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/LoopUtils.h" 89 #include "llvm/Transforms/Vectorize.h" 90 #include <algorithm> 91 #include <cassert> 92 #include <cstdint> 93 #include <iterator> 94 #include <memory> 95 #include <set> 96 #include <string> 97 #include <tuple> 98 #include <utility> 99 #include <vector> 100 101 using namespace llvm; 102 using namespace llvm::PatternMatch; 103 using namespace slpvectorizer; 104 105 #define SV_NAME "slp-vectorizer" 106 #define DEBUG_TYPE "SLP" 107 108 STATISTIC(NumVectorInstructions, "Number of vector instructions generated"); 109 110 cl::opt<bool> 111 llvm::RunSLPVectorization("vectorize-slp", cl::init(false), 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()->getVectorNumElements(); 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 (Vec->getType()->getVectorNumElements() != 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 analysis of the Instructions in \p VL described in 381 /// InstructionsState, the Opcode that we suppose the whole list 382 /// could be vectorized even if its structure is diverse. 383 static InstructionsState getSameOpcode(ArrayRef<Value *> VL, 384 unsigned BaseIndex = 0) { 385 // Make sure these are all Instructions. 386 if (llvm::any_of(VL, [](Value *V) { return !isa<Instruction>(V); })) 387 return InstructionsState(VL[BaseIndex], nullptr, nullptr); 388 389 bool IsCastOp = isa<CastInst>(VL[BaseIndex]); 390 bool IsBinOp = isa<BinaryOperator>(VL[BaseIndex]); 391 unsigned Opcode = cast<Instruction>(VL[BaseIndex])->getOpcode(); 392 unsigned AltOpcode = Opcode; 393 unsigned AltIndex = BaseIndex; 394 395 // Check for one alternate opcode from another BinaryOperator. 396 // TODO - generalize to support all operators (types, calls etc.). 397 for (int Cnt = 0, E = VL.size(); Cnt < E; Cnt++) { 398 unsigned InstOpcode = cast<Instruction>(VL[Cnt])->getOpcode(); 399 if (IsBinOp && isa<BinaryOperator>(VL[Cnt])) { 400 if (InstOpcode == Opcode || InstOpcode == AltOpcode) 401 continue; 402 if (Opcode == AltOpcode) { 403 AltOpcode = InstOpcode; 404 AltIndex = Cnt; 405 continue; 406 } 407 } else if (IsCastOp && isa<CastInst>(VL[Cnt])) { 408 Type *Ty0 = cast<Instruction>(VL[BaseIndex])->getOperand(0)->getType(); 409 Type *Ty1 = cast<Instruction>(VL[Cnt])->getOperand(0)->getType(); 410 if (Ty0 == Ty1) { 411 if (InstOpcode == Opcode || InstOpcode == AltOpcode) 412 continue; 413 if (Opcode == AltOpcode) { 414 AltOpcode = InstOpcode; 415 AltIndex = Cnt; 416 continue; 417 } 418 } 419 } else if (InstOpcode == Opcode || InstOpcode == AltOpcode) 420 continue; 421 return InstructionsState(VL[BaseIndex], nullptr, nullptr); 422 } 423 424 return InstructionsState(VL[BaseIndex], cast<Instruction>(VL[BaseIndex]), 425 cast<Instruction>(VL[AltIndex])); 426 } 427 428 /// \returns true if all of the values in \p VL have the same type or false 429 /// otherwise. 430 static bool allSameType(ArrayRef<Value *> VL) { 431 Type *Ty = VL[0]->getType(); 432 for (int i = 1, e = VL.size(); i < e; i++) 433 if (VL[i]->getType() != Ty) 434 return false; 435 436 return true; 437 } 438 439 /// \returns True if Extract{Value,Element} instruction extracts element Idx. 440 static Optional<unsigned> getExtractIndex(Instruction *E) { 441 unsigned Opcode = E->getOpcode(); 442 assert((Opcode == Instruction::ExtractElement || 443 Opcode == Instruction::ExtractValue) && 444 "Expected extractelement or extractvalue instruction."); 445 if (Opcode == Instruction::ExtractElement) { 446 auto *CI = dyn_cast<ConstantInt>(E->getOperand(1)); 447 if (!CI) 448 return None; 449 return CI->getZExtValue(); 450 } 451 ExtractValueInst *EI = cast<ExtractValueInst>(E); 452 if (EI->getNumIndices() != 1) 453 return None; 454 return *EI->idx_begin(); 455 } 456 457 /// \returns True if in-tree use also needs extract. This refers to 458 /// possible scalar operand in vectorized instruction. 459 static bool InTreeUserNeedToExtract(Value *Scalar, Instruction *UserInst, 460 TargetLibraryInfo *TLI) { 461 unsigned Opcode = UserInst->getOpcode(); 462 switch (Opcode) { 463 case Instruction::Load: { 464 LoadInst *LI = cast<LoadInst>(UserInst); 465 return (LI->getPointerOperand() == Scalar); 466 } 467 case Instruction::Store: { 468 StoreInst *SI = cast<StoreInst>(UserInst); 469 return (SI->getPointerOperand() == Scalar); 470 } 471 case Instruction::Call: { 472 CallInst *CI = cast<CallInst>(UserInst); 473 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 474 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 475 if (hasVectorInstrinsicScalarOpd(ID, i)) 476 return (CI->getArgOperand(i) == Scalar); 477 } 478 LLVM_FALLTHROUGH; 479 } 480 default: 481 return false; 482 } 483 } 484 485 /// \returns the AA location that is being access by the instruction. 486 static MemoryLocation getLocation(Instruction *I, AliasAnalysis *AA) { 487 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 488 return MemoryLocation::get(SI); 489 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 490 return MemoryLocation::get(LI); 491 return MemoryLocation(); 492 } 493 494 /// \returns True if the instruction is not a volatile or atomic load/store. 495 static bool isSimple(Instruction *I) { 496 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 497 return LI->isSimple(); 498 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 499 return SI->isSimple(); 500 if (MemIntrinsic *MI = dyn_cast<MemIntrinsic>(I)) 501 return !MI->isVolatile(); 502 return true; 503 } 504 505 namespace llvm { 506 507 namespace slpvectorizer { 508 509 /// Bottom Up SLP Vectorizer. 510 class BoUpSLP { 511 struct TreeEntry; 512 struct ScheduleData; 513 514 public: 515 using ValueList = SmallVector<Value *, 8>; 516 using InstrList = SmallVector<Instruction *, 16>; 517 using ValueSet = SmallPtrSet<Value *, 16>; 518 using StoreList = SmallVector<StoreInst *, 8>; 519 using ExtraValueToDebugLocsMap = 520 MapVector<Value *, SmallVector<Instruction *, 2>>; 521 522 BoUpSLP(Function *Func, ScalarEvolution *Se, TargetTransformInfo *Tti, 523 TargetLibraryInfo *TLi, AliasAnalysis *Aa, LoopInfo *Li, 524 DominatorTree *Dt, AssumptionCache *AC, DemandedBits *DB, 525 const DataLayout *DL, OptimizationRemarkEmitter *ORE) 526 : F(Func), SE(Se), TTI(Tti), TLI(TLi), AA(Aa), LI(Li), DT(Dt), AC(AC), 527 DB(DB), DL(DL), ORE(ORE), Builder(Se->getContext()) { 528 CodeMetrics::collectEphemeralValues(F, AC, EphValues); 529 // Use the vector register size specified by the target unless overridden 530 // by a command-line option. 531 // TODO: It would be better to limit the vectorization factor based on 532 // data type rather than just register size. For example, x86 AVX has 533 // 256-bit registers, but it does not support integer operations 534 // at that width (that requires AVX2). 535 if (MaxVectorRegSizeOption.getNumOccurrences()) 536 MaxVecRegSize = MaxVectorRegSizeOption; 537 else 538 MaxVecRegSize = TTI->getRegisterBitWidth(true); 539 540 if (MinVectorRegSizeOption.getNumOccurrences()) 541 MinVecRegSize = MinVectorRegSizeOption; 542 else 543 MinVecRegSize = TTI->getMinVectorRegisterBitWidth(); 544 } 545 546 /// Vectorize the tree that starts with the elements in \p VL. 547 /// Returns the vectorized root. 548 Value *vectorizeTree(); 549 550 /// Vectorize the tree but with the list of externally used values \p 551 /// ExternallyUsedValues. Values in this MapVector can be replaced but the 552 /// generated extractvalue instructions. 553 Value *vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues); 554 555 /// \returns the cost incurred by unwanted spills and fills, caused by 556 /// holding live values over call sites. 557 int getSpillCost() const; 558 559 /// \returns the vectorization cost of the subtree that starts at \p VL. 560 /// A negative number means that this is profitable. 561 int getTreeCost(); 562 563 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 564 /// the purpose of scheduling and extraction in the \p UserIgnoreLst. 565 void buildTree(ArrayRef<Value *> Roots, 566 ArrayRef<Value *> UserIgnoreLst = None); 567 568 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 569 /// the purpose of scheduling and extraction in the \p UserIgnoreLst taking 570 /// into account (and updating it, if required) list of externally used 571 /// values stored in \p ExternallyUsedValues. 572 void buildTree(ArrayRef<Value *> Roots, 573 ExtraValueToDebugLocsMap &ExternallyUsedValues, 574 ArrayRef<Value *> UserIgnoreLst = None); 575 576 /// Clear the internal data structures that are created by 'buildTree'. 577 void deleteTree() { 578 VectorizableTree.clear(); 579 ScalarToTreeEntry.clear(); 580 MustGather.clear(); 581 ExternalUses.clear(); 582 NumOpsWantToKeepOrder.clear(); 583 NumOpsWantToKeepOriginalOrder = 0; 584 for (auto &Iter : BlocksSchedules) { 585 BlockScheduling *BS = Iter.second.get(); 586 BS->clear(); 587 } 588 MinBWs.clear(); 589 } 590 591 unsigned getTreeSize() const { return VectorizableTree.size(); } 592 593 /// Perform LICM and CSE on the newly generated gather sequences. 594 void optimizeGatherSequence(); 595 596 /// \returns The best order of instructions for vectorization. 597 Optional<ArrayRef<unsigned>> bestOrder() const { 598 auto I = std::max_element( 599 NumOpsWantToKeepOrder.begin(), NumOpsWantToKeepOrder.end(), 600 [](const decltype(NumOpsWantToKeepOrder)::value_type &D1, 601 const decltype(NumOpsWantToKeepOrder)::value_type &D2) { 602 return D1.second < D2.second; 603 }); 604 if (I == NumOpsWantToKeepOrder.end() || 605 I->getSecond() <= NumOpsWantToKeepOriginalOrder) 606 return None; 607 608 return makeArrayRef(I->getFirst()); 609 } 610 611 /// \return The vector element size in bits to use when vectorizing the 612 /// expression tree ending at \p V. If V is a store, the size is the width of 613 /// the stored value. Otherwise, the size is the width of the largest loaded 614 /// value reaching V. This method is used by the vectorizer to calculate 615 /// vectorization factors. 616 unsigned getVectorElementSize(Value *V) const; 617 618 /// Compute the minimum type sizes required to represent the entries in a 619 /// vectorizable tree. 620 void computeMinimumValueSizes(); 621 622 // \returns maximum vector register size as set by TTI or overridden by cl::opt. 623 unsigned getMaxVecRegSize() const { 624 return MaxVecRegSize; 625 } 626 627 // \returns minimum vector register size as set by cl::opt. 628 unsigned getMinVecRegSize() const { 629 return MinVecRegSize; 630 } 631 632 /// Check if homogeneous aggregate is isomorphic to some VectorType. 633 /// Accepts homogeneous multidimensional aggregate of scalars/vectors like 634 /// {[4 x i16], [4 x i16]}, { <2 x float>, <2 x float> }, 635 /// {{{i16, i16}, {i16, i16}}, {{i16, i16}, {i16, i16}}} and so on. 636 /// 637 /// \returns number of elements in vector if isomorphism exists, 0 otherwise. 638 unsigned canMapToVector(Type *T, const DataLayout &DL) const; 639 640 /// \returns True if the VectorizableTree is both tiny and not fully 641 /// vectorizable. We do not vectorize such trees. 642 bool isTreeTinyAndNotFullyVectorizable() const; 643 644 /// Assume that a legal-sized 'or'-reduction of shifted/zexted loaded values 645 /// can be load combined in the backend. Load combining may not be allowed in 646 /// the IR optimizer, so we do not want to alter the pattern. For example, 647 /// partially transforming a scalar bswap() pattern into vector code is 648 /// effectively impossible for the backend to undo. 649 /// TODO: If load combining is allowed in the IR optimizer, this analysis 650 /// may not be necessary. 651 bool isLoadCombineReductionCandidate(unsigned ReductionOpcode) const; 652 653 OptimizationRemarkEmitter *getORE() { return ORE; } 654 655 /// This structure holds any data we need about the edges being traversed 656 /// during buildTree_rec(). We keep track of: 657 /// (i) the user TreeEntry index, and 658 /// (ii) the index of the edge. 659 struct EdgeInfo { 660 EdgeInfo() = default; 661 EdgeInfo(TreeEntry *UserTE, unsigned EdgeIdx) 662 : UserTE(UserTE), EdgeIdx(EdgeIdx) {} 663 /// The user TreeEntry. 664 TreeEntry *UserTE = nullptr; 665 /// The operand index of the use. 666 unsigned EdgeIdx = UINT_MAX; 667 #ifndef NDEBUG 668 friend inline raw_ostream &operator<<(raw_ostream &OS, 669 const BoUpSLP::EdgeInfo &EI) { 670 EI.dump(OS); 671 return OS; 672 } 673 /// Debug print. 674 void dump(raw_ostream &OS) const { 675 OS << "{User:" << (UserTE ? std::to_string(UserTE->Idx) : "null") 676 << " EdgeIdx:" << EdgeIdx << "}"; 677 } 678 LLVM_DUMP_METHOD void dump() const { dump(dbgs()); } 679 #endif 680 }; 681 682 /// A helper data structure to hold the operands of a vector of instructions. 683 /// This supports a fixed vector length for all operand vectors. 684 class VLOperands { 685 /// For each operand we need (i) the value, and (ii) the opcode that it 686 /// would be attached to if the expression was in a left-linearized form. 687 /// This is required to avoid illegal operand reordering. 688 /// For example: 689 /// \verbatim 690 /// 0 Op1 691 /// |/ 692 /// Op1 Op2 Linearized + Op2 693 /// \ / ----------> |/ 694 /// - - 695 /// 696 /// Op1 - Op2 (0 + Op1) - Op2 697 /// \endverbatim 698 /// 699 /// Value Op1 is attached to a '+' operation, and Op2 to a '-'. 700 /// 701 /// Another way to think of this is to track all the operations across the 702 /// path from the operand all the way to the root of the tree and to 703 /// calculate the operation that corresponds to this path. For example, the 704 /// path from Op2 to the root crosses the RHS of the '-', therefore the 705 /// corresponding operation is a '-' (which matches the one in the 706 /// linearized tree, as shown above). 707 /// 708 /// For lack of a better term, we refer to this operation as Accumulated 709 /// Path Operation (APO). 710 struct OperandData { 711 OperandData() = default; 712 OperandData(Value *V, bool APO, bool IsUsed) 713 : V(V), APO(APO), IsUsed(IsUsed) {} 714 /// The operand value. 715 Value *V = nullptr; 716 /// TreeEntries only allow a single opcode, or an alternate sequence of 717 /// them (e.g, +, -). Therefore, we can safely use a boolean value for the 718 /// APO. It is set to 'true' if 'V' is attached to an inverse operation 719 /// in the left-linearized form (e.g., Sub/Div), and 'false' otherwise 720 /// (e.g., Add/Mul) 721 bool APO = false; 722 /// Helper data for the reordering function. 723 bool IsUsed = false; 724 }; 725 726 /// During operand reordering, we are trying to select the operand at lane 727 /// that matches best with the operand at the neighboring lane. Our 728 /// selection is based on the type of value we are looking for. For example, 729 /// if the neighboring lane has a load, we need to look for a load that is 730 /// accessing a consecutive address. These strategies are summarized in the 731 /// 'ReorderingMode' enumerator. 732 enum class ReorderingMode { 733 Load, ///< Matching loads to consecutive memory addresses 734 Opcode, ///< Matching instructions based on opcode (same or alternate) 735 Constant, ///< Matching constants 736 Splat, ///< Matching the same instruction multiple times (broadcast) 737 Failed, ///< We failed to create a vectorizable group 738 }; 739 740 using OperandDataVec = SmallVector<OperandData, 2>; 741 742 /// A vector of operand vectors. 743 SmallVector<OperandDataVec, 4> OpsVec; 744 745 const DataLayout &DL; 746 ScalarEvolution &SE; 747 const BoUpSLP &R; 748 749 /// \returns the operand data at \p OpIdx and \p Lane. 750 OperandData &getData(unsigned OpIdx, unsigned Lane) { 751 return OpsVec[OpIdx][Lane]; 752 } 753 754 /// \returns the operand data at \p OpIdx and \p Lane. Const version. 755 const OperandData &getData(unsigned OpIdx, unsigned Lane) const { 756 return OpsVec[OpIdx][Lane]; 757 } 758 759 /// Clears the used flag for all entries. 760 void clearUsed() { 761 for (unsigned OpIdx = 0, NumOperands = getNumOperands(); 762 OpIdx != NumOperands; ++OpIdx) 763 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 764 ++Lane) 765 OpsVec[OpIdx][Lane].IsUsed = false; 766 } 767 768 /// Swap the operand at \p OpIdx1 with that one at \p OpIdx2. 769 void swap(unsigned OpIdx1, unsigned OpIdx2, unsigned Lane) { 770 std::swap(OpsVec[OpIdx1][Lane], OpsVec[OpIdx2][Lane]); 771 } 772 773 // The hard-coded scores listed here are not very important. When computing 774 // the scores of matching one sub-tree with another, we are basically 775 // counting the number of values that are matching. So even if all scores 776 // are set to 1, we would still get a decent matching result. 777 // However, sometimes we have to break ties. For example we may have to 778 // choose between matching loads vs matching opcodes. This is what these 779 // scores are helping us with: they provide the order of preference. 780 781 /// Loads from consecutive memory addresses, e.g. load(A[i]), load(A[i+1]). 782 static const int ScoreConsecutiveLoads = 3; 783 /// ExtractElementInst from same vector and consecutive indexes. 784 static const int ScoreConsecutiveExtracts = 3; 785 /// Constants. 786 static const int ScoreConstants = 2; 787 /// Instructions with the same opcode. 788 static const int ScoreSameOpcode = 2; 789 /// Instructions with alt opcodes (e.g, add + sub). 790 static const int ScoreAltOpcodes = 1; 791 /// Identical instructions (a.k.a. splat or broadcast). 792 static const int ScoreSplat = 1; 793 /// Matching with an undef is preferable to failing. 794 static const int ScoreUndef = 1; 795 /// Score for failing to find a decent match. 796 static const int ScoreFail = 0; 797 /// User exteranl to the vectorized code. 798 static const int ExternalUseCost = 1; 799 /// The user is internal but in a different lane. 800 static const int UserInDiffLaneCost = ExternalUseCost; 801 802 /// \returns the score of placing \p V1 and \p V2 in consecutive lanes. 803 static int getShallowScore(Value *V1, Value *V2, const DataLayout &DL, 804 ScalarEvolution &SE) { 805 auto *LI1 = dyn_cast<LoadInst>(V1); 806 auto *LI2 = dyn_cast<LoadInst>(V2); 807 if (LI1 && LI2) 808 return isConsecutiveAccess(LI1, LI2, DL, SE) 809 ? VLOperands::ScoreConsecutiveLoads 810 : VLOperands::ScoreFail; 811 812 auto *C1 = dyn_cast<Constant>(V1); 813 auto *C2 = dyn_cast<Constant>(V2); 814 if (C1 && C2) 815 return VLOperands::ScoreConstants; 816 817 // Extracts from consecutive indexes of the same vector better score as 818 // the extracts could be optimized away. 819 auto *Ex1 = dyn_cast<ExtractElementInst>(V1); 820 auto *Ex2 = dyn_cast<ExtractElementInst>(V2); 821 if (Ex1 && Ex2 && Ex1->getVectorOperand() == Ex2->getVectorOperand() && 822 cast<ConstantInt>(Ex1->getIndexOperand())->getZExtValue() + 1 == 823 cast<ConstantInt>(Ex2->getIndexOperand())->getZExtValue()) { 824 return VLOperands::ScoreConsecutiveExtracts; 825 } 826 827 auto *I1 = dyn_cast<Instruction>(V1); 828 auto *I2 = dyn_cast<Instruction>(V2); 829 if (I1 && I2) { 830 if (I1 == I2) 831 return VLOperands::ScoreSplat; 832 InstructionsState S = getSameOpcode({I1, I2}); 833 // Note: Only consider instructions with <= 2 operands to avoid 834 // complexity explosion. 835 if (S.getOpcode() && S.MainOp->getNumOperands() <= 2) 836 return S.isAltShuffle() ? VLOperands::ScoreAltOpcodes 837 : VLOperands::ScoreSameOpcode; 838 } 839 840 if (isa<UndefValue>(V2)) 841 return VLOperands::ScoreUndef; 842 843 return VLOperands::ScoreFail; 844 } 845 846 /// Holds the values and their lane that are taking part in the look-ahead 847 /// score calculation. This is used in the external uses cost calculation. 848 SmallDenseMap<Value *, int> InLookAheadValues; 849 850 /// \Returns the additinal cost due to uses of \p LHS and \p RHS that are 851 /// either external to the vectorized code, or require shuffling. 852 int getExternalUsesCost(const std::pair<Value *, int> &LHS, 853 const std::pair<Value *, int> &RHS) { 854 int Cost = 0; 855 SmallVector<std::pair<Value *, int>, 2> Values = {LHS, RHS}; 856 for (int Idx = 0, IdxE = Values.size(); Idx != IdxE; ++Idx) { 857 Value *V = Values[Idx].first; 858 // Calculate the absolute lane, using the minimum relative lane of LHS 859 // and RHS as base and Idx as the offset. 860 int Ln = std::min(LHS.second, RHS.second) + Idx; 861 assert(Ln >= 0 && "Bad lane calculation"); 862 unsigned UsersBudget = LookAheadUsersBudget; 863 for (User *U : V->users()) { 864 if (const TreeEntry *UserTE = R.getTreeEntry(U)) { 865 // The user is in the VectorizableTree. Check if we need to insert. 866 auto It = llvm::find(UserTE->Scalars, U); 867 assert(It != UserTE->Scalars.end() && "U is in UserTE"); 868 int UserLn = std::distance(UserTE->Scalars.begin(), It); 869 assert(UserLn >= 0 && "Bad lane"); 870 if (UserLn != Ln) 871 Cost += UserInDiffLaneCost; 872 } else { 873 // Check if the user is in the look-ahead code. 874 auto It2 = InLookAheadValues.find(U); 875 if (It2 != InLookAheadValues.end()) { 876 // The user is in the look-ahead code. Check the lane. 877 if (It2->second != Ln) 878 Cost += UserInDiffLaneCost; 879 } else { 880 // The user is neither in SLP tree nor in the look-ahead code. 881 Cost += ExternalUseCost; 882 } 883 } 884 // Limit the number of visited uses to cap compilation time. 885 if (--UsersBudget == 0) 886 break; 887 } 888 } 889 return Cost; 890 } 891 892 /// Go through the operands of \p LHS and \p RHS recursively until \p 893 /// MaxLevel, and return the cummulative score. For example: 894 /// \verbatim 895 /// A[0] B[0] A[1] B[1] C[0] D[0] B[1] A[1] 896 /// \ / \ / \ / \ / 897 /// + + + + 898 /// G1 G2 G3 G4 899 /// \endverbatim 900 /// The getScoreAtLevelRec(G1, G2) function will try to match the nodes at 901 /// each level recursively, accumulating the score. It starts from matching 902 /// the additions at level 0, then moves on to the loads (level 1). The 903 /// score of G1 and G2 is higher than G1 and G3, because {A[0],A[1]} and 904 /// {B[0],B[1]} match with VLOperands::ScoreConsecutiveLoads, while 905 /// {A[0],C[0]} has a score of VLOperands::ScoreFail. 906 /// Please note that the order of the operands does not matter, as we 907 /// evaluate the score of all profitable combinations of operands. In 908 /// other words the score of G1 and G4 is the same as G1 and G2. This 909 /// heuristic is based on ideas described in: 910 /// Look-ahead SLP: Auto-vectorization in the presence of commutative 911 /// operations, CGO 2018 by Vasileios Porpodas, Rodrigo C. O. Rocha, 912 /// Luís F. W. Góes 913 int getScoreAtLevelRec(const std::pair<Value *, int> &LHS, 914 const std::pair<Value *, int> &RHS, int CurrLevel, 915 int MaxLevel) { 916 917 Value *V1 = LHS.first; 918 Value *V2 = RHS.first; 919 // Get the shallow score of V1 and V2. 920 int ShallowScoreAtThisLevel = 921 std::max((int)ScoreFail, getShallowScore(V1, V2, DL, SE) - 922 getExternalUsesCost(LHS, RHS)); 923 int Lane1 = LHS.second; 924 int Lane2 = RHS.second; 925 926 // If reached MaxLevel, 927 // or if V1 and V2 are not instructions, 928 // or if they are SPLAT, 929 // or if they are not consecutive, early return the current cost. 930 auto *I1 = dyn_cast<Instruction>(V1); 931 auto *I2 = dyn_cast<Instruction>(V2); 932 if (CurrLevel == MaxLevel || !(I1 && I2) || I1 == I2 || 933 ShallowScoreAtThisLevel == VLOperands::ScoreFail || 934 (isa<LoadInst>(I1) && isa<LoadInst>(I2) && ShallowScoreAtThisLevel)) 935 return ShallowScoreAtThisLevel; 936 assert(I1 && I2 && "Should have early exited."); 937 938 // Keep track of in-tree values for determining the external-use cost. 939 InLookAheadValues[V1] = Lane1; 940 InLookAheadValues[V2] = Lane2; 941 942 // Contains the I2 operand indexes that got matched with I1 operands. 943 SmallSet<unsigned, 4> Op2Used; 944 945 // Recursion towards the operands of I1 and I2. We are trying all possbile 946 // operand pairs, and keeping track of the best score. 947 for (unsigned OpIdx1 = 0, NumOperands1 = I1->getNumOperands(); 948 OpIdx1 != NumOperands1; ++OpIdx1) { 949 // Try to pair op1I with the best operand of I2. 950 int MaxTmpScore = 0; 951 unsigned MaxOpIdx2 = 0; 952 bool FoundBest = false; 953 // If I2 is commutative try all combinations. 954 unsigned FromIdx = isCommutative(I2) ? 0 : OpIdx1; 955 unsigned ToIdx = isCommutative(I2) 956 ? I2->getNumOperands() 957 : std::min(I2->getNumOperands(), OpIdx1 + 1); 958 assert(FromIdx <= ToIdx && "Bad index"); 959 for (unsigned OpIdx2 = FromIdx; OpIdx2 != ToIdx; ++OpIdx2) { 960 // Skip operands already paired with OpIdx1. 961 if (Op2Used.count(OpIdx2)) 962 continue; 963 // Recursively calculate the cost at each level 964 int TmpScore = getScoreAtLevelRec({I1->getOperand(OpIdx1), Lane1}, 965 {I2->getOperand(OpIdx2), Lane2}, 966 CurrLevel + 1, MaxLevel); 967 // Look for the best score. 968 if (TmpScore > VLOperands::ScoreFail && TmpScore > MaxTmpScore) { 969 MaxTmpScore = TmpScore; 970 MaxOpIdx2 = OpIdx2; 971 FoundBest = true; 972 } 973 } 974 if (FoundBest) { 975 // Pair {OpIdx1, MaxOpIdx2} was found to be best. Never revisit it. 976 Op2Used.insert(MaxOpIdx2); 977 ShallowScoreAtThisLevel += MaxTmpScore; 978 } 979 } 980 return ShallowScoreAtThisLevel; 981 } 982 983 /// \Returns the look-ahead score, which tells us how much the sub-trees 984 /// rooted at \p LHS and \p RHS match, the more they match the higher the 985 /// score. This helps break ties in an informed way when we cannot decide on 986 /// the order of the operands by just considering the immediate 987 /// predecessors. 988 int getLookAheadScore(const std::pair<Value *, int> &LHS, 989 const std::pair<Value *, int> &RHS) { 990 InLookAheadValues.clear(); 991 return getScoreAtLevelRec(LHS, RHS, 1, LookAheadMaxDepth); 992 } 993 994 // Search all operands in Ops[*][Lane] for the one that matches best 995 // Ops[OpIdx][LastLane] and return its opreand index. 996 // If no good match can be found, return None. 997 Optional<unsigned> 998 getBestOperand(unsigned OpIdx, int Lane, int LastLane, 999 ArrayRef<ReorderingMode> ReorderingModes) { 1000 unsigned NumOperands = getNumOperands(); 1001 1002 // The operand of the previous lane at OpIdx. 1003 Value *OpLastLane = getData(OpIdx, LastLane).V; 1004 1005 // Our strategy mode for OpIdx. 1006 ReorderingMode RMode = ReorderingModes[OpIdx]; 1007 1008 // The linearized opcode of the operand at OpIdx, Lane. 1009 bool OpIdxAPO = getData(OpIdx, Lane).APO; 1010 1011 // The best operand index and its score. 1012 // Sometimes we have more than one option (e.g., Opcode and Undefs), so we 1013 // are using the score to differentiate between the two. 1014 struct BestOpData { 1015 Optional<unsigned> Idx = None; 1016 unsigned Score = 0; 1017 } BestOp; 1018 1019 // Iterate through all unused operands and look for the best. 1020 for (unsigned Idx = 0; Idx != NumOperands; ++Idx) { 1021 // Get the operand at Idx and Lane. 1022 OperandData &OpData = getData(Idx, Lane); 1023 Value *Op = OpData.V; 1024 bool OpAPO = OpData.APO; 1025 1026 // Skip already selected operands. 1027 if (OpData.IsUsed) 1028 continue; 1029 1030 // Skip if we are trying to move the operand to a position with a 1031 // different opcode in the linearized tree form. This would break the 1032 // semantics. 1033 if (OpAPO != OpIdxAPO) 1034 continue; 1035 1036 // Look for an operand that matches the current mode. 1037 switch (RMode) { 1038 case ReorderingMode::Load: 1039 case ReorderingMode::Constant: 1040 case ReorderingMode::Opcode: { 1041 bool LeftToRight = Lane > LastLane; 1042 Value *OpLeft = (LeftToRight) ? OpLastLane : Op; 1043 Value *OpRight = (LeftToRight) ? Op : OpLastLane; 1044 unsigned Score = 1045 getLookAheadScore({OpLeft, LastLane}, {OpRight, Lane}); 1046 if (Score > BestOp.Score) { 1047 BestOp.Idx = Idx; 1048 BestOp.Score = Score; 1049 } 1050 break; 1051 } 1052 case ReorderingMode::Splat: 1053 if (Op == OpLastLane) 1054 BestOp.Idx = Idx; 1055 break; 1056 case ReorderingMode::Failed: 1057 return None; 1058 } 1059 } 1060 1061 if (BestOp.Idx) { 1062 getData(BestOp.Idx.getValue(), Lane).IsUsed = true; 1063 return BestOp.Idx; 1064 } 1065 // If we could not find a good match return None. 1066 return None; 1067 } 1068 1069 /// Helper for reorderOperandVecs. \Returns the lane that we should start 1070 /// reordering from. This is the one which has the least number of operands 1071 /// that can freely move about. 1072 unsigned getBestLaneToStartReordering() const { 1073 unsigned BestLane = 0; 1074 unsigned Min = UINT_MAX; 1075 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 1076 ++Lane) { 1077 unsigned NumFreeOps = getMaxNumOperandsThatCanBeReordered(Lane); 1078 if (NumFreeOps < Min) { 1079 Min = NumFreeOps; 1080 BestLane = Lane; 1081 } 1082 } 1083 return BestLane; 1084 } 1085 1086 /// \Returns the maximum number of operands that are allowed to be reordered 1087 /// for \p Lane. This is used as a heuristic for selecting the first lane to 1088 /// start operand reordering. 1089 unsigned getMaxNumOperandsThatCanBeReordered(unsigned Lane) const { 1090 unsigned CntTrue = 0; 1091 unsigned NumOperands = getNumOperands(); 1092 // Operands with the same APO can be reordered. We therefore need to count 1093 // how many of them we have for each APO, like this: Cnt[APO] = x. 1094 // Since we only have two APOs, namely true and false, we can avoid using 1095 // a map. Instead we can simply count the number of operands that 1096 // correspond to one of them (in this case the 'true' APO), and calculate 1097 // the other by subtracting it from the total number of operands. 1098 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) 1099 if (getData(OpIdx, Lane).APO) 1100 ++CntTrue; 1101 unsigned CntFalse = NumOperands - CntTrue; 1102 return std::max(CntTrue, CntFalse); 1103 } 1104 1105 /// Go through the instructions in VL and append their operands. 1106 void appendOperandsOfVL(ArrayRef<Value *> VL) { 1107 assert(!VL.empty() && "Bad VL"); 1108 assert((empty() || VL.size() == getNumLanes()) && 1109 "Expected same number of lanes"); 1110 assert(isa<Instruction>(VL[0]) && "Expected instruction"); 1111 unsigned NumOperands = cast<Instruction>(VL[0])->getNumOperands(); 1112 OpsVec.resize(NumOperands); 1113 unsigned NumLanes = VL.size(); 1114 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1115 OpsVec[OpIdx].resize(NumLanes); 1116 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { 1117 assert(isa<Instruction>(VL[Lane]) && "Expected instruction"); 1118 // Our tree has just 3 nodes: the root and two operands. 1119 // It is therefore trivial to get the APO. We only need to check the 1120 // opcode of VL[Lane] and whether the operand at OpIdx is the LHS or 1121 // RHS operand. The LHS operand of both add and sub is never attached 1122 // to an inversese operation in the linearized form, therefore its APO 1123 // is false. The RHS is true only if VL[Lane] is an inverse operation. 1124 1125 // Since operand reordering is performed on groups of commutative 1126 // operations or alternating sequences (e.g., +, -), we can safely 1127 // tell the inverse operations by checking commutativity. 1128 bool IsInverseOperation = !isCommutative(cast<Instruction>(VL[Lane])); 1129 bool APO = (OpIdx == 0) ? false : IsInverseOperation; 1130 OpsVec[OpIdx][Lane] = {cast<Instruction>(VL[Lane])->getOperand(OpIdx), 1131 APO, false}; 1132 } 1133 } 1134 } 1135 1136 /// \returns the number of operands. 1137 unsigned getNumOperands() const { return OpsVec.size(); } 1138 1139 /// \returns the number of lanes. 1140 unsigned getNumLanes() const { return OpsVec[0].size(); } 1141 1142 /// \returns the operand value at \p OpIdx and \p Lane. 1143 Value *getValue(unsigned OpIdx, unsigned Lane) const { 1144 return getData(OpIdx, Lane).V; 1145 } 1146 1147 /// \returns true if the data structure is empty. 1148 bool empty() const { return OpsVec.empty(); } 1149 1150 /// Clears the data. 1151 void clear() { OpsVec.clear(); } 1152 1153 /// \Returns true if there are enough operands identical to \p Op to fill 1154 /// the whole vector. 1155 /// Note: This modifies the 'IsUsed' flag, so a cleanUsed() must follow. 1156 bool shouldBroadcast(Value *Op, unsigned OpIdx, unsigned Lane) { 1157 bool OpAPO = getData(OpIdx, Lane).APO; 1158 for (unsigned Ln = 0, Lns = getNumLanes(); Ln != Lns; ++Ln) { 1159 if (Ln == Lane) 1160 continue; 1161 // This is set to true if we found a candidate for broadcast at Lane. 1162 bool FoundCandidate = false; 1163 for (unsigned OpI = 0, OpE = getNumOperands(); OpI != OpE; ++OpI) { 1164 OperandData &Data = getData(OpI, Ln); 1165 if (Data.APO != OpAPO || Data.IsUsed) 1166 continue; 1167 if (Data.V == Op) { 1168 FoundCandidate = true; 1169 Data.IsUsed = true; 1170 break; 1171 } 1172 } 1173 if (!FoundCandidate) 1174 return false; 1175 } 1176 return true; 1177 } 1178 1179 public: 1180 /// Initialize with all the operands of the instruction vector \p RootVL. 1181 VLOperands(ArrayRef<Value *> RootVL, const DataLayout &DL, 1182 ScalarEvolution &SE, const BoUpSLP &R) 1183 : DL(DL), SE(SE), R(R) { 1184 // Append all the operands of RootVL. 1185 appendOperandsOfVL(RootVL); 1186 } 1187 1188 /// \Returns a value vector with the operands across all lanes for the 1189 /// opearnd at \p OpIdx. 