1 //===- LoopVectorize.cpp - A Loop Vectorizer ------------------------------===//
3 // The LLVM Compiler Infrastructure
5 // This file is distributed under the University of Illinois Open Source
6 // License. See LICENSE.TXT for details.
8 //===----------------------------------------------------------------------===//
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.
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.
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.
29 //===----------------------------------------------------------------------===//
31 // The reduction-variable vectorization is based on the paper:
32 // D. Nuzman and R. Henderson. Multi-platform Auto-vectorization.
34 // Variable uniformity checks are inspired by:
35 // Karrenberg, R. and Hack, S. Whole Function Vectorization.
37 // Other ideas/concepts are from:
38 // A. Zaks and D. Nuzman. Autovectorization in GCC-two years later.
40 // S. Maleki, Y. Gao, M. Garzaran, T. Wong and D. Padua. An Evaluation of
41 // Vectorizing Compilers.
43 //===----------------------------------------------------------------------===//
45 #include "llvm/Transforms/Vectorize.h"
46 #include "llvm/ADT/DenseMap.h"
47 #include "llvm/ADT/EquivalenceClasses.h"
48 #include "llvm/ADT/Hashing.h"
49 #include "llvm/ADT/MapVector.h"
50 #include "llvm/ADT/SetVector.h"
51 #include "llvm/ADT/SmallPtrSet.h"
52 #include "llvm/ADT/SmallSet.h"
53 #include "llvm/ADT/SmallVector.h"
54 #include "llvm/ADT/Statistic.h"
55 #include "llvm/ADT/StringExtras.h"
56 #include "llvm/Analysis/AliasAnalysis.h"
57 #include "llvm/Analysis/AliasSetTracker.h"
58 #include "llvm/Analysis/AssumptionTracker.h"
59 #include "llvm/Analysis/BlockFrequencyInfo.h"
60 #include "llvm/Analysis/CodeMetrics.h"
61 #include "llvm/Analysis/LoopInfo.h"
62 #include "llvm/Analysis/LoopIterator.h"
63 #include "llvm/Analysis/LoopPass.h"
64 #include "llvm/Analysis/ScalarEvolution.h"
65 #include "llvm/Analysis/ScalarEvolutionExpander.h"
66 #include "llvm/Analysis/ScalarEvolutionExpressions.h"
67 #include "llvm/Analysis/TargetTransformInfo.h"
68 #include "llvm/Analysis/ValueTracking.h"
69 #include "llvm/IR/Constants.h"
70 #include "llvm/IR/DataLayout.h"
71 #include "llvm/IR/DebugInfo.h"
72 #include "llvm/IR/DerivedTypes.h"
73 #include "llvm/IR/DiagnosticInfo.h"
74 #include "llvm/IR/Dominators.h"
75 #include "llvm/IR/Function.h"
76 #include "llvm/IR/IRBuilder.h"
77 #include "llvm/IR/Instructions.h"
78 #include "llvm/IR/IntrinsicInst.h"
79 #include "llvm/IR/LLVMContext.h"
80 #include "llvm/IR/Module.h"
81 #include "llvm/IR/PatternMatch.h"
82 #include "llvm/IR/Type.h"
83 #include "llvm/IR/Value.h"
84 #include "llvm/IR/ValueHandle.h"
85 #include "llvm/IR/Verifier.h"
86 #include "llvm/Pass.h"
87 #include "llvm/Support/BranchProbability.h"
88 #include "llvm/Support/CommandLine.h"
89 #include "llvm/Support/Debug.h"
90 #include "llvm/Support/raw_ostream.h"
91 #include "llvm/Transforms/Scalar.h"
92 #include "llvm/Transforms/Utils/BasicBlockUtils.h"
93 #include "llvm/Transforms/Utils/Local.h"
94 #include "llvm/Transforms/Utils/VectorUtils.h"
100 using namespace llvm::PatternMatch;
102 #define LV_NAME "loop-vectorize"
103 #define DEBUG_TYPE LV_NAME
105 STATISTIC(LoopsVectorized, "Number of loops vectorized");
106 STATISTIC(LoopsAnalyzed, "Number of loops analyzed for vectorization");
108 static cl::opt<unsigned>
109 VectorizationFactor("force-vector-width", cl::init(0), cl::Hidden,
110 cl::desc("Sets the SIMD width. Zero is autoselect."));
112 static cl::opt<unsigned>
113 VectorizationInterleave("force-vector-interleave", cl::init(0), cl::Hidden,
114 cl::desc("Sets the vectorization interleave count. "
115 "Zero is autoselect."));
118 EnableIfConversion("enable-if-conversion", cl::init(true), cl::Hidden,
119 cl::desc("Enable if-conversion during vectorization."));
121 /// We don't vectorize loops with a known constant trip count below this number.
122 static cl::opt<unsigned>
123 TinyTripCountVectorThreshold("vectorizer-min-trip-count", cl::init(16),
125 cl::desc("Don't vectorize loops with a constant "
126 "trip count that is smaller than this "
129 /// This enables versioning on the strides of symbolically striding memory
130 /// accesses in code like the following.
131 /// for (i = 0; i < N; ++i)
132 /// A[i * Stride1] += B[i * Stride2] ...
134 /// Will be roughly translated to
135 /// if (Stride1 == 1 && Stride2 == 1) {
136 /// for (i = 0; i < N; i+=4)
140 static cl::opt<bool> EnableMemAccessVersioning(
141 "enable-mem-access-versioning", cl::init(true), cl::Hidden,
142 cl::desc("Enable symblic stride memory access versioning"));
144 /// We don't unroll loops with a known constant trip count below this number.
145 static const unsigned TinyTripCountUnrollThreshold = 128;
147 /// When performing memory disambiguation checks at runtime do not make more
148 /// than this number of comparisons.
149 static const unsigned RuntimeMemoryCheckThreshold = 8;
151 /// Maximum simd width.
152 static const unsigned MaxVectorWidth = 64;
154 static cl::opt<unsigned> ForceTargetNumScalarRegs(
155 "force-target-num-scalar-regs", cl::init(0), cl::Hidden,
156 cl::desc("A flag that overrides the target's number of scalar registers."));
158 static cl::opt<unsigned> ForceTargetNumVectorRegs(
159 "force-target-num-vector-regs", cl::init(0), cl::Hidden,
160 cl::desc("A flag that overrides the target's number of vector registers."));
162 /// Maximum vectorization interleave count.
163 static const unsigned MaxInterleaveFactor = 16;
165 static cl::opt<unsigned> ForceTargetMaxScalarInterleaveFactor(
166 "force-target-max-scalar-interleave", cl::init(0), cl::Hidden,
167 cl::desc("A flag that overrides the target's max interleave factor for "
170 static cl::opt<unsigned> ForceTargetMaxVectorInterleaveFactor(
171 "force-target-max-vector-interleave", cl::init(0), cl::Hidden,
172 cl::desc("A flag that overrides the target's max interleave factor for "
173 "vectorized loops."));
175 static cl::opt<unsigned> ForceTargetInstructionCost(
176 "force-target-instruction-cost", cl::init(0), cl::Hidden,
177 cl::desc("A flag that overrides the target's expected cost for "
178 "an instruction to a single constant value. Mostly "
179 "useful for getting consistent testing."));
181 static cl::opt<unsigned> SmallLoopCost(
182 "small-loop-cost", cl::init(20), cl::Hidden,
183 cl::desc("The cost of a loop that is considered 'small' by the unroller."));
185 static cl::opt<bool> LoopVectorizeWithBlockFrequency(
186 "loop-vectorize-with-block-frequency", cl::init(false), cl::Hidden,
187 cl::desc("Enable the use of the block frequency analysis to access PGO "
188 "heuristics minimizing code growth in cold regions and being more "
189 "aggressive in hot regions."));
191 // Runtime unroll loops for load/store throughput.
192 static cl::opt<bool> EnableLoadStoreRuntimeUnroll(
193 "enable-loadstore-runtime-unroll", cl::init(true), cl::Hidden,
194 cl::desc("Enable runtime unrolling until load/store ports are saturated"));
196 /// The number of stores in a loop that are allowed to need predication.
197 static cl::opt<unsigned> NumberOfStoresToPredicate(
198 "vectorize-num-stores-pred", cl::init(1), cl::Hidden,
199 cl::desc("Max number of stores to be predicated behind an if."));
201 static cl::opt<bool> EnableIndVarRegisterHeur(
202 "enable-ind-var-reg-heur", cl::init(true), cl::Hidden,
203 cl::desc("Count the induction variable only once when unrolling"));
205 static cl::opt<bool> EnableCondStoresVectorization(
206 "enable-cond-stores-vec", cl::init(false), cl::Hidden,
207 cl::desc("Enable if predication of stores during vectorization."));
209 static cl::opt<unsigned> MaxNestedScalarReductionUF(
210 "max-nested-scalar-reduction-unroll", cl::init(2), cl::Hidden,
211 cl::desc("The maximum unroll factor to use when unrolling a scalar "
212 "reduction in a nested loop."));
216 // Forward declarations.
217 class LoopVectorizationLegality;
218 class LoopVectorizationCostModel;
219 class LoopVectorizeHints;
221 /// Optimization analysis message produced during vectorization. Messages inform
222 /// the user why vectorization did not occur.
225 raw_string_ostream Out;
229 Report(Instruction *I = nullptr) : Out(Message), Instr(I) {
230 Out << "loop not vectorized: ";
233 template <typename A> Report &operator<<(const A &Value) {
238 Instruction *getInstr() { return Instr; }
240 std::string &str() { return Out.str(); }
241 operator Twine() { return Out.str(); }
244 /// InnerLoopVectorizer vectorizes loops which contain only one basic
245 /// block to a specified vectorization factor (VF).
246 /// This class performs the widening of scalars into vectors, or multiple
247 /// scalars. This class also implements the following features:
248 /// * It inserts an epilogue loop for handling loops that don't have iteration
249 /// counts that are known to be a multiple of the vectorization factor.
250 /// * It handles the code generation for reduction variables.
251 /// * Scalarization (implementation using scalars) of un-vectorizable
253 /// InnerLoopVectorizer does not perform any vectorization-legality
254 /// checks, and relies on the caller to check for the different legality
255 /// aspects. The InnerLoopVectorizer relies on the
256 /// LoopVectorizationLegality class to provide information about the induction
257 /// and reduction variables that were found to a given vectorization factor.
258 class InnerLoopVectorizer {
260 InnerLoopVectorizer(Loop *OrigLoop, ScalarEvolution *SE, LoopInfo *LI,
261 DominatorTree *DT, const DataLayout *DL,
262 const TargetLibraryInfo *TLI, unsigned VecWidth,
263 unsigned UnrollFactor)
264 : OrigLoop(OrigLoop), SE(SE), LI(LI), DT(DT), DL(DL), TLI(TLI),
265 VF(VecWidth), UF(UnrollFactor), Builder(SE->getContext()),
266 Induction(nullptr), OldInduction(nullptr), WidenMap(UnrollFactor),
269 // Perform the actual loop widening (vectorization).
270 void vectorize(LoopVectorizationLegality *L) {
272 // Create a new empty loop. Unlink the old loop and connect the new one.
274 // Widen each instruction in the old loop to a new one in the new loop.
275 // Use the Legality module to find the induction and reduction variables.
277 // Register the new loop and update the analysis passes.
281 virtual ~InnerLoopVectorizer() {}
284 /// A small list of PHINodes.
285 typedef SmallVector<PHINode*, 4> PhiVector;
286 /// When we unroll loops we have multiple vector values for each scalar.
287 /// This data structure holds the unrolled and vectorized values that
288 /// originated from one scalar instruction.
289 typedef SmallVector<Value*, 2> VectorParts;
291 // When we if-convert we need create edge masks. We have to cache values so
292 // that we don't end up with exponential recursion/IR.
293 typedef DenseMap<std::pair<BasicBlock*, BasicBlock*>,
294 VectorParts> EdgeMaskCache;
296 /// \brief Add code that checks at runtime if the accessed arrays overlap.
298 /// Returns a pair of instructions where the first element is the first
299 /// instruction generated in possibly a sequence of instructions and the
300 /// second value is the final comparator value or NULL if no check is needed.
301 std::pair<Instruction *, Instruction *> addRuntimeCheck(Instruction *Loc);
303 /// \brief Add checks for strides that where assumed to be 1.
305 /// Returns the last check instruction and the first check instruction in the
306 /// pair as (first, last).
307 std::pair<Instruction *, Instruction *> addStrideCheck(Instruction *Loc);
309 /// Create an empty loop, based on the loop ranges of the old loop.
310 void createEmptyLoop();
311 /// Copy and widen the instructions from the old loop.
312 virtual void vectorizeLoop();
314 /// \brief The Loop exit block may have single value PHI nodes where the
315 /// incoming value is 'Undef'. While vectorizing we only handled real values
316 /// that were defined inside the loop. Here we fix the 'undef case'.
320 /// A helper function that computes the predicate of the block BB, assuming
321 /// that the header block of the loop is set to True. It returns the *entry*
322 /// mask for the block BB.
323 VectorParts createBlockInMask(BasicBlock *BB);
324 /// A helper function that computes the predicate of the edge between SRC
326 VectorParts createEdgeMask(BasicBlock *Src, BasicBlock *Dst);
328 /// A helper function to vectorize a single BB within the innermost loop.
329 void vectorizeBlockInLoop(BasicBlock *BB, PhiVector *PV);
331 /// Vectorize a single PHINode in a block. This method handles the induction
332 /// variable canonicalization. It supports both VF = 1 for unrolled loops and
333 /// arbitrary length vectors.
334 void widenPHIInstruction(Instruction *PN, VectorParts &Entry,
335 unsigned UF, unsigned VF, PhiVector *PV);
337 /// Insert the new loop to the loop hierarchy and pass manager
338 /// and update the analysis passes.
339 void updateAnalysis();
341 /// This instruction is un-vectorizable. Implement it as a sequence
342 /// of scalars. If \p IfPredicateStore is true we need to 'hide' each
343 /// scalarized instruction behind an if block predicated on the control
344 /// dependence of the instruction.
345 virtual void scalarizeInstruction(Instruction *Instr,
346 bool IfPredicateStore=false);
348 /// Vectorize Load and Store instructions,
349 virtual void vectorizeMemoryInstruction(Instruction *Instr);
351 /// Create a broadcast instruction. This method generates a broadcast
352 /// instruction (shuffle) for loop invariant values and for the induction
353 /// value. If this is the induction variable then we extend it to N, N+1, ...
354 /// this is needed because each iteration in the loop corresponds to a SIMD
356 virtual Value *getBroadcastInstrs(Value *V);
358 /// This function adds 0, 1, 2 ... to each vector element, starting at zero.
359 /// If Negate is set then negative numbers are added e.g. (0, -1, -2, ...).
360 /// The sequence starts at StartIndex.
361 virtual Value *getConsecutiveVector(Value* Val, int StartIdx, bool Negate);
363 /// When we go over instructions in the basic block we rely on previous
364 /// values within the current basic block or on loop invariant values.
365 /// When we widen (vectorize) values we place them in the map. If the values
366 /// are not within the map, they have to be loop invariant, so we simply
367 /// broadcast them into a vector.
368 VectorParts &getVectorValue(Value *V);
370 /// Generate a shuffle sequence that will reverse the vector Vec.
371 virtual Value *reverseVector(Value *Vec);
373 /// This is a helper class that holds the vectorizer state. It maps scalar
374 /// instructions to vector instructions. When the code is 'unrolled' then
375 /// then a single scalar value is mapped to multiple vector parts. The parts
376 /// are stored in the VectorPart type.
378 /// C'tor. UnrollFactor controls the number of vectors ('parts') that
380 ValueMap(unsigned UnrollFactor) : UF(UnrollFactor) {}
382 /// \return True if 'Key' is saved in the Value Map.
383 bool has(Value *Key) const { return MapStorage.count(Key); }
385 /// Initializes a new entry in the map. Sets all of the vector parts to the
386 /// save value in 'Val'.
387 /// \return A reference to a vector with splat values.
388 VectorParts &splat(Value *Key, Value *Val) {
389 VectorParts &Entry = MapStorage[Key];
390 Entry.assign(UF, Val);
394 ///\return A reference to the value that is stored at 'Key'.
395 VectorParts &get(Value *Key) {
396 VectorParts &Entry = MapStorage[Key];
399 assert(Entry.size() == UF);
404 /// The unroll factor. Each entry in the map stores this number of vector
408 /// Map storage. We use std::map and not DenseMap because insertions to a
409 /// dense map invalidates its iterators.
410 std::map<Value *, VectorParts> MapStorage;
413 /// The original loop.
415 /// Scev analysis to use.
424 const DataLayout *DL;
425 /// Target Library Info.
426 const TargetLibraryInfo *TLI;
428 /// The vectorization SIMD factor to use. Each vector will have this many
433 /// The vectorization unroll factor to use. Each scalar is vectorized to this
434 /// many different vector instructions.
437 /// The builder that we use
440 // --- Vectorization state ---
442 /// The vector-loop preheader.
443 BasicBlock *LoopVectorPreHeader;
444 /// The scalar-loop preheader.
445 BasicBlock *LoopScalarPreHeader;
446 /// Middle Block between the vector and the scalar.
447 BasicBlock *LoopMiddleBlock;
448 ///The ExitBlock of the scalar loop.
449 BasicBlock *LoopExitBlock;
450 ///The vector loop body.
451 SmallVector<BasicBlock *, 4> LoopVectorBody;
452 ///The scalar loop body.
453 BasicBlock *LoopScalarBody;
454 /// A list of all bypass blocks. The first block is the entry of the loop.
455 SmallVector<BasicBlock *, 4> LoopBypassBlocks;
457 /// The new Induction variable which was added to the new block.
459 /// The induction variable of the old basic block.
460 PHINode *OldInduction;
461 /// Holds the extended (to the widest induction type) start index.
463 /// Maps scalars to widened vectors.
465 EdgeMaskCache MaskCache;
467 LoopVectorizationLegality *Legal;
470 class InnerLoopUnroller : public InnerLoopVectorizer {
472 InnerLoopUnroller(Loop *OrigLoop, ScalarEvolution *SE, LoopInfo *LI,
473 DominatorTree *DT, const DataLayout *DL,
474 const TargetLibraryInfo *TLI, unsigned UnrollFactor) :
475 InnerLoopVectorizer(OrigLoop, SE, LI, DT, DL, TLI, 1, UnrollFactor) { }
478 void scalarizeInstruction(Instruction *Instr,
479 bool IfPredicateStore = false) override;
480 void vectorizeMemoryInstruction(Instruction *Instr) override;
481 Value *getBroadcastInstrs(Value *V) override;
482 Value *getConsecutiveVector(Value* Val, int StartIdx, bool Negate) override;
483 Value *reverseVector(Value *Vec) override;
486 /// \brief Look for a meaningful debug location on the instruction or it's
488 static Instruction *getDebugLocFromInstOrOperands(Instruction *I) {
493 if (I->getDebugLoc() != Empty)
496 for (User::op_iterator OI = I->op_begin(), OE = I->op_end(); OI != OE; ++OI) {
497 if (Instruction *OpInst = dyn_cast<Instruction>(*OI))
498 if (OpInst->getDebugLoc() != Empty)
505 /// \brief Set the debug location in the builder using the debug location in the
507 static void setDebugLocFromInst(IRBuilder<> &B, const Value *Ptr) {
508 if (const Instruction *Inst = dyn_cast_or_null<Instruction>(Ptr))
509 B.SetCurrentDebugLocation(Inst->getDebugLoc());
511 B.SetCurrentDebugLocation(DebugLoc());
515 /// \return string containing a file name and a line # for the given loop.
516 static std::string getDebugLocString(const Loop *L) {
519 raw_string_ostream OS(Result);
520 const DebugLoc LoopDbgLoc = L->getStartLoc();
521 if (!LoopDbgLoc.isUnknown())
522 LoopDbgLoc.print(L->getHeader()->getContext(), OS);
524 // Just print the module name.
525 OS << L->getHeader()->getParent()->getParent()->getModuleIdentifier();
532 /// \brief Propagate known metadata from one instruction to another.
533 static void propagateMetadata(Instruction *To, const Instruction *From) {
534 SmallVector<std::pair<unsigned, MDNode *>, 4> Metadata;
535 From->getAllMetadataOtherThanDebugLoc(Metadata);
537 for (auto M : Metadata) {
538 unsigned Kind = M.first;
540 // These are safe to transfer (this is safe for TBAA, even when we
541 // if-convert, because should that metadata have had a control dependency
542 // on the condition, and thus actually aliased with some other
543 // non-speculated memory access when the condition was false, this would be
544 // caught by the runtime overlap checks).
545 if (Kind != LLVMContext::MD_tbaa &&
546 Kind != LLVMContext::MD_alias_scope &&
547 Kind != LLVMContext::MD_noalias &&
548 Kind != LLVMContext::MD_fpmath)
551 To->setMetadata(Kind, M.second);
555 /// \brief Propagate known metadata from one instruction to a vector of others.
556 static void propagateMetadata(SmallVectorImpl<Value *> &To, const Instruction *From) {
558 if (Instruction *I = dyn_cast<Instruction>(V))
559 propagateMetadata(I, From);
562 /// LoopVectorizationLegality checks if it is legal to vectorize a loop, and
563 /// to what vectorization factor.
564 /// This class does not look at the profitability of vectorization, only the
565 /// legality. This class has two main kinds of checks:
566 /// * Memory checks - The code in canVectorizeMemory checks if vectorization
567 /// will change the order of memory accesses in a way that will change the
568 /// correctness of the program.
569 /// * Scalars checks - The code in canVectorizeInstrs and canVectorizeMemory
570 /// checks for a number of different conditions, such as the availability of a
571 /// single induction variable, that all types are supported and vectorize-able,
572 /// etc. This code reflects the capabilities of InnerLoopVectorizer.
573 /// This class is also used by InnerLoopVectorizer for identifying
574 /// induction variable and the different reduction variables.
575 class LoopVectorizationLegality {
579 unsigned NumPredStores;
581 LoopVectorizationLegality(Loop *L, ScalarEvolution *SE, const DataLayout *DL,
582 DominatorTree *DT, TargetLibraryInfo *TLI,
583 AliasAnalysis *AA, Function *F,
584 const TargetTransformInfo *TTI)
585 : NumLoads(0), NumStores(0), NumPredStores(0), TheLoop(L), SE(SE), DL(DL),
586 DT(DT), TLI(TLI), AA(AA), TheFunction(F), TTI(TTI), Induction(nullptr),
587 WidestIndTy(nullptr), HasFunNoNaNAttr(false), MaxSafeDepDistBytes(-1U) {
590 /// This enum represents the kinds of reductions that we support.
592 RK_NoReduction, ///< Not a reduction.
593 RK_IntegerAdd, ///< Sum of integers.
594 RK_IntegerMult, ///< Product of integers.
595 RK_IntegerOr, ///< Bitwise or logical OR of numbers.
596 RK_IntegerAnd, ///< Bitwise or logical AND of numbers.
597 RK_IntegerXor, ///< Bitwise or logical XOR of numbers.
598 RK_IntegerMinMax, ///< Min/max implemented in terms of select(cmp()).
599 RK_FloatAdd, ///< Sum of floats.
600 RK_FloatMult, ///< Product of floats.
601 RK_FloatMinMax ///< Min/max implemented in terms of select(cmp()).
604 /// This enum represents the kinds of inductions that we support.
606 IK_NoInduction, ///< Not an induction variable.
607 IK_IntInduction, ///< Integer induction variable. Step = 1.
608 IK_ReverseIntInduction, ///< Reverse int induction variable. Step = -1.
609 IK_PtrInduction, ///< Pointer induction var. Step = sizeof(elem).
610 IK_ReversePtrInduction ///< Reverse ptr indvar. Step = - sizeof(elem).
613 // This enum represents the kind of minmax reduction.
614 enum MinMaxReductionKind {
624 /// This struct holds information about reduction variables.
625 struct ReductionDescriptor {
626 ReductionDescriptor() : StartValue(nullptr), LoopExitInstr(nullptr),
627 Kind(RK_NoReduction), MinMaxKind(MRK_Invalid) {}
629 ReductionDescriptor(Value *Start, Instruction *Exit, ReductionKind K,
630 MinMaxReductionKind MK)
631 : StartValue(Start), LoopExitInstr(Exit), Kind(K), MinMaxKind(MK) {}
633 // The starting value of the reduction.
634 // It does not have to be zero!
635 TrackingVH<Value> StartValue;
636 // The instruction who's value is used outside the loop.
637 Instruction *LoopExitInstr;
638 // The kind of the reduction.
640 // If this a min/max reduction the kind of reduction.
641 MinMaxReductionKind MinMaxKind;
644 /// This POD struct holds information about a potential reduction operation.
645 struct ReductionInstDesc {
646 ReductionInstDesc(bool IsRedux, Instruction *I) :
647 IsReduction(IsRedux), PatternLastInst(I), MinMaxKind(MRK_Invalid) {}
649 ReductionInstDesc(Instruction *I, MinMaxReductionKind K) :
650 IsReduction(true), PatternLastInst(I), MinMaxKind(K) {}
652 // Is this instruction a reduction candidate.
654 // The last instruction in a min/max pattern (select of the select(icmp())
655 // pattern), or the current reduction instruction otherwise.
656 Instruction *PatternLastInst;
657 // If this is a min/max pattern the comparison predicate.
658 MinMaxReductionKind MinMaxKind;
661 /// This struct holds information about the memory runtime legality
662 /// check that a group of pointers do not overlap.
663 struct RuntimePointerCheck {
664 RuntimePointerCheck() : Need(false) {}
666 /// Reset the state of the pointer runtime information.
673 DependencySetId.clear();
677 /// Insert a pointer and calculate the start and end SCEVs.
678 void insert(ScalarEvolution *SE, Loop *Lp, Value *Ptr, bool WritePtr,
679 unsigned DepSetId, unsigned ASId, ValueToValueMap &Strides);
681 /// This flag indicates if we need to add the runtime check.
683 /// Holds the pointers that we need to check.
684 SmallVector<TrackingVH<Value>, 2> Pointers;
685 /// Holds the pointer value at the beginning of the loop.
686 SmallVector<const SCEV*, 2> Starts;
687 /// Holds the pointer value at the end of the loop.
688 SmallVector<const SCEV*, 2> Ends;
689 /// Holds the information if this pointer is used for writing to memory.
690 SmallVector<bool, 2> IsWritePtr;
691 /// Holds the id of the set of pointers that could be dependent because of a
692 /// shared underlying object.
693 SmallVector<unsigned, 2> DependencySetId;
694 /// Holds the id of the disjoint alias set to which this pointer belongs.
695 SmallVector<unsigned, 2> AliasSetId;
698 /// A struct for saving information about induction variables.
699 struct InductionInfo {
700 InductionInfo(Value *Start, InductionKind K) : StartValue(Start), IK(K) {}
701 InductionInfo() : StartValue(nullptr), IK(IK_NoInduction) {}
703 TrackingVH<Value> StartValue;
708 /// ReductionList contains the reduction descriptors for all
709 /// of the reductions that were found in the loop.
710 typedef DenseMap<PHINode*, ReductionDescriptor> ReductionList;
712 /// InductionList saves induction variables and maps them to the
713 /// induction descriptor.
714 typedef MapVector<PHINode*, InductionInfo> InductionList;
716 /// Returns true if it is legal to vectorize this loop.
717 /// This does not mean that it is profitable to vectorize this
718 /// loop, only that it is legal to do so.
721 /// Returns the Induction variable.
722 PHINode *getInduction() { return Induction; }
724 /// Returns the reduction variables found in the loop.
725 ReductionList *getReductionVars() { return &Reductions; }
727 /// Returns the induction variables found in the loop.
728 InductionList *getInductionVars() { return &Inductions; }
730 /// Returns the widest induction type.
731 Type *getWidestInductionType() { return WidestIndTy; }
733 /// Returns True if V is an induction variable in this loop.
734 bool isInductionVariable(const Value *V);
736 /// Return true if the block BB needs to be predicated in order for the loop
737 /// to be vectorized.
738 bool blockNeedsPredication(BasicBlock *BB);
740 /// Check if this pointer is consecutive when vectorizing. This happens
741 /// when the last index of the GEP is the induction variable, or that the
742 /// pointer itself is an induction variable.
743 /// This check allows us to vectorize A[idx] into a wide load/store.
745 /// 0 - Stride is unknown or non-consecutive.
746 /// 1 - Address is consecutive.
747 /// -1 - Address is consecutive, and decreasing.
748 int isConsecutivePtr(Value *Ptr);
750 /// Returns true if the value V is uniform within the loop.
751 bool isUniform(Value *V);
753 /// Returns true if this instruction will remain scalar after vectorization.
754 bool isUniformAfterVectorization(Instruction* I) { return Uniforms.count(I); }
756 /// Returns the information that we collected about runtime memory check.
757 RuntimePointerCheck *getRuntimePointerCheck() { return &PtrRtCheck; }
759 /// This function returns the identity element (or neutral element) for
761 static Constant *getReductionIdentity(ReductionKind K, Type *Tp);
763 unsigned getMaxSafeDepDistBytes() { return MaxSafeDepDistBytes; }
765 bool hasStride(Value *V) { return StrideSet.count(V); }
766 bool mustCheckStrides() { return !StrideSet.empty(); }
767 SmallPtrSet<Value *, 8>::iterator strides_begin() {
768 return StrideSet.begin();
770 SmallPtrSet<Value *, 8>::iterator strides_end() { return StrideSet.end(); }
772 /// Returns true if the target machine supports masked store operation
773 /// for the given \p DataType and kind of access to \p Ptr.
774 bool isLegalMaskedStore(Type *DataType, Value *Ptr) {
775 return TTI->isLegalMaskedStore(DataType, isConsecutivePtr(Ptr));
777 /// Returns true if the target machine supports masked load operation
778 /// for the given \p DataType and kind of access to \p Ptr.
779 bool isLegalMaskedLoad(Type *DataType, Value *Ptr) {
780 return TTI->isLegalMaskedLoad(DataType, isConsecutivePtr(Ptr));
782 /// Returns true if vector representation of the instruction \p I
784 bool isMaskRequired(const Instruction* I) {
785 return (MaskedOp.count(I) != 0);
788 /// Check if a single basic block loop is vectorizable.
789 /// At this point we know that this is a loop with a constant trip count
790 /// and we only need to check individual instructions.
791 bool canVectorizeInstrs();
793 /// When we vectorize loops we may change the order in which
794 /// we read and write from memory. This method checks if it is
795 /// legal to vectorize the code, considering only memory constrains.
796 /// Returns true if the loop is vectorizable
797 bool canVectorizeMemory();
799 /// Return true if we can vectorize this loop using the IF-conversion
801 bool canVectorizeWithIfConvert();
803 /// Collect the variables that need to stay uniform after vectorization.
804 void collectLoopUniforms();
806 /// Return true if all of the instructions in the block can be speculatively
807 /// executed. \p SafePtrs is a list of addresses that are known to be legal
808 /// and we know that we can read from them without segfault.
