forked from OSchip/llvm-project
1277 lines
48 KiB
C++
1277 lines
48 KiB
C++
//===- SampleProfile.cpp - Incorporate sample profiles into the IR --------===//
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//
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// The LLVM Compiler Infrastructure
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//
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// This file is distributed under the University of Illinois Open Source
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// License. See LICENSE.TXT for details.
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//
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//===----------------------------------------------------------------------===//
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//
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// This file implements the SampleProfileLoader transformation. This pass
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// reads a profile file generated by a sampling profiler (e.g. Linux Perf -
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// http://perf.wiki.kernel.org/) and generates IR metadata to reflect the
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// profile information in the given profile.
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//
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// This pass generates branch weight annotations on the IR:
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//
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// - prof: Represents branch weights. This annotation is added to branches
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// to indicate the weights of each edge coming out of the branch.
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// The weight of each edge is the weight of the target block for
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// that edge. The weight of a block B is computed as the maximum
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// number of samples found in B.
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//
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//===----------------------------------------------------------------------===//
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#include "llvm/ADT/DenseMap.h"
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#include "llvm/ADT/SmallPtrSet.h"
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#include "llvm/ADT/SmallSet.h"
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#include "llvm/ADT/StringRef.h"
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#include "llvm/Analysis/LoopInfo.h"
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#include "llvm/Analysis/PostDominators.h"
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#include "llvm/IR/Constants.h"
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#include "llvm/IR/DebugInfo.h"
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#include "llvm/IR/DiagnosticInfo.h"
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#include "llvm/IR/Dominators.h"
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#include "llvm/IR/Function.h"
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#include "llvm/IR/InstIterator.h"
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#include "llvm/IR/IntrinsicInst.h"
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#include "llvm/IR/Instructions.h"
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#include "llvm/IR/LLVMContext.h"
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#include "llvm/IR/MDBuilder.h"
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#include "llvm/IR/Metadata.h"
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#include "llvm/IR/Module.h"
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#include "llvm/Pass.h"
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#include "llvm/ProfileData/SampleProfReader.h"
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#include "llvm/Support/CommandLine.h"
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#include "llvm/Support/Debug.h"
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#include "llvm/Support/ErrorOr.h"
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#include "llvm/Support/Format.h"
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#include "llvm/Support/raw_ostream.h"
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#include "llvm/Transforms/IPO.h"
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#include "llvm/Transforms/InstCombine/InstCombine.h"
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#include "llvm/Transforms/Utils/Cloning.h"
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#include <cctype>
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using namespace llvm;
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using namespace sampleprof;
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#define DEBUG_TYPE "sample-profile"
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// Command line option to specify the file to read samples from. This is
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// mainly used for debugging.
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static cl::opt<std::string> SampleProfileFile(
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"sample-profile-file", cl::init(""), cl::value_desc("filename"),
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cl::desc("Profile file loaded by -sample-profile"), cl::Hidden);
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static cl::opt<unsigned> SampleProfileMaxPropagateIterations(
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"sample-profile-max-propagate-iterations", cl::init(100),
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cl::desc("Maximum number of iterations to go through when propagating "
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"sample block/edge weights through the CFG."));
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static cl::opt<unsigned> SampleProfileRecordCoverage(
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"sample-profile-check-record-coverage", cl::init(0), cl::value_desc("N"),
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cl::desc("Emit a warning if less than N% of records in the input profile "
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"are matched to the IR."));
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static cl::opt<unsigned> SampleProfileSampleCoverage(
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"sample-profile-check-sample-coverage", cl::init(0), cl::value_desc("N"),
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cl::desc("Emit a warning if less than N% of samples in the input profile "
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"are matched to the IR."));
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static cl::opt<double> SampleProfileHotThreshold(
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"sample-profile-inline-hot-threshold", cl::init(0.1), cl::value_desc("N"),
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cl::desc("Inlined functions that account for more than N% of all samples "
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"collected in the parent function, will be inlined again."));
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static cl::opt<double> SampleProfileGlobalHotThreshold(
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"sample-profile-global-hot-threshold", cl::init(30), cl::value_desc("N"),
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cl::desc("Top-level functions that account for more than N% of all samples "
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"collected in the profile, will be marked as hot for the inliner "
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"to consider."));
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static cl::opt<double> SampleProfileGlobalColdThreshold(
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"sample-profile-global-cold-threshold", cl::init(0.5), cl::value_desc("N"),
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cl::desc("Top-level functions that account for less than N% of all samples "
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"collected in the profile, will be marked as cold for the inliner "
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"to consider."));
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namespace {
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typedef DenseMap<const BasicBlock *, uint64_t> BlockWeightMap;
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typedef DenseMap<const BasicBlock *, const BasicBlock *> EquivalenceClassMap;
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typedef std::pair<const BasicBlock *, const BasicBlock *> Edge;
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typedef DenseMap<Edge, uint64_t> EdgeWeightMap;
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typedef DenseMap<const BasicBlock *, SmallVector<const BasicBlock *, 8>>
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BlockEdgeMap;
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/// \brief Sample profile pass.
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///
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/// This pass reads profile data from the file specified by
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/// -sample-profile-file and annotates every affected function with the
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/// profile information found in that file.
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class SampleProfileLoader : public ModulePass {
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public:
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// Class identification, replacement for typeinfo
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static char ID;
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SampleProfileLoader(StringRef Name = SampleProfileFile)
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: ModulePass(ID), DT(nullptr), PDT(nullptr), LI(nullptr), Reader(),
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Samples(nullptr), Filename(Name), ProfileIsValid(false),
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TotalCollectedSamples(0) {
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initializeSampleProfileLoaderPass(*PassRegistry::getPassRegistry());
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}
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bool doInitialization(Module &M) override;
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void dump() { Reader->dump(); }
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const char *getPassName() const override { return "Sample profile pass"; }
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bool runOnModule(Module &M) override;
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void getAnalysisUsage(AnalysisUsage &AU) const override {
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AU.addRequired<InstructionCombiningPass>();
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}
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protected:
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bool runOnFunction(Function &F);
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unsigned getFunctionLoc(Function &F);
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bool emitAnnotations(Function &F);
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ErrorOr<uint64_t> getInstWeight(const Instruction &I) const;
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ErrorOr<uint64_t> getBlockWeight(const BasicBlock *BB) const;
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const FunctionSamples *findCalleeFunctionSamples(const CallInst &I) const;
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const FunctionSamples *findFunctionSamples(const Instruction &I) const;
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bool inlineHotFunctions(Function &F);
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bool emitInlineHints(Function &F);
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void printEdgeWeight(raw_ostream &OS, Edge E);
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void printBlockWeight(raw_ostream &OS, const BasicBlock *BB) const;
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void printBlockEquivalence(raw_ostream &OS, const BasicBlock *BB);
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bool computeBlockWeights(Function &F);
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void findEquivalenceClasses(Function &F);
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void findEquivalencesFor(BasicBlock *BB1, ArrayRef<BasicBlock *> Descendants,
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DominatorTreeBase<BasicBlock> *DomTree);
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void propagateWeights(Function &F);
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uint64_t visitEdge(Edge E, unsigned *NumUnknownEdges, Edge *UnknownEdge);
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void buildEdges(Function &F);
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bool propagateThroughEdges(Function &F);
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void computeDominanceAndLoopInfo(Function &F);
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unsigned getOffset(unsigned L, unsigned H) const;
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void clearFunctionData();
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/// \brief Map basic blocks to their computed weights.
