1 //===- LoopVectorize.cpp - A Loop 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 is the LLVM loop vectorizer. This pass modifies 'vectorizable' loops 11 // and generates target-independent LLVM-IR. 12 // The vectorizer uses the TargetTransformInfo analysis to estimate the costs 13 // of instructions in order to estimate the profitability of vectorization. 14 // 15 // The loop vectorizer combines consecutive loop iterations into a single 16 // 'wide' iteration. After this transformation the index is incremented 17 // by the SIMD vector width, and not by one. 18 // 19 // This pass has three parts: 20 // 1. The main loop pass that drives the different parts. 21 // 2. LoopVectorizationLegality - A unit that checks for the legality 22 // of the vectorization. 23 // 3. InnerLoopVectorizer - A unit that performs the actual 24 // widening of instructions. 25 // 4. LoopVectorizationCostModel - A unit that checks for the profitability 26 // of vectorization. It decides on the optimal vector width, which 27 // can be one, if vectorization is not profitable. 28 // 29 //===----------------------------------------------------------------------===// 30 // 31 // The reduction-variable vectorization is based on the paper: 32 // D. Nuzman and R. Henderson. Multi-platform Auto-vectorization. 33 // 34 // Variable uniformity checks are inspired by: 35 // Karrenberg, R. and Hack, S. Whole Function Vectorization. 36 // 37 // The interleaved access vectorization is based on the paper: 38 // Dorit Nuzman, Ira Rosen and Ayal Zaks. Auto-Vectorization of Interleaved 39 // Data for SIMD 40 // 41 // Other ideas/concepts are from: 42 // A. Zaks and D. Nuzman. Autovectorization in GCC-two years later. 43 // 44 // S. Maleki, Y. Gao, M. Garzaran, T. Wong and D. Padua. An Evaluation of 45 // Vectorizing Compilers. 46 // 47 //===----------------------------------------------------------------------===// 48 49 #include "llvm/Transforms/Vectorize.h" 50 #include "llvm/ADT/DenseMap.h" 51 #include "llvm/ADT/EquivalenceClasses.h" 52 #include "llvm/ADT/Hashing.h" 53 #include "llvm/ADT/MapVector.h" 54 #include "llvm/ADT/SetVector.h" 55 #include "llvm/ADT/SmallPtrSet.h" 56 #include "llvm/ADT/SmallSet.h" 57 #include "llvm/ADT/SmallVector.h" 58 #include "llvm/ADT/Statistic.h" 59 #include "llvm/ADT/StringExtras.h" 60 #include "llvm/Analysis/AliasAnalysis.h" 61 #include "llvm/Analysis/AliasSetTracker.h" 62 #include "llvm/Analysis/AssumptionCache.h" 63 #include "llvm/Analysis/BlockFrequencyInfo.h" 64 #include "llvm/Analysis/CodeMetrics.h" 65 #include "llvm/Analysis/LoopAccessAnalysis.h" 66 #include "llvm/Analysis/LoopInfo.h" 67 #include "llvm/Analysis/LoopIterator.h" 68 #include "llvm/Analysis/LoopPass.h" 69 #include "llvm/Analysis/ScalarEvolution.h" 70 #include "llvm/Analysis/ScalarEvolutionExpander.h" 71 #include "llvm/Analysis/ScalarEvolutionExpressions.h" 72 #include "llvm/Analysis/TargetTransformInfo.h" 73 #include "llvm/Analysis/ValueTracking.h" 74 #include "llvm/IR/Constants.h" 75 #include "llvm/IR/DataLayout.h" 76 #include "llvm/IR/DebugInfo.h" 77 #include "llvm/IR/DerivedTypes.h" 78 #include "llvm/IR/DiagnosticInfo.h" 79 #include "llvm/IR/Dominators.h" 80 #include "llvm/IR/Function.h" 81 #include "llvm/IR/IRBuilder.h" 82 #include "llvm/IR/Instructions.h" 83 #include "llvm/IR/IntrinsicInst.h" 84 #include "llvm/IR/LLVMContext.h" 85 #include "llvm/IR/Module.h" 86 #include "llvm/IR/PatternMatch.h" 87 #include "llvm/IR/Type.h" 88 #include "llvm/IR/Value.h" 89 #include "llvm/IR/ValueHandle.h" 90 #include "llvm/IR/Verifier.h" 91 #include "llvm/Pass.h" 92 #include "llvm/Support/BranchProbability.h" 93 #include "llvm/Support/CommandLine.h" 94 #include "llvm/Support/Debug.h" 95 #include "llvm/Support/raw_ostream.h" 96 #include "llvm/Transforms/Scalar.h" 97 #include "llvm/Transforms/Utils/BasicBlockUtils.h" 98 #include "llvm/Transforms/Utils/Local.h" 99 #include "llvm/Analysis/VectorUtils.h" 100 #include "llvm/Transforms/Utils/LoopUtils.h" 101 #include <algorithm> 102 #include <map> 103 #include <tuple> 104 105 using namespace llvm; 106 using namespace llvm::PatternMatch; 107 108 #define LV_NAME "loop-vectorize" 109 #define DEBUG_TYPE LV_NAME 110 111 STATISTIC(LoopsVectorized, "Number of loops vectorized"); 112 STATISTIC(LoopsAnalyzed, "Number of loops analyzed for vectorization"); 113 114 static cl::opt<bool> 115 EnableIfConversion("enable-if-conversion", cl::init(true), cl::Hidden, 116 cl::desc("Enable if-conversion during vectorization.")); 117 118 /// We don't vectorize loops with a known constant trip count below this number. 119 static cl::opt<unsigned> 120 TinyTripCountVectorThreshold("vectorizer-min-trip-count", cl::init(16), 121 cl::Hidden, 122 cl::desc("Don't vectorize loops with a constant " 123 "trip count that is smaller than this " 124 "value.")); 125 126 /// This enables versioning on the strides of symbolically striding memory 127 /// accesses in code like the following. 128 /// for (i = 0; i < N; ++i) 129 /// A[i * Stride1] += B[i * Stride2] ... 130 /// 131 /// Will be roughly translated to 132 /// if (Stride1 == 1 && Stride2 == 1) { 133 /// for (i = 0; i < N; i+=4) 134 /// A[i:i+3] += ... 135 /// } else 136 /// ... 137 static cl::opt<bool> EnableMemAccessVersioning( 138 "enable-mem-access-versioning", cl::init(true), cl::Hidden, 139 cl::desc("Enable symblic stride memory access versioning")); 140 141 static cl::opt<bool> EnableInterleavedMemAccesses( 142 "enable-interleaved-mem-accesses", cl::init(false), cl::Hidden, 143 cl::desc("Enable vectorization on interleaved memory accesses in a loop")); 144 145 /// Maximum factor for an interleaved memory access. 146 static cl::opt<unsigned> MaxInterleaveGroupFactor( 147 "max-interleave-group-factor", cl::Hidden, 148 cl::desc("Maximum factor for an interleaved access group (default = 8)"), 149 cl::init(8)); 150 151 /// We don't interleave loops with a known constant trip count below this 152 /// number. 153 static const unsigned TinyTripCountInterleaveThreshold = 128; 154 155 static cl::opt<unsigned> ForceTargetNumScalarRegs( 156 "force-target-num-scalar-regs", cl::init(0), cl::Hidden, 157 cl::desc("A flag that overrides the target's number of scalar registers.")); 158 159 static cl::opt<unsigned> ForceTargetNumVectorRegs( 160 "force-target-num-vector-regs", cl::init(0), cl::Hidden, 161 cl::desc("A flag that overrides the target's number of vector registers.")); 162 163 /// Maximum vectorization interleave count. 164 static const unsigned MaxInterleaveFactor = 16; 165 166 static cl::opt<unsigned> ForceTargetMaxScalarInterleaveFactor( 167 "force-target-max-scalar-interleave", cl::init(0), cl::Hidden, 168 cl::desc("A flag that overrides the target's max interleave factor for " 169 "scalar loops.")); 170 171 static cl::opt<unsigned> ForceTargetMaxVectorInterleaveFactor( 172 "force-target-max-vector-interleave", cl::init(0), cl::Hidden, 173 cl::desc("A flag that overrides the target's max interleave factor for " 174 "vectorized loops.")); 175 176 static cl::opt<unsigned> ForceTargetInstructionCost( 177 "force-target-instruction-cost", cl::init(0), cl::Hidden, 178 cl::desc("A flag that overrides the target's expected cost for " 179 "an instruction to a single constant value. Mostly " 180 "useful for getting consistent testing.")); 181 182 static cl::opt<unsigned> SmallLoopCost( 183 "small-loop-cost", cl::init(20), cl::Hidden, 184 cl::desc( 185 "The cost of a loop that is considered 'small' by the interleaver.")); 186 187 static cl::opt<bool> LoopVectorizeWithBlockFrequency( 188 "loop-vectorize-with-block-frequency", cl::init(false), cl::Hidden, 189 cl::desc("Enable the use of the block frequency analysis to access PGO " 190 "heuristics minimizing code growth in cold regions and being more " 191 "aggressive in hot regions.")); 192 193 // Runtime interleave loops for load/store throughput. 194 static cl::opt<bool> EnableLoadStoreRuntimeInterleave( 195 "enable-loadstore-runtime-interleave", cl::init(true), cl::Hidden, 196 cl::desc( 197 "Enable runtime interleaving until load/store ports are saturated")); 198 199 /// The number of stores in a loop that are allowed to need predication. 200 static cl::opt<unsigned> NumberOfStoresToPredicate( 201 "vectorize-num-stores-pred", cl::init(1), cl::Hidden, 202 cl::desc("Max number of stores to be predicated behind an if.")); 203 204 static cl::opt<bool> EnableIndVarRegisterHeur( 205 "enable-ind-var-reg-heur", cl::init(true), cl::Hidden, 206 cl::desc("Count the induction variable only once when interleaving")); 207 208 static cl::opt<bool> EnableCondStoresVectorization( 209 "enable-cond-stores-vec", cl::init(false), cl::Hidden, 210 cl::desc("Enable if predication of stores during vectorization.")); 211 212 static cl::opt<unsigned> MaxNestedScalarReductionIC( 213 "max-nested-scalar-reduction-interleave", cl::init(2), cl::Hidden, 214 cl::desc("The maximum interleave count to use when interleaving a scalar " 215 "reduction in a nested loop.")); 216 217 namespace { 218 219 // Forward declarations. 220 class LoopVectorizeHints; 221 class LoopVectorizationLegality; 222 class LoopVectorizationCostModel; 223 class LoopVectorizationRequirements; 224 225 /// \brief This modifies LoopAccessReport to initialize message with 226 /// loop-vectorizer-specific part. 227 class VectorizationReport : public LoopAccessReport { 228 public: 229 VectorizationReport(Instruction *I = nullptr) 230 : LoopAccessReport("loop not vectorized: ", I) {} 231 232 /// \brief This allows promotion of the loop-access analysis report into the 233 /// loop-vectorizer report. It modifies the message to add the 234 /// loop-vectorizer-specific part of the message. 235 explicit VectorizationReport(const LoopAccessReport &R) 236 : LoopAccessReport(Twine("loop not vectorized: ") + R.str(), 237 R.getInstr()) {} 238 }; 239 240 /// A helper function for converting Scalar types to vector types. 241 /// If the incoming type is void, we return void. If the VF is 1, we return 242 /// the scalar type. 243 static Type* ToVectorTy(Type *Scalar, unsigned VF) { 244 if (Scalar->isVoidTy() || VF == 1) 245 return Scalar; 246 return VectorType::get(Scalar, VF); 247 } 248 249 /// InnerLoopVectorizer vectorizes loops which contain only one basic 250 /// block to a specified vectorization factor (VF). 251 /// This class performs the widening of scalars into vectors, or multiple 252 /// scalars. This class also implements the following features: 253 /// * It inserts an epilogue loop for handling loops that don't have iteration 254 /// counts that are known to be a multiple of the vectorization factor. 255 /// * It handles the code generation for reduction variables. 256 /// * Scalarization (implementation using scalars) of un-vectorizable 257 /// instructions. 258 /// InnerLoopVectorizer does not perform any vectorization-legality 259 /// checks, and relies on the caller to check for the different legality 260 /// aspects. The InnerLoopVectorizer relies on the 261 /// LoopVectorizationLegality class to provide information about the induction 262 /// and reduction variables that were found to a given vectorization factor. 263 class InnerLoopVectorizer { 264 public: 265 InnerLoopVectorizer(Loop *OrigLoop, ScalarEvolution *SE, LoopInfo *LI, 266 DominatorTree *DT, const TargetLibraryInfo *TLI, 267 const TargetTransformInfo *TTI, unsigned VecWidth, 268 unsigned UnrollFactor) 269 : OrigLoop(OrigLoop), SE(SE), LI(LI), DT(DT), TLI(TLI), TTI(TTI), 270 VF(VecWidth), UF(UnrollFactor), Builder(SE->getContext()), 271 Induction(nullptr), OldInduction(nullptr), WidenMap(UnrollFactor), 272 Legal(nullptr), AddedSafetyChecks(false) {} 273 274 // Perform the actual loop widening (vectorization). 275 void vectorize(LoopVectorizationLegality *L) { 276 Legal = L; 277 // Create a new empty loop. Unlink the old loop and connect the new one. 278 createEmptyLoop(); 279 // Widen each instruction in the old loop to a new one in the new loop. 280 // Use the Legality module to find the induction and reduction variables. 281 vectorizeLoop(); 282 // Register the new loop and update the analysis passes. 283 updateAnalysis(); 284 } 285 286 // Return true if any runtime check is added. 287 bool IsSafetyChecksAdded() { 288 return AddedSafetyChecks; 289 } 290 291 virtual ~InnerLoopVectorizer() {} 292 293 protected: 294 /// A small list of PHINodes. 295 typedef SmallVector<PHINode*, 4> PhiVector; 296 /// When we unroll loops we have multiple vector values for each scalar. 297 /// This data structure holds the unrolled and vectorized values that 298 /// originated from one scalar instruction. 299 typedef SmallVector<Value*, 2> VectorParts; 300 301 // When we if-convert we need to create edge masks. We have to cache values 302 // so that we don't end up with exponential recursion/IR. 303 typedef DenseMap<std::pair<BasicBlock*, BasicBlock*>, 304 VectorParts> EdgeMaskCache; 305 306 /// \brief Add checks for strides that were assumed to be 1. 307 /// 308 /// Returns the last check instruction and the first check instruction in the 309 /// pair as (first, last). 310 std::pair<Instruction *, Instruction *> addStrideCheck(Instruction *Loc); 311 312 /// Create an empty loop, based on the loop ranges of the old loop. 313 void createEmptyLoop(); 314 /// Copy and widen the instructions from the old loop. 315 virtual void vectorizeLoop(); 316 317 /// \brief The Loop exit block may have single value PHI nodes where the 318 /// incoming value is 'Undef'. While vectorizing we only handled real values 319 /// that were defined inside the loop. Here we fix the 'undef case'. 320 /// See PR14725. 321 void fixLCSSAPHIs(); 322 323 /// A helper function that computes the predicate of the block BB, assuming 324 /// that the header block of the loop is set to True. It returns the *entry* 325 /// mask for the block BB. 326 VectorParts createBlockInMask(BasicBlock *BB); 327 /// A helper function that computes the predicate of the edge between SRC 328 /// and DST. 329 VectorParts createEdgeMask(BasicBlock *Src, BasicBlock *Dst); 330 331 /// A helper function to vectorize a single BB within the innermost loop. 332 void vectorizeBlockInLoop(BasicBlock *BB, PhiVector *PV); 333 334 /// Vectorize a single PHINode in a block. This method handles the induction 335 /// variable canonicalization. It supports both VF = 1 for unrolled loops and 336 /// arbitrary length vectors. 337 void widenPHIInstruction(Instruction *PN, VectorParts &Entry, 338 unsigned UF, unsigned VF, PhiVector *PV); 339 340 /// Insert the new loop to the loop hierarchy and pass manager 341 /// and update the analysis passes. 342 void updateAnalysis(); 343 344 /// This instruction is un-vectorizable. Implement it as a sequence 345 /// of scalars. If \p IfPredicateStore is true we need to 'hide' each 346 /// scalarized instruction behind an if block predicated on the control 347 /// dependence of the instruction. 348 virtual void scalarizeInstruction(Instruction *Instr, 349 bool IfPredicateStore=false); 350 351 /// Vectorize Load and Store instructions, 352 virtual void vectorizeMemoryInstruction(Instruction *Instr); 353 354 /// Create a broadcast instruction. This method generates a broadcast 355 /// instruction (shuffle) for loop invariant values and for the induction 356 /// value. If this is the induction variable then we extend it to N, N+1, ... 357 /// this is needed because each iteration in the loop corresponds to a SIMD 358 /// element. 359 virtual Value *getBroadcastInstrs(Value *V); 360 361 /// This function adds (StartIdx, StartIdx + Step, StartIdx + 2*Step, ...) 362 /// to each vector element of Val. The sequence starts at StartIndex. 363 virtual Value *getStepVector(Value *Val, int StartIdx, Value *Step); 364 365 /// When we go over instructions in the basic block we rely on previous 366 /// values within the current basic block or on loop invariant values. 367 /// When we widen (vectorize) values we place them in the map. If the values 368 /// are not within the map, they have to be loop invariant, so we simply 369 /// broadcast them into a vector. 370 VectorParts &getVectorValue(Value *V); 371 372 /// Try to vectorize the interleaved access group that \p Instr belongs to. 373 void vectorizeInterleaveGroup(Instruction *Instr); 374 375 /// Generate a shuffle sequence that will reverse the vector Vec. 376 virtual Value *reverseVector(Value *Vec); 377 378 /// This is a helper class that holds the vectorizer state. It maps scalar 379 /// instructions to vector instructions. When the code is 'unrolled' then 380 /// then a single scalar value is mapped to multiple vector parts. The parts 381 /// are stored in the VectorPart type. 382 struct ValueMap { 383 /// C'tor. UnrollFactor controls the number of vectors ('parts') that 384 /// are mapped. 385 ValueMap(unsigned UnrollFactor) : UF(UnrollFactor) {} 386 387 /// \return True if 'Key' is saved in the Value Map. 388 bool has(Value *Key) const { return MapStorage.count(Key); } 389 390 /// Initializes a new entry in the map. Sets all of the vector parts to the 391 /// save value in 'Val'. 392 /// \return A reference to a vector with splat values. 393 VectorParts &splat(Value *Key, Value *Val) { 394 VectorParts &Entry = MapStorage[Key]; 395 Entry.assign(UF, Val); 396 return Entry; 397 } 398 399 ///\return A reference to the value that is stored at 'Key'. 400 VectorParts &get(Value *Key) { 401 VectorParts &Entry = MapStorage[Key]; 402 if (Entry.empty()) 403 Entry.resize(UF); 404 assert(Entry.size() == UF); 405 return Entry; 406 } 407 408 private: 409 /// The unroll factor. Each entry in the map stores this number of vector 410 /// elements. 411 unsigned UF; 412 413 /// Map storage. We use std::map and not DenseMap because insertions to a 414 /// dense map invalidates its iterators. 415 std::map<Value *, VectorParts> MapStorage; 416 }; 417 418 /// The original loop. 419 Loop *OrigLoop; 420 /// Scev analysis to use. 421 ScalarEvolution *SE; 422 /// Loop Info. 423 LoopInfo *LI; 424 /// Dominator Tree. 425 DominatorTree *DT; 426 /// Alias Analysis. 427 AliasAnalysis *AA; 428 /// Target Library Info. 429 const TargetLibraryInfo *TLI; 430 /// Target Transform Info. 431 const TargetTransformInfo *TTI; 432 433 /// The vectorization SIMD factor to use. Each vector will have this many 434 /// vector elements. 435 unsigned VF; 436 437 protected: 438 /// The vectorization unroll factor to use. Each scalar is vectorized to this 439 /// many different vector instructions. 440 unsigned UF; 441 442 /// The builder that we use 443 IRBuilder<> Builder; 444 445 // --- Vectorization state --- 446 447 /// The vector-loop preheader. 448 BasicBlock *LoopVectorPreHeader; 449 /// The scalar-loop preheader. 450 BasicBlock *LoopScalarPreHeader; 451 /// Middle Block between the vector and the scalar. 452 BasicBlock *LoopMiddleBlock; 453 ///The ExitBlock of the scalar loop. 454 BasicBlock *LoopExitBlock; 455 ///The vector loop body. 456 SmallVector<BasicBlock *, 4> LoopVectorBody; 457 ///The scalar loop body. 458 BasicBlock *LoopScalarBody; 459 /// A list of all bypass blocks. The first block is the entry of the loop. 460 SmallVector<BasicBlock *, 4> LoopBypassBlocks; 461 462 /// The new Induction variable which was added to the new block. 463 PHINode *Induction; 464 /// The induction variable of the old basic block. 465 PHINode *OldInduction; 466 /// Holds the extended (to the widest induction type) start index. 467 Value *ExtendedIdx; 468 /// Maps scalars to widened vectors. 469 ValueMap WidenMap; 470 EdgeMaskCache MaskCache; 471 472 LoopVectorizationLegality *Legal; 473 474 // Record whether runtime check is added. 475 bool AddedSafetyChecks; 476 }; 477 478 class InnerLoopUnroller : public InnerLoopVectorizer { 479 public: 480 InnerLoopUnroller(Loop *OrigLoop, ScalarEvolution *SE, LoopInfo *LI, 481 DominatorTree *DT, const TargetLibraryInfo *TLI, 482 const TargetTransformInfo *TTI, unsigned UnrollFactor) 483 : InnerLoopVectorizer(OrigLoop, SE, LI, DT, TLI, TTI, 1, UnrollFactor) {} 484 485 private: 486 void scalarizeInstruction(Instruction *Instr, 487 bool IfPredicateStore = false) override; 488 void vectorizeMemoryInstruction(Instruction *Instr) override; 489 Value *getBroadcastInstrs(Value *V) override; 490 Value *getStepVector(Value *Val, int StartIdx, Value *Step) override; 491 Value *reverseVector(Value *Vec) override; 492 }; 493 494 /// \brief Look for a meaningful debug location on the instruction or it's 495 /// operands. 496 static Instruction *getDebugLocFromInstOrOperands(Instruction *I) { 497 if (!I) 498 return I; 499 500 DebugLoc Empty; 501 if (I->getDebugLoc() != Empty) 502 return I; 503 504 for (User::op_iterator OI = I->op_begin(), OE = I->op_end(); OI != OE; ++OI) { 505 if (Instruction *OpInst = dyn_cast<Instruction>(*OI)) 506 if (OpInst->getDebugLoc() != Empty) 507 return OpInst; 508 } 509 510 return I; 511 } 512 513 /// \brief Set the debug location in the builder using the debug location in the 514 /// instruction. 515 static void setDebugLocFromInst(IRBuilder<> &B, const Value *Ptr) { 516 if (const Instruction *Inst = dyn_cast_or_null<Instruction>(Ptr)) 517 B.SetCurrentDebugLocation(Inst->getDebugLoc()); 518 else 519 B.SetCurrentDebugLocation(DebugLoc()); 520 } 521 522 #ifndef NDEBUG 523 /// \return string containing a file name and a line # for the given loop. 524 static std::string getDebugLocString(const Loop *L) { 525 std::string Result; 526 if (L) { 527 raw_string_ostream OS(Result); 528 if (const DebugLoc LoopDbgLoc = L->getStartLoc()) 529 LoopDbgLoc.print(OS); 530 else 531 // Just print the module name. 532 OS << L->getHeader()->getParent()->getParent()->getModuleIdentifier(); 533 OS.flush(); 534 } 535 return Result; 536 } 537 #endif 538 539 /// \brief Propagate known metadata from one instruction to another. 540 static void propagateMetadata(Instruction *To, const Instruction *From) { 541 SmallVector<std::pair<unsigned, MDNode *>, 4> Metadata; 542 From->getAllMetadataOtherThanDebugLoc(Metadata); 543 544 for (auto M : Metadata) { 545 unsigned Kind = M.first; 546 547 // These are safe to transfer (this is safe for TBAA, even when we 548 // if-convert, because should that metadata have had a control dependency 549 // on the condition, and thus actually aliased with some other 550 // non-speculated memory access when the condition was false, this would be 551 // caught by the runtime overlap checks). 552 if (Kind != LLVMContext::MD_tbaa && 553 Kind != LLVMContext::MD_alias_scope && 554 Kind != LLVMContext::MD_noalias && 555 Kind != LLVMContext::MD_fpmath && 556 Kind != LLVMContext::MD_nontemporal) 557 continue; 558 559 To->setMetadata(Kind, M.second); 560 } 561 } 562 563 /// \brief Propagate known metadata from one instruction to a vector of others. 564 static void propagateMetadata(SmallVectorImpl<Value *> &To, const Instruction *From) { 565 for (Value *V : To) 566 if (Instruction *I = dyn_cast<Instruction>(V)) 567 propagateMetadata(I, From); 568 } 569 570 /// \brief The group of interleaved loads/stores sharing the same stride and 571 /// close to each other. 572 /// 573 /// Each member in this group has an index starting from 0, and the largest 574 /// index should be less than interleaved factor, which is equal to the absolute 575 /// value of the access's stride. 576 /// 577 /// E.g. An interleaved load group of factor 4: 578 /// for (unsigned i = 0; i < 1024; i+=4) { 579 /// a = A[i]; // Member of index 0 580 /// b = A[i+1]; // Member of index 1 581 /// d = A[i+3]; // Member of index 3 582 /// ... 583 /// } 584 /// 585 /// An interleaved store group of factor 4: 586 /// for (unsigned i = 0; i < 1024; i+=4) { 587 /// ... 588 /// A[i] = a; // Member of index 0 589 /// A[i+1] = b; // Member of index 1 590 /// A[i+2] = c; // Member of index 2 591 /// A[i+3] = d; // Member of index 3 592 /// } 593 /// 594 /// Note: the interleaved load group could have gaps (missing members), but 595 /// the interleaved store group doesn't allow gaps. 596 class InterleaveGroup { 597 public: 598 InterleaveGroup(Instruction *Instr, int Stride, unsigned Align) 599 : Align(Align), SmallestKey(0), LargestKey(0), InsertPos(Instr) { 600 assert(Align && "The alignment should be non-zero"); 601 602 Factor = std::abs(Stride); 603 assert(Factor > 1 && "Invalid interleave factor"); 604 605 Reverse = Stride < 0; 606 Members[0] = Instr; 607 } 608 609 bool isReverse() const { return Reverse; } 610 unsigned getFactor() const { return Factor; } 611 unsigned getAlignment() const { return Align; } 612 unsigned getNumMembers() const { return Members.size(); } 613 614 /// \brief Try to insert a new member \p Instr with index \p Index and 615 /// alignment \p NewAlign. The index is related to the leader and it could be 616 /// negative if it is the new leader. 617 /// 618 /// \returns false if the instruction doesn't belong to the group. 619 bool insertMember(Instruction *Instr, int Index, unsigned NewAlign) { 620 assert(NewAlign && "The new member's alignment should be non-zero"); 621 622 int Key = Index + SmallestKey; 623 624 // Skip if there is already a member with the same index. 625 if (Members.count(Key)) 626 return false; 627 628 if (Key > LargestKey) { 629 // The largest index is always less than the interleave factor. 630 if (Index >= static_cast<int>(Factor)) 631 return false; 632 633 LargestKey = Key; 634 } else if (Key < SmallestKey) { 635 // The largest index is always less than the interleave factor. 636 if (LargestKey - Key >= static_cast<int>(Factor)) 637 return false; 638 639 SmallestKey = Key; 640 } 641 642 // It's always safe to select the minimum alignment. 643 Align = std::min(Align, NewAlign); 644 Members[Key] = Instr; 645 return true; 646 } 647 648 /// \brief Get the member with the given index \p Index 649 /// 650 /// \returns nullptr if contains no such member. 651 Instruction *getMember(unsigned Index) const { 652 int Key = SmallestKey + Index; 653 if (!Members.count(Key)) 654 return nullptr; 655 656 return Members.find(Key)->second; 657 } 658 659 /// \brief Get the index for the given member. Unlike the key in the member 660 /// map, the index starts from 0. 661 unsigned getIndex(Instruction *Instr) const { 662 for (auto I : Members) 663 if (I.second == Instr) 664 return I.first - SmallestKey; 665 666 llvm_unreachable("InterleaveGroup contains no such member"); 667 } 668 669 Instruction *getInsertPos() const { return InsertPos; } 670 void setInsertPos(Instruction *Inst) { InsertPos = Inst; } 671 672 private: 673 unsigned Factor; // Interleave Factor. 674 bool Reverse; 675 unsigned Align; 676 DenseMap<int, Instruction *> Members; 677 int SmallestKey; 678 int LargestKey; 679 680 // To avoid breaking dependences, vectorized instructions of an interleave 681 // group should be inserted at either the first load or the last store in 682 // program order. 683 // 684 // E.g. %even = load i32 // Insert Position 685 // %add = add i32 %even // Use of %even 686 // %odd = load i32 687 // 688 // store i32 %even 689 // %odd = add i32 // Def of %odd 690 // store i32 %odd // Insert Position 691 Instruction *InsertPos; 692 }; 693 694 /// \brief Drive the analysis of interleaved memory accesses in the loop. 695 /// 696 /// Use this class to analyze interleaved accesses only when we can vectorize 697 /// a loop. Otherwise it's meaningless to do analysis as the vectorization 698 /// on interleaved accesses is unsafe. 