1 //===- SLPVectorizer.cpp - A bottom up SLP Vectorizer ---------------------===// 2 // 3 // The LLVM Compiler Infrastructure 4 // 5 // This file is distributed under the University of Illinois Open Source 6 // License. See LICENSE.TXT for details. 7 // 8 //===----------------------------------------------------------------------===// 9 // 10 // This pass implements the Bottom Up SLP vectorizer. It detects consecutive 11 // stores that can be put together into vector-stores. Next, it attempts to 12 // construct vectorizable tree using the use-def chains. If a profitable tree 13 // was found, the SLP vectorizer performs vectorization on the tree. 14 // 15 // The pass is inspired by the work described in the paper: 16 // "Loop-Aware SLP in GCC" by Ira Rosen, Dorit Nuzman, Ayal Zaks. 17 // 18 //===----------------------------------------------------------------------===// 19 20 #include "llvm/Transforms/Vectorize/SLPVectorizer.h" 21 #include "llvm/ADT/ArrayRef.h" 22 #include "llvm/ADT/DenseMap.h" 23 #include "llvm/ADT/DenseSet.h" 24 #include "llvm/ADT/MapVector.h" 25 #include "llvm/ADT/None.h" 26 #include "llvm/ADT/Optional.h" 27 #include "llvm/ADT/PostOrderIterator.h" 28 #include "llvm/ADT/STLExtras.h" 29 #include "llvm/ADT/SetVector.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/Pass.h" 77 #include "llvm/Support/Casting.h" 78 #include "llvm/Support/CommandLine.h" 79 #include "llvm/Support/Compiler.h" 80 #include "llvm/Support/DOTGraphTraits.h" 81 #include "llvm/Support/Debug.h" 82 #include "llvm/Support/ErrorHandling.h" 83 #include "llvm/Support/GraphWriter.h" 84 #include "llvm/Support/KnownBits.h" 85 #include "llvm/Support/MathExtras.h" 86 #include "llvm/Support/raw_ostream.h" 87 #include "llvm/Transforms/Utils/LoopUtils.h" 88 #include "llvm/Transforms/Vectorize.h" 89 #include <algorithm> 90 #include <cassert> 91 #include <cstdint> 92 #include <iterator> 93 #include <memory> 94 #include <set> 95 #include <string> 96 #include <tuple> 97 #include <utility> 98 #include <vector> 99 100 using namespace llvm; 101 using namespace llvm::PatternMatch; 102 using namespace slpvectorizer; 103 104 #define SV_NAME "slp-vectorizer" 105 #define DEBUG_TYPE "SLP" 106 107 STATISTIC(NumVectorInstructions, "Number of vector instructions generated"); 108 109 static cl::opt<int> 110 SLPCostThreshold("slp-threshold", cl::init(0), cl::Hidden, 111 cl::desc("Only vectorize if you gain more than this " 112 "number ")); 113 114 static cl::opt<bool> 115 ShouldVectorizeHor("slp-vectorize-hor", cl::init(true), cl::Hidden, 116 cl::desc("Attempt to vectorize horizontal reductions")); 117 118 static cl::opt<bool> ShouldStartVectorizeHorAtStore( 119 "slp-vectorize-hor-store", cl::init(false), cl::Hidden, 120 cl::desc( 121 "Attempt to vectorize horizontal reductions feeding into a store")); 122 123 static cl::opt<int> 124 MaxVectorRegSizeOption("slp-max-reg-size", cl::init(128), cl::Hidden, 125 cl::desc("Attempt to vectorize for this register size in bits")); 126 127 /// Limits the size of scheduling regions in a block. 128 /// It avoid long compile times for _very_ large blocks where vector 129 /// instructions are spread over a wide range. 130 /// This limit is way higher than needed by real-world functions. 131 static cl::opt<int> 132 ScheduleRegionSizeBudget("slp-schedule-budget", cl::init(100000), cl::Hidden, 133 cl::desc("Limit the size of the SLP scheduling region per block")); 134 135 static cl::opt<int> MinVectorRegSizeOption( 136 "slp-min-reg-size", cl::init(128), cl::Hidden, 137 cl::desc("Attempt to vectorize for this register size in bits")); 138 139 static cl::opt<unsigned> RecursionMaxDepth( 140 "slp-recursion-max-depth", cl::init(12), cl::Hidden, 141 cl::desc("Limit the recursion depth when building a vectorizable tree")); 142 143 static cl::opt<unsigned> MinTreeSize( 144 "slp-min-tree-size", cl::init(3), cl::Hidden, 145 cl::desc("Only vectorize small trees if they are fully vectorizable")); 146 147 static cl::opt<bool> 148 ViewSLPTree("view-slp-tree", cl::Hidden, 149 cl::desc("Display the SLP trees with Graphviz")); 150 151 // Limit the number of alias checks. The limit is chosen so that 152 // it has no negative effect on the llvm benchmarks. 153 static const unsigned AliasedCheckLimit = 10; 154 155 // Another limit for the alias checks: The maximum distance between load/store 156 // instructions where alias checks are done. 157 // This limit is useful for very large basic blocks. 158 static const unsigned MaxMemDepDistance = 160; 159 160 /// If the ScheduleRegionSizeBudget is exhausted, we allow small scheduling 161 /// regions to be handled. 162 static const int MinScheduleRegionSize = 16; 163 164 /// \brief Predicate for the element types that the SLP vectorizer supports. 165 /// 166 /// The most important thing to filter here are types which are invalid in LLVM 167 /// vectors. We also filter target specific types which have absolutely no 168 /// meaningful vectorization path such as x86_fp80 and ppc_f128. This just 169 /// avoids spending time checking the cost model and realizing that they will 170 /// be inevitably scalarized. 171 static bool isValidElementType(Type *Ty) { 172 return VectorType::isValidElementType(Ty) && !Ty->isX86_FP80Ty() && 173 !Ty->isPPC_FP128Ty(); 174 } 175 176 /// \returns true if all of the instructions in \p VL are in the same block or 177 /// false otherwise. 178 static bool allSameBlock(ArrayRef<Value *> VL) { 179 Instruction *I0 = dyn_cast<Instruction>(VL[0]); 180 if (!I0) 181 return false; 182 BasicBlock *BB = I0->getParent(); 183 for (int i = 1, e = VL.size(); i < e; i++) { 184 Instruction *I = dyn_cast<Instruction>(VL[i]); 185 if (!I) 186 return false; 187 188 if (BB != I->getParent()) 189 return false; 190 } 191 return true; 192 } 193 194 /// \returns True if all of the values in \p VL are constants. 195 static bool allConstant(ArrayRef<Value *> VL) { 196 for (Value *i : VL) 197 if (!isa<Constant>(i)) 198 return false; 199 return true; 200 } 201 202 /// \returns True if all of the values in \p VL are identical. 203 static bool isSplat(ArrayRef<Value *> VL) { 204 for (unsigned i = 1, e = VL.size(); i < e; ++i) 205 if (VL[i] != VL[0]) 206 return false; 207 return true; 208 } 209 210 /// Checks if the vector of instructions can be represented as a shuffle, like: 211 /// %x0 = extractelement <4 x i8> %x, i32 0 212 /// %x3 = extractelement <4 x i8> %x, i32 3 213 /// %y1 = extractelement <4 x i8> %y, i32 1 214 /// %y2 = extractelement <4 x i8> %y, i32 2 215 /// %x0x0 = mul i8 %x0, %x0 216 /// %x3x3 = mul i8 %x3, %x3 217 /// %y1y1 = mul i8 %y1, %y1 218 /// %y2y2 = mul i8 %y2, %y2 219 /// %ins1 = insertelement <4 x i8> undef, i8 %x0x0, i32 0 220 /// %ins2 = insertelement <4 x i8> %ins1, i8 %x3x3, i32 1 221 /// %ins3 = insertelement <4 x i8> %ins2, i8 %y1y1, i32 2 222 /// %ins4 = insertelement <4 x i8> %ins3, i8 %y2y2, i32 3 223 /// ret <4 x i8> %ins4 224 /// can be transformed into: 225 /// %1 = shufflevector <4 x i8> %x, <4 x i8> %y, <4 x i32> <i32 0, i32 3, i32 5, 226 /// i32 6> 227 /// %2 = mul <4 x i8> %1, %1 228 /// ret <4 x i8> %2 229 /// We convert this initially to something like: 230 /// %x0 = extractelement <4 x i8> %x, i32 0 231 /// %x3 = extractelement <4 x i8> %x, i32 3 232 /// %y1 = extractelement <4 x i8> %y, i32 1 233 /// %y2 = extractelement <4 x i8> %y, i32 2 234 /// %1 = insertelement <4 x i8> undef, i8 %x0, i32 0 235 /// %2 = insertelement <4 x i8> %1, i8 %x3, i32 1 236 /// %3 = insertelement <4 x i8> %2, i8 %y1, i32 2 237 /// %4 = insertelement <4 x i8> %3, i8 %y2, i32 3 238 /// %5 = mul <4 x i8> %4, %4 239 /// %6 = extractelement <4 x i8> %5, i32 0 240 /// %ins1 = insertelement <4 x i8> undef, i8 %6, i32 0 241 /// %7 = extractelement <4 x i8> %5, i32 1 242 /// %ins2 = insertelement <4 x i8> %ins1, i8 %7, i32 1 243 /// %8 = extractelement <4 x i8> %5, i32 2 244 /// %ins3 = insertelement <4 x i8> %ins2, i8 %8, i32 2 245 /// %9 = extractelement <4 x i8> %5, i32 3 246 /// %ins4 = insertelement <4 x i8> %ins3, i8 %9, i32 3 247 /// ret <4 x i8> %ins4 248 /// InstCombiner transforms this into a shuffle and vector mul 249 static Optional<TargetTransformInfo::ShuffleKind> 250 isShuffle(ArrayRef<Value *> VL) { 251 auto *EI0 = cast<ExtractElementInst>(VL[0]); 252 unsigned Size = EI0->getVectorOperandType()->getVectorNumElements(); 253 Value *Vec1 = nullptr; 254 Value *Vec2 = nullptr; 255 enum ShuffleMode {Unknown, FirstAlternate, SecondAlternate, Permute}; 256 ShuffleMode CommonShuffleMode = Unknown; 257 for (unsigned I = 0, E = VL.size(); I < E; ++I) { 258 auto *EI = cast<ExtractElementInst>(VL[I]); 259 auto *Vec = EI->getVectorOperand(); 260 // All vector operands must have the same number of vector elements. 261 if (Vec->getType()->getVectorNumElements() != Size) 262 return None; 263 auto *Idx = dyn_cast<ConstantInt>(EI->getIndexOperand()); 264 if (!Idx) 265 return None; 266 // Undefined behavior if Idx is negative or >= Size. 267 if (Idx->getValue().uge(Size)) 268 continue; 269 unsigned IntIdx = Idx->getValue().getZExtValue(); 270 // We can extractelement from undef vector. 271 if (isa<UndefValue>(Vec)) 272 continue; 273 // For correct shuffling we have to have at most 2 different vector operands 274 // in all extractelement instructions. 275 if (Vec1 && Vec2 && Vec != Vec1 && Vec != Vec2) 276 return None; 277 if (CommonShuffleMode == Permute) 278 continue; 279 // If the extract index is not the same as the operation number, it is a 280 // permutation. 281 if (IntIdx != I) { 282 CommonShuffleMode = Permute; 283 continue; 284 } 285 // Check the shuffle mode for the current operation. 286 if (!Vec1) 287 Vec1 = Vec; 288 else if (Vec != Vec1) 289 Vec2 = Vec; 290 // Example: shufflevector A, B, <0,5,2,7> 291 // I is odd and IntIdx for A == I - FirstAlternate shuffle. 292 // I is even and IntIdx for B == I - FirstAlternate shuffle. 293 // Example: shufflevector A, B, <4,1,6,3> 294 // I is even and IntIdx for A == I - SecondAlternate shuffle. 295 // I is odd and IntIdx for B == I - SecondAlternate shuffle. 296 const bool IIsEven = I & 1; 297 const bool CurrVecIsA = Vec == Vec1; 298 const bool IIsOdd = !IIsEven; 299 const bool CurrVecIsB = !CurrVecIsA; 300 ShuffleMode CurrentShuffleMode = 301 ((IIsOdd && CurrVecIsA) || (IIsEven && CurrVecIsB)) ? FirstAlternate 302 : SecondAlternate; 303 // Common mode is not set or the same as the shuffle mode of the current 304 // operation - alternate. 305 if (CommonShuffleMode == Unknown) 306 CommonShuffleMode = CurrentShuffleMode; 307 // Common shuffle mode is not the same as the shuffle mode of the current 308 // operation - permutation. 309 if (CommonShuffleMode != CurrentShuffleMode) 310 CommonShuffleMode = Permute; 311 } 312 // If we're not crossing lanes in different vectors, consider it as blending. 313 if ((CommonShuffleMode == FirstAlternate || 314 CommonShuffleMode == SecondAlternate) && 315 Vec2) 316 return TargetTransformInfo::SK_Alternate; 317 // If Vec2 was never used, we have a permutation of a single vector, otherwise 318 // we have permutation of 2 vectors. 319 return Vec2 ? TargetTransformInfo::SK_PermuteTwoSrc 320 : TargetTransformInfo::SK_PermuteSingleSrc; 321 } 322 323 ///\returns Opcode that can be clubbed with \p Op to create an alternate 324 /// sequence which can later be merged as a ShuffleVector instruction. 325 static unsigned getAltOpcode(unsigned Op) { 326 switch (Op) { 327 case Instruction::FAdd: 328 return Instruction::FSub; 329 case Instruction::FSub: 330 return Instruction::FAdd; 331 case Instruction::Add: 332 return Instruction::Sub; 333 case Instruction::Sub: 334 return Instruction::Add; 335 default: 336 return 0; 337 } 338 } 339 340 static bool isOdd(unsigned Value) { 341 return Value & 1; 342 } 343 344 static bool sameOpcodeOrAlt(unsigned Opcode, unsigned AltOpcode, 345 unsigned CheckedOpcode) { 346 return Opcode == CheckedOpcode || AltOpcode == CheckedOpcode; 347 } 348 349 /// Chooses the correct key for scheduling data. If \p Op has the same (or 350 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is \p 351 /// OpValue. 352 static Value *isOneOf(Value *OpValue, Value *Op) { 353 auto *I = dyn_cast<Instruction>(Op); 354 if (!I) 355 return OpValue; 356 auto *OpInst = cast<Instruction>(OpValue); 357 unsigned OpInstOpcode = OpInst->getOpcode(); 358 unsigned IOpcode = I->getOpcode(); 359 if (sameOpcodeOrAlt(OpInstOpcode, getAltOpcode(OpInstOpcode), IOpcode)) 360 return Op; 361 return OpValue; 362 } 363 364 namespace { 365 366 /// Contains data for the instructions going to be vectorized. 367 struct RawInstructionsData { 368 /// Main Opcode of the instructions going to be vectorized. 369 unsigned Opcode = 0; 370 371 /// The list of instructions have some instructions with alternate opcodes. 372 bool HasAltOpcodes = false; 373 }; 374 375 } // end anonymous namespace 376 377 /// Checks the list of the vectorized instructions \p VL and returns info about 378 /// this list. 379 static RawInstructionsData getMainOpcode(ArrayRef<Value *> VL) { 380 auto *I0 = dyn_cast<Instruction>(VL[0]); 381 if (!I0) 382 return {}; 383 RawInstructionsData Res; 384 unsigned Opcode = I0->getOpcode(); 385 // Walk through the list of the vectorized instructions 386 // in order to check its structure described by RawInstructionsData. 387 for (unsigned Cnt = 0, E = VL.size(); Cnt != E; ++Cnt) { 388 auto *I = dyn_cast<Instruction>(VL[Cnt]); 389 if (!I) 390 return {}; 391 if (Opcode != I->getOpcode()) 392 Res.HasAltOpcodes = true; 393 } 394 Res.Opcode = Opcode; 395 return Res; 396 } 397 398 namespace { 399 400 /// Main data required for vectorization of instructions. 401 struct InstructionsState { 402 /// The very first instruction in the list with the main opcode. 403 Value *OpValue = nullptr; 404 405 /// The main opcode for the list of instructions. 406 unsigned Opcode = 0; 407 408 /// Some of the instructions in the list have alternate opcodes. 409 bool IsAltShuffle = false; 410 411 InstructionsState() = default; 412 InstructionsState(Value *OpValue, unsigned Opcode, bool IsAltShuffle) 413 : OpValue(OpValue), Opcode(Opcode), IsAltShuffle(IsAltShuffle) {} 414 }; 415 416 } // end anonymous namespace 417 418 /// \returns analysis of the Instructions in \p VL described in 419 /// InstructionsState, the Opcode that we suppose the whole list 420 /// could be vectorized even if its structure is diverse. 421 static InstructionsState getSameOpcode(ArrayRef<Value *> VL) { 422 auto Res = getMainOpcode(VL); 423 unsigned Opcode = Res.Opcode; 424 if (!Res.HasAltOpcodes) 425 return InstructionsState(VL[0], Opcode, false); 426 auto *OpInst = cast<Instruction>(VL[0]); 427 unsigned AltOpcode = getAltOpcode(Opcode); 428 // Examine each element in the list instructions VL to determine 429 // if some operations there could be considered as an alternative 430 // (for example as subtraction relates to addition operation). 431 for (int Cnt = 0, E = VL.size(); Cnt < E; Cnt++) { 432 auto *I = cast<Instruction>(VL[Cnt]); 433 unsigned InstOpcode = I->getOpcode(); 434 if ((Res.HasAltOpcodes && 435 InstOpcode != (isOdd(Cnt) ? AltOpcode : Opcode)) || 436 (!Res.HasAltOpcodes && InstOpcode != Opcode)) { 437 return InstructionsState(OpInst, 0, false); 438 } 439 } 440 return InstructionsState(OpInst, Opcode, Res.HasAltOpcodes); 441 } 442 443 /// \returns true if all of the values in \p VL have the same type or false 444 /// otherwise. 445 static bool allSameType(ArrayRef<Value *> VL) { 446 Type *Ty = VL[0]->getType(); 447 for (int i = 1, e = VL.size(); i < e; i++) 448 if (VL[i]->getType() != Ty) 449 return false; 450 451 return true; 452 } 453 454 /// \returns True if Extract{Value,Element} instruction extracts element Idx. 455 static bool matchExtractIndex(Instruction *E, unsigned Idx, unsigned Opcode) { 456 assert(Opcode == Instruction::ExtractElement || 457 Opcode == Instruction::ExtractValue); 458 if (Opcode == Instruction::ExtractElement) { 459 ConstantInt *CI = dyn_cast<ConstantInt>(E->getOperand(1)); 460 return CI && CI->getZExtValue() == Idx; 461 } else { 462 ExtractValueInst *EI = cast<ExtractValueInst>(E); 463 return EI->getNumIndices() == 1 && *EI->idx_begin() == Idx; 464 } 465 } 466 467 /// \returns True if in-tree use also needs extract. This refers to 468 /// possible scalar operand in vectorized instruction. 469 static bool InTreeUserNeedToExtract(Value *Scalar, Instruction *UserInst, 470 TargetLibraryInfo *TLI) { 471 unsigned Opcode = UserInst->getOpcode(); 472 switch (Opcode) { 473 case Instruction::Load: { 474 LoadInst *LI = cast<LoadInst>(UserInst); 475 return (LI->getPointerOperand() == Scalar); 476 } 477 case Instruction::Store: { 478 StoreInst *SI = cast<StoreInst>(UserInst); 479 return (SI->getPointerOperand() == Scalar); 480 } 481 case Instruction::Call: { 482 CallInst *CI = cast<CallInst>(UserInst); 483 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 484 if (hasVectorInstrinsicScalarOpd(ID, 1)) { 485 return (CI->getArgOperand(1) == Scalar); 486 } 487 LLVM_FALLTHROUGH; 488 } 489 default: 490 return false; 491 } 492 } 493 494 /// \returns the AA location that is being access by the instruction. 495 static MemoryLocation getLocation(Instruction *I, AliasAnalysis *AA) { 496 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 497 return MemoryLocation::get(SI); 498 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 499 return MemoryLocation::get(LI); 500 return MemoryLocation(); 501 } 502 503 /// \returns True if the instruction is not a volatile or atomic load/store. 504 static bool isSimple(Instruction *I) { 505 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 506 return LI->isSimple(); 507 if (StoreInst *SI = dyn_cast<StoreInst>(I)) 508 return SI->isSimple(); 509 if (MemIntrinsic *MI = dyn_cast<MemIntrinsic>(I)) 510 return !MI->isVolatile(); 511 return true; 512 } 513 514 namespace llvm { 515 516 namespace slpvectorizer { 517 518 /// Bottom Up SLP Vectorizer. 519 class BoUpSLP { 520 public: 521 using ValueList = SmallVector<Value *, 8>; 522 using InstrList = SmallVector<Instruction *, 16>; 523 using ValueSet = SmallPtrSet<Value *, 16>; 524 using StoreList = SmallVector<StoreInst *, 8>; 525 using ExtraValueToDebugLocsMap = 526 MapVector<Value *, SmallVector<Instruction *, 2>>; 527 528 BoUpSLP(Function *Func, ScalarEvolution *Se, TargetTransformInfo *Tti, 529 TargetLibraryInfo *TLi, AliasAnalysis *Aa, LoopInfo *Li, 530 DominatorTree *Dt, AssumptionCache *AC, DemandedBits *DB, 531 const DataLayout *DL, OptimizationRemarkEmitter *ORE) 532 : F(Func), SE(Se), TTI(Tti), TLI(TLi), AA(Aa), LI(Li), DT(Dt), AC(AC), 533 DB(DB), DL(DL), ORE(ORE), Builder(Se->getContext()) { 534 CodeMetrics::collectEphemeralValues(F, AC, EphValues); 535 // Use the vector register size specified by the target unless overridden 536 // by a command-line option. 537 // TODO: It would be better to limit the vectorization factor based on 538 // data type rather than just register size. For example, x86 AVX has 539 // 256-bit registers, but it does not support integer operations 540 // at that width (that requires AVX2). 541 if (MaxVectorRegSizeOption.getNumOccurrences()) 542 MaxVecRegSize = MaxVectorRegSizeOption; 543 else 544 MaxVecRegSize = TTI->getRegisterBitWidth(true); 545 546 if (MinVectorRegSizeOption.getNumOccurrences()) 547 MinVecRegSize = MinVectorRegSizeOption; 548 else 549 MinVecRegSize = TTI->getMinVectorRegisterBitWidth(); 550 } 551 552 /// \brief Vectorize the tree that starts with the elements in \p VL. 553 /// Returns the vectorized root. 554 Value *vectorizeTree(); 555 556 /// Vectorize the tree but with the list of externally used values \p 557 /// ExternallyUsedValues. Values in this MapVector can be replaced but the 558 /// generated extractvalue instructions. 559 Value *vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues); 560 561 /// \returns the cost incurred by unwanted spills and fills, caused by 562 /// holding live values over call sites. 563 int getSpillCost(); 564 565 /// \returns the vectorization cost of the subtree that starts at \p VL. 566 /// A negative number means that this is profitable. 567 int getTreeCost(); 568 569 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 570 /// the purpose of scheduling and extraction in the \p UserIgnoreLst. 571 void buildTree(ArrayRef<Value *> Roots, 572 ArrayRef<Value *> UserIgnoreLst = None); 573 574 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for 575 /// the purpose of scheduling and extraction in the \p UserIgnoreLst taking 576 /// into account (anf updating it, if required) list of externally used 577 /// values stored in \p ExternallyUsedValues. 578 void buildTree(ArrayRef<Value *> Roots, 579 ExtraValueToDebugLocsMap &ExternallyUsedValues, 580 ArrayRef<Value *> UserIgnoreLst = None); 581 582 /// Clear the internal data structures that are created by 'buildTree'. 583 void deleteTree() { 584 VectorizableTree.clear(); 585 ScalarToTreeEntry.clear(); 586 MustGather.clear(); 587 ExternalUses.clear(); 588 NumOpsWantToKeepOrder.clear(); 589 for (auto &Iter : BlocksSchedules) { 590 BlockScheduling *BS = Iter.second.get(); 591 BS->clear(); 592 } 593 MinBWs.clear(); 594 } 595 596 unsigned getTreeSize() const { return VectorizableTree.size(); } 597 598 /// \brief Perform LICM and CSE on the newly generated gather sequences. 599 void optimizeGatherSequence(); 600 601 /// \returns true if it is beneficial to reverse the vector order. 602 bool shouldReorder() const { 603 return std::accumulate( 604 NumOpsWantToKeepOrder.begin(), NumOpsWantToKeepOrder.end(), 0, 605 [](int Val1, 606 const decltype(NumOpsWantToKeepOrder)::value_type &Val2) { 607 return Val1 + (Val2.second < 0 ? 1 : -1); 608 }) > 0; 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); 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 /// \brief Check if ArrayType or StructType is isomorphic to some VectorType. 633 /// 634 /// \returns number of elements in vector if isomorphism exists, 0 otherwise. 635 unsigned canMapToVector(Type *T, const DataLayout &DL) const; 636 637 /// \returns True if the VectorizableTree is both tiny and not fully 638 /// vectorizable. We do not vectorize such trees. 639 bool isTreeTinyAndNotFullyVectorizable(); 640 641 OptimizationRemarkEmitter *getORE() { return ORE; } 642 643 private: 644 struct TreeEntry; 645 646 /// Checks if all users of \p I are the part of the vectorization tree. 647 bool areAllUsersVectorized(Instruction *I) const; 648 649 /// \returns the cost of the vectorizable entry. 650 int getEntryCost(TreeEntry *E); 651 652 /// This is the recursive part of buildTree. 653 void buildTree_rec(ArrayRef<Value *> Roots, unsigned Depth, int); 654 655 /// \returns True if the ExtractElement/ExtractValue instructions in VL can 656 /// be vectorized to use the original vector (or aggregate "bitcast" to a vector). 657 bool canReuseExtract(ArrayRef<Value *> VL, Value *OpValue) const; 658 659 /// Vectorize a single entry in the tree. 660 Value *vectorizeTree(TreeEntry *E); 661 662 /// Vectorize a single entry in the tree, starting in \p VL. 663 Value *vectorizeTree(ArrayRef<Value *> VL); 664 665 /// \returns the scalarization cost for this type. Scalarization in this 666 /// context means the creation of vectors from a group of scalars. 667 int getGatherCost(Type *Ty, const DenseSet<unsigned> &ShuffledIndices); 668 669 /// \returns the scalarization cost for this list of values. Assuming that 670 /// this subtree gets vectorized, we may need to extract the values from the 671 /// roots. This method calculates the cost of extracting the values. 672 int getGatherCost(ArrayRef<Value *> VL); 673 674 /// \brief Set the Builder insert point to one after the last instruction in 675 /// the bundle 676 void setInsertPointAfterBundle(ArrayRef<Value *> VL, Value *OpValue); 677 678 /// \returns a vector from a collection of scalars in \p VL. 679 Value *Gather(ArrayRef<Value *> VL, VectorType *Ty); 680 681 /// \returns whether the VectorizableTree is fully vectorizable and will 682 /// be beneficial even the tree height is tiny. 683 bool isFullyVectorizableTinyTree(); 684 685 /// \reorder commutative operands in alt shuffle if they result in 686 /// vectorized code. 687 void reorderAltShuffleOperands(unsigned Opcode, ArrayRef<Value *> VL, 688 SmallVectorImpl<Value *> &Left, 689 SmallVectorImpl<Value *> &Right); 690 691 /// \reorder commutative operands to get better probability of 692 /// generating vectorized code. 693 void reorderInputsAccordingToOpcode(unsigned Opcode, ArrayRef<Value *> VL, 694 SmallVectorImpl<Value *> &Left, 695 SmallVectorImpl<Value *> &Right); 696 struct TreeEntry { 697 TreeEntry(std::vector<TreeEntry> &Container) : Container(Container) {} 698 699 /// \returns true if the scalars in VL are equal to this entry. 700 bool isSame(ArrayRef<Value *> VL) const { 701 if (VL.size() == Scalars.size()) 702 return std::equal(VL.begin(), VL.end(), Scalars.begin()); 703 return VL.size() == ReuseShuffleIndices.size() && 704 std::equal( 705 VL.begin(), VL.end(), ReuseShuffleIndices.begin(), 706 [this](Value *V, unsigned Idx) { return V == Scalars[Idx]; }); 707 } 708 709 /// A vector of scalars. 710 ValueList Scalars; 711 712 /// The Scalars are vectorized into this value. It is initialized to Null. 713 Value *VectorizedValue = nullptr; 714 715 /// Do we need to gather this sequence ? 716 bool NeedToGather = false; 717 718 /// Does this sequence require some shuffling? 719 SmallVector<unsigned, 4> ReuseShuffleIndices; 720 721 /// Points back to the VectorizableTree. 722 /// 723 /// Only used for Graphviz right now. Unfortunately GraphTrait::NodeRef has 724 /// to be a pointer and needs to be able to initialize the child iterator. 725 /// Thus we need a reference back to the container to translate the indices 726 /// to entries. 727 std::vector<TreeEntry> &Container; 728 729 /// The TreeEntry index containing the user of this entry. We can actually 730 /// have multiple users so the data structure is not truly a tree. 731 SmallVector<int, 1> UserTreeIndices; 732 }; 733 734 /// Create a new VectorizableTree entry. 735 void newTreeEntry(ArrayRef<Value *> VL, bool Vectorized, int &UserTreeIdx, 736 ArrayRef<unsigned> ReuseShuffleIndices = None) { 737 VectorizableTree.emplace_back(VectorizableTree); 738 int idx = VectorizableTree.size() - 1; 739 TreeEntry *Last = &VectorizableTree[idx]; 740 Last->Scalars.insert(Last->Scalars.begin(), VL.begin(), VL.end()); 741 Last->NeedToGather = !Vectorized; 742 Last->ReuseShuffleIndices.append(ReuseShuffleIndices.begin(), 743 ReuseShuffleIndices.end()); 744 if (Vectorized) { 745 for (int i = 0, e = VL.size(); i != e; ++i) { 746 assert(!getTreeEntry(VL[i]) && "Scalar already in tree!"); 747 ScalarToTreeEntry[VL[i]] = idx; 748 } 749 } else { 750 MustGather.insert(VL.begin(), VL.end()); 751 } 752 753 if (UserTreeIdx >= 0) 754 Last->UserTreeIndices.push_back(UserTreeIdx); 755 UserTreeIdx = idx; 756 } 757 758 /// -- Vectorization State -- 759 /// Holds all of the tree entries. 760 std::vector<TreeEntry> VectorizableTree; 761 762 TreeEntry *getTreeEntry(Value *V) { 763 auto I = ScalarToTreeEntry.find(V); 764 if (I != ScalarToTreeEntry.end()) 765 return &VectorizableTree[I->second]; 766 return nullptr; 767 } 768 769 /// Maps a specific scalar to its tree entry. 770 SmallDenseMap<Value*, int> ScalarToTreeEntry; 771 772 /// A list of scalars that we found that we need to keep as scalars. 773 ValueSet MustGather; 774 775 /// This POD struct describes one external user in the vectorized tree. 776 struct ExternalUser { 777 ExternalUser(Value *S, llvm::User *U, int L) 778 : Scalar(S), User(U), Lane(L) {} 779 780 // Which scalar in our function. 781 Value *Scalar; 782 783 // Which user that uses the scalar. 784 llvm::User *User; 785 786 // Which lane does the scalar belong to. 787 int Lane; 788 }; 789 using UserList = SmallVector<ExternalUser, 16>; 790 791 /// Checks if two instructions may access the same memory. 792 /// 793 /// \p Loc1 is the location of \p Inst1. It is passed explicitly because it 794 /// is invariant in the calling loop. 795 bool isAliased(const MemoryLocation &Loc1, Instruction *Inst1, 796 Instruction *Inst2) { 797 // First check if the result is already in the cache. 798 AliasCacheKey key = std::make_pair(Inst1, Inst2); 799 Optional<bool> &result = AliasCache[key]; 800 if (result.hasValue()) { 801 return result.getValue(); 802 } 803 MemoryLocation Loc2 = getLocation(Inst2, AA); 804 bool aliased = true; 805 if (Loc1.Ptr && Loc2.Ptr && isSimple(Inst1) && isSimple(Inst2)) { 806 // Do the alias check. 807 aliased = AA->alias(Loc1, Loc2); 808 } 809 // Store the result in the cache. 