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. Legalization of the IR is done
12 // in the codegen. However, the vectorizer uses (will use) the codegen
13 // interfaces to generate IR that is likely to result in an optimal binary.
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/MapVector.h"
51 #include "llvm/ADT/SmallPtrSet.h"
52 #include "llvm/ADT/SmallSet.h"
53 #include "llvm/ADT/SmallVector.h"
54 #include "llvm/ADT/StringExtras.h"
55 #include "llvm/Analysis/AliasAnalysis.h"
56 #include "llvm/Analysis/AliasSetTracker.h"
57 #include "llvm/Analysis/Dominators.h"
58 #include "llvm/Analysis/LoopInfo.h"
59 #include "llvm/Analysis/LoopIterator.h"
60 #include "llvm/Analysis/LoopPass.h"
61 #include "llvm/Analysis/ScalarEvolution.h"
62 #include "llvm/Analysis/ScalarEvolutionExpander.h"
63 #include "llvm/Analysis/ScalarEvolutionExpressions.h"
64 #include "llvm/Analysis/TargetTransformInfo.h"
65 #include "llvm/Analysis/ValueTracking.h"
66 #include "llvm/Analysis/Verifier.h"
67 #include "llvm/IR/Constants.h"
68 #include "llvm/IR/DataLayout.h"
69 #include "llvm/IR/DerivedTypes.h"
70 #include "llvm/IR/Function.h"
71 #include "llvm/IR/IRBuilder.h"
72 #include "llvm/IR/Instructions.h"
73 #include "llvm/IR/IntrinsicInst.h"
74 #include "llvm/IR/LLVMContext.h"
75 #include "llvm/IR/Module.h"
76 #include "llvm/IR/Type.h"
77 #include "llvm/IR/Value.h"
78 #include "llvm/Pass.h"
79 #include "llvm/Support/CommandLine.h"
80 #include "llvm/Support/Debug.h"
81 #include "llvm/Support/raw_ostream.h"
82 #include "llvm/Transforms/Scalar.h"
83 #include "llvm/Transforms/Utils/BasicBlockUtils.h"
84 #include "llvm/Transforms/Utils/Local.h"
90 static cl::opt<unsigned>
91 VectorizationFactor("force-vector-width", cl::init(0), cl::Hidden,
92 cl::desc("Sets the SIMD width. Zero is autoselect."));
94 static cl::opt<unsigned>
95 VectorizationUnroll("force-vector-unroll", cl::init(0), cl::Hidden,
96 cl::desc("Sets the vectorization unroll count. "
97 "Zero is autoselect."));
100 EnableIfConversion("enable-if-conversion", cl::init(true), cl::Hidden,
101 cl::desc("Enable if-conversion during vectorization."));
103 /// We don't vectorize loops with a known constant trip count below this number.
104 static cl::opt<unsigned>
105 TinyTripCountVectorThreshold("vectorizer-min-trip-count", cl::init(16),
107 cl::desc("Don't vectorize loops with a constant "
108 "trip count that is smaller than this "
111 /// We don't unroll loops with a known constant trip count below this number.
112 static const unsigned TinyTripCountUnrollThreshold = 128;
114 /// When performing a runtime memory check, do not check more than this
115 /// number of pointers. Notice that the check is quadratic!
116 static const unsigned RuntimeMemoryCheckThreshold = 4;
120 // Forward declarations.
121 class LoopVectorizationLegality;
122 class LoopVectorizationCostModel;
124 /// InnerLoopVectorizer vectorizes loops which contain only one basic
125 /// block to a specified vectorization factor (VF).
126 /// This class performs the widening of scalars into vectors, or multiple
127 /// scalars. This class also implements the following features:
128 /// * It inserts an epilogue loop for handling loops that don't have iteration
129 /// counts that are known to be a multiple of the vectorization factor.
130 /// * It handles the code generation for reduction variables.
131 /// * Scalarization (implementation using scalars) of un-vectorizable
133 /// InnerLoopVectorizer does not perform any vectorization-legality
134 /// checks, and relies on the caller to check for the different legality
135 /// aspects. The InnerLoopVectorizer relies on the
136 /// LoopVectorizationLegality class to provide information about the induction
137 /// and reduction variables that were found to a given vectorization factor.
138 class InnerLoopVectorizer {
140 InnerLoopVectorizer(Loop *OrigLoop, ScalarEvolution *SE, LoopInfo *LI,
141 DominatorTree *DT, DataLayout *DL, unsigned VecWidth,
142 unsigned UnrollFactor)
143 : OrigLoop(OrigLoop), SE(SE), LI(LI), DT(DT), DL(DL), VF(VecWidth),
144 UF(UnrollFactor), Builder(SE->getContext()), Induction(0),
145 OldInduction(0), WidenMap(UnrollFactor) {}
147 // Perform the actual loop widening (vectorization).
148 void vectorize(LoopVectorizationLegality *Legal) {
149 // Create a new empty loop. Unlink the old loop and connect the new one.
150 createEmptyLoop(Legal);
151 // Widen each instruction in the old loop to a new one in the new loop.
152 // Use the Legality module to find the induction and reduction variables.
153 vectorizeLoop(Legal);
154 // Register the new loop and update the analysis passes.
159 /// A small list of PHINodes.
160 typedef SmallVector<PHINode*, 4> PhiVector;
161 /// When we unroll loops we have multiple vector values for each scalar.
162 /// This data structure holds the unrolled and vectorized values that
163 /// originated from one scalar instruction.
164 typedef SmallVector<Value*, 2> VectorParts;
166 /// Add code that checks at runtime if the accessed arrays overlap.
167 /// Returns the comparator value or NULL if no check is needed.
168 Instruction *addRuntimeCheck(LoopVectorizationLegality *Legal,
170 /// Create an empty loop, based on the loop ranges of the old loop.
171 void createEmptyLoop(LoopVectorizationLegality *Legal);
172 /// Copy and widen the instructions from the old loop.
173 void vectorizeLoop(LoopVectorizationLegality *Legal);
175 /// A helper function that computes the predicate of the block BB, assuming
176 /// that the header block of the loop is set to True. It returns the *entry*
177 /// mask for the block BB.
178 VectorParts createBlockInMask(BasicBlock *BB);
179 /// A helper function that computes the predicate of the edge between SRC
181 VectorParts createEdgeMask(BasicBlock *Src, BasicBlock *Dst);
183 /// A helper function to vectorize a single BB within the innermost loop.
184 void vectorizeBlockInLoop(LoopVectorizationLegality *Legal, BasicBlock *BB,
187 /// Insert the new loop to the loop hierarchy and pass manager
188 /// and update the analysis passes.
189 void updateAnalysis();
191 /// This instruction is un-vectorizable. Implement it as a sequence
193 void scalarizeInstruction(Instruction *Instr);
195 /// Vectorize Load and Store instructions,
196 void vectorizeMemoryInstruction(Instruction *Instr,
197 LoopVectorizationLegality *Legal);
199 /// Create a broadcast instruction. This method generates a broadcast
200 /// instruction (shuffle) for loop invariant values and for the induction
201 /// value. If this is the induction variable then we extend it to N, N+1, ...
202 /// this is needed because each iteration in the loop corresponds to a SIMD
204 Value *getBroadcastInstrs(Value *V);
206 /// This function adds 0, 1, 2 ... to each vector element, starting at zero.
207 /// If Negate is set then negative numbers are added e.g. (0, -1, -2, ...).
208 /// The sequence starts at StartIndex.
209 Value *getConsecutiveVector(Value* Val, unsigned StartIdx, bool Negate);
211 /// When we go over instructions in the basic block we rely on previous
212 /// values within the current basic block or on loop invariant values.
213 /// When we widen (vectorize) values we place them in the map. If the values
214 /// are not within the map, they have to be loop invariant, so we simply
215 /// broadcast them into a vector.
216 VectorParts &getVectorValue(Value *V);
218 /// Generate a shuffle sequence that will reverse the vector Vec.
219 Value *reverseVector(Value *Vec);
221 /// This is a helper class that holds the vectorizer state. It maps scalar
222 /// instructions to vector instructions. When the code is 'unrolled' then
223 /// then a single scalar value is mapped to multiple vector parts. The parts
224 /// are stored in the VectorPart type.
226 /// C'tor. UnrollFactor controls the number of vectors ('parts') that
228 ValueMap(unsigned UnrollFactor) : UF(UnrollFactor) {}
230 /// \return True if 'Key' is saved in the Value Map.
231 bool has(Value *Key) const { return MapStorage.count(Key); }
233 /// Initializes a new entry in the map. Sets all of the vector parts to the
234 /// save value in 'Val'.
235 /// \return A reference to a vector with splat values.
236 VectorParts &splat(Value *Key, Value *Val) {
237 VectorParts &Entry = MapStorage[Key];
238 Entry.assign(UF, Val);
242 ///\return A reference to the value that is stored at 'Key'.
243 VectorParts &get(Value *Key) {
244 VectorParts &Entry = MapStorage[Key];
247 assert(Entry.size() == UF);
252 /// The unroll factor. Each entry in the map stores this number of vector
256 /// Map storage. We use std::map and not DenseMap because insertions to a
257 /// dense map invalidates its iterators.
258 std::map<Value *, VectorParts> MapStorage;
261 /// The original loop.
263 /// Scev analysis to use.
271 /// The vectorization SIMD factor to use. Each vector will have this many
274 /// The vectorization unroll factor to use. Each scalar is vectorized to this
275 /// many different vector instructions.
278 /// The builder that we use
281 // --- Vectorization state ---
283 /// The vector-loop preheader.
284 BasicBlock *LoopVectorPreHeader;
285 /// The scalar-loop preheader.
286 BasicBlock *LoopScalarPreHeader;
287 /// Middle Block between the vector and the scalar.
288 BasicBlock *LoopMiddleBlock;
289 ///The ExitBlock of the scalar loop.
290 BasicBlock *LoopExitBlock;
291 ///The vector loop body.
292 BasicBlock *LoopVectorBody;
293 ///The scalar loop body.
294 BasicBlock *LoopScalarBody;
295 /// A list of all bypass blocks. The first block is the entry of the loop.
296 SmallVector<BasicBlock *, 4> LoopBypassBlocks;
298 /// The new Induction variable which was added to the new block.
300 /// The induction variable of the old basic block.
301 PHINode *OldInduction;
302 /// Maps scalars to widened vectors.
306 /// LoopVectorizationLegality checks if it is legal to vectorize a loop, and
307 /// to what vectorization factor.
308 /// This class does not look at the profitability of vectorization, only the
309 /// legality. This class has two main kinds of checks:
310 /// * Memory checks - The code in canVectorizeMemory checks if vectorization
311 /// will change the order of memory accesses in a way that will change the
312 /// correctness of the program.
313 /// * Scalars checks - The code in canVectorizeInstrs and canVectorizeMemory
314 /// checks for a number of different conditions, such as the availability of a
315 /// single induction variable, that all types are supported and vectorize-able,
316 /// etc. This code reflects the capabilities of InnerLoopVectorizer.
317 /// This class is also used by InnerLoopVectorizer for identifying
318 /// induction variable and the different reduction variables.
319 class LoopVectorizationLegality {
321 LoopVectorizationLegality(Loop *L, ScalarEvolution *SE, DataLayout *DL,
322 DominatorTree *DT, TargetTransformInfo* TTI,
324 : TheLoop(L), SE(SE), DL(DL), DT(DT), TTI(TTI), AA(AA), Induction(0) {}
326 /// This enum represents the kinds of reductions that we support.
328 RK_NoReduction, ///< Not a reduction.
329 RK_IntegerAdd, ///< Sum of integers.
330 RK_IntegerMult, ///< Product of integers.
331 RK_IntegerOr, ///< Bitwise or logical OR of numbers.
332 RK_IntegerAnd, ///< Bitwise or logical AND of numbers.
333 RK_IntegerXor, ///< Bitwise or logical XOR of numbers.
334 RK_FloatAdd, ///< Sum of floats.
335 RK_FloatMult ///< Product of floats.
338 /// This enum represents the kinds of inductions that we support.
340 IK_NoInduction, ///< Not an induction variable.
341 IK_IntInduction, ///< Integer induction variable. Step = 1.
342 IK_ReverseIntInduction, ///< Reverse int induction variable. Step = -1.
343 IK_PtrInduction, ///< Pointer induction var. Step = sizeof(elem).
344 IK_ReversePtrInduction ///< Reverse ptr indvar. Step = - sizeof(elem).
347 /// This POD struct holds information about reduction variables.
348 struct ReductionDescriptor {
349 ReductionDescriptor() : StartValue(0), LoopExitInstr(0),
350 Kind(RK_NoReduction) {}
352 ReductionDescriptor(Value *Start, Instruction *Exit, ReductionKind K)
353 : StartValue(Start), LoopExitInstr(Exit), Kind(K) {}
355 // The starting value of the reduction.
356 // It does not have to be zero!
358 // The instruction who's value is used outside the loop.
359 Instruction *LoopExitInstr;
360 // The kind of the reduction.
364 // This POD struct holds information about the memory runtime legality
365 // check that a group of pointers do not overlap.
366 struct RuntimePointerCheck {
367 RuntimePointerCheck() : Need(false) {}
369 /// Reset the state of the pointer runtime information.
377 /// Insert a pointer and calculate the start and end SCEVs.
378 void insert(ScalarEvolution *SE, Loop *Lp, Value *Ptr);
380 /// This flag indicates if we need to add the runtime check.
382 /// Holds the pointers that we need to check.
383 SmallVector<Value*, 2> Pointers;
384 /// Holds the pointer value at the beginning of the loop.
385 SmallVector<const SCEV*, 2> Starts;
386 /// Holds the pointer value at the end of the loop.
387 SmallVector<const SCEV*, 2> Ends;
390 /// A POD for saving information about induction variables.
391 struct InductionInfo {
392 InductionInfo(Value *Start, InductionKind K) : StartValue(Start), IK(K) {}
393 InductionInfo() : StartValue(0), IK(IK_NoInduction) {}
400 /// ReductionList contains the reduction descriptors for all
401 /// of the reductions that were found in the loop.
402 typedef DenseMap<PHINode*, ReductionDescriptor> ReductionList;
404 /// InductionList saves induction variables and maps them to the
405 /// induction descriptor.
406 typedef MapVector<PHINode*, InductionInfo> InductionList;
408 /// Alias(Multi)Map stores the values (GEPs or underlying objects and their
409 /// respective Store/Load instruction(s) to calculate aliasing.
410 typedef DenseMap<Value*, Instruction* > AliasMap;
411 typedef DenseMap<Value*, std::vector<Instruction*> > AliasMultiMap;
413 /// Returns true if it is legal to vectorize this loop.
414 /// This does not mean that it is profitable to vectorize this
415 /// loop, only that it is legal to do so.
418 /// Returns the Induction variable.
419 PHINode *getInduction() { return Induction; }
421 /// Returns the reduction variables found in the loop.
422 ReductionList *getReductionVars() { return &Reductions; }
424 /// Returns the induction variables found in the loop.
425 InductionList *getInductionVars() { return &Inductions; }
427 /// Returns True if V is an induction variable in this loop.
428 bool isInductionVariable(const Value *V);
430 /// Return true if the block BB needs to be predicated in order for the loop
431 /// to be vectorized.
432 bool blockNeedsPredication(BasicBlock *BB);
434 /// Check if this pointer is consecutive when vectorizing. This happens
435 /// when the last index of the GEP is the induction variable, or that the
436 /// pointer itself is an induction variable.
437 /// This check allows us to vectorize A[idx] into a wide load/store.
439 /// 0 - Stride is unknown or non consecutive.
440 /// 1 - Address is consecutive.
441 /// -1 - Address is consecutive, and decreasing.
442 int isConsecutivePtr(Value *Ptr);
444 /// Returns true if the value V is uniform within the loop.
445 bool isUniform(Value *V);
447 /// Returns true if this instruction will remain scalar after vectorization.
448 bool isUniformAfterVectorization(Instruction* I) { return Uniforms.count(I); }
450 /// Returns the information that we collected about runtime memory check.
451 RuntimePointerCheck *getRuntimePointerCheck() { return &PtrRtCheck; }
453 /// Check if a single basic block loop is vectorizable.
