analysis/GlobalsModRef.h" 40 #include "llvm/Analysis/LoopAccessAnalysis.h" 41 #include "llvm/Analysis/LoopInfo.h" 42 #include "llvm/Analysis/MemoryLocation.h" 43 #include "llvm/Analysis/OptimizationRemarkEmitter.h" 44 #include "llvm/Analysis/ScalarEvolution.h" 45 #include "llvm/Analysis/ScalarEvolutionExpressions.h" 46 #include "llvm/Analysis/TargetLibraryInfo.h" 47 #include "llvm/Analysis/TargetTransformInfo.h" 48 #include "llvm/Analysis/ValueTracking.h" 49 #include "llvm/Analysis/VectorUtils.h" 50 #include "llvm/IR/Attributes.h" 51 #include "llvm/IR/BasicBlock.h" 52 #include "llvm/IR/Constant.h" 53 #include "llvm/IR/Constants.h" 54 #include "llvm/IR/DataLayout.h" 55 #include "llvm/IR/DebugLoc.h" 56 #include "llvm/IR/DerivedTypes.h" 57 #include "llvm/IR/Dominators.h" 58 #include "llvm/IR/Function.h" 59 #include "llvm/IR/IRBuilder.h" 60 #include "llvm/IR/InstrTypes.h" 61 #include "llvm/IR/Instruction.h" 62 #include "llvm/IR/Instructions.h" 63 #include "llvm/IR/IntrinsicInst.h" 64 #include "llvm/IR/Intrinsics.h" 65 #include "llvm/IR/Module.h" 66 #include "llvm/IR/NoFolder.h" 67 #include "llvm/IR/Operator.h" 68 #include "llvm/IR/PassManager.h" 69 #include "llvm/IR/PatternMatch.h" 70 #include "llvm/IR/Type.h" 71 #include "llvm/IR/Use.h" 72 #include "llvm/IR/User.h" 73 #include "llvm/IR/Value.h" 74 #include "llvm/IR/ValueHandle.h" 75 #include "llvm/IR/Verifier.h" 76 #include "llvm/InitializePasses.h" 77 #include "llvm/Pass.h" 78 #include "llvm/Support/Casting.h" 79 #include "llvm/Support/CommandLine.h" 80 #include "llvm/Support/Compiler.h" 81 #include "llvm/Support/DOTGraphTraits.h" 82 #include "llvm/Support/Debug.h" 83 #include "llvm/Support/ErrorHandling.h" 84 #include "llvm/Support/GraphWriter.h" 85 #include "llvm/Support/KnownBits.h" 86 #include "llvm/Support/MathExtras.h" 87 #include "llvm/Support/raw_ostream.h" 88 #include "llvm/Transforms/Utils/InjectTLIMappings.h" 89 #include "llvm/Transforms/Utils/LoopUtils.h" 90 #include "llvm/Transforms/Vectorize.h" 91 #include <algorithm> 92 #include <cassert> 93 #include <cstdint> 94 #include <iterator> 95 #include <memory> 96 #include <set> 97 #include <string> 98 #include <tuple> 99 #include <utility> 100 #include <vector> 101 102 using namespace llvm; 103 using namespace llvm::PatternMatch; 104 using namespace slpvectorizer; 105 106 #define SV_NAME "slp-vectorizer" 107 #define DEBUG_TYPE "SLP" 108 109 STATISTIC(NumVectorInstructions, "Number of vector instructions generated"); 110 111 cl::opt<bool> RunSLPVectorization("vectorize-slp", cl::init(true), cl::Hidden, 112 cl::desc("Run the SLP vectorization passes")); 113 114 static cl::opt<int> 115 SLPCostThreshold("slp-threshold", cl::init(0), cl::Hidden, 116 cl::desc("Only vectorize if you gain more than this " 117 "number ")); 118 119 static cl::opt<bool> 120 ShouldVectorizeHor("slp-vectorize-hor", cl::init(true), cl::Hidden, 121 cl::desc("Attempt to vectorize horizontal reductions")); 122 123 static cl::opt<bool> ShouldStartVectorizeHorAtStore( 124 "slp-vectorize-hor-store", cl::init(false), cl::Hidden, 125 cl::desc( 126 "Attempt to vectorize horizontal reductions feeding into a store")); 127 128 static cl::opt<int> 129 MaxVectorRegSizeOption("slp-max-reg-size", cl::init(128), cl::Hidden, 130 cl::desc("Attempt to vectorize for this register size in bits")); 131 132 static cl::opt<int> 133 MaxStoreLookup("slp-max-store-lookup", cl::init(32), cl::Hidden, 134 cl::desc("Maximum depth of the lookup for consecutive stores.")); 135 136 /// Limits the size of scheduling regions in a block. 137 /// It avoid long compile times for _very_ large blocks where vector 138 /// instructions are spread over a wide range. 139 /// This limit is way higher than needed by real-world functions. 140 static cl::opt<int> 141 ScheduleRegionSizeBudget("slp-schedule-budget", cl::init(100000), cl::Hidden, 142 cl::desc("Limit the size of the SLP scheduling region per block")); 143 144 static cl::opt<int> MinVectorRegSizeOption( 145 "slp-min-reg-size", cl::init(128), cl::Hidden, 146 cl::desc("Attempt to vectorize for this register size in bits")); 147 148 static cl::opt<unsigned> RecursionMaxDepth( 149 "slp-recursion-max-depth", cl::init(12), cl::Hidden, 150 cl::desc("Limit the recursion depth when building a vectorizable tree")); 151 152 static cl::opt<unsigned> MinTreeSize( 153 "slp-min-tree-size", cl::init(3), cl::Hidden, 154 cl::desc("Only vectorize small trees if they are fully vectorizable")); 155 156 // The maximum depth that the look-ahead score heuristic will explore. 157 // The higher this value, the higher the compilation time overhead. 158 static cl::opt<int> LookAheadMaxDepth( 159 "slp-max-look-ahead-depth", cl::init(2), cl::Hidden, 160 cl::desc("The maximum look-ahead depth for operand reordering scores")); 161 162 // The Look-ahead heuristic goes through the users of the bundle to calculate 163 // the users cost in getExternalUsesCost(). To avoid compilation time increase 164 // we limit the number of users visited to this value. 165 static cl::opt<unsigned> LookAheadUsersBudget( 166 "slp-look-ahead-users-budget", cl::init(2), cl::Hidden, 167 cl::desc("The maximum number of users to visit while visiting the " 168 "predecessors. This prevents compilation time increase.")); 169 170 static cl::opt<bool> 171 ViewSLPTree("view-slp-tree", cl::Hidden, 172 cl::desc("Display the SLP trees with Graphviz")); 173 174 // Limit the number of alias checks. The limit is chosen so that 175 // it has no negative effect on the llvm benchmarks. 176 static const unsigned AliasedCheckLimit = 10; 177 178 // Another limit for the alias checks: The maximum distance between load/store 179 // instructions where alias checks are done. 180 // This limit is useful for very large basic blocks. 181 static const unsigned MaxMemDepDistance = 160; 182 183 /// If the ScheduleRegionSizeBudget is exhausted, we allow small scheduling 184 /// regions to be handled. 185 static const int MinScheduleRegionSize = 16; 186 187 /// Predicate for the element types that the SLP vectorizer supports. 188 /// 189 /// The most important thing to filter here are types which are invalid in LLVM 190 /// vectors. We also filter target specific types which have absolutely no 191 /// meaningful vectorization path such as x86_fp80 and ppc_f128. This just 192 /// avoids spending time checking the cost model and realizing that they will 193 /// be inevitably scalarized. 194 static bool isValidElementType(Type *Ty) { 195 return VectorType::isValidElementType(Ty) && !Ty->isX86_FP80Ty() && 196 !Ty->isPPC_FP128Ty(); 197 } 198 199 /// \returns true if all of the instructions in \p VL are in the same block or 200 /// false otherwise. 201 static bool allSameBlock(ArrayRef<Value *> VL) { 202 Instruction *I0 = dyn_cast<Instruction>(VL[0]); 203 if (!I0) 204 return false; 205 BasicBlock *BB = I0->getParent(); 206 for (int i = 1, e = VL.size(); i < e; i++) { 207 Instruction *I = dyn_cast<Instruction>(VL[i]); 208 if (!I) 209 return false; 210 211 if (BB != I->getParent()) 212 return false; 213 } 214 return true; 215 } 216 217 /// \returns True if all of the values in \p VL are constants (but not 218 /// globals/constant expressions). 219 static bool allConstant(ArrayRef<Value *> VL) { 220 // Constant expressions and globals can't be vectorized like normal integer/FP 221 // constants. 222 for (Value *i : VL) 223 if (!isa<Constant>(i) || isa<ConstantExpr>(i) || isa<GlobalValue>(i)) 224 return false; 225 return true; 226 } 227 228 /// \returns True if all of the values in \p VL are identical. 229 static bool isSplat(ArrayRef<Value *> VL) { 230 for (unsigned i = 1, e = VL.size(); i < e; ++i) 231 if (VL[i] != VL[0]) 232 return false; 233 return true; 234 } 235 236 /// \returns True if \p I is commutative, handles CmpInst as well as Instruction. 237 static bool isCommutative(Instruction *I) { 238 if (auto *IC = dyn_cast<CmpInst>(I)) 239 return IC->isCommutative(); 240 return I->isCommutative(); 241 } 242 243 /// Checks if the vector of instructions can be represented as a shuffle, like: 244 /// %x0 = extractelement <4 x i8> %x, i32 0 245 /// %x3 = extractelement <4 x i8> %x, i32 3 246 /// %y1 = extractelement <4 x i8> %y, i32 1 247 /// %y2 = extractelement <4 x i8> %y, i32 2 248 /// %x0x0 = mul i8 %x0, %x0 249 /// %x3x3 = mul i8 %x3, %x3 250 /// %y1y1 = mul i8 %y1, %y1 251 /// %y2y2 = mul i8 %y2, %y2 252 /// %ins1 = insertelement <4 x i8> undef, i8 %x0x0, i32 0 253 /// %ins2 = insertelement <4 x i8> %ins1, i8 %x3x3, i32 1 254 /// %ins3 = insertelement <4 x i8> %ins2, i8 %y1y1, i32 2 255 /// %ins4 = insertelement <4 x i8> %ins3, i8 %y2y2, i32 3 256 /// ret <4 x i8> %ins4 257 /// can be transformed into: 258 /// %1 = shufflevector <4 x i8> %x, <4 x i8> %y, <4 x i32> <i32 0, i32 3, i32 5, 259 /// i32 6> 260 /// %2 = mul <4 x i8> %1, %1 261 /// ret <4 x i8> %2 262 /// We convert this initially to something like: 263 /// %x0 = extractelement <4 x i8> %x, i32 0 264 /// %x3 = extractelement <4 x i8> %x, i32 3 265 /// %y1 = extractelement <4 x i8> %y, i32 1 266 /// %y2 = extractelement <4 x i8> %y, i32 2 267 /// %1 = insertelement <4 x i8> undef, i8 %x0, i32 0 268 /// %2 = insertelement <4 x i8> %1, i8 %x3, i32 1 269 /// %3 = insertelement <4 x i8> %2, i8 %y1, i32 2 270 /// %4 = insertelement <4 x i8> %3, i8 %y2, i32 3 271 /// %5 = mul <4 x i8> %4, %4 272 /// %6 = extractelement <4 x i8> %5, i32 0 273 /// %ins1 = insertelement <4 x i8> undef, i8 %6, i32 0 274 /// %7 = extractelement <4 x i8> %5, i32 1 275 /// %ins2 = insertelement <4 x i8> %ins1, i8 %7, i32 1 276 /// %8 = extractelement <4 x i8> %5, i32 2 277 /// %ins3 = insertelement <4 x i8> %ins2, i8 %8, i32 2 278 /// %9 = extractelement <4 x i8> %5, i32 3 279 /// %ins4 = insertelement <4 x i8> %ins3, i8 %9, i32 3 280 /// ret <4 x i8> %ins4 281 /// InstCombiner transforms this into a shuffle and vector mul 282 /// TODO: Can we split off and reuse the shuffle mask detection from 283 /// TargetTransformInfo::getInstructionThroughput? 284 static Optional<TargetTransformInfo::ShuffleKind> 285 isShuffle(ArrayRef<Value *> VL) { 286 auto *EI0 = cast<ExtractElementInst>(VL[0]); 287 unsigned Size = EI0->getVectorOperandType()->getNumElements(); 288 Value *Vec1 = nullptr; 289 Value *Vec2 = nullptr; 290 enum ShuffleMode { Unknown, Select, Permute }; 291 ShuffleMode CommonShuffleMode = Unknown; 292 for (unsigned I = 0, E = VL.size(); I < E; ++I) { 293 auto *EI = cast<ExtractElementInst>(VL[I]); 294 auto *Vec = EI->getVectorOperand(); 295 // All vector operands must have the same number of vector elements. 296 if (cast<VectorType>(Vec->getType())->getNumElements() != Size) 297 return None; 298 auto *Idx = dyn_cast<ConstantInt>(EI->getIndexOperand()); 299 if (!Idx) 300 return None; 301 // Undefined behavior if Idx is negative or >= Size. 302 if (Idx->getValue().uge(Size)) 303 continue; 304 unsigned IntIdx = Idx->getValue().getZExtValue(); 305 // We can extractelement from undef vector. 306 if (isa<UndefValue>(Vec)) 307 continue; 308 // For correct shuffling we have to have at most 2 different vector operands 309 // in all extractelement instructions. 310 if (!Vec1 || Vec1 == Vec) 311 Vec1 = Vec; 312 else if (!Vec2 || Vec2 == Vec) 313 Vec2 = Vec; 314 else 315 return None; 316 if (CommonShuffleMode == Permute) 317 continue; 318 // If the extract index is not the same as the operation number, it is a 319 // permutation. 320 if (IntIdx != I) { 321 CommonShuffleMode = Permute; 322 continue; 323 } 324 CommonShuffleMode = Select; 325 } 326 // If we're not crossing lanes in different vectors, consider it as blending. 327 if (CommonShuffleMode == Select && Vec2) 328 return TargetTransformInfo::SK_Select; 329 // If Vec2 was never used, we have a permutation of a single vector, otherwise 330 // we have permutation of 2 vectors. 331 return Vec2 ? TargetTransformInfo::SK_PermuteTwoSrc 332 : TargetTransformInfo::SK_PermuteSingleSrc; 333 } 334 335 namespace { 336 337 /// Main data required for vectorization of instructions. 338 struct InstructionsState { 339 /// The very first instruction in the list with the main opcode. 340 Value *OpValue = nullptr; 341 342 /// The main/alternate instruction. 343 Instruction *MainOp = nullptr; 344 Instruction *AltOp = nullptr; 345 346 /// The main/alternate opcodes for the list of instructions. 347 unsigned getOpcode() const { 348 return MainOp ? MainOp->getOpcode() : 0; 349 } 350 351 unsigned getAltOpcode() const { 352 return AltOp ? AltOp->getOpcode() : 0; 353 } 354 355 /// Some of the instructions in the list have alternate opcodes. 356 bool isAltShuffle() const { return getOpcode() != getAltOpcode(); } 357 358 bool isOpcodeOrAlt(Instruction *I) const { 359 unsigned CheckedOpcode = I->getOpcode(); 360 return getOpcode() == CheckedOpcode || getAltOpcode() == CheckedOpcode; 361 } 362 363 InstructionsState() = delete; 364 InstructionsState(Value *OpValue, Instruction *MainOp, Instruction *AltOp) 365 : OpValue(OpValue), MainOp(MainOp), AltOp(AltOp) {} 366 }; 367 368 } // end anonymous namespace 369 370 /// Chooses the correct key for scheduling data. If \p Op has the same (or 371 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is \p 372 /// OpValue. 373 static Value *isOneOf(const InstructionsState &S, Value *Op) { 374 auto *I = dyn_cast<Instruction>(Op); 375 if (I && S.isOpcodeOrAlt(I)) 376 return Op; 377 return S.OpValue; 378 } 379 380 /// \returns true if \p Opcode is allowed as part of of the main/alternate 381 /// instruction for SLP vectorization. 382 /// 383 /// Example of unsupported opcode is SDIV that can potentially cause UB if the 384 /// "shuffled out" lane would result in division by zero. 385 static bool isValidForAlternation(unsigned Opcode) { 386 if (Instruction::isIntDivRem(Opcode)) 387 return false; 388 389 return true; 390 } 391 392 /// \returns analysis of the Instructions in \p VL described in 393 /// InstructionsState, the Opcode that we suppose the whole list 394 /// could be vectorized even if its structure is diverse. 395 static InstructionsState getSameOpcode(ArrayRef<Value *> VL, 396 unsigned BaseIndex = 0) { 397 // Make sure these are all Instructions. 398 if (llvm::any_of(VL, [](Value *V) { return !isa<Instruction>(V); })) 399 return InstructionsState(VL[BaseIndex], nullptr, nullptr); 400 401 bool IsCastOp = isa<CastInst>(VL[BaseIndex]); 402 bool IsBinOp = isa<BinaryOperator>(VL[BaseIndex]); 403 unsigned Opcode = cast<Instruction>(VL[BaseIndex])->getOpcode(); 404 unsigned AltOpcode = Opcode; 405 unsigned AltIndex = BaseIndex; 406 407 // Check for one alternate opcode from another BinaryOperator. 408 // TODO - generalize to support all operators (types, calls etc.). 409 for (int Cnt = 0, E = VL.size(); Cnt < E; Cnt++) { 410 unsigned InstOpcode = cast<Instruction>(VL[Cnt])->getOpcode(); 411 if (IsBinOp && isa<BinaryOperator>(VL[Cnt])) { 412 if (InstOpcode == Opcode || InstOpcode == AltOpcode) 413 continue; 414 if (Opcode == AltOpcode && isValidForAlternation(InstOpcode) && 415 isValidForAlternation(Opcode)) { 416 AltOpcode = InstOpcode; 417 AltIndex = Cnt; 418 continue; 419 } 420 } else if (IsCastOp && isa<CastInst>(VL[Cnt])) { 421 Type *Ty0 = cast<Instruction>(VL[BaseIndex])->getOperand(0)->getType(); 422 Type *Ty1 = cast<Instruction>(VL[Cnt])->getOperand(0)->getType(); 423 if (Ty0 == Ty1) { 424 if (InstOpcode == Opcode || InstOpcode == AltOpcode) 425 continue; 426 if (Opcode == AltOpcode) { 427 assert(isValidForAlternation(Opcode) && 428 isValidForAlternation(InstOpcode) && 429 "Cast isn't safe for alternation, logic needs to be updated!"); 430 AltOpcode = InstOpcode; 431 AltIndex = Cnt; 432 continue; 433 } 434 } 435 } else if (InstOpcode == Opcode || InstOpcode == AltOpcode) 436 continue; 437 return InstructionsState(VL[BaseIndex], nullptr, nullptr); 438 } 439 440 return InstructionsState(VL[BaseIndex], cast<Instruction>(VL[BaseIndex]), 441 cast<Instruction>(VL[AltIndex])); 442 } 443 444 /// \returns true if all of the values in \p VL have the same type or false 445 /// otherwise. 446 static bool allSameType(ArrayRef<Value *> VL) { 447 Type *Ty = VL[0]->getType(); 448 for (int i = 1, e = VL.size(); i < e; i++) 449 if (VL[i]->getType() != Ty) 450 return false; 451 452 return true; 453 } 454 455 /// \returns True if Extract{Value,Element} instruction extracts element Idx. 456 static Optional<unsigned> getExtractIndex(Instruction *E) { 457 unsigned Opcode = E->getOpcode(); 458 assert((Opcode == Instruction::ExtractElement || 459 Opcode == Instruction::ExtractValue) && 460 "Expected extractelement or extractvalue instruction."); 461 if (Opcode == Instruction::ExtractElement) { 462 auto *CI = dyn_cast<ConstantInt>(E->getOperand(1)); 463 if (!CI) 464 return None; 465 return CI->getZExtValue(); 466 } 467 ExtractValueInst *EI = cast<ExtractValueInst>(E); 468 if (EI->getNumIndices() != 1) 469 return None; 470 return *EI->idx_begin(); 471 } 472 473 /// \returns True if in-tree use also needs extract. This refers to 474 /// possible scalar operand in vectorized instruction. 475 static bool InTreeUserNeedToExtract(Value *Scalar, Instruction *UserInst, 476 TargetLibraryInfo *TLI) { 477 unsigned Opcode = UserInst->getOpcode(); 478 switch (Opcode) { 479 case Instruction::Load: { 480 LoadInst *LI = cast<LoadInst>(UserInst); 481 return (LI->getPointerOperand() == Scalar); 482 } 483 case Instruction::Store: { 484 StoreInst *SI = cast<StoreInst>(UserInst); 485 return (SI->getPointerOperand() == Scalar); 486 } 487 case Instruction::Call: { 488 CallInst *CI = cast<CallInst>(UserInst); 489 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 490 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 491 if (hasVectorInstrinsicScalarOpd(ID, i)) 492 return (CI->getArgOperand(i) == Scalar); 493 } 494 LLVM_FALLTHROUGH; 495 } 496 default: 497 return false; 498 } 499 } 500 501 /// \returns the AA location that is being access by the instruction. 502 static MemoryLocation getLocation(Instruction *I, AliasAnalysis *AA) { 503 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 504 return MemoryLocation::get(SI); 505 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 506 return MemoryLocation::get(LI); 507 return MemoryLocation(); 508 } 509 510 /// \returns True if the instruction is not a volatile or atomic load/store. 511 static bool isSimple(Instruction *I) { 512 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 513 return LI->isSimple(); 514 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 515 return SI->isSimple(); 516 if (MemIntrinsic *MI = dyn_cast<MemIntrinsic>(I)) 517 return !MI->isVolatile(); 518 return true; 519 } 520 521 namespace llvm { 522 523 namespace slpvectorizer { 524 525 /// Bottom Up SLP Vectorizer. 526 class BoUpSLP { 527 struct TreeEntry; 528 struct ScheduleData; 529 530 public: 531 using ValueList = SmallVector<Value *, 8>; 532 using InstrList = SmallVector<Instruction *, 16>; 533 using ValueSet = SmallPtrSet<Value *, 16>; 534 using StoreList = SmallVector<StoreInst *, 8>; 535 using ExtraValueToDebugLocsMap = 536 MapVector<Value *, SmallVector<Instruction *, 2>>; 537 538 BoUpSLP(Function *Func, ScalarEvolution *Se, TargetTransformInfo *Tti, 539 TargetLibraryInfo *TLi, AliasAnalysis *Aa, LoopInfo *Li, 540 DominatorTree *Dt, AssumptionCache *AC, DemandedBits *DB, 541 const DataLayout *DL, OptimizationRemarkEmitter *ORE) 542 : F(Func), SE(Se), TTI(Tti), TLI(TLi), AA(Aa), LI(Li), DT(Dt), AC(AC), 543 DB(DB), DL(DL), ORE(ORE), Builder(Se->getContext()) { 544 CodeMetrics::collectEphemeralValues(F, AC, EphValues); 545 // Use the vector register size specified by the target unless overridden 546 // by a command-line option. 547 // TODO: It would be better to limit the vectorization factor based on 548 // data type rather than just register size. For example, x86 AVX has 549 // 256-bit registers, but it does not support integer operations 550 // at that width (that requires AVX2). 551 if (MaxVectorRegSizeOption.getNumOccurrences()) 552 MaxVecRegSize = MaxVectorRegSizeOption; 553 else 554 MaxVecRegSize = TTI->getRegisterBitWidth(true); 555 556 if (MinVectorRegSizeOption.getNumOccurrences()) 557 MinVecRegSize = MinVectorRegSizeOption; 558 else 559 MinVecRegSize = TTI->getMinVectorRegisterBitWidth(); 560 } 561 562 /// Vectorize the tree that starts with the elements in \p VL. 563 /// Returns the vectorized root. 564 Value *vectorizeTree(); 565 566 /// Vectorize the tree but with the list of externally used values \p 567 /// ExternallyUsedValues. Values in this MapVector can be replaced but the 568 /// generated extractvalue instructions. 569 Value *vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues); 570 571 /// \returns the cost incurred by unwanted spills and fills, caused by 572 /// holding live values over call sites. 573 int getSpillCost() const; 574 575 /// \returns the vectorization cost of the subtree that starts at \p VL. 576 /// A negative number means that this is profitable. 577 int getTreeCost(); 578 579 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 580 /// the purpose of scheduling and extraction in the \p UserIgnoreLst. 581 void buildTree(ArrayRef<Value *> Roots, 582 ArrayRef<Value *> UserIgnoreLst = None); 583 584 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 585 /// the purpose of scheduling and extraction in the \p UserIgnoreLst taking 586 /// into account (and updating it, if required) list of externally used 587 /// values stored in \p ExternallyUsedValues. 588 void buildTree(ArrayRef<Value *> Roots, 589 ExtraValueToDebugLocsMap &ExternallyUsedValues, 590 ArrayRef<Value *> UserIgnoreLst = None); 591 592 /// Clear the internal data structures that are created by 'buildTree'. 593 void deleteTree() { 594 VectorizableTree.clear(); 595 ScalarToTreeEntry.clear(); 596 MustGather.clear(); 597 ExternalUses.clear(); 598 NumOpsWantToKeepOrder.clear(); 599 NumOpsWantToKeepOriginalOrder = 0; 600 for (auto &Iter : BlocksSchedules) { 601 BlockScheduling *BS = Iter.second.get(); 602 BS->clear(); 603 } 604 MinBWs.clear(); 605 } 606 607 unsigned getTreeSize() const { return VectorizableTree.size(); } 608 609 /// Perform LICM and CSE on the newly generated gather sequences. 610 void optimizeGatherSequence(); 611 612 /// \returns The best order of instructions for vectorization. 613 Optional<ArrayRef<unsigned>> bestOrder() const { 614 auto I = std::max_element( 615 NumOpsWantToKeepOrder.begin(), NumOpsWantToKeepOrder.end(), 616 [](const decltype(NumOpsWantToKeepOrder)::value_type &D1, 617 const decltype(NumOpsWantToKeepOrder)::value_type &D2) { 618 return D1.second < D2.second; 619 }); 620 if (I == NumOpsWantToKeepOrder.end() || 621 I->getSecond() <= NumOpsWantToKeepOriginalOrder) 622 return None; 623 624 return makeArrayRef(I->getFirst()); 625 } 626 627 /// \return The vector element size in bits to use when vectorizing the 628 /// expression tree ending at \p V. If V is a store, the size is the width of 629 /// the stored value. Otherwise, the size is the width of the largest loaded 630 /// value reaching V. This method is used by the vectorizer to calculate 631 /// vectorization factors. 632 unsigned getVectorElementSize(Value *V) const; 633 634 /// Compute the minimum type sizes required to represent the entries in a 635 /// vectorizable tree. 636 void computeMinimumValueSizes(); 637 638 // \returns maximum vector register size as set by TTI or overridden by cl::opt. 639 unsigned getMaxVecRegSize() const { 640 return MaxVecRegSize; 641 } 642 643 // \returns minimum vector register size as set by cl::opt. 644 unsigned getMinVecRegSize() const { 645 return MinVecRegSize; 646 } 647 648 /// Check if homogeneous aggregate is isomorphic to some VectorType. 649 /// Accepts homogeneous multidimensional aggregate of scalars/vectors like 650 /// {[4 x i16], [4 x i16]}, { <2 x float>, <2 x float> }, 651 /// {{{i16, i16}, {i16, i16}}, {{i16, i16}, {i16, i16}}} and so on. 652 /// 653 /// \returns number of elements in vector if isomorphism exists, 0 otherwise. 654 unsigned canMapToVector(Type *T, const DataLayout &DL) const; 655 656 /// \returns True if the VectorizableTree is both tiny and not fully 657 /// vectorizable. We do not vectorize such trees. 658 bool isTreeTinyAndNotFullyVectorizable() const; 659 660 /// Assume that a legal-sized 'or'-reduction of shifted/zexted loaded values 661 /// can be load combined in the backend. Load combining may not be allowed in 662 /// the IR optimizer, so we do not want to alter the pattern. For example, 663 /// partially transforming a scalar bswap() pattern into vector code is 664 /// effectively impossible for the backend to undo. 665 /// TODO: If load combining is allowed in the IR optimizer, this analysis 666 /// may not be necessary. 667 bool isLoadCombineReductionCandidate(unsigned ReductionOpcode) const; 668 669 OptimizationRemarkEmitter *getORE() { return ORE; } 670 671 /// This structure holds any data we need about the edges being traversed 672 /// during buildTree_rec(). We keep track of: 673 /// (i) the user TreeEntry index, and 674 /// (ii) the index of the edge. 675 struct EdgeInfo { 676 EdgeInfo() = default; 677 EdgeInfo(TreeEntry *UserTE, unsigned EdgeIdx) 678 : UserTE(UserTE), EdgeIdx(EdgeIdx) {} 679 /// The user TreeEntry. 680 TreeEntry *UserTE = nullptr; 681 /// The operand index of the use. 682 unsigned EdgeIdx = UINT_MAX; 683 #ifndef NDEBUG 684 friend inline raw_ostream &operator<<(raw_ostream &OS, 685 const BoUpSLP::EdgeInfo &EI) { 686 EI.dump(OS); 687 return OS; 688 } 689 /// Debug print. 690 void dump(raw_ostream &OS) const { 691 OS << "{User:" << (UserTE ? std::to_string(UserTE->Idx) : "null") 692 << " EdgeIdx:" << EdgeIdx << "}"; 693 } 694 LLVM_DUMP_METHOD void dump() const { dump(dbgs()); } 695 #endif 696 }; 697 698 /// A helper data structure to hold the operands of a vector of instructions. 699 /// This supports a fixed vector length for all operand vectors. 700 class VLOperands { 701 /// For each operand we need (i) the value, and (ii) the opcode that it 702 /// would be attached to if the expression was in a left-linearized form. 703 /// This is required to avoid illegal operand reordering. 704 /// For example: 705 /// \verbatim 706 /// 0 Op1 707 /// |/ 708 /// Op1 Op2 Linearized + Op2 709 /// \ / ----------> |/ 710 /// - - 711 /// 712 /// Op1 - Op2 (0 + Op1) - Op2 713 /// \endverbatim 714 /// 715 /// Value Op1 is attached to a '+' operation, and Op2 to a '-'. 716 /// 717 /// Another way to think of this is to track all the operations across the 718 /// path from the operand all the way to the root of the tree and to 719 /// calculate the operation that corresponds to this path. For example, the 720 /// path from Op2 to the root crosses the RHS of the '-', therefore the 721 /// corresponding operation is a '-' (which matches the one in the 722 /// linearized tree, as shown above). 723 /// 724 /// For lack of a better term, we refer to this operation as Accumulated 725 /// Path Operation (APO). 726 struct OperandData { 727 OperandData() = default; 728 OperandData(Value *V, bool APO, bool IsUsed) 729 : V(V), APO(APO), IsUsed(IsUsed) {} 730 /// The operand value. 731 Value *V = nullptr; 732 /// TreeEntries only allow a single opcode, or an alternate sequence of 733 /// them (e.g, +, -). Therefore, we can safely use a boolean value for the 734 /// APO. It is set to 'true' if 'V' is attached to an inverse operation 735 /// in the left-linearized form (e.g., Sub/Div), and 'false' otherwise 736 /// (e.g., Add/Mul) 737 bool APO = false; 738 /// Helper data for the reordering function. 739 bool IsUsed = false; 740 }; 741 742 /// During operand reordering, we are trying to select the operand at lane 743 /// that matches best with the operand at the neighboring lane. Our 744 /// selection is based on the type of value we are looking for. For example, 745 /// if the neighboring lane has a load, we need to look for a load that is 746 /// accessing a consecutive address. These strategies are summarized in the 747 /// 'ReorderingMode' enumerator. 748 enum class ReorderingMode { 749 Load, ///< Matching loads to consecutive memory addresses 750 Opcode, ///< Matching instructions based on opcode (same or alternate) 751 Constant, ///< Matching constants 752 Splat, ///< Matching the same instruction multiple times (broadcast) 753 Failed, ///< We failed to create a vectorizable group 754 }; 755 756 using OperandDataVec = SmallVector<OperandData, 2>; 757 758 /// A vector of operand vectors. 759 SmallVector<OperandDataVec, 4> OpsVec; 760 761 const DataLayout &DL; 762 ScalarEvolution &SE; 763 const BoUpSLP &R; 764 765 /// \returns the operand data at \p OpIdx and \p Lane. 766 OperandData &getData(unsigned OpIdx, unsigned Lane) { 767 return OpsVec[OpIdx][Lane]; 768 } 769 770 /// \returns the operand data at \p OpIdx and \p Lane. Const version. 771 const OperandData &getData(unsigned OpIdx, unsigned Lane) const { 772 return OpsVec[OpIdx][Lane]; 773 } 774 775 /// Clears the used flag for all entries. 776 void clearUsed() { 777 for (unsigned OpIdx = 0, NumOperands = getNumOperands(); 778 OpIdx != NumOperands; ++OpIdx) 779 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 780 ++Lane) 781 OpsVec[OpIdx][Lane].IsUsed = false; 782 } 783 784 /// Swap the operand at \p OpIdx1 with that one at \p OpIdx2. 785 void swap(unsigned OpIdx1, unsigned OpIdx2, unsigned Lane) { 786 std::swap(OpsVec[OpIdx1][Lane], OpsVec[OpIdx2][Lane]); 787 } 788 789 // The hard-coded scores listed here are not very important. When computing 790 // the scores of matching one sub-tree with another, we are basically 791 // counting the number of values that are matching. So even if all scores 792 // are set to 1, we would still get a decent matching result. 793 // However, sometimes we have to break ties. For example we may have to 794 // choose between matching loads vs matching opcodes. This is what these 795 // scores are helping us with: they provide the order of preference. 796 797 /// Loads from consecutive memory addresses, e.g. load(A[i]), load(A[i+1]). 798 static const int ScoreConsecutiveLoads = 3; 799 /// ExtractElementInst from same vector and consecutive indexes. 800 static const int ScoreConsecutiveExtracts = 3; 801 /// Constants. 802 static const int ScoreConstants = 2; 803 /// Instructions with the same opcode. 804 static const int ScoreSameOpcode = 2; 805 /// Instructions with alt opcodes (e.g, add + sub). 806 static const int ScoreAltOpcodes = 1; 807 /// Identical instructions (a.k.a. splat or broadcast). 808 static const int ScoreSplat = 1; 809 /// Matching with an undef is preferable to failing. 810 static const int ScoreUndef = 1; 811 /// Score for failing to find a decent match. 812 static const int ScoreFail = 0; 813 /// User exteranl to the vectorized code. 814 static const int ExternalUseCost = 1; 815 /// The user is internal but in a different lane. 816 static const int UserInDiffLaneCost = ExternalUseCost; 817 818 /// \returns the score of placing \p V1 and \p V2 in consecutive lanes. 819 static int getShallowScore(Value *V1, Value *V2, const DataLayout &DL, 820 ScalarEvolution &SE) { 821 auto *LI1 = dyn_cast<LoadInst>(V1); 822 auto *LI2 = dyn_cast<LoadInst>(V2); 823 if (LI1 && LI2) 824 return isConsecutiveAccess(LI1, LI2, DL, SE) 825 ? VLOperands::ScoreConsecutiveLoads 826 : VLOperands::ScoreFail; 827 828 auto *C1 = dyn_cast<Constant>(V1); 829 auto *C2 = dyn_cast<Constant>(V2); 830 if (C1 && C2) 831 return VLOperands::ScoreConstants; 832 833 // Extracts from consecutive indexes of the same vector better score as 834 // the extracts could be optimized away. 835 Value *EV; 836 ConstantInt *Ex1Idx, *Ex2Idx; 837 if (match(V1, m_ExtractElement(m_Value(EV), m_ConstantInt(Ex1Idx))) && 838 match(V2, m_ExtractElement(m_Deferred(EV), m_ConstantInt(Ex2Idx))) && 839 Ex1Idx->getZExtValue() + 1 == Ex2Idx->getZExtValue()) 840 return VLOperands::ScoreConsecutiveExtracts; 841 842 auto *I1 = dyn_cast<Instruction>(V1); 843 auto *I2 = dyn_cast<Instruction>(V2); 844 if (I1 && I2) { 845 if (I1 == I2) 846 return VLOperands::ScoreSplat; 847 InstructionsState S = getSameOpcode({I1, I2}); 848 // Note: Only consider instructions with <= 2 operands to avoid 849 // complexity explosion. 850 if (S.getOpcode() && S.MainOp->getNumOperands() <= 2) 851 return S.isAltShuffle() ? VLOperands::ScoreAltOpcodes 852 : VLOperands::ScoreSameOpcode; 853 } 854 855 if (isa<UndefValue>(V2)) 856 return VLOperands::ScoreUndef; 857 858 return VLOperands::ScoreFail; 859 } 860 861 /// Holds the values and their lane that are taking part in the look-ahead 862 /// score calculation. This is used in the external uses cost calculation. 863 SmallDenseMap<Value *, int> InLookAheadValues; 864 865 /// \Returns the additinal cost due to uses of \p LHS and \p RHS that are 866 /// either external to the vectorized code, or require shuffling. 867 int getExternalUsesCost(const std::pair<Value *, int> &LHS, 868 const std::pair<Value *, int> &RHS) { 869 int Cost = 0; 870 std::array<std::pair<Value *, int>, 2> Values = {{LHS, RHS}}; 871 for (int Idx = 0, IdxE = Values.size(); Idx != IdxE; ++Idx) { 872 Value *V = Values[Idx].first; 873 // Calculate the absolute lane, using the minimum relative lane of LHS 874 // and RHS as base and Idx as the offset. 875 int Ln = std::min(LHS.second, RHS.second) + Idx; 876 assert(Ln >= 0 && "Bad lane calculation"); 877 unsigned UsersBudget = LookAheadUsersBudget; 878 for (User *U : V->users()) { 879 if (const TreeEntry *UserTE = R.getTreeEntry(U)) { 880 // The user is in the VectorizableTree. Check if we need to insert. 881 auto It = llvm::find(UserTE->Scalars, U); 882 assert(It != UserTE->Scalars.end() && "U is in UserTE"); 883 int UserLn = std::distance(UserTE->Scalars.begin(), It); 884 assert(UserLn >= 0 && "Bad lane"); 885 if (UserLn != Ln) 886 Cost += UserInDiffLaneCost; 887 } else { 888 // Check if the user is in the look-ahead code. 889 auto It2 = InLookAheadValues.find(U); 890 if (It2 != InLookAheadValues.end()) { 891 // The user is in the look-ahead code. Check the lane. 892 if (It2->second != Ln) 893 Cost += UserInDiffLaneCost; 894 } else { 895 // The user is neither in SLP tree nor in the look-ahead code. 896 Cost += ExternalUseCost; 897 } 898 } 899 // Limit the number of visited uses to cap compilation time. 900 if (--UsersBudget == 0) 901 break; 902 } 903 } 904 return Cost; 905 } 906 907 /// Go through the operands of \p LHS and \p RHS recursively until \p 908 /// MaxLevel, and return the cummulative score. For example: 909 /// \verbatim 910 /// A[0] B[0] A[1] B[1] C[0] D[0] B[1] A[1] 911 /// \ / \ / \ / \ / 912 /// + + + + 913 /// G1 G2 G3 G4 914 /// \endverbatim 915 /// The getScoreAtLevelRec(G1, G2) function will try to match the nodes at 916 /// each level recursively, accumulating the score. It starts from matching 917 /// the additions at level 0, then moves on to the loads (level 1). The 918 /// score of G1 and G2 is higher than G1 and G3, because {A[0],A[1]} and 919 /// {B[0],B[1]} match with VLOperands::ScoreConsecutiveLoads, while 920 /// {A[0],C[0]} has a score of VLOperands::ScoreFail. 