699 /// 700 /// The analysis collects interleave groups and records the relationships 701 /// between the member and the group in a map. 702 class InterleavedAccessInfo { 703 public: 704 InterleavedAccessInfo(ScalarEvolution *SE, Loop *L, DominatorTree *DT) 705 : SE(SE), TheLoop(L), DT(DT) {} 706 707 ~InterleavedAccessInfo() { 708 SmallSet<InterleaveGroup *, 4> DelSet; 709 // Avoid releasing a pointer twice. 710 for (auto &I : InterleaveGroupMap) 711 DelSet.insert(I.second); 712 for (auto *Ptr : DelSet) 713 delete Ptr; 714 } 715 716 /// \brief Analyze the interleaved accesses and collect them in interleave 717 /// groups. Substitute symbolic strides using \p Strides. 718 void analyzeInterleaving(const ValueToValueMap &Strides); 719 720 /// \brief Check if \p Instr belongs to any interleave group. 721 bool isInterleaved(Instruction *Instr) const { 722 return InterleaveGroupMap.count(Instr); 723 } 724 725 /// \brief Get the interleave group that \p Instr belongs to. 726 /// 727 /// \returns nullptr if doesn't have such group. 728 InterleaveGroup *getInterleaveGroup(Instruction *Instr) const { 729 if (InterleaveGroupMap.count(Instr)) 730 return InterleaveGroupMap.find(Instr)->second; 731 return nullptr; 732 } 733 734 private: 735 ScalarEvolution *SE; 736 Loop *TheLoop; 737 DominatorTree *DT; 738 739 /// Holds the relationships between the members and the interleave group. 740 DenseMap<Instruction *, InterleaveGroup *> InterleaveGroupMap; 741 742 /// \brief The descriptor for a strided memory access. 743 struct StrideDescriptor { 744 StrideDescriptor(int Stride, const SCEV *Scev, unsigned Size, 745 unsigned Align) 746 : Stride(Stride), Scev(Scev), Size(Size), Align(Align) {} 747 748 StrideDescriptor() : Stride(0), Scev(nullptr), Size(0), Align(0) {} 749 750 int Stride; // The access's stride. It is negative for a reverse access. 751 const SCEV *Scev; // The scalar expression of this access 752 unsigned Size; // The size of the memory object. 753 unsigned Align; // The alignment of this access. 754 }; 755 756 /// \brief Create a new interleave group with the given instruction \p Instr, 757 /// stride \p Stride and alignment \p Align. 758 /// 759 /// \returns the newly created interleave group. 760 InterleaveGroup *createInterleaveGroup(Instruction *Instr, int Stride, 761 unsigned Align) { 762 assert(!InterleaveGroupMap.count(Instr) && 763 "Already in an interleaved access group"); 764 InterleaveGroupMap[Instr] = new InterleaveGroup(Instr, Stride, Align); 765 return InterleaveGroupMap[Instr]; 766 } 767 768 /// \brief Release the group and remove all the relationships. 769 void releaseGroup(InterleaveGroup *Group) { 770 for (unsigned i = 0; i < Group->getFactor(); i++) 771 if (Instruction *Member = Group->getMember(i)) 772 InterleaveGroupMap.erase(Member); 773 774 delete Group; 775 } 776 777 /// \brief Collect all the accesses with a constant stride in program order. 778 void collectConstStridedAccesses( 779 MapVector<Instruction *, StrideDescriptor> &StrideAccesses, 780 const ValueToValueMap &Strides); 781 }; 782 783 /// Utility class for getting and setting loop vectorizer hints in the form 784 /// of loop metadata. 785 /// This class keeps a number of loop annotations locally (as member variables) 786 /// and can, upon request, write them back as metadata on the loop. It will 787 /// initially scan the loop for existing metadata, and will update the local 788 /// values based on information in the loop. 789 /// We cannot write all values to metadata, as the mere presence of some info, 790 /// for example 'force', means a decision has been made. So, we need to be 791 /// careful NOT to add them if the user hasn't specifically asked so. 792 class LoopVectorizeHints { 793 enum HintKind { 794 HK_WIDTH, 795 HK_UNROLL, 796 HK_FORCE 797 }; 798 799 /// Hint - associates name and validation with the hint value. 800 struct Hint { 801 const char * Name; 802 unsigned Value; // This may have to change for non-numeric values. 803 HintKind Kind; 804 805 Hint(const char * Name, unsigned Value, HintKind Kind) 806 : Name(Name), Value(Value), Kind(Kind) { } 807 808 bool validate(unsigned Val) { 809 switch (Kind) { 810 case HK_WIDTH: 811 return isPowerOf2_32(Val) && Val <= VectorizerParams::MaxVectorWidth; 812 case HK_UNROLL: 813 return isPowerOf2_32(Val) && Val <= MaxInterleaveFactor; 814 case HK_FORCE: 815 return (Val <= 1); 816 } 817 return false; 818 } 819 }; 820 821 /// Vectorization width. 822 Hint Width; 823 /// Vectorization interleave factor. 824 Hint Interleave; 825 /// Vectorization forced 826 Hint Force; 827 828 /// Return the loop metadata prefix. 829 static StringRef Prefix() { return "llvm.loop."; } 830 831 public: 832 enum ForceKind { 833 FK_Undefined = -1, ///< Not selected. 834 FK_Disabled = 0, ///< Forcing disabled. 835 FK_Enabled = 1, ///< Forcing enabled. 836 }; 837 838 LoopVectorizeHints(const Loop *L, bool DisableInterleaving) 839 : Width("vectorize.width", VectorizerParams::VectorizationFactor, 840 HK_WIDTH), 841 Interleave("interleave.count", DisableInterleaving, HK_UNROLL), 842 Force("vectorize.enable", FK_Undefined, HK_FORCE), 843 TheLoop(L) { 844 // Populate values with existing loop metadata. 845 getHintsFromMetadata(); 846 847 // force-vector-interleave overrides DisableInterleaving. 848 if (VectorizerParams::isInterleaveForced()) 849 Interleave.Value = VectorizerParams::VectorizationInterleave; 850 851 DEBUG(if (DisableInterleaving && Interleave.Value == 1) dbgs() 852 << "LV: Interleaving disabled by the pass manager\n"); 853 } 854 855 /// Mark the loop L as already vectorized by setting the width to 1. 856 void setAlreadyVectorized() { 857 Width.Value = Interleave.Value = 1; 858 Hint Hints[] = {Width, Interleave}; 859 writeHintsToMetadata(Hints); 860 } 861 862 bool allowVectorization(Function *F, Loop *L, bool AlwaysVectorize) const { 863 if (getForce() == LoopVectorizeHints::FK_Disabled) { 864 DEBUG(dbgs() << "LV: Not vectorizing: #pragma vectorize disable.\n"); 865 emitOptimizationRemarkAnalysis(F->getContext(), DEBUG_TYPE, *F, 866 L->getStartLoc(), emitRemark()); 867 return false; 868 } 869 870 if (!AlwaysVectorize && getForce() != LoopVectorizeHints::FK_Enabled) { 871 DEBUG(dbgs() << "LV: Not vectorizing: No #pragma vectorize enable.\n"); 872 emitOptimizationRemarkAnalysis(F->getContext(), DEBUG_TYPE, *F, 873 L->getStartLoc(), emitRemark()); 874 return false; 875 } 876 877 if (getWidth() == 1 && getInterleave() == 1) { 878 // FIXME: Add a separate metadata to indicate when the loop has already 879 // been vectorized instead of setting width and count to 1. 880 DEBUG(dbgs() << "LV: Not vectorizing: Disabled/already vectorized.\n"); 881 // FIXME: Add interleave.disable metadata. This will allow 882 // vectorize.disable to be used without disabling the pass and errors 883 // to differentiate between disabled vectorization and a width of 1. 884 emitOptimizationRemarkAnalysis( 885 F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(), 886 "loop not vectorized: vectorization and interleaving are explicitly " 887 "disabled, or vectorize width and interleave count are both set to " 888 "1"); 889 return false; 890 } 891 892 return true; 893 } 894 895 /// Dumps all the hint information. 896 std::string emitRemark() const { 897 VectorizationReport R; 898 if (Force.Value == LoopVectorizeHints::FK_Disabled) 899 R << "vectorization is explicitly disabled"; 900 else { 901 R << "use -Rpass-analysis=loop-vectorize for more info"; 902 if (Force.Value == LoopVectorizeHints::FK_Enabled) { 903 R << " (Force=true"; 904 if (Width.Value != 0) 905 R << ", Vector Width=" << Width.Value; 906 if (Interleave.Value != 0) 907 R << ", Interleave Count=" << Interleave.Value; 908 R << ")"; 909 } 910 } 911 912 return R.str(); 913 } 914 915 unsigned getWidth() const { return Width.Value; } 916 unsigned getInterleave() const { return Interleave.Value; } 917 enum ForceKind getForce() const { return (ForceKind)Force.Value; } 918 bool isForced() const { 919 return getForce() == LoopVectorizeHints::FK_Enabled || getWidth() > 1 || 920 getInterleave() > 1; 921 } 922 923 private: 924 /// Find hints specified in the loop metadata and update local values. 925 void getHintsFromMetadata() { 926 MDNode *LoopID = TheLoop->getLoopID(); 927 if (!LoopID) 928 return; 929 930 // First operand should refer to the loop id itself. 931 assert(LoopID->getNumOperands() > 0 && "requires at least one operand"); 932 assert(LoopID->getOperand(0) == LoopID && "invalid loop id"); 933 934 for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) { 935 const MDString *S = nullptr; 936 SmallVector<Metadata *, 4> Args; 937 938 // The expected hint is either a MDString or a MDNode with the first 939 // operand a MDString. 940 if (const MDNode *MD = dyn_cast<MDNode>(LoopID->getOperand(i))) { 941 if (!MD || MD->getNumOperands() == 0) 942 continue; 943 S = dyn_cast<MDString>(MD->getOperand(0)); 944 for (unsigned i = 1, ie = MD->getNumOperands(); i < ie; ++i) 945 Args.push_back(MD->getOperand(i)); 946 } else { 947 S = dyn_cast<MDString>(LoopID->getOperand(i)); 948 assert(Args.size() == 0 && "too many arguments for MDString"); 949 } 950 951 if (!S) 952 continue; 953 954 // Check if the hint starts with the loop metadata prefix. 955 StringRef Name = S->getString(); 956 if (Args.size() == 1) 957 setHint(Name, Args[0]); 958 } 959 } 960 961 /// Checks string hint with one operand and set value if valid. 962 void setHint(StringRef Name, Metadata *Arg) { 963 if (!Name.startswith(Prefix())) 964 return; 965 Name = Name.substr(Prefix().size(), StringRef::npos); 966 967 const ConstantInt *C = mdconst::dyn_extract<ConstantInt>(Arg); 968 if (!C) return; 969 unsigned Val = C->getZExtValue(); 970 971 Hint *Hints[] = {&Width, &Interleave, &Force}; 972 for (auto H : Hints) { 973 if (Name == H->Name) { 974 if (H->validate(Val)) 975 H->Value = Val; 976 else 977 DEBUG(dbgs() << "LV: ignoring invalid hint '" << Name << "'\n"); 978 break; 979 } 980 } 981 } 982 983 /// Create a new hint from name / value pair. 984 MDNode *createHintMetadata(StringRef Name, unsigned V) const { 985 LLVMContext &Context = TheLoop->getHeader()->getContext(); 986 Metadata *MDs[] = {MDString::get(Context, Name), 987 ConstantAsMetadata::get( 988 ConstantInt::get(Type::getInt32Ty(Context), V))}; 989 return MDNode::get(Context, MDs); 990 } 991 992 /// Matches metadata with hint name. 993 bool matchesHintMetadataName(MDNode *Node, ArrayRef<Hint> HintTypes) { 994 MDString* Name = dyn_cast<MDString>(Node->getOperand(0)); 995 if (!Name) 996 return false; 997 998 for (auto H : HintTypes) 999 if (Name->getString().endswith(H.Name)) 1000 return true; 1001 return false; 1002 } 1003 1004 /// Sets current hints into loop metadata, keeping other values intact. 1005 void writeHintsToMetadata(ArrayRef<Hint> HintTypes) { 1006 if (HintTypes.size() == 0) 1007 return; 1008 1009 // Reserve the first element to LoopID (see below). 1010 SmallVector<Metadata *, 4> MDs(1); 1011 // If the loop already has metadata, then ignore the existing operands. 1012 MDNode *LoopID = TheLoop->getLoopID(); 1013 if (LoopID) { 1014 for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) { 1015 MDNode *Node = cast<MDNode>(LoopID->getOperand(i)); 1016 // If node in update list, ignore old value. 1017 if (!matchesHintMetadataName(Node, HintTypes)) 1018 MDs.push_back(Node); 1019 } 1020 } 1021 1022 // Now, add the missing hints. 1023 for (auto H : HintTypes) 1024 MDs.push_back(createHintMetadata(Twine(Prefix(), H.Name).str(), H.Value)); 1025 1026 // Replace current metadata node with new one. 1027 LLVMContext &Context = TheLoop->getHeader()->getContext(); 1028 MDNode *NewLoopID = MDNode::get(Context, MDs); 1029 // Set operand 0 to refer to the loop id itself. 1030 NewLoopID->replaceOperandWith(0, NewLoopID); 1031 1032 TheLoop->setLoopID(NewLoopID); 1033 } 1034 1035 /// The loop these hints belong to. 1036 const Loop *TheLoop; 1037 }; 1038 1039 static void emitAnalysisDiag(const Function *TheFunction, const Loop *TheLoop, 1040 const LoopVectorizeHints &Hints, 1041 const LoopAccessReport &Message) { 1042 // If a loop hint is provided the diagnostic is always produced. 1043 const char *Name = Hints.isForced() ? DiagnosticInfo::AlwaysPrint : LV_NAME; 1044 LoopAccessReport::emitAnalysis(Message, TheFunction, TheLoop, Name); 1045 } 1046 1047 static void emitMissedWarning(Function *F, Loop *L, 1048 const LoopVectorizeHints &LH) { 1049 emitOptimizationRemarkMissed(F->getContext(), DEBUG_TYPE, *F, 1050 L->getStartLoc(), LH.emitRemark()); 1051 1052 if (LH.getForce() == LoopVectorizeHints::FK_Enabled) { 1053 if (LH.getWidth() != 1) 1054 emitLoopVectorizeWarning( 1055 F->getContext(), *F, L->getStartLoc(), 1056 "failed explicitly specified loop vectorization"); 1057 else if (LH.getInterleave() != 1) 1058 emitLoopInterleaveWarning( 1059 F->getContext(), *F, L->getStartLoc(), 1060 "failed explicitly specified loop interleaving"); 1061 } 1062 } 1063 1064 /// LoopVectorizationLegality checks if it is legal to vectorize a loop, and 1065 /// to what vectorization factor. 1066 /// This class does not look at the profitability of vectorization, only the 1067 /// legality. This class has two main kinds of checks: 1068 /// * Memory checks - The code in canVectorizeMemory checks if vectorization 1069 /// will change the order of memory accesses in a way that will change the 1070 /// correctness of the program. 1071 /// * Scalars checks - The code in canVectorizeInstrs and canVectorizeMemory 1072 /// checks for a number of different conditions, such as the availability of a 1073 /// single induction variable, that all types are supported and vectorize-able, 1074 /// etc. This code reflects the capabilities of InnerLoopVectorizer. 1075 /// This class is also used by InnerLoopVectorizer for identifying 1076 /// induction variable and the different reduction variables. 1077 class LoopVectorizationLegality { 1078 public: 1079 LoopVectorizationLegality(Loop *L, ScalarEvolution *SE, DominatorTree *DT, 1080 TargetLibraryInfo *TLI, AliasAnalysis *AA, 1081 Function *F, const TargetTransformInfo *TTI, 1082 LoopAccessAnalysis *LAA, 1083 LoopVectorizationRequirements *R, 1084 const LoopVectorizeHints *H) 1085 : NumPredStores(0), TheLoop(L), SE(SE), TLI(TLI), TheFunction(F), 1086 TTI(TTI), DT(DT), LAA(LAA), LAI(nullptr), InterleaveInfo(SE, L, DT), 1087 Induction(nullptr), WidestIndTy(nullptr), HasFunNoNaNAttr(false), 1088 Requirements(R), Hints(H) {} 1089 1090 /// This enum represents the kinds of inductions that we support. 1091 enum InductionKind { 1092 IK_NoInduction, ///< Not an induction variable. 1093 IK_IntInduction, ///< Integer induction variable. Step = C. 1094 IK_PtrInduction ///< Pointer induction var. Step = C / sizeof(elem). 1095 }; 1096 1097 /// A struct for saving information about induction variables. 1098 struct InductionInfo { 1099 InductionInfo(Value *Start, InductionKind K, ConstantInt *Step) 1100 : StartValue(Start), IK(K), StepValue(Step) { 1101 assert(IK != IK_NoInduction && "Not an induction"); 1102 assert(StartValue && "StartValue is null"); 1103 assert(StepValue && !StepValue->isZero() && "StepValue is zero"); 1104 assert((IK != IK_PtrInduction || StartValue->getType()->isPointerTy()) && 1105 "StartValue is not a pointer for pointer induction"); 1106 assert((IK != IK_IntInduction || StartValue->getType()->isIntegerTy()) && 1107 "StartValue is not an integer for integer induction"); 1108 assert(StepValue->getType()->isIntegerTy() && 1109 "StepValue is not an integer"); 1110 } 1111 InductionInfo() 1112 : StartValue(nullptr), IK(IK_NoInduction), StepValue(nullptr) {} 1113 1114 /// Get the consecutive direction. Returns: 1115 /// 0 - unknown or non-consecutive. 1116 /// 1 - consecutive and increasing. 1117 /// -1 - consecutive and decreasing. 1118 int getConsecutiveDirection() const { 1119 if (StepValue && (StepValue->isOne() || StepValue->isMinusOne())) 1120 return StepValue->getSExtValue(); 1121 return 0; 1122 } 1123 1124 /// Compute the transformed value of Index at offset StartValue using step 1125 /// StepValue. 1126 /// For integer induction, returns StartValue + Index * StepValue. 1127 /// For pointer induction, returns StartValue[Index * StepValue]. 1128 /// FIXME: The newly created binary instructions should contain nsw/nuw 1129 /// flags, which can be found from the original scalar operations. 1130 Value *transform(IRBuilder<> &B, Value *Index) const { 1131 switch (IK) { 1132 case IK_IntInduction: 1133 assert(Index->getType() == StartValue->getType() && 1134 "Index type does not match StartValue type"); 1135 if (StepValue->isMinusOne()) 1136 return B.CreateSub(StartValue, Index); 1137 if (!StepValue->isOne()) 1138 Index = B.CreateMul(Index, StepValue); 1139 return B.CreateAdd(StartValue, Index); 1140 1141 case IK_PtrInduction: 1142 assert(Index->getType() == StepValue->getType() && 1143 "Index type does not match StepValue type"); 1144 if (StepValue->isMinusOne()) 1145 Index = B.CreateNeg(Index); 1146 else if (!StepValue->isOne()) 1147 Index = B.CreateMul(Index, StepValue); 1148 return B.CreateGEP(nullptr, StartValue, Index); 1149 1150 case IK_NoInduction: 1151 return nullptr; 1152 } 1153 llvm_unreachable("invalid enum"); 1154 } 1155 1156 /// Start value. 1157 TrackingVH<Value> StartValue; 1158 /// Induction kind. 1159 InductionKind IK; 1160 /// Step value. 1161 ConstantInt *StepValue; 1162 }; 1163 1164 /// ReductionList contains the reduction descriptors for all 1165 /// of the reductions that were found in the loop. 1166 typedef DenseMap<PHINode *, RecurrenceDescriptor> ReductionList; 1167 1168 /// InductionList saves induction variables and maps them to the 1169 /// induction descriptor. 1170 typedef MapVector<PHINode*, InductionInfo> InductionList; 1171 1172 /// Returns true if it is legal to vectorize this loop. 1173 /// This does not mean that it is profitable to vectorize this 1174 /// loop, only that it is legal to do so. 1175 bool canVectorize(); 1176 1177 /// Returns the Induction variable. 1178 PHINode *getInduction() { return Induction; } 1179 1180 /// Returns the reduction variables found in the loop. 1181 ReductionList *getReductionVars() { return &Reductions; } 1182 1183 /// Returns the induction variables found in the loop. 1184 InductionList *getInductionVars() { return &Inductions; } 1185 1186 /// Returns the widest induction type. 1187 Type *getWidestInductionType() { return WidestIndTy; } 1188 1189 /// Returns True if V is an induction variable in this loop. 1190 bool isInductionVariable(const Value *V); 1191 1192 /// Return true if the block BB needs to be predicated in order for the loop 1193 /// to be vectorized. 1194 bool blockNeedsPredication(BasicBlock *BB); 1195 1196 /// Check if this pointer is consecutive when vectorizing. This happens 1197 /// when the last index of the GEP is the induction variable, or that the 1198 /// pointer itself is an induction variable. 1199 /// This check allows us to vectorize A[idx] into a wide load/store. 1200 /// Returns: 1201 /// 0 - Stride is unknown or non-consecutive. 1202 /// 1 - Address is consecutive. 1203 /// -1 - Address is consecutive, and decreasing. 1204 int isConsecutivePtr(Value *Ptr); 1205 1206 /// Returns true if the value V is uniform within the loop. 1207 bool isUniform(Value *V); 1208 1209 /// Returns true if this instruction will remain scalar after vectorization. 1210 bool isUniformAfterVectorization(Instruction* I) { return Uniforms.count(I); } 1211 1212 /// Returns the information that we collected about runtime memory check. 1213 const RuntimePointerChecking *getRuntimePointerChecking() const { 1214 return LAI->getRuntimePointerChecking(); 1215 } 1216 1217 const LoopAccessInfo *getLAI() const { 1218 return LAI; 1219 } 1220 1221 /// \brief Check if \p Instr belongs to any interleaved access group. 1222 bool isAccessInterleaved(Instruction *Instr) { 1223 return InterleaveInfo.isInterleaved(Instr); 1224 } 1225 1226 /// \brief Get the interleaved access group that \p Instr belongs to. 1227 const InterleaveGroup *getInterleavedAccessGroup(Instruction *Instr) { 1228 return InterleaveInfo.getInterleaveGroup(Instr); 1229 } 1230 1231 unsigned getMaxSafeDepDistBytes() { return LAI->getMaxSafeDepDistBytes(); } 1232 1233 bool hasStride(Value *V) { return StrideSet.count(V); } 1234 bool mustCheckStrides() { return !StrideSet.empty(); } 1235 SmallPtrSet<Value *, 8>::iterator strides_begin() { 1236 return StrideSet.begin(); 1237 } 1238 SmallPtrSet<Value *, 8>::iterator strides_end() { return StrideSet.end(); } 1239 1240 /// Returns true if the target machine supports masked store operation 1241 /// for the given \p DataType and kind of access to \p Ptr. 1242 bool isLegalMaskedStore(Type *DataType, Value *Ptr) { 1243 return TTI->isLegalMaskedStore(DataType, isConsecutivePtr(Ptr)); 1244 } 1245 /// Returns true if the target machine supports masked load operation 1246 /// for the given \p DataType and kind of access to \p Ptr. 1247 bool isLegalMaskedLoad(Type *DataType, Value *Ptr) { 1248 return TTI->isLegalMaskedLoad(DataType, isConsecutivePtr(Ptr)); 1249 } 1250 /// Returns true if vector representation of the instruction \p I 1251 /// requires mask. 1252 bool isMaskRequired(const Instruction* I) { 1253 return (MaskedOp.count(I) != 0); 1254 } 1255 unsigned getNumStores() const { 1256 return LAI->getNumStores(); 1257 } 1258 unsigned getNumLoads() const { 1259 return LAI->getNumLoads(); 1260 } 1261 unsigned getNumPredStores() const { 1262 return NumPredStores; 1263 } 1264 private: 1265 /// Check if a single basic block loop is vectorizable. 1266 /// At this point we know that this is a loop with a constant trip count 1267 /// and we only need to check individual instructions. 1268 bool canVectorizeInstrs(); 1269 1270 /// When we vectorize loops we may change the order in which 1271 /// we read and write from memory. This method checks if it is 1272 /// legal to vectorize the code, considering only memory constrains. 1273 /// Returns true if the loop is vectorizable 1274 bool canVectorizeMemory(); 1275 1276 /// Return true if we can vectorize this loop using the IF-conversion 1277 /// transformation. 1278 bool canVectorizeWithIfConvert(); 1279 1280 /// Collect the variables that need to stay uniform after vectorization. 1281 void collectLoopUniforms(); 1282 1283 /// Return true if all of the instructions in the block can be speculatively 1284 /// executed. \p SafePtrs is a list of addresses that are known to be legal 1285 /// and we know that we can read from them without segfault. 1286 bool blockCanBePredicated(BasicBlock *BB, SmallPtrSetImpl<Value *> &SafePtrs); 1287 1288 /// Returns the induction kind of Phi and record the step. This function may 1289 /// return NoInduction if the PHI is not an induction variable. 1290 InductionKind isInductionVariable(PHINode *Phi, ConstantInt *&StepValue); 1291 1292 /// \brief Collect memory access with loop invariant strides. 1293 /// 1294 /// Looks for accesses like "a[i * StrideA]" where "StrideA" is loop 1295 /// invariant. 1296 void collectStridedAccess(Value *LoadOrStoreInst); 1297 1298 /// Report an analysis message to assist the user in diagnosing loops that are 1299 /// not vectorized. These are handled as LoopAccessReport rather than 1300 /// VectorizationReport because the << operator of VectorizationReport returns 1301 /// LoopAccessReport. 1302 void emitAnalysis(const LoopAccessReport &Message) const { 1303 emitAnalysisDiag(TheFunction, TheLoop, *Hints, Message); 1304 } 1305 1306 unsigned NumPredStores; 1307 1308 /// The loop that we evaluate. 1309 Loop *TheLoop; 1310 /// Scev analysis. 1311 ScalarEvolution *SE; 1312 /// Target Library Info. 1313 TargetLibraryInfo *TLI; 1314 /// Parent function 1315 Function *TheFunction; 1316 /// Target Transform Info 1317 const TargetTransformInfo *TTI; 1318 /// Dominator Tree. 1319 DominatorTree *DT; 1320 // LoopAccess analysis. 1321 LoopAccessAnalysis *LAA; 1322 // And the loop-accesses info corresponding to this loop. This pointer is 1323 // null until canVectorizeMemory sets it up. 1324 const LoopAccessInfo *LAI; 1325 1326 /// The interleave access information contains groups of interleaved accesses 1327 /// with the same stride and close to each other. 1328 InterleavedAccessInfo InterleaveInfo; 1329 1330 // --- vectorization state --- // 1331 1332 /// Holds the integer induction variable. This is the counter of the 1333 /// loop. 1334 PHINode *Induction; 1335 /// Holds the reduction variables. 1336 ReductionList Reductions; 1337 /// Holds all of the induction variables that we found in the loop. 1338 /// Notice that inductions don't need to start at zero and that induction 1339 /// variables can be pointers. 1340 InductionList Inductions; 1341 /// Holds the widest induction type encountered. 1342 Type *WidestIndTy; 1343 1344 /// Allowed outside users. This holds the reduction 1345 /// vars which can be accessed from outside the loop. 1346 SmallPtrSet<Value*, 4> AllowedExit; 1347 /// This set holds the variables which are known to be uniform after 1348 /// vectorization. 1349 SmallPtrSet<Instruction*, 4> Uniforms; 1350 1351 /// Can we assume the absence of NaNs. 1352 bool HasFunNoNaNAttr; 1353 1354 /// Vectorization requirements that will go through late-evaluation. 1355 LoopVectorizationRequirements *Requirements; 1356 1357 /// Used to emit an analysis of any legality issues. 1358 const LoopVectorizeHints *Hints; 1359 1360 ValueToValueMap Strides; 1361 SmallPtrSet<Value *, 8> StrideSet; 1362 1363 /// While vectorizing these instructions we have to generate a 1364 /// call to the appropriate masked intrinsic 1365 SmallPtrSet<const Instruction*, 8> MaskedOp; 1366 }; 1367 1368 /// LoopVectorizationCostModel - estimates the expected speedups due to 1369 /// vectorization. 1370 /// In many cases vectorization is not profitable. This can happen because of 1371 /// a number of reasons. In this class we mainly attempt to predict the 1372 /// expected speedup/slowdowns due to the supported instruction set. We use the 1373 /// TargetTransformInfo to query the different backends for the cost of 1374 /// different operations. 1375 class LoopVectorizationCostModel { 1376 public: 1377 LoopVectorizationCostModel(Loop *L, ScalarEvolution *SE, LoopInfo *LI, 1378 LoopVectorizationLegality *Legal, 1379 const TargetTransformInfo &TTI, 1380 const TargetLibraryInfo *TLI, AssumptionCache *AC, 1381 const Function *F, const LoopVectorizeHints *Hints) 1382 : TheLoop(L), SE(SE), LI(LI), Legal(Legal), TTI(TTI), TLI(TLI), 1383 TheFunction(F), Hints(Hints) { 1384 CodeMetrics::collectEphemeralValues(L, AC, EphValues); 1385 } 1386 1387 /// Information about vectorization costs 1388 struct VectorizationFactor { 1389 unsigned Width; // Vector width with best cost 1390 unsigned Cost; // Cost of the loop with that width 1391 }; 1392 /// \return The most profitable vectorization factor and the cost of that VF. 1393 /// This method checks every power of two up to VF. If UserVF is not ZERO 1394 /// then this vectorization factor will be selected if vectorization is 1395 /// possible. 