454 /// At this point we know that this is a loop with a constant trip count
455 /// and we only need to check individual instructions.
456 bool canVectorizeInstrs();
458 /// When we vectorize loops we may change the order in which
459 /// we read and write from memory. This method checks if it is
460 /// legal to vectorize the code, considering only memory constrains.
461 /// Returns true if the loop is vectorizable
462 bool canVectorizeMemory();
464 /// Return true if we can vectorize this loop using the IF-conversion
466 bool canVectorizeWithIfConvert();
468 /// Collect the variables that need to stay uniform after vectorization.
469 void collectLoopUniforms();
471 /// Return true if all of the instructions in the block can be speculatively
473 bool blockCanBePredicated(BasicBlock *BB);
475 /// Returns True, if 'Phi' is the kind of reduction variable for type
476 /// 'Kind'. If this is a reduction variable, it adds it to ReductionList.
477 bool AddReductionVar(PHINode *Phi, ReductionKind Kind);
478 /// Returns true if the instruction I can be a reduction variable of type
480 bool isReductionInstr(Instruction *I, ReductionKind Kind);
481 /// Returns the induction kind of Phi. This function may return NoInduction
482 /// if the PHI is not an induction variable.
483 InductionKind isInductionVariable(PHINode *Phi);
484 /// Return true if can compute the address bounds of Ptr within the loop.
485 bool hasComputableBounds(Value *Ptr);
486 /// Return true if there is the chance of write reorder.
487 bool hasPossibleGlobalWriteReorder(Value *Object,
489 AliasMultiMap &WriteObjects,
490 unsigned MaxByteWidth);
491 /// Return the AA location for a load or a store.
492 AliasAnalysis::Location getLoadStoreLocation(Instruction *Inst);
495 /// The loop that we evaluate.
499 /// DataLayout analysis.
504 TargetTransformInfo *TTI;
508 // --- vectorization state --- //
510 /// Holds the integer induction variable. This is the counter of the
513 /// Holds the reduction variables.
514 ReductionList Reductions;
515 /// Holds all of the induction variables that we found in the loop.
516 /// Notice that inductions don't need to start at zero and that induction
517 /// variables can be pointers.
518 InductionList Inductions;
520 /// Allowed outside users. This holds the reduction
521 /// vars which can be accessed from outside the loop.
522 SmallPtrSet<Value*, 4> AllowedExit;
523 /// This set holds the variables which are known to be uniform after
525 SmallPtrSet<Instruction*, 4> Uniforms;
526 /// We need to check that all of the pointers in this list are disjoint
528 RuntimePointerCheck PtrRtCheck;
531 /// LoopVectorizationCostModel - estimates the expected speedups due to
533 /// In many cases vectorization is not profitable. This can happen because of
534 /// a number of reasons. In this class we mainly attempt to predict the
535 /// expected speedup/slowdowns due to the supported instruction set. We use the
536 /// TargetTransformInfo to query the different backends for the cost of
537 /// different operations.
538 class LoopVectorizationCostModel {
540 LoopVectorizationCostModel(Loop *L, ScalarEvolution *SE, LoopInfo *LI,
541 LoopVectorizationLegality *Legal,
542 const TargetTransformInfo &TTI,
544 : TheLoop(L), SE(SE), LI(LI), Legal(Legal), TTI(TTI), DL(DL) {}
546 /// Information about vectorization costs
547 struct VectorizationFactor {
548 unsigned Width; // Vector width with best cost
549 unsigned Cost; // Cost of the loop with that width
551 /// \return The most profitable vectorization factor and the cost of that VF.
552 /// This method checks every power of two up to VF. If UserVF is not ZERO
553 /// then this vectorization factor will be selected if vectorization is
555 VectorizationFactor selectVectorizationFactor(bool OptForSize,
558 /// \return The size (in bits) of the widest type in the code that
559 /// needs to be vectorized. We ignore values that remain scalar such as
560 /// 64 bit loop indices.
561 unsigned getWidestType();
563 /// \return The most profitable unroll factor.
564 /// If UserUF is non-zero then this method finds the best unroll-factor
565 /// based on register pressure and other parameters.
566 /// VF and LoopCost are the selected vectorization factor and the cost of the
568 unsigned selectUnrollFactor(bool OptForSize, unsigned UserUF, unsigned VF,
571 /// \brief A struct that represents some properties of the register usage
573 struct RegisterUsage {
574 /// Holds the number of loop invariant values that are used in the loop.
575 unsigned LoopInvariantRegs;
576 /// Holds the maximum number of concurrent live intervals in the loop.
577 unsigned MaxLocalUsers;
578 /// Holds the number of instructions in the loop.
579 unsigned NumInstructions;
582 /// \return information about the register usage of the loop.
583 RegisterUsage calculateRegisterUsage();
586 /// Returns the expected execution cost. The unit of the cost does
587 /// not matter because we use the 'cost' units to compare different
588 /// vector widths. The cost that is returned is *not* normalized by
589 /// the factor width.
590 unsigned expectedCost(unsigned VF);
592 /// Returns the execution time cost of an instruction for a given vector
593 /// width. Vector width of one means scalar.
594 unsigned getInstructionCost(Instruction *I, unsigned VF);
596 /// A helper function for converting Scalar types to vector types.
597 /// If the incoming type is void, we return void. If the VF is 1, we return
599 static Type* ToVectorTy(Type *Scalar, unsigned VF);
601 /// Returns whether the instruction is a load or store and will be a emitted
602 /// as a vector operation.
603 bool isConsecutiveLoadOrStore(Instruction *I);
605 /// The loop that we evaluate.
609 /// Loop Info analysis.
611 /// Vectorization legality.
612 LoopVectorizationLegality *Legal;
613 /// Vector target information.
614 const TargetTransformInfo &TTI;
615 /// Target data layout information.
619 /// The LoopVectorize Pass.
620 struct LoopVectorize : public LoopPass {
621 /// Pass identification, replacement for typeid
624 explicit LoopVectorize() : LoopPass(ID) {
625 initializeLoopVectorizePass(*PassRegistry::getPassRegistry());
631 TargetTransformInfo *TTI;
635 virtual bool runOnLoop(Loop *L, LPPassManager &LPM) {
636 // We only vectorize innermost loops.
640 SE = &getAnalysis<ScalarEvolution>();
641 DL = getAnalysisIfAvailable<DataLayout>();
642 LI = &getAnalysis<LoopInfo>();
643 TTI = &getAnalysis<TargetTransformInfo>();
644 DT = &getAnalysis<DominatorTree>();
645 AA = getAnalysisIfAvailable<AliasAnalysis>();
647 DEBUG(dbgs() << "LV: Checking a loop in \"" <<
648 L->getHeader()->getParent()->getName() << "\"\n");
650 // Check if it is legal to vectorize the loop.
651 LoopVectorizationLegality LVL(L, SE, DL, DT, TTI, AA);
652 if (!LVL.canVectorize()) {
653 DEBUG(dbgs() << "LV: Not vectorizing.\n");
657 // Use the cost model.
658 LoopVectorizationCostModel CM(L, SE, LI, &LVL, *TTI, DL);
660 // Check the function attributes to find out if this function should be
661 // optimized for size.
662 Function *F = L->getHeader()->getParent();
663 Attribute::AttrKind SzAttr = Attribute::OptimizeForSize;
664 Attribute::AttrKind FlAttr = Attribute::NoImplicitFloat;
665 unsigned FnIndex = AttributeSet::FunctionIndex;
666 bool OptForSize = F->getAttributes().hasAttribute(FnIndex, SzAttr);
667 bool NoFloat = F->getAttributes().hasAttribute(FnIndex, FlAttr);
670 DEBUG(dbgs() << "LV: Can't vectorize when the NoImplicitFloat"
671 "attribute is used.\n");
675 // Select the optimal vectorization factor.
676 LoopVectorizationCostModel::VectorizationFactor VF;
677 VF = CM.selectVectorizationFactor(OptForSize, VectorizationFactor);
678 // Select the unroll factor.
679 unsigned UF = CM.selectUnrollFactor(OptForSize, VectorizationUnroll,
683 DEBUG(dbgs() << "LV: Vectorization is possible but not beneficial.\n");
687 DEBUG(dbgs() << "LV: Found a vectorizable loop ("<< VF.Width << ") in "<<
688 F->getParent()->getModuleIdentifier()<<"\n");
689 DEBUG(dbgs() << "LV: Unroll Factor is " << UF << "\n");
691 // If we decided that it is *legal* to vectorize the loop then do it.
692 InnerLoopVectorizer LB(L, SE, LI, DT, DL, VF.Width, UF);
695 DEBUG(verifyFunction(*L->getHeader()->getParent()));
699 virtual void getAnalysisUsage(AnalysisUsage &AU) const {
700 LoopPass::getAnalysisUsage(AU);
701 AU.addRequiredID(LoopSimplifyID);
702 AU.addRequiredID(LCSSAID);
703 AU.addRequired<DominatorTree>();
704 AU.addRequired<LoopInfo>();
705 AU.addRequired<ScalarEvolution>();
706 AU.addRequired<TargetTransformInfo>();
707 AU.addPreserved<LoopInfo>();
708 AU.addPreserved<DominatorTree>();
713 } // end anonymous namespace
715 //===----------------------------------------------------------------------===//
716 // Implementation of LoopVectorizationLegality, InnerLoopVectorizer and
717 // LoopVectorizationCostModel.
718 //===----------------------------------------------------------------------===//
721 LoopVectorizationLegality::RuntimePointerCheck::insert(ScalarEvolution *SE,
722 Loop *Lp, Value *Ptr) {
723 const SCEV *Sc = SE->getSCEV(Ptr);
724 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Sc);
725 assert(AR && "Invalid addrec expression");
726 const SCEV *Ex = SE->getExitCount(Lp, Lp->getLoopLatch());
727 const SCEV *ScEnd = AR->evaluateAtIteration(Ex, *SE);
728 Pointers.push_back(Ptr);
729 Starts.push_back(AR->getStart());
730 Ends.push_back(ScEnd);
733 Value *InnerLoopVectorizer::getBroadcastInstrs(Value *V) {
734 // Save the current insertion location.
735 Instruction *Loc = Builder.GetInsertPoint();
737 // We need to place the broadcast of invariant variables outside the loop.
738 Instruction *Instr = dyn_cast<Instruction>(V);
739 bool NewInstr = (Instr && Instr->getParent() == LoopVectorBody);
740 bool Invariant = OrigLoop->isLoopInvariant(V) && !NewInstr;
742 // Place the code for broadcasting invariant variables in the new preheader.
744 Builder.SetInsertPoint(LoopVectorPreHeader->getTerminator());
746 // Broadcast the scalar into all locations in the vector.
747 Value *Shuf = Builder.CreateVectorSplat(VF, V, "broadcast");
749 // Restore the builder insertion point.
751 Builder.SetInsertPoint(Loc);
756 Value *InnerLoopVectorizer::getConsecutiveVector(Value* Val, unsigned StartIdx,
758 assert(Val->getType()->isVectorTy() && "Must be a vector");
759 assert(Val->getType()->getScalarType()->isIntegerTy() &&
760 "Elem must be an integer");
762 Type *ITy = Val->getType()->getScalarType();
763 VectorType *Ty = cast<VectorType>(Val->getType());
764 int VLen = Ty->getNumElements();
765 SmallVector<Constant*, 8> Indices;
767 // Create a vector of consecutive numbers from zero to VF.
768 for (int i = 0; i < VLen; ++i) {
769 int Idx = Negate ? (-i): i;
770 Indices.push_back(ConstantInt::get(ITy, StartIdx + Idx));
773 // Add the consecutive indices to the vector value.
774 Constant *Cv = ConstantVector::get(Indices);
775 assert(Cv->getType() == Val->getType() && "Invalid consecutive vec");
776 return Builder.CreateAdd(Val, Cv, "induction");
779 int LoopVectorizationLegality::isConsecutivePtr(Value *Ptr) {
780 assert(Ptr->getType()->isPointerTy() && "Unexpected non ptr");
781 // Make sure that the pointer does not point to structs.
782 if (cast<PointerType>(Ptr->getType())->getElementType()->isAggregateType())
785 // If this value is a pointer induction variable we know it is consecutive.
786 PHINode *Phi = dyn_cast_or_null<PHINode>(Ptr);
787 if (Phi && Inductions.count(Phi)) {
788 InductionInfo II = Inductions[Phi];
789 if (IK_PtrInduction == II.IK)
791 else if (IK_ReversePtrInduction == II.IK)
795 GetElementPtrInst *Gep = dyn_cast_or_null<GetElementPtrInst>(Ptr);
799 unsigned NumOperands = Gep->getNumOperands();
800 Value *LastIndex = Gep->getOperand(NumOperands - 1);
802 Value *GpPtr = Gep->getPointerOperand();
803 // If this GEP value is a consecutive pointer induction variable and all of
804 // the indices are constant then we know it is consecutive. We can
805 Phi = dyn_cast<PHINode>(GpPtr);
806 if (Phi && Inductions.count(Phi)) {
808 // Make sure that the pointer does not point to structs.
809 PointerType *GepPtrType = cast<PointerType>(GpPtr->getType());
810 if (GepPtrType->getElementType()->isAggregateType())
813 // Make sure that all of the index operands are loop invariant.
814 for (unsigned i = 1; i < NumOperands; ++i)
815 if (!SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop))
818 InductionInfo II = Inductions[Phi];
819 if (IK_PtrInduction == II.IK)
821 else if (IK_ReversePtrInduction == II.IK)
825 // Check that all of the gep indices are uniform except for the last.
826 for (unsigned i = 0; i < NumOperands - 1; ++i)
827 if (!SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop))
830 // We can emit wide load/stores only if the last index is the induction
832 const SCEV *Last = SE->getSCEV(LastIndex);
833 if (const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Last)) {
834 const SCEV *Step = AR->getStepRecurrence(*SE);
836 // The memory is consecutive because the last index is consecutive
837 // and all other indices are loop invariant.
840 if (Step->isAllOnesValue())
847 bool LoopVectorizationLegality::isUniform(Value *V) {
848 return (SE->isLoopInvariant(SE->getSCEV(V), TheLoop));
851 InnerLoopVectorizer::VectorParts&
852 InnerLoopVectorizer::getVectorValue(Value *V) {
853 assert(V != Induction && "The new induction variable should not be used.");
854 assert(!V->getType()->isVectorTy() && "Can't widen a vector");
856 // If we have this scalar in the map, return it.
858 return WidenMap.get(V);
860 // If this scalar is unknown, assume that it is a constant or that it is
861 // loop invariant. Broadcast V and save the value for future uses.
862 Value *B = getBroadcastInstrs(V);
863 return WidenMap.splat(V, B);
866 Value *InnerLoopVectorizer::reverseVector(Value *Vec) {
867 assert(Vec->getType()->isVectorTy() && "Invalid type");
868 SmallVector<Constant*, 8> ShuffleMask;
869 for (unsigned i = 0; i < VF; ++i)
870 ShuffleMask.push_back(Builder.getInt32(VF - i - 1));
872 return Builder.CreateShuffleVector(Vec, UndefValue::get(Vec->getType()),
873 ConstantVector::get(ShuffleMask),
878 void InnerLoopVectorizer::vectorizeMemoryInstruction(Instruction *Instr,
879 LoopVectorizationLegality *Legal) {
880 // Attempt to issue a wide load.
881 LoadInst *LI = dyn_cast<LoadInst>(Instr);
882 StoreInst *SI = dyn_cast<StoreInst>(Instr);
884 assert((LI || SI) && "Invalid Load/Store instruction");
886 Type *ScalarDataTy = LI ? LI->getType() : SI->getValueOperand()->getType();
887 Type *DataTy = VectorType::get(ScalarDataTy, VF);
888 Value *Ptr = LI ? LI->getPointerOperand() : SI->getPointerOperand();
889 unsigned Alignment = LI ? LI->getAlignment() : SI->getAlignment();
891 // If the pointer is loop invariant or if it is non consecutive,
892 // scalarize the load.
