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//===- llvm/Transforms/Vectorize/LoopVectorizationLegality.h ----*- C++ -*-===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
//
/// \file
/// This file defines the LoopVectorizationLegality class. Original code
/// in Loop Vectorizer has been moved out to its own file for modularity
/// and reusability.
///
/// Currently, it works for innermost loop vectorization. Extending this to
/// outer loop vectorization is a TODO item.
///
/// Also provides:
/// 1) LoopVectorizeHints class which keeps a number of loop annotations
/// locally for easy look up. It has the ability to write them back as
/// loop metadata, upon request.
/// 2) LoopVectorizationRequirements class for lazy bail out for the purpose
/// of reporting useful failure to vectorize message.
//
//===----------------------------------------------------------------------===//
#ifndef LLVM_TRANSFORMS_VECTORIZE_LOOPVECTORIZATIONLEGALITY_H
#define LLVM_TRANSFORMS_VECTORIZE_LOOPVECTORIZATIONLEGALITY_H
#include "llvm/ADT/MapVector.h"
#include "llvm/Analysis/LoopAccessAnalysis.h"
#include "llvm/Support/TypeSize.h"
#include "llvm/Transforms/Utils/LoopUtils.h"
namespace llvm {
class AssumptionCache;
class BasicBlock;
class BlockFrequencyInfo;
class DemandedBits;
class DominatorTree;
class Function;
class Loop;
class LoopInfo;
class Metadata;
class OptimizationRemarkEmitter;
class PredicatedScalarEvolution;
class ProfileSummaryInfo;
class TargetLibraryInfo;
class TargetTransformInfo;
class Type;
/// Utility class for getting and setting loop vectorizer hints in the form
/// of loop metadata.
/// This class keeps a number of loop annotations locally (as member variables)
/// and can, upon request, write them back as metadata on the loop. It will
/// initially scan the loop for existing metadata, and will update the local
/// values based on information in the loop.
/// We cannot write all values to metadata, as the mere presence of some info,
/// for example 'force', means a decision has been made. So, we need to be
/// careful NOT to add them if the user hasn't specifically asked so.
class LoopVectorizeHints {
enum HintKind {
HK_WIDTH,
HK_INTERLEAVE,
HK_FORCE,
HK_ISVECTORIZED,
HK_PREDICATE,
HK_SCALABLE
};
/// Hint - associates name and validation with the hint value.
struct Hint {
const char *Name;
unsigned Value; // This may have to change for non-numeric values.
HintKind Kind;
Hint(const char *Name, unsigned Value, HintKind Kind)
: Name(Name), Value(Value), Kind(Kind) {}
bool validate(unsigned Val);
};
/// Vectorization width.
Hint Width;
/// Vectorization interleave factor.
Hint Interleave;
/// Vectorization forced
Hint Force;
/// Already Vectorized
Hint IsVectorized;
/// Vector Predicate
Hint Predicate;
/// Says whether we should use fixed width or scalable vectorization.
Hint Scalable;
/// Return the loop metadata prefix.
static StringRef Prefix() { return "llvm.loop."; }
/// True if there is any unsafe math in the loop.
bool PotentiallyUnsafe = false;
public:
enum ForceKind {
FK_Undefined = -1, ///< Not selected.
FK_Disabled = 0, ///< Forcing disabled.
FK_Enabled = 1, ///< Forcing enabled.
};
enum ScalableForceKind {
/// Not selected.
SK_Unspecified = -1,
/// Disables vectorization with scalable vectors.
SK_FixedWidthOnly = 0,
/// Vectorize loops using scalable vectors or fixed-width vectors, but favor
/// scalable vectors when the cost-model is inconclusive. This is the
/// default when the scalable.enable hint is enabled through a pragma.
