LoopVectorize.cpp revision 3f4f420ab7acb10221ba971543a7eed5489fb626
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// Other ideas/concepts are from: 38// A. Zaks and D. Nuzman. Autovectorization in GCC-two years later. 39// 40// S. Maleki, Y. Gao, M. Garzaran, T. Wong and D. Padua. An Evaluation of 41// Vectorizing Compilers. 42// 43//===----------------------------------------------------------------------===// 44 45#define LV_NAME "loop-vectorize" 46#define DEBUG_TYPE LV_NAME 47 48#include "llvm/Transforms/Vectorize.h" 49#include "llvm/ADT/DenseMap.h" 50#include "llvm/ADT/EquivalenceClasses.h" 51#include "llvm/ADT/MapVector.h" 52#include "llvm/ADT/SetVector.h" 53#include "llvm/ADT/SmallPtrSet.h" 54#include "llvm/ADT/SmallSet.h" 55#include "llvm/ADT/SmallVector.h" 56#include "llvm/ADT/StringExtras.h" 57#include "llvm/Analysis/AliasAnalysis.h" 58#include "llvm/Analysis/Dominators.h" 59#include "llvm/Analysis/LoopInfo.h" 60#include "llvm/Analysis/LoopIterator.h" 61#include "llvm/Analysis/LoopPass.h" 62#include "llvm/Analysis/ScalarEvolution.h" 63#include "llvm/Analysis/ScalarEvolutionExpander.h" 64#include "llvm/Analysis/ScalarEvolutionExpressions.h" 65#include "llvm/Analysis/TargetTransformInfo.h" 66#include "llvm/Analysis/ValueTracking.h" 67#include "llvm/Analysis/Verifier.h" 68#include "llvm/IR/Constants.h" 69#include "llvm/IR/DataLayout.h" 70#include "llvm/IR/DerivedTypes.h" 71#include "llvm/IR/Function.h" 72#include "llvm/IR/IRBuilder.h" 73#include "llvm/IR/Instructions.h" 74#include "llvm/IR/IntrinsicInst.h" 75#include "llvm/IR/LLVMContext.h" 76#include "llvm/IR/Module.h" 77#include "llvm/IR/Type.h" 78#include "llvm/IR/Value.h" 79#include "llvm/Pass.h" 80#include "llvm/Support/CommandLine.h" 81#include "llvm/Support/Debug.h" 82#include "llvm/Support/PatternMatch.h" 83#include "llvm/Support/raw_ostream.h" 84#include "llvm/Support/ValueHandle.h" 85#include "llvm/Target/TargetLibraryInfo.h" 86#include "llvm/Transforms/Scalar.h" 87#include "llvm/Transforms/Utils/BasicBlockUtils.h" 88#include "llvm/Transforms/Utils/Local.h" 89#include <algorithm> 90#include <map> 91 92using namespace llvm; 93using namespace llvm::PatternMatch; 94 95static cl::opt<unsigned> 96VectorizationFactor("force-vector-width", cl::init(0), cl::Hidden, 97 cl::desc("Sets the SIMD width. Zero is autoselect.")); 98 99static cl::opt<unsigned> 100VectorizationUnroll("force-vector-unroll", cl::init(0), cl::Hidden, 101 cl::desc("Sets the vectorization unroll count. " 102 "Zero is autoselect.")); 103 104static cl::opt<bool> 105EnableIfConversion("enable-if-conversion", cl::init(true), cl::Hidden, 106 cl::desc("Enable if-conversion during vectorization.")); 107 108/// We don't vectorize loops with a known constant trip count below this number. 109static cl::opt<unsigned> 110TinyTripCountVectorThreshold("vectorizer-min-trip-count", cl::init(16), 111 cl::Hidden, 112 cl::desc("Don't vectorize loops with a constant " 113 "trip count that is smaller than this " 114 "value.")); 115 116/// We don't unroll loops with a known constant trip count below this number. 117static const unsigned TinyTripCountUnrollThreshold = 128; 118 119/// When performing memory disambiguation checks at runtime do not make more 120/// than this number of comparisons. 121static const unsigned RuntimeMemoryCheckThreshold = 8; 122 123/// Maximum simd width. 124static const unsigned MaxVectorWidth = 64; 125 126/// Maximum vectorization unroll count. 127static const unsigned MaxUnrollFactor = 16; 128 129/// The cost of a loop that is considered 'small' by the unroller. 130static const unsigned SmallLoopCost = 20; 131 132namespace { 133 134// Forward declarations. 135class LoopVectorizationLegality; 136class LoopVectorizationCostModel; 137 138/// InnerLoopVectorizer vectorizes loops which contain only one basic 139/// block to a specified vectorization factor (VF). 140/// This class performs the widening of scalars into vectors, or multiple 141/// scalars. This class also implements the following features: 142/// * It inserts an epilogue loop for handling loops that don't have iteration 143/// counts that are known to be a multiple of the vectorization factor. 144/// * It handles the code generation for reduction variables. 145/// * Scalarization (implementation using scalars) of un-vectorizable 146/// instructions. 147/// InnerLoopVectorizer does not perform any vectorization-legality 148/// checks, and relies on the caller to check for the different legality 149/// aspects. The InnerLoopVectorizer relies on the 150/// LoopVectorizationLegality class to provide information about the induction 151/// and reduction variables that were found to a given vectorization factor. 152class InnerLoopVectorizer { 153public: 154 InnerLoopVectorizer(Loop *OrigLoop, ScalarEvolution *SE, LoopInfo *LI, 155 DominatorTree *DT, DataLayout *DL, 156 const TargetLibraryInfo *TLI, unsigned VecWidth, 157 unsigned UnrollFactor) 158 : OrigLoop(OrigLoop), SE(SE), LI(LI), DT(DT), DL(DL), TLI(TLI), 159 VF(VecWidth), UF(UnrollFactor), Builder(SE->getContext()), Induction(0), 160 OldInduction(0), WidenMap(UnrollFactor) {} 161 162 // Perform the actual loop widening (vectorization). 163 void vectorize(LoopVectorizationLegality *Legal) { 164 // Create a new empty loop. Unlink the old loop and connect the new one. 165 createEmptyLoop(Legal); 166 // Widen each instruction in the old loop to a new one in the new loop. 167 // Use the Legality module to find the induction and reduction variables. 168 vectorizeLoop(Legal); 169 // Register the new loop and update the analysis passes. 170 updateAnalysis(); 171 } 172 173 virtual ~InnerLoopVectorizer() {} 174 175protected: 176 /// A small list of PHINodes. 177 typedef SmallVector<PHINode*, 4> PhiVector; 178 /// When we unroll loops we have multiple vector values for each scalar. 179 /// This data structure holds the unrolled and vectorized values that 180 /// originated from one scalar instruction. 181 typedef SmallVector<Value*, 2> VectorParts; 182 183 // When we if-convert we need create edge masks. We have to cache values so 184 // that we don't end up with exponential recursion/IR. 185 typedef DenseMap<std::pair<BasicBlock*, BasicBlock*>, 186 VectorParts> EdgeMaskCache; 187 188 /// Add code that checks at runtime if the accessed arrays overlap. 189 /// Returns the comparator value or NULL if no check is needed. 190 Instruction *addRuntimeCheck(LoopVectorizationLegality *Legal, 191 Instruction *Loc); 192 /// Create an empty loop, based on the loop ranges of the old loop. 193 void createEmptyLoop(LoopVectorizationLegality *Legal); 194 /// Copy and widen the instructions from the old loop. 195 virtual void vectorizeLoop(LoopVectorizationLegality *Legal); 196 197 /// \brief The Loop exit block may have single value PHI nodes where the 198 /// incoming value is 'Undef'. While vectorizing we only handled real values 199 /// that were defined inside the loop. Here we fix the 'undef case'. 200 /// See PR14725. 201 void fixLCSSAPHIs(); 202 203 /// A helper function that computes the predicate of the block BB, assuming 204 /// that the header block of the loop is set to True. It returns the *entry* 205 /// mask for the block BB. 206 VectorParts createBlockInMask(BasicBlock *BB); 207 /// A helper function that computes the predicate of the edge between SRC 208 /// and DST. 209 VectorParts createEdgeMask(BasicBlock *Src, BasicBlock *Dst); 210 211 /// A helper function to vectorize a single BB within the innermost loop. 212 void vectorizeBlockInLoop(LoopVectorizationLegality *Legal, BasicBlock *BB, 213 PhiVector *PV); 214 215 /// Vectorize a single PHINode in a block. This method handles the induction 216 /// variable canonicalization. It supports both VF = 1 for unrolled loops and 217 /// arbitrary length vectors. 218 void widenPHIInstruction(Instruction *PN, VectorParts &Entry, 219 LoopVectorizationLegality *Legal, 220 unsigned UF, unsigned VF, PhiVector *PV); 221 222 /// Insert the new loop to the loop hierarchy and pass manager 223 /// and update the analysis passes. 224 void updateAnalysis(); 225 226 /// This instruction is un-vectorizable. Implement it as a sequence 227 /// of scalars. 228 virtual void scalarizeInstruction(Instruction *Instr); 229 230 /// Vectorize Load and Store instructions, 231 virtual void vectorizeMemoryInstruction(Instruction *Instr, 232 LoopVectorizationLegality *Legal); 233 234 /// Create a broadcast instruction. This method generates a broadcast 235 /// instruction (shuffle) for loop invariant values and for the induction 236 /// value. If this is the induction variable then we extend it to N, N+1, ... 237 /// this is needed because each iteration in the loop corresponds to a SIMD 238 /// element. 239 virtual Value *getBroadcastInstrs(Value *V); 240 241 /// This function adds 0, 1, 2 ... to each vector element, starting at zero. 242 /// If Negate is set then negative numbers are added e.g. (0, -1, -2, ...). 243 /// The sequence starts at StartIndex. 244 virtual Value *getConsecutiveVector(Value* Val, int StartIdx, bool Negate); 245 246 /// When we go over instructions in the basic block we rely on previous 247 /// values within the current basic block or on loop invariant values. 248 /// When we widen (vectorize) values we place them in the map. If the values 249 /// are not within the map, they have to be loop invariant, so we simply 250 /// broadcast them into a vector. 251 VectorParts &getVectorValue(Value *V); 252 253 /// Generate a shuffle sequence that will reverse the vector Vec. 254 virtual Value *reverseVector(Value *Vec); 255 256 /// This is a helper class that holds the vectorizer state. It maps scalar 257 /// instructions to vector instructions. When the code is 'unrolled' then 258 /// then a single scalar value is mapped to multiple vector parts. The parts 259 /// are stored in the VectorPart type. 260 struct ValueMap { 261 /// C'tor. UnrollFactor controls the number of vectors ('parts') that 262 /// are mapped. 263 ValueMap(unsigned UnrollFactor) : UF(UnrollFactor) {} 264 265 /// \return True if 'Key' is saved in the Value Map. 266 bool has(Value *Key) const { return MapStorage.count(Key); } 267 268 /// Initializes a new entry in the map. Sets all of the vector parts to the 269 /// save value in 'Val'. 270 /// \return A reference to a vector with splat values. 271 VectorParts &splat(Value *Key, Value *Val) { 272 VectorParts &Entry = MapStorage[Key]; 273 Entry.assign(UF, Val); 274 return Entry; 275 } 276 277 ///\return A reference to the value that is stored at 'Key'. 278 VectorParts &get(Value *Key) { 279 VectorParts &Entry = MapStorage[Key]; 280 if (Entry.empty()) 281 Entry.resize(UF); 282 assert(Entry.size() == UF); 283 return Entry; 284 } 285 286 private: 287 /// The unroll factor. Each entry in the map stores this number of vector 288 /// elements. 289 unsigned UF; 290 291 /// Map storage. We use std::map and not DenseMap because insertions to a 292 /// dense map invalidates its iterators. 293 std::map<Value *, VectorParts> MapStorage; 294 }; 295 296 /// The original loop. 297 Loop *OrigLoop; 298 /// Scev analysis to use. 299 ScalarEvolution *SE; 300 /// Loop Info. 301 LoopInfo *LI; 302 /// Dominator Tree. 303 DominatorTree *DT; 304 /// Data Layout. 305 DataLayout *DL; 306 /// Target Library Info. 307 const TargetLibraryInfo *TLI; 308 309 /// The vectorization SIMD factor to use. Each vector will have this many 310 /// vector elements. 311 unsigned VF; 312 313protected: 314 /// The vectorization unroll factor to use. Each scalar is vectorized to this 315 /// many different vector instructions. 316 unsigned UF; 317 318 /// The builder that we use 319 IRBuilder<> Builder; 320 321 // --- Vectorization state --- 322 323 /// The vector-loop preheader. 324 BasicBlock *LoopVectorPreHeader; 325 /// The scalar-loop preheader. 326 BasicBlock *LoopScalarPreHeader; 327 /// Middle Block between the vector and the scalar. 328 BasicBlock *LoopMiddleBlock; 329 ///The ExitBlock of the scalar loop. 330 BasicBlock *LoopExitBlock; 331 ///The vector loop body. 332 BasicBlock *LoopVectorBody; 333 ///The scalar loop body. 334 BasicBlock *LoopScalarBody; 335 /// A list of all bypass blocks. The first block is the entry of the loop. 336 SmallVector<BasicBlock *, 4> LoopBypassBlocks; 337 338 /// The new Induction variable which was added to the new block. 339 PHINode *Induction; 340 /// The induction variable of the old basic block. 341 PHINode *OldInduction; 342 /// Holds the extended (to the widest induction type) start index. 343 Value *ExtendedIdx; 344 /// Maps scalars to widened vectors. 345 ValueMap WidenMap; 346 EdgeMaskCache MaskCache; 347}; 348 349class InnerLoopUnroller : public InnerLoopVectorizer { 350public: 351 InnerLoopUnroller(Loop *OrigLoop, ScalarEvolution *SE, LoopInfo *LI, 352 DominatorTree *DT, DataLayout *DL, 353 const TargetLibraryInfo *TLI, unsigned UnrollFactor) : 354 InnerLoopVectorizer(OrigLoop, SE, LI, DT, DL, TLI, 1, UnrollFactor) { } 355 356private: 357 virtual void scalarizeInstruction(Instruction *Instr); 358 virtual void vectorizeMemoryInstruction(Instruction *Instr, 359 LoopVectorizationLegality *Legal); 360 virtual Value *getBroadcastInstrs(Value *V); 361 virtual Value *getConsecutiveVector(Value* Val, int StartIdx, bool Negate); 362 virtual Value *reverseVector(Value *Vec); 363}; 364 365/// \brief Look for a meaningful debug location on the instruction or it's 366/// operands. 367static Instruction *getDebugLocFromInstOrOperands(Instruction *I) { 368 if (!I) 369 return I; 370 371 DebugLoc Empty; 372 if (I->getDebugLoc() != Empty) 373 return I; 374 375 for (User::op_iterator OI = I->op_begin(), OE = I->op_end(); OI != OE; ++OI) { 376 if (Instruction *OpInst = dyn_cast<Instruction>(*OI)) 377 if (OpInst->getDebugLoc() != Empty) 378 return OpInst; 379 } 380 381 return I; 382} 383 384/// \brief Set the debug location in the builder using the debug location in the 385/// instruction. 386static void setDebugLocFromInst(IRBuilder<> &B, const Value *Ptr) { 387 if (const Instruction *Inst = dyn_cast_or_null<Instruction>(Ptr)) 388 B.SetCurrentDebugLocation(Inst->getDebugLoc()); 389 else 390 B.SetCurrentDebugLocation(DebugLoc()); 391} 392 393/// LoopVectorizationLegality checks if it is legal to vectorize a loop, and 394/// to what vectorization factor. 395/// This class does not look at the profitability of vectorization, only the 396/// legality. This class has two main kinds of checks: 397/// * Memory checks - The code in canVectorizeMemory checks if vectorization 398/// will change the order of memory accesses in a way that will change the 399/// correctness of the program. 400/// * Scalars checks - The code in canVectorizeInstrs and canVectorizeMemory 401/// checks for a number of different conditions, such as the availability of a 402/// single induction variable, that all types are supported and vectorize-able, 403/// etc. This code reflects the capabilities of InnerLoopVectorizer. 404/// This class is also used by InnerLoopVectorizer for identifying 405/// induction variable and the different reduction variables. 406class LoopVectorizationLegality { 407public: 408 LoopVectorizationLegality(Loop *L, ScalarEvolution *SE, DataLayout *DL, 409 DominatorTree *DT, TargetLibraryInfo *TLI) 410 : TheLoop(L), SE(SE), DL(DL), DT(DT), TLI(TLI), 411 Induction(0), WidestIndTy(0), HasFunNoNaNAttr(false), 412 MaxSafeDepDistBytes(-1U) {} 413 414 /// This enum represents the kinds of reductions that we support. 415 enum ReductionKind { 416 RK_NoReduction, ///< Not a reduction. 417 RK_IntegerAdd, ///< Sum of integers. 418 RK_IntegerMult, ///< Product of integers. 419 RK_IntegerOr, ///< Bitwise or logical OR of numbers. 420 RK_IntegerAnd, ///< Bitwise or logical AND of numbers. 421 RK_IntegerXor, ///< Bitwise or logical XOR of numbers. 422 RK_IntegerMinMax, ///< Min/max implemented in terms of select(cmp()). 423 RK_FloatAdd, ///< Sum of floats. 424 RK_FloatMult, ///< Product of floats. 425 RK_FloatMinMax ///< Min/max implemented in terms of select(cmp()). 426 }; 427 428 /// This enum represents the kinds of inductions that we support. 429 enum InductionKind { 430 IK_NoInduction, ///< Not an induction variable. 431 IK_IntInduction, ///< Integer induction variable. Step = 1. 432 IK_ReverseIntInduction, ///< Reverse int induction variable. Step = -1. 433 IK_PtrInduction, ///< Pointer induction var. Step = sizeof(elem). 434 IK_ReversePtrInduction ///< Reverse ptr indvar. Step = - sizeof(elem). 435 }; 436 437 // This enum represents the kind of minmax reduction. 438 enum MinMaxReductionKind { 439 MRK_Invalid, 440 MRK_UIntMin, 441 MRK_UIntMax, 442 MRK_SIntMin, 443 MRK_SIntMax, 444 MRK_FloatMin, 445 MRK_FloatMax 446 }; 447 448 /// This POD struct holds information about reduction variables. 449 struct ReductionDescriptor { 450 ReductionDescriptor() : StartValue(0), LoopExitInstr(0), 451 Kind(RK_NoReduction), MinMaxKind(MRK_Invalid) {} 452 453 ReductionDescriptor(Value *Start, Instruction *Exit, ReductionKind K, 454 MinMaxReductionKind MK) 455 : StartValue(Start), LoopExitInstr(Exit), Kind(K), MinMaxKind(MK) {} 456 457 // The starting value of the reduction. 458 // It does not have to be zero! 459 TrackingVH<Value> StartValue; 460 // The instruction who's value is used outside the loop. 461 Instruction *LoopExitInstr; 462 // The kind of the reduction. 463 ReductionKind Kind; 464 // If this a min/max reduction the kind of reduction. 465 MinMaxReductionKind MinMaxKind; 466 }; 467 468 /// This POD struct holds information about a potential reduction operation. 469 struct ReductionInstDesc { 470 ReductionInstDesc(bool IsRedux, Instruction *I) : 471 IsReduction(IsRedux), PatternLastInst(I), MinMaxKind(MRK_Invalid) {} 472 473 ReductionInstDesc(Instruction *I, MinMaxReductionKind K) : 474 IsReduction(true), PatternLastInst(I), MinMaxKind(K) {} 475 476 // Is this instruction a reduction candidate. 477 bool IsReduction; 478 // The last instruction in a min/max pattern (select of the select(icmp()) 479 // pattern), or the current reduction instruction otherwise. 480 Instruction *PatternLastInst; 481 // If this is a min/max pattern the comparison predicate. 482 MinMaxReductionKind MinMaxKind; 483 }; 484 485 // This POD struct holds information about the memory runtime legality 486 // check that a group of pointers do not overlap. 487 struct RuntimePointerCheck { 488 RuntimePointerCheck() : Need(false) {} 489 490 /// Reset the state of the pointer runtime information. 491 void reset() { 492 Need = false; 493 Pointers.clear(); 494 Starts.clear(); 495 Ends.clear(); 496 } 497 498 /// Insert a pointer and calculate the start and end SCEVs. 499 void insert(ScalarEvolution *SE, Loop *Lp, Value *Ptr, bool WritePtr, 500 unsigned DepSetId); 501 502 /// This flag indicates if we need to add the runtime check. 503 bool Need; 504 /// Holds the pointers that we need to check. 505 SmallVector<TrackingVH<Value>, 2> Pointers; 506 /// Holds the pointer value at the beginning of the loop. 507 SmallVector<const SCEV*, 2> Starts; 508 /// Holds the pointer value at the end of the loop. 509 SmallVector<const SCEV*, 2> Ends; 510 /// Holds the information if this pointer is used for writing to memory. 511 SmallVector<bool, 2> IsWritePtr; 512 /// Holds the id of the set of pointers that could be dependent because of a 513 /// shared underlying object. 514 SmallVector<unsigned, 2> DependencySetId; 515 }; 516 517 /// A POD for saving information about induction variables. 518 struct InductionInfo { 519 InductionInfo(Value *Start, InductionKind K) : StartValue(Start), IK(K) {} 520 InductionInfo() : StartValue(0), IK(IK_NoInduction) {} 521 /// Start value. 522 TrackingVH<Value> StartValue; 523 /// Induction kind. 524 InductionKind IK; 525 }; 526 527 /// ReductionList contains the reduction descriptors for all 528 /// of the reductions that were found in the loop. 529 typedef DenseMap<PHINode*, ReductionDescriptor> ReductionList; 530 531 /// InductionList saves induction variables and maps them to the 532 /// induction descriptor. 533 typedef MapVector<PHINode*, InductionInfo> InductionList; 534 535 /// Returns true if it is legal to vectorize this loop. 536 /// This does not mean that it is profitable to vectorize this 537 /// loop, only that it is legal to do so. 538 bool canVectorize(); 539 540 /// Returns the Induction variable. 541 PHINode *getInduction() { return Induction; } 542 543 /// Returns the reduction variables found in the loop. 544 ReductionList *getReductionVars() { return &Reductions; } 545 546 /// Returns the induction variables found in the loop. 547 InductionList *getInductionVars() { return &Inductions; } 548 549 /// Returns the widest induction type. 550 Type *getWidestInductionType() { return WidestIndTy; } 551 552 /// Returns True if V is an induction variable in this loop. 553 bool isInductionVariable(const Value *V); 554 555 /// Return true if the block BB needs to be predicated in order for the loop 556 /// to be vectorized. 557 bool blockNeedsPredication(BasicBlock *BB); 558 559 /// Check if this pointer is consecutive when vectorizing. This happens 560 /// when the last index of the GEP is the induction variable, or that the 561 /// pointer itself is an induction variable. 562 /// This check allows us to vectorize A[idx] into a wide load/store. 563 /// Returns: 564 /// 0 - Stride is unknown or non consecutive. 565 /// 1 - Address is consecutive. 566 /// -1 - Address is consecutive, and decreasing. 567 int isConsecutivePtr(Value *Ptr); 568 569 /// Returns true if the value V is uniform within the loop. 570 bool isUniform(Value *V); 571 572 /// Returns true if this instruction will remain scalar after vectorization. 573 bool isUniformAfterVectorization(Instruction* I) { return Uniforms.count(I); } 574 575 /// Returns the information that we collected about runtime memory check. 576 RuntimePointerCheck *getRuntimePointerCheck() { return &PtrRtCheck; } 577 578 /// This function returns the identity element (or neutral element) for 579 /// the operation K. 580 static Constant *getReductionIdentity(ReductionKind K, Type *Tp); 581 582 unsigned getMaxSafeDepDistBytes() { return MaxSafeDepDistBytes; } 583 584private: 585 /// Check if a single basic block loop is vectorizable. 586 /// At this point we know that this is a loop with a constant trip count 587 /// and we only need to check individual instructions. 588 bool canVectorizeInstrs(); 589 590 /// When we vectorize loops we may change the order in which 591 /// we read and write from memory. This method checks if it is 592 /// legal to vectorize the code, considering only memory constrains. 593 /// Returns true if the loop is vectorizable 594 bool canVectorizeMemory(); 595 596 /// Return true if we can vectorize this loop using the IF-conversion 597 /// transformation. 598 bool canVectorizeWithIfConvert(); 599 600 /// Collect the variables that need to stay uniform after vectorization. 601 void collectLoopUniforms(); 602 603 /// Return true if all of the instructions in the block can be speculatively 604 /// executed. \p SafePtrs is a list of addresses that are known to be legal 605 /// and we know that we can read from them without segfault. 606 bool blockCanBePredicated(BasicBlock *BB, SmallPtrSet<Value *, 8>& SafePtrs); 607 608 /// Returns True, if 'Phi' is the kind of reduction variable for type 609 /// 'Kind'. If this is a reduction variable, it adds it to ReductionList. 