LoopVectorize.cpp revision 41418d17cced656f91038b2482bc9d173b4974b0
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 129namespace { 130 131// Forward declarations. 132class LoopVectorizationLegality; 133class LoopVectorizationCostModel; 134 135/// InnerLoopVectorizer vectorizes loops which contain only one basic 136/// block to a specified vectorization factor (VF). 137/// This class performs the widening of scalars into vectors, or multiple 138/// scalars. This class also implements the following features: 139/// * It inserts an epilogue loop for handling loops that don't have iteration 140/// counts that are known to be a multiple of the vectorization factor. 141/// * It handles the code generation for reduction variables. 142/// * Scalarization (implementation using scalars) of un-vectorizable 143/// instructions. 144/// InnerLoopVectorizer does not perform any vectorization-legality 145/// checks, and relies on the caller to check for the different legality 146/// aspects. The InnerLoopVectorizer relies on the 147/// LoopVectorizationLegality class to provide information about the induction 148/// and reduction variables that were found to a given vectorization factor. 149class InnerLoopVectorizer { 150public: 151 InnerLoopVectorizer(Loop *OrigLoop, ScalarEvolution *SE, LoopInfo *LI, 152 DominatorTree *DT, DataLayout *DL, 153 const TargetLibraryInfo *TLI, unsigned VecWidth, 154 unsigned UnrollFactor) 155 : OrigLoop(OrigLoop), SE(SE), LI(LI), DT(DT), DL(DL), TLI(TLI), 156 VF(VecWidth), UF(UnrollFactor), Builder(SE->getContext()), Induction(0), 157 OldInduction(0), WidenMap(UnrollFactor) {} 158 159 // Perform the actual loop widening (vectorization). 160 void vectorize(LoopVectorizationLegality *Legal) { 161 // Create a new empty loop. Unlink the old loop and connect the new one. 162 createEmptyLoop(Legal); 163 // Widen each instruction in the old loop to a new one in the new loop. 164 // Use the Legality module to find the induction and reduction variables. 165 vectorizeLoop(Legal); 166 // Register the new loop and update the analysis passes. 167 updateAnalysis(); 168 } 169 170private: 171 /// A small list of PHINodes. 172 typedef SmallVector<PHINode*, 4> PhiVector; 173 /// When we unroll loops we have multiple vector values for each scalar. 174 /// This data structure holds the unrolled and vectorized values that 175 /// originated from one scalar instruction. 176 typedef SmallVector<Value*, 2> VectorParts; 177 178 // When we if-convert we need create edge masks. We have to cache values so 179 // that we don't end up with exponential recursion/IR. 180 typedef DenseMap<std::pair<BasicBlock*, BasicBlock*>, 181 VectorParts> EdgeMaskCache; 182 183 /// Add code that checks at runtime if the accessed arrays overlap. 184 /// Returns the comparator value or NULL if no check is needed. 185 Instruction *addRuntimeCheck(LoopVectorizationLegality *Legal, 186 Instruction *Loc); 187 /// Create an empty loop, based on the loop ranges of the old loop. 188 void createEmptyLoop(LoopVectorizationLegality *Legal); 189 /// Copy and widen the instructions from the old loop. 190 void vectorizeLoop(LoopVectorizationLegality *Legal); 191 192 /// A helper function that computes the predicate of the block BB, assuming 193 /// that the header block of the loop is set to True. It returns the *entry* 194 /// mask for the block BB. 195 VectorParts createBlockInMask(BasicBlock *BB); 196 /// A helper function that computes the predicate of the edge between SRC 197 /// and DST. 198 VectorParts createEdgeMask(BasicBlock *Src, BasicBlock *Dst); 199 200 /// A helper function to vectorize a single BB within the innermost loop. 201 void vectorizeBlockInLoop(LoopVectorizationLegality *Legal, BasicBlock *BB, 202 PhiVector *PV); 203 204 /// Insert the new loop to the loop hierarchy and pass manager 205 /// and update the analysis passes. 206 void updateAnalysis(); 207 208 /// This instruction is un-vectorizable. Implement it as a sequence 209 /// of scalars. 210 void scalarizeInstruction(Instruction *Instr); 211 212 /// Vectorize Load and Store instructions, 213 void vectorizeMemoryInstruction(Instruction *Instr, 214 LoopVectorizationLegality *Legal); 215 216 /// Create a broadcast instruction. This method generates a broadcast 217 /// instruction (shuffle) for loop invariant values and for the induction 218 /// value. If this is the induction variable then we extend it to N, N+1, ... 219 /// this is needed because each iteration in the loop corresponds to a SIMD 220 /// element. 221 Value *getBroadcastInstrs(Value *V); 222 223 /// This function adds 0, 1, 2 ... to each vector element, starting at zero. 224 /// If Negate is set then negative numbers are added e.g. (0, -1, -2, ...). 225 /// The sequence starts at StartIndex. 226 Value *getConsecutiveVector(Value* Val, int StartIdx, bool Negate); 227 228 /// When we go over instructions in the basic block we rely on previous 229 /// values within the current basic block or on loop invariant values. 230 /// When we widen (vectorize) values we place them in the map. If the values 231 /// are not within the map, they have to be loop invariant, so we simply 232 /// broadcast them into a vector. 233 VectorParts &getVectorValue(Value *V); 234 235 /// Generate a shuffle sequence that will reverse the vector Vec. 236 Value *reverseVector(Value *Vec); 237 238 /// This is a helper class that holds the vectorizer state. It maps scalar 239 /// instructions to vector instructions. When the code is 'unrolled' then 240 /// then a single scalar value is mapped to multiple vector parts. The parts 241 /// are stored in the VectorPart type. 242 struct ValueMap { 243 /// C'tor. UnrollFactor controls the number of vectors ('parts') that 244 /// are mapped. 245 ValueMap(unsigned UnrollFactor) : UF(UnrollFactor) {} 246 247 /// \return True if 'Key' is saved in the Value Map. 248 bool has(Value *Key) const { return MapStorage.count(Key); } 249 250 /// Initializes a new entry in the map. Sets all of the vector parts to the 251 /// save value in 'Val'. 252 /// \return A reference to a vector with splat values. 253 VectorParts &splat(Value *Key, Value *Val) { 254 VectorParts &Entry = MapStorage[Key]; 255 Entry.assign(UF, Val); 256 return Entry; 257 } 258 259 ///\return A reference to the value that is stored at 'Key'. 260 VectorParts &get(Value *Key) { 261 VectorParts &Entry = MapStorage[Key]; 262 if (Entry.empty()) 263 Entry.resize(UF); 264 assert(Entry.size() == UF); 265 return Entry; 266 } 267 268 private: 269 /// The unroll factor. Each entry in the map stores this number of vector 270 /// elements. 271 unsigned UF; 272 273 /// Map storage. We use std::map and not DenseMap because insertions to a 274 /// dense map invalidates its iterators. 275 std::map<Value *, VectorParts> MapStorage; 276 }; 277 278 /// The original loop. 279 Loop *OrigLoop; 280 /// Scev analysis to use. 281 ScalarEvolution *SE; 282 /// Loop Info. 283 LoopInfo *LI; 284 /// Dominator Tree. 285 DominatorTree *DT; 286 /// Data Layout. 287 DataLayout *DL; 288 /// Target Library Info. 289 const TargetLibraryInfo *TLI; 290 291 /// The vectorization SIMD factor to use. Each vector will have this many 292 /// vector elements. 293 unsigned VF; 294 /// The vectorization unroll factor to use. Each scalar is vectorized to this 295 /// many different vector instructions. 296 unsigned UF; 297 298 /// The builder that we use 299 IRBuilder<> Builder; 300 301 // --- Vectorization state --- 302 303 /// The vector-loop preheader. 304 BasicBlock *LoopVectorPreHeader; 305 /// The scalar-loop preheader. 306 BasicBlock *LoopScalarPreHeader; 307 /// Middle Block between the vector and the scalar. 308 BasicBlock *LoopMiddleBlock; 309 ///The ExitBlock of the scalar loop. 310 BasicBlock *LoopExitBlock; 311 ///The vector loop body. 312 BasicBlock *LoopVectorBody; 313 ///The scalar loop body. 314 BasicBlock *LoopScalarBody; 315 /// A list of all bypass blocks. The first block is the entry of the loop. 316 SmallVector<BasicBlock *, 4> LoopBypassBlocks; 317 318 /// The new Induction variable which was added to the new block. 319 PHINode *Induction; 320 /// The induction variable of the old basic block. 321 PHINode *OldInduction; 322 /// Holds the extended (to the widest induction type) start index. 323 Value *ExtendedIdx; 324 /// Maps scalars to widened vectors. 325 ValueMap WidenMap; 326 EdgeMaskCache MaskCache; 327}; 328 329/// \brief Look for a meaningful debug location on the instruction or it's 330/// operands. 331static Instruction *getDebugLocFromInstOrOperands(Instruction *I) { 332 if (!I) 333 return I; 334 335 DebugLoc Empty; 336 if (I->getDebugLoc() != Empty) 337 return I; 338 339 for (User::op_iterator OI = I->op_begin(), OE = I->op_end(); OI != OE; ++OI) { 340 if (Instruction *OpInst = dyn_cast<Instruction>(*OI)) 341 if (OpInst->getDebugLoc() != Empty) 342 return OpInst; 343 } 344 345 return I; 346} 347 348/// \brief Set the debug location in the builder using the debug location in the 349/// instruction. 350static void setDebugLocFromInst(IRBuilder<> &B, const Value *Ptr) { 351 if (const Instruction *Inst = dyn_cast_or_null<Instruction>(Ptr)) 352 B.SetCurrentDebugLocation(Inst->getDebugLoc()); 353 else 354 B.SetCurrentDebugLocation(DebugLoc()); 355} 356 357/// LoopVectorizationLegality checks if it is legal to vectorize a loop, and 358/// to what vectorization factor. 359/// This class does not look at the profitability of vectorization, only the 360/// legality. This class has two main kinds of checks: 361/// * Memory checks - The code in canVectorizeMemory checks if vectorization 362/// will change the order of memory accesses in a way that will change the 363/// correctness of the program. 364/// * Scalars checks - The code in canVectorizeInstrs and canVectorizeMemory 365/// checks for a number of different conditions, such as the availability of a 366/// single induction variable, that all types are supported and vectorize-able, 367/// etc. This code reflects the capabilities of InnerLoopVectorizer. 368/// This class is also used by InnerLoopVectorizer for identifying 369/// induction variable and the different reduction variables. 370class LoopVectorizationLegality { 371public: 372 LoopVectorizationLegality(Loop *L, ScalarEvolution *SE, DataLayout *DL, 373 DominatorTree *DT, TargetLibraryInfo *TLI) 374 : TheLoop(L), SE(SE), DL(DL), DT(DT), TLI(TLI), 375 Induction(0), WidestIndTy(0), HasFunNoNaNAttr(false), 376 MaxSafeDepDistBytes(-1U) {} 377 378 /// This enum represents the kinds of reductions that we support. 379 enum ReductionKind { 380 RK_NoReduction, ///< Not a reduction. 381 RK_IntegerAdd, ///< Sum of integers. 382 RK_IntegerMult, ///< Product of integers. 383 RK_IntegerOr, ///< Bitwise or logical OR of numbers. 384 RK_IntegerAnd, ///< Bitwise or logical AND of numbers. 385 RK_IntegerXor, ///< Bitwise or logical XOR of numbers. 386 RK_IntegerMinMax, ///< Min/max implemented in terms of select(cmp()). 387 RK_FloatAdd, ///< Sum of floats. 388 RK_FloatMult, ///< Product of floats. 389 RK_FloatMinMax ///< Min/max implemented in terms of select(cmp()). 390 }; 391 392 /// This enum represents the kinds of inductions that we support. 393 enum InductionKind { 394 IK_NoInduction, ///< Not an induction variable. 395 IK_IntInduction, ///< Integer induction variable. Step = 1. 396 IK_ReverseIntInduction, ///< Reverse int induction variable. Step = -1. 397 IK_PtrInduction, ///< Pointer induction var. Step = sizeof(elem). 398 IK_ReversePtrInduction ///< Reverse ptr indvar. Step = - sizeof(elem). 399 }; 400 401 // This enum represents the kind of minmax reduction. 402 enum MinMaxReductionKind { 403 MRK_Invalid, 404 MRK_UIntMin, 405 MRK_UIntMax, 406 MRK_SIntMin, 407 MRK_SIntMax, 408 MRK_FloatMin, 409 MRK_FloatMax 410 }; 411 412 /// This POD struct holds information about reduction variables. 413 struct ReductionDescriptor { 414 ReductionDescriptor() : StartValue(0), LoopExitInstr(0), 415 Kind(RK_NoReduction), MinMaxKind(MRK_Invalid) {} 416 417 ReductionDescriptor(Value *Start, Instruction *Exit, ReductionKind K, 418 MinMaxReductionKind MK) 419 : StartValue(Start), LoopExitInstr(Exit), Kind(K), MinMaxKind(MK) {} 420 421 // The starting value of the reduction. 422 // It does not have to be zero! 423 TrackingVH<Value> StartValue; 424 // The instruction who's value is used outside the loop. 425 Instruction *LoopExitInstr; 426 // The kind of the reduction. 427 ReductionKind Kind; 428 // If this a min/max reduction the kind of reduction. 429 MinMaxReductionKind MinMaxKind; 430 }; 431 432 /// This POD struct holds information about a potential reduction operation. 433 struct ReductionInstDesc { 434 ReductionInstDesc(bool IsRedux, Instruction *I) : 435 IsReduction(IsRedux), PatternLastInst(I), MinMaxKind(MRK_Invalid) {} 436 437 ReductionInstDesc(Instruction *I, MinMaxReductionKind K) : 438 IsReduction(true), PatternLastInst(I), MinMaxKind(K) {} 439 440 // Is this instruction a reduction candidate. 441 bool IsReduction; 442 // The last instruction in a min/max pattern (select of the select(icmp()) 443 // pattern), or the current reduction instruction otherwise. 444 Instruction *PatternLastInst; 445 // If this is a min/max pattern the comparison predicate. 446 MinMaxReductionKind MinMaxKind; 447 }; 448 449 // This POD struct holds information about the memory runtime legality 450 // check that a group of pointers do not overlap. 451 struct RuntimePointerCheck { 452 RuntimePointerCheck() : Need(false) {} 453 454 /// Reset the state of the pointer runtime information. 455 void reset() { 456 Need = false; 457 Pointers.clear(); 458 Starts.clear(); 459 Ends.clear(); 460 } 461 462 /// Insert a pointer and calculate the start and end SCEVs. 463 void insert(ScalarEvolution *SE, Loop *Lp, Value *Ptr, bool WritePtr, 464 unsigned DepSetId); 465 466 /// This flag indicates if we need to add the runtime check. 467 bool Need; 468 /// Holds the pointers that we need to check. 469 SmallVector<TrackingVH<Value>, 2> Pointers; 470 /// Holds the pointer value at the beginning of the loop. 471 SmallVector<const SCEV*, 2> Starts; 472 /// Holds the pointer value at the end of the loop. 473 SmallVector<const SCEV*, 2> Ends; 474 /// Holds the information if this pointer is used for writing to memory. 475 SmallVector<bool, 2> IsWritePtr; 476 /// Holds the id of the set of pointers that could be dependent because of a 477 /// shared underlying object. 478 SmallVector<unsigned, 2> DependencySetId; 479 }; 480 481 /// A POD for saving information about induction variables. 482 struct InductionInfo { 483 InductionInfo(Value *Start, InductionKind K) : StartValue(Start), IK(K) {} 484 InductionInfo() : StartValue(0), IK(IK_NoInduction) {} 485 /// Start value. 486 TrackingVH<Value> StartValue; 487 /// Induction kind. 488 InductionKind IK; 489 }; 490 491 /// ReductionList contains the reduction descriptors for all 492 /// of the reductions that were found in the loop. 493 typedef DenseMap<PHINode*, ReductionDescriptor> ReductionList; 494 495 /// InductionList saves induction variables and maps them to the 496 /// induction descriptor. 497 typedef MapVector<PHINode*, InductionInfo> InductionList; 498 499 /// Returns true if it is legal to vectorize this loop. 500 /// This does not mean that it is profitable to vectorize this 501 /// loop, only that it is legal to do so. 502 bool canVectorize(); 503 504 /// Returns the Induction variable. 505 PHINode *getInduction() { return Induction; } 506 507 /// Returns the reduction variables found in the loop. 508 ReductionList *getReductionVars() { return &Reductions; } 509 510 /// Returns the induction variables found in the loop. 511 InductionList *getInductionVars() { return &Inductions; } 512 513 /// Returns the widest induction type. 514 Type *getWidestInductionType() { return WidestIndTy; } 515 516 /// Returns True if V is an induction variable in this loop. 517 bool isInductionVariable(const Value *V); 518 519 /// Return true if the block BB needs to be predicated in order for the loop 520 /// to be vectorized. 521 bool blockNeedsPredication(BasicBlock *BB); 522 523 /// Check if this pointer is consecutive when vectorizing. This happens 524 /// when the last index of the GEP is the induction variable, or that the 525 /// pointer itself is an induction variable. 526 /// This check allows us to vectorize A[idx] into a wide load/store. 527 /// Returns: 528 /// 0 - Stride is unknown or non consecutive. 529 /// 1 - Address is consecutive. 530 /// -1 - Address is consecutive, and decreasing. 531 int isConsecutivePtr(Value *Ptr); 532 533 /// Returns true if the value V is uniform within the loop. 534 bool isUniform(Value *V); 535 536 /// Returns true if this instruction will remain scalar after vectorization. 537 bool isUniformAfterVectorization(Instruction* I) { return Uniforms.count(I); } 538 539 /// Returns the information that we collected about runtime memory check. 540 RuntimePointerCheck *getRuntimePointerCheck() { return &PtrRtCheck; } 541 542 /// This function returns the identity element (or neutral element) for 543 /// the operation K. 544 static Constant *getReductionIdentity(ReductionKind K, Type *Tp); 545 546 unsigned getMaxSafeDepDistBytes() { return MaxSafeDepDistBytes; } 547 548private: 549 /// Check if a single basic block loop is vectorizable. 550 /// At this point we know that this is a loop with a constant trip count 551 /// and we only need to check individual instructions. 552 bool canVectorizeInstrs(); 553 554 /// When we vectorize loops we may change the order in which 555 /// we read and write from memory. This method checks if it is 556 /// legal to vectorize the code, considering only memory constrains. 557 /// Returns true if the loop is vectorizable 558 bool canVectorizeMemory(); 559 560 /// Return true if we can vectorize this loop using the IF-conversion 561 /// transformation. 562 bool canVectorizeWithIfConvert(); 563 564 /// Collect the variables that need to stay uniform after vectorization. 565 void collectLoopUniforms(); 566 567 /// Return true if all of the instructions in the block can be speculatively 568 /// executed. \p SafePtrs is a list of addresses that are known to be legal 569 /// and we know that we can read from them without segfault. 570 bool blockCanBePredicated(BasicBlock *BB, SmallPtrSet<Value *, 8>& SafePtrs); 571 572 /// Returns True, if 'Phi' is the kind of reduction variable for type 573 /// 'Kind'. If this is a reduction variable, it adds it to ReductionList. 574 bool AddReductionVar(PHINode *Phi, ReductionKind Kind); 575 /// Returns a struct describing if the instruction 'I' can be a reduction 576 /// variable of type 'Kind'. If the reduction is a min/max pattern of 577 /// select(icmp()) this function advances the instruction pointer 'I' from the 578 /// compare instruction to the select instruction and stores this pointer in 579 /// 'PatternLastInst' member of the returned struct. 580 ReductionInstDesc isReductionInstr(Instruction *I, ReductionKind Kind, 581 ReductionInstDesc &Desc); 582 /// Returns true if the instruction is a Select(ICmp(X, Y), X, Y) instruction 583 /// pattern corresponding to a min(X, Y) or max(X, Y). 584 static ReductionInstDesc isMinMaxSelectCmpPattern(Instruction *I, 585 ReductionInstDesc &Prev); 586 /// Returns the induction kind of Phi. This function may return NoInduction 587 /// if the PHI is not an induction variable. 588 InductionKind isInductionVariable(PHINode *Phi); 589 590 /// The loop that we evaluate. 591 Loop *TheLoop; 592 /// Scev analysis. 593 ScalarEvolution *SE; 594 /// DataLayout analysis. 595 DataLayout *DL; 596 /// Dominators. 597 DominatorTree *DT; 598 /// Target Library Info. 599 TargetLibraryInfo *TLI; 600 601 // --- vectorization state --- // 602 603 /// Holds the integer induction variable. This is the counter of the 604 /// loop. 605 PHINode *Induction; 606 /// Holds the reduction variables. 607 ReductionList Reductions; 608 /// Holds all of the induction variables that we found in the loop. 609 /// Notice that inductions don't need to start at zero and that induction 610 /// variables can be pointers. 611 InductionList Inductions; 612 /// Holds the widest induction type encountered. 613 Type *WidestIndTy; 614 615 /// Allowed outside users. This holds the reduction 616 /// vars which can be accessed from outside the loop. 617 SmallPtrSet<Value*, 4> AllowedExit; 618 /// This set holds the variables which are known to be uniform after 619 /// vectorization. 620 SmallPtrSet<Instruction*, 4> Uniforms; 621 /// We need to check that all of the pointers in this list are disjoint 622 /// at runtime. 623 RuntimePointerCheck PtrRtCheck; 624 /// Can we assume the absence of NaNs. 625 bool HasFunNoNaNAttr; 626 627 unsigned MaxSafeDepDistBytes; 628}; 629 630/// LoopVectorizationCostModel - estimates the expected speedups due to 631/// vectorization. 632/// In many cases vectorization is not profitable. This can happen because of 633/// a number of reasons. In this class we mainly attempt to predict the 634/// expected speedup/slowdowns due to the supported instruction set. We use the 635/// TargetTransformInfo to query the different backends for the cost of 636/// different operations. 637class LoopVectorizationCostModel { 638public: 639 LoopVectorizationCostModel(Loop *L, ScalarEvolution *SE, LoopInfo *LI, 640 LoopVectorizationLegality *Legal, 641 const TargetTransformInfo &TTI, 642 DataLayout *DL, const TargetLibraryInfo *TLI) 643 : TheLoop(L), SE(SE), LI(LI), Legal(Legal), TTI(TTI), DL(DL), TLI(TLI) {} 644 645 /// Information about vectorization costs 646 struct VectorizationFactor { 647 unsigned Width; // Vector width with best cost 648 unsigned Cost; // Cost of the loop with that width 649 }; 650 /// \return The most profitable vectorization factor and the cost of that VF. 651 /// This method checks every power of two up to VF. If UserVF is not ZERO 652 /// then this vectorization factor will be selected if vectorization is 653 /// possible. 