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96cc0219ad
This change enables vectorization of multiple exit loops when the exit count is statically computable. That requirement - shared with the rest of LV - in turn requires each exit to be analyzeable and to dominate the latch. The majority of work to support this was done in a set of previous patches. In particular,, 72314466 avoids having multiple edges from the middle block to the exits, and 4b33b2387 which added support for non-latch single exit and multiple exits with a single exiting block. As a result, this change is basically just removing a bailout and adjusting some tests now that the prerequisite work is done and has stuck in tree for a bit. Differential Revision: https://reviews.llvm.org/D105817
1304 lines
50 KiB
C++
1304 lines
50 KiB
C++
//===- LoopVectorizationLegality.cpp --------------------------------------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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//
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// This file provides loop vectorization legality analysis. Original code
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// resided in LoopVectorize.cpp for a long time.
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//
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// At this point, it is implemented as a utility class, not as an analysis
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// pass. It should be easy to create an analysis pass around it if there
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// is a need (but D45420 needs to happen first).
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//
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#include "llvm/Transforms/Vectorize/LoopVectorizationLegality.h"
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#include "llvm/Analysis/Loads.h"
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#include "llvm/Analysis/LoopInfo.h"
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#include "llvm/Analysis/TargetLibraryInfo.h"
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#include "llvm/Analysis/ValueTracking.h"
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#include "llvm/Analysis/VectorUtils.h"
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#include "llvm/IR/IntrinsicInst.h"
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#include "llvm/IR/PatternMatch.h"
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#include "llvm/Transforms/Utils/SizeOpts.h"
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#include "llvm/Transforms/Vectorize/LoopVectorize.h"
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using namespace llvm;
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using namespace PatternMatch;
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#define LV_NAME "loop-vectorize"
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#define DEBUG_TYPE LV_NAME
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extern cl::opt<bool> EnableVPlanPredication;
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static cl::opt<bool>
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EnableIfConversion("enable-if-conversion", cl::init(true), cl::Hidden,
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cl::desc("Enable if-conversion during vectorization."));
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namespace llvm {
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cl::opt<bool>
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HintsAllowReordering("hints-allow-reordering", cl::init(true), cl::Hidden,
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cl::desc("Allow enabling loop hints to reorder "
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"FP operations during vectorization."));
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}
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// TODO: Move size-based thresholds out of legality checking, make cost based
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// decisions instead of hard thresholds.
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static cl::opt<unsigned> VectorizeSCEVCheckThreshold(
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"vectorize-scev-check-threshold", cl::init(16), cl::Hidden,
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cl::desc("The maximum number of SCEV checks allowed."));
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static cl::opt<unsigned> PragmaVectorizeSCEVCheckThreshold(
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"pragma-vectorize-scev-check-threshold", cl::init(128), cl::Hidden,
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cl::desc("The maximum number of SCEV checks allowed with a "
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"vectorize(enable) pragma"));
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// FIXME: When scalable vectorization is stable enough, change the default
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// to SK_PreferFixedWidth.
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static cl::opt<LoopVectorizeHints::ScalableForceKind> ScalableVectorization(
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"scalable-vectorization", cl::init(LoopVectorizeHints::SK_FixedWidthOnly),
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cl::Hidden,
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cl::desc("Control whether the compiler can use scalable vectors to "
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"vectorize a loop"),
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cl::values(
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clEnumValN(LoopVectorizeHints::SK_FixedWidthOnly, "off",
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"Scalable vectorization is disabled."),
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clEnumValN(LoopVectorizeHints::SK_PreferFixedWidth, "on",
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"Scalable vectorization is available, but favor fixed-width "
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"vectorization when the cost is inconclusive."),
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clEnumValN(LoopVectorizeHints::SK_PreferScalable, "preferred",
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"Scalable vectorization is available and favored when the "
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"cost is inconclusive.")));
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/// Maximum vectorization interleave count.
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static const unsigned MaxInterleaveFactor = 16;
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namespace llvm {
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bool LoopVectorizeHints::Hint::validate(unsigned Val) {
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switch (Kind) {
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case HK_WIDTH:
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return isPowerOf2_32(Val) && Val <= VectorizerParams::MaxVectorWidth;
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case HK_INTERLEAVE:
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return isPowerOf2_32(Val) && Val <= MaxInterleaveFactor;
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case HK_FORCE:
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return (Val <= 1);
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case HK_ISVECTORIZED:
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case HK_PREDICATE:
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case HK_SCALABLE:
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return (Val == 0 || Val == 1);
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}
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return false;
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}
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LoopVectorizeHints::LoopVectorizeHints(const Loop *L,
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bool InterleaveOnlyWhenForced,
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OptimizationRemarkEmitter &ORE)
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: Width("vectorize.width", VectorizerParams::VectorizationFactor, HK_WIDTH),
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Interleave("interleave.count", InterleaveOnlyWhenForced, HK_INTERLEAVE),
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Force("vectorize.enable", FK_Undefined, HK_FORCE),
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IsVectorized("isvectorized", 0, HK_ISVECTORIZED),
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Predicate("vectorize.predicate.enable", FK_Undefined, HK_PREDICATE),
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Scalable("vectorize.scalable.enable", SK_Unspecified, HK_SCALABLE),
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TheLoop(L), ORE(ORE) {
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// Populate values with existing loop metadata.
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getHintsFromMetadata();
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// force-vector-interleave overrides DisableInterleaving.
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if (VectorizerParams::isInterleaveForced())
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Interleave.Value = VectorizerParams::VectorizationInterleave;
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if ((LoopVectorizeHints::ScalableForceKind)Scalable.Value == SK_Unspecified)
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// If the width is set, but the metadata says nothing about the scalable
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// property, then assume it concerns only a fixed-width UserVF.
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// If width is not set, the flag takes precedence.
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Scalable.Value = Width.Value ? SK_FixedWidthOnly : ScalableVectorization;
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else if (ScalableVectorization == SK_FixedWidthOnly)
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// If the flag is set to disable any use of scalable vectors, override the
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// loop hint.
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Scalable.Value = SK_FixedWidthOnly;
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if (IsVectorized.Value != 1)
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// If the vectorization width and interleaving count are both 1 then
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// consider the loop to have been already vectorized because there's
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// nothing more that we can do.
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IsVectorized.Value =
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getWidth() == ElementCount::getFixed(1) && getInterleave() == 1;
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LLVM_DEBUG(if (InterleaveOnlyWhenForced && getInterleave() == 1) dbgs()
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<< "LV: Interleaving disabled by the pass manager\n");
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}
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void LoopVectorizeHints::setAlreadyVectorized() {
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LLVMContext &Context = TheLoop->getHeader()->getContext();
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MDNode *IsVectorizedMD = MDNode::get(
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Context,
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{MDString::get(Context, "llvm.loop.isvectorized"),
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ConstantAsMetadata::get(ConstantInt::get(Context, APInt(32, 1)))});
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MDNode *LoopID = TheLoop->getLoopID();
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MDNode *NewLoopID =
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makePostTransformationMetadata(Context, LoopID,
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{Twine(Prefix(), "vectorize.").str(),
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Twine(Prefix(), "interleave.").str()},
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{IsVectorizedMD});
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TheLoop->setLoopID(NewLoopID);
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// Update internal cache.