610 bool AddReductionVar(PHINode *Phi, ReductionKind Kind); 611 /// Returns a struct describing if the instruction 'I' can be a reduction 612 /// variable of type 'Kind'. If the reduction is a min/max pattern of 613 /// select(icmp()) this function advances the instruction pointer 'I' from the 614 /// compare instruction to the select instruction and stores this pointer in 615 /// 'PatternLastInst' member of the returned struct. 616 ReductionInstDesc isReductionInstr(Instruction *I, ReductionKind Kind, 617 ReductionInstDesc &Desc); 618 /// Returns true if the instruction is a Select(ICmp(X, Y), X, Y) instruction 619 /// pattern corresponding to a min(X, Y) or max(X, Y). 620 static ReductionInstDesc isMinMaxSelectCmpPattern(Instruction *I, 621 ReductionInstDesc &Prev); 622 /// Returns the induction kind of Phi. This function may return NoInduction 623 /// if the PHI is not an induction variable. 624 InductionKind isInductionVariable(PHINode *Phi); 625 626 /// The loop that we evaluate. 627 Loop *TheLoop; 628 /// Scev analysis. 629 ScalarEvolution *SE; 630 /// DataLayout analysis. 631 DataLayout *DL; 632 /// Dominators. 633 DominatorTree *DT; 634 /// Target Library Info. 635 TargetLibraryInfo *TLI; 636 637 // --- vectorization state --- // 638 639 /// Holds the integer induction variable. This is the counter of the 640 /// loop. 641 PHINode *Induction; 642 /// Holds the reduction variables. 643 ReductionList Reductions; 644 /// Holds all of the induction variables that we found in the loop. 645 /// Notice that inductions don't need to start at zero and that induction 646 /// variables can be pointers. 647 InductionList Inductions; 648 /// Holds the widest induction type encountered. 649 Type *WidestIndTy; 650 651 /// Allowed outside users. This holds the reduction 652 /// vars which can be accessed from outside the loop. 653 SmallPtrSet<Value*, 4> AllowedExit; 654 /// This set holds the variables which are known to be uniform after 655 /// vectorization. 656 SmallPtrSet<Instruction*, 4> Uniforms; 657 /// We need to check that all of the pointers in this list are disjoint 658 /// at runtime. 659 RuntimePointerCheck PtrRtCheck; 660 /// Can we assume the absence of NaNs. 661 bool HasFunNoNaNAttr; 662 663 unsigned MaxSafeDepDistBytes; 664}; 665 666/// LoopVectorizationCostModel - estimates the expected speedups due to 667/// vectorization. 668/// In many cases vectorization is not profitable. This can happen because of 669/// a number of reasons. In this class we mainly attempt to predict the 670/// expected speedup/slowdowns due to the supported instruction set. We use the 671/// TargetTransformInfo to query the different backends for the cost of 672/// different operations. 673class LoopVectorizationCostModel { 674public: 675 LoopVectorizationCostModel(Loop *L, ScalarEvolution *SE, LoopInfo *LI, 676 LoopVectorizationLegality *Legal, 677 const TargetTransformInfo &TTI, 678 DataLayout *DL, const TargetLibraryInfo *TLI) 679 : TheLoop(L), SE(SE), LI(LI), Legal(Legal), TTI(TTI), DL(DL), TLI(TLI) {} 680 681 /// Information about vectorization costs 682 struct VectorizationFactor { 683 unsigned Width; // Vector width with best cost 684 unsigned Cost; // Cost of the loop with that width 685 }; 686 /// \return The most profitable vectorization factor and the cost of that VF. 687 /// This method checks every power of two up to VF. If UserVF is not ZERO 688 /// then this vectorization factor will be selected if vectorization is 689 /// possible. 690 VectorizationFactor selectVectorizationFactor(bool OptForSize, 691 unsigned UserVF); 692 693 /// \return The size (in bits) of the widest type in the code that 694 /// needs to be vectorized. We ignore values that remain scalar such as 695 /// 64 bit loop indices. 696 unsigned getWidestType(); 697 698 /// \return The most profitable unroll factor. 699 /// If UserUF is non-zero then this method finds the best unroll-factor 700 /// based on register pressure and other parameters. 701 /// VF and LoopCost are the selected vectorization factor and the cost of the 702 /// selected VF. 703 unsigned selectUnrollFactor(bool OptForSize, unsigned UserUF, unsigned VF, 704 unsigned LoopCost); 705 706 /// \brief A struct that represents some properties of the register usage 707 /// of a loop. 708 struct RegisterUsage { 709 /// Holds the number of loop invariant values that are used in the loop. 710 unsigned LoopInvariantRegs; 711 /// Holds the maximum number of concurrent live intervals in the loop. 712 unsigned MaxLocalUsers; 713 /// Holds the number of instructions in the loop. 714 unsigned NumInstructions; 715 }; 716 717 /// \return information about the register usage of the loop. 718 RegisterUsage calculateRegisterUsage(); 719 720private: 721 /// Returns the expected execution cost. The unit of the cost does 722 /// not matter because we use the 'cost' units to compare different 723 /// vector widths. The cost that is returned is *not* normalized by 724 /// the factor width. 725 unsigned expectedCost(unsigned VF); 726 727 /// Returns the execution time cost of an instruction for a given vector 728 /// width. Vector width of one means scalar. 729 unsigned getInstructionCost(Instruction *I, unsigned VF); 730 731 /// A helper function for converting Scalar types to vector types. 732 /// If the incoming type is void, we return void. If the VF is 1, we return 733 /// the scalar type. 734 static Type* ToVectorTy(Type *Scalar, unsigned VF); 735 736 /// Returns whether the instruction is a load or store and will be a emitted 737 /// as a vector operation. 738 bool isConsecutiveLoadOrStore(Instruction *I); 739 740 /// The loop that we evaluate. 741 Loop *TheLoop; 742 /// Scev analysis. 743 ScalarEvolution *SE; 744 /// Loop Info analysis. 745 LoopInfo *LI; 746 /// Vectorization legality. 747 LoopVectorizationLegality *Legal; 748 /// Vector target information. 749 const TargetTransformInfo &TTI; 750 /// Target data layout information. 751 DataLayout *DL; 752 /// Target Library Info. 753 const TargetLibraryInfo *TLI; 754}; 755 756/// Utility class for getting and setting loop vectorizer hints in the form 757/// of loop metadata. 758struct LoopVectorizeHints { 759 /// Vectorization width. 760 unsigned Width; 761 /// Vectorization unroll factor. 762 unsigned Unroll; 763 764 LoopVectorizeHints(const Loop *L, bool DisableUnrolling) 765 : Width(VectorizationFactor) 766 , Unroll(DisableUnrolling ? 1 : VectorizationUnroll) 767 , LoopID(L->getLoopID()) { 768 getHints(L); 769 // The command line options override any loop metadata except for when 770 // width == 1 which is used to indicate the loop is already vectorized. 771 if (VectorizationFactor.getNumOccurrences() > 0 && Width != 1) 772 Width = VectorizationFactor; 773 if (VectorizationUnroll.getNumOccurrences() > 0) 774 Unroll = VectorizationUnroll; 775 776 DEBUG(if (DisableUnrolling && Unroll == 1) 777 dbgs() << "LV: Unrolling disabled by the pass manager\n"); 778 } 779 780 /// Return the loop vectorizer metadata prefix. 781 static StringRef Prefix() { return "llvm.vectorizer."; } 782 783 MDNode *createHint(LLVMContext &Context, StringRef Name, unsigned V) { 784 SmallVector<Value*, 2> Vals; 785 Vals.push_back(MDString::get(Context, Name)); 786 Vals.push_back(ConstantInt::get(Type::getInt32Ty(Context), V)); 787 return MDNode::get(Context, Vals); 788 } 789 790 /// Mark the loop L as already vectorized by setting the width to 1. 791 void setAlreadyVectorized(Loop *L) { 792 LLVMContext &Context = L->getHeader()->getContext(); 793 794 Width = 1; 795 796 // Create a new loop id with one more operand for the already_vectorized 797 // hint. If the loop already has a loop id then copy the existing operands. 798 SmallVector<Value*, 4> Vals(1); 799 if (LoopID) 800 for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) 801 Vals.push_back(LoopID->getOperand(i)); 802 803 Vals.push_back(createHint(Context, Twine(Prefix(), "width").str(), Width)); 804 805 MDNode *NewLoopID = MDNode::get(Context, Vals); 806 // Set operand 0 to refer to the loop id itself. 807 NewLoopID->replaceOperandWith(0, NewLoopID); 808 809 L->setLoopID(NewLoopID); 810 if (LoopID) 811 LoopID->replaceAllUsesWith(NewLoopID); 812 813 LoopID = NewLoopID; 814 } 815 816private: 817 MDNode *LoopID; 818 819 /// Find hints specified in the loop metadata. 820 void getHints(const Loop *L) { 821 if (!LoopID) 822 return; 823 824 // First operand should refer to the loop id itself. 825 assert(LoopID->getNumOperands() > 0 && "requires at least one operand"); 826 assert(LoopID->getOperand(0) == LoopID && "invalid loop id"); 827 828 for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) { 829 const MDString *S = 0; 830 SmallVector<Value*, 4> Args; 831 832 // The expected hint is either a MDString or a MDNode with the first 833 // operand a MDString. 834 if (const MDNode *MD = dyn_cast<MDNode>(LoopID->getOperand(i))) { 835 if (!MD || MD->getNumOperands() == 0) 836 continue; 837 S = dyn_cast<MDString>(MD->getOperand(0)); 838 for (unsigned i = 1, ie = MD->getNumOperands(); i < ie; ++i) 839 Args.push_back(MD->getOperand(i)); 840 } else { 841 S = dyn_cast<MDString>(LoopID->getOperand(i)); 842 assert(Args.size() == 0 && "too many arguments for MDString"); 843 } 844 845 if (!S) 846 continue; 847 848 // Check if the hint starts with the vectorizer prefix. 849 StringRef Hint = S->getString(); 850 if (!Hint.startswith(Prefix())) 851 continue; 852 // Remove the prefix. 853 Hint = Hint.substr(Prefix().size(), StringRef::npos); 854 855 if (Args.size() == 1) 856 getHint(Hint, Args[0]); 857 } 858 } 859 860 // Check string hint with one operand. 861 void getHint(StringRef Hint, Value *Arg) { 862 const ConstantInt *C = dyn_cast<ConstantInt>(Arg); 863 if (!C) return; 864 unsigned Val = C->getZExtValue(); 865 866 if (Hint == "width") { 867 if (isPowerOf2_32(Val) && Val <= MaxVectorWidth) 868 Width = Val; 869 else 870 DEBUG(dbgs() << "LV: ignoring invalid width hint metadata"); 871 } else if (Hint == "unroll") { 872 if (isPowerOf2_32(Val) && Val <= MaxUnrollFactor) 873 Unroll = Val; 874 else 875 DEBUG(dbgs() << "LV: ignoring invalid unroll hint metadata"); 876 } else { 877 DEBUG(dbgs() << "LV: ignoring unknown hint " << Hint); 878 } 879 } 880}; 881 882/// The LoopVectorize Pass. 883struct LoopVectorize : public LoopPass { 884 /// Pass identification, replacement for typeid 885 static char ID; 886 887 explicit LoopVectorize(bool NoUnrolling = false) 888 : LoopPass(ID), DisableUnrolling(NoUnrolling) { 889 initializeLoopVectorizePass(*PassRegistry::getPassRegistry()); 890 } 891 892 ScalarEvolution *SE; 893 DataLayout *DL; 894 LoopInfo *LI; 895 TargetTransformInfo *TTI; 896 DominatorTree *DT; 897 TargetLibraryInfo *TLI; 898 bool DisableUnrolling; 899 900 virtual bool runOnLoop(Loop *L, LPPassManager &LPM) { 901 // We only vectorize innermost loops. 902 if (!L->empty()) 903 return false; 904 905 SE = &getAnalysis<ScalarEvolution>(); 906 DL = getAnalysisIfAvailable<DataLayout>(); 907 LI = &getAnalysis<LoopInfo>(); 908 TTI = &getAnalysis<TargetTransformInfo>(); 909 DT = &getAnalysis<DominatorTree>(); 910 TLI = getAnalysisIfAvailable<TargetLibraryInfo>(); 911 912 // If the target claims to have no vector registers don't attempt 913 // vectorization. 914 if (!TTI->getNumberOfRegisters(true)) 915 return false; 916 917 if (DL == NULL) { 918 DEBUG(dbgs() << "LV: Not vectorizing because of missing data layout"); 919 return false; 920 } 921 922 DEBUG(dbgs() << "LV: Checking a loop in \"" << 923 L->getHeader()->getParent()->getName() << "\"\n"); 924 925 LoopVectorizeHints Hints(L, DisableUnrolling); 926 927 if (Hints.Width == 1 && Hints.Unroll == 1) { 928 DEBUG(dbgs() << "LV: Not vectorizing.\n"); 929 return false; 930 } 931 932 // Check if it is legal to vectorize the loop. 933 LoopVectorizationLegality LVL(L, SE, DL, DT, TLI); 934 if (!LVL.canVectorize()) { 935 DEBUG(dbgs() << "LV: Not vectorizing.\n"); 936 return false; 937 } 938 939 // Use the cost model. 940 LoopVectorizationCostModel CM(L, SE, LI, &LVL, *TTI, DL, TLI); 941 942 // Check the function attributes to find out if this function should be 943 // optimized for size. 944 Function *F = L->getHeader()->getParent(); 945 Attribute::AttrKind SzAttr = Attribute::OptimizeForSize; 946 Attribute::AttrKind FlAttr = Attribute::NoImplicitFloat; 947 unsigned FnIndex = AttributeSet::FunctionIndex; 948 bool OptForSize = F->getAttributes().hasAttribute(FnIndex, SzAttr); 949 bool NoFloat = F->getAttributes().hasAttribute(FnIndex, FlAttr); 950 951 if (NoFloat) { 952 DEBUG(dbgs() << "LV: Can't vectorize when the NoImplicitFloat" 953 "attribute is used.\n"); 954 return false; 955 } 956 957 // Select the optimal vectorization factor. 958 LoopVectorizationCostModel::VectorizationFactor VF; 959 VF = CM.selectVectorizationFactor(OptForSize, Hints.Width); 960 // Select the unroll factor. 961 unsigned UF = CM.selectUnrollFactor(OptForSize, Hints.Unroll, VF.Width, 962 VF.Cost); 963 964 if (VF.Width == 1) { 965 DEBUG(dbgs() << "LV: Vectorization is possible but not beneficial.\n"); 966 } 967 968 DEBUG(dbgs() << "LV: Found a vectorizable loop ("<< VF.Width << ") in "<< 969 F->getParent()->getModuleIdentifier()<<"\n"); 970 DEBUG(dbgs() << "LV: Unroll Factor is " << UF << "\n"); 971 972 if (VF.Width == 1) { 973 if (UF == 1) 974 return false; 975 // We decided not to vectorize, but we may want to unroll. 976 InnerLoopUnroller Unroller(L, SE, LI, DT, DL, TLI, UF); 977 Unroller.vectorize(&LVL); 978 } else { 979 // If we decided that it is *legal* to vectorize the loop then do it. 980 InnerLoopVectorizer LB(L, SE, LI, DT, DL, TLI, VF.Width, UF); 981 LB.vectorize(&LVL); 982 } 983 984 // Mark the loop as already vectorized to avoid vectorizing again. 985 Hints.setAlreadyVectorized(L); 986 987 DEBUG(verifyFunction(*L->getHeader()->getParent())); 988 return true; 989 } 990 991 virtual void getAnalysisUsage(AnalysisUsage &AU) const { 992 LoopPass::getAnalysisUsage(AU); 993 AU.addRequiredID(LoopSimplifyID); 994 AU.addRequiredID(LCSSAID); 995 AU.addRequired<DominatorTree>(); 996 AU.addRequired<LoopInfo>(); 997 AU.addRequired<ScalarEvolution>(); 998 AU.addRequired<TargetTransformInfo>(); 999 AU.addPreserved<LoopInfo>(); 1000 AU.addPreserved<DominatorTree>(); 1001 } 1002 1003}; 1004 1005} // end anonymous namespace 1006 1007//===----------------------------------------------------------------------===// 1008// Implementation of LoopVectorizationLegality, InnerLoopVectorizer and 1009// LoopVectorizationCostModel. 1010//===----------------------------------------------------------------------===// 1011 1012void 1013LoopVectorizationLegality::RuntimePointerCheck::insert(ScalarEvolution *SE, 1014 Loop *Lp, Value *Ptr, 1015 bool WritePtr, 1016 unsigned DepSetId) { 1017 const SCEV *Sc = SE->getSCEV(Ptr); 1018 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Sc); 1019 assert(AR && "Invalid addrec expression"); 1020 const SCEV *Ex = SE->getBackedgeTakenCount(Lp); 1021 const SCEV *ScEnd = AR->evaluateAtIteration(Ex, *SE); 1022 Pointers.push_back(Ptr); 1023 Starts.push_back(AR->getStart()); 1024 Ends.push_back(ScEnd); 1025 IsWritePtr.push_back(WritePtr); 1026 DependencySetId.push_back(DepSetId); 1027} 1028 1029Value *InnerLoopVectorizer::getBroadcastInstrs(Value *V) { 1030 // Save the current insertion location. 1031 Instruction *Loc = Builder.GetInsertPoint(); 1032 1033 // We need to place the broadcast of invariant variables outside the loop. 1034 Instruction *Instr = dyn_cast<Instruction>(V); 1035 bool NewInstr = (Instr && Instr->getParent() == LoopVectorBody); 1036 bool Invariant = OrigLoop->isLoopInvariant(V) && !NewInstr; 1037 1038 // Place the code for broadcasting invariant variables in the new preheader. 1039 if (Invariant) 1040 Builder.SetInsertPoint(LoopVectorPreHeader->getTerminator()); 1041 1042 // Broadcast the scalar into all locations in the vector. 1043 Value *Shuf = Builder.CreateVectorSplat(VF, V, "broadcast"); 1044 1045 // Restore the builder insertion point. 1046 if (Invariant) 1047 Builder.SetInsertPoint(Loc); 1048 1049 return Shuf; 1050} 1051 1052Value *InnerLoopVectorizer::getConsecutiveVector(Value* Val, int StartIdx, 1053 bool Negate) { 1054 assert(Val->getType()->isVectorTy() && "Must be a vector"); 1055 assert(Val->getType()->getScalarType()->isIntegerTy() && 1056 "Elem must be an integer"); 1057 // Create the types. 1058 Type *ITy = Val->getType()->getScalarType(); 1059 VectorType *Ty = cast<VectorType>(Val->getType()); 1060 int VLen = Ty->getNumElements(); 1061 SmallVector<Constant*, 8> Indices; 1062 1063 // Create a vector of consecutive numbers from zero to VF. 1064 for (int i = 0; i < VLen; ++i) { 1065 int64_t Idx = Negate ? (-i) : i; 1066 Indices.push_back(ConstantInt::get(ITy, StartIdx + Idx, Negate)); 1067 } 1068 1069 // Add the consecutive indices to the vector value. 1070 Constant *Cv = ConstantVector::get(Indices); 1071 assert(Cv->getType() == Val->getType() && "Invalid consecutive vec"); 1072 return Builder.CreateAdd(Val, Cv, "induction"); 1073} 1074 1075int LoopVectorizationLegality::isConsecutivePtr(Value *Ptr) { 1076 assert(Ptr->getType()->isPointerTy() && "Unexpected non ptr"); 1077 // Make sure that the pointer does not point to structs. 1078 if (cast<PointerType>(Ptr->getType())->getElementType()->isAggregateType()) 1079 return 0; 1080 1081 // If this value is a pointer induction variable we know it is consecutive. 1082 PHINode *Phi = dyn_cast_or_null<PHINode>(Ptr); 1083 if (Phi && Inductions.count(Phi)) { 1084 InductionInfo II = Inductions[Phi]; 1085 if (IK_PtrInduction == II.IK) 1086 return 1; 1087 else if (IK_ReversePtrInduction == II.IK) 1088 return -1; 1089 } 1090 1091 GetElementPtrInst *Gep = dyn_cast_or_null<GetElementPtrInst>(Ptr); 1092 if (!Gep) 1093 return 0; 1094 1095 unsigned NumOperands = Gep->getNumOperands(); 1096 Value *LastIndex = Gep->getOperand(NumOperands - 1); 1097 1098 Value *GpPtr = Gep->getPointerOperand(); 1099 // If this GEP value is a consecutive pointer induction variable and all of 1100 // the indices are constant then we know it is consecutive. We can 1101 Phi = dyn_cast<PHINode>(GpPtr); 1102 if (Phi && Inductions.count(Phi)) { 1103 1104 // Make sure that the pointer does not point to structs. 1105 PointerType *GepPtrType = cast<PointerType>(GpPtr->getType()); 1106 if (GepPtrType->getElementType()->isAggregateType()) 1107 return 0; 1108 1109 // Make sure that all of the index operands are loop invariant. 1110 for (unsigned i = 1; i < NumOperands; ++i) 1111 if (!SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop)) 1112 return 0; 1113 1114 InductionInfo II = Inductions[Phi]; 1115 if (IK_PtrInduction == II.IK) 1116 return 1; 1117 else if (IK_ReversePtrInduction == II.IK) 1118 return -1; 1119 } 1120 1121 // Check that all of the gep indices are uniform except for the last. 1122 for (unsigned i = 0; i < NumOperands - 1; ++i) 1123 if (!SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop)) 1124 return 0; 1125 1126 // We can emit wide load/stores only if the last index is the induction 1127 // variable. 1128 const SCEV *Last = SE->getSCEV(LastIndex); 1129 if (const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Last)) { 1130 const SCEV *Step = AR->getStepRecurrence(*SE); 1131 1132 // The memory is consecutive because the last index is consecutive 1133 // and all other indices are loop invariant. 1134 if (Step->isOne()) 1135 return 1; 1136 if (Step->isAllOnesValue()) 1137 return -1; 1138 } 1139 1140 return 0; 1141} 1142 1143bool LoopVectorizationLegality::isUniform(Value *V) { 1144 return (SE->isLoopInvariant(SE->getSCEV(V), TheLoop)); 1145} 1146 1147InnerLoopVectorizer::VectorParts& 1148InnerLoopVectorizer::getVectorValue(Value *V) { 1149 assert(V != Induction && "The new induction variable should not be used."); 1150 assert(!V->getType()->isVectorTy() && "Can't widen a vector"); 1151 1152 // If we have this scalar in the map, return it. 1153 if (WidenMap.has(V)) 1154 return WidenMap.get(V); 1155 1156 // If this scalar is unknown, assume that it is a constant or that it is 1157 // loop invariant. Broadcast V and save the value for future uses. 1158 Value *B = getBroadcastInstrs(V); 1159 return WidenMap.splat(V, B); 1160} 1161 1162Value *InnerLoopVectorizer::reverseVector(Value *Vec) { 1163 assert(Vec->getType()->isVectorTy() && "Invalid type"); 1164 SmallVector<Constant*, 8> ShuffleMask; 1165 for (unsigned i = 0; i < VF; ++i) 1166 ShuffleMask.push_back(Builder.getInt32(VF - i - 1)); 1167 1168 return Builder.CreateShuffleVector(Vec, UndefValue::get(Vec->getType()), 1169 ConstantVector::get(ShuffleMask), 1170 "reverse"); 1171} 1172 1173 1174void InnerLoopVectorizer::vectorizeMemoryInstruction(Instruction *Instr, 1175 LoopVectorizationLegality *Legal) { 1176 // Attempt to issue a wide load. 1177 LoadInst *LI = dyn_cast<LoadInst>(Instr); 1178 StoreInst *SI = dyn_cast<StoreInst>(Instr); 1179 1180 assert((LI || SI) && "Invalid Load/Store instruction"); 1181 1182 Type *ScalarDataTy = LI ? LI->getType() : SI->getValueOperand()->getType(); 1183 Type *DataTy = VectorType::get(ScalarDataTy, VF); 1184 Value *Ptr = LI ? LI->getPointerOperand() : SI->getPointerOperand(); 1185 unsigned Alignment = LI ? LI->getAlignment() : SI->getAlignment(); 1186 unsigned AddressSpace = Ptr->getType()->getPointerAddressSpace(); 1187 unsigned ScalarAllocatedSize = DL->getTypeAllocSize(ScalarDataTy); 1188 unsigned VectorElementSize = DL->getTypeStoreSize(DataTy)/VF; 1189 1190 if (ScalarAllocatedSize != VectorElementSize) 1191 return scalarizeInstruction(Instr); 1192 1193 // If the pointer is loop invariant or if it is non consecutive, 1194 // scalarize the load. 1195 int ConsecutiveStride = Legal->isConsecutivePtr(Ptr); 1196 bool Reverse = ConsecutiveStride < 0; 1197 bool UniformLoad = LI && Legal->isUniform(Ptr); 1198 if (!ConsecutiveStride || UniformLoad) 1199 return scalarizeInstruction(Instr); 1200 1201 Constant *Zero = Builder.getInt32(0); 1202 VectorParts &Entry = WidenMap.get(Instr); 1203 1204 // Handle consecutive loads/stores. 1205 GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr); 1206 if (Gep && Legal->isInductionVariable(Gep->getPointerOperand())) { 1207 setDebugLocFromInst(Builder, Gep); 1208 Value *PtrOperand = Gep->getPointerOperand(); 1209 Value *FirstBasePtr = getVectorValue(PtrOperand)[0]; 1210 FirstBasePtr = Builder.CreateExtractElement(FirstBasePtr, Zero); 1211 1212 // Create the new GEP with the new induction variable. 1213 GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone()); 1214 Gep2->setOperand(0, FirstBasePtr); 1215 Gep2->setName("gep.indvar.base"); 1216 Ptr = Builder.Insert(Gep2); 1217 } else if (Gep) { 1218 setDebugLocFromInst(Builder, Gep); 1219 assert(SE->isLoopInvariant(SE->getSCEV(Gep->getPointerOperand()), 1220 OrigLoop) && "Base ptr must be invariant"); 1221 1222 // The last index does not have to be the induction. It can be 1223 // consecutive and be a function of the index. For example A[I+1]; 1224 unsigned NumOperands = Gep->getNumOperands(); 1225 unsigned LastOperand = NumOperands - 1; 1226 // Create the new GEP with the new induction variable. 