654 VectorizationFactor selectVectorizationFactor(bool OptForSize, 655 unsigned UserVF); 656 657 /// \return The size (in bits) of the widest type in the code that 658 /// needs to be vectorized. We ignore values that remain scalar such as 659 /// 64 bit loop indices. 660 unsigned getWidestType(); 661 662 /// \return The most profitable unroll factor. 663 /// If UserUF is non-zero then this method finds the best unroll-factor 664 /// based on register pressure and other parameters. 665 /// VF and LoopCost are the selected vectorization factor and the cost of the 666 /// selected VF. 667 unsigned selectUnrollFactor(bool OptForSize, unsigned UserUF, unsigned VF, 668 unsigned LoopCost); 669 670 /// \brief A struct that represents some properties of the register usage 671 /// of a loop. 672 struct RegisterUsage { 673 /// Holds the number of loop invariant values that are used in the loop. 674 unsigned LoopInvariantRegs; 675 /// Holds the maximum number of concurrent live intervals in the loop. 676 unsigned MaxLocalUsers; 677 /// Holds the number of instructions in the loop. 678 unsigned NumInstructions; 679 }; 680 681 /// \return information about the register usage of the loop. 682 RegisterUsage calculateRegisterUsage(); 683 684private: 685 /// Returns the expected execution cost. The unit of the cost does 686 /// not matter because we use the 'cost' units to compare different 687 /// vector widths. The cost that is returned is *not* normalized by 688 /// the factor width. 689 unsigned expectedCost(unsigned VF); 690 691 /// Returns the execution time cost of an instruction for a given vector 692 /// width. Vector width of one means scalar. 693 unsigned getInstructionCost(Instruction *I, unsigned VF); 694 695 /// A helper function for converting Scalar types to vector types. 696 /// If the incoming type is void, we return void. If the VF is 1, we return 697 /// the scalar type. 698 static Type* ToVectorTy(Type *Scalar, unsigned VF); 699 700 /// Returns whether the instruction is a load or store and will be a emitted 701 /// as a vector operation. 702 bool isConsecutiveLoadOrStore(Instruction *I); 703 704 /// The loop that we evaluate. 705 Loop *TheLoop; 706 /// Scev analysis. 707 ScalarEvolution *SE; 708 /// Loop Info analysis. 709 LoopInfo *LI; 710 /// Vectorization legality. 711 LoopVectorizationLegality *Legal; 712 /// Vector target information. 713 const TargetTransformInfo &TTI; 714 /// Target data layout information. 715 DataLayout *DL; 716 /// Target Library Info. 717 const TargetLibraryInfo *TLI; 718}; 719 720/// Utility class for getting and setting loop vectorizer hints in the form 721/// of loop metadata. 722struct LoopVectorizeHints { 723 /// Vectorization width. 724 unsigned Width; 725 /// Vectorization unroll factor. 726 unsigned Unroll; 727 728 LoopVectorizeHints(const Loop *L) 729 : Width(VectorizationFactor) 730 , Unroll(VectorizationUnroll) 731 , LoopID(L->getLoopID()) { 732 getHints(L); 733 // The command line options override any loop metadata except for when 734 // width == 1 which is used to indicate the loop is already vectorized. 735 if (VectorizationFactor.getNumOccurrences() > 0 && Width != 1) 736 Width = VectorizationFactor; 737 if (VectorizationUnroll.getNumOccurrences() > 0) 738 Unroll = VectorizationUnroll; 739 } 740 741 /// Return the loop vectorizer metadata prefix. 742 static StringRef Prefix() { return "llvm.vectorizer."; } 743 744 MDNode *createHint(LLVMContext &Context, StringRef Name, unsigned V) { 745 SmallVector<Value*, 2> Vals; 746 Vals.push_back(MDString::get(Context, Name)); 747 Vals.push_back(ConstantInt::get(Type::getInt32Ty(Context), V)); 748 return MDNode::get(Context, Vals); 749 } 750 751 /// Mark the loop L as already vectorized by setting the width to 1. 752 void setAlreadyVectorized(Loop *L) { 753 LLVMContext &Context = L->getHeader()->getContext(); 754 755 Width = 1; 756 757 // Create a new loop id with one more operand for the already_vectorized 758 // hint. If the loop already has a loop id then copy the existing operands. 759 SmallVector<Value*, 4> Vals(1); 760 if (LoopID) 761 for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) 762 Vals.push_back(LoopID->getOperand(i)); 763 764 Vals.push_back(createHint(Context, Twine(Prefix(), "width").str(), Width)); 765 766 MDNode *NewLoopID = MDNode::get(Context, Vals); 767 // Set operand 0 to refer to the loop id itself. 768 NewLoopID->replaceOperandWith(0, NewLoopID); 769 770 L->setLoopID(NewLoopID); 771 if (LoopID) 772 LoopID->replaceAllUsesWith(NewLoopID); 773 774 LoopID = NewLoopID; 775 } 776 777private: 778 MDNode *LoopID; 779 780 /// Find hints specified in the loop metadata. 781 void getHints(const Loop *L) { 782 if (!LoopID) 783 return; 784 785 // First operand should refer to the loop id itself. 786 assert(LoopID->getNumOperands() > 0 && "requires at least one operand"); 787 assert(LoopID->getOperand(0) == LoopID && "invalid loop id"); 788 789 for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) { 790 const MDString *S = 0; 791 SmallVector<Value*, 4> Args; 792 793 // The expected hint is either a MDString or a MDNode with the first 794 // operand a MDString. 795 if (const MDNode *MD = dyn_cast<MDNode>(LoopID->getOperand(i))) { 796 if (!MD || MD->getNumOperands() == 0) 797 continue; 798 S = dyn_cast<MDString>(MD->getOperand(0)); 799 for (unsigned i = 1, ie = MD->getNumOperands(); i < ie; ++i) 800 Args.push_back(MD->getOperand(i)); 801 } else { 802 S = dyn_cast<MDString>(LoopID->getOperand(i)); 803 assert(Args.size() == 0 && "too many arguments for MDString"); 804 } 805 806 if (!S) 807 continue; 808 809 // Check if the hint starts with the vectorizer prefix. 810 StringRef Hint = S->getString(); 811 if (!Hint.startswith(Prefix())) 812 continue; 813 // Remove the prefix. 814 Hint = Hint.substr(Prefix().size(), StringRef::npos); 815 816 if (Args.size() == 1) 817 getHint(Hint, Args[0]); 818 } 819 } 820 821 // Check string hint with one operand. 822 void getHint(StringRef Hint, Value *Arg) { 823 const ConstantInt *C = dyn_cast<ConstantInt>(Arg); 824 if (!C) return; 825 unsigned Val = C->getZExtValue(); 826 827 if (Hint == "width") { 828 assert(isPowerOf2_32(Val) && Val <= MaxVectorWidth && 829 "Invalid width metadata"); 830 Width = Val; 831 } else if (Hint == "unroll") { 832 assert(isPowerOf2_32(Val) && Val <= MaxUnrollFactor && 833 "Invalid unroll metadata"); 834 Unroll = Val; 835 } else 836 DEBUG(dbgs() << "LV: ignoring unknown hint " << Hint); 837 } 838}; 839 840/// The LoopVectorize Pass. 841struct LoopVectorize : public LoopPass { 842 /// Pass identification, replacement for typeid 843 static char ID; 844 845 explicit LoopVectorize() : LoopPass(ID) { 846 initializeLoopVectorizePass(*PassRegistry::getPassRegistry()); 847 } 848 849 ScalarEvolution *SE; 850 DataLayout *DL; 851 LoopInfo *LI; 852 TargetTransformInfo *TTI; 853 DominatorTree *DT; 854 TargetLibraryInfo *TLI; 855 856 virtual bool runOnLoop(Loop *L, LPPassManager &LPM) { 857 // We only vectorize innermost loops. 858 if (!L->empty()) 859 return false; 860 861 SE = &getAnalysis<ScalarEvolution>(); 862 DL = getAnalysisIfAvailable<DataLayout>(); 863 LI = &getAnalysis<LoopInfo>(); 864 TTI = &getAnalysis<TargetTransformInfo>(); 865 DT = &getAnalysis<DominatorTree>(); 866 TLI = getAnalysisIfAvailable<TargetLibraryInfo>(); 867 868 if (DL == NULL) { 869 DEBUG(dbgs() << "LV: Not vectorizing because of missing data layout"); 870 return false; 871 } 872 873 DEBUG(dbgs() << "LV: Checking a loop in \"" << 874 L->getHeader()->getParent()->getName() << "\"\n"); 875 876 LoopVectorizeHints Hints(L); 877 878 if (Hints.Width == 1) { 879 DEBUG(dbgs() << "LV: Not vectorizing.\n"); 880 return false; 881 } 882 883 // Check if it is legal to vectorize the loop. 884 LoopVectorizationLegality LVL(L, SE, DL, DT, TLI); 885 if (!LVL.canVectorize()) { 886 DEBUG(dbgs() << "LV: Not vectorizing.\n"); 887 return false; 888 } 889 890 // Use the cost model. 891 LoopVectorizationCostModel CM(L, SE, LI, &LVL, *TTI, DL, TLI); 892 893 // Check the function attributes to find out if this function should be 894 // optimized for size. 895 Function *F = L->getHeader()->getParent(); 896 Attribute::AttrKind SzAttr = Attribute::OptimizeForSize; 897 Attribute::AttrKind FlAttr = Attribute::NoImplicitFloat; 898 unsigned FnIndex = AttributeSet::FunctionIndex; 899 bool OptForSize = F->getAttributes().hasAttribute(FnIndex, SzAttr); 900 bool NoFloat = F->getAttributes().hasAttribute(FnIndex, FlAttr); 901 902 if (NoFloat) { 903 DEBUG(dbgs() << "LV: Can't vectorize when the NoImplicitFloat" 904 "attribute is used.\n"); 905 return false; 906 } 907 908 // Select the optimal vectorization factor. 909 LoopVectorizationCostModel::VectorizationFactor VF; 910 VF = CM.selectVectorizationFactor(OptForSize, Hints.Width); 911 // Select the unroll factor. 912 unsigned UF = CM.selectUnrollFactor(OptForSize, Hints.Unroll, VF.Width, 913 VF.Cost); 914 915 if (VF.Width == 1) { 916 DEBUG(dbgs() << "LV: Vectorization is possible but not beneficial.\n"); 917 return false; 918 } 919 920 DEBUG(dbgs() << "LV: Found a vectorizable loop ("<< VF.Width << ") in "<< 921 F->getParent()->getModuleIdentifier()<<"\n"); 922 DEBUG(dbgs() << "LV: Unroll Factor is " << UF << "\n"); 923 924 // If we decided that it is *legal* to vectorize the loop then do it. 925 InnerLoopVectorizer LB(L, SE, LI, DT, DL, TLI, VF.Width, UF); 926 LB.vectorize(&LVL); 927 928 // Mark the loop as already vectorized to avoid vectorizing again. 929 Hints.setAlreadyVectorized(L); 930 931 DEBUG(verifyFunction(*L->getHeader()->getParent())); 932 return true; 933 } 934 935 virtual void getAnalysisUsage(AnalysisUsage &AU) const { 936 LoopPass::getAnalysisUsage(AU); 937 AU.addRequiredID(LoopSimplifyID); 938 AU.addRequiredID(LCSSAID); 939 AU.addRequired<DominatorTree>(); 940 AU.addRequired<LoopInfo>(); 941 AU.addRequired<ScalarEvolution>(); 942 AU.addRequired<TargetTransformInfo>(); 943 AU.addPreserved<LoopInfo>(); 944 AU.addPreserved<DominatorTree>(); 945 } 946 947}; 948 949} // end anonymous namespace 950 951//===----------------------------------------------------------------------===// 952// Implementation of LoopVectorizationLegality, InnerLoopVectorizer and 953// LoopVectorizationCostModel. 954//===----------------------------------------------------------------------===// 955 956void 957LoopVectorizationLegality::RuntimePointerCheck::insert(ScalarEvolution *SE, 958 Loop *Lp, Value *Ptr, 959 bool WritePtr, 960 unsigned DepSetId) { 961 const SCEV *Sc = SE->getSCEV(Ptr); 962 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Sc); 963 assert(AR && "Invalid addrec expression"); 964 const SCEV *Ex = SE->getBackedgeTakenCount(Lp); 965 const SCEV *ScEnd = AR->evaluateAtIteration(Ex, *SE); 966 Pointers.push_back(Ptr); 967 Starts.push_back(AR->getStart()); 968 Ends.push_back(ScEnd); 969 IsWritePtr.push_back(WritePtr); 970 DependencySetId.push_back(DepSetId); 971} 972 973Value *InnerLoopVectorizer::getBroadcastInstrs(Value *V) { 974 // Save the current insertion location. 975 Instruction *Loc = Builder.GetInsertPoint(); 976 977 // We need to place the broadcast of invariant variables outside the loop. 978 Instruction *Instr = dyn_cast<Instruction>(V); 979 bool NewInstr = (Instr && Instr->getParent() == LoopVectorBody); 980 bool Invariant = OrigLoop->isLoopInvariant(V) && !NewInstr; 981 982 // Place the code for broadcasting invariant variables in the new preheader. 983 if (Invariant) 984 Builder.SetInsertPoint(LoopVectorPreHeader->getTerminator()); 985 986 // Broadcast the scalar into all locations in the vector. 987 Value *Shuf = Builder.CreateVectorSplat(VF, V, "broadcast"); 988 989 // Restore the builder insertion point. 990 if (Invariant) 991 Builder.SetInsertPoint(Loc); 992 993 return Shuf; 994} 995 996Value *InnerLoopVectorizer::getConsecutiveVector(Value* Val, int StartIdx, 997 bool Negate) { 998 assert(Val->getType()->isVectorTy() && "Must be a vector"); 999 assert(Val->getType()->getScalarType()->isIntegerTy() && 1000 "Elem must be an integer"); 1001 // Create the types. 1002 Type *ITy = Val->getType()->getScalarType(); 1003 VectorType *Ty = cast<VectorType>(Val->getType()); 1004 int VLen = Ty->getNumElements(); 1005 SmallVector<Constant*, 8> Indices; 1006 1007 // Create a vector of consecutive numbers from zero to VF. 1008 for (int i = 0; i < VLen; ++i) { 1009 int64_t Idx = Negate ? (-i) : i; 1010 Indices.push_back(ConstantInt::get(ITy, StartIdx + Idx, Negate)); 1011 } 1012 1013 // Add the consecutive indices to the vector value. 1014 Constant *Cv = ConstantVector::get(Indices); 1015 assert(Cv->getType() == Val->getType() && "Invalid consecutive vec"); 1016 return Builder.CreateAdd(Val, Cv, "induction"); 1017} 1018 1019int LoopVectorizationLegality::isConsecutivePtr(Value *Ptr) { 1020 assert(Ptr->getType()->isPointerTy() && "Unexpected non ptr"); 1021 // Make sure that the pointer does not point to structs. 1022 if (cast<PointerType>(Ptr->getType())->getElementType()->isAggregateType()) 1023 return 0; 1024 1025 // If this value is a pointer induction variable we know it is consecutive. 1026 PHINode *Phi = dyn_cast_or_null<PHINode>(Ptr); 1027 if (Phi && Inductions.count(Phi)) { 1028 InductionInfo II = Inductions[Phi]; 1029 if (IK_PtrInduction == II.IK) 1030 return 1; 1031 else if (IK_ReversePtrInduction == II.IK) 1032 return -1; 1033 } 1034 1035 GetElementPtrInst *Gep = dyn_cast_or_null<GetElementPtrInst>(Ptr); 1036 if (!Gep) 1037 return 0; 1038 1039 unsigned NumOperands = Gep->getNumOperands(); 1040 Value *LastIndex = Gep->getOperand(NumOperands - 1); 1041 1042 Value *GpPtr = Gep->getPointerOperand(); 1043 // If this GEP value is a consecutive pointer induction variable and all of 1044 // the indices are constant then we know it is consecutive. We can 1045 Phi = dyn_cast<PHINode>(GpPtr); 1046 if (Phi && Inductions.count(Phi)) { 1047 1048 // Make sure that the pointer does not point to structs. 1049 PointerType *GepPtrType = cast<PointerType>(GpPtr->getType()); 1050 if (GepPtrType->getElementType()->isAggregateType()) 1051 return 0; 1052 1053 // Make sure that all of the index operands are loop invariant. 1054 for (unsigned i = 1; i < NumOperands; ++i) 1055 if (!SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop)) 1056 return 0; 1057 1058 InductionInfo II = Inductions[Phi]; 1059 if (IK_PtrInduction == II.IK) 1060 return 1; 1061 else if (IK_ReversePtrInduction == II.IK) 1062 return -1; 1063 } 1064 1065 // Check that all of the gep indices are uniform except for the last. 1066 for (unsigned i = 0; i < NumOperands - 1; ++i) 1067 if (!SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop)) 1068 return 0; 1069 1070 // We can emit wide load/stores only if the last index is the induction 1071 // variable. 1072 const SCEV *Last = SE->getSCEV(LastIndex); 1073 if (const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Last)) { 1074 const SCEV *Step = AR->getStepRecurrence(*SE); 1075 1076 // The memory is consecutive because the last index is consecutive 1077 // and all other indices are loop invariant. 1078 if (Step->isOne()) 1079 return 1; 1080 if (Step->isAllOnesValue()) 1081 return -1; 1082 } 1083 1084 return 0; 1085} 1086 1087bool LoopVectorizationLegality::isUniform(Value *V) { 1088 return (SE->isLoopInvariant(SE->getSCEV(V), TheLoop)); 1089} 1090 1091InnerLoopVectorizer::VectorParts& 1092InnerLoopVectorizer::getVectorValue(Value *V) { 1093 assert(V != Induction && "The new induction variable should not be used."); 1094 assert(!V->getType()->isVectorTy() && "Can't widen a vector"); 1095 1096 // If we have this scalar in the map, return it. 1097 if (WidenMap.has(V)) 1098 return WidenMap.get(V); 1099 1100 // If this scalar is unknown, assume that it is a constant or that it is 1101 // loop invariant. Broadcast V and save the value for future uses. 1102 Value *B = getBroadcastInstrs(V); 1103 return WidenMap.splat(V, B); 1104} 1105 1106Value *InnerLoopVectorizer::reverseVector(Value *Vec) { 1107 assert(Vec->getType()->isVectorTy() && "Invalid type"); 1108 SmallVector<Constant*, 8> ShuffleMask; 1109 for (unsigned i = 0; i < VF; ++i) 1110 ShuffleMask.push_back(Builder.getInt32(VF - i - 1)); 1111 1112 return Builder.CreateShuffleVector(Vec, UndefValue::get(Vec->getType()), 1113 ConstantVector::get(ShuffleMask), 1114 "reverse"); 1115} 1116 1117 1118void InnerLoopVectorizer::vectorizeMemoryInstruction(Instruction *Instr, 1119 LoopVectorizationLegality *Legal) { 1120 // Attempt to issue a wide load. 1121 LoadInst *LI = dyn_cast<LoadInst>(Instr); 1122 StoreInst *SI = dyn_cast<StoreInst>(Instr); 1123 1124 assert((LI || SI) && "Invalid Load/Store instruction"); 1125 1126 Type *ScalarDataTy = LI ? LI->getType() : SI->getValueOperand()->getType(); 1127 Type *DataTy = VectorType::get(ScalarDataTy, VF); 1128 Value *Ptr = LI ? LI->getPointerOperand() : SI->getPointerOperand(); 1129 unsigned Alignment = LI ? LI->getAlignment() : SI->getAlignment(); 1130 unsigned AddressSpace = Ptr->getType()->getPointerAddressSpace(); 1131 unsigned ScalarAllocatedSize = DL->getTypeAllocSize(ScalarDataTy); 1132 unsigned VectorElementSize = DL->getTypeStoreSize(DataTy)/VF; 1133 1134 if (ScalarAllocatedSize != VectorElementSize) 1135 return scalarizeInstruction(Instr); 1136 1137 // If the pointer is loop invariant or if it is non consecutive, 1138 // scalarize the load. 1139 int ConsecutiveStride = Legal->isConsecutivePtr(Ptr); 1140 bool Reverse = ConsecutiveStride < 0; 1141 bool UniformLoad = LI && Legal->isUniform(Ptr); 1142 if (!ConsecutiveStride || UniformLoad) 1143 return scalarizeInstruction(Instr); 1144 1145 Constant *Zero = Builder.getInt32(0); 1146 VectorParts &Entry = WidenMap.get(Instr); 1147 1148 // Handle consecutive loads/stores. 1149 GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr); 1150 if (Gep && Legal->isInductionVariable(Gep->getPointerOperand())) { 1151 setDebugLocFromInst(Builder, Gep); 1152 Value *PtrOperand = Gep->getPointerOperand(); 1153 Value *FirstBasePtr = getVectorValue(PtrOperand)[0]; 1154 FirstBasePtr = Builder.CreateExtractElement(FirstBasePtr, Zero); 1155 1156 // Create the new GEP with the new induction variable. 1157 GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone()); 1158 Gep2->setOperand(0, FirstBasePtr); 1159 Gep2->setName("gep.indvar.base"); 1160 Ptr = Builder.Insert(Gep2); 1161 } else if (Gep) { 1162 setDebugLocFromInst(Builder, Gep); 1163 assert(SE->isLoopInvariant(SE->getSCEV(Gep->getPointerOperand()), 1164 OrigLoop) && "Base ptr must be invariant"); 1165 1166 // The last index does not have to be the induction. It can be 1167 // consecutive and be a function of the index. For example A[I+1]; 1168 unsigned NumOperands = Gep->getNumOperands(); 1169 unsigned LastOperand = NumOperands - 1; 1170 // Create the new GEP with the new induction variable. 1171 GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone()); 1172 1173 for (unsigned i = 0; i < NumOperands; ++i) { 1174 Value *GepOperand = Gep->getOperand(i); 1175 Instruction *GepOperandInst = dyn_cast<Instruction>(GepOperand); 1176 1177 // Update last index or loop invariant instruction anchored in loop. 1178 if (i == LastOperand || 1179 (GepOperandInst && OrigLoop->contains(GepOperandInst))) { 1180 assert((i == LastOperand || 1181 SE->isLoopInvariant(SE->getSCEV(GepOperandInst), OrigLoop)) && 1182 "Must be last index or loop invariant"); 1183 1184 VectorParts &GEPParts = getVectorValue(GepOperand); 1185 Value *Index = GEPParts[0]; 1186 Index = Builder.CreateExtractElement(Index, Zero); 1187 Gep2->setOperand(i, Index); 1188 Gep2->setName("gep.indvar.idx"); 1189 } 1190 } 1191 Ptr = Builder.Insert(Gep2); 1192 } else { 1193 // Use the induction element ptr. 1194 assert(isa<PHINode>(Ptr) && "Invalid induction ptr"); 1195 setDebugLocFromInst(Builder, Ptr); 1196 VectorParts &PtrVal = getVectorValue(Ptr); 1197 Ptr = Builder.CreateExtractElement(PtrVal[0], Zero); 1198 } 1199 1200 // Handle Stores: 1201 if (SI) { 1202 assert(!Legal->isUniform(SI->getPointerOperand()) && 1203 "We do not allow storing to uniform addresses"); 1204 setDebugLocFromInst(Builder, SI); 1205 // We don't want to update the value in the map as it might be used in 1206 // another expression. So don't use a reference type for "StoredVal". 1207 VectorParts StoredVal = getVectorValue(SI->getValueOperand()); 1208 1209 for (unsigned Part = 0; Part < UF; ++Part) { 1210 // Calculate the pointer for the specific unroll-part. 1211 Value *PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(Part * VF)); 1212 1213 if (Reverse) { 1214 // If we store to reverse consecutive memory locations then we need 1215 // to reverse the order of elements in the stored value. 1216 StoredVal[Part] = reverseVector(StoredVal[Part]); 1217 // If the address is consecutive but reversed, then the 1218 // wide store needs to start at the last vector element. 1219 PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(-Part * VF)); 1220 PartPtr = Builder.CreateGEP(PartPtr, Builder.getInt32(1 - VF)); 1221 } 1222 1223 Value *VecPtr = Builder.CreateBitCast(PartPtr, 1224 DataTy->getPointerTo(AddressSpace)); 1225 Builder.CreateStore(StoredVal[Part], VecPtr)->setAlignment(Alignment); 1226 } 1227 return; 1228 } 1229 1230 // Handle loads. 1231 assert(LI && "Must have a load instruction"); 1232 setDebugLocFromInst(Builder, LI); 1233 for (unsigned Part = 0; Part < UF; ++Part) { 1234 // Calculate the pointer for the specific unroll-part. 1235 Value *PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(Part * VF)); 1236 1237 if (Reverse) { 1238 // If the address is consecutive but reversed, then the 1239 // wide store needs to start at the last vector element. 