810 result = aliased; 811 return aliased; 812 } 813 814 using AliasCacheKey = std::pair<Instruction *, Instruction *>; 815 816 /// Cache for alias results. 817 /// TODO: consider moving this to the AliasAnalysis itself. 818 DenseMap<AliasCacheKey, Optional<bool>> AliasCache; 819 820 /// Removes an instruction from its block and eventually deletes it. 821 /// It's like Instruction::eraseFromParent() except that the actual deletion 822 /// is delayed until BoUpSLP is destructed. 823 /// This is required to ensure that there are no incorrect collisions in the 824 /// AliasCache, which can happen if a new instruction is allocated at the 825 /// same address as a previously deleted instruction. 826 void eraseInstruction(Instruction *I) { 827 I->removeFromParent(); 828 I->dropAllReferences(); 829 DeletedInstructions.emplace_back(I); 830 } 831 832 /// Temporary store for deleted instructions. Instructions will be deleted 833 /// eventually when the BoUpSLP is destructed. 834 SmallVector<unique_value, 8> DeletedInstructions; 835 836 /// A list of values that need to extracted out of the tree. 837 /// This list holds pairs of (Internal Scalar : External User). External User 838 /// can be nullptr, it means that this Internal Scalar will be used later, 839 /// after vectorization. 840 UserList ExternalUses; 841 842 /// Values used only by @llvm.assume calls. 843 SmallPtrSet<const Value *, 32> EphValues; 844 845 /// Holds all of the instructions that we gathered. 846 SetVector<Instruction *> GatherSeq; 847 848 /// A list of blocks that we are going to CSE. 849 SetVector<BasicBlock *> CSEBlocks; 850 851 /// Contains all scheduling relevant data for an instruction. 852 /// A ScheduleData either represents a single instruction or a member of an 853 /// instruction bundle (= a group of instructions which is combined into a 854 /// vector instruction). 855 struct ScheduleData { 856 // The initial value for the dependency counters. It means that the 857 // dependencies are not calculated yet. 858 enum { InvalidDeps = -1 }; 859 860 ScheduleData() = default; 861 862 void init(int BlockSchedulingRegionID, Value *OpVal) { 863 FirstInBundle = this; 864 NextInBundle = nullptr; 865 NextLoadStore = nullptr; 866 IsScheduled = false; 867 SchedulingRegionID = BlockSchedulingRegionID; 868 UnscheduledDepsInBundle = UnscheduledDeps; 869 clearDependencies(); 870 OpValue = OpVal; 871 } 872 873 /// Returns true if the dependency information has been calculated. 874 bool hasValidDependencies() const { return Dependencies != InvalidDeps; } 875 876 /// Returns true for single instructions and for bundle representatives 877 /// (= the head of a bundle). 878 bool isSchedulingEntity() const { return FirstInBundle == this; } 879 880 /// Returns true if it represents an instruction bundle and not only a 881 /// single instruction. 882 bool isPartOfBundle() const { 883 return NextInBundle != nullptr || FirstInBundle != this; 884 } 885 886 /// Returns true if it is ready for scheduling, i.e. it has no more 887 /// unscheduled depending instructions/bundles. 888 bool isReady() const { 889 assert(isSchedulingEntity() && 890 "can't consider non-scheduling entity for ready list"); 891 return UnscheduledDepsInBundle == 0 && !IsScheduled; 892 } 893 894 /// Modifies the number of unscheduled dependencies, also updating it for 895 /// the whole bundle. 896 int incrementUnscheduledDeps(int Incr) { 897 UnscheduledDeps += Incr; 898 return FirstInBundle->UnscheduledDepsInBundle += Incr; 899 } 900 901 /// Sets the number of unscheduled dependencies to the number of 902 /// dependencies. 903 void resetUnscheduledDeps() { 904 incrementUnscheduledDeps(Dependencies - UnscheduledDeps); 905 } 906 907 /// Clears all dependency information. 908 void clearDependencies() { 909 Dependencies = InvalidDeps; 910 resetUnscheduledDeps(); 911 MemoryDependencies.clear(); 912 } 913 914 void dump(raw_ostream &os) const { 915 if (!isSchedulingEntity()) { 916 os << "/ " << *Inst; 917 } else if (NextInBundle) { 918 os << '[' << *Inst; 919 ScheduleData *SD = NextInBundle; 920 while (SD) { 921 os << ';' << *SD->Inst; 922 SD = SD->NextInBundle; 923 } 924 os << ']'; 925 } else { 926 os << *Inst; 927 } 928 } 929 930 Instruction *Inst = nullptr; 931 932 /// Points to the head in an instruction bundle (and always to this for 933 /// single instructions). 934 ScheduleData *FirstInBundle = nullptr; 935 936 /// Single linked list of all instructions in a bundle. Null if it is a 937 /// single instruction. 938 ScheduleData *NextInBundle = nullptr; 939 940 /// Single linked list of all memory instructions (e.g. load, store, call) 941 /// in the block - until the end of the scheduling region. 942 ScheduleData *NextLoadStore = nullptr; 943 944 /// The dependent memory instructions. 945 /// This list is derived on demand in calculateDependencies(). 946 SmallVector<ScheduleData *, 4> MemoryDependencies; 947 948 /// This ScheduleData is in the current scheduling region if this matches 949 /// the current SchedulingRegionID of BlockScheduling. 950 int SchedulingRegionID = 0; 951 952 /// Used for getting a "good" final ordering of instructions. 953 int SchedulingPriority = 0; 954 955 /// The number of dependencies. Constitutes of the number of users of the 956 /// instruction plus the number of dependent memory instructions (if any). 957 /// This value is calculated on demand. 958 /// If InvalidDeps, the number of dependencies is not calculated yet. 959 int Dependencies = InvalidDeps; 960 961 /// The number of dependencies minus the number of dependencies of scheduled 962 /// instructions. As soon as this is zero, the instruction/bundle gets ready 963 /// for scheduling. 964 /// Note that this is negative as long as Dependencies is not calculated. 965 int UnscheduledDeps = InvalidDeps; 966 967 /// The sum of UnscheduledDeps in a bundle. Equals to UnscheduledDeps for 968 /// single instructions. 969 int UnscheduledDepsInBundle = InvalidDeps; 970 971 /// True if this instruction is scheduled (or considered as scheduled in the 972 /// dry-run). 973 bool IsScheduled = false; 974 975 /// Opcode of the current instruction in the schedule data. 976 Value *OpValue = nullptr; 977 }; 978 979 #ifndef NDEBUG 980 friend inline raw_ostream &operator<<(raw_ostream &os, 981 const BoUpSLP::ScheduleData &SD) { 982 SD.dump(os); 983 return os; 984 } 985 #endif 986 987 friend struct GraphTraits<BoUpSLP *>; 988 friend struct DOTGraphTraits<BoUpSLP *>; 989 990 /// Contains all scheduling data for a basic block. 991 struct BlockScheduling { 992 BlockScheduling(BasicBlock *BB) 993 : BB(BB), ChunkSize(BB->size()), ChunkPos(ChunkSize) {} 994 995 void clear() { 996 ReadyInsts.clear(); 997 ScheduleStart = nullptr; 998 ScheduleEnd = nullptr; 999 FirstLoadStoreInRegion = nullptr; 1000 LastLoadStoreInRegion = nullptr; 1001 1002 // Reduce the maximum schedule region size by the size of the 1003 // previous scheduling run. 1004 ScheduleRegionSizeLimit -= ScheduleRegionSize; 1005 if (ScheduleRegionSizeLimit < MinScheduleRegionSize) 1006 ScheduleRegionSizeLimit = MinScheduleRegionSize; 1007 ScheduleRegionSize = 0; 1008 1009 // Make a new scheduling region, i.e. all existing ScheduleData is not 1010 // in the new region yet. 1011 ++SchedulingRegionID; 1012 } 1013 1014 ScheduleData *getScheduleData(Value *V) { 1015 ScheduleData *SD = ScheduleDataMap[V]; 1016 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 1017 return SD; 1018 return nullptr; 1019 } 1020 1021 ScheduleData *getScheduleData(Value *V, Value *Key) { 1022 if (V == Key) 1023 return getScheduleData(V); 1024 auto I = ExtraScheduleDataMap.find(V); 1025 if (I != ExtraScheduleDataMap.end()) { 1026 ScheduleData *SD = I->second[Key]; 1027 if (SD && SD->SchedulingRegionID == SchedulingRegionID) 1028 return SD; 1029 } 1030 return nullptr; 1031 } 1032 1033 bool isInSchedulingRegion(ScheduleData *SD) { 1034 return SD->SchedulingRegionID == SchedulingRegionID; 1035 } 1036 1037 /// Marks an instruction as scheduled and puts all dependent ready 1038 /// instructions into the ready-list. 1039 template <typename ReadyListType> 1040 void schedule(ScheduleData *SD, ReadyListType &ReadyList) { 1041 SD->IsScheduled = true; 1042 DEBUG(dbgs() << "SLP: schedule " << *SD << "\n"); 1043 1044 ScheduleData *BundleMember = SD; 1045 while (BundleMember) { 1046 if (BundleMember->Inst != BundleMember->OpValue) { 1047 BundleMember = BundleMember->NextInBundle; 1048 continue; 1049 } 1050 // Handle the def-use chain dependencies. 1051 for (Use &U : BundleMember->Inst->operands()) { 1052 auto *I = dyn_cast<Instruction>(U.get()); 1053 if (!I) 1054 continue; 1055 doForAllOpcodes(I, [&ReadyList](ScheduleData *OpDef) { 1056 if (OpDef && OpDef->hasValidDependencies() && 1057 OpDef->incrementUnscheduledDeps(-1) == 0) { 1058 // There are no more unscheduled dependencies after 1059 // decrementing, so we can put the dependent instruction 1060 // into the ready list. 1061 ScheduleData *DepBundle = OpDef->FirstInBundle; 1062 assert(!DepBundle->IsScheduled && 1063 "already scheduled bundle gets ready"); 1064 ReadyList.insert(DepBundle); 1065 DEBUG(dbgs() 1066 << "SLP: gets ready (def): " << *DepBundle << "\n"); 1067 } 1068 }); 1069 } 1070 // Handle the memory dependencies. 1071 for (ScheduleData *MemoryDepSD : BundleMember->MemoryDependencies) { 1072 if (MemoryDepSD->incrementUnscheduledDeps(-1) == 0) { 1073 // There are no more unscheduled dependencies after decrementing, 1074 // so we can put the dependent instruction into the ready list. 1075 ScheduleData *DepBundle = MemoryDepSD->FirstInBundle; 1076 assert(!DepBundle->IsScheduled && 1077 "already scheduled bundle gets ready"); 1078 ReadyList.insert(DepBundle); 1079 DEBUG(dbgs() << "SLP: gets ready (mem): " << *DepBundle 1080 << "\n"); 1081 } 1082 } 1083 BundleMember = BundleMember->NextInBundle; 1084 } 1085 } 1086 1087 void doForAllOpcodes(Value *V, 1088 function_ref<void(ScheduleData *SD)> Action) { 1089 if (ScheduleData *SD = getScheduleData(V)) 1090 Action(SD); 1091 auto I = ExtraScheduleDataMap.find(V); 1092 if (I != ExtraScheduleDataMap.end()) 1093 for (auto &P : I->second) 1094 if (P.second->SchedulingRegionID == SchedulingRegionID) 1095 Action(P.second); 1096 } 1097 1098 /// Put all instructions into the ReadyList which are ready for scheduling. 1099 template <typename ReadyListType> 1100 void initialFillReadyList(ReadyListType &ReadyList) { 1101 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 1102 doForAllOpcodes(I, [&](ScheduleData *SD) { 1103 if (SD->isSchedulingEntity() && SD->isReady()) { 1104 ReadyList.insert(SD); 1105 DEBUG(dbgs() << "SLP: initially in ready list: " << *I << "\n"); 1106 } 1107 }); 1108 } 1109 } 1110 1111 /// Checks if a bundle of instructions can be scheduled, i.e. has no 1112 /// cyclic dependencies. This is only a dry-run, no instructions are 1113 /// actually moved at this stage. 1114 bool tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, Value *OpValue); 1115 1116 /// Un-bundles a group of instructions. 1117 void cancelScheduling(ArrayRef<Value *> VL, Value *OpValue); 1118 1119 /// Allocates schedule data chunk. 1120 ScheduleData *allocateScheduleDataChunks(); 1121 1122 /// Extends the scheduling region so that V is inside the region. 1123 /// \returns true if the region size is within the limit. 1124 bool extendSchedulingRegion(Value *V, Value *OpValue); 1125 1126 /// Initialize the ScheduleData structures for new instructions in the 1127 /// scheduling region. 1128 void initScheduleData(Instruction *FromI, Instruction *ToI, 1129 ScheduleData *PrevLoadStore, 1130 ScheduleData *NextLoadStore); 1131 1132 /// Updates the dependency information of a bundle and of all instructions/ 1133 /// bundles which depend on the original bundle. 1134 void calculateDependencies(ScheduleData *SD, bool InsertInReadyList, 1135 BoUpSLP *SLP); 1136 1137 /// Sets all instruction in the scheduling region to un-scheduled. 1138 void resetSchedule(); 1139 1140 BasicBlock *BB; 1141 1142 /// Simple memory allocation for ScheduleData. 1143 std::vector<std::unique_ptr<ScheduleData[]>> ScheduleDataChunks; 1144 1145 /// The size of a ScheduleData array in ScheduleDataChunks. 1146 int ChunkSize; 1147 1148 /// The allocator position in the current chunk, which is the last entry 1149 /// of ScheduleDataChunks. 1150 int ChunkPos; 1151 1152 /// Attaches ScheduleData to Instruction. 1153 /// Note that the mapping survives during all vectorization iterations, i.e. 1154 /// ScheduleData structures are recycled. 1155 DenseMap<Value *, ScheduleData *> ScheduleDataMap; 1156 1157 /// Attaches ScheduleData to Instruction with the leading key. 1158 DenseMap<Value *, SmallDenseMap<Value *, ScheduleData *>> 1159 ExtraScheduleDataMap; 1160 1161 struct ReadyList : SmallVector<ScheduleData *, 8> { 1162 void insert(ScheduleData *SD) { push_back(SD); } 1163 }; 1164 1165 /// The ready-list for scheduling (only used for the dry-run). 1166 ReadyList ReadyInsts; 1167 1168 /// The first instruction of the scheduling region. 1169 Instruction *ScheduleStart = nullptr; 1170 1171 /// The first instruction _after_ the scheduling region. 1172 Instruction *ScheduleEnd = nullptr; 1173 1174 /// The first memory accessing instruction in the scheduling region 1175 /// (can be null). 1176 ScheduleData *FirstLoadStoreInRegion = nullptr; 1177 1178 /// The last memory accessing instruction in the scheduling region 1179 /// (can be null). 1180 ScheduleData *LastLoadStoreInRegion = nullptr; 1181 1182 /// The current size of the scheduling region. 1183 int ScheduleRegionSize = 0; 1184 1185 /// The maximum size allowed for the scheduling region. 1186 int ScheduleRegionSizeLimit = ScheduleRegionSizeBudget; 1187 1188 /// The ID of the scheduling region. For a new vectorization iteration this 1189 /// is incremented which "removes" all ScheduleData from the region. 1190 // Make sure that the initial SchedulingRegionID is greater than the 1191 // initial SchedulingRegionID in ScheduleData (which is 0). 1192 int SchedulingRegionID = 1; 1193 }; 1194 1195 /// Attaches the BlockScheduling structures to basic blocks. 1196 MapVector<BasicBlock *, std::unique_ptr<BlockScheduling>> BlocksSchedules; 1197 1198 /// Performs the "real" scheduling. Done before vectorization is actually 1199 /// performed in a basic block. 1200 void scheduleBlock(BlockScheduling *BS); 1201 1202 /// List of users to ignore during scheduling and that don't need extracting. 1203 ArrayRef<Value *> UserIgnoreList; 1204 1205 /// Number of operation bundles that contain consecutive operations - number 1206 /// of operation bundles that contain consecutive operations in reversed 1207 /// order. 1208 DenseMap<unsigned, int> NumOpsWantToKeepOrder; 1209 1210 // Analysis and block reference. 1211 Function *F; 1212 ScalarEvolution *SE; 1213 TargetTransformInfo *TTI; 1214 TargetLibraryInfo *TLI; 1215 AliasAnalysis *AA; 1216 LoopInfo *LI; 1217 DominatorTree *DT; 1218 AssumptionCache *AC; 1219 DemandedBits *DB; 1220 const DataLayout *DL; 1221 OptimizationRemarkEmitter *ORE; 1222 1223 unsigned MaxVecRegSize; // This is set by TTI or overridden by cl::opt. 1224 unsigned MinVecRegSize; // Set by cl::opt (default: 128). 1225 1226 /// Instruction builder to construct the vectorized tree. 1227 IRBuilder<> Builder; 1228 1229 /// A map of scalar integer values to the smallest bit width with which they 1230 /// can legally be represented. The values map to (width, signed) pairs, 1231 /// where "width" indicates the minimum bit width and "signed" is True if the 1232 /// value must be signed-extended, rather than zero-extended, back to its 1233 /// original width. 1234 MapVector<Value *, std::pair<uint64_t, bool>> MinBWs; 1235 }; 1236 1237 } // end namespace slpvectorizer 1238 1239 template <> struct GraphTraits<BoUpSLP *> { 1240 using TreeEntry = BoUpSLP::TreeEntry; 1241 1242 /// NodeRef has to be a pointer per the GraphWriter. 1243 using NodeRef = TreeEntry *; 1244 1245 /// \brief Add the VectorizableTree to the index iterator to be able to return 1246 /// TreeEntry pointers. 1247 struct ChildIteratorType 1248 : public iterator_adaptor_base<ChildIteratorType, 1249 SmallVector<int, 1>::iterator> { 1250 std::vector<TreeEntry> &VectorizableTree; 1251 1252 ChildIteratorType(SmallVector<int, 1>::iterator W, 1253 std::vector<TreeEntry> &VT) 1254 : ChildIteratorType::iterator_adaptor_base(W), VectorizableTree(VT) {} 1255 1256 NodeRef operator*() { return &VectorizableTree[*I]; } 1257 }; 1258 1259 static NodeRef getEntryNode(BoUpSLP &R) { return &R.VectorizableTree[0]; } 1260 1261 static ChildIteratorType child_begin(NodeRef N) { 1262 return {N->UserTreeIndices.begin(), N->Container}; 1263 } 1264 1265 static ChildIteratorType child_end(NodeRef N) { 1266 return {N->UserTreeIndices.end(), N->Container}; 1267 } 1268 1269 /// For the node iterator we just need to turn the TreeEntry iterator into a 1270 /// TreeEntry* iterator so that it dereferences to NodeRef. 1271 using nodes_iterator = pointer_iterator<std::vector<TreeEntry>::iterator>; 1272 1273 static nodes_iterator nodes_begin(BoUpSLP *R) { 1274 return nodes_iterator(R->VectorizableTree.begin()); 1275 } 1276 1277 static nodes_iterator nodes_end(BoUpSLP *R) { 1278 return nodes_iterator(R->VectorizableTree.end()); 1279 } 1280 1281 static unsigned size(BoUpSLP *R) { return R->VectorizableTree.size(); } 1282 }; 1283 1284 template <> struct DOTGraphTraits<BoUpSLP *> : public DefaultDOTGraphTraits { 1285 using TreeEntry = BoUpSLP::TreeEntry; 1286 1287 DOTGraphTraits(bool isSimple = false) : DefaultDOTGraphTraits(isSimple) {} 1288 1289 std::string getNodeLabel(const TreeEntry *Entry, const BoUpSLP *R) { 1290 std::string Str; 1291 raw_string_ostream OS(Str); 1292 if (isSplat(Entry->Scalars)) { 1293 OS << "<splat> " << *Entry->Scalars[0]; 1294 return Str; 1295 } 1296 for (auto V : Entry->Scalars) { 1297 OS << *V; 1298 if (std::any_of( 1299 R->ExternalUses.begin(), R->ExternalUses.end(), 1300 [&](const BoUpSLP::ExternalUser &EU) { return EU.Scalar == V; })) 1301 OS << " <extract>"; 1302 OS << "\n"; 1303 } 1304 return Str; 1305 } 1306 1307 static std::string getNodeAttributes(const TreeEntry *Entry, 1308 const BoUpSLP *) { 1309 if (Entry->NeedToGather) 1310 return "color=red"; 1311 return ""; 1312 } 1313 }; 1314 1315 } // end namespace llvm 1316 1317 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 1318 ArrayRef<Value *> UserIgnoreLst) { 1319 ExtraValueToDebugLocsMap ExternallyUsedValues; 1320 buildTree(Roots, ExternallyUsedValues, UserIgnoreLst); 1321 } 1322 1323 void BoUpSLP::buildTree(ArrayRef<Value *> Roots, 1324 ExtraValueToDebugLocsMap &ExternallyUsedValues, 1325 ArrayRef<Value *> UserIgnoreLst) { 1326 deleteTree(); 1327 UserIgnoreList = UserIgnoreLst; 1328 if (!allSameType(Roots)) 1329 return; 1330 buildTree_rec(Roots, 0, -1); 1331 1332 // Collect the values that we need to extract from the tree. 1333 for (TreeEntry &EIdx : VectorizableTree) { 1334 TreeEntry *Entry = &EIdx; 1335 1336 // No need to handle users of gathered values. 1337 if (Entry->NeedToGather) 1338 continue; 1339 1340 // For each lane: 1341 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 1342 Value *Scalar = Entry->Scalars[Lane]; 1343 int FoundLane = Lane; 1344 if (!Entry->ReuseShuffleIndices.empty()) { 1345 FoundLane = 1346 std::distance(Entry->ReuseShuffleIndices.begin(), 1347 llvm::find(Entry->ReuseShuffleIndices, FoundLane)); 1348 } 1349 1350 // Check if the scalar is externally used as an extra arg. 1351 auto ExtI = ExternallyUsedValues.find(Scalar); 1352 if (ExtI != ExternallyUsedValues.end()) { 1353 DEBUG(dbgs() << "SLP: Need to extract: Extra arg from lane " << 1354 Lane << " from " << *Scalar << ".\n"); 1355 ExternalUses.emplace_back(Scalar, nullptr, FoundLane); 1356 } 1357 for (User *U : Scalar->users()) { 1358 DEBUG(dbgs() << "SLP: Checking user:" << *U << ".\n"); 1359 1360 Instruction *UserInst = dyn_cast<Instruction>(U); 1361 if (!UserInst) 1362 continue; 1363 1364 // Skip in-tree scalars that become vectors 1365 if (TreeEntry *UseEntry = getTreeEntry(U)) { 1366 Value *UseScalar = UseEntry->Scalars[0]; 1367 // Some in-tree scalars will remain as scalar in vectorized 1368 // instructions. If that is the case, the one in Lane 0 will 1369 // be used. 1370 if (UseScalar != U || 1371 !InTreeUserNeedToExtract(Scalar, UserInst, TLI)) { 1372 DEBUG(dbgs() << "SLP: \tInternal user will be removed:" << *U 1373 << ".\n"); 1374 assert(!UseEntry->NeedToGather && "Bad state"); 1375 continue; 1376 } 1377 } 1378 1379 // Ignore users in the user ignore list. 1380 if (is_contained(UserIgnoreList, UserInst)) 1381 continue; 1382 1383 DEBUG(dbgs() << "SLP: Need to extract:" << *U << " from lane " << 1384 Lane << " from " << *Scalar << ".\n"); 1385 ExternalUses.push_back(ExternalUser(Scalar, U, FoundLane)); 1386 } 1387 } 1388 } 1389 } 1390 1391 void BoUpSLP::buildTree_rec(ArrayRef<Value *> VL, unsigned Depth, 1392 int UserTreeIdx) { 1393 assert((allConstant(VL) || allSameType(VL)) && "Invalid types!"); 1394 1395 InstructionsState S = getSameOpcode(VL); 1396 if (Depth == RecursionMaxDepth) { 1397 DEBUG(dbgs() << "SLP: Gathering due to max recursion depth.\n"); 1398 newTreeEntry(VL, false, UserTreeIdx); 1399 return; 1400 } 1401 1402 // Don't handle vectors. 1403 if (S.OpValue->getType()->isVectorTy()) { 1404 DEBUG(dbgs() << "SLP: Gathering due to vector type.\n"); 1405 newTreeEntry(VL, false, UserTreeIdx); 1406 return; 1407 } 1408 1409 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) 1410 if (SI->getValueOperand()->getType()->isVectorTy()) { 1411 DEBUG(dbgs() << "SLP: Gathering due to store vector type.\n"); 1412 newTreeEntry(VL, false, UserTreeIdx); 1413 return; 1414 } 1415 1416 // If all of the operands are identical or constant we have a simple solution. 1417 if (allConstant(VL) || isSplat(VL) || !allSameBlock(VL) || !S.Opcode) { 1418 DEBUG(dbgs() << "SLP: Gathering due to C,S,B,O. \n"); 1419 newTreeEntry(VL, false, UserTreeIdx); 1420 return; 1421 } 1422 1423 // We now know that this is a vector of instructions of the same type from 1424 // the same block. 1425 1426 // Don't vectorize ephemeral values. 1427 for (unsigned i = 0, e = VL.size(); i != e; ++i) { 1428 if (EphValues.count(VL[i])) { 1429 DEBUG(dbgs() << "SLP: The instruction (" << *VL[i] << 1430 ") is ephemeral.\n"); 1431 newTreeEntry(VL, false, UserTreeIdx); 1432 return; 1433 } 1434 } 1435 1436 // Check if this is a duplicate of another entry. 1437 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 1438 DEBUG(dbgs() << "SLP: \tChecking bundle: " << *S.OpValue << ".\n"); 1439 if (!E->isSame(VL)) { 1440 DEBUG(dbgs() << "SLP: Gathering due to partial overlap.\n"); 1441 newTreeEntry(VL, false, UserTreeIdx); 1442 return; 1443 } 1444 // Record the reuse of the tree node. FIXME, currently this is only used to 1445 // properly draw the graph rather than for the actual vectorization. 1446 E->UserTreeIndices.push_back(UserTreeIdx); 1447 DEBUG(dbgs() << "SLP: Perfect diamond merge at " << *S.OpValue << ".\n"); 1448 return; 1449 } 1450 1451 // Check that none of the instructions in the bundle are already in the tree. 1452 for (unsigned i = 0, e = VL.size(); i != e; ++i) { 1453 auto *I = dyn_cast<Instruction>(VL[i]); 1454 if (!I) 1455 continue; 1456 if (getTreeEntry(I)) { 1457 DEBUG(dbgs() << "SLP: The instruction (" << *VL[i] << 1458 ") is already in tree.\n"); 1459 newTreeEntry(VL, false, UserTreeIdx); 1460 return; 1461 } 1462 } 1463 1464 // If any of the scalars is marked as a value that needs to stay scalar, then 1465 // we need to gather the scalars. 1466 for (unsigned i = 0, e = VL.size(); i != e; ++i) { 1467 if (MustGather.count(VL[i])) { 1468 DEBUG(dbgs() << "SLP: Gathering due to gathered scalar.\n"); 1469 newTreeEntry(VL, false, UserTreeIdx); 1470 return; 1471 } 1472 } 1473 1474 // Check that all of the users of the scalars that we want to vectorize are 1475 // schedulable. 1476 auto *VL0 = cast<Instruction>(S.OpValue); 1477 BasicBlock *BB = VL0->getParent(); 1478 1479 if (!DT->isReachableFromEntry(BB)) { 1480 // Don't go into unreachable blocks. They may contain instructions with 1481 // dependency cycles which confuse the final scheduling. 1482 DEBUG(dbgs() << "SLP: bundle in unreachable block.\n"); 1483 newTreeEntry(VL, false, UserTreeIdx); 1484 return; 1485 } 1486 1487 // Check that every instruction appears once in this bundle. 1488 SmallVector<unsigned, 4> ReuseShuffleIndicies; 1489 SmallVector<Value *, 4> UniqueValues; 1490 DenseMap<Value *, unsigned> UniquePositions; 1491 for (Value *V : VL) { 1492 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 1493 ReuseShuffleIndicies.emplace_back(Res.first->second); 1494 if (Res.second) 1495 UniqueValues.emplace_back(V); 1496 } 1497 if (UniqueValues.size() == VL.size()) { 1498 ReuseShuffleIndicies.clear(); 1499 } else { 1500 DEBUG(dbgs() << "SLP: Shuffle for reused scalars.\n"); 1501 if (UniqueValues.size() <= 1 || !llvm::isPowerOf2_32(UniqueValues.size())) { 1502 DEBUG(dbgs() << "SLP: Scalar used twice in bundle.\n"); 1503 newTreeEntry(VL, false, UserTreeIdx); 1504 return; 1505 } 1506 VL = UniqueValues; 1507 } 1508 1509 auto &BSRef = BlocksSchedules[BB]; 1510 if (!BSRef) 1511 BSRef = llvm::make_unique<BlockScheduling>(BB); 1512 1513 BlockScheduling &BS = *BSRef.get(); 1514 1515 if (!BS.tryScheduleBundle(VL, this, VL0)) { 1516 DEBUG(dbgs() << "SLP: We are not able to schedule this bundle!\n"); 1517 assert((!BS.getScheduleData(VL0) || 1518 !BS.getScheduleData(VL0)->isPartOfBundle()) && 1519 "tryScheduleBundle should cancelScheduling on failure"); 1520 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 1521 return; 1522 } 1523 DEBUG(dbgs() << "SLP: We are able to schedule this bundle.\n"); 1524 1525 unsigned ShuffleOrOp = S.IsAltShuffle ? 1526 (unsigned) Instruction::ShuffleVector : S.Opcode; 1527 switch (ShuffleOrOp) { 1528 case Instruction::PHI: { 1529 PHINode *PH = dyn_cast<PHINode>(VL0); 1530 1531 // Check for terminator values (e.g. invoke). 1532 for (unsigned j = 0; j < VL.size(); ++j) 1533 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 1534 TerminatorInst *Term = dyn_cast<TerminatorInst>( 1535 cast<PHINode>(VL[j])->getIncomingValueForBlock(PH->getIncomingBlock(i))); 1536 if (Term) { 1537 DEBUG(dbgs() << "SLP: Need to swizzle PHINodes (TerminatorInst use).\n"); 1538 BS.cancelScheduling(VL, VL0); 1539 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 1540 return; 1541 } 1542 } 1543 1544 newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies); 1545 DEBUG(dbgs() << "SLP: added a vector of PHINodes.\n"); 1546 1547 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 1548 ValueList Operands; 1549 // Prepare the operand vector. 1550 for (Value *j : VL) 1551 Operands.push_back(cast<PHINode>(j)->getIncomingValueForBlock( 1552 PH->getIncomingBlock(i))); 1553 1554 buildTree_rec(Operands, Depth + 1, UserTreeIdx); 1555 } 1556 return; 1557 } 1558 case Instruction::ExtractValue: 1559 case Instruction::ExtractElement: { 1560 bool Reuse = canReuseExtract(VL, VL0); 1561 if (Reuse) { 1562 DEBUG(dbgs() << "SLP: Reusing or shuffling extract sequence.\n"); 1563 ++NumOpsWantToKeepOrder[S.Opcode]; 1564 } else { 1565 SmallVector<Value *, 4> ReverseVL(VL.rbegin(), VL.rend()); 1566 if (canReuseExtract(ReverseVL, VL0)) 1567 --NumOpsWantToKeepOrder[S.Opcode]; 1568 BS.cancelScheduling(VL, VL0); 1569 } 1570 newTreeEntry(VL, Reuse, UserTreeIdx, ReuseShuffleIndicies); 1571 return; 1572 } 1573 case Instruction::Load: { 1574 // Check that a vectorized load would load the same memory as a scalar 1575 // load. For example, we don't want to vectorize loads that are smaller 1576 // than 8-bit. Even though we have a packed struct {<i2, i2, i2, i2>} LLVM 1577 // treats loading/storing it as an i8 struct. If we vectorize loads/stores 1578 // from such a struct, we read/write packed bits disagreeing with the 1579 // unvectorized version. 1580 Type *ScalarTy = VL0->getType(); 1581 1582 if (DL->getTypeSizeInBits(ScalarTy) != 1583 DL->getTypeAllocSizeInBits(ScalarTy)) { 1584 BS.cancelScheduling(VL, VL0); 1585 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 1586 DEBUG(dbgs() << "SLP: Gathering loads of non-packed type.\n"); 1587 return; 1588 } 1589 1590 // Make sure all loads in the bundle are simple - we can't vectorize 1591 // atomic or volatile loads. 1592 for (unsigned i = 0, e = VL.size() - 1; i < e; ++i) { 1593 LoadInst *L = cast<LoadInst>(VL[i]); 1594 if (!L->isSimple()) { 1595 BS.cancelScheduling(VL, VL0); 1596 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 1597 DEBUG(dbgs() << "SLP: Gathering non-simple loads.