809 bool blockCanBePredicated(BasicBlock *BB, SmallPtrSetImpl<Value *> &SafePtrs);
811 /// Returns True, if 'Phi' is the kind of reduction variable for type
812 /// 'Kind'. If this is a reduction variable, it adds it to ReductionList.
813 bool AddReductionVar(PHINode *Phi, ReductionKind Kind);
814 /// Returns a struct describing if the instruction 'I' can be a reduction
815 /// variable of type 'Kind'. If the reduction is a min/max pattern of
816 /// select(icmp()) this function advances the instruction pointer 'I' from the
817 /// compare instruction to the select instruction and stores this pointer in
818 /// 'PatternLastInst' member of the returned struct.
819 ReductionInstDesc isReductionInstr(Instruction *I, ReductionKind Kind,
820 ReductionInstDesc &Desc);
821 /// Returns true if the instruction is a Select(ICmp(X, Y), X, Y) instruction
822 /// pattern corresponding to a min(X, Y) or max(X, Y).
823 static ReductionInstDesc isMinMaxSelectCmpPattern(Instruction *I,
824 ReductionInstDesc &Prev);
825 /// Returns the induction kind of Phi. This function may return NoInduction
826 /// if the PHI is not an induction variable.
827 InductionKind isInductionVariable(PHINode *Phi);
829 /// \brief Collect memory access with loop invariant strides.
831 /// Looks for accesses like "a[i * StrideA]" where "StrideA" is loop
833 void collectStridedAcccess(Value *LoadOrStoreInst);
835 /// Report an analysis message to assist the user in diagnosing loops that are
837 void emitAnalysis(Report &Message) {
838 DebugLoc DL = TheLoop->getStartLoc();
839 if (Instruction *I = Message.getInstr())
840 DL = I->getDebugLoc();
841 emitOptimizationRemarkAnalysis(TheFunction->getContext(), DEBUG_TYPE,
842 *TheFunction, DL, Message.str());
845 /// The loop that we evaluate.
849 /// DataLayout analysis.
850 const DataLayout *DL;
853 /// Target Library Info.
854 TargetLibraryInfo *TLI;
858 Function *TheFunction;
859 /// Target Transform Info
860 const TargetTransformInfo *TTI;
862 // --- vectorization state --- //
864 /// Holds the integer induction variable. This is the counter of the
867 /// Holds the reduction variables.
868 ReductionList Reductions;
869 /// Holds all of the induction variables that we found in the loop.
870 /// Notice that inductions don't need to start at zero and that induction
871 /// variables can be pointers.
872 InductionList Inductions;
873 /// Holds the widest induction type encountered.
876 /// Allowed outside users. This holds the reduction
877 /// vars which can be accessed from outside the loop.
878 SmallPtrSet<Value*, 4> AllowedExit;
879 /// This set holds the variables which are known to be uniform after
881 SmallPtrSet<Instruction*, 4> Uniforms;
882 /// We need to check that all of the pointers in this list are disjoint
884 RuntimePointerCheck PtrRtCheck;
885 /// Can we assume the absence of NaNs.
886 bool HasFunNoNaNAttr;
888 unsigned MaxSafeDepDistBytes;
890 ValueToValueMap Strides;
891 SmallPtrSet<Value *, 8> StrideSet;
893 /// While vectorizing these instructions we have to generate a
894 /// call to the appropriate masked intrinsic
895 SmallPtrSet<const Instruction*, 8> MaskedOp;
898 /// LoopVectorizationCostModel - estimates the expected speedups due to
900 /// In many cases vectorization is not profitable. This can happen because of
901 /// a number of reasons. In this class we mainly attempt to predict the
902 /// expected speedup/slowdowns due to the supported instruction set. We use the
903 /// TargetTransformInfo to query the different backends for the cost of
904 /// different operations.
905 class LoopVectorizationCostModel {
907 LoopVectorizationCostModel(Loop *L, ScalarEvolution *SE, LoopInfo *LI,
908 LoopVectorizationLegality *Legal,
909 const TargetTransformInfo &TTI,
910 const DataLayout *DL, const TargetLibraryInfo *TLI,
911 AssumptionTracker *AT, const Function *F,
912 const LoopVectorizeHints *Hints)
913 : TheLoop(L), SE(SE), LI(LI), Legal(Legal), TTI(TTI), DL(DL), TLI(TLI),
914 TheFunction(F), Hints(Hints) {
915 CodeMetrics::collectEphemeralValues(L, AT, EphValues);
918 /// Information about vectorization costs
919 struct VectorizationFactor {
920 unsigned Width; // Vector width with best cost
921 unsigned Cost; // Cost of the loop with that width
923 /// \return The most profitable vectorization factor and the cost of that VF.
924 /// This method checks every power of two up to VF. If UserVF is not ZERO
925 /// then this vectorization factor will be selected if vectorization is
927 VectorizationFactor selectVectorizationFactor(bool OptForSize);
929 /// \return The size (in bits) of the widest type in the code that
930 /// needs to be vectorized. We ignore values that remain scalar such as
931 /// 64 bit loop indices.
932 unsigned getWidestType();
934 /// \return The most profitable unroll factor.
935 /// If UserUF is non-zero then this method finds the best unroll-factor
936 /// based on register pressure and other parameters.
937 /// VF and LoopCost are the selected vectorization factor and the cost of the
939 unsigned selectUnrollFactor(bool OptForSize, unsigned VF, unsigned LoopCost);
941 /// \brief A struct that represents some properties of the register usage
943 struct RegisterUsage {
944 /// Holds the number of loop invariant values that are used in the loop.
945 unsigned LoopInvariantRegs;
946 /// Holds the maximum number of concurrent live intervals in the loop.
947 unsigned MaxLocalUsers;
948 /// Holds the number of instructions in the loop.
949 unsigned NumInstructions;
952 /// \return information about the register usage of the loop.
953 RegisterUsage calculateRegisterUsage();
956 /// Returns the expected execution cost. The unit of the cost does
957 /// not matter because we use the 'cost' units to compare different
958 /// vector widths. The cost that is returned is *not* normalized by
959 /// the factor width.
960 unsigned expectedCost(unsigned VF);
962 /// Returns the execution time cost of an instruction for a given vector
963 /// width. Vector width of one means scalar.
964 unsigned getInstructionCost(Instruction *I, unsigned VF);
966 /// A helper function for converting Scalar types to vector types.
967 /// If the incoming type is void, we return void. If the VF is 1, we return
969 static Type* ToVectorTy(Type *Scalar, unsigned VF);
971 /// Returns whether the instruction is a load or store and will be a emitted
972 /// as a vector operation.
973 bool isConsecutiveLoadOrStore(Instruction *I);
975 /// Report an analysis message to assist the user in diagnosing loops that are
977 void emitAnalysis(Report &Message) {
978 DebugLoc DL = TheLoop->getStartLoc();
979 if (Instruction *I = Message.getInstr())
980 DL = I->getDebugLoc();
981 emitOptimizationRemarkAnalysis(TheFunction->getContext(), DEBUG_TYPE,
982 *TheFunction, DL, Message.str());
985 /// Values used only by @llvm.assume calls.
986 SmallPtrSet<const Value *, 32> EphValues;
988 /// The loop that we evaluate.
992 /// Loop Info analysis.
994 /// Vectorization legality.
995 LoopVectorizationLegality *Legal;
996 /// Vector target information.
997 const TargetTransformInfo &TTI;
998 /// Target data layout information.
999 const DataLayout *DL;
1000 /// Target Library Info.
1001 const TargetLibraryInfo *TLI;
1002 const Function *TheFunction;
1003 // Loop Vectorize Hint.
1004 const LoopVectorizeHints *Hints;
1007 /// Utility class for getting and setting loop vectorizer hints in the form
1008 /// of loop metadata.
1009 /// This class keeps a number of loop annotations locally (as member variables)
1010 /// and can, upon request, write them back as metadata on the loop. It will
1011 /// initially scan the loop for existing metadata, and will update the local
1012 /// values based on information in the loop.
1013 /// We cannot write all values to metadata, as the mere presence of some info,
1014 /// for example 'force', means a decision has been made. So, we need to be
1015 /// careful NOT to add them if the user hasn't specifically asked so.
1016 class LoopVectorizeHints {
1023 /// Hint - associates name and validation with the hint value.
1026 unsigned Value; // This may have to change for non-numeric values.
1029 Hint(const char * Name, unsigned Value, HintKind Kind)
1030 : Name(Name), Value(Value), Kind(Kind) { }
1032 bool validate(unsigned Val) {
1035 return isPowerOf2_32(Val) && Val <= MaxVectorWidth;
1037 return isPowerOf2_32(Val) && Val <= MaxInterleaveFactor;
1045 /// Vectorization width.
1047 /// Vectorization interleave factor.
1049 /// Vectorization forced
1052 /// Return the loop metadata prefix.
1053 static StringRef Prefix() { return "llvm.loop."; }
1057 FK_Undefined = -1, ///< Not selected.
1058 FK_Disabled = 0, ///< Forcing disabled.
1059 FK_Enabled = 1, ///< Forcing enabled.
1062 LoopVectorizeHints(const Loop *L, bool DisableInterleaving)
1063 : Width("vectorize.width", VectorizationFactor, HK_WIDTH),
1064 Interleave("interleave.count", DisableInterleaving, HK_UNROLL),
1065 Force("vectorize.enable", FK_Undefined, HK_FORCE),
1067 // Populate values with existing loop metadata.
1068 getHintsFromMetadata();
1070 // force-vector-interleave overrides DisableInterleaving.
1071 if (VectorizationInterleave.getNumOccurrences() > 0)
1072 Interleave.Value = VectorizationInterleave;
1074 DEBUG(if (DisableInterleaving && Interleave.Value == 1) dbgs()
1075 << "LV: Interleaving disabled by the pass manager\n");
1078 /// Mark the loop L as already vectorized by setting the width to 1.
1079 void setAlreadyVectorized() {
1080 Width.Value = Interleave.Value = 1;
1081 Hint Hints[] = {Width, Interleave};
1082 writeHintsToMetadata(Hints);
1085 /// Dumps all the hint information.
1086 std::string emitRemark() const {
1088 if (Force.Value == LoopVectorizeHints::FK_Disabled)
1089 R << "vectorization is explicitly disabled";
1091 R << "use -Rpass-analysis=loop-vectorize for more info";
1092 if (Force.Value == LoopVectorizeHints::FK_Enabled) {
1093 R << " (Force=true";
1094 if (Width.Value != 0)
1095 R << ", Vector Width=" << Width.Value;
1096 if (Interleave.Value != 0)
1097 R << ", Interleave Count=" << Interleave.Value;
1105 unsigned getWidth() const { return Width.Value; }
1106 unsigned getInterleave() const { return Interleave.Value; }
1107 enum ForceKind getForce() const { return (ForceKind)Force.Value; }
1110 /// Find hints specified in the loop metadata and update local values.
1111 void getHintsFromMetadata() {
1112 MDNode *LoopID = TheLoop->getLoopID();
1116 // First operand should refer to the loop id itself.
1117 assert(LoopID->getNumOperands() > 0 && "requires at least one operand");
1118 assert(LoopID->getOperand(0) == LoopID && "invalid loop id");
1120 for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) {
1121 const MDString *S = nullptr;
1122 SmallVector<Metadata *, 4> Args;
1124 // The expected hint is either a MDString or a MDNode with the first
1125 // operand a MDString.
1126 if (const MDNode *MD = dyn_cast<MDNode>(LoopID->getOperand(i))) {
1127 if (!MD || MD->getNumOperands() == 0)
1129 S = dyn_cast<MDString>(MD->getOperand(0));
1130 for (unsigned i = 1, ie = MD->getNumOperands(); i < ie; ++i)
1131 Args.push_back(MD->getOperand(i));
1133 S = dyn_cast<MDString>(LoopID->getOperand(i));
1134 assert(Args.size() == 0 && "too many arguments for MDString");
1140 // Check if the hint starts with the loop metadata prefix.
1141 StringRef Name = S->getString();
1142 if (Args.size() == 1)
1143 setHint(Name, Args[0]);
1147 /// Checks string hint with one operand and set value if valid.
1148 void setHint(StringRef Name, Metadata *Arg) {
1149 if (!Name.startswith(Prefix()))
1151 Name = Name.substr(Prefix().size(), StringRef::npos);
1153 const ConstantInt *C = mdconst::dyn_extract<ConstantInt>(Arg);
1155 unsigned Val = C->getZExtValue();
1157 Hint *Hints[] = {&Width, &Interleave, &Force};
1158 for (auto H : Hints) {
1159 if (Name == H->Name) {
1160 if (H->validate(Val))
1163 DEBUG(dbgs() << "LV: ignoring invalid hint '" << Name << "'\n");
1169 /// Create a new hint from name / value pair.
1170 MDNode *createHintMetadata(StringRef Name, unsigned V) const {
1171 LLVMContext &Context = TheLoop->getHeader()->getContext();
1172 Metadata *MDs[] = {MDString::get(Context, Name),
1173 ConstantAsMetadata::get(
1174 ConstantInt::get(Type::getInt32Ty(Context), V))};
1175 return MDNode::get(Context, MDs);
1178 /// Matches metadata with hint name.
1179 bool matchesHintMetadataName(MDNode *Node, ArrayRef<Hint> HintTypes) {
1180 MDString* Name = dyn_cast<MDString>(Node->getOperand(0));
1184 for (auto H : HintTypes)
1185 if (Name->getString().endswith(H.Name))
1190 /// Sets current hints into loop metadata, keeping other values intact.
1191 void writeHintsToMetadata(ArrayRef<Hint> HintTypes) {
1192 if (HintTypes.size() == 0)
1195 // Reserve the first element to LoopID (see below).
1196 SmallVector<Metadata *, 4> MDs(1);
1197 // If the loop already has metadata, then ignore the existing operands.
1198 MDNode *LoopID = TheLoop->getLoopID();
1200 for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) {
1201 MDNode *Node = cast<MDNode>(LoopID->getOperand(i));
1202 // If node in update list, ignore old value.
1203 if (!matchesHintMetadataName(Node, HintTypes))
1204 MDs.push_back(Node);
1208 // Now, add the missing hints.
1209 for (auto H : HintTypes)
1210 MDs.push_back(createHintMetadata(Twine(Prefix(), H.Name).str(), H.Value));
1212 // Replace current metadata node with new one.
1213 LLVMContext &Context = TheLoop->getHeader()->getContext();
1214 MDNode *NewLoopID = MDNode::get(Context, MDs);
1215 // Set operand 0 to refer to the loop id itself.
1216 NewLoopID->replaceOperandWith(0, NewLoopID);
1218 TheLoop->setLoopID(NewLoopID);
1221 /// The loop these hints belong to.
1222 const Loop *TheLoop;
1225 static void emitMissedWarning(Function *F, Loop *L,
1226 const LoopVectorizeHints &LH) {
1227 emitOptimizationRemarkMissed(F->getContext(), DEBUG_TYPE, *F,
1228 L->getStartLoc(), LH.emitRemark());
1230 if (LH.getForce() == LoopVectorizeHints::FK_Enabled) {
1231 if (LH.getWidth() != 1)
1232 emitLoopVectorizeWarning(
1233 F->getContext(), *F, L->getStartLoc(),
1234 "failed explicitly specified loop vectorization");
1235 else if (LH.getInterleave() != 1)
1236 emitLoopInterleaveWarning(
1237 F->getContext(), *F, L->getStartLoc(),
1238 "failed explicitly specified loop interleaving");
1242 static void addInnerLoop(Loop &L, SmallVectorImpl<Loop *> &V) {
1244 return V.push_back(&L);
1246 for (Loop *InnerL : L)
1247 addInnerLoop(*InnerL, V);
1250 /// The LoopVectorize Pass.
1251 struct LoopVectorize : public FunctionPass {
1252 /// Pass identification, replacement for typeid
1255 explicit LoopVectorize(bool NoUnrolling = false, bool AlwaysVectorize = true)
1257 DisableUnrolling(NoUnrolling),
1258 AlwaysVectorize(AlwaysVectorize) {
1259 initializeLoopVectorizePass(*PassRegistry::getPassRegistry());
1262 ScalarEvolution *SE;
1263 const DataLayout *DL;
1265 TargetTransformInfo *TTI;
1267 BlockFrequencyInfo *BFI;
1268 TargetLibraryInfo *TLI;
1270 AssumptionTracker *AT;
1271 bool DisableUnrolling;
1272 bool AlwaysVectorize;
1274 BlockFrequency ColdEntryFreq;
1276 bool runOnFunction(Function &F) override {
1277 SE = &getAnalysis<ScalarEvolution>();
1278 DataLayoutPass *DLP = getAnalysisIfAvailable<DataLayoutPass>();
1279 DL = DLP ? &DLP->getDataLayout() : nullptr;
1280 LI = &getAnalysis<LoopInfo>();
1281 TTI = &getAnalysis<TargetTransformInfo>();
1282 DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree();
1283 BFI = &getAnalysis<BlockFrequencyInfo>();
1284 TLI = getAnalysisIfAvailable<TargetLibraryInfo>();
1285 AA = &getAnalysis<AliasAnalysis>();
1286 AT = &getAnalysis<AssumptionTracker>();
1288 // Compute some weights outside of the loop over the loops. Compute this
1289 // using a BranchProbability to re-use its scaling math.
1290 const BranchProbability ColdProb(1, 5); // 20%
1291 ColdEntryFreq = BlockFrequency(BFI->getEntryFreq()) * ColdProb;
1293 // If the target claims to have no vector registers don't attempt
1295 if (!TTI->getNumberOfRegisters(true))
1299 DEBUG(dbgs() << "\nLV: Not vectorizing " << F.getName()
1300 << ": Missing data layout\n");
1304 // Build up a worklist of inner-loops to vectorize. This is necessary as
1305 // the act of vectorizing or partially unrolling a loop creates new loops
1306 // and can invalidate iterators across the loops.
1307 SmallVector<Loop *, 8> Worklist;
1310 addInnerLoop(*L, Worklist);
1312 LoopsAnalyzed += Worklist.size();
1314 // Now walk the identified inner loops.
1315 bool Changed = false;
1316 while (!Worklist.empty())
1317 Changed |= processLoop(Worklist.pop_back_val());
1319 // Process each loop nest in the function.
1323 bool processLoop(Loop *L) {
1324 assert(L->empty() && "Only process inner loops.");
1327 const std::string DebugLocStr = getDebugLocString(L);
1330 DEBUG(dbgs() << "\nLV: Checking a loop in \""
1331 << L->getHeader()->getParent()->getName() << "\" from "
1332 << DebugLocStr << "\n");
1334 LoopVectorizeHints Hints(L, DisableUnrolling);
1336 DEBUG(dbgs() << "LV: Loop hints:"
1338 << (Hints.getForce() == LoopVectorizeHints::FK_Disabled
1340 : (Hints.getForce() == LoopVectorizeHints::FK_Enabled
1342 : "?")) << " width=" << Hints.getWidth()
1343 << " unroll=" << Hints.getInterleave() << "\n");
1345 // Function containing loop
1346 Function *F = L->getHeader()->getParent();
1348 // Looking at the diagnostic output is the only way to determine if a loop
1349 // was vectorized (other than looking at the IR or machine code), so it
1350 // is important to generate an optimization remark for each loop. Most of
1351 // these messages are generated by emitOptimizationRemarkAnalysis. Remarks
1352 // generated by emitOptimizationRemark and emitOptimizationRemarkMissed are
1353 // less verbose reporting vectorized loops and unvectorized loops that may
1354 // benefit from vectorization, respectively.
1356 if (Hints.getForce() == LoopVectorizeHints::FK_Disabled) {
1357 DEBUG(dbgs() << "LV: Not vectorizing: #pragma vectorize disable.\n");
1358 emitOptimizationRemarkAnalysis(F->getContext(), DEBUG_TYPE, *F,
1359 L->getStartLoc(), Hints.emitRemark());
1363 if (!AlwaysVectorize && Hints.getForce() != LoopVectorizeHints::FK_Enabled) {
1364 DEBUG(dbgs() << "LV: Not vectorizing: No #pragma vectorize enable.\n");
1365 emitOptimizationRemarkAnalysis(F->getContext(), DEBUG_TYPE, *F,
1366 L->getStartLoc(), Hints.emitRemark());
1370 if (Hints.getWidth() == 1 && Hints.getInterleave() == 1) {
1371 DEBUG(dbgs() << "LV: Not vectorizing: Disabled/already vectorized.\n");
1372 emitOptimizationRemarkAnalysis(
1373 F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(),
1374 "loop not vectorized: vector width and interleave count are "
1375 "explicitly set to 1");
1379 // Check the loop for a trip count threshold:
1380 // do not vectorize loops with a tiny trip count.
1381 const unsigned TC = SE->getSmallConstantTripCount(L);
1382 if (TC > 0u && TC < TinyTripCountVectorThreshold) {
1383 DEBUG(dbgs() << "LV: Found a loop with a very small trip count. "
1384 << "This loop is not worth vectorizing.");
1385 if (Hints.getForce() == LoopVectorizeHints::FK_Enabled)
1386 DEBUG(dbgs() << " But vectorizing was explicitly forced.\n");
1388 DEBUG(dbgs() << "\n");
1389 emitOptimizationRemarkAnalysis(
1390 F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(),
1391 "vectorization is not beneficial and is not explicitly forced");
1396 // Check if it is legal to vectorize the loop.
1397 LoopVectorizationLegality LVL(L, SE, DL, DT, TLI, AA, F, TTI);
1398 if (!LVL.canVectorize()) {
1399 DEBUG(dbgs() << "LV: Not vectorizing: Cannot prove legality.\n");
1400 emitMissedWarning(F, L, Hints);
1404 // Use the cost model.
1405 LoopVectorizationCostModel CM(L, SE, LI, &LVL, *TTI, DL, TLI, AT, F,
1408 // Check the function attributes to find out if this function should be
1409 // optimized for size.
1410 bool OptForSize = Hints.getForce() != LoopVectorizeHints::FK_Enabled &&
1411 F->hasFnAttribute(Attribute::OptimizeForSize);
1413 // Compute the weighted frequency of this loop being executed and see if it
1414 // is less than 20% of the function entry baseline frequency. Note that we
1415 // always have a canonical loop here because we think we *can* vectoriez.
1416 // FIXME: This is hidden behind a flag due to pervasive problems with
1417 // exactly what block frequency models.
1418 if (LoopVectorizeWithBlockFrequency) {
1419 BlockFrequency LoopEntryFreq = BFI->getBlockFreq(L->getLoopPreheader());
1420 if (Hints.getForce() != LoopVectorizeHints::FK_Enabled &&
1421 LoopEntryFreq < ColdEntryFreq)
1425 // Check the function attributes to see if implicit floats are allowed.a
1426 // FIXME: This check doesn't seem possibly correct -- what if the loop is
1427 // an integer loop and the vector instructions selected are purely integer
1428 // vector instructions?
1429 if (F->hasFnAttribute(Attribute::NoImplicitFloat)) {
1430 DEBUG(dbgs() << "LV: Can't vectorize when the NoImplicitFloat"
1431 "attribute is used.\n");
1432 emitOptimizationRemarkAnalysis(
1433 F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(),
1434 "loop not vectorized due to NoImplicitFloat attribute");
1435 emitMissedWarning(F, L, Hints);
1439 // Select the optimal vectorization factor.
1440 const LoopVectorizationCostModel::VectorizationFactor VF =
1441 CM.selectVectorizationFactor(OptForSize);
1443 // Select the unroll factor.
1445 CM.selectUnrollFactor(OptForSize, VF.Width, VF.Cost);
1447 DEBUG(dbgs() << "LV: Found a vectorizable loop (" << VF.Width << ") in "
1448 << DebugLocStr << '\n');
1449 DEBUG(dbgs() << "LV: Unroll Factor is " << UF << '\n');
1451 if (VF.Width == 1) {
1452 DEBUG(dbgs() << "LV: Vectorization is possible but not beneficial\n");
1455 emitOptimizationRemarkAnalysis(
1456 F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(),
1457 "not beneficial to vectorize and user disabled interleaving");
1460 DEBUG(dbgs() << "LV: Trying to at least unroll the loops.\n");
1462 // Report the unrolling decision.
1463 emitOptimizationRemark(F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(),
1464 Twine("unrolled with interleaving factor " +
1466 " (vectorization not beneficial)"));
1468 // We decided not to vectorize, but we may want to unroll.
1470 InnerLoopUnroller Unroller(L, SE, LI, DT, DL, TLI, UF);
1471 Unroller.vectorize(&LVL);
1473 // If we decided that it is *legal* to vectorize the loop then do it.
1474 InnerLoopVectorizer LB(L, SE, LI, DT, DL, TLI, VF.Width, UF);
1478 // Report the vectorization decision.
1479 emitOptimizationRemark(
1480 F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(),
1481 Twine("vectorized loop (vectorization factor: ") + Twine(VF.Width) +
1482 ", unrolling interleave factor: " + Twine(UF) + ")");
1485 // Mark the loop as already vectorized to avoid vectorizing again.
1486 Hints.setAlreadyVectorized();
1488 DEBUG(verifyFunction(*L->getHeader()->getParent()));
1492 void getAnalysisUsage(AnalysisUsage &AU) const override {
1493 AU.addRequired<AssumptionTracker>();
1494 AU.addRequiredID(LoopSimplifyID);
1495 AU.addRequiredID(LCSSAID);
1496 AU.addRequired<BlockFrequencyInfo>();
1497 AU.addRequired<DominatorTreeWrapperPass>();
1498 AU.addRequired<LoopInfo>();
1499 AU.addRequired<ScalarEvolution>();
1500 AU.addRequired<TargetTransformInfo>();
1501 AU.addRequired<AliasAnalysis>();
1502 AU.addPreserved<LoopInfo>();
1503 AU.addPreserved<DominatorTreeWrapperPass>();
1504 AU.addPreserved<AliasAnalysis>();
1509 } // end anonymous namespace
1511 //===----------------------------------------------------------------------===//
1512 // Implementation of LoopVectorizationLegality, InnerLoopVectorizer and
1513 // LoopVectorizationCostModel.
1514 //===----------------------------------------------------------------------===//
1516 static Value *stripIntegerCast(Value *V) {
1517 if (CastInst *CI = dyn_cast<CastInst>(V))
1518 if (CI->getOperand(0)->getType()->isIntegerTy())
1519 return CI->getOperand(0);
1523 ///\brief Replaces the symbolic stride in a pointer SCEV expression by one.
1525 /// If \p OrigPtr is not null, use it to look up the stride value instead of
1527 static const SCEV *replaceSymbolicStrideSCEV(ScalarEvolution *SE,
1528 ValueToValueMap &PtrToStride,
1529 Value *Ptr, Value *OrigPtr = nullptr) {
1531 const SCEV *OrigSCEV = SE->getSCEV(Ptr);
1533 // If there is an entry in the map return the SCEV of the pointer with the
1534 // symbolic stride replaced by one.
1535 ValueToValueMap::iterator SI = PtrToStride.find(OrigPtr ? OrigPtr : Ptr);
1536 if (SI != PtrToStride.end()) {
1537 Value *StrideVal = SI->second;
1540 StrideVal = stripIntegerCast(StrideVal);
1542 // Replace symbolic stride by one.
1543 Value *One = ConstantInt::get(StrideVal->getType(), 1);
1544 ValueToValueMap RewriteMap;
1545 RewriteMap[StrideVal] = One;
1548 SCEVParameterRewriter::rewrite(OrigSCEV, *SE, RewriteMap, true);
1549 DEBUG(dbgs() << "LV: Replacing SCEV: " << *OrigSCEV << " by: " << *ByOne
1554 // Otherwise, just return the SCEV of the original pointer.
1555 return SE->getSCEV(Ptr);
1558 void LoopVectorizationLegality::RuntimePointerCheck::insert(
1559 ScalarEvolution *SE, Loop *Lp, Value *Ptr, bool WritePtr, unsigned DepSetId,
1560 unsigned ASId, ValueToValueMap &Strides) {
1561 // Get the stride replaced scev.
1562 const SCEV *Sc = replaceSymbolicStrideSCEV(SE, Strides, Ptr);
1563 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Sc);
1564 assert(AR && "Invalid addrec expression");
1565 const SCEV *Ex = SE->getBackedgeTakenCount(Lp);
1566 const SCEV *ScEnd = AR->evaluateAtIteration(Ex, *SE);
1567 Pointers.push_back(Ptr);
1568 Starts.push_back(AR->getStart());
1569 Ends.push_back(ScEnd);
1570 IsWritePtr.push_back(WritePtr);
1571 DependencySetId.push_back(DepSetId);
1572 AliasSetId.push_back(ASId);
1575 Value *InnerLoopVectorizer::getBroadcastInstrs(Value *V) {
1576 // We need to place the broadcast of invariant variables outside the loop.
1577 Instruction *Instr = dyn_cast<Instruction>(V);
1579 (Instr && std::find(LoopVectorBody.begin(), LoopVectorBody.end(),
1580 Instr->getParent()) != LoopVectorBody.end());
1581 bool Invariant = OrigLoop->isLoopInvariant(V) && !NewInstr;
1583 // Place the code for broadcasting invariant variables in the new preheader.
1584 IRBuilder<>::InsertPointGuard Guard(Builder);
1586 Builder.SetInsertPoint(LoopVectorPreHeader->getTerminator());
1588 // Broadcast the scalar into all locations in the vector.
1589 Value *Shuf = Builder.CreateVectorSplat(VF, V, "broadcast");
1594 Value *InnerLoopVectorizer::getConsecutiveVector(Value* Val, int StartIdx,
1596 assert(Val->getType()->isVectorTy() && "Must be a vector");
1597 assert(Val->getType()->getScalarType()->isIntegerTy() &&
1598 "Elem must be an integer");
1599 // Create the types.
1600 Type *ITy = Val->getType()->getScalarType();
1601 VectorType *Ty = cast<VectorType>(Val->getType());
1602 int VLen = Ty->getNumElements();
1603 SmallVector<Constant*, 8> Indices;
1605 // Create a vector of consecutive numbers from zero to VF.
1606 for (int i = 0; i < VLen; ++i) {
1607 int64_t Idx = Negate ? (-i) : i;
1608 Indices.push_back(ConstantInt::get(ITy, StartIdx + Idx, Negate));
1611 // Add the consecutive indices to the vector value.
1612 Constant *Cv = ConstantVector::get(Indices);
1613 assert(Cv->getType() == Val->getType() && "Invalid consecutive vec");
1614 return Builder.CreateAdd(Val, Cv, "induction");
1617 /// \brief Find the operand of the GEP that should be checked for consecutive
1618 /// stores. This ignores trailing indices that have no effect on the final
1620 static unsigned getGEPInductionOperand(const DataLayout *DL,
1621 const GetElementPtrInst *Gep) {
1622 unsigned LastOperand = Gep->getNumOperands() - 1;
1623 unsigned GEPAllocSize = DL->getTypeAllocSize(
1624 cast<PointerType>(Gep->getType()->getScalarType())->getElementType());
1626 // Walk backwards and try to peel off zeros.