1190 ValueList getVL(unsigned OpIdx) const { 1191 ValueList OpVL(OpsVec[OpIdx].size()); 1192 assert(OpsVec[OpIdx].size() == getNumLanes() && 1193 "Expected same num of lanes across all operands"); 1194 for (unsigned Lane = 0, Lanes = getNumLanes(); Lane != Lanes; ++Lane) 1195 OpVL[Lane] = OpsVec[OpIdx][Lane].V; 1196 return OpVL; 1197 } 1198 1199 // Performs operand reordering for 2 or more operands. 1200 // The original operands are in OrigOps[OpIdx][Lane]. 1201 // The reordered operands are returned in 'SortedOps[OpIdx][Lane]'. 1202 void reorder() { 1203 unsigned NumOperands = getNumOperands(); 1204 unsigned NumLanes = getNumLanes(); 1205 // Each operand has its own mode. We are using this mode to help us select 1206 // the instructions for each lane, so that they match best with the ones 1207 // we have selected so far. 1208 SmallVector<ReorderingMode, 2> ReorderingModes(NumOperands); 1209 1210 // This is a greedy single-pass algorithm. We are going over each lane 1211 // once and deciding on the best order right away with no back-tracking. 1212 // However, in order to increase its effectiveness, we start with the lane 1213 // that has operands that can move the least. For example, given the 1214 // following lanes: 1215 // Lane 0 : A[0] = B[0] + C[0] // Visited 3rd 1216 // Lane 1 : A[1] = C[1] - B[1] // Visited 1st 1217 // Lane 2 : A[2] = B[2] + C[2] // Visited 2nd 1218 // Lane 3 : A[3] = C[3] - B[3] // Visited 4th 1219 // we will start at Lane 1, since the operands of the subtraction cannot 1220 // be reordered. Then we will visit the rest of the lanes in a circular 1221 // fashion. That is, Lanes 2, then Lane 0, and finally Lane 3. 1222 1223 // Find the first lane that we will start our search from. 1224 unsigned FirstLane = getBestLaneToStartReordering(); 1225 1226 // Initialize the modes. 1227 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1228 Value *OpLane0 = getValue(OpIdx, FirstLane); 1229 // Keep track if we have instructions with all the same opcode on one 1230 // side. 1231 if (isa<LoadInst>(OpLane0)) 1232 ReorderingModes[OpIdx] = ReorderingMode::Load; 1233 else if (isa<Instruction>(OpLane0)) { 1234 // Check if OpLane0 should be broadcast. 1235 if (shouldBroadcast(OpLane0, OpIdx, FirstLane)) 1236 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1237 else 1238 ReorderingModes[OpIdx] = ReorderingMode::Opcode; 1239 } 1240 else if (isa<Constant>(OpLane0)) 1241 ReorderingModes[OpIdx] = ReorderingMode::Constant; 1242 else if (isa<Argument>(OpLane0)) 1243 // Our best hope is a Splat. It may save some cost in some cases. 1244 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1245 else 1246 // NOTE: This should be unreachable. 1247 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1248 } 1249 1250 // If the initial strategy fails for any of the operand indexes, then we 1251 // perform reordering again in a second pass. This helps avoid assigning 1252 // high priority to the failed strategy, and should improve reordering for 1253 // the non-failed operand indexes. 1254 for (int Pass = 0; Pass != 2; ++Pass) { 1255 // Skip the second pass if the first pass did not fail. 1256 bool StrategyFailed = false; 1257 // Mark all operand data as free to use. 1258 clearUsed(); 1259 // We keep the original operand order for the FirstLane, so reorder the 1260 // rest of the lanes. We are visiting the nodes in a circular fashion, 1261 // using FirstLane as the center point and increasing the radius 1262 // distance. 1263 for (unsigned Distance = 1; Distance != NumLanes; ++Distance) { 1264 // Visit the lane on the right and then the lane on the left. 1265 for (int Direction : {+1, -1}) { 1266 int Lane = FirstLane + Direction * Distance; 1267 if (Lane < 0 || Lane >= (int)NumLanes) 1268 continue; 1269 int LastLane = Lane - Direction; 1270 assert(LastLane >= 0 && LastLane < (int)NumLanes && 1271 "Out of bounds"); 1272 // Look for a good match for each operand. 1273 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1274 // Search for the operand that matches SortedOps[OpIdx][Lane-1]. 1275 Optional<unsigned> BestIdx = 1276 getBestOperand(OpIdx, Lane, LastLane, ReorderingModes); 1277 // By not selecting a value, we allow the operands that follow to 1278 // select a better matching value. We will get a non-null value in 1279 // the next run of getBestOperand(). 1280 if (BestIdx) { 1281 // Swap the current operand with the one returned by 1282 // getBestOperand(). 1283 swap(OpIdx, BestIdx.getValue(), Lane); 1284 } else { 1285 // We failed to find a best operand, set mode to 'Failed'. 1286 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1287 // Enable the second pass. 1288 StrategyFailed = true; 1289 } 1290 } 1291 } 1292 } 1293 // Skip second pass if the strategy did not fail. 1294 if (!StrategyFailed) 1295 break; 1296 } 1297 } 1298 1299 #if !defined(NDEBUG) || defined(LLVM_ENABLE_DUMP) 1300 LLVM_DUMP_METHOD static StringRef getModeStr(ReorderingMode RMode) { 1301 switch (RMode) { 1302 case ReorderingMode::Load: 1303 return "Load"; 1304 case ReorderingMode::Opcode: 1305 return "Opcode"; 1306 case ReorderingMode::Constant: 1307 return "Constant"; 1308 case ReorderingMode::Splat: 1309 return "Splat"; 1310 case ReorderingMode::Failed: 1311 return "Failed"; 1312 } 1313 llvm_unreachable("Unimplemented Reordering Type"); 1314 } 1315 1316 LLVM_DUMP_METHOD static raw_ostream &printMode(ReorderingMode RMode, 1317 raw_ostream &OS) { 1318 return OS << getModeStr(RMode); 1319 } 1320 1321 /// Debug print. 1322 LLVM_DUMP_METHOD static void dumpMode(ReorderingMode RMode) { 1323 printMode(RMode, dbgs()); 1324 } 1325 1326 friend raw_ostream &operator<<(raw_ostream &OS, ReorderingMode RMode) { 1327 return printMode(RMode, OS); 1328 } 1329 1330 LLVM_DUMP_METHOD raw_ostream &print(raw_ostream &OS) const { 1331 const unsigned Indent = 2; 1332 unsigned Cnt = 0; 1333 for (const OperandDataVec &OpDataVec : OpsVec) { 1334 OS << "Operand " << Cnt++ << "\n"; 1335 for (const OperandData &OpData : OpDataVec) { 1336 OS.indent(Indent) << "{"; 1337 if (Value *V = OpData.V) 1338 OS << *V; 1339 else 1340 OS << "null"; 1341 OS << ", APO:" << OpData.APO << "}\n"; 1342 } 1343 OS << "\n"; 1344 } 1345 return OS; 1346 } 1347 1348 /// Debug print. 1349 LLVM_DUMP_METHOD void dump() const { print(dbgs()); } 1350 #endif 1351 }; 1352 1353 /// Checks if the instruction is marked for deletion. 1354 bool isDeleted(Instruction *I) const { return DeletedInstructions.count(I); } 1355 1356 /// Marks values operands for later deletion by replacing them with Undefs. 1357 void eraseInstructions(ArrayRef<Value *> AV); 1358 1359 ~BoUpSLP(); 1360 1361 private: 1362 /// Checks if all users of \p I are the part of the vectorization tree. 1363 bool areAllUsersVectorized(Instruction *I) const; 1364 1365 /// \returns the cost of the vectorizable entry. 1366 int getEntryCost(TreeEntry *E); 1367 1368 /// This is the recursive part of buildTree. 1369 void buildTree_rec(ArrayRef<Value *> Roots, unsigned Depth, 1370 const EdgeInfo &EI); 1371 1372 /// \returns true if the ExtractElement/ExtractValue instructions in \p VL can 1373 /// be vectorized to use the original vector (or aggregate "bitcast" to a 1374 /// vector) and sets \p CurrentOrder to the identity permutation; otherwise 1375 /// returns false, setting \p CurrentOrder to either an empty vector or a 1376 /// non-identity permutation that allows to reuse extract instructions. 1377 bool canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 1378 SmallVectorImpl<unsigned> &CurrentOrder) const; 1379 1380 /// Vectorize a single entry in the tree. 1381 Value *vectorizeTree(TreeEntry *E); 1382 1383 /// Vectorize a single entry in the tree, starting in \p VL. 1384 Value *vectorizeTree(ArrayRef<Value *> VL); 1385 1386 /// \returns the scalarization cost for this type. Scalarization in this 1387 /// context means the creation of vectors from a group of scalars. 1388 int getGatherCost(Type *Ty, const DenseSet<unsigned> &ShuffledIndices) const; 1389 1390 /// \returns the scalarization cost for this list of values. Assuming that 1391 /// this subtree gets vectorized, we may need to extract the values from the 1392 /// roots. This method calculates the cost of extracting the values. 1393 int getGatherCost(ArrayRef<Value *> VL) const; 1394 1395 /// Set the Builder insert point to one after the last instruction in 1396 /// the bundle 1397 void setInsertPointAfterBundle(TreeEntry *E); 1398 1399 /// \returns a vector from a collection of scalars in \p VL. 1400 Value *Gather(ArrayRef<Value *> VL, VectorType *Ty); 1401 1402 /// \returns whether the VectorizableTree is fully vectorizable and will 1403 /// be beneficial even the tree height is tiny. 1404 bool isFullyVectorizableTinyTree() const; 1405 1406 /// Reorder commutative or alt operands to get better probability of 1407 /// generating vectorized code. 1408 static void reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 1409 SmallVectorImpl<Value *> &Left, 1410 SmallVectorImpl<Value *> &Right, 1411 const DataLayout &DL, 1412 ScalarEvolution &SE, 1413 const BoUpSLP &R); 1414 struct TreeEntry { 1415 using VecTreeTy = SmallVector<std::unique_ptr<TreeEntry>, 8>; 1416 TreeEntry(VecTreeTy &Container) : Container(Container) {} 1417 1418 /// \returns true if the scalars in VL are equal to this entry. 1419 bool isSame(ArrayRef<Value *> VL) const { 1420 if (VL.size() == Scalars.size()) 1421 return std::equal(VL.begin(), VL.end(), Scalars.begin()); 1422 return VL.size() == ReuseShuffleIndices.size() && 1423 std::equal( 1424 VL.begin(), VL.end(), ReuseShuffleIndices.begin(), 1425 [this](Value *V, unsigned Idx) { return V == Scalars[Idx]; }); 1426 } 1427 1428 /// A vector of scalars. 1429 ValueList Scalars; 1430 1431 /// The Scalars are vectorized into this value. It is initialized to Null. 1432 Value *VectorizedValue = nullptr; 1433 1434 /// Do we need to gather this sequence ? 1435 bool NeedToGather = false; 1436 1437 /// Does this sequence require some shuffling? 1438 SmallVector<unsigned, 4> ReuseShuffleIndices; 1439 1440 /// Does this entry require reordering? 1441 ArrayRef<unsigned> ReorderIndices; 1442 1443 /// Points back to the VectorizableTree. 1444 /// 1445 /// Only used for Graphviz right now. Unfortunately GraphTrait::NodeRef has 1446 /// to be a pointer and needs to be able to initialize the child iterator. 1447 /// Thus we need a reference back to the container to translate the indices 1448 /// to entries. 1449 VecTreeTy &Container; 1450 1451 /// The TreeEntry index containing the user of this entry. We can actually 1452 /// have multiple users so the data structure is not truly a tree. 1453 SmallVector<EdgeInfo, 1> UserTreeIndices; 1454 1455 /// The index of this treeEntry in VectorizableTree. 1456 int Idx = -1; 1457 1458 private: 1459 /// The operands of each instruction in each lane Operands[op_index][lane]. 1460 /// Note: This helps avoid the replication of the code that performs the 1461 /// reordering of operands during buildTree_rec() and vectorizeTree(). 1462 SmallVector<ValueList, 2> Operands; 1463 1464 /// The main/alternate instruction. 1465 Instruction *MainOp = nullptr; 1466 Instruction *AltOp = nullptr; 1467 1468 public: 1469 /// Set this bundle's \p OpIdx'th operand to \p OpVL. 1470 void setOperand(unsigned OpIdx, ArrayRef<Value *> OpVL) { 1471 if (Operands.size() < OpIdx + 1) 1472 Operands.resize(OpIdx + 1); 1473 assert(Operands[OpIdx].size() == 0 && "Already resized?"); 1474 Operands[OpIdx].resize(Scalars.size()); 1475 for (unsigned Lane = 0, E = Scalars.size(); Lane != E; ++Lane) 1476 Operands[OpIdx][Lane] = OpVL[Lane]; 1477 } 1478 1479 /// Set the operands of this bundle in their original order. 1480 void setOperandsInOrder() { 1481 assert(Operands.empty() && "Already initialized?"); 1482 auto *I0 = cast<Instruction>(Scalars[0]); 1483 Operands.resize(I0->getNumOperands()); 1484 unsigned NumLanes = Scalars.size(); 1485 for (unsigned OpIdx = 0, NumOperands = I0->getNumOperands(); 1486 OpIdx != NumOperands; ++OpIdx) { 1487 Operands[OpIdx].resize(NumLanes); 1488 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { 1489 auto *I = cast<Instruction>(Scalars[Lane]); 1490 assert(I->getNumOperands() == NumOperands && 1491 "Expected same number of operands"); 1492 Operands[OpIdx][Lane] = I->getOperand(OpIdx); 1493 } 1494 } 1495 } 1496 1497 /// \returns the \p OpIdx operand of this TreeEntry. 1498 ValueList &getOperand(unsigned OpIdx) { 1499 assert(OpIdx < Operands.size() && "Off bounds"); 1500 return Operands[OpIdx]; 1501 } 1502 1503 /// \returns the number of operands. 1504 unsigned getNumOperands() const { return Operands.size(); } 1505 1506 /// \return the single \p OpIdx operand. 1507 Value *getSingleOperand(unsigned OpIdx) const { 1508 assert(OpIdx < Operands.size() && "Off bounds"); 1509 assert(!Operands[OpIdx].empty() && "No operand available"); 1510 return Operands[OpIdx][0]; 1511 } 1512 1513 /// Some of the instructions in the list have alternate opcodes. 1514 bool isAltShuffle() const { 1515 return getOpcode() != getAltOpcode(); 1516 } 1517 1518 bool isOpcodeOrAlt(Instruction *I) const { 1519 unsigned CheckedOpcode = I->getOpcode(); 1520 return (getOpcode() == CheckedOpcode || 1521 getAltOpcode() == CheckedOpcode); 1522 } 1523 1524 /// Chooses the correct key for scheduling data. If \p Op has the same (or 1525 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is 1526 /// \p OpValue. 1527 Value *isOneOf(Value *Op) const { 1528 auto *I = dyn_cast<Instruction>(Op); 1529 if (I && isOpcodeOrAlt(I)) 1530 return Op; 1531 return MainOp; 1532 } 1533 1534 void setOperations(const InstructionsState &S) { 1535 MainOp = S.MainOp; 1536 AltOp = S.AltOp; 1537 } 1538 1539 Instruction *getMainOp() const { 1540 return MainOp; 1541 } 1542 1543 Instruction *getAltOp() const { 1544 return AltOp; 1545 } 1546 1547 /// The main/alternate opcodes for the list of instructions. 1548 unsigned getOpcode() const { 1549 return MainOp ? MainOp->getOpcode() : 0; 1550 } 1551 1552 unsigned getAltOpcode() const { 1553 return AltOp ? AltOp->getOpcode() : 0; 1554 } 1555 1556 /// Update operations state of this entry if reorder occurred. 1557 bool updateStateIfReorder() { 1558 if (ReorderIndices.empty()) 1559 return false; 1560 InstructionsState S = getSameOpcode(Scalars, ReorderIndices.front()); 1561 setOperations(S); 1562 return true; 1563 } 1564 1565 #ifndef NDEBUG 1566 /// Debug printer. 1567 LLVM_DUMP_METHOD void dump() const { 1568 dbgs() << Idx << ".\n"; 1569 for (unsigned OpI = 0, OpE = Operands.size(); OpI != OpE; ++OpI) { 1570 dbgs() << "Operand " << OpI << ":\n"; 1571 for (const Value *V : Operands[OpI]) 1572 dbgs().indent(2) << *V << "\n"; 1573 } 1574 dbgs() << "Scalars: \n"; 1575 for (Value *V : Scalars) 1576 dbgs().indent(2) << *V << "\n"; 1577 dbgs() << "NeedToGather: " << NeedToGather << "\n"; 1578 dbgs() << "MainOp: "; 1579 if (MainOp) 1580 dbgs() << *MainOp << "\n"; 1581 else 1582 dbgs() << "NULL\n"; 1583 dbgs() << "AltOp: "; 1584 if (AltOp) 1585 dbgs() << *AltOp << "\n"; 1586 else 1587 dbgs() << "NULL\n"; 1588 dbgs() << "VectorizedValue: "; 1589 if (VectorizedValue) 1590 dbgs() << *VectorizedValue << "\n"; 1591 else 1592 dbgs() << "NULL\n"; 1593 dbgs() << "ReuseShuffleIndices: "; 1594 if (ReuseShuffleIndices.empty()) 1595 dbgs() << "Emtpy"; 1596 else 1597 for (unsigned ReuseIdx : ReuseShuffleIndices) 1598 dbgs() << ReuseIdx << ", "; 1599 dbgs() << "\n"; 1600 dbgs() << "ReorderIndices: "; 1601 for (unsigned ReorderIdx : ReorderIndices) 1602 dbgs() << ReorderIdx << ", "; 1603 dbgs() << "\n"; 1604 dbgs() << "UserTreeIndices: "; 1605 for (const auto &EInfo : UserTreeIndices) 1606 dbgs() << EInfo << ", "; 1607 dbgs() << "\n"; 1608 } 1609 #endif 1610 }; 1611 1612 /// Create a new VectorizableTree entry. 1613 TreeEntry *newTreeEntry(ArrayRef<Value *> VL, Optional<ScheduleData *> Bundle, 1614 const InstructionsState &S, 1615 const EdgeInfo &UserTreeIdx, 1616 ArrayRef<unsigned> ReuseShuffleIndices = None, 1617 ArrayRef<unsigned> ReorderIndices = None) { 1618 bool Vectorized = (bool)Bundle; 1619 VectorizableTree.push_back(std::make_unique<TreeEntry>(VectorizableTree)); 1620 TreeEntry *Last = VectorizableTree.back().get(); 1621 Last->Idx = VectorizableTree.size() - 1; 1622 Last->Scalars.insert(Last->Scalars.begin(), VL.begin(), VL.end()); 1623 Last->NeedToGather = !Vectorized; 1624 Last->ReuseShuffleIndices.append(ReuseShuffleIndices.begin(), 1625 ReuseShuffleIndices.end()); 1626 Last->ReorderIndices = ReorderIndices; 1627 Last->setOperations(S); 1628 if (Vectorized) { 1629 for (int i = 0, e = VL.size(); i != e; ++i) { 1630 assert(!getTreeEntry(VL[i]) && "Scalar already in tree!"); 1631 ScalarToTreeEntry[VL[i]] = Last; 1632 } 1633 // Update the scheduler bundle to point to this TreeEntry. 1634 unsigned Lane = 0; 1635 for (ScheduleData *BundleMember = Bundle.getValue(); BundleMember; 1636 BundleMember = BundleMember->NextInBundle) { 1637 BundleMember->TE = Last; 1638 BundleMember->Lane = Lane; 1639 ++Lane; 1640 } 1641 assert((!Bundle.getValue() || Lane == VL.size()) && 1642 "Bundle and VL out of sync"); 1643 } else { 1644 MustGather.insert(VL.begin(), VL.end()); 1645 } 1646 1647 if (UserTreeIdx.UserTE) 1648 Last->UserTreeIndices.push_back(UserTreeIdx); 1649 1650 return Last; 1651 } 1652 1653 /// -- Vectorization State -- 1654 /// Holds all of the tree entries. 1655 TreeEntry::VecTreeTy VectorizableTree; 1656 1657 #ifndef NDEBUG 1658 /// Debug printer. 1659 LLVM_DUMP_METHOD void dumpVectorizableTree() const { 1660 for (unsigned Id = 0, IdE = VectorizableTree.size(); Id != IdE; ++Id) { 1661 VectorizableTree[Id]->dump(); 1662 dbgs() << "\n"; 1663 } 1664 } 1665 #endif 1666 1667 TreeEntry *getTreeEntry(Value *V) { 1668 auto I = ScalarToTreeEntry.find(V); 1669 if (I != ScalarToTreeEntry.end()) 1670 return I->second; 1671 return nullptr; 1672 } 1673 1674 const TreeEntry *getTreeEntry(Value *V) const { 1675 auto I = ScalarToTreeEntry.find(V); 1676 if (I != ScalarToTreeEntry.end()) 1677 return I->second; 1678 return nullptr; 1679 } 1680 1681 /// Maps a specific scalar to its tree entry. 1682 SmallDenseMap<Value*, TreeEntry *> ScalarToTreeEntry; 1683 1684 /// A list of scalars that we found that we need to keep as scalars. 1685 ValueSet MustGather; 1686 1687 /// This POD struct describes one external user in the vectorized tree. 1688 struct ExternalUser { 1689 ExternalUser(Value *S, llvm::User *U, int L) 1690 : Scalar(S), User(U), Lane(L) {} 1691 1692 // Which scalar in our function. 1693 Value *Scalar; 1694 1695 // Which user that uses the scalar. 1696 llvm::User *User; 1697 1698 // Which lane does the scalar belong to. 1699 int Lane; 1700 }; 1701 using UserList = SmallVector<ExternalUser, 16>; 1702 1703 /// Checks if two instructions may access the same memory. 1704 /// 1705 /// \p Loc1 is the location of \p Inst1. It is passed explicitly because it 1706 /// is invariant in the calling loop. 1707 bool isAliased(const MemoryLocation &Loc1, Instruction *Inst1, 1708 Instruction *Inst2) { 1709 // First check if the result is already in the cache. 1710 AliasCacheKey key = std::make_pair(Inst1, Inst2); 1711 Optional<bool> &result = AliasCache[key]; 1712 if (result.hasValue()) { 1713 return result.getValue(); 1714 } 1715 MemoryLocation Loc2 = getLocation(Inst2, AA); 1716 bool aliased = true; 1717 if (Loc1.Ptr && Loc2.Ptr && isSimple(Inst1) && isSimple(Inst2)) { 1718 // Do the alias check. 1719 aliased = AA->alias(Loc1, Loc2); 1720 } 1721 // Store the result in the cache. 1722 result = aliased; 1723 return aliased; 1724 } 1725 1726 using AliasCacheKey = std::pair<Instruction *, Instruction *>; 1727 1728 /// Cache for alias results. 1729 /// TODO: consider moving this to the AliasAnalysis itself. 1730 DenseMap<AliasCacheKey, Optional<bool>> AliasCache; 1731 1732 /// Removes an instruction from its block and eventually deletes it. 1733 /// It's like Instruction::eraseFromParent() except that the actual deletion 1734 /// is delayed until BoUpSLP is destructed. 1735 /// This is required to ensure that there are no incorrect collisions in the 1736 /// AliasCache, which can happen if a new instruction is allocated at the 1737 /// same address as a previously deleted instruction. 1738 void eraseInstruction(Instruction *I, bool ReplaceOpsWithUndef = false) { 1739 auto It = DeletedInstructions.try_emplace(I, ReplaceOpsWithUndef).first; 1740 It->getSecond() = It->getSecond() && ReplaceOpsWithUndef; 1741 } 1742 1743 /// Temporary store for deleted instructions. Instructions will be deleted 1744 /// eventually when the BoUpSLP is destructed. 1745 DenseMap<Instruction *, bool> DeletedInstructions; 1746 1747 /// A list of values that need to extracted out of the tree. 1748 /// This list holds pairs of (Internal Scalar : External User). External User 1749 /// can be nullptr, it means that this Internal Scalar will be used later, 1750 /// after vectorization. 1751 UserList ExternalUses; 1752 1753 /// Values used only by @llvm.assume calls. 1754 SmallPtrSet<const Value *, 32> EphValues; 1755 1756 /// Holds all of the instructions that we gathered. 1757 SetVector<Instruction *> GatherSeq; 1758 1759 /// A list of blocks that we are going to CSE. 1760 SetVector<BasicBlock *> CSEBlocks; 1761 1762 /// Contains all scheduling relevant data for an instruction. 1763 /// A ScheduleData either represents a single instruction or a member of an 1764 /// instruction bundle (= a group of instructions which is combined into a 1765 /// vector instruction). 1766 struct ScheduleData { 1767 // The initial value for the dependency counters. It means that the 1768 // dependencies are not calculated yet. 1769 enum { InvalidDeps = -1 }; 1770 1771 ScheduleData() = default; 1772 1773 void init(int BlockSchedulingRegionID, Value *OpVal) { 1774 FirstInBundle = this; 1775 NextInBundle = nullptr; 1776 NextLoadStore = nullptr; 1777 IsScheduled = false; 1778 SchedulingRegionID = BlockSchedulingRegionID; 1779 UnscheduledDepsInBundle = UnscheduledDeps; 1780 clearDependencies(); 1781 OpValue = OpVal; 1782 TE = nullptr; 1783 Lane = -1; 1784 } 1785 1786 /// Returns true if the dependency information has been calculated. 1787 bool hasValidDependencies() const { return Dependencies != InvalidDeps; } 1788 1789 /// Returns true for single instructions and for bundle representatives 1790 /// (= the head of a bundle). 1791 bool isSchedulingEntity() const { return FirstInBundle == this; } 1792 1793 /// Returns true if it represents an instruction bundle and not only a 1794 /// single instruction. 1795 bool isPartOfBundle() const { 1796 return NextInBundle != nullptr || FirstInBundle != this; 1797 } 1798 1799 /// Returns true if it is ready for scheduling, i.e. it has no more 1800 /// unscheduled depending instructions/bundles. 1801 bool isReady() const { 1802 assert(isSchedulingEntity() && 1803 "can't consider non-scheduling entity for ready list"); 1804 return UnscheduledDepsInBundle == 0 && !IsScheduled; 1805 } 1806 1807 /// Modifies the number of unscheduled dependencies, also updating it for 1808 /// the whole bundle. 1809 int incrementUnscheduledDeps(int Incr) { 1810 UnscheduledDeps += Incr; 1811 return FirstInBundle->UnscheduledDepsInBundle += Incr; 1812 } 1813 1814 /// Sets the number of unscheduled dependencies to the number of 1815 /// dependencies. 1816 void resetUnscheduledDeps() { 1817 incrementUnscheduledDeps(Dependencies - UnscheduledDeps); 1818 } 1819 1820 /// Clears all dependency information. 1821 void clearDependencies() { 1822 Dependencies = InvalidDeps; 1823 resetUnscheduledDeps(); 1824 MemoryDependencies.clear(); 1825 } 1826 1827 void dump(raw_ostream &os) const { 1828 if (!isSchedulingEntity()) { 1829 os << "/ " << *Inst; 1830 } else if (NextInBundle) { 1831 os << '[' << *Inst; 1832 ScheduleData *SD = NextInBundle; 1833 while (SD) { 1834 os << ';' << *SD->Inst; 1835 SD = SD->NextInBundle; 1836 } 1837 os << ']'; 1838 } else { 1839 os << *Inst; 1840 } 1841 } 1842 1843 Instruction *Inst = nullptr; 1844 1845 /// Points to the head in an instruction bundle (and always to this for 1846 /// single instructions). 1847 ScheduleData *FirstInBundle = nullptr; 1848 1849 /// Single linked list of all instructions in a bundle. Null if it is a 1850 /// single instruction. 1851 ScheduleData *NextInBundle = nullptr; 1852 1853 /// Single linked list of all memory instructions (e.g. load, store, call) 1854 /// in the block - until the end of the scheduling region. 1855 ScheduleData *NextLoadStore = nullptr; 1856 1857 /// The dependent memory instructions. 1858 /// This list is derived on demand in calculateDependencies(). 1859 SmallVector<ScheduleData *, 4> MemoryDependencies; 1860 1861 /// This ScheduleData is in the current scheduling region if this matches 1862 /// the current SchedulingRegionID of BlockScheduling. 1863 int SchedulingRegionID = 0; 1864 1865 /// Used for getting a "good" final ordering of instructions. 1866 int SchedulingPriority = 0; 1867 1868 /// The number of dependencies. Constitutes of the number of users of the 1869 /// instruction plus the number of dependent memory instructions (if any). 1870 /// This value is calculated on demand. 1871 /// If InvalidDeps, the number of dependencies is not calculated yet. 1872 int Dependencies = InvalidDeps; 1873 1874 /// The number of dependencies minus the number of dependencies of scheduled 1875 /// instructions. As soon as this is zero, the instruction/bundle gets ready 1876 /// for scheduling. 1877 /// Note that this is negative as long as Dependencies is not calculated. 1878 int UnscheduledDeps = InvalidDeps; 1879 1880 /// The sum of UnscheduledDeps in a bundle. Equals to UnscheduledDeps for 1881 /// single instructions. 1882 int UnscheduledDepsInBundle = InvalidDeps; 1883 1884 /// True if this instruction is scheduled (or considered as scheduled in the 1885 /// dry-run). 1886 bool IsScheduled = false; 1887 1888 /// Opcode of the current instruction in the schedule data. 1889 Value *OpValue = nullptr; 1890 1891 /// The TreeEntry that this instruction corresponds to. 1892 TreeEntry *TE = nullptr; 1893 1894 /// The lane of this node in the TreeEntry. 1895 int Lane = -1; 1896 }; 1897 1898 #ifndef NDEBUG 1899 friend inline raw_ostream &operator<<(raw_ostream &os, 1900 const BoUpSLP::ScheduleData &SD) { 1901 SD.dump(os); 1902 return os; 1903 } 1904 #endif 1905 1906 friend struct GraphTraits<BoUpSLP *>; 1907 friend struct DOTGraphTraits<BoUpSLP *>; 1908 1909 /// Contains all scheduling data for a basic block. 1910 struct BlockScheduling { 1911 BlockScheduling(BasicBlock *BB) 1912 : BB(BB), ChunkSize(BB->size()), ChunkPos(ChunkSize) {} 1913 1914 void clear() { 1915 ReadyInsts.clear(); 1916 ScheduleStart = nullptr; 1917 ScheduleEnd = nullptr; 1918 FirstLoadStoreInRegion = nullptr; 1919 LastLoadStoreInRegion = nullptr; 1920 1921 // Reduce the maximum schedule region size by the size of the 1922 // previous scheduling run. 1923 ScheduleRegionSizeLimit -= ScheduleRegionSize; 1924 if (ScheduleRegionSizeLimit < MinScheduleRegionSize) 1925 ScheduleRegionSizeLimit = MinScheduleRegionSize; 1926 ScheduleRegionSize = 0; 1927 1928 // Make a new scheduling region, i.e. all existing ScheduleData is not 1929 // in the new region yet. 1930 ++SchedulingRegionID; 1931 } 1932 1933 ScheduleData *getScheduleData(Value *V) { 1934 ScheduleData *SD = ScheduleDataMap[V]; 1935 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 1936 return SD; 1937 return nullptr; 1938 } 1939 1940 ScheduleData *getScheduleData(Value *V, Value *Key) { 1941 if (V == Key) 1942 return getScheduleData(V); 1943 auto I = ExtraScheduleDataMap.find(V); 1944 if (I != ExtraScheduleDataMap.end()) { 1945 ScheduleData *SD = I->second[Key]; 1946 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 1947 return SD; 1948 } 1949 return nullptr; 1950 } 1951 1952 bool isInSchedulingRegion(ScheduleData *SD) const { 1953 return SD->SchedulingRegionID == SchedulingRegionID; 1954 } 1955 1956 /// Marks an instruction as scheduled and puts all dependent ready 1957 /// instructions into the ready-list. 1958 template <typename ReadyListType> 1959 void schedule(ScheduleData *SD, ReadyListType &ReadyList) { 1960 SD->IsScheduled = true; 1961 LLVM_DEBUG(dbgs() << "SLP: schedule " << *SD << "\n"); 1962 1963 ScheduleData *BundleMember = SD; 1964 while (BundleMember) { 1965 if (BundleMember->Inst != BundleMember->OpValue) { 1966 BundleMember = BundleMember->NextInBundle; 1967 continue; 1968 } 1969 // Handle the def-use chain dependencies. 1970 1971 // Decrement the unscheduled counter and insert to ready list if ready. 1972 auto &&DecrUnsched = [this, &ReadyList](Instruction *I) { 1973 doForAllOpcodes(I, [&ReadyList](ScheduleData *OpDef) { 1974 if (OpDef && OpDef->hasValidDependencies() && 1975 OpDef->incrementUnscheduledDeps(-1) == 0) { 1976 // There are no more unscheduled dependencies after 1977 // decrementing, so we can put the dependent instruction 1978 // into the ready list. 1979 ScheduleData *DepBundle = OpDef->FirstInBundle; 1980 assert(!DepBundle->IsScheduled && 1981 "already scheduled bundle gets ready"); 1982 ReadyList.insert(DepBundle); 1983 LLVM_DEBUG(dbgs() 1984 << "SLP: gets ready (def): " << *DepBundle << "\n"); 1985 } 1986 }); 1987 }; 1988 1989 // If BundleMember is a vector bundle, its operands may have been 1990 // reordered duiring buildTree(). We therefore need to get its operands 1991 // through the TreeEntry. 1992 if (TreeEntry *TE = BundleMember->TE) { 1993 int Lane = BundleMember->Lane; 1994 assert(Lane >= 0 && "Lane not set"); 1995 for (unsigned OpIdx = 0, NumOperands = TE->getNumOperands(); 1996 OpIdx != NumOperands; ++OpIdx) 1997 if (auto *I = dyn_cast<Instruction>(TE->getOperand(OpIdx)[Lane])) 1998 DecrUnsched(I); 1999 } else { 2000 // If BundleMember is a stand-alone instruction, no operand reordering 2001 // has taken place, so we directly access its operands. 2002 for (Use &U : BundleMember->Inst->operands()) 2003 if (auto *I = dyn_cast<Instruction>(U.get())) 2004 DecrUnsched(I); 2005 } 2006 // Handle the memory dependencies. 2007 for (ScheduleData *MemoryDepSD : BundleMember->MemoryDependencies) { 2008 if (MemoryDepSD->incrementUnscheduledDeps(-1) == 0) { 2009 // There are no more unscheduled dependencies after decrementing, 2010 // so we can put the dependent instruction into the ready list. 2011 ScheduleData *DepBundle = MemoryDepSD->FirstInBundle; 2012 assert(!DepBundle->IsScheduled && 2013 "already scheduled bundle gets ready"); 2014 ReadyList.insert(DepBundle); 2015 LLVM_DEBUG(dbgs() 2016 << "SLP: gets ready (mem): " << *DepBundle << "\n"); 2017 } 2018 } 2019 BundleMember = BundleMember->NextInBundle; 2020 } 2021 } 2022 2023 void doForAllOpcodes(Value *V, 2024 function_ref<void(ScheduleData *SD)> Action) { 2025 if (ScheduleData *SD = getScheduleData(V)) 2026 Action(SD); 2027 auto I = ExtraScheduleDataMap.find(V); 2028 if (I != ExtraScheduleDataMap.end()) 2029 for (auto &P : I->second) 2030 if (P.second->SchedulingRegionID == SchedulingRegionID) 2031 Action(P.second); 2032 } 2033 2034 /// Put all instructions into the ReadyList which are ready for scheduling. 2035 template <typename ReadyListType> 2036 void initialFillReadyList(ReadyListType &ReadyList) { 2037 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 2038 doForAllOpcodes(I, [&](ScheduleData *SD) { 2039 if (SD->isSchedulingEntity() && SD->isReady()) { 2040 ReadyList.insert(SD); 2041 LLVM_DEBUG(dbgs() 2042 << "SLP: initially in ready list: " << *I << "\n"); 2043 } 2044 }); 2045 } 2046 } 2047 2048 /// Checks if a bundle of instructions can be scheduled, i.e. has no 2049 /// cyclic dependencies. This is only a dry-run, no instructions are 2050 /// actually moved at this stage. 2051 /// \returns the scheduling bundle. The returned Optional value is non-None 2052 /// if \p VL is allowed to be scheduled. 2053 Optional<ScheduleData *> 2054 tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 2055 const InstructionsState &S); 2056 2057 /// Un-bundles a group of instructions. 2058 void cancelScheduling(ArrayRef<Value *> VL, Value *OpValue); 2059 2060 /// Allocates schedule data chunk. 2061 ScheduleData *allocateScheduleDataChunks(); 2062 2063 /// Extends the scheduling region so that V is inside the region. 2064 /// \returns true if the region size is within the limit. 2065 bool extendSchedulingRegion(Value *V, const InstructionsState &S); 2066 2067 /// Initialize the ScheduleData structures for new instructions in the 2068 /// scheduling region. 2069 void initScheduleData(Instruction *FromI, Instruction *ToI, 2070 ScheduleData *PrevLoadStore, 2071 ScheduleData *NextLoadStore); 2072 2073 /// Updates the dependency information of a bundle and of all instructions/ 2074 /// bundles which depend on the original bundle. 2075 void calculateDependencies(ScheduleData *SD, bool InsertInReadyList, 2076 BoUpSLP *SLP); 2077 2078 /// Sets all instruction in the scheduling region to un-scheduled. 2079 void resetSchedule(); 2080 2081 BasicBlock *BB; 2082 2083 /// Simple memory allocation for ScheduleData. 