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 ArrayType or StructType is isomorphic to some VectorType. 633 /// Accepts homogeneous aggregate of vectors like 634 /// { <2 x float>, <2 x float> } 635 /// 636 /// \returns number of elements in vector if isomorphism exists, 0 otherwise. 637 unsigned canMapToVector(Type *T, const DataLayout &DL) const; 638 639 /// \returns True if the VectorizableTree is both tiny and not fully 640 /// vectorizable. We do not vectorize such trees. 641 bool isTreeTinyAndNotFullyVectorizable() const; 642 643 /// Assume that a legal-sized 'or'-reduction of shifted/zexted loaded values 644 /// can be load combined in the backend. Load combining may not be allowed in 645 /// the IR optimizer, so we do not want to alter the pattern. For example, 646 /// partially transforming a scalar bswap() pattern into vector code is 647 /// effectively impossible for the backend to undo. 648 /// TODO: If load combining is allowed in the IR optimizer, this analysis 649 /// may not be necessary. 650 bool isLoadCombineReductionCandidate(unsigned ReductionOpcode) const; 651 652 OptimizationRemarkEmitter *getORE() { return ORE; } 653 654 /// This structure holds any data we need about the edges being traversed 655 /// during buildTree_rec(). We keep track of: 656 /// (i) the user TreeEntry index, and 657 /// (ii) the index of the edge. 658 struct EdgeInfo { 659 EdgeInfo() = default; 660 EdgeInfo(TreeEntry *UserTE, unsigned EdgeIdx) 661 : UserTE(UserTE), EdgeIdx(EdgeIdx) {} 662 /// The user TreeEntry. 663 TreeEntry *UserTE = nullptr; 664 /// The operand index of the use. 665 unsigned EdgeIdx = UINT_MAX; 666 #ifndef NDEBUG 667 friend inline raw_ostream &operator<<(raw_ostream &OS, 668 const BoUpSLP::EdgeInfo &EI) { 669 EI.dump(OS); 670 return OS; 671 } 672 /// Debug print. 673 void dump(raw_ostream &OS) const { 674 OS << "{User:" << (UserTE ? std::to_string(UserTE->Idx) : "null") 675 << " EdgeIdx:" << EdgeIdx << "}"; 676 } 677 LLVM_DUMP_METHOD void dump() const { dump(dbgs()); } 678 #endif 679 }; 680 681 /// A helper data structure to hold the operands of a vector of instructions. 682 /// This supports a fixed vector length for all operand vectors. 683 class VLOperands { 684 /// For each operand we need (i) the value, and (ii) the opcode that it 685 /// would be attached to if the expression was in a left-linearized form. 686 /// This is required to avoid illegal operand reordering. 687 /// For example: 688 /// \verbatim 689 /// 0 Op1 690 /// |/ 691 /// Op1 Op2 Linearized + Op2 692 /// \ / ----------> |/ 693 /// - - 694 /// 695 /// Op1 - Op2 (0 + Op1) - Op2 696 /// \endverbatim 697 /// 698 /// Value Op1 is attached to a '+' operation, and Op2 to a '-'. 699 /// 700 /// Another way to think of this is to track all the operations across the 701 /// path from the operand all the way to the root of the tree and to 702 /// calculate the operation that corresponds to this path. For example, the 703 /// path from Op2 to the root crosses the RHS of the '-', therefore the 704 /// corresponding operation is a '-' (which matches the one in the 705 /// linearized tree, as shown above). 706 /// 707 /// For lack of a better term, we refer to this operation as Accumulated 708 /// Path Operation (APO). 709 struct OperandData { 710 OperandData() = default; 711 OperandData(Value *V, bool APO, bool IsUsed) 712 : V(V), APO(APO), IsUsed(IsUsed) {} 713 /// The operand value. 714 Value *V = nullptr; 715 /// TreeEntries only allow a single opcode, or an alternate sequence of 716 /// them (e.g, +, -). Therefore, we can safely use a boolean value for the 717 /// APO. It is set to 'true' if 'V' is attached to an inverse operation 718 /// in the left-linearized form (e.g., Sub/Div), and 'false' otherwise 719 /// (e.g., Add/Mul) 720 bool APO = false; 721 /// Helper data for the reordering function. 722 bool IsUsed = false; 723 }; 724 725 /// During operand reordering, we are trying to select the operand at lane 726 /// that matches best with the operand at the neighboring lane. Our 727 /// selection is based on the type of value we are looking for. For example, 728 /// if the neighboring lane has a load, we need to look for a load that is 729 /// accessing a consecutive address. These strategies are summarized in the 730 /// 'ReorderingMode' enumerator. 731 enum class ReorderingMode { 732 Load, ///< Matching loads to consecutive memory addresses 733 Opcode, ///< Matching instructions based on opcode (same or alternate) 734 Constant, ///< Matching constants 735 Splat, ///< Matching the same instruction multiple times (broadcast) 736 Failed, ///< We failed to create a vectorizable group 737 }; 738 739 using OperandDataVec = SmallVector<OperandData, 2>; 740 741 /// A vector of operand vectors. 742 SmallVector<OperandDataVec, 4> OpsVec; 743 744 const DataLayout &DL; 745 ScalarEvolution &SE; 746 const BoUpSLP &R; 747 748 /// \returns the operand data at \p OpIdx and \p Lane. 749 OperandData &getData(unsigned OpIdx, unsigned Lane) { 750 return OpsVec[OpIdx][Lane]; 751 } 752 753 /// \returns the operand data at \p OpIdx and \p Lane. Const version. 754 const OperandData &getData(unsigned OpIdx, unsigned Lane) const { 755 return OpsVec[OpIdx][Lane]; 756 } 757 758 /// Clears the used flag for all entries. 759 void clearUsed() { 760 for (unsigned OpIdx = 0, NumOperands = getNumOperands(); 761 OpIdx != NumOperands; ++OpIdx) 762 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 763 ++Lane) 764 OpsVec[OpIdx][Lane].IsUsed = false; 765 } 766 767 /// Swap the operand at \p OpIdx1 with that one at \p OpIdx2. 768 void swap(unsigned OpIdx1, unsigned OpIdx2, unsigned Lane) { 769 std::swap(OpsVec[OpIdx1][Lane], OpsVec[OpIdx2][Lane]); 770 } 771 772 // The hard-coded scores listed here are not very important. When computing 773 // the scores of matching one sub-tree with another, we are basically 774 // counting the number of values that are matching. So even if all scores 775 // are set to 1, we would still get a decent matching result. 776 // However, sometimes we have to break ties. For example we may have to 777 // choose between matching loads vs matching opcodes. This is what these 778 // scores are helping us with: they provide the order of preference. 779 780 /// Loads from consecutive memory addresses, e.g. load(A[i]), load(A[i+1]). 781 static const int ScoreConsecutiveLoads = 3; 782 /// ExtractElementInst from same vector and consecutive indexes. 783 static const int ScoreConsecutiveExtracts = 3; 784 /// Constants. 785 static const int ScoreConstants = 2; 786 /// Instructions with the same opcode. 787 static const int ScoreSameOpcode = 2; 788 /// Instructions with alt opcodes (e.g, add + sub). 789 static const int ScoreAltOpcodes = 1; 790 /// Identical instructions (a.k.a. splat or broadcast). 791 static const int ScoreSplat = 1; 792 /// Matching with an undef is preferable to failing. 793 static const int ScoreUndef = 1; 794 /// Score for failing to find a decent match. 795 static const int ScoreFail = 0; 796 /// User exteranl to the vectorized code. 797 static const int ExternalUseCost = 1; 798 /// The user is internal but in a different lane. 799 static const int UserInDiffLaneCost = ExternalUseCost; 800 801 /// \returns the score of placing \p V1 and \p V2 in consecutive lanes. 802 static int getShallowScore(Value *V1, Value *V2, const DataLayout &DL, 803 ScalarEvolution &SE) { 804 auto *LI1 = dyn_cast<LoadInst>(V1); 805 auto *LI2 = dyn_cast<LoadInst>(V2); 806 if (LI1 && LI2) 807 return isConsecutiveAccess(LI1, LI2, DL, SE) 808 ? VLOperands::ScoreConsecutiveLoads 809 : VLOperands::ScoreFail; 810 811 auto *C1 = dyn_cast<Constant>(V1); 812 auto *C2 = dyn_cast<Constant>(V2); 813 if (C1 && C2) 814 return VLOperands::ScoreConstants; 815 816 // Extracts from consecutive indexes of the same vector better score as 817 // the extracts could be optimized away. 818 auto *Ex1 = dyn_cast<ExtractElementInst>(V1); 819 auto *Ex2 = dyn_cast<ExtractElementInst>(V2); 820 if (Ex1 && Ex2 && Ex1->getVectorOperand() == Ex2->getVectorOperand() && 821 cast<ConstantInt>(Ex1->getIndexOperand())->getZExtValue() + 1 == 822 cast<ConstantInt>(Ex2->getIndexOperand())->getZExtValue()) { 823 return VLOperands::ScoreConsecutiveExtracts; 824 } 825 826 auto *I1 = dyn_cast<Instruction>(V1); 827 auto *I2 = dyn_cast<Instruction>(V2); 828 if (I1 && I2) { 829 if (I1 == I2) 830 return VLOperands::ScoreSplat; 831 InstructionsState S = getSameOpcode({I1, I2}); 832 // Note: Only consider instructions with <= 2 operands to avoid 833 // complexity explosion. 834 if (S.getOpcode() && S.MainOp->getNumOperands() <= 2) 835 return S.isAltShuffle() ? VLOperands::ScoreAltOpcodes 836 : VLOperands::ScoreSameOpcode; 837 } 838 839 if (isa<UndefValue>(V2)) 840 return VLOperands::ScoreUndef; 841 842 return VLOperands::ScoreFail; 843 } 844 845 /// Holds the values and their lane that are taking part in the look-ahead 846 /// score calculation. This is used in the external uses cost calculation. 847 SmallDenseMap<Value *, int> InLookAheadValues; 848 849 /// \Returns the additinal cost due to uses of \p LHS and \p RHS that are 850 /// either external to the vectorized code, or require shuffling. 851 int getExternalUsesCost(const std::pair<Value *, int> &LHS, 852 const std::pair<Value *, int> &RHS) { 853 int Cost = 0; 854 SmallVector<std::pair<Value *, int>, 2> Values = {LHS, RHS}; 855 for (int Idx = 0, IdxE = Values.size(); Idx != IdxE; ++Idx) { 856 Value *V = Values[Idx].first; 857 // Calculate the absolute lane, using the minimum relative lane of LHS 858 // and RHS as base and Idx as the offset. 859 int Ln = std::min(LHS.second, RHS.second) + Idx; 860 assert(Ln >= 0 && "Bad lane calculation"); 861 unsigned UsersBudget = LookAheadUsersBudget; 862 for (User *U : V->users()) { 863 if (const TreeEntry *UserTE = R.getTreeEntry(U)) { 864 // The user is in the VectorizableTree. Check if we need to insert. 865 auto It = llvm::find(UserTE->Scalars, U); 866 assert(It != UserTE->Scalars.end() && "U is in UserTE"); 867 int UserLn = std::distance(UserTE->Scalars.begin(), It); 868 assert(UserLn >= 0 && "Bad lane"); 869 if (UserLn != Ln) 870 Cost += UserInDiffLaneCost; 871 } else { 872 // Check if the user is in the look-ahead code. 873 auto It2 = InLookAheadValues.find(U); 874 if (It2 != InLookAheadValues.end()) { 875 // The user is in the look-ahead code. Check the lane. 876 if (It2->second != Ln) 877 Cost += UserInDiffLaneCost; 878 } else { 879 // The user is neither in SLP tree nor in the look-ahead code. 880 Cost += ExternalUseCost; 881 } 882 } 883 // Limit the number of visited uses to cap compilation time. 884 if (--UsersBudget == 0) 885 break; 886 } 887 } 888 return Cost; 889 } 890 891 /// Go through the operands of \p LHS and \p RHS recursively until \p 892 /// MaxLevel, and return the cummulative score. For example: 893 /// \verbatim 894 /// A[0] B[0] A[1] B[1] C[0] D[0] B[1] A[1] 895 /// \ / \ / \ / \ / 896 /// + + + + 897 /// G1 G2 G3 G4 898 /// \endverbatim 899 /// The getScoreAtLevelRec(G1, G2) function will try to match the nodes at 900 /// each level recursively, accumulating the score. It starts from matching 901 /// the additions at level 0, then moves on to the loads (level 1). The 902 /// score of G1 and G2 is higher than G1 and G3, because {A[0],A[1]} and 903 /// {B[0],B[1]} match with VLOperands::ScoreConsecutiveLoads, while 904 /// {A[0],C[0]} has a score of VLOperands::ScoreFail. 905 /// Please note that the order of the operands does not matter, as we 906 /// evaluate the score of all profitable combinations of operands. In 907 /// other words the score of G1 and G4 is the same as G1 and G2. This 908 /// heuristic is based on ideas described in: 909 /// Look-ahead SLP: Auto-vectorization in the presence of commutative 910 /// operations, CGO 2018 by Vasileios Porpodas, Rodrigo C. O. Rocha, 911 /// Luís F. W. Góes 912 int getScoreAtLevelRec(const std::pair<Value *, int> &LHS, 913 const std::pair<Value *, int> &RHS, int CurrLevel, 914 int MaxLevel) { 915 916 Value *V1 = LHS.first; 917 Value *V2 = RHS.first; 918 // Get the shallow score of V1 and V2. 919 int ShallowScoreAtThisLevel = 920 std::max((int)ScoreFail, getShallowScore(V1, V2, DL, SE) - 921 getExternalUsesCost(LHS, RHS)); 922 int Lane1 = LHS.second; 923 int Lane2 = RHS.second; 924 925 // If reached MaxLevel, 926 // or if V1 and V2 are not instructions, 927 // or if they are SPLAT, 928 // or if they are not consecutive, early return the current cost. 929 auto *I1 = dyn_cast<Instruction>(V1); 930 auto *I2 = dyn_cast<Instruction>(V2); 931 if (CurrLevel == MaxLevel || !(I1 && I2) || I1 == I2 || 932 ShallowScoreAtThisLevel == VLOperands::ScoreFail || 933 (isa<LoadInst>(I1) && isa<LoadInst>(I2) && ShallowScoreAtThisLevel)) 934 return ShallowScoreAtThisLevel; 935 assert(I1 && I2 && "Should have early exited."); 936 937 // Keep track of in-tree values for determining the external-use cost. 938 InLookAheadValues[V1] = Lane1; 939 InLookAheadValues[V2] = Lane2; 940 941 // Contains the I2 operand indexes that got matched with I1 operands. 942 SmallSet<unsigned, 4> Op2Used; 943 944 // Recursion towards the operands of I1 and I2. We are trying all possbile 945 // operand pairs, and keeping track of the best score. 946 for (unsigned OpIdx1 = 0, NumOperands1 = I1->getNumOperands(); 947 OpIdx1 != NumOperands1; ++OpIdx1) { 948 // Try to pair op1I with the best operand of I2. 949 int MaxTmpScore = 0; 950 unsigned MaxOpIdx2 = 0; 951 bool FoundBest = false; 952 // If I2 is commutative try all combinations. 953 unsigned FromIdx = isCommutative(I2) ? 0 : OpIdx1; 954 unsigned ToIdx = isCommutative(I2) 955 ? I2->getNumOperands() 956 : std::min(I2->getNumOperands(), OpIdx1 + 1); 957 assert(FromIdx <= ToIdx && "Bad index"); 958 for (unsigned OpIdx2 = FromIdx; OpIdx2 != ToIdx; ++OpIdx2) { 959 // Skip operands already paired with OpIdx1. 960 if (Op2Used.count(OpIdx2)) 961 continue; 962 // Recursively calculate the cost at each level 963 int TmpScore = getScoreAtLevelRec({I1->getOperand(OpIdx1), Lane1}, 964 {I2->getOperand(OpIdx2), Lane2}, 965 CurrLevel + 1, MaxLevel); 966 // Look for the best score. 967 if (TmpScore > VLOperands::ScoreFail && TmpScore > MaxTmpScore) { 968 MaxTmpScore = TmpScore; 969 MaxOpIdx2 = OpIdx2; 970 FoundBest = true; 971 } 972 } 973 if (FoundBest) { 974 // Pair {OpIdx1, MaxOpIdx2} was found to be best. Never revisit it. 975 Op2Used.insert(MaxOpIdx2); 976 ShallowScoreAtThisLevel += MaxTmpScore; 977 } 978 } 979 return ShallowScoreAtThisLevel; 980 } 981 982 /// \Returns the look-ahead score, which tells us how much the sub-trees 983 /// rooted at \p LHS and \p RHS match, the more they match the higher the 984 /// score. This helps break ties in an informed way when we cannot decide on 985 /// the order of the operands by just considering the immediate 986 /// predecessors. 987 int getLookAheadScore(const std::pair<Value *, int> &LHS, 988 const std::pair<Value *, int> &RHS) { 989 InLookAheadValues.clear(); 990 return getScoreAtLevelRec(LHS, RHS, 1, LookAheadMaxDepth); 991 } 992 993 // Search all operands in Ops[*][Lane] for the one that matches best 994 // Ops[OpIdx][LastLane] and return its opreand index. 995 // If no good match can be found, return None. 996 Optional<unsigned> 997 getBestOperand(unsigned OpIdx, int Lane, int LastLane, 998 ArrayRef<ReorderingMode> ReorderingModes) { 999 unsigned NumOperands = getNumOperands(); 1000 1001 // The operand of the previous lane at OpIdx. 1002 Value *OpLastLane = getData(OpIdx, LastLane).V; 1003 1004 // Our strategy mode for OpIdx. 1005 ReorderingMode RMode = ReorderingModes[OpIdx]; 1006 1007 // The linearized opcode of the operand at OpIdx, Lane. 1008 bool OpIdxAPO = getData(OpIdx, Lane).APO; 1009 1010 // The best operand index and its score. 1011 // Sometimes we have more than one option (e.g., Opcode and Undefs), so we 1012 // are using the score to differentiate between the two. 1013 struct BestOpData { 1014 Optional<unsigned> Idx = None; 1015 unsigned Score = 0; 1016 } BestOp; 1017 1018 // Iterate through all unused operands and look for the best. 1019 for (unsigned Idx = 0; Idx != NumOperands; ++Idx) { 1020 // Get the operand at Idx and Lane. 1021 OperandData &OpData = getData(Idx, Lane); 1022 Value *Op = OpData.V; 1023 bool OpAPO = OpData.APO; 1024 1025 // Skip already selected operands. 1026 if (OpData.IsUsed) 1027 continue; 1028 1029 // Skip if we are trying to move the operand to a position with a 1030 // different opcode in the linearized tree form. This would break the 1031 // semantics. 1032 if (OpAPO != OpIdxAPO) 1033 continue; 1034 1035 // Look for an operand that matches the current mode. 1036 switch (RMode) { 1037 case ReorderingMode::Load: 1038 case ReorderingMode::Constant: 1039 case ReorderingMode::Opcode: { 1040 bool LeftToRight = Lane > LastLane; 1041 Value *OpLeft = (LeftToRight) ? OpLastLane : Op; 1042 Value *OpRight = (LeftToRight) ? Op : OpLastLane; 1043 unsigned Score = 1044 getLookAheadScore({OpLeft, LastLane}, {OpRight, Lane}); 1045 if (Score > BestOp.Score) { 1046 BestOp.Idx = Idx; 1047 BestOp.Score = Score; 1048 } 1049 break; 1050 } 1051 case ReorderingMode::Splat: 1052 if (Op == OpLastLane) 1053 BestOp.Idx = Idx; 1054 break; 1055 case ReorderingMode::Failed: 1056 return None; 1057 } 1058 } 1059 1060 if (BestOp.Idx) { 1061 getData(BestOp.Idx.getValue(), Lane).IsUsed = true; 1062 return BestOp.Idx; 1063 } 1064 // If we could not find a good match return None. 1065 return None; 1066 } 1067 1068 /// Helper for reorderOperandVecs. \Returns the lane that we should start 1069 /// reordering from. This is the one which has the least number of operands 1070 /// that can freely move about. 1071 unsigned getBestLaneToStartReordering() const { 1072 unsigned BestLane = 0; 1073 unsigned Min = UINT_MAX; 1074 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; 1075 ++Lane) { 1076 unsigned NumFreeOps = getMaxNumOperandsThatCanBeReordered(Lane); 1077 if (NumFreeOps < Min) { 1078 Min = NumFreeOps; 1079 BestLane = Lane; 1080 } 1081 } 1082 return BestLane; 1083 } 1084 1085 /// \Returns the maximum number of operands that are allowed to be reordered 1086 /// for \p Lane. This is used as a heuristic for selecting the first lane to 1087 /// start operand reordering. 1088 unsigned getMaxNumOperandsThatCanBeReordered(unsigned Lane) const { 1089 unsigned CntTrue = 0; 1090 unsigned NumOperands = getNumOperands(); 1091 // Operands with the same APO can be reordered. We therefore need to count 1092 // how many of them we have for each APO, like this: Cnt[APO] = x. 1093 // Since we only have two APOs, namely true and false, we can avoid using 1094 // a map. Instead we can simply count the number of operands that 1095 // correspond to one of them (in this case the 'true' APO), and calculate 1096 // the other by subtracting it from the total number of operands. 1097 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) 1098 if (getData(OpIdx, Lane).APO) 1099 ++CntTrue; 1100 unsigned CntFalse = NumOperands - CntTrue; 1101 return std::max(CntTrue, CntFalse); 1102 } 1103 1104 /// Go through the instructions in VL and append their operands. 1105 void appendOperandsOfVL(ArrayRef<Value *> VL) { 1106 assert(!VL.empty() && "Bad VL"); 1107 assert((empty() || VL.size() == getNumLanes()) && 1108 "Expected same number of lanes"); 1109 assert(isa<Instruction>(VL[0]) && "Expected instruction"); 1110 unsigned NumOperands = cast<Instruction>(VL[0])->getNumOperands(); 1111 OpsVec.resize(NumOperands); 1112 unsigned NumLanes = VL.size(); 1113 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1114 OpsVec[OpIdx].resize(NumLanes); 1115 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { 1116 assert(isa<Instruction>(VL[Lane]) && "Expected instruction"); 1117 // Our tree has just 3 nodes: the root and two operands. 1118 // It is therefore trivial to get the APO. We only need to check the 1119 // opcode of VL[Lane] and whether the operand at OpIdx is the LHS or 1120 // RHS operand. The LHS operand of both add and sub is never attached 1121 // to an inversese operation in the linearized form, therefore its APO 1122 // is false. The RHS is true only if VL[Lane] is an inverse operation. 1123 1124 // Since operand reordering is performed on groups of commutative 1125 // operations or alternating sequences (e.g., +, -), we can safely 1126 // tell the inverse operations by checking commutativity. 1127 bool IsInverseOperation = !isCommutative(cast<Instruction>(VL[Lane])); 1128 bool APO = (OpIdx == 0) ? false : IsInverseOperation; 1129 OpsVec[OpIdx][Lane] = {cast<Instruction>(VL[Lane])->getOperand(OpIdx), 1130 APO, false}; 1131 } 1132 } 1133 } 1134 1135 /// \returns the number of operands. 1136 unsigned getNumOperands() const { return OpsVec.size(); } 1137 1138 /// \returns the number of lanes. 1139 unsigned getNumLanes() const { return OpsVec[0].size(); } 1140 1141 /// \returns the operand value at \p OpIdx and \p Lane. 1142 Value *getValue(unsigned OpIdx, unsigned Lane) const { 1143 return getData(OpIdx, Lane).V; 1144 } 1145 1146 /// \returns true if the data structure is empty. 1147 bool empty() const { return OpsVec.empty(); } 1148 1149 /// Clears the data. 1150 void clear() { OpsVec.clear(); } 1151 1152 /// \Returns true if there are enough operands identical to \p Op to fill 1153 /// the whole vector. 1154 /// Note: This modifies the 'IsUsed' flag, so a cleanUsed() must follow. 1155 bool shouldBroadcast(Value *Op, unsigned OpIdx, unsigned Lane) { 1156 bool OpAPO = getData(OpIdx, Lane).APO; 1157 for (unsigned Ln = 0, Lns = getNumLanes(); Ln != Lns; ++Ln) { 1158 if (Ln == Lane) 1159 continue; 1160 // This is set to true if we found a candidate for broadcast at Lane. 1161 bool FoundCandidate = false; 1162 for (unsigned OpI = 0, OpE = getNumOperands(); OpI != OpE; ++OpI) { 1163 OperandData &Data = getData(OpI, Ln); 1164 if (Data.APO != OpAPO || Data.IsUsed) 1165 continue; 1166 if (Data.V == Op) { 1167 FoundCandidate = true; 1168 Data.IsUsed = true; 1169 break; 1170 } 1171 } 1172 if (!FoundCandidate) 1173 return false; 1174 } 1175 return true; 1176 } 1177 1178 public: 1179 /// Initialize with all the operands of the instruction vector \p RootVL. 1180 VLOperands(ArrayRef<Value *> RootVL, const DataLayout &DL, 1181 ScalarEvolution &SE, const BoUpSLP &R) 1182 : DL(DL), SE(SE), R(R) { 1183 // Append all the operands of RootVL. 1184 appendOperandsOfVL(RootVL); 1185 } 1186 1187 /// \Returns a value vector with the operands across all lanes for the 1188 /// opearnd at \p OpIdx. 1189 ValueList getVL(unsigned OpIdx) const { 1190 ValueList OpVL(OpsVec[OpIdx].size()); 1191 assert(OpsVec[OpIdx].size() == getNumLanes() && 1192 "Expected same num of lanes across all operands"); 1193 for (unsigned Lane = 0, Lanes = getNumLanes(); Lane != Lanes; ++Lane) 1194 OpVL[Lane] = OpsVec[OpIdx][Lane].V; 1195 return OpVL; 1196 } 1197 1198 // Performs operand reordering for 2 or more operands. 1199 // The original operands are in OrigOps[OpIdx][Lane]. 1200 // The reordered operands are returned in 'SortedOps[OpIdx][Lane]'. 1201 void reorder() { 1202 unsigned NumOperands = getNumOperands(); 1203 unsigned NumLanes = getNumLanes(); 1204 // Each operand has its own mode. We are using this mode to help us select 1205 // the instructions for each lane, so that they match best with the ones 1206 // we have selected so far. 1207 SmallVector<ReorderingMode, 2> ReorderingModes(NumOperands); 1208 1209 // This is a greedy single-pass algorithm. We are going over each lane 1210 // once and deciding on the best order right away with no back-tracking. 1211 // However, in order to increase its effectiveness, we start with the lane 1212 // that has operands that can move the least. For example, given the 1213 // following lanes: 1214 // Lane 0 : A[0] = B[0] + C[0] // Visited 3rd 1215 // Lane 1 : A[1] = C[1] - B[1] // Visited 1st 1216 // Lane 2 : A[2] = B[2] + C[2] // Visited 2nd 1217 // Lane 3 : A[3] = C[3] - B[3] // Visited 4th 1218 // we will start at Lane 1, since the operands of the subtraction cannot 1219 // be reordered. Then we will visit the rest of the lanes in a circular 1220 // fashion. That is, Lanes 2, then Lane 0, and finally Lane 3. 1221 1222 // Find the first lane that we will start our search from. 1223 unsigned FirstLane = getBestLaneToStartReordering(); 1224 1225 // Initialize the modes. 1226 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1227 Value *OpLane0 = getValue(OpIdx, FirstLane); 1228 // Keep track if we have instructions with all the same opcode on one 1229 // side. 1230 if (isa<LoadInst>(OpLane0)) 1231 ReorderingModes[OpIdx] = ReorderingMode::Load; 1232 else if (isa<Instruction>(OpLane0)) { 1233 // Check if OpLane0 should be broadcast. 1234 if (shouldBroadcast(OpLane0, OpIdx, FirstLane)) 1235 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1236 else 1237 ReorderingModes[OpIdx] = ReorderingMode::Opcode; 1238 } 1239 else if (isa<Constant>(OpLane0)) 1240 ReorderingModes[OpIdx] = ReorderingMode::Constant; 1241 else if (isa<Argument>(OpLane0)) 1242 // Our best hope is a Splat. It may save some cost in some cases. 1243 ReorderingModes[OpIdx] = ReorderingMode::Splat; 1244 else 1245 // NOTE: This should be unreachable. 1246 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1247 } 1248 1249 // If the initial strategy fails for any of the operand indexes, then we 1250 // perform reordering again in a second pass. This helps avoid assigning 1251 // high priority to the failed strategy, and should improve reordering for 1252 // the non-failed operand indexes. 1253 for (int Pass = 0; Pass != 2; ++Pass) { 1254 // Skip the second pass if the first pass did not fail. 1255 bool StrategyFailed = false; 1256 // Mark all operand data as free to use. 1257 clearUsed(); 1258 // We keep the original operand order for the FirstLane, so reorder the 1259 // rest of the lanes. We are visiting the nodes in a circular fashion, 1260 // using FirstLane as the center point and increasing the radius 1261 // distance. 1262 for (unsigned Distance = 1; Distance != NumLanes; ++Distance) { 1263 // Visit the lane on the right and then the lane on the left. 1264 for (int Direction : {+1, -1}) { 1265 int Lane = FirstLane + Direction * Distance; 1266 if (Lane < 0 || Lane >= (int)NumLanes) 1267 continue; 1268 int LastLane = Lane - Direction; 1269 assert(LastLane >= 0 && LastLane < (int)NumLanes && 1270 "Out of bounds"); 1271 // Look for a good match for each operand. 1272 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { 1273 // Search for the operand that matches SortedOps[OpIdx][Lane-1]. 1274 Optional<unsigned> BestIdx = 1275 getBestOperand(OpIdx, Lane, LastLane, ReorderingModes); 1276 // By not selecting a value, we allow the operands that follow to 1277 // select a better matching value. We will get a non-null value in 1278 // the next run of getBestOperand(). 1279 if (BestIdx) { 1280 // Swap the current operand with the one returned by 1281 // getBestOperand(). 1282 swap(OpIdx, BestIdx.getValue(), Lane); 1283 } else { 1284 // We failed to find a best operand, set mode to 'Failed'. 1285 ReorderingModes[OpIdx] = ReorderingMode::Failed; 1286 // Enable the second pass. 1287 StrategyFailed = true; 1288 } 1289 } 1290 } 1291 } 1292 // Skip second pass if the strategy did not fail. 1293 if (!StrategyFailed) 1294 break; 1295 } 1296 } 1297 1298 #if !defined(NDEBUG) || defined(LLVM_ENABLE_DUMP) 1299 LLVM_DUMP_METHOD static StringRef getModeStr(ReorderingMode RMode) { 1300 switch (RMode) { 1301 case ReorderingMode::Load: 1302 return "Load"; 1303 case ReorderingMode::Opcode: 1304 return "Opcode"; 1305 case ReorderingMode::Constant: 1306 return "Constant"; 1307 case ReorderingMode::Splat: 1308 return "Splat"; 1309 case ReorderingMode::Failed: 1310 return "Failed"; 1311 } 1312 llvm_unreachable("Unimplemented Reordering Type"); 1313 } 1314 1315 LLVM_DUMP_METHOD static raw_ostream &printMode(ReorderingMode RMode, 1316 raw_ostream &OS) { 1317 return OS << getModeStr(RMode); 1318 } 1319 1320 /// Debug print. 1321 LLVM_DUMP_METHOD static void dumpMode(ReorderingMode RMode) { 1322 printMode(RMode, dbgs()); 1323 } 1324 1325 friend raw_ostream &operator<<(raw_ostream &OS, ReorderingMode RMode) { 1326 return printMode(RMode, OS); 1327 } 1328 1329 LLVM_DUMP_METHOD raw_ostream &print(raw_ostream &OS) const { 1330 const unsigned Indent = 2; 1331 unsigned Cnt = 0; 1332 for (const OperandDataVec &OpDataVec : OpsVec) { 1333 OS << "Operand " << Cnt++ << "\n"; 1334 for (const OperandData &OpData : OpDataVec) { 1335 OS.indent(Indent) << "{"; 1336 if (Value *V = OpData.V) 1337 OS << *V; 1338 else 1339 OS << "null"; 1340 OS << ", APO:" << OpData.APO << "}\n"; 1341 } 1342 OS << "\n"; 1343 } 1344 return OS; 1345 } 1346 1347 /// Debug print. 1348 LLVM_DUMP_METHOD void dump() const { print(dbgs()); } 1349 #endif 1350 }; 1351 1352 /// Checks if the instruction is marked for deletion. 1353 bool isDeleted(Instruction *I) const { return DeletedInstructions.count(I); } 1354 1355 /// Marks values operands for later deletion by replacing them with Undefs. 1356 void eraseInstructions(ArrayRef<Value *> AV); 1357 1358 ~BoUpSLP(); 1359 1360 private: 1361 /// Checks if all users of \p I are the part of the vectorization tree. 1362 bool areAllUsersVectorized(Instruction *I) const; 1363 1364 /// \returns the cost of the vectorizable entry. 1365 int getEntryCost(TreeEntry *E); 1366 1367 /// This is the recursive part of buildTree. 1368 void buildTree_rec(ArrayRef<Value *> Roots, unsigned Depth, 1369 const EdgeInfo &EI); 1370 1371 /// \returns true if the ExtractElement/ExtractValue instructions in \p VL can 1372 /// be vectorized to use the original vector (or aggregate "bitcast" to a 1373 /// vector) and sets \p CurrentOrder to the identity permutation; otherwise 1374 /// returns false, setting \p CurrentOrder to either an empty vector or a 1375 /// non-identity permutation that allows to reuse extract instructions. 1376 bool canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 1377 SmallVectorImpl<unsigned> &CurrentOrder) const; 1378 1379 /// Vectorize a single entry in the tree. 1380 Value *vectorizeTree(TreeEntry *E); 1381 1382 /// Vectorize a single entry in the tree, starting in \p VL. 1383 Value *vectorizeTree(ArrayRef<Value *> VL); 1384 1385 /// \returns the scalarization cost for this type. Scalarization in this 1386 /// context means the creation of vectors from a group of scalars. 1387 int getGatherCost(Type *Ty, const DenseSet<unsigned> &ShuffledIndices) const; 1388 1389 /// \returns the scalarization cost for this list of values. Assuming that 1390 /// this subtree gets vectorized, we may need to extract the values from the 1391 /// roots. This method calculates the cost of extracting the values. 1392 int getGatherCost(ArrayRef<Value *> VL) const; 1393 1394 /// Set the Builder insert point to one after the last instruction in 1395 /// the bundle 1396 void setInsertPointAfterBundle(TreeEntry *E); 1397 1398 /// \returns a vector from a collection of scalars in \p VL. 1399 Value *Gather(ArrayRef<Value *> VL, VectorType *Ty); 1400 1401 /// \returns whether the VectorizableTree is fully vectorizable and will 1402 /// be beneficial even the tree height is tiny. 1403 bool isFullyVectorizableTinyTree() const; 1404 1405 /// Reorder commutative or alt operands to get better probability of 1406 /// generating vectorized code. 1407 static void reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 1408 SmallVectorImpl<Value *> &Left, 1409 SmallVectorImpl<Value *> &Right, 1410 const DataLayout &DL, 1411 ScalarEvolution &SE, 1412 const BoUpSLP &R); 1413 struct TreeEntry { 1414 using VecTreeTy = SmallVector<std::unique_ptr<TreeEntry>, 8>; 1415 TreeEntry(VecTreeTy &Container) : Container(Container) {} 1416 1417 /// \returns true if the scalars in VL are equal to this entry. 