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 #define LV_NAME "loop-vectorize"
46 #define DEBUG_TYPE LV_NAME
48 #include "llvm/Transforms/Vectorize.h"
49 #include "llvm/ADT/DenseMap.h"
50 #include "llvm/ADT/EquivalenceClasses.h"
51 #include "llvm/ADT/Hashing.h"
52 #include "llvm/ADT/MapVector.h"
53 #include "llvm/ADT/SetVector.h"
54 #include "llvm/ADT/SmallPtrSet.h"
55 #include "llvm/ADT/SmallSet.h"
56 #include "llvm/ADT/SmallVector.h"
57 #include "llvm/ADT/StringExtras.h"
58 #include "llvm/Analysis/AliasAnalysis.h"
59 #include "llvm/Analysis/LoopInfo.h"
60 #include "llvm/Analysis/LoopIterator.h"
61 #include "llvm/Analysis/LoopPass.h"
62 #include "llvm/Analysis/ScalarEvolution.h"
63 #include "llvm/Analysis/ScalarEvolutionExpander.h"
64 #include "llvm/Analysis/ScalarEvolutionExpressions.h"
65 #include "llvm/Analysis/TargetTransformInfo.h"
66 #include "llvm/Analysis/ValueTracking.h"
67 #include "llvm/IR/Constants.h"
68 #include "llvm/IR/DataLayout.h"
69 #include "llvm/IR/DerivedTypes.h"
70 #include "llvm/IR/Dominators.h"
71 #include "llvm/IR/Function.h"
72 #include "llvm/IR/IRBuilder.h"
73 #include "llvm/IR/Instructions.h"
74 #include "llvm/IR/IntrinsicInst.h"
75 #include "llvm/IR/LLVMContext.h"
76 #include "llvm/IR/Module.h"
77 #include "llvm/IR/Type.h"
78 #include "llvm/IR/Value.h"
79 #include "llvm/IR/Verifier.h"
80 #include "llvm/Pass.h"
81 #include "llvm/Support/CommandLine.h"
82 #include "llvm/Support/Debug.h"
83 #include "llvm/Support/PatternMatch.h"
84 #include "llvm/Support/ValueHandle.h"
85 #include "llvm/Support/raw_ostream.h"
86 #include "llvm/Target/TargetLibraryInfo.h"
87 #include "llvm/Transforms/Scalar.h"
88 #include "llvm/Transforms/Utils/BasicBlockUtils.h"
89 #include "llvm/Transforms/Utils/Local.h"
94 using namespace llvm::PatternMatch;
96 static cl::opt<unsigned>
97 VectorizationFactor("force-vector-width", cl::init(0), cl::Hidden,
98 cl::desc("Sets the SIMD width. Zero is autoselect."));
100 static cl::opt<unsigned>
101 VectorizationUnroll("force-vector-unroll", cl::init(0), cl::Hidden,
102 cl::desc("Sets the vectorization unroll count. "
103 "Zero is autoselect."));
106 EnableIfConversion("enable-if-conversion", cl::init(true), cl::Hidden,
107 cl::desc("Enable if-conversion during vectorization."));
109 /// We don't vectorize loops with a known constant trip count below this number.
110 static cl::opt<unsigned>
111 TinyTripCountVectorThreshold("vectorizer-min-trip-count", cl::init(16),
113 cl::desc("Don't vectorize loops with a constant "
114 "trip count that is smaller than this "
117 /// This enables versioning on the strides of symbolically striding memory
118 /// accesses in code like the following.
119 /// for (i = 0; i < N; ++i)
120 /// A[i * Stride1] += B[i * Stride2] ...
122 /// Will be roughly translated to
123 /// if (Stride1 == 1 && Stride2 == 1) {
124 /// for (i = 0; i < N; i+=4)
128 static cl::opt<bool> EnableMemAccessVersioning(
129 "enable-mem-access-versioning", cl::init(true), cl::Hidden,
130 cl::desc("Enable symblic stride memory access versioning"));
132 /// We don't unroll loops with a known constant trip count below this number.
133 static const unsigned TinyTripCountUnrollThreshold = 128;
135 /// When performing memory disambiguation checks at runtime do not make more
136 /// than this number of comparisons.
137 static const unsigned RuntimeMemoryCheckThreshold = 8;
139 /// Maximum simd width.
140 static const unsigned MaxVectorWidth = 64;
142 static cl::opt<unsigned> ForceTargetNumScalarRegs(
143 "force-target-num-scalar-regs", cl::init(0), cl::Hidden,
144 cl::desc("A flag that overrides the target's number of scalar registers."));
146 static cl::opt<unsigned> ForceTargetNumVectorRegs(
147 "force-target-num-vector-regs", cl::init(0), cl::Hidden,
148 cl::desc("A flag that overrides the target's number of vector registers."));
150 /// Maximum vectorization unroll count.
151 static const unsigned MaxUnrollFactor = 16;
153 static cl::opt<unsigned> ForceTargetMaxScalarUnrollFactor(
154 "force-target-max-scalar-unroll", cl::init(0), cl::Hidden,
155 cl::desc("A flag that overrides the target's max unroll factor for scalar "
158 static cl::opt<unsigned> ForceTargetMaxVectorUnrollFactor(
159 "force-target-max-vector-unroll", cl::init(0), cl::Hidden,
160 cl::desc("A flag that overrides the target's max unroll factor for "
161 "vectorized loops."));
163 static cl::opt<unsigned> ForceTargetInstructionCost(
164 "force-target-instruction-cost", cl::init(0), cl::Hidden,
165 cl::desc("A flag that overrides the target's expected cost for "
166 "an instruction to a single constant value. Mostly "
167 "useful for getting consistent testing."));
169 static cl::opt<unsigned> SmallLoopCost(
170 "small-loop-cost", cl::init(20), cl::Hidden,
171 cl::desc("The cost of a loop that is considered 'small' by the unroller."));
175 // Forward declarations.
176 class LoopVectorizationLegality;
177 class LoopVectorizationCostModel;
179 /// InnerLoopVectorizer vectorizes loops which contain only one basic
180 /// block to a specified vectorization factor (VF).
181 /// This class performs the widening of scalars into vectors, or multiple
182 /// scalars. This class also implements the following features:
183 /// * It inserts an epilogue loop for handling loops that don't have iteration
184 /// counts that are known to be a multiple of the vectorization factor.
185 /// * It handles the code generation for reduction variables.
186 /// * Scalarization (implementation using scalars) of un-vectorizable
188 /// InnerLoopVectorizer does not perform any vectorization-legality
189 /// checks, and relies on the caller to check for the different legality
190 /// aspects. The InnerLoopVectorizer relies on the
191 /// LoopVectorizationLegality class to provide information about the induction
192 /// and reduction variables that were found to a given vectorization factor.
193 class InnerLoopVectorizer {
195 InnerLoopVectorizer(Loop *OrigLoop, ScalarEvolution *SE, LoopInfo *LI,
196 DominatorTree *DT, DataLayout *DL,
197 const TargetLibraryInfo *TLI, unsigned VecWidth,
198 unsigned UnrollFactor)
199 : OrigLoop(OrigLoop), SE(SE), LI(LI), DT(DT), DL(DL), TLI(TLI),
200 VF(VecWidth), UF(UnrollFactor), Builder(SE->getContext()), Induction(0),
201 OldInduction(0), WidenMap(UnrollFactor), Legal(0) {}
203 // Perform the actual loop widening (vectorization).
204 void vectorize(LoopVectorizationLegality *L) {
206 // Create a new empty loop. Unlink the old loop and connect the new one.
208 // Widen each instruction in the old loop to a new one in the new loop.
209 // Use the Legality module to find the induction and reduction variables.
211 // Register the new loop and update the analysis passes.
215 virtual ~InnerLoopVectorizer() {}
218 /// A small list of PHINodes.
219 typedef SmallVector<PHINode*, 4> PhiVector;
220 /// When we unroll loops we have multiple vector values for each scalar.
221 /// This data structure holds the unrolled and vectorized values that
222 /// originated from one scalar instruction.
223 typedef SmallVector<Value*, 2> VectorParts;
225 // When we if-convert we need create edge masks. We have to cache values so
226 // that we don't end up with exponential recursion/IR.
227 typedef DenseMap<std::pair<BasicBlock*, BasicBlock*>,
228 VectorParts> EdgeMaskCache;
230 /// \brief Add code that checks at runtime if the accessed arrays overlap.
232 /// Returns a pair of instructions where the first element is the first
233 /// instruction generated in possibly a sequence of instructions and the
234 /// second value is the final comparator value or NULL if no check is needed.
235 std::pair<Instruction *, Instruction *> addRuntimeCheck(Instruction *Loc);
237 /// \brief Add checks for strides that where assumed to be 1.
239 /// Returns the last check instruction and the first check instruction in the
240 /// pair as (first, last).
241 std::pair<Instruction *, Instruction *> addStrideCheck(Instruction *Loc);
243 /// Create an empty loop, based on the loop ranges of the old loop.
244 void createEmptyLoop();
245 /// Copy and widen the instructions from the old loop.
246 virtual void vectorizeLoop();
248 /// \brief The Loop exit block may have single value PHI nodes where the
249 /// incoming value is 'Undef'. While vectorizing we only handled real values
250 /// that were defined inside the loop. Here we fix the 'undef case'.
254 /// A helper function that computes the predicate of the block BB, assuming
255 /// that the header block of the loop is set to True. It returns the *entry*
256 /// mask for the block BB.
257 VectorParts createBlockInMask(BasicBlock *BB);
258 /// A helper function that computes the predicate of the edge between SRC
260 VectorParts createEdgeMask(BasicBlock *Src, BasicBlock *Dst);
262 /// A helper function to vectorize a single BB within the innermost loop.
263 void vectorizeBlockInLoop(BasicBlock *BB, PhiVector *PV);
265 /// Vectorize a single PHINode in a block. This method handles the induction
266 /// variable canonicalization. It supports both VF = 1 for unrolled loops and
267 /// arbitrary length vectors.
268 void widenPHIInstruction(Instruction *PN, VectorParts &Entry,
269 unsigned UF, unsigned VF, PhiVector *PV);
271 /// Insert the new loop to the loop hierarchy and pass manager
272 /// and update the analysis passes.
273 void updateAnalysis();
275 /// This instruction is un-vectorizable. Implement it as a sequence
277 virtual void scalarizeInstruction(Instruction *Instr);
279 /// Vectorize Load and Store instructions,
280 virtual void vectorizeMemoryInstruction(Instruction *Instr);
282 /// Create a broadcast instruction. This method generates a broadcast
283 /// instruction (shuffle) for loop invariant values and for the induction
284 /// value. If this is the induction variable then we extend it to N, N+1, ...
285 /// this is needed because each iteration in the loop corresponds to a SIMD
287 virtual Value *getBroadcastInstrs(Value *V);
289 /// This function adds 0, 1, 2 ... to each vector element, starting at zero.
290 /// If Negate is set then negative numbers are added e.g. (0, -1, -2, ...).
291 /// The sequence starts at StartIndex.
292 virtual Value *getConsecutiveVector(Value* Val, int StartIdx, bool Negate);
294 /// When we go over instructions in the basic block we rely on previous
295 /// values within the current basic block or on loop invariant values.
296 /// When we widen (vectorize) values we place them in the map. If the values
297 /// are not within the map, they have to be loop invariant, so we simply
298 /// broadcast them into a vector.
299 VectorParts &getVectorValue(Value *V);
301 /// Generate a shuffle sequence that will reverse the vector Vec.
302 virtual Value *reverseVector(Value *Vec);
304 /// This is a helper class that holds the vectorizer state. It maps scalar
305 /// instructions to vector instructions. When the code is 'unrolled' then
306 /// then a single scalar value is mapped to multiple vector parts. The parts
307 /// are stored in the VectorPart type.
309 /// C'tor. UnrollFactor controls the number of vectors ('parts') that
311 ValueMap(unsigned UnrollFactor) : UF(UnrollFactor) {}
313 /// \return True if 'Key' is saved in the Value Map.
314 bool has(Value *Key) const { return MapStorage.count(Key); }
316 /// Initializes a new entry in the map. Sets all of the vector parts to the
317 /// save value in 'Val'.
318 /// \return A reference to a vector with splat values.
319 VectorParts &splat(Value *Key, Value *Val) {
320 VectorParts &Entry = MapStorage[Key];
321 Entry.assign(UF, Val);
325 ///\return A reference to the value that is stored at 'Key'.
326 VectorParts &get(Value *Key) {
327 VectorParts &Entry = MapStorage[Key];
330 assert(Entry.size() == UF);
335 /// The unroll factor. Each entry in the map stores this number of vector
339 /// Map storage. We use std::map and not DenseMap because insertions to a
340 /// dense map invalidates its iterators.
341 std::map<Value *, VectorParts> MapStorage;
344 /// The original loop.
346 /// Scev analysis to use.
354 /// Target Library Info.
355 const TargetLibraryInfo *TLI;
357 /// The vectorization SIMD factor to use. Each vector will have this many
362 /// The vectorization unroll factor to use. Each scalar is vectorized to this
363 /// many different vector instructions.
366 /// The builder that we use
369 // --- Vectorization state ---
371 /// The vector-loop preheader.
372 BasicBlock *LoopVectorPreHeader;
373 /// The scalar-loop preheader.
374 BasicBlock *LoopScalarPreHeader;
375 /// Middle Block between the vector and the scalar.
376 BasicBlock *LoopMiddleBlock;
377 ///The ExitBlock of the scalar loop.
378 BasicBlock *LoopExitBlock;
379 ///The vector loop body.
380 BasicBlock *LoopVectorBody;
381 ///The scalar loop body.
382 BasicBlock *LoopScalarBody;
383 /// A list of all bypass blocks. The first block is the entry of the loop.
384 SmallVector<BasicBlock *, 4> LoopBypassBlocks;
386 /// The new Induction variable which was added to the new block.
388 /// The induction variable of the old basic block.
389 PHINode *OldInduction;
390 /// Holds the extended (to the widest induction type) start index.
392 /// Maps scalars to widened vectors.
394 EdgeMaskCache MaskCache;
396 LoopVectorizationLegality *Legal;
399 class InnerLoopUnroller : public InnerLoopVectorizer {
401 InnerLoopUnroller(Loop *OrigLoop, ScalarEvolution *SE, LoopInfo *LI,
402 DominatorTree *DT, DataLayout *DL,
403 const TargetLibraryInfo *TLI, unsigned UnrollFactor) :
404 InnerLoopVectorizer(OrigLoop, SE, LI, DT, DL, TLI, 1, UnrollFactor) { }
407 virtual void scalarizeInstruction(Instruction *Instr);
408 virtual void vectorizeMemoryInstruction(Instruction *Instr);
409 virtual Value *getBroadcastInstrs(Value *V);
410 virtual Value *getConsecutiveVector(Value* Val, int StartIdx, bool Negate);
411 virtual Value *reverseVector(Value *Vec);
414 /// \brief Look for a meaningful debug location on the instruction or it's
416 static Instruction *getDebugLocFromInstOrOperands(Instruction *I) {
421 if (I->getDebugLoc() != Empty)
424 for (User::op_iterator OI = I->op_begin(), OE = I->op_end(); OI != OE; ++OI) {
425 if (Instruction *OpInst = dyn_cast<Instruction>(*OI))
426 if (OpInst->getDebugLoc() != Empty)
433 /// \brief Set the debug location in the builder using the debug location in the
435 static void setDebugLocFromInst(IRBuilder<> &B, const Value *Ptr) {
436 if (const Instruction *Inst = dyn_cast_or_null<Instruction>(Ptr))
437 B.SetCurrentDebugLocation(Inst->getDebugLoc());
439 B.SetCurrentDebugLocation(DebugLoc());
442 /// LoopVectorizationLegality checks if it is legal to vectorize a loop, and
443 /// to what vectorization factor.
444 /// This class does not look at the profitability of vectorization, only the
445 /// legality. This class has two main kinds of checks:
446 /// * Memory checks - The code in canVectorizeMemory checks if vectorization
447 /// will change the order of memory accesses in a way that will change the
448 /// correctness of the program.
449 /// * Scalars checks - The code in canVectorizeInstrs and canVectorizeMemory
450 /// checks for a number of different conditions, such as the availability of a
451 /// single induction variable, that all types are supported and vectorize-able,
452 /// etc. This code reflects the capabilities of InnerLoopVectorizer.
453 /// This class is also used by InnerLoopVectorizer for identifying
454 /// induction variable and the different reduction variables.
455 class LoopVectorizationLegality {
457 LoopVectorizationLegality(Loop *L, ScalarEvolution *SE, DataLayout *DL,
458 DominatorTree *DT, TargetLibraryInfo *TLI)
459 : TheLoop(L), SE(SE), DL(DL), DT(DT), TLI(TLI),
460 Induction(0), WidestIndTy(0), HasFunNoNaNAttr(false),
461 MaxSafeDepDistBytes(-1U) {}
463 /// This enum represents the kinds of reductions that we support.
465 RK_NoReduction, ///< Not a reduction.
466 RK_IntegerAdd, ///< Sum of integers.
467 RK_IntegerMult, ///< Product of integers.
468 RK_IntegerOr, ///< Bitwise or logical OR of numbers.
469 RK_IntegerAnd, ///< Bitwise or logical AND of numbers.
470 RK_IntegerXor, ///< Bitwise or logical XOR of numbers.
471 RK_IntegerMinMax, ///< Min/max implemented in terms of select(cmp()).
472 RK_FloatAdd, ///< Sum of floats.
473 RK_FloatMult, ///< Product of floats.
474 RK_FloatMinMax ///< Min/max implemented in terms of select(cmp()).
477 /// This enum represents the kinds of inductions that we support.
479 IK_NoInduction, ///< Not an induction variable.
480 IK_IntInduction, ///< Integer induction variable. Step = 1.
481 IK_ReverseIntInduction, ///< Reverse int induction variable. Step = -1.
482 IK_PtrInduction, ///< Pointer induction var. Step = sizeof(elem).
483 IK_ReversePtrInduction ///< Reverse ptr indvar. Step = - sizeof(elem).
486 // This enum represents the kind of minmax reduction.
487 enum MinMaxReductionKind {
497 /// This struct holds information about reduction variables.
498 struct ReductionDescriptor {
499 ReductionDescriptor() : StartValue(0), LoopExitInstr(0),
500 Kind(RK_NoReduction), MinMaxKind(MRK_Invalid) {}
502 ReductionDescriptor(Value *Start, Instruction *Exit, ReductionKind K,
503 MinMaxReductionKind MK)
504 : StartValue(Start), LoopExitInstr(Exit), Kind(K), MinMaxKind(MK) {}
506 // The starting value of the reduction.
507 // It does not have to be zero!
508 TrackingVH<Value> StartValue;
509 // The instruction who's value is used outside the loop.
510 Instruction *LoopExitInstr;
511 // The kind of the reduction.
513 // If this a min/max reduction the kind of reduction.
514 MinMaxReductionKind MinMaxKind;
517 /// This POD struct holds information about a potential reduction operation.
518 struct ReductionInstDesc {
519 ReductionInstDesc(bool IsRedux, Instruction *I) :
520 IsReduction(IsRedux), PatternLastInst(I), MinMaxKind(MRK_Invalid) {}
522 ReductionInstDesc(Instruction *I, MinMaxReductionKind K) :
523 IsReduction(true), PatternLastInst(I), MinMaxKind(K) {}
525 // Is this instruction a reduction candidate.
527 // The last instruction in a min/max pattern (select of the select(icmp())
528 // pattern), or the current reduction instruction otherwise.
529 Instruction *PatternLastInst;
530 // If this is a min/max pattern the comparison predicate.
531 MinMaxReductionKind MinMaxKind;
534 /// This struct holds information about the memory runtime legality
535 /// check that a group of pointers do not overlap.
536 struct RuntimePointerCheck {
537 RuntimePointerCheck() : Need(false) {}
539 /// Reset the state of the pointer runtime information.
546 DependencySetId.clear();
549 /// Insert a pointer and calculate the start and end SCEVs.
550 void insert(ScalarEvolution *SE, Loop *Lp, Value *Ptr, bool WritePtr,
551 unsigned DepSetId, ValueToValueMap &Strides);
553 /// This flag indicates if we need to add the runtime check.
555 /// Holds the pointers that we need to check.
556 SmallVector<TrackingVH<Value>, 2> Pointers;
557 /// Holds the pointer value at the beginning of the loop.
558 SmallVector<const SCEV*, 2> Starts;
559 /// Holds the pointer value at the end of the loop.
560 SmallVector<const SCEV*, 2> Ends;
561 /// Holds the information if this pointer is used for writing to memory.
562 SmallVector<bool, 2> IsWritePtr;
563 /// Holds the id of the set of pointers that could be dependent because of a
564 /// shared underlying object.
565 SmallVector<unsigned, 2> DependencySetId;
568 /// A struct for saving information about induction variables.
569 struct InductionInfo {
570 InductionInfo(Value *Start, InductionKind K) : StartValue(Start), IK(K) {}
571 InductionInfo() : StartValue(0), IK(IK_NoInduction) {}
573 TrackingVH<Value> StartValue;
578 /// ReductionList contains the reduction descriptors for all
579 /// of the reductions that were found in the loop.
580 typedef DenseMap<PHINode*, ReductionDescriptor> ReductionList;
582 /// InductionList saves induction variables and maps them to the
583 /// induction descriptor.
584 typedef MapVector<PHINode*, InductionInfo> InductionList;
586 /// Returns true if it is legal to vectorize this loop.
587 /// This does not mean that it is profitable to vectorize this
588 /// loop, only that it is legal to do so.
591 /// Returns the Induction variable.
592 PHINode *getInduction() { return Induction; }
594 /// Returns the reduction variables found in the loop.
595 ReductionList *getReductionVars() { return &Reductions; }
597 /// Returns the induction variables found in the loop.
598 InductionList *getInductionVars() { return &Inductions; }
600 /// Returns the widest induction type.
601 Type *getWidestInductionType() { return WidestIndTy; }
603 /// Returns True if V is an induction variable in this loop.
604 bool isInductionVariable(const Value *V);
606 /// Return true if the block BB needs to be predicated in order for the loop
607 /// to be vectorized.
608 bool blockNeedsPredication(BasicBlock *BB);
610 /// Check if this pointer is consecutive when vectorizing. This happens
611 /// when the last index of the GEP is the induction variable, or that the
612 /// pointer itself is an induction variable.
613 /// This check allows us to vectorize A[idx] into a wide load/store.
615 /// 0 - Stride is unknown or non-consecutive.
616 /// 1 - Address is consecutive.
617 /// -1 - Address is consecutive, and decreasing.
618 int isConsecutivePtr(Value *Ptr);
620 /// Returns true if the value V is uniform within the loop.
621 bool isUniform(Value *V);
623 /// Returns true if this instruction will remain scalar after vectorization.
624 bool isUniformAfterVectorization(Instruction* I) { return Uniforms.count(I); }
626 /// Returns the information that we collected about runtime memory check.
627 RuntimePointerCheck *getRuntimePointerCheck() { return &PtrRtCheck; }
629 /// This function returns the identity element (or neutral element) for
631 static Constant *getReductionIdentity(ReductionKind K, Type *Tp);
633 unsigned getMaxSafeDepDistBytes() { return MaxSafeDepDistBytes; }
635 bool hasStride(Value *V) { return StrideSet.count(V); }
636 bool mustCheckStrides() { return !StrideSet.empty(); }
637 SmallPtrSet<Value *, 8>::iterator strides_begin() {
638 return StrideSet.begin();
640 SmallPtrSet<Value *, 8>::iterator strides_end() { return StrideSet.end(); }
643 /// Check if a single basic block loop is vectorizable.
644 /// At this point we know that this is a loop with a constant trip count
645 /// and we only need to check individual instructions.
646 bool canVectorizeInstrs();
648 /// When we vectorize loops we may change the order in which
649 /// we read and write from memory. This method checks if it is
650 /// legal to vectorize the code, considering only memory constrains.
651 /// Returns true if the loop is vectorizable
652 bool canVectorizeMemory();
654 /// Return true if we can vectorize this loop using the IF-conversion
656 bool canVectorizeWithIfConvert();
658 /// Collect the variables that need to stay uniform after vectorization.
659 void collectLoopUniforms();
661 /// Return true if all of the instructions in the block can be speculatively
662 /// executed. \p SafePtrs is a list of addresses that are known to be legal
663 /// and we know that we can read from them without segfault.
664 bool blockCanBePredicated(BasicBlock *BB, SmallPtrSet<Value *, 8>& SafePtrs);
666 /// Returns True, if 'Phi' is the kind of reduction variable for type
667 /// 'Kind'. If this is a reduction variable, it adds it to ReductionList.
668 bool AddReductionVar(PHINode *Phi, ReductionKind Kind);
669 /// Returns a struct describing if the instruction 'I' can be a reduction
670 /// variable of type 'Kind'. If the reduction is a min/max pattern of
671 /// select(icmp()) this function advances the instruction pointer 'I' from the
672 /// compare instruction to the select instruction and stores this pointer in
673 /// 'PatternLastInst' member of the returned struct.
674 ReductionInstDesc isReductionInstr(Instruction *I, ReductionKind Kind,
675 ReductionInstDesc &Desc);
676 /// Returns true if the instruction is a Select(ICmp(X, Y), X, Y) instruction
677 /// pattern corresponding to a min(X, Y) or max(X, Y).
678 static ReductionInstDesc isMinMaxSelectCmpPattern(Instruction *I,
679 ReductionInstDesc &Prev);
680 /// Returns the induction kind of Phi. This function may return NoInduction
681 /// if the PHI is not an induction variable.
682 InductionKind isInductionVariable(PHINode *Phi);
684 /// \brief Collect memory access with loop invariant strides.
686 /// Looks for accesses like "a[i * StrideA]" where "StrideA" is loop
688 void collectStridedAcccess(Value *LoadOrStoreInst);
690 /// The loop that we evaluate.
694 /// DataLayout analysis.
698 /// Target Library Info.
699 TargetLibraryInfo *TLI;
701 // --- vectorization state --- //
703 /// Holds the integer induction variable. This is the counter of the
706 /// Holds the reduction variables.
707 ReductionList Reductions;
708 /// Holds all of the induction variables that we found in the loop.
709 /// Notice that inductions don't need to start at zero and that induction
710 /// variables can be pointers.
711 InductionList Inductions;
712 /// Holds the widest induction type encountered.
715 /// Allowed outside users. This holds the reduction
716 /// vars which can be accessed from outside the loop.
717 SmallPtrSet<Value*, 4> AllowedExit;
718 /// This set holds the variables which are known to be uniform after
720 SmallPtrSet<Instruction*, 4> Uniforms;
721 /// We need to check that all of the pointers in this list are disjoint
723 RuntimePointerCheck PtrRtCheck;
724 /// Can we assume the absence of NaNs.