2084 std::vector<std::unique_ptr<ScheduleData[]>> ScheduleDataChunks; 2085 2086 /// The size of a ScheduleData array in ScheduleDataChunks. 2087 int ChunkSize; 2088 2089 /// The allocator position in the current chunk, which is the last entry 2090 /// of ScheduleDataChunks. 2091 int ChunkPos; 2092 2093 /// Attaches ScheduleData to Instruction. 2094 /// Note that the mapping survives during all vectorization iterations, i.e. 2095 /// ScheduleData structures are recycled. 2096 DenseMap<Value *, ScheduleData *> ScheduleDataMap; 2097 2098 /// Attaches ScheduleData to Instruction with the leading key. 2099 DenseMap<Value *, SmallDenseMap<Value *, ScheduleData *>> 2100 ExtraScheduleDataMap; 2101 2102 struct ReadyList : SmallVector<ScheduleData *, 8> { 2103 void insert(ScheduleData *SD) { push_back(SD); } 2104 }; 2105 2106 /// The ready-list for scheduling (only used for the dry-run). 2107 ReadyList ReadyInsts; 2108 2109 /// The first instruction of the scheduling region. 2110 Instruction *ScheduleStart = nullptr; 2111 2112 /// The first instruction _after_ the scheduling region. 2113 Instruction *ScheduleEnd = nullptr; 2114 2115 /// The first memory accessing instruction in the scheduling region 2116 /// (can be null). 2117 ScheduleData *FirstLoadStoreInRegion = nullptr; 2118 2119 /// The last memory accessing instruction in the scheduling region 2120 /// (can be null). 2121 ScheduleData *LastLoadStoreInRegion = nullptr; 2122 2123 /// The current size of the scheduling region. 2124 int ScheduleRegionSize = 0; 2125 2126 /// The maximum size allowed for the scheduling region. 2127 int ScheduleRegionSizeLimit = ScheduleRegionSizeBudget; 2128 2129 /// The ID of the scheduling region. For a new vectorization iteration this 2130 /// is incremented which "removes" all ScheduleData from the region. 2131 // Make sure that the initial SchedulingRegionID is greater than the 2132 // initial SchedulingRegionID in ScheduleData (which is 0). 2133 int SchedulingRegionID = 1; 2134 }; 2135 2136 /// Attaches the BlockScheduling structures to basic blocks. 2137 MapVector<BasicBlock *, std::unique_ptr<BlockScheduling>> BlocksSchedules; 2138 2139 /// Performs the "real" scheduling. Done before vectorization is actually 2140 /// performed in a basic block. 2141 void scheduleBlock(BlockScheduling *BS); 2142 2143 /// List of users to ignore during scheduling and that don't need extracting. 2144 ArrayRef<Value *> UserIgnoreList; 2145 2146 using OrdersType = SmallVector<unsigned, 4>; 2147 /// A DenseMapInfo implementation for holding DenseMaps and DenseSets of 2148 /// sorted SmallVectors of unsigned. 2149 struct OrdersTypeDenseMapInfo { 2150 static OrdersType getEmptyKey() { 2151 OrdersType V; 2152 V.push_back(~1U); 2153 return V; 2154 } 2155 2156 static OrdersType getTombstoneKey() { 2157 OrdersType V; 2158 V.push_back(~2U); 2159 return V; 2160 } 2161 2162 static unsigned getHashValue(const OrdersType &V) { 2163 return static_cast<unsigned>(hash_combine_range(V.begin(), V.end())); 2164 } 2165 2166 static bool isEqual(const OrdersType &LHS, const OrdersType &RHS) { 2167 return LHS == RHS; 2168 } 2169 }; 2170 2171 /// Contains orders of operations along with the number of bundles that have 2172 /// operations in this order. It stores only those orders that require 2173 /// reordering, if reordering is not required it is counted using \a 2174 /// NumOpsWantToKeepOriginalOrder. 2175 DenseMap<OrdersType, unsigned, OrdersTypeDenseMapInfo> NumOpsWantToKeepOrder; 2176 /// Number of bundles that do not require reordering. 2177 unsigned NumOpsWantToKeepOriginalOrder = 0; 2178 2179 // Analysis and block reference. 2180 Function *F; 2181 ScalarEvolution *SE; 2182 TargetTransformInfo *TTI; 2183 TargetLibraryInfo *TLI; 2184 AliasAnalysis *AA; 2185 LoopInfo *LI; 2186 DominatorTree *DT; 2187 AssumptionCache *AC; 2188 DemandedBits *DB; 2189 const DataLayout *DL; 2190 OptimizationRemarkEmitter *ORE; 2191 2192 unsigned MaxVecRegSize; // This is set by TTI or overridden by cl::opt. 2193 unsigned MinVecRegSize; // Set by cl::opt (default: 128). 2194 2195 /// Instruction builder to construct the vectorized tree. 2196 IRBuilder<> Builder; 2197 2198 /// A map of scalar integer values to the smallest bit width with which they 2199 /// can legally be represented. The values map to (width, signed) pairs, 2200 /// where "width" indicates the minimum bit width and "signed" is True if the 2201 /// value must be signed-extended, rather than zero-extended, back to its 2202 /// original width. 2203 MapVector<Value *, std::pair<uint64_t, bool>> MinBWs; 2204 }; 2205 2206 } // end namespace slpvectorizer 2207 2208 template <> struct GraphTraits<BoUpSLP *> { 2209 using TreeEntry = BoUpSLP::TreeEntry; 2210 2211 /// NodeRef has to be a pointer per the GraphWriter. 2212 using NodeRef = TreeEntry *; 2213 2214 using ContainerTy = BoUpSLP::TreeEntry::VecTreeTy; 2215 2216 /// Add the VectorizableTree to the index iterator to be able to return 2217 /// TreeEntry pointers. 2218 struct ChildIteratorType 2219 : public iterator_adaptor_base< 2220 ChildIteratorType, SmallVector<BoUpSLP::EdgeInfo, 1>::iterator> { 2221 ContainerTy &VectorizableTree; 2222 2223 ChildIteratorType(SmallVector<BoUpSLP::EdgeInfo, 1>::iterator W, 2224 ContainerTy &VT) 2225 : ChildIteratorType::iterator_adaptor_base(W), VectorizableTree(VT) {} 2226 2227 NodeRef operator*() { return I->UserTE; } 2228 }; 2229 2230 static NodeRef getEntryNode(BoUpSLP &R) { 2231 return R.VectorizableTree[0].get(); 2232 } 2233 2234 static ChildIteratorType child_begin(NodeRef N) { 2235 return {N->UserTreeIndices.begin(), N->Container}; 2236 } 2237 2238 static ChildIteratorType child_end(NodeRef N) { 2239 return {N->UserTreeIndices.end(), N->Container}; 2240 } 2241 2242 /// For the node iterator we just need to turn the TreeEntry iterator into a 2243 /// TreeEntry* iterator so that it dereferences to NodeRef. 2244 class nodes_iterator { 2245 using ItTy = ContainerTy::iterator; 2246 ItTy It; 2247 2248 public: 2249 nodes_iterator(const ItTy &It2) : It(It2) {} 2250 NodeRef operator*() { return It->get(); } 2251 nodes_iterator operator++() { 2252 ++It; 2253 return *this; 2254 } 2255 bool operator!=(const nodes_iterator &N2) const { return N2.It != It; } 2256 }; 2257 2258 static nodes_iterator nodes_begin(BoUpSLP *R) { 2259 return nodes_iterator(R->VectorizableTree.begin()); 2260 } 2261 2262 static nodes_iterator nodes_end(BoUpSLP *R) { 2263 return nodes_iterator(R->VectorizableTree.end()); 2264 } 2265 2266 static unsigned size(BoUpSLP *R) { return R->VectorizableTree.size(); } 2267 }; 2268 2269 template <> struct DOTGraphTraits<BoUpSLP *> : public DefaultDOTGraphTraits { 2270 using TreeEntry = BoUpSLP::TreeEntry; 2271 2272 DOTGraphTraits(bool isSimple = false) : DefaultDOTGraphTraits(isSimple) {} 2273 2274 std::string getNodeLabel(const TreeEntry *Entry, const BoUpSLP *R) { 2275 std::string Str; 2276 raw_string_ostream OS(Str); 2277 if (isSplat(Entry->Scalars)) { 2278 OS << "<splat> " << *Entry->Scalars[0]; 2279 return Str; 2280 } 2281 for (auto V : Entry->Scalars) { 2282 OS << *V; 2283 if (std::any_of( 2284 R->ExternalUses.begin(), R->ExternalUses.end(), 2285 [&](const BoUpSLP::ExternalUser &EU) { return EU.Scalar == V; })) 2286 OS << " <extract>"; 2287 OS << "\n"; 2288 } 2289 return Str; 2290 } 2291 2292 static std::string getNodeAttributes(const TreeEntry *Entry, 2293 const BoUpSLP *) { 2294 if (Entry->NeedToGather) 2295 return "color=red"; 2296 return ""; 2297 } 2298 }; 2299 2300 } // end namespace llvm 2301 2302 BoUpSLP::~BoUpSLP() { 2303 for (const auto &Pair : DeletedInstructions) { 2304 // Replace operands of ignored instructions with Undefs in case if they were 2305 // marked for deletion. 2306 if (Pair.getSecond()) { 2307 Value *Undef = UndefValue::get(Pair.getFirst()->getType()); 2308 Pair.getFirst()->replaceAllUsesWith(Undef); 2309 } 2310 Pair.getFirst()->dropAllReferences(); 2311 } 2312 for (const auto &Pair : DeletedInstructions) { 2313 assert(Pair.getFirst()->use_empty() && 2314 "trying to erase instruction with users."); 2315 Pair.getFirst()->eraseFromParent(); 2316 } 2317 } 2318 2319 void BoUpSLP::eraseInstructions(ArrayRef<Value *> AV) { 2320 for (auto *V : AV) { 2321 if (auto *I = dyn_cast<Instruction>(V)) 2322 eraseInstruction(I, /*ReplaceWithUndef=*/true); 2323 }; 2324 } 2325 2326 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2327 ArrayRef<Value *> UserIgnoreLst) { 2328 ExtraValueToDebugLocsMap ExternallyUsedValues; 2329 buildTree(Roots, ExternallyUsedValues, UserIgnoreLst); 2330 } 2331 2332 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2333 ExtraValueToDebugLocsMap &ExternallyUsedValues, 2334 ArrayRef<Value *> UserIgnoreLst) { 2335 deleteTree(); 2336 UserIgnoreList = UserIgnoreLst; 2337 if (!allSameType(Roots)) 2338 return; 2339 buildTree_rec(Roots, 0, EdgeInfo()); 2340 2341 // Collect the values that we need to extract from the tree. 2342 for (auto &TEPtr : VectorizableTree) { 2343 TreeEntry *Entry = TEPtr.get(); 2344 2345 // No need to handle users of gathered values. 2346 if (Entry->NeedToGather) 2347 continue; 2348 2349 // For each lane: 2350 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 2351 Value *Scalar = Entry->Scalars[Lane]; 2352 int FoundLane = Lane; 2353 if (!Entry->ReuseShuffleIndices.empty()) { 2354 FoundLane = 2355 std::distance(Entry->ReuseShuffleIndices.begin(), 2356 llvm::find(Entry->ReuseShuffleIndices, FoundLane)); 2357 } 2358 2359 // Check if the scalar is externally used as an extra arg. 2360 auto ExtI = ExternallyUsedValues.find(Scalar); 2361 if (ExtI != ExternallyUsedValues.end()) { 2362 LLVM_DEBUG(dbgs() << "SLP: Need to extract: Extra arg from lane " 2363 << Lane << " from " << *Scalar << ".\n"); 2364 ExternalUses.emplace_back(Scalar, nullptr, FoundLane); 2365 } 2366 for (User *U : Scalar->users()) { 2367 LLVM_DEBUG(dbgs() << "SLP: Checking user:" << *U << ".\n"); 2368 2369 Instruction *UserInst = dyn_cast<Instruction>(U); 2370 if (!UserInst) 2371 continue; 2372 2373 // Skip in-tree scalars that become vectors 2374 if (TreeEntry *UseEntry = getTreeEntry(U)) { 2375 Value *UseScalar = UseEntry->Scalars[0]; 2376 // Some in-tree scalars will remain as scalar in vectorized 2377 // instructions. If that is the case, the one in Lane 0 will 2378 // be used. 2379 if (UseScalar != U || 2380 !InTreeUserNeedToExtract(Scalar, UserInst, TLI)) { 2381 LLVM_DEBUG(dbgs() << "SLP: \tInternal user will be removed:" << *U 2382 << ".\n"); 2383 assert(!UseEntry->NeedToGather && "Bad state"); 2384 continue; 2385 } 2386 } 2387 2388 // Ignore users in the user ignore list. 2389 if (is_contained(UserIgnoreList, UserInst)) 2390 continue; 2391 2392 LLVM_DEBUG(dbgs() << "SLP: Need to extract:" << *U << " from lane " 2393 << Lane << " from " << *Scalar << ".\n"); 2394 ExternalUses.push_back(ExternalUser(Scalar, U, FoundLane)); 2395 } 2396 } 2397 } 2398 } 2399 2400 void BoUpSLP::buildTree_rec(ArrayRef<Value *> VL, unsigned Depth, 2401 const EdgeInfo &UserTreeIdx) { 2402 assert((allConstant(VL) || allSameType(VL)) && "Invalid types!"); 2403 2404 InstructionsState S = getSameOpcode(VL); 2405 if (Depth == RecursionMaxDepth) { 2406 LLVM_DEBUG(dbgs() << "SLP: Gathering due to max recursion depth.\n"); 2407 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2408 return; 2409 } 2410 2411 // Don't handle vectors. 2412 if (S.OpValue->getType()->isVectorTy()) { 2413 LLVM_DEBUG(dbgs() << "SLP: Gathering due to vector type.\n"); 2414 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2415 return; 2416 } 2417 2418 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) 2419 if (SI->getValueOperand()->getType()->isVectorTy()) { 2420 LLVM_DEBUG(dbgs() << "SLP: Gathering due to store vector type.\n"); 2421 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2422 return; 2423 } 2424 2425 // If all of the operands are identical or constant we have a simple solution. 2426 if (allConstant(VL) || isSplat(VL) || !allSameBlock(VL) || !S.getOpcode()) { 2427 LLVM_DEBUG(dbgs() << "SLP: Gathering due to C,S,B,O. \n"); 2428 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2429 return; 2430 } 2431 2432 // We now know that this is a vector of instructions of the same type from 2433 // the same block. 2434 2435 // Don't vectorize ephemeral values. 2436 for (Value *V : VL) { 2437 if (EphValues.count(V)) { 2438 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2439 << ") is ephemeral.\n"); 2440 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2441 return; 2442 } 2443 } 2444 2445 // Check if this is a duplicate of another entry. 2446 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 2447 LLVM_DEBUG(dbgs() << "SLP: \tChecking bundle: " << *S.OpValue << ".\n"); 2448 if (!E->isSame(VL)) { 2449 LLVM_DEBUG(dbgs() << "SLP: Gathering due to partial overlap.\n"); 2450 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2451 return; 2452 } 2453 // Record the reuse of the tree node. FIXME, currently this is only used to 2454 // properly draw the graph rather than for the actual vectorization. 2455 E->UserTreeIndices.push_back(UserTreeIdx); 2456 LLVM_DEBUG(dbgs() << "SLP: Perfect diamond merge at " << *S.OpValue 2457 << ".\n"); 2458 return; 2459 } 2460 2461 // Check that none of the instructions in the bundle are already in the tree. 2462 for (Value *V : VL) { 2463 auto *I = dyn_cast<Instruction>(V); 2464 if (!I) 2465 continue; 2466 if (getTreeEntry(I)) { 2467 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2468 << ") is already in tree.\n"); 2469 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2470 return; 2471 } 2472 } 2473 2474 // If any of the scalars is marked as a value that needs to stay scalar, then 2475 // we need to gather the scalars. 2476 // The reduction nodes (stored in UserIgnoreList) also should stay scalar. 2477 for (Value *V : VL) { 2478 if (MustGather.count(V) || is_contained(UserIgnoreList, V)) { 2479 LLVM_DEBUG(dbgs() << "SLP: Gathering due to gathered scalar.\n"); 2480 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2481 return; 2482 } 2483 } 2484 2485 // Check that all of the users of the scalars that we want to vectorize are 2486 // schedulable. 2487 auto *VL0 = cast<Instruction>(S.OpValue); 2488 BasicBlock *BB = VL0->getParent(); 2489 2490 if (!DT->isReachableFromEntry(BB)) { 2491 // Don't go into unreachable blocks. They may contain instructions with 2492 // dependency cycles which confuse the final scheduling. 2493 LLVM_DEBUG(dbgs() << "SLP: bundle in unreachable block.\n"); 2494 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2495 return; 2496 } 2497 2498 // Check that every instruction appears once in this bundle. 2499 SmallVector<unsigned, 4> ReuseShuffleIndicies; 2500 SmallVector<Value *, 4> UniqueValues; 2501 DenseMap<Value *, unsigned> UniquePositions; 2502 for (Value *V : VL) { 2503 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 2504 ReuseShuffleIndicies.emplace_back(Res.first->second); 2505 if (Res.second) 2506 UniqueValues.emplace_back(V); 2507 } 2508 size_t NumUniqueScalarValues = UniqueValues.size(); 2509 if (NumUniqueScalarValues == VL.size()) { 2510 ReuseShuffleIndicies.clear(); 2511 } else { 2512 LLVM_DEBUG(dbgs() << "SLP: Shuffle for reused scalars.\n"); 2513 if (NumUniqueScalarValues <= 1 || 2514 !llvm::isPowerOf2_32(NumUniqueScalarValues)) { 2515 LLVM_DEBUG(dbgs() << "SLP: Scalar used twice in bundle.\n"); 2516 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2517 return; 2518 } 2519 VL = UniqueValues; 2520 } 2521 2522 auto &BSRef = BlocksSchedules[BB]; 2523 if (!BSRef) 2524 BSRef = std::make_unique<BlockScheduling>(BB); 2525 2526 BlockScheduling &BS = *BSRef.get(); 2527 2528 Optional<ScheduleData *> Bundle = BS.tryScheduleBundle(VL, this, S); 2529 if (!Bundle) { 2530 LLVM_DEBUG(dbgs() << "SLP: We are not able to schedule this bundle!\n"); 2531 assert((!BS.getScheduleData(VL0) || 2532 !BS.getScheduleData(VL0)->isPartOfBundle()) && 2533 "tryScheduleBundle should cancelScheduling on failure"); 2534 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2535 ReuseShuffleIndicies); 2536 return; 2537 } 2538 LLVM_DEBUG(dbgs() << "SLP: We are able to schedule this bundle.\n"); 2539 2540 unsigned ShuffleOrOp = S.isAltShuffle() ? 2541 (unsigned) Instruction::ShuffleVector : S.getOpcode(); 2542 switch (ShuffleOrOp) { 2543 case Instruction::PHI: { 2544 auto *PH = cast<PHINode>(VL0); 2545 2546 // Check for terminator values (e.g. invoke). 2547 for (unsigned j = 0; j < VL.size(); ++j) 2548 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 2549 Instruction *Term = dyn_cast<Instruction>( 2550 cast<PHINode>(VL[j])->getIncomingValueForBlock( 2551 PH->getIncomingBlock(i))); 2552 if (Term && Term->isTerminator()) { 2553 LLVM_DEBUG(dbgs() 2554 << "SLP: Need to swizzle PHINodes (terminator use).\n"); 2555 BS.cancelScheduling(VL, VL0); 2556 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2557 ReuseShuffleIndicies); 2558 return; 2559 } 2560 } 2561 2562 TreeEntry *TE = 2563 newTreeEntry(VL, Bundle, S, UserTreeIdx, ReuseShuffleIndicies); 2564 LLVM_DEBUG(dbgs() << "SLP: added a vector of PHINodes.\n"); 2565 2566 // Keeps the reordered operands to avoid code duplication. 2567 SmallVector<ValueList, 2> OperandsVec; 2568 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 2569 ValueList Operands; 2570 // Prepare the operand vector. 2571 for (Value *j : VL) 2572 Operands.push_back(cast<PHINode>(j)->getIncomingValueForBlock( 2573 PH->getIncomingBlock(i))); 2574 TE->setOperand(i, Operands); 2575 OperandsVec.push_back(Operands); 2576 } 2577 for (unsigned OpIdx = 0, OpE = OperandsVec.size(); OpIdx != OpE; ++OpIdx) 2578 buildTree_rec(OperandsVec[OpIdx], Depth + 1, {TE, OpIdx}); 2579 return; 2580 } 2581 case Instruction::ExtractValue: 2582 case Instruction::ExtractElement: { 2583 OrdersType CurrentOrder; 2584 bool Reuse = canReuseExtract(VL, VL0, CurrentOrder); 2585 if (Reuse) { 2586 LLVM_DEBUG(dbgs() << "SLP: Reusing or shuffling extract sequence.\n"); 2587 ++NumOpsWantToKeepOriginalOrder; 2588 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2589 ReuseShuffleIndicies); 2590 // This is a special case, as it does not gather, but at the same time 2591 // we are not extending buildTree_rec() towards the operands. 2592 ValueList Op0; 2593 Op0.assign(VL.size(), VL0->getOperand(0)); 2594 VectorizableTree.back()->setOperand(0, Op0); 2595 return; 2596 } 2597 if (!CurrentOrder.empty()) { 2598 LLVM_DEBUG({ 2599 dbgs() << "SLP: Reusing or shuffling of reordered extract sequence " 2600 "with order"; 2601 for (unsigned Idx : CurrentOrder) 2602 dbgs() << " " << Idx; 2603 dbgs() << "\n"; 2604 }); 2605 // Insert new order with initial value 0, if it does not exist, 2606 // otherwise return the iterator to the existing one. 2607 auto StoredCurrentOrderAndNum = 2608 NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first; 2609 ++StoredCurrentOrderAndNum->getSecond(); 2610 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2611 ReuseShuffleIndicies, 2612 StoredCurrentOrderAndNum->getFirst()); 2613 // This is a special case, as it does not gather, but at the same time 2614 // we are not extending buildTree_rec() towards the operands. 2615 ValueList Op0; 2616 Op0.assign(VL.size(), VL0->getOperand(0)); 2617 VectorizableTree.back()->setOperand(0, Op0); 2618 return; 2619 } 2620 LLVM_DEBUG(dbgs() << "SLP: Gather extract sequence.\n"); 2621 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2622 ReuseShuffleIndicies); 2623 BS.cancelScheduling(VL, VL0); 2624 return; 2625 } 2626 case Instruction::Load: { 2627 // Check that a vectorized load would load the same memory as a scalar 2628 // load. For example, we don't want to vectorize loads that are smaller 2629 // than 8-bit. Even though we have a packed struct {<i2, i2, i2, i2>} LLVM 2630 // treats loading/storing it as an i8 struct. If we vectorize loads/stores 2631 // from such a struct, we read/write packed bits disagreeing with the 2632 // unvectorized version. 2633 Type *ScalarTy = VL0->getType(); 2634 2635 if (DL->getTypeSizeInBits(ScalarTy) != 2636 DL->getTypeAllocSizeInBits(ScalarTy)) { 2637 BS.cancelScheduling(VL, VL0); 2638 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2639 ReuseShuffleIndicies); 2640 LLVM_DEBUG(dbgs() << "SLP: Gathering loads of non-packed type.\n"); 2641 return; 2642 } 2643 2644 // Make sure all loads in the bundle are simple - we can't vectorize 2645 // atomic or volatile loads. 2646 SmallVector<Value *, 4> PointerOps(VL.size()); 2647 auto POIter = PointerOps.begin(); 2648 for (Value *V : VL) { 2649 auto *L = cast<LoadInst>(V); 2650 if (!L->isSimple()) { 2651 BS.cancelScheduling(VL, VL0); 2652 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2653 ReuseShuffleIndicies); 2654 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple loads.\n"); 2655 return; 2656 } 2657 *POIter = L->getPointerOperand(); 2658 ++POIter; 2659 } 2660 2661 OrdersType CurrentOrder; 2662 // Check the order of pointer operands. 2663 if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) { 2664 Value *Ptr0; 2665 Value *PtrN; 2666 if (CurrentOrder.empty()) { 2667 Ptr0 = PointerOps.front(); 2668 PtrN = PointerOps.back(); 2669 } else { 2670 Ptr0 = PointerOps[CurrentOrder.front()]; 2671 PtrN = PointerOps[CurrentOrder.back()]; 2672 } 2673 const SCEV *Scev0 = SE->getSCEV(Ptr0); 2674 const SCEV *ScevN = SE->getSCEV(PtrN); 2675 const auto *Diff = 2676 dyn_cast<SCEVConstant>(SE->getMinusSCEV(ScevN, Scev0)); 2677 uint64_t Size = DL->getTypeAllocSize(ScalarTy); 2678 // Check that the sorted loads are consecutive. 2679 if (Diff && Diff->getAPInt() == (VL.size() - 1) * Size) { 2680 if (CurrentOrder.empty()) { 2681 // Original loads are consecutive and does not require reordering. 2682 ++NumOpsWantToKeepOriginalOrder; 2683 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, 2684 UserTreeIdx, ReuseShuffleIndicies); 2685 TE->setOperandsInOrder(); 2686 LLVM_DEBUG(dbgs() << "SLP: added a vector of loads.\n"); 2687 } else { 2688 // Need to reorder. 2689 auto I = NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first; 2690 ++I->getSecond(); 2691 TreeEntry *TE = 2692 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2693 ReuseShuffleIndicies, I->getFirst()); 2694 TE->setOperandsInOrder(); 2695 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled loads.\n"); 2696 } 2697 return; 2698 } 2699 } 2700 2701 LLVM_DEBUG(dbgs() << "SLP: Gathering non-consecutive loads.\n"); 2702 BS.cancelScheduling(VL, VL0); 2703 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2704 ReuseShuffleIndicies); 2705 return; 2706 } 2707 case Instruction::ZExt: 2708 case Instruction::SExt: 2709 case Instruction::FPToUI: 2710 case Instruction::FPToSI: 2711 case Instruction::FPExt: 2712 case Instruction::PtrToInt: 2713 case Instruction::IntToPtr: 2714 case Instruction::SIToFP: 2715 case Instruction::UIToFP: 2716 case Instruction::Trunc: 2717 case Instruction::FPTrunc: 2718 case Instruction::BitCast: { 2719 Type *SrcTy = VL0->getOperand(0)->getType(); 2720 for (Value *V : VL) { 2721 Type *Ty = cast<Instruction>(V)->getOperand(0)->getType(); 2722 if (Ty != SrcTy || !isValidElementType(Ty)) { 2723 BS.cancelScheduling(VL, VL0); 2724 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2725 ReuseShuffleIndicies); 2726 LLVM_DEBUG(dbgs() 2727 << "SLP: Gathering casts with different src types.\n"); 2728 return; 2729 } 2730 } 2731 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2732 ReuseShuffleIndicies); 2733 LLVM_DEBUG(dbgs() << "SLP: added a vector of casts.\n"); 2734 2735 TE->setOperandsInOrder(); 2736 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 2737 ValueList Operands; 2738 // Prepare the operand vector. 2739 for (Value *V : VL) 2740 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 2741 2742 buildTree_rec(Operands, Depth + 1, {TE, i}); 2743 } 2744 return; 2745 } 2746 case Instruction::ICmp: 2747 case Instruction::FCmp: { 2748 // Check that all of the compares have the same predicate. 2749 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 2750 CmpInst::Predicate SwapP0 = CmpInst::getSwappedPredicate(P0); 2751 Type *ComparedTy = VL0->getOperand(0)->getType(); 2752 for (Value *V : VL) { 2753 CmpInst *Cmp = cast<CmpInst>(V); 2754 if ((Cmp->getPredicate() != P0 && Cmp->getPredicate() != SwapP0) || 2755 Cmp->getOperand(0)->getType() != ComparedTy) { 2756 BS.cancelScheduling(VL, VL0); 2757 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2758 ReuseShuffleIndicies); 2759 LLVM_DEBUG(dbgs() 2760 << "SLP: Gathering cmp with different predicate.\n"); 2761 return; 2762 } 2763 } 2764 2765 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2766 ReuseShuffleIndicies); 2767 LLVM_DEBUG(dbgs() << "SLP: added a vector of compares.\n"); 2768 2769 ValueList Left, Right; 2770 if (cast<CmpInst>(VL0)->isCommutative()) { 2771 // Commutative predicate - collect + sort operands of the instructions 2772 // so that each side is more likely to have the same opcode. 2773 assert(P0 == SwapP0 && "Commutative Predicate mismatch"); 2774 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 2775 } else { 2776 // Collect operands - commute if it uses the swapped predicate. 2777 for (Value *V : VL) { 2778 auto *Cmp = cast<CmpInst>(V); 2779 Value *LHS = Cmp->getOperand(0); 2780 Value *RHS = Cmp->getOperand(1); 2781 if (Cmp->getPredicate() != P0) 2782 std::swap(LHS, RHS); 2783 Left.push_back(LHS); 2784 Right.push_back(RHS); 2785 } 2786 } 2787 TE->setOperand(0, Left); 2788 TE->setOperand(1, Right); 2789 buildTree_rec(Left, Depth + 1, {TE, 0}); 2790 buildTree_rec(Right, Depth + 1, {TE, 1}); 2791 return; 2792 } 2793 case Instruction::Select: 2794 case Instruction::FNeg: 2795 case Instruction::Add: 2796 case Instruction::FAdd: 2797 case Instruction::Sub: 2798 case Instruction::FSub: 2799 case Instruction::Mul: 2800 case Instruction::FMul: 2801 case Instruction::UDiv: 2802 case Instruction::SDiv: 2803 case Instruction::FDiv: 2804 case Instruction::URem: 2805 case Instruction::SRem: 2806 case Instruction::FRem: 2807 case Instruction::Shl: 2808 case Instruction::LShr: 2809 case Instruction::AShr: 2810 case Instruction::And: 2811 case Instruction::Or: 2812 case Instruction::Xor: { 2813 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2814 ReuseShuffleIndicies); 2815 LLVM_DEBUG(dbgs() << "SLP: added a vector of un/bin op.\n"); 2816 2817 // Sort operands of the instructions so that each side is more likely to 2818 // have the same opcode. 2819 if (isa<BinaryOperator>(VL0) && VL0->isCommutative()) { 2820 ValueList Left, Right; 2821 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 2822 TE->setOperand(0, Left); 2823 TE->setOperand(1, Right); 2824 buildTree_rec(Left, Depth + 1, {TE, 0}); 2825 buildTree_rec(Right, Depth + 1, {TE, 1}); 2826 return; 2827 } 2828 2829 TE->setOperandsInOrder(); 2830 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 2831 ValueList Operands; 2832 // Prepare the operand vector. 2833 for (Value *j : VL) 2834 Operands.push_back(cast<Instruction>(j)->getOperand(i)); 2835 2836 buildTree_rec(Operands, Depth + 1, {TE, i}); 2837 } 2838 return; 2839 } 2840 case Instruction::GetElementPtr: { 2841 // We don't combine GEPs with complicated (nested) indexing. 2842 for (Value *V : VL) { 2843 if (cast<Instruction>(V)->getNumOperands() != 2) { 2844 LLVM_DEBUG(dbgs() << "SLP: not-vectorizable GEP (nested indexes).\n"); 2845 BS.cancelScheduling(VL, VL0); 2846 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2847 ReuseShuffleIndicies); 2848 return; 2849 } 2850 } 2851 2852 // We can't combine several GEPs into one vector if they operate on 2853 // different types. 2854 Type *Ty0 = VL0->getOperand(0)->getType(); 2855 for (Value *V : VL) { 2856 Type *CurTy = cast<Instruction>(V)->getOperand(0)->getType(); 2857 if (Ty0 != CurTy) { 2858 LLVM_DEBUG(dbgs() 2859 << "SLP: not-vectorizable GEP (different types).\n"); 2860 BS.cancelScheduling(VL, VL0); 2861 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2862 ReuseShuffleIndicies); 2863 return; 2864 } 2865 } 2866 2867 // We don't combine GEPs with non-constant indexes. 2868 Type *Ty1 = VL0->getOperand(1)->getType(); 2869 for (Value *V : VL) { 2870 auto Op = cast<Instruction>(V)->getOperand(1); 2871 if (!isa<ConstantInt>(Op) || 2872 (Op->getType() != Ty1 && 2873 Op->getType()->getScalarSizeInBits() > 2874 DL->getIndexSizeInBits( 2875 V->getType()->getPointerAddressSpace()))) { 2876 LLVM_DEBUG(dbgs() 2877 << "SLP: not-vectorizable GEP (non-constant indexes).\n"); 2878 BS.cancelScheduling(VL, VL0); 2879 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2880 ReuseShuffleIndicies); 2881 return; 2882 } 2883 } 2884 2885 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2886 ReuseShuffleIndicies); 2887 LLVM_DEBUG(dbgs() << "SLP: added a vector of GEPs.\n"); 2888 TE->setOperandsInOrder(); 2889 for (unsigned i = 0, e = 2; i < e; ++i) { 2890 ValueList Operands; 2891 // Prepare the operand vector. 2892 for (Value *V : VL) 2893 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 2894 2895 buildTree_rec(Operands, Depth + 1, {TE, i}); 2896 } 2897 return; 2898 } 2899 case Instruction::Store: { 2900 // Check if the stores are consecutive or if we need to swizzle them. 2901 llvm::Type *ScalarTy = cast<StoreInst>(VL0)->getValueOperand()->getType(); 2902 // Make sure all stores in the bundle are simple - we can't vectorize 2903 // atomic or volatile stores. 2904 SmallVector<Value *, 4> PointerOps(VL.size()); 2905 ValueList Operands(VL.size()); 2906 auto POIter = PointerOps.begin(); 2907 auto OIter = Operands.begin(); 2908 for (Value *V : VL) { 2909 auto *SI = cast<StoreInst>(V); 2910 if (!SI->isSimple()) { 2911 BS.cancelScheduling(VL, VL0); 2912 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2913 ReuseShuffleIndicies); 2914 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple stores.\n"); 2915 return; 2916 } 2917 *POIter = SI->getPointerOperand(); 2918 *OIter = SI->getValueOperand(); 2919 ++POIter; 2920 ++OIter; 2921 } 2922 2923 OrdersType CurrentOrder; 2924 // Check the order of pointer operands. 2925 if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) { 2926 Value *Ptr0; 2927 Value *PtrN; 2928 if (CurrentOrder.empty()) { 2929 Ptr0 = PointerOps.front(); 2930 PtrN = PointerOps.back(); 2931 } else { 2932 Ptr0 = PointerOps[CurrentOrder.front()]; 2933 PtrN = PointerOps[CurrentOrder.back()]; 2934 } 2935 const SCEV *Scev0 = SE->getSCEV(Ptr0); 2936 const SCEV *ScevN = SE->getSCEV(PtrN); 2937 const auto *Diff = 2938 dyn_cast<SCEVConstant>(SE->getMinusSCEV(ScevN, Scev0)); 2939 uint64_t Size = DL->getTypeAllocSize(ScalarTy); 2940 // Check that the sorted pointer operands are consecutive. 2941 if (Diff && Diff->getAPInt() == (VL.size() - 1) * Size) { 2942 if (CurrentOrder.empty()) { 2943 // Original stores are consecutive and does not require reordering. 2944 ++NumOpsWantToKeepOriginalOrder; 2945 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, 2946 UserTreeIdx, ReuseShuffleIndicies); 2947 TE->setOperandsInOrder(); 2948 buildTree_rec(Operands, Depth + 1, {TE, 0}); 2949 LLVM_DEBUG(dbgs() << "SLP: added a vector of stores.\n"); 2950 } else { 2951 // Need to reorder. 2952 auto I = NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first; 2953 ++(I->getSecond()); 2954 TreeEntry *TE = 2955 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2956 ReuseShuffleIndicies, I->getFirst()); 2957 TE->setOperandsInOrder(); 2958 buildTree_rec(Operands, Depth + 1, {TE, 0}); 2959 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled stores.\n"); 2960 } 2961 return; 2962 } 2963 } 2964 2965 BS.cancelScheduling(VL, VL0); 2966 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2967 ReuseShuffleIndicies); 2968 LLVM_DEBUG(dbgs() << "SLP: Non-consecutive store.\n"); 2969 return; 2970 } 2971 case Instruction::Call: { 2972 // Check if the calls are all to the same vectorizable intrinsic. 2973 CallInst *CI = cast<CallInst>(VL0); 2974 // Check if this is an Intrinsic call or something that can be 2975 // represented by an intrinsic call 2976 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 2977 if (!isTriviallyVectorizable(ID)) { 2978 BS.cancelScheduling(VL, VL0); 2979 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2980 ReuseShuffleIndicies); 2981 LLVM_DEBUG(dbgs() << "SLP: Non-vectorizable call.\n"); 2982 return; 2983 } 2984 Function *Int = CI->getCalledFunction(); 2985 unsigned NumArgs = CI->getNumArgOperands(); 2986 SmallVector<Value*, 4> ScalarArgs(NumArgs, nullptr); 2987 for (unsigned j = 0; j != NumArgs; ++j) 2988 if (hasVectorInstrinsicScalarOpd(ID, j)) 2989 ScalarArgs[j] = CI->getArgOperand(j); 2990 for (Value *V : VL) { 2991 CallInst *CI2 = dyn_cast<CallInst>(V); 2992 if (!CI2 || CI2->getCalledFunction() != Int || 2993 getVectorIntrinsicIDForCall(CI2, TLI) != ID || 2994 !CI->hasIdenticalOperandBundleSchema(*CI2)) { 2995 BS.cancelScheduling(VL, VL0); 2996 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2997 ReuseShuffleIndicies); 2998 LLVM_DEBUG(dbgs() << "SLP: mismatched calls:" << *CI << "!