1418 bool isSame(ArrayRef<Value *> VL) const { 1419 if (VL.size() == Scalars.size()) 1420 return std::equal(VL.begin(), VL.end(), Scalars.begin()); 1421 return VL.size() == ReuseShuffleIndices.size() && 1422 std::equal( 1423 VL.begin(), VL.end(), ReuseShuffleIndices.begin(), 1424 [this](Value *V, unsigned Idx) { return V == Scalars[Idx]; }); 1425 } 1426 1427 /// A vector of scalars. 1428 ValueList Scalars; 1429 1430 /// The Scalars are vectorized into this value. It is initialized to Null. 1431 Value *VectorizedValue = nullptr; 1432 1433 /// Do we need to gather this sequence ? 1434 bool NeedToGather = false; 1435 1436 /// Does this sequence require some shuffling? 1437 SmallVector<unsigned, 4> ReuseShuffleIndices; 1438 1439 /// Does this entry require reordering? 1440 ArrayRef<unsigned> ReorderIndices; 1441 1442 /// Points back to the VectorizableTree. 1443 /// 1444 /// Only used for Graphviz right now. Unfortunately GraphTrait::NodeRef has 1445 /// to be a pointer and needs to be able to initialize the child iterator. 1446 /// Thus we need a reference back to the container to translate the indices 1447 /// to entries. 1448 VecTreeTy &Container; 1449 1450 /// The TreeEntry index containing the user of this entry. We can actually 1451 /// have multiple users so the data structure is not truly a tree. 1452 SmallVector<EdgeInfo, 1> UserTreeIndices; 1453 1454 /// The index of this treeEntry in VectorizableTree. 1455 int Idx = -1; 1456 1457 private: 1458 /// The operands of each instruction in each lane Operands[op_index][lane]. 1459 /// Note: This helps avoid the replication of the code that performs the 1460 /// reordering of operands during buildTree_rec() and vectorizeTree(). 1461 SmallVector<ValueList, 2> Operands; 1462 1463 /// The main/alternate instruction. 1464 Instruction *MainOp = nullptr; 1465 Instruction *AltOp = nullptr; 1466 1467 public: 1468 /// Set this bundle's \p OpIdx'th operand to \p OpVL. 1469 void setOperand(unsigned OpIdx, ArrayRef<Value *> OpVL) { 1470 if (Operands.size() < OpIdx + 1) 1471 Operands.resize(OpIdx + 1); 1472 assert(Operands[OpIdx].size() == 0 && "Already resized?"); 1473 Operands[OpIdx].resize(Scalars.size()); 1474 for (unsigned Lane = 0, E = Scalars.size(); Lane != E; ++Lane) 1475 Operands[OpIdx][Lane] = OpVL[Lane]; 1476 } 1477 1478 /// Set the operands of this bundle in their original order. 1479 void setOperandsInOrder() { 1480 assert(Operands.empty() && "Already initialized?"); 1481 auto *I0 = cast<Instruction>(Scalars[0]); 1482 Operands.resize(I0->getNumOperands()); 1483 unsigned NumLanes = Scalars.size(); 1484 for (unsigned OpIdx = 0, NumOperands = I0->getNumOperands(); 1485 OpIdx != NumOperands; ++OpIdx) { 1486 Operands[OpIdx].resize(NumLanes); 1487 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { 1488 auto *I = cast<Instruction>(Scalars[Lane]); 1489 assert(I->getNumOperands() == NumOperands && 1490 "Expected same number of operands"); 1491 Operands[OpIdx][Lane] = I->getOperand(OpIdx); 1492 } 1493 } 1494 } 1495 1496 /// \returns the \p OpIdx operand of this TreeEntry. 1497 ValueList &getOperand(unsigned OpIdx) { 1498 assert(OpIdx < Operands.size() && "Off bounds"); 1499 return Operands[OpIdx]; 1500 } 1501 1502 /// \returns the number of operands. 1503 unsigned getNumOperands() const { return Operands.size(); } 1504 1505 /// \return the single \p OpIdx operand. 1506 Value *getSingleOperand(unsigned OpIdx) const { 1507 assert(OpIdx < Operands.size() && "Off bounds"); 1508 assert(!Operands[OpIdx].empty() && "No operand available"); 1509 return Operands[OpIdx][0]; 1510 } 1511 1512 /// Some of the instructions in the list have alternate opcodes. 1513 bool isAltShuffle() const { 1514 return getOpcode() != getAltOpcode(); 1515 } 1516 1517 bool isOpcodeOrAlt(Instruction *I) const { 1518 unsigned CheckedOpcode = I->getOpcode(); 1519 return (getOpcode() == CheckedOpcode || 1520 getAltOpcode() == CheckedOpcode); 1521 } 1522 1523 /// Chooses the correct key for scheduling data. If \p Op has the same (or 1524 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is 1525 /// \p OpValue. 1526 Value *isOneOf(Value *Op) const { 1527 auto *I = dyn_cast<Instruction>(Op); 1528 if (I && isOpcodeOrAlt(I)) 1529 return Op; 1530 return MainOp; 1531 } 1532 1533 void setOperations(const InstructionsState &S) { 1534 MainOp = S.MainOp; 1535 AltOp = S.AltOp; 1536 } 1537 1538 Instruction *getMainOp() const { 1539 return MainOp; 1540 } 1541 1542 Instruction *getAltOp() const { 1543 return AltOp; 1544 } 1545 1546 /// The main/alternate opcodes for the list of instructions. 1547 unsigned getOpcode() const { 1548 return MainOp ? MainOp->getOpcode() : 0; 1549 } 1550 1551 unsigned getAltOpcode() const { 1552 return AltOp ? AltOp->getOpcode() : 0; 1553 } 1554 1555 /// Update operations state of this entry if reorder occurred. 1556 bool updateStateIfReorder() { 1557 if (ReorderIndices.empty()) 1558 return false; 1559 InstructionsState S = getSameOpcode(Scalars, ReorderIndices.front()); 1560 setOperations(S); 1561 return true; 1562 } 1563 1564 #ifndef NDEBUG 1565 /// Debug printer. 1566 LLVM_DUMP_METHOD void dump() const { 1567 dbgs() << Idx << ".\n"; 1568 for (unsigned OpI = 0, OpE = Operands.size(); OpI != OpE; ++OpI) { 1569 dbgs() << "Operand " << OpI << ":\n"; 1570 for (const Value *V : Operands[OpI]) 1571 dbgs().indent(2) << *V << "\n"; 1572 } 1573 dbgs() << "Scalars: \n"; 1574 for (Value *V : Scalars) 1575 dbgs().indent(2) << *V << "\n"; 1576 dbgs() << "NeedToGather: " << NeedToGather << "\n"; 1577 dbgs() << "MainOp: "; 1578 if (MainOp) 1579 dbgs() << *MainOp << "\n"; 1580 else 1581 dbgs() << "NULL\n"; 1582 dbgs() << "AltOp: "; 1583 if (AltOp) 1584 dbgs() << *AltOp << "\n"; 1585 else 1586 dbgs() << "NULL\n"; 1587 dbgs() << "VectorizedValue: "; 1588 if (VectorizedValue) 1589 dbgs() << *VectorizedValue << "\n"; 1590 else 1591 dbgs() << "NULL\n"; 1592 dbgs() << "ReuseShuffleIndices: "; 1593 if (ReuseShuffleIndices.empty()) 1594 dbgs() << "Emtpy"; 1595 else 1596 for (unsigned ReuseIdx : ReuseShuffleIndices) 1597 dbgs() << ReuseIdx << ", "; 1598 dbgs() << "\n"; 1599 dbgs() << "ReorderIndices: "; 1600 for (unsigned ReorderIdx : ReorderIndices) 1601 dbgs() << ReorderIdx << ", "; 1602 dbgs() << "\n"; 1603 dbgs() << "UserTreeIndices: "; 1604 for (const auto &EInfo : UserTreeIndices) 1605 dbgs() << EInfo << ", "; 1606 dbgs() << "\n"; 1607 } 1608 #endif 1609 }; 1610 1611 /// Create a new VectorizableTree entry. 1612 TreeEntry *newTreeEntry(ArrayRef<Value *> VL, Optional<ScheduleData *> Bundle, 1613 const InstructionsState &S, 1614 const EdgeInfo &UserTreeIdx, 1615 ArrayRef<unsigned> ReuseShuffleIndices = None, 1616 ArrayRef<unsigned> ReorderIndices = None) { 1617 bool Vectorized = (bool)Bundle; 1618 VectorizableTree.push_back(std::make_unique<TreeEntry>(VectorizableTree)); 1619 TreeEntry *Last = VectorizableTree.back().get(); 1620 Last->Idx = VectorizableTree.size() - 1; 1621 Last->Scalars.insert(Last->Scalars.begin(), VL.begin(), VL.end()); 1622 Last->NeedToGather = !Vectorized; 1623 Last->ReuseShuffleIndices.append(ReuseShuffleIndices.begin(), 1624 ReuseShuffleIndices.end()); 1625 Last->ReorderIndices = ReorderIndices; 1626 Last->setOperations(S); 1627 if (Vectorized) { 1628 for (int i = 0, e = VL.size(); i != e; ++i) { 1629 assert(!getTreeEntry(VL[i]) && "Scalar already in tree!"); 1630 ScalarToTreeEntry[VL[i]] = Last; 1631 } 1632 // Update the scheduler bundle to point to this TreeEntry. 1633 unsigned Lane = 0; 1634 for (ScheduleData *BundleMember = Bundle.getValue(); BundleMember; 1635 BundleMember = BundleMember->NextInBundle) { 1636 BundleMember->TE = Last; 1637 BundleMember->Lane = Lane; 1638 ++Lane; 1639 } 1640 assert((!Bundle.getValue() || Lane == VL.size()) && 1641 "Bundle and VL out of sync"); 1642 } else { 1643 MustGather.insert(VL.begin(), VL.end()); 1644 } 1645 1646 if (UserTreeIdx.UserTE) 1647 Last->UserTreeIndices.push_back(UserTreeIdx); 1648 1649 return Last; 1650 } 1651 1652 /// -- Vectorization State -- 1653 /// Holds all of the tree entries. 1654 TreeEntry::VecTreeTy VectorizableTree; 1655 1656 #ifndef NDEBUG 1657 /// Debug printer. 1658 LLVM_DUMP_METHOD void dumpVectorizableTree() const { 1659 for (unsigned Id = 0, IdE = VectorizableTree.size(); Id != IdE; ++Id) { 1660 VectorizableTree[Id]->dump(); 1661 dbgs() << "\n"; 1662 } 1663 } 1664 #endif 1665 1666 TreeEntry *getTreeEntry(Value *V) { 1667 auto I = ScalarToTreeEntry.find(V); 1668 if (I != ScalarToTreeEntry.end()) 1669 return I->second; 1670 return nullptr; 1671 } 1672 1673 const TreeEntry *getTreeEntry(Value *V) const { 1674 auto I = ScalarToTreeEntry.find(V); 1675 if (I != ScalarToTreeEntry.end()) 1676 return I->second; 1677 return nullptr; 1678 } 1679 1680 /// Maps a specific scalar to its tree entry. 1681 SmallDenseMap<Value*, TreeEntry *> ScalarToTreeEntry; 1682 1683 /// A list of scalars that we found that we need to keep as scalars. 1684 ValueSet MustGather; 1685 1686 /// This POD struct describes one external user in the vectorized tree. 1687 struct ExternalUser { 1688 ExternalUser(Value *S, llvm::User *U, int L) 1689 : Scalar(S), User(U), Lane(L) {} 1690 1691 // Which scalar in our function. 1692 Value *Scalar; 1693 1694 // Which user that uses the scalar. 1695 llvm::User *User; 1696 1697 // Which lane does the scalar belong to. 1698 int Lane; 1699 }; 1700 using UserList = SmallVector<ExternalUser, 16>; 1701 1702 /// Checks if two instructions may access the same memory. 1703 /// 1704 /// \p Loc1 is the location of \p Inst1. It is passed explicitly because it 1705 /// is invariant in the calling loop. 1706 bool isAliased(const MemoryLocation &Loc1, Instruction *Inst1, 1707 Instruction *Inst2) { 1708 // First check if the result is already in the cache. 1709 AliasCacheKey key = std::make_pair(Inst1, Inst2); 1710 Optional<bool> &result = AliasCache[key]; 1711 if (result.hasValue()) { 1712 return result.getValue(); 1713 } 1714 MemoryLocation Loc2 = getLocation(Inst2, AA); 1715 bool aliased = true; 1716 if (Loc1.Ptr && Loc2.Ptr && isSimple(Inst1) && isSimple(Inst2)) { 1717 // Do the alias check. 1718 aliased = AA->alias(Loc1, Loc2); 1719 } 1720 // Store the result in the cache. 1721 result = aliased; 1722 return aliased; 1723 } 1724 1725 using AliasCacheKey = std::pair<Instruction *, Instruction *>; 1726 1727 /// Cache for alias results. 1728 /// TODO: consider moving this to the AliasAnalysis itself. 1729 DenseMap<AliasCacheKey, Optional<bool>> AliasCache; 1730 1731 /// Removes an instruction from its block and eventually deletes it. 1732 /// It's like Instruction::eraseFromParent() except that the actual deletion 1733 /// is delayed until BoUpSLP is destructed. 1734 /// This is required to ensure that there are no incorrect collisions in the 1735 /// AliasCache, which can happen if a new instruction is allocated at the 1736 /// same address as a previously deleted instruction. 1737 void eraseInstruction(Instruction *I, bool ReplaceOpsWithUndef = false) { 1738 auto It = DeletedInstructions.try_emplace(I, ReplaceOpsWithUndef).first; 1739 It->getSecond() = It->getSecond() && ReplaceOpsWithUndef; 1740 } 1741 1742 /// Temporary store for deleted instructions. Instructions will be deleted 1743 /// eventually when the BoUpSLP is destructed. 1744 DenseMap<Instruction *, bool> DeletedInstructions; 1745 1746 /// A list of values that need to extracted out of the tree. 1747 /// This list holds pairs of (Internal Scalar : External User). External User 1748 /// can be nullptr, it means that this Internal Scalar will be used later, 1749 /// after vectorization. 1750 UserList ExternalUses; 1751 1752 /// Values used only by @llvm.assume calls. 1753 SmallPtrSet<const Value *, 32> EphValues; 1754 1755 /// Holds all of the instructions that we gathered. 1756 SetVector<Instruction *> GatherSeq; 1757 1758 /// A list of blocks that we are going to CSE. 1759 SetVector<BasicBlock *> CSEBlocks; 1760 1761 /// Contains all scheduling relevant data for an instruction. 1762 /// A ScheduleData either represents a single instruction or a member of an 1763 /// instruction bundle (= a group of instructions which is combined into a 1764 /// vector instruction). 1765 struct ScheduleData { 1766 // The initial value for the dependency counters. It means that the 1767 // dependencies are not calculated yet. 1768 enum { InvalidDeps = -1 }; 1769 1770 ScheduleData() = default; 1771 1772 void init(int BlockSchedulingRegionID, Value *OpVal) { 1773 FirstInBundle = this; 1774 NextInBundle = nullptr; 1775 NextLoadStore = nullptr; 1776 IsScheduled = false; 1777 SchedulingRegionID = BlockSchedulingRegionID; 1778 UnscheduledDepsInBundle = UnscheduledDeps; 1779 clearDependencies(); 1780 OpValue = OpVal; 1781 TE = nullptr; 1782 Lane = -1; 1783 } 1784 1785 /// Returns true if the dependency information has been calculated. 1786 bool hasValidDependencies() const { return Dependencies != InvalidDeps; } 1787 1788 /// Returns true for single instructions and for bundle representatives 1789 /// (= the head of a bundle). 1790 bool isSchedulingEntity() const { return FirstInBundle == this; } 1791 1792 /// Returns true if it represents an instruction bundle and not only a 1793 /// single instruction. 1794 bool isPartOfBundle() const { 1795 return NextInBundle != nullptr || FirstInBundle != this; 1796 } 1797 1798 /// Returns true if it is ready for scheduling, i.e. it has no more 1799 /// unscheduled depending instructions/bundles. 1800 bool isReady() const { 1801 assert(isSchedulingEntity() && 1802 "can't consider non-scheduling entity for ready list"); 1803 return UnscheduledDepsInBundle == 0 && !IsScheduled; 1804 } 1805 1806 /// Modifies the number of unscheduled dependencies, also updating it for 1807 /// the whole bundle. 1808 int incrementUnscheduledDeps(int Incr) { 1809 UnscheduledDeps += Incr; 1810 return FirstInBundle->UnscheduledDepsInBundle += Incr; 1811 } 1812 1813 /// Sets the number of unscheduled dependencies to the number of 1814 /// dependencies. 1815 void resetUnscheduledDeps() { 1816 incrementUnscheduledDeps(Dependencies - UnscheduledDeps); 1817 } 1818 1819 /// Clears all dependency information. 1820 void clearDependencies() { 1821 Dependencies = InvalidDeps; 1822 resetUnscheduledDeps(); 1823 MemoryDependencies.clear(); 1824 } 1825 1826 void dump(raw_ostream &os) const { 1827 if (!isSchedulingEntity()) { 1828 os << "/ " << *Inst; 1829 } else if (NextInBundle) { 1830 os << '[' << *Inst; 1831 ScheduleData *SD = NextInBundle; 1832 while (SD) { 1833 os << ';' << *SD->Inst; 1834 SD = SD->NextInBundle; 1835 } 1836 os << ']'; 1837 } else { 1838 os << *Inst; 1839 } 1840 } 1841 1842 Instruction *Inst = nullptr; 1843 1844 /// Points to the head in an instruction bundle (and always to this for 1845 /// single instructions). 1846 ScheduleData *FirstInBundle = nullptr; 1847 1848 /// Single linked list of all instructions in a bundle. Null if it is a 1849 /// single instruction. 1850 ScheduleData *NextInBundle = nullptr; 1851 1852 /// Single linked list of all memory instructions (e.g. load, store, call) 1853 /// in the block - until the end of the scheduling region. 1854 ScheduleData *NextLoadStore = nullptr; 1855 1856 /// The dependent memory instructions. 1857 /// This list is derived on demand in calculateDependencies(). 1858 SmallVector<ScheduleData *, 4> MemoryDependencies; 1859 1860 /// This ScheduleData is in the current scheduling region if this matches 1861 /// the current SchedulingRegionID of BlockScheduling. 1862 int SchedulingRegionID = 0; 1863 1864 /// Used for getting a "good" final ordering of instructions. 1865 int SchedulingPriority = 0; 1866 1867 /// The number of dependencies. Constitutes of the number of users of the 1868 /// instruction plus the number of dependent memory instructions (if any). 1869 /// This value is calculated on demand. 1870 /// If InvalidDeps, the number of dependencies is not calculated yet. 1871 int Dependencies = InvalidDeps; 1872 1873 /// The number of dependencies minus the number of dependencies of scheduled 1874 /// instructions. As soon as this is zero, the instruction/bundle gets ready 1875 /// for scheduling. 1876 /// Note that this is negative as long as Dependencies is not calculated. 1877 int UnscheduledDeps = InvalidDeps; 1878 1879 /// The sum of UnscheduledDeps in a bundle. Equals to UnscheduledDeps for 1880 /// single instructions. 1881 int UnscheduledDepsInBundle = InvalidDeps; 1882 1883 /// True if this instruction is scheduled (or considered as scheduled in the 1884 /// dry-run). 1885 bool IsScheduled = false; 1886 1887 /// Opcode of the current instruction in the schedule data. 1888 Value *OpValue = nullptr; 1889 1890 /// The TreeEntry that this instruction corresponds to. 1891 TreeEntry *TE = nullptr; 1892 1893 /// The lane of this node in the TreeEntry. 1894 int Lane = -1; 1895 }; 1896 1897 #ifndef NDEBUG 1898 friend inline raw_ostream &operator<<(raw_ostream &os, 1899 const BoUpSLP::ScheduleData &SD) { 1900 SD.dump(os); 1901 return os; 1902 } 1903 #endif 1904 1905 friend struct GraphTraits<BoUpSLP *>; 1906 friend struct DOTGraphTraits<BoUpSLP *>; 1907 1908 /// Contains all scheduling data for a basic block. 1909 struct BlockScheduling { 1910 BlockScheduling(BasicBlock *BB) 1911 : BB(BB), ChunkSize(BB->size()), ChunkPos(ChunkSize) {} 1912 1913 void clear() { 1914 ReadyInsts.clear(); 1915 ScheduleStart = nullptr; 1916 ScheduleEnd = nullptr; 1917 FirstLoadStoreInRegion = nullptr; 1918 LastLoadStoreInRegion = nullptr; 1919 1920 // Reduce the maximum schedule region size by the size of the 1921 // previous scheduling run. 1922 ScheduleRegionSizeLimit -= ScheduleRegionSize; 1923 if (ScheduleRegionSizeLimit < MinScheduleRegionSize) 1924 ScheduleRegionSizeLimit = MinScheduleRegionSize; 1925 ScheduleRegionSize = 0; 1926 1927 // Make a new scheduling region, i.e. all existing ScheduleData is not 1928 // in the new region yet. 1929 ++SchedulingRegionID; 1930 } 1931 1932 ScheduleData *getScheduleData(Value *V) { 1933 ScheduleData *SD = ScheduleDataMap[V]; 1934 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 1935 return SD; 1936 return nullptr; 1937 } 1938 1939 ScheduleData *getScheduleData(Value *V, Value *Key) { 1940 if (V == Key) 1941 return getScheduleData(V); 1942 auto I = ExtraScheduleDataMap.find(V); 1943 if (I != ExtraScheduleDataMap.end()) { 1944 ScheduleData *SD = I->second[Key]; 1945 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 1946 return SD; 1947 } 1948 return nullptr; 1949 } 1950 1951 bool isInSchedulingRegion(ScheduleData *SD) const { 1952 return SD->SchedulingRegionID == SchedulingRegionID; 1953 } 1954 1955 /// Marks an instruction as scheduled and puts all dependent ready 1956 /// instructions into the ready-list. 1957 template <typename ReadyListType> 1958 void schedule(ScheduleData *SD, ReadyListType &ReadyList) { 1959 SD->IsScheduled = true; 1960 LLVM_DEBUG(dbgs() << "SLP: schedule " << *SD << "\n"); 1961 1962 ScheduleData *BundleMember = SD; 1963 while (BundleMember) { 1964 if (BundleMember->Inst != BundleMember->OpValue) { 1965 BundleMember = BundleMember->NextInBundle; 1966 continue; 1967 } 1968 // Handle the def-use chain dependencies. 1969 1970 // Decrement the unscheduled counter and insert to ready list if ready. 1971 auto &&DecrUnsched = [this, &ReadyList](Instruction *I) { 1972 doForAllOpcodes(I, [&ReadyList](ScheduleData *OpDef) { 1973 if (OpDef && OpDef->hasValidDependencies() && 1974 OpDef->incrementUnscheduledDeps(-1) == 0) { 1975 // There are no more unscheduled dependencies after 1976 // decrementing, so we can put the dependent instruction 1977 // into the ready list. 1978 ScheduleData *DepBundle = OpDef->FirstInBundle; 1979 assert(!DepBundle->IsScheduled && 1980 "already scheduled bundle gets ready"); 1981 ReadyList.insert(DepBundle); 1982 LLVM_DEBUG(dbgs() 1983 << "SLP: gets ready (def): " << *DepBundle << "\n"); 1984 } 1985 }); 1986 }; 1987 1988 // If BundleMember is a vector bundle, its operands may have been 1989 // reordered duiring buildTree(). We therefore need to get its operands 1990 // through the TreeEntry. 1991 if (TreeEntry *TE = BundleMember->TE) { 1992 int Lane = BundleMember->Lane; 1993 assert(Lane >= 0 && "Lane not set"); 1994 for (unsigned OpIdx = 0, NumOperands = TE->getNumOperands(); 1995 OpIdx != NumOperands; ++OpIdx) 1996 if (auto *I = dyn_cast<Instruction>(TE->getOperand(OpIdx)[Lane])) 1997 DecrUnsched(I); 1998 } else { 1999 // If BundleMember is a stand-alone instruction, no operand reordering 2000 // has taken place, so we directly access its operands. 2001 for (Use &U : BundleMember->Inst->operands()) 2002 if (auto *I = dyn_cast<Instruction>(U.get())) 2003 DecrUnsched(I); 2004 } 2005 // Handle the memory dependencies. 2006 for (ScheduleData *MemoryDepSD : BundleMember->MemoryDependencies) { 2007 if (MemoryDepSD->incrementUnscheduledDeps(-1) == 0) { 2008 // There are no more unscheduled dependencies after decrementing, 2009 // so we can put the dependent instruction into the ready list. 2010 ScheduleData *DepBundle = MemoryDepSD->FirstInBundle; 2011 assert(!DepBundle->IsScheduled && 2012 "already scheduled bundle gets ready"); 2013 ReadyList.insert(DepBundle); 2014 LLVM_DEBUG(dbgs() 2015 << "SLP: gets ready (mem): " << *DepBundle << "\n"); 2016 } 2017 } 2018 BundleMember = BundleMember->NextInBundle; 2019 } 2020 } 2021 2022 void doForAllOpcodes(Value *V, 2023 function_ref<void(ScheduleData *SD)> Action) { 2024 if (ScheduleData *SD = getScheduleData(V)) 2025 Action(SD); 2026 auto I = ExtraScheduleDataMap.find(V); 2027 if (I != ExtraScheduleDataMap.end()) 2028 for (auto &P : I->second) 2029 if (P.second->SchedulingRegionID == SchedulingRegionID) 2030 Action(P.second); 2031 } 2032 2033 /// Put all instructions into the ReadyList which are ready for scheduling. 2034 template <typename ReadyListType> 2035 void initialFillReadyList(ReadyListType &ReadyList) { 2036 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 2037 doForAllOpcodes(I, [&](ScheduleData *SD) { 2038 if (SD->isSchedulingEntity() && SD->isReady()) { 2039 ReadyList.insert(SD); 2040 LLVM_DEBUG(dbgs() 2041 << "SLP: initially in ready list: " << *I << "\n"); 2042 } 2043 }); 2044 } 2045 } 2046 2047 /// Checks if a bundle of instructions can be scheduled, i.e. has no 2048 /// cyclic dependencies. This is only a dry-run, no instructions are 2049 /// actually moved at this stage. 2050 /// \returns the scheduling bundle. The returned Optional value is non-None 2051 /// if \p VL is allowed to be scheduled. 2052 Optional<ScheduleData *> 2053 tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 2054 const InstructionsState &S); 2055 2056 /// Un-bundles a group of instructions. 2057 void cancelScheduling(ArrayRef<Value *> VL, Value *OpValue); 2058 2059 /// Allocates schedule data chunk. 2060 ScheduleData *allocateScheduleDataChunks(); 2061 2062 /// Extends the scheduling region so that V is inside the region. 2063 /// \returns true if the region size is within the limit. 2064 bool extendSchedulingRegion(Value *V, const InstructionsState &S); 2065 2066 /// Initialize the ScheduleData structures for new instructions in the 2067 /// scheduling region. 2068 void initScheduleData(Instruction *FromI, Instruction *ToI, 2069 ScheduleData *PrevLoadStore, 2070 ScheduleData *NextLoadStore); 2071 2072 /// Updates the dependency information of a bundle and of all instructions/ 2073 /// bundles which depend on the original bundle. 2074 void calculateDependencies(ScheduleData *SD, bool InsertInReadyList, 2075 BoUpSLP *SLP); 2076 2077 /// Sets all instruction in the scheduling region to un-scheduled. 2078 void resetSchedule(); 2079 2080 BasicBlock *BB; 2081 2082 /// Simple memory allocation for ScheduleData. 2083 std::vector<std::unique_ptr<ScheduleData[]>> ScheduleDataChunks; 2084 2085 /// The size of a ScheduleData array in ScheduleDataChunks. 2086 int ChunkSize; 2087 2088 /// The allocator position in the current chunk, which is the last entry 2089 /// of ScheduleDataChunks. 2090 int ChunkPos; 2091 2092 /// Attaches ScheduleData to Instruction. 2093 /// Note that the mapping survives during all vectorization iterations, i.e. 2094 /// ScheduleData structures are recycled. 2095 DenseMap<Value *, ScheduleData *> ScheduleDataMap; 2096 2097 /// Attaches ScheduleData to Instruction with the leading key. 2098 DenseMap<Value *, SmallDenseMap<Value *, ScheduleData *>> 2099 ExtraScheduleDataMap; 2100 2101 struct ReadyList : SmallVector<ScheduleData *, 8> { 2102 void insert(ScheduleData *SD) { push_back(SD); } 2103 }; 2104 2105 /// The ready-list for scheduling (only used for the dry-run). 2106 ReadyList ReadyInsts; 2107 2108 /// The first instruction of the scheduling region. 2109 Instruction *ScheduleStart = nullptr; 2110 2111 /// The first instruction _after_ the scheduling region. 2112 Instruction *ScheduleEnd = nullptr; 2113 2114 /// The first memory accessing instruction in the scheduling region 2115 /// (can be null). 2116 ScheduleData *FirstLoadStoreInRegion = nullptr; 2117 2118 /// The last memory accessing instruction in the scheduling region 2119 /// (can be null). 2120 ScheduleData *LastLoadStoreInRegion = nullptr; 2121 2122 /// The current size of the scheduling region. 2123 int ScheduleRegionSize = 0; 2124 2125 /// The maximum size allowed for the scheduling region. 2126 int ScheduleRegionSizeLimit = ScheduleRegionSizeBudget; 2127 2128 /// The ID of the scheduling region. For a new vectorization iteration this 2129 /// is incremented which "removes" all ScheduleData from the region. 2130 // Make sure that the initial SchedulingRegionID is greater than the 2131 // initial SchedulingRegionID in ScheduleData (which is 0). 2132 int SchedulingRegionID = 1; 2133 }; 2134 2135 /// Attaches the BlockScheduling structures to basic blocks. 2136 MapVector<BasicBlock *, std::unique_ptr<BlockScheduling>> BlocksSchedules; 2137 2138 /// Performs the "real" scheduling. Done before vectorization is actually 2139 /// performed in a basic block. 2140 void scheduleBlock(BlockScheduling *BS); 2141 2142 /// List of users to ignore during scheduling and that don't need extracting. 2143 ArrayRef<Value *> UserIgnoreList; 2144 2145 using OrdersType = SmallVector<unsigned, 4>; 2146 /// A DenseMapInfo implementation for holding DenseMaps and DenseSets of 2147 /// sorted SmallVectors of unsigned. 2148 struct OrdersTypeDenseMapInfo { 2149 static OrdersType getEmptyKey() { 2150 OrdersType V; 2151 V.push_back(~1U); 2152 return V; 2153 } 2154 2155 static OrdersType getTombstoneKey() { 2156 OrdersType V; 2157 V.push_back(~2U); 2158 return V; 2159 } 2160 2161 static unsigned getHashValue(const OrdersType &V) { 2162 return static_cast<unsigned>(hash_combine_range(V.begin(), V.end())); 2163 } 2164 2165 static bool isEqual(const OrdersType &LHS, const OrdersType &RHS) { 2166 return LHS == RHS; 2167 } 2168 }; 2169 2170 /// Contains orders of operations along with the number of bundles that have 2171 /// operations in this order. It stores only those orders that require 2172 /// reordering, if reordering is not required it is counted using \a 2173 /// NumOpsWantToKeepOriginalOrder. 2174 DenseMap<OrdersType, unsigned, OrdersTypeDenseMapInfo> NumOpsWantToKeepOrder; 2175 /// Number of bundles that do not require reordering. 2176 unsigned NumOpsWantToKeepOriginalOrder = 0; 2177 2178 // Analysis and block reference. 2179 Function *F; 2180 ScalarEvolution *SE; 2181 TargetTransformInfo *TTI; 2182 TargetLibraryInfo *TLI; 2183 AliasAnalysis *AA; 2184 LoopInfo *LI; 2185 DominatorTree *DT; 2186 AssumptionCache *AC; 2187 DemandedBits *DB; 2188 const DataLayout *DL; 2189 OptimizationRemarkEmitter *ORE; 2190 2191 unsigned MaxVecRegSize; // This is set by TTI or overridden by cl::opt. 2192 unsigned MinVecRegSize; // Set by cl::opt (default: 128). 2193 2194 /// Instruction builder to construct the vectorized tree. 2195 IRBuilder<> Builder; 2196 2197 /// A map of scalar integer values to the smallest bit width with which they 2198 /// can legally be represented. The values map to (width, signed) pairs, 2199 /// where "width" indicates the minimum bit width and "signed" is True if the 2200 /// value must be signed-extended, rather than zero-extended, back to its 2201 /// original width. 2202 MapVector<Value *, std::pair<uint64_t, bool>> MinBWs; 2203 }; 2204 2205 } // end namespace slpvectorizer 2206 2207 template <> struct GraphTraits<BoUpSLP *> { 2208 using TreeEntry = BoUpSLP::TreeEntry; 2209 2210 /// NodeRef has to be a pointer per the GraphWriter. 2211 using NodeRef = TreeEntry *; 2212 2213 using ContainerTy = BoUpSLP::TreeEntry::VecTreeTy; 2214 2215 /// Add the VectorizableTree to the index iterator to be able to return 2216 /// TreeEntry pointers. 2217 struct ChildIteratorType 2218 : public iterator_adaptor_base< 2219 ChildIteratorType, SmallVector<BoUpSLP::EdgeInfo, 1>::iterator> { 2220 ContainerTy &VectorizableTree; 2221 2222 ChildIteratorType(SmallVector<BoUpSLP::EdgeInfo, 1>::iterator W, 2223 ContainerTy &VT) 2224 : ChildIteratorType::iterator_adaptor_base(W), VectorizableTree(VT) {} 2225 2226 NodeRef operator*() { return I->UserTE; } 2227 }; 2228 2229 static NodeRef getEntryNode(BoUpSLP &R) { 2230 return R.VectorizableTree[0].get(); 2231 } 2232 2233 static ChildIteratorType child_begin(NodeRef N) { 2234 return {N->UserTreeIndices.begin(), N->Container}; 2235 } 2236 2237 static ChildIteratorType child_end(NodeRef N) { 2238 return {N->UserTreeIndices.end(), N->Container}; 2239 } 2240 2241 /// For the node iterator we just need to turn the TreeEntry iterator into a 2242 /// TreeEntry* iterator so that it dereferences to NodeRef. 2243 class nodes_iterator { 2244 using ItTy = ContainerTy::iterator; 2245 ItTy It; 2246 2247 public: 2248 nodes_iterator(const ItTy &It2) : It(It2) {} 2249 NodeRef operator*() { return It->get(); } 2250 nodes_iterator operator++() { 2251 ++It; 2252 return *this; 2253 } 2254 bool operator!=(const nodes_iterator &N2) const { return N2.It != It; } 2255 }; 2256 2257 static nodes_iterator nodes_begin(BoUpSLP *R) { 2258 return nodes_iterator(R->VectorizableTree.begin()); 2259 } 2260 2261 static nodes_iterator nodes_end(BoUpSLP *R) { 2262 return nodes_iterator(R->VectorizableTree.end()); 2263 } 2264 2265 static unsigned size(BoUpSLP *R) { return R->VectorizableTree.size(); } 2266 }; 2267 2268 template <> struct DOTGraphTraits<BoUpSLP *> : public DefaultDOTGraphTraits { 2269 using TreeEntry = BoUpSLP::TreeEntry; 2270 2271 DOTGraphTraits(bool isSimple = false) : DefaultDOTGraphTraits(isSimple) {} 2272 2273 std::string getNodeLabel(const TreeEntry *Entry, const BoUpSLP *R) { 2274 std::string Str; 2275 raw_string_ostream OS(Str); 2276 if (isSplat(Entry->Scalars)) { 2277 OS << "<splat> " << *Entry->Scalars[0]; 2278 return Str; 2279 } 2280 for (auto V : Entry->Scalars) { 2281 OS << *V; 2282 if (std::any_of( 2283 R->ExternalUses.begin(), R->ExternalUses.end(), 2284 [&](const BoUpSLP::ExternalUser &EU) { return EU.Scalar == V; })) 2285 OS << " <extract>"; 2286 OS << "\n"; 2287 } 2288 return Str; 2289 } 2290 2291 static std::string getNodeAttributes(const TreeEntry *Entry, 2292 const BoUpSLP *) { 2293 if (Entry->NeedToGather) 2294 return "color=red"; 2295 return ""; 2296 } 2297 }; 2298 2299 } // end namespace llvm 2300 2301 BoUpSLP::~BoUpSLP() { 2302 for (const auto &Pair : DeletedInstructions) { 2303 // Replace operands of ignored instructions with Undefs in case if they were 2304 // marked for deletion. 