893 int Stride = Legal->isConsecutivePtr(Ptr);
894 bool Reverse = Stride < 0;
895 bool UniformLoad = LI && Legal->isUniform(Ptr);
896 if (Stride == 0 || UniformLoad)
897 return scalarizeInstruction(Instr);
899 Constant *Zero = Builder.getInt32(0);
900 VectorParts &Entry = WidenMap.get(Instr);
902 // Handle consecutive loads/stores.
903 GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr);
904 if (Gep && Legal->isInductionVariable(Gep->getPointerOperand())) {
905 Value *PtrOperand = Gep->getPointerOperand();
906 Value *FirstBasePtr = getVectorValue(PtrOperand)[0];
907 FirstBasePtr = Builder.CreateExtractElement(FirstBasePtr, Zero);
909 // Create the new GEP with the new induction variable.
910 GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone());
911 Gep2->setOperand(0, FirstBasePtr);
912 Gep2->setName("gep.indvar.base");
913 Ptr = Builder.Insert(Gep2);
915 assert(SE->isLoopInvariant(SE->getSCEV(Gep->getPointerOperand()),
916 OrigLoop) && "Base ptr must be invariant");
918 // The last index does not have to be the induction. It can be
919 // consecutive and be a function of the index. For example A[I+1];
920 unsigned NumOperands = Gep->getNumOperands();
922 Value *LastGepOperand = Gep->getOperand(NumOperands - 1);
923 VectorParts &GEPParts = getVectorValue(LastGepOperand);
924 Value *LastIndex = GEPParts[0];
925 LastIndex = Builder.CreateExtractElement(LastIndex, Zero);
927 // Create the new GEP with the new induction variable.
928 GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone());
929 Gep2->setOperand(NumOperands - 1, LastIndex);
930 Gep2->setName("gep.indvar.idx");
931 Ptr = Builder.Insert(Gep2);
933 // Use the induction element ptr.
934 assert(isa<PHINode>(Ptr) && "Invalid induction ptr");
935 VectorParts &PtrVal = getVectorValue(Ptr);
936 Ptr = Builder.CreateExtractElement(PtrVal[0], Zero);
941 assert(!Legal->isUniform(SI->getPointerOperand()) &&
942 "We do not allow storing to uniform addresses");
944 VectorParts &StoredVal = getVectorValue(SI->getValueOperand());
945 for (unsigned Part = 0; Part < UF; ++Part) {
946 // Calculate the pointer for the specific unroll-part.
947 Value *PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(Part * VF));
950 // If we store to reverse consecutive memory locations then we need
951 // to reverse the order of elements in the stored value.
952 StoredVal[Part] = reverseVector(StoredVal[Part]);
953 // If the address is consecutive but reversed, then the
954 // wide store needs to start at the last vector element.
955 PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(-Part * VF));
956 PartPtr = Builder.CreateGEP(PartPtr, Builder.getInt32(1 - VF));
959 Value *VecPtr = Builder.CreateBitCast(PartPtr, DataTy->getPointerTo());
960 Builder.CreateStore(StoredVal[Part], VecPtr)->setAlignment(Alignment);
964 for (unsigned Part = 0; Part < UF; ++Part) {
965 // Calculate the pointer for the specific unroll-part.
966 Value *PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(Part * VF));
969 // If the address is consecutive but reversed, then the
970 // wide store needs to start at the last vector element.
971 PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(-Part * VF));
972 PartPtr = Builder.CreateGEP(PartPtr, Builder.getInt32(1 - VF));
975 Value *VecPtr = Builder.CreateBitCast(PartPtr, DataTy->getPointerTo());
976 Value *LI = Builder.CreateLoad(VecPtr, "wide.load");
977 cast<LoadInst>(LI)->setAlignment(Alignment);
978 Entry[Part] = Reverse ? reverseVector(LI) : LI;
982 void InnerLoopVectorizer::scalarizeInstruction(Instruction *Instr) {
983 assert(!Instr->getType()->isAggregateType() && "Can't handle vectors");
984 // Holds vector parameters or scalars, in case of uniform vals.
985 SmallVector<VectorParts, 4> Params;
987 // Find all of the vectorized parameters.
988 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
989 Value *SrcOp = Instr->getOperand(op);
991 // If we are accessing the old induction variable, use the new one.
992 if (SrcOp == OldInduction) {
993 Params.push_back(getVectorValue(SrcOp));
997 // Try using previously calculated values.
998 Instruction *SrcInst = dyn_cast<Instruction>(SrcOp);
1000 // If the src is an instruction that appeared earlier in the basic block
1001 // then it should already be vectorized.
1002 if (SrcInst && OrigLoop->contains(SrcInst)) {
1003 assert(WidenMap.has(SrcInst) && "Source operand is unavailable");
1004 // The parameter is a vector value from earlier.
1005 Params.push_back(WidenMap.get(SrcInst));
1007 // The parameter is a scalar from outside the loop. Maybe even a constant.
1008 VectorParts Scalars;
1009 Scalars.append(UF, SrcOp);
1010 Params.push_back(Scalars);
1014 assert(Params.size() == Instr->getNumOperands() &&
1015 "Invalid number of operands");
1017 // Does this instruction return a value ?
1018 bool IsVoidRetTy = Instr->getType()->isVoidTy();
1020 Value *UndefVec = IsVoidRetTy ? 0 :
1021 UndefValue::get(VectorType::get(Instr->getType(), VF));
1022 // Create a new entry in the WidenMap and initialize it to Undef or Null.
1023 VectorParts &VecResults = WidenMap.splat(Instr, UndefVec);
1025 // For each scalar that we create:
1026 for (unsigned Width = 0; Width < VF; ++Width) {
1027 // For each vector unroll 'part':
1028 for (unsigned Part = 0; Part < UF; ++Part) {
1029 Instruction *Cloned = Instr->clone();
1031 Cloned->setName(Instr->getName() + ".cloned");
1032 // Replace the operands of the cloned instrucions with extracted scalars.
1033 for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
1034 Value *Op = Params[op][Part];
1035 // Param is a vector. Need to extract the right lane.
1036 if (Op->getType()->isVectorTy())
1037 Op = Builder.CreateExtractElement(Op, Builder.getInt32(Width));
1038 Cloned->setOperand(op, Op);
1041 // Place the cloned scalar in the new loop.
1042 Builder.Insert(Cloned);
1044 // If the original scalar returns a value we need to place it in a vector
1045 // so that future users will be able to use it.
1047 VecResults[Part] = Builder.CreateInsertElement(VecResults[Part], Cloned,
1048 Builder.getInt32(Width));
1054 InnerLoopVectorizer::addRuntimeCheck(LoopVectorizationLegality *Legal,
1056 LoopVectorizationLegality::RuntimePointerCheck *PtrRtCheck =
1057 Legal->getRuntimePointerCheck();
1059 if (!PtrRtCheck->Need)
1062 Instruction *MemoryRuntimeCheck = 0;
1063 unsigned NumPointers = PtrRtCheck->Pointers.size();
1064 SmallVector<Value* , 2> Starts;
1065 SmallVector<Value* , 2> Ends;
1067 SCEVExpander Exp(*SE, "induction");
1069 // Use this type for pointer arithmetic.
1070 Type* PtrArithTy = Type::getInt8PtrTy(Loc->getContext(), 0);
1072 for (unsigned i = 0; i < NumPointers; ++i) {
1073 Value *Ptr = PtrRtCheck->Pointers[i];
1074 const SCEV *Sc = SE->getSCEV(Ptr);
1076 if (SE->isLoopInvariant(Sc, OrigLoop)) {
1077 DEBUG(dbgs() << "LV: Adding RT check for a loop invariant ptr:" <<
1079 Starts.push_back(Ptr);
1080 Ends.push_back(Ptr);
1082 DEBUG(dbgs() << "LV: Adding RT check for range:" << *Ptr <<"\n");
1084 Value *Start = Exp.expandCodeFor(PtrRtCheck->Starts[i], PtrArithTy, Loc);
1085 Value *End = Exp.expandCodeFor(PtrRtCheck->Ends[i], PtrArithTy, Loc);
1086 Starts.push_back(Start);
1087 Ends.push_back(End);
1091 IRBuilder<> ChkBuilder(Loc);
1093 for (unsigned i = 0; i < NumPointers; ++i) {
1094 for (unsigned j = i+1; j < NumPointers; ++j) {
1095 Value *Start0 = ChkBuilder.CreateBitCast(Starts[i], PtrArithTy, "bc");
1096 Value *Start1 = ChkBuilder.CreateBitCast(Starts[j], PtrArithTy, "bc");
1097 Value *End0 = ChkBuilder.CreateBitCast(Ends[i], PtrArithTy, "bc");
1098 Value *End1 = ChkBuilder.CreateBitCast(Ends[j], PtrArithTy, "bc");
1100 Value *Cmp0 = ChkBuilder.CreateICmpULE(Start0, End1, "bound0");
1101 Value *Cmp1 = ChkBuilder.CreateICmpULE(Start1, End0, "bound1");
1102 Value *IsConflict = ChkBuilder.CreateAnd(Cmp0, Cmp1, "found.conflict");
1103 if (MemoryRuntimeCheck)
1104 IsConflict = ChkBuilder.CreateOr(MemoryRuntimeCheck, IsConflict,
1107 MemoryRuntimeCheck = cast<Instruction>(IsConflict);
1111 return MemoryRuntimeCheck;
1115 InnerLoopVectorizer::createEmptyLoop(LoopVectorizationLegality *Legal) {
1117 In this function we generate a new loop. The new loop will contain
1118 the vectorized instructions while the old loop will continue to run the
1121 [ ] <-- vector loop bypass (may consist of multiple blocks).
1124 | [ ] <-- vector pre header.
1128 | [ ]_| <-- vector loop.
1131 >[ ] <--- middle-block.
1134 | [ ] <--- new preheader.
1138 | [ ]_| <-- old scalar loop to handle remainder.
1141 >[ ] <-- exit block.
1145 BasicBlock *OldBasicBlock = OrigLoop->getHeader();
1146 BasicBlock *BypassBlock = OrigLoop->getLoopPreheader();
1147 BasicBlock *ExitBlock = OrigLoop->getExitBlock();
1148 assert(ExitBlock && "Must have an exit block");
1150 // Some loops have a single integer induction variable, while other loops
1151 // don't. One example is c++ iterators that often have multiple pointer
1152 // induction variables. In the code below we also support a case where we
1153 // don't have a single induction variable.
1154 OldInduction = Legal->getInduction();
1155 Type *IdxTy = OldInduction ? OldInduction->getType() :
1156 DL->getIntPtrType(SE->getContext());
1158 // Find the loop boundaries.
1159 const SCEV *ExitCount = SE->getExitCount(OrigLoop, OrigLoop->getLoopLatch());
1160 assert(ExitCount != SE->getCouldNotCompute() && "Invalid loop count");
1162 // Get the total trip count from the count by adding 1.
1163 ExitCount = SE->getAddExpr(ExitCount,
1164 SE->getConstant(ExitCount->getType(), 1));
1166 // Expand the trip count and place the new instructions in the preheader.
1167 // Notice that the pre-header does not change, only the loop body.
1168 SCEVExpander Exp(*SE, "induction");
1170 // Count holds the overall loop count (N).
1171 Value *Count = Exp.expandCodeFor(ExitCount, ExitCount->getType(),
1172 BypassBlock->getTerminator());
1174 // The loop index does not have to start at Zero. Find the original start
1175 // value from the induction PHI node. If we don't have an induction variable
1176 // then we know that it starts at zero.
1177 Value *StartIdx = OldInduction ?
1178 OldInduction->getIncomingValueForBlock(BypassBlock):
1179 ConstantInt::get(IdxTy, 0);
1181 assert(BypassBlock && "Invalid loop structure");
1182 LoopBypassBlocks.push_back(BypassBlock);
1184 // Split the single block loop into the two loop structure described above.
1185 BasicBlock *VectorPH =
1186 BypassBlock->splitBasicBlock(BypassBlock->getTerminator(), "vector.ph");
1187 BasicBlock *VecBody =
1188 VectorPH->splitBasicBlock(VectorPH->getTerminator(), "vector.body");
1189 BasicBlock *MiddleBlock =
1190 VecBody->splitBasicBlock(VecBody->getTerminator(), "middle.block");
1191 BasicBlock *ScalarPH =
1192 MiddleBlock->splitBasicBlock(MiddleBlock->getTerminator(), "scalar.ph");
1194 // Use this IR builder to create the loop instructions (Phi, Br, Cmp)
1196 Builder.SetInsertPoint(VecBody->getFirstInsertionPt());
1198 // Generate the induction variable.
1199 Induction = Builder.CreatePHI(IdxTy, 2, "index");
1200 // The loop step is equal to the vectorization factor (num of SIMD elements)
1201 // times the unroll factor (num of SIMD instructions).
1202 Constant *Step = ConstantInt::get(IdxTy, VF * UF);
1204 // This is the IR builder that we use to add all of the logic for bypassing
1205 // the new vector loop.
1206 IRBuilder<> BypassBuilder(BypassBlock->getTerminator());
1208 // We may need to extend the index in case there is a type mismatch.
1209 // We know that the count starts at zero and does not overflow.
1210 if (Count->getType() != IdxTy) {
1211 // The exit count can be of pointer type. Convert it to the correct
1213 if (ExitCount->getType()->isPointerTy())
1214 Count = BypassBuilder.CreatePointerCast(Count, IdxTy, "ptrcnt.to.int");
1216 Count = BypassBuilder.CreateZExtOrTrunc(Count, IdxTy, "cnt.cast");
1219 // Add the start index to the loop count to get the new end index.
1220 Value *IdxEnd = BypassBuilder.CreateAdd(Count, StartIdx, "end.idx");
1222 // Now we need to generate the expression for N - (N % VF), which is
1223 // the part that the vectorized body will execute.
1224 Value *R = BypassBuilder.CreateURem(Count, Step, "n.mod.vf");
1225 Value *CountRoundDown = BypassBuilder.CreateSub(Count, R, "n.vec");
1226 Value *IdxEndRoundDown = BypassBuilder.CreateAdd(CountRoundDown, StartIdx,
1227 "end.idx.rnd.down");
1229 // Now, compare the new count to zero. If it is zero skip the vector loop and
1230 // jump to the scalar loop.
1231 Value *Cmp = BypassBuilder.CreateICmpEQ(IdxEndRoundDown, StartIdx,
1234 BasicBlock *LastBypassBlock = BypassBlock;
1236 // Generate the code that checks in runtime if arrays overlap. We put the
1237 // checks into a separate block to make the more common case of few elements
1239 Instruction *MemRuntimeCheck = addRuntimeCheck(Legal,
1240 BypassBlock->getTerminator());
1241 if (MemRuntimeCheck) {
1242 // Create a new block containing the memory check.
1243 BasicBlock *CheckBlock = BypassBlock->splitBasicBlock(MemRuntimeCheck,
1245 LoopBypassBlocks.push_back(CheckBlock);
1247 // Replace the branch into the memory check block with a conditional branch
1248 // for the "few elements case".
1249 Instruction *OldTerm = BypassBlock->getTerminator();
1250 BranchInst::Create(MiddleBlock, CheckBlock, Cmp, OldTerm);
1251 OldTerm->eraseFromParent();
1253 Cmp = MemRuntimeCheck;
1254 LastBypassBlock = CheckBlock;
1257 LastBypassBlock->getTerminator()->eraseFromParent();
1258 BranchInst::Create(MiddleBlock, VectorPH, Cmp,
1261 // We are going to resume the execution of the scalar loop.
1262 // Go over all of the induction variables that we found and fix the
1263 // PHIs that are left in the scalar version of the loop.
1264 // The starting values of PHI nodes depend on the counter of the last
1265 // iteration in the vectorized loop.
1266 // If we come from a bypass edge then we need to start from the original
1269 // This variable saves the new starting index for the scalar loop.