921 /// Please note that the order of the operands does not matter, as we 922 /// evaluate the score of all profitable combinations of operands. In 923 /// other words the score of G1 and G4 is the same as G1 and G2. This 924 /// heuristic is based on ideas described in: 925 /// Look-ahead SLP: Auto-vectorization in the presence of commutative 926 /// operations, CGO 2018 by Vasileios Porpodas, Rodrigo C. O. Rocha, 927 /// Luís F. W. Góes 928 int getScoreAtLevelRec(const std::pair<Value *, int> &LHS, 929 const std::pair<Value *, int> &RHS, int CurrLevel, 930 int MaxLevel) { 931 932 Value *V1 = LHS.first; 933 Value *V2 = RHS.first; 934 // Get the shallow score of V1 and V2. 935 int ShallowScoreAtThisLevel = 936 std::max((int)ScoreFail, getShallowScore(V1, V2, DL, SE) - 937 getExternalUsesCost(LHS, RHS)); 938 int Lane1 = LHS.second; 939 int Lane2 = RHS.second; 940 941 // If reached MaxLevel, 942 // or if V1 and V2 are not instructions, 943 // or if they are SPLAT, 944 // or if they are not consecutive, early return the current cost. 945 auto *I1 = dyn_cast<Instruction>(V1); 946 auto *I2 = dyn_cast<Instruction>(V2); 947 if (CurrLevel == MaxLevel || !(I1 && I2) || I1 == I2 || 948 ShallowScoreAtThisLevel == VLOperands::ScoreFail || 949 (isa<LoadInst>(I1) && isa<LoadInst>(I2) && ShallowScoreAtThisLevel)) 950 return ShallowScoreAtThisLevel; 951 assert(I1 && I2 && "Should have early exited."); 952 953 // Keep track of in-tree values for determining the external-use cost. 954 InLookAheadValues[V1] = Lane1; 955 InLookAheadValues[V2] = Lane2; 956 957 // Contains the I2 operand indexes that got matched with I1 operands. 958 SmallSet<unsigned, 4> Op2Used; 959 960 // Recursion towards the operands of I1 and I2. We are trying all possbile 961 // operand pairs, and keeping track of the best score. 962 for (unsigned OpIdx1 = 0, NumOperands1 = I1->getNumOperands(); 963 OpIdx1 != NumOperands1; ++OpIdx1) { 964 // Try to pair op1I with the best operand of I2. 965 int MaxTmpScore = 0; 966 unsigned MaxOpIdx2 = 0; 967 bool FoundBest = false; 968 // If I2 is commutative try all combinations. 969 unsigned FromIdx = isCommutative(I2) ? 0 : OpIdx1; 970 unsigned ToIdx = isCommutative(I2) 971 ? I2->getNumOperands() 972 : std::min(I2->getNumOperands(), OpIdx1 + 1); 973 assert(FromIdx <= ToIdx && "Bad index"); 974 for (unsigned OpIdx2 = FromIdx; OpIdx2 != ToIdx; ++OpIdx2) { 975 // Skip operands already paired with OpIdx1. 976 if (Op2Used.count(OpIdx2)) 977 continue; 978 // Recursively calculate the cost at each level 979 int TmpScore = getScoreAtLevelRec({I1->getOperand(OpIdx1), Lane1}, 980 {I2->getOperand(OpIdx2), Lane2}, 981 CurrLevel + 1, MaxLevel); 982 // Look for the best score. 983 if (TmpScore > VLOperands::ScoreFail && TmpScore > MaxTmpScore) { 984 MaxTmpScore = TmpScore; 985 MaxOpIdx2 = OpIdx2; 986 FoundBest = true; 987 } 988 } 989 if (FoundBest) { 990 // Pair {OpIdx1, MaxOpIdx2} was found to be best. Never revisit it. 991 Op2Used.insert(MaxOpIdx2); 992 ShallowScoreAtThisLevel += MaxTmpScore; 993 } 994 } 995 return ShallowScoreAtThisLevel; 996 } 997 998 /// \Returns the look-ahead score, which tells us how much the sub-trees 999 /// rooted at \p LHS and \p RHS match, the more they match the higher the 1000 /// score. This helps break ties in an informed way when we cannot decide on 1001 /// the order of the operands by just considering the immediate 1002 /// predecessors. 1003 int getLookAheadScore(const std::pair<Value *, int> &LHS, 1004 const std::pair<Value *, int> &RHS) { 1005 InLookAheadValues.clear(); 1006 return getScoreAtLevelRec(LHS, RHS, 1, LookAheadMaxDepth); 1007 } 1008 1009 // Search all operands in Ops[*][Lane] for the one that matches best 1010 // Ops[OpIdx][LastLane] and return its opreand index. 1011 // If no good match can be found, return None. 1012 Optional<unsigned> 1013 getBestOperand(unsigned OpIdx, int Lane, int LastLane, 1014 ArrayRef<ReorderingMode> ReorderingModes) { 1015 unsigned NumOperands = getNumOperands(); 1016 1017 // The operand of the previous lane at OpIdx. 1018 Value *OpLastLane = getData(OpIdx, LastLane).V; 1019 1020 // Our strategy mode for OpIdx. 1021 ReorderingMode RMode = ReorderingModes[OpIdx]; 1022 1023 // The linearized opcode of the operand at OpIdx, Lane. 1024 bool OpIdxAPO = getData(OpIdx, Lane).APO; 1025 1026 // The best operand index and its score. 1027 // Sometimes we have more than one option (e.g., Opcode and Undefs), so we 1028 // are using the score to differentiate between the two. 1029 struct BestOpData { 1030 Optional<unsigned> Idx = None; 1031 unsigned Score = 0; 1032 } BestOp; 1033 1034 // Iterate through all unused operands and look for the best. 1035 for (unsigned Idx = 0; Idx != NumOperands; ++Idx) { 1036 // Get the operand at Idx and Lane. 1037 OperandData &OpData = getData(Idx, Lane); 1038 Value *Op = OpData.V; 1039 bool OpAPO = OpData.APO; 1040 1041 // Skip already selected operands. 1042 if (OpData.IsUsed) 1043 continue; 1044 1045 // Skip if we are trying to move the operand to a position with a 1046 // different opcode in the linearized tree form. This would break the 1047 // semantics. 1048 if (OpAPO != OpIdxAPO) 1049 continue; 1050 1051 // Look for an operand that matches the current mode. 1052 switch (RMode) { 1053 case ReorderingMode::Load: 1054 case ReorderingMode::Constant: 1055 case ReorderingMode::Opcode: { 1056 bool LeftToRight = Lane > LastLane; 1057 Value *OpLeft = (LeftToRight) ? OpLastLane : Op; 1058 Value *OpRight = (LeftToRight) ? Op : OpLastLane; 1059 unsigned Score = 1060 getLookAheadScore({OpLeft, LastLane}, {OpRight, Lane}); 1061 if (Score > BestOp.Score) { 1062 BestOp.Idx = Idx; 1063 BestOp.Score = Score; 1064 } 1065 break; 1066 } 1067 case ReorderingMode::Splat: 1068 if (Op == OpLastLane) 1069 BestOp.Idx = Idx; 1070 break; 1071 case ReorderingMode::Failed: 1072 return None; 1073 } 1074 } 1075 1076 if (BestOp.Idx) { 1077 getData(BestOp.Idx.getValue(), Lane).IsUsed = true; 1078 return BestOp.Idx; 1079 } 1080 // If we could not find a good match return None. 1081 return None; 1082 } 1083 1084 /// Helper for reorderOperandVecs. \Returns the lane that we should start 1085 /// reordering from. This is the one which has the least number of operands 1086 /// that can freely move about. 1087 unsigned getBestLaneToStartReordering() const { 1088 unsigned BestLane = 0; 1089 unsigned Min = UINT_MAX; 1090 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 1091 ++Lane) { 1092 unsigned NumFreeOps = getMaxNumOperandsThatCanBeReordered(Lane); 1093 if (NumFreeOps < Min) { 1094 Min = NumFreeOps; 1095 BestLane = Lane; 1096 } 1097 } 1098 return BestLane; 1099 } 1100 1101 /// \Returns the maximum number of operands that are allowed to be reordered 1102 /// for \p Lane. This is used as a heuristic for selecting the first lane to 1103 /// start operand reordering. 1104 unsigned getMaxNumOperandsThatCanBeReordered(unsigned Lane) const { 1105 unsigned CntTrue = 0; 1106 unsigned NumOperands = getNumOperands(); 1107 // Operands with the same APO can be reordered. We therefore need to count 1108 // how many of them we have for each APO, like this: Cnt[APO] = x. 1109 // Since we only have two APOs, namely true and false, we can avoid using 1110 // a map. Instead we can simply count the number of operands that 1111 // correspond to one of them (in this case the 'true' APO), and calculate 1112 // the other by subtracting it from the total number of operands. 1113 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) 1114 if (getData(OpIdx, Lane).APO) 1115 ++CntTrue; 1116 unsigned CntFalse = NumOperands - CntTrue; 1117 return std::max(CntTrue, CntFalse); 1118 } 1119 1120 /// Go through the instructions in VL and append their operands. 1121 void appendOperandsOfVL(ArrayRef<Value *> VL) { 1122 assert(!VL.empty() && "Bad VL"); 1123 assert((empty() || VL.size() == getNumLanes()) && 1124 "Expected same number of lanes"); 1125 assert(isa<Instruction>(VL[0]) && "Expected instruction"); 1126 unsigned NumOperands = cast<Instruction>(VL[0])->getNumOperands(); 1127 OpsVec.resize(NumOperands); 1128 unsigned NumLanes = VL.size(); 1129 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1130 OpsVec[OpIdx].resize(NumLanes); 1131 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { 1132 assert(isa<Instruction>(VL[Lane]) && "Expected instruction"); 1133 // Our tree has just 3 nodes: the root and two operands. 1134 // It is therefore trivial to get the APO. We only need to check the 1135 // opcode of VL[Lane] and whether the operand at OpIdx is the LHS or 1136 // RHS operand. The LHS operand of both add and sub is never attached 1137 // to an inversese operation in the linearized form, therefore its APO 1138 // is false. The RHS is true only if VL[Lane] is an inverse operation. 1139 1140 // Since operand reordering is performed on groups of commutative 1141 // operations or alternating sequences (e.g., +, -), we can safely 1142 // tell the inverse operations by checking commutativity. 1143 bool IsInverseOperation = !isCommutative(cast<Instruction>(VL[Lane])); 1144 bool APO = (OpIdx == 0) ? false : IsInverseOperation; 1145 OpsVec[OpIdx][Lane] = {cast<Instruction>(VL[Lane])->getOperand(OpIdx), 1146 APO, false}; 1147 } 1148 } 1149 } 1150 1151 /// \returns the number of operands. 1152 unsigned getNumOperands() const { return OpsVec.size(); } 1153 1154 /// \returns the number of lanes. 1155 unsigned getNumLanes() const { return OpsVec[0].size(); } 1156 1157 /// \returns the operand value at \p OpIdx and \p Lane. 1158 Value *getValue(unsigned OpIdx, unsigned Lane) const { 1159 return getData(OpIdx, Lane).V; 1160 } 1161 1162 /// \returns true if the data structure is empty. 1163 bool empty() const { return OpsVec.empty(); } 1164 1165 /// Clears the data. 1166 void clear() { OpsVec.clear(); } 1167 1168 /// \Returns true if there are enough operands identical to \p Op to fill 1169 /// the whole vector. 1170 /// Note: This modifies the 'IsUsed' flag, so a cleanUsed() must follow. 1171 bool shouldBroadcast(Value *Op, unsigned OpIdx, unsigned Lane) { 1172 bool OpAPO = getData(OpIdx, Lane).APO; 1173 for (unsigned Ln = 0, Lns = getNumLanes(); Ln != Lns; ++Ln) { 1174 if (Ln == Lane) 1175 continue; 1176 // This is set to true if we found a candidate for broadcast at Lane. 1177 bool FoundCandidate = false; 1178 for (unsigned OpI = 0, OpE = getNumOperands(); OpI != OpE; ++OpI) { 1179 OperandData &Data = getData(OpI, Ln); 1180 if (Data.APO != OpAPO || Data.IsUsed) 1181 continue; 1182 if (Data.V == Op) { 1183 FoundCandidate = true; 1184 Data.IsUsed = true; 1185 break; 1186 } 1187 } 1188 if (!FoundCandidate) 1189 return false; 1190 } 1191 return true; 1192 } 1193 1194 public: 1195 /// Initialize with all the operands of the instruction vector \p RootVL. 1196 VLOperands(ArrayRef<Value *> RootVL, const DataLayout &DL, 1197 ScalarEvolution &SE, const BoUpSLP &R) 1198 : DL(DL), SE(SE), R(R) { 1199 // Append all the operands of RootVL. 1200 appendOperandsOfVL(RootVL); 1201 } 1202 1203 /// \Returns a value vector with the operands across all lanes for the 1204 /// opearnd at \p OpIdx. 1205 ValueList getVL(unsigned OpIdx) const { 1206 ValueList OpVL(OpsVec[OpIdx].size()); 1207 assert(OpsVec[OpIdx].size() == getNumLanes() && 1208 "Expected same num of lanes across all operands"); 1209 for (unsigned Lane = 0, Lanes = getNumLanes(); Lane != Lanes; ++Lane) 1210 OpVL[Lane] = OpsVec[OpIdx][Lane].V; 1211 return OpVL; 1212 } 1213 1214 // Performs operand reordering for 2 or more operands. 1215 // The original operands are in OrigOps[OpIdx][Lane]. 1216 // The reordered operands are returned in 'SortedOps[OpIdx][Lane]'. 1217 void reorder() { 1218 unsigned NumOperands = getNumOperands(); 1219 unsigned NumLanes = getNumLanes(); 1220 // Each operand has its own mode. We are using this mode to help us select 1221 // the instructions for each lane, so that they match best with the ones 1222 // we have selected so far. 1223 SmallVector<ReorderingMode, 2> ReorderingModes(NumOperands); 1224 1225 // This is a greedy single-pass algorithm. We are going over each lane 1226 // once and deciding on the best order right away with no back-tracking. 1227 // However, in order to increase its effectiveness, we start with the lane 1228 // that has operands that can move the least. For example, given the 1229 // following lanes: 1230 // Lane 0 : A[0] = B[0] + C[0] // Visited 3rd 1231 // Lane 1 : A[1] = C[1] - B[1] // Visited 1st 1232 // Lane 2 : A[2] = B[2] + C[2] // Visited 2nd 1233 // Lane 3 : A[3] = C[3] - B[3] // Visited 4th 1234 // we will start at Lane 1, since the operands of the subtraction cannot 1235 // be reordered. Then we will visit the rest of the lanes in a circular 1236 // fashion. That is, Lanes 2, then Lane 0, and finally Lane 3. 1237 1238 // Find the first lane that we will start our search from. 1239 unsigned FirstLane = getBestLaneToStartReordering(); 1240 1241 // Initialize the modes. 1242 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1243 Value *OpLane0 = getValue(OpIdx, FirstLane); 1244 // Keep track if we have instructions with all the same opcode on one 1245 // side. 1246 if (isa<LoadInst>(OpLane0)) 1247 ReorderingModes[OpIdx] = ReorderingMode::Load; 1248 else if (isa<Instruction>(OpLane0)) { 1249 // Check if OpLane0 should be broadcast. 1250 if (shouldBroadcast(OpLane0, OpIdx, FirstLane)) 1251 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1252 else 1253 ReorderingModes[OpIdx] = ReorderingMode::Opcode; 1254 } 1255 else if (isa<Constant>(OpLane0)) 1256 ReorderingModes[OpIdx] = ReorderingMode::Constant; 1257 else if (isa<Argument>(OpLane0)) 1258 // Our best hope is a Splat. It may save some cost in some cases. 1259 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1260 else 1261 // NOTE: This should be unreachable. 1262 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1263 } 1264 1265 // If the initial strategy fails for any of the operand indexes, then we 1266 // perform reordering again in a second pass. This helps avoid assigning 1267 // high priority to the failed strategy, and should improve reordering for 1268 // the non-failed operand indexes. 1269 for (int Pass = 0; Pass != 2; ++Pass) { 1270 // Skip the second pass if the first pass did not fail. 1271 bool StrategyFailed = false; 1272 // Mark all operand data as free to use. 1273 clearUsed(); 1274 // We keep the original operand order for the FirstLane, so reorder the 1275 // rest of the lanes. We are visiting the nodes in a circular fashion, 1276 // using FirstLane as the center point and increasing the radius 1277 // distance. 1278 for (unsigned Distance = 1; Distance != NumLanes; ++Distance) { 1279 // Visit the lane on the right and then the lane on the left. 1280 for (int Direction : {+1, -1}) { 1281 int Lane = FirstLane + Direction * Distance; 1282 if (Lane < 0 || Lane >= (int)NumLanes) 1283 continue; 1284 int LastLane = Lane - Direction; 1285 assert(LastLane >= 0 && LastLane < (int)NumLanes && 1286 "Out of bounds"); 1287 // Look for a good match for each operand. 1288 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1289 // Search for the operand that matches SortedOps[OpIdx][Lane-1]. 1290 Optional<unsigned> BestIdx = 1291 getBestOperand(OpIdx, Lane, LastLane, ReorderingModes); 1292 // By not selecting a value, we allow the operands that follow to 1293 // select a better matching value. We will get a non-null value in 1294 // the next run of getBestOperand(). 1295 if (BestIdx) { 1296 // Swap the current operand with the one returned by 1297 // getBestOperand(). 1298 swap(OpIdx, BestIdx.getValue(), Lane); 1299 } else { 1300 // We failed to find a best operand, set mode to 'Failed'. 1301 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1302 // Enable the second pass. 1303 StrategyFailed = true; 1304 } 1305 } 1306 } 1307 } 1308 // Skip second pass if the strategy did not fail. 1309 if (!StrategyFailed) 1310 break; 1311 } 1312 } 1313 1314 #if !defined(NDEBUG) || defined(LLVM_ENABLE_DUMP) 1315 LLVM_DUMP_METHOD static StringRef getModeStr(ReorderingMode RMode) { 1316 switch (RMode) { 1317 case ReorderingMode::Load: 1318 return "Load"; 1319 case ReorderingMode::Opcode: 1320 return "Opcode"; 1321 case ReorderingMode::Constant: 1322 return "Constant"; 1323 case ReorderingMode::Splat: 1324 return "Splat"; 1325 case ReorderingMode::Failed: 1326 return "Failed"; 1327 } 1328 llvm_unreachable("Unimplemented Reordering Type"); 1329 } 1330 1331 LLVM_DUMP_METHOD static raw_ostream &printMode(ReorderingMode RMode, 1332 raw_ostream &OS) { 1333 return OS << getModeStr(RMode); 1334 } 1335 1336 /// Debug print. 1337 LLVM_DUMP_METHOD static void dumpMode(ReorderingMode RMode) { 1338 printMode(RMode, dbgs()); 1339 } 1340 1341 friend raw_ostream &operator<<(raw_ostream &OS, ReorderingMode RMode) { 1342 return printMode(RMode, OS); 1343 } 1344 1345 LLVM_DUMP_METHOD raw_ostream &print(raw_ostream &OS) const { 1346 const unsigned Indent = 2; 1347 unsigned Cnt = 0; 1348 for (const OperandDataVec &OpDataVec : OpsVec) { 1349 OS << "Operand " << Cnt++ << "\n"; 1350 for (const OperandData &OpData : OpDataVec) { 1351 OS.indent(Indent) << "{"; 1352 if (Value *V = OpData.V) 1353 OS << *V; 1354 else 1355 OS << "null"; 1356 OS << ", APO:" << OpData.APO << "}\n"; 1357 } 1358 OS << "\n"; 1359 } 1360 return OS; 1361 } 1362 1363 /// Debug print. 1364 LLVM_DUMP_METHOD void dump() const { print(dbgs()); } 1365 #endif 1366 }; 1367 1368 /// Checks if the instruction is marked for deletion. 1369 bool isDeleted(Instruction *I) const { return DeletedInstructions.count(I); } 1370 1371 /// Marks values operands for later deletion by replacing them with Undefs. 1372 void eraseInstructions(ArrayRef<Value *> AV); 1373 1374 ~BoUpSLP(); 1375 1376 private: 1377 /// Checks if all users of \p I are the part of the vectorization tree. 1378 bool areAllUsersVectorized(Instruction *I) const; 1379 1380 /// \returns the cost of the vectorizable entry. 1381 int getEntryCost(TreeEntry *E); 1382 1383 /// This is the recursive part of buildTree. 1384 void buildTree_rec(ArrayRef<Value *> Roots, unsigned Depth, 1385 const EdgeInfo &EI); 1386 1387 /// \returns true if the ExtractElement/ExtractValue instructions in \p VL can 1388 /// be vectorized to use the original vector (or aggregate "bitcast" to a 1389 /// vector) and sets \p CurrentOrder to the identity permutation; otherwise 1390 /// returns false, setting \p CurrentOrder to either an empty vector or a 1391 /// non-identity permutation that allows to reuse extract instructions. 1392 bool canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 1393 SmallVectorImpl<unsigned> &CurrentOrder) const; 1394 1395 /// Vectorize a single entry in the tree. 1396 Value *vectorizeTree(TreeEntry *E); 1397 1398 /// Vectorize a single entry in the tree, starting in \p VL. 1399 Value *vectorizeTree(ArrayRef<Value *> VL); 1400 1401 /// \returns the scalarization cost for this type. Scalarization in this 1402 /// context means the creation of vectors from a group of scalars. 1403 int getGatherCost(Type *Ty, const DenseSet<unsigned> &ShuffledIndices) const; 1404 1405 /// \returns the scalarization cost for this list of values. Assuming that 1406 /// this subtree gets vectorized, we may need to extract the values from the 1407 /// roots. This method calculates the cost of extracting the values. 1408 int getGatherCost(ArrayRef<Value *> VL) const; 1409 1410 /// Set the Builder insert point to one after the last instruction in 1411 /// the bundle 1412 void setInsertPointAfterBundle(TreeEntry *E); 1413 1414 /// \returns a vector from a collection of scalars in \p VL. 1415 Value *Gather(ArrayRef<Value *> VL, VectorType *Ty); 1416 1417 /// \returns whether the VectorizableTree is fully vectorizable and will 1418 /// be beneficial even the tree height is tiny. 1419 bool isFullyVectorizableTinyTree() const; 1420 1421 /// Reorder commutative or alt operands to get better probability of 1422 /// generating vectorized code. 1423 static void reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 1424 SmallVectorImpl<Value *> &Left, 1425 SmallVectorImpl<Value *> &Right, 1426 const DataLayout &DL, 1427 ScalarEvolution &SE, 1428 const BoUpSLP &R); 1429 struct TreeEntry { 1430 using VecTreeTy = SmallVector<std::unique_ptr<TreeEntry>, 8>; 1431 TreeEntry(VecTreeTy &Container) : Container(Container) {} 1432 1433 /// \returns true if the scalars in VL are equal to this entry. 1434 bool isSame(ArrayRef<Value *> VL) const { 1435 if (VL.size() == Scalars.size()) 1436 return std::equal(VL.begin(), VL.end(), Scalars.begin()); 1437 return VL.size() == ReuseShuffleIndices.size() && 1438 std::equal( 1439 VL.begin(), VL.end(), ReuseShuffleIndices.begin(), 1440 [this](Value *V, int Idx) { return V == Scalars[Idx]; }); 1441 } 1442 1443 /// A vector of scalars. 1444 ValueList Scalars; 1445 1446 /// The Scalars are vectorized into this value. It is initialized to Null. 1447 Value *VectorizedValue = nullptr; 1448 1449 /// Do we need to gather this sequence ? 1450 enum EntryState { Vectorize, NeedToGather }; 1451 EntryState State; 1452 1453 /// Does this sequence require some shuffling? 1454 SmallVector<int, 4> ReuseShuffleIndices; 1455 1456 /// Does this entry require reordering? 1457 ArrayRef<unsigned> ReorderIndices; 1458 1459 /// Points back to the VectorizableTree. 1460 /// 1461 /// Only used for Graphviz right now. Unfortunately GraphTrait::NodeRef has 1462 /// to be a pointer and needs to be able to initialize the child iterator. 1463 /// Thus we need a reference back to the container to translate the indices 1464 /// to entries. 1465 VecTreeTy &Container; 1466 1467 /// The TreeEntry index containing the user of this entry. We can actually 1468 /// have multiple users so the data structure is not truly a tree. 1469 SmallVector<EdgeInfo, 1> UserTreeIndices; 1470 1471 /// The index of this treeEntry in VectorizableTree. 1472 int Idx = -1; 1473 1474 private: 1475 /// The operands of each instruction in each lane Operands[op_index][lane]. 1476 /// Note: This helps avoid the replication of the code that performs the 1477 /// reordering of operands during buildTree_rec() and vectorizeTree(). 1478 SmallVector<ValueList, 2> Operands; 1479 1480 /// The main/alternate instruction. 1481 Instruction *MainOp = nullptr; 1482 Instruction *AltOp = nullptr; 1483 1484 public: 1485 /// Set this bundle's \p OpIdx'th operand to \p OpVL. 1486 void setOperand(unsigned OpIdx, ArrayRef<Value *> OpVL) { 1487 if (Operands.size() < OpIdx + 1) 1488 Operands.resize(OpIdx + 1); 1489 assert(Operands[OpIdx].size() == 0 && "Already resized?"); 1490 Operands[OpIdx].resize(Scalars.size()); 1491 for (unsigned Lane = 0, E = Scalars.size(); Lane != E; ++Lane) 1492 Operands[OpIdx][Lane] = OpVL[Lane]; 1493 } 1494 1495 /// Set the operands of this bundle in their original order. 1496 void setOperandsInOrder() { 1497 assert(Operands.empty() && "Already initialized?"); 1498 auto *I0 = cast<Instruction>(Scalars[0]); 1499 Operands.resize(I0->getNumOperands()); 1500 unsigned NumLanes = Scalars.size(); 1501 for (unsigned OpIdx = 0, NumOperands = I0->getNumOperands(); 1502 OpIdx != NumOperands; ++OpIdx) { 1503 Operands[OpIdx].resize(NumLanes); 1504 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { 1505 auto *I = cast<Instruction>(Scalars[Lane]); 1506 assert(I->getNumOperands() == NumOperands && 1507 "Expected same number of operands"); 1508 Operands[OpIdx][Lane] = I->getOperand(OpIdx); 1509 } 1510 } 1511 } 1512 1513 /// \returns the \p OpIdx operand of this TreeEntry. 1514 ValueList &getOperand(unsigned OpIdx) { 1515 assert(OpIdx < Operands.size() && "Off bounds"); 1516 return Operands[OpIdx]; 1517 } 1518 1519 /// \returns the number of operands. 1520 unsigned getNumOperands() const { return Operands.size(); } 1521 1522 /// \return the single \p OpIdx operand. 1523 Value *getSingleOperand(unsigned OpIdx) const { 1524 assert(OpIdx < Operands.size() && "Off bounds"); 1525 assert(!Operands[OpIdx].empty() && "No operand available"); 1526 return Operands[OpIdx][0]; 1527 } 1528 1529 /// Some of the instructions in the list have alternate opcodes. 1530 bool isAltShuffle() const { 1531 return getOpcode() != getAltOpcode(); 1532 } 1533 1534 bool isOpcodeOrAlt(Instruction *I) const { 1535 unsigned CheckedOpcode = I->getOpcode(); 1536 return (getOpcode() == CheckedOpcode || 1537 getAltOpcode() == CheckedOpcode); 1538 } 1539 1540 /// Chooses the correct key for scheduling data. If \p Op has the same (or 1541 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is 1542 /// \p OpValue. 1543 Value *isOneOf(Value *Op) const { 1544 auto *I = dyn_cast<Instruction>(Op); 1545 if (I && isOpcodeOrAlt(I)) 1546 return Op; 1547 return MainOp; 1548 } 1549 1550 void setOperations(const InstructionsState &S) { 1551 MainOp = S.MainOp; 1552 AltOp = S.AltOp; 1553 } 1554 1555 Instruction *getMainOp() const { 1556 return MainOp; 1557 } 1558 1559 Instruction *getAltOp() const { 1560 return AltOp; 1561 } 1562 1563 /// The main/alternate opcodes for the list of instructions. 1564 unsigned getOpcode() const { 1565 return MainOp ? MainOp->getOpcode() : 0; 1566 } 1567 1568 unsigned getAltOpcode() const { 1569 return AltOp ? AltOp->getOpcode() : 0; 1570 } 1571 1572 /// Update operations state of this entry if reorder occurred. 1573 bool updateStateIfReorder() { 1574 if (ReorderIndices.empty()) 1575 return false; 1576 InstructionsState S = getSameOpcode(Scalars, ReorderIndices.front()); 1577 setOperations(S); 1578 return true; 1579 } 1580 1581 #ifndef NDEBUG 1582 /// Debug printer. 1583 LLVM_DUMP_METHOD void dump() const { 1584 dbgs() << Idx << ".\n"; 1585 for (unsigned OpI = 0, OpE = Operands.size(); OpI != OpE; ++OpI) { 1586 dbgs() << "Operand " << OpI << ":\n"; 1587 for (const Value *V : Operands[OpI]) 1588 dbgs().indent(2) << *V << "\n"; 1589 } 1590 dbgs() << "Scalars: \n"; 1591 for (Value *V : Scalars) 1592 dbgs().indent(2) << *V << "\n"; 1593 dbgs() << "State: "; 1594 switch (State) { 1595 case Vectorize: 1596 dbgs() << "Vectorize\n"; 1597 break; 1598 case NeedToGather: 1599 dbgs() << "NeedToGather\n"; 1600 break; 1601 } 1602 dbgs() << "MainOp: "; 1603 if (MainOp) 1604 dbgs() << *MainOp << "\n"; 1605 else 1606 dbgs() << "NULL\n"; 1607 dbgs() << "AltOp: "; 1608 if (AltOp) 1609 dbgs() << *AltOp << "\n"; 1610 else 1611 dbgs() << "NULL\n"; 1612 dbgs() << "VectorizedValue: "; 1613 if (VectorizedValue) 1614 dbgs() << *VectorizedValue << "\n"; 1615 else 1616 dbgs() << "NULL\n"; 1617 dbgs() << "ReuseShuffleIndices: "; 1618 if (ReuseShuffleIndices.empty()) 1619 dbgs() << "Emtpy"; 1620 else 1621 for (unsigned ReuseIdx : ReuseShuffleIndices) 1622 dbgs() << ReuseIdx << ", "; 1623 dbgs() << "\n"; 1624 dbgs() << "ReorderIndices: "; 1625 for (unsigned ReorderIdx : ReorderIndices) 1626 dbgs() << ReorderIdx << ", "; 1627 dbgs() << "\n"; 1628 dbgs() << "UserTreeIndices: "; 1629 for (const auto &EInfo : UserTreeIndices) 1630 dbgs() << EInfo << ", "; 1631 dbgs() << "\n"; 1632 } 1633 #endif 1634 }; 1635 1636 /// Create a new VectorizableTree entry. 1637 TreeEntry *newTreeEntry(ArrayRef<Value *> VL, Optional<ScheduleData *> Bundle, 1638 const InstructionsState &S, 1639 const EdgeInfo &UserTreeIdx, 1640 ArrayRef<unsigned> ReuseShuffleIndices = None, 1641 ArrayRef<unsigned> ReorderIndices = None) { 1642 bool Vectorized = (bool)Bundle; 1643 VectorizableTree.push_back(std::make_unique<TreeEntry>(VectorizableTree)); 1644 TreeEntry *Last = VectorizableTree.back().get(); 1645 Last->Idx = VectorizableTree.size() - 1; 1646 Last->Scalars.insert(Last->Scalars.begin(), VL.begin(), VL.end()); 1647 Last->State = Vectorized ? TreeEntry::Vectorize : TreeEntry::NeedToGather; 1648 Last->ReuseShuffleIndices.append(ReuseShuffleIndices.begin(), 1649 ReuseShuffleIndices.end()); 1650 Last->ReorderIndices = ReorderIndices; 1651 Last->setOperations(S); 1652 if (Vectorized) { 1653 for (int i = 0, e = VL.size(); i != e; ++i) { 1654 assert(!getTreeEntry(VL[i]) && "Scalar already in tree!"); 1655 ScalarToTreeEntry[VL[i]] = Last; 1656 } 1657 // Update the scheduler bundle to point to this TreeEntry. 1658 unsigned Lane = 0; 1659 for (ScheduleData *BundleMember = Bundle.getValue(); BundleMember; 1660 BundleMember = BundleMember->NextInBundle) { 1661 BundleMember->TE = Last; 1662 BundleMember->Lane = Lane; 1663 ++Lane; 1664 } 1665 assert((!Bundle.getValue() || Lane == VL.size()) && 1666 "Bundle and VL out of sync"); 1667 } else { 1668 MustGather.insert(VL.begin(), VL.end()); 1669 } 1670 1671 if (UserTreeIdx.UserTE) 1672 Last->UserTreeIndices.push_back(UserTreeIdx); 1673 1674 return Last; 1675 } 1676 1677 /// -- Vectorization State -- 1678 /// Holds all of the tree entries. 1679 TreeEntry::VecTreeTy VectorizableTree; 1680 1681 #ifndef NDEBUG 1682 /// Debug printer. 1683 LLVM_DUMP_METHOD void dumpVectorizableTree() const { 1684 for (unsigned Id = 0, IdE = VectorizableTree.size(); Id != IdE; ++Id) { 1685 VectorizableTree[Id]->dump(); 1686 dbgs() << "\n"; 1687 } 1688 } 1689 #endif 1690 1691 TreeEntry *getTreeEntry(Value *V) { 1692 auto I = ScalarToTreeEntry.find(V); 1693 if (I != ScalarToTreeEntry.end()) 1694 return I->second; 1695 return nullptr; 1696 } 1697 1698 const TreeEntry *getTreeEntry(Value *V) const { 1699 auto I = ScalarToTreeEntry.find(V); 1700 if (I != ScalarToTreeEntry.end()) 1701 return I->second; 1702 return nullptr; 1703 } 1704 1705 /// Maps a specific scalar to its tree entry. 1706 SmallDenseMap<Value*, TreeEntry *> ScalarToTreeEntry; 1707 1708 /// A list of scalars that we found that we need to keep as scalars. 1709 ValueSet MustGather; 1710 1711 /// This POD struct describes one external user in the vectorized tree. 1712 struct ExternalUser { 1713 ExternalUser(Value *S, llvm::User *U, int L) 1714 : Scalar(S), User(U), Lane(L) {} 1715 1716 // Which scalar in our function. 1717 Value *Scalar; 1718 1719 // Which user that uses the scalar. 1720 llvm::User *User; 1721 1722 // Which lane does the scalar belong to. 1723 int Lane; 1724 }; 1725 using UserList = SmallVector<ExternalUser, 16>; 1726 1727 /// Checks if two instructions may access the same memory. 1728 /// 1729 /// \p Loc1 is the location of \p Inst1. It is passed explicitly because it 1730 /// is invariant in the calling loop. 1731 bool isAliased(const MemoryLocation &Loc1, Instruction *Inst1, 1732 Instruction *Inst2) { 1733 // First check if the result is already in the cache. 1734 AliasCacheKey key = std::make_pair(Inst1, Inst2); 1735 Optional<bool> &result = AliasCache[key]; 1736 if (result.hasValue()) { 1737 return result.getValue(); 1738 } 1739 MemoryLocation Loc2 = getLocation(Inst2, AA); 1740 bool aliased = true; 1741 if (Loc1.Ptr && Loc2.Ptr && isSimple(Inst1) && isSimple(Inst2)) { 1742 // Do the alias check. 1743 aliased = AA->alias(Loc1, Loc2); 1744 } 1745 // Store the result in the cache. 1746 result = aliased; 1747 return aliased; 1748 } 1749 1750 using AliasCacheKey = std::pair<Instruction *, Instruction *>; 1751 1752 /// Cache for alias results. 1753 /// TODO: consider moving this to the AliasAnalysis itself. 1754 DenseMap<AliasCacheKey, Optional<bool>> AliasCache; 1755 1756 /// Removes an instruction from its block and eventually deletes it. 1757 /// It's like Instruction::eraseFromParent() except that the actual deletion 1758 /// is delayed until BoUpSLP is destructed. 1759 /// This is required to ensure that there are no incorrect collisions in the 1760 /// AliasCache, which can happen if a new instruction is allocated at the 1761 /// same address as a previously deleted instruction. 1762 void eraseInstruction(Instruction *I, bool ReplaceOpsWithUndef = false) { 1763 auto It = DeletedInstructions.try_emplace(I, ReplaceOpsWithUndef).first; 1764 It->getSecond() = It->getSecond() && ReplaceOpsWithUndef; 1765 } 1766 1767 /// Temporary store for deleted instructions. Instructions will be deleted 1768 /// eventually when the BoUpSLP is destructed. 1769 DenseMap<Instruction *, bool> DeletedInstructions; 1770 1771 /// A list of values that need to extracted out of the tree. 1772 /// This list holds pairs of (Internal Scalar : External User). External User 1773 /// can be nullptr, it means that this Internal Scalar will be used later, 1774 /// after vectorization. 1775 UserList ExternalUses; 1776 1777 /// Values used only by @llvm.assume calls. 1778 SmallPtrSet<const Value *, 32> EphValues; 1779 1780 /// Holds all of the instructions that we gathered. 1781 SetVector<Instruction *> GatherSeq; 1782 1783 /// A list of blocks that we are going to CSE. 1784 SetVector<BasicBlock *> CSEBlocks; 1785 1786 /// Contains all scheduling relevant data for an instruction. 1787 /// A ScheduleData either represents a single instruction or a member of an 1788 /// instruction bundle (= a group of instructions which is combined into a 1789 /// vector instruction). 1790 struct ScheduleData { 1791 // The initial value for the dependency counters. It means that the 1792 // dependencies are not calculated yet. 1793 enum { InvalidDeps = -1 }; 1794 1795 ScheduleData() = default; 1796 1797 void init(int BlockSchedulingRegionID, Value *OpVal) { 1798 FirstInBundle = this; 1799 NextInBundle = nullptr; 1800 NextLoadStore = nullptr; 1801 IsScheduled = false; 1802 SchedulingRegionID = BlockSchedulingRegionID; 1803 UnscheduledDepsInBundle = UnscheduledDeps; 1804 clearDependencies(); 1805 OpValue = OpVal; 1806 TE = nullptr; 1807 Lane = -1; 1808 } 1809 1810 /// Returns true if the dependency information has been calculated. 1811 bool hasValidDependencies() const { return Dependencies != InvalidDeps; } 1812 1813 /// Returns true for single instructions and for bundle representatives 1814 /// (= the head of a bundle). 1815 bool isSchedulingEntity() const { return FirstInBundle == this; } 1816 1817 /// Returns true if it represents an instruction bundle and not only a 1818 /// single instruction. 1819 bool isPartOfBundle() const { 1820 return NextInBundle != nullptr || FirstInBundle != this; 1821 } 1822 1823 /// Returns true if it is ready for scheduling, i.e. it has no more 1824 /// unscheduled depending instructions/bundles. 1825 bool isReady() const { 1826 assert(isSchedulingEntity() && 1827 "can't consider non-scheduling entity for ready list"); 1828 return UnscheduledDepsInBundle == 0 && !IsScheduled; 1829 } 1830 1831 /// Modifies the number of unscheduled dependencies, also updating it for 1832 /// the whole bundle. 1833 int incrementUnscheduledDeps(int Incr) { 1834 UnscheduledDeps += Incr; 1835 return FirstInBundle->UnscheduledDepsInBundle += Incr; 1836 } 1837 1838 /// Sets the number of unscheduled dependencies to the number of 1839 /// dependencies. 1840 void resetUnscheduledDeps() { 1841 incrementUnscheduledDeps(Dependencies - UnscheduledDeps); 1842 } 1843 1844 /// Clears all dependency information. 