1227 GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone()); 1228 1229 for (unsigned i = 0; i < NumOperands; ++i) { 1230 Value *GepOperand = Gep->getOperand(i); 1231 Instruction *GepOperandInst = dyn_cast<Instruction>(GepOperand); 1232 1233 // Update last index or loop invariant instruction anchored in loop. 1234 if (i == LastOperand || 1235 (GepOperandInst && OrigLoop->contains(GepOperandInst))) { 1236 assert((i == LastOperand || 1237 SE->isLoopInvariant(SE->getSCEV(GepOperandInst), OrigLoop)) && 1238 "Must be last index or loop invariant"); 1239 1240 VectorParts &GEPParts = getVectorValue(GepOperand); 1241 Value *Index = GEPParts[0]; 1242 Index = Builder.CreateExtractElement(Index, Zero); 1243 Gep2->setOperand(i, Index); 1244 Gep2->setName("gep.indvar.idx"); 1245 } 1246 } 1247 Ptr = Builder.Insert(Gep2); 1248 } else { 1249 // Use the induction element ptr. 1250 assert(isa<PHINode>(Ptr) && "Invalid induction ptr"); 1251 setDebugLocFromInst(Builder, Ptr); 1252 VectorParts &PtrVal = getVectorValue(Ptr); 1253 Ptr = Builder.CreateExtractElement(PtrVal[0], Zero); 1254 } 1255 1256 // Handle Stores: 1257 if (SI) { 1258 assert(!Legal->isUniform(SI->getPointerOperand()) && 1259 "We do not allow storing to uniform addresses"); 1260 setDebugLocFromInst(Builder, SI); 1261 // We don't want to update the value in the map as it might be used in 1262 // another expression. So don't use a reference type for "StoredVal". 1263 VectorParts StoredVal = getVectorValue(SI->getValueOperand()); 1264 1265 for (unsigned Part = 0; Part < UF; ++Part) { 1266 // Calculate the pointer for the specific unroll-part. 1267 Value *PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(Part * VF)); 1268 1269 if (Reverse) { 1270 // If we store to reverse consecutive memory locations then we need 1271 // to reverse the order of elements in the stored value. 1272 StoredVal[Part] = reverseVector(StoredVal[Part]); 1273 // If the address is consecutive but reversed, then the 1274 // wide store needs to start at the last vector element. 1275 PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(-Part * VF)); 1276 PartPtr = Builder.CreateGEP(PartPtr, Builder.getInt32(1 - VF)); 1277 } 1278 1279 Value *VecPtr = Builder.CreateBitCast(PartPtr, 1280 DataTy->getPointerTo(AddressSpace)); 1281 Builder.CreateStore(StoredVal[Part], VecPtr)->setAlignment(Alignment); 1282 } 1283 return; 1284 } 1285 1286 // Handle loads. 1287 assert(LI && "Must have a load instruction"); 1288 setDebugLocFromInst(Builder, LI); 1289 for (unsigned Part = 0; Part < UF; ++Part) { 1290 // Calculate the pointer for the specific unroll-part. 1291 Value *PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(Part * VF)); 1292 1293 if (Reverse) { 1294 // If the address is consecutive but reversed, then the 1295 // wide store needs to start at the last vector element. 1296 PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(-Part * VF)); 1297 PartPtr = Builder.CreateGEP(PartPtr, Builder.getInt32(1 - VF)); 1298 } 1299 1300 Value *VecPtr = Builder.CreateBitCast(PartPtr, 1301 DataTy->getPointerTo(AddressSpace)); 1302 Value *LI = Builder.CreateLoad(VecPtr, "wide.load"); 1303 cast<LoadInst>(LI)->setAlignment(Alignment); 1304 Entry[Part] = Reverse ? reverseVector(LI) : LI; 1305 } 1306} 1307 1308void InnerLoopVectorizer::scalarizeInstruction(Instruction *Instr) { 1309 assert(!Instr->getType()->isAggregateType() && "Can't handle vectors"); 1310 // Holds vector parameters or scalars, in case of uniform vals. 1311 SmallVector<VectorParts, 4> Params; 1312 1313 setDebugLocFromInst(Builder, Instr); 1314 1315 // Find all of the vectorized parameters. 1316 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) { 1317 Value *SrcOp = Instr->getOperand(op); 1318 1319 // If we are accessing the old induction variable, use the new one. 1320 if (SrcOp == OldInduction) { 1321 Params.push_back(getVectorValue(SrcOp)); 1322 continue; 1323 } 1324 1325 // Try using previously calculated values. 1326 Instruction *SrcInst = dyn_cast<Instruction>(SrcOp); 1327 1328 // If the src is an instruction that appeared earlier in the basic block 1329 // then it should already be vectorized. 1330 if (SrcInst && OrigLoop->contains(SrcInst)) { 1331 assert(WidenMap.has(SrcInst) && "Source operand is unavailable"); 1332 // The parameter is a vector value from earlier. 1333 Params.push_back(WidenMap.get(SrcInst)); 1334 } else { 1335 // The parameter is a scalar from outside the loop. Maybe even a constant. 1336 VectorParts Scalars; 1337 Scalars.append(UF, SrcOp); 1338 Params.push_back(Scalars); 1339 } 1340 } 1341 1342 assert(Params.size() == Instr->getNumOperands() && 1343 "Invalid number of operands"); 1344 1345 // Does this instruction return a value ? 1346 bool IsVoidRetTy = Instr->getType()->isVoidTy(); 1347 1348 Value *UndefVec = IsVoidRetTy ? 0 : 1349 UndefValue::get(VectorType::get(Instr->getType(), VF)); 1350 // Create a new entry in the WidenMap and initialize it to Undef or Null. 1351 VectorParts &VecResults = WidenMap.splat(Instr, UndefVec); 1352 1353 // For each vector unroll 'part': 1354 for (unsigned Part = 0; Part < UF; ++Part) { 1355 // For each scalar that we create: 1356 for (unsigned Width = 0; Width < VF; ++Width) { 1357 Instruction *Cloned = Instr->clone(); 1358 if (!IsVoidRetTy) 1359 Cloned->setName(Instr->getName() + ".cloned"); 1360 // Replace the operands of the cloned instructions with extracted scalars. 1361 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) { 1362 Value *Op = Params[op][Part]; 1363 // Param is a vector. Need to extract the right lane. 1364 if (Op->getType()->isVectorTy()) 1365 Op = Builder.CreateExtractElement(Op, Builder.getInt32(Width)); 1366 Cloned->setOperand(op, Op); 1367 } 1368 1369 // Place the cloned scalar in the new loop. 1370 Builder.Insert(Cloned); 1371 1372 // If the original scalar returns a value we need to place it in a vector 1373 // so that future users will be able to use it. 1374 if (!IsVoidRetTy) 1375 VecResults[Part] = Builder.CreateInsertElement(VecResults[Part], Cloned, 1376 Builder.getInt32(Width)); 1377 } 1378 } 1379} 1380 1381Instruction * 1382InnerLoopVectorizer::addRuntimeCheck(LoopVectorizationLegality *Legal, 1383 Instruction *Loc) { 1384 LoopVectorizationLegality::RuntimePointerCheck *PtrRtCheck = 1385 Legal->getRuntimePointerCheck(); 1386 1387 if (!PtrRtCheck->Need) 1388 return NULL; 1389 1390 unsigned NumPointers = PtrRtCheck->Pointers.size(); 1391 SmallVector<TrackingVH<Value> , 2> Starts; 1392 SmallVector<TrackingVH<Value> , 2> Ends; 1393 1394 SCEVExpander Exp(*SE, "induction"); 1395 1396 // Use this type for pointer arithmetic. 1397 Type* PtrArithTy = Type::getInt8PtrTy(Loc->getContext(), 0); 1398 1399 for (unsigned i = 0; i < NumPointers; ++i) { 1400 Value *Ptr = PtrRtCheck->Pointers[i]; 1401 const SCEV *Sc = SE->getSCEV(Ptr); 1402 1403 if (SE->isLoopInvariant(Sc, OrigLoop)) { 1404 DEBUG(dbgs() << "LV: Adding RT check for a loop invariant ptr:" << 1405 *Ptr <<"\n"); 1406 Starts.push_back(Ptr); 1407 Ends.push_back(Ptr); 1408 } else { 1409 DEBUG(dbgs() << "LV: Adding RT check for range:" << *Ptr <<"\n"); 1410 1411 Value *Start = Exp.expandCodeFor(PtrRtCheck->Starts[i], PtrArithTy, Loc); 1412 Value *End = Exp.expandCodeFor(PtrRtCheck->Ends[i], PtrArithTy, Loc); 1413 Starts.push_back(Start); 1414 Ends.push_back(End); 1415 } 1416 } 1417 1418 IRBuilder<> ChkBuilder(Loc); 1419 // Our instructions might fold to a constant. 1420 Value *MemoryRuntimeCheck = 0; 1421 for (unsigned i = 0; i < NumPointers; ++i) { 1422 for (unsigned j = i+1; j < NumPointers; ++j) { 1423 // No need to check if two readonly pointers intersect. 1424 if (!PtrRtCheck->IsWritePtr[i] && !PtrRtCheck->IsWritePtr[j]) 1425 continue; 1426 1427 // Only need to check pointers between two different dependency sets. 1428 if (PtrRtCheck->DependencySetId[i] == PtrRtCheck->DependencySetId[j]) 1429 continue; 1430 1431 Value *Start0 = ChkBuilder.CreateBitCast(Starts[i], PtrArithTy, "bc"); 1432 Value *Start1 = ChkBuilder.CreateBitCast(Starts[j], PtrArithTy, "bc"); 1433 Value *End0 = ChkBuilder.CreateBitCast(Ends[i], PtrArithTy, "bc"); 1434 Value *End1 = ChkBuilder.CreateBitCast(Ends[j], PtrArithTy, "bc"); 1435 1436 Value *Cmp0 = ChkBuilder.CreateICmpULE(Start0, End1, "bound0"); 1437 Value *Cmp1 = ChkBuilder.CreateICmpULE(Start1, End0, "bound1"); 1438 Value *IsConflict = ChkBuilder.CreateAnd(Cmp0, Cmp1, "found.conflict"); 1439 if (MemoryRuntimeCheck) 1440 IsConflict = ChkBuilder.CreateOr(MemoryRuntimeCheck, IsConflict, 1441 "conflict.rdx"); 1442 MemoryRuntimeCheck = IsConflict; 1443 } 1444 } 1445 1446 // We have to do this trickery because the IRBuilder might fold the check to a 1447 // constant expression in which case there is no Instruction anchored in a 1448 // the block. 1449 LLVMContext &Ctx = Loc->getContext(); 1450 Instruction * Check = BinaryOperator::CreateAnd(MemoryRuntimeCheck, 1451 ConstantInt::getTrue(Ctx)); 1452 ChkBuilder.Insert(Check, "memcheck.conflict"); 1453 return Check; 1454} 1455 1456void 1457InnerLoopVectorizer::createEmptyLoop(LoopVectorizationLegality *Legal) { 1458 /* 1459 In this function we generate a new loop. The new loop will contain 1460 the vectorized instructions while the old loop will continue to run the 1461 scalar remainder. 1462 1463 [ ] <-- vector loop bypass (may consist of multiple blocks). 1464 / | 1465 / v 1466 | [ ] <-- vector pre header. 1467 | | 1468 | v 1469 | [ ] \ 1470 | [ ]_| <-- vector loop. 1471 | | 1472 \ v 1473 >[ ] <--- middle-block. 1474 / | 1475 / v 1476 | [ ] <--- new preheader. 1477 | | 1478 | v 1479 | [ ] \ 1480 | [ ]_| <-- old scalar loop to handle remainder. 1481 \ | 1482 \ v 1483 >[ ] <-- exit block. 1484 ... 1485 */ 1486 1487 BasicBlock *OldBasicBlock = OrigLoop->getHeader(); 1488 BasicBlock *BypassBlock = OrigLoop->getLoopPreheader(); 1489 BasicBlock *ExitBlock = OrigLoop->getExitBlock(); 1490 assert(ExitBlock && "Must have an exit block"); 1491 1492 // Some loops have a single integer induction variable, while other loops 1493 // don't. One example is c++ iterators that often have multiple pointer 1494 // induction variables. In the code below we also support a case where we 1495 // don't have a single induction variable. 1496 OldInduction = Legal->getInduction(); 1497 Type *IdxTy = Legal->getWidestInductionType(); 1498 1499 // Find the loop boundaries. 1500 const SCEV *ExitCount = SE->getBackedgeTakenCount(OrigLoop); 1501 assert(ExitCount != SE->getCouldNotCompute() && "Invalid loop count"); 1502 1503 // Get the total trip count from the count by adding 1. 1504 ExitCount = SE->getAddExpr(ExitCount, 1505 SE->getConstant(ExitCount->getType(), 1)); 1506 1507 // Expand the trip count and place the new instructions in the preheader. 1508 // Notice that the pre-header does not change, only the loop body. 1509 SCEVExpander Exp(*SE, "induction"); 1510 1511 // Count holds the overall loop count (N). 1512 Value *Count = Exp.expandCodeFor(ExitCount, ExitCount->getType(), 1513 BypassBlock->getTerminator()); 1514 1515 // The loop index does not have to start at Zero. Find the original start 1516 // value from the induction PHI node. If we don't have an induction variable 1517 // then we know that it starts at zero. 1518 Builder.SetInsertPoint(BypassBlock->getTerminator()); 1519 Value *StartIdx = ExtendedIdx = OldInduction ? 1520 Builder.CreateZExt(OldInduction->getIncomingValueForBlock(BypassBlock), 1521 IdxTy): 1522 ConstantInt::get(IdxTy, 0); 1523 1524 assert(BypassBlock && "Invalid loop structure"); 1525 LoopBypassBlocks.push_back(BypassBlock); 1526 1527 // Split the single block loop into the two loop structure described above. 1528 BasicBlock *VectorPH = 1529 BypassBlock->splitBasicBlock(BypassBlock->getTerminator(), "vector.ph"); 1530 BasicBlock *VecBody = 1531 VectorPH->splitBasicBlock(VectorPH->getTerminator(), "vector.body"); 1532 BasicBlock *MiddleBlock = 1533 VecBody->splitBasicBlock(VecBody->getTerminator(), "middle.block"); 1534 BasicBlock *ScalarPH = 1535 MiddleBlock->splitBasicBlock(MiddleBlock->getTerminator(), "scalar.ph"); 1536 1537 // Create and register the new vector loop. 1538 Loop* Lp = new Loop(); 1539 Loop *ParentLoop = OrigLoop->getParentLoop(); 1540 1541 // Insert the new loop into the loop nest and register the new basic blocks 1542 // before calling any utilities such as SCEV that require valid LoopInfo. 1543 if (ParentLoop) { 1544 ParentLoop->addChildLoop(Lp); 1545 ParentLoop->addBasicBlockToLoop(ScalarPH, LI->getBase()); 1546 ParentLoop->addBasicBlockToLoop(VectorPH, LI->getBase()); 1547 ParentLoop->addBasicBlockToLoop(MiddleBlock, LI->getBase()); 1548 } else { 1549 LI->addTopLevelLoop(Lp); 1550 } 1551 Lp->addBasicBlockToLoop(VecBody, LI->getBase()); 1552 1553 // Use this IR builder to create the loop instructions (Phi, Br, Cmp) 1554 // inside the loop. 1555 Builder.SetInsertPoint(VecBody->getFirstNonPHI()); 1556 1557 // Generate the induction variable. 1558 setDebugLocFromInst(Builder, getDebugLocFromInstOrOperands(OldInduction)); 1559 Induction = Builder.CreatePHI(IdxTy, 2, "index"); 1560 // The loop step is equal to the vectorization factor (num of SIMD elements) 1561 // times the unroll factor (num of SIMD instructions). 1562 Constant *Step = ConstantInt::get(IdxTy, VF * UF); 1563 1564 // This is the IR builder that we use to add all of the logic for bypassing 1565 // the new vector loop. 1566 IRBuilder<> BypassBuilder(BypassBlock->getTerminator()); 1567 setDebugLocFromInst(BypassBuilder, 1568 getDebugLocFromInstOrOperands(OldInduction)); 1569 1570 // We may need to extend the index in case there is a type mismatch. 1571 // We know that the count starts at zero and does not overflow. 1572 if (Count->getType() != IdxTy) { 1573 // The exit count can be of pointer type. Convert it to the correct 1574 // integer type. 1575 if (ExitCount->getType()->isPointerTy()) 1576 Count = BypassBuilder.CreatePointerCast(Count, IdxTy, "ptrcnt.to.int"); 1577 else 1578 Count = BypassBuilder.CreateZExtOrTrunc(Count, IdxTy, "cnt.cast"); 1579 } 1580 1581 // Add the start index to the loop count to get the new end index. 1582 Value *IdxEnd = BypassBuilder.CreateAdd(Count, StartIdx, "end.idx"); 1583 1584 // Now we need to generate the expression for N - (N % VF), which is 1585 // the part that the vectorized body will execute. 1586 Value *R = BypassBuilder.CreateURem(Count, Step, "n.mod.vf"); 1587 Value *CountRoundDown = BypassBuilder.CreateSub(Count, R, "n.vec"); 1588 Value *IdxEndRoundDown = BypassBuilder.CreateAdd(CountRoundDown, StartIdx, 1589 "end.idx.rnd.down"); 1590 1591 // Now, compare the new count to zero. If it is zero skip the vector loop and 1592 // jump to the scalar loop. 1593 Value *Cmp = BypassBuilder.CreateICmpEQ(IdxEndRoundDown, StartIdx, 1594 "cmp.zero"); 1595 1596 BasicBlock *LastBypassBlock = BypassBlock; 1597 1598 // Generate the code that checks in runtime if arrays overlap. We put the 1599 // checks into a separate block to make the more common case of few elements 1600 // faster. 1601 Instruction *MemRuntimeCheck = addRuntimeCheck(Legal, 1602 BypassBlock->getTerminator()); 1603 if (MemRuntimeCheck) { 1604 // Create a new block containing the memory check. 1605 BasicBlock *CheckBlock = BypassBlock->splitBasicBlock(MemRuntimeCheck, 1606 "vector.memcheck"); 1607 if (ParentLoop) 1608 ParentLoop->addBasicBlockToLoop(CheckBlock, LI->getBase()); 1609 LoopBypassBlocks.push_back(CheckBlock); 1610 1611 // Replace the branch into the memory check block with a conditional branch 1612 // for the "few elements case". 1613 Instruction *OldTerm = BypassBlock->getTerminator(); 1614 BranchInst::Create(MiddleBlock, CheckBlock, Cmp, OldTerm); 1615 OldTerm->eraseFromParent(); 1616 1617 Cmp = MemRuntimeCheck; 1618 LastBypassBlock = CheckBlock; 1619 } 1620 1621 LastBypassBlock->getTerminator()->eraseFromParent(); 1622 BranchInst::Create(MiddleBlock, VectorPH, Cmp, 1623 LastBypassBlock); 1624 1625 // We are going to resume the execution of the scalar loop. 1626 // Go over all of the induction variables that we found and fix the 1627 // PHIs that are left in the scalar version of the loop. 1628 // The starting values of PHI nodes depend on the counter of the last 1629 // iteration in the vectorized loop. 1630 // If we come from a bypass edge then we need to start from the original 1631 // start value. 1632 1633 // This variable saves the new starting index for the scalar loop. 1634 PHINode *ResumeIndex = 0; 1635 LoopVectorizationLegality::InductionList::iterator I, E; 1636 LoopVectorizationLegality::InductionList *List = Legal->getInductionVars(); 1637 // Set builder to point to last bypass block. 1638 BypassBuilder.SetInsertPoint(LoopBypassBlocks.back()->getTerminator()); 1639 for (I = List->begin(), E = List->end(); I != E; ++I) { 1640 PHINode *OrigPhi = I->first; 1641 LoopVectorizationLegality::InductionInfo II = I->second; 1642 1643 Type *ResumeValTy = (OrigPhi == OldInduction) ? IdxTy : OrigPhi->getType(); 1644 PHINode *ResumeVal = PHINode::Create(ResumeValTy, 2, "resume.val", 1645 MiddleBlock->getTerminator()); 1646 // We might have extended the type of the induction variable but we need a 1647 // truncated version for the scalar loop. 1648 PHINode *TruncResumeVal = (OrigPhi == OldInduction) ? 1649 PHINode::Create(OrigPhi->getType(), 2, "trunc.resume.val", 1650 MiddleBlock->getTerminator()) : 0; 1651 1652 Value *EndValue = 0; 1653 switch (II.IK) { 1654 case LoopVectorizationLegality::IK_NoInduction: 1655 llvm_unreachable("Unknown induction"); 1656 case LoopVectorizationLegality::IK_IntInduction: { 1657 // Handle the integer induction counter. 1658 assert(OrigPhi->getType()->isIntegerTy() && "Invalid type"); 1659 1660 // We have the canonical induction variable. 1661 if (OrigPhi == OldInduction) { 1662 // Create a truncated version of the resume value for the scalar loop, 1663 // we might have promoted the type to a larger width. 1664 EndValue = 1665 BypassBuilder.CreateTrunc(IdxEndRoundDown, OrigPhi->getType()); 1666 // The new PHI merges the original incoming value, in case of a bypass, 1667 // or the value at the end of the vectorized loop. 1668 for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I) 1669 TruncResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]); 1670 TruncResumeVal->addIncoming(EndValue, VecBody); 1671 1672 // We know what the end value is. 1673 EndValue = IdxEndRoundDown; 1674 // We also know which PHI node holds it. 1675 ResumeIndex = ResumeVal; 1676 break; 1677 } 1678 1679 // Not the canonical induction variable - add the vector loop count to the 1680 // start value. 1681 Value *CRD = BypassBuilder.CreateSExtOrTrunc(CountRoundDown, 1682 II.StartValue->getType(), 1683 "cast.crd"); 1684 EndValue = BypassBuilder.CreateAdd(CRD, II.StartValue , "ind.end"); 1685 break; 1686 } 1687 case LoopVectorizationLegality::IK_ReverseIntInduction: { 1688 // Convert the CountRoundDown variable to the PHI size. 1689 Value *CRD = BypassBuilder.CreateSExtOrTrunc(CountRoundDown, 1690 II.StartValue->getType(), 1691 "cast.crd"); 1692 // Handle reverse integer induction counter. 1693 EndValue = BypassBuilder.CreateSub(II.StartValue, CRD, "rev.ind.end"); 1694 break; 1695 } 1696 case LoopVectorizationLegality::IK_PtrInduction: { 1697 // For pointer induction variables, calculate the offset using 1698 // the end index. 1699 EndValue = BypassBuilder.CreateGEP(II.StartValue, CountRoundDown, 1700 "ptr.ind.end"); 1701 break; 1702 } 1703 case LoopVectorizationLegality::IK_ReversePtrInduction: { 1704 // The value at the end of the loop for the reverse pointer is calculated 1705 // by creating a GEP with a negative index starting from the start value. 1706 Value *Zero = ConstantInt::get(CountRoundDown->getType(), 0); 1707 Value *NegIdx = BypassBuilder.CreateSub(Zero, CountRoundDown, 1708 "rev.ind.end"); 1709 EndValue = BypassBuilder.CreateGEP(II.StartValue, NegIdx, 1710 "rev.ptr.ind.end"); 1711 break; 1712 } 1713 }// end of case 1714 1715 // The new PHI merges the original incoming value, in case of a bypass, 1716 // or the value at the end of the vectorized loop. 1717 for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I) { 1718 if (OrigPhi == OldInduction) 1719 ResumeVal->addIncoming(StartIdx, LoopBypassBlocks[I]); 1720 else 1721 ResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]); 1722 } 1723 ResumeVal->addIncoming(EndValue, VecBody); 1724 1725 // Fix the scalar body counter (PHI node). 1726 unsigned BlockIdx = OrigPhi->getBasicBlockIndex(ScalarPH); 1727 // The old inductions phi node in the scalar body needs the truncated value. 1728 if (OrigPhi == OldInduction) 1729 OrigPhi->setIncomingValue(BlockIdx, TruncResumeVal); 1730 else 1731 OrigPhi->setIncomingValue(BlockIdx, ResumeVal); 1732 } 1733 1734 // If we are generating a new induction variable then we also need to 1735 // generate the code that calculates the exit value. This value is not 1736 // simply the end of the counter because we may skip the vectorized body 1737 // in case of a runtime check. 1738 if (!OldInduction){ 1739 assert(!ResumeIndex && "Unexpected resume value found"); 1740 ResumeIndex = PHINode::Create(IdxTy, 2, "new.indc.resume.val", 1741 MiddleBlock->getTerminator()); 1742 for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I) 1743 ResumeIndex->addIncoming(StartIdx, LoopBypassBlocks[I]); 1744 ResumeIndex->addIncoming(IdxEndRoundDown, VecBody); 1745 } 1746 1747 // Make sure that we found the index where scalar loop needs to continue. 1748 assert(ResumeIndex && ResumeIndex->getType()->isIntegerTy() && 1749 "Invalid resume Index"); 1750 1751 // Add a check in the middle block to see if we have completed 1752 // all of the iterations in the first vector loop. 1753 // If (N - N%VF) == N, then we *don't* need to run the remainder. 1754 Value *CmpN = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ, IdxEnd, 1755 ResumeIndex, "cmp.n", 1756 MiddleBlock->getTerminator()); 1757 1758 BranchInst::Create(ExitBlock, ScalarPH, CmpN, MiddleBlock->getTerminator()); 1759 // Remove the old terminator. 1760 MiddleBlock->getTerminator()->eraseFromParent(); 1761 1762 // Create i+1 and fill the PHINode. 1763 Value *NextIdx = Builder.CreateAdd(Induction, Step, "index.next"); 1764 Induction->addIncoming(StartIdx, VectorPH); 1765 Induction->addIncoming(NextIdx, VecBody); 1766 // Create the compare. 1767 Value *ICmp = Builder.CreateICmpEQ(NextIdx, IdxEndRoundDown); 1768 Builder.CreateCondBr(ICmp, MiddleBlock, VecBody); 1769 1770 // Now we have two terminators. Remove the old one from the block. 1771 VecBody->getTerminator()->eraseFromParent(); 1772 1773 // Get ready to start creating new instructions into the vectorized body. 1774 Builder.SetInsertPoint(VecBody->getFirstInsertionPt()); 1775 1776 // Save the state. 