LoopVectorize.cpp revision 5df684a6d1bc655c93df4d2f1efafe9093420f4f
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/SmallPtrSet.h" 53#include "llvm/ADT/SmallSet.h" 54#include "llvm/ADT/SmallVector.h" 55#include "llvm/ADT/StringExtras.h" 56#include "llvm/Analysis/AliasAnalysis.h" 57#include "llvm/Analysis/AliasSetTracker.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 /// Add code that checks at runtime if the accessed arrays overlap. 179 /// Returns the comparator value or NULL if no check is needed. 180 Instruction *addRuntimeCheck(LoopVectorizationLegality *Legal, 181 Instruction *Loc); 182 /// Create an empty loop, based on the loop ranges of the old loop. 183 void createEmptyLoop(LoopVectorizationLegality *Legal); 184 /// Copy and widen the instructions from the old loop. 185 void vectorizeLoop(LoopVectorizationLegality *Legal); 186 187 /// A helper function that computes the predicate of the block BB, assuming 188 /// that the header block of the loop is set to True. It returns the *entry* 189 /// mask for the block BB. 190 VectorParts createBlockInMask(BasicBlock *BB); 191 /// A helper function that computes the predicate of the edge between SRC 192 /// and DST. 193 VectorParts createEdgeMask(BasicBlock *Src, BasicBlock *Dst); 194 195 /// A helper function to vectorize a single BB within the innermost loop. 196 void vectorizeBlockInLoop(LoopVectorizationLegality *Legal, BasicBlock *BB, 197 PhiVector *PV); 198 199 /// Insert the new loop to the loop hierarchy and pass manager 200 /// and update the analysis passes. 201 void updateAnalysis(); 202 203 /// This instruction is un-vectorizable. Implement it as a sequence 204 /// of scalars. 205 void scalarizeInstruction(Instruction *Instr); 206 207 /// Vectorize Load and Store instructions, 208 void vectorizeMemoryInstruction(Instruction *Instr, 209 LoopVectorizationLegality *Legal); 210 211 /// Create a broadcast instruction. This method generates a broadcast 212 /// instruction (shuffle) for loop invariant values and for the induction 213 /// value. If this is the induction variable then we extend it to N, N+1, ... 214 /// this is needed because each iteration in the loop corresponds to a SIMD 215 /// element. 216 Value *getBroadcastInstrs(Value *V); 217 218 /// This function adds 0, 1, 2 ... to each vector element, starting at zero. 219 /// If Negate is set then negative numbers are added e.g. (0, -1, -2, ...). 220 /// The sequence starts at StartIndex. 221 Value *getConsecutiveVector(Value* Val, int StartIdx, bool Negate); 222 223 /// When we go over instructions in the basic block we rely on previous 224 /// values within the current basic block or on loop invariant values. 225 /// When we widen (vectorize) values we place them in the map. If the values 226 /// are not within the map, they have to be loop invariant, so we simply 227 /// broadcast them into a vector. 228 VectorParts &getVectorValue(Value *V); 229 230 /// Generate a shuffle sequence that will reverse the vector Vec. 231 Value *reverseVector(Value *Vec); 232 233 /// This is a helper class that holds the vectorizer state. It maps scalar 234 /// instructions to vector instructions. When the code is 'unrolled' then 235 /// then a single scalar value is mapped to multiple vector parts. The parts 236 /// are stored in the VectorPart type. 237 struct ValueMap { 238 /// C'tor. UnrollFactor controls the number of vectors ('parts') that 239 /// are mapped. 240 ValueMap(unsigned UnrollFactor) : UF(UnrollFactor) {} 241 242 /// \return True if 'Key' is saved in the Value Map. 243 bool has(Value *Key) const { return MapStorage.count(Key); } 244 245 /// Initializes a new entry in the map. Sets all of the vector parts to the 246 /// save value in 'Val'. 247 /// \return A reference to a vector with splat values. 248 VectorParts &splat(Value *Key, Value *Val) { 249 VectorParts &Entry = MapStorage[Key]; 250 Entry.assign(UF, Val); 251 return Entry; 252 } 253 254 ///\return A reference to the value that is stored at 'Key'. 255 VectorParts &get(Value *Key) { 256 VectorParts &Entry = MapStorage[Key]; 257 if (Entry.empty()) 258 Entry.resize(UF); 259 assert(Entry.size() == UF); 260 return Entry; 261 } 262 263 private: 264 /// The unroll factor. Each entry in the map stores this number of vector 265 /// elements. 266 unsigned UF; 267 268 /// Map storage. We use std::map and not DenseMap because insertions to a 269 /// dense map invalidates its iterators. 270 std::map<Value *, VectorParts> MapStorage; 271 }; 272 273 /// The original loop. 274 Loop *OrigLoop; 275 /// Scev analysis to use. 276 ScalarEvolution *SE; 277 /// Loop Info. 278 LoopInfo *LI; 279 /// Dominator Tree. 280 DominatorTree *DT; 281 /// Data Layout. 282 DataLayout *DL; 283 /// Target Library Info. 284 const TargetLibraryInfo *TLI; 285 286 /// The vectorization SIMD factor to use. Each vector will have this many 287 /// vector elements. 288 unsigned VF; 289 /// The vectorization unroll factor to use. Each scalar is vectorized to this 290 /// many different vector instructions. 291 unsigned UF; 292 293 /// The builder that we use 294 IRBuilder<> Builder; 295 296 // --- Vectorization state --- 297 298 /// The vector-loop preheader. 299 BasicBlock *LoopVectorPreHeader; 300 /// The scalar-loop preheader. 301 BasicBlock *LoopScalarPreHeader; 302 /// Middle Block between the vector and the scalar. 303 BasicBlock *LoopMiddleBlock; 304 ///The ExitBlock of the scalar loop. 305 BasicBlock *LoopExitBlock; 306 ///The vector loop body. 307 BasicBlock *LoopVectorBody; 308 ///The scalar loop body. 309 BasicBlock *LoopScalarBody; 310 /// A list of all bypass blocks. The first block is the entry of the loop. 311 SmallVector<BasicBlock *, 4> LoopBypassBlocks; 312 313 /// The new Induction variable which was added to the new block. 314 PHINode *Induction; 315 /// The induction variable of the old basic block. 316 PHINode *OldInduction; 317 /// Holds the extended (to the widest induction type) start index. 318 Value *ExtendedIdx; 319 /// Maps scalars to widened vectors. 320 ValueMap WidenMap; 321}; 322 323/// \brief Check if conditionally executed loads are hoistable. 324/// 325/// This class has two functions: isHoistableLoad and canHoistAllLoads. 326/// isHoistableLoad should be called on all load instructions that are executed 327/// conditionally. After all conditional loads are processed, the client should 328/// call canHoistAllLoads to determine if all of the conditional executed loads 329/// have an unconditional memory access to the same memory address in the loop. 330class LoadHoisting { 331 typedef SmallPtrSet<Value *, 8> MemorySet; 332 333 Loop *TheLoop; 334 DominatorTree *DT; 335 MemorySet CondLoadAddrSet; 336 337public: 338 LoadHoisting(Loop *L, DominatorTree *D) : TheLoop(L), DT(D) {} 339 340 /// \brief Check if the instruction is a load with a identifiable address. 341 bool isHoistableLoad(Instruction *L); 342 343 /// \brief Check if all of the conditional loads are hoistable because there 344 /// exists an unconditional memory access to the same address in the loop. 345 bool canHoistAllLoads(); 346}; 347 348bool LoadHoisting::isHoistableLoad(Instruction *L) { 349 LoadInst *LI = dyn_cast<LoadInst>(L); 350 if (!LI) 351 return false; 352 353 CondLoadAddrSet.insert(LI->getPointerOperand()); 354 return true; 355} 356 357static void addMemAccesses(BasicBlock *BB, SmallPtrSet<Value *, 8> &Set) { 358 for (BasicBlock::iterator BI = BB->begin(), BE = BB->end(); BI != BE; ++BI) { 359 if (LoadInst *LI = dyn_cast<LoadInst>(BI)) // Try a load. 360 Set.insert(LI->getPointerOperand()); 361 else if (StoreInst *SI = dyn_cast<StoreInst>(BI)) // Try a store. 362 Set.insert(SI->getPointerOperand()); 363 } 364} 365 366bool LoadHoisting::canHoistAllLoads() { 367 // No conditional loads. 368 if (CondLoadAddrSet.empty()) 369 return true; 370 371 MemorySet UncondMemAccesses; 372 std::vector<BasicBlock*> &LoopBlocks = TheLoop->getBlocksVector(); 373 BasicBlock *LoopLatch = TheLoop->getLoopLatch(); 374 375 // Iterate over the unconditional blocks and collect memory access addresses. 376 for (unsigned i = 0, e = LoopBlocks.size(); i < e; ++i) { 377 BasicBlock *BB = LoopBlocks[i]; 378 379 // Ignore conditional blocks. 380 if (BB != LoopLatch && !DT->dominates(BB, LoopLatch)) 381 continue; 382 383 addMemAccesses(BB, UncondMemAccesses); 384 } 385 386 // And make sure there is a matching unconditional access for every 387 // conditional load. 388 for (MemorySet::iterator MI = CondLoadAddrSet.begin(), 389 ME = CondLoadAddrSet.end(); MI != ME; ++MI) 390 if (!UncondMemAccesses.count(*MI)) 391 return false; 392 393 return true; 394} 395 396/// LoopVectorizationLegality checks if it is legal to vectorize a loop, and 397/// to what vectorization factor. 398/// This class does not look at the profitability of vectorization, only the 399/// legality. This class has two main kinds of checks: 400/// * Memory checks - The code in canVectorizeMemory checks if vectorization 401/// will change the order of memory accesses in a way that will change the 402/// correctness of the program. 403/// * Scalars checks - The code in canVectorizeInstrs and canVectorizeMemory 404/// checks for a number of different conditions, such as the availability of a 405/// single induction variable, that all types are supported and vectorize-able, 406/// etc. This code reflects the capabilities of InnerLoopVectorizer. 407/// This class is also used by InnerLoopVectorizer for identifying 408/// induction variable and the different reduction variables. 409class LoopVectorizationLegality { 410public: 411 LoopVectorizationLegality(Loop *L, ScalarEvolution *SE, DataLayout *DL, 412 DominatorTree *DT, TargetTransformInfo* TTI, 413 AliasAnalysis *AA, TargetLibraryInfo *TLI) 414 : TheLoop(L), SE(SE), DL(DL), DT(DT), TTI(TTI), AA(AA), TLI(TLI), 415 Induction(0), WidestIndTy(0), HasFunNoNaNAttr(false), 416 LoadSpeculation(L, DT) {} 417 418 /// This enum represents the kinds of reductions that we support. 419 enum ReductionKind { 420 RK_NoReduction, ///< Not a reduction. 421 RK_IntegerAdd, ///< Sum of integers. 422 RK_IntegerMult, ///< Product of integers. 423 RK_IntegerOr, ///< Bitwise or logical OR of numbers. 424 RK_IntegerAnd, ///< Bitwise or logical AND of numbers. 425 RK_IntegerXor, ///< Bitwise or logical XOR of numbers. 426 RK_IntegerMinMax, ///< Min/max implemented in terms of select(cmp()). 427 RK_FloatAdd, ///< Sum of floats. 428 RK_FloatMult, ///< Product of floats. 429 RK_FloatMinMax ///< Min/max implemented in terms of select(cmp()). 430 }; 431 432 /// This enum represents the kinds of inductions that we support. 433 enum InductionKind { 434 IK_NoInduction, ///< Not an induction variable. 435 IK_IntInduction, ///< Integer induction variable. Step = 1. 436 IK_ReverseIntInduction, ///< Reverse int induction variable. Step = -1. 437 IK_PtrInduction, ///< Pointer induction var. Step = sizeof(elem). 438 IK_ReversePtrInduction ///< Reverse ptr indvar. Step = - sizeof(elem). 439 }; 440 441 // This enum represents the kind of minmax reduction. 442 enum MinMaxReductionKind { 443 MRK_Invalid, 444 MRK_UIntMin, 445 MRK_UIntMax, 446 MRK_SIntMin, 447 MRK_SIntMax, 448 MRK_FloatMin, 449 MRK_FloatMax 450 }; 451 452 /// This POD struct holds information about reduction variables. 453 struct ReductionDescriptor { 454 ReductionDescriptor() : StartValue(0), LoopExitInstr(0), 455 Kind(RK_NoReduction), MinMaxKind(MRK_Invalid) {} 456 457 ReductionDescriptor(Value *Start, Instruction *Exit, ReductionKind K, 458 MinMaxReductionKind MK) 459 : StartValue(Start), LoopExitInstr(Exit), Kind(K), MinMaxKind(MK) {} 460 461 // The starting value of the reduction. 462 // It does not have to be zero! 463 TrackingVH<Value> StartValue; 464 // The instruction who's value is used outside the loop. 465 Instruction *LoopExitInstr; 466 // The kind of the reduction. 467 ReductionKind Kind; 468 // If this a min/max reduction the kind of reduction. 469 MinMaxReductionKind MinMaxKind; 470 }; 471 472 /// This POD struct holds information about a potential reduction operation. 473 struct ReductionInstDesc { 474 ReductionInstDesc(bool IsRedux, Instruction *I) : 475 IsReduction(IsRedux), PatternLastInst(I), MinMaxKind(MRK_Invalid) {} 476 477 ReductionInstDesc(Instruction *I, MinMaxReductionKind K) : 478 IsReduction(true), PatternLastInst(I), MinMaxKind(K) {} 479 480 // Is this instruction a reduction candidate. 481 bool IsReduction; 482 // The last instruction in a min/max pattern (select of the select(icmp()) 483 // pattern), or the current reduction instruction otherwise. 484 Instruction *PatternLastInst; 485 // If this is a min/max pattern the comparison predicate. 486 MinMaxReductionKind MinMaxKind; 487 }; 488 489 // This POD struct holds information about the memory runtime legality 490 // check that a group of pointers do not overlap. 491 struct RuntimePointerCheck { 492 RuntimePointerCheck() : Need(false) {} 493 494 /// Reset the state of the pointer runtime information. 495 void reset() { 496 Need = false; 497 Pointers.clear(); 498 Starts.clear(); 499 Ends.clear(); 500 } 501 502 /// Insert a pointer and calculate the start and end SCEVs. 503 void insert(ScalarEvolution *SE, Loop *Lp, Value *Ptr, bool WritePtr); 504 505 /// This flag indicates if we need to add the runtime check. 506 bool Need; 507 /// Holds the pointers that we need to check. 508 SmallVector<TrackingVH<Value>, 2> Pointers; 509 /// Holds the pointer value at the beginning of the loop. 510 SmallVector<const SCEV*, 2> Starts; 511 /// Holds the pointer value at the end of the loop. 512 SmallVector<const SCEV*, 2> Ends; 513 /// Holds the information if this pointer is used for writing to memory. 514 SmallVector<bool, 2> IsWritePtr; 515 }; 516 517 /// A POD for saving information about induction variables. 518 struct InductionInfo { 519 InductionInfo(Value *Start, InductionKind K) : StartValue(Start), IK(K) {} 520 InductionInfo() : StartValue(0), IK(IK_NoInduction) {} 521 /// Start value. 522 TrackingVH<Value> StartValue; 523 /// Induction kind. 524 InductionKind IK; 525 }; 526 527 /// ReductionList contains the reduction descriptors for all 528 /// of the reductions that were found in the loop. 529 typedef DenseMap<PHINode*, ReductionDescriptor> ReductionList; 530 531 /// InductionList saves induction variables and maps them to the 532 /// induction descriptor. 533 typedef MapVector<PHINode*, InductionInfo> InductionList; 534 535 /// Alias(Multi)Map stores the values (GEPs or underlying objects and their 536 /// respective Store/Load instruction(s) to calculate aliasing. 537 typedef MapVector<Value*, Instruction* > AliasMap; 538 typedef DenseMap<Value*, std::vector<Instruction*> > AliasMultiMap; 539 540 /// Returns true if it is legal to vectorize this loop. 541 /// This does not mean that it is profitable to vectorize this 542 /// loop, only that it is legal to do so. 543 bool canVectorize(); 544 545 /// Returns the Induction variable. 546 PHINode *getInduction() { return Induction; } 547 548 /// Returns the reduction variables found in the loop. 549 ReductionList *getReductionVars() { return &Reductions; } 550 551 /// Returns the induction variables found in the loop. 552 InductionList *getInductionVars() { return &Inductions; } 553 554 /// Returns the widest induction type. 555 Type *getWidestInductionType() { return WidestIndTy; } 556 557 /// Returns True if V is an induction variable in this loop. 558 bool isInductionVariable(const Value *V); 559 560 /// Return true if the block BB needs to be predicated in order for the loop 561 /// to be vectorized. 562 bool blockNeedsPredication(BasicBlock *BB); 563 564 /// Check if this pointer is consecutive when vectorizing. This happens 565 /// when the last index of the GEP is the induction variable, or that the 566 /// pointer itself is an induction variable. 567 /// This check allows us to vectorize A[idx] into a wide load/store. 568 /// Returns: 569 /// 0 - Stride is unknown or non consecutive. 570 /// 1 - Address is consecutive. 571 /// -1 - Address is consecutive, and decreasing. 572 int isConsecutivePtr(Value *Ptr); 573 574 /// Returns true if the value V is uniform within the loop. 575 bool isUniform(Value *V); 576 577 /// Returns true if this instruction will remain scalar after vectorization. 578 bool isUniformAfterVectorization(Instruction* I) { return Uniforms.count(I); } 579 580 /// Returns the information that we collected about runtime memory check. 581 RuntimePointerCheck *getRuntimePointerCheck() { return &PtrRtCheck; } 582 583 /// This function returns the identity element (or neutral element) for 584 /// the operation K. 585 static Constant *getReductionIdentity(ReductionKind K, Type *Tp); 586private: 587 /// Check if a single basic block loop is vectorizable. 588 /// At this point we know that this is a loop with a constant trip count 589 /// and we only need to check individual instructions. 590 bool canVectorizeInstrs(); 591 592 /// When we vectorize loops we may change the order in which 593 /// we read and write from memory. This method checks if it is 594 /// legal to vectorize the code, considering only memory constrains. 595 /// Returns true if the loop is vectorizable 596 bool canVectorizeMemory(); 597 598 /// Return true if we can vectorize this loop using the IF-conversion 599 /// transformation. 600 bool canVectorizeWithIfConvert(); 601 602 /// Collect the variables that need to stay uniform after vectorization. 603 void collectLoopUniforms(); 604 605 /// Return true if all of the instructions in the block can be speculatively 606 /// executed. 607 bool blockCanBePredicated(BasicBlock *BB); 608 609 /// Returns True, if 'Phi' is the kind of reduction variable for type 610 /// 'Kind'. If this is a reduction variable, it adds it to ReductionList. 611 bool AddReductionVar(PHINode *Phi, ReductionKind Kind); 612 /// Returns a struct describing if the instruction 'I' can be a reduction 613 /// variable of type 'Kind'. If the reduction is a min/max pattern of 614 /// select(icmp()) this function advances the instruction pointer 'I' from the 615 /// compare instruction to the select instruction and stores this pointer in 616 /// 'PatternLastInst' member of the returned struct. 617 ReductionInstDesc isReductionInstr(Instruction *I, ReductionKind Kind, 618 ReductionInstDesc &Desc); 619 /// Returns true if the instruction is a Select(ICmp(X, Y), X, Y) instruction 620 /// pattern corresponding to a min(X, Y) or max(X, Y). 621 static ReductionInstDesc isMinMaxSelectCmpPattern(Instruction *I, 622 ReductionInstDesc &Prev); 623 /// Returns the induction kind of Phi. This function may return NoInduction 624 /// if the PHI is not an induction variable. 625 InductionKind isInductionVariable(PHINode *Phi); 626 /// Return true if can compute the address bounds of Ptr within the loop. 627 bool hasComputableBounds(Value *Ptr); 628 /// Return true if there is the chance of write reorder. 629 bool hasPossibleGlobalWriteReorder(Value *Object, 630 Instruction *Inst, 631 AliasMultiMap &WriteObjects, 632 unsigned MaxByteWidth); 633 /// Return the AA location for a load or a store. 634 AliasAnalysis::Location getLoadStoreLocation(Instruction *Inst); 635 636 637 /// The loop that we evaluate. 638 Loop *TheLoop; 639 /// Scev analysis. 640 ScalarEvolution *SE; 641 /// DataLayout analysis. 642 DataLayout *DL; 643 /// Dominators. 644 DominatorTree *DT; 645 /// Target Info. 646 TargetTransformInfo *TTI; 647 /// Alias Analysis. 648 AliasAnalysis *AA; 649 /// Target Library Info. 650 TargetLibraryInfo *TLI; 651 652 // --- vectorization state --- // 653 654 /// Holds the integer induction variable. This is the counter of the 655 /// loop. 656 PHINode *Induction; 657 /// Holds the reduction variables. 658 ReductionList Reductions; 659 /// Holds all of the induction variables that we found in the loop. 660 /// Notice that inductions don't need to start at zero and that induction 661 /// variables can be pointers. 662 InductionList Inductions; 663 /// Holds the widest induction type encountered. 664 Type *WidestIndTy; 665 666 /// Allowed outside users. This holds the reduction 667 /// vars which can be accessed from outside the loop. 668 SmallPtrSet<Value*, 4> AllowedExit; 669 /// This set holds the variables which are known to be uniform after 670 /// vectorization. 671 SmallPtrSet<Instruction*, 4> Uniforms; 672 /// We need to check that all of the pointers in this list are disjoint 673 /// at runtime. 674 RuntimePointerCheck PtrRtCheck; 675 /// Can we assume the absence of NaNs. 676 bool HasFunNoNaNAttr; 677 678 /// Utility to determine whether loads can be speculated. 679 LoadHoisting LoadSpeculation; 680}; 681 682/// LoopVectorizationCostModel - estimates the expected speedups due to 683/// vectorization. 684/// In many cases vectorization is not profitable. This can happen because of 685/// a number of reasons. In this class we mainly attempt to predict the 686/// expected speedup/slowdowns due to the supported instruction set. We use the 687/// TargetTransformInfo to query the different backends for the cost of 688/// different operations. 689class LoopVectorizationCostModel { 690public: 691 LoopVectorizationCostModel(Loop *L, ScalarEvolution *SE, LoopInfo *LI, 692 LoopVectorizationLegality *Legal, 693 const TargetTransformInfo &TTI, 694 DataLayout *DL, const TargetLibraryInfo *TLI) 695 : TheLoop(L), SE(SE), LI(LI), Legal(Legal), TTI(TTI), DL(DL), TLI(TLI) {} 696 697 /// Information about vectorization costs 698 struct VectorizationFactor { 699 unsigned Width; // Vector width with best cost 700 unsigned Cost; // Cost of the loop with that width 701 }; 702 /// \return The most profitable vectorization factor and the cost of that VF. 703 /// This method checks every power of two up to VF. If UserVF is not ZERO 704 /// then this vectorization factor will be selected if vectorization is 705 /// possible. 