1845 void clearDependencies() { 1846 Dependencies = InvalidDeps; 1847 resetUnscheduledDeps(); 1848 MemoryDependencies.clear(); 1849 } 1850 1851 void dump(raw_ostream &os) const { 1852 if (!isSchedulingEntity()) { 1853 os << "/ " << *Inst; 1854 } else if (NextInBundle) { 1855 os << '[' << *Inst; 1856 ScheduleData *SD = NextInBundle; 1857 while (SD) { 1858 os << ';' << *SD->Inst; 1859 SD = SD->NextInBundle; 1860 } 1861 os << ']'; 1862 } else { 1863 os << *Inst; 1864 } 1865 } 1866 1867 Instruction *Inst = nullptr; 1868 1869 /// Points to the head in an instruction bundle (and always to this for 1870 /// single instructions). 1871 ScheduleData *FirstInBundle = nullptr; 1872 1873 /// Single linked list of all instructions in a bundle. Null if it is a 1874 /// single instruction. 1875 ScheduleData *NextInBundle = nullptr; 1876 1877 /// Single linked list of all memory instructions (e.g. load, store, call) 1878 /// in the block - until the end of the scheduling region. 1879 ScheduleData *NextLoadStore = nullptr; 1880 1881 /// The dependent memory instructions. 1882 /// This list is derived on demand in calculateDependencies(). 1883 SmallVector<ScheduleData *, 4> MemoryDependencies; 1884 1885 /// This ScheduleData is in the current scheduling region if this matches 1886 /// the current SchedulingRegionID of BlockScheduling. 1887 int SchedulingRegionID = 0; 1888 1889 /// Used for getting a "good" final ordering of instructions. 1890 int SchedulingPriority = 0; 1891 1892 /// The number of dependencies. Constitutes of the number of users of the 1893 /// instruction plus the number of dependent memory instructions (if any). 1894 /// This value is calculated on demand. 1895 /// If InvalidDeps, the number of dependencies is not calculated yet. 1896 int Dependencies = InvalidDeps; 1897 1898 /// The number of dependencies minus the number of dependencies of scheduled 1899 /// instructions. As soon as this is zero, the instruction/bundle gets ready 1900 /// for scheduling. 1901 /// Note that this is negative as long as Dependencies is not calculated. 1902 int UnscheduledDeps = InvalidDeps; 1903 1904 /// The sum of UnscheduledDeps in a bundle. Equals to UnscheduledDeps for 1905 /// single instructions. 1906 int UnscheduledDepsInBundle = InvalidDeps; 1907 1908 /// True if this instruction is scheduled (or considered as scheduled in the 1909 /// dry-run). 1910 bool IsScheduled = false; 1911 1912 /// Opcode of the current instruction in the schedule data. 1913 Value *OpValue = nullptr; 1914 1915 /// The TreeEntry that this instruction corresponds to. 1916 TreeEntry *TE = nullptr; 1917 1918 /// The lane of this node in the TreeEntry. 1919 int Lane = -1; 1920 }; 1921 1922 #ifndef NDEBUG 1923 friend inline raw_ostream &operator<<(raw_ostream &os, 1924 const BoUpSLP::ScheduleData &SD) { 1925 SD.dump(os); 1926 return os; 1927 } 1928 #endif 1929 1930 friend struct GraphTraits<BoUpSLP *>; 1931 friend struct DOTGraphTraits<BoUpSLP *>; 1932 1933 /// Contains all scheduling data for a basic block. 1934 struct BlockScheduling { 1935 BlockScheduling(BasicBlock *BB) 1936 : BB(BB), ChunkSize(BB->size()), ChunkPos(ChunkSize) {} 1937 1938 void clear() { 1939 ReadyInsts.clear(); 1940 ScheduleStart = nullptr; 1941 ScheduleEnd = nullptr; 1942 FirstLoadStoreInRegion = nullptr; 1943 LastLoadStoreInRegion = nullptr; 1944 1945 // Reduce the maximum schedule region size by the size of the 1946 // previous scheduling run. 1947 ScheduleRegionSizeLimit -= ScheduleRegionSize; 1948 if (ScheduleRegionSizeLimit < MinScheduleRegionSize) 1949 ScheduleRegionSizeLimit = MinScheduleRegionSize; 1950 ScheduleRegionSize = 0; 1951 1952 // Make a new scheduling region, i.e. all existing ScheduleData is not 1953 // in the new region yet. 1954 ++SchedulingRegionID; 1955 } 1956 1957 ScheduleData *getScheduleData(Value *V) { 1958 ScheduleData *SD = ScheduleDataMap[V]; 1959 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 1960 return SD; 1961 return nullptr; 1962 } 1963 1964 ScheduleData *getScheduleData(Value *V, Value *Key) { 1965 if (V == Key) 1966 return getScheduleData(V); 1967 auto I = ExtraScheduleDataMap.find(V); 1968 if (I != ExtraScheduleDataMap.end()) { 1969 ScheduleData *SD = I->second[Key]; 1970 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 1971 return SD; 1972 } 1973 return nullptr; 1974 } 1975 1976 bool isInSchedulingRegion(ScheduleData *SD) const { 1977 return SD->SchedulingRegionID == SchedulingRegionID; 1978 } 1979 1980 /// Marks an instruction as scheduled and puts all dependent ready 1981 /// instructions into the ready-list. 1982 template <typename ReadyListType> 1983 void schedule(ScheduleData *SD, ReadyListType &ReadyList) { 1984 SD->IsScheduled = true; 1985 LLVM_DEBUG(dbgs() << "SLP: schedule " << *SD << "\n"); 1986 1987 ScheduleData *BundleMember = SD; 1988 while (BundleMember) { 1989 if (BundleMember->Inst != BundleMember->OpValue) { 1990 BundleMember = BundleMember->NextInBundle; 1991 continue; 1992 } 1993 // Handle the def-use chain dependencies. 1994 1995 // Decrement the unscheduled counter and insert to ready list if ready. 1996 auto &&DecrUnsched = [this, &ReadyList](Instruction *I) { 1997 doForAllOpcodes(I, [&ReadyList](ScheduleData *OpDef) { 1998 if (OpDef && OpDef->hasValidDependencies() && 1999 OpDef->incrementUnscheduledDeps(-1) == 0) { 2000 // There are no more unscheduled dependencies after 2001 // decrementing, so we can put the dependent instruction 2002 // into the ready list. 2003 ScheduleData *DepBundle = OpDef->FirstInBundle; 2004 assert(!DepBundle->IsScheduled && 2005 "already scheduled bundle gets ready"); 2006 ReadyList.insert(DepBundle); 2007 LLVM_DEBUG(dbgs() 2008 << "SLP: gets ready (def): " << *DepBundle << "\n"); 2009 } 2010 }); 2011 }; 2012 2013 // If BundleMember is a vector bundle, its operands may have been 2014 // reordered duiring buildTree(). We therefore need to get its operands 2015 // through the TreeEntry. 2016 if (TreeEntry *TE = BundleMember->TE) { 2017 int Lane = BundleMember->Lane; 2018 assert(Lane >= 0 && "Lane not set"); 2019 2020 // Since vectorization tree is being built recursively this assertion 2021 // ensures that the tree entry has all operands set before reaching 2022 // this code. Couple of exceptions known at the moment are extracts 2023 // where their second (immediate) operand is not added. Since 2024 // immediates do not affect scheduler behavior this is considered 2025 // okay. 2026 auto *In = TE->getMainOp(); 2027 assert(In && 2028 (isa<ExtractValueInst>(In) || isa<ExtractElementInst>(In) || 2029 In->getNumOperands() == TE->getNumOperands()) && 2030 "Missed TreeEntry operands?"); 2031 (void)In; // fake use to avoid build failure when assertions disabled 2032 2033 for (unsigned OpIdx = 0, NumOperands = TE->getNumOperands(); 2034 OpIdx != NumOperands; ++OpIdx) 2035 if (auto *I = dyn_cast<Instruction>(TE->getOperand(OpIdx)[Lane])) 2036 DecrUnsched(I); 2037 } else { 2038 // If BundleMember is a stand-alone instruction, no operand reordering 2039 // has taken place, so we directly access its operands. 2040 for (Use &U : BundleMember->Inst->operands()) 2041 if (auto *I = dyn_cast<Instruction>(U.get())) 2042 DecrUnsched(I); 2043 } 2044 // Handle the memory dependencies. 2045 for (ScheduleData *MemoryDepSD : BundleMember->MemoryDependencies) { 2046 if (MemoryDepSD->incrementUnscheduledDeps(-1) == 0) { 2047 // There are no more unscheduled dependencies after decrementing, 2048 // so we can put the dependent instruction into the ready list. 2049 ScheduleData *DepBundle = MemoryDepSD->FirstInBundle; 2050 assert(!DepBundle->IsScheduled && 2051 "already scheduled bundle gets ready"); 2052 ReadyList.insert(DepBundle); 2053 LLVM_DEBUG(dbgs() 2054 << "SLP: gets ready (mem): " << *DepBundle << "\n"); 2055 } 2056 } 2057 BundleMember = BundleMember->NextInBundle; 2058 } 2059 } 2060 2061 void doForAllOpcodes(Value *V, 2062 function_ref<void(ScheduleData *SD)> Action) { 2063 if (ScheduleData *SD = getScheduleData(V)) 2064 Action(SD); 2065 auto I = ExtraScheduleDataMap.find(V); 2066 if (I != ExtraScheduleDataMap.end()) 2067 for (auto &P : I->second) 2068 if (P.second->SchedulingRegionID == SchedulingRegionID) 2069 Action(P.second); 2070 } 2071 2072 /// Put all instructions into the ReadyList which are ready for scheduling. 2073 template <typename ReadyListType> 2074 void initialFillReadyList(ReadyListType &ReadyList) { 2075 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 2076 doForAllOpcodes(I, [&](ScheduleData *SD) { 2077 if (SD->isSchedulingEntity() && SD->isReady()) { 2078 ReadyList.insert(SD); 2079 LLVM_DEBUG(dbgs() 2080 << "SLP: initially in ready list: " << *I << "\n"); 2081 } 2082 }); 2083 } 2084 } 2085 2086 /// Checks if a bundle of instructions can be scheduled, i.e. has no 2087 /// cyclic dependencies. This is only a dry-run, no instructions are 2088 /// actually moved at this stage. 2089 /// \returns the scheduling bundle. The returned Optional value is non-None 2090 /// if \p VL is allowed to be scheduled. 2091 Optional<ScheduleData *> 2092 tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 2093 const InstructionsState &S); 2094 2095 /// Un-bundles a group of instructions. 2096 void cancelScheduling(ArrayRef<Value *> VL, Value *OpValue); 2097 2098 /// Allocates schedule data chunk. 2099 ScheduleData *allocateScheduleDataChunks(); 2100 2101 /// Extends the scheduling region so that V is inside the region. 2102 /// \returns true if the region size is within the limit. 2103 bool extendSchedulingRegion(Value *V, const InstructionsState &S); 2104 2105 /// Initialize the ScheduleData structures for new instructions in the 2106 /// scheduling region. 2107 void initScheduleData(Instruction *FromI, Instruction *ToI, 2108 ScheduleData *PrevLoadStore, 2109 ScheduleData *NextLoadStore); 2110 2111 /// Updates the dependency information of a bundle and of all instructions/ 2112 /// bundles which depend on the original bundle. 2113 void calculateDependencies(ScheduleData *SD, bool InsertInReadyList, 2114 BoUpSLP *SLP); 2115 2116 /// Sets all instruction in the scheduling region to un-scheduled. 2117 void resetSchedule(); 2118 2119 BasicBlock *BB; 2120 2121 /// Simple memory allocation for ScheduleData. 2122 std::vector<std::unique_ptr<ScheduleData[]>> ScheduleDataChunks; 2123 2124 /// The size of a ScheduleData array in ScheduleDataChunks. 2125 int ChunkSize; 2126 2127 /// The allocator position in the current chunk, which is the last entry 2128 /// of ScheduleDataChunks. 2129 int ChunkPos; 2130 2131 /// Attaches ScheduleData to Instruction. 2132 /// Note that the mapping survives during all vectorization iterations, i.e. 2133 /// ScheduleData structures are recycled. 2134 DenseMap<Value *, ScheduleData *> ScheduleDataMap; 2135 2136 /// Attaches ScheduleData to Instruction with the leading key. 2137 DenseMap<Value *, SmallDenseMap<Value *, ScheduleData *>> 2138 ExtraScheduleDataMap; 2139 2140 struct ReadyList : SmallVector<ScheduleData *, 8> { 2141 void insert(ScheduleData *SD) { push_back(SD); } 2142 }; 2143 2144 /// The ready-list for scheduling (only used for the dry-run). 2145 ReadyList ReadyInsts; 2146 2147 /// The first instruction of the scheduling region. 2148 Instruction *ScheduleStart = nullptr; 2149 2150 /// The first instruction _after_ the scheduling region. 2151 Instruction *ScheduleEnd = nullptr; 2152 2153 /// The first memory accessing instruction in the scheduling region 2154 /// (can be null). 2155 ScheduleData *FirstLoadStoreInRegion = nullptr; 2156 2157 /// The last memory accessing instruction in the scheduling region 2158 /// (can be null). 2159 ScheduleData *LastLoadStoreInRegion = nullptr; 2160 2161 /// The current size of the scheduling region. 2162 int ScheduleRegionSize = 0; 2163 2164 /// The maximum size allowed for the scheduling region. 2165 int ScheduleRegionSizeLimit = ScheduleRegionSizeBudget; 2166 2167 /// The ID of the scheduling region. For a new vectorization iteration this 2168 /// is incremented which "removes" all ScheduleData from the region. 2169 // Make sure that the initial SchedulingRegionID is greater than the 2170 // initial SchedulingRegionID in ScheduleData (which is 0). 2171 int SchedulingRegionID = 1; 2172 }; 2173 2174 /// Attaches the BlockScheduling structures to basic blocks. 2175 MapVector<BasicBlock *, std::unique_ptr<BlockScheduling>> BlocksSchedules; 2176 2177 /// Performs the "real" scheduling. Done before vectorization is actually 2178 /// performed in a basic block. 2179 void scheduleBlock(BlockScheduling *BS); 2180 2181 /// List of users to ignore during scheduling and that don't need extracting. 2182 ArrayRef<Value *> UserIgnoreList; 2183 2184 using OrdersType = SmallVector<unsigned, 4>; 2185 /// A DenseMapInfo implementation for holding DenseMaps and DenseSets of 2186 /// sorted SmallVectors of unsigned. 2187 struct OrdersTypeDenseMapInfo { 2188 static OrdersType getEmptyKey() { 2189 OrdersType V; 2190 V.push_back(~1U); 2191 return V; 2192 } 2193 2194 static OrdersType getTombstoneKey() { 2195 OrdersType V; 2196 V.push_back(~2U); 2197 return V; 2198 } 2199 2200 static unsigned getHashValue(const OrdersType &V) { 2201 return static_cast<unsigned>(hash_combine_range(V.begin(), V.end())); 2202 } 2203 2204 static bool isEqual(const OrdersType &LHS, const OrdersType &RHS) { 2205 return LHS == RHS; 2206 } 2207 }; 2208 2209 /// Contains orders of operations along with the number of bundles that have 2210 /// operations in this order. It stores only those orders that require 2211 /// reordering, if reordering is not required it is counted using \a 2212 /// NumOpsWantToKeepOriginalOrder. 2213 DenseMap<OrdersType, unsigned, OrdersTypeDenseMapInfo> NumOpsWantToKeepOrder; 2214 /// Number of bundles that do not require reordering. 2215 unsigned NumOpsWantToKeepOriginalOrder = 0; 2216 2217 // Analysis and block reference. 2218 Function *F; 2219 ScalarEvolution *SE; 2220 TargetTransformInfo *TTI; 2221 TargetLibraryInfo *TLI; 2222 AliasAnalysis *AA; 2223 LoopInfo *LI; 2224 DominatorTree *DT; 2225 AssumptionCache *AC; 2226 DemandedBits *DB; 2227 const DataLayout *DL; 2228 OptimizationRemarkEmitter *ORE; 2229 2230 unsigned MaxVecRegSize; // This is set by TTI or overridden by cl::opt. 2231 unsigned MinVecRegSize; // Set by cl::opt (default: 128). 2232 2233 /// Instruction builder to construct the vectorized tree. 2234 IRBuilder<> Builder; 2235 2236 /// A map of scalar integer values to the smallest bit width with which they 2237 /// can legally be represented. The values map to (width, signed) pairs, 2238 /// where "width" indicates the minimum bit width and "signed" is True if the 2239 /// value must be signed-extended, rather than zero-extended, back to its 2240 /// original width. 2241 MapVector<Value *, std::pair<uint64_t, bool>> MinBWs; 2242 }; 2243 2244 } // end namespace slpvectorizer 2245 2246 template <> struct GraphTraits<BoUpSLP *> { 2247 using TreeEntry = BoUpSLP::TreeEntry; 2248 2249 /// NodeRef has to be a pointer per the GraphWriter. 2250 using NodeRef = TreeEntry *; 2251 2252 using ContainerTy = BoUpSLP::TreeEntry::VecTreeTy; 2253 2254 /// Add the VectorizableTree to the index iterator to be able to return 2255 /// TreeEntry pointers. 2256 struct ChildIteratorType 2257 : public iterator_adaptor_base< 2258 ChildIteratorType, SmallVector<BoUpSLP::EdgeInfo, 1>::iterator> { 2259 ContainerTy &VectorizableTree; 2260 2261 ChildIteratorType(SmallVector<BoUpSLP::EdgeInfo, 1>::iterator W, 2262 ContainerTy &VT) 2263 : ChildIteratorType::iterator_adaptor_base(W), VectorizableTree(VT) {} 2264 2265 NodeRef operator*() { return I->UserTE; } 2266 }; 2267 2268 static NodeRef getEntryNode(BoUpSLP &R) { 2269 return R.VectorizableTree[0].get(); 2270 } 2271 2272 static ChildIteratorType child_begin(NodeRef N) { 2273 return {N->UserTreeIndices.begin(), N->Container}; 2274 } 2275 2276 static ChildIteratorType child_end(NodeRef N) { 2277 return {N->UserTreeIndices.end(), N->Container}; 2278 } 2279 2280 /// For the node iterator we just need to turn the TreeEntry iterator into a 2281 /// TreeEntry* iterator so that it dereferences to NodeRef. 2282 class nodes_iterator { 2283 using ItTy = ContainerTy::iterator; 2284 ItTy It; 2285 2286 public: 2287 nodes_iterator(const ItTy &It2) : It(It2) {} 2288 NodeRef operator*() { return It->get(); } 2289 nodes_iterator operator++() { 2290 ++It; 2291 return *this; 2292 } 2293 bool operator!=(const nodes_iterator &N2) const { return N2.It != It; } 2294 }; 2295 2296 static nodes_iterator nodes_begin(BoUpSLP *R) { 2297 return nodes_iterator(R->VectorizableTree.begin()); 2298 } 2299 2300 static nodes_iterator nodes_end(BoUpSLP *R) { 2301 return nodes_iterator(R->VectorizableTree.end()); 2302 } 2303 2304 static unsigned size(BoUpSLP *R) { return R->VectorizableTree.size(); } 2305 }; 2306 2307 template <> struct DOTGraphTraits<BoUpSLP *> : public DefaultDOTGraphTraits { 2308 using TreeEntry = BoUpSLP::TreeEntry; 2309 2310 DOTGraphTraits(bool isSimple = false) : DefaultDOTGraphTraits(isSimple) {} 2311 2312 std::string getNodeLabel(const TreeEntry *Entry, const BoUpSLP *R) { 2313 std::string Str; 2314 raw_string_ostream OS(Str); 2315 if (isSplat(Entry->Scalars)) { 2316 OS << "<splat> " << *Entry->Scalars[0]; 2317 return Str; 2318 } 2319 for (auto V : Entry->Scalars) { 2320 OS << *V; 2321 if (std::any_of( 2322 R->ExternalUses.begin(), R->ExternalUses.end(), 2323 [&](const BoUpSLP::ExternalUser &EU) { return EU.Scalar == V; })) 2324 OS << " <extract>"; 2325 OS << "\n"; 2326 } 2327 return Str; 2328 } 2329 2330 static std::string getNodeAttributes(const TreeEntry *Entry, 2331 const BoUpSLP *) { 2332 if (Entry->State == TreeEntry::NeedToGather) 2333 return "color=red"; 2334 return ""; 2335 } 2336 }; 2337 2338 } // end namespace llvm 2339 2340 BoUpSLP::~BoUpSLP() { 2341 for (const auto &Pair : DeletedInstructions) { 2342 // Replace operands of ignored instructions with Undefs in case if they were 2343 // marked for deletion. 2344 if (Pair.getSecond()) { 2345 Value *Undef = UndefValue::get(Pair.getFirst()->getType()); 2346 Pair.getFirst()->replaceAllUsesWith(Undef); 2347 } 2348 Pair.getFirst()->dropAllReferences(); 2349 } 2350 for (const auto &Pair : DeletedInstructions) { 2351 assert(Pair.getFirst()->use_empty() && 2352 "trying to erase instruction with users."); 2353 Pair.getFirst()->eraseFromParent(); 2354 } 2355 } 2356 2357 void BoUpSLP::eraseInstructions(ArrayRef<Value *> AV) { 2358 for (auto *V : AV) { 2359 if (auto *I = dyn_cast<Instruction>(V)) 2360 eraseInstruction(I, /*ReplaceWithUndef=*/true); 2361 }; 2362 } 2363 2364 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2365 ArrayRef<Value *> UserIgnoreLst) { 2366 ExtraValueToDebugLocsMap ExternallyUsedValues; 2367 buildTree(Roots, ExternallyUsedValues, UserIgnoreLst); 2368 } 2369 2370 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2371 ExtraValueToDebugLocsMap &ExternallyUsedValues, 2372 ArrayRef<Value *> UserIgnoreLst) { 2373 deleteTree(); 2374 UserIgnoreList = UserIgnoreLst; 2375 if (!allSameType(Roots)) 2376 return; 2377 buildTree_rec(Roots, 0, EdgeInfo()); 2378 2379 // Collect the values that we need to extract from the tree. 2380 for (auto &TEPtr : VectorizableTree) { 2381 TreeEntry *Entry = TEPtr.get(); 2382 2383 // No need to handle users of gathered values. 2384 if (Entry->State == TreeEntry::NeedToGather) 2385 continue; 2386 2387 // For each lane: 2388 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 2389 Value *Scalar = Entry->Scalars[Lane]; 2390 int FoundLane = Lane; 2391 if (!Entry->ReuseShuffleIndices.empty()) { 2392 FoundLane = 2393 std::distance(Entry->ReuseShuffleIndices.begin(), 2394 llvm::find(Entry->ReuseShuffleIndices, FoundLane)); 2395 } 2396 2397 // Check if the scalar is externally used as an extra arg. 2398 auto ExtI = ExternallyUsedValues.find(Scalar); 2399 if (ExtI != ExternallyUsedValues.end()) { 2400 LLVM_DEBUG(dbgs() << "SLP: Need to extract: Extra arg from lane " 2401 << Lane << " from " << *Scalar << ".\n"); 2402 ExternalUses.emplace_back(Scalar, nullptr, FoundLane); 2403 } 2404 for (User *U : Scalar->users()) { 2405 LLVM_DEBUG(dbgs() << "SLP: Checking user:" << *U << ".\n"); 2406 2407 Instruction *UserInst = dyn_cast<Instruction>(U); 2408 if (!UserInst) 2409 continue; 2410 2411 // Skip in-tree scalars that become vectors 2412 if (TreeEntry *UseEntry = getTreeEntry(U)) { 2413 Value *UseScalar = UseEntry->Scalars[0]; 2414 // Some in-tree scalars will remain as scalar in vectorized 2415 // instructions. If that is the case, the one in Lane 0 will 2416 // be used. 2417 if (UseScalar != U || 2418 !InTreeUserNeedToExtract(Scalar, UserInst, TLI)) { 2419 LLVM_DEBUG(dbgs() << "SLP: \tInternal user will be removed:" << *U 2420 << ".\n"); 2421 assert(UseEntry->State != TreeEntry::NeedToGather && "Bad state"); 2422 continue; 2423 } 2424 } 2425 2426 // Ignore users in the user ignore list. 2427 if (is_contained(UserIgnoreList, UserInst)) 2428 continue; 2429 2430 LLVM_DEBUG(dbgs() << "SLP: Need to extract:" << *U << " from lane " 2431 << Lane << " from " << *Scalar << ".\n"); 2432 ExternalUses.push_back(ExternalUser(Scalar, U, FoundLane)); 2433 } 2434 } 2435 } 2436 } 2437 2438 void BoUpSLP::buildTree_rec(ArrayRef<Value *> VL, unsigned Depth, 2439 const EdgeInfo &UserTreeIdx) { 2440 assert((allConstant(VL) || allSameType(VL)) && "Invalid types!"); 2441 2442 InstructionsState S = getSameOpcode(VL); 2443 if (Depth == RecursionMaxDepth) { 2444 LLVM_DEBUG(dbgs() << "SLP: Gathering due to max recursion depth.\n"); 2445 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2446 return; 2447 } 2448 2449 // Don't handle vectors. 2450 if (S.OpValue->getType()->isVectorTy()) { 2451 LLVM_DEBUG(dbgs() << "SLP: Gathering due to vector type.\n"); 2452 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2453 return; 2454 } 2455 2456 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) 2457 if (SI->getValueOperand()->getType()->isVectorTy()) { 2458 LLVM_DEBUG(dbgs() << "SLP: Gathering due to store vector type.\n"); 2459 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2460 return; 2461 } 2462 2463 // If all of the operands are identical or constant we have a simple solution. 2464 if (allConstant(VL) || isSplat(VL) || !allSameBlock(VL) || !S.getOpcode()) { 2465 LLVM_DEBUG(dbgs() << "SLP: Gathering due to C,S,B,O. \n"); 2466 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2467 return; 2468 } 2469 2470 // We now know that this is a vector of instructions of the same type from 2471 // the same block. 2472 2473 // Don't vectorize ephemeral values. 2474 for (Value *V : VL) { 2475 if (EphValues.count(V)) { 2476 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2477 << ") is ephemeral.\n"); 2478 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2479 return; 2480 } 2481 } 2482 2483 // Check if this is a duplicate of another entry. 2484 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 2485 LLVM_DEBUG(dbgs() << "SLP: \tChecking bundle: " << *S.OpValue << ".\n"); 2486 if (!E->isSame(VL)) { 2487 LLVM_DEBUG(dbgs() << "SLP: Gathering due to partial overlap.\n"); 2488 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2489 return; 2490 } 2491 // Record the reuse of the tree node. FIXME, currently this is only used to 2492 // properly draw the graph rather than for the actual vectorization. 2493 E->UserTreeIndices.push_back(UserTreeIdx); 2494 LLVM_DEBUG(dbgs() << "SLP: Perfect diamond merge at " << *S.OpValue 2495 << ".\n"); 2496 return; 2497 } 2498 2499 // Check that none of the instructions in the bundle are already in the tree. 2500 for (Value *V : VL) { 2501 auto *I = dyn_cast<Instruction>(V); 2502 if (!I) 2503 continue; 2504 if (getTreeEntry(I)) { 2505 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2506 << ") is already in tree.\n"); 2507 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2508 return; 2509 } 2510 } 2511 2512 // If any of the scalars is marked as a value that needs to stay scalar, then 2513 // we need to gather the scalars. 2514 // The reduction nodes (stored in UserIgnoreList) also should stay scalar. 2515 for (Value *V : VL) { 2516 if (MustGather.count(V) || is_contained(UserIgnoreList, V)) { 2517 LLVM_DEBUG(dbgs() << "SLP: Gathering due to gathered scalar.\n"); 2518 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2519 return; 2520 } 2521 } 2522 2523 // Check that all of the users of the scalars that we want to vectorize are 2524 // schedulable. 2525 auto *VL0 = cast<Instruction>(S.OpValue); 2526 BasicBlock *BB = VL0->getParent(); 2527 2528 if (!DT->isReachableFromEntry(BB)) { 2529 // Don't go into unreachable blocks. They may contain instructions with 2530 // dependency cycles which confuse the final scheduling. 2531 LLVM_DEBUG(dbgs() << "SLP: bundle in unreachable block.\n"); 2532 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2533 return; 2534 } 2535 2536 // Check that every instruction appears once in this bundle. 2537 SmallVector<unsigned, 4> ReuseShuffleIndicies; 2538 SmallVector<Value *, 4> UniqueValues; 2539 DenseMap<Value *, unsigned> UniquePositions; 2540 for (Value *V : VL) { 2541 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 2542 ReuseShuffleIndicies.emplace_back(Res.first->second); 2543 if (Res.second) 2544 UniqueValues.emplace_back(V); 2545 } 2546 size_t NumUniqueScalarValues = UniqueValues.size(); 2547 if (NumUniqueScalarValues == VL.size()) { 2548 ReuseShuffleIndicies.clear(); 2549 } else { 2550 LLVM_DEBUG(dbgs() << "SLP: Shuffle for reused scalars.\n"); 2551 if (NumUniqueScalarValues <= 1 || 2552 !llvm::isPowerOf2_32(NumUniqueScalarValues)) { 2553 LLVM_DEBUG(dbgs() << "SLP: Scalar used twice in bundle.\n"); 2554 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2555 return; 2556 } 2557 VL = UniqueValues; 2558 } 2559 2560 auto &BSRef = BlocksSchedules[BB]; 2561 if (!BSRef) 2562 BSRef = std::make_unique<BlockScheduling>(BB); 2563 2564 BlockScheduling &BS = *BSRef.get(); 2565 2566 Optional<ScheduleData *> Bundle = BS.tryScheduleBundle(VL, this, S); 2567 if (!Bundle) { 2568 LLVM_DEBUG(dbgs() << "SLP: We are not able to schedule this bundle!\n"); 2569 assert((!BS.getScheduleData(VL0) || 2570 !BS.getScheduleData(VL0)->isPartOfBundle()) && 2571 "tryScheduleBundle should cancelScheduling on failure"); 2572 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2573 ReuseShuffleIndicies); 2574 return; 2575 } 2576 LLVM_DEBUG(dbgs() << "SLP: We are able to schedule this bundle.\n"); 2577 2578 unsigned ShuffleOrOp = S.isAltShuffle() ? 2579 (unsigned) Instruction::ShuffleVector : S.getOpcode(); 2580 switch (ShuffleOrOp) { 2581 case Instruction::PHI: { 2582 auto *PH = cast<PHINode>(VL0); 2583 2584 // Check for terminator values (e.g. invoke). 2585 for (unsigned j = 0; j < VL.size(); ++j) 2586 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 2587 Instruction *Term = dyn_cast<Instruction>( 2588 cast<PHINode>(VL[j])->getIncomingValueForBlock( 2589 PH->getIncomingBlock(i))); 2590 if (Term && Term->isTerminator()) { 2591 LLVM_DEBUG(dbgs() 2592 << "SLP: Need to swizzle PHINodes (terminator use).\n"); 2593 BS.cancelScheduling(VL, VL0); 2594 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2595 ReuseShuffleIndicies); 2596 return; 2597 } 2598 } 2599 2600 TreeEntry *TE = 2601 newTreeEntry(VL, Bundle, S, UserTreeIdx, ReuseShuffleIndicies); 2602 LLVM_DEBUG(dbgs() << "SLP: added a vector of PHINodes.\n"); 2603 2604 // Keeps the reordered operands to avoid code duplication. 2605 SmallVector<ValueList, 2> OperandsVec; 2606 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 2607 ValueList Operands; 2608 // Prepare the operand vector. 2609 for (Value *j : VL) 2610 Operands.push_back(cast<PHINode>(j)->getIncomingValueForBlock( 2611 PH->getIncomingBlock(i))); 2612 TE->setOperand(i, Operands); 2613 OperandsVec.push_back(Operands); 2614 } 2615 for (unsigned OpIdx = 0, OpE = OperandsVec.size(); OpIdx != OpE; ++OpIdx) 2616 buildTree_rec(OperandsVec[OpIdx], Depth + 1, {TE, OpIdx}); 2617 return; 2618 } 2619 case Instruction::ExtractValue: 2620 case Instruction::ExtractElement: { 2621 OrdersType CurrentOrder; 2622 bool Reuse = canReuseExtract(VL, VL0, CurrentOrder); 2623 if (Reuse) { 2624 LLVM_DEBUG(dbgs() << "SLP: Reusing or shuffling extract sequence.\n"); 2625 ++NumOpsWantToKeepOriginalOrder; 2626 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2627 ReuseShuffleIndicies); 2628 // This is a special case, as it does not gather, but at the same time 2629 // we are not extending buildTree_rec() towards the operands. 2630 ValueList Op0; 2631 Op0.assign(VL.size(), VL0->getOperand(0)); 2632 VectorizableTree.back()->setOperand(0, Op0); 2633 return; 2634 } 2635 if (!CurrentOrder.empty()) { 2636 LLVM_DEBUG({ 2637 dbgs() << "SLP: Reusing or shuffling of reordered extract sequence " 2638 "with order"; 2639 for (unsigned Idx : CurrentOrder) 2640 dbgs() << " " << Idx; 2641 dbgs() << "\n"; 2642 }); 2643 // Insert new order with initial value 0, if it does not exist, 2644 // otherwise return the iterator to the existing one. 2645 auto StoredCurrentOrderAndNum = 2646 NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first; 2647 ++StoredCurrentOrderAndNum->getSecond(); 2648 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2649 ReuseShuffleIndicies, 2650 StoredCurrentOrderAndNum->getFirst()); 2651 // This is a special case, as it does not gather, but at the same time 2652 // we are not extending buildTree_rec() towards the operands. 2653 ValueList Op0; 2654 Op0.assign(VL.size(), VL0->getOperand(0)); 2655 VectorizableTree.back()->setOperand(0, Op0); 2656 return; 2657 } 2658 LLVM_DEBUG(dbgs() << "SLP: Gather extract sequence.\n"); 2659 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2660 ReuseShuffleIndicies); 2661 BS.cancelScheduling(VL, VL0); 2662 return; 2663 } 2664 case Instruction::Load: { 2665 // Check that a vectorized load would load the same memory as a scalar 2666 // load. For example, we don't want to vectorize loads that are smaller 2667 // than 8-bit. Even though we have a packed struct {<i2, i2, i2, i2>} LLVM 2668 // treats loading/storing it as an i8 struct. If we vectorize loads/stores 2669 // from such a struct, we read/write packed bits disagreeing with the 2670 // unvectorized version. 2671 Type *ScalarTy = VL0->getType(); 2672 2673 if (DL->getTypeSizeInBits(ScalarTy) != 2674 DL->getTypeAllocSizeInBits(ScalarTy)) { 2675 BS.cancelScheduling(VL, VL0); 2676 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2677 ReuseShuffleIndicies); 2678 LLVM_DEBUG(dbgs() << "SLP: Gathering loads of non-packed type.\n"); 2679 return; 2680 } 2681 2682 // Make sure all loads in the bundle are simple - we can't vectorize 2683 // atomic or volatile loads. 2684 SmallVector<Value *, 4> PointerOps(VL.size()); 2685 auto POIter = PointerOps.begin(); 2686 for (Value *V : VL) { 2687 auto *L = cast<LoadInst>(V); 2688 if (!L->isSimple()) { 2689 BS.cancelScheduling(VL, VL0); 2690 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2691 ReuseShuffleIndicies); 2692 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple loads.\n"); 2693 return; 2694 } 2695 *POIter = L->getPointerOperand(); 2696 ++POIter; 2697 } 2698 2699 OrdersType CurrentOrder; 2700 // Check the order of pointer operands. 2701 if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) { 2702 Value *Ptr0; 2703 Value *PtrN; 2704 if (CurrentOrder.empty()) { 2705 Ptr0 = PointerOps.front(); 2706 PtrN = PointerOps.back(); 2707 } else { 2708 Ptr0 = PointerOps[CurrentOrder.front()]; 2709 PtrN = PointerOps[CurrentOrder.back()]; 2710 } 2711 const SCEV *Scev0 = SE->getSCEV(Ptr0); 2712 const SCEV *ScevN = SE->getSCEV(PtrN); 2713 const auto *Diff = 2714 dyn_cast<SCEVConstant>(SE->getMinusSCEV(ScevN, Scev0)); 2715 uint64_t Size = DL->getTypeAllocSize(ScalarTy); 2716 // Check that the sorted loads are consecutive. 2717 if (Diff && Diff->getAPInt() == (VL.size() - 1) * Size) { 2718 if (CurrentOrder.empty()) { 2719 // Original loads are consecutive and does not require reordering. 2720 ++NumOpsWantToKeepOriginalOrder; 2721 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, 2722 UserTreeIdx, ReuseShuffleIndicies); 2723 TE->setOperandsInOrder(); 2724 LLVM_DEBUG(dbgs() << "SLP: added a vector of loads.\n"); 2725 } else { 2726 // Need to reorder. 2727 auto I = NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first; 2728 ++I->getSecond(); 2729 TreeEntry *TE = 2730 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2731 ReuseShuffleIndicies, I->getFirst()); 2732 TE->setOperandsInOrder(); 2733 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled loads.\n"); 2734 } 2735 return; 2736 } 2737 } 2738 2739 LLVM_DEBUG(dbgs() << "SLP: Gathering non-consecutive loads.\n"); 2740 BS.cancelScheduling(VL, VL0); 2741 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2742 ReuseShuffleIndicies); 2743 return; 2744 } 2745 case Instruction::ZExt: 2746 case Instruction::SExt: 2747 case Instruction::FPToUI: 2748 case Instruction::FPToSI: 2749 case Instruction::FPExt: 2750 case Instruction::PtrToInt: 2751 case Instruction::IntToPtr: 2752 case Instruction::SIToFP: 2753 case Instruction::UIToFP: 2754 case Instruction::Trunc: 2755 case Instruction::FPTrunc: 2756 case Instruction::BitCast: { 2757 Type *SrcTy = VL0->getOperand(0)->getType(); 2758 for (Value *V : VL) { 2759 Type *Ty = cast<Instruction>(V)->getOperand(0)->getType(); 2760 if (Ty != SrcTy || !isValidElementType(Ty)) { 2761 BS.cancelScheduling(VL, VL0); 2762 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2763 ReuseShuffleIndicies); 2764 LLVM_DEBUG(dbgs() 2765 << "SLP: Gathering casts with different src types.\n"); 2766 return; 2767 } 2768 } 2769 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2770 ReuseShuffleIndicies); 2771 LLVM_DEBUG(dbgs() << "SLP: added a vector of casts.\n"); 2772 2773 TE->setOperandsInOrder(); 2774 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 2775 ValueList Operands; 2776 // Prepare the operand vector. 2777 for (Value *V : VL) 2778 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 2779 2780 buildTree_rec(Operands, Depth + 1, {TE, i}); 2781 } 2782 return; 2783 } 2784 case Instruction::ICmp: 2785 case Instruction::FCmp: { 2786 // Check that all of the compares have the same predicate. 2787 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 2788 CmpInst::Predicate SwapP0 = CmpInst::getSwappedPredicate(P0); 2789 Type *ComparedTy = VL0->getOperand(0)->getType(); 2790 for (Value *V : VL) { 2791 CmpInst *Cmp = cast<CmpInst>(V); 2792 if ((Cmp->getPredicate() != P0 && Cmp->getPredicate() != SwapP0) || 2793 Cmp->getOperand(0)->getType() != ComparedTy) { 2794 BS.cancelScheduling(VL, VL0); 2795 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2796 ReuseShuffleIndicies); 2797 LLVM_DEBUG(dbgs() 2798 << "SLP: Gathering cmp with different predicate.\n"); 2799 return; 2800 } 2801 } 2802 2803 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2804 ReuseShuffleIndicies); 2805 LLVM_DEBUG(dbgs() << "SLP: added a vector of compares.