\n"); 1598 return; 1599 } 1600 } 1601 1602 // Check if the loads are consecutive, reversed, or neither. 1603 // TODO: What we really want is to sort the loads, but for now, check 1604 // the two likely directions. 1605 bool Consecutive = true; 1606 bool ReverseConsecutive = true; 1607 for (unsigned i = 0, e = VL.size() - 1; i < e; ++i) { 1608 if (!isConsecutiveAccess(VL[i], VL[i + 1], *DL, *SE)) { 1609 Consecutive = false; 1610 break; 1611 } else { 1612 ReverseConsecutive = false; 1613 } 1614 } 1615 1616 if (Consecutive) { 1617 ++NumOpsWantToKeepOrder[S.Opcode]; 1618 newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies); 1619 DEBUG(dbgs() << "SLP: added a vector of loads.\n"); 1620 return; 1621 } 1622 1623 // If none of the load pairs were consecutive when checked in order, 1624 // check the reverse order. 1625 if (ReverseConsecutive) 1626 for (unsigned i = VL.size() - 1; i > 0; --i) 1627 if (!isConsecutiveAccess(VL[i], VL[i - 1], *DL, *SE)) { 1628 ReverseConsecutive = false; 1629 break; 1630 } 1631 1632 if (ReverseConsecutive) { 1633 --NumOpsWantToKeepOrder[S.Opcode]; 1634 newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies); 1635 DEBUG(dbgs() << "SLP: added a vector of reversed loads.\n"); 1636 return; 1637 } 1638 1639 DEBUG(dbgs() << "SLP: Gathering non-consecutive loads.\n"); 1640 BS.cancelScheduling(VL, VL0); 1641 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 1642 return; 1643 } 1644 case Instruction::ZExt: 1645 case Instruction::SExt: 1646 case Instruction::FPToUI: 1647 case Instruction::FPToSI: 1648 case Instruction::FPExt: 1649 case Instruction::PtrToInt: 1650 case Instruction::IntToPtr: 1651 case Instruction::SIToFP: 1652 case Instruction::UIToFP: 1653 case Instruction::Trunc: 1654 case Instruction::FPTrunc: 1655 case Instruction::BitCast: { 1656 Type *SrcTy = VL0->getOperand(0)->getType(); 1657 for (unsigned i = 0; i < VL.size(); ++i) { 1658 Type *Ty = cast<Instruction>(VL[i])->getOperand(0)->getType(); 1659 if (Ty != SrcTy || !isValidElementType(Ty)) { 1660 BS.cancelScheduling(VL, VL0); 1661 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 1662 DEBUG(dbgs() << "SLP: Gathering casts with different src types.\n"); 1663 return; 1664 } 1665 } 1666 newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies); 1667 DEBUG(dbgs() << "SLP: added a vector of casts.\n"); 1668 1669 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 1670 ValueList Operands; 1671 // Prepare the operand vector. 1672 for (Value *j : VL) 1673 Operands.push_back(cast<Instruction>(j)->getOperand(i)); 1674 1675 buildTree_rec(Operands, Depth + 1, UserTreeIdx); 1676 } 1677 return; 1678 } 1679 case Instruction::ICmp: 1680 case Instruction::FCmp: { 1681 // Check that all of the compares have the same predicate. 1682 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 1683 Type *ComparedTy = VL0->getOperand(0)->getType(); 1684 for (unsigned i = 1, e = VL.size(); i < e; ++i) { 1685 CmpInst *Cmp = cast<CmpInst>(VL[i]); 1686 if (Cmp->getPredicate() != P0 || 1687 Cmp->getOperand(0)->getType() != ComparedTy) { 1688 BS.cancelScheduling(VL, VL0); 1689 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 1690 DEBUG(dbgs() << "SLP: Gathering cmp with different predicate.\n"); 1691 return; 1692 } 1693 } 1694 1695 newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies); 1696 DEBUG(dbgs() << "SLP: added a vector of compares.\n"); 1697 1698 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 1699 ValueList Operands; 1700 // Prepare the operand vector. 1701 for (Value *j : VL) 1702 Operands.push_back(cast<Instruction>(j)->getOperand(i)); 1703 1704 buildTree_rec(Operands, Depth + 1, UserTreeIdx); 1705 } 1706 return; 1707 } 1708 case Instruction::Select: 1709 case Instruction::Add: 1710 case Instruction::FAdd: 1711 case Instruction::Sub: 1712 case Instruction::FSub: 1713 case Instruction::Mul: 1714 case Instruction::FMul: 1715 case Instruction::UDiv: 1716 case Instruction::SDiv: 1717 case Instruction::FDiv: 1718 case Instruction::URem: 1719 case Instruction::SRem: 1720 case Instruction::FRem: 1721 case Instruction::Shl: 1722 case Instruction::LShr: 1723 case Instruction::AShr: 1724 case Instruction::And: 1725 case Instruction::Or: 1726 case Instruction::Xor: 1727 newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies); 1728 DEBUG(dbgs() << "SLP: added a vector of bin op.\n"); 1729 1730 // Sort operands of the instructions so that each side is more likely to 1731 // have the same opcode. 1732 if (isa<BinaryOperator>(VL0) && VL0->isCommutative()) { 1733 ValueList Left, Right; 1734 reorderInputsAccordingToOpcode(S.Opcode, VL, Left, Right); 1735 buildTree_rec(Left, Depth + 1, UserTreeIdx); 1736 buildTree_rec(Right, Depth + 1, UserTreeIdx); 1737 return; 1738 } 1739 1740 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 1741 ValueList Operands; 1742 // Prepare the operand vector. 1743 for (Value *j : VL) 1744 Operands.push_back(cast<Instruction>(j)->getOperand(i)); 1745 1746 buildTree_rec(Operands, Depth + 1, UserTreeIdx); 1747 } 1748 return; 1749 1750 case Instruction::GetElementPtr: { 1751 // We don't combine GEPs with complicated (nested) indexing. 1752 for (unsigned j = 0; j < VL.size(); ++j) { 1753 if (cast<Instruction>(VL[j])->getNumOperands() != 2) { 1754 DEBUG(dbgs() << "SLP: not-vectorizable GEP (nested indexes).\n"); 1755 BS.cancelScheduling(VL, VL0); 1756 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 1757 return; 1758 } 1759 } 1760 1761 // We can't combine several GEPs into one vector if they operate on 1762 // different types. 1763 Type *Ty0 = VL0->getOperand(0)->getType(); 1764 for (unsigned j = 0; j < VL.size(); ++j) { 1765 Type *CurTy = cast<Instruction>(VL[j])->getOperand(0)->getType(); 1766 if (Ty0 != CurTy) { 1767 DEBUG(dbgs() << "SLP: not-vectorizable GEP (different types).\n"); 1768 BS.cancelScheduling(VL, VL0); 1769 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 1770 return; 1771 } 1772 } 1773 1774 // We don't combine GEPs with non-constant indexes. 1775 for (unsigned j = 0; j < VL.size(); ++j) { 1776 auto Op = cast<Instruction>(VL[j])->getOperand(1); 1777 if (!isa<ConstantInt>(Op)) { 1778 DEBUG( 1779 dbgs() << "SLP: not-vectorizable GEP (non-constant indexes).\n"); 1780 BS.cancelScheduling(VL, VL0); 1781 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 1782 return; 1783 } 1784 } 1785 1786 newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies); 1787 DEBUG(dbgs() << "SLP: added a vector of GEPs.\n"); 1788 for (unsigned i = 0, e = 2; i < e; ++i) { 1789 ValueList Operands; 1790 // Prepare the operand vector. 1791 for (Value *j : VL) 1792 Operands.push_back(cast<Instruction>(j)->getOperand(i)); 1793 1794 buildTree_rec(Operands, Depth + 1, UserTreeIdx); 1795 } 1796 return; 1797 } 1798 case Instruction::Store: { 1799 // Check if the stores are consecutive or of we need to swizzle them. 1800 for (unsigned i = 0, e = VL.size() - 1; i < e; ++i) 1801 if (!isConsecutiveAccess(VL[i], VL[i + 1], *DL, *SE)) { 1802 BS.cancelScheduling(VL, VL0); 1803 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 1804 DEBUG(dbgs() << "SLP: Non-consecutive store.\n"); 1805 return; 1806 } 1807 1808 newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies); 1809 DEBUG(dbgs() << "SLP: added a vector of stores.\n"); 1810 1811 ValueList Operands; 1812 for (Value *j : VL) 1813 Operands.push_back(cast<Instruction>(j)->getOperand(0)); 1814 1815 buildTree_rec(Operands, Depth + 1, UserTreeIdx); 1816 return; 1817 } 1818 case Instruction::Call: { 1819 // Check if the calls are all to the same vectorizable intrinsic. 1820 CallInst *CI = cast<CallInst>(VL0); 1821 // Check if this is an Intrinsic call or something that can be 1822 // represented by an intrinsic call 1823 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 1824 if (!isTriviallyVectorizable(ID)) { 1825 BS.cancelScheduling(VL, VL0); 1826 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 1827 DEBUG(dbgs() << "SLP: Non-vectorizable call.\n"); 1828 return; 1829 } 1830 Function *Int = CI->getCalledFunction(); 1831 Value *A1I = nullptr; 1832 if (hasVectorInstrinsicScalarOpd(ID, 1)) 1833 A1I = CI->getArgOperand(1); 1834 for (unsigned i = 1, e = VL.size(); i != e; ++i) { 1835 CallInst *CI2 = dyn_cast<CallInst>(VL[i]); 1836 if (!CI2 || CI2->getCalledFunction() != Int || 1837 getVectorIntrinsicIDForCall(CI2, TLI) != ID || 1838 !CI->hasIdenticalOperandBundleSchema(*CI2)) { 1839 BS.cancelScheduling(VL, VL0); 1840 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 1841 DEBUG(dbgs() << "SLP: mismatched calls:" << *CI << "!=" << *VL[i] 1842 << "\n"); 1843 return; 1844 } 1845 // ctlz,cttz and powi are special intrinsics whose second argument 1846 // should be same in order for them to be vectorized. 1847 if (hasVectorInstrinsicScalarOpd(ID, 1)) { 1848 Value *A1J = CI2->getArgOperand(1); 1849 if (A1I != A1J) { 1850 BS.cancelScheduling(VL, VL0); 1851 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 1852 DEBUG(dbgs() << "SLP: mismatched arguments in call:" << *CI 1853 << " argument "<< A1I<<"!=" << A1J 1854 << "\n"); 1855 return; 1856 } 1857 } 1858 // Verify that the bundle operands are identical between the two calls. 1859 if (CI->hasOperandBundles() && 1860 !std::equal(CI->op_begin() + CI->getBundleOperandsStartIndex(), 1861 CI->op_begin() + CI->getBundleOperandsEndIndex(), 1862 CI2->op_begin() + CI2->getBundleOperandsStartIndex())) { 1863 BS.cancelScheduling(VL, VL0); 1864 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 1865 DEBUG(dbgs() << "SLP: mismatched bundle operands in calls:" << *CI << "!=" 1866 << *VL[i] << '\n'); 1867 return; 1868 } 1869 } 1870 1871 newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies); 1872 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) { 1873 ValueList Operands; 1874 // Prepare the operand vector. 1875 for (Value *j : VL) { 1876 CallInst *CI2 = dyn_cast<CallInst>(j); 1877 Operands.push_back(CI2->getArgOperand(i)); 1878 } 1879 buildTree_rec(Operands, Depth + 1, UserTreeIdx); 1880 } 1881 return; 1882 } 1883 case Instruction::ShuffleVector: 1884 // If this is not an alternate sequence of opcode like add-sub 1885 // then do not vectorize this instruction. 1886 if (!S.IsAltShuffle) { 1887 BS.cancelScheduling(VL, VL0); 1888 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 1889 DEBUG(dbgs() << "SLP: ShuffleVector are not vectorized.\n"); 1890 return; 1891 } 1892 newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies); 1893 DEBUG(dbgs() << "SLP: added a ShuffleVector op.\n"); 1894 1895 // Reorder operands if reordering would enable vectorization. 1896 if (isa<BinaryOperator>(VL0)) { 1897 ValueList Left, Right; 1898 reorderAltShuffleOperands(S.Opcode, VL, Left, Right); 1899 buildTree_rec(Left, Depth + 1, UserTreeIdx); 1900 buildTree_rec(Right, Depth + 1, UserTreeIdx); 1901 return; 1902 } 1903 1904 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { 1905 ValueList Operands; 1906 // Prepare the operand vector. 1907 for (Value *j : VL) 1908 Operands.push_back(cast<Instruction>(j)->getOperand(i)); 1909 1910 buildTree_rec(Operands, Depth + 1, UserTreeIdx); 1911 } 1912 return; 1913 1914 default: 1915 BS.cancelScheduling(VL, VL0); 1916 newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies); 1917 DEBUG(dbgs() << "SLP: Gathering unknown instruction.\n"); 1918 return; 1919 } 1920 } 1921 1922 unsigned BoUpSLP::canMapToVector(Type *T, const DataLayout &DL) const { 1923 unsigned N; 1924 Type *EltTy; 1925 auto *ST = dyn_cast<StructType>(T); 1926 if (ST) { 1927 N = ST->getNumElements(); 1928 EltTy = *ST->element_begin(); 1929 } else { 1930 N = cast<ArrayType>(T)->getNumElements(); 1931 EltTy = cast<ArrayType>(T)->getElementType(); 1932 } 1933 if (!isValidElementType(EltTy)) 1934 return 0; 1935 uint64_t VTSize = DL.getTypeStoreSizeInBits(VectorType::get(EltTy, N)); 1936 if (VTSize < MinVecRegSize || VTSize > MaxVecRegSize || VTSize != DL.getTypeStoreSizeInBits(T)) 1937 return 0; 1938 if (ST) { 1939 // Check that struct is homogeneous. 1940 for (const auto *Ty : ST->elements()) 1941 if (Ty != EltTy) 1942 return 0; 1943 } 1944 return N; 1945 } 1946 1947 bool BoUpSLP::canReuseExtract(ArrayRef<Value *> VL, Value *OpValue) const { 1948 Instruction *E0 = cast<Instruction>(OpValue); 1949 assert(E0->getOpcode() == Instruction::ExtractElement || 1950 E0->getOpcode() == Instruction::ExtractValue); 1951 assert(E0->getOpcode() == getSameOpcode(VL).Opcode && "Invalid opcode"); 1952 // Check if all of the extracts come from the same vector and from the 1953 // correct offset. 1954 Value *Vec = E0->getOperand(0); 1955 1956 // We have to extract from a vector/aggregate with the same number of elements. 1957 unsigned NElts; 1958 if (E0->getOpcode() == Instruction::ExtractValue) { 1959 const DataLayout &DL = E0->getModule()->getDataLayout(); 1960 NElts = canMapToVector(Vec->getType(), DL); 1961 if (!NElts) 1962 return false; 1963 // Check if load can be rewritten as load of vector. 1964 LoadInst *LI = dyn_cast<LoadInst>(Vec); 1965 if (!LI || !LI->isSimple() || !LI->hasNUses(VL.size())) 1966 return false; 1967 } else { 1968 NElts = Vec->getType()->getVectorNumElements(); 1969 } 1970 1971 if (NElts != VL.size()) 1972 return false; 1973 1974 // Check that all of the indices extract from the correct offset. 1975 for (unsigned I = 0, E = VL.size(); I < E; ++I) { 1976 Instruction *Inst = cast<Instruction>(VL[I]); 1977 if (!matchExtractIndex(Inst, I, Inst->getOpcode())) 1978 return false; 1979 if (Inst->getOperand(0) != Vec) 1980 return false; 1981 } 1982 1983 return true; 1984 } 1985 1986 bool BoUpSLP::areAllUsersVectorized(Instruction *I) const { 1987 return I->hasOneUse() || 1988 std::all_of(I->user_begin(), I->user_end(), [this](User *U) { 1989 return ScalarToTreeEntry.count(U) > 0; 1990 }); 1991 } 1992 1993 int BoUpSLP::getEntryCost(TreeEntry *E) { 1994 ArrayRef<Value*> VL = E->Scalars; 1995 1996 Type *ScalarTy = VL[0]->getType(); 1997 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 1998 ScalarTy = SI->getValueOperand()->getType(); 1999 else if (CmpInst *CI = dyn_cast<CmpInst>(VL[0])) 2000 ScalarTy = CI->getOperand(0)->getType(); 2001 VectorType *VecTy = VectorType::get(ScalarTy, VL.size()); 2002 2003 // If we have computed a smaller type for the expression, update VecTy so 2004 // that the costs will be accurate. 2005 if (MinBWs.count(VL[0])) 2006 VecTy = VectorType::get( 2007 IntegerType::get(F->getContext(), MinBWs[VL[0]].first), VL.size()); 2008 2009 unsigned ReuseShuffleNumbers = E->ReuseShuffleIndices.size(); 2010 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 2011 int ReuseShuffleCost = 0; 2012 if (NeedToShuffleReuses) { 2013 ReuseShuffleCost = 2014 TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 2015 } 2016 if (E->NeedToGather) { 2017 if (allConstant(VL)) 2018 return 0; 2019 if (isSplat(VL)) { 2020 return ReuseShuffleCost + 2021 TTI->getShuffleCost(TargetTransformInfo::SK_Broadcast, VecTy, 0); 2022 } 2023 if (getSameOpcode(VL).Opcode == Instruction::ExtractElement && 2024 allSameType(VL) && allSameBlock(VL)) { 2025 Optional<TargetTransformInfo::ShuffleKind> ShuffleKind = isShuffle(VL); 2026 if (ShuffleKind.hasValue()) { 2027 int Cost = TTI->getShuffleCost(ShuffleKind.getValue(), VecTy); 2028 for (auto *V : VL) { 2029 // If all users of instruction are going to be vectorized and this 2030 // instruction itself is not going to be vectorized, consider this 2031 // instruction as dead and remove its cost from the final cost of the 2032 // vectorized tree. 2033 if (areAllUsersVectorized(cast<Instruction>(V)) && 2034 !ScalarToTreeEntry.count(V)) { 2035 auto *IO = cast<ConstantInt>( 2036 cast<ExtractElementInst>(V)->getIndexOperand()); 2037 Cost -= TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, 2038 IO->getZExtValue()); 2039 } 2040 } 2041 return ReuseShuffleCost + Cost; 2042 } 2043 } 2044 return ReuseShuffleCost + getGatherCost(VL); 2045 } 2046 InstructionsState S = getSameOpcode(VL); 2047 assert(S.Opcode && allSameType(VL) && allSameBlock(VL) && "Invalid VL"); 2048 Instruction *VL0 = cast<Instruction>(S.OpValue); 2049 unsigned ShuffleOrOp = S.IsAltShuffle ? 2050 (unsigned) Instruction::ShuffleVector : S.Opcode; 2051 switch (ShuffleOrOp) { 2052 case Instruction::PHI: 2053 return 0; 2054 2055 case Instruction::ExtractValue: 2056 case Instruction::ExtractElement: 2057 if (NeedToShuffleReuses) { 2058 unsigned Idx = 0; 2059 for (unsigned I : E->ReuseShuffleIndices) { 2060 if (ShuffleOrOp == Instruction::ExtractElement) { 2061 auto *IO = cast<ConstantInt>( 2062 cast<ExtractElementInst>(VL[I])->getIndexOperand()); 2063 Idx = IO->getZExtValue(); 2064 ReuseShuffleCost -= TTI->getVectorInstrCost( 2065 Instruction::ExtractElement, VecTy, Idx); 2066 } else { 2067 ReuseShuffleCost -= TTI->getVectorInstrCost( 2068 Instruction::ExtractElement, VecTy, Idx); 2069 ++Idx; 2070 } 2071 } 2072 Idx = ReuseShuffleNumbers; 2073 for (Value *V : VL) { 2074 if (ShuffleOrOp == Instruction::ExtractElement) { 2075 auto *IO = cast<ConstantInt>( 2076 cast<ExtractElementInst>(V)->getIndexOperand()); 2077 Idx = IO->getZExtValue(); 2078 } else { 2079 --Idx; 2080 } 2081 ReuseShuffleCost += 2082 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, Idx); 2083 } 2084 } 2085 if (canReuseExtract(VL, S.OpValue)) { 2086 int DeadCost = ReuseShuffleCost; 2087 for (unsigned i = 0, e = VL.size(); i < e; ++i) { 2088 Instruction *E = cast<Instruction>(VL[i]); 2089 // If all users are going to be vectorized, instruction can be 2090 // considered as dead. 2091 // The same, if have only one user, it will be vectorized for sure. 2092 if (areAllUsersVectorized(E)) 2093 // Take credit for instruction that will become dead. 2094 DeadCost -= 2095 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, i); 2096 } 2097 return DeadCost; 2098 } 2099 return ReuseShuffleCost + getGatherCost(VL); 2100 2101 case Instruction::ZExt: 2102 case Instruction::SExt: 2103 case Instruction::FPToUI: 2104 case Instruction::FPToSI: 2105 case Instruction::FPExt: 2106 case Instruction::PtrToInt: 2107 case Instruction::IntToPtr: 2108 case Instruction::SIToFP: 2109 case Instruction::UIToFP: 2110 case Instruction::Trunc: 2111 case Instruction::FPTrunc: 2112 case Instruction::BitCast: { 2113 Type *SrcTy = VL0->getOperand(0)->getType(); 2114 if (NeedToShuffleReuses) { 2115 ReuseShuffleCost -= 2116 (ReuseShuffleNumbers - VL.size()) * 2117 TTI->getCastInstrCost(S.Opcode, ScalarTy, SrcTy, VL0); 2118 } 2119 2120 // Calculate the cost of this instruction. 2121 int ScalarCost = VL.size() * TTI->getCastInstrCost(VL0->getOpcode(), 2122 VL0->getType(), SrcTy, VL0); 2123 2124 VectorType *SrcVecTy = VectorType::get(SrcTy, VL.size()); 2125 int VecCost = 0; 2126 // Check if the values are candidates to demote. 2127 if (!MinBWs.count(VL0) || VecTy != SrcVecTy) { 2128 VecCost = ReuseShuffleCost + 2129 TTI->getCastInstrCost(VL0->getOpcode(), VecTy, SrcVecTy, VL0); 2130 } 2131 return VecCost - ScalarCost; 2132 } 2133 case Instruction::FCmp: 2134 case Instruction::ICmp: 2135 case Instruction::Select: { 2136 // Calculate the cost of this instruction. 2137 if (NeedToShuffleReuses) { 2138 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * 2139 TTI->getCmpSelInstrCost(S.Opcode, ScalarTy, 2140 Builder.getInt1Ty(), VL0); 2141 } 2142 VectorType *MaskTy = VectorType::get(Builder.getInt1Ty(), VL.size()); 2143 int ScalarCost = VecTy->getNumElements() * 2144 TTI->getCmpSelInstrCost(S.Opcode, ScalarTy, Builder.getInt1Ty(), VL0); 2145 int VecCost = TTI->getCmpSelInstrCost(S.Opcode, VecTy, MaskTy, VL0); 2146 return ReuseShuffleCost + VecCost - ScalarCost; 2147 } 2148 case Instruction::Add: 2149 case Instruction::FAdd: 2150 case Instruction::Sub: 2151 case Instruction::FSub: 2152 case Instruction::Mul: 2153 case Instruction::FMul: 2154 case Instruction::UDiv: 2155 case Instruction::SDiv: 2156 case Instruction::FDiv: 2157 case Instruction::URem: 2158 case Instruction::SRem: 2159 case Instruction::FRem: 2160 case Instruction::Shl: 2161 case Instruction::LShr: 2162 case Instruction::AShr: 2163 case Instruction::And: 2164 case Instruction::Or: 2165 case Instruction::Xor: { 2166 // Certain instructions can be cheaper to vectorize if they have a 2167 // constant second vector operand. 2168 TargetTransformInfo::OperandValueKind Op1VK = 2169 TargetTransformInfo::OK_AnyValue; 2170 TargetTransformInfo::OperandValueKind Op2VK = 2171 TargetTransformInfo::OK_UniformConstantValue; 2172 TargetTransformInfo::OperandValueProperties Op1VP = 2173 TargetTransformInfo::OP_None; 2174 TargetTransformInfo::OperandValueProperties Op2VP = 2175 TargetTransformInfo::OP_None; 2176 2177 // If all operands are exactly the same ConstantInt then set the 2178 // operand kind to OK_UniformConstantValue. 2179 // If instead not all operands are constants, then set the operand kind 2180 // to OK_AnyValue. If all operands are constants but not the same, 2181 // then set the operand kind to OK_NonUniformConstantValue. 2182 ConstantInt *CInt = nullptr; 2183 for (unsigned i = 0; i < VL.size(); ++i) { 2184 const Instruction *I = cast<Instruction>(VL[i]); 2185 if (!isa<ConstantInt>(I->getOperand(1))) { 2186 Op2VK = TargetTransformInfo::OK_AnyValue; 2187 break; 2188 } 2189 if (i == 0) { 2190 CInt = cast<ConstantInt>(I->getOperand(1)); 2191 continue; 2192 } 2193 if (Op2VK == TargetTransformInfo::OK_UniformConstantValue && 2194 CInt != cast<ConstantInt>(I->getOperand(1))) 2195 Op2VK = TargetTransformInfo::OK_NonUniformConstantValue; 2196 } 2197 // FIXME: Currently cost of model modification for division by power of 2198 // 2 is handled for X86 and AArch64. Add support for other targets. 2199 if (Op2VK == TargetTransformInfo::OK_UniformConstantValue && CInt && 2200 CInt->getValue().isPowerOf2()) 2201 Op2VP = TargetTransformInfo::OP_PowerOf2; 2202 2203 SmallVector<const Value *, 4> Operands(VL0->operand_values()); 2204 if (NeedToShuffleReuses) { 2205 ReuseShuffleCost -= 2206 (ReuseShuffleNumbers - VL.size()) * 2207 TTI->getArithmeticInstrCost(S.Opcode, ScalarTy, Op1VK, Op2VK, Op1VP, 2208 Op2VP, Operands); 2209 } 2210 int ScalarCost = 2211 VecTy->getNumElements() * 2212 TTI->getArithmeticInstrCost(S.Opcode, ScalarTy, Op1VK, Op2VK, Op1VP, 2213 Op2VP, Operands); 2214 int VecCost = TTI->getArithmeticInstrCost(S.Opcode, VecTy, Op1VK, Op2VK, 2215 Op1VP, Op2VP, Operands); 2216 return ReuseShuffleCost + VecCost - ScalarCost; 2217 } 2218 case Instruction::GetElementPtr: { 2219 TargetTransformInfo::OperandValueKind Op1VK = 2220 TargetTransformInfo::OK_AnyValue; 2221 TargetTransformInfo::OperandValueKind Op2VK = 2222 TargetTransformInfo::OK_UniformConstantValue; 2223 2224 if (NeedToShuffleReuses) { 2225 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * 2226 TTI->getArithmeticInstrCost(Instruction::Add, 2227 ScalarTy, Op1VK, Op2VK); 2228 } 2229 int ScalarCost = 2230 VecTy->getNumElements() * 2231 TTI->getArithmeticInstrCost(Instruction::Add, ScalarTy, Op1VK, Op2VK); 2232 int VecCost = 2233 TTI->getArithmeticInstrCost(Instruction::Add, VecTy, Op1VK, Op2VK); 2234 2235 return ReuseShuffleCost + VecCost - ScalarCost; 2236 } 2237 case Instruction::Load: { 2238 // Cost of wide load - cost of scalar loads. 2239 unsigned alignment = dyn_cast<LoadInst>(VL0)->getAlignment(); 2240 if (NeedToShuffleReuses) { 2241 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * 2242 TTI->getMemoryOpCost(Instruction::Load, ScalarTy, 2243 alignment, 0, VL0); 2244 } 2245 int ScalarLdCost = VecTy->getNumElements() * 2246 TTI->getMemoryOpCost(Instruction::Load, ScalarTy, alignment, 0, VL0); 2247 int VecLdCost = TTI->getMemoryOpCost(Instruction::Load, 2248 VecTy, alignment, 0, VL0); 2249 if (!isConsecutiveAccess(VL[0], VL[1], *DL, *SE)) { 2250 VecLdCost += TTI->getShuffleCost( 2251 TargetTransformInfo::SK_PermuteSingleSrc, VecTy); 2252 } 2253 return ReuseShuffleCost + VecLdCost - ScalarLdCost; 2254 } 2255 case Instruction::Store: { 2256 // We know that we can merge the stores. Calculate the cost. 2257 unsigned alignment = dyn_cast<StoreInst>(VL0)->getAlignment(); 2258 if (NeedToShuffleReuses) { 2259 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * 2260 TTI->getMemoryOpCost(Instruction::Store, ScalarTy, 2261 alignment, 0, VL0); 2262 } 2263 int ScalarStCost = VecTy->getNumElements() * 2264 TTI->getMemoryOpCost(Instruction::Store, ScalarTy, alignment, 0, VL0); 2265 int VecStCost = TTI->getMemoryOpCost(Instruction::Store, 2266 VecTy, alignment, 0, VL0); 2267 return ReuseShuffleCost + VecStCost - ScalarStCost; 2268 } 2269 case Instruction::Call: { 2270 CallInst *CI = cast<CallInst>(VL0); 2271 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 2272 2273 // Calculate the cost of the scalar and vector calls. 2274 SmallVector<Type*, 4> ScalarTys; 2275 for (unsigned op = 0, opc = CI->getNumArgOperands(); op!= opc; ++op) 2276 ScalarTys.push_back(CI->getArgOperand(op)->getType()); 2277 2278 FastMathFlags FMF; 2279 if (auto *FPMO = dyn_cast<FPMathOperator>(CI)) 2280 FMF = FPMO->getFastMathFlags(); 2281 2282 if (NeedToShuffleReuses) { 2283 ReuseShuffleCost -= 2284 (ReuseShuffleNumbers - VL.size()) * 2285 TTI->getIntrinsicInstrCost(ID, ScalarTy, ScalarTys, FMF); 2286 } 2287 int ScalarCallCost = VecTy->getNumElements() * 2288 TTI->getIntrinsicInstrCost(ID, ScalarTy, ScalarTys, FMF); 2289 2290 SmallVector<Value *, 4> Args(CI->arg_operands()); 2291 int VecCallCost = TTI->getIntrinsicInstrCost(ID, CI->getType(), Args, FMF, 2292 VecTy->getNumElements()); 2293 2294 DEBUG(dbgs() << "SLP: Call cost "<< VecCallCost - ScalarCallCost 2295 << " (" << VecCallCost << "-" << ScalarCallCost << ")" 2296 << " for " << *CI << "\n"); 2297 2298 return ReuseShuffleCost + VecCallCost - ScalarCallCost; 2299 } 2300 case Instruction::ShuffleVector: { 2301 TargetTransformInfo::OperandValueKind Op1VK = 2302 TargetTransformInfo::OK_AnyValue; 2303 TargetTransformInfo::OperandValueKind Op2VK = 2304 TargetTransformInfo::OK_AnyValue; 2305 int ScalarCost = 0; 2306 if (NeedToShuffleReuses) { 2307 for (unsigned Idx : E->ReuseShuffleIndices) { 2308 Instruction *I = cast<Instruction>(VL[Idx]); 2309 if (!I) 2310 continue; 2311 ReuseShuffleCost -= TTI->getArithmeticInstrCost( 2312 I->getOpcode(), ScalarTy, Op1VK, Op2VK); 2313 } 2314 for (Value *V : VL) { 2315 Instruction *I = cast<Instruction>(V); 2316 if (!I) 2317 continue; 2318 ReuseShuffleCost += TTI->getArithmeticInstrCost( 2319 I->getOpcode(), ScalarTy, Op1VK, Op2VK); 2320 } 2321 } 2322 int VecCost = 0; 2323 for (Value *i : VL) { 2324 Instruction *I = cast<Instruction>(i); 2325 if (!I) 2326 break; 2327 ScalarCost += 2328 TTI->getArithmeticInstrCost(I->getOpcode(), ScalarTy, Op1VK, Op2VK); 2329 } 2330 // VecCost is equal to sum of the cost of creating 2 vectors 2331 // and the cost of creating shuffle. 2332 Instruction *I0 = cast<Instruction>(VL[0]); 2333 VecCost = 2334 TTI->getArithmeticInstrCost(I0->getOpcode(), VecTy, Op1VK, Op2VK); 2335 Instruction *I1 = cast<Instruction>(VL[1]); 2336 VecCost += 2337 TTI->getArithmeticInstrCost(I1->getOpcode(), VecTy, Op1VK, Op2VK); 2338 VecCost += 2339 TTI->getShuffleCost(TargetTransformInfo::SK_Alternate, VecTy, 0); 2340 return ReuseShuffleCost + VecCost - ScalarCost; 2341 } 2342 default: 2343 llvm_unreachable("Unknown instruction"); 2344 } 2345 } 2346 2347 bool BoUpSLP::isFullyVectorizableTinyTree() { 2348 DEBUG(dbgs() << "SLP: Check whether the tree with height " << 2349 VectorizableTree.size() << " is fully vectorizable .\n"); 2350 2351 // We only handle trees of heights 1 and 2. 2352 if (VectorizableTree.size() == 1 && !VectorizableTree[0].NeedToGather) 2353 return true; 2354 2355 if (VectorizableTree.size() != 2) 2356 return false; 2357 2358 // Handle splat and all-constants stores. 2359 if (!VectorizableTree[0].NeedToGather && 2360 (allConstant(VectorizableTree[1].Scalars) || 2361 isSplat(VectorizableTree[1].Scalars))) 2362 return true; 2363 2364 // Gathering cost would be too much for tiny trees. 2365 if (VectorizableTree[0].NeedToGather || VectorizableTree[1].NeedToGather) 2366 return false; 2367 2368 return true; 2369 } 2370 2371 bool BoUpSLP::isTreeTinyAndNotFullyVectorizable() { 2372 // We can vectorize the tree if its size is greater than or equal to the 2373 // minimum size specified by the MinTreeSize command line option. 2374 if (VectorizableTree.size() >= MinTreeSize) 2375 return false; 2376 2377 // If we have a tiny tree (a tree whose size is less than MinTreeSize), we 2378 // can vectorize it if we can prove it fully vectorizable. 