1//===- LoopVectorize.cpp - A Loop Vectorizer ------------------------------===//
2//
3//                     The LLVM Compiler Infrastructure
4//
5// This file is distributed under the University of Illinois Open Source
6// License. See LICENSE.TXT for details.
7//
8//===----------------------------------------------------------------------===//
9//
10// This is the LLVM loop vectorizer. This pass modifies 'vectorizable' loops
11// and generates target-independent LLVM-IR.
12// The vectorizer uses the TargetTransformInfo analysis to estimate the costs
13// of instructions in order to estimate the profitability of vectorization.
14//
15// The loop vectorizer combines consecutive loop iterations into a single
16// 'wide' iteration. After this transformation the index is incremented
17// by the SIMD vector width, and not by one.
18//
19// This pass has three parts:
20// 1. The main loop pass that drives the different parts.
21// 2. LoopVectorizationLegality - A unit that checks for the legality
22//    of the vectorization.
23// 3. InnerLoopVectorizer - A unit that performs the actual
24//    widening of instructions.
25// 4. LoopVectorizationCostModel - A unit that checks for the profitability
26//    of vectorization. It decides on the optimal vector width, which
27//    can be one, if vectorization is not profitable.
28//
29//===----------------------------------------------------------------------===//
30//
31// The reduction-variable vectorization is based on the paper:
32//  D. Nuzman and R. Henderson. Multi-platform Auto-vectorization.
33//
34// Variable uniformity checks are inspired by:
35//  Karrenberg, R. and Hack, S. Whole Function Vectorization.
36//
37// Other ideas/concepts are from:
38//  A. Zaks and D. Nuzman. Autovectorization in GCC-two years later.
39//
40//  S. Maleki, Y. Gao, M. Garzaran, T. Wong and D. Padua.  An Evaluation of
41//  Vectorizing Compilers.
42//
43//===----------------------------------------------------------------------===//
44
45#include "llvm/Transforms/Vectorize.h"
46#include "llvm/ADT/DenseMap.h"
47#include "llvm/ADT/EquivalenceClasses.h"
48#include "llvm/ADT/Hashing.h"
49#include "llvm/ADT/MapVector.h"
50#include "llvm/ADT/SetVector.h"
51#include "llvm/ADT/SmallPtrSet.h"
52#include "llvm/ADT/SmallSet.h"
53#include "llvm/ADT/SmallVector.h"
54#include "llvm/ADT/Statistic.h"
55#include "llvm/ADT/StringExtras.h"
56#include "llvm/Analysis/AliasAnalysis.h"
57#include "llvm/Analysis/AliasSetTracker.h"
58#include "llvm/Analysis/AssumptionCache.h"
59#include "llvm/Analysis/BlockFrequencyInfo.h"
60#include "llvm/Analysis/CodeMetrics.h"
61#include "llvm/Analysis/LoopAccessAnalysis.h"
62#include "llvm/Analysis/LoopInfo.h"
63#include "llvm/Analysis/LoopIterator.h"
64#include "llvm/Analysis/LoopPass.h"
65#include "llvm/Analysis/ScalarEvolution.h"
66#include "llvm/Analysis/ScalarEvolutionExpander.h"
67#include "llvm/Analysis/ScalarEvolutionExpressions.h"
68#include "llvm/Analysis/TargetTransformInfo.h"
69#include "llvm/Analysis/ValueTracking.h"
70#include "llvm/IR/Constants.h"
71#include "llvm/IR/DataLayout.h"
72#include "llvm/IR/DebugInfo.h"
73#include "llvm/IR/DerivedTypes.h"
74#include "llvm/IR/DiagnosticInfo.h"
75#include "llvm/IR/Dominators.h"
76#include "llvm/IR/Function.h"
77#include "llvm/IR/IRBuilder.h"
78#include "llvm/IR/Instructions.h"
79#include "llvm/IR/IntrinsicInst.h"
80#include "llvm/IR/LLVMContext.h"
81#include "llvm/IR/Module.h"
82#include "llvm/IR/PatternMatch.h"
83#include "llvm/IR/Type.h"
84#include "llvm/IR/Value.h"
85#include "llvm/IR/ValueHandle.h"
86#include "llvm/IR/Verifier.h"
87#include "llvm/Pass.h"
88#include "llvm/Support/BranchProbability.h"
89#include "llvm/Support/CommandLine.h"
90#include "llvm/Support/Debug.h"
91#include "llvm/Support/raw_ostream.h"
92#include "llvm/Transforms/Scalar.h"
93#include "llvm/Transforms/Utils/BasicBlockUtils.h"
94#include "llvm/Transforms/Utils/Local.h"
95#include "llvm/Transforms/Utils/VectorUtils.h"
96#include "llvm/Transforms/Utils/LoopUtils.h"
97#include <algorithm>
98#include <map>
99#include <tuple>
100
101using namespace llvm;
102using namespace llvm::PatternMatch;
103
104#define LV_NAME "loop-vectorize"
105#define DEBUG_TYPE LV_NAME
106
107STATISTIC(LoopsVectorized, "Number of loops vectorized");
108STATISTIC(LoopsAnalyzed, "Number of loops analyzed for vectorization");
109
110static cl::opt<bool>
111EnableIfConversion("enable-if-conversion", cl::init(true), cl::Hidden,
112                   cl::desc("Enable if-conversion during vectorization."));
113
114/// We don't vectorize loops with a known constant trip count below this number.
115static cl::opt<unsigned>
116TinyTripCountVectorThreshold("vectorizer-min-trip-count", cl::init(16),
117                             cl::Hidden,
118                             cl::desc("Don't vectorize loops with a constant "
119                                      "trip count that is smaller than this "
120                                      "value."));
121
122/// This enables versioning on the strides of symbolically striding memory
123/// accesses in code like the following.
124///   for (i = 0; i < N; ++i)
125///     A[i * Stride1] += B[i * Stride2] ...
126///
127/// Will be roughly translated to
128///    if (Stride1 == 1 && Stride2 == 1) {
129///      for (i = 0; i < N; i+=4)
130///       A[i:i+3] += ...
131///    } else
132///      ...
133static cl::opt<bool> EnableMemAccessVersioning(
134    "enable-mem-access-versioning", cl::init(true), cl::Hidden,
135    cl::desc("Enable symblic stride memory access versioning"));
136
137/// We don't unroll loops with a known constant trip count below this number.
138static const unsigned TinyTripCountUnrollThreshold = 128;
139
140static cl::opt<unsigned> ForceTargetNumScalarRegs(
141    "force-target-num-scalar-regs", cl::init(0), cl::Hidden,
142    cl::desc("A flag that overrides the target's number of scalar registers."));
143
144static cl::opt<unsigned> ForceTargetNumVectorRegs(
145    "force-target-num-vector-regs", cl::init(0), cl::Hidden,
146    cl::desc("A flag that overrides the target's number of vector registers."));
147
148/// Maximum vectorization interleave count.
149static const unsigned MaxInterleaveFactor = 16;
150
151static cl::opt<unsigned> ForceTargetMaxScalarInterleaveFactor(
152    "force-target-max-scalar-interleave", cl::init(0), cl::Hidden,
153    cl::desc("A flag that overrides the target's max interleave factor for "
154             "scalar loops."));
155
156static cl::opt<unsigned> ForceTargetMaxVectorInterleaveFactor(
157    "force-target-max-vector-interleave", cl::init(0), cl::Hidden,
158    cl::desc("A flag that overrides the target's max interleave factor for "
159             "vectorized loops."));
160
161static cl::opt<unsigned> ForceTargetInstructionCost(
162    "force-target-instruction-cost", cl::init(0), cl::Hidden,
163    cl::desc("A flag that overrides the target's expected cost for "
164             "an instruction to a single constant value. Mostly "
165             "useful for getting consistent testing."));
166
167static cl::opt<unsigned> SmallLoopCost(
168    "small-loop-cost", cl::init(20), cl::Hidden,
169    cl::desc("The cost of a loop that is considered 'small' by the unroller."));
170
171static cl::opt<bool> LoopVectorizeWithBlockFrequency(
172    "loop-vectorize-with-block-frequency", cl::init(false), cl::Hidden,
173    cl::desc("Enable the use of the block frequency analysis to access PGO "
174             "heuristics minimizing code growth in cold regions and being more "
175             "aggressive in hot regions."));
176
177// Runtime unroll loops for load/store throughput.
178static cl::opt<bool> EnableLoadStoreRuntimeUnroll(
179    "enable-loadstore-runtime-unroll", cl::init(true), cl::Hidden,
180    cl::desc("Enable runtime unrolling until load/store ports are saturated"));
181
182/// The number of stores in a loop that are allowed to need predication.
183static cl::opt<unsigned> NumberOfStoresToPredicate(
184    "vectorize-num-stores-pred", cl::init(1), cl::Hidden,
185    cl::desc("Max number of stores to be predicated behind an if."));
186
187static cl::opt<bool> EnableIndVarRegisterHeur(
188    "enable-ind-var-reg-heur", cl::init(true), cl::Hidden,
189    cl::desc("Count the induction variable only once when unrolling"));
190
191static cl::opt<bool> EnableCondStoresVectorization(
192    "enable-cond-stores-vec", cl::init(false), cl::Hidden,
193    cl::desc("Enable if predication of stores during vectorization."));
194
195static cl::opt<unsigned> MaxNestedScalarReductionUF(
196    "max-nested-scalar-reduction-unroll", cl::init(2), cl::Hidden,
197    cl::desc("The maximum unroll factor to use when unrolling a scalar "
198             "reduction in a nested loop."));
199
200namespace {
201
202// Forward declarations.
203class LoopVectorizationLegality;
204class LoopVectorizationCostModel;
205class LoopVectorizeHints;
206
207/// \brief This modifies LoopAccessReport to initialize message with
208/// loop-vectorizer-specific part.
209class VectorizationReport : public LoopAccessReport {
210public:
211  VectorizationReport(Instruction *I = nullptr)
212      : LoopAccessReport("loop not vectorized: ", I) {}
213
214  /// \brief This allows promotion of the loop-access analysis report into the
215  /// loop-vectorizer report.  It modifies the message to add the
216  /// loop-vectorizer-specific part of the message.
217  explicit VectorizationReport(const LoopAccessReport &R)
218      : LoopAccessReport(Twine("loop not vectorized: ") + R.str(),
219                         R.getInstr()) {}
220};
221
222/// A helper function for converting Scalar types to vector types.
223/// If the incoming type is void, we return void. If the VF is 1, we return
224/// the scalar type.
225static Type* ToVectorTy(Type *Scalar, unsigned VF) {
226  if (Scalar->isVoidTy() || VF == 1)
227    return Scalar;
228  return VectorType::get(Scalar, VF);
229}
230
231/// InnerLoopVectorizer vectorizes loops which contain only one basic
232/// block to a specified vectorization factor (VF).
233/// This class performs the widening of scalars into vectors, or multiple
234/// scalars. This class also implements the following features:
235/// * It inserts an epilogue loop for handling loops that don't have iteration
236///   counts that are known to be a multiple of the vectorization factor.
237/// * It handles the code generation for reduction variables.
238/// * Scalarization (implementation using scalars) of un-vectorizable
239///   instructions.
240/// InnerLoopVectorizer does not perform any vectorization-legality
241/// checks, and relies on the caller to check for the different legality
242/// aspects. The InnerLoopVectorizer relies on the
243/// LoopVectorizationLegality class to provide information about the induction
244/// and reduction variables that were found to a given vectorization factor.
245class InnerLoopVectorizer {
246public:
247  InnerLoopVectorizer(Loop *OrigLoop, ScalarEvolution *SE, LoopInfo *LI,
248                      DominatorTree *DT, const TargetLibraryInfo *TLI,
249                      const TargetTransformInfo *TTI, unsigned VecWidth,
250                      unsigned UnrollFactor)
251      : OrigLoop(OrigLoop), SE(SE), LI(LI), DT(DT), TLI(TLI), TTI(TTI),
252        VF(VecWidth), UF(UnrollFactor), Builder(SE->getContext()),
253        Induction(nullptr), OldInduction(nullptr), WidenMap(UnrollFactor),
254        Legal(nullptr), AddedSafetyChecks(false) {}
255
256  // Perform the actual loop widening (vectorization).
257  void vectorize(LoopVectorizationLegality *L) {
258    Legal = L;
259    // Create a new empty loop. Unlink the old loop and connect the new one.
260    createEmptyLoop();
261    // Widen each instruction in the old loop to a new one in the new loop.
262    // Use the Legality module to find the induction and reduction variables.
263    vectorizeLoop();
264    // Register the new loop and update the analysis passes.
265    updateAnalysis();
266  }
267
268  // Return true if any runtime check is added.
269  bool IsSafetyChecksAdded() {
270    return AddedSafetyChecks;
271  }
272
273  virtual ~InnerLoopVectorizer() {}
274
275protected:
276  /// A small list of PHINodes.
277  typedef SmallVector<PHINode*, 4> PhiVector;
278  /// When we unroll loops we have multiple vector values for each scalar.
279  /// This data structure holds the unrolled and vectorized values that
280  /// originated from one scalar instruction.
281  typedef SmallVector<Value*, 2> VectorParts;
282
283  // When we if-convert we need create edge masks. We have to cache values so
284  // that we don't end up with exponential recursion/IR.
285  typedef DenseMap<std::pair<BasicBlock*, BasicBlock*>,
286                   VectorParts> EdgeMaskCache;
287
288  /// \brief Add checks for strides that where assumed to be 1.
289  ///
290  /// Returns the last check instruction and the first check instruction in the
291  /// pair as (first, last).
292  std::pair<Instruction *, Instruction *> addStrideCheck(Instruction *Loc);
293
294  /// Create an empty loop, based on the loop ranges of the old loop.
295  void createEmptyLoop();
296  /// Copy and widen the instructions from the old loop.
297  virtual void vectorizeLoop();
298
299  /// \brief The Loop exit block may have single value PHI nodes where the
300  /// incoming value is 'Undef'. While vectorizing we only handled real values
301  /// that were defined inside the loop. Here we fix the 'undef case'.
302  /// See PR14725.
303  void fixLCSSAPHIs();
304
305  /// A helper function that computes the predicate of the block BB, assuming
306  /// that the header block of the loop is set to True. It returns the *entry*
307  /// mask for the block BB.
308  VectorParts createBlockInMask(BasicBlock *BB);
309  /// A helper function that computes the predicate of the edge between SRC
310  /// and DST.
311  VectorParts createEdgeMask(BasicBlock *Src, BasicBlock *Dst);
312
313  /// A helper function to vectorize a single BB within the innermost loop.
314  void vectorizeBlockInLoop(BasicBlock *BB, PhiVector *PV);
315
316  /// Vectorize a single PHINode in a block. This method handles the induction
317  /// variable canonicalization. It supports both VF = 1 for unrolled loops and
318  /// arbitrary length vectors.
319  void widenPHIInstruction(Instruction *PN, VectorParts &Entry,
320                           unsigned UF, unsigned VF, PhiVector *PV);
321
322  /// Insert the new loop to the loop hierarchy and pass manager
323  /// and update the analysis passes.
324  void updateAnalysis();
325
326  /// This instruction is un-vectorizable. Implement it as a sequence
327  /// of scalars. If \p IfPredicateStore is true we need to 'hide' each
328  /// scalarized instruction behind an if block predicated on the control
329  /// dependence of the instruction.
330  virtual void scalarizeInstruction(Instruction *Instr,
331                                    bool IfPredicateStore=false);
332
333  /// Vectorize Load and Store instructions,
334  virtual void vectorizeMemoryInstruction(Instruction *Instr);
335
336  /// Create a broadcast instruction. This method generates a broadcast
337  /// instruction (shuffle) for loop invariant values and for the induction
338  /// value. If this is the induction variable then we extend it to N, N+1, ...
339  /// this is needed because each iteration in the loop corresponds to a SIMD
340  /// element.
341  virtual Value *getBroadcastInstrs(Value *V);
342
343  /// This function adds (StartIdx, StartIdx + Step, StartIdx + 2*Step, ...)
344  /// to each vector element of Val. The sequence starts at StartIndex.
345  virtual Value *getStepVector(Value *Val, int StartIdx, Value *Step);
346
347  /// When we go over instructions in the basic block we rely on previous
348  /// values within the current basic block or on loop invariant values.
349  /// When we widen (vectorize) values we place them in the map. If the values
350  /// are not within the map, they have to be loop invariant, so we simply
351  /// broadcast them into a vector.
352  VectorParts &getVectorValue(Value *V);
353
354  /// Generate a shuffle sequence that will reverse the vector Vec.
355  virtual Value *reverseVector(Value *Vec);
356
357  /// This is a helper class that holds the vectorizer state. It maps scalar
358  /// instructions to vector instructions. When the code is 'unrolled' then
359  /// then a single scalar value is mapped to multiple vector parts. The parts
360  /// are stored in the VectorPart type.
361  struct ValueMap {
362    /// C'tor.  UnrollFactor controls the number of vectors ('parts') that
363    /// are mapped.
364    ValueMap(unsigned UnrollFactor) : UF(UnrollFactor) {}
365
366    /// \return True if 'Key' is saved in the Value Map.
367    bool has(Value *Key) const { return MapStorage.count(Key); }
368
369    /// Initializes a new entry in the map. Sets all of the vector parts to the
370    /// save value in 'Val'.
371    /// \return A reference to a vector with splat values.
372    VectorParts &splat(Value *Key, Value *Val) {
373      VectorParts &Entry = MapStorage[Key];
374      Entry.assign(UF, Val);
375      return Entry;
376    }
377
378    ///\return A reference to the value that is stored at 'Key'.
379    VectorParts &get(Value *Key) {
380      VectorParts &Entry = MapStorage[Key];
381      if (Entry.empty())
382        Entry.resize(UF);
383      assert(Entry.size() == UF);
384      return Entry;
385    }
386
387  private:
388    /// The unroll factor. Each entry in the map stores this number of vector
389    /// elements.
390    unsigned UF;
391
392    /// Map storage. We use std::map and not DenseMap because insertions to a
393    /// dense map invalidates its iterators.
394    std::map<Value *, VectorParts> MapStorage;
395  };
396
397  /// The original loop.
398  Loop *OrigLoop;
399  /// Scev analysis to use.
400  ScalarEvolution *SE;
401  /// Loop Info.
402  LoopInfo *LI;
403  /// Dominator Tree.
404  DominatorTree *DT;
405  /// Alias Analysis.
406  AliasAnalysis *AA;
407  /// Target Library Info.
408  const TargetLibraryInfo *TLI;
409  /// Target Transform Info.
410  const TargetTransformInfo *TTI;
411
412  /// The vectorization SIMD factor to use. Each vector will have this many
413  /// vector elements.
414  unsigned VF;
415
416protected:
417  /// The vectorization unroll factor to use. Each scalar is vectorized to this
418  /// many different vector instructions.
419  unsigned UF;
420
421  /// The builder that we use
422  IRBuilder<> Builder;
423
424  // --- Vectorization state ---
425
426  /// The vector-loop preheader.
427  BasicBlock *LoopVectorPreHeader;
428  /// The scalar-loop preheader.
429  BasicBlock *LoopScalarPreHeader;
430  /// Middle Block between the vector and the scalar.
431  BasicBlock *LoopMiddleBlock;
432  ///The ExitBlock of the scalar loop.
433  BasicBlock *LoopExitBlock;
434  ///The vector loop body.
435  SmallVector<BasicBlock *, 4> LoopVectorBody;
436  ///The scalar loop body.
437  BasicBlock *LoopScalarBody;
438  /// A list of all bypass blocks. The first block is the entry of the loop.
439  SmallVector<BasicBlock *, 4> LoopBypassBlocks;
440
441  /// The new Induction variable which was added to the new block.
442  PHINode *Induction;
443  /// The induction variable of the old basic block.
444  PHINode *OldInduction;
445  /// Holds the extended (to the widest induction type) start index.
446  Value *ExtendedIdx;
447  /// Maps scalars to widened vectors.
448  ValueMap WidenMap;
449  EdgeMaskCache MaskCache;
450
451  LoopVectorizationLegality *Legal;
452
453  // Record whether runtime check is added.
454  bool AddedSafetyChecks;
455};
456
457class InnerLoopUnroller : public InnerLoopVectorizer {
458public:
459  InnerLoopUnroller(Loop *OrigLoop, ScalarEvolution *SE, LoopInfo *LI,
460                    DominatorTree *DT, const TargetLibraryInfo *TLI,
461                    const TargetTransformInfo *TTI, unsigned UnrollFactor)
462      : InnerLoopVectorizer(OrigLoop, SE, LI, DT, TLI, TTI, 1, UnrollFactor) {}
463
464private:
465  void scalarizeInstruction(Instruction *Instr,
466                            bool IfPredicateStore = false) override;
467  void vectorizeMemoryInstruction(Instruction *Instr) override;
468  Value *getBroadcastInstrs(Value *V) override;
469  Value *getStepVector(Value *Val, int StartIdx, Value *Step) override;
470  Value *reverseVector(Value *Vec) override;
471};
472
473/// \brief Look for a meaningful debug location on the instruction or it's
474/// operands.
475static Instruction *getDebugLocFromInstOrOperands(Instruction *I) {
476  if (!I)
477    return I;
478
479  DebugLoc Empty;
480  if (I->getDebugLoc() != Empty)
481    return I;
482
483  for (User::op_iterator OI = I->op_begin(), OE = I->op_end(); OI != OE; ++OI) {
484    if (Instruction *OpInst = dyn_cast<Instruction>(*OI))
485      if (OpInst->getDebugLoc() != Empty)
486        return OpInst;
487  }
488
489  return I;
490}
491
492/// \brief Set the debug location in the builder using the debug location in the
493/// instruction.
494static void setDebugLocFromInst(IRBuilder<> &B, const Value *Ptr) {
495  if (const Instruction *Inst = dyn_cast_or_null<Instruction>(Ptr))
496    B.SetCurrentDebugLocation(Inst->getDebugLoc());
497  else
498    B.SetCurrentDebugLocation(DebugLoc());
499}
500
501#ifndef NDEBUG
502/// \return string containing a file name and a line # for the given loop.
503static std::string getDebugLocString(const Loop *L) {
504  std::string Result;
505  if (L) {
506    raw_string_ostream OS(Result);
507    if (const DebugLoc LoopDbgLoc = L->getStartLoc())
508      LoopDbgLoc.print(OS);
509    else
510      // Just print the module name.
511      OS << L->getHeader()->getParent()->getParent()->getModuleIdentifier();
512    OS.flush();
513  }
514  return Result;
515}
516#endif
517
518/// \brief Propagate known metadata from one instruction to another.
519static void propagateMetadata(Instruction *To, const Instruction *From) {
520  SmallVector<std::pair<unsigned, MDNode *>, 4> Metadata;
521  From->getAllMetadataOtherThanDebugLoc(Metadata);
522
523  for (auto M : Metadata) {
524    unsigned Kind = M.first;
525
526    // These are safe to transfer (this is safe for TBAA, even when we
527    // if-convert, because should that metadata have had a control dependency
528    // on the condition, and thus actually aliased with some other
529    // non-speculated memory access when the condition was false, this would be
530    // caught by the runtime overlap checks).
531    if (Kind != LLVMContext::MD_tbaa &&
532        Kind != LLVMContext::MD_alias_scope &&
533        Kind != LLVMContext::MD_noalias &&
534        Kind != LLVMContext::MD_fpmath)
535      continue;
536
537    To->setMetadata(Kind, M.second);
538  }
539}
540
541/// \brief Propagate known metadata from one instruction to a vector of others.
542static void propagateMetadata(SmallVectorImpl<Value *> &To, const Instruction *From) {
543  for (Value *V : To)
544    if (Instruction *I = dyn_cast<Instruction>(V))
545      propagateMetadata(I, From);
546}
547
548/// LoopVectorizationLegality checks if it is legal to vectorize a loop, and
549/// to what vectorization factor.
550/// This class does not look at the profitability of vectorization, only the
551/// legality. This class has two main kinds of checks:
552/// * Memory checks - The code in canVectorizeMemory checks if vectorization
553///   will change the order of memory accesses in a way that will change the
554///   correctness of the program.
555/// * Scalars checks - The code in canVectorizeInstrs and canVectorizeMemory
556/// checks for a number of different conditions, such as the availability of a
557/// single induction variable, that all types are supported and vectorize-able,
558/// etc. This code reflects the capabilities of InnerLoopVectorizer.
559/// This class is also used by InnerLoopVectorizer for identifying
560/// induction variable and the different reduction variables.
561class LoopVectorizationLegality {
562public:
563  LoopVectorizationLegality(Loop *L, ScalarEvolution *SE, DominatorTree *DT,
564                            TargetLibraryInfo *TLI, AliasAnalysis *AA,
565                            Function *F, const TargetTransformInfo *TTI,
566                            LoopAccessAnalysis *LAA)
567      : NumPredStores(0), TheLoop(L), SE(SE), TLI(TLI), TheFunction(F),
568        TTI(TTI), DT(DT), LAA(LAA), LAI(nullptr), Induction(nullptr),
569        WidestIndTy(nullptr), HasFunNoNaNAttr(false) {}
570
571  /// This enum represents the kinds of reductions that we support.
572  enum ReductionKind {
573    RK_NoReduction, ///< Not a reduction.
574    RK_IntegerAdd,  ///< Sum of integers.
575    RK_IntegerMult, ///< Product of integers.
576    RK_IntegerOr,   ///< Bitwise or logical OR of numbers.
577    RK_IntegerAnd,  ///< Bitwise or logical AND of numbers.
578    RK_IntegerXor,  ///< Bitwise or logical XOR of numbers.
579    RK_IntegerMinMax, ///< Min/max implemented in terms of select(cmp()).
580    RK_FloatAdd,    ///< Sum of floats.
581    RK_FloatMult,   ///< Product of floats.
582    RK_FloatMinMax  ///< Min/max implemented in terms of select(cmp()).
583  };
584
585  /// This enum represents the kinds of inductions that we support.
586  enum InductionKind {
587    IK_NoInduction,  ///< Not an induction variable.
588    IK_IntInduction, ///< Integer induction variable. Step = C.
589    IK_PtrInduction  ///< Pointer induction var. Step = C / sizeof(elem).
590  };
591
592  // This enum represents the kind of minmax reduction.
593  enum MinMaxReductionKind {
594    MRK_Invalid,
595    MRK_UIntMin,
596    MRK_UIntMax,
597    MRK_SIntMin,
598    MRK_SIntMax,
599    MRK_FloatMin,
600    MRK_FloatMax
601  };
602
603  /// This struct holds information about reduction variables.
604  struct ReductionDescriptor {
605    ReductionDescriptor() : StartValue(nullptr), LoopExitInstr(nullptr),
606      Kind(RK_NoReduction), MinMaxKind(MRK_Invalid) {}
607
608    ReductionDescriptor(Value *Start, Instruction *Exit, ReductionKind K,
609                        MinMaxReductionKind MK)
610        : StartValue(Start), LoopExitInstr(Exit), Kind(K), MinMaxKind(MK) {}
611
612    // The starting value of the reduction.
613    // It does not have to be zero!
614    TrackingVH<Value> StartValue;
615    // The instruction who's value is used outside the loop.
616    Instruction *LoopExitInstr;
617    // The kind of the reduction.
618    ReductionKind Kind;
619    // If this a min/max reduction the kind of reduction.
620    MinMaxReductionKind MinMaxKind;
621  };
622
623  /// This POD struct holds information about a potential reduction operation.
624  struct ReductionInstDesc {
625    ReductionInstDesc(bool IsRedux, Instruction *I) :
626      IsReduction(IsRedux), PatternLastInst(I), MinMaxKind(MRK_Invalid) {}
627
628    ReductionInstDesc(Instruction *I, MinMaxReductionKind K) :
629      IsReduction(true), PatternLastInst(I), MinMaxKind(K) {}
630
631    // Is this instruction a reduction candidate.
632    bool IsReduction;
633    // The last instruction in a min/max pattern (select of the select(icmp())
634    // pattern), or the current reduction instruction otherwise.
635    Instruction *PatternLastInst;
636    // If this is a min/max pattern the comparison predicate.
637    MinMaxReductionKind MinMaxKind;
638  };
639
640  /// A struct for saving information about induction variables.
641  struct InductionInfo {
642    InductionInfo(Value *Start, InductionKind K, ConstantInt *Step)
643        : StartValue(Start), IK(K), StepValue(Step) {
644      assert(IK != IK_NoInduction && "Not an induction");
645      assert(StartValue && "StartValue is null");
646      assert(StepValue && !StepValue->isZero() && "StepValue is zero");
647      assert((IK != IK_PtrInduction || StartValue->getType()->isPointerTy()) &&
648             "StartValue is not a pointer for pointer induction");
649      assert((IK != IK_IntInduction || StartValue->getType()->isIntegerTy()) &&
650             "StartValue is not an integer for integer induction");
651      assert(StepValue->getType()->isIntegerTy() &&
652             "StepValue is not an integer");
653    }
654    InductionInfo()
655        : StartValue(nullptr), IK(IK_NoInduction), StepValue(nullptr) {}
656
657    /// Get the consecutive direction. Returns:
658    ///   0 - unknown or non-consecutive.
659    ///   1 - consecutive and increasing.
660    ///  -1 - consecutive and decreasing.
661    int getConsecutiveDirection() const {
662      if (StepValue && (StepValue->isOne() || StepValue->isMinusOne()))
663        return StepValue->getSExtValue();
664      return 0;
665    }
666
667    /// Compute the transformed value of Index at offset StartValue using step
668    /// StepValue.
669    /// For integer induction, returns StartValue + Index * StepValue.
670    /// For pointer induction, returns StartValue[Index * StepValue].
671    /// FIXME: The newly created binary instructions should contain nsw/nuw
672    /// flags, which can be found from the original scalar operations.