706 VectorizationFactor selectVectorizationFactor(bool OptForSize, 707 unsigned UserVF); 708 709 /// \return The size (in bits) of the widest type in the code that 710 /// needs to be vectorized. We ignore values that remain scalar such as 711 /// 64 bit loop indices. 712 unsigned getWidestType(); 713 714 /// \return The most profitable unroll factor. 715 /// If UserUF is non-zero then this method finds the best unroll-factor 716 /// based on register pressure and other parameters. 717 /// VF and LoopCost are the selected vectorization factor and the cost of the 718 /// selected VF. 719 unsigned selectUnrollFactor(bool OptForSize, unsigned UserUF, unsigned VF, 720 unsigned LoopCost); 721 722 /// \brief A struct that represents some properties of the register usage 723 /// of a loop. 724 struct RegisterUsage { 725 /// Holds the number of loop invariant values that are used in the loop. 726 unsigned LoopInvariantRegs; 727 /// Holds the maximum number of concurrent live intervals in the loop. 728 unsigned MaxLocalUsers; 729 /// Holds the number of instructions in the loop. 730 unsigned NumInstructions; 731 }; 732 733 /// \return information about the register usage of the loop. 734 RegisterUsage calculateRegisterUsage(); 735 736private: 737 /// Returns the expected execution cost. The unit of the cost does 738 /// not matter because we use the 'cost' units to compare different 739 /// vector widths. The cost that is returned is *not* normalized by 740 /// the factor width. 741 unsigned expectedCost(unsigned VF); 742 743 /// Returns the execution time cost of an instruction for a given vector 744 /// width. Vector width of one means scalar. 745 unsigned getInstructionCost(Instruction *I, unsigned VF); 746 747 /// A helper function for converting Scalar types to vector types. 748 /// If the incoming type is void, we return void. If the VF is 1, we return 749 /// the scalar type. 750 static Type* ToVectorTy(Type *Scalar, unsigned VF); 751 752 /// Returns whether the instruction is a load or store and will be a emitted 753 /// as a vector operation. 754 bool isConsecutiveLoadOrStore(Instruction *I); 755 756 /// The loop that we evaluate. 757 Loop *TheLoop; 758 /// Scev analysis. 759 ScalarEvolution *SE; 760 /// Loop Info analysis. 761 LoopInfo *LI; 762 /// Vectorization legality. 763 LoopVectorizationLegality *Legal; 764 /// Vector target information. 765 const TargetTransformInfo &TTI; 766 /// Target data layout information. 767 DataLayout *DL; 768 /// Target Library Info. 769 const TargetLibraryInfo *TLI; 770}; 771 772/// Utility class for getting and setting loop vectorizer hints in the form 773/// of loop metadata. 774struct LoopVectorizeHints { 775 /// Vectorization width. 776 unsigned Width; 777 /// Vectorization unroll factor. 778 unsigned Unroll; 779 780 LoopVectorizeHints(const Loop *L) 781 : Width(VectorizationFactor) 782 , Unroll(VectorizationUnroll) 783 , LoopID(L->getLoopID()) { 784 getHints(L); 785 // The command line options override any loop metadata except for when 786 // width == 1 which is used to indicate the loop is already vectorized. 787 if (VectorizationFactor.getNumOccurrences() > 0 && Width != 1) 788 Width = VectorizationFactor; 789 if (VectorizationUnroll.getNumOccurrences() > 0) 790 Unroll = VectorizationUnroll; 791 } 792 793 /// Return the loop vectorizer metadata prefix. 794 static StringRef Prefix() { return "llvm.vectorizer."; } 795 796 MDNode *createHint(LLVMContext &Context, StringRef Name, unsigned V) { 797 SmallVector<Value*, 2> Vals; 798 Vals.push_back(MDString::get(Context, Name)); 799 Vals.push_back(ConstantInt::get(Type::getInt32Ty(Context), V)); 800 return MDNode::get(Context, Vals); 801 } 802 803 /// Mark the loop L as already vectorized by setting the width to 1. 804 void setAlreadyVectorized(Loop *L) { 805 LLVMContext &Context = L->getHeader()->getContext(); 806 807 Width = 1; 808 809 // Create a new loop id with one more operand for the already_vectorized 810 // hint. If the loop already has a loop id then copy the existing operands. 811 SmallVector<Value*, 4> Vals(1); 812 if (LoopID) 813 for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) 814 Vals.push_back(LoopID->getOperand(i)); 815 816 Vals.push_back(createHint(Context, Twine(Prefix(), "width").str(), Width)); 817 818 MDNode *NewLoopID = MDNode::get(Context, Vals); 819 // Set operand 0 to refer to the loop id itself. 820 NewLoopID->replaceOperandWith(0, NewLoopID); 821 822 L->setLoopID(NewLoopID); 823 if (LoopID) 824 LoopID->replaceAllUsesWith(NewLoopID); 825 826 LoopID = NewLoopID; 827 } 828 829private: 830 MDNode *LoopID; 831 832 /// Find hints specified in the loop metadata. 833 void getHints(const Loop *L) { 834 if (!LoopID) 835 return; 836 837 // First operand should refer to the loop id itself. 838 assert(LoopID->getNumOperands() > 0 && "requires at least one operand"); 839 assert(LoopID->getOperand(0) == LoopID && "invalid loop id"); 840 841 for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) { 842 const MDString *S = 0; 843 SmallVector<Value*, 4> Args; 844 845 // The expected hint is either a MDString or a MDNode with the first 846 // operand a MDString. 847 if (const MDNode *MD = dyn_cast<MDNode>(LoopID->getOperand(i))) { 848 if (!MD || MD->getNumOperands() == 0) 849 continue; 850 S = dyn_cast<MDString>(MD->getOperand(0)); 851 for (unsigned i = 1, ie = MD->getNumOperands(); i < ie; ++i) 852 Args.push_back(MD->getOperand(i)); 853 } else { 854 S = dyn_cast<MDString>(LoopID->getOperand(i)); 855 assert(Args.size() == 0 && "too many arguments for MDString"); 856 } 857 858 if (!S) 859 continue; 860 861 // Check if the hint starts with the vectorizer prefix. 862 StringRef Hint = S->getString(); 863 if (!Hint.startswith(Prefix())) 864 continue; 865 // Remove the prefix. 866 Hint = Hint.substr(Prefix().size(), StringRef::npos); 867 868 if (Args.size() == 1) 869 getHint(Hint, Args[0]); 870 } 871 } 872 873 // Check string hint with one operand. 874 void getHint(StringRef Hint, Value *Arg) { 875 const ConstantInt *C = dyn_cast<ConstantInt>(Arg); 876 if (!C) return; 877 unsigned Val = C->getZExtValue(); 878 879 if (Hint == "width") { 880 assert(isPowerOf2_32(Val) && Val <= MaxVectorWidth && 881 "Invalid width metadata"); 882 Width = Val; 883 } else if (Hint == "unroll") { 884 assert(isPowerOf2_32(Val) && Val <= MaxUnrollFactor && 885 "Invalid unroll metadata"); 886 Unroll = Val; 887 } else 888 DEBUG(dbgs() << "LV: ignoring unknown hint " << Hint); 889 } 890}; 891 892/// The LoopVectorize Pass. 893struct LoopVectorize : public LoopPass { 894 /// Pass identification, replacement for typeid 895 static char ID; 896 897 explicit LoopVectorize() : LoopPass(ID) { 898 initializeLoopVectorizePass(*PassRegistry::getPassRegistry()); 899 } 900 901 ScalarEvolution *SE; 902 DataLayout *DL; 903 LoopInfo *LI; 904 TargetTransformInfo *TTI; 905 DominatorTree *DT; 906 AliasAnalysis *AA; 907 TargetLibraryInfo *TLI; 908 909 virtual bool runOnLoop(Loop *L, LPPassManager &LPM) { 910 // We only vectorize innermost loops. 911 if (!L->empty()) 912 return false; 913 914 SE = &getAnalysis<ScalarEvolution>(); 915 DL = getAnalysisIfAvailable<DataLayout>(); 916 LI = &getAnalysis<LoopInfo>(); 917 TTI = &getAnalysis<TargetTransformInfo>(); 918 DT = &getAnalysis<DominatorTree>(); 919 AA = getAnalysisIfAvailable<AliasAnalysis>(); 920 TLI = getAnalysisIfAvailable<TargetLibraryInfo>(); 921 922 if (DL == NULL) { 923 DEBUG(dbgs() << "LV: Not vectorizing because of missing data layout"); 924 return false; 925 } 926 927 DEBUG(dbgs() << "LV: Checking a loop in \"" << 928 L->getHeader()->getParent()->getName() << "\"\n"); 929 930 LoopVectorizeHints Hints(L); 931 932 if (Hints.Width == 1) { 933 DEBUG(dbgs() << "LV: Not vectorizing.\n"); 934 return false; 935 } 936 937 // Check if it is legal to vectorize the loop. 938 LoopVectorizationLegality LVL(L, SE, DL, DT, TTI, AA, TLI); 939 if (!LVL.canVectorize()) { 940 DEBUG(dbgs() << "LV: Not vectorizing.\n"); 941 return false; 942 } 943 944 // Use the cost model. 945 LoopVectorizationCostModel CM(L, SE, LI, &LVL, *TTI, DL, TLI); 946 947 // Check the function attributes to find out if this function should be 948 // optimized for size. 949 Function *F = L->getHeader()->getParent(); 950 Attribute::AttrKind SzAttr = Attribute::OptimizeForSize; 951 Attribute::AttrKind FlAttr = Attribute::NoImplicitFloat; 952 unsigned FnIndex = AttributeSet::FunctionIndex; 953 bool OptForSize = F->getAttributes().hasAttribute(FnIndex, SzAttr); 954 bool NoFloat = F->getAttributes().hasAttribute(FnIndex, FlAttr); 955 956 if (NoFloat) { 957 DEBUG(dbgs() << "LV: Can't vectorize when the NoImplicitFloat" 958 "attribute is used.\n"); 959 return false; 960 } 961 962 // Select the optimal vectorization factor. 963 LoopVectorizationCostModel::VectorizationFactor VF; 964 VF = CM.selectVectorizationFactor(OptForSize, Hints.Width); 965 // Select the unroll factor. 966 unsigned UF = CM.selectUnrollFactor(OptForSize, Hints.Unroll, VF.Width, 967 VF.Cost); 968 969 if (VF.Width == 1) { 970 DEBUG(dbgs() << "LV: Vectorization is possible but not beneficial.\n"); 971 return false; 972 } 973 974 DEBUG(dbgs() << "LV: Found a vectorizable loop ("<< VF.Width << ") in "<< 975 F->getParent()->getModuleIdentifier()<<"\n"); 976 DEBUG(dbgs() << "LV: Unroll Factor is " << UF << "\n"); 977 978 // If we decided that it is *legal* to vectorize the loop then do it. 979 InnerLoopVectorizer LB(L, SE, LI, DT, DL, TLI, VF.Width, UF); 980 LB.vectorize(&LVL); 981 982 // Mark the loop as already vectorized to avoid vectorizing again. 983 Hints.setAlreadyVectorized(L); 984 985 DEBUG(verifyFunction(*L->getHeader()->getParent())); 986 return true; 987 } 988 989 virtual void getAnalysisUsage(AnalysisUsage &AU) const { 990 LoopPass::getAnalysisUsage(AU); 991 AU.addRequiredID(LoopSimplifyID); 992 AU.addRequiredID(LCSSAID); 993 AU.addRequired<DominatorTree>(); 994 AU.addRequired<LoopInfo>(); 995 AU.addRequired<ScalarEvolution>(); 996 AU.addRequired<TargetTransformInfo>(); 997 AU.addPreserved<LoopInfo>(); 998 AU.addPreserved<DominatorTree>(); 999 } 1000 1001}; 1002 1003} // end anonymous namespace 1004 1005//===----------------------------------------------------------------------===// 1006// Implementation of LoopVectorizationLegality, InnerLoopVectorizer and 1007// LoopVectorizationCostModel. 1008//===----------------------------------------------------------------------===// 1009 1010void 1011LoopVectorizationLegality::RuntimePointerCheck::insert(ScalarEvolution *SE, 1012 Loop *Lp, Value *Ptr, 1013 bool WritePtr) { 1014 const SCEV *Sc = SE->getSCEV(Ptr); 1015 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Sc); 1016 assert(AR && "Invalid addrec expression"); 1017 const SCEV *Ex = SE->getBackedgeTakenCount(Lp); 1018 const SCEV *ScEnd = AR->evaluateAtIteration(Ex, *SE); 1019 Pointers.push_back(Ptr); 1020 Starts.push_back(AR->getStart()); 1021 Ends.push_back(ScEnd); 1022 IsWritePtr.push_back(WritePtr); 1023} 1024 1025Value *InnerLoopVectorizer::getBroadcastInstrs(Value *V) { 1026 // Save the current insertion location. 1027 Instruction *Loc = Builder.GetInsertPoint(); 1028 1029 // We need to place the broadcast of invariant variables outside the loop. 1030 Instruction *Instr = dyn_cast<Instruction>(V); 1031 bool NewInstr = (Instr && Instr->getParent() == LoopVectorBody); 1032 bool Invariant = OrigLoop->isLoopInvariant(V) && !NewInstr; 1033 1034 // Place the code for broadcasting invariant variables in the new preheader. 1035 if (Invariant) 1036 Builder.SetInsertPoint(LoopVectorPreHeader->getTerminator()); 1037 1038 // Broadcast the scalar into all locations in the vector. 1039 Value *Shuf = Builder.CreateVectorSplat(VF, V, "broadcast"); 1040 1041 // Restore the builder insertion point. 1042 if (Invariant) 1043 Builder.SetInsertPoint(Loc); 1044 1045 return Shuf; 1046} 1047 1048Value *InnerLoopVectorizer::getConsecutiveVector(Value* Val, int StartIdx, 1049 bool Negate) { 1050 assert(Val->getType()->isVectorTy() && "Must be a vector"); 1051 assert(Val->getType()->getScalarType()->isIntegerTy() && 1052 "Elem must be an integer"); 1053 // Create the types. 1054 Type *ITy = Val->getType()->getScalarType(); 1055 VectorType *Ty = cast<VectorType>(Val->getType()); 1056 int VLen = Ty->getNumElements(); 1057 SmallVector<Constant*, 8> Indices; 1058 1059 // Create a vector of consecutive numbers from zero to VF. 1060 for (int i = 0; i < VLen; ++i) { 1061 int64_t Idx = Negate ? (-i) : i; 1062 Indices.push_back(ConstantInt::get(ITy, StartIdx + Idx, Negate)); 1063 } 1064 1065 // Add the consecutive indices to the vector value. 1066 Constant *Cv = ConstantVector::get(Indices); 1067 assert(Cv->getType() == Val->getType() && "Invalid consecutive vec"); 1068 return Builder.CreateAdd(Val, Cv, "induction"); 1069} 1070 1071int LoopVectorizationLegality::isConsecutivePtr(Value *Ptr) { 1072 assert(Ptr->getType()->isPointerTy() && "Unexpected non ptr"); 1073 // Make sure that the pointer does not point to structs. 1074 if (cast<PointerType>(Ptr->getType())->getElementType()->isAggregateType()) 1075 return 0; 1076 1077 // If this value is a pointer induction variable we know it is consecutive. 1078 PHINode *Phi = dyn_cast_or_null<PHINode>(Ptr); 1079 if (Phi && Inductions.count(Phi)) { 1080 InductionInfo II = Inductions[Phi]; 1081 if (IK_PtrInduction == II.IK) 1082 return 1; 1083 else if (IK_ReversePtrInduction == II.IK) 1084 return -1; 1085 } 1086 1087 GetElementPtrInst *Gep = dyn_cast_or_null<GetElementPtrInst>(Ptr); 1088 if (!Gep) 1089 return 0; 1090 1091 unsigned NumOperands = Gep->getNumOperands(); 1092 Value *LastIndex = Gep->getOperand(NumOperands - 1); 1093 1094 Value *GpPtr = Gep->getPointerOperand(); 1095 // If this GEP value is a consecutive pointer induction variable and all of 1096 // the indices are constant then we know it is consecutive. We can 1097 Phi = dyn_cast<PHINode>(GpPtr); 1098 if (Phi && Inductions.count(Phi)) { 1099 1100 // Make sure that the pointer does not point to structs. 1101 PointerType *GepPtrType = cast<PointerType>(GpPtr->getType()); 1102 if (GepPtrType->getElementType()->isAggregateType()) 1103 return 0; 1104 1105 // Make sure that all of the index operands are loop invariant. 1106 for (unsigned i = 1; i < NumOperands; ++i) 1107 if (!SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop)) 1108 return 0; 1109 1110 InductionInfo II = Inductions[Phi]; 1111 if (IK_PtrInduction == II.IK) 1112 return 1; 1113 else if (IK_ReversePtrInduction == II.IK) 1114 return -1; 1115 } 1116 1117 // Check that all of the gep indices are uniform except for the last. 1118 for (unsigned i = 0; i < NumOperands - 1; ++i) 1119 if (!SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop)) 1120 return 0; 1121 1122 // We can emit wide load/stores only if the last index is the induction 1123 // variable. 1124 const SCEV *Last = SE->getSCEV(LastIndex); 1125 if (const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Last)) { 1126 const SCEV *Step = AR->getStepRecurrence(*SE); 1127 1128 // The memory is consecutive because the last index is consecutive 1129 // and all other indices are loop invariant. 1130 if (Step->isOne()) 1131 return 1; 1132 if (Step->isAllOnesValue()) 1133 return -1; 1134 } 1135 1136 return 0; 1137} 1138 1139bool LoopVectorizationLegality::isUniform(Value *V) { 1140 return (SE->isLoopInvariant(SE->getSCEV(V), TheLoop)); 1141} 1142 1143InnerLoopVectorizer::VectorParts& 1144InnerLoopVectorizer::getVectorValue(Value *V) { 1145 assert(V != Induction && "The new induction variable should not be used."); 1146 assert(!V->getType()->isVectorTy() && "Can't widen a vector"); 1147 1148 // If we have this scalar in the map, return it. 1149 if (WidenMap.has(V)) 1150 return WidenMap.get(V); 1151 1152 // If this scalar is unknown, assume that it is a constant or that it is 1153 // loop invariant. Broadcast V and save the value for future uses. 1154 Value *B = getBroadcastInstrs(V); 1155 return WidenMap.splat(V, B); 1156} 1157 1158Value *InnerLoopVectorizer::reverseVector(Value *Vec) { 1159 assert(Vec->getType()->isVectorTy() && "Invalid type"); 1160 SmallVector<Constant*, 8> ShuffleMask; 1161 for (unsigned i = 0; i < VF; ++i) 1162 ShuffleMask.push_back(Builder.getInt32(VF - i - 1)); 1163 1164 return Builder.CreateShuffleVector(Vec, UndefValue::get(Vec->getType()), 1165 ConstantVector::get(ShuffleMask), 1166 "reverse"); 1167} 1168 1169 1170void InnerLoopVectorizer::vectorizeMemoryInstruction(Instruction *Instr, 1171 LoopVectorizationLegality *Legal) { 1172 // Attempt to issue a wide load. 1173 LoadInst *LI = dyn_cast<LoadInst>(Instr); 1174 StoreInst *SI = dyn_cast<StoreInst>(Instr); 1175 1176 assert((LI || SI) && "Invalid Load/Store instruction"); 1177 1178 Type *ScalarDataTy = LI ? LI->getType() : SI->getValueOperand()->getType(); 1179 Type *DataTy = VectorType::get(ScalarDataTy, VF); 1180 Value *Ptr = LI ? LI->getPointerOperand() : SI->getPointerOperand(); 1181 unsigned Alignment = LI ? LI->getAlignment() : SI->getAlignment(); 1182 unsigned AddressSpace = Ptr->getType()->getPointerAddressSpace(); 1183 unsigned ScalarAllocatedSize = DL->getTypeAllocSize(ScalarDataTy); 1184 unsigned VectorElementSize = DL->getTypeStoreSize(DataTy)/VF; 1185 1186 if (ScalarAllocatedSize != VectorElementSize) 1187 return scalarizeInstruction(Instr); 1188 1189 // If the pointer is loop invariant or if it is non consecutive, 1190 // scalarize the load. 1191 int ConsecutiveStride = Legal->isConsecutivePtr(Ptr); 1192 bool Reverse = ConsecutiveStride < 0; 1193 bool UniformLoad = LI && Legal->isUniform(Ptr); 1194 if (!ConsecutiveStride || UniformLoad) 1195 return scalarizeInstruction(Instr); 1196 1197 Constant *Zero = Builder.getInt32(0); 1198 VectorParts &Entry = WidenMap.get(Instr); 1199 1200 // Handle consecutive loads/stores. 1201 GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr); 1202 if (Gep && Legal->isInductionVariable(Gep->getPointerOperand())) { 1203 Value *PtrOperand = Gep->getPointerOperand(); 1204 Value *FirstBasePtr = getVectorValue(PtrOperand)[0]; 1205 FirstBasePtr = Builder.CreateExtractElement(FirstBasePtr, Zero); 1206 1207 // Create the new GEP with the new induction variable. 1208 GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone()); 1209 Gep2->setOperand(0, FirstBasePtr); 1210 Gep2->setName("gep.indvar.base"); 1211 Ptr = Builder.Insert(Gep2); 1212 } else if (Gep) { 1213 assert(SE->isLoopInvariant(SE->getSCEV(Gep->getPointerOperand()), 1214 OrigLoop) && "Base ptr must be invariant"); 1215 1216 // The last index does not have to be the induction. It can be 1217 // consecutive and be a function of the index. For example A[I+1]; 1218 unsigned NumOperands = Gep->getNumOperands(); 1219 1220 Value *LastGepOperand = Gep->getOperand(NumOperands - 1); 1221 VectorParts &GEPParts = getVectorValue(LastGepOperand); 1222 Value *LastIndex = GEPParts[0]; 1223 LastIndex = Builder.CreateExtractElement(LastIndex, Zero); 1224 1225 // Create the new GEP with the new induction variable. 1226 GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone()); 1227 Gep2->setOperand(NumOperands - 1, LastIndex); 1228 Gep2->setName("gep.indvar.idx"); 1229 Ptr = Builder.Insert(Gep2); 1230 } else { 1231 // Use the induction element ptr. 1232 assert(isa<PHINode>(Ptr) && "Invalid induction ptr"); 1233 VectorParts &PtrVal = getVectorValue(Ptr); 1234 Ptr = Builder.CreateExtractElement(PtrVal[0], Zero); 1235 } 1236 1237 // Handle Stores: 1238 if (SI) { 1239 assert(!Legal->isUniform(SI->getPointerOperand()) && 1240 "We do not allow storing to uniform addresses"); 1241 1242 VectorParts &StoredVal = getVectorValue(SI->getValueOperand()); 1243 for (unsigned Part = 0; Part < UF; ++Part) { 1244 // Calculate the pointer for the specific unroll-part. 1245 Value *PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(Part * VF)); 1246 1247 if (Reverse) { 1248 // If we store to reverse consecutive memory locations then we need 1249 // to reverse the order of elements in the stored value. 1250 StoredVal[Part] = reverseVector(StoredVal[Part]); 1251 // If the address is consecutive but reversed, then the 1252 // wide store needs to start at the last vector element. 1253 PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(-Part * VF)); 1254 PartPtr = Builder.CreateGEP(PartPtr, Builder.getInt32(1 - VF)); 1255 } 1256 1257 Value *VecPtr = Builder.CreateBitCast(PartPtr, DataTy->getPointerTo(AddressSpace)); 1258 Builder.CreateStore(StoredVal[Part], VecPtr)->setAlignment(Alignment); 1259 } 1260 } 1261 1262 for (unsigned Part = 0; Part < UF; ++Part) { 1263 // Calculate the pointer for the specific unroll-part. 1264 Value *PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(Part * VF)); 1265 1266 if (Reverse) { 1267 // If the address is consecutive but reversed, then the 1268 // wide store needs to start at the last vector element. 1269 PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(-Part * VF)); 1270 PartPtr = Builder.CreateGEP(PartPtr, Builder.getInt32(1 - VF)); 1271 } 1272 1273 Value *VecPtr = Builder.CreateBitCast(PartPtr, DataTy->getPointerTo(AddressSpace)); 1274 Value *LI = Builder.CreateLoad(VecPtr, "wide.load"); 1275 cast<LoadInst>(LI)->setAlignment(Alignment); 1276 Entry[Part] = Reverse ? reverseVector(LI) : LI; 1277 } 1278} 1279 1280void InnerLoopVectorizer::scalarizeInstruction(Instruction *Instr) { 1281 assert(!Instr->getType()->isAggregateType() && "Can't handle vectors"); 1282 // Holds vector parameters or scalars, in case of uniform vals. 1283 SmallVector<VectorParts, 4> Params; 1284 1285 // Find all of the vectorized parameters. 