2379 if (isFullyVectorizableTinyTree()) 2380 return false; 2381 2382 assert(VectorizableTree.empty() 2383 ? ExternalUses.empty() 2384 : true && "We shouldn't have any external users"); 2385 2386 // Otherwise, we can't vectorize the tree. It is both tiny and not fully 2387 // vectorizable. 2388 return true; 2389 } 2390 2391 int BoUpSLP::getSpillCost() { 2392 // Walk from the bottom of the tree to the top, tracking which values are 2393 // live. When we see a call instruction that is not part of our tree, 2394 // query TTI to see if there is a cost to keeping values live over it 2395 // (for example, if spills and fills are required). 2396 unsigned BundleWidth = VectorizableTree.front().Scalars.size(); 2397 int Cost = 0; 2398 2399 SmallPtrSet<Instruction*, 4> LiveValues; 2400 Instruction *PrevInst = nullptr; 2401 2402 for (const auto &N : VectorizableTree) { 2403 Instruction *Inst = dyn_cast<Instruction>(N.Scalars[0]); 2404 if (!Inst) 2405 continue; 2406 2407 if (!PrevInst) { 2408 PrevInst = Inst; 2409 continue; 2410 } 2411 2412 // Update LiveValues. 2413 LiveValues.erase(PrevInst); 2414 for (auto &J : PrevInst->operands()) { 2415 if (isa<Instruction>(&*J) && getTreeEntry(&*J)) 2416 LiveValues.insert(cast<Instruction>(&*J)); 2417 } 2418 2419 DEBUG( 2420 dbgs() << "SLP: #LV: " << LiveValues.size(); 2421 for (auto *X : LiveValues) 2422 dbgs() << " " << X->getName(); 2423 dbgs() << ", Looking at "; 2424 Inst->dump(); 2425 ); 2426 2427 // Now find the sequence of instructions between PrevInst and Inst. 2428 BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(), 2429 PrevInstIt = 2430 PrevInst->getIterator().getReverse(); 2431 while (InstIt != PrevInstIt) { 2432 if (PrevInstIt == PrevInst->getParent()->rend()) { 2433 PrevInstIt = Inst->getParent()->rbegin(); 2434 continue; 2435 } 2436 2437 if (isa<CallInst>(&*PrevInstIt) && &*PrevInstIt != PrevInst) { 2438 SmallVector<Type*, 4> V; 2439 for (auto *II : LiveValues) 2440 V.push_back(VectorType::get(II->getType(), BundleWidth)); 2441 Cost += TTI->getCostOfKeepingLiveOverCall(V); 2442 } 2443 2444 ++PrevInstIt; 2445 } 2446 2447 PrevInst = Inst; 2448 } 2449 2450 return Cost; 2451 } 2452 2453 int BoUpSLP::getTreeCost() { 2454 int Cost = 0; 2455 DEBUG(dbgs() << "SLP: Calculating cost for tree of size " << 2456 VectorizableTree.size() << ".\n"); 2457 2458 unsigned BundleWidth = VectorizableTree[0].Scalars.size(); 2459 2460 for (unsigned I = 0, E = VectorizableTree.size(); I < E; ++I) { 2461 TreeEntry &TE = VectorizableTree[I]; 2462 2463 // We create duplicate tree entries for gather sequences that have multiple 2464 // uses. However, we should not compute the cost of duplicate sequences. 2465 // For example, if we have a build vector (i.e., insertelement sequence) 2466 // that is used by more than one vector instruction, we only need to 2467 // compute the cost of the insertelement instructions once. The redundent 2468 // instructions will be eliminated by CSE. 2469 // 2470 // We should consider not creating duplicate tree entries for gather 2471 // sequences, and instead add additional edges to the tree representing 2472 // their uses. Since such an approach results in fewer total entries, 2473 // existing heuristics based on tree size may yeild different results. 2474 // 2475 if (TE.NeedToGather && 2476 std::any_of(std::next(VectorizableTree.begin(), I + 1), 2477 VectorizableTree.end(), [TE](TreeEntry &Entry) { 2478 return Entry.NeedToGather && Entry.isSame(TE.Scalars); 2479 })) 2480 continue; 2481 2482 int C = getEntryCost(&TE); 2483 DEBUG(dbgs() << "SLP: Adding cost " << C << " for bundle that starts with " 2484 << *TE.Scalars[0] << ".\n"); 2485 Cost += C; 2486 } 2487 2488 SmallSet<Value *, 16> ExtractCostCalculated; 2489 int ExtractCost = 0; 2490 for (ExternalUser &EU : ExternalUses) { 2491 // We only add extract cost once for the same scalar. 2492 if (!ExtractCostCalculated.insert(EU.Scalar).second) 2493 continue; 2494 2495 // Uses by ephemeral values are free (because the ephemeral value will be 2496 // removed prior to code generation, and so the extraction will be 2497 // removed as well). 2498 if (EphValues.count(EU.User)) 2499 continue; 2500 2501 // If we plan to rewrite the tree in a smaller type, we will need to sign 2502 // extend the extracted value back to the original type. Here, we account 2503 // for the extract and the added cost of the sign extend if needed. 2504 auto *VecTy = VectorType::get(EU.Scalar->getType(), BundleWidth); 2505 auto *ScalarRoot = VectorizableTree[0].Scalars[0]; 2506 if (MinBWs.count(ScalarRoot)) { 2507 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 2508 auto Extend = 2509 MinBWs[ScalarRoot].second ? Instruction::SExt : Instruction::ZExt; 2510 VecTy = VectorType::get(MinTy, BundleWidth); 2511 ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(), 2512 VecTy, EU.Lane); 2513 } else { 2514 ExtractCost += 2515 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, EU.Lane); 2516 } 2517 } 2518 2519 int SpillCost = getSpillCost(); 2520 Cost += SpillCost + ExtractCost; 2521 2522 std::string Str; 2523 { 2524 raw_string_ostream OS(Str); 2525 OS << "SLP: Spill Cost = " << SpillCost << ".\n" 2526 << "SLP: Extract Cost = " << ExtractCost << ".\n" 2527 << "SLP: Total Cost = " << Cost << ".\n"; 2528 } 2529 DEBUG(dbgs() << Str); 2530 2531 if (ViewSLPTree) 2532 ViewGraph(this, "SLP" + F->getName(), false, Str); 2533 2534 return Cost; 2535 } 2536 2537 int BoUpSLP::getGatherCost(Type *Ty, 2538 const DenseSet<unsigned> &ShuffledIndices) { 2539 int Cost = 0; 2540 for (unsigned i = 0, e = cast<VectorType>(Ty)->getNumElements(); i < e; ++i) 2541 if (!ShuffledIndices.count(i)) 2542 Cost += TTI->getVectorInstrCost(Instruction::InsertElement, Ty, i); 2543 if (!ShuffledIndices.empty()) 2544 Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, Ty); 2545 return Cost; 2546 } 2547 2548 int BoUpSLP::getGatherCost(ArrayRef<Value *> VL) { 2549 // Find the type of the operands in VL. 2550 Type *ScalarTy = VL[0]->getType(); 2551 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) 2552 ScalarTy = SI->getValueOperand()->getType(); 2553 VectorType *VecTy = VectorType::get(ScalarTy, VL.size()); 2554 // Find the cost of inserting/extracting values from the vector. 2555 // Check if the same elements are inserted several times and count them as 2556 // shuffle candidates. 2557 DenseSet<unsigned> ShuffledElements; 2558 DenseSet<Value *> UniqueElements; 2559 // Iterate in reverse order to consider insert elements with the high cost. 2560 for (unsigned I = VL.size(); I > 0; --I) { 2561 unsigned Idx = I - 1; 2562 if (!UniqueElements.insert(VL[Idx]).second) 2563 ShuffledElements.insert(Idx); 2564 } 2565 return getGatherCost(VecTy, ShuffledElements); 2566 } 2567 2568 // Reorder commutative operations in alternate shuffle if the resulting vectors 2569 // are consecutive loads. This would allow us to vectorize the tree. 2570 // If we have something like- 2571 // load a[0] - load b[0] 2572 // load b[1] + load a[1] 2573 // load a[2] - load b[2] 2574 // load a[3] + load b[3] 2575 // Reordering the second load b[1] load a[1] would allow us to vectorize this 2576 // code. 2577 void BoUpSLP::reorderAltShuffleOperands(unsigned Opcode, ArrayRef<Value *> VL, 2578 SmallVectorImpl<Value *> &Left, 2579 SmallVectorImpl<Value *> &Right) { 2580 // Push left and right operands of binary operation into Left and Right 2581 unsigned AltOpcode = getAltOpcode(Opcode); 2582 (void)AltOpcode; 2583 for (Value *V : VL) { 2584 auto *I = cast<Instruction>(V); 2585 assert(sameOpcodeOrAlt(Opcode, AltOpcode, I->getOpcode()) && 2586 "Incorrect instruction in vector"); 2587 Left.push_back(I->getOperand(0)); 2588 Right.push_back(I->getOperand(1)); 2589 } 2590 2591 // Reorder if we have a commutative operation and consecutive access 2592 // are on either side of the alternate instructions. 2593 for (unsigned j = 0; j < VL.size() - 1; ++j) { 2594 if (LoadInst *L = dyn_cast<LoadInst>(Left[j])) { 2595 if (LoadInst *L1 = dyn_cast<LoadInst>(Right[j + 1])) { 2596 Instruction *VL1 = cast<Instruction>(VL[j]); 2597 Instruction *VL2 = cast<Instruction>(VL[j + 1]); 2598 if (VL1->isCommutative() && isConsecutiveAccess(L, L1, *DL, *SE)) { 2599 std::swap(Left[j], Right[j]); 2600 continue; 2601 } else if (VL2->isCommutative() && 2602 isConsecutiveAccess(L, L1, *DL, *SE)) { 2603 std::swap(Left[j + 1], Right[j + 1]); 2604 continue; 2605 } 2606 // else unchanged 2607 } 2608 } 2609 if (LoadInst *L = dyn_cast<LoadInst>(Right[j])) { 2610 if (LoadInst *L1 = dyn_cast<LoadInst>(Left[j + 1])) { 2611 Instruction *VL1 = cast<Instruction>(VL[j]); 2612 Instruction *VL2 = cast<Instruction>(VL[j + 1]); 2613 if (VL1->isCommutative() && isConsecutiveAccess(L, L1, *DL, *SE)) { 2614 std::swap(Left[j], Right[j]); 2615 continue; 2616 } else if (VL2->isCommutative() && 2617 isConsecutiveAccess(L, L1, *DL, *SE)) { 2618 std::swap(Left[j + 1], Right[j + 1]); 2619 continue; 2620 } 2621 // else unchanged 2622 } 2623 } 2624 } 2625 } 2626 2627 // Return true if I should be commuted before adding it's left and right 2628 // operands to the arrays Left and Right. 2629 // 2630 // The vectorizer is trying to either have all elements one side being 2631 // instruction with the same opcode to enable further vectorization, or having 2632 // a splat to lower the vectorizing cost. 2633 static bool shouldReorderOperands( 2634 int i, unsigned Opcode, Instruction &I, ArrayRef<Value *> Left, 2635 ArrayRef<Value *> Right, bool AllSameOpcodeLeft, bool AllSameOpcodeRight, 2636 bool SplatLeft, bool SplatRight, Value *&VLeft, Value *&VRight) { 2637 VLeft = I.getOperand(0); 2638 VRight = I.getOperand(1); 2639 // If we have "SplatRight", try to see if commuting is needed to preserve it. 2640 if (SplatRight) { 2641 if (VRight == Right[i - 1]) 2642 // Preserve SplatRight 2643 return false; 2644 if (VLeft == Right[i - 1]) { 2645 // Commuting would preserve SplatRight, but we don't want to break 2646 // SplatLeft either, i.e. preserve the original order if possible. 2647 // (FIXME: why do we care?) 2648 if (SplatLeft && VLeft == Left[i - 1]) 2649 return false; 2650 return true; 2651 } 2652 } 2653 // Symmetrically handle Right side. 2654 if (SplatLeft) { 2655 if (VLeft == Left[i - 1]) 2656 // Preserve SplatLeft 2657 return false; 2658 if (VRight == Left[i - 1]) 2659 return true; 2660 } 2661 2662 Instruction *ILeft = dyn_cast<Instruction>(VLeft); 2663 Instruction *IRight = dyn_cast<Instruction>(VRight); 2664 2665 // If we have "AllSameOpcodeRight", try to see if the left operands preserves 2666 // it and not the right, in this case we want to commute. 2667 if (AllSameOpcodeRight) { 2668 unsigned RightPrevOpcode = cast<Instruction>(Right[i - 1])->getOpcode(); 2669 if (IRight && RightPrevOpcode == IRight->getOpcode()) 2670 // Do not commute, a match on the right preserves AllSameOpcodeRight 2671 return false; 2672 if (ILeft && RightPrevOpcode == ILeft->getOpcode()) { 2673 // We have a match and may want to commute, but first check if there is 2674 // not also a match on the existing operands on the Left to preserve 2675 // AllSameOpcodeLeft, i.e. preserve the original order if possible. 2676 // (FIXME: why do we care?) 2677 if (AllSameOpcodeLeft && ILeft && 2678 cast<Instruction>(Left[i - 1])->getOpcode() == ILeft->getOpcode()) 2679 return false; 2680 return true; 2681 } 2682 } 2683 // Symmetrically handle Left side. 2684 if (AllSameOpcodeLeft) { 2685 unsigned LeftPrevOpcode = cast<Instruction>(Left[i - 1])->getOpcode(); 2686 if (ILeft && LeftPrevOpcode == ILeft->getOpcode()) 2687 return false; 2688 if (IRight && LeftPrevOpcode == IRight->getOpcode()) 2689 return true; 2690 } 2691 return false; 2692 } 2693 2694 void BoUpSLP::reorderInputsAccordingToOpcode(unsigned Opcode, 2695 ArrayRef<Value *> VL, 2696 SmallVectorImpl<Value *> &Left, 2697 SmallVectorImpl<Value *> &Right) { 2698 if (!VL.empty()) { 2699 // Peel the first iteration out of the loop since there's nothing 2700 // interesting to do anyway and it simplifies the checks in the loop. 2701 auto *I = cast<Instruction>(VL[0]); 2702 Value *VLeft = I->getOperand(0); 2703 Value *VRight = I->getOperand(1); 2704 if (!isa<Instruction>(VRight) && isa<Instruction>(VLeft)) 2705 // Favor having instruction to the right. FIXME: why? 2706 std::swap(VLeft, VRight); 2707 Left.push_back(VLeft); 2708 Right.push_back(VRight); 2709 } 2710 2711 // Keep track if we have instructions with all the same opcode on one side. 2712 bool AllSameOpcodeLeft = isa<Instruction>(Left[0]); 2713 bool AllSameOpcodeRight = isa<Instruction>(Right[0]); 2714 // Keep track if we have one side with all the same value (broadcast). 2715 bool SplatLeft = true; 2716 bool SplatRight = true; 2717 2718 for (unsigned i = 1, e = VL.size(); i != e; ++i) { 2719 Instruction *I = cast<Instruction>(VL[i]); 2720 assert(((I->getOpcode() == Opcode && I->isCommutative()) || 2721 (I->getOpcode() != Opcode && Instruction::isCommutative(Opcode))) && 2722 "Can only process commutative instruction"); 2723 // Commute to favor either a splat or maximizing having the same opcodes on 2724 // one side. 2725 Value *VLeft; 2726 Value *VRight; 2727 if (shouldReorderOperands(i, Opcode, *I, Left, Right, AllSameOpcodeLeft, 2728 AllSameOpcodeRight, SplatLeft, SplatRight, VLeft, 2729 VRight)) { 2730 Left.push_back(VRight); 2731 Right.push_back(VLeft); 2732 } else { 2733 Left.push_back(VLeft); 2734 Right.push_back(VRight); 2735 } 2736 // Update Splat* and AllSameOpcode* after the insertion. 2737 SplatRight = SplatRight && (Right[i - 1] == Right[i]); 2738 SplatLeft = SplatLeft && (Left[i - 1] == Left[i]); 2739 AllSameOpcodeLeft = AllSameOpcodeLeft && isa<Instruction>(Left[i]) && 2740 (cast<Instruction>(Left[i - 1])->getOpcode() == 2741 cast<Instruction>(Left[i])->getOpcode()); 2742 AllSameOpcodeRight = AllSameOpcodeRight && isa<Instruction>(Right[i]) && 2743 (cast<Instruction>(Right[i - 1])->getOpcode() == 2744 cast<Instruction>(Right[i])->getOpcode()); 2745 } 2746 2747 // If one operand end up being broadcast, return this operand order. 2748 if (SplatRight || SplatLeft) 2749 return; 2750 2751 // Finally check if we can get longer vectorizable chain by reordering 2752 // without breaking the good operand order detected above. 2753 // E.g. If we have something like- 2754 // load a[0] load b[0] 2755 // load b[1] load a[1] 2756 // load a[2] load b[2] 2757 // load a[3] load b[3] 2758 // Reordering the second load b[1] load a[1] would allow us to vectorize 2759 // this code and we still retain AllSameOpcode property. 2760 // FIXME: This load reordering might break AllSameOpcode in some rare cases 2761 // such as- 2762 // add a[0],c[0] load b[0] 2763 // add a[1],c[2] load b[1] 2764 // b[2] load b[2] 2765 // add a[3],c[3] load b[3] 2766 for (unsigned j = 0; j < VL.size() - 1; ++j) { 2767 if (LoadInst *L = dyn_cast<LoadInst>(Left[j])) { 2768 if (LoadInst *L1 = dyn_cast<LoadInst>(Right[j + 1])) { 2769 if (isConsecutiveAccess(L, L1, *DL, *SE)) { 2770 std::swap(Left[j + 1], Right[j + 1]); 2771 continue; 2772 } 2773 } 2774 } 2775 if (LoadInst *L = dyn_cast<LoadInst>(Right[j])) { 2776 if (LoadInst *L1 = dyn_cast<LoadInst>(Left[j + 1])) { 2777 if (isConsecutiveAccess(L, L1, *DL, *SE)) { 2778 std::swap(Left[j + 1], Right[j + 1]); 2779 continue; 2780 } 2781 } 2782 } 2783 // else unchanged 2784 } 2785 } 2786 2787 void BoUpSLP::setInsertPointAfterBundle(ArrayRef<Value *> VL, Value *OpValue) { 2788 // Get the basic block this bundle is in. All instructions in the bundle 2789 // should be in this block. 2790 auto *Front = cast<Instruction>(OpValue); 2791 auto *BB = Front->getParent(); 2792 const unsigned Opcode = cast<Instruction>(OpValue)->getOpcode(); 2793 const unsigned AltOpcode = getAltOpcode(Opcode); 2794 assert(llvm::all_of(make_range(VL.begin(), VL.end()), [=](Value *V) -> bool { 2795 return !sameOpcodeOrAlt(Opcode, AltOpcode, 2796 cast<Instruction>(V)->getOpcode()) || 2797 cast<Instruction>(V)->getParent() == BB; 2798 })); 2799 2800 // The last instruction in the bundle in program order. 2801 Instruction *LastInst = nullptr; 2802 2803 // Find the last instruction. The common case should be that BB has been 2804 // scheduled, and the last instruction is VL.back(). So we start with 2805 // VL.back() and iterate over schedule data until we reach the end of the 2806 // bundle. The end of the bundle is marked by null ScheduleData. 2807 if (BlocksSchedules.count(BB)) { 2808 auto *Bundle = 2809 BlocksSchedules[BB]->getScheduleData(isOneOf(OpValue, VL.back())); 2810 if (Bundle && Bundle->isPartOfBundle()) 2811 for (; Bundle; Bundle = Bundle->NextInBundle) 2812 if (Bundle->OpValue == Bundle->Inst) 2813 LastInst = Bundle->Inst; 2814 } 2815 2816 // LastInst can still be null at this point if there's either not an entry 2817 // for BB in BlocksSchedules or there's no ScheduleData available for 2818 // VL.back(). This can be the case if buildTree_rec aborts for various 2819 // reasons (e.g., the maximum recursion depth is reached, the maximum region 2820 // size is reached, etc.). ScheduleData is initialized in the scheduling 2821 // "dry-run". 2822 // 2823 // If this happens, we can still find the last instruction by brute force. We 2824 // iterate forwards from Front (inclusive) until we either see all 2825 // instructions in the bundle or reach the end of the block. If Front is the 2826 // last instruction in program order, LastInst will be set to Front, and we 2827 // will visit all the remaining instructions in the block. 2828 // 2829 // One of the reasons we exit early from buildTree_rec is to place an upper 2830 // bound on compile-time. Thus, taking an additional compile-time hit here is 2831 // not ideal. However, this should be exceedingly rare since it requires that 2832 // we both exit early from buildTree_rec and that the bundle be out-of-order 2833 // (causing us to iterate all the way to the end of the block). 2834 if (!LastInst) { 2835 SmallPtrSet<Value *, 16> Bundle(VL.begin(), VL.end()); 2836 for (auto &I : make_range(BasicBlock::iterator(Front), BB->end())) { 2837 if (Bundle.erase(&I) && sameOpcodeOrAlt(Opcode, AltOpcode, I.getOpcode())) 2838 LastInst = &I; 2839 if (Bundle.empty()) 2840 break; 2841 } 2842 } 2843 2844 // Set the insertion point after the last instruction in the bundle. Set the 2845 // debug location to Front. 2846 Builder.SetInsertPoint(BB, ++LastInst->getIterator()); 2847 Builder.SetCurrentDebugLocation(Front->getDebugLoc()); 2848 } 2849 2850 Value *BoUpSLP::Gather(ArrayRef<Value *> VL, VectorType *Ty) { 2851 Value *Vec = UndefValue::get(Ty); 2852 // Generate the 'InsertElement' instruction. 2853 for (unsigned i = 0; i < Ty->getNumElements(); ++i) { 2854 Vec = Builder.CreateInsertElement(Vec, VL[i], Builder.getInt32(i)); 2855 if (Instruction *Insrt = dyn_cast<Instruction>(Vec)) { 2856 GatherSeq.insert(Insrt); 2857 CSEBlocks.insert(Insrt->getParent()); 2858 2859 // Add to our 'need-to-extract' list. 2860 if (TreeEntry *E = getTreeEntry(VL[i])) { 2861 // Find which lane we need to extract. 2862 int FoundLane = -1; 2863 for (unsigned Lane = 0, LE = E->Scalars.size(); Lane != LE; ++Lane) { 2864 // Is this the lane of the scalar that we are looking for ? 2865 if (E->Scalars[Lane] == VL[i]) { 2866 FoundLane = Lane; 2867 break; 2868 } 2869 } 2870 assert(FoundLane >= 0 && "Could not find the correct lane"); 2871 if (!E->ReuseShuffleIndices.empty()) { 2872 FoundLane = 2873 std::distance(E->ReuseShuffleIndices.begin(), 2874 llvm::find(E->ReuseShuffleIndices, FoundLane)); 2875 } 2876 ExternalUses.push_back(ExternalUser(VL[i], Insrt, FoundLane)); 2877 } 2878 } 2879 } 2880 2881 return Vec; 2882 } 2883 2884 Value *BoUpSLP::vectorizeTree(ArrayRef<Value *> VL) { 2885 InstructionsState S = getSameOpcode(VL); 2886 if (S.Opcode) { 2887 if (TreeEntry *E = getTreeEntry(S.OpValue)) { 2888 if (E->isSame(VL)) { 2889 Value *V = vectorizeTree(E); 2890 if (VL.size() == E->Scalars.size() && !E->ReuseShuffleIndices.empty()) { 2891 // We need to get the vectorized value but without shuffle. 2892 if (auto *SV = dyn_cast<ShuffleVectorInst>(V)) { 2893 V = SV->getOperand(0); 2894 } else { 2895 // Reshuffle to get only unique values. 2896 SmallVector<unsigned, 4> UniqueIdxs; 2897 SmallSet<unsigned, 4> UsedIdxs; 2898 for(unsigned Idx : E->ReuseShuffleIndices) 2899 if (UsedIdxs.insert(Idx).second) 2900 UniqueIdxs.emplace_back(Idx); 2901 V = Builder.CreateShuffleVector(V, UndefValue::get(V->getType()), 2902 UniqueIdxs); 2903 } 2904 } 2905 return V; 2906 } 2907 } 2908 } 2909 2910 Type *ScalarTy = S.OpValue->getType(); 2911 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) 2912 ScalarTy = SI->getValueOperand()->getType(); 2913 2914 // Check that every instruction appears once in this bundle. 2915 SmallVector<unsigned, 4> ReuseShuffleIndicies; 2916 SmallVector<Value *, 4> UniqueValues; 2917 if (VL.size() > 2) { 2918 DenseMap<Value *, unsigned> UniquePositions; 2919 for (Value *V : VL) { 2920 auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); 2921 ReuseShuffleIndicies.emplace_back(Res.first->second); 2922 if (Res.second || isa<Constant>(V)) 2923 UniqueValues.emplace_back(V); 2924 } 2925 // Do not shuffle single element or if number of unique values is not power 2926 // of 2. 2927 if (UniqueValues.size() == VL.size() || UniqueValues.size() <= 1 || 2928 !llvm::isPowerOf2_32(UniqueValues.size())) 2929 ReuseShuffleIndicies.clear(); 2930 else 2931 VL = UniqueValues; 2932 } 2933 VectorType *VecTy = VectorType::get(ScalarTy, VL.size()); 2934 2935 Value *V = Gather(VL, VecTy); 2936 if (!ReuseShuffleIndicies.empty()) { 2937 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 2938 ReuseShuffleIndicies, "shuffle"); 2939 if (auto *I = dyn_cast<Instruction>(V)) { 2940 GatherSeq.insert(I); 2941 CSEBlocks.insert(I->getParent()); 2942 } 2943 } 2944 return V; 2945 } 2946 2947 Value *BoUpSLP::vectorizeTree(TreeEntry *E) { 2948 IRBuilder<>::InsertPointGuard Guard(Builder); 2949 2950 if (E->VectorizedValue) { 2951 DEBUG(dbgs() << "SLP: Diamond merged for " << *E->Scalars[0] << ".\n"); 2952 return E->VectorizedValue; 2953 } 2954 2955 InstructionsState S = getSameOpcode(E->Scalars); 2956 Instruction *VL0 = cast<Instruction>(E->Scalars[0]); 2957 Type *ScalarTy = VL0->getType(); 2958 if (StoreInst *SI = dyn_cast<StoreInst>(VL0)) 2959 ScalarTy = SI->getValueOperand()->getType(); 2960 VectorType *VecTy = VectorType::get(ScalarTy, E->Scalars.size()); 2961 2962 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); 2963 2964 if (E->NeedToGather) { 2965 setInsertPointAfterBundle(E->Scalars, VL0); 2966 auto *V = Gather(E->Scalars, VecTy); 2967 if (NeedToShuffleReuses) { 2968 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 2969 E->ReuseShuffleIndices, "shuffle"); 2970 if (auto *I = dyn_cast<Instruction>(V)) { 2971 GatherSeq.insert(I); 2972 CSEBlocks.insert(I->getParent()); 2973 } 2974 } 2975 E->VectorizedValue = V; 2976 return V; 2977 } 2978 2979 unsigned ShuffleOrOp = S.IsAltShuffle ? 2980 (unsigned) Instruction::ShuffleVector : S.Opcode; 2981 switch (ShuffleOrOp) { 2982 case Instruction::PHI: { 2983 PHINode *PH = dyn_cast<PHINode>(VL0); 2984 Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI()); 2985 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 2986 PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues()); 2987 Value *V = NewPhi; 2988 if (NeedToShuffleReuses) { 2989 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 2990 E->ReuseShuffleIndices, "shuffle"); 2991 } 2992 E->VectorizedValue = V; 2993 2994 // PHINodes may have multiple entries from the same block. We want to 2995 // visit every block once. 2996 SmallSet<BasicBlock*, 4> VisitedBBs; 2997 2998 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) { 2999 ValueList Operands; 3000 BasicBlock *IBB = PH->getIncomingBlock(i); 3001 3002 if (!VisitedBBs.insert(IBB).second) { 3003 NewPhi->addIncoming(NewPhi->getIncomingValueForBlock(IBB), IBB); 3004 continue; 3005 } 3006 3007 // Prepare the operand vector. 3008 for (Value *V : E->Scalars) 3009 Operands.push_back(cast<PHINode>(V)->getIncomingValueForBlock(IBB)); 3010 3011 Builder.SetInsertPoint(IBB->getTerminator()); 3012 Builder.SetCurrentDebugLocation(PH->getDebugLoc()); 3013 Value *Vec = vectorizeTree(Operands); 3014 NewPhi->addIncoming(Vec, IBB); 3015 } 3016 3017 assert(NewPhi->getNumIncomingValues() == PH->getNumIncomingValues() && 3018 "Invalid number of incoming values"); 3019 return V; 3020 } 3021 3022 case Instruction::ExtractElement: { 3023 if (canReuseExtract(E->Scalars, VL0)) { 3024 Value *V = VL0->getOperand(0); 3025 if (NeedToShuffleReuses) { 3026 Builder.SetInsertPoint(VL0); 3027 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3028 E->ReuseShuffleIndices, "shuffle"); 3029 } 3030 E->VectorizedValue = V; 3031 return V; 3032 } 3033 setInsertPointAfterBundle(E->Scalars, VL0); 3034 auto *V = Gather(E->Scalars, VecTy); 3035 if (NeedToShuffleReuses) { 3036 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3037 E->ReuseShuffleIndices, "shuffle"); 3038 if (auto *I = dyn_cast<Instruction>(V)) { 3039 GatherSeq.insert(I); 3040 CSEBlocks.insert(I->getParent()); 3041 } 3042 } 3043 E->VectorizedValue = V; 3044 return V; 3045 } 3046 case Instruction::ExtractValue: { 3047 if (canReuseExtract(E->Scalars, VL0)) { 3048 LoadInst *LI = cast<LoadInst>(VL0->getOperand(0)); 3049 Builder.SetInsertPoint(LI); 3050 PointerType *PtrTy = PointerType::get(VecTy, LI->getPointerAddressSpace()); 3051 Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy); 3052 LoadInst *V = Builder.CreateAlignedLoad(Ptr, LI->getAlignment()); 3053 Value *NewV = propagateMetadata(V, E->Scalars); 3054 if (NeedToShuffleReuses) { 3055 NewV = Builder.CreateShuffleVector( 3056 NewV, UndefValue::get(VecTy), E->ReuseShuffleIndices, "shuffle"); 3057 } 3058 E->VectorizedValue = NewV; 3059 return NewV; 3060 } 3061 setInsertPointAfterBundle(E->Scalars, VL0); 3062 auto *V = Gather(E->Scalars, VecTy); 3063 if (NeedToShuffleReuses) { 3064 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3065 E->ReuseShuffleIndices, "shuffle"); 3066 if (auto *I = dyn_cast<Instruction>(V)) { 3067 GatherSeq.insert(I); 3068 CSEBlocks.insert(I->getParent()); 3069 } 3070 } 3071 E->VectorizedValue = V; 3072 return V; 3073 } 3074 case Instruction::ZExt: 3075 case Instruction::SExt: 3076 case Instruction::FPToUI: 3077 case Instruction::FPToSI: 3078 case Instruction::FPExt: 3079 case Instruction::PtrToInt: 3080 case Instruction::IntToPtr: 3081 case Instruction::SIToFP: 3082 case Instruction::UIToFP: 3083 case Instruction::Trunc: 3084 case Instruction::FPTrunc: 3085 case Instruction::BitCast: { 3086 ValueList INVL; 3087 for (Value *V : E->Scalars) 3088 INVL.push_back(cast<Instruction>(V)->getOperand(0)); 3089 3090 setInsertPointAfterBundle(E->Scalars, VL0); 3091 3092 Value *InVec = vectorizeTree(INVL); 3093 3094 if (E->VectorizedValue) { 3095 DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 3096 return E->VectorizedValue; 3097 } 3098 3099 CastInst *CI = dyn_cast<CastInst>(VL0); 3100 Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy); 3101 if (NeedToShuffleReuses) { 3102 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3103 E->ReuseShuffleIndices, "shuffle"); 3104 } 3105 E->VectorizedValue = V; 3106 ++NumVectorInstructions; 3107 return V; 3108 } 3109 case Instruction::FCmp: 3110 case Instruction::ICmp: { 3111 ValueList LHSV, RHSV; 3112 for (Value *V : E->Scalars) { 3113 LHSV.push_back(cast<Instruction>(V)->getOperand(0)); 3114 RHSV.push_back(cast<Instruction>(V)->getOperand(1)); 3115 } 3116 3117 setInsertPointAfterBundle(E->Scalars, VL0); 3118 3119 Value *L = vectorizeTree(LHSV); 3120 Value *R = vectorizeTree(RHSV); 3121 3122 if (E->VectorizedValue) { 3123 DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 3124 return E->VectorizedValue; 3125 } 3126 3127 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); 3128 Value *V; 3129 if (S.Opcode == Instruction::FCmp) 3130 V = Builder.CreateFCmp(P0, L, R); 3131 else 3132 V = Builder.CreateICmp(P0, L, R); 3133 3134 propagateIRFlags(V, E->Scalars, VL0); 3135 if (NeedToShuffleReuses) { 3136 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3137 E->ReuseShuffleIndices, "shuffle"); 3138 } 3139 E->VectorizedValue = V; 3140 ++NumVectorInstructions; 3141 return V; 3142 } 3143 case Instruction::Select: { 3144 ValueList TrueVec, FalseVec, CondVec; 3145 for (Value *V : E->Scalars) { 3146 CondVec.push_back(cast<Instruction>(V)->getOperand(0)); 3147 TrueVec.push_back(cast<Instruction>(V)->getOperand(1)); 3148 FalseVec.push_back(cast<Instruction>(V)->getOperand(2)); 3149 } 3150 3151 setInsertPointAfterBundle(E->Scalars, VL0); 3152 3153 Value *Cond = vectorizeTree(CondVec); 3154 Value *True = vectorizeTree(TrueVec); 3155 Value *False = vectorizeTree(FalseVec); 3156 3157 if (E->VectorizedValue) { 3158 DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 3159 return E->VectorizedValue; 3160 } 3161 3162 Value *V = Builder.CreateSelect(Cond, True, False); 3163 if (NeedToShuffleReuses) { 3164 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3165 E->ReuseShuffleIndices, "shuffle"); 3166 } 3167 E->VectorizedValue = V; 3168 ++NumVectorInstructions; 3169 return V; 3170 } 3171 case Instruction::Add: 3172 case Instruction::FAdd: 3173 case Instruction::Sub: 3174 case Instruction::FSub: 3175 case Instruction::Mul: 3176 case Instruction::FMul: 3177 case Instruction::UDiv: 3178 case Instruction::SDiv: 3179 case Instruction::FDiv: 3180 case Instruction::URem: 3181 case Instruction::SRem: 3182 case Instruction::FRem: 3183 case Instruction::Shl: 3184 case Instruction::LShr: 3185 case Instruction::AShr: 3186 case Instruction::And: 3187 case Instruction::Or: 3188 case Instruction::Xor: { 3189 ValueList LHSVL, RHSVL; 3190 if (isa<BinaryOperator>(VL0) && VL0->isCommutative()) 3191 reorderInputsAccordingToOpcode(S.Opcode, E->Scalars, LHSVL, 3192 RHSVL); 3193 else 3194 for (Value *V : E->Scalars) { 3195 auto *I = cast<Instruction>(V); 3196 LHSVL.push_back(I->getOperand(0)); 3197 RHSVL.push_back(I->getOperand(1)); 3198 } 3199 3200 setInsertPointAfterBundle(E->Scalars, VL0); 3201 3202 Value *LHS = vectorizeTree(LHSVL); 3203 Value *RHS = vectorizeTree(RHSVL); 3204 3205 if (E->VectorizedValue) { 3206 DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 3207 return E->VectorizedValue; 3208 } 3209 3210 Value *V = Builder.CreateBinOp( 3211 static_cast<Instruction::BinaryOps>(S.Opcode), LHS, RHS); 3212 propagateIRFlags(V, E->Scalars, VL0); 3213 if (auto *I = dyn_cast<Instruction>(V)) 3214 V = propagateMetadata(I, E->Scalars); 3215 3216 if (NeedToShuffleReuses) { 3217 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3218 E->ReuseShuffleIndices, "shuffle"); 3219 } 3220 E->VectorizedValue = V; 3221 ++NumVectorInstructions; 3222 3223 return V; 3224 } 3225 case Instruction::Load: { 3226 // Loads are inserted at the head of the tree because we don't want to 3227 // sink them all the way down past store instructions. 