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IsVectorized.Value = 1;
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}
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bool LoopVectorizeHints::allowVectorization(
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Function *F, Loop *L, bool VectorizeOnlyWhenForced) const {
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if (getForce() == LoopVectorizeHints::FK_Disabled) {
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LLVM_DEBUG(dbgs() << "LV: Not vectorizing: #pragma vectorize disable.\n");
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emitRemarkWithHints();
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return false;
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}
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if (VectorizeOnlyWhenForced && getForce() != LoopVectorizeHints::FK_Enabled) {
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LLVM_DEBUG(dbgs() << "LV: Not vectorizing: No #pragma vectorize enable.\n");
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emitRemarkWithHints();
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return false;
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}
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if (getIsVectorized() == 1) {
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LLVM_DEBUG(dbgs() << "LV: Not vectorizing: Disabled/already vectorized.\n");
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// FIXME: Add interleave.disable metadata. This will allow
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// vectorize.disable to be used without disabling the pass and errors
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// to differentiate between disabled vectorization and a width of 1.
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ORE.emit([&]() {
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return OptimizationRemarkAnalysis(vectorizeAnalysisPassName(),
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"AllDisabled", L->getStartLoc(),
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L->getHeader())
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<< "loop not vectorized: vectorization and interleaving are "
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"explicitly disabled, or the loop has already been "
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"vectorized";
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});
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return false;
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}
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return true;
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}
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void LoopVectorizeHints::emitRemarkWithHints() const {
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using namespace ore;
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ORE.emit([&]() {
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if (Force.Value == LoopVectorizeHints::FK_Disabled)
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return OptimizationRemarkMissed(LV_NAME, "MissedExplicitlyDisabled",
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TheLoop->getStartLoc(),
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TheLoop->getHeader())
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<< "loop not vectorized: vectorization is explicitly disabled";
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else {
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OptimizationRemarkMissed R(LV_NAME, "MissedDetails",
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TheLoop->getStartLoc(), TheLoop->getHeader());
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R << "loop not vectorized";
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if (Force.Value == LoopVectorizeHints::FK_Enabled) {
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R << " (Force=" << NV("Force", true);
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if (Width.Value != 0)
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R << ", Vector Width=" << NV("VectorWidth", getWidth());
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if (getInterleave() != 0)
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R << ", Interleave Count=" << NV("InterleaveCount", getInterleave());
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R << ")";
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}
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return R;
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}
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});
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}
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const char *LoopVectorizeHints::vectorizeAnalysisPassName() const {
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if (getWidth() == ElementCount::getFixed(1))
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return LV_NAME;
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if (getForce() == LoopVectorizeHints::FK_Disabled)
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return LV_NAME;
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if (getForce() == LoopVectorizeHints::FK_Undefined && getWidth().isZero())
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return LV_NAME;
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return OptimizationRemarkAnalysis::AlwaysPrint;
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}
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bool LoopVectorizeHints::allowReordering() const {
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// Allow the vectorizer to change the order of operations if enabling
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// loop hints are provided
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ElementCount EC = getWidth();
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return HintsAllowReordering &&
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(getForce() == LoopVectorizeHints::FK_Enabled ||
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EC.getKnownMinValue() > 1);
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}
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void LoopVectorizeHints::getHintsFromMetadata() {
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MDNode *LoopID = TheLoop->getLoopID();
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if (!LoopID)
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return;
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// First operand should refer to the loop id itself.
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assert(LoopID->getNumOperands() > 0 && "requires at least one operand");
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assert(LoopID->getOperand(0) == LoopID && "invalid loop id");
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for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) {
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const MDString *S = nullptr;
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SmallVector<Metadata *, 4> Args;
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// The expected hint is either a MDString or a MDNode with the first
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// operand a MDString.
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if (const MDNode *MD = dyn_cast<MDNode>(LoopID->getOperand(i))) {
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if (!MD || MD->getNumOperands() == 0)
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continue;
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S = dyn_cast<MDString>(MD->getOperand(0));
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for (unsigned i = 1, ie = MD->getNumOperands(); i < ie; ++i)
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Args.push_back(MD->getOperand(i));
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} else {
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S = dyn_cast<MDString>(LoopID->getOperand(i));
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assert(Args.size() == 0 && "too many arguments for MDString");
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}
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if (!S)
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continue;
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// Check if the hint starts with the loop metadata prefix.
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StringRef Name = S->getString();
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if (Args.size() == 1)
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setHint(Name, Args[0]);
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}
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}
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void LoopVectorizeHints::setHint(StringRef Name, Metadata *Arg) {
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if (!Name.startswith(Prefix()))
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return;
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Name = Name.substr(Prefix().size(), StringRef::npos);
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const ConstantInt *C = mdconst::dyn_extract<ConstantInt>(Arg);
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if (!C)
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return;
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unsigned Val = C->getZExtValue();
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Hint *Hints[] = {&Width, &Interleave, &Force,
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&IsVectorized, &Predicate, &Scalable};
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for (auto H : Hints) {
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if (Name == H->Name) {
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if (H->validate(Val))
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H->Value = Val;
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else
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LLVM_DEBUG(dbgs() << "LV: ignoring invalid hint '" << Name << "'\n");
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break;
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}
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}
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}
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// Return true if the inner loop \p Lp is uniform with regard to the outer loop
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// \p OuterLp (i.e., if the outer loop is vectorized, all the vector lanes
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// executing the inner loop will execute the same iterations). This check is
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// very constrained for now but it will be relaxed in the future. \p Lp is
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// considered uniform if it meets all the following conditions:
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// 1) it has a canonical IV (starting from 0 and with stride 1),
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// 2) its latch terminator is a conditional branch and,
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// 3) its latch condition is a compare instruction whose operands are the
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// canonical IV and an OuterLp invariant.
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// This check doesn't take into account the uniformity of other conditions not
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// related to the loop latch because they don't affect the loop uniformity.
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//
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// NOTE: We decided to keep all these checks and its associated documentation
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// together so that we can easily have a picture of the current supported loop
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// nests. However, some of the current checks don't depend on \p OuterLp and
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// would be redundantly executed for each \p Lp if we invoked this function for
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// different candidate outer loops. This is not the case for now because we
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// don't currently have the infrastructure to evaluate multiple candidate outer
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// loops and \p OuterLp will be a fixed parameter while we only support explicit
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// outer loop vectorization. It's also very likely that these checks go away
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// before introducing the aforementioned infrastructure. However, if this is not
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// the case, we should move the \p OuterLp independent checks to a separate
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// function that is only executed once for each \p Lp.
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static bool isUniformLoop(Loop *Lp, Loop *OuterLp) {
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assert(Lp->getLoopLatch() && "Expected loop with a single latch.");
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// If Lp is the outer loop, it's uniform by definition.
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if (Lp == OuterLp)
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return true;
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assert(OuterLp->contains(Lp) && "OuterLp must contain Lp.");
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// 1.
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PHINode *IV = Lp->getCanonicalInductionVariable();
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if (!IV) {
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LLVM_DEBUG(dbgs() << "LV: Canonical IV not found.\n");
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return false;
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}
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// 2.
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BasicBlock *Latch = Lp->getLoopLatch();
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auto *LatchBr = dyn_cast<BranchInst>(Latch->getTerminator());
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if (!LatchBr || LatchBr->isUnconditional()) {
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LLVM_DEBUG(dbgs() << "LV: Unsupported loop latch branch.\n");
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return false;
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}
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// 3.