1777 LoopVectorPreHeader = VectorPH; 1778 LoopScalarPreHeader = ScalarPH; 1779 LoopMiddleBlock = MiddleBlock; 1780 LoopExitBlock = ExitBlock; 1781 LoopVectorBody = VecBody; 1782 LoopScalarBody = OldBasicBlock; 1783} 1784 1785/// This function returns the identity element (or neutral element) for 1786/// the operation K. 1787Constant* 1788LoopVectorizationLegality::getReductionIdentity(ReductionKind K, Type *Tp) { 1789 switch (K) { 1790 case RK_IntegerXor: 1791 case RK_IntegerAdd: 1792 case RK_IntegerOr: 1793 // Adding, Xoring, Oring zero to a number does not change it. 1794 return ConstantInt::get(Tp, 0); 1795 case RK_IntegerMult: 1796 // Multiplying a number by 1 does not change it. 1797 return ConstantInt::get(Tp, 1); 1798 case RK_IntegerAnd: 1799 // AND-ing a number with an all-1 value does not change it. 1800 return ConstantInt::get(Tp, -1, true); 1801 case RK_FloatMult: 1802 // Multiplying a number by 1 does not change it. 1803 return ConstantFP::get(Tp, 1.0L); 1804 case RK_FloatAdd: 1805 // Adding zero to a number does not change it. 1806 return ConstantFP::get(Tp, 0.0L); 1807 default: 1808 llvm_unreachable("Unknown reduction kind"); 1809 } 1810} 1811 1812static Intrinsic::ID checkUnaryFloatSignature(const CallInst &I, 1813 Intrinsic::ID ValidIntrinsicID) { 1814 if (I.getNumArgOperands() != 1 || 1815 !I.getArgOperand(0)->getType()->isFloatingPointTy() || 1816 I.getType() != I.getArgOperand(0)->getType() || 1817 !I.onlyReadsMemory()) 1818 return Intrinsic::not_intrinsic; 1819 1820 return ValidIntrinsicID; 1821} 1822 1823static Intrinsic::ID checkBinaryFloatSignature(const CallInst &I, 1824 Intrinsic::ID ValidIntrinsicID) { 1825 if (I.getNumArgOperands() != 2 || 1826 !I.getArgOperand(0)->getType()->isFloatingPointTy() || 1827 !I.getArgOperand(1)->getType()->isFloatingPointTy() || 1828 I.getType() != I.getArgOperand(0)->getType() || 1829 I.getType() != I.getArgOperand(1)->getType() || 1830 !I.onlyReadsMemory()) 1831 return Intrinsic::not_intrinsic; 1832 1833 return ValidIntrinsicID; 1834} 1835 1836 1837static Intrinsic::ID 1838getIntrinsicIDForCall(CallInst *CI, const TargetLibraryInfo *TLI) { 1839 // If we have an intrinsic call, check if it is trivially vectorizable. 1840 if (IntrinsicInst *II = dyn_cast<IntrinsicInst>(CI)) { 1841 switch (II->getIntrinsicID()) { 1842 case Intrinsic::sqrt: 1843 case Intrinsic::sin: 1844 case Intrinsic::cos: 1845 case Intrinsic::exp: 1846 case Intrinsic::exp2: 1847 case Intrinsic::log: 1848 case Intrinsic::log10: 1849 case Intrinsic::log2: 1850 case Intrinsic::fabs: 1851 case Intrinsic::copysign: 1852 case Intrinsic::floor: 1853 case Intrinsic::ceil: 1854 case Intrinsic::trunc: 1855 case Intrinsic::rint: 1856 case Intrinsic::nearbyint: 1857 case Intrinsic::round: 1858 case Intrinsic::pow: 1859 case Intrinsic::fma: 1860 case Intrinsic::fmuladd: 1861 case Intrinsic::lifetime_start: 1862 case Intrinsic::lifetime_end: 1863 return II->getIntrinsicID(); 1864 default: 1865 return Intrinsic::not_intrinsic; 1866 } 1867 } 1868 1869 if (!TLI) 1870 return Intrinsic::not_intrinsic; 1871 1872 LibFunc::Func Func; 1873 Function *F = CI->getCalledFunction(); 1874 // We're going to make assumptions on the semantics of the functions, check 1875 // that the target knows that it's available in this environment and it does 1876 // not have local linkage. 1877 if (!F || F->hasLocalLinkage() || !TLI->getLibFunc(F->getName(), Func)) 1878 return Intrinsic::not_intrinsic; 1879 1880 // Otherwise check if we have a call to a function that can be turned into a 1881 // vector intrinsic. 1882 switch (Func) { 1883 default: 1884 break; 1885 case LibFunc::sin: 1886 case LibFunc::sinf: 1887 case LibFunc::sinl: 1888 return checkUnaryFloatSignature(*CI, Intrinsic::sin); 1889 case LibFunc::cos: 1890 case LibFunc::cosf: 1891 case LibFunc::cosl: 1892 return checkUnaryFloatSignature(*CI, Intrinsic::cos); 1893 case LibFunc::exp: 1894 case LibFunc::expf: 1895 case LibFunc::expl: 1896 return checkUnaryFloatSignature(*CI, Intrinsic::exp); 1897 case LibFunc::exp2: 1898 case LibFunc::exp2f: 1899 case LibFunc::exp2l: 1900 return checkUnaryFloatSignature(*CI, Intrinsic::exp2); 1901 case LibFunc::log: 1902 case LibFunc::logf: 1903 case LibFunc::logl: 1904 return checkUnaryFloatSignature(*CI, Intrinsic::log); 1905 case LibFunc::log10: 1906 case LibFunc::log10f: 1907 case LibFunc::log10l: 1908 return checkUnaryFloatSignature(*CI, Intrinsic::log10); 1909 case LibFunc::log2: 1910 case LibFunc::log2f: 1911 case LibFunc::log2l: 1912 return checkUnaryFloatSignature(*CI, Intrinsic::log2); 1913 case LibFunc::fabs: 1914 case LibFunc::fabsf: 1915 case LibFunc::fabsl: 1916 return checkUnaryFloatSignature(*CI, Intrinsic::fabs); 1917 case LibFunc::copysign: 1918 case LibFunc::copysignf: 1919 case LibFunc::copysignl: 1920 return checkBinaryFloatSignature(*CI, Intrinsic::copysign); 1921 case LibFunc::floor: 1922 case LibFunc::floorf: 1923 case LibFunc::floorl: 1924 return checkUnaryFloatSignature(*CI, Intrinsic::floor); 1925 case LibFunc::ceil: 1926 case LibFunc::ceilf: 1927 case LibFunc::ceill: 1928 return checkUnaryFloatSignature(*CI, Intrinsic::ceil); 1929 case LibFunc::trunc: 1930 case LibFunc::truncf: 1931 case LibFunc::truncl: 1932 return checkUnaryFloatSignature(*CI, Intrinsic::trunc); 1933 case LibFunc::rint: 1934 case LibFunc::rintf: 1935 case LibFunc::rintl: 1936 return checkUnaryFloatSignature(*CI, Intrinsic::rint); 1937 case LibFunc::nearbyint: 1938 case LibFunc::nearbyintf: 1939 case LibFunc::nearbyintl: 1940 return checkUnaryFloatSignature(*CI, Intrinsic::nearbyint); 1941 case LibFunc::round: 1942 case LibFunc::roundf: 1943 case LibFunc::roundl: 1944 return checkUnaryFloatSignature(*CI, Intrinsic::round); 1945 case LibFunc::pow: 1946 case LibFunc::powf: 1947 case LibFunc::powl: 1948 return checkBinaryFloatSignature(*CI, Intrinsic::pow); 1949 } 1950 1951 return Intrinsic::not_intrinsic; 1952} 1953 1954/// This function translates the reduction kind to an LLVM binary operator. 1955static unsigned 1956getReductionBinOp(LoopVectorizationLegality::ReductionKind Kind) { 1957 switch (Kind) { 1958 case LoopVectorizationLegality::RK_IntegerAdd: 1959 return Instruction::Add; 1960 case LoopVectorizationLegality::RK_IntegerMult: 1961 return Instruction::Mul; 1962 case LoopVectorizationLegality::RK_IntegerOr: 1963 return Instruction::Or; 1964 case LoopVectorizationLegality::RK_IntegerAnd: 1965 return Instruction::And; 1966 case LoopVectorizationLegality::RK_IntegerXor: 1967 return Instruction::Xor; 1968 case LoopVectorizationLegality::RK_FloatMult: 1969 return Instruction::FMul; 1970 case LoopVectorizationLegality::RK_FloatAdd: 1971 return Instruction::FAdd; 1972 case LoopVectorizationLegality::RK_IntegerMinMax: 1973 return Instruction::ICmp; 1974 case LoopVectorizationLegality::RK_FloatMinMax: 1975 return Instruction::FCmp; 1976 default: 1977 llvm_unreachable("Unknown reduction operation"); 1978 } 1979} 1980 1981Value *createMinMaxOp(IRBuilder<> &Builder, 1982 LoopVectorizationLegality::MinMaxReductionKind RK, 1983 Value *Left, 1984 Value *Right) { 1985 CmpInst::Predicate P = CmpInst::ICMP_NE; 1986 switch (RK) { 1987 default: 1988 llvm_unreachable("Unknown min/max reduction kind"); 1989 case LoopVectorizationLegality::MRK_UIntMin: 1990 P = CmpInst::ICMP_ULT; 1991 break; 1992 case LoopVectorizationLegality::MRK_UIntMax: 1993 P = CmpInst::ICMP_UGT; 1994 break; 1995 case LoopVectorizationLegality::MRK_SIntMin: 1996 P = CmpInst::ICMP_SLT; 1997 break; 1998 case LoopVectorizationLegality::MRK_SIntMax: 1999 P = CmpInst::ICMP_SGT; 2000 break; 2001 case LoopVectorizationLegality::MRK_FloatMin: 2002 P = CmpInst::FCMP_OLT; 2003 break; 2004 case LoopVectorizationLegality::MRK_FloatMax: 2005 P = CmpInst::FCMP_OGT; 2006 break; 2007 } 2008 2009 Value *Cmp; 2010 if (RK == LoopVectorizationLegality::MRK_FloatMin || 2011 RK == LoopVectorizationLegality::MRK_FloatMax) 2012 Cmp = Builder.CreateFCmp(P, Left, Right, "rdx.minmax.cmp"); 2013 else 2014 Cmp = Builder.CreateICmp(P, Left, Right, "rdx.minmax.cmp"); 2015 2016 Value *Select = Builder.CreateSelect(Cmp, Left, Right, "rdx.minmax.select"); 2017 return Select; 2018} 2019 2020void 2021InnerLoopVectorizer::vectorizeLoop(LoopVectorizationLegality *Legal) { 2022 //===------------------------------------------------===// 2023 // 2024 // Notice: any optimization or new instruction that go 2025 // into the code below should be also be implemented in 2026 // the cost-model. 2027 // 2028 //===------------------------------------------------===// 2029 Constant *Zero = Builder.getInt32(0); 2030 2031 // In order to support reduction variables we need to be able to vectorize 2032 // Phi nodes. Phi nodes have cycles, so we need to vectorize them in two 2033 // stages. First, we create a new vector PHI node with no incoming edges. 2034 // We use this value when we vectorize all of the instructions that use the 2035 // PHI. Next, after all of the instructions in the block are complete we 2036 // add the new incoming edges to the PHI. At this point all of the 2037 // instructions in the basic block are vectorized, so we can use them to 2038 // construct the PHI. 2039 PhiVector RdxPHIsToFix; 2040 2041 // Scan the loop in a topological order to ensure that defs are vectorized 2042 // before users. 2043 LoopBlocksDFS DFS(OrigLoop); 2044 DFS.perform(LI); 2045 2046 // Vectorize all of the blocks in the original loop. 2047 for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(), 2048 be = DFS.endRPO(); bb != be; ++bb) 2049 vectorizeBlockInLoop(Legal, *bb, &RdxPHIsToFix); 2050 2051 // At this point every instruction in the original loop is widened to 2052 // a vector form. We are almost done. Now, we need to fix the PHI nodes 2053 // that we vectorized. The PHI nodes are currently empty because we did 2054 // not want to introduce cycles. Notice that the remaining PHI nodes 2055 // that we need to fix are reduction variables. 2056 2057 // Create the 'reduced' values for each of the induction vars. 2058 // The reduced values are the vector values that we scalarize and combine 2059 // after the loop is finished. 2060 for (PhiVector::iterator it = RdxPHIsToFix.begin(), e = RdxPHIsToFix.end(); 2061 it != e; ++it) { 2062 PHINode *RdxPhi = *it; 2063 assert(RdxPhi && "Unable to recover vectorized PHI"); 2064 2065 // Find the reduction variable descriptor. 2066 assert(Legal->getReductionVars()->count(RdxPhi) && 2067 "Unable to find the reduction variable"); 2068 LoopVectorizationLegality::ReductionDescriptor RdxDesc = 2069 (*Legal->getReductionVars())[RdxPhi]; 2070 2071 setDebugLocFromInst(Builder, RdxDesc.StartValue); 2072 2073 // We need to generate a reduction vector from the incoming scalar. 2074 // To do so, we need to generate the 'identity' vector and overide 2075 // one of the elements with the incoming scalar reduction. We need 2076 // to do it in the vector-loop preheader. 2077 Builder.SetInsertPoint(LoopBypassBlocks.front()->getTerminator()); 2078 2079 // This is the vector-clone of the value that leaves the loop. 2080 VectorParts &VectorExit = getVectorValue(RdxDesc.LoopExitInstr); 2081 Type *VecTy = VectorExit[0]->getType(); 2082 2083 // Find the reduction identity variable. Zero for addition, or, xor, 2084 // one for multiplication, -1 for And. 2085 Value *Identity; 2086 Value *VectorStart; 2087 if (RdxDesc.Kind == LoopVectorizationLegality::RK_IntegerMinMax || 2088 RdxDesc.Kind == LoopVectorizationLegality::RK_FloatMinMax) { 2089 // MinMax reduction have the start value as their identify. 2090 if (VF == 1) { 2091 VectorStart = Identity = RdxDesc.StartValue; 2092 } else { 2093 VectorStart = Identity = Builder.CreateVectorSplat(VF, 2094 RdxDesc.StartValue, 2095 "minmax.ident"); 2096 } 2097 } else { 2098 // Handle other reduction kinds: 2099 Constant *Iden = 2100 LoopVectorizationLegality::getReductionIdentity(RdxDesc.Kind, 2101 VecTy->getScalarType()); 2102 if (VF == 1) { 2103 Identity = Iden; 2104 // This vector is the Identity vector where the first element is the 2105 // incoming scalar reduction. 2106 VectorStart = RdxDesc.StartValue; 2107 } else { 2108 Identity = ConstantVector::getSplat(VF, Iden); 2109 2110 // This vector is the Identity vector where the first element is the 2111 // incoming scalar reduction. 2112 VectorStart = Builder.CreateInsertElement(Identity, 2113 RdxDesc.StartValue, Zero); 2114 } 2115 } 2116 2117 // Fix the vector-loop phi. 2118 // We created the induction variable so we know that the 2119 // preheader is the first entry. 2120 BasicBlock *VecPreheader = Induction->getIncomingBlock(0); 2121 2122 // Reductions do not have to start at zero. They can start with 2123 // any loop invariant values. 2124 VectorParts &VecRdxPhi = WidenMap.get(RdxPhi); 2125 BasicBlock *Latch = OrigLoop->getLoopLatch(); 2126 Value *LoopVal = RdxPhi->getIncomingValueForBlock(Latch); 2127 VectorParts &Val = getVectorValue(LoopVal); 2128 for (unsigned part = 0; part < UF; ++part) { 2129 // Make sure to add the reduction stat value only to the 2130 // first unroll part. 2131 Value *StartVal = (part == 0) ? VectorStart : Identity; 2132 cast<PHINode>(VecRdxPhi[part])->addIncoming(StartVal, VecPreheader); 2133 cast<PHINode>(VecRdxPhi[part])->addIncoming(Val[part], LoopVectorBody); 2134 } 2135 2136 // Before each round, move the insertion point right between 2137 // the PHIs and the values we are going to write. 2138 // This allows us to write both PHINodes and the extractelement 2139 // instructions. 2140 Builder.SetInsertPoint(LoopMiddleBlock->getFirstInsertionPt()); 2141 2142 VectorParts RdxParts; 2143 setDebugLocFromInst(Builder, RdxDesc.LoopExitInstr); 2144 for (unsigned part = 0; part < UF; ++part) { 2145 // This PHINode contains the vectorized reduction variable, or 2146 // the initial value vector, if we bypass the vector loop. 2147 VectorParts &RdxExitVal = getVectorValue(RdxDesc.LoopExitInstr); 2148 PHINode *NewPhi = Builder.CreatePHI(VecTy, 2, "rdx.vec.exit.phi"); 2149 Value *StartVal = (part == 0) ? VectorStart : Identity; 2150 for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I) 2151 NewPhi->addIncoming(StartVal, LoopBypassBlocks[I]); 2152 NewPhi->addIncoming(RdxExitVal[part], LoopVectorBody); 2153 RdxParts.push_back(NewPhi); 2154 } 2155 2156 // Reduce all of the unrolled parts into a single vector. 2157 Value *ReducedPartRdx = RdxParts[0]; 2158 unsigned Op = getReductionBinOp(RdxDesc.Kind); 2159 setDebugLocFromInst(Builder, ReducedPartRdx); 2160 for (unsigned part = 1; part < UF; ++part) { 2161 if (Op != Instruction::ICmp && Op != Instruction::FCmp) 2162 ReducedPartRdx = Builder.CreateBinOp((Instruction::BinaryOps)Op, 2163 RdxParts[part], ReducedPartRdx, 2164 "bin.rdx"); 2165 else 2166 ReducedPartRdx = createMinMaxOp(Builder, RdxDesc.MinMaxKind, 2167 ReducedPartRdx, RdxParts[part]); 2168 } 2169 2170 if (VF > 1) { 2171 // VF is a power of 2 so we can emit the reduction using log2(VF) shuffles 2172 // and vector ops, reducing the set of values being computed by half each 2173 // round. 2174 assert(isPowerOf2_32(VF) && 2175 "Reduction emission only supported for pow2 vectors!"); 2176 Value *TmpVec = ReducedPartRdx; 2177 SmallVector<Constant*, 32> ShuffleMask(VF, 0); 2178 for (unsigned i = VF; i != 1; i >>= 1) { 2179 // Move the upper half of the vector to the lower half. 2180 for (unsigned j = 0; j != i/2; ++j) 2181 ShuffleMask[j] = Builder.getInt32(i/2 + j); 2182 2183 // Fill the rest of the mask with undef. 2184 std::fill(&ShuffleMask[i/2], ShuffleMask.end(), 2185 UndefValue::get(Builder.getInt32Ty())); 2186 2187 Value *Shuf = 2188 Builder.CreateShuffleVector(TmpVec, 2189 UndefValue::get(TmpVec->getType()), 2190 ConstantVector::get(ShuffleMask), 2191 "rdx.shuf"); 2192 2193 if (Op != Instruction::ICmp && Op != Instruction::FCmp) 2194 TmpVec = Builder.CreateBinOp((Instruction::BinaryOps)Op, TmpVec, Shuf, 2195 "bin.rdx"); 2196 else 2197 TmpVec = createMinMaxOp(Builder, RdxDesc.MinMaxKind, TmpVec, Shuf); 2198 } 2199 2200 // The result is in the first element of the vector. 2201 ReducedPartRdx = Builder.CreateExtractElement(TmpVec, 2202 Builder.getInt32(0)); 2203 } 2204 2205 // Now, we need to fix the users of the reduction variable 2206 // inside and outside of the scalar remainder loop. 2207 // We know that the loop is in LCSSA form. We need to update the 2208 // PHI nodes in the exit blocks. 2209 for (BasicBlock::iterator LEI = LoopExitBlock->begin(), 2210 LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) { 2211 PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI); 2212 if (!LCSSAPhi) break; 2213 2214 // All PHINodes need to have a single entry edge, or two if 2215 // we already fixed them. 2216 assert(LCSSAPhi->getNumIncomingValues() < 3 && "Invalid LCSSA PHI"); 2217 2218 // We found our reduction value exit-PHI. Update it with the 2219 // incoming bypass edge. 2220 if (LCSSAPhi->getIncomingValue(0) == RdxDesc.LoopExitInstr) { 2221 // Add an edge coming from the bypass. 2222 LCSSAPhi->addIncoming(ReducedPartRdx, LoopMiddleBlock); 2223 break; 2224 } 2225 }// end of the LCSSA phi scan. 2226 2227 // Fix the scalar loop reduction variable with the incoming reduction sum 2228 // from the vector body and from the backedge value. 2229 int IncomingEdgeBlockIdx = 2230 (RdxPhi)->getBasicBlockIndex(OrigLoop->getLoopLatch()); 2231 assert(IncomingEdgeBlockIdx >= 0 && "Invalid block index"); 2232 // Pick the other block. 2233 int SelfEdgeBlockIdx = (IncomingEdgeBlockIdx ? 0 : 1); 2234 (RdxPhi)->setIncomingValue(SelfEdgeBlockIdx, ReducedPartRdx); 2235 (RdxPhi)->setIncomingValue(IncomingEdgeBlockIdx, RdxDesc.LoopExitInstr); 2236 }// end of for each redux variable. 2237 2238 fixLCSSAPHIs(); 2239} 2240 2241void InnerLoopVectorizer::fixLCSSAPHIs() { 2242 for (BasicBlock::iterator LEI = LoopExitBlock->begin(), 2243 LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) { 2244 PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI); 2245 if (!LCSSAPhi) break; 2246 if (LCSSAPhi->getNumIncomingValues() == 1) 2247 LCSSAPhi->addIncoming(UndefValue::get(LCSSAPhi->getType()), 2248 LoopMiddleBlock); 2249 } 2250} 2251 2252InnerLoopVectorizer::VectorParts 2253InnerLoopVectorizer::createEdgeMask(BasicBlock *Src, BasicBlock *Dst) { 2254 assert(std::find(pred_begin(Dst), pred_end(Dst), Src) != pred_end(Dst) && 2255 "Invalid edge"); 2256 2257 // Look for cached value. 2258 std::pair<BasicBlock*, BasicBlock*> Edge(Src, Dst); 2259 EdgeMaskCache::iterator ECEntryIt = MaskCache.find(Edge); 2260 if (ECEntryIt != MaskCache.end()) 2261 return ECEntryIt->second; 2262 2263 VectorParts SrcMask = createBlockInMask(Src); 2264 2265 // The terminator has to be a branch inst! 2266 BranchInst *BI = dyn_cast<BranchInst>(Src->getTerminator()); 2267 assert(BI && "Unexpected terminator found"); 2268 2269 if (BI->isConditional()) { 2270 VectorParts EdgeMask = getVectorValue(BI->getCondition()); 2271 2272 if (BI->getSuccessor(0) != Dst) 2273 for (unsigned part = 0; part < UF; ++part) 2274 EdgeMask[part] = Builder.CreateNot(EdgeMask[part]); 2275 2276 for (unsigned part = 0; part < UF; ++part) 2277 EdgeMask[part] = Builder.CreateAnd(EdgeMask[part], SrcMask[part]); 2278 2279 MaskCache[Edge] = EdgeMask; 2280 return EdgeMask; 2281 } 2282 2283 MaskCache[Edge] = SrcMask; 2284 return SrcMask; 2285} 2286 2287InnerLoopVectorizer::VectorParts 2288InnerLoopVectorizer::createBlockInMask(BasicBlock *BB) { 2289 assert(OrigLoop->contains(BB) && "Block is not a part of a loop"); 2290 2291 // Loop incoming mask is all-one. 2292 if (OrigLoop->getHeader() == BB) { 2293 Value *C = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 1); 2294 return getVectorValue(C); 2295 } 2296 2297 // This is the block mask. We OR all incoming edges, and with zero. 2298 Value *Zero = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 0); 2299 VectorParts BlockMask = getVectorValue(Zero); 2300 2301 // For each pred: 2302 for (pred_iterator it = pred_begin(BB), e = pred_end(BB); it != e; ++it) { 2303 VectorParts EM = createEdgeMask(*it, BB); 2304 for (unsigned part = 0; part < UF; ++part) 2305 BlockMask[part] = Builder.CreateOr(BlockMask[part], EM[part]); 2306 } 2307 2308 return BlockMask; 2309} 2310 2311void InnerLoopVectorizer::widenPHIInstruction(Instruction *PN, 2312 InnerLoopVectorizer::VectorParts &Entry, 2313 LoopVectorizationLegality *Legal, 2314 unsigned UF, unsigned VF, PhiVector *PV) { 2315 PHINode* P = cast<PHINode>(PN); 2316 // Handle reduction variables: 2317 if (Legal->getReductionVars()->count(P)) { 2318 for (unsigned part = 0; part < UF; ++part) { 2319 // This is phase one of vectorizing PHIs. 2320 Type *VecTy = (VF == 1) ? PN->getType() : 2321 VectorType::get(PN->getType(), VF); 2322 Entry[part] = PHINode::Create(VecTy, 2, "vec.phi", 2323 LoopVectorBody-> getFirstInsertionPt()); 2324 } 2325 PV->push_back(P); 2326 return; 2327 } 2328 2329 setDebugLocFromInst(Builder, P); 2330 // Check for PHI nodes that are lowered to vector selects. 2331 if (P->getParent() != OrigLoop->getHeader()) { 2332 // We know that all PHIs in non header blocks are converted into 2333 // selects, so we don't have to worry about the insertion order and we 2334 // can just use the builder. 2335 // At this point we generate the predication tree. There may be 2336 // duplications since this is a simple recursive scan, but future 2337 // optimizations will clean it up. 2338 2339 unsigned NumIncoming = P->getNumIncomingValues(); 2340 2341 // Generate a sequence of selects of the form: 2342 // SELECT(Mask3, In3, 2343 // SELECT(Mask2, In2, 2344 // ( ...))) 2345 for (unsigned In = 0; In < NumIncoming; In++) { 2346 VectorParts Cond = createEdgeMask(P->getIncomingBlock(In), 2347 P->getParent()); 2348 VectorParts &In0 = getVectorValue(P->getIncomingValue(In)); 2349 2350 for (unsigned part = 0; part < UF; ++part) { 2351 // We might have single edge PHIs (blocks) - use an identity 2352 // 'select' for the first PHI operand. 2353 if (In == 0) 2354 Entry[part] = Builder.CreateSelect(Cond[part], In0[part], 2355 In0[part]); 2356 else 2357 // Select between the current value and the previous incoming edge 2358 // based on the incoming mask. 2359 Entry[part] = Builder.CreateSelect(Cond[part], In0[part], 2360 Entry[part], "predphi"); 2361 } 2362 } 2363 return; 2364 } 2365 2366 // This PHINode must be an induction variable. 2367 // Make sure that we know about it. 2368 assert(Legal->getInductionVars()->count(P) && 2369 "Not an induction variable"); 2370 2371 LoopVectorizationLegality::InductionInfo II = 2372 Legal->getInductionVars()->lookup(P); 2373 2374 switch (II.IK) { 2375 case LoopVectorizationLegality::IK_NoInduction: 2376 llvm_unreachable("Unknown induction"); 2377 case LoopVectorizationLegality::IK_IntInduction: { 2378 assert(P->getType() == II.StartValue->getType() && "Types must match"); 2379 Type *PhiTy = P->getType(); 2380 Value *Broadcasted; 2381 if (P == OldInduction) { 2382 // Handle the canonical induction variable. We might have had to 2383 // extend the type. 2384 Broadcasted = Builder.CreateTrunc(Induction, PhiTy); 2385 } else { 2386 // Handle other induction variables that are now based on the 2387 // canonical one. 2388 Value *NormalizedIdx = Builder.CreateSub(Induction, ExtendedIdx, 2389 "normalized.idx"); 2390 NormalizedIdx = Builder.CreateSExtOrTrunc(NormalizedIdx, PhiTy); 2391 Broadcasted = Builder.CreateAdd(II.StartValue, NormalizedIdx, 2392 "offset.idx"); 2393 } 2394 Broadcasted = getBroadcastInstrs(Broadcasted); 2395 // After broadcasting the induction variable we need to make the vector 2396 // consecutive by adding 0, 1, 2, etc. 2397 for (unsigned part = 0; part < UF; ++part) 2398 Entry[part] = getConsecutiveVector(Broadcasted, VF * part, false); 2399 return; 2400 } 2401 case LoopVectorizationLegality::IK_ReverseIntInduction: 2402 case LoopVectorizationLegality::IK_PtrInduction: 2403 case LoopVectorizationLegality::IK_ReversePtrInduction: 2404 // Handle reverse integer and pointer inductions. 2405 Value *StartIdx = ExtendedIdx; 2406 // This is the normalized GEP that starts counting at zero. 2407 Value *NormalizedIdx = Builder.CreateSub(Induction, StartIdx, 2408 "normalized.idx"); 2409 2410 // Handle the reverse integer induction variable case. 2411 if (LoopVectorizationLegality::IK_ReverseIntInduction == II.IK) { 2412 IntegerType *DstTy = cast<IntegerType>(II.StartValue->getType()); 2413 Value *CNI = Builder.CreateSExtOrTrunc(NormalizedIdx, DstTy, 2414 "resize.norm.idx"); 2415 Value *ReverseInd = Builder.CreateSub(II.StartValue, CNI, 2416 "reverse.idx"); 2417 2418 // This is a new value so do not hoist it out. 2419 Value *Broadcasted = getBroadcastInstrs(ReverseInd); 2420 // After broadcasting the induction variable we need to make the 2421 // vector consecutive by adding ... -3, -2, -1, 0. 