2305 if (Pair.getSecond()) { 2306 Value *Undef = UndefValue::get(Pair.getFirst()->getType()); 2307 Pair.getFirst()->replaceAllUsesWith(Undef); 2308 } 2309 Pair.getFirst()->dropAllReferences(); 2310 } 2311 for (const auto &Pair : DeletedInstructions) { 2312 assert(Pair.getFirst()->use_empty() && 2313 "trying to erase instruction with users."); 2314 Pair.getFirst()->eraseFromParent(); 2315 } 2316 } 2317 2318 void BoUpSLP::eraseInstructions(ArrayRef<Value *> AV) { 2319 for (auto *V : AV) { 2320 if (auto *I = dyn_cast<Instruction>(V)) 2321 eraseInstruction(I, /*ReplaceWithUndef=*/true); 2322 }; 2323 } 2324 2325 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2326 ArrayRef<Value *> UserIgnoreLst) { 2327 ExtraValueToDebugLocsMap ExternallyUsedValues; 2328 buildTree(Roots, ExternallyUsedValues, UserIgnoreLst); 2329 } 2330 2331 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 2332 ExtraValueToDebugLocsMap &ExternallyUsedValues, 2333 ArrayRef<Value *> UserIgnoreLst) { 2334 deleteTree(); 2335 UserIgnoreList = UserIgnoreLst; 2336 if (!allSameType(Roots)) 2337 return; 2338 buildTree_rec(Roots, 0, EdgeInfo()); 2339 2340 // Collect the values that we need to extract from the tree. 2341 for (auto &TEPtr : VectorizableTree) { 2342 TreeEntry *Entry = TEPtr.get(); 2343 2344 // No need to handle users of gathered values. 2345 if (Entry->NeedToGather) 2346 continue; 2347 2348 // For each lane: 2349 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 2350 Value *Scalar = Entry->Scalars[Lane]; 2351 int FoundLane = Lane; 2352 if (!Entry->ReuseShuffleIndices.empty()) { 2353 FoundLane = 2354 std::distance(Entry->ReuseShuffleIndices.begin(), 2355 llvm::find(Entry->ReuseShuffleIndices, FoundLane)); 2356 } 2357 2358 // Check if the scalar is externally used as an extra arg. 2359 auto ExtI = ExternallyUsedValues.find(Scalar); 2360 if (ExtI != ExternallyUsedValues.end()) { 2361 LLVM_DEBUG(dbgs() << "SLP: Need to extract: Extra arg from lane " 2362 << Lane << " from " << *Scalar << ".\n"); 2363 ExternalUses.emplace_back(Scalar, nullptr, FoundLane); 2364 } 2365 for (User *U : Scalar->users()) { 2366 LLVM_DEBUG(dbgs() << "SLP: Checking user:" << *U << ".\n"); 2367 2368 Instruction *UserInst = dyn_cast<Instruction>(U); 2369 if (!UserInst) 2370 continue; 2371 2372 // Skip in-tree scalars that become vectors 2373 if (TreeEntry *UseEntry = getTreeEntry(U)) { 2374 Value *UseScalar = UseEntry->Scalars[0]; 2375 // Some in-tree scalars will remain as scalar in vectorized 2376 // instructions. If that is the case, the one in Lane 0 will 2377 // be used. 2378 if (UseScalar != U || 2379 !InTreeUserNeedToExtract(Scalar, UserInst, TLI)) { 2380 LLVM_DEBUG(dbgs() << "SLP: \tInternal user will be removed:" << *U 2381 << ".\n"); 2382 assert(!UseEntry->NeedToGather && "Bad state"); 2383 continue; 2384 } 2385 } 2386 2387 // Ignore users in the user ignore list. 2388 if (is_contained(UserIgnoreList, UserInst)) 2389 continue; 2390 2391 LLVM_DEBUG(dbgs() << "SLP: Need to extract:" << *U << " from lane " 2392 << Lane << " from " << *Scalar << ".\n"); 2393 ExternalUses.push_back(ExternalUser(Scalar, U, FoundLane)); 2394 } 2395 } 2396 } 2397 } 2398 2399 void BoUpSLP::buildTree_rec(ArrayRef<Value *> VL, unsigned Depth, 2400 const EdgeInfo &UserTreeIdx) { 2401 assert((allConstant(VL) || allSameType(VL)) && "Invalid types!"); 2402 2403 InstructionsState S = getSameOpcode(VL); 2404 if (Depth == RecursionMaxDepth) { 2405 LLVM_DEBUG(dbgs() << "SLP: Gathering due to max recursion depth.\n"); 2406 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2407 return; 2408 } 2409 2410 // Don't handle vectors. 2411 if (S.OpValue->getType()->isVectorTy()) { 2412 LLVM_DEBUG(dbgs() << "SLP: Gathering due to vector type.\n"); 2413 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2414 return; 2415 } 2416 2417 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) 2418 if (SI->getValueOperand()->getType()->isVectorTy()) { 2419 LLVM_DEBUG(dbgs() << "SLP: Gathering due to store vector type.\n"); 2420 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2421 return; 2422 } 2423 2424 // If all of the operands are identical or constant we have a simple solution. 2425 if (allConstant(VL) || isSplat(VL) || !allSameBlock(VL) || !S.getOpcode()) { 2426 LLVM_DEBUG(dbgs() << "SLP: Gathering due to C,S,B,O. \n"); 2427 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2428 return; 2429 } 2430 2431 // We now know that this is a vector of instructions of the same type from 2432 // the same block. 2433 2434 // Don't vectorize ephemeral values. 2435 for (Value *V : VL) { 2436 if (EphValues.count(V)) { 2437 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2438 << ") is ephemeral.\n"); 2439 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2440 return; 2441 } 2442 } 2443 2444 // Check if this is a duplicate of another entry. 2445 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 2446 LLVM_DEBUG(dbgs() << "SLP: \tChecking bundle: " << *S.OpValue << ".\n"); 2447 if (!E->isSame(VL)) { 2448 LLVM_DEBUG(dbgs() << "SLP: Gathering due to partial overlap.\n"); 2449 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2450 return; 2451 } 2452 // Record the reuse of the tree node. FIXME, currently this is only used to 2453 // properly draw the graph rather than for the actual vectorization. 2454 E->UserTreeIndices.push_back(UserTreeIdx); 2455 LLVM_DEBUG(dbgs() << "SLP: Perfect diamond merge at " << *S.OpValue 2456 << ".\n"); 2457 return; 2458 } 2459 2460 // Check that none of the instructions in the bundle are already in the tree. 2461 for (Value *V : VL) { 2462 auto *I = dyn_cast<Instruction>(V); 2463 if (!I) 2464 continue; 2465 if (getTreeEntry(I)) { 2466 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V 2467 << ") is already in tree.\n"); 2468 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2469 return; 2470 } 2471 } 2472 2473 // If any of the scalars is marked as a value that needs to stay scalar, then 2474 // we need to gather the scalars. 2475 // The reduction nodes (stored in UserIgnoreList) also should stay scalar. 2476 for (Value *V : VL) { 2477 if (MustGather.count(V) || is_contained(UserIgnoreList, V)) { 2478 LLVM_DEBUG(dbgs() << "SLP: Gathering due to gathered scalar.\n"); 2479 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2480 return; 2481 } 2482 } 2483 2484 // Check that all of the users of the scalars that we want to vectorize are 2485 // schedulable. 2486 auto *VL0 = cast<Instruction>(S.OpValue); 2487 BasicBlock *BB = VL0->getParent(); 2488 2489 if (!DT->isReachableFromEntry(BB)) { 2490 // Don't go into unreachable blocks. They may contain instructions with 2491 // dependency cycles which confuse the final scheduling. 2492 LLVM_DEBUG(dbgs() << "SLP: bundle in unreachable block.\n"); 2493 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2494 return; 2495 } 2496 2497 // Check that every instruction appears once in this bundle. 2498 SmallVector<unsigned, 4> ReuseShuffleIndicies; 2499 SmallVector<Value *, 4> UniqueValues; 2500 DenseMap<Value *, unsigned> UniquePositions; 2501 for (Value *V : VL) { 2502 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 2503 ReuseShuffleIndicies.emplace_back(Res.first->second); 2504 if (Res.second) 2505 UniqueValues.emplace_back(V); 2506 } 2507 size_t NumUniqueScalarValues = UniqueValues.size(); 2508 if (NumUniqueScalarValues == VL.size()) { 2509 ReuseShuffleIndicies.clear(); 2510 } else { 2511 LLVM_DEBUG(dbgs() << "SLP: Shuffle for reused scalars.\n"); 2512 if (NumUniqueScalarValues <= 1 || 2513 !llvm::isPowerOf2_32(NumUniqueScalarValues)) { 2514 LLVM_DEBUG(dbgs() << "SLP: Scalar used twice in bundle.\n"); 2515 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); 2516 return; 2517 } 2518 VL = UniqueValues; 2519 } 2520 2521 auto &BSRef = BlocksSchedules[BB]; 2522 if (!BSRef) 2523 BSRef = std::make_unique<BlockScheduling>(BB); 2524 2525 BlockScheduling &BS = *BSRef.get(); 2526 2527 Optional<ScheduleData *> Bundle = BS.tryScheduleBundle(VL, this, S); 2528 if (!Bundle) { 2529 LLVM_DEBUG(dbgs() << "SLP: We are not able to schedule this bundle!\n"); 2530 assert((!BS.getScheduleData(VL0) || 2531 !BS.getScheduleData(VL0)->isPartOfBundle()) && 2532 "tryScheduleBundle should cancelScheduling on failure"); 2533 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2534 ReuseShuffleIndicies); 2535 return; 2536 } 2537 LLVM_DEBUG(dbgs() << "SLP: We are able to schedule this bundle.\n"); 2538 2539 unsigned ShuffleOrOp = S.isAltShuffle() ? 2540 (unsigned) Instruction::ShuffleVector : S.getOpcode(); 2541 switch (ShuffleOrOp) { 2542 case Instruction::PHI: { 2543 auto *PH = cast<PHINode>(VL0); 2544 2545 // Check for terminator values (e.g. invoke). 2546 for (unsigned j = 0; j < VL.size(); ++j) 2547 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 2548 Instruction *Term = dyn_cast<Instruction>( 2549 cast<PHINode>(VL[j])->getIncomingValueForBlock( 2550 PH->getIncomingBlock(i))); 2551 if (Term && Term->isTerminator()) { 2552 LLVM_DEBUG(dbgs() 2553 << "SLP: Need to swizzle PHINodes (terminator use).\n"); 2554 BS.cancelScheduling(VL, VL0); 2555 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2556 ReuseShuffleIndicies); 2557 return; 2558 } 2559 } 2560 2561 TreeEntry *TE = 2562 newTreeEntry(VL, Bundle, S, UserTreeIdx, ReuseShuffleIndicies); 2563 LLVM_DEBUG(dbgs() << "SLP: added a vector of PHINodes.\n"); 2564 2565 // Keeps the reordered operands to avoid code duplication. 2566 SmallVector<ValueList, 2> OperandsVec; 2567 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 2568 ValueList Operands; 2569 // Prepare the operand vector. 2570 for (Value *j : VL) 2571 Operands.push_back(cast<PHINode>(j)->getIncomingValueForBlock( 2572 PH->getIncomingBlock(i))); 2573 TE->setOperand(i, Operands); 2574 OperandsVec.push_back(Operands); 2575 } 2576 for (unsigned OpIdx = 0, OpE = OperandsVec.size(); OpIdx != OpE; ++OpIdx) 2577 buildTree_rec(OperandsVec[OpIdx], Depth + 1, {TE, OpIdx}); 2578 return; 2579 } 2580 case Instruction::ExtractValue: 2581 case Instruction::ExtractElement: { 2582 OrdersType CurrentOrder; 2583 bool Reuse = canReuseExtract(VL, VL0, CurrentOrder); 2584 if (Reuse) { 2585 LLVM_DEBUG(dbgs() << "SLP: Reusing or shuffling extract sequence.\n"); 2586 ++NumOpsWantToKeepOriginalOrder; 2587 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2588 ReuseShuffleIndicies); 2589 // This is a special case, as it does not gather, but at the same time 2590 // we are not extending buildTree_rec() towards the operands. 2591 ValueList Op0; 2592 Op0.assign(VL.size(), VL0->getOperand(0)); 2593 VectorizableTree.back()->setOperand(0, Op0); 2594 return; 2595 } 2596 if (!CurrentOrder.empty()) { 2597 LLVM_DEBUG({ 2598 dbgs() << "SLP: Reusing or shuffling of reordered extract sequence " 2599 "with order"; 2600 for (unsigned Idx : CurrentOrder) 2601 dbgs() << " " << Idx; 2602 dbgs() << "\n"; 2603 }); 2604 // Insert new order with initial value 0, if it does not exist, 2605 // otherwise return the iterator to the existing one. 2606 auto StoredCurrentOrderAndNum = 2607 NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first; 2608 ++StoredCurrentOrderAndNum->getSecond(); 2609 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2610 ReuseShuffleIndicies, 2611 StoredCurrentOrderAndNum->getFirst()); 2612 // This is a special case, as it does not gather, but at the same time 2613 // we are not extending buildTree_rec() towards the operands. 2614 ValueList Op0; 2615 Op0.assign(VL.size(), VL0->getOperand(0)); 2616 VectorizableTree.back()->setOperand(0, Op0); 2617 return; 2618 } 2619 LLVM_DEBUG(dbgs() << "SLP: Gather extract sequence.\n"); 2620 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2621 ReuseShuffleIndicies); 2622 BS.cancelScheduling(VL, VL0); 2623 return; 2624 } 2625 case Instruction::Load: { 2626 // Check that a vectorized load would load the same memory as a scalar 2627 // load. For example, we don't want to vectorize loads that are smaller 2628 // than 8-bit. Even though we have a packed struct {<i2, i2, i2, i2>} LLVM 2629 // treats loading/storing it as an i8 struct. If we vectorize loads/stores 2630 // from such a struct, we read/write packed bits disagreeing with the 2631 // unvectorized version. 2632 Type *ScalarTy = VL0->getType(); 2633 2634 if (DL->getTypeSizeInBits(ScalarTy) != 2635 DL->getTypeAllocSizeInBits(ScalarTy)) { 2636 BS.cancelScheduling(VL, VL0); 2637 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2638 ReuseShuffleIndicies); 2639 LLVM_DEBUG(dbgs() << "SLP: Gathering loads of non-packed type.\n"); 2640 return; 2641 } 2642 2643 // Make sure all loads in the bundle are simple - we can't vectorize 2644 // atomic or volatile loads. 2645 SmallVector<Value *, 4> PointerOps(VL.size()); 2646 auto POIter = PointerOps.begin(); 2647 for (Value *V : VL) { 2648 auto *L = cast<LoadInst>(V); 2649 if (!L->isSimple()) { 2650 BS.cancelScheduling(VL, VL0); 2651 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2652 ReuseShuffleIndicies); 2653 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple loads.\n"); 2654 return; 2655 } 2656 *POIter = L->getPointerOperand(); 2657 ++POIter; 2658 } 2659 2660 OrdersType CurrentOrder; 2661 // Check the order of pointer operands. 2662 if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) { 2663 Value *Ptr0; 2664 Value *PtrN; 2665 if (CurrentOrder.empty()) { 2666 Ptr0 = PointerOps.front(); 2667 PtrN = PointerOps.back(); 2668 } else { 2669 Ptr0 = PointerOps[CurrentOrder.front()]; 2670 PtrN = PointerOps[CurrentOrder.back()]; 2671 } 2672 const SCEV *Scev0 = SE->getSCEV(Ptr0); 2673 const SCEV *ScevN = SE->getSCEV(PtrN); 2674 const auto *Diff = 2675 dyn_cast<SCEVConstant>(SE->getMinusSCEV(ScevN, Scev0)); 2676 uint64_t Size = DL->getTypeAllocSize(ScalarTy); 2677 // Check that the sorted loads are consecutive. 2678 if (Diff && Diff->getAPInt() == (VL.size() - 1) * Size) { 2679 if (CurrentOrder.empty()) { 2680 // Original loads are consecutive and does not require reordering. 2681 ++NumOpsWantToKeepOriginalOrder; 2682 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, 2683 UserTreeIdx, ReuseShuffleIndicies); 2684 TE->setOperandsInOrder(); 2685 LLVM_DEBUG(dbgs() << "SLP: added a vector of loads.\n"); 2686 } else { 2687 // Need to reorder. 2688 auto I = NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first; 2689 ++I->getSecond(); 2690 TreeEntry *TE = 2691 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2692 ReuseShuffleIndicies, I->getFirst()); 2693 TE->setOperandsInOrder(); 2694 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled loads.\n"); 2695 } 2696 return; 2697 } 2698 } 2699 2700 LLVM_DEBUG(dbgs() << "SLP: Gathering non-consecutive loads.\n"); 2701 BS.cancelScheduling(VL, VL0); 2702 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2703 ReuseShuffleIndicies); 2704 return; 2705 } 2706 case Instruction::ZExt: 2707 case Instruction::SExt: 2708 case Instruction::FPToUI: 2709 case Instruction::FPToSI: 2710 case Instruction::FPExt: 2711 case Instruction::PtrToInt: 2712 case Instruction::IntToPtr: 2713 case Instruction::SIToFP: 2714 case Instruction::UIToFP: 2715 case Instruction::Trunc: 2716 case Instruction::FPTrunc: 2717 case Instruction::BitCast: { 2718 Type *SrcTy = VL0->getOperand(0)->getType(); 2719 for (Value *V : VL) { 2720 Type *Ty = cast<Instruction>(V)->getOperand(0)->getType(); 2721 if (Ty != SrcTy || !isValidElementType(Ty)) { 2722 BS.cancelScheduling(VL, VL0); 2723 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2724 ReuseShuffleIndicies); 2725 LLVM_DEBUG(dbgs() 2726 << "SLP: Gathering casts with different src types.\n"); 2727 return; 2728 } 2729 } 2730 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2731 ReuseShuffleIndicies); 2732 LLVM_DEBUG(dbgs() << "SLP: added a vector of casts.\n"); 2733 2734 TE->setOperandsInOrder(); 2735 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 2736 ValueList Operands; 2737 // Prepare the operand vector. 2738 for (Value *V : VL) 2739 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 2740 2741 buildTree_rec(Operands, Depth + 1, {TE, i}); 2742 } 2743 return; 2744 } 2745 case Instruction::ICmp: 2746 case Instruction::FCmp: { 2747 // Check that all of the compares have the same predicate. 2748 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 2749 CmpInst::Predicate SwapP0 = CmpInst::getSwappedPredicate(P0); 2750 Type *ComparedTy = VL0->getOperand(0)->getType(); 2751 for (Value *V : VL) { 2752 CmpInst *Cmp = cast<CmpInst>(V); 2753 if ((Cmp->getPredicate() != P0 && Cmp->getPredicate() != SwapP0) || 2754 Cmp->getOperand(0)->getType() != ComparedTy) { 2755 BS.cancelScheduling(VL, VL0); 2756 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2757 ReuseShuffleIndicies); 2758 LLVM_DEBUG(dbgs() 2759 << "SLP: Gathering cmp with different predicate.\n"); 2760 return; 2761 } 2762 } 2763 2764 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2765 ReuseShuffleIndicies); 2766 LLVM_DEBUG(dbgs() << "SLP: added a vector of compares.\n"); 2767 2768 ValueList Left, Right; 2769 if (cast<CmpInst>(VL0)->isCommutative()) { 2770 // Commutative predicate - collect + sort operands of the instructions 2771 // so that each side is more likely to have the same opcode. 2772 assert(P0 == SwapP0 && "Commutative Predicate mismatch"); 2773 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 2774 } else { 2775 // Collect operands - commute if it uses the swapped predicate. 2776 for (Value *V : VL) { 2777 auto *Cmp = cast<CmpInst>(V); 2778 Value *LHS = Cmp->getOperand(0); 2779 Value *RHS = Cmp->getOperand(1); 2780 if (Cmp->getPredicate() != P0) 2781 std::swap(LHS, RHS); 2782 Left.push_back(LHS); 2783 Right.push_back(RHS); 2784 } 2785 } 2786 TE->setOperand(0, Left); 2787 TE->setOperand(1, Right); 2788 buildTree_rec(Left, Depth + 1, {TE, 0}); 2789 buildTree_rec(Right, Depth + 1, {TE, 1}); 2790 return; 2791 } 2792 case Instruction::Select: 2793 case Instruction::FNeg: 2794 case Instruction::Add: 2795 case Instruction::FAdd: 2796 case Instruction::Sub: 2797 case Instruction::FSub: 2798 case Instruction::Mul: 2799 case Instruction::FMul: 2800 case Instruction::UDiv: 2801 case Instruction::SDiv: 2802 case Instruction::FDiv: 2803 case Instruction::URem: 2804 case Instruction::SRem: 2805 case Instruction::FRem: 2806 case Instruction::Shl: 2807 case Instruction::LShr: 2808 case Instruction::AShr: 2809 case Instruction::And: 2810 case Instruction::Or: 2811 case Instruction::Xor: { 2812 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2813 ReuseShuffleIndicies); 2814 LLVM_DEBUG(dbgs() << "SLP: added a vector of un/bin op.\n"); 2815 2816 // Sort operands of the instructions so that each side is more likely to 2817 // have the same opcode. 2818 if (isa<BinaryOperator>(VL0) && VL0->isCommutative()) { 2819 ValueList Left, Right; 2820 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 2821 TE->setOperand(0, Left); 2822 TE->setOperand(1, Right); 2823 buildTree_rec(Left, Depth + 1, {TE, 0}); 2824 buildTree_rec(Right, Depth + 1, {TE, 1}); 2825 return; 2826 } 2827 2828 TE->setOperandsInOrder(); 2829 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 2830 ValueList Operands; 2831 // Prepare the operand vector. 2832 for (Value *j : VL) 2833 Operands.push_back(cast<Instruction>(j)->getOperand(i)); 2834 2835 buildTree_rec(Operands, Depth + 1, {TE, i}); 2836 } 2837 return; 2838 } 2839 case Instruction::GetElementPtr: { 2840 // We don't combine GEPs with complicated (nested) indexing. 2841 for (Value *V : VL) { 2842 if (cast<Instruction>(V)->getNumOperands() != 2) { 2843 LLVM_DEBUG(dbgs() << "SLP: not-vectorizable GEP (nested indexes).\n"); 2844 BS.cancelScheduling(VL, VL0); 2845 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2846 ReuseShuffleIndicies); 2847 return; 2848 } 2849 } 2850 2851 // We can't combine several GEPs into one vector if they operate on 2852 // different types. 2853 Type *Ty0 = VL0->getOperand(0)->getType(); 2854 for (Value *V : VL) { 2855 Type *CurTy = cast<Instruction>(V)->getOperand(0)->getType(); 2856 if (Ty0 != CurTy) { 2857 LLVM_DEBUG(dbgs() 2858 << "SLP: not-vectorizable GEP (different types).\n"); 2859 BS.cancelScheduling(VL, VL0); 2860 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2861 ReuseShuffleIndicies); 2862 return; 2863 } 2864 } 2865 2866 // We don't combine GEPs with non-constant indexes. 2867 Type *Ty1 = VL0->getOperand(1)->getType(); 2868 for (Value *V : VL) { 2869 auto Op = cast<Instruction>(V)->getOperand(1); 2870 if (!isa<ConstantInt>(Op) || 2871 (Op->getType() != Ty1 && 2872 Op->getType()->getScalarSizeInBits() > 2873 DL->getIndexSizeInBits( 2874 V->getType()->getPointerAddressSpace()))) { 2875 LLVM_DEBUG(dbgs() 2876 << "SLP: not-vectorizable GEP (non-constant indexes).\n"); 2877 BS.cancelScheduling(VL, VL0); 2878 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2879 ReuseShuffleIndicies); 2880 return; 2881 } 2882 } 2883 2884 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2885 ReuseShuffleIndicies); 2886 LLVM_DEBUG(dbgs() << "SLP: added a vector of GEPs.\n"); 2887 TE->setOperandsInOrder(); 2888 for (unsigned i = 0, e = 2; i < e; ++i) { 2889 ValueList Operands; 2890 // Prepare the operand vector. 2891 for (Value *V : VL) 2892 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 2893 2894 buildTree_rec(Operands, Depth + 1, {TE, i}); 2895 } 2896 return; 2897 } 2898 case Instruction::Store: { 2899 // Check if the stores are consecutive or if we need to swizzle them. 2900 llvm::Type *ScalarTy = cast<StoreInst>(VL0)->getValueOperand()->getType(); 2901 // Make sure all stores in the bundle are simple - we can't vectorize 2902 // atomic or volatile stores. 2903 SmallVector<Value *, 4> PointerOps(VL.size()); 2904 ValueList Operands(VL.size()); 2905 auto POIter = PointerOps.begin(); 2906 auto OIter = Operands.begin(); 2907 for (Value *V : VL) { 2908 auto *SI = cast<StoreInst>(V); 2909 if (!SI->isSimple()) { 2910 BS.cancelScheduling(VL, VL0); 2911 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2912 ReuseShuffleIndicies); 2913 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple stores.\n"); 2914 return; 2915 } 2916 *POIter = SI->getPointerOperand(); 2917 *OIter = SI->getValueOperand(); 2918 ++POIter; 2919 ++OIter; 2920 } 2921 2922 OrdersType CurrentOrder; 2923 // Check the order of pointer operands. 2924 if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) { 2925 Value *Ptr0; 2926 Value *PtrN; 2927 if (CurrentOrder.empty()) { 2928 Ptr0 = PointerOps.front(); 2929 PtrN = PointerOps.back(); 2930 } else { 2931 Ptr0 = PointerOps[CurrentOrder.front()]; 2932 PtrN = PointerOps[CurrentOrder.back()]; 2933 } 2934 const SCEV *Scev0 = SE->getSCEV(Ptr0); 2935 const SCEV *ScevN = SE->getSCEV(PtrN); 2936 const auto *Diff = 2937 dyn_cast<SCEVConstant>(SE->getMinusSCEV(ScevN, Scev0)); 2938 uint64_t Size = DL->getTypeAllocSize(ScalarTy); 2939 // Check that the sorted pointer operands are consecutive. 2940 if (Diff && Diff->getAPInt() == (VL.size() - 1) * Size) { 2941 if (CurrentOrder.empty()) { 2942 // Original stores are consecutive and does not require reordering. 2943 ++NumOpsWantToKeepOriginalOrder; 2944 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, 2945 UserTreeIdx, ReuseShuffleIndicies); 2946 TE->setOperandsInOrder(); 2947 buildTree_rec(Operands, Depth + 1, {TE, 0}); 2948 LLVM_DEBUG(dbgs() << "SLP: added a vector of stores.\n"); 2949 } else { 2950 // Need to reorder. 2951 auto I = NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first; 2952 ++(I->getSecond()); 2953 TreeEntry *TE = 2954 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 2955 ReuseShuffleIndicies, I->getFirst()); 2956 TE->setOperandsInOrder(); 2957 buildTree_rec(Operands, Depth + 1, {TE, 0}); 2958 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled stores.\n"); 2959 } 2960 return; 2961 } 2962 } 2963 2964 BS.cancelScheduling(VL, VL0); 2965 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2966 ReuseShuffleIndicies); 2967 LLVM_DEBUG(dbgs() << "SLP: Non-consecutive store.\n"); 2968 return; 2969 } 2970 case Instruction::Call: { 2971 // Check if the calls are all to the same vectorizable intrinsic. 2972 CallInst *CI = cast<CallInst>(VL0); 2973 // Check if this is an Intrinsic call or something that can be 2974 // represented by an intrinsic call 2975 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 2976 if (!isTriviallyVectorizable(ID)) { 2977 BS.cancelScheduling(VL, VL0); 2978 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2979 ReuseShuffleIndicies); 2980 LLVM_DEBUG(dbgs() << "SLP: Non-vectorizable call.\n"); 2981 return; 2982 } 2983 Function *Int = CI->getCalledFunction(); 2984 unsigned NumArgs = CI->getNumArgOperands(); 2985 SmallVector<Value*, 4> ScalarArgs(NumArgs, nullptr); 2986 for (unsigned j = 0; j != NumArgs; ++j) 2987 if (hasVectorInstrinsicScalarOpd(ID, j)) 2988 ScalarArgs[j] = CI->getArgOperand(j); 2989 for (Value *V : VL) { 2990 CallInst *CI2 = dyn_cast<CallInst>(V); 2991 if (!CI2 || CI2->getCalledFunction() != Int || 2992 getVectorIntrinsicIDForCall(CI2, TLI) != ID || 2993 !CI->hasIdenticalOperandBundleSchema(*CI2)) { 2994 BS.cancelScheduling(VL, VL0); 2995 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 2996 ReuseShuffleIndicies); 2997 LLVM_DEBUG(dbgs() << "SLP: mismatched calls:" << *CI << "!=" << *V 2998 << "\n"); 2999 return; 3000 } 3001 // Some intrinsics have scalar arguments and should be same in order for 3002 // them to be vectorized. 3003 for (unsigned j = 0; j != NumArgs; ++j) { 3004 if (hasVectorInstrinsicScalarOpd(ID, j)) { 3005 Value *A1J = CI2->getArgOperand(j); 3006 if (ScalarArgs[j] != A1J) { 3007 BS.cancelScheduling(VL, VL0); 3008 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3009 ReuseShuffleIndicies); 3010 LLVM_DEBUG(dbgs() << "SLP: mismatched arguments in call:" << *CI 3011 << " argument " << ScalarArgs[j] << "!=" << A1J 3012 << "\n"); 3013 return; 3014 } 3015 } 3016 } 3017 // Verify that the bundle operands are identical between the two calls. 3018 if (CI->hasOperandBundles() && 3019 !std::equal(CI->op_begin() + CI->getBundleOperandsStartIndex(), 3020 CI->op_begin() + CI->getBundleOperandsEndIndex(), 3021 CI2->op_begin() + CI2->getBundleOperandsStartIndex())) { 3022 BS.cancelScheduling(VL, VL0); 3023 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3024 ReuseShuffleIndicies); 3025 LLVM_DEBUG(dbgs() << "SLP: mismatched bundle operands in calls:" 3026 << *CI << "!=" << *V << '\n'); 3027 return; 3028 } 3029 } 3030 3031 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3032 ReuseShuffleIndicies); 3033 TE->setOperandsInOrder(); 3034 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 3035 ValueList Operands; 3036 // Prepare the operand vector. 3037 for (Value *V : VL) { 3038 auto *CI2 = cast<CallInst>(V); 3039 Operands.push_back(CI2->getArgOperand(i)); 3040 } 3041 buildTree_rec(Operands, Depth + 1, {TE, i}); 3042 } 3043 return; 3044 } 3045 case Instruction::ShuffleVector: { 3046 // If this is not an alternate sequence of opcode like add-sub 3047 // then do not vectorize this instruction. 3048 if (!S.isAltShuffle()) { 3049 BS.cancelScheduling(VL, VL0); 3050 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3051 ReuseShuffleIndicies); 3052 LLVM_DEBUG(dbgs() << "SLP: ShuffleVector are not vectorized.\n"); 3053 return; 3054 } 3055 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, 3056 ReuseShuffleIndicies); 3057 LLVM_DEBUG(dbgs() << "SLP: added a ShuffleVector op.\n"); 3058 3059 // Reorder operands if reordering would enable vectorization. 3060 if (isa<BinaryOperator>(VL0)) { 3061 ValueList Left, Right; 3062 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); 3063 TE->setOperand(0, Left); 3064 TE->setOperand(1, Right); 3065 buildTree_rec(Left, Depth + 1, {TE, 0}); 3066 buildTree_rec(Right, Depth + 1, {TE, 1}); 3067 return; 3068 } 3069 3070 TE->setOperandsInOrder(); 3071 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 3072 ValueList Operands; 3073 // Prepare the operand vector. 3074 for (Value *V : VL) 3075 Operands.push_back(cast<Instruction>(V)->getOperand(i)); 3076 3077 buildTree_rec(Operands, Depth + 1, {TE, i}); 3078 } 3079 return; 3080 } 3081 default: 3082 BS.cancelScheduling(VL, VL0); 3083 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, 3084 ReuseShuffleIndicies); 3085 LLVM_DEBUG(dbgs() << "SLP: Gathering unknown instruction.\n"); 3086 return; 3087 } 3088 } 3089 3090 unsigned BoUpSLP::canMapToVector(Type *T, const DataLayout &DL) const { 3091 unsigned N; 3092 Type *EltTy; 3093 auto *ST = dyn_cast<StructType>(T); 3094 if (ST) { 3095 N = ST->getNumElements(); 3096 EltTy = *ST->element_begin(); 3097 } else { 3098 N = cast<ArrayType>(T)->getNumElements(); 3099 EltTy = cast<ArrayType>(T)->getElementType(); 3100 } 3101 3102 if (auto *VT = dyn_cast<VectorType>(EltTy)) { 3103 EltTy = VT->getElementType(); 3104 N *= VT->getNumElements(); 3105 } 3106 3107 if (!isValidElementType(EltTy)) 3108 return 0; 3109 uint64_t VTSize = DL.getTypeStoreSizeInBits(VectorType::get(EltTy, N)); 3110 if (VTSize < MinVecRegSize || VTSize > MaxVecRegSize || VTSize != DL.getTypeStoreSizeInBits(T)) 3111 return 0; 3112 if (ST) { 3113 // Check that struct is homogeneous. 3114 for (const auto *Ty : ST->elements()) 3115 if (Ty != *ST->element_begin()) 3116 return 0; 3117 } 3118 return N; 3119 } 3120 3121 bool BoUpSLP::canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, 3122 SmallVectorImpl<unsigned> &CurrentOrder) const { 3123 Instruction *E0 = cast<Instruction>(OpValue); 3124 assert(E0->getOpcode() == Instruction::ExtractElement || 3125 E0->getOpcode() == Instruction::ExtractValue); 3126 assert(E0->getOpcode() == getSameOpcode(VL).getOpcode() && "Invalid opcode"); 3127 // Check if all of the extracts come from the same vector and from the 3128 // correct offset. 3129 Value *Vec = E0->getOperand(0); 3130 3131 CurrentOrder.clear(); 3132 3133 // We have to extract from a vector/aggregate with the same number of elements. 3134 unsigned NElts; 3135 if (E0->getOpcode() == Instruction::ExtractValue) { 3136 const DataLayout &DL = E0->getModule()->getDataLayout(); 3137 NElts = canMapToVector(Vec->getType(), DL); 3138 if (!NElts) 3139 return false; 3140 // Check if load can be rewritten as load of vector. 3141 LoadInst *LI = dyn_cast<LoadInst>(Vec); 3142 if (!LI || !LI->isSimple() || !LI->hasNUses(VL.size())) 3143 return false; 3144 } else { 3145 NElts = Vec->getType()->getVectorNumElements(); 3146 } 3147 3148 if (NElts != VL.size()) 3149 return false; 3150 3151 // Check that all of the indices extract from the correct offset. 3152 bool ShouldKeepOrder = true; 3153 unsigned E = VL.size(); 3154 // Assign to all items the initial value E + 1 so we can check if the extract 3155 // instruction index was used already. 3156 // Also, later we can check that all the indices are used and we have a 3157 // consecutive access in the extract instructions, by checking that no 3158 // element of CurrentOrder still has value E + 1. 3159 CurrentOrder.assign(E, E + 1); 3160 unsigned I = 0; 3161 for (; I < E; ++I) { 3162 auto *Inst = cast<Instruction>(VL[I]); 3163 if (Inst->getOperand(0) != Vec) 3164 break; 3165 Optional<unsigned> Idx = getExtractIndex(Inst); 3166 if (!Idx) 3167 break; 3168 const unsigned ExtIdx = *Idx; 3169 if (ExtIdx != I) { 3170 if (ExtIdx >= E || CurrentOrder[ExtIdx] != E + 1) 3171 break; 3172 ShouldKeepOrder = false; 3173 CurrentOrder[ExtIdx] = I; 3174 } else { 3175 if (CurrentOrder[I] != E + 1) 3176 break; 3177 CurrentOrder[I] = I; 3178 } 3179 } 3180 if (I < E) { 3181 CurrentOrder.clear(); 3182 return false; 3183 } 3184 3185 return ShouldKeepOrder; 3186 } 3187 3188 bool BoUpSLP::areAllUsersVectorized(Instruction *I) const { 3189 return I->hasOneUse() || 3190 std::all_of(I->user_begin(), I->user_end(), [this](User *U) { 3191 return ScalarToTreeEntry.count(U) > 0; 3192 }); 3193 } 3194 3195 int BoUpSLP::getEntryCost(TreeEntry *E) { 3196 ArrayRef<Value*> VL = E->Scalars; 3197 3198 Type *ScalarTy = VL[0]->getType(); 3199 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 3200 ScalarTy = SI->getValueOperand()->getType(); 3201 else if (CmpInst *CI = dyn_cast<CmpInst>(VL[0])) 3202 ScalarTy = CI->getOperand(0)->getType(); 3203 VectorType *VecTy = VectorType::get(ScalarTy, VL.size()); 3204 3205 // If we have computed a smaller type for the expression, update VecTy so 3206 // that the costs will be accurate. 