1627 while (LastOperand > 1 && match(Gep->getOperand(LastOperand), m_Zero())) {
1628 // Find the type we're currently indexing into.
1629 gep_type_iterator GEPTI = gep_type_begin(Gep);
1630 std::advance(GEPTI, LastOperand - 1);
1632 // If it's a type with the same allocation size as the result of the GEP we
1633 // can peel off the zero index.
1634 if (DL->getTypeAllocSize(*GEPTI) != GEPAllocSize)
1642 int LoopVectorizationLegality::isConsecutivePtr(Value *Ptr) {
1643 assert(Ptr->getType()->isPointerTy() && "Unexpected non-ptr");
1644 // Make sure that the pointer does not point to structs.
1645 if (Ptr->getType()->getPointerElementType()->isAggregateType())
1648 // If this value is a pointer induction variable we know it is consecutive.
1649 PHINode *Phi = dyn_cast_or_null<PHINode>(Ptr);
1650 if (Phi && Inductions.count(Phi)) {
1651 InductionInfo II = Inductions[Phi];
1652 if (IK_PtrInduction == II.IK)
1654 else if (IK_ReversePtrInduction == II.IK)
1658 GetElementPtrInst *Gep = dyn_cast_or_null<GetElementPtrInst>(Ptr);
1662 unsigned NumOperands = Gep->getNumOperands();
1663 Value *GpPtr = Gep->getPointerOperand();
1664 // If this GEP value is a consecutive pointer induction variable and all of
1665 // the indices are constant then we know it is consecutive. We can
1666 Phi = dyn_cast<PHINode>(GpPtr);
1667 if (Phi && Inductions.count(Phi)) {
1669 // Make sure that the pointer does not point to structs.
1670 PointerType *GepPtrType = cast<PointerType>(GpPtr->getType());
1671 if (GepPtrType->getElementType()->isAggregateType())
1674 // Make sure that all of the index operands are loop invariant.
1675 for (unsigned i = 1; i < NumOperands; ++i)
1676 if (!SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop))
1679 InductionInfo II = Inductions[Phi];
1680 if (IK_PtrInduction == II.IK)
1682 else if (IK_ReversePtrInduction == II.IK)
1686 unsigned InductionOperand = getGEPInductionOperand(DL, Gep);
1688 // Check that all of the gep indices are uniform except for our induction
1690 for (unsigned i = 0; i != NumOperands; ++i)
1691 if (i != InductionOperand &&
1692 !SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop))
1695 // We can emit wide load/stores only if the last non-zero index is the
1696 // induction variable.
1697 const SCEV *Last = nullptr;
1698 if (!Strides.count(Gep))
1699 Last = SE->getSCEV(Gep->getOperand(InductionOperand));
1701 // Because of the multiplication by a stride we can have a s/zext cast.
1702 // We are going to replace this stride by 1 so the cast is safe to ignore.
1704 // %indvars.iv = phi i64 [ 0, %entry ], [ %indvars.iv.next, %for.body ]
1705 // %0 = trunc i64 %indvars.iv to i32
1706 // %mul = mul i32 %0, %Stride1
1707 // %idxprom = zext i32 %mul to i64 << Safe cast.
1708 // %arrayidx = getelementptr inbounds i32* %B, i64 %idxprom
1710 Last = replaceSymbolicStrideSCEV(SE, Strides,
1711 Gep->getOperand(InductionOperand), Gep);
1712 if (const SCEVCastExpr *C = dyn_cast<SCEVCastExpr>(Last))
1714 (C->getSCEVType() == scSignExtend || C->getSCEVType() == scZeroExtend)
1718 if (const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Last)) {
1719 const SCEV *Step = AR->getStepRecurrence(*SE);
1721 // The memory is consecutive because the last index is consecutive
1722 // and all other indices are loop invariant.
1725 if (Step->isAllOnesValue())
1732 bool LoopVectorizationLegality::isUniform(Value *V) {
1733 return (SE->isLoopInvariant(SE->getSCEV(V), TheLoop));
1736 InnerLoopVectorizer::VectorParts&
1737 InnerLoopVectorizer::getVectorValue(Value *V) {
1738 assert(V != Induction && "The new induction variable should not be used.");
1739 assert(!V->getType()->isVectorTy() && "Can't widen a vector");
1741 // If we have a stride that is replaced by one, do it here.
1742 if (Legal->hasStride(V))
1743 V = ConstantInt::get(V->getType(), 1);
1745 // If we have this scalar in the map, return it.
1746 if (WidenMap.has(V))
1747 return WidenMap.get(V);
1749 // If this scalar is unknown, assume that it is a constant or that it is
1750 // loop invariant. Broadcast V and save the value for future uses.
1751 Value *B = getBroadcastInstrs(V);
1752 return WidenMap.splat(V, B);
1755 Value *InnerLoopVectorizer::reverseVector(Value *Vec) {
1756 assert(Vec->getType()->isVectorTy() && "Invalid type");
1757 SmallVector<Constant*, 8> ShuffleMask;
1758 for (unsigned i = 0; i < VF; ++i)
1759 ShuffleMask.push_back(Builder.getInt32(VF - i - 1));
1761 return Builder.CreateShuffleVector(Vec, UndefValue::get(Vec->getType()),
1762 ConstantVector::get(ShuffleMask),
1766 void InnerLoopVectorizer::vectorizeMemoryInstruction(Instruction *Instr) {
1767 // Attempt to issue a wide load.
1768 LoadInst *LI = dyn_cast<LoadInst>(Instr);
1769 StoreInst *SI = dyn_cast<StoreInst>(Instr);
1771 assert((LI || SI) && "Invalid Load/Store instruction");
1773 Type *ScalarDataTy = LI ? LI->getType() : SI->getValueOperand()->getType();
1774 Type *DataTy = VectorType::get(ScalarDataTy, VF);
1775 Value *Ptr = LI ? LI->getPointerOperand() : SI->getPointerOperand();
1776 unsigned Alignment = LI ? LI->getAlignment() : SI->getAlignment();
1777 // An alignment of 0 means target abi alignment. We need to use the scalar's
1778 // target abi alignment in such a case.
1780 Alignment = DL->getABITypeAlignment(ScalarDataTy);
1781 unsigned AddressSpace = Ptr->getType()->getPointerAddressSpace();
1782 unsigned ScalarAllocatedSize = DL->getTypeAllocSize(ScalarDataTy);
1783 unsigned VectorElementSize = DL->getTypeStoreSize(DataTy)/VF;
1785 if (SI && Legal->blockNeedsPredication(SI->getParent()) &&
1786 !Legal->isMaskRequired(SI))
1787 return scalarizeInstruction(Instr, true);
1789 if (ScalarAllocatedSize != VectorElementSize)
1790 return scalarizeInstruction(Instr);
1792 // If the pointer is loop invariant or if it is non-consecutive,
1793 // scalarize the load.
1794 int ConsecutiveStride = Legal->isConsecutivePtr(Ptr);
1795 bool Reverse = ConsecutiveStride < 0;
1796 bool UniformLoad = LI && Legal->isUniform(Ptr);
1797 if (!ConsecutiveStride || UniformLoad)
1798 return scalarizeInstruction(Instr);
1800 Constant *Zero = Builder.getInt32(0);
1801 VectorParts &Entry = WidenMap.get(Instr);
1803 // Handle consecutive loads/stores.
1804 GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr);
1805 if (Gep && Legal->isInductionVariable(Gep->getPointerOperand())) {
1806 setDebugLocFromInst(Builder, Gep);
1807 Value *PtrOperand = Gep->getPointerOperand();
1808 Value *FirstBasePtr = getVectorValue(PtrOperand)[0];
1809 FirstBasePtr = Builder.CreateExtractElement(FirstBasePtr, Zero);
1811 // Create the new GEP with the new induction variable.
1812 GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone());
1813 Gep2->setOperand(0, FirstBasePtr);
1814 Gep2->setName("gep.indvar.base");
1815 Ptr = Builder.Insert(Gep2);
1817 setDebugLocFromInst(Builder, Gep);
1818 assert(SE->isLoopInvariant(SE->getSCEV(Gep->getPointerOperand()),
1819 OrigLoop) && "Base ptr must be invariant");
1821 // The last index does not have to be the induction. It can be
1822 // consecutive and be a function of the index. For example A[I+1];
1823 unsigned NumOperands = Gep->getNumOperands();
1824 unsigned InductionOperand = getGEPInductionOperand(DL, Gep);
1825 // Create the new GEP with the new induction variable.
1826 GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone());
1828 for (unsigned i = 0; i < NumOperands; ++i) {
1829 Value *GepOperand = Gep->getOperand(i);
1830 Instruction *GepOperandInst = dyn_cast<Instruction>(GepOperand);
1832 // Update last index or loop invariant instruction anchored in loop.
1833 if (i == InductionOperand ||
1834 (GepOperandInst && OrigLoop->contains(GepOperandInst))) {
1835 assert((i == InductionOperand ||
1836 SE->isLoopInvariant(SE->getSCEV(GepOperandInst), OrigLoop)) &&
1837 "Must be last index or loop invariant");
1839 VectorParts &GEPParts = getVectorValue(GepOperand);
1840 Value *Index = GEPParts[0];
1841 Index = Builder.CreateExtractElement(Index, Zero);
1842 Gep2->setOperand(i, Index);
1843 Gep2->setName("gep.indvar.idx");
1846 Ptr = Builder.Insert(Gep2);
1848 // Use the induction element ptr.
1849 assert(isa<PHINode>(Ptr) && "Invalid induction ptr");
1850 setDebugLocFromInst(Builder, Ptr);
1851 VectorParts &PtrVal = getVectorValue(Ptr);
1852 Ptr = Builder.CreateExtractElement(PtrVal[0], Zero);
1857 assert(!Legal->isUniform(SI->getPointerOperand()) &&
1858 "We do not allow storing to uniform addresses");
1859 setDebugLocFromInst(Builder, SI);
1860 // We don't want to update the value in the map as it might be used in
1861 // another expression. So don't use a reference type for "StoredVal".
1862 VectorParts StoredVal = getVectorValue(SI->getValueOperand());
1864 for (unsigned Part = 0; Part < UF; ++Part) {
1865 // Calculate the pointer for the specific unroll-part.
1866 Value *PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(Part * VF));
1869 // If we store to reverse consecutive memory locations then we need
1870 // to reverse the order of elements in the stored value.
1871 StoredVal[Part] = reverseVector(StoredVal[Part]);
1872 // If the address is consecutive but reversed, then the
1873 // wide store needs to start at the last vector element.
1874 PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(-Part * VF));
1875 PartPtr = Builder.CreateGEP(PartPtr, Builder.getInt32(1 - VF));
1878 Value *VecPtr = Builder.CreateBitCast(PartPtr,
1879 DataTy->getPointerTo(AddressSpace));
1882 if (Legal->isMaskRequired(SI)) {
1883 VectorParts Cond = createBlockInMask(SI->getParent());
1884 SmallVector <Value *, 8> Ops;
1885 Ops.push_back(StoredVal[Part]);
1886 Ops.push_back(VecPtr);
1887 Ops.push_back(Builder.getInt32(Alignment));
1888 Ops.push_back(Cond[Part]);
1889 NewSI = Builder.CreateMaskedStore(Ops);
1892 NewSI = Builder.CreateAlignedStore(StoredVal[Part], VecPtr, Alignment);
1893 propagateMetadata(NewSI, SI);
1899 assert(LI && "Must have a load instruction");
1900 setDebugLocFromInst(Builder, LI);
1901 for (unsigned Part = 0; Part < UF; ++Part) {
1902 // Calculate the pointer for the specific unroll-part.
1903 Value *PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(Part * VF));
1906 // If the address is consecutive but reversed, then the
1907 // wide load needs to start at the last vector element.
1908 PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(-Part * VF));
1909 PartPtr = Builder.CreateGEP(PartPtr, Builder.getInt32(1 - VF));
1913 Value *VecPtr = Builder.CreateBitCast(PartPtr,
1914 DataTy->getPointerTo(AddressSpace));
1915 if (Legal->isMaskRequired(LI)) {
1916 VectorParts SrcMask = createBlockInMask(LI->getParent());
1917 SmallVector <Value *, 8> Ops;
1918 Ops.push_back(VecPtr);
1919 Ops.push_back(Builder.getInt32(Alignment));
1920 Ops.push_back(SrcMask[Part]);
1921 Ops.push_back(UndefValue::get(DataTy));
1922 NewLI = Builder.CreateMaskedLoad(Ops);
1925 NewLI = Builder.CreateAlignedLoad(VecPtr, Alignment, "wide.load");
1927 propagateMetadata(NewLI, LI);
1928 Entry[Part] = Reverse ? reverseVector(NewLI) : NewLI;
1932 void InnerLoopVectorizer::scalarizeInstruction(Instruction *Instr, bool IfPredicateStore) {
1933 assert(!Instr->getType()->isAggregateType() && "Can't handle vectors");
1934 // Holds vector parameters or scalars, in case of uniform vals.
1935 SmallVector<VectorParts, 4> Params;
1937 setDebugLocFromInst(Builder, Instr);
1939 // Find all of the vectorized parameters.
1940 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
1941 Value *SrcOp = Instr->getOperand(op);
1943 // If we are accessing the old induction variable, use the new one.
1944 if (SrcOp == OldInduction) {
1945 Params.push_back(getVectorValue(SrcOp));
1949 // Try using previously calculated values.
1950 Instruction *SrcInst = dyn_cast<Instruction>(SrcOp);
1952 // If the src is an instruction that appeared earlier in the basic block
1953 // then it should already be vectorized.
1954 if (SrcInst && OrigLoop->contains(SrcInst)) {
1955 assert(WidenMap.has(SrcInst) && "Source operand is unavailable");
1956 // The parameter is a vector value from earlier.
1957 Params.push_back(WidenMap.get(SrcInst));
1959 // The parameter is a scalar from outside the loop. Maybe even a constant.
1960 VectorParts Scalars;
1961 Scalars.append(UF, SrcOp);
1962 Params.push_back(Scalars);
1966 assert(Params.size() == Instr->getNumOperands() &&
1967 "Invalid number of operands");
1969 // Does this instruction return a value ?
1970 bool IsVoidRetTy = Instr->getType()->isVoidTy();
1972 Value *UndefVec = IsVoidRetTy ? nullptr :
1973 UndefValue::get(VectorType::get(Instr->getType(), VF));
1974 // Create a new entry in the WidenMap and initialize it to Undef or Null.
1975 VectorParts &VecResults = WidenMap.splat(Instr, UndefVec);
1977 Instruction *InsertPt = Builder.GetInsertPoint();
1978 BasicBlock *IfBlock = Builder.GetInsertBlock();
1979 BasicBlock *CondBlock = nullptr;
1982 Loop *VectorLp = nullptr;
1983 if (IfPredicateStore) {
1984 assert(Instr->getParent()->getSinglePredecessor() &&
1985 "Only support single predecessor blocks");
1986 Cond = createEdgeMask(Instr->getParent()->getSinglePredecessor(),
1987 Instr->getParent());
1988 VectorLp = LI->getLoopFor(IfBlock);
1989 assert(VectorLp && "Must have a loop for this block");
1992 // For each vector unroll 'part':
1993 for (unsigned Part = 0; Part < UF; ++Part) {
1994 // For each scalar that we create:
1995 for (unsigned Width = 0; Width < VF; ++Width) {
1998 Value *Cmp = nullptr;
1999 if (IfPredicateStore) {
2000 Cmp = Builder.CreateExtractElement(Cond[Part], Builder.getInt32(Width));
2001 Cmp = Builder.CreateICmp(ICmpInst::ICMP_EQ, Cmp, ConstantInt::get(Cmp->getType(), 1));
2002 CondBlock = IfBlock->splitBasicBlock(InsertPt, "cond.store");
2003 LoopVectorBody.push_back(CondBlock);
2004 VectorLp->addBasicBlockToLoop(CondBlock, LI->getBase());
2005 // Update Builder with newly created basic block.
2006 Builder.SetInsertPoint(InsertPt);
2009 Instruction *Cloned = Instr->clone();
2011 Cloned->setName(Instr->getName() + ".cloned");
2012 // Replace the operands of the cloned instructions with extracted scalars.
2013 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
2014 Value *Op = Params[op][Part];
2015 // Param is a vector. Need to extract the right lane.
2016 if (Op->getType()->isVectorTy())
2017 Op = Builder.CreateExtractElement(Op, Builder.getInt32(Width));
2018 Cloned->setOperand(op, Op);
2021 // Place the cloned scalar in the new loop.
2022 Builder.Insert(Cloned);
2024 // If the original scalar returns a value we need to place it in a vector
2025 // so that future users will be able to use it.
2027 VecResults[Part] = Builder.CreateInsertElement(VecResults[Part], Cloned,
2028 Builder.getInt32(Width));
2030 if (IfPredicateStore) {
2031 BasicBlock *NewIfBlock = CondBlock->splitBasicBlock(InsertPt, "else");
2032 LoopVectorBody.push_back(NewIfBlock);
2033 VectorLp->addBasicBlockToLoop(NewIfBlock, LI->getBase());
2034 Builder.SetInsertPoint(InsertPt);
2035 Instruction *OldBr = IfBlock->getTerminator();
2036 BranchInst::Create(CondBlock, NewIfBlock, Cmp, OldBr);
2037 OldBr->eraseFromParent();
2038 IfBlock = NewIfBlock;
2044 static Instruction *getFirstInst(Instruction *FirstInst, Value *V,
2048 if (Instruction *I = dyn_cast<Instruction>(V))
2049 return I->getParent() == Loc->getParent() ? I : nullptr;
2053 std::pair<Instruction *, Instruction *>
2054 InnerLoopVectorizer::addStrideCheck(Instruction *Loc) {
2055 Instruction *tnullptr = nullptr;
2056 if (!Legal->mustCheckStrides())
2057 return std::pair<Instruction *, Instruction *>(tnullptr, tnullptr);
2059 IRBuilder<> ChkBuilder(Loc);
2062 Value *Check = nullptr;
2063 Instruction *FirstInst = nullptr;
2064 for (SmallPtrSet<Value *, 8>::iterator SI = Legal->strides_begin(),
2065 SE = Legal->strides_end();
2067 Value *Ptr = stripIntegerCast(*SI);
2068 Value *C = ChkBuilder.CreateICmpNE(Ptr, ConstantInt::get(Ptr->getType(), 1),
2070 // Store the first instruction we create.
2071 FirstInst = getFirstInst(FirstInst, C, Loc);
2073 Check = ChkBuilder.CreateOr(Check, C);
2078 // We have to do this trickery because the IRBuilder might fold the check to a
2079 // constant expression in which case there is no Instruction anchored in a
2081 LLVMContext &Ctx = Loc->getContext();
2082 Instruction *TheCheck =
2083 BinaryOperator::CreateAnd(Check, ConstantInt::getTrue(Ctx));
2084 ChkBuilder.Insert(TheCheck, "stride.not.one");
2085 FirstInst = getFirstInst(FirstInst, TheCheck, Loc);
2087 return std::make_pair(FirstInst, TheCheck);
2090 std::pair<Instruction *, Instruction *>
2091 InnerLoopVectorizer::addRuntimeCheck(Instruction *Loc) {
2092 LoopVectorizationLegality::RuntimePointerCheck *PtrRtCheck =
2093 Legal->getRuntimePointerCheck();
2095 Instruction *tnullptr = nullptr;
2096 if (!PtrRtCheck->Need)
2097 return std::pair<Instruction *, Instruction *>(tnullptr, tnullptr);
2099 unsigned NumPointers = PtrRtCheck->Pointers.size();
2100 SmallVector<TrackingVH<Value> , 2> Starts;
2101 SmallVector<TrackingVH<Value> , 2> Ends;
2103 LLVMContext &Ctx = Loc->getContext();
2104 SCEVExpander Exp(*SE, "induction");
2105 Instruction *FirstInst = nullptr;
2107 for (unsigned i = 0; i < NumPointers; ++i) {
2108 Value *Ptr = PtrRtCheck->Pointers[i];
2109 const SCEV *Sc = SE->getSCEV(Ptr);
2111 if (SE->isLoopInvariant(Sc, OrigLoop)) {
2112 DEBUG(dbgs() << "LV: Adding RT check for a loop invariant ptr:" <<
2114 Starts.push_back(Ptr);
2115 Ends.push_back(Ptr);
2117 DEBUG(dbgs() << "LV: Adding RT check for range:" << *Ptr << '\n');
2118 unsigned AS = Ptr->getType()->getPointerAddressSpace();
2120 // Use this type for pointer arithmetic.
2121 Type *PtrArithTy = Type::getInt8PtrTy(Ctx, AS);
2123 Value *Start = Exp.expandCodeFor(PtrRtCheck->Starts[i], PtrArithTy, Loc);
2124 Value *End = Exp.expandCodeFor(PtrRtCheck->Ends[i], PtrArithTy, Loc);
2125 Starts.push_back(Start);
2126 Ends.push_back(End);
2130 IRBuilder<> ChkBuilder(Loc);
2131 // Our instructions might fold to a constant.
2132 Value *MemoryRuntimeCheck = nullptr;
2133 for (unsigned i = 0; i < NumPointers; ++i) {
2134 for (unsigned j = i+1; j < NumPointers; ++j) {
2135 // No need to check if two readonly pointers intersect.
2136 if (!PtrRtCheck->IsWritePtr[i] && !PtrRtCheck->IsWritePtr[j])
2139 // Only need to check pointers between two different dependency sets.
2140 if (PtrRtCheck->DependencySetId[i] == PtrRtCheck->DependencySetId[j])
2142 // Only need to check pointers in the same alias set.
2143 if (PtrRtCheck->AliasSetId[i] != PtrRtCheck->AliasSetId[j])
2146 unsigned AS0 = Starts[i]->getType()->getPointerAddressSpace();
2147 unsigned AS1 = Starts[j]->getType()->getPointerAddressSpace();
2149 assert((AS0 == Ends[j]->getType()->getPointerAddressSpace()) &&
2150 (AS1 == Ends[i]->getType()->getPointerAddressSpace()) &&
2151 "Trying to bounds check pointers with different address spaces");
2153 Type *PtrArithTy0 = Type::getInt8PtrTy(Ctx, AS0);
2154 Type *PtrArithTy1 = Type::getInt8PtrTy(Ctx, AS1);
2156 Value *Start0 = ChkBuilder.CreateBitCast(Starts[i], PtrArithTy0, "bc");
2157 Value *Start1 = ChkBuilder.CreateBitCast(Starts[j], PtrArithTy1, "bc");
2158 Value *End0 = ChkBuilder.CreateBitCast(Ends[i], PtrArithTy1, "bc");
2159 Value *End1 = ChkBuilder.CreateBitCast(Ends[j], PtrArithTy0, "bc");
2161 Value *Cmp0 = ChkBuilder.CreateICmpULE(Start0, End1, "bound0");
2162 FirstInst = getFirstInst(FirstInst, Cmp0, Loc);
2163 Value *Cmp1 = ChkBuilder.CreateICmpULE(Start1, End0, "bound1");
2164 FirstInst = getFirstInst(FirstInst, Cmp1, Loc);
2165 Value *IsConflict = ChkBuilder.CreateAnd(Cmp0, Cmp1, "found.conflict");
2166 FirstInst = getFirstInst(FirstInst, IsConflict, Loc);
2167 if (MemoryRuntimeCheck) {
2168 IsConflict = ChkBuilder.CreateOr(MemoryRuntimeCheck, IsConflict,
2170 FirstInst = getFirstInst(FirstInst, IsConflict, Loc);
2172 MemoryRuntimeCheck = IsConflict;
2176 // We have to do this trickery because the IRBuilder might fold the check to a
2177 // constant expression in which case there is no Instruction anchored in a
2179 Instruction *Check = BinaryOperator::CreateAnd(MemoryRuntimeCheck,
2180 ConstantInt::getTrue(Ctx));
2181 ChkBuilder.Insert(Check, "memcheck.conflict");
2182 FirstInst = getFirstInst(FirstInst, Check, Loc);
2183 return std::make_pair(FirstInst, Check);
2186 void InnerLoopVectorizer::createEmptyLoop() {
2188 In this function we generate a new loop. The new loop will contain
2189 the vectorized instructions while the old loop will continue to run the
2192 [ ] <-- Back-edge taken count overflow check.
2195 | [ ] <-- vector loop bypass (may consist of multiple blocks).
2198 || [ ] <-- vector pre header.
2202 || [ ]_| <-- vector loop.
2205 | >[ ] <--- middle-block.
2208 -|- >[ ] <--- new preheader.
2212 | [ ]_| <-- old scalar loop to handle remainder.
2215 >[ ] <-- exit block.
2219 BasicBlock *OldBasicBlock = OrigLoop->getHeader();
2220 BasicBlock *BypassBlock = OrigLoop->getLoopPreheader();
2221 BasicBlock *ExitBlock = OrigLoop->getExitBlock();
2222 assert(BypassBlock && "Invalid loop structure");
2223 assert(ExitBlock && "Must have an exit block");
2225 // Some loops have a single integer induction variable, while other loops
2226 // don't. One example is c++ iterators that often have multiple pointer
2227 // induction variables. In the code below we also support a case where we
2228 // don't have a single induction variable.
2229 OldInduction = Legal->getInduction();
2230 Type *IdxTy = Legal->getWidestInductionType();
2232 // Find the loop boundaries.
2233 const SCEV *ExitCount = SE->getBackedgeTakenCount(OrigLoop);
2234 assert(ExitCount != SE->getCouldNotCompute() && "Invalid loop count");
2236 // The exit count might have the type of i64 while the phi is i32. This can
2237 // happen if we have an induction variable that is sign extended before the
2238 // compare. The only way that we get a backedge taken count is that the
2239 // induction variable was signed and as such will not overflow. In such a case
2240 // truncation is legal.
2241 if (ExitCount->getType()->getPrimitiveSizeInBits() >
2242 IdxTy->getPrimitiveSizeInBits())
2243 ExitCount = SE->getTruncateOrNoop(ExitCount, IdxTy);
2245 const SCEV *BackedgeTakeCount = SE->getNoopOrZeroExtend(ExitCount, IdxTy);
2246 // Get the total trip count from the count by adding 1.
2247 ExitCount = SE->getAddExpr(BackedgeTakeCount,
2248 SE->getConstant(BackedgeTakeCount->getType(), 1));
2250 // Expand the trip count and place the new instructions in the preheader.
2251 // Notice that the pre-header does not change, only the loop body.
2252 SCEVExpander Exp(*SE, "induction");
2254 // We need to test whether the backedge-taken count is uint##_max. Adding one
2255 // to it will cause overflow and an incorrect loop trip count in the vector
2256 // body. In case of overflow we want to directly jump to the scalar remainder
2258 Value *BackedgeCount =
2259 Exp.expandCodeFor(BackedgeTakeCount, BackedgeTakeCount->getType(),
2260 BypassBlock->getTerminator());
2261 if (BackedgeCount->getType()->isPointerTy())
2262 BackedgeCount = CastInst::CreatePointerCast(BackedgeCount, IdxTy,
2263 "backedge.ptrcnt.to.int",
2264 BypassBlock->getTerminator());
2265 Instruction *CheckBCOverflow =
2266 CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ, BackedgeCount,
2267 Constant::getAllOnesValue(BackedgeCount->getType()),
2268 "backedge.overflow", BypassBlock->getTerminator());
2270 // The loop index does not have to start at Zero. Find the original start
2271 // value from the induction PHI node. If we don't have an induction variable
2272 // then we know that it starts at zero.
2273 Builder.SetInsertPoint(BypassBlock->getTerminator());
2274 Value *StartIdx = ExtendedIdx = OldInduction ?
2275 Builder.CreateZExt(OldInduction->getIncomingValueForBlock(BypassBlock),
2277 ConstantInt::get(IdxTy, 0);
2279 // We need an instruction to anchor the overflow check on. StartIdx needs to
2280 // be defined before the overflow check branch. Because the scalar preheader
2281 // is going to merge the start index and so the overflow branch block needs to
2282 // contain a definition of the start index.
2283 Instruction *OverflowCheckAnchor = BinaryOperator::CreateAdd(
2284 StartIdx, ConstantInt::get(IdxTy, 0), "overflow.check.anchor",
2285 BypassBlock->getTerminator());
2287 // Count holds the overall loop count (N).
2288 Value *Count = Exp.expandCodeFor(ExitCount, ExitCount->getType(),
2289 BypassBlock->getTerminator());
2291 LoopBypassBlocks.push_back(BypassBlock);
2293 // Split the single block loop into the two loop structure described above.
2294 BasicBlock *VectorPH =
2295 BypassBlock->splitBasicBlock(BypassBlock->getTerminator(), "vector.ph");
2296 BasicBlock *VecBody =
2297 VectorPH->splitBasicBlock(VectorPH->getTerminator(), "vector.body");
2298 BasicBlock *MiddleBlock =
2299 VecBody->splitBasicBlock(VecBody->getTerminator(), "middle.block");
2300 BasicBlock *ScalarPH =
2301 MiddleBlock->splitBasicBlock(MiddleBlock->getTerminator(), "scalar.ph");
2303 // Create and register the new vector loop.
2304 Loop* Lp = new Loop();
2305 Loop *ParentLoop = OrigLoop->getParentLoop();
2307 // Insert the new loop into the loop nest and register the new basic blocks
2308 // before calling any utilities such as SCEV that require valid LoopInfo.
2310 ParentLoop->addChildLoop(Lp);
2311 ParentLoop->addBasicBlockToLoop(ScalarPH, LI->getBase());
2312 ParentLoop->addBasicBlockToLoop(VectorPH, LI->getBase());
2313 ParentLoop->addBasicBlockToLoop(MiddleBlock, LI->getBase());
2315 LI->addTopLevelLoop(Lp);
2317 Lp->addBasicBlockToLoop(VecBody, LI->getBase());
2319 // Use this IR builder to create the loop instructions (Phi, Br, Cmp)
2321 Builder.SetInsertPoint(VecBody->getFirstNonPHI());
2323 // Generate the induction variable.
2324 setDebugLocFromInst(Builder, getDebugLocFromInstOrOperands(OldInduction));
2325 Induction = Builder.CreatePHI(IdxTy, 2, "index");
2326 // The loop step is equal to the vectorization factor (num of SIMD elements)
2327 // times the unroll factor (num of SIMD instructions).
2328 Constant *Step = ConstantInt::get(IdxTy, VF * UF);
2330 // This is the IR builder that we use to add all of the logic for bypassing
2331 // the new vector loop.
2332 IRBuilder<> BypassBuilder(BypassBlock->getTerminator());
2333 setDebugLocFromInst(BypassBuilder,
2334 getDebugLocFromInstOrOperands(OldInduction));
2336 // We may need to extend the index in case there is a type mismatch.
2337 // We know that the count starts at zero and does not overflow.
2338 if (Count->getType() != IdxTy) {
2339 // The exit count can be of pointer type. Convert it to the correct
2341 if (ExitCount->getType()->isPointerTy())
2342 Count = BypassBuilder.CreatePointerCast(Count, IdxTy, "ptrcnt.to.int");
2344 Count = BypassBuilder.CreateZExtOrTrunc(Count, IdxTy, "cnt.cast");
2347 // Add the start index to the loop count to get the new end index.