1270 PHINode *ResumeIndex = 0;
1271 LoopVectorizationLegality::InductionList::iterator I, E;
1272 LoopVectorizationLegality::InductionList *List = Legal->getInductionVars();
1273 for (I = List->begin(), E = List->end(); I != E; ++I) {
1274 PHINode *OrigPhi = I->first;
1275 LoopVectorizationLegality::InductionInfo II = I->second;
1276 PHINode *ResumeVal = PHINode::Create(OrigPhi->getType(), 2, "resume.val",
1277 MiddleBlock->getTerminator());
1278 Value *EndValue = 0;
1280 case LoopVectorizationLegality::IK_NoInduction:
1281 llvm_unreachable("Unknown induction");
1282 case LoopVectorizationLegality::IK_IntInduction: {
1283 // Handle the integer induction counter:
1284 assert(OrigPhi->getType()->isIntegerTy() && "Invalid type");
1285 assert(OrigPhi == OldInduction && "Unknown integer PHI");
1286 // We know what the end value is.
1287 EndValue = IdxEndRoundDown;
1288 // We also know which PHI node holds it.
1289 ResumeIndex = ResumeVal;
1292 case LoopVectorizationLegality::IK_ReverseIntInduction: {
1293 // Convert the CountRoundDown variable to the PHI size.
1294 unsigned CRDSize = CountRoundDown->getType()->getScalarSizeInBits();
1295 unsigned IISize = II.StartValue->getType()->getScalarSizeInBits();
1296 Value *CRD = CountRoundDown;
1297 if (CRDSize > IISize)
1298 CRD = CastInst::Create(Instruction::Trunc, CountRoundDown,
1299 II.StartValue->getType(), "tr.crd",
1300 LoopBypassBlocks.back()->getTerminator());
1301 else if (CRDSize < IISize)
1302 CRD = CastInst::Create(Instruction::SExt, CountRoundDown,
1303 II.StartValue->getType(),
1305 LoopBypassBlocks.back()->getTerminator());
1306 // Handle reverse integer induction counter:
1308 BinaryOperator::CreateSub(II.StartValue, CRD, "rev.ind.end",
1309 LoopBypassBlocks.back()->getTerminator());
1312 case LoopVectorizationLegality::IK_PtrInduction: {
1313 // For pointer induction variables, calculate the offset using
1316 GetElementPtrInst::Create(II.StartValue, CountRoundDown, "ptr.ind.end",
1317 LoopBypassBlocks.back()->getTerminator());
1320 case LoopVectorizationLegality::IK_ReversePtrInduction: {
1321 // The value at the end of the loop for the reverse pointer is calculated
1322 // by creating a GEP with a negative index starting from the start value.
1323 Value *Zero = ConstantInt::get(CountRoundDown->getType(), 0);
1324 Value *NegIdx = BinaryOperator::CreateSub(Zero, CountRoundDown,
1326 LoopBypassBlocks.back()->getTerminator());
1327 EndValue = GetElementPtrInst::Create(II.StartValue, NegIdx,
1329 LoopBypassBlocks.back()->getTerminator());
1334 // The new PHI merges the original incoming value, in case of a bypass,
1335 // or the value at the end of the vectorized loop.
1336 for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I)
1337 ResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]);
1338 ResumeVal->addIncoming(EndValue, VecBody);
1340 // Fix the scalar body counter (PHI node).
1341 unsigned BlockIdx = OrigPhi->getBasicBlockIndex(ScalarPH);
1342 OrigPhi->setIncomingValue(BlockIdx, ResumeVal);
1345 // If we are generating a new induction variable then we also need to
1346 // generate the code that calculates the exit value. This value is not
1347 // simply the end of the counter because we may skip the vectorized body
1348 // in case of a runtime check.
1350 assert(!ResumeIndex && "Unexpected resume value found");
1351 ResumeIndex = PHINode::Create(IdxTy, 2, "new.indc.resume.val",
1352 MiddleBlock->getTerminator());
1353 for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I)
1354 ResumeIndex->addIncoming(StartIdx, LoopBypassBlocks[I]);
1355 ResumeIndex->addIncoming(IdxEndRoundDown, VecBody);
1358 // Make sure that we found the index where scalar loop needs to continue.
1359 assert(ResumeIndex && ResumeIndex->getType()->isIntegerTy() &&
1360 "Invalid resume Index");
1362 // Add a check in the middle block to see if we have completed
1363 // all of the iterations in the first vector loop.
1364 // If (N - N%VF) == N, then we *don't* need to run the remainder.
1365 Value *CmpN = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ, IdxEnd,
1366 ResumeIndex, "cmp.n",
1367 MiddleBlock->getTerminator());
1369 BranchInst::Create(ExitBlock, ScalarPH, CmpN, MiddleBlock->getTerminator());
1370 // Remove the old terminator.
1371 MiddleBlock->getTerminator()->eraseFromParent();
1373 // Create i+1 and fill the PHINode.
1374 Value *NextIdx = Builder.CreateAdd(Induction, Step, "index.next");
1375 Induction->addIncoming(StartIdx, VectorPH);
1376 Induction->addIncoming(NextIdx, VecBody);
1377 // Create the compare.
1378 Value *ICmp = Builder.CreateICmpEQ(NextIdx, IdxEndRoundDown);
1379 Builder.CreateCondBr(ICmp, MiddleBlock, VecBody);
1381 // Now we have two terminators. Remove the old one from the block.
1382 VecBody->getTerminator()->eraseFromParent();
1384 // Get ready to start creating new instructions into the vectorized body.
1385 Builder.SetInsertPoint(VecBody->getFirstInsertionPt());
1387 // Create and register the new vector loop.
1388 Loop* Lp = new Loop();
1389 Loop *ParentLoop = OrigLoop->getParentLoop();
1391 // Insert the new loop into the loop nest and register the new basic blocks.
1393 ParentLoop->addChildLoop(Lp);
1394 for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I)
1395 ParentLoop->addBasicBlockToLoop(LoopBypassBlocks[I], LI->getBase());
1396 ParentLoop->addBasicBlockToLoop(ScalarPH, LI->getBase());
1397 ParentLoop->addBasicBlockToLoop(VectorPH, LI->getBase());
1398 ParentLoop->addBasicBlockToLoop(MiddleBlock, LI->getBase());
1400 LI->addTopLevelLoop(Lp);
1403 Lp->addBasicBlockToLoop(VecBody, LI->getBase());
1406 LoopVectorPreHeader = VectorPH;
1407 LoopScalarPreHeader = ScalarPH;
1408 LoopMiddleBlock = MiddleBlock;
1409 LoopExitBlock = ExitBlock;
1410 LoopVectorBody = VecBody;
1411 LoopScalarBody = OldBasicBlock;
1414 /// This function returns the identity element (or neutral element) for
1415 /// the operation K.
1417 getReductionIdentity(LoopVectorizationLegality::ReductionKind K, Type *Tp) {
1419 case LoopVectorizationLegality:: RK_IntegerXor:
1420 case LoopVectorizationLegality:: RK_IntegerAdd:
1421 case LoopVectorizationLegality:: RK_IntegerOr:
1422 // Adding, Xoring, Oring zero to a number does not change it.
1423 return ConstantInt::get(Tp, 0);
1424 case LoopVectorizationLegality:: RK_IntegerMult:
1425 // Multiplying a number by 1 does not change it.
1426 return ConstantInt::get(Tp, 1);
1427 case LoopVectorizationLegality:: RK_IntegerAnd:
1428 // AND-ing a number with an all-1 value does not change it.
1429 return ConstantInt::get(Tp, -1, true);
1430 case LoopVectorizationLegality:: RK_FloatMult:
1431 // Multiplying a number by 1 does not change it.
1432 return ConstantFP::get(Tp, 1.0L);
1433 case LoopVectorizationLegality:: RK_FloatAdd:
1434 // Adding zero to a number does not change it.
1435 return ConstantFP::get(Tp, 0.0L);
1437 llvm_unreachable("Unknown reduction kind");
1442 isTriviallyVectorizableIntrinsic(Instruction *Inst) {
1443 IntrinsicInst *II = dyn_cast<IntrinsicInst>(Inst);
1446 switch (II->getIntrinsicID()) {
1447 case Intrinsic::sqrt:
1448 case Intrinsic::sin:
1449 case Intrinsic::cos:
1450 case Intrinsic::exp:
1451 case Intrinsic::exp2:
1452 case Intrinsic::log:
1453 case Intrinsic::log10:
1454 case Intrinsic::log2:
1455 case Intrinsic::fabs:
1456 case Intrinsic::floor:
1457 case Intrinsic::ceil:
1458 case Intrinsic::trunc:
1459 case Intrinsic::rint:
1460 case Intrinsic::nearbyint:
1461 case Intrinsic::pow:
1462 case Intrinsic::fma:
1463 case Intrinsic::fmuladd:
1471 /// This function translates the reduction kind to an LLVM binary operator.
1472 static Instruction::BinaryOps
1473 getReductionBinOp(LoopVectorizationLegality::ReductionKind Kind) {
1475 case LoopVectorizationLegality::RK_IntegerAdd:
1476 return Instruction::Add;
1477 case LoopVectorizationLegality::RK_IntegerMult:
1478 return Instruction::Mul;
1479 case LoopVectorizationLegality::RK_IntegerOr:
1480 return Instruction::Or;
1481 case LoopVectorizationLegality::RK_IntegerAnd:
1482 return Instruction::And;
1483 case LoopVectorizationLegality::RK_IntegerXor:
1484 return Instruction::Xor;
1485 case LoopVectorizationLegality::RK_FloatMult:
1486 return Instruction::FMul;
1487 case LoopVectorizationLegality::RK_FloatAdd:
1488 return Instruction::FAdd;
1490 llvm_unreachable("Unknown reduction operation");
1495 InnerLoopVectorizer::vectorizeLoop(LoopVectorizationLegality *Legal) {
1496 //===------------------------------------------------===//
1498 // Notice: any optimization or new instruction that go
1499 // into the code below should be also be implemented in
1502 //===------------------------------------------------===//
1503 Constant *Zero = Builder.getInt32(0);
1505 // In order to support reduction variables we need to be able to vectorize
1506 // Phi nodes. Phi nodes have cycles, so we need to vectorize them in two
1507 // stages. First, we create a new vector PHI node with no incoming edges.
1508 // We use this value when we vectorize all of the instructions that use the
1509 // PHI. Next, after all of the instructions in the block are complete we
1510 // add the new incoming edges to the PHI. At this point all of the
1511 // instructions in the basic block are vectorized, so we can use them to
1512 // construct the PHI.
1513 PhiVector RdxPHIsToFix;
1515 // Scan the loop in a topological order to ensure that defs are vectorized
1517 LoopBlocksDFS DFS(OrigLoop);
1520 // Vectorize all of the blocks in the original loop.
1521 for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(),
1522 be = DFS.endRPO(); bb != be; ++bb)
1523 vectorizeBlockInLoop(Legal, *bb, &RdxPHIsToFix);
1525 // At this point every instruction in the original loop is widened to
1526 // a vector form. We are almost done. Now, we need to fix the PHI nodes
1527 // that we vectorized. The PHI nodes are currently empty because we did
1528 // not want to introduce cycles. Notice that the remaining PHI nodes
1529 // that we need to fix are reduction variables.
1531 // Create the 'reduced' values for each of the induction vars.
1532 // The reduced values are the vector values that we scalarize and combine
1533 // after the loop is finished.
1534 for (PhiVector::iterator it = RdxPHIsToFix.begin(), e = RdxPHIsToFix.end();
1536 PHINode *RdxPhi = *it;
1537 assert(RdxPhi && "Unable to recover vectorized PHI");
1539 // Find the reduction variable descriptor.
1540 assert(Legal->getReductionVars()->count(RdxPhi) &&
1541 "Unable to find the reduction variable");
1542 LoopVectorizationLegality::ReductionDescriptor RdxDesc =
1543 (*Legal->getReductionVars())[RdxPhi];
1545 // We need to generate a reduction vector from the incoming scalar.
1546 // To do so, we need to generate the 'identity' vector and overide
1547 // one of the elements with the incoming scalar reduction. We need
1548 // to do it in the vector-loop preheader.
1549 Builder.SetInsertPoint(LoopBypassBlocks.back()->getTerminator());
1551 // This is the vector-clone of the value that leaves the loop.
1552 VectorParts &VectorExit = getVectorValue(RdxDesc.LoopExitInstr);
1553 Type *VecTy = VectorExit[0]->getType();
1555 // Find the reduction identity variable. Zero for addition, or, xor,
1556 // one for multiplication, -1 for And.
1557 Constant *Iden = getReductionIdentity(RdxDesc.Kind, VecTy->getScalarType());
1558 Constant *Identity = ConstantVector::getSplat(VF, Iden);
1560 // This vector is the Identity vector where the first element is the
1561 // incoming scalar reduction.
1562 Value *VectorStart = Builder.CreateInsertElement(Identity,
1563 RdxDesc.StartValue, Zero);
1565 // Fix the vector-loop phi.
1566 // We created the induction variable so we know that the
1567 // preheader is the first entry.
1568 BasicBlock *VecPreheader = Induction->getIncomingBlock(0);
1570 // Reductions do not have to start at zero. They can start with
1571 // any loop invariant values.
1572 VectorParts &VecRdxPhi = WidenMap.get(RdxPhi);
1573 BasicBlock *Latch = OrigLoop->getLoopLatch();
1574 Value *LoopVal = RdxPhi->getIncomingValueForBlock(Latch);
1575 VectorParts &Val = getVectorValue(LoopVal);
1576 for (unsigned part = 0; part < UF; ++part) {
1577 // Make sure to add the reduction stat value only to the
1578 // first unroll part.
1579 Value *StartVal = (part == 0) ? VectorStart : Identity;
1580 cast<PHINode>(VecRdxPhi[part])->addIncoming(StartVal, VecPreheader);
1581 cast<PHINode>(VecRdxPhi[part])->addIncoming(Val[part], LoopVectorBody);
1584 // Before each round, move the insertion point right between
1585 // the PHIs and the values we are going to write.
1586 // This allows us to write both PHINodes and the extractelement
1588 Builder.SetInsertPoint(LoopMiddleBlock->getFirstInsertionPt());
1590 VectorParts RdxParts;
1591 for (unsigned part = 0; part < UF; ++part) {
1592 // This PHINode contains the vectorized reduction variable, or
1593 // the initial value vector, if we bypass the vector loop.
1594 VectorParts &RdxExitVal = getVectorValue(RdxDesc.LoopExitInstr);
1595 PHINode *NewPhi = Builder.CreatePHI(VecTy, 2, "rdx.vec.exit.phi");
1596 Value *StartVal = (part == 0) ? VectorStart : Identity;
1597 for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I)
1598 NewPhi->addIncoming(StartVal, LoopBypassBlocks[I]);
1599 NewPhi->addIncoming(RdxExitVal[part], LoopVectorBody);
1600 RdxParts.push_back(NewPhi);
1603 // Reduce all of the unrolled parts into a single vector.
1604 Value *ReducedPartRdx = RdxParts[0];
1605 for (unsigned part = 1; part < UF; ++part) {
1606 Instruction::BinaryOps Op = getReductionBinOp(RdxDesc.Kind);
1607 ReducedPartRdx = Builder.CreateBinOp(Op, RdxParts[part], ReducedPartRdx,
1611 // VF is a power of 2 so we can emit the reduction using log2(VF) shuffles
1612 // and vector ops, reducing the set of values being computed by half each
1614 assert(isPowerOf2_32(VF) &&
1615 "Reduction emission only supported for pow2 vectors!");
1616 Value *TmpVec = ReducedPartRdx;
1617 SmallVector<Constant*, 32> ShuffleMask(VF, 0);
1618 for (unsigned i = VF; i != 1; i >>= 1) {
1619 // Move the upper half of the vector to the lower half.
1620 for (unsigned j = 0; j != i/2; ++j)
1621 ShuffleMask[j] = Builder.getInt32(i/2 + j);
1623 // Fill the rest of the mask with undef.
1624 std::fill(&ShuffleMask[i/2], ShuffleMask.end(),
1625 UndefValue::get(Builder.getInt32Ty()));
1628 Builder.CreateShuffleVector(TmpVec,
1629 UndefValue::get(TmpVec->getType()),
1630 ConstantVector::get(ShuffleMask),
1633 Instruction::BinaryOps Op = getReductionBinOp(RdxDesc.Kind);
1634 TmpVec = Builder.CreateBinOp(Op, TmpVec, Shuf, "bin.rdx");
1637 // The result is in the first element of the vector.