\n"); 2806 2807 ValueList Left, Right; 2808 if (cast<CmpInst>(VL0)->isCommutative()) { 2809 // Commutative predicate - collect + sort operands of the instructions 2810 // so that each side is more likely to have the same opcode. 2811 assert(P0 == SwapP0 && "Commutative Predicate mismatch"); 2812 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 2813 } else { 2814 // Collect operands - commute if it uses the swapped predicate. 2815 for (Value *V : VL) { 2816 auto *Cmp = cast<CmpInst>(V); 2817 Value *LHS = Cmp->getOperand(0); 2818 Value *RHS = Cmp->getOperand(1); 2819 if (Cmp->getPredicate() != P0) 2820 std::swap(LHS, RHS); 2821 Left.push_back(LHS); 2822 Right.push_back(RHS); 2823 } 2824 } 2825 TE->setOperand(0, Left); 2826 TE->setOperand(1, Right); 2827 buildTree_rec(Left, Depth + 1, {TE, 0}); 2828 buildTree_rec(Right, Depth + 1, {TE, 1}); 2829 return; 2830 } 2831 case Instruction::Select: 2832 case Instruction::FNeg: 2833 case Instruction::Add: 2834 case Instruction::FAdd: 2835 case Instruction::Sub: 2836 case Instruction::FSub: 2837 case Instruction::Mul: 2838 case Instruction::FMul: 2839 case Instruction::UDiv: 2840 case Instruction::SDiv: 2841 case Instruction::FDiv: 2842 case Instruction::URem: 2843 case Instruction::SRem: 2844 case Instruction::FRem: 2845 case Instruction::Shl: 2846 case Instruction::LShr: 2847 case Instruction::AShr: 2848 case Instruction::And: 2849 case Instruction::Or: 2850 case Instruction::Xor: { 2851 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2852 ReuseShuffleIndicies); 2853 LLVM_DEBUG(dbgs() << "SLP: added a vector of un/bin op.\n"); 2854 2855 // Sort operands of the instructions so that each side is more likely to 2856 // have the same opcode. 2857 if (isa<BinaryOperator>(VL0) && VL0->isCommutative()) { 2858 ValueList Left, Right; 2859 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 2860 TE->setOperand(0, Left); 2861 TE->setOperand(1, Right); 2862 buildTree_rec(Left, Depth + 1, {TE, 0}); 2863 buildTree_rec(Right, Depth + 1, {TE, 1}); 2864 return; 2865 } 2866 2867 TE->setOperandsInOrder(); 2868 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 2869 ValueList Operands; 2870 // Prepare the operand vector. 2871 for (Value *j : VL) 2872 Operands.push_back(cast<Instruction>(j)->getOperand(i)); 2873 2874 buildTree_rec(Operands, Depth + 1, {TE, i}); 2875 } 2876 return; 2877 } 2878 case Instruction::GetElementPtr: { 2879 // We don't combine GEPs with complicated (nested) indexing. 2880 for (Value *V : VL) { 2881 if (cast<Instruction>(V)->getNumOperands() != 2) { 2882 LLVM_DEBUG(dbgs() << "SLP: not-vectorizable GEP (nested indexes).\n"); 2883 BS.cancelScheduling(VL, VL0); 2884 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2885 ReuseShuffleIndicies); 2886 return; 2887 } 2888 } 2889 2890 // We can't combine several GEPs into one vector if they operate on 2891 // different types. 2892 Type *Ty0 = VL0->getOperand(0)->getType(); 2893 for (Value *V : VL) { 2894 Type *CurTy = cast<Instruction>(V)->getOperand(0)->getType(); 2895 if (Ty0 != CurTy) { 2896 LLVM_DEBUG(dbgs() 2897 << "SLP: not-vectorizable GEP (different types).\n"); 2898 BS.cancelScheduling(VL, VL0); 2899 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2900 ReuseShuffleIndicies); 2901 return; 2902 } 2903 } 2904 2905 // We don't combine GEPs with non-constant indexes. 2906 Type *Ty1 = VL0->getOperand(1)->getType(); 2907 for (Value *V : VL) { 2908 auto Op = cast<Instruction>(V)->getOperand(1); 2909 if (!isa<ConstantInt>(Op) || 2910 (Op->getType() != Ty1 && 2911 Op->getType()->getScalarSizeInBits() > 2912 DL->getIndexSizeInBits( 2913 V->getType()->getPointerAddressSpace()))) { 2914 LLVM_DEBUG(dbgs() 2915 << "SLP: not-vectorizable GEP (non-constant indexes).\n"); 2916 BS.cancelScheduling(VL, VL0); 2917 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2918 ReuseShuffleIndicies); 2919 return; 2920 } 2921 } 2922 2923 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2924 ReuseShuffleIndicies); 2925 LLVM_DEBUG(dbgs() << "SLP: added a vector of GEPs.\n"); 2926 TE->setOperandsInOrder(); 2927 for (unsigned i = 0, e = 2; i < e; ++i) { 2928 ValueList Operands; 2929 // Prepare the operand vector. 2930 for (Value *V : VL) 2931 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 2932 2933 buildTree_rec(Operands, Depth + 1, {TE, i}); 2934 } 2935 return; 2936 } 2937 case Instruction::Store: { 2938 // Check if the stores are consecutive or if we need to swizzle them. 2939 llvm::Type *ScalarTy = cast<StoreInst>(VL0)->getValueOperand()->getType(); 2940 // Make sure all stores in the bundle are simple - we can't vectorize 2941 // atomic or volatile stores. 2942 SmallVector<Value *, 4> PointerOps(VL.size()); 2943 ValueList Operands(VL.size()); 2944 auto POIter = PointerOps.begin(); 2945 auto OIter = Operands.begin(); 2946 for (Value *V : VL) { 2947 auto *SI = cast<StoreInst>(V); 2948 if (!SI->isSimple()) { 2949 BS.cancelScheduling(VL, VL0); 2950 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2951 ReuseShuffleIndicies); 2952 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple stores.\n"); 2953 return; 2954 } 2955 *POIter = SI->getPointerOperand(); 2956 *OIter = SI->getValueOperand(); 2957 ++POIter; 2958 ++OIter; 2959 } 2960 2961 OrdersType CurrentOrder; 2962 // Check the order of pointer operands. 2963 if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) { 2964 Value *Ptr0; 2965 Value *PtrN; 2966 if (CurrentOrder.empty()) { 2967 Ptr0 = PointerOps.front(); 2968 PtrN = PointerOps.back(); 2969 } else { 2970 Ptr0 = PointerOps[CurrentOrder.front()]; 2971 PtrN = PointerOps[CurrentOrder.back()]; 2972 } 2973 const SCEV *Scev0 = SE->getSCEV(Ptr0); 2974 const SCEV *ScevN = SE->getSCEV(PtrN); 2975 const auto *Diff = 2976 dyn_cast<SCEVConstant>(SE->getMinusSCEV(ScevN, Scev0)); 2977 uint64_t Size = DL->getTypeAllocSize(ScalarTy); 2978 // Check that the sorted pointer operands are consecutive. 2979 if (Diff && Diff->getAPInt() == (VL.size() - 1) * Size) { 2980 if (CurrentOrder.empty()) { 2981 // Original stores are consecutive and does not require reordering. 2982 ++NumOpsWantToKeepOriginalOrder; 2983 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, 2984 UserTreeIdx, ReuseShuffleIndicies); 2985 TE->setOperandsInOrder(); 2986 buildTree_rec(Operands, Depth + 1, {TE, 0}); 2987 LLVM_DEBUG(dbgs() << "SLP: added a vector of stores.\n"); 2988 } else { 2989 // Need to reorder. 2990 auto I = NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first; 2991 ++(I->getSecond()); 2992 TreeEntry *TE = 2993 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2994 ReuseShuffleIndicies, I->getFirst()); 2995 TE->setOperandsInOrder(); 2996 buildTree_rec(Operands, Depth + 1, {TE, 0}); 2997 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled stores.\n"); 2998 } 2999 return; 3000 } 3001 } 3002 3003 BS.cancelScheduling(VL, VL0); 3004 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3005 ReuseShuffleIndicies); 3006 LLVM_DEBUG(dbgs() << "SLP: Non-consecutive store.\n"); 3007 return; 3008 } 3009 case Instruction::Call: { 3010 // Check if the calls are all to the same vectorizable intrinsic. 3011 CallInst *CI = cast<CallInst>(VL0); 3012 // Check if this is an Intrinsic call or something that can be 3013 // represented by an intrinsic call 3014 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3015 if (!isTriviallyVectorizable(ID)) { 3016 BS.cancelScheduling(VL, VL0); 3017 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3018 ReuseShuffleIndicies); 3019 LLVM_DEBUG(dbgs() << "SLP: Non-vectorizable call.\n"); 3020 return; 3021 } 3022 Function *Int = CI->getCalledFunction(); 3023 unsigned NumArgs = CI->getNumArgOperands(); 3024 SmallVector<Value*, 4> ScalarArgs(NumArgs, nullptr); 3025 for (unsigned j = 0; j != NumArgs; ++j) 3026 if (hasVectorInstrinsicScalarOpd(ID, j)) 3027 ScalarArgs[j] = CI->getArgOperand(j); 3028 for (Value *V : VL) { 3029 CallInst *CI2 = dyn_cast<CallInst>(V); 3030 if (!CI2 || CI2->getCalledFunction() != Int || 3031 getVectorIntrinsicIDForCall(CI2, TLI) != ID || 3032 !CI->hasIdenticalOperandBundleSchema(*CI2)) { 3033 BS.cancelScheduling(VL, VL0); 3034 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3035 ReuseShuffleIndicies); 3036 LLVM_DEBUG(dbgs() << "SLP: mismatched calls:" << *CI << "!=" << *V 3037 << "\n"); 3038 return; 3039 } 3040 // Some intrinsics have scalar arguments and should be same in order for 3041 // them to be vectorized. 3042 for (unsigned j = 0; j != NumArgs; ++j) { 3043 if (hasVectorInstrinsicScalarOpd(ID, j)) { 3044 Value *A1J = CI2->getArgOperand(j); 3045 if (ScalarArgs[j] != A1J) { 3046 BS.cancelScheduling(VL, VL0); 3047 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3048 ReuseShuffleIndicies); 3049 LLVM_DEBUG(dbgs() << "SLP: mismatched arguments in call:" << *CI 3050 << " argument " << ScalarArgs[j] << "!=" << A1J 3051 << "\n"); 3052 return; 3053 } 3054 } 3055 } 3056 // Verify that the bundle operands are identical between the two calls. 3057 if (CI->hasOperandBundles() && 3058 !std::equal(CI->op_begin() + CI->getBundleOperandsStartIndex(), 3059 CI->op_begin() + CI->getBundleOperandsEndIndex(), 3060 CI2->op_begin() + CI2->getBundleOperandsStartIndex())) { 3061 BS.cancelScheduling(VL, VL0); 3062 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3063 ReuseShuffleIndicies); 3064 LLVM_DEBUG(dbgs() << "SLP: mismatched bundle operands in calls:" 3065 << *CI << "!=" << *V << '\n'); 3066 return; 3067 } 3068 } 3069 3070 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3071 ReuseShuffleIndicies); 3072 TE->setOperandsInOrder(); 3073 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 3074 ValueList Operands; 3075 // Prepare the operand vector. 3076 for (Value *V : VL) { 3077 auto *CI2 = cast<CallInst>(V); 3078 Operands.push_back(CI2->getArgOperand(i)); 3079 } 3080 buildTree_rec(Operands, Depth + 1, {TE, i}); 3081 } 3082 return; 3083 } 3084 case Instruction::ShuffleVector: { 3085 // If this is not an alternate sequence of opcode like add-sub 3086 // then do not vectorize this instruction. 3087 if (!S.isAltShuffle()) { 3088 BS.cancelScheduling(VL, VL0); 3089 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3090 ReuseShuffleIndicies); 3091 LLVM_DEBUG(dbgs() << "SLP: ShuffleVector are not vectorized.\n"); 3092 return; 3093 } 3094 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3095 ReuseShuffleIndicies); 3096 LLVM_DEBUG(dbgs() << "SLP: added a ShuffleVector op.\n"); 3097 3098 // Reorder operands if reordering would enable vectorization. 3099 if (isa<BinaryOperator>(VL0)) { 3100 ValueList Left, Right; 3101 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 3102 TE->setOperand(0, Left); 3103 TE->setOperand(1, Right); 3104 buildTree_rec(Left, Depth + 1, {TE, 0}); 3105 buildTree_rec(Right, Depth + 1, {TE, 1}); 3106 return; 3107 } 3108 3109 TE->setOperandsInOrder(); 3110 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 3111 ValueList Operands; 3112 // Prepare the operand vector. 3113 for (Value *V : VL) 3114 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3115 3116 buildTree_rec(Operands, Depth + 1, {TE, i}); 3117 } 3118 return; 3119 } 3120 default: 3121 BS.cancelScheduling(VL, VL0); 3122 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3123 ReuseShuffleIndicies); 3124 LLVM_DEBUG(dbgs() << "SLP: Gathering unknown instruction.\n"); 3125 return; 3126 } 3127 } 3128 3129 unsigned BoUpSLP::canMapToVector(Type *T, const DataLayout &DL) const { 3130 unsigned N = 1; 3131 Type *EltTy = T; 3132 3133 while (isa<StructType>(EltTy) || isa<ArrayType>(EltTy) || 3134 isa<VectorType>(EltTy)) { 3135 if (auto *ST = dyn_cast<StructType>(EltTy)) { 3136 // Check that struct is homogeneous. 3137 for (const auto *Ty : ST->elements()) 3138 if (Ty != *ST->element_begin()) 3139 return 0; 3140 N *= ST->getNumElements(); 3141 EltTy = *ST->element_begin(); 3142 } else if (auto *AT = dyn_cast<ArrayType>(EltTy)) { 3143 N *= AT->getNumElements(); 3144 EltTy = AT->getElementType(); 3145 } else { 3146 auto *VT = cast<VectorType>(EltTy); 3147 N *= VT->getNumElements(); 3148 EltTy = VT->getElementType(); 3149 } 3150 } 3151 3152 if (!isValidElementType(EltTy)) 3153 return 0; 3154 uint64_t VTSize = DL.getTypeStoreSizeInBits(VectorType::get(EltTy, N)); 3155 if (VTSize < MinVecRegSize || VTSize > MaxVecRegSize || VTSize != DL.getTypeStoreSizeInBits(T)) 3156 return 0; 3157 return N; 3158 } 3159 3160 bool BoUpSLP::canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 3161 SmallVectorImpl<unsigned> &CurrentOrder) const { 3162 Instruction *E0 = cast<Instruction>(OpValue); 3163 assert(E0->getOpcode() == Instruction::ExtractElement || 3164 E0->getOpcode() == Instruction::ExtractValue); 3165 assert(E0->getOpcode() == getSameOpcode(VL).getOpcode() && "Invalid opcode"); 3166 // Check if all of the extracts come from the same vector and from the 3167 // correct offset. 3168 Value *Vec = E0->getOperand(0); 3169 3170 CurrentOrder.clear(); 3171 3172 // We have to extract from a vector/aggregate with the same number of elements. 3173 unsigned NElts; 3174 if (E0->getOpcode() == Instruction::ExtractValue) { 3175 const DataLayout &DL = E0->getModule()->getDataLayout(); 3176 NElts = canMapToVector(Vec->getType(), DL); 3177 if (!NElts) 3178 return false; 3179 // Check if load can be rewritten as load of vector. 3180 LoadInst *LI = dyn_cast<LoadInst>(Vec); 3181 if (!LI || !LI->isSimple() || !LI->hasNUses(VL.size())) 3182 return false; 3183 } else { 3184 NElts = cast<VectorType>(Vec->getType())->getNumElements(); 3185 } 3186 3187 if (NElts != VL.size()) 3188 return false; 3189 3190 // Check that all of the indices extract from the correct offset. 3191 bool ShouldKeepOrder = true; 3192 unsigned E = VL.size(); 3193 // Assign to all items the initial value E + 1 so we can check if the extract 3194 // instruction index was used already. 3195 // Also, later we can check that all the indices are used and we have a 3196 // consecutive access in the extract instructions, by checking that no 3197 // element of CurrentOrder still has value E + 1. 3198 CurrentOrder.assign(E, E + 1); 3199 unsigned I = 0; 3200 for (; I < E; ++I) { 3201 auto *Inst = cast<Instruction>(VL[I]); 3202 if (Inst->getOperand(0) != Vec) 3203 break; 3204 Optional<unsigned> Idx = getExtractIndex(Inst); 3205 if (!Idx) 3206 break; 3207 const unsigned ExtIdx = *Idx; 3208 if (ExtIdx != I) { 3209 if (ExtIdx >= E || CurrentOrder[ExtIdx] != E + 1) 3210 break; 3211 ShouldKeepOrder = false; 3212 CurrentOrder[ExtIdx] = I; 3213 } else { 3214 if (CurrentOrder[I] != E + 1) 3215 break; 3216 CurrentOrder[I] = I; 3217 } 3218 } 3219 if (I < E) { 3220 CurrentOrder.clear(); 3221 return false; 3222 } 3223 3224 return ShouldKeepOrder; 3225 } 3226 3227 bool BoUpSLP::areAllUsersVectorized(Instruction *I) const { 3228 return I->hasOneUse() || 3229 std::all_of(I->user_begin(), I->user_end(), [this](User *U) { 3230 return ScalarToTreeEntry.count(U) > 0; 3231 }); 3232 } 3233 3234 static std::pair<unsigned, unsigned> 3235 getVectorCallCosts(CallInst *CI, VectorType *VecTy, TargetTransformInfo *TTI, 3236 TargetLibraryInfo *TLI) { 3237 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3238 3239 // Calculate the cost of the scalar and vector calls. 3240 FastMathFlags FMF; 3241 if (auto *FPMO = dyn_cast<FPMathOperator>(CI)) 3242 FMF = FPMO->getFastMathFlags(); 3243 3244 SmallVector<Value *, 4> Args(CI->arg_operands()); 3245 int IntrinsicCost = TTI->getIntrinsicInstrCost(ID, CI->getType(), Args, FMF, 3246 VecTy->getNumElements()); 3247 3248 auto Shape = 3249 VFShape::get(*CI, {static_cast<unsigned>(VecTy->getNumElements()), false}, 3250 false /*HasGlobalPred*/); 3251 Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape); 3252 int LibCost = IntrinsicCost; 3253 if (!CI->isNoBuiltin() && VecFunc) { 3254 // Calculate the cost of the vector library call. 3255 SmallVector<Type *, 4> VecTys; 3256 for (Use &Arg : CI->args()) 3257 VecTys.push_back( 3258 VectorType::get(Arg->getType(), VecTy->getNumElements())); 3259 3260 // If the corresponding vector call is cheaper, return its cost. 3261 LibCost = TTI->getCallInstrCost(nullptr, VecTy, VecTys); 3262 } 3263 return {IntrinsicCost, LibCost}; 3264 } 3265 3266 int BoUpSLP::getEntryCost(TreeEntry *E) { 3267 ArrayRef<Value*> VL = E->Scalars; 3268 3269 Type *ScalarTy = VL[0]->getType(); 3270 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 3271 ScalarTy = SI->getValueOperand()->getType(); 3272 else if (CmpInst *CI = dyn_cast<CmpInst>(VL[0])) 3273 ScalarTy = CI->getOperand(0)->getType(); 3274 VectorType *VecTy = VectorType::get(ScalarTy, VL.size()); 3275 3276 // If we have computed a smaller type for the expression, update VecTy so 3277 // that the costs will be accurate. 3278 if (MinBWs.count(VL[0])) 3279 VecTy = VectorType::get( 3280 IntegerType::get(F->getContext(), MinBWs[VL[0]].first), VL.size()); 3281 3282 unsigned ReuseShuffleNumbers = E->ReuseShuffleIndices.size(); 3283 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 3284 int ReuseShuffleCost = 0; 3285 if (NeedToShuffleReuses) { 3286 ReuseShuffleCost = 3287 TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3288 } 3289 if (E->State == TreeEntry::NeedToGather) { 3290 if (allConstant(VL)) 3291 return 0; 3292 if (isSplat(VL)) { 3293 return ReuseShuffleCost + 3294 TTI->getShuffleCost(TargetTransformInfo::SK_Broadcast, VecTy, 0); 3295 } 3296 if (E->getOpcode() == Instruction::ExtractElement && 3297 allSameType(VL) && allSameBlock(VL)) { 3298 Optional<TargetTransformInfo::ShuffleKind> ShuffleKind = isShuffle(VL); 3299 if (ShuffleKind.hasValue()) { 3300 int Cost = TTI->getShuffleCost(ShuffleKind.getValue(), VecTy); 3301 for (auto *V : VL) { 3302 // If all users of instruction are going to be vectorized and this 3303 // instruction itself is not going to be vectorized, consider this 3304 // instruction as dead and remove its cost from the final cost of the 3305 // vectorized tree. 3306 if (areAllUsersVectorized(cast<Instruction>(V)) && 3307 !ScalarToTreeEntry.count(V)) { 3308 auto *IO = cast<ConstantInt>( 3309 cast<ExtractElementInst>(V)->getIndexOperand()); 3310 Cost -= TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, 3311 IO->getZExtValue()); 3312 } 3313 } 3314 return ReuseShuffleCost + Cost; 3315 } 3316 } 3317 return ReuseShuffleCost + getGatherCost(VL); 3318 } 3319 assert(E->State == TreeEntry::Vectorize && "Unhandled state"); 3320 assert(E->getOpcode() && allSameType(VL) && allSameBlock(VL) && "Invalid VL"); 3321 Instruction *VL0 = E->getMainOp(); 3322 unsigned ShuffleOrOp = 3323 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 3324 switch (ShuffleOrOp) { 3325 case Instruction::PHI: 3326 return 0; 3327 3328 case Instruction::ExtractValue: 3329 case Instruction::ExtractElement: { 3330 if (NeedToShuffleReuses) { 3331 unsigned Idx = 0; 3332 for (unsigned I : E->ReuseShuffleIndices) { 3333 if (ShuffleOrOp == Instruction::ExtractElement) { 3334 auto *IO = cast<ConstantInt>( 3335 cast<ExtractElementInst>(VL[I])->getIndexOperand()); 3336 Idx = IO->getZExtValue(); 3337 ReuseShuffleCost -= TTI->getVectorInstrCost( 3338 Instruction::ExtractElement, VecTy, Idx); 3339 } else { 3340 ReuseShuffleCost -= TTI->getVectorInstrCost( 3341 Instruction::ExtractElement, VecTy, Idx); 3342 ++Idx; 3343 } 3344 } 3345 Idx = ReuseShuffleNumbers; 3346 for (Value *V : VL) { 3347 if (ShuffleOrOp == Instruction::ExtractElement) { 3348 auto *IO = cast<ConstantInt>( 3349 cast<ExtractElementInst>(V)->getIndexOperand()); 3350 Idx = IO->getZExtValue(); 3351 } else { 3352 --Idx; 3353 } 3354 ReuseShuffleCost += 3355 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, Idx); 3356 } 3357 } 3358 int DeadCost = ReuseShuffleCost; 3359 if (!E->ReorderIndices.empty()) { 3360 // TODO: Merge this shuffle with the ReuseShuffleCost. 3361 DeadCost += TTI->getShuffleCost( 3362 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3363 } 3364 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 3365 Instruction *E = cast<Instruction>(VL[i]); 3366 // If all users are going to be vectorized, instruction can be 3367 // considered as dead. 3368 // The same, if have only one user, it will be vectorized for sure. 3369 if (areAllUsersVectorized(E)) { 3370 // Take credit for instruction that will become dead. 3371 if (E->hasOneUse()) { 3372 Instruction *Ext = E->user_back(); 3373 if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) && 3374 all_of(Ext->users(), 3375 [](User *U) { return isa<GetElementPtrInst>(U); })) { 3376 // Use getExtractWithExtendCost() to calculate the cost of 3377 // extractelement/ext pair. 3378 DeadCost -= TTI->getExtractWithExtendCost( 3379 Ext->getOpcode(), Ext->getType(), VecTy, i); 3380 // Add back the cost of s|zext which is subtracted separately. 3381 DeadCost += TTI->getCastInstrCost( 3382 Ext->getOpcode(), Ext->getType(), E->getType(), Ext); 3383 continue; 3384 } 3385 } 3386 DeadCost -= 3387 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, i); 3388 } 3389 } 3390 return DeadCost; 3391 } 3392 case Instruction::ZExt: 3393 case Instruction::SExt: 3394 case Instruction::FPToUI: 3395 case Instruction::FPToSI: 3396 case Instruction::FPExt: 3397 case Instruction::PtrToInt: 3398 case Instruction::IntToPtr: 3399 case Instruction::SIToFP: 3400 case Instruction::UIToFP: 3401 case Instruction::Trunc: 3402 case Instruction::FPTrunc: 3403 case Instruction::BitCast: { 3404 Type *SrcTy = VL0->getOperand(0)->getType(); 3405 int ScalarEltCost = 3406 TTI->getCastInstrCost(E->getOpcode(), ScalarTy, SrcTy, VL0); 3407 if (NeedToShuffleReuses) { 3408 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3409 } 3410 3411 // Calculate the cost of this instruction. 3412 int ScalarCost = VL.size() * ScalarEltCost; 3413 3414 VectorType *SrcVecTy = VectorType::get(SrcTy, VL.size()); 3415 int VecCost = 0; 3416 // Check if the values are candidates to demote. 3417 if (!MinBWs.count(VL0) || VecTy != SrcVecTy) { 3418 VecCost = ReuseShuffleCost + 3419 TTI->getCastInstrCost(E->getOpcode(), VecTy, SrcVecTy, VL0); 3420 } 3421 return VecCost - ScalarCost; 3422 } 3423 case Instruction::FCmp: 3424 case Instruction::ICmp: 3425 case Instruction::Select: { 3426 // Calculate the cost of this instruction. 3427 int ScalarEltCost = TTI->getCmpSelInstrCost(E->getOpcode(), ScalarTy, 3428 Builder.getInt1Ty(), VL0); 3429 if (NeedToShuffleReuses) { 3430 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3431 } 3432 VectorType *MaskTy = VectorType::get(Builder.getInt1Ty(), VL.size()); 3433 int ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3434 int VecCost = TTI->getCmpSelInstrCost(E->getOpcode(), VecTy, MaskTy, VL0); 3435 return ReuseShuffleCost + VecCost - ScalarCost; 3436 } 3437 case Instruction::FNeg: 3438 case Instruction::Add: 3439 case Instruction::FAdd: 3440 case Instruction::Sub: 3441 case Instruction::FSub: 3442 case Instruction::Mul: 3443 case Instruction::FMul: 3444 case Instruction::UDiv: 3445 case Instruction::SDiv: 3446 case Instruction::FDiv: 3447 case Instruction::URem: 3448 case Instruction::SRem: 3449 case Instruction::FRem: 3450 case Instruction::Shl: 3451 case Instruction::LShr: 3452 case Instruction::AShr: 3453 case Instruction::And: 3454 case Instruction::Or: 3455 case Instruction::Xor: { 3456 // Certain instructions can be cheaper to vectorize if they have a 3457 // constant second vector operand. 3458 TargetTransformInfo::OperandValueKind Op1VK = 3459 TargetTransformInfo::OK_AnyValue; 3460 TargetTransformInfo::OperandValueKind Op2VK = 3461 TargetTransformInfo::OK_UniformConstantValue; 3462 TargetTransformInfo::OperandValueProperties Op1VP = 3463 TargetTransformInfo::OP_None; 3464 TargetTransformInfo::OperandValueProperties Op2VP = 3465 TargetTransformInfo::OP_PowerOf2; 3466 3467 // If all operands are exactly the same ConstantInt then set the 3468 // operand kind to OK_UniformConstantValue. 3469 // If instead not all operands are constants, then set the operand kind 3470 // to OK_AnyValue. If all operands are constants but not the same, 3471 // then set the operand kind to OK_NonUniformConstantValue. 3472 ConstantInt *CInt0 = nullptr; 3473 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 3474 const Instruction *I = cast<Instruction>(VL[i]); 3475 unsigned OpIdx = isa<BinaryOperator>(I) ? 1 : 0; 3476 ConstantInt *CInt = dyn_cast<ConstantInt>(I->getOperand(OpIdx)); 3477 if (!CInt) { 3478 Op2VK = TargetTransformInfo::OK_AnyValue; 3479 Op2VP = TargetTransformInfo::OP_None; 3480 break; 3481 } 3482 if (Op2VP == TargetTransformInfo::OP_PowerOf2 && 3483 !CInt->getValue().isPowerOf2()) 3484 Op2VP = TargetTransformInfo::OP_None; 3485 if (i == 0) { 3486 CInt0 = CInt; 3487 continue; 3488 } 3489 if (CInt0 != CInt) 3490 Op2VK = TargetTransformInfo::OK_NonUniformConstantValue; 3491 } 3492 3493 SmallVector<const Value *, 4> Operands(VL0->operand_values()); 3494 int ScalarEltCost = TTI->getArithmeticInstrCost( 3495 E->getOpcode(), ScalarTy, Op1VK, Op2VK, Op1VP, Op2VP, Operands, VL0); 3496 if (NeedToShuffleReuses) { 3497 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3498 } 3499 int ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3500 int VecCost = TTI->getArithmeticInstrCost( 3501 E->getOpcode(), VecTy, Op1VK, Op2VK, Op1VP, Op2VP, Operands, VL0); 3502 return ReuseShuffleCost + VecCost - ScalarCost; 3503 } 3504 case Instruction::GetElementPtr: { 3505 TargetTransformInfo::OperandValueKind Op1VK = 3506 TargetTransformInfo::OK_AnyValue; 3507 TargetTransformInfo::OperandValueKind Op2VK = 3508 TargetTransformInfo::OK_UniformConstantValue; 3509 3510 int ScalarEltCost = 3511 TTI->getArithmeticInstrCost(Instruction::Add, ScalarTy, Op1VK, Op2VK); 3512 if (NeedToShuffleReuses) { 3513 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3514 } 3515 int ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3516 int VecCost = 3517 TTI->getArithmeticInstrCost(Instruction::Add, VecTy, Op1VK, Op2VK); 3518 return ReuseShuffleCost + VecCost - ScalarCost; 3519 } 3520 case Instruction::Load: { 3521 // Cost of wide load - cost of scalar loads. 3522 MaybeAlign alignment(cast<LoadInst>(VL0)->getAlignment()); 3523 int ScalarEltCost = 3524 TTI->getMemoryOpCost(Instruction::Load, ScalarTy, alignment, 0, VL0); 3525 if (NeedToShuffleReuses) { 3526 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3527 } 3528 int ScalarLdCost = VecTy->getNumElements() * ScalarEltCost; 3529 int VecLdCost = 3530 TTI->getMemoryOpCost(Instruction::Load, VecTy, alignment, 0, VL0); 3531 if (!E->ReorderIndices.empty()) { 3532 // TODO: Merge this shuffle with the ReuseShuffleCost. 3533 VecLdCost += TTI->getShuffleCost( 3534 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3535 } 3536 return ReuseShuffleCost + VecLdCost - ScalarLdCost; 3537 } 3538 case Instruction::Store: { 3539 // We know that we can merge the stores. Calculate the cost. 3540 bool IsReorder = !E->ReorderIndices.empty(); 3541 auto *SI = 3542 cast<StoreInst>(IsReorder ? VL[E->ReorderIndices.front()] : VL0); 3543 MaybeAlign Alignment(SI->getAlignment()); 3544 int ScalarEltCost = 3545 TTI->getMemoryOpCost(Instruction::Store, ScalarTy, Alignment, 0, VL0); 3546 if (NeedToShuffleReuses) 3547 ReuseShuffleCost = -(ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3548 int ScalarStCost = VecTy->getNumElements() * ScalarEltCost; 3549 int VecStCost = TTI->getMemoryOpCost(Instruction::Store, 3550 VecTy, Alignment, 0, VL0); 3551 if (IsReorder) { 3552 // TODO: Merge this shuffle with the ReuseShuffleCost. 3553 VecStCost += TTI->getShuffleCost( 3554 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3555 } 3556 return ReuseShuffleCost + VecStCost - ScalarStCost; 3557 } 3558 case Instruction::Call: { 3559 CallInst *CI = cast<CallInst>(VL0); 3560 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3561 3562 // Calculate the cost of the scalar and vector calls. 3563 SmallVector<Type *, 4> ScalarTys; 3564 for (unsigned op = 0, opc = CI->getNumArgOperands(); op != opc; ++op) 3565 ScalarTys.push_back(CI->getArgOperand(op)->getType()); 3566 3567 FastMathFlags FMF; 3568 if (auto *FPMO = dyn_cast<FPMathOperator>(CI)) 3569 FMF = FPMO->getFastMathFlags(); 3570 3571 int ScalarEltCost = 3572 TTI->getIntrinsicInstrCost(ID, ScalarTy, ScalarTys, FMF); 3573 if (NeedToShuffleReuses) { 3574 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3575 } 3576 int ScalarCallCost = VecTy->getNumElements() * ScalarEltCost; 3577 3578 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 3579 int VecCallCost = std::min(VecCallCosts.first, VecCallCosts.second); 3580 3581 LLVM_DEBUG(dbgs() << "SLP: Call cost " << VecCallCost - ScalarCallCost 3582 << " (" << VecCallCost << "-" << ScalarCallCost << ")" 3583 << " for " << *CI << "\n"); 3584 3585 return ReuseShuffleCost + VecCallCost - ScalarCallCost; 3586 } 3587 case Instruction::ShuffleVector: { 3588 assert(E->isAltShuffle() && 3589 ((Instruction::isBinaryOp(E->getOpcode()) && 3590 Instruction::isBinaryOp(E->getAltOpcode())) || 3591 (Instruction::isCast(E->getOpcode()) && 3592 Instruction::isCast(E->getAltOpcode()))) && 3593 "Invalid Shuffle Vector Operand"); 3594 int ScalarCost = 0; 3595 if (NeedToShuffleReuses) { 3596 for (unsigned Idx : E->ReuseShuffleIndices) { 3597 Instruction *I = cast<Instruction>(VL[Idx]); 3598 ReuseShuffleCost -= TTI->getInstructionCost( 3599 I, TargetTransformInfo::TCK_RecipThroughput); 3600 } 3601 for (Value *V : VL) { 3602 Instruction *I = cast<Instruction>(V); 3603 ReuseShuffleCost += TTI->getInstructionCost( 3604 I, TargetTransformInfo::TCK_RecipThroughput); 3605 } 3606 } 3607 for (Value *V : VL) { 3608 Instruction *I = cast<Instruction>(V); 3609 assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode"); 3610 ScalarCost += TTI->getInstructionCost( 3611 I, TargetTransformInfo::TCK_RecipThroughput); 3612 } 3613 // VecCost is equal to sum of the cost of creating 2 vectors 3614 // and the cost of creating shuffle. 3615 int VecCost = 0; 3616 if (Instruction::isBinaryOp(E->getOpcode())) { 3617 VecCost = TTI->getArithmeticInstrCost(E->getOpcode(), VecTy); 3618 VecCost += TTI->getArithmeticInstrCost(E->getAltOpcode(), VecTy); 3619 } else { 3620 Type *Src0SclTy = E->getMainOp()->getOperand(0)->getType(); 3621 Type *Src1SclTy = E->getAltOp()->getOperand(0)->getType(); 3622 VectorType *Src0Ty = VectorType::get(Src0SclTy, VL.size()); 3623 VectorType *Src1Ty = VectorType::get(Src1SclTy, VL.size()); 3624 VecCost = TTI->getCastInstrCost(E->getOpcode(), VecTy, Src0Ty); 3625 VecCost += TTI->getCastInstrCost(E->getAltOpcode(), VecTy, Src1Ty); 3626 } 3627 VecCost += TTI->getShuffleCost(TargetTransformInfo::SK_Select, VecTy, 0); 3628 return ReuseShuffleCost + VecCost - ScalarCost; 3629 } 3630 default: 3631 llvm_unreachable("Unknown instruction"); 3632 } 3633 } 3634 3635 bool BoUpSLP::isFullyVectorizableTinyTree() const { 3636 LLVM_DEBUG(dbgs() << "SLP: Check whether the tree with height " 3637 << VectorizableTree.size() << " is fully vectorizable .\n"); 3638 3639 // We only handle trees of heights 1 and 2. 3640 if (VectorizableTree.size() == 1 && 3641 VectorizableTree[0]->State == TreeEntry::Vectorize) 3642 return true; 3643 3644 if (VectorizableTree.size() != 2) 3645 return false; 3646 3647 // Handle splat and all-constants stores. 3648 if (VectorizableTree[0]->State == TreeEntry::Vectorize && 3649 (allConstant(VectorizableTree[1]->Scalars) || 3650 isSplat(VectorizableTree[1]->Scalars))) 3651 return true; 3652 3653 // Gathering cost would be too much for tiny trees. 3654 if (VectorizableTree[0]->State == TreeEntry::NeedToGather || 3655 VectorizableTree[1]->State == TreeEntry::NeedToGather) 3656 return false; 3657 3658 return true; 3659 } 3660 3661 bool BoUpSLP::isLoadCombineReductionCandidate(unsigned RdxOpcode) const { 3662 if (RdxOpcode != Instruction::Or) 3663 return false; 3664 3665 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 3666 Value *FirstReduced = VectorizableTree[0]->Scalars[0]; 3667 3668 // Look past the reduction to find a source value. Arbitrarily follow the 3669 // path through operand 0 of any 'or'. Also, peek through optional 3670 // shift-left-by-constant. 3671 Value *ZextLoad = FirstReduced; 3672 while (match(ZextLoad, m_Or(m_Value(), m_Value())) || 3673 match(ZextLoad, m_Shl(m_Value(), m_Constant()))) 3674 ZextLoad = cast<BinaryOperator>(ZextLoad)->getOperand(0); 3675 3676 // Check if the input to the reduction is an extended load. 3677 Value *LoadPtr; 3678 if (!match(ZextLoad, m_ZExt(m_Load(m_Value(LoadPtr))))) 3679 return false; 3680 3681 // Require that the total load bit width is a legal integer type. 3682 // For example, <8 x i8> --> i64 is a legal integer on a 64-bit target. 3683 // But <16 x i8> --> i128 is not, so the backend probably can't reduce it. 3684 Type *SrcTy = LoadPtr->getType()->getPointerElementType(); 3685 unsigned LoadBitWidth = SrcTy->getIntegerBitWidth() * NumElts; 3686 LLVMContext &Context = FirstReduced->getContext(); 3687 if (!TTI->isTypeLegal(IntegerType::get(Context, LoadBitWidth))) 3688 return false; 3689 3690 // Everything matched - assume that we can fold the whole sequence using 3691 // load combining. 3692 LLVM_DEBUG(dbgs() << "SLP: Assume load combining for scalar reduction of " 3693 << *(cast<Instruction>(FirstReduced)) << "\n"); 3694 3695 return true; 3696 } 3697 3698 bool BoUpSLP::isTreeTinyAndNotFullyVectorizable() const { 3699 // We can vectorize the tree if its size is greater than or equal to the 3700 // minimum size specified by the MinTreeSize command line option. 3701 if (VectorizableTree.size() >= MinTreeSize) 3702 return false; 3703 3704 // If we have a tiny tree (a tree whose size is less than MinTreeSize), we 3705 // can vectorize it if we can prove it fully vectorizable. 3706 if (isFullyVectorizableTinyTree()) 3707 return false; 3708 3709 assert(VectorizableTree.empty() 3710 ? ExternalUses.empty() 3711 : true && "We shouldn't have any external users"); 3712 3713 // Otherwise, we can't vectorize the tree. It is both tiny and not fully 3714 // vectorizable. 3715 return true; 3716 } 3717 3718 int BoUpSLP::getSpillCost() const { 3719 // Walk from the bottom of the tree to the top, tracking which values are 3720 // live. When we see a call instruction that is not part of our tree, 3721 // query TTI to see if there is a cost to keeping values live over it 3722 // (for example, if spills and fills are required). 3723 unsigned BundleWidth = VectorizableTree.front()->Scalars.size(); 3724 int Cost = 0; 3725 3726 SmallPtrSet<Instruction*, 4> LiveValues; 3727 Instruction *PrevInst = nullptr; 3728 3729 for (const auto &TEPtr : VectorizableTree) { 3730 Instruction *Inst = dyn_cast<Instruction>(TEPtr->Scalars[0]); 3731 if (!Inst) 3732 continue; 3733 3734 if (!PrevInst) { 3735 PrevInst = Inst; 3736 continue; 3737 } 3738 3739 // Update LiveValues. 