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auto *LatchCmp = dyn_cast<CmpInst>(LatchBr->getCondition());
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if (!LatchCmp) {
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LLVM_DEBUG(
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dbgs() << "LV: Loop latch condition is not a compare instruction.\n");
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return false;
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}
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Value *CondOp0 = LatchCmp->getOperand(0);
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Value *CondOp1 = LatchCmp->getOperand(1);
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Value *IVUpdate = IV->getIncomingValueForBlock(Latch);
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if (!(CondOp0 == IVUpdate && OuterLp->isLoopInvariant(CondOp1)) &&
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!(CondOp1 == IVUpdate && OuterLp->isLoopInvariant(CondOp0))) {
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LLVM_DEBUG(dbgs() << "LV: Loop latch condition is not uniform.\n");
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return false;
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}
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return true;
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}
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// Return true if \p Lp and all its nested loops are uniform with regard to \p
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// OuterLp.
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static bool isUniformLoopNest(Loop *Lp, Loop *OuterLp) {
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if (!isUniformLoop(Lp, OuterLp))
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return false;
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// Check if nested loops are uniform.
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for (Loop *SubLp : *Lp)
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if (!isUniformLoopNest(SubLp, OuterLp))
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return false;
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return true;
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}
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/// Check whether it is safe to if-convert this phi node.
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///
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/// Phi nodes with constant expressions that can trap are not safe to if
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/// convert.
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static bool canIfConvertPHINodes(BasicBlock *BB) {
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for (PHINode &Phi : BB->phis()) {
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for (Value *V : Phi.incoming_values())
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if (auto *C = dyn_cast<Constant>(V))
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if (C->canTrap())
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return false;
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}
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return true;
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}
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static Type *convertPointerToIntegerType(const DataLayout &DL, Type *Ty) {
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if (Ty->isPointerTy())
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return DL.getIntPtrType(Ty);
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// It is possible that char's or short's overflow when we ask for the loop's
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// trip count, work around this by changing the type size.
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if (Ty->getScalarSizeInBits() < 32)
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return Type::getInt32Ty(Ty->getContext());
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return Ty;
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}
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static Type *getWiderType(const DataLayout &DL, Type *Ty0, Type *Ty1) {
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Ty0 = convertPointerToIntegerType(DL, Ty0);
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Ty1 = convertPointerToIntegerType(DL, Ty1);
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if (Ty0->getScalarSizeInBits() > Ty1->getScalarSizeInBits())
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return Ty0;
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return Ty1;
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}
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/// Check that the instruction has outside loop users and is not an
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/// identified reduction variable.
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static bool hasOutsideLoopUser(const Loop *TheLoop, Instruction *Inst,
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SmallPtrSetImpl<Value *> &AllowedExit) {
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// Reductions, Inductions and non-header phis are allowed to have exit users. All
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// other instructions must not have external users.
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if (!AllowedExit.count(Inst))
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// Check that all of the users of the loop are inside the BB.
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for (User *U : Inst->users()) {
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Instruction *UI = cast<Instruction>(U);
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// This user may be a reduction exit value.
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if (!TheLoop->contains(UI)) {
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LLVM_DEBUG(dbgs() << "LV: Found an outside user for : " << *UI << '\n');
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return true;
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}
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}
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return false;
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}
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int LoopVectorizationLegality::isConsecutivePtr(Value *Ptr) const {
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const ValueToValueMap &Strides =
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getSymbolicStrides() ? *getSymbolicStrides() : ValueToValueMap();
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Function *F = TheLoop->getHeader()->getParent();
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bool OptForSize = F->hasOptSize() ||
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llvm::shouldOptimizeForSize(TheLoop->getHeader(), PSI, BFI,
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PGSOQueryType::IRPass);
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bool CanAddPredicate = !OptForSize;
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int Stride = getPtrStride(PSE, Ptr, TheLoop, Strides, CanAddPredicate, false);
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if (Stride == 1 || Stride == -1)
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return Stride;
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return 0;
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}
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bool LoopVectorizationLegality::isUniform(Value *V) {
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return LAI->isUniform(V);
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}
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bool LoopVectorizationLegality::canVectorizeOuterLoop() {
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assert(!TheLoop->isInnermost() && "We are not vectorizing an outer loop.");
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// Store the result and return it at the end instead of exiting early, in case
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// allowExtraAnalysis is used to report multiple reasons for not vectorizing.
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bool Result = true;
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bool DoExtraAnalysis = ORE->allowExtraAnalysis(DEBUG_TYPE);
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for (BasicBlock *BB : TheLoop->blocks()) {
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// Check whether the BB terminator is a BranchInst. Any other terminator is
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// not supported yet.
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auto *Br = dyn_cast<BranchInst>(BB->getTerminator());
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if (!Br) {
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reportVectorizationFailure("Unsupported basic block terminator",
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"loop control flow is not understood by vectorizer",
|
|
"CFGNotUnderstood", ORE, TheLoop);
|
|
if (DoExtraAnalysis)
|
|
Result = false;
|
|
else
|
|
return false;
|
|
}
|
|
|
|
// Check whether the BranchInst is a supported one. Only unconditional
|
|
// branches, conditional branches with an outer loop invariant condition or
|
|
// backedges are supported.
|
|
// FIXME: We skip these checks when VPlan predication is enabled as we
|
|
// want to allow divergent branches. This whole check will be removed
|
|
// once VPlan predication is on by default.
|
|
if (!EnableVPlanPredication && Br && Br->isConditional() &&
|
|
!TheLoop->isLoopInvariant(Br->getCondition()) &&
|
|
!LI->isLoopHeader(Br->getSuccessor(0)) &&
|
|
!LI->isLoopHeader(Br->getSuccessor(1))) {
|
|
reportVectorizationFailure("Unsupported conditional branch",
|
|
"loop control flow is not understood by vectorizer",
|
|
"CFGNotUnderstood", ORE, TheLoop);
|
|
if (DoExtraAnalysis)
|
|
Result = false;
|
|
else
|
|
return false;
|
|
}
|
|
}
|
|
|
|
// Check whether inner loops are uniform. At this point, we only support
|
|
// simple outer loops scenarios with uniform nested loops.
|
|
if (!isUniformLoopNest(TheLoop /*loop nest*/,
|
|
TheLoop /*context outer loop*/)) {
|
|
reportVectorizationFailure("Outer loop contains divergent loops",
|
|
"loop control flow is not understood by vectorizer",
|
|
"CFGNotUnderstood", ORE, TheLoop);
|
|
if (DoExtraAnalysis)
|
|
Result = false;
|
|
else
|
|
return false;
|
|
}
|
|
|
|
// Check whether we are able to set up outer loop induction.
|
|
if (!setupOuterLoopInductions()) {
|
|
reportVectorizationFailure("Unsupported outer loop Phi(s)",
|
|
"Unsupported outer loop Phi(s)",
|
|
"UnsupportedPhi", ORE, TheLoop);
|
|
if (DoExtraAnalysis)
|
|
Result = false;
|
|
else
|
|
return false;
|
|
}
|
|
|
|
return Result;
|
|
}
|
|
|
|
void LoopVectorizationLegality::addInductionPhi(
|
|
PHINode *Phi, const InductionDescriptor &ID,
|
|
SmallPtrSetImpl<Value *> &AllowedExit) {
|
|
Inductions[Phi] = ID;
|
|
|
|
// In case this induction also comes with casts that we know we can ignore
|
|
// in the vectorized loop body, record them here. All casts could be recorded
|
|
// here for ignoring, but suffices to record only the first (as it is the
|
|
// only one that may bw used outside the cast sequence).