1240 PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(-Part * VF)); 1241 PartPtr = Builder.CreateGEP(PartPtr, Builder.getInt32(1 - VF)); 1242 } 1243 1244 Value *VecPtr = Builder.CreateBitCast(PartPtr, 1245 DataTy->getPointerTo(AddressSpace)); 1246 Value *LI = Builder.CreateLoad(VecPtr, "wide.load"); 1247 cast<LoadInst>(LI)->setAlignment(Alignment); 1248 Entry[Part] = Reverse ? reverseVector(LI) : LI; 1249 } 1250} 1251 1252void InnerLoopVectorizer::scalarizeInstruction(Instruction *Instr) { 1253 assert(!Instr->getType()->isAggregateType() && "Can't handle vectors"); 1254 // Holds vector parameters or scalars, in case of uniform vals. 1255 SmallVector<VectorParts, 4> Params; 1256 1257 setDebugLocFromInst(Builder, Instr); 1258 1259 // Find all of the vectorized parameters. 1260 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) { 1261 Value *SrcOp = Instr->getOperand(op); 1262 1263 // If we are accessing the old induction variable, use the new one. 1264 if (SrcOp == OldInduction) { 1265 Params.push_back(getVectorValue(SrcOp)); 1266 continue; 1267 } 1268 1269 // Try using previously calculated values. 1270 Instruction *SrcInst = dyn_cast<Instruction>(SrcOp); 1271 1272 // If the src is an instruction that appeared earlier in the basic block 1273 // then it should already be vectorized. 1274 if (SrcInst && OrigLoop->contains(SrcInst)) { 1275 assert(WidenMap.has(SrcInst) && "Source operand is unavailable"); 1276 // The parameter is a vector value from earlier. 1277 Params.push_back(WidenMap.get(SrcInst)); 1278 } else { 1279 // The parameter is a scalar from outside the loop. Maybe even a constant. 1280 VectorParts Scalars; 1281 Scalars.append(UF, SrcOp); 1282 Params.push_back(Scalars); 1283 } 1284 } 1285 1286 assert(Params.size() == Instr->getNumOperands() && 1287 "Invalid number of operands"); 1288 1289 // Does this instruction return a value ? 1290 bool IsVoidRetTy = Instr->getType()->isVoidTy(); 1291 1292 Value *UndefVec = IsVoidRetTy ? 0 : 1293 UndefValue::get(VectorType::get(Instr->getType(), VF)); 1294 // Create a new entry in the WidenMap and initialize it to Undef or Null. 1295 VectorParts &VecResults = WidenMap.splat(Instr, UndefVec); 1296 1297 // For each vector unroll 'part': 1298 for (unsigned Part = 0; Part < UF; ++Part) { 1299 // For each scalar that we create: 1300 for (unsigned Width = 0; Width < VF; ++Width) { 1301 Instruction *Cloned = Instr->clone(); 1302 if (!IsVoidRetTy) 1303 Cloned->setName(Instr->getName() + ".cloned"); 1304 // Replace the operands of the cloned instrucions with extracted scalars. 1305 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) { 1306 Value *Op = Params[op][Part]; 1307 // Param is a vector. Need to extract the right lane. 1308 if (Op->getType()->isVectorTy()) 1309 Op = Builder.CreateExtractElement(Op, Builder.getInt32(Width)); 1310 Cloned->setOperand(op, Op); 1311 } 1312 1313 // Place the cloned scalar in the new loop. 1314 Builder.Insert(Cloned); 1315 1316 // If the original scalar returns a value we need to place it in a vector 1317 // so that future users will be able to use it. 1318 if (!IsVoidRetTy) 1319 VecResults[Part] = Builder.CreateInsertElement(VecResults[Part], Cloned, 1320 Builder.getInt32(Width)); 1321 } 1322 } 1323} 1324 1325Instruction * 1326InnerLoopVectorizer::addRuntimeCheck(LoopVectorizationLegality *Legal, 1327 Instruction *Loc) { 1328 LoopVectorizationLegality::RuntimePointerCheck *PtrRtCheck = 1329 Legal->getRuntimePointerCheck(); 1330 1331 if (!PtrRtCheck->Need) 1332 return NULL; 1333 1334 unsigned NumPointers = PtrRtCheck->Pointers.size(); 1335 SmallVector<TrackingVH<Value> , 2> Starts; 1336 SmallVector<TrackingVH<Value> , 2> Ends; 1337 1338 SCEVExpander Exp(*SE, "induction"); 1339 1340 // Use this type for pointer arithmetic. 1341 Type* PtrArithTy = Type::getInt8PtrTy(Loc->getContext(), 0); 1342 1343 for (unsigned i = 0; i < NumPointers; ++i) { 1344 Value *Ptr = PtrRtCheck->Pointers[i]; 1345 const SCEV *Sc = SE->getSCEV(Ptr); 1346 1347 if (SE->isLoopInvariant(Sc, OrigLoop)) { 1348 DEBUG(dbgs() << "LV: Adding RT check for a loop invariant ptr:" << 1349 *Ptr <<"\n"); 1350 Starts.push_back(Ptr); 1351 Ends.push_back(Ptr); 1352 } else { 1353 DEBUG(dbgs() << "LV: Adding RT check for range:" << *Ptr <<"\n"); 1354 1355 Value *Start = Exp.expandCodeFor(PtrRtCheck->Starts[i], PtrArithTy, Loc); 1356 Value *End = Exp.expandCodeFor(PtrRtCheck->Ends[i], PtrArithTy, Loc); 1357 Starts.push_back(Start); 1358 Ends.push_back(End); 1359 } 1360 } 1361 1362 IRBuilder<> ChkBuilder(Loc); 1363 // Our instructions might fold to a constant. 1364 Value *MemoryRuntimeCheck = 0; 1365 for (unsigned i = 0; i < NumPointers; ++i) { 1366 for (unsigned j = i+1; j < NumPointers; ++j) { 1367 // No need to check if two readonly pointers intersect. 1368 if (!PtrRtCheck->IsWritePtr[i] && !PtrRtCheck->IsWritePtr[j]) 1369 continue; 1370 1371 // Only need to check pointers between two different dependency sets. 1372 if (PtrRtCheck->DependencySetId[i] == PtrRtCheck->DependencySetId[j]) 1373 continue; 1374 1375 Value *Start0 = ChkBuilder.CreateBitCast(Starts[i], PtrArithTy, "bc"); 1376 Value *Start1 = ChkBuilder.CreateBitCast(Starts[j], PtrArithTy, "bc"); 1377 Value *End0 = ChkBuilder.CreateBitCast(Ends[i], PtrArithTy, "bc"); 1378 Value *End1 = ChkBuilder.CreateBitCast(Ends[j], PtrArithTy, "bc"); 1379 1380 Value *Cmp0 = ChkBuilder.CreateICmpULE(Start0, End1, "bound0"); 1381 Value *Cmp1 = ChkBuilder.CreateICmpULE(Start1, End0, "bound1"); 1382 Value *IsConflict = ChkBuilder.CreateAnd(Cmp0, Cmp1, "found.conflict"); 1383 if (MemoryRuntimeCheck) 1384 IsConflict = ChkBuilder.CreateOr(MemoryRuntimeCheck, IsConflict, 1385 "conflict.rdx"); 1386 MemoryRuntimeCheck = IsConflict; 1387 } 1388 } 1389 1390 // We have to do this trickery because the IRBuilder might fold the check to a 1391 // constant expression in which case there is no Instruction anchored in a 1392 // the block. 1393 LLVMContext &Ctx = Loc->getContext(); 1394 Instruction * Check = BinaryOperator::CreateAnd(MemoryRuntimeCheck, 1395 ConstantInt::getTrue(Ctx)); 1396 ChkBuilder.Insert(Check, "memcheck.conflict"); 1397 return Check; 1398} 1399 1400void 1401InnerLoopVectorizer::createEmptyLoop(LoopVectorizationLegality *Legal) { 1402 /* 1403 In this function we generate a new loop. The new loop will contain 1404 the vectorized instructions while the old loop will continue to run the 1405 scalar remainder. 1406 1407 [ ] <-- vector loop bypass (may consist of multiple blocks). 1408 / | 1409 / v 1410 | [ ] <-- vector pre header. 1411 | | 1412 | v 1413 | [ ] \ 1414 | [ ]_| <-- vector loop. 1415 | | 1416 \ v 1417 >[ ] <--- middle-block. 1418 / | 1419 / v 1420 | [ ] <--- new preheader. 1421 | | 1422 | v 1423 | [ ] \ 1424 | [ ]_| <-- old scalar loop to handle remainder. 1425 \ | 1426 \ v 1427 >[ ] <-- exit block. 1428 ... 1429 */ 1430 1431 BasicBlock *OldBasicBlock = OrigLoop->getHeader(); 1432 BasicBlock *BypassBlock = OrigLoop->getLoopPreheader(); 1433 BasicBlock *ExitBlock = OrigLoop->getExitBlock(); 1434 assert(ExitBlock && "Must have an exit block"); 1435 1436 // Some loops have a single integer induction variable, while other loops 1437 // don't. One example is c++ iterators that often have multiple pointer 1438 // induction variables. In the code below we also support a case where we 1439 // don't have a single induction variable. 1440 OldInduction = Legal->getInduction(); 1441 Type *IdxTy = Legal->getWidestInductionType(); 1442 1443 // Find the loop boundaries. 1444 const SCEV *ExitCount = SE->getBackedgeTakenCount(OrigLoop); 1445 assert(ExitCount != SE->getCouldNotCompute() && "Invalid loop count"); 1446 1447 // Get the total trip count from the count by adding 1. 1448 ExitCount = SE->getAddExpr(ExitCount, 1449 SE->getConstant(ExitCount->getType(), 1)); 1450 1451 // Expand the trip count and place the new instructions in the preheader. 1452 // Notice that the pre-header does not change, only the loop body. 1453 SCEVExpander Exp(*SE, "induction"); 1454 1455 // Count holds the overall loop count (N). 1456 Value *Count = Exp.expandCodeFor(ExitCount, ExitCount->getType(), 1457 BypassBlock->getTerminator()); 1458 1459 // The loop index does not have to start at Zero. Find the original start 1460 // value from the induction PHI node. If we don't have an induction variable 1461 // then we know that it starts at zero. 1462 Builder.SetInsertPoint(BypassBlock->getTerminator()); 1463 Value *StartIdx = ExtendedIdx = OldInduction ? 1464 Builder.CreateZExt(OldInduction->getIncomingValueForBlock(BypassBlock), 1465 IdxTy): 1466 ConstantInt::get(IdxTy, 0); 1467 1468 assert(BypassBlock && "Invalid loop structure"); 1469 LoopBypassBlocks.push_back(BypassBlock); 1470 1471 // Split the single block loop into the two loop structure described above. 1472 BasicBlock *VectorPH = 1473 BypassBlock->splitBasicBlock(BypassBlock->getTerminator(), "vector.ph"); 1474 BasicBlock *VecBody = 1475 VectorPH->splitBasicBlock(VectorPH->getTerminator(), "vector.body"); 1476 BasicBlock *MiddleBlock = 1477 VecBody->splitBasicBlock(VecBody->getTerminator(), "middle.block"); 1478 BasicBlock *ScalarPH = 1479 MiddleBlock->splitBasicBlock(MiddleBlock->getTerminator(), "scalar.ph"); 1480 1481 // Create and register the new vector loop. 1482 Loop* Lp = new Loop(); 1483 Loop *ParentLoop = OrigLoop->getParentLoop(); 1484 1485 // Insert the new loop into the loop nest and register the new basic blocks 1486 // before calling any utilities such as SCEV that require valid LoopInfo. 1487 if (ParentLoop) { 1488 ParentLoop->addChildLoop(Lp); 1489 ParentLoop->addBasicBlockToLoop(ScalarPH, LI->getBase()); 1490 ParentLoop->addBasicBlockToLoop(VectorPH, LI->getBase()); 1491 ParentLoop->addBasicBlockToLoop(MiddleBlock, LI->getBase()); 1492 } else { 1493 LI->addTopLevelLoop(Lp); 1494 } 1495 Lp->addBasicBlockToLoop(VecBody, LI->getBase()); 1496 1497 // Use this IR builder to create the loop instructions (Phi, Br, Cmp) 1498 // inside the loop. 1499 Builder.SetInsertPoint(VecBody->getFirstInsertionPt()); 1500 1501 // Generate the induction variable. 1502 setDebugLocFromInst(Builder, getDebugLocFromInstOrOperands(OldInduction)); 1503 Induction = Builder.CreatePHI(IdxTy, 2, "index"); 1504 // The loop step is equal to the vectorization factor (num of SIMD elements) 1505 // times the unroll factor (num of SIMD instructions). 1506 Constant *Step = ConstantInt::get(IdxTy, VF * UF); 1507 1508 // This is the IR builder that we use to add all of the logic for bypassing 1509 // the new vector loop. 1510 IRBuilder<> BypassBuilder(BypassBlock->getTerminator()); 1511 setDebugLocFromInst(BypassBuilder, 1512 getDebugLocFromInstOrOperands(OldInduction)); 1513 1514 // We may need to extend the index in case there is a type mismatch. 1515 // We know that the count starts at zero and does not overflow. 1516 if (Count->getType() != IdxTy) { 1517 // The exit count can be of pointer type. Convert it to the correct 1518 // integer type. 1519 if (ExitCount->getType()->isPointerTy()) 1520 Count = BypassBuilder.CreatePointerCast(Count, IdxTy, "ptrcnt.to.int"); 1521 else 1522 Count = BypassBuilder.CreateZExtOrTrunc(Count, IdxTy, "cnt.cast"); 1523 } 1524 1525 // Add the start index to the loop count to get the new end index. 1526 Value *IdxEnd = BypassBuilder.CreateAdd(Count, StartIdx, "end.idx"); 1527 1528 // Now we need to generate the expression for N - (N % VF), which is 1529 // the part that the vectorized body will execute. 1530 Value *R = BypassBuilder.CreateURem(Count, Step, "n.mod.vf"); 1531 Value *CountRoundDown = BypassBuilder.CreateSub(Count, R, "n.vec"); 1532 Value *IdxEndRoundDown = BypassBuilder.CreateAdd(CountRoundDown, StartIdx, 1533 "end.idx.rnd.down"); 1534 1535 // Now, compare the new count to zero. If it is zero skip the vector loop and 1536 // jump to the scalar loop. 1537 Value *Cmp = BypassBuilder.CreateICmpEQ(IdxEndRoundDown, StartIdx, 1538 "cmp.zero"); 1539 1540 BasicBlock *LastBypassBlock = BypassBlock; 1541 1542 // Generate the code that checks in runtime if arrays overlap. We put the 1543 // checks into a separate block to make the more common case of few elements 1544 // faster. 1545 Instruction *MemRuntimeCheck = addRuntimeCheck(Legal, 1546 BypassBlock->getTerminator()); 1547 if (MemRuntimeCheck) { 1548 // Create a new block containing the memory check. 1549 BasicBlock *CheckBlock = BypassBlock->splitBasicBlock(MemRuntimeCheck, 1550 "vector.memcheck"); 1551 if (ParentLoop) 1552 ParentLoop->addBasicBlockToLoop(CheckBlock, LI->getBase()); 1553 LoopBypassBlocks.push_back(CheckBlock); 1554 1555 // Replace the branch into the memory check block with a conditional branch 1556 // for the "few elements case". 1557 Instruction *OldTerm = BypassBlock->getTerminator(); 1558 BranchInst::Create(MiddleBlock, CheckBlock, Cmp, OldTerm); 1559 OldTerm->eraseFromParent(); 1560 1561 Cmp = MemRuntimeCheck; 1562 LastBypassBlock = CheckBlock; 1563 } 1564 1565 LastBypassBlock->getTerminator()->eraseFromParent(); 1566 BranchInst::Create(MiddleBlock, VectorPH, Cmp, 1567 LastBypassBlock); 1568 1569 // We are going to resume the execution of the scalar loop. 1570 // Go over all of the induction variables that we found and fix the 1571 // PHIs that are left in the scalar version of the loop. 1572 // The starting values of PHI nodes depend on the counter of the last 1573 // iteration in the vectorized loop. 1574 // If we come from a bypass edge then we need to start from the original 1575 // start value. 1576 1577 // This variable saves the new starting index for the scalar loop. 1578 PHINode *ResumeIndex = 0; 1579 LoopVectorizationLegality::InductionList::iterator I, E; 1580 LoopVectorizationLegality::InductionList *List = Legal->getInductionVars(); 1581 // Set builder to point to last bypass block. 1582 BypassBuilder.SetInsertPoint(LoopBypassBlocks.back()->getTerminator()); 1583 for (I = List->begin(), E = List->end(); I != E; ++I) { 1584 PHINode *OrigPhi = I->first; 1585 LoopVectorizationLegality::InductionInfo II = I->second; 1586 1587 Type *ResumeValTy = (OrigPhi == OldInduction) ? IdxTy : OrigPhi->getType(); 1588 PHINode *ResumeVal = PHINode::Create(ResumeValTy, 2, "resume.val", 1589 MiddleBlock->getTerminator()); 1590 // We might have extended the type of the induction variable but we need a 1591 // truncated version for the scalar loop. 1592 PHINode *TruncResumeVal = (OrigPhi == OldInduction) ? 1593 PHINode::Create(OrigPhi->getType(), 2, "trunc.resume.val", 1594 MiddleBlock->getTerminator()) : 0; 1595 1596 Value *EndValue = 0; 1597 switch (II.IK) { 1598 case LoopVectorizationLegality::IK_NoInduction: 1599 llvm_unreachable("Unknown induction"); 1600 case LoopVectorizationLegality::IK_IntInduction: { 1601 // Handle the integer induction counter. 1602 assert(OrigPhi->getType()->isIntegerTy() && "Invalid type"); 1603 1604 // We have the canonical induction variable. 1605 if (OrigPhi == OldInduction) { 1606 // Create a truncated version of the resume value for the scalar loop, 1607 // we might have promoted the type to a larger width. 1608 EndValue = 1609 BypassBuilder.CreateTrunc(IdxEndRoundDown, OrigPhi->getType()); 1610 // The new PHI merges the original incoming value, in case of a bypass, 1611 // or the value at the end of the vectorized loop. 1612 for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I) 1613 TruncResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]); 1614 TruncResumeVal->addIncoming(EndValue, VecBody); 1615 1616 // We know what the end value is. 1617 EndValue = IdxEndRoundDown; 1618 // We also know which PHI node holds it. 1619 ResumeIndex = ResumeVal; 1620 break; 1621 } 1622 1623 // Not the canonical induction variable - add the vector loop count to the 1624 // start value. 1625 Value *CRD = BypassBuilder.CreateSExtOrTrunc(CountRoundDown, 1626 II.StartValue->getType(), 1627 "cast.crd"); 1628 EndValue = BypassBuilder.CreateAdd(CRD, II.StartValue , "ind.end"); 1629 break; 1630 } 1631 case LoopVectorizationLegality::IK_ReverseIntInduction: { 1632 // Convert the CountRoundDown variable to the PHI size. 1633 Value *CRD = BypassBuilder.CreateSExtOrTrunc(CountRoundDown, 1634 II.StartValue->getType(), 1635 "cast.crd"); 1636 // Handle reverse integer induction counter. 1637 EndValue = BypassBuilder.CreateSub(II.StartValue, CRD, "rev.ind.end"); 1638 break; 1639 } 1640 case LoopVectorizationLegality::IK_PtrInduction: { 1641 // For pointer induction variables, calculate the offset using 1642 // the end index. 1643 EndValue = BypassBuilder.CreateGEP(II.StartValue, CountRoundDown, 1644 "ptr.ind.end"); 1645 break; 1646 } 1647 case LoopVectorizationLegality::IK_ReversePtrInduction: { 1648 // The value at the end of the loop for the reverse pointer is calculated 1649 // by creating a GEP with a negative index starting from the start value. 1650 Value *Zero = ConstantInt::get(CountRoundDown->getType(), 0); 1651 Value *NegIdx = BypassBuilder.CreateSub(Zero, CountRoundDown, 1652 "rev.ind.end"); 1653 EndValue = BypassBuilder.CreateGEP(II.StartValue, NegIdx, 1654 "rev.ptr.ind.end"); 1655 break; 1656 } 1657 }// end of case 1658 1659 // The new PHI merges the original incoming value, in case of a bypass, 1660 // or the value at the end of the vectorized loop. 1661 for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I) { 1662 if (OrigPhi == OldInduction) 1663 ResumeVal->addIncoming(StartIdx, LoopBypassBlocks[I]); 1664 else 1665 ResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]); 1666 } 1667 ResumeVal->addIncoming(EndValue, VecBody); 1668 1669 // Fix the scalar body counter (PHI node). 1670 unsigned BlockIdx = OrigPhi->getBasicBlockIndex(ScalarPH); 1671 // The old inductions phi node in the scalar body needs the truncated value. 1672 if (OrigPhi == OldInduction) 1673 OrigPhi->setIncomingValue(BlockIdx, TruncResumeVal); 1674 else 1675 OrigPhi->setIncomingValue(BlockIdx, ResumeVal); 1676 } 1677 1678 // If we are generating a new induction variable then we also need to 1679 // generate the code that calculates the exit value. This value is not 1680 // simply the end of the counter because we may skip the vectorized body 1681 // in case of a runtime check. 1682 if (!OldInduction){ 1683 assert(!ResumeIndex && "Unexpected resume value found"); 1684 ResumeIndex = PHINode::Create(IdxTy, 2, "new.indc.resume.val", 1685 MiddleBlock->getTerminator()); 1686 for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I) 1687 ResumeIndex->addIncoming(StartIdx, LoopBypassBlocks[I]); 1688 ResumeIndex->addIncoming(IdxEndRoundDown, VecBody); 1689 } 1690 1691 // Make sure that we found the index where scalar loop needs to continue. 1692 assert(ResumeIndex && ResumeIndex->getType()->isIntegerTy() && 1693 "Invalid resume Index"); 1694 1695 // Add a check in the middle block to see if we have completed 1696 // all of the iterations in the first vector loop. 1697 // If (N - N%VF) == N, then we *don't* need to run the remainder. 1698 Value *CmpN = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ, IdxEnd, 1699 ResumeIndex, "cmp.n", 1700 MiddleBlock->getTerminator()); 1701 1702 BranchInst::Create(ExitBlock, ScalarPH, CmpN, MiddleBlock->getTerminator()); 1703 // Remove the old terminator. 1704 MiddleBlock->getTerminator()->eraseFromParent(); 1705 1706 // Create i+1 and fill the PHINode. 1707 Value *NextIdx = Builder.CreateAdd(Induction, Step, "index.next"); 1708 Induction->addIncoming(StartIdx, VectorPH); 1709 Induction->addIncoming(NextIdx, VecBody); 1710 // Create the compare. 1711 Value *ICmp = Builder.CreateICmpEQ(NextIdx, IdxEndRoundDown); 1712 Builder.CreateCondBr(ICmp, MiddleBlock, VecBody); 1713 1714 // Now we have two terminators. Remove the old one from the block. 1715 VecBody->getTerminator()->eraseFromParent(); 1716 1717 // Get ready to start creating new instructions into the vectorized body. 1718 Builder.SetInsertPoint(VecBody->getFirstInsertionPt()); 1719 1720 // Save the state. 1721 LoopVectorPreHeader = VectorPH; 1722 LoopScalarPreHeader = ScalarPH; 1723 LoopMiddleBlock = MiddleBlock; 1724 LoopExitBlock = ExitBlock; 1725 LoopVectorBody = VecBody; 1726 LoopScalarBody = OldBasicBlock; 1727} 1728 1729/// This function returns the identity element (or neutral element) for 1730/// the operation K. 1731Constant* 1732LoopVectorizationLegality::getReductionIdentity(ReductionKind K, Type *Tp) { 1733 switch (K) { 1734 case RK_IntegerXor: 1735 case RK_IntegerAdd: 1736 case RK_IntegerOr: 1737 // Adding, Xoring, Oring zero to a number does not change it. 1738 return ConstantInt::get(Tp, 0); 1739 case RK_IntegerMult: 1740 // Multiplying a number by 1 does not change it. 1741 return ConstantInt::get(Tp, 1); 1742 case RK_IntegerAnd: 1743 // AND-ing a number with an all-1 value does not change it. 1744 return ConstantInt::get(Tp, -1, true); 1745 case RK_FloatMult: 1746 // Multiplying a number by 1 does not change it. 1747 return ConstantFP::get(Tp, 1.0L); 1748 case RK_FloatAdd: 1749 // Adding zero to a number does not change it. 1750 return ConstantFP::get(Tp, 0.0L); 1751 default: 1752 llvm_unreachable("Unknown reduction kind"); 1753 } 1754} 1755 1756static Intrinsic::ID 1757getIntrinsicIDForCall(CallInst *CI, const TargetLibraryInfo *TLI) { 1758 // If we have an intrinsic call, check if it is trivially vectorizable. 1759 if (IntrinsicInst *II = dyn_cast<IntrinsicInst>(CI)) { 1760 switch (II->getIntrinsicID()) { 1761 case Intrinsic::sqrt: 1762 case Intrinsic::sin: 1763 case Intrinsic::cos: 1764 case Intrinsic::exp: 1765 case Intrinsic::exp2: 1766 case Intrinsic::log: 1767 case Intrinsic::log10: 1768 case Intrinsic::log2: 1769 case Intrinsic::fabs: 1770 case Intrinsic::floor: 1771 case Intrinsic::ceil: 1772 case Intrinsic::trunc: 1773 case Intrinsic::rint: 1774 case Intrinsic::nearbyint: 1775 case Intrinsic::round: 1776 case Intrinsic::pow: 1777 case Intrinsic::fma: 1778 case Intrinsic::fmuladd: 1779 case Intrinsic::lifetime_start: 1780 case Intrinsic::lifetime_end: 1781 return II->getIntrinsicID(); 1782 default: 1783 return Intrinsic::not_intrinsic; 1784 } 1785 } 1786 1787 if (!TLI) 1788 return Intrinsic::not_intrinsic; 1789 1790 LibFunc::Func Func; 1791 Function *F = CI->getCalledFunction(); 1792 // We're going to make assumptions on the semantics of the functions, check 1793 // that the target knows that it's available in this environment. 