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llvm-mirror/include/llvm/Transforms/Vectorize/LoopVectorizationLegality.h
Joachim Meyer 6b73f118b0 [LV] Parallel annotated loop does not imply all loads can be hoisted.
As noted in https://bugs.llvm.org/show_bug.cgi?id=46666, the current behavior of assuming if-conversion safety if a loop is annotated parallel (`!llvm.loop.parallel_accesses`), is not expectable, the documentation for this behavior was since removed from the LangRef again, and can lead to invalid reads.
This was observed in POCL (https://github.com/pocl/pocl/issues/757) and would require similar workarounds in current work at hipSYCL.

The question remains why this was initially added and what the implications of removing this optimization would be.
Do we need an alternative mechanism to propagate the information about legality of if-conversion?
Or is the idea that conditional loads in `#pragma clang loop vectorize(assume_safety)` can be executed unmasked without additional checks flawed in general?
I think this implication is not part of what a user of that pragma (and corresponding metadata) would expect and thus dangerous.

Only two additional tests failed, which are adapted in this patch. Depending on the further direction force-ifcvt.ll should be removed or further adapted.

Reviewed By: jdoerfert

Differential Revision: https://reviews.llvm.org/D103907
2021-06-10 23:37:57 +02:00

562 lines
22 KiB
C++

//===- 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/Analysis/OptimizationRemarkEmitter.h"
#include "llvm/Support/TypeSize.h"
#include "llvm/Transforms/Utils/LoopUtils.h"
namespace llvm {
/// 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,
/// Vectorize loops using scalable vectors or fixed-width vectors, but
/// favor fixed-width vectors when the cost is inconclusive.
SK_PreferFixedWidth = 2,
};
LoopVectorizeHints(const Loop *L, bool InterleaveOnlyWhenForced,
OptimizationRemarkEmitter &ORE);
/// 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,
isScalableVectorizationExplicitlyEnabled());
}
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 the cost-model for scalable vectorization should
/// favor vectorization with scalable vectors over fixed-width vectors when
/// the cost-model is inconclusive.
bool isScalableVectorizationPreferred() const {
return Scalable.Value == SK_PreferScalable;
}
/// \return true if scalable vectorization has been explicitly enabled.
bool isScalableVectorizationExplicitlyEnabled() const {
return Scalable.Value == SK_PreferFixedWidth ||
Scalable.Value == SK_PreferScalable;
}
/// \return true if scalable vectorization has been explicitly disabled.
bool isScalableVectorizationDisabled() const {
return 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;
}
void addRuntimePointerChecks(unsigned Num) { NumRuntimePointerChecks = Num; }
Instruction *getExactFPInst() { return ExactFPMathInst; }
unsigned getNumRuntimePointerChecks() const {
return NumRuntimePointerChecks;
}
private:
unsigned NumRuntimePointerChecks = 0;
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, AAResults *AA,
Function *F, std::function<const LoopAccessInfo &(Loop &)> *GetLAA,
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),
GetLAA(GetLAA), 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, and mark all respective loads/stores for masking.
/// This object's state is only modified iff this function returns true.
bool prepareToFoldTailByMasking();
/// Returns the primary induction variable.
PHINode *getPrimaryInduction() { return PrimaryInduction; }
/// Returns the reduction variables found in the loop.
ReductionList &getReductionVars() { return Reductions; }
/// Returns the induction variables found in the loop.
InductionList &getInductionVars() { return Inductions; }
/// Return the first-order recurrences found in the loop.
RecurrenceSet &getFirstOrderRecurrences() { return FirstOrderRecurrences; }
/// Return the set of instructions to sink to handle first-order recurrences.
MapVector<Instruction *, Instruction *> &getSinkAfter() { return SinkAfter; }
/// Returns the widest induction type.
Type *getWidestInductionType() { return WidestIndTy; }
/// Returns True if V is a Phi node of an induction variable in this loop.
bool isInductionPhi(const Value *V);
/// 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);
/// 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);
/// Returns True if PN is a reduction variable in this loop.
bool isReductionVariable(PHINode *PN) { return Reductions.count(PN); }
/// Returns True if Phi is a first-order recurrence in this loop.
bool isFirstOrderRecurrence(const PHINode *Phi);
/// 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(Value *Ptr) const;
/// Returns true if the value V is uniform within the loop.
bool isUniform(Value *V);
/// A uniform memory op is a load or store which accesses the same memory
/// location on all lanes.
bool isUniformMemOp(Instruction &I) {
Value *Ptr = getLoadStorePointerOperand(&I);
if (!Ptr)
return false;
// Note: There's nothing inherent which prevents predicated loads and
// stores from being uniform. The current lowering simply doesn't handle
// it; in particular, the cost model distinguishes scatter/gather from
// scalar w/predication, and we currently rely on the scalar path.
return isUniform(Ptr) && !blockNeedsPredication(I.getParent());
}
/// 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();
}
unsigned getMaxSafeDepDistBytes() { return LAI->getMaxSafeDepDistBytes(); }
uint64_t getMaxSafeVectorWidthInBits() const {
return LAI->getDepChecker().getMaxSafeVectorWidthInBits();
}
bool hasStride(Value *V) { return LAI->hasStride(V); }
/// Returns true if vector representation of the instruction \p I
/// requires mask.
bool isMaskRequired(const Instruction *I) const {
return MaskedOp.contains(I);
}
unsigned getNumStores() const { return LAI->getNumStores(); }
unsigned getNumLoads() const { return LAI->getNumLoads(); }
/// Returns all assume calls in predicated blocks. They need to be dropped
/// when flattening the CFG.
const SmallPtrSetImpl<Instruction *> &getConditionalAssumes() const {
return ConditionalAssumes;
}
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.
/// \p ConditionalAssumes is a list of assume instructions in predicated
/// blocks that must be dropped if the CFG gets flattened.
bool blockCanBePredicated(
BasicBlock *BB, SmallPtrSetImpl<Value *> &SafePtrs,
SmallPtrSetImpl<const Instruction *> &MaskedOp,
SmallPtrSetImpl<Instruction *> &ConditionalAssumes) 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);
/// If an access has a symbolic strides, this maps the pointer value to
/// the stride symbol.
const ValueToValueMap *getSymbolicStrides() const {
// FIXME: Currently, the set of symbolic strides is sometimes queried before
// it's collected. This happens from canVectorizeWithIfConvert, when the
// pointer is checked to reference consecutive elements suitable for a
// masked access.
return LAI ? &LAI->getSymbolicStrides() : nullptr;
}
/// 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.
std::function<const LoopAccessInfo &(Loop &)> *GetLAA;
// And the loop-accesses info corresponding to this loop. This pointer is
// null until canVectorizeMemory sets it up.
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 first-order recurrences.
RecurrenceSet FirstOrderRecurrences;
/// Holds instructions that need to sink past other instructions to handle
/// first-order recurrences.
MapVector<Instruction *, Instruction *> SinkAfter;
/// 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
SmallPtrSet<const Instruction *, 8> MaskedOp;
/// Assume instructions in predicated blocks must be dropped if the CFG gets
/// flattened.
SmallPtrSet<Instruction *, 8> ConditionalAssumes;
/// BFI and PSI are used to check for profile guided size optimizations.
BlockFrequencyInfo *BFI;
ProfileSummaryInfo *PSI;
};
} // namespace llvm
#endif // LLVM_TRANSFORMS_VECTORIZE_LOOPVECTORIZATIONLEGALITY_H