1396 VectorizationFactor selectVectorizationFactor(bool OptForSize); 1397 1398 /// \return The size (in bits) of the widest type in the code that 1399 /// needs to be vectorized. We ignore values that remain scalar such as 1400 /// 64 bit loop indices. 1401 unsigned getWidestType(); 1402 1403 /// \return The desired interleave count. 1404 /// If interleave count has been specified by metadata it will be returned. 1405 /// Otherwise, the interleave count is computed and returned. VF and LoopCost 1406 /// are the selected vectorization factor and the cost of the selected VF. 1407 unsigned selectInterleaveCount(bool OptForSize, unsigned VF, 1408 unsigned LoopCost); 1409 1410 /// \return The most profitable unroll factor. 1411 /// This method finds the best unroll-factor based on register pressure and 1412 /// other parameters. VF and LoopCost are the selected vectorization factor 1413 /// and the cost of the selected VF. 1414 unsigned computeInterleaveCount(bool OptForSize, unsigned VF, 1415 unsigned LoopCost); 1416 1417 /// \brief A struct that represents some properties of the register usage 1418 /// of a loop. 1419 struct RegisterUsage { 1420 /// Holds the number of loop invariant values that are used in the loop. 1421 unsigned LoopInvariantRegs; 1422 /// Holds the maximum number of concurrent live intervals in the loop. 1423 unsigned MaxLocalUsers; 1424 /// Holds the number of instructions in the loop. 1425 unsigned NumInstructions; 1426 }; 1427 1428 /// \return information about the register usage of the loop. 1429 RegisterUsage calculateRegisterUsage(); 1430 1431 private: 1432 /// Returns the expected execution cost. The unit of the cost does 1433 /// not matter because we use the 'cost' units to compare different 1434 /// vector widths. The cost that is returned is *not* normalized by 1435 /// the factor width. 1436 unsigned expectedCost(unsigned VF); 1437 1438 /// Returns the execution time cost of an instruction for a given vector 1439 /// width. Vector width of one means scalar. 1440 unsigned getInstructionCost(Instruction *I, unsigned VF); 1441 1442 /// Returns whether the instruction is a load or store and will be a emitted 1443 /// as a vector operation. 1444 bool isConsecutiveLoadOrStore(Instruction *I); 1445 1446 /// Report an analysis message to assist the user in diagnosing loops that are 1447 /// not vectorized. These are handled as LoopAccessReport rather than 1448 /// VectorizationReport because the << operator of VectorizationReport returns 1449 /// LoopAccessReport. 1450 void emitAnalysis(const LoopAccessReport &Message) const { 1451 emitAnalysisDiag(TheFunction, TheLoop, *Hints, Message); 1452 } 1453 1454 /// Values used only by @llvm.assume calls. 1455 SmallPtrSet<const Value *, 32> EphValues; 1456 1457 /// The loop that we evaluate. 1458 Loop *TheLoop; 1459 /// Scev analysis. 1460 ScalarEvolution *SE; 1461 /// Loop Info analysis. 1462 LoopInfo *LI; 1463 /// Vectorization legality. 1464 LoopVectorizationLegality *Legal; 1465 /// Vector target information. 1466 const TargetTransformInfo &TTI; 1467 /// Target Library Info. 1468 const TargetLibraryInfo *TLI; 1469 const Function *TheFunction; 1470 // Loop Vectorize Hint. 1471 const LoopVectorizeHints *Hints; 1472 }; 1473 1474 /// \brief This holds vectorization requirements that must be verified late in 1475 /// the process. The requirements are set by legalize and costmodel. Once 1476 /// vectorization has been determined to be possible and profitable the 1477 /// requirements can be verified by looking for metadata or compiler options. 1478 /// For example, some loops require FP commutativity which is only allowed if 1479 /// vectorization is explicitly specified or if the fast-math compiler option 1480 /// has been provided. 1481 /// Late evaluation of these requirements allows helpful diagnostics to be 1482 /// composed that tells the user what need to be done to vectorize the loop. For 1483 /// example, by specifying #pragma clang loop vectorize or -ffast-math. Late 1484 /// evaluation should be used only when diagnostics can generated that can be 1485 /// followed by a non-expert user. 1486 class LoopVectorizationRequirements { 1487 public: 1488 LoopVectorizationRequirements() 1489 : NumRuntimePointerChecks(0), UnsafeAlgebraInst(nullptr) {} 1490 1491 void addUnsafeAlgebraInst(Instruction *I) { 1492 // First unsafe algebra instruction. 1493 if (!UnsafeAlgebraInst) 1494 UnsafeAlgebraInst = I; 1495 } 1496 1497 void addRuntimePointerChecks(unsigned Num) { NumRuntimePointerChecks = Num; } 1498 1499 bool doesNotMeet(Function *F, Loop *L, const LoopVectorizeHints &Hints) { 1500 // If a loop hint is provided the diagnostic is always produced. 1501 const char *Name = Hints.isForced() ? DiagnosticInfo::AlwaysPrint : LV_NAME; 1502 bool Failed = false; 1503 if (UnsafeAlgebraInst && 1504 Hints.getForce() == LoopVectorizeHints::FK_Undefined && 1505 Hints.getWidth() == 0) { 1506 emitOptimizationRemarkAnalysisFPCommute( 1507 F->getContext(), Name, *F, UnsafeAlgebraInst->getDebugLoc(), 1508 VectorizationReport() << "vectorization requires changes in the " 1509 "order of operations, however IEEE 754 " 1510 "floating-point operations are not " 1511 "commutative"); 1512 Failed = true; 1513 } 1514 1515 if (NumRuntimePointerChecks > 1516 VectorizerParams::RuntimeMemoryCheckThreshold) { 1517 emitOptimizationRemarkAnalysisAliasing( 1518 F->getContext(), Name, *F, L->getStartLoc(), 1519 VectorizationReport() 1520 << "cannot prove pointers refer to independent arrays in memory. " 1521 "The loop requires " 1522 << NumRuntimePointerChecks 1523 << " runtime independence checks to vectorize the loop, but that " 1524 "would exceed the limit of " 1525 << VectorizerParams::RuntimeMemoryCheckThreshold << " checks"); 1526 DEBUG(dbgs() << "LV: Too many memory checks needed.\n"); 1527 Failed = true; 1528 } 1529 1530 return Failed; 1531 } 1532 1533 private: 1534 unsigned NumRuntimePointerChecks; 1535 Instruction *UnsafeAlgebraInst; 1536 }; 1537 1538 static void addInnerLoop(Loop &L, SmallVectorImpl<Loop *> &V) { 1539 if (L.empty()) 1540 return V.push_back(&L); 1541 1542 for (Loop *InnerL : L) 1543 addInnerLoop(*InnerL, V); 1544 } 1545 1546 /// The LoopVectorize Pass. 1547 struct LoopVectorize : public FunctionPass { 1548 /// Pass identification, replacement for typeid 1549 static char ID; 1550 1551 explicit LoopVectorize(bool NoUnrolling = false, bool AlwaysVectorize = true) 1552 : FunctionPass(ID), 1553 DisableUnrolling(NoUnrolling), 1554 AlwaysVectorize(AlwaysVectorize) { 1555 initializeLoopVectorizePass(*PassRegistry::getPassRegistry()); 1556 } 1557 1558 ScalarEvolution *SE; 1559 LoopInfo *LI; 1560 TargetTransformInfo *TTI; 1561 DominatorTree *DT; 1562 BlockFrequencyInfo *BFI; 1563 TargetLibraryInfo *TLI; 1564 AliasAnalysis *AA; 1565 AssumptionCache *AC; 1566 LoopAccessAnalysis *LAA; 1567 bool DisableUnrolling; 1568 bool AlwaysVectorize; 1569 1570 BlockFrequency ColdEntryFreq; 1571 1572 bool runOnFunction(Function &F) override { 1573 SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 1574 LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 1575 TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F); 1576 DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 1577 BFI = &getAnalysis<BlockFrequencyInfoWrapperPass>().getBFI(); 1578 auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>(); 1579 TLI = TLIP ? &TLIP->getTLI() : nullptr; 1580 AA = &getAnalysis<AliasAnalysis>(); 1581 AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F); 1582 LAA = &getAnalysis<LoopAccessAnalysis>(); 1583 1584 // Compute some weights outside of the loop over the loops. Compute this 1585 // using a BranchProbability to re-use its scaling math. 1586 const BranchProbability ColdProb(1, 5); // 20% 1587 ColdEntryFreq = BlockFrequency(BFI->getEntryFreq()) * ColdProb; 1588 1589 // Don't attempt if 1590 // 1. the target claims to have no vector registers, and 1591 // 2. interleaving won't help ILP. 1592 // 1593 // The second condition is necessary because, even if the target has no 1594 // vector registers, loop vectorization may still enable scalar 1595 // interleaving. 1596 if (!TTI->getNumberOfRegisters(true) && TTI->getMaxInterleaveFactor(1) < 2) 1597 return false; 1598 1599 // Build up a worklist of inner-loops to vectorize. This is necessary as 1600 // the act of vectorizing or partially unrolling a loop creates new loops 1601 // and can invalidate iterators across the loops. 1602 SmallVector<Loop *, 8> Worklist; 1603 1604 for (Loop *L : *LI) 1605 addInnerLoop(*L, Worklist); 1606 1607 LoopsAnalyzed += Worklist.size(); 1608 1609 // Now walk the identified inner loops. 1610 bool Changed = false; 1611 while (!Worklist.empty()) 1612 Changed |= processLoop(Worklist.pop_back_val()); 1613 1614 // Process each loop nest in the function. 1615 return Changed; 1616 } 1617 1618 static void AddRuntimeUnrollDisableMetaData(Loop *L) { 1619 SmallVector<Metadata *, 4> MDs; 1620 // Reserve first location for self reference to the LoopID metadata node. 1621 MDs.push_back(nullptr); 1622 bool IsUnrollMetadata = false; 1623 MDNode *LoopID = L->getLoopID(); 1624 if (LoopID) { 1625 // First find existing loop unrolling disable metadata. 1626 for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) { 1627 MDNode *MD = dyn_cast<MDNode>(LoopID->getOperand(i)); 1628 if (MD) { 1629 const MDString *S = dyn_cast<MDString>(MD->getOperand(0)); 1630 IsUnrollMetadata = 1631 S && S->getString().startswith("llvm.loop.unroll.disable"); 1632 } 1633 MDs.push_back(LoopID->getOperand(i)); 1634 } 1635 } 1636 1637 if (!IsUnrollMetadata) { 1638 // Add runtime unroll disable metadata. 1639 LLVMContext &Context = L->getHeader()->getContext(); 1640 SmallVector<Metadata *, 1> DisableOperands; 1641 DisableOperands.push_back( 1642 MDString::get(Context, "llvm.loop.unroll.runtime.disable")); 1643 MDNode *DisableNode = MDNode::get(Context, DisableOperands); 1644 MDs.push_back(DisableNode); 1645 MDNode *NewLoopID = MDNode::get(Context, MDs); 1646 // Set operand 0 to refer to the loop id itself. 1647 NewLoopID->replaceOperandWith(0, NewLoopID); 1648 L->setLoopID(NewLoopID); 1649 } 1650 } 1651 1652 bool processLoop(Loop *L) { 1653 assert(L->empty() && "Only process inner loops."); 1654 1655 #ifndef NDEBUG 1656 const std::string DebugLocStr = getDebugLocString(L); 1657 #endif /* NDEBUG */ 1658 1659 DEBUG(dbgs() << "\nLV: Checking a loop in \"" 1660 << L->getHeader()->getParent()->getName() << "\" from " 1661 << DebugLocStr << "\n"); 1662 1663 LoopVectorizeHints Hints(L, DisableUnrolling); 1664 1665 DEBUG(dbgs() << "LV: Loop hints:" 1666 << " force=" 1667 << (Hints.getForce() == LoopVectorizeHints::FK_Disabled 1668 ? "disabled" 1669 : (Hints.getForce() == LoopVectorizeHints::FK_Enabled 1670 ? "enabled" 1671 : "?")) << " width=" << Hints.getWidth() 1672 << " unroll=" << Hints.getInterleave() << "\n"); 1673 1674 // Function containing loop 1675 Function *F = L->getHeader()->getParent(); 1676 1677 // Looking at the diagnostic output is the only way to determine if a loop 1678 // was vectorized (other than looking at the IR or machine code), so it 1679 // is important to generate an optimization remark for each loop. Most of 1680 // these messages are generated by emitOptimizationRemarkAnalysis. Remarks 1681 // generated by emitOptimizationRemark and emitOptimizationRemarkMissed are 1682 // less verbose reporting vectorized loops and unvectorized loops that may 1683 // benefit from vectorization, respectively. 1684 1685 if (!Hints.allowVectorization(F, L, AlwaysVectorize)) { 1686 DEBUG(dbgs() << "LV: Loop hints prevent vectorization.\n"); 1687 return false; 1688 } 1689 1690 // Check the loop for a trip count threshold: 1691 // do not vectorize loops with a tiny trip count. 1692 const unsigned TC = SE->getSmallConstantTripCount(L); 1693 if (TC > 0u && TC < TinyTripCountVectorThreshold) { 1694 DEBUG(dbgs() << "LV: Found a loop with a very small trip count. " 1695 << "This loop is not worth vectorizing."); 1696 if (Hints.getForce() == LoopVectorizeHints::FK_Enabled) 1697 DEBUG(dbgs() << " But vectorizing was explicitly forced.\n"); 1698 else { 1699 DEBUG(dbgs() << "\n"); 1700 emitAnalysisDiag(F, L, Hints, VectorizationReport() 1701 << "vectorization is not beneficial " 1702 "and is not explicitly forced"); 1703 return false; 1704 } 1705 } 1706 1707 // Check if it is legal to vectorize the loop. 1708 LoopVectorizationRequirements Requirements; 1709 LoopVectorizationLegality LVL(L, SE, DT, TLI, AA, F, TTI, LAA, 1710 &Requirements, &Hints); 1711 if (!LVL.canVectorize()) { 1712 DEBUG(dbgs() << "LV: Not vectorizing: Cannot prove legality.\n"); 1713 emitMissedWarning(F, L, Hints); 1714 return false; 1715 } 1716 1717 // Use the cost model. 1718 LoopVectorizationCostModel CM(L, SE, LI, &LVL, *TTI, TLI, AC, F, &Hints); 1719 1720 // Check the function attributes to find out if this function should be 1721 // optimized for size. 1722 bool OptForSize = Hints.getForce() != LoopVectorizeHints::FK_Enabled && 1723 F->optForSize(); 1724 1725 // Compute the weighted frequency of this loop being executed and see if it 1726 // is less than 20% of the function entry baseline frequency. Note that we 1727 // always have a canonical loop here because we think we *can* vectorize. 1728 // FIXME: This is hidden behind a flag due to pervasive problems with 1729 // exactly what block frequency models. 1730 if (LoopVectorizeWithBlockFrequency) { 1731 BlockFrequency LoopEntryFreq = BFI->getBlockFreq(L->getLoopPreheader()); 1732 if (Hints.getForce() != LoopVectorizeHints::FK_Enabled && 1733 LoopEntryFreq < ColdEntryFreq) 1734 OptForSize = true; 1735 } 1736 1737 // Check the function attributes to see if implicit floats are allowed. 1738 // FIXME: This check doesn't seem possibly correct -- what if the loop is 1739 // an integer loop and the vector instructions selected are purely integer 1740 // vector instructions? 1741 if (F->hasFnAttribute(Attribute::NoImplicitFloat)) { 1742 DEBUG(dbgs() << "LV: Can't vectorize when the NoImplicitFloat" 1743 "attribute is used.\n"); 1744 emitAnalysisDiag( 1745 F, L, Hints, 1746 VectorizationReport() 1747 << "loop not vectorized due to NoImplicitFloat attribute"); 1748 emitMissedWarning(F, L, Hints); 1749 return false; 1750 } 1751 1752 // Select the optimal vectorization factor. 1753 const LoopVectorizationCostModel::VectorizationFactor VF = 1754 CM.selectVectorizationFactor(OptForSize); 1755 1756 // Select the interleave count. 1757 unsigned IC = CM.selectInterleaveCount(OptForSize, VF.Width, VF.Cost); 1758 1759 // Get user interleave count. 1760 unsigned UserIC = Hints.getInterleave(); 1761 1762 // Identify the diagnostic messages that should be produced. 1763 std::string VecDiagMsg, IntDiagMsg; 1764 bool VectorizeLoop = true, InterleaveLoop = true; 1765 1766 if (Requirements.doesNotMeet(F, L, Hints)) { 1767 DEBUG(dbgs() << "LV: Not vectorizing: loop did not meet vectorization " 1768 "requirements.\n"); 1769 emitMissedWarning(F, L, Hints); 1770 return false; 1771 } 1772 1773 if (VF.Width == 1) { 1774 DEBUG(dbgs() << "LV: Vectorization is possible but not beneficial.\n"); 1775 VecDiagMsg = 1776 "the cost-model indicates that vectorization is not beneficial"; 1777 VectorizeLoop = false; 1778 } 1779 1780 if (IC == 1 && UserIC <= 1) { 1781 // Tell the user interleaving is not beneficial. 1782 DEBUG(dbgs() << "LV: Interleaving is not beneficial.\n"); 1783 IntDiagMsg = 1784 "the cost-model indicates that interleaving is not beneficial"; 1785 InterleaveLoop = false; 1786 if (UserIC == 1) 1787 IntDiagMsg += 1788 " and is explicitly disabled or interleave count is set to 1"; 1789 } else if (IC > 1 && UserIC == 1) { 1790 // Tell the user interleaving is beneficial, but it explicitly disabled. 1791 DEBUG(dbgs() 1792 << "LV: Interleaving is beneficial but is explicitly disabled."); 1793 IntDiagMsg = "the cost-model indicates that interleaving is beneficial " 1794 "but is explicitly disabled or interleave count is set to 1"; 1795 InterleaveLoop = false; 1796 } 1797 1798 // Override IC if user provided an interleave count. 1799 IC = UserIC > 0 ? UserIC : IC; 1800 1801 // Emit diagnostic messages, if any. 1802 if (!VectorizeLoop && !InterleaveLoop) { 1803 // Do not vectorize or interleaving the loop. 1804 emitOptimizationRemarkAnalysis(F->getContext(), DEBUG_TYPE, *F, 1805 L->getStartLoc(), VecDiagMsg); 1806 emitOptimizationRemarkAnalysis(F->getContext(), DEBUG_TYPE, *F, 1807 L->getStartLoc(), IntDiagMsg); 1808 return false; 1809 } else if (!VectorizeLoop && InterleaveLoop) { 1810 DEBUG(dbgs() << "LV: Interleave Count is " << IC << '\n'); 1811 emitOptimizationRemarkAnalysis(F->getContext(), DEBUG_TYPE, *F, 1812 L->getStartLoc(), VecDiagMsg); 1813 } else if (VectorizeLoop && !InterleaveLoop) { 1814 DEBUG(dbgs() << "LV: Found a vectorizable loop (" << VF.Width << ") in " 1815 << DebugLocStr << '\n'); 1816 emitOptimizationRemarkAnalysis(F->getContext(), DEBUG_TYPE, *F, 1817 L->getStartLoc(), IntDiagMsg); 1818 } else if (VectorizeLoop && InterleaveLoop) { 1819 DEBUG(dbgs() << "LV: Found a vectorizable loop (" << VF.Width << ") in " 1820 << DebugLocStr << '\n'); 1821 DEBUG(dbgs() << "LV: Interleave Count is " << IC << '\n'); 1822 } 1823 1824 if (!VectorizeLoop) { 1825 assert(IC > 1 && "interleave count should not be 1 or 0"); 1826 // If we decided that it is not legal to vectorize the loop then 1827 // interleave it. 1828 InnerLoopUnroller Unroller(L, SE, LI, DT, TLI, TTI, IC); 1829 Unroller.vectorize(&LVL); 1830 1831 emitOptimizationRemark(F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(), 1832 Twine("interleaved loop (interleaved count: ") + 1833 Twine(IC) + ")"); 1834 } else { 1835 // If we decided that it is *legal* to vectorize the loop then do it. 1836 InnerLoopVectorizer LB(L, SE, LI, DT, TLI, TTI, VF.Width, IC); 1837 LB.vectorize(&LVL); 1838 ++LoopsVectorized; 1839 1840 // Add metadata to disable runtime unrolling scalar loop when there's no 1841 // runtime check about strides and memory. Because at this situation, 1842 // scalar loop is rarely used not worthy to be unrolled. 1843 if (!LB.IsSafetyChecksAdded()) 1844 AddRuntimeUnrollDisableMetaData(L); 1845 1846 // Report the vectorization decision. 1847 emitOptimizationRemark(F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(), 1848 Twine("vectorized loop (vectorization width: ") + 1849 Twine(VF.Width) + ", interleaved count: " + 1850 Twine(IC) + ")"); 1851 } 1852 1853 // Mark the loop as already vectorized to avoid vectorizing again. 1854 Hints.setAlreadyVectorized(); 1855 1856 DEBUG(verifyFunction(*L->getHeader()->getParent())); 1857 return true; 1858 } 1859 1860 void getAnalysisUsage(AnalysisUsage &AU) const override { 1861 AU.addRequired<AssumptionCacheTracker>(); 1862 AU.addRequiredID(LoopSimplifyID); 1863 AU.addRequiredID(LCSSAID); 1864 AU.addRequired<BlockFrequencyInfoWrapperPass>(); 1865 AU.addRequired<DominatorTreeWrapperPass>(); 1866 AU.addRequired<LoopInfoWrapperPass>(); 1867 AU.addRequired<ScalarEvolutionWrapperPass>(); 1868 AU.addRequired<TargetTransformInfoWrapperPass>(); 1869 AU.addRequired<AliasAnalysis>(); 1870 AU.addRequired<LoopAccessAnalysis>(); 1871 AU.addPreserved<LoopInfoWrapperPass>(); 1872 AU.addPreserved<DominatorTreeWrapperPass>(); 1873 AU.addPreserved<AliasAnalysis>(); 1874 } 1875 1876 }; 1877 1878 } // end anonymous namespace 1879 1880 //===----------------------------------------------------------------------===// 1881 // Implementation of LoopVectorizationLegality, InnerLoopVectorizer and 1882 // LoopVectorizationCostModel. 1883 //===----------------------------------------------------------------------===// 1884 1885 Value *InnerLoopVectorizer::getBroadcastInstrs(Value *V) { 1886 // We need to place the broadcast of invariant variables outside the loop. 1887 Instruction *Instr = dyn_cast<Instruction>(V); 1888 bool NewInstr = 1889 (Instr && std::find(LoopVectorBody.begin(), LoopVectorBody.end(), 1890 Instr->getParent()) != LoopVectorBody.end()); 1891 bool Invariant = OrigLoop->isLoopInvariant(V) && !NewInstr; 1892 1893 // Place the code for broadcasting invariant variables in the new preheader. 1894 IRBuilder<>::InsertPointGuard Guard(Builder); 1895 if (Invariant) 1896 Builder.SetInsertPoint(LoopVectorPreHeader->getTerminator()); 1897 1898 // Broadcast the scalar into all locations in the vector. 1899 Value *Shuf = Builder.CreateVectorSplat(VF, V, "broadcast"); 1900 1901 return Shuf; 1902 } 1903 1904 Value *InnerLoopVectorizer::getStepVector(Value *Val, int StartIdx, 1905 Value *Step) { 1906 assert(Val->getType()->isVectorTy() && "Must be a vector"); 1907 assert(Val->getType()->getScalarType()->isIntegerTy() && 1908 "Elem must be an integer"); 1909 assert(Step->getType() == Val->getType()->getScalarType() && 1910 "Step has wrong type"); 1911 // Create the types. 1912 Type *ITy = Val->getType()->getScalarType(); 1913 VectorType *Ty = cast<VectorType>(Val->getType()); 1914 int VLen = Ty->getNumElements(); 1915 SmallVector<Constant*, 8> Indices; 1916 1917 // Create a vector of consecutive numbers from zero to VF. 1918 for (int i = 0; i < VLen; ++i) 1919 Indices.push_back(ConstantInt::get(ITy, StartIdx + i)); 1920 1921 // Add the consecutive indices to the vector value. 1922 Constant *Cv = ConstantVector::get(Indices); 1923 assert(Cv->getType() == Val->getType() && "Invalid consecutive vec"); 1924 Step = Builder.CreateVectorSplat(VLen, Step); 1925 assert(Step->getType() == Val->getType() && "Invalid step vec"); 1926 // FIXME: The newly created binary instructions should contain nsw/nuw flags, 1927 // which can be found from the original scalar operations. 1928 Step = Builder.CreateMul(Cv, Step); 1929 return Builder.CreateAdd(Val, Step, "induction"); 1930 } 1931 1932 int LoopVectorizationLegality::isConsecutivePtr(Value *Ptr) { 1933 assert(Ptr->getType()->isPointerTy() && "Unexpected non-ptr"); 1934 // Make sure that the pointer does not point to structs. 1935 if (Ptr->getType()->getPointerElementType()->isAggregateType()) 1936 return 0; 1937 1938 // If this value is a pointer induction variable we know it is consecutive. 1939 PHINode *Phi = dyn_cast_or_null<PHINode>(Ptr); 1940 if (Phi && Inductions.count(Phi)) { 1941 InductionInfo II = Inductions[Phi]; 1942 return II.getConsecutiveDirection(); 1943 } 1944 1945 GetElementPtrInst *Gep = dyn_cast_or_null<GetElementPtrInst>(Ptr); 1946 if (!Gep) 1947 return 0; 1948 1949 unsigned NumOperands = Gep->getNumOperands(); 1950 Value *GpPtr = Gep->getPointerOperand(); 1951 // If this GEP value is a consecutive pointer induction variable and all of 1952 // the indices are constant then we know it is consecutive. We can 1953 Phi = dyn_cast<PHINode>(GpPtr); 1954 if (Phi && Inductions.count(Phi)) { 1955 1956 // Make sure that the pointer does not point to structs. 1957 PointerType *GepPtrType = cast<PointerType>(GpPtr->getType()); 1958 if (GepPtrType->getElementType()->isAggregateType()) 1959 return 0; 1960 1961 // Make sure that all of the index operands are loop invariant. 1962 for (unsigned i = 1; i < NumOperands; ++i) 1963 if (!SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop)) 1964 return 0; 1965 1966 InductionInfo II = Inductions[Phi]; 1967 return II.getConsecutiveDirection(); 1968 } 1969 1970 unsigned InductionOperand = getGEPInductionOperand(Gep); 1971 1972 // Check that all of the gep indices are uniform except for our induction 1973 // operand. 1974 for (unsigned i = 0; i != NumOperands; ++i) 1975 if (i != InductionOperand && 1976 !SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop)) 1977 return 0; 1978 1979 // We can emit wide load/stores only if the last non-zero index is the 1980 // induction variable. 1981 const SCEV *Last = nullptr; 1982 if (!Strides.count(Gep)) 1983 Last = SE->getSCEV(Gep->getOperand(InductionOperand)); 1984 else { 1985 // Because of the multiplication by a stride we can have a s/zext cast. 1986 // We are going to replace this stride by 1 so the cast is safe to ignore. 1987 // 1988 // %indvars.iv = phi i64 [ 0, %entry ], [ %indvars.iv.next, %for.body ] 1989 // %0 = trunc i64 %indvars.iv to i32 1990 // %mul = mul i32 %0, %Stride1 1991 // %idxprom = zext i32 %mul to i64 << Safe cast. 1992 // %arrayidx = getelementptr inbounds i32* %B, i64 %idxprom 1993 // 1994 Last = replaceSymbolicStrideSCEV(SE, Strides, 1995 Gep->getOperand(InductionOperand), Gep); 1996 if (const SCEVCastExpr *C = dyn_cast<SCEVCastExpr>(Last)) 1997 Last = 1998 (C->getSCEVType() == scSignExtend || C->getSCEVType() == scZeroExtend) 1999 ? C->getOperand() 2000 : Last; 2001 } 2002 if (const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Last)) { 2003 const SCEV *Step = AR->getStepRecurrence(*SE); 2004 2005 // The memory is consecutive because the last index is consecutive 2006 // and all other indices are loop invariant. 2007 if (Step->isOne()) 2008 return 1; 2009 if (Step->isAllOnesValue()) 2010 return -1; 2011 } 2012 2013 return 0; 2014 } 2015 2016 bool LoopVectorizationLegality::isUniform(Value *V) { 2017 return LAI->isUniform(V); 2018 } 2019 2020 InnerLoopVectorizer::VectorParts& 2021 InnerLoopVectorizer::getVectorValue(Value *V) { 2022 assert(V != Induction && "The new induction variable should not be used."); 2023 assert(!V->getType()->isVectorTy() && "Can't widen a vector"); 2024 2025 // If we have a stride that is replaced by one, do it here. 2026 if (Legal->hasStride(V)) 2027 V = ConstantInt::get(V->getType(), 1); 2028 2029 // If we have this scalar in the map, return it. 2030 if (WidenMap.has(V)) 2031 return WidenMap.get(V); 2032 2033 // If this scalar is unknown, assume that it is a constant or that it is 2034 // loop invariant. Broadcast V and save the value for future uses. 2035 Value *B = getBroadcastInstrs(V); 2036 return WidenMap.splat(V, B); 2037 } 2038 2039 Value *InnerLoopVectorizer::reverseVector(Value *Vec) { 2040 assert(Vec->getType()->isVectorTy() && "Invalid type"); 2041 SmallVector<Constant*, 8> ShuffleMask; 2042 for (unsigned i = 0; i < VF; ++i) 2043 ShuffleMask.push_back(Builder.getInt32(VF - i - 1)); 2044 2045 return Builder.CreateShuffleVector(Vec, UndefValue::get(Vec->getType()), 2046 ConstantVector::get(ShuffleMask), 2047 "reverse"); 2048 } 2049 2050 // Get a mask to interleave \p NumVec vectors into a wide vector. 2051 // I.e. <0, VF, VF*2, ..., VF*(NumVec-1), 1, VF+1, VF*2+1, ...> 2052 // E.g. For 2 interleaved vectors, if VF is 4, the mask is: 2053 // <0, 4, 1, 5, 2, 6, 3, 7> 2054 static Constant *getInterleavedMask(IRBuilder<> &Builder, unsigned VF, 2055 unsigned NumVec) { 2056 SmallVector<Constant *, 16> Mask; 2057 for (unsigned i = 0; i < VF; i++) 2058 for (unsigned j = 0; j < NumVec; j++) 2059 Mask.push_back(Builder.getInt32(j * VF + i)); 2060 2061 return ConstantVector::get(Mask); 2062 } 2063 2064 // Get the strided mask starting from index \p Start. 2065 // I.e. <Start, Start + Stride, ..., Start + Stride*(VF-1)> 2066 static Constant *getStridedMask(IRBuilder<> &Builder, unsigned Start, 2067 unsigned Stride, unsigned VF) { 2068 SmallVector<Constant *, 16> Mask; 2069 for (unsigned i = 0; i < VF; i++) 2070 Mask.push_back(Builder.getInt32(Start + i * Stride)); 2071 2072 return ConstantVector::get(Mask); 2073 } 2074 2075 // Get a mask of two parts: The first part consists of sequential integers 2076 // starting from 0, The second part consists of UNDEFs. 