673    Value *transform(IRBuilder<> &B, Value *Index) const {
674      switch (IK) {
675      case IK_IntInduction:
676        assert(Index->getType() == StartValue->getType() &&
677               "Index type does not match StartValue type");
678        if (StepValue->isMinusOne())
679          return B.CreateSub(StartValue, Index);
680        if (!StepValue->isOne())
681          Index = B.CreateMul(Index, StepValue);
682        return B.CreateAdd(StartValue, Index);
683
684      case IK_PtrInduction:
685        if (StepValue->isMinusOne())
686          Index = B.CreateNeg(Index);
687        else if (!StepValue->isOne())
688          Index = B.CreateMul(Index, StepValue);
689        return B.CreateGEP(nullptr, StartValue, Index);
690
691      case IK_NoInduction:
692        return nullptr;
693      }
694      llvm_unreachable("invalid enum");
695    }
696
697    /// Start value.
698    TrackingVH<Value> StartValue;
699    /// Induction kind.
700    InductionKind IK;
701    /// Step value.
702    ConstantInt *StepValue;
703  };
704
705  /// ReductionList contains the reduction descriptors for all
706  /// of the reductions that were found in the loop.
707  typedef DenseMap<PHINode*, ReductionDescriptor> ReductionList;
708
709  /// InductionList saves induction variables and maps them to the
710  /// induction descriptor.
711  typedef MapVector<PHINode*, InductionInfo> InductionList;
712
713  /// Returns true if it is legal to vectorize this loop.
714  /// This does not mean that it is profitable to vectorize this
715  /// loop, only that it is legal to do so.
716  bool canVectorize();
717
718  /// Returns the Induction variable.
719  PHINode *getInduction() { return Induction; }
720
721  /// Returns the reduction variables found in the loop.
722  ReductionList *getReductionVars() { return &Reductions; }
723
724  /// Returns the induction variables found in the loop.
725  InductionList *getInductionVars() { return &Inductions; }
726
727  /// Returns the widest induction type.
728  Type *getWidestInductionType() { return WidestIndTy; }
729
730  /// Returns True if V is an induction variable in this loop.
731  bool isInductionVariable(const Value *V);
732
733  /// Return true if the block BB needs to be predicated in order for the loop
734  /// to be vectorized.
735  bool blockNeedsPredication(BasicBlock *BB);
736
737  /// Check if this  pointer is consecutive when vectorizing. This happens
738  /// when the last index of the GEP is the induction variable, or that the
739  /// pointer itself is an induction variable.
740  /// This check allows us to vectorize A[idx] into a wide load/store.
741  /// Returns:
742  /// 0 - Stride is unknown or non-consecutive.
743  /// 1 - Address is consecutive.
744  /// -1 - Address is consecutive, and decreasing.
745  int isConsecutivePtr(Value *Ptr);
746
747  /// Returns true if the value V is uniform within the loop.
748  bool isUniform(Value *V);
749
750  /// Returns true if this instruction will remain scalar after vectorization.
751  bool isUniformAfterVectorization(Instruction* I) { return Uniforms.count(I); }
752
753  /// Returns the information that we collected about runtime memory check.
754  const LoopAccessInfo::RuntimePointerCheck *getRuntimePointerCheck() const {
755    return LAI->getRuntimePointerCheck();
756  }
757
758  const LoopAccessInfo *getLAI() const {
759    return LAI;
760  }
761
762  /// This function returns the identity element (or neutral element) for
763  /// the operation K.
764  static Constant *getReductionIdentity(ReductionKind K, Type *Tp);
765
766  unsigned getMaxSafeDepDistBytes() { return LAI->getMaxSafeDepDistBytes(); }
767
768  bool hasStride(Value *V) { return StrideSet.count(V); }
769  bool mustCheckStrides() { return !StrideSet.empty(); }
770  SmallPtrSet<Value *, 8>::iterator strides_begin() {
771    return StrideSet.begin();
772  }
773  SmallPtrSet<Value *, 8>::iterator strides_end() { return StrideSet.end(); }
774
775  /// Returns true if the target machine supports masked store operation
776  /// for the given \p DataType and kind of access to \p Ptr.
777  bool isLegalMaskedStore(Type *DataType, Value *Ptr) {
778    return TTI->isLegalMaskedStore(DataType, isConsecutivePtr(Ptr));
779  }
780  /// Returns true if the target machine supports masked load operation
781  /// for the given \p DataType and kind of access to \p Ptr.
782  bool isLegalMaskedLoad(Type *DataType, Value *Ptr) {
783    return TTI->isLegalMaskedLoad(DataType, isConsecutivePtr(Ptr));
784  }
785  /// Returns true if vector representation of the instruction \p I
786  /// requires mask.
787  bool isMaskRequired(const Instruction* I) {
788    return (MaskedOp.count(I) != 0);
789  }
790  unsigned getNumStores() const {
791    return LAI->getNumStores();
792  }
793  unsigned getNumLoads() const {
794    return LAI->getNumLoads();
795  }
796  unsigned getNumPredStores() const {
797    return NumPredStores;
798  }
799private:
800  /// Check if a single basic block loop is vectorizable.
801  /// At this point we know that this is a loop with a constant trip count
802  /// and we only need to check individual instructions.
803  bool canVectorizeInstrs();
804
805  /// When we vectorize loops we may change the order in which
806  /// we read and write from memory. This method checks if it is
807  /// legal to vectorize the code, considering only memory constrains.
808  /// Returns true if the loop is vectorizable
809  bool canVectorizeMemory();
810
811  /// Return true if we can vectorize this loop using the IF-conversion
812  /// transformation.
813  bool canVectorizeWithIfConvert();
814
815  /// Collect the variables that need to stay uniform after vectorization.
816  void collectLoopUniforms();
817
818  /// Return true if all of the instructions in the block can be speculatively
819  /// executed. \p SafePtrs is a list of addresses that are known to be legal
820  /// and we know that we can read from them without segfault.
821  bool blockCanBePredicated(BasicBlock *BB, SmallPtrSetImpl<Value *> &SafePtrs);
822
823  /// Returns True, if 'Phi' is the kind of reduction variable for type
824  /// 'Kind'. If this is a reduction variable, it adds it to ReductionList.
825  bool AddReductionVar(PHINode *Phi, ReductionKind Kind);
826  /// Returns a struct describing if the instruction 'I' can be a reduction
827  /// variable of type 'Kind'. If the reduction is a min/max pattern of
828  /// select(icmp()) this function advances the instruction pointer 'I' from the
829  /// compare instruction to the select instruction and stores this pointer in
830  /// 'PatternLastInst' member of the returned struct.
831  ReductionInstDesc isReductionInstr(Instruction *I, ReductionKind Kind,
832                                     ReductionInstDesc &Desc);
833  /// Returns true if the instruction is a Select(ICmp(X, Y), X, Y) instruction
834  /// pattern corresponding to a min(X, Y) or max(X, Y).
835  static ReductionInstDesc isMinMaxSelectCmpPattern(Instruction *I,
836                                                    ReductionInstDesc &Prev);
837  /// Returns the induction kind of Phi and record the step. This function may
838  /// return NoInduction if the PHI is not an induction variable.
839  InductionKind isInductionVariable(PHINode *Phi, ConstantInt *&StepValue);
840
841  /// \brief Collect memory access with loop invariant strides.
842  ///
843  /// Looks for accesses like "a[i * StrideA]" where "StrideA" is loop
844  /// invariant.
845  void collectStridedAccess(Value *LoadOrStoreInst);
846
847  /// Report an analysis message to assist the user in diagnosing loops that are
848  /// not vectorized.  These are handled as LoopAccessReport rather than
849  /// VectorizationReport because the << operator of VectorizationReport returns
850  /// LoopAccessReport.
851  void emitAnalysis(const LoopAccessReport &Message) {
852    LoopAccessReport::emitAnalysis(Message, TheFunction, TheLoop, LV_NAME);
853  }
854
855  unsigned NumPredStores;
856
857  /// The loop that we evaluate.
858  Loop *TheLoop;
859  /// Scev analysis.
860  ScalarEvolution *SE;
861  /// Target Library Info.
862  TargetLibraryInfo *TLI;
863  /// Parent function
864  Function *TheFunction;
865  /// Target Transform Info
866  const TargetTransformInfo *TTI;
867  /// Dominator Tree.
868  DominatorTree *DT;
869  // LoopAccess analysis.
870  LoopAccessAnalysis *LAA;
871  // And the loop-accesses info corresponding to this loop.  This pointer is
872  // null until canVectorizeMemory sets it up.
873  const LoopAccessInfo *LAI;
874
875  //  ---  vectorization state --- //
876
877  /// Holds the integer induction variable. This is the counter of the
878  /// loop.
879  PHINode *Induction;
880  /// Holds the reduction variables.
881  ReductionList Reductions;
882  /// Holds all of the induction variables that we found in the loop.
883  /// Notice that inductions don't need to start at zero and that induction
884  /// variables can be pointers.
885  InductionList Inductions;
886  /// Holds the widest induction type encountered.
887  Type *WidestIndTy;
888
889  /// Allowed outside users. This holds the reduction
890  /// vars which can be accessed from outside the loop.
891  SmallPtrSet<Value*, 4> AllowedExit;
892  /// This set holds the variables which are known to be uniform after
893  /// vectorization.
894  SmallPtrSet<Instruction*, 4> Uniforms;
895
896  /// Can we assume the absence of NaNs.
897  bool HasFunNoNaNAttr;
898
899  ValueToValueMap Strides;
900  SmallPtrSet<Value *, 8> StrideSet;
901
902  /// While vectorizing these instructions we have to generate a
903  /// call to the appropriate masked intrinsic
904  SmallPtrSet<const Instruction*, 8> MaskedOp;
905};
906
907/// LoopVectorizationCostModel - estimates the expected speedups due to
908/// vectorization.
909/// In many cases vectorization is not profitable. This can happen because of
910/// a number of reasons. In this class we mainly attempt to predict the
911/// expected speedup/slowdowns due to the supported instruction set. We use the
912/// TargetTransformInfo to query the different backends for the cost of
913/// different operations.
914class LoopVectorizationCostModel {
915public:
916  LoopVectorizationCostModel(Loop *L, ScalarEvolution *SE, LoopInfo *LI,
917                             LoopVectorizationLegality *Legal,
918                             const TargetTransformInfo &TTI,
919                             const TargetLibraryInfo *TLI, AssumptionCache *AC,
920                             const Function *F, const LoopVectorizeHints *Hints)
921      : TheLoop(L), SE(SE), LI(LI), Legal(Legal), TTI(TTI), TLI(TLI),
922        TheFunction(F), Hints(Hints) {
923    CodeMetrics::collectEphemeralValues(L, AC, EphValues);
924  }
925
926  /// Information about vectorization costs
927  struct VectorizationFactor {
928    unsigned Width; // Vector width with best cost
929    unsigned Cost; // Cost of the loop with that width
930  };
931  /// \return The most profitable vectorization factor and the cost of that VF.
932  /// This method checks every power of two up to VF. If UserVF is not ZERO
933  /// then this vectorization factor will be selected if vectorization is
934  /// possible.
935  VectorizationFactor selectVectorizationFactor(bool OptForSize);
936
937  /// \return The size (in bits) of the widest type in the code that
938  /// needs to be vectorized. We ignore values that remain scalar such as
939  /// 64 bit loop indices.
940  unsigned getWidestType();
941
942  /// \return The most profitable unroll factor.
943  /// If UserUF is non-zero then this method finds the best unroll-factor
944  /// based on register pressure and other parameters.
945  /// VF and LoopCost are the selected vectorization factor and the cost of the
946  /// selected VF.
947  unsigned selectUnrollFactor(bool OptForSize, unsigned VF, unsigned LoopCost);
948
949  /// \brief A struct that represents some properties of the register usage
950  /// of a loop.
951  struct RegisterUsage {
952    /// Holds the number of loop invariant values that are used in the loop.
953    unsigned LoopInvariantRegs;
954    /// Holds the maximum number of concurrent live intervals in the loop.
955    unsigned MaxLocalUsers;
956    /// Holds the number of instructions in the loop.
957    unsigned NumInstructions;
958  };
959
960  /// \return  information about the register usage of the loop.
961  RegisterUsage calculateRegisterUsage();
962
963private:
964  /// Returns the expected execution cost. The unit of the cost does
965  /// not matter because we use the 'cost' units to compare different
966  /// vector widths. The cost that is returned is *not* normalized by
967  /// the factor width.
968  unsigned expectedCost(unsigned VF);
969
970  /// Returns the execution time cost of an instruction for a given vector
971  /// width. Vector width of one means scalar.
972  unsigned getInstructionCost(Instruction *I, unsigned VF);
973
974  /// Returns whether the instruction is a load or store and will be a emitted
975  /// as a vector operation.
976  bool isConsecutiveLoadOrStore(Instruction *I);
977
978  /// Report an analysis message to assist the user in diagnosing loops that are
979  /// not vectorized.  These are handled as LoopAccessReport rather than
980  /// VectorizationReport because the << operator of VectorizationReport returns
981  /// LoopAccessReport.
982  void emitAnalysis(const LoopAccessReport &Message) {
983    LoopAccessReport::emitAnalysis(Message, TheFunction, TheLoop, LV_NAME);
984  }
985
986  /// Values used only by @llvm.assume calls.
987  SmallPtrSet<const Value *, 32> EphValues;
988
989  /// The loop that we evaluate.
990  Loop *TheLoop;
991  /// Scev analysis.
992  ScalarEvolution *SE;
993  /// Loop Info analysis.
994  LoopInfo *LI;
995  /// Vectorization legality.
996  LoopVectorizationLegality *Legal;
997  /// Vector target information.
998  const TargetTransformInfo &TTI;
999  /// Target Library Info.
1000  const TargetLibraryInfo *TLI;
1001  const Function *TheFunction;
1002  // Loop Vectorize Hint.
1003  const LoopVectorizeHints *Hints;
1004};
1005
1006/// Utility class for getting and setting loop vectorizer hints in the form
1007/// of loop metadata.
1008/// This class keeps a number of loop annotations locally (as member variables)
1009/// and can, upon request, write them back as metadata on the loop. It will
1010/// initially scan the loop for existing metadata, and will update the local
1011/// values based on information in the loop.
1012/// We cannot write all values to metadata, as the mere presence of some info,
1013/// for example 'force', means a decision has been made. So, we need to be
1014/// careful NOT to add them if the user hasn't specifically asked so.
1015class LoopVectorizeHints {
1016  enum HintKind {
1017    HK_WIDTH,
1018    HK_UNROLL,
1019    HK_FORCE
1020  };
1021
1022  /// Hint - associates name and validation with the hint value.
1023  struct Hint {
1024    const char * Name;
1025    unsigned Value; // This may have to change for non-numeric values.
1026    HintKind Kind;
1027
1028    Hint(const char * Name, unsigned Value, HintKind Kind)
1029      : Name(Name), Value(Value), Kind(Kind) { }
1030
1031    bool validate(unsigned Val) {
1032      switch (Kind) {
1033      case HK_WIDTH:
1034        return isPowerOf2_32(Val) && Val <= VectorizerParams::MaxVectorWidth;
1035      case HK_UNROLL:
1036        return isPowerOf2_32(Val) && Val <= MaxInterleaveFactor;
1037      case HK_FORCE:
1038        return (Val <= 1);
1039      }
1040      return false;
1041    }
1042  };
1043
1044  /// Vectorization width.
1045  Hint Width;
1046  /// Vectorization interleave factor.
1047  Hint Interleave;
1048  /// Vectorization forced
1049  Hint Force;
1050
1051  /// Return the loop metadata prefix.
1052  static StringRef Prefix() { return "llvm.loop."; }
1053
1054public:
1055  enum ForceKind {
1056    FK_Undefined = -1, ///< Not selected.
1057    FK_Disabled = 0,   ///< Forcing disabled.
1058    FK_Enabled = 1,    ///< Forcing enabled.
1059  };
1060
1061  LoopVectorizeHints(const Loop *L, bool DisableInterleaving)
1062      : Width("vectorize.width", VectorizerParams::VectorizationFactor,
1063              HK_WIDTH),
1064        Interleave("interleave.count", DisableInterleaving, HK_UNROLL),
1065        Force("vectorize.enable", FK_Undefined, HK_FORCE),
1066        TheLoop(L) {
1067    // Populate values with existing loop metadata.
1068    getHintsFromMetadata();
1069
1070    // force-vector-interleave overrides DisableInterleaving.
1071    if (VectorizerParams::isInterleaveForced())
1072      Interleave.Value = VectorizerParams::VectorizationInterleave;
1073
1074    DEBUG(if (DisableInterleaving && Interleave.Value == 1) dbgs()
1075          << "LV: Interleaving disabled by the pass manager\n");
1076  }
1077
1078  /// Mark the loop L as already vectorized by setting the width to 1.
1079  void setAlreadyVectorized() {
1080    Width.Value = Interleave.Value = 1;
1081    Hint Hints[] = {Width, Interleave};
1082    writeHintsToMetadata(Hints);
1083  }
1084
1085  /// Dumps all the hint information.
1086  std::string emitRemark() const {
1087    VectorizationReport R;
1088    if (Force.Value == LoopVectorizeHints::FK_Disabled)
1089      R << "vectorization is explicitly disabled";
1090    else {
1091      R << "use -Rpass-analysis=loop-vectorize for more info";
1092      if (Force.Value == LoopVectorizeHints::FK_Enabled) {
1093        R << " (Force=true";
1094        if (Width.Value != 0)
1095          R << ", Vector Width=" << Width.Value;
1096        if (Interleave.Value != 0)
1097          R << ", Interleave Count=" << Interleave.Value;
1098        R << ")";
1099      }
1100    }
1101
1102    return R.str();
1103  }
1104
1105  unsigned getWidth() const { return Width.Value; }
1106  unsigned getInterleave() const { return Interleave.Value; }
1107  enum ForceKind getForce() const { return (ForceKind)Force.Value; }
1108
1109private:
1110  /// Find hints specified in the loop metadata and update local values.
1111  void getHintsFromMetadata() {
1112    MDNode *LoopID = TheLoop->getLoopID();
1113    if (!LoopID)
1114      return;
1115
1116    // First operand should refer to the loop id itself.
1117    assert(LoopID->getNumOperands() > 0 && "requires at least one operand");
1118    assert(LoopID->getOperand(0) == LoopID && "invalid loop id");
1119
1120    for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) {
1121      const MDString *S = nullptr;
1122      SmallVector<Metadata *, 4> Args;
1123
1124      // The expected hint is either a MDString or a MDNode with the first
1125      // operand a MDString.
1126      if (const MDNode *MD = dyn_cast<MDNode>(LoopID->getOperand(i))) {
1127        if (!MD || MD->getNumOperands() == 0)
1128          continue;
1129        S = dyn_cast<MDString>(MD->getOperand(0));
1130        for (unsigned i = 1, ie = MD->getNumOperands(); i < ie; ++i)
1131          Args.push_back(MD->getOperand(i));
1132      } else {
1133        S = dyn_cast<MDString>(LoopID->getOperand(i));
1134        assert(Args.size() == 0 && "too many arguments for MDString");
1135      }
1136
1137      if (!S)
1138        continue;
1139
1140      // Check if the hint starts with the loop metadata prefix.
1141      StringRef Name = S->getString();
1142      if (Args.size() == 1)
1143        setHint(Name, Args[0]);
1144    }
1145  }
1146
1147  /// Checks string hint with one operand and set value if valid.
1148  void setHint(StringRef Name, Metadata *Arg) {
1149    if (!Name.startswith(Prefix()))
1150      return;
1151    Name = Name.substr(Prefix().size(), StringRef::npos);
1152
1153    const ConstantInt *C = mdconst::dyn_extract<ConstantInt>(Arg);
1154    if (!C) return;
1155    unsigned Val = C->getZExtValue();
1156
1157    Hint *Hints[] = {&Width, &Interleave, &Force};
1158    for (auto H : Hints) {
1159      if (Name == H->Name) {
1160        if (H->validate(Val))
1161          H->Value = Val;
1162        else
1163          DEBUG(dbgs() << "LV: ignoring invalid hint '" << Name << "'\n");
1164        break;
1165      }
1166    }
1167  }
1168
1169  /// Create a new hint from name / value pair.
1170  MDNode *createHintMetadata(StringRef Name, unsigned V) const {
1171    LLVMContext &Context = TheLoop->getHeader()->getContext();
1172    Metadata *MDs[] = {MDString::get(Context, Name),
1173                       ConstantAsMetadata::get(
1174                           ConstantInt::get(Type::getInt32Ty(Context), V))};
1175    return MDNode::get(Context, MDs);
1176  }
1177
1178  /// Matches metadata with hint name.
1179  bool matchesHintMetadataName(MDNode *Node, ArrayRef<Hint> HintTypes) {
1180    MDString* Name = dyn_cast<MDString>(Node->getOperand(0));
1181    if (!Name)
1182      return false;
1183
1184    for (auto H : HintTypes)
1185      if (Name->getString().endswith(H.Name))
1186        return true;
1187    return false;
1188  }
1189
1190  /// Sets current hints into loop metadata, keeping other values intact.
1191  void writeHintsToMetadata(ArrayRef<Hint> HintTypes) {
1192    if (HintTypes.size() == 0)
1193      return;
1194
1195    // Reserve the first element to LoopID (see below).
1196    SmallVector<Metadata *, 4> MDs(1);
1197    // If the loop already has metadata, then ignore the existing operands.
1198    MDNode *LoopID = TheLoop->getLoopID();
1199    if (LoopID) {
1200      for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) {
1201        MDNode *Node = cast<MDNode>(LoopID->getOperand(i));
1202        // If node in update list, ignore old value.
1203        if (!matchesHintMetadataName(Node, HintTypes))
1204          MDs.push_back(Node);
1205      }
1206    }
1207
1208    // Now, add the missing hints.
1209    for (auto H : HintTypes)
1210      MDs.push_back(createHintMetadata(Twine(Prefix(), H.Name).str(), H.Value));
1211
1212    // Replace current metadata node with new one.
1213    LLVMContext &Context = TheLoop->getHeader()->getContext();
1214    MDNode *NewLoopID = MDNode::get(Context, MDs);
1215    // Set operand 0 to refer to the loop id itself.
1216    NewLoopID->replaceOperandWith(0, NewLoopID);
1217
1218    TheLoop->setLoopID(NewLoopID);
1219  }
1220
1221  /// The loop these hints belong to.
1222  const Loop *TheLoop;
1223};
1224
1225static void emitMissedWarning(Function *F, Loop *L,
1226                              const LoopVectorizeHints &LH) {
1227  emitOptimizationRemarkMissed(F->getContext(), DEBUG_TYPE, *F,
1228                               L->getStartLoc(), LH.emitRemark());
1229
1230  if (LH.getForce() == LoopVectorizeHints::FK_Enabled) {
1231    if (LH.getWidth() != 1)
1232      emitLoopVectorizeWarning(
1233          F->getContext(), *F, L->getStartLoc(),
1234          "failed explicitly specified loop vectorization");
1235    else if (LH.getInterleave() != 1)
1236      emitLoopInterleaveWarning(
1237          F->getContext(), *F, L->getStartLoc(),
1238          "failed explicitly specified loop interleaving");
1239  }
1240}
1241
1242static void addInnerLoop(Loop &L, SmallVectorImpl<Loop *> &V) {
1243  if (L.empty())
1244    return V.push_back(&L);
1245
1246  for (Loop *InnerL : L)
1247    addInnerLoop(*InnerL, V);
1248}
1249
1250/// The LoopVectorize Pass.
1251struct LoopVectorize : public FunctionPass {
1252  /// Pass identification, replacement for typeid
1253  static char ID;
1254
1255  explicit LoopVectorize(bool NoUnrolling = false, bool AlwaysVectorize = true)
1256    : FunctionPass(ID),
1257      DisableUnrolling(NoUnrolling),
1258      AlwaysVectorize(AlwaysVectorize) {
1259    initializeLoopVectorizePass(*PassRegistry::getPassRegistry());
1260  }
1261
1262  ScalarEvolution *SE;
1263  LoopInfo *LI;
1264  TargetTransformInfo *TTI;
1265  DominatorTree *DT;
1266  BlockFrequencyInfo *BFI;
1267  TargetLibraryInfo *TLI;
1268  AliasAnalysis *AA;
1269  AssumptionCache *AC;
1270  LoopAccessAnalysis *LAA;
1271  bool DisableUnrolling;
1272  bool AlwaysVectorize;
1273
1274  BlockFrequency ColdEntryFreq;
1275
1276  bool runOnFunction(Function &F) override {
1277    SE = &getAnalysis<ScalarEvolution>();
1278    LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
1279    TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F);
1280    DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree();
1281    BFI = &getAnalysis<BlockFrequencyInfo>();
1282    auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>();
1283    TLI = TLIP ? &TLIP->getTLI() : nullptr;
1284    AA = &getAnalysis<AliasAnalysis>();
1285    AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F);
1286    LAA = &getAnalysis<LoopAccessAnalysis>();
1287
1288    // Compute some weights outside of the loop over the loops. Compute this
1289    // using a BranchProbability to re-use its scaling math.
1290    const BranchProbability ColdProb(1, 5); // 20%
1291    ColdEntryFreq = BlockFrequency(BFI->getEntryFreq()) * ColdProb;
1292
1293    // If the target claims to have no vector registers don't attempt
1294    // vectorization.
1295    if (!TTI->getNumberOfRegisters(true))
1296      return false;
1297
1298    // Build up a worklist of inner-loops to vectorize. This is necessary as
1299    // the act of vectorizing or partially unrolling a loop creates new loops
1300    // and can invalidate iterators across the loops.
1301    SmallVector<Loop *, 8> Worklist;
1302
1303    for (Loop *L : *LI)
1304      addInnerLoop(*L, Worklist);
1305
1306    LoopsAnalyzed += Worklist.size();
1307
1308    // Now walk the identified inner loops.
1309    bool Changed = false;
1310    while (!Worklist.empty())
1311      Changed |= processLoop(Worklist.pop_back_val());
1312
1313    // Process each loop nest in the function.
1314    return Changed;
1315  }
1316
1317  static void AddRuntimeUnrollDisableMetaData(Loop *L) {
1318    SmallVector<Metadata *, 4> MDs;
1319    // Reserve first location for self reference to the LoopID metadata node.
1320    MDs.push_back(nullptr);
1321    bool IsUnrollMetadata = false;
1322    MDNode *LoopID = L->getLoopID();
1323    if (LoopID) {
1324      // First find existing loop unrolling disable metadata.
1325      for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) {
1326        MDNode *MD = dyn_cast<MDNode>(LoopID->getOperand(i));
1327        if (MD) {
1328          const MDString *S = dyn_cast<MDString>(MD->getOperand(0));
1329          IsUnrollMetadata =
1330              S && S->getString().startswith("llvm.loop.unroll.disable");
1331        }
1332        MDs.push_back(LoopID->getOperand(i));
1333      }
1334    }
1335
1336    if (!IsUnrollMetadata) {
1337      // Add runtime unroll disable metadata.
1338      LLVMContext &Context = L->getHeader()->getContext();
1339      SmallVector<Metadata *, 1> DisableOperands;
1340      DisableOperands.push_back(
1341          MDString::get(Context, "llvm.loop.unroll.runtime.disable"));
1342      MDNode *DisableNode = MDNode::get(Context, DisableOperands);
1343      MDs.push_back(DisableNode);
1344      MDNode *NewLoopID = MDNode::get(Context, MDs);
1345      // Set operand 0 to refer to the loop id itself.
1346      NewLoopID->replaceOperandWith(0, NewLoopID);
1347      L->setLoopID(NewLoopID);
1348    }
1349  }
1350
1351  bool processLoop(Loop *L) {
1352    assert(L->empty() && "Only process inner loops.");
1353
1354#ifndef NDEBUG
1355    const std::string DebugLocStr = getDebugLocString(L);
1356#endif /* NDEBUG */
1357
1358    DEBUG(dbgs() << "\nLV: Checking a loop in \""
1359                 << L->getHeader()->getParent()->getName() << "\" from "
1360                 << DebugLocStr << "\n");
1361
1362    LoopVectorizeHints Hints(L, DisableUnrolling);
1363
1364    DEBUG(dbgs() << "LV: Loop hints:"
1365                 << " force="
1366                 << (Hints.getForce() == LoopVectorizeHints::FK_Disabled
1367                         ? "disabled"
1368                         : (Hints.getForce() == LoopVectorizeHints::FK_Enabled
1369                                ? "enabled"
1370                                : "?")) << " width=" << Hints.getWidth()
1371                 << " unroll=" << Hints.getInterleave() << "\n");
1372
1373    // Function containing loop
1374    Function *F = L->getHeader()->getParent();
1375
1376    // Looking at the diagnostic output is the only way to determine if a loop
1377    // was vectorized (other than looking at the IR or machine code), so it
1378    // is important to generate an optimization remark for each loop. Most of
1379    // these messages are generated by emitOptimizationRemarkAnalysis. Remarks
1380    // generated by emitOptimizationRemark and emitOptimizationRemarkMissed are
1381    // less verbose reporting vectorized loops and unvectorized loops that may
1382    // benefit from vectorization, respectively.
1383
1384    if (Hints.getForce() == LoopVectorizeHints::FK_Disabled) {
1385      DEBUG(dbgs() << "LV: Not vectorizing: #pragma vectorize disable.\n");
1386      emitOptimizationRemarkAnalysis(F->getContext(), DEBUG_TYPE, *F,
1387                                     L->getStartLoc(), Hints.emitRemark());
1388      return false;
1389    }
1390
1391    if (!AlwaysVectorize && Hints.getForce() != LoopVectorizeHints::FK_Enabled) {
1392      DEBUG(dbgs() << "LV: Not vectorizing: No #pragma vectorize enable.\n");
1393      emitOptimizationRemarkAnalysis(F->getContext(), DEBUG_TYPE, *F,
1394                                     L->getStartLoc(), Hints.emitRemark());
1395      return false;
1396    }
1397
1398    if (Hints.getWidth() == 1 && Hints.getInterleave() == 1) {
1399      DEBUG(dbgs() << "LV: Not vectorizing: Disabled/already vectorized.\n");
1400      emitOptimizationRemarkAnalysis(
1401          F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(),
1402          "loop not vectorized: vector width and interleave count are "
1403          "explicitly set to 1");
1404      return false;
1405    }
1406
1407    // Check the loop for a trip count threshold:
1408    // do not vectorize loops with a tiny trip count.