725 bool HasFunNoNaNAttr;
727 unsigned MaxSafeDepDistBytes;
729 ValueToValueMap Strides;
730 SmallPtrSet<Value *, 8> StrideSet;
733 /// LoopVectorizationCostModel - estimates the expected speedups due to
735 /// In many cases vectorization is not profitable. This can happen because of
736 /// a number of reasons. In this class we mainly attempt to predict the
737 /// expected speedup/slowdowns due to the supported instruction set. We use the
738 /// TargetTransformInfo to query the different backends for the cost of
739 /// different operations.
740 class LoopVectorizationCostModel {
742 LoopVectorizationCostModel(Loop *L, ScalarEvolution *SE, LoopInfo *LI,
743 LoopVectorizationLegality *Legal,
744 const TargetTransformInfo &TTI,
745 DataLayout *DL, const TargetLibraryInfo *TLI)
746 : TheLoop(L), SE(SE), LI(LI), Legal(Legal), TTI(TTI), DL(DL), TLI(TLI) {}
748 /// Information about vectorization costs
749 struct VectorizationFactor {
750 unsigned Width; // Vector width with best cost
751 unsigned Cost; // Cost of the loop with that width
753 /// \return The most profitable vectorization factor and the cost of that VF.
754 /// This method checks every power of two up to VF. If UserVF is not ZERO
755 /// then this vectorization factor will be selected if vectorization is
757 VectorizationFactor selectVectorizationFactor(bool OptForSize,
760 /// \return The size (in bits) of the widest type in the code that
761 /// needs to be vectorized. We ignore values that remain scalar such as
762 /// 64 bit loop indices.
763 unsigned getWidestType();
765 /// \return The most profitable unroll factor.
766 /// If UserUF is non-zero then this method finds the best unroll-factor
767 /// based on register pressure and other parameters.
768 /// VF and LoopCost are the selected vectorization factor and the cost of the
770 unsigned selectUnrollFactor(bool OptForSize, unsigned UserUF, unsigned VF,
773 /// \brief A struct that represents some properties of the register usage
775 struct RegisterUsage {
776 /// Holds the number of loop invariant values that are used in the loop.
777 unsigned LoopInvariantRegs;
778 /// Holds the maximum number of concurrent live intervals in the loop.
779 unsigned MaxLocalUsers;
780 /// Holds the number of instructions in the loop.
781 unsigned NumInstructions;
784 /// \return information about the register usage of the loop.
785 RegisterUsage calculateRegisterUsage();
788 /// Returns the expected execution cost. The unit of the cost does
789 /// not matter because we use the 'cost' units to compare different
790 /// vector widths. The cost that is returned is *not* normalized by
791 /// the factor width.
792 unsigned expectedCost(unsigned VF);
794 /// Returns the execution time cost of an instruction for a given vector
795 /// width. Vector width of one means scalar.
796 unsigned getInstructionCost(Instruction *I, unsigned VF);
798 /// A helper function for converting Scalar types to vector types.
799 /// If the incoming type is void, we return void. If the VF is 1, we return
801 static Type* ToVectorTy(Type *Scalar, unsigned VF);
803 /// Returns whether the instruction is a load or store and will be a emitted
804 /// as a vector operation.
805 bool isConsecutiveLoadOrStore(Instruction *I);
807 /// The loop that we evaluate.
811 /// Loop Info analysis.
813 /// Vectorization legality.
814 LoopVectorizationLegality *Legal;
815 /// Vector target information.
816 const TargetTransformInfo &TTI;
817 /// Target data layout information.
819 /// Target Library Info.
820 const TargetLibraryInfo *TLI;
823 /// Utility class for getting and setting loop vectorizer hints in the form
824 /// of loop metadata.
825 struct LoopVectorizeHints {
826 /// Vectorization width.
828 /// Vectorization unroll factor.
830 /// Vectorization forced (-1 not selected, 0 force disabled, 1 force enabled)
833 LoopVectorizeHints(const Loop *L, bool DisableUnrolling)
834 : Width(VectorizationFactor)
835 , Unroll(DisableUnrolling ? 1 : VectorizationUnroll)
837 , LoopID(L->getLoopID()) {
839 // The command line options override any loop metadata except for when
840 // width == 1 which is used to indicate the loop is already vectorized.
841 if (VectorizationFactor.getNumOccurrences() > 0 && Width != 1)
842 Width = VectorizationFactor;
843 if (VectorizationUnroll.getNumOccurrences() > 0)
844 Unroll = VectorizationUnroll;
846 DEBUG(if (DisableUnrolling && Unroll == 1)
847 dbgs() << "LV: Unrolling disabled by the pass manager\n");
850 /// Return the loop vectorizer metadata prefix.
851 static StringRef Prefix() { return "llvm.vectorizer."; }
853 MDNode *createHint(LLVMContext &Context, StringRef Name, unsigned V) {
854 SmallVector<Value*, 2> Vals;
855 Vals.push_back(MDString::get(Context, Name));
856 Vals.push_back(ConstantInt::get(Type::getInt32Ty(Context), V));
857 return MDNode::get(Context, Vals);
860 /// Mark the loop L as already vectorized by setting the width to 1.
861 void setAlreadyVectorized(Loop *L) {
862 LLVMContext &Context = L->getHeader()->getContext();
866 // Create a new loop id with one more operand for the already_vectorized
867 // hint. If the loop already has a loop id then copy the existing operands.
868 SmallVector<Value*, 4> Vals(1);
870 for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i)
871 Vals.push_back(LoopID->getOperand(i));
873 Vals.push_back(createHint(Context, Twine(Prefix(), "width").str(), Width));
874 Vals.push_back(createHint(Context, Twine(Prefix(), "unroll").str(), 1));
876 MDNode *NewLoopID = MDNode::get(Context, Vals);
877 // Set operand 0 to refer to the loop id itself.
878 NewLoopID->replaceOperandWith(0, NewLoopID);
880 L->setLoopID(NewLoopID);
882 LoopID->replaceAllUsesWith(NewLoopID);
890 /// Find hints specified in the loop metadata.
891 void getHints(const Loop *L) {
895 // First operand should refer to the loop id itself.
896 assert(LoopID->getNumOperands() > 0 && "requires at least one operand");
897 assert(LoopID->getOperand(0) == LoopID && "invalid loop id");
899 for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) {
900 const MDString *S = 0;
901 SmallVector<Value*, 4> Args;
903 // The expected hint is either a MDString or a MDNode with the first
904 // operand a MDString.
905 if (const MDNode *MD = dyn_cast<MDNode>(LoopID->getOperand(i))) {
906 if (!MD || MD->getNumOperands() == 0)
908 S = dyn_cast<MDString>(MD->getOperand(0));
909 for (unsigned i = 1, ie = MD->getNumOperands(); i < ie; ++i)
910 Args.push_back(MD->getOperand(i));
912 S = dyn_cast<MDString>(LoopID->getOperand(i));
913 assert(Args.size() == 0 && "too many arguments for MDString");
919 // Check if the hint starts with the vectorizer prefix.
920 StringRef Hint = S->getString();
921 if (!Hint.startswith(Prefix()))
923 // Remove the prefix.
924 Hint = Hint.substr(Prefix().size(), StringRef::npos);
926 if (Args.size() == 1)
927 getHint(Hint, Args[0]);
931 // Check string hint with one operand.
932 void getHint(StringRef Hint, Value *Arg) {
933 const ConstantInt *C = dyn_cast<ConstantInt>(Arg);
935 unsigned Val = C->getZExtValue();
937 if (Hint == "width") {
938 if (isPowerOf2_32(Val) && Val <= MaxVectorWidth)
941 DEBUG(dbgs() << "LV: ignoring invalid width hint metadata\n");
942 } else if (Hint == "unroll") {
943 if (isPowerOf2_32(Val) && Val <= MaxUnrollFactor)
946 DEBUG(dbgs() << "LV: ignoring invalid unroll hint metadata\n");
947 } else if (Hint == "enable") {
948 if (C->getBitWidth() == 1)
951 DEBUG(dbgs() << "LV: ignoring invalid enable hint metadata\n");
953 DEBUG(dbgs() << "LV: ignoring unknown hint " << Hint << '\n');
958 static void addInnerLoop(Loop *L, SmallVectorImpl<Loop *> &V) {
960 return V.push_back(L);
962 for (Loop::iterator I = L->begin(), E = L->end(); I != E; ++I)
966 /// The LoopVectorize Pass.
967 struct LoopVectorize : public FunctionPass {
968 /// Pass identification, replacement for typeid
971 explicit LoopVectorize(bool NoUnrolling = false, bool AlwaysVectorize = true)
973 DisableUnrolling(NoUnrolling),
974 AlwaysVectorize(AlwaysVectorize) {
975 initializeLoopVectorizePass(*PassRegistry::getPassRegistry());
981 TargetTransformInfo *TTI;
983 TargetLibraryInfo *TLI;
984 bool DisableUnrolling;
985 bool AlwaysVectorize;
987 virtual bool runOnFunction(Function &F) {
988 SE = &getAnalysis<ScalarEvolution>();
989 DL = getAnalysisIfAvailable<DataLayout>();
990 LI = &getAnalysis<LoopInfo>();
991 TTI = &getAnalysis<TargetTransformInfo>();
992 DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree();
993 TLI = getAnalysisIfAvailable<TargetLibraryInfo>();
995 // If the target claims to have no vector registers don't attempt
997 if (!TTI->getNumberOfRegisters(true))
1001 DEBUG(dbgs() << "LV: Not vectorizing: Missing data layout\n");
1005 // Build up a worklist of inner-loops to vectorize. This is necessary as
1006 // the act of vectorizing or partially unrolling a loop creates new loops
1007 // and can invalidate iterators across the loops.
1008 SmallVector<Loop *, 8> Worklist;
1010 for (LoopInfo::iterator I = LI->begin(), E = LI->end(); I != E; ++I)
1011 addInnerLoop(*I, Worklist);
1013 // Now walk the identified inner loops.
1014 bool Changed = false;
1015 while (!Worklist.empty())
1016 Changed |= processLoop(Worklist.pop_back_val());
1018 // Process each loop nest in the function.
1022 bool processLoop(Loop *L) {
1023 // We only handle inner loops, so if there are children just recurse.
1025 bool Changed = false;
1026 for (Loop::iterator I = L->begin(), E = L->begin(); I != E; ++I)
1027 Changed |= processLoop(*I);
1031 DEBUG(dbgs() << "LV: Checking a loop in \"" <<
1032 L->getHeader()->getParent()->getName() << "\"\n");
1034 LoopVectorizeHints Hints(L, DisableUnrolling);
1036 if (Hints.Force == 0) {
1037 DEBUG(dbgs() << "LV: Not vectorizing: #pragma vectorize disable.\n");
1041 if (!AlwaysVectorize && Hints.Force != 1) {
1042 DEBUG(dbgs() << "LV: Not vectorizing: No #pragma vectorize enable.\n");
1046 if (Hints.Width == 1 && Hints.Unroll == 1) {
1047 DEBUG(dbgs() << "LV: Not vectorizing: Disabled/already vectorized.\n");
1051 // Check if it is legal to vectorize the loop.
1052 LoopVectorizationLegality LVL(L, SE, DL, DT, TLI);
1053 if (!LVL.canVectorize()) {
1054 DEBUG(dbgs() << "LV: Not vectorizing: Cannot prove legality.\n");
1058 // Use the cost model.
1059 LoopVectorizationCostModel CM(L, SE, LI, &LVL, *TTI, DL, TLI);
1061 // Check the function attributes to find out if this function should be
1062 // optimized for size.
1063 Function *F = L->getHeader()->getParent();
1065 Hints.Force != 1 && F->hasFnAttribute(Attribute::OptimizeForSize);
1067 // Check the function attributes to see if implicit floats are allowed.a
1068 // FIXME: This check doesn't seem possibly correct -- what if the loop is
1069 // an integer loop and the vector instructions selected are purely integer
1070 // vector instructions?
1071 if (F->hasFnAttribute(Attribute::NoImplicitFloat)) {
1072 DEBUG(dbgs() << "LV: Can't vectorize when the NoImplicitFloat"
1073 "attribute is used.\n");
1077 // Select the optimal vectorization factor.
1078 LoopVectorizationCostModel::VectorizationFactor VF;
1079 VF = CM.selectVectorizationFactor(OptForSize, Hints.Width);
1080 // Select the unroll factor.
1081 unsigned UF = CM.selectUnrollFactor(OptForSize, Hints.Unroll, VF.Width,
1084 DEBUG(dbgs() << "LV: Found a vectorizable loop ("<< VF.Width << ") in "<<
1085 F->getParent()->getModuleIdentifier() << '\n');
1086 DEBUG(dbgs() << "LV: Unroll Factor is " << UF << '\n');
1088 if (VF.Width == 1) {
1089 DEBUG(dbgs() << "LV: Vectorization is possible but not beneficial.\n");
1092 DEBUG(dbgs() << "LV: Trying to at least unroll the loops.\n");
1093 // We decided not to vectorize, but we may want to unroll.
1094 InnerLoopUnroller Unroller(L, SE, LI, DT, DL, TLI, UF);
1095 Unroller.vectorize(&LVL);
1097 // If we decided that it is *legal* to vectorize the loop then do it.
1098 InnerLoopVectorizer LB(L, SE, LI, DT, DL, TLI, VF.Width, UF);
1102 // Mark the loop as already vectorized to avoid vectorizing again.
1103 Hints.setAlreadyVectorized(L);
1105 DEBUG(verifyFunction(*L->getHeader()->getParent()));
1109 virtual void getAnalysisUsage(AnalysisUsage &AU) const {
1110 AU.addRequiredID(LoopSimplifyID);
1111 AU.addRequiredID(LCSSAID);
1112 AU.addRequired<DominatorTreeWrapperPass>();
1113 AU.addRequired<LoopInfo>();
1114 AU.addRequired<ScalarEvolution>();
1115 AU.addRequired<TargetTransformInfo>();
1116 AU.addPreserved<LoopInfo>();
1117 AU.addPreserved<DominatorTreeWrapperPass>();
1122 } // end anonymous namespace
1124 //===----------------------------------------------------------------------===//
1125 // Implementation of LoopVectorizationLegality, InnerLoopVectorizer and
1126 // LoopVectorizationCostModel.
1127 //===----------------------------------------------------------------------===//
1129 static Value *stripIntegerCast(Value *V) {
1130 if (CastInst *CI = dyn_cast<CastInst>(V))
1131 if (CI->getOperand(0)->getType()->isIntegerTy())
1132 return CI->getOperand(0);
1136 ///\brief Replaces the symbolic stride in a pointer SCEV expression by one.
1138 /// If \p OrigPtr is not null, use it to look up the stride value instead of
1140 static const SCEV *replaceSymbolicStrideSCEV(ScalarEvolution *SE,
1141 ValueToValueMap &PtrToStride,
1142 Value *Ptr, Value *OrigPtr = 0) {
1144 const SCEV *OrigSCEV = SE->getSCEV(Ptr);
1146 // If there is an entry in the map return the SCEV of the pointer with the
1147 // symbolic stride replaced by one.
1148 ValueToValueMap::iterator SI = PtrToStride.find(OrigPtr ? OrigPtr : Ptr);
1149 if (SI != PtrToStride.end()) {
1150 Value *StrideVal = SI->second;
1153 StrideVal = stripIntegerCast(StrideVal);
1155 // Replace symbolic stride by one.
1156 Value *One = ConstantInt::get(StrideVal->getType(), 1);
1157 ValueToValueMap RewriteMap;
1158 RewriteMap[StrideVal] = One;
1161 SCEVParameterRewriter::rewrite(OrigSCEV, *SE, RewriteMap, true);
1162 DEBUG(dbgs() << "LV: Replacing SCEV: " << *OrigSCEV << " by: " << *ByOne
1167 // Otherwise, just return the SCEV of the original pointer.
1168 return SE->getSCEV(Ptr);
1171 void LoopVectorizationLegality::RuntimePointerCheck::insert(
1172 ScalarEvolution *SE, Loop *Lp, Value *Ptr, bool WritePtr, unsigned DepSetId,
1173 ValueToValueMap &Strides) {
1174 // Get the stride replaced scev.
1175 const SCEV *Sc = replaceSymbolicStrideSCEV(SE, Strides, Ptr);
1176 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Sc);
1177 assert(AR && "Invalid addrec expression");
1178 const SCEV *Ex = SE->getBackedgeTakenCount(Lp);
1179 const SCEV *ScEnd = AR->evaluateAtIteration(Ex, *SE);
1180 Pointers.push_back(Ptr);
1181 Starts.push_back(AR->getStart());
1182 Ends.push_back(ScEnd);
1183 IsWritePtr.push_back(WritePtr);
1184 DependencySetId.push_back(DepSetId);
1187 Value *InnerLoopVectorizer::getBroadcastInstrs(Value *V) {
1188 // We need to place the broadcast of invariant variables outside the loop.
1189 Instruction *Instr = dyn_cast<Instruction>(V);
1190 bool NewInstr = (Instr && Instr->getParent() == LoopVectorBody);
1191 bool Invariant = OrigLoop->isLoopInvariant(V) && !NewInstr;
1193 // Place the code for broadcasting invariant variables in the new preheader.
1194 IRBuilder<>::InsertPointGuard Guard(Builder);
1196 Builder.SetInsertPoint(LoopVectorPreHeader->getTerminator());
1198 // Broadcast the scalar into all locations in the vector.
1199 Value *Shuf = Builder.CreateVectorSplat(VF, V, "broadcast");
1204 Value *InnerLoopVectorizer::getConsecutiveVector(Value* Val, int StartIdx,
1206 assert(Val->getType()->isVectorTy() && "Must be a vector");
1207 assert(Val->getType()->getScalarType()->isIntegerTy() &&
1208 "Elem must be an integer");
1209 // Create the types.
1210 Type *ITy = Val->getType()->getScalarType();
1211 VectorType *Ty = cast<VectorType>(Val->getType());
1212 int VLen = Ty->getNumElements();
1213 SmallVector<Constant*, 8> Indices;
1215 // Create a vector of consecutive numbers from zero to VF.
1216 for (int i = 0; i < VLen; ++i) {
1217 int64_t Idx = Negate ? (-i) : i;
1218 Indices.push_back(ConstantInt::get(ITy, StartIdx + Idx, Negate));
1221 // Add the consecutive indices to the vector value.
1222 Constant *Cv = ConstantVector::get(Indices);
1223 assert(Cv->getType() == Val->getType() && "Invalid consecutive vec");
1224 return Builder.CreateAdd(Val, Cv, "induction");
1227 /// \brief Find the operand of the GEP that should be checked for consecutive
1228 /// stores. This ignores trailing indices that have no effect on the final
1230 static unsigned getGEPInductionOperand(DataLayout *DL,
1231 const GetElementPtrInst *Gep) {
1232 unsigned LastOperand = Gep->getNumOperands() - 1;
1233 unsigned GEPAllocSize = DL->getTypeAllocSize(
1234 cast<PointerType>(Gep->getType()->getScalarType())->getElementType());
1236 // Walk backwards and try to peel off zeros.
1237 while (LastOperand > 1 && match(Gep->getOperand(LastOperand), m_Zero())) {
1238 // Find the type we're currently indexing into.
1239 gep_type_iterator GEPTI = gep_type_begin(Gep);
1240 std::advance(GEPTI, LastOperand - 1);
1242 // If it's a type with the same allocation size as the result of the GEP we
1243 // can peel off the zero index.
1244 if (DL->getTypeAllocSize(*GEPTI) != GEPAllocSize)
1252 int LoopVectorizationLegality::isConsecutivePtr(Value *Ptr) {
1253 assert(Ptr->getType()->isPointerTy() && "Unexpected non-ptr");
1254 // Make sure that the pointer does not point to structs.
1255 if (Ptr->getType()->getPointerElementType()->isAggregateType())
1258 // If this value is a pointer induction variable we know it is consecutive.
1259 PHINode *Phi = dyn_cast_or_null<PHINode>(Ptr);
1260 if (Phi && Inductions.count(Phi)) {
1261 InductionInfo II = Inductions[Phi];
1262 if (IK_PtrInduction == II.IK)
1264 else if (IK_ReversePtrInduction == II.IK)
1268 GetElementPtrInst *Gep = dyn_cast_or_null<GetElementPtrInst>(Ptr);
1272 unsigned NumOperands = Gep->getNumOperands();
1273 Value *GpPtr = Gep->getPointerOperand();
1274 // If this GEP value is a consecutive pointer induction variable and all of
1275 // the indices are constant then we know it is consecutive. We can
1276 Phi = dyn_cast<PHINode>(GpPtr);
1277 if (Phi && Inductions.count(Phi)) {
1279 // Make sure that the pointer does not point to structs.
1280 PointerType *GepPtrType = cast<PointerType>(GpPtr->getType());
1281 if (GepPtrType->getElementType()->isAggregateType())
1284 // Make sure that all of the index operands are loop invariant.
1285 for (unsigned i = 1; i < NumOperands; ++i)
1286 if (!SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop))
1289 InductionInfo II = Inductions[Phi];
1290 if (IK_PtrInduction == II.IK)
1292 else if (IK_ReversePtrInduction == II.IK)
1296 unsigned InductionOperand = getGEPInductionOperand(DL, Gep);
1298 // Check that all of the gep indices are uniform except for our induction
1300 for (unsigned i = 0; i != NumOperands; ++i)
1301 if (i != InductionOperand &&
1302 !SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop))
1305 // We can emit wide load/stores only if the last non-zero index is the
1306 // induction variable.
1307 const SCEV *Last = 0;
1308 if (!Strides.count(Gep))
1309 Last = SE->getSCEV(Gep->getOperand(InductionOperand));
1311 // Because of the multiplication by a stride we can have a s/zext cast.
1312 // We are going to replace this stride by 1 so the cast is safe to ignore.
1314 // %indvars.iv = phi i64 [ 0, %entry ], [ %indvars.iv.next, %for.body ]
1315 // %0 = trunc i64 %indvars.iv to i32
1316 // %mul = mul i32 %0, %Stride1
1317 // %idxprom = zext i32 %mul to i64 << Safe cast.
1318 // %arrayidx = getelementptr inbounds i32* %B, i64 %idxprom
1320 Last = replaceSymbolicStrideSCEV(SE, Strides,
1321 Gep->getOperand(InductionOperand), Gep);
1322 if (const SCEVCastExpr *C = dyn_cast<SCEVCastExpr>(Last))
1324 (C->getSCEVType() == scSignExtend || C->getSCEVType() == scZeroExtend)
1328 if (const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Last)) {
1329 const SCEV *Step = AR->getStepRecurrence(*SE);
1331 // The memory is consecutive because the last index is consecutive
1332 // and all other indices are loop invariant.
1335 if (Step->isAllOnesValue())
1342 bool LoopVectorizationLegality::isUniform(Value *V) {
1343 return (SE->isLoopInvariant(SE->getSCEV(V), TheLoop));
1346 InnerLoopVectorizer::VectorParts&
1347 InnerLoopVectorizer::getVectorValue(Value *V) {
1348 assert(V != Induction && "The new induction variable should not be used.");
1349 assert(!V->getType()->isVectorTy() && "Can't widen a vector");
1351 // If we have a stride that is replaced by one, do it here.
1352 if (Legal->hasStride(V))
1353 V = ConstantInt::get(V->getType(), 1);
1355 // If we have this scalar in the map, return it.
1356 if (WidenMap.has(V))
1357 return WidenMap.get(V);
1359 // If this scalar is unknown, assume that it is a constant or that it is
1360 // loop invariant. Broadcast V and save the value for future uses.
1361 Value *B = getBroadcastInstrs(V);
1362 return WidenMap.splat(V, B);
1365 Value *InnerLoopVectorizer::reverseVector(Value *Vec) {
1366 assert(Vec->getType()->isVectorTy() && "Invalid type");
1367 SmallVector<Constant*, 8> ShuffleMask;
1368 for (unsigned i = 0; i < VF; ++i)
1369 ShuffleMask.push_back(Builder.getInt32(VF - i - 1));
1371 return Builder.CreateShuffleVector(Vec, UndefValue::get(Vec->getType()),
1372 ConstantVector::get(ShuffleMask),
1376 void InnerLoopVectorizer::vectorizeMemoryInstruction(Instruction *Instr) {
1377 // Attempt to issue a wide load.
1378 LoadInst *LI = dyn_cast<LoadInst>(Instr);
1379 StoreInst *SI = dyn_cast<StoreInst>(Instr);
1381 assert((LI || SI) && "Invalid Load/Store instruction");
1383 Type *ScalarDataTy = LI ? LI->getType() : SI->getValueOperand()->getType();
1384 Type *DataTy = VectorType::get(ScalarDataTy, VF);
1385 Value *Ptr = LI ? LI->getPointerOperand() : SI->getPointerOperand();
1386 unsigned Alignment = LI ? LI->getAlignment() : SI->getAlignment();
1387 // An alignment of 0 means target abi alignment. We need to use the scalar's
1388 // target abi alignment in such a case.
1390 Alignment = DL->getABITypeAlignment(ScalarDataTy);
1391 unsigned AddressSpace = Ptr->getType()->getPointerAddressSpace();
1392 unsigned ScalarAllocatedSize = DL->getTypeAllocSize(ScalarDataTy);
1393 unsigned VectorElementSize = DL->getTypeStoreSize(DataTy)/VF;
1395 if (ScalarAllocatedSize != VectorElementSize)
1396 return scalarizeInstruction(Instr);
1398 // If the pointer is loop invariant or if it is non-consecutive,
1399 // scalarize the load.
1400 int ConsecutiveStride = Legal->isConsecutivePtr(Ptr);
1401 bool Reverse = ConsecutiveStride < 0;
1402 bool UniformLoad = LI && Legal->isUniform(Ptr);
1403 if (!ConsecutiveStride || UniformLoad)
1404 return scalarizeInstruction(Instr);
1406 Constant *Zero = Builder.getInt32(0);
1407 VectorParts &Entry = WidenMap.get(Instr);
1409 // Handle consecutive loads/stores.
1410 GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr);
1411 if (Gep && Legal->isInductionVariable(Gep->getPointerOperand())) {
1412 setDebugLocFromInst(Builder, Gep);
1413 Value *PtrOperand = Gep->getPointerOperand();
1414 Value *FirstBasePtr = getVectorValue(PtrOperand)[0];
1415 FirstBasePtr = Builder.CreateExtractElement(FirstBasePtr, Zero);
1417 // Create the new GEP with the new induction variable.
1418 GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone());
1419 Gep2->setOperand(0, FirstBasePtr);
1420 Gep2->setName("gep.indvar.base");
1421 Ptr = Builder.Insert(Gep2);
1423 setDebugLocFromInst(Builder, Gep);
1424 assert(SE->isLoopInvariant(SE->getSCEV(Gep->getPointerOperand()),
1425 OrigLoop) && "Base ptr must be invariant");
1427 // The last index does not have to be the induction. It can be
1428 // consecutive and be a function of the index. For example A[I+1];
1429 unsigned NumOperands = Gep->getNumOperands();
1430 unsigned InductionOperand = getGEPInductionOperand(DL, Gep);
1431 // Create the new GEP with the new induction variable.
1432 GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone());
1434 for (unsigned i = 0; i < NumOperands; ++i) {
1435 Value *GepOperand = Gep->getOperand(i);
1436 Instruction *GepOperandInst = dyn_cast<Instruction>(GepOperand);
1438 // Update last index or loop invariant instruction anchored in loop.