1794 if (!F || !TLI->getLibFunc(F->getName(), Func)) 1795 return Intrinsic::not_intrinsic; 1796 1797 // Otherwise check if we have a call to a function that can be turned into a 1798 // vector intrinsic. 1799 switch (Func) { 1800 default: 1801 break; 1802 case LibFunc::sin: 1803 case LibFunc::sinf: 1804 case LibFunc::sinl: 1805 return Intrinsic::sin; 1806 case LibFunc::cos: 1807 case LibFunc::cosf: 1808 case LibFunc::cosl: 1809 return Intrinsic::cos; 1810 case LibFunc::exp: 1811 case LibFunc::expf: 1812 case LibFunc::expl: 1813 return Intrinsic::exp; 1814 case LibFunc::exp2: 1815 case LibFunc::exp2f: 1816 case LibFunc::exp2l: 1817 return Intrinsic::exp2; 1818 case LibFunc::log: 1819 case LibFunc::logf: 1820 case LibFunc::logl: 1821 return Intrinsic::log; 1822 case LibFunc::log10: 1823 case LibFunc::log10f: 1824 case LibFunc::log10l: 1825 return Intrinsic::log10; 1826 case LibFunc::log2: 1827 case LibFunc::log2f: 1828 case LibFunc::log2l: 1829 return Intrinsic::log2; 1830 case LibFunc::fabs: 1831 case LibFunc::fabsf: 1832 case LibFunc::fabsl: 1833 return Intrinsic::fabs; 1834 case LibFunc::floor: 1835 case LibFunc::floorf: 1836 case LibFunc::floorl: 1837 return Intrinsic::floor; 1838 case LibFunc::ceil: 1839 case LibFunc::ceilf: 1840 case LibFunc::ceill: 1841 return Intrinsic::ceil; 1842 case LibFunc::trunc: 1843 case LibFunc::truncf: 1844 case LibFunc::truncl: 1845 return Intrinsic::trunc; 1846 case LibFunc::rint: 1847 case LibFunc::rintf: 1848 case LibFunc::rintl: 1849 return Intrinsic::rint; 1850 case LibFunc::nearbyint: 1851 case LibFunc::nearbyintf: 1852 case LibFunc::nearbyintl: 1853 return Intrinsic::nearbyint; 1854 case LibFunc::round: 1855 case LibFunc::roundf: 1856 case LibFunc::roundl: 1857 return Intrinsic::round; 1858 case LibFunc::pow: 1859 case LibFunc::powf: 1860 case LibFunc::powl: 1861 return Intrinsic::pow; 1862 } 1863 1864 return Intrinsic::not_intrinsic; 1865} 1866 1867/// This function translates the reduction kind to an LLVM binary operator. 1868static unsigned 1869getReductionBinOp(LoopVectorizationLegality::ReductionKind Kind) { 1870 switch (Kind) { 1871 case LoopVectorizationLegality::RK_IntegerAdd: 1872 return Instruction::Add; 1873 case LoopVectorizationLegality::RK_IntegerMult: 1874 return Instruction::Mul; 1875 case LoopVectorizationLegality::RK_IntegerOr: 1876 return Instruction::Or; 1877 case LoopVectorizationLegality::RK_IntegerAnd: 1878 return Instruction::And; 1879 case LoopVectorizationLegality::RK_IntegerXor: 1880 return Instruction::Xor; 1881 case LoopVectorizationLegality::RK_FloatMult: 1882 return Instruction::FMul; 1883 case LoopVectorizationLegality::RK_FloatAdd: 1884 return Instruction::FAdd; 1885 case LoopVectorizationLegality::RK_IntegerMinMax: 1886 return Instruction::ICmp; 1887 case LoopVectorizationLegality::RK_FloatMinMax: 1888 return Instruction::FCmp; 1889 default: 1890 llvm_unreachable("Unknown reduction operation"); 1891 } 1892} 1893 1894Value *createMinMaxOp(IRBuilder<> &Builder, 1895 LoopVectorizationLegality::MinMaxReductionKind RK, 1896 Value *Left, 1897 Value *Right) { 1898 CmpInst::Predicate P = CmpInst::ICMP_NE; 1899 switch (RK) { 1900 default: 1901 llvm_unreachable("Unknown min/max reduction kind"); 1902 case LoopVectorizationLegality::MRK_UIntMin: 1903 P = CmpInst::ICMP_ULT; 1904 break; 1905 case LoopVectorizationLegality::MRK_UIntMax: 1906 P = CmpInst::ICMP_UGT; 1907 break; 1908 case LoopVectorizationLegality::MRK_SIntMin: 1909 P = CmpInst::ICMP_SLT; 1910 break; 1911 case LoopVectorizationLegality::MRK_SIntMax: 1912 P = CmpInst::ICMP_SGT; 1913 break; 1914 case LoopVectorizationLegality::MRK_FloatMin: 1915 P = CmpInst::FCMP_OLT; 1916 break; 1917 case LoopVectorizationLegality::MRK_FloatMax: 1918 P = CmpInst::FCMP_OGT; 1919 break; 1920 } 1921 1922 Value *Cmp; 1923 if (RK == LoopVectorizationLegality::MRK_FloatMin || 1924 RK == LoopVectorizationLegality::MRK_FloatMax) 1925 Cmp = Builder.CreateFCmp(P, Left, Right, "rdx.minmax.cmp"); 1926 else 1927 Cmp = Builder.CreateICmp(P, Left, Right, "rdx.minmax.cmp"); 1928 1929 Value *Select = Builder.CreateSelect(Cmp, Left, Right, "rdx.minmax.select"); 1930 return Select; 1931} 1932 1933void 1934InnerLoopVectorizer::vectorizeLoop(LoopVectorizationLegality *Legal) { 1935 //===------------------------------------------------===// 1936 // 1937 // Notice: any optimization or new instruction that go 1938 // into the code below should be also be implemented in 1939 // the cost-model. 1940 // 1941 //===------------------------------------------------===// 1942 Constant *Zero = Builder.getInt32(0); 1943 1944 // In order to support reduction variables we need to be able to vectorize 1945 // Phi nodes. Phi nodes have cycles, so we need to vectorize them in two 1946 // stages. First, we create a new vector PHI node with no incoming edges. 1947 // We use this value when we vectorize all of the instructions that use the 1948 // PHI. Next, after all of the instructions in the block are complete we 1949 // add the new incoming edges to the PHI. At this point all of the 1950 // instructions in the basic block are vectorized, so we can use them to 1951 // construct the PHI. 1952 PhiVector RdxPHIsToFix; 1953 1954 // Scan the loop in a topological order to ensure that defs are vectorized 1955 // before users. 1956 LoopBlocksDFS DFS(OrigLoop); 1957 DFS.perform(LI); 1958 1959 // Vectorize all of the blocks in the original loop. 1960 for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(), 1961 be = DFS.endRPO(); bb != be; ++bb) 1962 vectorizeBlockInLoop(Legal, *bb, &RdxPHIsToFix); 1963 1964 // At this point every instruction in the original loop is widened to 1965 // a vector form. We are almost done. Now, we need to fix the PHI nodes 1966 // that we vectorized. The PHI nodes are currently empty because we did 1967 // not want to introduce cycles. Notice that the remaining PHI nodes 1968 // that we need to fix are reduction variables. 1969 1970 // Create the 'reduced' values for each of the induction vars. 1971 // The reduced values are the vector values that we scalarize and combine 1972 // after the loop is finished. 1973 for (PhiVector::iterator it = RdxPHIsToFix.begin(), e = RdxPHIsToFix.end(); 1974 it != e; ++it) { 1975 PHINode *RdxPhi = *it; 1976 assert(RdxPhi && "Unable to recover vectorized PHI"); 1977 1978 // Find the reduction variable descriptor. 1979 assert(Legal->getReductionVars()->count(RdxPhi) && 1980 "Unable to find the reduction variable"); 1981 LoopVectorizationLegality::ReductionDescriptor RdxDesc = 1982 (*Legal->getReductionVars())[RdxPhi]; 1983 1984 setDebugLocFromInst(Builder, RdxDesc.StartValue); 1985 1986 // We need to generate a reduction vector from the incoming scalar. 1987 // To do so, we need to generate the 'identity' vector and overide 1988 // one of the elements with the incoming scalar reduction. We need 1989 // to do it in the vector-loop preheader. 1990 Builder.SetInsertPoint(LoopBypassBlocks.front()->getTerminator()); 1991 1992 // This is the vector-clone of the value that leaves the loop. 1993 VectorParts &VectorExit = getVectorValue(RdxDesc.LoopExitInstr); 1994 Type *VecTy = VectorExit[0]->getType(); 1995 1996 // Find the reduction identity variable. Zero for addition, or, xor, 1997 // one for multiplication, -1 for And. 1998 Value *Identity; 1999 Value *VectorStart; 2000 if (RdxDesc.Kind == LoopVectorizationLegality::RK_IntegerMinMax || 2001 RdxDesc.Kind == LoopVectorizationLegality::RK_FloatMinMax) { 2002 // MinMax reduction have the start value as their identify. 2003 VectorStart = Identity = Builder.CreateVectorSplat(VF, RdxDesc.StartValue, 2004 "minmax.ident"); 2005 } else { 2006 Constant *Iden = 2007 LoopVectorizationLegality::getReductionIdentity(RdxDesc.Kind, 2008 VecTy->getScalarType()); 2009 Identity = ConstantVector::getSplat(VF, Iden); 2010 2011 // This vector is the Identity vector where the first element is the 2012 // incoming scalar reduction. 2013 VectorStart = Builder.CreateInsertElement(Identity, 2014 RdxDesc.StartValue, Zero); 2015 } 2016 2017 // Fix the vector-loop phi. 2018 // We created the induction variable so we know that the 2019 // preheader is the first entry. 2020 BasicBlock *VecPreheader = Induction->getIncomingBlock(0); 2021 2022 // Reductions do not have to start at zero. They can start with 2023 // any loop invariant values. 2024 VectorParts &VecRdxPhi = WidenMap.get(RdxPhi); 2025 BasicBlock *Latch = OrigLoop->getLoopLatch(); 2026 Value *LoopVal = RdxPhi->getIncomingValueForBlock(Latch); 2027 VectorParts &Val = getVectorValue(LoopVal); 2028 for (unsigned part = 0; part < UF; ++part) { 2029 // Make sure to add the reduction stat value only to the 2030 // first unroll part. 2031 Value *StartVal = (part == 0) ? VectorStart : Identity; 2032 cast<PHINode>(VecRdxPhi[part])->addIncoming(StartVal, VecPreheader); 2033 cast<PHINode>(VecRdxPhi[part])->addIncoming(Val[part], LoopVectorBody); 2034 } 2035 2036 // Before each round, move the insertion point right between 2037 // the PHIs and the values we are going to write. 2038 // This allows us to write both PHINodes and the extractelement 2039 // instructions. 2040 Builder.SetInsertPoint(LoopMiddleBlock->getFirstInsertionPt()); 2041 2042 VectorParts RdxParts; 2043 setDebugLocFromInst(Builder, RdxDesc.LoopExitInstr); 2044 for (unsigned part = 0; part < UF; ++part) { 2045 // This PHINode contains the vectorized reduction variable, or 2046 // the initial value vector, if we bypass the vector loop. 2047 VectorParts &RdxExitVal = getVectorValue(RdxDesc.LoopExitInstr); 2048 PHINode *NewPhi = Builder.CreatePHI(VecTy, 2, "rdx.vec.exit.phi"); 2049 Value *StartVal = (part == 0) ? VectorStart : Identity; 2050 for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I) 2051 NewPhi->addIncoming(StartVal, LoopBypassBlocks[I]); 2052 NewPhi->addIncoming(RdxExitVal[part], LoopVectorBody); 2053 RdxParts.push_back(NewPhi); 2054 } 2055 2056 // Reduce all of the unrolled parts into a single vector. 2057 Value *ReducedPartRdx = RdxParts[0]; 2058 unsigned Op = getReductionBinOp(RdxDesc.Kind); 2059 setDebugLocFromInst(Builder, ReducedPartRdx); 2060 for (unsigned part = 1; part < UF; ++part) { 2061 if (Op != Instruction::ICmp && Op != Instruction::FCmp) 2062 ReducedPartRdx = Builder.CreateBinOp((Instruction::BinaryOps)Op, 2063 RdxParts[part], ReducedPartRdx, 2064 "bin.rdx"); 2065 else 2066 ReducedPartRdx = createMinMaxOp(Builder, RdxDesc.MinMaxKind, 2067 ReducedPartRdx, RdxParts[part]); 2068 } 2069 2070 // VF is a power of 2 so we can emit the reduction using log2(VF) shuffles 2071 // and vector ops, reducing the set of values being computed by half each 2072 // round. 2073 assert(isPowerOf2_32(VF) && 2074 "Reduction emission only supported for pow2 vectors!"); 2075 Value *TmpVec = ReducedPartRdx; 2076 SmallVector<Constant*, 32> ShuffleMask(VF, 0); 2077 for (unsigned i = VF; i != 1; i >>= 1) { 2078 // Move the upper half of the vector to the lower half. 2079 for (unsigned j = 0; j != i/2; ++j) 2080 ShuffleMask[j] = Builder.getInt32(i/2 + j); 2081 2082 // Fill the rest of the mask with undef. 2083 std::fill(&ShuffleMask[i/2], ShuffleMask.end(), 2084 UndefValue::get(Builder.getInt32Ty())); 2085 2086 Value *Shuf = 2087 Builder.CreateShuffleVector(TmpVec, 2088 UndefValue::get(TmpVec->getType()), 2089 ConstantVector::get(ShuffleMask), 2090 "rdx.shuf"); 2091 2092 if (Op != Instruction::ICmp && Op != Instruction::FCmp) 2093 TmpVec = Builder.CreateBinOp((Instruction::BinaryOps)Op, TmpVec, Shuf, 2094 "bin.rdx"); 2095 else 2096 TmpVec = createMinMaxOp(Builder, RdxDesc.MinMaxKind, TmpVec, Shuf); 2097 } 2098 2099 // The result is in the first element of the vector. 2100 Value *Scalar0 = Builder.CreateExtractElement(TmpVec, Builder.getInt32(0)); 2101 2102 // Now, we need to fix the users of the reduction variable 2103 // inside and outside of the scalar remainder loop. 2104 // We know that the loop is in LCSSA form. We need to update the 2105 // PHI nodes in the exit blocks. 2106 for (BasicBlock::iterator LEI = LoopExitBlock->begin(), 2107 LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) { 2108 PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI); 2109 if (!LCSSAPhi) continue; 2110 2111 // All PHINodes need to have a single entry edge, or two if 2112 // we already fixed them. 2113 assert(LCSSAPhi->getNumIncomingValues() < 3 && "Invalid LCSSA PHI"); 2114 2115 // We found our reduction value exit-PHI. Update it with the 2116 // incoming bypass edge. 2117 if (LCSSAPhi->getIncomingValue(0) == RdxDesc.LoopExitInstr) { 2118 // Add an edge coming from the bypass. 2119 LCSSAPhi->addIncoming(Scalar0, LoopMiddleBlock); 2120 break; 2121 } 2122 }// end of the LCSSA phi scan. 2123 2124 // Fix the scalar loop reduction variable with the incoming reduction sum 2125 // from the vector body and from the backedge value. 2126 int IncomingEdgeBlockIdx = 2127 (RdxPhi)->getBasicBlockIndex(OrigLoop->getLoopLatch()); 2128 assert(IncomingEdgeBlockIdx >= 0 && "Invalid block index"); 2129 // Pick the other block. 2130 int SelfEdgeBlockIdx = (IncomingEdgeBlockIdx ? 0 : 1); 2131 (RdxPhi)->setIncomingValue(SelfEdgeBlockIdx, Scalar0); 2132 (RdxPhi)->setIncomingValue(IncomingEdgeBlockIdx, RdxDesc.LoopExitInstr); 2133 }// end of for each redux variable. 2134 2135 // The Loop exit block may have single value PHI nodes where the incoming 2136 // value is 'undef'. While vectorizing we only handled real values that 2137 // were defined inside the loop. Here we handle the 'undef case'. 2138 // See PR14725. 2139 for (BasicBlock::iterator LEI = LoopExitBlock->begin(), 2140 LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) { 2141 PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI); 2142 if (!LCSSAPhi) continue; 2143 if (LCSSAPhi->getNumIncomingValues() == 1) 2144 LCSSAPhi->addIncoming(UndefValue::get(LCSSAPhi->getType()), 2145 LoopMiddleBlock); 2146 } 2147} 2148 2149InnerLoopVectorizer::VectorParts 2150InnerLoopVectorizer::createEdgeMask(BasicBlock *Src, BasicBlock *Dst) { 2151 assert(std::find(pred_begin(Dst), pred_end(Dst), Src) != pred_end(Dst) && 2152 "Invalid edge"); 2153 2154 // Look for cached value. 2155 std::pair<BasicBlock*, BasicBlock*> Edge(Src, Dst); 2156 EdgeMaskCache::iterator ECEntryIt = MaskCache.find(Edge); 2157 if (ECEntryIt != MaskCache.end()) 2158 return ECEntryIt->second; 2159 2160 VectorParts SrcMask = createBlockInMask(Src); 2161 2162 // The terminator has to be a branch inst! 2163 BranchInst *BI = dyn_cast<BranchInst>(Src->getTerminator()); 2164 assert(BI && "Unexpected terminator found"); 2165 2166 if (BI->isConditional()) { 2167 VectorParts EdgeMask = getVectorValue(BI->getCondition()); 2168 2169 if (BI->getSuccessor(0) != Dst) 2170 for (unsigned part = 0; part < UF; ++part) 2171 EdgeMask[part] = Builder.CreateNot(EdgeMask[part]); 2172 2173 for (unsigned part = 0; part < UF; ++part) 2174 EdgeMask[part] = Builder.CreateAnd(EdgeMask[part], SrcMask[part]); 2175 2176 MaskCache[Edge] = EdgeMask; 2177 return EdgeMask; 2178 } 2179 2180 MaskCache[Edge] = SrcMask; 2181 return SrcMask; 2182} 2183 2184InnerLoopVectorizer::VectorParts 2185InnerLoopVectorizer::createBlockInMask(BasicBlock *BB) { 2186 assert(OrigLoop->contains(BB) && "Block is not a part of a loop"); 2187 2188 // Loop incoming mask is all-one. 2189 if (OrigLoop->getHeader() == BB) { 2190 Value *C = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 1); 2191 return getVectorValue(C); 2192 } 2193 2194 // This is the block mask. We OR all incoming edges, and with zero. 2195 Value *Zero = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 0); 2196 VectorParts BlockMask = getVectorValue(Zero); 2197 2198 // For each pred: 2199 for (pred_iterator it = pred_begin(BB), e = pred_end(BB); it != e; ++it) { 2200 VectorParts EM = createEdgeMask(*it, BB); 2201 for (unsigned part = 0; part < UF; ++part) 2202 BlockMask[part] = Builder.CreateOr(BlockMask[part], EM[part]); 2203 } 2204 2205 return BlockMask; 2206} 2207 2208void 2209InnerLoopVectorizer::vectorizeBlockInLoop(LoopVectorizationLegality *Legal, 2210 BasicBlock *BB, PhiVector *PV) { 2211 // For each instruction in the old loop. 2212 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 2213 VectorParts &Entry = WidenMap.get(it); 2214 switch (it->getOpcode()) { 2215 case Instruction::Br: 2216 // Nothing to do for PHIs and BR, since we already took care of the 2217 // loop control flow instructions. 2218 continue; 2219 case Instruction::PHI:{ 2220 PHINode* P = cast<PHINode>(it); 2221 // Handle reduction variables: 2222 if (Legal->getReductionVars()->count(P)) { 2223 for (unsigned part = 0; part < UF; ++part) { 2224 // This is phase one of vectorizing PHIs. 2225 Type *VecTy = VectorType::get(it->getType(), VF); 2226 Entry[part] = PHINode::Create(VecTy, 2, "vec.phi", 2227 LoopVectorBody-> getFirstInsertionPt()); 2228 } 2229 PV->push_back(P); 2230 continue; 2231 } 2232 2233 setDebugLocFromInst(Builder, P); 2234 // Check for PHI nodes that are lowered to vector selects. 2235 if (P->getParent() != OrigLoop->getHeader()) { 2236 // We know that all PHIs in non header blocks are converted into 2237 // selects, so we don't have to worry about the insertion order and we 2238 // can just use the builder. 2239 // At this point we generate the predication tree. There may be 2240 // duplications since this is a simple recursive scan, but future 2241 // optimizations will clean it up. 2242 2243 unsigned NumIncoming = P->getNumIncomingValues(); 2244 2245 // Generate a sequence of selects of the form: 2246 // SELECT(Mask3, In3, 2247 // SELECT(Mask2, In2, 2248 // ( ...))) 2249 for (unsigned In = 0; In < NumIncoming; In++) { 2250 VectorParts Cond = createEdgeMask(P->getIncomingBlock(In), 2251 P->getParent()); 2252 VectorParts &In0 = getVectorValue(P->getIncomingValue(In)); 2253 2254 for (unsigned part = 0; part < UF; ++part) { 2255 // We might have single edge PHIs (blocks) - use an identity 2256 // 'select' for the first PHI operand. 2257 if (In == 0) 2258 Entry[part] = Builder.CreateSelect(Cond[part], In0[part], 2259 In0[part]); 2260 else 2261 // Select between the current value and the previous incoming edge 2262 // based on the incoming mask. 2263 Entry[part] = Builder.CreateSelect(Cond[part], In0[part], 2264 Entry[part], "predphi"); 2265 } 2266 } 2267 continue; 2268 } 2269 2270 // This PHINode must be an induction variable. 2271 // Make sure that we know about it. 2272 assert(Legal->getInductionVars()->count(P) && 2273 "Not an induction variable"); 2274 2275 LoopVectorizationLegality::InductionInfo II = 2276 Legal->getInductionVars()->lookup(P); 2277 2278 switch (II.IK) { 2279 case LoopVectorizationLegality::IK_NoInduction: 2280 llvm_unreachable("Unknown induction"); 2281 case LoopVectorizationLegality::IK_IntInduction: { 2282 assert(P->getType() == II.StartValue->getType() && "Types must match"); 2283 Type *PhiTy = P->getType(); 2284 Value *Broadcasted; 2285 if (P == OldInduction) { 2286 // Handle the canonical induction variable. We might have had to 2287 // extend the type. 2288 Broadcasted = Builder.CreateTrunc(Induction, PhiTy); 2289 } else { 2290 // Handle other induction variables that are now based on the 2291 // canonical one. 2292 Value *NormalizedIdx = Builder.CreateSub(Induction, ExtendedIdx, 2293 "normalized.idx"); 2294 NormalizedIdx = Builder.CreateSExtOrTrunc(NormalizedIdx, PhiTy); 2295 Broadcasted = Builder.CreateAdd(II.StartValue, NormalizedIdx, 2296 "offset.idx"); 2297 } 2298 Broadcasted = getBroadcastInstrs(Broadcasted); 2299 // After broadcasting the induction variable we need to make the vector 2300 // consecutive by adding 0, 1, 2, etc. 2301 for (unsigned part = 0; part < UF; ++part) 2302 Entry[part] = getConsecutiveVector(Broadcasted, VF * part, false); 2303 continue; 2304 } 2305 case LoopVectorizationLegality::IK_ReverseIntInduction: 2306 case LoopVectorizationLegality::IK_PtrInduction: 2307 case LoopVectorizationLegality::IK_ReversePtrInduction: 2308 // Handle reverse integer and pointer inductions. 2309 Value *StartIdx = ExtendedIdx; 2310 // This is the normalized GEP that starts counting at zero. 2311 Value *NormalizedIdx = Builder.CreateSub(Induction, StartIdx, 2312 "normalized.idx"); 2313 2314 // Handle the reverse integer induction variable case. 2315 if (LoopVectorizationLegality::IK_ReverseIntInduction == II.IK) { 2316 IntegerType *DstTy = cast<IntegerType>(II.StartValue->getType()); 2317 Value *CNI = Builder.CreateSExtOrTrunc(NormalizedIdx, DstTy, 2318 "resize.norm.idx"); 2319 Value *ReverseInd = Builder.CreateSub(II.StartValue, CNI, 2320 "reverse.idx"); 2321 2322 // This is a new value so do not hoist it out. 2323 Value *Broadcasted = getBroadcastInstrs(ReverseInd); 2324 // After broadcasting the induction variable we need to make the 2325 // vector consecutive by adding ... -3, -2, -1, 0. 