1409    const unsigned TC = SE->getSmallConstantTripCount(L);
1410    if (TC > 0u && TC < TinyTripCountVectorThreshold) {
1411      DEBUG(dbgs() << "LV: Found a loop with a very small trip count. "
1412                   << "This loop is not worth vectorizing.");
1413      if (Hints.getForce() == LoopVectorizeHints::FK_Enabled)
1414        DEBUG(dbgs() << " But vectorizing was explicitly forced.\n");
1415      else {
1416        DEBUG(dbgs() << "\n");
1417        emitOptimizationRemarkAnalysis(
1418            F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(),
1419            "vectorization is not beneficial and is not explicitly forced");
1420        return false;
1421      }
1422    }
1423
1424    // Check if it is legal to vectorize the loop.
1425    LoopVectorizationLegality LVL(L, SE, DT, TLI, AA, F, TTI, LAA);
1426    if (!LVL.canVectorize()) {
1427      DEBUG(dbgs() << "LV: Not vectorizing: Cannot prove legality.\n");
1428      emitMissedWarning(F, L, Hints);
1429      return false;
1430    }
1431
1432    // Use the cost model.
1433    LoopVectorizationCostModel CM(L, SE, LI, &LVL, *TTI, TLI, AC, F, &Hints);
1434
1435    // Check the function attributes to find out if this function should be
1436    // optimized for size.
1437    bool OptForSize = Hints.getForce() != LoopVectorizeHints::FK_Enabled &&
1438                      F->hasFnAttribute(Attribute::OptimizeForSize);
1439
1440    // Compute the weighted frequency of this loop being executed and see if it
1441    // is less than 20% of the function entry baseline frequency. Note that we
1442    // always have a canonical loop here because we think we *can* vectoriez.
1443    // FIXME: This is hidden behind a flag due to pervasive problems with
1444    // exactly what block frequency models.
1445    if (LoopVectorizeWithBlockFrequency) {
1446      BlockFrequency LoopEntryFreq = BFI->getBlockFreq(L->getLoopPreheader());
1447      if (Hints.getForce() != LoopVectorizeHints::FK_Enabled &&
1448          LoopEntryFreq < ColdEntryFreq)
1449        OptForSize = true;
1450    }
1451
1452    // Check the function attributes to see if implicit floats are allowed.a
1453    // FIXME: This check doesn't seem possibly correct -- what if the loop is
1454    // an integer loop and the vector instructions selected are purely integer
1455    // vector instructions?
1456    if (F->hasFnAttribute(Attribute::NoImplicitFloat)) {
1457      DEBUG(dbgs() << "LV: Can't vectorize when the NoImplicitFloat"
1458            "attribute is used.\n");
1459      emitOptimizationRemarkAnalysis(
1460          F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(),
1461          "loop not vectorized due to NoImplicitFloat attribute");
1462      emitMissedWarning(F, L, Hints);
1463      return false;
1464    }
1465
1466    // Select the optimal vectorization factor.
1467    const LoopVectorizationCostModel::VectorizationFactor VF =
1468        CM.selectVectorizationFactor(OptForSize);
1469
1470    // Select the unroll factor.
1471    const unsigned UF =
1472        CM.selectUnrollFactor(OptForSize, VF.Width, VF.Cost);
1473
1474    DEBUG(dbgs() << "LV: Found a vectorizable loop (" << VF.Width << ") in "
1475                 << DebugLocStr << '\n');
1476    DEBUG(dbgs() << "LV: Unroll Factor is " << UF << '\n');
1477
1478    if (VF.Width == 1) {
1479      DEBUG(dbgs() << "LV: Vectorization is possible but not beneficial\n");
1480
1481      if (UF == 1) {
1482        emitOptimizationRemarkAnalysis(
1483            F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(),
1484            "not beneficial to vectorize and user disabled interleaving");
1485        return false;
1486      }
1487      DEBUG(dbgs() << "LV: Trying to at least unroll the loops.\n");
1488
1489      // Report the unrolling decision.
1490      emitOptimizationRemark(F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(),
1491                             Twine("unrolled with interleaving factor " +
1492                                   Twine(UF) +
1493                                   " (vectorization not beneficial)"));
1494
1495      // We decided not to vectorize, but we may want to unroll.
1496
1497      InnerLoopUnroller Unroller(L, SE, LI, DT, TLI, TTI, UF);
1498      Unroller.vectorize(&LVL);
1499    } else {
1500      // If we decided that it is *legal* to vectorize the loop then do it.
1501      InnerLoopVectorizer LB(L, SE, LI, DT, TLI, TTI, VF.Width, UF);
1502      LB.vectorize(&LVL);
1503      ++LoopsVectorized;
1504
1505      // Add metadata to disable runtime unrolling scalar loop when there's no
1506      // runtime check about strides and memory. Because at this situation,
1507      // scalar loop is rarely used not worthy to be unrolled.
1508      if (!LB.IsSafetyChecksAdded())
1509        AddRuntimeUnrollDisableMetaData(L);
1510
1511      // Report the vectorization decision.
1512      emitOptimizationRemark(
1513          F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(),
1514          Twine("vectorized loop (vectorization factor: ") + Twine(VF.Width) +
1515              ", unrolling interleave factor: " + Twine(UF) + ")");
1516    }
1517
1518    // Mark the loop as already vectorized to avoid vectorizing again.
1519    Hints.setAlreadyVectorized();
1520
1521    DEBUG(verifyFunction(*L->getHeader()->getParent()));
1522    return true;
1523  }
1524
1525  void getAnalysisUsage(AnalysisUsage &AU) const override {
1526    AU.addRequired<AssumptionCacheTracker>();
1527    AU.addRequiredID(LoopSimplifyID);
1528    AU.addRequiredID(LCSSAID);
1529    AU.addRequired<BlockFrequencyInfo>();
1530    AU.addRequired<DominatorTreeWrapperPass>();
1531    AU.addRequired<LoopInfoWrapperPass>();
1532    AU.addRequired<ScalarEvolution>();
1533    AU.addRequired<TargetTransformInfoWrapperPass>();
1534    AU.addRequired<AliasAnalysis>();
1535    AU.addRequired<LoopAccessAnalysis>();
1536    AU.addPreserved<LoopInfoWrapperPass>();
1537    AU.addPreserved<DominatorTreeWrapperPass>();
1538    AU.addPreserved<AliasAnalysis>();
1539  }
1540
1541};
1542
1543} // end anonymous namespace
1544
1545//===----------------------------------------------------------------------===//
1546// Implementation of LoopVectorizationLegality, InnerLoopVectorizer and
1547// LoopVectorizationCostModel.
1548//===----------------------------------------------------------------------===//
1549
1550Value *InnerLoopVectorizer::getBroadcastInstrs(Value *V) {
1551  // We need to place the broadcast of invariant variables outside the loop.
1552  Instruction *Instr = dyn_cast<Instruction>(V);
1553  bool NewInstr =
1554      (Instr && std::find(LoopVectorBody.begin(), LoopVectorBody.end(),
1555                          Instr->getParent()) != LoopVectorBody.end());
1556  bool Invariant = OrigLoop->isLoopInvariant(V) && !NewInstr;
1557
1558  // Place the code for broadcasting invariant variables in the new preheader.
1559  IRBuilder<>::InsertPointGuard Guard(Builder);
1560  if (Invariant)
1561    Builder.SetInsertPoint(LoopVectorPreHeader->getTerminator());
1562
1563  // Broadcast the scalar into all locations in the vector.
1564  Value *Shuf = Builder.CreateVectorSplat(VF, V, "broadcast");
1565
1566  return Shuf;
1567}
1568
1569Value *InnerLoopVectorizer::getStepVector(Value *Val, int StartIdx,
1570                                          Value *Step) {
1571  assert(Val->getType()->isVectorTy() && "Must be a vector");
1572  assert(Val->getType()->getScalarType()->isIntegerTy() &&
1573         "Elem must be an integer");
1574  assert(Step->getType() == Val->getType()->getScalarType() &&
1575         "Step has wrong type");
1576  // Create the types.
1577  Type *ITy = Val->getType()->getScalarType();
1578  VectorType *Ty = cast<VectorType>(Val->getType());
1579  int VLen = Ty->getNumElements();
1580  SmallVector<Constant*, 8> Indices;
1581
1582  // Create a vector of consecutive numbers from zero to VF.
1583  for (int i = 0; i < VLen; ++i)
1584    Indices.push_back(ConstantInt::get(ITy, StartIdx + i));
1585
1586  // Add the consecutive indices to the vector value.
1587  Constant *Cv = ConstantVector::get(Indices);
1588  assert(Cv->getType() == Val->getType() && "Invalid consecutive vec");
1589  Step = Builder.CreateVectorSplat(VLen, Step);
1590  assert(Step->getType() == Val->getType() && "Invalid step vec");
1591  // FIXME: The newly created binary instructions should contain nsw/nuw flags,
1592  // which can be found from the original scalar operations.
1593  Step = Builder.CreateMul(Cv, Step);
1594  return Builder.CreateAdd(Val, Step, "induction");
1595}
1596
1597/// \brief Find the operand of the GEP that should be checked for consecutive
1598/// stores. This ignores trailing indices that have no effect on the final
1599/// pointer.
1600static unsigned getGEPInductionOperand(const GetElementPtrInst *Gep) {
1601  const DataLayout &DL = Gep->getModule()->getDataLayout();
1602  unsigned LastOperand = Gep->getNumOperands() - 1;
1603  unsigned GEPAllocSize = DL.getTypeAllocSize(
1604      cast<PointerType>(Gep->getType()->getScalarType())->getElementType());
1605
1606  // Walk backwards and try to peel off zeros.
1607  while (LastOperand > 1 && match(Gep->getOperand(LastOperand), m_Zero())) {
1608    // Find the type we're currently indexing into.
1609    gep_type_iterator GEPTI = gep_type_begin(Gep);
1610    std::advance(GEPTI, LastOperand - 1);
1611
1612    // If it's a type with the same allocation size as the result of the GEP we
1613    // can peel off the zero index.
1614    if (DL.getTypeAllocSize(*GEPTI) != GEPAllocSize)
1615      break;
1616    --LastOperand;
1617  }
1618
1619  return LastOperand;
1620}
1621
1622int LoopVectorizationLegality::isConsecutivePtr(Value *Ptr) {
1623  assert(Ptr->getType()->isPointerTy() && "Unexpected non-ptr");
1624  // Make sure that the pointer does not point to structs.
1625  if (Ptr->getType()->getPointerElementType()->isAggregateType())
1626    return 0;
1627
1628  // If this value is a pointer induction variable we know it is consecutive.
1629  PHINode *Phi = dyn_cast_or_null<PHINode>(Ptr);
1630  if (Phi && Inductions.count(Phi)) {
1631    InductionInfo II = Inductions[Phi];
1632    return II.getConsecutiveDirection();
1633  }
1634
1635  GetElementPtrInst *Gep = dyn_cast_or_null<GetElementPtrInst>(Ptr);
1636  if (!Gep)
1637    return 0;
1638
1639  unsigned NumOperands = Gep->getNumOperands();
1640  Value *GpPtr = Gep->getPointerOperand();
1641  // If this GEP value is a consecutive pointer induction variable and all of
1642  // the indices are constant then we know it is consecutive. We can
1643  Phi = dyn_cast<PHINode>(GpPtr);
1644  if (Phi && Inductions.count(Phi)) {
1645
1646    // Make sure that the pointer does not point to structs.
1647    PointerType *GepPtrType = cast<PointerType>(GpPtr->getType());
1648    if (GepPtrType->getElementType()->isAggregateType())
1649      return 0;
1650
1651    // Make sure that all of the index operands are loop invariant.
1652    for (unsigned i = 1; i < NumOperands; ++i)
1653      if (!SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop))
1654        return 0;
1655
1656    InductionInfo II = Inductions[Phi];
1657    return II.getConsecutiveDirection();
1658  }
1659
1660  unsigned InductionOperand = getGEPInductionOperand(Gep);
1661
1662  // Check that all of the gep indices are uniform except for our induction
1663  // operand.
1664  for (unsigned i = 0; i != NumOperands; ++i)
1665    if (i != InductionOperand &&
1666        !SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop))
1667      return 0;
1668
1669  // We can emit wide load/stores only if the last non-zero index is the
1670  // induction variable.
1671  const SCEV *Last = nullptr;
1672  if (!Strides.count(Gep))
1673    Last = SE->getSCEV(Gep->getOperand(InductionOperand));
1674  else {
1675    // Because of the multiplication by a stride we can have a s/zext cast.
1676    // We are going to replace this stride by 1 so the cast is safe to ignore.
1677    //
1678    //  %indvars.iv = phi i64 [ 0, %entry ], [ %indvars.iv.next, %for.body ]
1679    //  %0 = trunc i64 %indvars.iv to i32
1680    //  %mul = mul i32 %0, %Stride1
1681    //  %idxprom = zext i32 %mul to i64  << Safe cast.
1682    //  %arrayidx = getelementptr inbounds i32* %B, i64 %idxprom
1683    //
1684    Last = replaceSymbolicStrideSCEV(SE, Strides,
1685                                     Gep->getOperand(InductionOperand), Gep);
1686    if (const SCEVCastExpr *C = dyn_cast<SCEVCastExpr>(Last))
1687      Last =
1688          (C->getSCEVType() == scSignExtend || C->getSCEVType() == scZeroExtend)
1689              ? C->getOperand()
1690              : Last;
1691  }
1692  if (const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Last)) {
1693    const SCEV *Step = AR->getStepRecurrence(*SE);
1694
1695    // The memory is consecutive because the last index is consecutive
1696    // and all other indices are loop invariant.
1697    if (Step->isOne())
1698      return 1;
1699    if (Step->isAllOnesValue())
1700      return -1;
1701  }
1702
1703  return 0;
1704}
1705
1706bool LoopVectorizationLegality::isUniform(Value *V) {
1707  return LAI->isUniform(V);
1708}
1709
1710InnerLoopVectorizer::VectorParts&
1711InnerLoopVectorizer::getVectorValue(Value *V) {
1712  assert(V != Induction && "The new induction variable should not be used.");
1713  assert(!V->getType()->isVectorTy() && "Can't widen a vector");
1714
1715  // If we have a stride that is replaced by one, do it here.
1716  if (Legal->hasStride(V))
1717    V = ConstantInt::get(V->getType(), 1);
1718
1719  // If we have this scalar in the map, return it.
1720  if (WidenMap.has(V))
1721    return WidenMap.get(V);
1722
1723  // If this scalar is unknown, assume that it is a constant or that it is
1724  // loop invariant. Broadcast V and save the value for future uses.
1725  Value *B = getBroadcastInstrs(V);
1726  return WidenMap.splat(V, B);
1727}
1728
1729Value *InnerLoopVectorizer::reverseVector(Value *Vec) {
1730  assert(Vec->getType()->isVectorTy() && "Invalid type");
1731  SmallVector<Constant*, 8> ShuffleMask;
1732  for (unsigned i = 0; i < VF; ++i)
1733    ShuffleMask.push_back(Builder.getInt32(VF - i - 1));
1734
1735  return Builder.CreateShuffleVector(Vec, UndefValue::get(Vec->getType()),
1736                                     ConstantVector::get(ShuffleMask),
1737                                     "reverse");
1738}
1739
1740void InnerLoopVectorizer::vectorizeMemoryInstruction(Instruction *Instr) {
1741  // Attempt to issue a wide load.
1742  LoadInst *LI = dyn_cast<LoadInst>(Instr);
1743  StoreInst *SI = dyn_cast<StoreInst>(Instr);
1744
1745  assert((LI || SI) && "Invalid Load/Store instruction");
1746
1747  Type *ScalarDataTy = LI ? LI->getType() : SI->getValueOperand()->getType();
1748  Type *DataTy = VectorType::get(ScalarDataTy, VF);
1749  Value *Ptr = LI ? LI->getPointerOperand() : SI->getPointerOperand();
1750  unsigned Alignment = LI ? LI->getAlignment() : SI->getAlignment();
1751  // An alignment of 0 means target abi alignment. We need to use the scalar's
1752  // target abi alignment in such a case.
1753  const DataLayout &DL = Instr->getModule()->getDataLayout();
1754  if (!Alignment)
1755    Alignment = DL.getABITypeAlignment(ScalarDataTy);
1756  unsigned AddressSpace = Ptr->getType()->getPointerAddressSpace();
1757  unsigned ScalarAllocatedSize = DL.getTypeAllocSize(ScalarDataTy);
1758  unsigned VectorElementSize = DL.getTypeStoreSize(DataTy) / VF;
1759
1760  if (SI && Legal->blockNeedsPredication(SI->getParent()) &&
1761      !Legal->isMaskRequired(SI))
1762    return scalarizeInstruction(Instr, true);
1763
1764  if (ScalarAllocatedSize != VectorElementSize)
1765    return scalarizeInstruction(Instr);
1766
1767  // If the pointer is loop invariant or if it is non-consecutive,
1768  // scalarize the load.
1769  int ConsecutiveStride = Legal->isConsecutivePtr(Ptr);
1770  bool Reverse = ConsecutiveStride < 0;
1771  bool UniformLoad = LI && Legal->isUniform(Ptr);
1772  if (!ConsecutiveStride || UniformLoad)
1773    return scalarizeInstruction(Instr);
1774
1775  Constant *Zero = Builder.getInt32(0);
1776  VectorParts &Entry = WidenMap.get(Instr);
1777
1778  // Handle consecutive loads/stores.
1779  GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr);
1780  if (Gep && Legal->isInductionVariable(Gep->getPointerOperand())) {
1781    setDebugLocFromInst(Builder, Gep);
1782    Value *PtrOperand = Gep->getPointerOperand();
1783    Value *FirstBasePtr = getVectorValue(PtrOperand)[0];
1784    FirstBasePtr = Builder.CreateExtractElement(FirstBasePtr, Zero);
1785
1786    // Create the new GEP with the new induction variable.
1787    GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone());
1788    Gep2->setOperand(0, FirstBasePtr);
1789    Gep2->setName("gep.indvar.base");
1790    Ptr = Builder.Insert(Gep2);
1791  } else if (Gep) {
1792    setDebugLocFromInst(Builder, Gep);
1793    assert(SE->isLoopInvariant(SE->getSCEV(Gep->getPointerOperand()),
1794                               OrigLoop) && "Base ptr must be invariant");
1795
1796    // The last index does not have to be the induction. It can be
1797    // consecutive and be a function of the index. For example A[I+1];
1798    unsigned NumOperands = Gep->getNumOperands();
1799    unsigned InductionOperand = getGEPInductionOperand(Gep);
1800    // Create the new GEP with the new induction variable.
1801    GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone());
1802
1803    for (unsigned i = 0; i < NumOperands; ++i) {
1804      Value *GepOperand = Gep->getOperand(i);
1805      Instruction *GepOperandInst = dyn_cast<Instruction>(GepOperand);
1806
1807      // Update last index or loop invariant instruction anchored in loop.
1808      if (i == InductionOperand ||
1809          (GepOperandInst && OrigLoop->contains(GepOperandInst))) {
1810        assert((i == InductionOperand ||
1811               SE->isLoopInvariant(SE->getSCEV(GepOperandInst), OrigLoop)) &&
1812               "Must be last index or loop invariant");
1813
1814        VectorParts &GEPParts = getVectorValue(GepOperand);
1815        Value *Index = GEPParts[0];
1816        Index = Builder.CreateExtractElement(Index, Zero);
1817        Gep2->setOperand(i, Index);
1818        Gep2->setName("gep.indvar.idx");
1819      }
1820    }
1821    Ptr = Builder.Insert(Gep2);
1822  } else {
1823    // Use the induction element ptr.
1824    assert(isa<PHINode>(Ptr) && "Invalid induction ptr");
1825    setDebugLocFromInst(Builder, Ptr);
1826    VectorParts &PtrVal = getVectorValue(Ptr);
1827    Ptr = Builder.CreateExtractElement(PtrVal[0], Zero);
1828  }
1829
1830  VectorParts Mask = createBlockInMask(Instr->getParent());
1831  // Handle Stores:
1832  if (SI) {
1833    assert(!Legal->isUniform(SI->getPointerOperand()) &&
1834           "We do not allow storing to uniform addresses");
1835    setDebugLocFromInst(Builder, SI);
1836    // We don't want to update the value in the map as it might be used in
1837    // another expression. So don't use a reference type for "StoredVal".
1838    VectorParts StoredVal = getVectorValue(SI->getValueOperand());
1839
1840    for (unsigned Part = 0; Part < UF; ++Part) {
1841      // Calculate the pointer for the specific unroll-part.
1842      Value *PartPtr =
1843          Builder.CreateGEP(nullptr, Ptr, Builder.getInt32(Part * VF));
1844
1845      if (Reverse) {
1846        // If we store to reverse consecutive memory locations then we need
1847        // to reverse the order of elements in the stored value.
1848        StoredVal[Part] = reverseVector(StoredVal[Part]);
1849        // If the address is consecutive but reversed, then the
1850        // wide store needs to start at the last vector element.
1851        PartPtr = Builder.CreateGEP(nullptr, Ptr, Builder.getInt32(-Part * VF));
1852        PartPtr = Builder.CreateGEP(nullptr, PartPtr, Builder.getInt32(1 - VF));
1853        Mask[Part] = reverseVector(Mask[Part]);
1854      }
1855
1856      Value *VecPtr = Builder.CreateBitCast(PartPtr,
1857                                            DataTy->getPointerTo(AddressSpace));
1858
1859      Instruction *NewSI;
1860      if (Legal->isMaskRequired(SI))
1861        NewSI = Builder.CreateMaskedStore(StoredVal[Part], VecPtr, Alignment,
1862                                          Mask[Part]);
1863      else
1864        NewSI = Builder.CreateAlignedStore(StoredVal[Part], VecPtr, Alignment);
1865      propagateMetadata(NewSI, SI);
1866    }
1867    return;
1868  }
1869
1870  // Handle loads.
1871  assert(LI && "Must have a load instruction");
1872  setDebugLocFromInst(Builder, LI);
1873  for (unsigned Part = 0; Part < UF; ++Part) {
1874    // Calculate the pointer for the specific unroll-part.
1875    Value *PartPtr =
1876        Builder.CreateGEP(nullptr, Ptr, Builder.getInt32(Part * VF));
1877
1878    if (Reverse) {
1879      // If the address is consecutive but reversed, then the
1880      // wide load needs to start at the last vector element.
1881      PartPtr = Builder.CreateGEP(nullptr, Ptr, Builder.getInt32(-Part * VF));
1882      PartPtr = Builder.CreateGEP(nullptr, PartPtr, Builder.getInt32(1 - VF));
1883      Mask[Part] = reverseVector(Mask[Part]);
1884    }
1885
1886    Instruction* NewLI;
1887    Value *VecPtr = Builder.CreateBitCast(PartPtr,
1888                                          DataTy->getPointerTo(AddressSpace));
1889    if (Legal->isMaskRequired(LI))
1890      NewLI = Builder.CreateMaskedLoad(VecPtr, Alignment, Mask[Part],
1891                                       UndefValue::get(DataTy),
1892                                       "wide.masked.load");
1893    else
1894      NewLI = Builder.CreateAlignedLoad(VecPtr, Alignment, "wide.load");
1895    propagateMetadata(NewLI, LI);
1896    Entry[Part] = Reverse ? reverseVector(NewLI) :  NewLI;
1897  }
1898}
1899
1900void InnerLoopVectorizer::scalarizeInstruction(Instruction *Instr, bool IfPredicateStore) {
1901  assert(!Instr->getType()->isAggregateType() && "Can't handle vectors");
1902  // Holds vector parameters or scalars, in case of uniform vals.
1903  SmallVector<VectorParts, 4> Params;
1904
1905  setDebugLocFromInst(Builder, Instr);
1906
1907  // Find all of the vectorized parameters.
1908  for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
1909    Value *SrcOp = Instr->getOperand(op);
1910
1911    // If we are accessing the old induction variable, use the new one.
1912    if (SrcOp == OldInduction) {
1913      Params.push_back(getVectorValue(SrcOp));
1914      continue;
1915    }
1916
1917    // Try using previously calculated values.
1918    Instruction *SrcInst = dyn_cast<Instruction>(SrcOp);
1919
1920    // If the src is an instruction that appeared earlier in the basic block
1921    // then it should already be vectorized.
1922    if (SrcInst && OrigLoop->contains(SrcInst)) {
1923      assert(WidenMap.has(SrcInst) && "Source operand is unavailable");
1924      // The parameter is a vector value from earlier.
1925      Params.push_back(WidenMap.get(SrcInst));
1926    } else {
1927      // The parameter is a scalar from outside the loop. Maybe even a constant.
1928      VectorParts Scalars;
1929      Scalars.append(UF, SrcOp);
1930      Params.push_back(Scalars);
1931    }
1932  }
1933
1934  assert(Params.size() == Instr->getNumOperands() &&
1935         "Invalid number of operands");
1936
1937  // Does this instruction return a value ?
1938  bool IsVoidRetTy = Instr->getType()->isVoidTy();
1939
1940  Value *UndefVec = IsVoidRetTy ? nullptr :
1941    UndefValue::get(VectorType::get(Instr->getType(), VF));
1942  // Create a new entry in the WidenMap and initialize it to Undef or Null.
1943  VectorParts &VecResults = WidenMap.splat(Instr, UndefVec);
1944
1945  Instruction *InsertPt = Builder.GetInsertPoint();
1946  BasicBlock *IfBlock = Builder.GetInsertBlock();
1947  BasicBlock *CondBlock = nullptr;
1948
1949  VectorParts Cond;
1950  Loop *VectorLp = nullptr;
1951  if (IfPredicateStore) {
1952    assert(Instr->getParent()->getSinglePredecessor() &&
1953           "Only support single predecessor blocks");
1954    Cond = createEdgeMask(Instr->getParent()->getSinglePredecessor(),
1955                          Instr->getParent());
1956    VectorLp = LI->getLoopFor(IfBlock);
1957    assert(VectorLp && "Must have a loop for this block");
1958  }
1959
1960  // For each vector unroll 'part':
1961  for (unsigned Part = 0; Part < UF; ++Part) {
1962    // For each scalar that we create:
1963    for (unsigned Width = 0; Width < VF; ++Width) {
1964
1965      // Start if-block.
1966      Value *Cmp = nullptr;
1967      if (IfPredicateStore) {
1968        Cmp = Builder.CreateExtractElement(Cond[Part], Builder.getInt32(Width));
1969        Cmp = Builder.CreateICmp(ICmpInst::ICMP_EQ, Cmp, ConstantInt::get(Cmp->getType(), 1));
1970        CondBlock = IfBlock->splitBasicBlock(InsertPt, "cond.store");
1971        LoopVectorBody.push_back(CondBlock);
1972        VectorLp->addBasicBlockToLoop(CondBlock, *LI);
1973        // Update Builder with newly created basic block.
1974        Builder.SetInsertPoint(InsertPt);
1975      }
1976
1977      Instruction *Cloned = Instr->clone();
1978      if (!IsVoidRetTy)
1979        Cloned->setName(Instr->getName() + ".cloned");
1980      // Replace the operands of the cloned instructions with extracted scalars.
1981      for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
1982        Value *Op = Params[op][Part];
1983        // Param is a vector. Need to extract the right lane.
1984        if (Op->getType()->isVectorTy())
1985          Op = Builder.CreateExtractElement(Op, Builder.getInt32(Width));
1986        Cloned->setOperand(op, Op);
1987      }
1988
1989      // Place the cloned scalar in the new loop.
1990      Builder.Insert(Cloned);
1991
1992      // If the original scalar returns a value we need to place it in a vector
1993      // so that future users will be able to use it.
1994      if (!IsVoidRetTy)
1995        VecResults[Part] = Builder.CreateInsertElement(VecResults[Part], Cloned,
1996                                                       Builder.getInt32(Width));
1997      // End if-block.
1998      if (IfPredicateStore) {
1999         BasicBlock *NewIfBlock = CondBlock->splitBasicBlock(InsertPt, "else");
2000         LoopVectorBody.push_back(NewIfBlock);
2001         VectorLp->addBasicBlockToLoop(NewIfBlock, *LI);
2002         Builder.SetInsertPoint(InsertPt);
2003         Instruction *OldBr = IfBlock->getTerminator();
2004         BranchInst::Create(CondBlock, NewIfBlock, Cmp, OldBr);
2005         OldBr->eraseFromParent();
2006         IfBlock = NewIfBlock;
2007      }
2008    }
2009  }
2010}
2011
2012static Instruction *getFirstInst(Instruction *FirstInst, Value *V,
2013                                 Instruction *Loc) {
2014  if (FirstInst)
2015    return FirstInst;
2016  if (Instruction *I = dyn_cast<Instruction>(V))
2017    return I->getParent() == Loc->getParent() ? I : nullptr;
2018  return nullptr;
2019}
2020
2021std::pair<Instruction *, Instruction *>
2022InnerLoopVectorizer::addStrideCheck(Instruction *Loc) {
2023  Instruction *tnullptr = nullptr;
2024  if (!Legal->mustCheckStrides())
2025    return std::pair<Instruction *, Instruction *>(tnullptr, tnullptr);
2026
2027  IRBuilder<> ChkBuilder(Loc);
2028
2029  // Emit checks.