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///
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/// The weight of a basic block is defined to be the maximum
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/// of all the instruction weights in that block.
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BlockWeightMap BlockWeights;
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/// \brief Map edges to their computed weights.
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///
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/// Edge weights are computed by propagating basic block weights in
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/// SampleProfile::propagateWeights.
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EdgeWeightMap EdgeWeights;
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/// \brief Set of visited blocks during propagation.
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SmallPtrSet<const BasicBlock *, 32> VisitedBlocks;
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/// \brief Set of visited edges during propagation.
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SmallSet<Edge, 32> VisitedEdges;
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/// \brief Equivalence classes for block weights.
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///
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/// Two blocks BB1 and BB2 are in the same equivalence class if they
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/// dominate and post-dominate each other, and they are in the same loop
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/// nest. When this happens, the two blocks are guaranteed to execute
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/// the same number of times.
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EquivalenceClassMap EquivalenceClass;
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/// \brief Dominance, post-dominance and loop information.
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std::unique_ptr<DominatorTree> DT;
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std::unique_ptr<DominatorTreeBase<BasicBlock>> PDT;
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std::unique_ptr<LoopInfo> LI;
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/// \brief Predecessors for each basic block in the CFG.
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BlockEdgeMap Predecessors;
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/// \brief Successors for each basic block in the CFG.
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BlockEdgeMap Successors;
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/// \brief Profile reader object.
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std::unique_ptr<SampleProfileReader> Reader;
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/// \brief Samples collected for the body of this function.
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FunctionSamples *Samples;
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/// \brief Name of the profile file to load.
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StringRef Filename;
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/// \brief Flag indicating whether the profile input loaded successfully.
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bool ProfileIsValid;
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/// \brief Total number of samples collected in this profile.
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///
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/// This is the sum of all the samples collected in all the functions executed
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/// at runtime.
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uint64_t TotalCollectedSamples;
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};
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class SampleCoverageTracker {
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public:
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SampleCoverageTracker() : SampleCoverage(), TotalUsedSamples(0) {}
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bool markSamplesUsed(const FunctionSamples *FS, uint32_t LineOffset,
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uint32_t Discriminator, uint64_t Samples);
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unsigned computeCoverage(unsigned Used, unsigned Total) const;
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unsigned countUsedRecords(const FunctionSamples *FS) const;
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unsigned countBodyRecords(const FunctionSamples *FS) const;
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uint64_t getTotalUsedSamples() const { return TotalUsedSamples; }
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uint64_t countBodySamples(const FunctionSamples *FS) const;
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void clear() {
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SampleCoverage.clear();
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TotalUsedSamples = 0;
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}
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private:
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typedef std::map<LineLocation, unsigned> BodySampleCoverageMap;
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typedef DenseMap<const FunctionSamples *, BodySampleCoverageMap>
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FunctionSamplesCoverageMap;
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/// Coverage map for sampling records.
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///
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/// This map keeps a record of sampling records that have been matched to
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/// an IR instruction. This is used to detect some form of staleness in
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/// profiles (see flag -sample-profile-check-coverage).
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///
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/// Each entry in the map corresponds to a FunctionSamples instance. This is
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/// another map that counts how many times the sample record at the
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/// given location has been used.
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FunctionSamplesCoverageMap SampleCoverage;
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/// Number of samples used from the profile.
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///
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/// When a sampling record is used for the first time, the samples from
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/// that record are added to this accumulator. Coverage is later computed
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/// based on the total number of samples available in this function and
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/// its callsites.
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///
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/// Note that this accumulator tracks samples used from a single function
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/// and all the inlined callsites. Strictly, we should have a map of counters
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/// keyed by FunctionSamples pointers, but these stats are cleared after
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/// every function, so we just need to keep a single counter.
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uint64_t TotalUsedSamples;
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};
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SampleCoverageTracker CoverageTracker;
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/// Return true if the given callsite is hot wrt to its caller.
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///
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/// Functions that were inlined in the original binary will be represented
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/// in the inline stack in the sample profile. If the profile shows that
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/// the original inline decision was "good" (i.e., the callsite is executed
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/// frequently), then we will recreate the inline decision and apply the
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/// profile from the inlined callsite.
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///
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/// To decide whether an inlined callsite is hot, we compute the fraction
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/// of samples used by the callsite with respect to the total number of samples
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/// collected in the caller.
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///
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/// If that fraction is larger than the default given by
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/// SampleProfileHotThreshold, the callsite will be inlined again.
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bool callsiteIsHot(const FunctionSamples *CallerFS,
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const FunctionSamples *CallsiteFS) {
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if (!CallsiteFS)
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return false; // The callsite was not inlined in the original binary.
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uint64_t ParentTotalSamples = CallerFS->getTotalSamples();
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if (ParentTotalSamples == 0)
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return false; // Avoid division by zero.
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uint64_t CallsiteTotalSamples = CallsiteFS->getTotalSamples();
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if (CallsiteTotalSamples == 0)
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return false; // Callsite is trivially cold.
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double PercentSamples =
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(double)CallsiteTotalSamples / (double)ParentTotalSamples * 100.0;
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return PercentSamples >= SampleProfileHotThreshold;
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}
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}
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/// Mark as used the sample record for the given function samples at
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/// (LineOffset, Discriminator).
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///
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/// \returns true if this is the first time we mark the given record.
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bool SampleCoverageTracker::markSamplesUsed(const FunctionSamples *FS,
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uint32_t LineOffset,
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uint32_t Discriminator,
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uint64_t Samples) {
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LineLocation Loc(LineOffset, Discriminator);
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unsigned &Count = SampleCoverage[FS][Loc];
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bool FirstTime = (++Count == 1);
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if (FirstTime)
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TotalUsedSamples += Samples;
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return FirstTime;
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}
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/// Return the number of sample records that were applied from this profile.
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///
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/// This count does not include records from cold inlined callsites.
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unsigned
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SampleCoverageTracker::countUsedRecords(const FunctionSamples *FS) const {
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auto I = SampleCoverage.find(FS);
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// The size of the coverage map for FS represents the number of records
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// that were marked used at least once.
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unsigned Count = (I != SampleCoverage.end()) ? I->second.size() : 0;
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// If there are inlined callsites in this function, count the samples found
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// in the respective bodies. However, do not bother counting callees with 0
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// total samples, these are callees that were never invoked at runtime.
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for (const auto &I : FS->getCallsiteSamples()) {
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const FunctionSamples *CalleeSamples = &I.second;
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if (callsiteIsHot(FS, CalleeSamples))
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Count += countUsedRecords(CalleeSamples);
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}
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return Count;
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}
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/// Return the number of sample records in the body of this profile.
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///
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/// This count does not include records from cold inlined callsites.
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unsigned
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SampleCoverageTracker::countBodyRecords(const FunctionSamples *FS) const {
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unsigned Count = FS->getBodySamples().size();
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// Only count records in hot callsites.