1439 if (i == InductionOperand ||
1440 (GepOperandInst && OrigLoop->contains(GepOperandInst))) {
1441 assert((i == InductionOperand ||
1442 SE->isLoopInvariant(SE->getSCEV(GepOperandInst), OrigLoop)) &&
1443 "Must be last index or loop invariant");
1445 VectorParts &GEPParts = getVectorValue(GepOperand);
1446 Value *Index = GEPParts[0];
1447 Index = Builder.CreateExtractElement(Index, Zero);
1448 Gep2->setOperand(i, Index);
1449 Gep2->setName("gep.indvar.idx");
1452 Ptr = Builder.Insert(Gep2);
1454 // Use the induction element ptr.
1455 assert(isa<PHINode>(Ptr) && "Invalid induction ptr");
1456 setDebugLocFromInst(Builder, Ptr);
1457 VectorParts &PtrVal = getVectorValue(Ptr);
1458 Ptr = Builder.CreateExtractElement(PtrVal[0], Zero);
1463 assert(!Legal->isUniform(SI->getPointerOperand()) &&
1464 "We do not allow storing to uniform addresses");
1465 setDebugLocFromInst(Builder, SI);
1466 // We don't want to update the value in the map as it might be used in
1467 // another expression. So don't use a reference type for "StoredVal".
1468 VectorParts StoredVal = getVectorValue(SI->getValueOperand());
1470 for (unsigned Part = 0; Part < UF; ++Part) {
1471 // Calculate the pointer for the specific unroll-part.
1472 Value *PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(Part * VF));
1475 // If we store to reverse consecutive memory locations then we need
1476 // to reverse the order of elements in the stored value.
1477 StoredVal[Part] = reverseVector(StoredVal[Part]);
1478 // If the address is consecutive but reversed, then the
1479 // wide store needs to start at the last vector element.
1480 PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(-Part * VF));
1481 PartPtr = Builder.CreateGEP(PartPtr, Builder.getInt32(1 - VF));
1484 Value *VecPtr = Builder.CreateBitCast(PartPtr,
1485 DataTy->getPointerTo(AddressSpace));
1486 Builder.CreateStore(StoredVal[Part], VecPtr)->setAlignment(Alignment);
1492 assert(LI && "Must have a load instruction");
1493 setDebugLocFromInst(Builder, LI);
1494 for (unsigned Part = 0; Part < UF; ++Part) {
1495 // Calculate the pointer for the specific unroll-part.
1496 Value *PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(Part * VF));
1499 // If the address is consecutive but reversed, then the
1500 // wide store needs to start at the last vector element.
1501 PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(-Part * VF));
1502 PartPtr = Builder.CreateGEP(PartPtr, Builder.getInt32(1 - VF));
1505 Value *VecPtr = Builder.CreateBitCast(PartPtr,
1506 DataTy->getPointerTo(AddressSpace));
1507 Value *LI = Builder.CreateLoad(VecPtr, "wide.load");
1508 cast<LoadInst>(LI)->setAlignment(Alignment);
1509 Entry[Part] = Reverse ? reverseVector(LI) : LI;
1513 void InnerLoopVectorizer::scalarizeInstruction(Instruction *Instr) {
1514 assert(!Instr->getType()->isAggregateType() && "Can't handle vectors");
1515 // Holds vector parameters or scalars, in case of uniform vals.
1516 SmallVector<VectorParts, 4> Params;
1518 setDebugLocFromInst(Builder, Instr);
1520 // Find all of the vectorized parameters.
1521 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
1522 Value *SrcOp = Instr->getOperand(op);
1524 // If we are accessing the old induction variable, use the new one.
1525 if (SrcOp == OldInduction) {
1526 Params.push_back(getVectorValue(SrcOp));
1530 // Try using previously calculated values.
1531 Instruction *SrcInst = dyn_cast<Instruction>(SrcOp);
1533 // If the src is an instruction that appeared earlier in the basic block
1534 // then it should already be vectorized.
1535 if (SrcInst && OrigLoop->contains(SrcInst)) {
1536 assert(WidenMap.has(SrcInst) && "Source operand is unavailable");
1537 // The parameter is a vector value from earlier.
1538 Params.push_back(WidenMap.get(SrcInst));
1540 // The parameter is a scalar from outside the loop. Maybe even a constant.
1541 VectorParts Scalars;
1542 Scalars.append(UF, SrcOp);
1543 Params.push_back(Scalars);
1547 assert(Params.size() == Instr->getNumOperands() &&
1548 "Invalid number of operands");
1550 // Does this instruction return a value ?
1551 bool IsVoidRetTy = Instr->getType()->isVoidTy();
1553 Value *UndefVec = IsVoidRetTy ? 0 :
1554 UndefValue::get(VectorType::get(Instr->getType(), VF));
1555 // Create a new entry in the WidenMap and initialize it to Undef or Null.
1556 VectorParts &VecResults = WidenMap.splat(Instr, UndefVec);
1558 // For each vector unroll 'part':
1559 for (unsigned Part = 0; Part < UF; ++Part) {
1560 // For each scalar that we create:
1561 for (unsigned Width = 0; Width < VF; ++Width) {
1562 Instruction *Cloned = Instr->clone();
1564 Cloned->setName(Instr->getName() + ".cloned");
1565 // Replace the operands of the cloned instructions with extracted scalars.
1566 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
1567 Value *Op = Params[op][Part];
1568 // Param is a vector. Need to extract the right lane.
1569 if (Op->getType()->isVectorTy())
1570 Op = Builder.CreateExtractElement(Op, Builder.getInt32(Width));
1571 Cloned->setOperand(op, Op);
1574 // Place the cloned scalar in the new loop.
1575 Builder.Insert(Cloned);
1577 // If the original scalar returns a value we need to place it in a vector
1578 // so that future users will be able to use it.
1580 VecResults[Part] = Builder.CreateInsertElement(VecResults[Part], Cloned,
1581 Builder.getInt32(Width));
1586 static Instruction *getFirstInst(Instruction *FirstInst, Value *V,
1590 if (Instruction *I = dyn_cast<Instruction>(V))
1591 return I->getParent() == Loc->getParent() ? I : 0;
1595 std::pair<Instruction *, Instruction *>
1596 InnerLoopVectorizer::addStrideCheck(Instruction *Loc) {
1597 Instruction *tnullptr = 0;
1598 if (!Legal->mustCheckStrides())
1599 return std::pair<Instruction *, Instruction *>(tnullptr, tnullptr);
1601 IRBuilder<> ChkBuilder(Loc);
1605 Instruction *FirstInst = 0;
1606 for (SmallPtrSet<Value *, 8>::iterator SI = Legal->strides_begin(),
1607 SE = Legal->strides_end();
1609 Value *Ptr = stripIntegerCast(*SI);
1610 Value *C = ChkBuilder.CreateICmpNE(Ptr, ConstantInt::get(Ptr->getType(), 1),
1612 // Store the first instruction we create.
1613 FirstInst = getFirstInst(FirstInst, C, Loc);
1615 Check = ChkBuilder.CreateOr(Check, C);
1620 // We have to do this trickery because the IRBuilder might fold the check to a
1621 // constant expression in which case there is no Instruction anchored in a
1623 LLVMContext &Ctx = Loc->getContext();
1624 Instruction *TheCheck =
1625 BinaryOperator::CreateAnd(Check, ConstantInt::getTrue(Ctx));
1626 ChkBuilder.Insert(TheCheck, "stride.not.one");
1627 FirstInst = getFirstInst(FirstInst, TheCheck, Loc);
1629 return std::make_pair(FirstInst, TheCheck);
1632 std::pair<Instruction *, Instruction *>
1633 InnerLoopVectorizer::addRuntimeCheck(Instruction *Loc) {
1634 LoopVectorizationLegality::RuntimePointerCheck *PtrRtCheck =
1635 Legal->getRuntimePointerCheck();
1637 Instruction *tnullptr = 0;
1638 if (!PtrRtCheck->Need)
1639 return std::pair<Instruction *, Instruction *>(tnullptr, tnullptr);
1641 unsigned NumPointers = PtrRtCheck->Pointers.size();
1642 SmallVector<TrackingVH<Value> , 2> Starts;
1643 SmallVector<TrackingVH<Value> , 2> Ends;
1645 LLVMContext &Ctx = Loc->getContext();
1646 SCEVExpander Exp(*SE, "induction");
1647 Instruction *FirstInst = 0;
1649 for (unsigned i = 0; i < NumPointers; ++i) {
1650 Value *Ptr = PtrRtCheck->Pointers[i];
1651 const SCEV *Sc = SE->getSCEV(Ptr);
1653 if (SE->isLoopInvariant(Sc, OrigLoop)) {
1654 DEBUG(dbgs() << "LV: Adding RT check for a loop invariant ptr:" <<
1656 Starts.push_back(Ptr);
1657 Ends.push_back(Ptr);
1659 DEBUG(dbgs() << "LV: Adding RT check for range:" << *Ptr << '\n');
1660 unsigned AS = Ptr->getType()->getPointerAddressSpace();
1662 // Use this type for pointer arithmetic.
1663 Type *PtrArithTy = Type::getInt8PtrTy(Ctx, AS);
1665 Value *Start = Exp.expandCodeFor(PtrRtCheck->Starts[i], PtrArithTy, Loc);
1666 Value *End = Exp.expandCodeFor(PtrRtCheck->Ends[i], PtrArithTy, Loc);
1667 Starts.push_back(Start);
1668 Ends.push_back(End);
1672 IRBuilder<> ChkBuilder(Loc);
1673 // Our instructions might fold to a constant.
1674 Value *MemoryRuntimeCheck = 0;
1675 for (unsigned i = 0; i < NumPointers; ++i) {
1676 for (unsigned j = i+1; j < NumPointers; ++j) {
1677 // No need to check if two readonly pointers intersect.
1678 if (!PtrRtCheck->IsWritePtr[i] && !PtrRtCheck->IsWritePtr[j])
1681 // Only need to check pointers between two different dependency sets.
1682 if (PtrRtCheck->DependencySetId[i] == PtrRtCheck->DependencySetId[j])
1685 unsigned AS0 = Starts[i]->getType()->getPointerAddressSpace();
1686 unsigned AS1 = Starts[j]->getType()->getPointerAddressSpace();
1688 assert((AS0 == Ends[j]->getType()->getPointerAddressSpace()) &&
1689 (AS1 == Ends[i]->getType()->getPointerAddressSpace()) &&
1690 "Trying to bounds check pointers with different address spaces");
1692 Type *PtrArithTy0 = Type::getInt8PtrTy(Ctx, AS0);
1693 Type *PtrArithTy1 = Type::getInt8PtrTy(Ctx, AS1);
1695 Value *Start0 = ChkBuilder.CreateBitCast(Starts[i], PtrArithTy0, "bc");
1696 Value *Start1 = ChkBuilder.CreateBitCast(Starts[j], PtrArithTy1, "bc");
1697 Value *End0 = ChkBuilder.CreateBitCast(Ends[i], PtrArithTy1, "bc");
1698 Value *End1 = ChkBuilder.CreateBitCast(Ends[j], PtrArithTy0, "bc");
1700 Value *Cmp0 = ChkBuilder.CreateICmpULE(Start0, End1, "bound0");
1701 FirstInst = getFirstInst(FirstInst, Cmp0, Loc);
1702 Value *Cmp1 = ChkBuilder.CreateICmpULE(Start1, End0, "bound1");
1703 FirstInst = getFirstInst(FirstInst, Cmp1, Loc);
1704 Value *IsConflict = ChkBuilder.CreateAnd(Cmp0, Cmp1, "found.conflict");
1705 FirstInst = getFirstInst(FirstInst, IsConflict, Loc);
1706 if (MemoryRuntimeCheck) {
1707 IsConflict = ChkBuilder.CreateOr(MemoryRuntimeCheck, IsConflict,
1709 FirstInst = getFirstInst(FirstInst, IsConflict, Loc);
1711 MemoryRuntimeCheck = IsConflict;
1715 // We have to do this trickery because the IRBuilder might fold the check to a
1716 // constant expression in which case there is no Instruction anchored in a
1718 Instruction *Check = BinaryOperator::CreateAnd(MemoryRuntimeCheck,
1719 ConstantInt::getTrue(Ctx));
1720 ChkBuilder.Insert(Check, "memcheck.conflict");
1721 FirstInst = getFirstInst(FirstInst, Check, Loc);
1722 return std::make_pair(FirstInst, Check);
1725 void InnerLoopVectorizer::createEmptyLoop() {
1727 In this function we generate a new loop. The new loop will contain
1728 the vectorized instructions while the old loop will continue to run the
1731 [ ] <-- vector loop bypass (may consist of multiple blocks).
1734 | [ ] <-- vector pre header.
1738 | [ ]_| <-- vector loop.
1741 >[ ] <--- middle-block.
1744 | [ ] <--- new preheader.
1748 | [ ]_| <-- old scalar loop to handle remainder.
1751 >[ ] <-- exit block.
1755 BasicBlock *OldBasicBlock = OrigLoop->getHeader();
1756 BasicBlock *BypassBlock = OrigLoop->getLoopPreheader();
1757 BasicBlock *ExitBlock = OrigLoop->getExitBlock();
1758 assert(ExitBlock && "Must have an exit block");
1760 // Some loops have a single integer induction variable, while other loops
1761 // don't. One example is c++ iterators that often have multiple pointer
1762 // induction variables. In the code below we also support a case where we
1763 // don't have a single induction variable.
1764 OldInduction = Legal->getInduction();
1765 Type *IdxTy = Legal->getWidestInductionType();
1767 // Find the loop boundaries.
1768 const SCEV *ExitCount = SE->getBackedgeTakenCount(OrigLoop);
1769 assert(ExitCount != SE->getCouldNotCompute() && "Invalid loop count");
1771 // The exit count might have the type of i64 while the phi is i32. This can
1772 // happen if we have an induction variable that is sign extended before the
1773 // compare. The only way that we get a backedge taken count is that the
1774 // induction variable was signed and as such will not overflow. In such a case
1775 // truncation is legal.
1776 if (ExitCount->getType()->getPrimitiveSizeInBits() >
1777 IdxTy->getPrimitiveSizeInBits())
1778 ExitCount = SE->getTruncateOrNoop(ExitCount, IdxTy);
1780 ExitCount = SE->getNoopOrZeroExtend(ExitCount, IdxTy);
1781 // Get the total trip count from the count by adding 1.
1782 ExitCount = SE->getAddExpr(ExitCount,
1783 SE->getConstant(ExitCount->getType(), 1));
1785 // Expand the trip count and place the new instructions in the preheader.
1786 // Notice that the pre-header does not change, only the loop body.
1787 SCEVExpander Exp(*SE, "induction");
1789 // Count holds the overall loop count (N).
1790 Value *Count = Exp.expandCodeFor(ExitCount, ExitCount->getType(),
1791 BypassBlock->getTerminator());
1793 // The loop index does not have to start at Zero. Find the original start
1794 // value from the induction PHI node. If we don't have an induction variable
1795 // then we know that it starts at zero.
1796 Builder.SetInsertPoint(BypassBlock->getTerminator());
1797 Value *StartIdx = ExtendedIdx = OldInduction ?
1798 Builder.CreateZExt(OldInduction->getIncomingValueForBlock(BypassBlock),
1800 ConstantInt::get(IdxTy, 0);
1802 assert(BypassBlock && "Invalid loop structure");
1803 LoopBypassBlocks.push_back(BypassBlock);
1805 // Split the single block loop into the two loop structure described above.
1806 BasicBlock *VectorPH =
1807 BypassBlock->splitBasicBlock(BypassBlock->getTerminator(), "vector.ph");
1808 BasicBlock *VecBody =
1809 VectorPH->splitBasicBlock(VectorPH->getTerminator(), "vector.body");
1810 BasicBlock *MiddleBlock =
1811 VecBody->splitBasicBlock(VecBody->getTerminator(), "middle.block");
1812 BasicBlock *ScalarPH =
1813 MiddleBlock->splitBasicBlock(MiddleBlock->getTerminator(), "scalar.ph");
1815 // Create and register the new vector loop.
1816 Loop* Lp = new Loop();
1817 Loop *ParentLoop = OrigLoop->getParentLoop();
1819 // Insert the new loop into the loop nest and register the new basic blocks
1820 // before calling any utilities such as SCEV that require valid LoopInfo.
1822 ParentLoop->addChildLoop(Lp);
1823 ParentLoop->addBasicBlockToLoop(ScalarPH, LI->getBase());
1824 ParentLoop->addBasicBlockToLoop(VectorPH, LI->getBase());
1825 ParentLoop->addBasicBlockToLoop(MiddleBlock, LI->getBase());
1827 LI->addTopLevelLoop(Lp);
1829 Lp->addBasicBlockToLoop(VecBody, LI->getBase());
1831 // Use this IR builder to create the loop instructions (Phi, Br, Cmp)
1833 Builder.SetInsertPoint(VecBody->getFirstNonPHI());
1835 // Generate the induction variable.
1836 setDebugLocFromInst(Builder, getDebugLocFromInstOrOperands(OldInduction));
1837 Induction = Builder.CreatePHI(IdxTy, 2, "index");
1838 // The loop step is equal to the vectorization factor (num of SIMD elements)
1839 // times the unroll factor (num of SIMD instructions).
1840 Constant *Step = ConstantInt::get(IdxTy, VF * UF);
1842 // This is the IR builder that we use to add all of the logic for bypassing
1843 // the new vector loop.
1844 IRBuilder<> BypassBuilder(BypassBlock->getTerminator());
1845 setDebugLocFromInst(BypassBuilder,
1846 getDebugLocFromInstOrOperands(OldInduction));
1848 // We may need to extend the index in case there is a type mismatch.
1849 // We know that the count starts at zero and does not overflow.
1850 if (Count->getType() != IdxTy) {
1851 // The exit count can be of pointer type. Convert it to the correct
1853 if (ExitCount->getType()->isPointerTy())
1854 Count = BypassBuilder.CreatePointerCast(Count, IdxTy, "ptrcnt.to.int");
1856 Count = BypassBuilder.CreateZExtOrTrunc(Count, IdxTy, "cnt.cast");
1859 // Add the start index to the loop count to get the new end index.
1860 Value *IdxEnd = BypassBuilder.CreateAdd(Count, StartIdx, "end.idx");
1862 // Now we need to generate the expression for N - (N % VF), which is
1863 // the part that the vectorized body will execute.
1864 Value *R = BypassBuilder.CreateURem(Count, Step, "n.mod.vf");
1865 Value *CountRoundDown = BypassBuilder.CreateSub(Count, R, "n.vec");
1866 Value *IdxEndRoundDown = BypassBuilder.CreateAdd(CountRoundDown, StartIdx,
1867 "end.idx.rnd.down");
1869 // Now, compare the new count to zero. If it is zero skip the vector loop and
1870 // jump to the scalar loop.
1871 Value *Cmp = BypassBuilder.CreateICmpEQ(IdxEndRoundDown, StartIdx,
1874 BasicBlock *LastBypassBlock = BypassBlock;
1876 // Generate the code to check that the strides we assumed to be one are really
1877 // one. We want the new basic block to start at the first instruction in a
1878 // sequence of instructions that form a check.
1879 Instruction *StrideCheck;
1880 Instruction *FirstCheckInst;
1881 tie(FirstCheckInst, StrideCheck) =
1882 addStrideCheck(BypassBlock->getTerminator());
1884 // Create a new block containing the stride check.
1885 BasicBlock *CheckBlock =
1886 BypassBlock->splitBasicBlock(FirstCheckInst, "vector.stridecheck");
1888 ParentLoop->addBasicBlockToLoop(CheckBlock, LI->getBase());
1889 LoopBypassBlocks.push_back(CheckBlock);
1891 // Replace the branch into the memory check block with a conditional branch
1892 // for the "few elements case".
1893 Instruction *OldTerm = BypassBlock->getTerminator();
1894 BranchInst::Create(MiddleBlock, CheckBlock, Cmp, OldTerm);
1895 OldTerm->eraseFromParent();
1898 LastBypassBlock = CheckBlock;
1901 // Generate the code that checks in runtime if arrays overlap. We put the
1902 // checks into a separate block to make the more common case of few elements
1904 Instruction *MemRuntimeCheck;
1905 tie(FirstCheckInst, MemRuntimeCheck) =
1906 addRuntimeCheck(LastBypassBlock->getTerminator());
1907 if (MemRuntimeCheck) {
1908 // Create a new block containing the memory check.
1909 BasicBlock *CheckBlock =
1910 LastBypassBlock->splitBasicBlock(MemRuntimeCheck, "vector.memcheck");
1912 ParentLoop->addBasicBlockToLoop(CheckBlock, LI->getBase());
1913 LoopBypassBlocks.push_back(CheckBlock);
1915 // Replace the branch into the memory check block with a conditional branch
1916 // for the "few elements case".
1917 Instruction *OldTerm = LastBypassBlock->getTerminator();
1918 BranchInst::Create(MiddleBlock, CheckBlock, Cmp, OldTerm);
1919 OldTerm->eraseFromParent();
1921 Cmp = MemRuntimeCheck;
1922 LastBypassBlock = CheckBlock;
1925 LastBypassBlock->getTerminator()->eraseFromParent();
1926 BranchInst::Create(MiddleBlock, VectorPH, Cmp,
1929 // We are going to resume the execution of the scalar loop.
1930 // Go over all of the induction variables that we found and fix the
1931 // PHIs that are left in the scalar version of the loop.
1932 // The starting values of PHI nodes depend on the counter of the last
1933 // iteration in the vectorized loop.
1934 // If we come from a bypass edge then we need to start from the original
1937 // This variable saves the new starting index for the scalar loop.
1938 PHINode *ResumeIndex = 0;
1939 LoopVectorizationLegality::InductionList::iterator I, E;
1940 LoopVectorizationLegality::InductionList *List = Legal->getInductionVars();
1941 // Set builder to point to last bypass block.
1942 BypassBuilder.SetInsertPoint(LoopBypassBlocks.back()->getTerminator());
1943 for (I = List->begin(), E = List->end(); I != E; ++I) {
1944 PHINode *OrigPhi = I->first;
1945 LoopVectorizationLegality::InductionInfo II = I->second;
1947 Type *ResumeValTy = (OrigPhi == OldInduction) ? IdxTy : OrigPhi->getType();
1948 PHINode *ResumeVal = PHINode::Create(ResumeValTy, 2, "resume.val",
1949 MiddleBlock->getTerminator());
1950 // We might have extended the type of the induction variable but we need a
1951 // truncated version for the scalar loop.
1952 PHINode *TruncResumeVal = (OrigPhi == OldInduction) ?
1953 PHINode::Create(OrigPhi->getType(), 2, "trunc.resume.val",
1954 MiddleBlock->getTerminator()) : 0;
1956 Value *EndValue = 0;
1958 case LoopVectorizationLegality::IK_NoInduction:
1959 llvm_unreachable("Unknown induction");
1960 case LoopVectorizationLegality::IK_IntInduction: {
1961 // Handle the integer induction counter.
1962 assert(OrigPhi->getType()->isIntegerTy() && "Invalid type");
1964 // We have the canonical induction variable.
1965 if (OrigPhi == OldInduction) {
1966 // Create a truncated version of the resume value for the scalar loop,
1967 // we might have promoted the type to a larger width.
1969 BypassBuilder.CreateTrunc(IdxEndRoundDown, OrigPhi->getType());
1970 // The new PHI merges the original incoming value, in case of a bypass,
1971 // or the value at the end of the vectorized loop.
1972 for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I)
1973 TruncResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]);
1974 TruncResumeVal->addIncoming(EndValue, VecBody);
1976 // We know what the end value is.
1977 EndValue = IdxEndRoundDown;
1978 // We also know which PHI node holds it.
1979 ResumeIndex = ResumeVal;
1983 // Not the canonical induction variable - add the vector loop count to the
1985 Value *CRD = BypassBuilder.CreateSExtOrTrunc(CountRoundDown,
1986 II.StartValue->getType(),
1988 EndValue = BypassBuilder.CreateAdd(CRD, II.StartValue , "ind.end");
1991 case LoopVectorizationLegality::IK_ReverseIntInduction: {
1992 // Convert the CountRoundDown variable to the PHI size.
1993 Value *CRD = BypassBuilder.CreateSExtOrTrunc(CountRoundDown,
1994 II.StartValue->getType(),
1996 // Handle reverse integer induction counter.
1997 EndValue = BypassBuilder.CreateSub(II.StartValue, CRD, "rev.ind.end");
2000 case LoopVectorizationLegality::IK_PtrInduction: {
2001 // For pointer induction variables, calculate the offset using
2003 EndValue = BypassBuilder.CreateGEP(II.StartValue, CountRoundDown,
2007 case LoopVectorizationLegality::IK_ReversePtrInduction: {
2008 // The value at the end of the loop for the reverse pointer is calculated
2009 // by creating a GEP with a negative index starting from the start value.
2010 Value *Zero = ConstantInt::get(CountRoundDown->getType(), 0);
2011 Value *NegIdx = BypassBuilder.CreateSub(Zero, CountRoundDown,
2013 EndValue = BypassBuilder.CreateGEP(II.StartValue, NegIdx,
2019 // The new PHI merges the original incoming value, in case of a bypass,
2020 // or the value at the end of the vectorized loop.
2021 for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I) {
2022 if (OrigPhi == OldInduction)
2023 ResumeVal->addIncoming(StartIdx, LoopBypassBlocks[I]);
2025 ResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]);
2027 ResumeVal->addIncoming(EndValue, VecBody);
2029 // Fix the scalar body counter (PHI node).
2030 unsigned BlockIdx = OrigPhi->getBasicBlockIndex(ScalarPH);
2031 // The old inductions phi node in the scalar body needs the truncated value.
2032 if (OrigPhi == OldInduction)
2033 OrigPhi->setIncomingValue(BlockIdx, TruncResumeVal);
2035 OrigPhi->setIncomingValue(BlockIdx, ResumeVal);
2038 // If we are generating a new induction variable then we also need to
2039 // generate the code that calculates the exit value. This value is not
2040 // simply the end of the counter because we may skip the vectorized body
2041 // in case of a runtime check.
2043 assert(!ResumeIndex && "Unexpected resume value found");
2044 ResumeIndex = PHINode::Create(IdxTy, 2, "new.indc.resume.val",
2045 MiddleBlock->getTerminator());
2046 for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I)
2047 ResumeIndex->addIncoming(StartIdx, LoopBypassBlocks[I]);
2048 ResumeIndex->addIncoming(IdxEndRoundDown, VecBody);
2051 // Make sure that we found the index where scalar loop needs to continue.
2052 assert(ResumeIndex && ResumeIndex->getType()->isIntegerTy() &&
2053 "Invalid resume Index");
2055 // Add a check in the middle block to see if we have completed
2056 // all of the iterations in the first vector loop.
2057 // If (N - N%VF) == N, then we *don't* need to run the remainder.