3228 bool IsReversed = 3229 !isConsecutiveAccess(E->Scalars[0], E->Scalars[1], *DL, *SE); 3230 if (IsReversed) 3231 VL0 = cast<Instruction>(E->Scalars.back()); 3232 setInsertPointAfterBundle(E->Scalars, VL0); 3233 3234 LoadInst *LI = cast<LoadInst>(VL0); 3235 Type *ScalarLoadTy = LI->getType(); 3236 unsigned AS = LI->getPointerAddressSpace(); 3237 3238 Value *VecPtr = Builder.CreateBitCast(LI->getPointerOperand(), 3239 VecTy->getPointerTo(AS)); 3240 3241 // The pointer operand uses an in-tree scalar so we add the new BitCast to 3242 // ExternalUses list to make sure that an extract will be generated in the 3243 // future. 3244 Value *PO = LI->getPointerOperand(); 3245 if (getTreeEntry(PO)) 3246 ExternalUses.push_back(ExternalUser(PO, cast<User>(VecPtr), 0)); 3247 3248 unsigned Alignment = LI->getAlignment(); 3249 LI = Builder.CreateLoad(VecPtr); 3250 if (!Alignment) { 3251 Alignment = DL->getABITypeAlignment(ScalarLoadTy); 3252 } 3253 LI->setAlignment(Alignment); 3254 Value *V = propagateMetadata(LI, E->Scalars); 3255 if (IsReversed) { 3256 SmallVector<uint32_t, 4> Mask(E->Scalars.size()); 3257 std::iota(Mask.rbegin(), Mask.rend(), 0); 3258 V = Builder.CreateShuffleVector(V, UndefValue::get(V->getType()), Mask); 3259 } 3260 if (NeedToShuffleReuses) { 3261 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3262 E->ReuseShuffleIndices, "shuffle"); 3263 } 3264 E->VectorizedValue = V; 3265 ++NumVectorInstructions; 3266 return V; 3267 } 3268 case Instruction::Store: { 3269 StoreInst *SI = cast<StoreInst>(VL0); 3270 unsigned Alignment = SI->getAlignment(); 3271 unsigned AS = SI->getPointerAddressSpace(); 3272 3273 ValueList ScalarStoreValues; 3274 for (Value *V : E->Scalars) 3275 ScalarStoreValues.push_back(cast<StoreInst>(V)->getValueOperand()); 3276 3277 setInsertPointAfterBundle(E->Scalars, VL0); 3278 3279 Value *VecValue = vectorizeTree(ScalarStoreValues); 3280 Value *ScalarPtr = SI->getPointerOperand(); 3281 Value *VecPtr = Builder.CreateBitCast(ScalarPtr, VecTy->getPointerTo(AS)); 3282 StoreInst *S = Builder.CreateStore(VecValue, VecPtr); 3283 3284 // The pointer operand uses an in-tree scalar, so add the new BitCast to 3285 // ExternalUses to make sure that an extract will be generated in the 3286 // future. 3287 if (getTreeEntry(ScalarPtr)) 3288 ExternalUses.push_back(ExternalUser(ScalarPtr, cast<User>(VecPtr), 0)); 3289 3290 if (!Alignment) 3291 Alignment = DL->getABITypeAlignment(SI->getValueOperand()->getType()); 3292 3293 S->setAlignment(Alignment); 3294 Value *V = propagateMetadata(S, E->Scalars); 3295 if (NeedToShuffleReuses) { 3296 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3297 E->ReuseShuffleIndices, "shuffle"); 3298 } 3299 E->VectorizedValue = V; 3300 ++NumVectorInstructions; 3301 return V; 3302 } 3303 case Instruction::GetElementPtr: { 3304 setInsertPointAfterBundle(E->Scalars, VL0); 3305 3306 ValueList Op0VL; 3307 for (Value *V : E->Scalars) 3308 Op0VL.push_back(cast<GetElementPtrInst>(V)->getOperand(0)); 3309 3310 Value *Op0 = vectorizeTree(Op0VL); 3311 3312 std::vector<Value *> OpVecs; 3313 for (int j = 1, e = cast<GetElementPtrInst>(VL0)->getNumOperands(); j < e; 3314 ++j) { 3315 ValueList OpVL; 3316 for (Value *V : E->Scalars) 3317 OpVL.push_back(cast<GetElementPtrInst>(V)->getOperand(j)); 3318 3319 Value *OpVec = vectorizeTree(OpVL); 3320 OpVecs.push_back(OpVec); 3321 } 3322 3323 Value *V = Builder.CreateGEP( 3324 cast<GetElementPtrInst>(VL0)->getSourceElementType(), Op0, OpVecs); 3325 if (Instruction *I = dyn_cast<Instruction>(V)) 3326 V = propagateMetadata(I, E->Scalars); 3327 3328 if (NeedToShuffleReuses) { 3329 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3330 E->ReuseShuffleIndices, "shuffle"); 3331 } 3332 E->VectorizedValue = V; 3333 ++NumVectorInstructions; 3334 3335 return V; 3336 } 3337 case Instruction::Call: { 3338 CallInst *CI = cast<CallInst>(VL0); 3339 setInsertPointAfterBundle(E->Scalars, VL0); 3340 Function *FI; 3341 Intrinsic::ID IID = Intrinsic::not_intrinsic; 3342 Value *ScalarArg = nullptr; 3343 if (CI && (FI = CI->getCalledFunction())) { 3344 IID = FI->getIntrinsicID(); 3345 } 3346 std::vector<Value *> OpVecs; 3347 for (int j = 0, e = CI->getNumArgOperands(); j < e; ++j) { 3348 ValueList OpVL; 3349 // ctlz,cttz and powi are special intrinsics whose second argument is 3350 // a scalar. This argument should not be vectorized. 3351 if (hasVectorInstrinsicScalarOpd(IID, 1) && j == 1) { 3352 CallInst *CEI = cast<CallInst>(VL0); 3353 ScalarArg = CEI->getArgOperand(j); 3354 OpVecs.push_back(CEI->getArgOperand(j)); 3355 continue; 3356 } 3357 for (Value *V : E->Scalars) { 3358 CallInst *CEI = cast<CallInst>(V); 3359 OpVL.push_back(CEI->getArgOperand(j)); 3360 } 3361 3362 Value *OpVec = vectorizeTree(OpVL); 3363 DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n"); 3364 OpVecs.push_back(OpVec); 3365 } 3366 3367 Module *M = F->getParent(); 3368 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); 3369 Type *Tys[] = { VectorType::get(CI->getType(), E->Scalars.size()) }; 3370 Function *CF = Intrinsic::getDeclaration(M, ID, Tys); 3371 SmallVector<OperandBundleDef, 1> OpBundles; 3372 CI->getOperandBundlesAsDefs(OpBundles); 3373 Value *V = Builder.CreateCall(CF, OpVecs, OpBundles); 3374 3375 // The scalar argument uses an in-tree scalar so we add the new vectorized 3376 // call to ExternalUses list to make sure that an extract will be 3377 // generated in the future. 3378 if (ScalarArg && getTreeEntry(ScalarArg)) 3379 ExternalUses.push_back(ExternalUser(ScalarArg, cast<User>(V), 0)); 3380 3381 propagateIRFlags(V, E->Scalars, VL0); 3382 if (NeedToShuffleReuses) { 3383 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3384 E->ReuseShuffleIndices, "shuffle"); 3385 } 3386 E->VectorizedValue = V; 3387 ++NumVectorInstructions; 3388 return V; 3389 } 3390 case Instruction::ShuffleVector: { 3391 ValueList LHSVL, RHSVL; 3392 assert(Instruction::isBinaryOp(S.Opcode) && 3393 "Invalid Shuffle Vector Operand"); 3394 reorderAltShuffleOperands(S.Opcode, E->Scalars, LHSVL, RHSVL); 3395 setInsertPointAfterBundle(E->Scalars, VL0); 3396 3397 Value *LHS = vectorizeTree(LHSVL); 3398 Value *RHS = vectorizeTree(RHSVL); 3399 3400 if (E->VectorizedValue) { 3401 DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); 3402 return E->VectorizedValue; 3403 } 3404 3405 // Create a vector of LHS op1 RHS 3406 Value *V0 = Builder.CreateBinOp( 3407 static_cast<Instruction::BinaryOps>(S.Opcode), LHS, RHS); 3408 3409 unsigned AltOpcode = getAltOpcode(S.Opcode); 3410 // Create a vector of LHS op2 RHS 3411 Value *V1 = Builder.CreateBinOp( 3412 static_cast<Instruction::BinaryOps>(AltOpcode), LHS, RHS); 3413 3414 // Create shuffle to take alternate operations from the vector. 3415 // Also, gather up odd and even scalar ops to propagate IR flags to 3416 // each vector operation. 3417 ValueList OddScalars, EvenScalars; 3418 unsigned e = E->Scalars.size(); 3419 SmallVector<Constant *, 8> Mask(e); 3420 for (unsigned i = 0; i < e; ++i) { 3421 if (isOdd(i)) { 3422 Mask[i] = Builder.getInt32(e + i); 3423 OddScalars.push_back(E->Scalars[i]); 3424 } else { 3425 Mask[i] = Builder.getInt32(i); 3426 EvenScalars.push_back(E->Scalars[i]); 3427 } 3428 } 3429 3430 Value *ShuffleMask = ConstantVector::get(Mask); 3431 propagateIRFlags(V0, EvenScalars); 3432 propagateIRFlags(V1, OddScalars); 3433 3434 Value *V = Builder.CreateShuffleVector(V0, V1, ShuffleMask); 3435 if (Instruction *I = dyn_cast<Instruction>(V)) 3436 V = propagateMetadata(I, E->Scalars); 3437 if (NeedToShuffleReuses) { 3438 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), 3439 E->ReuseShuffleIndices, "shuffle"); 3440 } 3441 E->VectorizedValue = V; 3442 ++NumVectorInstructions; 3443 3444 return V; 3445 } 3446 default: 3447 llvm_unreachable("unknown inst"); 3448 } 3449 return nullptr; 3450 } 3451 3452 Value *BoUpSLP::vectorizeTree() { 3453 ExtraValueToDebugLocsMap ExternallyUsedValues; 3454 return vectorizeTree(ExternallyUsedValues); 3455 } 3456 3457 Value * 3458 BoUpSLP::vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues) { 3459 // All blocks must be scheduled before any instructions are inserted. 3460 for (auto &BSIter : BlocksSchedules) { 3461 scheduleBlock(BSIter.second.get()); 3462 } 3463 3464 Builder.SetInsertPoint(&F->getEntryBlock().front()); 3465 auto *VectorRoot = vectorizeTree(&VectorizableTree[0]); 3466 3467 // If the vectorized tree can be rewritten in a smaller type, we truncate the 3468 // vectorized root. InstCombine will then rewrite the entire expression. We 3469 // sign extend the extracted values below. 3470 auto *ScalarRoot = VectorizableTree[0].Scalars[0]; 3471 if (MinBWs.count(ScalarRoot)) { 3472 if (auto *I = dyn_cast<Instruction>(VectorRoot)) 3473 Builder.SetInsertPoint(&*++BasicBlock::iterator(I)); 3474 auto BundleWidth = VectorizableTree[0].Scalars.size(); 3475 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); 3476 auto *VecTy = VectorType::get(MinTy, BundleWidth); 3477 auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy); 3478 VectorizableTree[0].VectorizedValue = Trunc; 3479 } 3480 3481 DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size() << " values .\n"); 3482 3483 // If necessary, sign-extend or zero-extend ScalarRoot to the larger type 3484 // specified by ScalarType. 3485 auto extend = [&](Value *ScalarRoot, Value *Ex, Type *ScalarType) { 3486 if (!MinBWs.count(ScalarRoot)) 3487 return Ex; 3488 if (MinBWs[ScalarRoot].second) 3489 return Builder.CreateSExt(Ex, ScalarType); 3490 return Builder.CreateZExt(Ex, ScalarType); 3491 }; 3492 3493 // Extract all of the elements with the external uses. 3494 for (const auto &ExternalUse : ExternalUses) { 3495 Value *Scalar = ExternalUse.Scalar; 3496 llvm::User *User = ExternalUse.User; 3497 3498 // Skip users that we already RAUW. This happens when one instruction 3499 // has multiple uses of the same value. 3500 if (User && !is_contained(Scalar->users(), User)) 3501 continue; 3502 TreeEntry *E = getTreeEntry(Scalar); 3503 assert(E && "Invalid scalar"); 3504 assert(!E->NeedToGather && "Extracting from a gather list"); 3505 3506 Value *Vec = E->VectorizedValue; 3507 assert(Vec && "Can't find vectorizable value"); 3508 3509 Value *Lane = Builder.getInt32(ExternalUse.Lane); 3510 // If User == nullptr, the Scalar is used as extra arg. Generate 3511 // ExtractElement instruction and update the record for this scalar in 3512 // ExternallyUsedValues. 3513 if (!User) { 3514 assert(ExternallyUsedValues.count(Scalar) && 3515 "Scalar with nullptr as an external user must be registered in " 3516 "ExternallyUsedValues map"); 3517 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 3518 Builder.SetInsertPoint(VecI->getParent(), 3519 std::next(VecI->getIterator())); 3520 } else { 3521 Builder.SetInsertPoint(&F->getEntryBlock().front()); 3522 } 3523 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 3524 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 3525 CSEBlocks.insert(cast<Instruction>(Scalar)->getParent()); 3526 auto &Locs = ExternallyUsedValues[Scalar]; 3527 ExternallyUsedValues.insert({Ex, Locs}); 3528 ExternallyUsedValues.erase(Scalar); 3529 continue; 3530 } 3531 3532 // Generate extracts for out-of-tree users. 3533 // Find the insertion point for the extractelement lane. 3534 if (auto *VecI = dyn_cast<Instruction>(Vec)) { 3535 if (PHINode *PH = dyn_cast<PHINode>(User)) { 3536 for (int i = 0, e = PH->getNumIncomingValues(); i != e; ++i) { 3537 if (PH->getIncomingValue(i) == Scalar) { 3538 TerminatorInst *IncomingTerminator = 3539 PH->getIncomingBlock(i)->getTerminator(); 3540 if (isa<CatchSwitchInst>(IncomingTerminator)) { 3541 Builder.SetInsertPoint(VecI->getParent(), 3542 std::next(VecI->getIterator())); 3543 } else { 3544 Builder.SetInsertPoint(PH->getIncomingBlock(i)->getTerminator()); 3545 } 3546 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 3547 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 3548 CSEBlocks.insert(PH->getIncomingBlock(i)); 3549 PH->setOperand(i, Ex); 3550 } 3551 } 3552 } else { 3553 Builder.SetInsertPoint(cast<Instruction>(User)); 3554 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 3555 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 3556 CSEBlocks.insert(cast<Instruction>(User)->getParent()); 3557 User->replaceUsesOfWith(Scalar, Ex); 3558 } 3559 } else { 3560 Builder.SetInsertPoint(&F->getEntryBlock().front()); 3561 Value *Ex = Builder.CreateExtractElement(Vec, Lane); 3562 Ex = extend(ScalarRoot, Ex, Scalar->getType()); 3563 CSEBlocks.insert(&F->getEntryBlock()); 3564 User->replaceUsesOfWith(Scalar, Ex); 3565 } 3566 3567 DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n"); 3568 } 3569 3570 // For each vectorized value: 3571 for (TreeEntry &EIdx : VectorizableTree) { 3572 TreeEntry *Entry = &EIdx; 3573 3574 // No need to handle users of gathered values. 3575 if (Entry->NeedToGather) 3576 continue; 3577 3578 assert(Entry->VectorizedValue && "Can't find vectorizable value"); 3579 3580 // For each lane: 3581 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { 3582 Value *Scalar = Entry->Scalars[Lane]; 3583 3584 Type *Ty = Scalar->getType(); 3585 if (!Ty->isVoidTy()) { 3586 #ifndef NDEBUG 3587 for (User *U : Scalar->users()) { 3588 DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n"); 3589 3590 // It is legal to replace users in the ignorelist by undef. 3591 assert((getTreeEntry(U) || is_contained(UserIgnoreList, U)) && 3592 "Replacing out-of-tree value with undef"); 3593 } 3594 #endif 3595 Value *Undef = UndefValue::get(Ty); 3596 Scalar->replaceAllUsesWith(Undef); 3597 } 3598 DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n"); 3599 eraseInstruction(cast<Instruction>(Scalar)); 3600 } 3601 } 3602 3603 Builder.ClearInsertionPoint(); 3604 3605 return VectorizableTree[0].VectorizedValue; 3606 } 3607 3608 void BoUpSLP::optimizeGatherSequence() { 3609 DEBUG(dbgs() << "SLP: Optimizing " << GatherSeq.size() 3610 << " gather sequences instructions.\n"); 3611 // LICM InsertElementInst sequences. 3612 for (Instruction *I : GatherSeq) { 3613 if (!isa<InsertElementInst>(I) && !isa<ShuffleVectorInst>(I)) 3614 continue; 3615 3616 // Check if this block is inside a loop. 3617 Loop *L = LI->getLoopFor(I->getParent()); 3618 if (!L) 3619 continue; 3620 3621 // Check if it has a preheader. 3622 BasicBlock *PreHeader = L->getLoopPreheader(); 3623 if (!PreHeader) 3624 continue; 3625 3626 // If the vector or the element that we insert into it are 3627 // instructions that are defined in this basic block then we can't 3628 // hoist this instruction. 3629 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 3630 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 3631 if (Op0 && L->contains(Op0)) 3632 continue; 3633 if (Op1 && L->contains(Op1)) 3634 continue; 3635 3636 // We can hoist this instruction. Move it to the pre-header. 3637 I->moveBefore(PreHeader->getTerminator()); 3638 } 3639 3640 // Make a list of all reachable blocks in our CSE queue. 3641 SmallVector<const DomTreeNode *, 8> CSEWorkList; 3642 CSEWorkList.reserve(CSEBlocks.size()); 3643 for (BasicBlock *BB : CSEBlocks) 3644 if (DomTreeNode *N = DT->getNode(BB)) { 3645 assert(DT->isReachableFromEntry(N)); 3646 CSEWorkList.push_back(N); 3647 } 3648 3649 // Sort blocks by domination. This ensures we visit a block after all blocks 3650 // dominating it are visited. 3651 std::stable_sort(CSEWorkList.begin(), CSEWorkList.end(), 3652 [this](const DomTreeNode *A, const DomTreeNode *B) { 3653 return DT->properlyDominates(A, B); 3654 }); 3655 3656 // Perform O(N^2) search over the gather sequences and merge identical 3657 // instructions. TODO: We can further optimize this scan if we split the 3658 // instructions into different buckets based on the insert lane. 3659 SmallVector<Instruction *, 16> Visited; 3660 for (auto I = CSEWorkList.begin(), E = CSEWorkList.end(); I != E; ++I) { 3661 assert((I == CSEWorkList.begin() || !DT->dominates(*I, *std::prev(I))) && 3662 "Worklist not sorted properly!"); 3663 BasicBlock *BB = (*I)->getBlock(); 3664 // For all instructions in blocks containing gather sequences: 3665 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e;) { 3666 Instruction *In = &*it++; 3667 if (!isa<InsertElementInst>(In) && !isa<ExtractElementInst>(In)) 3668 continue; 3669 3670 // Check if we can replace this instruction with any of the 3671 // visited instructions. 3672 for (Instruction *v : Visited) { 3673 if (In->isIdenticalTo(v) && 3674 DT->dominates(v->getParent(), In->getParent())) { 3675 In->replaceAllUsesWith(v); 3676 eraseInstruction(In); 3677 In = nullptr; 3678 break; 3679 } 3680 } 3681 if (In) { 3682 assert(!is_contained(Visited, In)); 3683 Visited.push_back(In); 3684 } 3685 } 3686 } 3687 CSEBlocks.clear(); 3688 GatherSeq.clear(); 3689 } 3690 3691 // Groups the instructions to a bundle (which is then a single scheduling entity) 3692 // and schedules instructions until the bundle gets ready. 3693 bool BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL, 3694 BoUpSLP *SLP, Value *OpValue) { 3695 if (isa<PHINode>(OpValue)) 3696 return true; 3697 3698 // Initialize the instruction bundle. 3699 Instruction *OldScheduleEnd = ScheduleEnd; 3700 ScheduleData *PrevInBundle = nullptr; 3701 ScheduleData *Bundle = nullptr; 3702 bool ReSchedule = false; 3703 DEBUG(dbgs() << "SLP: bundle: " << *OpValue << "\n"); 3704 3705 // Make sure that the scheduling region contains all 3706 // instructions of the bundle. 3707 for (Value *V : VL) { 3708 if (!extendSchedulingRegion(V, OpValue)) 3709 return false; 3710 } 3711 3712 for (Value *V : VL) { 3713 ScheduleData *BundleMember = getScheduleData(V); 3714 assert(BundleMember && 3715 "no ScheduleData for bundle member (maybe not in same basic block)"); 3716 if (BundleMember->IsScheduled) { 3717 // A bundle member was scheduled as single instruction before and now 3718 // needs to be scheduled as part of the bundle. We just get rid of the 3719 // existing schedule. 3720 DEBUG(dbgs() << "SLP: reset schedule because " << *BundleMember 3721 << " was already scheduled\n"); 3722 ReSchedule = true; 3723 } 3724 assert(BundleMember->isSchedulingEntity() && 3725 "bundle member already part of other bundle"); 3726 if (PrevInBundle) { 3727 PrevInBundle->NextInBundle = BundleMember; 3728 } else { 3729 Bundle = BundleMember; 3730 } 3731 BundleMember->UnscheduledDepsInBundle = 0; 3732 Bundle->UnscheduledDepsInBundle += BundleMember->UnscheduledDeps; 3733 3734 // Group the instructions to a bundle. 3735 BundleMember->FirstInBundle = Bundle; 3736 PrevInBundle = BundleMember; 3737 } 3738 if (ScheduleEnd != OldScheduleEnd) { 3739 // The scheduling region got new instructions at the lower end (or it is a 3740 // new region for the first bundle). This makes it necessary to 3741 // recalculate all dependencies. 3742 // It is seldom that this needs to be done a second time after adding the 3743 // initial bundle to the region. 3744 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 3745 doForAllOpcodes(I, [](ScheduleData *SD) { 3746 SD->clearDependencies(); 3747 }); 3748 } 3749 ReSchedule = true; 3750 } 3751 if (ReSchedule) { 3752 resetSchedule(); 3753 initialFillReadyList(ReadyInsts); 3754 } 3755 3756 DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle << " in block " 3757 << BB->getName() << "\n"); 3758 3759 calculateDependencies(Bundle, true, SLP); 3760 3761 // Now try to schedule the new bundle. As soon as the bundle is "ready" it 3762 // means that there are no cyclic dependencies and we can schedule it. 3763 // Note that's important that we don't "schedule" the bundle yet (see 3764 // cancelScheduling). 3765 while (!Bundle->isReady() && !ReadyInsts.empty()) { 3766 3767 ScheduleData *pickedSD = ReadyInsts.back(); 3768 ReadyInsts.pop_back(); 3769 3770 if (pickedSD->isSchedulingEntity() && pickedSD->isReady()) { 3771 schedule(pickedSD, ReadyInsts); 3772 } 3773 } 3774 if (!Bundle->isReady()) { 3775 cancelScheduling(VL, OpValue); 3776 return false; 3777 } 3778 return true; 3779 } 3780 3781 void BoUpSLP::BlockScheduling::cancelScheduling(ArrayRef<Value *> VL, 3782 Value *OpValue) { 3783 if (isa<PHINode>(OpValue)) 3784 return; 3785 3786 ScheduleData *Bundle = getScheduleData(OpValue); 3787 DEBUG(dbgs() << "SLP: cancel scheduling of " << *Bundle << "\n"); 3788 assert(!Bundle->IsScheduled && 3789 "Can't cancel bundle which is already scheduled"); 3790 assert(Bundle->isSchedulingEntity() && Bundle->isPartOfBundle() && 3791 "tried to unbundle something which is not a bundle"); 3792 3793 // Un-bundle: make single instructions out of the bundle. 3794 ScheduleData *BundleMember = Bundle; 3795 while (BundleMember) { 3796 assert(BundleMember->FirstInBundle == Bundle && "corrupt bundle links"); 3797 BundleMember->FirstInBundle = BundleMember; 3798 ScheduleData *Next = BundleMember->NextInBundle; 3799 BundleMember->NextInBundle = nullptr; 3800 BundleMember->UnscheduledDepsInBundle = BundleMember->UnscheduledDeps; 3801 if (BundleMember->UnscheduledDepsInBundle == 0) { 3802 ReadyInsts.insert(BundleMember); 3803 } 3804 BundleMember = Next; 3805 } 3806 } 3807 3808 BoUpSLP::ScheduleData *BoUpSLP::BlockScheduling::allocateScheduleDataChunks() { 3809 // Allocate a new ScheduleData for the instruction. 3810 if (ChunkPos >= ChunkSize) { 3811 ScheduleDataChunks.push_back(llvm::make_unique<ScheduleData[]>(ChunkSize)); 3812 ChunkPos = 0; 3813 } 3814 return &(ScheduleDataChunks.back()[ChunkPos++]); 3815 } 3816 3817 bool BoUpSLP::BlockScheduling::extendSchedulingRegion(Value *V, 3818 Value *OpValue) { 3819 if (getScheduleData(V, isOneOf(OpValue, V))) 3820 return true; 3821 Instruction *I = dyn_cast<Instruction>(V); 3822 assert(I && "bundle member must be an instruction"); 3823 assert(!isa<PHINode>(I) && "phi nodes don't need to be scheduled"); 3824 auto &&CheckSheduleForI = [this, OpValue](Instruction *I) -> bool { 3825 ScheduleData *ISD = getScheduleData(I); 3826 if (!ISD) 3827 return false; 3828 assert(isInSchedulingRegion(ISD) && 3829 "ScheduleData not in scheduling region"); 3830 ScheduleData *SD = allocateScheduleDataChunks(); 3831 SD->Inst = I; 3832 SD->init(SchedulingRegionID, OpValue); 3833 ExtraScheduleDataMap[I][OpValue] = SD; 3834 return true; 3835 }; 3836 if (CheckSheduleForI(I)) 3837 return true; 3838 if (!ScheduleStart) { 3839 // It's the first instruction in the new region. 3840 initScheduleData(I, I->getNextNode(), nullptr, nullptr); 3841 ScheduleStart = I; 3842 ScheduleEnd = I->getNextNode(); 3843 if (isOneOf(OpValue, I) != I) 3844 CheckSheduleForI(I); 3845 assert(ScheduleEnd && "tried to vectorize a TerminatorInst?"); 3846 DEBUG(dbgs() << "SLP: initialize schedule region to " << *I << "\n"); 3847 return true; 3848 } 3849 // Search up and down at the same time, because we don't know if the new 3850 // instruction is above or below the existing scheduling region. 3851 BasicBlock::reverse_iterator UpIter = 3852 ++ScheduleStart->getIterator().getReverse(); 3853 BasicBlock::reverse_iterator UpperEnd = BB->rend(); 3854 BasicBlock::iterator DownIter = ScheduleEnd->getIterator(); 3855 BasicBlock::iterator LowerEnd = BB->end(); 3856 while (true) { 3857 if (++ScheduleRegionSize > ScheduleRegionSizeLimit) { 3858 DEBUG(dbgs() << "SLP: exceeded schedule region size limit\n"); 3859 return false; 3860 } 3861 3862 if (UpIter != UpperEnd) { 3863 if (&*UpIter == I) { 3864 initScheduleData(I, ScheduleStart, nullptr, FirstLoadStoreInRegion); 3865 ScheduleStart = I; 3866 if (isOneOf(OpValue, I) != I) 3867 CheckSheduleForI(I); 3868 DEBUG(dbgs() << "SLP: extend schedule region start to " << *I << "\n"); 3869 return true; 3870 } 3871 UpIter++; 3872 } 3873 if (DownIter != LowerEnd) { 3874 if (&*DownIter == I) { 3875 initScheduleData(ScheduleEnd, I->getNextNode(), LastLoadStoreInRegion, 3876 nullptr); 3877 ScheduleEnd = I->getNextNode(); 3878 if (isOneOf(OpValue, I) != I) 3879 CheckSheduleForI(I); 3880 assert(ScheduleEnd && "tried to vectorize a TerminatorInst?"); 3881 DEBUG(dbgs() << "SLP: extend schedule region end to " << *I << "\n"); 3882 return true; 3883 } 3884 DownIter++; 3885 } 3886 assert((UpIter != UpperEnd || DownIter != LowerEnd) && 3887 "instruction not found in block"); 3888 } 3889 return true; 3890 } 3891 3892 void BoUpSLP::BlockScheduling::initScheduleData(Instruction *FromI, 3893 Instruction *ToI, 3894 ScheduleData *PrevLoadStore, 3895 ScheduleData *NextLoadStore) { 3896 ScheduleData *CurrentLoadStore = PrevLoadStore; 3897 for (Instruction *I = FromI; I != ToI; I = I->getNextNode()) { 3898 ScheduleData *SD = ScheduleDataMap[I]; 3899 if (!SD) { 3900 SD = allocateScheduleDataChunks(); 3901 ScheduleDataMap[I] = SD; 3902 SD->Inst = I; 3903 } 3904 assert(!isInSchedulingRegion(SD) && 3905 "new ScheduleData already in scheduling region"); 3906 SD->init(SchedulingRegionID, I); 3907 3908 if (I->mayReadOrWriteMemory() && 3909 (!isa<IntrinsicInst>(I) || 3910 cast<IntrinsicInst>(I)->getIntrinsicID() != Intrinsic::sideeffect)) { 3911 // Update the linked list of memory accessing instructions. 3912 if (CurrentLoadStore) { 3913 CurrentLoadStore->NextLoadStore = SD; 3914 } else { 3915 FirstLoadStoreInRegion = SD; 3916 } 3917 CurrentLoadStore = SD; 3918 } 3919 } 3920 if (NextLoadStore) { 3921 if (CurrentLoadStore) 3922 CurrentLoadStore->NextLoadStore = NextLoadStore; 3923 } else { 3924 LastLoadStoreInRegion = CurrentLoadStore; 3925 } 3926 } 3927 3928 void BoUpSLP::BlockScheduling::calculateDependencies(ScheduleData *SD, 3929 bool InsertInReadyList, 3930 BoUpSLP *SLP) { 3931 assert(SD->isSchedulingEntity()); 3932 3933 SmallVector<ScheduleData *, 10> WorkList; 3934 WorkList.push_back(SD); 3935 3936 while (!WorkList.empty()) { 3937 ScheduleData *SD = WorkList.back(); 3938 WorkList.pop_back(); 3939 3940 ScheduleData *BundleMember = SD; 3941 while (BundleMember) { 3942 assert(isInSchedulingRegion(BundleMember)); 3943 if (!BundleMember->hasValidDependencies()) { 3944 3945 DEBUG(dbgs() << "SLP: update deps of " << *BundleMember << "\n"); 3946 BundleMember->Dependencies = 0; 3947 BundleMember->resetUnscheduledDeps(); 3948 3949 // Handle def-use chain dependencies. 