3740 LiveValues.erase(PrevInst); 3741 for (auto &J : PrevInst->operands()) { 3742 if (isa<Instruction>(&*J) && getTreeEntry(&*J)) 3743 LiveValues.insert(cast<Instruction>(&*J)); 3744 } 3745 3746 LLVM_DEBUG({ 3747 dbgs() << "SLP: #LV: " << LiveValues.size(); 3748 for (auto *X : LiveValues) 3749 dbgs() << " " << X->getName(); 3750 dbgs() << ", Looking at "; 3751 Inst->dump(); 3752 }); 3753 3754 // Now find the sequence of instructions between PrevInst and Inst. 3755 unsigned NumCalls = 0; 3756 BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(), 3757 PrevInstIt = 3758 PrevInst->getIterator().getReverse(); 3759 while (InstIt != PrevInstIt) { 3760 if (PrevInstIt == PrevInst->getParent()->rend()) { 3761 PrevInstIt = Inst->getParent()->rbegin(); 3762 continue; 3763 } 3764 3765 // Debug information does not impact spill cost. 3766 if ((isa<CallInst>(&*PrevInstIt) && 3767 !isa<DbgInfoIntrinsic>(&*PrevInstIt)) && 3768 &*PrevInstIt != PrevInst) 3769 NumCalls++; 3770 3771 ++PrevInstIt; 3772 } 3773 3774 if (NumCalls) { 3775 SmallVector<Type*, 4> V; 3776 for (auto *II : LiveValues) 3777 V.push_back(VectorType::get(II->getType(), BundleWidth)); 3778 Cost += NumCalls * TTI->getCostOfKeepingLiveOverCall(V); 3779 } 3780 3781 PrevInst = Inst; 3782 } 3783 3784 return Cost; 3785 } 3786 3787 int BoUpSLP::getTreeCost() { 3788 int Cost = 0; 3789 LLVM_DEBUG(dbgs() << "SLP: Calculating cost for tree of size " 3790 << VectorizableTree.size() << ".\n"); 3791 3792 unsigned BundleWidth = VectorizableTree[0]->Scalars.size(); 3793 3794 for (unsigned I = 0, E = VectorizableTree.size(); I < E; ++I) { 3795 TreeEntry &TE = *VectorizableTree[I].get(); 3796 3797 // We create duplicate tree entries for gather sequences that have multiple 3798 // uses. However, we should not compute the cost of duplicate sequences. 3799 // For example, if we have a build vector (i.e., insertelement sequence) 3800 // that is used by more than one vector instruction, we only need to 3801 // compute the cost of the insertelement instructions once. The redundant 3802 // instructions will be eliminated by CSE. 3803 // 3804 // We should consider not creating duplicate tree entries for gather 3805 // sequences, and instead add additional edges to the tree representing 3806 // their uses. Since such an approach results in fewer total entries, 3807 // existing heuristics based on tree size may yield different results. 3808 // 3809 if (TE.State == TreeEntry::NeedToGather && 3810 std::any_of(std::next(VectorizableTree.begin(), I + 1), 3811 VectorizableTree.end(), 3812 [TE](const std::unique_ptr<TreeEntry> &EntryPtr) { 3813 return EntryPtr->State == TreeEntry::NeedToGather && 3814 EntryPtr->isSame(TE.Scalars); 3815 })) 3816 continue; 3817 3818 int C = getEntryCost(&TE); 3819 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C 3820 << " for bundle that starts with " << *TE.Scalars[0] 3821 << ".\n"); 3822 Cost += C; 3823 } 3824 3825 SmallPtrSet<Value *, 16> ExtractCostCalculated; 3826 int ExtractCost = 0; 3827 for (ExternalUser &EU : ExternalUses) { 3828 // We only add extract cost once for the same scalar. 3829 if (!ExtractCostCalculated.insert(EU.Scalar).second) 3830 continue; 3831 3832 // Uses by ephemeral values are free (because the ephemeral value will be 3833 // removed prior to code generation, and so the extraction will be 3834 // removed as well). 3835 if (EphValues.count(EU.User)) 3836 continue; 3837 3838 // If we plan to rewrite the tree in a smaller type, we will need to sign 3839 // extend the extracted value back to the original type. Here, we account 3840 // for the extract and the added cost of the sign extend if needed. 3841 auto *VecTy = VectorType::get(EU.Scalar->getType(), BundleWidth); 3842 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 3843 if (MinBWs.count(ScalarRoot)) { 3844 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 3845 auto Extend = 3846 MinBWs[ScalarRoot].second ? Instruction::SExt : Instruction::ZExt; 3847 VecTy = VectorType::get(MinTy, BundleWidth); 3848 ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(), 3849 VecTy, EU.Lane); 3850 } else { 3851 ExtractCost += 3852 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, EU.Lane); 3853 } 3854 } 3855 3856 int SpillCost = getSpillCost(); 3857 Cost += SpillCost + ExtractCost; 3858 3859 std::string Str; 3860 { 3861 raw_string_ostream OS(Str); 3862 OS << "SLP: Spill Cost = " << SpillCost << ".\n" 3863 << "SLP: Extract Cost = " << ExtractCost << ".\n" 3864 << "SLP: Total Cost = " << Cost << ".\n"; 3865 } 3866 LLVM_DEBUG(dbgs() << Str); 3867 3868 if (ViewSLPTree) 3869 ViewGraph(this, "SLP" + F->getName(), false, Str); 3870 3871 return Cost; 3872 } 3873 3874 int BoUpSLP::getGatherCost(Type *Ty, 3875 const DenseSet<unsigned> &ShuffledIndices) const { 3876 int Cost = 0; 3877 for (unsigned i = 0, e = cast<VectorType>(Ty)->getNumElements(); i < e; ++i) 3878 if (!ShuffledIndices.count(i)) 3879 Cost += TTI->getVectorInstrCost(Instruction::InsertElement, Ty, i); 3880 if (!ShuffledIndices.empty()) 3881 Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, Ty); 3882 return Cost; 3883 } 3884 3885 int BoUpSLP::getGatherCost(ArrayRef<Value *> VL) const { 3886 // Find the type of the operands in VL. 3887 Type *ScalarTy = VL[0]->getType(); 3888 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 3889 ScalarTy = SI->getValueOperand()->getType(); 3890 VectorType *VecTy = VectorType::get(ScalarTy, VL.size()); 3891 // Find the cost of inserting/extracting values from the vector. 3892 // Check if the same elements are inserted several times and count them as 3893 // shuffle candidates. 3894 DenseSet<unsigned> ShuffledElements; 3895 DenseSet<Value *> UniqueElements; 3896 // Iterate in reverse order to consider insert elements with the high cost. 3897 for (unsigned I = VL.size(); I > 0; --I) { 3898 unsigned Idx = I - 1; 3899 if (!UniqueElements.insert(VL[Idx]).second) 3900 ShuffledElements.insert(Idx); 3901 } 3902 return getGatherCost(VecTy, ShuffledElements); 3903 } 3904 3905 // Perform operand reordering on the instructions in VL and return the reordered 3906 // operands in Left and Right. 3907 void BoUpSLP::reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 3908 SmallVectorImpl<Value *> &Left, 3909 SmallVectorImpl<Value *> &Right, 3910 const DataLayout &DL, 3911 ScalarEvolution &SE, 3912 const BoUpSLP &R) { 3913 if (VL.empty()) 3914 return; 3915 VLOperands Ops(VL, DL, SE, R); 3916 // Reorder the operands in place. 3917 Ops.reorder(); 3918 Left = Ops.getVL(0); 3919 Right = Ops.getVL(1); 3920 } 3921 3922 void BoUpSLP::setInsertPointAfterBundle(TreeEntry *E) { 3923 // Get the basic block this bundle is in. All instructions in the bundle 3924 // should be in this block. 3925 auto *Front = E->getMainOp(); 3926 auto *BB = Front->getParent(); 3927 assert(llvm::all_of(make_range(E->Scalars.begin(), E->Scalars.end()), 3928 [=](Value *V) -> bool { 3929 auto *I = cast<Instruction>(V); 3930 return !E->isOpcodeOrAlt(I) || I->getParent() == BB; 3931 })); 3932 3933 // The last instruction in the bundle in program order. 3934 Instruction *LastInst = nullptr; 3935 3936 // Find the last instruction. The common case should be that BB has been 3937 // scheduled, and the last instruction is VL.back(). So we start with 3938 // VL.back() and iterate over schedule data until we reach the end of the 3939 // bundle. The end of the bundle is marked by null ScheduleData. 3940 if (BlocksSchedules.count(BB)) { 3941 auto *Bundle = 3942 BlocksSchedules[BB]->getScheduleData(E->isOneOf(E->Scalars.back())); 3943 if (Bundle && Bundle->isPartOfBundle()) 3944 for (; Bundle; Bundle = Bundle->NextInBundle) 3945 if (Bundle->OpValue == Bundle->Inst) 3946 LastInst = Bundle->Inst; 3947 } 3948 3949 // LastInst can still be null at this point if there's either not an entry 3950 // for BB in BlocksSchedules or there's no ScheduleData available for 3951 // VL.back(). This can be the case if buildTree_rec aborts for various 3952 // reasons (e.g., the maximum recursion depth is reached, the maximum region 3953 // size is reached, etc.). ScheduleData is initialized in the scheduling 3954 // "dry-run". 3955 // 3956 // If this happens, we can still find the last instruction by brute force. We 3957 // iterate forwards from Front (inclusive) until we either see all 3958 // instructions in the bundle or reach the end of the block. If Front is the 3959 // last instruction in program order, LastInst will be set to Front, and we 3960 // will visit all the remaining instructions in the block. 3961 // 3962 // One of the reasons we exit early from buildTree_rec is to place an upper 3963 // bound on compile-time. Thus, taking an additional compile-time hit here is 3964 // not ideal. However, this should be exceedingly rare since it requires that 3965 // we both exit early from buildTree_rec and that the bundle be out-of-order 3966 // (causing us to iterate all the way to the end of the block). 3967 if (!LastInst) { 3968 SmallPtrSet<Value *, 16> Bundle(E->Scalars.begin(), E->Scalars.end()); 3969 for (auto &I : make_range(BasicBlock::iterator(Front), BB->end())) { 3970 if (Bundle.erase(&I) && E->isOpcodeOrAlt(&I)) 3971 LastInst = &I; 3972 if (Bundle.empty()) 3973 break; 3974 } 3975 } 3976 assert(LastInst && "Failed to find last instruction in bundle"); 3977 3978 // Set the insertion point after the last instruction in the bundle. Set the 3979 // debug location to Front. 3980 Builder.SetInsertPoint(BB, ++LastInst->getIterator()); 3981 Builder.SetCurrentDebugLocation(Front->getDebugLoc()); 3982 } 3983 3984 Value *BoUpSLP::Gather(ArrayRef<Value *> VL, VectorType *Ty) { 3985 Value *Vec = UndefValue::get(Ty); 3986 // Generate the 'InsertElement' instruction. 3987 for (unsigned i = 0; i < Ty->getNumElements(); ++i) { 3988 Vec = Builder.CreateInsertElement(Vec, VL[i], Builder.getInt32(i)); 3989 if (auto *Insrt = dyn_cast<InsertElementInst>(Vec)) { 3990 GatherSeq.insert(Insrt); 3991 CSEBlocks.insert(Insrt->getParent()); 3992 3993 // Add to our 'need-to-extract' list. 3994 if (TreeEntry *E = getTreeEntry(VL[i])) { 3995 // Find which lane we need to extract. 3996 int FoundLane = -1; 3997 for (unsigned Lane = 0, LE = E->Scalars.size(); Lane != LE; ++Lane) { 3998 // Is this the lane of the scalar that we are looking for ? 3999 if (E->Scalars[Lane] == VL[i]) { 4000 FoundLane = Lane; 4001 break; 4002 } 4003 } 4004 assert(FoundLane >= 0 && "Could not find the correct lane"); 4005 if (!E->ReuseShuffleIndices.empty()) { 4006 FoundLane = 4007 std::distance(E->ReuseShuffleIndices.begin(), 4008 llvm::find(E->ReuseShuffleIndices, FoundLane)); 4009 } 4010 ExternalUses.push_back(ExternalUser(VL[i], Insrt, FoundLane)); 4011 } 4012 } 4013 } 4014 4015 return Vec; 4016 } 4017 4018 Value *BoUpSLP::vectorizeTree(ArrayRef<Value *> VL) { 4019 InstructionsState S = getSameOpcode(VL); 4020 if (S.getOpcode()) { 4021 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 4022 if (E->isSame(VL)) { 4023 Value *V = vectorizeTree(E); 4024 if (VL.size() == E->Scalars.size() && !E->ReuseShuffleIndices.empty()) { 4025 // We need to get the vectorized value but without shuffle. 4026 if (auto *SV = dyn_cast<ShuffleVectorInst>(V)) { 4027 V = SV->getOperand(0); 4028 } else { 4029 // Reshuffle to get only unique values. 4030 SmallVector<int, 4> UniqueIdxs; 4031 SmallSet<int, 4> UsedIdxs; 4032 for (int Idx : E->ReuseShuffleIndices) 4033 if (UsedIdxs.insert(Idx).second) 4034 UniqueIdxs.emplace_back(Idx); 4035 V = Builder.CreateShuffleVector(V, UndefValue::get(V->getType()), 4036 UniqueIdxs); 4037 } 4038 } 4039 return V; 4040 } 4041 } 4042 } 4043 4044 Type *ScalarTy = S.OpValue->getType(); 4045 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) 4046 ScalarTy = SI->getValueOperand()->getType(); 4047 4048 // Check that every instruction appears once in this bundle. 4049 SmallVector<int, 4> ReuseShuffleIndicies; 4050 SmallVector<Value *, 4> UniqueValues; 4051 if (VL.size() > 2) { 4052 DenseMap<Value *, unsigned> UniquePositions; 4053 for (Value *V : VL) { 4054 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 4055 ReuseShuffleIndicies.emplace_back(Res.first->second); 4056 if (Res.second || isa<Constant>(V)) 4057 UniqueValues.emplace_back(V); 4058 } 4059 // Do not shuffle single element or if number of unique values is not power 4060 // of 2. 4061 if (UniqueValues.size() == VL.size() || UniqueValues.size() <= 1 || 4062 !llvm::isPowerOf2_32(UniqueValues.size())) 4063 ReuseShuffleIndicies.clear(); 4064 else 4065 VL = UniqueValues; 4066 } 4067 VectorType *VecTy = VectorType::get(ScalarTy, VL.size()); 4068 4069 Value *V = Gather(VL, VecTy); 4070 if (!ReuseShuffleIndicies.empty()) { 4071 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4072 ReuseShuffleIndicies, "shuffle"); 4073 if (auto *I = dyn_cast<Instruction>(V)) { 4074 GatherSeq.insert(I); 4075 CSEBlocks.insert(I->getParent()); 4076 } 4077 } 4078 return V; 4079 } 4080 4081 static void inversePermutation(ArrayRef<unsigned> Indices, 4082 SmallVectorImpl<unsigned> &Mask) { 4083 Mask.clear(); 4084 const unsigned E = Indices.size(); 4085 Mask.resize(E); 4086 for (unsigned I = 0; I < E; ++I) 4087 Mask[Indices[I]] = I; 4088 } 4089 4090 Value *BoUpSLP::vectorizeTree(TreeEntry *E) { 4091 IRBuilder<>::InsertPointGuard Guard(Builder); 4092 4093 if (E->VectorizedValue) { 4094 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *E->Scalars[0] << ".\n"); 4095 return E->VectorizedValue; 4096 } 4097 4098 Instruction *VL0 = E->getMainOp(); 4099 Type *ScalarTy = VL0->getType(); 4100 if (StoreInst *SI = dyn_cast<StoreInst>(VL0)) 4101 ScalarTy = SI->getValueOperand()->getType(); 4102 VectorType *VecTy = VectorType::get(ScalarTy, E->Scalars.size()); 4103 4104 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 4105 4106 if (E->State == TreeEntry::NeedToGather) { 4107 setInsertPointAfterBundle(E); 4108 auto *V = Gather(E->Scalars, VecTy); 4109 if (NeedToShuffleReuses) { 4110 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4111 E->ReuseShuffleIndices, "shuffle"); 4112 if (auto *I = dyn_cast<Instruction>(V)) { 4113 GatherSeq.insert(I); 4114 CSEBlocks.insert(I->getParent()); 4115 } 4116 } 4117 E->VectorizedValue = V; 4118 return V; 4119 } 4120 4121 assert(E->State == TreeEntry::Vectorize && "Unhandled state"); 4122 unsigned ShuffleOrOp = 4123 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 4124 switch (ShuffleOrOp) { 4125 case Instruction::PHI: { 4126 auto *PH = cast<PHINode>(VL0); 4127 Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI()); 4128 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 4129 PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues()); 4130 Value *V = NewPhi; 4131 if (NeedToShuffleReuses) { 4132 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4133 E->ReuseShuffleIndices, "shuffle"); 4134 } 4135 E->VectorizedValue = V; 4136 4137 // PHINodes may have multiple entries from the same block. We want to 4138 // visit every block once. 4139 SmallPtrSet<BasicBlock*, 4> VisitedBBs; 4140 4141 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 4142 ValueList Operands; 4143 BasicBlock *IBB = PH->getIncomingBlock(i); 4144 4145 if (!VisitedBBs.insert(IBB).second) { 4146 NewPhi->addIncoming(NewPhi->getIncomingValueForBlock(IBB), IBB); 4147 continue; 4148 } 4149 4150 Builder.SetInsertPoint(IBB->getTerminator()); 4151 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 4152 Value *Vec = vectorizeTree(E->getOperand(i)); 4153 NewPhi->addIncoming(Vec, IBB); 4154 } 4155 4156 assert(NewPhi->getNumIncomingValues() == PH->getNumIncomingValues() && 4157 "Invalid number of incoming values"); 4158 return V; 4159 } 4160 4161 case Instruction::ExtractElement: { 4162 Value *V = E->getSingleOperand(0); 4163 if (!E->ReorderIndices.empty()) { 4164 OrdersType Mask; 4165 inversePermutation(E->ReorderIndices, Mask); 4166 Builder.SetInsertPoint(VL0); 4167 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), Mask, 4168 "reorder_shuffle"); 4169 } 4170 if (NeedToShuffleReuses) { 4171 // TODO: Merge this shuffle with the ReorderShuffleMask. 4172 if (E->ReorderIndices.empty()) 4173 Builder.SetInsertPoint(VL0); 4174 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4175 E->ReuseShuffleIndices, "shuffle"); 4176 } 4177 E->VectorizedValue = V; 4178 return V; 4179 } 4180 case Instruction::ExtractValue: { 4181 LoadInst *LI = cast<LoadInst>(E->getSingleOperand(0)); 4182 Builder.SetInsertPoint(LI); 4183 PointerType *PtrTy = 4184 PointerType::get(VecTy, LI->getPointerAddressSpace()); 4185 Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy); 4186 LoadInst *V = Builder.CreateAlignedLoad(VecTy, Ptr, LI->getAlign()); 4187 Value *NewV = propagateMetadata(V, E->Scalars); 4188 if (!E->ReorderIndices.empty()) { 4189 OrdersType Mask; 4190 inversePermutation(E->ReorderIndices, Mask); 4191 NewV = Builder.CreateShuffleVector(NewV, UndefValue::get(VecTy), Mask, 4192 "reorder_shuffle"); 4193 } 4194 if (NeedToShuffleReuses) { 4195 // TODO: Merge this shuffle with the ReorderShuffleMask. 4196 NewV = Builder.CreateShuffleVector(NewV, UndefValue::get(VecTy), 4197 E->ReuseShuffleIndices, "shuffle"); 4198 } 4199 E->VectorizedValue = NewV; 4200 return NewV; 4201 } 4202 case Instruction::ZExt: 4203 case Instruction::SExt: 4204 case Instruction::FPToUI: 4205 case Instruction::FPToSI: 4206 case Instruction::FPExt: 4207 case Instruction::PtrToInt: 4208 case Instruction::IntToPtr: 4209 case Instruction::SIToFP: 4210 case Instruction::UIToFP: 4211 case Instruction::Trunc: 4212 case Instruction::FPTrunc: 4213 case Instruction::BitCast: { 4214 setInsertPointAfterBundle(E); 4215 4216 Value *InVec = vectorizeTree(E->getOperand(0)); 4217 4218 if (E->VectorizedValue) { 4219 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4220 return E->VectorizedValue; 4221 } 4222 4223 auto *CI = cast<CastInst>(VL0); 4224 Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy); 4225 if (NeedToShuffleReuses) { 4226 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4227 E->ReuseShuffleIndices, "shuffle"); 4228 } 4229 E->VectorizedValue = V; 4230 ++NumVectorInstructions; 4231 return V; 4232 } 4233 case Instruction::FCmp: 4234 case Instruction::ICmp: { 4235 setInsertPointAfterBundle(E); 4236 4237 Value *L = vectorizeTree(E->getOperand(0)); 4238 Value *R = vectorizeTree(E->getOperand(1)); 4239 4240 if (E->VectorizedValue) { 4241 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4242 return E->VectorizedValue; 4243 } 4244 4245 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 4246 Value *V; 4247 if (E->getOpcode() == Instruction::FCmp) 4248 V = Builder.CreateFCmp(P0, L, R); 4249 else 4250 V = Builder.CreateICmp(P0, L, R); 4251 4252 propagateIRFlags(V, E->Scalars, VL0); 4253 if (NeedToShuffleReuses) { 4254 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4255 E->ReuseShuffleIndices, "shuffle"); 4256 } 4257 E->VectorizedValue = V; 4258 ++NumVectorInstructions; 4259 return V; 4260 } 4261 case Instruction::Select: { 4262 setInsertPointAfterBundle(E); 4263 4264 Value *Cond = vectorizeTree(E->getOperand(0)); 4265 Value *True = vectorizeTree(E->getOperand(1)); 4266 Value *False = vectorizeTree(E->getOperand(2)); 4267 4268 if (E->VectorizedValue) { 4269 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4270 return E->VectorizedValue; 4271 } 4272 4273 Value *V = Builder.CreateSelect(Cond, True, False); 4274 if (NeedToShuffleReuses) { 4275 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4276 E->ReuseShuffleIndices, "shuffle"); 4277 } 4278 E->VectorizedValue = V; 4279 ++NumVectorInstructions; 4280 return V; 4281 } 4282 case Instruction::FNeg: { 4283 setInsertPointAfterBundle(E); 4284 4285 Value *Op = vectorizeTree(E->getOperand(0)); 4286 4287 if (E->VectorizedValue) { 4288 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4289 return E->VectorizedValue; 4290 } 4291 4292 Value *V = Builder.CreateUnOp( 4293 static_cast<Instruction::UnaryOps>(E->getOpcode()), Op); 4294 propagateIRFlags(V, E->Scalars, VL0); 4295 if (auto *I = dyn_cast<Instruction>(V)) 4296 V = propagateMetadata(I, E->Scalars); 4297 4298 if (NeedToShuffleReuses) { 4299 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4300 E->ReuseShuffleIndices, "shuffle"); 4301 } 4302 E->VectorizedValue = V; 4303 ++NumVectorInstructions; 4304 4305 return V; 4306 } 4307 case Instruction::Add: 4308 case Instruction::FAdd: 4309 case Instruction::Sub: 4310 case Instruction::FSub: 4311 case Instruction::Mul: 4312 case Instruction::FMul: 4313 case Instruction::UDiv: 4314 case Instruction::SDiv: 4315 case Instruction::FDiv: 4316 case Instruction::URem: 4317 case Instruction::SRem: 4318 case Instruction::FRem: 4319 case Instruction::Shl: 4320 case Instruction::LShr: 4321 case Instruction::AShr: 4322 case Instruction::And: 4323 case Instruction::Or: 4324 case Instruction::Xor: { 4325 setInsertPointAfterBundle(E); 4326 4327 Value *LHS = vectorizeTree(E->getOperand(0)); 4328 Value *RHS = vectorizeTree(E->getOperand(1)); 4329 4330 if (E->VectorizedValue) { 4331 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4332 return E->VectorizedValue; 4333 } 4334 4335 Value *V = Builder.CreateBinOp( 4336 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, 4337 RHS); 4338 propagateIRFlags(V, E->Scalars, VL0); 4339 if (auto *I = dyn_cast<Instruction>(V)) 4340 V = propagateMetadata(I, E->Scalars); 4341 4342 if (NeedToShuffleReuses) { 4343 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4344 E->ReuseShuffleIndices, "shuffle"); 4345 } 4346 E->VectorizedValue = V; 4347 ++NumVectorInstructions; 4348 4349 return V; 4350 } 4351 case Instruction::Load: { 4352 // Loads are inserted at the head of the tree because we don't want to 4353 // sink them all the way down past store instructions. 4354 bool IsReorder = E->updateStateIfReorder(); 4355 if (IsReorder) 4356 VL0 = E->getMainOp(); 4357 setInsertPointAfterBundle(E); 4358 4359 LoadInst *LI = cast<LoadInst>(VL0); 4360 Type *ScalarLoadTy = LI->getType(); 4361 unsigned AS = LI->getPointerAddressSpace(); 4362 4363 Value *VecPtr = Builder.CreateBitCast(LI->getPointerOperand(), 4364 VecTy->getPointerTo(AS)); 4365 4366 // The pointer operand uses an in-tree scalar so we add the new BitCast to 4367 // ExternalUses list to make sure that an extract will be generated in the 4368 // future. 4369 Value *PO = LI->getPointerOperand(); 4370 if (getTreeEntry(PO)) 4371 ExternalUses.push_back(ExternalUser(PO, cast<User>(VecPtr), 0)); 4372 4373 Align Alignment = DL->getValueOrABITypeAlignment(LI->getAlign(), 4374 ScalarLoadTy); 4375 LI = Builder.CreateAlignedLoad(VecTy, VecPtr, Alignment); 4376 Value *V = propagateMetadata(LI, E->Scalars); 4377 if (IsReorder) { 4378 OrdersType Mask; 4379 inversePermutation(E->ReorderIndices, Mask); 4380 V = Builder.CreateShuffleVector(V, UndefValue::get(V->getType()), 4381 Mask, "reorder_shuffle"); 4382 } 4383 if (NeedToShuffleReuses) { 4384 // TODO: Merge this shuffle with the ReorderShuffleMask. 4385 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4386 E->ReuseShuffleIndices, "shuffle"); 4387 } 4388 E->VectorizedValue = V; 4389 ++NumVectorInstructions; 4390 return V; 4391 } 4392 case Instruction::Store: { 4393 bool IsReorder = !E->ReorderIndices.empty(); 4394 auto *SI = cast<StoreInst>( 4395 IsReorder ? E->Scalars[E->ReorderIndices.front()] : VL0); 4396 unsigned Alignment = SI->getAlignment(); 4397 unsigned AS = SI->getPointerAddressSpace(); 4398 4399 setInsertPointAfterBundle(E); 4400 4401 Value *VecValue = vectorizeTree(E->getOperand(0)); 4402 if (IsReorder) { 4403 OrdersType Mask; 4404 inversePermutation(E->ReorderIndices, Mask); 4405 VecValue = Builder.CreateShuffleVector( 4406 VecValue, UndefValue::get(VecValue->getType()), E->ReorderIndices, 4407 "reorder_shuffle"); 4408 } 4409 Value *ScalarPtr = SI->getPointerOperand(); 4410 Value *VecPtr = Builder.CreateBitCast( 4411 ScalarPtr, VecValue->getType()->getPointerTo(AS)); 4412 StoreInst *ST = Builder.CreateStore(VecValue, VecPtr); 4413 4414 // The pointer operand uses an in-tree scalar, so add the new BitCast to 4415 // ExternalUses to make sure that an extract will be generated in the 4416 // future. 4417 if (getTreeEntry(ScalarPtr)) 4418 ExternalUses.push_back(ExternalUser(ScalarPtr, cast<User>(VecPtr), 0)); 4419 4420 if (!Alignment) 4421 Alignment = DL->getABITypeAlignment(SI->getValueOperand()->getType()); 4422 4423 ST->setAlignment(Align(Alignment)); 4424 Value *V = propagateMetadata(ST, E->Scalars); 4425 if (NeedToShuffleReuses) { 4426 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4427 E->ReuseShuffleIndices, "shuffle"); 4428 } 4429 E->VectorizedValue = V; 4430 ++NumVectorInstructions; 4431 return V; 4432 } 4433 case Instruction::GetElementPtr: { 4434 setInsertPointAfterBundle(E); 4435 4436 Value *Op0 = vectorizeTree(E->getOperand(0)); 4437 4438 std::vector<Value *> OpVecs; 4439 for (int j = 1, e = cast<GetElementPtrInst>(VL0)->getNumOperands(); j < e; 4440 ++j) { 4441 ValueList &VL = E->getOperand(j); 4442 // Need to cast all elements to the same type before vectorization to 4443 // avoid crash. 4444 Type *VL0Ty = VL0->getOperand(j)->getType(); 4445 Type *Ty = llvm::all_of( 4446 VL, [VL0Ty](Value *V) { return VL0Ty == V->getType(); }) 4447 ? VL0Ty 4448 : DL->getIndexType(cast<GetElementPtrInst>(VL0) 4449 ->getPointerOperandType() 4450 ->getScalarType()); 4451 for (Value *&V : VL) { 4452 auto *CI = cast<ConstantInt>(V); 4453 V = ConstantExpr::getIntegerCast(CI, Ty, 4454 CI->getValue().isSignBitSet()); 4455 } 4456 Value *OpVec = vectorizeTree(VL); 4457 OpVecs.push_back(OpVec); 4458 } 4459 4460 Value *V = Builder.CreateGEP( 4461 cast<GetElementPtrInst>(VL0)->getSourceElementType(), Op0, OpVecs); 4462 if (Instruction *I = dyn_cast<Instruction>(V)) 4463 V = propagateMetadata(I, E->Scalars); 4464 4465 if (NeedToShuffleReuses) { 4466 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4467 E->ReuseShuffleIndices, "shuffle"); 4468 } 4469 E->VectorizedValue = V; 4470 ++NumVectorInstructions; 4471 4472 return V; 4473 } 4474 case Instruction::Call: { 4475 CallInst *CI = cast<CallInst>(VL0); 4476 setInsertPointAfterBundle(E); 4477 4478 Intrinsic::ID IID = Intrinsic::not_intrinsic; 4479 if (Function *FI = CI->getCalledFunction()) 4480 IID = FI->getIntrinsicID(); 4481 4482 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 4483 4484 auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); 4485 bool UseIntrinsic = VecCallCosts.first <= VecCallCosts.second; 4486 4487 Value *ScalarArg = nullptr; 4488 std::vector<Value *> OpVecs; 4489 for (int j = 0, e = CI->getNumArgOperands(); j < e; ++j) { 4490 ValueList OpVL; 4491 // Some intrinsics have scalar arguments. This argument should not be 4492 // vectorized. 4493 if (UseIntrinsic && hasVectorInstrinsicScalarOpd(IID, j)) { 4494 CallInst *CEI = cast<CallInst>(VL0); 4495 ScalarArg = CEI->getArgOperand(j); 4496 OpVecs.push_back(CEI->getArgOperand(j)); 4497 continue; 4498 } 4499 4500 Value *OpVec = vectorizeTree(E->getOperand(j)); 4501 LLVM_DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n"); 4502 OpVecs.push_back(OpVec); 4503 } 4504 4505 Module *M = F->getParent(); 4506 Type *Tys[] = { VectorType::get(CI->getType(), E->Scalars.size()) }; 4507 Function *CF = Intrinsic::getDeclaration(M, ID, Tys); 4508 4509 if (!UseIntrinsic) { 4510 VFShape Shape = VFShape::get( 4511 *CI, {static_cast<unsigned>(VecTy->getNumElements()), false}, 4512 false /*HasGlobalPred*/); 4513 CF = VFDatabase(*CI).getVectorizedFunction(Shape); 4514 } 4515 4516 SmallVector<OperandBundleDef, 1> OpBundles; 4517 CI->getOperandBundlesAsDefs(OpBundles); 4518 Value *V = Builder.CreateCall(CF, OpVecs, OpBundles); 4519 4520 // The scalar argument uses an in-tree scalar so we add the new vectorized 4521 // call to ExternalUses list to make sure that an extract will be 4522 // generated in the future. 4523 if (ScalarArg && getTreeEntry(ScalarArg)) 4524 ExternalUses.push_back(ExternalUser(ScalarArg, cast<User>(V), 0)); 4525 4526 propagateIRFlags(V, E->Scalars, VL0); 4527 if (NeedToShuffleReuses) { 4528 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4529 E->ReuseShuffleIndices, "shuffle"); 4530 } 4531 E->VectorizedValue = V; 4532 ++NumVectorInstructions; 4533 return V; 4534 } 4535 case Instruction::ShuffleVector: { 4536 assert(E->isAltShuffle() && 4537 ((Instruction::isBinaryOp(E->getOpcode()) && 4538 Instruction::isBinaryOp(E->getAltOpcode())) || 4539 (Instruction::isCast(E->getOpcode()) && 4540 Instruction::isCast(E->getAltOpcode()))) && 4541 "Invalid Shuffle Vector Operand"); 4542 4543 Value *LHS = nullptr, *RHS = nullptr; 4544 if (Instruction::isBinaryOp(E->getOpcode())) { 4545 setInsertPointAfterBundle(E); 4546 LHS = vectorizeTree(E->getOperand(0)); 4547 RHS = vectorizeTree(E->getOperand(1)); 4548 } else { 4549 setInsertPointAfterBundle(E); 4550 LHS = vectorizeTree(E->getOperand(0)); 4551 } 4552 4553 if (E->VectorizedValue) { 4554 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4555 return E->VectorizedValue; 4556 } 4557 4558 Value *V0, *V1; 4559 if (Instruction::isBinaryOp(E->getOpcode())) { 4560 V0 = Builder.CreateBinOp( 4561 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, RHS); 4562 V1 = Builder.CreateBinOp( 4563 static_cast<Instruction::BinaryOps>(E->getAltOpcode()), LHS, RHS); 4564 } else { 4565 V0 = Builder.CreateCast( 4566 static_cast<Instruction::CastOps>(E->getOpcode()), LHS, VecTy); 4567 V1 = Builder.CreateCast( 4568 static_cast<Instruction::CastOps>(E->getAltOpcode()), LHS, VecTy); 4569 } 4570 4571 // Create shuffle to take alternate operations from the vector. 4572 // Also, gather up main and alt scalar ops to propagate IR flags to 4573 // each vector operation. 4574 ValueList OpScalars, AltScalars; 4575 unsigned e = E->Scalars.size(); 4576 SmallVector<int, 8> Mask(e); 4577 for (unsigned i = 0; i < e; ++i) { 4578 auto *OpInst = cast<Instruction>(E->Scalars[i]); 4579 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 4580 if (OpInst->getOpcode() == E->getAltOpcode()) { 4581 Mask[i] = e + i; 4582 AltScalars.push_back(E->Scalars[i]); 4583 } else { 4584 Mask[i] = i; 4585 OpScalars.push_back(E->Scalars[i]); 4586 } 4587 } 4588 4589 propagateIRFlags(V0, OpScalars); 4590 propagateIRFlags(V1, AltScalars); 4591 4592 Value *V = Builder.CreateShuffleVector(V0, V1, Mask); 4593 if (Instruction *I = dyn_cast<Instruction>(V)) 4594 V = propagateMetadata(I, E->Scalars); 4595 if (NeedToShuffleReuses) { 4596 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4597 E->ReuseShuffleIndices, "shuffle"); 4598 } 4599 E->VectorizedValue = V; 4600 ++NumVectorInstructions; 4601 4602 return V; 4603 } 4604 default: 4605 llvm_unreachable("unknown inst"); 4606 } 4607 return nullptr; 4608 } 4609 4610 Value *BoUpSLP::vectorizeTree() { 4611 ExtraValueToDebugLocsMap ExternallyUsedValues; 4612 return vectorizeTree(ExternallyUsedValues); 4613 } 4614 4615 Value * 4616 BoUpSLP::vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues) { 4617 // All blocks must be scheduled before any instructions are inserted. 4618 for (auto &BSIter : BlocksSchedules) { 4619 scheduleBlock(BSIter.second.get()); 4620 } 4621 4622 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4623 auto *VectorRoot = vectorizeTree(VectorizableTree[0].get()); 4624 4625 // If the vectorized tree can be rewritten in a smaller type, we truncate the 4626 // vectorized root. InstCombine will then rewrite the entire expression. We 4627 // sign extend the extracted values below. 4628 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 4629 if (MinBWs.count(ScalarRoot)) { 4630 if (auto *I = dyn_cast<Instruction>(VectorRoot)) 4631 Builder.SetInsertPoint(&*++BasicBlock::iterator(I)); 4632 auto BundleWidth = VectorizableTree[0]->Scalars.size(); 4633 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 4634 auto *VecTy = VectorType::get(MinTy, BundleWidth); 4635 auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy); 4636 VectorizableTree[0]->VectorizedValue = Trunc; 4637 } 4638 4639 LLVM_DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size() 4640 << " values .\n"); 4641 4642 // If necessary, sign-extend or zero-extend ScalarRoot to the larger type 4643 // specified by ScalarType. 4644 auto extend = [&](Value *ScalarRoot, Value *Ex, Type *ScalarType) { 4645 if (!MinBWs.count(ScalarRoot)) 4646 return Ex; 4647 if (MinBWs[ScalarRoot].second) 4648 return Builder.CreateSExt(Ex, ScalarType); 4649 return Builder.CreateZExt(Ex, ScalarType); 4650 }; 4651 4652 // Extract all of the elements with the external uses. 4653 for (const auto &ExternalUse : ExternalUses) { 4654 Value *Scalar = ExternalUse.Scalar; 4655 llvm::User *User = ExternalUse.User; 4656 4657 // Skip users that we already RAUW. This happens when one instruction 4658 // has multiple uses of the same value. 4659 if (User && !is_contained(Scalar->users(), User)) 4660 continue; 4661 TreeEntry *E = getTreeEntry(Scalar); 4662 assert(E && "Invalid scalar"); 4663 assert(E->State == TreeEntry::Vectorize && "Extracting from a gather list"); 4664 4665 Value *Vec = E->VectorizedValue; 4666 assert(Vec && "Can't find vectorizable value"); 4667 4668 Value *Lane = Builder.getInt32(ExternalUse.Lane); 4669 // If User == nullptr, the Scalar is used as extra arg. Generate 4670 // ExtractElement instruction and update the record for this scalar in 4671 // ExternallyUsedValues. 4672 if (!User) { 4673 assert(ExternallyUsedValues.count(Scalar) && 4674 "Scalar with nullptr as an external user must be registered in " 4675 "ExternallyUsedValues map"); 4676 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 4677 Builder.SetInsertPoint(VecI->getParent(), 4678 std::next(VecI->getIterator())); 4679 } else { 4680 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4681 } 4682 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4683 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4684 CSEBlocks.insert(cast<Instruction>(Scalar)->getParent()); 4685 auto &Locs = ExternallyUsedValues[Scalar]; 4686 ExternallyUsedValues.insert({Ex, Locs}); 4687 ExternallyUsedValues.erase(Scalar); 4688 // Required to update internally referenced instructions. 4689 Scalar->replaceAllUsesWith(Ex); 4690 continue; 4691 } 4692 4693 // Generate extracts for out-of-tree users. 4694 // Find the insertion point for the extractelement lane. 4695 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 4696 if (PHINode *PH = dyn_cast<PHINode>(User)) { 4697 for (int i = 0, e = PH->getNumIncomingValues(); i != e; ++i) { 4698 if (PH->getIncomingValue(i) == Scalar) { 4699 Instruction *IncomingTerminator = 4700 PH->getIncomingBlock(i)->getTerminator(); 4701 if (isa<CatchSwitchInst>(IncomingTerminator)) { 4702 Builder.SetInsertPoint(VecI->getParent(), 4703 std::next(VecI->getIterator())); 4704 } else { 4705 Builder.SetInsertPoint(PH->getIncomingBlock(i)->getTerminator()); 4706 } 4707 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4708 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4709 CSEBlocks.insert(PH->getIncomingBlock(i)); 4710 PH->setOperand(i, Ex); 4711 } 4712 } 4713 } else { 4714 Builder.SetInsertPoint(cast<Instruction>(User)); 4715 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4716 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4717 CSEBlocks.insert(cast<Instruction>(User)->getParent()); 4718 User->replaceUsesOfWith(Scalar, Ex); 4719 } 4720 } else { 4721 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4722 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4723 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4724 CSEBlocks.insert(&F->getEntryBlock()); 4725 User->replaceUsesOfWith(Scalar, Ex); 4726 } 4727 4728 LLVM_DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n"); 4729 } 4730 4731 // For each vectorized value: 4732 for (auto &TEPtr : VectorizableTree) { 4733 TreeEntry *Entry = TEPtr.get(); 4734 4735 // No need to handle users of gathered values. 