1286 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) { 1287 Value *SrcOp = Instr->getOperand(op); 1288 1289 // If we are accessing the old induction variable, use the new one. 1290 if (SrcOp == OldInduction) { 1291 Params.push_back(getVectorValue(SrcOp)); 1292 continue; 1293 } 1294 1295 // Try using previously calculated values. 1296 Instruction *SrcInst = dyn_cast<Instruction>(SrcOp); 1297 1298 // If the src is an instruction that appeared earlier in the basic block 1299 // then it should already be vectorized. 1300 if (SrcInst && OrigLoop->contains(SrcInst)) { 1301 assert(WidenMap.has(SrcInst) && "Source operand is unavailable"); 1302 // The parameter is a vector value from earlier. 1303 Params.push_back(WidenMap.get(SrcInst)); 1304 } else { 1305 // The parameter is a scalar from outside the loop. Maybe even a constant. 1306 VectorParts Scalars; 1307 Scalars.append(UF, SrcOp); 1308 Params.push_back(Scalars); 1309 } 1310 } 1311 1312 assert(Params.size() == Instr->getNumOperands() && 1313 "Invalid number of operands"); 1314 1315 // Does this instruction return a value ? 1316 bool IsVoidRetTy = Instr->getType()->isVoidTy(); 1317 1318 Value *UndefVec = IsVoidRetTy ? 0 : 1319 UndefValue::get(VectorType::get(Instr->getType(), VF)); 1320 // Create a new entry in the WidenMap and initialize it to Undef or Null. 1321 VectorParts &VecResults = WidenMap.splat(Instr, UndefVec); 1322 1323 // For each vector unroll 'part': 1324 for (unsigned Part = 0; Part < UF; ++Part) { 1325 // For each scalar that we create: 1326 for (unsigned Width = 0; Width < VF; ++Width) { 1327 Instruction *Cloned = Instr->clone(); 1328 if (!IsVoidRetTy) 1329 Cloned->setName(Instr->getName() + ".cloned"); 1330 // Replace the operands of the cloned instrucions with extracted scalars. 1331 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) { 1332 Value *Op = Params[op][Part]; 1333 // Param is a vector. Need to extract the right lane. 1334 if (Op->getType()->isVectorTy()) 1335 Op = Builder.CreateExtractElement(Op, Builder.getInt32(Width)); 1336 Cloned->setOperand(op, Op); 1337 } 1338 1339 // Place the cloned scalar in the new loop. 1340 Builder.Insert(Cloned); 1341 1342 // If the original scalar returns a value we need to place it in a vector 1343 // so that future users will be able to use it. 1344 if (!IsVoidRetTy) 1345 VecResults[Part] = Builder.CreateInsertElement(VecResults[Part], Cloned, 1346 Builder.getInt32(Width)); 1347 } 1348 } 1349} 1350 1351Instruction * 1352InnerLoopVectorizer::addRuntimeCheck(LoopVectorizationLegality *Legal, 1353 Instruction *Loc) { 1354 LoopVectorizationLegality::RuntimePointerCheck *PtrRtCheck = 1355 Legal->getRuntimePointerCheck(); 1356 1357 if (!PtrRtCheck->Need) 1358 return NULL; 1359 1360 Instruction *MemoryRuntimeCheck = 0; 1361 unsigned NumPointers = PtrRtCheck->Pointers.size(); 1362 SmallVector<Value* , 2> Starts; 1363 SmallVector<Value* , 2> Ends; 1364 1365 SCEVExpander Exp(*SE, "induction"); 1366 1367 // Use this type for pointer arithmetic. 1368 Type* PtrArithTy = Type::getInt8PtrTy(Loc->getContext(), 0); 1369 1370 for (unsigned i = 0; i < NumPointers; ++i) { 1371 Value *Ptr = PtrRtCheck->Pointers[i]; 1372 const SCEV *Sc = SE->getSCEV(Ptr); 1373 1374 if (SE->isLoopInvariant(Sc, OrigLoop)) { 1375 DEBUG(dbgs() << "LV: Adding RT check for a loop invariant ptr:" << 1376 *Ptr <<"\n"); 1377 Starts.push_back(Ptr); 1378 Ends.push_back(Ptr); 1379 } else { 1380 DEBUG(dbgs() << "LV: Adding RT check for range:" << *Ptr <<"\n"); 1381 1382 Value *Start = Exp.expandCodeFor(PtrRtCheck->Starts[i], PtrArithTy, Loc); 1383 Value *End = Exp.expandCodeFor(PtrRtCheck->Ends[i], PtrArithTy, Loc); 1384 Starts.push_back(Start); 1385 Ends.push_back(End); 1386 } 1387 } 1388 1389 IRBuilder<> ChkBuilder(Loc); 1390 1391 for (unsigned i = 0; i < NumPointers; ++i) { 1392 for (unsigned j = i+1; j < NumPointers; ++j) { 1393 // No need to check if two readonly pointers intersect. 1394 if (!PtrRtCheck->IsWritePtr[i] && !PtrRtCheck->IsWritePtr[j]) 1395 continue; 1396 1397 Value *Start0 = ChkBuilder.CreateBitCast(Starts[i], PtrArithTy, "bc"); 1398 Value *Start1 = ChkBuilder.CreateBitCast(Starts[j], PtrArithTy, "bc"); 1399 Value *End0 = ChkBuilder.CreateBitCast(Ends[i], PtrArithTy, "bc"); 1400 Value *End1 = ChkBuilder.CreateBitCast(Ends[j], PtrArithTy, "bc"); 1401 1402 Value *Cmp0 = ChkBuilder.CreateICmpULE(Start0, End1, "bound0"); 1403 Value *Cmp1 = ChkBuilder.CreateICmpULE(Start1, End0, "bound1"); 1404 Value *IsConflict = ChkBuilder.CreateAnd(Cmp0, Cmp1, "found.conflict"); 1405 if (MemoryRuntimeCheck) 1406 IsConflict = ChkBuilder.CreateOr(MemoryRuntimeCheck, IsConflict, 1407 "conflict.rdx"); 1408 1409 MemoryRuntimeCheck = cast<Instruction>(IsConflict); 1410 } 1411 } 1412 1413 return MemoryRuntimeCheck; 1414} 1415 1416void 1417InnerLoopVectorizer::createEmptyLoop(LoopVectorizationLegality *Legal) { 1418 /* 1419 In this function we generate a new loop. The new loop will contain 1420 the vectorized instructions while the old loop will continue to run the 1421 scalar remainder. 1422 1423 [ ] <-- vector loop bypass (may consist of multiple blocks). 1424 / | 1425 / v 1426 | [ ] <-- vector pre header. 1427 | | 1428 | v 1429 | [ ] \ 1430 | [ ]_| <-- vector loop. 1431 | | 1432 \ v 1433 >[ ] <--- middle-block. 1434 / | 1435 / v 1436 | [ ] <--- new preheader. 1437 | | 1438 | v 1439 | [ ] \ 1440 | [ ]_| <-- old scalar loop to handle remainder. 1441 \ | 1442 \ v 1443 >[ ] <-- exit block. 1444 ... 1445 */ 1446 1447 BasicBlock *OldBasicBlock = OrigLoop->getHeader(); 1448 BasicBlock *BypassBlock = OrigLoop->getLoopPreheader(); 1449 BasicBlock *ExitBlock = OrigLoop->getExitBlock(); 1450 assert(ExitBlock && "Must have an exit block"); 1451 1452 // Some loops have a single integer induction variable, while other loops 1453 // don't. One example is c++ iterators that often have multiple pointer 1454 // induction variables. In the code below we also support a case where we 1455 // don't have a single induction variable. 1456 OldInduction = Legal->getInduction(); 1457 Type *IdxTy = Legal->getWidestInductionType(); 1458 1459 // Find the loop boundaries. 1460 const SCEV *ExitCount = SE->getBackedgeTakenCount(OrigLoop); 1461 assert(ExitCount != SE->getCouldNotCompute() && "Invalid loop count"); 1462 1463 // Get the total trip count from the count by adding 1. 1464 ExitCount = SE->getAddExpr(ExitCount, 1465 SE->getConstant(ExitCount->getType(), 1)); 1466 1467 // Expand the trip count and place the new instructions in the preheader. 1468 // Notice that the pre-header does not change, only the loop body. 1469 SCEVExpander Exp(*SE, "induction"); 1470 1471 // Count holds the overall loop count (N). 1472 Value *Count = Exp.expandCodeFor(ExitCount, ExitCount->getType(), 1473 BypassBlock->getTerminator()); 1474 1475 // The loop index does not have to start at Zero. Find the original start 1476 // value from the induction PHI node. If we don't have an induction variable 1477 // then we know that it starts at zero. 1478 Builder.SetInsertPoint(BypassBlock->getTerminator()); 1479 Value *StartIdx = ExtendedIdx = OldInduction ? 1480 Builder.CreateZExt(OldInduction->getIncomingValueForBlock(BypassBlock), 1481 IdxTy): 1482 ConstantInt::get(IdxTy, 0); 1483 1484 assert(BypassBlock && "Invalid loop structure"); 1485 LoopBypassBlocks.push_back(BypassBlock); 1486 1487 // Split the single block loop into the two loop structure described above. 1488 BasicBlock *VectorPH = 1489 BypassBlock->splitBasicBlock(BypassBlock->getTerminator(), "vector.ph"); 1490 BasicBlock *VecBody = 1491 VectorPH->splitBasicBlock(VectorPH->getTerminator(), "vector.body"); 1492 BasicBlock *MiddleBlock = 1493 VecBody->splitBasicBlock(VecBody->getTerminator(), "middle.block"); 1494 BasicBlock *ScalarPH = 1495 MiddleBlock->splitBasicBlock(MiddleBlock->getTerminator(), "scalar.ph"); 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 Induction = Builder.CreatePHI(IdxTy, 2, "index"); 1503 // The loop step is equal to the vectorization factor (num of SIMD elements) 1504 // times the unroll factor (num of SIMD instructions). 1505 Constant *Step = ConstantInt::get(IdxTy, VF * UF); 1506 1507 // This is the IR builder that we use to add all of the logic for bypassing 1508 // the new vector loop. 1509 IRBuilder<> BypassBuilder(BypassBlock->getTerminator()); 1510 1511 // We may need to extend the index in case there is a type mismatch. 1512 // We know that the count starts at zero and does not overflow. 1513 if (Count->getType() != IdxTy) { 1514 // The exit count can be of pointer type. Convert it to the correct 1515 // integer type. 1516 if (ExitCount->getType()->isPointerTy()) 1517 Count = BypassBuilder.CreatePointerCast(Count, IdxTy, "ptrcnt.to.int"); 1518 else 1519 Count = BypassBuilder.CreateZExtOrTrunc(Count, IdxTy, "cnt.cast"); 1520 } 1521 1522 // Add the start index to the loop count to get the new end index. 1523 Value *IdxEnd = BypassBuilder.CreateAdd(Count, StartIdx, "end.idx"); 1524 1525 // Now we need to generate the expression for N - (N % VF), which is 1526 // the part that the vectorized body will execute. 1527 Value *R = BypassBuilder.CreateURem(Count, Step, "n.mod.vf"); 1528 Value *CountRoundDown = BypassBuilder.CreateSub(Count, R, "n.vec"); 1529 Value *IdxEndRoundDown = BypassBuilder.CreateAdd(CountRoundDown, StartIdx, 1530 "end.idx.rnd.down"); 1531 1532 // Now, compare the new count to zero. If it is zero skip the vector loop and 1533 // jump to the scalar loop. 1534 Value *Cmp = BypassBuilder.CreateICmpEQ(IdxEndRoundDown, StartIdx, 1535 "cmp.zero"); 1536 1537 BasicBlock *LastBypassBlock = BypassBlock; 1538 1539 // Generate the code that checks in runtime if arrays overlap. We put the 1540 // checks into a separate block to make the more common case of few elements 1541 // faster. 1542 Instruction *MemRuntimeCheck = addRuntimeCheck(Legal, 1543 BypassBlock->getTerminator()); 1544 if (MemRuntimeCheck) { 1545 // Create a new block containing the memory check. 1546 BasicBlock *CheckBlock = BypassBlock->splitBasicBlock(MemRuntimeCheck, 1547 "vector.memcheck"); 1548 LoopBypassBlocks.push_back(CheckBlock); 1549 1550 // Replace the branch into the memory check block with a conditional branch 1551 // for the "few elements case". 1552 Instruction *OldTerm = BypassBlock->getTerminator(); 1553 BranchInst::Create(MiddleBlock, CheckBlock, Cmp, OldTerm); 1554 OldTerm->eraseFromParent(); 1555 1556 Cmp = MemRuntimeCheck; 1557 LastBypassBlock = CheckBlock; 1558 } 1559 1560 LastBypassBlock->getTerminator()->eraseFromParent(); 1561 BranchInst::Create(MiddleBlock, VectorPH, Cmp, 1562 LastBypassBlock); 1563 1564 // We are going to resume the execution of the scalar loop. 1565 // Go over all of the induction variables that we found and fix the 1566 // PHIs that are left in the scalar version of the loop. 1567 // The starting values of PHI nodes depend on the counter of the last 1568 // iteration in the vectorized loop. 1569 // If we come from a bypass edge then we need to start from the original 1570 // start value. 1571 1572 // This variable saves the new starting index for the scalar loop. 1573 PHINode *ResumeIndex = 0; 1574 LoopVectorizationLegality::InductionList::iterator I, E; 1575 LoopVectorizationLegality::InductionList *List = Legal->getInductionVars(); 1576 // Set builder to point to last bypass block. 1577 BypassBuilder.SetInsertPoint(LoopBypassBlocks.back()->getTerminator()); 1578 for (I = List->begin(), E = List->end(); I != E; ++I) { 1579 PHINode *OrigPhi = I->first; 1580 LoopVectorizationLegality::InductionInfo II = I->second; 1581 1582 Type *ResumeValTy = (OrigPhi == OldInduction) ? IdxTy : OrigPhi->getType(); 1583 PHINode *ResumeVal = PHINode::Create(ResumeValTy, 2, "resume.val", 1584 MiddleBlock->getTerminator()); 1585 // We might have extended the type of the induction variable but we need a 1586 // truncated version for the scalar loop. 1587 PHINode *TruncResumeVal = (OrigPhi == OldInduction) ? 1588 PHINode::Create(OrigPhi->getType(), 2, "trunc.resume.val", 1589 MiddleBlock->getTerminator()) : 0; 1590 1591 Value *EndValue = 0; 1592 switch (II.IK) { 1593 case LoopVectorizationLegality::IK_NoInduction: 1594 llvm_unreachable("Unknown induction"); 1595 case LoopVectorizationLegality::IK_IntInduction: { 1596 // Handle the integer induction counter. 1597 assert(OrigPhi->getType()->isIntegerTy() && "Invalid type"); 1598 1599 // We have the canonical induction variable. 1600 if (OrigPhi == OldInduction) { 1601 // Create a truncated version of the resume value for the scalar loop, 1602 // we might have promoted the type to a larger width. 1603 EndValue = 1604 BypassBuilder.CreateTrunc(IdxEndRoundDown, OrigPhi->getType()); 1605 // The new PHI merges the original incoming value, in case of a bypass, 1606 // or the value at the end of the vectorized loop. 1607 for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I) 1608 TruncResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]); 1609 TruncResumeVal->addIncoming(EndValue, VecBody); 1610 1611 // We know what the end value is. 1612 EndValue = IdxEndRoundDown; 1613 // We also know which PHI node holds it. 1614 ResumeIndex = ResumeVal; 1615 break; 1616 } 1617 1618 // Not the canonical induction variable - add the vector loop count to the 1619 // start value. 1620 Value *CRD = BypassBuilder.CreateSExtOrTrunc(CountRoundDown, 1621 II.StartValue->getType(), 1622 "cast.crd"); 1623 EndValue = BypassBuilder.CreateAdd(CRD, II.StartValue , "ind.end"); 1624 break; 1625 } 1626 case LoopVectorizationLegality::IK_ReverseIntInduction: { 1627 // Convert the CountRoundDown variable to the PHI size. 1628 Value *CRD = BypassBuilder.CreateSExtOrTrunc(CountRoundDown, 1629 II.StartValue->getType(), 1630 "cast.crd"); 1631 // Handle reverse integer induction counter. 1632 EndValue = BypassBuilder.CreateSub(II.StartValue, CRD, "rev.ind.end"); 1633 break; 1634 } 1635 case LoopVectorizationLegality::IK_PtrInduction: { 1636 // For pointer induction variables, calculate the offset using 1637 // the end index. 1638 EndValue = BypassBuilder.CreateGEP(II.StartValue, CountRoundDown, 1639 "ptr.ind.end"); 1640 break; 1641 } 1642 case LoopVectorizationLegality::IK_ReversePtrInduction: { 1643 // The value at the end of the loop for the reverse pointer is calculated 1644 // by creating a GEP with a negative index starting from the start value. 1645 Value *Zero = ConstantInt::get(CountRoundDown->getType(), 0); 1646 Value *NegIdx = BypassBuilder.CreateSub(Zero, CountRoundDown, 1647 "rev.ind.end"); 1648 EndValue = BypassBuilder.CreateGEP(II.StartValue, NegIdx, 1649 "rev.ptr.ind.end"); 1650 break; 1651 } 1652 }// end of case 1653 1654 // The new PHI merges the original incoming value, in case of a bypass, 1655 // or the value at the end of the vectorized loop. 1656 for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I) { 1657 if (OrigPhi == OldInduction) 1658 ResumeVal->addIncoming(StartIdx, LoopBypassBlocks[I]); 1659 else 1660 ResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]); 1661 } 1662 ResumeVal->addIncoming(EndValue, VecBody); 1663 1664 // Fix the scalar body counter (PHI node). 1665 unsigned BlockIdx = OrigPhi->getBasicBlockIndex(ScalarPH); 1666 // The old inductions phi node in the scalar body needs the truncated value. 1667 if (OrigPhi == OldInduction) 1668 OrigPhi->setIncomingValue(BlockIdx, TruncResumeVal); 1669 else 1670 OrigPhi->setIncomingValue(BlockIdx, ResumeVal); 1671 } 1672 1673 // If we are generating a new induction variable then we also need to 1674 // generate the code that calculates the exit value. This value is not 1675 // simply the end of the counter because we may skip the vectorized body 1676 // in case of a runtime check. 1677 if (!OldInduction){ 1678 assert(!ResumeIndex && "Unexpected resume value found"); 1679 ResumeIndex = PHINode::Create(IdxTy, 2, "new.indc.resume.val", 1680 MiddleBlock->getTerminator()); 1681 for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I) 1682 ResumeIndex->addIncoming(StartIdx, LoopBypassBlocks[I]); 1683 ResumeIndex->addIncoming(IdxEndRoundDown, VecBody); 1684 } 1685 1686 // Make sure that we found the index where scalar loop needs to continue. 1687 assert(ResumeIndex && ResumeIndex->getType()->isIntegerTy() && 1688 "Invalid resume Index"); 1689 1690 // Add a check in the middle block to see if we have completed 1691 // all of the iterations in the first vector loop. 1692 // If (N - N%VF) == N, then we *don't* need to run the remainder. 1693 Value *CmpN = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ, IdxEnd, 1694 ResumeIndex, "cmp.n", 1695 MiddleBlock->getTerminator()); 1696 1697 BranchInst::Create(ExitBlock, ScalarPH, CmpN, MiddleBlock->getTerminator()); 1698 // Remove the old terminator. 1699 MiddleBlock->getTerminator()->eraseFromParent(); 1700 1701 // Create i+1 and fill the PHINode. 1702 Value *NextIdx = Builder.CreateAdd(Induction, Step, "index.next"); 1703 Induction->addIncoming(StartIdx, VectorPH); 1704 Induction->addIncoming(NextIdx, VecBody); 1705 // Create the compare. 1706 Value *ICmp = Builder.CreateICmpEQ(NextIdx, IdxEndRoundDown); 1707 Builder.CreateCondBr(ICmp, MiddleBlock, VecBody); 1708 1709 // Now we have two terminators. Remove the old one from the block. 1710 VecBody->getTerminator()->eraseFromParent(); 1711 1712 // Get ready to start creating new instructions into the vectorized body. 1713 Builder.SetInsertPoint(VecBody->getFirstInsertionPt()); 1714 1715 // Create and register the new vector loop. 1716 Loop* Lp = new Loop(); 1717 Loop *ParentLoop = OrigLoop->getParentLoop(); 1718 1719 // Insert the new loop into the loop nest and register the new basic blocks. 1720 if (ParentLoop) { 1721 ParentLoop->addChildLoop(Lp); 1722 for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I) 1723 ParentLoop->addBasicBlockToLoop(LoopBypassBlocks[I], LI->getBase()); 1724 ParentLoop->addBasicBlockToLoop(ScalarPH, LI->getBase()); 1725 ParentLoop->addBasicBlockToLoop(VectorPH, LI->getBase()); 1726 ParentLoop->addBasicBlockToLoop(MiddleBlock, LI->getBase()); 1727 } else { 1728 LI->addTopLevelLoop(Lp); 1729 } 1730 1731 Lp->addBasicBlockToLoop(VecBody, LI->getBase()); 1732 1733 // Save the state. 1734 LoopVectorPreHeader = VectorPH; 1735 LoopScalarPreHeader = ScalarPH; 1736 LoopMiddleBlock = MiddleBlock; 1737 LoopExitBlock = ExitBlock; 1738 LoopVectorBody = VecBody; 1739 LoopScalarBody = OldBasicBlock; 1740} 1741 1742/// This function returns the identity element (or neutral element) for 1743/// the operation K. 1744Constant* 1745LoopVectorizationLegality::getReductionIdentity(ReductionKind K, Type *Tp) { 1746 switch (K) { 1747 case RK_IntegerXor: 1748 case RK_IntegerAdd: 1749 case RK_IntegerOr: 1750 // Adding, Xoring, Oring zero to a number does not change it. 1751 return ConstantInt::get(Tp, 0); 1752 case RK_IntegerMult: 1753 // Multiplying a number by 1 does not change it. 1754 return ConstantInt::get(Tp, 1); 1755 case RK_IntegerAnd: 1756 // AND-ing a number with an all-1 value does not change it. 1757 return ConstantInt::get(Tp, -1, true); 1758 case RK_FloatMult: 1759 // Multiplying a number by 1 does not change it. 1760 return ConstantFP::get(Tp, 1.0L); 1761 case RK_FloatAdd: 1762 // Adding zero to a number does not change it. 1763 return ConstantFP::get(Tp, 0.0L); 1764 default: 1765 llvm_unreachable("Unknown reduction kind"); 1766 } 1767} 1768 1769static Intrinsic::ID 1770getIntrinsicIDForCall(CallInst *CI, const TargetLibraryInfo *TLI) { 1771 // If we have an intrinsic call, check if it is trivially vectorizable. 1772 if (IntrinsicInst *II = dyn_cast<IntrinsicInst>(CI)) { 1773 switch (II->getIntrinsicID()) { 1774 case Intrinsic::sqrt: 1775 case Intrinsic::sin: 1776 case Intrinsic::cos: 1777 case Intrinsic::exp: 1778 case Intrinsic::exp2: 1779 case Intrinsic::log: 1780 case Intrinsic::log10: 1781 case Intrinsic::log2: 1782 case Intrinsic::fabs: 1783 case Intrinsic::floor: 1784 case Intrinsic::ceil: 1785 case Intrinsic::trunc: 1786 case Intrinsic::rint: 1787 case Intrinsic::nearbyint: 1788 case Intrinsic::pow: 1789 case Intrinsic::fma: 1790 case Intrinsic::fmuladd: 1791 return II->getIntrinsicID(); 1792 default: 1793 return Intrinsic::not_intrinsic; 1794 } 1795 } 1796 1797 if (!TLI) 1798 return Intrinsic::not_intrinsic; 1799 1800 LibFunc::Func Func; 1801 Function *F = CI->getCalledFunction(); 1802 // We're going to make assumptions on the semantics of the functions, check 1803 // that the target knows that it's available in this environment. 1804 if (!F || !TLI->getLibFunc(F->getName(), Func)) 1805 return Intrinsic::not_intrinsic; 1806 1807 // Otherwise check if we have a call to a function that can be turned into a 1808 // vector intrinsic. 