2422 for (unsigned part = 0; part < UF; ++part) 2423 Entry[part] = getConsecutiveVector(Broadcasted, -(int)VF * part, 2424 true); 2425 return; 2426 } 2427 2428 // Handle the pointer induction variable case. 2429 assert(P->getType()->isPointerTy() && "Unexpected type."); 2430 2431 // Is this a reverse induction ptr or a consecutive induction ptr. 2432 bool Reverse = (LoopVectorizationLegality::IK_ReversePtrInduction == 2433 II.IK); 2434 2435 // This is the vector of results. Notice that we don't generate 2436 // vector geps because scalar geps result in better code. 2437 for (unsigned part = 0; part < UF; ++part) { 2438 if (VF == 1) { 2439 int EltIndex = (part) * (Reverse ? -1 : 1); 2440 Constant *Idx = ConstantInt::get(Induction->getType(), EltIndex); 2441 Value *GlobalIdx; 2442 if (Reverse) 2443 GlobalIdx = Builder.CreateSub(Idx, NormalizedIdx, "gep.ridx"); 2444 else 2445 GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx, "gep.idx"); 2446 2447 Value *SclrGep = Builder.CreateGEP(II.StartValue, GlobalIdx, 2448 "next.gep"); 2449 Entry[part] = SclrGep; 2450 continue; 2451 } 2452 2453 Value *VecVal = UndefValue::get(VectorType::get(P->getType(), VF)); 2454 for (unsigned int i = 0; i < VF; ++i) { 2455 int EltIndex = (i + part * VF) * (Reverse ? -1 : 1); 2456 Constant *Idx = ConstantInt::get(Induction->getType(), EltIndex); 2457 Value *GlobalIdx; 2458 if (!Reverse) 2459 GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx, "gep.idx"); 2460 else 2461 GlobalIdx = Builder.CreateSub(Idx, NormalizedIdx, "gep.ridx"); 2462 2463 Value *SclrGep = Builder.CreateGEP(II.StartValue, GlobalIdx, 2464 "next.gep"); 2465 VecVal = Builder.CreateInsertElement(VecVal, SclrGep, 2466 Builder.getInt32(i), 2467 "insert.gep"); 2468 } 2469 Entry[part] = VecVal; 2470 } 2471 return; 2472 } 2473} 2474 2475void 2476InnerLoopVectorizer::vectorizeBlockInLoop(LoopVectorizationLegality *Legal, 2477 BasicBlock *BB, PhiVector *PV) { 2478 // For each instruction in the old loop. 2479 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 2480 VectorParts &Entry = WidenMap.get(it); 2481 switch (it->getOpcode()) { 2482 case Instruction::Br: 2483 // Nothing to do for PHIs and BR, since we already took care of the 2484 // loop control flow instructions. 2485 continue; 2486 case Instruction::PHI:{ 2487 // Vectorize PHINodes. 2488 widenPHIInstruction(it, Entry, Legal, UF, VF, PV); 2489 continue; 2490 }// End of PHI. 2491 2492 case Instruction::Add: 2493 case Instruction::FAdd: 2494 case Instruction::Sub: 2495 case Instruction::FSub: 2496 case Instruction::Mul: 2497 case Instruction::FMul: 2498 case Instruction::UDiv: 2499 case Instruction::SDiv: 2500 case Instruction::FDiv: 2501 case Instruction::URem: 2502 case Instruction::SRem: 2503 case Instruction::FRem: 2504 case Instruction::Shl: 2505 case Instruction::LShr: 2506 case Instruction::AShr: 2507 case Instruction::And: 2508 case Instruction::Or: 2509 case Instruction::Xor: { 2510 // Just widen binops. 2511 BinaryOperator *BinOp = dyn_cast<BinaryOperator>(it); 2512 setDebugLocFromInst(Builder, BinOp); 2513 VectorParts &A = getVectorValue(it->getOperand(0)); 2514 VectorParts &B = getVectorValue(it->getOperand(1)); 2515 2516 // Use this vector value for all users of the original instruction. 2517 for (unsigned Part = 0; Part < UF; ++Part) { 2518 Value *V = Builder.CreateBinOp(BinOp->getOpcode(), A[Part], B[Part]); 2519 2520 // Update the NSW, NUW and Exact flags. Notice: V can be an Undef. 2521 BinaryOperator *VecOp = dyn_cast<BinaryOperator>(V); 2522 if (VecOp && isa<OverflowingBinaryOperator>(BinOp)) { 2523 VecOp->setHasNoSignedWrap(BinOp->hasNoSignedWrap()); 2524 VecOp->setHasNoUnsignedWrap(BinOp->hasNoUnsignedWrap()); 2525 } 2526 if (VecOp && isa<PossiblyExactOperator>(VecOp)) 2527 VecOp->setIsExact(BinOp->isExact()); 2528 2529 Entry[Part] = V; 2530 } 2531 break; 2532 } 2533 case Instruction::Select: { 2534 // Widen selects. 2535 // If the selector is loop invariant we can create a select 2536 // instruction with a scalar condition. Otherwise, use vector-select. 2537 bool InvariantCond = SE->isLoopInvariant(SE->getSCEV(it->getOperand(0)), 2538 OrigLoop); 2539 setDebugLocFromInst(Builder, it); 2540 2541 // The condition can be loop invariant but still defined inside the 2542 // loop. This means that we can't just use the original 'cond' value. 2543 // We have to take the 'vectorized' value and pick the first lane. 2544 // Instcombine will make this a no-op. 2545 VectorParts &Cond = getVectorValue(it->getOperand(0)); 2546 VectorParts &Op0 = getVectorValue(it->getOperand(1)); 2547 VectorParts &Op1 = getVectorValue(it->getOperand(2)); 2548 2549 Value *ScalarCond = (VF == 1) ? Cond[0] : 2550 Builder.CreateExtractElement(Cond[0], Builder.getInt32(0)); 2551 2552 for (unsigned Part = 0; Part < UF; ++Part) { 2553 Entry[Part] = Builder.CreateSelect( 2554 InvariantCond ? ScalarCond : Cond[Part], 2555 Op0[Part], 2556 Op1[Part]); 2557 } 2558 break; 2559 } 2560 2561 case Instruction::ICmp: 2562 case Instruction::FCmp: { 2563 // Widen compares. Generate vector compares. 2564 bool FCmp = (it->getOpcode() == Instruction::FCmp); 2565 CmpInst *Cmp = dyn_cast<CmpInst>(it); 2566 setDebugLocFromInst(Builder, it); 2567 VectorParts &A = getVectorValue(it->getOperand(0)); 2568 VectorParts &B = getVectorValue(it->getOperand(1)); 2569 for (unsigned Part = 0; Part < UF; ++Part) { 2570 Value *C = 0; 2571 if (FCmp) 2572 C = Builder.CreateFCmp(Cmp->getPredicate(), A[Part], B[Part]); 2573 else 2574 C = Builder.CreateICmp(Cmp->getPredicate(), A[Part], B[Part]); 2575 Entry[Part] = C; 2576 } 2577 break; 2578 } 2579 2580 case Instruction::Store: 2581 case Instruction::Load: 2582 vectorizeMemoryInstruction(it, Legal); 2583 break; 2584 case Instruction::ZExt: 2585 case Instruction::SExt: 2586 case Instruction::FPToUI: 2587 case Instruction::FPToSI: 2588 case Instruction::FPExt: 2589 case Instruction::PtrToInt: 2590 case Instruction::IntToPtr: 2591 case Instruction::SIToFP: 2592 case Instruction::UIToFP: 2593 case Instruction::Trunc: 2594 case Instruction::FPTrunc: 2595 case Instruction::BitCast: { 2596 CastInst *CI = dyn_cast<CastInst>(it); 2597 setDebugLocFromInst(Builder, it); 2598 /// Optimize the special case where the source is the induction 2599 /// variable. Notice that we can only optimize the 'trunc' case 2600 /// because: a. FP conversions lose precision, b. sext/zext may wrap, 2601 /// c. other casts depend on pointer size. 2602 if (CI->getOperand(0) == OldInduction && 2603 it->getOpcode() == Instruction::Trunc) { 2604 Value *ScalarCast = Builder.CreateCast(CI->getOpcode(), Induction, 2605 CI->getType()); 2606 Value *Broadcasted = getBroadcastInstrs(ScalarCast); 2607 for (unsigned Part = 0; Part < UF; ++Part) 2608 Entry[Part] = getConsecutiveVector(Broadcasted, VF * Part, false); 2609 break; 2610 } 2611 /// Vectorize casts. 2612 Type *DestTy = (VF == 1) ? CI->getType() : 2613 VectorType::get(CI->getType(), VF); 2614 2615 VectorParts &A = getVectorValue(it->getOperand(0)); 2616 for (unsigned Part = 0; Part < UF; ++Part) 2617 Entry[Part] = Builder.CreateCast(CI->getOpcode(), A[Part], DestTy); 2618 break; 2619 } 2620 2621 case Instruction::Call: { 2622 // Ignore dbg intrinsics. 2623 if (isa<DbgInfoIntrinsic>(it)) 2624 break; 2625 setDebugLocFromInst(Builder, it); 2626 2627 Module *M = BB->getParent()->getParent(); 2628 CallInst *CI = cast<CallInst>(it); 2629 Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI); 2630 assert(ID && "Not an intrinsic call!"); 2631 switch (ID) { 2632 case Intrinsic::lifetime_end: 2633 case Intrinsic::lifetime_start: 2634 scalarizeInstruction(it); 2635 break; 2636 default: 2637 for (unsigned Part = 0; Part < UF; ++Part) { 2638 SmallVector<Value *, 4> Args; 2639 for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i) { 2640 VectorParts &Arg = getVectorValue(CI->getArgOperand(i)); 2641 Args.push_back(Arg[Part]); 2642 } 2643 Type *Tys[] = {CI->getType()}; 2644 if (VF > 1) 2645 Tys[0] = VectorType::get(CI->getType()->getScalarType(), VF); 2646 2647 Function *F = Intrinsic::getDeclaration(M, ID, Tys); 2648 Entry[Part] = Builder.CreateCall(F, Args); 2649 } 2650 break; 2651 } 2652 break; 2653 } 2654 2655 default: 2656 // All other instructions are unsupported. Scalarize them. 2657 scalarizeInstruction(it); 2658 break; 2659 }// end of switch. 2660 }// end of for_each instr. 2661} 2662 2663void InnerLoopVectorizer::updateAnalysis() { 2664 // Forget the original basic block. 2665 SE->forgetLoop(OrigLoop); 2666 2667 // Update the dominator tree information. 2668 assert(DT->properlyDominates(LoopBypassBlocks.front(), LoopExitBlock) && 2669 "Entry does not dominate exit."); 2670 2671 for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I) 2672 DT->addNewBlock(LoopBypassBlocks[I], LoopBypassBlocks[I-1]); 2673 DT->addNewBlock(LoopVectorPreHeader, LoopBypassBlocks.back()); 2674 DT->addNewBlock(LoopVectorBody, LoopVectorPreHeader); 2675 DT->addNewBlock(LoopMiddleBlock, LoopBypassBlocks.front()); 2676 DT->addNewBlock(LoopScalarPreHeader, LoopMiddleBlock); 2677 DT->changeImmediateDominator(LoopScalarBody, LoopScalarPreHeader); 2678 DT->changeImmediateDominator(LoopExitBlock, LoopMiddleBlock); 2679 2680 DEBUG(DT->verifyAnalysis()); 2681} 2682 2683bool LoopVectorizationLegality::canVectorizeWithIfConvert() { 2684 if (!EnableIfConversion) 2685 return false; 2686 2687 assert(TheLoop->getNumBlocks() > 1 && "Single block loops are vectorizable"); 2688 std::vector<BasicBlock*> &LoopBlocks = TheLoop->getBlocksVector(); 2689 2690 // A list of pointers that we can safely read and write to. 2691 SmallPtrSet<Value *, 8> SafePointes; 2692 2693 // Collect safe addresses. 2694 for (unsigned i = 0, e = LoopBlocks.size(); i < e; ++i) { 2695 BasicBlock *BB = LoopBlocks[i]; 2696 2697 if (blockNeedsPredication(BB)) 2698 continue; 2699 2700 for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I) { 2701 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 2702 SafePointes.insert(LI->getPointerOperand()); 2703 else if (StoreInst *SI = dyn_cast<StoreInst>(I)) 2704 SafePointes.insert(SI->getPointerOperand()); 2705 } 2706 } 2707 2708 // Collect the blocks that need predication. 2709 for (unsigned i = 0, e = LoopBlocks.size(); i < e; ++i) { 2710 BasicBlock *BB = LoopBlocks[i]; 2711 2712 // We don't support switch statements inside loops. 2713 if (!isa<BranchInst>(BB->getTerminator())) 2714 return false; 2715 2716 // We must be able to predicate all blocks that need to be predicated. 2717 if (blockNeedsPredication(BB) && !blockCanBePredicated(BB, SafePointes)) 2718 return false; 2719 } 2720 2721 // We can if-convert this loop. 2722 return true; 2723} 2724 2725bool LoopVectorizationLegality::canVectorize() { 2726 // We must have a loop in canonical form. Loops with indirectbr in them cannot 2727 // be canonicalized. 2728 if (!TheLoop->getLoopPreheader()) 2729 return false; 2730 2731 // We can only vectorize innermost loops. 2732 if (TheLoop->getSubLoopsVector().size()) 2733 return false; 2734 2735 // We must have a single backedge. 2736 if (TheLoop->getNumBackEdges() != 1) 2737 return false; 2738 2739 // We must have a single exiting block. 2740 if (!TheLoop->getExitingBlock()) 2741 return false; 2742 2743 unsigned NumBlocks = TheLoop->getNumBlocks(); 2744 2745 // Check if we can if-convert non single-bb loops. 2746 if (NumBlocks != 1 && !canVectorizeWithIfConvert()) { 2747 DEBUG(dbgs() << "LV: Can't if-convert the loop.\n"); 2748 return false; 2749 } 2750 2751 // We need to have a loop header. 2752 BasicBlock *Latch = TheLoop->getLoopLatch(); 2753 DEBUG(dbgs() << "LV: Found a loop: " << 2754 TheLoop->getHeader()->getName() << "\n"); 2755 2756 // ScalarEvolution needs to be able to find the exit count. 2757 const SCEV *ExitCount = SE->getBackedgeTakenCount(TheLoop); 2758 if (ExitCount == SE->getCouldNotCompute()) { 2759 DEBUG(dbgs() << "LV: SCEV could not compute the loop exit count.\n"); 2760 return false; 2761 } 2762 2763 // Do not loop-vectorize loops with a tiny trip count. 2764 unsigned TC = SE->getSmallConstantTripCount(TheLoop, Latch); 2765 if (TC > 0u && TC < TinyTripCountVectorThreshold) { 2766 DEBUG(dbgs() << "LV: Found a loop with a very small trip count. " << 2767 "This loop is not worth vectorizing.\n"); 2768 return false; 2769 } 2770 2771 // Check if we can vectorize the instructions and CFG in this loop. 2772 if (!canVectorizeInstrs()) { 2773 DEBUG(dbgs() << "LV: Can't vectorize the instructions or CFG\n"); 2774 return false; 2775 } 2776 2777 // Go over each instruction and look at memory deps. 2778 if (!canVectorizeMemory()) { 2779 DEBUG(dbgs() << "LV: Can't vectorize due to memory conflicts\n"); 2780 return false; 2781 } 2782 2783 // Collect all of the variables that remain uniform after vectorization. 2784 collectLoopUniforms(); 2785 2786 DEBUG(dbgs() << "LV: We can vectorize this loop" << 2787 (PtrRtCheck.Need ? " (with a runtime bound check)" : "") 2788 <<"!\n"); 2789 2790 // Okay! We can vectorize. At this point we don't have any other mem analysis 2791 // which may limit our maximum vectorization factor, so just return true with 2792 // no restrictions. 2793 return true; 2794} 2795 2796static Type *convertPointerToIntegerType(DataLayout &DL, Type *Ty) { 2797 if (Ty->isPointerTy()) 2798 return DL.getIntPtrType(Ty); 2799 2800 return Ty; 2801} 2802 2803static Type* getWiderType(DataLayout &DL, Type *Ty0, Type *Ty1) { 2804 Ty0 = convertPointerToIntegerType(DL, Ty0); 2805 Ty1 = convertPointerToIntegerType(DL, Ty1); 2806 if (Ty0->getScalarSizeInBits() > Ty1->getScalarSizeInBits()) 2807 return Ty0; 2808 return Ty1; 2809} 2810 2811/// \brief Check that the instruction has outside loop users and is not an 2812/// identified reduction variable. 2813static bool hasOutsideLoopUser(const Loop *TheLoop, Instruction *Inst, 2814 SmallPtrSet<Value *, 4> &Reductions) { 2815 // Reduction instructions are allowed to have exit users. All other 2816 // instructions must not have external users. 2817 if (!Reductions.count(Inst)) 2818 //Check that all of the users of the loop are inside the BB. 2819 for (Value::use_iterator I = Inst->use_begin(), E = Inst->use_end(); 2820 I != E; ++I) { 2821 Instruction *U = cast<Instruction>(*I); 2822 // This user may be a reduction exit value. 2823 if (!TheLoop->contains(U)) { 2824 DEBUG(dbgs() << "LV: Found an outside user for : "<< *U << "\n"); 2825 return true; 2826 } 2827 } 2828 return false; 2829} 2830 2831bool LoopVectorizationLegality::canVectorizeInstrs() { 2832 BasicBlock *PreHeader = TheLoop->getLoopPreheader(); 2833 BasicBlock *Header = TheLoop->getHeader(); 2834 2835 // Look for the attribute signaling the absence of NaNs. 2836 Function &F = *Header->getParent(); 2837 if (F.hasFnAttribute("no-nans-fp-math")) 2838 HasFunNoNaNAttr = F.getAttributes().getAttribute( 2839 AttributeSet::FunctionIndex, 2840 "no-nans-fp-math").getValueAsString() == "true"; 2841 2842 // For each block in the loop. 2843 for (Loop::block_iterator bb = TheLoop->block_begin(), 2844 be = TheLoop->block_end(); bb != be; ++bb) { 2845 2846 // Scan the instructions in the block and look for hazards. 2847 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e; 2848 ++it) { 2849 2850 if (PHINode *Phi = dyn_cast<PHINode>(it)) { 2851 Type *PhiTy = Phi->getType(); 2852 // Check that this PHI type is allowed. 2853 if (!PhiTy->isIntegerTy() && 2854 !PhiTy->isFloatingPointTy() && 2855 !PhiTy->isPointerTy()) { 2856 DEBUG(dbgs() << "LV: Found an non-int non-pointer PHI.\n"); 2857 return false; 2858 } 2859 2860 // If this PHINode is not in the header block, then we know that we 2861 // can convert it to select during if-conversion. No need to check if 2862 // the PHIs in this block are induction or reduction variables. 2863 if (*bb != Header) { 2864 // Check that this instruction has no outside users or is an 2865 // identified reduction value with an outside user. 2866 if(!hasOutsideLoopUser(TheLoop, it, AllowedExit)) 2867 continue; 2868 return false; 2869 } 2870 2871 // We only allow if-converted PHIs with more than two incoming values. 2872 if (Phi->getNumIncomingValues() != 2) { 2873 DEBUG(dbgs() << "LV: Found an invalid PHI.\n"); 2874 return false; 2875 } 2876 2877 // This is the value coming from the preheader. 2878 Value *StartValue = Phi->getIncomingValueForBlock(PreHeader); 2879 // Check if this is an induction variable. 2880 InductionKind IK = isInductionVariable(Phi); 2881 2882 if (IK_NoInduction != IK) { 2883 // Get the widest type. 2884 if (!WidestIndTy) 2885 WidestIndTy = convertPointerToIntegerType(*DL, PhiTy); 2886 else 2887 WidestIndTy = getWiderType(*DL, PhiTy, WidestIndTy); 2888 2889 // Int inductions are special because we only allow one IV. 2890 if (IK == IK_IntInduction) { 2891 // Use the phi node with the widest type as induction. Use the last 2892 // one if there are multiple (no good reason for doing this other 2893 // than it is expedient). 2894 if (!Induction || PhiTy == WidestIndTy) 2895 Induction = Phi; 2896 } 2897 2898 DEBUG(dbgs() << "LV: Found an induction variable.\n"); 2899 Inductions[Phi] = InductionInfo(StartValue, IK); 2900 2901 // Until we explicitly handle the case of an induction variable with 2902 // an outside loop user we have to give up vectorizing this loop. 2903 if (hasOutsideLoopUser(TheLoop, it, AllowedExit)) 2904 return false; 2905 2906 continue; 2907 } 2908 2909 if (AddReductionVar(Phi, RK_IntegerAdd)) { 2910 DEBUG(dbgs() << "LV: Found an ADD reduction PHI."<< *Phi <<"\n"); 2911 continue; 2912 } 2913 if (AddReductionVar(Phi, RK_IntegerMult)) { 2914 DEBUG(dbgs() << "LV: Found a MUL reduction PHI."<< *Phi <<"\n"); 2915 continue; 2916 } 2917 if (AddReductionVar(Phi, RK_IntegerOr)) { 2918 DEBUG(dbgs() << "LV: Found an OR reduction PHI."<< *Phi <<"\n"); 2919 continue; 2920 } 2921 if (AddReductionVar(Phi, RK_IntegerAnd)) { 2922 DEBUG(dbgs() << "LV: Found an AND reduction PHI."<< *Phi <<"\n"); 2923 continue; 2924 } 2925 if (AddReductionVar(Phi, RK_IntegerXor)) { 2926 DEBUG(dbgs() << "LV: Found a XOR reduction PHI."<< *Phi <<"\n"); 2927 continue; 2928 } 2929 if (AddReductionVar(Phi, RK_IntegerMinMax)) { 2930 DEBUG(dbgs() << "LV: Found a MINMAX reduction PHI."<< *Phi <<"\n"); 2931 continue; 2932 } 2933 if (AddReductionVar(Phi, RK_FloatMult)) { 2934 DEBUG(dbgs() << "LV: Found an FMult reduction PHI."<< *Phi <<"\n"); 2935 continue; 2936 } 2937 if (AddReductionVar(Phi, RK_FloatAdd)) { 2938 DEBUG(dbgs() << "LV: Found an FAdd reduction PHI."<< *Phi <<"\n"); 2939 continue; 2940 } 2941 if (AddReductionVar(Phi, RK_FloatMinMax)) { 2942 DEBUG(dbgs() << "LV: Found an float MINMAX reduction PHI."<< *Phi << 2943 "\n"); 2944 continue; 2945 } 2946 2947 DEBUG(dbgs() << "LV: Found an unidentified PHI."<< *Phi <<"\n"); 2948 return false; 2949 }// end of PHI handling 2950 2951 // We still don't handle functions. However, we can ignore dbg intrinsic 2952 // calls and we do handle certain intrinsic and libm functions. 2953 CallInst *CI = dyn_cast<CallInst>(it); 2954 if (CI && !getIntrinsicIDForCall(CI, TLI) && !isa<DbgInfoIntrinsic>(CI)) { 2955 DEBUG(dbgs() << "LV: Found a call site.\n"); 2956 return false; 2957 } 2958 2959 // Check that the instruction return type is vectorizable. 2960 if (!VectorType::isValidElementType(it->getType()) && 2961 !it->getType()->isVoidTy()) { 2962 DEBUG(dbgs() << "LV: Found unvectorizable type." << "\n"); 2963 return false; 2964 } 2965 2966 // Check that the stored type is vectorizable. 2967 if (StoreInst *ST = dyn_cast<StoreInst>(it)) { 2968 Type *T = ST->getValueOperand()->getType(); 2969 if (!VectorType::isValidElementType(T)) 2970 return false; 2971 } 2972 2973 // Reduction instructions are allowed to have exit users. 2974 // All other instructions must not have external users. 2975 if (hasOutsideLoopUser(TheLoop, it, AllowedExit)) 2976 return false; 2977 2978 } // next instr. 2979 2980 } 2981 2982 if (!Induction) { 2983 DEBUG(dbgs() << "LV: Did not find one integer induction var.\n"); 2984 if (Inductions.empty()) 2985 return false; 2986 } 2987 2988 return true; 2989} 2990 2991void LoopVectorizationLegality::collectLoopUniforms() { 2992 // We now know that the loop is vectorizable! 2993 // Collect variables that will remain uniform after vectorization. 2994 std::vector<Value*> Worklist; 2995 BasicBlock *Latch = TheLoop->getLoopLatch(); 2996 2997 // Start with the conditional branch and walk up the block. 2998 Worklist.push_back(Latch->getTerminator()->getOperand(0)); 2999 3000 while (Worklist.size()) { 3001 Instruction *I = dyn_cast<Instruction>(Worklist.back()); 3002 Worklist.pop_back(); 3003 3004 // Look at instructions inside this loop. 3005 // Stop when reaching PHI nodes. 3006 // TODO: we need to follow values all over the loop, not only in this block. 3007 if (!I || !TheLoop->contains(I) || isa<PHINode>(I)) 3008 continue; 3009 3010 // This is a known uniform. 3011 Uniforms.insert(I); 3012 3013 // Insert all operands. 3014 Worklist.insert(Worklist.end(), I->op_begin(), I->op_end()); 3015 } 3016} 3017 3018namespace { 3019/// \brief Analyses memory accesses in a loop. 3020/// 3021/// Checks whether run time pointer checks are needed and builds sets for data 3022/// dependence checking. 3023class AccessAnalysis { 3024public: 3025 /// \brief Read or write access location. 3026 typedef PointerIntPair<Value *, 1, bool> MemAccessInfo; 3027 typedef SmallPtrSet<MemAccessInfo, 8> MemAccessInfoSet; 3028 3029 /// \brief Set of potential dependent memory accesses. 3030 typedef EquivalenceClasses<MemAccessInfo> DepCandidates; 3031 3032 AccessAnalysis(DataLayout *Dl, DepCandidates &DA) : 3033 DL(Dl), DepCands(DA), AreAllWritesIdentified(true), 3034 AreAllReadsIdentified(true), IsRTCheckNeeded(false) {} 3035 3036 /// \brief Register a load and whether it is only read from. 3037 void addLoad(Value *Ptr, bool IsReadOnly) { 3038 Accesses.insert(MemAccessInfo(Ptr, false)); 3039 if (IsReadOnly) 3040 ReadOnlyPtr.insert(Ptr); 3041 } 3042 3043 /// \brief Register a store. 3044 void addStore(Value *Ptr) { 3045 Accesses.insert(MemAccessInfo(Ptr, true)); 3046 } 3047 3048 /// \brief Check whether we can check the pointers at runtime for 3049 /// non-intersection. 3050 bool canCheckPtrAtRT(LoopVectorizationLegality::RuntimePointerCheck &RtCheck, 3051 unsigned &NumComparisons, ScalarEvolution *SE, 3052 Loop *TheLoop); 3053 3054 /// \brief Goes over all memory accesses, checks whether a RT check is needed 3055 /// and builds sets of dependent accesses. 3056 void buildDependenceSets() { 3057 // Process read-write pointers first. 3058 processMemAccesses(false); 3059 // Next, process read pointers. 3060 processMemAccesses(true); 3061 } 3062 3063 bool isRTCheckNeeded() { return IsRTCheckNeeded; } 3064 3065 bool isDependencyCheckNeeded() { return !CheckDeps.empty(); } 3066 3067 MemAccessInfoSet &getDependenciesToCheck() { return CheckDeps; } 3068 3069private: 3070 typedef SetVector<MemAccessInfo> PtrAccessSet; 3071 typedef DenseMap<Value*, MemAccessInfo> UnderlyingObjToAccessMap; 3072 3073 /// \brief Go over all memory access or only the deferred ones if 3074 /// \p UseDeferred is true and check whether runtime pointer checks are needed 3075 /// and build sets of dependency check candidates. 