2326 for (unsigned part = 0; part < UF; ++part) 2327 Entry[part] = getConsecutiveVector(Broadcasted, -(int)VF * part, 2328 true); 2329 continue; 2330 } 2331 2332 // Handle the pointer induction variable case. 2333 assert(P->getType()->isPointerTy() && "Unexpected type."); 2334 2335 // Is this a reverse induction ptr or a consecutive induction ptr. 2336 bool Reverse = (LoopVectorizationLegality::IK_ReversePtrInduction == 2337 II.IK); 2338 2339 // This is the vector of results. Notice that we don't generate 2340 // vector geps because scalar geps result in better code. 2341 for (unsigned part = 0; part < UF; ++part) { 2342 Value *VecVal = UndefValue::get(VectorType::get(P->getType(), VF)); 2343 for (unsigned int i = 0; i < VF; ++i) { 2344 int EltIndex = (i + part * VF) * (Reverse ? -1 : 1); 2345 Constant *Idx = ConstantInt::get(Induction->getType(), EltIndex); 2346 Value *GlobalIdx; 2347 if (!Reverse) 2348 GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx, "gep.idx"); 2349 else 2350 GlobalIdx = Builder.CreateSub(Idx, NormalizedIdx, "gep.ridx"); 2351 2352 Value *SclrGep = Builder.CreateGEP(II.StartValue, GlobalIdx, 2353 "next.gep"); 2354 VecVal = Builder.CreateInsertElement(VecVal, SclrGep, 2355 Builder.getInt32(i), 2356 "insert.gep"); 2357 } 2358 Entry[part] = VecVal; 2359 } 2360 continue; 2361 } 2362 2363 }// End of PHI. 2364 2365 case Instruction::Add: 2366 case Instruction::FAdd: 2367 case Instruction::Sub: 2368 case Instruction::FSub: 2369 case Instruction::Mul: 2370 case Instruction::FMul: 2371 case Instruction::UDiv: 2372 case Instruction::SDiv: 2373 case Instruction::FDiv: 2374 case Instruction::URem: 2375 case Instruction::SRem: 2376 case Instruction::FRem: 2377 case Instruction::Shl: 2378 case Instruction::LShr: 2379 case Instruction::AShr: 2380 case Instruction::And: 2381 case Instruction::Or: 2382 case Instruction::Xor: { 2383 // Just widen binops. 2384 BinaryOperator *BinOp = dyn_cast<BinaryOperator>(it); 2385 setDebugLocFromInst(Builder, BinOp); 2386 VectorParts &A = getVectorValue(it->getOperand(0)); 2387 VectorParts &B = getVectorValue(it->getOperand(1)); 2388 2389 // Use this vector value for all users of the original instruction. 2390 for (unsigned Part = 0; Part < UF; ++Part) { 2391 Value *V = Builder.CreateBinOp(BinOp->getOpcode(), A[Part], B[Part]); 2392 2393 // Update the NSW, NUW and Exact flags. Notice: V can be an Undef. 2394 BinaryOperator *VecOp = dyn_cast<BinaryOperator>(V); 2395 if (VecOp && isa<OverflowingBinaryOperator>(BinOp)) { 2396 VecOp->setHasNoSignedWrap(BinOp->hasNoSignedWrap()); 2397 VecOp->setHasNoUnsignedWrap(BinOp->hasNoUnsignedWrap()); 2398 } 2399 if (VecOp && isa<PossiblyExactOperator>(VecOp)) 2400 VecOp->setIsExact(BinOp->isExact()); 2401 2402 Entry[Part] = V; 2403 } 2404 break; 2405 } 2406 case Instruction::Select: { 2407 // Widen selects. 2408 // If the selector is loop invariant we can create a select 2409 // instruction with a scalar condition. Otherwise, use vector-select. 2410 bool InvariantCond = SE->isLoopInvariant(SE->getSCEV(it->getOperand(0)), 2411 OrigLoop); 2412 setDebugLocFromInst(Builder, it); 2413 2414 // The condition can be loop invariant but still defined inside the 2415 // loop. This means that we can't just use the original 'cond' value. 2416 // We have to take the 'vectorized' value and pick the first lane. 2417 // Instcombine will make this a no-op. 2418 VectorParts &Cond = getVectorValue(it->getOperand(0)); 2419 VectorParts &Op0 = getVectorValue(it->getOperand(1)); 2420 VectorParts &Op1 = getVectorValue(it->getOperand(2)); 2421 Value *ScalarCond = Builder.CreateExtractElement(Cond[0], 2422 Builder.getInt32(0)); 2423 for (unsigned Part = 0; Part < UF; ++Part) { 2424 Entry[Part] = Builder.CreateSelect( 2425 InvariantCond ? ScalarCond : Cond[Part], 2426 Op0[Part], 2427 Op1[Part]); 2428 } 2429 break; 2430 } 2431 2432 case Instruction::ICmp: 2433 case Instruction::FCmp: { 2434 // Widen compares. Generate vector compares. 2435 bool FCmp = (it->getOpcode() == Instruction::FCmp); 2436 CmpInst *Cmp = dyn_cast<CmpInst>(it); 2437 setDebugLocFromInst(Builder, it); 2438 VectorParts &A = getVectorValue(it->getOperand(0)); 2439 VectorParts &B = getVectorValue(it->getOperand(1)); 2440 for (unsigned Part = 0; Part < UF; ++Part) { 2441 Value *C = 0; 2442 if (FCmp) 2443 C = Builder.CreateFCmp(Cmp->getPredicate(), A[Part], B[Part]); 2444 else 2445 C = Builder.CreateICmp(Cmp->getPredicate(), A[Part], B[Part]); 2446 Entry[Part] = C; 2447 } 2448 break; 2449 } 2450 2451 case Instruction::Store: 2452 case Instruction::Load: 2453 vectorizeMemoryInstruction(it, Legal); 2454 break; 2455 case Instruction::ZExt: 2456 case Instruction::SExt: 2457 case Instruction::FPToUI: 2458 case Instruction::FPToSI: 2459 case Instruction::FPExt: 2460 case Instruction::PtrToInt: 2461 case Instruction::IntToPtr: 2462 case Instruction::SIToFP: 2463 case Instruction::UIToFP: 2464 case Instruction::Trunc: 2465 case Instruction::FPTrunc: 2466 case Instruction::BitCast: { 2467 CastInst *CI = dyn_cast<CastInst>(it); 2468 setDebugLocFromInst(Builder, it); 2469 /// Optimize the special case where the source is the induction 2470 /// variable. Notice that we can only optimize the 'trunc' case 2471 /// because: a. FP conversions lose precision, b. sext/zext may wrap, 2472 /// c. other casts depend on pointer size. 2473 if (CI->getOperand(0) == OldInduction && 2474 it->getOpcode() == Instruction::Trunc) { 2475 Value *ScalarCast = Builder.CreateCast(CI->getOpcode(), Induction, 2476 CI->getType()); 2477 Value *Broadcasted = getBroadcastInstrs(ScalarCast); 2478 for (unsigned Part = 0; Part < UF; ++Part) 2479 Entry[Part] = getConsecutiveVector(Broadcasted, VF * Part, false); 2480 break; 2481 } 2482 /// Vectorize casts. 2483 Type *DestTy = VectorType::get(CI->getType()->getScalarType(), VF); 2484 2485 VectorParts &A = getVectorValue(it->getOperand(0)); 2486 for (unsigned Part = 0; Part < UF; ++Part) 2487 Entry[Part] = Builder.CreateCast(CI->getOpcode(), A[Part], DestTy); 2488 break; 2489 } 2490 2491 case Instruction::Call: { 2492 // Ignore dbg intrinsics. 2493 if (isa<DbgInfoIntrinsic>(it)) 2494 break; 2495 setDebugLocFromInst(Builder, it); 2496 2497 Module *M = BB->getParent()->getParent(); 2498 CallInst *CI = cast<CallInst>(it); 2499 Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI); 2500 assert(ID && "Not an intrinsic call!"); 2501 switch (ID) { 2502 case Intrinsic::lifetime_end: 2503 case Intrinsic::lifetime_start: 2504 scalarizeInstruction(it); 2505 break; 2506 default: 2507 for (unsigned Part = 0; Part < UF; ++Part) { 2508 SmallVector<Value *, 4> Args; 2509 for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i) { 2510 VectorParts &Arg = getVectorValue(CI->getArgOperand(i)); 2511 Args.push_back(Arg[Part]); 2512 } 2513 Type *Tys[] = { VectorType::get(CI->getType()->getScalarType(), VF) }; 2514 Function *F = Intrinsic::getDeclaration(M, ID, Tys); 2515 Entry[Part] = Builder.CreateCall(F, Args); 2516 } 2517 break; 2518 } 2519 break; 2520 } 2521 2522 default: 2523 // All other instructions are unsupported. Scalarize them. 2524 scalarizeInstruction(it); 2525 break; 2526 }// end of switch. 2527 }// end of for_each instr. 2528} 2529 2530void InnerLoopVectorizer::updateAnalysis() { 2531 // Forget the original basic block. 2532 SE->forgetLoop(OrigLoop); 2533 2534 // Update the dominator tree information. 2535 assert(DT->properlyDominates(LoopBypassBlocks.front(), LoopExitBlock) && 2536 "Entry does not dominate exit."); 2537 2538 for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I) 2539 DT->addNewBlock(LoopBypassBlocks[I], LoopBypassBlocks[I-1]); 2540 DT->addNewBlock(LoopVectorPreHeader, LoopBypassBlocks.back()); 2541 DT->addNewBlock(LoopVectorBody, LoopVectorPreHeader); 2542 DT->addNewBlock(LoopMiddleBlock, LoopBypassBlocks.front()); 2543 DT->addNewBlock(LoopScalarPreHeader, LoopMiddleBlock); 2544 DT->changeImmediateDominator(LoopScalarBody, LoopScalarPreHeader); 2545 DT->changeImmediateDominator(LoopExitBlock, LoopMiddleBlock); 2546 2547 DEBUG(DT->verifyAnalysis()); 2548} 2549 2550bool LoopVectorizationLegality::canVectorizeWithIfConvert() { 2551 if (!EnableIfConversion) 2552 return false; 2553 2554 assert(TheLoop->getNumBlocks() > 1 && "Single block loops are vectorizable"); 2555 std::vector<BasicBlock*> &LoopBlocks = TheLoop->getBlocksVector(); 2556 2557 // A list of pointers that we can safely read and write to. 2558 SmallPtrSet<Value *, 8> SafePointes; 2559 2560 // Collect safe addresses. 2561 for (unsigned i = 0, e = LoopBlocks.size(); i < e; ++i) { 2562 BasicBlock *BB = LoopBlocks[i]; 2563 2564 if (blockNeedsPredication(BB)) 2565 continue; 2566 2567 for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I) { 2568 if (LoadInst *LI = dyn_cast<LoadInst>(I)) 2569 SafePointes.insert(LI->getPointerOperand()); 2570 else if (StoreInst *SI = dyn_cast<StoreInst>(I)) 2571 SafePointes.insert(SI->getPointerOperand()); 2572 } 2573 } 2574 2575 // Collect the blocks that need predication. 2576 for (unsigned i = 0, e = LoopBlocks.size(); i < e; ++i) { 2577 BasicBlock *BB = LoopBlocks[i]; 2578 2579 // We don't support switch statements inside loops. 2580 if (!isa<BranchInst>(BB->getTerminator())) 2581 return false; 2582 2583 // We must be able to predicate all blocks that need to be predicated. 2584 if (blockNeedsPredication(BB) && !blockCanBePredicated(BB, SafePointes)) 2585 return false; 2586 } 2587 2588 // We can if-convert this loop. 2589 return true; 2590} 2591 2592bool LoopVectorizationLegality::canVectorize() { 2593 // We must have a loop in canonical form. Loops with indirectbr in them cannot 2594 // be canonicalized. 2595 if (!TheLoop->getLoopPreheader()) 2596 return false; 2597 2598 // We can only vectorize innermost loops. 2599 if (TheLoop->getSubLoopsVector().size()) 2600 return false; 2601 2602 // We must have a single backedge. 2603 if (TheLoop->getNumBackEdges() != 1) 2604 return false; 2605 2606 // We must have a single exiting block. 2607 if (!TheLoop->getExitingBlock()) 2608 return false; 2609 2610 unsigned NumBlocks = TheLoop->getNumBlocks(); 2611 2612 // Check if we can if-convert non single-bb loops. 2613 if (NumBlocks != 1 && !canVectorizeWithIfConvert()) { 2614 DEBUG(dbgs() << "LV: Can't if-convert the loop.\n"); 2615 return false; 2616 } 2617 2618 // We need to have a loop header. 2619 BasicBlock *Latch = TheLoop->getLoopLatch(); 2620 DEBUG(dbgs() << "LV: Found a loop: " << 2621 TheLoop->getHeader()->getName() << "\n"); 2622 2623 // ScalarEvolution needs to be able to find the exit count. 2624 const SCEV *ExitCount = SE->getBackedgeTakenCount(TheLoop); 2625 if (ExitCount == SE->getCouldNotCompute()) { 2626 DEBUG(dbgs() << "LV: SCEV could not compute the loop exit count.\n"); 2627 return false; 2628 } 2629 2630 // Do not loop-vectorize loops with a tiny trip count. 2631 unsigned TC = SE->getSmallConstantTripCount(TheLoop, Latch); 2632 if (TC > 0u && TC < TinyTripCountVectorThreshold) { 2633 DEBUG(dbgs() << "LV: Found a loop with a very small trip count. " << 2634 "This loop is not worth vectorizing.\n"); 2635 return false; 2636 } 2637 2638 // Check if we can vectorize the instructions and CFG in this loop. 2639 if (!canVectorizeInstrs()) { 2640 DEBUG(dbgs() << "LV: Can't vectorize the instructions or CFG\n"); 2641 return false; 2642 } 2643 2644 // Go over each instruction and look at memory deps. 2645 if (!canVectorizeMemory()) { 2646 DEBUG(dbgs() << "LV: Can't vectorize due to memory conflicts\n"); 2647 return false; 2648 } 2649 2650 // Collect all of the variables that remain uniform after vectorization. 2651 collectLoopUniforms(); 2652 2653 DEBUG(dbgs() << "LV: We can vectorize this loop" << 2654 (PtrRtCheck.Need ? " (with a runtime bound check)" : "") 2655 <<"!\n"); 2656 2657 // Okay! We can vectorize. At this point we don't have any other mem analysis 2658 // which may limit our maximum vectorization factor, so just return true with 2659 // no restrictions. 2660 return true; 2661} 2662 2663static Type *convertPointerToIntegerType(DataLayout &DL, Type *Ty) { 2664 if (Ty->isPointerTy()) 2665 return DL.getIntPtrType(Ty->getContext()); 2666 return Ty; 2667} 2668 2669static Type* getWiderType(DataLayout &DL, Type *Ty0, Type *Ty1) { 2670 Ty0 = convertPointerToIntegerType(DL, Ty0); 2671 Ty1 = convertPointerToIntegerType(DL, Ty1); 2672 if (Ty0->getScalarSizeInBits() > Ty1->getScalarSizeInBits()) 2673 return Ty0; 2674 return Ty1; 2675} 2676 2677/// \brief Check that the instruction has outside loop users and is not an 2678/// identified reduction variable. 2679static bool hasOutsideLoopUser(const Loop *TheLoop, Instruction *Inst, 2680 SmallPtrSet<Value *, 4> &Reductions) { 2681 // Reduction instructions are allowed to have exit users. All other 2682 // instructions must not have external users. 2683 if (!Reductions.count(Inst)) 2684 //Check that all of the users of the loop are inside the BB. 2685 for (Value::use_iterator I = Inst->use_begin(), E = Inst->use_end(); 2686 I != E; ++I) { 2687 Instruction *U = cast<Instruction>(*I); 2688 // This user may be a reduction exit value. 2689 if (!TheLoop->contains(U)) { 2690 DEBUG(dbgs() << "LV: Found an outside user for : "<< *U << "\n"); 2691 return true; 2692 } 2693 } 2694 return false; 2695} 2696 2697bool LoopVectorizationLegality::canVectorizeInstrs() { 2698 BasicBlock *PreHeader = TheLoop->getLoopPreheader(); 2699 BasicBlock *Header = TheLoop->getHeader(); 2700 2701 // Look for the attribute signaling the absence of NaNs. 2702 Function &F = *Header->getParent(); 2703 if (F.hasFnAttribute("no-nans-fp-math")) 2704 HasFunNoNaNAttr = F.getAttributes().getAttribute( 2705 AttributeSet::FunctionIndex, 2706 "no-nans-fp-math").getValueAsString() == "true"; 2707 2708 // For each block in the loop. 2709 for (Loop::block_iterator bb = TheLoop->block_begin(), 2710 be = TheLoop->block_end(); bb != be; ++bb) { 2711 2712 // Scan the instructions in the block and look for hazards. 2713 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e; 2714 ++it) { 2715 2716 if (PHINode *Phi = dyn_cast<PHINode>(it)) { 2717 Type *PhiTy = Phi->getType(); 2718 // Check that this PHI type is allowed. 2719 if (!PhiTy->isIntegerTy() && 2720 !PhiTy->isFloatingPointTy() && 2721 !PhiTy->isPointerTy()) { 2722 DEBUG(dbgs() << "LV: Found an non-int non-pointer PHI.\n"); 2723 return false; 2724 } 2725 2726 // If this PHINode is not in the header block, then we know that we 2727 // can convert it to select during if-conversion. No need to check if 2728 // the PHIs in this block are induction or reduction variables. 2729 if (*bb != Header) { 2730 // Check that this instruction has no outside users or is an 2731 // identified reduction value with an outside user. 2732 if(!hasOutsideLoopUser(TheLoop, it, AllowedExit)) 2733 continue; 2734 return false; 2735 } 2736 2737 // We only allow if-converted PHIs with more than two incoming values. 2738 if (Phi->getNumIncomingValues() != 2) { 2739 DEBUG(dbgs() << "LV: Found an invalid PHI.\n"); 2740 return false; 2741 } 2742 2743 // This is the value coming from the preheader. 2744 Value *StartValue = Phi->getIncomingValueForBlock(PreHeader); 2745 // Check if this is an induction variable. 2746 InductionKind IK = isInductionVariable(Phi); 2747 2748 if (IK_NoInduction != IK) { 2749 // Get the widest type. 2750 if (!WidestIndTy) 2751 WidestIndTy = convertPointerToIntegerType(*DL, PhiTy); 2752 else 2753 WidestIndTy = getWiderType(*DL, PhiTy, WidestIndTy); 2754 2755 // Int inductions are special because we only allow one IV. 2756 if (IK == IK_IntInduction) { 2757 // Use the phi node with the widest type as induction. Use the last 2758 // one if there are multiple (no good reason for doing this other 2759 // than it is expedient). 2760 if (!Induction || PhiTy == WidestIndTy) 2761 Induction = Phi; 2762 } 2763 2764 DEBUG(dbgs() << "LV: Found an induction variable.\n"); 2765 Inductions[Phi] = InductionInfo(StartValue, IK); 2766 continue; 2767 } 2768 2769 if (AddReductionVar(Phi, RK_IntegerAdd)) { 2770 DEBUG(dbgs() << "LV: Found an ADD reduction PHI."<< *Phi <<"\n"); 2771 continue; 2772 } 2773 if (AddReductionVar(Phi, RK_IntegerMult)) { 2774 DEBUG(dbgs() << "LV: Found a MUL reduction PHI."<< *Phi <<"\n"); 2775 continue; 2776 } 2777 if (AddReductionVar(Phi, RK_IntegerOr)) { 2778 DEBUG(dbgs() << "LV: Found an OR reduction PHI."<< *Phi <<"\n"); 2779 continue; 2780 } 2781 if (AddReductionVar(Phi, RK_IntegerAnd)) { 2782 DEBUG(dbgs() << "LV: Found an AND reduction PHI."<< *Phi <<"\n"); 2783 continue; 2784 } 2785 if (AddReductionVar(Phi, RK_IntegerXor)) { 2786 DEBUG(dbgs() << "LV: Found a XOR reduction PHI."<< *Phi <<"\n"); 2787 continue; 2788 } 2789 if (AddReductionVar(Phi, RK_IntegerMinMax)) { 2790 DEBUG(dbgs() << "LV: Found a MINMAX reduction PHI."<< *Phi <<"\n"); 2791 continue; 2792 } 2793 if (AddReductionVar(Phi, RK_FloatMult)) { 2794 DEBUG(dbgs() << "LV: Found an FMult reduction PHI."<< *Phi <<"\n"); 2795 continue; 2796 } 2797 if (AddReductionVar(Phi, RK_FloatAdd)) { 2798 DEBUG(dbgs() << "LV: Found an FAdd reduction PHI."<< *Phi <<"\n"); 2799 continue; 2800 } 2801 if (AddReductionVar(Phi, RK_FloatMinMax)) { 2802 DEBUG(dbgs() << "LV: Found an float MINMAX reduction PHI."<< *Phi << 2803 "\n"); 2804 continue; 2805 } 2806 2807 DEBUG(dbgs() << "LV: Found an unidentified PHI."<< *Phi <<"\n"); 2808 return false; 2809 }// end of PHI handling 2810 2811 // We still don't handle functions. However, we can ignore dbg intrinsic 2812 // calls and we do handle certain intrinsic and libm functions. 2813 CallInst *CI = dyn_cast<CallInst>(it); 2814 if (CI && !getIntrinsicIDForCall(CI, TLI) && !isa<DbgInfoIntrinsic>(CI)) { 2815 DEBUG(dbgs() << "LV: Found a call site.\n"); 2816 return false; 2817 } 2818 2819 // Check that the instruction return type is vectorizable. 2820 if (!VectorType::isValidElementType(it->getType()) && 2821 !it->getType()->isVoidTy()) { 2822 DEBUG(dbgs() << "LV: Found unvectorizable type." << "\n"); 2823 return false; 2824 } 2825 2826 // Check that the stored type is vectorizable. 2827 if (StoreInst *ST = dyn_cast<StoreInst>(it)) { 2828 Type *T = ST->getValueOperand()->getType(); 2829 if (!VectorType::isValidElementType(T)) 2830 return false; 2831 } 2832 2833 // Reduction instructions are allowed to have exit users. 2834 // All other instructions must not have external users. 2835 if (hasOutsideLoopUser(TheLoop, it, AllowedExit)) 2836 return false; 2837 2838 } // next instr. 2839 2840 } 2841 2842 if (!Induction) { 2843 DEBUG(dbgs() << "LV: Did not find one integer induction var.\n"); 2844 if (Inductions.empty()) 2845 return false; 2846 } 2847 2848 return true; 2849} 2850 2851void LoopVectorizationLegality::collectLoopUniforms() { 2852 // We now know that the loop is vectorizable! 2853 // Collect variables that will remain uniform after vectorization. 2854 std::vector<Value*> Worklist; 2855 BasicBlock *Latch = TheLoop->getLoopLatch(); 2856 2857 // Start with the conditional branch and walk up the block. 2858 Worklist.push_back(Latch->getTerminator()->getOperand(0)); 2859 2860 while (Worklist.size()) { 2861 Instruction *I = dyn_cast<Instruction>(Worklist.back()); 2862 Worklist.pop_back(); 2863 2864 // Look at instructions inside this loop. 2865 // Stop when reaching PHI nodes. 2866 // TODO: we need to follow values all over the loop, not only in this block. 2867 if (!I || !TheLoop->contains(I) || isa<PHINode>(I)) 2868 continue; 2869 2870 // This is a known uniform. 2871 Uniforms.insert(I); 2872 2873 // Insert all operands. 2874 Worklist.insert(Worklist.end(), I->op_begin(), I->op_end()); 2875 } 2876} 2877 2878namespace { 2879/// \brief Analyses memory accesses in a loop. 2880/// 2881/// Checks whether run time pointer checks are needed and builds sets for data 2882/// dependence checking. 2883class AccessAnalysis { 2884public: 2885 /// \brief Read or write access location. 2886 typedef PointerIntPair<Value *, 1, bool> MemAccessInfo; 2887 typedef SmallPtrSet<MemAccessInfo, 8> MemAccessInfoSet; 2888 2889 /// \brief Set of potential dependent memory accesses. 2890 typedef EquivalenceClasses<MemAccessInfo> DepCandidates; 2891 2892 AccessAnalysis(DataLayout *Dl, DepCandidates &DA) : 2893 DL(Dl), DepCands(DA), AreAllWritesIdentified(true), 2894 AreAllReadsIdentified(true), IsRTCheckNeeded(false) {} 2895 2896 /// \brief Register a load and whether it is only read from. 2897 void addLoad(Value *Ptr, bool IsReadOnly) { 2898 Accesses.insert(MemAccessInfo(Ptr, false)); 2899 if (IsReadOnly) 2900 ReadOnlyPtr.insert(Ptr); 2901 } 2902 2903 /// \brief Register a store. 2904 void addStore(Value *Ptr) { 2905 Accesses.insert(MemAccessInfo(Ptr, true)); 2906 } 2907 2908 /// \brief Check whether we can check the pointers at runtime for 2909 /// non-intersection. 2910 bool canCheckPtrAtRT(LoopVectorizationLegality::RuntimePointerCheck &RtCheck, 2911 unsigned &NumComparisons, ScalarEvolution *SE, 2912 Loop *TheLoop); 2913 2914 /// \brief Goes over all memory accesses, checks whether a RT check is needed 2915 /// and builds sets of dependent accesses. 2916 void buildDependenceSets() { 2917 // Process read-write pointers first. 2918 processMemAccesses(false); 2919 // Next, process read pointers. 2920 processMemAccesses(true); 2921 } 2922 2923 bool isRTCheckNeeded() { return IsRTCheckNeeded; } 2924 2925 bool isDependencyCheckNeeded() { return !CheckDeps.empty(); } 2926 2927 MemAccessInfoSet &getDependenciesToCheck() { return CheckDeps; } 2928 2929private: 2930 typedef SetVector<MemAccessInfo> PtrAccessSet; 2931 typedef DenseMap<Value*, MemAccessInfo> UnderlyingObjToAccessMap; 2932 2933 /// \brief Go over all memory access or only the deferred ones if 2934 /// \p UseDeferred is true and check whether runtime pointer checks are needed 2935 /// and build sets of dependency check candidates. 2936 void processMemAccesses(bool UseDeferred); 2937 2938 /// Set of all accesses. 2939 PtrAccessSet Accesses; 2940 2941 /// Set of access to check after all writes have been processed. 2942 PtrAccessSet DeferredAccesses; 2943 2944 /// Map of pointers to last access encountered. 2945 UnderlyingObjToAccessMap ObjToLastAccess; 2946 2947 /// Set of accesses that need a further dependence check. 2948 MemAccessInfoSet CheckDeps; 2949 2950 /// Set of pointers that are read only. 2951 SmallPtrSet<Value*, 16> ReadOnlyPtr; 2952 2953 /// Set of underlying objects already written to. 2954 SmallPtrSet<Value*, 16> WriteObjects; 2955 2956 DataLayout *DL; 2957 2958 /// Sets of potentially dependent accesses - members of one set share an 2959 /// underlying pointer. The set "CheckDeps" identfies which sets really need a 2960 /// dependence check. 