SK_PreferScalable = 1
};
LoopVectorizeHints(const Loop *L, bool InterleaveOnlyWhenForced,
OptimizationRemarkEmitter &ORE,
const TargetTransformInfo *TTI = nullptr);
/// Mark the loop L as already vectorized by setting the width to 1.
void setAlreadyVectorized();
bool allowVectorization(Function *F, Loop *L,
bool VectorizeOnlyWhenForced) const;
/// Dumps all the hint information.
void emitRemarkWithHints() const;
ElementCount getWidth() const {
return ElementCount::get(Width.Value, (ScalableForceKind)Scalable.Value ==
SK_PreferScalable);
}
unsigned getInterleave() const {
if (Interleave.Value)
return Interleave.Value;
// If interleaving is not explicitly set, assume that if we do not want
// unrolling, we also don't want any interleaving.
if (llvm::hasUnrollTransformation(TheLoop) & TM_Disable)
return 1;
return 0;
}
unsigned getIsVectorized() const { return IsVectorized.Value; }
unsigned getPredicate() const { return Predicate.Value; }
enum ForceKind getForce() const {
if ((ForceKind)Force.Value == FK_Undefined &&
hasDisableAllTransformsHint(TheLoop))
return FK_Disabled;
return (ForceKind)Force.Value;
}
/// \return true if scalable vectorization has been explicitly disabled.
bool isScalableVectorizationDisabled() const {
return (ScalableForceKind)Scalable.Value == SK_FixedWidthOnly;
}
/// If hints are provided that force vectorization, use the AlwaysPrint
/// pass name to force the frontend to print the diagnostic.
const char *vectorizeAnalysisPassName() const;
/// When enabling loop hints are provided we allow the vectorizer to change
/// the order of operations that is given by the scalar loop. This is not
/// enabled by default because can be unsafe or inefficient. For example,
/// reordering floating-point operations will change the way round-off
/// error accumulates in the loop.
bool allowReordering() const;
bool isPotentiallyUnsafe() const {
// Avoid FP vectorization if the target is unsure about proper support.
// This may be related to the SIMD unit in the target not handling
// IEEE 754 FP ops properly, or bad single-to-double promotions.
// Otherwise, a sequence of vectorized loops, even without reduction,
// could lead to different end results on the destination vectors.
return getForce() != LoopVectorizeHints::FK_Enabled && PotentiallyUnsafe;
}
void setPotentiallyUnsafe() { PotentiallyUnsafe = true; }
private:
/// Find hints specified in the loop metadata and update local values.
void getHintsFromMetadata();
/// Checks string hint with one operand and set value if valid.
void setHint(StringRef Name, Metadata *Arg);
/// The loop these hints belong to.
const Loop *TheLoop;
/// Interface to emit optimization remarks.
OptimizationRemarkEmitter &ORE;
};
/// This holds vectorization requirements that must be verified late in
/// the process. The requirements are set by legalize and costmodel. Once
/// vectorization has been determined to be possible and profitable the
/// requirements can be verified by looking for metadata or compiler options.
/// For example, some loops require FP commutativity which is only allowed if
/// vectorization is explicitly specified or if the fast-math compiler option
/// has been provided.
/// Late evaluation of these requirements allows helpful diagnostics to be
/// composed that tells the user what need to be done to vectorize the loop. For
/// example, by specifying #pragma clang loop vectorize or -ffast-math. Late
/// evaluation should be used only when diagnostics can generated that can be
/// followed by a non-expert user.
class LoopVectorizationRequirements {
public:
/// Track the 1st floating-point instruction that can not be reassociated.
void addExactFPMathInst(Instruction *I) {
if (I && !ExactFPMathInst)
ExactFPMathInst = I;
}
Instruction *getExactFPInst() { return ExactFPMathInst; }
private:
Instruction *ExactFPMathInst = nullptr;
};
/// LoopVectorizationLegality checks if it is legal to vectorize a loop, and
/// to what vectorization factor.
/// This class does not look at the profitability of vectorization, only the
/// legality. This class has two main kinds of checks:
/// * Memory checks - The code in canVectorizeMemory checks if vectorization
/// will change the order of memory accesses in a way that will change the
/// correctness of the program.
/// * Scalars checks - The code in canVectorizeInstrs and canVectorizeMemory
/// checks for a number of different conditions, such as the availability of a
/// single induction variable, that all types are supported and vectorize-able,
/// etc. This code reflects the capabilities of InnerLoopVectorizer.