2030  Value *Check = nullptr;
2031  Instruction *FirstInst = nullptr;
2032  for (SmallPtrSet<Value *, 8>::iterator SI = Legal->strides_begin(),
2033                                         SE = Legal->strides_end();
2034       SI != SE; ++SI) {
2035    Value *Ptr = stripIntegerCast(*SI);
2036    Value *C = ChkBuilder.CreateICmpNE(Ptr, ConstantInt::get(Ptr->getType(), 1),
2037                                       "stride.chk");
2038    // Store the first instruction we create.
2039    FirstInst = getFirstInst(FirstInst, C, Loc);
2040    if (Check)
2041      Check = ChkBuilder.CreateOr(Check, C);
2042    else
2043      Check = C;
2044  }
2045
2046  // We have to do this trickery because the IRBuilder might fold the check to a
2047  // constant expression in which case there is no Instruction anchored in a
2048  // the block.
2049  LLVMContext &Ctx = Loc->getContext();
2050  Instruction *TheCheck =
2051      BinaryOperator::CreateAnd(Check, ConstantInt::getTrue(Ctx));
2052  ChkBuilder.Insert(TheCheck, "stride.not.one");
2053  FirstInst = getFirstInst(FirstInst, TheCheck, Loc);
2054
2055  return std::make_pair(FirstInst, TheCheck);
2056}
2057
2058void InnerLoopVectorizer::createEmptyLoop() {
2059  /*
2060   In this function we generate a new loop. The new loop will contain
2061   the vectorized instructions while the old loop will continue to run the
2062   scalar remainder.
2063
2064       [ ] <-- Back-edge taken count overflow check.
2065    /   |
2066   /    v
2067  |    [ ] <-- vector loop bypass (may consist of multiple blocks).
2068  |  /  |
2069  | /   v
2070  ||   [ ]     <-- vector pre header.
2071  ||    |
2072  ||    v
2073  ||   [  ] \
2074  ||   [  ]_|   <-- vector loop.
2075  ||    |
2076  | \   v
2077  |   >[ ]   <--- middle-block.
2078  |  /  |
2079  | /   v
2080  -|- >[ ]     <--- new preheader.
2081   |    |
2082   |    v
2083   |   [ ] \
2084   |   [ ]_|   <-- old scalar loop to handle remainder.
2085    \   |
2086     \  v
2087      >[ ]     <-- exit block.
2088   ...
2089   */
2090
2091  BasicBlock *OldBasicBlock = OrigLoop->getHeader();
2092  BasicBlock *BypassBlock = OrigLoop->getLoopPreheader();
2093  BasicBlock *ExitBlock = OrigLoop->getExitBlock();
2094  assert(BypassBlock && "Invalid loop structure");
2095  assert(ExitBlock && "Must have an exit block");
2096
2097  // Some loops have a single integer induction variable, while other loops
2098  // don't. One example is c++ iterators that often have multiple pointer
2099  // induction variables. In the code below we also support a case where we
2100  // don't have a single induction variable.
2101  OldInduction = Legal->getInduction();
2102  Type *IdxTy = Legal->getWidestInductionType();
2103
2104  // Find the loop boundaries.
2105  const SCEV *ExitCount = SE->getBackedgeTakenCount(OrigLoop);
2106  assert(ExitCount != SE->getCouldNotCompute() && "Invalid loop count");
2107
2108  // The exit count might have the type of i64 while the phi is i32. This can
2109  // happen if we have an induction variable that is sign extended before the
2110  // compare. The only way that we get a backedge taken count is that the
2111  // induction variable was signed and as such will not overflow. In such a case
2112  // truncation is legal.
2113  if (ExitCount->getType()->getPrimitiveSizeInBits() >
2114      IdxTy->getPrimitiveSizeInBits())
2115    ExitCount = SE->getTruncateOrNoop(ExitCount, IdxTy);
2116
2117  const SCEV *BackedgeTakeCount = SE->getNoopOrZeroExtend(ExitCount, IdxTy);
2118  // Get the total trip count from the count by adding 1.
2119  ExitCount = SE->getAddExpr(BackedgeTakeCount,
2120                             SE->getConstant(BackedgeTakeCount->getType(), 1));
2121
2122  const DataLayout &DL = OldBasicBlock->getModule()->getDataLayout();
2123
2124  // Expand the trip count and place the new instructions in the preheader.
2125  // Notice that the pre-header does not change, only the loop body.
2126  SCEVExpander Exp(*SE, DL, "induction");
2127
2128  // We need to test whether the backedge-taken count is uint##_max. Adding one
2129  // to it will cause overflow and an incorrect loop trip count in the vector
2130  // body. In case of overflow we want to directly jump to the scalar remainder
2131  // loop.
2132  Value *BackedgeCount =
2133      Exp.expandCodeFor(BackedgeTakeCount, BackedgeTakeCount->getType(),
2134                        BypassBlock->getTerminator());
2135  if (BackedgeCount->getType()->isPointerTy())
2136    BackedgeCount = CastInst::CreatePointerCast(BackedgeCount, IdxTy,
2137                                                "backedge.ptrcnt.to.int",
2138                                                BypassBlock->getTerminator());
2139  Instruction *CheckBCOverflow =
2140      CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ, BackedgeCount,
2141                      Constant::getAllOnesValue(BackedgeCount->getType()),
2142                      "backedge.overflow", BypassBlock->getTerminator());
2143
2144  // The loop index does not have to start at Zero. Find the original start
2145  // value from the induction PHI node. If we don't have an induction variable
2146  // then we know that it starts at zero.
2147  Builder.SetInsertPoint(BypassBlock->getTerminator());
2148  Value *StartIdx = ExtendedIdx = OldInduction ?
2149    Builder.CreateZExt(OldInduction->getIncomingValueForBlock(BypassBlock),
2150                       IdxTy):
2151    ConstantInt::get(IdxTy, 0);
2152
2153  // We need an instruction to anchor the overflow check on. StartIdx needs to
2154  // be defined before the overflow check branch. Because the scalar preheader
2155  // is going to merge the start index and so the overflow branch block needs to
2156  // contain a definition of the start index.
2157  Instruction *OverflowCheckAnchor = BinaryOperator::CreateAdd(
2158      StartIdx, ConstantInt::get(IdxTy, 0), "overflow.check.anchor",
2159      BypassBlock->getTerminator());
2160
2161  // Count holds the overall loop count (N).
2162  Value *Count = Exp.expandCodeFor(ExitCount, ExitCount->getType(),
2163                                   BypassBlock->getTerminator());
2164
2165  LoopBypassBlocks.push_back(BypassBlock);
2166
2167  // Split the single block loop into the two loop structure described above.
2168  BasicBlock *VectorPH =
2169  BypassBlock->splitBasicBlock(BypassBlock->getTerminator(), "vector.ph");
2170  BasicBlock *VecBody =
2171  VectorPH->splitBasicBlock(VectorPH->getTerminator(), "vector.body");
2172  BasicBlock *MiddleBlock =
2173  VecBody->splitBasicBlock(VecBody->getTerminator(), "middle.block");
2174  BasicBlock *ScalarPH =
2175  MiddleBlock->splitBasicBlock(MiddleBlock->getTerminator(), "scalar.ph");
2176
2177  // Create and register the new vector loop.
2178  Loop* Lp = new Loop();
2179  Loop *ParentLoop = OrigLoop->getParentLoop();
2180
2181  // Insert the new loop into the loop nest and register the new basic blocks
2182  // before calling any utilities such as SCEV that require valid LoopInfo.
2183  if (ParentLoop) {
2184    ParentLoop->addChildLoop(Lp);
2185    ParentLoop->addBasicBlockToLoop(ScalarPH, *LI);
2186    ParentLoop->addBasicBlockToLoop(VectorPH, *LI);
2187    ParentLoop->addBasicBlockToLoop(MiddleBlock, *LI);
2188  } else {
2189    LI->addTopLevelLoop(Lp);
2190  }
2191  Lp->addBasicBlockToLoop(VecBody, *LI);
2192
2193  // Use this IR builder to create the loop instructions (Phi, Br, Cmp)
2194  // inside the loop.
2195  Builder.SetInsertPoint(VecBody->getFirstNonPHI());
2196
2197  // Generate the induction variable.
2198  setDebugLocFromInst(Builder, getDebugLocFromInstOrOperands(OldInduction));
2199  Induction = Builder.CreatePHI(IdxTy, 2, "index");
2200  // The loop step is equal to the vectorization factor (num of SIMD elements)
2201  // times the unroll factor (num of SIMD instructions).
2202  Constant *Step = ConstantInt::get(IdxTy, VF * UF);
2203
2204  // This is the IR builder that we use to add all of the logic for bypassing
2205  // the new vector loop.
2206  IRBuilder<> BypassBuilder(BypassBlock->getTerminator());
2207  setDebugLocFromInst(BypassBuilder,
2208                      getDebugLocFromInstOrOperands(OldInduction));
2209
2210  // We may need to extend the index in case there is a type mismatch.
2211  // We know that the count starts at zero and does not overflow.
2212  if (Count->getType() != IdxTy) {
2213    // The exit count can be of pointer type. Convert it to the correct
2214    // integer type.
2215    if (ExitCount->getType()->isPointerTy())
2216      Count = BypassBuilder.CreatePointerCast(Count, IdxTy, "ptrcnt.to.int");
2217    else
2218      Count = BypassBuilder.CreateZExtOrTrunc(Count, IdxTy, "cnt.cast");
2219  }
2220
2221  // Add the start index to the loop count to get the new end index.
2222  Value *IdxEnd = BypassBuilder.CreateAdd(Count, StartIdx, "end.idx");
2223
2224  // Now we need to generate the expression for N - (N % VF), which is
2225  // the part that the vectorized body will execute.
2226  Value *R = BypassBuilder.CreateURem(Count, Step, "n.mod.vf");
2227  Value *CountRoundDown = BypassBuilder.CreateSub(Count, R, "n.vec");
2228  Value *IdxEndRoundDown = BypassBuilder.CreateAdd(CountRoundDown, StartIdx,
2229                                                     "end.idx.rnd.down");
2230
2231  // Now, compare the new count to zero. If it is zero skip the vector loop and
2232  // jump to the scalar loop.
2233  Value *Cmp =
2234      BypassBuilder.CreateICmpEQ(IdxEndRoundDown, StartIdx, "cmp.zero");
2235
2236  BasicBlock *LastBypassBlock = BypassBlock;
2237
2238  // Generate code to check that the loops trip count that we computed by adding
2239  // one to the backedge-taken count will not overflow.
2240  {
2241    auto PastOverflowCheck =
2242        std::next(BasicBlock::iterator(OverflowCheckAnchor));
2243    BasicBlock *CheckBlock =
2244      LastBypassBlock->splitBasicBlock(PastOverflowCheck, "overflow.checked");
2245    if (ParentLoop)
2246      ParentLoop->addBasicBlockToLoop(CheckBlock, *LI);
2247    LoopBypassBlocks.push_back(CheckBlock);
2248    Instruction *OldTerm = LastBypassBlock->getTerminator();
2249    BranchInst::Create(ScalarPH, CheckBlock, CheckBCOverflow, OldTerm);
2250    OldTerm->eraseFromParent();
2251    LastBypassBlock = CheckBlock;
2252  }
2253
2254  // Generate the code to check that the strides we assumed to be one are really
2255  // one. We want the new basic block to start at the first instruction in a
2256  // sequence of instructions that form a check.
2257  Instruction *StrideCheck;
2258  Instruction *FirstCheckInst;
2259  std::tie(FirstCheckInst, StrideCheck) =
2260      addStrideCheck(LastBypassBlock->getTerminator());
2261  if (StrideCheck) {
2262    AddedSafetyChecks = true;
2263    // Create a new block containing the stride check.
2264    BasicBlock *CheckBlock =
2265        LastBypassBlock->splitBasicBlock(FirstCheckInst, "vector.stridecheck");
2266    if (ParentLoop)
2267      ParentLoop->addBasicBlockToLoop(CheckBlock, *LI);
2268    LoopBypassBlocks.push_back(CheckBlock);
2269
2270    // Replace the branch into the memory check block with a conditional branch
2271    // for the "few elements case".
2272    Instruction *OldTerm = LastBypassBlock->getTerminator();
2273    BranchInst::Create(MiddleBlock, CheckBlock, Cmp, OldTerm);
2274    OldTerm->eraseFromParent();
2275
2276    Cmp = StrideCheck;
2277    LastBypassBlock = CheckBlock;
2278  }
2279
2280  // Generate the code that checks in runtime if arrays overlap. We put the
2281  // checks into a separate block to make the more common case of few elements
2282  // faster.
2283  Instruction *MemRuntimeCheck;
2284  std::tie(FirstCheckInst, MemRuntimeCheck) =
2285    Legal->getLAI()->addRuntimeCheck(LastBypassBlock->getTerminator());
2286  if (MemRuntimeCheck) {
2287    AddedSafetyChecks = true;
2288    // Create a new block containing the memory check.
2289    BasicBlock *CheckBlock =
2290        LastBypassBlock->splitBasicBlock(FirstCheckInst, "vector.memcheck");
2291    if (ParentLoop)
2292      ParentLoop->addBasicBlockToLoop(CheckBlock, *LI);
2293    LoopBypassBlocks.push_back(CheckBlock);
2294
2295    // Replace the branch into the memory check block with a conditional branch
2296    // for the "few elements case".
2297    Instruction *OldTerm = LastBypassBlock->getTerminator();
2298    BranchInst::Create(MiddleBlock, CheckBlock, Cmp, OldTerm);
2299    OldTerm->eraseFromParent();
2300
2301    Cmp = MemRuntimeCheck;
2302    LastBypassBlock = CheckBlock;
2303  }
2304
2305  LastBypassBlock->getTerminator()->eraseFromParent();
2306  BranchInst::Create(MiddleBlock, VectorPH, Cmp,
2307                     LastBypassBlock);
2308
2309  // We are going to resume the execution of the scalar loop.
2310  // Go over all of the induction variables that we found and fix the
2311  // PHIs that are left in the scalar version of the loop.
2312  // The starting values of PHI nodes depend on the counter of the last
2313  // iteration in the vectorized loop.
2314  // If we come from a bypass edge then we need to start from the original
2315  // start value.
2316
2317  // This variable saves the new starting index for the scalar loop.
2318  PHINode *ResumeIndex = nullptr;
2319  LoopVectorizationLegality::InductionList::iterator I, E;
2320  LoopVectorizationLegality::InductionList *List = Legal->getInductionVars();
2321  // Set builder to point to last bypass block.
2322  BypassBuilder.SetInsertPoint(LoopBypassBlocks.back()->getTerminator());
2323  for (I = List->begin(), E = List->end(); I != E; ++I) {
2324    PHINode *OrigPhi = I->first;
2325    LoopVectorizationLegality::InductionInfo II = I->second;
2326
2327    Type *ResumeValTy = (OrigPhi == OldInduction) ? IdxTy : OrigPhi->getType();
2328    PHINode *ResumeVal = PHINode::Create(ResumeValTy, 2, "resume.val",
2329                                         MiddleBlock->getTerminator());
2330    // We might have extended the type of the induction variable but we need a
2331    // truncated version for the scalar loop.
2332    PHINode *TruncResumeVal = (OrigPhi == OldInduction) ?
2333      PHINode::Create(OrigPhi->getType(), 2, "trunc.resume.val",
2334                      MiddleBlock->getTerminator()) : nullptr;
2335
2336    // Create phi nodes to merge from the  backedge-taken check block.
2337    PHINode *BCResumeVal = PHINode::Create(ResumeValTy, 3, "bc.resume.val",
2338                                           ScalarPH->getTerminator());
2339    BCResumeVal->addIncoming(ResumeVal, MiddleBlock);
2340
2341    PHINode *BCTruncResumeVal = nullptr;
2342    if (OrigPhi == OldInduction) {
2343      BCTruncResumeVal =
2344          PHINode::Create(OrigPhi->getType(), 2, "bc.trunc.resume.val",
2345                          ScalarPH->getTerminator());
2346      BCTruncResumeVal->addIncoming(TruncResumeVal, MiddleBlock);
2347    }
2348
2349    Value *EndValue = nullptr;
2350    switch (II.IK) {
2351    case LoopVectorizationLegality::IK_NoInduction:
2352      llvm_unreachable("Unknown induction");
2353    case LoopVectorizationLegality::IK_IntInduction: {
2354      // Handle the integer induction counter.
2355      assert(OrigPhi->getType()->isIntegerTy() && "Invalid type");
2356
2357      // We have the canonical induction variable.
2358      if (OrigPhi == OldInduction) {
2359        // Create a truncated version of the resume value for the scalar loop,
2360        // we might have promoted the type to a larger width.
2361        EndValue =
2362          BypassBuilder.CreateTrunc(IdxEndRoundDown, OrigPhi->getType());
2363        // The new PHI merges the original incoming value, in case of a bypass,
2364        // or the value at the end of the vectorized loop.
2365        for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I)
2366          TruncResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]);
2367        TruncResumeVal->addIncoming(EndValue, VecBody);
2368
2369        BCTruncResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[0]);
2370
2371        // We know what the end value is.
2372        EndValue = IdxEndRoundDown;
2373        // We also know which PHI node holds it.
2374        ResumeIndex = ResumeVal;
2375        break;
2376      }
2377
2378      // Not the canonical induction variable - add the vector loop count to the
2379      // start value.
2380      Value *CRD = BypassBuilder.CreateSExtOrTrunc(CountRoundDown,
2381                                                   II.StartValue->getType(),
2382                                                   "cast.crd");
2383      EndValue = II.transform(BypassBuilder, CRD);
2384      EndValue->setName("ind.end");
2385      break;
2386    }
2387    case LoopVectorizationLegality::IK_PtrInduction: {
2388      EndValue = II.transform(BypassBuilder, CountRoundDown);
2389      EndValue->setName("ptr.ind.end");
2390      break;
2391    }
2392    }// end of case
2393
2394    // The new PHI merges the original incoming value, in case of a bypass,
2395    // or the value at the end of the vectorized loop.
2396    for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I) {
2397      if (OrigPhi == OldInduction)
2398        ResumeVal->addIncoming(StartIdx, LoopBypassBlocks[I]);
2399      else
2400        ResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]);
2401    }
2402    ResumeVal->addIncoming(EndValue, VecBody);
2403
2404    // Fix the scalar body counter (PHI node).
2405    unsigned BlockIdx = OrigPhi->getBasicBlockIndex(ScalarPH);
2406
2407    // The old induction's phi node in the scalar body needs the truncated
2408    // value.
2409    if (OrigPhi == OldInduction) {
2410      BCResumeVal->addIncoming(StartIdx, LoopBypassBlocks[0]);
2411      OrigPhi->setIncomingValue(BlockIdx, BCTruncResumeVal);
2412    } else {
2413      BCResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[0]);
2414      OrigPhi->setIncomingValue(BlockIdx, BCResumeVal);
2415    }
2416  }
2417
2418  // If we are generating a new induction variable then we also need to
2419  // generate the code that calculates the exit value. This value is not
2420  // simply the end of the counter because we may skip the vectorized body
2421  // in case of a runtime check.
2422  if (!OldInduction){
2423    assert(!ResumeIndex && "Unexpected resume value found");
2424    ResumeIndex = PHINode::Create(IdxTy, 2, "new.indc.resume.val",
2425                                  MiddleBlock->getTerminator());
2426    for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I)
2427      ResumeIndex->addIncoming(StartIdx, LoopBypassBlocks[I]);
2428    ResumeIndex->addIncoming(IdxEndRoundDown, VecBody);
2429  }
2430
2431  // Make sure that we found the index where scalar loop needs to continue.
2432  assert(ResumeIndex && ResumeIndex->getType()->isIntegerTy() &&
2433         "Invalid resume Index");
2434
2435  // Add a check in the middle block to see if we have completed
2436  // all of the iterations in the first vector loop.
2437  // If (N - N%VF) == N, then we *don't* need to run the remainder.
2438  Value *CmpN = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ, IdxEnd,
2439                                ResumeIndex, "cmp.n",
2440                                MiddleBlock->getTerminator());
2441
2442  BranchInst::Create(ExitBlock, ScalarPH, CmpN, MiddleBlock->getTerminator());
2443  // Remove the old terminator.
2444  MiddleBlock->getTerminator()->eraseFromParent();
2445
2446  // Create i+1 and fill the PHINode.
2447  Value *NextIdx = Builder.CreateAdd(Induction, Step, "index.next");
2448  Induction->addIncoming(StartIdx, VectorPH);
2449  Induction->addIncoming(NextIdx, VecBody);
2450  // Create the compare.
2451  Value *ICmp = Builder.CreateICmpEQ(NextIdx, IdxEndRoundDown);
2452  Builder.CreateCondBr(ICmp, MiddleBlock, VecBody);
2453
2454  // Now we have two terminators. Remove the old one from the block.
2455  VecBody->getTerminator()->eraseFromParent();
2456
2457  // Get ready to start creating new instructions into the vectorized body.
2458  Builder.SetInsertPoint(VecBody->getFirstInsertionPt());
2459
2460  // Save the state.
2461  LoopVectorPreHeader = VectorPH;
2462  LoopScalarPreHeader = ScalarPH;
2463  LoopMiddleBlock = MiddleBlock;
2464  LoopExitBlock = ExitBlock;
2465  LoopVectorBody.push_back(VecBody);
2466  LoopScalarBody = OldBasicBlock;
2467
2468  LoopVectorizeHints Hints(Lp, true);
2469  Hints.setAlreadyVectorized();
2470}
2471
2472/// This function returns the identity element (or neutral element) for
2473/// the operation K.
2474Constant*
2475LoopVectorizationLegality::getReductionIdentity(ReductionKind K, Type *Tp) {
2476  switch (K) {
2477  case RK_IntegerXor:
2478  case RK_IntegerAdd:
2479  case RK_IntegerOr:
2480    // Adding, Xoring, Oring zero to a number does not change it.
2481    return ConstantInt::get(Tp, 0);
2482  case RK_IntegerMult:
2483    // Multiplying a number by 1 does not change it.
2484    return ConstantInt::get(Tp, 1);
2485  case RK_IntegerAnd:
2486    // AND-ing a number with an all-1 value does not change it.
2487    return ConstantInt::get(Tp, -1, true);
2488  case  RK_FloatMult:
2489    // Multiplying a number by 1 does not change it.
2490    return ConstantFP::get(Tp, 1.0L);
2491  case  RK_FloatAdd:
2492    // Adding zero to a number does not change it.
2493    return ConstantFP::get(Tp, 0.0L);
2494  default:
2495    llvm_unreachable("Unknown reduction kind");
2496  }
2497}
2498
2499/// This function translates the reduction kind to an LLVM binary operator.
2500static unsigned
2501getReductionBinOp(LoopVectorizationLegality::ReductionKind Kind) {
2502  switch (Kind) {
2503    case LoopVectorizationLegality::RK_IntegerAdd:
2504      return Instruction::Add;
2505    case LoopVectorizationLegality::RK_IntegerMult:
2506      return Instruction::Mul;
2507    case LoopVectorizationLegality::RK_IntegerOr:
2508      return Instruction::Or;
2509    case LoopVectorizationLegality::RK_IntegerAnd:
2510      return Instruction::And;
2511    case LoopVectorizationLegality::RK_IntegerXor:
2512      return Instruction::Xor;
2513    case LoopVectorizationLegality::RK_FloatMult:
2514      return Instruction::FMul;
2515    case LoopVectorizationLegality::RK_FloatAdd:
2516      return Instruction::FAdd;
2517    case LoopVectorizationLegality::RK_IntegerMinMax:
2518      return Instruction::ICmp;
2519    case LoopVectorizationLegality::RK_FloatMinMax:
2520      return Instruction::FCmp;
2521    default:
2522      llvm_unreachable("Unknown reduction operation");
2523  }
2524}
2525
2526static Value *createMinMaxOp(IRBuilder<> &Builder,
2527                             LoopVectorizationLegality::MinMaxReductionKind RK,
2528                             Value *Left, Value *Right) {
2529  CmpInst::Predicate P = CmpInst::ICMP_NE;
2530  switch (RK) {
2531  default:
2532    llvm_unreachable("Unknown min/max reduction kind");
2533  case LoopVectorizationLegality::MRK_UIntMin:
2534    P = CmpInst::ICMP_ULT;
2535    break;
2536  case LoopVectorizationLegality::MRK_UIntMax:
2537    P = CmpInst::ICMP_UGT;
2538    break;
2539  case LoopVectorizationLegality::MRK_SIntMin:
2540    P = CmpInst::ICMP_SLT;
2541    break;
2542  case LoopVectorizationLegality::MRK_SIntMax:
2543    P = CmpInst::ICMP_SGT;
2544    break;
2545  case LoopVectorizationLegality::MRK_FloatMin:
2546    P = CmpInst::FCMP_OLT;
2547    break;
2548  case LoopVectorizationLegality::MRK_FloatMax:
2549    P = CmpInst::FCMP_OGT;
2550    break;
2551  }
2552
2553  Value *Cmp;
2554  if (RK == LoopVectorizationLegality::MRK_FloatMin ||
2555      RK == LoopVectorizationLegality::MRK_FloatMax)
2556    Cmp = Builder.CreateFCmp(P, Left, Right, "rdx.minmax.cmp");
2557  else
2558    Cmp = Builder.CreateICmp(P, Left, Right, "rdx.minmax.cmp");
2559
2560  Value *Select = Builder.CreateSelect(Cmp, Left, Right, "rdx.minmax.select");
2561  return Select;
2562}
2563
2564namespace {
2565struct CSEDenseMapInfo {
2566  static bool canHandle(Instruction *I) {
2567    return isa<InsertElementInst>(I) || isa<ExtractElementInst>(I) ||
2568           isa<ShuffleVectorInst>(I) || isa<GetElementPtrInst>(I);
2569  }
2570  static inline Instruction *getEmptyKey() {
2571    return DenseMapInfo<Instruction *>::getEmptyKey();
2572  }
2573  static inline Instruction *getTombstoneKey() {
2574    return DenseMapInfo<Instruction *>::getTombstoneKey();
2575  }
2576  static unsigned getHashValue(Instruction *I) {
2577    assert(canHandle(I) && "Unknown instruction!");
2578    return hash_combine(I->getOpcode(), hash_combine_range(I->value_op_begin(),
2579                                                           I->value_op_end()));
2580  }
2581  static bool isEqual(Instruction *LHS, Instruction *RHS) {
2582    if (LHS == getEmptyKey() || RHS == getEmptyKey() ||
2583        LHS == getTombstoneKey() || RHS == getTombstoneKey())
2584      return LHS == RHS;
2585    return LHS->isIdenticalTo(RHS);
2586  }
2587};
2588}
2589
2590/// \brief Check whether this block is a predicated block.
2591/// Due to if predication of stores we might create a sequence of "if(pred) a[i]
2592/// = ...;  " blocks. We start with one vectorized basic block. For every
2593/// conditional block we split this vectorized block. Therefore, every second
2594/// block will be a predicated one.
2595static bool isPredicatedBlock(unsigned BlockNum) {
2596  return BlockNum % 2;
2597}
2598
2599///\brief Perform cse of induction variable instructions.
2600static void cse(SmallVector<BasicBlock *, 4> &BBs) {
2601  // Perform simple cse.
2602  SmallDenseMap<Instruction *, Instruction *, 4, CSEDenseMapInfo> CSEMap;
2603  for (unsigned i = 0, e = BBs.size(); i != e; ++i) {
2604    BasicBlock *BB = BBs[i];
2605    for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E;) {
2606      Instruction *In = I++;
2607
2608      if (!CSEDenseMapInfo::canHandle(In))
2609        continue;
2610
2611      // Check if we can replace this instruction with any of the
2612      // visited instructions.
2613      if (Instruction *V = CSEMap.lookup(In)) {
2614        In->replaceAllUsesWith(V);
2615        In->eraseFromParent();
2616        continue;
2617      }
2618      // Ignore instructions in conditional blocks. We create "if (pred) a[i] =
2619      // ...;" blocks for predicated stores. Every second block is a predicated
2620      // block.
2621      if (isPredicatedBlock(i))
2622        continue;
2623
2624      CSEMap[In] = In;
2625    }
2626  }
2627}
2628
2629/// \brief Adds a 'fast' flag to floating point operations.
2630static Value *addFastMathFlag(Value *V) {
2631  if (isa<FPMathOperator>(V)){
2632    FastMathFlags Flags;
2633    Flags.setUnsafeAlgebra();
2634    cast<Instruction>(V)->setFastMathFlags(Flags);
2635  }
2636  return V;
2637}
2638
2639/// Estimate the overhead of scalarizing a value. Insert and Extract are set if
2640/// the result needs to be inserted and/or extracted from vectors.
2641static unsigned getScalarizationOverhead(Type *Ty, bool Insert, bool Extract,
2642                                         const TargetTransformInfo &TTI) {
2643  if (Ty->isVoidTy())
2644    return 0;
2645
2646  assert(Ty->isVectorTy() && "Can only scalarize vectors");
2647  unsigned Cost = 0;
2648
2649  for (int i = 0, e = Ty->getVectorNumElements(); i < e; ++i) {
2650    if (Insert)
2651      Cost += TTI.getVectorInstrCost(Instruction::InsertElement, Ty, i);
2652    if (Extract)
2653      Cost += TTI.getVectorInstrCost(Instruction::ExtractElement, Ty, i);
2654  }
2655
2656  return Cost;
2657}
2658
2659// Estimate cost of a call instruction CI if it were vectorized with factor VF.
2660// Return the cost of the instruction, including scalarization overhead if it's
2661// needed. The flag NeedToScalarize shows if the call needs to be scalarized -
2662// i.e. either vector version isn't available, or is too expensive.
2663static unsigned getVectorCallCost(CallInst *CI, unsigned VF,
2664                                  const TargetTransformInfo &TTI,
2665                                  const TargetLibraryInfo *TLI,
2666                                  bool &NeedToScalarize) {
2667  Function *F = CI->getCalledFunction();
2668  StringRef FnName = CI->getCalledFunction()->getName();
2669  Type *ScalarRetTy = CI->getType();
2670  SmallVector<Type *, 4> Tys, ScalarTys;
2671  for (auto &ArgOp : CI->arg_operands())
2672    ScalarTys.push_back(ArgOp->getType());
2673
2674  // Estimate cost of scalarized vector call. The source operands are assumed
2675  // to be vectors, so we need to extract individual elements from there,
2676  // execute VF scalar calls, and then gather the result into the vector return
2677  // value.