3950 if (BundleMember->OpValue != BundleMember->Inst) { 3951 ScheduleData *UseSD = getScheduleData(BundleMember->Inst); 3952 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 3953 BundleMember->Dependencies++; 3954 ScheduleData *DestBundle = UseSD->FirstInBundle; 3955 if (!DestBundle->IsScheduled) 3956 BundleMember->incrementUnscheduledDeps(1); 3957 if (!DestBundle->hasValidDependencies()) 3958 WorkList.push_back(DestBundle); 3959 } 3960 } else { 3961 for (User *U : BundleMember->Inst->users()) { 3962 if (isa<Instruction>(U)) { 3963 ScheduleData *UseSD = getScheduleData(U); 3964 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) { 3965 BundleMember->Dependencies++; 3966 ScheduleData *DestBundle = UseSD->FirstInBundle; 3967 if (!DestBundle->IsScheduled) 3968 BundleMember->incrementUnscheduledDeps(1); 3969 if (!DestBundle->hasValidDependencies()) 3970 WorkList.push_back(DestBundle); 3971 } 3972 } else { 3973 // I'm not sure if this can ever happen. But we need to be safe. 3974 // This lets the instruction/bundle never be scheduled and 3975 // eventually disable vectorization. 3976 BundleMember->Dependencies++; 3977 BundleMember->incrementUnscheduledDeps(1); 3978 } 3979 } 3980 } 3981 3982 // Handle the memory dependencies. 3983 ScheduleData *DepDest = BundleMember->NextLoadStore; 3984 if (DepDest) { 3985 Instruction *SrcInst = BundleMember->Inst; 3986 MemoryLocation SrcLoc = getLocation(SrcInst, SLP->AA); 3987 bool SrcMayWrite = BundleMember->Inst->mayWriteToMemory(); 3988 unsigned numAliased = 0; 3989 unsigned DistToSrc = 1; 3990 3991 while (DepDest) { 3992 assert(isInSchedulingRegion(DepDest)); 3993 3994 // We have two limits to reduce the complexity: 3995 // 1) AliasedCheckLimit: It's a small limit to reduce calls to 3996 // SLP->isAliased (which is the expensive part in this loop). 3997 // 2) MaxMemDepDistance: It's for very large blocks and it aborts 3998 // the whole loop (even if the loop is fast, it's quadratic). 3999 // It's important for the loop break condition (see below) to 4000 // check this limit even between two read-only instructions. 4001 if (DistToSrc >= MaxMemDepDistance || 4002 ((SrcMayWrite || DepDest->Inst->mayWriteToMemory()) && 4003 (numAliased >= AliasedCheckLimit || 4004 SLP->isAliased(SrcLoc, SrcInst, DepDest->Inst)))) { 4005 4006 // We increment the counter only if the locations are aliased 4007 // (instead of counting all alias checks). This gives a better 4008 // balance between reduced runtime and accurate dependencies. 4009 numAliased++; 4010 4011 DepDest->MemoryDependencies.push_back(BundleMember); 4012 BundleMember->Dependencies++; 4013 ScheduleData *DestBundle = DepDest->FirstInBundle; 4014 if (!DestBundle->IsScheduled) { 4015 BundleMember->incrementUnscheduledDeps(1); 4016 } 4017 if (!DestBundle->hasValidDependencies()) { 4018 WorkList.push_back(DestBundle); 4019 } 4020 } 4021 DepDest = DepDest->NextLoadStore; 4022 4023 // Example, explaining the loop break condition: Let's assume our 4024 // starting instruction is i0 and MaxMemDepDistance = 3. 4025 // 4026 // +--------v--v--v 4027 // i0,i1,i2,i3,i4,i5,i6,i7,i8 4028 // +--------^--^--^ 4029 // 4030 // MaxMemDepDistance let us stop alias-checking at i3 and we add 4031 // dependencies from i0 to i3,i4,.. (even if they are not aliased). 4032 // Previously we already added dependencies from i3 to i6,i7,i8 4033 // (because of MaxMemDepDistance). As we added a dependency from 4034 // i0 to i3, we have transitive dependencies from i0 to i6,i7,i8 4035 // and we can abort this loop at i6. 4036 if (DistToSrc >= 2 * MaxMemDepDistance) 4037 break; 4038 DistToSrc++; 4039 } 4040 } 4041 } 4042 BundleMember = BundleMember->NextInBundle; 4043 } 4044 if (InsertInReadyList && SD->isReady()) { 4045 ReadyInsts.push_back(SD); 4046 DEBUG(dbgs() << "SLP: gets ready on update: " << *SD->Inst << "\n"); 4047 } 4048 } 4049 } 4050 4051 void BoUpSLP::BlockScheduling::resetSchedule() { 4052 assert(ScheduleStart && 4053 "tried to reset schedule on block which has not been scheduled"); 4054 for (Instruction *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) { 4055 doForAllOpcodes(I, [&](ScheduleData *SD) { 4056 assert(isInSchedulingRegion(SD) && 4057 "ScheduleData not in scheduling region"); 4058 SD->IsScheduled = false; 4059 SD->resetUnscheduledDeps(); 4060 }); 4061 } 4062 ReadyInsts.clear(); 4063 } 4064 4065 void BoUpSLP::scheduleBlock(BlockScheduling *BS) { 4066 if (!BS->ScheduleStart) 4067 return; 4068 4069 DEBUG(dbgs() << "SLP: schedule block " << BS->BB->getName() << "\n"); 4070 4071 BS->resetSchedule(); 4072 4073 // For the real scheduling we use a more sophisticated ready-list: it is 4074 // sorted by the original instruction location. This lets the final schedule 4075 // be as close as possible to the original instruction order. 4076 struct ScheduleDataCompare { 4077 bool operator()(ScheduleData *SD1, ScheduleData *SD2) const { 4078 return SD2->SchedulingPriority < SD1->SchedulingPriority; 4079 } 4080 }; 4081 std::set<ScheduleData *, ScheduleDataCompare> ReadyInsts; 4082 4083 // Ensure that all dependency data is updated and fill the ready-list with 4084 // initial instructions. 4085 int Idx = 0; 4086 int NumToSchedule = 0; 4087 for (auto *I = BS->ScheduleStart; I != BS->ScheduleEnd; 4088 I = I->getNextNode()) { 4089 BS->doForAllOpcodes(I, [this, &Idx, &NumToSchedule, BS](ScheduleData *SD) { 4090 assert(SD->isPartOfBundle() == 4091 (getTreeEntry(SD->Inst) != nullptr) && 4092 "scheduler and vectorizer bundle mismatch"); 4093 SD->FirstInBundle->SchedulingPriority = Idx++; 4094 if (SD->isSchedulingEntity()) { 4095 BS->calculateDependencies(SD, false, this); 4096 NumToSchedule++; 4097 } 4098 }); 4099 } 4100 BS->initialFillReadyList(ReadyInsts); 4101 4102 Instruction *LastScheduledInst = BS->ScheduleEnd; 4103 4104 // Do the "real" scheduling. 4105 while (!ReadyInsts.empty()) { 4106 ScheduleData *picked = *ReadyInsts.begin(); 4107 ReadyInsts.erase(ReadyInsts.begin()); 4108 4109 // Move the scheduled instruction(s) to their dedicated places, if not 4110 // there yet. 4111 ScheduleData *BundleMember = picked; 4112 while (BundleMember) { 4113 Instruction *pickedInst = BundleMember->Inst; 4114 if (LastScheduledInst->getNextNode() != pickedInst) { 4115 BS->BB->getInstList().remove(pickedInst); 4116 BS->BB->getInstList().insert(LastScheduledInst->getIterator(), 4117 pickedInst); 4118 } 4119 LastScheduledInst = pickedInst; 4120 BundleMember = BundleMember->NextInBundle; 4121 } 4122 4123 BS->schedule(picked, ReadyInsts); 4124 NumToSchedule--; 4125 } 4126 assert(NumToSchedule == 0 && "could not schedule all instructions"); 4127 4128 // Avoid duplicate scheduling of the block. 4129 BS->ScheduleStart = nullptr; 4130 } 4131 4132 unsigned BoUpSLP::getVectorElementSize(Value *V) { 4133 // If V is a store, just return the width of the stored value without 4134 // traversing the expression tree. This is the common case. 4135 if (auto *Store = dyn_cast<StoreInst>(V)) 4136 return DL->getTypeSizeInBits(Store->getValueOperand()->getType()); 4137 4138 // If V is not a store, we can traverse the expression tree to find loads 4139 // that feed it. The type of the loaded value may indicate a more suitable 4140 // width than V's type. We want to base the vector element size on the width 4141 // of memory operations where possible. 4142 SmallVector<Instruction *, 16> Worklist; 4143 SmallPtrSet<Instruction *, 16> Visited; 4144 if (auto *I = dyn_cast<Instruction>(V)) 4145 Worklist.push_back(I); 4146 4147 // Traverse the expression tree in bottom-up order looking for loads. If we 4148 // encounter an instruciton we don't yet handle, we give up. 4149 auto MaxWidth = 0u; 4150 auto FoundUnknownInst = false; 4151 while (!Worklist.empty() && !FoundUnknownInst) { 4152 auto *I = Worklist.pop_back_val(); 4153 Visited.insert(I); 4154 4155 // We should only be looking at scalar instructions here. If the current 4156 // instruction has a vector type, give up. 4157 auto *Ty = I->getType(); 4158 if (isa<VectorType>(Ty)) 4159 FoundUnknownInst = true; 4160 4161 // If the current instruction is a load, update MaxWidth to reflect the 4162 // width of the loaded value. 4163 else if (isa<LoadInst>(I)) 4164 MaxWidth = std::max<unsigned>(MaxWidth, DL->getTypeSizeInBits(Ty)); 4165 4166 // Otherwise, we need to visit the operands of the instruction. We only 4167 // handle the interesting cases from buildTree here. If an operand is an 4168 // instruction we haven't yet visited, we add it to the worklist. 4169 else if (isa<PHINode>(I) || isa<CastInst>(I) || isa<GetElementPtrInst>(I) || 4170 isa<CmpInst>(I) || isa<SelectInst>(I) || isa<BinaryOperator>(I)) { 4171 for (Use &U : I->operands()) 4172 if (auto *J = dyn_cast<Instruction>(U.get())) 4173 if (!Visited.count(J)) 4174 Worklist.push_back(J); 4175 } 4176 4177 // If we don't yet handle the instruction, give up. 4178 else 4179 FoundUnknownInst = true; 4180 } 4181 4182 // If we didn't encounter a memory access in the expression tree, or if we 4183 // gave up for some reason, just return the width of V. 4184 if (!MaxWidth || FoundUnknownInst) 4185 return DL->getTypeSizeInBits(V->getType()); 4186 4187 // Otherwise, return the maximum width we found. 4188 return MaxWidth; 4189 } 4190 4191 // Determine if a value V in a vectorizable expression Expr can be demoted to a 4192 // smaller type with a truncation. We collect the values that will be demoted 4193 // in ToDemote and additional roots that require investigating in Roots. 4194 static bool collectValuesToDemote(Value *V, SmallPtrSetImpl<Value *> &Expr, 4195 SmallVectorImpl<Value *> &ToDemote, 4196 SmallVectorImpl<Value *> &Roots) { 4197 // We can always demote constants. 4198 if (isa<Constant>(V)) { 4199 ToDemote.push_back(V); 4200 return true; 4201 } 4202 4203 // If the value is not an instruction in the expression with only one use, it 4204 // cannot be demoted. 4205 auto *I = dyn_cast<Instruction>(V); 4206 if (!I || !I->hasOneUse() || !Expr.count(I)) 4207 return false; 4208 4209 switch (I->getOpcode()) { 4210 4211 // We can always demote truncations and extensions. Since truncations can 4212 // seed additional demotion, we save the truncated value. 4213 case Instruction::Trunc: 4214 Roots.push_back(I->getOperand(0)); 4215 break; 4216 case Instruction::ZExt: 4217 case Instruction::SExt: 4218 break; 4219 4220 // We can demote certain binary operations if we can demote both of their 4221 // operands. 4222 case Instruction::Add: 4223 case Instruction::Sub: 4224 case Instruction::Mul: 4225 case Instruction::And: 4226 case Instruction::Or: 4227 case Instruction::Xor: 4228 if (!collectValuesToDemote(I->getOperand(0), Expr, ToDemote, Roots) || 4229 !collectValuesToDemote(I->getOperand(1), Expr, ToDemote, Roots)) 4230 return false; 4231 break; 4232 4233 // We can demote selects if we can demote their true and false values. 4234 case Instruction::Select: { 4235 SelectInst *SI = cast<SelectInst>(I); 4236 if (!collectValuesToDemote(SI->getTrueValue(), Expr, ToDemote, Roots) || 4237 !collectValuesToDemote(SI->getFalseValue(), Expr, ToDemote, Roots)) 4238 return false; 4239 break; 4240 } 4241 4242 // We can demote phis if we can demote all their incoming operands. Note that 4243 // we don't need to worry about cycles since we ensure single use above. 4244 case Instruction::PHI: { 4245 PHINode *PN = cast<PHINode>(I); 4246 for (Value *IncValue : PN->incoming_values()) 4247 if (!collectValuesToDemote(IncValue, Expr, ToDemote, Roots)) 4248 return false; 4249 break; 4250 } 4251 4252 // Otherwise, conservatively give up. 4253 default: 4254 return false; 4255 } 4256 4257 // Record the value that we can demote. 4258 ToDemote.push_back(V); 4259 return true; 4260 } 4261 4262 void BoUpSLP::computeMinimumValueSizes() { 4263 // If there are no external uses, the expression tree must be rooted by a 4264 // store. We can't demote in-memory values, so there is nothing to do here. 4265 if (ExternalUses.empty()) 4266 return; 4267 4268 // We only attempt to truncate integer expressions. 4269 auto &TreeRoot = VectorizableTree[0].Scalars; 4270 auto *TreeRootIT = dyn_cast<IntegerType>(TreeRoot[0]->getType()); 4271 if (!TreeRootIT) 4272 return; 4273 4274 // If the expression is not rooted by a store, these roots should have 4275 // external uses. We will rely on InstCombine to rewrite the expression in 4276 // the narrower type. However, InstCombine only rewrites single-use values. 4277 // This means that if a tree entry other than a root is used externally, it 4278 // must have multiple uses and InstCombine will not rewrite it. The code 4279 // below ensures that only the roots are used externally. 4280 SmallPtrSet<Value *, 32> Expr(TreeRoot.begin(), TreeRoot.end()); 4281 for (auto &EU : ExternalUses) 4282 if (!Expr.erase(EU.Scalar)) 4283 return; 4284 if (!Expr.empty()) 4285 return; 4286 4287 // Collect the scalar values of the vectorizable expression. We will use this 4288 // context to determine which values can be demoted. If we see a truncation, 4289 // we mark it as seeding another demotion. 4290 for (auto &Entry : VectorizableTree) 4291 Expr.insert(Entry.Scalars.begin(), Entry.Scalars.end()); 4292 4293 // Ensure the roots of the vectorizable tree don't form a cycle. They must 4294 // have a single external user that is not in the vectorizable tree. 4295 for (auto *Root : TreeRoot) 4296 if (!Root->hasOneUse() || Expr.count(*Root->user_begin())) 4297 return; 4298 4299 // Conservatively determine if we can actually truncate the roots of the 4300 // expression. Collect the values that can be demoted in ToDemote and 4301 // additional roots that require investigating in Roots. 4302 SmallVector<Value *, 32> ToDemote; 4303 SmallVector<Value *, 4> Roots; 4304 for (auto *Root : TreeRoot) { 4305 // Do not include top zext/sext/trunc operations to those to be demoted, it 4306 // produces noise cast<vect>, trunc <vect>, exctract <vect>, cast <extract> 4307 // sequence. 4308 if (isa<Constant>(Root)) 4309 continue; 4310 auto *I = dyn_cast<Instruction>(Root); 4311 if (!I || !I->hasOneUse() || !Expr.count(I)) 4312 return; 4313 if (isa<ZExtInst>(I) || isa<SExtInst>(I)) 4314 continue; 4315 if (auto *TI = dyn_cast<TruncInst>(I)) { 4316 Roots.push_back(TI->getOperand(0)); 4317 continue; 4318 } 4319 if (!collectValuesToDemote(Root, Expr, ToDemote, Roots)) 4320 return; 4321 } 4322 4323 // The maximum bit width required to represent all the values that can be 4324 // demoted without loss of precision. It would be safe to truncate the roots 4325 // of the expression to this width. 4326 auto MaxBitWidth = 8u; 4327 4328 // We first check if all the bits of the roots are demanded. If they're not, 4329 // we can truncate the roots to this narrower type. 4330 for (auto *Root : TreeRoot) { 4331 auto Mask = DB->getDemandedBits(cast<Instruction>(Root)); 4332 MaxBitWidth = std::max<unsigned>( 4333 Mask.getBitWidth() - Mask.countLeadingZeros(), MaxBitWidth); 4334 } 4335 4336 // True if the roots can be zero-extended back to their original type, rather 4337 // than sign-extended. We know that if the leading bits are not demanded, we 4338 // can safely zero-extend. So we initialize IsKnownPositive to True. 4339 bool IsKnownPositive = true; 4340 4341 // If all the bits of the roots are demanded, we can try a little harder to 4342 // compute a narrower type. This can happen, for example, if the roots are 4343 // getelementptr indices. InstCombine promotes these indices to the pointer 4344 // width. Thus, all their bits are technically demanded even though the 4345 // address computation might be vectorized in a smaller type. 4346 // 4347 // We start by looking at each entry that can be demoted. We compute the 4348 // maximum bit width required to store the scalar by using ValueTracking to 4349 // compute the number of high-order bits we can truncate. 4350 if (MaxBitWidth == DL->getTypeSizeInBits(TreeRoot[0]->getType())) { 4351 MaxBitWidth = 8u; 4352 4353 // Determine if the sign bit of all the roots is known to be zero. If not, 4354 // IsKnownPositive is set to False. 4355 IsKnownPositive = llvm::all_of(TreeRoot, [&](Value *R) { 4356 KnownBits Known = computeKnownBits(R, *DL); 4357 return Known.isNonNegative(); 4358 }); 4359 4360 // Determine the maximum number of bits required to store the scalar 4361 // values. 4362 for (auto *Scalar : ToDemote) { 4363 auto NumSignBits = ComputeNumSignBits(Scalar, *DL, 0, AC, nullptr, DT); 4364 auto NumTypeBits = DL->getTypeSizeInBits(Scalar->getType()); 4365 MaxBitWidth = std::max<unsigned>(NumTypeBits - NumSignBits, MaxBitWidth); 4366 } 4367 4368 // If we can't prove that the sign bit is zero, we must add one to the 4369 // maximum bit width to account for the unknown sign bit. This preserves 4370 // the existing sign bit so we can safely sign-extend the root back to the 4371 // original type. Otherwise, if we know the sign bit is zero, we will 4372 // zero-extend the root instead. 4373 // 4374 // FIXME: This is somewhat suboptimal, as there will be cases where adding 4375 // one to the maximum bit width will yield a larger-than-necessary 4376 // type. In general, we need to add an extra bit only if we can't 4377 // prove that the upper bit of the original type is equal to the 4378 // upper bit of the proposed smaller type. If these two bits are the 4379 // same (either zero or one) we know that sign-extending from the 4380 // smaller type will result in the same value. Here, since we can't 4381 // yet prove this, we are just making the proposed smaller type 4382 // larger to ensure correctness. 4383 if (!IsKnownPositive) 4384 ++MaxBitWidth; 4385 } 4386 4387 // Round MaxBitWidth up to the next power-of-two. 4388 if (!isPowerOf2_64(MaxBitWidth)) 4389 MaxBitWidth = NextPowerOf2(MaxBitWidth); 4390 4391 // If the maximum bit width we compute is less than the with of the roots' 4392 // type, we can proceed with the narrowing. Otherwise, do nothing. 4393 if (MaxBitWidth >= TreeRootIT->getBitWidth()) 4394 return; 4395 4396 // If we can truncate the root, we must collect additional values that might 4397 // be demoted as a result. That is, those seeded by truncations we will 4398 // modify. 4399 while (!Roots.empty()) 4400 collectValuesToDemote(Roots.pop_back_val(), Expr, ToDemote, Roots); 4401 4402 // Finally, map the values we can demote to the maximum bit with we computed. 4403 for (auto *Scalar : ToDemote) 4404 MinBWs[Scalar] = std::make_pair(MaxBitWidth, !IsKnownPositive); 4405 } 4406 4407 namespace { 4408 4409 /// The SLPVectorizer Pass. 4410 struct SLPVectorizer : public FunctionPass { 4411 SLPVectorizerPass Impl; 4412 4413 /// Pass identification, replacement for typeid 4414 static char ID; 4415 4416 explicit SLPVectorizer() : FunctionPass(ID) { 4417 initializeSLPVectorizerPass(*PassRegistry::getPassRegistry()); 4418 } 4419 4420 bool doInitialization(Module &M) override { 4421 return false; 4422 } 4423 4424 bool runOnFunction(Function &F) override { 4425 if (skipFunction(F)) 4426 return false; 4427 4428 auto *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 4429 auto *TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F); 4430 auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>(); 4431 auto *TLI = TLIP ? &TLIP->getTLI() : nullptr; 4432 auto *AA = &getAnalysis<AAResultsWrapperPass>().getAAResults(); 4433 auto *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 4434 auto *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 4435 auto *AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F); 4436 auto *DB = &getAnalysis<DemandedBitsWrapperPass>().getDemandedBits(); 4437 auto *ORE = &getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE(); 4438 4439 return Impl.runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 4440 } 4441 4442 void getAnalysisUsage(AnalysisUsage &AU) const override { 4443 FunctionPass::getAnalysisUsage(AU); 4444 AU.addRequired<AssumptionCacheTracker>(); 4445 AU.addRequired<ScalarEvolutionWrapperPass>(); 4446 AU.addRequired<AAResultsWrapperPass>(); 4447 AU.addRequired<TargetTransformInfoWrapperPass>(); 4448 AU.addRequired<LoopInfoWrapperPass>(); 4449 AU.addRequired<DominatorTreeWrapperPass>(); 4450 AU.addRequired<DemandedBitsWrapperPass>(); 4451 AU.addRequired<OptimizationRemarkEmitterWrapperPass>(); 4452 AU.addPreserved<LoopInfoWrapperPass>(); 4453 AU.addPreserved<DominatorTreeWrapperPass>(); 4454 AU.addPreserved<AAResultsWrapperPass>(); 4455 AU.addPreserved<GlobalsAAWrapperPass>(); 4456 AU.setPreservesCFG(); 4457 } 4458 }; 4459 4460 } // end anonymous namespace 4461 4462 PreservedAnalyses SLPVectorizerPass::run(Function &F, FunctionAnalysisManager &AM) { 4463 auto *SE = &AM.getResult<ScalarEvolutionAnalysis>(F); 4464 auto *TTI = &AM.getResult<TargetIRAnalysis>(F); 4465 auto *TLI = AM.getCachedResult<TargetLibraryAnalysis>(F); 4466 auto *AA = &AM.getResult<AAManager>(F); 4467 auto *LI = &AM.getResult<LoopAnalysis>(F); 4468 auto *DT = &AM.getResult<DominatorTreeAnalysis>(F); 4469 auto *AC = &AM.getResult<AssumptionAnalysis>(F); 4470 auto *DB = &AM.getResult<DemandedBitsAnalysis>(F); 4471 auto *ORE = &AM.getResult<OptimizationRemarkEmitterAnalysis>(F); 4472 4473 bool Changed = runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE); 4474 if (!Changed) 4475 return PreservedAnalyses::all(); 4476 4477 PreservedAnalyses PA; 4478 PA.preserveSet<CFGAnalyses>(); 4479 PA.preserve<AAManager>(); 4480 PA.preserve<GlobalsAA>(); 4481 return PA; 4482 } 4483 4484 bool SLPVectorizerPass::runImpl(Function &F, ScalarEvolution *SE_, 4485 TargetTransformInfo *TTI_, 4486 TargetLibraryInfo *TLI_, AliasAnalysis *AA_, 4487 LoopInfo *LI_, DominatorTree *DT_, 4488 AssumptionCache *AC_, DemandedBits *DB_, 4489 OptimizationRemarkEmitter *ORE_) { 4490 SE = SE_; 4491 TTI = TTI_; 4492 TLI = TLI_; 4493 AA = AA_; 4494 LI = LI_; 4495 DT = DT_; 4496 AC = AC_; 4497 DB = DB_; 4498 DL = &F.getParent()->getDataLayout(); 4499 4500 Stores.clear(); 4501 GEPs.clear(); 4502 bool Changed = false; 4503 4504 // If the target claims to have no vector registers don't attempt 4505 // vectorization. 4506 if (!TTI->getNumberOfRegisters(true)) 4507 return false; 4508 4509 // Don't vectorize when the attribute NoImplicitFloat is used. 4510 if (F.hasFnAttribute(Attribute::NoImplicitFloat)) 4511 return false; 4512 4513 DEBUG(dbgs() << "SLP: Analyzing blocks in " << F.getName() << ".\n"); 4514 4515 // Use the bottom up slp vectorizer to construct chains that start with 4516 // store instructions. 4517 BoUpSLP R(&F, SE, TTI, TLI, AA, LI, DT, AC, DB, DL, ORE_); 4518 4519 // A general note: the vectorizer must use BoUpSLP::eraseInstruction() to 4520 // delete instructions. 4521 4522 // Scan the blocks in the function in post order. 4523 for (auto BB : post_order(&F.getEntryBlock())) { 4524 collectSeedInstructions(BB); 4525 4526 // Vectorize trees that end at stores. 4527 if (!Stores.empty()) { 4528 DEBUG(dbgs() << "SLP: Found stores for " << Stores.size() 4529 << " underlying objects.\n"); 4530 Changed |= vectorizeStoreChains(R); 4531 } 4532 4533 // Vectorize trees that end at reductions. 4534 Changed |= vectorizeChainsInBlock(BB, R); 4535 4536 // Vectorize the index computations of getelementptr instructions. This 4537 // is primarily intended to catch gather-like idioms ending at 4538 // non-consecutive loads. 4539 if (!GEPs.empty()) { 4540 DEBUG(dbgs() << "SLP: Found GEPs for " << GEPs.size() 4541 << " underlying objects.\n"); 4542 Changed |= vectorizeGEPIndices(BB, R); 4543 } 4544 } 4545 4546 if (Changed) { 4547 R.optimizeGatherSequence(); 4548 DEBUG(dbgs() << "SLP: vectorized \"" << F.getName() << "\"\n"); 4549 DEBUG(verifyFunction(F)); 4550 } 4551 return Changed; 4552 } 4553 4554 /// \brief Check that the Values in the slice in VL array are still existent in 4555 /// the WeakTrackingVH array. 4556 /// Vectorization of part of the VL array may cause later values in the VL array 4557 /// to become invalid. We track when this has happened in the WeakTrackingVH 4558 /// array. 4559 static bool hasValueBeenRAUWed(ArrayRef<Value *> VL, 4560 ArrayRef<WeakTrackingVH> VH, unsigned SliceBegin, 4561 unsigned SliceSize) { 4562 VL = VL.slice(SliceBegin, SliceSize); 4563 VH = VH.slice(SliceBegin, SliceSize); 4564 return !std::equal(VL.begin(), VL.end(), VH.begin()); 4565 } 4566 4567 bool SLPVectorizerPass::vectorizeStoreChain(ArrayRef<Value *> Chain, BoUpSLP &R, 4568 unsigned VecRegSize) { 4569 const unsigned ChainLen = Chain.size(); 4570 DEBUG(dbgs() << "SLP: Analyzing a store chain of length " << ChainLen 4571 << "\n"); 4572 const unsigned Sz = R.getVectorElementSize(Chain[0]); 4573 const unsigned VF = VecRegSize / Sz; 4574 4575 if (!isPowerOf2_32(Sz) || VF < 2) 4576 return false; 4577 4578 // Keep track of values that were deleted by vectorizing in the loop below. 4579 const SmallVector<WeakTrackingVH, 8> TrackValues(Chain.begin(), Chain.end()); 4580 4581 bool Changed = false; 4582 // Look for profitable vectorizable trees at all offsets, starting at zero. 4583 for (unsigned i = 0, e = ChainLen; i + VF <= e; ++i) { 4584 4585 // Check that a previous iteration of this loop did not delete the Value. 4586 if (hasValueBeenRAUWed(Chain, TrackValues, i, VF)) 4587 continue; 4588 4589 DEBUG(dbgs() << "SLP: Analyzing " << VF << " stores at offset " << i 4590 << "\n"); 4591 ArrayRef<Value *> Operands = Chain.slice(i, VF); 4592 4593 R.buildTree(Operands); 4594 if (R.isTreeTinyAndNotFullyVectorizable()) 4595 continue; 4596 4597 R.computeMinimumValueSizes(); 4598 4599 int Cost = R.getTreeCost(); 4600 4601 DEBUG(dbgs() << "SLP: Found cost=" << Cost << " for VF=" << VF << "\n"); 4602 if (Cost < -SLPCostThreshold) { 4603 DEBUG(dbgs() << "SLP: Decided to vectorize cost=" << Cost << "\n"); 4604 4605 using namespace ore; 4606 4607 R.getORE()->emit(OptimizationRemark(SV_NAME, "StoresVectorized", 4608 cast<StoreInst>(Chain[i])) 4609 << "Stores SLP vectorized with cost " << NV("Cost", Cost) 4610 << " and with tree size " 4611 << NV("TreeSize", R.getTreeSize())); 4612 4613 R.vectorizeTree(); 4614 4615 // Move to the next bundle. 4616 i += VF - 1; 4617 Changed = true; 4618 } 4619 } 4620 4621 return Changed; 4622 } 4623 4624 bool SLPVectorizerPass::vectorizeStores(ArrayRef<StoreInst *> Stores, 4625 BoUpSLP &R) { 4626 SetVector<StoreInst *> Heads; 4627 SmallDenseSet<StoreInst *> Tails; 4628 SmallDenseMap<StoreInst *, StoreInst *> ConsecutiveChain; 4629 4630 // We may run into multiple chains that merge into a single chain. We mark the 4631 // stores that we vectorized so that we don't visit the same store twice. 4632 BoUpSLP::ValueSet VectorizedStores; 4633 bool Changed = false; 4634 4635 // Do a quadratic search on all of the given stores in reverse order and find 4636 // all of the pairs of stores that follow each other. 4637 SmallVector<unsigned, 16> IndexQueue; 4638 unsigned E = Stores.size(); 4639 IndexQueue.resize(E - 1); 4640 for (unsigned I = E; I > 0; --I) { 4641 unsigned Idx = I - 1; 4642 // If a store has multiple consecutive store candidates, search Stores 4643 // array according to the sequence: Idx-1, Idx+1, Idx-2, Idx+2, ... 4644 // This is because usually pairing with immediate succeeding or preceding 4645 // candidate create the best chance to find slp vectorization opportunity. 4646 unsigned Offset = 1; 4647 unsigned Cnt = 0; 4648 for (unsigned J = 0; J < E - 1; ++J, ++Offset) { 4649 if (Idx >= Offset) { 4650 IndexQueue[Cnt] = Idx - Offset; 4651 ++Cnt; 4652 } 4653 if (Idx + Offset < E) { 4654 IndexQueue[Cnt] = Idx + Offset; 4655 ++Cnt; 4656 } 4657 } 4658 4659 for (auto K : IndexQueue) { 4660 if (isConsecutiveAccess(Stores[K], Stores[Idx], *DL, *SE)) { 4661 Tails.insert(Stores[Idx]); 4662 Heads.insert(Stores[K]); 4663 ConsecutiveChain[Stores[K]] = Stores[Idx]; 4664 break; 4665 } 4666 } 4667 } 4668 4669 // For stores that start but don't end a link in the chain: 4670 for (auto *SI : llvm::reverse(Heads)) { 4671 if (Tails.count(SI)) 4672 continue; 4673 4674 // We found a store instr that starts a chain. Now follow the chain and try 4675 // to vectorize it. 4676 BoUpSLP::ValueList Operands; 4677 StoreInst *I = SI; 4678 // Collect the chain into a list. 4679 while ((Tails.count(I) || Heads.count(I)) && !VectorizedStores.count(I)) { 4680 Operands.push_back(I); 4681 // Move to the next value in the chain. 4682 I = ConsecutiveChain[I]; 4683 } 4684 4685 // FIXME: Is division-by-2 the correct step? Should we assert that the 4686 // register size is a power-of-2? 4687 for (unsigned Size = R.getMaxVecRegSize(); Size >= R.getMinVecRegSize(); 4688 Size /= 2) { 4689 if (vectorizeStoreChain(Operands, R, Size)) { 4690 // Mark the vectorized stores so that we don't vectorize them again. 4691 VectorizedStores.insert(Operands.begin(), Operands.end()); 4692 Changed = true; 4693 break; 4694 } 4695 } 4696 } 4697 4698 return Changed; 4699 } 4700 4701 void SLPVectorizerPass::collectSeedInstructions(BasicBlock *BB) { 4702 // Initialize the collections. We will make a single pass over the block. 