/// This class is also used by InnerLoopVectorizer for identifying
/// induction variable and the different reduction variables.
class LoopVectorizationLegality {
public:
LoopVectorizationLegality(
Loop *L, PredicatedScalarEvolution &PSE, DominatorTree *DT,
TargetTransformInfo *TTI, TargetLibraryInfo *TLI, Function *F,
LoopAccessInfoManager &LAIs, LoopInfo *LI, OptimizationRemarkEmitter *ORE,
LoopVectorizationRequirements *R, LoopVectorizeHints *H, DemandedBits *DB,
AssumptionCache *AC, BlockFrequencyInfo *BFI, ProfileSummaryInfo *PSI)
: TheLoop(L), LI(LI), PSE(PSE), TTI(TTI), TLI(TLI), DT(DT), LAIs(LAIs),
ORE(ORE), Requirements(R), Hints(H), DB(DB), AC(AC), BFI(BFI),
PSI(PSI) {}
/// ReductionList contains the reduction descriptors for all
/// of the reductions that were found in the loop.
using ReductionList = MapVector<PHINode *, RecurrenceDescriptor>;
/// InductionList saves induction variables and maps them to the
/// induction descriptor.
using InductionList = MapVector<PHINode *, InductionDescriptor>;
/// RecurrenceSet contains the phi nodes that are recurrences other than
/// inductions and reductions.
using RecurrenceSet = SmallPtrSet<const PHINode *, 8>;
/// Returns true if it is legal to vectorize this loop.
/// This does not mean that it is profitable to vectorize this
/// loop, only that it is legal to do so.
/// Temporarily taking UseVPlanNativePath parameter. If true, take
/// the new code path being implemented for outer loop vectorization
/// (should be functional for inner loop vectorization) based on VPlan.
/// If false, good old LV code.
bool canVectorize(bool UseVPlanNativePath);
/// Returns true if it is legal to vectorize the FP math operations in this
/// loop. Vectorizing is legal if we allow reordering of FP operations, or if
/// we can use in-order reductions.
bool canVectorizeFPMath(bool EnableStrictReductions);
/// Return true if we can vectorize this loop while folding its tail by
/// masking.
bool canFoldTailByMasking() const;
/// Mark all respective loads/stores for masking. Must only be called when
/// tail-folding is possible.
void prepareToFoldTailByMasking();
/// Returns the primary induction variable.
PHINode *getPrimaryInduction() { return PrimaryInduction; }
/// Returns the reduction variables found in the loop.
const ReductionList &getReductionVars() const { return Reductions; }
/// Returns the induction variables found in the loop.
const InductionList &getInductionVars() const { return Inductions; }
/// Return the fixed-order recurrences found in the loop.
RecurrenceSet &getFixedOrderRecurrences() { return FixedOrderRecurrences; }
/// Returns the widest induction type.
Type *getWidestInductionType() { return WidestIndTy; }
/// Returns True if given store is a final invariant store of one of the
/// reductions found in the loop.
bool isInvariantStoreOfReduction(StoreInst *SI);
/// Returns True if given address is invariant and is used to store recurrent
/// expression
bool isInvariantAddressOfReduction(Value *V);
/// Returns True if V is a Phi node of an induction variable in this loop.
bool isInductionPhi(const Value *V) const;
/// Returns a pointer to the induction descriptor, if \p Phi is an integer or
/// floating point induction.
const InductionDescriptor *getIntOrFpInductionDescriptor(PHINode *Phi) const;
/// Returns a pointer to the induction descriptor, if \p Phi is pointer
/// induction.
const InductionDescriptor *getPointerInductionDescriptor(PHINode *Phi) const;
/// Returns True if V is a cast that is part of an induction def-use chain,
/// and had been proven to be redundant under a runtime guard (in other
/// words, the cast has the same SCEV expression as the induction phi).
bool isCastedInductionVariable(const Value *V) const;
/// Returns True if V can be considered as an induction variable in this
/// loop. V can be the induction phi, or some redundant cast in the def-use
/// chain of the inducion phi.
bool isInductionVariable(const Value *V) const;
/// Returns True if PN is a reduction variable in this loop.
bool isReductionVariable(PHINode *PN) const { return Reductions.count(PN); }
/// Returns True if Phi is a fixed-order recurrence in this loop.
bool isFixedOrderRecurrence(const PHINode *Phi) const;
/// Return true if the block BB needs to be predicated in order for the loop
/// to be vectorized.
bool blockNeedsPredication(BasicBlock *BB) const;
/// Check if this pointer is consecutive when vectorizing. This happens
/// when the last index of the GEP is the induction variable, or that the
/// pointer itself is an induction variable.