2678  unsigned ScalarCallCost = TTI.getCallInstrCost(F, ScalarRetTy, ScalarTys);
2679  if (VF == 1)
2680    return ScalarCallCost;
2681
2682  // Compute corresponding vector type for return value and arguments.
2683  Type *RetTy = ToVectorTy(ScalarRetTy, VF);
2684  for (unsigned i = 0, ie = ScalarTys.size(); i != ie; ++i)
2685    Tys.push_back(ToVectorTy(ScalarTys[i], VF));
2686
2687  // Compute costs of unpacking argument values for the scalar calls and
2688  // packing the return values to a vector.
2689  unsigned ScalarizationCost =
2690      getScalarizationOverhead(RetTy, true, false, TTI);
2691  for (unsigned i = 0, ie = Tys.size(); i != ie; ++i)
2692    ScalarizationCost += getScalarizationOverhead(Tys[i], false, true, TTI);
2693
2694  unsigned Cost = ScalarCallCost * VF + ScalarizationCost;
2695
2696  // If we can't emit a vector call for this function, then the currently found
2697  // cost is the cost we need to return.
2698  NeedToScalarize = true;
2699  if (!TLI || !TLI->isFunctionVectorizable(FnName, VF) || CI->isNoBuiltin())
2700    return Cost;
2701
2702  // If the corresponding vector cost is cheaper, return its cost.
2703  unsigned VectorCallCost = TTI.getCallInstrCost(nullptr, RetTy, Tys);
2704  if (VectorCallCost < Cost) {
2705    NeedToScalarize = false;
2706    return VectorCallCost;
2707  }
2708  return Cost;
2709}
2710
2711// Estimate cost of an intrinsic call instruction CI if it were vectorized with
2712// factor VF.  Return the cost of the instruction, including scalarization
2713// overhead if it's needed.
2714static unsigned getVectorIntrinsicCost(CallInst *CI, unsigned VF,
2715                                       const TargetTransformInfo &TTI,
2716                                       const TargetLibraryInfo *TLI) {
2717  Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI);
2718  assert(ID && "Expected intrinsic call!");
2719
2720  Type *RetTy = ToVectorTy(CI->getType(), VF);
2721  SmallVector<Type *, 4> Tys;
2722  for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i)
2723    Tys.push_back(ToVectorTy(CI->getArgOperand(i)->getType(), VF));
2724
2725  return TTI.getIntrinsicInstrCost(ID, RetTy, Tys);
2726}
2727
2728void InnerLoopVectorizer::vectorizeLoop() {
2729  //===------------------------------------------------===//
2730  //
2731  // Notice: any optimization or new instruction that go
2732  // into the code below should be also be implemented in
2733  // the cost-model.
2734  //
2735  //===------------------------------------------------===//
2736  Constant *Zero = Builder.getInt32(0);
2737
2738  // In order to support reduction variables we need to be able to vectorize
2739  // Phi nodes. Phi nodes have cycles, so we need to vectorize them in two
2740  // stages. First, we create a new vector PHI node with no incoming edges.
2741  // We use this value when we vectorize all of the instructions that use the
2742  // PHI. Next, after all of the instructions in the block are complete we
2743  // add the new incoming edges to the PHI. At this point all of the
2744  // instructions in the basic block are vectorized, so we can use them to
2745  // construct the PHI.
2746  PhiVector RdxPHIsToFix;
2747
2748  // Scan the loop in a topological order to ensure that defs are vectorized
2749  // before users.
2750  LoopBlocksDFS DFS(OrigLoop);
2751  DFS.perform(LI);
2752
2753  // Vectorize all of the blocks in the original loop.
2754  for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(),
2755       be = DFS.endRPO(); bb != be; ++bb)
2756    vectorizeBlockInLoop(*bb, &RdxPHIsToFix);
2757
2758  // At this point every instruction in the original loop is widened to
2759  // a vector form. We are almost done. Now, we need to fix the PHI nodes
2760  // that we vectorized. The PHI nodes are currently empty because we did
2761  // not want to introduce cycles. Notice that the remaining PHI nodes
2762  // that we need to fix are reduction variables.
2763
2764  // Create the 'reduced' values for each of the induction vars.
2765  // The reduced values are the vector values that we scalarize and combine
2766  // after the loop is finished.
2767  for (PhiVector::iterator it = RdxPHIsToFix.begin(), e = RdxPHIsToFix.end();
2768       it != e; ++it) {
2769    PHINode *RdxPhi = *it;
2770    assert(RdxPhi && "Unable to recover vectorized PHI");
2771
2772    // Find the reduction variable descriptor.
2773    assert(Legal->getReductionVars()->count(RdxPhi) &&
2774           "Unable to find the reduction variable");
2775    LoopVectorizationLegality::ReductionDescriptor RdxDesc =
2776    (*Legal->getReductionVars())[RdxPhi];
2777
2778    setDebugLocFromInst(Builder, RdxDesc.StartValue);
2779
2780    // We need to generate a reduction vector from the incoming scalar.
2781    // To do so, we need to generate the 'identity' vector and override
2782    // one of the elements with the incoming scalar reduction. We need
2783    // to do it in the vector-loop preheader.
2784    Builder.SetInsertPoint(LoopBypassBlocks[1]->getTerminator());
2785
2786    // This is the vector-clone of the value that leaves the loop.
2787    VectorParts &VectorExit = getVectorValue(RdxDesc.LoopExitInstr);
2788    Type *VecTy = VectorExit[0]->getType();
2789
2790    // Find the reduction identity variable. Zero for addition, or, xor,
2791    // one for multiplication, -1 for And.
2792    Value *Identity;
2793    Value *VectorStart;
2794    if (RdxDesc.Kind == LoopVectorizationLegality::RK_IntegerMinMax ||
2795        RdxDesc.Kind == LoopVectorizationLegality::RK_FloatMinMax) {
2796      // MinMax reduction have the start value as their identify.
2797      if (VF == 1) {
2798        VectorStart = Identity = RdxDesc.StartValue;
2799      } else {
2800        VectorStart = Identity = Builder.CreateVectorSplat(VF,
2801                                                           RdxDesc.StartValue,
2802                                                           "minmax.ident");
2803      }
2804    } else {
2805      // Handle other reduction kinds:
2806      Constant *Iden =
2807      LoopVectorizationLegality::getReductionIdentity(RdxDesc.Kind,
2808                                                      VecTy->getScalarType());
2809      if (VF == 1) {
2810        Identity = Iden;
2811        // This vector is the Identity vector where the first element is the
2812        // incoming scalar reduction.
2813        VectorStart = RdxDesc.StartValue;
2814      } else {
2815        Identity = ConstantVector::getSplat(VF, Iden);
2816
2817        // This vector is the Identity vector where the first element is the
2818        // incoming scalar reduction.
2819        VectorStart = Builder.CreateInsertElement(Identity,
2820                                                  RdxDesc.StartValue, Zero);
2821      }
2822    }
2823
2824    // Fix the vector-loop phi.
2825
2826    // Reductions do not have to start at zero. They can start with
2827    // any loop invariant values.
2828    VectorParts &VecRdxPhi = WidenMap.get(RdxPhi);
2829    BasicBlock *Latch = OrigLoop->getLoopLatch();
2830    Value *LoopVal = RdxPhi->getIncomingValueForBlock(Latch);
2831    VectorParts &Val = getVectorValue(LoopVal);
2832    for (unsigned part = 0; part < UF; ++part) {
2833      // Make sure to add the reduction stat value only to the
2834      // first unroll part.
2835      Value *StartVal = (part == 0) ? VectorStart : Identity;
2836      cast<PHINode>(VecRdxPhi[part])->addIncoming(StartVal,
2837                                                  LoopVectorPreHeader);
2838      cast<PHINode>(VecRdxPhi[part])->addIncoming(Val[part],
2839                                                  LoopVectorBody.back());
2840    }
2841
2842    // Before each round, move the insertion point right between
2843    // the PHIs and the values we are going to write.
2844    // This allows us to write both PHINodes and the extractelement
2845    // instructions.
2846    Builder.SetInsertPoint(LoopMiddleBlock->getFirstInsertionPt());
2847
2848    VectorParts RdxParts;
2849    setDebugLocFromInst(Builder, RdxDesc.LoopExitInstr);
2850    for (unsigned part = 0; part < UF; ++part) {
2851      // This PHINode contains the vectorized reduction variable, or
2852      // the initial value vector, if we bypass the vector loop.
2853      VectorParts &RdxExitVal = getVectorValue(RdxDesc.LoopExitInstr);
2854      PHINode *NewPhi = Builder.CreatePHI(VecTy, 2, "rdx.vec.exit.phi");
2855      Value *StartVal = (part == 0) ? VectorStart : Identity;
2856      for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I)
2857        NewPhi->addIncoming(StartVal, LoopBypassBlocks[I]);
2858      NewPhi->addIncoming(RdxExitVal[part],
2859                          LoopVectorBody.back());
2860      RdxParts.push_back(NewPhi);
2861    }
2862
2863    // Reduce all of the unrolled parts into a single vector.
2864    Value *ReducedPartRdx = RdxParts[0];
2865    unsigned Op = getReductionBinOp(RdxDesc.Kind);
2866    setDebugLocFromInst(Builder, ReducedPartRdx);
2867    for (unsigned part = 1; part < UF; ++part) {
2868      if (Op != Instruction::ICmp && Op != Instruction::FCmp)
2869        // Floating point operations had to be 'fast' to enable the reduction.
2870        ReducedPartRdx = addFastMathFlag(
2871            Builder.CreateBinOp((Instruction::BinaryOps)Op, RdxParts[part],
2872                                ReducedPartRdx, "bin.rdx"));
2873      else
2874        ReducedPartRdx = createMinMaxOp(Builder, RdxDesc.MinMaxKind,
2875                                        ReducedPartRdx, RdxParts[part]);
2876    }
2877
2878    if (VF > 1) {
2879      // VF is a power of 2 so we can emit the reduction using log2(VF) shuffles
2880      // and vector ops, reducing the set of values being computed by half each
2881      // round.
2882      assert(isPowerOf2_32(VF) &&
2883             "Reduction emission only supported for pow2 vectors!");
2884      Value *TmpVec = ReducedPartRdx;
2885      SmallVector<Constant*, 32> ShuffleMask(VF, nullptr);
2886      for (unsigned i = VF; i != 1; i >>= 1) {
2887        // Move the upper half of the vector to the lower half.
2888        for (unsigned j = 0; j != i/2; ++j)
2889          ShuffleMask[j] = Builder.getInt32(i/2 + j);
2890
2891        // Fill the rest of the mask with undef.
2892        std::fill(&ShuffleMask[i/2], ShuffleMask.end(),
2893                  UndefValue::get(Builder.getInt32Ty()));
2894
2895        Value *Shuf =
2896        Builder.CreateShuffleVector(TmpVec,
2897                                    UndefValue::get(TmpVec->getType()),
2898                                    ConstantVector::get(ShuffleMask),
2899                                    "rdx.shuf");
2900
2901        if (Op != Instruction::ICmp && Op != Instruction::FCmp)
2902          // Floating point operations had to be 'fast' to enable the reduction.
2903          TmpVec = addFastMathFlag(Builder.CreateBinOp(
2904              (Instruction::BinaryOps)Op, TmpVec, Shuf, "bin.rdx"));
2905        else
2906          TmpVec = createMinMaxOp(Builder, RdxDesc.MinMaxKind, TmpVec, Shuf);
2907      }
2908
2909      // The result is in the first element of the vector.
2910      ReducedPartRdx = Builder.CreateExtractElement(TmpVec,
2911                                                    Builder.getInt32(0));
2912    }
2913
2914    // Create a phi node that merges control-flow from the backedge-taken check
2915    // block and the middle block.
2916    PHINode *BCBlockPhi = PHINode::Create(RdxPhi->getType(), 2, "bc.merge.rdx",
2917                                          LoopScalarPreHeader->getTerminator());
2918    BCBlockPhi->addIncoming(RdxDesc.StartValue, LoopBypassBlocks[0]);
2919    BCBlockPhi->addIncoming(ReducedPartRdx, LoopMiddleBlock);
2920
2921    // Now, we need to fix the users of the reduction variable
2922    // inside and outside of the scalar remainder loop.
2923    // We know that the loop is in LCSSA form. We need to update the
2924    // PHI nodes in the exit blocks.
2925    for (BasicBlock::iterator LEI = LoopExitBlock->begin(),
2926         LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) {
2927      PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI);
2928      if (!LCSSAPhi) break;
2929
2930      // All PHINodes need to have a single entry edge, or two if
2931      // we already fixed them.
2932      assert(LCSSAPhi->getNumIncomingValues() < 3 && "Invalid LCSSA PHI");
2933
2934      // We found our reduction value exit-PHI. Update it with the
2935      // incoming bypass edge.
2936      if (LCSSAPhi->getIncomingValue(0) == RdxDesc.LoopExitInstr) {
2937        // Add an edge coming from the bypass.
2938        LCSSAPhi->addIncoming(ReducedPartRdx, LoopMiddleBlock);
2939        break;
2940      }
2941    }// end of the LCSSA phi scan.
2942
2943    // Fix the scalar loop reduction variable with the incoming reduction sum
2944    // from the vector body and from the backedge value.
2945    int IncomingEdgeBlockIdx =
2946    (RdxPhi)->getBasicBlockIndex(OrigLoop->getLoopLatch());
2947    assert(IncomingEdgeBlockIdx >= 0 && "Invalid block index");
2948    // Pick the other block.
2949    int SelfEdgeBlockIdx = (IncomingEdgeBlockIdx ? 0 : 1);
2950    (RdxPhi)->setIncomingValue(SelfEdgeBlockIdx, BCBlockPhi);
2951    (RdxPhi)->setIncomingValue(IncomingEdgeBlockIdx, RdxDesc.LoopExitInstr);
2952  }// end of for each redux variable.
2953
2954  fixLCSSAPHIs();
2955
2956  // Remove redundant induction instructions.
2957  cse(LoopVectorBody);
2958}
2959
2960void InnerLoopVectorizer::fixLCSSAPHIs() {
2961  for (BasicBlock::iterator LEI = LoopExitBlock->begin(),
2962       LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) {
2963    PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI);
2964    if (!LCSSAPhi) break;
2965    if (LCSSAPhi->getNumIncomingValues() == 1)
2966      LCSSAPhi->addIncoming(UndefValue::get(LCSSAPhi->getType()),
2967                            LoopMiddleBlock);
2968  }
2969}
2970
2971InnerLoopVectorizer::VectorParts
2972InnerLoopVectorizer::createEdgeMask(BasicBlock *Src, BasicBlock *Dst) {
2973  assert(std::find(pred_begin(Dst), pred_end(Dst), Src) != pred_end(Dst) &&
2974         "Invalid edge");
2975
2976  // Look for cached value.
2977  std::pair<BasicBlock*, BasicBlock*> Edge(Src, Dst);
2978  EdgeMaskCache::iterator ECEntryIt = MaskCache.find(Edge);
2979  if (ECEntryIt != MaskCache.end())
2980    return ECEntryIt->second;
2981
2982  VectorParts SrcMask = createBlockInMask(Src);
2983
2984  // The terminator has to be a branch inst!
2985  BranchInst *BI = dyn_cast<BranchInst>(Src->getTerminator());
2986  assert(BI && "Unexpected terminator found");
2987
2988  if (BI->isConditional()) {
2989    VectorParts EdgeMask = getVectorValue(BI->getCondition());
2990
2991    if (BI->getSuccessor(0) != Dst)
2992      for (unsigned part = 0; part < UF; ++part)
2993        EdgeMask[part] = Builder.CreateNot(EdgeMask[part]);
2994
2995    for (unsigned part = 0; part < UF; ++part)
2996      EdgeMask[part] = Builder.CreateAnd(EdgeMask[part], SrcMask[part]);
2997
2998    MaskCache[Edge] = EdgeMask;
2999    return EdgeMask;
3000  }
3001
3002  MaskCache[Edge] = SrcMask;
3003  return SrcMask;
3004}
3005
3006InnerLoopVectorizer::VectorParts
3007InnerLoopVectorizer::createBlockInMask(BasicBlock *BB) {
3008  assert(OrigLoop->contains(BB) && "Block is not a part of a loop");
3009
3010  // Loop incoming mask is all-one.
3011  if (OrigLoop->getHeader() == BB) {
3012    Value *C = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 1);
3013    return getVectorValue(C);
3014  }
3015
3016  // This is the block mask. We OR all incoming edges, and with zero.
3017  Value *Zero = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 0);
3018  VectorParts BlockMask = getVectorValue(Zero);
3019
3020  // For each pred:
3021  for (pred_iterator it = pred_begin(BB), e = pred_end(BB); it != e; ++it) {
3022    VectorParts EM = createEdgeMask(*it, BB);
3023    for (unsigned part = 0; part < UF; ++part)
3024      BlockMask[part] = Builder.CreateOr(BlockMask[part], EM[part]);
3025  }
3026
3027  return BlockMask;
3028}
3029
3030void InnerLoopVectorizer::widenPHIInstruction(Instruction *PN,
3031                                              InnerLoopVectorizer::VectorParts &Entry,
3032                                              unsigned UF, unsigned VF, PhiVector *PV) {
3033  PHINode* P = cast<PHINode>(PN);
3034  // Handle reduction variables:
3035  if (Legal->getReductionVars()->count(P)) {
3036    for (unsigned part = 0; part < UF; ++part) {
3037      // This is phase one of vectorizing PHIs.
3038      Type *VecTy = (VF == 1) ? PN->getType() :
3039      VectorType::get(PN->getType(), VF);
3040      Entry[part] = PHINode::Create(VecTy, 2, "vec.phi",
3041                                    LoopVectorBody.back()-> getFirstInsertionPt());
3042    }
3043    PV->push_back(P);
3044    return;
3045  }
3046
3047  setDebugLocFromInst(Builder, P);
3048  // Check for PHI nodes that are lowered to vector selects.
3049  if (P->getParent() != OrigLoop->getHeader()) {
3050    // We know that all PHIs in non-header blocks are converted into
3051    // selects, so we don't have to worry about the insertion order and we
3052    // can just use the builder.
3053    // At this point we generate the predication tree. There may be
3054    // duplications since this is a simple recursive scan, but future
3055    // optimizations will clean it up.
3056
3057    unsigned NumIncoming = P->getNumIncomingValues();
3058
3059    // Generate a sequence of selects of the form:
3060    // SELECT(Mask3, In3,
3061    //      SELECT(Mask2, In2,
3062    //                   ( ...)))
3063    for (unsigned In = 0; In < NumIncoming; In++) {
3064      VectorParts Cond = createEdgeMask(P->getIncomingBlock(In),
3065                                        P->getParent());
3066      VectorParts &In0 = getVectorValue(P->getIncomingValue(In));
3067
3068      for (unsigned part = 0; part < UF; ++part) {
3069        // We might have single edge PHIs (blocks) - use an identity
3070        // 'select' for the first PHI operand.
3071        if (In == 0)
3072          Entry[part] = Builder.CreateSelect(Cond[part], In0[part],
3073                                             In0[part]);
3074        else
3075          // Select between the current value and the previous incoming edge
3076          // based on the incoming mask.
3077          Entry[part] = Builder.CreateSelect(Cond[part], In0[part],
3078                                             Entry[part], "predphi");
3079      }
3080    }
3081    return;
3082  }
3083
3084  // This PHINode must be an induction variable.
3085  // Make sure that we know about it.
3086  assert(Legal->getInductionVars()->count(P) &&
3087         "Not an induction variable");
3088
3089  LoopVectorizationLegality::InductionInfo II =
3090  Legal->getInductionVars()->lookup(P);
3091
3092  // FIXME: The newly created binary instructions should contain nsw/nuw flags,
3093  // which can be found from the original scalar operations.
3094  switch (II.IK) {
3095    case LoopVectorizationLegality::IK_NoInduction:
3096      llvm_unreachable("Unknown induction");
3097    case LoopVectorizationLegality::IK_IntInduction: {
3098      assert(P->getType() == II.StartValue->getType() && "Types must match");
3099      Type *PhiTy = P->getType();
3100      Value *Broadcasted;
3101      if (P == OldInduction) {
3102        // Handle the canonical induction variable. We might have had to
3103        // extend the type.
3104        Broadcasted = Builder.CreateTrunc(Induction, PhiTy);
3105      } else {
3106        // Handle other induction variables that are now based on the
3107        // canonical one.
3108        Value *NormalizedIdx = Builder.CreateSub(Induction, ExtendedIdx,
3109                                                 "normalized.idx");
3110        NormalizedIdx = Builder.CreateSExtOrTrunc(NormalizedIdx, PhiTy);
3111        Broadcasted = II.transform(Builder, NormalizedIdx);
3112        Broadcasted->setName("offset.idx");
3113      }
3114      Broadcasted = getBroadcastInstrs(Broadcasted);
3115      // After broadcasting the induction variable we need to make the vector
3116      // consecutive by adding 0, 1, 2, etc.
3117      for (unsigned part = 0; part < UF; ++part)
3118        Entry[part] = getStepVector(Broadcasted, VF * part, II.StepValue);
3119      return;
3120    }
3121    case LoopVectorizationLegality::IK_PtrInduction:
3122      // Handle the pointer induction variable case.
3123      assert(P->getType()->isPointerTy() && "Unexpected type.");
3124      // This is the normalized GEP that starts counting at zero.
3125      Value *NormalizedIdx =
3126          Builder.CreateSub(Induction, ExtendedIdx, "normalized.idx");
3127      // This is the vector of results. Notice that we don't generate
3128      // vector geps because scalar geps result in better code.
3129      for (unsigned part = 0; part < UF; ++part) {
3130        if (VF == 1) {
3131          int EltIndex = part;
3132          Constant *Idx = ConstantInt::get(Induction->getType(), EltIndex);
3133          Value *GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx);
3134          Value *SclrGep = II.transform(Builder, GlobalIdx);
3135          SclrGep->setName("next.gep");
3136          Entry[part] = SclrGep;
3137          continue;
3138        }
3139
3140        Value *VecVal = UndefValue::get(VectorType::get(P->getType(), VF));
3141        for (unsigned int i = 0; i < VF; ++i) {
3142          int EltIndex = i + part * VF;
3143          Constant *Idx = ConstantInt::get(Induction->getType(), EltIndex);
3144          Value *GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx);
3145          Value *SclrGep = II.transform(Builder, GlobalIdx);
3146          SclrGep->setName("next.gep");
3147          VecVal = Builder.CreateInsertElement(VecVal, SclrGep,
3148                                               Builder.getInt32(i),
3149                                               "insert.gep");
3150        }
3151        Entry[part] = VecVal;
3152      }
3153      return;
3154  }
3155}
3156
3157void InnerLoopVectorizer::vectorizeBlockInLoop(BasicBlock *BB, PhiVector *PV) {
3158  // For each instruction in the old loop.
3159  for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
3160    VectorParts &Entry = WidenMap.get(it);
3161    switch (it->getOpcode()) {
3162    case Instruction::Br:
3163      // Nothing to do for PHIs and BR, since we already took care of the
3164      // loop control flow instructions.
3165      continue;
3166    case Instruction::PHI: {
3167      // Vectorize PHINodes.
3168      widenPHIInstruction(it, Entry, UF, VF, PV);
3169      continue;
3170    }// End of PHI.
3171
3172    case Instruction::Add:
3173    case Instruction::FAdd:
3174    case Instruction::Sub:
3175    case Instruction::FSub:
3176    case Instruction::Mul:
3177    case Instruction::FMul:
3178    case Instruction::UDiv:
3179    case Instruction::SDiv:
3180    case Instruction::FDiv:
3181    case Instruction::URem:
3182    case Instruction::SRem:
3183    case Instruction::FRem:
3184    case Instruction::Shl:
3185    case Instruction::LShr:
3186    case Instruction::AShr:
3187    case Instruction::And:
3188    case Instruction::Or:
3189    case Instruction::Xor: {
3190      // Just widen binops.
3191      BinaryOperator *BinOp = dyn_cast<BinaryOperator>(it);
3192      setDebugLocFromInst(Builder, BinOp);
3193      VectorParts &A = getVectorValue(it->getOperand(0));
3194      VectorParts &B = getVectorValue(it->getOperand(1));
3195
3196      // Use this vector value for all users of the original instruction.
3197      for (unsigned Part = 0; Part < UF; ++Part) {
3198        Value *V = Builder.CreateBinOp(BinOp->getOpcode(), A[Part], B[Part]);
3199
3200        if (BinaryOperator *VecOp = dyn_cast<BinaryOperator>(V))
3201          VecOp->copyIRFlags(BinOp);
3202
3203        Entry[Part] = V;
3204      }
3205
3206      propagateMetadata(Entry, it);
3207      break;
3208    }
3209    case Instruction::Select: {
3210      // Widen selects.
3211      // If the selector is loop invariant we can create a select
3212      // instruction with a scalar condition. Otherwise, use vector-select.
3213      bool InvariantCond = SE->isLoopInvariant(SE->getSCEV(it->getOperand(0)),
3214                                               OrigLoop);
3215      setDebugLocFromInst(Builder, it);
3216
3217      // The condition can be loop invariant  but still defined inside the
3218      // loop. This means that we can't just use the original 'cond' value.
3219      // We have to take the 'vectorized' value and pick the first lane.
3220      // Instcombine will make this a no-op.
3221      VectorParts &Cond = getVectorValue(it->getOperand(0));
3222      VectorParts &Op0  = getVectorValue(it->getOperand(1));
3223      VectorParts &Op1  = getVectorValue(it->getOperand(2));
3224
3225      Value *ScalarCond = (VF == 1) ? Cond[0] :
3226        Builder.CreateExtractElement(Cond[0], Builder.getInt32(0));
3227
3228      for (unsigned Part = 0; Part < UF; ++Part) {
3229        Entry[Part] = Builder.CreateSelect(
3230          InvariantCond ? ScalarCond : Cond[Part],
3231          Op0[Part],
3232          Op1[Part]);
3233      }
3234
3235      propagateMetadata(Entry, it);
3236      break;
3237    }
3238
3239    case Instruction::ICmp:
3240    case Instruction::FCmp: {
3241      // Widen compares. Generate vector compares.
3242      bool FCmp = (it->getOpcode() == Instruction::FCmp);
3243      CmpInst *Cmp = dyn_cast<CmpInst>(it);
3244      setDebugLocFromInst(Builder, it);
3245      VectorParts &A = getVectorValue(it->getOperand(0));
3246      VectorParts &B = getVectorValue(it->getOperand(1));
3247      for (unsigned Part = 0; Part < UF; ++Part) {
3248        Value *C = nullptr;
3249        if (FCmp)
3250          C = Builder.CreateFCmp(Cmp->getPredicate(), A[Part], B[Part]);
3251        else
3252          C = Builder.CreateICmp(Cmp->getPredicate(), A[Part], B[Part]);
3253        Entry[Part] = C;
3254      }
3255
3256      propagateMetadata(Entry, it);
3257      break;
3258    }
3259
3260    case Instruction::Store:
3261    case Instruction::Load:
3262      vectorizeMemoryInstruction(it);
3263        break;
3264    case Instruction::ZExt:
3265    case Instruction::SExt:
3266    case Instruction::FPToUI:
3267    case Instruction::FPToSI:
3268    case Instruction::FPExt:
3269    case Instruction::PtrToInt:
3270    case Instruction::IntToPtr:
3271    case Instruction::SIToFP:
3272    case Instruction::UIToFP:
3273    case Instruction::Trunc:
3274    case Instruction::FPTrunc:
3275    case Instruction::BitCast: {
3276      CastInst *CI = dyn_cast<CastInst>(it);
3277      setDebugLocFromInst(Builder, it);
3278      /// Optimize the special case where the source is the induction
3279      /// variable. Notice that we can only optimize the 'trunc' case
3280      /// because: a. FP conversions lose precision, b. sext/zext may wrap,
3281      /// c. other casts depend on pointer size.
3282      if (CI->getOperand(0) == OldInduction &&
3283          it->getOpcode() == Instruction::Trunc) {
3284        Value *ScalarCast = Builder.CreateCast(CI->getOpcode(), Induction,
3285                                               CI->getType());
3286        Value *Broadcasted = getBroadcastInstrs(ScalarCast);
3287        LoopVectorizationLegality::InductionInfo II =
3288            Legal->getInductionVars()->lookup(OldInduction);
3289        Constant *Step =
3290            ConstantInt::getSigned(CI->getType(), II.StepValue->getSExtValue());
3291        for (unsigned Part = 0; Part < UF; ++Part)
3292          Entry[Part] = getStepVector(Broadcasted, VF * Part, Step);
3293        propagateMetadata(Entry, it);
3294        break;
3295      }
3296      /// Vectorize casts.
3297      Type *DestTy = (VF == 1) ? CI->getType() :
3298                                 VectorType::get(CI->getType(), VF);
3299
3300      VectorParts &A = getVectorValue(it->getOperand(0));
3301      for (unsigned Part = 0; Part < UF; ++Part)
3302        Entry[Part] = Builder.CreateCast(CI->getOpcode(), A[Part], DestTy);
3303      propagateMetadata(Entry, it);
3304      break;
3305    }
3306
3307    case Instruction::Call: {
3308      // Ignore dbg intrinsics.