=" << *V 2999 << "\n"); 3000 return; 3001 } 3002 // Some intrinsics have scalar arguments and should be same in order for 3003 // them to be vectorized. 3004 for (unsigned j = 0; j != NumArgs; ++j) { 3005 if (hasVectorInstrinsicScalarOpd(ID, j)) { 3006 Value *A1J = CI2->getArgOperand(j); 3007 if (ScalarArgs[j] != A1J) { 3008 BS.cancelScheduling(VL, VL0); 3009 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3010 ReuseShuffleIndicies); 3011 LLVM_DEBUG(dbgs() << "SLP: mismatched arguments in call:" << *CI 3012 << " argument " << ScalarArgs[j] << "!=" << A1J 3013 << "\n"); 3014 return; 3015 } 3016 } 3017 } 3018 // Verify that the bundle operands are identical between the two calls. 3019 if (CI->hasOperandBundles() && 3020 !std::equal(CI->op_begin() + CI->getBundleOperandsStartIndex(), 3021 CI->op_begin() + CI->getBundleOperandsEndIndex(), 3022 CI2->op_begin() + CI2->getBundleOperandsStartIndex())) { 3023 BS.cancelScheduling(VL, VL0); 3024 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3025 ReuseShuffleIndicies); 3026 LLVM_DEBUG(dbgs() << "SLP: mismatched bundle operands in calls:" 3027 << *CI << "!=" << *V << '\n'); 3028 return; 3029 } 3030 } 3031 3032 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3033 ReuseShuffleIndicies); 3034 TE->setOperandsInOrder(); 3035 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 3036 ValueList Operands; 3037 // Prepare the operand vector. 3038 for (Value *V : VL) { 3039 auto *CI2 = cast<CallInst>(V); 3040 Operands.push_back(CI2->getArgOperand(i)); 3041 } 3042 buildTree_rec(Operands, Depth + 1, {TE, i}); 3043 } 3044 return; 3045 } 3046 case Instruction::ShuffleVector: { 3047 // If this is not an alternate sequence of opcode like add-sub 3048 // then do not vectorize this instruction. 3049 if (!S.isAltShuffle()) { 3050 BS.cancelScheduling(VL, VL0); 3051 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3052 ReuseShuffleIndicies); 3053 LLVM_DEBUG(dbgs() << "SLP: ShuffleVector are not vectorized.\n"); 3054 return; 3055 } 3056 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3057 ReuseShuffleIndicies); 3058 LLVM_DEBUG(dbgs() << "SLP: added a ShuffleVector op.\n"); 3059 3060 // Reorder operands if reordering would enable vectorization. 3061 if (isa<BinaryOperator>(VL0)) { 3062 ValueList Left, Right; 3063 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 3064 TE->setOperand(0, Left); 3065 TE->setOperand(1, Right); 3066 buildTree_rec(Left, Depth + 1, {TE, 0}); 3067 buildTree_rec(Right, Depth + 1, {TE, 1}); 3068 return; 3069 } 3070 3071 TE->setOperandsInOrder(); 3072 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 3073 ValueList Operands; 3074 // Prepare the operand vector. 3075 for (Value *V : VL) 3076 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3077 3078 buildTree_rec(Operands, Depth + 1, {TE, i}); 3079 } 3080 return; 3081 } 3082 default: 3083 BS.cancelScheduling(VL, VL0); 3084 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3085 ReuseShuffleIndicies); 3086 LLVM_DEBUG(dbgs() << "SLP: Gathering unknown instruction.\n"); 3087 return; 3088 } 3089 } 3090 3091 unsigned BoUpSLP::canMapToVector(Type *T, const DataLayout &DL) const { 3092 unsigned N = 1; 3093 Type *EltTy = T; 3094 3095 while (isa<CompositeType>(EltTy)) { 3096 if (auto *ST = dyn_cast<StructType>(EltTy)) { 3097 // Check that struct is homogeneous. 3098 for (const auto *Ty : ST->elements()) 3099 if (Ty != *ST->element_begin()) 3100 return 0; 3101 N *= ST->getNumElements(); 3102 EltTy = *ST->element_begin(); 3103 } else { 3104 auto *SeqT = cast<SequentialType>(EltTy); 3105 N *= SeqT->getNumElements(); 3106 EltTy = SeqT->getElementType(); 3107 } 3108 } 3109 3110 if (!isValidElementType(EltTy)) 3111 return 0; 3112 uint64_t VTSize = DL.getTypeStoreSizeInBits(VectorType::get(EltTy, N)); 3113 if (VTSize < MinVecRegSize || VTSize > MaxVecRegSize || VTSize != DL.getTypeStoreSizeInBits(T)) 3114 return 0; 3115 return N; 3116 } 3117 3118 bool BoUpSLP::canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 3119 SmallVectorImpl<unsigned> &CurrentOrder) const { 3120 Instruction *E0 = cast<Instruction>(OpValue); 3121 assert(E0->getOpcode() == Instruction::ExtractElement || 3122 E0->getOpcode() == Instruction::ExtractValue); 3123 assert(E0->getOpcode() == getSameOpcode(VL).getOpcode() && "Invalid opcode"); 3124 // Check if all of the extracts come from the same vector and from the 3125 // correct offset. 3126 Value *Vec = E0->getOperand(0); 3127 3128 CurrentOrder.clear(); 3129 3130 // We have to extract from a vector/aggregate with the same number of elements. 3131 unsigned NElts; 3132 if (E0->getOpcode() == Instruction::ExtractValue) { 3133 const DataLayout &DL = E0->getModule()->getDataLayout(); 3134 NElts = canMapToVector(Vec->getType(), DL); 3135 if (!NElts) 3136 return false; 3137 // Check if load can be rewritten as load of vector. 3138 LoadInst *LI = dyn_cast<LoadInst>(Vec); 3139 if (!LI || !LI->isSimple() || !LI->hasNUses(VL.size())) 3140 return false; 3141 } else { 3142 NElts = Vec->getType()->getVectorNumElements(); 3143 } 3144 3145 if (NElts != VL.size()) 3146 return false; 3147 3148 // Check that all of the indices extract from the correct offset. 3149 bool ShouldKeepOrder = true; 3150 unsigned E = VL.size(); 3151 // Assign to all items the initial value E + 1 so we can check if the extract 3152 // instruction index was used already. 3153 // Also, later we can check that all the indices are used and we have a 3154 // consecutive access in the extract instructions, by checking that no 3155 // element of CurrentOrder still has value E + 1. 3156 CurrentOrder.assign(E, E + 1); 3157 unsigned I = 0; 3158 for (; I < E; ++I) { 3159 auto *Inst = cast<Instruction>(VL[I]); 3160 if (Inst->getOperand(0) != Vec) 3161 break; 3162 Optional<unsigned> Idx = getExtractIndex(Inst); 3163 if (!Idx) 3164 break; 3165 const unsigned ExtIdx = *Idx; 3166 if (ExtIdx != I) { 3167 if (ExtIdx >= E || CurrentOrder[ExtIdx] != E + 1) 3168 break; 3169 ShouldKeepOrder = false; 3170 CurrentOrder[ExtIdx] = I; 3171 } else { 3172 if (CurrentOrder[I] != E + 1) 3173 break; 3174 CurrentOrder[I] = I; 3175 } 3176 } 3177 if (I < E) { 3178 CurrentOrder.clear(); 3179 return false; 3180 } 3181 3182 return ShouldKeepOrder; 3183 } 3184 3185 bool BoUpSLP::areAllUsersVectorized(Instruction *I) const { 3186 return I->hasOneUse() || 3187 std::all_of(I->user_begin(), I->user_end(), [this](User *U) { 3188 return ScalarToTreeEntry.count(U) > 0; 3189 }); 3190 } 3191 3192 int BoUpSLP::getEntryCost(TreeEntry *E) { 3193 ArrayRef<Value*> VL = E->Scalars; 3194 3195 Type *ScalarTy = VL[0]->getType(); 3196 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 3197 ScalarTy = SI->getValueOperand()->getType(); 3198 else if (CmpInst *CI = dyn_cast<CmpInst>(VL[0])) 3199 ScalarTy = CI->getOperand(0)->getType(); 3200 VectorType *VecTy = VectorType::get(ScalarTy, VL.size()); 3201 3202 // If we have computed a smaller type for the expression, update VecTy so 3203 // that the costs will be accurate. 3204 if (MinBWs.count(VL[0])) 3205 VecTy = VectorType::get( 3206 IntegerType::get(F->getContext(), MinBWs[VL[0]].first), VL.size()); 3207 3208 unsigned ReuseShuffleNumbers = E->ReuseShuffleIndices.size(); 3209 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 3210 int ReuseShuffleCost = 0; 3211 if (NeedToShuffleReuses) { 3212 ReuseShuffleCost = 3213 TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3214 } 3215 if (E->NeedToGather) { 3216 if (allConstant(VL)) 3217 return 0; 3218 if (isSplat(VL)) { 3219 return ReuseShuffleCost + 3220 TTI->getShuffleCost(TargetTransformInfo::SK_Broadcast, VecTy, 0); 3221 } 3222 if (E->getOpcode() == Instruction::ExtractElement && 3223 allSameType(VL) && allSameBlock(VL)) { 3224 Optional<TargetTransformInfo::ShuffleKind> ShuffleKind = isShuffle(VL); 3225 if (ShuffleKind.hasValue()) { 3226 int Cost = TTI->getShuffleCost(ShuffleKind.getValue(), VecTy); 3227 for (auto *V : VL) { 3228 // If all users of instruction are going to be vectorized and this 3229 // instruction itself is not going to be vectorized, consider this 3230 // instruction as dead and remove its cost from the final cost of the 3231 // vectorized tree. 3232 if (areAllUsersVectorized(cast<Instruction>(V)) && 3233 !ScalarToTreeEntry.count(V)) { 3234 auto *IO = cast<ConstantInt>( 3235 cast<ExtractElementInst>(V)->getIndexOperand()); 3236 Cost -= TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, 3237 IO->getZExtValue()); 3238 } 3239 } 3240 return ReuseShuffleCost + Cost; 3241 } 3242 } 3243 return ReuseShuffleCost + getGatherCost(VL); 3244 } 3245 assert(E->getOpcode() && allSameType(VL) && allSameBlock(VL) && "Invalid VL"); 3246 Instruction *VL0 = E->getMainOp(); 3247 unsigned ShuffleOrOp = 3248 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 3249 switch (ShuffleOrOp) { 3250 case Instruction::PHI: 3251 return 0; 3252 3253 case Instruction::ExtractValue: 3254 case Instruction::ExtractElement: 3255 if (NeedToShuffleReuses) { 3256 unsigned Idx = 0; 3257 for (unsigned I : E->ReuseShuffleIndices) { 3258 if (ShuffleOrOp == Instruction::ExtractElement) { 3259 auto *IO = cast<ConstantInt>( 3260 cast<ExtractElementInst>(VL[I])->getIndexOperand()); 3261 Idx = IO->getZExtValue(); 3262 ReuseShuffleCost -= TTI->getVectorInstrCost( 3263 Instruction::ExtractElement, VecTy, Idx); 3264 } else { 3265 ReuseShuffleCost -= TTI->getVectorInstrCost( 3266 Instruction::ExtractElement, VecTy, Idx); 3267 ++Idx; 3268 } 3269 } 3270 Idx = ReuseShuffleNumbers; 3271 for (Value *V : VL) { 3272 if (ShuffleOrOp == Instruction::ExtractElement) { 3273 auto *IO = cast<ConstantInt>( 3274 cast<ExtractElementInst>(V)->getIndexOperand()); 3275 Idx = IO->getZExtValue(); 3276 } else { 3277 --Idx; 3278 } 3279 ReuseShuffleCost += 3280 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, Idx); 3281 } 3282 } 3283 if (!E->NeedToGather) { 3284 int DeadCost = ReuseShuffleCost; 3285 if (!E->ReorderIndices.empty()) { 3286 // TODO: Merge this shuffle with the ReuseShuffleCost. 3287 DeadCost += TTI->getShuffleCost( 3288 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3289 } 3290 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 3291 Instruction *E = cast<Instruction>(VL[i]); 3292 // If all users are going to be vectorized, instruction can be 3293 // considered as dead. 3294 // The same, if have only one user, it will be vectorized for sure. 3295 if (areAllUsersVectorized(E)) { 3296 // Take credit for instruction that will become dead. 3297 if (E->hasOneUse()) { 3298 Instruction *Ext = E->user_back(); 3299 if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) && 3300 all_of(Ext->users(), 3301 [](User *U) { return isa<GetElementPtrInst>(U); })) { 3302 // Use getExtractWithExtendCost() to calculate the cost of 3303 // extractelement/ext pair. 3304 DeadCost -= TTI->getExtractWithExtendCost( 3305 Ext->getOpcode(), Ext->getType(), VecTy, i); 3306 // Add back the cost of s|zext which is subtracted separately. 3307 DeadCost += TTI->getCastInstrCost( 3308 Ext->getOpcode(), Ext->getType(), E->getType(), Ext); 3309 continue; 3310 } 3311 } 3312 DeadCost -= 3313 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, i); 3314 } 3315 } 3316 return DeadCost; 3317 } 3318 return ReuseShuffleCost + getGatherCost(VL); 3319 3320 case Instruction::ZExt: 3321 case Instruction::SExt: 3322 case Instruction::FPToUI: 3323 case Instruction::FPToSI: 3324 case Instruction::FPExt: 3325 case Instruction::PtrToInt: 3326 case Instruction::IntToPtr: 3327 case Instruction::SIToFP: 3328 case Instruction::UIToFP: 3329 case Instruction::Trunc: 3330 case Instruction::FPTrunc: 3331 case Instruction::BitCast: { 3332 Type *SrcTy = VL0->getOperand(0)->getType(); 3333 int ScalarEltCost = 3334 TTI->getCastInstrCost(E->getOpcode(), ScalarTy, SrcTy, VL0); 3335 if (NeedToShuffleReuses) { 3336 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3337 } 3338 3339 // Calculate the cost of this instruction. 3340 int ScalarCost = VL.size() * ScalarEltCost; 3341 3342 VectorType *SrcVecTy = VectorType::get(SrcTy, VL.size()); 3343 int VecCost = 0; 3344 // Check if the values are candidates to demote. 3345 if (!MinBWs.count(VL0) || VecTy != SrcVecTy) { 3346 VecCost = ReuseShuffleCost + 3347 TTI->getCastInstrCost(E->getOpcode(), VecTy, SrcVecTy, VL0); 3348 } 3349 return VecCost - ScalarCost; 3350 } 3351 case Instruction::FCmp: 3352 case Instruction::ICmp: 3353 case Instruction::Select: { 3354 // Calculate the cost of this instruction. 3355 int ScalarEltCost = TTI->getCmpSelInstrCost(E->getOpcode(), ScalarTy, 3356 Builder.getInt1Ty(), VL0); 3357 if (NeedToShuffleReuses) { 3358 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3359 } 3360 VectorType *MaskTy = VectorType::get(Builder.getInt1Ty(), VL.size()); 3361 int ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3362 int VecCost = TTI->getCmpSelInstrCost(E->getOpcode(), VecTy, MaskTy, VL0); 3363 return ReuseShuffleCost + VecCost - ScalarCost; 3364 } 3365 case Instruction::FNeg: 3366 case Instruction::Add: 3367 case Instruction::FAdd: 3368 case Instruction::Sub: 3369 case Instruction::FSub: 3370 case Instruction::Mul: 3371 case Instruction::FMul: 3372 case Instruction::UDiv: 3373 case Instruction::SDiv: 3374 case Instruction::FDiv: 3375 case Instruction::URem: 3376 case Instruction::SRem: 3377 case Instruction::FRem: 3378 case Instruction::Shl: 3379 case Instruction::LShr: 3380 case Instruction::AShr: 3381 case Instruction::And: 3382 case Instruction::Or: 3383 case Instruction::Xor: { 3384 // Certain instructions can be cheaper to vectorize if they have a 3385 // constant second vector operand. 3386 TargetTransformInfo::OperandValueKind Op1VK = 3387 TargetTransformInfo::OK_AnyValue; 3388 TargetTransformInfo::OperandValueKind Op2VK = 3389 TargetTransformInfo::OK_UniformConstantValue; 3390 TargetTransformInfo::OperandValueProperties Op1VP = 3391 TargetTransformInfo::OP_None; 3392 TargetTransformInfo::OperandValueProperties Op2VP = 3393 TargetTransformInfo::OP_PowerOf2; 3394 3395 // If all operands are exactly the same ConstantInt then set the 3396 // operand kind to OK_UniformConstantValue. 3397 // If instead not all operands are constants, then set the operand kind 3398 // to OK_AnyValue. If all operands are constants but not the same, 3399 // then set the operand kind to OK_NonUniformConstantValue. 3400 ConstantInt *CInt0 = nullptr; 3401 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 3402 const Instruction *I = cast<Instruction>(VL[i]); 3403 unsigned OpIdx = isa<BinaryOperator>(I) ? 1 : 0; 3404 ConstantInt *CInt = dyn_cast<ConstantInt>(I->getOperand(OpIdx)); 3405 if (!CInt) { 3406 Op2VK = TargetTransformInfo::OK_AnyValue; 3407 Op2VP = TargetTransformInfo::OP_None; 3408 break; 3409 } 3410 if (Op2VP == TargetTransformInfo::OP_PowerOf2 && 3411 !CInt->getValue().isPowerOf2()) 3412 Op2VP = TargetTransformInfo::OP_None; 3413 if (i == 0) { 3414 CInt0 = CInt; 3415 continue; 3416 } 3417 if (CInt0 != CInt) 3418 Op2VK = TargetTransformInfo::OK_NonUniformConstantValue; 3419 } 3420 3421 SmallVector<const Value *, 4> Operands(VL0->operand_values()); 3422 int ScalarEltCost = TTI->getArithmeticInstrCost( 3423 E->getOpcode(), ScalarTy, Op1VK, Op2VK, Op1VP, Op2VP, Operands, VL0); 3424 if (NeedToShuffleReuses) { 3425 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3426 } 3427 int ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3428 int VecCost = TTI->getArithmeticInstrCost( 3429 E->getOpcode(), VecTy, Op1VK, Op2VK, Op1VP, Op2VP, Operands, VL0); 3430 return ReuseShuffleCost + VecCost - ScalarCost; 3431 } 3432 case Instruction::GetElementPtr: { 3433 TargetTransformInfo::OperandValueKind Op1VK = 3434 TargetTransformInfo::OK_AnyValue; 3435 TargetTransformInfo::OperandValueKind Op2VK = 3436 TargetTransformInfo::OK_UniformConstantValue; 3437 3438 int ScalarEltCost = 3439 TTI->getArithmeticInstrCost(Instruction::Add, ScalarTy, Op1VK, Op2VK); 3440 if (NeedToShuffleReuses) { 3441 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3442 } 3443 int ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3444 int VecCost = 3445 TTI->getArithmeticInstrCost(Instruction::Add, VecTy, Op1VK, Op2VK); 3446 return ReuseShuffleCost + VecCost - ScalarCost; 3447 } 3448 case Instruction::Load: { 3449 // Cost of wide load - cost of scalar loads. 3450 MaybeAlign alignment(cast<LoadInst>(VL0)->getAlignment()); 3451 int ScalarEltCost = 3452 TTI->getMemoryOpCost(Instruction::Load, ScalarTy, alignment, 0, VL0); 3453 if (NeedToShuffleReuses) { 3454 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3455 } 3456 int ScalarLdCost = VecTy->getNumElements() * ScalarEltCost; 3457 int VecLdCost = 3458 TTI->getMemoryOpCost(Instruction::Load, VecTy, alignment, 0, VL0); 3459 if (!E->ReorderIndices.empty()) { 3460 // TODO: Merge this shuffle with the ReuseShuffleCost. 3461 VecLdCost += TTI->getShuffleCost( 3462 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3463 } 3464 return ReuseShuffleCost + VecLdCost - ScalarLdCost; 3465 } 3466 case Instruction::Store: { 3467 // We know that we can merge the stores. Calculate the cost. 3468 bool IsReorder = !E->ReorderIndices.empty(); 3469 auto *SI = 3470 cast<StoreInst>(IsReorder ? VL[E->ReorderIndices.front()] : VL0); 3471 MaybeAlign Alignment(SI->getAlignment()); 3472 int ScalarEltCost = 3473 TTI->getMemoryOpCost(Instruction::Store, ScalarTy, Alignment, 0, VL0); 3474 if (NeedToShuffleReuses) 3475 ReuseShuffleCost = -(ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3476 int ScalarStCost = VecTy->getNumElements() * ScalarEltCost; 3477 int VecStCost = TTI->getMemoryOpCost(Instruction::Store, 3478 VecTy, Alignment, 0, VL0); 3479 if (IsReorder) { 3480 // TODO: Merge this shuffle with the ReuseShuffleCost. 3481 VecStCost += TTI->getShuffleCost( 3482 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3483 } 3484 return ReuseShuffleCost + VecStCost - ScalarStCost; 3485 } 3486 case Instruction::Call: { 3487 CallInst *CI = cast<CallInst>(VL0); 3488 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3489 3490 // Calculate the cost of the scalar and vector calls. 3491 SmallVector<Type *, 4> ScalarTys; 3492 for (unsigned op = 0, opc = CI->getNumArgOperands(); op != opc; ++op) 3493 ScalarTys.push_back(CI->getArgOperand(op)->getType()); 3494 3495 FastMathFlags FMF; 3496 if (auto *FPMO = dyn_cast<FPMathOperator>(CI)) 3497 FMF = FPMO->getFastMathFlags(); 3498 3499 int ScalarEltCost = 3500 TTI->getIntrinsicInstrCost(ID, ScalarTy, ScalarTys, FMF); 3501 if (NeedToShuffleReuses) { 3502 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3503 } 3504 int ScalarCallCost = VecTy->getNumElements() * ScalarEltCost; 3505 3506 SmallVector<Value *, 4> Args(CI->arg_operands()); 3507 int VecCallCost = TTI->getIntrinsicInstrCost(ID, CI->getType(), Args, FMF, 3508 VecTy->getNumElements()); 3509 3510 LLVM_DEBUG(dbgs() << "SLP: Call cost " << VecCallCost - ScalarCallCost 3511 << " (" << VecCallCost << "-" << ScalarCallCost << ")" 3512 << " for " << *CI << "\n"); 3513 3514 return ReuseShuffleCost + VecCallCost - ScalarCallCost; 3515 } 3516 case Instruction::ShuffleVector: { 3517 assert(E->isAltShuffle() && 3518 ((Instruction::isBinaryOp(E->getOpcode()) && 3519 Instruction::isBinaryOp(E->getAltOpcode())) || 3520 (Instruction::isCast(E->getOpcode()) && 3521 Instruction::isCast(E->getAltOpcode()))) && 3522 "Invalid Shuffle Vector Operand"); 3523 int ScalarCost = 0; 3524 if (NeedToShuffleReuses) { 3525 for (unsigned Idx : E->ReuseShuffleIndices) { 3526 Instruction *I = cast<Instruction>(VL[Idx]); 3527 ReuseShuffleCost -= TTI->getInstructionCost( 3528 I, TargetTransformInfo::TCK_RecipThroughput); 3529 } 3530 for (Value *V : VL) { 3531 Instruction *I = cast<Instruction>(V); 3532 ReuseShuffleCost += TTI->getInstructionCost( 3533 I, TargetTransformInfo::TCK_RecipThroughput); 3534 } 3535 } 3536 for (Value *V : VL) { 3537 Instruction *I = cast<Instruction>(V); 3538 assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode"); 3539 ScalarCost += TTI->getInstructionCost( 3540 I, TargetTransformInfo::TCK_RecipThroughput); 3541 } 3542 // VecCost is equal to sum of the cost of creating 2 vectors 3543 // and the cost of creating shuffle. 3544 int VecCost = 0; 3545 if (Instruction::isBinaryOp(E->getOpcode())) { 3546 VecCost = TTI->getArithmeticInstrCost(E->getOpcode(), VecTy); 3547 VecCost += TTI->getArithmeticInstrCost(E->getAltOpcode(), VecTy); 3548 } else { 3549 Type *Src0SclTy = E->getMainOp()->getOperand(0)->getType(); 3550 Type *Src1SclTy = E->getAltOp()->getOperand(0)->getType(); 3551 VectorType *Src0Ty = VectorType::get(Src0SclTy, VL.size()); 3552 VectorType *Src1Ty = VectorType::get(Src1SclTy, VL.size()); 3553 VecCost = TTI->getCastInstrCost(E->getOpcode(), VecTy, Src0Ty); 3554 VecCost += TTI->getCastInstrCost(E->getAltOpcode(), VecTy, Src1Ty); 3555 } 3556 VecCost += TTI->getShuffleCost(TargetTransformInfo::SK_Select, VecTy, 0); 3557 return ReuseShuffleCost + VecCost - ScalarCost; 3558 } 3559 default: 3560 llvm_unreachable("Unknown instruction"); 3561 } 3562 } 3563 3564 bool BoUpSLP::isFullyVectorizableTinyTree() const { 3565 LLVM_DEBUG(dbgs() << "SLP: Check whether the tree with height " 3566 << VectorizableTree.size() << " is fully vectorizable .\n"); 3567 3568 // We only handle trees of heights 1 and 2. 3569 if (VectorizableTree.size() == 1 && !VectorizableTree[0]->NeedToGather) 3570 return true; 3571 3572 if (VectorizableTree.size() != 2) 3573 return false; 3574 3575 // Handle splat and all-constants stores. 3576 if (!VectorizableTree[0]->NeedToGather && 3577 (allConstant(VectorizableTree[1]->Scalars) || 3578 isSplat(VectorizableTree[1]->Scalars))) 3579 return true; 3580 3581 // Gathering cost would be too much for tiny trees. 3582 if (VectorizableTree[0]->NeedToGather || VectorizableTree[1]->NeedToGather) 3583 return false; 3584 3585 return true; 3586 } 3587 3588 bool BoUpSLP::isLoadCombineReductionCandidate(unsigned RdxOpcode) const { 3589 if (RdxOpcode != Instruction::Or) 3590 return false; 3591 3592 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 3593 Value *FirstReduced = VectorizableTree[0]->Scalars[0]; 3594 3595 // Look past the reduction to find a source value. Arbitrarily follow the 3596 // path through operand 0 of any 'or'. Also, peek through optional 3597 // shift-left-by-constant. 3598 Value *ZextLoad = FirstReduced; 3599 while (match(ZextLoad, m_Or(m_Value(), m_Value())) || 3600 match(ZextLoad, m_Shl(m_Value(), m_Constant()))) 3601 ZextLoad = cast<BinaryOperator>(ZextLoad)->getOperand(0); 3602 3603 // Check if the input to the reduction is an extended load. 3604 Value *LoadPtr; 3605 if (!match(ZextLoad, m_ZExt(m_Load(m_Value(LoadPtr))))) 3606 return false; 3607 3608 // Require that the total load bit width is a legal integer type. 3609 // For example, <8 x i8> --> i64 is a legal integer on a 64-bit target. 3610 // But <16 x i8> --> i128 is not, so the backend probably can't reduce it. 3611 Type *SrcTy = LoadPtr->getType()->getPointerElementType(); 3612 unsigned LoadBitWidth = SrcTy->getIntegerBitWidth() * NumElts; 3613 LLVMContext &Context = FirstReduced->getContext(); 3614 if (!TTI->isTypeLegal(IntegerType::get(Context, LoadBitWidth))) 3615 return false; 3616 3617 // Everything matched - assume that we can fold the whole sequence using 3618 // load combining. 3619 LLVM_DEBUG(dbgs() << "SLP: Assume load combining for scalar reduction of " 3620 << *(cast<Instruction>(FirstReduced)) << "\n"); 3621 3622 return true; 3623 } 3624 3625 bool BoUpSLP::isTreeTinyAndNotFullyVectorizable() const { 3626 // We can vectorize the tree if its size is greater than or equal to the 3627 // minimum size specified by the MinTreeSize command line option. 3628 if (VectorizableTree.size() >= MinTreeSize) 3629 return false; 3630 3631 // If we have a tiny tree (a tree whose size is less than MinTreeSize), we 3632 // can vectorize it if we can prove it fully vectorizable. 3633 if (isFullyVectorizableTinyTree()) 3634 return false; 3635 3636 assert(VectorizableTree.empty() 3637 ? ExternalUses.empty() 3638 : true && "We shouldn't have any external users"); 3639 3640 // Otherwise, we can't vectorize the tree. It is both tiny and not fully 3641 // vectorizable. 3642 return true; 3643 } 3644 3645 int BoUpSLP::getSpillCost() const { 3646 // Walk from the bottom of the tree to the top, tracking which values are 3647 // live. When we see a call instruction that is not part of our tree, 3648 // query TTI to see if there is a cost to keeping values live over it 3649 // (for example, if spills and fills are required). 3650 unsigned BundleWidth = VectorizableTree.front()->Scalars.size(); 3651 int Cost = 0; 3652 3653 SmallPtrSet<Instruction*, 4> LiveValues; 3654 Instruction *PrevInst = nullptr; 3655 3656 for (const auto &TEPtr : VectorizableTree) { 3657 Instruction *Inst = dyn_cast<Instruction>(TEPtr->Scalars[0]); 3658 if (!Inst) 3659 continue; 3660 3661 if (!PrevInst) { 3662 PrevInst = Inst; 3663 continue; 3664 } 3665 3666 // Update LiveValues. 3667 LiveValues.erase(PrevInst); 3668 for (auto &J : PrevInst->operands()) { 3669 if (isa<Instruction>(&*J) && getTreeEntry(&*J)) 3670 LiveValues.insert(cast<Instruction>(&*J)); 3671 } 3672 3673 LLVM_DEBUG({ 3674 dbgs() << "SLP: #LV: " << LiveValues.size(); 3675 for (auto *X : LiveValues) 3676 dbgs() << " " << X->getName(); 3677 dbgs() << ", Looking at "; 3678 Inst->dump(); 3679 }); 3680 3681 // Now find the sequence of instructions between PrevInst and Inst. 3682 unsigned NumCalls = 0; 3683 BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(), 3684 PrevInstIt = 3685 PrevInst->getIterator().getReverse(); 3686 while (InstIt != PrevInstIt) { 3687 if (PrevInstIt == PrevInst->getParent()->rend()) { 3688 PrevInstIt = Inst->getParent()->rbegin(); 3689 continue; 3690 } 3691 3692 // Debug information does not impact spill cost. 3693 if ((isa<CallInst>(&*PrevInstIt) && 3694 !isa<DbgInfoIntrinsic>(&*PrevInstIt)) && 3695 &*PrevInstIt != PrevInst) 3696 NumCalls++; 3697 3698 ++PrevInstIt; 3699 } 3700 3701 if (NumCalls) { 3702 SmallVector<Type*, 4> V; 3703 for (auto *II : LiveValues) 3704 V.push_back(VectorType::get(II->getType(), BundleWidth)); 3705 Cost += NumCalls * TTI->getCostOfKeepingLiveOverCall(V); 3706 } 3707 3708 PrevInst = Inst; 3709 } 3710 3711 return Cost; 3712 } 3713 3714 int BoUpSLP::getTreeCost() { 3715 int Cost = 0; 3716 LLVM_DEBUG(dbgs() << "SLP: Calculating cost for tree of size " 3717 << VectorizableTree.size() << ".\n"); 3718 3719 unsigned BundleWidth = VectorizableTree[0]->Scalars.size(); 3720 3721 for (unsigned I = 0, E = VectorizableTree.size(); I < E; ++I) { 3722 TreeEntry &TE = *VectorizableTree[I].get(); 3723 3724 // We create duplicate tree entries for gather sequences that have multiple 3725 // uses. However, we should not compute the cost of duplicate sequences. 3726 // For example, if we have a build vector (i.e., insertelement sequence) 3727 // that is used by more than one vector instruction, we only need to 3728 // compute the cost of the insertelement instructions once. The redundant 3729 // instructions will be eliminated by CSE. 3730 // 3731 // We should consider not creating duplicate tree entries for gather 3732 // sequences, and instead add additional edges to the tree representing 3733 // their uses. Since such an approach results in fewer total entries, 3734 // existing heuristics based on tree size may yield different results. 3735 // 3736 if (TE.NeedToGather && 3737 std::any_of( 3738 std::next(VectorizableTree.begin(), I + 1), VectorizableTree.end(), 3739 [TE](const std::unique_ptr<TreeEntry> &EntryPtr) { 3740 return EntryPtr->NeedToGather && EntryPtr->isSame(TE.Scalars); 3741 })) 3742 continue; 3743 3744 int C = getEntryCost(&TE); 3745 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C 3746 << " for bundle that starts with " << *TE.Scalars[0] 3747 << ".\n"); 3748 Cost += C; 3749 } 3750 3751 SmallPtrSet<Value *, 16> ExtractCostCalculated; 3752 int ExtractCost = 0; 3753 for (ExternalUser &EU : ExternalUses) { 3754 // We only add extract cost once for the same scalar. 3755 if (!ExtractCostCalculated.insert(EU.Scalar).second) 3756 continue; 3757 3758 // Uses by ephemeral values are free (because the ephemeral value will be 3759 // removed prior to code generation, and so the extraction will be 3760 // removed as well). 3761 if (EphValues.count(EU.User)) 3762 continue; 3763 3764 // If we plan to rewrite the tree in a smaller type, we will need to sign 3765 // extend the extracted value back to the original type. Here, we account 3766 // for the extract and the added cost of the sign extend if needed. 3767 auto *VecTy = VectorType::get(EU.Scalar->getType(), BundleWidth); 3768 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 3769 if (MinBWs.count(ScalarRoot)) { 3770 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 3771 auto Extend = 3772 MinBWs[ScalarRoot].second ? Instruction::SExt : Instruction::ZExt; 3773 VecTy = VectorType::get(MinTy, BundleWidth); 3774 ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(), 3775 VecTy, EU.Lane); 3776 } else { 3777 ExtractCost += 3778 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, EU.Lane); 3779 } 3780 } 3781 3782 int SpillCost = getSpillCost(); 3783 Cost += SpillCost + ExtractCost; 3784 3785 std::string Str; 3786 { 3787 raw_string_ostream OS(Str); 3788 OS << "SLP: Spill Cost = " << SpillCost << ".\n" 3789 << "SLP: Extract Cost = " << ExtractCost << ".\n" 3790 << "SLP: Total Cost = " << Cost << ".\n"; 3791 } 3792 LLVM_DEBUG(dbgs() << Str); 3793 3794 if (ViewSLPTree) 3795 ViewGraph(this, "SLP" + F->getName(), false, Str); 3796 3797 return Cost; 3798 } 3799 3800 int BoUpSLP::getGatherCost(Type *Ty, 3801 const DenseSet<unsigned> &ShuffledIndices) const { 3802 int Cost = 0; 3803 for (unsigned i = 0, e = cast<VectorType>(Ty)->getNumElements(); i < e; ++i) 3804 if (!ShuffledIndices.count(i)) 3805 Cost += TTI->getVectorInstrCost(Instruction::InsertElement, Ty, i); 3806 if (!ShuffledIndices.empty()) 3807 Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, Ty); 3808 return Cost; 3809 } 3810 3811 int BoUpSLP::getGatherCost(ArrayRef<Value *> VL) const { 3812 // Find the type of the operands in VL. 3813 Type *ScalarTy = VL[0]->getType(); 3814 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 3815 ScalarTy = SI->getValueOperand()->getType(); 3816 VectorType *VecTy = VectorType::get(ScalarTy, VL.size()); 3817 // Find the cost of inserting/extracting values from the vector. 3818 // Check if the same elements are inserted several times and count them as 3819 // shuffle candidates. 3820 DenseSet<unsigned> ShuffledElements; 3821 DenseSet<Value *> UniqueElements; 3822 // Iterate in reverse order to consider insert elements with the high cost. 3823 for (unsigned I = VL.size(); I > 0; --I) { 3824 unsigned Idx = I - 1; 3825 if (!UniqueElements.insert(VL[Idx]).second) 3826 ShuffledElements.insert(Idx); 3827 } 3828 return getGatherCost(VecTy, ShuffledElements); 3829 } 3830 3831 // Perform operand reordering on the instructions in VL and return the reordered 3832 // operands in Left and Right. 3833 void BoUpSLP::reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 3834 SmallVectorImpl<Value *> &Left, 3835 SmallVectorImpl<Value *> &Right, 3836 const DataLayout &DL, 3837 ScalarEvolution &SE, 3838 const BoUpSLP &R) { 3839 if (VL.empty()) 3840 return; 3841 VLOperands Ops(VL, DL, SE, R); 3842 // Reorder the operands in place. 3843 Ops.reorder(); 3844 Left = Ops.getVL(0); 3845 Right = Ops.getVL(1); 3846 } 3847 3848 void BoUpSLP::setInsertPointAfterBundle(TreeEntry *E) { 3849 // Get the basic block this bundle is in. All instructions in the bundle 3850 // should be in this block. 3851 auto *Front = E->getMainOp(); 3852 auto *BB = Front->getParent(); 3853 assert(llvm::all_of(make_range(E->Scalars.begin(), E->Scalars.end()), 3854 [=](Value *V) -> bool { 3855 auto *I = cast<Instruction>(V); 3856 return !E->isOpcodeOrAlt(I) || I->getParent() == BB; 3857 })); 3858 3859 // The last instruction in the bundle in program order. 3860 Instruction *LastInst = nullptr; 3861 3862 // Find the last instruction. The common case should be that BB has been 3863 // scheduled, and the last instruction is VL.back(). So we start with 3864 // VL.back() and iterate over schedule data until we reach the end of the 3865 // bundle. The end of the bundle is marked by null ScheduleData. 3866 if (BlocksSchedules.count(BB)) { 3867 auto *Bundle = 3868 BlocksSchedules[BB]->getScheduleData(E->isOneOf(E->Scalars.back())); 3869 if (Bundle && Bundle->isPartOfBundle()) 3870 for (; Bundle; Bundle = Bundle->NextInBundle) 3871 if (Bundle->OpValue == Bundle->Inst) 3872 LastInst = Bundle->Inst; 3873 } 3874 3875 // LastInst can still be null at this point if there's either not an entry 3876 // for BB in BlocksSchedules or there's no ScheduleData available for 3877 // VL.back(). This can be the case if buildTree_rec aborts for various 3878 // reasons (e.g., the maximum recursion depth is reached, the maximum region 3879 // size is reached, etc.). ScheduleData is initialized in the scheduling 3880 // "dry-run". 