3207 if (MinBWs.count(VL[0])) 3208 VecTy = VectorType::get( 3209 IntegerType::get(F->getContext(), MinBWs[VL[0]].first), VL.size()); 3210 3211 unsigned ReuseShuffleNumbers = E->ReuseShuffleIndices.size(); 3212 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 3213 int ReuseShuffleCost = 0; 3214 if (NeedToShuffleReuses) { 3215 ReuseShuffleCost = 3216 TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3217 } 3218 if (E->NeedToGather) { 3219 if (allConstant(VL)) 3220 return 0; 3221 if (isSplat(VL)) { 3222 return ReuseShuffleCost + 3223 TTI->getShuffleCost(TargetTransformInfo::SK_Broadcast, VecTy, 0); 3224 } 3225 if (E->getOpcode() == Instruction::ExtractElement && 3226 allSameType(VL) && allSameBlock(VL)) { 3227 Optional<TargetTransformInfo::ShuffleKind> ShuffleKind = isShuffle(VL); 3228 if (ShuffleKind.hasValue()) { 3229 int Cost = TTI->getShuffleCost(ShuffleKind.getValue(), VecTy); 3230 for (auto *V : VL) { 3231 // If all users of instruction are going to be vectorized and this 3232 // instruction itself is not going to be vectorized, consider this 3233 // instruction as dead and remove its cost from the final cost of the 3234 // vectorized tree. 3235 if (areAllUsersVectorized(cast<Instruction>(V)) && 3236 !ScalarToTreeEntry.count(V)) { 3237 auto *IO = cast<ConstantInt>( 3238 cast<ExtractElementInst>(V)->getIndexOperand()); 3239 Cost -= TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, 3240 IO->getZExtValue()); 3241 } 3242 } 3243 return ReuseShuffleCost + Cost; 3244 } 3245 } 3246 return ReuseShuffleCost + getGatherCost(VL); 3247 } 3248 assert(E->getOpcode() && allSameType(VL) && allSameBlock(VL) && "Invalid VL"); 3249 Instruction *VL0 = E->getMainOp(); 3250 unsigned ShuffleOrOp = 3251 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 3252 switch (ShuffleOrOp) { 3253 case Instruction::PHI: 3254 return 0; 3255 3256 case Instruction::ExtractValue: 3257 case Instruction::ExtractElement: 3258 if (NeedToShuffleReuses) { 3259 unsigned Idx = 0; 3260 for (unsigned I : E->ReuseShuffleIndices) { 3261 if (ShuffleOrOp == Instruction::ExtractElement) { 3262 auto *IO = cast<ConstantInt>( 3263 cast<ExtractElementInst>(VL[I])->getIndexOperand()); 3264 Idx = IO->getZExtValue(); 3265 ReuseShuffleCost -= TTI->getVectorInstrCost( 3266 Instruction::ExtractElement, VecTy, Idx); 3267 } else { 3268 ReuseShuffleCost -= TTI->getVectorInstrCost( 3269 Instruction::ExtractElement, VecTy, Idx); 3270 ++Idx; 3271 } 3272 } 3273 Idx = ReuseShuffleNumbers; 3274 for (Value *V : VL) { 3275 if (ShuffleOrOp == Instruction::ExtractElement) { 3276 auto *IO = cast<ConstantInt>( 3277 cast<ExtractElementInst>(V)->getIndexOperand()); 3278 Idx = IO->getZExtValue(); 3279 } else { 3280 --Idx; 3281 } 3282 ReuseShuffleCost += 3283 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, Idx); 3284 } 3285 } 3286 if (!E->NeedToGather) { 3287 int DeadCost = ReuseShuffleCost; 3288 if (!E->ReorderIndices.empty()) { 3289 // TODO: Merge this shuffle with the ReuseShuffleCost. 3290 DeadCost += TTI->getShuffleCost( 3291 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3292 } 3293 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 3294 Instruction *E = cast<Instruction>(VL[i]); 3295 // If all users are going to be vectorized, instruction can be 3296 // considered as dead. 3297 // The same, if have only one user, it will be vectorized for sure. 3298 if (areAllUsersVectorized(E)) { 3299 // Take credit for instruction that will become dead. 3300 if (E->hasOneUse()) { 3301 Instruction *Ext = E->user_back(); 3302 if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) && 3303 all_of(Ext->users(), 3304 [](User *U) { return isa<GetElementPtrInst>(U); })) { 3305 // Use getExtractWithExtendCost() to calculate the cost of 3306 // extractelement/ext pair. 3307 DeadCost -= TTI->getExtractWithExtendCost( 3308 Ext->getOpcode(), Ext->getType(), VecTy, i); 3309 // Add back the cost of s|zext which is subtracted separately. 3310 DeadCost += TTI->getCastInstrCost( 3311 Ext->getOpcode(), Ext->getType(), E->getType(), Ext); 3312 continue; 3313 } 3314 } 3315 DeadCost -= 3316 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, i); 3317 } 3318 } 3319 return DeadCost; 3320 } 3321 return ReuseShuffleCost + getGatherCost(VL); 3322 3323 case Instruction::ZExt: 3324 case Instruction::SExt: 3325 case Instruction::FPToUI: 3326 case Instruction::FPToSI: 3327 case Instruction::FPExt: 3328 case Instruction::PtrToInt: 3329 case Instruction::IntToPtr: 3330 case Instruction::SIToFP: 3331 case Instruction::UIToFP: 3332 case Instruction::Trunc: 3333 case Instruction::FPTrunc: 3334 case Instruction::BitCast: { 3335 Type *SrcTy = VL0->getOperand(0)->getType(); 3336 int ScalarEltCost = 3337 TTI->getCastInstrCost(E->getOpcode(), ScalarTy, SrcTy, VL0); 3338 if (NeedToShuffleReuses) { 3339 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3340 } 3341 3342 // Calculate the cost of this instruction. 3343 int ScalarCost = VL.size() * ScalarEltCost; 3344 3345 VectorType *SrcVecTy = VectorType::get(SrcTy, VL.size()); 3346 int VecCost = 0; 3347 // Check if the values are candidates to demote. 3348 if (!MinBWs.count(VL0) || VecTy != SrcVecTy) { 3349 VecCost = ReuseShuffleCost + 3350 TTI->getCastInstrCost(E->getOpcode(), VecTy, SrcVecTy, VL0); 3351 } 3352 return VecCost - ScalarCost; 3353 } 3354 case Instruction::FCmp: 3355 case Instruction::ICmp: 3356 case Instruction::Select: { 3357 // Calculate the cost of this instruction. 3358 int ScalarEltCost = TTI->getCmpSelInstrCost(E->getOpcode(), ScalarTy, 3359 Builder.getInt1Ty(), VL0); 3360 if (NeedToShuffleReuses) { 3361 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3362 } 3363 VectorType *MaskTy = VectorType::get(Builder.getInt1Ty(), VL.size()); 3364 int ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3365 int VecCost = TTI->getCmpSelInstrCost(E->getOpcode(), VecTy, MaskTy, VL0); 3366 return ReuseShuffleCost + VecCost - ScalarCost; 3367 } 3368 case Instruction::FNeg: 3369 case Instruction::Add: 3370 case Instruction::FAdd: 3371 case Instruction::Sub: 3372 case Instruction::FSub: 3373 case Instruction::Mul: 3374 case Instruction::FMul: 3375 case Instruction::UDiv: 3376 case Instruction::SDiv: 3377 case Instruction::FDiv: 3378 case Instruction::URem: 3379 case Instruction::SRem: 3380 case Instruction::FRem: 3381 case Instruction::Shl: 3382 case Instruction::LShr: 3383 case Instruction::AShr: 3384 case Instruction::And: 3385 case Instruction::Or: 3386 case Instruction::Xor: { 3387 // Certain instructions can be cheaper to vectorize if they have a 3388 // constant second vector operand. 3389 TargetTransformInfo::OperandValueKind Op1VK = 3390 TargetTransformInfo::OK_AnyValue; 3391 TargetTransformInfo::OperandValueKind Op2VK = 3392 TargetTransformInfo::OK_UniformConstantValue; 3393 TargetTransformInfo::OperandValueProperties Op1VP = 3394 TargetTransformInfo::OP_None; 3395 TargetTransformInfo::OperandValueProperties Op2VP = 3396 TargetTransformInfo::OP_PowerOf2; 3397 3398 // If all operands are exactly the same ConstantInt then set the 3399 // operand kind to OK_UniformConstantValue. 3400 // If instead not all operands are constants, then set the operand kind 3401 // to OK_AnyValue. If all operands are constants but not the same, 3402 // then set the operand kind to OK_NonUniformConstantValue. 3403 ConstantInt *CInt0 = nullptr; 3404 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 3405 const Instruction *I = cast<Instruction>(VL[i]); 3406 unsigned OpIdx = isa<BinaryOperator>(I) ? 1 : 0; 3407 ConstantInt *CInt = dyn_cast<ConstantInt>(I->getOperand(OpIdx)); 3408 if (!CInt) { 3409 Op2VK = TargetTransformInfo::OK_AnyValue; 3410 Op2VP = TargetTransformInfo::OP_None; 3411 break; 3412 } 3413 if (Op2VP == TargetTransformInfo::OP_PowerOf2 && 3414 !CInt->getValue().isPowerOf2()) 3415 Op2VP = TargetTransformInfo::OP_None; 3416 if (i == 0) { 3417 CInt0 = CInt; 3418 continue; 3419 } 3420 if (CInt0 != CInt) 3421 Op2VK = TargetTransformInfo::OK_NonUniformConstantValue; 3422 } 3423 3424 SmallVector<const Value *, 4> Operands(VL0->operand_values()); 3425 int ScalarEltCost = TTI->getArithmeticInstrCost( 3426 E->getOpcode(), ScalarTy, Op1VK, Op2VK, Op1VP, Op2VP, Operands); 3427 if (NeedToShuffleReuses) { 3428 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3429 } 3430 int ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3431 int VecCost = TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, Op1VK, 3432 Op2VK, Op1VP, Op2VP, Operands); 3433 return ReuseShuffleCost + VecCost - ScalarCost; 3434 } 3435 case Instruction::GetElementPtr: { 3436 TargetTransformInfo::OperandValueKind Op1VK = 3437 TargetTransformInfo::OK_AnyValue; 3438 TargetTransformInfo::OperandValueKind Op2VK = 3439 TargetTransformInfo::OK_UniformConstantValue; 3440 3441 int ScalarEltCost = 3442 TTI->getArithmeticInstrCost(Instruction::Add, ScalarTy, Op1VK, Op2VK); 3443 if (NeedToShuffleReuses) { 3444 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3445 } 3446 int ScalarCost = VecTy->getNumElements() * ScalarEltCost; 3447 int VecCost = 3448 TTI->getArithmeticInstrCost(Instruction::Add, VecTy, Op1VK, Op2VK); 3449 return ReuseShuffleCost + VecCost - ScalarCost; 3450 } 3451 case Instruction::Load: { 3452 // Cost of wide load - cost of scalar loads. 3453 MaybeAlign alignment(cast<LoadInst>(VL0)->getAlignment()); 3454 int ScalarEltCost = 3455 TTI->getMemoryOpCost(Instruction::Load, ScalarTy, alignment, 0, VL0); 3456 if (NeedToShuffleReuses) { 3457 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3458 } 3459 int ScalarLdCost = VecTy->getNumElements() * ScalarEltCost; 3460 int VecLdCost = 3461 TTI->getMemoryOpCost(Instruction::Load, VecTy, alignment, 0, VL0); 3462 if (!E->ReorderIndices.empty()) { 3463 // TODO: Merge this shuffle with the ReuseShuffleCost. 3464 VecLdCost += TTI->getShuffleCost( 3465 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3466 } 3467 return ReuseShuffleCost + VecLdCost - ScalarLdCost; 3468 } 3469 case Instruction::Store: { 3470 // We know that we can merge the stores. Calculate the cost. 3471 bool IsReorder = !E->ReorderIndices.empty(); 3472 auto *SI = 3473 cast<StoreInst>(IsReorder ? VL[E->ReorderIndices.front()] : VL0); 3474 MaybeAlign Alignment(SI->getAlignment()); 3475 int ScalarEltCost = 3476 TTI->getMemoryOpCost(Instruction::Store, ScalarTy, Alignment, 0, VL0); 3477 if (NeedToShuffleReuses) 3478 ReuseShuffleCost = -(ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3479 int ScalarStCost = VecTy->getNumElements() * ScalarEltCost; 3480 int VecStCost = TTI->getMemoryOpCost(Instruction::Store, 3481 VecTy, Alignment, 0, VL0); 3482 if (IsReorder) { 3483 // TODO: Merge this shuffle with the ReuseShuffleCost. 3484 VecStCost += TTI->getShuffleCost( 3485 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 3486 } 3487 return ReuseShuffleCost + VecStCost - ScalarStCost; 3488 } 3489 case Instruction::Call: { 3490 CallInst *CI = cast<CallInst>(VL0); 3491 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3492 3493 // Calculate the cost of the scalar and vector calls. 3494 SmallVector<Type *, 4> ScalarTys; 3495 for (unsigned op = 0, opc = CI->getNumArgOperands(); op != opc; ++op) 3496 ScalarTys.push_back(CI->getArgOperand(op)->getType()); 3497 3498 FastMathFlags FMF; 3499 if (auto *FPMO = dyn_cast<FPMathOperator>(CI)) 3500 FMF = FPMO->getFastMathFlags(); 3501 3502 int ScalarEltCost = 3503 TTI->getIntrinsicInstrCost(ID, ScalarTy, ScalarTys, FMF); 3504 if (NeedToShuffleReuses) { 3505 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost; 3506 } 3507 int ScalarCallCost = VecTy->getNumElements() * ScalarEltCost; 3508 3509 SmallVector<Value *, 4> Args(CI->arg_operands()); 3510 int VecCallCost = TTI->getIntrinsicInstrCost(ID, CI->getType(), Args, FMF, 3511 VecTy->getNumElements()); 3512 3513 LLVM_DEBUG(dbgs() << "SLP: Call cost " << VecCallCost - ScalarCallCost 3514 << " (" << VecCallCost << "-" << ScalarCallCost << ")" 3515 << " for " << *CI << "\n"); 3516 3517 return ReuseShuffleCost + VecCallCost - ScalarCallCost; 3518 } 3519 case Instruction::ShuffleVector: { 3520 assert(E->isAltShuffle() && 3521 ((Instruction::isBinaryOp(E->getOpcode()) && 3522 Instruction::isBinaryOp(E->getAltOpcode())) || 3523 (Instruction::isCast(E->getOpcode()) && 3524 Instruction::isCast(E->getAltOpcode()))) && 3525 "Invalid Shuffle Vector Operand"); 3526 int ScalarCost = 0; 3527 if (NeedToShuffleReuses) { 3528 for (unsigned Idx : E->ReuseShuffleIndices) { 3529 Instruction *I = cast<Instruction>(VL[Idx]); 3530 ReuseShuffleCost -= TTI->getInstructionCost( 3531 I, TargetTransformInfo::TCK_RecipThroughput); 3532 } 3533 for (Value *V : VL) { 3534 Instruction *I = cast<Instruction>(V); 3535 ReuseShuffleCost += TTI->getInstructionCost( 3536 I, TargetTransformInfo::TCK_RecipThroughput); 3537 } 3538 } 3539 for (Value *V : VL) { 3540 Instruction *I = cast<Instruction>(V); 3541 assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode"); 3542 ScalarCost += TTI->getInstructionCost( 3543 I, TargetTransformInfo::TCK_RecipThroughput); 3544 } 3545 // VecCost is equal to sum of the cost of creating 2 vectors 3546 // and the cost of creating shuffle. 3547 int VecCost = 0; 3548 if (Instruction::isBinaryOp(E->getOpcode())) { 3549 VecCost = TTI->getArithmeticInstrCost(E->getOpcode(), VecTy); 3550 VecCost += TTI->getArithmeticInstrCost(E->getAltOpcode(), VecTy); 3551 } else { 3552 Type *Src0SclTy = E->getMainOp()->getOperand(0)->getType(); 3553 Type *Src1SclTy = E->getAltOp()->getOperand(0)->getType(); 3554 VectorType *Src0Ty = VectorType::get(Src0SclTy, VL.size()); 3555 VectorType *Src1Ty = VectorType::get(Src1SclTy, VL.size()); 3556 VecCost = TTI->getCastInstrCost(E->getOpcode(), VecTy, Src0Ty); 3557 VecCost += TTI->getCastInstrCost(E->getAltOpcode(), VecTy, Src1Ty); 3558 } 3559 VecCost += TTI->getShuffleCost(TargetTransformInfo::SK_Select, VecTy, 0); 3560 return ReuseShuffleCost + VecCost - ScalarCost; 3561 } 3562 default: 3563 llvm_unreachable("Unknown instruction"); 3564 } 3565 } 3566 3567 bool BoUpSLP::isFullyVectorizableTinyTree() const { 3568 LLVM_DEBUG(dbgs() << "SLP: Check whether the tree with height " 3569 << VectorizableTree.size() << " is fully vectorizable .\n"); 3570 3571 // We only handle trees of heights 1 and 2. 3572 if (VectorizableTree.size() == 1 && !VectorizableTree[0]->NeedToGather) 3573 return true; 3574 3575 if (VectorizableTree.size() != 2) 3576 return false; 3577 3578 // Handle splat and all-constants stores. 3579 if (!VectorizableTree[0]->NeedToGather && 3580 (allConstant(VectorizableTree[1]->Scalars) || 3581 isSplat(VectorizableTree[1]->Scalars))) 3582 return true; 3583 3584 // Gathering cost would be too much for tiny trees. 3585 if (VectorizableTree[0]->NeedToGather || VectorizableTree[1]->NeedToGather) 3586 return false; 3587 3588 return true; 3589 } 3590 3591 bool BoUpSLP::isLoadCombineReductionCandidate(unsigned RdxOpcode) const { 3592 if (RdxOpcode != Instruction::Or) 3593 return false; 3594 3595 unsigned NumElts = VectorizableTree[0]->Scalars.size(); 3596 Value *FirstReduced = VectorizableTree[0]->Scalars[0]; 3597 3598 // Look past the reduction to find a source value. Arbitrarily follow the 3599 // path through operand 0 of any 'or'. Also, peek through optional 3600 // shift-left-by-constant. 3601 Value *ZextLoad = FirstReduced; 3602 while (match(ZextLoad, m_Or(m_Value(), m_Value())) || 3603 match(ZextLoad, m_Shl(m_Value(), m_Constant()))) 3604 ZextLoad = cast<BinaryOperator>(ZextLoad)->getOperand(0); 3605 3606 // Check if the input to the reduction is an extended load. 3607 Value *LoadPtr; 3608 if (!match(ZextLoad, m_ZExt(m_Load(m_Value(LoadPtr))))) 3609 return false; 3610 3611 // Require that the total load bit width is a legal integer type. 3612 // For example, <8 x i8> --> i64 is a legal integer on a 64-bit target. 3613 // But <16 x i8> --> i128 is not, so the backend probably can't reduce it. 3614 Type *SrcTy = LoadPtr->getType()->getPointerElementType(); 3615 unsigned LoadBitWidth = SrcTy->getIntegerBitWidth() * NumElts; 3616 LLVMContext &Context = FirstReduced->getContext(); 3617 if (!TTI->isTypeLegal(IntegerType::get(Context, LoadBitWidth))) 3618 return false; 3619 3620 // Everything matched - assume that we can fold the whole sequence using 3621 // load combining. 3622 LLVM_DEBUG(dbgs() << "SLP: Assume load combining for scalar reduction of " 3623 << *(cast<Instruction>(FirstReduced)) << "\n"); 3624 3625 return true; 3626 } 3627 3628 bool BoUpSLP::isTreeTinyAndNotFullyVectorizable() const { 3629 // We can vectorize the tree if its size is greater than or equal to the 3630 // minimum size specified by the MinTreeSize command line option. 3631 if (VectorizableTree.size() >= MinTreeSize) 3632 return false; 3633 3634 // If we have a tiny tree (a tree whose size is less than MinTreeSize), we 3635 // can vectorize it if we can prove it fully vectorizable. 3636 if (isFullyVectorizableTinyTree()) 3637 return false; 3638 3639 assert(VectorizableTree.empty() 3640 ? ExternalUses.empty() 3641 : true && "We shouldn't have any external users"); 3642 3643 // Otherwise, we can't vectorize the tree. It is both tiny and not fully 3644 // vectorizable. 3645 return true; 3646 } 3647 3648 int BoUpSLP::getSpillCost() const { 3649 // Walk from the bottom of the tree to the top, tracking which values are 3650 // live. When we see a call instruction that is not part of our tree, 3651 // query TTI to see if there is a cost to keeping values live over it 3652 // (for example, if spills and fills are required). 3653 unsigned BundleWidth = VectorizableTree.front()->Scalars.size(); 3654 int Cost = 0; 3655 3656 SmallPtrSet<Instruction*, 4> LiveValues; 3657 Instruction *PrevInst = nullptr; 3658 3659 for (const auto &TEPtr : VectorizableTree) { 3660 Instruction *Inst = dyn_cast<Instruction>(TEPtr->Scalars[0]); 3661 if (!Inst) 3662 continue; 3663 3664 if (!PrevInst) { 3665 PrevInst = Inst; 3666 continue; 3667 } 3668 3669 // Update LiveValues. 3670 LiveValues.erase(PrevInst); 3671 for (auto &J : PrevInst->operands()) { 3672 if (isa<Instruction>(&*J) && getTreeEntry(&*J)) 3673 LiveValues.insert(cast<Instruction>(&*J)); 3674 } 3675 3676 LLVM_DEBUG({ 3677 dbgs() << "SLP: #LV: " << LiveValues.size(); 3678 for (auto *X : LiveValues) 3679 dbgs() << " " << X->getName(); 3680 dbgs() << ", Looking at "; 3681 Inst->dump(); 3682 }); 3683 3684 // Now find the sequence of instructions between PrevInst and Inst. 3685 unsigned NumCalls = 0; 3686 BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(), 3687 PrevInstIt = 3688 PrevInst->getIterator().getReverse(); 3689 while (InstIt != PrevInstIt) { 3690 if (PrevInstIt == PrevInst->getParent()->rend()) { 3691 PrevInstIt = Inst->getParent()->rbegin(); 3692 continue; 3693 } 3694 3695 // Debug information does not impact spill cost. 3696 if ((isa<CallInst>(&*PrevInstIt) && 3697 !isa<DbgInfoIntrinsic>(&*PrevInstIt)) && 3698 &*PrevInstIt != PrevInst) 3699 NumCalls++; 3700 3701 ++PrevInstIt; 3702 } 3703 3704 if (NumCalls) { 3705 SmallVector<Type*, 4> V; 3706 for (auto *II : LiveValues) 3707 V.push_back(VectorType::get(II->getType(), BundleWidth)); 3708 Cost += NumCalls * TTI->getCostOfKeepingLiveOverCall(V); 3709 } 3710 3711 PrevInst = Inst; 3712 } 3713 3714 return Cost; 3715 } 3716 3717 int BoUpSLP::getTreeCost() { 3718 int Cost = 0; 3719 LLVM_DEBUG(dbgs() << "SLP: Calculating cost for tree of size " 3720 << VectorizableTree.size() << ".\n"); 3721 3722 unsigned BundleWidth = VectorizableTree[0]->Scalars.size(); 3723 3724 for (unsigned I = 0, E = VectorizableTree.size(); I < E; ++I) { 3725 TreeEntry &TE = *VectorizableTree[I].get(); 3726 3727 // We create duplicate tree entries for gather sequences that have multiple 3728 // uses. However, we should not compute the cost of duplicate sequences. 3729 // For example, if we have a build vector (i.e., insertelement sequence) 3730 // that is used by more than one vector instruction, we only need to 3731 // compute the cost of the insertelement instructions once. The redundant 3732 // instructions will be eliminated by CSE. 3733 // 3734 // We should consider not creating duplicate tree entries for gather 3735 // sequences, and instead add additional edges to the tree representing 3736 // their uses. Since such an approach results in fewer total entries, 3737 // existing heuristics based on tree size may yield different results. 3738 // 3739 if (TE.NeedToGather && 3740 std::any_of( 3741 std::next(VectorizableTree.begin(), I + 1), VectorizableTree.end(), 3742 [TE](const std::unique_ptr<TreeEntry> &EntryPtr) { 3743 return EntryPtr->NeedToGather && EntryPtr->isSame(TE.Scalars); 3744 })) 3745 continue; 3746 3747 int C = getEntryCost(&TE); 3748 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C 3749 << " for bundle that starts with " << *TE.Scalars[0] 3750 << ".\n"); 3751 Cost += C; 3752 } 3753 3754 SmallPtrSet<Value *, 16> ExtractCostCalculated; 3755 int ExtractCost = 0; 3756 for (ExternalUser &EU : ExternalUses) { 3757 // We only add extract cost once for the same scalar. 3758 if (!ExtractCostCalculated.insert(EU.Scalar).second) 3759 continue; 3760 3761 // Uses by ephemeral values are free (because the ephemeral value will be 3762 // removed prior to code generation, and so the extraction will be 3763 // removed as well). 3764 if (EphValues.count(EU.User)) 3765 continue; 3766 3767 // If we plan to rewrite the tree in a smaller type, we will need to sign 3768 // extend the extracted value back to the original type. Here, we account 3769 // for the extract and the added cost of the sign extend if needed. 3770 auto *VecTy = VectorType::get(EU.Scalar->getType(), BundleWidth); 3771 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 3772 if (MinBWs.count(ScalarRoot)) { 3773 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 3774 auto Extend = 3775 MinBWs[ScalarRoot].second ? Instruction::SExt : Instruction::ZExt; 3776 VecTy = VectorType::get(MinTy, BundleWidth); 3777 ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(), 3778 VecTy, EU.Lane); 3779 } else { 3780 ExtractCost += 3781 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, EU.Lane); 3782 } 3783 } 3784 3785 int SpillCost = getSpillCost(); 3786 Cost += SpillCost + ExtractCost; 3787 3788 std::string Str; 3789 { 3790 raw_string_ostream OS(Str); 3791 OS << "SLP: Spill Cost = " << SpillCost << ".\n" 3792 << "SLP: Extract Cost = " << ExtractCost << ".\n" 3793 << "SLP: Total Cost = " << Cost << ".\n"; 3794 } 3795 LLVM_DEBUG(dbgs() << Str); 3796 3797 if (ViewSLPTree) 3798 ViewGraph(this, "SLP" + F->getName(), false, Str); 3799 3800 return Cost; 3801 } 3802 3803 int BoUpSLP::getGatherCost(Type *Ty, 3804 const DenseSet<unsigned> &ShuffledIndices) const { 3805 int Cost = 0; 3806 for (unsigned i = 0, e = cast<VectorType>(Ty)->getNumElements(); i < e; ++i) 3807 if (!ShuffledIndices.count(i)) 3808 Cost += TTI->getVectorInstrCost(Instruction::InsertElement, Ty, i); 3809 if (!ShuffledIndices.empty()) 3810 Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, Ty); 3811 return Cost; 3812 } 3813 3814 int BoUpSLP::getGatherCost(ArrayRef<Value *> VL) const { 3815 // Find the type of the operands in VL. 3816 Type *ScalarTy = VL[0]->getType(); 3817 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 3818 ScalarTy = SI->getValueOperand()->getType(); 3819 VectorType *VecTy = VectorType::get(ScalarTy, VL.size()); 3820 // Find the cost of inserting/extracting values from the vector. 3821 // Check if the same elements are inserted several times and count them as 3822 // shuffle candidates. 3823 DenseSet<unsigned> ShuffledElements; 3824 DenseSet<Value *> UniqueElements; 3825 // Iterate in reverse order to consider insert elements with the high cost. 3826 for (unsigned I = VL.size(); I > 0; --I) { 3827 unsigned Idx = I - 1; 3828 if (!UniqueElements.insert(VL[Idx]).second) 3829 ShuffledElements.insert(Idx); 3830 } 3831 return getGatherCost(VecTy, ShuffledElements); 3832 } 3833 3834 // Perform operand reordering on the instructions in VL and return the reordered 3835 // operands in Left and Right. 3836 void BoUpSLP::reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, 3837 SmallVectorImpl<Value *> &Left, 3838 SmallVectorImpl<Value *> &Right, 3839 const DataLayout &DL, 3840 ScalarEvolution &SE, 3841 const BoUpSLP &R) { 3842 if (VL.empty()) 3843 return; 3844 VLOperands Ops(VL, DL, SE, R); 3845 // Reorder the operands in place. 3846 Ops.reorder(); 3847 Left = Ops.getVL(0); 3848 Right = Ops.getVL(1); 3849 } 3850 3851 void BoUpSLP::setInsertPointAfterBundle(TreeEntry *E) { 3852 // Get the basic block this bundle is in. All instructions in the bundle 3853 // should be in this block. 3854 auto *Front = E->getMainOp(); 3855 auto *BB = Front->getParent(); 3856 assert(llvm::all_of(make_range(E->Scalars.begin(), E->Scalars.end()), 3857 [=](Value *V) -> bool { 3858 auto *I = cast<Instruction>(V); 3859 return !E->isOpcodeOrAlt(I) || I->getParent() == BB; 3860 })); 3861 3862 // The last instruction in the bundle in program order. 3863 Instruction *LastInst = nullptr; 3864 3865 // Find the last instruction. The common case should be that BB has been 3866 // scheduled, and the last instruction is VL.back(). So we start with 3867 // VL.back() and iterate over schedule data until we reach the end of the 3868 // bundle. The end of the bundle is marked by null ScheduleData. 3869 if (BlocksSchedules.count(BB)) { 3870 auto *Bundle = 3871 BlocksSchedules[BB]->getScheduleData(E->isOneOf(E->Scalars.back())); 3872 if (Bundle && Bundle->isPartOfBundle()) 3873 for (; Bundle; Bundle = Bundle->NextInBundle) 3874 if (Bundle->OpValue == Bundle->Inst) 3875 LastInst = Bundle->Inst; 3876 } 3877 3878 // LastInst can still be null at this point if there's either not an entry 3879 // for BB in BlocksSchedules or there's no ScheduleData available for 3880 // VL.back(). This can be the case if buildTree_rec aborts for various 3881 // reasons (e.g., the maximum recursion depth is reached, the maximum region 3882 // size is reached, etc.). ScheduleData is initialized in the scheduling 3883 // "dry-run". 3884 // 3885 // If this happens, we can still find the last instruction by brute force. We 3886 // iterate forwards from Front (inclusive) until we either see all 3887 // instructions in the bundle or reach the end of the block. If Front is the 3888 // last instruction in program order, LastInst will be set to Front, and we 3889 // will visit all the remaining instructions in the block. 3890 // 3891 // One of the reasons we exit early from buildTree_rec is to place an upper 3892 // bound on compile-time. Thus, taking an additional compile-time hit here is 3893 // not ideal. However, this should be exceedingly rare since it requires that 3894 // we both exit early from buildTree_rec and that the bundle be out-of-order 3895 // (causing us to iterate all the way to the end of the block). 3896 if (!LastInst) { 3897 SmallPtrSet<Value *, 16> Bundle(E->Scalars.begin(), E->Scalars.end()); 3898 for (auto &I : make_range(BasicBlock::iterator(Front), BB->end())) { 3899 if (Bundle.erase(&I) && E->isOpcodeOrAlt(&I)) 3900 LastInst = &I; 3901 if (Bundle.empty()) 3902 break; 3903 } 3904 } 3905 assert(LastInst && "Failed to find last instruction in bundle"); 3906 3907 // Set the insertion point after the last instruction in the bundle. Set the 3908 // debug location to Front. 3909 Builder.SetInsertPoint(BB, ++LastInst->getIterator()); 3910 Builder.SetCurrentDebugLocation(Front->getDebugLoc()); 3911 } 3912 3913 Value *BoUpSLP::Gather(ArrayRef<Value *> VL, VectorType *Ty) { 3914 Value *Vec = UndefValue::get(Ty); 3915 // Generate the 'InsertElement' instruction. 3916 for (unsigned i = 0; i < Ty->getNumElements(); ++i) { 3917 Vec = Builder.CreateInsertElement(Vec, VL[i], Builder.getInt32(i)); 3918 if (auto *Insrt = dyn_cast<InsertElementInst>(Vec)) { 3919 GatherSeq.insert(Insrt); 3920 CSEBlocks.insert(Insrt->getParent()); 3921 3922 // Add to our 'need-to-extract' list. 3923 if (TreeEntry *E = getTreeEntry(VL[i])) { 3924 // Find which lane we need to extract. 3925 int FoundLane = -1; 3926 for (unsigned Lane = 0, LE = E->Scalars.size(); Lane != LE; ++Lane) { 3927 // Is this the lane of the scalar that we are looking for ? 3928 if (E->Scalars[Lane] == VL[i]) { 3929 FoundLane = Lane; 3930 break; 3931 } 3932 } 3933 assert(FoundLane >= 0 && "Could not find the correct lane"); 3934 if (!E->ReuseShuffleIndices.empty()) { 3935 FoundLane = 3936 std::distance(E->ReuseShuffleIndices.begin(), 3937 llvm::find(E->ReuseShuffleIndices, FoundLane)); 3938 } 3939 ExternalUses.push_back(ExternalUser(VL[i], Insrt, FoundLane)); 3940 } 3941 } 3942 } 3943 3944 return Vec; 3945 } 3946 3947 Value *BoUpSLP::vectorizeTree(ArrayRef<Value *> VL) { 3948 InstructionsState S = getSameOpcode(VL); 3949 if (S.getOpcode()) { 3950 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 3951 if (E->isSame(VL)) { 3952 Value *V = vectorizeTree(E); 3953 if (VL.size() == E->Scalars.size() && !E->ReuseShuffleIndices.empty()) { 3954 // We need to get the vectorized value but without shuffle. 3955 if (auto *SV = dyn_cast<ShuffleVectorInst>(V)) { 3956 V = SV->getOperand(0); 3957 } else { 3958 // Reshuffle to get only unique values. 3959 SmallVector<unsigned, 4> UniqueIdxs; 3960 SmallSet<unsigned, 4> UsedIdxs; 3961 for(unsigned Idx : E->ReuseShuffleIndices) 3962 if (UsedIdxs.insert(Idx).second) 3963 UniqueIdxs.emplace_back(Idx); 3964 V = Builder.CreateShuffleVector(V, UndefValue::get(V->getType()), 3965 UniqueIdxs); 3966 } 3967 } 3968 return V; 3969 } 3970 } 3971 } 3972 3973 Type *ScalarTy = S.OpValue->getType(); 3974 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) 3975 ScalarTy = SI->getValueOperand()->getType(); 3976 3977 // Check that every instruction appears once in this bundle. 3978 SmallVector<unsigned, 4> ReuseShuffleIndicies; 3979 SmallVector<Value *, 4> UniqueValues; 3980 if (VL.size() > 2) { 3981 DenseMap<Value *, unsigned> UniquePositions; 3982 for (Value *V : VL) { 3983 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 3984 ReuseShuffleIndicies.emplace_back(Res.first->second); 3985 if (Res.second || isa<Constant>(V)) 3986 UniqueValues.emplace_back(V); 3987 } 3988 // Do not shuffle single element or if number of unique values is not power 3989 // of 2. 3990 if (UniqueValues.size() == VL.size() || UniqueValues.size() <= 1 || 3991 !llvm::isPowerOf2_32(UniqueValues.size())) 3992 ReuseShuffleIndicies.clear(); 3993 else 3994 VL = UniqueValues; 3995 } 3996 VectorType *VecTy = VectorType::get(ScalarTy, VL.size()); 3997 3998 Value *V = Gather(VL, VecTy); 3999 if (!ReuseShuffleIndicies.empty()) { 4000 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4001 ReuseShuffleIndicies, "shuffle"); 4002 if (auto *I = dyn_cast<Instruction>(V)) { 4003 GatherSeq.insert(I); 4004 CSEBlocks.insert(I->getParent()); 4005 } 4006 } 4007 return V; 4008 } 4009 4010 static void inversePermutation(ArrayRef<unsigned> Indices, 4011 SmallVectorImpl<unsigned> &Mask) { 4012 Mask.clear(); 4013 const unsigned E = Indices.size(); 4014 Mask.resize(E); 4015 for (unsigned I = 0; I < E; ++I) 4016 Mask[Indices[I]] = I; 4017 } 4018 4019 Value *BoUpSLP::vectorizeTree(TreeEntry *E) { 4020 IRBuilder<>::InsertPointGuard Guard(Builder); 4021 4022 if (E->VectorizedValue) { 4023 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *E->Scalars[0] << ".