/// This check allows us to vectorize A[idx] into a wide load/store.
/// Returns:
/// 0 - Stride is unknown or non-consecutive.
/// 1 - Address is consecutive.
/// -1 - Address is consecutive, and decreasing.
/// NOTE: This method must only be used before modifying the original scalar
/// loop. Do not use after invoking 'createVectorizedLoopSkeleton' (PR34965).
int isConsecutivePtr(Type *AccessTy, Value *Ptr) const;
/// Returns true if value V is uniform across \p VF lanes, when \p VF is
/// provided, and otherwise if \p V is invariant across all loop iterations.
bool isInvariant(Value *V) const;
/// Returns true if value V is uniform across \p VF lanes, when \p VF is
/// provided, and otherwise if \p V is invariant across all loop iterations.
bool isUniform(Value *V, ElementCount VF) const;
/// A uniform memory op is a load or store which accesses the same memory
/// location on all \p VF lanes, if \p VF is provided and otherwise if the
/// memory location is invariant.
bool isUniformMemOp(Instruction &I, ElementCount VF) const;
/// Returns the information that we collected about runtime memory check.
const RuntimePointerChecking *getRuntimePointerChecking() const {
return LAI->getRuntimePointerChecking();
}
const LoopAccessInfo *getLAI() const { return LAI; }
bool isSafeForAnyVectorWidth() const {
return LAI->getDepChecker().isSafeForAnyVectorWidth();
}
uint64_t getMaxSafeVectorWidthInBits() const {
return LAI->getDepChecker().getMaxSafeVectorWidthInBits();
}
/// Returns true if vector representation of the instruction \p I
/// requires mask.
bool isMaskRequired(const Instruction *I) const {
return MaskedOp.contains(I);
}
/// Returns true if there is at least one function call in the loop which
/// has a vectorized variant available.
bool hasVectorCallVariants() const { return VecCallVariantsFound; }
unsigned getNumStores() const { return LAI->getNumStores(); }
unsigned getNumLoads() const { return LAI->getNumLoads(); }
PredicatedScalarEvolution *getPredicatedScalarEvolution() const {
return &PSE;
}
Loop *getLoop() const { return TheLoop; }
LoopInfo *getLoopInfo() const { return LI; }
AssumptionCache *getAssumptionCache() const { return AC; }
ScalarEvolution *getScalarEvolution() const { return PSE.getSE(); }
DominatorTree *getDominatorTree() const { return DT; }
private:
/// Return true if the pre-header, exiting and latch blocks of \p Lp and all
/// its nested loops are considered legal for vectorization. These legal
/// checks are common for inner and outer loop vectorization.
/// Temporarily taking UseVPlanNativePath parameter. If true, take
/// the new code path being implemented for outer loop vectorization
/// (should be functional for inner loop vectorization) based on VPlan.
/// If false, good old LV code.
bool canVectorizeLoopNestCFG(Loop *Lp, bool UseVPlanNativePath);
/// Set up outer loop inductions by checking Phis in outer loop header for
/// supported inductions (int inductions). Return false if any of these Phis
/// is not a supported induction or if we fail to find an induction.
bool setupOuterLoopInductions();
/// Return true if the pre-header, exiting and latch blocks of \p Lp
/// (non-recursive) are considered legal for vectorization.
/// Temporarily taking UseVPlanNativePath parameter. If true, take
/// the new code path being implemented for outer loop vectorization
/// (should be functional for inner loop vectorization) based on VPlan.
/// If false, good old LV code.
bool canVectorizeLoopCFG(Loop *Lp, bool UseVPlanNativePath);
/// Check if a single basic block loop is vectorizable.
/// At this point we know that this is a loop with a constant trip count
/// and we only need to check individual instructions.
bool canVectorizeInstrs();
/// When we vectorize loops we may change the order in which
/// we read and write from memory. This method checks if it is
/// legal to vectorize the code, considering only memory constrains.