1809 switch (Func) { 1810 default: 1811 break; 1812 case LibFunc::sin: 1813 case LibFunc::sinf: 1814 case LibFunc::sinl: 1815 return Intrinsic::sin; 1816 case LibFunc::cos: 1817 case LibFunc::cosf: 1818 case LibFunc::cosl: 1819 return Intrinsic::cos; 1820 case LibFunc::exp: 1821 case LibFunc::expf: 1822 case LibFunc::expl: 1823 return Intrinsic::exp; 1824 case LibFunc::exp2: 1825 case LibFunc::exp2f: 1826 case LibFunc::exp2l: 1827 return Intrinsic::exp2; 1828 case LibFunc::log: 1829 case LibFunc::logf: 1830 case LibFunc::logl: 1831 return Intrinsic::log; 1832 case LibFunc::log10: 1833 case LibFunc::log10f: 1834 case LibFunc::log10l: 1835 return Intrinsic::log10; 1836 case LibFunc::log2: 1837 case LibFunc::log2f: 1838 case LibFunc::log2l: 1839 return Intrinsic::log2; 1840 case LibFunc::fabs: 1841 case LibFunc::fabsf: 1842 case LibFunc::fabsl: 1843 return Intrinsic::fabs; 1844 case LibFunc::floor: 1845 case LibFunc::floorf: 1846 case LibFunc::floorl: 1847 return Intrinsic::floor; 1848 case LibFunc::ceil: 1849 case LibFunc::ceilf: 1850 case LibFunc::ceill: 1851 return Intrinsic::ceil; 1852 case LibFunc::trunc: 1853 case LibFunc::truncf: 1854 case LibFunc::truncl: 1855 return Intrinsic::trunc; 1856 case LibFunc::rint: 1857 case LibFunc::rintf: 1858 case LibFunc::rintl: 1859 return Intrinsic::rint; 1860 case LibFunc::nearbyint: 1861 case LibFunc::nearbyintf: 1862 case LibFunc::nearbyintl: 1863 return Intrinsic::nearbyint; 1864 case LibFunc::pow: 1865 case LibFunc::powf: 1866 case LibFunc::powl: 1867 return Intrinsic::pow; 1868 } 1869 1870 return Intrinsic::not_intrinsic; 1871} 1872 1873/// This function translates the reduction kind to an LLVM binary operator. 1874static unsigned 1875getReductionBinOp(LoopVectorizationLegality::ReductionKind Kind) { 1876 switch (Kind) { 1877 case LoopVectorizationLegality::RK_IntegerAdd: 1878 return Instruction::Add; 1879 case LoopVectorizationLegality::RK_IntegerMult: 1880 return Instruction::Mul; 1881 case LoopVectorizationLegality::RK_IntegerOr: 1882 return Instruction::Or; 1883 case LoopVectorizationLegality::RK_IntegerAnd: 1884 return Instruction::And; 1885 case LoopVectorizationLegality::RK_IntegerXor: 1886 return Instruction::Xor; 1887 case LoopVectorizationLegality::RK_FloatMult: 1888 return Instruction::FMul; 1889 case LoopVectorizationLegality::RK_FloatAdd: 1890 return Instruction::FAdd; 1891 case LoopVectorizationLegality::RK_IntegerMinMax: 1892 return Instruction::ICmp; 1893 case LoopVectorizationLegality::RK_FloatMinMax: 1894 return Instruction::FCmp; 1895 default: 1896 llvm_unreachable("Unknown reduction operation"); 1897 } 1898} 1899 1900Value *createMinMaxOp(IRBuilder<> &Builder, 1901 LoopVectorizationLegality::MinMaxReductionKind RK, 1902 Value *Left, 1903 Value *Right) { 1904 CmpInst::Predicate P = CmpInst::ICMP_NE; 1905 switch (RK) { 1906 default: 1907 llvm_unreachable("Unknown min/max reduction kind"); 1908 case LoopVectorizationLegality::MRK_UIntMin: 1909 P = CmpInst::ICMP_ULT; 1910 break; 1911 case LoopVectorizationLegality::MRK_UIntMax: 1912 P = CmpInst::ICMP_UGT; 1913 break; 1914 case LoopVectorizationLegality::MRK_SIntMin: 1915 P = CmpInst::ICMP_SLT; 1916 break; 1917 case LoopVectorizationLegality::MRK_SIntMax: 1918 P = CmpInst::ICMP_SGT; 1919 break; 1920 case LoopVectorizationLegality::MRK_FloatMin: 1921 P = CmpInst::FCMP_OLT; 1922 break; 1923 case LoopVectorizationLegality::MRK_FloatMax: 1924 P = CmpInst::FCMP_OGT; 1925 break; 1926 } 1927 1928 Value *Cmp; 1929 if (RK == LoopVectorizationLegality::MRK_FloatMin || RK == LoopVectorizationLegality::MRK_FloatMax) 1930 Cmp = Builder.CreateFCmp(P, Left, Right, "rdx.minmax.cmp"); 1931 else 1932 Cmp = Builder.CreateICmp(P, Left, Right, "rdx.minmax.cmp"); 1933 1934 Value *Select = Builder.CreateSelect(Cmp, Left, Right, "rdx.minmax.select"); 1935 return Select; 1936} 1937 1938void 1939InnerLoopVectorizer::vectorizeLoop(LoopVectorizationLegality *Legal) { 1940 //===------------------------------------------------===// 1941 // 1942 // Notice: any optimization or new instruction that go 1943 // into the code below should be also be implemented in 1944 // the cost-model. 1945 // 1946 //===------------------------------------------------===// 1947 Constant *Zero = Builder.getInt32(0); 1948 1949 // In order to support reduction variables we need to be able to vectorize 1950 // Phi nodes. Phi nodes have cycles, so we need to vectorize them in two 1951 // stages. First, we create a new vector PHI node with no incoming edges. 1952 // We use this value when we vectorize all of the instructions that use the 1953 // PHI. Next, after all of the instructions in the block are complete we 1954 // add the new incoming edges to the PHI. At this point all of the 1955 // instructions in the basic block are vectorized, so we can use them to 1956 // construct the PHI. 1957 PhiVector RdxPHIsToFix; 1958 1959 // Scan the loop in a topological order to ensure that defs are vectorized 1960 // before users. 1961 LoopBlocksDFS DFS(OrigLoop); 1962 DFS.perform(LI); 1963 1964 // Vectorize all of the blocks in the original loop. 1965 for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(), 1966 be = DFS.endRPO(); bb != be; ++bb) 1967 vectorizeBlockInLoop(Legal, *bb, &RdxPHIsToFix); 1968 1969 // At this point every instruction in the original loop is widened to 1970 // a vector form. We are almost done. Now, we need to fix the PHI nodes 1971 // that we vectorized. The PHI nodes are currently empty because we did 1972 // not want to introduce cycles. Notice that the remaining PHI nodes 1973 // that we need to fix are reduction variables. 1974 1975 // Create the 'reduced' values for each of the induction vars. 1976 // The reduced values are the vector values that we scalarize and combine 1977 // after the loop is finished. 1978 for (PhiVector::iterator it = RdxPHIsToFix.begin(), e = RdxPHIsToFix.end(); 1979 it != e; ++it) { 1980 PHINode *RdxPhi = *it; 1981 assert(RdxPhi && "Unable to recover vectorized PHI"); 1982 1983 // Find the reduction variable descriptor. 1984 assert(Legal->getReductionVars()->count(RdxPhi) && 1985 "Unable to find the reduction variable"); 1986 LoopVectorizationLegality::ReductionDescriptor RdxDesc = 1987 (*Legal->getReductionVars())[RdxPhi]; 1988 1989 // We need to generate a reduction vector from the incoming scalar. 1990 // To do so, we need to generate the 'identity' vector and overide 1991 // one of the elements with the incoming scalar reduction. We need 1992 // to do it in the vector-loop preheader. 1993 Builder.SetInsertPoint(LoopBypassBlocks.front()->getTerminator()); 1994 1995 // This is the vector-clone of the value that leaves the loop. 1996 VectorParts &VectorExit = getVectorValue(RdxDesc.LoopExitInstr); 1997 Type *VecTy = VectorExit[0]->getType(); 1998 1999 // Find the reduction identity variable. Zero for addition, or, xor, 2000 // one for multiplication, -1 for And. 2001 Value *Identity; 2002 Value *VectorStart; 2003 if (RdxDesc.Kind == LoopVectorizationLegality::RK_IntegerMinMax || 2004 RdxDesc.Kind == LoopVectorizationLegality::RK_FloatMinMax) { 2005 // MinMax reduction have the start value as their identify. 2006 VectorStart = Identity = Builder.CreateVectorSplat(VF, RdxDesc.StartValue, 2007 "minmax.ident"); 2008 } else { 2009 Constant *Iden = 2010 LoopVectorizationLegality::getReductionIdentity(RdxDesc.Kind, 2011 VecTy->getScalarType()); 2012 Identity = ConstantVector::getSplat(VF, Iden); 2013 2014 // This vector is the Identity vector where the first element is the 2015 // incoming scalar reduction. 2016 VectorStart = Builder.CreateInsertElement(Identity, 2017 RdxDesc.StartValue, Zero); 2018 } 2019 2020 // Fix the vector-loop phi. 2021 // We created the induction variable so we know that the 2022 // preheader is the first entry. 2023 BasicBlock *VecPreheader = Induction->getIncomingBlock(0); 2024 2025 // Reductions do not have to start at zero. They can start with 2026 // any loop invariant values. 2027 VectorParts &VecRdxPhi = WidenMap.get(RdxPhi); 2028 BasicBlock *Latch = OrigLoop->getLoopLatch(); 2029 Value *LoopVal = RdxPhi->getIncomingValueForBlock(Latch); 2030 VectorParts &Val = getVectorValue(LoopVal); 2031 for (unsigned part = 0; part < UF; ++part) { 2032 // Make sure to add the reduction stat value only to the 2033 // first unroll part. 2034 Value *StartVal = (part == 0) ? VectorStart : Identity; 2035 cast<PHINode>(VecRdxPhi[part])->addIncoming(StartVal, VecPreheader); 2036 cast<PHINode>(VecRdxPhi[part])->addIncoming(Val[part], LoopVectorBody); 2037 } 2038 2039 // Before each round, move the insertion point right between 2040 // the PHIs and the values we are going to write. 2041 // This allows us to write both PHINodes and the extractelement 2042 // instructions. 2043 Builder.SetInsertPoint(LoopMiddleBlock->getFirstInsertionPt()); 2044 2045 VectorParts RdxParts; 2046 for (unsigned part = 0; part < UF; ++part) { 2047 // This PHINode contains the vectorized reduction variable, or 2048 // the initial value vector, if we bypass the vector loop. 2049 VectorParts &RdxExitVal = getVectorValue(RdxDesc.LoopExitInstr); 2050 PHINode *NewPhi = Builder.CreatePHI(VecTy, 2, "rdx.vec.exit.phi"); 2051 Value *StartVal = (part == 0) ? VectorStart : Identity; 2052 for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I) 2053 NewPhi->addIncoming(StartVal, LoopBypassBlocks[I]); 2054 NewPhi->addIncoming(RdxExitVal[part], LoopVectorBody); 2055 RdxParts.push_back(NewPhi); 2056 } 2057 2058 // Reduce all of the unrolled parts into a single vector. 2059 Value *ReducedPartRdx = RdxParts[0]; 2060 unsigned Op = getReductionBinOp(RdxDesc.Kind); 2061 for (unsigned part = 1; part < UF; ++part) { 2062 if (Op != Instruction::ICmp && Op != Instruction::FCmp) 2063 ReducedPartRdx = Builder.CreateBinOp((Instruction::BinaryOps)Op, 2064 RdxParts[part], ReducedPartRdx, 2065 "bin.rdx"); 2066 else 2067 ReducedPartRdx = createMinMaxOp(Builder, RdxDesc.MinMaxKind, 2068 ReducedPartRdx, RdxParts[part]); 2069 } 2070 2071 // VF is a power of 2 so we can emit the reduction using log2(VF) shuffles 2072 // and vector ops, reducing the set of values being computed by half each 2073 // round. 2074 assert(isPowerOf2_32(VF) && 2075 "Reduction emission only supported for pow2 vectors!"); 2076 Value *TmpVec = ReducedPartRdx; 2077 SmallVector<Constant*, 32> ShuffleMask(VF, 0); 2078 for (unsigned i = VF; i != 1; i >>= 1) { 2079 // Move the upper half of the vector to the lower half. 2080 for (unsigned j = 0; j != i/2; ++j) 2081 ShuffleMask[j] = Builder.getInt32(i/2 + j); 2082 2083 // Fill the rest of the mask with undef. 2084 std::fill(&ShuffleMask[i/2], ShuffleMask.end(), 2085 UndefValue::get(Builder.getInt32Ty())); 2086 2087 Value *Shuf = 2088 Builder.CreateShuffleVector(TmpVec, 2089 UndefValue::get(TmpVec->getType()), 2090 ConstantVector::get(ShuffleMask), 2091 "rdx.shuf"); 2092 2093 if (Op != Instruction::ICmp && Op != Instruction::FCmp) 2094 TmpVec = Builder.CreateBinOp((Instruction::BinaryOps)Op, TmpVec, Shuf, 2095 "bin.rdx"); 2096 else 2097 TmpVec = createMinMaxOp(Builder, RdxDesc.MinMaxKind, TmpVec, Shuf); 2098 } 2099 2100 // The result is in the first element of the vector. 2101 Value *Scalar0 = Builder.CreateExtractElement(TmpVec, Builder.getInt32(0)); 2102 2103 // Now, we need to fix the users of the reduction variable 2104 // inside and outside of the scalar remainder loop. 2105 // We know that the loop is in LCSSA form. We need to update the 2106 // PHI nodes in the exit blocks. 2107 for (BasicBlock::iterator LEI = LoopExitBlock->begin(), 2108 LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) { 2109 PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI); 2110 if (!LCSSAPhi) continue; 2111 2112 // All PHINodes need to have a single entry edge, or two if 2113 // we already fixed them. 2114 assert(LCSSAPhi->getNumIncomingValues() < 3 && "Invalid LCSSA PHI"); 2115 2116 // We found our reduction value exit-PHI. Update it with the 2117 // incoming bypass edge. 2118 if (LCSSAPhi->getIncomingValue(0) == RdxDesc.LoopExitInstr) { 2119 // Add an edge coming from the bypass. 2120 LCSSAPhi->addIncoming(Scalar0, LoopMiddleBlock); 2121 break; 2122 } 2123 }// end of the LCSSA phi scan. 2124 2125 // Fix the scalar loop reduction variable with the incoming reduction sum 2126 // from the vector body and from the backedge value. 2127 int IncomingEdgeBlockIdx = 2128 (RdxPhi)->getBasicBlockIndex(OrigLoop->getLoopLatch()); 2129 assert(IncomingEdgeBlockIdx >= 0 && "Invalid block index"); 2130 // Pick the other block. 2131 int SelfEdgeBlockIdx = (IncomingEdgeBlockIdx ? 0 : 1); 2132 (RdxPhi)->setIncomingValue(SelfEdgeBlockIdx, Scalar0); 2133 (RdxPhi)->setIncomingValue(IncomingEdgeBlockIdx, RdxDesc.LoopExitInstr); 2134 }// end of for each redux variable. 2135 2136 // The Loop exit block may have single value PHI nodes where the incoming 2137 // value is 'undef'. While vectorizing we only handled real values that 2138 // were defined inside the loop. Here we handle the 'undef case'. 2139 // See PR14725. 2140 for (BasicBlock::iterator LEI = LoopExitBlock->begin(), 2141 LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) { 2142 PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI); 2143 if (!LCSSAPhi) continue; 2144 if (LCSSAPhi->getNumIncomingValues() == 1) 2145 LCSSAPhi->addIncoming(UndefValue::get(LCSSAPhi->getType()), 2146 LoopMiddleBlock); 2147 } 2148} 2149 2150InnerLoopVectorizer::VectorParts 2151InnerLoopVectorizer::createEdgeMask(BasicBlock *Src, BasicBlock *Dst) { 2152 assert(std::find(pred_begin(Dst), pred_end(Dst), Src) != pred_end(Dst) && 2153 "Invalid edge"); 2154 2155 VectorParts SrcMask = createBlockInMask(Src); 2156 2157 // The terminator has to be a branch inst! 2158 BranchInst *BI = dyn_cast<BranchInst>(Src->getTerminator()); 2159 assert(BI && "Unexpected terminator found"); 2160 2161 if (BI->isConditional()) { 2162 VectorParts EdgeMask = getVectorValue(BI->getCondition()); 2163 2164 if (BI->getSuccessor(0) != Dst) 2165 for (unsigned part = 0; part < UF; ++part) 2166 EdgeMask[part] = Builder.CreateNot(EdgeMask[part]); 2167 2168 for (unsigned part = 0; part < UF; ++part) 2169 EdgeMask[part] = Builder.CreateAnd(EdgeMask[part], SrcMask[part]); 2170 return EdgeMask; 2171 } 2172 2173 return SrcMask; 2174} 2175 2176InnerLoopVectorizer::VectorParts 2177InnerLoopVectorizer::createBlockInMask(BasicBlock *BB) { 2178 assert(OrigLoop->contains(BB) && "Block is not a part of a loop"); 2179 2180 // Loop incoming mask is all-one. 2181 if (OrigLoop->getHeader() == BB) { 2182 Value *C = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 1); 2183 return getVectorValue(C); 2184 } 2185 2186 // This is the block mask. We OR all incoming edges, and with zero. 2187 Value *Zero = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 0); 2188 VectorParts BlockMask = getVectorValue(Zero); 2189 2190 // For each pred: 2191 for (pred_iterator it = pred_begin(BB), e = pred_end(BB); it != e; ++it) { 2192 VectorParts EM = createEdgeMask(*it, BB); 2193 for (unsigned part = 0; part < UF; ++part) 2194 BlockMask[part] = Builder.CreateOr(BlockMask[part], EM[part]); 2195 } 2196 2197 return BlockMask; 2198} 2199 2200void 2201InnerLoopVectorizer::vectorizeBlockInLoop(LoopVectorizationLegality *Legal, 2202 BasicBlock *BB, PhiVector *PV) { 2203 // For each instruction in the old loop. 2204 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 2205 VectorParts &Entry = WidenMap.get(it); 2206 switch (it->getOpcode()) { 2207 case Instruction::Br: 2208 // Nothing to do for PHIs and BR, since we already took care of the 2209 // loop control flow instructions. 2210 continue; 2211 case Instruction::PHI:{ 2212 PHINode* P = cast<PHINode>(it); 2213 // Handle reduction variables: 2214 if (Legal->getReductionVars()->count(P)) { 2215 for (unsigned part = 0; part < UF; ++part) { 2216 // This is phase one of vectorizing PHIs. 2217 Type *VecTy = VectorType::get(it->getType(), VF); 2218 Entry[part] = PHINode::Create(VecTy, 2, "vec.phi", 2219 LoopVectorBody-> getFirstInsertionPt()); 2220 } 2221 PV->push_back(P); 2222 continue; 2223 } 2224 2225 // Check for PHI nodes that are lowered to vector selects. 2226 if (P->getParent() != OrigLoop->getHeader()) { 2227 // We know that all PHIs in non header blocks are converted into 2228 // selects, so we don't have to worry about the insertion order and we 2229 // can just use the builder. 2230 // At this point we generate the predication tree. There may be 2231 // duplications since this is a simple recursive scan, but future 2232 // optimizations will clean it up. 2233 2234 unsigned NumIncoming = P->getNumIncomingValues(); 2235 2236 // Generate a sequence of selects of the form: 2237 // SELECT(Mask3, In3, 2238 // SELECT(Mask2, In2, 2239 // ( ...))) 2240 for (unsigned In = 0; In < NumIncoming; In++) { 2241 VectorParts Cond = createEdgeMask(P->getIncomingBlock(In), 2242 P->getParent()); 2243 VectorParts &In0 = getVectorValue(P->getIncomingValue(In)); 2244 2245 for (unsigned part = 0; part < UF; ++part) { 2246 // We might have single edge PHIs (blocks) - use an identity 2247 // 'select' for the first PHI operand. 2248 if (In == 0) 2249 Entry[part] = Builder.CreateSelect(Cond[part], In0[part], 2250 In0[part]); 2251 else 2252 // Select between the current value and the previous incoming edge 2253 // based on the incoming mask. 2254 Entry[part] = Builder.CreateSelect(Cond[part], In0[part], 2255 Entry[part], "predphi"); 2256 } 2257 } 2258 continue; 2259 } 2260 2261 // This PHINode must be an induction variable. 2262 // Make sure that we know about it. 2263 assert(Legal->getInductionVars()->count(P) && 2264 "Not an induction variable"); 2265 2266 LoopVectorizationLegality::InductionInfo II = 2267 Legal->getInductionVars()->lookup(P); 2268 2269 switch (II.IK) { 2270 case LoopVectorizationLegality::IK_NoInduction: 2271 llvm_unreachable("Unknown induction"); 2272 case LoopVectorizationLegality::IK_IntInduction: { 2273 assert(P->getType() == II.StartValue->getType() && "Types must match"); 2274 Type *PhiTy = P->getType(); 2275 Value *Broadcasted; 2276 if (P == OldInduction) { 2277 // Handle the canonical induction variable. We might have had to 2278 // extend the type. 2279 Broadcasted = Builder.CreateTrunc(Induction, PhiTy); 2280 } else { 2281 // Handle other induction variables that are now based on the 2282 // canonical one. 2283 Value *NormalizedIdx = Builder.CreateSub(Induction, ExtendedIdx, 2284 "normalized.idx"); 2285 NormalizedIdx = Builder.CreateSExtOrTrunc(NormalizedIdx, PhiTy); 2286 Broadcasted = Builder.CreateAdd(II.StartValue, NormalizedIdx, 2287 "offset.idx"); 2288 } 2289 Broadcasted = getBroadcastInstrs(Broadcasted); 2290 // After broadcasting the induction variable we need to make the vector 2291 // consecutive by adding 0, 1, 2, etc. 2292 for (unsigned part = 0; part < UF; ++part) 2293 Entry[part] = getConsecutiveVector(Broadcasted, VF * part, false); 2294 continue; 2295 } 2296 case LoopVectorizationLegality::IK_ReverseIntInduction: 2297 case LoopVectorizationLegality::IK_PtrInduction: 2298 case LoopVectorizationLegality::IK_ReversePtrInduction: 2299 // Handle reverse integer and pointer inductions. 2300 Value *StartIdx = ExtendedIdx; 2301 // This is the normalized GEP that starts counting at zero. 2302 Value *NormalizedIdx = Builder.CreateSub(Induction, StartIdx, 2303 "normalized.idx"); 2304 2305 // Handle the reverse integer induction variable case. 2306 if (LoopVectorizationLegality::IK_ReverseIntInduction == II.IK) { 2307 IntegerType *DstTy = cast<IntegerType>(II.StartValue->getType()); 2308 Value *CNI = Builder.CreateSExtOrTrunc(NormalizedIdx, DstTy, 2309 "resize.norm.idx"); 2310 Value *ReverseInd = Builder.CreateSub(II.StartValue, CNI, 2311 "reverse.idx"); 2312 2313 // This is a new value so do not hoist it out. 2314 Value *Broadcasted = getBroadcastInstrs(ReverseInd); 2315 // After broadcasting the induction variable we need to make the 2316 // vector consecutive by adding ... -3, -2, -1, 0. 2317 for (unsigned part = 0; part < UF; ++part) 2318 Entry[part] = getConsecutiveVector(Broadcasted, -(int)VF * part, 2319 true); 2320 continue; 2321 } 2322 2323 // Handle the pointer induction variable case. 2324 assert(P->getType()->isPointerTy() && "Unexpected type."); 2325 2326 // Is this a reverse induction ptr or a consecutive induction ptr. 2327 bool Reverse = (LoopVectorizationLegality::IK_ReversePtrInduction == 2328 II.IK); 2329 2330 // This is the vector of results. Notice that we don't generate 2331 // vector geps because scalar geps result in better code. 2332 for (unsigned part = 0; part < UF; ++part) { 2333 Value *VecVal = UndefValue::get(VectorType::get(P->getType(), VF)); 2334 for (unsigned int i = 0; i < VF; ++i) { 2335 int EltIndex = (i + part * VF) * (Reverse ? -1 : 1); 2336 Constant *Idx = ConstantInt::get(Induction->getType(), EltIndex); 2337 Value *GlobalIdx; 2338 if (!Reverse) 2339 GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx, "gep.idx"); 2340 else 2341 GlobalIdx = Builder.CreateSub(Idx, NormalizedIdx, "gep.ridx"); 2342 2343 Value *SclrGep = Builder.CreateGEP(II.StartValue, GlobalIdx, 2344 "next.gep"); 2345 VecVal = Builder.CreateInsertElement(VecVal, SclrGep, 2346 Builder.getInt32(i), 2347 "insert.gep"); 2348 } 2349 Entry[part] = VecVal; 2350 } 2351 continue; 2352 } 2353 2354 }// End of PHI. 2355 2356 case Instruction::Add: 2357 case Instruction::FAdd: 2358 case Instruction::Sub: 2359 case Instruction::FSub: 2360 case Instruction::Mul: 2361 case Instruction::FMul: 2362 case Instruction::UDiv: 2363 case Instruction::SDiv: 2364 case Instruction::FDiv: 2365 case Instruction::URem: 2366 case Instruction::SRem: 2367 case Instruction::FRem: 2368 case Instruction::Shl: 2369 case Instruction::LShr: 2370 case Instruction::AShr: 2371 case Instruction::And: 2372 case Instruction::Or: 2373 case Instruction::Xor: { 2374 // Just widen binops. 2375 BinaryOperator *BinOp = dyn_cast<BinaryOperator>(it); 2376 VectorParts &A = getVectorValue(it->getOperand(0)); 2377 VectorParts &B = getVectorValue(it->getOperand(1)); 2378 2379 // Use this vector value for all users of the original instruction. 