\n"); 4024 return E->VectorizedValue; 4025 } 4026 4027 Instruction *VL0 = E->getMainOp(); 4028 Type *ScalarTy = VL0->getType(); 4029 if (StoreInst *SI = dyn_cast<StoreInst>(VL0)) 4030 ScalarTy = SI->getValueOperand()->getType(); 4031 VectorType *VecTy = VectorType::get(ScalarTy, E->Scalars.size()); 4032 4033 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 4034 4035 if (E->NeedToGather) { 4036 setInsertPointAfterBundle(E); 4037 auto *V = Gather(E->Scalars, VecTy); 4038 if (NeedToShuffleReuses) { 4039 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4040 E->ReuseShuffleIndices, "shuffle"); 4041 if (auto *I = dyn_cast<Instruction>(V)) { 4042 GatherSeq.insert(I); 4043 CSEBlocks.insert(I->getParent()); 4044 } 4045 } 4046 E->VectorizedValue = V; 4047 return V; 4048 } 4049 4050 unsigned ShuffleOrOp = 4051 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); 4052 switch (ShuffleOrOp) { 4053 case Instruction::PHI: { 4054 auto *PH = cast<PHINode>(VL0); 4055 Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI()); 4056 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 4057 PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues()); 4058 Value *V = NewPhi; 4059 if (NeedToShuffleReuses) { 4060 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4061 E->ReuseShuffleIndices, "shuffle"); 4062 } 4063 E->VectorizedValue = V; 4064 4065 // PHINodes may have multiple entries from the same block. We want to 4066 // visit every block once. 4067 SmallPtrSet<BasicBlock*, 4> VisitedBBs; 4068 4069 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 4070 ValueList Operands; 4071 BasicBlock *IBB = PH->getIncomingBlock(i); 4072 4073 if (!VisitedBBs.insert(IBB).second) { 4074 NewPhi->addIncoming(NewPhi->getIncomingValueForBlock(IBB), IBB); 4075 continue; 4076 } 4077 4078 Builder.SetInsertPoint(IBB->getTerminator()); 4079 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 4080 Value *Vec = vectorizeTree(E->getOperand(i)); 4081 NewPhi->addIncoming(Vec, IBB); 4082 } 4083 4084 assert(NewPhi->getNumIncomingValues() == PH->getNumIncomingValues() && 4085 "Invalid number of incoming values"); 4086 return V; 4087 } 4088 4089 case Instruction::ExtractElement: { 4090 if (!E->NeedToGather) { 4091 Value *V = E->getSingleOperand(0); 4092 if (!E->ReorderIndices.empty()) { 4093 OrdersType Mask; 4094 inversePermutation(E->ReorderIndices, Mask); 4095 Builder.SetInsertPoint(VL0); 4096 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), Mask, 4097 "reorder_shuffle"); 4098 } 4099 if (NeedToShuffleReuses) { 4100 // TODO: Merge this shuffle with the ReorderShuffleMask. 4101 if (E->ReorderIndices.empty()) 4102 Builder.SetInsertPoint(VL0); 4103 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4104 E->ReuseShuffleIndices, "shuffle"); 4105 } 4106 E->VectorizedValue = V; 4107 return V; 4108 } 4109 setInsertPointAfterBundle(E); 4110 auto *V = Gather(E->Scalars, VecTy); 4111 if (NeedToShuffleReuses) { 4112 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4113 E->ReuseShuffleIndices, "shuffle"); 4114 if (auto *I = dyn_cast<Instruction>(V)) { 4115 GatherSeq.insert(I); 4116 CSEBlocks.insert(I->getParent()); 4117 } 4118 } 4119 E->VectorizedValue = V; 4120 return V; 4121 } 4122 case Instruction::ExtractValue: { 4123 if (!E->NeedToGather) { 4124 LoadInst *LI = cast<LoadInst>(E->getSingleOperand(0)); 4125 Builder.SetInsertPoint(LI); 4126 PointerType *PtrTy = PointerType::get(VecTy, LI->getPointerAddressSpace()); 4127 Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy); 4128 LoadInst *V = Builder.CreateAlignedLoad(VecTy, Ptr, LI->getAlignment()); 4129 Value *NewV = propagateMetadata(V, E->Scalars); 4130 if (!E->ReorderIndices.empty()) { 4131 OrdersType Mask; 4132 inversePermutation(E->ReorderIndices, Mask); 4133 NewV = Builder.CreateShuffleVector(NewV, UndefValue::get(VecTy), Mask, 4134 "reorder_shuffle"); 4135 } 4136 if (NeedToShuffleReuses) { 4137 // TODO: Merge this shuffle with the ReorderShuffleMask. 4138 NewV = Builder.CreateShuffleVector( 4139 NewV, UndefValue::get(VecTy), E->ReuseShuffleIndices, "shuffle"); 4140 } 4141 E->VectorizedValue = NewV; 4142 return NewV; 4143 } 4144 setInsertPointAfterBundle(E); 4145 auto *V = Gather(E->Scalars, VecTy); 4146 if (NeedToShuffleReuses) { 4147 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4148 E->ReuseShuffleIndices, "shuffle"); 4149 if (auto *I = dyn_cast<Instruction>(V)) { 4150 GatherSeq.insert(I); 4151 CSEBlocks.insert(I->getParent()); 4152 } 4153 } 4154 E->VectorizedValue = V; 4155 return V; 4156 } 4157 case Instruction::ZExt: 4158 case Instruction::SExt: 4159 case Instruction::FPToUI: 4160 case Instruction::FPToSI: 4161 case Instruction::FPExt: 4162 case Instruction::PtrToInt: 4163 case Instruction::IntToPtr: 4164 case Instruction::SIToFP: 4165 case Instruction::UIToFP: 4166 case Instruction::Trunc: 4167 case Instruction::FPTrunc: 4168 case Instruction::BitCast: { 4169 setInsertPointAfterBundle(E); 4170 4171 Value *InVec = vectorizeTree(E->getOperand(0)); 4172 4173 if (E->VectorizedValue) { 4174 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4175 return E->VectorizedValue; 4176 } 4177 4178 auto *CI = cast<CastInst>(VL0); 4179 Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy); 4180 if (NeedToShuffleReuses) { 4181 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4182 E->ReuseShuffleIndices, "shuffle"); 4183 } 4184 E->VectorizedValue = V; 4185 ++NumVectorInstructions; 4186 return V; 4187 } 4188 case Instruction::FCmp: 4189 case Instruction::ICmp: { 4190 setInsertPointAfterBundle(E); 4191 4192 Value *L = vectorizeTree(E->getOperand(0)); 4193 Value *R = vectorizeTree(E->getOperand(1)); 4194 4195 if (E->VectorizedValue) { 4196 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4197 return E->VectorizedValue; 4198 } 4199 4200 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 4201 Value *V; 4202 if (E->getOpcode() == Instruction::FCmp) 4203 V = Builder.CreateFCmp(P0, L, R); 4204 else 4205 V = Builder.CreateICmp(P0, L, R); 4206 4207 propagateIRFlags(V, E->Scalars, VL0); 4208 if (NeedToShuffleReuses) { 4209 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4210 E->ReuseShuffleIndices, "shuffle"); 4211 } 4212 E->VectorizedValue = V; 4213 ++NumVectorInstructions; 4214 return V; 4215 } 4216 case Instruction::Select: { 4217 setInsertPointAfterBundle(E); 4218 4219 Value *Cond = vectorizeTree(E->getOperand(0)); 4220 Value *True = vectorizeTree(E->getOperand(1)); 4221 Value *False = vectorizeTree(E->getOperand(2)); 4222 4223 if (E->VectorizedValue) { 4224 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4225 return E->VectorizedValue; 4226 } 4227 4228 Value *V = Builder.CreateSelect(Cond, True, False); 4229 if (NeedToShuffleReuses) { 4230 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4231 E->ReuseShuffleIndices, "shuffle"); 4232 } 4233 E->VectorizedValue = V; 4234 ++NumVectorInstructions; 4235 return V; 4236 } 4237 case Instruction::FNeg: { 4238 setInsertPointAfterBundle(E); 4239 4240 Value *Op = vectorizeTree(E->getOperand(0)); 4241 4242 if (E->VectorizedValue) { 4243 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4244 return E->VectorizedValue; 4245 } 4246 4247 Value *V = Builder.CreateUnOp( 4248 static_cast<Instruction::UnaryOps>(E->getOpcode()), Op); 4249 propagateIRFlags(V, E->Scalars, VL0); 4250 if (auto *I = dyn_cast<Instruction>(V)) 4251 V = propagateMetadata(I, E->Scalars); 4252 4253 if (NeedToShuffleReuses) { 4254 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4255 E->ReuseShuffleIndices, "shuffle"); 4256 } 4257 E->VectorizedValue = V; 4258 ++NumVectorInstructions; 4259 4260 return V; 4261 } 4262 case Instruction::Add: 4263 case Instruction::FAdd: 4264 case Instruction::Sub: 4265 case Instruction::FSub: 4266 case Instruction::Mul: 4267 case Instruction::FMul: 4268 case Instruction::UDiv: 4269 case Instruction::SDiv: 4270 case Instruction::FDiv: 4271 case Instruction::URem: 4272 case Instruction::SRem: 4273 case Instruction::FRem: 4274 case Instruction::Shl: 4275 case Instruction::LShr: 4276 case Instruction::AShr: 4277 case Instruction::And: 4278 case Instruction::Or: 4279 case Instruction::Xor: { 4280 setInsertPointAfterBundle(E); 4281 4282 Value *LHS = vectorizeTree(E->getOperand(0)); 4283 Value *RHS = vectorizeTree(E->getOperand(1)); 4284 4285 if (E->VectorizedValue) { 4286 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4287 return E->VectorizedValue; 4288 } 4289 4290 Value *V = Builder.CreateBinOp( 4291 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, 4292 RHS); 4293 propagateIRFlags(V, E->Scalars, VL0); 4294 if (auto *I = dyn_cast<Instruction>(V)) 4295 V = propagateMetadata(I, E->Scalars); 4296 4297 if (NeedToShuffleReuses) { 4298 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4299 E->ReuseShuffleIndices, "shuffle"); 4300 } 4301 E->VectorizedValue = V; 4302 ++NumVectorInstructions; 4303 4304 return V; 4305 } 4306 case Instruction::Load: { 4307 // Loads are inserted at the head of the tree because we don't want to 4308 // sink them all the way down past store instructions. 4309 bool IsReorder = E->updateStateIfReorder(); 4310 if (IsReorder) 4311 VL0 = E->getMainOp(); 4312 setInsertPointAfterBundle(E); 4313 4314 LoadInst *LI = cast<LoadInst>(VL0); 4315 Type *ScalarLoadTy = LI->getType(); 4316 unsigned AS = LI->getPointerAddressSpace(); 4317 4318 Value *VecPtr = Builder.CreateBitCast(LI->getPointerOperand(), 4319 VecTy->getPointerTo(AS)); 4320 4321 // The pointer operand uses an in-tree scalar so we add the new BitCast to 4322 // ExternalUses list to make sure that an extract will be generated in the 4323 // future. 4324 Value *PO = LI->getPointerOperand(); 4325 if (getTreeEntry(PO)) 4326 ExternalUses.push_back(ExternalUser(PO, cast<User>(VecPtr), 0)); 4327 4328 MaybeAlign Alignment = MaybeAlign(LI->getAlignment()); 4329 LI = Builder.CreateLoad(VecTy, VecPtr); 4330 if (!Alignment) 4331 Alignment = MaybeAlign(DL->getABITypeAlignment(ScalarLoadTy)); 4332 LI->setAlignment(Alignment); 4333 Value *V = propagateMetadata(LI, E->Scalars); 4334 if (IsReorder) { 4335 OrdersType Mask; 4336 inversePermutation(E->ReorderIndices, Mask); 4337 V = Builder.CreateShuffleVector(V, UndefValue::get(V->getType()), 4338 Mask, "reorder_shuffle"); 4339 } 4340 if (NeedToShuffleReuses) { 4341 // TODO: Merge this shuffle with the ReorderShuffleMask. 4342 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4343 E->ReuseShuffleIndices, "shuffle"); 4344 } 4345 E->VectorizedValue = V; 4346 ++NumVectorInstructions; 4347 return V; 4348 } 4349 case Instruction::Store: { 4350 bool IsReorder = !E->ReorderIndices.empty(); 4351 auto *SI = cast<StoreInst>( 4352 IsReorder ? E->Scalars[E->ReorderIndices.front()] : VL0); 4353 unsigned Alignment = SI->getAlignment(); 4354 unsigned AS = SI->getPointerAddressSpace(); 4355 4356 setInsertPointAfterBundle(E); 4357 4358 Value *VecValue = vectorizeTree(E->getOperand(0)); 4359 if (IsReorder) { 4360 OrdersType Mask; 4361 inversePermutation(E->ReorderIndices, Mask); 4362 VecValue = Builder.CreateShuffleVector( 4363 VecValue, UndefValue::get(VecValue->getType()), E->ReorderIndices, 4364 "reorder_shuffle"); 4365 } 4366 Value *ScalarPtr = SI->getPointerOperand(); 4367 Value *VecPtr = Builder.CreateBitCast( 4368 ScalarPtr, VecValue->getType()->getPointerTo(AS)); 4369 StoreInst *ST = Builder.CreateStore(VecValue, VecPtr); 4370 4371 // The pointer operand uses an in-tree scalar, so add the new BitCast to 4372 // ExternalUses to make sure that an extract will be generated in the 4373 // future. 4374 if (getTreeEntry(ScalarPtr)) 4375 ExternalUses.push_back(ExternalUser(ScalarPtr, cast<User>(VecPtr), 0)); 4376 4377 if (!Alignment) 4378 Alignment = DL->getABITypeAlignment(SI->getValueOperand()->getType()); 4379 4380 ST->setAlignment(Align(Alignment)); 4381 Value *V = propagateMetadata(ST, E->Scalars); 4382 if (NeedToShuffleReuses) { 4383 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4384 E->ReuseShuffleIndices, "shuffle"); 4385 } 4386 E->VectorizedValue = V; 4387 ++NumVectorInstructions; 4388 return V; 4389 } 4390 case Instruction::GetElementPtr: { 4391 setInsertPointAfterBundle(E); 4392 4393 Value *Op0 = vectorizeTree(E->getOperand(0)); 4394 4395 std::vector<Value *> OpVecs; 4396 for (int j = 1, e = cast<GetElementPtrInst>(VL0)->getNumOperands(); j < e; 4397 ++j) { 4398 ValueList &VL = E->getOperand(j); 4399 // Need to cast all elements to the same type before vectorization to 4400 // avoid crash. 4401 Type *VL0Ty = VL0->getOperand(j)->getType(); 4402 Type *Ty = llvm::all_of( 4403 VL, [VL0Ty](Value *V) { return VL0Ty == V->getType(); }) 4404 ? VL0Ty 4405 : DL->getIndexType(cast<GetElementPtrInst>(VL0) 4406 ->getPointerOperandType() 4407 ->getScalarType()); 4408 for (Value *&V : VL) { 4409 auto *CI = cast<ConstantInt>(V); 4410 V = ConstantExpr::getIntegerCast(CI, Ty, 4411 CI->getValue().isSignBitSet()); 4412 } 4413 Value *OpVec = vectorizeTree(VL); 4414 OpVecs.push_back(OpVec); 4415 } 4416 4417 Value *V = Builder.CreateGEP( 4418 cast<GetElementPtrInst>(VL0)->getSourceElementType(), Op0, OpVecs); 4419 if (Instruction *I = dyn_cast<Instruction>(V)) 4420 V = propagateMetadata(I, E->Scalars); 4421 4422 if (NeedToShuffleReuses) { 4423 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4424 E->ReuseShuffleIndices, "shuffle"); 4425 } 4426 E->VectorizedValue = V; 4427 ++NumVectorInstructions; 4428 4429 return V; 4430 } 4431 case Instruction::Call: { 4432 CallInst *CI = cast<CallInst>(VL0); 4433 setInsertPointAfterBundle(E); 4434 4435 Intrinsic::ID IID = Intrinsic::not_intrinsic; 4436 if (Function *FI = CI->getCalledFunction()) 4437 IID = FI->getIntrinsicID(); 4438 4439 Value *ScalarArg = nullptr; 4440 std::vector<Value *> OpVecs; 4441 for (int j = 0, e = CI->getNumArgOperands(); j < e; ++j) { 4442 ValueList OpVL; 4443 // Some intrinsics have scalar arguments. This argument should not be 4444 // vectorized. 4445 if (hasVectorInstrinsicScalarOpd(IID, j)) { 4446 CallInst *CEI = cast<CallInst>(VL0); 4447 ScalarArg = CEI->getArgOperand(j); 4448 OpVecs.push_back(CEI->getArgOperand(j)); 4449 continue; 4450 } 4451 4452 Value *OpVec = vectorizeTree(E->getOperand(j)); 4453 LLVM_DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n"); 4454 OpVecs.push_back(OpVec); 4455 } 4456 4457 Module *M = F->getParent(); 4458 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 4459 Type *Tys[] = { VectorType::get(CI->getType(), E->Scalars.size()) }; 4460 Function *CF = Intrinsic::getDeclaration(M, ID, Tys); 4461 SmallVector<OperandBundleDef, 1> OpBundles; 4462 CI->getOperandBundlesAsDefs(OpBundles); 4463 Value *V = Builder.CreateCall(CF, OpVecs, OpBundles); 4464 4465 // The scalar argument uses an in-tree scalar so we add the new vectorized 4466 // call to ExternalUses list to make sure that an extract will be 4467 // generated in the future. 4468 if (ScalarArg && getTreeEntry(ScalarArg)) 4469 ExternalUses.push_back(ExternalUser(ScalarArg, cast<User>(V), 0)); 4470 4471 propagateIRFlags(V, E->Scalars, VL0); 4472 if (NeedToShuffleReuses) { 4473 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4474 E->ReuseShuffleIndices, "shuffle"); 4475 } 4476 E->VectorizedValue = V; 4477 ++NumVectorInstructions; 4478 return V; 4479 } 4480 case Instruction::ShuffleVector: { 4481 assert(E->isAltShuffle() && 4482 ((Instruction::isBinaryOp(E->getOpcode()) && 4483 Instruction::isBinaryOp(E->getAltOpcode())) || 4484 (Instruction::isCast(E->getOpcode()) && 4485 Instruction::isCast(E->getAltOpcode()))) && 4486 "Invalid Shuffle Vector Operand"); 4487 4488 Value *LHS = nullptr, *RHS = nullptr; 4489 if (Instruction::isBinaryOp(E->getOpcode())) { 4490 setInsertPointAfterBundle(E); 4491 LHS = vectorizeTree(E->getOperand(0)); 4492 RHS = vectorizeTree(E->getOperand(1)); 4493 } else { 4494 setInsertPointAfterBundle(E); 4495 LHS = vectorizeTree(E->getOperand(0)); 4496 } 4497 4498 if (E->VectorizedValue) { 4499 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 4500 return E->VectorizedValue; 4501 } 4502 4503 Value *V0, *V1; 4504 if (Instruction::isBinaryOp(E->getOpcode())) { 4505 V0 = Builder.CreateBinOp( 4506 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, RHS); 4507 V1 = Builder.CreateBinOp( 4508 static_cast<Instruction::BinaryOps>(E->getAltOpcode()), LHS, RHS); 4509 } else { 4510 V0 = Builder.CreateCast( 4511 static_cast<Instruction::CastOps>(E->getOpcode()), LHS, VecTy); 4512 V1 = Builder.CreateCast( 4513 static_cast<Instruction::CastOps>(E->getAltOpcode()), LHS, VecTy); 4514 } 4515 4516 // Create shuffle to take alternate operations from the vector. 4517 // Also, gather up main and alt scalar ops to propagate IR flags to 4518 // each vector operation. 4519 ValueList OpScalars, AltScalars; 4520 unsigned e = E->Scalars.size(); 4521 SmallVector<Constant *, 8> Mask(e); 4522 for (unsigned i = 0; i < e; ++i) { 4523 auto *OpInst = cast<Instruction>(E->Scalars[i]); 4524 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode"); 4525 if (OpInst->getOpcode() == E->getAltOpcode()) { 4526 Mask[i] = Builder.getInt32(e + i); 4527 AltScalars.push_back(E->Scalars[i]); 4528 } else { 4529 Mask[i] = Builder.getInt32(i); 4530 OpScalars.push_back(E->Scalars[i]); 4531 } 4532 } 4533 4534 Value *ShuffleMask = ConstantVector::get(Mask); 4535 propagateIRFlags(V0, OpScalars); 4536 propagateIRFlags(V1, AltScalars); 4537 4538 Value *V = Builder.CreateShuffleVector(V0, V1, ShuffleMask); 4539 if (Instruction *I = dyn_cast<Instruction>(V)) 4540 V = propagateMetadata(I, E->Scalars); 4541 if (NeedToShuffleReuses) { 4542 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 4543 E->ReuseShuffleIndices, "shuffle"); 4544 } 4545 E->VectorizedValue = V; 4546 ++NumVectorInstructions; 4547 4548 return V; 4549 } 4550 default: 4551 llvm_unreachable("unknown inst"); 4552 } 4553 return nullptr; 4554 } 4555 4556 Value *BoUpSLP::vectorizeTree() { 4557 ExtraValueToDebugLocsMap ExternallyUsedValues; 4558 return vectorizeTree(ExternallyUsedValues); 4559 } 4560 4561 Value * 4562 BoUpSLP::vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues) { 4563 // All blocks must be scheduled before any instructions are inserted. 4564 for (auto &BSIter : BlocksSchedules) { 4565 scheduleBlock(BSIter.second.get()); 4566 } 4567 4568 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4569 auto *VectorRoot = vectorizeTree(VectorizableTree[0].get()); 4570 4571 // If the vectorized tree can be rewritten in a smaller type, we truncate the 4572 // vectorized root. InstCombine will then rewrite the entire expression. We 4573 // sign extend the extracted values below. 4574 auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; 4575 if (MinBWs.count(ScalarRoot)) { 4576 if (auto *I = dyn_cast<Instruction>(VectorRoot)) 4577 Builder.SetInsertPoint(&*++BasicBlock::iterator(I)); 4578 auto BundleWidth = VectorizableTree[0]->Scalars.size(); 4579 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 4580 auto *VecTy = VectorType::get(MinTy, BundleWidth); 4581 auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy); 4582 VectorizableTree[0]->VectorizedValue = Trunc; 4583 } 4584 4585 LLVM_DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size() 4586 << " values .\n"); 4587 4588 // If necessary, sign-extend or zero-extend ScalarRoot to the larger type 4589 // specified by ScalarType. 4590 auto extend = [&](Value *ScalarRoot, Value *Ex, Type *ScalarType) { 4591 if (!MinBWs.count(ScalarRoot)) 4592 return Ex; 4593 if (MinBWs[ScalarRoot].second) 4594 return Builder.CreateSExt(Ex, ScalarType); 4595 return Builder.CreateZExt(Ex, ScalarType); 4596 }; 4597 4598 // Extract all of the elements with the external uses. 4599 for (const auto &ExternalUse : ExternalUses) { 4600 Value *Scalar = ExternalUse.Scalar; 4601 llvm::User *User = ExternalUse.User; 4602 4603 // Skip users that we already RAUW. This happens when one instruction 4604 // has multiple uses of the same value. 4605 if (User && !is_contained(Scalar->users(), User)) 4606 continue; 4607 TreeEntry *E = getTreeEntry(Scalar); 4608 assert(E && "Invalid scalar"); 4609 assert(!E->NeedToGather && "Extracting from a gather list"); 4610 4611 Value *Vec = E->VectorizedValue; 4612 assert(Vec && "Can't find vectorizable value"); 4613 4614 Value *Lane = Builder.getInt32(ExternalUse.Lane); 4615 // If User == nullptr, the Scalar is used as extra arg. Generate 4616 // ExtractElement instruction and update the record for this scalar in 4617 // ExternallyUsedValues. 4618 if (!User) { 4619 assert(ExternallyUsedValues.count(Scalar) && 4620 "Scalar with nullptr as an external user must be registered in " 4621 "ExternallyUsedValues map"); 4622 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 4623 Builder.SetInsertPoint(VecI->getParent(), 4624 std::next(VecI->getIterator())); 4625 } else { 4626 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4627 } 4628 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4629 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4630 CSEBlocks.insert(cast<Instruction>(Scalar)->getParent()); 4631 auto &Locs = ExternallyUsedValues[Scalar]; 4632 ExternallyUsedValues.insert({Ex, Locs}); 4633 ExternallyUsedValues.erase(Scalar); 4634 // Required to update internally referenced instructions. 4635 Scalar->replaceAllUsesWith(Ex); 4636 continue; 4637 } 4638 4639 // Generate extracts for out-of-tree users. 4640 // Find the insertion point for the extractelement lane. 4641 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 4642 if (PHINode *PH = dyn_cast<PHINode>(User)) { 4643 for (int i = 0, e = PH->getNumIncomingValues(); i != e; ++i) { 4644 if (PH->getIncomingValue(i) == Scalar) { 4645 Instruction *IncomingTerminator = 4646 PH->getIncomingBlock(i)->getTerminator(); 4647 if (isa<CatchSwitchInst>(IncomingTerminator)) { 4648 Builder.SetInsertPoint(VecI->getParent(), 4649 std::next(VecI->getIterator())); 4650 } else { 4651 Builder.SetInsertPoint(PH->getIncomingBlock(i)->getTerminator()); 4652 } 4653 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4654 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4655 CSEBlocks.insert(PH->getIncomingBlock(i)); 4656 PH->setOperand(i, Ex); 4657 } 4658 } 4659 } else { 4660 Builder.SetInsertPoint(cast<Instruction>(User)); 4661 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4662 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4663 CSEBlocks.insert(cast<Instruction>(User)->getParent()); 4664 User->replaceUsesOfWith(Scalar, Ex); 4665 } 4666 } else { 4667 Builder.SetInsertPoint(&F->getEntryBlock().front()); 4668 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 4669 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 4670 CSEBlocks.insert(&F->getEntryBlock()); 4671 User->replaceUsesOfWith(Scalar, Ex); 4672 } 4673 4674 LLVM_DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n"); 4675 } 4676 4677 // For each vectorized value: 4678 for (auto &TEPtr : VectorizableTree) { 4679 TreeEntry *Entry = TEPtr.get(); 4680 4681 // No need to handle users of gathered values. 4682 if (Entry->NeedToGather) 4683 continue; 4684 4685 assert(Entry->VectorizedValue && "Can't find vectorizable value"); 4686 4687 // For each lane: 4688 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 4689 Value *Scalar = Entry->Scalars[Lane]; 4690 4691 #ifndef NDEBUG 4692 Type *Ty = Scalar->getType(); 4693 if (!Ty->isVoidTy()) { 4694 for (User *U : Scalar->users()) { 4695 LLVM_DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n"); 4696 4697 // It is legal to delete users in the ignorelist. 4698 assert((getTreeEntry(U) || is_contained(UserIgnoreList, U)) && 4699 "Deleting out-of-tree value"); 4700 } 4701 } 4702 #endif 4703 LLVM_DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n"); 4704 eraseInstruction(cast<Instruction>(Scalar)); 4705 } 4706 } 4707 4708 Builder.ClearInsertionPoint(); 4709 4710 return VectorizableTree[0]->VectorizedValue; 4711 } 4712 4713 void BoUpSLP::optimizeGatherSequence() { 4714 LLVM_DEBUG(dbgs() << "SLP: Optimizing " << GatherSeq.size() 4715 << " gather sequences instructions.\n"); 4716 // LICM InsertElementInst sequences. 4717 for (Instruction *I : GatherSeq) { 4718 if (isDeleted(I)) 4719 continue; 4720 4721 // Check if this block is inside a loop. 4722 Loop *L = LI->getLoopFor(I->getParent()); 4723 if (!L) 4724 continue; 4725 4726 // Check if it has a preheader. 4727 BasicBlock *PreHeader = L->getLoopPreheader(); 4728 if (!PreHeader) 4729 continue; 4730 4731 // If the vector or the element that we insert into it are 4732 // instructions that are defined in this basic block then we can't 4733 // hoist this instruction. 4734 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 4735 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 4736 if (Op0 && L->contains(Op0)) 4737 continue; 4738 if (Op1 && L->contains(Op1)) 4739 continue; 4740 4741 // We can hoist this instruction. Move it to the pre-header. 4742 I->moveBefore(PreHeader->getTerminator()); 4743 } 4744 4745 // Make a list of all reachable blocks in our CSE queue. 4746 SmallVector<const DomTreeNode *, 8> CSEWorkList; 4747 CSEWorkList.reserve(CSEBlocks.size()); 4748 for (BasicBlock *BB : CSEBlocks) 4749 if (DomTreeNode *N = DT->getNode(BB)) { 4750 assert(DT->isReachableFromEntry(N)); 4751 CSEWorkList.push_back(N); 4752 } 4753 4754 // Sort blocks by domination. This ensures we visit a block after all blocks 4755 // dominating it are visited. 4756 llvm::stable_sort(CSEWorkList, 4757 [this](const DomTreeNode *A, const DomTreeNode *B) { 4758 return DT->properlyDominates(A, B); 4759 }); 4760 4761 // Perform O(N^2) search over the gather sequences and merge identical 4762 // instructions. TODO: We can further optimize this scan if we split the 4763 // instructions into different buckets based on the insert lane. 4764 SmallVector<Instruction *, 16> Visited; 4765 for (auto I = CSEWorkList.begin(), E = CSEWorkList.end(); I != E; ++I) { 4766 assert((I == CSEWorkList.begin() || !DT->dominates(*I, *std::prev(I))) && 4767 "Worklist not sorted properly!"); 4768 BasicBlock *BB = (*I)->getBlock(); 4769 // For all instructions in blocks containing gather sequences: 4770 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e;) { 4771 Instruction *In = &*it++; 4772 if (isDeleted(In)) 4773 continue; 4774 if (!isa<InsertElementInst>(In) && !isa<ExtractElementInst>(In)) 4775 continue; 4776 4777 // Check if we can replace this instruction with any of the 4778 // visited instructions. 4779 for (Instruction *v : Visited) { 4780 if (In->isIdenticalTo(v) && 4781 DT->dominates(v->getParent(), In->getParent())) { 4782 In->replaceAllUsesWith(v); 4783 eraseInstruction(In); 4784 In = nullptr; 4785 break; 4786 } 4787 } 4788 if (In) { 4789 assert(!is_contained(Visited, In)); 4790 Visited.push_back(In); 4791 } 4792 } 4793 } 4794 CSEBlocks.clear(); 4795 GatherSeq.clear(); 4796 } 4797 4798 // Groups the instructions to a bundle (which is then a single scheduling entity) 4799 // and schedules instructions until the bundle gets ready. 4800 Optional<BoUpSLP::ScheduleData *> 4801 BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, 4802 const InstructionsState &S) { 4803 if (isa<PHINode>(S.OpValue)) 4804 return nullptr; 4805 4806 // Initialize the instruction bundle. 4807 Instruction *OldScheduleEnd = ScheduleEnd; 4808 ScheduleData *PrevInBundle = nullptr; 4809 ScheduleData *Bundle = nullptr; 4810 bool ReSchedule = false; 4811 LLVM_DEBUG(dbgs() << "SLP: bundle: " << *S.OpValue << "\n"); 4812 4813 // Make sure that the scheduling region contains all 4814 // instructions of the bundle. 4815 for (Value *V : VL) { 4816 if (!extendSchedulingRegion(V, S)) 4817 return None; 4818 } 4819 4820 for (Value *V : VL) { 4821 ScheduleData *BundleMember = getScheduleData(V); 4822 assert(BundleMember && 4823 "no ScheduleData for bundle member (maybe not in same basic block)"); 4824 if (BundleMember->IsScheduled) { 4825 // A bundle member was scheduled as single instruction before and now 4826 // needs to be scheduled as part of the bundle. We just get rid of the 4827 // existing schedule. 4828 LLVM_DEBUG(dbgs() << "SLP: reset schedule because " << *BundleMember 4829 << " was already scheduled\n"); 4830 ReSchedule = true; 4831 } 4832 assert(BundleMember->isSchedulingEntity() && 4833 "bundle member already part of other bundle"); 4834 if (PrevInBundle) { 4835 PrevInBundle->NextInBundle = BundleMember; 4836 } else { 4837 Bundle = BundleMember; 4838 } 4839 BundleMember->UnscheduledDepsInBundle = 0; 4840 Bundle->UnscheduledDepsInBundle += BundleMember->UnscheduledDeps; 4841 4842 // Group the instructions to a bundle. 4843 BundleMember->FirstInBundle = Bundle; 4844 PrevInBundle = BundleMember; 4845 } 4846 if (ScheduleEnd != OldScheduleEnd) { 4847 // The scheduling region got new instructions at the lower end (or it is a 4848 // new region for the first bundle). This makes it necessary to 4849 // recalculate all dependencies. 4850 // It is seldom that this needs to be done a second time after adding the 4851 // initial bundle to the region. 4852 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 4853 doForAllOpcodes(I, [](ScheduleData *SD) { 4854 SD->clearDependencies(); 4855 }); 4856 } 4857 ReSchedule = true; 4858 } 4859 if (ReSchedule) { 4860 resetSchedule(); 4861 initialFillReadyList(ReadyInsts); 4862 } 4863 assert(Bundle && "Failed to find schedule bundle"); 4864 4865 LLVM_DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle << " in block " 4866 << BB->getName() << "\n"); 4867 4868 calculateDependencies(Bundle, true, SLP); 4869 4870 // Now try to schedule the new bundle. As soon as the bundle is "ready" it 4871 // means that there are no cyclic dependencies and we can schedule it. 4872 // Note that's important that we don't "schedule" the bundle yet (see 4873 // cancelScheduling). 4874 while (!Bundle->isReady() && !ReadyInsts.empty()) { 4875 4876 ScheduleData *pickedSD = ReadyInsts.back(); 4877 ReadyInsts.pop_back(); 4878 4879 if (pickedSD->isSchedulingEntity() && pickedSD->isReady()) { 4880 schedule(pickedSD, ReadyInsts); 4881 } 4882 } 4883 if (!Bundle->isReady()) { 4884 cancelScheduling(VL, S.OpValue); 4885 return None; 4886 } 4887 return Bundle; 4888 } 4889 4890 void BoUpSLP::BlockScheduling::cancelScheduling(ArrayRef<Value *> VL, 4891 Value *OpValue) { 4892 if (isa<PHINode>(OpValue)) 4893 return; 4894 4895 ScheduleData *Bundle = getScheduleData(OpValue); 4896 LLVM_DEBUG(dbgs() << "SLP: cancel scheduling of " << *Bundle << "\n"); 4897 assert(!Bundle->IsScheduled && 4898 "Can't cancel bundle which is already scheduled"); 4899 assert(Bundle->isSchedulingEntity() && Bundle->isPartOfBundle() && 4900 "tried to unbundle something which is not a bundle"); 4901 4902 // Un-bundle: make single instructions out of the bundle. 4903 ScheduleData *BundleMember = Bundle; 4904 while (BundleMember) { 4905 assert(BundleMember->FirstInBundle == Bundle && "corrupt bundle links"); 4906 BundleMember->FirstInBundle = BundleMember; 4907 ScheduleData *Next = BundleMember->NextInBundle; 4908 BundleMember->NextInBundle = nullptr; 4909 BundleMember->UnscheduledDepsInBundle = BundleMember->UnscheduledDeps; 4910 if (BundleMember->UnscheduledDepsInBundle == 0) { 4911 ReadyInsts.insert(BundleMember); 4912 } 4913 BundleMember = Next; 4914 } 4915 } 4916 4917 BoUpSLP::ScheduleData *BoUpSLP::BlockScheduling::allocateScheduleDataChunks() { 4918 // Allocate a new ScheduleData for the instruction. 