4736 if (Entry->State == TreeEntry::NeedToGather) 4737 continue; 4738 4739 assert(Entry->VectorizedValue && "Can't find vectorizable value"); 4740 4741 // For each lane: 4742 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 4743 Value *Scalar = Entry->Scalars[Lane]; 4744 4745 #ifndef NDEBUG 4746 Type *Ty = Scalar->getType(); 4747 if (!Ty->isVoidTy()) { 4748 for (User *U : Scalar->users()) { 4749 LLVM_DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n"); 4750 4751 // It is legal to delete users in the ignorelist. 4752 assert((getTreeEntry(U) || is_contained(UserIgnoreList, U)) && 4753 "Deleting out-of-tree value"); 4754 } 4755 } 4756 #endif 4757 LLVM_DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n"); 4758 eraseInstruction(cast<Instruction>(Scalar)); 4759 } 4760 } 4761 4762 Builder.ClearInsertionPoint(); 4763 4764 return VectorizableTree[0]->VectorizedValue; 4765 } 4766 4767 void BoUpSLP::optimizeGatherSequence() { 4768 LLVM_DEBUG(dbgs() << "SLP: Optimizing " << GatherSeq.size() 4769 << " gather sequences instructions.\n"); 4770 // LICM InsertElementInst sequences. 4771 for (Instruction *I : GatherSeq) { 4772 if (isDeleted(I)) 4773 continue; 4774 4775 // Check if this block is inside a loop. 4776 Loop *L = LI->getLoopFor(I->getParent()); 4777 if (!L) 4778 continue; 4779 4780 // Check if it has a preheader. 4781 BasicBlock *PreHeader = L->getLoopPreheader(); 4782 if (!PreHeader) 4783 continue; 4784 4785 // If the vector or the element that we insert into it are 4786 // instructions that are defined in this basic block then we can't 4787 // hoist this instruction. 4788 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 4789 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 4790 if (Op0 && L->contains(Op0)) 4791 continue; 4792 if (Op1 && L->contains(Op1)) 4793 continue; 4794 4795 // We can hoist this instruction. Move it to the pre-header. 4796 I->moveBefore(PreHeader->getTerminator()); 4797 } 4798 4799 // Make a list of all reachable blocks in our CSE queue. 4800 SmallVector<const DomTreeNode *, 8> CSEWorkList; 4801 CSEWorkList.reserve(CSEBlocks.size()); 4802 for (BasicBlock *BB : CSEBlocks) 4803 if (DomTreeNode *N = DT->getNode(BB)) { 4804 assert(DT->isReachableFromEntry(N)); 4805 CSEWorkList.push_back(N); 4806 } 4807 4808 // Sort blocks by domination. This ensures we visit a block after all blocks 4809 // dominating it are visited. 4810 llvm::stable_sort(CSEWorkList, 4811 [this](const DomTreeNode *A, const DomTreeNode *B) { 4812 return DT->properlyDominates(A, B); 4813 }); 4814 4815 // Perform O(N^2) search over the gather sequences and merge identical 4816 // instructions. TODO: We can further optimize this scan if we split the 4817 // instructions into different buckets based on the insert lane. 4818 SmallVector<Instruction *, 16> Visited; 4819 for (auto I = CSEWorkList.begin(), E = CSEWorkList.end(); I != E; ++I) { 4820 assert((I == CSEWorkList.begin() || !DT->dominates(*I, *std::prev(I))) && 4821 "Worklist not sorted properly!"); 4822 BasicBlock *BB = (*I)->getBlock(); 4823 // For all instructions in blocks containing gather sequences: 4824 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e;) { 4825 Instruction *In = &*it++; 4826 if (isDeleted(In)) 4827 continue; 4828 if (!isa<InsertElementInst>(In) && !isa<ExtractElementInst>(In)) 4829 continue; 4830 4831 // Check if we can replace this instruction with any of the 4832 // visited instructions. 4833 for (Instruction *v : Visited) { 4834 if (In->isIdenticalTo(v) && 4835 DT->dominates(v->getParent(), In->getParent())) { 4836 In->replaceAllUsesWith(v); 4837 eraseInstruction(In); 4838 In = nullptr; 4839 break; 4840 } 4841 } 4842 if (In) { 4843 assert(!is_contained(Visited, In)); 4844 Visited.push_back(In); 4845 } 4846 } 4847 } 4848 CSEBlocks.clear(); 4849 GatherSeq.clear(); 4850 } 4851 4852 // Groups the instructions to a bundle (which is then a single scheduling entity) 4853 // and schedules instructions until the bundle gets ready. 4854 Optional<BoUpSLP::ScheduleData *> 4855 BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 4856 const InstructionsState &S) { 4857 if (isa<PHINode>(S.OpValue)) 4858 return nullptr; 4859 4860 // Initialize the instruction bundle. 4861 Instruction *OldScheduleEnd = ScheduleEnd; 4862 ScheduleData *PrevInBundle = nullptr; 4863 ScheduleData *Bundle = nullptr; 4864 bool ReSchedule = false; 4865 LLVM_DEBUG(dbgs() << "SLP: bundle: " << *S.OpValue << "\n"); 4866 4867 // Make sure that the scheduling region contains all 4868 // instructions of the bundle. 4869 for (Value *V : VL) { 4870 if (!extendSchedulingRegion(V, S)) 4871 return None; 4872 } 4873 4874 for (Value *V : VL) { 4875 ScheduleData *BundleMember = getScheduleData(V); 4876 assert(BundleMember && 4877 "no ScheduleData for bundle member (maybe not in same basic block)"); 4878 if (BundleMember->IsScheduled) { 4879 // A bundle member was scheduled as single instruction before and now 4880 // needs to be scheduled as part of the bundle. We just get rid of the 4881 // existing schedule. 4882 LLVM_DEBUG(dbgs() << "SLP: reset schedule because " << *BundleMember 4883 << " was already scheduled\n"); 4884 ReSchedule = true; 4885 } 4886 assert(BundleMember->isSchedulingEntity() && 4887 "bundle member already part of other bundle"); 4888 if (PrevInBundle) { 4889 PrevInBundle->NextInBundle = BundleMember; 4890 } else { 4891 Bundle = BundleMember; 4892 } 4893 BundleMember->UnscheduledDepsInBundle = 0; 4894 Bundle->UnscheduledDepsInBundle += BundleMember->UnscheduledDeps; 4895 4896 // Group the instructions to a bundle. 4897 BundleMember->FirstInBundle = Bundle; 4898 PrevInBundle = BundleMember; 4899 } 4900 if (ScheduleEnd != OldScheduleEnd) { 4901 // The scheduling region got new instructions at the lower end (or it is a 4902 // new region for the first bundle). This makes it necessary to 4903 // recalculate all dependencies. 4904 // It is seldom that this needs to be done a second time after adding the 4905 // initial bundle to the region. 4906 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 4907 doForAllOpcodes(I, [](ScheduleData *SD) { 4908 SD->clearDependencies(); 4909 }); 4910 } 4911 ReSchedule = true; 4912 } 4913 if (ReSchedule) { 4914 resetSchedule(); 4915 initialFillReadyList(ReadyInsts); 4916 } 4917 assert(Bundle && "Failed to find schedule bundle"); 4918 4919 LLVM_DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle << " in block " 4920 << BB->getName() << "\n"); 4921 4922 calculateDependencies(Bundle, true, SLP); 4923 4924 // Now try to schedule the new bundle. As soon as the bundle is "ready" it 4925 // means that there are no cyclic dependencies and we can schedule it. 4926 // Note that's important that we don't "schedule" the bundle yet (see 4927 // cancelScheduling). 4928 while (!Bundle->isReady() && !ReadyInsts.empty()) { 4929 4930 ScheduleData *pickedSD = ReadyInsts.back(); 4931 ReadyInsts.pop_back(); 4932 4933 if (pickedSD->isSchedulingEntity() && pickedSD->isReady()) { 4934 schedule(pickedSD, ReadyInsts); 4935 } 4936 } 4937 if (!Bundle->isReady()) { 4938 cancelScheduling(VL, S.OpValue); 4939 return None; 4940 } 4941 return Bundle; 4942 } 4943 4944 void BoUpSLP::BlockScheduling::cancelScheduling(ArrayRef<Value *> VL, 4945 Value *OpValue) { 4946 if (isa<PHINode>(OpValue)) 4947 return; 4948 4949 ScheduleData *Bundle = getScheduleData(OpValue); 4950 LLVM_DEBUG(dbgs() << "SLP: cancel scheduling of " << *Bundle << "\n"); 4951 assert(!Bundle->IsScheduled && 4952 "Can't cancel bundle which is already scheduled"); 4953 assert(Bundle->isSchedulingEntity() && Bundle->isPartOfBundle() && 4954 "tried to unbundle something which is not a bundle"); 4955 4956 // Un-bundle: make single instructions out of the bundle. 4957 ScheduleData *BundleMember = Bundle; 4958 while (BundleMember) { 4959 assert(BundleMember->FirstInBundle == Bundle && "corrupt bundle links"); 4960 BundleMember->FirstInBundle = BundleMember; 4961 ScheduleData *Next = BundleMember->NextInBundle; 4962 BundleMember->NextInBundle = nullptr; 4963 BundleMember->UnscheduledDepsInBundle = BundleMember->UnscheduledDeps; 4964 if (BundleMember->UnscheduledDepsInBundle == 0) { 4965 ReadyInsts.insert(BundleMember); 4966 } 4967 BundleMember = Next; 4968 } 4969 } 4970 4971 BoUpSLP::ScheduleData *BoUpSLP::BlockScheduling::allocateScheduleDataChunks() { 4972 // Allocate a new ScheduleData for the instruction. 4973 if (ChunkPos >= ChunkSize) { 4974 ScheduleDataChunks.push_back(std::make_unique<ScheduleData[]>(ChunkSize)); 4975 ChunkPos = 0; 4976 } 4977 return &(ScheduleDataChunks.back()[ChunkPos++]); 4978 } 4979 4980 bool BoUpSLP::BlockScheduling::extendSchedulingRegion(Value *V, 4981 const InstructionsState &S) { 4982 if (getScheduleData(V, isOneOf(S, V))) 4983 return true; 4984 Instruction *I = dyn_cast<Instruction>(V); 4985 assert(I && "bundle member must be an instruction"); 4986 assert(!isa<PHINode>(I) && "phi nodes don't need to be scheduled"); 4987 auto &&CheckSheduleForI = [this, &S](Instruction *I) -> bool { 4988 ScheduleData *ISD = getScheduleData(I); 4989 if (!ISD) 4990 return false; 4991 assert(isInSchedulingRegion(ISD) && 4992 "ScheduleData not in scheduling region"); 4993 ScheduleData *SD = allocateScheduleDataChunks(); 4994 SD->Inst = I; 4995 SD->init(SchedulingRegionID, S.OpValue); 4996 ExtraScheduleDataMap[I][S.OpValue] = SD; 4997 return true; 4998 }; 4999 if (CheckSheduleForI(I)) 5000 return true; 5001 if (!ScheduleStart) { 5002 // It's the first instruction in the new region. 5003 initScheduleData(I, I->getNextNode(), nullptr, nullptr); 5004 ScheduleStart = I; 5005 ScheduleEnd = I->getNextNode(); 5006 if (isOneOf(S, I) != I) 5007 CheckSheduleForI(I); 5008 assert(ScheduleEnd && "tried to vectorize a terminator?"); 5009 LLVM_DEBUG(dbgs() << "SLP: initialize schedule region to " << *I << "\n"); 5010 return true; 5011 } 5012 // Search up and down at the same time, because we don't know if the new 5013 // instruction is above or below the existing scheduling region. 5014 BasicBlock::reverse_iterator UpIter = 5015 ++ScheduleStart->getIterator().getReverse(); 5016 BasicBlock::reverse_iterator UpperEnd = BB->rend(); 5017 BasicBlock::iterator DownIter = ScheduleEnd->getIterator(); 5018 BasicBlock::iterator LowerEnd = BB->end(); 5019 while (true) { 5020 if (++ScheduleRegionSize > ScheduleRegionSizeLimit) { 5021 LLVM_DEBUG(dbgs() << "SLP: exceeded schedule region size limit\n"); 5022 return false; 5023 } 5024 5025 if (UpIter != UpperEnd) { 5026 if (&*UpIter == I) { 5027 initScheduleData(I, ScheduleStart, nullptr, FirstLoadStoreInRegion); 5028 ScheduleStart = I; 5029 if (isOneOf(S, I) != I) 5030 CheckSheduleForI(I); 5031 LLVM_DEBUG(dbgs() << "SLP: extend schedule region start to " << *I 5032 << "\n"); 5033 return true; 5034 } 5035 ++UpIter; 5036 } 5037 if (DownIter != LowerEnd) { 5038 if (&*DownIter == I) { 5039 initScheduleData(ScheduleEnd, I->getNextNode(), LastLoadStoreInRegion, 5040 nullptr); 5041 ScheduleEnd = I->getNextNode(); 5042 if (isOneOf(S, I) != I) 5043 CheckSheduleForI(I); 5044 assert(ScheduleEnd && "tried to vectorize a terminator?"); 5045 LLVM_DEBUG(dbgs() << "SLP: extend schedule region end to " << *I 5046 << "\n"); 5047 return true; 5048 } 5049 ++DownIter; 5050 } 5051 assert((UpIter != UpperEnd || DownIter != LowerEnd) && 5052 "instruction not found in block"); 5053 } 5054 return true; 5055 } 5056 5057 void BoUpSLP::BlockScheduling::initScheduleData(Instruction *FromI, 5058 Instruction *ToI, 5059 ScheduleData *PrevLoadStore, 5060 ScheduleData *NextLoadStore) { 5061 ScheduleData *CurrentLoadStore = PrevLoadStore; 5062 for (Instruction *I = FromI; I != ToI; I = I->getNextNode()) { 5063 ScheduleData *SD = ScheduleDataMap[I]; 5064 if (!SD) { 5065 SD = allocateScheduleDataChunks(); 5066 ScheduleDataMap[I] = SD; 5067 SD->Inst = I; 5068 } 5069 assert(!isInSchedulingRegion(SD) && 5070 "new ScheduleData already in scheduling region"); 5071 SD->init(SchedulingRegionID, I); 5072 5073 if (I->mayReadOrWriteMemory() && 5074 (!isa<IntrinsicInst>(I) || 5075 cast<IntrinsicInst>(I)->getIntrinsicID() != Intrinsic::sideeffect)) { 5076 // Update the linked list of memory accessing instructions. 5077 if (CurrentLoadStore) { 5078 CurrentLoadStore->NextLoadStore = SD; 5079 } else { 5080 FirstLoadStoreInRegion = SD; 5081 } 5082 CurrentLoadStore = SD; 5083 } 5084 } 5085 if (NextLoadStore) { 5086 if (CurrentLoadStore) 5087 CurrentLoadStore->NextLoadStore = NextLoadStore; 5088 } else { 5089 LastLoadStoreInRegion = CurrentLoadStore; 5090 } 5091 } 5092 5093 void BoUpSLP::BlockScheduling::calculateDependencies(ScheduleData *SD, 5094 bool InsertInReadyList, 5095 BoUpSLP *SLP) { 5096 assert(SD->isSchedulingEntity()); 5097 5098 SmallVector<ScheduleData *, 10> WorkList; 5099 WorkList.push_back(SD); 5100 5101 while (!WorkList.empty()) { 5102 ScheduleData *SD = WorkList.back(); 5103 WorkList.pop_back(); 5104 5105 ScheduleData *BundleMember = SD; 5106 while (BundleMember) { 5107 assert(isInSchedulingRegion(BundleMember)); 5108 if (!BundleMember->hasValidDependencies()) { 5109 5110 LLVM_DEBUG(dbgs() << "SLP: update deps of " << *BundleMember 5111 << "\n"); 5112 BundleMember->Dependencies = 0; 5113 BundleMember->resetUnscheduledDeps(); 5114 5115 // Handle def-use chain dependencies. 5116 if (BundleMember->OpValue != BundleMember->Inst) { 5117 ScheduleData *UseSD = getScheduleData(BundleMember->Inst); 5118 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 5119 BundleMember->Dependencies++; 5120 ScheduleData *DestBundle = UseSD->FirstInBundle; 5121 if (!DestBundle->IsScheduled) 5122 BundleMember->incrementUnscheduledDeps(1); 5123 if (!DestBundle->hasValidDependencies()) 5124 WorkList.push_back(DestBundle); 5125 } 5126 } else { 5127 for (User *U : BundleMember->Inst->users()) { 5128 if (isa<Instruction>(U)) { 5129 ScheduleData *UseSD = getScheduleData(U); 5130 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 5131 BundleMember->Dependencies++; 5132 ScheduleData *DestBundle = UseSD->FirstInBundle; 5133 if (!DestBundle->IsScheduled) 5134 BundleMember->incrementUnscheduledDeps(1); 5135 if (!DestBundle->hasValidDependencies()) 5136 WorkList.push_back(DestBundle); 5137 } 5138 } else { 5139 // I'm not sure if this can ever happen. But we need to be safe. 5140 // This lets the instruction/bundle never be scheduled and 5141 // eventually disable vectorization. 5142 BundleMember->Dependencies++; 5143 BundleMember->incrementUnscheduledDeps(1); 5144 } 5145 } 5146 } 5147 5148 // Handle the memory dependencies. 5149 ScheduleData *DepDest = BundleMember->NextLoadStore; 5150 if (DepDest) { 5151 Instruction *SrcInst = BundleMember->Inst; 5152 MemoryLocation SrcLoc = getLocation(SrcInst, SLP->AA); 5153 bool SrcMayWrite = BundleMember->Inst->mayWriteToMemory(); 5154 unsigned numAliased = 0; 5155 unsigned DistToSrc = 1; 5156 5157 while (DepDest) { 5158 assert(isInSchedulingRegion(DepDest)); 5159 5160 // We have two limits to reduce the complexity: 5161 // 1) AliasedCheckLimit: It's a small limit to reduce calls to 5162 // SLP->isAliased (which is the expensive part in this loop). 5163 // 2) MaxMemDepDistance: It's for very large blocks and it aborts 5164 // the whole loop (even if the loop is fast, it's quadratic). 5165 // It's important for the loop break condition (see below) to 5166 // check this limit even between two read-only instructions. 5167 if (DistToSrc >= MaxMemDepDistance || 5168 ((SrcMayWrite || DepDest->Inst->mayWriteToMemory()) && 5169 (numAliased >= AliasedCheckLimit || 5170 SLP->isAliased(SrcLoc, SrcInst, DepDest->Inst)))) { 5171 5172 // We increment the counter only if the locations are aliased 5173 // (instead of counting all alias checks). This gives a better 5174 // balance between reduced runtime and accurate dependencies. 5175 numAliased++; 5176 5177 DepDest->MemoryDependencies.push_back(BundleMember); 5178 BundleMember->Dependencies++; 5179 ScheduleData *DestBundle = DepDest->FirstInBundle; 5180 if (!DestBundle->IsScheduled) { 5181 BundleMember->incrementUnscheduledDeps(1); 5182 } 5183 if (!DestBundle->hasValidDependencies()) { 5184 WorkList.push_back(DestBundle); 5185 } 5186 } 5187 DepDest = DepDest->NextLoadStore; 5188 5189 // Example, explaining the loop break condition: Let's assume our 5190 // starting instruction is i0 and MaxMemDepDistance = 3. 5191 // 5192 // +--------v--v--v 5193 // i0,i1,i2,i3,i4,i5,i6,i7,i8 5194 // +--------^--^--^ 5195 // 5196 // MaxMemDepDistance let us stop alias-checking at i3 and we add 5197 // dependencies from i0 to i3,i4,.. (even if they are not aliased). 5198 // Previously we already added dependencies from i3 to i6,i7,i8 5199 // (because of MaxMemDepDistance). As we added a dependency from 5200 // i0 to i3, we have transitive dependencies from i0 to i6,i7,i8 5201 // and we can abort this loop at i6. 5202 if (DistToSrc >= 2 * MaxMemDepDistance) 5203 break; 5204 DistToSrc++; 5205 } 5206 } 5207 } 5208 BundleMember = BundleMember->NextInBundle; 5209 } 5210 if (InsertInReadyList && SD->isReady()) { 5211 ReadyInsts.push_back(SD); 5212 LLVM_DEBUG(dbgs() << "SLP: gets ready on update: " << *SD->Inst 5213 << "\n"); 5214 } 5215 } 5216 } 5217 5218 void BoUpSLP::BlockScheduling::resetSchedule() { 5219 assert(ScheduleStart && 5220 "tried to reset schedule on block which has not been scheduled"); 5221 for (Instruction *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 5222 doForAllOpcodes(I, [&](ScheduleData *SD) { 5223 assert(isInSchedulingRegion(SD) && 5224 "ScheduleData not in scheduling region"); 5225 SD->IsScheduled = false; 5226 SD->resetUnscheduledDeps(); 5227 }); 5228 } 5229 ReadyInsts.clear(); 5230 } 5231 5232 void BoUpSLP::scheduleBlock(BlockScheduling *BS) { 5233 if (!BS->ScheduleStart) 5234 return; 5235 5236 LLVM_DEBUG(dbgs() << "SLP: schedule block " << BS->BB->getName() << "\n"); 5237 5238 BS->resetSchedule(); 5239 5240 // For the real scheduling we use a more sophisticated ready-list: it is 5241 // sorted by the original instruction location. This lets the final schedule 5242 // be as close as possible to the original instruction order. 5243 struct ScheduleDataCompare { 5244 bool operator()(ScheduleData *SD1, ScheduleData *SD2) const { 5245 return SD2->SchedulingPriority < SD1->SchedulingPriority; 5246 } 5247 }; 5248 std::set<ScheduleData *, ScheduleDataCompare> ReadyInsts; 5249 5250 // Ensure that all dependency data is updated and fill the ready-list with 5251 // initial instructions. 5252 int Idx = 0; 5253 int NumToSchedule = 0; 5254 for (auto *I = BS->ScheduleStart; I != BS->ScheduleEnd; 5255 I = I->getNextNode()) { 5256 BS->doForAllOpcodes(I, [this, &Idx, &NumToSchedule, BS](ScheduleData *SD) { 5257 assert(SD->isPartOfBundle() == 5258 (getTreeEntry(SD->Inst) != nullptr) && 5259 "scheduler and vectorizer bundle mismatch"); 5260 SD->FirstInBundle->SchedulingPriority = Idx++; 5261 if (SD->isSchedulingEntity()) { 5262 BS->calculateDependencies(SD, false, this); 5263 NumToSchedule++; 5264 } 5265 }); 5266 } 5267 BS->initialFillReadyList(ReadyInsts); 5268 5269 Instruction *LastScheduledInst = BS->ScheduleEnd; 5270 5271 // Do the "real" scheduling. 5272 while (!ReadyInsts.empty()) { 5273 ScheduleData *picked = *ReadyInsts.begin(); 5274 ReadyInsts.erase(ReadyInsts.begin()); 5275 5276 // Move the scheduled instruction(s) to their dedicated places, if not 5277 // there yet. 5278 ScheduleData *BundleMember = picked; 5279 while (BundleMember) { 5280 Instruction *pickedInst = BundleMember->Inst; 5281 if (LastScheduledInst->getNextNode() != pickedInst) { 5282 BS->BB->getInstList().remove(pickedInst); 5283 BS->BB->getInstList().insert(LastScheduledInst->getIterator(), 5284 pickedInst); 5285 } 5286 LastScheduledInst = pickedInst; 5287 BundleMember = BundleMember->NextInBundle; 5288 } 5289 5290 BS->schedule(picked, ReadyInsts); 5291 NumToSchedule--; 5292 } 5293 assert(NumToSchedule == 0 && "could not schedule all instructions"); 5294 5295 // Avoid duplicate scheduling of the block. 5296 BS->ScheduleStart = nullptr; 5297 } 5298 5299 unsigned BoUpSLP::getVectorElementSize(Value *V) const { 5300 // If V is a store, just return the width of the stored value without 5301 // traversing the expression tree. This is the common case. 5302 if (auto *Store = dyn_cast<StoreInst>(V)) 5303 return DL->getTypeSizeInBits(Store->getValueOperand()->getType()); 5304 5305 // If V is not a store, we can traverse the expression tree to find loads 5306 // that feed it. The type of the loaded value may indicate a more suitable 5307 // width than V's type. We want to base the vector element size on the width 5308 // of memory operations where possible. 5309 SmallVector<Instruction *, 16> Worklist; 5310 SmallPtrSet<Instruction *, 16> Visited; 5311 if (auto *I = dyn_cast<Instruction>(V)) { 5312 Worklist.push_back(I); 5313 Visited.insert(I); 5314 } 5315 5316 // Traverse the expression tree in bottom-up order looking for loads. If we 5317 // encounter an instruction we don't yet handle, we give up. 5318 auto MaxWidth = 0u; 5319 auto FoundUnknownInst = false; 5320 while (!Worklist.empty() && !FoundUnknownInst) { 5321 auto *I = Worklist.pop_back_val(); 5322 5323 // We should only be looking at scalar instructions here. If the current 5324 // instruction has a vector type, give up. 5325 auto *Ty = I->getType(); 5326 if (isa<VectorType>(Ty)) 5327 FoundUnknownInst = true; 5328 5329 // If the current instruction is a load, update MaxWidth to reflect the 5330 // width of the loaded value. 5331 else if (isa<LoadInst>(I)) 5332 MaxWidth = std::max<unsigned>(MaxWidth, DL->getTypeSizeInBits(Ty)); 5333 5334 // Otherwise, we need to visit the operands of the instruction. We only 5335 // handle the interesting cases from buildTree here. If an operand is an 5336 // instruction we haven't yet visited, we add it to the worklist. 5337 else if (isa<PHINode>(I) || isa<CastInst>(I) || isa<GetElementPtrInst>(I) || 5338 isa<CmpInst>(I) || isa<SelectInst>(I) || isa<BinaryOperator>(I)) { 5339 for (Use &U : I->operands()) 5340 if (auto *J = dyn_cast<Instruction>(U.get())) 5341 if (Visited.insert(J).second) 5342 Worklist.push_back(J); 5343 } 5344 5345 // If we don't yet handle the instruction, give up. 5346 else 5347 FoundUnknownInst = true; 5348 } 5349 5350 // If we didn't encounter a memory access in the expression tree, or if we 5351 // gave up for some reason, just return the width of V. 5352 if (!MaxWidth || FoundUnknownInst) 5353 return DL->getTypeSizeInBits(V->getType()); 5354 5355 // Otherwise, return the maximum width we found. 5356 return MaxWidth; 5357 } 5358 5359 // Determine if a value V in a vectorizable expression Expr can be demoted to a 5360 // smaller type with a truncation. We collect the values that will be demoted 5361 // in ToDemote and additional roots that require investigating in Roots. 5362 static bool collectValuesToDemote(Value *V, SmallPtrSetImpl<Value *> &Expr, 5363 SmallVectorImpl<Value *> &ToDemote, 5364 SmallVectorImpl<Value *> &Roots) { 5365 // We can always demote constants. 5366 if (isa<Constant>(V)) { 5367 ToDemote.push_back(V); 5368 return true; 5369 } 5370 5371 // If the value is not an instruction in the expression with only one use, it 5372 // cannot be demoted. 5373 auto *I = dyn_cast<Instruction>(V); 5374 if (!I || !I->hasOneUse() || !Expr.count(I)) 5375 return false; 5376 5377 switch (I->getOpcode()) { 5378 5379 // We can always demote truncations and extensions. Since truncations can 5380 // seed additional demotion, we save the truncated value. 5381 case Instruction::Trunc: 5382 Roots.push_back(I->getOperand(0)); 5383 break; 5384 case Instruction::ZExt: 5385 case Instruction::SExt: 5386 break; 5387 5388 // We can demote certain binary operations if we can demote both of their 5389 // operands. 5390 case Instruction::Add: 5391 case Instruction::Sub: 5392 case Instruction::Mul: 5393 case Instruction::And: 5394 case Instruction::Or: 5395 case Instruction::Xor: 5396 if (!collectValuesToDemote(I->getOperand(0), Expr, ToDemote, Roots) || 5397 !collectValuesToDemote(I->getOperand(1), Expr, ToDemote, Roots)) 5398 return false; 5399 break; 5400 5401 // We can demote selects if we can demote their true and false values. 5402 case Instruction::Select: { 5403 SelectInst *SI = cast<SelectInst>(I); 5404 if (!collectValuesToDemote(SI->getTrueValue(), Expr, ToDemote, Roots) || 5405 !collectValuesToDemote(SI->getFalseValue(), Expr, ToDemote, Roots)) 5406 return false; 5407 break; 5408 } 5409 5410 // We can demote phis if we can demote all their incoming operands. Note that 5411 // we don't need to worry about cycles since we ensure single use above. 5412 case Instruction::PHI: { 5413 PHINode *PN = cast<PHINode>(I); 5414 for (Value *IncValue : PN->incoming_values()) 5415 if (!collectValuesToDemote(IncValue, Expr, ToDemote, Roots)) 5416 return false; 5417 break; 5418 } 5419 5420 // Otherwise, conservatively give up. 5421 default: 5422 return false; 5423 } 5424 5425 // Record the value that we can demote. 5426 ToDemote.push_back(V); 5427 return true; 5428 } 5429 5430 void BoUpSLP::computeMinimumValueSizes() { 5431 // If there are no external uses, the expression tree must be rooted by a 5432 // store. We can't demote in-memory values, so there is nothing to do here. 5433 if (ExternalUses.empty()) 5434 return; 5435 5436 // We only attempt to truncate integer expressions. 5437 auto &TreeRoot = VectorizableTree[0]->Scalars; 5438 auto *TreeRootIT = dyn_cast<IntegerType>(TreeRoot[0]->getType()); 5439 if (!TreeRootIT) 5440 return; 5441 5442 // If the expression is not rooted by a store, these roots should have 5443 // external uses. We will rely on InstCombine to rewrite the expression in 5444 // the narrower type. However, InstCombine only rewrites single-use values. 5445 // This means that if a tree entry other than a root is used externally, it 5446 // must have multiple uses and InstCombine will not rewrite it. The code 5447 // below ensures that only the roots are used externally. 5448 SmallPtrSet<Value *, 32> Expr(TreeRoot.begin(), TreeRoot.end()); 5449 for (auto &EU : ExternalUses) 5450 if (!Expr.erase(EU.Scalar)) 5451 return; 5452 if (!Expr.empty()) 5453 return; 5454 5455 // Collect the scalar values of the vectorizable expression. We will use this 5456 // context to determine which values can be demoted. If we see a truncation, 5457 // we mark it as seeding another demotion. 5458 for (auto &EntryPtr : VectorizableTree) 5459 Expr.insert(EntryPtr->Scalars.begin(), EntryPtr->Scalars.end()); 5460 5461 // Ensure the roots of the vectorizable tree don't form a cycle. They must 5462 // have a single external user that is not in the vectorizable tree. 5463 for (auto *Root : TreeRoot) 5464 if (!Root->hasOneUse() || Expr.count(*Root->user_begin())) 5465 return; 5466 5467 // Conservatively determine if we can actually truncate the roots of the 5468 // expression. Collect the values that can be demoted in ToDemote and 5469 // additional roots that require investigating in Roots. 5470 SmallVector<Value *, 32> ToDemote; 5471 SmallVector<Value *, 4> Roots; 5472 for (auto *Root : TreeRoot) 5473 if (!collectValuesToDemote(Root, Expr, ToDemote, Roots)) 5474 return; 5475 5476 // The maximum bit width required to represent all the values that can be 5477 // demoted without loss of precision. It would be safe to truncate the roots 5478 // of the expression to this width. 5479 auto MaxBitWidth = 8u; 5480 5481 // We first check if all the bits of the roots are demanded. If they're not, 5482 // we can truncate the roots to this narrower type. 5483 for (auto *Root : TreeRoot) { 5484 auto Mask = DB->getDemandedBits(cast<Instruction>(Root)); 5485 MaxBitWidth = std::max<unsigned>( 5486 Mask.getBitWidth() - Mask.countLeadingZeros(), MaxBitWidth); 5487 } 5488 5489 // True if the roots can be zero-extended back to their original type, rather 5490 // than sign-extended. We know that if the leading bits are not demanded, we 5491 // can safely zero-extend. So we initialize IsKnownPositive to True. 5492 bool IsKnownPositive = true; 5493 5494 // If all the bits of the roots are demanded, we can try a little harder to 5495 // compute a narrower type. This can happen, for example, if the roots are 5496 // getelementptr indices. InstCombine promotes these indices to the pointer 5497 // width. Thus, all their bits are technically demanded even though the 5498 // address computation might be vectorized in a smaller type. 5499 // 5500 // We start by looking at each entry that can be demoted. We compute the 5501 // maximum bit width required to store the scalar by using ValueTracking to 5502 // compute the number of high-order bits we can truncate. 5503 if (MaxBitWidth == DL->getTypeSizeInBits(TreeRoot[0]->getType()) && 5504 llvm::all_of(TreeRoot, [](Value *R) { 5505 assert(R->hasOneUse() && "Root should have only one use!"); 5506 return isa<GetElementPtrInst>(R->user_back()); 5507 })) { 5508 MaxBitWidth = 8u; 5509 5510 // Determine if the sign bit of all the roots is known to be zero. If not, 5511 // IsKnownPositive is set to False. 5512 IsKnownPositive = llvm::all_of(TreeRoot, [&](Value *R) { 5513 KnownBits Known = computeKnownBits(R, *DL); 5514 return Known.isNonNegative(); 5515 }); 5516 5517 // Determine the maximum number of bits required to store the scalar 5518 // values. 5519 for (auto *Scalar : ToDemote) { 5520 auto NumSignBits = ComputeNumSignBits(Scalar, *DL, 0, AC, nullptr, DT); 5521 auto NumTypeBits = DL->getTypeSizeInBits(Scalar->getType()); 5522 MaxBitWidth = std::max<unsigned>(NumTypeBits - NumSignBits, MaxBitWidth); 5523 } 5524 5525 // If we can't prove that the sign bit is zero, we must add one to the 5526 // maximum bit width to account for the unknown sign bit. This preserves 5527 // the existing sign bit so we can safely sign-extend the root back to the 5528 // original type. Otherwise, if we know the sign bit is zero, we will 5529 // zero-extend the root instead. 5530 // 5531 // FIXME: This is somewhat suboptimal, as there will be cases where adding 5532 // one to the maximum bit width will yield a larger-than-necessary 5533 // type. In general, we need to add an extra bit only if we can't 5534 // prove that the upper bit of the original type is equal to the 5535 // upper bit of the proposed smaller type. If these two bits are the 5536 // same (either zero or one) we know that sign-extending from the 5537 // smaller type will result in the same value. Here, since we can't 5538 // yet prove this, we are just making the proposed smaller type 5539 // larger to ensure correctness. 5540 if (!IsKnownPositive) 5541 ++MaxBitWidth; 5542 } 5543 5544 // Round MaxBitWidth up to the next power-of-two. 5545 if (!isPowerOf2_64(MaxBitWidth)) 5546 MaxBitWidth = NextPowerOf2(MaxBitWidth); 5547 5548 // If the maximum bit width we compute is less than the with of the roots' 5549 // type, we can proceed with the narrowing. Otherwise, do nothing. 5550 if (MaxBitWidth >= TreeRootIT->getBitWidth()) 5551 return; 5552 5553 // If we can truncate the root, we must collect additional values that might 5554 // be demoted as a result. That is, those seeded by truncations we will 5555 // modify. 5556 while (!Roots.empty()) 5557 collectValuesToDemote(Roots.pop_back_val(), Expr, ToDemote, Roots); 5558 5559 // Finally, map the values we can demote to the maximum bit with we computed. 5560 for (auto *Scalar : ToDemote) 5561 MinBWs[Scalar] = std::make_pair(MaxBitWidth, !IsKnownPositive); 5562 } 5563 5564 namespace { 5565 5566 /// The SLPVectorizer Pass. 5567 struct SLPVectorizer : public FunctionPass { 5568 SLPVectorizerPass Impl; 5569 5570 /// Pass identification, replacement for typeid 5571 static char ID; 5572 5573 explicit SLPVectorizer() : FunctionPass(ID) { 5574 initializeSLPVectorizerPass(*PassRegistry::getPassRegistry()); 5575 } 5576 5577 bool doInitialization(Module &M) override { 5578 return false; 5579 } 5580 5581 bool runOnFunction(Function &F) override { 5582 if (skipFunction(F)) 5583 return false; 5584 5585 auto *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 5586 auto *TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F); 5587 auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>(); 5588 auto *TLI = TLIP ? &TLIP->getTLI(F) : nullptr; 5589 auto *AA = &getAnalysis<AAResultsWrapperPass>().getAAResults(); 5590 auto *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 5591 auto *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 5592 auto *AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F); 5593 auto *DB = &getAnalysis<DemandedBitsWrapperPass>().getDemandedBits(); 5594 auto *ORE = &getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE(); 5595 5596 return Impl.runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 5597 } 5598 5599 void getAnalysisUsage(AnalysisUsage &AU) const override { 5600 FunctionPass::getAnalysisUsage(AU); 5601 AU.addRequired<AssumptionCacheTracker>(); 5602 AU.addRequired<ScalarEvolutionWrapperPass>(); 5603 AU.addRequired<AAResultsWrapperPass>(); 5604 AU.addRequired<TargetTransformInfoWrapperPass>(); 5605 AU.addRequired<LoopInfoWrapperPass>(); 5606 AU.addRequired<DominatorTreeWrapperPass>(); 5607 AU.addRequired<DemandedBitsWrapperPass>(); 5608 AU.addRequired<OptimizationRemarkEmitterWrapperPass>(); 5609 AU.addRequired<InjectTLIMappingsLegacy>(); 5610 AU.addPreserved<LoopInfoWrapperPass>(); 5611 AU.addPreserved<DominatorTreeWrapperPass>(); 5612 AU.addPreserved<AAResultsWrapperPass>(); 5613 AU.addPreserved<GlobalsAAWrapperPass>(); 5614 AU.setPreservesCFG(); 5615 } 5616 }; 5617 5618 } // end anonymous namespace 5619 5620 PreservedAnalyses SLPVectorizerPass::run(Function &F, FunctionAnalysisManager &AM) { 5621 auto *SE = &AM.getResult<ScalarEvolutionAnalysis>(F); 5622 auto *TTI = &AM.getResult<TargetIRAnalysis>(F); 5623 auto *TLI = AM.getCachedResult<TargetLibraryAnalysis>(F); 5624 auto *AA = &AM.getResult<AAManager>(F); 5625 auto *LI = &AM.getResult<LoopAnalysis>(F); 5626 auto *DT = &AM.getResult<DominatorTreeAnalysis>(F); 5627 auto *AC = &AM.getResult<AssumptionAnalysis>(F); 5628 auto *DB = &AM.getResult<DemandedBitsAnalysis>(F); 5629 auto *ORE = &AM.getResult<OptimizationRemarkEmitterAnalysis>(F); 5630 5631 bool Changed = runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 5632 if (!Changed) 5633 return PreservedAnalyses::all(); 5634 5635 PreservedAnalyses PA; 5636 PA.preserveSet<CFGAnalyses>(); 5637 PA.preserve<AAManager>(); 5638 PA.preserve<GlobalsAA>(); 5639 return PA; 5640 } 5641 5642 bool SLPVectorizerPass::runImpl(Function &F, ScalarEvolution *SE_, 5643 TargetTransformInfo *TTI_, 5644 TargetLibraryInfo *TLI_, AliasAnalysis *AA_, 5645 LoopInfo *LI_, DominatorTree *DT_, 5646 AssumptionCache *AC_, DemandedBits *DB_, 5647 OptimizationRemarkEmitter *ORE_) { 5648 if (!RunSLPVectorization) 5649 return false; 5650 SE = SE_; 5651 TTI = TTI_; 5652 TLI = TLI_; 5653 AA = AA_; 5654 LI = LI_; 5655 DT = DT_; 5656 AC = AC_; 5657 DB = DB_; 5658 DL = &F.getParent()->getDataLayout(); 5659 5660 Stores.clear(); 5661 GEPs.clear(); 5662 bool Changed = false; 5663 5664 // If the target claims to have no vector registers don't attempt 5665 // vectorization. 