2058 Value *CmpN = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ, IdxEnd,
2059 ResumeIndex, "cmp.n",
2060 MiddleBlock->getTerminator());
2062 BranchInst::Create(ExitBlock, ScalarPH, CmpN, MiddleBlock->getTerminator());
2063 // Remove the old terminator.
2064 MiddleBlock->getTerminator()->eraseFromParent();
2066 // Create i+1 and fill the PHINode.
2067 Value *NextIdx = Builder.CreateAdd(Induction, Step, "index.next");
2068 Induction->addIncoming(StartIdx, VectorPH);
2069 Induction->addIncoming(NextIdx, VecBody);
2070 // Create the compare.
2071 Value *ICmp = Builder.CreateICmpEQ(NextIdx, IdxEndRoundDown);
2072 Builder.CreateCondBr(ICmp, MiddleBlock, VecBody);
2074 // Now we have two terminators. Remove the old one from the block.
2075 VecBody->getTerminator()->eraseFromParent();
2077 // Get ready to start creating new instructions into the vectorized body.
2078 Builder.SetInsertPoint(VecBody->getFirstInsertionPt());
2081 LoopVectorPreHeader = VectorPH;
2082 LoopScalarPreHeader = ScalarPH;
2083 LoopMiddleBlock = MiddleBlock;
2084 LoopExitBlock = ExitBlock;
2085 LoopVectorBody = VecBody;
2086 LoopScalarBody = OldBasicBlock;
2088 LoopVectorizeHints Hints(Lp, true);
2089 Hints.setAlreadyVectorized(Lp);
2092 /// This function returns the identity element (or neutral element) for
2093 /// the operation K.
2095 LoopVectorizationLegality::getReductionIdentity(ReductionKind K, Type *Tp) {
2100 // Adding, Xoring, Oring zero to a number does not change it.
2101 return ConstantInt::get(Tp, 0);
2102 case RK_IntegerMult:
2103 // Multiplying a number by 1 does not change it.
2104 return ConstantInt::get(Tp, 1);
2106 // AND-ing a number with an all-1 value does not change it.
2107 return ConstantInt::get(Tp, -1, true);
2109 // Multiplying a number by 1 does not change it.
2110 return ConstantFP::get(Tp, 1.0L);
2112 // Adding zero to a number does not change it.
2113 return ConstantFP::get(Tp, 0.0L);
2115 llvm_unreachable("Unknown reduction kind");
2119 static Intrinsic::ID checkUnaryFloatSignature(const CallInst &I,
2120 Intrinsic::ID ValidIntrinsicID) {
2121 if (I.getNumArgOperands() != 1 ||
2122 !I.getArgOperand(0)->getType()->isFloatingPointTy() ||
2123 I.getType() != I.getArgOperand(0)->getType() ||
2124 !I.onlyReadsMemory())
2125 return Intrinsic::not_intrinsic;
2127 return ValidIntrinsicID;
2130 static Intrinsic::ID checkBinaryFloatSignature(const CallInst &I,
2131 Intrinsic::ID ValidIntrinsicID) {
2132 if (I.getNumArgOperands() != 2 ||
2133 !I.getArgOperand(0)->getType()->isFloatingPointTy() ||
2134 !I.getArgOperand(1)->getType()->isFloatingPointTy() ||
2135 I.getType() != I.getArgOperand(0)->getType() ||
2136 I.getType() != I.getArgOperand(1)->getType() ||
2137 !I.onlyReadsMemory())
2138 return Intrinsic::not_intrinsic;
2140 return ValidIntrinsicID;
2144 static Intrinsic::ID
2145 getIntrinsicIDForCall(CallInst *CI, const TargetLibraryInfo *TLI) {
2146 // If we have an intrinsic call, check if it is trivially vectorizable.
2147 if (IntrinsicInst *II = dyn_cast<IntrinsicInst>(CI)) {
2148 switch (II->getIntrinsicID()) {
2149 case Intrinsic::sqrt:
2150 case Intrinsic::sin:
2151 case Intrinsic::cos:
2152 case Intrinsic::exp:
2153 case Intrinsic::exp2:
2154 case Intrinsic::log:
2155 case Intrinsic::log10:
2156 case Intrinsic::log2:
2157 case Intrinsic::fabs:
2158 case Intrinsic::copysign:
2159 case Intrinsic::floor:
2160 case Intrinsic::ceil:
2161 case Intrinsic::trunc:
2162 case Intrinsic::rint:
2163 case Intrinsic::nearbyint:
2164 case Intrinsic::round:
2165 case Intrinsic::pow:
2166 case Intrinsic::fma:
2167 case Intrinsic::fmuladd:
2168 case Intrinsic::lifetime_start:
2169 case Intrinsic::lifetime_end:
2170 return II->getIntrinsicID();
2172 return Intrinsic::not_intrinsic;
2177 return Intrinsic::not_intrinsic;
2180 Function *F = CI->getCalledFunction();
2181 // We're going to make assumptions on the semantics of the functions, check
2182 // that the target knows that it's available in this environment and it does
2183 // not have local linkage.
2184 if (!F || F->hasLocalLinkage() || !TLI->getLibFunc(F->getName(), Func))
2185 return Intrinsic::not_intrinsic;
2187 // Otherwise check if we have a call to a function that can be turned into a
2188 // vector intrinsic.
2195 return checkUnaryFloatSignature(*CI, Intrinsic::sin);
2199 return checkUnaryFloatSignature(*CI, Intrinsic::cos);
2203 return checkUnaryFloatSignature(*CI, Intrinsic::exp);
2205 case LibFunc::exp2f:
2206 case LibFunc::exp2l:
2207 return checkUnaryFloatSignature(*CI, Intrinsic::exp2);
2211 return checkUnaryFloatSignature(*CI, Intrinsic::log);
2212 case LibFunc::log10:
2213 case LibFunc::log10f:
2214 case LibFunc::log10l:
2215 return checkUnaryFloatSignature(*CI, Intrinsic::log10);
2217 case LibFunc::log2f:
2218 case LibFunc::log2l:
2219 return checkUnaryFloatSignature(*CI, Intrinsic::log2);
2221 case LibFunc::fabsf:
2222 case LibFunc::fabsl:
2223 return checkUnaryFloatSignature(*CI, Intrinsic::fabs);
2224 case LibFunc::copysign:
2225 case LibFunc::copysignf:
2226 case LibFunc::copysignl:
2227 return checkBinaryFloatSignature(*CI, Intrinsic::copysign);
2228 case LibFunc::floor:
2229 case LibFunc::floorf:
2230 case LibFunc::floorl:
2231 return checkUnaryFloatSignature(*CI, Intrinsic::floor);
2233 case LibFunc::ceilf:
2234 case LibFunc::ceill:
2235 return checkUnaryFloatSignature(*CI, Intrinsic::ceil);
2236 case LibFunc::trunc:
2237 case LibFunc::truncf:
2238 case LibFunc::truncl:
2239 return checkUnaryFloatSignature(*CI, Intrinsic::trunc);
2241 case LibFunc::rintf:
2242 case LibFunc::rintl:
2243 return checkUnaryFloatSignature(*CI, Intrinsic::rint);
2244 case LibFunc::nearbyint:
2245 case LibFunc::nearbyintf:
2246 case LibFunc::nearbyintl:
2247 return checkUnaryFloatSignature(*CI, Intrinsic::nearbyint);
2248 case LibFunc::round:
2249 case LibFunc::roundf:
2250 case LibFunc::roundl:
2251 return checkUnaryFloatSignature(*CI, Intrinsic::round);
2255 return checkBinaryFloatSignature(*CI, Intrinsic::pow);
2258 return Intrinsic::not_intrinsic;
2261 /// This function translates the reduction kind to an LLVM binary operator.
2263 getReductionBinOp(LoopVectorizationLegality::ReductionKind Kind) {
2265 case LoopVectorizationLegality::RK_IntegerAdd:
2266 return Instruction::Add;
2267 case LoopVectorizationLegality::RK_IntegerMult:
2268 return Instruction::Mul;
2269 case LoopVectorizationLegality::RK_IntegerOr:
2270 return Instruction::Or;
2271 case LoopVectorizationLegality::RK_IntegerAnd:
2272 return Instruction::And;
2273 case LoopVectorizationLegality::RK_IntegerXor:
2274 return Instruction::Xor;
2275 case LoopVectorizationLegality::RK_FloatMult:
2276 return Instruction::FMul;
2277 case LoopVectorizationLegality::RK_FloatAdd:
2278 return Instruction::FAdd;
2279 case LoopVectorizationLegality::RK_IntegerMinMax:
2280 return Instruction::ICmp;
2281 case LoopVectorizationLegality::RK_FloatMinMax:
2282 return Instruction::FCmp;
2284 llvm_unreachable("Unknown reduction operation");
2288 Value *createMinMaxOp(IRBuilder<> &Builder,
2289 LoopVectorizationLegality::MinMaxReductionKind RK,
2292 CmpInst::Predicate P = CmpInst::ICMP_NE;
2295 llvm_unreachable("Unknown min/max reduction kind");
2296 case LoopVectorizationLegality::MRK_UIntMin:
2297 P = CmpInst::ICMP_ULT;
2299 case LoopVectorizationLegality::MRK_UIntMax:
2300 P = CmpInst::ICMP_UGT;
2302 case LoopVectorizationLegality::MRK_SIntMin:
2303 P = CmpInst::ICMP_SLT;
2305 case LoopVectorizationLegality::MRK_SIntMax:
2306 P = CmpInst::ICMP_SGT;
2308 case LoopVectorizationLegality::MRK_FloatMin:
2309 P = CmpInst::FCMP_OLT;
2311 case LoopVectorizationLegality::MRK_FloatMax:
2312 P = CmpInst::FCMP_OGT;
2317 if (RK == LoopVectorizationLegality::MRK_FloatMin ||
2318 RK == LoopVectorizationLegality::MRK_FloatMax)
2319 Cmp = Builder.CreateFCmp(P, Left, Right, "rdx.minmax.cmp");
2321 Cmp = Builder.CreateICmp(P, Left, Right, "rdx.minmax.cmp");
2323 Value *Select = Builder.CreateSelect(Cmp, Left, Right, "rdx.minmax.select");
2328 struct CSEDenseMapInfo {
2329 static bool canHandle(Instruction *I) {
2330 return isa<InsertElementInst>(I) || isa<ExtractElementInst>(I) ||
2331 isa<ShuffleVectorInst>(I) || isa<GetElementPtrInst>(I);
2333 static inline Instruction *getEmptyKey() {
2334 return DenseMapInfo<Instruction *>::getEmptyKey();
2336 static inline Instruction *getTombstoneKey() {
2337 return DenseMapInfo<Instruction *>::getTombstoneKey();
2339 static unsigned getHashValue(Instruction *I) {
2340 assert(canHandle(I) && "Unknown instruction!");
2341 return hash_combine(I->getOpcode(), hash_combine_range(I->value_op_begin(),
2342 I->value_op_end()));
2344 static bool isEqual(Instruction *LHS, Instruction *RHS) {
2345 if (LHS == getEmptyKey() || RHS == getEmptyKey() ||
2346 LHS == getTombstoneKey() || RHS == getTombstoneKey())
2348 return LHS->isIdenticalTo(RHS);
2353 ///\brief Perform cse of induction variable instructions.
2354 static void cse(BasicBlock *BB) {
2355 // Perform simple cse.
2356 SmallDenseMap<Instruction *, Instruction *, 4, CSEDenseMapInfo> CSEMap;
2357 for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E;) {
2358 Instruction *In = I++;
2360 if (!CSEDenseMapInfo::canHandle(In))
2363 // Check if we can replace this instruction with any of the
2364 // visited instructions.
2365 if (Instruction *V = CSEMap.lookup(In)) {
2366 In->replaceAllUsesWith(V);
2367 In->eraseFromParent();
2375 void InnerLoopVectorizer::vectorizeLoop() {
2376 //===------------------------------------------------===//
2378 // Notice: any optimization or new instruction that go
2379 // into the code below should be also be implemented in
2382 //===------------------------------------------------===//
2383 Constant *Zero = Builder.getInt32(0);
2385 // In order to support reduction variables we need to be able to vectorize
2386 // Phi nodes. Phi nodes have cycles, so we need to vectorize them in two
2387 // stages. First, we create a new vector PHI node with no incoming edges.
2388 // We use this value when we vectorize all of the instructions that use the
2389 // PHI. Next, after all of the instructions in the block are complete we
2390 // add the new incoming edges to the PHI. At this point all of the
2391 // instructions in the basic block are vectorized, so we can use them to
2392 // construct the PHI.
2393 PhiVector RdxPHIsToFix;
2395 // Scan the loop in a topological order to ensure that defs are vectorized
2397 LoopBlocksDFS DFS(OrigLoop);
2400 // Vectorize all of the blocks in the original loop.
2401 for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(),
2402 be = DFS.endRPO(); bb != be; ++bb)
2403 vectorizeBlockInLoop(*bb, &RdxPHIsToFix);
2405 // At this point every instruction in the original loop is widened to
2406 // a vector form. We are almost done. Now, we need to fix the PHI nodes
2407 // that we vectorized. The PHI nodes are currently empty because we did
2408 // not want to introduce cycles. Notice that the remaining PHI nodes
2409 // that we need to fix are reduction variables.
2411 // Create the 'reduced' values for each of the induction vars.
2412 // The reduced values are the vector values that we scalarize and combine
2413 // after the loop is finished.
2414 for (PhiVector::iterator it = RdxPHIsToFix.begin(), e = RdxPHIsToFix.end();
2416 PHINode *RdxPhi = *it;
2417 assert(RdxPhi && "Unable to recover vectorized PHI");
2419 // Find the reduction variable descriptor.
2420 assert(Legal->getReductionVars()->count(RdxPhi) &&
2421 "Unable to find the reduction variable");
2422 LoopVectorizationLegality::ReductionDescriptor RdxDesc =
2423 (*Legal->getReductionVars())[RdxPhi];
2425 setDebugLocFromInst(Builder, RdxDesc.StartValue);
2427 // We need to generate a reduction vector from the incoming scalar.
2428 // To do so, we need to generate the 'identity' vector and override
2429 // one of the elements with the incoming scalar reduction. We need
2430 // to do it in the vector-loop preheader.
2431 Builder.SetInsertPoint(LoopBypassBlocks.front()->getTerminator());
2433 // This is the vector-clone of the value that leaves the loop.
2434 VectorParts &VectorExit = getVectorValue(RdxDesc.LoopExitInstr);
2435 Type *VecTy = VectorExit[0]->getType();
2437 // Find the reduction identity variable. Zero for addition, or, xor,
2438 // one for multiplication, -1 for And.
2441 if (RdxDesc.Kind == LoopVectorizationLegality::RK_IntegerMinMax ||
2442 RdxDesc.Kind == LoopVectorizationLegality::RK_FloatMinMax) {
2443 // MinMax reduction have the start value as their identify.
2445 VectorStart = Identity = RdxDesc.StartValue;
2447 VectorStart = Identity = Builder.CreateVectorSplat(VF,
2452 // Handle other reduction kinds:
2454 LoopVectorizationLegality::getReductionIdentity(RdxDesc.Kind,
2455 VecTy->getScalarType());
2458 // This vector is the Identity vector where the first element is the
2459 // incoming scalar reduction.
2460 VectorStart = RdxDesc.StartValue;
2462 Identity = ConstantVector::getSplat(VF, Iden);
2464 // This vector is the Identity vector where the first element is the
2465 // incoming scalar reduction.
2466 VectorStart = Builder.CreateInsertElement(Identity,
2467 RdxDesc.StartValue, Zero);
2471 // Fix the vector-loop phi.
2472 // We created the induction variable so we know that the
2473 // preheader is the first entry.
2474 BasicBlock *VecPreheader = Induction->getIncomingBlock(0);
2476 // Reductions do not have to start at zero. They can start with
2477 // any loop invariant values.
2478 VectorParts &VecRdxPhi = WidenMap.get(RdxPhi);
2479 BasicBlock *Latch = OrigLoop->getLoopLatch();
2480 Value *LoopVal = RdxPhi->getIncomingValueForBlock(Latch);
2481 VectorParts &Val = getVectorValue(LoopVal);
2482 for (unsigned part = 0; part < UF; ++part) {
2483 // Make sure to add the reduction stat value only to the
2484 // first unroll part.
2485 Value *StartVal = (part == 0) ? VectorStart : Identity;
2486 cast<PHINode>(VecRdxPhi[part])->addIncoming(StartVal, VecPreheader);
2487 cast<PHINode>(VecRdxPhi[part])->addIncoming(Val[part], LoopVectorBody);
2490 // Before each round, move the insertion point right between
2491 // the PHIs and the values we are going to write.
2492 // This allows us to write both PHINodes and the extractelement
2494 Builder.SetInsertPoint(LoopMiddleBlock->getFirstInsertionPt());
2496 VectorParts RdxParts;
2497 setDebugLocFromInst(Builder, RdxDesc.LoopExitInstr);
2498 for (unsigned part = 0; part < UF; ++part) {
2499 // This PHINode contains the vectorized reduction variable, or
2500 // the initial value vector, if we bypass the vector loop.
2501 VectorParts &RdxExitVal = getVectorValue(RdxDesc.LoopExitInstr);
2502 PHINode *NewPhi = Builder.CreatePHI(VecTy, 2, "rdx.vec.exit.phi");
2503 Value *StartVal = (part == 0) ? VectorStart : Identity;
2504 for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I)
2505 NewPhi->addIncoming(StartVal, LoopBypassBlocks[I]);
2506 NewPhi->addIncoming(RdxExitVal[part], LoopVectorBody);
2507 RdxParts.push_back(NewPhi);
2510 // Reduce all of the unrolled parts into a single vector.
2511 Value *ReducedPartRdx = RdxParts[0];
2512 unsigned Op = getReductionBinOp(RdxDesc.Kind);
2513 setDebugLocFromInst(Builder, ReducedPartRdx);
2514 for (unsigned part = 1; part < UF; ++part) {
2515 if (Op != Instruction::ICmp && Op != Instruction::FCmp)
2516 ReducedPartRdx = Builder.CreateBinOp((Instruction::BinaryOps)Op,
2517 RdxParts[part], ReducedPartRdx,
2520 ReducedPartRdx = createMinMaxOp(Builder, RdxDesc.MinMaxKind,
2521 ReducedPartRdx, RdxParts[part]);
2525 // VF is a power of 2 so we can emit the reduction using log2(VF) shuffles
2526 // and vector ops, reducing the set of values being computed by half each
2528 assert(isPowerOf2_32(VF) &&
2529 "Reduction emission only supported for pow2 vectors!");
2530 Value *TmpVec = ReducedPartRdx;
2531 SmallVector<Constant*, 32> ShuffleMask(VF, 0);
2532 for (unsigned i = VF; i != 1; i >>= 1) {
2533 // Move the upper half of the vector to the lower half.
2534 for (unsigned j = 0; j != i/2; ++j)
2535 ShuffleMask[j] = Builder.getInt32(i/2 + j);
2537 // Fill the rest of the mask with undef.
2538 std::fill(&ShuffleMask[i/2], ShuffleMask.end(),
2539 UndefValue::get(Builder.getInt32Ty()));
2542 Builder.CreateShuffleVector(TmpVec,
2543 UndefValue::get(TmpVec->getType()),
2544 ConstantVector::get(ShuffleMask),
2547 if (Op != Instruction::ICmp && Op != Instruction::FCmp)
2548 TmpVec = Builder.CreateBinOp((Instruction::BinaryOps)Op, TmpVec, Shuf,
2551 TmpVec = createMinMaxOp(Builder, RdxDesc.MinMaxKind, TmpVec, Shuf);
2554 // The result is in the first element of the vector.
2555 ReducedPartRdx = Builder.CreateExtractElement(TmpVec,
2556 Builder.getInt32(0));
2559 // Now, we need to fix the users of the reduction variable
2560 // inside and outside of the scalar remainder loop.
2561 // We know that the loop is in LCSSA form. We need to update the
2562 // PHI nodes in the exit blocks.
2563 for (BasicBlock::iterator LEI = LoopExitBlock->begin(),
2564 LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) {
2565 PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI);
2566 if (!LCSSAPhi) break;
2568 // All PHINodes need to have a single entry edge, or two if
2569 // we already fixed them.
2570 assert(LCSSAPhi->getNumIncomingValues() < 3 && "Invalid LCSSA PHI");
2572 // We found our reduction value exit-PHI. Update it with the
2573 // incoming bypass edge.
2574 if (LCSSAPhi->getIncomingValue(0) == RdxDesc.LoopExitInstr) {
2575 // Add an edge coming from the bypass.
2576 LCSSAPhi->addIncoming(ReducedPartRdx, LoopMiddleBlock);
2579 }// end of the LCSSA phi scan.
2581 // Fix the scalar loop reduction variable with the incoming reduction sum
2582 // from the vector body and from the backedge value.
2583 int IncomingEdgeBlockIdx =
2584 (RdxPhi)->getBasicBlockIndex(OrigLoop->getLoopLatch());
2585 assert(IncomingEdgeBlockIdx >= 0 && "Invalid block index");
2586 // Pick the other block.
2587 int SelfEdgeBlockIdx = (IncomingEdgeBlockIdx ? 0 : 1);
2588 (RdxPhi)->setIncomingValue(SelfEdgeBlockIdx, ReducedPartRdx);
2589 (RdxPhi)->setIncomingValue(IncomingEdgeBlockIdx, RdxDesc.LoopExitInstr);
2590 }// end of for each redux variable.
2594 // Remove redundant induction instructions.
2595 cse(LoopVectorBody);
2598 void InnerLoopVectorizer::fixLCSSAPHIs() {
2599 for (BasicBlock::iterator LEI = LoopExitBlock->begin(),
2600 LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) {
2601 PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI);
2602 if (!LCSSAPhi) break;
2603 if (LCSSAPhi->getNumIncomingValues() == 1)
2604 LCSSAPhi->addIncoming(UndefValue::get(LCSSAPhi->getType()),
2609 InnerLoopVectorizer::VectorParts
2610 InnerLoopVectorizer::createEdgeMask(BasicBlock *Src, BasicBlock *Dst) {
2611 assert(std::find(pred_begin(Dst), pred_end(Dst), Src) != pred_end(Dst) &&
2614 // Look for cached value.
2615 std::pair<BasicBlock*, BasicBlock*> Edge(Src, Dst);
2616 EdgeMaskCache::iterator ECEntryIt = MaskCache.find(Edge);
2617 if (ECEntryIt != MaskCache.end())
2618 return ECEntryIt->second;
2620 VectorParts SrcMask = createBlockInMask(Src);
2622 // The terminator has to be a branch inst!
2623 BranchInst *BI = dyn_cast<BranchInst>(Src->getTerminator());
2624 assert(BI && "Unexpected terminator found");
2626 if (BI->isConditional()) {
2627 VectorParts EdgeMask = getVectorValue(BI->getCondition());
2629 if (BI->getSuccessor(0) != Dst)
2630 for (unsigned part = 0; part < UF; ++part)
2631 EdgeMask[part] = Builder.CreateNot(EdgeMask[part]);
2633 for (unsigned part = 0; part < UF; ++part)
2634 EdgeMask[part] = Builder.CreateAnd(EdgeMask[part], SrcMask[part]);
2636 MaskCache[Edge] = EdgeMask;
2640 MaskCache[Edge] = SrcMask;
2644 InnerLoopVectorizer::VectorParts
2645 InnerLoopVectorizer::createBlockInMask(BasicBlock *BB) {
2646 assert(OrigLoop->contains(BB) && "Block is not a part of a loop");
2648 // Loop incoming mask is all-one.
2649 if (OrigLoop->getHeader() == BB) {
2650 Value *C = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 1);
2651 return getVectorValue(C);
2654 // This is the block mask. We OR all incoming edges, and with zero.
2655 Value *Zero = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 0);
2656 VectorParts BlockMask = getVectorValue(Zero);
2659 for (pred_iterator it = pred_begin(BB), e = pred_end(BB); it != e; ++it) {
2660 VectorParts EM = createEdgeMask(*it, BB);
2661 for (unsigned part = 0; part < UF; ++part)
2662 BlockMask[part] = Builder.CreateOr(BlockMask[part], EM[part]);
2668 void InnerLoopVectorizer::widenPHIInstruction(Instruction *PN,
2669 InnerLoopVectorizer::VectorParts &Entry,
2670 unsigned UF, unsigned VF, PhiVector *PV) {
2671 PHINode* P = cast<PHINode>(PN);
2672 // Handle reduction variables:
2673 if (Legal->getReductionVars()->count(P)) {
2674 for (unsigned part = 0; part < UF; ++part) {
2675 // This is phase one of vectorizing PHIs.
2676 Type *VecTy = (VF == 1) ? PN->getType() :
2677 VectorType::get(PN->getType(), VF);
2678 Entry[part] = PHINode::Create(VecTy, 2, "vec.phi",
2679 LoopVectorBody-> getFirstInsertionPt());
2685 setDebugLocFromInst(Builder, P);
2686 // Check for PHI nodes that are lowered to vector selects.
2687 if (P->getParent() != OrigLoop->getHeader()) {
2688 // We know that all PHIs in non-header blocks are converted into
2689 // selects, so we don't have to worry about the insertion order and we
2690 // can just use the builder.
2691 // At this point we generate the predication tree. There may be
2692 // duplications since this is a simple recursive scan, but future
2693 // optimizations will clean it up.
2695 unsigned NumIncoming = P->getNumIncomingValues();
2697 // Generate a sequence of selects of the form:
2698 // SELECT(Mask3, In3,
2699 // SELECT(Mask2, In2,
2701 for (unsigned In = 0; In < NumIncoming; In++) {
2702 VectorParts Cond = createEdgeMask(P->getIncomingBlock(In),
2704 VectorParts &In0 = getVectorValue(P->getIncomingValue(In));
2706 for (unsigned part = 0; part < UF; ++part) {
2707 // We might have single edge PHIs (blocks) - use an identity
2708 // 'select' for the first PHI operand.
2710 Entry[part] = Builder.CreateSelect(Cond[part], In0[part],
2713 // Select between the current value and the previous incoming edge
2714 // based on the incoming mask.
2715 Entry[part] = Builder.CreateSelect(Cond[part], In0[part],
2716 Entry[part], "predphi");
2722 // This PHINode must be an induction variable.
2723 // Make sure that we know about it.
2724 assert(Legal->getInductionVars()->count(P) &&
2725 "Not an induction variable");
2727 LoopVectorizationLegality::InductionInfo II =
2728 Legal->getInductionVars()->lookup(P);
2731 case LoopVectorizationLegality::IK_NoInduction:
2732 llvm_unreachable("Unknown induction");
2733 case LoopVectorizationLegality::IK_IntInduction: {
2734 assert(P->getType() == II.StartValue->getType() && "Types must match");
2735 Type *PhiTy = P->getType();
2737 if (P == OldInduction) {
2738 // Handle the canonical induction variable. We might have had to
2740 Broadcasted = Builder.CreateTrunc(Induction, PhiTy);
2742 // Handle other induction variables that are now based on the
2744 Value *NormalizedIdx = Builder.CreateSub(Induction, ExtendedIdx,
2746 NormalizedIdx = Builder.CreateSExtOrTrunc(NormalizedIdx, PhiTy);
2747 Broadcasted = Builder.CreateAdd(II.StartValue, NormalizedIdx,
2750 Broadcasted = getBroadcastInstrs(Broadcasted);
2751 // After broadcasting the induction variable we need to make the vector
2752 // consecutive by adding 0, 1, 2, etc.