4703 Stores.clear(); 4704 GEPs.clear(); 4705 4706 // Visit the store and getelementptr instructions in BB and organize them in 4707 // Stores and GEPs according to the underlying objects of their pointer 4708 // operands. 4709 for (Instruction &I : *BB) { 4710 // Ignore store instructions that are volatile or have a pointer operand 4711 // that doesn't point to a scalar type. 4712 if (auto *SI = dyn_cast<StoreInst>(&I)) { 4713 if (!SI->isSimple()) 4714 continue; 4715 if (!isValidElementType(SI->getValueOperand()->getType())) 4716 continue; 4717 Stores[GetUnderlyingObject(SI->getPointerOperand(), *DL)].push_back(SI); 4718 } 4719 4720 // Ignore getelementptr instructions that have more than one index, a 4721 // constant index, or a pointer operand that doesn't point to a scalar 4722 // type. 4723 else if (auto *GEP = dyn_cast<GetElementPtrInst>(&I)) { 4724 auto Idx = GEP->idx_begin()->get(); 4725 if (GEP->getNumIndices() > 1 || isa<Constant>(Idx)) 4726 continue; 4727 if (!isValidElementType(Idx->getType())) 4728 continue; 4729 if (GEP->getType()->isVectorTy()) 4730 continue; 4731 GEPs[GetUnderlyingObject(GEP->getPointerOperand(), *DL)].push_back(GEP); 4732 } 4733 } 4734 } 4735 4736 bool SLPVectorizerPass::tryToVectorizePair(Value *A, Value *B, BoUpSLP &R) { 4737 if (!A || !B) 4738 return false; 4739 Value *VL[] = { A, B }; 4740 return tryToVectorizeList(VL, R, /*UserCost=*/0, true); 4741 } 4742 4743 bool SLPVectorizerPass::tryToVectorizeList(ArrayRef<Value *> VL, BoUpSLP &R, 4744 int UserCost, bool AllowReorder) { 4745 if (VL.size() < 2) 4746 return false; 4747 4748 DEBUG(dbgs() << "SLP: Trying to vectorize a list of length = " << VL.size() 4749 << ".\n"); 4750 4751 // Check that all of the parts are scalar instructions of the same type. 4752 Instruction *I0 = dyn_cast<Instruction>(VL[0]); 4753 if (!I0) 4754 return false; 4755 4756 unsigned Opcode0 = I0->getOpcode(); 4757 4758 unsigned Sz = R.getVectorElementSize(I0); 4759 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / Sz); 4760 unsigned MaxVF = std::max<unsigned>(PowerOf2Floor(VL.size()), MinVF); 4761 if (MaxVF < 2) { 4762 R.getORE()->emit([&]() { 4763 return OptimizationRemarkMissed( 4764 SV_NAME, "SmallVF", I0) 4765 << "Cannot SLP vectorize list: vectorization factor " 4766 << "less than 2 is not supported"; 4767 }); 4768 return false; 4769 } 4770 4771 for (Value *V : VL) { 4772 Type *Ty = V->getType(); 4773 if (!isValidElementType(Ty)) { 4774 // NOTE: the following will give user internal llvm type name, which may not be useful 4775 R.getORE()->emit([&]() { 4776 std::string type_str; 4777 llvm::raw_string_ostream rso(type_str); 4778 Ty->print(rso); 4779 return OptimizationRemarkMissed( 4780 SV_NAME, "UnsupportedType", I0) 4781 << "Cannot SLP vectorize list: type " 4782 << rso.str() + " is unsupported by vectorizer"; 4783 }); 4784 return false; 4785 } 4786 Instruction *Inst = dyn_cast<Instruction>(V); 4787 4788 if (!Inst) 4789 return false; 4790 if (Inst->getOpcode() != Opcode0) { 4791 R.getORE()->emit([&]() { 4792 return OptimizationRemarkMissed( 4793 SV_NAME, "InequableTypes", I0) 4794 << "Cannot SLP vectorize list: not all of the " 4795 << "parts of scalar instructions are of the same type: " 4796 << ore::NV("Instruction1Opcode", I0) << " and " 4797 << ore::NV("Instruction2Opcode", Inst); 4798 }); 4799 return false; 4800 } 4801 } 4802 4803 bool Changed = false; 4804 bool CandidateFound = false; 4805 int MinCost = SLPCostThreshold; 4806 4807 // Keep track of values that were deleted by vectorizing in the loop below. 4808 SmallVector<WeakTrackingVH, 8> TrackValues(VL.begin(), VL.end()); 4809 4810 unsigned NextInst = 0, MaxInst = VL.size(); 4811 for (unsigned VF = MaxVF; NextInst + 1 < MaxInst && VF >= MinVF; 4812 VF /= 2) { 4813 // No actual vectorization should happen, if number of parts is the same as 4814 // provided vectorization factor (i.e. the scalar type is used for vector 4815 // code during codegen). 4816 auto *VecTy = VectorType::get(VL[0]->getType(), VF); 4817 if (TTI->getNumberOfParts(VecTy) == VF) 4818 continue; 4819 for (unsigned I = NextInst; I < MaxInst; ++I) { 4820 unsigned OpsWidth = 0; 4821 4822 if (I + VF > MaxInst) 4823 OpsWidth = MaxInst - I; 4824 else 4825 OpsWidth = VF; 4826 4827 if (!isPowerOf2_32(OpsWidth) || OpsWidth < 2) 4828 break; 4829 4830 // Check that a previous iteration of this loop did not delete the Value. 4831 if (hasValueBeenRAUWed(VL, TrackValues, I, OpsWidth)) 4832 continue; 4833 4834 DEBUG(dbgs() << "SLP: Analyzing " << OpsWidth << " operations " 4835 << "\n"); 4836 ArrayRef<Value *> Ops = VL.slice(I, OpsWidth); 4837 4838 R.buildTree(Ops); 4839 // TODO: check if we can allow reordering for more cases. 4840 if (AllowReorder && R.shouldReorder()) { 4841 // Conceptually, there is nothing actually preventing us from trying to 4842 // reorder a larger list. In fact, we do exactly this when vectorizing 4843 // reductions. However, at this point, we only expect to get here when 4844 // there are exactly two operations. 4845 assert(Ops.size() == 2); 4846 Value *ReorderedOps[] = {Ops[1], Ops[0]}; 4847 R.buildTree(ReorderedOps, None); 4848 } 4849 if (R.isTreeTinyAndNotFullyVectorizable()) 4850 continue; 4851 4852 R.computeMinimumValueSizes(); 4853 int Cost = R.getTreeCost() - UserCost; 4854 CandidateFound = true; 4855 MinCost = std::min(MinCost, Cost); 4856 4857 if (Cost < -SLPCostThreshold) { 4858 DEBUG(dbgs() << "SLP: Vectorizing list at cost:" << Cost << ".\n"); 4859 R.getORE()->emit(OptimizationRemark(SV_NAME, "VectorizedList", 4860 cast<Instruction>(Ops[0])) 4861 << "SLP vectorized with cost " << ore::NV("Cost", Cost) 4862 << " and with tree size " 4863 << ore::NV("TreeSize", R.getTreeSize())); 4864 4865 R.vectorizeTree(); 4866 // Move to the next bundle. 4867 I += VF - 1; 4868 NextInst = I + 1; 4869 Changed = true; 4870 } 4871 } 4872 } 4873 4874 if (!Changed && CandidateFound) { 4875 R.getORE()->emit([&]() { 4876 return OptimizationRemarkMissed( 4877 SV_NAME, "NotBeneficial", I0) 4878 << "List vectorization was possible but not beneficial with cost " 4879 << ore::NV("Cost", MinCost) << " >= " 4880 << ore::NV("Treshold", -SLPCostThreshold); 4881 }); 4882 } else if (!Changed) { 4883 R.getORE()->emit([&]() { 4884 return OptimizationRemarkMissed( 4885 SV_NAME, "NotPossible", I0) 4886 << "Cannot SLP vectorize list: vectorization was impossible" 4887 << " with available vectorization factors"; 4888 }); 4889 } 4890 return Changed; 4891 } 4892 4893 bool SLPVectorizerPass::tryToVectorize(Instruction *I, BoUpSLP &R) { 4894 if (!I) 4895 return false; 4896 4897 if (!isa<BinaryOperator>(I) && !isa<CmpInst>(I)) 4898 return false; 4899 4900 Value *P = I->getParent(); 4901 4902 // Vectorize in current basic block only. 4903 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0)); 4904 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1)); 4905 if (!Op0 || !Op1 || Op0->getParent() != P || Op1->getParent() != P) 4906 return false; 4907 4908 // Try to vectorize V. 4909 if (tryToVectorizePair(Op0, Op1, R)) 4910 return true; 4911 4912 auto *A = dyn_cast<BinaryOperator>(Op0); 4913 auto *B = dyn_cast<BinaryOperator>(Op1); 4914 // Try to skip B. 4915 if (B && B->hasOneUse()) { 4916 auto *B0 = dyn_cast<BinaryOperator>(B->getOperand(0)); 4917 auto *B1 = dyn_cast<BinaryOperator>(B->getOperand(1)); 4918 if (B0 && B0->getParent() == P && tryToVectorizePair(A, B0, R)) 4919 return true; 4920 if (B1 && B1->getParent() == P && tryToVectorizePair(A, B1, R)) 4921 return true; 4922 } 4923 4924 // Try to skip A. 4925 if (A && A->hasOneUse()) { 4926 auto *A0 = dyn_cast<BinaryOperator>(A->getOperand(0)); 4927 auto *A1 = dyn_cast<BinaryOperator>(A->getOperand(1)); 4928 if (A0 && A0->getParent() == P && tryToVectorizePair(A0, B, R)) 4929 return true; 4930 if (A1 && A1->getParent() == P && tryToVectorizePair(A1, B, R)) 4931 return true; 4932 } 4933 return false; 4934 } 4935 4936 /// \brief Generate a shuffle mask to be used in a reduction tree. 4937 /// 4938 /// \param VecLen The length of the vector to be reduced. 4939 /// \param NumEltsToRdx The number of elements that should be reduced in the 4940 /// vector. 4941 /// \param IsPairwise Whether the reduction is a pairwise or splitting 4942 /// reduction. A pairwise reduction will generate a mask of 4943 /// <0,2,...> or <1,3,..> while a splitting reduction will generate 4944 /// <2,3, undef,undef> for a vector of 4 and NumElts = 2. 4945 /// \param IsLeft True will generate a mask of even elements, odd otherwise. 4946 static Value *createRdxShuffleMask(unsigned VecLen, unsigned NumEltsToRdx, 4947 bool IsPairwise, bool IsLeft, 4948 IRBuilder<> &Builder) { 4949 assert((IsPairwise || !IsLeft) && "Don't support a <0,1,undef,...> mask"); 4950 4951 SmallVector<Constant *, 32> ShuffleMask( 4952 VecLen, UndefValue::get(Builder.getInt32Ty())); 4953 4954 if (IsPairwise) 4955 // Build a mask of 0, 2, ... (left) or 1, 3, ... (right). 4956 for (unsigned i = 0; i != NumEltsToRdx; ++i) 4957 ShuffleMask[i] = Builder.getInt32(2 * i + !IsLeft); 4958 else 4959 // Move the upper half of the vector to the lower half. 4960 for (unsigned i = 0; i != NumEltsToRdx; ++i) 4961 ShuffleMask[i] = Builder.getInt32(NumEltsToRdx + i); 4962 4963 return ConstantVector::get(ShuffleMask); 4964 } 4965 4966 namespace { 4967 4968 /// Model horizontal reductions. 4969 /// 4970 /// A horizontal reduction is a tree of reduction operations (currently add and 4971 /// fadd) that has operations that can be put into a vector as its leaf. 4972 /// For example, this tree: 4973 /// 4974 /// mul mul mul mul 4975 /// \ / \ / 4976 /// + + 4977 /// \ / 4978 /// + 4979 /// This tree has "mul" as its reduced values and "+" as its reduction 4980 /// operations. A reduction might be feeding into a store or a binary operation 4981 /// feeding a phi. 4982 /// ... 4983 /// \ / 4984 /// + 4985 /// | 4986 /// phi += 4987 /// 4988 /// Or: 4989 /// ... 4990 /// \ / 4991 /// + 4992 /// | 4993 /// *p = 4994 /// 4995 class HorizontalReduction { 4996 using ReductionOpsType = SmallVector<Value *, 16>; 4997 using ReductionOpsListType = SmallVector<ReductionOpsType, 2>; 4998 ReductionOpsListType ReductionOps; 4999 SmallVector<Value *, 32> ReducedVals; 5000 // Use map vector to make stable output. 5001 MapVector<Instruction *, Value *> ExtraArgs; 5002 5003 /// Kind of the reduction data. 5004 enum ReductionKind { 5005 RK_None, /// Not a reduction. 5006 RK_Arithmetic, /// Binary reduction data. 5007 RK_Min, /// Minimum reduction data. 5008 RK_UMin, /// Unsigned minimum reduction data. 5009 RK_Max, /// Maximum reduction data. 5010 RK_UMax, /// Unsigned maximum reduction data. 5011 }; 5012 5013 /// Contains info about operation, like its opcode, left and right operands. 5014 class OperationData { 5015 /// Opcode of the instruction. 5016 unsigned Opcode = 0; 5017 5018 /// Left operand of the reduction operation. 5019 Value *LHS = nullptr; 5020 5021 /// Right operand of the reduction operation. 5022 Value *RHS = nullptr; 5023 5024 /// Kind of the reduction operation. 5025 ReductionKind Kind = RK_None; 5026 5027 /// True if float point min/max reduction has no NaNs. 5028 bool NoNaN = false; 5029 5030 /// Checks if the reduction operation can be vectorized. 5031 bool isVectorizable() const { 5032 return LHS && RHS && 5033 // We currently only support adds && min/max reductions. 5034 ((Kind == RK_Arithmetic && 5035 (Opcode == Instruction::Add || Opcode == Instruction::FAdd)) || 5036 ((Opcode == Instruction::ICmp || Opcode == Instruction::FCmp) && 5037 (Kind == RK_Min || Kind == RK_Max)) || 5038 (Opcode == Instruction::ICmp && 5039 (Kind == RK_UMin || Kind == RK_UMax))); 5040 } 5041 5042 /// Creates reduction operation with the current opcode. 5043 Value *createOp(IRBuilder<> &Builder, const Twine &Name) const { 5044 assert(isVectorizable() && 5045 "Expected add|fadd or min/max reduction operation."); 5046 Value *Cmp; 5047 switch (Kind) { 5048 case RK_Arithmetic: 5049 return Builder.CreateBinOp((Instruction::BinaryOps)Opcode, LHS, RHS, 5050 Name); 5051 case RK_Min: 5052 Cmp = Opcode == Instruction::ICmp ? Builder.CreateICmpSLT(LHS, RHS) 5053 : Builder.CreateFCmpOLT(LHS, RHS); 5054 break; 5055 case RK_Max: 5056 Cmp = Opcode == Instruction::ICmp ? Builder.CreateICmpSGT(LHS, RHS) 5057 : Builder.CreateFCmpOGT(LHS, RHS); 5058 break; 5059 case RK_UMin: 5060 assert(Opcode == Instruction::ICmp && "Expected integer types."); 5061 Cmp = Builder.CreateICmpULT(LHS, RHS); 5062 break; 5063 case RK_UMax: 5064 assert(Opcode == Instruction::ICmp && "Expected integer types."); 5065 Cmp = Builder.CreateICmpUGT(LHS, RHS); 5066 break; 5067 case RK_None: 5068 llvm_unreachable("Unknown reduction operation."); 5069 } 5070 return Builder.CreateSelect(Cmp, LHS, RHS, Name); 5071 } 5072 5073 public: 5074 explicit OperationData() = default; 5075 5076 /// Construction for reduced values. They are identified by opcode only and 5077 /// don't have associated LHS/RHS values. 5078 explicit OperationData(Value *V) { 5079 if (auto *I = dyn_cast<Instruction>(V)) 5080 Opcode = I->getOpcode(); 5081 } 5082 5083 /// Constructor for reduction operations with opcode and its left and 5084 /// right operands. 5085 OperationData(unsigned Opcode, Value *LHS, Value *RHS, ReductionKind Kind, 5086 bool NoNaN = false) 5087 : Opcode(Opcode), LHS(LHS), RHS(RHS), Kind(Kind), NoNaN(NoNaN) { 5088 assert(Kind != RK_None && "One of the reduction operations is expected."); 5089 } 5090 5091 explicit operator bool() const { return Opcode; } 5092 5093 /// Get the index of the first operand. 5094 unsigned getFirstOperandIndex() const { 5095 assert(!!*this && "The opcode is not set."); 5096 switch (Kind) { 5097 case RK_Min: 5098 case RK_UMin: 5099 case RK_Max: 5100 case RK_UMax: 5101 return 1; 5102 case RK_Arithmetic: 5103 case RK_None: 5104 break; 5105 } 5106 return 0; 5107 } 5108 5109 /// Total number of operands in the reduction operation. 5110 unsigned getNumberOfOperands() const { 5111 assert(Kind != RK_None && !!*this && LHS && RHS && 5112 "Expected reduction operation."); 5113 switch (Kind) { 5114 case RK_Arithmetic: 5115 return 2; 5116 case RK_Min: 5117 case RK_UMin: 5118 case RK_Max: 5119 case RK_UMax: 5120 return 3; 5121 case RK_None: 5122 break; 5123 } 5124 llvm_unreachable("Reduction kind is not set"); 5125 } 5126 5127 /// Checks if the operation has the same parent as \p P. 5128 bool hasSameParent(Instruction *I, Value *P, bool IsRedOp) const { 5129 assert(Kind != RK_None && !!*this && LHS && RHS && 5130 "Expected reduction operation."); 5131 if (!IsRedOp) 5132 return I->getParent() == P; 5133 switch (Kind) { 5134 case RK_Arithmetic: 5135 // Arithmetic reduction operation must be used once only. 5136 return I->getParent() == P; 5137 case RK_Min: 5138 case RK_UMin: 5139 case RK_Max: 5140 case RK_UMax: { 5141 // SelectInst must be used twice while the condition op must have single 5142 // use only. 5143 auto *Cmp = cast<Instruction>(cast<SelectInst>(I)->getCondition()); 5144 return I->getParent() == P && Cmp && Cmp->getParent() == P; 5145 } 5146 case RK_None: 5147 break; 5148 } 5149 llvm_unreachable("Reduction kind is not set"); 5150 } 5151 /// Expected number of uses for reduction operations/reduced values. 5152 bool hasRequiredNumberOfUses(Instruction *I, bool IsReductionOp) const { 5153 assert(Kind != RK_None && !!*this && LHS && RHS && 5154 "Expected reduction operation."); 5155 switch (Kind) { 5156 case RK_Arithmetic: 5157 return I->hasOneUse(); 5158 case RK_Min: 5159 case RK_UMin: 5160 case RK_Max: 5161 case RK_UMax: 5162 return I->hasNUses(2) && 5163 (!IsReductionOp || 5164 cast<SelectInst>(I)->getCondition()->hasOneUse()); 5165 case RK_None: 5166 break; 5167 } 5168 llvm_unreachable("Reduction kind is not set"); 5169 } 5170 5171 /// Initializes the list of reduction operations. 5172 void initReductionOps(ReductionOpsListType &ReductionOps) { 5173 assert(Kind != RK_None && !!*this && LHS && RHS && 5174 "Expected reduction operation."); 5175 switch (Kind) { 5176 case RK_Arithmetic: 5177 ReductionOps.assign(1, ReductionOpsType()); 5178 break; 5179 case RK_Min: 5180 case RK_UMin: 5181 case RK_Max: 5182 case RK_UMax: 5183 ReductionOps.assign(2, ReductionOpsType()); 5184 break; 5185 case RK_None: 5186 llvm_unreachable("Reduction kind is not set"); 5187 } 5188 } 5189 /// Add all reduction operations for the reduction instruction \p I. 5190 void addReductionOps(Instruction *I, ReductionOpsListType &ReductionOps) { 5191 assert(Kind != RK_None && !!*this && LHS && RHS && 5192 "Expected reduction operation."); 5193 switch (Kind) { 5194 case RK_Arithmetic: 5195 ReductionOps[0].emplace_back(I); 5196 break; 5197 case RK_Min: 5198 case RK_UMin: 5199 case RK_Max: 5200 case RK_UMax: 5201 ReductionOps[0].emplace_back(cast<SelectInst>(I)->getCondition()); 5202 ReductionOps[1].emplace_back(I); 5203 break; 5204 case RK_None: 5205 llvm_unreachable("Reduction kind is not set"); 5206 } 5207 } 5208 5209 /// Checks if instruction is associative and can be vectorized. 5210 bool isAssociative(Instruction *I) const { 5211 assert(Kind != RK_None && *this && LHS && RHS && 5212 "Expected reduction operation."); 5213 switch (Kind) { 5214 case RK_Arithmetic: 5215 return I->isAssociative(); 5216 case RK_Min: 5217 case RK_Max: 5218 return Opcode == Instruction::ICmp || 5219 cast<Instruction>(I->getOperand(0))->isFast(); 5220 case RK_UMin: 5221 case RK_UMax: 5222 assert(Opcode == Instruction::ICmp && 5223 "Only integer compare operation is expected."); 5224 return true; 5225 case RK_None: 5226 break; 5227 } 5228 llvm_unreachable("Reduction kind is not set"); 5229 } 5230 5231 /// Checks if the reduction operation can be vectorized. 5232 bool isVectorizable(Instruction *I) const { 5233 return isVectorizable() && isAssociative(I); 5234 } 5235 5236 /// Checks if two operation data are both a reduction op or both a reduced 5237 /// value. 5238 bool operator==(const OperationData &OD) { 5239 assert(((Kind != OD.Kind) || ((!LHS == !OD.LHS) && (!RHS == !OD.RHS))) && 5240 "One of the comparing operations is incorrect."); 5241 return this == &OD || (Kind == OD.Kind && Opcode == OD.Opcode); 5242 } 5243 bool operator!=(const OperationData &OD) { return !(*this == OD); } 5244 void clear() { 5245 Opcode = 0; 5246 LHS = nullptr; 5247 RHS = nullptr; 5248 Kind = RK_None; 5249 NoNaN = false; 5250 } 5251 5252 /// Get the opcode of the reduction operation. 5253 unsigned getOpcode() const { 5254 assert(isVectorizable() && "Expected vectorizable operation."); 5255 return Opcode; 5256 } 5257 5258 /// Get kind of reduction data. 5259 ReductionKind getKind() const { return Kind; } 5260 Value *getLHS() const { return LHS; } 5261 Value *getRHS() const { return RHS; } 5262 Type *getConditionType() const { 5263 switch (Kind) { 5264 case RK_Arithmetic: 5265 return nullptr; 5266 case RK_Min: 5267 case RK_Max: 5268 case RK_UMin: 5269 case RK_UMax: 5270 return CmpInst::makeCmpResultType(LHS->getType()); 5271 case RK_None: 5272 break; 5273 } 5274 llvm_unreachable("Reduction kind is not set"); 5275 } 5276 5277 /// Creates reduction operation with the current opcode with the IR flags 5278 /// from \p ReductionOps. 5279 Value *createOp(IRBuilder<> &Builder, const Twine &Name, 5280 const ReductionOpsListType &ReductionOps) const { 5281 assert(isVectorizable() && 5282 "Expected add|fadd or min/max reduction operation."); 5283 auto *Op = createOp(Builder, Name); 5284 switch (Kind) { 5285 case RK_Arithmetic: 5286 propagateIRFlags(Op, ReductionOps[0]); 5287 return Op; 5288 case RK_Min: 5289 case RK_Max: 5290 case RK_UMin: 5291 case RK_UMax: 5292 if (auto *SI = dyn_cast<SelectInst>(Op)) 5293 propagateIRFlags(SI->getCondition(), ReductionOps[0]); 5294 propagateIRFlags(Op, ReductionOps[1]); 5295 return Op; 5296 case RK_None: 5297 break; 5298 } 5299 llvm_unreachable("Unknown reduction operation."); 5300 } 5301 /// Creates reduction operation with the current opcode with the IR flags 5302 /// from \p I. 5303 Value *createOp(IRBuilder<> &Builder, const Twine &Name, 5304 Instruction *I) const { 5305 assert(isVectorizable() && 5306 "Expected add|fadd or min/max reduction operation."); 5307 auto *Op = createOp(Builder, Name); 5308 switch (Kind) { 5309 case RK_Arithmetic: 5310 propagateIRFlags(Op, I); 5311 return Op; 5312 case RK_Min: 5313 case RK_Max: 5314 case RK_UMin: 5315 case RK_UMax: 5316 if (auto *SI = dyn_cast<SelectInst>(Op)) { 5317 propagateIRFlags(SI->getCondition(), 5318 cast<SelectInst>(I)->getCondition()); 5319 } 5320 propagateIRFlags(Op, I); 5321 return Op; 5322 case RK_None: 5323 break; 5324 } 5325 llvm_unreachable("Unknown reduction operation."); 5326 } 5327 5328 TargetTransformInfo::ReductionFlags getFlags() const { 5329 TargetTransformInfo::ReductionFlags Flags; 5330 Flags.NoNaN = NoNaN; 5331 switch (Kind) { 5332 case RK_Arithmetic: 5333 break; 5334 case RK_Min: 5335 Flags.IsSigned = Opcode == Instruction::ICmp; 5336 Flags.IsMaxOp = false; 5337 break; 5338 case RK_Max: 5339 Flags.IsSigned = Opcode == Instruction::ICmp; 5340 Flags.IsMaxOp = true; 5341 break; 5342 case RK_UMin: 5343 Flags.IsSigned = false; 5344 Flags.IsMaxOp = false; 5345 break; 5346 case RK_UMax: 5347 Flags.IsSigned = false; 5348 Flags.IsMaxOp = true; 5349 break; 5350 case RK_None: 5351 llvm_unreachable("Reduction kind is not set"); 5352 } 5353 return Flags; 5354 } 5355 }; 5356 5357 Instruction *ReductionRoot = nullptr; 5358 5359 /// The operation data of the reduction operation. 5360 OperationData ReductionData; 5361 5362 /// The operation data of the values we perform a reduction on. 5363 OperationData ReducedValueData; 5364 5365 /// Should we model this reduction as a pairwise reduction tree or a tree that 5366 /// splits the vector in halves and adds those halves. 5367 bool IsPairwiseReduction = false; 5368 5369 /// Checks if the ParentStackElem.first should be marked as a reduction 5370 /// operation with an extra argument or as extra argument itself. 5371 void markExtraArg(std::pair<Instruction *, unsigned> &ParentStackElem, 5372 Value *ExtraArg) { 5373 if (ExtraArgs.count(ParentStackElem.first)) { 5374 ExtraArgs[ParentStackElem.first] = nullptr; 5375 // We ran into something like: 5376 // ParentStackElem.first = ExtraArgs[ParentStackElem.first] + ExtraArg. 5377 // The whole ParentStackElem.first should be considered as an extra value 5378 // in this case. 5379 // Do not perform analysis of remaining operands of ParentStackElem.first 5380 // instruction, this whole instruction is an extra argument. 5381 ParentStackElem.second = ParentStackElem.first->getNumOperands(); 5382 } else { 5383 // We ran into something like: 5384 // ParentStackElem.first += ... + ExtraArg + ... 5385 ExtraArgs[ParentStackElem.first] = ExtraArg; 5386 } 5387 } 5388 5389 static OperationData getOperationData(Value *V) { 5390 if (!V) 5391 return OperationData(); 5392 5393 Value *LHS; 5394 Value *RHS; 5395 if (m_BinOp(m_Value(LHS), m_Value(RHS)).match(V)) { 5396 return OperationData(cast<BinaryOperator>(V)->getOpcode(), LHS, RHS, 5397 RK_Arithmetic); 5398 } 5399 if (auto *Select = dyn_cast<SelectInst>(V)) { 5400 // Look for a min/max pattern. 5401 if (m_UMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 5402 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMin); 5403 } else if (m_SMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 5404 return OperationData(Instruction::ICmp, LHS, RHS, RK_Min); 5405 } else if (m_OrdFMin(m_Value(LHS), m_Value(RHS)).match(Select) || 5406 m_UnordFMin(m_Value(LHS), m_Value(RHS)).match(Select)) { 5407 return OperationData( 5408 Instruction::FCmp, LHS, RHS, RK_Min, 5409 cast<Instruction>(Select->getCondition())->hasNoNaNs()); 5410 } else if (m_UMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 5411 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMax); 5412 } else if (m_SMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 5413 return OperationData(Instruction::ICmp, LHS, RHS, RK_Max); 5414 } else if (m_OrdFMax(m_Value(LHS), m_Value(RHS)).match(Select) || 5415 m_UnordFMax(m_Value(LHS), m_Value(RHS)).match(Select)) { 5416 return OperationData( 5417 Instruction::FCmp, LHS, RHS, RK_Max, 5418 cast<Instruction>(Select->getCondition())->hasNoNaNs()); 5419 } 5420 } 5421 return OperationData(V); 5422 } 5423 5424 public: 5425 HorizontalReduction() = default; 5426 5427 /// \brief Try to find a reduction tree. 5428 bool matchAssociativeReduction(PHINode *Phi, Instruction *B) { 5429 assert((!Phi || is_contained(Phi->operands(), B)) && 5430 "Thi phi needs to use the binary operator"); 5431 5432 ReductionData = getOperationData(B); 5433 5434 // We could have a initial reductions that is not an add. 5435 // r *= v1 + v2 + v3 + v4 5436 // In such a case start looking for a tree rooted in the first '+'. 5437 if (Phi) { 5438 if (ReductionData.getLHS() == Phi) { 5439 Phi = nullptr; 5440 B = dyn_cast<Instruction>(ReductionData.getRHS()); 5441 ReductionData = getOperationData(B); 5442 } else if (ReductionData.getRHS() == Phi) { 5443 Phi = nullptr; 5444 B = dyn_cast<Instruction>(ReductionData.getLHS()); 5445 ReductionData = getOperationData(B); 5446 } 5447 } 5448 5449 if (!ReductionData.isVectorizable(B)) 5450 return false; 5451 5452 Type *Ty = B->getType(); 5453 if (!isValidElementType(Ty)) 5454 return false; 5455 5456 ReducedValueData.clear(); 5457 ReductionRoot = B; 5458 5459 // Post order traverse the reduction tree starting at B. We only handle true 5460 // trees containing only binary operators. 5461 SmallVector<std::pair<Instruction *, unsigned>, 32> Stack; 5462 Stack.push_back(std::make_pair(B, ReductionData.getFirstOperandIndex())); 5463 ReductionData.initReductionOps(ReductionOps); 5464 while (!Stack.empty()) { 5465 Instruction *TreeN = Stack.back().first; 5466 unsigned EdgeToVist = Stack.back().second++; 5467 OperationData OpData = getOperationData(TreeN); 5468 bool IsReducedValue = OpData != ReductionData; 5469 5470 // Postorder vist. 5471 if (IsReducedValue || EdgeToVist == OpData.getNumberOfOperands()) { 5472 if (IsReducedValue) 5473 ReducedVals.push_back(TreeN); 5474 else { 5475 auto I = ExtraArgs.find(TreeN); 5476 if (I != ExtraArgs.end() && !I->second) { 5477 // Check if TreeN is an extra argument of its parent operation. 5478 if (Stack.size() <= 1) { 5479 // TreeN can't be an extra argument as it is a root reduction 5480 // operation. 5481 return false; 5482 } 5483 // Yes, TreeN is an extra argument, do not add it to a list of 5484 // reduction operations. 5485 // Stack[Stack.size() - 2] always points to the parent operation. 5486 markExtraArg(Stack[Stack.size() - 2], TreeN); 5487 ExtraArgs.erase(TreeN); 5488 } else 5489 ReductionData.addReductionOps(TreeN, ReductionOps); 5490 } 5491 // Retract. 5492 Stack.pop_back(); 5493 continue; 5494 } 5495 5496 // Visit left or right. 5497 Value *NextV = TreeN->getOperand(EdgeToVist); 5498 if (NextV != Phi) { 5499 auto *I = dyn_cast<Instruction>(NextV); 5500 OpData = getOperationData(I); 5501 // Continue analysis if the next operand is a reduction operation or 5502 // (possibly) a reduced value. If the reduced value opcode is not set, 5503 // the first met operation != reduction operation is considered as the 5504 // reduced value class. 5505 if (I && (!ReducedValueData || OpData == ReducedValueData || 5506 OpData == ReductionData)) { 5507 const bool IsReductionOperation = OpData == ReductionData; 5508 // Only handle trees in the current basic block. 5509 if (!ReductionData.hasSameParent(I, B->getParent(), 5510 IsReductionOperation)) { 5511 // I is an extra argument for TreeN (its parent operation). 5512 markExtraArg(Stack.back(), I); 5513 continue; 5514 } 5515 5516 // Each tree node needs to have minimal number of users except for the 5517 // ultimate reduction. 5518 if (!ReductionData.hasRequiredNumberOfUses(I, 5519 OpData == ReductionData) && 5520 I != B) { 5521 // I is an extra argument for TreeN (its parent operation). 5522 markExtraArg(Stack.back(), I); 5523 continue; 5524 } 5525 5526 if (IsReductionOperation) { 5527 // We need to be able to reassociate the reduction operations. 5528 if (!OpData.isAssociative(I)) { 5529 // I is an extra argument for TreeN (its parent operation). 5530 markExtraArg(Stack.back(), I); 5531 continue; 5532 } 5533 } else if (ReducedValueData && 5534 ReducedValueData != OpData) { 5535 // Make sure that the opcodes of the operations that we are going to 5536 // reduce match. 5537 // I is an extra argument for TreeN (its parent operation). 5538 markExtraArg(Stack.back(), I); 5539 continue; 5540 } else if (!ReducedValueData) 5541 ReducedValueData = OpData; 5542 5543 Stack.push_back(std::make_pair(I, OpData.getFirstOperandIndex())); 5544 continue; 5545 } 5546 } 5547 // NextV is an extra argument for TreeN (its parent operation). 