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for (const auto &I : FS->getCallsiteSamples()) {
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const FunctionSamples *CalleeSamples = &I.second;
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if (callsiteIsHot(FS, CalleeSamples))
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Count += countBodyRecords(CalleeSamples);
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}
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return Count;
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}
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/// Return the number of samples collected in the body of this profile.
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///
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/// This count does not include samples from cold inlined callsites.
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uint64_t
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SampleCoverageTracker::countBodySamples(const FunctionSamples *FS) const {
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uint64_t Total = 0;
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for (const auto &I : FS->getBodySamples())
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Total += I.second.getSamples();
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// Only count samples in hot callsites.
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for (const auto &I : FS->getCallsiteSamples()) {
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const FunctionSamples *CalleeSamples = &I.second;
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if (callsiteIsHot(FS, CalleeSamples))
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Total += countBodySamples(CalleeSamples);
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}
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return Total;
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}
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/// Return the fraction of sample records used in this profile.
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///
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/// The returned value is an unsigned integer in the range 0-100 indicating
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/// the percentage of sample records that were used while applying this
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/// profile to the associated function.
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unsigned SampleCoverageTracker::computeCoverage(unsigned Used,
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unsigned Total) const {
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assert(Used <= Total &&
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"number of used records cannot exceed the total number of records");
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return Total > 0 ? Used * 100 / Total : 100;
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}
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/// Clear all the per-function data used to load samples and propagate weights.
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void SampleProfileLoader::clearFunctionData() {
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BlockWeights.clear();
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EdgeWeights.clear();
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VisitedBlocks.clear();
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VisitedEdges.clear();
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EquivalenceClass.clear();
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DT = nullptr;
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PDT = nullptr;
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LI = nullptr;
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Predecessors.clear();
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Successors.clear();
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CoverageTracker.clear();
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}
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/// \brief Returns the offset of lineno \p L to head_lineno \p H
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///
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/// \param L Lineno
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/// \param H Header lineno of the function
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///
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/// \returns offset to the header lineno. 16 bits are used to represent offset.
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/// We assume that a single function will not exceed 65535 LOC.
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unsigned SampleProfileLoader::getOffset(unsigned L, unsigned H) const {
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return (L - H) & 0xffff;
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}
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/// \brief Print the weight of edge \p E on stream \p OS.
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///
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/// \param OS Stream to emit the output to.
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/// \param E Edge to print.
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void SampleProfileLoader::printEdgeWeight(raw_ostream &OS, Edge E) {
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OS << "weight[" << E.first->getName() << "->" << E.second->getName()
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<< "]: " << EdgeWeights[E] << "\n";
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}
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/// \brief Print the equivalence class of block \p BB on stream \p OS.
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///
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/// \param OS Stream to emit the output to.
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/// \param BB Block to print.
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void SampleProfileLoader::printBlockEquivalence(raw_ostream &OS,
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const BasicBlock *BB) {
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const BasicBlock *Equiv = EquivalenceClass[BB];
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OS << "equivalence[" << BB->getName()
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<< "]: " << ((Equiv) ? EquivalenceClass[BB]->getName() : "NONE") << "\n";
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}
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/// \brief Print the weight of block \p BB on stream \p OS.
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///
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/// \param OS Stream to emit the output to.
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/// \param BB Block to print.
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void SampleProfileLoader::printBlockWeight(raw_ostream &OS,
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const BasicBlock *BB) const {
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const auto &I = BlockWeights.find(BB);
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uint64_t W = (I == BlockWeights.end() ? 0 : I->second);
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OS << "weight[" << BB->getName() << "]: " << W << "\n";
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}
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/// \brief Get the weight for an instruction.
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///
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/// The "weight" of an instruction \p Inst is the number of samples
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/// collected on that instruction at runtime. To retrieve it, we
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/// need to compute the line number of \p Inst relative to the start of its
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/// function. We use HeaderLineno to compute the offset. We then
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/// look up the samples collected for \p Inst using BodySamples.
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///
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/// \param Inst Instruction to query.
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///
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/// \returns the weight of \p Inst.
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ErrorOr<uint64_t>
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SampleProfileLoader::getInstWeight(const Instruction &Inst) const {
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DebugLoc DLoc = Inst.getDebugLoc();
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if (!DLoc)
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return std::error_code();
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const FunctionSamples *FS = findFunctionSamples(Inst);
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if (!FS)
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return std::error_code();
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// Ignore all dbg_value intrinsics.
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const IntrinsicInst *II = dyn_cast<IntrinsicInst>(&Inst);
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if (II && II->getIntrinsicID() == Intrinsic::dbg_value)
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return std::error_code();
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const DILocation *DIL = DLoc;
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unsigned Lineno = DLoc.getLine();
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unsigned HeaderLineno = DIL->getScope()->getSubprogram()->getLine();
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uint32_t LineOffset = getOffset(Lineno, HeaderLineno);
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uint32_t Discriminator = DIL->getDiscriminator();
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ErrorOr<uint64_t> R = FS->findSamplesAt(LineOffset, Discriminator);
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if (R) {
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bool FirstMark =
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CoverageTracker.markSamplesUsed(FS, LineOffset, Discriminator, R.get());
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if (FirstMark) {
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const Function *F = Inst.getParent()->getParent();
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LLVMContext &Ctx = F->getContext();
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emitOptimizationRemark(
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Ctx, DEBUG_TYPE, *F, DLoc,
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Twine("Applied ") + Twine(*R) + " samples from profile (offset: " +
|
|
Twine(LineOffset) +
|
|
((Discriminator) ? Twine(".") + Twine(Discriminator) : "") + ")");
|
|
}
|
|
DEBUG(dbgs() << " " << Lineno << "." << DIL->getDiscriminator() << ":"
|
|
<< Inst << " (line offset: " << Lineno - HeaderLineno << "."
|
|
<< DIL->getDiscriminator() << " - weight: " << R.get()
|
|
<< ")\n");
|
|
} else {
|
|
// If a call instruction is inlined in profile, but not inlined here,
|
|
// it means that the inlined callsite has no sample, thus the call
|
|
// instruction should have 0 count.
|
|
const CallInst *CI = dyn_cast<CallInst>(&Inst);
|
|
if (CI && findCalleeFunctionSamples(*CI))
|
|
R = 0;
|
|
}
|
|
return R;
|
|
}
|
|
|
|
/// \brief Compute the weight of a basic block.
|
|
///
|
|
/// The weight of basic block \p BB is the maximum weight of all the
|
|
/// instructions in BB.
|
|
///
|
|
/// \param BB The basic block to query.
|
|
///
|
|
/// \returns the weight for \p BB.
|
|
ErrorOr<uint64_t>
|
|
SampleProfileLoader::getBlockWeight(const BasicBlock *BB) const {
|
|
DenseMap<uint64_t, uint64_t> CM;
|
|
for (auto &I : BB->getInstList()) {
|
|
const ErrorOr<uint64_t> &R = getInstWeight(I);
|
|
if (R) CM[R.get()]++;
|
|
}
|
|
if (CM.size() == 0) return std::error_code();
|
|
uint64_t W = 0, C = 0;
|
|
for (const auto &C_W : CM) {
|
|
if (C_W.second == W) {
|
|
C = std::max(C, C_W.first);
|
|
} else if (C_W.second > W) {
|
|
C = C_W.first;
|
|
W = C_W.second;
|
|
}
|
|
}
|
|
return C;
|
|
}
|
|
|
|
/// \brief Compute and store the weights of every basic block.