2077 // I.e. <0, 1, 2, ..., NumInt - 1, undef, ..., undef> 2078 static Constant *getSequentialMask(IRBuilder<> &Builder, unsigned NumInt, 2079 unsigned NumUndef) { 2080 SmallVector<Constant *, 16> Mask; 2081 for (unsigned i = 0; i < NumInt; i++) 2082 Mask.push_back(Builder.getInt32(i)); 2083 2084 Constant *Undef = UndefValue::get(Builder.getInt32Ty()); 2085 for (unsigned i = 0; i < NumUndef; i++) 2086 Mask.push_back(Undef); 2087 2088 return ConstantVector::get(Mask); 2089 } 2090 2091 // Concatenate two vectors with the same element type. The 2nd vector should 2092 // not have more elements than the 1st vector. If the 2nd vector has less 2093 // elements, extend it with UNDEFs. 2094 static Value *ConcatenateTwoVectors(IRBuilder<> &Builder, Value *V1, 2095 Value *V2) { 2096 VectorType *VecTy1 = dyn_cast<VectorType>(V1->getType()); 2097 VectorType *VecTy2 = dyn_cast<VectorType>(V2->getType()); 2098 assert(VecTy1 && VecTy2 && 2099 VecTy1->getScalarType() == VecTy2->getScalarType() && 2100 "Expect two vectors with the same element type"); 2101 2102 unsigned NumElts1 = VecTy1->getNumElements(); 2103 unsigned NumElts2 = VecTy2->getNumElements(); 2104 assert(NumElts1 >= NumElts2 && "Unexpect the first vector has less elements"); 2105 2106 if (NumElts1 > NumElts2) { 2107 // Extend with UNDEFs. 2108 Constant *ExtMask = 2109 getSequentialMask(Builder, NumElts2, NumElts1 - NumElts2); 2110 V2 = Builder.CreateShuffleVector(V2, UndefValue::get(VecTy2), ExtMask); 2111 } 2112 2113 Constant *Mask = getSequentialMask(Builder, NumElts1 + NumElts2, 0); 2114 return Builder.CreateShuffleVector(V1, V2, Mask); 2115 } 2116 2117 // Concatenate vectors in the given list. All vectors have the same type. 2118 static Value *ConcatenateVectors(IRBuilder<> &Builder, 2119 ArrayRef<Value *> InputList) { 2120 unsigned NumVec = InputList.size(); 2121 assert(NumVec > 1 && "Should be at least two vectors"); 2122 2123 SmallVector<Value *, 8> ResList; 2124 ResList.append(InputList.begin(), InputList.end()); 2125 do { 2126 SmallVector<Value *, 8> TmpList; 2127 for (unsigned i = 0; i < NumVec - 1; i += 2) { 2128 Value *V0 = ResList[i], *V1 = ResList[i + 1]; 2129 assert((V0->getType() == V1->getType() || i == NumVec - 2) && 2130 "Only the last vector may have a different type"); 2131 2132 TmpList.push_back(ConcatenateTwoVectors(Builder, V0, V1)); 2133 } 2134 2135 // Push the last vector if the total number of vectors is odd. 2136 if (NumVec % 2 != 0) 2137 TmpList.push_back(ResList[NumVec - 1]); 2138 2139 ResList = TmpList; 2140 NumVec = ResList.size(); 2141 } while (NumVec > 1); 2142 2143 return ResList[0]; 2144 } 2145 2146 // Try to vectorize the interleave group that \p Instr belongs to. 2147 // 2148 // E.g. Translate following interleaved load group (factor = 3): 2149 // for (i = 0; i < N; i+=3) { 2150 // R = Pic[i]; // Member of index 0 2151 // G = Pic[i+1]; // Member of index 1 2152 // B = Pic[i+2]; // Member of index 2 2153 // ... // do something to R, G, B 2154 // } 2155 // To: 2156 // %wide.vec = load <12 x i32> ; Read 4 tuples of R,G,B 2157 // %R.vec = shuffle %wide.vec, undef, <0, 3, 6, 9> ; R elements 2158 // %G.vec = shuffle %wide.vec, undef, <1, 4, 7, 10> ; G elements 2159 // %B.vec = shuffle %wide.vec, undef, <2, 5, 8, 11> ; B elements 2160 // 2161 // Or translate following interleaved store group (factor = 3): 2162 // for (i = 0; i < N; i+=3) { 2163 // ... do something to R, G, B 2164 // Pic[i] = R; // Member of index 0 2165 // Pic[i+1] = G; // Member of index 1 2166 // Pic[i+2] = B; // Member of index 2 2167 // } 2168 // To: 2169 // %R_G.vec = shuffle %R.vec, %G.vec, <0, 1, 2, ..., 7> 2170 // %B_U.vec = shuffle %B.vec, undef, <0, 1, 2, 3, u, u, u, u> 2171 // %interleaved.vec = shuffle %R_G.vec, %B_U.vec, 2172 // <0, 4, 8, 1, 5, 9, 2, 6, 10, 3, 7, 11> ; Interleave R,G,B elements 2173 // store <12 x i32> %interleaved.vec ; Write 4 tuples of R,G,B 2174 void InnerLoopVectorizer::vectorizeInterleaveGroup(Instruction *Instr) { 2175 const InterleaveGroup *Group = Legal->getInterleavedAccessGroup(Instr); 2176 assert(Group && "Fail to get an interleaved access group."); 2177 2178 // Skip if current instruction is not the insert position. 2179 if (Instr != Group->getInsertPos()) 2180 return; 2181 2182 LoadInst *LI = dyn_cast<LoadInst>(Instr); 2183 StoreInst *SI = dyn_cast<StoreInst>(Instr); 2184 Value *Ptr = LI ? LI->getPointerOperand() : SI->getPointerOperand(); 2185 2186 // Prepare for the vector type of the interleaved load/store. 2187 Type *ScalarTy = LI ? LI->getType() : SI->getValueOperand()->getType(); 2188 unsigned InterleaveFactor = Group->getFactor(); 2189 Type *VecTy = VectorType::get(ScalarTy, InterleaveFactor * VF); 2190 Type *PtrTy = VecTy->getPointerTo(Ptr->getType()->getPointerAddressSpace()); 2191 2192 // Prepare for the new pointers. 2193 setDebugLocFromInst(Builder, Ptr); 2194 VectorParts &PtrParts = getVectorValue(Ptr); 2195 SmallVector<Value *, 2> NewPtrs; 2196 unsigned Index = Group->getIndex(Instr); 2197 for (unsigned Part = 0; Part < UF; Part++) { 2198 // Extract the pointer for current instruction from the pointer vector. A 2199 // reverse access uses the pointer in the last lane. 2200 Value *NewPtr = Builder.CreateExtractElement( 2201 PtrParts[Part], 2202 Group->isReverse() ? Builder.getInt32(VF - 1) : Builder.getInt32(0)); 2203 2204 // Notice current instruction could be any index. Need to adjust the address 2205 // to the member of index 0. 2206 // 2207 // E.g. a = A[i+1]; // Member of index 1 (Current instruction) 2208 // b = A[i]; // Member of index 0 2209 // Current pointer is pointed to A[i+1], adjust it to A[i]. 2210 // 2211 // E.g. A[i+1] = a; // Member of index 1 2212 // A[i] = b; // Member of index 0 2213 // A[i+2] = c; // Member of index 2 (Current instruction) 2214 // Current pointer is pointed to A[i+2], adjust it to A[i]. 2215 NewPtr = Builder.CreateGEP(NewPtr, Builder.getInt32(-Index)); 2216 2217 // Cast to the vector pointer type. 2218 NewPtrs.push_back(Builder.CreateBitCast(NewPtr, PtrTy)); 2219 } 2220 2221 setDebugLocFromInst(Builder, Instr); 2222 Value *UndefVec = UndefValue::get(VecTy); 2223 2224 // Vectorize the interleaved load group. 2225 if (LI) { 2226 for (unsigned Part = 0; Part < UF; Part++) { 2227 Instruction *NewLoadInstr = Builder.CreateAlignedLoad( 2228 NewPtrs[Part], Group->getAlignment(), "wide.vec"); 2229 2230 for (unsigned i = 0; i < InterleaveFactor; i++) { 2231 Instruction *Member = Group->getMember(i); 2232 2233 // Skip the gaps in the group. 2234 if (!Member) 2235 continue; 2236 2237 Constant *StrideMask = getStridedMask(Builder, i, InterleaveFactor, VF); 2238 Value *StridedVec = Builder.CreateShuffleVector( 2239 NewLoadInstr, UndefVec, StrideMask, "strided.vec"); 2240 2241 // If this member has different type, cast the result type. 2242 if (Member->getType() != ScalarTy) { 2243 VectorType *OtherVTy = VectorType::get(Member->getType(), VF); 2244 StridedVec = Builder.CreateBitOrPointerCast(StridedVec, OtherVTy); 2245 } 2246 2247 VectorParts &Entry = WidenMap.get(Member); 2248 Entry[Part] = 2249 Group->isReverse() ? reverseVector(StridedVec) : StridedVec; 2250 } 2251 2252 propagateMetadata(NewLoadInstr, Instr); 2253 } 2254 return; 2255 } 2256 2257 // The sub vector type for current instruction. 2258 VectorType *SubVT = VectorType::get(ScalarTy, VF); 2259 2260 // Vectorize the interleaved store group. 2261 for (unsigned Part = 0; Part < UF; Part++) { 2262 // Collect the stored vector from each member. 2263 SmallVector<Value *, 4> StoredVecs; 2264 for (unsigned i = 0; i < InterleaveFactor; i++) { 2265 // Interleaved store group doesn't allow a gap, so each index has a member 2266 Instruction *Member = Group->getMember(i); 2267 assert(Member && "Fail to get a member from an interleaved store group"); 2268 2269 Value *StoredVec = 2270 getVectorValue(dyn_cast<StoreInst>(Member)->getValueOperand())[Part]; 2271 if (Group->isReverse()) 2272 StoredVec = reverseVector(StoredVec); 2273 2274 // If this member has different type, cast it to an unified type. 2275 if (StoredVec->getType() != SubVT) 2276 StoredVec = Builder.CreateBitOrPointerCast(StoredVec, SubVT); 2277 2278 StoredVecs.push_back(StoredVec); 2279 } 2280 2281 // Concatenate all vectors into a wide vector. 2282 Value *WideVec = ConcatenateVectors(Builder, StoredVecs); 2283 2284 // Interleave the elements in the wide vector. 2285 Constant *IMask = getInterleavedMask(Builder, VF, InterleaveFactor); 2286 Value *IVec = Builder.CreateShuffleVector(WideVec, UndefVec, IMask, 2287 "interleaved.vec"); 2288 2289 Instruction *NewStoreInstr = 2290 Builder.CreateAlignedStore(IVec, NewPtrs[Part], Group->getAlignment()); 2291 propagateMetadata(NewStoreInstr, Instr); 2292 } 2293 } 2294 2295 void InnerLoopVectorizer::vectorizeMemoryInstruction(Instruction *Instr) { 2296 // Attempt to issue a wide load. 2297 LoadInst *LI = dyn_cast<LoadInst>(Instr); 2298 StoreInst *SI = dyn_cast<StoreInst>(Instr); 2299 2300 assert((LI || SI) && "Invalid Load/Store instruction"); 2301 2302 // Try to vectorize the interleave group if this access is interleaved. 2303 if (Legal->isAccessInterleaved(Instr)) 2304 return vectorizeInterleaveGroup(Instr); 2305 2306 Type *ScalarDataTy = LI ? LI->getType() : SI->getValueOperand()->getType(); 2307 Type *DataTy = VectorType::get(ScalarDataTy, VF); 2308 Value *Ptr = LI ? LI->getPointerOperand() : SI->getPointerOperand(); 2309 unsigned Alignment = LI ? LI->getAlignment() : SI->getAlignment(); 2310 // An alignment of 0 means target abi alignment. We need to use the scalar's 2311 // target abi alignment in such a case. 2312 const DataLayout &DL = Instr->getModule()->getDataLayout(); 2313 if (!Alignment) 2314 Alignment = DL.getABITypeAlignment(ScalarDataTy); 2315 unsigned AddressSpace = Ptr->getType()->getPointerAddressSpace(); 2316 unsigned ScalarAllocatedSize = DL.getTypeAllocSize(ScalarDataTy); 2317 unsigned VectorElementSize = DL.getTypeStoreSize(DataTy) / VF; 2318 2319 if (SI && Legal->blockNeedsPredication(SI->getParent()) && 2320 !Legal->isMaskRequired(SI)) 2321 return scalarizeInstruction(Instr, true); 2322 2323 if (ScalarAllocatedSize != VectorElementSize) 2324 return scalarizeInstruction(Instr); 2325 2326 // If the pointer is loop invariant or if it is non-consecutive, 2327 // scalarize the load. 2328 int ConsecutiveStride = Legal->isConsecutivePtr(Ptr); 2329 bool Reverse = ConsecutiveStride < 0; 2330 bool UniformLoad = LI && Legal->isUniform(Ptr); 2331 if (!ConsecutiveStride || UniformLoad) 2332 return scalarizeInstruction(Instr); 2333 2334 Constant *Zero = Builder.getInt32(0); 2335 VectorParts &Entry = WidenMap.get(Instr); 2336 2337 // Handle consecutive loads/stores. 2338 GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr); 2339 if (Gep && Legal->isInductionVariable(Gep->getPointerOperand())) { 2340 setDebugLocFromInst(Builder, Gep); 2341 Value *PtrOperand = Gep->getPointerOperand(); 2342 Value *FirstBasePtr = getVectorValue(PtrOperand)[0]; 2343 FirstBasePtr = Builder.CreateExtractElement(FirstBasePtr, Zero); 2344 2345 // Create the new GEP with the new induction variable. 2346 GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone()); 2347 Gep2->setOperand(0, FirstBasePtr); 2348 Gep2->setName("gep.indvar.base"); 2349 Ptr = Builder.Insert(Gep2); 2350 } else if (Gep) { 2351 setDebugLocFromInst(Builder, Gep); 2352 assert(SE->isLoopInvariant(SE->getSCEV(Gep->getPointerOperand()), 2353 OrigLoop) && "Base ptr must be invariant"); 2354 2355 // The last index does not have to be the induction. It can be 2356 // consecutive and be a function of the index. For example A[I+1]; 2357 unsigned NumOperands = Gep->getNumOperands(); 2358 unsigned InductionOperand = getGEPInductionOperand(Gep); 2359 // Create the new GEP with the new induction variable. 2360 GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone()); 2361 2362 for (unsigned i = 0; i < NumOperands; ++i) { 2363 Value *GepOperand = Gep->getOperand(i); 2364 Instruction *GepOperandInst = dyn_cast<Instruction>(GepOperand); 2365 2366 // Update last index or loop invariant instruction anchored in loop. 2367 if (i == InductionOperand || 2368 (GepOperandInst && OrigLoop->contains(GepOperandInst))) { 2369 assert((i == InductionOperand || 2370 SE->isLoopInvariant(SE->getSCEV(GepOperandInst), OrigLoop)) && 2371 "Must be last index or loop invariant"); 2372 2373 VectorParts &GEPParts = getVectorValue(GepOperand); 2374 Value *Index = GEPParts[0]; 2375 Index = Builder.CreateExtractElement(Index, Zero); 2376 Gep2->setOperand(i, Index); 2377 Gep2->setName("gep.indvar.idx"); 2378 } 2379 } 2380 Ptr = Builder.Insert(Gep2); 2381 } else { 2382 // Use the induction element ptr. 2383 assert(isa<PHINode>(Ptr) && "Invalid induction ptr"); 2384 setDebugLocFromInst(Builder, Ptr); 2385 VectorParts &PtrVal = getVectorValue(Ptr); 2386 Ptr = Builder.CreateExtractElement(PtrVal[0], Zero); 2387 } 2388 2389 VectorParts Mask = createBlockInMask(Instr->getParent()); 2390 // Handle Stores: 2391 if (SI) { 2392 assert(!Legal->isUniform(SI->getPointerOperand()) && 2393 "We do not allow storing to uniform addresses"); 2394 setDebugLocFromInst(Builder, SI); 2395 // We don't want to update the value in the map as it might be used in 2396 // another expression. So don't use a reference type for "StoredVal". 2397 VectorParts StoredVal = getVectorValue(SI->getValueOperand()); 2398 2399 for (unsigned Part = 0; Part < UF; ++Part) { 2400 // Calculate the pointer for the specific unroll-part. 2401 Value *PartPtr = 2402 Builder.CreateGEP(nullptr, Ptr, Builder.getInt32(Part * VF)); 2403 2404 if (Reverse) { 2405 // If we store to reverse consecutive memory locations, then we need 2406 // to reverse the order of elements in the stored value. 2407 StoredVal[Part] = reverseVector(StoredVal[Part]); 2408 // If the address is consecutive but reversed, then the 2409 // wide store needs to start at the last vector element. 2410 PartPtr = Builder.CreateGEP(nullptr, Ptr, Builder.getInt32(-Part * VF)); 2411 PartPtr = Builder.CreateGEP(nullptr, PartPtr, Builder.getInt32(1 - VF)); 2412 Mask[Part] = reverseVector(Mask[Part]); 2413 } 2414 2415 Value *VecPtr = Builder.CreateBitCast(PartPtr, 2416 DataTy->getPointerTo(AddressSpace)); 2417 2418 Instruction *NewSI; 2419 if (Legal->isMaskRequired(SI)) 2420 NewSI = Builder.CreateMaskedStore(StoredVal[Part], VecPtr, Alignment, 2421 Mask[Part]); 2422 else 2423 NewSI = Builder.CreateAlignedStore(StoredVal[Part], VecPtr, Alignment); 2424 propagateMetadata(NewSI, SI); 2425 } 2426 return; 2427 } 2428 2429 // Handle loads. 2430 assert(LI && "Must have a load instruction"); 2431 setDebugLocFromInst(Builder, LI); 2432 for (unsigned Part = 0; Part < UF; ++Part) { 2433 // Calculate the pointer for the specific unroll-part. 2434 Value *PartPtr = 2435 Builder.CreateGEP(nullptr, Ptr, Builder.getInt32(Part * VF)); 2436 2437 if (Reverse) { 2438 // If the address is consecutive but reversed, then the 2439 // wide load needs to start at the last vector element. 2440 PartPtr = Builder.CreateGEP(nullptr, Ptr, Builder.getInt32(-Part * VF)); 2441 PartPtr = Builder.CreateGEP(nullptr, PartPtr, Builder.getInt32(1 - VF)); 2442 Mask[Part] = reverseVector(Mask[Part]); 2443 } 2444 2445 Instruction* NewLI; 2446 Value *VecPtr = Builder.CreateBitCast(PartPtr, 2447 DataTy->getPointerTo(AddressSpace)); 2448 if (Legal->isMaskRequired(LI)) 2449 NewLI = Builder.CreateMaskedLoad(VecPtr, Alignment, Mask[Part], 2450 UndefValue::get(DataTy), 2451 "wide.masked.load"); 2452 else 2453 NewLI = Builder.CreateAlignedLoad(VecPtr, Alignment, "wide.load"); 2454 propagateMetadata(NewLI, LI); 2455 Entry[Part] = Reverse ? reverseVector(NewLI) : NewLI; 2456 } 2457 } 2458 2459 void InnerLoopVectorizer::scalarizeInstruction(Instruction *Instr, bool IfPredicateStore) { 2460 assert(!Instr->getType()->isAggregateType() && "Can't handle vectors"); 2461 // Holds vector parameters or scalars, in case of uniform vals. 2462 SmallVector<VectorParts, 4> Params; 2463 2464 setDebugLocFromInst(Builder, Instr); 2465 2466 // Find all of the vectorized parameters. 2467 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) { 2468 Value *SrcOp = Instr->getOperand(op); 2469 2470 // If we are accessing the old induction variable, use the new one. 2471 if (SrcOp == OldInduction) { 2472 Params.push_back(getVectorValue(SrcOp)); 2473 continue; 2474 } 2475 2476 // Try using previously calculated values. 2477 Instruction *SrcInst = dyn_cast<Instruction>(SrcOp); 2478 2479 // If the src is an instruction that appeared earlier in the basic block, 2480 // then it should already be vectorized. 2481 if (SrcInst && OrigLoop->contains(SrcInst)) { 2482 assert(WidenMap.has(SrcInst) && "Source operand is unavailable"); 2483 // The parameter is a vector value from earlier. 2484 Params.push_back(WidenMap.get(SrcInst)); 2485 } else { 2486 // The parameter is a scalar from outside the loop. Maybe even a constant. 2487 VectorParts Scalars; 2488 Scalars.append(UF, SrcOp); 2489 Params.push_back(Scalars); 2490 } 2491 } 2492 2493 assert(Params.size() == Instr->getNumOperands() && 2494 "Invalid number of operands"); 2495 2496 // Does this instruction return a value ? 2497 bool IsVoidRetTy = Instr->getType()->isVoidTy(); 2498 2499 Value *UndefVec = IsVoidRetTy ? nullptr : 2500 UndefValue::get(VectorType::get(Instr->getType(), VF)); 2501 // Create a new entry in the WidenMap and initialize it to Undef or Null. 2502 VectorParts &VecResults = WidenMap.splat(Instr, UndefVec); 2503 2504 Instruction *InsertPt = Builder.GetInsertPoint(); 2505 BasicBlock *IfBlock = Builder.GetInsertBlock(); 2506 BasicBlock *CondBlock = nullptr; 2507 2508 VectorParts Cond; 2509 Loop *VectorLp = nullptr; 2510 if (IfPredicateStore) { 2511 assert(Instr->getParent()->getSinglePredecessor() && 2512 "Only support single predecessor blocks"); 2513 Cond = createEdgeMask(Instr->getParent()->getSinglePredecessor(), 2514 Instr->getParent()); 2515 VectorLp = LI->getLoopFor(IfBlock); 2516 assert(VectorLp && "Must have a loop for this block"); 2517 } 2518 2519 // For each vector unroll 'part': 2520 for (unsigned Part = 0; Part < UF; ++Part) { 2521 // For each scalar that we create: 2522 for (unsigned Width = 0; Width < VF; ++Width) { 2523 2524 // Start if-block. 2525 Value *Cmp = nullptr; 2526 if (IfPredicateStore) { 2527 Cmp = Builder.CreateExtractElement(Cond[Part], Builder.getInt32(Width)); 2528 Cmp = Builder.CreateICmp(ICmpInst::ICMP_EQ, Cmp, ConstantInt::get(Cmp->getType(), 1)); 2529 CondBlock = IfBlock->splitBasicBlock(InsertPt, "cond.store"); 2530 LoopVectorBody.push_back(CondBlock); 2531 VectorLp->addBasicBlockToLoop(CondBlock, *LI); 2532 // Update Builder with newly created basic block. 2533 Builder.SetInsertPoint(InsertPt); 2534 } 2535 2536 Instruction *Cloned = Instr->clone(); 2537 if (!IsVoidRetTy) 2538 Cloned->setName(Instr->getName() + ".cloned"); 2539 // Replace the operands of the cloned instructions with extracted scalars. 2540 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) { 2541 Value *Op = Params[op][Part]; 2542 // Param is a vector. Need to extract the right lane. 2543 if (Op->getType()->isVectorTy()) 2544 Op = Builder.CreateExtractElement(Op, Builder.getInt32(Width)); 2545 Cloned->setOperand(op, Op); 2546 } 2547 2548 // Place the cloned scalar in the new loop. 2549 Builder.Insert(Cloned); 2550 2551 // If the original scalar returns a value we need to place it in a vector 2552 // so that future users will be able to use it. 2553 if (!IsVoidRetTy) 2554 VecResults[Part] = Builder.CreateInsertElement(VecResults[Part], Cloned, 2555 Builder.getInt32(Width)); 2556 // End if-block. 2557 if (IfPredicateStore) { 2558 BasicBlock *NewIfBlock = CondBlock->splitBasicBlock(InsertPt, "else"); 2559 LoopVectorBody.push_back(NewIfBlock); 2560 VectorLp->addBasicBlockToLoop(NewIfBlock, *LI); 2561 Builder.SetInsertPoint(InsertPt); 2562 ReplaceInstWithInst(IfBlock->getTerminator(), 2563 BranchInst::Create(CondBlock, NewIfBlock, Cmp)); 2564 IfBlock = NewIfBlock; 2565 } 2566 } 2567 } 2568 } 2569 2570 static Instruction *getFirstInst(Instruction *FirstInst, Value *V, 2571 Instruction *Loc) { 2572 if (FirstInst) 2573 return FirstInst; 2574 if (Instruction *I = dyn_cast<Instruction>(V)) 2575 return I->getParent() == Loc->getParent() ? I : nullptr; 2576 return nullptr; 2577 } 2578 2579 std::pair<Instruction *, Instruction *> 2580 InnerLoopVectorizer::addStrideCheck(Instruction *Loc) { 2581 Instruction *tnullptr = nullptr; 2582 if (!Legal->mustCheckStrides()) 2583 return std::pair<Instruction *, Instruction *>(tnullptr, tnullptr); 2584 2585 IRBuilder<> ChkBuilder(Loc); 2586 2587 // Emit checks. 2588 Value *Check = nullptr; 2589 Instruction *FirstInst = nullptr; 2590 for (SmallPtrSet<Value *, 8>::iterator SI = Legal->strides_begin(), 2591 SE = Legal->strides_end(); 2592 SI != SE; ++SI) { 2593 Value *Ptr = stripIntegerCast(*SI); 2594 Value *C = ChkBuilder.CreateICmpNE(Ptr, ConstantInt::get(Ptr->getType(), 1), 2595 "stride.chk"); 2596 // Store the first instruction we create. 2597 FirstInst = getFirstInst(FirstInst, C, Loc); 2598 if (Check) 2599 Check = ChkBuilder.CreateOr(Check, C); 2600 else 2601 Check = C; 2602 } 2603 2604 // We have to do this trickery because the IRBuilder might fold the check to a 2605 // constant expression in which case there is no Instruction anchored in a 2606 // the block. 2607 LLVMContext &Ctx = Loc->getContext(); 2608 Instruction *TheCheck = 2609 BinaryOperator::CreateAnd(Check, ConstantInt::getTrue(Ctx)); 2610 ChkBuilder.Insert(TheCheck, "stride.not.one"); 2611 FirstInst = getFirstInst(FirstInst, TheCheck, Loc); 2612 2613 return std::make_pair(FirstInst, TheCheck); 2614 } 2615 2616 void InnerLoopVectorizer::createEmptyLoop() { 2617 /* 2618 In this function we generate a new loop. The new loop will contain 2619 the vectorized instructions while the old loop will continue to run the 2620 scalar remainder. 2621 2622 [ ] <-- Back-edge taken count overflow check. 2623 / | 2624 / v 2625 | [ ] <-- vector loop bypass (may consist of multiple blocks). 2626 | / | 2627 | / v 2628 || [ ] <-- vector pre header. 2629 || | 2630 || v 2631 || [ ] \ 2632 || [ ]_| <-- vector loop. 2633 || | 2634 | \ v 2635 | >[ ] <--- middle-block. 2636 | / | 2637 | / v 2638 -|- >[ ] <--- new preheader. 2639 | | 2640 | v 2641 | [ ] \ 2642 | [ ]_| <-- old scalar loop to handle remainder. 2643 \ | 2644 \ v 2645 >[ ] <-- exit block. 2646 ... 2647 */ 2648 2649 BasicBlock *OldBasicBlock = OrigLoop->getHeader(); 2650 BasicBlock *VectorPH = OrigLoop->getLoopPreheader(); 2651 BasicBlock *ExitBlock = OrigLoop->getExitBlock(); 2652 assert(VectorPH && "Invalid loop structure"); 2653 assert(ExitBlock && "Must have an exit block"); 2654 2655 // Some loops have a single integer induction variable, while other loops 2656 // don't. One example is c++ iterators that often have multiple pointer 2657 // induction variables. In the code below we also support a case where we 2658 // don't have a single induction variable. 2659 OldInduction = Legal->getInduction(); 2660 Type *IdxTy = Legal->getWidestInductionType(); 2661 2662 // Find the loop boundaries. 2663 const SCEV *ExitCount = SE->getBackedgeTakenCount(OrigLoop); 2664 assert(ExitCount != SE->getCouldNotCompute() && "Invalid loop count"); 2665 2666 // The exit count might have the type of i64 while the phi is i32. This can 2667 // happen if we have an induction variable that is sign extended before the 2668 // compare. The only way that we get a backedge taken count is that the 2669 // induction variable was signed and as such will not overflow. In such a case 2670 // truncation is legal. 2671 if (ExitCount->getType()->getPrimitiveSizeInBits() > 2672 IdxTy->getPrimitiveSizeInBits()) 2673 ExitCount = SE->getTruncateOrNoop(ExitCount, IdxTy); 2674 2675 const SCEV *BackedgeTakeCount = SE->getNoopOrZeroExtend(ExitCount, IdxTy); 2676 // Get the total trip count from the count by adding 1. 2677 ExitCount = SE->getAddExpr(BackedgeTakeCount, 2678 SE->getConstant(BackedgeTakeCount->getType(), 1)); 2679 2680 const DataLayout &DL = OldBasicBlock->getModule()->getDataLayout(); 2681 2682 // Expand the trip count and place the new instructions in the preheader. 2683 // Notice that the pre-header does not change, only the loop body. 2684 SCEVExpander Exp(*SE, DL, "induction"); 2685 2686 // We need to test whether the backedge-taken count is uint##_max. Adding one 2687 // to it will cause overflow and an incorrect loop trip count in the vector 2688 // body. In case of overflow we want to directly jump to the scalar remainder 2689 // loop. 2690 Value *BackedgeCount = 2691 Exp.expandCodeFor(BackedgeTakeCount, BackedgeTakeCount->getType(), 2692 VectorPH->getTerminator()); 2693 if (BackedgeCount->getType()->isPointerTy()) 2694 BackedgeCount = CastInst::CreatePointerCast(BackedgeCount, IdxTy, 2695 "backedge.ptrcnt.to.int", 2696 VectorPH->getTerminator()); 2697 Instruction *CheckBCOverflow = 2698 CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ, BackedgeCount, 2699 Constant::getAllOnesValue(BackedgeCount->getType()), 2700 "backedge.overflow", VectorPH->getTerminator()); 2701 2702 // The loop index does not have to start at Zero. Find the original start 2703 // value from the induction PHI node. If we don't have an induction variable 2704 // then we know that it starts at zero. 2705 Builder.SetInsertPoint(VectorPH->getTerminator()); 2706 Value *StartIdx = ExtendedIdx = 2707 OldInduction 2708 ? Builder.CreateZExt(OldInduction->getIncomingValueForBlock(VectorPH), 2709 IdxTy) 2710 : ConstantInt::get(IdxTy, 0); 2711 2712 // Count holds the overall loop count (N). 2713 Value *Count = Exp.expandCodeFor(ExitCount, ExitCount->getType(), 2714 VectorPH->getTerminator()); 2715 2716 LoopBypassBlocks.push_back(VectorPH); 2717 2718 // Split the single block loop into the two loop structure described above. 2719 BasicBlock *VecBody = 2720 VectorPH->splitBasicBlock(VectorPH->getTerminator(), "vector.body"); 2721 BasicBlock *MiddleBlock = 2722 VecBody->splitBasicBlock(VecBody->getTerminator(), "middle.block"); 2723 BasicBlock *ScalarPH = 2724 MiddleBlock->splitBasicBlock(MiddleBlock->getTerminator(), "scalar.ph"); 2725 2726 // Create and register the new vector loop. 2727 Loop* Lp = new Loop(); 2728 Loop *ParentLoop = OrigLoop->getParentLoop(); 2729 2730 // Insert the new loop into the loop nest and register the new basic blocks 2731 // before calling any utilities such as SCEV that require valid LoopInfo. 2732 if (ParentLoop) { 2733 ParentLoop->addChildLoop(Lp); 2734 ParentLoop->addBasicBlockToLoop(ScalarPH, *LI); 2735 ParentLoop->addBasicBlockToLoop(MiddleBlock, *LI); 2736 } else { 2737 LI->addTopLevelLoop(Lp); 2738 } 2739 Lp->addBasicBlockToLoop(VecBody, *LI); 2740 2741 // Use this IR builder to create the loop instructions (Phi, Br, Cmp) 2742 // inside the loop. 2743 Builder.SetInsertPoint(VecBody->getFirstNonPHI()); 2744 2745 // Generate the induction variable. 2746 setDebugLocFromInst(Builder, getDebugLocFromInstOrOperands(OldInduction)); 2747 Induction = Builder.CreatePHI(IdxTy, 2, "index"); 2748 // The loop step is equal to the vectorization factor (num of SIMD elements) 2749 // times the unroll factor (num of SIMD instructions). 