|
|
const SmallVectorImpl<Instruction *> &Casts = ID.getCastInsts();
|
|
if (!Casts.empty())
|
|
InductionCastsToIgnore.insert(*Casts.begin());
|
|
|
|
Type *PhiTy = Phi->getType();
|
|
const DataLayout &DL = Phi->getModule()->getDataLayout();
|
|
|
|
// Get the widest type.
|
|
if (!PhiTy->isFloatingPointTy()) {
|
|
if (!WidestIndTy)
|
|
WidestIndTy = convertPointerToIntegerType(DL, PhiTy);
|
|
else
|
|
WidestIndTy = getWiderType(DL, PhiTy, WidestIndTy);
|
|
}
|
|
|
|
// Int inductions are special because we only allow one IV.
|
|
if (ID.getKind() == InductionDescriptor::IK_IntInduction &&
|
|
ID.getConstIntStepValue() && ID.getConstIntStepValue()->isOne() &&
|
|
isa<Constant>(ID.getStartValue()) &&
|
|
cast<Constant>(ID.getStartValue())->isNullValue()) {
|
|
|
|
// Use the phi node with the widest type as induction. Use the last
|
|
// one if there are multiple (no good reason for doing this other
|
|
// than it is expedient). We've checked that it begins at zero and
|
|
// steps by one, so this is a canonical induction variable.
|
|
if (!PrimaryInduction || PhiTy == WidestIndTy)
|
|
PrimaryInduction = Phi;
|
|
}
|
|
|
|
// Both the PHI node itself, and the "post-increment" value feeding
|
|
// back into the PHI node may have external users.
|
|
// We can allow those uses, except if the SCEVs we have for them rely
|
|
// on predicates that only hold within the loop, since allowing the exit
|
|
// currently means re-using this SCEV outside the loop (see PR33706 for more
|
|
// details).
|
|
if (PSE.getUnionPredicate().isAlwaysTrue()) {
|
|
AllowedExit.insert(Phi);
|
|
AllowedExit.insert(Phi->getIncomingValueForBlock(TheLoop->getLoopLatch()));
|
|
}
|
|
|
|
LLVM_DEBUG(dbgs() << "LV: Found an induction variable.\n");
|
|
}
|
|
|
|
bool LoopVectorizationLegality::setupOuterLoopInductions() {
|
|
BasicBlock *Header = TheLoop->getHeader();
|
|
|
|
// Returns true if a given Phi is a supported induction.
|
|
auto isSupportedPhi = [&](PHINode &Phi) -> bool {
|
|
InductionDescriptor ID;
|
|
if (InductionDescriptor::isInductionPHI(&Phi, TheLoop, PSE, ID) &&
|
|
ID.getKind() == InductionDescriptor::IK_IntInduction) {
|
|
addInductionPhi(&Phi, ID, AllowedExit);
|
|
return true;
|
|
} else {
|
|
// Bail out for any Phi in the outer loop header that is not a supported
|
|
// induction.
|
|
LLVM_DEBUG(
|
|
dbgs()
|
|
<< "LV: Found unsupported PHI for outer loop vectorization.\n");
|
|
return false;
|
|
}
|
|
};
|
|
|
|
if (llvm::all_of(Header->phis(), isSupportedPhi))
|
|
return true;
|
|
else
|
|
return false;
|
|
}
|
|
|
|
/// Checks if a function is scalarizable according to the TLI, in
|
|
/// the sense that it should be vectorized and then expanded in
|
|
/// multiple scalar calls. This is represented in the
|
|
/// TLI via mappings that do not specify a vector name, as in the
|
|
/// following example:
|
|
///
|
|
/// const VecDesc VecIntrinsics[] = {
|
|
/// {"llvm.phx.abs.i32", "", 4}
|
|
/// };
|
|
static bool isTLIScalarize(const TargetLibraryInfo &TLI, const CallInst &CI) {
|
|
const StringRef ScalarName = CI.getCalledFunction()->getName();
|
|
bool Scalarize = TLI.isFunctionVectorizable(ScalarName);
|
|
// Check that all known VFs are not associated to a vector
|
|
// function, i.e. the vector name is emty.
|
|
if (Scalarize) {
|
|
ElementCount WidestFixedVF, WidestScalableVF;
|
|
TLI.getWidestVF(ScalarName, WidestFixedVF, WidestScalableVF);
|
|
for (ElementCount VF = ElementCount::getFixed(2);
|
|
ElementCount::isKnownLE(VF, WidestFixedVF); VF *= 2)
|
|
Scalarize &= !TLI.isFunctionVectorizable(ScalarName, VF);
|
|
for (ElementCount VF = ElementCount::getScalable(1);
|
|
ElementCount::isKnownLE(VF, WidestScalableVF); VF *= 2)
|
|
Scalarize &= !TLI.isFunctionVectorizable(ScalarName, VF);
|
|
assert((WidestScalableVF.isZero() || !Scalarize) &&
|
|
"Caller may decide to scalarize a variant using a scalable VF");
|
|
}
|
|
return Scalarize;
|
|
}
|
|
|
|
bool LoopVectorizationLegality::canVectorizeInstrs() {
|
|
BasicBlock *Header = TheLoop->getHeader();
|
|
|
|
// For each block in the loop.
|
|
for (BasicBlock *BB : TheLoop->blocks()) {
|
|
// Scan the instructions in the block and look for hazards.
|
|
for (Instruction &I : *BB) {
|
|
if (auto *Phi = dyn_cast<PHINode>(&I)) {
|
|
Type *PhiTy = Phi->getType();
|
|
// Check that this PHI type is allowed.
|
|
if (!PhiTy->isIntegerTy() && !PhiTy->isFloatingPointTy() &&
|
|
!PhiTy->isPointerTy()) {
|
|
reportVectorizationFailure("Found a non-int non-pointer PHI",
|
|
"loop control flow is not understood by vectorizer",
|
|
"CFGNotUnderstood", ORE, TheLoop);
|
|
return false;
|
|
}
|
|
|
|
// If this PHINode is not in the header block, then we know that we
|
|
// can convert it to select during if-conversion. No need to check if
|
|
// the PHIs in this block are induction or reduction variables.
|
|
if (BB != Header) {
|
|
// Non-header phi nodes that have outside uses can be vectorized. Add
|
|
// them to the list of allowed exits.
|
|
// Unsafe cyclic dependencies with header phis are identified during
|
|
// legalization for reduction, induction and first order
|
|
// recurrences.
|
|
AllowedExit.insert(&I);
|
|
continue;
|
|
}
|
|
|
|
// We only allow if-converted PHIs with exactly two incoming values.
|
|
if (Phi->getNumIncomingValues() != 2) {
|
|
reportVectorizationFailure("Found an invalid PHI",
|
|
"loop control flow is not understood by vectorizer",
|
|
"CFGNotUnderstood", ORE, TheLoop, Phi);
|
|
return false;
|
|
}
|
|
|
|
RecurrenceDescriptor RedDes;
|
|
if (RecurrenceDescriptor::isReductionPHI(Phi, TheLoop, RedDes, DB, AC,
|
|
DT)) {
|
|
Requirements->addExactFPMathInst(RedDes.getExactFPMathInst());
|
|
AllowedExit.insert(RedDes.getLoopExitInstr());
|
|
Reductions[Phi] = RedDes;
|
|
continue;
|
|
}
|
|
|
|
// TODO: Instead of recording the AllowedExit, it would be good to record the
|
|
// complementary set: NotAllowedExit. These include (but may not be
|
|
// limited to):
|
|
// 1. Reduction phis as they represent the one-before-last value, which
|
|
// is not available when vectorized
|
|
// 2. Induction phis and increment when SCEV predicates cannot be used
|
|
// outside the loop - see addInductionPhi
|
|
// 3. Non-Phis with outside uses when SCEV predicates cannot be used
|
|
// outside the loop - see call to hasOutsideLoopUser in the non-phi
|
|
// handling below
|
|
// 4. FirstOrderRecurrence phis that can possibly be handled by
|
|
// extraction.