3309      if (isa<DbgInfoIntrinsic>(it))
3310        break;
3311      setDebugLocFromInst(Builder, it);
3312
3313      Module *M = BB->getParent()->getParent();
3314      CallInst *CI = cast<CallInst>(it);
3315
3316      StringRef FnName = CI->getCalledFunction()->getName();
3317      Function *F = CI->getCalledFunction();
3318      Type *RetTy = ToVectorTy(CI->getType(), VF);
3319      SmallVector<Type *, 4> Tys;
3320      for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i)
3321        Tys.push_back(ToVectorTy(CI->getArgOperand(i)->getType(), VF));
3322
3323      Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI);
3324      if (ID &&
3325          (ID == Intrinsic::assume || ID == Intrinsic::lifetime_end ||
3326           ID == Intrinsic::lifetime_start)) {
3327        scalarizeInstruction(it);
3328        break;
3329      }
3330      // The flag shows whether we use Intrinsic or a usual Call for vectorized
3331      // version of the instruction.
3332      // Is it beneficial to perform intrinsic call compared to lib call?
3333      bool NeedToScalarize;
3334      unsigned CallCost = getVectorCallCost(CI, VF, *TTI, TLI, NeedToScalarize);
3335      bool UseVectorIntrinsic =
3336          ID && getVectorIntrinsicCost(CI, VF, *TTI, TLI) <= CallCost;
3337      if (!UseVectorIntrinsic && NeedToScalarize) {
3338        scalarizeInstruction(it);
3339        break;
3340      }
3341
3342      for (unsigned Part = 0; Part < UF; ++Part) {
3343        SmallVector<Value *, 4> Args;
3344        for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i) {
3345          Value *Arg = CI->getArgOperand(i);
3346          // Some intrinsics have a scalar argument - don't replace it with a
3347          // vector.
3348          if (!UseVectorIntrinsic || !hasVectorInstrinsicScalarOpd(ID, i)) {
3349            VectorParts &VectorArg = getVectorValue(CI->getArgOperand(i));
3350            Arg = VectorArg[Part];
3351          }
3352          Args.push_back(Arg);
3353        }
3354
3355        Function *VectorF;
3356        if (UseVectorIntrinsic) {
3357          // Use vector version of the intrinsic.
3358          Type *TysForDecl[] = {CI->getType()};
3359          if (VF > 1)
3360            TysForDecl[0] = VectorType::get(CI->getType()->getScalarType(), VF);
3361          VectorF = Intrinsic::getDeclaration(M, ID, TysForDecl);
3362        } else {
3363          // Use vector version of the library call.
3364          StringRef VFnName = TLI->getVectorizedFunction(FnName, VF);
3365          assert(!VFnName.empty() && "Vector function name is empty.");
3366          VectorF = M->getFunction(VFnName);
3367          if (!VectorF) {
3368            // Generate a declaration
3369            FunctionType *FTy = FunctionType::get(RetTy, Tys, false);
3370            VectorF =
3371                Function::Create(FTy, Function::ExternalLinkage, VFnName, M);
3372            VectorF->copyAttributesFrom(F);
3373          }
3374        }
3375        assert(VectorF && "Can't create vector function.");
3376        Entry[Part] = Builder.CreateCall(VectorF, Args);
3377      }
3378
3379      propagateMetadata(Entry, it);
3380      break;
3381    }
3382
3383    default:
3384      // All other instructions are unsupported. Scalarize them.
3385      scalarizeInstruction(it);
3386      break;
3387    }// end of switch.
3388  }// end of for_each instr.
3389}
3390
3391void InnerLoopVectorizer::updateAnalysis() {
3392  // Forget the original basic block.
3393  SE->forgetLoop(OrigLoop);
3394
3395  // Update the dominator tree information.
3396  assert(DT->properlyDominates(LoopBypassBlocks.front(), LoopExitBlock) &&
3397         "Entry does not dominate exit.");
3398
3399  for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I)
3400    DT->addNewBlock(LoopBypassBlocks[I], LoopBypassBlocks[I-1]);
3401  DT->addNewBlock(LoopVectorPreHeader, LoopBypassBlocks.back());
3402
3403  // Due to if predication of stores we might create a sequence of "if(pred)
3404  // a[i] = ...;  " blocks.
3405  for (unsigned i = 0, e = LoopVectorBody.size(); i != e; ++i) {
3406    if (i == 0)
3407      DT->addNewBlock(LoopVectorBody[0], LoopVectorPreHeader);
3408    else if (isPredicatedBlock(i)) {
3409      DT->addNewBlock(LoopVectorBody[i], LoopVectorBody[i-1]);
3410    } else {
3411      DT->addNewBlock(LoopVectorBody[i], LoopVectorBody[i-2]);
3412    }
3413  }
3414
3415  DT->addNewBlock(LoopMiddleBlock, LoopBypassBlocks[1]);
3416  DT->addNewBlock(LoopScalarPreHeader, LoopBypassBlocks[0]);
3417  DT->changeImmediateDominator(LoopScalarBody, LoopScalarPreHeader);
3418  DT->changeImmediateDominator(LoopExitBlock, LoopBypassBlocks[0]);
3419
3420  DEBUG(DT->verifyDomTree());
3421}
3422
3423/// \brief Check whether it is safe to if-convert this phi node.
3424///
3425/// Phi nodes with constant expressions that can trap are not safe to if
3426/// convert.
3427static bool canIfConvertPHINodes(BasicBlock *BB) {
3428  for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I) {
3429    PHINode *Phi = dyn_cast<PHINode>(I);
3430    if (!Phi)
3431      return true;
3432    for (unsigned p = 0, e = Phi->getNumIncomingValues(); p != e; ++p)
3433      if (Constant *C = dyn_cast<Constant>(Phi->getIncomingValue(p)))
3434        if (C->canTrap())
3435          return false;
3436  }
3437  return true;
3438}
3439
3440bool LoopVectorizationLegality::canVectorizeWithIfConvert() {
3441  if (!EnableIfConversion) {
3442    emitAnalysis(VectorizationReport() << "if-conversion is disabled");
3443    return false;
3444  }
3445
3446  assert(TheLoop->getNumBlocks() > 1 && "Single block loops are vectorizable");
3447
3448  // A list of pointers that we can safely read and write to.
3449  SmallPtrSet<Value *, 8> SafePointes;
3450
3451  // Collect safe addresses.
3452  for (Loop::block_iterator BI = TheLoop->block_begin(),
3453         BE = TheLoop->block_end(); BI != BE; ++BI) {
3454    BasicBlock *BB = *BI;
3455
3456    if (blockNeedsPredication(BB))
3457      continue;
3458
3459    for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I) {
3460      if (LoadInst *LI = dyn_cast<LoadInst>(I))
3461        SafePointes.insert(LI->getPointerOperand());
3462      else if (StoreInst *SI = dyn_cast<StoreInst>(I))
3463        SafePointes.insert(SI->getPointerOperand());
3464    }
3465  }
3466
3467  // Collect the blocks that need predication.
3468  BasicBlock *Header = TheLoop->getHeader();
3469  for (Loop::block_iterator BI = TheLoop->block_begin(),
3470         BE = TheLoop->block_end(); BI != BE; ++BI) {
3471    BasicBlock *BB = *BI;
3472
3473    // We don't support switch statements inside loops.
3474    if (!isa<BranchInst>(BB->getTerminator())) {
3475      emitAnalysis(VectorizationReport(BB->getTerminator())
3476                   << "loop contains a switch statement");
3477      return false;
3478    }
3479
3480    // We must be able to predicate all blocks that need to be predicated.
3481    if (blockNeedsPredication(BB)) {
3482      if (!blockCanBePredicated(BB, SafePointes)) {
3483        emitAnalysis(VectorizationReport(BB->getTerminator())
3484                     << "control flow cannot be substituted for a select");
3485        return false;
3486      }
3487    } else if (BB != Header && !canIfConvertPHINodes(BB)) {
3488      emitAnalysis(VectorizationReport(BB->getTerminator())
3489                   << "control flow cannot be substituted for a select");
3490      return false;
3491    }
3492  }
3493
3494  // We can if-convert this loop.
3495  return true;
3496}
3497
3498bool LoopVectorizationLegality::canVectorize() {
3499  // We must have a loop in canonical form. Loops with indirectbr in them cannot
3500  // be canonicalized.
3501  if (!TheLoop->getLoopPreheader()) {
3502    emitAnalysis(
3503        VectorizationReport() <<
3504        "loop control flow is not understood by vectorizer");
3505    return false;
3506  }
3507
3508  // We can only vectorize innermost loops.
3509  if (!TheLoop->getSubLoopsVector().empty()) {
3510    emitAnalysis(VectorizationReport() << "loop is not the innermost loop");
3511    return false;
3512  }
3513
3514  // We must have a single backedge.
3515  if (TheLoop->getNumBackEdges() != 1) {
3516    emitAnalysis(
3517        VectorizationReport() <<
3518        "loop control flow is not understood by vectorizer");
3519    return false;
3520  }
3521
3522  // We must have a single exiting block.
3523  if (!TheLoop->getExitingBlock()) {
3524    emitAnalysis(
3525        VectorizationReport() <<
3526        "loop control flow is not understood by vectorizer");
3527    return false;
3528  }
3529
3530  // We only handle bottom-tested loops, i.e. loop in which the condition is
3531  // checked at the end of each iteration. With that we can assume that all
3532  // instructions in the loop are executed the same number of times.
3533  if (TheLoop->getExitingBlock() != TheLoop->getLoopLatch()) {
3534    emitAnalysis(
3535        VectorizationReport() <<
3536        "loop control flow is not understood by vectorizer");
3537    return false;
3538  }
3539
3540  // We need to have a loop header.
3541  DEBUG(dbgs() << "LV: Found a loop: " <<
3542        TheLoop->getHeader()->getName() << '\n');
3543
3544  // Check if we can if-convert non-single-bb loops.
3545  unsigned NumBlocks = TheLoop->getNumBlocks();
3546  if (NumBlocks != 1 && !canVectorizeWithIfConvert()) {
3547    DEBUG(dbgs() << "LV: Can't if-convert the loop.\n");
3548    return false;
3549  }
3550
3551  // ScalarEvolution needs to be able to find the exit count.
3552  const SCEV *ExitCount = SE->getBackedgeTakenCount(TheLoop);
3553  if (ExitCount == SE->getCouldNotCompute()) {
3554    emitAnalysis(VectorizationReport() <<
3555                 "could not determine number of loop iterations");
3556    DEBUG(dbgs() << "LV: SCEV could not compute the loop exit count.\n");
3557    return false;
3558  }
3559
3560  // Check if we can vectorize the instructions and CFG in this loop.
3561  if (!canVectorizeInstrs()) {
3562    DEBUG(dbgs() << "LV: Can't vectorize the instructions or CFG\n");
3563    return false;
3564  }
3565
3566  // Go over each instruction and look at memory deps.
3567  if (!canVectorizeMemory()) {
3568    DEBUG(dbgs() << "LV: Can't vectorize due to memory conflicts\n");
3569    return false;
3570  }
3571
3572  // Collect all of the variables that remain uniform after vectorization.
3573  collectLoopUniforms();
3574
3575  DEBUG(dbgs() << "LV: We can vectorize this loop" <<
3576        (LAI->getRuntimePointerCheck()->Need ? " (with a runtime bound check)" :
3577         "")
3578        <<"!\n");
3579
3580  // Okay! We can vectorize. At this point we don't have any other mem analysis
3581  // which may limit our maximum vectorization factor, so just return true with
3582  // no restrictions.
3583  return true;
3584}
3585
3586static Type *convertPointerToIntegerType(const DataLayout &DL, Type *Ty) {
3587  if (Ty->isPointerTy())
3588    return DL.getIntPtrType(Ty);
3589
3590  // It is possible that char's or short's overflow when we ask for the loop's
3591  // trip count, work around this by changing the type size.
3592  if (Ty->getScalarSizeInBits() < 32)
3593    return Type::getInt32Ty(Ty->getContext());
3594
3595  return Ty;
3596}
3597
3598static Type* getWiderType(const DataLayout &DL, Type *Ty0, Type *Ty1) {
3599  Ty0 = convertPointerToIntegerType(DL, Ty0);
3600  Ty1 = convertPointerToIntegerType(DL, Ty1);
3601  if (Ty0->getScalarSizeInBits() > Ty1->getScalarSizeInBits())
3602    return Ty0;
3603  return Ty1;
3604}
3605
3606/// \brief Check that the instruction has outside loop users and is not an
3607/// identified reduction variable.
3608static bool hasOutsideLoopUser(const Loop *TheLoop, Instruction *Inst,
3609                               SmallPtrSetImpl<Value *> &Reductions) {
3610  // Reduction instructions are allowed to have exit users. All other
3611  // instructions must not have external users.
3612  if (!Reductions.count(Inst))
3613    //Check that all of the users of the loop are inside the BB.
3614    for (User *U : Inst->users()) {
3615      Instruction *UI = cast<Instruction>(U);
3616      // This user may be a reduction exit value.
3617      if (!TheLoop->contains(UI)) {
3618        DEBUG(dbgs() << "LV: Found an outside user for : " << *UI << '\n');
3619        return true;
3620      }
3621    }
3622  return false;
3623}
3624
3625bool LoopVectorizationLegality::canVectorizeInstrs() {
3626  BasicBlock *PreHeader = TheLoop->getLoopPreheader();
3627  BasicBlock *Header = TheLoop->getHeader();
3628
3629  // Look for the attribute signaling the absence of NaNs.
3630  Function &F = *Header->getParent();
3631  const DataLayout &DL = F.getParent()->getDataLayout();
3632  if (F.hasFnAttribute("no-nans-fp-math"))
3633    HasFunNoNaNAttr =
3634        F.getFnAttribute("no-nans-fp-math").getValueAsString() == "true";
3635
3636  // For each block in the loop.
3637  for (Loop::block_iterator bb = TheLoop->block_begin(),
3638       be = TheLoop->block_end(); bb != be; ++bb) {
3639
3640    // Scan the instructions in the block and look for hazards.
3641    for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e;
3642         ++it) {
3643
3644      if (PHINode *Phi = dyn_cast<PHINode>(it)) {
3645        Type *PhiTy = Phi->getType();
3646        // Check that this PHI type is allowed.
3647        if (!PhiTy->isIntegerTy() &&
3648            !PhiTy->isFloatingPointTy() &&
3649            !PhiTy->isPointerTy()) {
3650          emitAnalysis(VectorizationReport(it)
3651                       << "loop control flow is not understood by vectorizer");
3652          DEBUG(dbgs() << "LV: Found an non-int non-pointer PHI.\n");
3653          return false;
3654        }
3655
3656        // If this PHINode is not in the header block, then we know that we
3657        // can convert it to select during if-conversion. No need to check if
3658        // the PHIs in this block are induction or reduction variables.
3659        if (*bb != Header) {
3660          // Check that this instruction has no outside users or is an
3661          // identified reduction value with an outside user.
3662          if (!hasOutsideLoopUser(TheLoop, it, AllowedExit))
3663            continue;
3664          emitAnalysis(VectorizationReport(it) <<
3665                       "value could not be identified as "
3666                       "an induction or reduction variable");
3667          return false;
3668        }
3669
3670        // We only allow if-converted PHIs with exactly two incoming values.
3671        if (Phi->getNumIncomingValues() != 2) {
3672          emitAnalysis(VectorizationReport(it)
3673                       << "control flow not understood by vectorizer");
3674          DEBUG(dbgs() << "LV: Found an invalid PHI.\n");
3675          return false;
3676        }
3677
3678        // This is the value coming from the preheader.
3679        Value *StartValue = Phi->getIncomingValueForBlock(PreHeader);
3680        ConstantInt *StepValue = nullptr;
3681        // Check if this is an induction variable.
3682        InductionKind IK = isInductionVariable(Phi, StepValue);
3683
3684        if (IK_NoInduction != IK) {
3685          // Get the widest type.
3686          if (!WidestIndTy)
3687            WidestIndTy = convertPointerToIntegerType(DL, PhiTy);
3688          else
3689            WidestIndTy = getWiderType(DL, PhiTy, WidestIndTy);
3690
3691          // Int inductions are special because we only allow one IV.
3692          if (IK == IK_IntInduction && StepValue->isOne()) {
3693            // Use the phi node with the widest type as induction. Use the last
3694            // one if there are multiple (no good reason for doing this other
3695            // than it is expedient).
3696            if (!Induction || PhiTy == WidestIndTy)
3697              Induction = Phi;
3698          }
3699
3700          DEBUG(dbgs() << "LV: Found an induction variable.\n");
3701          Inductions[Phi] = InductionInfo(StartValue, IK, StepValue);
3702
3703          // Until we explicitly handle the case of an induction variable with
3704          // an outside loop user we have to give up vectorizing this loop.
3705          if (hasOutsideLoopUser(TheLoop, it, AllowedExit)) {
3706            emitAnalysis(VectorizationReport(it) <<
3707                         "use of induction value outside of the "
3708                         "loop is not handled by vectorizer");
3709            return false;
3710          }
3711
3712          continue;
3713        }
3714
3715        if (AddReductionVar(Phi, RK_IntegerAdd)) {
3716          DEBUG(dbgs() << "LV: Found an ADD reduction PHI."<< *Phi <<"\n");
3717          continue;
3718        }
3719        if (AddReductionVar(Phi, RK_IntegerMult)) {
3720          DEBUG(dbgs() << "LV: Found a MUL reduction PHI."<< *Phi <<"\n");
3721          continue;
3722        }
3723        if (AddReductionVar(Phi, RK_IntegerOr)) {
3724          DEBUG(dbgs() << "LV: Found an OR reduction PHI."<< *Phi <<"\n");
3725          continue;
3726        }
3727        if (AddReductionVar(Phi, RK_IntegerAnd)) {
3728          DEBUG(dbgs() << "LV: Found an AND reduction PHI."<< *Phi <<"\n");
3729          continue;
3730        }
3731        if (AddReductionVar(Phi, RK_IntegerXor)) {
3732          DEBUG(dbgs() << "LV: Found a XOR reduction PHI."<< *Phi <<"\n");
3733          continue;
3734        }
3735        if (AddReductionVar(Phi, RK_IntegerMinMax)) {
3736          DEBUG(dbgs() << "LV: Found a MINMAX reduction PHI."<< *Phi <<"\n");
3737          continue;
3738        }
3739        if (AddReductionVar(Phi, RK_FloatMult)) {
3740          DEBUG(dbgs() << "LV: Found an FMult reduction PHI."<< *Phi <<"\n");
3741          continue;
3742        }
3743        if (AddReductionVar(Phi, RK_FloatAdd)) {
3744          DEBUG(dbgs() << "LV: Found an FAdd reduction PHI."<< *Phi <<"\n");
3745          continue;
3746        }
3747        if (AddReductionVar(Phi, RK_FloatMinMax)) {
3748          DEBUG(dbgs() << "LV: Found an float MINMAX reduction PHI."<< *Phi <<
3749                "\n");
3750          continue;
3751        }
3752
3753        emitAnalysis(VectorizationReport(it) <<
3754                     "value that could not be identified as "
3755                     "reduction is used outside the loop");
3756        DEBUG(dbgs() << "LV: Found an unidentified PHI."<< *Phi <<"\n");
3757        return false;
3758      }// end of PHI handling
3759
3760      // We handle calls that:
3761      //   * Are debug info intrinsics.
3762      //   * Have a mapping to an IR intrinsic.
3763      //   * Have a vector version available.
3764      CallInst *CI = dyn_cast<CallInst>(it);
3765      if (CI && !getIntrinsicIDForCall(CI, TLI) && !isa<DbgInfoIntrinsic>(CI) &&
3766          !(CI->getCalledFunction() && TLI &&
3767            TLI->isFunctionVectorizable(CI->getCalledFunction()->getName()))) {
3768        emitAnalysis(VectorizationReport(it) <<
3769                     "call instruction cannot be vectorized");
3770        DEBUG(dbgs() << "LV: Found a non-intrinsic, non-libfunc callsite.\n");
3771        return false;
3772      }
3773
3774      // Intrinsics such as powi,cttz and ctlz are legal to vectorize if the
3775      // second argument is the same (i.e. loop invariant)
3776      if (CI &&
3777          hasVectorInstrinsicScalarOpd(getIntrinsicIDForCall(CI, TLI), 1)) {
3778        if (!SE->isLoopInvariant(SE->getSCEV(CI->getOperand(1)), TheLoop)) {
3779          emitAnalysis(VectorizationReport(it)
3780                       << "intrinsic instruction cannot be vectorized");
3781          DEBUG(dbgs() << "LV: Found unvectorizable intrinsic " << *CI << "\n");
3782          return false;
3783        }
3784      }
3785
3786      // Check that the instruction return type is vectorizable.
3787      // Also, we can't vectorize extractelement instructions.
3788      if ((!VectorType::isValidElementType(it->getType()) &&
3789           !it->getType()->isVoidTy()) || isa<ExtractElementInst>(it)) {
3790        emitAnalysis(VectorizationReport(it)
3791                     << "instruction return type cannot be vectorized");
3792        DEBUG(dbgs() << "LV: Found unvectorizable type.\n");
3793        return false;
3794      }
3795
3796      // Check that the stored type is vectorizable.
3797      if (StoreInst *ST = dyn_cast<StoreInst>(it)) {
3798        Type *T = ST->getValueOperand()->getType();
3799        if (!VectorType::isValidElementType(T)) {
3800          emitAnalysis(VectorizationReport(ST) <<
3801                       "store instruction cannot be vectorized");
3802          return false;
3803        }
3804        if (EnableMemAccessVersioning)
3805          collectStridedAccess(ST);
3806      }
3807
3808      if (EnableMemAccessVersioning)
3809        if (LoadInst *LI = dyn_cast<LoadInst>(it))
3810          collectStridedAccess(LI);
3811
3812      // Reduction instructions are allowed to have exit users.
3813      // All other instructions must not have external users.
3814      if (hasOutsideLoopUser(TheLoop, it, AllowedExit)) {
3815        emitAnalysis(VectorizationReport(it) <<
3816                     "value cannot be used outside the loop");
3817        return false;
3818      }
3819
3820    } // next instr.
3821
3822  }
3823
3824  if (!Induction) {
3825    DEBUG(dbgs() << "LV: Did not find one integer induction var.\n");
3826    if (Inductions.empty()) {
3827      emitAnalysis(VectorizationReport()
3828                   << "loop induction variable could not be identified");
3829      return false;
3830    }
3831  }
3832
3833  return true;
3834}
3835
3836///\brief Remove GEPs whose indices but the last one are loop invariant and
3837/// return the induction operand of the gep pointer.
3838static Value *stripGetElementPtr(Value *Ptr, ScalarEvolution *SE, Loop *Lp) {
3839  GetElementPtrInst *GEP = dyn_cast<GetElementPtrInst>(Ptr);
3840  if (!GEP)
3841    return Ptr;
3842
3843  unsigned InductionOperand = getGEPInductionOperand(GEP);
3844
3845  // Check that all of the gep indices are uniform except for our induction
3846  // operand.
3847  for (unsigned i = 0, e = GEP->getNumOperands(); i != e; ++i)
3848    if (i != InductionOperand &&
3849        !SE->isLoopInvariant(SE->getSCEV(GEP->getOperand(i)), Lp))
3850      return Ptr;
3851  return GEP->getOperand(InductionOperand);
3852}
3853
3854///\brief Look for a cast use of the passed value.
3855static Value *getUniqueCastUse(Value *Ptr, Loop *Lp, Type *Ty) {
3856  Value *UniqueCast = nullptr;
3857  for (User *U : Ptr->users()) {
3858    CastInst *CI = dyn_cast<CastInst>(U);
3859    if (CI && CI->getType() == Ty) {
3860      if (!UniqueCast)
3861        UniqueCast = CI;
3862      else
3863        return nullptr;
3864    }
3865  }
3866  return UniqueCast;
3867}
3868
3869///\brief Get the stride of a pointer access in a loop.
3870/// Looks for symbolic strides "a[i*stride]". Returns the symbolic stride as a
3871/// pointer to the Value, or null otherwise.
3872static Value *getStrideFromPointer(Value *Ptr, ScalarEvolution *SE, Loop *Lp) {
3873  const PointerType *PtrTy = dyn_cast<PointerType>(Ptr->getType());
3874  if (!PtrTy || PtrTy->isAggregateType())
3875    return nullptr;
3876
3877  // Try to remove a gep instruction to make the pointer (actually index at this
3878  // point) easier analyzable. If OrigPtr is equal to Ptr we are analzying the
3879  // pointer, otherwise, we are analyzing the index.
3880  Value *OrigPtr = Ptr;
3881
3882  // The size of the pointer access.
3883  int64_t PtrAccessSize = 1;
3884
3885  Ptr = stripGetElementPtr(Ptr, SE, Lp);
3886  const SCEV *V = SE->getSCEV(Ptr);
3887
3888  if (Ptr != OrigPtr)
3889    // Strip off casts.
3890    while (const SCEVCastExpr *C = dyn_cast<SCEVCastExpr>(V))
3891      V = C->getOperand();
3892
3893  const SCEVAddRecExpr *S = dyn_cast<SCEVAddRecExpr>(V);
3894  if (!S)
3895    return nullptr;
3896
3897  V = S->getStepRecurrence(*SE);
3898  if (!V)
3899    return nullptr;
3900
3901  // Strip off the size of access multiplication if we are still analyzing the
3902  // pointer.
3903  if (OrigPtr == Ptr) {
3904    const DataLayout &DL = Lp->getHeader()->getModule()->getDataLayout();
3905    DL.getTypeAllocSize(PtrTy->getElementType());
3906    if (const SCEVMulExpr *M = dyn_cast<SCEVMulExpr>(V)) {
3907      if (M->getOperand(0)->getSCEVType() != scConstant)
3908        return nullptr;
3909
3910      const APInt &APStepVal =
3911          cast<SCEVConstant>(M->getOperand(0))->getValue()->getValue();
3912
3913      // Huge step value - give up.
3914      if (APStepVal.getBitWidth() > 64)
3915        return nullptr;
3916
3917      int64_t StepVal = APStepVal.getSExtValue();
3918      if (PtrAccessSize != StepVal)
3919        return nullptr;
3920      V = M->getOperand(1);
3921    }
3922  }
3923
3924  // Strip off casts.
3925  Type *StripedOffRecurrenceCast = nullptr;
3926  if (const SCEVCastExpr *C = dyn_cast<SCEVCastExpr>(V)) {
3927    StripedOffRecurrenceCast = C->getType();
3928    V = C->getOperand();
3929  }
3930
3931  // Look for the loop invariant symbolic value.
3932  const SCEVUnknown *U = dyn_cast<SCEVUnknown>(V);
3933  if (!U)
3934    return nullptr;
3935
3936  Value *Stride = U->getValue();
3937  if (!Lp->isLoopInvariant(Stride))
3938    return nullptr;
3939
3940  // If we have stripped off the recurrence cast we have to make sure that we
3941  // return the value that is used in this loop so that we can replace it later.
3942  if (StripedOffRecurrenceCast)
3943    Stride = getUniqueCastUse(Stride, Lp, StripedOffRecurrenceCast);
3944
3945  return Stride;
3946}
3947
3948void LoopVectorizationLegality::collectStridedAccess(Value *MemAccess) {
3949  Value *Ptr = nullptr;
3950  if (LoadInst *LI = dyn_cast<LoadInst>(MemAccess))
3951    Ptr = LI->getPointerOperand();
3952  else if (StoreInst *SI = dyn_cast<StoreInst>(MemAccess))
3953    Ptr = SI->getPointerOperand();
3954  else
3955    return;
3956
3957  Value *Stride = getStrideFromPointer(Ptr, SE, TheLoop);
3958  if (!Stride)
3959    return;
3960
3961  DEBUG(dbgs() << "LV: Found a strided access that we can version");
3962  DEBUG(dbgs() << "  Ptr: " << *Ptr << " Stride: " << *Stride << "\n");
3963  Strides[Ptr] = Stride;
3964  StrideSet.insert(Stride);
3965}
3966
3967void LoopVectorizationLegality::collectLoopUniforms() {
3968  // We now know that the loop is vectorizable!
3969  // Collect variables that will remain uniform after vectorization.
3970  std::vector<Value*> Worklist;
3971  BasicBlock *Latch = TheLoop->getLoopLatch();
3972
3973  // Start with the conditional branch and walk up the block.
3974  Worklist.push_back(Latch->getTerminator()->getOperand(0));
3975
3976  // Also add all consecutive pointer values; these values will be uniform
3977  // after vectorization (and subsequent cleanup) and, until revectorization is
3978  // supported, all dependencies must also be uniform.
3979  for (Loop::block_iterator B = TheLoop->block_begin(),
3980       BE = TheLoop->block_end(); B != BE; ++B)
3981    for (BasicBlock::iterator I = (*B)->begin(), IE = (*B)->end();
3982         I != IE; ++I)
3983      if (I->getType()->isPointerTy() && isConsecutivePtr(I))
3984        Worklist.insert(Worklist.end(), I->op_begin(), I->op_end());
3985
3986  while (!Worklist.empty()) {
3987    Instruction *I = dyn_cast<Instruction>(Worklist.back());
3988    Worklist.pop_back();
3989
3990    // Look at instructions inside this loop.
3991    // Stop when reaching PHI nodes.
3992    // TODO: we need to follow values all over the loop, not only in this block.
3993    if (!I || !TheLoop->contains(I) || isa<PHINode>(I))
3994      continue;
3995
3996    // This is a known uniform.
3997    Uniforms.insert(I);
3998
3999    // Insert all operands.