|
|
///
|
|
/// This populates the BlockWeights map by computing
|
|
/// the weights of every basic block in the CFG.
|
|
///
|
|
/// \param F The function to query.
|
|
bool SampleProfileLoader::computeBlockWeights(Function &F) {
|
|
bool Changed = false;
|
|
DEBUG(dbgs() << "Block weights\n");
|
|
for (const auto &BB : F) {
|
|
ErrorOr<uint64_t> Weight = getBlockWeight(&BB);
|
|
if (Weight) {
|
|
BlockWeights[&BB] = Weight.get();
|
|
VisitedBlocks.insert(&BB);
|
|
Changed = true;
|
|
}
|
|
DEBUG(printBlockWeight(dbgs(), &BB));
|
|
}
|
|
|
|
return Changed;
|
|
}
|
|
|
|
/// \brief Get the FunctionSamples for a call instruction.
|
|
///
|
|
/// The FunctionSamples of a call instruction \p Inst is the inlined
|
|
/// instance in which that call instruction is calling to. It contains
|
|
/// all samples that resides in the inlined instance. We first find the
|
|
/// inlined instance in which the call instruction is from, then we
|
|
/// traverse its children to find the callsite with the matching
|
|
/// location and callee function name.
|
|
///
|
|
/// \param Inst Call instruction to query.
|
|
///
|
|
/// \returns The FunctionSamples pointer to the inlined instance.
|
|
const FunctionSamples *
|
|
SampleProfileLoader::findCalleeFunctionSamples(const CallInst &Inst) const {
|
|
const DILocation *DIL = Inst.getDebugLoc();
|
|
if (!DIL) {
|
|
return nullptr;
|
|
}
|
|
DISubprogram *SP = DIL->getScope()->getSubprogram();
|
|
if (!SP)
|
|
return nullptr;
|
|
|
|
const FunctionSamples *FS = findFunctionSamples(Inst);
|
|
if (FS == nullptr)
|
|
return nullptr;
|
|
|
|
return FS->findFunctionSamplesAt(LineLocation(
|
|
getOffset(DIL->getLine(), SP->getLine()), DIL->getDiscriminator()));
|
|
}
|
|
|
|
/// \brief Get the FunctionSamples for an instruction.
|
|
///
|
|
/// The FunctionSamples of an instruction \p Inst is the inlined instance
|
|
/// in which that instruction is coming from. We traverse the inline stack
|
|
/// of that instruction, and match it with the tree nodes in the profile.
|
|
///
|
|
/// \param Inst Instruction to query.
|
|
///
|
|
/// \returns the FunctionSamples pointer to the inlined instance.
|
|
const FunctionSamples *
|
|
SampleProfileLoader::findFunctionSamples(const Instruction &Inst) const {
|
|
SmallVector<LineLocation, 10> S;
|
|
const DILocation *DIL = Inst.getDebugLoc();
|
|
if (!DIL) {
|
|
return Samples;
|
|
}
|
|
StringRef CalleeName;
|
|
for (const DILocation *DIL = Inst.getDebugLoc(); DIL;
|
|
DIL = DIL->getInlinedAt()) {
|
|
DISubprogram *SP = DIL->getScope()->getSubprogram();
|
|
if (!SP)
|
|
return nullptr;
|
|
if (!CalleeName.empty()) {
|
|
S.push_back(LineLocation(getOffset(DIL->getLine(), SP->getLine()),
|
|
DIL->getDiscriminator()));
|
|
}
|
|
CalleeName = SP->getLinkageName();
|
|
}
|
|
if (S.size() == 0)
|
|
return Samples;
|
|
const FunctionSamples *FS = Samples;
|
|
for (int i = S.size() - 1; i >= 0 && FS != nullptr; i--) {
|
|
FS = FS->findFunctionSamplesAt(S[i]);
|
|
}
|
|
return FS;
|
|
}
|
|
|
|
/// \brief Emit an inline hint if \p F is globally hot or cold.
|
|
///
|
|
/// If \p F consumes a significant fraction of samples (indicated by
|
|
/// SampleProfileGlobalHotThreshold), apply the InlineHint attribute for the
|
|
/// inliner to consider the function hot.
|
|
///
|
|
/// If \p F consumes a small fraction of samples (indicated by
|
|
/// SampleProfileGlobalColdThreshold), apply the Cold attribute for the inliner
|
|
/// to consider the function cold.
|
|
///
|
|
/// FIXME - This setting of inline hints is sub-optimal. Instead of marking a
|
|
/// function globally hot or cold, we should be annotating individual callsites.
|
|
/// This is not currently possible, but work on the inliner will eventually
|
|
/// provide this ability. See http://reviews.llvm.org/D15003 for details and
|
|
/// discussion.
|
|
///
|
|
/// \returns True if either attribute was applied to \p F.
|
|
bool SampleProfileLoader::emitInlineHints(Function &F) {
|
|
if (TotalCollectedSamples == 0)
|
|
return false;
|
|
|
|
uint64_t FunctionSamples = Samples->getTotalSamples();
|
|
double SamplesPercent =
|
|
(double)FunctionSamples / (double)TotalCollectedSamples * 100.0;
|
|
|
|
// If the function collected more samples than the hot threshold, mark
|
|
// it globally hot.
|
|
if (SamplesPercent >= SampleProfileGlobalHotThreshold) {
|
|
F.addFnAttr(llvm::Attribute::InlineHint);
|
|
std::string Msg;
|
|
raw_string_ostream S(Msg);
|
|
S << "Applied inline hint to globally hot function '" << F.getName()
|
|
<< "' with " << format("%.2f", SamplesPercent)
|
|
<< "% of samples (threshold: "
|
|
<< format("%.2f", SampleProfileGlobalHotThreshold.getValue()) << "%)";
|
|
S.flush();
|
|
emitOptimizationRemark(F.getContext(), DEBUG_TYPE, F, DebugLoc(), Msg);
|
|
return true;
|
|
}
|
|
|
|
// If the function collected fewer samples than the cold threshold, mark
|
|
// it globally cold.
|
|
if (SamplesPercent <= SampleProfileGlobalColdThreshold) {
|
|
F.addFnAttr(llvm::Attribute::Cold);
|
|
std::string Msg;
|
|
raw_string_ostream S(Msg);
|
|
S << "Applied cold hint to globally cold function '" << F.getName()
|
|
<< "' with " << format("%.2f", SamplesPercent)
|
|
<< "% of samples (threshold: "
|
|
<< format("%.2f", SampleProfileGlobalColdThreshold.getValue()) << "%)";
|
|
S.flush();
|
|
emitOptimizationRemark(F.getContext(), DEBUG_TYPE, F, DebugLoc(), Msg);
|
|
return true;
|
|
}
|
|
|
|
return false;
|
|
}
|
|
|
|
/// \brief Iteratively inline hot callsites of a function.
|
|
///
|
|
/// Iteratively traverse all callsites of the function \p F, and find if
|
|
/// the corresponding inlined instance exists and is hot in profile. If
|
|
/// it is hot enough, inline the callsites and adds new callsites of the
|
|
/// callee into the caller.