3881 // 3882 // If this happens, we can still find the last instruction by brute force. We 3883 // iterate forwards from Front (inclusive) until we either see all 3884 // instructions in the bundle or reach the end of the block. If Front is the 3885 // last instruction in program order, LastInst will be set to Front, and we 3886 // will visit all the remaining instructions in the block. 3887 // 3888 // One of the reasons we exit early from buildTree_rec is to place an upper 3889 // bound on compile-time. Thus, taking an additional compile-time hit here is 3890 // not ideal. However, this should be exceedingly rare since it requires that 3891 // we both exit early from buildTree_rec and that the bundle be out-of-order 3892 // (causing us to iterate all the way to the end of the block). 3893 if (!LastInst) { 3894 SmallPtrSet<Value *, 16> Bundle(E->Scalars.begin(), E->Scalars.end()); 3895 for (auto &I : make_range(BasicBlock::iterator(Front), BB->end())) { 3896 if (Bundle.erase(&I) && E->isOpcodeOrAlt(&I)) 3897 LastInst = &I; 3898 if (Bundle.empty()) 3899 break; 3900 } 3901 } 3902 assert(LastInst && "Failed to find last instruction in bundle"); 3903 3904 // Set the insertion point after the last instruction in the bundle. Set the 3905 // debug location to Front. 3906 Builder.SetInsertPoint(BB, ++LastInst->getIterator()); 3907 Builder.SetCurrentDebugLocation(Front->getDebugLoc()); 3908 } 3909 3910 Value *BoUpSLP::Gather(ArrayRef<Value *> VL, VectorType *Ty) { 3911 Value *Vec = UndefValue::get(Ty); 3912 // Generate the 'InsertElement' instruction. 3913 for (unsigned i = 0; i < Ty->getNumElements(); ++i) { 3914 Vec = Builder.CreateInsertElement(Vec, VL[i], Builder.getInt32(i)); 3915 if (auto *Insrt = dyn_cast<InsertElementInst>(Vec)) { 3916 GatherSeq.insert(Insrt); 3917 CSEBlocks.insert(Insrt->getParent()); 3918 3919 // Add to our 'need-to-extract' list. 3920 if (TreeEntry *E = getTreeEntry(VL[i])) { 3921 // Find which lane we need to extract. 3922 int FoundLane = -1; 3923 for (unsigned Lane = 0, LE = E->Scalars.size(); Lane != LE; ++Lane) { 3924 // Is this the lane of the scalar that we are looking for ? 3925 if (E->Scalars[Lane] == VL[i]) { 3926 FoundLane = Lane; 3927 break; 3928 } 3929 } 3930 assert(FoundLane >= 0 && "Could not find the correct lane"); 3931 if (!E->ReuseShuffleIndices.empty()) { 3932 FoundLane = 3933 std::distance(E->ReuseShuffleIndices.begin(), 3934 llvm::find(E->ReuseShuffleIndices, FoundLane)); 3935 } 3936 ExternalUses.push_back(ExternalUser(VL[i], Insrt, FoundLane)); 3937 } 3938 } 3939 } 3940 3941 return Vec; 3942 } 3943 3944 Value *BoUpSLP::vectorizeTree(ArrayRef<Value *> VL) { 3945 InstructionsState S = getSameOpcode(VL); 3946 if (S.getOpcode()) { 3947 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 3948 if (E->isSame(VL)) { 3949 Value *V = vectorizeTree(E); 3950 if (VL.size() == E->Scalars.size() && !E->ReuseShuffleIndices.empty()) { 3951 // We need to get the vectorized value but without shuffle. 3952 if (auto *SV = dyn_cast<ShuffleVectorInst>(V)) { 3953 V = SV->getOperand(0); 3954 } else { 3955 // Reshuffle to get only unique values. 3956 SmallVector<unsigned, 4> UniqueIdxs; 3957 SmallSet<unsigned, 4> UsedIdxs; 3958 for(unsigned Idx : E->ReuseShuffleIndices) 3959 if (UsedIdxs.insert(Idx).second) 3960 UniqueIdxs.emplace_back(Idx); 3961 V = Builder.CreateShuffleVector(V, UndefValue::get(V->getType()), 3962 UniqueIdxs); 3963 } 3964 } 3965 return V; 3966 } 3967 } 3968 } 3969 3970 Type *ScalarTy = S.OpValue->getType(); 3971 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) 3972 ScalarTy = SI->getValueOperand()->getType(); 3973 3974 // Check that every instruction appears once in this bundle. 3975 SmallVector<unsigned, 4> ReuseShuffleIndicies; 3976 SmallVector<Value *, 4> UniqueValues; 3977 if (VL.size() > 2) { 3978 DenseMap<Value *, unsigned> UniquePositions; 3979 for (Value *V : VL) { 3980 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 3981 ReuseShuffleIndicies.emplace_back(Res.first->second); 3982 if (Res.second || isa<Constant>(V)) 3983 UniqueValues.emplace_back(V); 3984 } 3985 // Do not shuffle single element or if number of unique values is not power 3986 // of 2. 3987 if (UniqueValues.size() == VL.size() || UniqueValues.size() <= 1 || 3988 !llvm::isPowerOf2_32(UniqueValues.size())) 3989 ReuseShuffleIndicies.clear(); 3990 else 3991 VL = UniqueValues; 3992 } 3993 VectorType *VecTy = VectorType::get(ScalarTy, VL.size()); 3994 3995 Value *V = Gather(VL, VecTy); 3996 if (!ReuseShuffleIndicies.empty()) { 3997 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3998 ReuseShuffleIndicies, "shuffle"); 3999 if (auto *I = dyn_cast<Instruction>(V)) { 4000 GatherSeq.insert(I); 4001 CSEBlocks.insert(I->getParent()); 4002 } 4003 } 4004 return V; 4005 } 4006 4007 static void inversePermutation(ArrayRef<unsigned> Indices, 4008 SmallVectorImpl<unsigned> &Mask) { 4009 Mask.clear(); 4010 const unsigned E = Indices.size(); 4011 Mask.resize(E); 4012 for (unsigned I = 0; I < E; ++I) 4013 Mask[Indices[I]] = I; 4014 } 4015 4016 Value *BoUpSLP::vectorizeTree(TreeEntry *E) { 4017 IRBuilder<>::InsertPointGuard Guard(Builder); 4018 4019 if (E->VectorizedValue) { 4020 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *E->Scalars[0] << ".\n"); 4021 return E->VectorizedValue; 4022 } 4023 4024 Instruction *VL0 = E->getMainOp(); 4025 Type *ScalarTy = VL0->getType(); 4026 if (StoreInst *SI = dyn_cast<StoreInst>(VL0)) 4027 ScalarTy = SI->getValueOperand()->getType(); 4028 VectorType *VecTy = VectorType::get(ScalarTy, E->Scalars.size()); 4029 4030 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 4031 4032 if (E->NeedToGather) { 4033 setInsertPointAfterBundle(E); 4034 auto *V = Gather(E->Scalars, VecTy); 4035 if (NeedToShuffleReuses) { 4036 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4037 E->ReuseShuffleIndices, "shuffle"); 4038 if (auto *I = dyn_cast<Instruction>(V)) { 4039 GatherSeq.insert(I); 4040 CSEBlocks.insert(I->getParent()); 4041 } 4042 } 4043 E->VectorizedValue = V; 4044 return V; 4045 } 4046 4047 unsigned ShuffleOrOp = 4048 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 4049 switch (ShuffleOrOp) { 4050 case Instruction::PHI: { 4051 auto *PH = cast<PHINode>(VL0); 4052 Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI()); 4053 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 4054 PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues()); 4055 Value *V = NewPhi; 4056 if (NeedToShuffleReuses) { 4057 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4058 E->ReuseShuffleIndices, "shuffle"); 4059 } 4060 E->VectorizedValue = V; 4061 4062 // PHINodes may have multiple entries from the same block. We want to 4063 // visit every block once. 4064 SmallPtrSet<BasicBlock*, 4> VisitedBBs; 4065 4066 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 4067 ValueList Operands; 4068 BasicBlock *IBB = PH->getIncomingBlock(i); 4069 4070 if (!VisitedBBs.insert(IBB).second) { 4071 NewPhi->addIncoming(NewPhi->getIncomingValueForBlock(IBB), IBB); 4072 continue; 4073 } 4074 4075 Builder.SetInsertPoint(IBB->getTerminator()); 4076 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 4077 Value *Vec = vectorizeTree(E->getOperand(i)); 4078 NewPhi->addIncoming(Vec, IBB); 4079 } 4080 4081 assert(NewPhi->getNumIncomingValues() == PH->getNumIncomingValues() && 4082 "Invalid number of incoming values"); 4083 return V; 4084 } 4085 4086 case Instruction::ExtractElement: { 4087 if (!E->NeedToGather) { 4088 Value *V = E->getSingleOperand(0); 4089 if (!E->ReorderIndices.empty()) { 4090 OrdersType Mask; 4091 inversePermutation(E->ReorderIndices, Mask); 4092 Builder.SetInsertPoint(VL0); 4093 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), Mask, 4094 "reorder_shuffle"); 4095 } 4096 if (NeedToShuffleReuses) { 4097 // TODO: Merge this shuffle with the ReorderShuffleMask. 4098 if (E->ReorderIndices.empty()) 4099 Builder.SetInsertPoint(VL0); 4100 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4101 E->ReuseShuffleIndices, "shuffle"); 4102 } 4103 E->VectorizedValue = V; 4104 return V; 4105 } 4106 setInsertPointAfterBundle(E); 4107 auto *V = Gather(E->Scalars, VecTy); 4108 if (NeedToShuffleReuses) { 4109 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4110 E->ReuseShuffleIndices, "shuffle"); 4111 if (auto *I = dyn_cast<Instruction>(V)) { 4112 GatherSeq.insert(I); 4113 CSEBlocks.insert(I->getParent()); 4114 } 4115 } 4116 E->VectorizedValue = V; 4117 return V; 4118 } 4119 case Instruction::ExtractValue: { 4120 if (!E->NeedToGather) { 4121 LoadInst *LI = cast<LoadInst>(E->getSingleOperand(0)); 4122 Builder.SetInsertPoint(LI); 4123 PointerType *PtrTy = PointerType::get(VecTy, LI->getPointerAddressSpace()); 4124 Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy); 4125 LoadInst *V = Builder.CreateAlignedLoad(VecTy, Ptr, LI->getAlignment()); 4126 Value *NewV = propagateMetadata(V, E->Scalars); 4127 if (!E->ReorderIndices.empty()) { 4128 OrdersType Mask; 4129 inversePermutation(E->ReorderIndices, Mask); 4130 NewV = Builder.CreateShuffleVector(NewV, UndefValue::get(VecTy), Mask, 4131 "reorder_shuffle"); 4132 } 4133 if (NeedToShuffleReuses) { 4134 // TODO: Merge this shuffle with the ReorderShuffleMask. 4135 NewV = Builder.CreateShuffleVector( 4136 NewV, UndefValue::get(VecTy), E->ReuseShuffleIndices, "shuffle"); 4137 } 4138 E->VectorizedValue = NewV; 4139 return NewV; 4140 } 4141 setInsertPointAfterBundle(E); 4142 auto *V = Gather(E->Scalars, VecTy); 4143 if (NeedToShuffleReuses) { 4144 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4145 E->ReuseShuffleIndices, "shuffle"); 4146 if (auto *I = dyn_cast<Instruction>(V)) { 4147 GatherSeq.insert(I); 4148 CSEBlocks.insert(I->getParent()); 4149 } 4150 } 4151 E->VectorizedValue = V; 4152 return V; 4153 } 4154 case Instruction::ZExt: 4155 case Instruction::SExt: 4156 case Instruction::FPToUI: 4157 case Instruction::FPToSI: 4158 case Instruction::FPExt: 4159 case Instruction::PtrToInt: 4160 case Instruction::IntToPtr: 4161 case Instruction::SIToFP: 4162 case Instruction::UIToFP: 4163 case Instruction::Trunc: 4164 case Instruction::FPTrunc: 4165 case Instruction::BitCast: { 4166 setInsertPointAfterBundle(E); 4167 4168 Value *InVec = vectorizeTree(E->getOperand(0)); 4169 4170 if (E->VectorizedValue) { 4171 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4172 return E->VectorizedValue; 4173 } 4174 4175 auto *CI = cast<CastInst>(VL0); 4176 Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy); 4177 if (NeedToShuffleReuses) { 4178 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4179 E->ReuseShuffleIndices, "shuffle"); 4180 } 4181 E->VectorizedValue = V; 4182 ++NumVectorInstructions; 4183 return V; 4184 } 4185 case Instruction::FCmp: 4186 case Instruction::ICmp: { 4187 setInsertPointAfterBundle(E); 4188 4189 Value *L = vectorizeTree(E->getOperand(0)); 4190 Value *R = vectorizeTree(E->getOperand(1)); 4191 4192 if (E->VectorizedValue) { 4193 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4194 return E->VectorizedValue; 4195 } 4196 4197 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 4198 Value *V; 4199 if (E->getOpcode() == Instruction::FCmp) 4200 V = Builder.CreateFCmp(P0, L, R); 4201 else 4202 V = Builder.CreateICmp(P0, L, R); 4203 4204 propagateIRFlags(V, E->Scalars, VL0); 4205 if (NeedToShuffleReuses) { 4206 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4207 E->ReuseShuffleIndices, "shuffle"); 4208 } 4209 E->VectorizedValue = V; 4210 ++NumVectorInstructions; 4211 return V; 4212 } 4213 case Instruction::Select: { 4214 setInsertPointAfterBundle(E); 4215 4216 Value *Cond = vectorizeTree(E->getOperand(0)); 4217 Value *True = vectorizeTree(E->getOperand(1)); 4218 Value *False = vectorizeTree(E->getOperand(2)); 4219 4220 if (E->VectorizedValue) { 4221 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4222 return E->VectorizedValue; 4223 } 4224 4225 Value *V = Builder.CreateSelect(Cond, True, False); 4226 if (NeedToShuffleReuses) { 4227 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4228 E->ReuseShuffleIndices, "shuffle"); 4229 } 4230 E->VectorizedValue = V; 4231 ++NumVectorInstructions; 4232 return V; 4233 } 4234 case Instruction::FNeg: { 4235 setInsertPointAfterBundle(E); 4236 4237 Value *Op = vectorizeTree(E->getOperand(0)); 4238 4239 if (E->VectorizedValue) { 4240 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4241 return E->VectorizedValue; 4242 } 4243 4244 Value *V = Builder.CreateUnOp( 4245 static_cast<Instruction::UnaryOps>(E->getOpcode()), Op); 4246 propagateIRFlags(V, E->Scalars, VL0); 4247 if (auto *I = dyn_cast<Instruction>(V)) 4248 V = propagateMetadata(I, E->Scalars); 4249 4250 if (NeedToShuffleReuses) { 4251 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4252 E->ReuseShuffleIndices, "shuffle"); 4253 } 4254 E->VectorizedValue = V; 4255 ++NumVectorInstructions; 4256 4257 return V; 4258 } 4259 case Instruction::Add: 4260 case Instruction::FAdd: 4261 case Instruction::Sub: 4262 case Instruction::FSub: 4263 case Instruction::Mul: 4264 case Instruction::FMul: 4265 case Instruction::UDiv: 4266 case Instruction::SDiv: 4267 case Instruction::FDiv: 4268 case Instruction::URem: 4269 case Instruction::SRem: 4270 case Instruction::FRem: 4271 case Instruction::Shl: 4272 case Instruction::LShr: 4273 case Instruction::AShr: 4274 case Instruction::And: 4275 case Instruction::Or: 4276 case Instruction::Xor: { 4277 setInsertPointAfterBundle(E); 4278 4279 Value *LHS = vectorizeTree(E->getOperand(0)); 4280 Value *RHS = vectorizeTree(E->getOperand(1)); 4281 4282 if (E->VectorizedValue) { 4283 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4284 return E->VectorizedValue; 4285 } 4286 4287 Value *V = Builder.CreateBinOp( 4288 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, 4289 RHS); 4290 propagateIRFlags(V, E->Scalars, VL0); 4291 if (auto *I = dyn_cast<Instruction>(V)) 4292 V = propagateMetadata(I, E->Scalars); 4293 4294 if (NeedToShuffleReuses) { 4295 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4296 E->ReuseShuffleIndices, "shuffle"); 4297 } 4298 E->VectorizedValue = V; 4299 ++NumVectorInstructions; 4300 4301 return V; 4302 } 4303 case Instruction::Load: { 4304 // Loads are inserted at the head of the tree because we don't want to 4305 // sink them all the way down past store instructions. 4306 bool IsReorder = E->updateStateIfReorder(); 4307 if (IsReorder) 4308 VL0 = E->getMainOp(); 4309 setInsertPointAfterBundle(E); 4310 4311 LoadInst *LI = cast<LoadInst>(VL0); 4312 Type *ScalarLoadTy = LI->getType(); 4313 unsigned AS = LI->getPointerAddressSpace(); 4314 4315 Value *VecPtr = Builder.CreateBitCast(LI->getPointerOperand(), 4316 VecTy->getPointerTo(AS)); 4317 4318 // The pointer operand uses an in-tree scalar so we add the new BitCast to 4319 // ExternalUses list to make sure that an extract will be generated in the 4320 // future. 4321 Value *PO = LI->getPointerOperand(); 4322 if (getTreeEntry(PO)) 4323 ExternalUses.push_back(ExternalUser(PO, cast<User>(VecPtr), 0)); 4324 4325 MaybeAlign Alignment = MaybeAlign(LI->getAlignment()); 4326 LI = Builder.CreateLoad(VecTy, VecPtr); 4327 if (!Alignment) 4328 Alignment = MaybeAlign(DL->getABITypeAlignment(ScalarLoadTy)); 4329 LI->setAlignment(Alignment); 4330 Value *V = propagateMetadata(LI, E->Scalars); 4331 if (IsReorder) { 4332 OrdersType Mask; 4333 inversePermutation(E->ReorderIndices, Mask); 4334 V = Builder.CreateShuffleVector(V, UndefValue::get(V->getType()), 4335 Mask, "reorder_shuffle"); 4336 } 4337 if (NeedToShuffleReuses) { 4338 // TODO: Merge this shuffle with the ReorderShuffleMask. 4339 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4340 E->ReuseShuffleIndices, "shuffle"); 4341 } 4342 E->VectorizedValue = V; 4343 ++NumVectorInstructions; 4344 return V; 4345 } 4346 case Instruction::Store: { 4347 bool IsReorder = !E->ReorderIndices.empty(); 4348 auto *SI = cast<StoreInst>( 4349 IsReorder ? E->Scalars[E->ReorderIndices.front()] : VL0); 4350 unsigned Alignment = SI->getAlignment(); 4351 unsigned AS = SI->getPointerAddressSpace(); 4352 4353 setInsertPointAfterBundle(E); 4354 4355 Value *VecValue = vectorizeTree(E->getOperand(0)); 4356 if (IsReorder) { 4357 OrdersType Mask; 4358 inversePermutation(E->ReorderIndices, Mask); 4359 VecValue = Builder.CreateShuffleVector( 4360 VecValue, UndefValue::get(VecValue->getType()), E->ReorderIndices, 4361 "reorder_shuffle"); 4362 } 4363 Value *ScalarPtr = SI->getPointerOperand(); 4364 Value *VecPtr = Builder.CreateBitCast( 4365 ScalarPtr, VecValue->getType()->getPointerTo(AS)); 4366 StoreInst *ST = Builder.CreateStore(VecValue, VecPtr); 4367 4368 // The pointer operand uses an in-tree scalar, so add the new BitCast to 4369 // ExternalUses to make sure that an extract will be generated in the 4370 // future. 4371 if (getTreeEntry(ScalarPtr)) 4372 ExternalUses.push_back(ExternalUser(ScalarPtr, cast<User>(VecPtr), 0)); 4373 4374 if (!Alignment) 4375 Alignment = DL->getABITypeAlignment(SI->getValueOperand()->getType()); 4376 4377 ST->setAlignment(Align(Alignment)); 4378 Value *V = propagateMetadata(ST, E->Scalars); 4379 if (NeedToShuffleReuses) { 4380 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4381 E->ReuseShuffleIndices, "shuffle"); 4382 } 4383 E->VectorizedValue = V; 4384 ++NumVectorInstructions; 4385 return V; 4386 } 4387 case Instruction::GetElementPtr: { 4388 setInsertPointAfterBundle(E); 4389 4390 Value *Op0 = vectorizeTree(E->getOperand(0)); 4391 4392 std::vector<Value *> OpVecs; 4393 for (int j = 1, e = cast<GetElementPtrInst>(VL0)->getNumOperands(); j < e; 4394 ++j) { 4395 ValueList &VL = E->getOperand(j); 4396 // Need to cast all elements to the same type before vectorization to 4397 // avoid crash. 4398 Type *VL0Ty = VL0->getOperand(j)->getType(); 4399 Type *Ty = llvm::all_of( 4400 VL, [VL0Ty](Value *V) { return VL0Ty == V->getType(); }) 4401 ? VL0Ty 4402 : DL->getIndexType(cast<GetElementPtrInst>(VL0) 4403 ->getPointerOperandType() 4404 ->getScalarType()); 4405 for (Value *&V : VL) { 4406 auto *CI = cast<ConstantInt>(V); 4407 V = ConstantExpr::getIntegerCast(CI, Ty, 4408 CI->getValue().isSignBitSet()); 4409 } 4410 Value *OpVec = vectorizeTree(VL); 4411 OpVecs.push_back(OpVec); 4412 } 4413 4414 Value *V = Builder.CreateGEP( 4415 cast<GetElementPtrInst>(VL0)->getSourceElementType(), Op0, OpVecs); 4416 if (Instruction *I = dyn_cast<Instruction>(V)) 4417 V = propagateMetadata(I, E->Scalars); 4418 4419 if (NeedToShuffleReuses) { 4420 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4421 E->ReuseShuffleIndices, "shuffle"); 4422 } 4423 E->VectorizedValue = V; 4424 ++NumVectorInstructions; 4425 4426 return V; 4427 } 4428 case Instruction::Call: { 4429 CallInst *CI = cast<CallInst>(VL0); 4430 setInsertPointAfterBundle(E); 4431 4432 Intrinsic::ID IID = Intrinsic::not_intrinsic; 4433 if (Function *FI = CI->getCalledFunction()) 4434 IID = FI->getIntrinsicID(); 4435 4436 Value *ScalarArg = nullptr; 4437 std::vector<Value *> OpVecs; 4438 for (int j = 0, e = CI->getNumArgOperands(); j < e; ++j) { 4439 ValueList OpVL; 4440 // Some intrinsics have scalar arguments. This argument should not be 4441 // vectorized. 4442 if (hasVectorInstrinsicScalarOpd(IID, j)) { 4443 CallInst *CEI = cast<CallInst>(VL0); 4444 ScalarArg = CEI->getArgOperand(j); 4445 OpVecs.push_back(CEI->getArgOperand(j)); 4446 continue; 4447 } 4448 4449 Value *OpVec = vectorizeTree(E->getOperand(j)); 4450 LLVM_DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n"); 4451 OpVecs.push_back(OpVec); 4452 } 4453 4454 Module *M = F->getParent(); 4455 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 4456 Type *Tys[] = { VectorType::get(CI->getType(), E->Scalars.size()) }; 4457 Function *CF = Intrinsic::getDeclaration(M, ID, Tys); 4458 SmallVector<OperandBundleDef, 1> OpBundles; 4459 CI->getOperandBundlesAsDefs(OpBundles); 4460 Value *V = Builder.CreateCall(CF, OpVecs, OpBundles); 4461 4462 // The scalar argument uses an in-tree scalar so we add the new vectorized 4463 // call to ExternalUses list to make sure that an extract will be 4464 // generated in the future. 4465 if (ScalarArg && getTreeEntry(ScalarArg)) 4466 ExternalUses.push_back(ExternalUser(ScalarArg, cast<User>(V), 0)); 4467 4468 propagateIRFlags(V, E->Scalars, VL0); 4469 if (NeedToShuffleReuses) { 4470 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4471 E->ReuseShuffleIndices, "shuffle"); 4472 } 4473 E->VectorizedValue = V; 4474 ++NumVectorInstructions; 4475 return V; 4476 } 4477 case Instruction::ShuffleVector: { 4478 assert(E->isAltShuffle() && 4479 ((Instruction::isBinaryOp(E->getOpcode()) && 4480 Instruction::isBinaryOp(E->getAltOpcode())) || 4481 (Instruction::isCast(E->getOpcode()) && 4482 Instruction::isCast(E->getAltOpcode()))) && 4483 "Invalid Shuffle Vector Operand"); 4484 4485 Value *LHS = nullptr, *RHS = nullptr; 4486 if (Instruction::isBinaryOp(E->getOpcode())) { 4487 setInsertPointAfterBundle(E); 4488 LHS = vectorizeTree(E->getOperand(0)); 4489 RHS = vectorizeTree(E->getOperand(1)); 4490 } else { 4491 setInsertPointAfterBundle(E); 4492 LHS = vectorizeTree(E->getOperand(0)); 4493 } 4494 4495 if (E->VectorizedValue) { 4496 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4497 return E->VectorizedValue; 4498 } 4499 4500 Value *V0, *V1; 4501 if (Instruction::isBinaryOp(E->getOpcode())) { 4502 V0 = Builder.CreateBinOp( 4503 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, RHS); 4504 V1 = Builder.CreateBinOp( 4505 static_cast<Instruction::BinaryOps>(E->getAltOpcode()), LHS, RHS); 4506 } else { 4507 V0 = Builder.CreateCast( 4508 static_cast<Instruction::CastOps>(E->getOpcode()), LHS, VecTy); 4509 V1 = Builder.CreateCast( 4510 static_cast<Instruction::CastOps>(E->getAltOpcode()), LHS, VecTy); 4511 } 4512 4513 // Create shuffle to take alternate operations from the vector. 4514 // Also, gather up main and alt scalar ops to propagate IR flags to 4515 // each vector operation. 4516 ValueList OpScalars, AltScalars; 4517 unsigned e = E->Scalars.size(); 4518 SmallVector<Constant *, 8> Mask(e); 4519 for (unsigned i = 0; i < e; ++i) { 4520 auto *OpInst = cast<Instruction>(E->Scalars[i]); 4521 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 4522 if (OpInst->getOpcode() == E->getAltOpcode()) { 4523 Mask[i] = Builder.getInt32(e + i); 4524 AltScalars.push_back(E->Scalars[i]); 4525 } else { 4526 Mask[i] = Builder.getInt32(i); 4527 OpScalars.push_back(E->Scalars[i]); 4528 } 4529 } 4530 4531 Value *ShuffleMask = ConstantVector::get(Mask); 4532 propagateIRFlags(V0, OpScalars); 4533 propagateIRFlags(V1, AltScalars); 4534 4535 Value *V = Builder.CreateShuffleVector(V0, V1, ShuffleMask); 4536 if (Instruction *I = dyn_cast<Instruction>(V)) 4537 V = propagateMetadata(I, E->Scalars); 4538 if (NeedToShuffleReuses) { 4539 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4540 E->ReuseShuffleIndices, "shuffle"); 4541 } 4542 E->VectorizedValue = V; 4543 ++NumVectorInstructions; 4544 4545 return V; 4546 } 4547 default: 4548 llvm_unreachable("unknown inst"); 4549 } 4550 return nullptr; 4551 } 4552 4553 Value *BoUpSLP::vectorizeTree() { 4554 ExtraValueToDebugLocsMap ExternallyUsedValues; 4555 return vectorizeTree(ExternallyUsedValues); 4556 } 4557 4558 Value * 4559 BoUpSLP::vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues) { 4560 // All blocks must be scheduled before any instructions are inserted. 4561 for (auto &BSIter : BlocksSchedules) { 4562 scheduleBlock(BSIter.second.get()); 4563 } 4564 4565 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4566 auto *VectorRoot = vectorizeTree(VectorizableTree[0].get()); 4567 4568 // If the vectorized tree can be rewritten in a smaller type, we truncate the 4569 // vectorized root. InstCombine will then rewrite the entire expression. We 4570 // sign extend the extracted values below. 4571 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 4572 if (MinBWs.count(ScalarRoot)) { 4573 if (auto *I = dyn_cast<Instruction>(VectorRoot)) 4574 Builder.SetInsertPoint(&*++BasicBlock::iterator(I)); 4575 auto BundleWidth = VectorizableTree[0]->Scalars.size(); 4576 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 4577 auto *VecTy = VectorType::get(MinTy, BundleWidth); 4578 auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy); 4579 VectorizableTree[0]->VectorizedValue = Trunc; 4580 } 4581 4582 LLVM_DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size() 4583 << " values .\n"); 4584 4585 // If necessary, sign-extend or zero-extend ScalarRoot to the larger type 4586 // specified by ScalarType. 4587 auto extend = [&](Value *ScalarRoot, Value *Ex, Type *ScalarType) { 4588 if (!MinBWs.count(ScalarRoot)) 4589 return Ex; 4590 if (MinBWs[ScalarRoot].second) 4591 return Builder.CreateSExt(Ex, ScalarType); 4592 return Builder.CreateZExt(Ex, ScalarType); 4593 }; 4594 4595 // Extract all of the elements with the external uses. 4596 for (const auto &ExternalUse : ExternalUses) { 4597 Value *Scalar = ExternalUse.Scalar; 4598 llvm::User *User = ExternalUse.User; 4599 4600 // Skip users that we already RAUW. This happens when one instruction 4601 // has multiple uses of the same value. 4602 if (User && !is_contained(Scalar->users(), User)) 4603 continue; 4604 TreeEntry *E = getTreeEntry(Scalar); 4605 assert(E && "Invalid scalar"); 4606 assert(!E->NeedToGather && "Extracting from a gather list"); 4607 4608 Value *Vec = E->VectorizedValue; 4609 assert(Vec && "Can't find vectorizable value"); 4610 4611 Value *Lane = Builder.getInt32(ExternalUse.Lane); 4612 // If User == nullptr, the Scalar is used as extra arg. Generate 4613 // ExtractElement instruction and update the record for this scalar in 4614 // ExternallyUsedValues. 4615 if (!User) { 4616 assert(ExternallyUsedValues.count(Scalar) && 4617 "Scalar with nullptr as an external user must be registered in " 4618 "ExternallyUsedValues map"); 4619 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 4620 Builder.SetInsertPoint(VecI->getParent(), 4621 std::next(VecI->getIterator())); 4622 } else { 4623 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4624 } 4625 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4626 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4627 CSEBlocks.insert(cast<Instruction>(Scalar)->getParent()); 4628 auto &Locs = ExternallyUsedValues[Scalar]; 4629 ExternallyUsedValues.insert({Ex, Locs}); 4630 ExternallyUsedValues.erase(Scalar); 4631 // Required to update internally referenced instructions. 4632 Scalar->replaceAllUsesWith(Ex); 4633 continue; 4634 } 4635 4636 // Generate extracts for out-of-tree users. 4637 // Find the insertion point for the extractelement lane. 4638 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 4639 if (PHINode *PH = dyn_cast<PHINode>(User)) { 4640 for (int i = 0, e = PH->getNumIncomingValues(); i != e; ++i) { 4641 if (PH->getIncomingValue(i) == Scalar) { 4642 Instruction *IncomingTerminator = 4643 PH->getIncomingBlock(i)->getTerminator(); 4644 if (isa<CatchSwitchInst>(IncomingTerminator)) { 4645 Builder.SetInsertPoint(VecI->getParent(), 4646 std::next(VecI->getIterator())); 4647 } else { 4648 Builder.SetInsertPoint(PH->getIncomingBlock(i)->getTerminator()); 4649 } 4650 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4651 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4652 CSEBlocks.insert(PH->getIncomingBlock(i)); 4653 PH->setOperand(i, Ex); 4654 } 4655 } 4656 } else { 4657 Builder.SetInsertPoint(cast<Instruction>(User)); 4658 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4659 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4660 CSEBlocks.insert(cast<Instruction>(User)->getParent()); 4661 User->replaceUsesOfWith(Scalar, Ex); 4662 } 4663 } else { 4664 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4665 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4666 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4667 CSEBlocks.insert(&F->getEntryBlock()); 4668 User->replaceUsesOfWith(Scalar, Ex); 4669 } 4670 4671 LLVM_DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n"); 4672 } 4673 4674 // For each vectorized value: 4675 for (auto &TEPtr : VectorizableTree) { 4676 TreeEntry *Entry = TEPtr.get(); 4677 4678 // No need to handle users of gathered values. 4679 if (Entry->NeedToGather) 4680 continue; 4681 4682 assert(Entry->VectorizedValue && "Can't find vectorizable value"); 4683 4684 // For each lane: 4685 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 4686 Value *Scalar = Entry->Scalars[Lane]; 4687 4688 #ifndef NDEBUG 4689 Type *Ty = Scalar->getType(); 4690 if (!Ty->isVoidTy()) { 4691 for (User *U : Scalar->users()) { 4692 LLVM_DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n"); 4693 4694 // It is legal to delete users in the ignorelist. 4695 assert((getTreeEntry(U) || is_contained(UserIgnoreList, U)) && 4696 "Deleting out-of-tree value"); 4697 } 4698 } 4699 #endif 4700 LLVM_DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n"); 4701 eraseInstruction(cast<Instruction>(Scalar)); 4702 } 4703 } 4704 4705 Builder.ClearInsertionPoint(); 4706 4707 return VectorizableTree[0]->VectorizedValue; 4708 } 4709 4710 void BoUpSLP::optimizeGatherSequence() { 4711 LLVM_DEBUG(dbgs() << "SLP: Optimizing " << GatherSeq.size() 4712 << " gather sequences instructions.\n"); 4713 // LICM InsertElementInst sequences. 4714 for (Instruction *I : GatherSeq) { 4715 if (isDeleted(I)) 4716 continue; 4717 4718 // Check if this block is inside a loop. 4719 Loop *L = LI->getLoopFor(I->getParent()); 4720 if (!L) 4721 continue; 4722 4723 // Check if it has a preheader. 4724 BasicBlock *PreHeader = L->getLoopPreheader(); 4725 if (!PreHeader) 4726 continue; 4727 4728 // If the vector or the element that we insert into it are 4729 // instructions that are defined in this basic block then we can't 4730 // hoist this instruction. 4731 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 4732 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 4733 if (Op0 && L->contains(Op0)) 4734 continue; 4735 if (Op1 && L->contains(Op1)) 4736 continue; 4737 4738 // We can hoist this instruction. Move it to the pre-header. 4739 I->moveBefore(PreHeader->getTerminator()); 4740 } 4741 4742 // Make a list of all reachable blocks in our CSE queue. 4743 SmallVector<const DomTreeNode *, 8> CSEWorkList; 4744 CSEWorkList.reserve(CSEBlocks.size()); 4745 for (BasicBlock *BB : CSEBlocks) 4746 if (DomTreeNode *N = DT->getNode(BB)) { 4747 assert(DT->isReachableFromEntry(N)); 4748 CSEWorkList.push_back(N); 4749 } 4750 4751 // Sort blocks by domination. This ensures we visit a block after all blocks 4752 // dominating it are visited. 4753 llvm::stable_sort(CSEWorkList, 4754 [this](const DomTreeNode *A, const DomTreeNode *B) { 4755 return DT->properlyDominates(A, B); 4756 }); 4757 4758 // Perform O(N^2) search over the gather sequences and merge identical 4759 // instructions. TODO: We can further optimize this scan if we split the 4760 // instructions into different buckets based on the insert lane. 4761 SmallVector<Instruction *, 16> Visited; 4762 for (auto I = CSEWorkList.begin(), E = CSEWorkList.end(); I != E; ++I) { 4763 assert((I == CSEWorkList.begin() || !DT->dominates(*I, *std::prev(I))) && 4764 "Worklist not sorted properly!"); 4765 BasicBlock *BB = (*I)->getBlock(); 4766 // For all instructions in blocks containing gather sequences: 4767 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e;) { 4768 Instruction *In = &*it++; 4769 if (isDeleted(In)) 4770 continue; 4771 if (!isa<InsertElementInst>(In) && !isa<ExtractElementInst>(In)) 4772 continue; 4773 4774 // Check if we can replace this instruction with any of the 4775 // visited instructions. 4776 for (Instruction *v : Visited) { 4777 if (In->isIdenticalTo(v) && 4778 DT->dominates(v->getParent(), In->getParent())) { 4779 In->replaceAllUsesWith(v); 4780 eraseInstruction(In); 4781 In = nullptr; 4782 break; 4783 } 4784 } 4785 if (In) { 4786 assert(!is_contained(Visited, In)); 4787 Visited.push_back(In); 4788 } 4789 } 4790 } 4791 CSEBlocks.clear(); 4792 GatherSeq.clear(); 4793 } 4794 4795 // Groups the instructions to a bundle (which is then a single scheduling entity) 4796 // and schedules instructions until the bundle gets ready. 4797 Optional<BoUpSLP::ScheduleData *> 4798 BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 4799 const InstructionsState &S) { 4800 if (isa<PHINode>(S.OpValue)) 4801 return nullptr; 4802 4803 // Initialize the instruction bundle. 4804 Instruction *OldScheduleEnd = ScheduleEnd; 4805 ScheduleData *PrevInBundle = nullptr; 4806 ScheduleData *Bundle = nullptr; 4807 bool ReSchedule = false; 4808 LLVM_DEBUG(dbgs() << "SLP: bundle: " << *S.OpValue << "\n"); 4809 4810 // Make sure that the scheduling region contains all 4811 // instructions of the bundle. 4812 for (Value *V : VL) { 4813 if (!extendSchedulingRegion(V, S)) 4814 return None; 4815 } 4816 4817 for (Value *V : VL) { 4818 ScheduleData *BundleMember = getScheduleData(V); 4819 assert(BundleMember && 4820 "no ScheduleData for bundle member (maybe not in same basic block)"); 4821 if (BundleMember->IsScheduled) { 4822 // A bundle member was scheduled as single instruction before and now 4823 // needs to be scheduled as part of the bundle. We just get rid of the 4824 // existing schedule. 