2753 for (unsigned part = 0; part < UF; ++part)
2754 Entry[part] = getConsecutiveVector(Broadcasted, VF * part, false);
2757 case LoopVectorizationLegality::IK_ReverseIntInduction:
2758 case LoopVectorizationLegality::IK_PtrInduction:
2759 case LoopVectorizationLegality::IK_ReversePtrInduction:
2760 // Handle reverse integer and pointer inductions.
2761 Value *StartIdx = ExtendedIdx;
2762 // This is the normalized GEP that starts counting at zero.
2763 Value *NormalizedIdx = Builder.CreateSub(Induction, StartIdx,
2766 // Handle the reverse integer induction variable case.
2767 if (LoopVectorizationLegality::IK_ReverseIntInduction == II.IK) {
2768 IntegerType *DstTy = cast<IntegerType>(II.StartValue->getType());
2769 Value *CNI = Builder.CreateSExtOrTrunc(NormalizedIdx, DstTy,
2771 Value *ReverseInd = Builder.CreateSub(II.StartValue, CNI,
2774 // This is a new value so do not hoist it out.
2775 Value *Broadcasted = getBroadcastInstrs(ReverseInd);
2776 // After broadcasting the induction variable we need to make the
2777 // vector consecutive by adding ... -3, -2, -1, 0.
2778 for (unsigned part = 0; part < UF; ++part)
2779 Entry[part] = getConsecutiveVector(Broadcasted, -(int)VF * part,
2784 // Handle the pointer induction variable case.
2785 assert(P->getType()->isPointerTy() && "Unexpected type.");
2787 // Is this a reverse induction ptr or a consecutive induction ptr.
2788 bool Reverse = (LoopVectorizationLegality::IK_ReversePtrInduction ==
2791 // This is the vector of results. Notice that we don't generate
2792 // vector geps because scalar geps result in better code.
2793 for (unsigned part = 0; part < UF; ++part) {
2795 int EltIndex = (part) * (Reverse ? -1 : 1);
2796 Constant *Idx = ConstantInt::get(Induction->getType(), EltIndex);
2799 GlobalIdx = Builder.CreateSub(Idx, NormalizedIdx, "gep.ridx");
2801 GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx, "gep.idx");
2803 Value *SclrGep = Builder.CreateGEP(II.StartValue, GlobalIdx,
2805 Entry[part] = SclrGep;
2809 Value *VecVal = UndefValue::get(VectorType::get(P->getType(), VF));
2810 for (unsigned int i = 0; i < VF; ++i) {
2811 int EltIndex = (i + part * VF) * (Reverse ? -1 : 1);
2812 Constant *Idx = ConstantInt::get(Induction->getType(), EltIndex);
2815 GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx, "gep.idx");
2817 GlobalIdx = Builder.CreateSub(Idx, NormalizedIdx, "gep.ridx");
2819 Value *SclrGep = Builder.CreateGEP(II.StartValue, GlobalIdx,
2821 VecVal = Builder.CreateInsertElement(VecVal, SclrGep,
2822 Builder.getInt32(i),
2825 Entry[part] = VecVal;
2831 void InnerLoopVectorizer::vectorizeBlockInLoop(BasicBlock *BB, PhiVector *PV) {
2832 // For each instruction in the old loop.
2833 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
2834 VectorParts &Entry = WidenMap.get(it);
2835 switch (it->getOpcode()) {
2836 case Instruction::Br:
2837 // Nothing to do for PHIs and BR, since we already took care of the
2838 // loop control flow instructions.
2840 case Instruction::PHI:{
2841 // Vectorize PHINodes.
2842 widenPHIInstruction(it, Entry, UF, VF, PV);
2846 case Instruction::Add:
2847 case Instruction::FAdd:
2848 case Instruction::Sub:
2849 case Instruction::FSub:
2850 case Instruction::Mul:
2851 case Instruction::FMul:
2852 case Instruction::UDiv:
2853 case Instruction::SDiv:
2854 case Instruction::FDiv:
2855 case Instruction::URem:
2856 case Instruction::SRem:
2857 case Instruction::FRem:
2858 case Instruction::Shl:
2859 case Instruction::LShr:
2860 case Instruction::AShr:
2861 case Instruction::And:
2862 case Instruction::Or:
2863 case Instruction::Xor: {
2864 // Just widen binops.
2865 BinaryOperator *BinOp = dyn_cast<BinaryOperator>(it);
2866 setDebugLocFromInst(Builder, BinOp);
2867 VectorParts &A = getVectorValue(it->getOperand(0));
2868 VectorParts &B = getVectorValue(it->getOperand(1));
2870 // Use this vector value for all users of the original instruction.
2871 for (unsigned Part = 0; Part < UF; ++Part) {
2872 Value *V = Builder.CreateBinOp(BinOp->getOpcode(), A[Part], B[Part]);
2874 // Update the NSW, NUW and Exact flags. Notice: V can be an Undef.
2875 BinaryOperator *VecOp = dyn_cast<BinaryOperator>(V);
2876 if (VecOp && isa<OverflowingBinaryOperator>(BinOp)) {
2877 VecOp->setHasNoSignedWrap(BinOp->hasNoSignedWrap());
2878 VecOp->setHasNoUnsignedWrap(BinOp->hasNoUnsignedWrap());
2880 if (VecOp && isa<PossiblyExactOperator>(VecOp))
2881 VecOp->setIsExact(BinOp->isExact());
2887 case Instruction::Select: {
2889 // If the selector is loop invariant we can create a select
2890 // instruction with a scalar condition. Otherwise, use vector-select.
2891 bool InvariantCond = SE->isLoopInvariant(SE->getSCEV(it->getOperand(0)),
2893 setDebugLocFromInst(Builder, it);
2895 // The condition can be loop invariant but still defined inside the
2896 // loop. This means that we can't just use the original 'cond' value.
2897 // We have to take the 'vectorized' value and pick the first lane.
2898 // Instcombine will make this a no-op.
2899 VectorParts &Cond = getVectorValue(it->getOperand(0));
2900 VectorParts &Op0 = getVectorValue(it->getOperand(1));
2901 VectorParts &Op1 = getVectorValue(it->getOperand(2));
2903 Value *ScalarCond = (VF == 1) ? Cond[0] :
2904 Builder.CreateExtractElement(Cond[0], Builder.getInt32(0));
2906 for (unsigned Part = 0; Part < UF; ++Part) {
2907 Entry[Part] = Builder.CreateSelect(
2908 InvariantCond ? ScalarCond : Cond[Part],
2915 case Instruction::ICmp:
2916 case Instruction::FCmp: {
2917 // Widen compares. Generate vector compares.
2918 bool FCmp = (it->getOpcode() == Instruction::FCmp);
2919 CmpInst *Cmp = dyn_cast<CmpInst>(it);
2920 setDebugLocFromInst(Builder, it);
2921 VectorParts &A = getVectorValue(it->getOperand(0));
2922 VectorParts &B = getVectorValue(it->getOperand(1));
2923 for (unsigned Part = 0; Part < UF; ++Part) {
2926 C = Builder.CreateFCmp(Cmp->getPredicate(), A[Part], B[Part]);
2928 C = Builder.CreateICmp(Cmp->getPredicate(), A[Part], B[Part]);
2934 case Instruction::Store:
2935 case Instruction::Load:
2936 vectorizeMemoryInstruction(it);
2938 case Instruction::ZExt:
2939 case Instruction::SExt:
2940 case Instruction::FPToUI:
2941 case Instruction::FPToSI:
2942 case Instruction::FPExt:
2943 case Instruction::PtrToInt:
2944 case Instruction::IntToPtr:
2945 case Instruction::SIToFP:
2946 case Instruction::UIToFP:
2947 case Instruction::Trunc:
2948 case Instruction::FPTrunc:
2949 case Instruction::BitCast: {
2950 CastInst *CI = dyn_cast<CastInst>(it);
2951 setDebugLocFromInst(Builder, it);
2952 /// Optimize the special case where the source is the induction
2953 /// variable. Notice that we can only optimize the 'trunc' case
2954 /// because: a. FP conversions lose precision, b. sext/zext may wrap,
2955 /// c. other casts depend on pointer size.
2956 if (CI->getOperand(0) == OldInduction &&
2957 it->getOpcode() == Instruction::Trunc) {
2958 Value *ScalarCast = Builder.CreateCast(CI->getOpcode(), Induction,
2960 Value *Broadcasted = getBroadcastInstrs(ScalarCast);
2961 for (unsigned Part = 0; Part < UF; ++Part)
2962 Entry[Part] = getConsecutiveVector(Broadcasted, VF * Part, false);
2965 /// Vectorize casts.
2966 Type *DestTy = (VF == 1) ? CI->getType() :
2967 VectorType::get(CI->getType(), VF);
2969 VectorParts &A = getVectorValue(it->getOperand(0));
2970 for (unsigned Part = 0; Part < UF; ++Part)
2971 Entry[Part] = Builder.CreateCast(CI->getOpcode(), A[Part], DestTy);
2975 case Instruction::Call: {
2976 // Ignore dbg intrinsics.
2977 if (isa<DbgInfoIntrinsic>(it))
2979 setDebugLocFromInst(Builder, it);
2981 Module *M = BB->getParent()->getParent();
2982 CallInst *CI = cast<CallInst>(it);
2983 Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI);
2984 assert(ID && "Not an intrinsic call!");
2986 case Intrinsic::lifetime_end:
2987 case Intrinsic::lifetime_start:
2988 scalarizeInstruction(it);
2991 for (unsigned Part = 0; Part < UF; ++Part) {
2992 SmallVector<Value *, 4> Args;
2993 for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i) {
2994 VectorParts &Arg = getVectorValue(CI->getArgOperand(i));
2995 Args.push_back(Arg[Part]);
2997 Type *Tys[] = {CI->getType()};
2999 Tys[0] = VectorType::get(CI->getType()->getScalarType(), VF);
3001 Function *F = Intrinsic::getDeclaration(M, ID, Tys);
3002 Entry[Part] = Builder.CreateCall(F, Args);
3010 // All other instructions are unsupported. Scalarize them.
3011 scalarizeInstruction(it);
3014 }// end of for_each instr.
3017 void InnerLoopVectorizer::updateAnalysis() {
3018 // Forget the original basic block.
3019 SE->forgetLoop(OrigLoop);
3021 // Update the dominator tree information.
3022 assert(DT->properlyDominates(LoopBypassBlocks.front(), LoopExitBlock) &&
3023 "Entry does not dominate exit.");
3025 for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I)
3026 DT->addNewBlock(LoopBypassBlocks[I], LoopBypassBlocks[I-1]);
3027 DT->addNewBlock(LoopVectorPreHeader, LoopBypassBlocks.back());
3028 DT->addNewBlock(LoopVectorBody, LoopVectorPreHeader);
3029 DT->addNewBlock(LoopMiddleBlock, LoopBypassBlocks.front());
3030 DT->addNewBlock(LoopScalarPreHeader, LoopMiddleBlock);
3031 DT->changeImmediateDominator(LoopScalarBody, LoopScalarPreHeader);
3032 DT->changeImmediateDominator(LoopExitBlock, LoopMiddleBlock);
3034 DEBUG(DT->verifyDomTree());
3037 /// \brief Check whether it is safe to if-convert this phi node.
3039 /// Phi nodes with constant expressions that can trap are not safe to if
3041 static bool canIfConvertPHINodes(BasicBlock *BB) {
3042 for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I) {
3043 PHINode *Phi = dyn_cast<PHINode>(I);
3046 for (unsigned p = 0, e = Phi->getNumIncomingValues(); p != e; ++p)
3047 if (Constant *C = dyn_cast<Constant>(Phi->getIncomingValue(p)))
3054 bool LoopVectorizationLegality::canVectorizeWithIfConvert() {
3055 if (!EnableIfConversion)
3058 assert(TheLoop->getNumBlocks() > 1 && "Single block loops are vectorizable");
3060 // A list of pointers that we can safely read and write to.
3061 SmallPtrSet<Value *, 8> SafePointes;
3063 // Collect safe addresses.
3064 for (Loop::block_iterator BI = TheLoop->block_begin(),
3065 BE = TheLoop->block_end(); BI != BE; ++BI) {
3066 BasicBlock *BB = *BI;
3068 if (blockNeedsPredication(BB))
3071 for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I) {
3072 if (LoadInst *LI = dyn_cast<LoadInst>(I))
3073 SafePointes.insert(LI->getPointerOperand());
3074 else if (StoreInst *SI = dyn_cast<StoreInst>(I))
3075 SafePointes.insert(SI->getPointerOperand());
3079 // Collect the blocks that need predication.
3080 BasicBlock *Header = TheLoop->getHeader();
3081 for (Loop::block_iterator BI = TheLoop->block_begin(),
3082 BE = TheLoop->block_end(); BI != BE; ++BI) {
3083 BasicBlock *BB = *BI;
3085 // We don't support switch statements inside loops.
3086 if (!isa<BranchInst>(BB->getTerminator()))
3089 // We must be able to predicate all blocks that need to be predicated.
3090 if (blockNeedsPredication(BB)) {
3091 if (!blockCanBePredicated(BB, SafePointes))
3093 } else if (BB != Header && !canIfConvertPHINodes(BB))
3098 // We can if-convert this loop.
3102 bool LoopVectorizationLegality::canVectorize() {
3103 // We must have a loop in canonical form. Loops with indirectbr in them cannot
3104 // be canonicalized.
3105 if (!TheLoop->getLoopPreheader())
3108 // We can only vectorize innermost loops.
3109 if (TheLoop->getSubLoopsVector().size())
3112 // We must have a single backedge.
3113 if (TheLoop->getNumBackEdges() != 1)
3116 // We must have a single exiting block.
3117 if (!TheLoop->getExitingBlock())
3120 // We need to have a loop header.
3121 DEBUG(dbgs() << "LV: Found a loop: " <<
3122 TheLoop->getHeader()->getName() << '\n');
3124 // Check if we can if-convert non-single-bb loops.
3125 unsigned NumBlocks = TheLoop->getNumBlocks();
3126 if (NumBlocks != 1 && !canVectorizeWithIfConvert()) {
3127 DEBUG(dbgs() << "LV: Can't if-convert the loop.\n");
3131 // ScalarEvolution needs to be able to find the exit count.
3132 const SCEV *ExitCount = SE->getBackedgeTakenCount(TheLoop);
3133 if (ExitCount == SE->getCouldNotCompute()) {
3134 DEBUG(dbgs() << "LV: SCEV could not compute the loop exit count.\n");
3138 // Do not loop-vectorize loops with a tiny trip count.
3139 BasicBlock *Latch = TheLoop->getLoopLatch();
3140 unsigned TC = SE->getSmallConstantTripCount(TheLoop, Latch);
3141 if (TC > 0u && TC < TinyTripCountVectorThreshold) {
3142 DEBUG(dbgs() << "LV: Found a loop with a very small trip count. " <<
3143 "This loop is not worth vectorizing.\n");
3147 // Check if we can vectorize the instructions and CFG in this loop.
3148 if (!canVectorizeInstrs()) {
3149 DEBUG(dbgs() << "LV: Can't vectorize the instructions or CFG\n");
3153 // Go over each instruction and look at memory deps.
3154 if (!canVectorizeMemory()) {
3155 DEBUG(dbgs() << "LV: Can't vectorize due to memory conflicts\n");
3159 // Collect all of the variables that remain uniform after vectorization.
3160 collectLoopUniforms();
3162 DEBUG(dbgs() << "LV: We can vectorize this loop" <<
3163 (PtrRtCheck.Need ? " (with a runtime bound check)" : "")
3166 // Okay! We can vectorize. At this point we don't have any other mem analysis
3167 // which may limit our maximum vectorization factor, so just return true with
3172 static Type *convertPointerToIntegerType(DataLayout &DL, Type *Ty) {
3173 if (Ty->isPointerTy())
3174 return DL.getIntPtrType(Ty);
3176 // It is possible that char's or short's overflow when we ask for the loop's
3177 // trip count, work around this by changing the type size.
3178 if (Ty->getScalarSizeInBits() < 32)
3179 return Type::getInt32Ty(Ty->getContext());
3184 static Type* getWiderType(DataLayout &DL, Type *Ty0, Type *Ty1) {
3185 Ty0 = convertPointerToIntegerType(DL, Ty0);
3186 Ty1 = convertPointerToIntegerType(DL, Ty1);
3187 if (Ty0->getScalarSizeInBits() > Ty1->getScalarSizeInBits())
3192 /// \brief Check that the instruction has outside loop users and is not an
3193 /// identified reduction variable.
3194 static bool hasOutsideLoopUser(const Loop *TheLoop, Instruction *Inst,
3195 SmallPtrSet<Value *, 4> &Reductions) {
3196 // Reduction instructions are allowed to have exit users. All other
3197 // instructions must not have external users.
3198 if (!Reductions.count(Inst))
3199 //Check that all of the users of the loop are inside the BB.
3200 for (Value::use_iterator I = Inst->use_begin(), E = Inst->use_end();
3202 Instruction *U = cast<Instruction>(*I);
3203 // This user may be a reduction exit value.
3204 if (!TheLoop->contains(U)) {
3205 DEBUG(dbgs() << "LV: Found an outside user for : " << *U << '\n');
3212 bool LoopVectorizationLegality::canVectorizeInstrs() {
3213 BasicBlock *PreHeader = TheLoop->getLoopPreheader();
3214 BasicBlock *Header = TheLoop->getHeader();
3216 // Look for the attribute signaling the absence of NaNs.
3217 Function &F = *Header->getParent();
3218 if (F.hasFnAttribute("no-nans-fp-math"))
3219 HasFunNoNaNAttr = F.getAttributes().getAttribute(
3220 AttributeSet::FunctionIndex,
3221 "no-nans-fp-math").getValueAsString() == "true";
3223 // For each block in the loop.
3224 for (Loop::block_iterator bb = TheLoop->block_begin(),
3225 be = TheLoop->block_end(); bb != be; ++bb) {
3227 // Scan the instructions in the block and look for hazards.
3228 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e;
3231 if (PHINode *Phi = dyn_cast<PHINode>(it)) {
3232 Type *PhiTy = Phi->getType();
3233 // Check that this PHI type is allowed.
3234 if (!PhiTy->isIntegerTy() &&
3235 !PhiTy->isFloatingPointTy() &&
3236 !PhiTy->isPointerTy()) {
3237 DEBUG(dbgs() << "LV: Found an non-int non-pointer PHI.\n");
3241 // If this PHINode is not in the header block, then we know that we
3242 // can convert it to select during if-conversion. No need to check if
3243 // the PHIs in this block are induction or reduction variables.
3244 if (*bb != Header) {
3245 // Check that this instruction has no outside users or is an
3246 // identified reduction value with an outside user.
3247 if(!hasOutsideLoopUser(TheLoop, it, AllowedExit))
3252 // We only allow if-converted PHIs with more than two incoming values.
3253 if (Phi->getNumIncomingValues() != 2) {
3254 DEBUG(dbgs() << "LV: Found an invalid PHI.\n");
3258 // This is the value coming from the preheader.
3259 Value *StartValue = Phi->getIncomingValueForBlock(PreHeader);
3260 // Check if this is an induction variable.
3261 InductionKind IK = isInductionVariable(Phi);
3263 if (IK_NoInduction != IK) {
3264 // Get the widest type.
3266 WidestIndTy = convertPointerToIntegerType(*DL, PhiTy);
3268 WidestIndTy = getWiderType(*DL, PhiTy, WidestIndTy);
3270 // Int inductions are special because we only allow one IV.
3271 if (IK == IK_IntInduction) {
3272 // Use the phi node with the widest type as induction. Use the last
3273 // one if there are multiple (no good reason for doing this other
3274 // than it is expedient).
3275 if (!Induction || PhiTy == WidestIndTy)
3279 DEBUG(dbgs() << "LV: Found an induction variable.\n");
3280 Inductions[Phi] = InductionInfo(StartValue, IK);
3282 // Until we explicitly handle the case of an induction variable with
3283 // an outside loop user we have to give up vectorizing this loop.
3284 if (hasOutsideLoopUser(TheLoop, it, AllowedExit))
3290 if (AddReductionVar(Phi, RK_IntegerAdd)) {
3291 DEBUG(dbgs() << "LV: Found an ADD reduction PHI."<< *Phi <<"\n");
3294 if (AddReductionVar(Phi, RK_IntegerMult)) {
3295 DEBUG(dbgs() << "LV: Found a MUL reduction PHI."<< *Phi <<"\n");
3298 if (AddReductionVar(Phi, RK_IntegerOr)) {
3299 DEBUG(dbgs() << "LV: Found an OR reduction PHI."<< *Phi <<"\n");
3302 if (AddReductionVar(Phi, RK_IntegerAnd)) {
3303 DEBUG(dbgs() << "LV: Found an AND reduction PHI."<< *Phi <<"\n");
3306 if (AddReductionVar(Phi, RK_IntegerXor)) {
3307 DEBUG(dbgs() << "LV: Found a XOR reduction PHI."<< *Phi <<"\n");
3310 if (AddReductionVar(Phi, RK_IntegerMinMax)) {
3311 DEBUG(dbgs() << "LV: Found a MINMAX reduction PHI."<< *Phi <<"\n");
3314 if (AddReductionVar(Phi, RK_FloatMult)) {
3315 DEBUG(dbgs() << "LV: Found an FMult reduction PHI."<< *Phi <<"\n");
3318 if (AddReductionVar(Phi, RK_FloatAdd)) {
3319 DEBUG(dbgs() << "LV: Found an FAdd reduction PHI."<< *Phi <<"\n");
3322 if (AddReductionVar(Phi, RK_FloatMinMax)) {
3323 DEBUG(dbgs() << "LV: Found an float MINMAX reduction PHI."<< *Phi <<
3328 DEBUG(dbgs() << "LV: Found an unidentified PHI."<< *Phi <<"\n");
3330 }// end of PHI handling
3332 // We still don't handle functions. However, we can ignore dbg intrinsic
3333 // calls and we do handle certain intrinsic and libm functions.
3334 CallInst *CI = dyn_cast<CallInst>(it);
3335 if (CI && !getIntrinsicIDForCall(CI, TLI) && !isa<DbgInfoIntrinsic>(CI)) {
3336 DEBUG(dbgs() << "LV: Found a call site.\n");
3340 // Check that the instruction return type is vectorizable.
3341 // Also, we can't vectorize extractelement instructions.
3342 if ((!VectorType::isValidElementType(it->getType()) &&
3343 !it->getType()->isVoidTy()) || isa<ExtractElementInst>(it)) {
3344 DEBUG(dbgs() << "LV: Found unvectorizable type.\n");
3348 // Check that the stored type is vectorizable.
3349 if (StoreInst *ST = dyn_cast<StoreInst>(it)) {
3350 Type *T = ST->getValueOperand()->getType();
3351 if (!VectorType::isValidElementType(T))
3353 if (EnableMemAccessVersioning)
3354 collectStridedAcccess(ST);
3357 if (EnableMemAccessVersioning)
3358 if (LoadInst *LI = dyn_cast<LoadInst>(it))
3359 collectStridedAcccess(LI);
3361 // Reduction instructions are allowed to have exit users.
3362 // All other instructions must not have external users.
3363 if (hasOutsideLoopUser(TheLoop, it, AllowedExit))
3371 DEBUG(dbgs() << "LV: Did not find one integer induction var.\n");
3372 if (Inductions.empty())
3379 ///\brief Remove GEPs whose indices but the last one are loop invariant and
3380 /// return the induction operand of the gep pointer.
3381 static Value *stripGetElementPtr(Value *Ptr, ScalarEvolution *SE,
3382 DataLayout *DL, Loop *Lp) {
3383 GetElementPtrInst *GEP = dyn_cast<GetElementPtrInst>(Ptr);
3387 unsigned InductionOperand = getGEPInductionOperand(DL, GEP);
3389 // Check that all of the gep indices are uniform except for our induction
3391 for (unsigned i = 0, e = GEP->getNumOperands(); i != e; ++i)
3392 if (i != InductionOperand &&
3393 !SE->isLoopInvariant(SE->getSCEV(GEP->getOperand(i)), Lp))
3395 return GEP->getOperand(InductionOperand);
3398 ///\brief Look for a cast use of the passed value.
3399 static Value *getUniqueCastUse(Value *Ptr, Loop *Lp, Type *Ty) {
3400 Value *UniqueCast = 0;
3401 for (Value::use_iterator UI = Ptr->use_begin(), UE = Ptr->use_end(); UI != UE;
3403 CastInst *CI = dyn_cast<CastInst>(*UI);
3404 if (CI && CI->getType() == Ty) {
3414 ///\brief Get the stride of a pointer access in a loop.
3415 /// Looks for symbolic strides "a[i*stride]". Returns the symbolic stride as a
3416 /// pointer to the Value, or null otherwise.
3417 static Value *getStrideFromPointer(Value *Ptr, ScalarEvolution *SE,
3418 DataLayout *DL, Loop *Lp) {
3419 const PointerType *PtrTy = dyn_cast<PointerType>(Ptr->getType());
3420 if (!PtrTy || PtrTy->isAggregateType())
3423 // Try to remove a gep instruction to make the pointer (actually index at this
3424 // point) easier analyzable. If OrigPtr is equal to Ptr we are analzying the
3425 // pointer, otherwise, we are analyzing the index.
3426 Value *OrigPtr = Ptr;
3428 // The size of the pointer access.
3429 int64_t PtrAccessSize = 1;
3431 Ptr = stripGetElementPtr(Ptr, SE, DL, Lp);
3432 const SCEV *V = SE->getSCEV(Ptr);
3436 while (const SCEVCastExpr *C = dyn_cast<SCEVCastExpr>(V))
3437 V = C->getOperand();
3439 const SCEVAddRecExpr *S = dyn_cast<SCEVAddRecExpr>(V);
3443 V = S->getStepRecurrence(*SE);
3447 // Strip off the size of access multiplication if we are still analyzing the
3449 if (OrigPtr == Ptr) {
3450 DL->getTypeAllocSize(PtrTy->getElementType());
3451 if (const SCEVMulExpr *M = dyn_cast<SCEVMulExpr>(V)) {
3452 if (M->getOperand(0)->getSCEVType() != scConstant)
3455 const APInt &APStepVal =
3456 cast<SCEVConstant>(M->getOperand(0))->getValue()->getValue();
3458 // Huge step value - give up.
3459 if (APStepVal.getBitWidth() > 64)
3462 int64_t StepVal = APStepVal.getSExtValue();
3463 if (PtrAccessSize != StepVal)
3465 V = M->getOperand(1);
3470 Type *StripedOffRecurrenceCast = 0;
3471 if (const SCEVCastExpr *C = dyn_cast<SCEVCastExpr>(V)) {
3472 StripedOffRecurrenceCast = C->getType();
3473 V = C->getOperand();
3476 // Look for the loop invariant symbolic value.