5548 markExtraArg(Stack.back(), NextV); 5549 } 5550 return true; 5551 } 5552 5553 /// \brief Attempt to vectorize the tree found by 5554 /// matchAssociativeReduction. 5555 bool tryToReduce(BoUpSLP &V, TargetTransformInfo *TTI) { 5556 if (ReducedVals.empty()) 5557 return false; 5558 5559 // If there is a sufficient number of reduction values, reduce 5560 // to a nearby power-of-2. Can safely generate oversized 5561 // vectors and rely on the backend to split them to legal sizes. 5562 unsigned NumReducedVals = ReducedVals.size(); 5563 if (NumReducedVals < 4) 5564 return false; 5565 5566 unsigned ReduxWidth = PowerOf2Floor(NumReducedVals); 5567 5568 Value *VectorizedTree = nullptr; 5569 IRBuilder<> Builder(ReductionRoot); 5570 FastMathFlags Unsafe; 5571 Unsafe.setFast(); 5572 Builder.setFastMathFlags(Unsafe); 5573 unsigned i = 0; 5574 5575 BoUpSLP::ExtraValueToDebugLocsMap ExternallyUsedValues; 5576 // The same extra argument may be used several time, so log each attempt 5577 // to use it. 5578 for (auto &Pair : ExtraArgs) 5579 ExternallyUsedValues[Pair.second].push_back(Pair.first); 5580 SmallVector<Value *, 16> IgnoreList; 5581 for (auto &V : ReductionOps) 5582 IgnoreList.append(V.begin(), V.end()); 5583 while (i < NumReducedVals - ReduxWidth + 1 && ReduxWidth > 2) { 5584 auto VL = makeArrayRef(&ReducedVals[i], ReduxWidth); 5585 V.buildTree(VL, ExternallyUsedValues, IgnoreList); 5586 if (V.shouldReorder()) { 5587 SmallVector<Value *, 8> Reversed(VL.rbegin(), VL.rend()); 5588 V.buildTree(Reversed, ExternallyUsedValues, IgnoreList); 5589 } 5590 if (V.isTreeTinyAndNotFullyVectorizable()) 5591 break; 5592 5593 V.computeMinimumValueSizes(); 5594 5595 // Estimate cost. 5596 int Cost = 5597 V.getTreeCost() + getReductionCost(TTI, ReducedVals[i], ReduxWidth); 5598 if (Cost >= -SLPCostThreshold) { 5599 V.getORE()->emit([&]() { 5600 return OptimizationRemarkMissed( 5601 SV_NAME, "HorSLPNotBeneficial", cast<Instruction>(VL[0])) 5602 << "Vectorizing horizontal reduction is possible" 5603 << "but not beneficial with cost " 5604 << ore::NV("Cost", Cost) << " and threshold " 5605 << ore::NV("Threshold", -SLPCostThreshold); 5606 }); 5607 break; 5608 } 5609 5610 DEBUG(dbgs() << "SLP: Vectorizing horizontal reduction at cost:" << Cost 5611 << ". (HorRdx)\n"); 5612 V.getORE()->emit([&]() { 5613 return OptimizationRemark( 5614 SV_NAME, "VectorizedHorizontalReduction", cast<Instruction>(VL[0])) 5615 << "Vectorized horizontal reduction with cost " 5616 << ore::NV("Cost", Cost) << " and with tree size " 5617 << ore::NV("TreeSize", V.getTreeSize()); 5618 }); 5619 5620 // Vectorize a tree. 5621 DebugLoc Loc = cast<Instruction>(ReducedVals[i])->getDebugLoc(); 5622 Value *VectorizedRoot = V.vectorizeTree(ExternallyUsedValues); 5623 5624 // Emit a reduction. 5625 Value *ReducedSubTree = 5626 emitReduction(VectorizedRoot, Builder, ReduxWidth, TTI); 5627 if (VectorizedTree) { 5628 Builder.SetCurrentDebugLocation(Loc); 5629 OperationData VectReductionData(ReductionData.getOpcode(), 5630 VectorizedTree, ReducedSubTree, 5631 ReductionData.getKind()); 5632 VectorizedTree = 5633 VectReductionData.createOp(Builder, "op.rdx", ReductionOps); 5634 } else 5635 VectorizedTree = ReducedSubTree; 5636 i += ReduxWidth; 5637 ReduxWidth = PowerOf2Floor(NumReducedVals - i); 5638 } 5639 5640 if (VectorizedTree) { 5641 // Finish the reduction. 5642 for (; i < NumReducedVals; ++i) { 5643 auto *I = cast<Instruction>(ReducedVals[i]); 5644 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 5645 OperationData VectReductionData(ReductionData.getOpcode(), 5646 VectorizedTree, I, 5647 ReductionData.getKind()); 5648 VectorizedTree = VectReductionData.createOp(Builder, "", ReductionOps); 5649 } 5650 for (auto &Pair : ExternallyUsedValues) { 5651 assert(!Pair.second.empty() && 5652 "At least one DebugLoc must be inserted"); 5653 // Add each externally used value to the final reduction. 5654 for (auto *I : Pair.second) { 5655 Builder.SetCurrentDebugLocation(I->getDebugLoc()); 5656 OperationData VectReductionData(ReductionData.getOpcode(), 5657 VectorizedTree, Pair.first, 5658 ReductionData.getKind()); 5659 VectorizedTree = VectReductionData.createOp(Builder, "op.extra", I); 5660 } 5661 } 5662 // Update users. 5663 ReductionRoot->replaceAllUsesWith(VectorizedTree); 5664 } 5665 return VectorizedTree != nullptr; 5666 } 5667 5668 unsigned numReductionValues() const { 5669 return ReducedVals.size(); 5670 } 5671 5672 private: 5673 /// \brief Calculate the cost of a reduction. 5674 int getReductionCost(TargetTransformInfo *TTI, Value *FirstReducedVal, 5675 unsigned ReduxWidth) { 5676 Type *ScalarTy = FirstReducedVal->getType(); 5677 Type *VecTy = VectorType::get(ScalarTy, ReduxWidth); 5678 5679 int PairwiseRdxCost; 5680 int SplittingRdxCost; 5681 switch (ReductionData.getKind()) { 5682 case RK_Arithmetic: 5683 PairwiseRdxCost = 5684 TTI->getArithmeticReductionCost(ReductionData.getOpcode(), VecTy, 5685 /*IsPairwiseForm=*/true); 5686 SplittingRdxCost = 5687 TTI->getArithmeticReductionCost(ReductionData.getOpcode(), VecTy, 5688 /*IsPairwiseForm=*/false); 5689 break; 5690 case RK_Min: 5691 case RK_Max: 5692 case RK_UMin: 5693 case RK_UMax: { 5694 Type *VecCondTy = CmpInst::makeCmpResultType(VecTy); 5695 bool IsUnsigned = ReductionData.getKind() == RK_UMin || 5696 ReductionData.getKind() == RK_UMax; 5697 PairwiseRdxCost = 5698 TTI->getMinMaxReductionCost(VecTy, VecCondTy, 5699 /*IsPairwiseForm=*/true, IsUnsigned); 5700 SplittingRdxCost = 5701 TTI->getMinMaxReductionCost(VecTy, VecCondTy, 5702 /*IsPairwiseForm=*/false, IsUnsigned); 5703 break; 5704 } 5705 case RK_None: 5706 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 5707 } 5708 5709 IsPairwiseReduction = PairwiseRdxCost < SplittingRdxCost; 5710 int VecReduxCost = IsPairwiseReduction ? PairwiseRdxCost : SplittingRdxCost; 5711 5712 int ScalarReduxCost; 5713 switch (ReductionData.getKind()) { 5714 case RK_Arithmetic: 5715 ScalarReduxCost = 5716 TTI->getArithmeticInstrCost(ReductionData.getOpcode(), ScalarTy); 5717 break; 5718 case RK_Min: 5719 case RK_Max: 5720 case RK_UMin: 5721 case RK_UMax: 5722 ScalarReduxCost = 5723 TTI->getCmpSelInstrCost(ReductionData.getOpcode(), ScalarTy) + 5724 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, 5725 CmpInst::makeCmpResultType(ScalarTy)); 5726 break; 5727 case RK_None: 5728 llvm_unreachable("Expected arithmetic or min/max reduction operation"); 5729 } 5730 ScalarReduxCost *= (ReduxWidth - 1); 5731 5732 DEBUG(dbgs() << "SLP: Adding cost " << VecReduxCost - ScalarReduxCost 5733 << " for reduction that starts with " << *FirstReducedVal 5734 << " (It is a " 5735 << (IsPairwiseReduction ? "pairwise" : "splitting") 5736 << " reduction)\n"); 5737 5738 return VecReduxCost - ScalarReduxCost; 5739 } 5740 5741 /// \brief Emit a horizontal reduction of the vectorized value. 5742 Value *emitReduction(Value *VectorizedValue, IRBuilder<> &Builder, 5743 unsigned ReduxWidth, const TargetTransformInfo *TTI) { 5744 assert(VectorizedValue && "Need to have a vectorized tree node"); 5745 assert(isPowerOf2_32(ReduxWidth) && 5746 "We only handle power-of-two reductions for now"); 5747 5748 if (!IsPairwiseReduction) 5749 return createSimpleTargetReduction( 5750 Builder, TTI, ReductionData.getOpcode(), VectorizedValue, 5751 ReductionData.getFlags(), ReductionOps.back()); 5752 5753 Value *TmpVec = VectorizedValue; 5754 for (unsigned i = ReduxWidth / 2; i != 0; i >>= 1) { 5755 Value *LeftMask = 5756 createRdxShuffleMask(ReduxWidth, i, true, true, Builder); 5757 Value *RightMask = 5758 createRdxShuffleMask(ReduxWidth, i, true, false, Builder); 5759 5760 Value *LeftShuf = Builder.CreateShuffleVector( 5761 TmpVec, UndefValue::get(TmpVec->getType()), LeftMask, "rdx.shuf.l"); 5762 Value *RightShuf = Builder.CreateShuffleVector( 5763 TmpVec, UndefValue::get(TmpVec->getType()), (RightMask), 5764 "rdx.shuf.r"); 5765 OperationData VectReductionData(ReductionData.getOpcode(), LeftShuf, 5766 RightShuf, ReductionData.getKind()); 5767 TmpVec = VectReductionData.createOp(Builder, "op.rdx", ReductionOps); 5768 } 5769 5770 // The result is in the first element of the vector. 5771 return Builder.CreateExtractElement(TmpVec, Builder.getInt32(0)); 5772 } 5773 }; 5774 5775 } // end anonymous namespace 5776 5777 /// \brief Recognize construction of vectors like 5778 /// %ra = insertelement <4 x float> undef, float %s0, i32 0 5779 /// %rb = insertelement <4 x float> %ra, float %s1, i32 1 5780 /// %rc = insertelement <4 x float> %rb, float %s2, i32 2 5781 /// %rd = insertelement <4 x float> %rc, float %s3, i32 3 5782 /// starting from the last insertelement instruction. 5783 /// 5784 /// Returns true if it matches 5785 static bool findBuildVector(InsertElementInst *LastInsertElem, 5786 TargetTransformInfo *TTI, 5787 SmallVectorImpl<Value *> &BuildVectorOpds, 5788 int &UserCost) { 5789 UserCost = 0; 5790 Value *V = nullptr; 5791 do { 5792 if (auto *CI = dyn_cast<ConstantInt>(LastInsertElem->getOperand(2))) { 5793 UserCost += TTI->getVectorInstrCost(Instruction::InsertElement, 5794 LastInsertElem->getType(), 5795 CI->getZExtValue()); 5796 } 5797 BuildVectorOpds.push_back(LastInsertElem->getOperand(1)); 5798 V = LastInsertElem->getOperand(0); 5799 if (isa<UndefValue>(V)) 5800 break; 5801 LastInsertElem = dyn_cast<InsertElementInst>(V); 5802 if (!LastInsertElem || !LastInsertElem->hasOneUse()) 5803 return false; 5804 } while (true); 5805 std::reverse(BuildVectorOpds.begin(), BuildVectorOpds.end()); 5806 return true; 5807 } 5808 5809 /// \brief Like findBuildVector, but looks for construction of aggregate. 5810 /// 5811 /// \return true if it matches. 5812 static bool findBuildAggregate(InsertValueInst *IV, 5813 SmallVectorImpl<Value *> &BuildVectorOpds) { 5814 Value *V; 5815 do { 5816 BuildVectorOpds.push_back(IV->getInsertedValueOperand()); 5817 V = IV->getAggregateOperand(); 5818 if (isa<UndefValue>(V)) 5819 break; 5820 IV = dyn_cast<InsertValueInst>(V); 5821 if (!IV || !IV->hasOneUse()) 5822 return false; 5823 } while (true); 5824 std::reverse(BuildVectorOpds.begin(), BuildVectorOpds.end()); 5825 return true; 5826 } 5827 5828 static bool PhiTypeSorterFunc(Value *V, Value *V2) { 5829 return V->getType() < V2->getType(); 5830 } 5831 5832 /// \brief Try and get a reduction value from a phi node. 5833 /// 5834 /// Given a phi node \p P in a block \p ParentBB, consider possible reductions 5835 /// if they come from either \p ParentBB or a containing loop latch. 5836 /// 5837 /// \returns A candidate reduction value if possible, or \code nullptr \endcode 5838 /// if not possible. 5839 static Value *getReductionValue(const DominatorTree *DT, PHINode *P, 5840 BasicBlock *ParentBB, LoopInfo *LI) { 5841 // There are situations where the reduction value is not dominated by the 5842 // reduction phi. Vectorizing such cases has been reported to cause 5843 // miscompiles. See PR25787. 5844 auto DominatedReduxValue = [&](Value *R) { 5845 return ( 5846 dyn_cast<Instruction>(R) && 5847 DT->dominates(P->getParent(), dyn_cast<Instruction>(R)->getParent())); 5848 }; 5849 5850 Value *Rdx = nullptr; 5851 5852 // Return the incoming value if it comes from the same BB as the phi node. 5853 if (P->getIncomingBlock(0) == ParentBB) { 5854 Rdx = P->getIncomingValue(0); 5855 } else if (P->getIncomingBlock(1) == ParentBB) { 5856 Rdx = P->getIncomingValue(1); 5857 } 5858 5859 if (Rdx && DominatedReduxValue(Rdx)) 5860 return Rdx; 5861 5862 // Otherwise, check whether we have a loop latch to look at. 5863 Loop *BBL = LI->getLoopFor(ParentBB); 5864 if (!BBL) 5865 return nullptr; 5866 BasicBlock *BBLatch = BBL->getLoopLatch(); 5867 if (!BBLatch) 5868 return nullptr; 5869 5870 // There is a loop latch, return the incoming value if it comes from 5871 // that. This reduction pattern occasionally turns up. 5872 if (P->getIncomingBlock(0) == BBLatch) { 5873 Rdx = P->getIncomingValue(0); 5874 } else if (P->getIncomingBlock(1) == BBLatch) { 5875 Rdx = P->getIncomingValue(1); 5876 } 5877 5878 if (Rdx && DominatedReduxValue(Rdx)) 5879 return Rdx; 5880 5881 return nullptr; 5882 } 5883 5884 /// Attempt to reduce a horizontal reduction. 5885 /// If it is legal to match a horizontal reduction feeding the phi node \a P 5886 /// with reduction operators \a Root (or one of its operands) in a basic block 5887 /// \a BB, then check if it can be done. If horizontal reduction is not found 5888 /// and root instruction is a binary operation, vectorization of the operands is 5889 /// attempted. 5890 /// \returns true if a horizontal reduction was matched and reduced or operands 5891 /// of one of the binary instruction were vectorized. 5892 /// \returns false if a horizontal reduction was not matched (or not possible) 5893 /// or no vectorization of any binary operation feeding \a Root instruction was 5894 /// performed. 5895 static bool tryToVectorizeHorReductionOrInstOperands( 5896 PHINode *P, Instruction *Root, BasicBlock *BB, BoUpSLP &R, 5897 TargetTransformInfo *TTI, 5898 const function_ref<bool(Instruction *, BoUpSLP &)> Vectorize) { 5899 if (!ShouldVectorizeHor) 5900 return false; 5901 5902 if (!Root) 5903 return false; 5904 5905 if (Root->getParent() != BB || isa<PHINode>(Root)) 5906 return false; 5907 // Start analysis starting from Root instruction. If horizontal reduction is 5908 // found, try to vectorize it. If it is not a horizontal reduction or 5909 // vectorization is not possible or not effective, and currently analyzed 5910 // instruction is a binary operation, try to vectorize the operands, using 5911 // pre-order DFS traversal order. If the operands were not vectorized, repeat 5912 // the same procedure considering each operand as a possible root of the 5913 // horizontal reduction. 5914 // Interrupt the process if the Root instruction itself was vectorized or all 5915 // sub-trees not higher that RecursionMaxDepth were analyzed/vectorized. 5916 SmallVector<std::pair<WeakTrackingVH, unsigned>, 8> Stack(1, {Root, 0}); 5917 SmallSet<Value *, 8> VisitedInstrs; 5918 bool Res = false; 5919 while (!Stack.empty()) { 5920 Value *V; 5921 unsigned Level; 5922 std::tie(V, Level) = Stack.pop_back_val(); 5923 if (!V) 5924 continue; 5925 auto *Inst = dyn_cast<Instruction>(V); 5926 if (!Inst) 5927 continue; 5928 auto *BI = dyn_cast<BinaryOperator>(Inst); 5929 auto *SI = dyn_cast<SelectInst>(Inst); 5930 if (BI || SI) { 5931 HorizontalReduction HorRdx; 5932 if (HorRdx.matchAssociativeReduction(P, Inst)) { 5933 if (HorRdx.tryToReduce(R, TTI)) { 5934 Res = true; 5935 // Set P to nullptr to avoid re-analysis of phi node in 5936 // matchAssociativeReduction function unless this is the root node. 5937 P = nullptr; 5938 continue; 5939 } 5940 } 5941 if (P && BI) { 5942 Inst = dyn_cast<Instruction>(BI->getOperand(0)); 5943 if (Inst == P) 5944 Inst = dyn_cast<Instruction>(BI->getOperand(1)); 5945 if (!Inst) { 5946 // Set P to nullptr to avoid re-analysis of phi node in 5947 // matchAssociativeReduction function unless this is the root node. 5948 P = nullptr; 5949 continue; 5950 } 5951 } 5952 } 5953 // Set P to nullptr to avoid re-analysis of phi node in 5954 // matchAssociativeReduction function unless this is the root node. 5955 P = nullptr; 5956 if (Vectorize(Inst, R)) { 5957 Res = true; 5958 continue; 5959 } 5960 5961 // Try to vectorize operands. 5962 // Continue analysis for the instruction from the same basic block only to 5963 // save compile time. 5964 if (++Level < RecursionMaxDepth) 5965 for (auto *Op : Inst->operand_values()) 5966 if (VisitedInstrs.insert(Op).second) 5967 if (auto *I = dyn_cast<Instruction>(Op)) 5968 if (!isa<PHINode>(I) && I->getParent() == BB) 5969 Stack.emplace_back(Op, Level); 5970 } 5971 return Res; 5972 } 5973 5974 bool SLPVectorizerPass::vectorizeRootInstruction(PHINode *P, Value *V, 5975 BasicBlock *BB, BoUpSLP &R, 5976 TargetTransformInfo *TTI) { 5977 if (!V) 5978 return false; 5979 auto *I = dyn_cast<Instruction>(V); 5980 if (!I) 5981 return false; 5982 5983 if (!isa<BinaryOperator>(I)) 5984 P = nullptr; 5985 // Try to match and vectorize a horizontal reduction. 5986 auto &&ExtraVectorization = [this](Instruction *I, BoUpSLP &R) -> bool { 5987 return tryToVectorize(I, R); 5988 }; 5989 return tryToVectorizeHorReductionOrInstOperands(P, I, BB, R, TTI, 5990 ExtraVectorization); 5991 } 5992 5993 bool SLPVectorizerPass::vectorizeInsertValueInst(InsertValueInst *IVI, 5994 BasicBlock *BB, BoUpSLP &R) { 5995 const DataLayout &DL = BB->getModule()->getDataLayout(); 5996 if (!R.canMapToVector(IVI->getType(), DL)) 5997 return false; 5998 5999 SmallVector<Value *, 16> BuildVectorOpds; 6000 if (!findBuildAggregate(IVI, BuildVectorOpds)) 6001 return false; 6002 6003 DEBUG(dbgs() << "SLP: array mappable to vector: " << *IVI << "\n"); 6004 // Aggregate value is unlikely to be processed in vector register, we need to 6005 // extract scalars into scalar registers, so NeedExtraction is set true. 6006 return tryToVectorizeList(BuildVectorOpds, R); 6007 } 6008 6009 bool SLPVectorizerPass::vectorizeInsertElementInst(InsertElementInst *IEI, 6010 BasicBlock *BB, BoUpSLP &R) { 6011 int UserCost; 6012 SmallVector<Value *, 16> BuildVectorOpds; 6013 if (!findBuildVector(IEI, TTI, BuildVectorOpds, UserCost) || 6014 (llvm::all_of(BuildVectorOpds, 6015 [](Value *V) { return isa<ExtractElementInst>(V); }) && 6016 isShuffle(BuildVectorOpds))) 6017 return false; 6018 6019 // Vectorize starting with the build vector operands ignoring the BuildVector 6020 // instructions for the purpose of scheduling and user extraction. 6021 return tryToVectorizeList(BuildVectorOpds, R, UserCost); 6022 } 6023 6024 bool SLPVectorizerPass::vectorizeCmpInst(CmpInst *CI, BasicBlock *BB, 6025 BoUpSLP &R) { 6026 if (tryToVectorizePair(CI->getOperand(0), CI->getOperand(1), R)) 6027 return true; 6028 6029 bool OpsChanged = false; 6030 for (int Idx = 0; Idx < 2; ++Idx) { 6031 OpsChanged |= 6032 vectorizeRootInstruction(nullptr, CI->getOperand(Idx), BB, R, TTI); 6033 } 6034 return OpsChanged; 6035 } 6036 6037 bool SLPVectorizerPass::vectorizeSimpleInstructions( 6038 SmallVectorImpl<WeakVH> &Instructions, BasicBlock *BB, BoUpSLP &R) { 6039 bool OpsChanged = false; 6040 for (auto &VH : reverse(Instructions)) { 6041 auto *I = dyn_cast_or_null<Instruction>(VH); 6042 if (!I) 6043 continue; 6044 if (auto *LastInsertValue = dyn_cast<InsertValueInst>(I)) 6045 OpsChanged |= vectorizeInsertValueInst(LastInsertValue, BB, R); 6046 else if (auto *LastInsertElem = dyn_cast<InsertElementInst>(I)) 6047 OpsChanged |= vectorizeInsertElementInst(LastInsertElem, BB, R); 6048 else if (auto *CI = dyn_cast<CmpInst>(I)) 6049 OpsChanged |= vectorizeCmpInst(CI, BB, R); 6050 } 6051 Instructions.clear(); 6052 return OpsChanged; 6053 } 6054 6055 bool SLPVectorizerPass::vectorizeChainsInBlock(BasicBlock *BB, BoUpSLP &R) { 6056 bool Changed = false; 6057 SmallVector<Value *, 4> Incoming; 6058 SmallSet<Value *, 16> VisitedInstrs; 6059 6060 bool HaveVectorizedPhiNodes = true; 6061 while (HaveVectorizedPhiNodes) { 6062 HaveVectorizedPhiNodes = false; 6063 6064 // Collect the incoming values from the PHIs. 6065 Incoming.clear(); 6066 for (Instruction &I : *BB) { 6067 PHINode *P = dyn_cast<PHINode>(&I); 6068 if (!P) 6069 break; 6070 6071 if (!VisitedInstrs.count(P)) 6072 Incoming.push_back(P); 6073 } 6074 6075 // Sort by type. 6076 std::stable_sort(Incoming.begin(), Incoming.end(), PhiTypeSorterFunc); 6077 6078 // Try to vectorize elements base on their type. 6079 for (SmallVector<Value *, 4>::iterator IncIt = Incoming.begin(), 6080 E = Incoming.end(); 6081 IncIt != E;) { 6082 6083 // Look for the next elements with the same type. 6084 SmallVector<Value *, 4>::iterator SameTypeIt = IncIt; 6085 while (SameTypeIt != E && 6086 (*SameTypeIt)->getType() == (*IncIt)->getType()) { 6087 VisitedInstrs.insert(*SameTypeIt); 6088 ++SameTypeIt; 6089 } 6090 6091 // Try to vectorize them. 6092 unsigned NumElts = (SameTypeIt - IncIt); 6093 DEBUG(errs() << "SLP: Trying to vectorize starting at PHIs (" << NumElts << ")\n"); 6094 // The order in which the phi nodes appear in the program does not matter. 6095 // So allow tryToVectorizeList to reorder them if it is beneficial. This 6096 // is done when there are exactly two elements since tryToVectorizeList 6097 // asserts that there are only two values when AllowReorder is true. 6098 bool AllowReorder = NumElts == 2; 6099 if (NumElts > 1 && tryToVectorizeList(makeArrayRef(IncIt, NumElts), R, 6100 /*UserCost=*/0, AllowReorder)) { 6101 // Success start over because instructions might have been changed. 6102 HaveVectorizedPhiNodes = true; 6103 Changed = true; 6104 break; 6105 } 6106 6107 // Start over at the next instruction of a different type (or the end). 6108 IncIt = SameTypeIt; 6109 } 6110 } 6111 6112 VisitedInstrs.clear(); 6113 6114 SmallVector<WeakVH, 8> PostProcessInstructions; 6115 SmallDenseSet<Instruction *, 4> KeyNodes; 6116 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; it++) { 6117 // We may go through BB multiple times so skip the one we have checked. 6118 if (!VisitedInstrs.insert(&*it).second) { 6119 if (it->use_empty() && KeyNodes.count(&*it) > 0 && 6120 vectorizeSimpleInstructions(PostProcessInstructions, BB, R)) { 6121 // We would like to start over since some instructions are deleted 6122 // and the iterator may become invalid value. 6123 Changed = true; 6124 it = BB->begin(); 6125 e = BB->end(); 6126 } 6127 continue; 6128 } 6129 6130 if (isa<DbgInfoIntrinsic>(it)) 6131 continue; 6132 6133 // Try to vectorize reductions that use PHINodes. 6134 if (PHINode *P = dyn_cast<PHINode>(it)) { 6135 // Check that the PHI is a reduction PHI. 6136 if (P->getNumIncomingValues() != 2) 6137 return Changed; 6138 6139 // Try to match and vectorize a horizontal reduction. 6140 if (vectorizeRootInstruction(P, getReductionValue(DT, P, BB, LI), BB, R, 6141 TTI)) { 6142 Changed = true; 6143 it = BB->begin(); 6144 e = BB->end(); 6145 continue; 6146 } 6147 continue; 6148 } 6149 6150 // Ran into an instruction without users, like terminator, or function call 6151 // with ignored return value, store. Ignore unused instructions (basing on 6152 // instruction type, except for CallInst and InvokeInst). 6153 if (it->use_empty() && (it->getType()->isVoidTy() || isa<CallInst>(it) || 6154 isa<InvokeInst>(it))) { 6155 KeyNodes.insert(&*it); 6156 bool OpsChanged = false; 6157 if (ShouldStartVectorizeHorAtStore || !isa<StoreInst>(it)) { 6158 for (auto *V : it->operand_values()) { 6159 // Try to match and vectorize a horizontal reduction. 6160 OpsChanged |= vectorizeRootInstruction(nullptr, V, BB, R, TTI); 6161 } 6162 } 6163 // Start vectorization of post-process list of instructions from the 6164 // top-tree instructions to try to vectorize as many instructions as 6165 // possible. 6166 OpsChanged |= vectorizeSimpleInstructions(PostProcessInstructions, BB, R); 6167 if (OpsChanged) { 6168 // We would like to start over since some instructions are deleted 6169 // and the iterator may become invalid value. 6170 Changed = true; 6171 it = BB->begin(); 6172 e = BB->end(); 6173 continue; 6174 } 6175 } 6176 6177 if (isa<InsertElementInst>(it) || isa<CmpInst>(it) || 6178 isa<InsertValueInst>(it)) 6179 PostProcessInstructions.push_back(&*it); 6180 6181 } 6182 6183 return Changed; 6184 } 6185 6186 bool SLPVectorizerPass::vectorizeGEPIndices(BasicBlock *BB, BoUpSLP &R) { 6187 auto Changed = false; 6188 for (auto &Entry : GEPs) { 6189 // If the getelementptr list has fewer than two elements, there's nothing 6190 // to do. 6191 if (Entry.second.size() < 2) 6192 continue; 6193 6194 DEBUG(dbgs() << "SLP: Analyzing a getelementptr list of length " 6195 << Entry.second.size() << ".\n"); 6196 6197 // We process the getelementptr list in chunks of 16 (like we do for 6198 // stores) to minimize compile-time. 6199 for (unsigned BI = 0, BE = Entry.second.size(); BI < BE; BI += 16) { 6200 auto Len = std::min<unsigned>(BE - BI, 16); 6201 auto GEPList = makeArrayRef(&Entry.second[BI], Len); 6202 6203 // Initialize a set a candidate getelementptrs. Note that we use a 6204 // SetVector here to preserve program order. If the index computations 6205 // are vectorizable and begin with loads, we want to minimize the chance 6206 // of having to reorder them later. 6207 SetVector<Value *> Candidates(GEPList.begin(), GEPList.end()); 6208 6209 // Some of the candidates may have already been vectorized after we 6210 // initially collected them. If so, the WeakTrackingVHs will have 6211 // nullified the 6212 // values, so remove them from the set of candidates. 6213 Candidates.remove(nullptr); 6214 6215 // Remove from the set of candidates all pairs of getelementptrs with 6216 // constant differences. Such getelementptrs are likely not good 6217 // candidates for vectorization in a bottom-up phase since one can be 6218 // computed from the other. We also ensure all candidate getelementptr 6219 // indices are unique. 6220 for (int I = 0, E = GEPList.size(); I < E && Candidates.size() > 1; ++I) { 6221 auto *GEPI = cast<GetElementPtrInst>(GEPList[I]); 6222 if (!Candidates.count(GEPI)) 6223 continue; 6224 auto *SCEVI = SE->getSCEV(GEPList[I]); 6225 for (int J = I + 1; J < E && Candidates.size() > 1; ++J) { 6226 auto *GEPJ = cast<GetElementPtrInst>(GEPList[J]); 6227 auto *SCEVJ = SE->getSCEV(GEPList[J]); 6228 if (isa<SCEVConstant>(SE->getMinusSCEV(SCEVI, SCEVJ))) { 6229 Candidates.remove(GEPList[I]); 6230 Candidates.remove(GEPList[J]); 6231 } else if (GEPI->idx_begin()->get() == GEPJ->idx_begin()->get()) { 6232 Candidates.remove(GEPList[J]); 6233 } 6234 } 6235 } 6236 6237 // We break out of the above computation as soon as we know there are 6238 // fewer than two candidates remaining. 6239 if (Candidates.size() < 2) 6240 continue; 6241 6242 // Add the single, non-constant index of each candidate to the bundle. We 6243 // ensured the indices met these constraints when we originally collected 6244 // the getelementptrs. 6245 SmallVector<Value *, 16> Bundle(Candidates.size()); 6246 auto BundleIndex = 0u; 6247 for (auto *V : Candidates) { 6248 auto *GEP = cast<GetElementPtrInst>(V); 6249 auto *GEPIdx = GEP->idx_begin()->get(); 6250 assert(GEP->getNumIndices() == 1 || !isa<Constant>(GEPIdx)); 6251 Bundle[BundleIndex++] = GEPIdx; 6252 } 6253 6254 // Try and vectorize the indices. We are currently only interested in 6255 // gather-like cases of the form: 6256 // 6257 // ... = g[a[0] - b[0]] + g[a[1] - b[1]] + ... 6258 // 6259 // where the loads of "a", the loads of "b", and the subtractions can be 6260 // performed in parallel. It's likely that detecting this pattern in a 6261 // bottom-up phase will be simpler and less costly than building a 6262 // full-blown top-down phase beginning at the consecutive loads. 6263 Changed |= tryToVectorizeList(Bundle, R); 6264 } 6265 } 6266 return Changed; 6267 } 6268 6269 bool SLPVectorizerPass::vectorizeStoreChains(BoUpSLP &R) { 6270 bool Changed = false; 6271 // Attempt to sort and vectorize each of the store-groups. 6272 for (StoreListMap::iterator it = Stores.begin(), e = Stores.end(); it != e; 6273 ++it) { 6274 if (it->second.size() < 2) 6275 continue; 6276 6277 DEBUG(dbgs() << "SLP: Analyzing a store chain of length " 6278 << it->second.size() << ".\n"); 6279 6280 // Process the stores in chunks of 16. 6281 // TODO: The limit of 16 inhibits greater vectorization factors. 6282 // For example, AVX2 supports v32i8. Increasing this limit, however, 6283 // may cause a significant compile-time increase. 6284 for (unsigned CI = 0, CE = it->second.size(); CI < CE; CI+=16) { 6285 unsigned Len = std::min<unsigned>(CE - CI, 16); 6286 Changed |= vectorizeStores(makeArrayRef(&it->second[CI], Len), R); 6287 } 6288 } 6289 return Changed; 6290 } 6291 6292 char SLPVectorizer::ID = 0; 6293 6294 static const char lv_name[] = "SLP Vectorizer"; 6295 6296 INITIALIZE_PASS_BEGIN(SLPVectorizer, SV_NAME, lv_name, false, false) 6297 INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass) 6298 INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass) 6299 INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker) 6300 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass) 6301 INITIALIZE_PASS_DEPENDENCY(LoopSimplify) 6302 INITIALIZE_PASS_DEPENDENCY(DemandedBitsWrapperPass) 6303 INITIALIZE_PASS_DEPENDENCY(OptimizationRemarkEmitterWrapperPass) 6304 INITIALIZE_PASS_END(SLPVectorizer, SV_NAME, lv_name, false, false) 6305 6306 Pass *llvm::createSLPVectorizerPass() { return new SLPVectorizer(); } 6307