2380 for (unsigned Part = 0; Part < UF; ++Part) { 2381 Value *V = Builder.CreateBinOp(BinOp->getOpcode(), A[Part], B[Part]); 2382 2383 // Update the NSW, NUW and Exact flags. Notice: V can be an Undef. 2384 BinaryOperator *VecOp = dyn_cast<BinaryOperator>(V); 2385 if (VecOp && isa<OverflowingBinaryOperator>(BinOp)) { 2386 VecOp->setHasNoSignedWrap(BinOp->hasNoSignedWrap()); 2387 VecOp->setHasNoUnsignedWrap(BinOp->hasNoUnsignedWrap()); 2388 } 2389 if (VecOp && isa<PossiblyExactOperator>(VecOp)) 2390 VecOp->setIsExact(BinOp->isExact()); 2391 2392 Entry[Part] = V; 2393 } 2394 break; 2395 } 2396 case Instruction::Select: { 2397 // Widen selects. 2398 // If the selector is loop invariant we can create a select 2399 // instruction with a scalar condition. Otherwise, use vector-select. 2400 bool InvariantCond = SE->isLoopInvariant(SE->getSCEV(it->getOperand(0)), 2401 OrigLoop); 2402 2403 // The condition can be loop invariant but still defined inside the 2404 // loop. This means that we can't just use the original 'cond' value. 2405 // We have to take the 'vectorized' value and pick the first lane. 2406 // Instcombine will make this a no-op. 2407 VectorParts &Cond = getVectorValue(it->getOperand(0)); 2408 VectorParts &Op0 = getVectorValue(it->getOperand(1)); 2409 VectorParts &Op1 = getVectorValue(it->getOperand(2)); 2410 Value *ScalarCond = Builder.CreateExtractElement(Cond[0], 2411 Builder.getInt32(0)); 2412 for (unsigned Part = 0; Part < UF; ++Part) { 2413 Entry[Part] = Builder.CreateSelect( 2414 InvariantCond ? ScalarCond : Cond[Part], 2415 Op0[Part], 2416 Op1[Part]); 2417 } 2418 break; 2419 } 2420 2421 case Instruction::ICmp: 2422 case Instruction::FCmp: { 2423 // Widen compares. Generate vector compares. 2424 bool FCmp = (it->getOpcode() == Instruction::FCmp); 2425 CmpInst *Cmp = dyn_cast<CmpInst>(it); 2426 VectorParts &A = getVectorValue(it->getOperand(0)); 2427 VectorParts &B = getVectorValue(it->getOperand(1)); 2428 for (unsigned Part = 0; Part < UF; ++Part) { 2429 Value *C = 0; 2430 if (FCmp) 2431 C = Builder.CreateFCmp(Cmp->getPredicate(), A[Part], B[Part]); 2432 else 2433 C = Builder.CreateICmp(Cmp->getPredicate(), A[Part], B[Part]); 2434 Entry[Part] = C; 2435 } 2436 break; 2437 } 2438 2439 case Instruction::Store: 2440 case Instruction::Load: 2441 vectorizeMemoryInstruction(it, Legal); 2442 break; 2443 case Instruction::ZExt: 2444 case Instruction::SExt: 2445 case Instruction::FPToUI: 2446 case Instruction::FPToSI: 2447 case Instruction::FPExt: 2448 case Instruction::PtrToInt: 2449 case Instruction::IntToPtr: 2450 case Instruction::SIToFP: 2451 case Instruction::UIToFP: 2452 case Instruction::Trunc: 2453 case Instruction::FPTrunc: 2454 case Instruction::BitCast: { 2455 CastInst *CI = dyn_cast<CastInst>(it); 2456 /// Optimize the special case where the source is the induction 2457 /// variable. Notice that we can only optimize the 'trunc' case 2458 /// because: a. FP conversions lose precision, b. sext/zext may wrap, 2459 /// c. other casts depend on pointer size. 2460 if (CI->getOperand(0) == OldInduction && 2461 it->getOpcode() == Instruction::Trunc) { 2462 Value *ScalarCast = Builder.CreateCast(CI->getOpcode(), Induction, 2463 CI->getType()); 2464 Value *Broadcasted = getBroadcastInstrs(ScalarCast); 2465 for (unsigned Part = 0; Part < UF; ++Part) 2466 Entry[Part] = getConsecutiveVector(Broadcasted, VF * Part, false); 2467 break; 2468 } 2469 /// Vectorize casts. 2470 Type *DestTy = VectorType::get(CI->getType()->getScalarType(), VF); 2471 2472 VectorParts &A = getVectorValue(it->getOperand(0)); 2473 for (unsigned Part = 0; Part < UF; ++Part) 2474 Entry[Part] = Builder.CreateCast(CI->getOpcode(), A[Part], DestTy); 2475 break; 2476 } 2477 2478 case Instruction::Call: { 2479 // Ignore dbg intrinsics. 2480 if (isa<DbgInfoIntrinsic>(it)) 2481 break; 2482 2483 Module *M = BB->getParent()->getParent(); 2484 CallInst *CI = cast<CallInst>(it); 2485 Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI); 2486 assert(ID && "Not an intrinsic call!"); 2487 for (unsigned Part = 0; Part < UF; ++Part) { 2488 SmallVector<Value*, 4> Args; 2489 for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i) { 2490 VectorParts &Arg = getVectorValue(CI->getArgOperand(i)); 2491 Args.push_back(Arg[Part]); 2492 } 2493 Type *Tys[] = { VectorType::get(CI->getType()->getScalarType(), VF) }; 2494 Function *F = Intrinsic::getDeclaration(M, ID, Tys); 2495 Entry[Part] = Builder.CreateCall(F, Args); 2496 } 2497 break; 2498 } 2499 2500 default: 2501 // All other instructions are unsupported. Scalarize them. 2502 scalarizeInstruction(it); 2503 break; 2504 }// end of switch. 2505 }// end of for_each instr. 2506} 2507 2508void InnerLoopVectorizer::updateAnalysis() { 2509 // Forget the original basic block. 2510 SE->forgetLoop(OrigLoop); 2511 2512 // Update the dominator tree information. 2513 assert(DT->properlyDominates(LoopBypassBlocks.front(), LoopExitBlock) && 2514 "Entry does not dominate exit."); 2515 2516 for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I) 2517 DT->addNewBlock(LoopBypassBlocks[I], LoopBypassBlocks[I-1]); 2518 DT->addNewBlock(LoopVectorPreHeader, LoopBypassBlocks.back()); 2519 DT->addNewBlock(LoopVectorBody, LoopVectorPreHeader); 2520 DT->addNewBlock(LoopMiddleBlock, LoopBypassBlocks.front()); 2521 DT->addNewBlock(LoopScalarPreHeader, LoopMiddleBlock); 2522 DT->changeImmediateDominator(LoopScalarBody, LoopScalarPreHeader); 2523 DT->changeImmediateDominator(LoopExitBlock, LoopMiddleBlock); 2524 2525 DEBUG(DT->verifyAnalysis()); 2526} 2527 2528bool LoopVectorizationLegality::canVectorizeWithIfConvert() { 2529 if (!EnableIfConversion) 2530 return false; 2531 2532 assert(TheLoop->getNumBlocks() > 1 && "Single block loops are vectorizable"); 2533 std::vector<BasicBlock*> &LoopBlocks = TheLoop->getBlocksVector(); 2534 2535 // Collect the blocks that need predication. 2536 for (unsigned i = 0, e = LoopBlocks.size(); i < e; ++i) { 2537 BasicBlock *BB = LoopBlocks[i]; 2538 2539 // We don't support switch statements inside loops. 2540 if (!isa<BranchInst>(BB->getTerminator())) 2541 return false; 2542 2543 // We must be able to predicate all blocks that need to be predicated. 2544 if (blockNeedsPredication(BB) && !blockCanBePredicated(BB)) 2545 return false; 2546 } 2547 2548 // Check that we can actually speculate the hoistable loads. 2549 if (!LoadSpeculation.canHoistAllLoads()) 2550 return false; 2551 2552 // We can if-convert this loop. 2553 return true; 2554} 2555 2556bool LoopVectorizationLegality::canVectorize() { 2557 // We must have a loop in canonical form. Loops with indirectbr in them cannot 2558 // be canonicalized. 2559 if (!TheLoop->getLoopPreheader()) 2560 return false; 2561 2562 // We can only vectorize innermost loops. 2563 if (TheLoop->getSubLoopsVector().size()) 2564 return false; 2565 2566 // We must have a single backedge. 2567 if (TheLoop->getNumBackEdges() != 1) 2568 return false; 2569 2570 // We must have a single exiting block. 2571 if (!TheLoop->getExitingBlock()) 2572 return false; 2573 2574 unsigned NumBlocks = TheLoop->getNumBlocks(); 2575 2576 // Check if we can if-convert non single-bb loops. 2577 if (NumBlocks != 1 && !canVectorizeWithIfConvert()) { 2578 DEBUG(dbgs() << "LV: Can't if-convert the loop.\n"); 2579 return false; 2580 } 2581 2582 // We need to have a loop header. 2583 BasicBlock *Latch = TheLoop->getLoopLatch(); 2584 DEBUG(dbgs() << "LV: Found a loop: " << 2585 TheLoop->getHeader()->getName() << "\n"); 2586 2587 // ScalarEvolution needs to be able to find the exit count. 2588 const SCEV *ExitCount = SE->getBackedgeTakenCount(TheLoop); 2589 if (ExitCount == SE->getCouldNotCompute()) { 2590 DEBUG(dbgs() << "LV: SCEV could not compute the loop exit count.\n"); 2591 return false; 2592 } 2593 2594 // Do not loop-vectorize loops with a tiny trip count. 2595 unsigned TC = SE->getSmallConstantTripCount(TheLoop, Latch); 2596 if (TC > 0u && TC < TinyTripCountVectorThreshold) { 2597 DEBUG(dbgs() << "LV: Found a loop with a very small trip count. " << 2598 "This loop is not worth vectorizing.\n"); 2599 return false; 2600 } 2601 2602 // Check if we can vectorize the instructions and CFG in this loop. 2603 if (!canVectorizeInstrs()) { 2604 DEBUG(dbgs() << "LV: Can't vectorize the instructions or CFG\n"); 2605 return false; 2606 } 2607 2608 // Go over each instruction and look at memory deps. 2609 if (!canVectorizeMemory()) { 2610 DEBUG(dbgs() << "LV: Can't vectorize due to memory conflicts\n"); 2611 return false; 2612 } 2613 2614 // Collect all of the variables that remain uniform after vectorization. 2615 collectLoopUniforms(); 2616 2617 DEBUG(dbgs() << "LV: We can vectorize this loop" << 2618 (PtrRtCheck.Need ? " (with a runtime bound check)" : "") 2619 <<"!\n"); 2620 2621 // Okay! We can vectorize. At this point we don't have any other mem analysis 2622 // which may limit our maximum vectorization factor, so just return true with 2623 // no restrictions. 2624 return true; 2625} 2626 2627static Type *convertPointerToIntegerType(DataLayout &DL, Type *Ty) { 2628 if (Ty->isPointerTy()) 2629 return DL.getIntPtrType(Ty->getContext()); 2630 return Ty; 2631} 2632 2633static Type* getWiderType(DataLayout &DL, Type *Ty0, Type *Ty1) { 2634 Ty0 = convertPointerToIntegerType(DL, Ty0); 2635 Ty1 = convertPointerToIntegerType(DL, Ty1); 2636 if (Ty0->getScalarSizeInBits() > Ty1->getScalarSizeInBits()) 2637 return Ty0; 2638 return Ty1; 2639} 2640 2641/// \brief Check that the instruction has outside loop users and is not an 2642/// identified reduction variable. 2643static bool hasOutsideLoopUser(const Loop *TheLoop, Instruction *Inst, 2644 SmallPtrSet<Value *, 4> &Reductions) { 2645 // Reduction instructions are allowed to have exit users. All other 2646 // instructions must not have external users. 2647 if (!Reductions.count(Inst)) 2648 //Check that all of the users of the loop are inside the BB. 2649 for (Value::use_iterator I = Inst->use_begin(), E = Inst->use_end(); 2650 I != E; ++I) { 2651 Instruction *U = cast<Instruction>(*I); 2652 // This user may be a reduction exit value. 2653 if (!TheLoop->contains(U)) { 2654 DEBUG(dbgs() << "LV: Found an outside user for : "<< *U << "\n"); 2655 return true; 2656 } 2657 } 2658 return false; 2659} 2660 2661bool LoopVectorizationLegality::canVectorizeInstrs() { 2662 BasicBlock *PreHeader = TheLoop->getLoopPreheader(); 2663 BasicBlock *Header = TheLoop->getHeader(); 2664 2665 // Look for the attribute signaling the absence of NaNs. 2666 Function &F = *Header->getParent(); 2667 if (F.hasFnAttribute("no-nans-fp-math")) 2668 HasFunNoNaNAttr = F.getAttributes().getAttribute( 2669 AttributeSet::FunctionIndex, 2670 "no-nans-fp-math").getValueAsString() == "true"; 2671 2672 // For each block in the loop. 2673 for (Loop::block_iterator bb = TheLoop->block_begin(), 2674 be = TheLoop->block_end(); bb != be; ++bb) { 2675 2676 // Scan the instructions in the block and look for hazards. 2677 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e; 2678 ++it) { 2679 2680 if (PHINode *Phi = dyn_cast<PHINode>(it)) { 2681 Type *PhiTy = Phi->getType(); 2682 // Check that this PHI type is allowed. 2683 if (!PhiTy->isIntegerTy() && 2684 !PhiTy->isFloatingPointTy() && 2685 !PhiTy->isPointerTy()) { 2686 DEBUG(dbgs() << "LV: Found an non-int non-pointer PHI.\n"); 2687 return false; 2688 } 2689 2690 // If this PHINode is not in the header block, then we know that we 2691 // can convert it to select during if-conversion. No need to check if 2692 // the PHIs in this block are induction or reduction variables. 2693 if (*bb != Header) { 2694 // Check that this instruction has no outside users or is an 2695 // identified reduction value with an outside user. 2696 if(!hasOutsideLoopUser(TheLoop, it, AllowedExit)) 2697 continue; 2698 return false; 2699 } 2700 2701 // We only allow if-converted PHIs with more than two incoming values. 2702 if (Phi->getNumIncomingValues() != 2) { 2703 DEBUG(dbgs() << "LV: Found an invalid PHI.\n"); 2704 return false; 2705 } 2706 2707 // This is the value coming from the preheader. 2708 Value *StartValue = Phi->getIncomingValueForBlock(PreHeader); 2709 // Check if this is an induction variable. 2710 InductionKind IK = isInductionVariable(Phi); 2711 2712 if (IK_NoInduction != IK) { 2713 // Get the widest type. 2714 if (!WidestIndTy) 2715 WidestIndTy = convertPointerToIntegerType(*DL, PhiTy); 2716 else 2717 WidestIndTy = getWiderType(*DL, PhiTy, WidestIndTy); 2718 2719 // Int inductions are special because we only allow one IV. 2720 if (IK == IK_IntInduction) { 2721 // Use the phi node with the widest type as induction. Use the last 2722 // one if there are multiple (no good reason for doing this other 2723 // than it is expedient). 2724 if (!Induction || PhiTy == WidestIndTy) 2725 Induction = Phi; 2726 } 2727 2728 DEBUG(dbgs() << "LV: Found an induction variable.\n"); 2729 Inductions[Phi] = InductionInfo(StartValue, IK); 2730 continue; 2731 } 2732 2733 if (AddReductionVar(Phi, RK_IntegerAdd)) { 2734 DEBUG(dbgs() << "LV: Found an ADD reduction PHI."<< *Phi <<"\n"); 2735 continue; 2736 } 2737 if (AddReductionVar(Phi, RK_IntegerMult)) { 2738 DEBUG(dbgs() << "LV: Found a MUL reduction PHI."<< *Phi <<"\n"); 2739 continue; 2740 } 2741 if (AddReductionVar(Phi, RK_IntegerOr)) { 2742 DEBUG(dbgs() << "LV: Found an OR reduction PHI."<< *Phi <<"\n"); 2743 continue; 2744 } 2745 if (AddReductionVar(Phi, RK_IntegerAnd)) { 2746 DEBUG(dbgs() << "LV: Found an AND reduction PHI."<< *Phi <<"\n"); 2747 continue; 2748 } 2749 if (AddReductionVar(Phi, RK_IntegerXor)) { 2750 DEBUG(dbgs() << "LV: Found a XOR reduction PHI."<< *Phi <<"\n"); 2751 continue; 2752 } 2753 if (AddReductionVar(Phi, RK_IntegerMinMax)) { 2754 DEBUG(dbgs() << "LV: Found a MINMAX reduction PHI."<< *Phi <<"\n"); 2755 continue; 2756 } 2757 if (AddReductionVar(Phi, RK_FloatMult)) { 2758 DEBUG(dbgs() << "LV: Found an FMult reduction PHI."<< *Phi <<"\n"); 2759 continue; 2760 } 2761 if (AddReductionVar(Phi, RK_FloatAdd)) { 2762 DEBUG(dbgs() << "LV: Found an FAdd reduction PHI."<< *Phi <<"\n"); 2763 continue; 2764 } 2765 if (AddReductionVar(Phi, RK_FloatMinMax)) { 2766 DEBUG(dbgs() << "LV: Found an float MINMAX reduction PHI."<< *Phi <<"\n"); 2767 continue; 2768 } 2769 2770 DEBUG(dbgs() << "LV: Found an unidentified PHI."<< *Phi <<"\n"); 2771 return false; 2772 }// end of PHI handling 2773 2774 // We still don't handle functions. However, we can ignore dbg intrinsic 2775 // calls and we do handle certain intrinsic and libm functions. 2776 CallInst *CI = dyn_cast<CallInst>(it); 2777 if (CI && !getIntrinsicIDForCall(CI, TLI) && !isa<DbgInfoIntrinsic>(CI)) { 2778 DEBUG(dbgs() << "LV: Found a call site.\n"); 2779 return false; 2780 } 2781 2782 // Check that the instruction return type is vectorizable. 2783 if (!VectorType::isValidElementType(it->getType()) && 2784 !it->getType()->isVoidTy()) { 2785 DEBUG(dbgs() << "LV: Found unvectorizable type." << "\n"); 2786 return false; 2787 } 2788 2789 // Check that the stored type is vectorizable. 2790 if (StoreInst *ST = dyn_cast<StoreInst>(it)) { 2791 Type *T = ST->getValueOperand()->getType(); 2792 if (!VectorType::isValidElementType(T)) 2793 return false; 2794 } 2795 2796 // Reduction instructions are allowed to have exit users. 2797 // All other instructions must not have external users. 2798 if (hasOutsideLoopUser(TheLoop, it, AllowedExit)) 2799 return false; 2800 2801 } // next instr. 2802 2803 } 2804 2805 if (!Induction) { 2806 DEBUG(dbgs() << "LV: Did not find one integer induction var.\n"); 2807 if (Inductions.empty()) 2808 return false; 2809 } 2810 2811 return true; 2812} 2813 2814void LoopVectorizationLegality::collectLoopUniforms() { 2815 // We now know that the loop is vectorizable! 2816 // Collect variables that will remain uniform after vectorization. 2817 std::vector<Value*> Worklist; 2818 BasicBlock *Latch = TheLoop->getLoopLatch(); 2819 2820 // Start with the conditional branch and walk up the block. 2821 Worklist.push_back(Latch->getTerminator()->getOperand(0)); 2822 2823 while (Worklist.size()) { 2824 Instruction *I = dyn_cast<Instruction>(Worklist.back()); 2825 Worklist.pop_back(); 2826 2827 // Look at instructions inside this loop. 2828 // Stop when reaching PHI nodes. 2829 // TODO: we need to follow values all over the loop, not only in this block. 2830 if (!I || !TheLoop->contains(I) || isa<PHINode>(I)) 2831 continue; 2832 2833 // This is a known uniform. 2834 Uniforms.insert(I); 2835 2836 // Insert all operands. 2837 Worklist.insert(Worklist.end(), I->op_begin(), I->op_end()); 2838 } 2839} 2840 2841/// \brief Analyses memory accesses in a loop. 2842/// 2843/// Checks whether run time pointer checks are needed and builds sets for data 2844/// dependence checking. 2845class AccessAnalysis { 2846public: 2847 /// \brief Read or write access location. 2848 typedef std::pair<Value*, char> MemAccessInfo; 2849 2850 /// \brief Set of potential dependent memory accesses. 2851 typedef EquivalenceClasses<MemAccessInfo> DepCandidates; 2852 2853 AccessAnalysis(DataLayout *Dl, DepCandidates &DA) : 2854 DL(Dl), DepCands(DA), AreAllWritesIdentified(true), 2855 AreAllReadsIdentified(true), IsRTCheckNeeded(false) {} 2856 2857 /// \brief Register a load and whether it is only read from. 2858 void addLoad(Value *Ptr, bool IsReadOnly) { 2859 Accesses.insert(std::make_pair(Ptr, false)); 2860 if (IsReadOnly) 2861 ReadOnlyPtr.insert(Ptr); 2862 } 2863 2864 /// \brief Register a store. 2865 void addStore(Value *Ptr) { 2866 Accesses.insert(std::make_pair(Ptr, true)); 2867 } 2868 2869 /// \brief Check whether we can check the pointers at runtime for 2870 /// non-intersection. 2871 bool canCheckPtrAtRT(LoopVectorizationLegality::RuntimePointerCheck &RtCheck, 2872 unsigned &NumComparisons, ScalarEvolution *SE, 2873 Loop *TheLoop); 2874 2875 /// \brief Goes over all memory accesses, checks whether a RT check is needed 2876 /// and builds sets of dependent accesses. 2877 void buildDependenceSets() { 2878 // Process read-write pointers first. 2879 processMemAccesses(false); 2880 // Next, process read pointers. 2881 processMemAccesses(true); 2882 } 2883 2884 bool isRTCheckNeeded() { return IsRTCheckNeeded; } 2885 2886 bool isDependencyCheckNeeded() { return !CheckDeps.empty(); } 2887 2888 DenseSet<MemAccessInfo> &getDependenciesToCheck() { return CheckDeps; } 2889 2890private: 2891 typedef DenseSet<MemAccessInfo> PtrAccessSet; 2892 typedef DenseMap<Value*, MemAccessInfo> UnderlyingObjToAccessMap; 2893 2894 /// \brief Go over all memory access or only the deferred ones if 2895 /// \p UseDeferred is true and check whether runtime pointer checks are needed 2896 /// and build sets of dependency check candidates. 2897 void processMemAccesses(bool UseDeferred); 2898 2899 /// Set of all accesses. 2900 PtrAccessSet Accesses; 2901 2902 /// Set of access to check after all writes have been processed. 2903 PtrAccessSet DeferredAccesses; 2904 2905 /// Map of pointers to last access encountered. 2906 UnderlyingObjToAccessMap ObjToLastAccess; 2907 2908 /// Set of accesses that need a further dependence check. 2909 DenseSet<MemAccessInfo> CheckDeps; 2910 2911 /// Set of pointers that are read only. 2912 SmallPtrSet<Value*, 16> ReadOnlyPtr; 2913 2914 /// Set of underlying objects already written to. 2915 SmallPtrSet<Value*, 16> WriteObjects; 2916 2917 DataLayout *DL; 2918 2919 /// Sets of potentially dependent accesses - members of one set share an 2920 /// underlying pointer. The set "CheckDeps" identfies which sets really need a 2921 /// dependence check. 2922 DepCandidates &DepCands; 2923 2924 bool AreAllWritesIdentified; 2925 bool AreAllReadsIdentified; 2926 bool IsRTCheckNeeded; 2927}; 2928 2929/// \brief Check whether a pointer can participate in a runtime bounds check. 2930static bool hasComputableBounds(ScalarEvolution *SE, Value *Ptr) { 2931 const SCEV *PtrScev = SE->getSCEV(Ptr); 2932 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PtrScev); 2933 if (!AR) 2934 return false; 2935 2936 return AR->isAffine(); 2937} 2938 2939bool AccessAnalysis::canCheckPtrAtRT( 2940 LoopVectorizationLegality::RuntimePointerCheck &RtCheck, 2941 unsigned &NumComparisons, ScalarEvolution *SE, 2942 Loop *TheLoop) { 2943 // Find pointers with computable bounds. We are going to use this information 2944 // to place a runtime bound check. 2945 unsigned NumReadPtrChecks = 0; 2946 unsigned NumWritePtrChecks = 0; 2947 bool CanDoRT = true; 2948 2949 bool IsDepCheckNeeded = isDependencyCheckNeeded(); 2950 // We assign consecutive id to access from different dependence sets. 2951 // Accesses within the same set don't need a runtime check. 2952 unsigned RunningDepId = 1; 2953 DenseMap<Value *, unsigned> DepSetId; 2954 2955 for (PtrAccessSet::iterator AI = Accesses.begin(), AE = Accesses.end(); 2956 AI != AE; ++AI) { 2957 const MemAccessInfo &Access = *AI; 2958 Value *Ptr = Access.first; 2959 bool IsWrite = Access.second; 2960 2961 // Just add write checks if we have both. 2962 if (!IsWrite && Accesses.count(std::make_pair(Ptr, true))) 2963 continue; 2964 2965 if (IsWrite) 2966 ++NumWritePtrChecks; 2967 else 2968 ++NumReadPtrChecks; 2969 2970 if (hasComputableBounds(SE, Ptr)) { 2971 // The id of the dependence set. 2972 unsigned DepId; 2973 2974 if (IsDepCheckNeeded) { 2975 Value *Leader = DepCands.getLeaderValue(Access).first; 2976 unsigned &LeaderId = DepSetId[Leader]; 2977 if (!LeaderId) 2978 LeaderId = RunningDepId++; 2979 DepId = LeaderId; 2980 } else 2981 // Each access has its own dependence set. 2982 DepId = RunningDepId++; 2983 2984 //RtCheck.insert(SE, TheLoop, Ptr, IsWrite, DepId); 2985 2986 DEBUG(dbgs() << "LV: Found a runtime check ptr:" << *Ptr <<"\n"); 2987 } else { 2988 CanDoRT = false; 2989 } 2990 } 2991 2992 if (IsDepCheckNeeded && CanDoRT && RunningDepId == 2) 2993 NumComparisons = 0; // Only one dependence set. 2994 else 2995 NumComparisons = (NumWritePtrChecks * (NumReadPtrChecks + 2996 NumWritePtrChecks - 1)); 2997 return CanDoRT; 2998} 2999 3000static bool isFunctionScopeIdentifiedObject(Value *Ptr) { 3001 return isNoAliasArgument(Ptr) || isNoAliasCall(Ptr) || isa<AllocaInst>(Ptr); 3002} 3003 3004void AccessAnalysis::processMemAccesses(bool UseDeferred) { 3005 // We process the set twice: first we process read-write pointers, last we 3006 // process read-only pointers. This allows us to skip dependence tests for 3007 // read-only pointers. 