3477 const SCEVUnknown *U = dyn_cast<SCEVUnknown>(V);
3481 Value *Stride = U->getValue();
3482 if (!Lp->isLoopInvariant(Stride))
3485 // If we have stripped off the recurrence cast we have to make sure that we
3486 // return the value that is used in this loop so that we can replace it later.
3487 if (StripedOffRecurrenceCast)
3488 Stride = getUniqueCastUse(Stride, Lp, StripedOffRecurrenceCast);
3493 void LoopVectorizationLegality::collectStridedAcccess(Value *MemAccess) {
3495 if (LoadInst *LI = dyn_cast<LoadInst>(MemAccess))
3496 Ptr = LI->getPointerOperand();
3497 else if (StoreInst *SI = dyn_cast<StoreInst>(MemAccess))
3498 Ptr = SI->getPointerOperand();
3502 Value *Stride = getStrideFromPointer(Ptr, SE, DL, TheLoop);
3506 DEBUG(dbgs() << "LV: Found a strided access that we can version");
3507 DEBUG(dbgs() << " Ptr: " << *Ptr << " Stride: " << *Stride << "\n");
3508 Strides[Ptr] = Stride;
3509 StrideSet.insert(Stride);
3512 void LoopVectorizationLegality::collectLoopUniforms() {
3513 // We now know that the loop is vectorizable!
3514 // Collect variables that will remain uniform after vectorization.
3515 std::vector<Value*> Worklist;
3516 BasicBlock *Latch = TheLoop->getLoopLatch();
3518 // Start with the conditional branch and walk up the block.
3519 Worklist.push_back(Latch->getTerminator()->getOperand(0));
3521 while (Worklist.size()) {
3522 Instruction *I = dyn_cast<Instruction>(Worklist.back());
3523 Worklist.pop_back();
3525 // Look at instructions inside this loop.
3526 // Stop when reaching PHI nodes.
3527 // TODO: we need to follow values all over the loop, not only in this block.
3528 if (!I || !TheLoop->contains(I) || isa<PHINode>(I))
3531 // This is a known uniform.
3534 // Insert all operands.
3535 Worklist.insert(Worklist.end(), I->op_begin(), I->op_end());
3540 /// \brief Analyses memory accesses in a loop.
3542 /// Checks whether run time pointer checks are needed and builds sets for data
3543 /// dependence checking.
3544 class AccessAnalysis {
3546 /// \brief Read or write access location.
3547 typedef PointerIntPair<Value *, 1, bool> MemAccessInfo;
3548 typedef SmallPtrSet<MemAccessInfo, 8> MemAccessInfoSet;
3550 /// \brief Set of potential dependent memory accesses.
3551 typedef EquivalenceClasses<MemAccessInfo> DepCandidates;
3553 AccessAnalysis(DataLayout *Dl, DepCandidates &DA) :
3554 DL(Dl), DepCands(DA), AreAllWritesIdentified(true),
3555 AreAllReadsIdentified(true), IsRTCheckNeeded(false) {}
3557 /// \brief Register a load and whether it is only read from.
3558 void addLoad(Value *Ptr, bool IsReadOnly) {
3559 Accesses.insert(MemAccessInfo(Ptr, false));
3561 ReadOnlyPtr.insert(Ptr);
3564 /// \brief Register a store.
3565 void addStore(Value *Ptr) {
3566 Accesses.insert(MemAccessInfo(Ptr, true));
3569 /// \brief Check whether we can check the pointers at runtime for
3570 /// non-intersection.
3571 bool canCheckPtrAtRT(LoopVectorizationLegality::RuntimePointerCheck &RtCheck,
3572 unsigned &NumComparisons, ScalarEvolution *SE,
3573 Loop *TheLoop, ValueToValueMap &Strides,
3574 bool ShouldCheckStride = false);
3576 /// \brief Goes over all memory accesses, checks whether a RT check is needed
3577 /// and builds sets of dependent accesses.
3578 void buildDependenceSets() {
3579 // Process read-write pointers first.
3580 processMemAccesses(false);
3581 // Next, process read pointers.
3582 processMemAccesses(true);
3585 bool isRTCheckNeeded() { return IsRTCheckNeeded; }
3587 bool isDependencyCheckNeeded() { return !CheckDeps.empty(); }
3588 void resetDepChecks() { CheckDeps.clear(); }
3590 MemAccessInfoSet &getDependenciesToCheck() { return CheckDeps; }
3593 typedef SetVector<MemAccessInfo> PtrAccessSet;
3594 typedef DenseMap<Value*, MemAccessInfo> UnderlyingObjToAccessMap;
3596 /// \brief Go over all memory access or only the deferred ones if
3597 /// \p UseDeferred is true and check whether runtime pointer checks are needed
3598 /// and build sets of dependency check candidates.
3599 void processMemAccesses(bool UseDeferred);
3601 /// Set of all accesses.
3602 PtrAccessSet Accesses;
3604 /// Set of access to check after all writes have been processed.
3605 PtrAccessSet DeferredAccesses;
3607 /// Map of pointers to last access encountered.
3608 UnderlyingObjToAccessMap ObjToLastAccess;
3610 /// Set of accesses that need a further dependence check.
3611 MemAccessInfoSet CheckDeps;
3613 /// Set of pointers that are read only.
3614 SmallPtrSet<Value*, 16> ReadOnlyPtr;
3616 /// Set of underlying objects already written to.
3617 SmallPtrSet<Value*, 16> WriteObjects;
3621 /// Sets of potentially dependent accesses - members of one set share an
3622 /// underlying pointer. The set "CheckDeps" identfies which sets really need a
3623 /// dependence check.
3624 DepCandidates &DepCands;
3626 bool AreAllWritesIdentified;
3627 bool AreAllReadsIdentified;
3628 bool IsRTCheckNeeded;
3631 } // end anonymous namespace
3633 /// \brief Check whether a pointer can participate in a runtime bounds check.
3634 static bool hasComputableBounds(ScalarEvolution *SE, ValueToValueMap &Strides,
3636 const SCEV *PtrScev = replaceSymbolicStrideSCEV(SE, Strides, Ptr);
3637 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PtrScev);
3641 return AR->isAffine();
3644 /// \brief Check the stride of the pointer and ensure that it does not wrap in
3645 /// the address space.
3646 static int isStridedPtr(ScalarEvolution *SE, DataLayout *DL, Value *Ptr,
3647 const Loop *Lp, ValueToValueMap &StridesMap);
3649 bool AccessAnalysis::canCheckPtrAtRT(
3650 LoopVectorizationLegality::RuntimePointerCheck &RtCheck,
3651 unsigned &NumComparisons, ScalarEvolution *SE, Loop *TheLoop,
3652 ValueToValueMap &StridesMap, bool ShouldCheckStride) {
3653 // Find pointers with computable bounds. We are going to use this information
3654 // to place a runtime bound check.
3655 unsigned NumReadPtrChecks = 0;
3656 unsigned NumWritePtrChecks = 0;
3657 bool CanDoRT = true;
3659 bool IsDepCheckNeeded = isDependencyCheckNeeded();
3660 // We assign consecutive id to access from different dependence sets.
3661 // Accesses within the same set don't need a runtime check.
3662 unsigned RunningDepId = 1;
3663 DenseMap<Value *, unsigned> DepSetId;
3665 for (PtrAccessSet::iterator AI = Accesses.begin(), AE = Accesses.end();
3667 const MemAccessInfo &Access = *AI;
3668 Value *Ptr = Access.getPointer();
3669 bool IsWrite = Access.getInt();
3671 // Just add write checks if we have both.
3672 if (!IsWrite && Accesses.count(MemAccessInfo(Ptr, true)))
3676 ++NumWritePtrChecks;
3680 if (hasComputableBounds(SE, StridesMap, Ptr) &&
3681 // When we run after a failing dependency check we have to make sure we
3682 // don't have wrapping pointers.
3683 (!ShouldCheckStride ||
3684 isStridedPtr(SE, DL, Ptr, TheLoop, StridesMap) == 1)) {
3685 // The id of the dependence set.
3688 if (IsDepCheckNeeded) {
3689 Value *Leader = DepCands.getLeaderValue(Access).getPointer();
3690 unsigned &LeaderId = DepSetId[Leader];
3692 LeaderId = RunningDepId++;
3695 // Each access has its own dependence set.
3696 DepId = RunningDepId++;
3698 RtCheck.insert(SE, TheLoop, Ptr, IsWrite, DepId, StridesMap);
3700 DEBUG(dbgs() << "LV: Found a runtime check ptr:" << *Ptr << '\n');
3706 if (IsDepCheckNeeded && CanDoRT && RunningDepId == 2)
3707 NumComparisons = 0; // Only one dependence set.
3709 NumComparisons = (NumWritePtrChecks * (NumReadPtrChecks +
3710 NumWritePtrChecks - 1));
3713 // If the pointers that we would use for the bounds comparison have different
3714 // address spaces, assume the values aren't directly comparable, so we can't
3715 // use them for the runtime check. We also have to assume they could
3716 // overlap. In the future there should be metadata for whether address spaces
3718 unsigned NumPointers = RtCheck.Pointers.size();
3719 for (unsigned i = 0; i < NumPointers; ++i) {
3720 for (unsigned j = i + 1; j < NumPointers; ++j) {
3721 // Only need to check pointers between two different dependency sets.
3722 if (RtCheck.DependencySetId[i] == RtCheck.DependencySetId[j])
3725 Value *PtrI = RtCheck.Pointers[i];
3726 Value *PtrJ = RtCheck.Pointers[j];
3728 unsigned ASi = PtrI->getType()->getPointerAddressSpace();
3729 unsigned ASj = PtrJ->getType()->getPointerAddressSpace();
3731 DEBUG(dbgs() << "LV: Runtime check would require comparison between"
3732 " different address spaces\n");
3741 static bool isFunctionScopeIdentifiedObject(Value *Ptr) {
3742 return isNoAliasArgument(Ptr) || isNoAliasCall(Ptr) || isa<AllocaInst>(Ptr);
3745 void AccessAnalysis::processMemAccesses(bool UseDeferred) {
3746 // We process the set twice: first we process read-write pointers, last we
3747 // process read-only pointers. This allows us to skip dependence tests for
3748 // read-only pointers.
3750 PtrAccessSet &S = UseDeferred ? DeferredAccesses : Accesses;
3751 for (PtrAccessSet::iterator AI = S.begin(), AE = S.end(); AI != AE; ++AI) {
3752 const MemAccessInfo &Access = *AI;
3753 Value *Ptr = Access.getPointer();
3754 bool IsWrite = Access.getInt();
3756 DepCands.insert(Access);
3758 // Memorize read-only pointers for later processing and skip them in the
3759 // first round (they need to be checked after we have seen all write
3760 // pointers). Note: we also mark pointer that are not consecutive as
3761 // "read-only" pointers (so that we check "a[b[i]] +="). Hence, we need the
3762 // second check for "!IsWrite".
3763 bool IsReadOnlyPtr = ReadOnlyPtr.count(Ptr) && !IsWrite;
3764 if (!UseDeferred && IsReadOnlyPtr) {
3765 DeferredAccesses.insert(Access);
3769 bool NeedDepCheck = false;
3770 // Check whether there is the possibility of dependency because of
3771 // underlying objects being the same.
3772 typedef SmallVector<Value*, 16> ValueVector;
3773 ValueVector TempObjects;
3774 GetUnderlyingObjects(Ptr, TempObjects, DL);
3775 for (ValueVector::iterator UI = TempObjects.begin(), UE = TempObjects.end();
3777 Value *UnderlyingObj = *UI;
3779 // If this is a write then it needs to be an identified object. If this a
3780 // read and all writes (so far) are identified function scope objects we
3781 // don't need an identified underlying object but only an Argument (the
3782 // next write is going to invalidate this assumption if it is
3784 // This is a micro-optimization for the case where all writes are
3785 // identified and we have one argument pointer.
3786 // Otherwise, we do need a runtime check.
3787 if ((IsWrite && !isFunctionScopeIdentifiedObject(UnderlyingObj)) ||
3788 (!IsWrite && (!AreAllWritesIdentified ||
3789 !isa<Argument>(UnderlyingObj)) &&
3790 !isIdentifiedObject(UnderlyingObj))) {
3791 DEBUG(dbgs() << "LV: Found an unidentified " <<
3792 (IsWrite ? "write" : "read" ) << " ptr: " << *UnderlyingObj <<
3794 IsRTCheckNeeded = (IsRTCheckNeeded ||
3795 !isIdentifiedObject(UnderlyingObj) ||
3796 !AreAllReadsIdentified);
3799 AreAllWritesIdentified = false;
3801 AreAllReadsIdentified = false;
3804 // If this is a write - check other reads and writes for conflicts. If
3805 // this is a read only check other writes for conflicts (but only if there
3806 // is no other write to the ptr - this is an optimization to catch "a[i] =
3807 // a[i] + " without having to do a dependence check).
3808 if ((IsWrite || IsReadOnlyPtr) && WriteObjects.count(UnderlyingObj))
3809 NeedDepCheck = true;
3812 WriteObjects.insert(UnderlyingObj);
3814 // Create sets of pointers connected by shared underlying objects.
3815 UnderlyingObjToAccessMap::iterator Prev =
3816 ObjToLastAccess.find(UnderlyingObj);
3817 if (Prev != ObjToLastAccess.end())
3818 DepCands.unionSets(Access, Prev->second);
3820 ObjToLastAccess[UnderlyingObj] = Access;
3824 CheckDeps.insert(Access);
3829 /// \brief Checks memory dependences among accesses to the same underlying
3830 /// object to determine whether there vectorization is legal or not (and at
3831 /// which vectorization factor).
3833 /// This class works under the assumption that we already checked that memory
3834 /// locations with different underlying pointers are "must-not alias".
3835 /// We use the ScalarEvolution framework to symbolically evalutate access
3836 /// functions pairs. Since we currently don't restructure the loop we can rely
3837 /// on the program order of memory accesses to determine their safety.
3838 /// At the moment we will only deem accesses as safe for:
3839 /// * A negative constant distance assuming program order.
3841 /// Safe: tmp = a[i + 1]; OR a[i + 1] = x;
3842 /// a[i] = tmp; y = a[i];
3844 /// The latter case is safe because later checks guarantuee that there can't
3845 /// be a cycle through a phi node (that is, we check that "x" and "y" is not
3846 /// the same variable: a header phi can only be an induction or a reduction, a
3847 /// reduction can't have a memory sink, an induction can't have a memory
3848 /// source). This is important and must not be violated (or we have to
3849 /// resort to checking for cycles through memory).
3851 /// * A positive constant distance assuming program order that is bigger
3852 /// than the biggest memory access.
3854 /// tmp = a[i] OR b[i] = x
3855 /// a[i+2] = tmp y = b[i+2];
3857 /// Safe distance: 2 x sizeof(a[0]), and 2 x sizeof(b[0]), respectively.
3859 /// * Zero distances and all accesses have the same size.
3861 class MemoryDepChecker {
3863 typedef PointerIntPair<Value *, 1, bool> MemAccessInfo;
3864 typedef SmallPtrSet<MemAccessInfo, 8> MemAccessInfoSet;
3866 MemoryDepChecker(ScalarEvolution *Se, DataLayout *Dl, const Loop *L)
3867 : SE(Se), DL(Dl), InnermostLoop(L), AccessIdx(0),
3868 ShouldRetryWithRuntimeCheck(false) {}
3870 /// \brief Register the location (instructions are given increasing numbers)
3871 /// of a write access.
3872 void addAccess(StoreInst *SI) {
3873 Value *Ptr = SI->getPointerOperand();
3874 Accesses[MemAccessInfo(Ptr, true)].push_back(AccessIdx);
3875 InstMap.push_back(SI);
3879 /// \brief Register the location (instructions are given increasing numbers)
3880 /// of a write access.
3881 void addAccess(LoadInst *LI) {
3882 Value *Ptr = LI->getPointerOperand();
3883 Accesses[MemAccessInfo(Ptr, false)].push_back(AccessIdx);
3884 InstMap.push_back(LI);
3888 /// \brief Check whether the dependencies between the accesses are safe.
3890 /// Only checks sets with elements in \p CheckDeps.
3891 bool areDepsSafe(AccessAnalysis::DepCandidates &AccessSets,
3892 MemAccessInfoSet &CheckDeps, ValueToValueMap &Strides);
3894 /// \brief The maximum number of bytes of a vector register we can vectorize
3895 /// the accesses safely with.
3896 unsigned getMaxSafeDepDistBytes() { return MaxSafeDepDistBytes; }
3898 /// \brief In same cases when the dependency check fails we can still
3899 /// vectorize the loop with a dynamic array access check.
3900 bool shouldRetryWithRuntimeCheck() { return ShouldRetryWithRuntimeCheck; }
3903 ScalarEvolution *SE;
3905 const Loop *InnermostLoop;
3907 /// \brief Maps access locations (ptr, read/write) to program order.
3908 DenseMap<MemAccessInfo, std::vector<unsigned> > Accesses;
3910 /// \brief Memory access instructions in program order.
3911 SmallVector<Instruction *, 16> InstMap;
3913 /// \brief The program order index to be used for the next instruction.
3916 // We can access this many bytes in parallel safely.
3917 unsigned MaxSafeDepDistBytes;
3919 /// \brief If we see a non-constant dependence distance we can still try to
3920 /// vectorize this loop with runtime checks.
3921 bool ShouldRetryWithRuntimeCheck;
3923 /// \brief Check whether there is a plausible dependence between the two
3926 /// Access \p A must happen before \p B in program order. The two indices
3927 /// identify the index into the program order map.
3929 /// This function checks whether there is a plausible dependence (or the
3930 /// absence of such can't be proved) between the two accesses. If there is a
3931 /// plausible dependence but the dependence distance is bigger than one
3932 /// element access it records this distance in \p MaxSafeDepDistBytes (if this
3933 /// distance is smaller than any other distance encountered so far).
3934 /// Otherwise, this function returns true signaling a possible dependence.
3935 bool isDependent(const MemAccessInfo &A, unsigned AIdx,
3936 const MemAccessInfo &B, unsigned BIdx,
3937 ValueToValueMap &Strides);
3939 /// \brief Check whether the data dependence could prevent store-load
3941 bool couldPreventStoreLoadForward(unsigned Distance, unsigned TypeByteSize);
3944 } // end anonymous namespace
3946 static bool isInBoundsGep(Value *Ptr) {
3947 if (GetElementPtrInst *GEP = dyn_cast<GetElementPtrInst>(Ptr))
3948 return GEP->isInBounds();
3952 /// \brief Check whether the access through \p Ptr has a constant stride.
3953 static int isStridedPtr(ScalarEvolution *SE, DataLayout *DL, Value *Ptr,
3954 const Loop *Lp, ValueToValueMap &StridesMap) {
3955 const Type *Ty = Ptr->getType();
3956 assert(Ty->isPointerTy() && "Unexpected non-ptr");
3958 // Make sure that the pointer does not point to aggregate types.
3959 const PointerType *PtrTy = cast<PointerType>(Ty);
3960 if (PtrTy->getElementType()->isAggregateType()) {
3961 DEBUG(dbgs() << "LV: Bad stride - Not a pointer to a scalar type" << *Ptr <<
3966 const SCEV *PtrScev = replaceSymbolicStrideSCEV(SE, StridesMap, Ptr);
3968 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PtrScev);
3970 DEBUG(dbgs() << "LV: Bad stride - Not an AddRecExpr pointer "
3971 << *Ptr << " SCEV: " << *PtrScev << "\n");
3975 // The accesss function must stride over the innermost loop.
3976 if (Lp != AR->getLoop()) {
3977 DEBUG(dbgs() << "LV: Bad stride - Not striding over innermost loop " <<
3978 *Ptr << " SCEV: " << *PtrScev << "\n");
3981 // The address calculation must not wrap. Otherwise, a dependence could be
3983 // An inbounds getelementptr that is a AddRec with a unit stride
3984 // cannot wrap per definition. The unit stride requirement is checked later.
3985 // An getelementptr without an inbounds attribute and unit stride would have
3986 // to access the pointer value "0" which is undefined behavior in address
3987 // space 0, therefore we can also vectorize this case.
3988 bool IsInBoundsGEP = isInBoundsGep(Ptr);
3989 bool IsNoWrapAddRec = AR->getNoWrapFlags(SCEV::NoWrapMask);
3990 bool IsInAddressSpaceZero = PtrTy->getAddressSpace() == 0;
3991 if (!IsNoWrapAddRec && !IsInBoundsGEP && !IsInAddressSpaceZero) {
3992 DEBUG(dbgs() << "LV: Bad stride - Pointer may wrap in the address space "
3993 << *Ptr << " SCEV: " << *PtrScev << "\n");
3997 // Check the step is constant.
3998 const SCEV *Step = AR->getStepRecurrence(*SE);
4000 // Calculate the pointer stride and check if it is consecutive.
4001 const SCEVConstant *C = dyn_cast<SCEVConstant>(Step);
4003 DEBUG(dbgs() << "LV: Bad stride - Not a constant strided " << *Ptr <<
4004 " SCEV: " << *PtrScev << "\n");
4008 int64_t Size = DL->getTypeAllocSize(PtrTy->getElementType());
4009 const APInt &APStepVal = C->getValue()->getValue();
4011 // Huge step value - give up.
4012 if (APStepVal.getBitWidth() > 64)
4015 int64_t StepVal = APStepVal.getSExtValue();
4018 int64_t Stride = StepVal / Size;
4019 int64_t Rem = StepVal % Size;
4023 // If the SCEV could wrap but we have an inbounds gep with a unit stride we
4024 // know we can't "wrap around the address space". In case of address space
4025 // zero we know that this won't happen without triggering undefined behavior.
4026 if (!IsNoWrapAddRec && (IsInBoundsGEP || IsInAddressSpaceZero) &&
4027 Stride != 1 && Stride != -1)
4033 bool MemoryDepChecker::couldPreventStoreLoadForward(unsigned Distance,
4034 unsigned TypeByteSize) {
4035 // If loads occur at a distance that is not a multiple of a feasible vector
4036 // factor store-load forwarding does not take place.
4037 // Positive dependences might cause troubles because vectorizing them might
4038 // prevent store-load forwarding making vectorized code run a lot slower.
4039 // a[i] = a[i-3] ^ a[i-8];
4040 // The stores to a[i:i+1] don't align with the stores to a[i-3:i-2] and
4041 // hence on your typical architecture store-load forwarding does not take
4042 // place. Vectorizing in such cases does not make sense.
4043 // Store-load forwarding distance.
4044 const unsigned NumCyclesForStoreLoadThroughMemory = 8*TypeByteSize;
4045 // Maximum vector factor.
4046 unsigned MaxVFWithoutSLForwardIssues = MaxVectorWidth*TypeByteSize;
4047 if(MaxSafeDepDistBytes < MaxVFWithoutSLForwardIssues)
4048 MaxVFWithoutSLForwardIssues = MaxSafeDepDistBytes;
4050 for (unsigned vf = 2*TypeByteSize; vf <= MaxVFWithoutSLForwardIssues;
4052 if (Distance % vf && Distance / vf < NumCyclesForStoreLoadThroughMemory) {
4053 MaxVFWithoutSLForwardIssues = (vf >>=1);
4058 if (MaxVFWithoutSLForwardIssues< 2*TypeByteSize) {
4059 DEBUG(dbgs() << "LV: Distance " << Distance <<
4060 " that could cause a store-load forwarding conflict\n");
4064 if (MaxVFWithoutSLForwardIssues < MaxSafeDepDistBytes &&
4065 MaxVFWithoutSLForwardIssues != MaxVectorWidth*TypeByteSize)
4066 MaxSafeDepDistBytes = MaxVFWithoutSLForwardIssues;
4070 bool MemoryDepChecker::isDependent(const MemAccessInfo &A, unsigned AIdx,
4071 const MemAccessInfo &B, unsigned BIdx,
4072 ValueToValueMap &Strides) {
4073 assert (AIdx < BIdx && "Must pass arguments in program order");
4075 Value *APtr = A.getPointer();
4076 Value *BPtr = B.getPointer();
4077 bool AIsWrite = A.getInt();
4078 bool BIsWrite = B.getInt();
4080 // Two reads are independent.
4081 if (!AIsWrite && !BIsWrite)
4084 const SCEV *AScev = replaceSymbolicStrideSCEV(SE, Strides, APtr);
4085 const SCEV *BScev = replaceSymbolicStrideSCEV(SE, Strides, BPtr);
4087 int StrideAPtr = isStridedPtr(SE, DL, APtr, InnermostLoop, Strides);
4088 int StrideBPtr = isStridedPtr(SE, DL, BPtr, InnermostLoop, Strides);
4090 const SCEV *Src = AScev;
4091 const SCEV *Sink = BScev;
4093 // If the induction step is negative we have to invert source and sink of the
4095 if (StrideAPtr < 0) {
4098 std::swap(APtr, BPtr);
4099 std::swap(Src, Sink);
4100 std::swap(AIsWrite, BIsWrite);
4101 std::swap(AIdx, BIdx);
4102 std::swap(StrideAPtr, StrideBPtr);
4105 const SCEV *Dist = SE->getMinusSCEV(Sink, Src);
4107 DEBUG(dbgs() << "LV: Src Scev: " << *Src << "Sink Scev: " << *Sink
4108 << "(Induction step: " << StrideAPtr << ")\n");
4109 DEBUG(dbgs() << "LV: Distance for " << *InstMap[AIdx] << " to "
4110 << *InstMap[BIdx] << ": " << *Dist << "\n");
4112 // Need consecutive accesses. We don't want to vectorize
4113 // "A[B[i]] += ..." and similar code or pointer arithmetic that could wrap in
4114 // the address space.
4115 if (!StrideAPtr || !StrideBPtr || StrideAPtr != StrideBPtr){
4116 DEBUG(dbgs() << "Non-consecutive pointer access\n");
4120 const SCEVConstant *C = dyn_cast<SCEVConstant>(Dist);
4122 DEBUG(dbgs() << "LV: Dependence because of non-constant distance\n");
4123 ShouldRetryWithRuntimeCheck = true;
4127 Type *ATy = APtr->getType()->getPointerElementType();
4128 Type *BTy = BPtr->getType()->getPointerElementType();
4129 unsigned TypeByteSize = DL->getTypeAllocSize(ATy);
4131 // Negative distances are not plausible dependencies.
4132 const APInt &Val = C->getValue()->getValue();
4133 if (Val.isNegative()) {
4134 bool IsTrueDataDependence = (AIsWrite && !BIsWrite);
4135 if (IsTrueDataDependence &&
4136 (couldPreventStoreLoadForward(Val.abs().getZExtValue(), TypeByteSize) ||
4140 DEBUG(dbgs() << "LV: Dependence is negative: NoDep\n");
4144 // Write to the same location with the same size.
4145 // Could be improved to assert type sizes are the same (i32 == float, etc).
4149 DEBUG(dbgs() << "LV: Zero dependence difference but different types\n");
4153 assert(Val.isStrictlyPositive() && "Expect a positive value");
4155 // Positive distance bigger than max vectorization factor.