2961 DepCandidates &DepCands; 2962 2963 bool AreAllWritesIdentified; 2964 bool AreAllReadsIdentified; 2965 bool IsRTCheckNeeded; 2966}; 2967 2968} // end anonymous namespace 2969 2970/// \brief Check whether a pointer can participate in a runtime bounds check. 2971static bool hasComputableBounds(ScalarEvolution *SE, Value *Ptr) { 2972 const SCEV *PtrScev = SE->getSCEV(Ptr); 2973 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PtrScev); 2974 if (!AR) 2975 return false; 2976 2977 return AR->isAffine(); 2978} 2979 2980bool AccessAnalysis::canCheckPtrAtRT( 2981 LoopVectorizationLegality::RuntimePointerCheck &RtCheck, 2982 unsigned &NumComparisons, ScalarEvolution *SE, 2983 Loop *TheLoop) { 2984 // Find pointers with computable bounds. We are going to use this information 2985 // to place a runtime bound check. 2986 unsigned NumReadPtrChecks = 0; 2987 unsigned NumWritePtrChecks = 0; 2988 bool CanDoRT = true; 2989 2990 bool IsDepCheckNeeded = isDependencyCheckNeeded(); 2991 // We assign consecutive id to access from different dependence sets. 2992 // Accesses within the same set don't need a runtime check. 2993 unsigned RunningDepId = 1; 2994 DenseMap<Value *, unsigned> DepSetId; 2995 2996 for (PtrAccessSet::iterator AI = Accesses.begin(), AE = Accesses.end(); 2997 AI != AE; ++AI) { 2998 const MemAccessInfo &Access = *AI; 2999 Value *Ptr = Access.getPointer(); 3000 bool IsWrite = Access.getInt(); 3001 3002 // Just add write checks if we have both. 3003 if (!IsWrite && Accesses.count(MemAccessInfo(Ptr, true))) 3004 continue; 3005 3006 if (IsWrite) 3007 ++NumWritePtrChecks; 3008 else 3009 ++NumReadPtrChecks; 3010 3011 if (hasComputableBounds(SE, Ptr)) { 3012 // The id of the dependence set. 3013 unsigned DepId; 3014 3015 if (IsDepCheckNeeded) { 3016 Value *Leader = DepCands.getLeaderValue(Access).getPointer(); 3017 unsigned &LeaderId = DepSetId[Leader]; 3018 if (!LeaderId) 3019 LeaderId = RunningDepId++; 3020 DepId = LeaderId; 3021 } else 3022 // Each access has its own dependence set. 3023 DepId = RunningDepId++; 3024 3025 RtCheck.insert(SE, TheLoop, Ptr, IsWrite, DepId); 3026 3027 DEBUG(dbgs() << "LV: Found a runtime check ptr:" << *Ptr <<"\n"); 3028 } else { 3029 CanDoRT = false; 3030 } 3031 } 3032 3033 if (IsDepCheckNeeded && CanDoRT && RunningDepId == 2) 3034 NumComparisons = 0; // Only one dependence set. 3035 else 3036 NumComparisons = (NumWritePtrChecks * (NumReadPtrChecks + 3037 NumWritePtrChecks - 1)); 3038 return CanDoRT; 3039} 3040 3041static bool isFunctionScopeIdentifiedObject(Value *Ptr) { 3042 return isNoAliasArgument(Ptr) || isNoAliasCall(Ptr) || isa<AllocaInst>(Ptr); 3043} 3044 3045void AccessAnalysis::processMemAccesses(bool UseDeferred) { 3046 // We process the set twice: first we process read-write pointers, last we 3047 // process read-only pointers. This allows us to skip dependence tests for 3048 // read-only pointers. 3049 3050 PtrAccessSet &S = UseDeferred ? DeferredAccesses : Accesses; 3051 for (PtrAccessSet::iterator AI = S.begin(), AE = S.end(); AI != AE; ++AI) { 3052 const MemAccessInfo &Access = *AI; 3053 Value *Ptr = Access.getPointer(); 3054 bool IsWrite = Access.getInt(); 3055 3056 DepCands.insert(Access); 3057 3058 // Memorize read-only pointers for later processing and skip them in the 3059 // first round (they need to be checked after we have seen all write 3060 // pointers). Note: we also mark pointer that are not consecutive as 3061 // "read-only" pointers (so that we check "a[b[i]] +="). Hence, we need the 3062 // second check for "!IsWrite". 3063 bool IsReadOnlyPtr = ReadOnlyPtr.count(Ptr) && !IsWrite; 3064 if (!UseDeferred && IsReadOnlyPtr) { 3065 DeferredAccesses.insert(Access); 3066 continue; 3067 } 3068 3069 bool NeedDepCheck = false; 3070 // Check whether there is the possiblity of dependency because of underlying 3071 // objects being the same. 3072 typedef SmallVector<Value*, 16> ValueVector; 3073 ValueVector TempObjects; 3074 GetUnderlyingObjects(Ptr, TempObjects, DL); 3075 for (ValueVector::iterator UI = TempObjects.begin(), UE = TempObjects.end(); 3076 UI != UE; ++UI) { 3077 Value *UnderlyingObj = *UI; 3078 3079 // If this is a write then it needs to be an identified object. If this a 3080 // read and all writes (so far) are identified function scope objects we 3081 // don't need an identified underlying object but only an Argument (the 3082 // next write is going to invalidate this assumption if it is 3083 // unidentified). 3084 // This is a micro-optimization for the case where all writes are 3085 // identified and we have one argument pointer. 3086 // Otherwise, we do need a runtime check. 3087 if ((IsWrite && !isFunctionScopeIdentifiedObject(UnderlyingObj)) || 3088 (!IsWrite && (!AreAllWritesIdentified || 3089 !isa<Argument>(UnderlyingObj)) && 3090 !isIdentifiedObject(UnderlyingObj))) { 3091 DEBUG(dbgs() << "LV: Found an unidentified " << 3092 (IsWrite ? "write" : "read" ) << " ptr:" << *UnderlyingObj << 3093 "\n"); 3094 IsRTCheckNeeded = (IsRTCheckNeeded || 3095 !isIdentifiedObject(UnderlyingObj) || 3096 !AreAllReadsIdentified); 3097 3098 if (IsWrite) 3099 AreAllWritesIdentified = false; 3100 if (!IsWrite) 3101 AreAllReadsIdentified = false; 3102 } 3103 3104 // If this is a write - check other reads and writes for conflicts. If 3105 // this is a read only check other writes for conflicts (but only if there 3106 // is no other write to the ptr - this is an optimization to catch "a[i] = 3107 // a[i] + " without having to do a dependence check). 3108 if ((IsWrite || IsReadOnlyPtr) && WriteObjects.count(UnderlyingObj)) 3109 NeedDepCheck = true; 3110 3111 if (IsWrite) 3112 WriteObjects.insert(UnderlyingObj); 3113 3114 // Create sets of pointers connected by shared underlying objects. 3115 UnderlyingObjToAccessMap::iterator Prev = 3116 ObjToLastAccess.find(UnderlyingObj); 3117 if (Prev != ObjToLastAccess.end()) 3118 DepCands.unionSets(Access, Prev->second); 3119 3120 ObjToLastAccess[UnderlyingObj] = Access; 3121 } 3122 3123 if (NeedDepCheck) 3124 CheckDeps.insert(Access); 3125 } 3126} 3127 3128namespace { 3129/// \brief Checks memory dependences among accesses to the same underlying 3130/// object to determine whether there vectorization is legal or not (and at 3131/// which vectorization factor). 3132/// 3133/// This class works under the assumption that we already checked that memory 3134/// locations with different underlying pointers are "must-not alias". 3135/// We use the ScalarEvolution framework to symbolically evalutate access 3136/// functions pairs. Since we currently don't restructure the loop we can rely 3137/// on the program order of memory accesses to determine their safety. 3138/// At the moment we will only deem accesses as safe for: 3139/// * A negative constant distance assuming program order. 3140/// 3141/// Safe: tmp = a[i + 1]; OR a[i + 1] = x; 3142/// a[i] = tmp; y = a[i]; 3143/// 3144/// The latter case is safe because later checks guarantuee that there can't 3145/// be a cycle through a phi node (that is, we check that "x" and "y" is not 3146/// the same variable: a header phi can only be an induction or a reduction, a 3147/// reduction can't have a memory sink, an induction can't have a memory 3148/// source). This is important and must not be violated (or we have to 3149/// resort to checking for cycles through memory). 3150/// 3151/// * A positive constant distance assuming program order that is bigger 3152/// than the biggest memory access. 3153/// 3154/// tmp = a[i] OR b[i] = x 3155/// a[i+2] = tmp y = b[i+2]; 3156/// 3157/// Safe distance: 2 x sizeof(a[0]), and 2 x sizeof(b[0]), respectively. 3158/// 3159/// * Zero distances and all accesses have the same size. 3160/// 3161class MemoryDepChecker { 3162public: 3163 typedef PointerIntPair<Value *, 1, bool> MemAccessInfo; 3164 typedef SmallPtrSet<MemAccessInfo, 8> MemAccessInfoSet; 3165 3166 MemoryDepChecker(ScalarEvolution *Se, DataLayout *Dl, const Loop *L) : 3167 SE(Se), DL(Dl), InnermostLoop(L), AccessIdx(0) {} 3168 3169 /// \brief Register the location (instructions are given increasing numbers) 3170 /// of a write access. 3171 void addAccess(StoreInst *SI) { 3172 Value *Ptr = SI->getPointerOperand(); 3173 Accesses[MemAccessInfo(Ptr, true)].push_back(AccessIdx); 3174 InstMap.push_back(SI); 3175 ++AccessIdx; 3176 } 3177 3178 /// \brief Register the location (instructions are given increasing numbers) 3179 /// of a write access. 3180 void addAccess(LoadInst *LI) { 3181 Value *Ptr = LI->getPointerOperand(); 3182 Accesses[MemAccessInfo(Ptr, false)].push_back(AccessIdx); 3183 InstMap.push_back(LI); 3184 ++AccessIdx; 3185 } 3186 3187 /// \brief Check whether the dependencies between the accesses are safe. 3188 /// 3189 /// Only checks sets with elements in \p CheckDeps. 3190 bool areDepsSafe(AccessAnalysis::DepCandidates &AccessSets, 3191 MemAccessInfoSet &CheckDeps); 3192 3193 /// \brief The maximum number of bytes of a vector register we can vectorize 3194 /// the accesses safely with. 3195 unsigned getMaxSafeDepDistBytes() { return MaxSafeDepDistBytes; } 3196 3197private: 3198 ScalarEvolution *SE; 3199 DataLayout *DL; 3200 const Loop *InnermostLoop; 3201 3202 /// \brief Maps access locations (ptr, read/write) to program order. 3203 DenseMap<MemAccessInfo, std::vector<unsigned> > Accesses; 3204 3205 /// \brief Memory access instructions in program order. 3206 SmallVector<Instruction *, 16> InstMap; 3207 3208 /// \brief The program order index to be used for the next instruction. 3209 unsigned AccessIdx; 3210 3211 // We can access this many bytes in parallel safely. 3212 unsigned MaxSafeDepDistBytes; 3213 3214 /// \brief Check whether there is a plausible dependence between the two 3215 /// accesses. 3216 /// 3217 /// Access \p A must happen before \p B in program order. The two indices 3218 /// identify the index into the program order map. 3219 /// 3220 /// This function checks whether there is a plausible dependence (or the 3221 /// absence of such can't be proved) between the two accesses. If there is a 3222 /// plausible dependence but the dependence distance is bigger than one 3223 /// element access it records this distance in \p MaxSafeDepDistBytes (if this 3224 /// distance is smaller than any other distance encountered so far). 3225 /// Otherwise, this function returns true signaling a possible dependence. 3226 bool isDependent(const MemAccessInfo &A, unsigned AIdx, 3227 const MemAccessInfo &B, unsigned BIdx); 3228 3229 /// \brief Check whether the data dependence could prevent store-load 3230 /// forwarding. 3231 bool couldPreventStoreLoadForward(unsigned Distance, unsigned TypeByteSize); 3232}; 3233 3234} // end anonymous namespace 3235 3236static bool isInBoundsGep(Value *Ptr) { 3237 if (GetElementPtrInst *GEP = dyn_cast<GetElementPtrInst>(Ptr)) 3238 return GEP->isInBounds(); 3239 return false; 3240} 3241 3242/// \brief Check whether the access through \p Ptr has a constant stride. 3243static int isStridedPtr(ScalarEvolution *SE, DataLayout *DL, Value *Ptr, 3244 const Loop *Lp) { 3245 const Type *Ty = Ptr->getType(); 3246 assert(Ty->isPointerTy() && "Unexpected non ptr"); 3247 3248 // Make sure that the pointer does not point to aggregate types. 3249 const PointerType *PtrTy = cast<PointerType>(Ty); 3250 if (PtrTy->getElementType()->isAggregateType()) { 3251 DEBUG(dbgs() << "LV: Bad stride - Not a pointer to a scalar type" << *Ptr << 3252 "\n"); 3253 return 0; 3254 } 3255 3256 const SCEV *PtrScev = SE->getSCEV(Ptr); 3257 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PtrScev); 3258 if (!AR) { 3259 DEBUG(dbgs() << "LV: Bad stride - Not an AddRecExpr pointer " 3260 << *Ptr << " SCEV: " << *PtrScev << "\n"); 3261 return 0; 3262 } 3263 3264 // The accesss function must stride over the innermost loop. 3265 if (Lp != AR->getLoop()) { 3266 DEBUG(dbgs() << "LV: Bad stride - Not striding over innermost loop " << 3267 *Ptr << " SCEV: " << *PtrScev << "\n"); 3268 } 3269 3270 // The address calculation must not wrap. Otherwise, a dependence could be 3271 // inverted. 3272 // An inbounds getelementptr that is a AddRec with a unit stride 3273 // cannot wrap per definition. The unit stride requirement is checked later. 3274 // An getelementptr without an inbounds attribute and unit stride would have 3275 // to access the pointer value "0" which is undefined behavior in address 3276 // space 0, therefore we can also vectorize this case. 3277 bool IsInBoundsGEP = isInBoundsGep(Ptr); 3278 bool IsNoWrapAddRec = AR->getNoWrapFlags(SCEV::NoWrapMask); 3279 bool IsInAddressSpaceZero = PtrTy->getAddressSpace() == 0; 3280 if (!IsNoWrapAddRec && !IsInBoundsGEP && !IsInAddressSpaceZero) { 3281 DEBUG(dbgs() << "LV: Bad stride - Pointer may wrap in the address space " 3282 << *Ptr << " SCEV: " << *PtrScev << "\n"); 3283 return 0; 3284 } 3285 3286 // Check the step is constant. 3287 const SCEV *Step = AR->getStepRecurrence(*SE); 3288 3289 // Calculate the pointer stride and check if it is consecutive. 3290 const SCEVConstant *C = dyn_cast<SCEVConstant>(Step); 3291 if (!C) { 3292 DEBUG(dbgs() << "LV: Bad stride - Not a constant strided " << *Ptr << 3293 " SCEV: " << *PtrScev << "\n"); 3294 return 0; 3295 } 3296 3297 int64_t Size = DL->getTypeAllocSize(PtrTy->getElementType()); 3298 const APInt &APStepVal = C->getValue()->getValue(); 3299 3300 // Huge step value - give up. 3301 if (APStepVal.getBitWidth() > 64) 3302 return 0; 3303 3304 int64_t StepVal = APStepVal.getSExtValue(); 3305 3306 // Strided access. 3307 int64_t Stride = StepVal / Size; 3308 int64_t Rem = StepVal % Size; 3309 if (Rem) 3310 return 0; 3311 3312 // If the SCEV could wrap but we have an inbounds gep with a unit stride we 3313 // know we can't "wrap around the address space". In case of address space 3314 // zero we know that this won't happen without triggering undefined behavior. 3315 if (!IsNoWrapAddRec && (IsInBoundsGEP || IsInAddressSpaceZero) && 3316 Stride != 1 && Stride != -1) 3317 return 0; 3318 3319 return Stride; 3320} 3321 3322bool MemoryDepChecker::couldPreventStoreLoadForward(unsigned Distance, 3323 unsigned TypeByteSize) { 3324 // If loads occur at a distance that is not a multiple of a feasible vector 3325 // factor store-load forwarding does not take place. 3326 // Positive dependences might cause troubles because vectorizing them might 3327 // prevent store-load forwarding making vectorized code run a lot slower. 3328 // a[i] = a[i-3] ^ a[i-8]; 3329 // The stores to a[i:i+1] don't align with the stores to a[i-3:i-2] and 3330 // hence on your typical architecture store-load forwarding does not take 3331 // place. Vectorizing in such cases does not make sense. 3332 // Store-load forwarding distance. 3333 const unsigned NumCyclesForStoreLoadThroughMemory = 8*TypeByteSize; 3334 // Maximum vector factor. 3335 unsigned MaxVFWithoutSLForwardIssues = MaxVectorWidth*TypeByteSize; 3336 if(MaxSafeDepDistBytes < MaxVFWithoutSLForwardIssues) 3337 MaxVFWithoutSLForwardIssues = MaxSafeDepDistBytes; 3338 3339 for (unsigned vf = 2*TypeByteSize; vf <= MaxVFWithoutSLForwardIssues; 3340 vf *= 2) { 3341 if (Distance % vf && Distance / vf < NumCyclesForStoreLoadThroughMemory) { 3342 MaxVFWithoutSLForwardIssues = (vf >>=1); 3343 break; 3344 } 3345 } 3346 3347 if (MaxVFWithoutSLForwardIssues< 2*TypeByteSize) { 3348 DEBUG(dbgs() << "LV: Distance " << Distance << 3349 " that could cause a store-load forwarding conflict\n"); 3350 return true; 3351 } 3352 3353 if (MaxVFWithoutSLForwardIssues < MaxSafeDepDistBytes && 3354 MaxVFWithoutSLForwardIssues != MaxVectorWidth*TypeByteSize) 3355 MaxSafeDepDistBytes = MaxVFWithoutSLForwardIssues; 3356 return false; 3357} 3358 3359bool MemoryDepChecker::isDependent(const MemAccessInfo &A, unsigned AIdx, 3360 const MemAccessInfo &B, unsigned BIdx) { 3361 assert (AIdx < BIdx && "Must pass arguments in program order"); 3362 3363 Value *APtr = A.getPointer(); 3364 Value *BPtr = B.getPointer(); 3365 bool AIsWrite = A.getInt(); 3366 bool BIsWrite = B.getInt(); 3367 3368 // Two reads are independent. 3369 if (!AIsWrite && !BIsWrite) 3370 return false; 3371 3372 const SCEV *AScev = SE->getSCEV(APtr); 3373 const SCEV *BScev = SE->getSCEV(BPtr); 3374 3375 int StrideAPtr = isStridedPtr(SE, DL, APtr, InnermostLoop); 3376 int StrideBPtr = isStridedPtr(SE, DL, BPtr, InnermostLoop); 3377 3378 const SCEV *Src = AScev; 3379 const SCEV *Sink = BScev; 3380 3381 // If the induction step is negative we have to invert source and sink of the 3382 // dependence. 3383 if (StrideAPtr < 0) { 3384 //Src = BScev; 3385 //Sink = AScev; 3386 std::swap(APtr, BPtr); 3387 std::swap(Src, Sink); 3388 std::swap(AIsWrite, BIsWrite); 3389 std::swap(AIdx, BIdx); 3390 std::swap(StrideAPtr, StrideBPtr); 3391 } 3392 3393 const SCEV *Dist = SE->getMinusSCEV(Sink, Src); 3394 3395 DEBUG(dbgs() << "LV: Src Scev: " << *Src << "Sink Scev: " << *Sink 3396 << "(Induction step: " << StrideAPtr << ")\n"); 3397 DEBUG(dbgs() << "LV: Distance for " << *InstMap[AIdx] << " to " 3398 << *InstMap[BIdx] << ": " << *Dist << "\n"); 3399 3400 // Need consecutive accesses. We don't want to vectorize 3401 // "A[B[i]] += ..." and similar code or pointer arithmetic that could wrap in 3402 // the address space. 3403 if (!StrideAPtr || !StrideBPtr || StrideAPtr != StrideBPtr){ 3404 DEBUG(dbgs() << "Non-consecutive pointer access\n"); 3405 return true; 3406 } 3407 3408 const SCEVConstant *C = dyn_cast<SCEVConstant>(Dist); 3409 if (!C) { 3410 DEBUG(dbgs() << "LV: Dependence because of non constant distance\n"); 3411 return true; 3412 } 3413 3414 Type *ATy = APtr->getType()->getPointerElementType(); 3415 Type *BTy = BPtr->getType()->getPointerElementType(); 3416 unsigned TypeByteSize = DL->getTypeAllocSize(ATy); 3417 3418 // Negative distances are not plausible dependencies. 3419 const APInt &Val = C->getValue()->getValue(); 3420 if (Val.isNegative()) { 3421 bool IsTrueDataDependence = (AIsWrite && !BIsWrite); 3422 if (IsTrueDataDependence && 3423 (couldPreventStoreLoadForward(Val.abs().getZExtValue(), TypeByteSize) || 3424 ATy != BTy)) 3425 return true; 3426 3427 DEBUG(dbgs() << "LV: Dependence is negative: NoDep\n"); 3428 return false; 3429 } 3430 3431 // Write to the same location with the same size. 3432 // Could be improved to assert type sizes are the same (i32 == float, etc). 3433 if (Val == 0) { 3434 if (ATy == BTy) 3435 return false; 3436 DEBUG(dbgs() << "LV: Zero dependence difference but different types"); 3437 return true; 3438 } 3439 3440 assert(Val.isStrictlyPositive() && "Expect a positive value"); 3441 3442 // Positive distance bigger than max vectorization factor. 3443 if (ATy != BTy) { 3444 DEBUG(dbgs() << 3445 "LV: ReadWrite-Write positive dependency with different types"); 3446 return false; 3447 } 3448 3449 unsigned Distance = (unsigned) Val.getZExtValue(); 3450 3451 // Bail out early if passed-in parameters make vectorization not feasible. 3452 unsigned ForcedFactor = VectorizationFactor ? VectorizationFactor : 1; 3453 unsigned ForcedUnroll = VectorizationUnroll ? VectorizationUnroll : 1; 3454 3455 // The distance must be bigger than the size needed for a vectorized version 3456 // of the operation and the size of the vectorized operation must not be 3457 // bigger than the currrent maximum size. 3458 if (Distance < 2*TypeByteSize || 3459 2*TypeByteSize > MaxSafeDepDistBytes || 3460 Distance < TypeByteSize * ForcedUnroll * ForcedFactor) { 3461 DEBUG(dbgs() << "LV: Failure because of Positive distance " 3462 << Val.getSExtValue() << "\n"); 3463 return true; 3464 } 3465 3466 MaxSafeDepDistBytes = Distance < MaxSafeDepDistBytes ? 3467 Distance : MaxSafeDepDistBytes; 3468 3469 bool IsTrueDataDependence = (!AIsWrite && BIsWrite); 3470 if (IsTrueDataDependence && 3471 couldPreventStoreLoadForward(Distance, TypeByteSize)) 3472 return true; 3473 3474 DEBUG(dbgs() << "LV: Positive distance " << Val.getSExtValue() << 3475 " with max VF=" << MaxSafeDepDistBytes/TypeByteSize << "\n"); 3476 3477 return false; 3478} 3479 3480bool 3481MemoryDepChecker::areDepsSafe(AccessAnalysis::DepCandidates &AccessSets, 3482 MemAccessInfoSet &CheckDeps) { 3483 3484 MaxSafeDepDistBytes = -1U; 3485 while (!CheckDeps.empty()) { 3486 MemAccessInfo CurAccess = *CheckDeps.begin(); 3487 3488 // Get the relevant memory access set. 3489 EquivalenceClasses<MemAccessInfo>::iterator I = 3490 AccessSets.findValue(AccessSets.getLeaderValue(CurAccess)); 3491 3492 // Check accesses within this set. 3493 EquivalenceClasses<MemAccessInfo>::member_iterator AI, AE; 3494 AI = AccessSets.member_begin(I), AE = AccessSets.member_end(); 3495 3496 // Check every access pair. 3497 while (AI != AE) { 3498 CheckDeps.erase(*AI); 3499 EquivalenceClasses<MemAccessInfo>::member_iterator OI = llvm::next(AI); 3500 while (OI != AE) { 3501 // Check every accessing instruction pair in program order. 3502 for (std::vector<unsigned>::iterator I1 = Accesses[*AI].begin(), 3503 I1E = Accesses[*AI].end(); I1 != I1E; ++I1) 3504 for (std::vector<unsigned>::iterator I2 = Accesses[*OI].begin(), 3505 I2E = Accesses[*OI].end(); I2 != I2E; ++I2) { 3506 if (*I1 < *I2 && isDependent(*AI, *I1, *OI, *I2)) 3507 return false; 3508 if (*I2 < *I1 && isDependent(*OI, *I2, *AI, *I1)) 3509 return false; 3510 } 3511 ++OI; 3512 } 3513 AI++; 3514 } 3515 } 3516 return true; 3517} 3518 3519bool LoopVectorizationLegality::canVectorizeMemory() { 3520 3521 typedef SmallVector<Value*, 16> ValueVector; 3522 typedef SmallPtrSet<Value*, 16> ValueSet; 3523 3524 // Holds the Load and Store *instructions*. 3525 ValueVector Loads; 3526 ValueVector Stores; 3527 3528 // Holds all the different accesses in the loop. 3529 unsigned NumReads = 0; 3530 unsigned NumReadWrites = 0; 3531 3532 PtrRtCheck.Pointers.clear(); 3533 PtrRtCheck.Need = false; 3534 3535 const bool IsAnnotatedParallel = TheLoop->isAnnotatedParallel(); 3536 MemoryDepChecker DepChecker(SE, DL, TheLoop); 3537 3538 // For each block. 3539 for (Loop::block_iterator bb = TheLoop->block_begin(), 3540 be = TheLoop->block_end(); bb != be; ++bb) { 3541 3542 // Scan the BB and collect legal loads and stores. 