|
|
///
|
|
/// TODO: investigate the possibility of not invoking InlineFunction directly.
|
|
///
|
|
/// \param F function to perform iterative inlining.
|
|
///
|
|
/// \returns True if there is any inline happened.
|
|
bool SampleProfileLoader::inlineHotFunctions(Function &F) {
|
|
bool Changed = false;
|
|
LLVMContext &Ctx = F.getContext();
|
|
while (true) {
|
|
bool LocalChanged = false;
|
|
SmallVector<CallInst *, 10> CIS;
|
|
for (auto &BB : F) {
|
|
for (auto &I : BB.getInstList()) {
|
|
CallInst *CI = dyn_cast<CallInst>(&I);
|
|
if (CI && callsiteIsHot(Samples, findCalleeFunctionSamples(*CI)))
|
|
CIS.push_back(CI);
|
|
}
|
|
}
|
|
for (auto CI : CIS) {
|
|
InlineFunctionInfo IFI;
|
|
Function *CalledFunction = CI->getCalledFunction();
|
|
DebugLoc DLoc = CI->getDebugLoc();
|
|
uint64_t NumSamples = findCalleeFunctionSamples(*CI)->getTotalSamples();
|
|
if (InlineFunction(CI, IFI)) {
|
|
LocalChanged = true;
|
|
emitOptimizationRemark(Ctx, DEBUG_TYPE, F, DLoc,
|
|
Twine("inlined hot callee '") +
|
|
CalledFunction->getName() + "' with " +
|
|
Twine(NumSamples) + " samples into '" +
|
|
F.getName() + "'");
|
|
}
|
|
}
|
|
if (LocalChanged) {
|
|
Changed = true;
|
|
} else {
|
|
break;
|
|
}
|
|
}
|
|
return Changed;
|
|
}
|
|
|
|
/// \brief Find equivalence classes for the given block.
|
|
///
|
|
/// This finds all the blocks that are guaranteed to execute the same
|
|
/// number of times as \p BB1. To do this, it traverses all the
|
|
/// descendants of \p BB1 in the dominator or post-dominator tree.
|
|
///
|
|
/// A block BB2 will be in the same equivalence class as \p BB1 if
|
|
/// the following holds:
|
|
///
|
|
/// 1- \p BB1 is a descendant of BB2 in the opposite tree. So, if BB2
|
|
/// is a descendant of \p BB1 in the dominator tree, then BB2 should
|
|
/// dominate BB1 in the post-dominator tree.
|
|
///
|
|
/// 2- Both BB2 and \p BB1 must be in the same loop.
|
|
///
|
|
/// For every block BB2 that meets those two requirements, we set BB2's
|
|
/// equivalence class to \p BB1.
|
|
///
|
|
/// \param BB1 Block to check.
|
|
/// \param Descendants Descendants of \p BB1 in either the dom or pdom tree.
|
|
/// \param DomTree Opposite dominator tree. If \p Descendants is filled
|
|
/// with blocks from \p BB1's dominator tree, then
|
|
/// this is the post-dominator tree, and vice versa.
|
|
void SampleProfileLoader::findEquivalencesFor(
|
|
BasicBlock *BB1, ArrayRef<BasicBlock *> Descendants,
|
|
DominatorTreeBase<BasicBlock> *DomTree) {
|
|
const BasicBlock *EC = EquivalenceClass[BB1];
|
|
uint64_t Weight = BlockWeights[EC];
|
|
for (const auto *BB2 : Descendants) {
|
|
bool IsDomParent = DomTree->dominates(BB2, BB1);
|
|
bool IsInSameLoop = LI->getLoopFor(BB1) == LI->getLoopFor(BB2);
|
|
if (BB1 != BB2 && IsDomParent && IsInSameLoop) {
|
|
EquivalenceClass[BB2] = EC;
|
|
|
|
// If BB2 is heavier than BB1, make BB2 have the same weight
|
|
// as BB1.
|
|
//
|
|
// Note that we don't worry about the opposite situation here
|
|
// (when BB2 is lighter than BB1). We will deal with this
|
|
// during the propagation phase. Right now, we just want to
|
|
// make sure that BB1 has the largest weight of all the
|
|
// members of its equivalence set.
|
|
Weight = std::max(Weight, BlockWeights[BB2]);
|
|
}
|
|
}
|
|
BlockWeights[EC] = Weight;
|
|
}
|
|
|
|
/// \brief Find equivalence classes.
|
|
///
|
|
/// Since samples may be missing from blocks, we can fill in the gaps by setting
|
|
/// the weights of all the blocks in the same equivalence class to the same
|
|
/// weight. To compute the concept of equivalence, we use dominance and loop
|
|
/// information. Two blocks B1 and B2 are in the same equivalence class if B1
|
|
/// dominates B2, B2 post-dominates B1 and both are in the same loop.
|
|
///
|
|
/// \param F The function to query.
|
|
void SampleProfileLoader::findEquivalenceClasses(Function &F) {
|
|
SmallVector<BasicBlock *, 8> DominatedBBs;
|
|
DEBUG(dbgs() << "\nBlock equivalence classes\n");
|
|
// Find equivalence sets based on dominance and post-dominance information.
|
|
for (auto &BB : F) {
|
|
BasicBlock *BB1 = &BB;
|
|
|
|
// Compute BB1's equivalence class once.
|
|
if (EquivalenceClass.count(BB1)) {
|
|
DEBUG(printBlockEquivalence(dbgs(), BB1));
|
|
continue;
|
|
}
|
|
|
|
// By default, blocks are in their own equivalence class.
|
|
EquivalenceClass[BB1] = BB1;
|
|
|
|
// Traverse all the blocks dominated by BB1. We are looking for
|
|
// every basic block BB2 such that:
|
|
//
|
|
// 1- BB1 dominates BB2.
|
|
// 2- BB2 post-dominates BB1.
|
|
// 3- BB1 and BB2 are in the same loop nest.
|
|
//
|
|
// If all those conditions hold, it means that BB2 is executed
|
|
// as many times as BB1, so they are placed in the same equivalence
|
|
// class by making BB2's equivalence class be BB1.
|
|
DominatedBBs.clear();
|
|
DT->getDescendants(BB1, DominatedBBs);
|
|
findEquivalencesFor(BB1, DominatedBBs, PDT.get());
|
|
|
|
DEBUG(printBlockEquivalence(dbgs(), BB1));
|
|
}
|
|
|
|
// Assign weights to equivalence classes.
|
|
//
|
|
// All the basic blocks in the same equivalence class will execute
|
|
// the same number of times. Since we know that the head block in
|
|
// each equivalence class has the largest weight, assign that weight
|
|
// to all the blocks in that equivalence class.
|
|
DEBUG(dbgs() << "\nAssign the same weight to all blocks in the same class\n");
|
|
for (auto &BI : F) {
|
|
const BasicBlock *BB = &BI;
|
|
const BasicBlock *EquivBB = EquivalenceClass[BB];
|
|
if (BB != EquivBB)
|
|
BlockWeights[BB] = BlockWeights[EquivBB];
|
|
DEBUG(printBlockWeight(dbgs(), BB));
|
|
}
|
|
}
|
|
|
|
/// \brief Visit the given edge to decide if it has a valid weight.