3076 void processMemAccesses(bool UseDeferred); 3077 3078 /// Set of all accesses. 3079 PtrAccessSet Accesses; 3080 3081 /// Set of access to check after all writes have been processed. 3082 PtrAccessSet DeferredAccesses; 3083 3084 /// Map of pointers to last access encountered. 3085 UnderlyingObjToAccessMap ObjToLastAccess; 3086 3087 /// Set of accesses that need a further dependence check. 3088 MemAccessInfoSet CheckDeps; 3089 3090 /// Set of pointers that are read only. 3091 SmallPtrSet<Value*, 16> ReadOnlyPtr; 3092 3093 /// Set of underlying objects already written to. 3094 SmallPtrSet<Value*, 16> WriteObjects; 3095 3096 DataLayout *DL; 3097 3098 /// Sets of potentially dependent accesses - members of one set share an 3099 /// underlying pointer. The set "CheckDeps" identfies which sets really need a 3100 /// dependence check. 3101 DepCandidates &DepCands; 3102 3103 bool AreAllWritesIdentified; 3104 bool AreAllReadsIdentified; 3105 bool IsRTCheckNeeded; 3106}; 3107 3108} // end anonymous namespace 3109 3110/// \brief Check whether a pointer can participate in a runtime bounds check. 3111static bool hasComputableBounds(ScalarEvolution *SE, Value *Ptr) { 3112 const SCEV *PtrScev = SE->getSCEV(Ptr); 3113 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PtrScev); 3114 if (!AR) 3115 return false; 3116 3117 return AR->isAffine(); 3118} 3119 3120bool AccessAnalysis::canCheckPtrAtRT( 3121 LoopVectorizationLegality::RuntimePointerCheck &RtCheck, 3122 unsigned &NumComparisons, ScalarEvolution *SE, 3123 Loop *TheLoop) { 3124 // Find pointers with computable bounds. We are going to use this information 3125 // to place a runtime bound check. 3126 unsigned NumReadPtrChecks = 0; 3127 unsigned NumWritePtrChecks = 0; 3128 bool CanDoRT = true; 3129 3130 bool IsDepCheckNeeded = isDependencyCheckNeeded(); 3131 // We assign consecutive id to access from different dependence sets. 3132 // Accesses within the same set don't need a runtime check. 3133 unsigned RunningDepId = 1; 3134 DenseMap<Value *, unsigned> DepSetId; 3135 3136 for (PtrAccessSet::iterator AI = Accesses.begin(), AE = Accesses.end(); 3137 AI != AE; ++AI) { 3138 const MemAccessInfo &Access = *AI; 3139 Value *Ptr = Access.getPointer(); 3140 bool IsWrite = Access.getInt(); 3141 3142 // Just add write checks if we have both. 3143 if (!IsWrite && Accesses.count(MemAccessInfo(Ptr, true))) 3144 continue; 3145 3146 if (IsWrite) 3147 ++NumWritePtrChecks; 3148 else 3149 ++NumReadPtrChecks; 3150 3151 if (hasComputableBounds(SE, Ptr)) { 3152 // The id of the dependence set. 3153 unsigned DepId; 3154 3155 if (IsDepCheckNeeded) { 3156 Value *Leader = DepCands.getLeaderValue(Access).getPointer(); 3157 unsigned &LeaderId = DepSetId[Leader]; 3158 if (!LeaderId) 3159 LeaderId = RunningDepId++; 3160 DepId = LeaderId; 3161 } else 3162 // Each access has its own dependence set. 3163 DepId = RunningDepId++; 3164 3165 RtCheck.insert(SE, TheLoop, Ptr, IsWrite, DepId); 3166 3167 DEBUG(dbgs() << "LV: Found a runtime check ptr:" << *Ptr <<"\n"); 3168 } else { 3169 CanDoRT = false; 3170 } 3171 } 3172 3173 if (IsDepCheckNeeded && CanDoRT && RunningDepId == 2) 3174 NumComparisons = 0; // Only one dependence set. 3175 else 3176 NumComparisons = (NumWritePtrChecks * (NumReadPtrChecks + 3177 NumWritePtrChecks - 1)); 3178 return CanDoRT; 3179} 3180 3181static bool isFunctionScopeIdentifiedObject(Value *Ptr) { 3182 return isNoAliasArgument(Ptr) || isNoAliasCall(Ptr) || isa<AllocaInst>(Ptr); 3183} 3184 3185void AccessAnalysis::processMemAccesses(bool UseDeferred) { 3186 // We process the set twice: first we process read-write pointers, last we 3187 // process read-only pointers. This allows us to skip dependence tests for 3188 // read-only pointers. 3189 3190 PtrAccessSet &S = UseDeferred ? DeferredAccesses : Accesses; 3191 for (PtrAccessSet::iterator AI = S.begin(), AE = S.end(); AI != AE; ++AI) { 3192 const MemAccessInfo &Access = *AI; 3193 Value *Ptr = Access.getPointer(); 3194 bool IsWrite = Access.getInt(); 3195 3196 DepCands.insert(Access); 3197 3198 // Memorize read-only pointers for later processing and skip them in the 3199 // first round (they need to be checked after we have seen all write 3200 // pointers). Note: we also mark pointer that are not consecutive as 3201 // "read-only" pointers (so that we check "a[b[i]] +="). Hence, we need the 3202 // second check for "!IsWrite". 3203 bool IsReadOnlyPtr = ReadOnlyPtr.count(Ptr) && !IsWrite; 3204 if (!UseDeferred && IsReadOnlyPtr) { 3205 DeferredAccesses.insert(Access); 3206 continue; 3207 } 3208 3209 bool NeedDepCheck = false; 3210 // Check whether there is the possiblity of dependency because of underlying 3211 // objects being the same. 3212 typedef SmallVector<Value*, 16> ValueVector; 3213 ValueVector TempObjects; 3214 GetUnderlyingObjects(Ptr, TempObjects, DL); 3215 for (ValueVector::iterator UI = TempObjects.begin(), UE = TempObjects.end(); 3216 UI != UE; ++UI) { 3217 Value *UnderlyingObj = *UI; 3218 3219 // If this is a write then it needs to be an identified object. If this a 3220 // read and all writes (so far) are identified function scope objects we 3221 // don't need an identified underlying object but only an Argument (the 3222 // next write is going to invalidate this assumption if it is 3223 // unidentified). 3224 // This is a micro-optimization for the case where all writes are 3225 // identified and we have one argument pointer. 3226 // Otherwise, we do need a runtime check. 3227 if ((IsWrite && !isFunctionScopeIdentifiedObject(UnderlyingObj)) || 3228 (!IsWrite && (!AreAllWritesIdentified || 3229 !isa<Argument>(UnderlyingObj)) && 3230 !isIdentifiedObject(UnderlyingObj))) { 3231 DEBUG(dbgs() << "LV: Found an unidentified " << 3232 (IsWrite ? "write" : "read" ) << " ptr:" << *UnderlyingObj << 3233 "\n"); 3234 IsRTCheckNeeded = (IsRTCheckNeeded || 3235 !isIdentifiedObject(UnderlyingObj) || 3236 !AreAllReadsIdentified); 3237 3238 if (IsWrite) 3239 AreAllWritesIdentified = false; 3240 if (!IsWrite) 3241 AreAllReadsIdentified = false; 3242 } 3243 3244 // If this is a write - check other reads and writes for conflicts. If 3245 // this is a read only check other writes for conflicts (but only if there 3246 // is no other write to the ptr - this is an optimization to catch "a[i] = 3247 // a[i] + " without having to do a dependence check). 3248 if ((IsWrite || IsReadOnlyPtr) && WriteObjects.count(UnderlyingObj)) 3249 NeedDepCheck = true; 3250 3251 if (IsWrite) 3252 WriteObjects.insert(UnderlyingObj); 3253 3254 // Create sets of pointers connected by shared underlying objects. 3255 UnderlyingObjToAccessMap::iterator Prev = 3256 ObjToLastAccess.find(UnderlyingObj); 3257 if (Prev != ObjToLastAccess.end()) 3258 DepCands.unionSets(Access, Prev->second); 3259 3260 ObjToLastAccess[UnderlyingObj] = Access; 3261 } 3262 3263 if (NeedDepCheck) 3264 CheckDeps.insert(Access); 3265 } 3266} 3267 3268namespace { 3269/// \brief Checks memory dependences among accesses to the same underlying 3270/// object to determine whether there vectorization is legal or not (and at 3271/// which vectorization factor). 3272/// 3273/// This class works under the assumption that we already checked that memory 3274/// locations with different underlying pointers are "must-not alias". 3275/// We use the ScalarEvolution framework to symbolically evalutate access 3276/// functions pairs. Since we currently don't restructure the loop we can rely 3277/// on the program order of memory accesses to determine their safety. 3278/// At the moment we will only deem accesses as safe for: 3279/// * A negative constant distance assuming program order. 3280/// 3281/// Safe: tmp = a[i + 1]; OR a[i + 1] = x; 3282/// a[i] = tmp; y = a[i]; 3283/// 3284/// The latter case is safe because later checks guarantuee that there can't 3285/// be a cycle through a phi node (that is, we check that "x" and "y" is not 3286/// the same variable: a header phi can only be an induction or a reduction, a 3287/// reduction can't have a memory sink, an induction can't have a memory 3288/// source). This is important and must not be violated (or we have to 3289/// resort to checking for cycles through memory). 3290/// 3291/// * A positive constant distance assuming program order that is bigger 3292/// than the biggest memory access. 3293/// 3294/// tmp = a[i] OR b[i] = x 3295/// a[i+2] = tmp y = b[i+2]; 3296/// 3297/// Safe distance: 2 x sizeof(a[0]), and 2 x sizeof(b[0]), respectively. 3298/// 3299/// * Zero distances and all accesses have the same size. 3300/// 3301class MemoryDepChecker { 3302public: 3303 typedef PointerIntPair<Value *, 1, bool> MemAccessInfo; 3304 typedef SmallPtrSet<MemAccessInfo, 8> MemAccessInfoSet; 3305 3306 MemoryDepChecker(ScalarEvolution *Se, DataLayout *Dl, const Loop *L) : 3307 SE(Se), DL(Dl), InnermostLoop(L), AccessIdx(0) {} 3308 3309 /// \brief Register the location (instructions are given increasing numbers) 3310 /// of a write access. 3311 void addAccess(StoreInst *SI) { 3312 Value *Ptr = SI->getPointerOperand(); 3313 Accesses[MemAccessInfo(Ptr, true)].push_back(AccessIdx); 3314 InstMap.push_back(SI); 3315 ++AccessIdx; 3316 } 3317 3318 /// \brief Register the location (instructions are given increasing numbers) 3319 /// of a write access. 3320 void addAccess(LoadInst *LI) { 3321 Value *Ptr = LI->getPointerOperand(); 3322 Accesses[MemAccessInfo(Ptr, false)].push_back(AccessIdx); 3323 InstMap.push_back(LI); 3324 ++AccessIdx; 3325 } 3326 3327 /// \brief Check whether the dependencies between the accesses are safe. 3328 /// 3329 /// Only checks sets with elements in \p CheckDeps. 3330 bool areDepsSafe(AccessAnalysis::DepCandidates &AccessSets, 3331 MemAccessInfoSet &CheckDeps); 3332 3333 /// \brief The maximum number of bytes of a vector register we can vectorize 3334 /// the accesses safely with. 3335 unsigned getMaxSafeDepDistBytes() { return MaxSafeDepDistBytes; } 3336 3337private: 3338 ScalarEvolution *SE; 3339 DataLayout *DL; 3340 const Loop *InnermostLoop; 3341 3342 /// \brief Maps access locations (ptr, read/write) to program order. 3343 DenseMap<MemAccessInfo, std::vector<unsigned> > Accesses; 3344 3345 /// \brief Memory access instructions in program order. 3346 SmallVector<Instruction *, 16> InstMap; 3347 3348 /// \brief The program order index to be used for the next instruction. 3349 unsigned AccessIdx; 3350 3351 // We can access this many bytes in parallel safely. 3352 unsigned MaxSafeDepDistBytes; 3353 3354 /// \brief Check whether there is a plausible dependence between the two 3355 /// accesses. 3356 /// 3357 /// Access \p A must happen before \p B in program order. The two indices 3358 /// identify the index into the program order map. 3359 /// 3360 /// This function checks whether there is a plausible dependence (or the 3361 /// absence of such can't be proved) between the two accesses. If there is a 3362 /// plausible dependence but the dependence distance is bigger than one 3363 /// element access it records this distance in \p MaxSafeDepDistBytes (if this 3364 /// distance is smaller than any other distance encountered so far). 3365 /// Otherwise, this function returns true signaling a possible dependence. 3366 bool isDependent(const MemAccessInfo &A, unsigned AIdx, 3367 const MemAccessInfo &B, unsigned BIdx); 3368 3369 /// \brief Check whether the data dependence could prevent store-load 3370 /// forwarding. 3371 bool couldPreventStoreLoadForward(unsigned Distance, unsigned TypeByteSize); 3372}; 3373 3374} // end anonymous namespace 3375 3376static bool isInBoundsGep(Value *Ptr) { 3377 if (GetElementPtrInst *GEP = dyn_cast<GetElementPtrInst>(Ptr)) 3378 return GEP->isInBounds(); 3379 return false; 3380} 3381 3382/// \brief Check whether the access through \p Ptr has a constant stride. 3383static int isStridedPtr(ScalarEvolution *SE, DataLayout *DL, Value *Ptr, 3384 const Loop *Lp) { 3385 const Type *Ty = Ptr->getType(); 3386 assert(Ty->isPointerTy() && "Unexpected non ptr"); 3387 3388 // Make sure that the pointer does not point to aggregate types. 3389 const PointerType *PtrTy = cast<PointerType>(Ty); 3390 if (PtrTy->getElementType()->isAggregateType()) { 3391 DEBUG(dbgs() << "LV: Bad stride - Not a pointer to a scalar type" << *Ptr << 3392 "\n"); 3393 return 0; 3394 } 3395 3396 const SCEV *PtrScev = SE->getSCEV(Ptr); 3397 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PtrScev); 3398 if (!AR) { 3399 DEBUG(dbgs() << "LV: Bad stride - Not an AddRecExpr pointer " 3400 << *Ptr << " SCEV: " << *PtrScev << "\n"); 3401 return 0; 3402 } 3403 3404 // The accesss function must stride over the innermost loop. 3405 if (Lp != AR->getLoop()) { 3406 DEBUG(dbgs() << "LV: Bad stride - Not striding over innermost loop " << 3407 *Ptr << " SCEV: " << *PtrScev << "\n"); 3408 } 3409 3410 // The address calculation must not wrap. Otherwise, a dependence could be 3411 // inverted. 3412 // An inbounds getelementptr that is a AddRec with a unit stride 3413 // cannot wrap per definition. The unit stride requirement is checked later. 3414 // An getelementptr without an inbounds attribute and unit stride would have 3415 // to access the pointer value "0" which is undefined behavior in address 3416 // space 0, therefore we can also vectorize this case. 3417 bool IsInBoundsGEP = isInBoundsGep(Ptr); 3418 bool IsNoWrapAddRec = AR->getNoWrapFlags(SCEV::NoWrapMask); 3419 bool IsInAddressSpaceZero = PtrTy->getAddressSpace() == 0; 3420 if (!IsNoWrapAddRec && !IsInBoundsGEP && !IsInAddressSpaceZero) { 3421 DEBUG(dbgs() << "LV: Bad stride - Pointer may wrap in the address space " 3422 << *Ptr << " SCEV: " << *PtrScev << "\n"); 3423 return 0; 3424 } 3425 3426 // Check the step is constant. 3427 const SCEV *Step = AR->getStepRecurrence(*SE); 3428 3429 // Calculate the pointer stride and check if it is consecutive. 3430 const SCEVConstant *C = dyn_cast<SCEVConstant>(Step); 3431 if (!C) { 3432 DEBUG(dbgs() << "LV: Bad stride - Not a constant strided " << *Ptr << 3433 " SCEV: " << *PtrScev << "\n"); 3434 return 0; 3435 } 3436 3437 int64_t Size = DL->getTypeAllocSize(PtrTy->getElementType()); 3438 const APInt &APStepVal = C->getValue()->getValue(); 3439 3440 // Huge step value - give up. 3441 if (APStepVal.getBitWidth() > 64) 3442 return 0; 3443 3444 int64_t StepVal = APStepVal.getSExtValue(); 3445 3446 // Strided access. 3447 int64_t Stride = StepVal / Size; 3448 int64_t Rem = StepVal % Size; 3449 if (Rem) 3450 return 0; 3451 3452 // If the SCEV could wrap but we have an inbounds gep with a unit stride we 3453 // know we can't "wrap around the address space". In case of address space 3454 // zero we know that this won't happen without triggering undefined behavior. 3455 if (!IsNoWrapAddRec && (IsInBoundsGEP || IsInAddressSpaceZero) && 3456 Stride != 1 && Stride != -1) 3457 return 0; 3458 3459 return Stride; 3460} 3461 3462bool MemoryDepChecker::couldPreventStoreLoadForward(unsigned Distance, 3463 unsigned TypeByteSize) { 3464 // If loads occur at a distance that is not a multiple of a feasible vector 3465 // factor store-load forwarding does not take place. 3466 // Positive dependences might cause troubles because vectorizing them might 3467 // prevent store-load forwarding making vectorized code run a lot slower. 3468 // a[i] = a[i-3] ^ a[i-8]; 3469 // The stores to a[i:i+1] don't align with the stores to a[i-3:i-2] and 3470 // hence on your typical architecture store-load forwarding does not take 3471 // place. Vectorizing in such cases does not make sense. 3472 // Store-load forwarding distance. 3473 const unsigned NumCyclesForStoreLoadThroughMemory = 8*TypeByteSize; 3474 // Maximum vector factor. 3475 unsigned MaxVFWithoutSLForwardIssues = MaxVectorWidth*TypeByteSize; 3476 if(MaxSafeDepDistBytes < MaxVFWithoutSLForwardIssues) 3477 MaxVFWithoutSLForwardIssues = MaxSafeDepDistBytes; 3478 3479 for (unsigned vf = 2*TypeByteSize; vf <= MaxVFWithoutSLForwardIssues; 3480 vf *= 2) { 3481 if (Distance % vf && Distance / vf < NumCyclesForStoreLoadThroughMemory) { 3482 MaxVFWithoutSLForwardIssues = (vf >>=1); 3483 break; 3484 } 3485 } 3486 3487 if (MaxVFWithoutSLForwardIssues< 2*TypeByteSize) { 3488 DEBUG(dbgs() << "LV: Distance " << Distance << 3489 " that could cause a store-load forwarding conflict\n"); 3490 return true; 3491 } 3492 3493 if (MaxVFWithoutSLForwardIssues < MaxSafeDepDistBytes && 3494 MaxVFWithoutSLForwardIssues != MaxVectorWidth*TypeByteSize) 3495 MaxSafeDepDistBytes = MaxVFWithoutSLForwardIssues; 3496 return false; 3497} 3498 3499bool MemoryDepChecker::isDependent(const MemAccessInfo &A, unsigned AIdx, 3500 const MemAccessInfo &B, unsigned BIdx) { 3501 assert (AIdx < BIdx && "Must pass arguments in program order"); 3502 3503 Value *APtr = A.getPointer(); 3504 Value *BPtr = B.getPointer(); 3505 bool AIsWrite = A.getInt(); 3506 bool BIsWrite = B.getInt(); 3507 3508 // Two reads are independent. 3509 if (!AIsWrite && !BIsWrite) 3510 return false; 3511 3512 const SCEV *AScev = SE->getSCEV(APtr); 3513 const SCEV *BScev = SE->getSCEV(BPtr); 3514 3515 int StrideAPtr = isStridedPtr(SE, DL, APtr, InnermostLoop); 3516 int StrideBPtr = isStridedPtr(SE, DL, BPtr, InnermostLoop); 3517 3518 const SCEV *Src = AScev; 3519 const SCEV *Sink = BScev; 3520 3521 // If the induction step is negative we have to invert source and sink of the 3522 // dependence. 3523 if (StrideAPtr < 0) { 3524 //Src = BScev; 3525 //Sink = AScev; 3526 std::swap(APtr, BPtr); 3527 std::swap(Src, Sink); 3528 std::swap(AIsWrite, BIsWrite); 3529 std::swap(AIdx, BIdx); 3530 std::swap(StrideAPtr, StrideBPtr); 3531 } 3532 3533 const SCEV *Dist = SE->getMinusSCEV(Sink, Src); 3534 3535 DEBUG(dbgs() << "LV: Src Scev: " << *Src << "Sink Scev: " << *Sink 3536 << "(Induction step: " << StrideAPtr << ")\n"); 3537 DEBUG(dbgs() << "LV: Distance for " << *InstMap[AIdx] << " to " 3538 << *InstMap[BIdx] << ": " << *Dist << "\n"); 3539 3540 // Need consecutive accesses. We don't want to vectorize 3541 // "A[B[i]] += ..." and similar code or pointer arithmetic that could wrap in 3542 // the address space. 3543 if (!StrideAPtr || !StrideBPtr || StrideAPtr != StrideBPtr){ 3544 DEBUG(dbgs() << "Non-consecutive pointer access\n"); 3545 return true; 3546 } 3547 3548 const SCEVConstant *C = dyn_cast<SCEVConstant>(Dist); 3549 if (!C) { 3550 DEBUG(dbgs() << "LV: Dependence because of non constant distance\n"); 3551 return true; 3552 } 3553 3554 Type *ATy = APtr->getType()->getPointerElementType(); 3555 Type *BTy = BPtr->getType()->getPointerElementType(); 3556 unsigned TypeByteSize = DL->getTypeAllocSize(ATy); 3557 3558 // Negative distances are not plausible dependencies. 3559 const APInt &Val = C->getValue()->getValue(); 3560 if (Val.isNegative()) { 3561 bool IsTrueDataDependence = (AIsWrite && !BIsWrite); 3562 if (IsTrueDataDependence && 3563 (couldPreventStoreLoadForward(Val.abs().getZExtValue(), TypeByteSize) || 3564 ATy != BTy)) 3565 return true; 3566 3567 DEBUG(dbgs() << "LV: Dependence is negative: NoDep\n"); 3568 return false; 3569 } 3570 3571 // Write to the same location with the same size. 3572 // Could be improved to assert type sizes are the same (i32 == float, etc). 3573 if (Val == 0) { 3574 if (ATy == BTy) 3575 return false; 3576 DEBUG(dbgs() << "LV: Zero dependence difference but different types"); 3577 return true; 3578 } 3579 3580 assert(Val.isStrictlyPositive() && "Expect a positive value"); 3581 3582 // Positive distance bigger than max vectorization factor. 3583 if (ATy != BTy) { 3584 DEBUG(dbgs() << 3585 "LV: ReadWrite-Write positive dependency with different types"); 3586 return false; 3587 } 3588 3589 unsigned Distance = (unsigned) Val.getZExtValue(); 3590 3591 // Bail out early if passed-in parameters make vectorization not feasible. 3592 unsigned ForcedFactor = VectorizationFactor ? VectorizationFactor : 1; 3593 unsigned ForcedUnroll = VectorizationUnroll ? VectorizationUnroll : 1; 3594 3595 // The distance must be bigger than the size needed for a vectorized version 3596 // of the operation and the size of the vectorized operation must not be 3597 // bigger than the currrent maximum size. 3598 if (Distance < 2*TypeByteSize || 3599 2*TypeByteSize > MaxSafeDepDistBytes || 3600 Distance < TypeByteSize * ForcedUnroll * ForcedFactor) { 3601 DEBUG(dbgs() << "LV: Failure because of Positive distance " 3602 << Val.getSExtValue() << "\n"); 3603 return true; 3604 } 3605 3606 MaxSafeDepDistBytes = Distance < MaxSafeDepDistBytes ? 3607 Distance : MaxSafeDepDistBytes; 3608 3609 bool IsTrueDataDependence = (!AIsWrite && BIsWrite); 3610 if (IsTrueDataDependence && 3611 couldPreventStoreLoadForward(Distance, TypeByteSize)) 3612 return true; 3613 3614 DEBUG(dbgs() << "LV: Positive distance " << Val.getSExtValue() << 3615 " with max VF=" << MaxSafeDepDistBytes/TypeByteSize << "\n"); 3616 3617 return false; 3618} 3619 3620bool 3621MemoryDepChecker::areDepsSafe(AccessAnalysis::DepCandidates &AccessSets, 3622 MemAccessInfoSet &CheckDeps) { 3623 3624 MaxSafeDepDistBytes = -1U; 3625 while (!CheckDeps.empty()) { 3626 MemAccessInfo CurAccess = *CheckDeps.begin(); 3627 3628 // Get the relevant memory access set. 3629 EquivalenceClasses<MemAccessInfo>::iterator I = 3630 AccessSets.findValue(AccessSets.getLeaderValue(CurAccess)); 3631 3632 // Check accesses within this set. 3633 EquivalenceClasses<MemAccessInfo>::member_iterator AI, AE; 3634 AI = AccessSets.member_begin(I), AE = AccessSets.member_end(); 3635 3636 // Check every access pair. 3637 while (AI != AE) { 3638 CheckDeps.erase(*AI); 3639 EquivalenceClasses<MemAccessInfo>::member_iterator OI = llvm::next(AI); 3640 while (OI != AE) { 3641 // Check every accessing instruction pair in program order. 3642 for (std::vector<unsigned>::iterator I1 = Accesses[*AI].begin(), 3643 I1E = Accesses[*AI].end(); I1 != I1E; ++I1) 3644 for (std::vector<unsigned>::iterator I2 = Accesses[*OI].begin(), 3645 I2E = Accesses[*OI].end(); I2 != I2E; ++I2) { 3646 if (*I1 < *I2 && isDependent(*AI, *I1, *OI, *I2)) 3647 return false; 3648 if (*I2 < *I1 && isDependent(*OI, *I2, *AI, *I1)) 3649 return false; 3650 } 3651 ++OI; 3652 } 3653 AI++; 3654 } 3655 } 3656 return true; 3657} 3658 3659bool LoopVectorizationLegality::canVectorizeMemory() { 3660 3661 typedef SmallVector<Value*, 16> ValueVector; 3662 typedef SmallPtrSet<Value*, 16> ValueSet; 3663 3664 // Holds the Load and Store *instructions*. 3665 ValueVector Loads; 3666 ValueVector Stores; 3667 3668 // Holds all the different accesses in the loop. 3669 unsigned NumReads = 0; 3670 unsigned NumReadWrites = 0; 3671 3672 PtrRtCheck.Pointers.clear(); 3673 PtrRtCheck.Need = false; 3674 3675 const bool IsAnnotatedParallel = TheLoop->isAnnotatedParallel(); 3676 MemoryDepChecker DepChecker(SE, DL, TheLoop); 3677 3678 // For each block. 3679 for (Loop::block_iterator bb = TheLoop->block_begin(), 3680 be = TheLoop->block_end(); bb != be; ++bb) { 3681 3682 // Scan the BB and collect legal loads and stores. 3683 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e; 3684 ++it) { 3685 3686 // If this is a load, save it. If this instruction can read from memory 3687 // but is not a load, then we quit. Notice that we don't handle function 3688 // calls that read or write. 3689 if (it->mayReadFromMemory()) { 3690 // Many math library functions read the rounding mode. We will only 3691 // vectorize a loop if it contains known function calls that don't set 3692 // the flag. Therefore, it is safe to ignore this read from memory. 