4000    Worklist.insert(Worklist.end(), I->op_begin(), I->op_end());
4001  }
4002}
4003
4004bool LoopVectorizationLegality::canVectorizeMemory() {
4005  LAI = &LAA->getInfo(TheLoop, Strides);
4006  auto &OptionalReport = LAI->getReport();
4007  if (OptionalReport)
4008    emitAnalysis(VectorizationReport(*OptionalReport));
4009  if (!LAI->canVectorizeMemory())
4010    return false;
4011
4012  if (LAI->hasStoreToLoopInvariantAddress()) {
4013    emitAnalysis(
4014        VectorizationReport()
4015        << "write to a loop invariant address could not be vectorized");
4016    DEBUG(dbgs() << "LV: We don't allow storing to uniform addresses\n");
4017    return false;
4018  }
4019
4020  if (LAI->getNumRuntimePointerChecks() >
4021      VectorizerParams::RuntimeMemoryCheckThreshold) {
4022    emitAnalysis(VectorizationReport()
4023                 << LAI->getNumRuntimePointerChecks() << " exceeds limit of "
4024                 << VectorizerParams::RuntimeMemoryCheckThreshold
4025                 << " dependent memory operations checked at runtime");
4026    DEBUG(dbgs() << "LV: Too many memory checks needed.\n");
4027    return false;
4028  }
4029  return true;
4030}
4031
4032static bool hasMultipleUsesOf(Instruction *I,
4033                              SmallPtrSetImpl<Instruction *> &Insts) {
4034  unsigned NumUses = 0;
4035  for(User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E; ++Use) {
4036    if (Insts.count(dyn_cast<Instruction>(*Use)))
4037      ++NumUses;
4038    if (NumUses > 1)
4039      return true;
4040  }
4041
4042  return false;
4043}
4044
4045static bool areAllUsesIn(Instruction *I, SmallPtrSetImpl<Instruction *> &Set) {
4046  for(User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E; ++Use)
4047    if (!Set.count(dyn_cast<Instruction>(*Use)))
4048      return false;
4049  return true;
4050}
4051
4052bool LoopVectorizationLegality::AddReductionVar(PHINode *Phi,
4053                                                ReductionKind Kind) {
4054  if (Phi->getNumIncomingValues() != 2)
4055    return false;
4056
4057  // Reduction variables are only found in the loop header block.
4058  if (Phi->getParent() != TheLoop->getHeader())
4059    return false;
4060
4061  // Obtain the reduction start value from the value that comes from the loop
4062  // preheader.
4063  Value *RdxStart = Phi->getIncomingValueForBlock(TheLoop->getLoopPreheader());
4064
4065  // ExitInstruction is the single value which is used outside the loop.
4066  // We only allow for a single reduction value to be used outside the loop.
4067  // This includes users of the reduction, variables (which form a cycle
4068  // which ends in the phi node).
4069  Instruction *ExitInstruction = nullptr;
4070  // Indicates that we found a reduction operation in our scan.
4071  bool FoundReduxOp = false;
4072
4073  // We start with the PHI node and scan for all of the users of this
4074  // instruction. All users must be instructions that can be used as reduction
4075  // variables (such as ADD). We must have a single out-of-block user. The cycle
4076  // must include the original PHI.
4077  bool FoundStartPHI = false;
4078
4079  // To recognize min/max patterns formed by a icmp select sequence, we store
4080  // the number of instruction we saw from the recognized min/max pattern,
4081  //  to make sure we only see exactly the two instructions.
4082  unsigned NumCmpSelectPatternInst = 0;
4083  ReductionInstDesc ReduxDesc(false, nullptr);
4084
4085  SmallPtrSet<Instruction *, 8> VisitedInsts;
4086  SmallVector<Instruction *, 8> Worklist;
4087  Worklist.push_back(Phi);
4088  VisitedInsts.insert(Phi);
4089
4090  // A value in the reduction can be used:
4091  //  - By the reduction:
4092  //      - Reduction operation:
4093  //        - One use of reduction value (safe).
4094  //        - Multiple use of reduction value (not safe).
4095  //      - PHI:
4096  //        - All uses of the PHI must be the reduction (safe).
4097  //        - Otherwise, not safe.
4098  //  - By one instruction outside of the loop (safe).
4099  //  - By further instructions outside of the loop (not safe).
4100  //  - By an instruction that is not part of the reduction (not safe).
4101  //    This is either:
4102  //      * An instruction type other than PHI or the reduction operation.
4103  //      * A PHI in the header other than the initial PHI.
4104  while (!Worklist.empty()) {
4105    Instruction *Cur = Worklist.back();
4106    Worklist.pop_back();
4107
4108    // No Users.
4109    // If the instruction has no users then this is a broken chain and can't be
4110    // a reduction variable.
4111    if (Cur->use_empty())
4112      return false;
4113
4114    bool IsAPhi = isa<PHINode>(Cur);
4115
4116    // A header PHI use other than the original PHI.
4117    if (Cur != Phi && IsAPhi && Cur->getParent() == Phi->getParent())
4118      return false;
4119
4120    // Reductions of instructions such as Div, and Sub is only possible if the
4121    // LHS is the reduction variable.
4122    if (!Cur->isCommutative() && !IsAPhi && !isa<SelectInst>(Cur) &&
4123        !isa<ICmpInst>(Cur) && !isa<FCmpInst>(Cur) &&
4124        !VisitedInsts.count(dyn_cast<Instruction>(Cur->getOperand(0))))
4125      return false;
4126
4127    // Any reduction instruction must be of one of the allowed kinds.
4128    ReduxDesc = isReductionInstr(Cur, Kind, ReduxDesc);
4129    if (!ReduxDesc.IsReduction)
4130      return false;
4131
4132    // A reduction operation must only have one use of the reduction value.
4133    if (!IsAPhi && Kind != RK_IntegerMinMax && Kind != RK_FloatMinMax &&
4134        hasMultipleUsesOf(Cur, VisitedInsts))
4135      return false;
4136
4137    // All inputs to a PHI node must be a reduction value.
4138    if(IsAPhi && Cur != Phi && !areAllUsesIn(Cur, VisitedInsts))
4139      return false;
4140
4141    if (Kind == RK_IntegerMinMax && (isa<ICmpInst>(Cur) ||
4142                                     isa<SelectInst>(Cur)))
4143      ++NumCmpSelectPatternInst;
4144    if (Kind == RK_FloatMinMax && (isa<FCmpInst>(Cur) ||
4145                                   isa<SelectInst>(Cur)))
4146      ++NumCmpSelectPatternInst;
4147
4148    // Check  whether we found a reduction operator.
4149    FoundReduxOp |= !IsAPhi;
4150
4151    // Process users of current instruction. Push non-PHI nodes after PHI nodes
4152    // onto the stack. This way we are going to have seen all inputs to PHI
4153    // nodes once we get to them.
4154    SmallVector<Instruction *, 8> NonPHIs;
4155    SmallVector<Instruction *, 8> PHIs;
4156    for (User *U : Cur->users()) {
4157      Instruction *UI = cast<Instruction>(U);
4158
4159      // Check if we found the exit user.
4160      BasicBlock *Parent = UI->getParent();
4161      if (!TheLoop->contains(Parent)) {
4162        // Exit if you find multiple outside users or if the header phi node is
4163        // being used. In this case the user uses the value of the previous
4164        // iteration, in which case we would loose "VF-1" iterations of the
4165        // reduction operation if we vectorize.
4166        if (ExitInstruction != nullptr || Cur == Phi)
4167          return false;
4168
4169        // The instruction used by an outside user must be the last instruction
4170        // before we feed back to the reduction phi. Otherwise, we loose VF-1
4171        // operations on the value.
4172        if (std::find(Phi->op_begin(), Phi->op_end(), Cur) == Phi->op_end())
4173         return false;
4174
4175        ExitInstruction = Cur;
4176        continue;
4177      }
4178
4179      // Process instructions only once (termination). Each reduction cycle
4180      // value must only be used once, except by phi nodes and min/max
4181      // reductions which are represented as a cmp followed by a select.
4182      ReductionInstDesc IgnoredVal(false, nullptr);
4183      if (VisitedInsts.insert(UI).second) {
4184        if (isa<PHINode>(UI))
4185          PHIs.push_back(UI);
4186        else
4187          NonPHIs.push_back(UI);
4188      } else if (!isa<PHINode>(UI) &&
4189                 ((!isa<FCmpInst>(UI) &&
4190                   !isa<ICmpInst>(UI) &&
4191                   !isa<SelectInst>(UI)) ||
4192                  !isMinMaxSelectCmpPattern(UI, IgnoredVal).IsReduction))
4193        return false;
4194
4195      // Remember that we completed the cycle.
4196      if (UI == Phi)
4197        FoundStartPHI = true;
4198    }
4199    Worklist.append(PHIs.begin(), PHIs.end());
4200    Worklist.append(NonPHIs.begin(), NonPHIs.end());
4201  }
4202
4203  // This means we have seen one but not the other instruction of the
4204  // pattern or more than just a select and cmp.
4205  if ((Kind == RK_IntegerMinMax || Kind == RK_FloatMinMax) &&
4206      NumCmpSelectPatternInst != 2)
4207    return false;
4208
4209  if (!FoundStartPHI || !FoundReduxOp || !ExitInstruction)
4210    return false;
4211
4212  // We found a reduction var if we have reached the original phi node and we
4213  // only have a single instruction with out-of-loop users.
4214
4215  // This instruction is allowed to have out-of-loop users.
4216  AllowedExit.insert(ExitInstruction);
4217
4218  // Save the description of this reduction variable.
4219  ReductionDescriptor RD(RdxStart, ExitInstruction, Kind,
4220                         ReduxDesc.MinMaxKind);
4221  Reductions[Phi] = RD;
4222  // We've ended the cycle. This is a reduction variable if we have an
4223  // outside user and it has a binary op.
4224
4225  return true;
4226}
4227
4228/// Returns true if the instruction is a Select(ICmp(X, Y), X, Y) instruction
4229/// pattern corresponding to a min(X, Y) or max(X, Y).
4230LoopVectorizationLegality::ReductionInstDesc
4231LoopVectorizationLegality::isMinMaxSelectCmpPattern(Instruction *I,
4232                                                    ReductionInstDesc &Prev) {
4233
4234  assert((isa<ICmpInst>(I) || isa<FCmpInst>(I) || isa<SelectInst>(I)) &&
4235         "Expect a select instruction");
4236  Instruction *Cmp = nullptr;
4237  SelectInst *Select = nullptr;
4238
4239  // We must handle the select(cmp()) as a single instruction. Advance to the
4240  // select.
4241  if ((Cmp = dyn_cast<ICmpInst>(I)) || (Cmp = dyn_cast<FCmpInst>(I))) {
4242    if (!Cmp->hasOneUse() || !(Select = dyn_cast<SelectInst>(*I->user_begin())))
4243      return ReductionInstDesc(false, I);
4244    return ReductionInstDesc(Select, Prev.MinMaxKind);
4245  }
4246
4247  // Only handle single use cases for now.
4248  if (!(Select = dyn_cast<SelectInst>(I)))
4249    return ReductionInstDesc(false, I);
4250  if (!(Cmp = dyn_cast<ICmpInst>(I->getOperand(0))) &&
4251      !(Cmp = dyn_cast<FCmpInst>(I->getOperand(0))))
4252    return ReductionInstDesc(false, I);
4253  if (!Cmp->hasOneUse())
4254    return ReductionInstDesc(false, I);
4255
4256  Value *CmpLeft;
4257  Value *CmpRight;
4258
4259  // Look for a min/max pattern.
4260  if (m_UMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
4261    return ReductionInstDesc(Select, MRK_UIntMin);
4262  else if (m_UMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
4263    return ReductionInstDesc(Select, MRK_UIntMax);
4264  else if (m_SMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
4265    return ReductionInstDesc(Select, MRK_SIntMax);
4266  else if (m_SMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
4267    return ReductionInstDesc(Select, MRK_SIntMin);
4268  else if (m_OrdFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
4269    return ReductionInstDesc(Select, MRK_FloatMin);
4270  else if (m_OrdFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
4271    return ReductionInstDesc(Select, MRK_FloatMax);
4272  else if (m_UnordFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
4273    return ReductionInstDesc(Select, MRK_FloatMin);
4274  else if (m_UnordFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
4275    return ReductionInstDesc(Select, MRK_FloatMax);
4276
4277  return ReductionInstDesc(false, I);
4278}
4279
4280LoopVectorizationLegality::ReductionInstDesc
4281LoopVectorizationLegality::isReductionInstr(Instruction *I,
4282                                            ReductionKind Kind,
4283                                            ReductionInstDesc &Prev) {
4284  bool FP = I->getType()->isFloatingPointTy();
4285  bool FastMath = FP && I->hasUnsafeAlgebra();
4286  switch (I->getOpcode()) {
4287  default:
4288    return ReductionInstDesc(false, I);
4289  case Instruction::PHI:
4290      if (FP && (Kind != RK_FloatMult && Kind != RK_FloatAdd &&
4291                 Kind != RK_FloatMinMax))
4292        return ReductionInstDesc(false, I);
4293    return ReductionInstDesc(I, Prev.MinMaxKind);
4294  case Instruction::Sub:
4295  case Instruction::Add:
4296    return ReductionInstDesc(Kind == RK_IntegerAdd, I);
4297  case Instruction::Mul:
4298    return ReductionInstDesc(Kind == RK_IntegerMult, I);
4299  case Instruction::And:
4300    return ReductionInstDesc(Kind == RK_IntegerAnd, I);
4301  case Instruction::Or:
4302    return ReductionInstDesc(Kind == RK_IntegerOr, I);
4303  case Instruction::Xor:
4304    return ReductionInstDesc(Kind == RK_IntegerXor, I);
4305  case Instruction::FMul:
4306    return ReductionInstDesc(Kind == RK_FloatMult && FastMath, I);
4307  case Instruction::FSub:
4308  case Instruction::FAdd:
4309    return ReductionInstDesc(Kind == RK_FloatAdd && FastMath, I);
4310  case Instruction::FCmp:
4311  case Instruction::ICmp:
4312  case Instruction::Select:
4313    if (Kind != RK_IntegerMinMax &&
4314        (!HasFunNoNaNAttr || Kind != RK_FloatMinMax))
4315      return ReductionInstDesc(false, I);
4316    return isMinMaxSelectCmpPattern(I, Prev);
4317  }
4318}
4319
4320bool llvm::isInductionPHI(PHINode *Phi, ScalarEvolution *SE,
4321                          ConstantInt *&StepValue) {
4322  Type *PhiTy = Phi->getType();
4323  // We only handle integer and pointer inductions variables.
4324  if (!PhiTy->isIntegerTy() && !PhiTy->isPointerTy())
4325    return false;
4326
4327  // Check that the PHI is consecutive.
4328  const SCEV *PhiScev = SE->getSCEV(Phi);
4329  const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PhiScev);
4330  if (!AR) {
4331    DEBUG(dbgs() << "LV: PHI is not a poly recurrence.\n");
4332    return false;
4333  }
4334
4335  const SCEV *Step = AR->getStepRecurrence(*SE);
4336  // Calculate the pointer stride and check if it is consecutive.
4337  const SCEVConstant *C = dyn_cast<SCEVConstant>(Step);
4338  if (!C)
4339    return false;
4340
4341  ConstantInt *CV = C->getValue();
4342  if (PhiTy->isIntegerTy()) {
4343    StepValue = CV;
4344    return true;
4345  }
4346
4347  assert(PhiTy->isPointerTy() && "The PHI must be a pointer");
4348  Type *PointerElementType = PhiTy->getPointerElementType();
4349  // The pointer stride cannot be determined if the pointer element type is not
4350  // sized.
4351  if (!PointerElementType->isSized())
4352    return false;
4353
4354  const DataLayout &DL = Phi->getModule()->getDataLayout();
4355  int64_t Size = static_cast<int64_t>(DL.getTypeAllocSize(PointerElementType));
4356  int64_t CVSize = CV->getSExtValue();
4357  if (CVSize % Size)
4358    return false;
4359  StepValue = ConstantInt::getSigned(CV->getType(), CVSize / Size);
4360  return true;
4361}
4362
4363LoopVectorizationLegality::InductionKind
4364LoopVectorizationLegality::isInductionVariable(PHINode *Phi,
4365                                               ConstantInt *&StepValue) {
4366  if (!isInductionPHI(Phi, SE, StepValue))
4367    return IK_NoInduction;
4368
4369  Type *PhiTy = Phi->getType();
4370  // Found an Integer induction variable.
4371  if (PhiTy->isIntegerTy())
4372    return IK_IntInduction;
4373  // Found an Pointer induction variable.
4374  return IK_PtrInduction;
4375}
4376
4377bool LoopVectorizationLegality::isInductionVariable(const Value *V) {
4378  Value *In0 = const_cast<Value*>(V);
4379  PHINode *PN = dyn_cast_or_null<PHINode>(In0);
4380  if (!PN)
4381    return false;
4382
4383  return Inductions.count(PN);
4384}
4385
4386bool LoopVectorizationLegality::blockNeedsPredication(BasicBlock *BB)  {
4387  return LoopAccessInfo::blockNeedsPredication(BB, TheLoop, DT);
4388}
4389
4390bool LoopVectorizationLegality::blockCanBePredicated(BasicBlock *BB,
4391                                           SmallPtrSetImpl<Value *> &SafePtrs) {
4392
4393  for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
4394    // Check that we don't have a constant expression that can trap as operand.
4395    for (Instruction::op_iterator OI = it->op_begin(), OE = it->op_end();
4396         OI != OE; ++OI) {
4397      if (Constant *C = dyn_cast<Constant>(*OI))
4398        if (C->canTrap())
4399          return false;
4400    }
4401    // We might be able to hoist the load.
4402    if (it->mayReadFromMemory()) {
4403      LoadInst *LI = dyn_cast<LoadInst>(it);
4404      if (!LI)
4405        return false;
4406      if (!SafePtrs.count(LI->getPointerOperand())) {
4407        if (isLegalMaskedLoad(LI->getType(), LI->getPointerOperand())) {
4408          MaskedOp.insert(LI);
4409          continue;
4410        }
4411        return false;
4412      }
4413    }
4414
4415    // We don't predicate stores at the moment.
4416    if (it->mayWriteToMemory()) {
4417      StoreInst *SI = dyn_cast<StoreInst>(it);
4418      // We only support predication of stores in basic blocks with one
4419      // predecessor.
4420      if (!SI)
4421        return false;
4422
4423      bool isSafePtr = (SafePtrs.count(SI->getPointerOperand()) != 0);
4424      bool isSinglePredecessor = SI->getParent()->getSinglePredecessor();
4425
4426      if (++NumPredStores > NumberOfStoresToPredicate || !isSafePtr ||
4427          !isSinglePredecessor) {
4428        // Build a masked store if it is legal for the target, otherwise scalarize
4429        // the block.
4430        bool isLegalMaskedOp =
4431          isLegalMaskedStore(SI->getValueOperand()->getType(),
4432                             SI->getPointerOperand());
4433        if (isLegalMaskedOp) {
4434          --NumPredStores;
4435          MaskedOp.insert(SI);
4436          continue;
4437        }
4438        return false;
4439      }
4440    }
4441    if (it->mayThrow())
4442      return false;
4443
4444    // The instructions below can trap.
4445    switch (it->getOpcode()) {
4446    default: continue;
4447    case Instruction::UDiv:
4448    case Instruction::SDiv:
4449    case Instruction::URem:
4450    case Instruction::SRem:
4451      return false;
4452    }
4453  }
4454
4455  return true;
4456}
4457
4458LoopVectorizationCostModel::VectorizationFactor
4459LoopVectorizationCostModel::selectVectorizationFactor(bool OptForSize) {
4460  // Width 1 means no vectorize
4461  VectorizationFactor Factor = { 1U, 0U };
4462  if (OptForSize && Legal->getRuntimePointerCheck()->Need) {
4463    emitAnalysis(VectorizationReport() <<
4464                 "runtime pointer checks needed. Enable vectorization of this "
4465                 "loop with '#pragma clang loop vectorize(enable)' when "
4466                 "compiling with -Os");
4467    DEBUG(dbgs() << "LV: Aborting. Runtime ptr check is required in Os.\n");
4468    return Factor;
4469  }
4470
4471  if (!EnableCondStoresVectorization && Legal->getNumPredStores()) {
4472    emitAnalysis(VectorizationReport() <<
4473                 "store that is conditionally executed prevents vectorization");
4474    DEBUG(dbgs() << "LV: No vectorization. There are conditional stores.\n");
4475    return Factor;
4476  }
4477
4478  // Find the trip count.
4479  unsigned TC = SE->getSmallConstantTripCount(TheLoop);
4480  DEBUG(dbgs() << "LV: Found trip count: " << TC << '\n');
4481
4482  unsigned WidestType = getWidestType();
4483  unsigned WidestRegister = TTI.getRegisterBitWidth(true);
4484  unsigned MaxSafeDepDist = -1U;
4485  if (Legal->getMaxSafeDepDistBytes() != -1U)
4486    MaxSafeDepDist = Legal->getMaxSafeDepDistBytes() * 8;
4487  WidestRegister = ((WidestRegister < MaxSafeDepDist) ?
4488                    WidestRegister : MaxSafeDepDist);
4489  unsigned MaxVectorSize = WidestRegister / WidestType;
4490  DEBUG(dbgs() << "LV: The Widest type: " << WidestType << " bits.\n");
4491  DEBUG(dbgs() << "LV: The Widest register is: "
4492          << WidestRegister << " bits.\n");
4493
4494  if (MaxVectorSize == 0) {
4495    DEBUG(dbgs() << "LV: The target has no vector registers.\n");
4496    MaxVectorSize = 1;
4497  }
4498
4499  assert(MaxVectorSize <= 64 && "Did not expect to pack so many elements"
4500         " into one vector!");
4501
4502  unsigned VF = MaxVectorSize;
4503
4504  // If we optimize the program for size, avoid creating the tail loop.
4505  if (OptForSize) {
4506    // If we are unable to calculate the trip count then don't try to vectorize.
4507    if (TC < 2) {
4508      emitAnalysis
4509        (VectorizationReport() <<
4510         "unable to calculate the loop count due to complex control flow");
4511      DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n");
4512      return Factor;
4513    }
4514
4515    // Find the maximum SIMD width that can fit within the trip count.
4516    VF = TC % MaxVectorSize;
4517
4518    if (VF == 0)
4519      VF = MaxVectorSize;
4520
4521    // If the trip count that we found modulo the vectorization factor is not
4522    // zero then we require a tail.
4523    if (VF < 2) {
4524      emitAnalysis(VectorizationReport() <<
4525                   "cannot optimize for size and vectorize at the "
4526                   "same time. Enable vectorization of this loop "
4527                   "with '#pragma clang loop vectorize(enable)' "
4528                   "when compiling with -Os");
4529      DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n");
4530      return Factor;
4531    }
4532  }
4533
4534  int UserVF = Hints->getWidth();
4535  if (UserVF != 0) {
4536    assert(isPowerOf2_32(UserVF) && "VF needs to be a power of two");
4537    DEBUG(dbgs() << "LV: Using user VF " << UserVF << ".\n");
4538
4539    Factor.Width = UserVF;
4540    return Factor;
4541  }
4542
4543  float Cost = expectedCost(1);
4544#ifndef NDEBUG
4545  const float ScalarCost = Cost;
4546#endif /* NDEBUG */
4547  unsigned Width = 1;
4548  DEBUG(dbgs() << "LV: Scalar loop costs: " << (int)ScalarCost << ".\n");
4549
4550  bool ForceVectorization = Hints->getForce() == LoopVectorizeHints::FK_Enabled;
4551  // Ignore scalar width, because the user explicitly wants vectorization.
4552  if (ForceVectorization && VF > 1) {
4553    Width = 2;
4554    Cost = expectedCost(Width) / (float)Width;
4555  }
4556
4557  for (unsigned i=2; i <= VF; i*=2) {
4558    // Notice that the vector loop needs to be executed less times, so
4559    // we need to divide the cost of the vector loops by the width of
4560    // the vector elements.
4561    float VectorCost = expectedCost(i) / (float)i;
4562    DEBUG(dbgs() << "LV: Vector loop of width " << i << " costs: " <<
4563          (int)VectorCost << ".\n");
4564    if (VectorCost < Cost) {
4565      Cost = VectorCost;
4566      Width = i;
4567    }
4568  }
4569
4570  DEBUG(if (ForceVectorization && Width > 1 && Cost >= ScalarCost) dbgs()
4571        << "LV: Vectorization seems to be not beneficial, "
4572        << "but was forced by a user.\n");
4573  DEBUG(dbgs() << "LV: Selecting VF: "<< Width << ".\n");
4574  Factor.Width = Width;
4575  Factor.Cost = Width * Cost;
4576  return Factor;
4577}
4578
4579unsigned LoopVectorizationCostModel::getWidestType() {
4580  unsigned MaxWidth = 8;
4581  const DataLayout &DL = TheFunction->getParent()->getDataLayout();
4582
4583  // For each block.
4584  for (Loop::block_iterator bb = TheLoop->block_begin(),
4585       be = TheLoop->block_end(); bb != be; ++bb) {
4586    BasicBlock *BB = *bb;
4587
4588    // For each instruction in the loop.
4589    for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
4590      Type *T = it->getType();
4591
4592      // Ignore ephemeral values.
4593      if (EphValues.count(it))
4594        continue;
4595
4596      // Only examine Loads, Stores and PHINodes.
4597      if (!isa<LoadInst>(it) && !isa<StoreInst>(it) && !isa<PHINode>(it))
4598        continue;
4599
4600      // Examine PHI nodes that are reduction variables.
4601      if (PHINode *PN = dyn_cast<PHINode>(it))
4602        if (!Legal->getReductionVars()->count(PN))
4603          continue;
4604
4605      // Examine the stored values.
4606      if (StoreInst *ST = dyn_cast<StoreInst>(it))
4607        T = ST->getValueOperand()->getType();
4608
4609      // Ignore loaded pointer types and stored pointer types that are not
4610      // consecutive. However, we do want to take consecutive stores/loads of
4611      // pointer vectors into account.
4612      if (T->isPointerTy() && !isConsecutiveLoadOrStore(it))
4613        continue;
4614
4615      MaxWidth = std::max(MaxWidth,
4616                          (unsigned)DL.getTypeSizeInBits(T->getScalarType()));
4617    }
4618  }
4619
4620  return MaxWidth;
4621}
4622
4623unsigned
4624LoopVectorizationCostModel::selectUnrollFactor(bool OptForSize,
4625                                               unsigned VF,
4626                                               unsigned LoopCost) {
4627
4628  // -- The unroll heuristics --
4629  // We unroll the loop in order to expose ILP and reduce the loop overhead.
4630  // There are many micro-architectural considerations that we can't predict
4631  // at this level. For example, frontend pressure (on decode or fetch) due to
4632  // code size, or the number and capabilities of the execution ports.
4633  //
4634  // We use the following heuristics to select the unroll factor:
4635  // 1. If the code has reductions, then we unroll in order to break the cross
4636  // iteration dependency.
4637  // 2. If the loop is really small, then we unroll in order to reduce the loop
4638  // overhead.
4639  // 3. We don't unroll if we think that we will spill registers to memory due
4640  // to the increased register pressure.
4641
4642  // Use the user preference, unless 'auto' is selected.
4643  int UserUF = Hints->getInterleave();
4644  if (UserUF != 0)
4645    return UserUF;
4646
4647  // When we optimize for size, we don't unroll.
4648  if (OptForSize)
4649    return 1;
4650
4651  // We used the distance for the unroll factor.
4652  if (Legal->getMaxSafeDepDistBytes() != -1U)
4653    return 1;
4654
4655  // Do not unroll loops with a relatively small trip count.
4656  unsigned TC = SE->getSmallConstantTripCount(TheLoop);
4657  if (TC > 1 && TC < TinyTripCountUnrollThreshold)
4658    return 1;
4659
4660  unsigned TargetNumRegisters = TTI.getNumberOfRegisters(VF > 1);
4661  DEBUG(dbgs() << "LV: The target has " << TargetNumRegisters <<
4662        " registers\n");
4663
4664  if (VF == 1) {
4665    if (ForceTargetNumScalarRegs.getNumOccurrences() > 0)
4666      TargetNumRegisters = ForceTargetNumScalarRegs;
4667  } else {
4668    if (ForceTargetNumVectorRegs.getNumOccurrences() > 0)
4669      TargetNumRegisters = ForceTargetNumVectorRegs;
4670  }
4671
4672  LoopVectorizationCostModel::RegisterUsage R = calculateRegisterUsage();
4673  // We divide by these constants so assume that we have at least one
4674  // instruction that uses at least one register.
4675  R.MaxLocalUsers = std::max(R.MaxLocalUsers, 1U);
4676  R.NumInstructions = std::max(R.NumInstructions, 1U);
4677
4678  // We calculate the unroll factor using the following formula.
4679  // Subtract the number of loop invariants from the number of available
4680  // registers. These registers are used by all of the unrolled instances.
4681  // Next, divide the remaining registers by the number of registers that is
4682  // required by the loop, in order to estimate how many parallel instances
4683  // fit without causing spills. All of this is rounded down if necessary to be
4684  // a power of two. We want power of two unroll factors to simplify any
4685  // addressing operations or alignment considerations.
4686  unsigned UF = PowerOf2Floor((TargetNumRegisters - R.LoopInvariantRegs) /
4687                              R.MaxLocalUsers);
4688
4689  // Don't count the induction variable as unrolled.
4690  if (EnableIndVarRegisterHeur)
4691    UF = PowerOf2Floor((TargetNumRegisters - R.LoopInvariantRegs - 1) /
4692                       std::max(1U, (R.MaxLocalUsers - 1)));
4693
4694  // Clamp the unroll factor ranges to reasonable factors.
4695  unsigned MaxInterleaveSize = TTI.getMaxInterleaveFactor();
4696
4697  // Check if the user has overridden the unroll max.
4698  if (VF == 1) {
4699    if (ForceTargetMaxScalarInterleaveFactor.getNumOccurrences() > 0)
4700      MaxInterleaveSize = ForceTargetMaxScalarInterleaveFactor;
4701  } else {
4702    if (ForceTargetMaxVectorInterleaveFactor.getNumOccurrences() > 0)
4703      MaxInterleaveSize = ForceTargetMaxVectorInterleaveFactor;
4704  }
4705
4706  // If we did not calculate the cost for VF (because the user selected the VF)
4707  // then we calculate the cost of VF here.
4708  if (LoopCost == 0)
4709    LoopCost = expectedCost(VF);
4710
4711  // Clamp the calculated UF to be between the 1 and the max unroll factor
4712  // that the target allows.