2750 Constant *Step = ConstantInt::get(IdxTy, VF * UF); 2751 2752 // Generate code to check that the loop's trip count that we computed by 2753 // adding one to the backedge-taken count will not overflow. 2754 BasicBlock *NewVectorPH = 2755 VectorPH->splitBasicBlock(VectorPH->getTerminator(), "overflow.checked"); 2756 if (ParentLoop) 2757 ParentLoop->addBasicBlockToLoop(NewVectorPH, *LI); 2758 ReplaceInstWithInst( 2759 VectorPH->getTerminator(), 2760 BranchInst::Create(ScalarPH, NewVectorPH, CheckBCOverflow)); 2761 VectorPH = NewVectorPH; 2762 2763 // This is the IR builder that we use to add all of the logic for bypassing 2764 // the new vector loop. 2765 IRBuilder<> BypassBuilder(VectorPH->getTerminator()); 2766 setDebugLocFromInst(BypassBuilder, 2767 getDebugLocFromInstOrOperands(OldInduction)); 2768 2769 // We may need to extend the index in case there is a type mismatch. 2770 // We know that the count starts at zero and does not overflow. 2771 if (Count->getType() != IdxTy) { 2772 // The exit count can be of pointer type. Convert it to the correct 2773 // integer type. 2774 if (ExitCount->getType()->isPointerTy()) 2775 Count = BypassBuilder.CreatePointerCast(Count, IdxTy, "ptrcnt.to.int"); 2776 else 2777 Count = BypassBuilder.CreateZExtOrTrunc(Count, IdxTy, "cnt.cast"); 2778 } 2779 2780 // Add the start index to the loop count to get the new end index. 2781 Value *IdxEnd = BypassBuilder.CreateAdd(Count, StartIdx, "end.idx"); 2782 2783 // Now we need to generate the expression for N - (N % VF), which is 2784 // the part that the vectorized body will execute. 2785 Value *R = BypassBuilder.CreateURem(Count, Step, "n.mod.vf"); 2786 Value *CountRoundDown = BypassBuilder.CreateSub(Count, R, "n.vec"); 2787 Value *IdxEndRoundDown = BypassBuilder.CreateAdd(CountRoundDown, StartIdx, 2788 "end.idx.rnd.down"); 2789 2790 // Now, compare the new count to zero. If it is zero skip the vector loop and 2791 // jump to the scalar loop. 2792 Value *Cmp = 2793 BypassBuilder.CreateICmpEQ(IdxEndRoundDown, StartIdx, "cmp.zero"); 2794 NewVectorPH = 2795 VectorPH->splitBasicBlock(VectorPH->getTerminator(), "vector.ph"); 2796 if (ParentLoop) 2797 ParentLoop->addBasicBlockToLoop(NewVectorPH, *LI); 2798 LoopBypassBlocks.push_back(VectorPH); 2799 ReplaceInstWithInst(VectorPH->getTerminator(), 2800 BranchInst::Create(MiddleBlock, NewVectorPH, Cmp)); 2801 VectorPH = NewVectorPH; 2802 2803 // Generate the code to check that the strides we assumed to be one are really 2804 // one. We want the new basic block to start at the first instruction in a 2805 // sequence of instructions that form a check. 2806 Instruction *StrideCheck; 2807 Instruction *FirstCheckInst; 2808 std::tie(FirstCheckInst, StrideCheck) = 2809 addStrideCheck(VectorPH->getTerminator()); 2810 if (StrideCheck) { 2811 AddedSafetyChecks = true; 2812 // Create a new block containing the stride check. 2813 VectorPH->setName("vector.stridecheck"); 2814 NewVectorPH = 2815 VectorPH->splitBasicBlock(VectorPH->getTerminator(), "vector.ph"); 2816 if (ParentLoop) 2817 ParentLoop->addBasicBlockToLoop(NewVectorPH, *LI); 2818 LoopBypassBlocks.push_back(VectorPH); 2819 2820 // Replace the branch into the memory check block with a conditional branch 2821 // for the "few elements case". 2822 ReplaceInstWithInst( 2823 VectorPH->getTerminator(), 2824 BranchInst::Create(MiddleBlock, NewVectorPH, StrideCheck)); 2825 2826 VectorPH = NewVectorPH; 2827 } 2828 2829 // Generate the code that checks in runtime if arrays overlap. We put the 2830 // checks into a separate block to make the more common case of few elements 2831 // faster. 2832 Instruction *MemRuntimeCheck; 2833 std::tie(FirstCheckInst, MemRuntimeCheck) = 2834 Legal->getLAI()->addRuntimeChecks(VectorPH->getTerminator()); 2835 if (MemRuntimeCheck) { 2836 AddedSafetyChecks = true; 2837 // Create a new block containing the memory check. 2838 VectorPH->setName("vector.memcheck"); 2839 NewVectorPH = 2840 VectorPH->splitBasicBlock(VectorPH->getTerminator(), "vector.ph"); 2841 if (ParentLoop) 2842 ParentLoop->addBasicBlockToLoop(NewVectorPH, *LI); 2843 LoopBypassBlocks.push_back(VectorPH); 2844 2845 // Replace the branch into the memory check block with a conditional branch 2846 // for the "few elements case". 2847 ReplaceInstWithInst( 2848 VectorPH->getTerminator(), 2849 BranchInst::Create(MiddleBlock, NewVectorPH, MemRuntimeCheck)); 2850 2851 VectorPH = NewVectorPH; 2852 } 2853 2854 // We are going to resume the execution of the scalar loop. 2855 // Go over all of the induction variables that we found and fix the 2856 // PHIs that are left in the scalar version of the loop. 2857 // The starting values of PHI nodes depend on the counter of the last 2858 // iteration in the vectorized loop. 2859 // If we come from a bypass edge then we need to start from the original 2860 // start value. 2861 2862 // This variable saves the new starting index for the scalar loop. 2863 PHINode *ResumeIndex = nullptr; 2864 LoopVectorizationLegality::InductionList::iterator I, E; 2865 LoopVectorizationLegality::InductionList *List = Legal->getInductionVars(); 2866 // Set builder to point to last bypass block. 2867 BypassBuilder.SetInsertPoint(LoopBypassBlocks.back()->getTerminator()); 2868 for (I = List->begin(), E = List->end(); I != E; ++I) { 2869 PHINode *OrigPhi = I->first; 2870 LoopVectorizationLegality::InductionInfo II = I->second; 2871 2872 Type *ResumeValTy = (OrigPhi == OldInduction) ? IdxTy : OrigPhi->getType(); 2873 PHINode *ResumeVal = PHINode::Create(ResumeValTy, 2, "resume.val", 2874 MiddleBlock->getTerminator()); 2875 // We might have extended the type of the induction variable but we need a 2876 // truncated version for the scalar loop. 2877 PHINode *TruncResumeVal = (OrigPhi == OldInduction) ? 2878 PHINode::Create(OrigPhi->getType(), 2, "trunc.resume.val", 2879 MiddleBlock->getTerminator()) : nullptr; 2880 2881 // Create phi nodes to merge from the backedge-taken check block. 2882 PHINode *BCResumeVal = PHINode::Create(ResumeValTy, 3, "bc.resume.val", 2883 ScalarPH->getTerminator()); 2884 BCResumeVal->addIncoming(ResumeVal, MiddleBlock); 2885 2886 PHINode *BCTruncResumeVal = nullptr; 2887 if (OrigPhi == OldInduction) { 2888 BCTruncResumeVal = 2889 PHINode::Create(OrigPhi->getType(), 2, "bc.trunc.resume.val", 2890 ScalarPH->getTerminator()); 2891 BCTruncResumeVal->addIncoming(TruncResumeVal, MiddleBlock); 2892 } 2893 2894 Value *EndValue = nullptr; 2895 switch (II.IK) { 2896 case LoopVectorizationLegality::IK_NoInduction: 2897 llvm_unreachable("Unknown induction"); 2898 case LoopVectorizationLegality::IK_IntInduction: { 2899 // Handle the integer induction counter. 2900 assert(OrigPhi->getType()->isIntegerTy() && "Invalid type"); 2901 2902 // We have the canonical induction variable. 2903 if (OrigPhi == OldInduction) { 2904 // Create a truncated version of the resume value for the scalar loop, 2905 // we might have promoted the type to a larger width. 2906 EndValue = 2907 BypassBuilder.CreateTrunc(IdxEndRoundDown, OrigPhi->getType()); 2908 // The new PHI merges the original incoming value, in case of a bypass, 2909 // or the value at the end of the vectorized loop. 2910 for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I) 2911 TruncResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]); 2912 TruncResumeVal->addIncoming(EndValue, VecBody); 2913 2914 BCTruncResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[0]); 2915 2916 // We know what the end value is. 2917 EndValue = IdxEndRoundDown; 2918 // We also know which PHI node holds it. 2919 ResumeIndex = ResumeVal; 2920 break; 2921 } 2922 2923 // Not the canonical induction variable - add the vector loop count to the 2924 // start value. 2925 Value *CRD = BypassBuilder.CreateSExtOrTrunc(CountRoundDown, 2926 II.StartValue->getType(), 2927 "cast.crd"); 2928 EndValue = II.transform(BypassBuilder, CRD); 2929 EndValue->setName("ind.end"); 2930 break; 2931 } 2932 case LoopVectorizationLegality::IK_PtrInduction: { 2933 Value *CRD = BypassBuilder.CreateSExtOrTrunc(CountRoundDown, 2934 II.StepValue->getType(), 2935 "cast.crd"); 2936 EndValue = II.transform(BypassBuilder, CRD); 2937 EndValue->setName("ptr.ind.end"); 2938 break; 2939 } 2940 }// end of case 2941 2942 // The new PHI merges the original incoming value, in case of a bypass, 2943 // or the value at the end of the vectorized loop. 2944 for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I) { 2945 if (OrigPhi == OldInduction) 2946 ResumeVal->addIncoming(StartIdx, LoopBypassBlocks[I]); 2947 else 2948 ResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]); 2949 } 2950 ResumeVal->addIncoming(EndValue, VecBody); 2951 2952 // Fix the scalar body counter (PHI node). 2953 unsigned BlockIdx = OrigPhi->getBasicBlockIndex(ScalarPH); 2954 2955 // The old induction's phi node in the scalar body needs the truncated 2956 // value. 2957 if (OrigPhi == OldInduction) { 2958 BCResumeVal->addIncoming(StartIdx, LoopBypassBlocks[0]); 2959 OrigPhi->setIncomingValue(BlockIdx, BCTruncResumeVal); 2960 } else { 2961 BCResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[0]); 2962 OrigPhi->setIncomingValue(BlockIdx, BCResumeVal); 2963 } 2964 } 2965 2966 // If we are generating a new induction variable then we also need to 2967 // generate the code that calculates the exit value. This value is not 2968 // simply the end of the counter because we may skip the vectorized body 2969 // in case of a runtime check. 2970 if (!OldInduction){ 2971 assert(!ResumeIndex && "Unexpected resume value found"); 2972 ResumeIndex = PHINode::Create(IdxTy, 2, "new.indc.resume.val", 2973 MiddleBlock->getTerminator()); 2974 for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I) 2975 ResumeIndex->addIncoming(StartIdx, LoopBypassBlocks[I]); 2976 ResumeIndex->addIncoming(IdxEndRoundDown, VecBody); 2977 } 2978 2979 // Make sure that we found the index where scalar loop needs to continue. 2980 assert(ResumeIndex && ResumeIndex->getType()->isIntegerTy() && 2981 "Invalid resume Index"); 2982 2983 // Add a check in the middle block to see if we have completed 2984 // all of the iterations in the first vector loop. 2985 // If (N - N%VF) == N, then we *don't* need to run the remainder. 2986 Value *CmpN = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ, IdxEnd, 2987 ResumeIndex, "cmp.n", 2988 MiddleBlock->getTerminator()); 2989 ReplaceInstWithInst(MiddleBlock->getTerminator(), 2990 BranchInst::Create(ExitBlock, ScalarPH, CmpN)); 2991 2992 // Create i+1 and fill the PHINode. 2993 Value *NextIdx = Builder.CreateAdd(Induction, Step, "index.next"); 2994 Induction->addIncoming(StartIdx, VectorPH); 2995 Induction->addIncoming(NextIdx, VecBody); 2996 // Create the compare. 2997 Value *ICmp = Builder.CreateICmpEQ(NextIdx, IdxEndRoundDown); 2998 Builder.CreateCondBr(ICmp, MiddleBlock, VecBody); 2999 3000 // Now we have two terminators. Remove the old one from the block. 3001 VecBody->getTerminator()->eraseFromParent(); 3002 3003 // Get ready to start creating new instructions into the vectorized body. 3004 Builder.SetInsertPoint(VecBody->getFirstInsertionPt()); 3005 3006 // Save the state. 3007 LoopVectorPreHeader = VectorPH; 3008 LoopScalarPreHeader = ScalarPH; 3009 LoopMiddleBlock = MiddleBlock; 3010 LoopExitBlock = ExitBlock; 3011 LoopVectorBody.push_back(VecBody); 3012 LoopScalarBody = OldBasicBlock; 3013 3014 LoopVectorizeHints Hints(Lp, true); 3015 Hints.setAlreadyVectorized(); 3016 } 3017 3018 namespace { 3019 struct CSEDenseMapInfo { 3020 static bool canHandle(Instruction *I) { 3021 return isa<InsertElementInst>(I) || isa<ExtractElementInst>(I) || 3022 isa<ShuffleVectorInst>(I) || isa<GetElementPtrInst>(I); 3023 } 3024 static inline Instruction *getEmptyKey() { 3025 return DenseMapInfo<Instruction *>::getEmptyKey(); 3026 } 3027 static inline Instruction *getTombstoneKey() { 3028 return DenseMapInfo<Instruction *>::getTombstoneKey(); 3029 } 3030 static unsigned getHashValue(Instruction *I) { 3031 assert(canHandle(I) && "Unknown instruction!"); 3032 return hash_combine(I->getOpcode(), hash_combine_range(I->value_op_begin(), 3033 I->value_op_end())); 3034 } 3035 static bool isEqual(Instruction *LHS, Instruction *RHS) { 3036 if (LHS == getEmptyKey() || RHS == getEmptyKey() || 3037 LHS == getTombstoneKey() || RHS == getTombstoneKey()) 3038 return LHS == RHS; 3039 return LHS->isIdenticalTo(RHS); 3040 } 3041 }; 3042 } 3043 3044 /// \brief Check whether this block is a predicated block. 3045 /// Due to if predication of stores we might create a sequence of "if(pred) a[i] 3046 /// = ...; " blocks. We start with one vectorized basic block. For every 3047 /// conditional block we split this vectorized block. Therefore, every second 3048 /// block will be a predicated one. 3049 static bool isPredicatedBlock(unsigned BlockNum) { 3050 return BlockNum % 2; 3051 } 3052 3053 ///\brief Perform cse of induction variable instructions. 3054 static void cse(SmallVector<BasicBlock *, 4> &BBs) { 3055 // Perform simple cse. 3056 SmallDenseMap<Instruction *, Instruction *, 4, CSEDenseMapInfo> CSEMap; 3057 for (unsigned i = 0, e = BBs.size(); i != e; ++i) { 3058 BasicBlock *BB = BBs[i]; 3059 for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E;) { 3060 Instruction *In = I++; 3061 3062 if (!CSEDenseMapInfo::canHandle(In)) 3063 continue; 3064 3065 // Check if we can replace this instruction with any of the 3066 // visited instructions. 3067 if (Instruction *V = CSEMap.lookup(In)) { 3068 In->replaceAllUsesWith(V); 3069 In->eraseFromParent(); 3070 continue; 3071 } 3072 // Ignore instructions in conditional blocks. We create "if (pred) a[i] = 3073 // ...;" blocks for predicated stores. Every second block is a predicated 3074 // block. 3075 if (isPredicatedBlock(i)) 3076 continue; 3077 3078 CSEMap[In] = In; 3079 } 3080 } 3081 } 3082 3083 /// \brief Adds a 'fast' flag to floating point operations. 3084 static Value *addFastMathFlag(Value *V) { 3085 if (isa<FPMathOperator>(V)){ 3086 FastMathFlags Flags; 3087 Flags.setUnsafeAlgebra(); 3088 cast<Instruction>(V)->setFastMathFlags(Flags); 3089 } 3090 return V; 3091 } 3092 3093 /// Estimate the overhead of scalarizing a value. Insert and Extract are set if 3094 /// the result needs to be inserted and/or extracted from vectors. 3095 static unsigned getScalarizationOverhead(Type *Ty, bool Insert, bool Extract, 3096 const TargetTransformInfo &TTI) { 3097 if (Ty->isVoidTy()) 3098 return 0; 3099 3100 assert(Ty->isVectorTy() && "Can only scalarize vectors"); 3101 unsigned Cost = 0; 3102 3103 for (int i = 0, e = Ty->getVectorNumElements(); i < e; ++i) { 3104 if (Insert) 3105 Cost += TTI.getVectorInstrCost(Instruction::InsertElement, Ty, i); 3106 if (Extract) 3107 Cost += TTI.getVectorInstrCost(Instruction::ExtractElement, Ty, i); 3108 } 3109 3110 return Cost; 3111 } 3112 3113 // Estimate cost of a call instruction CI if it were vectorized with factor VF. 3114 // Return the cost of the instruction, including scalarization overhead if it's 3115 // needed. The flag NeedToScalarize shows if the call needs to be scalarized - 3116 // i.e. either vector version isn't available, or is too expensive. 3117 static unsigned getVectorCallCost(CallInst *CI, unsigned VF, 3118 const TargetTransformInfo &TTI, 3119 const TargetLibraryInfo *TLI, 3120 bool &NeedToScalarize) { 3121 Function *F = CI->getCalledFunction(); 3122 StringRef FnName = CI->getCalledFunction()->getName(); 3123 Type *ScalarRetTy = CI->getType(); 3124 SmallVector<Type *, 4> Tys, ScalarTys; 3125 for (auto &ArgOp : CI->arg_operands()) 3126 ScalarTys.push_back(ArgOp->getType()); 3127 3128 // Estimate cost of scalarized vector call. The source operands are assumed 3129 // to be vectors, so we need to extract individual elements from there, 3130 // execute VF scalar calls, and then gather the result into the vector return 3131 // value. 3132 unsigned ScalarCallCost = TTI.getCallInstrCost(F, ScalarRetTy, ScalarTys); 3133 if (VF == 1) 3134 return ScalarCallCost; 3135 3136 // Compute corresponding vector type for return value and arguments. 3137 Type *RetTy = ToVectorTy(ScalarRetTy, VF); 3138 for (unsigned i = 0, ie = ScalarTys.size(); i != ie; ++i) 3139 Tys.push_back(ToVectorTy(ScalarTys[i], VF)); 3140 3141 // Compute costs of unpacking argument values for the scalar calls and 3142 // packing the return values to a vector. 3143 unsigned ScalarizationCost = 3144 getScalarizationOverhead(RetTy, true, false, TTI); 3145 for (unsigned i = 0, ie = Tys.size(); i != ie; ++i) 3146 ScalarizationCost += getScalarizationOverhead(Tys[i], false, true, TTI); 3147 3148 unsigned Cost = ScalarCallCost * VF + ScalarizationCost; 3149 3150 // If we can't emit a vector call for this function, then the currently found 3151 // cost is the cost we need to return. 3152 NeedToScalarize = true; 3153 if (!TLI || !TLI->isFunctionVectorizable(FnName, VF) || CI->isNoBuiltin()) 3154 return Cost; 3155 3156 // If the corresponding vector cost is cheaper, return its cost. 3157 unsigned VectorCallCost = TTI.getCallInstrCost(nullptr, RetTy, Tys); 3158 if (VectorCallCost < Cost) { 3159 NeedToScalarize = false; 3160 return VectorCallCost; 3161 } 3162 return Cost; 3163 } 3164 3165 // Estimate cost of an intrinsic call instruction CI if it were vectorized with 3166 // factor VF. Return the cost of the instruction, including scalarization 3167 // overhead if it's needed. 3168 static unsigned getVectorIntrinsicCost(CallInst *CI, unsigned VF, 3169 const TargetTransformInfo &TTI, 3170 const TargetLibraryInfo *TLI) { 3171 Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI); 3172 assert(ID && "Expected intrinsic call!"); 3173 3174 Type *RetTy = ToVectorTy(CI->getType(), VF); 3175 SmallVector<Type *, 4> Tys; 3176 for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i) 3177 Tys.push_back(ToVectorTy(CI->getArgOperand(i)->getType(), VF)); 3178 3179 return TTI.getIntrinsicInstrCost(ID, RetTy, Tys); 3180 } 3181 3182 void InnerLoopVectorizer::vectorizeLoop() { 3183 //===------------------------------------------------===// 3184 // 3185 // Notice: any optimization or new instruction that go 3186 // into the code below should be also be implemented in 3187 // the cost-model. 3188 // 3189 //===------------------------------------------------===// 3190 Constant *Zero = Builder.getInt32(0); 3191 3192 // In order to support reduction variables we need to be able to vectorize 3193 // Phi nodes. Phi nodes have cycles, so we need to vectorize them in two 3194 // stages. First, we create a new vector PHI node with no incoming edges. 3195 // We use this value when we vectorize all of the instructions that use the 3196 // PHI. Next, after all of the instructions in the block are complete we 3197 // add the new incoming edges to the PHI. At this point all of the 3198 // instructions in the basic block are vectorized, so we can use them to 3199 // construct the PHI. 3200 PhiVector RdxPHIsToFix; 3201 3202 // Scan the loop in a topological order to ensure that defs are vectorized 3203 // before users. 3204 LoopBlocksDFS DFS(OrigLoop); 3205 DFS.perform(LI); 3206 3207 // Vectorize all of the blocks in the original loop. 3208 for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(), 3209 be = DFS.endRPO(); bb != be; ++bb) 3210 vectorizeBlockInLoop(*bb, &RdxPHIsToFix); 3211 3212 // At this point every instruction in the original loop is widened to 3213 // a vector form. We are almost done. Now, we need to fix the PHI nodes 3214 // that we vectorized. The PHI nodes are currently empty because we did 3215 // not want to introduce cycles. Notice that the remaining PHI nodes 3216 // that we need to fix are reduction variables. 3217 3218 // Create the 'reduced' values for each of the induction vars. 3219 // The reduced values are the vector values that we scalarize and combine 3220 // after the loop is finished. 3221 for (PhiVector::iterator it = RdxPHIsToFix.begin(), e = RdxPHIsToFix.end(); 3222 it != e; ++it) { 3223 PHINode *RdxPhi = *it; 3224 assert(RdxPhi && "Unable to recover vectorized PHI"); 3225 3226 // Find the reduction variable descriptor. 3227 assert(Legal->getReductionVars()->count(RdxPhi) && 3228 "Unable to find the reduction variable"); 3229 RecurrenceDescriptor RdxDesc = (*Legal->getReductionVars())[RdxPhi]; 3230 3231 RecurrenceDescriptor::RecurrenceKind RK = RdxDesc.getRecurrenceKind(); 3232 TrackingVH<Value> ReductionStartValue = RdxDesc.getRecurrenceStartValue(); 3233 Instruction *LoopExitInst = RdxDesc.getLoopExitInstr(); 3234 RecurrenceDescriptor::MinMaxRecurrenceKind MinMaxKind = 3235 RdxDesc.getMinMaxRecurrenceKind(); 3236 setDebugLocFromInst(Builder, ReductionStartValue); 3237 3238 // We need to generate a reduction vector from the incoming scalar. 3239 // To do so, we need to generate the 'identity' vector and override 3240 // one of the elements with the incoming scalar reduction. We need 3241 // to do it in the vector-loop preheader. 3242 Builder.SetInsertPoint(LoopBypassBlocks[1]->getTerminator()); 3243 3244 // This is the vector-clone of the value that leaves the loop. 3245 VectorParts &VectorExit = getVectorValue(LoopExitInst); 3246 Type *VecTy = VectorExit[0]->getType(); 3247 3248 // Find the reduction identity variable. Zero for addition, or, xor, 3249 // one for multiplication, -1 for And. 3250 Value *Identity; 3251 Value *VectorStart; 3252 if (RK == RecurrenceDescriptor::RK_IntegerMinMax || 3253 RK == RecurrenceDescriptor::RK_FloatMinMax) { 3254 // MinMax reduction have the start value as their identify. 3255 if (VF == 1) { 3256 VectorStart = Identity = ReductionStartValue; 3257 } else { 3258 VectorStart = Identity = 3259 Builder.CreateVectorSplat(VF, ReductionStartValue, "minmax.ident"); 3260 } 3261 } else { 3262 // Handle other reduction kinds: 3263 Constant *Iden = RecurrenceDescriptor::getRecurrenceIdentity( 3264 RK, VecTy->getScalarType()); 3265 if (VF == 1) { 3266 Identity = Iden; 3267 // This vector is the Identity vector where the first element is the 3268 // incoming scalar reduction. 3269 VectorStart = ReductionStartValue; 3270 } else { 3271 Identity = ConstantVector::getSplat(VF, Iden); 3272 3273 // This vector is the Identity vector where the first element is the 3274 // incoming scalar reduction. 3275 VectorStart = 3276 Builder.CreateInsertElement(Identity, ReductionStartValue, Zero); 3277 } 3278 } 3279 3280 // Fix the vector-loop phi. 3281 3282 // Reductions do not have to start at zero. They can start with 3283 // any loop invariant values. 3284 VectorParts &VecRdxPhi = WidenMap.get(RdxPhi); 3285 BasicBlock *Latch = OrigLoop->getLoopLatch(); 3286 Value *LoopVal = RdxPhi->getIncomingValueForBlock(Latch); 3287 VectorParts &Val = getVectorValue(LoopVal); 3288 for (unsigned part = 0; part < UF; ++part) { 3289 // Make sure to add the reduction stat value only to the 3290 // first unroll part. 3291 Value *StartVal = (part == 0) ? VectorStart : Identity; 3292 cast<PHINode>(VecRdxPhi[part])->addIncoming(StartVal, 3293 LoopVectorPreHeader); 3294 cast<PHINode>(VecRdxPhi[part])->addIncoming(Val[part], 3295 LoopVectorBody.back()); 3296 } 3297 3298 // Before each round, move the insertion point right between 3299 // the PHIs and the values we are going to write. 3300 // This allows us to write both PHINodes and the extractelement 3301 // instructions. 3302 Builder.SetInsertPoint(LoopMiddleBlock->getFirstInsertionPt()); 3303 3304 VectorParts RdxParts; 3305 setDebugLocFromInst(Builder, LoopExitInst); 3306 for (unsigned part = 0; part < UF; ++part) { 3307 // This PHINode contains the vectorized reduction variable, or 3308 // the initial value vector, if we bypass the vector loop. 3309 VectorParts &RdxExitVal = getVectorValue(LoopExitInst); 3310 PHINode *NewPhi = Builder.CreatePHI(VecTy, 2, "rdx.vec.exit.phi"); 3311 Value *StartVal = (part == 0) ? VectorStart : Identity; 3312 for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I) 3313 NewPhi->addIncoming(StartVal, LoopBypassBlocks[I]); 3314 NewPhi->addIncoming(RdxExitVal[part], 3315 LoopVectorBody.back()); 3316 RdxParts.push_back(NewPhi); 3317 } 3318 3319 // Reduce all of the unrolled parts into a single vector. 3320 Value *ReducedPartRdx = RdxParts[0]; 3321 unsigned Op = RecurrenceDescriptor::getRecurrenceBinOp(RK); 3322 setDebugLocFromInst(Builder, ReducedPartRdx); 3323 for (unsigned part = 1; part < UF; ++part) { 3324 if (Op != Instruction::ICmp && Op != Instruction::FCmp) 3325 // Floating point operations had to be 'fast' to enable the reduction. 3326 ReducedPartRdx = addFastMathFlag( 3327 Builder.CreateBinOp((Instruction::BinaryOps)Op, RdxParts[part], 3328 ReducedPartRdx, "bin.rdx")); 3329 else 3330 ReducedPartRdx = RecurrenceDescriptor::createMinMaxOp( 3331 Builder, MinMaxKind, ReducedPartRdx, RdxParts[part]); 3332 } 3333 3334 if (VF > 1) { 3335 // VF is a power of 2 so we can emit the reduction using log2(VF) shuffles 3336 // and vector ops, reducing the set of values being computed by half each 3337 // round. 3338 assert(isPowerOf2_32(VF) && 3339 "Reduction emission only supported for pow2 vectors!"); 3340 Value *TmpVec = ReducedPartRdx; 3341 SmallVector<Constant*, 32> ShuffleMask(VF, nullptr); 3342 for (unsigned i = VF; i != 1; i >>= 1) { 3343 // Move the upper half of the vector to the lower half. 3344 for (unsigned j = 0; j != i/2; ++j) 3345 ShuffleMask[j] = Builder.getInt32(i/2 + j); 3346 3347 // Fill the rest of the mask with undef. 3348 std::fill(&ShuffleMask[i/2], ShuffleMask.end(), 3349 UndefValue::get(Builder.getInt32Ty())); 3350 3351 Value *Shuf = 3352 Builder.CreateShuffleVector(TmpVec, 3353 UndefValue::get(TmpVec->getType()), 3354 ConstantVector::get(ShuffleMask), 3355 "rdx.shuf"); 3356 3357 if (Op != Instruction::ICmp && Op != Instruction::FCmp) 3358 // Floating point operations had to be 'fast' to enable the reduction. 3359 TmpVec = addFastMathFlag(Builder.CreateBinOp( 3360 (Instruction::BinaryOps)Op, TmpVec, Shuf, "bin.rdx")); 3361 else 3362 TmpVec = RecurrenceDescriptor::createMinMaxOp(Builder, MinMaxKind, 3363 TmpVec, Shuf); 3364 } 3365 3366 // The result is in the first element of the vector. 3367 ReducedPartRdx = Builder.CreateExtractElement(TmpVec, 3368 Builder.getInt32(0)); 3369 } 3370 3371 // Create a phi node that merges control-flow from the backedge-taken check 3372 // block and the middle block. 3373 PHINode *BCBlockPhi = PHINode::Create(RdxPhi->getType(), 2, "bc.merge.rdx", 3374 LoopScalarPreHeader->getTerminator()); 3375 BCBlockPhi->addIncoming(ReductionStartValue, LoopBypassBlocks[0]); 3376 BCBlockPhi->addIncoming(ReducedPartRdx, LoopMiddleBlock); 3377 3378 // Now, we need to fix the users of the reduction variable 3379 // inside and outside of the scalar remainder loop. 3380 // We know that the loop is in LCSSA form. We need to update the 3381 // PHI nodes in the exit blocks. 3382 for (BasicBlock::iterator LEI = LoopExitBlock->begin(), 3383 LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) { 3384 PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI); 3385 if (!LCSSAPhi) break; 3386 3387 // All PHINodes need to have a single entry edge, or two if 3388 // we already fixed them. 3389 assert(LCSSAPhi->getNumIncomingValues() < 3 && "Invalid LCSSA PHI"); 3390 3391 // We found our reduction value exit-PHI. Update it with the 3392 // incoming bypass edge. 3393 if (LCSSAPhi->getIncomingValue(0) == LoopExitInst) { 3394 // Add an edge coming from the bypass. 