3693 CallInst *Call = dyn_cast<CallInst>(it); 3694 if (Call && getIntrinsicIDForCall(Call, TLI)) 3695 continue; 3696 3697 LoadInst *Ld = dyn_cast<LoadInst>(it); 3698 if (!Ld) return false; 3699 if (!Ld->isSimple() && !IsAnnotatedParallel) { 3700 DEBUG(dbgs() << "LV: Found a non-simple load.\n"); 3701 return false; 3702 } 3703 Loads.push_back(Ld); 3704 DepChecker.addAccess(Ld); 3705 continue; 3706 } 3707 3708 // Save 'store' instructions. Abort if other instructions write to memory. 3709 if (it->mayWriteToMemory()) { 3710 StoreInst *St = dyn_cast<StoreInst>(it); 3711 if (!St) return false; 3712 if (!St->isSimple() && !IsAnnotatedParallel) { 3713 DEBUG(dbgs() << "LV: Found a non-simple store.\n"); 3714 return false; 3715 } 3716 Stores.push_back(St); 3717 DepChecker.addAccess(St); 3718 } 3719 } // next instr. 3720 } // next block. 3721 3722 // Now we have two lists that hold the loads and the stores. 3723 // Next, we find the pointers that they use. 3724 3725 // Check if we see any stores. If there are no stores, then we don't 3726 // care if the pointers are *restrict*. 3727 if (!Stores.size()) { 3728 DEBUG(dbgs() << "LV: Found a read-only loop!\n"); 3729 return true; 3730 } 3731 3732 AccessAnalysis::DepCandidates DependentAccesses; 3733 AccessAnalysis Accesses(DL, DependentAccesses); 3734 3735 // Holds the analyzed pointers. We don't want to call GetUnderlyingObjects 3736 // multiple times on the same object. If the ptr is accessed twice, once 3737 // for read and once for write, it will only appear once (on the write 3738 // list). This is okay, since we are going to check for conflicts between 3739 // writes and between reads and writes, but not between reads and reads. 3740 ValueSet Seen; 3741 3742 ValueVector::iterator I, IE; 3743 for (I = Stores.begin(), IE = Stores.end(); I != IE; ++I) { 3744 StoreInst *ST = cast<StoreInst>(*I); 3745 Value* Ptr = ST->getPointerOperand(); 3746 3747 if (isUniform(Ptr)) { 3748 DEBUG(dbgs() << "LV: We don't allow storing to uniform addresses\n"); 3749 return false; 3750 } 3751 3752 // If we did *not* see this pointer before, insert it to the read-write 3753 // list. At this phase it is only a 'write' list. 3754 if (Seen.insert(Ptr)) { 3755 ++NumReadWrites; 3756 Accesses.addStore(Ptr); 3757 } 3758 } 3759 3760 if (IsAnnotatedParallel) { 3761 DEBUG(dbgs() 3762 << "LV: A loop annotated parallel, ignore memory dependency " 3763 << "checks.\n"); 3764 return true; 3765 } 3766 3767 SmallPtrSet<Value *, 16> ReadOnlyPtr; 3768 for (I = Loads.begin(), IE = Loads.end(); I != IE; ++I) { 3769 LoadInst *LD = cast<LoadInst>(*I); 3770 Value* Ptr = LD->getPointerOperand(); 3771 // If we did *not* see this pointer before, insert it to the 3772 // read list. If we *did* see it before, then it is already in 3773 // the read-write list. This allows us to vectorize expressions 3774 // such as A[i] += x; Because the address of A[i] is a read-write 3775 // pointer. This only works if the index of A[i] is consecutive. 3776 // If the address of i is unknown (for example A[B[i]]) then we may 3777 // read a few words, modify, and write a few words, and some of the 3778 // words may be written to the same address. 3779 bool IsReadOnlyPtr = false; 3780 if (Seen.insert(Ptr) || !isStridedPtr(SE, DL, Ptr, TheLoop)) { 3781 ++NumReads; 3782 IsReadOnlyPtr = true; 3783 } 3784 Accesses.addLoad(Ptr, IsReadOnlyPtr); 3785 } 3786 3787 // If we write (or read-write) to a single destination and there are no 3788 // other reads in this loop then is it safe to vectorize. 3789 if (NumReadWrites == 1 && NumReads == 0) { 3790 DEBUG(dbgs() << "LV: Found a write-only loop!\n"); 3791 return true; 3792 } 3793 3794 // Build dependence sets and check whether we need a runtime pointer bounds 3795 // check. 3796 Accesses.buildDependenceSets(); 3797 bool NeedRTCheck = Accesses.isRTCheckNeeded(); 3798 3799 // Find pointers with computable bounds. We are going to use this information 3800 // to place a runtime bound check. 3801 unsigned NumComparisons = 0; 3802 bool CanDoRT = false; 3803 if (NeedRTCheck) 3804 CanDoRT = Accesses.canCheckPtrAtRT(PtrRtCheck, NumComparisons, SE, TheLoop); 3805 3806 3807 DEBUG(dbgs() << "LV: We need to do " << NumComparisons << 3808 " pointer comparisons.\n"); 3809 3810 // If we only have one set of dependences to check pointers among we don't 3811 // need a runtime check. 3812 if (NumComparisons == 0 && NeedRTCheck) 3813 NeedRTCheck = false; 3814 3815 // Check that we did not collect too many pointers or found a unsizeable 3816 // pointer. 3817 if (!CanDoRT || NumComparisons > RuntimeMemoryCheckThreshold) { 3818 PtrRtCheck.reset(); 3819 CanDoRT = false; 3820 } 3821 3822 if (CanDoRT) { 3823 DEBUG(dbgs() << "LV: We can perform a memory runtime check if needed.\n"); 3824 } 3825 3826 if (NeedRTCheck && !CanDoRT) { 3827 DEBUG(dbgs() << "LV: We can't vectorize because we can't find " << 3828 "the array bounds.\n"); 3829 PtrRtCheck.reset(); 3830 return false; 3831 } 3832 3833 PtrRtCheck.Need = NeedRTCheck; 3834 3835 bool CanVecMem = true; 3836 if (Accesses.isDependencyCheckNeeded()) { 3837 DEBUG(dbgs() << "LV: Checking memory dependencies\n"); 3838 CanVecMem = DepChecker.areDepsSafe(DependentAccesses, 3839 Accesses.getDependenciesToCheck()); 3840 MaxSafeDepDistBytes = DepChecker.getMaxSafeDepDistBytes(); 3841 } 3842 3843 DEBUG(dbgs() << "LV: We "<< (NeedRTCheck ? "" : "don't") << 3844 " need a runtime memory check.\n"); 3845 3846 return CanVecMem; 3847} 3848 3849static bool hasMultipleUsesOf(Instruction *I, 3850 SmallPtrSet<Instruction *, 8> &Insts) { 3851 unsigned NumUses = 0; 3852 for(User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E; ++Use) { 3853 if (Insts.count(dyn_cast<Instruction>(*Use))) 3854 ++NumUses; 3855 if (NumUses > 1) 3856 return true; 3857 } 3858 3859 return false; 3860} 3861 3862static bool areAllUsesIn(Instruction *I, SmallPtrSet<Instruction *, 8> &Set) { 3863 for(User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E; ++Use) 3864 if (!Set.count(dyn_cast<Instruction>(*Use))) 3865 return false; 3866 return true; 3867} 3868 3869bool LoopVectorizationLegality::AddReductionVar(PHINode *Phi, 3870 ReductionKind Kind) { 3871 if (Phi->getNumIncomingValues() != 2) 3872 return false; 3873 3874 // Reduction variables are only found in the loop header block. 3875 if (Phi->getParent() != TheLoop->getHeader()) 3876 return false; 3877 3878 // Obtain the reduction start value from the value that comes from the loop 3879 // preheader. 3880 Value *RdxStart = Phi->getIncomingValueForBlock(TheLoop->getLoopPreheader()); 3881 3882 // ExitInstruction is the single value which is used outside the loop. 3883 // We only allow for a single reduction value to be used outside the loop. 3884 // This includes users of the reduction, variables (which form a cycle 3885 // which ends in the phi node). 3886 Instruction *ExitInstruction = 0; 3887 // Indicates that we found a reduction operation in our scan. 3888 bool FoundReduxOp = false; 3889 3890 // We start with the PHI node and scan for all of the users of this 3891 // instruction. All users must be instructions that can be used as reduction 3892 // variables (such as ADD). We must have a single out-of-block user. The cycle 3893 // must include the original PHI. 3894 bool FoundStartPHI = false; 3895 3896 // To recognize min/max patterns formed by a icmp select sequence, we store 3897 // the number of instruction we saw from the recognized min/max pattern, 3898 // to make sure we only see exactly the two instructions. 3899 unsigned NumCmpSelectPatternInst = 0; 3900 ReductionInstDesc ReduxDesc(false, 0); 3901 3902 SmallPtrSet<Instruction *, 8> VisitedInsts; 3903 SmallVector<Instruction *, 8> Worklist; 3904 Worklist.push_back(Phi); 3905 VisitedInsts.insert(Phi); 3906 3907 // A value in the reduction can be used: 3908 // - By the reduction: 3909 // - Reduction operation: 3910 // - One use of reduction value (safe). 3911 // - Multiple use of reduction value (not safe). 3912 // - PHI: 3913 // - All uses of the PHI must be the reduction (safe). 3914 // - Otherwise, not safe. 3915 // - By one instruction outside of the loop (safe). 3916 // - By further instructions outside of the loop (not safe). 3917 // - By an instruction that is not part of the reduction (not safe). 3918 // This is either: 3919 // * An instruction type other than PHI or the reduction operation. 3920 // * A PHI in the header other than the initial PHI. 3921 while (!Worklist.empty()) { 3922 Instruction *Cur = Worklist.back(); 3923 Worklist.pop_back(); 3924 3925 // No Users. 3926 // If the instruction has no users then this is a broken chain and can't be 3927 // a reduction variable. 3928 if (Cur->use_empty()) 3929 return false; 3930 3931 bool IsAPhi = isa<PHINode>(Cur); 3932 3933 // A header PHI use other than the original PHI. 3934 if (Cur != Phi && IsAPhi && Cur->getParent() == Phi->getParent()) 3935 return false; 3936 3937 // Reductions of instructions such as Div, and Sub is only possible if the 3938 // LHS is the reduction variable. 3939 if (!Cur->isCommutative() && !IsAPhi && !isa<SelectInst>(Cur) && 3940 !isa<ICmpInst>(Cur) && !isa<FCmpInst>(Cur) && 3941 !VisitedInsts.count(dyn_cast<Instruction>(Cur->getOperand(0)))) 3942 return false; 3943 3944 // Any reduction instruction must be of one of the allowed kinds. 3945 ReduxDesc = isReductionInstr(Cur, Kind, ReduxDesc); 3946 if (!ReduxDesc.IsReduction) 3947 return false; 3948 3949 // A reduction operation must only have one use of the reduction value. 3950 if (!IsAPhi && Kind != RK_IntegerMinMax && Kind != RK_FloatMinMax && 3951 hasMultipleUsesOf(Cur, VisitedInsts)) 3952 return false; 3953 3954 // All inputs to a PHI node must be a reduction value. 3955 if(IsAPhi && Cur != Phi && !areAllUsesIn(Cur, VisitedInsts)) 3956 return false; 3957 3958 if (Kind == RK_IntegerMinMax && (isa<ICmpInst>(Cur) || 3959 isa<SelectInst>(Cur))) 3960 ++NumCmpSelectPatternInst; 3961 if (Kind == RK_FloatMinMax && (isa<FCmpInst>(Cur) || 3962 isa<SelectInst>(Cur))) 3963 ++NumCmpSelectPatternInst; 3964 3965 // Check whether we found a reduction operator. 3966 FoundReduxOp |= !IsAPhi; 3967 3968 // Process users of current instruction. Push non PHI nodes after PHI nodes 3969 // onto the stack. This way we are going to have seen all inputs to PHI 3970 // nodes once we get to them. 3971 SmallVector<Instruction *, 8> NonPHIs; 3972 SmallVector<Instruction *, 8> PHIs; 3973 for (Value::use_iterator UI = Cur->use_begin(), E = Cur->use_end(); UI != E; 3974 ++UI) { 3975 Instruction *Usr = cast<Instruction>(*UI); 3976 3977 // Check if we found the exit user. 3978 BasicBlock *Parent = Usr->getParent(); 3979 if (!TheLoop->contains(Parent)) { 3980 // Exit if you find multiple outside users or if the header phi node is 3981 // being used. In this case the user uses the value of the previous 3982 // iteration, in which case we would loose "VF-1" iterations of the 3983 // reduction operation if we vectorize. 3984 if (ExitInstruction != 0 || Cur == Phi) 3985 return false; 3986 3987 ExitInstruction = Cur; 3988 continue; 3989 } 3990 3991 // Process instructions only once (termination). 3992 if (VisitedInsts.insert(Usr)) { 3993 if (isa<PHINode>(Usr)) 3994 PHIs.push_back(Usr); 3995 else 3996 NonPHIs.push_back(Usr); 3997 } 3998 // Remember that we completed the cycle. 3999 if (Usr == Phi) 4000 FoundStartPHI = true; 4001 } 4002 Worklist.append(PHIs.begin(), PHIs.end()); 4003 Worklist.append(NonPHIs.begin(), NonPHIs.end()); 4004 } 4005 4006 // This means we have seen one but not the other instruction of the 4007 // pattern or more than just a select and cmp. 4008 if ((Kind == RK_IntegerMinMax || Kind == RK_FloatMinMax) && 4009 NumCmpSelectPatternInst != 2) 4010 return false; 4011 4012 if (!FoundStartPHI || !FoundReduxOp || !ExitInstruction) 4013 return false; 4014 4015 // We found a reduction var if we have reached the original phi node and we 4016 // only have a single instruction with out-of-loop users. 4017 4018 // This instruction is allowed to have out-of-loop users. 4019 AllowedExit.insert(ExitInstruction); 4020 4021 // Save the description of this reduction variable. 4022 ReductionDescriptor RD(RdxStart, ExitInstruction, Kind, 4023 ReduxDesc.MinMaxKind); 4024 Reductions[Phi] = RD; 4025 // We've ended the cycle. This is a reduction variable if we have an 4026 // outside user and it has a binary op. 4027 4028 return true; 4029} 4030 4031/// Returns true if the instruction is a Select(ICmp(X, Y), X, Y) instruction 4032/// pattern corresponding to a min(X, Y) or max(X, Y). 4033LoopVectorizationLegality::ReductionInstDesc 4034LoopVectorizationLegality::isMinMaxSelectCmpPattern(Instruction *I, 4035 ReductionInstDesc &Prev) { 4036 4037 assert((isa<ICmpInst>(I) || isa<FCmpInst>(I) || isa<SelectInst>(I)) && 4038 "Expect a select instruction"); 4039 Instruction *Cmp = 0; 4040 SelectInst *Select = 0; 4041 4042 // We must handle the select(cmp()) as a single instruction. Advance to the 4043 // select. 4044 if ((Cmp = dyn_cast<ICmpInst>(I)) || (Cmp = dyn_cast<FCmpInst>(I))) { 4045 if (!Cmp->hasOneUse() || !(Select = dyn_cast<SelectInst>(*I->use_begin()))) 4046 return ReductionInstDesc(false, I); 4047 return ReductionInstDesc(Select, Prev.MinMaxKind); 4048 } 4049 4050 // Only handle single use cases for now. 4051 if (!(Select = dyn_cast<SelectInst>(I))) 4052 return ReductionInstDesc(false, I); 4053 if (!(Cmp = dyn_cast<ICmpInst>(I->getOperand(0))) && 4054 !(Cmp = dyn_cast<FCmpInst>(I->getOperand(0)))) 4055 return ReductionInstDesc(false, I); 4056 if (!Cmp->hasOneUse()) 4057 return ReductionInstDesc(false, I); 4058 4059 Value *CmpLeft; 4060 Value *CmpRight; 4061 4062 // Look for a min/max pattern. 4063 if (m_UMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 4064 return ReductionInstDesc(Select, MRK_UIntMin); 4065 else if (m_UMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 4066 return ReductionInstDesc(Select, MRK_UIntMax); 4067 else if (m_SMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 4068 return ReductionInstDesc(Select, MRK_SIntMax); 4069 else if (m_SMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 4070 return ReductionInstDesc(Select, MRK_SIntMin); 4071 else if (m_OrdFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 4072 return ReductionInstDesc(Select, MRK_FloatMin); 4073 else if (m_OrdFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 4074 return ReductionInstDesc(Select, MRK_FloatMax); 4075 else if (m_UnordFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 4076 return ReductionInstDesc(Select, MRK_FloatMin); 4077 else if (m_UnordFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 4078 return ReductionInstDesc(Select, MRK_FloatMax); 4079 4080 return ReductionInstDesc(false, I); 4081} 4082 4083LoopVectorizationLegality::ReductionInstDesc 4084LoopVectorizationLegality::isReductionInstr(Instruction *I, 4085 ReductionKind Kind, 4086 ReductionInstDesc &Prev) { 4087 bool FP = I->getType()->isFloatingPointTy(); 4088 bool FastMath = (FP && I->isCommutative() && I->isAssociative()); 4089 switch (I->getOpcode()) { 4090 default: 4091 return ReductionInstDesc(false, I); 4092 case Instruction::PHI: 4093 if (FP && (Kind != RK_FloatMult && Kind != RK_FloatAdd && 4094 Kind != RK_FloatMinMax)) 4095 return ReductionInstDesc(false, I); 4096 return ReductionInstDesc(I, Prev.MinMaxKind); 4097 case Instruction::Sub: 4098 case Instruction::Add: 4099 return ReductionInstDesc(Kind == RK_IntegerAdd, I); 4100 case Instruction::Mul: 4101 return ReductionInstDesc(Kind == RK_IntegerMult, I); 4102 case Instruction::And: 4103 return ReductionInstDesc(Kind == RK_IntegerAnd, I); 4104 case Instruction::Or: 4105 return ReductionInstDesc(Kind == RK_IntegerOr, I); 4106 case Instruction::Xor: 4107 return ReductionInstDesc(Kind == RK_IntegerXor, I); 4108 case Instruction::FMul: 4109 return ReductionInstDesc(Kind == RK_FloatMult && FastMath, I); 4110 case Instruction::FAdd: 4111 return ReductionInstDesc(Kind == RK_FloatAdd && FastMath, I); 4112 case Instruction::FCmp: 4113 case Instruction::ICmp: 4114 case Instruction::Select: 4115 if (Kind != RK_IntegerMinMax && 4116 (!HasFunNoNaNAttr || Kind != RK_FloatMinMax)) 4117 return ReductionInstDesc(false, I); 4118 return isMinMaxSelectCmpPattern(I, Prev); 4119 } 4120} 4121 4122LoopVectorizationLegality::InductionKind 4123LoopVectorizationLegality::isInductionVariable(PHINode *Phi) { 4124 Type *PhiTy = Phi->getType(); 4125 // We only handle integer and pointer inductions variables. 4126 if (!PhiTy->isIntegerTy() && !PhiTy->isPointerTy()) 4127 return IK_NoInduction; 4128 4129 // Check that the PHI is consecutive. 4130 const SCEV *PhiScev = SE->getSCEV(Phi); 4131 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PhiScev); 4132 if (!AR) { 4133 DEBUG(dbgs() << "LV: PHI is not a poly recurrence.\n"); 4134 return IK_NoInduction; 4135 } 4136 const SCEV *Step = AR->getStepRecurrence(*SE); 4137 4138 // Integer inductions need to have a stride of one. 4139 if (PhiTy->isIntegerTy()) { 4140 if (Step->isOne()) 4141 return IK_IntInduction; 4142 if (Step->isAllOnesValue()) 4143 return IK_ReverseIntInduction; 4144 return IK_NoInduction; 4145 } 4146 4147 // Calculate the pointer stride and check if it is consecutive. 4148 const SCEVConstant *C = dyn_cast<SCEVConstant>(Step); 4149 if (!C) 4150 return IK_NoInduction; 4151 4152 assert(PhiTy->isPointerTy() && "The PHI must be a pointer"); 4153 uint64_t Size = DL->getTypeAllocSize(PhiTy->getPointerElementType()); 4154 if (C->getValue()->equalsInt(Size)) 4155 return IK_PtrInduction; 4156 else if (C->getValue()->equalsInt(0 - Size)) 4157 return IK_ReversePtrInduction; 4158 4159 return IK_NoInduction; 4160} 4161 4162bool LoopVectorizationLegality::isInductionVariable(const Value *V) { 4163 Value *In0 = const_cast<Value*>(V); 4164 PHINode *PN = dyn_cast_or_null<PHINode>(In0); 4165 if (!PN) 4166 return false; 4167 4168 return Inductions.count(PN); 4169} 4170 4171bool LoopVectorizationLegality::blockNeedsPredication(BasicBlock *BB) { 4172 assert(TheLoop->contains(BB) && "Unknown block used"); 4173 4174 // Blocks that do not dominate the latch need predication. 4175 BasicBlock* Latch = TheLoop->getLoopLatch(); 4176 return !DT->dominates(BB, Latch); 4177} 4178 4179bool LoopVectorizationLegality::blockCanBePredicated(BasicBlock *BB, 4180 SmallPtrSet<Value *, 8>& SafePtrs) { 4181 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 4182 // We might be able to hoist the load. 4183 if (it->mayReadFromMemory()) { 4184 LoadInst *LI = dyn_cast<LoadInst>(it); 4185 if (!LI || !SafePtrs.count(LI->getPointerOperand())) 4186 return false; 4187 } 4188 4189 // We don't predicate stores at the moment. 4190 if (it->mayWriteToMemory() || it->mayThrow()) 4191 return false; 4192 4193 // The instructions below can trap. 4194 switch (it->getOpcode()) { 4195 default: continue; 4196 case Instruction::UDiv: 4197 case Instruction::SDiv: 4198 case Instruction::URem: 4199 case Instruction::SRem: 4200 return false; 4201 } 4202 } 4203 4204 return true; 4205} 4206 4207LoopVectorizationCostModel::VectorizationFactor 4208LoopVectorizationCostModel::selectVectorizationFactor(bool OptForSize, 4209 unsigned UserVF) { 4210 // Width 1 means no vectorize 4211 VectorizationFactor Factor = { 1U, 0U }; 4212 if (OptForSize && Legal->getRuntimePointerCheck()->Need) { 4213 DEBUG(dbgs() << "LV: Aborting. Runtime ptr check is required in Os.\n"); 4214 return Factor; 4215 } 4216 4217 // Find the trip count. 4218 unsigned TC = SE->getSmallConstantTripCount(TheLoop, TheLoop->getLoopLatch()); 4219 DEBUG(dbgs() << "LV: Found trip count:"<<TC<<"\n"); 4220 4221 unsigned WidestType = getWidestType(); 4222 unsigned WidestRegister = TTI.getRegisterBitWidth(true); 4223 unsigned MaxSafeDepDist = -1U; 4224 if (Legal->getMaxSafeDepDistBytes() != -1U) 4225 MaxSafeDepDist = Legal->getMaxSafeDepDistBytes() * 8; 4226 WidestRegister = ((WidestRegister < MaxSafeDepDist) ? 4227 WidestRegister : MaxSafeDepDist); 4228 unsigned MaxVectorSize = WidestRegister / WidestType; 4229 DEBUG(dbgs() << "LV: The Widest type: " << WidestType << " bits.\n"); 4230 DEBUG(dbgs() << "LV: The Widest register is:" << WidestRegister << "bits.\n"); 4231 4232 if (MaxVectorSize == 0) { 4233 DEBUG(dbgs() << "LV: The target has no vector registers.\n"); 4234 MaxVectorSize = 1; 4235 } 4236 4237 assert(MaxVectorSize <= 32 && "Did not expect to pack so many elements" 4238 " into one vector!"); 4239 4240 unsigned VF = MaxVectorSize; 4241 4242 // If we optimize the program for size, avoid creating the tail loop. 4243 if (OptForSize) { 4244 // If we are unable to calculate the trip count then don't try to vectorize. 4245 if (TC < 2) { 4246 DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n"); 4247 return Factor; 4248 } 4249 4250 // Find the maximum SIMD width that can fit within the trip count. 4251 VF = TC % MaxVectorSize; 4252 4253 if (VF == 0) 4254 VF = MaxVectorSize; 4255 4256 // If the trip count that we found modulo the vectorization factor is not 4257 // zero then we require a tail. 4258 if (VF < 2) { 4259 DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n"); 4260 return Factor; 4261 } 4262 } 4263 4264 if (UserVF != 0) { 4265 assert(isPowerOf2_32(UserVF) && "VF needs to be a power of two"); 4266 DEBUG(dbgs() << "LV: Using user VF "<<UserVF<<".\n"); 4267 4268 Factor.Width = UserVF; 4269 return Factor; 4270 } 4271 4272 float Cost = expectedCost(1); 4273 unsigned Width = 1; 4274 DEBUG(dbgs() << "LV: Scalar loop costs: "<< (int)Cost << ".\n"); 4275 for (unsigned i=2; i <= VF; i*=2) { 4276 // Notice that the vector loop needs to be executed less times, so 4277 // we need to divide the cost of the vector loops by the width of 4278 // the vector elements. 4279 float VectorCost = expectedCost(i) / (float)i; 4280 DEBUG(dbgs() << "LV: Vector loop of width "<< i << " costs: " << 4281 (int)VectorCost << ".\n"); 4282 if (VectorCost < Cost) { 4283 Cost = VectorCost; 4284 Width = i; 4285 } 4286 } 4287 4288 DEBUG(dbgs() << "LV: Selecting VF = : "<< Width << ".\n"); 4289 Factor.Width = Width; 4290 Factor.Cost = Width * Cost; 4291 return Factor; 4292} 4293 4294unsigned LoopVectorizationCostModel::getWidestType() { 4295 unsigned MaxWidth = 8; 4296 4297 // For each block. 4298 for (Loop::block_iterator bb = TheLoop->block_begin(), 4299 be = TheLoop->block_end(); bb != be; ++bb) { 4300 BasicBlock *BB = *bb; 4301 4302 // For each instruction in the loop. 4303 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 4304 Type *T = it->getType(); 4305 4306 // Only examine Loads, Stores and PHINodes. 4307 if (!isa<LoadInst>(it) && !isa<StoreInst>(it) && !isa<PHINode>(it)) 4308 continue; 4309 4310 // Examine PHI nodes that are reduction variables. 4311 if (PHINode *PN = dyn_cast<PHINode>(it)) 4312 if (!Legal->getReductionVars()->count(PN)) 4313 continue; 4314 4315 // Examine the stored values. 4316 if (StoreInst *ST = dyn_cast<StoreInst>(it)) 4317 T = ST->getValueOperand()->getType(); 4318 4319 // Ignore loaded pointer types and stored pointer types that are not 4320 // consecutive. However, we do want to take consecutive stores/loads of 4321 // pointer vectors into account. 4322 if (T->isPointerTy() && !isConsecutiveLoadOrStore(it)) 4323 continue; 4324 4325 MaxWidth = std::max(MaxWidth, 4326 (unsigned)DL->getTypeSizeInBits(T->getScalarType())); 4327 } 4328 } 4329 4330 return MaxWidth; 4331} 4332 4333unsigned 4334LoopVectorizationCostModel::selectUnrollFactor(bool OptForSize, 4335 unsigned UserUF, 4336 unsigned VF, 4337 unsigned LoopCost) { 4338 4339 // -- The unroll heuristics -- 4340 // We unroll the loop in order to expose ILP and reduce the loop overhead. 