1638 Value *Scalar0 = Builder.CreateExtractElement(TmpVec, Builder.getInt32(0));
1640 // Now, we need to fix the users of the reduction variable
1641 // inside and outside of the scalar remainder loop.
1642 // We know that the loop is in LCSSA form. We need to update the
1643 // PHI nodes in the exit blocks.
1644 for (BasicBlock::iterator LEI = LoopExitBlock->begin(),
1645 LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) {
1646 PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI);
1647 if (!LCSSAPhi) continue;
1649 // All PHINodes need to have a single entry edge, or two if
1650 // we already fixed them.
1651 assert(LCSSAPhi->getNumIncomingValues() < 3 && "Invalid LCSSA PHI");
1653 // We found our reduction value exit-PHI. Update it with the
1654 // incoming bypass edge.
1655 if (LCSSAPhi->getIncomingValue(0) == RdxDesc.LoopExitInstr) {
1656 // Add an edge coming from the bypass.
1657 LCSSAPhi->addIncoming(Scalar0, LoopMiddleBlock);
1660 }// end of the LCSSA phi scan.
1662 // Fix the scalar loop reduction variable with the incoming reduction sum
1663 // from the vector body and from the backedge value.
1664 int IncomingEdgeBlockIdx =
1665 (RdxPhi)->getBasicBlockIndex(OrigLoop->getLoopLatch());
1666 assert(IncomingEdgeBlockIdx >= 0 && "Invalid block index");
1667 // Pick the other block.
1668 int SelfEdgeBlockIdx = (IncomingEdgeBlockIdx ? 0 : 1);
1669 (RdxPhi)->setIncomingValue(SelfEdgeBlockIdx, Scalar0);
1670 (RdxPhi)->setIncomingValue(IncomingEdgeBlockIdx, RdxDesc.LoopExitInstr);
1671 }// end of for each redux variable.
1673 // The Loop exit block may have single value PHI nodes where the incoming
1674 // value is 'undef'. While vectorizing we only handled real values that
1675 // were defined inside the loop. Here we handle the 'undef case'.
1677 for (BasicBlock::iterator LEI = LoopExitBlock->begin(),
1678 LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) {
1679 PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI);
1680 if (!LCSSAPhi) continue;
1681 if (LCSSAPhi->getNumIncomingValues() == 1)
1682 LCSSAPhi->addIncoming(UndefValue::get(LCSSAPhi->getType()),
1687 InnerLoopVectorizer::VectorParts
1688 InnerLoopVectorizer::createEdgeMask(BasicBlock *Src, BasicBlock *Dst) {
1689 assert(std::find(pred_begin(Dst), pred_end(Dst), Src) != pred_end(Dst) &&
1692 VectorParts SrcMask = createBlockInMask(Src);
1694 // The terminator has to be a branch inst!
1695 BranchInst *BI = dyn_cast<BranchInst>(Src->getTerminator());
1696 assert(BI && "Unexpected terminator found");
1698 if (BI->isConditional()) {
1699 VectorParts EdgeMask = getVectorValue(BI->getCondition());
1701 if (BI->getSuccessor(0) != Dst)
1702 for (unsigned part = 0; part < UF; ++part)
1703 EdgeMask[part] = Builder.CreateNot(EdgeMask[part]);
1705 for (unsigned part = 0; part < UF; ++part)
1706 EdgeMask[part] = Builder.CreateAnd(EdgeMask[part], SrcMask[part]);
1713 InnerLoopVectorizer::VectorParts
1714 InnerLoopVectorizer::createBlockInMask(BasicBlock *BB) {
1715 assert(OrigLoop->contains(BB) && "Block is not a part of a loop");
1717 // Loop incoming mask is all-one.
1718 if (OrigLoop->getHeader() == BB) {
1719 Value *C = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 1);
1720 return getVectorValue(C);
1723 // This is the block mask. We OR all incoming edges, and with zero.
1724 Value *Zero = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 0);
1725 VectorParts BlockMask = getVectorValue(Zero);
1728 for (pred_iterator it = pred_begin(BB), e = pred_end(BB); it != e; ++it) {
1729 VectorParts EM = createEdgeMask(*it, BB);
1730 for (unsigned part = 0; part < UF; ++part)
1731 BlockMask[part] = Builder.CreateOr(BlockMask[part], EM[part]);
1738 InnerLoopVectorizer::vectorizeBlockInLoop(LoopVectorizationLegality *Legal,
1739 BasicBlock *BB, PhiVector *PV) {
1740 // For each instruction in the old loop.
1741 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
1742 VectorParts &Entry = WidenMap.get(it);
1743 switch (it->getOpcode()) {
1744 case Instruction::Br:
1745 // Nothing to do for PHIs and BR, since we already took care of the
1746 // loop control flow instructions.
1748 case Instruction::PHI:{
1749 PHINode* P = cast<PHINode>(it);
1750 // Handle reduction variables:
1751 if (Legal->getReductionVars()->count(P)) {
1752 for (unsigned part = 0; part < UF; ++part) {
1753 // This is phase one of vectorizing PHIs.
1754 Type *VecTy = VectorType::get(it->getType(), VF);
1755 Entry[part] = PHINode::Create(VecTy, 2, "vec.phi",
1756 LoopVectorBody-> getFirstInsertionPt());
1762 // Check for PHI nodes that are lowered to vector selects.
1763 if (P->getParent() != OrigLoop->getHeader()) {
1764 // We know that all PHIs in non header blocks are converted into
1765 // selects, so we don't have to worry about the insertion order and we
1766 // can just use the builder.
1768 // At this point we generate the predication tree. There may be
1769 // duplications since this is a simple recursive scan, but future
1770 // optimizations will clean it up.
1771 VectorParts Cond = createEdgeMask(P->getIncomingBlock(0),
1774 for (unsigned part = 0; part < UF; ++part) {
1775 VectorParts &In0 = getVectorValue(P->getIncomingValue(0));
1776 VectorParts &In1 = getVectorValue(P->getIncomingValue(1));
1777 Entry[part] = Builder.CreateSelect(Cond[part], In0[part], In1[part],
1783 // This PHINode must be an induction variable.
1784 // Make sure that we know about it.
1785 assert(Legal->getInductionVars()->count(P) &&
1786 "Not an induction variable");
1788 LoopVectorizationLegality::InductionInfo II =
1789 Legal->getInductionVars()->lookup(P);
1792 case LoopVectorizationLegality::IK_NoInduction:
1793 llvm_unreachable("Unknown induction");
1794 case LoopVectorizationLegality::IK_IntInduction: {
1795 assert(P == OldInduction && "Unexpected PHI");
1796 Value *Broadcasted = getBroadcastInstrs(Induction);
1797 // After broadcasting the induction variable we need to make the
1798 // vector consecutive by adding 0, 1, 2 ...
1799 for (unsigned part = 0; part < UF; ++part)
1800 Entry[part] = getConsecutiveVector(Broadcasted, VF * part, false);
1803 case LoopVectorizationLegality::IK_ReverseIntInduction:
1804 case LoopVectorizationLegality::IK_PtrInduction:
1805 case LoopVectorizationLegality::IK_ReversePtrInduction:
1806 // Handle reverse integer and pointer inductions.
1807 Value *StartIdx = 0;
1808 // If we have a single integer induction variable then use it.
1809 // Otherwise, start counting at zero.
1811 LoopVectorizationLegality::InductionInfo OldII =
1812 Legal->getInductionVars()->lookup(OldInduction);
1813 StartIdx = OldII.StartValue;
1815 StartIdx = ConstantInt::get(Induction->getType(), 0);
1817 // This is the normalized GEP that starts counting at zero.
1818 Value *NormalizedIdx = Builder.CreateSub(Induction, StartIdx,
1821 // Handle the reverse integer induction variable case.
1822 if (LoopVectorizationLegality::IK_ReverseIntInduction == II.IK) {
1823 IntegerType *DstTy = cast<IntegerType>(II.StartValue->getType());
1824 Value *CNI = Builder.CreateSExtOrTrunc(NormalizedIdx, DstTy,
1826 Value *ReverseInd = Builder.CreateSub(II.StartValue, CNI,
1829 // This is a new value so do not hoist it out.
1830 Value *Broadcasted = getBroadcastInstrs(ReverseInd);
1831 // After broadcasting the induction variable we need to make the
1832 // vector consecutive by adding ... -3, -2, -1, 0.
1833 for (unsigned part = 0; part < UF; ++part)
1834 Entry[part] = getConsecutiveVector(Broadcasted, -VF * part, true);
1838 // Handle the pointer induction variable case.
1839 assert(P->getType()->isPointerTy() && "Unexpected type.");
1841 // Is this a reverse induction ptr or a consecutive induction ptr.
1842 bool Reverse = (LoopVectorizationLegality::IK_ReversePtrInduction ==
1845 // This is the vector of results. Notice that we don't generate
1846 // vector geps because scalar geps result in better code.
1847 for (unsigned part = 0; part < UF; ++part) {
1848 Value *VecVal = UndefValue::get(VectorType::get(P->getType(), VF));
1849 for (unsigned int i = 0; i < VF; ++i) {
1850 int EltIndex = (i + part * VF) * (Reverse ? -1 : 1);
1851 Constant *Idx = ConstantInt::get(Induction->getType(), EltIndex);
1854 GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx, "gep.idx");
1856 GlobalIdx = Builder.CreateSub(Idx, NormalizedIdx, "gep.ridx");
1858 Value *SclrGep = Builder.CreateGEP(II.StartValue, GlobalIdx,
1860 VecVal = Builder.CreateInsertElement(VecVal, SclrGep,
1861 Builder.getInt32(i),
1864 Entry[part] = VecVal;
1871 case Instruction::Add:
1872 case Instruction::FAdd:
1873 case Instruction::Sub:
1874 case Instruction::FSub:
1875 case Instruction::Mul:
1876 case Instruction::FMul:
1877 case Instruction::UDiv:
1878 case Instruction::SDiv:
1879 case Instruction::FDiv:
1880 case Instruction::URem:
1881 case Instruction::SRem:
1882 case Instruction::FRem:
1883 case Instruction::Shl:
1884 case Instruction::LShr:
1885 case Instruction::AShr:
1886 case Instruction::And:
1887 case Instruction::Or:
1888 case Instruction::Xor: {
1889 // Just widen binops.
1890 BinaryOperator *BinOp = dyn_cast<BinaryOperator>(it);
1891 VectorParts &A = getVectorValue(it->getOperand(0));
1892 VectorParts &B = getVectorValue(it->getOperand(1));
1894 // Use this vector value for all users of the original instruction.
1895 for (unsigned Part = 0; Part < UF; ++Part) {
1896 Value *V = Builder.CreateBinOp(BinOp->getOpcode(), A[Part], B[Part]);
1898 // Update the NSW, NUW and Exact flags. Notice: V can be an Undef.
1899 BinaryOperator *VecOp = dyn_cast<BinaryOperator>(V);
1900 if (VecOp && isa<OverflowingBinaryOperator>(BinOp)) {
1901 VecOp->setHasNoSignedWrap(BinOp->hasNoSignedWrap());
1902 VecOp->setHasNoUnsignedWrap(BinOp->hasNoUnsignedWrap());
1904 if (VecOp && isa<PossiblyExactOperator>(VecOp))
1905 VecOp->setIsExact(BinOp->isExact());
1911 case Instruction::Select: {
1913 // If the selector is loop invariant we can create a select
1914 // instruction with a scalar condition. Otherwise, use vector-select.
1915 bool InvariantCond = SE->isLoopInvariant(SE->getSCEV(it->getOperand(0)),
1918 // The condition can be loop invariant but still defined inside the
1919 // loop. This means that we can't just use the original 'cond' value.
1920 // We have to take the 'vectorized' value and pick the first lane.
1921 // Instcombine will make this a no-op.
1922 VectorParts &Cond = getVectorValue(it->getOperand(0));
1923 VectorParts &Op0 = getVectorValue(it->getOperand(1));
1924 VectorParts &Op1 = getVectorValue(it->getOperand(2));
1925 Value *ScalarCond = Builder.CreateExtractElement(Cond[0],
1926 Builder.getInt32(0));
1927 for (unsigned Part = 0; Part < UF; ++Part) {
1928 Entry[Part] = Builder.CreateSelect(
1929 InvariantCond ? ScalarCond : Cond[Part],
1936 case Instruction::ICmp:
1937 case Instruction::FCmp: {
1938 // Widen compares. Generate vector compares.
1939 bool FCmp = (it->getOpcode() == Instruction::FCmp);
1940 CmpInst *Cmp = dyn_cast<CmpInst>(it);
1941 VectorParts &A = getVectorValue(it->getOperand(0));
1942 VectorParts &B = getVectorValue(it->getOperand(1));
1943 for (unsigned Part = 0; Part < UF; ++Part) {
1946 C = Builder.CreateFCmp(Cmp->getPredicate(), A[Part], B[Part]);
1948 C = Builder.CreateICmp(Cmp->getPredicate(), A[Part], B[Part]);
1954 case Instruction::Store:
1955 case Instruction::Load:
1956 vectorizeMemoryInstruction(it, Legal);
1958 case Instruction::ZExt:
1959 case Instruction::SExt:
1960 case Instruction::FPToUI:
1961 case Instruction::FPToSI:
1962 case Instruction::FPExt:
1963 case Instruction::PtrToInt:
1964 case Instruction::IntToPtr:
1965 case Instruction::SIToFP:
1966 case Instruction::UIToFP:
1967 case Instruction::Trunc:
1968 case Instruction::FPTrunc:
1969 case Instruction::BitCast: {
1970 CastInst *CI = dyn_cast<CastInst>(it);
1971 /// Optimize the special case where the source is the induction
1972 /// variable. Notice that we can only optimize the 'trunc' case
1973 /// because: a. FP conversions lose precision, b. sext/zext may wrap,
1974 /// c. other casts depend on pointer size.
1975 if (CI->getOperand(0) == OldInduction &&
1976 it->getOpcode() == Instruction::Trunc) {
1977 Value *ScalarCast = Builder.CreateCast(CI->getOpcode(), Induction,
1979 Value *Broadcasted = getBroadcastInstrs(ScalarCast);
1980 for (unsigned Part = 0; Part < UF; ++Part)
1981 Entry[Part] = getConsecutiveVector(Broadcasted, VF * Part, false);
1984 /// Vectorize casts.
1985 Type *DestTy = VectorType::get(CI->getType()->getScalarType(), VF);
1987 VectorParts &A = getVectorValue(it->getOperand(0));
1988 for (unsigned Part = 0; Part < UF; ++Part)
1989 Entry[Part] = Builder.CreateCast(CI->getOpcode(), A[Part], DestTy);
1993 case Instruction::Call: {
1994 assert(isTriviallyVectorizableIntrinsic(it));
1995 Module *M = BB->getParent()->getParent();
1996 IntrinsicInst *II = cast<IntrinsicInst>(it);
1997 Intrinsic::ID ID = II->getIntrinsicID();
1998 for (unsigned Part = 0; Part < UF; ++Part) {
1999 SmallVector<Value*, 4> Args;
2000 for (unsigned i = 0, ie = II->getNumArgOperands(); i != ie; ++i) {
2001 VectorParts &Arg = getVectorValue(II->getArgOperand(i));
2002 Args.push_back(Arg[Part]);
2004 Type *Tys[] = { VectorType::get(II->getType()->getScalarType(), VF) };
2005 Function *F = Intrinsic::getDeclaration(M, ID, Tys);
2006 Entry[Part] = Builder.CreateCall(F, Args);
2012 // All other instructions are unsupported. Scalarize them.
2013 scalarizeInstruction(it);
2016 }// end of for_each instr.
2019 void InnerLoopVectorizer::updateAnalysis() {
2020 // Forget the original basic block.
2021 SE->forgetLoop(OrigLoop);
2023 // Update the dominator tree information.