4158 "LV: ReadWrite-Write positive dependency with different types\n");
4162 unsigned Distance = (unsigned) Val.getZExtValue();
4164 // Bail out early if passed-in parameters make vectorization not feasible.
4165 unsigned ForcedFactor = VectorizationFactor ? VectorizationFactor : 1;
4166 unsigned ForcedUnroll = VectorizationUnroll ? VectorizationUnroll : 1;
4168 // The distance must be bigger than the size needed for a vectorized version
4169 // of the operation and the size of the vectorized operation must not be
4170 // bigger than the currrent maximum size.
4171 if (Distance < 2*TypeByteSize ||
4172 2*TypeByteSize > MaxSafeDepDistBytes ||
4173 Distance < TypeByteSize * ForcedUnroll * ForcedFactor) {
4174 DEBUG(dbgs() << "LV: Failure because of Positive distance "
4175 << Val.getSExtValue() << '\n');
4179 MaxSafeDepDistBytes = Distance < MaxSafeDepDistBytes ?
4180 Distance : MaxSafeDepDistBytes;
4182 bool IsTrueDataDependence = (!AIsWrite && BIsWrite);
4183 if (IsTrueDataDependence &&
4184 couldPreventStoreLoadForward(Distance, TypeByteSize))
4187 DEBUG(dbgs() << "LV: Positive distance " << Val.getSExtValue() <<
4188 " with max VF = " << MaxSafeDepDistBytes / TypeByteSize << '\n');
4193 bool MemoryDepChecker::areDepsSafe(AccessAnalysis::DepCandidates &AccessSets,
4194 MemAccessInfoSet &CheckDeps,
4195 ValueToValueMap &Strides) {
4197 MaxSafeDepDistBytes = -1U;
4198 while (!CheckDeps.empty()) {
4199 MemAccessInfo CurAccess = *CheckDeps.begin();
4201 // Get the relevant memory access set.
4202 EquivalenceClasses<MemAccessInfo>::iterator I =
4203 AccessSets.findValue(AccessSets.getLeaderValue(CurAccess));
4205 // Check accesses within this set.
4206 EquivalenceClasses<MemAccessInfo>::member_iterator AI, AE;
4207 AI = AccessSets.member_begin(I), AE = AccessSets.member_end();
4209 // Check every access pair.
4211 CheckDeps.erase(*AI);
4212 EquivalenceClasses<MemAccessInfo>::member_iterator OI = llvm::next(AI);
4214 // Check every accessing instruction pair in program order.
4215 for (std::vector<unsigned>::iterator I1 = Accesses[*AI].begin(),
4216 I1E = Accesses[*AI].end(); I1 != I1E; ++I1)
4217 for (std::vector<unsigned>::iterator I2 = Accesses[*OI].begin(),
4218 I2E = Accesses[*OI].end(); I2 != I2E; ++I2) {
4219 if (*I1 < *I2 && isDependent(*AI, *I1, *OI, *I2, Strides))
4221 if (*I2 < *I1 && isDependent(*OI, *I2, *AI, *I1, Strides))
4232 bool LoopVectorizationLegality::canVectorizeMemory() {
4234 typedef SmallVector<Value*, 16> ValueVector;
4235 typedef SmallPtrSet<Value*, 16> ValueSet;
4237 // Holds the Load and Store *instructions*.
4241 // Holds all the different accesses in the loop.
4242 unsigned NumReads = 0;
4243 unsigned NumReadWrites = 0;
4245 PtrRtCheck.Pointers.clear();
4246 PtrRtCheck.Need = false;
4248 const bool IsAnnotatedParallel = TheLoop->isAnnotatedParallel();
4249 MemoryDepChecker DepChecker(SE, DL, TheLoop);
4252 for (Loop::block_iterator bb = TheLoop->block_begin(),
4253 be = TheLoop->block_end(); bb != be; ++bb) {
4255 // Scan the BB and collect legal loads and stores.
4256 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e;
4259 // If this is a load, save it. If this instruction can read from memory
4260 // but is not a load, then we quit. Notice that we don't handle function
4261 // calls that read or write.
4262 if (it->mayReadFromMemory()) {
4263 // Many math library functions read the rounding mode. We will only
4264 // vectorize a loop if it contains known function calls that don't set
4265 // the flag. Therefore, it is safe to ignore this read from memory.
4266 CallInst *Call = dyn_cast<CallInst>(it);
4267 if (Call && getIntrinsicIDForCall(Call, TLI))
4270 LoadInst *Ld = dyn_cast<LoadInst>(it);
4271 if (!Ld) return false;
4272 if (!Ld->isSimple() && !IsAnnotatedParallel) {
4273 DEBUG(dbgs() << "LV: Found a non-simple load.\n");
4276 Loads.push_back(Ld);
4277 DepChecker.addAccess(Ld);
4281 // Save 'store' instructions. Abort if other instructions write to memory.
4282 if (it->mayWriteToMemory()) {
4283 StoreInst *St = dyn_cast<StoreInst>(it);
4284 if (!St) return false;
4285 if (!St->isSimple() && !IsAnnotatedParallel) {
4286 DEBUG(dbgs() << "LV: Found a non-simple store.\n");
4289 Stores.push_back(St);
4290 DepChecker.addAccess(St);
4295 // Now we have two lists that hold the loads and the stores.
4296 // Next, we find the pointers that they use.
4298 // Check if we see any stores. If there are no stores, then we don't
4299 // care if the pointers are *restrict*.
4300 if (!Stores.size()) {
4301 DEBUG(dbgs() << "LV: Found a read-only loop!\n");
4305 AccessAnalysis::DepCandidates DependentAccesses;
4306 AccessAnalysis Accesses(DL, DependentAccesses);
4308 // Holds the analyzed pointers. We don't want to call GetUnderlyingObjects
4309 // multiple times on the same object. If the ptr is accessed twice, once
4310 // for read and once for write, it will only appear once (on the write
4311 // list). This is okay, since we are going to check for conflicts between
4312 // writes and between reads and writes, but not between reads and reads.
4315 ValueVector::iterator I, IE;
4316 for (I = Stores.begin(), IE = Stores.end(); I != IE; ++I) {
4317 StoreInst *ST = cast<StoreInst>(*I);
4318 Value* Ptr = ST->getPointerOperand();
4320 if (isUniform(Ptr)) {
4321 DEBUG(dbgs() << "LV: We don't allow storing to uniform addresses\n");
4325 // If we did *not* see this pointer before, insert it to the read-write
4326 // list. At this phase it is only a 'write' list.
4327 if (Seen.insert(Ptr)) {
4329 Accesses.addStore(Ptr);
4333 if (IsAnnotatedParallel) {
4335 << "LV: A loop annotated parallel, ignore memory dependency "
4340 for (I = Loads.begin(), IE = Loads.end(); I != IE; ++I) {
4341 LoadInst *LD = cast<LoadInst>(*I);
4342 Value* Ptr = LD->getPointerOperand();
4343 // If we did *not* see this pointer before, insert it to the
4344 // read list. If we *did* see it before, then it is already in
4345 // the read-write list. This allows us to vectorize expressions
4346 // such as A[i] += x; Because the address of A[i] is a read-write
4347 // pointer. This only works if the index of A[i] is consecutive.
4348 // If the address of i is unknown (for example A[B[i]]) then we may
4349 // read a few words, modify, and write a few words, and some of the
4350 // words may be written to the same address.
4351 bool IsReadOnlyPtr = false;
4352 if (Seen.insert(Ptr) || !isStridedPtr(SE, DL, Ptr, TheLoop, Strides)) {
4354 IsReadOnlyPtr = true;
4356 Accesses.addLoad(Ptr, IsReadOnlyPtr);
4359 // If we write (or read-write) to a single destination and there are no
4360 // other reads in this loop then is it safe to vectorize.
4361 if (NumReadWrites == 1 && NumReads == 0) {
4362 DEBUG(dbgs() << "LV: Found a write-only loop!\n");
4366 // Build dependence sets and check whether we need a runtime pointer bounds
4368 Accesses.buildDependenceSets();
4369 bool NeedRTCheck = Accesses.isRTCheckNeeded();
4371 // Find pointers with computable bounds. We are going to use this information
4372 // to place a runtime bound check.
4373 unsigned NumComparisons = 0;
4374 bool CanDoRT = false;
4376 CanDoRT = Accesses.canCheckPtrAtRT(PtrRtCheck, NumComparisons, SE, TheLoop,
4379 DEBUG(dbgs() << "LV: We need to do " << NumComparisons <<
4380 " pointer comparisons.\n");
4382 // If we only have one set of dependences to check pointers among we don't
4383 // need a runtime check.
4384 if (NumComparisons == 0 && NeedRTCheck)
4385 NeedRTCheck = false;
4387 // Check that we did not collect too many pointers or found an unsizeable
4389 if (!CanDoRT || NumComparisons > RuntimeMemoryCheckThreshold) {
4395 DEBUG(dbgs() << "LV: We can perform a memory runtime check if needed.\n");
4398 if (NeedRTCheck && !CanDoRT) {
4399 DEBUG(dbgs() << "LV: We can't vectorize because we can't find " <<
4400 "the array bounds.\n");
4405 PtrRtCheck.Need = NeedRTCheck;
4407 bool CanVecMem = true;
4408 if (Accesses.isDependencyCheckNeeded()) {
4409 DEBUG(dbgs() << "LV: Checking memory dependencies\n");
4410 CanVecMem = DepChecker.areDepsSafe(
4411 DependentAccesses, Accesses.getDependenciesToCheck(), Strides);
4412 MaxSafeDepDistBytes = DepChecker.getMaxSafeDepDistBytes();
4414 if (!CanVecMem && DepChecker.shouldRetryWithRuntimeCheck()) {
4415 DEBUG(dbgs() << "LV: Retrying with memory checks\n");
4418 // Clear the dependency checks. We assume they are not needed.
4419 Accesses.resetDepChecks();
4422 PtrRtCheck.Need = true;
4424 CanDoRT = Accesses.canCheckPtrAtRT(PtrRtCheck, NumComparisons, SE,
4425 TheLoop, Strides, true);
4426 // Check that we did not collect too many pointers or found an unsizeable
4428 if (!CanDoRT || NumComparisons > RuntimeMemoryCheckThreshold) {
4429 DEBUG(dbgs() << "LV: Can't vectorize with memory checks\n");
4438 DEBUG(dbgs() << "LV: We" << (NeedRTCheck ? "" : " don't") <<
4439 " need a runtime memory check.\n");
4444 static bool hasMultipleUsesOf(Instruction *I,
4445 SmallPtrSet<Instruction *, 8> &Insts) {
4446 unsigned NumUses = 0;
4447 for(User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E; ++Use) {
4448 if (Insts.count(dyn_cast<Instruction>(*Use)))
4457 static bool areAllUsesIn(Instruction *I, SmallPtrSet<Instruction *, 8> &Set) {
4458 for(User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E; ++Use)
4459 if (!Set.count(dyn_cast<Instruction>(*Use)))
4464 bool LoopVectorizationLegality::AddReductionVar(PHINode *Phi,
4465 ReductionKind Kind) {
4466 if (Phi->getNumIncomingValues() != 2)
4469 // Reduction variables are only found in the loop header block.
4470 if (Phi->getParent() != TheLoop->getHeader())
4473 // Obtain the reduction start value from the value that comes from the loop
4475 Value *RdxStart = Phi->getIncomingValueForBlock(TheLoop->getLoopPreheader());
4477 // ExitInstruction is the single value which is used outside the loop.
4478 // We only allow for a single reduction value to be used outside the loop.
4479 // This includes users of the reduction, variables (which form a cycle
4480 // which ends in the phi node).
4481 Instruction *ExitInstruction = 0;
4482 // Indicates that we found a reduction operation in our scan.
4483 bool FoundReduxOp = false;
4485 // We start with the PHI node and scan for all of the users of this
4486 // instruction. All users must be instructions that can be used as reduction
4487 // variables (such as ADD). We must have a single out-of-block user. The cycle
4488 // must include the original PHI.
4489 bool FoundStartPHI = false;
4491 // To recognize min/max patterns formed by a icmp select sequence, we store
4492 // the number of instruction we saw from the recognized min/max pattern,
4493 // to make sure we only see exactly the two instructions.
4494 unsigned NumCmpSelectPatternInst = 0;
4495 ReductionInstDesc ReduxDesc(false, 0);
4497 SmallPtrSet<Instruction *, 8> VisitedInsts;
4498 SmallVector<Instruction *, 8> Worklist;
4499 Worklist.push_back(Phi);
4500 VisitedInsts.insert(Phi);
4502 // A value in the reduction can be used:
4503 // - By the reduction:
4504 // - Reduction operation:
4505 // - One use of reduction value (safe).
4506 // - Multiple use of reduction value (not safe).
4508 // - All uses of the PHI must be the reduction (safe).
4509 // - Otherwise, not safe.
4510 // - By one instruction outside of the loop (safe).
4511 // - By further instructions outside of the loop (not safe).
4512 // - By an instruction that is not part of the reduction (not safe).
4514 // * An instruction type other than PHI or the reduction operation.
4515 // * A PHI in the header other than the initial PHI.
4516 while (!Worklist.empty()) {
4517 Instruction *Cur = Worklist.back();
4518 Worklist.pop_back();
4521 // If the instruction has no users then this is a broken chain and can't be
4522 // a reduction variable.
4523 if (Cur->use_empty())
4526 bool IsAPhi = isa<PHINode>(Cur);
4528 // A header PHI use other than the original PHI.
4529 if (Cur != Phi && IsAPhi && Cur->getParent() == Phi->getParent())
4532 // Reductions of instructions such as Div, and Sub is only possible if the
4533 // LHS is the reduction variable.
4534 if (!Cur->isCommutative() && !IsAPhi && !isa<SelectInst>(Cur) &&
4535 !isa<ICmpInst>(Cur) && !isa<FCmpInst>(Cur) &&
4536 !VisitedInsts.count(dyn_cast<Instruction>(Cur->getOperand(0))))
4539 // Any reduction instruction must be of one of the allowed kinds.
4540 ReduxDesc = isReductionInstr(Cur, Kind, ReduxDesc);
4541 if (!ReduxDesc.IsReduction)
4544 // A reduction operation must only have one use of the reduction value.
4545 if (!IsAPhi && Kind != RK_IntegerMinMax && Kind != RK_FloatMinMax &&
4546 hasMultipleUsesOf(Cur, VisitedInsts))
4549 // All inputs to a PHI node must be a reduction value.
4550 if(IsAPhi && Cur != Phi && !areAllUsesIn(Cur, VisitedInsts))
4553 if (Kind == RK_IntegerMinMax && (isa<ICmpInst>(Cur) ||
4554 isa<SelectInst>(Cur)))
4555 ++NumCmpSelectPatternInst;
4556 if (Kind == RK_FloatMinMax && (isa<FCmpInst>(Cur) ||
4557 isa<SelectInst>(Cur)))
4558 ++NumCmpSelectPatternInst;
4560 // Check whether we found a reduction operator.
4561 FoundReduxOp |= !IsAPhi;
4563 // Process users of current instruction. Push non-PHI nodes after PHI nodes
4564 // onto the stack. This way we are going to have seen all inputs to PHI
4565 // nodes once we get to them.
4566 SmallVector<Instruction *, 8> NonPHIs;
4567 SmallVector<Instruction *, 8> PHIs;
4568 for (Value::use_iterator UI = Cur->use_begin(), E = Cur->use_end(); UI != E;
4570 Instruction *Usr = cast<Instruction>(*UI);
4572 // Check if we found the exit user.
4573 BasicBlock *Parent = Usr->getParent();
4574 if (!TheLoop->contains(Parent)) {
4575 // Exit if you find multiple outside users or if the header phi node is
4576 // being used. In this case the user uses the value of the previous
4577 // iteration, in which case we would loose "VF-1" iterations of the
4578 // reduction operation if we vectorize.
4579 if (ExitInstruction != 0 || Cur == Phi)
4582 // The instruction used by an outside user must be the last instruction
4583 // before we feed back to the reduction phi. Otherwise, we loose VF-1
4584 // operations on the value.
4585 if (std::find(Phi->op_begin(), Phi->op_end(), Cur) == Phi->op_end())
4588 ExitInstruction = Cur;
4592 // Process instructions only once (termination). Each reduction cycle
4593 // value must only be used once, except by phi nodes and min/max
4594 // reductions which are represented as a cmp followed by a select.
4595 ReductionInstDesc IgnoredVal(false, 0);
4596 if (VisitedInsts.insert(Usr)) {
4597 if (isa<PHINode>(Usr))
4598 PHIs.push_back(Usr);
4600 NonPHIs.push_back(Usr);
4601 } else if (!isa<PHINode>(Usr) &&
4602 ((!isa<FCmpInst>(Usr) &&
4603 !isa<ICmpInst>(Usr) &&
4604 !isa<SelectInst>(Usr)) ||
4605 !isMinMaxSelectCmpPattern(Usr, IgnoredVal).IsReduction))
4608 // Remember that we completed the cycle.
4610 FoundStartPHI = true;
4612 Worklist.append(PHIs.begin(), PHIs.end());
4613 Worklist.append(NonPHIs.begin(), NonPHIs.end());
4616 // This means we have seen one but not the other instruction of the
4617 // pattern or more than just a select and cmp.
4618 if ((Kind == RK_IntegerMinMax || Kind == RK_FloatMinMax) &&
4619 NumCmpSelectPatternInst != 2)
4622 if (!FoundStartPHI || !FoundReduxOp || !ExitInstruction)
4625 // We found a reduction var if we have reached the original phi node and we
4626 // only have a single instruction with out-of-loop users.
4628 // This instruction is allowed to have out-of-loop users.
4629 AllowedExit.insert(ExitInstruction);
4631 // Save the description of this reduction variable.
4632 ReductionDescriptor RD(RdxStart, ExitInstruction, Kind,
4633 ReduxDesc.MinMaxKind);
4634 Reductions[Phi] = RD;
4635 // We've ended the cycle. This is a reduction variable if we have an
4636 // outside user and it has a binary op.
4641 /// Returns true if the instruction is a Select(ICmp(X, Y), X, Y) instruction
4642 /// pattern corresponding to a min(X, Y) or max(X, Y).
4643 LoopVectorizationLegality::ReductionInstDesc
4644 LoopVectorizationLegality::isMinMaxSelectCmpPattern(Instruction *I,
4645 ReductionInstDesc &Prev) {
4647 assert((isa<ICmpInst>(I) || isa<FCmpInst>(I) || isa<SelectInst>(I)) &&
4648 "Expect a select instruction");
4649 Instruction *Cmp = 0;
4650 SelectInst *Select = 0;
4652 // We must handle the select(cmp()) as a single instruction. Advance to the
4654 if ((Cmp = dyn_cast<ICmpInst>(I)) || (Cmp = dyn_cast<FCmpInst>(I))) {
4655 if (!Cmp->hasOneUse() || !(Select = dyn_cast<SelectInst>(*I->use_begin())))
4656 return ReductionInstDesc(false, I);
4657 return ReductionInstDesc(Select, Prev.MinMaxKind);
4660 // Only handle single use cases for now.
4661 if (!(Select = dyn_cast<SelectInst>(I)))
4662 return ReductionInstDesc(false, I);
4663 if (!(Cmp = dyn_cast<ICmpInst>(I->getOperand(0))) &&
4664 !(Cmp = dyn_cast<FCmpInst>(I->getOperand(0))))
4665 return ReductionInstDesc(false, I);
4666 if (!Cmp->hasOneUse())
4667 return ReductionInstDesc(false, I);
4672 // Look for a min/max pattern.
4673 if (m_UMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
4674 return ReductionInstDesc(Select, MRK_UIntMin);
4675 else if (m_UMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
4676 return ReductionInstDesc(Select, MRK_UIntMax);
4677 else if (m_SMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
4678 return ReductionInstDesc(Select, MRK_SIntMax);
4679 else if (m_SMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
4680 return ReductionInstDesc(Select, MRK_SIntMin);
4681 else if (m_OrdFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
4682 return ReductionInstDesc(Select, MRK_FloatMin);
4683 else if (m_OrdFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
4684 return ReductionInstDesc(Select, MRK_FloatMax);
4685 else if (m_UnordFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
4686 return ReductionInstDesc(Select, MRK_FloatMin);
4687 else if (m_UnordFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
4688 return ReductionInstDesc(Select, MRK_FloatMax);
4690 return ReductionInstDesc(false, I);
4693 LoopVectorizationLegality::ReductionInstDesc
4694 LoopVectorizationLegality::isReductionInstr(Instruction *I,
4696 ReductionInstDesc &Prev) {
4697 bool FP = I->getType()->isFloatingPointTy();
4698 bool FastMath = (FP && I->isCommutative() && I->isAssociative());
4699 switch (I->getOpcode()) {
4701 return ReductionInstDesc(false, I);
4702 case Instruction::PHI:
4703 if (FP && (Kind != RK_FloatMult && Kind != RK_FloatAdd &&
4704 Kind != RK_FloatMinMax))
4705 return ReductionInstDesc(false, I);
4706 return ReductionInstDesc(I, Prev.MinMaxKind);
4707 case Instruction::Sub:
4708 case Instruction::Add:
4709 return ReductionInstDesc(Kind == RK_IntegerAdd, I);
4710 case Instruction::Mul:
4711 return ReductionInstDesc(Kind == RK_IntegerMult, I);
4712 case Instruction::And:
4713 return ReductionInstDesc(Kind == RK_IntegerAnd, I);
4714 case Instruction::Or:
4715 return ReductionInstDesc(Kind == RK_IntegerOr, I);
4716 case Instruction::Xor:
4717 return ReductionInstDesc(Kind == RK_IntegerXor, I);
4718 case Instruction::FMul:
4719 return ReductionInstDesc(Kind == RK_FloatMult && FastMath, I);
4720 case Instruction::FAdd:
4721 return ReductionInstDesc(Kind == RK_FloatAdd && FastMath, I);
4722 case Instruction::FCmp:
4723 case Instruction::ICmp:
4724 case Instruction::Select:
4725 if (Kind != RK_IntegerMinMax &&
4726 (!HasFunNoNaNAttr || Kind != RK_FloatMinMax))
4727 return ReductionInstDesc(false, I);
4728 return isMinMaxSelectCmpPattern(I, Prev);
4732 LoopVectorizationLegality::InductionKind
4733 LoopVectorizationLegality::isInductionVariable(PHINode *Phi) {
4734 Type *PhiTy = Phi->getType();
4735 // We only handle integer and pointer inductions variables.
4736 if (!PhiTy->isIntegerTy() && !PhiTy->isPointerTy())
4737 return IK_NoInduction;
4739 // Check that the PHI is consecutive.
4740 const SCEV *PhiScev = SE->getSCEV(Phi);
4741 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PhiScev);
4743 DEBUG(dbgs() << "LV: PHI is not a poly recurrence.\n");
4744 return IK_NoInduction;
4746 const SCEV *Step = AR->getStepRecurrence(*SE);
4748 // Integer inductions need to have a stride of one.
4749 if (PhiTy->isIntegerTy()) {
4751 return IK_IntInduction;
4752 if (Step->isAllOnesValue())
4753 return IK_ReverseIntInduction;
4754 return IK_NoInduction;
4757 // Calculate the pointer stride and check if it is consecutive.
4758 const SCEVConstant *C = dyn_cast<SCEVConstant>(Step);
4760 return IK_NoInduction;
4762 assert(PhiTy->isPointerTy() && "The PHI must be a pointer");
4763 uint64_t Size = DL->getTypeAllocSize(PhiTy->getPointerElementType());
4764 if (C->getValue()->equalsInt(Size))
4765 return IK_PtrInduction;
4766 else if (C->getValue()->equalsInt(0 - Size))
4767 return IK_ReversePtrInduction;
4769 return IK_NoInduction;
4772 bool LoopVectorizationLegality::isInductionVariable(const Value *V) {
4773 Value *In0 = const_cast<Value*>(V);
4774 PHINode *PN = dyn_cast_or_null<PHINode>(In0);
4778 return Inductions.count(PN);
4781 bool LoopVectorizationLegality::blockNeedsPredication(BasicBlock *BB) {
4782 assert(TheLoop->contains(BB) && "Unknown block used");
4784 // Blocks that do not dominate the latch need predication.
4785 BasicBlock* Latch = TheLoop->getLoopLatch();
4786 return !DT->dominates(BB, Latch);
4789 bool LoopVectorizationLegality::blockCanBePredicated(BasicBlock *BB,
4790 SmallPtrSet<Value *, 8>& SafePtrs) {
4791 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
4792 // We might be able to hoist the load.
4793 if (it->mayReadFromMemory()) {
4794 LoadInst *LI = dyn_cast<LoadInst>(it);
4795 if (!LI || !SafePtrs.count(LI->getPointerOperand()))
4799 // We don't predicate stores at the moment.
4800 if (it->mayWriteToMemory() || it->mayThrow())
4803 // Check that we don't have a constant expression that can trap as operand.
4804 for (Instruction::op_iterator OI = it->op_begin(), OE = it->op_end();
4806 if (Constant *C = dyn_cast<Constant>(*OI))
4811 // The instructions below can trap.
4812 switch (it->getOpcode()) {
4814 case Instruction::UDiv:
4815 case Instruction::SDiv:
4816 case Instruction::URem:
4817 case Instruction::SRem:
4825 LoopVectorizationCostModel::VectorizationFactor
4826 LoopVectorizationCostModel::selectVectorizationFactor(bool OptForSize,
4828 // Width 1 means no vectorize
4829 VectorizationFactor Factor = { 1U, 0U };
4830 if (OptForSize && Legal->getRuntimePointerCheck()->Need) {
4831 DEBUG(dbgs() << "LV: Aborting. Runtime ptr check is required in Os.\n");
4835 // Find the trip count.
4836 unsigned TC = SE->getSmallConstantTripCount(TheLoop, TheLoop->getLoopLatch());
4837 DEBUG(dbgs() << "LV: Found trip count: " << TC << '\n');
4839 unsigned WidestType = getWidestType();
4840 unsigned WidestRegister = TTI.getRegisterBitWidth(true);
4841 unsigned MaxSafeDepDist = -1U;
4842 if (Legal->getMaxSafeDepDistBytes() != -1U)
4843 MaxSafeDepDist = Legal->getMaxSafeDepDistBytes() * 8;
4844 WidestRegister = ((WidestRegister < MaxSafeDepDist) ?
4845 WidestRegister : MaxSafeDepDist);
4846 unsigned MaxVectorSize = WidestRegister / WidestType;
4847 DEBUG(dbgs() << "LV: The Widest type: " << WidestType << " bits.\n");
4848 DEBUG(dbgs() << "LV: The Widest register is: "
4849 << WidestRegister << " bits.\n");
4851 if (MaxVectorSize == 0) {
4852 DEBUG(dbgs() << "LV: The target has no vector registers.\n");
4856 assert(MaxVectorSize <= 32 && "Did not expect to pack so many elements"
4857 " into one vector!");
4859 unsigned VF = MaxVectorSize;
4861 // If we optimize the program for size, avoid creating the tail loop.
4863 // If we are unable to calculate the trip count then don't try to vectorize.