4919 if (ChunkPos >= ChunkSize) { 4920 ScheduleDataChunks.push_back(std::make_unique<ScheduleData[]>(ChunkSize)); 4921 ChunkPos = 0; 4922 } 4923 return &(ScheduleDataChunks.back()[ChunkPos++]); 4924 } 4925 4926 bool BoUpSLP::BlockScheduling::extendSchedulingRegion(Value *V, 4927 const InstructionsState &S) { 4928 if (getScheduleData(V, isOneOf(S, V))) 4929 return true; 4930 Instruction *I = dyn_cast<Instruction>(V); 4931 assert(I && "bundle member must be an instruction"); 4932 assert(!isa<PHINode>(I) && "phi nodes don't need to be scheduled"); 4933 auto &&CheckSheduleForI = [this, &S](Instruction *I) -> bool { 4934 ScheduleData *ISD = getScheduleData(I); 4935 if (!ISD) 4936 return false; 4937 assert(isInSchedulingRegion(ISD) && 4938 "ScheduleData not in scheduling region"); 4939 ScheduleData *SD = allocateScheduleDataChunks(); 4940 SD->Inst = I; 4941 SD->init(SchedulingRegionID, S.OpValue); 4942 ExtraScheduleDataMap[I][S.OpValue] = SD; 4943 return true; 4944 }; 4945 if (CheckSheduleForI(I)) 4946 return true; 4947 if (!ScheduleStart) { 4948 // It's the first instruction in the new region. 4949 initScheduleData(I, I->getNextNode(), nullptr, nullptr); 4950 ScheduleStart = I; 4951 ScheduleEnd = I->getNextNode(); 4952 if (isOneOf(S, I) != I) 4953 CheckSheduleForI(I); 4954 assert(ScheduleEnd && "tried to vectorize a terminator?"); 4955 LLVM_DEBUG(dbgs() << "SLP: initialize schedule region to " << *I << "\n"); 4956 return true; 4957 } 4958 // Search up and down at the same time, because we don't know if the new 4959 // instruction is above or below the existing scheduling region. 4960 BasicBlock::reverse_iterator UpIter = 4961 ++ScheduleStart->getIterator().getReverse(); 4962 BasicBlock::reverse_iterator UpperEnd = BB->rend(); 4963 BasicBlock::iterator DownIter = ScheduleEnd->getIterator(); 4964 BasicBlock::iterator LowerEnd = BB->end(); 4965 while (true) { 4966 if (++ScheduleRegionSize > ScheduleRegionSizeLimit) { 4967 LLVM_DEBUG(dbgs() << "SLP: exceeded schedule region size limit\n"); 4968 return false; 4969 } 4970 4971 if (UpIter != UpperEnd) { 4972 if (&*UpIter == I) { 4973 initScheduleData(I, ScheduleStart, nullptr, FirstLoadStoreInRegion); 4974 ScheduleStart = I; 4975 if (isOneOf(S, I) != I) 4976 CheckSheduleForI(I); 4977 LLVM_DEBUG(dbgs() << "SLP: extend schedule region start to " << *I 4978 << "\n"); 4979 return true; 4980 } 4981 ++UpIter; 4982 } 4983 if (DownIter != LowerEnd) { 4984 if (&*DownIter == I) { 4985 initScheduleData(ScheduleEnd, I->getNextNode(), LastLoadStoreInRegion, 4986 nullptr); 4987 ScheduleEnd = I->getNextNode(); 4988 if (isOneOf(S, I) != I) 4989 CheckSheduleForI(I); 4990 assert(ScheduleEnd && "tried to vectorize a terminator?"); 4991 LLVM_DEBUG(dbgs() << "SLP: extend schedule region end to " << *I 4992 << "\n"); 4993 return true; 4994 } 4995 ++DownIter; 4996 } 4997 assert((UpIter != UpperEnd || DownIter != LowerEnd) && 4998 "instruction not found in block"); 4999 } 5000 return true; 5001 } 5002 5003 void BoUpSLP::BlockScheduling::initScheduleData(Instruction *FromI, 5004 Instruction *ToI, 5005 ScheduleData *PrevLoadStore, 5006 ScheduleData *NextLoadStore) { 5007 ScheduleData *CurrentLoadStore = PrevLoadStore; 5008 for (Instruction *I = FromI; I != ToI; I = I->getNextNode()) { 5009 ScheduleData *SD = ScheduleDataMap[I]; 5010 if (!SD) { 5011 SD = allocateScheduleDataChunks(); 5012 ScheduleDataMap[I] = SD; 5013 SD->Inst = I; 5014 } 5015 assert(!isInSchedulingRegion(SD) && 5016 "new ScheduleData already in scheduling region"); 5017 SD->init(SchedulingRegionID, I); 5018 5019 if (I->mayReadOrWriteMemory() && 5020 (!isa<IntrinsicInst>(I) || 5021 cast<IntrinsicInst>(I)->getIntrinsicID() != Intrinsic::sideeffect)) { 5022 // Update the linked list of memory accessing instructions. 5023 if (CurrentLoadStore) { 5024 CurrentLoadStore->NextLoadStore = SD; 5025 } else { 5026 FirstLoadStoreInRegion = SD; 5027 } 5028 CurrentLoadStore = SD; 5029 } 5030 } 5031 if (NextLoadStore) { 5032 if (CurrentLoadStore) 5033 CurrentLoadStore->NextLoadStore = NextLoadStore; 5034 } else { 5035 LastLoadStoreInRegion = CurrentLoadStore; 5036 } 5037 } 5038 5039 void BoUpSLP::BlockScheduling::calculateDependencies(ScheduleData *SD, 5040 bool InsertInReadyList, 5041 BoUpSLP *SLP) { 5042 assert(SD->isSchedulingEntity()); 5043 5044 SmallVector<ScheduleData *, 10> WorkList; 5045 WorkList.push_back(SD); 5046 5047 while (!WorkList.empty()) { 5048 ScheduleData *SD = WorkList.back(); 5049 WorkList.pop_back(); 5050 5051 ScheduleData *BundleMember = SD; 5052 while (BundleMember) { 5053 assert(isInSchedulingRegion(BundleMember)); 5054 if (!BundleMember->hasValidDependencies()) { 5055 5056 LLVM_DEBUG(dbgs() << "SLP: update deps of " << *BundleMember 5057 << "\n"); 5058 BundleMember->Dependencies = 0; 5059 BundleMember->resetUnscheduledDeps(); 5060 5061 // Handle def-use chain dependencies. 5062 if (BundleMember->OpValue != BundleMember->Inst) { 5063 ScheduleData *UseSD = getScheduleData(BundleMember->Inst); 5064 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 5065 BundleMember->Dependencies++; 5066 ScheduleData *DestBundle = UseSD->FirstInBundle; 5067 if (!DestBundle->IsScheduled) 5068 BundleMember->incrementUnscheduledDeps(1); 5069 if (!DestBundle->hasValidDependencies()) 5070 WorkList.push_back(DestBundle); 5071 } 5072 } else { 5073 for (User *U : BundleMember->Inst->users()) { 5074 if (isa<Instruction>(U)) { 5075 ScheduleData *UseSD = getScheduleData(U); 5076 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 5077 BundleMember->Dependencies++; 5078 ScheduleData *DestBundle = UseSD->FirstInBundle; 5079 if (!DestBundle->IsScheduled) 5080 BundleMember->incrementUnscheduledDeps(1); 5081 if (!DestBundle->hasValidDependencies()) 5082 WorkList.push_back(DestBundle); 5083 } 5084 } else { 5085 // I'm not sure if this can ever happen. But we need to be safe. 5086 // This lets the instruction/bundle never be scheduled and 5087 // eventually disable vectorization. 5088 BundleMember->Dependencies++; 5089 BundleMember->incrementUnscheduledDeps(1); 5090 } 5091 } 5092 } 5093 5094 // Handle the memory dependencies. 5095 ScheduleData *DepDest = BundleMember->NextLoadStore; 5096 if (DepDest) { 5097 Instruction *SrcInst = BundleMember->Inst; 5098 MemoryLocation SrcLoc = getLocation(SrcInst, SLP->AA); 5099 bool SrcMayWrite = BundleMember->Inst->mayWriteToMemory(); 5100 unsigned numAliased = 0; 5101 unsigned DistToSrc = 1; 5102 5103 while (DepDest) { 5104 assert(isInSchedulingRegion(DepDest)); 5105 5106 // We have two limits to reduce the complexity: 5107 // 1) AliasedCheckLimit: It's a small limit to reduce calls to 5108 // SLP->isAliased (which is the expensive part in this loop). 5109 // 2) MaxMemDepDistance: It's for very large blocks and it aborts 5110 // the whole loop (even if the loop is fast, it's quadratic). 5111 // It's important for the loop break condition (see below) to 5112 // check this limit even between two read-only instructions. 5113 if (DistToSrc >= MaxMemDepDistance || 5114 ((SrcMayWrite || DepDest->Inst->mayWriteToMemory()) && 5115 (numAliased >= AliasedCheckLimit || 5116 SLP->isAliased(SrcLoc, SrcInst, DepDest->Inst)))) { 5117 5118 // We increment the counter only if the locations are aliased 5119 // (instead of counting all alias checks). This gives a better 5120 // balance between reduced runtime and accurate dependencies. 5121 numAliased++; 5122 5123 DepDest->MemoryDependencies.push_back(BundleMember); 5124 BundleMember->Dependencies++; 5125 ScheduleData *DestBundle = DepDest->FirstInBundle; 5126 if (!DestBundle->IsScheduled) { 5127 BundleMember->incrementUnscheduledDeps(1); 5128 } 5129 if (!DestBundle->hasValidDependencies()) { 5130 WorkList.push_back(DestBundle); 5131 } 5132 } 5133 DepDest = DepDest->NextLoadStore; 5134 5135 // Example, explaining the loop break condition: Let's assume our 5136 // starting instruction is i0 and MaxMemDepDistance = 3. 5137 // 5138 // +--------v--v--v 5139 // i0,i1,i2,i3,i4,i5,i6,i7,i8 5140 // +--------^--^--^ 5141 // 5142 // MaxMemDepDistance let us stop alias-checking at i3 and we add 5143 // dependencies from i0 to i3,i4,.. (even if they are not aliased). 5144 // Previously we already added dependencies from i3 to i6,i7,i8 5145 // (because of MaxMemDepDistance). As we added a dependency from 5146 // i0 to i3, we have transitive dependencies from i0 to i6,i7,i8 5147 // and we can abort this loop at i6. 5148 if (DistToSrc >= 2 * MaxMemDepDistance) 5149 break; 5150 DistToSrc++; 5151 } 5152 } 5153 } 5154 BundleMember = BundleMember->NextInBundle; 5155 } 5156 if (InsertInReadyList && SD->isReady()) { 5157 ReadyInsts.push_back(SD); 5158 LLVM_DEBUG(dbgs() << "SLP: gets ready on update: " << *SD->Inst 5159 << "\n"); 5160 } 5161 } 5162 } 5163 5164 void BoUpSLP::BlockScheduling::resetSchedule() { 5165 assert(ScheduleStart && 5166 "tried to reset schedule on block which has not been scheduled"); 5167 for (Instruction *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 5168 doForAllOpcodes(I, [&](ScheduleData *SD) { 5169 assert(isInSchedulingRegion(SD) && 5170 "ScheduleData not in scheduling region"); 5171 SD->IsScheduled = false; 5172 SD->resetUnscheduledDeps(); 5173 }); 5174 } 5175 ReadyInsts.clear(); 5176 } 5177 5178 void BoUpSLP::scheduleBlock(BlockScheduling *BS) { 5179 if (!BS->ScheduleStart) 5180 return; 5181 5182 LLVM_DEBUG(dbgs() << "SLP: schedule block " << BS->BB->getName() << "\n"); 5183 5184 BS->resetSchedule(); 5185 5186 // For the real scheduling we use a more sophisticated ready-list: it is 5187 // sorted by the original instruction location. This lets the final schedule 5188 // be as close as possible to the original instruction order. 5189 struct ScheduleDataCompare { 5190 bool operator()(ScheduleData *SD1, ScheduleData *SD2) const { 5191 return SD2->SchedulingPriority < SD1->SchedulingPriority; 5192 } 5193 }; 5194 std::set<ScheduleData *, ScheduleDataCompare> ReadyInsts; 5195 5196 // Ensure that all dependency data is updated and fill the ready-list with 5197 // initial instructions. 5198 int Idx = 0; 5199 int NumToSchedule = 0; 5200 for (auto *I = BS->ScheduleStart; I != BS->ScheduleEnd; 5201 I = I->getNextNode()) { 5202 BS->doForAllOpcodes(I, [this, &Idx, &NumToSchedule, BS](ScheduleData *SD) { 5203 assert(SD->isPartOfBundle() == 5204 (getTreeEntry(SD->Inst) != nullptr) && 5205 "scheduler and vectorizer bundle mismatch"); 5206 SD->FirstInBundle->SchedulingPriority = Idx++; 5207 if (SD->isSchedulingEntity()) { 5208 BS->calculateDependencies(SD, false, this); 5209 NumToSchedule++; 5210 } 5211 }); 5212 } 5213 BS->initialFillReadyList(ReadyInsts); 5214 5215 Instruction *LastScheduledInst = BS->ScheduleEnd; 5216 5217 // Do the "real" scheduling. 5218 while (!ReadyInsts.empty()) { 5219 ScheduleData *picked = *ReadyInsts.begin(); 5220 ReadyInsts.erase(ReadyInsts.begin()); 5221 5222 // Move the scheduled instruction(s) to their dedicated places, if not 5223 // there yet. 5224 ScheduleData *BundleMember = picked; 5225 while (BundleMember) { 5226 Instruction *pickedInst = BundleMember->Inst; 5227 if (LastScheduledInst->getNextNode() != pickedInst) { 5228 BS->BB->getInstList().remove(pickedInst); 5229 BS->BB->getInstList().insert(LastScheduledInst->getIterator(), 5230 pickedInst); 5231 } 5232 LastScheduledInst = pickedInst; 5233 BundleMember = BundleMember->NextInBundle; 5234 } 5235 5236 BS->schedule(picked, ReadyInsts); 5237 NumToSchedule--; 5238 } 5239 assert(NumToSchedule == 0 && "could not schedule all instructions"); 5240 5241 // Avoid duplicate scheduling of the block. 5242 BS->ScheduleStart = nullptr; 5243 } 5244 5245 unsigned BoUpSLP::getVectorElementSize(Value *V) const { 5246 // If V is a store, just return the width of the stored value without 5247 // traversing the expression tree. This is the common case. 5248 if (auto *Store = dyn_cast<StoreInst>(V)) 5249 return DL->getTypeSizeInBits(Store->getValueOperand()->getType()); 5250 5251 // If V is not a store, we can traverse the expression tree to find loads 5252 // that feed it. The type of the loaded value may indicate a more suitable 5253 // width than V's type. We want to base the vector element size on the width 5254 // of memory operations where possible. 5255 SmallVector<Instruction *, 16> Worklist; 5256 SmallPtrSet<Instruction *, 16> Visited; 5257 if (auto *I = dyn_cast<Instruction>(V)) 5258 Worklist.push_back(I); 5259 5260 // Traverse the expression tree in bottom-up order looking for loads. If we 5261 // encounter an instruction we don't yet handle, we give up. 5262 auto MaxWidth = 0u; 5263 auto FoundUnknownInst = false; 5264 while (!Worklist.empty() && !FoundUnknownInst) { 5265 auto *I = Worklist.pop_back_val(); 5266 Visited.insert(I); 5267 5268 // We should only be looking at scalar instructions here. If the current 5269 // instruction has a vector type, give up. 5270 auto *Ty = I->getType(); 5271 if (isa<VectorType>(Ty)) 5272 FoundUnknownInst = true; 5273 5274 // If the current instruction is a load, update MaxWidth to reflect the 5275 // width of the loaded value. 5276 else if (isa<LoadInst>(I)) 5277 MaxWidth = std::max<unsigned>(MaxWidth, DL->getTypeSizeInBits(Ty)); 5278 5279 // Otherwise, we need to visit the operands of the instruction. We only 5280 // handle the interesting cases from buildTree here. If an operand is an 5281 // instruction we haven't yet visited, we add it to the worklist. 5282 else if (isa<PHINode>(I) || isa<CastInst>(I) || isa<GetElementPtrInst>(I) || 5283 isa<CmpInst>(I) || isa<SelectInst>(I) || isa<BinaryOperator>(I)) { 5284 for (Use &U : I->operands()) 5285 if (auto *J = dyn_cast<Instruction>(U.get())) 5286 if (!Visited.count(J)) 5287 Worklist.push_back(J); 5288 } 5289 5290 // If we don't yet handle the instruction, give up. 5291 else 5292 FoundUnknownInst = true; 5293 } 5294 5295 // If we didn't encounter a memory access in the expression tree, or if we 5296 // gave up for some reason, just return the width of V. 5297 if (!MaxWidth || FoundUnknownInst) 5298 return DL->getTypeSizeInBits(V->getType()); 5299 5300 // Otherwise, return the maximum width we found. 5301 return MaxWidth; 5302 } 5303 5304 // Determine if a value V in a vectorizable expression Expr can be demoted to a 5305 // smaller type with a truncation. We collect the values that will be demoted 5306 // in ToDemote and additional roots that require investigating in Roots. 5307 static bool collectValuesToDemote(Value *V, SmallPtrSetImpl<Value *> &Expr, 5308 SmallVectorImpl<Value *> &ToDemote, 5309 SmallVectorImpl<Value *> &Roots) { 5310 // We can always demote constants. 5311 if (isa<Constant>(V)) { 5312 ToDemote.push_back(V); 5313 return true; 5314 } 5315 5316 // If the value is not an instruction in the expression with only one use, it 5317 // cannot be demoted. 5318 auto *I = dyn_cast<Instruction>(V); 5319 if (!I || !I->hasOneUse() || !Expr.count(I)) 5320 return false; 5321 5322 switch (I->getOpcode()) { 5323 5324 // We can always demote truncations and extensions. Since truncations can 5325 // seed additional demotion, we save the truncated value. 5326 case Instruction::Trunc: 5327 Roots.push_back(I->getOperand(0)); 5328 break; 5329 case Instruction::ZExt: 5330 case Instruction::SExt: 5331 break; 5332 5333 // We can demote certain binary operations if we can demote both of their 5334 // operands. 5335 case Instruction::Add: 5336 case Instruction::Sub: 5337 case Instruction::Mul: 5338 case Instruction::And: 5339 case Instruction::Or: 5340 case Instruction::Xor: 5341 if (!collectValuesToDemote(I->getOperand(0), Expr, ToDemote, Roots) || 5342 !collectValuesToDemote(I->getOperand(1), Expr, ToDemote, Roots)) 5343 return false; 5344 break; 5345 5346 // We can demote selects if we can demote their true and false values. 5347 case Instruction::Select: { 5348 SelectInst *SI = cast<SelectInst>(I); 5349 if (!collectValuesToDemote(SI->getTrueValue(), Expr, ToDemote, Roots) || 5350 !collectValuesToDemote(SI->getFalseValue(), Expr, ToDemote, Roots)) 5351 return false; 5352 break; 5353 } 5354 5355 // We can demote phis if we can demote all their incoming operands. Note that 5356 // we don't need to worry about cycles since we ensure single use above. 5357 case Instruction::PHI: { 5358 PHINode *PN = cast<PHINode>(I); 5359 for (Value *IncValue : PN->incoming_values()) 5360 if (!collectValuesToDemote(IncValue, Expr, ToDemote, Roots)) 5361 return false; 5362 break; 5363 } 5364 5365 // Otherwise, conservatively give up. 5366 default: 5367 return false; 5368 } 5369 5370 // Record the value that we can demote. 5371 ToDemote.push_back(V); 5372 return true; 5373 } 5374 5375 void BoUpSLP::computeMinimumValueSizes() { 5376 // If there are no external uses, the expression tree must be rooted by a 5377 // store. We can't demote in-memory values, so there is nothing to do here. 5378 if (ExternalUses.empty()) 5379 return; 5380 5381 // We only attempt to truncate integer expressions. 5382 auto &TreeRoot = VectorizableTree[0]->Scalars; 5383 auto *TreeRootIT = dyn_cast<IntegerType>(TreeRoot[0]->getType()); 5384 if (!TreeRootIT) 5385 return; 5386 5387 // If the expression is not rooted by a store, these roots should have 5388 // external uses. We will rely on InstCombine to rewrite the expression in 5389 // the narrower type. However, InstCombine only rewrites single-use values. 5390 // This means that if a tree entry other than a root is used externally, it 5391 // must have multiple uses and InstCombine will not rewrite it. The code 5392 // below ensures that only the roots are used externally. 5393 SmallPtrSet<Value *, 32> Expr(TreeRoot.begin(), TreeRoot.end()); 5394 for (auto &EU : ExternalUses) 5395 if (!Expr.erase(EU.Scalar)) 5396 return; 5397 if (!Expr.empty()) 5398 return; 5399 5400 // Collect the scalar values of the vectorizable expression. We will use this 5401 // context to determine which values can be demoted. If we see a truncation, 5402 // we mark it as seeding another demotion. 5403 for (auto &EntryPtr : VectorizableTree) 5404 Expr.insert(EntryPtr->Scalars.begin(), EntryPtr->Scalars.end()); 5405 5406 // Ensure the roots of the vectorizable tree don't form a cycle. They must 5407 // have a single external user that is not in the vectorizable tree. 5408 for (auto *Root : TreeRoot) 5409 if (!Root->hasOneUse() || Expr.count(*Root->user_begin())) 5410 return; 5411 5412 // Conservatively determine if we can actually truncate the roots of the 5413 // expression. Collect the values that can be demoted in ToDemote and 5414 // additional roots that require investigating in Roots. 5415 SmallVector<Value *, 32> ToDemote; 5416 SmallVector<Value *, 4> Roots; 5417 for (auto *Root : TreeRoot) 5418 if (!collectValuesToDemote(Root, Expr, ToDemote, Roots)) 5419 return; 5420 5421 // The maximum bit width required to represent all the values that can be 5422 // demoted without loss of precision. It would be safe to truncate the roots 5423 // of the expression to this width. 5424 auto MaxBitWidth = 8u; 5425 5426 // We first check if all the bits of the roots are demanded. If they're not, 5427 // we can truncate the roots to this narrower type. 5428 for (auto *Root : TreeRoot) { 5429 auto Mask = DB->getDemandedBits(cast<Instruction>(Root)); 5430 MaxBitWidth = std::max<unsigned>( 5431 Mask.getBitWidth() - Mask.countLeadingZeros(), MaxBitWidth); 5432 } 5433 5434 // True if the roots can be zero-extended back to their original type, rather 5435 // than sign-extended. We know that if the leading bits are not demanded, we 5436 // can safely zero-extend. So we initialize IsKnownPositive to True. 5437 bool IsKnownPositive = true; 5438 5439 // If all the bits of the roots are demanded, we can try a little harder to 5440 // compute a narrower type. This can happen, for example, if the roots are 5441 // getelementptr indices. InstCombine promotes these indices to the pointer 5442 // width. Thus, all their bits are technically demanded even though the 5443 // address computation might be vectorized in a smaller type. 5444 // 5445 // We start by looking at each entry that can be demoted. We compute the 5446 // maximum bit width required to store the scalar by using ValueTracking to 5447 // compute the number of high-order bits we can truncate. 5448 if (MaxBitWidth == DL->getTypeSizeInBits(TreeRoot[0]->getType()) && 5449 llvm::all_of(TreeRoot, [](Value *R) { 5450 assert(R->hasOneUse() && "Root should have only one use!"); 5451 return isa<GetElementPtrInst>(R->user_back()); 5452 })) { 5453 MaxBitWidth = 8u; 5454 5455 // Determine if the sign bit of all the roots is known to be zero. If not, 5456 // IsKnownPositive is set to False. 5457 IsKnownPositive = llvm::all_of(TreeRoot, [&](Value *R) { 5458 KnownBits Known = computeKnownBits(R, *DL); 5459 return Known.isNonNegative(); 5460 }); 5461 5462 // Determine the maximum number of bits required to store the scalar 5463 // values. 5464 for (auto *Scalar : ToDemote) { 5465 auto NumSignBits = ComputeNumSignBits(Scalar, *DL, 0, AC, nullptr, DT); 5466 auto NumTypeBits = DL->getTypeSizeInBits(Scalar->getType()); 5467 MaxBitWidth = std::max<unsigned>(NumTypeBits - NumSignBits, MaxBitWidth); 5468 } 5469 5470 // If we can't prove that the sign bit is zero, we must add one to the 5471 // maximum bit width to account for the unknown sign bit. This preserves 5472 // the existing sign bit so we can safely sign-extend the root back to the 5473 // original type. Otherwise, if we know the sign bit is zero, we will 5474 // zero-extend the root instead. 5475 // 5476 // FIXME: This is somewhat suboptimal, as there will be cases where adding 5477 // one to the maximum bit width will yield a larger-than-necessary 5478 // type. In general, we need to add an extra bit only if we can't 5479 // prove that the upper bit of the original type is equal to the 5480 // upper bit of the proposed smaller type. If these two bits are the 5481 // same (either zero or one) we know that sign-extending from the 5482 // smaller type will result in the same value. Here, since we can't 5483 // yet prove this, we are just making the proposed smaller type 5484 // larger to ensure correctness. 5485 if (!IsKnownPositive) 5486 ++MaxBitWidth; 5487 } 5488 5489 // Round MaxBitWidth up to the next power-of-two. 5490 if (!isPowerOf2_64(MaxBitWidth)) 5491 MaxBitWidth = NextPowerOf2(MaxBitWidth); 5492 5493 // If the maximum bit width we compute is less than the with of the roots' 5494 // type, we can proceed with the narrowing. Otherwise, do nothing. 5495 if (MaxBitWidth >= TreeRootIT->getBitWidth()) 5496 return; 5497 5498 // If we can truncate the root, we must collect additional values that might 5499 // be demoted as a result. That is, those seeded by truncations we will 5500 // modify. 5501 while (!Roots.empty()) 5502 collectValuesToDemote(Roots.pop_back_val(), Expr, ToDemote, Roots); 5503 5504 // Finally, map the values we can demote to the maximum bit with we computed. 5505 for (auto *Scalar : ToDemote) 5506 MinBWs[Scalar] = std::make_pair(MaxBitWidth, !IsKnownPositive); 5507 } 5508 5509 namespace { 5510 5511 /// The SLPVectorizer Pass. 5512 struct SLPVectorizer : public FunctionPass { 5513 SLPVectorizerPass Impl; 5514 5515 /// Pass identification, replacement for typeid 5516 static char ID; 5517 5518 explicit SLPVectorizer() : FunctionPass(ID) { 5519 initializeSLPVectorizerPass(*PassRegistry::getPassRegistry()); 5520 } 5521 5522 bool doInitialization(Module &M) override { 5523 return false; 5524 } 5525 5526 bool runOnFunction(Function &F) override { 5527 if (skipFunction(F)) 5528 return false; 5529 5530 auto *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 5531 auto *TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F); 5532 auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>(); 5533 auto *TLI = TLIP ? &TLIP->getTLI(F) : nullptr; 5534 auto *AA = &getAnalysis<AAResultsWrapperPass>().getAAResults(); 5535 auto *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 5536 auto *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 5537 auto *AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F); 5538 auto *DB = &getAnalysis<DemandedBitsWrapperPass>().getDemandedBits(); 5539 auto *ORE = &getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE(); 5540 5541 return Impl.runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 5542 } 5543 5544 void getAnalysisUsage(AnalysisUsage &AU) const override { 5545 FunctionPass::getAnalysisUsage(AU); 5546 AU.addRequired<AssumptionCacheTracker>(); 5547 AU.addRequired<ScalarEvolutionWrapperPass>(); 5548 AU.addRequired<AAResultsWrapperPass>(); 5549 AU.addRequired<TargetTransformInfoWrapperPass>(); 5550 AU.addRequired<LoopInfoWrapperPass>(); 5551 AU.addRequired<DominatorTreeWrapperPass>(); 5552 AU.addRequired<DemandedBitsWrapperPass>(); 5553 AU.addRequired<OptimizationRemarkEmitterWrapperPass>(); 5554 AU.addPreserved<LoopInfoWrapperPass>(); 5555 AU.addPreserved<DominatorTreeWrapperPass>(); 5556 AU.addPreserved<AAResultsWrapperPass>(); 5557 AU.addPreserved<GlobalsAAWrapperPass>(); 5558 AU.setPreservesCFG(); 5559 } 5560 }; 5561 5562 } // end anonymous namespace 5563 5564 PreservedAnalyses SLPVectorizerPass::run(Function &F, FunctionAnalysisManager &AM) { 5565 auto *SE = &AM.getResult<ScalarEvolutionAnalysis>(F); 5566 auto *TTI = &AM.getResult<TargetIRAnalysis>(F); 5567 auto *TLI = AM.getCachedResult<TargetLibraryAnalysis>(F); 5568 auto *AA = &AM.getResult<AAManager>(F); 5569 auto *LI = &AM.getResult<LoopAnalysis>(F); 5570 auto *DT = &AM.getResult<DominatorTreeAnalysis>(F); 5571 auto *AC = &AM.getResult<AssumptionAnalysis>(F); 5572 auto *DB = &AM.getResult<DemandedBitsAnalysis>(F); 5573 auto *ORE = &AM.getResult<OptimizationRemarkEmitterAnalysis>(F); 5574 5575 bool Changed = runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 5576 if (!Changed) 5577 return PreservedAnalyses::all(); 5578 5579 PreservedAnalyses PA; 5580 PA.preserveSet<CFGAnalyses>(); 5581 PA.preserve<AAManager>(); 5582 PA.preserve<GlobalsAA>(); 5583 return PA; 5584 } 5585 5586 bool SLPVectorizerPass::runImpl(Function &F, ScalarEvolution *SE_, 5587 TargetTransformInfo *TTI_, 5588 TargetLibraryInfo *TLI_, AliasAnalysis *AA_, 5589 LoopInfo *LI_, DominatorTree *DT_, 5590 AssumptionCache *AC_, DemandedBits *DB_, 5591 OptimizationRemarkEmitter *ORE_) { 5592 SE = SE_; 5593 TTI = TTI_; 5594 TLI = TLI_; 5595 AA = AA_; 5596 LI = LI_; 5597 DT = DT_; 5598 AC = AC_; 5599 DB = DB_; 5600 DL = &F.getParent()->getDataLayout(); 5601 5602 Stores.clear(); 5603 GEPs.clear(); 5604 bool Changed = false; 5605 5606 // If the target claims to have no vector registers don't attempt 5607 // vectorization. 5608 if (!TTI->getNumberOfRegisters(TTI->getRegisterClassForType(true))) 5609 return false; 5610 5611 // Don't vectorize when the attribute NoImplicitFloat is used. 5612 if (F.hasFnAttribute(Attribute::NoImplicitFloat)) 5613 return false; 5614 5615 LLVM_DEBUG(dbgs() << "SLP: Analyzing blocks in " << F.getName() << ".\n"); 5616 5617 // Use the bottom up slp vectorizer to construct chains that start with 5618 // store instructions. 5619 BoUpSLP R(&F, SE, TTI, TLI, AA, LI, DT, AC, DB, DL, ORE_); 5620 5621 // A general note: the vectorizer must use BoUpSLP::eraseInstruction() to 5622 // delete instructions. 5623 5624 // Scan the blocks in the function in post order. 5625 for (auto BB : post_order(&F.getEntryBlock())) { 5626 collectSeedInstructions(BB); 5627 5628 // Vectorize trees that end at stores. 5629 if (!Stores.empty()) { 5630 LLVM_DEBUG(dbgs() << "SLP: Found stores for " << Stores.size() 5631 << " underlying objects.\n"); 5632 Changed |= vectorizeStoreChains(R); 5633 } 5634 5635 // Vectorize trees that end at reductions. 5636 Changed |= vectorizeChainsInBlock(BB, R); 5637 5638 // Vectorize the index computations of getelementptr instructions. This 5639 // is primarily intended to catch gather-like idioms ending at 5640 // non-consecutive loads. 5641 if (!GEPs.empty()) { 5642 LLVM_DEBUG(dbgs() << "SLP: Found GEPs for " << GEPs.size() 5643 << " underlying objects.\n"); 5644 Changed |= vectorizeGEPIndices(BB, R); 5645 } 5646 } 5647 5648 if (Changed) { 5649 R.optimizeGatherSequence(); 5650 LLVM_DEBUG(dbgs() << "SLP: vectorized \"" << F.getName() << "\"\n"); 5651 LLVM_DEBUG(verifyFunction(F)); 5652 } 5653 return Changed; 5654 } 5655 5656 bool SLPVectorizerPass::vectorizeStoreChain(ArrayRef<Value *> Chain, BoUpSLP &R, 5657 unsigned Idx) { 5658 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " << Chain.size() 5659 << "\n"); 5660 const unsigned Sz = R.getVectorElementSize(Chain[0]); 5661 const unsigned MinVF = R.getMinVecRegSize() / Sz; 5662 unsigned VF = Chain.size(); 5663 5664 if (!isPowerOf2_32(Sz) || !isPowerOf2_32(VF) || VF < 2 || VF < MinVF) 5665 return false; 5666 5667 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << VF << " stores at offset " << Idx 5668 << "\n"); 5669 5670 R.buildTree(Chain); 5671 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 5672 // TODO: Handle orders of size less than number of elements in the vector. 5673 if (Order && Order->size() == Chain.size()) { 5674 // TODO: reorder tree nodes without tree rebuilding. 5675 SmallVector<Value *, 4> ReorderedOps(Chain.rbegin(), Chain.rend()); 5676 llvm::transform(*Order, ReorderedOps.begin(), 5677 [Chain](const unsigned Idx) { return Chain[Idx]; }); 5678 R.buildTree(ReorderedOps); 5679 } 5680 if (R.isTreeTinyAndNotFullyVectorizable()) 5681 return false; 5682 5683 R.computeMinimumValueSizes(); 5684 5685 int Cost = R.getTreeCost(); 5686 5687 LLVM_DEBUG(dbgs() << "SLP: Found cost=" << Cost << " for VF=" << VF << "\n"); 5688 if (Cost < -SLPCostThreshold) { 5689 LLVM_DEBUG(dbgs() << "SLP: Decided to vectorize cost=" << Cost << "\n"); 5690 5691 using namespace ore; 5692 5693 R.getORE()->emit(OptimizationRemark(SV_NAME, "StoresVectorized", 5694 cast<StoreInst>(Chain[0])) 5695 << "Stores SLP vectorized with cost " << NV("Cost", Cost) 5696 << " and with tree size " 5697 << NV("TreeSize", R.getTreeSize())); 5698 5699 R.vectorizeTree(); 5700 return true; 5701 } 5702 5703 return false; 5704 } 5705 5706 bool SLPVectorizerPass::vectorizeStores(ArrayRef<StoreInst *> Stores, 5707 BoUpSLP &R) { 5708 // We may run into multiple chains that merge into a single chain. We mark the 5709 // stores that we vectorized so that we don't visit the same store twice. 5710 BoUpSLP::ValueSet VectorizedStores; 5711 bool Changed = false; 5712 5713 int E = Stores.size(); 5714 SmallBitVector Tails(E, false); 5715 SmallVector<int, 16> ConsecutiveChain(E, E + 1); 5716 int MaxIter = MaxStoreLookup.getValue(); 5717 int IterCnt; 5718 auto &&FindConsecutiveAccess = [this, &Stores, &Tails, &IterCnt, MaxIter, 5719 &ConsecutiveChain](int K, int Idx) { 5720 if (IterCnt >= MaxIter) 5721 return true; 5722 ++IterCnt; 5723 if (!isConsecutiveAccess(Stores[K], Stores[Idx], *DL, *SE)) 5724 return false; 5725 5726 Tails.set(Idx); 5727 ConsecutiveChain[K] = Idx; 5728 return true; 5729 }; 5730 // Do a quadratic search on all of the given stores in reverse order and find 5731 // all of the pairs of stores that follow each other. 5732 for (int Idx = E - 1; Idx >= 0; --Idx) { 5733 // If a store has multiple consecutive store candidates, search according 5734 // to the sequence: Idx-1, Idx+1, Idx-2, Idx+2, ... 5735 // This is because usually pairing with immediate succeeding or preceding 5736 // candidate create the best chance to find slp vectorization opportunity. 5737 const int MaxLookDepth = std::max(E - Idx, Idx + 1); 5738 IterCnt = 0; 5739 for (int Offset = 1, F = MaxLookDepth; Offset < F; ++Offset) 5740 if ((Idx >= Offset && FindConsecutiveAccess(Idx - Offset, Idx)) || 5741 (Idx + Offset < E && FindConsecutiveAccess(Idx + Offset, Idx))) 5742 break; 5743 } 5744 5745 // For stores that start but don't end a link in the chain: 5746 for (int Cnt = E; Cnt > 0; --Cnt) { 5747 int I = Cnt - 1; 5748 if (ConsecutiveChain[I] == E + 1 || Tails.test(I)) 5749 continue; 5750 // We found a store instr that starts a chain. Now follow the chain and try 5751 // to vectorize it. 5752 BoUpSLP::ValueList Operands; 5753 // Collect the chain into a list. 5754 while (I != E + 1 && !VectorizedStores.count(Stores[I])) { 5755 Operands.push_back(Stores[I]); 5756 // Move to the next value in the chain. 