/// Returns true if the loop is vectorizable
bool canVectorizeMemory();
/// Return true if we can vectorize this loop using the IF-conversion
/// transformation.
bool canVectorizeWithIfConvert();
/// Return true if we can vectorize this outer loop. The method performs
/// specific checks for outer loop vectorization.
bool canVectorizeOuterLoop();
/// Return true if all of the instructions in the block can be speculatively
/// executed, and record the loads/stores that require masking.
/// \p SafePtrs is a list of addresses that are known to be legal and we know
/// that we can read from them without segfault.
/// \p MaskedOp is a list of instructions that have to be transformed into
/// calls to the appropriate masked intrinsic when the loop is vectorized
/// or dropped if the instruction is a conditional assume intrinsic.
bool
blockCanBePredicated(BasicBlock *BB, SmallPtrSetImpl<Value *> &SafePtrs,
SmallPtrSetImpl<const Instruction *> &MaskedOp) const;
/// Updates the vectorization state by adding \p Phi to the inductions list.
/// This can set \p Phi as the main induction of the loop if \p Phi is a
/// better choice for the main induction than the existing one.
void addInductionPhi(PHINode *Phi, const InductionDescriptor &ID,
SmallPtrSetImpl<Value *> &AllowedExit);
/// The loop that we evaluate.
Loop *TheLoop;
/// Loop Info analysis.
LoopInfo *LI;
/// A wrapper around ScalarEvolution used to add runtime SCEV checks.
/// Applies dynamic knowledge to simplify SCEV expressions in the context
/// of existing SCEV assumptions. The analysis will also add a minimal set
/// of new predicates if this is required to enable vectorization and
/// unrolling.
PredicatedScalarEvolution &PSE;
/// Target Transform Info.
TargetTransformInfo *TTI;
/// Target Library Info.
TargetLibraryInfo *TLI;
/// Dominator Tree.
DominatorTree *DT;
// LoopAccess analysis.
LoopAccessInfoManager &LAIs;
const LoopAccessInfo *LAI = nullptr;
/// Interface to emit optimization remarks.
OptimizationRemarkEmitter *ORE;
// --- vectorization state --- //
/// Holds the primary induction variable. This is the counter of the
/// loop.
PHINode *PrimaryInduction = nullptr;
/// Holds the reduction variables.
ReductionList Reductions;
/// Holds all of the induction variables that we found in the loop.
/// Notice that inductions don't need to start at zero and that induction
/// variables can be pointers.
InductionList Inductions;
/// Holds all the casts that participate in the update chain of the induction
/// variables, and that have been proven to be redundant (possibly under a
/// runtime guard). These casts can be ignored when creating the vectorized
/// loop body.
SmallPtrSet<Instruction *, 4> InductionCastsToIgnore;
/// Holds the phi nodes that are fixed-order recurrences.
RecurrenceSet FixedOrderRecurrences;
/// Holds the widest induction type encountered.
Type *WidestIndTy = nullptr;
/// Allowed outside users. This holds the variables that can be accessed from
/// outside the loop.
SmallPtrSet<Value *, 4> AllowedExit;
/// Vectorization requirements that will go through late-evaluation.
LoopVectorizationRequirements *Requirements;
/// Used to emit an analysis of any legality issues.
LoopVectorizeHints *Hints;
/// The demanded bits analysis is used to compute the minimum type size in
/// which a reduction can be computed.
DemandedBits *DB;
/// The assumption cache analysis is used to compute the minimum type size in
/// which a reduction can be computed.
AssumptionCache *AC;
/// While vectorizing these instructions we have to generate a
/// call to the appropriate masked intrinsic or drop them in case of
/// conditional assumes.
SmallPtrSet<const Instruction *, 8> MaskedOp;
/// BFI and PSI are used to check for profile guided size optimizations.
BlockFrequencyInfo *BFI;
ProfileSummaryInfo *PSI;
/// If we discover function calls within the loop which have a valid
/// vectorized variant, record that fact so that LoopVectorize can
/// (potentially) make a better decision on the maximum VF and enable
/// the use of those function variants.
bool VecCallVariantsFound = false;
};
} // namespace llvm
#endif // LLVM_TRANSFORMS_VECTORIZE_LOOPVECTORIZATIONLEGALITY_H
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