2348 Value *IdxEnd = BypassBuilder.CreateAdd(Count, StartIdx, "end.idx");
2350 // Now we need to generate the expression for N - (N % VF), which is
2351 // the part that the vectorized body will execute.
2352 Value *R = BypassBuilder.CreateURem(Count, Step, "n.mod.vf");
2353 Value *CountRoundDown = BypassBuilder.CreateSub(Count, R, "n.vec");
2354 Value *IdxEndRoundDown = BypassBuilder.CreateAdd(CountRoundDown, StartIdx,
2355 "end.idx.rnd.down");
2357 // Now, compare the new count to zero. If it is zero skip the vector loop and
2358 // jump to the scalar loop.
2360 BypassBuilder.CreateICmpEQ(IdxEndRoundDown, StartIdx, "cmp.zero");
2362 BasicBlock *LastBypassBlock = BypassBlock;
2364 // Generate code to check that the loops trip count that we computed by adding
2365 // one to the backedge-taken count will not overflow.
2367 auto PastOverflowCheck =
2368 std::next(BasicBlock::iterator(OverflowCheckAnchor));
2369 BasicBlock *CheckBlock =
2370 LastBypassBlock->splitBasicBlock(PastOverflowCheck, "overflow.checked");
2372 ParentLoop->addBasicBlockToLoop(CheckBlock, LI->getBase());
2373 LoopBypassBlocks.push_back(CheckBlock);
2374 Instruction *OldTerm = LastBypassBlock->getTerminator();
2375 BranchInst::Create(ScalarPH, CheckBlock, CheckBCOverflow, OldTerm);
2376 OldTerm->eraseFromParent();
2377 LastBypassBlock = CheckBlock;
2380 // Generate the code to check that the strides we assumed to be one are really
2381 // one. We want the new basic block to start at the first instruction in a
2382 // sequence of instructions that form a check.
2383 Instruction *StrideCheck;
2384 Instruction *FirstCheckInst;
2385 std::tie(FirstCheckInst, StrideCheck) =
2386 addStrideCheck(LastBypassBlock->getTerminator());
2388 // Create a new block containing the stride check.
2389 BasicBlock *CheckBlock =
2390 LastBypassBlock->splitBasicBlock(FirstCheckInst, "vector.stridecheck");
2392 ParentLoop->addBasicBlockToLoop(CheckBlock, LI->getBase());
2393 LoopBypassBlocks.push_back(CheckBlock);
2395 // Replace the branch into the memory check block with a conditional branch
2396 // for the "few elements case".
2397 Instruction *OldTerm = LastBypassBlock->getTerminator();
2398 BranchInst::Create(MiddleBlock, CheckBlock, Cmp, OldTerm);
2399 OldTerm->eraseFromParent();
2402 LastBypassBlock = CheckBlock;
2405 // Generate the code that checks in runtime if arrays overlap. We put the
2406 // checks into a separate block to make the more common case of few elements
2408 Instruction *MemRuntimeCheck;
2409 std::tie(FirstCheckInst, MemRuntimeCheck) =
2410 addRuntimeCheck(LastBypassBlock->getTerminator());
2411 if (MemRuntimeCheck) {
2412 // Create a new block containing the memory check.
2413 BasicBlock *CheckBlock =
2414 LastBypassBlock->splitBasicBlock(MemRuntimeCheck, "vector.memcheck");
2416 ParentLoop->addBasicBlockToLoop(CheckBlock, LI->getBase());
2417 LoopBypassBlocks.push_back(CheckBlock);
2419 // Replace the branch into the memory check block with a conditional branch
2420 // for the "few elements case".
2421 Instruction *OldTerm = LastBypassBlock->getTerminator();
2422 BranchInst::Create(MiddleBlock, CheckBlock, Cmp, OldTerm);
2423 OldTerm->eraseFromParent();
2425 Cmp = MemRuntimeCheck;
2426 LastBypassBlock = CheckBlock;
2429 LastBypassBlock->getTerminator()->eraseFromParent();
2430 BranchInst::Create(MiddleBlock, VectorPH, Cmp,
2433 // We are going to resume the execution of the scalar loop.
2434 // Go over all of the induction variables that we found and fix the
2435 // PHIs that are left in the scalar version of the loop.
2436 // The starting values of PHI nodes depend on the counter of the last
2437 // iteration in the vectorized loop.
2438 // If we come from a bypass edge then we need to start from the original
2441 // This variable saves the new starting index for the scalar loop.
2442 PHINode *ResumeIndex = nullptr;
2443 LoopVectorizationLegality::InductionList::iterator I, E;
2444 LoopVectorizationLegality::InductionList *List = Legal->getInductionVars();
2445 // Set builder to point to last bypass block.
2446 BypassBuilder.SetInsertPoint(LoopBypassBlocks.back()->getTerminator());
2447 for (I = List->begin(), E = List->end(); I != E; ++I) {
2448 PHINode *OrigPhi = I->first;
2449 LoopVectorizationLegality::InductionInfo II = I->second;
2451 Type *ResumeValTy = (OrigPhi == OldInduction) ? IdxTy : OrigPhi->getType();
2452 PHINode *ResumeVal = PHINode::Create(ResumeValTy, 2, "resume.val",
2453 MiddleBlock->getTerminator());
2454 // We might have extended the type of the induction variable but we need a
2455 // truncated version for the scalar loop.
2456 PHINode *TruncResumeVal = (OrigPhi == OldInduction) ?
2457 PHINode::Create(OrigPhi->getType(), 2, "trunc.resume.val",
2458 MiddleBlock->getTerminator()) : nullptr;
2460 // Create phi nodes to merge from the backedge-taken check block.
2461 PHINode *BCResumeVal = PHINode::Create(ResumeValTy, 3, "bc.resume.val",
2462 ScalarPH->getTerminator());
2463 BCResumeVal->addIncoming(ResumeVal, MiddleBlock);
2465 PHINode *BCTruncResumeVal = nullptr;
2466 if (OrigPhi == OldInduction) {
2468 PHINode::Create(OrigPhi->getType(), 2, "bc.trunc.resume.val",
2469 ScalarPH->getTerminator());
2470 BCTruncResumeVal->addIncoming(TruncResumeVal, MiddleBlock);
2473 Value *EndValue = nullptr;
2475 case LoopVectorizationLegality::IK_NoInduction:
2476 llvm_unreachable("Unknown induction");
2477 case LoopVectorizationLegality::IK_IntInduction: {
2478 // Handle the integer induction counter.
2479 assert(OrigPhi->getType()->isIntegerTy() && "Invalid type");
2481 // We have the canonical induction variable.
2482 if (OrigPhi == OldInduction) {
2483 // Create a truncated version of the resume value for the scalar loop,
2484 // we might have promoted the type to a larger width.
2486 BypassBuilder.CreateTrunc(IdxEndRoundDown, OrigPhi->getType());
2487 // The new PHI merges the original incoming value, in case of a bypass,
2488 // or the value at the end of the vectorized loop.
2489 for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I)
2490 TruncResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]);
2491 TruncResumeVal->addIncoming(EndValue, VecBody);
2493 BCTruncResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[0]);
2495 // We know what the end value is.
2496 EndValue = IdxEndRoundDown;
2497 // We also know which PHI node holds it.
2498 ResumeIndex = ResumeVal;
2502 // Not the canonical induction variable - add the vector loop count to the
2504 Value *CRD = BypassBuilder.CreateSExtOrTrunc(CountRoundDown,
2505 II.StartValue->getType(),
2507 EndValue = BypassBuilder.CreateAdd(CRD, II.StartValue , "ind.end");
2510 case LoopVectorizationLegality::IK_ReverseIntInduction: {
2511 // Convert the CountRoundDown variable to the PHI size.
2512 Value *CRD = BypassBuilder.CreateSExtOrTrunc(CountRoundDown,
2513 II.StartValue->getType(),
2515 // Handle reverse integer induction counter.
2516 EndValue = BypassBuilder.CreateSub(II.StartValue, CRD, "rev.ind.end");
2519 case LoopVectorizationLegality::IK_PtrInduction: {
2520 // For pointer induction variables, calculate the offset using
2522 EndValue = BypassBuilder.CreateGEP(II.StartValue, CountRoundDown,
2526 case LoopVectorizationLegality::IK_ReversePtrInduction: {
2527 // The value at the end of the loop for the reverse pointer is calculated
2528 // by creating a GEP with a negative index starting from the start value.
2529 Value *Zero = ConstantInt::get(CountRoundDown->getType(), 0);
2530 Value *NegIdx = BypassBuilder.CreateSub(Zero, CountRoundDown,
2532 EndValue = BypassBuilder.CreateGEP(II.StartValue, NegIdx,
2538 // The new PHI merges the original incoming value, in case of a bypass,
2539 // or the value at the end of the vectorized loop.
2540 for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I) {
2541 if (OrigPhi == OldInduction)
2542 ResumeVal->addIncoming(StartIdx, LoopBypassBlocks[I]);
2544 ResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]);
2546 ResumeVal->addIncoming(EndValue, VecBody);
2548 // Fix the scalar body counter (PHI node).
2549 unsigned BlockIdx = OrigPhi->getBasicBlockIndex(ScalarPH);
2551 // The old induction's phi node in the scalar body needs the truncated
2553 if (OrigPhi == OldInduction) {
2554 BCResumeVal->addIncoming(StartIdx, LoopBypassBlocks[0]);
2555 OrigPhi->setIncomingValue(BlockIdx, BCTruncResumeVal);
2557 BCResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[0]);
2558 OrigPhi->setIncomingValue(BlockIdx, BCResumeVal);
2562 // If we are generating a new induction variable then we also need to
2563 // generate the code that calculates the exit value. This value is not
2564 // simply the end of the counter because we may skip the vectorized body
2565 // in case of a runtime check.
2567 assert(!ResumeIndex && "Unexpected resume value found");
2568 ResumeIndex = PHINode::Create(IdxTy, 2, "new.indc.resume.val",
2569 MiddleBlock->getTerminator());
2570 for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I)
2571 ResumeIndex->addIncoming(StartIdx, LoopBypassBlocks[I]);
2572 ResumeIndex->addIncoming(IdxEndRoundDown, VecBody);
2575 // Make sure that we found the index where scalar loop needs to continue.
2576 assert(ResumeIndex && ResumeIndex->getType()->isIntegerTy() &&
2577 "Invalid resume Index");
2579 // Add a check in the middle block to see if we have completed
2580 // all of the iterations in the first vector loop.
2581 // If (N - N%VF) == N, then we *don't* need to run the remainder.
2582 Value *CmpN = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ, IdxEnd,
2583 ResumeIndex, "cmp.n",
2584 MiddleBlock->getTerminator());
2586 BranchInst::Create(ExitBlock, ScalarPH, CmpN, MiddleBlock->getTerminator());
2587 // Remove the old terminator.
2588 MiddleBlock->getTerminator()->eraseFromParent();
2590 // Create i+1 and fill the PHINode.
2591 Value *NextIdx = Builder.CreateAdd(Induction, Step, "index.next");
2592 Induction->addIncoming(StartIdx, VectorPH);
2593 Induction->addIncoming(NextIdx, VecBody);
2594 // Create the compare.
2595 Value *ICmp = Builder.CreateICmpEQ(NextIdx, IdxEndRoundDown);
2596 Builder.CreateCondBr(ICmp, MiddleBlock, VecBody);
2598 // Now we have two terminators. Remove the old one from the block.
2599 VecBody->getTerminator()->eraseFromParent();
2601 // Get ready to start creating new instructions into the vectorized body.
2602 Builder.SetInsertPoint(VecBody->getFirstInsertionPt());
2605 LoopVectorPreHeader = VectorPH;
2606 LoopScalarPreHeader = ScalarPH;
2607 LoopMiddleBlock = MiddleBlock;
2608 LoopExitBlock = ExitBlock;
2609 LoopVectorBody.push_back(VecBody);
2610 LoopScalarBody = OldBasicBlock;
2612 LoopVectorizeHints Hints(Lp, true);
2613 Hints.setAlreadyVectorized();
2616 /// This function returns the identity element (or neutral element) for
2617 /// the operation K.
2619 LoopVectorizationLegality::getReductionIdentity(ReductionKind K, Type *Tp) {
2624 // Adding, Xoring, Oring zero to a number does not change it.
2625 return ConstantInt::get(Tp, 0);
2626 case RK_IntegerMult:
2627 // Multiplying a number by 1 does not change it.
2628 return ConstantInt::get(Tp, 1);
2630 // AND-ing a number with an all-1 value does not change it.
2631 return ConstantInt::get(Tp, -1, true);
2633 // Multiplying a number by 1 does not change it.
2634 return ConstantFP::get(Tp, 1.0L);
2636 // Adding zero to a number does not change it.
2637 return ConstantFP::get(Tp, 0.0L);
2639 llvm_unreachable("Unknown reduction kind");
2643 /// This function translates the reduction kind to an LLVM binary operator.
2645 getReductionBinOp(LoopVectorizationLegality::ReductionKind Kind) {
2647 case LoopVectorizationLegality::RK_IntegerAdd:
2648 return Instruction::Add;
2649 case LoopVectorizationLegality::RK_IntegerMult:
2650 return Instruction::Mul;
2651 case LoopVectorizationLegality::RK_IntegerOr:
2652 return Instruction::Or;
2653 case LoopVectorizationLegality::RK_IntegerAnd:
2654 return Instruction::And;
2655 case LoopVectorizationLegality::RK_IntegerXor:
2656 return Instruction::Xor;
2657 case LoopVectorizationLegality::RK_FloatMult:
2658 return Instruction::FMul;
2659 case LoopVectorizationLegality::RK_FloatAdd:
2660 return Instruction::FAdd;
2661 case LoopVectorizationLegality::RK_IntegerMinMax:
2662 return Instruction::ICmp;
2663 case LoopVectorizationLegality::RK_FloatMinMax:
2664 return Instruction::FCmp;
2666 llvm_unreachable("Unknown reduction operation");
2670 Value *createMinMaxOp(IRBuilder<> &Builder,
2671 LoopVectorizationLegality::MinMaxReductionKind RK,
2674 CmpInst::Predicate P = CmpInst::ICMP_NE;
2677 llvm_unreachable("Unknown min/max reduction kind");
2678 case LoopVectorizationLegality::MRK_UIntMin:
2679 P = CmpInst::ICMP_ULT;
2681 case LoopVectorizationLegality::MRK_UIntMax:
2682 P = CmpInst::ICMP_UGT;
2684 case LoopVectorizationLegality::MRK_SIntMin:
2685 P = CmpInst::ICMP_SLT;
2687 case LoopVectorizationLegality::MRK_SIntMax:
2688 P = CmpInst::ICMP_SGT;
2690 case LoopVectorizationLegality::MRK_FloatMin:
2691 P = CmpInst::FCMP_OLT;
2693 case LoopVectorizationLegality::MRK_FloatMax:
2694 P = CmpInst::FCMP_OGT;
2699 if (RK == LoopVectorizationLegality::MRK_FloatMin ||
2700 RK == LoopVectorizationLegality::MRK_FloatMax)
2701 Cmp = Builder.CreateFCmp(P, Left, Right, "rdx.minmax.cmp");
2703 Cmp = Builder.CreateICmp(P, Left, Right, "rdx.minmax.cmp");
2705 Value *Select = Builder.CreateSelect(Cmp, Left, Right, "rdx.minmax.select");
2710 struct CSEDenseMapInfo {
2711 static bool canHandle(Instruction *I) {
2712 return isa<InsertElementInst>(I) || isa<ExtractElementInst>(I) ||
2713 isa<ShuffleVectorInst>(I) || isa<GetElementPtrInst>(I);
2715 static inline Instruction *getEmptyKey() {
2716 return DenseMapInfo<Instruction *>::getEmptyKey();
2718 static inline Instruction *getTombstoneKey() {
2719 return DenseMapInfo<Instruction *>::getTombstoneKey();
2721 static unsigned getHashValue(Instruction *I) {
2722 assert(canHandle(I) && "Unknown instruction!");
2723 return hash_combine(I->getOpcode(), hash_combine_range(I->value_op_begin(),
2724 I->value_op_end()));
2726 static bool isEqual(Instruction *LHS, Instruction *RHS) {
2727 if (LHS == getEmptyKey() || RHS == getEmptyKey() ||
2728 LHS == getTombstoneKey() || RHS == getTombstoneKey())
2730 return LHS->isIdenticalTo(RHS);
2735 /// \brief Check whether this block is a predicated block.
2736 /// Due to if predication of stores we might create a sequence of "if(pred) a[i]
2737 /// = ...; " blocks. We start with one vectorized basic block. For every
2738 /// conditional block we split this vectorized block. Therefore, every second
2739 /// block will be a predicated one.
2740 static bool isPredicatedBlock(unsigned BlockNum) {
2741 return BlockNum % 2;
2744 ///\brief Perform cse of induction variable instructions.
2745 static void cse(SmallVector<BasicBlock *, 4> &BBs) {
2746 // Perform simple cse.
2747 SmallDenseMap<Instruction *, Instruction *, 4, CSEDenseMapInfo> CSEMap;
2748 for (unsigned i = 0, e = BBs.size(); i != e; ++i) {
2749 BasicBlock *BB = BBs[i];
2750 for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E;) {
2751 Instruction *In = I++;
2753 if (!CSEDenseMapInfo::canHandle(In))
2756 // Check if we can replace this instruction with any of the
2757 // visited instructions.
2758 if (Instruction *V = CSEMap.lookup(In)) {
2759 In->replaceAllUsesWith(V);
2760 In->eraseFromParent();
2763 // Ignore instructions in conditional blocks. We create "if (pred) a[i] =
2764 // ...;" blocks for predicated stores. Every second block is a predicated
2766 if (isPredicatedBlock(i))
2774 /// \brief Adds a 'fast' flag to floating point operations.
2775 static Value *addFastMathFlag(Value *V) {
2776 if (isa<FPMathOperator>(V)){
2777 FastMathFlags Flags;
2778 Flags.setUnsafeAlgebra();
2779 cast<Instruction>(V)->setFastMathFlags(Flags);
2784 void InnerLoopVectorizer::vectorizeLoop() {
2785 //===------------------------------------------------===//
2787 // Notice: any optimization or new instruction that go
2788 // into the code below should be also be implemented in
2791 //===------------------------------------------------===//
2792 Constant *Zero = Builder.getInt32(0);
2794 // In order to support reduction variables we need to be able to vectorize
2795 // Phi nodes. Phi nodes have cycles, so we need to vectorize them in two
2796 // stages. First, we create a new vector PHI node with no incoming edges.
2797 // We use this value when we vectorize all of the instructions that use the
2798 // PHI. Next, after all of the instructions in the block are complete we
2799 // add the new incoming edges to the PHI. At this point all of the
2800 // instructions in the basic block are vectorized, so we can use them to
2801 // construct the PHI.
2802 PhiVector RdxPHIsToFix;
2804 // Scan the loop in a topological order to ensure that defs are vectorized
2806 LoopBlocksDFS DFS(OrigLoop);
2809 // Vectorize all of the blocks in the original loop.
2810 for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(),
2811 be = DFS.endRPO(); bb != be; ++bb)
2812 vectorizeBlockInLoop(*bb, &RdxPHIsToFix);
2814 // At this point every instruction in the original loop is widened to
2815 // a vector form. We are almost done. Now, we need to fix the PHI nodes
2816 // that we vectorized. The PHI nodes are currently empty because we did
2817 // not want to introduce cycles. Notice that the remaining PHI nodes
2818 // that we need to fix are reduction variables.
2820 // Create the 'reduced' values for each of the induction vars.
2821 // The reduced values are the vector values that we scalarize and combine
2822 // after the loop is finished.
2823 for (PhiVector::iterator it = RdxPHIsToFix.begin(), e = RdxPHIsToFix.end();
2825 PHINode *RdxPhi = *it;
2826 assert(RdxPhi && "Unable to recover vectorized PHI");
2828 // Find the reduction variable descriptor.
2829 assert(Legal->getReductionVars()->count(RdxPhi) &&
2830 "Unable to find the reduction variable");
2831 LoopVectorizationLegality::ReductionDescriptor RdxDesc =
2832 (*Legal->getReductionVars())[RdxPhi];
2834 setDebugLocFromInst(Builder, RdxDesc.StartValue);
2836 // We need to generate a reduction vector from the incoming scalar.
2837 // To do so, we need to generate the 'identity' vector and override
2838 // one of the elements with the incoming scalar reduction. We need
2839 // to do it in the vector-loop preheader.
2840 Builder.SetInsertPoint(LoopBypassBlocks[1]->getTerminator());
2842 // This is the vector-clone of the value that leaves the loop.
2843 VectorParts &VectorExit = getVectorValue(RdxDesc.LoopExitInstr);
2844 Type *VecTy = VectorExit[0]->getType();
2846 // Find the reduction identity variable. Zero for addition, or, xor,
2847 // one for multiplication, -1 for And.
2850 if (RdxDesc.Kind == LoopVectorizationLegality::RK_IntegerMinMax ||
2851 RdxDesc.Kind == LoopVectorizationLegality::RK_FloatMinMax) {
2852 // MinMax reduction have the start value as their identify.
2854 VectorStart = Identity = RdxDesc.StartValue;
2856 VectorStart = Identity = Builder.CreateVectorSplat(VF,
2861 // Handle other reduction kinds:
2863 LoopVectorizationLegality::getReductionIdentity(RdxDesc.Kind,
2864 VecTy->getScalarType());
2867 // This vector is the Identity vector where the first element is the
2868 // incoming scalar reduction.
2869 VectorStart = RdxDesc.StartValue;
2871 Identity = ConstantVector::getSplat(VF, Iden);
2873 // This vector is the Identity vector where the first element is the
2874 // incoming scalar reduction.
2875 VectorStart = Builder.CreateInsertElement(Identity,
2876 RdxDesc.StartValue, Zero);
2880 // Fix the vector-loop phi.
2882 // Reductions do not have to start at zero. They can start with
2883 // any loop invariant values.
2884 VectorParts &VecRdxPhi = WidenMap.get(RdxPhi);
2885 BasicBlock *Latch = OrigLoop->getLoopLatch();
2886 Value *LoopVal = RdxPhi->getIncomingValueForBlock(Latch);
2887 VectorParts &Val = getVectorValue(LoopVal);
2888 for (unsigned part = 0; part < UF; ++part) {
2889 // Make sure to add the reduction stat value only to the
2890 // first unroll part.
2891 Value *StartVal = (part == 0) ? VectorStart : Identity;
2892 cast<PHINode>(VecRdxPhi[part])->addIncoming(StartVal,
2893 LoopVectorPreHeader);
2894 cast<PHINode>(VecRdxPhi[part])->addIncoming(Val[part],
2895 LoopVectorBody.back());
2898 // Before each round, move the insertion point right between
2899 // the PHIs and the values we are going to write.
2900 // This allows us to write both PHINodes and the extractelement
2902 Builder.SetInsertPoint(LoopMiddleBlock->getFirstInsertionPt());
2904 VectorParts RdxParts;
2905 setDebugLocFromInst(Builder, RdxDesc.LoopExitInstr);
2906 for (unsigned part = 0; part < UF; ++part) {
2907 // This PHINode contains the vectorized reduction variable, or
2908 // the initial value vector, if we bypass the vector loop.
2909 VectorParts &RdxExitVal = getVectorValue(RdxDesc.LoopExitInstr);
2910 PHINode *NewPhi = Builder.CreatePHI(VecTy, 2, "rdx.vec.exit.phi");
2911 Value *StartVal = (part == 0) ? VectorStart : Identity;
2912 for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I)
2913 NewPhi->addIncoming(StartVal, LoopBypassBlocks[I]);
2914 NewPhi->addIncoming(RdxExitVal[part],
2915 LoopVectorBody.back());
2916 RdxParts.push_back(NewPhi);
2919 // Reduce all of the unrolled parts into a single vector.
2920 Value *ReducedPartRdx = RdxParts[0];
2921 unsigned Op = getReductionBinOp(RdxDesc.Kind);
2922 setDebugLocFromInst(Builder, ReducedPartRdx);
2923 for (unsigned part = 1; part < UF; ++part) {
2924 if (Op != Instruction::ICmp && Op != Instruction::FCmp)
2925 // Floating point operations had to be 'fast' to enable the reduction.
2926 ReducedPartRdx = addFastMathFlag(
2927 Builder.CreateBinOp((Instruction::BinaryOps)Op, RdxParts[part],
2928 ReducedPartRdx, "bin.rdx"));
2930 ReducedPartRdx = createMinMaxOp(Builder, RdxDesc.MinMaxKind,
2931 ReducedPartRdx, RdxParts[part]);
2935 // VF is a power of 2 so we can emit the reduction using log2(VF) shuffles
2936 // and vector ops, reducing the set of values being computed by half each
2938 assert(isPowerOf2_32(VF) &&
2939 "Reduction emission only supported for pow2 vectors!");
2940 Value *TmpVec = ReducedPartRdx;
2941 SmallVector<Constant*, 32> ShuffleMask(VF, nullptr);
2942 for (unsigned i = VF; i != 1; i >>= 1) {
2943 // Move the upper half of the vector to the lower half.
2944 for (unsigned j = 0; j != i/2; ++j)
2945 ShuffleMask[j] = Builder.getInt32(i/2 + j);
2947 // Fill the rest of the mask with undef.
2948 std::fill(&ShuffleMask[i/2], ShuffleMask.end(),
2949 UndefValue::get(Builder.getInt32Ty()));
2952 Builder.CreateShuffleVector(TmpVec,
2953 UndefValue::get(TmpVec->getType()),
2954 ConstantVector::get(ShuffleMask),
2957 if (Op != Instruction::ICmp && Op != Instruction::FCmp)
2958 // Floating point operations had to be 'fast' to enable the reduction.
2959 TmpVec = addFastMathFlag(Builder.CreateBinOp(
2960 (Instruction::BinaryOps)Op, TmpVec, Shuf, "bin.rdx"));
2962 TmpVec = createMinMaxOp(Builder, RdxDesc.MinMaxKind, TmpVec, Shuf);
2965 // The result is in the first element of the vector.
2966 ReducedPartRdx = Builder.CreateExtractElement(TmpVec,
2967 Builder.getInt32(0));
2970 // Create a phi node that merges control-flow from the backedge-taken check
2971 // block and the middle block.
2972 PHINode *BCBlockPhi = PHINode::Create(RdxPhi->getType(), 2, "bc.merge.rdx",
2973 LoopScalarPreHeader->getTerminator());
2974 BCBlockPhi->addIncoming(RdxDesc.StartValue, LoopBypassBlocks[0]);
2975 BCBlockPhi->addIncoming(ReducedPartRdx, LoopMiddleBlock);
2977 // Now, we need to fix the users of the reduction variable
2978 // inside and outside of the scalar remainder loop.
2979 // We know that the loop is in LCSSA form. We need to update the
2980 // PHI nodes in the exit blocks.
2981 for (BasicBlock::iterator LEI = LoopExitBlock->begin(),
2982 LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) {
2983 PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI);
2984 if (!LCSSAPhi) break;
2986 // All PHINodes need to have a single entry edge, or two if
2987 // we already fixed them.
2988 assert(LCSSAPhi->getNumIncomingValues() < 3 && "Invalid LCSSA PHI");
2990 // We found our reduction value exit-PHI. Update it with the
2991 // incoming bypass edge.
2992 if (LCSSAPhi->getIncomingValue(0) == RdxDesc.LoopExitInstr) {
2993 // Add an edge coming from the bypass.
2994 LCSSAPhi->addIncoming(ReducedPartRdx, LoopMiddleBlock);
2997 }// end of the LCSSA phi scan.
2999 // Fix the scalar loop reduction variable with the incoming reduction sum
3000 // from the vector body and from the backedge value.
3001 int IncomingEdgeBlockIdx =
3002 (RdxPhi)->getBasicBlockIndex(OrigLoop->getLoopLatch());
3003 assert(IncomingEdgeBlockIdx >= 0 && "Invalid block index");
3004 // Pick the other block.
3005 int SelfEdgeBlockIdx = (IncomingEdgeBlockIdx ? 0 : 1);
3006 (RdxPhi)->setIncomingValue(SelfEdgeBlockIdx, BCBlockPhi);
3007 (RdxPhi)->setIncomingValue(IncomingEdgeBlockIdx, RdxDesc.LoopExitInstr);
3008 }// end of for each redux variable.
3012 // Remove redundant induction instructions.
3013 cse(LoopVectorBody);
3016 void InnerLoopVectorizer::fixLCSSAPHIs() {
3017 for (BasicBlock::iterator LEI = LoopExitBlock->begin(),
3018 LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) {
3019 PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI);
3020 if (!LCSSAPhi) break;
3021 if (LCSSAPhi->getNumIncomingValues() == 1)
3022 LCSSAPhi->addIncoming(UndefValue::get(LCSSAPhi->getType()),
3027 InnerLoopVectorizer::VectorParts
3028 InnerLoopVectorizer::createEdgeMask(BasicBlock *Src, BasicBlock *Dst) {
3029 assert(std::find(pred_begin(Dst), pred_end(Dst), Src) != pred_end(Dst) &&
3032 // Look for cached value.
3033 std::pair<BasicBlock*, BasicBlock*> Edge(Src, Dst);
3034 EdgeMaskCache::iterator ECEntryIt = MaskCache.find(Edge);
3035 if (ECEntryIt != MaskCache.end())
3036 return ECEntryIt->second;
3038 VectorParts SrcMask = createBlockInMask(Src);
3040 // The terminator has to be a branch inst!
3041 BranchInst *BI = dyn_cast<BranchInst>(Src->getTerminator());
3042 assert(BI && "Unexpected terminator found");
3044 if (BI->isConditional()) {
3045 VectorParts EdgeMask = getVectorValue(BI->getCondition());
3047 if (BI->getSuccessor(0) != Dst)
3048 for (unsigned part = 0; part < UF; ++part)
3049 EdgeMask[part] = Builder.CreateNot(EdgeMask[part]);
3051 for (unsigned part = 0; part < UF; ++part)
3052 EdgeMask[part] = Builder.CreateAnd(EdgeMask[part], SrcMask[part]);
3054 MaskCache[Edge] = EdgeMask;
3058 MaskCache[Edge] = SrcMask;
3062 InnerLoopVectorizer::VectorParts
3063 InnerLoopVectorizer::createBlockInMask(BasicBlock *BB) {
3064 assert(OrigLoop->contains(BB) && "Block is not a part of a loop");
3066 // Loop incoming mask is all-one.
3067 if (OrigLoop->getHeader() == BB) {
3068 Value *C = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 1);
3069 return getVectorValue(C);
3072 // This is the block mask. We OR all incoming edges, and with zero.