5757 I = ConsecutiveChain[I]; 5758 } 5759 5760 // If a vector register can't hold 1 element, we are done. 5761 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 5762 unsigned EltSize = R.getVectorElementSize(Stores[0]); 5763 if (MaxVecRegSize % EltSize != 0) 5764 continue; 5765 5766 unsigned MaxElts = MaxVecRegSize / EltSize; 5767 // FIXME: Is division-by-2 the correct step? Should we assert that the 5768 // register size is a power-of-2? 5769 unsigned StartIdx = 0; 5770 for (unsigned Size = llvm::PowerOf2Ceil(MaxElts); Size >= 2; Size /= 2) { 5771 for (unsigned Cnt = StartIdx, E = Operands.size(); Cnt + Size <= E;) { 5772 ArrayRef<Value *> Slice = makeArrayRef(Operands).slice(Cnt, Size); 5773 if (!VectorizedStores.count(Slice.front()) && 5774 !VectorizedStores.count(Slice.back()) && 5775 vectorizeStoreChain(Slice, R, Cnt)) { 5776 // Mark the vectorized stores so that we don't vectorize them again. 5777 VectorizedStores.insert(Slice.begin(), Slice.end()); 5778 Changed = true; 5779 // If we vectorized initial block, no need to try to vectorize it 5780 // again. 5781 if (Cnt == StartIdx) 5782 StartIdx += Size; 5783 Cnt += Size; 5784 continue; 5785 } 5786 ++Cnt; 5787 } 5788 // Check if the whole array was vectorized already - exit. 5789 if (StartIdx >= Operands.size()) 5790 break; 5791 } 5792 } 5793 5794 return Changed; 5795 } 5796 5797 void SLPVectorizerPass::collectSeedInstructions(BasicBlock *BB) { 5798 // Initialize the collections. We will make a single pass over the block. 5799 Stores.clear(); 5800 GEPs.clear(); 5801 5802 // Visit the store and getelementptr instructions in BB and organize them in 5803 // Stores and GEPs according to the underlying objects of their pointer 5804 // operands. 5805 for (Instruction &I : *BB) { 5806 // Ignore store instructions that are volatile or have a pointer operand 5807 // that doesn't point to a scalar type. 5808 if (auto *SI = dyn_cast<StoreInst>(&I)) { 5809 if (!SI->isSimple()) 5810 continue; 5811 if (!isValidElementType(SI->getValueOperand()->getType())) 5812 continue; 5813 Stores[GetUnderlyingObject(SI->getPointerOperand(), *DL)].push_back(SI); 5814 } 5815 5816 // Ignore getelementptr instructions that have more than one index, a 5817 // constant index, or a pointer operand that doesn't point to a scalar 5818 // type. 5819 else if (auto *GEP = dyn_cast<GetElementPtrInst>(&I)) { 5820 auto Idx = GEP->idx_begin()->get(); 5821 if (GEP->getNumIndices() > 1 || isa<Constant>(Idx)) 5822 continue; 5823 if (!isValidElementType(Idx->getType())) 5824 continue; 5825 if (GEP->getType()->isVectorTy()) 5826 continue; 5827 GEPs[GEP->getPointerOperand()].push_back(GEP); 5828 } 5829 } 5830 } 5831 5832 bool SLPVectorizerPass::tryToVectorizePair(Value *A, Value *B, BoUpSLP &R) { 5833 if (!A || !B) 5834 return false; 5835 Value *VL[] = { A, B }; 5836 return tryToVectorizeList(VL, R, /*UserCost=*/0, true); 5837 } 5838 5839 bool SLPVectorizerPass::tryToVectorizeList(ArrayRef<Value *> VL, BoUpSLP &R, 5840 int UserCost, bool AllowReorder) { 5841 if (VL.size() < 2) 5842 return false; 5843 5844 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize a list of length = " 5845 << VL.size() << ".\n"); 5846 5847 // Check that all of the parts are scalar instructions of the same type, 5848 // we permit an alternate opcode via InstructionsState. 5849 InstructionsState S = getSameOpcode(VL); 5850 if (!S.getOpcode()) 5851 return false; 5852 5853 Instruction *I0 = cast<Instruction>(S.OpValue); 5854 unsigned Sz = R.getVectorElementSize(I0); 5855 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / Sz); 5856 unsigned MaxVF = std::max<unsigned>(PowerOf2Floor(VL.size()), MinVF); 5857 if (MaxVF < 2) { 5858 R.getORE()->emit([&]() { 5859 return OptimizationRemarkMissed(SV_NAME, "SmallVF", I0) 5860 << "Cannot SLP vectorize list: vectorization factor " 5861 << "less than 2 is not supported"; 5862 }); 5863 return false; 5864 } 5865 5866 for (Value *V : VL) { 5867 Type *Ty = V->getType(); 5868 if (!isValidElementType(Ty)) { 5869 // NOTE: the following will give user internal llvm type name, which may 5870 // not be useful. 5871 R.getORE()->emit([&]() { 5872 std::string type_str; 5873 llvm::raw_string_ostream rso(type_str); 5874 Ty->print(rso); 5875 return OptimizationRemarkMissed(SV_NAME, "UnsupportedType", I0) 5876 << "Cannot SLP vectorize list: type " 5877 << rso.str() + " is unsupported by vectorizer"; 5878 }); 5879 return false; 5880 } 5881 } 5882 5883 bool Changed = false; 5884 bool CandidateFound = false; 5885 int MinCost = SLPCostThreshold; 5886 5887 unsigned NextInst = 0, MaxInst = VL.size(); 5888 for (unsigned VF = MaxVF; NextInst + 1 < MaxInst && VF >= MinVF; VF /= 2) { 5889 // No actual vectorization should happen, if number of parts is the same as 5890 // provided vectorization factor (i.e. the scalar type is used for vector 5891 // code during codegen). 5892 auto *VecTy = VectorType::get(VL[0]->getType(), VF); 5893 if (TTI->getNumberOfParts(VecTy) == VF) 5894 continue; 5895 for (unsigned I = NextInst; I < MaxInst; ++I) { 5896 unsigned OpsWidth = 0; 5897 5898 if (I + VF > MaxInst) 5899 OpsWidth = MaxInst - I; 5900 else 5901 OpsWidth = VF; 5902 5903 if (!isPowerOf2_32(OpsWidth) || OpsWidth < 2) 5904 break; 5905 5906 ArrayRef<Value *> Ops = VL.slice(I, OpsWidth); 5907 // Check that a previous iteration of this loop did not delete the Value. 5908 if (llvm::any_of(Ops, [&R](Value *V) { 5909 auto *I = dyn_cast<Instruction>(V); 5910 return I && R.isDeleted(I); 5911 })) 5912 continue; 5913 5914 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << OpsWidth << " operations " 5915 << "\n"); 5916 5917 R.buildTree(Ops); 5918 Optional<ArrayRef<unsigned>> Order = R.bestOrder(); 5919 // TODO: check if we can allow reordering for more cases. 5920 if (AllowReorder && Order) { 5921 // TODO: reorder tree nodes without tree rebuilding. 5922 // Conceptually, there is nothing actually preventing us from trying to 5923 // reorder a larger list. In fact, we do exactly this when vectorizing 5924 // reductions. However, at this point, we only expect to get here when 5925 // there are exactly two operations. 5926 assert(Ops.size() == 2); 5927 Value *ReorderedOps[] = {Ops[1], Ops[0]}; 5928 R.buildTree(ReorderedOps, None); 5929 } 5930 if (R.isTreeTinyAndNotFullyVectorizable()) 5931 continue; 5932 5933 R.computeMinimumValueSizes(); 5934 int Cost = R.getTreeCost() - UserCost; 5935 CandidateFound = true; 5936 MinCost = std::min(MinCost, Cost); 5937 5938 if (Cost < -SLPCostThreshold) { 5939 LLVM_DEBUG(dbgs() << "SLP: Vectorizing list at cost:" << Cost << ".\n"); 5940 R.getORE()->emit(OptimizationRemark(SV_NAME, "VectorizedList", 5941 cast<Instruction>(Ops[0])) 5942 << "SLP vectorized with cost " << ore::NV("Cost", Cost) 5943 << " and with tree size " 5944 << ore::NV("TreeSize", R.getTreeSize())); 5945 5946 R.vectorizeTree(); 5947 // Move to the next bundle. 5948 I += VF - 1; 5949 NextInst = I + 1; 5950 Changed = true; 5951 } 5952 } 5953 } 5954 5955 if (!Changed && CandidateFound) { 5956 R.getORE()->emit([&]() { 5957 return OptimizationRemarkMissed(SV_NAME, "NotBeneficial", I0) 5958 << "List vectorization was possible but not beneficial with cost " 5959 << ore::NV("Cost", MinCost) << " >= " 5960 << ore::NV("Treshold", -SLPCostThreshold); 5961 }); 5962 } else if (!Changed) { 5963 R.getORE()->emit([&]() { 5964 return OptimizationRemarkMissed(SV_NAME, "NotPossible", I0) 5965 << "Cannot SLP vectorize list: vectorization was impossible" 5966 << " with available vectorization factors"; 5967 }); 5968 } 5969 return Changed; 5970 } 5971 5972 bool SLPVectorizerPass::tryToVectorize(Instruction *I, BoUpSLP &R) { 5973 if (!I) 5974 return false; 5975 5976 if (!isa<BinaryOperator>(I) && !isa<CmpInst>(I)) 5977 return false; 5978 5979 Value *P = I->getParent(); 5980 5981 // Vectorize in current basic block only. 5982 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 5983 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 5984 if (!Op0 || !Op1 || Op0->getParent() != P || Op1->getParent() != P) 5985 return false; 5986 5987 // Try to vectorize V. 5988 if (tryToVectorizePair(Op0, Op1, R)) 5989 return true; 5990 5991 auto *A = dyn_cast<BinaryOperator>(Op0); 5992 auto *B = dyn_cast<BinaryOperator>(Op1); 5993 // Try to skip B. 5994 if (B && B->hasOneUse()) { 5995 auto *B0 = dyn_cast<BinaryOperator>(B->getOperand(0)); 5996 auto *B1 = dyn_cast<BinaryOperator>(B->getOperand(1)); 5997 if (B0 && B0->getParent() == P && tryToVectorizePair(A, B0, R)) 5998 return true; 5999 if (B1 && B1->getParent() == P && tryToVectorizePair(A, B1, R)) 6000 return true; 6001 } 6002 6003 // Try to skip A. 6004 if (A && A->hasOneUse()) { 6005 auto *A0 = dyn_cast<BinaryOperator>(A->getOperand(0)); 6006 auto *A1 = dyn_cast<BinaryOperator>(A->getOperand(1)); 6007 if (A0 && A0->getParent() == P && tryToVectorizePair(A0, B, R)) 6008 return true; 6009 if (A1 && A1->getParent() == P && tryToVectorizePair(A1, B, R)) 6010 return true; 6011 } 6012 return false; 6013 } 6014 6015 /// Generate a shuffle mask to be used in a reduction tree. 6016 /// 6017 /// \param VecLen The length of the vector to be reduced. 6018 /// \param NumEltsToRdx The number of elements that should be reduced in the 6019 /// vector. 6020 /// \param IsPairwise Whether the reduction is a pairwise or splitting 6021 /// reduction. A pairwise reduction will generate a mask of 6022 /// <0,2,...> or <1,3,..> while a splitting reduction will generate 6023 /// <2,3, undef,undef> for a vector of 4 and NumElts = 2. 6024 /// \param IsLeft True will generate a mask of even elements, odd otherwise. 6025 static Value *createRdxShuffleMask(unsigned VecLen, unsigned NumEltsToRdx, 6026 bool IsPairwise, bool IsLeft, 6027 IRBuilder<> &Builder) { 6028 assert((IsPairwise || !IsLeft) && "Don't support a <0,1,undef,...> mask"); 6029 6030 SmallVector<Constant *, 32> ShuffleMask( 6031 VecLen, UndefValue::get(Builder.getInt32Ty())); 6032 6033 if (IsPairwise) 6034 // Build a mask of 0, 2, ... (left) or 1, 3, ... (right). 6035 for (unsigned i = 0; i != NumEltsToRdx; ++i) 6036 ShuffleMask[i] = Builder.getInt32(2 * i + !IsLeft); 6037 else 6038 // Move the upper half of the vector to the lower half. 6039 for (unsigned i = 0; i != NumEltsToRdx; ++i) 6040 ShuffleMask[i] = Builder.getInt32(NumEltsToRdx + i); 6041 6042 return ConstantVector::get(ShuffleMask); 6043 } 6044 6045 namespace { 6046 6047 /// Model horizontal reductions. 6048 /// 6049 /// A horizontal reduction is a tree of reduction operations (currently add and 6050 /// fadd) that has operations that can be put into a vector as its leaf. 6051 /// For example, this tree: 6052 /// 6053 /// mul mul mul mul 6054 /// \ / \ / 6055 /// + + 6056 /// \ / 6057 /// + 6058 /// This tree has "mul" as its reduced values and "+" as its reduction 6059 /// operations. A reduction might be feeding into a store or a binary operation 6060 /// feeding a phi. 6061 /// ... 6062 /// \ / 6063 /// + 6064 /// | 6065 /// phi += 6066 /// 6067 /// Or: 6068 /// ... 6069 /// \ / 6070 /// + 6071 /// | 6072 /// *p = 6073 /// 6074 class HorizontalReduction { 6075 using ReductionOpsType = SmallVector<Value *, 16>; 6076 using ReductionOpsListType = SmallVector<ReductionOpsType, 2>; 6077 ReductionOpsListType ReductionOps; 6078 SmallVector<Value *, 32> ReducedVals; 6079 // Use map vector to make stable output. 6080 MapVector<Instruction *, Value *> ExtraArgs; 6081 6082 /// Kind of the reduction data. 6083 enum ReductionKind { 6084 RK_None, /// Not a reduction. 6085 RK_Arithmetic, /// Binary reduction data. 6086 RK_Min, /// Minimum reduction data. 6087 RK_UMin, /// Unsigned minimum reduction data. 6088 RK_Max, /// Maximum reduction data. 6089 RK_UMax, /// Unsigned maximum reduction data. 6090 }; 6091 6092 /// Contains info about operation, like its opcode, left and right operands. 6093 class OperationData { 6094 /// Opcode of the instruction. 6095 unsigned Opcode = 0; 6096 6097 /// Left operand of the reduction operation. 6098 Value *LHS = nullptr; 6099 6100 /// Right operand of the reduction operation. 6101 Value *RHS = nullptr; 6102 6103 /// Kind of the reduction operation. 6104 ReductionKind Kind = RK_None; 6105 6106 /// True if float point min/max reduction has no NaNs. 6107 bool NoNaN = false; 6108 6109 /// Checks if the reduction operation can be vectorized. 6110 bool isVectorizable() const { 6111 return LHS && RHS && 6112 // We currently only support add/mul/logical && min/max reductions. 6113 ((Kind == RK_Arithmetic && 6114 (Opcode == Instruction::Add || Opcode == Instruction::FAdd || 6115 Opcode == Instruction::Mul || Opcode == Instruction::FMul || 6116 Opcode == Instruction::And || Opcode == Instruction::Or || 6117 Opcode == Instruction::Xor)) || 6118 ((Opcode == Instruction::ICmp || Opcode == Instruction::FCmp) && 6119 (Kind == RK_Min || Kind == RK_Max)) || 6120 (Opcode == Instruction::ICmp && 6121 (Kind == RK_UMin || Kind == RK_UMax))); 6122 } 6123 6124 /// Creates reduction operation with the current opcode. 6125 Value *createOp(IRBuilder<> &Builder, const Twine &Name) const { 6126 assert(isVectorizable() && 6127 "Expected add|fadd or min/max reduction operation."); 6128 Value *Cmp = nullptr; 6129 switch (Kind) { 6130 case RK_Arithmetic: 6131 return Builder.CreateBinOp((Instruction::BinaryOps)Opcode, LHS, RHS, 6132 Name); 6133 case RK_Min: 6134 Cmp = Opcode == Instruction::ICmp ? Builder.CreateICmpSLT(LHS, RHS) 6135 : Builder.CreateFCmpOLT(LHS, RHS); 6136 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6137 case RK_Max: 6138 Cmp = Opcode == Instruction::ICmp ? Builder.CreateICmpSGT(LHS, RHS) 6139 : Builder.CreateFCmpOGT(LHS, RHS); 6140 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6141 case RK_UMin: 6142 assert(Opcode == Instruction::ICmp && "Expected integer types."); 6143 Cmp = Builder.CreateICmpULT(LHS, RHS); 6144 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6145 case RK_UMax: 6146 assert(Opcode == Instruction::ICmp && "Expected integer types."); 6147 Cmp = Builder.CreateICmpUGT(LHS, RHS); 6148 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 6149 case RK_None: 6150 break; 6151 } 6152 llvm_unreachable("Unknown reduction operation."); 6153 } 6154 6155 public: 6156 explicit OperationData() = default; 6157 6158 /// Construction for reduced values. They are identified by opcode only and 6159 /// don't have associated LHS/RHS values. 6160 explicit OperationData(Value *V) { 6161 if (auto *I = dyn_cast<Instruction>(V)) 6162 Opcode = I->getOpcode(); 6163 } 6164 6165 /// Constructor for reduction operations with opcode and its left and 6166 /// right operands. 6167 OperationData(unsigned Opcode, Value *LHS, Value *RHS, ReductionKind Kind, 6168 bool NoNaN = false) 6169 : Opcode(Opcode), LHS(LHS), RHS(RHS), Kind(Kind), NoNaN(NoNaN) { 6170 assert(Kind != RK_None && "One of the reduction operations is expected."); 6171 } 6172 6173 explicit operator bool() const { return Opcode; } 6174 6175 /// Return true if this operation is any kind of minimum or maximum. 6176 bool isMinMax() const { 6177 switch (Kind) { 6178 case RK_Arithmetic: 6179 return false; 6180 case RK_Min: 6181 case RK_Max: 6182 case RK_UMin: 6183 case RK_UMax: 6184 return true; 6185 case RK_None: 6186 break; 6187 } 6188 llvm_unreachable("Reduction kind is not set"); 6189 } 6190 6191 /// Get the index of the first operand. 6192 unsigned getFirstOperandIndex() const { 6193 assert(!!*this && "The opcode is not set."); 6194 // We allow calling this before 'Kind' is set, so handle that specially. 6195 if (Kind == RK_None) 6196 return 0; 6197 return isMinMax() ? 1 : 0; 6198 } 6199 6200 /// Total number of operands in the reduction operation. 6201 unsigned getNumberOfOperands() const { 6202 assert(Kind != RK_None && !!*this && LHS && RHS && 6203 "Expected reduction operation."); 6204 return isMinMax() ? 3 : 2; 6205 } 6206 6207 /// Checks if the operation has the same parent as \p P. 6208 bool hasSameParent(Instruction *I, Value *P, bool IsRedOp) const { 6209 assert(Kind != RK_None && !!*this && LHS && RHS && 6210 "Expected reduction operation."); 6211 if (!IsRedOp) 6212 return I->getParent() == P; 6213 if (isMinMax()) { 6214 // SelectInst must be used twice while the condition op must have single 6215 // use only. 6216 auto *Cmp = cast<Instruction>(cast<SelectInst>(I)->getCondition()); 6217 return I->getParent() == P && Cmp && Cmp->getParent() == P; 6218 } 6219 // Arithmetic reduction operation must be used once only. 6220 return I->getParent() == P; 6221 } 6222 6223 /// Expected number of uses for reduction operations/reduced values. 6224 bool hasRequiredNumberOfUses(Instruction *I, bool IsReductionOp) const { 6225 assert(Kind != RK_None && !!*this && LHS && RHS && 6226 "Expected reduction operation."); 6227 if (isMinMax()) 6228 return I->hasNUses(2) && 6229 (!IsReductionOp || 6230 cast<SelectInst>(I)->getCondition()->hasOneUse()); 6231 return I->hasOneUse(); 6232 } 6233 6234 /// Initializes the list of reduction operations. 6235 void initReductionOps(ReductionOpsListType &ReductionOps) { 6236 assert(Kind != RK_None && !!*this && LHS && RHS && 6237 "Expected reduction operation."); 6238 if (isMinMax()) 6239 ReductionOps.assign(2, ReductionOpsType()); 6240 else 6241 ReductionOps.assign(1, ReductionOpsType()); 6242 } 6243 6244 /// Add all reduction operations for the reduction instruction \p I. 6245 void addReductionOps(Instruction *I, ReductionOpsListType &ReductionOps) { 6246 assert(Kind != RK_None && !!*this && LHS && RHS && 6247 "Expected reduction operation."); 6248 if (isMinMax()) { 6249 ReductionOps[0].emplace_back(cast<SelectInst>(I)->getCondition()); 6250 ReductionOps[1].emplace_back(I); 6251 } else { 6252 ReductionOps[0].emplace_back(I); 6253 } 6254 } 6255 6256 /// Checks if instruction is associative and can be vectorized. 6257 bool isAssociative(Instruction *I) const { 6258 assert(Kind != RK_None && *this && LHS && RHS && 6259 "Expected reduction operation."); 6260 switch (Kind) { 6261 case RK_Arithmetic: 6262 return I->isAssociative(); 6263 case RK_Min: 6264 case RK_Max: 6265 return Opcode == Instruction::ICmp || 6266 cast<Instruction>(I->getOperand(0))->isFast(); 6267 case RK_UMin: 6268 case RK_UMax: 6269 assert(Opcode == Instruction::ICmp && 6270 "Only integer compare operation is expected."); 6271 return true; 6272 case RK_None: 6273 break; 6274 } 6275 llvm_unreachable("Reduction kind is not set"); 6276 } 6277 6278 /// Checks if the reduction operation can be vectorized. 6279 bool isVectorizable(Instruction *I) const { 6280 return isVectorizable() && isAssociative(I); 6281 } 6282 6283 /// Checks if two operation data are both a reduction op or both a reduced 6284 /// value. 6285 bool operator==(const OperationData &OD) const { 6286 assert(((Kind != OD.Kind) || ((!LHS == !OD.LHS) && (!RHS == !OD.RHS))) && 6287 "One of the comparing operations is incorrect."); 6288 return this == &OD || (Kind == OD.Kind && Opcode == OD.Opcode); 6289 } 6290 bool operator!=(const OperationData &OD) const { return !(*this == OD); } 6291 void clear() { 6292 Opcode = 0; 6293 LHS = nullptr; 6294 RHS = nullptr; 6295 Kind = RK_None; 6296 NoNaN = false; 6297 } 6298 6299 /// Get the opcode of the reduction operation. 6300 unsigned getOpcode() const { 6301 assert(isVectorizable() && "Expected vectorizable operation."); 6302 return Opcode; 6303 } 6304 6305 /// Get kind of reduction data. 6306 ReductionKind getKind() const { return Kind; } 6307 Value *getLHS() const { return LHS; } 6308 Value *getRHS() const { return RHS; } 6309 Type *getConditionType() const { 6310 return isMinMax() ? CmpInst::makeCmpResultType(LHS->getType()) : nullptr; 6311 } 6312 6313 /// Creates reduction operation with the current opcode with the IR flags 6314 /// from \p ReductionOps. 6315 Value *createOp(IRBuilder<> &Builder, const Twine &Name, 6316 const ReductionOpsListType &ReductionOps) const { 6317 assert(isVectorizable() && 6318 "Expected add|fadd or min/max reduction operation."); 6319 auto *Op = createOp(Builder, Name); 6320 switch (Kind) { 6321 case RK_Arithmetic: 6322 propagateIRFlags(Op, ReductionOps[0]); 6323 return Op; 6324 case RK_Min: 6325 case RK_Max: 6326 case RK_UMin: 6327 case RK_UMax: 6328 if (auto *SI = dyn_cast<SelectInst>(Op)) 6329 propagateIRFlags(SI->getCondition(), ReductionOps[0]); 6330 propagateIRFlags(Op, ReductionOps[1]); 6331 return Op; 6332 case RK_None: 6333 break; 6334 } 6335 llvm_unreachable("Unknown reduction operation."); 6336 } 6337 /// Creates reduction operation with the current opcode with the IR flags 6338 /// from \p I. 6339 Value *createOp(IRBuilder<> &Builder, const Twine &Name, 6340 Instruction *I) const { 6341 assert(isVectorizable() && 6342 "Expected add|fadd or min/max reduction operation."); 6343 auto *Op = createOp(Builder, Name); 6344 switch (Kind) { 6345 case RK_Arithmetic: 6346 propagateIRFlags(Op, I); 6347 return Op; 6348 case RK_Min: 6349 case RK_Max: 6350 case RK_UMin: 6351 case RK_UMax: 6352 if (auto *SI = dyn_cast<SelectInst>(Op)) { 6353 propagateIRFlags(SI->getCondition(), 6354 cast<SelectInst>(I)->getCondition()); 6355 } 6356 propagateIRFlags(Op, I); 6357 return Op; 6358 case RK_None: 6359 break; 6360 } 6361 llvm_unreachable("Unknown reduction operation."); 6362 } 6363 6364 TargetTransformInfo::ReductionFlags getFlags() const { 6365 TargetTransformInfo::ReductionFlags Flags; 6366 Flags.NoNaN = NoNaN; 6367 switch (Kind) { 6368 case RK_Arithmetic: 6369 break; 6370 case RK_Min: 6371 Flags.IsSigned = Opcode == Instruction::ICmp; 6372 Flags.IsMaxOp = false; 6373 break; 6374 case RK_Max: 6375 Flags.IsSigned = Opcode == Instruction::ICmp; 6376 Flags.IsMaxOp = true; 6377 break; 6378 case RK_UMin: 6379 Flags.IsSigned = false; 6380 Flags.IsMaxOp = false; 6381 break; 6382 case RK_UMax: 6383 Flags.IsSigned = false; 6384 Flags.IsMaxOp = true; 6385 break; 6386 case RK_None: 6387 llvm_unreachable("Reduction kind is not set"); 6388 } 6389 return Flags; 6390 } 6391 }; 6392 6393 WeakTrackingVH ReductionRoot; 6394 6395 /// The operation data of the reduction operation. 6396 OperationData ReductionData; 6397 6398 /// The operation data of the values we perform a reduction on. 6399 OperationData ReducedValueData; 6400 6401 /// Should we model this reduction as a pairwise reduction tree or a tree that 6402 /// splits the vector in halves and adds those halves. 6403 bool IsPairwiseReduction = false; 6404 6405 /// Checks if the ParentStackElem.first should be marked as a reduction 6406 /// operation with an extra argument or as extra argument itself. 6407 void markExtraArg(std::pair<Instruction *, unsigned> &ParentStackElem, 6408 Value *ExtraArg) { 6409 if (ExtraArgs.count(ParentStackElem.first)) { 6410 ExtraArgs[ParentStackElem.first] = nullptr; 6411 // We ran into something like: 6412 // ParentStackElem.first = ExtraArgs[ParentStackElem.first] + ExtraArg. 6413 // The whole ParentStackElem.first should be considered as an extra value 6414 // in this case. 6415 // Do not perform analysis of remaining operands of ParentStackElem.first 6416 // instruction, this whole instruction is an extra argument. 6417 ParentStackElem.second = ParentStackElem.first->getNumOperands(); 6418 } else { 6419 // We ran into something like: 6420 // ParentStackElem.first += ... + ExtraArg + ... 6421 ExtraArgs[ParentStackElem.first] = ExtraArg; 6422 } 6423 } 6424 6425 static OperationData getOperationData(Value *V) { 6426 if (!V) 6427 return OperationData(); 6428 6429 Value *LHS; 6430 Value *RHS; 6431 if (m_BinOp(m_Value(LHS), m_Value(RHS)).match(V)) { 6432 return OperationData(cast<BinaryOperator>(V)->getOpcode(), LHS, RHS, 6433 RK_Arithmetic); 6434 } 6435 if (auto *Select = dyn_cast<SelectInst>(V)) { 6436 // Look for a min/max pattern. 6437 if (m_UMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 6438 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMin); 6439 } else if (m_SMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 6440 return OperationData(Instruction::ICmp, LHS, RHS, RK_Min); 6441 } else if (m_OrdFMin(m_Value(LHS), m_Value(RHS)).match(Select) || 6442 m_UnordFMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 6443 return OperationData( 6444 Instruction::FCmp, LHS, RHS, RK_Min, 6445 cast<Instruction>(Select->getCondition())->hasNoNaNs()); 6446 } else if (m_UMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 6447 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMax); 6448 } else if (m_SMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 6449 return OperationData(Instruction::ICmp, LHS, RHS, RK_Max); 6450 } else if (m_OrdFMax(m_Value(LHS), m_Value(RHS)).match(Select) || 6451 m_UnordFMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 6452 return OperationData( 6453 Instruction::FCmp, LHS, RHS, RK_Max, 6454 cast<Instruction>(Select->getCondition())->hasNoNaNs()); 6455 } else { 6456 // Try harder: look for min/max pattern based on instructions producing 6457 // same values such as: select ((cmp Inst1, Inst2), Inst1, Inst2). 6458 // During the intermediate stages of SLP, it's very common to have 6459 // pattern like this (since optimizeGatherSequence is run only once 6460 // at the end): 6461 // %1 = extractelement <2 x i32> %a, i32 0 6462 // %2 = extractelement <2 x i32> %a, i32 1 6463 // %cond = icmp sgt i32 %1, %2 6464 // %3 = extractelement <2 x i32> %a, i32 0 6465 // %4 = extractelement <2 x i32> %a, i32 1 6466 // %select = select i1 %cond, i32 %3, i32 %4 6467 CmpInst::Predicate Pred; 6468 Instruction *L1; 6469 Instruction *L2; 6470 6471 LHS = Select->getTrueValue(); 6472 RHS = Select->getFalseValue(); 6473 Value *Cond = Select->getCondition(); 6474 6475 // TODO: Support inverse predicates. 6476 if (match(Cond, m_Cmp(Pred, m_Specific(LHS), m_Instruction(L2)))) { 6477 if (!isa<ExtractElementInst>(RHS) || 6478 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6479 return OperationData(V); 6480 } else if (match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Specific(RHS)))) { 6481 if (!isa<ExtractElementInst>(LHS) || 6482 !L1->isIdenticalTo(cast<Instruction>(LHS))) 6483 return OperationData(V); 6484 } else { 6485 if (!isa<ExtractElementInst>(LHS) || !isa<ExtractElementInst>(RHS)) 6486 return OperationData(V); 6487 if (!match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Instruction(L2))) || 6488 !L1->isIdenticalTo(cast<Instruction>(LHS)) || 6489 !L2->isIdenticalTo(cast<Instruction>(RHS))) 6490 return OperationData(V); 6491 } 6492 switch (Pred) { 6493 default: 6494 return OperationData(V); 6495 6496 case CmpInst::ICMP_ULT: 6497 case CmpInst::ICMP_ULE: 6498 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMin); 6499 6500 case CmpInst::ICMP_SLT: 6501 case CmpInst::ICMP_SLE: 6502 return OperationData(Instruction::ICmp, LHS, RHS, RK_Min); 6503 6504 case CmpInst::FCMP_OLT: 6505 case CmpInst::FCMP_OLE: 6506 case CmpInst::FCMP_ULT: 6507 case CmpInst::FCMP_ULE: 6508 return OperationData(Instruction::FCmp, LHS, RHS, RK_Min, 6509 cast<Instruction>(Cond)->hasNoNaNs()); 6510 6511 case CmpInst::ICMP_UGT: 6512 case CmpInst::ICMP_UGE: 6513 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMax); 6514 6515 case CmpInst::ICMP_SGT: 6516 case CmpInst::ICMP_SGE: 6517 return OperationData(Instruction::ICmp, LHS, RHS, RK_Max); 6518 6519 case CmpInst::FCMP_OGT: 6520 case CmpInst::FCMP_OGE: 6521 case CmpInst::FCMP_UGT: 6522 case CmpInst::FCMP_UGE: 6523 return OperationData(Instruction::FCmp, LHS, RHS, RK_Max, 6524 cast<Instruction>(Cond)->hasNoNaNs()); 6525 } 6526 } 6527 } 6528 return OperationData(V); 6529 } 6530 6531 public: 6532 HorizontalReduction() = default; 6533 6534 /// Try to find a reduction tree. 6535 bool matchAssociativeReduction(PHINode *Phi, Instruction *B) { 6536 assert((!Phi || is_contained(Phi->operands(), B)) && 6537 "Thi phi needs to use the binary operator"); 6538 6539 ReductionData = getOperationData(B); 6540 6541 // We could have a initial reductions that is not an add. 6542 // r *= v1 + v2 + v3 + v4 6543 // In such a case start looking for a tree rooted in the first '+'. 6544 if (Phi) { 6545 if (ReductionData.getLHS() == Phi) { 6546 Phi = nullptr; 6547 B = dyn_cast<Instruction>(ReductionData.getRHS()); 6548 ReductionData = getOperationData(B); 6549 } else if (ReductionData.getRHS() == Phi) { 6550 Phi = nullptr; 6551 B = dyn_cast<Instruction>(ReductionData.getLHS()); 6552 ReductionData = getOperationData(B); 6553 } 6554 } 6555 6556 if (!ReductionData.isVectorizable(B)) 6557 return false; 6558 6559 Type *Ty = B->getType(); 6560 if (!isValidElementType(Ty)) 6561 return false; 6562 if (!Ty->isIntOrIntVectorTy() && !Ty->isFPOrFPVectorTy()) 6563 return false; 6564 6565 ReducedValueData.clear(); 6566 ReductionRoot = B; 6567 6568 // Post order traverse the reduction tree starting at B. We only handle true 6569 // trees containing only binary operators. 6570 SmallVector<std::pair<Instruction *, unsigned>, 32> Stack; 6571 Stack.push_back(std::make_pair(B, ReductionData.getFirstOperandIndex())); 6572 ReductionData.initReductionOps(ReductionOps); 6573 while (!Stack.empty()) { 6574 Instruction *TreeN = Stack.back().first; 6575 unsigned EdgeToVist = Stack.back().second++; 6576 OperationData OpData = getOperationData(TreeN); 6577 bool IsReducedValue = OpData != ReductionData; 6578 6579 // Postorder vist. 6580 if (IsReducedValue || EdgeToVist == OpData.getNumberOfOperands()) { 6581 if (IsReducedValue) 6582 ReducedVals.push_back(TreeN); 6583 else { 6584 auto I = ExtraArgs.find(TreeN); 6585 if (I != ExtraArgs.end() && !I->second) { 6586 // Check if TreeN is an extra argument of its parent operation. 6587 if (Stack.size() <= 1) { 6588 // TreeN can't be an extra argument as it is a root reduction 6589 // operation. 6590 return false; 6591 } 6592 // Yes, TreeN is an extra argument, do not add it to a list of 6593 // reduction operations. 6594 // Stack[Stack.size() - 2] always points to the parent operation. 6595 markExtraArg(Stack[Stack.size() - 2], TreeN); 6596 ExtraArgs.erase(TreeN); 6597 } else 6598 ReductionData.addReductionOps(TreeN, ReductionOps); 6599 } 6600 // Retract. 6601 Stack.pop_back(); 6602 continue; 6603 } 6604 6605 // Visit left or right. 6606 Value *NextV = TreeN->getOperand(EdgeToVist); 6607 if (NextV != Phi) { 6608 auto *I = dyn_cast<Instruction>(NextV); 6609 OpData = getOperationData(I); 6610 // Continue analysis if the next operand is a reduction operation or 6611 // (possibly) a reduced value. If the reduced value opcode is not set, 6612 // the first met operation != reduction operation is considered as the 6613 // reduced value class. 6614 if (I && (!ReducedValueData || OpData == ReducedValueData || 6615 OpData == ReductionData)) { 6616 const bool IsReductionOperation = OpData == ReductionData; 6617 // Only handle trees in the current basic block. 6618 if (!ReductionData.hasSameParent(I, B->getParent(), 6619 IsReductionOperation)) { 6620 // I is an extra argument for TreeN (its parent operation). 6621 markExtraArg(Stack.back(), I); 6622 continue; 6623 } 6624 6625 // Each tree node needs to have minimal number of users except for the 6626 // ultimate reduction. 6627 if (!ReductionData.hasRequiredNumberOfUses(I, 6628 OpData == ReductionData) && 6629 I != B) { 6630 // I is an extra argument for TreeN (its parent operation). 6631 markExtraArg(Stack.back(), I); 6632 continue; 6633 } 6634 6635 if (IsReductionOperation) { 6636 // We need to be able to reassociate the reduction operations. 6637 if (!OpData.isAssociative(I)) { 6638 // I is an extra argument for TreeN (its parent operation). 6639 markExtraArg(Stack.back(), I); 6640 continue; 6641 } 6642 } else if (ReducedValueData && 6643 ReducedValueData != OpData) { 6644 // Make sure that the opcodes of the operations that we are going to 6645 // reduce match. 