4341 // There are many micro-architectural considerations that we can't predict 4342 // at this level. For example frontend pressure (on decode or fetch) due to 4343 // code size, or the number and capabilities of the execution ports. 4344 // 4345 // We use the following heuristics to select the unroll factor: 4346 // 1. If the code has reductions the we unroll in order to break the cross 4347 // iteration dependency. 4348 // 2. If the loop is really small then we unroll in order to reduce the loop 4349 // overhead. 4350 // 3. We don't unroll if we think that we will spill registers to memory due 4351 // to the increased register pressure. 4352 4353 // Use the user preference, unless 'auto' is selected. 4354 if (UserUF != 0) 4355 return UserUF; 4356 4357 // When we optimize for size we don't unroll. 4358 if (OptForSize) 4359 return 1; 4360 4361 // We used the distance for the unroll factor. 4362 if (Legal->getMaxSafeDepDistBytes() != -1U) 4363 return 1; 4364 4365 // Do not unroll loops with a relatively small trip count. 4366 unsigned TC = SE->getSmallConstantTripCount(TheLoop, 4367 TheLoop->getLoopLatch()); 4368 if (TC > 1 && TC < TinyTripCountUnrollThreshold) 4369 return 1; 4370 4371 unsigned TargetVectorRegisters = TTI.getNumberOfRegisters(true); 4372 DEBUG(dbgs() << "LV: The target has " << TargetVectorRegisters << 4373 " vector registers\n"); 4374 4375 LoopVectorizationCostModel::RegisterUsage R = calculateRegisterUsage(); 4376 // We divide by these constants so assume that we have at least one 4377 // instruction that uses at least one register. 4378 R.MaxLocalUsers = std::max(R.MaxLocalUsers, 1U); 4379 R.NumInstructions = std::max(R.NumInstructions, 1U); 4380 4381 // We calculate the unroll factor using the following formula. 4382 // Subtract the number of loop invariants from the number of available 4383 // registers. These registers are used by all of the unrolled instances. 4384 // Next, divide the remaining registers by the number of registers that is 4385 // required by the loop, in order to estimate how many parallel instances 4386 // fit without causing spills. 4387 unsigned UF = (TargetVectorRegisters - R.LoopInvariantRegs) / R.MaxLocalUsers; 4388 4389 // Clamp the unroll factor ranges to reasonable factors. 4390 unsigned MaxUnrollSize = TTI.getMaximumUnrollFactor(); 4391 4392 // If we did not calculate the cost for VF (because the user selected the VF) 4393 // then we calculate the cost of VF here. 4394 if (LoopCost == 0) 4395 LoopCost = expectedCost(VF); 4396 4397 // Clamp the calculated UF to be between the 1 and the max unroll factor 4398 // that the target allows. 4399 if (UF > MaxUnrollSize) 4400 UF = MaxUnrollSize; 4401 else if (UF < 1) 4402 UF = 1; 4403 4404 bool HasReductions = Legal->getReductionVars()->size(); 4405 4406 // Decide if we want to unroll if we decided that it is legal to vectorize 4407 // but not profitable. 4408 if (VF == 1) { 4409 if (TheLoop->getNumBlocks() > 1 || !HasReductions || 4410 LoopCost > SmallLoopCost) 4411 return 1; 4412 4413 return UF; 4414 } 4415 4416 if (HasReductions) { 4417 DEBUG(dbgs() << "LV: Unrolling because of reductions. \n"); 4418 return UF; 4419 } 4420 4421 // We want to unroll tiny loops in order to reduce the loop overhead. 4422 // We assume that the cost overhead is 1 and we use the cost model 4423 // to estimate the cost of the loop and unroll until the cost of the 4424 // loop overhead is about 5% of the cost of the loop. 4425 DEBUG(dbgs() << "LV: Loop cost is "<< LoopCost <<" \n"); 4426 if (LoopCost < SmallLoopCost) { 4427 DEBUG(dbgs() << "LV: Unrolling to reduce branch cost. \n"); 4428 unsigned NewUF = SmallLoopCost / (LoopCost + 1); 4429 return std::min(NewUF, UF); 4430 } 4431 4432 DEBUG(dbgs() << "LV: Not Unrolling. \n"); 4433 return 1; 4434} 4435 4436LoopVectorizationCostModel::RegisterUsage 4437LoopVectorizationCostModel::calculateRegisterUsage() { 4438 // This function calculates the register usage by measuring the highest number 4439 // of values that are alive at a single location. Obviously, this is a very 4440 // rough estimation. We scan the loop in a topological order in order and 4441 // assign a number to each instruction. We use RPO to ensure that defs are 4442 // met before their users. We assume that each instruction that has in-loop 4443 // users starts an interval. We record every time that an in-loop value is 4444 // used, so we have a list of the first and last occurrences of each 4445 // instruction. Next, we transpose this data structure into a multi map that 4446 // holds the list of intervals that *end* at a specific location. This multi 4447 // map allows us to perform a linear search. We scan the instructions linearly 4448 // and record each time that a new interval starts, by placing it in a set. 4449 // If we find this value in the multi-map then we remove it from the set. 4450 // The max register usage is the maximum size of the set. 4451 // We also search for instructions that are defined outside the loop, but are 4452 // used inside the loop. We need this number separately from the max-interval 4453 // usage number because when we unroll, loop-invariant values do not take 4454 // more register. 4455 LoopBlocksDFS DFS(TheLoop); 4456 DFS.perform(LI); 4457 4458 RegisterUsage R; 4459 R.NumInstructions = 0; 4460 4461 // Each 'key' in the map opens a new interval. The values 4462 // of the map are the index of the 'last seen' usage of the 4463 // instruction that is the key. 4464 typedef DenseMap<Instruction*, unsigned> IntervalMap; 4465 // Maps instruction to its index. 4466 DenseMap<unsigned, Instruction*> IdxToInstr; 4467 // Marks the end of each interval. 4468 IntervalMap EndPoint; 4469 // Saves the list of instruction indices that are used in the loop. 4470 SmallSet<Instruction*, 8> Ends; 4471 // Saves the list of values that are used in the loop but are 4472 // defined outside the loop, such as arguments and constants. 4473 SmallPtrSet<Value*, 8> LoopInvariants; 4474 4475 unsigned Index = 0; 4476 for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(), 4477 be = DFS.endRPO(); bb != be; ++bb) { 4478 R.NumInstructions += (*bb)->size(); 4479 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e; 4480 ++it) { 4481 Instruction *I = it; 4482 IdxToInstr[Index++] = I; 4483 4484 // Save the end location of each USE. 4485 for (unsigned i = 0; i < I->getNumOperands(); ++i) { 4486 Value *U = I->getOperand(i); 4487 Instruction *Instr = dyn_cast<Instruction>(U); 4488 4489 // Ignore non-instruction values such as arguments, constants, etc. 4490 if (!Instr) continue; 4491 4492 // If this instruction is outside the loop then record it and continue. 4493 if (!TheLoop->contains(Instr)) { 4494 LoopInvariants.insert(Instr); 4495 continue; 4496 } 4497 4498 // Overwrite previous end points. 4499 EndPoint[Instr] = Index; 4500 Ends.insert(Instr); 4501 } 4502 } 4503 } 4504 4505 // Saves the list of intervals that end with the index in 'key'. 4506 typedef SmallVector<Instruction*, 2> InstrList; 4507 DenseMap<unsigned, InstrList> TransposeEnds; 4508 4509 // Transpose the EndPoints to a list of values that end at each index. 4510 for (IntervalMap::iterator it = EndPoint.begin(), e = EndPoint.end(); 4511 it != e; ++it) 4512 TransposeEnds[it->second].push_back(it->first); 4513 4514 SmallSet<Instruction*, 8> OpenIntervals; 4515 unsigned MaxUsage = 0; 4516 4517 4518 DEBUG(dbgs() << "LV(REG): Calculating max register usage:\n"); 4519 for (unsigned int i = 0; i < Index; ++i) { 4520 Instruction *I = IdxToInstr[i]; 4521 // Ignore instructions that are never used within the loop. 4522 if (!Ends.count(I)) continue; 4523 4524 // Remove all of the instructions that end at this location. 4525 InstrList &List = TransposeEnds[i]; 4526 for (unsigned int j=0, e = List.size(); j < e; ++j) 4527 OpenIntervals.erase(List[j]); 4528 4529 // Count the number of live interals. 4530 MaxUsage = std::max(MaxUsage, OpenIntervals.size()); 4531 4532 DEBUG(dbgs() << "LV(REG): At #" << i << " Interval # " << 4533 OpenIntervals.size() <<"\n"); 4534 4535 // Add the current instruction to the list of open intervals. 4536 OpenIntervals.insert(I); 4537 } 4538 4539 unsigned Invariant = LoopInvariants.size(); 4540 DEBUG(dbgs() << "LV(REG): Found max usage: " << MaxUsage << " \n"); 4541 DEBUG(dbgs() << "LV(REG): Found invariant usage: " << Invariant << " \n"); 4542 DEBUG(dbgs() << "LV(REG): LoopSize: " << R.NumInstructions << " \n"); 4543 4544 R.LoopInvariantRegs = Invariant; 4545 R.MaxLocalUsers = MaxUsage; 4546 return R; 4547} 4548 4549unsigned LoopVectorizationCostModel::expectedCost(unsigned VF) { 4550 unsigned Cost = 0; 4551 4552 // For each block. 4553 for (Loop::block_iterator bb = TheLoop->block_begin(), 4554 be = TheLoop->block_end(); bb != be; ++bb) { 4555 unsigned BlockCost = 0; 4556 BasicBlock *BB = *bb; 4557 4558 // For each instruction in the old loop. 4559 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 4560 // Skip dbg intrinsics. 4561 if (isa<DbgInfoIntrinsic>(it)) 4562 continue; 4563 4564 unsigned C = getInstructionCost(it, VF); 4565 BlockCost += C; 4566 DEBUG(dbgs() << "LV: Found an estimated cost of "<< C <<" for VF " << 4567 VF << " For instruction: "<< *it << "\n"); 4568 } 4569 4570 // We assume that if-converted blocks have a 50% chance of being executed. 4571 // When the code is scalar then some of the blocks are avoided due to CF. 4572 // When the code is vectorized we execute all code paths. 4573 if (VF == 1 && Legal->blockNeedsPredication(*bb)) 4574 BlockCost /= 2; 4575 4576 Cost += BlockCost; 4577 } 4578 4579 return Cost; 4580} 4581 4582/// \brief Check whether the address computation for a non-consecutive memory 4583/// access looks like an unlikely candidate for being merged into the indexing 4584/// mode. 4585/// 4586/// We look for a GEP which has one index that is an induction variable and all 4587/// other indices are loop invariant. If the stride of this access is also 4588/// within a small bound we decide that this address computation can likely be 4589/// merged into the addressing mode. 4590/// In all other cases, we identify the address computation as complex. 4591static bool isLikelyComplexAddressComputation(Value *Ptr, 4592 LoopVectorizationLegality *Legal, 4593 ScalarEvolution *SE, 4594 const Loop *TheLoop) { 4595 GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr); 4596 if (!Gep) 4597 return true; 4598 4599 // We are looking for a gep with all loop invariant indices except for one 4600 // which should be an induction variable. 4601 unsigned NumOperands = Gep->getNumOperands(); 4602 for (unsigned i = 1; i < NumOperands; ++i) { 4603 Value *Opd = Gep->getOperand(i); 4604 if (!SE->isLoopInvariant(SE->getSCEV(Opd), TheLoop) && 4605 !Legal->isInductionVariable(Opd)) 4606 return true; 4607 } 4608 4609 // Now we know we have a GEP ptr, %inv, %ind, %inv. Make sure that the step 4610 // can likely be merged into the address computation. 4611 unsigned MaxMergeDistance = 64; 4612 4613 const SCEVAddRecExpr *AddRec = dyn_cast<SCEVAddRecExpr>(SE->getSCEV(Ptr)); 4614 if (!AddRec) 4615 return true; 4616 4617 // Check the step is constant. 4618 const SCEV *Step = AddRec->getStepRecurrence(*SE); 4619 // Calculate the pointer stride and check if it is consecutive. 4620 const SCEVConstant *C = dyn_cast<SCEVConstant>(Step); 4621 if (!C) 4622 return true; 4623 4624 const APInt &APStepVal = C->getValue()->getValue(); 4625 4626 // Huge step value - give up. 4627 if (APStepVal.getBitWidth() > 64) 4628 return true; 4629 4630 int64_t StepVal = APStepVal.getSExtValue(); 4631 4632 return StepVal > MaxMergeDistance; 4633} 4634 4635unsigned 4636LoopVectorizationCostModel::getInstructionCost(Instruction *I, unsigned VF) { 4637 // If we know that this instruction will remain uniform, check the cost of 4638 // the scalar version. 4639 if (Legal->isUniformAfterVectorization(I)) 4640 VF = 1; 4641 4642 Type *RetTy = I->getType(); 4643 Type *VectorTy = ToVectorTy(RetTy, VF); 4644 4645 // TODO: We need to estimate the cost of intrinsic calls. 4646 switch (I->getOpcode()) { 4647 case Instruction::GetElementPtr: 4648 // We mark this instruction as zero-cost because the cost of GEPs in 4649 // vectorized code depends on whether the corresponding memory instruction 4650 // is scalarized or not. Therefore, we handle GEPs with the memory 4651 // instruction cost. 4652 return 0; 4653 case Instruction::Br: { 4654 return TTI.getCFInstrCost(I->getOpcode()); 4655 } 4656 case Instruction::PHI: 4657 //TODO: IF-converted IFs become selects. 4658 return 0; 4659 case Instruction::Add: 4660 case Instruction::FAdd: 4661 case Instruction::Sub: 4662 case Instruction::FSub: 4663 case Instruction::Mul: 4664 case Instruction::FMul: 4665 case Instruction::UDiv: 4666 case Instruction::SDiv: 4667 case Instruction::FDiv: 4668 case Instruction::URem: 4669 case Instruction::SRem: 4670 case Instruction::FRem: 4671 case Instruction::Shl: 4672 case Instruction::LShr: 4673 case Instruction::AShr: 4674 case Instruction::And: 4675 case Instruction::Or: 4676 case Instruction::Xor: { 4677 // Certain instructions can be cheaper to vectorize if they have a constant 4678 // second vector operand. One example of this are shifts on x86. 4679 TargetTransformInfo::OperandValueKind Op1VK = 4680 TargetTransformInfo::OK_AnyValue; 4681 TargetTransformInfo::OperandValueKind Op2VK = 4682 TargetTransformInfo::OK_AnyValue; 4683 4684 if (isa<ConstantInt>(I->getOperand(1))) 4685 Op2VK = TargetTransformInfo::OK_UniformConstantValue; 4686 4687 return TTI.getArithmeticInstrCost(I->getOpcode(), VectorTy, Op1VK, Op2VK); 4688 } 4689 case Instruction::Select: { 4690 SelectInst *SI = cast<SelectInst>(I); 4691 const SCEV *CondSCEV = SE->getSCEV(SI->getCondition()); 4692 bool ScalarCond = (SE->isLoopInvariant(CondSCEV, TheLoop)); 4693 Type *CondTy = SI->getCondition()->getType(); 4694 if (!ScalarCond) 4695 CondTy = VectorType::get(CondTy, VF); 4696 4697 return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy, CondTy); 4698 } 4699 case Instruction::ICmp: 4700 case Instruction::FCmp: { 4701 Type *ValTy = I->getOperand(0)->getType(); 4702 VectorTy = ToVectorTy(ValTy, VF); 4703 return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy); 4704 } 4705 case Instruction::Store: 4706 case Instruction::Load: { 4707 StoreInst *SI = dyn_cast<StoreInst>(I); 4708 LoadInst *LI = dyn_cast<LoadInst>(I); 4709 Type *ValTy = (SI ? SI->getValueOperand()->getType() : 4710 LI->getType()); 4711 VectorTy = ToVectorTy(ValTy, VF); 4712 4713 unsigned Alignment = SI ? SI->getAlignment() : LI->getAlignment(); 4714 unsigned AS = SI ? SI->getPointerAddressSpace() : 4715 LI->getPointerAddressSpace(); 4716 Value *Ptr = SI ? SI->getPointerOperand() : LI->getPointerOperand(); 4717 // We add the cost of address computation here instead of with the gep 4718 // instruction because only here we know whether the operation is 4719 // scalarized. 4720 if (VF == 1) 4721 return TTI.getAddressComputationCost(VectorTy) + 4722 TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS); 4723 4724 // Scalarized loads/stores. 4725 int ConsecutiveStride = Legal->isConsecutivePtr(Ptr); 4726 bool Reverse = ConsecutiveStride < 0; 4727 unsigned ScalarAllocatedSize = DL->getTypeAllocSize(ValTy); 4728 unsigned VectorElementSize = DL->getTypeStoreSize(VectorTy)/VF; 4729 if (!ConsecutiveStride || ScalarAllocatedSize != VectorElementSize) { 4730 bool IsComplexComputation = 4731 isLikelyComplexAddressComputation(Ptr, Legal, SE, TheLoop); 4732 unsigned Cost = 0; 4733 // The cost of extracting from the value vector and pointer vector. 4734 Type *PtrTy = ToVectorTy(Ptr->getType(), VF); 4735 for (unsigned i = 0; i < VF; ++i) { 4736 // The cost of extracting the pointer operand. 4737 Cost += TTI.getVectorInstrCost(Instruction::ExtractElement, PtrTy, i); 4738 // In case of STORE, the cost of ExtractElement from the vector. 4739 // In case of LOAD, the cost of InsertElement into the returned 4740 // vector. 4741 Cost += TTI.getVectorInstrCost(SI ? Instruction::ExtractElement : 4742 Instruction::InsertElement, 4743 VectorTy, i); 4744 } 4745 4746 // The cost of the scalar loads/stores. 4747 Cost += VF * TTI.getAddressComputationCost(PtrTy, IsComplexComputation); 4748 Cost += VF * TTI.getMemoryOpCost(I->getOpcode(), ValTy->getScalarType(), 4749 Alignment, AS); 4750 return Cost; 4751 } 4752 4753 // Wide load/stores. 4754 unsigned Cost = TTI.getAddressComputationCost(VectorTy); 4755 Cost += TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS); 4756 4757 if (Reverse) 4758 Cost += TTI.getShuffleCost(TargetTransformInfo::SK_Reverse, 4759 VectorTy, 0); 4760 return Cost; 4761 } 4762 case Instruction::ZExt: 4763 case Instruction::SExt: 4764 case Instruction::FPToUI: 4765 case Instruction::FPToSI: 4766 case Instruction::FPExt: 4767 case Instruction::PtrToInt: 4768 case Instruction::IntToPtr: 4769 case Instruction::SIToFP: 4770 case Instruction::UIToFP: 4771 case Instruction::Trunc: 4772 case Instruction::FPTrunc: 4773 case Instruction::BitCast: { 4774 // We optimize the truncation of induction variable. 4775 // The cost of these is the same as the scalar operation. 4776 if (I->getOpcode() == Instruction::Trunc && 4777 Legal->isInductionVariable(I->getOperand(0))) 4778 return TTI.getCastInstrCost(I->getOpcode(), I->getType(), 4779 I->getOperand(0)->getType()); 4780 4781 Type *SrcVecTy = ToVectorTy(I->getOperand(0)->getType(), VF); 4782 return TTI.getCastInstrCost(I->getOpcode(), VectorTy, SrcVecTy); 4783 } 4784 case Instruction::Call: { 4785 CallInst *CI = cast<CallInst>(I); 4786 Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI); 4787 assert(ID && "Not an intrinsic call!"); 4788 Type *RetTy = ToVectorTy(CI->getType(), VF); 4789 SmallVector<Type*, 4> Tys; 4790 for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i) 4791 Tys.push_back(ToVectorTy(CI->getArgOperand(i)->getType(), VF)); 4792 return TTI.getIntrinsicInstrCost(ID, RetTy, Tys); 4793 } 4794 default: { 4795 // We are scalarizing the instruction. Return the cost of the scalar 4796 // instruction, plus the cost of insert and extract into vector 4797 // elements, times the vector width. 4798 unsigned Cost = 0; 4799 4800 if (!RetTy->isVoidTy() && VF != 1) { 4801 unsigned InsCost = TTI.getVectorInstrCost(Instruction::InsertElement, 4802 VectorTy); 4803 unsigned ExtCost = TTI.getVectorInstrCost(Instruction::ExtractElement, 4804 VectorTy); 4805 4806 // The cost of inserting the results plus extracting each one of the 4807 // operands. 4808 Cost += VF * (InsCost + ExtCost * I->getNumOperands()); 4809 } 4810 4811 // The cost of executing VF copies of the scalar instruction. This opcode 4812 // is unknown. Assume that it is the same as 'mul'. 4813 Cost += VF * TTI.getArithmeticInstrCost(Instruction::Mul, VectorTy); 4814 return Cost; 4815 } 4816 }// end of switch. 4817} 4818 4819Type* LoopVectorizationCostModel::ToVectorTy(Type *Scalar, unsigned VF) { 4820 if (Scalar->isVoidTy() || VF == 1) 4821 return Scalar; 4822 return VectorType::get(Scalar, VF); 4823} 4824 4825char LoopVectorize::ID = 0; 4826static const char lv_name[] = "Loop Vectorization"; 4827INITIALIZE_PASS_BEGIN(LoopVectorize, LV_NAME, lv_name, false, false) 4828INITIALIZE_AG_DEPENDENCY(TargetTransformInfo) 4829INITIALIZE_PASS_DEPENDENCY(ScalarEvolution) 4830INITIALIZE_PASS_DEPENDENCY(LoopSimplify) 4831INITIALIZE_PASS_END(LoopVectorize, LV_NAME, lv_name, false, false) 4832 4833namespace llvm { 4834 Pass *createLoopVectorizePass(bool NoUnrolling) { 4835 return new LoopVectorize(NoUnrolling); 4836 } 4837} 4838 4839bool LoopVectorizationCostModel::isConsecutiveLoadOrStore(Instruction *Inst) { 4840 // Check for a store. 4841 if (StoreInst *ST = dyn_cast<StoreInst>(Inst)) 4842 return Legal->isConsecutivePtr(ST->getPointerOperand()) != 0; 4843 4844 // Check for a load. 4845 if (LoadInst *LI = dyn_cast<LoadInst>(Inst)) 4846 return Legal->isConsecutivePtr(LI->getPointerOperand()) != 0; 4847 4848 return false; 4849} 4850 4851 4852void InnerLoopUnroller::scalarizeInstruction(Instruction *Instr) { 4853 assert(!Instr->getType()->isAggregateType() && "Can't handle vectors"); 4854 // Holds vector parameters or scalars, in case of uniform vals. 4855 SmallVector<VectorParts, 4> Params; 4856 4857 setDebugLocFromInst(Builder, Instr); 4858 4859 // Find all of the vectorized parameters. 4860 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) { 4861 Value *SrcOp = Instr->getOperand(op); 4862 4863 // If we are accessing the old induction variable, use the new one. 4864 if (SrcOp == OldInduction) { 4865 Params.push_back(getVectorValue(SrcOp)); 4866 continue; 4867 } 4868 4869 // Try using previously calculated values. 4870 Instruction *SrcInst = dyn_cast<Instruction>(SrcOp); 4871 4872 // If the src is an instruction that appeared earlier in the basic block 4873 // then it should already be vectorized. 4874 if (SrcInst && OrigLoop->contains(SrcInst)) { 4875 assert(WidenMap.has(SrcInst) && "Source operand is unavailable"); 4876 // The parameter is a vector value from earlier. 4877 Params.push_back(WidenMap.get(SrcInst)); 4878 } else { 4879 // The parameter is a scalar from outside the loop. Maybe even a constant. 4880 VectorParts Scalars; 4881 Scalars.append(UF, SrcOp); 4882 Params.push_back(Scalars); 4883 } 4884 } 4885 4886 assert(Params.size() == Instr->getNumOperands() && 4887 "Invalid number of operands"); 4888 4889 // Does this instruction return a value ? 4890 bool IsVoidRetTy = Instr->getType()->isVoidTy(); 4891 4892 Value *UndefVec = IsVoidRetTy ? 0 : 4893 UndefValue::get(Instr->getType()); 4894 // Create a new entry in the WidenMap and initialize it to Undef or Null. 4895 VectorParts &VecResults = WidenMap.splat(Instr, UndefVec); 4896 4897 // For each vector unroll 'part': 4898 for (unsigned Part = 0; Part < UF; ++Part) { 4899 // For each scalar that we create: 4900 4901 Instruction *Cloned = Instr->clone(); 4902 if (!IsVoidRetTy) 4903 Cloned->setName(Instr->getName() + ".cloned"); 4904 // Replace the operands of the cloned instructions with extracted scalars. 4905 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) { 4906 Value *Op = Params[op][Part]; 4907 Cloned->setOperand(op, Op); 4908 } 4909 4910 // Place the cloned scalar in the new loop. 4911 Builder.Insert(Cloned); 4912 4913 // If the original scalar returns a value we need to place it in a vector 4914 // so that future users will be able to use it. 4915 if (!IsVoidRetTy) 4916 VecResults[Part] = Cloned; 4917 } 4918} 4919 4920void 4921InnerLoopUnroller::vectorizeMemoryInstruction(Instruction *Instr, 4922 LoopVectorizationLegality*) { 4923 return scalarizeInstruction(Instr); 4924} 4925 4926Value *InnerLoopUnroller::reverseVector(Value *Vec) { 4927 return Vec; 4928} 4929 4930Value *InnerLoopUnroller::getBroadcastInstrs(Value *V) { 4931 return V; 4932} 4933 4934Value *InnerLoopUnroller::getConsecutiveVector(Value* Val, int StartIdx, 4935 bool Negate) { 4936 // When unrolling and the VF is 1, we only need to add a simple scalar. 4937 Type *ITy = Val->getType(); 4938 assert(!ITy->isVectorTy() && "Val must be a scalar"); 4939 Constant *C = ConstantInt::get(ITy, StartIdx, Negate); 4940 return Builder.CreateAdd(Val, C, "induction"); 4941} 4942 4943