3008 3009 PtrAccessSet &S = UseDeferred ? DeferredAccesses : Accesses; 3010 for (PtrAccessSet::iterator AI = S.begin(), AE = S.end(); AI != AE; ++AI) { 3011 const MemAccessInfo &Access = *AI; 3012 Value *Ptr = Access.first; 3013 bool IsWrite = Access.second; 3014 3015 DepCands.insert(Access); 3016 3017 // Memorize read-only pointers for later processing and skip them in the 3018 // first round (they need to be checked after we have seen all write 3019 // pointers). Note: we also mark pointer that are not consecutive as 3020 // "read-only" pointers (so that we check "a[b[i]] +="). Hence, we need the 3021 // second check for "!IsWrite". 3022 bool IsReadOnlyPtr = ReadOnlyPtr.count(Ptr) && !IsWrite; 3023 if (!UseDeferred && IsReadOnlyPtr) { 3024 DeferredAccesses.insert(Access); 3025 continue; 3026 } 3027 3028 bool NeedDepCheck = false; 3029 // Check whether there is the possiblity of dependency because of underlying 3030 // objects being the same. 3031 typedef SmallVector<Value*, 16> ValueVector; 3032 ValueVector TempObjects; 3033 GetUnderlyingObjects(Ptr, TempObjects, DL); 3034 for (ValueVector::iterator UI = TempObjects.begin(), UE = TempObjects.end(); 3035 UI != UE; ++UI) { 3036 Value *UnderlyingObj = *UI; 3037 3038 // If this is a write then it needs to be an identified object. If this a 3039 // read and all writes (so far) are identified function scope objects we 3040 // don't need an identified underlying object but only an Argument (the 3041 // next write is going to invalidate this assumption if it is 3042 // unidentified). 3043 // This is a micro-optimization for the case where all writes are 3044 // identified and we have one argument pointer. 3045 // Otherwise, we do need a runtime check. 3046 if ((IsWrite && !isFunctionScopeIdentifiedObject(UnderlyingObj)) || 3047 (!IsWrite && (!AreAllWritesIdentified || 3048 !isa<Argument>(UnderlyingObj)) && 3049 !isIdentifiedObject(UnderlyingObj))) { 3050 DEBUG(dbgs() << "LV: Found an unidentified " << 3051 (IsWrite ? "write" : "read" ) << " ptr:" << *UnderlyingObj << 3052 "\n"); 3053 IsRTCheckNeeded = (IsRTCheckNeeded || 3054 !isIdentifiedObject(UnderlyingObj) || 3055 !AreAllReadsIdentified); 3056 3057 if (IsWrite) 3058 AreAllWritesIdentified = false; 3059 if (!IsWrite) 3060 AreAllReadsIdentified = false; 3061 } 3062 3063 // If this is a write - check other reads and writes for conflicts. If 3064 // this is a read only check other writes for conflicts (but only if there 3065 // is no other write to the ptr - this is an optimization to catch "a[i] = 3066 // a[i] + " without having to do a dependence check). 3067 if ((IsWrite || IsReadOnlyPtr) && WriteObjects.count(UnderlyingObj)) 3068 NeedDepCheck = true; 3069 3070 if (IsWrite) 3071 WriteObjects.insert(UnderlyingObj); 3072 3073 // Create sets of pointers connected by shared underlying objects. 3074 UnderlyingObjToAccessMap::iterator Prev = 3075 ObjToLastAccess.find(UnderlyingObj); 3076 if (Prev != ObjToLastAccess.end()) 3077 DepCands.unionSets(Access, Prev->second); 3078 3079 ObjToLastAccess[UnderlyingObj] = Access; 3080 } 3081 3082 if (NeedDepCheck) 3083 CheckDeps.insert(Access); 3084 } 3085} 3086 3087/// \brief Checks memory dependences among accesses to the same underlying 3088/// object to determine whether there vectorization is legal or not (and at 3089/// which vectorization factor). 3090/// 3091/// This class works under the assumption that we already checked that memory 3092/// locations with different underlying pointers are "must-not alias". 3093/// We use the ScalarEvolution framework to symbolically evalutate access 3094/// functions pairs. Since we currently don't restructure the loop we can rely 3095/// on the program order of memory accesses to determine their safety. 3096/// At the moment we will only deem accesses as safe for: 3097/// * A negative constant distance assuming program order. 3098/// 3099/// Safe: tmp = a[i + 1]; OR a[i + 1] = x; 3100/// a[i] = tmp; y = a[i]; 3101/// 3102/// The latter case is safe because later checks guarantuee that there can't 3103/// be a cycle through a phi node (that is, we check that "x" and "y" is not 3104/// the same variable: a header phi can only be an induction or a reduction, a 3105/// reduction can't have a memory sink, an induction can't have a memory 3106/// source). This is important and must not be violated (or we have to 3107/// resort to checking for cycles through memory). 3108/// 3109/// * A positive constant distance assuming program order that is bigger 3110/// than the biggest memory access. 3111/// 3112/// tmp = a[i] OR b[i] = x 3113/// a[i+2] = tmp y = b[i+2]; 3114/// 3115/// Safe distance: 2 x sizeof(a[0]), and 2 x sizeof(b[0]), respectively. 3116/// 3117/// * Zero distances and all accesses have the same size. 3118/// 3119class MemoryDepChecker { 3120public: 3121 typedef std::pair<Value*, char> MemAccessInfo; 3122 3123 MemoryDepChecker(ScalarEvolution *Se, DataLayout *Dl, const Loop *L) : 3124 SE(Se), DL(Dl), InnermostLoop(L), AccessIdx(0) {} 3125 3126 /// \brief Register the location (instructions are given increasing numbers) 3127 /// of a write access. 3128 void addAccess(StoreInst *SI) { 3129 Value *Ptr = SI->getPointerOperand(); 3130 Accesses[std::make_pair(Ptr, true)].push_back(AccessIdx); 3131 InstMap.push_back(SI); 3132 ++AccessIdx; 3133 } 3134 3135 /// \brief Register the location (instructions are given increasing numbers) 3136 /// of a write access. 3137 void addAccess(LoadInst *LI) { 3138 Value *Ptr = LI->getPointerOperand(); 3139 Accesses[std::make_pair(Ptr, false)].push_back(AccessIdx); 3140 InstMap.push_back(LI); 3141 ++AccessIdx; 3142 } 3143 3144 /// \brief Check whether the dependencies between the accesses are safe. 3145 /// 3146 /// Only checks sets with elements in \p CheckDeps. 3147 bool areDepsSafe(AccessAnalysis::DepCandidates &AccessSets, 3148 DenseSet<MemAccessInfo> &CheckDeps); 3149 3150 /// \brief The maximum number of bytes of a vector register we can vectorize 3151 /// the accesses safely with. 3152 unsigned getMaxSafeDepDistBytes() { return MaxSafeDepDistBytes; } 3153 3154private: 3155 ScalarEvolution *SE; 3156 DataLayout *DL; 3157 const Loop *InnermostLoop; 3158 3159 /// \brief Maps access locations (ptr, read/write) to program order. 3160 DenseMap<MemAccessInfo, std::vector<unsigned> > Accesses; 3161 3162 /// \brief Memory access instructions in program order. 3163 SmallVector<Instruction *, 16> InstMap; 3164 3165 /// \brief The program order index to be used for the next instruction. 3166 unsigned AccessIdx; 3167 3168 // We can access this many bytes in parallel safely. 3169 unsigned MaxSafeDepDistBytes; 3170 3171 /// \brief Check whether there is a plausible dependence between the two 3172 /// accesses. 3173 /// 3174 /// Access \p A must happen before \p B in program order. The two indices 3175 /// identify the index into the program order map. 3176 /// 3177 /// This function checks whether there is a plausible dependence (or the 3178 /// absence of such can't be proved) between the two accesses. If there is a 3179 /// plausible dependence but the dependence distance is bigger than one 3180 /// element access it records this distance in \p MaxSafeDepDistBytes (if this 3181 /// distance is smaller than any other distance encountered so far). 3182 /// Otherwise, this function returns true signaling a possible dependence. 3183 bool isDependent(const MemAccessInfo &A, unsigned AIdx, 3184 const MemAccessInfo &B, unsigned BIdx); 3185 3186 /// \brief Check whether the data dependence could prevent store-load 3187 /// forwarding. 3188 bool couldPreventStoreLoadForward(unsigned Distance, unsigned TypeByteSize); 3189}; 3190 3191static bool isInBoundsGep(Value *Ptr) { 3192 if (GetElementPtrInst *GEP = dyn_cast<GetElementPtrInst>(Ptr)) 3193 return GEP->isInBounds(); 3194 return false; 3195} 3196 3197/// \brief Check whether the access through \p Ptr has a constant stride. 3198static int isStridedPtr(ScalarEvolution *SE, DataLayout *DL, Value *Ptr, 3199 const Loop *Lp) { 3200 const Type *PtrTy = Ptr->getType(); 3201 assert(PtrTy->isPointerTy() && "Unexpected non ptr"); 3202 3203 // Make sure that the pointer does not point to aggregate types. 3204 if (cast<PointerType>(Ptr->getType())->getElementType()->isAggregateType()) { 3205 DEBUG(dbgs() << "LV: Bad stride - Not a pointer to a scalar type" << *Ptr 3206 << "\n"); 3207 return 0; 3208 } 3209 3210 const SCEV *PtrScev = SE->getSCEV(Ptr); 3211 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PtrScev); 3212 if (!AR) { 3213 DEBUG(dbgs() << "LV: Bad stride - Not an AddRecExpr pointer " 3214 << *Ptr << " SCEV: " << *PtrScev << "\n"); 3215 return 0; 3216 } 3217 3218 // The accesss function must stride over the innermost loop. 3219 if (Lp != AR->getLoop()) { 3220 DEBUG(dbgs() << "LV: Bad stride - Not striding over innermost loop " << *Ptr 3221 << " SCEV: " << *PtrScev << "\n"); 3222 } 3223 3224 // The address calculation must not wrap. Otherwise, a dependence could be 3225 // inverted. An inbounds getelementptr that is a AddRec with a unit stride 3226 // cannot wrap per definition. The unit stride requirement is checked later. 3227 bool IsInBoundsGEP = isInBoundsGep(Ptr); 3228 bool IsNoWrapAddRec = AR->getNoWrapFlags(SCEV::NoWrapMask); 3229 if (!IsNoWrapAddRec && !IsInBoundsGEP) { 3230 DEBUG(dbgs() << "LV: Bad stride - Pointer may wrap in the address space " 3231 << *Ptr << " SCEV: " << *PtrScev << "\n"); 3232 return 0; 3233 } 3234 3235 // Check the step is constant. 3236 const SCEV *Step = AR->getStepRecurrence(*SE); 3237 3238 // Calculate the pointer stride and check if it is consecutive. 3239 const SCEVConstant *C = dyn_cast<SCEVConstant>(Step); 3240 if (!C) { 3241 DEBUG(dbgs() << "LV: Bad stride - Not a constant strided " << *Ptr << 3242 " SCEV: " << *PtrScev << "\n"); 3243 return 0; 3244 } 3245 3246 int64_t Size = DL->getTypeAllocSize(PtrTy->getPointerElementType()); 3247 const APInt &APStepVal = C->getValue()->getValue(); 3248 3249 // Huge step value - give up. 3250 if (APStepVal.getBitWidth() > 64) 3251 return 0; 3252 3253 int64_t StepVal = APStepVal.getSExtValue(); 3254 3255 // Strided access. 3256 int64_t Stride = StepVal / Size; 3257 int64_t Rem = StepVal % Size; 3258 if (Rem) 3259 return 0; 3260 3261 // If the SCEV could wrap but we have an inbounds gep with a unit stride we 3262 // know we can't "wrap around the address space". 3263 if (!IsNoWrapAddRec && IsInBoundsGEP && Stride != 1 && Stride != -1) 3264 return 0; 3265 3266 return Stride; 3267} 3268 3269bool MemoryDepChecker::couldPreventStoreLoadForward(unsigned Distance, 3270 unsigned TypeByteSize) { 3271 // If loads occur at a distance that is not a multiple of a feasible vector 3272 // factor store-load forwarding does not take place. 3273 // Positive dependences might cause troubles because vectorizing them might 3274 // prevent store-load forwarding making vectorized code run a lot slower. 3275 // a[i] = a[i-3] ^ a[i-8]; 3276 // The stores to a[i:i+1] don't align with the stores to a[i-3:i-2] and 3277 // hence on your typical architecture store-load forwarding does not take 3278 // place. Vectorizing in such cases does not make sense. 3279 // Store-load forwarding distance. 3280 const unsigned NumCyclesForStoreLoadThroughMemory = 8*TypeByteSize; 3281 // Maximum vector factor. 3282 unsigned MaxVFWithoutSLForwardIssues = MaxVectorWidth*TypeByteSize; 3283 if(MaxSafeDepDistBytes < MaxVFWithoutSLForwardIssues) 3284 MaxVFWithoutSLForwardIssues = MaxSafeDepDistBytes; 3285 3286 for (unsigned vf = 2*TypeByteSize; vf <= MaxVFWithoutSLForwardIssues; 3287 vf *= 2) { 3288 if (Distance % vf && Distance / vf < NumCyclesForStoreLoadThroughMemory) { 3289 MaxVFWithoutSLForwardIssues = (vf >>=1); 3290 break; 3291 } 3292 } 3293 3294 if (MaxVFWithoutSLForwardIssues< 2*TypeByteSize) { 3295 DEBUG(dbgs() << "LV: Distance " << Distance << 3296 " that could cause a store-load forwarding conflict\n"); 3297 return true; 3298 } 3299 3300 if (MaxVFWithoutSLForwardIssues < MaxSafeDepDistBytes && 3301 MaxVFWithoutSLForwardIssues != MaxVectorWidth*TypeByteSize) 3302 MaxSafeDepDistBytes = MaxVFWithoutSLForwardIssues; 3303 return false; 3304} 3305 3306bool MemoryDepChecker::isDependent(const MemAccessInfo &A, unsigned AIdx, 3307 const MemAccessInfo &B, unsigned BIdx) { 3308 assert (AIdx < BIdx && "Must pass arguments in program order"); 3309 3310 Value *APtr = A.first; 3311 Value *BPtr = B.first; 3312 bool AIsWrite = A.second; 3313 bool BIsWrite = B.second; 3314 3315 // Two reads are independent. 3316 if (!AIsWrite && !BIsWrite) 3317 return false; 3318 3319 const SCEV *AScev = SE->getSCEV(APtr); 3320 const SCEV *BScev = SE->getSCEV(BPtr); 3321 3322 int StrideAPtr = isStridedPtr(SE, DL, APtr, InnermostLoop); 3323 int StrideBPtr = isStridedPtr(SE, DL, BPtr, InnermostLoop); 3324 3325 const SCEV *Src = AScev; 3326 const SCEV *Sink = BScev; 3327 3328 // If the induction step is negative we have to invert source and sink of the 3329 // dependence. 3330 if (StrideAPtr < 0) { 3331 //Src = BScev; 3332 //Sink = AScev; 3333 std::swap(APtr, BPtr); 3334 std::swap(Src, Sink); 3335 std::swap(AIsWrite, BIsWrite); 3336 std::swap(AIdx, BIdx); 3337 std::swap(StrideAPtr, StrideBPtr); 3338 } 3339 3340 const SCEV *Dist = SE->getMinusSCEV(Sink, Src); 3341 3342 DEBUG(dbgs() << "LV: Src Scev: " << *Src << "Sink Scev: " << *Sink 3343 << "(Induction step: " << StrideAPtr << ")\n"); 3344 DEBUG(dbgs() << "LV: Distance for " << *InstMap[AIdx] << " to " 3345 << *InstMap[BIdx] << ": " << *Dist << "\n"); 3346 3347 // Need consecutive accesses. We don't want to vectorize 3348 // "A[B[i]] += ..." and similar code or pointer arithmetic that could wrap in 3349 // the address space. 3350 if (!StrideAPtr || !StrideBPtr || StrideAPtr != StrideBPtr){ 3351 DEBUG(dbgs() << "Non-consecutive pointer access\n"); 3352 return true; 3353 } 3354 3355 const SCEVConstant *C = dyn_cast<SCEVConstant>(Dist); 3356 if (!C) { 3357 DEBUG(dbgs() << "LV: Dependence because of non constant distance\n"); 3358 return true; 3359 } 3360 3361 Type *ATy = APtr->getType()->getPointerElementType(); 3362 Type *BTy = BPtr->getType()->getPointerElementType(); 3363 unsigned TypeByteSize = DL->getTypeAllocSize(ATy); 3364 3365 // Negative distances are not plausible dependencies. 3366 const APInt &Val = C->getValue()->getValue(); 3367 if (Val.isNegative()) { 3368 bool IsTrueDataDependence = (AIsWrite && !BIsWrite); 3369 if (IsTrueDataDependence && 3370 (couldPreventStoreLoadForward(Val.abs().getZExtValue(), TypeByteSize) || 3371 ATy != BTy)) 3372 return true; 3373 3374 DEBUG(dbgs() << "LV: Dependence is negative: NoDep\n"); 3375 return false; 3376 } 3377 3378 // Write to the same location with the same size. 3379 // Could be improved to assert type sizes are the same (i32 == float, etc). 3380 if (Val == 0) { 3381 if (ATy == BTy) 3382 return false; 3383 DEBUG(dbgs() << "LV: Zero dependence difference but different types"); 3384 return true; 3385 } 3386 3387 assert(Val.isStrictlyPositive() && "Expect a positive value"); 3388 3389 // Positive distance bigger than max vectorization factor. 3390 if (ATy != BTy) { 3391 DEBUG(dbgs() << 3392 "LV: ReadWrite-Write positive dependency with different types"); 3393 return false; 3394 } 3395 3396 unsigned Distance = (unsigned) Val.getZExtValue(); 3397 3398 // Bail out early if passed-in parameters make vectorization not feasible. 3399 unsigned ForcedFactor = VectorizationFactor ? VectorizationFactor : 1; 3400 unsigned ForcedUnroll = VectorizationUnroll ? VectorizationUnroll : 1; 3401 3402 // The distance must be bigger than the size needed for a vectorized version 3403 // of the operation and the size of the vectorized operation must not be 3404 // bigger than the currrent maximum size. 3405 if (Distance < 2*TypeByteSize || 3406 2*TypeByteSize > MaxSafeDepDistBytes || 3407 Distance < TypeByteSize * ForcedUnroll * ForcedFactor) { 3408 DEBUG(dbgs() << "LV: Failure because of Positive distance " 3409 << Val.getSExtValue() << "\n"); 3410 return true; 3411 } 3412 3413 MaxSafeDepDistBytes = Distance < MaxSafeDepDistBytes ? 3414 Distance : MaxSafeDepDistBytes; 3415 3416 bool IsTrueDataDependence = (!AIsWrite && BIsWrite); 3417 if (IsTrueDataDependence && 3418 couldPreventStoreLoadForward(Distance, TypeByteSize)) 3419 return true; 3420 3421 DEBUG(dbgs() << "LV: Positive distance " << Val.getSExtValue() << 3422 " with max VF=" << MaxSafeDepDistBytes/TypeByteSize << "\n"); 3423 3424 return false; 3425} 3426 3427bool 3428MemoryDepChecker::areDepsSafe(AccessAnalysis::DepCandidates &AccessSets, 3429 DenseSet<MemAccessInfo> &CheckDeps) { 3430 3431 MaxSafeDepDistBytes = -1U; 3432 while (!CheckDeps.empty()) { 3433 MemAccessInfo CurAccess = *CheckDeps.begin(); 3434 3435 // Get the relevant memory access set. 3436 EquivalenceClasses<MemAccessInfo>::iterator I = 3437 AccessSets.findValue(AccessSets.getLeaderValue(CurAccess)); 3438 3439 // Check accesses within this set. 3440 EquivalenceClasses<MemAccessInfo>::member_iterator AI, AE; 3441 AI = AccessSets.member_begin(I), AE = AccessSets.member_end(); 3442 3443 // Check every access pair. 3444 while (AI != AE) { 3445 CheckDeps.erase(*AI); 3446 EquivalenceClasses<MemAccessInfo>::member_iterator OI = llvm::next(AI); 3447 while (OI != AE) { 3448 // Check every accessing instruction pair in program order. 3449 for (std::vector<unsigned>::iterator I1 = Accesses[*AI].begin(), 3450 I1E = Accesses[*AI].end(); I1 != I1E; ++I1) 3451 for (std::vector<unsigned>::iterator I2 = Accesses[*OI].begin(), 3452 I2E = Accesses[*OI].end(); I2 != I2E; ++I2) { 3453 if (*I1 < *I2 && isDependent(*AI, *I1, *OI, *I2)) 3454 return false; 3455 if (*I2 < *I1 && isDependent(*OI, *I2, *AI, *I1)) 3456 return false; 3457 } 3458 ++OI; 3459 } 3460 AI++; 3461 } 3462 } 3463 return true; 3464} 3465 3466AliasAnalysis::Location 3467LoopVectorizationLegality::getLoadStoreLocation(Instruction *Inst) { 3468 if (StoreInst *Store = dyn_cast<StoreInst>(Inst)) 3469 return AA->getLocation(Store); 3470 else if (LoadInst *Load = dyn_cast<LoadInst>(Inst)) 3471 return AA->getLocation(Load); 3472 3473 llvm_unreachable("Should be either load or store instruction"); 3474} 3475 3476bool 3477LoopVectorizationLegality::hasPossibleGlobalWriteReorder( 3478 Value *Object, 3479 Instruction *Inst, 3480 AliasMultiMap& WriteObjects, 3481 unsigned MaxByteWidth) { 3482 3483 AliasAnalysis::Location ThisLoc = getLoadStoreLocation(Inst); 3484 3485 std::vector<Instruction*>::iterator 3486 it = WriteObjects[Object].begin(), 3487 end = WriteObjects[Object].end(); 3488 3489 for (; it != end; ++it) { 3490 Instruction* I = *it; 3491 if (I == Inst) 3492 continue; 3493 3494 AliasAnalysis::Location ThatLoc = getLoadStoreLocation(I); 3495 if (AA->alias(ThisLoc.getWithNewSize(MaxByteWidth), 3496 ThatLoc.getWithNewSize(MaxByteWidth))) 3497 return true; 3498 } 3499 return false; 3500} 3501 3502bool LoopVectorizationLegality::canVectorizeMemory() { 3503 3504 typedef SmallVector<Value*, 16> ValueVector; 3505 typedef SmallPtrSet<Value*, 16> ValueSet; 3506 // Holds the Load and Store *instructions*. 3507 ValueVector Loads; 3508 ValueVector Stores; 3509 PtrRtCheck.Pointers.clear(); 3510 PtrRtCheck.Need = false; 3511 3512 const bool IsAnnotatedParallel = TheLoop->isAnnotatedParallel(); 3513 3514 // For each block. 3515 for (Loop::block_iterator bb = TheLoop->block_begin(), 3516 be = TheLoop->block_end(); bb != be; ++bb) { 3517 3518 // Scan the BB and collect legal loads and stores. 3519 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e; 3520 ++it) { 3521 3522 // If this is a load, save it. If this instruction can read from memory 3523 // but is not a load, then we quit. Notice that we don't handle function 3524 // calls that read or write. 3525 if (it->mayReadFromMemory()) { 3526 LoadInst *Ld = dyn_cast<LoadInst>(it); 3527 if (!Ld) return false; 3528 if (!Ld->isSimple() && !IsAnnotatedParallel) { 3529 DEBUG(dbgs() << "LV: Found a non-simple load.\n"); 3530 return false; 3531 } 3532 Loads.push_back(Ld); 3533 continue; 3534 } 3535 3536 // Save 'store' instructions. Abort if other instructions write to memory. 3537 if (it->mayWriteToMemory()) { 3538 StoreInst *St = dyn_cast<StoreInst>(it); 3539 if (!St) return false; 3540 if (!St->isSimple() && !IsAnnotatedParallel) { 3541 DEBUG(dbgs() << "LV: Found a non-simple store.\n"); 3542 return false; 3543 } 3544 Stores.push_back(St); 3545 } 3546 } // next instr. 3547 } // next block. 3548 3549 // Now we have two lists that hold the loads and the stores. 3550 // Next, we find the pointers that they use. 3551 3552 // Check if we see any stores. If there are no stores, then we don't 3553 // care if the pointers are *restrict*. 3554 if (!Stores.size()) { 3555 DEBUG(dbgs() << "LV: Found a read-only loop!\n"); 3556 return true; 3557 } 3558 3559 // Holds the read and read-write *pointers* that we find. These maps hold 3560 // unique values for pointers (so no need for multi-map). 