|
|
///
|
|
/// If \p E has not been visited before, we copy to \p UnknownEdge
|
|
/// and increment the count of unknown edges.
|
|
///
|
|
/// \param E Edge to visit.
|
|
/// \param NumUnknownEdges Current number of unknown edges.
|
|
/// \param UnknownEdge Set if E has not been visited before.
|
|
///
|
|
/// \returns E's weight, if known. Otherwise, return 0.
|
|
uint64_t SampleProfileLoader::visitEdge(Edge E, unsigned *NumUnknownEdges,
|
|
Edge *UnknownEdge) {
|
|
if (!VisitedEdges.count(E)) {
|
|
(*NumUnknownEdges)++;
|
|
*UnknownEdge = E;
|
|
return 0;
|
|
}
|
|
|
|
return EdgeWeights[E];
|
|
}
|
|
|
|
/// \brief Propagate weights through incoming/outgoing edges.
|
|
///
|
|
/// If the weight of a basic block is known, and there is only one edge
|
|
/// with an unknown weight, we can calculate the weight of that edge.
|
|
///
|
|
/// Similarly, if all the edges have a known count, we can calculate the
|
|
/// count of the basic block, if needed.
|
|
///
|
|
/// \param F Function to process.
|
|
///
|
|
/// \returns True if new weights were assigned to edges or blocks.
|
|
bool SampleProfileLoader::propagateThroughEdges(Function &F) {
|
|
bool Changed = false;
|
|
DEBUG(dbgs() << "\nPropagation through edges\n");
|
|
for (const auto &BI : F) {
|
|
const BasicBlock *BB = &BI;
|
|
const BasicBlock *EC = EquivalenceClass[BB];
|
|
|
|
// Visit all the predecessor and successor edges to determine
|
|
// which ones have a weight assigned already. Note that it doesn't
|
|
// matter that we only keep track of a single unknown edge. The
|
|
// only case we are interested in handling is when only a single
|
|
// edge is unknown (see setEdgeOrBlockWeight).
|
|
for (unsigned i = 0; i < 2; i++) {
|
|
uint64_t TotalWeight = 0;
|
|
unsigned NumUnknownEdges = 0;
|
|
Edge UnknownEdge, SelfReferentialEdge;
|
|
|
|
if (i == 0) {
|
|
// First, visit all predecessor edges.
|
|
for (auto *Pred : Predecessors[BB]) {
|
|
Edge E = std::make_pair(Pred, BB);
|
|
TotalWeight += visitEdge(E, &NumUnknownEdges, &UnknownEdge);
|
|
if (E.first == E.second)
|
|
SelfReferentialEdge = E;
|
|
}
|
|
} else {
|
|
// On the second round, visit all successor edges.
|
|
for (auto *Succ : Successors[BB]) {
|
|
Edge E = std::make_pair(BB, Succ);
|
|
TotalWeight += visitEdge(E, &NumUnknownEdges, &UnknownEdge);
|
|
}
|
|
}
|
|
|
|
// After visiting all the edges, there are three cases that we
|
|
// can handle immediately:
|
|
//
|
|
// - All the edge weights are known (i.e., NumUnknownEdges == 0).
|
|
// In this case, we simply check that the sum of all the edges
|
|
// is the same as BB's weight. If not, we change BB's weight
|
|
// to match. Additionally, if BB had not been visited before,
|
|
// we mark it visited.
|
|
//
|
|
// - Only one edge is unknown and BB has already been visited.
|
|
// In this case, we can compute the weight of the edge by
|
|
// subtracting the total block weight from all the known
|
|
// edge weights. If the edges weight more than BB, then the
|
|
// edge of the last remaining edge is set to zero.
|
|
//
|
|
// - There exists a self-referential edge and the weight of BB is
|
|
// known. In this case, this edge can be based on BB's weight.
|
|
// We add up all the other known edges and set the weight on
|
|
// the self-referential edge as we did in the previous case.
|
|
//
|
|
// In any other case, we must continue iterating. Eventually,
|
|
// all edges will get a weight, or iteration will stop when
|
|
// it reaches SampleProfileMaxPropagateIterations.
|
|
if (NumUnknownEdges <= 1) {
|
|
uint64_t &BBWeight = BlockWeights[EC];
|
|
if (NumUnknownEdges == 0) {
|
|
// If we already know the weight of all edges, the weight of the
|
|
// basic block can be computed. It should be no larger than the sum
|
|
// of all edge weights.
|
|
if (TotalWeight > BBWeight) {
|
|
BBWeight = TotalWeight;
|
|
Changed = true;
|
|
DEBUG(dbgs() << "All edge weights for " << BB->getName()
|
|
<< " known. Set weight for block: ";
|
|
printBlockWeight(dbgs(), BB););
|
|
}
|
|
if (VisitedBlocks.insert(EC).second)
|
|
Changed = true;
|
|
} else if (NumUnknownEdges == 1 && VisitedBlocks.count(EC)) {
|
|
// If there is a single unknown edge and the block has been
|
|
// visited, then we can compute E's weight.
|
|
if (BBWeight >= TotalWeight)
|
|
EdgeWeights[UnknownEdge] = BBWeight - TotalWeight;
|
|
else
|
|
EdgeWeights[UnknownEdge] = 0;
|
|
VisitedEdges.insert(UnknownEdge);
|
|
Changed = true;
|
|
DEBUG(dbgs() << "Set weight for edge: ";
|
|
printEdgeWeight(dbgs(), UnknownEdge));
|
|
}
|
|
} else if (SelfReferentialEdge.first && VisitedBlocks.count(EC)) {
|
|
uint64_t &BBWeight = BlockWeights[BB];
|
|
// We have a self-referential edge and the weight of BB is known.
|
|
if (BBWeight >= TotalWeight)
|
|
EdgeWeights[SelfReferentialEdge] = BBWeight - TotalWeight;
|
|
else
|
|
EdgeWeights[SelfReferentialEdge] = 0;
|
|
VisitedEdges.insert(SelfReferentialEdge);
|
|
Changed = true;
|
|
DEBUG(dbgs() << "Set self-referential edge weight to: ";
|
|
printEdgeWeight(dbgs(), SelfReferentialEdge));
|
|
}
|
|
}
|
|
}
|
|
|
|
return Changed;
|
|
}
|
|
|
|
/// \brief Build in/out edge lists for each basic block in the CFG.
|
|
///
|
|
/// We are interested in unique edges. If a block B1 has multiple
|
|
/// edges to another block B2, we only add a single B1->B2 edge.
|
|
void SampleProfileLoader::buildEdges(Function &F) {
|
|
for (auto &BI : F) {
|
|
BasicBlock *B1 = &BI;
|
|
|
|
// Add predecessors for B1.
|
|
SmallPtrSet<BasicBlock *, 16> Visited;
|
|
if (!Predecessors[B1].empty())
|
|
llvm_unreachable("Found a stale predecessors list in a basic block.");
|
|
for (pred_iterator PI = pred_begin(B1), PE = pred_end(B1); PI != PE; ++PI) {
|
|
BasicBlock *B2 = *PI;
|
|
if (Visited.insert(B2).second)
|
|
Predecessors[B1].push_back(B2);
|
|
}
|
|
|
|
// Add successors for B1.