3073 Value *Zero = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 0);
3074 VectorParts BlockMask = getVectorValue(Zero);
3077 for (pred_iterator it = pred_begin(BB), e = pred_end(BB); it != e; ++it) {
3078 VectorParts EM = createEdgeMask(*it, BB);
3079 for (unsigned part = 0; part < UF; ++part)
3080 BlockMask[part] = Builder.CreateOr(BlockMask[part], EM[part]);
3086 void InnerLoopVectorizer::widenPHIInstruction(Instruction *PN,
3087 InnerLoopVectorizer::VectorParts &Entry,
3088 unsigned UF, unsigned VF, PhiVector *PV) {
3089 PHINode* P = cast<PHINode>(PN);
3090 // Handle reduction variables:
3091 if (Legal->getReductionVars()->count(P)) {
3092 for (unsigned part = 0; part < UF; ++part) {
3093 // This is phase one of vectorizing PHIs.
3094 Type *VecTy = (VF == 1) ? PN->getType() :
3095 VectorType::get(PN->getType(), VF);
3096 Entry[part] = PHINode::Create(VecTy, 2, "vec.phi",
3097 LoopVectorBody.back()-> getFirstInsertionPt());
3103 setDebugLocFromInst(Builder, P);
3104 // Check for PHI nodes that are lowered to vector selects.
3105 if (P->getParent() != OrigLoop->getHeader()) {
3106 // We know that all PHIs in non-header blocks are converted into
3107 // selects, so we don't have to worry about the insertion order and we
3108 // can just use the builder.
3109 // At this point we generate the predication tree. There may be
3110 // duplications since this is a simple recursive scan, but future
3111 // optimizations will clean it up.
3113 unsigned NumIncoming = P->getNumIncomingValues();
3115 // Generate a sequence of selects of the form:
3116 // SELECT(Mask3, In3,
3117 // SELECT(Mask2, In2,
3119 for (unsigned In = 0; In < NumIncoming; In++) {
3120 VectorParts Cond = createEdgeMask(P->getIncomingBlock(In),
3122 VectorParts &In0 = getVectorValue(P->getIncomingValue(In));
3124 for (unsigned part = 0; part < UF; ++part) {
3125 // We might have single edge PHIs (blocks) - use an identity
3126 // 'select' for the first PHI operand.
3128 Entry[part] = Builder.CreateSelect(Cond[part], In0[part],
3131 // Select between the current value and the previous incoming edge
3132 // based on the incoming mask.
3133 Entry[part] = Builder.CreateSelect(Cond[part], In0[part],
3134 Entry[part], "predphi");
3140 // This PHINode must be an induction variable.
3141 // Make sure that we know about it.
3142 assert(Legal->getInductionVars()->count(P) &&
3143 "Not an induction variable");
3145 LoopVectorizationLegality::InductionInfo II =
3146 Legal->getInductionVars()->lookup(P);
3149 case LoopVectorizationLegality::IK_NoInduction:
3150 llvm_unreachable("Unknown induction");
3151 case LoopVectorizationLegality::IK_IntInduction: {
3152 assert(P->getType() == II.StartValue->getType() && "Types must match");
3153 Type *PhiTy = P->getType();
3155 if (P == OldInduction) {
3156 // Handle the canonical induction variable. We might have had to
3158 Broadcasted = Builder.CreateTrunc(Induction, PhiTy);
3160 // Handle other induction variables that are now based on the
3162 Value *NormalizedIdx = Builder.CreateSub(Induction, ExtendedIdx,
3164 NormalizedIdx = Builder.CreateSExtOrTrunc(NormalizedIdx, PhiTy);
3165 Broadcasted = Builder.CreateAdd(II.StartValue, NormalizedIdx,
3168 Broadcasted = getBroadcastInstrs(Broadcasted);
3169 // After broadcasting the induction variable we need to make the vector
3170 // consecutive by adding 0, 1, 2, etc.
3171 for (unsigned part = 0; part < UF; ++part)
3172 Entry[part] = getConsecutiveVector(Broadcasted, VF * part, false);
3175 case LoopVectorizationLegality::IK_ReverseIntInduction:
3176 case LoopVectorizationLegality::IK_PtrInduction:
3177 case LoopVectorizationLegality::IK_ReversePtrInduction:
3178 // Handle reverse integer and pointer inductions.
3179 Value *StartIdx = ExtendedIdx;
3180 // This is the normalized GEP that starts counting at zero.
3181 Value *NormalizedIdx = Builder.CreateSub(Induction, StartIdx,
3184 // Handle the reverse integer induction variable case.
3185 if (LoopVectorizationLegality::IK_ReverseIntInduction == II.IK) {
3186 IntegerType *DstTy = cast<IntegerType>(II.StartValue->getType());
3187 Value *CNI = Builder.CreateSExtOrTrunc(NormalizedIdx, DstTy,
3189 Value *ReverseInd = Builder.CreateSub(II.StartValue, CNI,
3192 // This is a new value so do not hoist it out.
3193 Value *Broadcasted = getBroadcastInstrs(ReverseInd);
3194 // After broadcasting the induction variable we need to make the
3195 // vector consecutive by adding ... -3, -2, -1, 0.
3196 for (unsigned part = 0; part < UF; ++part)
3197 Entry[part] = getConsecutiveVector(Broadcasted, -(int)VF * part,
3202 // Handle the pointer induction variable case.
3203 assert(P->getType()->isPointerTy() && "Unexpected type.");
3205 // Is this a reverse induction ptr or a consecutive induction ptr.
3206 bool Reverse = (LoopVectorizationLegality::IK_ReversePtrInduction ==
3209 // This is the vector of results. Notice that we don't generate
3210 // vector geps because scalar geps result in better code.
3211 for (unsigned part = 0; part < UF; ++part) {
3213 int EltIndex = (part) * (Reverse ? -1 : 1);
3214 Constant *Idx = ConstantInt::get(Induction->getType(), EltIndex);
3217 GlobalIdx = Builder.CreateSub(Idx, NormalizedIdx, "gep.ridx");
3219 GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx, "gep.idx");
3221 Value *SclrGep = Builder.CreateGEP(II.StartValue, GlobalIdx,
3223 Entry[part] = SclrGep;
3227 Value *VecVal = UndefValue::get(VectorType::get(P->getType(), VF));
3228 for (unsigned int i = 0; i < VF; ++i) {
3229 int EltIndex = (i + part * VF) * (Reverse ? -1 : 1);
3230 Constant *Idx = ConstantInt::get(Induction->getType(), EltIndex);
3233 GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx, "gep.idx");
3235 GlobalIdx = Builder.CreateSub(Idx, NormalizedIdx, "gep.ridx");
3237 Value *SclrGep = Builder.CreateGEP(II.StartValue, GlobalIdx,
3239 VecVal = Builder.CreateInsertElement(VecVal, SclrGep,
3240 Builder.getInt32(i),
3243 Entry[part] = VecVal;
3249 void InnerLoopVectorizer::vectorizeBlockInLoop(BasicBlock *BB, PhiVector *PV) {
3250 // For each instruction in the old loop.
3251 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
3252 VectorParts &Entry = WidenMap.get(it);
3253 switch (it->getOpcode()) {
3254 case Instruction::Br:
3255 // Nothing to do for PHIs and BR, since we already took care of the
3256 // loop control flow instructions.
3258 case Instruction::PHI:{
3259 // Vectorize PHINodes.
3260 widenPHIInstruction(it, Entry, UF, VF, PV);
3264 case Instruction::Add:
3265 case Instruction::FAdd:
3266 case Instruction::Sub:
3267 case Instruction::FSub:
3268 case Instruction::Mul:
3269 case Instruction::FMul:
3270 case Instruction::UDiv:
3271 case Instruction::SDiv:
3272 case Instruction::FDiv:
3273 case Instruction::URem:
3274 case Instruction::SRem:
3275 case Instruction::FRem:
3276 case Instruction::Shl:
3277 case Instruction::LShr:
3278 case Instruction::AShr:
3279 case Instruction::And:
3280 case Instruction::Or:
3281 case Instruction::Xor: {
3282 // Just widen binops.
3283 BinaryOperator *BinOp = dyn_cast<BinaryOperator>(it);
3284 setDebugLocFromInst(Builder, BinOp);
3285 VectorParts &A = getVectorValue(it->getOperand(0));
3286 VectorParts &B = getVectorValue(it->getOperand(1));
3288 // Use this vector value for all users of the original instruction.
3289 for (unsigned Part = 0; Part < UF; ++Part) {
3290 Value *V = Builder.CreateBinOp(BinOp->getOpcode(), A[Part], B[Part]);
3292 if (BinaryOperator *VecOp = dyn_cast<BinaryOperator>(V))
3293 VecOp->copyIRFlags(BinOp);
3298 propagateMetadata(Entry, it);
3301 case Instruction::Select: {
3303 // If the selector is loop invariant we can create a select
3304 // instruction with a scalar condition. Otherwise, use vector-select.
3305 bool InvariantCond = SE->isLoopInvariant(SE->getSCEV(it->getOperand(0)),
3307 setDebugLocFromInst(Builder, it);
3309 // The condition can be loop invariant but still defined inside the
3310 // loop. This means that we can't just use the original 'cond' value.
3311 // We have to take the 'vectorized' value and pick the first lane.
3312 // Instcombine will make this a no-op.
3313 VectorParts &Cond = getVectorValue(it->getOperand(0));
3314 VectorParts &Op0 = getVectorValue(it->getOperand(1));
3315 VectorParts &Op1 = getVectorValue(it->getOperand(2));
3317 Value *ScalarCond = (VF == 1) ? Cond[0] :
3318 Builder.CreateExtractElement(Cond[0], Builder.getInt32(0));
3320 for (unsigned Part = 0; Part < UF; ++Part) {
3321 Entry[Part] = Builder.CreateSelect(
3322 InvariantCond ? ScalarCond : Cond[Part],
3327 propagateMetadata(Entry, it);
3331 case Instruction::ICmp:
3332 case Instruction::FCmp: {
3333 // Widen compares. Generate vector compares.
3334 bool FCmp = (it->getOpcode() == Instruction::FCmp);
3335 CmpInst *Cmp = dyn_cast<CmpInst>(it);
3336 setDebugLocFromInst(Builder, it);
3337 VectorParts &A = getVectorValue(it->getOperand(0));
3338 VectorParts &B = getVectorValue(it->getOperand(1));
3339 for (unsigned Part = 0; Part < UF; ++Part) {
3342 C = Builder.CreateFCmp(Cmp->getPredicate(), A[Part], B[Part]);
3344 C = Builder.CreateICmp(Cmp->getPredicate(), A[Part], B[Part]);
3348 propagateMetadata(Entry, it);
3352 case Instruction::Store:
3353 case Instruction::Load:
3354 vectorizeMemoryInstruction(it);
3356 case Instruction::ZExt:
3357 case Instruction::SExt:
3358 case Instruction::FPToUI:
3359 case Instruction::FPToSI:
3360 case Instruction::FPExt:
3361 case Instruction::PtrToInt:
3362 case Instruction::IntToPtr:
3363 case Instruction::SIToFP:
3364 case Instruction::UIToFP:
3365 case Instruction::Trunc:
3366 case Instruction::FPTrunc:
3367 case Instruction::BitCast: {
3368 CastInst *CI = dyn_cast<CastInst>(it);
3369 setDebugLocFromInst(Builder, it);
3370 /// Optimize the special case where the source is the induction
3371 /// variable. Notice that we can only optimize the 'trunc' case
3372 /// because: a. FP conversions lose precision, b. sext/zext may wrap,
3373 /// c. other casts depend on pointer size.
3374 if (CI->getOperand(0) == OldInduction &&
3375 it->getOpcode() == Instruction::Trunc) {
3376 Value *ScalarCast = Builder.CreateCast(CI->getOpcode(), Induction,
3378 Value *Broadcasted = getBroadcastInstrs(ScalarCast);
3379 for (unsigned Part = 0; Part < UF; ++Part)
3380 Entry[Part] = getConsecutiveVector(Broadcasted, VF * Part, false);
3381 propagateMetadata(Entry, it);
3384 /// Vectorize casts.
3385 Type *DestTy = (VF == 1) ? CI->getType() :
3386 VectorType::get(CI->getType(), VF);
3388 VectorParts &A = getVectorValue(it->getOperand(0));
3389 for (unsigned Part = 0; Part < UF; ++Part)
3390 Entry[Part] = Builder.CreateCast(CI->getOpcode(), A[Part], DestTy);
3391 propagateMetadata(Entry, it);
3395 case Instruction::Call: {
3396 // Ignore dbg intrinsics.
3397 if (isa<DbgInfoIntrinsic>(it))
3399 setDebugLocFromInst(Builder, it);
3401 Module *M = BB->getParent()->getParent();
3402 CallInst *CI = cast<CallInst>(it);
3403 Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI);
3404 assert(ID && "Not an intrinsic call!");
3406 case Intrinsic::assume:
3407 case Intrinsic::lifetime_end:
3408 case Intrinsic::lifetime_start:
3409 scalarizeInstruction(it);
3412 bool HasScalarOpd = hasVectorInstrinsicScalarOpd(ID, 1);
3413 for (unsigned Part = 0; Part < UF; ++Part) {
3414 SmallVector<Value *, 4> Args;
3415 for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i) {
3416 if (HasScalarOpd && i == 1) {
3417 Args.push_back(CI->getArgOperand(i));
3420 VectorParts &Arg = getVectorValue(CI->getArgOperand(i));
3421 Args.push_back(Arg[Part]);
3423 Type *Tys[] = {CI->getType()};
3425 Tys[0] = VectorType::get(CI->getType()->getScalarType(), VF);
3427 Function *F = Intrinsic::getDeclaration(M, ID, Tys);
3428 Entry[Part] = Builder.CreateCall(F, Args);
3431 propagateMetadata(Entry, it);
3438 // All other instructions are unsupported. Scalarize them.
3439 scalarizeInstruction(it);
3442 }// end of for_each instr.
3445 void InnerLoopVectorizer::updateAnalysis() {
3446 // Forget the original basic block.
3447 SE->forgetLoop(OrigLoop);
3449 // Update the dominator tree information.
3450 assert(DT->properlyDominates(LoopBypassBlocks.front(), LoopExitBlock) &&
3451 "Entry does not dominate exit.");
3453 for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I)
3454 DT->addNewBlock(LoopBypassBlocks[I], LoopBypassBlocks[I-1]);
3455 DT->addNewBlock(LoopVectorPreHeader, LoopBypassBlocks.back());
3457 // Due to if predication of stores we might create a sequence of "if(pred)
3458 // a[i] = ...; " blocks.
3459 for (unsigned i = 0, e = LoopVectorBody.size(); i != e; ++i) {
3461 DT->addNewBlock(LoopVectorBody[0], LoopVectorPreHeader);
3462 else if (isPredicatedBlock(i)) {
3463 DT->addNewBlock(LoopVectorBody[i], LoopVectorBody[i-1]);
3465 DT->addNewBlock(LoopVectorBody[i], LoopVectorBody[i-2]);
3469 DT->addNewBlock(LoopMiddleBlock, LoopBypassBlocks[1]);
3470 DT->addNewBlock(LoopScalarPreHeader, LoopBypassBlocks[0]);
3471 DT->changeImmediateDominator(LoopScalarBody, LoopScalarPreHeader);
3472 DT->changeImmediateDominator(LoopExitBlock, LoopBypassBlocks[0]);
3474 DEBUG(DT->verifyDomTree());
3477 /// \brief Check whether it is safe to if-convert this phi node.
3479 /// Phi nodes with constant expressions that can trap are not safe to if
3481 static bool canIfConvertPHINodes(BasicBlock *BB) {
3482 for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I) {
3483 PHINode *Phi = dyn_cast<PHINode>(I);
3486 for (unsigned p = 0, e = Phi->getNumIncomingValues(); p != e; ++p)
3487 if (Constant *C = dyn_cast<Constant>(Phi->getIncomingValue(p)))
3494 bool LoopVectorizationLegality::canVectorizeWithIfConvert() {
3495 if (!EnableIfConversion) {
3496 emitAnalysis(Report() << "if-conversion is disabled");
3500 assert(TheLoop->getNumBlocks() > 1 && "Single block loops are vectorizable");
3502 // A list of pointers that we can safely read and write to.
3503 SmallPtrSet<Value *, 8> SafePointes;
3505 // Collect safe addresses.
3506 for (Loop::block_iterator BI = TheLoop->block_begin(),
3507 BE = TheLoop->block_end(); BI != BE; ++BI) {
3508 BasicBlock *BB = *BI;
3510 if (blockNeedsPredication(BB))
3513 for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I) {
3514 if (LoadInst *LI = dyn_cast<LoadInst>(I))
3515 SafePointes.insert(LI->getPointerOperand());
3516 else if (StoreInst *SI = dyn_cast<StoreInst>(I))
3517 SafePointes.insert(SI->getPointerOperand());
3521 // Collect the blocks that need predication.
3522 BasicBlock *Header = TheLoop->getHeader();
3523 for (Loop::block_iterator BI = TheLoop->block_begin(),
3524 BE = TheLoop->block_end(); BI != BE; ++BI) {
3525 BasicBlock *BB = *BI;
3527 // We don't support switch statements inside loops.
3528 if (!isa<BranchInst>(BB->getTerminator())) {
3529 emitAnalysis(Report(BB->getTerminator())
3530 << "loop contains a switch statement");
3534 // We must be able to predicate all blocks that need to be predicated.
3535 if (blockNeedsPredication(BB)) {
3536 if (!blockCanBePredicated(BB, SafePointes)) {
3537 emitAnalysis(Report(BB->getTerminator())
3538 << "control flow cannot be substituted for a select");
3541 } else if (BB != Header && !canIfConvertPHINodes(BB)) {
3542 emitAnalysis(Report(BB->getTerminator())
3543 << "control flow cannot be substituted for a select");
3548 // We can if-convert this loop.
3552 bool LoopVectorizationLegality::canVectorize() {
3553 // We must have a loop in canonical form. Loops with indirectbr in them cannot
3554 // be canonicalized.
3555 if (!TheLoop->getLoopPreheader()) {
3557 Report() << "loop control flow is not understood by vectorizer");
3561 // We can only vectorize innermost loops.
3562 if (TheLoop->getSubLoopsVector().size()) {
3563 emitAnalysis(Report() << "loop is not the innermost loop");
3567 // We must have a single backedge.
3568 if (TheLoop->getNumBackEdges() != 1) {
3570 Report() << "loop control flow is not understood by vectorizer");
3574 // We must have a single exiting block.
3575 if (!TheLoop->getExitingBlock()) {
3577 Report() << "loop control flow is not understood by vectorizer");
3581 // We only handle bottom-tested loops, i.e. loop in which the condition is
3582 // checked at the end of each iteration. With that we can assume that all
3583 // instructions in the loop are executed the same number of times.
3584 if (TheLoop->getExitingBlock() != TheLoop->getLoopLatch()) {
3586 Report() << "loop control flow is not understood by vectorizer");
3590 // We need to have a loop header.
3591 DEBUG(dbgs() << "LV: Found a loop: " <<
3592 TheLoop->getHeader()->getName() << '\n');
3594 // Check if we can if-convert non-single-bb loops.
3595 unsigned NumBlocks = TheLoop->getNumBlocks();
3596 if (NumBlocks != 1 && !canVectorizeWithIfConvert()) {
3597 DEBUG(dbgs() << "LV: Can't if-convert the loop.\n");
3601 // ScalarEvolution needs to be able to find the exit count.
3602 const SCEV *ExitCount = SE->getBackedgeTakenCount(TheLoop);
3603 if (ExitCount == SE->getCouldNotCompute()) {
3604 emitAnalysis(Report() << "could not determine number of loop iterations");
3605 DEBUG(dbgs() << "LV: SCEV could not compute the loop exit count.\n");
3609 // Check if we can vectorize the instructions and CFG in this loop.
3610 if (!canVectorizeInstrs()) {
3611 DEBUG(dbgs() << "LV: Can't vectorize the instructions or CFG\n");
3615 // Go over each instruction and look at memory deps.
3616 if (!canVectorizeMemory()) {
3617 DEBUG(dbgs() << "LV: Can't vectorize due to memory conflicts\n");
3621 // Collect all of the variables that remain uniform after vectorization.
3622 collectLoopUniforms();
3624 DEBUG(dbgs() << "LV: We can vectorize this loop" <<
3625 (PtrRtCheck.Need ? " (with a runtime bound check)" : "")
3628 // Okay! We can vectorize. At this point we don't have any other mem analysis
3629 // which may limit our maximum vectorization factor, so just return true with
3634 static Type *convertPointerToIntegerType(const DataLayout &DL, Type *Ty) {
3635 if (Ty->isPointerTy())
3636 return DL.getIntPtrType(Ty);
3638 // It is possible that char's or short's overflow when we ask for the loop's
3639 // trip count, work around this by changing the type size.
3640 if (Ty->getScalarSizeInBits() < 32)
3641 return Type::getInt32Ty(Ty->getContext());
3646 static Type* getWiderType(const DataLayout &DL, Type *Ty0, Type *Ty1) {
3647 Ty0 = convertPointerToIntegerType(DL, Ty0);
3648 Ty1 = convertPointerToIntegerType(DL, Ty1);
3649 if (Ty0->getScalarSizeInBits() > Ty1->getScalarSizeInBits())
3654 /// \brief Check that the instruction has outside loop users and is not an
3655 /// identified reduction variable.
3656 static bool hasOutsideLoopUser(const Loop *TheLoop, Instruction *Inst,
3657 SmallPtrSetImpl<Value *> &Reductions) {
3658 // Reduction instructions are allowed to have exit users. All other
3659 // instructions must not have external users.
3660 if (!Reductions.count(Inst))
3661 //Check that all of the users of the loop are inside the BB.
3662 for (User *U : Inst->users()) {
3663 Instruction *UI = cast<Instruction>(U);
3664 // This user may be a reduction exit value.
3665 if (!TheLoop->contains(UI)) {
3666 DEBUG(dbgs() << "LV: Found an outside user for : " << *UI << '\n');
3673 bool LoopVectorizationLegality::canVectorizeInstrs() {
3674 BasicBlock *PreHeader = TheLoop->getLoopPreheader();
3675 BasicBlock *Header = TheLoop->getHeader();
3677 // Look for the attribute signaling the absence of NaNs.
3678 Function &F = *Header->getParent();
3679 if (F.hasFnAttribute("no-nans-fp-math"))
3680 HasFunNoNaNAttr = F.getAttributes().getAttribute(
3681 AttributeSet::FunctionIndex,
3682 "no-nans-fp-math").getValueAsString() == "true";
3684 // For each block in the loop.
3685 for (Loop::block_iterator bb = TheLoop->block_begin(),
3686 be = TheLoop->block_end(); bb != be; ++bb) {
3688 // Scan the instructions in the block and look for hazards.
3689 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e;
3692 if (PHINode *Phi = dyn_cast<PHINode>(it)) {
3693 Type *PhiTy = Phi->getType();
3694 // Check that this PHI type is allowed.
3695 if (!PhiTy->isIntegerTy() &&
3696 !PhiTy->isFloatingPointTy() &&
3697 !PhiTy->isPointerTy()) {
3698 emitAnalysis(Report(it)
3699 << "loop control flow is not understood by vectorizer");
3700 DEBUG(dbgs() << "LV: Found an non-int non-pointer PHI.\n");
3704 // If this PHINode is not in the header block, then we know that we
3705 // can convert it to select during if-conversion. No need to check if
3706 // the PHIs in this block are induction or reduction variables.
3707 if (*bb != Header) {
3708 // Check that this instruction has no outside users or is an
3709 // identified reduction value with an outside user.
3710 if (!hasOutsideLoopUser(TheLoop, it, AllowedExit))
3712 emitAnalysis(Report(it) << "value could not be identified as "
3713 "an induction or reduction variable");
3717 // We only allow if-converted PHIs with more than two incoming values.
3718 if (Phi->getNumIncomingValues() != 2) {
3719 emitAnalysis(Report(it)
3720 << "control flow not understood by vectorizer");
3721 DEBUG(dbgs() << "LV: Found an invalid PHI.\n");
3725 // This is the value coming from the preheader.
3726 Value *StartValue = Phi->getIncomingValueForBlock(PreHeader);
3727 // Check if this is an induction variable.
3728 InductionKind IK = isInductionVariable(Phi);
3730 if (IK_NoInduction != IK) {
3731 // Get the widest type.
3733 WidestIndTy = convertPointerToIntegerType(*DL, PhiTy);
3735 WidestIndTy = getWiderType(*DL, PhiTy, WidestIndTy);
3737 // Int inductions are special because we only allow one IV.
3738 if (IK == IK_IntInduction) {
3739 // Use the phi node with the widest type as induction. Use the last
3740 // one if there are multiple (no good reason for doing this other
3741 // than it is expedient).
3742 if (!Induction || PhiTy == WidestIndTy)
3746 DEBUG(dbgs() << "LV: Found an induction variable.\n");
3747 Inductions[Phi] = InductionInfo(StartValue, IK);
3749 // Until we explicitly handle the case of an induction variable with
3750 // an outside loop user we have to give up vectorizing this loop.
3751 if (hasOutsideLoopUser(TheLoop, it, AllowedExit)) {
3752 emitAnalysis(Report(it) << "use of induction value outside of the "
3753 "loop is not handled by vectorizer");
3760 if (AddReductionVar(Phi, RK_IntegerAdd)) {
3761 DEBUG(dbgs() << "LV: Found an ADD reduction PHI."<< *Phi <<"\n");
3764 if (AddReductionVar(Phi, RK_IntegerMult)) {
3765 DEBUG(dbgs() << "LV: Found a MUL reduction PHI."<< *Phi <<"\n");
3768 if (AddReductionVar(Phi, RK_IntegerOr)) {
3769 DEBUG(dbgs() << "LV: Found an OR reduction PHI."<< *Phi <<"\n");
3772 if (AddReductionVar(Phi, RK_IntegerAnd)) {
3773 DEBUG(dbgs() << "LV: Found an AND reduction PHI."<< *Phi <<"\n");
3776 if (AddReductionVar(Phi, RK_IntegerXor)) {
3777 DEBUG(dbgs() << "LV: Found a XOR reduction PHI."<< *Phi <<"\n");
3780 if (AddReductionVar(Phi, RK_IntegerMinMax)) {
3781 DEBUG(dbgs() << "LV: Found a MINMAX reduction PHI."<< *Phi <<"\n");
3784 if (AddReductionVar(Phi, RK_FloatMult)) {
3785 DEBUG(dbgs() << "LV: Found an FMult reduction PHI."<< *Phi <<"\n");
3788 if (AddReductionVar(Phi, RK_FloatAdd)) {
3789 DEBUG(dbgs() << "LV: Found an FAdd reduction PHI."<< *Phi <<"\n");
3792 if (AddReductionVar(Phi, RK_FloatMinMax)) {
3793 DEBUG(dbgs() << "LV: Found an float MINMAX reduction PHI."<< *Phi <<
3798 emitAnalysis(Report(it) << "value that could not be identified as "
3799 "reduction is used outside the loop");
3800 DEBUG(dbgs() << "LV: Found an unidentified PHI."<< *Phi <<"\n");
3802 }// end of PHI handling
3804 // We still don't handle functions. However, we can ignore dbg intrinsic
3805 // calls and we do handle certain intrinsic and libm functions.
3806 CallInst *CI = dyn_cast<CallInst>(it);
3807 if (CI && !getIntrinsicIDForCall(CI, TLI) && !isa<DbgInfoIntrinsic>(CI)) {
3808 emitAnalysis(Report(it) << "call instruction cannot be vectorized");
3809 DEBUG(dbgs() << "LV: Found a call site.\n");
3813 // Intrinsics such as powi,cttz and ctlz are legal to vectorize if the
3814 // second argument is the same (i.e. loop invariant)
3816 hasVectorInstrinsicScalarOpd(getIntrinsicIDForCall(CI, TLI), 1)) {
3817 if (!SE->isLoopInvariant(SE->getSCEV(CI->getOperand(1)), TheLoop)) {
3818 emitAnalysis(Report(it)
3819 << "intrinsic instruction cannot be vectorized");
3820 DEBUG(dbgs() << "LV: Found unvectorizable intrinsic " << *CI << "\n");
3825 // Check that the instruction return type is vectorizable.
3826 // Also, we can't vectorize extractelement instructions.
3827 if ((!VectorType::isValidElementType(it->getType()) &&
3828 !it->getType()->isVoidTy()) || isa<ExtractElementInst>(it)) {
3829 emitAnalysis(Report(it)
3830 << "instruction return type cannot be vectorized");
3831 DEBUG(dbgs() << "LV: Found unvectorizable type.\n");
3835 // Check that the stored type is vectorizable.
3836 if (StoreInst *ST = dyn_cast<StoreInst>(it)) {
3837 Type *T = ST->getValueOperand()->getType();
3838 if (!VectorType::isValidElementType(T)) {
3839 emitAnalysis(Report(ST) << "store instruction cannot be vectorized");
3842 if (EnableMemAccessVersioning)
3843 collectStridedAcccess(ST);
3846 if (EnableMemAccessVersioning)
3847 if (LoadInst *LI = dyn_cast<LoadInst>(it))
3848 collectStridedAcccess(LI);
3850 // Reduction instructions are allowed to have exit users.
3851 // All other instructions must not have external users.
3852 if (hasOutsideLoopUser(TheLoop, it, AllowedExit)) {
3853 emitAnalysis(Report(it) << "value cannot be used outside the loop");
3862 DEBUG(dbgs() << "LV: Did not find one integer induction var.\n");
3863 if (Inductions.empty()) {
3864 emitAnalysis(Report()
3865 << "loop induction variable could not be identified");
3873 ///\brief Remove GEPs whose indices but the last one are loop invariant and
3874 /// return the induction operand of the gep pointer.
3875 static Value *stripGetElementPtr(Value *Ptr, ScalarEvolution *SE,
3876 const DataLayout *DL, Loop *Lp) {
3877 GetElementPtrInst *GEP = dyn_cast<GetElementPtrInst>(Ptr);
3881 unsigned InductionOperand = getGEPInductionOperand(DL, GEP);
3883 // Check that all of the gep indices are uniform except for our induction
3885 for (unsigned i = 0, e = GEP->getNumOperands(); i != e; ++i)
3886 if (i != InductionOperand &&
3887 !SE->isLoopInvariant(SE->getSCEV(GEP->getOperand(i)), Lp))
3889 return GEP->getOperand(InductionOperand);
3892 ///\brief Look for a cast use of the passed value.
3893 static Value *getUniqueCastUse(Value *Ptr, Loop *Lp, Type *Ty) {
3894 Value *UniqueCast = nullptr;
3895 for (User *U : Ptr->users()) {
3896 CastInst *CI = dyn_cast<CastInst>(U);
3897 if (CI && CI->getType() == Ty) {
3907 ///\brief Get the stride of a pointer access in a loop.
3908 /// Looks for symbolic strides "a[i*stride]". Returns the symbolic stride as a
3909 /// pointer to the Value, or null otherwise.
3910 static Value *getStrideFromPointer(Value *Ptr, ScalarEvolution *SE,
3911 const DataLayout *DL, Loop *Lp) {
3912 const PointerType *PtrTy = dyn_cast<PointerType>(Ptr->getType());
3913 if (!PtrTy || PtrTy->isAggregateType())
3916 // Try to remove a gep instruction to make the pointer (actually index at this
3917 // point) easier analyzable. If OrigPtr is equal to Ptr we are analzying the
3918 // pointer, otherwise, we are analyzing the index.