3561 AliasMap Reads; 3562 AliasMap ReadWrites; 3563 3564 // Holds the analyzed pointers. We don't want to call GetUnderlyingObjects 3565 // multiple times on the same object. If the ptr is accessed twice, once 3566 // for read and once for write, it will only appear once (on the write 3567 // list). This is okay, since we are going to check for conflicts between 3568 // writes and between reads and writes, but not between reads and reads. 3569 ValueSet Seen; 3570 3571 ValueVector::iterator I, IE; 3572 for (I = Stores.begin(), IE = Stores.end(); I != IE; ++I) { 3573 StoreInst *ST = cast<StoreInst>(*I); 3574 Value* Ptr = ST->getPointerOperand(); 3575 3576 if (isUniform(Ptr)) { 3577 DEBUG(dbgs() << "LV: We don't allow storing to uniform addresses\n"); 3578 return false; 3579 } 3580 3581 // If we did *not* see this pointer before, insert it to 3582 // the read-write list. At this phase it is only a 'write' list. 3583 if (Seen.insert(Ptr)) 3584 ReadWrites.insert(std::make_pair(Ptr, ST)); 3585 } 3586 3587 if (IsAnnotatedParallel) { 3588 DEBUG(dbgs() 3589 << "LV: A loop annotated parallel, ignore memory dependency " 3590 << "checks.\n"); 3591 return true; 3592 } 3593 3594 for (I = Loads.begin(), IE = Loads.end(); I != IE; ++I) { 3595 LoadInst *LD = cast<LoadInst>(*I); 3596 Value* Ptr = LD->getPointerOperand(); 3597 // If we did *not* see this pointer before, insert it to the 3598 // read list. If we *did* see it before, then it is already in 3599 // the read-write list. This allows us to vectorize expressions 3600 // such as A[i] += x; Because the address of A[i] is a read-write 3601 // pointer. This only works if the index of A[i] is consecutive. 3602 // If the address of i is unknown (for example A[B[i]]) then we may 3603 // read a few words, modify, and write a few words, and some of the 3604 // words may be written to the same address. 3605 if (Seen.insert(Ptr) || 0 == isConsecutivePtr(Ptr)) 3606 Reads.insert(std::make_pair(Ptr, LD)); 3607 } 3608 3609 // If we write (or read-write) to a single destination and there are no 3610 // other reads in this loop then is it safe to vectorize. 3611 if (ReadWrites.size() == 1 && Reads.size() == 0) { 3612 DEBUG(dbgs() << "LV: Found a write-only loop!\n"); 3613 return true; 3614 } 3615 3616 unsigned NumReadPtrs = 0; 3617 unsigned NumWritePtrs = 0; 3618 3619 // Find pointers with computable bounds. We are going to use this information 3620 // to place a runtime bound check. 3621 bool CanDoRT = true; 3622 AliasMap::iterator MI, ME; 3623 for (MI = ReadWrites.begin(), ME = ReadWrites.end(); MI != ME; ++MI) { 3624 Value *V = (*MI).first; 3625 if (hasComputableBounds(V)) { 3626 PtrRtCheck.insert(SE, TheLoop, V, true); 3627 NumWritePtrs++; 3628 DEBUG(dbgs() << "LV: Found a runtime check ptr:" << *V <<"\n"); 3629 } else { 3630 CanDoRT = false; 3631 break; 3632 } 3633 } 3634 for (MI = Reads.begin(), ME = Reads.end(); MI != ME; ++MI) { 3635 Value *V = (*MI).first; 3636 if (hasComputableBounds(V)) { 3637 PtrRtCheck.insert(SE, TheLoop, V, false); 3638 NumReadPtrs++; 3639 DEBUG(dbgs() << "LV: Found a runtime check ptr:" << *V <<"\n"); 3640 } else { 3641 CanDoRT = false; 3642 break; 3643 } 3644 } 3645 3646 // Check that we did not collect too many pointers or found a 3647 // unsizeable pointer. 3648 unsigned NumComparisons = (NumWritePtrs * (NumReadPtrs + NumWritePtrs - 1)); 3649 DEBUG(dbgs() << "LV: We need to compare " << NumComparisons << " ptrs.\n"); 3650 if (!CanDoRT || NumComparisons > RuntimeMemoryCheckThreshold) { 3651 PtrRtCheck.reset(); 3652 CanDoRT = false; 3653 } 3654 3655 if (CanDoRT) { 3656 DEBUG(dbgs() << "LV: We can perform a memory runtime check if needed.\n"); 3657 } 3658 3659 bool NeedRTCheck = false; 3660 3661 // Biggest vectorized access possible, vector width * unroll factor. 3662 // TODO: We're being very pessimistic here, find a way to know the 3663 // real access width before getting here. 3664 unsigned MaxByteWidth = (TTI->getRegisterBitWidth(true) / 8) * 3665 TTI->getMaximumUnrollFactor(); 3666 // Now that the pointers are in two lists (Reads and ReadWrites), we 3667 // can check that there are no conflicts between each of the writes and 3668 // between the writes to the reads. 3669 // Note that WriteObjects duplicates the stores (indexed now by underlying 3670 // objects) to avoid pointing to elements inside ReadWrites. 3671 // TODO: Maybe create a new type where they can interact without duplication. 3672 AliasMultiMap WriteObjects; 3673 ValueVector TempObjects; 3674 3675 // Check that the read-writes do not conflict with other read-write 3676 // pointers. 3677 bool AllWritesIdentified = true; 3678 for (MI = ReadWrites.begin(), ME = ReadWrites.end(); MI != ME; ++MI) { 3679 Value *Val = (*MI).first; 3680 Instruction *Inst = (*MI).second; 3681 3682 GetUnderlyingObjects(Val, TempObjects, DL); 3683 for (ValueVector::iterator UI=TempObjects.begin(), UE=TempObjects.end(); 3684 UI != UE; ++UI) { 3685 if (!isIdentifiedObject(*UI)) { 3686 DEBUG(dbgs() << "LV: Found an unidentified write ptr:"<< **UI <<"\n"); 3687 NeedRTCheck = true; 3688 AllWritesIdentified = false; 3689 } 3690 3691 // Never seen it before, can't alias. 3692 if (WriteObjects[*UI].empty()) { 3693 DEBUG(dbgs() << "LV: Adding Underlying value:" << **UI <<"\n"); 3694 WriteObjects[*UI].push_back(Inst); 3695 continue; 3696 } 3697 // Direct alias found. 3698 if (!AA || dyn_cast<GlobalValue>(*UI) == NULL) { 3699 DEBUG(dbgs() << "LV: Found a possible write-write reorder:" 3700 << **UI <<"\n"); 3701 return false; 3702 } 3703 DEBUG(dbgs() << "LV: Found a conflicting global value:" 3704 << **UI <<"\n"); 3705 DEBUG(dbgs() << "LV: While examining store:" << *Inst <<"\n"); 3706 DEBUG(dbgs() << "LV: On value:" << *Val <<"\n"); 3707 3708 // If global alias, make sure they do alias. 3709 if (hasPossibleGlobalWriteReorder(*UI, 3710 Inst, 3711 WriteObjects, 3712 MaxByteWidth)) { 3713 DEBUG(dbgs() << "LV: Found a possible write-write reorder:" << **UI 3714 << "\n"); 3715 return false; 3716 } 3717 3718 // Didn't alias, insert into map for further reference. 3719 WriteObjects[*UI].push_back(Inst); 3720 } 3721 TempObjects.clear(); 3722 } 3723 3724 /// Check that the reads don't conflict with the read-writes. 3725 for (MI = Reads.begin(), ME = Reads.end(); MI != ME; ++MI) { 3726 Value *Val = (*MI).first; 3727 GetUnderlyingObjects(Val, TempObjects, DL); 3728 for (ValueVector::iterator UI=TempObjects.begin(), UE=TempObjects.end(); 3729 UI != UE; ++UI) { 3730 // If all of the writes are identified then we don't care if the read 3731 // pointer is identified or not. 3732 if (!AllWritesIdentified && !isIdentifiedObject(*UI)) { 3733 DEBUG(dbgs() << "LV: Found an unidentified read ptr:"<< **UI <<"\n"); 3734 NeedRTCheck = true; 3735 } 3736 3737 // Never seen it before, can't alias. 3738 if (WriteObjects[*UI].empty()) 3739 continue; 3740 // Direct alias found. 3741 if (!AA || dyn_cast<GlobalValue>(*UI) == NULL) { 3742 DEBUG(dbgs() << "LV: Found a possible write-write reorder:" 3743 << **UI <<"\n"); 3744 return false; 3745 } 3746 DEBUG(dbgs() << "LV: Found a global value: " 3747 << **UI <<"\n"); 3748 Instruction *Inst = (*MI).second; 3749 DEBUG(dbgs() << "LV: While examining load:" << *Inst <<"\n"); 3750 DEBUG(dbgs() << "LV: On value:" << *Val <<"\n"); 3751 3752 // If global alias, make sure they do alias. 3753 if (hasPossibleGlobalWriteReorder(*UI, 3754 Inst, 3755 WriteObjects, 3756 MaxByteWidth)) { 3757 DEBUG(dbgs() << "LV: Found a possible read-write reorder:" << **UI 3758 << "\n"); 3759 return false; 3760 } 3761 } 3762 TempObjects.clear(); 3763 } 3764 3765 PtrRtCheck.Need = NeedRTCheck; 3766 if (NeedRTCheck && !CanDoRT) { 3767 DEBUG(dbgs() << "LV: We can't vectorize because we can't find " << 3768 "the array bounds.\n"); 3769 PtrRtCheck.reset(); 3770 return false; 3771 } 3772 3773 DEBUG(dbgs() << "LV: We "<< (NeedRTCheck ? "" : "don't") << 3774 " need a runtime memory check.\n"); 3775 return true; 3776} 3777 3778static bool hasMultipleUsesOf(Instruction *I, 3779 SmallPtrSet<Instruction *, 8> &Insts) { 3780 unsigned NumUses = 0; 3781 for(User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E; ++Use) { 3782 if (Insts.count(dyn_cast<Instruction>(*Use))) 3783 ++NumUses; 3784 if (NumUses > 1) 3785 return true; 3786 } 3787 3788 return false; 3789} 3790 3791static bool areAllUsesIn(Instruction *I, SmallPtrSet<Instruction *, 8> &Set) { 3792 for(User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E; ++Use) 3793 if (!Set.count(dyn_cast<Instruction>(*Use))) 3794 return false; 3795 return true; 3796} 3797 3798bool LoopVectorizationLegality::AddReductionVar(PHINode *Phi, 3799 ReductionKind Kind) { 3800 if (Phi->getNumIncomingValues() != 2) 3801 return false; 3802 3803 // Reduction variables are only found in the loop header block. 3804 if (Phi->getParent() != TheLoop->getHeader()) 3805 return false; 3806 3807 // Obtain the reduction start value from the value that comes from the loop 3808 // preheader. 3809 Value *RdxStart = Phi->getIncomingValueForBlock(TheLoop->getLoopPreheader()); 3810 3811 // ExitInstruction is the single value which is used outside the loop. 3812 // We only allow for a single reduction value to be used outside the loop. 3813 // This includes users of the reduction, variables (which form a cycle 3814 // which ends in the phi node). 3815 Instruction *ExitInstruction = 0; 3816 // Indicates that we found a reduction operation in our scan. 3817 bool FoundReduxOp = false; 3818 3819 // We start with the PHI node and scan for all of the users of this 3820 // instruction. All users must be instructions that can be used as reduction 3821 // variables (such as ADD). We must have a single out-of-block user. The cycle 3822 // must include the original PHI. 3823 bool FoundStartPHI = false; 3824 3825 // To recognize min/max patterns formed by a icmp select sequence, we store 3826 // the number of instruction we saw from the recognized min/max pattern, 3827 // to make sure we only see exactly the two instructions. 3828 unsigned NumCmpSelectPatternInst = 0; 3829 ReductionInstDesc ReduxDesc(false, 0); 3830 3831 SmallPtrSet<Instruction *, 8> VisitedInsts; 3832 SmallVector<Instruction *, 8> Worklist; 3833 Worklist.push_back(Phi); 3834 VisitedInsts.insert(Phi); 3835 3836 // A value in the reduction can be used: 3837 // - By the reduction: 3838 // - Reduction operation: 3839 // - One use of reduction value (safe). 3840 // - Multiple use of reduction value (not safe). 3841 // - PHI: 3842 // - All uses of the PHI must be the reduction (safe). 3843 // - Otherwise, not safe. 3844 // - By one instruction outside of the loop (safe). 3845 // - By further instructions outside of the loop (not safe). 3846 // - By an instruction that is not part of the reduction (not safe). 3847 // This is either: 3848 // * An instruction type other than PHI or the reduction operation. 3849 // * A PHI in the header other than the initial PHI. 3850 while (!Worklist.empty()) { 3851 Instruction *Cur = Worklist.back(); 3852 Worklist.pop_back(); 3853 3854 // No Users. 3855 // If the instruction has no users then this is a broken chain and can't be 3856 // a reduction variable. 3857 if (Cur->use_empty()) 3858 return false; 3859 3860 bool IsAPhi = isa<PHINode>(Cur); 3861 3862 // A header PHI use other than the original PHI. 3863 if (Cur != Phi && IsAPhi && Cur->getParent() == Phi->getParent()) 3864 return false; 3865 3866 // Reductions of instructions such as Div, and Sub is only possible if the 3867 // LHS is the reduction variable. 3868 if (!Cur->isCommutative() && !IsAPhi && !isa<SelectInst>(Cur) && 3869 !isa<ICmpInst>(Cur) && !isa<FCmpInst>(Cur) && 3870 !VisitedInsts.count(dyn_cast<Instruction>(Cur->getOperand(0)))) 3871 return false; 3872 3873 // Any reduction instruction must be of one of the allowed kinds. 3874 ReduxDesc = isReductionInstr(Cur, Kind, ReduxDesc); 3875 if (!ReduxDesc.IsReduction) 3876 return false; 3877 3878 // A reduction operation must only have one use of the reduction value. 3879 if (!IsAPhi && Kind != RK_IntegerMinMax && Kind != RK_FloatMinMax && 3880 hasMultipleUsesOf(Cur, VisitedInsts)) 3881 return false; 3882 3883 // All inputs to a PHI node must be a reduction value. 3884 if(IsAPhi && Cur != Phi && !areAllUsesIn(Cur, VisitedInsts)) 3885 return false; 3886 3887 if (Kind == RK_IntegerMinMax && (isa<ICmpInst>(Cur) || 3888 isa<SelectInst>(Cur))) 3889 ++NumCmpSelectPatternInst; 3890 if (Kind == RK_FloatMinMax && (isa<FCmpInst>(Cur) || 3891 isa<SelectInst>(Cur))) 3892 ++NumCmpSelectPatternInst; 3893 3894 // Check whether we found a reduction operator. 3895 FoundReduxOp |= !IsAPhi; 3896 3897 // Process users of current instruction. Push non PHI nodes after PHI nodes 3898 // onto the stack. This way we are going to have seen all inputs to PHI 3899 // nodes once we get to them. 3900 SmallVector<Instruction *, 8> NonPHIs; 3901 SmallVector<Instruction *, 8> PHIs; 3902 for (Value::use_iterator UI = Cur->use_begin(), E = Cur->use_end(); UI != E; 3903 ++UI) { 3904 Instruction *Usr = cast<Instruction>(*UI); 3905 3906 // Check if we found the exit user. 3907 BasicBlock *Parent = Usr->getParent(); 3908 if (!TheLoop->contains(Parent)) { 3909 // Exit if you find multiple outside users. 3910 if (ExitInstruction != 0) 3911 return false; 3912 ExitInstruction = Cur; 3913 continue; 3914 } 3915 3916 // Process instructions only once (termination). 3917 if (VisitedInsts.insert(Usr)) { 3918 if (isa<PHINode>(Usr)) 3919 PHIs.push_back(Usr); 3920 else 3921 NonPHIs.push_back(Usr); 3922 } 3923 // Remember that we completed the cycle. 3924 if (Usr == Phi) 3925 FoundStartPHI = true; 3926 } 3927 Worklist.append(PHIs.begin(), PHIs.end()); 3928 Worklist.append(NonPHIs.begin(), NonPHIs.end()); 3929 } 3930 3931 // This means we have seen one but not the other instruction of the 3932 // pattern or more than just a select and cmp. 3933 if ((Kind == RK_IntegerMinMax || Kind == RK_FloatMinMax) && 3934 NumCmpSelectPatternInst != 2) 3935 return false; 3936 3937 if (!FoundStartPHI || !FoundReduxOp || !ExitInstruction) 3938 return false; 3939 3940 // We found a reduction var if we have reached the original phi node and we 3941 // only have a single instruction with out-of-loop users. 3942 3943 // This instruction is allowed to have out-of-loop users. 3944 AllowedExit.insert(ExitInstruction); 3945 3946 // Save the description of this reduction variable. 3947 ReductionDescriptor RD(RdxStart, ExitInstruction, Kind, 3948 ReduxDesc.MinMaxKind); 3949 Reductions[Phi] = RD; 3950 // We've ended the cycle. This is a reduction variable if we have an 3951 // outside user and it has a binary op. 3952 3953 return true; 3954} 3955 3956/// Returns true if the instruction is a Select(ICmp(X, Y), X, Y) instruction 3957/// pattern corresponding to a min(X, Y) or max(X, Y). 3958LoopVectorizationLegality::ReductionInstDesc 3959LoopVectorizationLegality::isMinMaxSelectCmpPattern(Instruction *I, 3960 ReductionInstDesc &Prev) { 3961 3962 assert((isa<ICmpInst>(I) || isa<FCmpInst>(I) || isa<SelectInst>(I)) && 3963 "Expect a select instruction"); 3964 Instruction *Cmp = 0; 3965 SelectInst *Select = 0; 3966 3967 // We must handle the select(cmp()) as a single instruction. Advance to the 3968 // select. 3969 if ((Cmp = dyn_cast<ICmpInst>(I)) || (Cmp = dyn_cast<FCmpInst>(I))) { 3970 if (!Cmp->hasOneUse() || !(Select = dyn_cast<SelectInst>(*I->use_begin()))) 3971 return ReductionInstDesc(false, I); 3972 return ReductionInstDesc(Select, Prev.MinMaxKind); 3973 } 3974 3975 // Only handle single use cases for now. 3976 if (!(Select = dyn_cast<SelectInst>(I))) 3977 return ReductionInstDesc(false, I); 3978 if (!(Cmp = dyn_cast<ICmpInst>(I->getOperand(0))) && 3979 !(Cmp = dyn_cast<FCmpInst>(I->getOperand(0)))) 3980 return ReductionInstDesc(false, I); 3981 if (!Cmp->hasOneUse()) 3982 return ReductionInstDesc(false, I); 3983 3984 Value *CmpLeft; 3985 Value *CmpRight; 3986 3987 // Look for a min/max pattern. 3988 if (m_UMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 3989 return ReductionInstDesc(Select, MRK_UIntMin); 3990 else if (m_UMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 3991 return ReductionInstDesc(Select, MRK_UIntMax); 3992 else if (m_SMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 3993 return ReductionInstDesc(Select, MRK_SIntMax); 3994 else if (m_SMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 3995 return ReductionInstDesc(Select, MRK_SIntMin); 3996 else if (m_OrdFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 3997 return ReductionInstDesc(Select, MRK_FloatMin); 3998 else if (m_OrdFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 3999 return ReductionInstDesc(Select, MRK_FloatMax); 4000 else if (m_UnordFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 4001 return ReductionInstDesc(Select, MRK_FloatMin); 4002 else if (m_UnordFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) 4003 return ReductionInstDesc(Select, MRK_FloatMax); 4004 4005 return ReductionInstDesc(false, I); 4006} 4007 4008LoopVectorizationLegality::ReductionInstDesc 4009LoopVectorizationLegality::isReductionInstr(Instruction *I, 4010 ReductionKind Kind, 4011 ReductionInstDesc &Prev) { 4012 bool FP = I->getType()->isFloatingPointTy(); 4013 bool FastMath = (FP && I->isCommutative() && I->isAssociative()); 4014 switch (I->getOpcode()) { 4015 default: 4016 return ReductionInstDesc(false, I); 4017 case Instruction::PHI: 4018 if (FP && (Kind != RK_FloatMult && Kind != RK_FloatAdd && 4019 Kind != RK_FloatMinMax)) 4020 return ReductionInstDesc(false, I); 4021 return ReductionInstDesc(I, Prev.MinMaxKind); 4022 case Instruction::Sub: 4023 case Instruction::Add: 4024 return ReductionInstDesc(Kind == RK_IntegerAdd, I); 4025 case Instruction::Mul: 4026 return ReductionInstDesc(Kind == RK_IntegerMult, I); 4027 case Instruction::And: 4028 return ReductionInstDesc(Kind == RK_IntegerAnd, I); 4029 case Instruction::Or: 4030 return ReductionInstDesc(Kind == RK_IntegerOr, I); 4031 case Instruction::Xor: 4032 return ReductionInstDesc(Kind == RK_IntegerXor, I); 4033 case Instruction::FMul: 4034 return ReductionInstDesc(Kind == RK_FloatMult && FastMath, I); 4035 case Instruction::FAdd: 4036 return ReductionInstDesc(Kind == RK_FloatAdd && FastMath, I); 4037 case Instruction::FCmp: 4038 case Instruction::ICmp: 4039 case Instruction::Select: 4040 if (Kind != RK_IntegerMinMax && 4041 (!HasFunNoNaNAttr || Kind != RK_FloatMinMax)) 4042 return ReductionInstDesc(false, I); 4043 return isMinMaxSelectCmpPattern(I, Prev); 4044 } 4045} 4046 4047LoopVectorizationLegality::InductionKind 4048LoopVectorizationLegality::isInductionVariable(PHINode *Phi) { 4049 Type *PhiTy = Phi->getType(); 4050 // We only handle integer and pointer inductions variables. 4051 if (!PhiTy->isIntegerTy() && !PhiTy->isPointerTy()) 4052 return IK_NoInduction; 4053 4054 // Check that the PHI is consecutive. 4055 const SCEV *PhiScev = SE->getSCEV(Phi); 4056 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PhiScev); 4057 if (!AR) { 4058 DEBUG(dbgs() << "LV: PHI is not a poly recurrence.\n"); 4059 return IK_NoInduction; 4060 } 4061 const SCEV *Step = AR->getStepRecurrence(*SE); 4062 4063 // Integer inductions need to have a stride of one. 4064 if (PhiTy->isIntegerTy()) { 4065 if (Step->isOne()) 4066 return IK_IntInduction; 4067 if (Step->isAllOnesValue()) 4068 return IK_ReverseIntInduction; 4069 return IK_NoInduction; 4070 } 4071 4072 // Calculate the pointer stride and check if it is consecutive. 4073 const SCEVConstant *C = dyn_cast<SCEVConstant>(Step); 4074 if (!C) 4075 return IK_NoInduction; 4076 4077 assert(PhiTy->isPointerTy() && "The PHI must be a pointer"); 4078 uint64_t Size = DL->getTypeAllocSize(PhiTy->getPointerElementType()); 4079 if (C->getValue()->equalsInt(Size)) 4080 return IK_PtrInduction; 4081 else if (C->getValue()->equalsInt(0 - Size)) 4082 return IK_ReversePtrInduction; 4083 4084 return IK_NoInduction; 4085} 4086 4087bool LoopVectorizationLegality::isInductionVariable(const Value *V) { 4088 Value *In0 = const_cast<Value*>(V); 4089 PHINode *PN = dyn_cast_or_null<PHINode>(In0); 4090 if (!PN) 4091 return false; 4092 4093 return Inductions.count(PN); 4094} 4095 4096bool LoopVectorizationLegality::blockNeedsPredication(BasicBlock *BB) { 4097 assert(TheLoop->contains(BB) && "Unknown block used"); 4098 4099 // Blocks that do not dominate the latch need predication. 4100 BasicBlock* Latch = TheLoop->getLoopLatch(); 4101 return !DT->dominates(BB, Latch); 4102} 4103 4104bool LoopVectorizationLegality::blockCanBePredicated(BasicBlock *BB) { 4105 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 4106 // We might be able to hoist the load. 4107 if (it->mayReadFromMemory() && !LoadSpeculation.isHoistableLoad(it)) 4108 return false; 4109 4110 // We don't predicate stores at the moment. 4111 if (it->mayWriteToMemory() || it->mayThrow()) 4112 return false; 4113 4114 // The instructions below can trap. 4115 switch (it->getOpcode()) { 4116 default: continue; 4117 case Instruction::UDiv: 4118 case Instruction::SDiv: 4119 case Instruction::URem: 4120 case Instruction::SRem: 4121 return false; 4122 } 4123 } 4124 4125 return true; 4126} 4127 4128bool LoopVectorizationLegality::hasComputableBounds(Value *Ptr) { 4129 const SCEV *PhiScev = SE->getSCEV(Ptr); 4130 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PhiScev); 4131 if (!AR) 4132 return false; 4133 4134 return AR->isAffine(); 4135} 4136 4137LoopVectorizationCostModel::VectorizationFactor 4138LoopVectorizationCostModel::selectVectorizationFactor(bool OptForSize, 4139 unsigned UserVF) { 4140 // Width 1 means no vectorize 4141 VectorizationFactor Factor = { 1U, 0U }; 4142 if (OptForSize && Legal->getRuntimePointerCheck()->Need) { 4143 DEBUG(dbgs() << "LV: Aborting. Runtime ptr check is required in Os.