4825 LLVM_DEBUG(dbgs() << "SLP: reset schedule because " << *BundleMember 4826 << " was already scheduled\n"); 4827 ReSchedule = true; 4828 } 4829 assert(BundleMember->isSchedulingEntity() && 4830 "bundle member already part of other bundle"); 4831 if (PrevInBundle) { 4832 PrevInBundle->NextInBundle = BundleMember; 4833 } else { 4834 Bundle = BundleMember; 4835 } 4836 BundleMember->UnscheduledDepsInBundle = 0; 4837 Bundle->UnscheduledDepsInBundle += BundleMember->UnscheduledDeps; 4838 4839 // Group the instructions to a bundle. 4840 BundleMember->FirstInBundle = Bundle; 4841 PrevInBundle = BundleMember; 4842 } 4843 if (ScheduleEnd != OldScheduleEnd) { 4844 // The scheduling region got new instructions at the lower end (or it is a 4845 // new region for the first bundle). This makes it necessary to 4846 // recalculate all dependencies. 4847 // It is seldom that this needs to be done a second time after adding the 4848 // initial bundle to the region. 4849 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 4850 doForAllOpcodes(I, [](ScheduleData *SD) { 4851 SD->clearDependencies(); 4852 }); 4853 } 4854 ReSchedule = true; 4855 } 4856 if (ReSchedule) { 4857 resetSchedule(); 4858 initialFillReadyList(ReadyInsts); 4859 } 4860 assert(Bundle && "Failed to find schedule bundle"); 4861 4862 LLVM_DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle << " in block " 4863 << BB->getName() << "\n"); 4864 4865 calculateDependencies(Bundle, true, SLP); 4866 4867 // Now try to schedule the new bundle. As soon as the bundle is "ready" it 4868 // means that there are no cyclic dependencies and we can schedule it. 4869 // Note that's important that we don't "schedule" the bundle yet (see 4870 // cancelScheduling). 4871 while (!Bundle->isReady() && !ReadyInsts.empty()) { 4872 4873 ScheduleData *pickedSD = ReadyInsts.back(); 4874 ReadyInsts.pop_back(); 4875 4876 if (pickedSD->isSchedulingEntity() && pickedSD->isReady()) { 4877 schedule(pickedSD, ReadyInsts); 4878 } 4879 } 4880 if (!Bundle->isReady()) { 4881 cancelScheduling(VL, S.OpValue); 4882 return None; 4883 } 4884 return Bundle; 4885 } 4886 4887 void BoUpSLP::BlockScheduling::cancelScheduling(ArrayRef<Value *> VL, 4888 Value *OpValue) { 4889 if (isa<PHINode>(OpValue)) 4890 return; 4891 4892 ScheduleData *Bundle = getScheduleData(OpValue); 4893 LLVM_DEBUG(dbgs() << "SLP: cancel scheduling of " << *Bundle << "\n"); 4894 assert(!Bundle->IsScheduled && 4895 "Can't cancel bundle which is already scheduled"); 4896 assert(Bundle->isSchedulingEntity() && Bundle->isPartOfBundle() && 4897 "tried to unbundle something which is not a bundle"); 4898 4899 // Un-bundle: make single instructions out of the bundle. 4900 ScheduleData *BundleMember = Bundle; 4901 while (BundleMember) { 4902 assert(BundleMember->FirstInBundle == Bundle && "corrupt bundle links"); 4903 BundleMember->FirstInBundle = BundleMember; 4904 ScheduleData *Next = BundleMember->NextInBundle; 4905 BundleMember->NextInBundle = nullptr; 4906 BundleMember->UnscheduledDepsInBundle = BundleMember->UnscheduledDeps; 4907 if (BundleMember->UnscheduledDepsInBundle == 0) { 4908 ReadyInsts.insert(BundleMember); 4909 } 4910 BundleMember = Next; 4911 } 4912 } 4913 4914 BoUpSLP::ScheduleData *BoUpSLP::BlockScheduling::allocateScheduleDataChunks() { 4915 // Allocate a new ScheduleData for the instruction. 4916 if (ChunkPos >= ChunkSize) { 4917 ScheduleDataChunks.push_back(std::make_unique<ScheduleData[]>(ChunkSize)); 4918 ChunkPos = 0; 4919 } 4920 return &(ScheduleDataChunks.back()[ChunkPos++]); 4921 } 4922 4923 bool BoUpSLP::BlockScheduling::extendSchedulingRegion(Value *V, 4924 const InstructionsState &S) { 4925 if (getScheduleData(V, isOneOf(S, V))) 4926 return true; 4927 Instruction *I = dyn_cast<Instruction>(V); 4928 assert(I && "bundle member must be an instruction"); 4929 assert(!isa<PHINode>(I) && "phi nodes don't need to be scheduled"); 4930 auto &&CheckSheduleForI = [this, &S](Instruction *I) -> bool { 4931 ScheduleData *ISD = getScheduleData(I); 4932 if (!ISD) 4933 return false; 4934 assert(isInSchedulingRegion(ISD) && 4935 "ScheduleData not in scheduling region"); 4936 ScheduleData *SD = allocateScheduleDataChunks(); 4937 SD->Inst = I; 4938 SD->init(SchedulingRegionID, S.OpValue); 4939 ExtraScheduleDataMap[I][S.OpValue] = SD; 4940 return true; 4941 }; 4942 if (CheckSheduleForI(I)) 4943 return true; 4944 if (!ScheduleStart) { 4945 // It's the first instruction in the new region. 4946 initScheduleData(I, I->getNextNode(), nullptr, nullptr); 4947 ScheduleStart = I; 4948 ScheduleEnd = I->getNextNode(); 4949 if (isOneOf(S, I) != I) 4950 CheckSheduleForI(I); 4951 assert(ScheduleEnd && "tried to vectorize a terminator?"); 4952 LLVM_DEBUG(dbgs() << "SLP: initialize schedule region to " << *I << "\n"); 4953 return true; 4954 } 4955 // Search up and down at the same time, because we don't know if the new 4956 // instruction is above or below the existing scheduling region. 4957 BasicBlock::reverse_iterator UpIter = 4958 ++ScheduleStart->getIterator().getReverse(); 4959 BasicBlock::reverse_iterator UpperEnd = BB->rend(); 4960 BasicBlock::iterator DownIter = ScheduleEnd->getIterator(); 4961 BasicBlock::iterator LowerEnd = BB->end(); 4962 while (true) { 4963 if (++ScheduleRegionSize > ScheduleRegionSizeLimit) { 4964 LLVM_DEBUG(dbgs() << "SLP: exceeded schedule region size limit\n"); 4965 return false; 4966 } 4967 4968 if (UpIter != UpperEnd) { 4969 if (&*UpIter == I) { 4970 initScheduleData(I, ScheduleStart, nullptr, FirstLoadStoreInRegion); 4971 ScheduleStart = I; 4972 if (isOneOf(S, I) != I) 4973 CheckSheduleForI(I); 4974 LLVM_DEBUG(dbgs() << "SLP: extend schedule region start to " << *I 4975 << "\n"); 4976 return true; 4977 } 4978 ++UpIter; 4979 } 4980 if (DownIter != LowerEnd) { 4981 if (&*DownIter == I) { 4982 initScheduleData(ScheduleEnd, I->getNextNode(), LastLoadStoreInRegion, 4983 nullptr); 4984 ScheduleEnd = I->getNextNode(); 4985 if (isOneOf(S, I) != I) 4986 CheckSheduleForI(I); 4987 assert(ScheduleEnd && "tried to vectorize a terminator?"); 4988 LLVM_DEBUG(dbgs() << "SLP: extend schedule region end to " << *I 4989 << "\n"); 4990 return true; 4991 } 4992 ++DownIter; 4993 } 4994 assert((UpIter != UpperEnd || DownIter != LowerEnd) && 4995 "instruction not found in block"); 4996 } 4997 return true; 4998 } 4999 5000 void BoUpSLP::BlockScheduling::initScheduleData(Instruction *FromI, 5001 Instruction *ToI, 5002 ScheduleData *PrevLoadStore, 5003 ScheduleData *NextLoadStore) { 5004 ScheduleData *CurrentLoadStore = PrevLoadStore; 5005 for (Instruction *I = FromI; I != ToI; I = I->getNextNode()) { 5006 ScheduleData *SD = ScheduleDataMap[I]; 5007 if (!SD) { 5008 SD = allocateScheduleDataChunks(); 5009 ScheduleDataMap[I] = SD; 5010 SD->Inst = I; 5011 } 5012 assert(!isInSchedulingRegion(SD) && 5013 "new ScheduleData already in scheduling region"); 5014 SD->init(SchedulingRegionID, I); 5015 5016 if (I->mayReadOrWriteMemory() && 5017 (!isa<IntrinsicInst>(I) || 5018 cast<IntrinsicInst>(I)->getIntrinsicID() != Intrinsic::sideeffect)) { 5019 // Update the linked list of memory accessing instructions. 5020 if (CurrentLoadStore) { 5021 CurrentLoadStore->NextLoadStore = SD; 5022 } else { 5023 FirstLoadStoreInRegion = SD; 5024 } 5025 CurrentLoadStore = SD; 5026 } 5027 } 5028 if (NextLoadStore) { 5029 if (CurrentLoadStore) 5030 CurrentLoadStore->NextLoadStore = NextLoadStore; 5031 } else { 5032 LastLoadStoreInRegion = CurrentLoadStore; 5033 } 5034 } 5035 5036 void BoUpSLP::BlockScheduling::calculateDependencies(ScheduleData *SD, 5037 bool InsertInReadyList, 5038 BoUpSLP *SLP) { 5039 assert(SD->isSchedulingEntity()); 5040 5041 SmallVector<ScheduleData *, 10> WorkList; 5042 WorkList.push_back(SD); 5043 5044 while (!WorkList.empty()) { 5045 ScheduleData *SD = WorkList.back(); 5046 WorkList.pop_back(); 5047 5048 ScheduleData *BundleMember = SD; 5049 while (BundleMember) { 5050 assert(isInSchedulingRegion(BundleMember)); 5051 if (!BundleMember->hasValidDependencies()) { 5052 5053 LLVM_DEBUG(dbgs() << "SLP: update deps of " << *BundleMember 5054 << "\n"); 5055 BundleMember->Dependencies = 0; 5056 BundleMember->resetUnscheduledDeps(); 5057 5058 // Handle def-use chain dependencies. 5059 if (BundleMember->OpValue != BundleMember->Inst) { 5060 ScheduleData *UseSD = getScheduleData(BundleMember->Inst); 5061 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 5062 BundleMember->Dependencies++; 5063 ScheduleData *DestBundle = UseSD->FirstInBundle; 5064 if (!DestBundle->IsScheduled) 5065 BundleMember->incrementUnscheduledDeps(1); 5066 if (!DestBundle->hasValidDependencies()) 5067 WorkList.push_back(DestBundle); 5068 } 5069 } else { 5070 for (User *U : BundleMember->Inst->users()) { 5071 if (isa<Instruction>(U)) { 5072 ScheduleData *UseSD = getScheduleData(U); 5073 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 5074 BundleMember->Dependencies++; 5075 ScheduleData *DestBundle = UseSD->FirstInBundle; 5076 if (!DestBundle->IsScheduled) 5077 BundleMember->incrementUnscheduledDeps(1); 5078 if (!DestBundle->hasValidDependencies()) 5079 WorkList.push_back(DestBundle); 5080 } 5081 } else { 5082 // I'm not sure if this can ever happen. But we need to be safe. 5083 // This lets the instruction/bundle never be scheduled and 5084 // eventually disable vectorization. 5085 BundleMember->Dependencies++; 5086 BundleMember->incrementUnscheduledDeps(1); 5087 } 5088 } 5089 } 5090 5091 // Handle the memory dependencies. 5092 ScheduleData *DepDest = BundleMember->NextLoadStore; 5093 if (DepDest) { 5094 Instruction *SrcInst = BundleMember->Inst; 5095 MemoryLocation SrcLoc = getLocation(SrcInst, SLP->AA); 5096 bool SrcMayWrite = BundleMember->Inst->mayWriteToMemory(); 5097 unsigned numAliased = 0; 5098 unsigned DistToSrc = 1; 5099 5100 while (DepDest) { 5101 assert(isInSchedulingRegion(DepDest)); 5102 5103 // We have two limits to reduce the complexity: 5104 // 1) AliasedCheckLimit: It's a small limit to reduce calls to 5105 // SLP->isAliased (which is the expensive part in this loop). 5106 // 2) MaxMemDepDistance: It's for very large blocks and it aborts 5107 // the whole loop (even if the loop is fast, it's quadratic). 5108 // It's important for the loop break condition (see below) to 5109 // check this limit even between two read-only instructions. 5110 if (DistToSrc >= MaxMemDepDistance || 5111 ((SrcMayWrite || DepDest->Inst->mayWriteToMemory()) && 5112 (numAliased >= AliasedCheckLimit || 5113 SLP->isAliased(SrcLoc, SrcInst, DepDest->Inst)))) { 5114 5115 // We increment the counter only if the locations are aliased 5116 // (instead of counting all alias checks). This gives a better 5117 // balance between reduced runtime and accurate dependencies. 5118 numAliased++; 5119 5120 DepDest->MemoryDependencies.push_back(BundleMember); 5121 BundleMember->Dependencies++; 5122 ScheduleData *DestBundle = DepDest->FirstInBundle; 5123 if (!DestBundle->IsScheduled) { 5124 BundleMember->incrementUnscheduledDeps(1); 5125 } 5126 if (!DestBundle->hasValidDependencies()) { 5127 WorkList.push_back(DestBundle); 5128 } 5129 } 5130 DepDest = DepDest->NextLoadStore; 5131 5132 // Example, explaining the loop break condition: Let's assume our 5133 // starting instruction is i0 and MaxMemDepDistance = 3. 5134 // 5135 // +--------v--v--v 5136 // i0,i1,i2,i3,i4,i5,i6,i7,i8 5137 // +--------^--^--^ 5138 // 5139 // MaxMemDepDistance let us stop alias-checking at i3 and we add 5140 // dependencies from i0 to i3,i4,.. (even if they are not aliased). 5141 // Previously we already added dependencies from i3 to i6,i7,i8 5142 // (because of MaxMemDepDistance). As we added a dependency from 5143 // i0 to i3, we have transitive dependencies from i0 to i6,i7,i8 5144 // and we can abort this loop at i6. 5145 if (DistToSrc >= 2 * MaxMemDepDistance) 5146 break; 5147 DistToSrc++; 5148 } 5149 } 5150 } 5151 BundleMember = BundleMember->NextInBundle; 5152 } 5153 if (InsertInReadyList && SD->isReady()) { 5154 ReadyInsts.push_back(SD); 5155 LLVM_DEBUG(dbgs() << "SLP: gets ready on update: " << *SD->Inst 5156 << "\n"); 5157 } 5158 } 5159 } 5160 5161 void BoUpSLP::BlockScheduling::resetSchedule() { 5162 assert(ScheduleStart && 5163 "tried to reset schedule on block which has not been scheduled"); 5164 for (Instruction *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 5165 doForAllOpcodes(I, [&](ScheduleData *SD) { 5166 assert(isInSchedulingRegion(SD) && 5167 "ScheduleData not in scheduling region"); 5168 SD->IsScheduled = false; 5169 SD->resetUnscheduledDeps(); 5170 }); 5171 } 5172 ReadyInsts.clear(); 5173 } 5174 5175 void BoUpSLP::scheduleBlock(BlockScheduling *BS) { 5176 if (!BS->ScheduleStart) 5177 return; 5178 5179 LLVM_DEBUG(dbgs() << "SLP: schedule block " << BS->BB->getName() << "\n"); 5180 5181 BS->resetSchedule(); 5182 5183 // For the real scheduling we use a more sophisticated ready-list: it is 5184 // sorted by the original instruction location. This lets the final schedule 5185 // be as close as possible to the original instruction order. 5186 struct ScheduleDataCompare { 5187 bool operator()(ScheduleData *SD1, ScheduleData *SD2) const { 5188 return SD2->SchedulingPriority < SD1->SchedulingPriority; 5189 } 5190 }; 5191 std::set<ScheduleData *, ScheduleDataCompare> ReadyInsts; 5192 5193 // Ensure that all dependency data is updated and fill the ready-list with 5194 // initial instructions. 5195 int Idx = 0; 5196 int NumToSchedule = 0; 5197 for (auto *I = BS->ScheduleStart; I != BS->ScheduleEnd; 5198 I = I->getNextNode()) { 5199 BS->doForAllOpcodes(I, [this, &Idx, &NumToSchedule, BS](ScheduleData *SD) { 5200 assert(SD->isPartOfBundle() == 5201 (getTreeEntry(SD->Inst) != nullptr) && 5202 "scheduler and vectorizer bundle mismatch"); 5203 SD->FirstInBundle->SchedulingPriority = Idx++; 5204 if (SD->isSchedulingEntity()) { 5205 BS->calculateDependencies(SD, false, this); 5206 NumToSchedule++; 5207 } 5208 }); 5209 } 5210 BS->initialFillReadyList(ReadyInsts); 5211 5212 Instruction *LastScheduledInst = BS->ScheduleEnd; 5213 5214 // Do the "real" scheduling. 5215 while (!ReadyInsts.empty()) { 5216 ScheduleData *picked = *ReadyInsts.begin(); 5217 ReadyInsts.erase(ReadyInsts.begin()); 5218 5219 // Move the scheduled instruction(s) to their dedicated places, if not 5220 // there yet. 5221 ScheduleData *BundleMember = picked; 5222 while (BundleMember) { 5223 Instruction *pickedInst = BundleMember->Inst; 5224 if (LastScheduledInst->getNextNode() != pickedInst) { 5225 BS->BB->getInstList().remove(pickedInst); 5226 BS->BB->getInstList().insert(LastScheduledInst->getIterator(), 5227 pickedInst); 5228 } 5229 LastScheduledInst = pickedInst; 5230 BundleMember = BundleMember->NextInBundle; 5231 } 5232 5233 BS->schedule(picked, ReadyInsts); 5234 NumToSchedule--; 5235 } 5236 assert(NumToSchedule == 0 && "could not schedule all instructions"); 5237 5238 // Avoid duplicate scheduling of the block. 5239 BS->ScheduleStart = nullptr; 5240 } 5241 5242 unsigned BoUpSLP::getVectorElementSize(Value *V) const { 5243 // If V is a store, just return the width of the stored value without 5244 // traversing the expression tree. This is the common case. 5245 if (auto *Store = dyn_cast<StoreInst>(V)) 5246 return DL->getTypeSizeInBits(Store->getValueOperand()->getType()); 5247 5248 // If V is not a store, we can traverse the expression tree to find loads 5249 // that feed it. The type of the loaded value may indicate a more suitable 5250 // width than V's type. We want to base the vector element size on the width 5251 // of memory operations where possible. 5252 SmallVector<Instruction *, 16> Worklist; 5253 SmallPtrSet<Instruction *, 16> Visited; 5254 if (auto *I = dyn_cast<Instruction>(V)) 5255 Worklist.push_back(I); 5256 5257 // Traverse the expression tree in bottom-up order looking for loads. If we 5258 // encounter an instruction we don't yet handle, we give up. 5259 auto MaxWidth = 0u; 5260 auto FoundUnknownInst = false; 5261 while (!Worklist.empty() && !FoundUnknownInst) { 5262 auto *I = Worklist.pop_back_val(); 5263 Visited.insert(I); 5264 5265 // We should only be looking at scalar instructions here. If the current 5266 // instruction has a vector type, give up. 5267 auto *Ty = I->getType(); 5268 if (isa<VectorType>(Ty)) 5269 FoundUnknownInst = true; 5270 5271 // If the current instruction is a load, update MaxWidth to reflect the 5272 // width of the loaded value. 5273 else if (isa<LoadInst>(I)) 5274 MaxWidth = std::max<unsigned>(MaxWidth, DL->getTypeSizeInBits(Ty)); 5275 5276 // Otherwise, we need to visit the operands of the instruction. We only 5277 // handle the interesting cases from buildTree here. If an operand is an 5278 // instruction we haven't yet visited, we add it to the worklist. 5279 else if (isa<PHINode>(I) || isa<CastInst>(I) || isa<GetElementPtrInst>(I) || 5280 isa<CmpInst>(I) || isa<SelectInst>(I) || isa<BinaryOperator>(I)) { 5281 for (Use &U : I->operands()) 5282 if (auto *J = dyn_cast<Instruction>(U.get())) 5283 if (!Visited.count(J)) 5284 Worklist.push_back(J); 5285 } 5286 5287 // If we don't yet handle the instruction, give up. 5288 else 5289 FoundUnknownInst = true; 5290 } 5291 5292 // If we didn't encounter a memory access in the expression tree, or if we 5293 // gave up for some reason, just return the width of V. 5294 if (!MaxWidth || FoundUnknownInst) 5295 return DL->getTypeSizeInBits(V->getType()); 5296 5297 // Otherwise, return the maximum width we found. 5298 return MaxWidth; 5299 } 5300 5301 // Determine if a value V in a vectorizable expression Expr can be demoted to a 5302 // smaller type with a truncation. We collect the values that will be demoted 5303 // in ToDemote and additional roots that require investigating in Roots. 5304 static bool collectValuesToDemote(Value *V, SmallPtrSetImpl<Value *> &Expr, 5305 SmallVectorImpl<Value *> &ToDemote, 5306 SmallVectorImpl<Value *> &Roots) { 5307 // We can always demote constants. 5308 if (isa<Constant>(V)) { 5309 ToDemote.push_back(V); 5310 return true; 5311 } 5312 5313 // If the value is not an instruction in the expression with only one use, it 5314 // cannot be demoted. 5315 auto *I = dyn_cast<Instruction>(V); 5316 if (!I || !I->hasOneUse() || !Expr.count(I)) 5317 return false; 5318 5319 switch (I->getOpcode()) { 5320 5321 // We can always demote truncations and extensions. Since truncations can 5322 // seed additional demotion, we save the truncated value. 5323 case Instruction::Trunc: 5324 Roots.push_back(I->getOperand(0)); 5325 break; 5326 case Instruction::ZExt: 5327 case Instruction::SExt: 5328 break; 5329 5330 // We can demote certain binary operations if we can demote both of their 5331 // operands. 5332 case Instruction::Add: 5333 case Instruction::Sub: 5334 case Instruction::Mul: 5335 case Instruction::And: 5336 case Instruction::Or: 5337 case Instruction::Xor: 5338 if (!collectValuesToDemote(I->getOperand(0), Expr, ToDemote, Roots) || 5339 !collectValuesToDemote(I->getOperand(1), Expr, ToDemote, Roots)) 5340 return false; 5341 break; 5342 5343 // We can demote selects if we can demote their true and false values. 5344 case Instruction::Select: { 5345 SelectInst *SI = cast<SelectInst>(I); 5346 if (!collectValuesToDemote(SI->getTrueValue(), Expr, ToDemote, Roots) || 5347 !collectValuesToDemote(SI->getFalseValue(), Expr, ToDemote, Roots)) 5348 return false; 5349 break; 5350 } 5351 5352 // We can demote phis if we can demote all their incoming operands. Note that 5353 // we don't need to worry about cycles since we ensure single use above. 5354 case Instruction::PHI: { 5355 PHINode *PN = cast<PHINode>(I); 5356 for (Value *IncValue : PN->incoming_values()) 5357 if (!collectValuesToDemote(IncValue, Expr, ToDemote, Roots)) 5358 return false; 5359 break; 5360 } 5361 5362 // Otherwise, conservatively give up. 5363 default: 5364 return false; 5365 } 5366 5367 // Record the value that we can demote. 5368 ToDemote.push_back(V); 5369 return true; 5370 } 5371 5372 void BoUpSLP::computeMinimumValueSizes() { 5373 // If there are no external uses, the expression tree must be rooted by a 5374 // store. We can't demote in-memory values, so there is nothing to do here. 5375 if (ExternalUses.empty()) 5376 return; 5377 5378 // We only attempt to truncate integer expressions. 5379 auto &TreeRoot = VectorizableTree[0]->Scalars; 5380 auto *TreeRootIT = dyn_cast<IntegerType>(TreeRoot[0]->getType()); 5381 if (!TreeRootIT) 5382 return; 5383 5384 // If the expression is not rooted by a store, these roots should have 5385 // external uses. We will rely on InstCombine to rewrite the expression in 5386 // the narrower type. However, InstCombine only rewrites single-use values. 5387 // This means that if a tree entry other than a root is used externally, it 5388 // must have multiple uses and InstCombine will not rewrite it. The code 5389 // below ensures that only the roots are used externally. 5390 SmallPtrSet<Value *, 32> Expr(TreeRoot.begin(), TreeRoot.end()); 5391 for (auto &EU : ExternalUses) 5392 if (!Expr.erase(EU.Scalar)) 5393 return; 5394 if (!Expr.empty()) 5395 return; 5396 5397 // Collect the scalar values of the vectorizable expression. We will use this 5398 // context to determine which values can be demoted. If we see a truncation, 5399 // we mark it as seeding another demotion. 5400 for (auto &EntryPtr : VectorizableTree) 5401 Expr.insert(EntryPtr->Scalars.begin(), EntryPtr->Scalars.end()); 5402 5403 // Ensure the roots of the vectorizable tree don't form a cycle. They must 5404 // have a single external user that is not in the vectorizable tree. 5405 for (auto *Root : TreeRoot) 5406 if (!Root->hasOneUse() || Expr.count(*Root->user_begin())) 5407 return; 5408 5409 // Conservatively determine if we can actually truncate the roots of the 5410 // expression. Collect the values that can be demoted in ToDemote and 5411 // additional roots that require investigating in Roots. 5412 SmallVector<Value *, 32> ToDemote; 5413 SmallVector<Value *, 4> Roots; 5414 for (auto *Root : TreeRoot) 5415 if (!collectValuesToDemote(Root, Expr, ToDemote, Roots)) 5416 return; 5417 5418 // The maximum bit width required to represent all the values that can be 5419 // demoted without loss of precision. It would be safe to truncate the roots 5420 // of the expression to this width. 5421 auto MaxBitWidth = 8u; 5422 5423 // We first check if all the bits of the roots are demanded. If they're not, 5424 // we can truncate the roots to this narrower type. 5425 for (auto *Root : TreeRoot) { 5426 auto Mask = DB->getDemandedBits(cast<Instruction>(Root)); 5427 MaxBitWidth = std::max<unsigned>( 5428 Mask.getBitWidth() - Mask.countLeadingZeros(), MaxBitWidth); 5429 } 5430 5431 // True if the roots can be zero-extended back to their original type, rather 5432 // than sign-extended. We know that if the leading bits are not demanded, we 5433 // can safely zero-extend. So we initialize IsKnownPositive to True. 5434 bool IsKnownPositive = true; 5435 5436 // If all the bits of the roots are demanded, we can try a little harder to 5437 // compute a narrower type. This can happen, for example, if the roots are 5438 // getelementptr indices. InstCombine promotes these indices to the pointer 5439 // width. Thus, all their bits are technically demanded even though the 5440 // address computation might be vectorized in a smaller type. 5441 // 5442 // We start by looking at each entry that can be demoted. We compute the 5443 // maximum bit width required to store the scalar by using ValueTracking to 5444 // compute the number of high-order bits we can truncate. 5445 if (MaxBitWidth == DL->getTypeSizeInBits(TreeRoot[0]->getType()) && 5446 llvm::all_of(TreeRoot, [](Value *R) { 5447 assert(R->hasOneUse() && "Root should have only one use!"); 5448 return isa<GetElementPtrInst>(R->user_back()); 5449 })) { 5450 MaxBitWidth = 8u; 5451 5452 // Determine if the sign bit of all the roots is known to be zero. If not, 5453 // IsKnownPositive is set to False. 5454 IsKnownPositive = llvm::all_of(TreeRoot, [&](Value *R) { 5455 KnownBits Known = computeKnownBits(R, *DL); 5456 return Known.isNonNegative(); 5457 }); 5458 5459 // Determine the maximum number of bits required to store the scalar 5460 // values. 5461 for (auto *Scalar : ToDemote) { 5462 auto NumSignBits = ComputeNumSignBits(Scalar, *DL, 0, AC, nullptr, DT); 5463 auto NumTypeBits = DL->getTypeSizeInBits(Scalar->getType()); 5464 MaxBitWidth = std::max<unsigned>(NumTypeBits - NumSignBits, MaxBitWidth); 5465 } 5466 5467 // If we can't prove that the sign bit is zero, we must add one to the 5468 // maximum bit width to account for the unknown sign bit. This preserves 5469 // the existing sign bit so we can safely sign-extend the root back to the 5470 // original type. Otherwise, if we know the sign bit is zero, we will 5471 // zero-extend the root instead. 5472 // 5473 // FIXME: This is somewhat suboptimal, as there will be cases where adding 5474 // one to the maximum bit width will yield a larger-than-necessary 5475 // type. In general, we need to add an extra bit only if we can't 5476 // prove that the upper bit of the original type is equal to the 5477 // upper bit of the proposed smaller type. If these two bits are the 5478 // same (either zero or one) we know that sign-extending from the 5479 // smaller type will result in the same value. Here, since we can't 5480 // yet prove this, we are just making the proposed smaller type 5481 // larger to ensure correctness. 5482 if (!IsKnownPositive) 5483 ++MaxBitWidth; 5484 } 5485 5486 // Round MaxBitWidth up to the next power-of-two. 5487 if (!isPowerOf2_64(MaxBitWidth)) 5488 MaxBitWidth = NextPowerOf2(MaxBitWidth); 5489 5490 // If the maximum bit width we compute is less than the with of the roots' 5491 // type, we can proceed with the narrowing. Otherwise, do nothing. 5492 if (MaxBitWidth >= TreeRootIT->getBitWidth()) 5493 return; 5494 5495 // If we can truncate the root, we must collect additional values that might 5496 // be demoted as a result. That is, those seeded by truncations we will 5497 // modify. 5498 while (!Roots.empty()) 5499 collectValuesToDemote(Roots.pop_back_val(), Expr, ToDemote, Roots); 5500 5501 // Finally, map the values we can demote to the maximum bit with we computed. 5502 for (auto *Scalar : ToDemote) 5503 MinBWs[Scalar] = std::make_pair(MaxBitWidth, !IsKnownPositive); 5504 } 5505 5506 namespace { 5507 5508 /// The SLPVectorizer Pass. 5509 struct SLPVectorizer : public FunctionPass { 5510 SLPVectorizerPass Impl; 5511 5512 /// Pass identification, replacement for typeid 5513 static char ID; 5514 5515 explicit SLPVectorizer() : FunctionPass(ID) { 5516 initializeSLPVectorizerPass(*PassRegistry::getPassRegistry()); 5517 } 5518 5519 bool doInitialization(Module &M) override { 5520 return false; 5521 } 5522 5523 bool runOnFunction(Function &F) override { 5524 if (skipFunction(F)) 5525 return false; 5526 5527 auto *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 5528 auto *TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F); 5529 auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>(); 5530 auto *TLI = TLIP ? &TLIP->getTLI(F) : nullptr; 5531 auto *AA = &getAnalysis<AAResultsWrapperPass>().getAAResults(); 5532 auto *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 5533 auto *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 5534 auto *AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F); 5535 auto *DB = &getAnalysis<DemandedBitsWrapperPass>().getDemandedBits(); 5536 auto *ORE = &getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE(); 5537 5538 return Impl.runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 5539 } 5540 5541 void getAnalysisUsage(AnalysisUsage &AU) const override { 5542 FunctionPass::getAnalysisUsage(AU); 5543 AU.addRequired<AssumptionCacheTracker>(); 5544 AU.addRequired<ScalarEvolutionWrapperPass>(); 5545 AU.addRequired<AAResultsWrapperPass>(); 5546 AU.addRequired<TargetTransformInfoWrapperPass>(); 5547 AU.addRequired<LoopInfoWrapperPass>(); 5548 AU.addRequired<DominatorTreeWrapperPass>(); 5549 AU.addRequired<DemandedBitsWrapperPass>(); 5550 AU.addRequired<OptimizationRemarkEmitterWrapperPass>(); 5551 AU.addPreserved<LoopInfoWrapperPass>(); 5552 AU.addPreserved<DominatorTreeWrapperPass>(); 5553 AU.addPreserved<AAResultsWrapperPass>(); 5554 AU.addPreserved<GlobalsAAWrapperPass>(); 5555 AU.setPreservesCFG(); 5556 } 5557 }; 5558 5559 } // end anonymous namespace 5560 5561 PreservedAnalyses SLPVectorizerPass::run(Function &F, FunctionAnalysisManager &AM) { 5562 auto *SE = &AM.getResult<ScalarEvolutionAnalysis>(F); 5563 auto *TTI = &AM.getResult<TargetIRAnalysis>(F); 5564 auto *TLI = AM.getCachedResult<TargetLibraryAnalysis>(F); 5565 auto *AA = &AM.getResult<AAManager>(F); 5566 auto *LI = &AM.getResult<LoopAnalysis>(F); 5567 auto *DT = &AM.getResult<DominatorTreeAnalysis>(F); 5568 auto *AC = &AM.getResult<AssumptionAnalysis>(F); 5569 auto *DB = &AM.getResult<DemandedBitsAnalysis>(F); 5570 auto *ORE = &AM.getResult<OptimizationRemarkEmitterAnalysis>(F); 5571 5572 bool Changed = runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 5573 if (!Changed) 5574 return PreservedAnalyses::all(); 5575 5576 PreservedAnalyses PA; 5577 PA.preserveSet<CFGAnalyses>(); 5578 PA.preserve<AAManager>(); 5579 PA.preserve<GlobalsAA>(); 5580 return PA; 5581 } 5582 5583 bool SLPVectorizerPass::runImpl(Function &F, ScalarEvolution *SE_, 5584 TargetTransformInfo *TTI_, 5585 TargetLibraryInfo *TLI_, AliasAnalysis *AA_, 5586 LoopInfo *LI_, DominatorTree *DT_, 5587 AssumptionCache *AC_, DemandedBits *DB_, 5588 OptimizationRemarkEmitter *ORE_) { 5589 SE = SE_; 5590 TTI = TTI_; 5591 TLI = TLI_; 5592 AA = AA_; 5593 LI = LI_; 5594 DT = DT_; 5595 AC = AC_; 5596 DB = DB_; 5597 DL = &F.getParent()->getDataLayout(); 5598 5599 Stores.clear(); 5600 GEPs.clear(); 5601 bool Changed = false; 5602 5603 // If the target claims to have no vector registers don't attempt 5604 // vectorization. 5605 if (!TTI->getNumberOfRegisters(TTI->getRegisterClassForType(true))) 5606 return false; 5607 5608 // Don't vectorize when the attribute NoImplicitFloat is used. 5609 if (F.hasFnAttribute(Attribute::NoImplicitFloat)) 5610 return false; 5611 5612 LLVM_DEBUG(dbgs() << "SLP: Analyzing blocks in " << F.getName() << ".\n"); 5613 5614 // Use the bottom up slp vectorizer to construct chains that start with 5615 // store instructions. 5616 BoUpSLP R(&F, SE, TTI, TLI, AA, LI, DT, AC, DB, DL, ORE_); 5617 5618 // A general note: the vectorizer must use BoUpSLP::eraseInstruction() to 5619 // delete instructions. 5620 5621 // Scan the blocks in the function in post order. 5622 for (auto BB : post_order(&F.getEntryBlock())) { 5623 collectSeedInstructions(BB); 5624 5625 // Vectorize trees that end at stores. 5626 if (!Stores.empty()) { 5627 LLVM_DEBUG(dbgs() << "SLP: Found stores for " << Stores.size() 5628 << " underlying objects.\n"); 5629 Changed |= vectorizeStoreChains(R); 5630 } 5631 5632 // Vectorize trees that end at reductions. 5633 Changed |= vectorizeChainsInBlock(BB, R); 5634 5635 // Vectorize the index computations of getelementptr instructions. This 5636 // is primarily intended to catch gather-like idioms ending at 5637 // non-consecutive loads. 5638 if (!GEPs.empty()) { 5639 LLVM_DEBUG(dbgs() << "SLP: Found GEPs for " << GEPs.size() 5640 << " underlying objects.\n"); 5641 Changed |= vectorizeGEPIndices(BB, R); 5642 } 5643 } 5644 5645 if (Changed) { 5646 R.optimizeGatherSequence(); 5647 LLVM_DEBUG(dbgs() << "SLP: vectorized \"" << F.getName() << "\"\n"); 5648 LLVM_DEBUG(verifyFunction(F)); 5649 } 5650 return Changed; 5651 } 5652 5653 bool SLPVectorizerPass::vectorizeStoreChain(ArrayRef<Value *> Chain, BoUpSLP &R, 5654 unsigned Idx) { 5655 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " << Chain.size() 5656 << "\n"); 5657 const unsigned Sz = R.getVectorElementSize(Chain[0]); 5658 const unsigned MinVF = R.getMinVecRegSize() / Sz; 5659 unsigned VF = Chain.size(); 5660 5661 if (!isPowerOf2_32(Sz) || !isPowerOf2_32(VF) || VF < 2 || VF < MinVF) 5662 return false; 5663 5664 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << VF << " stores at offset " << Idx 5665 << "\n"); 5666 5667 R.buildTree(Chain); 5668 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 5669 // TODO: Handle orders of size less than number of elements in the vector. 5670 if (Order && Order->size() == Chain.size()) { 5671 // TODO: reorder tree nodes without tree rebuilding. 