3919 Value *OrigPtr = Ptr;
3921 // The size of the pointer access.
3922 int64_t PtrAccessSize = 1;
3924 Ptr = stripGetElementPtr(Ptr, SE, DL, Lp);
3925 const SCEV *V = SE->getSCEV(Ptr);
3929 while (const SCEVCastExpr *C = dyn_cast<SCEVCastExpr>(V))
3930 V = C->getOperand();
3932 const SCEVAddRecExpr *S = dyn_cast<SCEVAddRecExpr>(V);
3936 V = S->getStepRecurrence(*SE);
3940 // Strip off the size of access multiplication if we are still analyzing the
3942 if (OrigPtr == Ptr) {
3943 DL->getTypeAllocSize(PtrTy->getElementType());
3944 if (const SCEVMulExpr *M = dyn_cast<SCEVMulExpr>(V)) {
3945 if (M->getOperand(0)->getSCEVType() != scConstant)
3948 const APInt &APStepVal =
3949 cast<SCEVConstant>(M->getOperand(0))->getValue()->getValue();
3951 // Huge step value - give up.
3952 if (APStepVal.getBitWidth() > 64)
3955 int64_t StepVal = APStepVal.getSExtValue();
3956 if (PtrAccessSize != StepVal)
3958 V = M->getOperand(1);
3963 Type *StripedOffRecurrenceCast = nullptr;
3964 if (const SCEVCastExpr *C = dyn_cast<SCEVCastExpr>(V)) {
3965 StripedOffRecurrenceCast = C->getType();
3966 V = C->getOperand();
3969 // Look for the loop invariant symbolic value.
3970 const SCEVUnknown *U = dyn_cast<SCEVUnknown>(V);
3974 Value *Stride = U->getValue();
3975 if (!Lp->isLoopInvariant(Stride))
3978 // If we have stripped off the recurrence cast we have to make sure that we
3979 // return the value that is used in this loop so that we can replace it later.
3980 if (StripedOffRecurrenceCast)
3981 Stride = getUniqueCastUse(Stride, Lp, StripedOffRecurrenceCast);
3986 void LoopVectorizationLegality::collectStridedAcccess(Value *MemAccess) {
3987 Value *Ptr = nullptr;
3988 if (LoadInst *LI = dyn_cast<LoadInst>(MemAccess))
3989 Ptr = LI->getPointerOperand();
3990 else if (StoreInst *SI = dyn_cast<StoreInst>(MemAccess))
3991 Ptr = SI->getPointerOperand();
3995 Value *Stride = getStrideFromPointer(Ptr, SE, DL, TheLoop);
3999 DEBUG(dbgs() << "LV: Found a strided access that we can version");
4000 DEBUG(dbgs() << " Ptr: " << *Ptr << " Stride: " << *Stride << "\n");
4001 Strides[Ptr] = Stride;
4002 StrideSet.insert(Stride);
4005 void LoopVectorizationLegality::collectLoopUniforms() {
4006 // We now know that the loop is vectorizable!
4007 // Collect variables that will remain uniform after vectorization.
4008 std::vector<Value*> Worklist;
4009 BasicBlock *Latch = TheLoop->getLoopLatch();
4011 // Start with the conditional branch and walk up the block.
4012 Worklist.push_back(Latch->getTerminator()->getOperand(0));
4014 // Also add all consecutive pointer values; these values will be uniform
4015 // after vectorization (and subsequent cleanup) and, until revectorization is
4016 // supported, all dependencies must also be uniform.
4017 for (Loop::block_iterator B = TheLoop->block_begin(),
4018 BE = TheLoop->block_end(); B != BE; ++B)
4019 for (BasicBlock::iterator I = (*B)->begin(), IE = (*B)->end();
4021 if (I->getType()->isPointerTy() && isConsecutivePtr(I))
4022 Worklist.insert(Worklist.end(), I->op_begin(), I->op_end());
4024 while (Worklist.size()) {
4025 Instruction *I = dyn_cast<Instruction>(Worklist.back());
4026 Worklist.pop_back();
4028 // Look at instructions inside this loop.
4029 // Stop when reaching PHI nodes.
4030 // TODO: we need to follow values all over the loop, not only in this block.
4031 if (!I || !TheLoop->contains(I) || isa<PHINode>(I))
4034 // This is a known uniform.
4037 // Insert all operands.
4038 Worklist.insert(Worklist.end(), I->op_begin(), I->op_end());
4043 /// \brief Analyses memory accesses in a loop.
4045 /// Checks whether run time pointer checks are needed and builds sets for data
4046 /// dependence checking.
4047 class AccessAnalysis {
4049 /// \brief Read or write access location.
4050 typedef PointerIntPair<Value *, 1, bool> MemAccessInfo;
4051 typedef SmallPtrSet<MemAccessInfo, 8> MemAccessInfoSet;
4053 /// \brief Set of potential dependent memory accesses.
4054 typedef EquivalenceClasses<MemAccessInfo> DepCandidates;
4056 AccessAnalysis(const DataLayout *Dl, AliasAnalysis *AA, DepCandidates &DA) :
4057 DL(Dl), AST(*AA), DepCands(DA), IsRTCheckNeeded(false) {}
4059 /// \brief Register a load and whether it is only read from.
4060 void addLoad(AliasAnalysis::Location &Loc, bool IsReadOnly) {
4061 Value *Ptr = const_cast<Value*>(Loc.Ptr);
4062 AST.add(Ptr, AliasAnalysis::UnknownSize, Loc.AATags);
4063 Accesses.insert(MemAccessInfo(Ptr, false));
4065 ReadOnlyPtr.insert(Ptr);
4068 /// \brief Register a store.
4069 void addStore(AliasAnalysis::Location &Loc) {
4070 Value *Ptr = const_cast<Value*>(Loc.Ptr);
4071 AST.add(Ptr, AliasAnalysis::UnknownSize, Loc.AATags);
4072 Accesses.insert(MemAccessInfo(Ptr, true));
4075 /// \brief Check whether we can check the pointers at runtime for
4076 /// non-intersection.
4077 bool canCheckPtrAtRT(LoopVectorizationLegality::RuntimePointerCheck &RtCheck,
4078 unsigned &NumComparisons, ScalarEvolution *SE,
4079 Loop *TheLoop, ValueToValueMap &Strides,
4080 bool ShouldCheckStride = false);
4082 /// \brief Goes over all memory accesses, checks whether a RT check is needed
4083 /// and builds sets of dependent accesses.
4084 void buildDependenceSets() {
4085 processMemAccesses();
4088 bool isRTCheckNeeded() { return IsRTCheckNeeded; }
4090 bool isDependencyCheckNeeded() { return !CheckDeps.empty(); }
4091 void resetDepChecks() { CheckDeps.clear(); }
4093 MemAccessInfoSet &getDependenciesToCheck() { return CheckDeps; }
4096 typedef SetVector<MemAccessInfo> PtrAccessSet;
4098 /// \brief Go over all memory access and check whether runtime pointer checks
4099 /// are needed /// and build sets of dependency check candidates.
4100 void processMemAccesses();
4102 /// Set of all accesses.
4103 PtrAccessSet Accesses;
4105 /// Set of accesses that need a further dependence check.
4106 MemAccessInfoSet CheckDeps;
4108 /// Set of pointers that are read only.
4109 SmallPtrSet<Value*, 16> ReadOnlyPtr;
4111 const DataLayout *DL;
4113 /// An alias set tracker to partition the access set by underlying object and
4114 //intrinsic property (such as TBAA metadata).
4115 AliasSetTracker AST;
4117 /// Sets of potentially dependent accesses - members of one set share an
4118 /// underlying pointer. The set "CheckDeps" identfies which sets really need a
4119 /// dependence check.
4120 DepCandidates &DepCands;
4122 bool IsRTCheckNeeded;
4125 } // end anonymous namespace
4127 /// \brief Check whether a pointer can participate in a runtime bounds check.
4128 static bool hasComputableBounds(ScalarEvolution *SE, ValueToValueMap &Strides,
4130 const SCEV *PtrScev = replaceSymbolicStrideSCEV(SE, Strides, Ptr);
4131 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PtrScev);
4135 return AR->isAffine();
4138 /// \brief Check the stride of the pointer and ensure that it does not wrap in
4139 /// the address space.
4140 static int isStridedPtr(ScalarEvolution *SE, const DataLayout *DL, Value *Ptr,
4141 const Loop *Lp, ValueToValueMap &StridesMap);
4143 bool AccessAnalysis::canCheckPtrAtRT(
4144 LoopVectorizationLegality::RuntimePointerCheck &RtCheck,
4145 unsigned &NumComparisons, ScalarEvolution *SE, Loop *TheLoop,
4146 ValueToValueMap &StridesMap, bool ShouldCheckStride) {
4147 // Find pointers with computable bounds. We are going to use this information
4148 // to place a runtime bound check.
4149 bool CanDoRT = true;
4151 bool IsDepCheckNeeded = isDependencyCheckNeeded();
4154 // We assign a consecutive id to access from different alias sets.
4155 // Accesses between different groups doesn't need to be checked.
4157 for (auto &AS : AST) {
4158 unsigned NumReadPtrChecks = 0;
4159 unsigned NumWritePtrChecks = 0;
4161 // We assign consecutive id to access from different dependence sets.
4162 // Accesses within the same set don't need a runtime check.
4163 unsigned RunningDepId = 1;
4164 DenseMap<Value *, unsigned> DepSetId;
4167 Value *Ptr = A.getValue();
4168 bool IsWrite = Accesses.count(MemAccessInfo(Ptr, true));
4169 MemAccessInfo Access(Ptr, IsWrite);
4172 ++NumWritePtrChecks;
4176 if (hasComputableBounds(SE, StridesMap, Ptr) &&
4177 // When we run after a failing dependency check we have to make sure we
4178 // don't have wrapping pointers.
4179 (!ShouldCheckStride ||
4180 isStridedPtr(SE, DL, Ptr, TheLoop, StridesMap) == 1)) {
4181 // The id of the dependence set.
4184 if (IsDepCheckNeeded) {
4185 Value *Leader = DepCands.getLeaderValue(Access).getPointer();
4186 unsigned &LeaderId = DepSetId[Leader];
4188 LeaderId = RunningDepId++;
4191 // Each access has its own dependence set.
4192 DepId = RunningDepId++;
4194 RtCheck.insert(SE, TheLoop, Ptr, IsWrite, DepId, ASId, StridesMap);
4196 DEBUG(dbgs() << "LV: Found a runtime check ptr:" << *Ptr << '\n');
4202 if (IsDepCheckNeeded && CanDoRT && RunningDepId == 2)
4203 NumComparisons += 0; // Only one dependence set.
4205 NumComparisons += (NumWritePtrChecks * (NumReadPtrChecks +
4206 NumWritePtrChecks - 1));
4212 // If the pointers that we would use for the bounds comparison have different
4213 // address spaces, assume the values aren't directly comparable, so we can't
4214 // use them for the runtime check. We also have to assume they could
4215 // overlap. In the future there should be metadata for whether address spaces
4217 unsigned NumPointers = RtCheck.Pointers.size();
4218 for (unsigned i = 0; i < NumPointers; ++i) {
4219 for (unsigned j = i + 1; j < NumPointers; ++j) {
4220 // Only need to check pointers between two different dependency sets.
4221 if (RtCheck.DependencySetId[i] == RtCheck.DependencySetId[j])
4223 // Only need to check pointers in the same alias set.
4224 if (RtCheck.AliasSetId[i] != RtCheck.AliasSetId[j])
4227 Value *PtrI = RtCheck.Pointers[i];
4228 Value *PtrJ = RtCheck.Pointers[j];
4230 unsigned ASi = PtrI->getType()->getPointerAddressSpace();
4231 unsigned ASj = PtrJ->getType()->getPointerAddressSpace();
4233 DEBUG(dbgs() << "LV: Runtime check would require comparison between"
4234 " different address spaces\n");
4243 void AccessAnalysis::processMemAccesses() {
4244 // We process the set twice: first we process read-write pointers, last we
4245 // process read-only pointers. This allows us to skip dependence tests for
4246 // read-only pointers.
4248 DEBUG(dbgs() << "LV: Processing memory accesses...\n");
4249 DEBUG(dbgs() << " AST: "; AST.dump());
4250 DEBUG(dbgs() << "LV: Accesses:\n");
4252 for (auto A : Accesses)
4253 dbgs() << "\t" << *A.getPointer() << " (" <<
4254 (A.getInt() ? "write" : (ReadOnlyPtr.count(A.getPointer()) ?
4255 "read-only" : "read")) << ")\n";
4258 // The AliasSetTracker has nicely partitioned our pointers by metadata
4259 // compatibility and potential for underlying-object overlap. As a result, we
4260 // only need to check for potential pointer dependencies within each alias
4262 for (auto &AS : AST) {
4263 // Note that both the alias-set tracker and the alias sets themselves used
4264 // linked lists internally and so the iteration order here is deterministic
4265 // (matching the original instruction order within each set).
4267 bool SetHasWrite = false;
4269 // Map of pointers to last access encountered.
4270 typedef DenseMap<Value*, MemAccessInfo> UnderlyingObjToAccessMap;
4271 UnderlyingObjToAccessMap ObjToLastAccess;
4273 // Set of access to check after all writes have been processed.
4274 PtrAccessSet DeferredAccesses;
4276 // Iterate over each alias set twice, once to process read/write pointers,
4277 // and then to process read-only pointers.
4278 for (int SetIteration = 0; SetIteration < 2; ++SetIteration) {
4279 bool UseDeferred = SetIteration > 0;
4280 PtrAccessSet &S = UseDeferred ? DeferredAccesses : Accesses;
4283 Value *Ptr = A.getValue();
4284 bool IsWrite = S.count(MemAccessInfo(Ptr, true));
4286 // If we're using the deferred access set, then it contains only reads.
4287 bool IsReadOnlyPtr = ReadOnlyPtr.count(Ptr) && !IsWrite;
4288 if (UseDeferred && !IsReadOnlyPtr)
4290 // Otherwise, the pointer must be in the PtrAccessSet, either as a read
4292 assert(((IsReadOnlyPtr && UseDeferred) || IsWrite ||
4293 S.count(MemAccessInfo(Ptr, false))) &&
4294 "Alias-set pointer not in the access set?");
4296 MemAccessInfo Access(Ptr, IsWrite);
4297 DepCands.insert(Access);
4299 // Memorize read-only pointers for later processing and skip them in the
4300 // first round (they need to be checked after we have seen all write
4301 // pointers). Note: we also mark pointer that are not consecutive as
4302 // "read-only" pointers (so that we check "a[b[i]] +="). Hence, we need
4303 // the second check for "!IsWrite".
4304 if (!UseDeferred && IsReadOnlyPtr) {
4305 DeferredAccesses.insert(Access);
4309 // If this is a write - check other reads and writes for conflicts. If
4310 // this is a read only check other writes for conflicts (but only if
4311 // there is no other write to the ptr - this is an optimization to
4312 // catch "a[i] = a[i] + " without having to do a dependence check).
4313 if ((IsWrite || IsReadOnlyPtr) && SetHasWrite) {
4314 CheckDeps.insert(Access);
4315 IsRTCheckNeeded = true;
4321 // Create sets of pointers connected by a shared alias set and
4322 // underlying object.
4323 typedef SmallVector<Value *, 16> ValueVector;
4324 ValueVector TempObjects;
4325 GetUnderlyingObjects(Ptr, TempObjects, DL);
4326 for (Value *UnderlyingObj : TempObjects) {
4327 UnderlyingObjToAccessMap::iterator Prev =
4328 ObjToLastAccess.find(UnderlyingObj);
4329 if (Prev != ObjToLastAccess.end())
4330 DepCands.unionSets(Access, Prev->second);
4332 ObjToLastAccess[UnderlyingObj] = Access;
4340 /// \brief Checks memory dependences among accesses to the same underlying
4341 /// object to determine whether there vectorization is legal or not (and at
4342 /// which vectorization factor).
4344 /// This class works under the assumption that we already checked that memory
4345 /// locations with different underlying pointers are "must-not alias".
4346 /// We use the ScalarEvolution framework to symbolically evalutate access
4347 /// functions pairs. Since we currently don't restructure the loop we can rely
4348 /// on the program order of memory accesses to determine their safety.
4349 /// At the moment we will only deem accesses as safe for:
4350 /// * A negative constant distance assuming program order.
4352 /// Safe: tmp = a[i + 1]; OR a[i + 1] = x;
4353 /// a[i] = tmp; y = a[i];
4355 /// The latter case is safe because later checks guarantuee that there can't
4356 /// be a cycle through a phi node (that is, we check that "x" and "y" is not
4357 /// the same variable: a header phi can only be an induction or a reduction, a
4358 /// reduction can't have a memory sink, an induction can't have a memory
4359 /// source). This is important and must not be violated (or we have to
4360 /// resort to checking for cycles through memory).
4362 /// * A positive constant distance assuming program order that is bigger
4363 /// than the biggest memory access.
4365 /// tmp = a[i] OR b[i] = x
4366 /// a[i+2] = tmp y = b[i+2];
4368 /// Safe distance: 2 x sizeof(a[0]), and 2 x sizeof(b[0]), respectively.
4370 /// * Zero distances and all accesses have the same size.
4372 class MemoryDepChecker {
4374 typedef PointerIntPair<Value *, 1, bool> MemAccessInfo;
4375 typedef SmallPtrSet<MemAccessInfo, 8> MemAccessInfoSet;
4377 MemoryDepChecker(ScalarEvolution *Se, const DataLayout *Dl, const Loop *L)
4378 : SE(Se), DL(Dl), InnermostLoop(L), AccessIdx(0),
4379 ShouldRetryWithRuntimeCheck(false) {}
4381 /// \brief Register the location (instructions are given increasing numbers)
4382 /// of a write access.
4383 void addAccess(StoreInst *SI) {
4384 Value *Ptr = SI->getPointerOperand();
4385 Accesses[MemAccessInfo(Ptr, true)].push_back(AccessIdx);
4386 InstMap.push_back(SI);
4390 /// \brief Register the location (instructions are given increasing numbers)
4391 /// of a write access.
4392 void addAccess(LoadInst *LI) {
4393 Value *Ptr = LI->getPointerOperand();
4394 Accesses[MemAccessInfo(Ptr, false)].push_back(AccessIdx);
4395 InstMap.push_back(LI);
4399 /// \brief Check whether the dependencies between the accesses are safe.
4401 /// Only checks sets with elements in \p CheckDeps.
4402 bool areDepsSafe(AccessAnalysis::DepCandidates &AccessSets,
4403 MemAccessInfoSet &CheckDeps, ValueToValueMap &Strides);
4405 /// \brief The maximum number of bytes of a vector register we can vectorize
4406 /// the accesses safely with.
4407 unsigned getMaxSafeDepDistBytes() { return MaxSafeDepDistBytes; }
4409 /// \brief In same cases when the dependency check fails we can still
4410 /// vectorize the loop with a dynamic array access check.
4411 bool shouldRetryWithRuntimeCheck() { return ShouldRetryWithRuntimeCheck; }
4414 ScalarEvolution *SE;
4415 const DataLayout *DL;
4416 const Loop *InnermostLoop;
4418 /// \brief Maps access locations (ptr, read/write) to program order.
4419 DenseMap<MemAccessInfo, std::vector<unsigned> > Accesses;
4421 /// \brief Memory access instructions in program order.
4422 SmallVector<Instruction *, 16> InstMap;
4424 /// \brief The program order index to be used for the next instruction.
4427 // We can access this many bytes in parallel safely.
4428 unsigned MaxSafeDepDistBytes;
4430 /// \brief If we see a non-constant dependence distance we can still try to
4431 /// vectorize this loop with runtime checks.
4432 bool ShouldRetryWithRuntimeCheck;
4434 /// \brief Check whether there is a plausible dependence between the two
4437 /// Access \p A must happen before \p B in program order. The two indices
4438 /// identify the index into the program order map.
4440 /// This function checks whether there is a plausible dependence (or the
4441 /// absence of such can't be proved) between the two accesses. If there is a
4442 /// plausible dependence but the dependence distance is bigger than one
4443 /// element access it records this distance in \p MaxSafeDepDistBytes (if this
4444 /// distance is smaller than any other distance encountered so far).
4445 /// Otherwise, this function returns true signaling a possible dependence.
4446 bool isDependent(const MemAccessInfo &A, unsigned AIdx,
4447 const MemAccessInfo &B, unsigned BIdx,
4448 ValueToValueMap &Strides);
4450 /// \brief Check whether the data dependence could prevent store-load
4452 bool couldPreventStoreLoadForward(unsigned Distance, unsigned TypeByteSize);
4455 } // end anonymous namespace
4457 static bool isInBoundsGep(Value *Ptr) {
4458 if (GetElementPtrInst *GEP = dyn_cast<GetElementPtrInst>(Ptr))
4459 return GEP->isInBounds();
4463 /// \brief Check whether the access through \p Ptr has a constant stride.
4464 static int isStridedPtr(ScalarEvolution *SE, const DataLayout *DL, Value *Ptr,
4465 const Loop *Lp, ValueToValueMap &StridesMap) {
4466 const Type *Ty = Ptr->getType();
4467 assert(Ty->isPointerTy() && "Unexpected non-ptr");
4469 // Make sure that the pointer does not point to aggregate types.
4470 const PointerType *PtrTy = cast<PointerType>(Ty);
4471 if (PtrTy->getElementType()->isAggregateType()) {
4472 DEBUG(dbgs() << "LV: Bad stride - Not a pointer to a scalar type" << *Ptr <<
4477 const SCEV *PtrScev = replaceSymbolicStrideSCEV(SE, StridesMap, Ptr);
4479 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PtrScev);
4481 DEBUG(dbgs() << "LV: Bad stride - Not an AddRecExpr pointer "
4482 << *Ptr << " SCEV: " << *PtrScev << "\n");
4486 // The accesss function must stride over the innermost loop.
4487 if (Lp != AR->getLoop()) {
4488 DEBUG(dbgs() << "LV: Bad stride - Not striding over innermost loop " <<
4489 *Ptr << " SCEV: " << *PtrScev << "\n");
4492 // The address calculation must not wrap. Otherwise, a dependence could be
4494 // An inbounds getelementptr that is a AddRec with a unit stride
4495 // cannot wrap per definition. The unit stride requirement is checked later.
4496 // An getelementptr without an inbounds attribute and unit stride would have
4497 // to access the pointer value "0" which is undefined behavior in address
4498 // space 0, therefore we can also vectorize this case.
4499 bool IsInBoundsGEP = isInBoundsGep(Ptr);
4500 bool IsNoWrapAddRec = AR->getNoWrapFlags(SCEV::NoWrapMask);
4501 bool IsInAddressSpaceZero = PtrTy->getAddressSpace() == 0;
4502 if (!IsNoWrapAddRec && !IsInBoundsGEP && !IsInAddressSpaceZero) {
4503 DEBUG(dbgs() << "LV: Bad stride - Pointer may wrap in the address space "
4504 << *Ptr << " SCEV: " << *PtrScev << "\n");
4508 // Check the step is constant.
4509 const SCEV *Step = AR->getStepRecurrence(*SE);
4511 // Calculate the pointer stride and check if it is consecutive.
4512 const SCEVConstant *C = dyn_cast<SCEVConstant>(Step);
4514 DEBUG(dbgs() << "LV: Bad stride - Not a constant strided " << *Ptr <<
4515 " SCEV: " << *PtrScev << "\n");
4519 int64_t Size = DL->getTypeAllocSize(PtrTy->getElementType());
4520 const APInt &APStepVal = C->getValue()->getValue();
4522 // Huge step value - give up.
4523 if (APStepVal.getBitWidth() > 64)
4526 int64_t StepVal = APStepVal.getSExtValue();
4529 int64_t Stride = StepVal / Size;
4530 int64_t Rem = StepVal % Size;
4534 // If the SCEV could wrap but we have an inbounds gep with a unit stride we
4535 // know we can't "wrap around the address space". In case of address space
4536 // zero we know that this won't happen without triggering undefined behavior.
4537 if (!IsNoWrapAddRec && (IsInBoundsGEP || IsInAddressSpaceZero) &&
4538 Stride != 1 && Stride != -1)
4544 bool MemoryDepChecker::couldPreventStoreLoadForward(unsigned Distance,
4545 unsigned TypeByteSize) {
4546 // If loads occur at a distance that is not a multiple of a feasible vector
4547 // factor store-load forwarding does not take place.
4548 // Positive dependences might cause troubles because vectorizing them might
4549 // prevent store-load forwarding making vectorized code run a lot slower.
4550 // a[i] = a[i-3] ^ a[i-8];
4551 // The stores to a[i:i+1] don't align with the stores to a[i-3:i-2] and
4552 // hence on your typical architecture store-load forwarding does not take
4553 // place. Vectorizing in such cases does not make sense.
4554 // Store-load forwarding distance.
4555 const unsigned NumCyclesForStoreLoadThroughMemory = 8*TypeByteSize;
4556 // Maximum vector factor.
4557 unsigned MaxVFWithoutSLForwardIssues = MaxVectorWidth*TypeByteSize;
4558 if(MaxSafeDepDistBytes < MaxVFWithoutSLForwardIssues)
4559 MaxVFWithoutSLForwardIssues = MaxSafeDepDistBytes;
4561 for (unsigned vf = 2*TypeByteSize; vf <= MaxVFWithoutSLForwardIssues;
4563 if (Distance % vf && Distance / vf < NumCyclesForStoreLoadThroughMemory) {
4564 MaxVFWithoutSLForwardIssues = (vf >>=1);
4569 if (MaxVFWithoutSLForwardIssues< 2*TypeByteSize) {
4570 DEBUG(dbgs() << "LV: Distance " << Distance <<
4571 " that could cause a store-load forwarding conflict\n");
4575 if (MaxVFWithoutSLForwardIssues < MaxSafeDepDistBytes &&
4576 MaxVFWithoutSLForwardIssues != MaxVectorWidth*TypeByteSize)
4577 MaxSafeDepDistBytes = MaxVFWithoutSLForwardIssues;
4581 bool MemoryDepChecker::isDependent(const MemAccessInfo &A, unsigned AIdx,
4582 const MemAccessInfo &B, unsigned BIdx,
4583 ValueToValueMap &Strides) {
4584 assert (AIdx < BIdx && "Must pass arguments in program order");
4586 Value *APtr = A.getPointer();
4587 Value *BPtr = B.getPointer();
4588 bool AIsWrite = A.getInt();
4589 bool BIsWrite = B.getInt();
4591 // Two reads are independent.
4592 if (!AIsWrite && !BIsWrite)
4595 // We cannot check pointers in different address spaces.
4596 if (APtr->getType()->getPointerAddressSpace() !=
4597 BPtr->getType()->getPointerAddressSpace())
4600 const SCEV *AScev = replaceSymbolicStrideSCEV(SE, Strides, APtr);
4601 const SCEV *BScev = replaceSymbolicStrideSCEV(SE, Strides, BPtr);
4603 int StrideAPtr = isStridedPtr(SE, DL, APtr, InnermostLoop, Strides);
4604 int StrideBPtr = isStridedPtr(SE, DL, BPtr, InnermostLoop, Strides);
4606 const SCEV *Src = AScev;
4607 const SCEV *Sink = BScev;
4609 // If the induction step is negative we have to invert source and sink of the
4611 if (StrideAPtr < 0) {
4614 std::swap(APtr, BPtr);
4615 std::swap(Src, Sink);
4616 std::swap(AIsWrite, BIsWrite);
4617 std::swap(AIdx, BIdx);
4618 std::swap(StrideAPtr, StrideBPtr);
4621 const SCEV *Dist = SE->getMinusSCEV(Sink, Src);
4623 DEBUG(dbgs() << "LV: Src Scev: " << *Src << "Sink Scev: " << *Sink
4624 << "(Induction step: " << StrideAPtr << ")\n");
4625 DEBUG(dbgs() << "LV: Distance for " << *InstMap[AIdx] << " to "
4626 << *InstMap[BIdx] << ": " << *Dist << "\n");
4628 // Need consecutive accesses. We don't want to vectorize
4629 // "A[B[i]] += ..." and similar code or pointer arithmetic that could wrap in
4630 // the address space.
4631 if (!StrideAPtr || !StrideBPtr || StrideAPtr != StrideBPtr){
4632 DEBUG(dbgs() << "Non-consecutive pointer access\n");
4636 const SCEVConstant *C = dyn_cast<SCEVConstant>(Dist);
4638 DEBUG(dbgs() << "LV: Dependence because of non-constant distance\n");
4639 ShouldRetryWithRuntimeCheck = true;
4643 Type *ATy = APtr->getType()->getPointerElementType();
4644 Type *BTy = BPtr->getType()->getPointerElementType();
4645 unsigned TypeByteSize = DL->getTypeAllocSize(ATy);
4647 // Negative distances are not plausible dependencies.
4648 const APInt &Val = C->getValue()->getValue();
4649 if (Val.isNegative()) {
4650 bool IsTrueDataDependence = (AIsWrite && !BIsWrite);
4651 if (IsTrueDataDependence &&
4652 (couldPreventStoreLoadForward(Val.abs().getZExtValue(), TypeByteSize) ||
4656 DEBUG(dbgs() << "LV: Dependence is negative: NoDep\n");
4660 // Write to the same location with the same size.
4661 // Could be improved to assert type sizes are the same (i32 == float, etc).
4665 DEBUG(dbgs() << "LV: Zero dependence difference but different types\n");
4669 assert(Val.isStrictlyPositive() && "Expect a positive value");
4671 // Positive distance bigger than max vectorization factor.
4674 "LV: ReadWrite-Write positive dependency with different types\n");
4678 unsigned Distance = (unsigned) Val.getZExtValue();
4680 // Bail out early if passed-in parameters make vectorization not feasible.
4681 unsigned ForcedFactor = VectorizationFactor ? VectorizationFactor : 1;
4682 unsigned ForcedUnroll = VectorizationInterleave ? VectorizationInterleave : 1;
4684 // The distance must be bigger than the size needed for a vectorized version
4685 // of the operation and the size of the vectorized operation must not be
4686 // bigger than the currrent maximum size.
4687 if (Distance < 2*TypeByteSize ||
4688 2*TypeByteSize > MaxSafeDepDistBytes ||
4689 Distance < TypeByteSize * ForcedUnroll * ForcedFactor) {
4690 DEBUG(dbgs() << "LV: Failure because of Positive distance "
4691 << Val.getSExtValue() << '\n');
4695 MaxSafeDepDistBytes = Distance < MaxSafeDepDistBytes ?
4696 Distance : MaxSafeDepDistBytes;
4698 bool IsTrueDataDependence = (!AIsWrite && BIsWrite);
4699 if (IsTrueDataDependence &&
4700 couldPreventStoreLoadForward(Distance, TypeByteSize))
4703 DEBUG(dbgs() << "LV: Positive distance " << Val.getSExtValue() <<
4704 " with max VF = " << MaxSafeDepDistBytes / TypeByteSize << '\n');
4709 bool MemoryDepChecker::areDepsSafe(AccessAnalysis::DepCandidates &AccessSets,
4710 MemAccessInfoSet &CheckDeps,
4711 ValueToValueMap &Strides) {
4713 MaxSafeDepDistBytes = -1U;
4714 while (!CheckDeps.empty()) {
4715 MemAccessInfo CurAccess = *CheckDeps.begin();
4717 // Get the relevant memory access set.