|
|
Visited.clear();
|
|
if (!Successors[B1].empty())
|
|
llvm_unreachable("Found a stale successors list in a basic block.");
|
|
for (succ_iterator SI = succ_begin(B1), SE = succ_end(B1); SI != SE; ++SI) {
|
|
BasicBlock *B2 = *SI;
|
|
if (Visited.insert(B2).second)
|
|
Successors[B1].push_back(B2);
|
|
}
|
|
}
|
|
}
|
|
|
|
/// \brief Propagate weights into edges
|
|
///
|
|
/// The following rules are applied to every block BB in the CFG:
|
|
///
|
|
/// - If BB has a single predecessor/successor, then the weight
|
|
/// of that edge is the weight of the block.
|
|
///
|
|
/// - If all incoming or outgoing edges are known except one, and the
|
|
/// weight of the block is already known, the weight of the unknown
|
|
/// edge will be the weight of the block minus the sum of all the known
|
|
/// edges. If the sum of all the known edges is larger than BB's weight,
|
|
/// we set the unknown edge weight to zero.
|
|
///
|
|
/// - If there is a self-referential edge, and the weight of the block is
|
|
/// known, the weight for that edge is set to the weight of the block
|
|
/// minus the weight of the other incoming edges to that block (if
|
|
/// known).
|
|
void SampleProfileLoader::propagateWeights(Function &F) {
|
|
bool Changed = true;
|
|
unsigned I = 0;
|
|
|
|
// Add an entry count to the function using the samples gathered
|
|
// at the function entry.
|
|
F.setEntryCount(Samples->getHeadSamples());
|
|
|
|
// Before propagation starts, build, for each block, a list of
|
|
// unique predecessors and successors. This is necessary to handle
|
|
// identical edges in multiway branches. Since we visit all blocks and all
|
|
// edges of the CFG, it is cleaner to build these lists once at the start
|
|
// of the pass.
|
|
buildEdges(F);
|
|
|
|
// Propagate until we converge or we go past the iteration limit.
|
|
while (Changed && I++ < SampleProfileMaxPropagateIterations) {
|
|
Changed = propagateThroughEdges(F);
|
|
}
|
|
|
|
// Generate MD_prof metadata for every branch instruction using the
|
|
// edge weights computed during propagation.
|
|
DEBUG(dbgs() << "\nPropagation complete. Setting branch weights\n");
|
|
LLVMContext &Ctx = F.getContext();
|
|
MDBuilder MDB(Ctx);
|
|
for (auto &BI : F) {
|
|
BasicBlock *BB = &BI;
|
|
TerminatorInst *TI = BB->getTerminator();
|
|
if (TI->getNumSuccessors() == 1)
|
|
continue;
|
|
if (!isa<BranchInst>(TI) && !isa<SwitchInst>(TI))
|
|
continue;
|
|
|
|
DEBUG(dbgs() << "\nGetting weights for branch at line "
|
|
<< TI->getDebugLoc().getLine() << ".\n");
|
|
SmallVector<uint32_t, 4> Weights;
|
|
uint32_t MaxWeight = 0;
|
|
DebugLoc MaxDestLoc;
|
|
for (unsigned I = 0; I < TI->getNumSuccessors(); ++I) {
|
|
BasicBlock *Succ = TI->getSuccessor(I);
|
|
Edge E = std::make_pair(BB, Succ);
|
|
uint64_t Weight = EdgeWeights[E];
|
|
DEBUG(dbgs() << "\t"; printEdgeWeight(dbgs(), E));
|
|
// Use uint32_t saturated arithmetic to adjust the incoming weights,
|
|
// if needed. Sample counts in profiles are 64-bit unsigned values,
|
|
// but internally branch weights are expressed as 32-bit values.
|
|
if (Weight > std::numeric_limits<uint32_t>::max()) {
|
|
DEBUG(dbgs() << " (saturated due to uint32_t overflow)");
|
|
Weight = std::numeric_limits<uint32_t>::max();
|
|
}
|
|
Weights.push_back(static_cast<uint32_t>(Weight));
|
|
if (Weight != 0) {
|
|
if (Weight > MaxWeight) {
|
|
MaxWeight = Weight;
|
|
MaxDestLoc = Succ->getFirstNonPHIOrDbgOrLifetime()->getDebugLoc();
|
|
}
|
|
}
|
|
}
|
|
|
|
// Only set weights if there is at least one non-zero weight.
|
|
// In any other case, let the analyzer set weights.
|
|
if (MaxWeight > 0) {
|
|
DEBUG(dbgs() << "SUCCESS. Found non-zero weights.\n");
|
|
TI->setMetadata(llvm::LLVMContext::MD_prof,
|
|
MDB.createBranchWeights(Weights));
|
|
DebugLoc BranchLoc = TI->getDebugLoc();
|
|
emitOptimizationRemark(
|
|
Ctx, DEBUG_TYPE, F, MaxDestLoc,
|
|
Twine("most popular destination for conditional branches at ") +
|
|
((BranchLoc) ? Twine(BranchLoc->getFilename() + ":" +
|
|
Twine(BranchLoc.getLine()) + ":" +
|
|
Twine(BranchLoc.getCol()))
|
|
: Twine("<UNKNOWN LOCATION>")));
|
|
} else {
|
|
DEBUG(dbgs() << "SKIPPED. All branch weights are zero.\n");
|
|
}
|
|
}
|
|
}
|
|
|
|
/// \brief Get the line number for the function header.
|
|
///
|
|
/// This looks up function \p F in the current compilation unit and
|
|
/// retrieves the line number where the function is defined. This is
|
|
/// line 0 for all the samples read from the profile file. Every line
|
|
/// number is relative to this line.
|
|
///
|
|
/// \param F Function object to query.
|
|
///
|
|
/// \returns the line number where \p F is defined. If it returns 0,
|
|
/// it means that there is no debug information available for \p F.
|
|
unsigned SampleProfileLoader::getFunctionLoc(Function &F) {
|
|
if (DISubprogram *S = F.getSubprogram())
|
|
return S->getLine();
|
|
|
|
// If the start of \p F is missing, emit a diagnostic to inform the user
|
|
// about the missed opportunity.
|
|
F.getContext().diagnose(DiagnosticInfoSampleProfile(
|
|
"No debug information found in function " + F.getName() +
|
|
": Function profile not used",
|
|
DS_Warning));
|
|
return 0;
|
|
}
|
|
|
|
void SampleProfileLoader::computeDominanceAndLoopInfo(Function &F) {
|
|
DT.reset(new DominatorTree);
|
|
DT->recalculate(F);
|
|
|
|
PDT.reset(new DominatorTreeBase<BasicBlock>(true));
|
|
PDT->recalculate(F);
|
|
|
|
LI.reset(new LoopInfo);
|
|
LI->analyze(*DT);
|
|
}
|
|
|
|
/// \brief Generate branch weight metadata for all branches in \p F.