3395 LCSSAPhi->addIncoming(ReducedPartRdx, LoopMiddleBlock); 3396 break; 3397 } 3398 }// end of the LCSSA phi scan. 3399 3400 // Fix the scalar loop reduction variable with the incoming reduction sum 3401 // from the vector body and from the backedge value. 3402 int IncomingEdgeBlockIdx = 3403 (RdxPhi)->getBasicBlockIndex(OrigLoop->getLoopLatch()); 3404 assert(IncomingEdgeBlockIdx >= 0 && "Invalid block index"); 3405 // Pick the other block. 3406 int SelfEdgeBlockIdx = (IncomingEdgeBlockIdx ? 0 : 1); 3407 (RdxPhi)->setIncomingValue(SelfEdgeBlockIdx, BCBlockPhi); 3408 (RdxPhi)->setIncomingValue(IncomingEdgeBlockIdx, LoopExitInst); 3409 }// end of for each redux variable. 3410 3411 fixLCSSAPHIs(); 3412 3413 // Remove redundant induction instructions. 3414 cse(LoopVectorBody); 3415 } 3416 3417 void InnerLoopVectorizer::fixLCSSAPHIs() { 3418 for (BasicBlock::iterator LEI = LoopExitBlock->begin(), 3419 LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) { 3420 PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI); 3421 if (!LCSSAPhi) break; 3422 if (LCSSAPhi->getNumIncomingValues() == 1) 3423 LCSSAPhi->addIncoming(UndefValue::get(LCSSAPhi->getType()), 3424 LoopMiddleBlock); 3425 } 3426 } 3427 3428 InnerLoopVectorizer::VectorParts 3429 InnerLoopVectorizer::createEdgeMask(BasicBlock *Src, BasicBlock *Dst) { 3430 assert(std::find(pred_begin(Dst), pred_end(Dst), Src) != pred_end(Dst) && 3431 "Invalid edge"); 3432 3433 // Look for cached value. 3434 std::pair<BasicBlock*, BasicBlock*> Edge(Src, Dst); 3435 EdgeMaskCache::iterator ECEntryIt = MaskCache.find(Edge); 3436 if (ECEntryIt != MaskCache.end()) 3437 return ECEntryIt->second; 3438 3439 VectorParts SrcMask = createBlockInMask(Src); 3440 3441 // The terminator has to be a branch inst! 3442 BranchInst *BI = dyn_cast<BranchInst>(Src->getTerminator()); 3443 assert(BI && "Unexpected terminator found"); 3444 3445 if (BI->isConditional()) { 3446 VectorParts EdgeMask = getVectorValue(BI->getCondition()); 3447 3448 if (BI->getSuccessor(0) != Dst) 3449 for (unsigned part = 0; part < UF; ++part) 3450 EdgeMask[part] = Builder.CreateNot(EdgeMask[part]); 3451 3452 for (unsigned part = 0; part < UF; ++part) 3453 EdgeMask[part] = Builder.CreateAnd(EdgeMask[part], SrcMask[part]); 3454 3455 MaskCache[Edge] = EdgeMask; 3456 return EdgeMask; 3457 } 3458 3459 MaskCache[Edge] = SrcMask; 3460 return SrcMask; 3461 } 3462 3463 InnerLoopVectorizer::VectorParts 3464 InnerLoopVectorizer::createBlockInMask(BasicBlock *BB) { 3465 assert(OrigLoop->contains(BB) && "Block is not a part of a loop"); 3466 3467 // Loop incoming mask is all-one. 3468 if (OrigLoop->getHeader() == BB) { 3469 Value *C = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 1); 3470 return getVectorValue(C); 3471 } 3472 3473 // This is the block mask. We OR all incoming edges, and with zero. 3474 Value *Zero = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 0); 3475 VectorParts BlockMask = getVectorValue(Zero); 3476 3477 // For each pred: 3478 for (pred_iterator it = pred_begin(BB), e = pred_end(BB); it != e; ++it) { 3479 VectorParts EM = createEdgeMask(*it, BB); 3480 for (unsigned part = 0; part < UF; ++part) 3481 BlockMask[part] = Builder.CreateOr(BlockMask[part], EM[part]); 3482 } 3483 3484 return BlockMask; 3485 } 3486 3487 void InnerLoopVectorizer::widenPHIInstruction(Instruction *PN, 3488 InnerLoopVectorizer::VectorParts &Entry, 3489 unsigned UF, unsigned VF, PhiVector *PV) { 3490 PHINode* P = cast<PHINode>(PN); 3491 // Handle reduction variables: 3492 if (Legal->getReductionVars()->count(P)) { 3493 for (unsigned part = 0; part < UF; ++part) { 3494 // This is phase one of vectorizing PHIs. 3495 Type *VecTy = (VF == 1) ? PN->getType() : 3496 VectorType::get(PN->getType(), VF); 3497 Entry[part] = PHINode::Create(VecTy, 2, "vec.phi", 3498 LoopVectorBody.back()-> getFirstInsertionPt()); 3499 } 3500 PV->push_back(P); 3501 return; 3502 } 3503 3504 setDebugLocFromInst(Builder, P); 3505 // Check for PHI nodes that are lowered to vector selects. 3506 if (P->getParent() != OrigLoop->getHeader()) { 3507 // We know that all PHIs in non-header blocks are converted into 3508 // selects, so we don't have to worry about the insertion order and we 3509 // can just use the builder. 3510 // At this point we generate the predication tree. There may be 3511 // duplications since this is a simple recursive scan, but future 3512 // optimizations will clean it up. 3513 3514 unsigned NumIncoming = P->getNumIncomingValues(); 3515 3516 // Generate a sequence of selects of the form: 3517 // SELECT(Mask3, In3, 3518 // SELECT(Mask2, In2, 3519 // ( ...))) 3520 for (unsigned In = 0; In < NumIncoming; In++) { 3521 VectorParts Cond = createEdgeMask(P->getIncomingBlock(In), 3522 P->getParent()); 3523 VectorParts &In0 = getVectorValue(P->getIncomingValue(In)); 3524 3525 for (unsigned part = 0; part < UF; ++part) { 3526 // We might have single edge PHIs (blocks) - use an identity 3527 // 'select' for the first PHI operand. 3528 if (In == 0) 3529 Entry[part] = Builder.CreateSelect(Cond[part], In0[part], 3530 In0[part]); 3531 else 3532 // Select between the current value and the previous incoming edge 3533 // based on the incoming mask. 3534 Entry[part] = Builder.CreateSelect(Cond[part], In0[part], 3535 Entry[part], "predphi"); 3536 } 3537 } 3538 return; 3539 } 3540 3541 // This PHINode must be an induction variable. 3542 // Make sure that we know about it. 3543 assert(Legal->getInductionVars()->count(P) && 3544 "Not an induction variable"); 3545 3546 LoopVectorizationLegality::InductionInfo II = 3547 Legal->getInductionVars()->lookup(P); 3548 3549 // FIXME: The newly created binary instructions should contain nsw/nuw flags, 3550 // which can be found from the original scalar operations. 3551 switch (II.IK) { 3552 case LoopVectorizationLegality::IK_NoInduction: 3553 llvm_unreachable("Unknown induction"); 3554 case LoopVectorizationLegality::IK_IntInduction: { 3555 assert(P->getType() == II.StartValue->getType() && "Types must match"); 3556 Type *PhiTy = P->getType(); 3557 Value *Broadcasted; 3558 if (P == OldInduction) { 3559 // Handle the canonical induction variable. We might have had to 3560 // extend the type. 3561 Broadcasted = Builder.CreateTrunc(Induction, PhiTy); 3562 } else { 3563 // Handle other induction variables that are now based on the 3564 // canonical one. 3565 Value *NormalizedIdx = Builder.CreateSub(Induction, ExtendedIdx, 3566 "normalized.idx"); 3567 NormalizedIdx = Builder.CreateSExtOrTrunc(NormalizedIdx, PhiTy); 3568 Broadcasted = II.transform(Builder, NormalizedIdx); 3569 Broadcasted->setName("offset.idx"); 3570 } 3571 Broadcasted = getBroadcastInstrs(Broadcasted); 3572 // After broadcasting the induction variable we need to make the vector 3573 // consecutive by adding 0, 1, 2, etc. 3574 for (unsigned part = 0; part < UF; ++part) 3575 Entry[part] = getStepVector(Broadcasted, VF * part, II.StepValue); 3576 return; 3577 } 3578 case LoopVectorizationLegality::IK_PtrInduction: 3579 // Handle the pointer induction variable case. 3580 assert(P->getType()->isPointerTy() && "Unexpected type."); 3581 // This is the normalized GEP that starts counting at zero. 3582 Value *NormalizedIdx = 3583 Builder.CreateSub(Induction, ExtendedIdx, "normalized.idx"); 3584 NormalizedIdx = 3585 Builder.CreateSExtOrTrunc(NormalizedIdx, II.StepValue->getType()); 3586 // This is the vector of results. Notice that we don't generate 3587 // vector geps because scalar geps result in better code. 3588 for (unsigned part = 0; part < UF; ++part) { 3589 if (VF == 1) { 3590 int EltIndex = part; 3591 Constant *Idx = ConstantInt::get(NormalizedIdx->getType(), EltIndex); 3592 Value *GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx); 3593 Value *SclrGep = II.transform(Builder, GlobalIdx); 3594 SclrGep->setName("next.gep"); 3595 Entry[part] = SclrGep; 3596 continue; 3597 } 3598 3599 Value *VecVal = UndefValue::get(VectorType::get(P->getType(), VF)); 3600 for (unsigned int i = 0; i < VF; ++i) { 3601 int EltIndex = i + part * VF; 3602 Constant *Idx = ConstantInt::get(NormalizedIdx->getType(), EltIndex); 3603 Value *GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx); 3604 Value *SclrGep = II.transform(Builder, GlobalIdx); 3605 SclrGep->setName("next.gep"); 3606 VecVal = Builder.CreateInsertElement(VecVal, SclrGep, 3607 Builder.getInt32(i), 3608 "insert.gep"); 3609 } 3610 Entry[part] = VecVal; 3611 } 3612 return; 3613 } 3614 } 3615 3616 void InnerLoopVectorizer::vectorizeBlockInLoop(BasicBlock *BB, PhiVector *PV) { 3617 // For each instruction in the old loop. 3618 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 3619 VectorParts &Entry = WidenMap.get(it); 3620 switch (it->getOpcode()) { 3621 case Instruction::Br: 3622 // Nothing to do for PHIs and BR, since we already took care of the 3623 // loop control flow instructions. 3624 continue; 3625 case Instruction::PHI: { 3626 // Vectorize PHINodes. 3627 widenPHIInstruction(it, Entry, UF, VF, PV); 3628 continue; 3629 }// End of PHI. 3630 3631 case Instruction::Add: 3632 case Instruction::FAdd: 3633 case Instruction::Sub: 3634 case Instruction::FSub: 3635 case Instruction::Mul: 3636 case Instruction::FMul: 3637 case Instruction::UDiv: 3638 case Instruction::SDiv: 3639 case Instruction::FDiv: 3640 case Instruction::URem: 3641 case Instruction::SRem: 3642 case Instruction::FRem: 3643 case Instruction::Shl: 3644 case Instruction::LShr: 3645 case Instruction::AShr: 3646 case Instruction::And: 3647 case Instruction::Or: 3648 case Instruction::Xor: { 3649 // Just widen binops. 3650 BinaryOperator *BinOp = dyn_cast<BinaryOperator>(it); 3651 setDebugLocFromInst(Builder, BinOp); 3652 VectorParts &A = getVectorValue(it->getOperand(0)); 3653 VectorParts &B = getVectorValue(it->getOperand(1)); 3654 3655 // Use this vector value for all users of the original instruction. 3656 for (unsigned Part = 0; Part < UF; ++Part) { 3657 Value *V = Builder.CreateBinOp(BinOp->getOpcode(), A[Part], B[Part]); 3658 3659 if (BinaryOperator *VecOp = dyn_cast<BinaryOperator>(V)) 3660 VecOp->copyIRFlags(BinOp); 3661 3662 Entry[Part] = V; 3663 } 3664 3665 propagateMetadata(Entry, it); 3666 break; 3667 } 3668 case Instruction::Select: { 3669 // Widen selects. 3670 // If the selector is loop invariant we can create a select 3671 // instruction with a scalar condition. Otherwise, use vector-select. 3672 bool InvariantCond = SE->isLoopInvariant(SE->getSCEV(it->getOperand(0)), 3673 OrigLoop); 3674 setDebugLocFromInst(Builder, it); 3675 3676 // The condition can be loop invariant but still defined inside the 3677 // loop. This means that we can't just use the original 'cond' value. 3678 // We have to take the 'vectorized' value and pick the first lane. 3679 // Instcombine will make this a no-op. 3680 VectorParts &Cond = getVectorValue(it->getOperand(0)); 3681 VectorParts &Op0 = getVectorValue(it->getOperand(1)); 3682 VectorParts &Op1 = getVectorValue(it->getOperand(2)); 3683 3684 Value *ScalarCond = (VF == 1) ? Cond[0] : 3685 Builder.CreateExtractElement(Cond[0], Builder.getInt32(0)); 3686 3687 for (unsigned Part = 0; Part < UF; ++Part) { 3688 Entry[Part] = Builder.CreateSelect( 3689 InvariantCond ? ScalarCond : Cond[Part], 3690 Op0[Part], 3691 Op1[Part]); 3692 } 3693 3694 propagateMetadata(Entry, it); 3695 break; 3696 } 3697 3698 case Instruction::ICmp: 3699 case Instruction::FCmp: { 3700 // Widen compares. Generate vector compares. 3701 bool FCmp = (it->getOpcode() == Instruction::FCmp); 3702 CmpInst *Cmp = dyn_cast<CmpInst>(it); 3703 setDebugLocFromInst(Builder, it); 3704 VectorParts &A = getVectorValue(it->getOperand(0)); 3705 VectorParts &B = getVectorValue(it->getOperand(1)); 3706 for (unsigned Part = 0; Part < UF; ++Part) { 3707 Value *C = nullptr; 3708 if (FCmp) 3709 C = Builder.CreateFCmp(Cmp->getPredicate(), A[Part], B[Part]); 3710 else 3711 C = Builder.CreateICmp(Cmp->getPredicate(), A[Part], B[Part]); 3712 Entry[Part] = C; 3713 } 3714 3715 propagateMetadata(Entry, it); 3716 break; 3717 } 3718 3719 case Instruction::Store: 3720 case Instruction::Load: 3721 vectorizeMemoryInstruction(it); 3722 break; 3723 case Instruction::ZExt: 3724 case Instruction::SExt: 3725 case Instruction::FPToUI: 3726 case Instruction::FPToSI: 3727 case Instruction::FPExt: 3728 case Instruction::PtrToInt: 3729 case Instruction::IntToPtr: 3730 case Instruction::SIToFP: 3731 case Instruction::UIToFP: 3732 case Instruction::Trunc: 3733 case Instruction::FPTrunc: 3734 case Instruction::BitCast: { 3735 CastInst *CI = dyn_cast<CastInst>(it); 3736 setDebugLocFromInst(Builder, it); 3737 /// Optimize the special case where the source is the induction 3738 /// variable. Notice that we can only optimize the 'trunc' case 3739 /// because: a. FP conversions lose precision, b. sext/zext may wrap, 3740 /// c. other casts depend on pointer size. 3741 if (CI->getOperand(0) == OldInduction && 3742 it->getOpcode() == Instruction::Trunc) { 3743 Value *ScalarCast = Builder.CreateCast(CI->getOpcode(), Induction, 3744 CI->getType()); 3745 Value *Broadcasted = getBroadcastInstrs(ScalarCast); 3746 LoopVectorizationLegality::InductionInfo II = 3747 Legal->getInductionVars()->lookup(OldInduction); 3748 Constant *Step = 3749 ConstantInt::getSigned(CI->getType(), II.StepValue->getSExtValue()); 3750 for (unsigned Part = 0; Part < UF; ++Part) 3751 Entry[Part] = getStepVector(Broadcasted, VF * Part, Step); 3752 propagateMetadata(Entry, it); 3753 break; 3754 } 3755 /// Vectorize casts. 3756 Type *DestTy = (VF == 1) ? CI->getType() : 3757 VectorType::get(CI->getType(), VF); 3758 3759 VectorParts &A = getVectorValue(it->getOperand(0)); 3760 for (unsigned Part = 0; Part < UF; ++Part) 3761 Entry[Part] = Builder.CreateCast(CI->getOpcode(), A[Part], DestTy); 3762 propagateMetadata(Entry, it); 3763 break; 3764 } 3765 3766 case Instruction::Call: { 3767 // Ignore dbg intrinsics. 3768 if (isa<DbgInfoIntrinsic>(it)) 3769 break; 3770 setDebugLocFromInst(Builder, it); 3771 3772 Module *M = BB->getParent()->getParent(); 3773 CallInst *CI = cast<CallInst>(it); 3774 3775 StringRef FnName = CI->getCalledFunction()->getName(); 3776 Function *F = CI->getCalledFunction(); 3777 Type *RetTy = ToVectorTy(CI->getType(), VF); 3778 SmallVector<Type *, 4> Tys; 3779 for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i) 3780 Tys.push_back(ToVectorTy(CI->getArgOperand(i)->getType(), VF)); 3781 3782 Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI); 3783 if (ID && 3784 (ID == Intrinsic::assume || ID == Intrinsic::lifetime_end || 3785 ID == Intrinsic::lifetime_start)) { 3786 scalarizeInstruction(it); 3787 break; 3788 } 3789 // The flag shows whether we use Intrinsic or a usual Call for vectorized 3790 // version of the instruction. 3791 // Is it beneficial to perform intrinsic call compared to lib call? 3792 bool NeedToScalarize; 3793 unsigned CallCost = getVectorCallCost(CI, VF, *TTI, TLI, NeedToScalarize); 3794 bool UseVectorIntrinsic = 3795 ID && getVectorIntrinsicCost(CI, VF, *TTI, TLI) <= CallCost; 3796 if (!UseVectorIntrinsic && NeedToScalarize) { 3797 scalarizeInstruction(it); 3798 break; 3799 } 3800 3801 for (unsigned Part = 0; Part < UF; ++Part) { 3802 SmallVector<Value *, 4> Args; 3803 for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i) { 3804 Value *Arg = CI->getArgOperand(i); 3805 // Some intrinsics have a scalar argument - don't replace it with a 3806 // vector. 3807 if (!UseVectorIntrinsic || !hasVectorInstrinsicScalarOpd(ID, i)) { 3808 VectorParts &VectorArg = getVectorValue(CI->getArgOperand(i)); 3809 Arg = VectorArg[Part]; 3810 } 3811 Args.push_back(Arg); 3812 } 3813 3814 Function *VectorF; 3815 if (UseVectorIntrinsic) { 3816 // Use vector version of the intrinsic. 3817 Type *TysForDecl[] = {CI->getType()}; 3818 if (VF > 1) 3819 TysForDecl[0] = VectorType::get(CI->getType()->getScalarType(), VF); 3820 VectorF = Intrinsic::getDeclaration(M, ID, TysForDecl); 3821 } else { 3822 // Use vector version of the library call. 3823 StringRef VFnName = TLI->getVectorizedFunction(FnName, VF); 3824 assert(!VFnName.empty() && "Vector function name is empty."); 3825 VectorF = M->getFunction(VFnName); 3826 if (!VectorF) { 3827 // Generate a declaration 3828 FunctionType *FTy = FunctionType::get(RetTy, Tys, false); 3829 VectorF = 3830 Function::Create(FTy, Function::ExternalLinkage, VFnName, M); 3831 VectorF->copyAttributesFrom(F); 3832 } 3833 } 3834 assert(VectorF && "Can't create vector function."); 3835 Entry[Part] = Builder.CreateCall(VectorF, Args); 3836 } 3837 3838 propagateMetadata(Entry, it); 3839 break; 3840 } 3841 3842 default: 3843 // All other instructions are unsupported. Scalarize them. 3844 scalarizeInstruction(it); 3845 break; 3846 }// end of switch. 3847 }// end of for_each instr. 3848 } 3849 3850 void InnerLoopVectorizer::updateAnalysis() { 3851 // Forget the original basic block. 3852 SE->forgetLoop(OrigLoop); 3853 3854 // Update the dominator tree information. 3855 assert(DT->properlyDominates(LoopBypassBlocks.front(), LoopExitBlock) && 3856 "Entry does not dominate exit."); 3857 3858 for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I) 3859 DT->addNewBlock(LoopBypassBlocks[I], LoopBypassBlocks[I-1]); 3860 DT->addNewBlock(LoopVectorPreHeader, LoopBypassBlocks.back()); 3861 3862 // Due to if predication of stores we might create a sequence of "if(pred) 3863 // a[i] = ...; " blocks. 3864 for (unsigned i = 0, e = LoopVectorBody.size(); i != e; ++i) { 3865 if (i == 0) 3866 DT->addNewBlock(LoopVectorBody[0], LoopVectorPreHeader); 3867 else if (isPredicatedBlock(i)) { 3868 DT->addNewBlock(LoopVectorBody[i], LoopVectorBody[i-1]); 3869 } else { 3870 DT->addNewBlock(LoopVectorBody[i], LoopVectorBody[i-2]); 3871 } 3872 } 3873 3874 DT->addNewBlock(LoopMiddleBlock, LoopBypassBlocks[1]); 3875 DT->addNewBlock(LoopScalarPreHeader, LoopBypassBlocks[0]); 3876 DT->changeImmediateDominator(LoopScalarBody, LoopScalarPreHeader); 3877 DT->changeImmediateDominator(LoopExitBlock, LoopBypassBlocks[0]); 3878 3879 DEBUG(DT->verifyDomTree()); 3880 } 3881 3882 /// \brief Check whether it is safe to if-convert this phi node. 3883 /// 3884 /// Phi nodes with constant expressions that can trap are not safe to if 3885 /// convert. 3886 static bool canIfConvertPHINodes(BasicBlock *BB) { 3887 for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I) { 3888 PHINode *Phi = dyn_cast<PHINode>(I); 3889 if (!Phi) 3890 return true; 3891 for (unsigned p = 0, e = Phi->getNumIncomingValues(); p != e; ++p) 3892 if (Constant *C = dyn_cast<Constant>(Phi->getIncomingValue(p))) 3893 if (C->canTrap()) 3894 return false; 3895 } 3896 return true; 3897 } 3898 3899 bool LoopVectorizationLegality::canVectorizeWithIfConvert() { 3900 if (!EnableIfConversion) { 3901 emitAnalysis(VectorizationReport() << "if-conversion is disabled"); 3902 return false; 3903 } 3904 3905 assert(TheLoop->getNumBlocks() > 1 && "Single block loops are vectorizable"); 3906 3907 // A list of pointers that we can safely read and write to. 3908 SmallPtrSet<Value *, 8> SafePointes; 3909 3910 // Collect safe addresses. 3911 for (Loop::block_iterator BI = TheLoop->block_begin(), 3912 BE = TheLoop->block_end(); BI != BE; ++BI) { 3913 BasicBlock *BB = *BI; 3914 3915 if (blockNeedsPredication(BB)) 3916 continue; 3917 3918 for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I) { 3919 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 3920 SafePointes.insert(LI->getPointerOperand()); 3921 else if (StoreInst *SI = dyn_cast<StoreInst>(I)) 3922 SafePointes.insert(SI->getPointerOperand()); 3923 } 3924 } 3925 3926 // Collect the blocks that need predication. 3927 BasicBlock *Header = TheLoop->getHeader(); 3928 for (Loop::block_iterator BI = TheLoop->block_begin(), 3929 BE = TheLoop->block_end(); BI != BE; ++BI) { 3930 BasicBlock *BB = *BI; 3931 3932 // We don't support switch statements inside loops. 3933 if (!isa<BranchInst>(BB->getTerminator())) { 3934 emitAnalysis(VectorizationReport(BB->getTerminator()) 3935 << "loop contains a switch statement"); 3936 return false; 3937 } 3938 3939 // We must be able to predicate all blocks that need to be predicated. 3940 if (blockNeedsPredication(BB)) { 3941 if (!blockCanBePredicated(BB, SafePointes)) { 3942 emitAnalysis(VectorizationReport(BB->getTerminator()) 3943 << "control flow cannot be substituted for a select"); 3944 return false; 3945 } 3946 } else if (BB != Header && !canIfConvertPHINodes(BB)) { 3947 emitAnalysis(VectorizationReport(BB->getTerminator()) 3948 << "control flow cannot be substituted for a select"); 3949 return false; 3950 } 3951 } 3952 3953 // We can if-convert this loop. 3954 return true; 3955 } 3956 3957 bool LoopVectorizationLegality::canVectorize() { 3958 // We must have a loop in canonical form. Loops with indirectbr in them cannot 3959 // be canonicalized. 3960 if (!TheLoop->getLoopPreheader()) { 3961 emitAnalysis( 3962 VectorizationReport() << 3963 "loop control flow is not understood by vectorizer"); 3964 return false; 3965 } 3966 3967 // We can only vectorize innermost loops. 3968 if (!TheLoop->empty()) { 3969 emitAnalysis(VectorizationReport() << "loop is not the innermost loop"); 3970 return false; 3971 } 3972 3973 // We must have a single backedge. 3974 if (TheLoop->getNumBackEdges() != 1) { 3975 emitAnalysis( 3976 VectorizationReport() << 3977 "loop control flow is not understood by vectorizer"); 3978 return false; 3979 } 3980 3981 // We must have a single exiting block. 3982 if (!TheLoop->getExitingBlock()) { 3983 emitAnalysis( 3984 VectorizationReport() << 3985 "loop control flow is not understood by vectorizer"); 3986 return false; 3987 } 3988 3989 // We only handle bottom-tested loops, i.e. loop in which the condition is 3990 // checked at the end of each iteration. With that we can assume that all 3991 // instructions in the loop are executed the same number of times. 3992 if (TheLoop->getExitingBlock() != TheLoop->getLoopLatch()) { 3993 emitAnalysis( 3994 VectorizationReport() << 3995 "loop control flow is not understood by vectorizer"); 3996 return false; 3997 } 3998 3999 // We need to have a loop header. 4000 DEBUG(dbgs() << "LV: Found a loop: " << 4001 TheLoop->getHeader()->getName() << '\n'); 4002 4003 // Check if we can if-convert non-single-bb loops. 4004 unsigned NumBlocks = TheLoop->getNumBlocks(); 4005 if (NumBlocks != 1 && !canVectorizeWithIfConvert()) { 4006 DEBUG(dbgs() << "LV: Can't if-convert the loop.\n"); 4007 return false; 4008 } 4009 4010 // ScalarEvolution needs to be able to find the exit count. 4011 const SCEV *ExitCount = SE->getBackedgeTakenCount(TheLoop); 4012 if (ExitCount == SE->getCouldNotCompute()) { 4013 emitAnalysis(VectorizationReport() << 4014 "could not determine number of loop iterations"); 4015 DEBUG(dbgs() << "LV: SCEV could not compute the loop exit count.\n"); 4016 return false; 4017 } 4018 4019 // Check if we can vectorize the instructions and CFG in this loop. 4020 if (!canVectorizeInstrs()) { 4021 DEBUG(dbgs() << "LV: Can't vectorize the instructions or CFG\n"); 4022 return false; 4023 } 4024 4025 // Go over each instruction and look at memory deps. 4026 if (!canVectorizeMemory()) { 4027 DEBUG(dbgs() << "LV: Can't vectorize due to memory conflicts\n"); 4028 return false; 4029 } 4030 4031 // Collect all of the variables that remain uniform after vectorization. 4032 collectLoopUniforms(); 4033 4034 DEBUG(dbgs() << "LV: We can vectorize this loop" 4035 << (LAI->getRuntimePointerChecking()->Need 4036 ? " (with a runtime bound check)" 4037 : "") 4038 << "!\n"); 4039 4040 bool UseInterleaved = TTI->enableInterleavedAccessVectorization(); 4041 4042 // If an override option has been passed in for interleaved accesses, use it. 4043 if (EnableInterleavedMemAccesses.getNumOccurrences() > 0) 4044 UseInterleaved = EnableInterleavedMemAccesses; 4045 4046 // Analyze interleaved memory accesses. 4047 if (UseInterleaved) 4048 InterleaveInfo.analyzeInterleaving(Strides); 4049 4050 // Okay! We can vectorize. At this point we don't have any other mem analysis 4051 // which may limit our maximum vectorization factor, so just return true with 4052 // no restrictions. 4053 return true; 4054 } 4055 4056 static Type *convertPointerToIntegerType(const DataLayout &DL, Type *Ty) { 4057 if (Ty->isPointerTy()) 4058 return DL.getIntPtrType(Ty); 4059 4060 // It is possible that char's or short's overflow when we ask for the loop's 4061 // trip count, work around this by changing the type size. 4062 if (Ty->getScalarSizeInBits() < 32) 4063 return Type::getInt32Ty(Ty->getContext()); 4064 4065 return Ty; 4066 } 4067 4068 static Type* getWiderType(const DataLayout &DL, Type *Ty0, Type *Ty1) { 4069 Ty0 = convertPointerToIntegerType(DL, Ty0); 4070 Ty1 = convertPointerToIntegerType(DL, Ty1); 4071 if (Ty0->getScalarSizeInBits() > Ty1->getScalarSizeInBits()) 4072 return Ty0; 4073 return Ty1; 4074 } 4075 4076 /// \brief Check that the instruction has outside loop users and is not an 4077 /// identified reduction variable. 4078 static bool hasOutsideLoopUser(const Loop *TheLoop, Instruction *Inst, 4079 SmallPtrSetImpl<Value *> &Reductions) { 4080 // Reduction instructions are allowed to have exit users. All other 4081 // instructions must not have external users. 4082 if (!Reductions.count(Inst)) 4083 //Check that all of the users of the loop are inside the BB. 4084 for (User *U : Inst->users()) { 4085 Instruction *UI = cast<Instruction>(U); 4086 // This user may be a reduction exit value. 4087 if (!TheLoop->contains(UI)) { 4088 DEBUG(dbgs() << "LV: Found an outside user for : " << *UI << '\n'); 4089 return true; 4090 } 4091 } 4092 return false; 4093 } 4094 4095 bool LoopVectorizationLegality::canVectorizeInstrs() { 4096 BasicBlock *PreHeader = TheLoop->getLoopPreheader(); 4097 BasicBlock *Header = TheLoop->getHeader(); 4098 4099 // Look for the attribute signaling the absence of NaNs. 4100 Function &F = *Header->getParent(); 4101 const DataLayout &DL = F.getParent()->getDataLayout(); 4102 if (F.hasFnAttribute("no-nans-fp-math")) 4103 HasFunNoNaNAttr = 4104 F.getFnAttribute("no-nans-fp-math").getValueAsString() == "true"; 4105 4106 // For each block in the loop. 4107 for (Loop::block_iterator bb = TheLoop->block_begin(), 4108 be = TheLoop->block_end(); bb != be; ++bb) { 4109 4110 // Scan the instructions in the block and look for hazards. 4111 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e; 4112 ++it) { 4113 4114 if (PHINode *Phi = dyn_cast<PHINode>(it)) { 4115 Type *PhiTy = Phi->getType(); 4116 // Check that this PHI type is allowed. 4117 if (!PhiTy->isIntegerTy() && 4118 !PhiTy->isFloatingPointTy() && 4119 !PhiTy->isPointerTy()) { 4120 emitAnalysis(VectorizationReport(it) 4121 << "loop control flow is not understood by vectorizer"); 4122 DEBUG(dbgs() << "LV: Found an non-int non-pointer PHI.\n"); 4123 return false; 4124 } 4125 4126 // If this PHINode is not in the header block, then we know that we 4127 // can convert it to select during if-conversion. No need to check if 4128 // the PHIs in this block are induction or reduction variables. 