4865 DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n");
4869 // Find the maximum SIMD width that can fit within the trip count.
4870 VF = TC % MaxVectorSize;
4875 // If the trip count that we found modulo the vectorization factor is not
4876 // zero then we require a tail.
4878 DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n");
4884 assert(isPowerOf2_32(UserVF) && "VF needs to be a power of two");
4885 DEBUG(dbgs() << "LV: Using user VF " << UserVF << ".\n");
4887 Factor.Width = UserVF;
4891 float Cost = expectedCost(1);
4893 DEBUG(dbgs() << "LV: Scalar loop costs: " << (int)Cost << ".\n");
4894 for (unsigned i=2; i <= VF; i*=2) {
4895 // Notice that the vector loop needs to be executed less times, so
4896 // we need to divide the cost of the vector loops by the width of
4897 // the vector elements.
4898 float VectorCost = expectedCost(i) / (float)i;
4899 DEBUG(dbgs() << "LV: Vector loop of width " << i << " costs: " <<
4900 (int)VectorCost << ".\n");
4901 if (VectorCost < Cost) {
4907 DEBUG(dbgs() << "LV: Selecting VF = : "<< Width << ".\n");
4908 Factor.Width = Width;
4909 Factor.Cost = Width * Cost;
4913 unsigned LoopVectorizationCostModel::getWidestType() {
4914 unsigned MaxWidth = 8;
4917 for (Loop::block_iterator bb = TheLoop->block_begin(),
4918 be = TheLoop->block_end(); bb != be; ++bb) {
4919 BasicBlock *BB = *bb;
4921 // For each instruction in the loop.
4922 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
4923 Type *T = it->getType();
4925 // Only examine Loads, Stores and PHINodes.
4926 if (!isa<LoadInst>(it) && !isa<StoreInst>(it) && !isa<PHINode>(it))
4929 // Examine PHI nodes that are reduction variables.
4930 if (PHINode *PN = dyn_cast<PHINode>(it))
4931 if (!Legal->getReductionVars()->count(PN))
4934 // Examine the stored values.
4935 if (StoreInst *ST = dyn_cast<StoreInst>(it))
4936 T = ST->getValueOperand()->getType();
4938 // Ignore loaded pointer types and stored pointer types that are not
4939 // consecutive. However, we do want to take consecutive stores/loads of
4940 // pointer vectors into account.
4941 if (T->isPointerTy() && !isConsecutiveLoadOrStore(it))
4944 MaxWidth = std::max(MaxWidth,
4945 (unsigned)DL->getTypeSizeInBits(T->getScalarType()));
4953 LoopVectorizationCostModel::selectUnrollFactor(bool OptForSize,
4956 unsigned LoopCost) {
4958 // -- The unroll heuristics --
4959 // We unroll the loop in order to expose ILP and reduce the loop overhead.
4960 // There are many micro-architectural considerations that we can't predict
4961 // at this level. For example frontend pressure (on decode or fetch) due to
4962 // code size, or the number and capabilities of the execution ports.
4964 // We use the following heuristics to select the unroll factor:
4965 // 1. If the code has reductions the we unroll in order to break the cross
4966 // iteration dependency.
4967 // 2. If the loop is really small then we unroll in order to reduce the loop
4969 // 3. We don't unroll if we think that we will spill registers to memory due
4970 // to the increased register pressure.
4972 // Use the user preference, unless 'auto' is selected.
4976 // When we optimize for size we don't unroll.
4980 // We used the distance for the unroll factor.
4981 if (Legal->getMaxSafeDepDistBytes() != -1U)
4984 // Do not unroll loops with a relatively small trip count.
4985 unsigned TC = SE->getSmallConstantTripCount(TheLoop,
4986 TheLoop->getLoopLatch());
4987 if (TC > 1 && TC < TinyTripCountUnrollThreshold)
4990 unsigned TargetNumRegisters = TTI.getNumberOfRegisters(VF > 1);
4991 DEBUG(dbgs() << "LV: The target has " << TargetNumRegisters <<
4995 if (ForceTargetNumScalarRegs.getNumOccurrences() > 0)
4996 TargetNumRegisters = ForceTargetNumScalarRegs;
4998 if (ForceTargetNumVectorRegs.getNumOccurrences() > 0)
4999 TargetNumRegisters = ForceTargetNumVectorRegs;
5002 LoopVectorizationCostModel::RegisterUsage R = calculateRegisterUsage();
5003 // We divide by these constants so assume that we have at least one
5004 // instruction that uses at least one register.
5005 R.MaxLocalUsers = std::max(R.MaxLocalUsers, 1U);
5006 R.NumInstructions = std::max(R.NumInstructions, 1U);
5008 // We calculate the unroll factor using the following formula.
5009 // Subtract the number of loop invariants from the number of available
5010 // registers. These registers are used by all of the unrolled instances.
5011 // Next, divide the remaining registers by the number of registers that is
5012 // required by the loop, in order to estimate how many parallel instances
5013 // fit without causing spills. All of this is rounded down if necessary to be
5014 // a power of two. We want power of two unroll factors to simplify any
5015 // addressing operations or alignment considerations.
5016 unsigned UF = PowerOf2Floor((TargetNumRegisters - R.LoopInvariantRegs) /
5019 // Clamp the unroll factor ranges to reasonable factors.
5020 unsigned MaxUnrollSize = TTI.getMaximumUnrollFactor();
5022 // Check if the user has overridden the unroll max.
5024 if (ForceTargetMaxScalarUnrollFactor.getNumOccurrences() > 0)
5025 MaxUnrollSize = ForceTargetMaxScalarUnrollFactor;
5027 if (ForceTargetMaxVectorUnrollFactor.getNumOccurrences() > 0)
5028 MaxUnrollSize = ForceTargetMaxVectorUnrollFactor;
5031 // If we did not calculate the cost for VF (because the user selected the VF)
5032 // then we calculate the cost of VF here.
5034 LoopCost = expectedCost(VF);
5036 // Clamp the calculated UF to be between the 1 and the max unroll factor
5037 // that the target allows.
5038 if (UF > MaxUnrollSize)
5043 // Unroll if we vectorized this loop and there is a reduction that could
5044 // benefit from unrolling.
5045 if (VF > 1 && Legal->getReductionVars()->size()) {
5046 DEBUG(dbgs() << "LV: Unrolling because of reductions.\n");
5050 // We want to unroll tiny loops in order to reduce the loop overhead.
5051 // We assume that the cost overhead is 1 and we use the cost model
5052 // to estimate the cost of the loop and unroll until the cost of the
5053 // loop overhead is about 5% of the cost of the loop.
5054 DEBUG(dbgs() << "LV: Loop cost is " << LoopCost << '\n');
5055 if (LoopCost < SmallLoopCost) {
5056 DEBUG(dbgs() << "LV: Unrolling to reduce branch cost.\n");
5057 unsigned NewUF = PowerOf2Floor(SmallLoopCost / LoopCost);
5058 return std::min(NewUF, UF);
5061 DEBUG(dbgs() << "LV: Not Unrolling.\n");
5065 LoopVectorizationCostModel::RegisterUsage
5066 LoopVectorizationCostModel::calculateRegisterUsage() {
5067 // This function calculates the register usage by measuring the highest number
5068 // of values that are alive at a single location. Obviously, this is a very
5069 // rough estimation. We scan the loop in a topological order in order and
5070 // assign a number to each instruction. We use RPO to ensure that defs are
5071 // met before their users. We assume that each instruction that has in-loop
5072 // users starts an interval. We record every time that an in-loop value is
5073 // used, so we have a list of the first and last occurrences of each
5074 // instruction. Next, we transpose this data structure into a multi map that
5075 // holds the list of intervals that *end* at a specific location. This multi
5076 // map allows us to perform a linear search. We scan the instructions linearly
5077 // and record each time that a new interval starts, by placing it in a set.
5078 // If we find this value in the multi-map then we remove it from the set.
5079 // The max register usage is the maximum size of the set.
5080 // We also search for instructions that are defined outside the loop, but are
5081 // used inside the loop. We need this number separately from the max-interval
5082 // usage number because when we unroll, loop-invariant values do not take
5084 LoopBlocksDFS DFS(TheLoop);
5088 R.NumInstructions = 0;
5090 // Each 'key' in the map opens a new interval. The values
5091 // of the map are the index of the 'last seen' usage of the
5092 // instruction that is the key.
5093 typedef DenseMap<Instruction*, unsigned> IntervalMap;
5094 // Maps instruction to its index.
5095 DenseMap<unsigned, Instruction*> IdxToInstr;
5096 // Marks the end of each interval.
5097 IntervalMap EndPoint;
5098 // Saves the list of instruction indices that are used in the loop.
5099 SmallSet<Instruction*, 8> Ends;
5100 // Saves the list of values that are used in the loop but are
5101 // defined outside the loop, such as arguments and constants.
5102 SmallPtrSet<Value*, 8> LoopInvariants;
5105 for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(),
5106 be = DFS.endRPO(); bb != be; ++bb) {
5107 R.NumInstructions += (*bb)->size();
5108 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e;
5110 Instruction *I = it;
5111 IdxToInstr[Index++] = I;
5113 // Save the end location of each USE.
5114 for (unsigned i = 0; i < I->getNumOperands(); ++i) {
5115 Value *U = I->getOperand(i);
5116 Instruction *Instr = dyn_cast<Instruction>(U);
5118 // Ignore non-instruction values such as arguments, constants, etc.
5119 if (!Instr) continue;
5121 // If this instruction is outside the loop then record it and continue.
5122 if (!TheLoop->contains(Instr)) {
5123 LoopInvariants.insert(Instr);
5127 // Overwrite previous end points.
5128 EndPoint[Instr] = Index;
5134 // Saves the list of intervals that end with the index in 'key'.
5135 typedef SmallVector<Instruction*, 2> InstrList;
5136 DenseMap<unsigned, InstrList> TransposeEnds;
5138 // Transpose the EndPoints to a list of values that end at each index.
5139 for (IntervalMap::iterator it = EndPoint.begin(), e = EndPoint.end();
5141 TransposeEnds[it->second].push_back(it->first);
5143 SmallSet<Instruction*, 8> OpenIntervals;
5144 unsigned MaxUsage = 0;
5147 DEBUG(dbgs() << "LV(REG): Calculating max register usage:\n");
5148 for (unsigned int i = 0; i < Index; ++i) {
5149 Instruction *I = IdxToInstr[i];
5150 // Ignore instructions that are never used within the loop.
5151 if (!Ends.count(I)) continue;
5153 // Remove all of the instructions that end at this location.
5154 InstrList &List = TransposeEnds[i];
5155 for (unsigned int j=0, e = List.size(); j < e; ++j)
5156 OpenIntervals.erase(List[j]);
5158 // Count the number of live interals.
5159 MaxUsage = std::max(MaxUsage, OpenIntervals.size());
5161 DEBUG(dbgs() << "LV(REG): At #" << i << " Interval # " <<
5162 OpenIntervals.size() << '\n');
5164 // Add the current instruction to the list of open intervals.
5165 OpenIntervals.insert(I);
5168 unsigned Invariant = LoopInvariants.size();
5169 DEBUG(dbgs() << "LV(REG): Found max usage: " << MaxUsage << '\n');
5170 DEBUG(dbgs() << "LV(REG): Found invariant usage: " << Invariant << '\n');
5171 DEBUG(dbgs() << "LV(REG): LoopSize: " << R.NumInstructions << '\n');
5173 R.LoopInvariantRegs = Invariant;
5174 R.MaxLocalUsers = MaxUsage;
5178 unsigned LoopVectorizationCostModel::expectedCost(unsigned VF) {
5182 for (Loop::block_iterator bb = TheLoop->block_begin(),
5183 be = TheLoop->block_end(); bb != be; ++bb) {
5184 unsigned BlockCost = 0;
5185 BasicBlock *BB = *bb;
5187 // For each instruction in the old loop.
5188 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
5189 // Skip dbg intrinsics.
5190 if (isa<DbgInfoIntrinsic>(it))
5193 unsigned C = getInstructionCost(it, VF);
5195 // Check if we should override the cost.
5196 if (ForceTargetInstructionCost.getNumOccurrences() > 0)
5197 C = ForceTargetInstructionCost;
5200 DEBUG(dbgs() << "LV: Found an estimated cost of " << C << " for VF " <<
5201 VF << " For instruction: " << *it << '\n');
5204 // We assume that if-converted blocks have a 50% chance of being executed.
5205 // When the code is scalar then some of the blocks are avoided due to CF.
5206 // When the code is vectorized we execute all code paths.
5207 if (VF == 1 && Legal->blockNeedsPredication(*bb))
5216 /// \brief Check whether the address computation for a non-consecutive memory
5217 /// access looks like an unlikely candidate for being merged into the indexing
5220 /// We look for a GEP which has one index that is an induction variable and all
5221 /// other indices are loop invariant. If the stride of this access is also
5222 /// within a small bound we decide that this address computation can likely be
5223 /// merged into the addressing mode.
5224 /// In all other cases, we identify the address computation as complex.
5225 static bool isLikelyComplexAddressComputation(Value *Ptr,
5226 LoopVectorizationLegality *Legal,
5227 ScalarEvolution *SE,
5228 const Loop *TheLoop) {
5229 GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr);
5233 // We are looking for a gep with all loop invariant indices except for one
5234 // which should be an induction variable.
5235 unsigned NumOperands = Gep->getNumOperands();
5236 for (unsigned i = 1; i < NumOperands; ++i) {
5237 Value *Opd = Gep->getOperand(i);
5238 if (!SE->isLoopInvariant(SE->getSCEV(Opd), TheLoop) &&
5239 !Legal->isInductionVariable(Opd))
5243 // Now we know we have a GEP ptr, %inv, %ind, %inv. Make sure that the step
5244 // can likely be merged into the address computation.
5245 unsigned MaxMergeDistance = 64;
5247 const SCEVAddRecExpr *AddRec = dyn_cast<SCEVAddRecExpr>(SE->getSCEV(Ptr));
5251 // Check the step is constant.
5252 const SCEV *Step = AddRec->getStepRecurrence(*SE);
5253 // Calculate the pointer stride and check if it is consecutive.
5254 const SCEVConstant *C = dyn_cast<SCEVConstant>(Step);
5258 const APInt &APStepVal = C->getValue()->getValue();
5260 // Huge step value - give up.
5261 if (APStepVal.getBitWidth() > 64)
5264 int64_t StepVal = APStepVal.getSExtValue();
5266 return StepVal > MaxMergeDistance;
5269 static bool isStrideMul(Instruction *I, LoopVectorizationLegality *Legal) {
5270 if (Legal->hasStride(I->getOperand(0)) || Legal->hasStride(I->getOperand(1)))
5276 LoopVectorizationCostModel::getInstructionCost(Instruction *I, unsigned VF) {
5277 // If we know that this instruction will remain uniform, check the cost of
5278 // the scalar version.
5279 if (Legal->isUniformAfterVectorization(I))
5282 Type *RetTy = I->getType();
5283 Type *VectorTy = ToVectorTy(RetTy, VF);
5285 // TODO: We need to estimate the cost of intrinsic calls.
5286 switch (I->getOpcode()) {
5287 case Instruction::GetElementPtr:
5288 // We mark this instruction as zero-cost because the cost of GEPs in
5289 // vectorized code depends on whether the corresponding memory instruction
5290 // is scalarized or not. Therefore, we handle GEPs with the memory
5291 // instruction cost.
5293 case Instruction::Br: {
5294 return TTI.getCFInstrCost(I->getOpcode());
5296 case Instruction::PHI:
5297 //TODO: IF-converted IFs become selects.
5299 case Instruction::Add:
5300 case Instruction::FAdd:
5301 case Instruction::Sub:
5302 case Instruction::FSub:
5303 case Instruction::Mul:
5304 case Instruction::FMul:
5305 case Instruction::UDiv:
5306 case Instruction::SDiv:
5307 case Instruction::FDiv:
5308 case Instruction::URem:
5309 case Instruction::SRem:
5310 case Instruction::FRem:
5311 case Instruction::Shl:
5312 case Instruction::LShr:
5313 case Instruction::AShr:
5314 case Instruction::And:
5315 case Instruction::Or:
5316 case Instruction::Xor: {
5317 // Since we will replace the stride by 1 the multiplication should go away.
5318 if (I->getOpcode() == Instruction::Mul && isStrideMul(I, Legal))
5320 // Certain instructions can be cheaper to vectorize if they have a constant
5321 // second vector operand. One example of this are shifts on x86.
5322 TargetTransformInfo::OperandValueKind Op1VK =
5323 TargetTransformInfo::OK_AnyValue;
5324 TargetTransformInfo::OperandValueKind Op2VK =
5325 TargetTransformInfo::OK_AnyValue;
5327 if (isa<ConstantInt>(I->getOperand(1)))
5328 Op2VK = TargetTransformInfo::OK_UniformConstantValue;
5330 return TTI.getArithmeticInstrCost(I->getOpcode(), VectorTy, Op1VK, Op2VK);
5332 case Instruction::Select: {
5333 SelectInst *SI = cast<SelectInst>(I);
5334 const SCEV *CondSCEV = SE->getSCEV(SI->getCondition());
5335 bool ScalarCond = (SE->isLoopInvariant(CondSCEV, TheLoop));
5336 Type *CondTy = SI->getCondition()->getType();
5338 CondTy = VectorType::get(CondTy, VF);
5340 return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy, CondTy);
5342 case Instruction::ICmp:
5343 case Instruction::FCmp: {
5344 Type *ValTy = I->getOperand(0)->getType();
5345 VectorTy = ToVectorTy(ValTy, VF);
5346 return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy);
5348 case Instruction::Store:
5349 case Instruction::Load: {
5350 StoreInst *SI = dyn_cast<StoreInst>(I);
5351 LoadInst *LI = dyn_cast<LoadInst>(I);
5352 Type *ValTy = (SI ? SI->getValueOperand()->getType() :
5354 VectorTy = ToVectorTy(ValTy, VF);
5356 unsigned Alignment = SI ? SI->getAlignment() : LI->getAlignment();
5357 unsigned AS = SI ? SI->getPointerAddressSpace() :
5358 LI->getPointerAddressSpace();
5359 Value *Ptr = SI ? SI->getPointerOperand() : LI->getPointerOperand();
5360 // We add the cost of address computation here instead of with the gep
5361 // instruction because only here we know whether the operation is
5364 return TTI.getAddressComputationCost(VectorTy) +
5365 TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS);
5367 // Scalarized loads/stores.
5368 int ConsecutiveStride = Legal->isConsecutivePtr(Ptr);
5369 bool Reverse = ConsecutiveStride < 0;
5370 unsigned ScalarAllocatedSize = DL->getTypeAllocSize(ValTy);
5371 unsigned VectorElementSize = DL->getTypeStoreSize(VectorTy)/VF;
5372 if (!ConsecutiveStride || ScalarAllocatedSize != VectorElementSize) {
5373 bool IsComplexComputation =
5374 isLikelyComplexAddressComputation(Ptr, Legal, SE, TheLoop);
5376 // The cost of extracting from the value vector and pointer vector.
5377 Type *PtrTy = ToVectorTy(Ptr->getType(), VF);
5378 for (unsigned i = 0; i < VF; ++i) {
5379 // The cost of extracting the pointer operand.
5380 Cost += TTI.getVectorInstrCost(Instruction::ExtractElement, PtrTy, i);
5381 // In case of STORE, the cost of ExtractElement from the vector.
5382 // In case of LOAD, the cost of InsertElement into the returned
5384 Cost += TTI.getVectorInstrCost(SI ? Instruction::ExtractElement :
5385 Instruction::InsertElement,
5389 // The cost of the scalar loads/stores.
5390 Cost += VF * TTI.getAddressComputationCost(PtrTy, IsComplexComputation);
5391 Cost += VF * TTI.getMemoryOpCost(I->getOpcode(), ValTy->getScalarType(),
5396 // Wide load/stores.
5397 unsigned Cost = TTI.getAddressComputationCost(VectorTy);
5398 Cost += TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS);
5401 Cost += TTI.getShuffleCost(TargetTransformInfo::SK_Reverse,
5405 case Instruction::ZExt:
5406 case Instruction::SExt:
5407 case Instruction::FPToUI:
5408 case Instruction::FPToSI:
5409 case Instruction::FPExt:
5410 case Instruction::PtrToInt:
5411 case Instruction::IntToPtr:
5412 case Instruction::SIToFP:
5413 case Instruction::UIToFP:
5414 case Instruction::Trunc:
5415 case Instruction::FPTrunc:
5416 case Instruction::BitCast: {
5417 // We optimize the truncation of induction variable.
5418 // The cost of these is the same as the scalar operation.
5419 if (I->getOpcode() == Instruction::Trunc &&
5420 Legal->isInductionVariable(I->getOperand(0)))
5421 return TTI.getCastInstrCost(I->getOpcode(), I->getType(),
5422 I->getOperand(0)->getType());
5424 Type *SrcVecTy = ToVectorTy(I->getOperand(0)->getType(), VF);
5425 return TTI.getCastInstrCost(I->getOpcode(), VectorTy, SrcVecTy);
5427 case Instruction::Call: {
5428 CallInst *CI = cast<CallInst>(I);
5429 Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI);
5430 assert(ID && "Not an intrinsic call!");
5431 Type *RetTy = ToVectorTy(CI->getType(), VF);
5432 SmallVector<Type*, 4> Tys;
5433 for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i)
5434 Tys.push_back(ToVectorTy(CI->getArgOperand(i)->getType(), VF));
5435 return TTI.getIntrinsicInstrCost(ID, RetTy, Tys);
5438 // We are scalarizing the instruction. Return the cost of the scalar
5439 // instruction, plus the cost of insert and extract into vector
5440 // elements, times the vector width.
5443 if (!RetTy->isVoidTy() && VF != 1) {
5444 unsigned InsCost = TTI.getVectorInstrCost(Instruction::InsertElement,
5446 unsigned ExtCost = TTI.getVectorInstrCost(Instruction::ExtractElement,
5449 // The cost of inserting the results plus extracting each one of the
5451 Cost += VF * (InsCost + ExtCost * I->getNumOperands());
5454 // The cost of executing VF copies of the scalar instruction. This opcode
5455 // is unknown. Assume that it is the same as 'mul'.
5456 Cost += VF * TTI.getArithmeticInstrCost(Instruction::Mul, VectorTy);
5462 Type* LoopVectorizationCostModel::ToVectorTy(Type *Scalar, unsigned VF) {
5463 if (Scalar->isVoidTy() || VF == 1)
5465 return VectorType::get(Scalar, VF);
5468 char LoopVectorize::ID = 0;
5469 static const char lv_name[] = "Loop Vectorization";
5470 INITIALIZE_PASS_BEGIN(LoopVectorize, LV_NAME, lv_name, false, false)
5471 INITIALIZE_AG_DEPENDENCY(TargetTransformInfo)
5472 INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass)
5473 INITIALIZE_PASS_DEPENDENCY(ScalarEvolution)
5474 INITIALIZE_PASS_DEPENDENCY(LCSSA)
5475 INITIALIZE_PASS_DEPENDENCY(LoopInfo)
5476 INITIALIZE_PASS_DEPENDENCY(LoopSimplify)
5477 INITIALIZE_PASS_END(LoopVectorize, LV_NAME, lv_name, false, false)
5480 Pass *createLoopVectorizePass(bool NoUnrolling, bool AlwaysVectorize) {
5481 return new LoopVectorize(NoUnrolling, AlwaysVectorize);
5485 bool LoopVectorizationCostModel::isConsecutiveLoadOrStore(Instruction *Inst) {
5486 // Check for a store.
5487 if (StoreInst *ST = dyn_cast<StoreInst>(Inst))
5488 return Legal->isConsecutivePtr(ST->getPointerOperand()) != 0;
5490 // Check for a load.
5491 if (LoadInst *LI = dyn_cast<LoadInst>(Inst))
5492 return Legal->isConsecutivePtr(LI->getPointerOperand()) != 0;
5498 void InnerLoopUnroller::scalarizeInstruction(Instruction *Instr) {
5499 assert(!Instr->getType()->isAggregateType() && "Can't handle vectors");
5500 // Holds vector parameters or scalars, in case of uniform vals.
5501 SmallVector<VectorParts, 4> Params;
5503 setDebugLocFromInst(Builder, Instr);
5505 // Find all of the vectorized parameters.
5506 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
5507 Value *SrcOp = Instr->getOperand(op);
5509 // If we are accessing the old induction variable, use the new one.
5510 if (SrcOp == OldInduction) {
5511 Params.push_back(getVectorValue(SrcOp));
5515 // Try using previously calculated values.
5516 Instruction *SrcInst = dyn_cast<Instruction>(SrcOp);
5518 // If the src is an instruction that appeared earlier in the basic block
5519 // then it should already be vectorized.
5520 if (SrcInst && OrigLoop->contains(SrcInst)) {
5521 assert(WidenMap.has(SrcInst) && "Source operand is unavailable");
5522 // The parameter is a vector value from earlier.
5523 Params.push_back(WidenMap.get(SrcInst));
5525 // The parameter is a scalar from outside the loop. Maybe even a constant.
5526 VectorParts Scalars;
5527 Scalars.append(UF, SrcOp);
5528 Params.push_back(Scalars);
5532 assert(Params.size() == Instr->getNumOperands() &&
5533 "Invalid number of operands");
5535 // Does this instruction return a value ?
5536 bool IsVoidRetTy = Instr->getType()->isVoidTy();
5538 Value *UndefVec = IsVoidRetTy ? 0 :
5539 UndefValue::get(Instr->getType());
5540 // Create a new entry in the WidenMap and initialize it to Undef or Null.
5541 VectorParts &VecResults = WidenMap.splat(Instr, UndefVec);
5543 // For each vector unroll 'part':
5544 for (unsigned Part = 0; Part < UF; ++Part) {
5545 // For each scalar that we create:
5547 Instruction *Cloned = Instr->clone();
5549 Cloned->setName(Instr->getName() + ".cloned");
5550 // Replace the operands of the cloned instructions with extracted scalars.
5551 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
5552 Value *Op = Params[op][Part];
5553 Cloned->setOperand(op, Op);
5556 // Place the cloned scalar in the new loop.
5557 Builder.Insert(Cloned);
5559 // If the original scalar returns a value we need to place it in a vector
5560 // so that future users will be able to use it.
5562 VecResults[Part] = Cloned;
5566 void InnerLoopUnroller::vectorizeMemoryInstruction(Instruction *Instr) {
5567 return scalarizeInstruction(Instr);
5570 Value *InnerLoopUnroller::reverseVector(Value *Vec) {
5574 Value *InnerLoopUnroller::getBroadcastInstrs(Value *V) {
5578 Value *InnerLoopUnroller::getConsecutiveVector(Value* Val, int StartIdx,
5580 // When unrolling and the VF is 1, we only need to add a simple scalar.
5581 Type *ITy = Val->getType();
5582 assert(!ITy->isVectorTy() && "Val must be a scalar");
5583 Constant *C = ConstantInt::get(ITy, StartIdx, Negate);
5584 return Builder.CreateAdd(Val, C, "induction");