5666 if (!TTI->getNumberOfRegisters(TTI->getRegisterClassForType(true))) 5667 return false; 5668 5669 // Don't vectorize when the attribute NoImplicitFloat is used. 5670 if (F.hasFnAttribute(Attribute::NoImplicitFloat)) 5671 return false; 5672 5673 LLVM_DEBUG(dbgs() << "SLP: Analyzing blocks in " << F.getName() << ".\n"); 5674 5675 // Use the bottom up slp vectorizer to construct chains that start with 5676 // store instructions. 5677 BoUpSLP R(&F, SE, TTI, TLI, AA, LI, DT, AC, DB, DL, ORE_); 5678 5679 // A general note: the vectorizer must use BoUpSLP::eraseInstruction() to 5680 // delete instructions. 5681 5682 // Scan the blocks in the function in post order. 5683 for (auto BB : post_order(&F.getEntryBlock())) { 5684 collectSeedInstructions(BB); 5685 5686 // Vectorize trees that end at stores. 5687 if (!Stores.empty()) { 5688 LLVM_DEBUG(dbgs() << "SLP: Found stores for " << Stores.size() 5689 << " underlying objects.\n"); 5690 Changed |= vectorizeStoreChains(R); 5691 } 5692 5693 // Vectorize trees that end at reductions. 5694 Changed |= vectorizeChainsInBlock(BB, R); 5695 5696 // Vectorize the index computations of getelementptr instructions. This 5697 // is primarily intended to catch gather-like idioms ending at 5698 // non-consecutive loads. 5699 if (!GEPs.empty()) { 5700 LLVM_DEBUG(dbgs() << "SLP: Found GEPs for " << GEPs.size() 5701 << " underlying objects.\n"); 5702 Changed |= vectorizeGEPIndices(BB, R); 5703 } 5704 } 5705 5706 if (Changed) { 5707 R.optimizeGatherSequence(); 5708 LLVM_DEBUG(dbgs() << "SLP: vectorized \"" << F.getName() << "\"\n"); 5709 LLVM_DEBUG(verifyFunction(F)); 5710 } 5711 return Changed; 5712 } 5713 5714 bool SLPVectorizerPass::vectorizeStoreChain(ArrayRef<Value *> Chain, BoUpSLP &R, 5715 unsigned Idx) { 5716 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " << Chain.size() 5717 << "\n"); 5718 const unsigned Sz = R.getVectorElementSize(Chain[0]); 5719 const unsigned MinVF = R.getMinVecRegSize() / Sz; 5720 unsigned VF = Chain.size(); 5721 5722 if (!isPowerOf2_32(Sz) || !isPowerOf2_32(VF) || VF < 2 || VF < MinVF) 5723 return false; 5724 5725 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << VF << " stores at offset " << Idx 5726 << "\n"); 5727 5728 R.buildTree(Chain); 5729 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 5730 // TODO: Handle orders of size less than number of elements in the vector. 5731 if (Order && Order->size() == Chain.size()) { 5732 // TODO: reorder tree nodes without tree rebuilding. 5733 SmallVector<Value *, 4> ReorderedOps(Chain.rbegin(), Chain.rend()); 5734 llvm::transform(*Order, ReorderedOps.begin(), 5735 [Chain](const unsigned Idx) { return Chain[Idx]; }); 5736 R.buildTree(ReorderedOps); 5737 } 5738 if (R.isTreeTinyAndNotFullyVectorizable()) 5739 return false; 5740 5741 R.computeMinimumValueSizes(); 5742 5743 int Cost = R.getTreeCost(); 5744 5745 LLVM_DEBUG(dbgs() << "SLP: Found cost=" << Cost << " for VF=" << VF << "\n"); 5746 if (Cost < -SLPCostThreshold) { 5747 LLVM_DEBUG(dbgs() << "SLP: Decided to vectorize cost=" << Cost << "\n"); 5748 5749 using namespace ore; 5750 5751 R.getORE()->emit(OptimizationRemark(SV_NAME, "StoresVectorized", 5752 cast<StoreInst>(Chain[0])) 5753 << "Stores SLP vectorized with cost " << NV("Cost", Cost) 5754 << " and with tree size " 5755 << NV("TreeSize", R.getTreeSize())); 5756 5757 R.vectorizeTree(); 5758 return true; 5759 } 5760 5761 return false; 5762 } 5763 5764 bool SLPVectorizerPass::vectorizeStores(ArrayRef<StoreInst *> Stores, 5765 BoUpSLP &R) { 5766 // We may run into multiple chains that merge into a single chain. We mark the 5767 // stores that we vectorized so that we don't visit the same store twice. 5768 BoUpSLP::ValueSet VectorizedStores; 5769 bool Changed = false; 5770 5771 int E = Stores.size(); 5772 SmallBitVector Tails(E, false); 5773 SmallVector<int, 16> ConsecutiveChain(E, E + 1); 5774 int MaxIter = MaxStoreLookup.getValue(); 5775 int IterCnt; 5776 auto &&FindConsecutiveAccess = [this, &Stores, &Tails, &IterCnt, MaxIter, 5777 &ConsecutiveChain](int K, int Idx) { 5778 if (IterCnt >= MaxIter) 5779 return true; 5780 ++IterCnt; 5781 if (!isConsecutiveAccess(Stores[K], Stores[Idx], *DL, *SE)) 5782 return false; 5783 5784 Tails.set(Idx); 5785 ConsecutiveChain[K] = Idx; 5786 return true; 5787 }; 5788 // Do a quadratic search on all of the given stores in reverse order and find 5789 // all of the pairs of stores that follow each other. 5790 for (int Idx = E - 1; Idx >= 0; --Idx) { 5791 // If a store has multiple consecutive store candidates, search according 5792 // to the sequence: Idx-1, Idx+1, Idx-2, Idx+2, ... 5793 // This is because usually pairing with immediate succeeding or preceding 5794 // candidate create the best chance to find slp vectorization opportunity. 5795 const int MaxLookDepth = std::max(E - Idx, Idx + 1); 5796 IterCnt = 0; 5797 for (int Offset = 1, F = MaxLookDepth; Offset < F; ++Offset) 5798 if ((Idx >= Offset && FindConsecutiveAccess(Idx - Offset, Idx)) || 5799 (Idx + Offset < E && FindConsecutiveAccess(Idx + Offset, Idx))) 5800 break; 5801 } 5802 5803 // For stores that start but don't end a link in the chain: 5804 for (int Cnt = E; Cnt > 0; --Cnt) { 5805 int I = Cnt - 1; 5806 if (ConsecutiveChain[I] == E + 1 || Tails.test(I)) 5807 continue; 5808 // We found a store instr that starts a chain. Now follow the chain and try 5809 // to vectorize it. 5810 BoUpSLP::ValueList Operands; 5811 // Collect the chain into a list. 5812 while (I != E + 1 && !VectorizedStores.count(Stores[I])) { 5813 Operands.push_back(Stores[I]); 5814 // Move to the next value in the chain. 5815 I = ConsecutiveChain[I]; 5816 } 5817 5818 // If a vector register can't hold 1 element, we are done. 5819 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 5820 unsigned EltSize = R.getVectorElementSize(Stores[0]); 5821 if (MaxVecRegSize % EltSize != 0) 5822 continue; 5823 5824 unsigned MaxElts = MaxVecRegSize / EltSize; 5825 // FIXME: Is division-by-2 the correct step? Should we assert that the 5826 // register size is a power-of-2? 5827 unsigned StartIdx = 0; 5828 for (unsigned Size = llvm::PowerOf2Ceil(MaxElts); Size >= 2; Size /= 2) { 5829 for (unsigned Cnt = StartIdx, E = Operands.size(); Cnt + Size <= E;) { 5830 ArrayRef<Value *> Slice = makeArrayRef(Operands).slice(Cnt, Size); 5831 if (!VectorizedStores.count(Slice.front()) && 5832 !VectorizedStores.count(Slice.back()) && 5833 vectorizeStoreChain(Slice, R, Cnt)) { 5834 // Mark the vectorized stores so that we don't vectorize them again. 5835 VectorizedStores.insert(Slice.begin(), Slice.end()); 5836 Changed = true; 5837 // If we vectorized initial block, no need to try to vectorize it 5838 // again. 5839 if (Cnt == StartIdx) 5840 StartIdx += Size; 5841 Cnt += Size; 5842 continue; 5843 } 5844 ++Cnt; 5845 } 5846 // Check if the whole array was vectorized already - exit. 5847 if (StartIdx >= Operands.size()) 5848 break; 5849 } 5850 } 5851 5852 return Changed; 5853 } 5854 5855 void SLPVectorizerPass::collectSeedInstructions(BasicBlock *BB) { 5856 // Initialize the collections. We will make a single pass over the block. 5857 Stores.clear(); 5858 GEPs.clear(); 5859 5860 // Visit the store and getelementptr instructions in BB and organize them in 5861 // Stores and GEPs according to the underlying objects of their pointer 5862 // operands. 5863 for (Instruction &I : *BB) { 5864 // Ignore store instructions that are volatile or have a pointer operand 5865 // that doesn't point to a scalar type. 5866 if (auto *SI = dyn_cast<StoreInst>(&I)) { 5867 if (!SI->isSimple()) 5868 continue; 5869 if (!isValidElementType(SI->getValueOperand()->getType())) 5870 continue; 5871 Stores[GetUnderlyingObject(SI->getPointerOperand(), *DL)].push_back(SI); 5872 } 5873 5874 // Ignore getelementptr instructions that have more than one index, a 5875 // constant index, or a pointer operand that doesn't point to a scalar 5876 // type. 5877 else if (auto *GEP = dyn_cast<GetElementPtrInst>(&I)) { 5878 auto Idx = GEP->idx_begin()->get(); 5879 if (GEP->getNumIndices() > 1 || isa<Constant>(Idx)) 5880 continue; 5881 if (!isValidElementType(Idx->getType())) 5882 continue; 5883 if (GEP->getType()->isVectorTy()) 5884 continue; 5885 GEPs[GEP->getPointerOperand()].push_back(GEP); 5886 } 5887 } 5888 } 5889 5890 bool SLPVectorizerPass::tryToVectorizePair(Value *A, Value *B, BoUpSLP &R) { 5891 if (!A || !B) 5892 return false; 5893 Value *VL[] = { A, B }; 5894 return tryToVectorizeList(VL, R, /*UserCost=*/0, true); 5895 } 5896 5897 bool SLPVectorizerPass::tryToVectorizeList(ArrayRef<Value *> VL, BoUpSLP &R, 5898 int UserCost, bool AllowReorder) { 5899 if (VL.size() < 2) 5900 return false; 5901 5902 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize a list of length = " 5903 << VL.size() << ".\n"); 5904 5905 // Check that all of the parts are instructions of the same type, 5906 // we permit an alternate opcode via InstructionsState. 5907 InstructionsState S = getSameOpcode(VL); 5908 if (!S.getOpcode()) 5909 return false; 5910 5911 Instruction *I0 = cast<Instruction>(S.OpValue); 5912 // Make sure invalid types (including vector type) are rejected before 5913 // determining vectorization factor for scalar instructions. 5914 for (Value *V : VL) { 5915 Type *Ty = V->getType(); 5916 if (!isValidElementType(Ty)) { 5917 // NOTE: the following will give user internal llvm type name, which may 5918 // not be useful. 5919 R.getORE()->emit([&]() { 5920 std::string type_str; 5921 llvm::raw_string_ostream rso(type_str); 5922 Ty->print(rso); 5923 return OptimizationRemarkMissed(SV_NAME, "UnsupportedType", I0) 5924 << "Cannot SLP vectorize list: type " 5925 << rso.str() + " is unsupported by vectorizer"; 5926 }); 5927 return false; 5928 } 5929 } 5930 5931 unsigned Sz = R.getVectorElementSize(I0); 5932 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / Sz); 5933 unsigned MaxVF = std::max<unsigned>(PowerOf2Floor(VL.size()), MinVF); 5934 if (MaxVF < 2) { 5935 R.getORE()->emit([&]() { 5936 return OptimizationRemarkMissed(SV_NAME, "SmallVF", I0) 5937 << "Cannot SLP vectorize list: vectorization factor " 5938 << "less than 2 is not supported"; 5939 }); 5940 return false; 5941 } 5942 5943 bool Changed = false; 5944 bool CandidateFound = false; 5945 int MinCost = SLPCostThreshold; 5946 5947 unsigned NextInst = 0, MaxInst = VL.size(); 5948 for (unsigned VF = MaxVF; NextInst + 1 < MaxInst && VF >= MinVF; VF /= 2) { 5949 // No actual vectorization should happen, if number of parts is the same as 5950 // provided vectorization factor (i.e. the scalar type is used for vector 5951 // code during codegen). 5952 auto *VecTy = VectorType::get(VL[0]->getType(), VF); 5953 if (TTI->getNumberOfParts(VecTy) == VF) 5954 continue; 5955 for (unsigned I = NextInst; I < MaxInst; ++I) { 5956 unsigned OpsWidth = 0; 5957 5958 if (I + VF > MaxInst) 5959 OpsWidth = MaxInst - I; 5960 else 5961 OpsWidth = VF; 5962 5963 if (!isPowerOf2_32(OpsWidth) || OpsWidth < 2) 5964 break; 5965 5966 ArrayRef<Value *> Ops = VL.slice(I, OpsWidth); 5967 // Check that a previous iteration of this loop did not delete the Value. 5968 if (llvm::any_of(Ops, [&R](Value *V) { 5969 auto *I = dyn_cast<Instruction>(V); 5970 return I && R.isDeleted(I); 5971 })) 5972 continue; 5973 5974 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << OpsWidth << " operations " 5975 << "\n"); 5976 5977 R.buildTree(Ops); 5978 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 5979 // TODO: check if we can allow reordering for more cases. 5980 if (AllowReorder && Order) { 5981 // TODO: reorder tree nodes without tree rebuilding. 5982 // Conceptually, there is nothing actually preventing us from trying to 5983 // reorder a larger list. In fact, we do exactly this when vectorizing 5984 // reductions. However, at this point, we only expect to get here when 5985 // there are exactly two operations. 5986 assert(Ops.size() == 2); 5987 Value *ReorderedOps[] = {Ops[1], Ops[0]}; 5988 R.buildTree(ReorderedOps, None); 5989 } 5990 if (R.isTreeTinyAndNotFullyVectorizable()) 5991 continue; 5992 5993 R.computeMinimumValueSizes(); 5994 int Cost = R.getTreeCost() - UserCost; 5995 CandidateFound = true; 5996 MinCost = std::min(MinCost, Cost); 5997 5998 if (Cost < -SLPCostThreshold) { 5999 LLVM_DEBUG(dbgs() << "SLP: Vectorizing list at cost:" << Cost << ".\n"); 6000 R.getORE()->emit(OptimizationRemark(SV_NAME, "VectorizedList", 6001 cast<Instruction>(Ops[0])) 6002 << "SLP vectorized with cost " << ore::NV("Cost", Cost) 6003 << " and with tree size " 6004 << ore::NV("TreeSize", R.getTreeSize())); 6005 6006 R.vectorizeTree(); 6007 // Move to the next bundle. 6008 I += VF - 1; 6009 NextInst = I + 1; 6010 Changed = true; 6011 } 6012 } 6013 } 6014 6015 if (!Changed && CandidateFound) { 6016 R.getORE()->emit([&]() { 6017 return OptimizationRemarkMissed(SV_NAME, "NotBeneficial", I0) 6018 << "List vectorization was possible but not beneficial with cost " 6019 << ore::NV("Cost", MinCost) << " >= " 6020 << ore::NV("Treshold", -SLPCostThreshold); 6021 }); 6022 } else if (!Changed) { 6023 R.getORE()->emit([&]() { 6024 return OptimizationRemarkMissed(SV_NAME, "NotPossible", I0) 6025 << "Cannot SLP vectorize list: vectorization was impossible" 6026 << " with available vectorization factors"; 6027 }); 6028 } 6029 return Changed; 6030 } 6031 6032 bool SLPVectorizerPass::tryToVectorize(Instruction *I, BoUpSLP &R) { 6033 if (!I) 6034 return false; 6035 6036 if (!isa<BinaryOperator>(I) && !isa<CmpInst>(I)) 6037 return false; 6038 6039 Value *P = I->getParent(); 6040 6041 // Vectorize in current basic block only. 6042 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 6043 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 6044 if (!Op0 || !Op1 || Op0->getParent() != P || Op1->getParent() != P) 6045 return false; 6046 6047 // Try to vectorize V. 6048 if (tryToVectorizePair(Op0, Op1, R)) 6049 return true; 6050 6051 auto *A = dyn_cast<BinaryOperator>(Op0); 6052 auto *B = dyn_cast<BinaryOperator>(Op1); 6053 // Try to skip B. 6054 if (B && B->hasOneUse()) { 6055 auto *B0 = dyn_cast<BinaryOperator>(B->getOperand(0)); 6056 auto *B1 = dyn_cast<BinaryOperator>(B->getOperand(1)); 6057 if (B0 && B0->getParent() == P && tryToVectorizePair(A, B0, R)) 6058 return true; 6059 if (B1 && B1->getParent() == P && tryToVectorizePair(A, B1, R)) 6060 return true; 6061 } 6062 6063 // Try to skip A. 6064 if (A && A->hasOneUse()) { 6065 auto *A0 = dyn_cast<BinaryOperator>(A->getOperand(0)); 6066 auto *A1 = dyn_cast<BinaryOperator>(A->getOperand(1)); 6067 if (A0 && A0->getParent() == P && tryToVectorizePair(A0, B, R)) 6068 return true; 6069 if (A1 && A1->getParent() == P && tryToVectorizePair(A1, B, R)) 6070 return true; 6071 } 6072 return false; 6073 } 6074 6075 /// Generate a shuffle mask to be used in a reduction tree. 6076 /// 6077 /// \param VecLen The length of the vector to be reduced. 6078 /// \param NumEltsToRdx The number of elements that should be reduced in the 6079 /// vector. 6080 /// \param IsPairwise Whether the reduction is a pairwise or splitting 6081 /// reduction. A pairwise reduction will generate a mask of 6082 /// <0,2,...> or <1,3,..> while a splitting reduction will generate 6083 /// <2,3, undef,undef> for a vector of 4 and NumElts = 2. 6084 /// \param IsLeft True will generate a mask of even elements, odd otherwise. 6085 static SmallVector<int, 32> createRdxShuffleMask(unsigned VecLen, 6086 unsigned NumEltsToRdx, 6087 bool IsPairwise, bool IsLeft) { 6088 assert((IsPairwise || !IsLeft) && "Don't support a <0,1,undef,...> mask"); 6089 6090 SmallVector<int, 32> ShuffleMask(VecLen, -1); 6091 6092 if (IsPairwise) 6093 // Build a mask of 0, 2, ... (left) or 1, 3, ... (right). 6094 for (unsigned i = 0; i != NumEltsToRdx; ++i) 6095 ShuffleMask[i] = 2 * i + !IsLeft; 6096 else 6097 // Move the upper half of the vector to the lower half. 6098 for (unsigned i = 0; i != NumEltsToRdx; ++i) 6099 ShuffleMask[i] = NumEltsToRdx + i; 6100 6101 return ShuffleMask; 6102 } 6103 6104 namespace { 6105 6106 /// Model horizontal reductions. 6107 /// 6108 /// A horizontal reduction is a tree of reduction operations (currently add and 6109 /// fadd) that has operations that can be put into a vector as its leaf. 6110 /// For example, this tree: 6111 /// 6112 /// mul mul mul mul 6113 /// \ / \ / 6114 /// + + 6115 /// \ / 6116 /// + 6117 /// This tree has "mul" as its reduced values and "+" as its reduction 6118 /// operations. A reduction might be feeding into a store or a binary operation 6119 /// feeding a phi. 6120 /// ... 6121 /// \ / 6122 /// + 6123 /// | 6124 /// phi += 6125 /// 6126 /// Or: 6127 /// ... 6128 /// \ / 6129 /// + 6130 /// | 6131 /// *p = 6132 /// 6133 class HorizontalReduction { 6134 using ReductionOpsType = SmallVector<Value *, 16>; 6135 using ReductionOpsListType = SmallVector<ReductionOpsType, 2>; 6136 ReductionOpsListType ReductionOps; 6137 SmallVector<Value *, 32> ReducedVals; 6138 // Use map vector to make stable output. 6139 MapVector<Instruction *, Value *> ExtraArgs; 6140 6141 /// Kind of the reduction data. 6142 enum ReductionKind { 6143 RK_None, /// Not a reduction. 6144 RK_Arithmetic, /// Binary reduction data. 6145 RK_Min, /// Minimum reduction data. 6146 RK_UMin, /// Unsigned minimum reduction data. 6147 RK_Max, /// Maximum reduction data. 6148 RK_UMax, /// Unsigned maximum reduction data. 6149 }; 6150 6151 /// Contains info about operation, like its opcode, left and right operands. 6152 class OperationData { 6153 /// Opcode of the instruction. 6154 unsigned Opcode = 0; 6155 6156 /// Left operand of the reduction operation. 6157 Value *LHS = nullptr; 6158 6159 /// Right operand of the reduction operation. 6160 Value *RHS = nullptr; 6161 6162 /// Kind of the reduction operation. 6163 ReductionKind Kind = RK_None; 6164 6165 /// True if float point min/max reduction has no NaNs. 6166 bool NoNaN = false; 6167 6168 /// Checks if the reduction operation can be vectorized. 6169 bool isVectorizable() const { 6170 return LHS && RHS && 6171 // We currently only support add/mul/logical && min/max reductions. 6172 ((Kind == RK_Arithmetic && 6173 (Opcode == Instruction::Add || Opcode == Instruction::FAdd || 6174 Opcode == Instruction::Mul || Opcode == Instruction::FMul || 6175 Opcode == Instruction::And || Opcode == Instruction::Or || 6176 Opcode == Instruction::Xor)) || 6177 ((Opcode == Instruction::ICmp || Opcode == Instruction::FCmp) && 6178 (Kind == RK_Min || Kind == RK_Max)) || 6179 (Opcode == Instruction::ICmp && 6180 (Kind == RK_UMin || Kind == RK_UMax))); 6181 } 6182 6183 /// Creates reduction operation with the current opcode. 6184 Value *createOp(IRBuilder<> &Builder, const Twine &Name) const { 6185 assert(isVectorizable() && 6186 "Expected add|fadd or min/max reduction operation."); 6187 Value *Cmp = nullptr; 6188 switch (Kind) { 6189 case RK_Arithmetic: 6190 return Builder.CreateBinOp((Instruction::BinaryOps)Opcode, LHS, RHS, 6191 Name); 6192 case RK_Min: 6193 Cmp = Opcode == Instruction::ICmp ? Builder.CreateICmpSLT(LHS, RHS) 6194 : Builder.CreateFCmpOLT(LHS, RHS); 6195 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6196 case RK_Max: 6197 Cmp = Opcode == Instruction::ICmp ? Builder.CreateICmpSGT(LHS, RHS) 6198 : Builder.CreateFCmpOGT(LHS, RHS); 6199 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6200 case RK_UMin: 6201 assert(Opcode == Instruction::ICmp && "Expected integer types."); 6202 Cmp = Builder.CreateICmpULT(LHS, RHS); 6203 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6204 case RK_UMax: 6205 assert(Opcode == Instruction::ICmp && "Expected integer types."); 6206 Cmp = Builder.CreateICmpUGT(LHS, RHS); 6207 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6208 case RK_None: 6209 break; 6210 } 6211 llvm_unreachable("Unknown reduction operation."); 6212 } 6213 6214 public: 6215 explicit OperationData() = default; 6216 6217 /// Construction for reduced values. They are identified by opcode only and 6218 /// don't have associated LHS/RHS values. 6219 explicit OperationData(Value *V) { 6220 if (auto *I = dyn_cast<Instruction>(V)) 6221 Opcode = I->getOpcode(); 6222 } 6223 6224 /// Constructor for reduction operations with opcode and its left and 6225 /// right operands. 6226 OperationData(unsigned Opcode, Value *LHS, Value *RHS, ReductionKind Kind, 6227 bool NoNaN = false) 6228 : Opcode(Opcode), LHS(LHS), RHS(RHS), Kind(Kind), NoNaN(NoNaN) { 6229 assert(Kind != RK_None && "One of the reduction operations is expected."); 6230 } 6231 6232 explicit operator bool() const { return Opcode; } 6233 6234 /// Return true if this operation is any kind of minimum or maximum. 6235 bool isMinMax() const { 6236 switch (Kind) { 6237 case RK_Arithmetic: 6238 return false; 6239 case RK_Min: 6240 case RK_Max: 6241 case RK_UMin: 6242 case RK_UMax: 6243 return true; 6244 case RK_None: 6245 break; 6246 } 6247 llvm_unreachable("Reduction kind is not set"); 6248 } 6249 6250 /// Get the index of the first operand. 6251 unsigned getFirstOperandIndex() const { 6252 assert(!!*this && "The opcode is not set."); 6253 // We allow calling this before 'Kind' is set, so handle that specially. 6254 if (Kind == RK_None) 6255 return 0; 6256 return isMinMax() ? 1 : 0; 6257 } 6258 6259 /// Total number of operands in the reduction operation. 6260 unsigned getNumberOfOperands() const { 6261 assert(Kind != RK_None && !!*this && LHS && RHS && 6262 "Expected reduction operation."); 6263 return isMinMax() ? 3 : 2; 6264 } 6265 6266 /// Checks if the operation has the same parent as \p P. 6267 bool hasSameParent(Instruction *I, Value *P, bool IsRedOp) const { 6268 assert(Kind != RK_None && !!*this && LHS && RHS && 6269 "Expected reduction operation."); 6270 if (!IsRedOp) 6271 return I->getParent() == P; 6272 if (isMinMax()) { 6273 // SelectInst must be used twice while the condition op must have single 6274 // use only. 6275 auto *Cmp = cast<Instruction>(cast<SelectInst>(I)->getCondition()); 6276 return I->getParent() == P && Cmp && Cmp->getParent() == P; 6277 } 6278 // Arithmetic reduction operation must be used once only. 6279 return I->getParent() == P; 6280 } 6281 6282 /// Expected number of uses for reduction operations/reduced values. 6283 bool hasRequiredNumberOfUses(Instruction *I, bool IsReductionOp) const { 6284 assert(Kind != RK_None && !!*this && LHS && RHS && 6285 "Expected reduction operation."); 6286 if (isMinMax()) 6287 return I->hasNUses(2) && 6288 (!IsReductionOp || 6289 cast<SelectInst>(I)->getCondition()->hasOneUse()); 6290 return I->hasOneUse(); 6291 } 6292 6293 /// Initializes the list of reduction operations. 6294 void initReductionOps(ReductionOpsListType &ReductionOps) { 6295 assert(Kind != RK_None && !!*this && LHS && RHS && 6296 "Expected reduction operation."); 6297 if (isMinMax()) 6298 ReductionOps.assign(2, ReductionOpsType()); 6299 else 6300 ReductionOps.assign(1, ReductionOpsType()); 6301 } 6302 6303 /// Add all reduction operations for the reduction instruction \p I. 6304 void addReductionOps(Instruction *I, ReductionOpsListType &ReductionOps) { 6305 assert(Kind != RK_None && !!*this && LHS && RHS && 6306 "Expected reduction operation."); 6307 if (isMinMax()) { 6308 ReductionOps[0].emplace_back(cast<SelectInst>(I)->getCondition()); 6309 ReductionOps[1].emplace_back(I); 6310 } else { 6311 ReductionOps[0].emplace_back(I); 6312 } 6313 } 6314 6315 /// Checks if instruction is associative and can be vectorized. 6316 bool isAssociative(Instruction *I) const { 6317 assert(Kind != RK_None && *this && LHS && RHS && 6318 "Expected reduction operation."); 6319 switch (Kind) { 6320 case RK_Arithmetic: 6321 return I->isAssociative(); 6322 case RK_Min: 6323 case RK_Max: 6324 return Opcode == Instruction::ICmp || 6325 cast<Instruction>(I->getOperand(0))->isFast(); 6326 case RK_UMin: 6327 case RK_UMax: 6328 assert(Opcode == Instruction::ICmp && 6329 "Only integer compare operation is expected."); 6330 return true; 6331 case RK_None: 6332 break; 6333 } 6334 llvm_unreachable("Reduction kind is not set"); 6335 } 6336 6337 /// Checks if the reduction operation can be vectorized. 6338 bool isVectorizable(Instruction *I) const { 6339 return isVectorizable() && isAssociative(I); 6340 } 6341 6342 /// Checks if two operation data are both a reduction op or both a reduced 6343 /// value. 6344 bool operator==(const OperationData &OD) const { 6345 assert(((Kind != OD.Kind) || ((!LHS == !OD.LHS) && (!RHS == !OD.RHS))) && 6346 "One of the comparing operations is incorrect."); 6347 return this == &OD || (Kind == OD.Kind && Opcode == OD.Opcode); 6348 } 6349 bool operator!=(const OperationData &OD) const { return !(*this == OD); } 6350 void clear() { 6351 Opcode = 0; 6352 LHS = nullptr; 6353 RHS = nullptr; 6354 Kind = RK_None; 6355 NoNaN = false; 6356 } 6357 6358 /// Get the opcode of the reduction operation. 6359 unsigned getOpcode() const { 6360 assert(isVectorizable() && "Expected vectorizable operation."); 6361 return Opcode; 6362 } 6363 6364 /// Get kind of reduction data. 6365 ReductionKind getKind() const { return Kind; } 6366 Value *getLHS() const { return LHS; } 6367 Value *getRHS() const { return RHS; } 6368 Type *getConditionType() const { 6369 return isMinMax() ? CmpInst::makeCmpResultType(LHS->getType()) : nullptr; 6370 } 6371 6372 /// Creates reduction operation with the current opcode with the IR flags 6373 /// from \p ReductionOps. 6374 Value *createOp(IRBuilder<> &Builder, const Twine &Name, 6375 const ReductionOpsListType &ReductionOps) const { 6376 assert(isVectorizable() && 6377 "Expected add|fadd or min/max reduction operation."); 6378 auto *Op = createOp(Builder, Name); 6379 switch (Kind) { 6380 case RK_Arithmetic: 6381 propagateIRFlags(Op, ReductionOps[0]); 6382 return Op; 6383 case RK_Min: 6384 case RK_Max: 6385 case RK_UMin: 6386 case RK_UMax: 6387 if (auto *SI = dyn_cast<SelectInst>(Op)) 6388 propagateIRFlags(SI->getCondition(), ReductionOps[0]); 6389 propagateIRFlags(Op, ReductionOps[1]); 6390 return Op; 6391 case RK_None: 6392 break; 6393 } 6394 llvm_unreachable("Unknown reduction operation."); 6395 } 6396 /// Creates reduction operation with the current opcode with the IR flags 6397 /// from \p I. 6398 Value *createOp(IRBuilder<> &Builder, const Twine &Name, 6399 Instruction *I) const { 6400 assert(isVectorizable() && 6401 "Expected add|fadd or min/max reduction operation."); 6402 auto *Op = createOp(Builder, Name); 6403 switch (Kind) { 6404 case RK_Arithmetic: 6405 propagateIRFlags(Op, I); 6406 return Op; 6407 case RK_Min: 6408 case RK_Max: 6409 case RK_UMin: 6410 case RK_UMax: 6411 if (auto *SI = dyn_cast<SelectInst>(Op)) { 6412 propagateIRFlags(SI->getCondition(), 6413 cast<SelectInst>(I)->getCondition()); 6414 } 6415 propagateIRFlags(Op, I); 6416 return Op; 6417 case RK_None: 6418 break; 6419 } 6420 llvm_unreachable("Unknown reduction operation."); 6421 } 6422 6423 TargetTransformInfo::ReductionFlags getFlags() const { 6424 TargetTransformInfo::ReductionFlags Flags; 6425 Flags.NoNaN = NoNaN; 6426 switch (Kind) { 6427 case RK_Arithmetic: 6428 break; 6429 case RK_Min: 6430 Flags.IsSigned = Opcode == Instruction::ICmp; 6431 Flags.IsMaxOp = false; 6432 break; 6433 case RK_Max: 6434 Flags.IsSigned = Opcode == Instruction::ICmp; 6435 Flags.IsMaxOp = true; 6436 break; 6437 case RK_UMin: 6438 Flags.IsSigned = false; 6439 Flags.IsMaxOp = false; 6440 break; 6441 case RK_UMax: 6442 Flags.IsSigned = false; 6443 Flags.IsMaxOp = true; 6444 break; 6445 case RK_None: 6446 llvm_unreachable("Reduction kind is not set"); 6447 } 6448 return Flags; 6449 } 6450 }; 6451 6452 WeakTrackingVH ReductionRoot; 6453 6454 /// The operation data of the reduction operation. 6455 OperationData ReductionData; 6456 6457 /// The operation data of the values we perform a reduction on. 6458 OperationData ReducedValueData; 6459 6460 /// Should we model this reduction as a pairwise reduction tree or a tree that 6461 /// splits the vector in halves and adds those halves. 6462 bool IsPairwiseReduction = false; 6463 6464 /// Checks if the ParentStackElem.first should be marked as a reduction 6465 /// operation with an extra argument or as extra argument itself. 6466 void markExtraArg(std::pair<Instruction *, unsigned> &ParentStackElem, 6467 Value *ExtraArg) { 6468 if (ExtraArgs.count(ParentStackElem.first)) { 6469 ExtraArgs[ParentStackElem.first] = nullptr; 6470 // We ran into something like: 6471 // ParentStackElem.first = ExtraArgs[ParentStackElem.first] + ExtraArg. 6472 // The whole ParentStackElem.first should be considered as an extra value 6473 // in this case. 6474 // Do not perform analysis of remaining operands of ParentStackElem.first 6475 // instruction, this whole instruction is an extra argument. 6476 ParentStackElem.second = ParentStackElem.first->getNumOperands(); 6477 } else { 6478 // We ran into something like: 6479 // ParentStackElem.first += ... + ExtraArg + ... 6480 ExtraArgs[ParentStackElem.first] = ExtraArg; 6481 } 6482 } 6483 6484 static OperationData getOperationData(Value *V) { 6485 if (!V) 6486 return OperationData(); 6487 6488 Value *LHS; 6489 Value *RHS; 6490 if (m_BinOp(m_Value(LHS), m_Value(RHS)).match(V)) { 6491 return OperationData(cast<BinaryOperator>(V)->getOpcode(), LHS, RHS, 6492 RK_Arithmetic); 6493 } 6494 if (auto *Select = dyn_cast<SelectInst>(V)) { 6495 // Look for a min/max pattern. 6496 if (m_UMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 6497 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMin); 6498 } else if (m_SMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 6499 return OperationData(Instruction::ICmp, LHS, RHS, RK_Min); 6500 } else if (m_OrdFMin(m_Value(LHS), m_Value(RHS)).match(Select) || 6501 m_UnordFMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 6502 return OperationData( 6503 Instruction::FCmp, LHS, RHS, RK_Min, 6504 cast<Instruction>(Select->getCondition())->hasNoNaNs()); 6505 } else if (m_UMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 6506 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMax); 6507 } else if (m_SMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 6508 return OperationData(Instruction::ICmp, LHS, RHS, RK_Max); 6509 } else if (m_OrdFMax(m_Value(LHS), m_Value(RHS)).match(Select) || 6510 m_UnordFMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 6511 return OperationData( 6512 Instruction::FCmp, LHS, RHS, RK_Max, 6513 cast<Instruction>(Select->getCondition())->hasNoNaNs()); 6514 } else { 6515 // Try harder: look for min/max pattern based on instructions producing 6516 // same values such as: select ((cmp Inst1, Inst2), Inst1, Inst2). 6517 // During the intermediate stages of SLP, it's very common to have 6518 // pattern like this (since optimizeGatherSequence is run only once 6519 // at the end): 6520 // %1 = extractelement <2 x i32> %a, i32 0 6521 // %2 = extractelement <2 x i32> %a, i32 1 6522 // %cond = icmp sgt i32 %1, %2 6523 // %3 = extractelement <2 x i32> %a, i32 0 6524 // %4 = extractelement <2 x i32> %a, i32 1 6525 // %select = select i1 %cond, i32 %3, i32 %4 6526 CmpInst::Predicate Pred; 6527 Instruction *L1; 6528 Instruction *L2; 6529 6530 LHS = Select->getTrueValue(); 6531 RHS = Select->getFalseValue(); 6532 Value *Cond = Select->getCondition(); 6533 6534 // TODO: Support inverse predicates. 6535 if (match(Cond, m_Cmp(Pred, m_Specific(LHS), m_Instruction(L2)))) { 6536 if (!isa<ExtractElementInst>(RHS) || 6537 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6538 return OperationData(V); 6539 } else if (match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Specific(RHS)))) { 6540 if (!isa<ExtractElementInst>(LHS) || 6541 !L1->isIdenticalTo(cast<Instruction>(LHS))) 6542 return OperationData(V); 6543 } else { 6544 if (!isa<ExtractElementInst>(LHS) || !isa<ExtractElementInst>(RHS)) 6545 return OperationData(V); 6546 if (!match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Instruction(L2))) || 6547 !L1->isIdenticalTo(cast<Instruction>(LHS)) || 6548 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6549 return OperationData(V); 6550 } 6551 switch (Pred) { 6552 default: 6553 return OperationData(V); 6554 6555 case CmpInst::ICMP_ULT: 6556 case CmpInst::ICMP_ULE: 6557 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMin); 6558 6559 case CmpInst::ICMP_SLT: 6560 case CmpInst::ICMP_SLE: 6561 return OperationData(Instruction::ICmp, LHS, RHS, RK_Min); 6562 6563 case CmpInst::FCMP_OLT: 6564 case CmpInst::FCMP_OLE: 6565 case CmpInst::FCMP_ULT: 6566 case CmpInst::FCMP_ULE: 6567 return OperationData(Instruction::FCmp, LHS, RHS, RK_Min, 6568 cast<Instruction>(Cond)->hasNoNaNs()); 6569 6570 case CmpInst::ICMP_UGT: 6571 case CmpInst::ICMP_UGE: 6572 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMax); 6573 6574 case CmpInst::ICMP_SGT: 6575 case CmpInst::ICMP_SGE: 6576 return OperationData(Instruction::ICmp, LHS, RHS, RK_Max); 6577 6578 case CmpInst::FCMP_OGT: 6579 case CmpInst::FCMP_OGE: 6580 case CmpInst::FCMP_UGT: 6581 case CmpInst::FCMP_UGE: 6582 return OperationData(Instruction::FCmp, LHS, RHS, RK_Max, 6583 cast<Instruction>(Cond)->hasNoNaNs()); 6584 } 6585 } 6586 } 6587 return OperationData(V); 6588 } 6589 6590 public: 6591 HorizontalReduction() = default; 6592 6593 /// Try to find a reduction tree. 6594 bool matchAssociativeReduction(PHINode *Phi, Instruction *B) { 6595 assert((!Phi || is_contained(Phi->operands(), B)) && 6596 "Thi phi needs to use the binary operator"); 6597 6598 ReductionData = getOperationData(B); 6599 6600 // We could have a initial reductions that is not an add. 6601 // r *= v1 + v2 + v3 + v4 6602 // In such a case start looking for a tree rooted in the first '+'. 6603 if (Phi) { 6604 if (ReductionData.getLHS() == Phi) { 6605 Phi = nullptr; 6606 B = dyn_cast<Instruction>(ReductionData.getRHS()); 6607 ReductionData = getOperationData(B); 6608 } else if (ReductionData.getRHS() == Phi) { 6609 Phi = nullptr; 6610 B = dyn_cast<Instruction>(ReductionData.getLHS()); 6611 ReductionData = getOperationData(B); 6612 } 6613 } 6614 6615 if (!ReductionData.isVectorizable(B)) 6616 return false; 6617 6618 Type *Ty = B->getType(); 6619 if (!isValidElementType(Ty)) 6620 return false; 6621 if (!Ty->isIntOrIntVectorTy() && !Ty->isFPOrFPVectorTy()) 6622 return false; 6623 6624 ReducedValueData.clear(); 6625 ReductionRoot = B; 6626 6627 // Post order traverse the reduction tree starting at B. We only handle true 6628 // trees containing only binary operators. 