|
|
///
|
|
/// Branch weights are computed out of instruction samples using a
|
|
/// propagation heuristic. Propagation proceeds in 3 phases:
|
|
///
|
|
/// 1- Assignment of block weights. All the basic blocks in the function
|
|
/// are initial assigned the same weight as their most frequently
|
|
/// executed instruction.
|
|
///
|
|
/// 2- Creation of equivalence classes. Since samples may be missing from
|
|
/// blocks, we can fill in the gaps by setting the weights of all the
|
|
/// blocks in the same equivalence class to the same weight. To compute
|
|
/// the concept of equivalence, we use dominance and loop information.
|
|
/// Two blocks B1 and B2 are in the same equivalence class if B1
|
|
/// dominates B2, B2 post-dominates B1 and both are in the same loop.
|
|
///
|
|
/// 3- Propagation of block weights into edges. This uses a simple
|
|
/// propagation heuristic. The following rules are applied to every
|
|
/// block BB in the CFG:
|
|
///
|
|
/// - If BB has a single predecessor/successor, then the weight
|
|
/// of that edge is the weight of the block.
|
|
///
|
|
/// - If all the edges are known except one, and the weight of the
|
|
/// block is already known, the weight of the unknown edge will
|
|
/// be the weight of the block minus the sum of all the known
|
|
/// edges. If the sum of all the known edges is larger than BB's weight,
|
|
/// we set the unknown edge weight to zero.
|
|
///
|
|
/// - If there is a self-referential edge, and the weight of the block is
|
|
/// known, the weight for that edge is set to the weight of the block
|
|
/// minus the weight of the other incoming edges to that block (if
|
|
/// known).
|
|
///
|
|
/// Since this propagation is not guaranteed to finalize for every CFG, we
|
|
/// only allow it to proceed for a limited number of iterations (controlled
|
|
/// by -sample-profile-max-propagate-iterations).
|
|
///
|
|
/// FIXME: Try to replace this propagation heuristic with a scheme
|
|
/// that is guaranteed to finalize. A work-list approach similar to
|
|
/// the standard value propagation algorithm used by SSA-CCP might
|
|
/// work here.
|
|
///
|
|
/// Once all the branch weights are computed, we emit the MD_prof
|
|
/// metadata on BB using the computed values for each of its branches.
|
|
///
|
|
/// \param F The function to query.
|
|
///
|
|
/// \returns true if \p F was modified. Returns false, otherwise.
|
|
bool SampleProfileLoader::emitAnnotations(Function &F) {
|
|
bool Changed = false;
|
|
|
|
if (getFunctionLoc(F) == 0)
|
|
return false;
|
|
|
|
DEBUG(dbgs() << "Line number for the first instruction in " << F.getName()
|
|
<< ": " << getFunctionLoc(F) << "\n");
|
|
|
|
Changed |= emitInlineHints(F);
|
|
|
|
Changed |= inlineHotFunctions(F);
|
|
|
|
// Compute basic block weights.
|
|
Changed |= computeBlockWeights(F);
|
|
|
|
if (Changed) {
|
|
// Compute dominance and loop info needed for propagation.
|
|
computeDominanceAndLoopInfo(F);
|
|
|
|
// Find equivalence classes.
|
|
findEquivalenceClasses(F);
|
|
|
|
// Propagate weights to all edges.
|
|
propagateWeights(F);
|
|
}
|
|
|
|
// If coverage checking was requested, compute it now.
|
|
if (SampleProfileRecordCoverage) {
|
|
unsigned Used = CoverageTracker.countUsedRecords(Samples);
|
|
unsigned Total = CoverageTracker.countBodyRecords(Samples);
|
|
unsigned Coverage = CoverageTracker.computeCoverage(Used, Total);
|
|
if (Coverage < SampleProfileRecordCoverage) {
|
|
F.getContext().diagnose(DiagnosticInfoSampleProfile(
|
|
F.getSubprogram()->getFilename(), getFunctionLoc(F),
|
|
Twine(Used) + " of " + Twine(Total) + " available profile records (" +
|
|
Twine(Coverage) + "%) were applied",
|
|
DS_Warning));
|
|
}
|
|
}
|
|
|
|
if (SampleProfileSampleCoverage) {
|
|
uint64_t Used = CoverageTracker.getTotalUsedSamples();
|
|
uint64_t Total = CoverageTracker.countBodySamples(Samples);
|
|
unsigned Coverage = CoverageTracker.computeCoverage(Used, Total);
|
|
if (Coverage < SampleProfileSampleCoverage) {
|
|
F.getContext().diagnose(DiagnosticInfoSampleProfile(
|
|
F.getSubprogram()->getFilename(), getFunctionLoc(F),
|
|
Twine(Used) + " of " + Twine(Total) + " available profile samples (" +
|
|
Twine(Coverage) + "%) were applied",
|
|
DS_Warning));
|
|
}
|
|
}
|
|
return Changed;
|
|
}
|
|
|
|
char SampleProfileLoader::ID = 0;
|
|
INITIALIZE_PASS_BEGIN(SampleProfileLoader, "sample-profile",
|
|
"Sample Profile loader", false, false)
|
|
INITIALIZE_PASS_DEPENDENCY(AddDiscriminators)
|
|
INITIALIZE_PASS_DEPENDENCY(InstructionCombiningPass)
|
|
INITIALIZE_PASS_END(SampleProfileLoader, "sample-profile",
|
|
"Sample Profile loader", false, false)
|
|
|
|
bool SampleProfileLoader::doInitialization(Module &M) {
|
|
auto &Ctx = M.getContext();
|
|
auto ReaderOrErr = SampleProfileReader::create(Filename, Ctx);
|
|
if (std::error_code EC = ReaderOrErr.getError()) {
|
|
std::string Msg = "Could not open profile: " + EC.message();
|
|
Ctx.diagnose(DiagnosticInfoSampleProfile(Filename, Msg));
|
|
return false;
|
|
}
|
|
Reader = std::move(ReaderOrErr.get());
|
|
ProfileIsValid = (Reader->read() == sampleprof_error::success);
|
|
return true;
|
|
}
|
|
|
|
ModulePass *llvm::createSampleProfileLoaderPass() {
|
|
return new SampleProfileLoader(SampleProfileFile);
|
|
}
|
|
|
|
ModulePass *llvm::createSampleProfileLoaderPass(StringRef Name) {
|
|
return new SampleProfileLoader(Name);
|
|
}
|
|
|
|
bool SampleProfileLoader::runOnModule(Module &M) {
|
|
if (!ProfileIsValid)
|
|
return false;
|
|
|
|
// Compute the total number of samples collected in this profile.
|
|
for (const auto &I : Reader->getProfiles())
|
|
TotalCollectedSamples += I.second.getTotalSamples();
|
|
|
|
bool retval = false;
|
|
for (auto &F : M)
|
|
if (!F.isDeclaration()) {
|
|
clearFunctionData();
|
|
retval |= runOnFunction(F);
|
|
}
|
|
return retval;
|
|
}
|
|
|
|
bool SampleProfileLoader::runOnFunction(Function &F) {
|
|
F.setEntryCount(0);
|
|
getAnalysis<InstructionCombiningPass>(F);
|
|
Samples = Reader->getSamplesFor(F);
|
|
if (!Samples->empty())
|
|
return emitAnnotations(F);
|
|
return false;
|
|
}
|