3543 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e; 3544 ++it) { 3545 3546 // If this is a load, save it. If this instruction can read from memory 3547 // but is not a load, then we quit. Notice that we don't handle function 3548 // calls that read or write. 3549 if (it->mayReadFromMemory()) { 3550 // Many math library functions read the rounding mode. We will only 3551 // vectorize a loop if it contains known function calls that don't set 3552 // the flag. Therefore, it is safe to ignore this read from memory. 3553 CallInst *Call = dyn_cast<CallInst>(it); 3554 if (Call && getIntrinsicIDForCall(Call, TLI)) 3555 continue; 3556 3557 LoadInst *Ld = dyn_cast<LoadInst>(it); 3558 if (!Ld) return false; 3559 if (!Ld->isSimple() && !IsAnnotatedParallel) { 3560 DEBUG(dbgs() << "LV: Found a non-simple load.\n"); 3561 return false; 3562 } 3563 Loads.push_back(Ld); 3564 DepChecker.addAccess(Ld); 3565 continue; 3566 } 3567 3568 // Save 'store' instructions. Abort if other instructions write to memory. 3569 if (it->mayWriteToMemory()) { 3570 StoreInst *St = dyn_cast<StoreInst>(it); 3571 if (!St) return false; 3572 if (!St->isSimple() && !IsAnnotatedParallel) { 3573 DEBUG(dbgs() << "LV: Found a non-simple store.\n"); 3574 return false; 3575 } 3576 Stores.push_back(St); 3577 DepChecker.addAccess(St); 3578 } 3579 } // next instr. 3580 } // next block. 3581 3582 // Now we have two lists that hold the loads and the stores. 3583 // Next, we find the pointers that they use. 3584 3585 // Check if we see any stores. If there are no stores, then we don't 3586 // care if the pointers are *restrict*. 3587 if (!Stores.size()) { 3588 DEBUG(dbgs() << "LV: Found a read-only loop!\n"); 3589 return true; 3590 } 3591 3592 AccessAnalysis::DepCandidates DependentAccesses; 3593 AccessAnalysis Accesses(DL, DependentAccesses); 3594 3595 // Holds the analyzed pointers. We don't want to call GetUnderlyingObjects 3596 // multiple times on the same object. If the ptr is accessed twice, once 3597 // for read and once for write, it will only appear once (on the write 3598 // list). This is okay, since we are going to check for conflicts between 3599 // writes and between reads and writes, but not between reads and reads. 3600 ValueSet Seen; 3601 3602 ValueVector::iterator I, IE; 3603 for (I = Stores.begin(), IE = Stores.end(); I != IE; ++I) { 3604 StoreInst *ST = cast<StoreInst>(*I); 3605 Value* Ptr = ST->getPointerOperand(); 3606 3607 if (isUniform(Ptr)) { 3608 DEBUG(dbgs() << "LV: We don't allow storing to uniform addresses\n"); 3609 return false; 3610 } 3611 3612 // If we did *not* see this pointer before, insert it to the read-write 3613 // list. At this phase it is only a 'write' list. 3614 if (Seen.insert(Ptr)) { 3615 ++NumReadWrites; 3616 Accesses.addStore(Ptr); 3617 } 3618 } 3619 3620 if (IsAnnotatedParallel) { 3621 DEBUG(dbgs() 3622 << "LV: A loop annotated parallel, ignore memory dependency " 3623 << "checks.\n"); 3624 return true; 3625 } 3626 3627 SmallPtrSet<Value *, 16> ReadOnlyPtr; 3628 for (I = Loads.begin(), IE = Loads.end(); I != IE; ++I) { 3629 LoadInst *LD = cast<LoadInst>(*I); 3630 Value* Ptr = LD->getPointerOperand(); 3631 // If we did *not* see this pointer before, insert it to the 3632 // read list. If we *did* see it before, then it is already in 3633 // the read-write list. This allows us to vectorize expressions 3634 // such as A[i] += x; Because the address of A[i] is a read-write 3635 // pointer. This only works if the index of A[i] is consecutive. 3636 // If the address of i is unknown (for example A[B[i]]) then we may 3637 // read a few words, modify, and write a few words, and some of the 3638 // words may be written to the same address. 3639 bool IsReadOnlyPtr = false; 3640 if (Seen.insert(Ptr) || !isStridedPtr(SE, DL, Ptr, TheLoop)) { 3641 ++NumReads; 3642 IsReadOnlyPtr = true; 3643 } 3644 Accesses.addLoad(Ptr, IsReadOnlyPtr); 3645 } 3646 3647 // If we write (or read-write) to a single destination and there are no 3648 // other reads in this loop then is it safe to vectorize. 3649 if (NumReadWrites == 1 && NumReads == 0) { 3650 DEBUG(dbgs() << "LV: Found a write-only loop!\n"); 3651 return true; 3652 } 3653 3654 // Build dependence sets and check whether we need a runtime pointer bounds 3655 // check. 3656 Accesses.buildDependenceSets(); 3657 bool NeedRTCheck = Accesses.isRTCheckNeeded(); 3658 3659 // Find pointers with computable bounds. We are going to use this information 3660 // to place a runtime bound check. 3661 unsigned NumComparisons = 0; 3662 bool CanDoRT = false; 3663 if (NeedRTCheck) 3664 CanDoRT = Accesses.canCheckPtrAtRT(PtrRtCheck, NumComparisons, SE, TheLoop); 3665 3666 3667 DEBUG(dbgs() << "LV: We need to do " << NumComparisons << 3668 " pointer comparisons.\n"); 3669 3670 // If we only have one set of dependences to check pointers among we don't 3671 // need a runtime check. 3672 if (NumComparisons == 0 && NeedRTCheck) 3673 NeedRTCheck = false; 3674 3675 // Check that we did not collect too many pointers or found a unsizeable 3676 // pointer. 3677 if (!CanDoRT || NumComparisons > RuntimeMemoryCheckThreshold) { 3678 PtrRtCheck.reset(); 3679 CanDoRT = false; 3680 } 3681 3682 if (CanDoRT) { 3683 DEBUG(dbgs() << "LV: We can perform a memory runtime check if needed.\n"); 3684 } 3685 3686 if (NeedRTCheck && !CanDoRT) { 3687 DEBUG(dbgs() << "LV: We can't vectorize because we can't find " << 3688 "the array bounds.\n"); 3689 PtrRtCheck.reset(); 3690 return false; 3691 } 3692 3693 PtrRtCheck.Need = NeedRTCheck; 3694 3695 bool CanVecMem = true; 3696 if (Accesses.isDependencyCheckNeeded()) { 3697 DEBUG(dbgs() << "LV: Checking memory dependencies\n"); 3698 CanVecMem = DepChecker.areDepsSafe(DependentAccesses, 3699 Accesses.getDependenciesToCheck()); 3700 MaxSafeDepDistBytes = DepChecker.getMaxSafeDepDistBytes(); 3701 } 3702 3703 DEBUG(dbgs() << "LV: We "<< (NeedRTCheck ? "" : "don't") << 3704 " need a runtime memory check.\n"); 3705 3706 return CanVecMem; 3707} 3708 3709static bool hasMultipleUsesOf(Instruction *I, 3710 SmallPtrSet<Instruction *, 8> &Insts) { 3711 unsigned NumUses = 0; 3712 for(User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E; ++Use) { 3713 if (Insts.count(dyn_cast<Instruction>(*Use))) 3714 ++NumUses; 3715 if (NumUses > 1) 3716 return true; 3717 } 3718 3719 return false; 3720} 3721 3722static bool areAllUsesIn(Instruction *I, SmallPtrSet<Instruction *, 8> &Set) { 3723 for(User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E; ++Use) 3724 if (!Set.count(dyn_cast<Instruction>(*Use))) 3725 return false; 3726 return true; 3727} 3728 3729bool LoopVectorizationLegality::AddReductionVar(PHINode *Phi, 3730 ReductionKind Kind) { 3731 if (Phi->getNumIncomingValues() != 2) 3732 return false; 3733 3734 // Reduction variables are only found in the loop header block. 3735 if (Phi->getParent() != TheLoop->getHeader()) 3736 return false; 3737 3738 // Obtain the reduction start value from the value that comes from the loop 3739 // preheader. 3740 Value *RdxStart = Phi->getIncomingValueForBlock(TheLoop->getLoopPreheader()); 3741 3742 // ExitInstruction is the single value which is used outside the loop. 3743 // We only allow for a single reduction value to be used outside the loop. 3744 // This includes users of the reduction, variables (which form a cycle 3745 // which ends in the phi node). 3746 Instruction *ExitInstruction = 0; 3747 // Indicates that we found a reduction operation in our scan. 3748 bool FoundReduxOp = false; 3749 3750 // We start with the PHI node and scan for all of the users of this 3751 // instruction. All users must be instructions that can be used as reduction 3752 // variables (such as ADD). We must have a single out-of-block user. The cycle 3753 // must include the original PHI. 3754 bool FoundStartPHI = false; 3755 3756 // To recognize min/max patterns formed by a icmp select sequence, we store 3757 // the number of instruction we saw from the recognized min/max pattern, 3758 // to make sure we only see exactly the two instructions. 3759 unsigned NumCmpSelectPatternInst = 0; 3760 ReductionInstDesc ReduxDesc(false, 0); 3761 3762 SmallPtrSet<Instruction *, 8> VisitedInsts; 3763 SmallVector<Instruction *, 8> Worklist; 3764 Worklist.push_back(Phi); 3765 VisitedInsts.insert(Phi); 3766 3767 // A value in the reduction can be used: 3768 // - By the reduction: 3769 // - Reduction operation: 3770 // - One use of reduction value (safe). 3771 // - Multiple use of reduction value (not safe). 3772 // - PHI: 3773 // - All uses of the PHI must be the reduction (safe). 3774 // - Otherwise, not safe. 3775 // - By one instruction outside of the loop (safe). 3776 // - By further instructions outside of the loop (not safe). 3777 // - By an instruction that is not part of the reduction (not safe). 3778 // This is either: 3779 // * An instruction type other than PHI or the reduction operation. 3780 // * A PHI in the header other than the initial PHI. 3781 while (!Worklist.empty()) { 3782 Instruction *Cur = Worklist.back(); 3783 Worklist.pop_back(); 3784 3785 // No Users. 3786 // If the instruction has no users then this is a broken chain and can't be 3787 // a reduction variable. 3788 if (Cur->use_empty()) 3789 return false; 3790 3791 bool IsAPhi = isa<PHINode>(Cur); 3792 3793 // A header PHI use other than the original PHI. 3794 if (Cur != Phi && IsAPhi && Cur->getParent() == Phi->getParent()) 3795 return false; 3796 3797 // Reductions of instructions such as Div, and Sub is only possible if the 3798 // LHS is the reduction variable. 3799 if (!Cur->isCommutative() && !IsAPhi && !isa<SelectInst>(Cur) && 3800 !isa<ICmpInst>(Cur) && !isa<FCmpInst>(Cur) && 3801 !VisitedInsts.count(dyn_cast<Instruction>(Cur->getOperand(0)))) 3802 return false; 3803 3804 // Any reduction instruction must be of one of the allowed kinds. 3805 ReduxDesc = isReductionInstr(Cur, Kind, ReduxDesc); 3806 if (!ReduxDesc.IsReduction) 3807 return false; 3808 3809 // A reduction operation must only have one use of the reduction value. 3810 if (!IsAPhi && Kind != RK_IntegerMinMax && Kind != RK_FloatMinMax && 3811 hasMultipleUsesOf(Cur, VisitedInsts)) 3812 return false; 3813 3814 // All inputs to a PHI node must be a reduction value. 3815 if(IsAPhi && Cur != Phi && !areAllUsesIn(Cur, VisitedInsts)) 3816 return false; 3817 3818 if (Kind == RK_IntegerMinMax && (isa<ICmpInst>(Cur) || 3819 isa<SelectInst>(Cur))) 3820 ++NumCmpSelectPatternInst; 3821 if (Kind == RK_FloatMinMax && (isa<FCmpInst>(Cur) || 3822 isa<SelectInst>(Cur))) 3823 ++NumCmpSelectPatternInst; 3824 3825 // Check whether we found a reduction operator. 3826 FoundReduxOp |= !IsAPhi; 3827 3828 // Process users of current instruction. Push non PHI nodes after PHI nodes 3829 // onto the stack. This way we are going to have seen all inputs to PHI 3830 // nodes once we get to them. 3831 SmallVector<Instruction *, 8> NonPHIs; 3832 SmallVector<Instruction *, 8> PHIs; 3833 for (Value::use_iterator UI = Cur->use_begin(), E = Cur->use_end(); UI != E; 3834 ++UI) { 3835 Instruction *Usr = cast<Instruction>(*UI); 3836 3837 // Check if we found the exit user. 3838 BasicBlock *Parent = Usr->getParent(); 3839 if (!TheLoop->contains(Parent)) { 3840 // Exit if you find multiple outside users or if the header phi node is 3841 // being used. In this case the user uses the value of the previous 3842 // iteration, in which case we would loose "VF-1" iterations of the 3843 // reduction operation if we vectorize. 3844 if (ExitInstruction != 0 || Cur == Phi) 3845 return false; 3846 3847 ExitInstruction = Cur; 3848 continue; 3849 } 3850 3851 // Process instructions only once (termination). 3852 if (VisitedInsts.insert(Usr)) { 3853 if (isa<PHINode>(Usr)) 3854 PHIs.push_back(Usr); 3855 else 3856 NonPHIs.push_back(Usr); 3857 } 3858 // Remember that we completed the cycle. 3859 if (Usr == Phi) 3860 FoundStartPHI = true; 3861 } 3862 Worklist.append(PHIs.begin(), PHIs.end()); 3863 Worklist.append(NonPHIs.begin(), NonPHIs.end()); 3864 } 3865 3866 // This means we have seen one but not the other instruction of the 3867 // pattern or more than just a select and cmp. 3868 if ((Kind == RK_IntegerMinMax || Kind == RK_FloatMinMax) && 3869 NumCmpSelectPatternInst != 2) 3870 return false; 3871 3872 if (!FoundStartPHI || !FoundReduxOp || !ExitInstruction) 3873 return false; 3874 3875 // We found a reduction var if we have reached the original phi node and we 3876 // only have a single instruction with out-of-loop users. 3877 3878 // This instruction is allowed to have out-of-loop users. 3879 AllowedExit.insert(ExitInstruction); 3880 3881 // Save the description of this reduction variable. 3882 ReductionDescriptor RD(RdxStart, ExitInstruction, Kind, 3883 ReduxDesc.MinMaxKind); 3884 Reductions[Phi] = RD; 3885 // We've ended the cycle. This is a reduction variable if we have an 3886 // outside user and it has a binary op. 3887 3888 return true; 3889} 3890 3891/// Returns true if the instruction is a Select(ICmp(X, Y), X, Y) instruction 3892/// pattern corresponding to a min(X, Y) or max(X, Y). 3893LoopVectorizationLegality::ReductionInstDesc 3894LoopVectorizationLegality::isMinMaxSelectCmpPattern(Instruction *I, 3895 ReductionInstDesc &Prev) { 3896 3897 assert((isa<ICmpInst>(I) || isa<FCmpInst>(I) || isa<SelectInst>(I)) && 3898 "Expect a select instruction"); 3899 Instruction *Cmp = 0; 3900 SelectInst *Select = 0; 3901 3902 // We must handle the select(cmp()) as a single instruction. Advance to the 3903 // select. 3904 if ((Cmp = dyn_cast<ICmpInst>(I)) || (Cmp = dyn_cast<FCmpInst>(I))) { 3905 if (!Cmp->hasOneUse() || !(Select = dyn_cast<SelectInst>(*I->use_begin()))) 3906 return ReductionInstDesc(false, I); 3907 return ReductionInstDesc(Select, Prev.MinMaxKind); 3908 } 3909 3910 // Only handle single use cases for now. 3911 if (!(Select = dyn_cast<SelectInst>(I))) 3912 return ReductionInstDesc(false, I); 3913 if (!(Cmp = dyn_cast<ICmpInst>(I->getOperand(0))) && 3914 !(Cmp = dyn_cast<FCmpInst>(I->getOperand(0)))) 3915 return ReductionInstDesc(false, I); 3916 if (!Cmp->hasOneUse()) 3917 return ReductionInstDesc(false, I); 3918 3919 Value *CmpLeft; 3920 Value *CmpRight; 3921 3922 // Look for a min/max pattern. 3923 if (m_UMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 3924 return ReductionInstDesc(Select, MRK_UIntMin); 3925 else if (m_UMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 3926 return ReductionInstDesc(Select, MRK_UIntMax); 3927 else if (m_SMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 3928 return ReductionInstDesc(Select, MRK_SIntMax); 3929 else if (m_SMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 3930 return ReductionInstDesc(Select, MRK_SIntMin); 3931 else if (m_OrdFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 3932 return ReductionInstDesc(Select, MRK_FloatMin); 3933 else if (m_OrdFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 3934 return ReductionInstDesc(Select, MRK_FloatMax); 3935 else if (m_UnordFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 3936 return ReductionInstDesc(Select, MRK_FloatMin); 3937 else if (m_UnordFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 3938 return ReductionInstDesc(Select, MRK_FloatMax); 3939 3940 return ReductionInstDesc(false, I); 3941} 3942 3943LoopVectorizationLegality::ReductionInstDesc 3944LoopVectorizationLegality::isReductionInstr(Instruction *I, 3945 ReductionKind Kind, 3946 ReductionInstDesc &Prev) { 3947 bool FP = I->getType()->isFloatingPointTy(); 3948 bool FastMath = (FP && I->isCommutative() && I->isAssociative()); 3949 switch (I->getOpcode()) { 3950 default: 3951 return ReductionInstDesc(false, I); 3952 case Instruction::PHI: 3953 if (FP && (Kind != RK_FloatMult && Kind != RK_FloatAdd && 3954 Kind != RK_FloatMinMax)) 3955 return ReductionInstDesc(false, I); 3956 return ReductionInstDesc(I, Prev.MinMaxKind); 3957 case Instruction::Sub: 3958 case Instruction::Add: 3959 return ReductionInstDesc(Kind == RK_IntegerAdd, I); 3960 case Instruction::Mul: 3961 return ReductionInstDesc(Kind == RK_IntegerMult, I); 3962 case Instruction::And: 3963 return ReductionInstDesc(Kind == RK_IntegerAnd, I); 3964 case Instruction::Or: 3965 return ReductionInstDesc(Kind == RK_IntegerOr, I); 3966 case Instruction::Xor: 3967 return ReductionInstDesc(Kind == RK_IntegerXor, I); 3968 case Instruction::FMul: 3969 return ReductionInstDesc(Kind == RK_FloatMult && FastMath, I); 3970 case Instruction::FAdd: 3971 return ReductionInstDesc(Kind == RK_FloatAdd && FastMath, I); 3972 case Instruction::FCmp: 3973 case Instruction::ICmp: 3974 case Instruction::Select: 3975 if (Kind != RK_IntegerMinMax && 3976 (!HasFunNoNaNAttr || Kind != RK_FloatMinMax)) 3977 return ReductionInstDesc(false, I); 3978 return isMinMaxSelectCmpPattern(I, Prev); 3979 } 3980} 3981 3982LoopVectorizationLegality::InductionKind 3983LoopVectorizationLegality::isInductionVariable(PHINode *Phi) { 3984 Type *PhiTy = Phi->getType(); 3985 // We only handle integer and pointer inductions variables. 3986 if (!PhiTy->isIntegerTy() && !PhiTy->isPointerTy()) 3987 return IK_NoInduction; 3988 3989 // Check that the PHI is consecutive. 3990 const SCEV *PhiScev = SE->getSCEV(Phi); 3991 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PhiScev); 3992 if (!AR) { 3993 DEBUG(dbgs() << "LV: PHI is not a poly recurrence.\n"); 3994 return IK_NoInduction; 3995 } 3996 const SCEV *Step = AR->getStepRecurrence(*SE); 3997 3998 // Integer inductions need to have a stride of one. 3999 if (PhiTy->isIntegerTy()) { 4000 if (Step->isOne()) 4001 return IK_IntInduction; 4002 if (Step->isAllOnesValue()) 4003 return IK_ReverseIntInduction; 4004 return IK_NoInduction; 4005 } 4006 4007 // Calculate the pointer stride and check if it is consecutive. 4008 const SCEVConstant *C = dyn_cast<SCEVConstant>(Step); 4009 if (!C) 4010 return IK_NoInduction; 4011 4012 assert(PhiTy->isPointerTy() && "The PHI must be a pointer"); 4013 uint64_t Size = DL->getTypeAllocSize(PhiTy->getPointerElementType()); 4014 if (C->getValue()->equalsInt(Size)) 4015 return IK_PtrInduction; 4016 else if (C->getValue()->equalsInt(0 - Size)) 4017 return IK_ReversePtrInduction; 4018 4019 return IK_NoInduction; 4020} 4021 4022bool LoopVectorizationLegality::isInductionVariable(const Value *V) { 4023 Value *In0 = const_cast<Value*>(V); 4024 PHINode *PN = dyn_cast_or_null<PHINode>(In0); 4025 if (!PN) 4026 return false; 4027 4028 return Inductions.count(PN); 4029} 4030 4031bool LoopVectorizationLegality::blockNeedsPredication(BasicBlock *BB) { 4032 assert(TheLoop->contains(BB) && "Unknown block used"); 4033 4034 // Blocks that do not dominate the latch need predication. 4035 BasicBlock* Latch = TheLoop->getLoopLatch(); 4036 return !DT->dominates(BB, Latch); 4037} 4038 4039bool LoopVectorizationLegality::blockCanBePredicated(BasicBlock *BB, 4040 SmallPtrSet<Value *, 8>& SafePtrs) { 4041 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 4042 // We might be able to hoist the load. 4043 if (it->mayReadFromMemory()) { 4044 LoadInst *LI = dyn_cast<LoadInst>(it); 4045 if (!LI || !SafePtrs.count(LI->getPointerOperand())) 4046 return false; 4047 } 4048 4049 // We don't predicate stores at the moment. 4050 if (it->mayWriteToMemory() || it->mayThrow()) 4051 return false; 4052 4053 // The instructions below can trap. 4054 switch (it->getOpcode()) { 4055 default: continue; 4056 case Instruction::UDiv: 4057 case Instruction::SDiv: 4058 case Instruction::URem: 4059 case Instruction::SRem: 4060 return false; 4061 } 4062 } 4063 4064 return true; 4065} 4066 4067LoopVectorizationCostModel::VectorizationFactor 4068LoopVectorizationCostModel::selectVectorizationFactor(bool OptForSize, 4069 unsigned UserVF) { 4070 // Width 1 means no vectorize 4071 VectorizationFactor Factor = { 1U, 0U }; 4072 if (OptForSize && Legal->getRuntimePointerCheck()->Need) { 4073 DEBUG(dbgs() << "LV: Aborting. Runtime ptr check is required in Os.\n"); 4074 return Factor; 4075 } 4076 4077 // Find the trip count. 4078 unsigned TC = SE->getSmallConstantTripCount(TheLoop, TheLoop->getLoopLatch()); 4079 DEBUG(dbgs() << "LV: Found trip count:"<<TC<<"\n"); 4080 4081 unsigned WidestType = getWidestType(); 4082 unsigned WidestRegister = TTI.getRegisterBitWidth(true); 4083 unsigned MaxSafeDepDist = -1U; 4084 if (Legal->getMaxSafeDepDistBytes() != -1U) 4085 MaxSafeDepDist = Legal->getMaxSafeDepDistBytes() * 8; 4086 WidestRegister = ((WidestRegister < MaxSafeDepDist) ? 4087 WidestRegister : MaxSafeDepDist); 4088 unsigned MaxVectorSize = WidestRegister / WidestType; 4089 DEBUG(dbgs() << "LV: The Widest type: " << WidestType << " bits.\n"); 4090 DEBUG(dbgs() << "LV: The Widest register is:" << WidestRegister << "bits.\n"); 4091 4092 if (MaxVectorSize == 0) { 4093 DEBUG(dbgs() << "LV: The target has no vector registers.\n"); 4094 MaxVectorSize = 1; 4095 } 4096 4097 assert(MaxVectorSize <= 32 && "Did not expect to pack so many elements" 4098 " into one vector!"); 4099 4100 unsigned VF = MaxVectorSize; 4101 4102 // If we optimize the program for size, avoid creating the tail loop. 4103 if (OptForSize) { 4104 // If we are unable to calculate the trip count then don't try to vectorize. 4105 if (TC < 2) { 4106 DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n"); 4107 return Factor; 4108 } 4109 4110 // Find the maximum SIMD width that can fit within the trip count. 4111 VF = TC % MaxVectorSize; 4112 4113 if (VF == 0) 4114 VF = MaxVectorSize; 4115 4116 // If the trip count that we found modulo the vectorization factor is not 4117 // zero then we require a tail. 4118 if (VF < 2) { 4119 DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n"); 4120 return Factor; 4121 } 4122 } 4123 4124 if (UserVF != 0) { 4125 assert(isPowerOf2_32(UserVF) && "VF needs to be a power of two"); 4126 DEBUG(dbgs() << "LV: Using user VF "<<UserVF<<".