2024 assert(DT->properlyDominates(LoopBypassBlocks.front(), LoopExitBlock) &&
2025 "Entry does not dominate exit.");
2027 for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I)
2028 DT->addNewBlock(LoopBypassBlocks[I], LoopBypassBlocks[I-1]);
2029 DT->addNewBlock(LoopVectorPreHeader, LoopBypassBlocks.back());
2030 DT->addNewBlock(LoopVectorBody, LoopVectorPreHeader);
2031 DT->addNewBlock(LoopMiddleBlock, LoopBypassBlocks.front());
2032 DT->addNewBlock(LoopScalarPreHeader, LoopMiddleBlock);
2033 DT->changeImmediateDominator(LoopScalarBody, LoopScalarPreHeader);
2034 DT->changeImmediateDominator(LoopExitBlock, LoopMiddleBlock);
2036 DEBUG(DT->verifyAnalysis());
2039 bool LoopVectorizationLegality::canVectorizeWithIfConvert() {
2040 if (!EnableIfConversion)
2043 assert(TheLoop->getNumBlocks() > 1 && "Single block loops are vectorizable");
2044 std::vector<BasicBlock*> &LoopBlocks = TheLoop->getBlocksVector();
2046 // Collect the blocks that need predication.
2047 for (unsigned i = 0, e = LoopBlocks.size(); i < e; ++i) {
2048 BasicBlock *BB = LoopBlocks[i];
2050 // We don't support switch statements inside loops.
2051 if (!isa<BranchInst>(BB->getTerminator()))
2054 // We must have at most two predecessors because we need to convert
2055 // all PHIs to selects.
2056 unsigned Preds = std::distance(pred_begin(BB), pred_end(BB));
2060 // We must be able to predicate all blocks that need to be predicated.
2061 if (blockNeedsPredication(BB) && !blockCanBePredicated(BB))
2065 // We can if-convert this loop.
2069 bool LoopVectorizationLegality::canVectorize() {
2070 assert(TheLoop->getLoopPreheader() && "No preheader!!");
2072 // We can only vectorize innermost loops.
2073 if (TheLoop->getSubLoopsVector().size())
2076 // We must have a single backedge.
2077 if (TheLoop->getNumBackEdges() != 1)
2080 // We must have a single exiting block.
2081 if (!TheLoop->getExitingBlock())
2084 unsigned NumBlocks = TheLoop->getNumBlocks();
2086 // Check if we can if-convert non single-bb loops.
2087 if (NumBlocks != 1 && !canVectorizeWithIfConvert()) {
2088 DEBUG(dbgs() << "LV: Can't if-convert the loop.\n");
2092 // We need to have a loop header.
2093 BasicBlock *Latch = TheLoop->getLoopLatch();
2094 DEBUG(dbgs() << "LV: Found a loop: " <<
2095 TheLoop->getHeader()->getName() << "\n");
2097 // ScalarEvolution needs to be able to find the exit count.
2098 const SCEV *ExitCount = SE->getExitCount(TheLoop, Latch);
2099 if (ExitCount == SE->getCouldNotCompute()) {
2100 DEBUG(dbgs() << "LV: SCEV could not compute the loop exit count.\n");
2104 // Do not loop-vectorize loops with a tiny trip count.
2105 unsigned TC = SE->getSmallConstantTripCount(TheLoop, Latch);
2106 if (TC > 0u && TC < TinyTripCountVectorThreshold) {
2107 DEBUG(dbgs() << "LV: Found a loop with a very small trip count. " <<
2108 "This loop is not worth vectorizing.\n");
2112 // Check if we can vectorize the instructions and CFG in this loop.
2113 if (!canVectorizeInstrs()) {
2114 DEBUG(dbgs() << "LV: Can't vectorize the instructions or CFG\n");
2118 // Go over each instruction and look at memory deps.
2119 if (!canVectorizeMemory()) {
2120 DEBUG(dbgs() << "LV: Can't vectorize due to memory conflicts\n");
2124 // Collect all of the variables that remain uniform after vectorization.
2125 collectLoopUniforms();
2127 DEBUG(dbgs() << "LV: We can vectorize this loop" <<
2128 (PtrRtCheck.Need ? " (with a runtime bound check)" : "")
2131 // Okay! We can vectorize. At this point we don't have any other mem analysis
2132 // which may limit our maximum vectorization factor, so just return true with
2137 bool LoopVectorizationLegality::canVectorizeInstrs() {
2138 BasicBlock *PreHeader = TheLoop->getLoopPreheader();
2139 BasicBlock *Header = TheLoop->getHeader();
2141 // For each block in the loop.
2142 for (Loop::block_iterator bb = TheLoop->block_begin(),
2143 be = TheLoop->block_end(); bb != be; ++bb) {
2145 // Scan the instructions in the block and look for hazards.
2146 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e;
2149 if (PHINode *Phi = dyn_cast<PHINode>(it)) {
2150 // This should not happen because the loop should be normalized.
2151 if (Phi->getNumIncomingValues() != 2) {
2152 DEBUG(dbgs() << "LV: Found an invalid PHI.\n");
2156 // Check that this PHI type is allowed.
2157 if (!Phi->getType()->isIntegerTy() &&
2158 !Phi->getType()->isFloatingPointTy() &&
2159 !Phi->getType()->isPointerTy()) {
2160 DEBUG(dbgs() << "LV: Found an non-int non-pointer PHI.\n");
2164 // If this PHINode is not in the header block, then we know that we
2165 // can convert it to select during if-conversion. No need to check if
2166 // the PHIs in this block are induction or reduction variables.
2170 // This is the value coming from the preheader.
2171 Value *StartValue = Phi->getIncomingValueForBlock(PreHeader);
2172 // Check if this is an induction variable.
2173 InductionKind IK = isInductionVariable(Phi);
2175 if (IK_NoInduction != IK) {
2176 // Int inductions are special because we only allow one IV.
2177 if (IK == IK_IntInduction) {
2179 DEBUG(dbgs() << "LV: Found too many inductions."<< *Phi <<"\n");
2185 DEBUG(dbgs() << "LV: Found an induction variable.\n");
2186 Inductions[Phi] = InductionInfo(StartValue, IK);
2190 if (AddReductionVar(Phi, RK_IntegerAdd)) {
2191 DEBUG(dbgs() << "LV: Found an ADD reduction PHI."<< *Phi <<"\n");
2194 if (AddReductionVar(Phi, RK_IntegerMult)) {
2195 DEBUG(dbgs() << "LV: Found a MUL reduction PHI."<< *Phi <<"\n");
2198 if (AddReductionVar(Phi, RK_IntegerOr)) {
2199 DEBUG(dbgs() << "LV: Found an OR reduction PHI."<< *Phi <<"\n");
2202 if (AddReductionVar(Phi, RK_IntegerAnd)) {
2203 DEBUG(dbgs() << "LV: Found an AND reduction PHI."<< *Phi <<"\n");
2206 if (AddReductionVar(Phi, RK_IntegerXor)) {
2207 DEBUG(dbgs() << "LV: Found a XOR reduction PHI."<< *Phi <<"\n");
2210 if (AddReductionVar(Phi, RK_FloatMult)) {
2211 DEBUG(dbgs() << "LV: Found an FMult reduction PHI."<< *Phi <<"\n");
2214 if (AddReductionVar(Phi, RK_FloatAdd)) {
2215 DEBUG(dbgs() << "LV: Found an FAdd reduction PHI."<< *Phi <<"\n");
2219 DEBUG(dbgs() << "LV: Found an unidentified PHI."<< *Phi <<"\n");
2221 }// end of PHI handling
2223 // We still don't handle functions.
2224 CallInst *CI = dyn_cast<CallInst>(it);
2225 if (CI && !isTriviallyVectorizableIntrinsic(it)) {
2226 DEBUG(dbgs() << "LV: Found a call site.\n");
2230 // Check that the instruction return type is vectorizable.
2231 if (!VectorType::isValidElementType(it->getType()) &&
2232 !it->getType()->isVoidTy()) {
2233 DEBUG(dbgs() << "LV: Found unvectorizable type." << "\n");
2237 // Check that the stored type is vectorizable.
2238 if (StoreInst *ST = dyn_cast<StoreInst>(it)) {
2239 Type *T = ST->getValueOperand()->getType();
2240 if (!VectorType::isValidElementType(T))
2244 // Reduction instructions are allowed to have exit users.
2245 // All other instructions must not have external users.
2246 if (!AllowedExit.count(it))
2247 //Check that all of the users of the loop are inside the BB.
2248 for (Value::use_iterator I = it->use_begin(), E = it->use_end();
2250 Instruction *U = cast<Instruction>(*I);
2251 // This user may be a reduction exit value.
2252 if (!TheLoop->contains(U)) {
2253 DEBUG(dbgs() << "LV: Found an outside user for : "<< *U << "\n");
2262 DEBUG(dbgs() << "LV: Did not find one integer induction var.\n");
2263 assert(getInductionVars()->size() && "No induction variables");
2269 void LoopVectorizationLegality::collectLoopUniforms() {
2270 // We now know that the loop is vectorizable!
2271 // Collect variables that will remain uniform after vectorization.
2272 std::vector<Value*> Worklist;
2273 BasicBlock *Latch = TheLoop->getLoopLatch();
2275 // Start with the conditional branch and walk up the block.
2276 Worklist.push_back(Latch->getTerminator()->getOperand(0));
2278 while (Worklist.size()) {
2279 Instruction *I = dyn_cast<Instruction>(Worklist.back());
2280 Worklist.pop_back();
2282 // Look at instructions inside this loop.
2283 // Stop when reaching PHI nodes.
2284 // TODO: we need to follow values all over the loop, not only in this block.
2285 if (!I || !TheLoop->contains(I) || isa<PHINode>(I))
2288 // This is a known uniform.
2291 // Insert all operands.
2292 for (int i = 0, Op = I->getNumOperands(); i < Op; ++i) {
2293 Worklist.push_back(I->getOperand(i));
2298 AliasAnalysis::Location
2299 LoopVectorizationLegality::getLoadStoreLocation(Instruction *Inst) {
2300 if (StoreInst *Store = dyn_cast<StoreInst>(Inst))
2301 return AA->getLocation(Store);
2302 else if (LoadInst *Load = dyn_cast<LoadInst>(Inst))
2303 return AA->getLocation(Load);
2305 llvm_unreachable("Should be either load or store instruction");
2309 LoopVectorizationLegality::hasPossibleGlobalWriteReorder(
2312 AliasMultiMap& WriteObjects,
2313 unsigned MaxByteWidth) {
2315 AliasAnalysis::Location ThisLoc = getLoadStoreLocation(Inst);
2317 std::vector<Instruction*>::iterator
2318 it = WriteObjects[Object].begin(),
2319 end = WriteObjects[Object].end();
2321 for (; it != end; ++it) {
2322 Instruction* I = *it;
2326 AliasAnalysis::Location ThatLoc = getLoadStoreLocation(I);
2327 if (AA->alias(ThisLoc.getWithNewSize(MaxByteWidth),
2328 ThatLoc.getWithNewSize(MaxByteWidth)))
2334 bool LoopVectorizationLegality::canVectorizeMemory() {
2336 if (TheLoop->isAnnotatedParallel()) {
2338 << "LV: A loop annotated parallel, ignore memory dependency "
2343 typedef SmallVector<Value*, 16> ValueVector;
2344 typedef SmallPtrSet<Value*, 16> ValueSet;
2345 // Holds the Load and Store *instructions*.
2348 PtrRtCheck.Pointers.clear();
2349 PtrRtCheck.Need = false;
2352 for (Loop::block_iterator bb = TheLoop->block_begin(),
2353 be = TheLoop->block_end(); bb != be; ++bb) {
2355 // Scan the BB and collect legal loads and stores.
2356 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e;
2359 // If this is a load, save it. If this instruction can read from memory
2360 // but is not a load, then we quit. Notice that we don't handle function
2361 // calls that read or write.
2362 if (it->mayReadFromMemory()) {
2363 LoadInst *Ld = dyn_cast<LoadInst>(it);
2364 if (!Ld) return false;
2365 if (!Ld->isSimple()) {
2366 DEBUG(dbgs() << "LV: Found a non-simple load.\n");
2369 Loads.push_back(Ld);
2373 // Save 'store' instructions. Abort if other instructions write to memory.
2374 if (it->mayWriteToMemory()) {
2375 StoreInst *St = dyn_cast<StoreInst>(it);
2376 if (!St) return false;
2377 if (!St->isSimple()) {
2378 DEBUG(dbgs() << "LV: Found a non-simple store.\n");
2381 Stores.push_back(St);
2386 // Now we have two lists that hold the loads and the stores.
2387 // Next, we find the pointers that they use.
2389 // Check if we see any stores. If there are no stores, then we don't
2390 // care if the pointers are *restrict*.
2391 if (!Stores.size()) {
2392 DEBUG(dbgs() << "LV: Found a read-only loop!\n");
2396 // Holds the read and read-write *pointers* that we find. These maps hold
2397 // unique values for pointers (so no need for multi-map).
2399 AliasMap ReadWrites;
2401 // Holds the analyzed pointers. We don't want to call GetUnderlyingObjects
2402 // multiple times on the same object. If the ptr is accessed twice, once
2403 // for read and once for write, it will only appear once (on the write
2404 // list). This is okay, since we are going to check for conflicts between
2405 // writes and between reads and writes, but not between reads and reads.
2408 ValueVector::iterator I, IE;
2409 for (I = Stores.begin(), IE = Stores.end(); I != IE; ++I) {
2410 StoreInst *ST = cast<StoreInst>(*I);
2411 Value* Ptr = ST->getPointerOperand();
2413 if (isUniform(Ptr)) {
2414 DEBUG(dbgs() << "LV: We don't allow storing to uniform addresses\n");
2418 // If we did *not* see this pointer before, insert it to
2419 // the read-write list. At this phase it is only a 'write' list.
2420 if (Seen.insert(Ptr))
2421 ReadWrites.insert(std::make_pair(Ptr, ST));
2424 for (I = Loads.begin(), IE = Loads.end(); I != IE; ++I) {
2425 LoadInst *LD = cast<LoadInst>(*I);
2426 Value* Ptr = LD->getPointerOperand();
2427 // If we did *not* see this pointer before, insert it to the
2428 // read list. If we *did* see it before, then it is already in
2429 // the read-write list. This allows us to vectorize expressions
2430 // such as A[i] += x; Because the address of A[i] is a read-write
2431 // pointer. This only works if the index of A[i] is consecutive.
2432 // If the address of i is unknown (for example A[B[i]]) then we may
2433 // read a few words, modify, and write a few words, and some of the
2434 // words may be written to the same address.
2435 if (Seen.insert(Ptr) || 0 == isConsecutivePtr(Ptr))
2436 Reads.insert(std::make_pair(Ptr, LD));
2439 // If we write (or read-write) to a single destination and there are no
2440 // other reads in this loop then is it safe to vectorize.
2441 if (ReadWrites.size() == 1 && Reads.size() == 0) {
2442 DEBUG(dbgs() << "LV: Found a write-only loop!\n");
2446 // Find pointers with computable bounds. We are going to use this information
2447 // to place a runtime bound check.
2448 bool CanDoRT = true;
2449 AliasMap::iterator MI, ME;
2450 for (MI = ReadWrites.begin(), ME = ReadWrites.end(); MI != ME; ++MI) {
2451 Value *V = (*MI).first;
2452 if (hasComputableBounds(V)) {
2453 PtrRtCheck.insert(SE, TheLoop, V);
2454 DEBUG(dbgs() << "LV: Found a runtime check ptr:" << *V <<"\n");
2460 for (MI = Reads.begin(), ME = Reads.end(); MI != ME; ++MI) {
2461 Value *V = (*MI).first;
2462 if (hasComputableBounds(V)) {
2463 PtrRtCheck.insert(SE, TheLoop, V);
2464 DEBUG(dbgs() << "LV: Found a runtime check ptr:" << *V <<"\n");
2471 // Check that we did not collect too many pointers or found a
2472 // unsizeable pointer.
2473 if (!CanDoRT || PtrRtCheck.Pointers.size() > RuntimeMemoryCheckThreshold) {
2479 DEBUG(dbgs() << "LV: We can perform a memory runtime check if needed.\n");
2482 bool NeedRTCheck = false;
2484 // Biggest vectorized access possible, vector width * unroll factor.
2485 // TODO: We're being very pessimistic here, find a way to know the
2486 // real access width before getting here.