6646 // I is an extra argument for TreeN (its parent operation). 6647 markExtraArg(Stack.back(), I); 6648 continue; 6649 } else if (!ReducedValueData) 6650 ReducedValueData = OpData; 6651 6652 Stack.push_back(std::make_pair(I, OpData.getFirstOperandIndex())); 6653 continue; 6654 } 6655 } 6656 // NextV is an extra argument for TreeN (its parent operation). 6657 markExtraArg(Stack.back(), NextV); 6658 } 6659 return true; 6660 } 6661 6662 /// Attempt to vectorize the tree found by 6663 /// matchAssociativeReduction. 6664 bool tryToReduce(BoUpSLP &V, TargetTransformInfo *TTI) { 6665 if (ReducedVals.empty()) 6666 return false; 6667 6668 // If there is a sufficient number of reduction values, reduce 6669 // to a nearby power-of-2. Can safely generate oversized 6670 // vectors and rely on the backend to split them to legal sizes. 6671 unsigned NumReducedVals = ReducedVals.size(); 6672 if (NumReducedVals < 4) 6673 return false; 6674 6675 unsigned ReduxWidth = PowerOf2Floor(NumReducedVals); 6676 6677 Value *VectorizedTree = nullptr; 6678 6679 // FIXME: Fast-math-flags should be set based on the instructions in the 6680 // reduction (not all of 'fast' are required). 6681 IRBuilder<> Builder(cast<Instruction>(ReductionRoot)); 6682 FastMathFlags Unsafe; 6683 Unsafe.setFast(); 6684 Builder.setFastMathFlags(Unsafe); 6685 unsigned i = 0; 6686 6687 BoUpSLP::ExtraValueToDebugLocsMap ExternallyUsedValues; 6688 // The same extra argument may be used several time, so log each attempt 6689 // to use it. 6690 for (auto &Pair : ExtraArgs) { 6691 assert(Pair.first && "DebugLoc must be set."); 6692 ExternallyUsedValues[Pair.second].push_back(Pair.first); 6693 } 6694 6695 // The compare instruction of a min/max is the insertion point for new 6696 // instructions and may be replaced with a new compare instruction. 6697 auto getCmpForMinMaxReduction = [](Instruction *RdxRootInst) { 6698 assert(isa<SelectInst>(RdxRootInst) && 6699 "Expected min/max reduction to have select root instruction"); 6700 Value *ScalarCond = cast<SelectInst>(RdxRootInst)->getCondition(); 6701 assert(isa<Instruction>(ScalarCond) && 6702 "Expected min/max reduction to have compare condition"); 6703 return cast<Instruction>(ScalarCond); 6704 }; 6705 6706 // The reduction root is used as the insertion point for new instructions, 6707 // so set it as externally used to prevent it from being deleted. 6708 ExternallyUsedValues[ReductionRoot]; 6709 SmallVector<Value *, 16> IgnoreList; 6710 for (auto &V : ReductionOps) 6711 IgnoreList.append(V.begin(), V.end()); 6712 while (i < NumReducedVals - ReduxWidth + 1 && ReduxWidth > 2) { 6713 auto VL = makeArrayRef(&ReducedVals[i], ReduxWidth); 6714 V.buildTree(VL, ExternallyUsedValues, IgnoreList); 6715 Optional<ArrayRef<unsigned>> Order = V.bestOrder(); 6716 // TODO: Handle orders of size less than number of elements in the vector. 6717 if (Order && Order->size() == VL.size()) { 6718 // TODO: reorder tree nodes without tree rebuilding. 6719 SmallVector<Value *, 4> ReorderedOps(VL.size()); 6720 llvm::transform(*Order, ReorderedOps.begin(), 6721 [VL](const unsigned Idx) { return VL[Idx]; }); 6722 V.buildTree(ReorderedOps, ExternallyUsedValues, IgnoreList); 6723 } 6724 if (V.isTreeTinyAndNotFullyVectorizable()) 6725 break; 6726 if (V.isLoadCombineReductionCandidate(ReductionData.getOpcode())) 6727 break; 6728 6729 V.computeMinimumValueSizes(); 6730 6731 // Estimate cost. 6732 int TreeCost = V.getTreeCost(); 6733 int ReductionCost = getReductionCost(TTI, ReducedVals[i], ReduxWidth); 6734 int Cost = TreeCost + ReductionCost; 6735 if (Cost >= -SLPCostThreshold) { 6736 V.getORE()->emit([&]() { 6737 return OptimizationRemarkMissed( 6738 SV_NAME, "HorSLPNotBeneficial", cast<Instruction>(VL[0])) 6739 << "Vectorizing horizontal reduction is possible" 6740 << "but not beneficial with cost " 6741 << ore::NV("Cost", Cost) << " and threshold " 6742 << ore::NV("Threshold", -SLPCostThreshold); 6743 }); 6744 break; 6745 } 6746 6747 LLVM_DEBUG(dbgs() << "SLP: Vectorizing horizontal reduction at cost:" 6748 << Cost << ". (HorRdx)\n"); 6749 V.getORE()->emit([&]() { 6750 return OptimizationRemark( 6751 SV_NAME, "VectorizedHorizontalReduction", cast<Instruction>(VL[0])) 6752 << "Vectorized horizontal reduction with cost " 6753 << ore::NV("Cost", Cost) << " and with tree size " 6754 << ore::NV("TreeSize", V.getTreeSize()); 6755 }); 6756 6757 // Vectorize a tree. 6758 DebugLoc Loc = cast<Instruction>(ReducedVals[i])->getDebugLoc(); 6759 Value *VectorizedRoot = V.vectorizeTree(ExternallyUsedValues); 6760 6761 // Emit a reduction. For min/max, the root is a select, but the insertion 6762 // point is the compare condition of that select. 6763 Instruction *RdxRootInst = cast<Instruction>(ReductionRoot); 6764 if (ReductionData.isMinMax()) 6765 Builder.SetInsertPoint(getCmpForMinMaxReduction(RdxRootInst)); 6766 else 6767 Builder.SetInsertPoint(RdxRootInst); 6768 6769 Value *ReducedSubTree = 6770 emitReduction(VectorizedRoot, Builder, ReduxWidth, TTI); 6771 if (VectorizedTree) { 6772 Builder.SetCurrentDebugLocation(Loc); 6773 OperationData VectReductionData(ReductionData.getOpcode(), 6774 VectorizedTree, ReducedSubTree, 6775 ReductionData.getKind()); 6776 VectorizedTree = 6777 VectReductionData.createOp(Builder, "op.rdx", ReductionOps); 6778 } else 6779 VectorizedTree = ReducedSubTree; 6780 i += ReduxWidth; 6781 ReduxWidth = PowerOf2Floor(NumReducedVals - i); 6782 } 6783 6784 if (VectorizedTree) { 6785 // Finish the reduction. 6786 for (; i < NumReducedVals; ++i) { 6787 auto *I = cast<Instruction>(ReducedVals[i]); 6788 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 6789 OperationData VectReductionData(ReductionData.getOpcode(), 6790 VectorizedTree, I, 6791 ReductionData.getKind()); 6792 VectorizedTree = VectReductionData.createOp(Builder, "", ReductionOps); 6793 } 6794 for (auto &Pair : ExternallyUsedValues) { 6795 // Add each externally used value to the final reduction. 6796 for (auto *I : Pair.second) { 6797 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 6798 OperationData VectReductionData(ReductionData.getOpcode(), 6799 VectorizedTree, Pair.first, 6800 ReductionData.getKind()); 6801 VectorizedTree = VectReductionData.createOp(Builder, "op.extra", I); 6802 } 6803 } 6804 6805 // Update users. For a min/max reduction that ends with a compare and 6806 // select, we also have to RAUW for the compare instruction feeding the 6807 // reduction root. That's because the original compare may have extra uses 6808 // besides the final select of the reduction. 6809 if (ReductionData.isMinMax()) { 6810 if (auto *VecSelect = dyn_cast<SelectInst>(VectorizedTree)) { 6811 Instruction *ScalarCmp = 6812 getCmpForMinMaxReduction(cast<Instruction>(ReductionRoot)); 6813 ScalarCmp->replaceAllUsesWith(VecSelect->getCondition()); 6814 } 6815 } 6816 ReductionRoot->replaceAllUsesWith(VectorizedTree); 6817 6818 // Mark all scalar reduction ops for deletion, they are replaced by the 6819 // vector reductions. 6820 V.eraseInstructions(IgnoreList); 6821 } 6822 return VectorizedTree != nullptr; 6823 } 6824 6825 unsigned numReductionValues() const { 6826 return ReducedVals.size(); 6827 } 6828 6829 private: 6830 /// Calculate the cost of a reduction. 6831 int getReductionCost(TargetTransformInfo *TTI, Value *FirstReducedVal, 6832 unsigned ReduxWidth) { 6833 Type *ScalarTy = FirstReducedVal->getType(); 6834 Type *VecTy = VectorType::get(ScalarTy, ReduxWidth); 6835 6836 int PairwiseRdxCost; 6837 int SplittingRdxCost; 6838 switch (ReductionData.getKind()) { 6839 case RK_Arithmetic: 6840 PairwiseRdxCost = 6841 TTI->getArithmeticReductionCost(ReductionData.getOpcode(), VecTy, 6842 /*IsPairwiseForm=*/true); 6843 SplittingRdxCost = 6844 TTI->getArithmeticReductionCost(ReductionData.getOpcode(), VecTy, 6845 /*IsPairwiseForm=*/false); 6846 break; 6847 case RK_Min: 6848 case RK_Max: 6849 case RK_UMin: 6850 case RK_UMax: { 6851 Type *VecCondTy = CmpInst::makeCmpResultType(VecTy); 6852 bool IsUnsigned = ReductionData.getKind() == RK_UMin || 6853 ReductionData.getKind() == RK_UMax; 6854 PairwiseRdxCost = 6855 TTI->getMinMaxReductionCost(VecTy, VecCondTy, 6856 /*IsPairwiseForm=*/true, IsUnsigned); 6857 SplittingRdxCost = 6858 TTI->getMinMaxReductionCost(VecTy, VecCondTy, 6859 /*IsPairwiseForm=*/false, IsUnsigned); 6860 break; 6861 } 6862 case RK_None: 6863 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 6864 } 6865 6866 IsPairwiseReduction = PairwiseRdxCost < SplittingRdxCost; 6867 int VecReduxCost = IsPairwiseReduction ? PairwiseRdxCost : SplittingRdxCost; 6868 6869 int ScalarReduxCost = 0; 6870 switch (ReductionData.getKind()) { 6871 case RK_Arithmetic: 6872 ScalarReduxCost = 6873 TTI->getArithmeticInstrCost(ReductionData.getOpcode(), ScalarTy); 6874 break; 6875 case RK_Min: 6876 case RK_Max: 6877 case RK_UMin: 6878 case RK_UMax: 6879 ScalarReduxCost = 6880 TTI->getCmpSelInstrCost(ReductionData.getOpcode(), ScalarTy) + 6881 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 6882 CmpInst::makeCmpResultType(ScalarTy)); 6883 break; 6884 case RK_None: 6885 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 6886 } 6887 ScalarReduxCost *= (ReduxWidth - 1); 6888 6889 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << VecReduxCost - ScalarReduxCost 6890 << " for reduction that starts with " << *FirstReducedVal 6891 << " (It is a " 6892 << (IsPairwiseReduction ? "pairwise" : "splitting") 6893 << " reduction)\n"); 6894 6895 return VecReduxCost - ScalarReduxCost; 6896 } 6897 6898 /// Emit a horizontal reduction of the vectorized value. 6899 Value *emitReduction(Value *VectorizedValue, IRBuilder<> &Builder, 6900 unsigned ReduxWidth, const TargetTransformInfo *TTI) { 6901 assert(VectorizedValue && "Need to have a vectorized tree node"); 6902 assert(isPowerOf2_32(ReduxWidth) && 6903 "We only handle power-of-two reductions for now"); 6904 6905 if (!IsPairwiseReduction) { 6906 // FIXME: The builder should use an FMF guard. It should not be hard-coded 6907 // to 'fast'. 6908 assert(Builder.getFastMathFlags().isFast() && "Expected 'fast' FMF"); 6909 return createSimpleTargetReduction( 6910 Builder, TTI, ReductionData.getOpcode(), VectorizedValue, 6911 ReductionData.getFlags(), ReductionOps.back()); 6912 } 6913 6914 Value *TmpVec = VectorizedValue; 6915 for (unsigned i = ReduxWidth / 2; i != 0; i >>= 1) { 6916 Value *LeftMask = 6917 createRdxShuffleMask(ReduxWidth, i, true, true, Builder); 6918 Value *RightMask = 6919 createRdxShuffleMask(ReduxWidth, i, true, false, Builder); 6920 6921 Value *LeftShuf = Builder.CreateShuffleVector( 6922 TmpVec, UndefValue::get(TmpVec->getType()), LeftMask, "rdx.shuf.l"); 6923 Value *RightShuf = Builder.CreateShuffleVector( 6924 TmpVec, UndefValue::get(TmpVec->getType()), (RightMask), 6925 "rdx.shuf.r"); 6926 OperationData VectReductionData(ReductionData.getOpcode(), LeftShuf, 6927 RightShuf, ReductionData.getKind()); 6928 TmpVec = VectReductionData.createOp(Builder, "op.rdx", ReductionOps); 6929 } 6930 6931 // The result is in the first element of the vector. 6932 return Builder.CreateExtractElement(TmpVec, Builder.getInt32(0)); 6933 } 6934 }; 6935 6936 } // end anonymous namespace 6937 6938 /// Recognize construction of vectors like 6939 /// %ra = insertelement <4 x float> undef, float %s0, i32 0 6940 /// %rb = insertelement <4 x float> %ra, float %s1, i32 1 6941 /// %rc = insertelement <4 x float> %rb, float %s2, i32 2 6942 /// %rd = insertelement <4 x float> %rc, float %s3, i32 3 6943 /// starting from the last insertelement instruction. 6944 /// 6945 /// Returns true if it matches 6946 static bool findBuildVector(InsertElementInst *LastInsertElem, 6947 TargetTransformInfo *TTI, 6948 SmallVectorImpl<Value *> &BuildVectorOpds, 6949 int &UserCost) { 6950 UserCost = 0; 6951 Value *V = nullptr; 6952 do { 6953 if (auto *CI = dyn_cast<ConstantInt>(LastInsertElem->getOperand(2))) { 6954 UserCost += TTI->getVectorInstrCost(Instruction::InsertElement, 6955 LastInsertElem->getType(), 6956 CI->getZExtValue()); 6957 } 6958 BuildVectorOpds.push_back(LastInsertElem->getOperand(1)); 6959 V = LastInsertElem->getOperand(0); 6960 if (isa<UndefValue>(V)) 6961 break; 6962 LastInsertElem = dyn_cast<InsertElementInst>(V); 6963 if (!LastInsertElem || !LastInsertElem->hasOneUse()) 6964 return false; 6965 } while (true); 6966 std::reverse(BuildVectorOpds.begin(), BuildVectorOpds.end()); 6967 return true; 6968 } 6969 6970 /// Like findBuildVector, but looks for construction of aggregate. 6971 /// Accepts homegeneous aggregate of vectors like { <2 x float>, <2 x float> }. 6972 /// 6973 /// \return true if it matches. 6974 static bool findBuildAggregate(InsertValueInst *IV, TargetTransformInfo *TTI, 6975 SmallVectorImpl<Value *> &BuildVectorOpds, 6976 int &UserCost) { 6977 UserCost = 0; 6978 do { 6979 if (auto *IE = dyn_cast<InsertElementInst>(IV->getInsertedValueOperand())) { 6980 int TmpUserCost; 6981 SmallVector<Value *, 4> TmpBuildVectorOpds; 6982 if (!findBuildVector(IE, TTI, TmpBuildVectorOpds, TmpUserCost)) 6983 return false; 6984 BuildVectorOpds.append(TmpBuildVectorOpds.rbegin(), TmpBuildVectorOpds.rend()); 6985 UserCost += TmpUserCost; 6986 } else { 6987 BuildVectorOpds.push_back(IV->getInsertedValueOperand()); 6988 } 6989 Value *V = IV->getAggregateOperand(); 6990 if (isa<UndefValue>(V)) 6991 break; 6992 IV = dyn_cast<InsertValueInst>(V); 6993 if (!IV || !IV->hasOneUse()) 6994 return false; 6995 } while (true); 6996 std::reverse(BuildVectorOpds.begin(), BuildVectorOpds.end()); 6997 return true; 6998 } 6999 7000 static bool PhiTypeSorterFunc(Value *V, Value *V2) { 7001 return V->getType() < V2->getType(); 7002 } 7003 7004 /// Try and get a reduction value from a phi node. 7005 /// 7006 /// Given a phi node \p P in a block \p ParentBB, consider possible reductions 7007 /// if they come from either \p ParentBB or a containing loop latch. 7008 /// 7009 /// \returns A candidate reduction value if possible, or \code nullptr \endcode 7010 /// if not possible. 7011 static Value *getReductionValue(const DominatorTree *DT, PHINode *P, 7012 BasicBlock *ParentBB, LoopInfo *LI) { 7013 // There are situations where the reduction value is not dominated by the 7014 // reduction phi. Vectorizing such cases has been reported to cause 7015 // miscompiles. See PR25787. 7016 auto DominatedReduxValue = [&](Value *R) { 7017 return isa<Instruction>(R) && 7018 DT->dominates(P->getParent(), cast<Instruction>(R)->getParent()); 7019 }; 7020 7021 Value *Rdx = nullptr; 7022 7023 // Return the incoming value if it comes from the same BB as the phi node. 7024 if (P->getIncomingBlock(0) == ParentBB) { 7025 Rdx = P->getIncomingValue(0); 7026 } else if (P->getIncomingBlock(1) == ParentBB) { 7027 Rdx = P->getIncomingValue(1); 7028 } 7029 7030 if (Rdx && DominatedReduxValue(Rdx)) 7031 return Rdx; 7032 7033 // Otherwise, check whether we have a loop latch to look at. 7034 Loop *BBL = LI->getLoopFor(ParentBB); 7035 if (!BBL) 7036 return nullptr; 7037 BasicBlock *BBLatch = BBL->getLoopLatch(); 7038 if (!BBLatch) 7039 return nullptr; 7040 7041 // There is a loop latch, return the incoming value if it comes from 7042 // that. This reduction pattern occasionally turns up. 7043 if (P->getIncomingBlock(0) == BBLatch) { 7044 Rdx = P->getIncomingValue(0); 7045 } else if (P->getIncomingBlock(1) == BBLatch) { 7046 Rdx = P->getIncomingValue(1); 7047 } 7048 7049 if (Rdx && DominatedReduxValue(Rdx)) 7050 return Rdx; 7051 7052 return nullptr; 7053 } 7054 7055 /// Attempt to reduce a horizontal reduction. 7056 /// If it is legal to match a horizontal reduction feeding the phi node \a P 7057 /// with reduction operators \a Root (or one of its operands) in a basic block 7058 /// \a BB, then check if it can be done. If horizontal reduction is not found 7059 /// and root instruction is a binary operation, vectorization of the operands is 7060 /// attempted. 7061 /// \returns true if a horizontal reduction was matched and reduced or operands 7062 /// of one of the binary instruction were vectorized. 7063 /// \returns false if a horizontal reduction was not matched (or not possible) 7064 /// or no vectorization of any binary operation feeding \a Root instruction was 7065 /// performed. 7066 static bool tryToVectorizeHorReductionOrInstOperands( 7067 PHINode *P, Instruction *Root, BasicBlock *BB, BoUpSLP &R, 7068 TargetTransformInfo *TTI, 7069 const function_ref<bool(Instruction *, BoUpSLP &)> Vectorize) { 7070 if (!ShouldVectorizeHor) 7071 return false; 7072 7073 if (!Root) 7074 return false; 7075 7076 if (Root->getParent() != BB || isa<PHINode>(Root)) 7077 return false; 7078 // Start analysis starting from Root instruction. If horizontal reduction is 7079 // found, try to vectorize it. If it is not a horizontal reduction or 7080 // vectorization is not possible or not effective, and currently analyzed 7081 // instruction is a binary operation, try to vectorize the operands, using 7082 // pre-order DFS traversal order. If the operands were not vectorized, repeat 7083 // the same procedure considering each operand as a possible root of the 7084 // horizontal reduction. 7085 // Interrupt the process if the Root instruction itself was vectorized or all 7086 // sub-trees not higher that RecursionMaxDepth were analyzed/vectorized. 7087 SmallVector<std::pair<Instruction *, unsigned>, 8> Stack(1, {Root, 0}); 7088 SmallPtrSet<Value *, 8> VisitedInstrs; 7089 bool Res = false; 7090 while (!Stack.empty()) { 7091 Instruction *Inst; 7092 unsigned Level; 7093 std::tie(Inst, Level) = Stack.pop_back_val(); 7094 auto *BI = dyn_cast<BinaryOperator>(Inst); 7095 auto *SI = dyn_cast<SelectInst>(Inst); 7096 if (BI || SI) { 7097 HorizontalReduction HorRdx; 7098 if (HorRdx.matchAssociativeReduction(P, Inst)) { 7099 if (HorRdx.tryToReduce(R, TTI)) { 7100 Res = true; 7101 // Set P to nullptr to avoid re-analysis of phi node in 7102 // matchAssociativeReduction function unless this is the root node. 7103 P = nullptr; 7104 continue; 7105 } 7106 } 7107 if (P && BI) { 7108 Inst = dyn_cast<Instruction>(BI->getOperand(0)); 7109 if (Inst == P) 7110 Inst = dyn_cast<Instruction>(BI->getOperand(1)); 7111 if (!Inst) { 7112 // Set P to nullptr to avoid re-analysis of phi node in 7113 // matchAssociativeReduction function unless this is the root node. 7114 P = nullptr; 7115 continue; 7116 } 7117 } 7118 } 7119 // Set P to nullptr to avoid re-analysis of phi node in 7120 // matchAssociativeReduction function unless this is the root node. 7121 P = nullptr; 7122 if (Vectorize(Inst, R)) { 7123 Res = true; 7124 continue; 7125 } 7126 7127 // Try to vectorize operands. 7128 // Continue analysis for the instruction from the same basic block only to 7129 // save compile time. 7130 if (++Level < RecursionMaxDepth) 7131 for (auto *Op : Inst->operand_values()) 7132 if (VisitedInstrs.insert(Op).second) 7133 if (auto *I = dyn_cast<Instruction>(Op)) 7134 if (!isa<PHINode>(I) && !R.isDeleted(I) && I->getParent() == BB) 7135 Stack.emplace_back(I, Level); 7136 } 7137 return Res; 7138 } 7139 7140 bool SLPVectorizerPass::vectorizeRootInstruction(PHINode *P, Value *V, 7141 BasicBlock *BB, BoUpSLP &R, 7142 TargetTransformInfo *TTI) { 7143 if (!V) 7144 return false; 7145 auto *I = dyn_cast<Instruction>(V); 7146 if (!I) 7147 return false; 7148 7149 if (!isa<BinaryOperator>(I)) 7150 P = nullptr; 7151 // Try to match and vectorize a horizontal reduction. 7152 auto &&ExtraVectorization = [this](Instruction *I, BoUpSLP &R) -> bool { 7153 return tryToVectorize(I, R); 7154 }; 7155 return tryToVectorizeHorReductionOrInstOperands(P, I, BB, R, TTI, 7156 ExtraVectorization); 7157 } 7158 7159 bool SLPVectorizerPass::vectorizeInsertValueInst(InsertValueInst *IVI, 7160 BasicBlock *BB, BoUpSLP &R) { 7161 int UserCost = 0; 7162 const DataLayout &DL = BB->getModule()->getDataLayout(); 7163 if (!R.canMapToVector(IVI->getType(), DL)) 7164 return false; 7165 7166 SmallVector<Value *, 16> BuildVectorOpds; 7167 if (!findBuildAggregate(IVI, TTI, BuildVectorOpds, UserCost)) 7168 return false; 7169 7170 LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IVI << "\n"); 7171 // Aggregate value is unlikely to be processed in vector register, we need to 7172 // extract scalars into scalar registers, so NeedExtraction is set true. 7173 return tryToVectorizeList(BuildVectorOpds, R, UserCost); 7174 } 7175 7176 bool SLPVectorizerPass::vectorizeInsertElementInst(InsertElementInst *IEI, 7177 BasicBlock *BB, BoUpSLP &R) { 7178 int UserCost; 7179 SmallVector<Value *, 16> BuildVectorOpds; 7180 if (!findBuildVector(IEI, TTI, BuildVectorOpds, UserCost) || 7181 (llvm::all_of(BuildVectorOpds, 7182 [](Value *V) { return isa<ExtractElementInst>(V); }) && 7183 isShuffle(BuildVectorOpds))) 7184 return false; 7185 7186 // Vectorize starting with the build vector operands ignoring the BuildVector 7187 // instructions for the purpose of scheduling and user extraction. 7188 return tryToVectorizeList(BuildVectorOpds, R, UserCost); 7189 } 7190 7191 bool SLPVectorizerPass::vectorizeCmpInst(CmpInst *CI, BasicBlock *BB, 7192 BoUpSLP &R) { 7193 if (tryToVectorizePair(CI->getOperand(0), CI->getOperand(1), R)) 7194 return true; 7195 7196 bool OpsChanged = false; 7197 for (int Idx = 0; Idx < 2; ++Idx) { 7198 OpsChanged |= 7199 vectorizeRootInstruction(nullptr, CI->getOperand(Idx), BB, R, TTI); 7200 } 7201 return OpsChanged; 7202 } 7203 7204 bool SLPVectorizerPass::vectorizeSimpleInstructions( 7205 SmallVectorImpl<Instruction *> &Instructions, BasicBlock *BB, BoUpSLP &R) { 7206 bool OpsChanged = false; 7207 for (auto *I : reverse(Instructions)) { 7208 if (R.isDeleted(I)) 7209 continue; 7210 if (auto *LastInsertValue = dyn_cast<InsertValueInst>(I)) 7211 OpsChanged |= vectorizeInsertValueInst(LastInsertValue, BB, R); 7212 else if (auto *LastInsertElem = dyn_cast<InsertElementInst>(I)) 7213 OpsChanged |= vectorizeInsertElementInst(LastInsertElem, BB, R); 7214 else if (auto *CI = dyn_cast<CmpInst>(I)) 7215 OpsChanged |= vectorizeCmpInst(CI, BB, R); 7216 } 7217 Instructions.clear(); 7218 return OpsChanged; 7219 } 7220 7221 bool SLPVectorizerPass::vectorizeChainsInBlock(BasicBlock *BB, BoUpSLP &R) { 7222 bool Changed = false; 7223 SmallVector<Value *, 4> Incoming; 7224 SmallPtrSet<Value *, 16> VisitedInstrs; 7225 7226 bool HaveVectorizedPhiNodes = true; 7227 while (HaveVectorizedPhiNodes) { 7228 HaveVectorizedPhiNodes = false; 7229 7230 // Collect the incoming values from the PHIs. 7231 Incoming.clear(); 7232 for (Instruction &I : *BB) { 7233 PHINode *P = dyn_cast<PHINode>(&I); 7234 if (!P) 7235 break; 7236 7237 if (!VisitedInstrs.count(P) && !R.isDeleted(P)) 7238 Incoming.push_back(P); 7239 } 7240 7241 // Sort by type. 7242 llvm::stable_sort(Incoming, PhiTypeSorterFunc); 7243 7244 // Try to vectorize elements base on their type. 7245 for (SmallVector<Value *, 4>::iterator IncIt = Incoming.begin(), 7246 E = Incoming.end(); 7247 IncIt != E;) { 7248 7249 // Look for the next elements with the same type. 7250 SmallVector<Value *, 4>::iterator SameTypeIt = IncIt; 7251 while (SameTypeIt != E && 7252 (*SameTypeIt)->getType() == (*IncIt)->getType()) { 7253 VisitedInstrs.insert(*SameTypeIt); 7254 ++SameTypeIt; 7255 } 7256 7257 // Try to vectorize them. 7258 unsigned NumElts = (SameTypeIt - IncIt); 7259 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize starting at PHIs (" 7260 << NumElts << ")\n"); 7261 // The order in which the phi nodes appear in the program does not matter. 7262 // So allow tryToVectorizeList to reorder them if it is beneficial. This 7263 // is done when there are exactly two elements since tryToVectorizeList 7264 // asserts that there are only two values when AllowReorder is true. 7265 bool AllowReorder = NumElts == 2; 7266 if (NumElts > 1 && tryToVectorizeList(makeArrayRef(IncIt, NumElts), R, 7267 /*UserCost=*/0, AllowReorder)) { 7268 // Success start over because instructions might have been changed. 7269 HaveVectorizedPhiNodes = true; 7270 Changed = true; 7271 break; 7272 } 7273 7274 // Start over at the next instruction of a different type (or the end). 7275 IncIt = SameTypeIt; 7276 } 7277 } 7278 7279 VisitedInstrs.clear(); 7280 7281 SmallVector<Instruction *, 8> PostProcessInstructions; 7282 SmallDenseSet<Instruction *, 4> KeyNodes; 7283 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 7284 // Skip instructions marked for the deletion. 7285 if (R.isDeleted(&*it)) 7286 continue; 7287 // We may go through BB multiple times so skip the one we have checked. 7288 if (!VisitedInstrs.insert(&*it).second) { 7289 if (it->use_empty() && KeyNodes.count(&*it) > 0 && 7290 vectorizeSimpleInstructions(PostProcessInstructions, BB, R)) { 7291 // We would like to start over since some instructions are deleted 7292 // and the iterator may become invalid value. 7293 Changed = true; 7294 it = BB->begin(); 7295 e = BB->end(); 7296 } 7297 continue; 7298 } 7299 7300 if (isa<DbgInfoIntrinsic>(it)) 7301 continue; 7302 7303 // Try to vectorize reductions that use PHINodes. 7304 if (PHINode *P = dyn_cast<PHINode>(it)) { 7305 // Check that the PHI is a reduction PHI. 7306 if (P->getNumIncomingValues() != 2) 7307 return Changed; 7308 7309 // Try to match and vectorize a horizontal reduction. 7310 if (vectorizeRootInstruction(P, getReductionValue(DT, P, BB, LI), BB, R, 7311 TTI)) { 7312 Changed = true; 7313 it = BB->begin(); 7314 e = BB->end(); 7315 continue; 7316 } 7317 continue; 7318 } 7319 7320 // Ran into an instruction without users, like terminator, or function call 7321 // with ignored return value, store. Ignore unused instructions (basing on 7322 // instruction type, except for CallInst and InvokeInst). 7323 if (it->use_empty() && (it->getType()->isVoidTy() || isa<CallInst>(it) || 7324 isa<InvokeInst>(it))) { 7325 KeyNodes.insert(&*it); 7326 bool OpsChanged = false; 7327 if (ShouldStartVectorizeHorAtStore || !isa<StoreInst>(it)) { 7328 for (auto *V : it->operand_values()) { 7329 // Try to match and vectorize a horizontal reduction. 7330 OpsChanged |= vectorizeRootInstruction(nullptr, V, BB, R, TTI); 7331 } 7332 } 7333 // Start vectorization of post-process list of instructions from the 7334 // top-tree instructions to try to vectorize as many instructions as 7335 // possible. 7336 OpsChanged |= vectorizeSimpleInstructions(PostProcessInstructions, BB, R); 7337 if (OpsChanged) { 7338 // We would like to start over since some instructions are deleted 7339 // and the iterator may become invalid value. 7340 Changed = true; 7341 it = BB->begin(); 7342 e = BB->end(); 7343 continue; 7344 } 7345 } 7346 7347 if (isa<InsertElementInst>(it) || isa<CmpInst>(it) || 7348 isa<InsertValueInst>(it)) 7349 PostProcessInstructions.push_back(&*it); 7350 } 7351 7352 return Changed; 7353 } 7354 7355 bool SLPVectorizerPass::vectorizeGEPIndices(BasicBlock *BB, BoUpSLP &R) { 7356 auto Changed = false; 7357 for (auto &Entry : GEPs) { 7358 // If the getelementptr list has fewer than two elements, there's nothing 7359 // to do. 7360 if (Entry.second.size() < 2) 7361 continue; 7362 7363 LLVM_DEBUG(dbgs() << "SLP: Analyzing a getelementptr list of length " 7364 << Entry.second.size() << ".\n"); 7365 7366 // Process the GEP list in chunks suitable for the target's supported 7367 // vector size. If a vector register can't hold 1 element, we are done. 7368 unsigned MaxVecRegSize = R.getMaxVecRegSize(); 7369 unsigned EltSize = R.getVectorElementSize(Entry.second[0]); 7370 if (MaxVecRegSize < EltSize) 7371 continue; 7372 7373 unsigned MaxElts = MaxVecRegSize / EltSize; 7374 for (unsigned BI = 0, BE = Entry.second.size(); BI < BE; BI += MaxElts) { 7375 auto Len = std::min<unsigned>(BE - BI, MaxElts); 7376 auto GEPList = makeArrayRef(&Entry.second[BI], Len); 7377 7378 // Initialize a set a candidate getelementptrs. Note that we use a 7379 // SetVector here to preserve program order. If the index computations 7380 // are vectorizable and begin with loads, we want to minimize the chance 7381 // of having to reorder them later. 7382 SetVector<Value *> Candidates(GEPList.begin(), GEPList.end()); 7383 7384 // Some of the candidates may have already been vectorized after we 7385 // initially collected them. If so, they are marked as deleted, so remove 7386 // them from the set of candidates. 7387 Candidates.remove_if( 7388 [&R](Value *I) { return R.isDeleted(cast<Instruction>(I)); }); 7389 7390 // Remove from the set of candidates all pairs of getelementptrs with 7391 // constant differences. Such getelementptrs are likely not good 7392 // candidates for vectorization in a bottom-up phase since one can be 7393 // computed from the other. We also ensure all candidate getelementptr 7394 // indices are unique. 7395 for (int I = 0, E = GEPList.size(); I < E && Candidates.size() > 1; ++I) { 7396 auto *GEPI = GEPList[I]; 7397 if (!Candidates.count(GEPI)) 7398 continue; 7399 auto *SCEVI = SE->getSCEV(GEPList[I]); 7400 for (int J = I + 1; J < E && Candidates.size() > 1; ++J) { 7401 auto *GEPJ = GEPList[J]; 7402 auto *SCEVJ = SE->getSCEV(GEPList[J]); 7403 if (isa<SCEVConstant>(SE->getMinusSCEV(SCEVI, SCEVJ))) { 7404 Candidates.remove(GEPI); 7405 Candidates.remove(GEPJ); 7406 } else if (GEPI->idx_begin()->get() == GEPJ->idx_begin()->get()) { 7407 Candidates.remove(GEPJ); 7408 } 7409 } 7410 } 7411 7412 // We break out of the above computation as soon as we know there are 7413 // fewer than two candidates remaining. 7414 if (Candidates.size() < 2) 7415 continue; 7416 7417 // Add the single, non-constant index of each candidate to the bundle. We 7418 // ensured the indices met these constraints when we originally collected 7419 // the getelementptrs. 7420 SmallVector<Value *, 16> Bundle(Candidates.size()); 7421 auto BundleIndex = 0u; 7422 for (auto *V : Candidates) { 7423 auto *GEP = cast<GetElementPtrInst>(V); 7424 auto *GEPIdx = GEP->idx_begin()->get(); 7425 assert(GEP->getNumIndices() == 1 || !isa<Constant>(GEPIdx)); 7426 Bundle[BundleIndex++] = GEPIdx; 7427 } 7428 7429 // Try and vectorize the indices. We are currently only interested in 7430 // gather-like cases of the form: 7431 // 7432 // ... = g[a[0] - b[0]] + g[a[1] - b[1]] + ... 7433 // 7434 // where the loads of "a", the loads of "b", and the subtractions can be 7435 // performed in parallel. It's likely that detecting this pattern in a 7436 // bottom-up phase will be simpler and less costly than building a 7437 // full-blown top-down phase beginning at the consecutive loads. 7438 Changed |= tryToVectorizeList(Bundle, R); 7439 } 7440 } 7441 return Changed; 7442 } 7443 7444 bool SLPVectorizerPass::vectorizeStoreChains(BoUpSLP &R) { 7445 bool Changed = false; 7446 // Attempt to sort and vectorize each of the store-groups. 7447 for (StoreListMap::iterator it = Stores.begin(), e = Stores.end(); it != e; 7448 ++it) { 7449 if (it->second.size() < 2) 7450 continue; 7451 7452 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " 7453 << it->second.size() << ".\n"); 7454 7455 Changed |= vectorizeStores(it->second, R); 7456 } 7457 return Changed; 7458 } 7459 7460 char SLPVectorizer::ID = 0; 7461 7462 static const char lv_name[] = "SLP Vectorizer"; 7463 7464 INITIALIZE_PASS_BEGIN(SLPVectorizer, SV_NAME, lv_name, false, false) 7465 INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass) 7466 INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass) 7467 INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker) 7468 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass) 7469 INITIALIZE_PASS_DEPENDENCY(LoopSimplify) 7470 INITIALIZE_PASS_DEPENDENCY(DemandedBitsWrapperPass) 7471 INITIALIZE_PASS_DEPENDENCY(OptimizationRemarkEmitterWrapperPass) 7472 INITIALIZE_PASS_END(SLPVectorizer, SV_NAME, lv_name, false, false) 7473 7474 Pass *llvm::createSLPVectorizerPass() { return new SLPVectorizer(); } 7475