|
|
// By recording these, we can then reason about ways to vectorize each
|
|
// of these NotAllowedExit.
|
|
InductionDescriptor ID;
|
|
if (InductionDescriptor::isInductionPHI(Phi, TheLoop, PSE, ID)) {
|
|
addInductionPhi(Phi, ID, AllowedExit);
|
|
Requirements->addExactFPMathInst(ID.getExactFPMathInst());
|
|
continue;
|
|
}
|
|
|
|
if (RecurrenceDescriptor::isFirstOrderRecurrence(Phi, TheLoop,
|
|
SinkAfter, DT)) {
|
|
AllowedExit.insert(Phi);
|
|
FirstOrderRecurrences.insert(Phi);
|
|
continue;
|
|
}
|
|
|
|
// As a last resort, coerce the PHI to a AddRec expression
|
|
// and re-try classifying it a an induction PHI.
|
|
if (InductionDescriptor::isInductionPHI(Phi, TheLoop, PSE, ID, true)) {
|
|
addInductionPhi(Phi, ID, AllowedExit);
|
|
continue;
|
|
}
|
|
|
|
reportVectorizationFailure("Found an unidentified PHI",
|
|
"value that could not be identified as "
|
|
"reduction is used outside the loop",
|
|
"NonReductionValueUsedOutsideLoop", ORE, TheLoop, Phi);
|
|
return false;
|
|
} // end of PHI handling
|
|
|
|
// We handle calls that:
|
|
// * Are debug info intrinsics.
|
|
// * Have a mapping to an IR intrinsic.
|
|
// * Have a vector version available.
|
|
auto *CI = dyn_cast<CallInst>(&I);
|
|
|
|
if (CI && !getVectorIntrinsicIDForCall(CI, TLI) &&
|
|
!isa<DbgInfoIntrinsic>(CI) &&
|
|
!(CI->getCalledFunction() && TLI &&
|
|
(!VFDatabase::getMappings(*CI).empty() ||
|
|
isTLIScalarize(*TLI, *CI)))) {
|
|
// If the call is a recognized math libary call, it is likely that
|
|
// we can vectorize it given loosened floating-point constraints.
|
|
LibFunc Func;
|
|
bool IsMathLibCall =
|
|
TLI && CI->getCalledFunction() &&
|
|
CI->getType()->isFloatingPointTy() &&
|
|
TLI->getLibFunc(CI->getCalledFunction()->getName(), Func) &&
|
|
TLI->hasOptimizedCodeGen(Func);
|
|
|
|
if (IsMathLibCall) {
|
|
// TODO: Ideally, we should not use clang-specific language here,
|
|
// but it's hard to provide meaningful yet generic advice.
|
|
// Also, should this be guarded by allowExtraAnalysis() and/or be part
|
|
// of the returned info from isFunctionVectorizable()?
|
|
reportVectorizationFailure(
|
|
"Found a non-intrinsic callsite",
|
|
"library call cannot be vectorized. "
|
|
"Try compiling with -fno-math-errno, -ffast-math, "
|
|
"or similar flags",
|
|
"CantVectorizeLibcall", ORE, TheLoop, CI);
|
|
} else {
|
|
reportVectorizationFailure("Found a non-intrinsic callsite",
|
|
"call instruction cannot be vectorized",
|
|
"CantVectorizeLibcall", ORE, TheLoop, CI);
|
|
}
|
|
return false;
|
|
}
|
|
|
|
// Some intrinsics have scalar arguments and should be same in order for
|
|
// them to be vectorized (i.e. loop invariant).
|
|
if (CI) {
|
|
auto *SE = PSE.getSE();
|
|
Intrinsic::ID IntrinID = getVectorIntrinsicIDForCall(CI, TLI);
|
|
for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i)
|
|
if (hasVectorInstrinsicScalarOpd(IntrinID, i)) {
|
|
if (!SE->isLoopInvariant(PSE.getSCEV(CI->getOperand(i)), TheLoop)) {
|
|
reportVectorizationFailure("Found unvectorizable intrinsic",
|
|
"intrinsic instruction cannot be vectorized",
|
|
"CantVectorizeIntrinsic", ORE, TheLoop, CI);
|
|
return false;
|
|
}
|
|
}
|
|
}
|
|
|
|
// Check that the instruction return type is vectorizable.
|
|
// Also, we can't vectorize extractelement instructions.
|
|
if ((!VectorType::isValidElementType(I.getType()) &&
|
|
!I.getType()->isVoidTy()) ||
|
|
isa<ExtractElementInst>(I)) {
|
|
reportVectorizationFailure("Found unvectorizable type",
|
|
"instruction return type cannot be vectorized",
|
|
"CantVectorizeInstructionReturnType", ORE, TheLoop, &I);
|
|
return false;
|
|
}
|
|
|
|
// Check that the stored type is vectorizable.
|
|
if (auto *ST = dyn_cast<StoreInst>(&I)) {
|
|
Type *T = ST->getValueOperand()->getType();
|
|
if (!VectorType::isValidElementType(T)) {
|
|
reportVectorizationFailure("Store instruction cannot be vectorized",
|
|
"store instruction cannot be vectorized",
|
|
"CantVectorizeStore", ORE, TheLoop, ST);
|
|
return false;
|
|
}
|
|
|
|
// For nontemporal stores, check that a nontemporal vector version is
|
|
// supported on the target.
|
|
if (ST->getMetadata(LLVMContext::MD_nontemporal)) {
|
|
// Arbitrarily try a vector of 2 elements.
|
|
auto *VecTy = FixedVectorType::get(T, /*NumElts=*/2);
|
|
assert(VecTy && "did not find vectorized version of stored type");
|
|
if (!TTI->isLegalNTStore(VecTy, ST->getAlign())) {
|
|
reportVectorizationFailure(
|
|
"nontemporal store instruction cannot be vectorized",
|
|
"nontemporal store instruction cannot be vectorized",
|
|
"CantVectorizeNontemporalStore", ORE, TheLoop, ST);
|
|
return false;
|
|
}
|
|
}
|
|
|
|
} else if (auto *LD = dyn_cast<LoadInst>(&I)) {
|
|
if (LD->getMetadata(LLVMContext::MD_nontemporal)) {
|
|
// For nontemporal loads, check that a nontemporal vector version is
|
|
// supported on the target (arbitrarily try a vector of 2 elements).
|
|
auto *VecTy = FixedVectorType::get(I.getType(), /*NumElts=*/2);
|
|
assert(VecTy && "did not find vectorized version of load type");
|
|
if (!TTI->isLegalNTLoad(VecTy, LD->getAlign())) {
|
|
reportVectorizationFailure(
|
|
"nontemporal load instruction cannot be vectorized",
|
|
"nontemporal load instruction cannot be vectorized",
|
|
"CantVectorizeNontemporalLoad", ORE, TheLoop, LD);
|
|
return false;
|
|
}
|
|
}
|
|
|
|
// FP instructions can allow unsafe algebra, thus vectorizable by
|
|
// non-IEEE-754 compliant SIMD units.