6629 SmallVector<std::pair<Instruction *, unsigned>, 32> Stack; 6630 Stack.push_back(std::make_pair(B, ReductionData.getFirstOperandIndex())); 6631 ReductionData.initReductionOps(ReductionOps); 6632 while (!Stack.empty()) { 6633 Instruction *TreeN = Stack.back().first; 6634 unsigned EdgeToVist = Stack.back().second++; 6635 OperationData OpData = getOperationData(TreeN); 6636 bool IsReducedValue = OpData != ReductionData; 6637 6638 // Postorder vist. 6639 if (IsReducedValue || EdgeToVist == OpData.getNumberOfOperands()) { 6640 if (IsReducedValue) 6641 ReducedVals.push_back(TreeN); 6642 else { 6643 auto I = ExtraArgs.find(TreeN); 6644 if (I != ExtraArgs.end() && !I->second) { 6645 // Check if TreeN is an extra argument of its parent operation. 6646 if (Stack.size() <= 1) { 6647 // TreeN can't be an extra argument as it is a root reduction 6648 // operation. 6649 return false; 6650 } 6651 // Yes, TreeN is an extra argument, do not add it to a list of 6652 // reduction operations. 6653 // Stack[Stack.size() - 2] always points to the parent operation. 6654 markExtraArg(Stack[Stack.size() - 2], TreeN); 6655 ExtraArgs.erase(TreeN); 6656 } else 6657 ReductionData.addReductionOps(TreeN, ReductionOps); 6658 } 6659 // Retract. 6660 Stack.pop_back(); 6661 continue; 6662 } 6663 6664 // Visit left or right. 6665 Value *NextV = TreeN->getOperand(EdgeToVist); 6666 if (NextV != Phi) { 6667 auto *I = dyn_cast<Instruction>(NextV); 6668 OpData = getOperationData(I); 6669 // Continue analysis if the next operand is a reduction operation or 6670 // (possibly) a reduced value. If the reduced value opcode is not set, 6671 // the first met operation != reduction operation is considered as the 6672 // reduced value class. 6673 if (I && (!ReducedValueData || OpData == ReducedValueData || 6674 OpData == ReductionData)) { 6675 const bool IsReductionOperation = OpData == ReductionData; 6676 // Only handle trees in the current basic block. 6677 if (!ReductionData.hasSameParent(I, B->getParent(), 6678 IsReductionOperation)) { 6679 // I is an extra argument for TreeN (its parent operation). 6680 markExtraArg(Stack.back(), I); 6681 continue; 6682 } 6683 6684 // Each tree node needs to have minimal number of users except for the 6685 // ultimate reduction. 6686 if (!ReductionData.hasRequiredNumberOfUses(I, 6687 OpData == ReductionData) && 6688 I != B) { 6689 // I is an extra argument for TreeN (its parent operation). 6690 markExtraArg(Stack.back(), I); 6691 continue; 6692 } 6693 6694 if (IsReductionOperation) { 6695 // We need to be able to reassociate the reduction operations. 6696 if (!OpData.isAssociative(I)) { 6697 // I is an extra argument for TreeN (its parent operation). 6698 markExtraArg(Stack.back(), I); 6699 continue; 6700 } 6701 } else if (ReducedValueData && 6702 ReducedValueData != OpData) { 6703 // Make sure that the opcodes of the operations that we are going to 6704 // reduce match. 6705 // I is an extra argument for TreeN (its parent operation). 6706 markExtraArg(Stack.back(), I); 6707 continue; 6708 } else if (!ReducedValueData) 6709 ReducedValueData = OpData; 6710 6711 Stack.push_back(std::make_pair(I, OpData.getFirstOperandIndex())); 6712 continue; 6713 } 6714 } 6715 // NextV is an extra argument for TreeN (its parent operation). 6716 markExtraArg(Stack.back(), NextV); 6717 } 6718 return true; 6719 } 6720 6721 /// Attempt to vectorize the tree found by 6722 /// matchAssociativeReduction. 6723 bool tryToReduce(BoUpSLP &V, TargetTransformInfo *TTI) { 6724 if (ReducedVals.empty()) 6725 return false; 6726 6727 // If there is a sufficient number of reduction values, reduce 6728 // to a nearby power-of-2. Can safely generate oversized 6729 // vectors and rely on the backend to split them to legal sizes. 6730 unsigned NumReducedVals = ReducedVals.size(); 6731 if (NumReducedVals < 4) 6732 return false; 6733 6734 unsigned ReduxWidth = PowerOf2Floor(NumReducedVals); 6735 6736 Value *VectorizedTree = nullptr; 6737 6738 // FIXME: Fast-math-flags should be set based on the instructions in the 6739 // reduction (not all of 'fast' are required). 6740 IRBuilder<> Builder(cast<Instruction>(ReductionRoot)); 6741 FastMathFlags Unsafe; 6742 Unsafe.setFast(); 6743 Builder.setFastMathFlags(Unsafe); 6744 unsigned i = 0; 6745 6746 BoUpSLP::ExtraValueToDebugLocsMap ExternallyUsedValues; 6747 // The same extra argument may be used several time, so log each attempt 6748 // to use it. 6749 for (auto &Pair : ExtraArgs) { 6750 assert(Pair.first && "DebugLoc must be set."); 6751 ExternallyUsedValues[Pair.second].push_back(Pair.first); 6752 } 6753 6754 // The compare instruction of a min/max is the insertion point for new 6755 // instructions and may be replaced with a new compare instruction. 6756 auto getCmpForMinMaxReduction = [](Instruction *RdxRootInst) { 6757 assert(isa<SelectInst>(RdxRootInst) && 6758 "Expected min/max reduction to have select root instruction"); 6759 Value *ScalarCond = cast<SelectInst>(RdxRootInst)->getCondition(); 6760 assert(isa<Instruction>(ScalarCond) && 6761 "Expected min/max reduction to have compare condition"); 6762 return cast<Instruction>(ScalarCond); 6763 }; 6764 6765 // The reduction root is used as the insertion point for new instructions, 6766 // so set it as externally used to prevent it from being deleted. 6767 ExternallyUsedValues[ReductionRoot]; 6768 SmallVector<Value *, 16> IgnoreList; 6769 for (auto &V : ReductionOps) 6770 IgnoreList.append(V.begin(), V.end()); 6771 while (i < NumReducedVals - ReduxWidth + 1 && ReduxWidth > 2) { 6772 auto VL = makeArrayRef(&ReducedVals[i], ReduxWidth); 6773 V.buildTree(VL, ExternallyUsedValues, IgnoreList); 6774 Optional<ArrayRef<unsigned>> Order = V.bestOrder(); 6775 // TODO: Handle orders of size less than number of elements in the vector. 6776 if (Order && Order->size() == VL.size()) { 6777 // TODO: reorder tree nodes without tree rebuilding. 6778 SmallVector<Value *, 4> ReorderedOps(VL.size()); 6779 llvm::transform(*Order, ReorderedOps.begin(), 6780 [VL](const unsigned Idx) { return VL[Idx]; }); 6781 V.buildTree(ReorderedOps, ExternallyUsedValues, IgnoreList); 6782 } 6783 if (V.isTreeTinyAndNotFullyVectorizable()) 6784 break; 6785 if (V.isLoadCombineReductionCandidate(ReductionData.getOpcode())) 6786 break; 6787 6788 V.computeMinimumValueSizes(); 6789 6790 // Estimate cost. 6791 int TreeCost = V.getTreeCost(); 6792 int ReductionCost = getReductionCost(TTI, ReducedVals[i], ReduxWidth); 6793 int Cost = TreeCost + ReductionCost; 6794 if (Cost >= -SLPCostThreshold) { 6795 V.getORE()->emit([&]() { 6796 return OptimizationRemarkMissed( 6797 SV_NAME, "HorSLPNotBeneficial", cast<Instruction>(VL[0])) 6798 << "Vectorizing horizontal reduction is possible" 6799 << "but not beneficial with cost " 6800 << ore::NV("Cost", Cost) << " and threshold " 6801 << ore::NV("Threshold", -SLPCostThreshold); 6802 }); 6803 break; 6804 } 6805 6806 LLVM_DEBUG(dbgs() << "SLP: Vectorizing horizontal reduction at cost:" 6807 << Cost << ". (HorRdx)\n"); 6808 V.getORE()->emit([&]() { 6809 return OptimizationRemark( 6810 SV_NAME, "VectorizedHorizontalReduction", cast<Instruction>(VL[0])) 6811 << "Vectorized horizontal reduction with cost " 6812 << ore::NV("Cost", Cost) << " and with tree size " 6813 << ore::NV("TreeSize", V.getTreeSize()); 6814 }); 6815 6816 // Vectorize a tree. 6817 DebugLoc Loc = cast<Instruction>(ReducedVals[i])->getDebugLoc(); 6818 Value *VectorizedRoot = V.vectorizeTree(ExternallyUsedValues); 6819 6820 // Emit a reduction. For min/max, the root is a select, but the insertion 6821 // point is the compare condition of that select. 6822 Instruction *RdxRootInst = cast<Instruction>(ReductionRoot); 6823 if (ReductionData.isMinMax()) 6824 Builder.SetInsertPoint(getCmpForMinMaxReduction(RdxRootInst)); 6825 else 6826 Builder.SetInsertPoint(RdxRootInst); 6827 6828 Value *ReducedSubTree = 6829 emitReduction(VectorizedRoot, Builder, ReduxWidth, TTI); 6830 if (VectorizedTree) { 6831 Builder.SetCurrentDebugLocation(Loc); 6832 OperationData VectReductionData(ReductionData.getOpcode(), 6833 VectorizedTree, ReducedSubTree, 6834 ReductionData.getKind()); 6835 VectorizedTree = 6836 VectReductionData.createOp(Builder, "op.rdx", ReductionOps); 6837 } else 6838 VectorizedTree = ReducedSubTree; 6839 i += ReduxWidth; 6840 ReduxWidth = PowerOf2Floor(NumReducedVals - i); 6841 } 6842 6843 if (VectorizedTree) { 6844 // Finish the reduction. 6845 for (; i < NumReducedVals; ++i) { 6846 auto *I = cast<Instruction>(ReducedVals[i]); 6847 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 6848 OperationData VectReductionData(ReductionData.getOpcode(), 6849 VectorizedTree, I, 6850 ReductionData.getKind()); 6851 VectorizedTree = VectReductionData.createOp(Builder, "", ReductionOps); 6852 } 6853 for (auto &Pair : ExternallyUsedValues) { 6854 // Add each externally used value to the final reduction. 6855 for (auto *I : Pair.second) { 6856 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 6857 OperationData VectReductionData(ReductionData.getOpcode(), 6858 VectorizedTree, Pair.first, 6859 ReductionData.getKind()); 6860 VectorizedTree = VectReductionData.createOp(Builder, "op.extra", I); 6861 } 6862 } 6863 6864 // Update users. For a min/max reduction that ends with a compare and 6865 // select, we also have to RAUW for the compare instruction feeding the 6866 // reduction root. That's because the original compare may have extra uses 6867 // besides the final select of the reduction. 6868 if (ReductionData.isMinMax()) { 6869 if (auto *VecSelect = dyn_cast<SelectInst>(VectorizedTree)) { 6870 Instruction *ScalarCmp = 6871 getCmpForMinMaxReduction(cast<Instruction>(ReductionRoot)); 6872 ScalarCmp->replaceAllUsesWith(VecSelect->getCondition()); 6873 } 6874 } 6875 ReductionRoot->replaceAllUsesWith(VectorizedTree); 6876 6877 // Mark all scalar reduction ops for deletion, they are replaced by the 6878 // vector reductions. 6879 V.eraseInstructions(IgnoreList); 6880 } 6881 return VectorizedTree != nullptr; 6882 } 6883 6884 unsigned numReductionValues() const { 6885 return ReducedVals.size(); 6886 } 6887 6888 private: 6889 /// Calculate the cost of a reduction. 6890 int getReductionCost(TargetTransformInfo *TTI, Value *FirstReducedVal, 6891 unsigned ReduxWidth) { 6892 Type *ScalarTy = FirstReducedVal->getType(); 6893 Type *VecTy = VectorType::get(ScalarTy, ReduxWidth); 6894 6895 int PairwiseRdxCost; 6896 int SplittingRdxCost; 6897 switch (ReductionData.getKind()) { 6898 case RK_Arithmetic: 6899 PairwiseRdxCost = 6900 TTI->getArithmeticReductionCost(ReductionData.getOpcode(), VecTy, 6901 /*IsPairwiseForm=*/true); 6902 SplittingRdxCost = 6903 TTI->getArithmeticReductionCost(ReductionData.getOpcode(), VecTy, 6904 /*IsPairwiseForm=*/false); 6905 break; 6906 case RK_Min: 6907 case RK_Max: 6908 case RK_UMin: 6909 case RK_UMax: { 6910 Type *VecCondTy = CmpInst::makeCmpResultType(VecTy); 6911 bool IsUnsigned = ReductionData.getKind() == RK_UMin || 6912 ReductionData.getKind() == RK_UMax; 6913 PairwiseRdxCost = 6914 TTI->getMinMaxReductionCost(VecTy, VecCondTy, 6915 /*IsPairwiseForm=*/true, IsUnsigned); 6916 SplittingRdxCost = 6917 TTI->getMinMaxReductionCost(VecTy, VecCondTy, 6918 /*IsPairwiseForm=*/false, IsUnsigned); 6919 break; 6920 } 6921 case RK_None: 6922 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 6923 } 6924 6925 IsPairwiseReduction = PairwiseRdxCost < SplittingRdxCost; 6926 int VecReduxCost = IsPairwiseReduction ? PairwiseRdxCost : SplittingRdxCost; 6927 6928 int ScalarReduxCost = 0; 6929 switch (ReductionData.getKind()) { 6930 case RK_Arithmetic: 6931 ScalarReduxCost = 6932 TTI->getArithmeticInstrCost(ReductionData.getOpcode(), ScalarTy); 6933 break; 6934 case RK_Min: 6935 case RK_Max: 6936 case RK_UMin: 6937 case RK_UMax: 6938 ScalarReduxCost = 6939 TTI->getCmpSelInstrCost(ReductionData.getOpcode(), ScalarTy) + 6940 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 6941 CmpInst::makeCmpResultType(ScalarTy)); 6942 break; 6943 case RK_None: 6944 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 6945 } 6946 ScalarReduxCost *= (ReduxWidth - 1); 6947 6948 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << VecReduxCost - ScalarReduxCost 6949 << " for reduction that starts with " << *FirstReducedVal 6950 << " (It is a " 6951 << (IsPairwiseReduction ? "pairwise" : "splitting") 6952 << " reduction)\n"); 6953 6954 return VecReduxCost - ScalarReduxCost; 6955 } 6956 6957 /// Emit a horizontal reduction of the vectorized value. 6958 Value *emitReduction(Value *VectorizedValue, IRBuilder<> &Builder, 6959 unsigned ReduxWidth, const TargetTransformInfo *TTI) { 6960 assert(VectorizedValue && "Need to have a vectorized tree node"); 6961 assert(isPowerOf2_32(ReduxWidth) && 6962 "We only handle power-of-two reductions for now"); 6963 6964 if (!IsPairwiseReduction) { 6965 // FIXME: The builder should use an FMF guard. It should not be hard-coded 6966 // to 'fast'. 6967 assert(Builder.getFastMathFlags().isFast() && "Expected 'fast' FMF"); 6968 return createSimpleTargetReduction( 6969 Builder, TTI, ReductionData.getOpcode(), VectorizedValue, 6970 ReductionData.getFlags(), ReductionOps.back()); 6971 } 6972 6973 Value *TmpVec = VectorizedValue; 6974 for (unsigned i = ReduxWidth / 2; i != 0; i >>= 1) { 6975 auto LeftMask = createRdxShuffleMask(ReduxWidth, i, true, true); 6976 auto RightMask = createRdxShuffleMask(ReduxWidth, i, true, false); 6977 6978 Value *LeftShuf = Builder.CreateShuffleVector( 6979 TmpVec, UndefValue::get(TmpVec->getType()), LeftMask, "rdx.shuf.l"); 6980 Value *RightShuf = Builder.CreateShuffleVector( 6981 TmpVec, UndefValue::get(TmpVec->getType()), (RightMask), 6982 "rdx.shuf.r"); 6983 OperationData VectReductionData(ReductionData.getOpcode(), LeftShuf, 6984 RightShuf, ReductionData.getKind()); 6985 TmpVec = VectReductionData.createOp(Builder, "op.rdx", ReductionOps); 6986 } 6987 6988 // The result is in the first element of the vector. 6989 return Builder.CreateExtractElement(TmpVec, Builder.getInt32(0)); 6990 } 6991 }; 6992 6993 } // end anonymous namespace 6994 6995 /// Recognize construction of vectors like 6996 /// %ra = insertelement <4 x float> undef, float %s0, i32 0 6997 /// %rb = insertelement <4 x float> %ra, float %s1, i32 1 6998 /// %rc = insertelement <4 x float> %rb, float %s2, i32 2 6999 /// %rd = insertelement <4 x float> %rc, float %s3, i32 3 7000 /// starting from the last insertelement or insertvalue instruction. 7001 /// 7002 /// Also recognize aggregates like {<2 x float>, <2 x float>}, 7003 /// {{float, float}, {float, float}}, [2 x {float, float}] and so on. 7004 /// See llvm/test/Transforms/SLPVectorizer/X86/pr42022.ll for examples. 7005 /// 7006 /// Assume LastInsertInst is of InsertElementInst or InsertValueInst type. 7007 /// 7008 /// \return true if it matches. 7009 static bool findBuildAggregate(Value *LastInsertInst, TargetTransformInfo *TTI, 7010 SmallVectorImpl<Value *> &BuildVectorOpds, 7011 int &UserCost) { 7012 assert((isa<InsertElementInst>(LastInsertInst) || 7013 isa<InsertValueInst>(LastInsertInst)) && 7014 "Expected insertelement or insertvalue instruction!"); 7015 UserCost = 0; 7016 do { 7017 Value *InsertedOperand; 7018 if (auto *IE = dyn_cast<InsertElementInst>(LastInsertInst)) { 7019 InsertedOperand = IE->getOperand(1); 7020 LastInsertInst = IE->getOperand(0); 7021 if (auto *CI = dyn_cast<ConstantInt>(IE->getOperand(2))) { 7022 UserCost += TTI->getVectorInstrCost(Instruction::InsertElement, 7023 IE->getType(), CI->getZExtValue()); 7024 } 7025 } else { 7026 auto *IV = cast<InsertValueInst>(LastInsertInst); 7027 InsertedOperand = IV->getInsertedValueOperand(); 7028 LastInsertInst = IV->getAggregateOperand(); 7029 } 7030 if (isa<InsertElementInst>(InsertedOperand) || 7031 isa<InsertValueInst>(InsertedOperand)) { 7032 int TmpUserCost; 7033 SmallVector<Value *, 8> TmpBuildVectorOpds; 7034 if (!findBuildAggregate(InsertedOperand, TTI, TmpBuildVectorOpds, 7035 TmpUserCost)) 7036 return false; 7037 BuildVectorOpds.append(TmpBuildVectorOpds.rbegin(), 7038 TmpBuildVectorOpds.rend()); 7039 UserCost += TmpUserCost; 7040 } else { 7041 BuildVectorOpds.push_back(InsertedOperand); 7042 } 7043 if (isa<UndefValue>(LastInsertInst)) 7044 break; 7045 if ((!isa<InsertValueInst>(LastInsertInst) && 7046 !isa<InsertElementInst>(LastInsertInst)) || 7047 !LastInsertInst->hasOneUse()) 7048 return false; 7049 } while (true); 7050 std::reverse(BuildVectorOpds.begin(), BuildVectorOpds.end()); 7051 return true; 7052 } 7053 7054 static bool PhiTypeSorterFunc(Value *V, Value *V2) { 7055 return V->getType() < V2->getType(); 7056 } 7057 7058 /// Try and get a reduction value from a phi node. 7059 /// 7060 /// Given a phi node \p P in a block \p ParentBB, consider possible reductions 7061 /// if they come from either \p ParentBB or a containing loop latch. 7062 /// 7063 /// \returns A candidate reduction value if possible, or \code nullptr \endcode 7064 /// if not possible. 7065 static Value *getReductionValue(const DominatorTree *DT, PHINode *P, 7066 BasicBlock *ParentBB, LoopInfo *LI) { 7067 // There are situations where the reduction value is not dominated by the 7068 // reduction phi. Vectorizing such cases has been reported to cause 7069 // miscompiles. See PR25787. 7070 auto DominatedReduxValue = [&](Value *R) { 7071 return isa<Instruction>(R) && 7072 DT->dominates(P->getParent(), cast<Instruction>(R)->getParent()); 7073 }; 7074 7075 Value *Rdx = nullptr; 7076 7077 // Return the incoming value if it comes from the same BB as the phi node. 7078 if (P->getIncomingBlock(0) == ParentBB) { 7079 Rdx = P->getIncomingValue(0); 7080 } else if (P->getIncomingBlock(1) == ParentBB) { 7081 Rdx = P->getIncomingValue(1); 7082 } 7083 7084 if (Rdx && DominatedReduxValue(Rdx)) 7085 return Rdx; 7086 7087 // Otherwise, check whether we have a loop latch to look at. 7088 Loop *BBL = LI->getLoopFor(ParentBB); 7089 if (!BBL) 7090 return nullptr; 7091 BasicBlock *BBLatch = BBL->getLoopLatch(); 7092 if (!BBLatch) 7093 return nullptr; 7094 7095 // There is a loop latch, return the incoming value if it comes from 7096 // that. This reduction pattern occasionally turns up. 7097 if (P->getIncomingBlock(0) == BBLatch) { 7098 Rdx = P->getIncomingValue(0); 7099 } else if (P->getIncomingBlock(1) == BBLatch) { 7100 Rdx = P->getIncomingValue(1); 7101 } 7102 7103 if (Rdx && DominatedReduxValue(Rdx)) 7104 return Rdx; 7105 7106 return nullptr; 7107 } 7108 7109 /// Attempt to reduce a horizontal reduction. 7110 /// If it is legal to match a horizontal reduction feeding the phi node \a P 7111 /// with reduction operators \a Root (or one of its operands) in a basic block 7112 /// \a BB, then check if it can be done. If horizontal reduction is not found 7113 /// and root instruction is a binary operation, vectorization of the operands is 7114 /// attempted. 7115 /// \returns true if a horizontal reduction was matched and reduced or operands 7116 /// of one of the binary instruction were vectorized. 7117 /// \returns false if a horizontal reduction was not matched (or not possible) 7118 /// or no vectorization of any binary operation feeding \a Root instruction was 7119 /// performed. 7120 static bool tryToVectorizeHorReductionOrInstOperands( 7121 PHINode *P, Instruction *Root, BasicBlock *BB, BoUpSLP &R, 7122 TargetTransformInfo *TTI, 7123 const function_ref<bool(Instruction *, BoUpSLP &)> Vectorize) { 7124 if (!ShouldVectorizeHor) 7125 return false; 7126 7127 if (!Root) 7128 return false; 7129 7130 if (Root->getParent() != BB || isa<PHINode>(Root)) 7131 return false; 7132 // Start analysis starting from Root instruction. If horizontal reduction is 7133 // found, try to vectorize it. If it is not a horizontal reduction or 7134 // vectorization is not possible or not effective, and currently analyzed 7135 // instruction is a binary operation, try to vectorize the operands, using 7136 // pre-order DFS traversal order. If the operands were not vectorized, repeat 7137 // the same procedure considering each operand as a possible root of the 7138 // horizontal reduction. 7139 // Interrupt the process if the Root instruction itself was vectorized or all 7140 // sub-trees not higher that RecursionMaxDepth were analyzed/vectorized. 7141 SmallVector<std::pair<Instruction *, unsigned>, 8> Stack(1, {Root, 0}); 7142 SmallPtrSet<Value *, 8> VisitedInstrs; 7143 bool Res = false; 7144 while (!Stack.empty()) { 7145 Instruction *Inst; 7146 unsigned Level; 7147 std::tie(Inst, Level) = Stack.pop_back_val(); 7148 auto *BI = dyn_cast<BinaryOperator>(Inst); 7149 auto *SI = dyn_cast<SelectInst>(Inst); 7150 if (BI || SI) { 7151 HorizontalReduction HorRdx; 7152 if (HorRdx.matchAssociativeReduction(P, Inst)) { 7153 if (HorRdx.tryToReduce(R, TTI)) { 7154 Res = true; 7155 // Set P to nullptr to avoid re-analysis of phi node in 7156 // matchAssociativeReduction function unless this is the root node. 7157 P = nullptr; 7158 continue; 7159 } 7160 } 7161 if (P && BI) { 7162 Inst = dyn_cast<Instruction>(BI->getOperand(0)); 7163 if (Inst == P) 7164 Inst = dyn_cast<Instruction>(BI->getOperand(1)); 7165 if (!Inst) { 7166 // Set P to nullptr to avoid re-analysis of phi node in 7167 // matchAssociativeReduction function unless this is the root node. 7168 P = nullptr; 7169 continue; 7170 } 7171 } 7172 } 7173 // Set P to nullptr to avoid re-analysis of phi node in 7174 // matchAssociativeReduction function unless this is the root node. 7175 P = nullptr; 7176 if (Vectorize(Inst, R)) { 7177 Res = true; 7178 continue; 7179 } 7180 7181 // Try to vectorize operands. 7182 // Continue analysis for the instruction from the same basic block only to 7183 // save compile time. 7184 if (++Level < RecursionMaxDepth) 7185 for (auto *Op : Inst->operand_values()) 7186 if (VisitedInstrs.insert(Op).second) 7187 if (auto *I = dyn_cast<Instruction>(Op)) 7188 if (!isa<PHINode>(I) && !R.isDeleted(I) && I->getParent() == BB) 7189 Stack.emplace_back(I, Level); 7190 } 7191 return Res; 7192 } 7193 7194 bool SLPVectorizerPass::vectorizeRootInstruction(PHINode *P, Value *V, 7195 BasicBlock *BB, BoUpSLP &R, 7196 TargetTransformInfo *TTI) { 7197 if (!V) 7198 return false; 7199 auto *I = dyn_cast<Instruction>(V); 7200 if (!I) 7201 return false; 7202 7203 if (!isa<BinaryOperator>(I)) 7204 P = nullptr; 7205 // Try to match and vectorize a horizontal reduction. 7206 auto &&ExtraVectorization = [this](Instruction *I, BoUpSLP &R) -> bool { 7207 return tryToVectorize(I, R); 7208 }; 7209 return tryToVectorizeHorReductionOrInstOperands(P, I, BB, R, TTI, 7210 ExtraVectorization); 7211 } 7212 7213 bool SLPVectorizerPass::vectorizeInsertValueInst(InsertValueInst *IVI, 7214 BasicBlock *BB, BoUpSLP &R) { 7215 int UserCost = 0; 7216 const DataLayout &DL = BB->getModule()->getDataLayout(); 7217 if (!R.canMapToVector(IVI->getType(), DL)) 7218 return false; 7219 7220 SmallVector<Value *, 16> BuildVectorOpds; 7221 if (!findBuildAggregate(IVI, TTI, BuildVectorOpds, UserCost)) 7222 return false; 7223 7224 LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IVI << "\n"); 7225 // Aggregate value is unlikely to be processed in vector register, we need to 7226 // extract scalars into scalar registers, so NeedExtraction is set true. 7227 return tryToVectorizeList(BuildVectorOpds, R, UserCost); 7228 } 7229 7230 bool SLPVectorizerPass::vectorizeInsertElementInst(InsertElementInst *IEI, 7231 BasicBlock *BB, BoUpSLP &R) { 7232 int UserCost; 7233 SmallVector<Value *, 16> BuildVectorOpds; 7234 if (!findBuildAggregate(IEI, TTI, BuildVectorOpds, UserCost) || 7235 (llvm::all_of(BuildVectorOpds, 7236 [](Value *V) { return isa<ExtractElementInst>(V); }) && 7237 isShuffle(BuildVectorOpds))) 7238 return false; 7239 7240 // Vectorize starting with the build vector operands ignoring the BuildVector 7241 // instructions for the purpose of scheduling and user extraction. 7242 return tryToVectorizeList(BuildVectorOpds, R, UserCost); 7243 } 7244 7245 bool SLPVectorizerPass::vectorizeCmpInst(CmpInst *CI, BasicBlock *BB, 7246 BoUpSLP &R) { 7247 if (tryToVectorizePair(CI->getOperand(0), CI->getOperand(1), R)) 7248 return true; 7249 7250 bool OpsChanged = false; 7251 for (int Idx = 0; Idx < 2; ++Idx) { 7252 OpsChanged |= 7253 vectorizeRootInstruction(nullptr, CI->getOperand(Idx), BB, R, TTI); 7254 } 7255 return OpsChanged; 7256 } 7257 7258 bool SLPVectorizerPass::vectorizeSimpleInstructions( 7259 SmallVectorImpl<Instruction *> &Instructions, BasicBlock *BB, BoUpSLP &R) { 7260 bool OpsChanged = false; 7261 for (auto *I : reverse(Instructions)) { 7262 if (R.isDeleted(I)) 7263 continue; 7264 if (auto *LastInsertValue = dyn_cast<InsertValueInst>(I)) 7265 OpsChanged |= vectorizeInsertValueInst(LastInsertValue, BB, R); 7266 else if (auto *LastInsertElem = dyn_cast<InsertElementInst>(I)) 7267 OpsChanged |= vectorizeInsertElementInst(LastInsertElem, BB, R); 7268 else if (auto *CI = dyn_cast<CmpInst>(I)) 7269 OpsChanged |= vectorizeCmpInst(CI, BB, R); 7270 } 7271 Instructions.clear(); 7272 return OpsChanged; 7273 } 7274 7275 bool SLPVectorizerPass::vectorizeChainsInBlock(BasicBlock *BB, BoUpSLP &R) { 7276 bool Changed = false; 7277 SmallVector<Value *, 4> Incoming; 7278 SmallPtrSet<Value *, 16> VisitedInstrs; 7279 7280 bool HaveVectorizedPhiNodes = true; 7281 while (HaveVectorizedPhiNodes) { 7282 HaveVectorizedPhiNodes = false; 7283 7284 // Collect the incoming values from the PHIs. 7285 Incoming.clear(); 7286 for (Instruction &I : *BB) { 7287 PHINode *P = dyn_cast<PHINode>(&I); 7288 if (!P) 7289 break; 7290 7291 if (!VisitedInstrs.count(P) && !R.isDeleted(P)) 7292 Incoming.push_back(P); 7293 } 7294 7295 // Sort by type. 7296 llvm::stable_sort(Incoming, PhiTypeSorterFunc); 7297 7298 // Try to vectorize elements base on their type. 7299 for (SmallVector<Value *, 4>::iterator IncIt = Incoming.begin(), 7300 E = Incoming.end(); 7301 IncIt != E;) { 7302 7303 // Look for the next elements with the same type. 7304 SmallVector<Value *, 4>::iterator SameTypeIt = IncIt; 7305 while (SameTypeIt != E && 7306 (*SameTypeIt)->getType() == (*IncIt)->getType()) { 7307 VisitedInstrs.insert(*SameTypeIt); 7308 ++SameTypeIt; 7309 } 7310 7311 // Try to vectorize them. 7312 unsigned NumElts = (SameTypeIt - IncIt); 7313 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize starting at PHIs (" 7314 << NumElts << ")\n"); 7315 // The order in which the phi nodes appear in the program does not matter. 7316 // So allow tryToVectorizeList to reorder them if it is beneficial. This 7317 // is done when there are exactly two elements since tryToVectorizeList 7318 // asserts that there are only two values when AllowReorder is true. 7319 bool AllowReorder = NumElts == 2; 7320 if (NumElts > 1 && tryToVectorizeList(makeArrayRef(IncIt, NumElts), R, 7321 /*UserCost=*/0, AllowReorder)) { 7322 // Success start over because instructions might have been changed. 7323 HaveVectorizedPhiNodes = true; 7324 Changed = true; 7325 break; 7326 } 7327 7328 // Start over at the next instruction of a different type (or the end). 7329 IncIt = SameTypeIt; 7330 } 7331 } 7332 7333 VisitedInstrs.clear(); 7334 7335 SmallVector<Instruction *, 8> PostProcessInstructions; 7336 SmallDenseSet<Instruction *, 4> KeyNodes; 7337 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 7338 // Skip instructions marked for the deletion. 7339 if (R.isDeleted(&*it)) 7340 continue; 7341 // We may go through BB multiple times so skip the one we have checked. 7342 if (!VisitedInstrs.insert(&*it).second) { 7343 if (it->use_empty() && KeyNodes.count(&*it) > 0 && 7344 vectorizeSimpleInstructions(PostProcessInstructions, BB, R)) { 7345 // We would like to start over since some instructions are deleted 7346 // and the iterator may become invalid value. 7347 Changed = true; 7348 it = BB->begin(); 7349 e = BB->end(); 7350 } 7351 continue; 7352 } 7353 7354 if (isa<DbgInfoIntrinsic>(it)) 7355 continue; 7356 7357 // Try to vectorize reductions that use PHINodes. 7358 if (PHINode *P = dyn_cast<PHINode>(it)) { 7359 // Check that the PHI is a reduction PHI. 7360 if (P->getNumIncomingValues() != 2) 7361 return Changed; 7362 7363 // Try to match and vectorize a horizontal reduction. 7364 if (vectorizeRootInstruction(P, getReductionValue(DT, P, BB, LI), BB, R, 7365 TTI)) { 7366 Changed = true; 7367 it = BB->begin(); 7368 e = BB->end(); 7369 continue; 7370 } 7371 continue; 7372 } 7373 7374 // Ran into an instruction without users, like terminator, or function call 7375 // with ignored return value, store. Ignore unused instructions (basing on 7376 // instruction type, except for CallInst and InvokeInst). 7377 if (it->use_empty() && (it->getType()->isVoidTy() || isa<CallInst>(it) || 7378 isa<InvokeInst>(it))) { 7379 KeyNodes.insert(&*it); 7380 bool OpsChanged = false; 7381 if (ShouldStartVectorizeHorAtStore || !isa<StoreInst>(it)) { 7382 for (auto *V : it->operand_values()) { 7383 // Try to match and vectorize a horizontal reduction. 7384 OpsChanged |= vectorizeRootInstruction(nullptr, V, BB, R, TTI); 7385 } 7386 } 7387 // Start vectorization of post-process list of instructions from the 7388 // top-tree instructions to try to vectorize as many instructions as 7389 // possible. 7390 OpsChanged |= vectorizeSimpleInstructions(PostProcessInstructions, BB, R); 7391 if (OpsChanged) { 7392 // We would like to start over since some instructions are deleted 7393 // and the iterator may become invalid value. 7394 Changed = true; 7395 it = BB->begin(); 7396 e = BB->end(); 7397 continue; 7398 } 7399 } 7400 7401 if (isa<InsertElementInst>(it) || isa<CmpInst>(it) || 7402 isa<InsertValueInst>(it)) 7403 PostProcessInstructions.push_back(&*it); 7404 } 7405 7406 return Changed; 7407 } 7408 7409 bool SLPVectorizerPass::vectorizeGEPIndices(BasicBlock *BB, BoUpSLP &R) { 7410 auto Changed = false; 7411 for (auto &Entry : GEPs) { 7412 // If the getelementptr list has fewer than two elements, there's nothing 7413 // to do. 7414 if (Entry.second.size() < 2) 7415 continue; 7416 7417 LLVM_DEBUG(dbgs() << "SLP: Analyzing a getelementptr list of length " 7418 << Entry.second.size() << ".\n"); 7419 7420 // Process the GEP list in chunks suitable for the target's supported 7421 // vector size. If a vector register can't hold 1 element, we are done. 7422 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 7423 unsigned EltSize = R.getVectorElementSize(Entry.second[0]); 7424 if (MaxVecRegSize < EltSize) 7425 continue; 7426 7427 unsigned MaxElts = MaxVecRegSize / EltSize; 7428 for (unsigned BI = 0, BE = Entry.second.size(); BI < BE; BI += MaxElts) { 7429 auto Len = std::min<unsigned>(BE - BI, MaxElts); 7430 auto GEPList = makeArrayRef(&Entry.second[BI], Len); 7431 7432 // Initialize a set a candidate getelementptrs. Note that we use a 7433 // SetVector here to preserve program order. If the index computations 7434 // are vectorizable and begin with loads, we want to minimize the chance 7435 // of having to reorder them later. 7436 SetVector<Value *> Candidates(GEPList.begin(), GEPList.end()); 7437 7438 // Some of the candidates may have already been vectorized after we 7439 // initially collected them. If so, they are marked as deleted, so remove 7440 // them from the set of candidates. 7441 Candidates.remove_if( 7442 [&R](Value *I) { return R.isDeleted(cast<Instruction>(I)); }); 7443 7444 // Remove from the set of candidates all pairs of getelementptrs with 7445 // constant differences. Such getelementptrs are likely not good 7446 // candidates for vectorization in a bottom-up phase since one can be 7447 // computed from the other. We also ensure all candidate getelementptr 7448 // indices are unique. 7449 for (int I = 0, E = GEPList.size(); I < E && Candidates.size() > 1; ++I) { 7450 auto *GEPI = GEPList[I]; 7451 if (!Candidates.count(GEPI)) 7452 continue; 7453 auto *SCEVI = SE->getSCEV(GEPList[I]); 7454 for (int J = I + 1; J < E && Candidates.size() > 1; ++J) { 7455 auto *GEPJ = GEPList[J]; 7456 auto *SCEVJ = SE->getSCEV(GEPList[J]); 7457 if (isa<SCEVConstant>(SE->getMinusSCEV(SCEVI, SCEVJ))) { 7458 Candidates.remove(GEPI); 7459 Candidates.remove(GEPJ); 7460 } else if (GEPI->idx_begin()->get() == GEPJ->idx_begin()->get()) { 7461 Candidates.remove(GEPJ); 7462 } 7463 } 7464 } 7465 7466 // We break out of the above computation as soon as we know there are 7467 // fewer than two candidates remaining. 7468 if (Candidates.size() < 2) 7469 continue; 7470 7471 // Add the single, non-constant index of each candidate to the bundle. We 7472 // ensured the indices met these constraints when we originally collected 7473 // the getelementptrs. 7474 SmallVector<Value *, 16> Bundle(Candidates.size()); 7475 auto BundleIndex = 0u; 7476 for (auto *V : Candidates) { 7477 auto *GEP = cast<GetElementPtrInst>(V); 7478 auto *GEPIdx = GEP->idx_begin()->get(); 7479 assert(GEP->getNumIndices() == 1 || !isa<Constant>(GEPIdx)); 7480 Bundle[BundleIndex++] = GEPIdx; 7481 } 7482 7483 // Try and vectorize the indices. We are currently only interested in 7484 // gather-like cases of the form: 7485 // 7486 // ... = g[a[0] - b[0]] + g[a[1] - b[1]] + ... 7487 // 7488 // where the loads of "a", the loads of "b", and the subtractions can be 7489 // performed in parallel. It's likely that detecting this pattern in a 7490 // bottom-up phase will be simpler and less costly than building a 7491 // full-blown top-down phase beginning at the consecutive loads. 7492 Changed |= tryToVectorizeList(Bundle, R); 7493 } 7494 } 7495 return Changed; 7496 } 7497 7498 bool SLPVectorizerPass::vectorizeStoreChains(BoUpSLP &R) { 7499 bool Changed = false; 7500 // Attempt to sort and vectorize each of the store-groups. 7501 for (StoreListMap::iterator it = Stores.begin(), e = Stores.end(); it != e; 7502 ++it) { 7503 if (it->second.size() < 2) 7504 continue; 7505 7506 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " 7507 << it->second.size() << ".\n"); 7508 7509 Changed |= vectorizeStores(it->second, R); 7510 } 7511 return Changed; 7512 } 7513 7514 char SLPVectorizer::ID = 0; 7515 7516 static const char lv_name[] = "SLP Vectorizer"; 7517 7518 INITIALIZE_PASS_BEGIN(SLPVectorizer, SV_NAME, lv_name, false, false) 7519 INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass) 7520 INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass) 7521 INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker) 7522 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass) 7523 INITIALIZE_PASS_DEPENDENCY(LoopSimplify) 7524 INITIALIZE_PASS_DEPENDENCY(DemandedBitsWrapperPass) 7525 INITIALIZE_PASS_DEPENDENCY(OptimizationRemarkEmitterWrapperPass) 7526 INITIALIZE_PASS_DEPENDENCY(InjectTLIMappingsLegacy) 7527 INITIALIZE_PASS_END(SLPVectorizer, SV_NAME, lv_name, false, false) 7528 7529 Pass *llvm::createSLPVectorizerPass() { return new SLPVectorizer(); } 7530