5672 SmallVector<Value *, 4> ReorderedOps(Chain.rbegin(), Chain.rend()); 5673 llvm::transform(*Order, ReorderedOps.begin(), 5674 [Chain](const unsigned Idx) { return Chain[Idx]; }); 5675 R.buildTree(ReorderedOps); 5676 } 5677 if (R.isTreeTinyAndNotFullyVectorizable()) 5678 return false; 5679 5680 R.computeMinimumValueSizes(); 5681 5682 int Cost = R.getTreeCost(); 5683 5684 LLVM_DEBUG(dbgs() << "SLP: Found cost=" << Cost << " for VF=" << VF << "\n"); 5685 if (Cost < -SLPCostThreshold) { 5686 LLVM_DEBUG(dbgs() << "SLP: Decided to vectorize cost=" << Cost << "\n"); 5687 5688 using namespace ore; 5689 5690 R.getORE()->emit(OptimizationRemark(SV_NAME, "StoresVectorized", 5691 cast<StoreInst>(Chain[0])) 5692 << "Stores SLP vectorized with cost " << NV("Cost", Cost) 5693 << " and with tree size " 5694 << NV("TreeSize", R.getTreeSize())); 5695 5696 R.vectorizeTree(); 5697 return true; 5698 } 5699 5700 return false; 5701 } 5702 5703 bool SLPVectorizerPass::vectorizeStores(ArrayRef<StoreInst *> Stores, 5704 BoUpSLP &R) { 5705 // We may run into multiple chains that merge into a single chain. We mark the 5706 // stores that we vectorized so that we don't visit the same store twice. 5707 BoUpSLP::ValueSet VectorizedStores; 5708 bool Changed = false; 5709 5710 int E = Stores.size(); 5711 SmallBitVector Tails(E, false); 5712 SmallVector<int, 16> ConsecutiveChain(E, E + 1); 5713 int MaxIter = MaxStoreLookup.getValue(); 5714 int IterCnt; 5715 auto &&FindConsecutiveAccess = [this, &Stores, &Tails, &IterCnt, MaxIter, 5716 &ConsecutiveChain](int K, int Idx) { 5717 if (IterCnt >= MaxIter) 5718 return true; 5719 ++IterCnt; 5720 if (!isConsecutiveAccess(Stores[K], Stores[Idx], *DL, *SE)) 5721 return false; 5722 5723 Tails.set(Idx); 5724 ConsecutiveChain[K] = Idx; 5725 return true; 5726 }; 5727 // Do a quadratic search on all of the given stores in reverse order and find 5728 // all of the pairs of stores that follow each other. 5729 for (int Idx = E - 1; Idx >= 0; --Idx) { 5730 // If a store has multiple consecutive store candidates, search according 5731 // to the sequence: Idx-1, Idx+1, Idx-2, Idx+2, ... 5732 // This is because usually pairing with immediate succeeding or preceding 5733 // candidate create the best chance to find slp vectorization opportunity. 5734 const int MaxLookDepth = std::max(E - Idx, Idx + 1); 5735 IterCnt = 0; 5736 for (int Offset = 1, F = MaxLookDepth; Offset < F; ++Offset) 5737 if ((Idx >= Offset && FindConsecutiveAccess(Idx - Offset, Idx)) || 5738 (Idx + Offset < E && FindConsecutiveAccess(Idx + Offset, Idx))) 5739 break; 5740 } 5741 5742 // For stores that start but don't end a link in the chain: 5743 for (int Cnt = E; Cnt > 0; --Cnt) { 5744 int I = Cnt - 1; 5745 if (ConsecutiveChain[I] == E + 1 || Tails.test(I)) 5746 continue; 5747 // We found a store instr that starts a chain. Now follow the chain and try 5748 // to vectorize it. 5749 BoUpSLP::ValueList Operands; 5750 // Collect the chain into a list. 5751 while (I != E + 1 && !VectorizedStores.count(Stores[I])) { 5752 Operands.push_back(Stores[I]); 5753 // Move to the next value in the chain. 5754 I = ConsecutiveChain[I]; 5755 } 5756 5757 // If a vector register can't hold 1 element, we are done. 5758 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 5759 unsigned EltSize = R.getVectorElementSize(Stores[0]); 5760 if (MaxVecRegSize % EltSize != 0) 5761 continue; 5762 5763 unsigned MaxElts = MaxVecRegSize / EltSize; 5764 // FIXME: Is division-by-2 the correct step? Should we assert that the 5765 // register size is a power-of-2? 5766 unsigned StartIdx = 0; 5767 for (unsigned Size = llvm::PowerOf2Ceil(MaxElts); Size >= 2; Size /= 2) { 5768 for (unsigned Cnt = StartIdx, E = Operands.size(); Cnt + Size <= E;) { 5769 ArrayRef<Value *> Slice = makeArrayRef(Operands).slice(Cnt, Size); 5770 if (!VectorizedStores.count(Slice.front()) && 5771 !VectorizedStores.count(Slice.back()) && 5772 vectorizeStoreChain(Slice, R, Cnt)) { 5773 // Mark the vectorized stores so that we don't vectorize them again. 5774 VectorizedStores.insert(Slice.begin(), Slice.end()); 5775 Changed = true; 5776 // If we vectorized initial block, no need to try to vectorize it 5777 // again. 5778 if (Cnt == StartIdx) 5779 StartIdx += Size; 5780 Cnt += Size; 5781 continue; 5782 } 5783 ++Cnt; 5784 } 5785 // Check if the whole array was vectorized already - exit. 5786 if (StartIdx >= Operands.size()) 5787 break; 5788 } 5789 } 5790 5791 return Changed; 5792 } 5793 5794 void SLPVectorizerPass::collectSeedInstructions(BasicBlock *BB) { 5795 // Initialize the collections. We will make a single pass over the block. 5796 Stores.clear(); 5797 GEPs.clear(); 5798 5799 // Visit the store and getelementptr instructions in BB and organize them in 5800 // Stores and GEPs according to the underlying objects of their pointer 5801 // operands. 5802 for (Instruction &I : *BB) { 5803 // Ignore store instructions that are volatile or have a pointer operand 5804 // that doesn't point to a scalar type. 5805 if (auto *SI = dyn_cast<StoreInst>(&I)) { 5806 if (!SI->isSimple()) 5807 continue; 5808 if (!isValidElementType(SI->getValueOperand()->getType())) 5809 continue; 5810 Stores[GetUnderlyingObject(SI->getPointerOperand(), *DL)].push_back(SI); 5811 } 5812 5813 // Ignore getelementptr instructions that have more than one index, a 5814 // constant index, or a pointer operand that doesn't point to a scalar 5815 // type. 5816 else if (auto *GEP = dyn_cast<GetElementPtrInst>(&I)) { 5817 auto Idx = GEP->idx_begin()->get(); 5818 if (GEP->getNumIndices() > 1 || isa<Constant>(Idx)) 5819 continue; 5820 if (!isValidElementType(Idx->getType())) 5821 continue; 5822 if (GEP->getType()->isVectorTy()) 5823 continue; 5824 GEPs[GEP->getPointerOperand()].push_back(GEP); 5825 } 5826 } 5827 } 5828 5829 bool SLPVectorizerPass::tryToVectorizePair(Value *A, Value *B, BoUpSLP &R) { 5830 if (!A || !B) 5831 return false; 5832 Value *VL[] = { A, B }; 5833 return tryToVectorizeList(VL, R, /*UserCost=*/0, true); 5834 } 5835 5836 bool SLPVectorizerPass::tryToVectorizeList(ArrayRef<Value *> VL, BoUpSLP &R, 5837 int UserCost, bool AllowReorder) { 5838 if (VL.size() < 2) 5839 return false; 5840 5841 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize a list of length = " 5842 << VL.size() << ".\n"); 5843 5844 // Check that all of the parts are scalar instructions of the same type, 5845 // we permit an alternate opcode via InstructionsState. 5846 InstructionsState S = getSameOpcode(VL); 5847 if (!S.getOpcode()) 5848 return false; 5849 5850 Instruction *I0 = cast<Instruction>(S.OpValue); 5851 unsigned Sz = R.getVectorElementSize(I0); 5852 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / Sz); 5853 unsigned MaxVF = std::max<unsigned>(PowerOf2Floor(VL.size()), MinVF); 5854 if (MaxVF < 2) { 5855 R.getORE()->emit([&]() { 5856 return OptimizationRemarkMissed(SV_NAME, "SmallVF", I0) 5857 << "Cannot SLP vectorize list: vectorization factor " 5858 << "less than 2 is not supported"; 5859 }); 5860 return false; 5861 } 5862 5863 for (Value *V : VL) { 5864 Type *Ty = V->getType(); 5865 if (!isValidElementType(Ty)) { 5866 // NOTE: the following will give user internal llvm type name, which may 5867 // not be useful. 5868 R.getORE()->emit([&]() { 5869 std::string type_str; 5870 llvm::raw_string_ostream rso(type_str); 5871 Ty->print(rso); 5872 return OptimizationRemarkMissed(SV_NAME, "UnsupportedType", I0) 5873 << "Cannot SLP vectorize list: type " 5874 << rso.str() + " is unsupported by vectorizer"; 5875 }); 5876 return false; 5877 } 5878 } 5879 5880 bool Changed = false; 5881 bool CandidateFound = false; 5882 int MinCost = SLPCostThreshold; 5883 5884 unsigned NextInst = 0, MaxInst = VL.size(); 5885 for (unsigned VF = MaxVF; NextInst + 1 < MaxInst && VF >= MinVF; VF /= 2) { 5886 // No actual vectorization should happen, if number of parts is the same as 5887 // provided vectorization factor (i.e. the scalar type is used for vector 5888 // code during codegen). 5889 auto *VecTy = VectorType::get(VL[0]->getType(), VF); 5890 if (TTI->getNumberOfParts(VecTy) == VF) 5891 continue; 5892 for (unsigned I = NextInst; I < MaxInst; ++I) { 5893 unsigned OpsWidth = 0; 5894 5895 if (I + VF > MaxInst) 5896 OpsWidth = MaxInst - I; 5897 else 5898 OpsWidth = VF; 5899 5900 if (!isPowerOf2_32(OpsWidth) || OpsWidth < 2) 5901 break; 5902 5903 ArrayRef<Value *> Ops = VL.slice(I, OpsWidth); 5904 // Check that a previous iteration of this loop did not delete the Value. 5905 if (llvm::any_of(Ops, [&R](Value *V) { 5906 auto *I = dyn_cast<Instruction>(V); 5907 return I && R.isDeleted(I); 5908 })) 5909 continue; 5910 5911 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << OpsWidth << " operations " 5912 << "\n"); 5913 5914 R.buildTree(Ops); 5915 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 5916 // TODO: check if we can allow reordering for more cases. 5917 if (AllowReorder && Order) { 5918 // TODO: reorder tree nodes without tree rebuilding. 5919 // Conceptually, there is nothing actually preventing us from trying to 5920 // reorder a larger list. In fact, we do exactly this when vectorizing 5921 // reductions. However, at this point, we only expect to get here when 5922 // there are exactly two operations. 5923 assert(Ops.size() == 2); 5924 Value *ReorderedOps[] = {Ops[1], Ops[0]}; 5925 R.buildTree(ReorderedOps, None); 5926 } 5927 if (R.isTreeTinyAndNotFullyVectorizable()) 5928 continue; 5929 5930 R.computeMinimumValueSizes(); 5931 int Cost = R.getTreeCost() - UserCost; 5932 CandidateFound = true; 5933 MinCost = std::min(MinCost, Cost); 5934 5935 if (Cost < -SLPCostThreshold) { 5936 LLVM_DEBUG(dbgs() << "SLP: Vectorizing list at cost:" << Cost << ".\n"); 5937 R.getORE()->emit(OptimizationRemark(SV_NAME, "VectorizedList", 5938 cast<Instruction>(Ops[0])) 5939 << "SLP vectorized with cost " << ore::NV("Cost", Cost) 5940 << " and with tree size " 5941 << ore::NV("TreeSize", R.getTreeSize())); 5942 5943 R.vectorizeTree(); 5944 // Move to the next bundle. 5945 I += VF - 1; 5946 NextInst = I + 1; 5947 Changed = true; 5948 } 5949 } 5950 } 5951 5952 if (!Changed && CandidateFound) { 5953 R.getORE()->emit([&]() { 5954 return OptimizationRemarkMissed(SV_NAME, "NotBeneficial", I0) 5955 << "List vectorization was possible but not beneficial with cost " 5956 << ore::NV("Cost", MinCost) << " >= " 5957 << ore::NV("Treshold", -SLPCostThreshold); 5958 }); 5959 } else if (!Changed) { 5960 R.getORE()->emit([&]() { 5961 return OptimizationRemarkMissed(SV_NAME, "NotPossible", I0) 5962 << "Cannot SLP vectorize list: vectorization was impossible" 5963 << " with available vectorization factors"; 5964 }); 5965 } 5966 return Changed; 5967 } 5968 5969 bool SLPVectorizerPass::tryToVectorize(Instruction *I, BoUpSLP &R) { 5970 if (!I) 5971 return false; 5972 5973 if (!isa<BinaryOperator>(I) && !isa<CmpInst>(I)) 5974 return false; 5975 5976 Value *P = I->getParent(); 5977 5978 // Vectorize in current basic block only. 5979 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 5980 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 5981 if (!Op0 || !Op1 || Op0->getParent() != P || Op1->getParent() != P) 5982 return false; 5983 5984 // Try to vectorize V. 5985 if (tryToVectorizePair(Op0, Op1, R)) 5986 return true; 5987 5988 auto *A = dyn_cast<BinaryOperator>(Op0); 5989 auto *B = dyn_cast<BinaryOperator>(Op1); 5990 // Try to skip B. 5991 if (B && B->hasOneUse()) { 5992 auto *B0 = dyn_cast<BinaryOperator>(B->getOperand(0)); 5993 auto *B1 = dyn_cast<BinaryOperator>(B->getOperand(1)); 5994 if (B0 && B0->getParent() == P && tryToVectorizePair(A, B0, R)) 5995 return true; 5996 if (B1 && B1->getParent() == P && tryToVectorizePair(A, B1, R)) 5997 return true; 5998 } 5999 6000 // Try to skip A. 6001 if (A && A->hasOneUse()) { 6002 auto *A0 = dyn_cast<BinaryOperator>(A->getOperand(0)); 6003 auto *A1 = dyn_cast<BinaryOperator>(A->getOperand(1)); 6004 if (A0 && A0->getParent() == P && tryToVectorizePair(A0, B, R)) 6005 return true; 6006 if (A1 && A1->getParent() == P && tryToVectorizePair(A1, B, R)) 6007 return true; 6008 } 6009 return false; 6010 } 6011 6012 /// Generate a shuffle mask to be used in a reduction tree. 6013 /// 6014 /// \param VecLen The length of the vector to be reduced. 6015 /// \param NumEltsToRdx The number of elements that should be reduced in the 6016 /// vector. 6017 /// \param IsPairwise Whether the reduction is a pairwise or splitting 6018 /// reduction. A pairwise reduction will generate a mask of 6019 /// <0,2,...> or <1,3,..> while a splitting reduction will generate 6020 /// <2,3, undef,undef> for a vector of 4 and NumElts = 2. 6021 /// \param IsLeft True will generate a mask of even elements, odd otherwise. 6022 static Value *createRdxShuffleMask(unsigned VecLen, unsigned NumEltsToRdx, 6023 bool IsPairwise, bool IsLeft, 6024 IRBuilder<> &Builder) { 6025 assert((IsPairwise || !IsLeft) && "Don't support a <0,1,undef,...> mask"); 6026 6027 SmallVector<Constant *, 32> ShuffleMask( 6028 VecLen, UndefValue::get(Builder.getInt32Ty())); 6029 6030 if (IsPairwise) 6031 // Build a mask of 0, 2, ... (left) or 1, 3, ... (right). 6032 for (unsigned i = 0; i != NumEltsToRdx; ++i) 6033 ShuffleMask[i] = Builder.getInt32(2 * i + !IsLeft); 6034 else 6035 // Move the upper half of the vector to the lower half. 6036 for (unsigned i = 0; i != NumEltsToRdx; ++i) 6037 ShuffleMask[i] = Builder.getInt32(NumEltsToRdx + i); 6038 6039 return ConstantVector::get(ShuffleMask); 6040 } 6041 6042 namespace { 6043 6044 /// Model horizontal reductions. 6045 /// 6046 /// A horizontal reduction is a tree of reduction operations (currently add and 6047 /// fadd) that has operations that can be put into a vector as its leaf. 6048 /// For example, this tree: 6049 /// 6050 /// mul mul mul mul 6051 /// \ / \ / 6052 /// + + 6053 /// \ / 6054 /// + 6055 /// This tree has "mul" as its reduced values and "+" as its reduction 6056 /// operations. A reduction might be feeding into a store or a binary operation 6057 /// feeding a phi. 6058 /// ... 6059 /// \ / 6060 /// + 6061 /// | 6062 /// phi += 6063 /// 6064 /// Or: 6065 /// ... 6066 /// \ / 6067 /// + 6068 /// | 6069 /// *p = 6070 /// 6071 class HorizontalReduction { 6072 using ReductionOpsType = SmallVector<Value *, 16>; 6073 using ReductionOpsListType = SmallVector<ReductionOpsType, 2>; 6074 ReductionOpsListType ReductionOps; 6075 SmallVector<Value *, 32> ReducedVals; 6076 // Use map vector to make stable output. 6077 MapVector<Instruction *, Value *> ExtraArgs; 6078 6079 /// Kind of the reduction data. 6080 enum ReductionKind { 6081 RK_None, /// Not a reduction. 6082 RK_Arithmetic, /// Binary reduction data. 6083 RK_Min, /// Minimum reduction data. 6084 RK_UMin, /// Unsigned minimum reduction data. 6085 RK_Max, /// Maximum reduction data. 6086 RK_UMax, /// Unsigned maximum reduction data. 6087 }; 6088 6089 /// Contains info about operation, like its opcode, left and right operands. 6090 class OperationData { 6091 /// Opcode of the instruction. 6092 unsigned Opcode = 0; 6093 6094 /// Left operand of the reduction operation. 6095 Value *LHS = nullptr; 6096 6097 /// Right operand of the reduction operation. 6098 Value *RHS = nullptr; 6099 6100 /// Kind of the reduction operation. 6101 ReductionKind Kind = RK_None; 6102 6103 /// True if float point min/max reduction has no NaNs. 6104 bool NoNaN = false; 6105 6106 /// Checks if the reduction operation can be vectorized. 6107 bool isVectorizable() const { 6108 return LHS && RHS && 6109 // We currently only support add/mul/logical && min/max reductions. 6110 ((Kind == RK_Arithmetic && 6111 (Opcode == Instruction::Add || Opcode == Instruction::FAdd || 6112 Opcode == Instruction::Mul || Opcode == Instruction::FMul || 6113 Opcode == Instruction::And || Opcode == Instruction::Or || 6114 Opcode == Instruction::Xor)) || 6115 ((Opcode == Instruction::ICmp || Opcode == Instruction::FCmp) && 6116 (Kind == RK_Min || Kind == RK_Max)) || 6117 (Opcode == Instruction::ICmp && 6118 (Kind == RK_UMin || Kind == RK_UMax))); 6119 } 6120 6121 /// Creates reduction operation with the current opcode. 6122 Value *createOp(IRBuilder<> &Builder, const Twine &Name) const { 6123 assert(isVectorizable() && 6124 "Expected add|fadd or min/max reduction operation."); 6125 Value *Cmp = nullptr; 6126 switch (Kind) { 6127 case RK_Arithmetic: 6128 return Builder.CreateBinOp((Instruction::BinaryOps)Opcode, LHS, RHS, 6129 Name); 6130 case RK_Min: 6131 Cmp = Opcode == Instruction::ICmp ? Builder.CreateICmpSLT(LHS, RHS) 6132 : Builder.CreateFCmpOLT(LHS, RHS); 6133 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6134 case RK_Max: 6135 Cmp = Opcode == Instruction::ICmp ? Builder.CreateICmpSGT(LHS, RHS) 6136 : Builder.CreateFCmpOGT(LHS, RHS); 6137 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6138 case RK_UMin: 6139 assert(Opcode == Instruction::ICmp && "Expected integer types."); 6140 Cmp = Builder.CreateICmpULT(LHS, RHS); 6141 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6142 case RK_UMax: 6143 assert(Opcode == Instruction::ICmp && "Expected integer types."); 6144 Cmp = Builder.CreateICmpUGT(LHS, RHS); 6145 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6146 case RK_None: 6147 break; 6148 } 6149 llvm_unreachable("Unknown reduction operation."); 6150 } 6151 6152 public: 6153 explicit OperationData() = default; 6154 6155 /// Construction for reduced values. They are identified by opcode only and 6156 /// don't have associated LHS/RHS values. 6157 explicit OperationData(Value *V) { 6158 if (auto *I = dyn_cast<Instruction>(V)) 6159 Opcode = I->getOpcode(); 6160 } 6161 6162 /// Constructor for reduction operations with opcode and its left and 6163 /// right operands. 6164 OperationData(unsigned Opcode, Value *LHS, Value *RHS, ReductionKind Kind, 6165 bool NoNaN = false) 6166 : Opcode(Opcode), LHS(LHS), RHS(RHS), Kind(Kind), NoNaN(NoNaN) { 6167 assert(Kind != RK_None && "One of the reduction operations is expected."); 6168 } 6169 6170 explicit operator bool() const { return Opcode; } 6171 6172 /// Return true if this operation is any kind of minimum or maximum. 6173 bool isMinMax() const { 6174 switch (Kind) { 6175 case RK_Arithmetic: 6176 return false; 6177 case RK_Min: 6178 case RK_Max: 6179 case RK_UMin: 6180 case RK_UMax: 6181 return true; 6182 case RK_None: 6183 break; 6184 } 6185 llvm_unreachable("Reduction kind is not set"); 6186 } 6187 6188 /// Get the index of the first operand. 6189 unsigned getFirstOperandIndex() const { 6190 assert(!!*this && "The opcode is not set."); 6191 // We allow calling this before 'Kind' is set, so handle that specially. 6192 if (Kind == RK_None) 6193 return 0; 6194 return isMinMax() ? 1 : 0; 6195 } 6196 6197 /// Total number of operands in the reduction operation. 6198 unsigned getNumberOfOperands() const { 6199 assert(Kind != RK_None && !!*this && LHS && RHS && 6200 "Expected reduction operation."); 6201 return isMinMax() ? 3 : 2; 6202 } 6203 6204 /// Checks if the operation has the same parent as \p P. 6205 bool hasSameParent(Instruction *I, Value *P, bool IsRedOp) const { 6206 assert(Kind != RK_None && !!*this && LHS && RHS && 6207 "Expected reduction operation."); 6208 if (!IsRedOp) 6209 return I->getParent() == P; 6210 if (isMinMax()) { 6211 // SelectInst must be used twice while the condition op must have single 6212 // use only. 6213 auto *Cmp = cast<Instruction>(cast<SelectInst>(I)->getCondition()); 6214 return I->getParent() == P && Cmp && Cmp->getParent() == P; 6215 } 6216 // Arithmetic reduction operation must be used once only. 6217 return I->getParent() == P; 6218 } 6219 6220 /// Expected number of uses for reduction operations/reduced values. 6221 bool hasRequiredNumberOfUses(Instruction *I, bool IsReductionOp) const { 6222 assert(Kind != RK_None && !!*this && LHS && RHS && 6223 "Expected reduction operation."); 6224 if (isMinMax()) 6225 return I->hasNUses(2) && 6226 (!IsReductionOp || 6227 cast<SelectInst>(I)->getCondition()->hasOneUse()); 6228 return I->hasOneUse(); 6229 } 6230 6231 /// Initializes the list of reduction operations. 6232 void initReductionOps(ReductionOpsListType &ReductionOps) { 6233 assert(Kind != RK_None && !!*this && LHS && RHS && 6234 "Expected reduction operation."); 6235 if (isMinMax()) 6236 ReductionOps.assign(2, ReductionOpsType()); 6237 else 6238 ReductionOps.assign(1, ReductionOpsType()); 6239 } 6240 6241 /// Add all reduction operations for the reduction instruction \p I. 6242 void addReductionOps(Instruction *I, ReductionOpsListType &ReductionOps) { 6243 assert(Kind != RK_None && !!*this && LHS && RHS && 6244 "Expected reduction operation."); 6245 if (isMinMax()) { 6246 ReductionOps[0].emplace_back(cast<SelectInst>(I)->getCondition()); 6247 ReductionOps[1].emplace_back(I); 6248 } else { 6249 ReductionOps[0].emplace_back(I); 6250 } 6251 } 6252 6253 /// Checks if instruction is associative and can be vectorized. 6254 bool isAssociative(Instruction *I) const { 6255 assert(Kind != RK_None && *this && LHS && RHS && 6256 "Expected reduction operation."); 6257 switch (Kind) { 6258 case RK_Arithmetic: 6259 return I->isAssociative(); 6260 case RK_Min: 6261 case RK_Max: 6262 return Opcode == Instruction::ICmp || 6263 cast<Instruction>(I->getOperand(0))->isFast(); 6264 case RK_UMin: 6265 case RK_UMax: 6266 assert(Opcode == Instruction::ICmp && 6267 "Only integer compare operation is expected."); 6268 return true; 6269 case RK_None: 6270 break; 6271 } 6272 llvm_unreachable("Reduction kind is not set"); 6273 } 6274 6275 /// Checks if the reduction operation can be vectorized. 6276 bool isVectorizable(Instruction *I) const { 6277 return isVectorizable() && isAssociative(I); 6278 } 6279 6280 /// Checks if two operation data are both a reduction op or both a reduced 6281 /// value. 6282 bool operator==(const OperationData &OD) const { 6283 assert(((Kind != OD.Kind) || ((!LHS == !OD.LHS) && (!RHS == !OD.RHS))) && 6284 "One of the comparing operations is incorrect."); 6285 return this == &OD || (Kind == OD.Kind && Opcode == OD.Opcode); 6286 } 6287 bool operator!=(const OperationData &OD) const { return !(*this == OD); } 6288 void clear() { 6289 Opcode = 0; 6290 LHS = nullptr; 6291 RHS = nullptr; 6292 Kind = RK_None; 6293 NoNaN = false; 6294 } 6295 6296 /// Get the opcode of the reduction operation. 6297 unsigned getOpcode() const { 6298 assert(isVectorizable() && "Expected vectorizable operation."); 6299 return Opcode; 6300 } 6301 6302 /// Get kind of reduction data. 6303 ReductionKind getKind() const { return Kind; } 6304 Value *getLHS() const { return LHS; } 6305 Value *getRHS() const { return RHS; } 6306 Type *getConditionType() const { 6307 return isMinMax() ? CmpInst::makeCmpResultType(LHS->getType()) : nullptr; 6308 } 6309 6310 /// Creates reduction operation with the current opcode with the IR flags 6311 /// from \p ReductionOps. 6312 Value *createOp(IRBuilder<> &Builder, const Twine &Name, 6313 const ReductionOpsListType &ReductionOps) const { 6314 assert(isVectorizable() && 6315 "Expected add|fadd or min/max reduction operation."); 6316 auto *Op = createOp(Builder, Name); 6317 switch (Kind) { 6318 case RK_Arithmetic: 6319 propagateIRFlags(Op, ReductionOps[0]); 6320 return Op; 6321 case RK_Min: 6322 case RK_Max: 6323 case RK_UMin: 6324 case RK_UMax: 6325 if (auto *SI = dyn_cast<SelectInst>(Op)) 6326 propagateIRFlags(SI->getCondition(), ReductionOps[0]); 6327 propagateIRFlags(Op, ReductionOps[1]); 6328 return Op; 6329 case RK_None: 6330 break; 6331 } 6332 llvm_unreachable("Unknown reduction operation."); 6333 } 6334 /// Creates reduction operation with the current opcode with the IR flags 6335 /// from \p I. 6336 Value *createOp(IRBuilder<> &Builder, const Twine &Name, 6337 Instruction *I) const { 6338 assert(isVectorizable() && 6339 "Expected add|fadd or min/max reduction operation."); 6340 auto *Op = createOp(Builder, Name); 6341 switch (Kind) { 6342 case RK_Arithmetic: 6343 propagateIRFlags(Op, I); 6344 return Op; 6345 case RK_Min: 6346 case RK_Max: 6347 case RK_UMin: 6348 case RK_UMax: 6349 if (auto *SI = dyn_cast<SelectInst>(Op)) { 6350 propagateIRFlags(SI->getCondition(), 6351 cast<SelectInst>(I)->getCondition()); 6352 } 6353 propagateIRFlags(Op, I); 6354 return Op; 6355 case RK_None: 6356 break; 6357 } 6358 llvm_unreachable("Unknown reduction operation."); 6359 } 6360 6361 TargetTransformInfo::ReductionFlags getFlags() const { 6362 TargetTransformInfo::ReductionFlags Flags; 6363 Flags.NoNaN = NoNaN; 6364 switch (Kind) { 6365 case RK_Arithmetic: 6366 break; 6367 case RK_Min: 6368 Flags.IsSigned = Opcode == Instruction::ICmp; 6369 Flags.IsMaxOp = false; 6370 break; 6371 case RK_Max: 6372 Flags.IsSigned = Opcode == Instruction::ICmp; 6373 Flags.IsMaxOp = true; 6374 break; 6375 case RK_UMin: 6376 Flags.IsSigned = false; 6377 Flags.IsMaxOp = false; 6378 break; 6379 case RK_UMax: 6380 Flags.IsSigned = false; 6381 Flags.IsMaxOp = true; 6382 break; 6383 case RK_None: 6384 llvm_unreachable("Reduction kind is not set"); 6385 } 6386 return Flags; 6387 } 6388 }; 6389 6390 WeakTrackingVH ReductionRoot; 6391 6392 /// The operation data of the reduction operation. 6393 OperationData ReductionData; 6394 6395 /// The operation data of the values we perform a reduction on. 6396 OperationData ReducedValueData; 6397 6398 /// Should we model this reduction as a pairwise reduction tree or a tree that 6399 /// splits the vector in halves and adds those halves. 6400 bool IsPairwiseReduction = false; 6401 6402 /// Checks if the ParentStackElem.first should be marked as a reduction 6403 /// operation with an extra argument or as extra argument itself. 6404 void markExtraArg(std::pair<Instruction *, unsigned> &ParentStackElem, 6405 Value *ExtraArg) { 6406 if (ExtraArgs.count(ParentStackElem.first)) { 6407 ExtraArgs[ParentStackElem.first] = nullptr; 6408 // We ran into something like: 6409 // ParentStackElem.first = ExtraArgs[ParentStackElem.first] + ExtraArg. 6410 // The whole ParentStackElem.first should be considered as an extra value 6411 // in this case. 6412 // Do not perform analysis of remaining operands of ParentStackElem.first 6413 // instruction, this whole instruction is an extra argument. 6414 ParentStackElem.second = ParentStackElem.first->getNumOperands(); 6415 } else { 6416 // We ran into something like: 6417 // ParentStackElem.first += ... + ExtraArg + ... 6418 ExtraArgs[ParentStackElem.first] = ExtraArg; 6419 } 6420 } 6421 6422 static OperationData getOperationData(Value *V) { 6423 if (!V) 6424 return OperationData(); 6425 6426 Value *LHS; 6427 Value *RHS; 6428 if (m_BinOp(m_Value(LHS), m_Value(RHS)).match(V)) { 6429 return OperationData(cast<BinaryOperator>(V)->getOpcode(), LHS, RHS, 6430 RK_Arithmetic); 6431 } 6432 if (auto *Select = dyn_cast<SelectInst>(V)) { 6433 // Look for a min/max pattern. 6434 if (m_UMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 6435 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMin); 6436 } else if (m_SMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 6437 return OperationData(Instruction::ICmp, LHS, RHS, RK_Min); 6438 } else if (m_OrdFMin(m_Value(LHS), m_Value(RHS)).match(Select) || 6439 m_UnordFMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 6440 return OperationData( 6441 Instruction::FCmp, LHS, RHS, RK_Min, 6442 cast<Instruction>(Select->getCondition())->hasNoNaNs()); 6443 } else if (m_UMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 6444 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMax); 6445 } else if (m_SMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 6446 return OperationData(Instruction::ICmp, LHS, RHS, RK_Max); 6447 } else if (m_OrdFMax(m_Value(LHS), m_Value(RHS)).match(Select) || 6448 m_UnordFMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 6449 return OperationData( 6450 Instruction::FCmp, LHS, RHS, RK_Max, 6451 cast<Instruction>(Select->getCondition())->hasNoNaNs()); 6452 } else { 6453 // Try harder: look for min/max pattern based on instructions producing 6454 // same values such as: select ((cmp Inst1, Inst2), Inst1, Inst2). 6455 // During the intermediate stages of SLP, it's very common to have 6456 // pattern like this (since optimizeGatherSequence is run only once 6457 // at the end): 6458 // %1 = extractelement <2 x i32> %a, i32 0 6459 // %2 = extractelement <2 x i32> %a, i32 1 6460 // %cond = icmp sgt i32 %1, %2 6461 // %3 = extractelement <2 x i32> %a, i32 0 6462 // %4 = extractelement <2 x i32> %a, i32 1 6463 // %select = select i1 %cond, i32 %3, i32 %4 6464 CmpInst::Predicate Pred; 6465 Instruction *L1; 6466 Instruction *L2; 6467 6468 LHS = Select->getTrueValue(); 6469 RHS = Select->getFalseValue(); 6470 Value *Cond = Select->getCondition(); 6471 6472 // TODO: Support inverse predicates. 6473 if (match(Cond, m_Cmp(Pred, m_Specific(LHS), m_Instruction(L2)))) { 6474 if (!isa<ExtractElementInst>(RHS) || 6475 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6476 return OperationData(V); 6477 } else if (match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Specific(RHS)))) { 6478 if (!isa<ExtractElementInst>(LHS) || 6479 !L1->isIdenticalTo(cast<Instruction>(LHS))) 6480 return OperationData(V); 6481 } else { 6482 if (!isa<ExtractElementInst>(LHS) || !isa<ExtractElementInst>(RHS)) 6483 return OperationData(V); 6484 if (!match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Instruction(L2))) || 6485 !L1->isIdenticalTo(cast<Instruction>(LHS)) || 6486 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6487 return OperationData(V); 6488 } 6489 switch (Pred) { 6490 default: 6491 return OperationData(V); 6492 6493 case CmpInst::ICMP_ULT: 6494 case CmpInst::ICMP_ULE: 6495 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMin); 6496 6497 case CmpInst::ICMP_SLT: 6498 case CmpInst::ICMP_SLE: 6499 return OperationData(Instruction::ICmp, LHS, RHS, RK_Min); 6500 6501 case CmpInst::FCMP_OLT: 6502 case CmpInst::FCMP_OLE: 6503 case CmpInst::FCMP_ULT: 6504 case CmpInst::FCMP_ULE: 6505 return OperationData(Instruction::FCmp, LHS, RHS, RK_Min, 6506 cast<Instruction>(Cond)->hasNoNaNs()); 6507 6508 case CmpInst::ICMP_UGT: 6509 case CmpInst::ICMP_UGE: 6510 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMax); 6511 6512 case CmpInst::ICMP_SGT: 6513 case CmpInst::ICMP_SGE: 6514 return OperationData(Instruction::ICmp, LHS, RHS, RK_Max); 6515 6516 case CmpInst::FCMP_OGT: 6517 case CmpInst::FCMP_OGE: 6518 case CmpInst::FCMP_UGT: 6519 case CmpInst::FCMP_UGE: 6520 return OperationData(Instruction::FCmp, LHS, RHS, RK_Max, 6521 cast<Instruction>(Cond)->hasNoNaNs()); 6522 } 6523 } 6524 } 6525 return OperationData(V); 6526 } 6527 6528 public: 6529 HorizontalReduction() = default; 6530 6531 /// Try to find a reduction tree. 6532 bool matchAssociativeReduction(PHINode *Phi, Instruction *B) { 6533 assert((!Phi || is_contained(Phi->operands(), B)) && 6534 "Thi phi needs to use the binary operator"); 6535 6536 ReductionData = getOperationData(B); 6537 6538 // We could have a initial reductions that is not an add. 6539 // r *= v1 + v2 + v3 + v4 6540 // In such a case start looking for a tree rooted in the first '+'. 6541 if (Phi) { 6542 if (ReductionData.getLHS() == Phi) { 6543 Phi = nullptr; 6544 B = dyn_cast<Instruction>(ReductionData.getRHS()); 6545 ReductionData = getOperationData(B); 6546 } else if (ReductionData.getRHS() == Phi) { 6547 Phi = nullptr; 6548 B = dyn_cast<Instruction>(ReductionData.getLHS()); 6549 ReductionData = getOperationData(B); 6550 } 6551 } 6552 6553 if (!ReductionData.isVectorizable(B)) 6554 return false; 6555 6556 Type *Ty = B->getType(); 6557 if (!isValidElementType(Ty)) 6558 return false; 6559 if (!Ty->isIntOrIntVectorTy() && !Ty->isFPOrFPVectorTy()) 6560 return false; 6561 6562 ReducedValueData.clear(); 6563 ReductionRoot = B; 6564 6565 // Post order traverse the reduction tree starting at B. We only handle true 6566 // trees containing only binary operators. 6567 SmallVector<std::pair<Instruction *, unsigned>, 32> Stack; 6568 Stack.push_back(std::make_pair(B, ReductionData.getFirstOperandIndex())); 6569 ReductionData.initReductionOps(ReductionOps); 6570 while (!Stack.empty()) { 6571 Instruction *TreeN = Stack.back().first; 6572 unsigned EdgeToVist = Stack.back().second++; 6573 OperationData OpData = getOperationData(TreeN); 6574 bool IsReducedValue = OpData != ReductionData; 6575 6576 // Postorder vist. 6577 if (IsReducedValue || EdgeToVist == OpData.getNumberOfOperands()) { 6578 if (IsReducedValue) 6579 ReducedVals.push_back(TreeN); 6580 else { 6581 auto I = ExtraArgs.find(TreeN); 6582 if (I != ExtraArgs.end() && !I->second) { 6583 // Check if TreeN is an extra argument of its parent operation. 6584 if (Stack.size() <= 1) { 6585 // TreeN can't be an extra argument as it is a root reduction 6586 // operation. 6587 return false; 6588 } 6589 // Yes, TreeN is an extra argument, do not add it to a list of 6590 // reduction operations. 6591 // Stack[Stack.size() - 2] always points to the parent operation. 6592 markExtraArg(Stack[Stack.size() - 2], TreeN); 6593 ExtraArgs.erase(TreeN); 6594 } else 6595 ReductionData.addReductionOps(TreeN, ReductionOps); 6596 } 6597 // Retract. 6598 Stack.pop_back(); 6599 continue; 6600 } 6601 6602 // Visit left or right. 6603 Value *NextV = TreeN->getOperand(EdgeToVist); 6604 if (NextV != Phi) { 6605 auto *I = dyn_cast<Instruction>(NextV); 6606 OpData = getOperationData(I); 6607 // Continue analysis if the next operand is a reduction operation or 6608 // (possibly) a reduced value. If the reduced value opcode is not set, 6609 // the first met operation != reduction operation is considered as the 6610 // reduced value class. 