2487 unsigned MaxByteWidth = (TTI->getRegisterBitWidth(true) / 8) *
2488 TTI->getMaximumUnrollFactor();
2489 // Now that the pointers are in two lists (Reads and ReadWrites), we
2490 // can check that there are no conflicts between each of the writes and
2491 // between the writes to the reads.
2492 // Note that WriteObjects duplicates the stores (indexed now by underlying
2493 // objects) to avoid pointing to elements inside ReadWrites.
2494 // TODO: Maybe create a new type where they can interact without duplication.
2495 AliasMultiMap WriteObjects;
2496 ValueVector TempObjects;
2498 // Check that the read-writes do not conflict with other read-write
2500 bool AllWritesIdentified = true;
2501 for (MI = ReadWrites.begin(), ME = ReadWrites.end(); MI != ME; ++MI) {
2502 Value *Val = (*MI).first;
2503 Instruction *Inst = (*MI).second;
2505 GetUnderlyingObjects(Val, TempObjects, DL);
2506 for (ValueVector::iterator UI=TempObjects.begin(), UE=TempObjects.end();
2508 if (!isIdentifiedObject(*UI)) {
2509 DEBUG(dbgs() << "LV: Found an unidentified write ptr:"<< **UI <<"\n");
2511 AllWritesIdentified = false;
2514 // Never seen it before, can't alias.
2515 if (WriteObjects[*UI].empty()) {
2516 DEBUG(dbgs() << "LV: Adding Underlying value:" << **UI <<"\n");
2517 WriteObjects[*UI].push_back(Inst);
2520 // Direct alias found.
2521 if (!AA || dyn_cast<GlobalValue>(*UI) == NULL) {
2522 DEBUG(dbgs() << "LV: Found a possible write-write reorder:"
2526 DEBUG(dbgs() << "LV: Found a conflicting global value:"
2528 DEBUG(dbgs() << "LV: While examining store:" << *Inst <<"\n");
2529 DEBUG(dbgs() << "LV: On value:" << *Val <<"\n");
2531 // If global alias, make sure they do alias.
2532 if (hasPossibleGlobalWriteReorder(*UI,
2536 DEBUG(dbgs() << "LV: Found a possible write-write reorder:"
2541 // Didn't alias, insert into map for further reference.
2542 WriteObjects[*UI].push_back(Inst);
2544 TempObjects.clear();
2547 /// Check that the reads don't conflict with the read-writes.
2548 for (MI = Reads.begin(), ME = Reads.end(); MI != ME; ++MI) {
2549 Value *Val = (*MI).first;
2550 GetUnderlyingObjects(Val, TempObjects, DL);
2551 for (ValueVector::iterator UI=TempObjects.begin(), UE=TempObjects.end();
2553 // If all of the writes are identified then we don't care if the read
2554 // pointer is identified or not.
2555 if (!AllWritesIdentified && !isIdentifiedObject(*UI)) {
2556 DEBUG(dbgs() << "LV: Found an unidentified read ptr:"<< **UI <<"\n");
2560 // Never seen it before, can't alias.
2561 if (WriteObjects[*UI].empty())
2563 // Direct alias found.
2564 if (!AA || dyn_cast<GlobalValue>(*UI) == NULL) {
2565 DEBUG(dbgs() << "LV: Found a possible write-write reorder:"
2569 DEBUG(dbgs() << "LV: Found a global value: "
2571 Instruction *Inst = (*MI).second;
2572 DEBUG(dbgs() << "LV: While examining load:" << *Inst <<"\n");
2573 DEBUG(dbgs() << "LV: On value:" << *Val <<"\n");
2575 // If global alias, make sure they do alias.
2576 if (hasPossibleGlobalWriteReorder(*UI,
2580 DEBUG(dbgs() << "LV: Found a possible read-write reorder:"
2585 TempObjects.clear();
2588 PtrRtCheck.Need = NeedRTCheck;
2589 if (NeedRTCheck && !CanDoRT) {
2590 DEBUG(dbgs() << "LV: We can't vectorize because we can't find " <<
2591 "the array bounds.\n");
2596 DEBUG(dbgs() << "LV: We "<< (NeedRTCheck ? "" : "don't") <<
2597 " need a runtime memory check.\n");
2601 bool LoopVectorizationLegality::AddReductionVar(PHINode *Phi,
2602 ReductionKind Kind) {
2603 if (Phi->getNumIncomingValues() != 2)
2606 // Reduction variables are only found in the loop header block.
2607 if (Phi->getParent() != TheLoop->getHeader())
2610 // Obtain the reduction start value from the value that comes from the loop
2612 Value *RdxStart = Phi->getIncomingValueForBlock(TheLoop->getLoopPreheader());
2614 // ExitInstruction is the single value which is used outside the loop.
2615 // We only allow for a single reduction value to be used outside the loop.
2616 // This includes users of the reduction, variables (which form a cycle
2617 // which ends in the phi node).
2618 Instruction *ExitInstruction = 0;
2619 // Indicates that we found a binary operation in our scan.
2620 bool FoundBinOp = false;
2622 // Iter is our iterator. We start with the PHI node and scan for all of the
2623 // users of this instruction. All users must be instructions that can be
2624 // used as reduction variables (such as ADD). We may have a single
2625 // out-of-block user. The cycle must end with the original PHI.
2626 Instruction *Iter = Phi;
2628 // If the instruction has no users then this is a broken
2629 // chain and can't be a reduction variable.
2630 if (Iter->use_empty())
2633 // Did we find a user inside this loop already ?
2634 bool FoundInBlockUser = false;
2635 // Did we reach the initial PHI node already ?
2636 bool FoundStartPHI = false;
2638 // Is this a bin op ?
2639 FoundBinOp |= !isa<PHINode>(Iter);
2641 // For each of the *users* of iter.
2642 for (Value::use_iterator it = Iter->use_begin(), e = Iter->use_end();
2644 Instruction *U = cast<Instruction>(*it);
2645 // We already know that the PHI is a user.
2647 FoundStartPHI = true;
2651 // Check if we found the exit user.
2652 BasicBlock *Parent = U->getParent();
2653 if (!TheLoop->contains(Parent)) {
2654 // Exit if you find multiple outside users.
2655 if (ExitInstruction != 0)
2657 ExitInstruction = Iter;
2660 // We allow in-loop PHINodes which are not the original reduction PHI
2661 // node. If this PHI is the only user of Iter (happens in IF w/ no ELSE
2662 // structure) then don't skip this PHI.
2663 if (isa<PHINode>(Iter) && isa<PHINode>(U) &&
2664 U->getParent() != TheLoop->getHeader() &&
2665 TheLoop->contains(U) &&
2666 Iter->getNumUses() > 1)
2669 // We can't have multiple inside users.
2670 if (FoundInBlockUser)
2672 FoundInBlockUser = true;
2674 // Any reduction instr must be of one of the allowed kinds.
2675 if (!isReductionInstr(U, Kind))
2678 // Reductions of instructions such as Div, and Sub is only
2679 // possible if the LHS is the reduction variable.
2680 if (!U->isCommutative() && !isa<PHINode>(U) && U->getOperand(0) != Iter)
2686 // We found a reduction var if we have reached the original
2687 // phi node and we only have a single instruction with out-of-loop
2689 if (FoundStartPHI) {
2690 // This instruction is allowed to have out-of-loop users.
2691 AllowedExit.insert(ExitInstruction);
2693 // Save the description of this reduction variable.
2694 ReductionDescriptor RD(RdxStart, ExitInstruction, Kind);
2695 Reductions[Phi] = RD;
2696 // We've ended the cycle. This is a reduction variable if we have an
2697 // outside user and it has a binary op.
2698 return FoundBinOp && ExitInstruction;
2704 LoopVectorizationLegality::isReductionInstr(Instruction *I,
2705 ReductionKind Kind) {
2706 bool FP = I->getType()->isFloatingPointTy();
2707 bool FastMath = (FP && I->isCommutative() && I->isAssociative());
2709 switch (I->getOpcode()) {
2712 case Instruction::PHI:
2713 if (FP && (Kind != RK_FloatMult && Kind != RK_FloatAdd))
2717 case Instruction::Sub:
2718 case Instruction::Add:
2719 return Kind == RK_IntegerAdd;
2720 case Instruction::SDiv:
2721 case Instruction::UDiv:
2722 case Instruction::Mul:
2723 return Kind == RK_IntegerMult;
2724 case Instruction::And:
2725 return Kind == RK_IntegerAnd;
2726 case Instruction::Or:
2727 return Kind == RK_IntegerOr;
2728 case Instruction::Xor:
2729 return Kind == RK_IntegerXor;
2730 case Instruction::FMul:
2731 return Kind == RK_FloatMult && FastMath;
2732 case Instruction::FAdd:
2733 return Kind == RK_FloatAdd && FastMath;
2737 LoopVectorizationLegality::InductionKind
2738 LoopVectorizationLegality::isInductionVariable(PHINode *Phi) {
2739 Type *PhiTy = Phi->getType();
2740 // We only handle integer and pointer inductions variables.
2741 if (!PhiTy->isIntegerTy() && !PhiTy->isPointerTy())
2742 return IK_NoInduction;
2744 // Check that the PHI is consecutive.
2745 const SCEV *PhiScev = SE->getSCEV(Phi);
2746 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PhiScev);
2748 DEBUG(dbgs() << "LV: PHI is not a poly recurrence.\n");
2749 return IK_NoInduction;
2751 const SCEV *Step = AR->getStepRecurrence(*SE);
2753 // Integer inductions need to have a stride of one.
2754 if (PhiTy->isIntegerTy()) {
2756 return IK_IntInduction;
2757 if (Step->isAllOnesValue())
2758 return IK_ReverseIntInduction;
2759 return IK_NoInduction;
2762 // Calculate the pointer stride and check if it is consecutive.
2763 const SCEVConstant *C = dyn_cast<SCEVConstant>(Step);
2765 return IK_NoInduction;
2767 assert(PhiTy->isPointerTy() && "The PHI must be a pointer");
2768 uint64_t Size = DL->getTypeAllocSize(PhiTy->getPointerElementType());
2769 if (C->getValue()->equalsInt(Size))
2770 return IK_PtrInduction;
2771 else if (C->getValue()->equalsInt(0 - Size))
2772 return IK_ReversePtrInduction;
2774 return IK_NoInduction;
2777 bool LoopVectorizationLegality::isInductionVariable(const Value *V) {
2778 Value *In0 = const_cast<Value*>(V);
2779 PHINode *PN = dyn_cast_or_null<PHINode>(In0);
2783 return Inductions.count(PN);
2786 bool LoopVectorizationLegality::blockNeedsPredication(BasicBlock *BB) {
2787 assert(TheLoop->contains(BB) && "Unknown block used");
2789 // Blocks that do not dominate the latch need predication.
2790 BasicBlock* Latch = TheLoop->getLoopLatch();
2791 return !DT->dominates(BB, Latch);
2794 bool LoopVectorizationLegality::blockCanBePredicated(BasicBlock *BB) {
2795 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
2796 // We don't predicate loads/stores at the moment.
2797 if (it->mayReadFromMemory() || it->mayWriteToMemory() || it->mayThrow())
2800 // The instructions below can trap.
2801 switch (it->getOpcode()) {
2803 case Instruction::UDiv:
2804 case Instruction::SDiv:
2805 case Instruction::URem:
2806 case Instruction::SRem:
2814 bool LoopVectorizationLegality::hasComputableBounds(Value *Ptr) {
2815 const SCEV *PhiScev = SE->getSCEV(Ptr);
2816 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PhiScev);
2820 return AR->isAffine();
2823 LoopVectorizationCostModel::VectorizationFactor
2824 LoopVectorizationCostModel::selectVectorizationFactor(bool OptForSize,
2826 // Width 1 means no vectorize
2827 VectorizationFactor Factor = { 1U, 0U };
2828 if (OptForSize && Legal->getRuntimePointerCheck()->Need) {
2829 DEBUG(dbgs() << "LV: Aborting. Runtime ptr check is required in Os.\n");
2833 // Find the trip count.
2834 unsigned TC = SE->getSmallConstantTripCount(TheLoop, TheLoop->getLoopLatch());
2835 DEBUG(dbgs() << "LV: Found trip count:"<<TC<<"\n");
2837 unsigned WidestType = getWidestType();
2838 unsigned WidestRegister = TTI.getRegisterBitWidth(true);
2839 unsigned MaxVectorSize = WidestRegister / WidestType;
2840 DEBUG(dbgs() << "LV: The Widest type: " << WidestType << " bits.\n");
2841 DEBUG(dbgs() << "LV: The Widest register is:" << WidestRegister << "bits.\n");
2843 if (MaxVectorSize == 0) {
2844 DEBUG(dbgs() << "LV: The target has no vector registers.\n");
2848 assert(MaxVectorSize <= 32 && "Did not expect to pack so many elements"
2849 " into one vector!");
2851 unsigned VF = MaxVectorSize;
2853 // If we optimize the program for size, avoid creating the tail loop.
2855 // If we are unable to calculate the trip count then don't try to vectorize.
2857 DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n");
2861 // Find the maximum SIMD width that can fit within the trip count.
2862 VF = TC % MaxVectorSize;
2867 // If the trip count that we found modulo the vectorization factor is not
2868 // zero then we require a tail.
2870 DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n");
2876 assert(isPowerOf2_32(UserVF) && "VF needs to be a power of two");
2877 DEBUG(dbgs() << "LV: Using user VF "<<UserVF<<".\n");
2879 Factor.Width = UserVF;
2883 float Cost = expectedCost(1);
2885 DEBUG(dbgs() << "LV: Scalar loop costs: "<< (int)Cost << ".\n");
2886 for (unsigned i=2; i <= VF; i*=2) {
2887 // Notice that the vector loop needs to be executed less times, so
2888 // we need to divide the cost of the vector loops by the width of
2889 // the vector elements.
2890 float VectorCost = expectedCost(i) / (float)i;
2891 DEBUG(dbgs() << "LV: Vector loop of width "<< i << " costs: " <<
2892 (int)VectorCost << ".\n");
2893 if (VectorCost < Cost) {
2899 DEBUG(dbgs() << "LV: Selecting VF = : "<< Width << ".\n");
2900 Factor.Width = Width;
2901 Factor.Cost = Width * Cost;
2905 unsigned LoopVectorizationCostModel::getWidestType() {
2906 unsigned MaxWidth = 8;
2909 for (Loop::block_iterator bb = TheLoop->block_begin(),
2910 be = TheLoop->block_end(); bb != be; ++bb) {
2911 BasicBlock *BB = *bb;
2913 // For each instruction in the loop.
2914 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
2915 Type *T = it->getType();
2917 // Only examine Loads, Stores and PHINodes.
2918 if (!isa<LoadInst>(it) && !isa<StoreInst>(it) && !isa<PHINode>(it))
2921 // Examine PHI nodes that are reduction variables.
2922 if (PHINode *PN = dyn_cast<PHINode>(it))
2923 if (!Legal->getReductionVars()->count(PN))
2926 // Examine the stored values.
2927 if (StoreInst *ST = dyn_cast<StoreInst>(it))
2928 T = ST->getValueOperand()->getType();
2930 // Ignore loaded pointer types and stored pointer types that are not
2931 // consecutive. However, we do want to take consecutive stores/loads of
2932 // pointer vectors into account.
2933 if (T->isPointerTy() && !isConsecutiveLoadOrStore(it))
2936 MaxWidth = std::max(MaxWidth,
2937 (unsigned)DL->getTypeSizeInBits(T->getScalarType()));
2945 LoopVectorizationCostModel::selectUnrollFactor(bool OptForSize,
2948 unsigned LoopCost) {
2950 // -- The unroll heuristics --
2951 // We unroll the loop in order to expose ILP and reduce the loop overhead.
2952 // There are many micro-architectural considerations that we can't predict
2953 // at this level. For example frontend pressure (on decode or fetch) due to
2954 // code size, or the number and capabilities of the execution ports.
2956 // We use the following heuristics to select the unroll factor:
2957 // 1. If the code has reductions the we unroll in order to break the cross
2958 // iteration dependency.
2959 // 2. If the loop is really small then we unroll in order to reduce the loop
2961 // 3. We don't unroll if we think that we will spill registers to memory due
2962 // to the increased register pressure.