4718 EquivalenceClasses<MemAccessInfo>::iterator I =
4719 AccessSets.findValue(AccessSets.getLeaderValue(CurAccess));
4721 // Check accesses within this set.
4722 EquivalenceClasses<MemAccessInfo>::member_iterator AI, AE;
4723 AI = AccessSets.member_begin(I), AE = AccessSets.member_end();
4725 // Check every access pair.
4727 CheckDeps.erase(*AI);
4728 EquivalenceClasses<MemAccessInfo>::member_iterator OI = std::next(AI);
4730 // Check every accessing instruction pair in program order.
4731 for (std::vector<unsigned>::iterator I1 = Accesses[*AI].begin(),
4732 I1E = Accesses[*AI].end(); I1 != I1E; ++I1)
4733 for (std::vector<unsigned>::iterator I2 = Accesses[*OI].begin(),
4734 I2E = Accesses[*OI].end(); I2 != I2E; ++I2) {
4735 if (*I1 < *I2 && isDependent(*AI, *I1, *OI, *I2, Strides))
4737 if (*I2 < *I1 && isDependent(*OI, *I2, *AI, *I1, Strides))
4748 bool LoopVectorizationLegality::canVectorizeMemory() {
4750 typedef SmallVector<Value*, 16> ValueVector;
4751 typedef SmallPtrSet<Value*, 16> ValueSet;
4753 // Holds the Load and Store *instructions*.
4757 // Holds all the different accesses in the loop.
4758 unsigned NumReads = 0;
4759 unsigned NumReadWrites = 0;
4761 PtrRtCheck.Pointers.clear();
4762 PtrRtCheck.Need = false;
4764 const bool IsAnnotatedParallel = TheLoop->isAnnotatedParallel();
4765 MemoryDepChecker DepChecker(SE, DL, TheLoop);
4768 for (Loop::block_iterator bb = TheLoop->block_begin(),
4769 be = TheLoop->block_end(); bb != be; ++bb) {
4771 // Scan the BB and collect legal loads and stores.
4772 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e;
4775 // If this is a load, save it. If this instruction can read from memory
4776 // but is not a load, then we quit. Notice that we don't handle function
4777 // calls that read or write.
4778 if (it->mayReadFromMemory()) {
4779 // Many math library functions read the rounding mode. We will only
4780 // vectorize a loop if it contains known function calls that don't set
4781 // the flag. Therefore, it is safe to ignore this read from memory.
4782 CallInst *Call = dyn_cast<CallInst>(it);
4783 if (Call && getIntrinsicIDForCall(Call, TLI))
4786 LoadInst *Ld = dyn_cast<LoadInst>(it);
4787 if (!Ld || (!Ld->isSimple() && !IsAnnotatedParallel)) {
4788 emitAnalysis(Report(Ld)
4789 << "read with atomic ordering or volatile read");
4790 DEBUG(dbgs() << "LV: Found a non-simple load.\n");
4794 Loads.push_back(Ld);
4795 DepChecker.addAccess(Ld);
4799 // Save 'store' instructions. Abort if other instructions write to memory.
4800 if (it->mayWriteToMemory()) {
4801 StoreInst *St = dyn_cast<StoreInst>(it);
4803 emitAnalysis(Report(it) << "instruction cannot be vectorized");
4806 if (!St->isSimple() && !IsAnnotatedParallel) {
4807 emitAnalysis(Report(St)
4808 << "write with atomic ordering or volatile write");
4809 DEBUG(dbgs() << "LV: Found a non-simple store.\n");
4813 Stores.push_back(St);
4814 DepChecker.addAccess(St);
4819 // Now we have two lists that hold the loads and the stores.
4820 // Next, we find the pointers that they use.
4822 // Check if we see any stores. If there are no stores, then we don't
4823 // care if the pointers are *restrict*.
4824 if (!Stores.size()) {
4825 DEBUG(dbgs() << "LV: Found a read-only loop!\n");
4829 AccessAnalysis::DepCandidates DependentAccesses;
4830 AccessAnalysis Accesses(DL, AA, DependentAccesses);
4832 // Holds the analyzed pointers. We don't want to call GetUnderlyingObjects
4833 // multiple times on the same object. If the ptr is accessed twice, once
4834 // for read and once for write, it will only appear once (on the write
4835 // list). This is okay, since we are going to check for conflicts between
4836 // writes and between reads and writes, but not between reads and reads.
4839 ValueVector::iterator I, IE;
4840 for (I = Stores.begin(), IE = Stores.end(); I != IE; ++I) {
4841 StoreInst *ST = cast<StoreInst>(*I);
4842 Value* Ptr = ST->getPointerOperand();
4844 if (isUniform(Ptr)) {
4847 << "write to a loop invariant address could not be vectorized");
4848 DEBUG(dbgs() << "LV: We don't allow storing to uniform addresses\n");
4852 // If we did *not* see this pointer before, insert it to the read-write
4853 // list. At this phase it is only a 'write' list.
4854 if (Seen.insert(Ptr).second) {
4857 AliasAnalysis::Location Loc = AA->getLocation(ST);
4858 // The TBAA metadata could have a control dependency on the predication
4859 // condition, so we cannot rely on it when determining whether or not we
4860 // need runtime pointer checks.
4861 if (blockNeedsPredication(ST->getParent()))
4862 Loc.AATags.TBAA = nullptr;
4864 Accesses.addStore(Loc);
4868 if (IsAnnotatedParallel) {
4870 << "LV: A loop annotated parallel, ignore memory dependency "
4875 for (I = Loads.begin(), IE = Loads.end(); I != IE; ++I) {
4876 LoadInst *LD = cast<LoadInst>(*I);
4877 Value* Ptr = LD->getPointerOperand();
4878 // If we did *not* see this pointer before, insert it to the
4879 // read list. If we *did* see it before, then it is already in
4880 // the read-write list. This allows us to vectorize expressions
4881 // such as A[i] += x; Because the address of A[i] is a read-write
4882 // pointer. This only works if the index of A[i] is consecutive.
4883 // If the address of i is unknown (for example A[B[i]]) then we may
4884 // read a few words, modify, and write a few words, and some of the
4885 // words may be written to the same address.
4886 bool IsReadOnlyPtr = false;
4887 if (Seen.insert(Ptr).second ||
4888 !isStridedPtr(SE, DL, Ptr, TheLoop, Strides)) {
4890 IsReadOnlyPtr = true;
4893 AliasAnalysis::Location Loc = AA->getLocation(LD);
4894 // The TBAA metadata could have a control dependency on the predication
4895 // condition, so we cannot rely on it when determining whether or not we
4896 // need runtime pointer checks.
4897 if (blockNeedsPredication(LD->getParent()))
4898 Loc.AATags.TBAA = nullptr;
4900 Accesses.addLoad(Loc, IsReadOnlyPtr);
4903 // If we write (or read-write) to a single destination and there are no
4904 // other reads in this loop then is it safe to vectorize.
4905 if (NumReadWrites == 1 && NumReads == 0) {
4906 DEBUG(dbgs() << "LV: Found a write-only loop!\n");
4910 // Build dependence sets and check whether we need a runtime pointer bounds
4912 Accesses.buildDependenceSets();
4913 bool NeedRTCheck = Accesses.isRTCheckNeeded();
4915 // Find pointers with computable bounds. We are going to use this information
4916 // to place a runtime bound check.
4917 unsigned NumComparisons = 0;
4918 bool CanDoRT = false;
4920 CanDoRT = Accesses.canCheckPtrAtRT(PtrRtCheck, NumComparisons, SE, TheLoop,
4923 DEBUG(dbgs() << "LV: We need to do " << NumComparisons <<
4924 " pointer comparisons.\n");
4926 // If we only have one set of dependences to check pointers among we don't
4927 // need a runtime check.
4928 if (NumComparisons == 0 && NeedRTCheck)
4929 NeedRTCheck = false;
4931 // Check that we did not collect too many pointers or found an unsizeable
4933 if (!CanDoRT || NumComparisons > RuntimeMemoryCheckThreshold) {
4939 DEBUG(dbgs() << "LV: We can perform a memory runtime check if needed.\n");
4942 if (NeedRTCheck && !CanDoRT) {
4943 emitAnalysis(Report() << "cannot identify array bounds");
4944 DEBUG(dbgs() << "LV: We can't vectorize because we can't find " <<
4945 "the array bounds.\n");
4950 PtrRtCheck.Need = NeedRTCheck;
4952 bool CanVecMem = true;
4953 if (Accesses.isDependencyCheckNeeded()) {
4954 DEBUG(dbgs() << "LV: Checking memory dependencies\n");
4955 CanVecMem = DepChecker.areDepsSafe(
4956 DependentAccesses, Accesses.getDependenciesToCheck(), Strides);
4957 MaxSafeDepDistBytes = DepChecker.getMaxSafeDepDistBytes();
4959 if (!CanVecMem && DepChecker.shouldRetryWithRuntimeCheck()) {
4960 DEBUG(dbgs() << "LV: Retrying with memory checks\n");
4963 // Clear the dependency checks. We assume they are not needed.
4964 Accesses.resetDepChecks();
4967 PtrRtCheck.Need = true;
4969 CanDoRT = Accesses.canCheckPtrAtRT(PtrRtCheck, NumComparisons, SE,
4970 TheLoop, Strides, true);
4971 // Check that we did not collect too many pointers or found an unsizeable
4973 if (!CanDoRT || NumComparisons > RuntimeMemoryCheckThreshold) {
4974 if (!CanDoRT && NumComparisons > 0)
4975 emitAnalysis(Report()
4976 << "cannot check memory dependencies at runtime");
4978 emitAnalysis(Report()
4979 << NumComparisons << " exceeds limit of "
4980 << RuntimeMemoryCheckThreshold
4981 << " dependent memory operations checked at runtime");
4982 DEBUG(dbgs() << "LV: Can't vectorize with memory checks\n");
4992 emitAnalysis(Report() << "unsafe dependent memory operations in loop");
4994 DEBUG(dbgs() << "LV: We" << (NeedRTCheck ? "" : " don't") <<
4995 " need a runtime memory check.\n");
5000 static bool hasMultipleUsesOf(Instruction *I,
5001 SmallPtrSetImpl<Instruction *> &Insts) {
5002 unsigned NumUses = 0;
5003 for(User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E; ++Use) {
5004 if (Insts.count(dyn_cast<Instruction>(*Use)))
5013 static bool areAllUsesIn(Instruction *I, SmallPtrSetImpl<Instruction *> &Set) {
5014 for(User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E; ++Use)
5015 if (!Set.count(dyn_cast<Instruction>(*Use)))
5020 bool LoopVectorizationLegality::AddReductionVar(PHINode *Phi,
5021 ReductionKind Kind) {
5022 if (Phi->getNumIncomingValues() != 2)
5025 // Reduction variables are only found in the loop header block.
5026 if (Phi->getParent() != TheLoop->getHeader())
5029 // Obtain the reduction start value from the value that comes from the loop
5031 Value *RdxStart = Phi->getIncomingValueForBlock(TheLoop->getLoopPreheader());
5033 // ExitInstruction is the single value which is used outside the loop.
5034 // We only allow for a single reduction value to be used outside the loop.
5035 // This includes users of the reduction, variables (which form a cycle
5036 // which ends in the phi node).
5037 Instruction *ExitInstruction = nullptr;
5038 // Indicates that we found a reduction operation in our scan.
5039 bool FoundReduxOp = false;
5041 // We start with the PHI node and scan for all of the users of this
5042 // instruction. All users must be instructions that can be used as reduction
5043 // variables (such as ADD). We must have a single out-of-block user. The cycle
5044 // must include the original PHI.
5045 bool FoundStartPHI = false;
5047 // To recognize min/max patterns formed by a icmp select sequence, we store
5048 // the number of instruction we saw from the recognized min/max pattern,
5049 // to make sure we only see exactly the two instructions.
5050 unsigned NumCmpSelectPatternInst = 0;
5051 ReductionInstDesc ReduxDesc(false, nullptr);
5053 SmallPtrSet<Instruction *, 8> VisitedInsts;
5054 SmallVector<Instruction *, 8> Worklist;
5055 Worklist.push_back(Phi);
5056 VisitedInsts.insert(Phi);
5058 // A value in the reduction can be used:
5059 // - By the reduction:
5060 // - Reduction operation:
5061 // - One use of reduction value (safe).
5062 // - Multiple use of reduction value (not safe).
5064 // - All uses of the PHI must be the reduction (safe).
5065 // - Otherwise, not safe.
5066 // - By one instruction outside of the loop (safe).
5067 // - By further instructions outside of the loop (not safe).
5068 // - By an instruction that is not part of the reduction (not safe).
5070 // * An instruction type other than PHI or the reduction operation.
5071 // * A PHI in the header other than the initial PHI.
5072 while (!Worklist.empty()) {
5073 Instruction *Cur = Worklist.back();
5074 Worklist.pop_back();
5077 // If the instruction has no users then this is a broken chain and can't be
5078 // a reduction variable.
5079 if (Cur->use_empty())
5082 bool IsAPhi = isa<PHINode>(Cur);
5084 // A header PHI use other than the original PHI.
5085 if (Cur != Phi && IsAPhi && Cur->getParent() == Phi->getParent())
5088 // Reductions of instructions such as Div, and Sub is only possible if the
5089 // LHS is the reduction variable.
5090 if (!Cur->isCommutative() && !IsAPhi && !isa<SelectInst>(Cur) &&
5091 !isa<ICmpInst>(Cur) && !isa<FCmpInst>(Cur) &&
5092 !VisitedInsts.count(dyn_cast<Instruction>(Cur->getOperand(0))))
5095 // Any reduction instruction must be of one of the allowed kinds.
5096 ReduxDesc = isReductionInstr(Cur, Kind, ReduxDesc);
5097 if (!ReduxDesc.IsReduction)
5100 // A reduction operation must only have one use of the reduction value.
5101 if (!IsAPhi && Kind != RK_IntegerMinMax && Kind != RK_FloatMinMax &&
5102 hasMultipleUsesOf(Cur, VisitedInsts))
5105 // All inputs to a PHI node must be a reduction value.
5106 if(IsAPhi && Cur != Phi && !areAllUsesIn(Cur, VisitedInsts))
5109 if (Kind == RK_IntegerMinMax && (isa<ICmpInst>(Cur) ||
5110 isa<SelectInst>(Cur)))
5111 ++NumCmpSelectPatternInst;
5112 if (Kind == RK_FloatMinMax && (isa<FCmpInst>(Cur) ||
5113 isa<SelectInst>(Cur)))
5114 ++NumCmpSelectPatternInst;
5116 // Check whether we found a reduction operator.
5117 FoundReduxOp |= !IsAPhi;
5119 // Process users of current instruction. Push non-PHI nodes after PHI nodes
5120 // onto the stack. This way we are going to have seen all inputs to PHI
5121 // nodes once we get to them.
5122 SmallVector<Instruction *, 8> NonPHIs;
5123 SmallVector<Instruction *, 8> PHIs;
5124 for (User *U : Cur->users()) {
5125 Instruction *UI = cast<Instruction>(U);
5127 // Check if we found the exit user.
5128 BasicBlock *Parent = UI->getParent();
5129 if (!TheLoop->contains(Parent)) {
5130 // Exit if you find multiple outside users or if the header phi node is
5131 // being used. In this case the user uses the value of the previous
5132 // iteration, in which case we would loose "VF-1" iterations of the
5133 // reduction operation if we vectorize.
5134 if (ExitInstruction != nullptr || Cur == Phi)
5137 // The instruction used by an outside user must be the last instruction
5138 // before we feed back to the reduction phi. Otherwise, we loose VF-1
5139 // operations on the value.
5140 if (std::find(Phi->op_begin(), Phi->op_end(), Cur) == Phi->op_end())
5143 ExitInstruction = Cur;
5147 // Process instructions only once (termination). Each reduction cycle
5148 // value must only be used once, except by phi nodes and min/max
5149 // reductions which are represented as a cmp followed by a select.
5150 ReductionInstDesc IgnoredVal(false, nullptr);
5151 if (VisitedInsts.insert(UI).second) {
5152 if (isa<PHINode>(UI))
5155 NonPHIs.push_back(UI);
5156 } else if (!isa<PHINode>(UI) &&
5157 ((!isa<FCmpInst>(UI) &&
5158 !isa<ICmpInst>(UI) &&
5159 !isa<SelectInst>(UI)) ||
5160 !isMinMaxSelectCmpPattern(UI, IgnoredVal).IsReduction))
5163 // Remember that we completed the cycle.
5165 FoundStartPHI = true;
5167 Worklist.append(PHIs.begin(), PHIs.end());
5168 Worklist.append(NonPHIs.begin(), NonPHIs.end());
5171 // This means we have seen one but not the other instruction of the
5172 // pattern or more than just a select and cmp.
5173 if ((Kind == RK_IntegerMinMax || Kind == RK_FloatMinMax) &&
5174 NumCmpSelectPatternInst != 2)
5177 if (!FoundStartPHI || !FoundReduxOp || !ExitInstruction)
5180 // We found a reduction var if we have reached the original phi node and we
5181 // only have a single instruction with out-of-loop users.
5183 // This instruction is allowed to have out-of-loop users.
5184 AllowedExit.insert(ExitInstruction);
5186 // Save the description of this reduction variable.
5187 ReductionDescriptor RD(RdxStart, ExitInstruction, Kind,
5188 ReduxDesc.MinMaxKind);
5189 Reductions[Phi] = RD;
5190 // We've ended the cycle. This is a reduction variable if we have an
5191 // outside user and it has a binary op.
5196 /// Returns true if the instruction is a Select(ICmp(X, Y), X, Y) instruction
5197 /// pattern corresponding to a min(X, Y) or max(X, Y).
5198 LoopVectorizationLegality::ReductionInstDesc
5199 LoopVectorizationLegality::isMinMaxSelectCmpPattern(Instruction *I,
5200 ReductionInstDesc &Prev) {
5202 assert((isa<ICmpInst>(I) || isa<FCmpInst>(I) || isa<SelectInst>(I)) &&
5203 "Expect a select instruction");
5204 Instruction *Cmp = nullptr;
5205 SelectInst *Select = nullptr;
5207 // We must handle the select(cmp()) as a single instruction. Advance to the
5209 if ((Cmp = dyn_cast<ICmpInst>(I)) || (Cmp = dyn_cast<FCmpInst>(I))) {
5210 if (!Cmp->hasOneUse() || !(Select = dyn_cast<SelectInst>(*I->user_begin())))
5211 return ReductionInstDesc(false, I);
5212 return ReductionInstDesc(Select, Prev.MinMaxKind);
5215 // Only handle single use cases for now.
5216 if (!(Select = dyn_cast<SelectInst>(I)))
5217 return ReductionInstDesc(false, I);
5218 if (!(Cmp = dyn_cast<ICmpInst>(I->getOperand(0))) &&
5219 !(Cmp = dyn_cast<FCmpInst>(I->getOperand(0))))
5220 return ReductionInstDesc(false, I);
5221 if (!Cmp->hasOneUse())
5222 return ReductionInstDesc(false, I);
5227 // Look for a min/max pattern.
5228 if (m_UMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
5229 return ReductionInstDesc(Select, MRK_UIntMin);
5230 else if (m_UMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
5231 return ReductionInstDesc(Select, MRK_UIntMax);
5232 else if (m_SMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
5233 return ReductionInstDesc(Select, MRK_SIntMax);
5234 else if (m_SMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
5235 return ReductionInstDesc(Select, MRK_SIntMin);
5236 else if (m_OrdFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
5237 return ReductionInstDesc(Select, MRK_FloatMin);
5238 else if (m_OrdFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
5239 return ReductionInstDesc(Select, MRK_FloatMax);
5240 else if (m_UnordFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
5241 return ReductionInstDesc(Select, MRK_FloatMin);
5242 else if (m_UnordFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
5243 return ReductionInstDesc(Select, MRK_FloatMax);
5245 return ReductionInstDesc(false, I);
5248 LoopVectorizationLegality::ReductionInstDesc
5249 LoopVectorizationLegality::isReductionInstr(Instruction *I,
5251 ReductionInstDesc &Prev) {
5252 bool FP = I->getType()->isFloatingPointTy();
5253 bool FastMath = FP && I->hasUnsafeAlgebra();
5254 switch (I->getOpcode()) {
5256 return ReductionInstDesc(false, I);
5257 case Instruction::PHI:
5258 if (FP && (Kind != RK_FloatMult && Kind != RK_FloatAdd &&
5259 Kind != RK_FloatMinMax))
5260 return ReductionInstDesc(false, I);
5261 return ReductionInstDesc(I, Prev.MinMaxKind);
5262 case Instruction::Sub:
5263 case Instruction::Add:
5264 return ReductionInstDesc(Kind == RK_IntegerAdd, I);
5265 case Instruction::Mul:
5266 return ReductionInstDesc(Kind == RK_IntegerMult, I);
5267 case Instruction::And:
5268 return ReductionInstDesc(Kind == RK_IntegerAnd, I);
5269 case Instruction::Or:
5270 return ReductionInstDesc(Kind == RK_IntegerOr, I);
5271 case Instruction::Xor:
5272 return ReductionInstDesc(Kind == RK_IntegerXor, I);
5273 case Instruction::FMul:
5274 return ReductionInstDesc(Kind == RK_FloatMult && FastMath, I);
5275 case Instruction::FSub:
5276 case Instruction::FAdd:
5277 return ReductionInstDesc(Kind == RK_FloatAdd && FastMath, I);
5278 case Instruction::FCmp:
5279 case Instruction::ICmp:
5280 case Instruction::Select:
5281 if (Kind != RK_IntegerMinMax &&
5282 (!HasFunNoNaNAttr || Kind != RK_FloatMinMax))
5283 return ReductionInstDesc(false, I);
5284 return isMinMaxSelectCmpPattern(I, Prev);
5288 LoopVectorizationLegality::InductionKind
5289 LoopVectorizationLegality::isInductionVariable(PHINode *Phi) {
5290 Type *PhiTy = Phi->getType();
5291 // We only handle integer and pointer inductions variables.
5292 if (!PhiTy->isIntegerTy() && !PhiTy->isPointerTy())
5293 return IK_NoInduction;
5295 // Check that the PHI is consecutive.
5296 const SCEV *PhiScev = SE->getSCEV(Phi);
5297 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PhiScev);
5299 DEBUG(dbgs() << "LV: PHI is not a poly recurrence.\n");
5300 return IK_NoInduction;
5302 const SCEV *Step = AR->getStepRecurrence(*SE);
5304 // Integer inductions need to have a stride of one.
5305 if (PhiTy->isIntegerTy()) {
5307 return IK_IntInduction;
5308 if (Step->isAllOnesValue())
5309 return IK_ReverseIntInduction;
5310 return IK_NoInduction;
5313 // Calculate the pointer stride and check if it is consecutive.
5314 const SCEVConstant *C = dyn_cast<SCEVConstant>(Step);
5316 return IK_NoInduction;
5318 assert(PhiTy->isPointerTy() && "The PHI must be a pointer");
5319 Type *PointerElementType = PhiTy->getPointerElementType();
5320 // The pointer stride cannot be determined if the pointer element type is not
5322 if (!PointerElementType->isSized())
5323 return IK_NoInduction;
5325 uint64_t Size = DL->getTypeAllocSize(PointerElementType);
5326 if (C->getValue()->equalsInt(Size))
5327 return IK_PtrInduction;
5328 else if (C->getValue()->equalsInt(0 - Size))
5329 return IK_ReversePtrInduction;
5331 return IK_NoInduction;
5334 bool LoopVectorizationLegality::isInductionVariable(const Value *V) {
5335 Value *In0 = const_cast<Value*>(V);
5336 PHINode *PN = dyn_cast_or_null<PHINode>(In0);
5340 return Inductions.count(PN);
5343 bool LoopVectorizationLegality::blockNeedsPredication(BasicBlock *BB) {
5344 assert(TheLoop->contains(BB) && "Unknown block used");
5346 // Blocks that do not dominate the latch need predication.
5347 BasicBlock* Latch = TheLoop->getLoopLatch();
5348 return !DT->dominates(BB, Latch);
5351 bool LoopVectorizationLegality::blockCanBePredicated(BasicBlock *BB,
5352 SmallPtrSetImpl<Value *> &SafePtrs) {
5354 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
5355 // Check that we don't have a constant expression that can trap as operand.
5356 for (Instruction::op_iterator OI = it->op_begin(), OE = it->op_end();
5358 if (Constant *C = dyn_cast<Constant>(*OI))
5362 // We might be able to hoist the load.
5363 if (it->mayReadFromMemory()) {
5364 LoadInst *LI = dyn_cast<LoadInst>(it);
5367 if (!SafePtrs.count(LI->getPointerOperand())) {
5368 if (isLegalMaskedLoad(LI->getType(), LI->getPointerOperand())) {
5369 MaskedOp.insert(LI);
5376 // We don't predicate stores at the moment.
5377 if (it->mayWriteToMemory()) {
5378 StoreInst *SI = dyn_cast<StoreInst>(it);
5379 // We only support predication of stores in basic blocks with one
5384 bool isSafePtr = (SafePtrs.count(SI->getPointerOperand()) != 0);
5385 bool isSinglePredecessor = SI->getParent()->getSinglePredecessor();
5387 if (++NumPredStores > NumberOfStoresToPredicate || !isSafePtr ||
5388 !isSinglePredecessor) {
5389 // Build a masked store if it is legal for the target, otherwise scalarize
5391 bool isLegalMaskedOp =
5392 isLegalMaskedStore(SI->getValueOperand()->getType(),
5393 SI->getPointerOperand());
5394 if (isLegalMaskedOp) {
5396 MaskedOp.insert(SI);
5405 // The instructions below can trap.
5406 switch (it->getOpcode()) {
5408 case Instruction::UDiv:
5409 case Instruction::SDiv:
5410 case Instruction::URem:
5411 case Instruction::SRem:
5419 LoopVectorizationCostModel::VectorizationFactor
5420 LoopVectorizationCostModel::selectVectorizationFactor(bool OptForSize) {
5421 // Width 1 means no vectorize
5422 VectorizationFactor Factor = { 1U, 0U };
5423 if (OptForSize && Legal->getRuntimePointerCheck()->Need) {
5424 emitAnalysis(Report() << "runtime pointer checks needed. Enable vectorization of this loop with '#pragma clang loop vectorize(enable)' when compiling with -Os");
5425 DEBUG(dbgs() << "LV: Aborting. Runtime ptr check is required in Os.\n");
5429 if (!EnableCondStoresVectorization && Legal->NumPredStores) {
5430 emitAnalysis(Report() << "store that is conditionally executed prevents vectorization");
5431 DEBUG(dbgs() << "LV: No vectorization. There are conditional stores.\n");
5435 // Find the trip count.
5436 unsigned TC = SE->getSmallConstantTripCount(TheLoop);
5437 DEBUG(dbgs() << "LV: Found trip count: " << TC << '\n');
5439 unsigned WidestType = getWidestType();
5440 unsigned WidestRegister = TTI.getRegisterBitWidth(true);
5441 unsigned MaxSafeDepDist = -1U;
5442 if (Legal->getMaxSafeDepDistBytes() != -1U)
5443 MaxSafeDepDist = Legal->getMaxSafeDepDistBytes() * 8;
5444 WidestRegister = ((WidestRegister < MaxSafeDepDist) ?
5445 WidestRegister : MaxSafeDepDist);
5446 unsigned MaxVectorSize = WidestRegister / WidestType;
5447 DEBUG(dbgs() << "LV: The Widest type: " << WidestType << " bits.\n");
5448 DEBUG(dbgs() << "LV: The Widest register is: "
5449 << WidestRegister << " bits.\n");
5451 if (MaxVectorSize == 0) {
5452 DEBUG(dbgs() << "LV: The target has no vector registers.\n");
5456 assert(MaxVectorSize <= 64 && "Did not expect to pack so many elements"
5457 " into one vector!");
5459 unsigned VF = MaxVectorSize;
5461 // If we optimize the program for size, avoid creating the tail loop.
5463 // If we are unable to calculate the trip count then don't try to vectorize.
5465 emitAnalysis(Report() << "unable to calculate the loop count due to complex control flow");
5466 DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n");
5470 // Find the maximum SIMD width that can fit within the trip count.
5471 VF = TC % MaxVectorSize;
5476 // If the trip count that we found modulo the vectorization factor is not
5477 // zero then we require a tail.
5479 emitAnalysis(Report() << "cannot optimize for size and vectorize at the "
5480 "same time. Enable vectorization of this loop "
5481 "with '#pragma clang loop vectorize(enable)' "
5482 "when compiling with -Os");
5483 DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n");
5488 int UserVF = Hints->getWidth();
5490 assert(isPowerOf2_32(UserVF) && "VF needs to be a power of two");
5491 DEBUG(dbgs() << "LV: Using user VF " << UserVF << ".\n");
5493 Factor.Width = UserVF;
5497 float Cost = expectedCost(1);
5499 const float ScalarCost = Cost;
5502 DEBUG(dbgs() << "LV: Scalar loop costs: " << (int)ScalarCost << ".\n");
5504 bool ForceVectorization = Hints->getForce() == LoopVectorizeHints::FK_Enabled;
5505 // Ignore scalar width, because the user explicitly wants vectorization.
5506 if (ForceVectorization && VF > 1) {
5508 Cost = expectedCost(Width) / (float)Width;
5511 for (unsigned i=2; i <= VF; i*=2) {
5512 // Notice that the vector loop needs to be executed less times, so
5513 // we need to divide the cost of the vector loops by the width of
5514 // the vector elements.
5515 float VectorCost = expectedCost(i) / (float)i;
5516 DEBUG(dbgs() << "LV: Vector loop of width " << i << " costs: " <<
5517 (int)VectorCost << ".\n");
5518 if (VectorCost < Cost) {
5524 DEBUG(if (ForceVectorization && Width > 1 && Cost >= ScalarCost) dbgs()
5525 << "LV: Vectorization seems to be not beneficial, "
5526 << "but was forced by a user.\n");
5527 DEBUG(dbgs() << "LV: Selecting VF: "<< Width << ".\n");
5528 Factor.Width = Width;
5529 Factor.Cost = Width * Cost;
5533 unsigned LoopVectorizationCostModel::getWidestType() {
5534 unsigned MaxWidth = 8;
5537 for (Loop::block_iterator bb = TheLoop->block_begin(),
5538 be = TheLoop->block_end(); bb != be; ++bb) {
5539 BasicBlock *BB = *bb;
5541 // For each instruction in the loop.
5542 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
5543 Type *T = it->getType();
5545 // Ignore ephemeral values.