6611 if (I && (!ReducedValueData || OpData == ReducedValueData || 6612 OpData == ReductionData)) { 6613 const bool IsReductionOperation = OpData == ReductionData; 6614 // Only handle trees in the current basic block. 6615 if (!ReductionData.hasSameParent(I, B->getParent(), 6616 IsReductionOperation)) { 6617 // I is an extra argument for TreeN (its parent operation). 6618 markExtraArg(Stack.back(), I); 6619 continue; 6620 } 6621 6622 // Each tree node needs to have minimal number of users except for the 6623 // ultimate reduction. 6624 if (!ReductionData.hasRequiredNumberOfUses(I, 6625 OpData == ReductionData) && 6626 I != B) { 6627 // I is an extra argument for TreeN (its parent operation). 6628 markExtraArg(Stack.back(), I); 6629 continue; 6630 } 6631 6632 if (IsReductionOperation) { 6633 // We need to be able to reassociate the reduction operations. 6634 if (!OpData.isAssociative(I)) { 6635 // I is an extra argument for TreeN (its parent operation). 6636 markExtraArg(Stack.back(), I); 6637 continue; 6638 } 6639 } else if (ReducedValueData && 6640 ReducedValueData != OpData) { 6641 // Make sure that the opcodes of the operations that we are going to 6642 // reduce match. 6643 // I is an extra argument for TreeN (its parent operation). 6644 markExtraArg(Stack.back(), I); 6645 continue; 6646 } else if (!ReducedValueData) 6647 ReducedValueData = OpData; 6648 6649 Stack.push_back(std::make_pair(I, OpData.getFirstOperandIndex())); 6650 continue; 6651 } 6652 } 6653 // NextV is an extra argument for TreeN (its parent operation). 6654 markExtraArg(Stack.back(), NextV); 6655 } 6656 return true; 6657 } 6658 6659 /// Attempt to vectorize the tree found by 6660 /// matchAssociativeReduction. 6661 bool tryToReduce(BoUpSLP &V, TargetTransformInfo *TTI) { 6662 if (ReducedVals.empty()) 6663 return false; 6664 6665 // If there is a sufficient number of reduction values, reduce 6666 // to a nearby power-of-2. Can safely generate oversized 6667 // vectors and rely on the backend to split them to legal sizes. 6668 unsigned NumReducedVals = ReducedVals.size(); 6669 if (NumReducedVals < 4) 6670 return false; 6671 6672 unsigned ReduxWidth = PowerOf2Floor(NumReducedVals); 6673 6674 Value *VectorizedTree = nullptr; 6675 6676 // FIXME: Fast-math-flags should be set based on the instructions in the 6677 // reduction (not all of 'fast' are required). 6678 IRBuilder<> Builder(cast<Instruction>(ReductionRoot)); 6679 FastMathFlags Unsafe; 6680 Unsafe.setFast(); 6681 Builder.setFastMathFlags(Unsafe); 6682 unsigned i = 0; 6683 6684 BoUpSLP::ExtraValueToDebugLocsMap ExternallyUsedValues; 6685 // The same extra argument may be used several time, so log each attempt 6686 // to use it. 6687 for (auto &Pair : ExtraArgs) { 6688 assert(Pair.first && "DebugLoc must be set."); 6689 ExternallyUsedValues[Pair.second].push_back(Pair.first); 6690 } 6691 6692 // The compare instruction of a min/max is the insertion point for new 6693 // instructions and may be replaced with a new compare instruction. 6694 auto getCmpForMinMaxReduction = [](Instruction *RdxRootInst) { 6695 assert(isa<SelectInst>(RdxRootInst) && 6696 "Expected min/max reduction to have select root instruction"); 6697 Value *ScalarCond = cast<SelectInst>(RdxRootInst)->getCondition(); 6698 assert(isa<Instruction>(ScalarCond) && 6699 "Expected min/max reduction to have compare condition"); 6700 return cast<Instruction>(ScalarCond); 6701 }; 6702 6703 // The reduction root is used as the insertion point for new instructions, 6704 // so set it as externally used to prevent it from being deleted. 6705 ExternallyUsedValues[ReductionRoot]; 6706 SmallVector<Value *, 16> IgnoreList; 6707 for (auto &V : ReductionOps) 6708 IgnoreList.append(V.begin(), V.end()); 6709 while (i < NumReducedVals - ReduxWidth + 1 && ReduxWidth > 2) { 6710 auto VL = makeArrayRef(&ReducedVals[i], ReduxWidth); 6711 V.buildTree(VL, ExternallyUsedValues, IgnoreList); 6712 Optional<ArrayRef<unsigned>> Order = V.bestOrder(); 6713 // TODO: Handle orders of size less than number of elements in the vector. 6714 if (Order && Order->size() == VL.size()) { 6715 // TODO: reorder tree nodes without tree rebuilding. 6716 SmallVector<Value *, 4> ReorderedOps(VL.size()); 6717 llvm::transform(*Order, ReorderedOps.begin(), 6718 [VL](const unsigned Idx) { return VL[Idx]; }); 6719 V.buildTree(ReorderedOps, ExternallyUsedValues, IgnoreList); 6720 } 6721 if (V.isTreeTinyAndNotFullyVectorizable()) 6722 break; 6723 if (V.isLoadCombineReductionCandidate(ReductionData.getOpcode())) 6724 break; 6725 6726 V.computeMinimumValueSizes(); 6727 6728 // Estimate cost. 6729 int TreeCost = V.getTreeCost(); 6730 int ReductionCost = getReductionCost(TTI, ReducedVals[i], ReduxWidth); 6731 int Cost = TreeCost + ReductionCost; 6732 if (Cost >= -SLPCostThreshold) { 6733 V.getORE()->emit([&]() { 6734 return OptimizationRemarkMissed( 6735 SV_NAME, "HorSLPNotBeneficial", cast<Instruction>(VL[0])) 6736 << "Vectorizing horizontal reduction is possible" 6737 << "but not beneficial with cost " 6738 << ore::NV("Cost", Cost) << " and threshold " 6739 << ore::NV("Threshold", -SLPCostThreshold); 6740 }); 6741 break; 6742 } 6743 6744 LLVM_DEBUG(dbgs() << "SLP: Vectorizing horizontal reduction at cost:" 6745 << Cost << ". (HorRdx)\n"); 6746 V.getORE()->emit([&]() { 6747 return OptimizationRemark( 6748 SV_NAME, "VectorizedHorizontalReduction", cast<Instruction>(VL[0])) 6749 << "Vectorized horizontal reduction with cost " 6750 << ore::NV("Cost", Cost) << " and with tree size " 6751 << ore::NV("TreeSize", V.getTreeSize()); 6752 }); 6753 6754 // Vectorize a tree. 6755 DebugLoc Loc = cast<Instruction>(ReducedVals[i])->getDebugLoc(); 6756 Value *VectorizedRoot = V.vectorizeTree(ExternallyUsedValues); 6757 6758 // Emit a reduction. For min/max, the root is a select, but the insertion 6759 // point is the compare condition of that select. 6760 Instruction *RdxRootInst = cast<Instruction>(ReductionRoot); 6761 if (ReductionData.isMinMax()) 6762 Builder.SetInsertPoint(getCmpForMinMaxReduction(RdxRootInst)); 6763 else 6764 Builder.SetInsertPoint(RdxRootInst); 6765 6766 Value *ReducedSubTree = 6767 emitReduction(VectorizedRoot, Builder, ReduxWidth, TTI); 6768 if (VectorizedTree) { 6769 Builder.SetCurrentDebugLocation(Loc); 6770 OperationData VectReductionData(ReductionData.getOpcode(), 6771 VectorizedTree, ReducedSubTree, 6772 ReductionData.getKind()); 6773 VectorizedTree = 6774 VectReductionData.createOp(Builder, "op.rdx", ReductionOps); 6775 } else 6776 VectorizedTree = ReducedSubTree; 6777 i += ReduxWidth; 6778 ReduxWidth = PowerOf2Floor(NumReducedVals - i); 6779 } 6780 6781 if (VectorizedTree) { 6782 // Finish the reduction. 6783 for (; i < NumReducedVals; ++i) { 6784 auto *I = cast<Instruction>(ReducedVals[i]); 6785 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 6786 OperationData VectReductionData(ReductionData.getOpcode(), 6787 VectorizedTree, I, 6788 ReductionData.getKind()); 6789 VectorizedTree = VectReductionData.createOp(Builder, "", ReductionOps); 6790 } 6791 for (auto &Pair : ExternallyUsedValues) { 6792 // Add each externally used value to the final reduction. 6793 for (auto *I : Pair.second) { 6794 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 6795 OperationData VectReductionData(ReductionData.getOpcode(), 6796 VectorizedTree, Pair.first, 6797 ReductionData.getKind()); 6798 VectorizedTree = VectReductionData.createOp(Builder, "op.extra", I); 6799 } 6800 } 6801 6802 // Update users. For a min/max reduction that ends with a compare and 6803 // select, we also have to RAUW for the compare instruction feeding the 6804 // reduction root. That's because the original compare may have extra uses 6805 // besides the final select of the reduction. 6806 if (ReductionData.isMinMax()) { 6807 if (auto *VecSelect = dyn_cast<SelectInst>(VectorizedTree)) { 6808 Instruction *ScalarCmp = 6809 getCmpForMinMaxReduction(cast<Instruction>(ReductionRoot)); 6810 ScalarCmp->replaceAllUsesWith(VecSelect->getCondition()); 6811 } 6812 } 6813 ReductionRoot->replaceAllUsesWith(VectorizedTree); 6814 6815 // Mark all scalar reduction ops for deletion, they are replaced by the 6816 // vector reductions. 6817 V.eraseInstructions(IgnoreList); 6818 } 6819 return VectorizedTree != nullptr; 6820 } 6821 6822 unsigned numReductionValues() const { 6823 return ReducedVals.size(); 6824 } 6825 6826 private: 6827 /// Calculate the cost of a reduction. 6828 int getReductionCost(TargetTransformInfo *TTI, Value *FirstReducedVal, 6829 unsigned ReduxWidth) { 6830 Type *ScalarTy = FirstReducedVal->getType(); 6831 Type *VecTy = VectorType::get(ScalarTy, ReduxWidth); 6832 6833 int PairwiseRdxCost; 6834 int SplittingRdxCost; 6835 switch (ReductionData.getKind()) { 6836 case RK_Arithmetic: 6837 PairwiseRdxCost = 6838 TTI->getArithmeticReductionCost(ReductionData.getOpcode(), VecTy, 6839 /*IsPairwiseForm=*/true); 6840 SplittingRdxCost = 6841 TTI->getArithmeticReductionCost(ReductionData.getOpcode(), VecTy, 6842 /*IsPairwiseForm=*/false); 6843 break; 6844 case RK_Min: 6845 case RK_Max: 6846 case RK_UMin: 6847 case RK_UMax: { 6848 Type *VecCondTy = CmpInst::makeCmpResultType(VecTy); 6849 bool IsUnsigned = ReductionData.getKind() == RK_UMin || 6850 ReductionData.getKind() == RK_UMax; 6851 PairwiseRdxCost = 6852 TTI->getMinMaxReductionCost(VecTy, VecCondTy, 6853 /*IsPairwiseForm=*/true, IsUnsigned); 6854 SplittingRdxCost = 6855 TTI->getMinMaxReductionCost(VecTy, VecCondTy, 6856 /*IsPairwiseForm=*/false, IsUnsigned); 6857 break; 6858 } 6859 case RK_None: 6860 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 6861 } 6862 6863 IsPairwiseReduction = PairwiseRdxCost < SplittingRdxCost; 6864 int VecReduxCost = IsPairwiseReduction ? PairwiseRdxCost : SplittingRdxCost; 6865 6866 int ScalarReduxCost = 0; 6867 switch (ReductionData.getKind()) { 6868 case RK_Arithmetic: 6869 ScalarReduxCost = 6870 TTI->getArithmeticInstrCost(ReductionData.getOpcode(), ScalarTy); 6871 break; 6872 case RK_Min: 6873 case RK_Max: 6874 case RK_UMin: 6875 case RK_UMax: 6876 ScalarReduxCost = 6877 TTI->getCmpSelInstrCost(ReductionData.getOpcode(), ScalarTy) + 6878 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 6879 CmpInst::makeCmpResultType(ScalarTy)); 6880 break; 6881 case RK_None: 6882 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 6883 } 6884 ScalarReduxCost *= (ReduxWidth - 1); 6885 6886 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << VecReduxCost - ScalarReduxCost 6887 << " for reduction that starts with " << *FirstReducedVal 6888 << " (It is a " 6889 << (IsPairwiseReduction ? "pairwise" : "splitting") 6890 << " reduction)\n"); 6891 6892 return VecReduxCost - ScalarReduxCost; 6893 } 6894 6895 /// Emit a horizontal reduction of the vectorized value. 6896 Value *emitReduction(Value *VectorizedValue, IRBuilder<> &Builder, 6897 unsigned ReduxWidth, const TargetTransformInfo *TTI) { 6898 assert(VectorizedValue && "Need to have a vectorized tree node"); 6899 assert(isPowerOf2_32(ReduxWidth) && 6900 "We only handle power-of-two reductions for now"); 6901 6902 if (!IsPairwiseReduction) { 6903 // FIXME: The builder should use an FMF guard. It should not be hard-coded 6904 // to 'fast'. 6905 assert(Builder.getFastMathFlags().isFast() && "Expected 'fast' FMF"); 6906 return createSimpleTargetReduction( 6907 Builder, TTI, ReductionData.getOpcode(), VectorizedValue, 6908 ReductionData.getFlags(), ReductionOps.back()); 6909 } 6910 6911 Value *TmpVec = VectorizedValue; 6912 for (unsigned i = ReduxWidth / 2; i != 0; i >>= 1) { 6913 Value *LeftMask = 6914 createRdxShuffleMask(ReduxWidth, i, true, true, Builder); 6915 Value *RightMask = 6916 createRdxShuffleMask(ReduxWidth, i, true, false, Builder); 6917 6918 Value *LeftShuf = Builder.CreateShuffleVector( 6919 TmpVec, UndefValue::get(TmpVec->getType()), LeftMask, "rdx.shuf.l"); 6920 Value *RightShuf = Builder.CreateShuffleVector( 6921 TmpVec, UndefValue::get(TmpVec->getType()), (RightMask), 6922 "rdx.shuf.r"); 6923 OperationData VectReductionData(ReductionData.getOpcode(), LeftShuf, 6924 RightShuf, ReductionData.getKind()); 6925 TmpVec = VectReductionData.createOp(Builder, "op.rdx", ReductionOps); 6926 } 6927 6928 // The result is in the first element of the vector. 6929 return Builder.CreateExtractElement(TmpVec, Builder.getInt32(0)); 6930 } 6931 }; 6932 6933 } // end anonymous namespace 6934 6935 /// Recognize construction of vectors like 6936 /// %ra = insertelement <4 x float> undef, float %s0, i32 0 6937 /// %rb = insertelement <4 x float> %ra, float %s1, i32 1 6938 /// %rc = insertelement <4 x float> %rb, float %s2, i32 2 6939 /// %rd = insertelement <4 x float> %rc, float %s3, i32 3 6940 /// starting from the last insertelement or insertvalue instruction. 6941 /// 6942 /// Also recognize aggregates like {<2 x float>, <2 x float>}, 6943 /// {{float, float}, {float, float}}, [2 x {float, float}] and so on. 6944 /// See llvm/test/Transforms/SLPVectorizer/X86/pr42022.ll for examples. 6945 /// 6946 /// Assume LastInsertInst is of InsertElementInst or InsertValueInst type. 6947 /// 6948 /// \return true if it matches. 6949 static bool findBuildAggregate(Value *LastInsertInst, TargetTransformInfo *TTI, 6950 SmallVectorImpl<Value *> &BuildVectorOpds, 6951 int &UserCost) { 6952 assert((isa<InsertElementInst>(LastInsertInst) || 6953 isa<InsertValueInst>(LastInsertInst)) && 6954 "Expected insertelement or insertvalue instruction!"); 6955 UserCost = 0; 6956 do { 6957 Value *InsertedOperand; 6958 if (auto *IE = dyn_cast<InsertElementInst>(LastInsertInst)) { 6959 InsertedOperand = IE->getOperand(1); 6960 LastInsertInst = IE->getOperand(0); 6961 if (auto *CI = dyn_cast<ConstantInt>(IE->getOperand(2))) { 6962 UserCost += TTI->getVectorInstrCost(Instruction::InsertElement, 6963 IE->getType(), CI->getZExtValue()); 6964 } 6965 } else { 6966 auto *IV = cast<InsertValueInst>(LastInsertInst); 6967 InsertedOperand = IV->getInsertedValueOperand(); 6968 LastInsertInst = IV->getAggregateOperand(); 6969 } 6970 if (isa<InsertElementInst>(InsertedOperand) || 6971 isa<InsertValueInst>(InsertedOperand)) { 6972 int TmpUserCost; 6973 SmallVector<Value *, 8> TmpBuildVectorOpds; 6974 if (!findBuildAggregate(InsertedOperand, TTI, TmpBuildVectorOpds, 6975 TmpUserCost)) 6976 return false; 6977 BuildVectorOpds.append(TmpBuildVectorOpds.rbegin(), 6978 TmpBuildVectorOpds.rend()); 6979 UserCost += TmpUserCost; 6980 } else { 6981 BuildVectorOpds.push_back(InsertedOperand); 6982 } 6983 if (isa<UndefValue>(LastInsertInst)) 6984 break; 6985 if ((!isa<InsertValueInst>(LastInsertInst) && 6986 !isa<InsertElementInst>(LastInsertInst)) || 6987 !LastInsertInst->hasOneUse()) 6988 return false; 6989 } while (true); 6990 std::reverse(BuildVectorOpds.begin(), BuildVectorOpds.end()); 6991 return true; 6992 } 6993 6994 static bool PhiTypeSorterFunc(Value *V, Value *V2) { 6995 return V->getType() < V2->getType(); 6996 } 6997 6998 /// Try and get a reduction value from a phi node. 6999 /// 7000 /// Given a phi node \p P in a block \p ParentBB, consider possible reductions 7001 /// if they come from either \p ParentBB or a containing loop latch. 7002 /// 7003 /// \returns A candidate reduction value if possible, or \code nullptr \endcode 7004 /// if not possible. 7005 static Value *getReductionValue(const DominatorTree *DT, PHINode *P, 7006 BasicBlock *ParentBB, LoopInfo *LI) { 7007 // There are situations where the reduction value is not dominated by the 7008 // reduction phi. Vectorizing such cases has been reported to cause 7009 // miscompiles. See PR25787. 7010 auto DominatedReduxValue = [&](Value *R) { 7011 return isa<Instruction>(R) && 7012 DT->dominates(P->getParent(), cast<Instruction>(R)->getParent()); 7013 }; 7014 7015 Value *Rdx = nullptr; 7016 7017 // Return the incoming value if it comes from the same BB as the phi node. 7018 if (P->getIncomingBlock(0) == ParentBB) { 7019 Rdx = P->getIncomingValue(0); 7020 } else if (P->getIncomingBlock(1) == ParentBB) { 7021 Rdx = P->getIncomingValue(1); 7022 } 7023 7024 if (Rdx && DominatedReduxValue(Rdx)) 7025 return Rdx; 7026 7027 // Otherwise, check whether we have a loop latch to look at. 7028 Loop *BBL = LI->getLoopFor(ParentBB); 7029 if (!BBL) 7030 return nullptr; 7031 BasicBlock *BBLatch = BBL->getLoopLatch(); 7032 if (!BBLatch) 7033 return nullptr; 7034 7035 // There is a loop latch, return the incoming value if it comes from 7036 // that. This reduction pattern occasionally turns up. 7037 if (P->getIncomingBlock(0) == BBLatch) { 7038 Rdx = P->getIncomingValue(0); 7039 } else if (P->getIncomingBlock(1) == BBLatch) { 7040 Rdx = P->getIncomingValue(1); 7041 } 7042 7043 if (Rdx && DominatedReduxValue(Rdx)) 7044 return Rdx; 7045 7046 return nullptr; 7047 } 7048 7049 /// Attempt to reduce a horizontal reduction. 7050 /// If it is legal to match a horizontal reduction feeding the phi node \a P 7051 /// with reduction operators \a Root (or one of its operands) in a basic block 7052 /// \a BB, then check if it can be done. If horizontal reduction is not found 7053 /// and root instruction is a binary operation, vectorization of the operands is 7054 /// attempted. 7055 /// \returns true if a horizontal reduction was matched and reduced or operands 7056 /// of one of the binary instruction were vectorized. 7057 /// \returns false if a horizontal reduction was not matched (or not possible) 7058 /// or no vectorization of any binary operation feeding \a Root instruction was 7059 /// performed. 7060 static bool tryToVectorizeHorReductionOrInstOperands( 7061 PHINode *P, Instruction *Root, BasicBlock *BB, BoUpSLP &R, 7062 TargetTransformInfo *TTI, 7063 const function_ref<bool(Instruction *, BoUpSLP &)> Vectorize) { 7064 if (!ShouldVectorizeHor) 7065 return false; 7066 7067 if (!Root) 7068 return false; 7069 7070 if (Root->getParent() != BB || isa<PHINode>(Root)) 7071 return false; 7072 // Start analysis starting from Root instruction. If horizontal reduction is 7073 // found, try to vectorize it. If it is not a horizontal reduction or 7074 // vectorization is not possible or not effective, and currently analyzed 7075 // instruction is a binary operation, try to vectorize the operands, using 7076 // pre-order DFS traversal order. If the operands were not vectorized, repeat 7077 // the same procedure considering each operand as a possible root of the 7078 // horizontal reduction. 7079 // Interrupt the process if the Root instruction itself was vectorized or all 7080 // sub-trees not higher that RecursionMaxDepth were analyzed/vectorized. 7081 SmallVector<std::pair<Instruction *, unsigned>, 8> Stack(1, {Root, 0}); 7082 SmallPtrSet<Value *, 8> VisitedInstrs; 7083 bool Res = false; 7084 while (!Stack.empty()) { 7085 Instruction *Inst; 7086 unsigned Level; 7087 std::tie(Inst, Level) = Stack.pop_back_val(); 7088 auto *BI = dyn_cast<BinaryOperator>(Inst); 7089 auto *SI = dyn_cast<SelectInst>(Inst); 7090 if (BI || SI) { 7091 HorizontalReduction HorRdx; 7092 if (HorRdx.matchAssociativeReduction(P, Inst)) { 7093 if (HorRdx.tryToReduce(R, TTI)) { 7094 Res = true; 7095 // Set P to nullptr to avoid re-analysis of phi node in 7096 // matchAssociativeReduction function unless this is the root node. 7097 P = nullptr; 7098 continue; 7099 } 7100 } 7101 if (P && BI) { 7102 Inst = dyn_cast<Instruction>(BI->getOperand(0)); 7103 if (Inst == P) 7104 Inst = dyn_cast<Instruction>(BI->getOperand(1)); 7105 if (!Inst) { 7106 // Set P to nullptr to avoid re-analysis of phi node in 7107 // matchAssociativeReduction function unless this is the root node. 7108 P = nullptr; 7109 continue; 7110 } 7111 } 7112 } 7113 // Set P to nullptr to avoid re-analysis of phi node in 7114 // matchAssociativeReduction function unless this is the root node. 7115 P = nullptr; 7116 if (Vectorize(Inst, R)) { 7117 Res = true; 7118 continue; 7119 } 7120 7121 // Try to vectorize operands. 7122 // Continue analysis for the instruction from the same basic block only to 7123 // save compile time. 7124 if (++Level < RecursionMaxDepth) 7125 for (auto *Op : Inst->operand_values()) 7126 if (VisitedInstrs.insert(Op).second) 7127 if (auto *I = dyn_cast<Instruction>(Op)) 7128 if (!isa<PHINode>(I) && !R.isDeleted(I) && I->getParent() == BB) 7129 Stack.emplace_back(I, Level); 7130 } 7131 return Res; 7132 } 7133 7134 bool SLPVectorizerPass::vectorizeRootInstruction(PHINode *P, Value *V, 7135 BasicBlock *BB, BoUpSLP &R, 7136 TargetTransformInfo *TTI) { 7137 if (!V) 7138 return false; 7139 auto *I = dyn_cast<Instruction>(V); 7140 if (!I) 7141 return false; 7142 7143 if (!isa<BinaryOperator>(I)) 7144 P = nullptr; 7145 // Try to match and vectorize a horizontal reduction. 7146 auto &&ExtraVectorization = [this](Instruction *I, BoUpSLP &R) -> bool { 7147 return tryToVectorize(I, R); 7148 }; 7149 return tryToVectorizeHorReductionOrInstOperands(P, I, BB, R, TTI, 7150 ExtraVectorization); 7151 } 7152 7153 bool SLPVectorizerPass::vectorizeInsertValueInst(InsertValueInst *IVI, 7154 BasicBlock *BB, BoUpSLP &R) { 7155 int UserCost = 0; 7156 const DataLayout &DL = BB->getModule()->getDataLayout(); 7157 if (!R.canMapToVector(IVI->getType(), DL)) 7158 return false; 7159 7160 SmallVector<Value *, 16> BuildVectorOpds; 7161 if (!findBuildAggregate(IVI, TTI, BuildVectorOpds, UserCost)) 7162 return false; 7163 7164 LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IVI << "\n"); 7165 // Aggregate value is unlikely to be processed in vector register, we need to 7166 // extract scalars into scalar registers, so NeedExtraction is set true. 7167 return tryToVectorizeList(BuildVectorOpds, R, UserCost); 7168 } 7169 7170 bool SLPVectorizerPass::vectorizeInsertElementInst(InsertElementInst *IEI, 7171 BasicBlock *BB, BoUpSLP &R) { 7172 int UserCost; 7173 SmallVector<Value *, 16> BuildVectorOpds; 7174 if (!findBuildAggregate(IEI, TTI, BuildVectorOpds, UserCost) || 7175 (llvm::all_of(BuildVectorOpds, 7176 [](Value *V) { return isa<ExtractElementInst>(V); }) && 7177 isShuffle(BuildVectorOpds))) 7178 return false; 7179 7180 // Vectorize starting with the build vector operands ignoring the BuildVector 7181 // instructions for the purpose of scheduling and user extraction. 7182 return tryToVectorizeList(BuildVectorOpds, R, UserCost); 7183 } 7184 7185 bool SLPVectorizerPass::vectorizeCmpInst(CmpInst *CI, BasicBlock *BB, 7186 BoUpSLP &R) { 7187 if (tryToVectorizePair(CI->getOperand(0), CI->getOperand(1), R)) 7188 return true; 7189 7190 bool OpsChanged = false; 7191 for (int Idx = 0; Idx < 2; ++Idx) { 7192 OpsChanged |= 7193 vectorizeRootInstruction(nullptr, CI->getOperand(Idx), BB, R, TTI); 7194 } 7195 return OpsChanged; 7196 } 7197 7198 bool SLPVectorizerPass::vectorizeSimpleInstructions( 7199 SmallVectorImpl<Instruction *> &Instructions, BasicBlock *BB, BoUpSLP &R) { 7200 bool OpsChanged = false; 7201 for (auto *I : reverse(Instructions)) { 7202 if (R.isDeleted(I)) 7203 continue; 7204 if (auto *LastInsertValue = dyn_cast<InsertValueInst>(I)) 7205 OpsChanged |= vectorizeInsertValueInst(LastInsertValue, BB, R); 7206 else if (auto *LastInsertElem = dyn_cast<InsertElementInst>(I)) 7207 OpsChanged |= vectorizeInsertElementInst(LastInsertElem, BB, R); 7208 else if (auto *CI = dyn_cast<CmpInst>(I)) 7209 OpsChanged |= vectorizeCmpInst(CI, BB, R); 7210 } 7211 Instructions.clear(); 7212 return OpsChanged; 7213 } 7214 7215 bool SLPVectorizerPass::vectorizeChainsInBlock(BasicBlock *BB, BoUpSLP &R) { 7216 bool Changed = false; 7217 SmallVector<Value *, 4> Incoming; 7218 SmallPtrSet<Value *, 16> VisitedInstrs; 7219 7220 bool HaveVectorizedPhiNodes = true; 7221 while (HaveVectorizedPhiNodes) { 7222 HaveVectorizedPhiNodes = false; 7223 7224 // Collect the incoming values from the PHIs. 7225 Incoming.clear(); 7226 for (Instruction &I : *BB) { 7227 PHINode *P = dyn_cast<PHINode>(&I); 7228 if (!P) 7229 break; 7230 7231 if (!VisitedInstrs.count(P) && !R.isDeleted(P)) 7232 Incoming.push_back(P); 7233 } 7234 7235 // Sort by type. 7236 llvm::stable_sort(Incoming, PhiTypeSorterFunc); 7237 7238 // Try to vectorize elements base on their type. 7239 for (SmallVector<Value *, 4>::iterator IncIt = Incoming.begin(), 7240 E = Incoming.end(); 7241 IncIt != E;) { 7242 7243 // Look for the next elements with the same type. 7244 SmallVector<Value *, 4>::iterator SameTypeIt = IncIt; 7245 while (SameTypeIt != E && 7246 (*SameTypeIt)->getType() == (*IncIt)->getType()) { 7247 VisitedInstrs.insert(*SameTypeIt); 7248 ++SameTypeIt; 7249 } 7250 7251 // Try to vectorize them. 7252 unsigned NumElts = (SameTypeIt - IncIt); 7253 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize starting at PHIs (" 7254 << NumElts << ")\n"); 7255 // The order in which the phi nodes appear in the program does not matter. 7256 // So allow tryToVectorizeList to reorder them if it is beneficial. This 7257 // is done when there are exactly two elements since tryToVectorizeList 7258 // asserts that there are only two values when AllowReorder is true. 7259 bool AllowReorder = NumElts == 2; 7260 if (NumElts > 1 && tryToVectorizeList(makeArrayRef(IncIt, NumElts), R, 7261 /*UserCost=*/0, AllowReorder)) { 7262 // Success start over because instructions might have been changed. 7263 HaveVectorizedPhiNodes = true; 7264 Changed = true; 7265 break; 7266 } 7267 7268 // Start over at the next instruction of a different type (or the end). 7269 IncIt = SameTypeIt; 7270 } 7271 } 7272 7273 VisitedInstrs.clear(); 7274 7275 SmallVector<Instruction *, 8> PostProcessInstructions; 7276 SmallDenseSet<Instruction *, 4> KeyNodes; 7277 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 7278 // Skip instructions marked for the deletion. 7279 if (R.isDeleted(&*it)) 7280 continue; 7281 // We may go through BB multiple times so skip the one we have checked. 7282 if (!VisitedInstrs.insert(&*it).second) { 7283 if (it->use_empty() && KeyNodes.count(&*it) > 0 && 7284 vectorizeSimpleInstructions(PostProcessInstructions, BB, R)) { 7285 // We would like to start over since some instructions are deleted 7286 // and the iterator may become invalid value. 7287 Changed = true; 7288 it = BB->begin(); 7289 e = BB->end(); 7290 } 7291 continue; 7292 } 7293 7294 if (isa<DbgInfoIntrinsic>(it)) 7295 continue; 7296 7297 // Try to vectorize reductions that use PHINodes. 7298 if (PHINode *P = dyn_cast<PHINode>(it)) { 7299 // Check that the PHI is a reduction PHI. 7300 if (P->getNumIncomingValues() != 2) 7301 return Changed; 7302 7303 // Try to match and vectorize a horizontal reduction. 7304 if (vectorizeRootInstruction(P, getReductionValue(DT, P, BB, LI), BB, R, 7305 TTI)) { 7306 Changed = true; 7307 it = BB->begin(); 7308 e = BB->end(); 7309 continue; 7310 } 7311 continue; 7312 } 7313 7314 // Ran into an instruction without users, like terminator, or function call 7315 // with ignored return value, store. Ignore unused instructions (basing on 7316 // instruction type, except for CallInst and InvokeInst). 7317 if (it->use_empty() && (it->getType()->isVoidTy() || isa<CallInst>(it) || 7318 isa<InvokeInst>(it))) { 7319 KeyNodes.insert(&*it); 7320 bool OpsChanged = false; 7321 if (ShouldStartVectorizeHorAtStore || !isa<StoreInst>(it)) { 7322 for (auto *V : it->operand_values()) { 7323 // Try to match and vectorize a horizontal reduction. 7324 OpsChanged |= vectorizeRootInstruction(nullptr, V, BB, R, TTI); 7325 } 7326 } 7327 // Start vectorization of post-process list of instructions from the 7328 // top-tree instructions to try to vectorize as many instructions as 7329 // possible. 7330 OpsChanged |= vectorizeSimpleInstructions(PostProcessInstructions, BB, R); 7331 if (OpsChanged) { 7332 // We would like to start over since some instructions are deleted 7333 // and the iterator may become invalid value. 7334 Changed = true; 7335 it = BB->begin(); 7336 e = BB->end(); 7337 continue; 7338 } 7339 } 7340 7341 if (isa<InsertElementInst>(it) || isa<CmpInst>(it) || 7342 isa<InsertValueInst>(it)) 7343 PostProcessInstructions.push_back(&*it); 7344 } 7345 7346 return Changed; 7347 } 7348 7349 bool SLPVectorizerPass::vectorizeGEPIndices(BasicBlock *BB, BoUpSLP &R) { 7350 auto Changed = false; 7351 for (auto &Entry : GEPs) { 7352 // If the getelementptr list has fewer than two elements, there's nothing 7353 // to do. 7354 if (Entry.second.size() < 2) 7355 continue; 7356 7357 LLVM_DEBUG(dbgs() << "SLP: Analyzing a getelementptr list of length " 7358 << Entry.second.size() << ".\n"); 7359 7360 // Process the GEP list in chunks suitable for the target's supported 7361 // vector size. If a vector register can't hold 1 element, we are done. 7362 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 7363 unsigned EltSize = R.getVectorElementSize(Entry.second[0]); 7364 if (MaxVecRegSize < EltSize) 7365 continue; 7366 7367 unsigned MaxElts = MaxVecRegSize / EltSize; 7368 for (unsigned BI = 0, BE = Entry.second.size(); BI < BE; BI += MaxElts) { 7369 auto Len = std::min<unsigned>(BE - BI, MaxElts); 7370 auto GEPList = makeArrayRef(&Entry.second[BI], Len); 7371 7372 // Initialize a set a candidate getelementptrs. Note that we use a 7373 // SetVector here to preserve program order. If the index computations 7374 // are vectorizable and begin with loads, we want to minimize the chance 7375 // of having to reorder them later. 7376 SetVector<Value *> Candidates(GEPList.begin(), GEPList.end()); 7377 7378 // Some of the candidates may have already been vectorized after we 7379 // initially collected them. If so, they are marked as deleted, so remove 7380 // them from the set of candidates. 7381 Candidates.remove_if( 7382 [&R](Value *I) { return R.isDeleted(cast<Instruction>(I)); }); 7383 7384 // Remove from the set of candidates all pairs of getelementptrs with 7385 // constant differences. Such getelementptrs are likely not good 7386 // candidates for vectorization in a bottom-up phase since one can be 7387 // computed from the other. We also ensure all candidate getelementptr 7388 // indices are unique. 7389 for (int I = 0, E = GEPList.size(); I < E && Candidates.size() > 1; ++I) { 7390 auto *GEPI = GEPList[I]; 7391 if (!Candidates.count(GEPI)) 7392 continue; 7393 auto *SCEVI = SE->getSCEV(GEPList[I]); 7394 for (int J = I + 1; J < E && Candidates.size() > 1; ++J) { 7395 auto *GEPJ = GEPList[J]; 7396 auto *SCEVJ = SE->getSCEV(GEPList[J]); 7397 if (isa<SCEVConstant>(SE->getMinusSCEV(SCEVI, SCEVJ))) { 7398 Candidates.remove(GEPI); 7399 Candidates.remove(GEPJ); 7400 } else if (GEPI->idx_begin()->get() == GEPJ->idx_begin()->get()) { 7401 Candidates.remove(GEPJ); 7402 } 7403 } 7404 } 7405 7406 // We break out of the above computation as soon as we know there are 7407 // fewer than two candidates remaining. 7408 if (Candidates.size() < 2) 7409 continue; 7410 7411 // Add the single, non-constant index of each candidate to the bundle. We 7412 // ensured the indices met these constraints when we originally collected 7413 // the getelementptrs. 7414 SmallVector<Value *, 16> Bundle(Candidates.size()); 7415 auto BundleIndex = 0u; 7416 for (auto *V : Candidates) { 7417 auto *GEP = cast<GetElementPtrInst>(V); 7418 auto *GEPIdx = GEP->idx_begin()->get(); 7419 assert(GEP->getNumIndices() == 1 || !isa<Constant>(GEPIdx)); 7420 Bundle[BundleIndex++] = GEPIdx; 7421 } 7422 7423 // Try and vectorize the indices. We are currently only interested in 7424 // gather-like cases of the form: 7425 // 7426 // ... = g[a[0] - b[0]] + g[a[1] - b[1]] + ... 7427 // 7428 // where the loads of "a", the loads of "b", and the subtractions can be 7429 // performed in parallel. It's likely that detecting this pattern in a 7430 // bottom-up phase will be simpler and less costly than building a 7431 // full-blown top-down phase beginning at the consecutive loads. 7432 Changed |= tryToVectorizeList(Bundle, R); 7433 } 7434 } 7435 return Changed; 7436 } 7437 7438 bool SLPVectorizerPass::vectorizeStoreChains(BoUpSLP &R) { 7439 bool Changed = false; 7440 // Attempt to sort and vectorize each of the store-groups. 7441 for (StoreListMap::iterator it = Stores.begin(), e = Stores.end(); it != e; 7442 ++it) { 7443 if (it->second.size() < 2) 7444 continue; 7445 7446 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " 7447 << it->second.size() << ".\n"); 7448 7449 Changed |= vectorizeStores(it->second, R); 7450 } 7451 return Changed; 7452 } 7453 7454 char SLPVectorizer::ID = 0; 7455 7456 static const char lv_name[] = "SLP Vectorizer"; 7457 7458 INITIALIZE_PASS_BEGIN(SLPVectorizer, SV_NAME, lv_name, false, false) 7459 INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass) 7460 INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass) 7461 INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker) 7462 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass) 7463 INITIALIZE_PASS_DEPENDENCY(LoopSimplify) 7464 INITIALIZE_PASS_DEPENDENCY(DemandedBitsWrapperPass) 7465 INITIALIZE_PASS_DEPENDENCY(OptimizationRemarkEmitterWrapperPass) 7466 INITIALIZE_PASS_END(SLPVectorizer, SV_NAME, lv_name, false, false) 7467 7468 Pass *llvm::createSLPVectorizerPass() { return new SLPVectorizer(); } 7469