|
|
// This applies to floating-point math operations and calls, not memory
|
|
// operations, shuffles, or casts, as they don't change precision or
|
|
// semantics.
|
|
} else if (I.getType()->isFloatingPointTy() && (CI || I.isBinaryOp()) &&
|
|
!I.isFast()) {
|
|
LLVM_DEBUG(dbgs() << "LV: Found FP op with unsafe algebra.\n");
|
|
Hints->setPotentiallyUnsafe();
|
|
}
|
|
|
|
// Reduction instructions are allowed to have exit users.
|
|
// All other instructions must not have external users.
|
|
if (hasOutsideLoopUser(TheLoop, &I, AllowedExit)) {
|
|
// We can safely vectorize loops where instructions within the loop are
|
|
// used outside the loop only if the SCEV predicates within the loop is
|
|
// same as outside the loop. Allowing the exit means reusing the SCEV
|
|
// outside the loop.
|
|
if (PSE.getUnionPredicate().isAlwaysTrue()) {
|
|
AllowedExit.insert(&I);
|
|
continue;
|
|
}
|
|
reportVectorizationFailure("Value cannot be used outside the loop",
|
|
"value cannot be used outside the loop",
|
|
"ValueUsedOutsideLoop", ORE, TheLoop, &I);
|
|
return false;
|
|
}
|
|
} // next instr.
|
|
}
|
|
|
|
if (!PrimaryInduction) {
|
|
if (Inductions.empty()) {
|
|
reportVectorizationFailure("Did not find one integer induction var",
|
|
"loop induction variable could not be identified",
|
|
"NoInductionVariable", ORE, TheLoop);
|
|
return false;
|
|
} else if (!WidestIndTy) {
|
|
reportVectorizationFailure("Did not find one integer induction var",
|
|
"integer loop induction variable could not be identified",
|
|
"NoIntegerInductionVariable", ORE, TheLoop);
|
|
return false;
|
|
} else {
|
|
LLVM_DEBUG(dbgs() << "LV: Did not find one integer induction var.\n");
|
|
}
|
|
}
|
|
|
|
// For first order recurrences, we use the previous value (incoming value from
|
|
// the latch) to check if it dominates all users of the recurrence. Bail out
|
|
// if we have to sink such an instruction for another recurrence, as the
|
|
// dominance requirement may not hold after sinking.
|
|
BasicBlock *LoopLatch = TheLoop->getLoopLatch();
|
|
if (any_of(FirstOrderRecurrences, [LoopLatch, this](const PHINode *Phi) {
|
|
Instruction *V =
|
|
cast<Instruction>(Phi->getIncomingValueForBlock(LoopLatch));
|
|
return SinkAfter.find(V) != SinkAfter.end();
|
|
}))
|
|
return false;
|
|
|
|
// Now we know the widest induction type, check if our found induction
|
|
// is the same size. If it's not, unset it here and InnerLoopVectorizer
|
|
// will create another.
|
|
if (PrimaryInduction && WidestIndTy != PrimaryInduction->getType())
|
|
PrimaryInduction = nullptr;
|
|
|
|
return true;
|
|
}
|
|
|
|
bool LoopVectorizationLegality::canVectorizeMemory() {
|
|
LAI = &(*GetLAA)(*TheLoop);
|
|
const OptimizationRemarkAnalysis *LAR = LAI->getReport();
|
|
if (LAR) {
|
|
ORE->emit([&]() {
|
|
return OptimizationRemarkAnalysis(Hints->vectorizeAnalysisPassName(),
|
|
"loop not vectorized: ", *LAR);
|
|
});
|
|
}
|
|
|
|
if (!LAI->canVectorizeMemory())
|
|
return false;
|
|
|
|
if (LAI->hasDependenceInvolvingLoopInvariantAddress()) {
|
|
reportVectorizationFailure("Stores to a uniform address",
|
|
"write to a loop invariant address could not be vectorized",
|
|
"CantVectorizeStoreToLoopInvariantAddress", ORE, TheLoop);
|
|
return false;
|
|
}
|
|
|
|
Requirements->addRuntimePointerChecks(LAI->getNumRuntimePointerChecks());
|
|
PSE.addPredicate(LAI->getPSE().getUnionPredicate());
|
|
return true;
|
|
}
|
|
|
|
bool LoopVectorizationLegality::canVectorizeFPMath(
|
|
bool EnableStrictReductions) {
|
|
|
|
// First check if there is any ExactFP math or if we allow reassociations
|
|
if (!Requirements->getExactFPInst() || Hints->allowReordering())
|
|
return true;
|
|
|
|
// If the above is false, we have ExactFPMath & do not allow reordering.
|
|
// If the EnableStrictReductions flag is set, first check if we have any
|
|
// Exact FP induction vars, which we cannot vectorize.
|
|
if (!EnableStrictReductions ||
|
|
any_of(getInductionVars(), [&](auto &Induction) -> bool {
|
|
InductionDescriptor IndDesc = Induction.second;
|
|
return IndDesc.getExactFPMathInst();
|
|
}))
|
|
return false;
|
|
|
|
// We can now only vectorize if all reductions with Exact FP math also
|
|
// have the isOrdered flag set, which indicates that we can move the
|
|
// reduction operations in-loop.
|
|
return (all_of(getReductionVars(), [&](auto &Reduction) -> bool {
|
|
const RecurrenceDescriptor &RdxDesc = Reduction.second;
|
|
return !RdxDesc.hasExactFPMath() || RdxDesc.isOrdered();
|
|
}));
|
|
}
|
|
|
|
bool LoopVectorizationLegality::isInductionPhi(const Value *V) {
|
|
Value *In0 = const_cast<Value *>(V);
|
|
PHINode *PN = dyn_cast_or_null<PHINode>(In0);
|
|
if (!PN)
|
|
return false;
|
|
|
|
return Inductions.count(PN);
|
|
}
|
|
|
|
bool LoopVectorizationLegality::isCastedInductionVariable(const Value *V) {
|
|
auto *Inst = dyn_cast<Instruction>(V);
|
|
return (Inst && InductionCastsToIgnore.count(Inst));
|
|
}
|
|
|
|
bool LoopVectorizationLegality::isInductionVariable(const Value *V) {
|
|
return isInductionPhi(V) || isCastedInductionVariable(V);
|
|
}
|
|
|
|
bool LoopVectorizationLegality::isFirstOrderRecurrence(const PHINode *Phi) {
|
|
return FirstOrderRecurrences.count(Phi);
|
|
}
|
|
|
|
bool LoopVectorizationLegality::blockNeedsPredication(BasicBlock *BB) const {
|
|
return LoopAccessInfo::blockNeedsPredication(BB, TheLoop, DT);
|
|
}
|
|
|
|
bool LoopVectorizationLegality::blockCanBePredicated(
|
|
BasicBlock *BB, SmallPtrSetImpl<Value *> &SafePtrs,
|
|
SmallPtrSetImpl<const Instruction *> &MaskedOp,
|
|
SmallPtrSetImpl<Instruction *> &ConditionalAssumes) const {
|
|
for (Instruction &I : *BB) {
|
|
// Check that we don't have a constant expression that can trap as operand.