2964 // Use the user preference, unless 'auto' is selected.
2968 // When we optimize for size we don't unroll.
2972 // Do not unroll loops with a relatively small trip count.
2973 unsigned TC = SE->getSmallConstantTripCount(TheLoop,
2974 TheLoop->getLoopLatch());
2975 if (TC > 1 && TC < TinyTripCountUnrollThreshold)
2978 unsigned TargetVectorRegisters = TTI.getNumberOfRegisters(true);
2979 DEBUG(dbgs() << "LV: The target has " << TargetVectorRegisters <<
2980 " vector registers\n");
2982 LoopVectorizationCostModel::RegisterUsage R = calculateRegisterUsage();
2983 // We divide by these constants so assume that we have at least one
2984 // instruction that uses at least one register.
2985 R.MaxLocalUsers = std::max(R.MaxLocalUsers, 1U);
2986 R.NumInstructions = std::max(R.NumInstructions, 1U);
2988 // We calculate the unroll factor using the following formula.
2989 // Subtract the number of loop invariants from the number of available
2990 // registers. These registers are used by all of the unrolled instances.
2991 // Next, divide the remaining registers by the number of registers that is
2992 // required by the loop, in order to estimate how many parallel instances
2993 // fit without causing spills.
2994 unsigned UF = (TargetVectorRegisters - R.LoopInvariantRegs) / R.MaxLocalUsers;
2996 // Clamp the unroll factor ranges to reasonable factors.
2997 unsigned MaxUnrollSize = TTI.getMaximumUnrollFactor();
2999 // If we did not calculate the cost for VF (because the user selected the VF)
3000 // then we calculate the cost of VF here.
3002 LoopCost = expectedCost(VF);
3004 // Clamp the calculated UF to be between the 1 and the max unroll factor
3005 // that the target allows.
3006 if (UF > MaxUnrollSize)
3011 if (Legal->getReductionVars()->size()) {
3012 DEBUG(dbgs() << "LV: Unrolling because of reductions. \n");
3016 // We want to unroll tiny loops in order to reduce the loop overhead.
3017 // We assume that the cost overhead is 1 and we use the cost model
3018 // to estimate the cost of the loop and unroll until the cost of the
3019 // loop overhead is about 5% of the cost of the loop.
3020 DEBUG(dbgs() << "LV: Loop cost is "<< LoopCost <<" \n");
3021 if (LoopCost < 20) {
3022 DEBUG(dbgs() << "LV: Unrolling to reduce branch cost. \n");
3023 unsigned NewUF = 20/LoopCost + 1;
3024 return std::min(NewUF, UF);
3027 DEBUG(dbgs() << "LV: Not Unrolling. \n");
3031 LoopVectorizationCostModel::RegisterUsage
3032 LoopVectorizationCostModel::calculateRegisterUsage() {
3033 // This function calculates the register usage by measuring the highest number
3034 // of values that are alive at a single location. Obviously, this is a very
3035 // rough estimation. We scan the loop in a topological order in order and
3036 // assign a number to each instruction. We use RPO to ensure that defs are
3037 // met before their users. We assume that each instruction that has in-loop
3038 // users starts an interval. We record every time that an in-loop value is
3039 // used, so we have a list of the first and last occurrences of each
3040 // instruction. Next, we transpose this data structure into a multi map that
3041 // holds the list of intervals that *end* at a specific location. This multi
3042 // map allows us to perform a linear search. We scan the instructions linearly
3043 // and record each time that a new interval starts, by placing it in a set.
3044 // If we find this value in the multi-map then we remove it from the set.
3045 // The max register usage is the maximum size of the set.
3046 // We also search for instructions that are defined outside the loop, but are
3047 // used inside the loop. We need this number separately from the max-interval
3048 // usage number because when we unroll, loop-invariant values do not take
3050 LoopBlocksDFS DFS(TheLoop);
3054 R.NumInstructions = 0;
3056 // Each 'key' in the map opens a new interval. The values
3057 // of the map are the index of the 'last seen' usage of the
3058 // instruction that is the key.
3059 typedef DenseMap<Instruction*, unsigned> IntervalMap;
3060 // Maps instruction to its index.
3061 DenseMap<unsigned, Instruction*> IdxToInstr;
3062 // Marks the end of each interval.
3063 IntervalMap EndPoint;
3064 // Saves the list of instruction indices that are used in the loop.
3065 SmallSet<Instruction*, 8> Ends;
3066 // Saves the list of values that are used in the loop but are
3067 // defined outside the loop, such as arguments and constants.
3068 SmallPtrSet<Value*, 8> LoopInvariants;
3071 for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(),
3072 be = DFS.endRPO(); bb != be; ++bb) {
3073 R.NumInstructions += (*bb)->size();
3074 for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e;
3076 Instruction *I = it;
3077 IdxToInstr[Index++] = I;
3079 // Save the end location of each USE.
3080 for (unsigned i = 0; i < I->getNumOperands(); ++i) {
3081 Value *U = I->getOperand(i);
3082 Instruction *Instr = dyn_cast<Instruction>(U);
3084 // Ignore non-instruction values such as arguments, constants, etc.
3085 if (!Instr) continue;
3087 // If this instruction is outside the loop then record it and continue.
3088 if (!TheLoop->contains(Instr)) {
3089 LoopInvariants.insert(Instr);
3093 // Overwrite previous end points.
3094 EndPoint[Instr] = Index;
3100 // Saves the list of intervals that end with the index in 'key'.
3101 typedef SmallVector<Instruction*, 2> InstrList;
3102 DenseMap<unsigned, InstrList> TransposeEnds;
3104 // Transpose the EndPoints to a list of values that end at each index.
3105 for (IntervalMap::iterator it = EndPoint.begin(), e = EndPoint.end();
3107 TransposeEnds[it->second].push_back(it->first);
3109 SmallSet<Instruction*, 8> OpenIntervals;
3110 unsigned MaxUsage = 0;
3113 DEBUG(dbgs() << "LV(REG): Calculating max register usage:\n");
3114 for (unsigned int i = 0; i < Index; ++i) {
3115 Instruction *I = IdxToInstr[i];
3116 // Ignore instructions that are never used within the loop.
3117 if (!Ends.count(I)) continue;
3119 // Remove all of the instructions that end at this location.
3120 InstrList &List = TransposeEnds[i];
3121 for (unsigned int j=0, e = List.size(); j < e; ++j)
3122 OpenIntervals.erase(List[j]);
3124 // Count the number of live interals.
3125 MaxUsage = std::max(MaxUsage, OpenIntervals.size());
3127 DEBUG(dbgs() << "LV(REG): At #" << i << " Interval # " <<
3128 OpenIntervals.size() <<"\n");
3130 // Add the current instruction to the list of open intervals.
3131 OpenIntervals.insert(I);
3134 unsigned Invariant = LoopInvariants.size();
3135 DEBUG(dbgs() << "LV(REG): Found max usage: " << MaxUsage << " \n");
3136 DEBUG(dbgs() << "LV(REG): Found invariant usage: " << Invariant << " \n");
3137 DEBUG(dbgs() << "LV(REG): LoopSize: " << R.NumInstructions << " \n");
3139 R.LoopInvariantRegs = Invariant;
3140 R.MaxLocalUsers = MaxUsage;
3144 unsigned LoopVectorizationCostModel::expectedCost(unsigned VF) {
3148 for (Loop::block_iterator bb = TheLoop->block_begin(),
3149 be = TheLoop->block_end(); bb != be; ++bb) {
3150 unsigned BlockCost = 0;
3151 BasicBlock *BB = *bb;
3153 // For each instruction in the old loop.
3154 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
3155 unsigned C = getInstructionCost(it, VF);
3157 DEBUG(dbgs() << "LV: Found an estimated cost of "<< C <<" for VF " <<
3158 VF << " For instruction: "<< *it << "\n");
3161 // We assume that if-converted blocks have a 50% chance of being executed.
3162 // When the code is scalar then some of the blocks are avoided due to CF.
3163 // When the code is vectorized we execute all code paths.
3164 if (Legal->blockNeedsPredication(*bb) && VF == 1)
3174 LoopVectorizationCostModel::getInstructionCost(Instruction *I, unsigned VF) {
3175 // If we know that this instruction will remain uniform, check the cost of
3176 // the scalar version.
3177 if (Legal->isUniformAfterVectorization(I))
3180 Type *RetTy = I->getType();
3181 Type *VectorTy = ToVectorTy(RetTy, VF);
3183 // TODO: We need to estimate the cost of intrinsic calls.
3184 switch (I->getOpcode()) {
3185 case Instruction::GetElementPtr:
3186 // We mark this instruction as zero-cost because the cost of GEPs in
3187 // vectorized code depends on whether the corresponding memory instruction
3188 // is scalarized or not. Therefore, we handle GEPs with the memory
3189 // instruction cost.
3191 case Instruction::Br: {
3192 return TTI.getCFInstrCost(I->getOpcode());
3194 case Instruction::PHI:
3195 //TODO: IF-converted IFs become selects.
3197 case Instruction::Add:
3198 case Instruction::FAdd:
3199 case Instruction::Sub:
3200 case Instruction::FSub:
3201 case Instruction::Mul:
3202 case Instruction::FMul:
3203 case Instruction::UDiv:
3204 case Instruction::SDiv:
3205 case Instruction::FDiv:
3206 case Instruction::URem:
3207 case Instruction::SRem:
3208 case Instruction::FRem:
3209 case Instruction::Shl:
3210 case Instruction::LShr:
3211 case Instruction::AShr:
3212 case Instruction::And:
3213 case Instruction::Or:
3214 case Instruction::Xor:
3215 return TTI.getArithmeticInstrCost(I->getOpcode(), VectorTy);
3216 case Instruction::Select: {
3217 SelectInst *SI = cast<SelectInst>(I);
3218 const SCEV *CondSCEV = SE->getSCEV(SI->getCondition());
3219 bool ScalarCond = (SE->isLoopInvariant(CondSCEV, TheLoop));
3220 Type *CondTy = SI->getCondition()->getType();
3222 CondTy = VectorType::get(CondTy, VF);
3224 return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy, CondTy);
3226 case Instruction::ICmp:
3227 case Instruction::FCmp: {
3228 Type *ValTy = I->getOperand(0)->getType();
3229 VectorTy = ToVectorTy(ValTy, VF);
3230 return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy);
3232 case Instruction::Store:
3233 case Instruction::Load: {
3234 StoreInst *SI = dyn_cast<StoreInst>(I);
3235 LoadInst *LI = dyn_cast<LoadInst>(I);
3236 Type *ValTy = (SI ? SI->getValueOperand()->getType() :
3238 VectorTy = ToVectorTy(ValTy, VF);
3240 unsigned Alignment = SI ? SI->getAlignment() : LI->getAlignment();
3241 unsigned AS = SI ? SI->getPointerAddressSpace() :
3242 LI->getPointerAddressSpace();
3243 Value *Ptr = SI ? SI->getPointerOperand() : LI->getPointerOperand();
3244 // We add the cost of address computation here instead of with the gep
3245 // instruction because only here we know whether the operation is
3248 return TTI.getAddressComputationCost(VectorTy) +
3249 TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS);
3251 // Scalarized loads/stores.
3252 int Stride = Legal->isConsecutivePtr(Ptr);
3253 bool Reverse = Stride < 0;
3256 // The cost of extracting from the value vector and pointer vector.
3257 Type *PtrTy = ToVectorTy(Ptr->getType(), VF);
3258 for (unsigned i = 0; i < VF; ++i) {
3259 // The cost of extracting the pointer operand.
3260 Cost += TTI.getVectorInstrCost(Instruction::ExtractElement, PtrTy, i);
3261 // In case of STORE, the cost of ExtractElement from the vector.
3262 // In case of LOAD, the cost of InsertElement into the returned
3264 Cost += TTI.getVectorInstrCost(SI ? Instruction::ExtractElement :
3265 Instruction::InsertElement,
3269 // The cost of the scalar loads/stores.
3270 Cost += VF * TTI.getAddressComputationCost(ValTy->getScalarType());
3271 Cost += VF * TTI.getMemoryOpCost(I->getOpcode(), ValTy->getScalarType(),
3276 // Wide load/stores.
3277 unsigned Cost = TTI.getAddressComputationCost(VectorTy);
3278 Cost += TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS);
3281 Cost += TTI.getShuffleCost(TargetTransformInfo::SK_Reverse,
3285 case Instruction::ZExt:
3286 case Instruction::SExt:
3287 case Instruction::FPToUI:
3288 case Instruction::FPToSI:
3289 case Instruction::FPExt:
3290 case Instruction::PtrToInt:
3291 case Instruction::IntToPtr:
3292 case Instruction::SIToFP:
3293 case Instruction::UIToFP:
3294 case Instruction::Trunc:
3295 case Instruction::FPTrunc:
3296 case Instruction::BitCast: {
3297 // We optimize the truncation of induction variable.
3298 // The cost of these is the same as the scalar operation.
3299 if (I->getOpcode() == Instruction::Trunc &&
3300 Legal->isInductionVariable(I->getOperand(0)))
3301 return TTI.getCastInstrCost(I->getOpcode(), I->getType(),
3302 I->getOperand(0)->getType());
3304 Type *SrcVecTy = ToVectorTy(I->getOperand(0)->getType(), VF);
3305 return TTI.getCastInstrCost(I->getOpcode(), VectorTy, SrcVecTy);
3307 case Instruction::Call: {
3308 assert(isTriviallyVectorizableIntrinsic(I));
3309 IntrinsicInst *II = cast<IntrinsicInst>(I);
3310 Type *RetTy = ToVectorTy(II->getType(), VF);
3311 SmallVector<Type*, 4> Tys;
3312 for (unsigned i = 0, ie = II->getNumArgOperands(); i != ie; ++i)
3313 Tys.push_back(ToVectorTy(II->getArgOperand(i)->getType(), VF));
3314 return TTI.getIntrinsicInstrCost(II->getIntrinsicID(), RetTy, Tys);
3317 // We are scalarizing the instruction. Return the cost of the scalar
3318 // instruction, plus the cost of insert and extract into vector
3319 // elements, times the vector width.
3322 if (!RetTy->isVoidTy() && VF != 1) {
3323 unsigned InsCost = TTI.getVectorInstrCost(Instruction::InsertElement,
3325 unsigned ExtCost = TTI.getVectorInstrCost(Instruction::ExtractElement,
3328 // The cost of inserting the results plus extracting each one of the
3330 Cost += VF * (InsCost + ExtCost * I->getNumOperands());
3333 // The cost of executing VF copies of the scalar instruction. This opcode
3334 // is unknown. Assume that it is the same as 'mul'.
3335 Cost += VF * TTI.getArithmeticInstrCost(Instruction::Mul, VectorTy);
3341 Type* LoopVectorizationCostModel::ToVectorTy(Type *Scalar, unsigned VF) {
3342 if (Scalar->isVoidTy() || VF == 1)
3344 return VectorType::get(Scalar, VF);
3347 char LoopVectorize::ID = 0;
3348 static const char lv_name[] = "Loop Vectorization";
3349 INITIALIZE_PASS_BEGIN(LoopVectorize, LV_NAME, lv_name, false, false)
3350 INITIALIZE_AG_DEPENDENCY(AliasAnalysis)
3351 INITIALIZE_AG_DEPENDENCY(TargetTransformInfo)
3352 INITIALIZE_PASS_DEPENDENCY(ScalarEvolution)
3353 INITIALIZE_PASS_DEPENDENCY(LoopSimplify)
3354 INITIALIZE_PASS_END(LoopVectorize, LV_NAME, lv_name, false, false)
3357 Pass *createLoopVectorizePass() {
3358 return new LoopVectorize();
3362 bool LoopVectorizationCostModel::isConsecutiveLoadOrStore(Instruction *Inst) {
3363 // Check for a store.
3364 if (StoreInst *ST = dyn_cast<StoreInst>(Inst))
3365 return Legal->isConsecutivePtr(ST->getPointerOperand()) != 0;
3367 // Check for a load.
3368 if (LoadInst *LI = dyn_cast<LoadInst>(Inst))
3369 return Legal->isConsecutivePtr(LI->getPointerOperand()) != 0;