\n"); 4144 return Factor; 4145 } 4146 4147 // Find the trip count. 4148 unsigned TC = SE->getSmallConstantTripCount(TheLoop, TheLoop->getLoopLatch()); 4149 DEBUG(dbgs() << "LV: Found trip count:"<<TC<<"\n"); 4150 4151 unsigned WidestType = getWidestType(); 4152 unsigned WidestRegister = TTI.getRegisterBitWidth(true); 4153 unsigned MaxVectorSize = WidestRegister / WidestType; 4154 DEBUG(dbgs() << "LV: The Widest type: " << WidestType << " bits.\n"); 4155 DEBUG(dbgs() << "LV: The Widest register is:" << WidestRegister << "bits.\n"); 4156 4157 if (MaxVectorSize == 0) { 4158 DEBUG(dbgs() << "LV: The target has no vector registers.\n"); 4159 MaxVectorSize = 1; 4160 } 4161 4162 assert(MaxVectorSize <= 32 && "Did not expect to pack so many elements" 4163 " into one vector!"); 4164 4165 unsigned VF = MaxVectorSize; 4166 4167 // If we optimize the program for size, avoid creating the tail loop. 4168 if (OptForSize) { 4169 // If we are unable to calculate the trip count then don't try to vectorize. 4170 if (TC < 2) { 4171 DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n"); 4172 return Factor; 4173 } 4174 4175 // Find the maximum SIMD width that can fit within the trip count. 4176 VF = TC % MaxVectorSize; 4177 4178 if (VF == 0) 4179 VF = MaxVectorSize; 4180 4181 // If the trip count that we found modulo the vectorization factor is not 4182 // zero then we require a tail. 4183 if (VF < 2) { 4184 DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n"); 4185 return Factor; 4186 } 4187 } 4188 4189 if (UserVF != 0) { 4190 assert(isPowerOf2_32(UserVF) && "VF needs to be a power of two"); 4191 DEBUG(dbgs() << "LV: Using user VF "<<UserVF<<".\n"); 4192 4193 Factor.Width = UserVF; 4194 return Factor; 4195 } 4196 4197 float Cost = expectedCost(1); 4198 unsigned Width = 1; 4199 DEBUG(dbgs() << "LV: Scalar loop costs: "<< (int)Cost << ".\n"); 4200 for (unsigned i=2; i <= VF; i*=2) { 4201 // Notice that the vector loop needs to be executed less times, so 4202 // we need to divide the cost of the vector loops by the width of 4203 // the vector elements. 4204 float VectorCost = expectedCost(i) / (float)i; 4205 DEBUG(dbgs() << "LV: Vector loop of width "<< i << " costs: " << 4206 (int)VectorCost << ".\n"); 4207 if (VectorCost < Cost) { 4208 Cost = VectorCost; 4209 Width = i; 4210 } 4211 } 4212 4213 DEBUG(dbgs() << "LV: Selecting VF = : "<< Width << ".\n"); 4214 Factor.Width = Width; 4215 Factor.Cost = Width * Cost; 4216 return Factor; 4217} 4218 4219unsigned LoopVectorizationCostModel::getWidestType() { 4220 unsigned MaxWidth = 8; 4221 4222 // For each block. 4223 for (Loop::block_iterator bb = TheLoop->block_begin(), 4224 be = TheLoop->block_end(); bb != be; ++bb) { 4225 BasicBlock *BB = *bb; 4226 4227 // For each instruction in the loop. 4228 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 4229 Type *T = it->getType(); 4230 4231 // Only examine Loads, Stores and PHINodes. 4232 if (!isa<LoadInst>(it) && !isa<StoreInst>(it) && !isa<PHINode>(it)) 4233 continue; 4234 4235 // Examine PHI nodes that are reduction variables. 4236 if (PHINode *PN = dyn_cast<PHINode>(it)) 4237 if (!Legal->getReductionVars()->count(PN)) 4238 continue; 4239 4240 // Examine the stored values. 4241 if (StoreInst *ST = dyn_cast<StoreInst>(it)) 4242 T = ST->getValueOperand()->getType(); 4243 4244 // Ignore loaded pointer types and stored pointer types that are not 4245 // consecutive. However, we do want to take consecutive stores/loads of 4246 // pointer vectors into account. 4247 if (T->isPointerTy() && !isConsecutiveLoadOrStore(it)) 4248 continue; 4249 4250 MaxWidth = std::max(MaxWidth, 4251 (unsigned)DL->getTypeSizeInBits(T->getScalarType())); 4252 } 4253 } 4254 4255 return MaxWidth; 4256} 4257 4258unsigned 4259LoopVectorizationCostModel::selectUnrollFactor(bool OptForSize, 4260 unsigned UserUF, 4261 unsigned VF, 4262 unsigned LoopCost) { 4263 4264 // -- The unroll heuristics -- 4265 // We unroll the loop in order to expose ILP and reduce the loop overhead. 4266 // There are many micro-architectural considerations that we can't predict 4267 // at this level. For example frontend pressure (on decode or fetch) due to 4268 // code size, or the number and capabilities of the execution ports. 4269 // 4270 // We use the following heuristics to select the unroll factor: 4271 // 1. If the code has reductions the we unroll in order to break the cross 4272 // iteration dependency. 4273 // 2. If the loop is really small then we unroll in order to reduce the loop 4274 // overhead. 4275 // 3. We don't unroll if we think that we will spill registers to memory due 4276 // to the increased register pressure. 4277 4278 // Use the user preference, unless 'auto' is selected. 4279 if (UserUF != 0) 4280 return UserUF; 4281 4282 // When we optimize for size we don't unroll. 4283 if (OptForSize) 4284 return 1; 4285 4286 // Do not unroll loops with a relatively small trip count. 4287 unsigned TC = SE->getSmallConstantTripCount(TheLoop, 4288 TheLoop->getLoopLatch()); 4289 if (TC > 1 && TC < TinyTripCountUnrollThreshold) 4290 return 1; 4291 4292 unsigned TargetVectorRegisters = TTI.getNumberOfRegisters(true); 4293 DEBUG(dbgs() << "LV: The target has " << TargetVectorRegisters << 4294 " vector registers\n"); 4295 4296 LoopVectorizationCostModel::RegisterUsage R = calculateRegisterUsage(); 4297 // We divide by these constants so assume that we have at least one 4298 // instruction that uses at least one register. 4299 R.MaxLocalUsers = std::max(R.MaxLocalUsers, 1U); 4300 R.NumInstructions = std::max(R.NumInstructions, 1U); 4301 4302 // We calculate the unroll factor using the following formula. 4303 // Subtract the number of loop invariants from the number of available 4304 // registers. These registers are used by all of the unrolled instances. 4305 // Next, divide the remaining registers by the number of registers that is 4306 // required by the loop, in order to estimate how many parallel instances 4307 // fit without causing spills. 4308 unsigned UF = (TargetVectorRegisters - R.LoopInvariantRegs) / R.MaxLocalUsers; 4309 4310 // Clamp the unroll factor ranges to reasonable factors. 4311 unsigned MaxUnrollSize = TTI.getMaximumUnrollFactor(); 4312 4313 // If we did not calculate the cost for VF (because the user selected the VF) 4314 // then we calculate the cost of VF here. 4315 if (LoopCost == 0) 4316 LoopCost = expectedCost(VF); 4317 4318 // Clamp the calculated UF to be between the 1 and the max unroll factor 4319 // that the target allows. 4320 if (UF > MaxUnrollSize) 4321 UF = MaxUnrollSize; 4322 else if (UF < 1) 4323 UF = 1; 4324 4325 if (Legal->getReductionVars()->size()) { 4326 DEBUG(dbgs() << "LV: Unrolling because of reductions. \n"); 4327 return UF; 4328 } 4329 4330 // We want to unroll tiny loops in order to reduce the loop overhead. 4331 // We assume that the cost overhead is 1 and we use the cost model 4332 // to estimate the cost of the loop and unroll until the cost of the 4333 // loop overhead is about 5% of the cost of the loop. 4334 DEBUG(dbgs() << "LV: Loop cost is "<< LoopCost <<" \n"); 4335 if (LoopCost < 20) { 4336 DEBUG(dbgs() << "LV: Unrolling to reduce branch cost. \n"); 4337 unsigned NewUF = 20/LoopCost + 1; 4338 return std::min(NewUF, UF); 4339 } 4340 4341 DEBUG(dbgs() << "LV: Not Unrolling. \n"); 4342 return 1; 4343} 4344 4345LoopVectorizationCostModel::RegisterUsage 4346LoopVectorizationCostModel::calculateRegisterUsage() { 4347 // This function calculates the register usage by measuring the highest number 4348 // of values that are alive at a single location. Obviously, this is a very 4349 // rough estimation. We scan the loop in a topological order in order and 4350 // assign a number to each instruction. We use RPO to ensure that defs are 4351 // met before their users. We assume that each instruction that has in-loop 4352 // users starts an interval. We record every time that an in-loop value is 4353 // used, so we have a list of the first and last occurrences of each 4354 // instruction. Next, we transpose this data structure into a multi map that 4355 // holds the list of intervals that *end* at a specific location. This multi 4356 // map allows us to perform a linear search. We scan the instructions linearly 4357 // and record each time that a new interval starts, by placing it in a set. 4358 // If we find this value in the multi-map then we remove it from the set. 4359 // The max register usage is the maximum size of the set. 4360 // We also search for instructions that are defined outside the loop, but are 4361 // used inside the loop. We need this number separately from the max-interval 4362 // usage number because when we unroll, loop-invariant values do not take 4363 // more register. 4364 LoopBlocksDFS DFS(TheLoop); 4365 DFS.perform(LI); 4366 4367 RegisterUsage R; 4368 R.NumInstructions = 0; 4369 4370 // Each 'key' in the map opens a new interval. The values 4371 // of the map are the index of the 'last seen' usage of the 4372 // instruction that is the key. 4373 typedef DenseMap<Instruction*, unsigned> IntervalMap; 4374 // Maps instruction to its index. 4375 DenseMap<unsigned, Instruction*> IdxToInstr; 4376 // Marks the end of each interval. 4377 IntervalMap EndPoint; 4378 // Saves the list of instruction indices that are used in the loop. 4379 SmallSet<Instruction*, 8> Ends; 4380 // Saves the list of values that are used in the loop but are 4381 // defined outside the loop, such as arguments and constants. 4382 SmallPtrSet<Value*, 8> LoopInvariants; 4383 4384 unsigned Index = 0; 4385 for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(), 4386 be = DFS.endRPO(); bb != be; ++bb) { 4387 R.NumInstructions += (*bb)->size(); 4388 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e; 4389 ++it) { 4390 Instruction *I = it; 4391 IdxToInstr[Index++] = I; 4392 4393 // Save the end location of each USE. 4394 for (unsigned i = 0; i < I->getNumOperands(); ++i) { 4395 Value *U = I->getOperand(i); 4396 Instruction *Instr = dyn_cast<Instruction>(U); 4397 4398 // Ignore non-instruction values such as arguments, constants, etc. 4399 if (!Instr) continue; 4400 4401 // If this instruction is outside the loop then record it and continue. 4402 if (!TheLoop->contains(Instr)) { 4403 LoopInvariants.insert(Instr); 4404 continue; 4405 } 4406 4407 // Overwrite previous end points. 4408 EndPoint[Instr] = Index; 4409 Ends.insert(Instr); 4410 } 4411 } 4412 } 4413 4414 // Saves the list of intervals that end with the index in 'key'. 4415 typedef SmallVector<Instruction*, 2> InstrList; 4416 DenseMap<unsigned, InstrList> TransposeEnds; 4417 4418 // Transpose the EndPoints to a list of values that end at each index. 4419 for (IntervalMap::iterator it = EndPoint.begin(), e = EndPoint.end(); 4420 it != e; ++it) 4421 TransposeEnds[it->second].push_back(it->first); 4422 4423 SmallSet<Instruction*, 8> OpenIntervals; 4424 unsigned MaxUsage = 0; 4425 4426 4427 DEBUG(dbgs() << "LV(REG): Calculating max register usage:\n"); 4428 for (unsigned int i = 0; i < Index; ++i) { 4429 Instruction *I = IdxToInstr[i]; 4430 // Ignore instructions that are never used within the loop. 4431 if (!Ends.count(I)) continue; 4432 4433 // Remove all of the instructions that end at this location. 4434 InstrList &List = TransposeEnds[i]; 4435 for (unsigned int j=0, e = List.size(); j < e; ++j) 4436 OpenIntervals.erase(List[j]); 4437 4438 // Count the number of live interals. 4439 MaxUsage = std::max(MaxUsage, OpenIntervals.size()); 4440 4441 DEBUG(dbgs() << "LV(REG): At #" << i << " Interval # " << 4442 OpenIntervals.size() <<"\n"); 4443 4444 // Add the current instruction to the list of open intervals. 4445 OpenIntervals.insert(I); 4446 } 4447 4448 unsigned Invariant = LoopInvariants.size(); 4449 DEBUG(dbgs() << "LV(REG): Found max usage: " << MaxUsage << " \n"); 4450 DEBUG(dbgs() << "LV(REG): Found invariant usage: " << Invariant << " \n"); 4451 DEBUG(dbgs() << "LV(REG): LoopSize: " << R.NumInstructions << " \n"); 4452 4453 R.LoopInvariantRegs = Invariant; 4454 R.MaxLocalUsers = MaxUsage; 4455 return R; 4456} 4457 4458unsigned LoopVectorizationCostModel::expectedCost(unsigned VF) { 4459 unsigned Cost = 0; 4460 4461 // For each block. 4462 for (Loop::block_iterator bb = TheLoop->block_begin(), 4463 be = TheLoop->block_end(); bb != be; ++bb) { 4464 unsigned BlockCost = 0; 4465 BasicBlock *BB = *bb; 4466 4467 // For each instruction in the old loop. 4468 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { 4469 // Skip dbg intrinsics. 4470 if (isa<DbgInfoIntrinsic>(it)) 4471 continue; 4472 4473 unsigned C = getInstructionCost(it, VF); 4474 Cost += C; 4475 DEBUG(dbgs() << "LV: Found an estimated cost of "<< C <<" for VF " << 4476 VF << " For instruction: "<< *it << "\n"); 4477 } 4478 4479 // We assume that if-converted blocks have a 50% chance of being executed. 4480 // When the code is scalar then some of the blocks are avoided due to CF. 4481 // When the code is vectorized we execute all code paths. 4482 if (Legal->blockNeedsPredication(*bb) && VF == 1) 4483 BlockCost /= 2; 4484 4485 Cost += BlockCost; 4486 } 4487 4488 return Cost; 4489} 4490 4491unsigned 4492LoopVectorizationCostModel::getInstructionCost(Instruction *I, unsigned VF) { 4493 // If we know that this instruction will remain uniform, check the cost of 4494 // the scalar version. 4495 if (Legal->isUniformAfterVectorization(I)) 4496 VF = 1; 4497 4498 Type *RetTy = I->getType(); 4499 Type *VectorTy = ToVectorTy(RetTy, VF); 4500 4501 // TODO: We need to estimate the cost of intrinsic calls. 4502 switch (I->getOpcode()) { 4503 case Instruction::GetElementPtr: 4504 // We mark this instruction as zero-cost because the cost of GEPs in 4505 // vectorized code depends on whether the corresponding memory instruction 4506 // is scalarized or not. Therefore, we handle GEPs with the memory 4507 // instruction cost. 4508 return 0; 4509 case Instruction::Br: { 4510 return TTI.getCFInstrCost(I->getOpcode()); 4511 } 4512 case Instruction::PHI: 4513 //TODO: IF-converted IFs become selects. 4514 return 0; 4515 case Instruction::Add: 4516 case Instruction::FAdd: 4517 case Instruction::Sub: 4518 case Instruction::FSub: 4519 case Instruction::Mul: 4520 case Instruction::FMul: 4521 case Instruction::UDiv: 4522 case Instruction::SDiv: 4523 case Instruction::FDiv: 4524 case Instruction::URem: 4525 case Instruction::SRem: 4526 case Instruction::FRem: 4527 case Instruction::Shl: 4528 case Instruction::LShr: 4529 case Instruction::AShr: 4530 case Instruction::And: 4531 case Instruction::Or: 4532 case Instruction::Xor: { 4533 // Certain instructions can be cheaper to vectorize if they have a constant 4534 // second vector operand. One example of this are shifts on x86. 4535 TargetTransformInfo::OperandValueKind Op1VK = 4536 TargetTransformInfo::OK_AnyValue; 4537 TargetTransformInfo::OperandValueKind Op2VK = 4538 TargetTransformInfo::OK_AnyValue; 4539 4540 if (isa<ConstantInt>(I->getOperand(1))) 4541 Op2VK = TargetTransformInfo::OK_UniformConstantValue; 4542 4543 return TTI.getArithmeticInstrCost(I->getOpcode(), VectorTy, Op1VK, Op2VK); 4544 } 4545 case Instruction::Select: { 4546 SelectInst *SI = cast<SelectInst>(I); 4547 const SCEV *CondSCEV = SE->getSCEV(SI->getCondition()); 4548 bool ScalarCond = (SE->isLoopInvariant(CondSCEV, TheLoop)); 4549 Type *CondTy = SI->getCondition()->getType(); 4550 if (!ScalarCond) 4551 CondTy = VectorType::get(CondTy, VF); 4552 4553 return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy, CondTy); 4554 } 4555 case Instruction::ICmp: 4556 case Instruction::FCmp: { 4557 Type *ValTy = I->getOperand(0)->getType(); 4558 VectorTy = ToVectorTy(ValTy, VF); 4559 return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy); 4560 } 4561 case Instruction::Store: 4562 case Instruction::Load: { 4563 StoreInst *SI = dyn_cast<StoreInst>(I); 4564 LoadInst *LI = dyn_cast<LoadInst>(I); 4565 Type *ValTy = (SI ? SI->getValueOperand()->getType() : 4566 LI->getType()); 4567 VectorTy = ToVectorTy(ValTy, VF); 4568 4569 unsigned Alignment = SI ? SI->getAlignment() : LI->getAlignment(); 4570 unsigned AS = SI ? SI->getPointerAddressSpace() : 4571 LI->getPointerAddressSpace(); 4572 Value *Ptr = SI ? SI->getPointerOperand() : LI->getPointerOperand(); 4573 // We add the cost of address computation here instead of with the gep 4574 // instruction because only here we know whether the operation is 4575 // scalarized. 4576 if (VF == 1) 4577 return TTI.getAddressComputationCost(VectorTy) + 4578 TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS); 4579 4580 // Scalarized loads/stores. 4581 int ConsecutiveStride = Legal->isConsecutivePtr(Ptr); 4582 bool Reverse = ConsecutiveStride < 0; 4583 unsigned ScalarAllocatedSize = DL->getTypeAllocSize(ValTy); 4584 unsigned VectorElementSize = DL->getTypeStoreSize(VectorTy)/VF; 4585 if (!ConsecutiveStride || ScalarAllocatedSize != VectorElementSize) { 4586 unsigned Cost = 0; 4587 // The cost of extracting from the value vector and pointer vector. 4588 Type *PtrTy = ToVectorTy(Ptr->getType(), VF); 4589 for (unsigned i = 0; i < VF; ++i) { 4590 // The cost of extracting the pointer operand. 4591 Cost += TTI.getVectorInstrCost(Instruction::ExtractElement, PtrTy, i); 4592 // In case of STORE, the cost of ExtractElement from the vector. 4593 // In case of LOAD, the cost of InsertElement into the returned 4594 // vector. 4595 Cost += TTI.getVectorInstrCost(SI ? Instruction::ExtractElement : 4596 Instruction::InsertElement, 4597 VectorTy, i); 4598 } 4599 4600 // The cost of the scalar loads/stores. 4601 Cost += VF * TTI.getAddressComputationCost(ValTy->getScalarType()); 4602 Cost += VF * TTI.getMemoryOpCost(I->getOpcode(), ValTy->getScalarType(), 4603 Alignment, AS); 4604 return Cost; 4605 } 4606 4607 // Wide load/stores. 4608 unsigned Cost = TTI.getAddressComputationCost(VectorTy); 4609 Cost += TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS); 4610 4611 if (Reverse) 4612 Cost += TTI.getShuffleCost(TargetTransformInfo::SK_Reverse, 4613 VectorTy, 0); 4614 return Cost; 4615 } 4616 case Instruction::ZExt: 4617 case Instruction::SExt: 4618 case Instruction::FPToUI: 4619 case Instruction::FPToSI: 4620 case Instruction::FPExt: 4621 case Instruction::PtrToInt: 4622 case Instruction::IntToPtr: 4623 case Instruction::SIToFP: 4624 case Instruction::UIToFP: 4625 case Instruction::Trunc: 4626 case Instruction::FPTrunc: 4627 case Instruction::BitCast: { 4628 // We optimize the truncation of induction variable. 4629 // The cost of these is the same as the scalar operation. 4630 if (I->getOpcode() == Instruction::Trunc && 4631 Legal->isInductionVariable(I->getOperand(0))) 4632 return TTI.getCastInstrCost(I->getOpcode(), I->getType(), 4633 I->getOperand(0)->getType()); 4634 4635 Type *SrcVecTy = ToVectorTy(I->getOperand(0)->getType(), VF); 4636 return TTI.getCastInstrCost(I->getOpcode(), VectorTy, SrcVecTy); 4637 } 4638 case Instruction::Call: { 4639 CallInst *CI = cast<CallInst>(I); 4640 Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI); 4641 assert(ID && "Not an intrinsic call!"); 4642 Type *RetTy = ToVectorTy(CI->getType(), VF); 4643 SmallVector<Type*, 4> Tys; 4644 for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i) 4645 Tys.push_back(ToVectorTy(CI->getArgOperand(i)->getType(), VF)); 4646 return TTI.getIntrinsicInstrCost(ID, RetTy, Tys); 4647 } 4648 default: { 4649 // We are scalarizing the instruction. Return the cost of the scalar 4650 // instruction, plus the cost of insert and extract into vector 4651 // elements, times the vector width. 4652 unsigned Cost = 0; 4653 4654 if (!RetTy->isVoidTy() && VF != 1) { 4655 unsigned InsCost = TTI.getVectorInstrCost(Instruction::InsertElement, 4656 VectorTy); 4657 unsigned ExtCost = TTI.getVectorInstrCost(Instruction::ExtractElement, 4658 VectorTy); 4659 4660 // The cost of inserting the results plus extracting each one of the 4661 // operands. 4662 Cost += VF * (InsCost + ExtCost * I->getNumOperands()); 4663 } 4664 4665 // The cost of executing VF copies of the scalar instruction. This opcode 4666 // is unknown. Assume that it is the same as 'mul'. 4667 Cost += VF * TTI.getArithmeticInstrCost(Instruction::Mul, VectorTy); 4668 return Cost; 4669 } 4670 }// end of switch. 4671} 4672 4673Type* LoopVectorizationCostModel::ToVectorTy(Type *Scalar, unsigned VF) { 4674 if (Scalar->isVoidTy() || VF == 1) 4675 return Scalar; 4676 return VectorType::get(Scalar, VF); 4677} 4678 4679char LoopVectorize::ID = 0; 4680static const char lv_name[] = "Loop Vectorization"; 4681INITIALIZE_PASS_BEGIN(LoopVectorize, LV_NAME, lv_name, false, false) 4682INITIALIZE_AG_DEPENDENCY(AliasAnalysis) 4683INITIALIZE_AG_DEPENDENCY(TargetTransformInfo) 4684INITIALIZE_PASS_DEPENDENCY(ScalarEvolution) 4685INITIALIZE_PASS_DEPENDENCY(LoopSimplify) 4686INITIALIZE_PASS_END(LoopVectorize, LV_NAME, lv_name, false, false) 4687 4688namespace llvm { 4689 Pass *createLoopVectorizePass() { 4690 return new LoopVectorize(); 4691 } 4692} 4693 4694bool LoopVectorizationCostModel::isConsecutiveLoadOrStore(Instruction *Inst) { 4695 // Check for a store. 4696 if (StoreInst *ST = dyn_cast<StoreInst>(Inst)) 4697 return Legal->isConsecutivePtr(ST->getPointerOperand()) != 0; 4698 4699 // Check for a load. 4700 if (LoadInst *LI = dyn_cast<LoadInst>(Inst)) 4701 return Legal->isConsecutivePtr(LI->getPointerOperand()) != 0; 4702 4703 return false; 4704} 4705