|
|
for (Value *Operand : I.operands()) {
|
|
if (auto *C = dyn_cast<Constant>(Operand))
|
|
if (C->canTrap())
|
|
return false;
|
|
}
|
|
|
|
// We can predicate blocks with calls to assume, as long as we drop them in
|
|
// case we flatten the CFG via predication.
|
|
if (match(&I, m_Intrinsic<Intrinsic::assume>())) {
|
|
ConditionalAssumes.insert(&I);
|
|
continue;
|
|
}
|
|
|
|
// Do not let llvm.experimental.noalias.scope.decl block the vectorization.
|
|
// TODO: there might be cases that it should block the vectorization. Let's
|
|
// ignore those for now.
|
|
if (isa<NoAliasScopeDeclInst>(&I))
|
|
continue;
|
|
|
|
// We might be able to hoist the load.
|
|
if (I.mayReadFromMemory()) {
|
|
auto *LI = dyn_cast<LoadInst>(&I);
|
|
if (!LI)
|
|
return false;
|
|
if (!SafePtrs.count(LI->getPointerOperand())) {
|
|
MaskedOp.insert(LI);
|
|
continue;
|
|
}
|
|
}
|
|
|
|
if (I.mayWriteToMemory()) {
|
|
auto *SI = dyn_cast<StoreInst>(&I);
|
|
if (!SI)
|
|
return false;
|
|
// Predicated store requires some form of masking:
|
|
// 1) masked store HW instruction,
|
|
// 2) emulation via load-blend-store (only if safe and legal to do so,
|
|
// be aware on the race conditions), or
|
|
// 3) element-by-element predicate check and scalar store.
|
|
MaskedOp.insert(SI);
|
|
continue;
|
|
}
|
|
if (I.mayThrow())
|
|
return false;
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
bool LoopVectorizationLegality::canVectorizeWithIfConvert() {
|
|
if (!EnableIfConversion) {
|
|
reportVectorizationFailure("If-conversion is disabled",
|
|
"if-conversion is disabled",
|
|
"IfConversionDisabled",
|
|
ORE, TheLoop);
|
|
return false;
|
|
}
|
|
|
|
assert(TheLoop->getNumBlocks() > 1 && "Single block loops are vectorizable");
|
|
|
|
// A list of pointers which are known to be dereferenceable within scope of
|
|
// the loop body for each iteration of the loop which executes. That is,
|
|
// the memory pointed to can be dereferenced (with the access size implied by
|
|
// the value's type) unconditionally within the loop header without
|
|
// introducing a new fault.
|
|
SmallPtrSet<Value *, 8> SafePointers;
|
|
|
|
// Collect safe addresses.
|
|
for (BasicBlock *BB : TheLoop->blocks()) {
|
|
if (!blockNeedsPredication(BB)) {
|
|
for (Instruction &I : *BB)
|
|
if (auto *Ptr = getLoadStorePointerOperand(&I))
|
|
SafePointers.insert(Ptr);
|
|
continue;
|
|
}
|
|
|
|
// For a block which requires predication, a address may be safe to access
|
|
// in the loop w/o predication if we can prove dereferenceability facts
|
|
// sufficient to ensure it'll never fault within the loop. For the moment,
|
|
// we restrict this to loads; stores are more complicated due to
|
|
// concurrency restrictions.
|
|
ScalarEvolution &SE = *PSE.getSE();
|
|
for (Instruction &I : *BB) {
|
|
LoadInst *LI = dyn_cast<LoadInst>(&I);
|
|
if (LI && !LI->getType()->isVectorTy() && !mustSuppressSpeculation(*LI) &&
|
|
isDereferenceableAndAlignedInLoop(LI, TheLoop, SE, *DT))
|
|
SafePointers.insert(LI->getPointerOperand());
|
|
}
|
|
}
|
|
|
|
// Collect the blocks that need predication.
|
|
BasicBlock *Header = TheLoop->getHeader();
|
|
for (BasicBlock *BB : TheLoop->blocks()) {
|
|
// We don't support switch statements inside loops.
|
|
if (!isa<BranchInst>(BB->getTerminator())) {
|
|
reportVectorizationFailure("Loop contains a switch statement",
|
|
"loop contains a switch statement",
|
|
"LoopContainsSwitch", ORE, TheLoop,
|
|
BB->getTerminator());
|
|
return false;
|
|
}
|
|
|
|
// We must be able to predicate all blocks that need to be predicated.
|
|
if (blockNeedsPredication(BB)) {
|
|
if (!blockCanBePredicated(BB, SafePointers, MaskedOp,
|
|
ConditionalAssumes)) {
|
|
reportVectorizationFailure(
|
|
"Control flow cannot be substituted for a select",
|
|
"control flow cannot be substituted for a select",
|
|
"NoCFGForSelect", ORE, TheLoop,
|
|
BB->getTerminator());
|
|
return false;
|
|
}
|
|
} else if (BB != Header && !canIfConvertPHINodes(BB)) {
|
|
reportVectorizationFailure(
|
|
"Control flow cannot be substituted for a select",
|
|
"control flow cannot be substituted for a select",
|
|
"NoCFGForSelect", ORE, TheLoop,
|
|
BB->getTerminator());
|
|
return false;
|
|
}
|
|
}
|
|
|
|
// We can if-convert this loop.
|
|
return true;
|
|
}
|
|
|
|
// Helper function to canVectorizeLoopNestCFG.
|
|
bool LoopVectorizationLegality::canVectorizeLoopCFG(Loop *Lp,
|
|
bool UseVPlanNativePath) {
|
|
assert((UseVPlanNativePath || Lp->isInnermost()) &&
|
|
"VPlan-native path is not enabled.");
|
|
|
|
// TODO: ORE should be improved to show more accurate information when an
|
|
// outer loop can't be vectorized because a nested loop is not understood or
|
|
// legal. Something like: "outer_loop_location: loop not vectorized:
|
|
// (inner_loop_location) loop control flow is not understood by vectorizer".
|
|
|
|
// Store the result and return it at the end instead of exiting early, in case
|
|
// allowExtraAnalysis is used to report multiple reasons for not vectorizing.
|
|
bool Result = true;
|
|
bool DoExtraAnalysis = ORE->allowExtraAnalysis(DEBUG_TYPE);
|
|
|
|
// We must have a loop in canonical form. Loops with indirectbr in them cannot
|
|
// be canonicalized.
|
|
if (!Lp->getLoopPreheader()) {
|
|
reportVectorizationFailure("Loop doesn't have a legal pre-header",
|
|
"loop control flow is not understood by vectorizer",
|
|
"CFGNotUnderstood", ORE, TheLoop);
|
|
if (DoExtraAnalysis)
|
|
Result = false;
|
|
else
|
|
return false;
|
|
}
|
|
|
|
// We must have a single backedge.
|
|
if (Lp->getNumBackEdges() != 1) {
|
|
reportVectorizationFailure("The loop must have a single backedge",
|
|
"loop control flow is not understood by vectorizer",
|
|
"CFGNotUnderstood", ORE, TheLoop);
|
|
if (DoExtraAnalysis)
|
|
Result = false;
|
|
else
|
|
return false;
|
|
}
|
|
|
|
return Result;
|
|
}
|
|
|
|
bool LoopVectorizationLegality::canVectorizeLoopNestCFG(
|
|
Loop *Lp, bool UseVPlanNativePath) {
|
|
// Store the result and return it at the end instead of exiting early, in case
|
|
// allowExtraAnalysis is used to report multiple reasons for not vectorizing.