4129 if (*bb != Header) { 4130 // Check that this instruction has no outside users or is an 4131 // identified reduction value with an outside user. 4132 if (!hasOutsideLoopUser(TheLoop, it, AllowedExit)) 4133 continue; 4134 emitAnalysis(VectorizationReport(it) << 4135 "value could not be identified as " 4136 "an induction or reduction variable"); 4137 return false; 4138 } 4139 4140 // We only allow if-converted PHIs with exactly two incoming values. 4141 if (Phi->getNumIncomingValues() != 2) { 4142 emitAnalysis(VectorizationReport(it) 4143 << "control flow not understood by vectorizer"); 4144 DEBUG(dbgs() << "LV: Found an invalid PHI.\n"); 4145 return false; 4146 } 4147 4148 // This is the value coming from the preheader. 4149 Value *StartValue = Phi->getIncomingValueForBlock(PreHeader); 4150 ConstantInt *StepValue = nullptr; 4151 // Check if this is an induction variable. 4152 InductionKind IK = isInductionVariable(Phi, StepValue); 4153 4154 if (IK_NoInduction != IK) { 4155 // Get the widest type. 4156 if (!WidestIndTy) 4157 WidestIndTy = convertPointerToIntegerType(DL, PhiTy); 4158 else 4159 WidestIndTy = getWiderType(DL, PhiTy, WidestIndTy); 4160 4161 // Int inductions are special because we only allow one IV. 4162 if (IK == IK_IntInduction && StepValue->isOne()) { 4163 // Use the phi node with the widest type as induction. Use the last 4164 // one if there are multiple (no good reason for doing this other 4165 // than it is expedient). 4166 if (!Induction || PhiTy == WidestIndTy) 4167 Induction = Phi; 4168 } 4169 4170 DEBUG(dbgs() << "LV: Found an induction variable.\n"); 4171 Inductions[Phi] = InductionInfo(StartValue, IK, StepValue); 4172 4173 // Until we explicitly handle the case of an induction variable with 4174 // an outside loop user we have to give up vectorizing this loop. 4175 if (hasOutsideLoopUser(TheLoop, it, AllowedExit)) { 4176 emitAnalysis(VectorizationReport(it) << 4177 "use of induction value outside of the " 4178 "loop is not handled by vectorizer"); 4179 return false; 4180 } 4181 4182 continue; 4183 } 4184 4185 if (RecurrenceDescriptor::isReductionPHI(Phi, TheLoop, 4186 Reductions[Phi])) { 4187 if (Reductions[Phi].hasUnsafeAlgebra()) 4188 Requirements->addUnsafeAlgebraInst( 4189 Reductions[Phi].getUnsafeAlgebraInst()); 4190 AllowedExit.insert(Reductions[Phi].getLoopExitInstr()); 4191 continue; 4192 } 4193 4194 emitAnalysis(VectorizationReport(it) << 4195 "value that could not be identified as " 4196 "reduction is used outside the loop"); 4197 DEBUG(dbgs() << "LV: Found an unidentified PHI."<< *Phi <<"\n"); 4198 return false; 4199 }// end of PHI handling 4200 4201 // We handle calls that: 4202 // * Are debug info intrinsics. 4203 // * Have a mapping to an IR intrinsic. 4204 // * Have a vector version available. 4205 CallInst *CI = dyn_cast<CallInst>(it); 4206 if (CI && !getIntrinsicIDForCall(CI, TLI) && !isa<DbgInfoIntrinsic>(CI) && 4207 !(CI->getCalledFunction() && TLI && 4208 TLI->isFunctionVectorizable(CI->getCalledFunction()->getName()))) { 4209 emitAnalysis(VectorizationReport(it) << 4210 "call instruction cannot be vectorized"); 4211 DEBUG(dbgs() << "LV: Found a non-intrinsic, non-libfunc callsite.\n"); 4212 return false; 4213 } 4214 4215 // Intrinsics such as powi,cttz and ctlz are legal to vectorize if the 4216 // second argument is the same (i.e. loop invariant) 4217 if (CI && 4218 hasVectorInstrinsicScalarOpd(getIntrinsicIDForCall(CI, TLI), 1)) { 4219 if (!SE->isLoopInvariant(SE->getSCEV(CI->getOperand(1)), TheLoop)) { 4220 emitAnalysis(VectorizationReport(it) 4221 << "intrinsic instruction cannot be vectorized"); 4222 DEBUG(dbgs() << "LV: Found unvectorizable intrinsic " << *CI << "\n"); 4223 return false; 4224 } 4225 } 4226 4227 // Check that the instruction return type is vectorizable. 4228 // Also, we can't vectorize extractelement instructions. 4229 if ((!VectorType::isValidElementType(it->getType()) && 4230 !it->getType()->isVoidTy()) || isa<ExtractElementInst>(it)) { 4231 emitAnalysis(VectorizationReport(it) 4232 << "instruction return type cannot be vectorized"); 4233 DEBUG(dbgs() << "LV: Found unvectorizable type.\n"); 4234 return false; 4235 } 4236 4237 // Check that the stored type is vectorizable. 4238 if (StoreInst *ST = dyn_cast<StoreInst>(it)) { 4239 Type *T = ST->getValueOperand()->getType(); 4240 if (!VectorType::isValidElementType(T)) { 4241 emitAnalysis(VectorizationReport(ST) << 4242 "store instruction cannot be vectorized"); 4243 return false; 4244 } 4245 if (EnableMemAccessVersioning) 4246 collectStridedAccess(ST); 4247 } 4248 4249 if (EnableMemAccessVersioning) 4250 if (LoadInst *LI = dyn_cast<LoadInst>(it)) 4251 collectStridedAccess(LI); 4252 4253 // Reduction instructions are allowed to have exit users. 4254 // All other instructions must not have external users. 4255 if (hasOutsideLoopUser(TheLoop, it, AllowedExit)) { 4256 emitAnalysis(VectorizationReport(it) << 4257 "value cannot be used outside the loop"); 4258 return false; 4259 } 4260 4261 } // next instr. 4262 4263 } 4264 4265 if (!Induction) { 4266 DEBUG(dbgs() << "LV: Did not find one integer induction var.\n"); 4267 if (Inductions.empty()) { 4268 emitAnalysis(VectorizationReport() 4269 << "loop induction variable could not be identified"); 4270 return false; 4271 } 4272 } 4273 4274 return true; 4275 } 4276 4277 void LoopVectorizationLegality::collectStridedAccess(Value *MemAccess) { 4278 Value *Ptr = nullptr; 4279 if (LoadInst *LI = dyn_cast<LoadInst>(MemAccess)) 4280 Ptr = LI->getPointerOperand(); 4281 else if (StoreInst *SI = dyn_cast<StoreInst>(MemAccess)) 4282 Ptr = SI->getPointerOperand(); 4283 else 4284 return; 4285 4286 Value *Stride = getStrideFromPointer(Ptr, SE, TheLoop); 4287 if (!Stride) 4288 return; 4289 4290 DEBUG(dbgs() << "LV: Found a strided access that we can version"); 4291 DEBUG(dbgs() << " Ptr: " << *Ptr << " Stride: " << *Stride << "\n"); 4292 Strides[Ptr] = Stride; 4293 StrideSet.insert(Stride); 4294 } 4295 4296 void LoopVectorizationLegality::collectLoopUniforms() { 4297 // We now know that the loop is vectorizable! 4298 // Collect variables that will remain uniform after vectorization. 4299 std::vector<Value*> Worklist; 4300 BasicBlock *Latch = TheLoop->getLoopLatch(); 4301 4302 // Start with the conditional branch and walk up the block. 4303 Worklist.push_back(Latch->getTerminator()->getOperand(0)); 4304 4305 // Also add all consecutive pointer values; these values will be uniform 4306 // after vectorization (and subsequent cleanup) and, until revectorization is 4307 // supported, all dependencies must also be uniform. 4308 for (Loop::block_iterator B = TheLoop->block_begin(), 4309 BE = TheLoop->block_end(); B != BE; ++B) 4310 for (BasicBlock::iterator I = (*B)->begin(), IE = (*B)->end(); 4311 I != IE; ++I) 4312 if (I->getType()->isPointerTy() && isConsecutivePtr(I)) 4313 Worklist.insert(Worklist.end(), I->op_begin(), I->op_end()); 4314 4315 while (!Worklist.empty()) { 4316 Instruction *I = dyn_cast<Instruction>(Worklist.back()); 4317 Worklist.pop_back(); 4318 4319 // Look at instructions inside this loop. 4320 // Stop when reaching PHI nodes. 4321 // TODO: we need to follow values all over the loop, not only in this block. 4322 if (!I || !TheLoop->contains(I) || isa<PHINode>(I)) 4323 continue; 4324 4325 // This is a known uniform. 4326 Uniforms.insert(I); 4327 4328 // Insert all operands. 4329 Worklist.insert(Worklist.end(), I->op_begin(), I->op_end()); 4330 } 4331 } 4332 4333 bool LoopVectorizationLegality::canVectorizeMemory() { 4334 LAI = &LAA->getInfo(TheLoop, Strides); 4335 auto &OptionalReport = LAI->getReport(); 4336 if (OptionalReport) 4337 emitAnalysis(VectorizationReport(*OptionalReport)); 4338 if (!LAI->canVectorizeMemory()) 4339 return false; 4340 4341 if (LAI->hasStoreToLoopInvariantAddress()) { 4342 emitAnalysis( 4343 VectorizationReport() 4344 << "write to a loop invariant address could not be vectorized"); 4345 DEBUG(dbgs() << "LV: We don't allow storing to uniform addresses\n"); 4346 return false; 4347 } 4348 4349 Requirements->addRuntimePointerChecks(LAI->getNumRuntimePointerChecks()); 4350 4351 return true; 4352 } 4353 4354 LoopVectorizationLegality::InductionKind 4355 LoopVectorizationLegality::isInductionVariable(PHINode *Phi, 4356 ConstantInt *&StepValue) { 4357 if (!isInductionPHI(Phi, SE, StepValue)) 4358 return IK_NoInduction; 4359 4360 Type *PhiTy = Phi->getType(); 4361 // Found an Integer induction variable. 4362 if (PhiTy->isIntegerTy()) 4363 return IK_IntInduction; 4364 // Found an Pointer induction variable. 4365 return IK_PtrInduction; 4366 } 4367 4368 bool LoopVectorizationLegality::isInductionVariable(const Value *V) { 4369 Value *In0 = const_cast<Value*>(V); 4370 PHINode *PN = dyn_cast_or_null<PHINode>(In0); 4371 if (!PN) 4372 return false; 4373 4374 return Inductions.count(PN); 4375 } 4376 4377 bool LoopVectorizationLegality::blockNeedsPredication(BasicBlock *BB) { 4378 return LoopAccessInfo::blockNeedsPredication(BB, TheLoop, DT); 4379 } 4380 4381 bool LoopVectorizationLegality::blockCanBePredicated(BasicBlock *BB, 4382 SmallPtrSetImpl<Value *> &SafePtrs) { 4383 4384 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 4385 // Check that we don't have a constant expression that can trap as operand. 4386 for (Instruction::op_iterator OI = it->op_begin(), OE = it->op_end(); 4387 OI != OE; ++OI) { 4388 if (Constant *C = dyn_cast<Constant>(*OI)) 4389 if (C->canTrap()) 4390 return false; 4391 } 4392 // We might be able to hoist the load. 4393 if (it->mayReadFromMemory()) { 4394 LoadInst *LI = dyn_cast<LoadInst>(it); 4395 if (!LI) 4396 return false; 4397 if (!SafePtrs.count(LI->getPointerOperand())) { 4398 if (isLegalMaskedLoad(LI->getType(), LI->getPointerOperand())) { 4399 MaskedOp.insert(LI); 4400 continue; 4401 } 4402 return false; 4403 } 4404 } 4405 4406 // We don't predicate stores at the moment. 4407 if (it->mayWriteToMemory()) { 4408 StoreInst *SI = dyn_cast<StoreInst>(it); 4409 // We only support predication of stores in basic blocks with one 4410 // predecessor. 4411 if (!SI) 4412 return false; 4413 4414 bool isSafePtr = (SafePtrs.count(SI->getPointerOperand()) != 0); 4415 bool isSinglePredecessor = SI->getParent()->getSinglePredecessor(); 4416 4417 if (++NumPredStores > NumberOfStoresToPredicate || !isSafePtr || 4418 !isSinglePredecessor) { 4419 // Build a masked store if it is legal for the target, otherwise scalarize 4420 // the block. 4421 bool isLegalMaskedOp = 4422 isLegalMaskedStore(SI->getValueOperand()->getType(), 4423 SI->getPointerOperand()); 4424 if (isLegalMaskedOp) { 4425 --NumPredStores; 4426 MaskedOp.insert(SI); 4427 continue; 4428 } 4429 return false; 4430 } 4431 } 4432 if (it->mayThrow()) 4433 return false; 4434 4435 // The instructions below can trap. 4436 switch (it->getOpcode()) { 4437 default: continue; 4438 case Instruction::UDiv: 4439 case Instruction::SDiv: 4440 case Instruction::URem: 4441 case Instruction::SRem: 4442 return false; 4443 } 4444 } 4445 4446 return true; 4447 } 4448 4449 void InterleavedAccessInfo::collectConstStridedAccesses( 4450 MapVector<Instruction *, StrideDescriptor> &StrideAccesses, 4451 const ValueToValueMap &Strides) { 4452 // Holds load/store instructions in program order. 4453 SmallVector<Instruction *, 16> AccessList; 4454 4455 for (auto *BB : TheLoop->getBlocks()) { 4456 bool IsPred = LoopAccessInfo::blockNeedsPredication(BB, TheLoop, DT); 4457 4458 for (auto &I : *BB) { 4459 if (!isa<LoadInst>(&I) && !isa<StoreInst>(&I)) 4460 continue; 4461 // FIXME: Currently we can't handle mixed accesses and predicated accesses 4462 if (IsPred) 4463 return; 4464 4465 AccessList.push_back(&I); 4466 } 4467 } 4468 4469 if (AccessList.empty()) 4470 return; 4471 4472 auto &DL = TheLoop->getHeader()->getModule()->getDataLayout(); 4473 for (auto I : AccessList) { 4474 LoadInst *LI = dyn_cast<LoadInst>(I); 4475 StoreInst *SI = dyn_cast<StoreInst>(I); 4476 4477 Value *Ptr = LI ? LI->getPointerOperand() : SI->getPointerOperand(); 4478 int Stride = isStridedPtr(SE, Ptr, TheLoop, Strides); 4479 4480 // The factor of the corresponding interleave group. 4481 unsigned Factor = std::abs(Stride); 4482 4483 // Ignore the access if the factor is too small or too large. 4484 if (Factor < 2 || Factor > MaxInterleaveGroupFactor) 4485 continue; 4486 4487 const SCEV *Scev = replaceSymbolicStrideSCEV(SE, Strides, Ptr); 4488 PointerType *PtrTy = dyn_cast<PointerType>(Ptr->getType()); 4489 unsigned Size = DL.getTypeAllocSize(PtrTy->getElementType()); 4490 4491 // An alignment of 0 means target ABI alignment. 4492 unsigned Align = LI ? LI->getAlignment() : SI->getAlignment(); 4493 if (!Align) 4494 Align = DL.getABITypeAlignment(PtrTy->getElementType()); 4495 4496 StrideAccesses[I] = StrideDescriptor(Stride, Scev, Size, Align); 4497 } 4498 } 4499 4500 // Analyze interleaved accesses and collect them into interleave groups. 4501 // 4502 // Notice that the vectorization on interleaved groups will change instruction 4503 // orders and may break dependences. But the memory dependence check guarantees 4504 // that there is no overlap between two pointers of different strides, element 4505 // sizes or underlying bases. 4506 // 4507 // For pointers sharing the same stride, element size and underlying base, no 4508 // need to worry about Read-After-Write dependences and Write-After-Read 4509 // dependences. 4510 // 4511 // E.g. The RAW dependence: A[i] = a; 4512 // b = A[i]; 4513 // This won't exist as it is a store-load forwarding conflict, which has 4514 // already been checked and forbidden in the dependence check. 4515 // 4516 // E.g. The WAR dependence: a = A[i]; // (1) 4517 // A[i] = b; // (2) 4518 // The store group of (2) is always inserted at or below (2), and the load group 4519 // of (1) is always inserted at or above (1). The dependence is safe. 4520 void InterleavedAccessInfo::analyzeInterleaving( 4521 const ValueToValueMap &Strides) { 4522 DEBUG(dbgs() << "LV: Analyzing interleaved accesses...\n"); 4523 4524 // Holds all the stride accesses. 4525 MapVector<Instruction *, StrideDescriptor> StrideAccesses; 4526 collectConstStridedAccesses(StrideAccesses, Strides); 4527 4528 if (StrideAccesses.empty()) 4529 return; 4530 4531 // Holds all interleaved store groups temporarily. 4532 SmallSetVector<InterleaveGroup *, 4> StoreGroups; 4533 4534 // Search the load-load/write-write pair B-A in bottom-up order and try to 4535 // insert B into the interleave group of A according to 3 rules: 4536 // 1. A and B have the same stride. 4537 // 2. A and B have the same memory object size. 4538 // 3. B belongs to the group according to the distance. 4539 // 4540 // The bottom-up order can avoid breaking the Write-After-Write dependences 4541 // between two pointers of the same base. 4542 // E.g. A[i] = a; (1) 4543 // A[i] = b; (2) 4544 // A[i+1] = c (3) 4545 // We form the group (2)+(3) in front, so (1) has to form groups with accesses 4546 // above (1), which guarantees that (1) is always above (2). 4547 for (auto I = StrideAccesses.rbegin(), E = StrideAccesses.rend(); I != E; 4548 ++I) { 4549 Instruction *A = I->first; 4550 StrideDescriptor DesA = I->second; 4551 4552 InterleaveGroup *Group = getInterleaveGroup(A); 4553 if (!Group) { 4554 DEBUG(dbgs() << "LV: Creating an interleave group with:" << *A << '\n'); 4555 Group = createInterleaveGroup(A, DesA.Stride, DesA.Align); 4556 } 4557 4558 if (A->mayWriteToMemory()) 4559 StoreGroups.insert(Group); 4560 4561 for (auto II = std::next(I); II != E; ++II) { 4562 Instruction *B = II->first; 4563 StrideDescriptor DesB = II->second; 4564 4565 // Ignore if B is already in a group or B is a different memory operation. 4566 if (isInterleaved(B) || A->mayReadFromMemory() != B->mayReadFromMemory()) 4567 continue; 4568 4569 // Check the rule 1 and 2. 4570 if (DesB.Stride != DesA.Stride || DesB.Size != DesA.Size) 4571 continue; 4572 4573 // Calculate the distance and prepare for the rule 3. 4574 const SCEVConstant *DistToA = 4575 dyn_cast<SCEVConstant>(SE->getMinusSCEV(DesB.Scev, DesA.Scev)); 4576 if (!DistToA) 4577 continue; 4578 4579 int DistanceToA = DistToA->getValue()->getValue().getSExtValue(); 4580 4581 // Skip if the distance is not multiple of size as they are not in the 4582 // same group. 4583 if (DistanceToA % static_cast<int>(DesA.Size)) 4584 continue; 4585 4586 // The index of B is the index of A plus the related index to A. 4587 int IndexB = 4588 Group->getIndex(A) + DistanceToA / static_cast<int>(DesA.Size); 4589 4590 // Try to insert B into the group. 4591 if (Group->insertMember(B, IndexB, DesB.Align)) { 4592 DEBUG(dbgs() << "LV: Inserted:" << *B << '\n' 4593 << " into the interleave group with" << *A << '\n'); 4594 InterleaveGroupMap[B] = Group; 4595 4596 // Set the first load in program order as the insert position. 4597 if (B->mayReadFromMemory()) 4598 Group->setInsertPos(B); 4599 } 4600 } // Iteration on instruction B 4601 } // Iteration on instruction A 4602 4603 // Remove interleaved store groups with gaps. 4604 for (InterleaveGroup *Group : StoreGroups) 4605 if (Group->getNumMembers() != Group->getFactor()) 4606 releaseGroup(Group); 4607 } 4608 4609 LoopVectorizationCostModel::VectorizationFactor 4610 LoopVectorizationCostModel::selectVectorizationFactor(bool OptForSize) { 4611 // Width 1 means no vectorize 4612 VectorizationFactor Factor = { 1U, 0U }; 4613 if (OptForSize && Legal->getRuntimePointerChecking()->Need) { 4614 emitAnalysis(VectorizationReport() << 4615 "runtime pointer checks needed. Enable vectorization of this " 4616 "loop with '#pragma clang loop vectorize(enable)' when " 4617 "compiling with -Os/-Oz"); 4618 DEBUG(dbgs() << 4619 "LV: Aborting. Runtime ptr check is required with -Os/-Oz.\n"); 4620 return Factor; 4621 } 4622 4623 if (!EnableCondStoresVectorization && Legal->getNumPredStores()) { 4624 emitAnalysis(VectorizationReport() << 4625 "store that is conditionally executed prevents vectorization"); 4626 DEBUG(dbgs() << "LV: No vectorization. There are conditional stores.\n"); 4627 return Factor; 4628 } 4629 4630 // Find the trip count. 4631 unsigned TC = SE->getSmallConstantTripCount(TheLoop); 4632 DEBUG(dbgs() << "LV: Found trip count: " << TC << '\n'); 4633 4634 unsigned WidestType = getWidestType(); 4635 unsigned WidestRegister = TTI.getRegisterBitWidth(true); 4636 unsigned MaxSafeDepDist = -1U; 4637 if (Legal->getMaxSafeDepDistBytes() != -1U) 4638 MaxSafeDepDist = Legal->getMaxSafeDepDistBytes() * 8; 4639 WidestRegister = ((WidestRegister < MaxSafeDepDist) ? 4640 WidestRegister : MaxSafeDepDist); 4641 unsigned MaxVectorSize = WidestRegister / WidestType; 4642 DEBUG(dbgs() << "LV: The Widest type: " << WidestType << " bits.\n"); 4643 DEBUG(dbgs() << "LV: The Widest register is: " 4644 << WidestRegister << " bits.\n"); 4645 4646 if (MaxVectorSize == 0) { 4647 DEBUG(dbgs() << "LV: The target has no vector registers.\n"); 4648 MaxVectorSize = 1; 4649 } 4650 4651 assert(MaxVectorSize <= 64 && "Did not expect to pack so many elements" 4652 " into one vector!"); 4653 4654 unsigned VF = MaxVectorSize; 4655 4656 // If we optimize the program for size, avoid creating the tail loop. 4657 if (OptForSize) { 4658 // If we are unable to calculate the trip count then don't try to vectorize. 4659 if (TC < 2) { 4660 emitAnalysis 4661 (VectorizationReport() << 4662 "unable to calculate the loop count due to complex control flow"); 4663 DEBUG(dbgs() << "LV: Aborting. A tail loop is required with -Os/-Oz.\n"); 4664 return Factor; 4665 } 4666 4667 // Find the maximum SIMD width that can fit within the trip count. 4668 VF = TC % MaxVectorSize; 4669 4670 if (VF == 0) 4671 VF = MaxVectorSize; 4672 else { 4673 // If the trip count that we found modulo the vectorization factor is not 4674 // zero then we require a tail. 4675 emitAnalysis(VectorizationReport() << 4676 "cannot optimize for size and vectorize at the " 4677 "same time. Enable vectorization of this loop " 4678 "with '#pragma clang loop vectorize(enable)' " 4679 "when compiling with -Os/-Oz"); 4680 DEBUG(dbgs() << "LV: Aborting. A tail loop is required with -Os/-Oz.\n"); 4681 return Factor; 4682 } 4683 } 4684 4685 int UserVF = Hints->getWidth(); 4686 if (UserVF != 0) { 4687 assert(isPowerOf2_32(UserVF) && "VF needs to be a power of two"); 4688 DEBUG(dbgs() << "LV: Using user VF " << UserVF << ".\n"); 4689 4690 Factor.Width = UserVF; 4691 return Factor; 4692 } 4693 4694 float Cost = expectedCost(1); 4695 #ifndef NDEBUG 4696 const float ScalarCost = Cost; 4697 #endif /* NDEBUG */ 4698 unsigned Width = 1; 4699 DEBUG(dbgs() << "LV: Scalar loop costs: " << (int)ScalarCost << ".\n"); 4700 4701 bool ForceVectorization = Hints->getForce() == LoopVectorizeHints::FK_Enabled; 4702 // Ignore scalar width, because the user explicitly wants vectorization. 4703 if (ForceVectorization && VF > 1) { 4704 Width = 2; 4705 Cost = expectedCost(Width) / (float)Width; 4706 } 4707 4708 for (unsigned i=2; i <= VF; i*=2) { 4709 // Notice that the vector loop needs to be executed less times, so 4710 // we need to divide the cost of the vector loops by the width of 4711 // the vector elements. 4712 float VectorCost = expectedCost(i) / (float)i; 4713 DEBUG(dbgs() << "LV: Vector loop of width " << i << " costs: " << 4714 (int)VectorCost << ".\n"); 4715 if (VectorCost < Cost) { 4716 Cost = VectorCost; 4717 Width = i; 4718 } 4719 } 4720 4721 DEBUG(if (ForceVectorization && Width > 1 && Cost >= ScalarCost) dbgs() 4722 << "LV: Vectorization seems to be not beneficial, " 4723 << "but was forced by a user.\n"); 4724 DEBUG(dbgs() << "LV: Selecting VF: "<< Width << ".\n"); 4725 Factor.Width = Width; 4726 Factor.Cost = Width * Cost; 4727 return Factor; 4728 } 4729 4730 unsigned LoopVectorizationCostModel::getWidestType() { 4731 unsigned MaxWidth = 8; 4732 const DataLayout &DL = TheFunction->getParent()->getDataLayout(); 4733 4734 // For each block. 4735 for (Loop::block_iterator bb = TheLoop->block_begin(), 4736 be = TheLoop->block_end(); bb != be; ++bb) { 4737 BasicBlock *BB = *bb; 4738 4739 // For each instruction in the loop. 4740 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 4741 Type *T = it->getType(); 4742 4743 // Ignore ephemeral values. 4744 if (EphValues.count(it)) 4745 continue; 4746 4747 // Only examine Loads, Stores and PHINodes. 4748 if (!isa<LoadInst>(it) && !isa<StoreInst>(it) && !isa<PHINode>(it)) 4749 continue; 4750 4751 // Examine PHI nodes that are reduction variables. 4752 if (PHINode *PN = dyn_cast<PHINode>(it)) 4753 if (!Legal->getReductionVars()->count(PN)) 4754 continue; 4755 4756 // Examine the stored values. 4757 if (StoreInst *ST = dyn_cast<StoreInst>(it)) 4758 T = ST->getValueOperand()->getType(); 4759 4760 // Ignore loaded pointer types and stored pointer types that are not 4761 // consecutive. However, we do want to take consecutive stores/loads of 4762 // pointer vectors into account. 4763 if (T->isPointerTy() && !isConsecutiveLoadOrStore(it)) 4764 continue; 4765 4766 MaxWidth = std::max(MaxWidth, 4767 (unsigned)DL.getTypeSizeInBits(T->getScalarType())); 4768 } 4769 } 4770 4771 return MaxWidth; 4772 } 4773 4774 unsigned LoopVectorizationCostModel::selectInterleaveCount(bool OptForSize, 4775 unsigned VF, 4776 unsigned LoopCost) { 4777 4778 // -- The interleave heuristics -- 4779 // We interleave the loop in order to expose ILP and reduce the loop overhead. 4780 // There are many micro-architectural considerations that we can't predict 4781 // at this level. For example, frontend pressure (on decode or fetch) due to 4782 // code size, or the number and capabilities of the execution ports. 4783 // 4784 // We use the following heuristics to select the interleave count: 4785 // 1. If the code has reductions, then we interleave to break the cross 4786 // iteration dependency. 4787 // 2. If the loop is really small, then we interleave to reduce the loop 4788 // overhead. 4789 // 3. We don't interleave if we think that we will spill registers to memory 4790 // due to the increased register pressure. 4791 4792 // When we optimize for size, we don't interleave. 4793 if (OptForSize) 4794 return 1; 4795 4796 // We used the distance for the interleave count. 4797 if (Legal->getMaxSafeDepDistBytes() != -1U) 4798 return 1; 4799 4800 // Do not interleave loops with a relatively small trip count. 4801 unsigned TC = SE->getSmallConstantTripCount(TheLoop); 4802 if (TC > 1 && TC < TinyTripCountInterleaveThreshold) 4803 return 1; 4804 4805 unsigned TargetNumRegisters = TTI.getNumberOfRegisters(VF > 1); 4806 DEBUG(dbgs() << "LV: The target has " << TargetNumRegisters << 4807 " registers\n"); 4808 4809 if (VF == 1) { 4810 if (ForceTargetNumScalarRegs.getNumOccurrences() > 0) 4811 TargetNumRegisters = ForceTargetNumScalarRegs; 4812 } else { 4813 if (ForceTargetNumVectorRegs.getNumOccurrences() > 0) 4814 TargetNumRegisters = ForceTargetNumVectorRegs; 4815 } 4816 4817 LoopVectorizationCostModel::RegisterUsage R = calculateRegisterUsage(); 4818 // We divide by these constants so assume that we have at least one 4819 // instruction that uses at least one register. 4820 R.MaxLocalUsers = std::max(R.MaxLocalUsers, 1U); 4821 R.NumInstructions = std::max(R.NumInstructions, 1U); 4822 4823 // We calculate the interleave count using the following formula. 4824 // Subtract the number of loop invariants from the number of available 4825 // registers. These registers are used by all of the interleaved instances. 4826 // Next, divide the remaining registers by the number of registers that is 4827 // required by the loop, in order to estimate how many parallel instances 4828 // fit without causing spills. All of this is rounded down if necessary to be 4829 // a power of two. We want power of two interleave count to simplify any 4830 // addressing operations or alignment considerations. 4831 unsigned IC = PowerOf2Floor((TargetNumRegisters - R.LoopInvariantRegs) / 4832 R.MaxLocalUsers); 4833 4834 // Don't count the induction variable as interleaved. 4835 if (EnableIndVarRegisterHeur) 4836 IC = PowerOf2Floor((TargetNumRegisters - R.LoopInvariantRegs - 1) / 4837 std::max(1U, (R.MaxLocalUsers - 1))); 4838 4839 // Clamp the interleave ranges to reasonable counts. 4840 unsigned MaxInterleaveCount = TTI.getMaxInterleaveFactor(VF); 4841 4842 // Check if the user has overridden the max. 4843 if (VF == 1) { 4844 if (ForceTargetMaxScalarInterleaveFactor.getNumOccurrences() > 0) 4845 MaxInterleaveCount = ForceTargetMaxScalarInterleaveFactor; 4846 } else { 4847 if (ForceTargetMaxVectorInterleaveFactor.getNumOccurrences() > 0) 4848 MaxInterleaveCount = ForceTargetMaxVectorInterleaveFactor; 4849 } 4850 4851 // If we did not calculate the cost for VF (because the user selected the VF) 4852 // then we calculate the cost of VF here. 4853 if (LoopCost == 0) 4854 LoopCost = expectedCost(VF); 4855 4856 // Clamp the calculated IC to be between the 1 and the max interleave count 4857 // that the target allows. 4858 if (IC > MaxInterleaveCount) 4859 IC = MaxInterleaveCount; 4860 else if (IC < 1) 4861 IC = 1; 4862 4863 // Interleave if we vectorized this loop and there is a reduction that could 4864 // benefit from interleaving. 