\n"); 4127 4128 Factor.Width = UserVF; 4129 return Factor; 4130 } 4131 4132 float Cost = expectedCost(1); 4133 unsigned Width = 1; 4134 DEBUG(dbgs() << "LV: Scalar loop costs: "<< (int)Cost << ".\n"); 4135 for (unsigned i=2; i <= VF; i*=2) { 4136 // Notice that the vector loop needs to be executed less times, so 4137 // we need to divide the cost of the vector loops by the width of 4138 // the vector elements. 4139 float VectorCost = expectedCost(i) / (float)i; 4140 DEBUG(dbgs() << "LV: Vector loop of width "<< i << " costs: " << 4141 (int)VectorCost << ".\n"); 4142 if (VectorCost < Cost) { 4143 Cost = VectorCost; 4144 Width = i; 4145 } 4146 } 4147 4148 DEBUG(dbgs() << "LV: Selecting VF = : "<< Width << ".\n"); 4149 Factor.Width = Width; 4150 Factor.Cost = Width * Cost; 4151 return Factor; 4152} 4153 4154unsigned LoopVectorizationCostModel::getWidestType() { 4155 unsigned MaxWidth = 8; 4156 4157 // For each block. 4158 for (Loop::block_iterator bb = TheLoop->block_begin(), 4159 be = TheLoop->block_end(); bb != be; ++bb) { 4160 BasicBlock *BB = *bb; 4161 4162 // For each instruction in the loop. 4163 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 4164 Type *T = it->getType(); 4165 4166 // Only examine Loads, Stores and PHINodes. 4167 if (!isa<LoadInst>(it) && !isa<StoreInst>(it) && !isa<PHINode>(it)) 4168 continue; 4169 4170 // Examine PHI nodes that are reduction variables. 4171 if (PHINode *PN = dyn_cast<PHINode>(it)) 4172 if (!Legal->getReductionVars()->count(PN)) 4173 continue; 4174 4175 // Examine the stored values. 4176 if (StoreInst *ST = dyn_cast<StoreInst>(it)) 4177 T = ST->getValueOperand()->getType(); 4178 4179 // Ignore loaded pointer types and stored pointer types that are not 4180 // consecutive. However, we do want to take consecutive stores/loads of 4181 // pointer vectors into account. 4182 if (T->isPointerTy() && !isConsecutiveLoadOrStore(it)) 4183 continue; 4184 4185 MaxWidth = std::max(MaxWidth, 4186 (unsigned)DL->getTypeSizeInBits(T->getScalarType())); 4187 } 4188 } 4189 4190 return MaxWidth; 4191} 4192 4193unsigned 4194LoopVectorizationCostModel::selectUnrollFactor(bool OptForSize, 4195 unsigned UserUF, 4196 unsigned VF, 4197 unsigned LoopCost) { 4198 4199 // -- The unroll heuristics -- 4200 // We unroll the loop in order to expose ILP and reduce the loop overhead. 4201 // There are many micro-architectural considerations that we can't predict 4202 // at this level. For example frontend pressure (on decode or fetch) due to 4203 // code size, or the number and capabilities of the execution ports. 4204 // 4205 // We use the following heuristics to select the unroll factor: 4206 // 1. If the code has reductions the we unroll in order to break the cross 4207 // iteration dependency. 4208 // 2. If the loop is really small then we unroll in order to reduce the loop 4209 // overhead. 4210 // 3. We don't unroll if we think that we will spill registers to memory due 4211 // to the increased register pressure. 4212 4213 // Use the user preference, unless 'auto' is selected. 4214 if (UserUF != 0) 4215 return UserUF; 4216 4217 // When we optimize for size we don't unroll. 4218 if (OptForSize) 4219 return 1; 4220 4221 // We used the distance for the unroll factor. 4222 if (Legal->getMaxSafeDepDistBytes() != -1U) 4223 return 1; 4224 4225 // Do not unroll loops with a relatively small trip count. 4226 unsigned TC = SE->getSmallConstantTripCount(TheLoop, 4227 TheLoop->getLoopLatch()); 4228 if (TC > 1 && TC < TinyTripCountUnrollThreshold) 4229 return 1; 4230 4231 unsigned TargetVectorRegisters = TTI.getNumberOfRegisters(true); 4232 DEBUG(dbgs() << "LV: The target has " << TargetVectorRegisters << 4233 " vector registers\n"); 4234 4235 LoopVectorizationCostModel::RegisterUsage R = calculateRegisterUsage(); 4236 // We divide by these constants so assume that we have at least one 4237 // instruction that uses at least one register. 4238 R.MaxLocalUsers = std::max(R.MaxLocalUsers, 1U); 4239 R.NumInstructions = std::max(R.NumInstructions, 1U); 4240 4241 // We calculate the unroll factor using the following formula. 4242 // Subtract the number of loop invariants from the number of available 4243 // registers. These registers are used by all of the unrolled instances. 4244 // Next, divide the remaining registers by the number of registers that is 4245 // required by the loop, in order to estimate how many parallel instances 4246 // fit without causing spills. 4247 unsigned UF = (TargetVectorRegisters - R.LoopInvariantRegs) / R.MaxLocalUsers; 4248 4249 // Clamp the unroll factor ranges to reasonable factors. 4250 unsigned MaxUnrollSize = TTI.getMaximumUnrollFactor(); 4251 4252 // If we did not calculate the cost for VF (because the user selected the VF) 4253 // then we calculate the cost of VF here. 4254 if (LoopCost == 0) 4255 LoopCost = expectedCost(VF); 4256 4257 // Clamp the calculated UF to be between the 1 and the max unroll factor 4258 // that the target allows. 4259 if (UF > MaxUnrollSize) 4260 UF = MaxUnrollSize; 4261 else if (UF < 1) 4262 UF = 1; 4263 4264 if (Legal->getReductionVars()->size()) { 4265 DEBUG(dbgs() << "LV: Unrolling because of reductions. \n"); 4266 return UF; 4267 } 4268 4269 // We want to unroll tiny loops in order to reduce the loop overhead. 4270 // We assume that the cost overhead is 1 and we use the cost model 4271 // to estimate the cost of the loop and unroll until the cost of the 4272 // loop overhead is about 5% of the cost of the loop. 4273 DEBUG(dbgs() << "LV: Loop cost is "<< LoopCost <<" \n"); 4274 if (LoopCost < 20) { 4275 DEBUG(dbgs() << "LV: Unrolling to reduce branch cost. \n"); 4276 unsigned NewUF = 20/LoopCost + 1; 4277 return std::min(NewUF, UF); 4278 } 4279 4280 DEBUG(dbgs() << "LV: Not Unrolling. \n"); 4281 return 1; 4282} 4283 4284LoopVectorizationCostModel::RegisterUsage 4285LoopVectorizationCostModel::calculateRegisterUsage() { 4286 // This function calculates the register usage by measuring the highest number 4287 // of values that are alive at a single location. Obviously, this is a very 4288 // rough estimation. We scan the loop in a topological order in order and 4289 // assign a number to each instruction. We use RPO to ensure that defs are 4290 // met before their users. We assume that each instruction that has in-loop 4291 // users starts an interval. We record every time that an in-loop value is 4292 // used, so we have a list of the first and last occurrences of each 4293 // instruction. Next, we transpose this data structure into a multi map that 4294 // holds the list of intervals that *end* at a specific location. This multi 4295 // map allows us to perform a linear search. We scan the instructions linearly 4296 // and record each time that a new interval starts, by placing it in a set. 4297 // If we find this value in the multi-map then we remove it from the set. 4298 // The max register usage is the maximum size of the set. 4299 // We also search for instructions that are defined outside the loop, but are 4300 // used inside the loop. We need this number separately from the max-interval 4301 // usage number because when we unroll, loop-invariant values do not take 4302 // more register. 4303 LoopBlocksDFS DFS(TheLoop); 4304 DFS.perform(LI); 4305 4306 RegisterUsage R; 4307 R.NumInstructions = 0; 4308 4309 // Each 'key' in the map opens a new interval. The values 4310 // of the map are the index of the 'last seen' usage of the 4311 // instruction that is the key. 4312 typedef DenseMap<Instruction*, unsigned> IntervalMap; 4313 // Maps instruction to its index. 4314 DenseMap<unsigned, Instruction*> IdxToInstr; 4315 // Marks the end of each interval. 4316 IntervalMap EndPoint; 4317 // Saves the list of instruction indices that are used in the loop. 4318 SmallSet<Instruction*, 8> Ends; 4319 // Saves the list of values that are used in the loop but are 4320 // defined outside the loop, such as arguments and constants. 4321 SmallPtrSet<Value*, 8> LoopInvariants; 4322 4323 unsigned Index = 0; 4324 for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(), 4325 be = DFS.endRPO(); bb != be; ++bb) { 4326 R.NumInstructions += (*bb)->size(); 4327 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e; 4328 ++it) { 4329 Instruction *I = it; 4330 IdxToInstr[Index++] = I; 4331 4332 // Save the end location of each USE. 4333 for (unsigned i = 0; i < I->getNumOperands(); ++i) { 4334 Value *U = I->getOperand(i); 4335 Instruction *Instr = dyn_cast<Instruction>(U); 4336 4337 // Ignore non-instruction values such as arguments, constants, etc. 4338 if (!Instr) continue; 4339 4340 // If this instruction is outside the loop then record it and continue. 4341 if (!TheLoop->contains(Instr)) { 4342 LoopInvariants.insert(Instr); 4343 continue; 4344 } 4345 4346 // Overwrite previous end points. 4347 EndPoint[Instr] = Index; 4348 Ends.insert(Instr); 4349 } 4350 } 4351 } 4352 4353 // Saves the list of intervals that end with the index in 'key'. 4354 typedef SmallVector<Instruction*, 2> InstrList; 4355 DenseMap<unsigned, InstrList> TransposeEnds; 4356 4357 // Transpose the EndPoints to a list of values that end at each index. 4358 for (IntervalMap::iterator it = EndPoint.begin(), e = EndPoint.end(); 4359 it != e; ++it) 4360 TransposeEnds[it->second].push_back(it->first); 4361 4362 SmallSet<Instruction*, 8> OpenIntervals; 4363 unsigned MaxUsage = 0; 4364 4365 4366 DEBUG(dbgs() << "LV(REG): Calculating max register usage:\n"); 4367 for (unsigned int i = 0; i < Index; ++i) { 4368 Instruction *I = IdxToInstr[i]; 4369 // Ignore instructions that are never used within the loop. 4370 if (!Ends.count(I)) continue; 4371 4372 // Remove all of the instructions that end at this location. 4373 InstrList &List = TransposeEnds[i]; 4374 for (unsigned int j=0, e = List.size(); j < e; ++j) 4375 OpenIntervals.erase(List[j]); 4376 4377 // Count the number of live interals. 4378 MaxUsage = std::max(MaxUsage, OpenIntervals.size()); 4379 4380 DEBUG(dbgs() << "LV(REG): At #" << i << " Interval # " << 4381 OpenIntervals.size() <<"\n"); 4382 4383 // Add the current instruction to the list of open intervals. 4384 OpenIntervals.insert(I); 4385 } 4386 4387 unsigned Invariant = LoopInvariants.size(); 4388 DEBUG(dbgs() << "LV(REG): Found max usage: " << MaxUsage << " \n"); 4389 DEBUG(dbgs() << "LV(REG): Found invariant usage: " << Invariant << " \n"); 4390 DEBUG(dbgs() << "LV(REG): LoopSize: " << R.NumInstructions << " \n"); 4391 4392 R.LoopInvariantRegs = Invariant; 4393 R.MaxLocalUsers = MaxUsage; 4394 return R; 4395} 4396 4397unsigned LoopVectorizationCostModel::expectedCost(unsigned VF) { 4398 unsigned Cost = 0; 4399 4400 // For each block. 4401 for (Loop::block_iterator bb = TheLoop->block_begin(), 4402 be = TheLoop->block_end(); bb != be; ++bb) { 4403 unsigned BlockCost = 0; 4404 BasicBlock *BB = *bb; 4405 4406 // For each instruction in the old loop. 4407 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 4408 // Skip dbg intrinsics. 4409 if (isa<DbgInfoIntrinsic>(it)) 4410 continue; 4411 4412 unsigned C = getInstructionCost(it, VF); 4413 BlockCost += C; 4414 DEBUG(dbgs() << "LV: Found an estimated cost of "<< C <<" for VF " << 4415 VF << " For instruction: "<< *it << "\n"); 4416 } 4417 4418 // We assume that if-converted blocks have a 50% chance of being executed. 4419 // When the code is scalar then some of the blocks are avoided due to CF. 4420 // When the code is vectorized we execute all code paths. 4421 if (VF == 1 && Legal->blockNeedsPredication(*bb)) 4422 BlockCost /= 2; 4423 4424 Cost += BlockCost; 4425 } 4426 4427 return Cost; 4428} 4429 4430/// \brief Check whether the address computation for a non-consecutive memory 4431/// access looks like an unlikely candidate for being merged into the indexing 4432/// mode. 4433/// 4434/// We look for a GEP which has one index that is an induction variable and all 4435/// other indices are loop invariant. If the stride of this access is also 4436/// within a small bound we decide that this address computation can likely be 4437/// merged into the addressing mode. 4438/// In all other cases, we identify the address computation as complex. 4439static bool isLikelyComplexAddressComputation(Value *Ptr, 4440 LoopVectorizationLegality *Legal, 4441 ScalarEvolution *SE, 4442 const Loop *TheLoop) { 4443 GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr); 4444 if (!Gep) 4445 return true; 4446 4447 // We are looking for a gep with all loop invariant indices except for one 4448 // which should be an induction variable. 4449 unsigned NumOperands = Gep->getNumOperands(); 4450 for (unsigned i = 1; i < NumOperands; ++i) { 4451 Value *Opd = Gep->getOperand(i); 4452 if (!SE->isLoopInvariant(SE->getSCEV(Opd), TheLoop) && 4453 !Legal->isInductionVariable(Opd)) 4454 return true; 4455 } 4456 4457 // Now we know we have a GEP ptr, %inv, %ind, %inv. Make sure that the step 4458 // can likely be merged into the address computation. 4459 unsigned MaxMergeDistance = 64; 4460 4461 const SCEVAddRecExpr *AddRec = dyn_cast<SCEVAddRecExpr>(SE->getSCEV(Ptr)); 4462 if (!AddRec) 4463 return true; 4464 4465 // Check the step is constant. 4466 const SCEV *Step = AddRec->getStepRecurrence(*SE); 4467 // Calculate the pointer stride and check if it is consecutive. 4468 const SCEVConstant *C = dyn_cast<SCEVConstant>(Step); 4469 if (!C) 4470 return true; 4471 4472 const APInt &APStepVal = C->getValue()->getValue(); 4473 4474 // Huge step value - give up. 4475 if (APStepVal.getBitWidth() > 64) 4476 return true; 4477 4478 int64_t StepVal = APStepVal.getSExtValue(); 4479 4480 return StepVal > MaxMergeDistance; 4481} 4482 4483unsigned 4484LoopVectorizationCostModel::getInstructionCost(Instruction *I, unsigned VF) { 4485 // If we know that this instruction will remain uniform, check the cost of 4486 // the scalar version. 4487 if (Legal->isUniformAfterVectorization(I)) 4488 VF = 1; 4489 4490 Type *RetTy = I->getType(); 4491 Type *VectorTy = ToVectorTy(RetTy, VF); 4492 4493 // TODO: We need to estimate the cost of intrinsic calls. 4494 switch (I->getOpcode()) { 4495 case Instruction::GetElementPtr: 4496 // We mark this instruction as zero-cost because the cost of GEPs in 4497 // vectorized code depends on whether the corresponding memory instruction 4498 // is scalarized or not. Therefore, we handle GEPs with the memory 4499 // instruction cost. 4500 return 0; 4501 case Instruction::Br: { 4502 return TTI.getCFInstrCost(I->getOpcode()); 4503 } 4504 case Instruction::PHI: 4505 //TODO: IF-converted IFs become selects. 4506 return 0; 4507 case Instruction::Add: 4508 case Instruction::FAdd: 4509 case Instruction::Sub: 4510 case Instruction::FSub: 4511 case Instruction::Mul: 4512 case Instruction::FMul: 4513 case Instruction::UDiv: 4514 case Instruction::SDiv: 4515 case Instruction::FDiv: 4516 case Instruction::URem: 4517 case Instruction::SRem: 4518 case Instruction::FRem: 4519 case Instruction::Shl: 4520 case Instruction::LShr: 4521 case Instruction::AShr: 4522 case Instruction::And: 4523 case Instruction::Or: 4524 case Instruction::Xor: { 4525 // Certain instructions can be cheaper to vectorize if they have a constant 4526 // second vector operand. One example of this are shifts on x86. 4527 TargetTransformInfo::OperandValueKind Op1VK = 4528 TargetTransformInfo::OK_AnyValue; 4529 TargetTransformInfo::OperandValueKind Op2VK = 4530 TargetTransformInfo::OK_AnyValue; 4531 4532 if (isa<ConstantInt>(I->getOperand(1))) 4533 Op2VK = TargetTransformInfo::OK_UniformConstantValue; 4534 4535 return TTI.getArithmeticInstrCost(I->getOpcode(), VectorTy, Op1VK, Op2VK); 4536 } 4537 case Instruction::Select: { 4538 SelectInst *SI = cast<SelectInst>(I); 4539 const SCEV *CondSCEV = SE->getSCEV(SI->getCondition()); 4540 bool ScalarCond = (SE->isLoopInvariant(CondSCEV, TheLoop)); 4541 Type *CondTy = SI->getCondition()->getType(); 4542 if (!ScalarCond) 4543 CondTy = VectorType::get(CondTy, VF); 4544 4545 return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy, CondTy); 4546 } 4547 case Instruction::ICmp: 4548 case Instruction::FCmp: { 4549 Type *ValTy = I->getOperand(0)->getType(); 4550 VectorTy = ToVectorTy(ValTy, VF); 4551 return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy); 4552 } 4553 case Instruction::Store: 4554 case Instruction::Load: { 4555 StoreInst *SI = dyn_cast<StoreInst>(I); 4556 LoadInst *LI = dyn_cast<LoadInst>(I); 4557 Type *ValTy = (SI ? SI->getValueOperand()->getType() : 4558 LI->getType()); 4559 VectorTy = ToVectorTy(ValTy, VF); 4560 4561 unsigned Alignment = SI ? SI->getAlignment() : LI->getAlignment(); 4562 unsigned AS = SI ? SI->getPointerAddressSpace() : 4563 LI->getPointerAddressSpace(); 4564 Value *Ptr = SI ? SI->getPointerOperand() : LI->getPointerOperand(); 4565 // We add the cost of address computation here instead of with the gep 4566 // instruction because only here we know whether the operation is 4567 // scalarized. 4568 if (VF == 1) 4569 return TTI.getAddressComputationCost(VectorTy) + 4570 TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS); 4571 4572 // Scalarized loads/stores. 4573 int ConsecutiveStride = Legal->isConsecutivePtr(Ptr); 4574 bool Reverse = ConsecutiveStride < 0; 4575 unsigned ScalarAllocatedSize = DL->getTypeAllocSize(ValTy); 4576 unsigned VectorElementSize = DL->getTypeStoreSize(VectorTy)/VF; 4577 if (!ConsecutiveStride || ScalarAllocatedSize != VectorElementSize) { 4578 bool IsComplexComputation = 4579 isLikelyComplexAddressComputation(Ptr, Legal, SE, TheLoop); 4580 unsigned Cost = 0; 4581 // The cost of extracting from the value vector and pointer vector. 4582 Type *PtrTy = ToVectorTy(Ptr->getType(), VF); 4583 for (unsigned i = 0; i < VF; ++i) { 4584 // The cost of extracting the pointer operand. 4585 Cost += TTI.getVectorInstrCost(Instruction::ExtractElement, PtrTy, i); 4586 // In case of STORE, the cost of ExtractElement from the vector. 4587 // In case of LOAD, the cost of InsertElement into the returned 4588 // vector. 4589 Cost += TTI.getVectorInstrCost(SI ? Instruction::ExtractElement : 4590 Instruction::InsertElement, 4591 VectorTy, i); 4592 } 4593 4594 // The cost of the scalar loads/stores. 4595 Cost += VF * TTI.getAddressComputationCost(PtrTy, IsComplexComputation); 4596 Cost += VF * TTI.getMemoryOpCost(I->getOpcode(), ValTy->getScalarType(), 4597 Alignment, AS); 4598 return Cost; 4599 } 4600 4601 // Wide load/stores. 4602 unsigned Cost = TTI.getAddressComputationCost(VectorTy); 4603 Cost += TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS); 4604 4605 if (Reverse) 4606 Cost += TTI.getShuffleCost(TargetTransformInfo::SK_Reverse, 4607 VectorTy, 0); 4608 return Cost; 4609 } 4610 case Instruction::ZExt: 4611 case Instruction::SExt: 4612 case Instruction::FPToUI: 4613 case Instruction::FPToSI: 4614 case Instruction::FPExt: 4615 case Instruction::PtrToInt: 4616 case Instruction::IntToPtr: 4617 case Instruction::SIToFP: 4618 case Instruction::UIToFP: 4619 case Instruction::Trunc: 4620 case Instruction::FPTrunc: 4621 case Instruction::BitCast: { 4622 // We optimize the truncation of induction variable. 4623 // The cost of these is the same as the scalar operation. 4624 if (I->getOpcode() == Instruction::Trunc && 4625 Legal->isInductionVariable(I->getOperand(0))) 4626 return TTI.getCastInstrCost(I->getOpcode(), I->getType(), 4627 I->getOperand(0)->getType()); 4628 4629 Type *SrcVecTy = ToVectorTy(I->getOperand(0)->getType(), VF); 4630 return TTI.getCastInstrCost(I->getOpcode(), VectorTy, SrcVecTy); 4631 } 4632 case Instruction::Call: { 4633 CallInst *CI = cast<CallInst>(I); 4634 Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI); 4635 assert(ID && "Not an intrinsic call!"); 4636 Type *RetTy = ToVectorTy(CI->getType(), VF); 4637 SmallVector<Type*, 4> Tys; 4638 for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i) 4639 Tys.push_back(ToVectorTy(CI->getArgOperand(i)->getType(), VF)); 4640 return TTI.getIntrinsicInstrCost(ID, RetTy, Tys); 4641 } 4642 default: { 4643 // We are scalarizing the instruction. Return the cost of the scalar 4644 // instruction, plus the cost of insert and extract into vector 4645 // elements, times the vector width. 4646 unsigned Cost = 0; 4647 4648 if (!RetTy->isVoidTy() && VF != 1) { 4649 unsigned InsCost = TTI.getVectorInstrCost(Instruction::InsertElement, 4650 VectorTy); 4651 unsigned ExtCost = TTI.getVectorInstrCost(Instruction::ExtractElement, 4652 VectorTy); 4653 4654 // The cost of inserting the results plus extracting each one of the 4655 // operands. 4656 Cost += VF * (InsCost + ExtCost * I->getNumOperands()); 4657 } 4658 4659 // The cost of executing VF copies of the scalar instruction. This opcode 4660 // is unknown. Assume that it is the same as 'mul'. 4661 Cost += VF * TTI.getArithmeticInstrCost(Instruction::Mul, VectorTy); 4662 return Cost; 4663 } 4664 }// end of switch. 4665} 4666 4667Type* LoopVectorizationCostModel::ToVectorTy(Type *Scalar, unsigned VF) { 4668 if (Scalar->isVoidTy() || VF == 1) 4669 return Scalar; 4670 return VectorType::get(Scalar, VF); 4671} 4672 4673char LoopVectorize::ID = 0; 4674static const char lv_name[] = "Loop Vectorization"; 4675INITIALIZE_PASS_BEGIN(LoopVectorize, LV_NAME, lv_name, false, false) 4676INITIALIZE_AG_DEPENDENCY(TargetTransformInfo) 4677INITIALIZE_PASS_DEPENDENCY(ScalarEvolution) 4678INITIALIZE_PASS_DEPENDENCY(LoopSimplify) 4679INITIALIZE_PASS_END(LoopVectorize, LV_NAME, lv_name, false, false) 4680 4681namespace llvm { 4682 Pass *createLoopVectorizePass() { 4683 return new LoopVectorize(); 4684 } 4685} 4686 4687bool LoopVectorizationCostModel::isConsecutiveLoadOrStore(Instruction *Inst) { 4688 // Check for a store. 4689 if (StoreInst *ST = dyn_cast<StoreInst>(Inst)) 4690 return Legal->isConsecutivePtr(ST->getPointerOperand()) != 0; 4691 4692 // Check for a load. 4693 if (LoadInst *LI = dyn_cast<LoadInst>(Inst)) 4694 return Legal->isConsecutivePtr(LI->getPointerOperand()) != 0; 4695 4696 return false; 4697} 4698