|
|
bool Result = true;
|
|
bool DoExtraAnalysis = ORE->allowExtraAnalysis(DEBUG_TYPE);
|
|
if (!canVectorizeLoopCFG(Lp, UseVPlanNativePath)) {
|
|
if (DoExtraAnalysis)
|
|
Result = false;
|
|
else
|
|
return false;
|
|
}
|
|
|
|
// Recursively check whether the loop control flow of nested loops is
|
|
// understood.
|
|
for (Loop *SubLp : *Lp)
|
|
if (!canVectorizeLoopNestCFG(SubLp, UseVPlanNativePath)) {
|
|
if (DoExtraAnalysis)
|
|
Result = false;
|
|
else
|
|
return false;
|
|
}
|
|
|
|
return Result;
|
|
}
|
|
|
|
bool LoopVectorizationLegality::canVectorize(bool UseVPlanNativePath) {
|
|
// Store the result and return it at the end instead of exiting early, in case
|
|
// allowExtraAnalysis is used to report multiple reasons for not vectorizing.
|
|
bool Result = true;
|
|
|
|
bool DoExtraAnalysis = ORE->allowExtraAnalysis(DEBUG_TYPE);
|
|
// Check whether the loop-related control flow in the loop nest is expected by
|
|
// vectorizer.
|
|
if (!canVectorizeLoopNestCFG(TheLoop, UseVPlanNativePath)) {
|
|
if (DoExtraAnalysis)
|
|
Result = false;
|
|
else
|
|
return false;
|
|
}
|
|
|
|
// We need to have a loop header.
|
|
LLVM_DEBUG(dbgs() << "LV: Found a loop: " << TheLoop->getHeader()->getName()
|
|
<< '\n');
|
|
|
|
// Specific checks for outer loops. We skip the remaining legal checks at this
|
|
// point because they don't support outer loops.
|
|
if (!TheLoop->isInnermost()) {
|
|
assert(UseVPlanNativePath && "VPlan-native path is not enabled.");
|
|
|
|
if (!canVectorizeOuterLoop()) {
|
|
reportVectorizationFailure("Unsupported outer loop",
|
|
"unsupported outer loop",
|
|
"UnsupportedOuterLoop",
|
|
ORE, TheLoop);
|
|
// TODO: Implement DoExtraAnalysis when subsequent legal checks support
|
|
// outer loops.
|
|
return false;
|
|
}
|
|
|
|
LLVM_DEBUG(dbgs() << "LV: We can vectorize this outer loop!\n");
|
|
return Result;
|
|
}
|
|
|
|
assert(TheLoop->isInnermost() && "Inner loop expected.");
|
|
// Check if we can if-convert non-single-bb loops.
|
|
unsigned NumBlocks = TheLoop->getNumBlocks();
|
|
if (NumBlocks != 1 && !canVectorizeWithIfConvert()) {
|
|
LLVM_DEBUG(dbgs() << "LV: Can't if-convert the loop.\n");
|
|
if (DoExtraAnalysis)
|
|
Result = false;
|
|
else
|
|
return false;
|
|
}
|
|
|
|
// Check if we can vectorize the instructions and CFG in this loop.
|
|
if (!canVectorizeInstrs()) {
|
|
LLVM_DEBUG(dbgs() << "LV: Can't vectorize the instructions or CFG\n");
|
|
if (DoExtraAnalysis)
|
|
Result = false;
|
|
else
|
|
return false;
|
|
}
|
|
|
|
// Go over each instruction and look at memory deps.
|
|
if (!canVectorizeMemory()) {
|
|
LLVM_DEBUG(dbgs() << "LV: Can't vectorize due to memory conflicts\n");
|
|
if (DoExtraAnalysis)
|
|
Result = false;
|
|
else
|
|
return false;
|
|
}
|
|
|
|
LLVM_DEBUG(dbgs() << "LV: We can vectorize this loop"
|
|
<< (LAI->getRuntimePointerChecking()->Need
|
|
? " (with a runtime bound check)"
|
|
: "")
|
|
<< "!\n");
|
|
|
|
unsigned SCEVThreshold = VectorizeSCEVCheckThreshold;
|
|
if (Hints->getForce() == LoopVectorizeHints::FK_Enabled)
|
|
SCEVThreshold = PragmaVectorizeSCEVCheckThreshold;
|
|
|
|
if (PSE.getUnionPredicate().getComplexity() > SCEVThreshold) {
|
|
reportVectorizationFailure("Too many SCEV checks needed",
|
|
"Too many SCEV assumptions need to be made and checked at runtime",
|
|
"TooManySCEVRunTimeChecks", ORE, TheLoop);
|
|
if (DoExtraAnalysis)
|
|
Result = false;
|
|
else
|
|
return false;
|
|
}
|
|
|
|
// Okay! We've done all the tests. If any have failed, return false. Otherwise
|
|
// we can vectorize, and at this point we don't have any other mem analysis
|
|
// which may limit our maximum vectorization factor, so just return true with
|
|
// no restrictions.
|
|
return Result;
|
|
}
|
|
|
|
bool LoopVectorizationLegality::prepareToFoldTailByMasking() {
|
|
|
|
LLVM_DEBUG(dbgs() << "LV: checking if tail can be folded by masking.\n");
|
|
|
|
SmallPtrSet<const Value *, 8> ReductionLiveOuts;
|
|
|
|
for (auto &Reduction : getReductionVars())
|
|
ReductionLiveOuts.insert(Reduction.second.getLoopExitInstr());
|
|
|
|
// TODO: handle non-reduction outside users when tail is folded by masking.
|
|
for (auto *AE : AllowedExit) {
|
|
// Check that all users of allowed exit values are inside the loop or
|
|
// are the live-out of a reduction.
|
|
if (ReductionLiveOuts.count(AE))
|
|
continue;
|
|
for (User *U : AE->users()) {
|
|
Instruction *UI = cast<Instruction>(U);
|
|
if (TheLoop->contains(UI))
|
|
continue;
|
|
LLVM_DEBUG(
|
|
dbgs()
|
|
<< "LV: Cannot fold tail by masking, loop has an outside user for "
|
|
<< *UI << "\n");
|
|
return false;
|
|
}
|
|
}
|
|
|
|
// The list of pointers that we can safely read and write to remains empty.
|
|
SmallPtrSet<Value *, 8> SafePointers;
|
|
|
|
SmallPtrSet<const Instruction *, 8> TmpMaskedOp;
|
|
SmallPtrSet<Instruction *, 8> TmpConditionalAssumes;
|
|
|
|
// Check and mark all blocks for predication, including those that ordinarily
|
|
// do not need predication such as the header block.
|
|
for (BasicBlock *BB : TheLoop->blocks()) {
|
|
if (!blockCanBePredicated(BB, SafePointers, TmpMaskedOp,
|
|
TmpConditionalAssumes)) {
|
|
LLVM_DEBUG(dbgs() << "LV: Cannot fold tail by masking as requested.\n");
|
|
return false;
|
|
}
|
|
}
|
|
|
|
LLVM_DEBUG(dbgs() << "LV: can fold tail by masking.\n");
|
|
|
|
MaskedOp.insert(TmpMaskedOp.begin(), TmpMaskedOp.end());
|
|
ConditionalAssumes.insert(TmpConditionalAssumes.begin(),
|
|
TmpConditionalAssumes.end());
|
|
|
|
return true;
|
|
}
|
|
|
|
} // namespace llvm
|