5546 if (EphValues.count(it))
5549 // Only examine Loads, Stores and PHINodes.
5550 if (!isa<LoadInst>(it) && !isa<StoreInst>(it) && !isa<PHINode>(it))
5553 // Examine PHI nodes that are reduction variables.
5554 if (PHINode *PN = dyn_cast<PHINode>(it))
5555 if (!Legal->getReductionVars()->count(PN))
5558 // Examine the stored values.
5559 if (StoreInst *ST = dyn_cast<StoreInst>(it))
5560 T = ST->getValueOperand()->getType();
5562 // Ignore loaded pointer types and stored pointer types that are not
5563 // consecutive. However, we do want to take consecutive stores/loads of
5564 // pointer vectors into account.
5565 if (T->isPointerTy() && !isConsecutiveLoadOrStore(it))
5568 MaxWidth = std::max(MaxWidth,
5569 (unsigned)DL->getTypeSizeInBits(T->getScalarType()));
5577 LoopVectorizationCostModel::selectUnrollFactor(bool OptForSize,
5579 unsigned LoopCost) {
5581 // -- The unroll heuristics --
5582 // We unroll the loop in order to expose ILP and reduce the loop overhead.
5583 // There are many micro-architectural considerations that we can't predict
5584 // at this level. For example, frontend pressure (on decode or fetch) due to
5585 // code size, or the number and capabilities of the execution ports.
5587 // We use the following heuristics to select the unroll factor:
5588 // 1. If the code has reductions, then we unroll in order to break the cross
5589 // iteration dependency.
5590 // 2. If the loop is really small, then we unroll in order to reduce the loop
5592 // 3. We don't unroll if we think that we will spill registers to memory due
5593 // to the increased register pressure.
5595 // Use the user preference, unless 'auto' is selected.
5596 int UserUF = Hints->getInterleave();
5600 // When we optimize for size, we don't unroll.
5604 // We used the distance for the unroll factor.
5605 if (Legal->getMaxSafeDepDistBytes() != -1U)
5608 // Do not unroll loops with a relatively small trip count.
5609 unsigned TC = SE->getSmallConstantTripCount(TheLoop);
5610 if (TC > 1 && TC < TinyTripCountUnrollThreshold)
5613 unsigned TargetNumRegisters = TTI.getNumberOfRegisters(VF > 1);
5614 DEBUG(dbgs() << "LV: The target has " << TargetNumRegisters <<
5618 if (ForceTargetNumScalarRegs.getNumOccurrences() > 0)
5619 TargetNumRegisters = ForceTargetNumScalarRegs;
5621 if (ForceTargetNumVectorRegs.getNumOccurrences() > 0)
5622 TargetNumRegisters = ForceTargetNumVectorRegs;
5625 LoopVectorizationCostModel::RegisterUsage R = calculateRegisterUsage();
5626 // We divide by these constants so assume that we have at least one
5627 // instruction that uses at least one register.
5628 R.MaxLocalUsers = std::max(R.MaxLocalUsers, 1U);
5629 R.NumInstructions = std::max(R.NumInstructions, 1U);
5631 // We calculate the unroll factor using the following formula.
5632 // Subtract the number of loop invariants from the number of available
5633 // registers. These registers are used by all of the unrolled instances.
5634 // Next, divide the remaining registers by the number of registers that is
5635 // required by the loop, in order to estimate how many parallel instances
5636 // fit without causing spills. All of this is rounded down if necessary to be
5637 // a power of two. We want power of two unroll factors to simplify any
5638 // addressing operations or alignment considerations.
5639 unsigned UF = PowerOf2Floor((TargetNumRegisters - R.LoopInvariantRegs) /
5642 // Don't count the induction variable as unrolled.
5643 if (EnableIndVarRegisterHeur)
5644 UF = PowerOf2Floor((TargetNumRegisters - R.LoopInvariantRegs - 1) /
5645 std::max(1U, (R.MaxLocalUsers - 1)));
5647 // Clamp the unroll factor ranges to reasonable factors.
5648 unsigned MaxInterleaveSize = TTI.getMaxInterleaveFactor();
5650 // Check if the user has overridden the unroll max.
5652 if (ForceTargetMaxScalarInterleaveFactor.getNumOccurrences() > 0)
5653 MaxInterleaveSize = ForceTargetMaxScalarInterleaveFactor;
5655 if (ForceTargetMaxVectorInterleaveFactor.getNumOccurrences() > 0)
5656 MaxInterleaveSize = ForceTargetMaxVectorInterleaveFactor;
5659 // If we did not calculate the cost for VF (because the user selected the VF)
5660 // then we calculate the cost of VF here.
5662 LoopCost = expectedCost(VF);
5664 // Clamp the calculated UF to be between the 1 and the max unroll factor
5665 // that the target allows.
5666 if (UF > MaxInterleaveSize)
5667 UF = MaxInterleaveSize;
5671 // Unroll if we vectorized this loop and there is a reduction that could
5672 // benefit from unrolling.
5673 if (VF > 1 && Legal->getReductionVars()->size()) {
5674 DEBUG(dbgs() << "LV: Unrolling because of reductions.\n");
5678 // Note that if we've already vectorized the loop we will have done the
5679 // runtime check and so unrolling won't require further checks.
5680 bool UnrollingRequiresRuntimePointerCheck =
5681 (VF == 1 && Legal->getRuntimePointerCheck()->Need);
5683 // We want to unroll small loops in order to reduce the loop overhead and
5684 // potentially expose ILP opportunities.
5685 DEBUG(dbgs() << "LV: Loop cost is " << LoopCost << '\n');
5686 if (!UnrollingRequiresRuntimePointerCheck &&
5687 LoopCost < SmallLoopCost) {
5688 // We assume that the cost overhead is 1 and we use the cost model
5689 // to estimate the cost of the loop and unroll until the cost of the
5690 // loop overhead is about 5% of the cost of the loop.
5691 unsigned SmallUF = std::min(UF, (unsigned)PowerOf2Floor(SmallLoopCost / LoopCost));
5693 // Unroll until store/load ports (estimated by max unroll factor) are
5695 unsigned StoresUF = UF / (Legal->NumStores ? Legal->NumStores : 1);
5696 unsigned LoadsUF = UF / (Legal->NumLoads ? Legal->NumLoads : 1);
5698 // If we have a scalar reduction (vector reductions are already dealt with
5699 // by this point), we can increase the critical path length if the loop
5700 // we're unrolling is inside another loop. Limit, by default to 2, so the
5701 // critical path only gets increased by one reduction operation.
5702 if (Legal->getReductionVars()->size() &&
5703 TheLoop->getLoopDepth() > 1) {
5704 unsigned F = static_cast<unsigned>(MaxNestedScalarReductionUF);
5705 SmallUF = std::min(SmallUF, F);
5706 StoresUF = std::min(StoresUF, F);
5707 LoadsUF = std::min(LoadsUF, F);
5710 if (EnableLoadStoreRuntimeUnroll && std::max(StoresUF, LoadsUF) > SmallUF) {
5711 DEBUG(dbgs() << "LV: Unrolling to saturate store or load ports.\n");
5712 return std::max(StoresUF, LoadsUF);
5715 DEBUG(dbgs() << "LV: Unrolling to reduce branch cost.\n");
5719 DEBUG(dbgs() << "LV: Not Unrolling.\n");
5723 LoopVectorizationCostModel::RegisterUsage
5724 LoopVectorizationCostModel::calculateRegisterUsage() {
5725 // This function calculates the register usage by measuring the highest number
5726 // of values that are alive at a single location. Obviously, this is a very
5727 // rough estimation. We scan the loop in a topological order in order and
5728 // assign a number to each instruction. We use RPO to ensure that defs are
5729 // met before their users. We assume that each instruction that has in-loop
5730 // users starts an interval. We record every time that an in-loop value is
5731 // used, so we have a list of the first and last occurrences of each
5732 // instruction. Next, we transpose this data structure into a multi map that
5733 // holds the list of intervals that *end* at a specific location. This multi
5734 // map allows us to perform a linear search. We scan the instructions linearly
5735 // and record each time that a new interval starts, by placing it in a set.
5736 // If we find this value in the multi-map then we remove it from the set.
5737 // The max register usage is the maximum size of the set.
5738 // We also search for instructions that are defined outside the loop, but are
5739 // used inside the loop. We need this number separately from the max-interval
5740 // usage number because when we unroll, loop-invariant values do not take
5742 LoopBlocksDFS DFS(TheLoop);
5746 R.NumInstructions = 0;
5748 // Each 'key' in the map opens a new interval. The values
5749 // of the map are the index of the 'last seen' usage of the
5750 // instruction that is the key.
5751 typedef DenseMap<Instruction*, unsigned> IntervalMap;
5752 // Maps instruction to its index.
5753 DenseMap<unsigned, Instruction*> IdxToInstr;
5754 // Marks the end of each interval.
5755 IntervalMap EndPoint;
5756 // Saves the list of instruction indices that are used in the loop.
5757 SmallSet<Instruction*, 8> Ends;
5758 // Saves the list of values that are used in the loop but are
5759 // defined outside the loop, such as arguments and constants.
5760 SmallPtrSet<Value*, 8> LoopInvariants;
5763 for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(),
5764 be = DFS.endRPO(); bb != be; ++bb) {
5765 R.NumInstructions += (*bb)->size();
5766 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e;
5768 Instruction *I = it;
5769 IdxToInstr[Index++] = I;
5771 // Save the end location of each USE.
5772 for (unsigned i = 0; i < I->getNumOperands(); ++i) {
5773 Value *U = I->getOperand(i);
5774 Instruction *Instr = dyn_cast<Instruction>(U);
5776 // Ignore non-instruction values such as arguments, constants, etc.
5777 if (!Instr) continue;
5779 // If this instruction is outside the loop then record it and continue.
5780 if (!TheLoop->contains(Instr)) {
5781 LoopInvariants.insert(Instr);
5785 // Overwrite previous end points.
5786 EndPoint[Instr] = Index;
5792 // Saves the list of intervals that end with the index in 'key'.
5793 typedef SmallVector<Instruction*, 2> InstrList;
5794 DenseMap<unsigned, InstrList> TransposeEnds;
5796 // Transpose the EndPoints to a list of values that end at each index.
5797 for (IntervalMap::iterator it = EndPoint.begin(), e = EndPoint.end();
5799 TransposeEnds[it->second].push_back(it->first);
5801 SmallSet<Instruction*, 8> OpenIntervals;
5802 unsigned MaxUsage = 0;
5805 DEBUG(dbgs() << "LV(REG): Calculating max register usage:\n");
5806 for (unsigned int i = 0; i < Index; ++i) {
5807 Instruction *I = IdxToInstr[i];
5808 // Ignore instructions that are never used within the loop.
5809 if (!Ends.count(I)) continue;
5811 // Ignore ephemeral values.
5812 if (EphValues.count(I))
5815 // Remove all of the instructions that end at this location.
5816 InstrList &List = TransposeEnds[i];
5817 for (unsigned int j=0, e = List.size(); j < e; ++j)
5818 OpenIntervals.erase(List[j]);
5820 // Count the number of live interals.
5821 MaxUsage = std::max(MaxUsage, OpenIntervals.size());
5823 DEBUG(dbgs() << "LV(REG): At #" << i << " Interval # " <<
5824 OpenIntervals.size() << '\n');
5826 // Add the current instruction to the list of open intervals.
5827 OpenIntervals.insert(I);
5830 unsigned Invariant = LoopInvariants.size();
5831 DEBUG(dbgs() << "LV(REG): Found max usage: " << MaxUsage << '\n');
5832 DEBUG(dbgs() << "LV(REG): Found invariant usage: " << Invariant << '\n');
5833 DEBUG(dbgs() << "LV(REG): LoopSize: " << R.NumInstructions << '\n');
5835 R.LoopInvariantRegs = Invariant;
5836 R.MaxLocalUsers = MaxUsage;
5840 unsigned LoopVectorizationCostModel::expectedCost(unsigned VF) {
5844 for (Loop::block_iterator bb = TheLoop->block_begin(),
5845 be = TheLoop->block_end(); bb != be; ++bb) {
5846 unsigned BlockCost = 0;
5847 BasicBlock *BB = *bb;
5849 // For each instruction in the old loop.
5850 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
5851 // Skip dbg intrinsics.
5852 if (isa<DbgInfoIntrinsic>(it))
5855 // Ignore ephemeral values.
5856 if (EphValues.count(it))
5859 unsigned C = getInstructionCost(it, VF);
5861 // Check if we should override the cost.
5862 if (ForceTargetInstructionCost.getNumOccurrences() > 0)
5863 C = ForceTargetInstructionCost;
5866 DEBUG(dbgs() << "LV: Found an estimated cost of " << C << " for VF " <<
5867 VF << " For instruction: " << *it << '\n');
5870 // We assume that if-converted blocks have a 50% chance of being executed.
5871 // When the code is scalar then some of the blocks are avoided due to CF.
5872 // When the code is vectorized we execute all code paths.
5873 if (VF == 1 && Legal->blockNeedsPredication(*bb))
5882 /// \brief Check whether the address computation for a non-consecutive memory
5883 /// access looks like an unlikely candidate for being merged into the indexing
5886 /// We look for a GEP which has one index that is an induction variable and all
5887 /// other indices are loop invariant. If the stride of this access is also
5888 /// within a small bound we decide that this address computation can likely be
5889 /// merged into the addressing mode.
5890 /// In all other cases, we identify the address computation as complex.
5891 static bool isLikelyComplexAddressComputation(Value *Ptr,
5892 LoopVectorizationLegality *Legal,
5893 ScalarEvolution *SE,
5894 const Loop *TheLoop) {
5895 GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr);
5899 // We are looking for a gep with all loop invariant indices except for one
5900 // which should be an induction variable.
5901 unsigned NumOperands = Gep->getNumOperands();
5902 for (unsigned i = 1; i < NumOperands; ++i) {
5903 Value *Opd = Gep->getOperand(i);
5904 if (!SE->isLoopInvariant(SE->getSCEV(Opd), TheLoop) &&
5905 !Legal->isInductionVariable(Opd))
5909 // Now we know we have a GEP ptr, %inv, %ind, %inv. Make sure that the step
5910 // can likely be merged into the address computation.
5911 unsigned MaxMergeDistance = 64;
5913 const SCEVAddRecExpr *AddRec = dyn_cast<SCEVAddRecExpr>(SE->getSCEV(Ptr));
5917 // Check the step is constant.
5918 const SCEV *Step = AddRec->getStepRecurrence(*SE);
5919 // Calculate the pointer stride and check if it is consecutive.
5920 const SCEVConstant *C = dyn_cast<SCEVConstant>(Step);
5924 const APInt &APStepVal = C->getValue()->getValue();
5926 // Huge step value - give up.
5927 if (APStepVal.getBitWidth() > 64)
5930 int64_t StepVal = APStepVal.getSExtValue();
5932 return StepVal > MaxMergeDistance;
5935 static bool isStrideMul(Instruction *I, LoopVectorizationLegality *Legal) {
5936 if (Legal->hasStride(I->getOperand(0)) || Legal->hasStride(I->getOperand(1)))
5942 LoopVectorizationCostModel::getInstructionCost(Instruction *I, unsigned VF) {
5943 // If we know that this instruction will remain uniform, check the cost of
5944 // the scalar version.
5945 if (Legal->isUniformAfterVectorization(I))
5948 Type *RetTy = I->getType();
5949 Type *VectorTy = ToVectorTy(RetTy, VF);
5951 // TODO: We need to estimate the cost of intrinsic calls.
5952 switch (I->getOpcode()) {
5953 case Instruction::GetElementPtr:
5954 // We mark this instruction as zero-cost because the cost of GEPs in
5955 // vectorized code depends on whether the corresponding memory instruction
5956 // is scalarized or not. Therefore, we handle GEPs with the memory
5957 // instruction cost.
5959 case Instruction::Br: {
5960 return TTI.getCFInstrCost(I->getOpcode());
5962 case Instruction::PHI:
5963 //TODO: IF-converted IFs become selects.
5965 case Instruction::Add:
5966 case Instruction::FAdd:
5967 case Instruction::Sub:
5968 case Instruction::FSub:
5969 case Instruction::Mul:
5970 case Instruction::FMul:
5971 case Instruction::UDiv:
5972 case Instruction::SDiv:
5973 case Instruction::FDiv:
5974 case Instruction::URem:
5975 case Instruction::SRem:
5976 case Instruction::FRem:
5977 case Instruction::Shl:
5978 case Instruction::LShr:
5979 case Instruction::AShr:
5980 case Instruction::And:
5981 case Instruction::Or:
5982 case Instruction::Xor: {
5983 // Since we will replace the stride by 1 the multiplication should go away.
5984 if (I->getOpcode() == Instruction::Mul && isStrideMul(I, Legal))
5986 // Certain instructions can be cheaper to vectorize if they have a constant
5987 // second vector operand. One example of this are shifts on x86.
5988 TargetTransformInfo::OperandValueKind Op1VK =
5989 TargetTransformInfo::OK_AnyValue;
5990 TargetTransformInfo::OperandValueKind Op2VK =
5991 TargetTransformInfo::OK_AnyValue;
5992 TargetTransformInfo::OperandValueProperties Op1VP =
5993 TargetTransformInfo::OP_None;
5994 TargetTransformInfo::OperandValueProperties Op2VP =
5995 TargetTransformInfo::OP_None;
5996 Value *Op2 = I->getOperand(1);
5998 // Check for a splat of a constant or for a non uniform vector of constants.
5999 if (isa<ConstantInt>(Op2)) {
6000 ConstantInt *CInt = cast<ConstantInt>(Op2);
6001 if (CInt && CInt->getValue().isPowerOf2())
6002 Op2VP = TargetTransformInfo::OP_PowerOf2;
6003 Op2VK = TargetTransformInfo::OK_UniformConstantValue;
6004 } else if (isa<ConstantVector>(Op2) || isa<ConstantDataVector>(Op2)) {
6005 Op2VK = TargetTransformInfo::OK_NonUniformConstantValue;
6006 Constant *SplatValue = cast<Constant>(Op2)->getSplatValue();
6008 ConstantInt *CInt = dyn_cast<ConstantInt>(SplatValue);
6009 if (CInt && CInt->getValue().isPowerOf2())
6010 Op2VP = TargetTransformInfo::OP_PowerOf2;
6011 Op2VK = TargetTransformInfo::OK_UniformConstantValue;
6015 return TTI.getArithmeticInstrCost(I->getOpcode(), VectorTy, Op1VK, Op2VK,
6018 case Instruction::Select: {
6019 SelectInst *SI = cast<SelectInst>(I);
6020 const SCEV *CondSCEV = SE->getSCEV(SI->getCondition());
6021 bool ScalarCond = (SE->isLoopInvariant(CondSCEV, TheLoop));
6022 Type *CondTy = SI->getCondition()->getType();
6024 CondTy = VectorType::get(CondTy, VF);
6026 return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy, CondTy);
6028 case Instruction::ICmp:
6029 case Instruction::FCmp: {
6030 Type *ValTy = I->getOperand(0)->getType();
6031 VectorTy = ToVectorTy(ValTy, VF);
6032 return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy);
6034 case Instruction::Store:
6035 case Instruction::Load: {
6036 StoreInst *SI = dyn_cast<StoreInst>(I);
6037 LoadInst *LI = dyn_cast<LoadInst>(I);
6038 Type *ValTy = (SI ? SI->getValueOperand()->getType() :
6040 VectorTy = ToVectorTy(ValTy, VF);
6042 unsigned Alignment = SI ? SI->getAlignment() : LI->getAlignment();
6043 unsigned AS = SI ? SI->getPointerAddressSpace() :
6044 LI->getPointerAddressSpace();
6045 Value *Ptr = SI ? SI->getPointerOperand() : LI->getPointerOperand();
6046 // We add the cost of address computation here instead of with the gep
6047 // instruction because only here we know whether the operation is
6050 return TTI.getAddressComputationCost(VectorTy) +
6051 TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS);
6053 // Scalarized loads/stores.
6054 int ConsecutiveStride = Legal->isConsecutivePtr(Ptr);
6055 bool Reverse = ConsecutiveStride < 0;
6056 unsigned ScalarAllocatedSize = DL->getTypeAllocSize(ValTy);
6057 unsigned VectorElementSize = DL->getTypeStoreSize(VectorTy)/VF;
6058 if (!ConsecutiveStride || ScalarAllocatedSize != VectorElementSize) {
6059 bool IsComplexComputation =
6060 isLikelyComplexAddressComputation(Ptr, Legal, SE, TheLoop);
6062 // The cost of extracting from the value vector and pointer vector.
6063 Type *PtrTy = ToVectorTy(Ptr->getType(), VF);
6064 for (unsigned i = 0; i < VF; ++i) {
6065 // The cost of extracting the pointer operand.
6066 Cost += TTI.getVectorInstrCost(Instruction::ExtractElement, PtrTy, i);
6067 // In case of STORE, the cost of ExtractElement from the vector.
6068 // In case of LOAD, the cost of InsertElement into the returned
6070 Cost += TTI.getVectorInstrCost(SI ? Instruction::ExtractElement :
6071 Instruction::InsertElement,
6075 // The cost of the scalar loads/stores.
6076 Cost += VF * TTI.getAddressComputationCost(PtrTy, IsComplexComputation);
6077 Cost += VF * TTI.getMemoryOpCost(I->getOpcode(), ValTy->getScalarType(),
6082 // Wide load/stores.
6083 unsigned Cost = TTI.getAddressComputationCost(VectorTy);
6084 Cost += TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS);
6087 Cost += TTI.getShuffleCost(TargetTransformInfo::SK_Reverse,
6091 case Instruction::ZExt:
6092 case Instruction::SExt:
6093 case Instruction::FPToUI:
6094 case Instruction::FPToSI:
6095 case Instruction::FPExt:
6096 case Instruction::PtrToInt:
6097 case Instruction::IntToPtr:
6098 case Instruction::SIToFP:
6099 case Instruction::UIToFP:
6100 case Instruction::Trunc:
6101 case Instruction::FPTrunc:
6102 case Instruction::BitCast: {
6103 // We optimize the truncation of induction variable.
6104 // The cost of these is the same as the scalar operation.
6105 if (I->getOpcode() == Instruction::Trunc &&
6106 Legal->isInductionVariable(I->getOperand(0)))
6107 return TTI.getCastInstrCost(I->getOpcode(), I->getType(),
6108 I->getOperand(0)->getType());
6110 Type *SrcVecTy = ToVectorTy(I->getOperand(0)->getType(), VF);
6111 return TTI.getCastInstrCost(I->getOpcode(), VectorTy, SrcVecTy);
6113 case Instruction::Call: {
6114 CallInst *CI = cast<CallInst>(I);
6115 Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI);
6116 assert(ID && "Not an intrinsic call!");
6117 Type *RetTy = ToVectorTy(CI->getType(), VF);
6118 SmallVector<Type*, 4> Tys;
6119 for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i)
6120 Tys.push_back(ToVectorTy(CI->getArgOperand(i)->getType(), VF));
6121 return TTI.getIntrinsicInstrCost(ID, RetTy, Tys);
6124 // We are scalarizing the instruction. Return the cost of the scalar
6125 // instruction, plus the cost of insert and extract into vector
6126 // elements, times the vector width.
6129 if (!RetTy->isVoidTy() && VF != 1) {
6130 unsigned InsCost = TTI.getVectorInstrCost(Instruction::InsertElement,
6132 unsigned ExtCost = TTI.getVectorInstrCost(Instruction::ExtractElement,
6135 // The cost of inserting the results plus extracting each one of the
6137 Cost += VF * (InsCost + ExtCost * I->getNumOperands());
6140 // The cost of executing VF copies of the scalar instruction. This opcode
6141 // is unknown. Assume that it is the same as 'mul'.
6142 Cost += VF * TTI.getArithmeticInstrCost(Instruction::Mul, VectorTy);
6148 Type* LoopVectorizationCostModel::ToVectorTy(Type *Scalar, unsigned VF) {
6149 if (Scalar->isVoidTy() || VF == 1)
6151 return VectorType::get(Scalar, VF);
6154 char LoopVectorize::ID = 0;
6155 static const char lv_name[] = "Loop Vectorization";
6156 INITIALIZE_PASS_BEGIN(LoopVectorize, LV_NAME, lv_name, false, false)
6157 INITIALIZE_AG_DEPENDENCY(TargetTransformInfo)
6158 INITIALIZE_AG_DEPENDENCY(AliasAnalysis)
6159 INITIALIZE_PASS_DEPENDENCY(AssumptionTracker)
6160 INITIALIZE_PASS_DEPENDENCY(BlockFrequencyInfo)
6161 INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass)
6162 INITIALIZE_PASS_DEPENDENCY(ScalarEvolution)
6163 INITIALIZE_PASS_DEPENDENCY(LCSSA)
6164 INITIALIZE_PASS_DEPENDENCY(LoopInfo)
6165 INITIALIZE_PASS_DEPENDENCY(LoopSimplify)
6166 INITIALIZE_PASS_END(LoopVectorize, LV_NAME, lv_name, false, false)
6169 Pass *createLoopVectorizePass(bool NoUnrolling, bool AlwaysVectorize) {
6170 return new LoopVectorize(NoUnrolling, AlwaysVectorize);
6174 bool LoopVectorizationCostModel::isConsecutiveLoadOrStore(Instruction *Inst) {
6175 // Check for a store.
6176 if (StoreInst *ST = dyn_cast<StoreInst>(Inst))
6177 return Legal->isConsecutivePtr(ST->getPointerOperand()) != 0;
6179 // Check for a load.
6180 if (LoadInst *LI = dyn_cast<LoadInst>(Inst))
6181 return Legal->isConsecutivePtr(LI->getPointerOperand()) != 0;
6187 void InnerLoopUnroller::scalarizeInstruction(Instruction *Instr,
6188 bool IfPredicateStore) {
6189 assert(!Instr->getType()->isAggregateType() && "Can't handle vectors");
6190 // Holds vector parameters or scalars, in case of uniform vals.
6191 SmallVector<VectorParts, 4> Params;
6193 setDebugLocFromInst(Builder, Instr);
6195 // Find all of the vectorized parameters.
6196 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
6197 Value *SrcOp = Instr->getOperand(op);
6199 // If we are accessing the old induction variable, use the new one.
6200 if (SrcOp == OldInduction) {
6201 Params.push_back(getVectorValue(SrcOp));
6205 // Try using previously calculated values.
6206 Instruction *SrcInst = dyn_cast<Instruction>(SrcOp);
6208 // If the src is an instruction that appeared earlier in the basic block
6209 // then it should already be vectorized.
6210 if (SrcInst && OrigLoop->contains(SrcInst)) {
6211 assert(WidenMap.has(SrcInst) && "Source operand is unavailable");
6212 // The parameter is a vector value from earlier.
6213 Params.push_back(WidenMap.get(SrcInst));
6215 // The parameter is a scalar from outside the loop. Maybe even a constant.
6216 VectorParts Scalars;
6217 Scalars.append(UF, SrcOp);
6218 Params.push_back(Scalars);
6222 assert(Params.size() == Instr->getNumOperands() &&
6223 "Invalid number of operands");
6225 // Does this instruction return a value ?
6226 bool IsVoidRetTy = Instr->getType()->isVoidTy();
6228 Value *UndefVec = IsVoidRetTy ? nullptr :
6229 UndefValue::get(Instr->getType());
6230 // Create a new entry in the WidenMap and initialize it to Undef or Null.
6231 VectorParts &VecResults = WidenMap.splat(Instr, UndefVec);
6233 Instruction *InsertPt = Builder.GetInsertPoint();
6234 BasicBlock *IfBlock = Builder.GetInsertBlock();
6235 BasicBlock *CondBlock = nullptr;
6238 Loop *VectorLp = nullptr;
6239 if (IfPredicateStore) {
6240 assert(Instr->getParent()->getSinglePredecessor() &&
6241 "Only support single predecessor blocks");
6242 Cond = createEdgeMask(Instr->getParent()->getSinglePredecessor(),
6243 Instr->getParent());
6244 VectorLp = LI->getLoopFor(IfBlock);
6245 assert(VectorLp && "Must have a loop for this block");
6248 // For each vector unroll 'part':
6249 for (unsigned Part = 0; Part < UF; ++Part) {
6250 // For each scalar that we create:
6252 // Start an "if (pred) a[i] = ..." block.
6253 Value *Cmp = nullptr;
6254 if (IfPredicateStore) {
6255 if (Cond[Part]->getType()->isVectorTy())
6257 Builder.CreateExtractElement(Cond[Part], Builder.getInt32(0));
6258 Cmp = Builder.CreateICmp(ICmpInst::ICMP_EQ, Cond[Part],
6259 ConstantInt::get(Cond[Part]->getType(), 1));
6260 CondBlock = IfBlock->splitBasicBlock(InsertPt, "cond.store");
6261 LoopVectorBody.push_back(CondBlock);
6262 VectorLp->addBasicBlockToLoop(CondBlock, LI->getBase());
6263 // Update Builder with newly created basic block.
6264 Builder.SetInsertPoint(InsertPt);
6267 Instruction *Cloned = Instr->clone();
6269 Cloned->setName(Instr->getName() + ".cloned");
6270 // Replace the operands of the cloned instructions with extracted scalars.
6271 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
6272 Value *Op = Params[op][Part];
6273 Cloned->setOperand(op, Op);
6276 // Place the cloned scalar in the new loop.
6277 Builder.Insert(Cloned);
6279 // If the original scalar returns a value we need to place it in a vector
6280 // so that future users will be able to use it.
6282 VecResults[Part] = Cloned;
6285 if (IfPredicateStore) {
6286 BasicBlock *NewIfBlock = CondBlock->splitBasicBlock(InsertPt, "else");
6287 LoopVectorBody.push_back(NewIfBlock);
6288 VectorLp->addBasicBlockToLoop(NewIfBlock, LI->getBase());
6289 Builder.SetInsertPoint(InsertPt);
6290 Instruction *OldBr = IfBlock->getTerminator();
6291 BranchInst::Create(CondBlock, NewIfBlock, Cmp, OldBr);
6292 OldBr->eraseFromParent();
6293 IfBlock = NewIfBlock;
6298 void InnerLoopUnroller::vectorizeMemoryInstruction(Instruction *Instr) {
6299 StoreInst *SI = dyn_cast<StoreInst>(Instr);
6300 bool IfPredicateStore = (SI && Legal->blockNeedsPredication(SI->getParent()));
6302 return scalarizeInstruction(Instr, IfPredicateStore);
6305 Value *InnerLoopUnroller::reverseVector(Value *Vec) {
6309 Value *InnerLoopUnroller::getBroadcastInstrs(Value *V) {
6313 Value *InnerLoopUnroller::getConsecutiveVector(Value* Val, int StartIdx,
6315 // When unrolling and the VF is 1, we only need to add a simple scalar.
6316 Type *ITy = Val->getType();
6317 assert(!ITy->isVectorTy() && "Val must be a scalar");
6318 Constant *C = ConstantInt::get(ITy, StartIdx, Negate);
6319 return Builder.CreateAdd(Val, C, "induction");