4865 if (VF > 1 && Legal->getReductionVars()->size()) { 4866 DEBUG(dbgs() << "LV: Interleaving because of reductions.\n"); 4867 return IC; 4868 } 4869 4870 // Note that if we've already vectorized the loop we will have done the 4871 // runtime check and so interleaving won't require further checks. 4872 bool InterleavingRequiresRuntimePointerCheck = 4873 (VF == 1 && Legal->getRuntimePointerChecking()->Need); 4874 4875 // We want to interleave small loops in order to reduce the loop overhead and 4876 // potentially expose ILP opportunities. 4877 DEBUG(dbgs() << "LV: Loop cost is " << LoopCost << '\n'); 4878 if (!InterleavingRequiresRuntimePointerCheck && LoopCost < SmallLoopCost) { 4879 // We assume that the cost overhead is 1 and we use the cost model 4880 // to estimate the cost of the loop and interleave until the cost of the 4881 // loop overhead is about 5% of the cost of the loop. 4882 unsigned SmallIC = 4883 std::min(IC, (unsigned)PowerOf2Floor(SmallLoopCost / LoopCost)); 4884 4885 // Interleave until store/load ports (estimated by max interleave count) are 4886 // saturated. 4887 unsigned NumStores = Legal->getNumStores(); 4888 unsigned NumLoads = Legal->getNumLoads(); 4889 unsigned StoresIC = IC / (NumStores ? NumStores : 1); 4890 unsigned LoadsIC = IC / (NumLoads ? NumLoads : 1); 4891 4892 // If we have a scalar reduction (vector reductions are already dealt with 4893 // by this point), we can increase the critical path length if the loop 4894 // we're interleaving is inside another loop. Limit, by default to 2, so the 4895 // critical path only gets increased by one reduction operation. 4896 if (Legal->getReductionVars()->size() && 4897 TheLoop->getLoopDepth() > 1) { 4898 unsigned F = static_cast<unsigned>(MaxNestedScalarReductionIC); 4899 SmallIC = std::min(SmallIC, F); 4900 StoresIC = std::min(StoresIC, F); 4901 LoadsIC = std::min(LoadsIC, F); 4902 } 4903 4904 if (EnableLoadStoreRuntimeInterleave && 4905 std::max(StoresIC, LoadsIC) > SmallIC) { 4906 DEBUG(dbgs() << "LV: Interleaving to saturate store or load ports.\n"); 4907 return std::max(StoresIC, LoadsIC); 4908 } 4909 4910 DEBUG(dbgs() << "LV: Interleaving to reduce branch cost.\n"); 4911 return SmallIC; 4912 } 4913 4914 // Interleave if this is a large loop (small loops are already dealt with by 4915 // this 4916 // point) that could benefit from interleaving. 4917 bool HasReductions = (Legal->getReductionVars()->size() > 0); 4918 if (TTI.enableAggressiveInterleaving(HasReductions)) { 4919 DEBUG(dbgs() << "LV: Interleaving to expose ILP.\n"); 4920 return IC; 4921 } 4922 4923 DEBUG(dbgs() << "LV: Not Interleaving.\n"); 4924 return 1; 4925 } 4926 4927 LoopVectorizationCostModel::RegisterUsage 4928 LoopVectorizationCostModel::calculateRegisterUsage() { 4929 // This function calculates the register usage by measuring the highest number 4930 // of values that are alive at a single location. Obviously, this is a very 4931 // rough estimation. We scan the loop in a topological order in order and 4932 // assign a number to each instruction. We use RPO to ensure that defs are 4933 // met before their users. We assume that each instruction that has in-loop 4934 // users starts an interval. We record every time that an in-loop value is 4935 // used, so we have a list of the first and last occurrences of each 4936 // instruction. Next, we transpose this data structure into a multi map that 4937 // holds the list of intervals that *end* at a specific location. This multi 4938 // map allows us to perform a linear search. We scan the instructions linearly 4939 // and record each time that a new interval starts, by placing it in a set. 4940 // If we find this value in the multi-map then we remove it from the set. 4941 // The max register usage is the maximum size of the set. 4942 // We also search for instructions that are defined outside the loop, but are 4943 // used inside the loop. We need this number separately from the max-interval 4944 // usage number because when we unroll, loop-invariant values do not take 4945 // more register. 4946 LoopBlocksDFS DFS(TheLoop); 4947 DFS.perform(LI); 4948 4949 RegisterUsage R; 4950 R.NumInstructions = 0; 4951 4952 // Each 'key' in the map opens a new interval. The values 4953 // of the map are the index of the 'last seen' usage of the 4954 // instruction that is the key. 4955 typedef DenseMap<Instruction*, unsigned> IntervalMap; 4956 // Maps instruction to its index. 4957 DenseMap<unsigned, Instruction*> IdxToInstr; 4958 // Marks the end of each interval. 4959 IntervalMap EndPoint; 4960 // Saves the list of instruction indices that are used in the loop. 4961 SmallSet<Instruction*, 8> Ends; 4962 // Saves the list of values that are used in the loop but are 4963 // defined outside the loop, such as arguments and constants. 4964 SmallPtrSet<Value*, 8> LoopInvariants; 4965 4966 unsigned Index = 0; 4967 for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(), 4968 be = DFS.endRPO(); bb != be; ++bb) { 4969 R.NumInstructions += (*bb)->size(); 4970 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e; 4971 ++it) { 4972 Instruction *I = it; 4973 IdxToInstr[Index++] = I; 4974 4975 // Save the end location of each USE. 4976 for (unsigned i = 0; i < I->getNumOperands(); ++i) { 4977 Value *U = I->getOperand(i); 4978 Instruction *Instr = dyn_cast<Instruction>(U); 4979 4980 // Ignore non-instruction values such as arguments, constants, etc. 4981 if (!Instr) continue; 4982 4983 // If this instruction is outside the loop then record it and continue. 4984 if (!TheLoop->contains(Instr)) { 4985 LoopInvariants.insert(Instr); 4986 continue; 4987 } 4988 4989 // Overwrite previous end points. 4990 EndPoint[Instr] = Index; 4991 Ends.insert(Instr); 4992 } 4993 } 4994 } 4995 4996 // Saves the list of intervals that end with the index in 'key'. 4997 typedef SmallVector<Instruction*, 2> InstrList; 4998 DenseMap<unsigned, InstrList> TransposeEnds; 4999 5000 // Transpose the EndPoints to a list of values that end at each index. 5001 for (IntervalMap::iterator it = EndPoint.begin(), e = EndPoint.end(); 5002 it != e; ++it) 5003 TransposeEnds[it->second].push_back(it->first); 5004 5005 SmallSet<Instruction*, 8> OpenIntervals; 5006 unsigned MaxUsage = 0; 5007 5008 5009 DEBUG(dbgs() << "LV(REG): Calculating max register usage:\n"); 5010 for (unsigned int i = 0; i < Index; ++i) { 5011 Instruction *I = IdxToInstr[i]; 5012 // Ignore instructions that are never used within the loop. 5013 if (!Ends.count(I)) continue; 5014 5015 // Ignore ephemeral values. 5016 if (EphValues.count(I)) 5017 continue; 5018 5019 // Remove all of the instructions that end at this location. 5020 InstrList &List = TransposeEnds[i]; 5021 for (unsigned int j=0, e = List.size(); j < e; ++j) 5022 OpenIntervals.erase(List[j]); 5023 5024 // Count the number of live interals. 5025 MaxUsage = std::max(MaxUsage, OpenIntervals.size()); 5026 5027 DEBUG(dbgs() << "LV(REG): At #" << i << " Interval # " << 5028 OpenIntervals.size() << '\n'); 5029 5030 // Add the current instruction to the list of open intervals. 5031 OpenIntervals.insert(I); 5032 } 5033 5034 unsigned Invariant = LoopInvariants.size(); 5035 DEBUG(dbgs() << "LV(REG): Found max usage: " << MaxUsage << '\n'); 5036 DEBUG(dbgs() << "LV(REG): Found invariant usage: " << Invariant << '\n'); 5037 DEBUG(dbgs() << "LV(REG): LoopSize: " << R.NumInstructions << '\n'); 5038 5039 R.LoopInvariantRegs = Invariant; 5040 R.MaxLocalUsers = MaxUsage; 5041 return R; 5042 } 5043 5044 unsigned LoopVectorizationCostModel::expectedCost(unsigned VF) { 5045 unsigned Cost = 0; 5046 5047 // For each block. 5048 for (Loop::block_iterator bb = TheLoop->block_begin(), 5049 be = TheLoop->block_end(); bb != be; ++bb) { 5050 unsigned BlockCost = 0; 5051 BasicBlock *BB = *bb; 5052 5053 // For each instruction in the old loop. 5054 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 5055 // Skip dbg intrinsics. 5056 if (isa<DbgInfoIntrinsic>(it)) 5057 continue; 5058 5059 // Ignore ephemeral values. 5060 if (EphValues.count(it)) 5061 continue; 5062 5063 unsigned C = getInstructionCost(it, VF); 5064 5065 // Check if we should override the cost. 5066 if (ForceTargetInstructionCost.getNumOccurrences() > 0) 5067 C = ForceTargetInstructionCost; 5068 5069 BlockCost += C; 5070 DEBUG(dbgs() << "LV: Found an estimated cost of " << C << " for VF " << 5071 VF << " For instruction: " << *it << '\n'); 5072 } 5073 5074 // We assume that if-converted blocks have a 50% chance of being executed. 5075 // When the code is scalar then some of the blocks are avoided due to CF. 5076 // When the code is vectorized we execute all code paths. 5077 if (VF == 1 && Legal->blockNeedsPredication(*bb)) 5078 BlockCost /= 2; 5079 5080 Cost += BlockCost; 5081 } 5082 5083 return Cost; 5084 } 5085 5086 /// \brief Check whether the address computation for a non-consecutive memory 5087 /// access looks like an unlikely candidate for being merged into the indexing 5088 /// mode. 5089 /// 5090 /// We look for a GEP which has one index that is an induction variable and all 5091 /// other indices are loop invariant. If the stride of this access is also 5092 /// within a small bound we decide that this address computation can likely be 5093 /// merged into the addressing mode. 5094 /// In all other cases, we identify the address computation as complex. 5095 static bool isLikelyComplexAddressComputation(Value *Ptr, 5096 LoopVectorizationLegality *Legal, 5097 ScalarEvolution *SE, 5098 const Loop *TheLoop) { 5099 GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr); 5100 if (!Gep) 5101 return true; 5102 5103 // We are looking for a gep with all loop invariant indices except for one 5104 // which should be an induction variable. 5105 unsigned NumOperands = Gep->getNumOperands(); 5106 for (unsigned i = 1; i < NumOperands; ++i) { 5107 Value *Opd = Gep->getOperand(i); 5108 if (!SE->isLoopInvariant(SE->getSCEV(Opd), TheLoop) && 5109 !Legal->isInductionVariable(Opd)) 5110 return true; 5111 } 5112 5113 // Now we know we have a GEP ptr, %inv, %ind, %inv. Make sure that the step 5114 // can likely be merged into the address computation. 5115 unsigned MaxMergeDistance = 64; 5116 5117 const SCEVAddRecExpr *AddRec = dyn_cast<SCEVAddRecExpr>(SE->getSCEV(Ptr)); 5118 if (!AddRec) 5119 return true; 5120 5121 // Check the step is constant. 5122 const SCEV *Step = AddRec->getStepRecurrence(*SE); 5123 // Calculate the pointer stride and check if it is consecutive. 5124 const SCEVConstant *C = dyn_cast<SCEVConstant>(Step); 5125 if (!C) 5126 return true; 5127 5128 const APInt &APStepVal = C->getValue()->getValue(); 5129 5130 // Huge step value - give up. 5131 if (APStepVal.getBitWidth() > 64) 5132 return true; 5133 5134 int64_t StepVal = APStepVal.getSExtValue(); 5135 5136 return StepVal > MaxMergeDistance; 5137 } 5138 5139 static bool isStrideMul(Instruction *I, LoopVectorizationLegality *Legal) { 5140 if (Legal->hasStride(I->getOperand(0)) || Legal->hasStride(I->getOperand(1))) 5141 return true; 5142 return false; 5143 } 5144 5145 unsigned 5146 LoopVectorizationCostModel::getInstructionCost(Instruction *I, unsigned VF) { 5147 // If we know that this instruction will remain uniform, check the cost of 5148 // the scalar version. 5149 if (Legal->isUniformAfterVectorization(I)) 5150 VF = 1; 5151 5152 Type *RetTy = I->getType(); 5153 Type *VectorTy = ToVectorTy(RetTy, VF); 5154 5155 // TODO: We need to estimate the cost of intrinsic calls. 5156 switch (I->getOpcode()) { 5157 case Instruction::GetElementPtr: 5158 // We mark this instruction as zero-cost because the cost of GEPs in 5159 // vectorized code depends on whether the corresponding memory instruction 5160 // is scalarized or not. Therefore, we handle GEPs with the memory 5161 // instruction cost. 5162 return 0; 5163 case Instruction::Br: { 5164 return TTI.getCFInstrCost(I->getOpcode()); 5165 } 5166 case Instruction::PHI: 5167 //TODO: IF-converted IFs become selects. 5168 return 0; 5169 case Instruction::Add: 5170 case Instruction::FAdd: 5171 case Instruction::Sub: 5172 case Instruction::FSub: 5173 case Instruction::Mul: 5174 case Instruction::FMul: 5175 case Instruction::UDiv: 5176 case Instruction::SDiv: 5177 case Instruction::FDiv: 5178 case Instruction::URem: 5179 case Instruction::SRem: 5180 case Instruction::FRem: 5181 case Instruction::Shl: 5182 case Instruction::LShr: 5183 case Instruction::AShr: 5184 case Instruction::And: 5185 case Instruction::Or: 5186 case Instruction::Xor: { 5187 // Since we will replace the stride by 1 the multiplication should go away. 5188 if (I->getOpcode() == Instruction::Mul && isStrideMul(I, Legal)) 5189 return 0; 5190 // Certain instructions can be cheaper to vectorize if they have a constant 5191 // second vector operand. One example of this are shifts on x86. 5192 TargetTransformInfo::OperandValueKind Op1VK = 5193 TargetTransformInfo::OK_AnyValue; 5194 TargetTransformInfo::OperandValueKind Op2VK = 5195 TargetTransformInfo::OK_AnyValue; 5196 TargetTransformInfo::OperandValueProperties Op1VP = 5197 TargetTransformInfo::OP_None; 5198 TargetTransformInfo::OperandValueProperties Op2VP = 5199 TargetTransformInfo::OP_None; 5200 Value *Op2 = I->getOperand(1); 5201 5202 // Check for a splat of a constant or for a non uniform vector of constants. 5203 if (isa<ConstantInt>(Op2)) { 5204 ConstantInt *CInt = cast<ConstantInt>(Op2); 5205 if (CInt && CInt->getValue().isPowerOf2()) 5206 Op2VP = TargetTransformInfo::OP_PowerOf2; 5207 Op2VK = TargetTransformInfo::OK_UniformConstantValue; 5208 } else if (isa<ConstantVector>(Op2) || isa<ConstantDataVector>(Op2)) { 5209 Op2VK = TargetTransformInfo::OK_NonUniformConstantValue; 5210 Constant *SplatValue = cast<Constant>(Op2)->getSplatValue(); 5211 if (SplatValue) { 5212 ConstantInt *CInt = dyn_cast<ConstantInt>(SplatValue); 5213 if (CInt && CInt->getValue().isPowerOf2()) 5214 Op2VP = TargetTransformInfo::OP_PowerOf2; 5215 Op2VK = TargetTransformInfo::OK_UniformConstantValue; 5216 } 5217 } 5218 5219 return TTI.getArithmeticInstrCost(I->getOpcode(), VectorTy, Op1VK, Op2VK, 5220 Op1VP, Op2VP); 5221 } 5222 case Instruction::Select: { 5223 SelectInst *SI = cast<SelectInst>(I); 5224 const SCEV *CondSCEV = SE->getSCEV(SI->getCondition()); 5225 bool ScalarCond = (SE->isLoopInvariant(CondSCEV, TheLoop)); 5226 Type *CondTy = SI->getCondition()->getType(); 5227 if (!ScalarCond) 5228 CondTy = VectorType::get(CondTy, VF); 5229 5230 return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy, CondTy); 5231 } 5232 case Instruction::ICmp: 5233 case Instruction::FCmp: { 5234 Type *ValTy = I->getOperand(0)->getType(); 5235 VectorTy = ToVectorTy(ValTy, VF); 5236 return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy); 5237 } 5238 case Instruction::Store: 5239 case Instruction::Load: { 5240 StoreInst *SI = dyn_cast<StoreInst>(I); 5241 LoadInst *LI = dyn_cast<LoadInst>(I); 5242 Type *ValTy = (SI ? SI->getValueOperand()->getType() : 5243 LI->getType()); 5244 VectorTy = ToVectorTy(ValTy, VF); 5245 5246 unsigned Alignment = SI ? SI->getAlignment() : LI->getAlignment(); 5247 unsigned AS = SI ? SI->getPointerAddressSpace() : 5248 LI->getPointerAddressSpace(); 5249 Value *Ptr = SI ? SI->getPointerOperand() : LI->getPointerOperand(); 5250 // We add the cost of address computation here instead of with the gep 5251 // instruction because only here we know whether the operation is 5252 // scalarized. 5253 if (VF == 1) 5254 return TTI.getAddressComputationCost(VectorTy) + 5255 TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS); 5256 5257 // For an interleaved access, calculate the total cost of the whole 5258 // interleave group. 5259 if (Legal->isAccessInterleaved(I)) { 5260 auto Group = Legal->getInterleavedAccessGroup(I); 5261 assert(Group && "Fail to get an interleaved access group."); 5262 5263 // Only calculate the cost once at the insert position. 5264 if (Group->getInsertPos() != I) 5265 return 0; 5266 5267 unsigned InterleaveFactor = Group->getFactor(); 5268 Type *WideVecTy = 5269 VectorType::get(VectorTy->getVectorElementType(), 5270 VectorTy->getVectorNumElements() * InterleaveFactor); 5271 5272 // Holds the indices of existing members in an interleaved load group. 5273 // An interleaved store group doesn't need this as it dones't allow gaps. 5274 SmallVector<unsigned, 4> Indices; 5275 if (LI) { 5276 for (unsigned i = 0; i < InterleaveFactor; i++) 5277 if (Group->getMember(i)) 5278 Indices.push_back(i); 5279 } 5280 5281 // Calculate the cost of the whole interleaved group. 5282 unsigned Cost = TTI.getInterleavedMemoryOpCost( 5283 I->getOpcode(), WideVecTy, Group->getFactor(), Indices, 5284 Group->getAlignment(), AS); 5285 5286 if (Group->isReverse()) 5287 Cost += 5288 Group->getNumMembers() * 5289 TTI.getShuffleCost(TargetTransformInfo::SK_Reverse, VectorTy, 0); 5290 5291 // FIXME: The interleaved load group with a huge gap could be even more 5292 // expensive than scalar operations. Then we could ignore such group and 5293 // use scalar operations instead. 5294 return Cost; 5295 } 5296 5297 // Scalarized loads/stores. 5298 int ConsecutiveStride = Legal->isConsecutivePtr(Ptr); 5299 bool Reverse = ConsecutiveStride < 0; 5300 const DataLayout &DL = I->getModule()->getDataLayout(); 5301 unsigned ScalarAllocatedSize = DL.getTypeAllocSize(ValTy); 5302 unsigned VectorElementSize = DL.getTypeStoreSize(VectorTy) / VF; 5303 if (!ConsecutiveStride || ScalarAllocatedSize != VectorElementSize) { 5304 bool IsComplexComputation = 5305 isLikelyComplexAddressComputation(Ptr, Legal, SE, TheLoop); 5306 unsigned Cost = 0; 5307 // The cost of extracting from the value vector and pointer vector. 5308 Type *PtrTy = ToVectorTy(Ptr->getType(), VF); 5309 for (unsigned i = 0; i < VF; ++i) { 5310 // The cost of extracting the pointer operand. 5311 Cost += TTI.getVectorInstrCost(Instruction::ExtractElement, PtrTy, i); 5312 // In case of STORE, the cost of ExtractElement from the vector. 5313 // In case of LOAD, the cost of InsertElement into the returned 5314 // vector. 5315 Cost += TTI.getVectorInstrCost(SI ? Instruction::ExtractElement : 5316 Instruction::InsertElement, 5317 VectorTy, i); 5318 } 5319 5320 // The cost of the scalar loads/stores. 5321 Cost += VF * TTI.getAddressComputationCost(PtrTy, IsComplexComputation); 5322 Cost += VF * TTI.getMemoryOpCost(I->getOpcode(), ValTy->getScalarType(), 5323 Alignment, AS); 5324 return Cost; 5325 } 5326 5327 // Wide load/stores. 5328 unsigned Cost = TTI.getAddressComputationCost(VectorTy); 5329 if (Legal->isMaskRequired(I)) 5330 Cost += TTI.getMaskedMemoryOpCost(I->getOpcode(), VectorTy, Alignment, 5331 AS); 5332 else 5333 Cost += TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS); 5334 5335 if (Reverse) 5336 Cost += TTI.getShuffleCost(TargetTransformInfo::SK_Reverse, 5337 VectorTy, 0); 5338 return Cost; 5339 } 5340 case Instruction::ZExt: 5341 case Instruction::SExt: 5342 case Instruction::FPToUI: 5343 case Instruction::FPToSI: 5344 case Instruction::FPExt: 5345 case Instruction::PtrToInt: 5346 case Instruction::IntToPtr: 5347 case Instruction::SIToFP: 5348 case Instruction::UIToFP: 5349 case Instruction::Trunc: 5350 case Instruction::FPTrunc: 5351 case Instruction::BitCast: { 5352 // We optimize the truncation of induction variable. 5353 // The cost of these is the same as the scalar operation. 5354 if (I->getOpcode() == Instruction::Trunc && 5355 Legal->isInductionVariable(I->getOperand(0))) 5356 return TTI.getCastInstrCost(I->getOpcode(), I->getType(), 5357 I->getOperand(0)->getType()); 5358 5359 Type *SrcVecTy = ToVectorTy(I->getOperand(0)->getType(), VF); 5360 return TTI.getCastInstrCost(I->getOpcode(), VectorTy, SrcVecTy); 5361 } 5362 case Instruction::Call: { 5363 bool NeedToScalarize; 5364 CallInst *CI = cast<CallInst>(I); 5365 unsigned CallCost = getVectorCallCost(CI, VF, TTI, TLI, NeedToScalarize); 5366 if (getIntrinsicIDForCall(CI, TLI)) 5367 return std::min(CallCost, getVectorIntrinsicCost(CI, VF, TTI, TLI)); 5368 return CallCost; 5369 } 5370 default: { 5371 // We are scalarizing the instruction. Return the cost of the scalar 5372 // instruction, plus the cost of insert and extract into vector 5373 // elements, times the vector width. 5374 unsigned Cost = 0; 5375 5376 if (!RetTy->isVoidTy() && VF != 1) { 5377 unsigned InsCost = TTI.getVectorInstrCost(Instruction::InsertElement, 5378 VectorTy); 5379 unsigned ExtCost = TTI.getVectorInstrCost(Instruction::ExtractElement, 5380 VectorTy); 5381 5382 // The cost of inserting the results plus extracting each one of the 5383 // operands. 5384 Cost += VF * (InsCost + ExtCost * I->getNumOperands()); 5385 } 5386 5387 // The cost of executing VF copies of the scalar instruction. This opcode 5388 // is unknown. Assume that it is the same as 'mul'. 5389 Cost += VF * TTI.getArithmeticInstrCost(Instruction::Mul, VectorTy); 5390 return Cost; 5391 } 5392 }// end of switch. 5393 } 5394 5395 char LoopVectorize::ID = 0; 5396 static const char lv_name[] = "Loop Vectorization"; 5397 INITIALIZE_PASS_BEGIN(LoopVectorize, LV_NAME, lv_name, false, false) 5398 INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass) 5399 INITIALIZE_AG_DEPENDENCY(AliasAnalysis) 5400 INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker) 5401 INITIALIZE_PASS_DEPENDENCY(BlockFrequencyInfoWrapperPass) 5402 INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass) 5403 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass) 5404 INITIALIZE_PASS_DEPENDENCY(LCSSA) 5405 INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass) 5406 INITIALIZE_PASS_DEPENDENCY(LoopSimplify) 5407 INITIALIZE_PASS_DEPENDENCY(LoopAccessAnalysis) 5408 INITIALIZE_PASS_END(LoopVectorize, LV_NAME, lv_name, false, false) 5409 5410 namespace llvm { 5411 Pass *createLoopVectorizePass(bool NoUnrolling, bool AlwaysVectorize) { 5412 return new LoopVectorize(NoUnrolling, AlwaysVectorize); 5413 } 5414 } 5415 5416 bool LoopVectorizationCostModel::isConsecutiveLoadOrStore(Instruction *Inst) { 5417 // Check for a store. 5418 if (StoreInst *ST = dyn_cast<StoreInst>(Inst)) 5419 return Legal->isConsecutivePtr(ST->getPointerOperand()) != 0; 5420 5421 // Check for a load. 5422 if (LoadInst *LI = dyn_cast<LoadInst>(Inst)) 5423 return Legal->isConsecutivePtr(LI->getPointerOperand()) != 0; 5424 5425 return false; 5426 } 5427 5428 5429 void InnerLoopUnroller::scalarizeInstruction(Instruction *Instr, 5430 bool IfPredicateStore) { 5431 assert(!Instr->getType()->isAggregateType() && "Can't handle vectors"); 5432 // Holds vector parameters or scalars, in case of uniform vals. 5433 SmallVector<VectorParts, 4> Params; 5434 5435 setDebugLocFromInst(Builder, Instr); 5436 5437 // Find all of the vectorized parameters. 5438 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) { 5439 Value *SrcOp = Instr->getOperand(op); 5440 5441 // If we are accessing the old induction variable, use the new one. 5442 if (SrcOp == OldInduction) { 5443 Params.push_back(getVectorValue(SrcOp)); 5444 continue; 5445 } 5446 5447 // Try using previously calculated values. 5448 Instruction *SrcInst = dyn_cast<Instruction>(SrcOp); 5449 5450 // If the src is an instruction that appeared earlier in the basic block 5451 // then it should already be vectorized. 5452 if (SrcInst && OrigLoop->contains(SrcInst)) { 5453 assert(WidenMap.has(SrcInst) && "Source operand is unavailable"); 5454 // The parameter is a vector value from earlier. 5455 Params.push_back(WidenMap.get(SrcInst)); 5456 } else { 5457 // The parameter is a scalar from outside the loop. Maybe even a constant. 5458 VectorParts Scalars; 5459 Scalars.append(UF, SrcOp); 5460 Params.push_back(Scalars); 5461 } 5462 } 5463 5464 assert(Params.size() == Instr->getNumOperands() && 5465 "Invalid number of operands"); 5466 5467 // Does this instruction return a value ? 5468 bool IsVoidRetTy = Instr->getType()->isVoidTy(); 5469 5470 Value *UndefVec = IsVoidRetTy ? nullptr : 5471 UndefValue::get(Instr->getType()); 5472 // Create a new entry in the WidenMap and initialize it to Undef or Null. 5473 VectorParts &VecResults = WidenMap.splat(Instr, UndefVec); 5474 5475 Instruction *InsertPt = Builder.GetInsertPoint(); 5476 BasicBlock *IfBlock = Builder.GetInsertBlock(); 5477 BasicBlock *CondBlock = nullptr; 5478 5479 VectorParts Cond; 5480 Loop *VectorLp = nullptr; 5481 if (IfPredicateStore) { 5482 assert(Instr->getParent()->getSinglePredecessor() && 5483 "Only support single predecessor blocks"); 5484 Cond = createEdgeMask(Instr->getParent()->getSinglePredecessor(), 5485 Instr->getParent()); 5486 VectorLp = LI->getLoopFor(IfBlock); 5487 assert(VectorLp && "Must have a loop for this block"); 5488 } 5489 5490 // For each vector unroll 'part': 5491 for (unsigned Part = 0; Part < UF; ++Part) { 5492 // For each scalar that we create: 5493 5494 // Start an "if (pred) a[i] = ..." block. 5495 Value *Cmp = nullptr; 5496 if (IfPredicateStore) { 5497 if (Cond[Part]->getType()->isVectorTy()) 5498 Cond[Part] = 5499 Builder.CreateExtractElement(Cond[Part], Builder.getInt32(0)); 5500 Cmp = Builder.CreateICmp(ICmpInst::ICMP_EQ, Cond[Part], 5501 ConstantInt::get(Cond[Part]->getType(), 1)); 5502 CondBlock = IfBlock->splitBasicBlock(InsertPt, "cond.store"); 5503 LoopVectorBody.push_back(CondBlock); 5504 VectorLp->addBasicBlockToLoop(CondBlock, *LI); 5505 // Update Builder with newly created basic block. 5506 Builder.SetInsertPoint(InsertPt); 5507 } 5508 5509 Instruction *Cloned = Instr->clone(); 5510 if (!IsVoidRetTy) 5511 Cloned->setName(Instr->getName() + ".cloned"); 5512 // Replace the operands of the cloned instructions with extracted scalars. 5513 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) { 5514 Value *Op = Params[op][Part]; 5515 Cloned->setOperand(op, Op); 5516 } 5517 5518 // Place the cloned scalar in the new loop. 5519 Builder.Insert(Cloned); 5520 5521 // If the original scalar returns a value we need to place it in a vector 5522 // so that future users will be able to use it. 5523 if (!IsVoidRetTy) 5524 VecResults[Part] = Cloned; 5525 5526 // End if-block. 5527 if (IfPredicateStore) { 5528 BasicBlock *NewIfBlock = CondBlock->splitBasicBlock(InsertPt, "else"); 5529 LoopVectorBody.push_back(NewIfBlock); 5530 VectorLp->addBasicBlockToLoop(NewIfBlock, *LI); 5531 Builder.SetInsertPoint(InsertPt); 5532 ReplaceInstWithInst(IfBlock->getTerminator(), 5533 BranchInst::Create(CondBlock, NewIfBlock, Cmp)); 5534 IfBlock = NewIfBlock; 5535 } 5536 } 5537 } 5538 5539 void InnerLoopUnroller::vectorizeMemoryInstruction(Instruction *Instr) { 5540 StoreInst *SI = dyn_cast<StoreInst>(Instr); 5541 bool IfPredicateStore = (SI && Legal->blockNeedsPredication(SI->getParent())); 5542 5543 return scalarizeInstruction(Instr, IfPredicateStore); 5544 } 5545 5546 Value *InnerLoopUnroller::reverseVector(Value *Vec) { 5547 return Vec; 5548 } 5549 5550 Value *InnerLoopUnroller::getBroadcastInstrs(Value *V) { 5551 return V; 5552 } 5553 5554 Value *InnerLoopUnroller::getStepVector(Value *Val, int StartIdx, Value *Step) { 5555 // When unrolling and the VF is 1, we only need to add a simple scalar. 5556 Type *ITy = Val->getType(); 5557 assert(!ITy->isVectorTy() && "Val must be a scalar"); 5558 Constant *C = ConstantInt::get(ITy, StartIdx); 5559 return Builder.CreateAdd(Val, Builder.CreateMul(C, Step), "induction"); 5560 } 5561