4713  if (UF > MaxInterleaveSize)
4714    UF = MaxInterleaveSize;
4715  else if (UF < 1)
4716    UF = 1;
4717
4718  // Unroll if we vectorized this loop and there is a reduction that could
4719  // benefit from unrolling.
4720  if (VF > 1 && Legal->getReductionVars()->size()) {
4721    DEBUG(dbgs() << "LV: Unrolling because of reductions.\n");
4722    return UF;
4723  }
4724
4725  // Note that if we've already vectorized the loop we will have done the
4726  // runtime check and so unrolling won't require further checks.
4727  bool UnrollingRequiresRuntimePointerCheck =
4728      (VF == 1 && Legal->getRuntimePointerCheck()->Need);
4729
4730  // We want to unroll small loops in order to reduce the loop overhead and
4731  // potentially expose ILP opportunities.
4732  DEBUG(dbgs() << "LV: Loop cost is " << LoopCost << '\n');
4733  if (!UnrollingRequiresRuntimePointerCheck &&
4734      LoopCost < SmallLoopCost) {
4735    // We assume that the cost overhead is 1 and we use the cost model
4736    // to estimate the cost of the loop and unroll until the cost of the
4737    // loop overhead is about 5% of the cost of the loop.
4738    unsigned SmallUF = std::min(UF, (unsigned)PowerOf2Floor(SmallLoopCost / LoopCost));
4739
4740    // Unroll until store/load ports (estimated by max unroll factor) are
4741    // saturated.
4742    unsigned NumStores = Legal->getNumStores();
4743    unsigned NumLoads = Legal->getNumLoads();
4744    unsigned StoresUF = UF / (NumStores ? NumStores : 1);
4745    unsigned LoadsUF = UF /  (NumLoads ? NumLoads : 1);
4746
4747    // If we have a scalar reduction (vector reductions are already dealt with
4748    // by this point), we can increase the critical path length if the loop
4749    // we're unrolling is inside another loop. Limit, by default to 2, so the
4750    // critical path only gets increased by one reduction operation.
4751    if (Legal->getReductionVars()->size() &&
4752        TheLoop->getLoopDepth() > 1) {
4753      unsigned F = static_cast<unsigned>(MaxNestedScalarReductionUF);
4754      SmallUF = std::min(SmallUF, F);
4755      StoresUF = std::min(StoresUF, F);
4756      LoadsUF = std::min(LoadsUF, F);
4757    }
4758
4759    if (EnableLoadStoreRuntimeUnroll && std::max(StoresUF, LoadsUF) > SmallUF) {
4760      DEBUG(dbgs() << "LV: Unrolling to saturate store or load ports.\n");
4761      return std::max(StoresUF, LoadsUF);
4762    }
4763
4764    DEBUG(dbgs() << "LV: Unrolling to reduce branch cost.\n");
4765    return SmallUF;
4766  }
4767
4768  // Unroll if this is a large loop (small loops are already dealt with by this
4769  // point) that could benefit from interleaved unrolling.
4770  bool HasReductions = (Legal->getReductionVars()->size() > 0);
4771  if (TTI.enableAggressiveInterleaving(HasReductions)) {
4772    DEBUG(dbgs() << "LV: Unrolling to expose ILP.\n");
4773    return UF;
4774  }
4775
4776  DEBUG(dbgs() << "LV: Not Unrolling.\n");
4777  return 1;
4778}
4779
4780LoopVectorizationCostModel::RegisterUsage
4781LoopVectorizationCostModel::calculateRegisterUsage() {
4782  // This function calculates the register usage by measuring the highest number
4783  // of values that are alive at a single location. Obviously, this is a very
4784  // rough estimation. We scan the loop in a topological order in order and
4785  // assign a number to each instruction. We use RPO to ensure that defs are
4786  // met before their users. We assume that each instruction that has in-loop
4787  // users starts an interval. We record every time that an in-loop value is
4788  // used, so we have a list of the first and last occurrences of each
4789  // instruction. Next, we transpose this data structure into a multi map that
4790  // holds the list of intervals that *end* at a specific location. This multi
4791  // map allows us to perform a linear search. We scan the instructions linearly
4792  // and record each time that a new interval starts, by placing it in a set.
4793  // If we find this value in the multi-map then we remove it from the set.
4794  // The max register usage is the maximum size of the set.
4795  // We also search for instructions that are defined outside the loop, but are
4796  // used inside the loop. We need this number separately from the max-interval
4797  // usage number because when we unroll, loop-invariant values do not take
4798  // more register.
4799  LoopBlocksDFS DFS(TheLoop);
4800  DFS.perform(LI);
4801
4802  RegisterUsage R;
4803  R.NumInstructions = 0;
4804
4805  // Each 'key' in the map opens a new interval. The values
4806  // of the map are the index of the 'last seen' usage of the
4807  // instruction that is the key.
4808  typedef DenseMap<Instruction*, unsigned> IntervalMap;
4809  // Maps instruction to its index.
4810  DenseMap<unsigned, Instruction*> IdxToInstr;
4811  // Marks the end of each interval.
4812  IntervalMap EndPoint;
4813  // Saves the list of instruction indices that are used in the loop.
4814  SmallSet<Instruction*, 8> Ends;
4815  // Saves the list of values that are used in the loop but are
4816  // defined outside the loop, such as arguments and constants.
4817  SmallPtrSet<Value*, 8> LoopInvariants;
4818
4819  unsigned Index = 0;
4820  for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(),
4821       be = DFS.endRPO(); bb != be; ++bb) {
4822    R.NumInstructions += (*bb)->size();
4823    for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e;
4824         ++it) {
4825      Instruction *I = it;
4826      IdxToInstr[Index++] = I;
4827
4828      // Save the end location of each USE.
4829      for (unsigned i = 0; i < I->getNumOperands(); ++i) {
4830        Value *U = I->getOperand(i);
4831        Instruction *Instr = dyn_cast<Instruction>(U);
4832
4833        // Ignore non-instruction values such as arguments, constants, etc.
4834        if (!Instr) continue;
4835
4836        // If this instruction is outside the loop then record it and continue.
4837        if (!TheLoop->contains(Instr)) {
4838          LoopInvariants.insert(Instr);
4839          continue;
4840        }
4841
4842        // Overwrite previous end points.
4843        EndPoint[Instr] = Index;
4844        Ends.insert(Instr);
4845      }
4846    }
4847  }
4848
4849  // Saves the list of intervals that end with the index in 'key'.
4850  typedef SmallVector<Instruction*, 2> InstrList;
4851  DenseMap<unsigned, InstrList> TransposeEnds;
4852
4853  // Transpose the EndPoints to a list of values that end at each index.
4854  for (IntervalMap::iterator it = EndPoint.begin(), e = EndPoint.end();
4855       it != e; ++it)
4856    TransposeEnds[it->second].push_back(it->first);
4857
4858  SmallSet<Instruction*, 8> OpenIntervals;
4859  unsigned MaxUsage = 0;
4860
4861
4862  DEBUG(dbgs() << "LV(REG): Calculating max register usage:\n");
4863  for (unsigned int i = 0; i < Index; ++i) {
4864    Instruction *I = IdxToInstr[i];
4865    // Ignore instructions that are never used within the loop.
4866    if (!Ends.count(I)) continue;
4867
4868    // Ignore ephemeral values.
4869    if (EphValues.count(I))
4870      continue;
4871
4872    // Remove all of the instructions that end at this location.
4873    InstrList &List = TransposeEnds[i];
4874    for (unsigned int j=0, e = List.size(); j < e; ++j)
4875      OpenIntervals.erase(List[j]);
4876
4877    // Count the number of live interals.
4878    MaxUsage = std::max(MaxUsage, OpenIntervals.size());
4879
4880    DEBUG(dbgs() << "LV(REG): At #" << i << " Interval # " <<
4881          OpenIntervals.size() << '\n');
4882
4883    // Add the current instruction to the list of open intervals.
4884    OpenIntervals.insert(I);
4885  }
4886
4887  unsigned Invariant = LoopInvariants.size();
4888  DEBUG(dbgs() << "LV(REG): Found max usage: " << MaxUsage << '\n');
4889  DEBUG(dbgs() << "LV(REG): Found invariant usage: " << Invariant << '\n');
4890  DEBUG(dbgs() << "LV(REG): LoopSize: " << R.NumInstructions << '\n');
4891
4892  R.LoopInvariantRegs = Invariant;
4893  R.MaxLocalUsers = MaxUsage;
4894  return R;
4895}
4896
4897unsigned LoopVectorizationCostModel::expectedCost(unsigned VF) {
4898  unsigned Cost = 0;
4899
4900  // For each block.
4901  for (Loop::block_iterator bb = TheLoop->block_begin(),
4902       be = TheLoop->block_end(); bb != be; ++bb) {
4903    unsigned BlockCost = 0;
4904    BasicBlock *BB = *bb;
4905
4906    // For each instruction in the old loop.
4907    for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
4908      // Skip dbg intrinsics.
4909      if (isa<DbgInfoIntrinsic>(it))
4910        continue;
4911
4912      // Ignore ephemeral values.
4913      if (EphValues.count(it))
4914        continue;
4915
4916      unsigned C = getInstructionCost(it, VF);
4917
4918      // Check if we should override the cost.
4919      if (ForceTargetInstructionCost.getNumOccurrences() > 0)
4920        C = ForceTargetInstructionCost;
4921
4922      BlockCost += C;
4923      DEBUG(dbgs() << "LV: Found an estimated cost of " << C << " for VF " <<
4924            VF << " For instruction: " << *it << '\n');
4925    }
4926
4927    // We assume that if-converted blocks have a 50% chance of being executed.
4928    // When the code is scalar then some of the blocks are avoided due to CF.
4929    // When the code is vectorized we execute all code paths.
4930    if (VF == 1 && Legal->blockNeedsPredication(*bb))
4931      BlockCost /= 2;
4932
4933    Cost += BlockCost;
4934  }
4935
4936  return Cost;
4937}
4938
4939/// \brief Check whether the address computation for a non-consecutive memory
4940/// access looks like an unlikely candidate for being merged into the indexing
4941/// mode.
4942///
4943/// We look for a GEP which has one index that is an induction variable and all
4944/// other indices are loop invariant. If the stride of this access is also
4945/// within a small bound we decide that this address computation can likely be
4946/// merged into the addressing mode.
4947/// In all other cases, we identify the address computation as complex.
4948static bool isLikelyComplexAddressComputation(Value *Ptr,
4949                                              LoopVectorizationLegality *Legal,
4950                                              ScalarEvolution *SE,
4951                                              const Loop *TheLoop) {
4952  GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr);
4953  if (!Gep)
4954    return true;
4955
4956  // We are looking for a gep with all loop invariant indices except for one
4957  // which should be an induction variable.
4958  unsigned NumOperands = Gep->getNumOperands();
4959  for (unsigned i = 1; i < NumOperands; ++i) {
4960    Value *Opd = Gep->getOperand(i);
4961    if (!SE->isLoopInvariant(SE->getSCEV(Opd), TheLoop) &&
4962        !Legal->isInductionVariable(Opd))
4963      return true;
4964  }
4965
4966  // Now we know we have a GEP ptr, %inv, %ind, %inv. Make sure that the step
4967  // can likely be merged into the address computation.
4968  unsigned MaxMergeDistance = 64;
4969
4970  const SCEVAddRecExpr *AddRec = dyn_cast<SCEVAddRecExpr>(SE->getSCEV(Ptr));
4971  if (!AddRec)
4972    return true;
4973
4974  // Check the step is constant.
4975  const SCEV *Step = AddRec->getStepRecurrence(*SE);
4976  // Calculate the pointer stride and check if it is consecutive.
4977  const SCEVConstant *C = dyn_cast<SCEVConstant>(Step);
4978  if (!C)
4979    return true;
4980
4981  const APInt &APStepVal = C->getValue()->getValue();
4982
4983  // Huge step value - give up.
4984  if (APStepVal.getBitWidth() > 64)
4985    return true;
4986
4987  int64_t StepVal = APStepVal.getSExtValue();
4988
4989  return StepVal > MaxMergeDistance;
4990}
4991
4992static bool isStrideMul(Instruction *I, LoopVectorizationLegality *Legal) {
4993  if (Legal->hasStride(I->getOperand(0)) || Legal->hasStride(I->getOperand(1)))
4994    return true;
4995  return false;
4996}
4997
4998unsigned
4999LoopVectorizationCostModel::getInstructionCost(Instruction *I, unsigned VF) {
5000  // If we know that this instruction will remain uniform, check the cost of
5001  // the scalar version.
5002  if (Legal->isUniformAfterVectorization(I))
5003    VF = 1;
5004
5005  Type *RetTy = I->getType();
5006  Type *VectorTy = ToVectorTy(RetTy, VF);
5007
5008  // TODO: We need to estimate the cost of intrinsic calls.
5009  switch (I->getOpcode()) {
5010  case Instruction::GetElementPtr:
5011    // We mark this instruction as zero-cost because the cost of GEPs in
5012    // vectorized code depends on whether the corresponding memory instruction
5013    // is scalarized or not. Therefore, we handle GEPs with the memory
5014    // instruction cost.
5015    return 0;
5016  case Instruction::Br: {
5017    return TTI.getCFInstrCost(I->getOpcode());
5018  }
5019  case Instruction::PHI:
5020    //TODO: IF-converted IFs become selects.
5021    return 0;
5022  case Instruction::Add:
5023  case Instruction::FAdd:
5024  case Instruction::Sub:
5025  case Instruction::FSub:
5026  case Instruction::Mul:
5027  case Instruction::FMul:
5028  case Instruction::UDiv:
5029  case Instruction::SDiv:
5030  case Instruction::FDiv:
5031  case Instruction::URem:
5032  case Instruction::SRem:
5033  case Instruction::FRem:
5034  case Instruction::Shl:
5035  case Instruction::LShr:
5036  case Instruction::AShr:
5037  case Instruction::And:
5038  case Instruction::Or:
5039  case Instruction::Xor: {
5040    // Since we will replace the stride by 1 the multiplication should go away.
5041    if (I->getOpcode() == Instruction::Mul && isStrideMul(I, Legal))
5042      return 0;
5043    // Certain instructions can be cheaper to vectorize if they have a constant
5044    // second vector operand. One example of this are shifts on x86.
5045    TargetTransformInfo::OperandValueKind Op1VK =
5046      TargetTransformInfo::OK_AnyValue;
5047    TargetTransformInfo::OperandValueKind Op2VK =
5048      TargetTransformInfo::OK_AnyValue;
5049    TargetTransformInfo::OperandValueProperties Op1VP =
5050        TargetTransformInfo::OP_None;
5051    TargetTransformInfo::OperandValueProperties Op2VP =
5052        TargetTransformInfo::OP_None;
5053    Value *Op2 = I->getOperand(1);
5054
5055    // Check for a splat of a constant or for a non uniform vector of constants.
5056    if (isa<ConstantInt>(Op2)) {
5057      ConstantInt *CInt = cast<ConstantInt>(Op2);
5058      if (CInt && CInt->getValue().isPowerOf2())
5059        Op2VP = TargetTransformInfo::OP_PowerOf2;
5060      Op2VK = TargetTransformInfo::OK_UniformConstantValue;
5061    } else if (isa<ConstantVector>(Op2) || isa<ConstantDataVector>(Op2)) {
5062      Op2VK = TargetTransformInfo::OK_NonUniformConstantValue;
5063      Constant *SplatValue = cast<Constant>(Op2)->getSplatValue();
5064      if (SplatValue) {
5065        ConstantInt *CInt = dyn_cast<ConstantInt>(SplatValue);
5066        if (CInt && CInt->getValue().isPowerOf2())
5067          Op2VP = TargetTransformInfo::OP_PowerOf2;
5068        Op2VK = TargetTransformInfo::OK_UniformConstantValue;
5069      }
5070    }
5071
5072    return TTI.getArithmeticInstrCost(I->getOpcode(), VectorTy, Op1VK, Op2VK,
5073                                      Op1VP, Op2VP);
5074  }
5075  case Instruction::Select: {
5076    SelectInst *SI = cast<SelectInst>(I);
5077    const SCEV *CondSCEV = SE->getSCEV(SI->getCondition());
5078    bool ScalarCond = (SE->isLoopInvariant(CondSCEV, TheLoop));
5079    Type *CondTy = SI->getCondition()->getType();
5080    if (!ScalarCond)
5081      CondTy = VectorType::get(CondTy, VF);
5082
5083    return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy, CondTy);
5084  }
5085  case Instruction::ICmp:
5086  case Instruction::FCmp: {
5087    Type *ValTy = I->getOperand(0)->getType();
5088    VectorTy = ToVectorTy(ValTy, VF);
5089    return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy);
5090  }
5091  case Instruction::Store:
5092  case Instruction::Load: {
5093    StoreInst *SI = dyn_cast<StoreInst>(I);
5094    LoadInst *LI = dyn_cast<LoadInst>(I);
5095    Type *ValTy = (SI ? SI->getValueOperand()->getType() :
5096                   LI->getType());
5097    VectorTy = ToVectorTy(ValTy, VF);
5098
5099    unsigned Alignment = SI ? SI->getAlignment() : LI->getAlignment();
5100    unsigned AS = SI ? SI->getPointerAddressSpace() :
5101      LI->getPointerAddressSpace();
5102    Value *Ptr = SI ? SI->getPointerOperand() : LI->getPointerOperand();
5103    // We add the cost of address computation here instead of with the gep
5104    // instruction because only here we know whether the operation is
5105    // scalarized.
5106    if (VF == 1)
5107      return TTI.getAddressComputationCost(VectorTy) +
5108        TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS);
5109
5110    // Scalarized loads/stores.
5111    int ConsecutiveStride = Legal->isConsecutivePtr(Ptr);
5112    bool Reverse = ConsecutiveStride < 0;
5113    const DataLayout &DL = I->getModule()->getDataLayout();
5114    unsigned ScalarAllocatedSize = DL.getTypeAllocSize(ValTy);
5115    unsigned VectorElementSize = DL.getTypeStoreSize(VectorTy) / VF;
5116    if (!ConsecutiveStride || ScalarAllocatedSize != VectorElementSize) {
5117      bool IsComplexComputation =
5118        isLikelyComplexAddressComputation(Ptr, Legal, SE, TheLoop);
5119      unsigned Cost = 0;
5120      // The cost of extracting from the value vector and pointer vector.
5121      Type *PtrTy = ToVectorTy(Ptr->getType(), VF);
5122      for (unsigned i = 0; i < VF; ++i) {
5123        //  The cost of extracting the pointer operand.
5124        Cost += TTI.getVectorInstrCost(Instruction::ExtractElement, PtrTy, i);
5125        // In case of STORE, the cost of ExtractElement from the vector.
5126        // In case of LOAD, the cost of InsertElement into the returned
5127        // vector.
5128        Cost += TTI.getVectorInstrCost(SI ? Instruction::ExtractElement :
5129                                            Instruction::InsertElement,
5130                                            VectorTy, i);
5131      }
5132
5133      // The cost of the scalar loads/stores.
5134      Cost += VF * TTI.getAddressComputationCost(PtrTy, IsComplexComputation);
5135      Cost += VF * TTI.getMemoryOpCost(I->getOpcode(), ValTy->getScalarType(),
5136                                       Alignment, AS);
5137      return Cost;
5138    }
5139
5140    // Wide load/stores.
5141    unsigned Cost = TTI.getAddressComputationCost(VectorTy);
5142    if (Legal->isMaskRequired(I))
5143      Cost += TTI.getMaskedMemoryOpCost(I->getOpcode(), VectorTy, Alignment,
5144                                        AS);
5145    else
5146      Cost += TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS);
5147
5148    if (Reverse)
5149      Cost += TTI.getShuffleCost(TargetTransformInfo::SK_Reverse,
5150                                  VectorTy, 0);
5151    return Cost;
5152  }
5153  case Instruction::ZExt:
5154  case Instruction::SExt:
5155  case Instruction::FPToUI:
5156  case Instruction::FPToSI:
5157  case Instruction::FPExt:
5158  case Instruction::PtrToInt:
5159  case Instruction::IntToPtr:
5160  case Instruction::SIToFP:
5161  case Instruction::UIToFP:
5162  case Instruction::Trunc:
5163  case Instruction::FPTrunc:
5164  case Instruction::BitCast: {
5165    // We optimize the truncation of induction variable.
5166    // The cost of these is the same as the scalar operation.
5167    if (I->getOpcode() == Instruction::Trunc &&
5168        Legal->isInductionVariable(I->getOperand(0)))
5169      return TTI.getCastInstrCost(I->getOpcode(), I->getType(),
5170                                  I->getOperand(0)->getType());
5171
5172    Type *SrcVecTy = ToVectorTy(I->getOperand(0)->getType(), VF);
5173    return TTI.getCastInstrCost(I->getOpcode(), VectorTy, SrcVecTy);
5174  }
5175  case Instruction::Call: {
5176    bool NeedToScalarize;
5177    CallInst *CI = cast<CallInst>(I);
5178    unsigned CallCost = getVectorCallCost(CI, VF, TTI, TLI, NeedToScalarize);
5179    if (getIntrinsicIDForCall(CI, TLI))
5180      return std::min(CallCost, getVectorIntrinsicCost(CI, VF, TTI, TLI));
5181    return CallCost;
5182  }
5183  default: {
5184    // We are scalarizing the instruction. Return the cost of the scalar
5185    // instruction, plus the cost of insert and extract into vector
5186    // elements, times the vector width.
5187    unsigned Cost = 0;
5188
5189    if (!RetTy->isVoidTy() && VF != 1) {
5190      unsigned InsCost = TTI.getVectorInstrCost(Instruction::InsertElement,
5191                                                VectorTy);
5192      unsigned ExtCost = TTI.getVectorInstrCost(Instruction::ExtractElement,
5193                                                VectorTy);
5194
5195      // The cost of inserting the results plus extracting each one of the
5196      // operands.
5197      Cost += VF * (InsCost + ExtCost * I->getNumOperands());
5198    }
5199
5200    // The cost of executing VF copies of the scalar instruction. This opcode
5201    // is unknown. Assume that it is the same as 'mul'.
5202    Cost += VF * TTI.getArithmeticInstrCost(Instruction::Mul, VectorTy);
5203    return Cost;
5204  }
5205  }// end of switch.
5206}
5207
5208char LoopVectorize::ID = 0;
5209static const char lv_name[] = "Loop Vectorization";
5210INITIALIZE_PASS_BEGIN(LoopVectorize, LV_NAME, lv_name, false, false)
5211INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass)
5212INITIALIZE_AG_DEPENDENCY(AliasAnalysis)
5213INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker)
5214INITIALIZE_PASS_DEPENDENCY(BlockFrequencyInfo)
5215INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass)
5216INITIALIZE_PASS_DEPENDENCY(ScalarEvolution)
5217INITIALIZE_PASS_DEPENDENCY(LCSSA)
5218INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass)
5219INITIALIZE_PASS_DEPENDENCY(LoopSimplify)
5220INITIALIZE_PASS_DEPENDENCY(LoopAccessAnalysis)
5221INITIALIZE_PASS_END(LoopVectorize, LV_NAME, lv_name, false, false)
5222
5223namespace llvm {
5224  Pass *createLoopVectorizePass(bool NoUnrolling, bool AlwaysVectorize) {
5225    return new LoopVectorize(NoUnrolling, AlwaysVectorize);
5226  }
5227}
5228
5229bool LoopVectorizationCostModel::isConsecutiveLoadOrStore(Instruction *Inst) {
5230  // Check for a store.
5231  if (StoreInst *ST = dyn_cast<StoreInst>(Inst))
5232    return Legal->isConsecutivePtr(ST->getPointerOperand()) != 0;
5233
5234  // Check for a load.
5235  if (LoadInst *LI = dyn_cast<LoadInst>(Inst))
5236    return Legal->isConsecutivePtr(LI->getPointerOperand()) != 0;
5237
5238  return false;
5239}
5240
5241
5242void InnerLoopUnroller::scalarizeInstruction(Instruction *Instr,
5243                                             bool IfPredicateStore) {
5244  assert(!Instr->getType()->isAggregateType() && "Can't handle vectors");
5245  // Holds vector parameters or scalars, in case of uniform vals.
5246  SmallVector<VectorParts, 4> Params;
5247
5248  setDebugLocFromInst(Builder, Instr);
5249
5250  // Find all of the vectorized parameters.
5251  for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
5252    Value *SrcOp = Instr->getOperand(op);
5253
5254    // If we are accessing the old induction variable, use the new one.
5255    if (SrcOp == OldInduction) {
5256      Params.push_back(getVectorValue(SrcOp));
5257      continue;
5258    }
5259
5260    // Try using previously calculated values.
5261    Instruction *SrcInst = dyn_cast<Instruction>(SrcOp);
5262
5263    // If the src is an instruction that appeared earlier in the basic block
5264    // then it should already be vectorized.
5265    if (SrcInst && OrigLoop->contains(SrcInst)) {
5266      assert(WidenMap.has(SrcInst) && "Source operand is unavailable");
5267      // The parameter is a vector value from earlier.
5268      Params.push_back(WidenMap.get(SrcInst));
5269    } else {
5270      // The parameter is a scalar from outside the loop. Maybe even a constant.
5271      VectorParts Scalars;
5272      Scalars.append(UF, SrcOp);
5273      Params.push_back(Scalars);
5274    }
5275  }
5276
5277  assert(Params.size() == Instr->getNumOperands() &&
5278         "Invalid number of operands");
5279
5280  // Does this instruction return a value ?
5281  bool IsVoidRetTy = Instr->getType()->isVoidTy();
5282
5283  Value *UndefVec = IsVoidRetTy ? nullptr :
5284  UndefValue::get(Instr->getType());
5285  // Create a new entry in the WidenMap and initialize it to Undef or Null.
5286  VectorParts &VecResults = WidenMap.splat(Instr, UndefVec);
5287
5288  Instruction *InsertPt = Builder.GetInsertPoint();
5289  BasicBlock *IfBlock = Builder.GetInsertBlock();
5290  BasicBlock *CondBlock = nullptr;
5291
5292  VectorParts Cond;
5293  Loop *VectorLp = nullptr;
5294  if (IfPredicateStore) {
5295    assert(Instr->getParent()->getSinglePredecessor() &&
5296           "Only support single predecessor blocks");
5297    Cond = createEdgeMask(Instr->getParent()->getSinglePredecessor(),
5298                          Instr->getParent());
5299    VectorLp = LI->getLoopFor(IfBlock);
5300    assert(VectorLp && "Must have a loop for this block");
5301  }
5302
5303  // For each vector unroll 'part':
5304  for (unsigned Part = 0; Part < UF; ++Part) {
5305    // For each scalar that we create:
5306
5307    // Start an "if (pred) a[i] = ..." block.
5308    Value *Cmp = nullptr;
5309    if (IfPredicateStore) {
5310      if (Cond[Part]->getType()->isVectorTy())
5311        Cond[Part] =
5312            Builder.CreateExtractElement(Cond[Part], Builder.getInt32(0));
5313      Cmp = Builder.CreateICmp(ICmpInst::ICMP_EQ, Cond[Part],
5314                               ConstantInt::get(Cond[Part]->getType(), 1));
5315      CondBlock = IfBlock->splitBasicBlock(InsertPt, "cond.store");
5316      LoopVectorBody.push_back(CondBlock);
5317      VectorLp->addBasicBlockToLoop(CondBlock, *LI);
5318      // Update Builder with newly created basic block.
5319      Builder.SetInsertPoint(InsertPt);
5320    }
5321
5322    Instruction *Cloned = Instr->clone();
5323      if (!IsVoidRetTy)
5324        Cloned->setName(Instr->getName() + ".cloned");
5325      // Replace the operands of the cloned instructions with extracted scalars.
5326      for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
5327        Value *Op = Params[op][Part];
5328        Cloned->setOperand(op, Op);
5329      }
5330
5331      // Place the cloned scalar in the new loop.
5332      Builder.Insert(Cloned);
5333
5334      // If the original scalar returns a value we need to place it in a vector
5335      // so that future users will be able to use it.
5336      if (!IsVoidRetTy)
5337        VecResults[Part] = Cloned;
5338
5339    // End if-block.
5340      if (IfPredicateStore) {
5341        BasicBlock *NewIfBlock = CondBlock->splitBasicBlock(InsertPt, "else");
5342        LoopVectorBody.push_back(NewIfBlock);
5343        VectorLp->addBasicBlockToLoop(NewIfBlock, *LI);
5344        Builder.SetInsertPoint(InsertPt);
5345        Instruction *OldBr = IfBlock->getTerminator();
5346        BranchInst::Create(CondBlock, NewIfBlock, Cmp, OldBr);
5347        OldBr->eraseFromParent();
5348        IfBlock = NewIfBlock;
5349      }
5350  }
5351}
5352
5353void InnerLoopUnroller::vectorizeMemoryInstruction(Instruction *Instr) {
5354  StoreInst *SI = dyn_cast<StoreInst>(Instr);
5355  bool IfPredicateStore = (SI && Legal->blockNeedsPredication(SI->getParent()));
5356
5357  return scalarizeInstruction(Instr, IfPredicateStore);
5358}
5359
5360Value *InnerLoopUnroller::reverseVector(Value *Vec) {
5361  return Vec;
5362}
5363
5364Value *InnerLoopUnroller::getBroadcastInstrs(Value *V) {
5365  return V;
5366}
5367
5368Value *InnerLoopUnroller::getStepVector(Value *Val, int StartIdx, Value *Step) {
5369  // When unrolling and the VF is 1, we only need to add a simple scalar.
5370  Type *ITy = Val->getType();
5371  assert(!ITy->isVectorTy() && "Val must be a scalar");
5372  Constant *C = ConstantInt::get(ITy, StartIdx);
5373  return Builder.CreateAdd(Val, Builder.CreateMul(C, Step), "induction");
5374}
5375