mirror of
https://github.com/c64scene-ar/llvm-6502.git
synced 2024-08-25 00:29:20 +00:00
Same as r234255, but for lib/Analysis and lib/Transforms. git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@234257 91177308-0d34-0410-b5e6-96231b3b80d8
774 lines
29 KiB
C++
774 lines
29 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/Transforms/Scalar.h"
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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/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/raw_ostream.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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namespace {
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typedef DenseMap<BasicBlock *, unsigned> BlockWeightMap;
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typedef DenseMap<BasicBlock *, BasicBlock *> EquivalenceClassMap;
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typedef std::pair<BasicBlock *, BasicBlock *> Edge;
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typedef DenseMap<Edge, unsigned> EdgeWeightMap;
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typedef DenseMap<BasicBlock *, SmallVector<BasicBlock *, 8>> 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 FunctionPass {
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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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: FunctionPass(ID), DT(nullptr), PDT(nullptr), LI(nullptr), Ctx(nullptr),
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Reader(), Samples(nullptr), Filename(Name), ProfileIsValid(false) {
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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 runOnFunction(Function &F) override;
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void getAnalysisUsage(AnalysisUsage &AU) const override {
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AU.setPreservesCFG();
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AU.addRequired<LoopInfoWrapperPass>();
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AU.addRequired<DominatorTreeWrapperPass>();
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AU.addRequired<PostDominatorTree>();
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}
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protected:
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unsigned getFunctionLoc(Function &F);
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bool emitAnnotations(Function &F);
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unsigned getInstWeight(Instruction &I);
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unsigned getBlockWeight(BasicBlock *BB);
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void printEdgeWeight(raw_ostream &OS, Edge E);
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void printBlockWeight(raw_ostream &OS, BasicBlock *BB);
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void printBlockEquivalence(raw_ostream &OS, 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,
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SmallVector<BasicBlock *, 8> Descendants,
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DominatorTreeBase<BasicBlock> *DomTree);
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void propagateWeights(Function &F);
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unsigned 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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/// \brief Line number for the function header. Used to compute absolute
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/// line numbers from the relative line numbers found in the profile.
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unsigned HeaderLineno;
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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<BasicBlock *, 128> VisitedBlocks;
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/// \brief Set of visited edges during propagation.
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SmallSet<Edge, 128> 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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DominatorTree *DT;
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PostDominatorTree *PDT;
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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 LLVM context holding the debug data we need.
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LLVMContext *Ctx;
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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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};
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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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BasicBlock *BB) {
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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, BasicBlock *BB) {
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OS << "weight[" << BB->getName() << "]: " << BlockWeights[BB] << "\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 profiled weight of I.
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unsigned SampleProfileLoader::getInstWeight(Instruction &Inst) {
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DebugLoc DLoc = Inst.getDebugLoc();
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if (!DLoc)
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return 0;
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unsigned Lineno = DLoc.getLine();
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if (Lineno < HeaderLineno)
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return 0;
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DILocation DIL = DLoc.get();
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int LOffset = Lineno - HeaderLineno;
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unsigned Discriminator = DIL.getDiscriminator();
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unsigned Weight = Samples->samplesAt(LOffset, Discriminator);
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DEBUG(dbgs() << " " << Lineno << "." << Discriminator << ":" << Inst
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<< " (line offset: " << LOffset << "." << Discriminator
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<< " - weight: " << Weight << ")\n");
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return Weight;
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}
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/// \brief Compute the weight of a basic block.
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///
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/// The weight of basic block \p BB is the maximum weight of all the
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/// instructions in BB. The weight of \p BB is computed and cached in
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/// the BlockWeights map.
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///
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/// \param BB The basic block to query.
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///
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/// \returns The computed weight of BB.
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unsigned SampleProfileLoader::getBlockWeight(BasicBlock *BB) {
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// If we've computed BB's weight before, return it.
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std::pair<BlockWeightMap::iterator, bool> Entry =
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BlockWeights.insert(std::make_pair(BB, 0));
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if (!Entry.second)
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return Entry.first->second;
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// Otherwise, compute and cache BB's weight.
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unsigned Weight = 0;
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for (auto &I : BB->getInstList()) {
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unsigned InstWeight = getInstWeight(I);
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if (InstWeight > Weight)
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Weight = InstWeight;
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}
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Entry.first->second = Weight;
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return Weight;
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}
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/// \brief Compute and store the weights of every basic block.
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///
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/// This populates the BlockWeights map by computing
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/// the weights of every basic block in the CFG.
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///
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/// \param F The function to query.
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bool SampleProfileLoader::computeBlockWeights(Function &F) {
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bool Changed = false;
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DEBUG(dbgs() << "Block weights\n");
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for (auto &BB : F) {
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unsigned Weight = getBlockWeight(&BB);
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Changed |= (Weight > 0);
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DEBUG(printBlockWeight(dbgs(), &BB));
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}
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return Changed;
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}
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/// \brief Find equivalence classes for the given block.
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///
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/// This finds all the blocks that are guaranteed to execute the same
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/// number of times as \p BB1. To do this, it traverses all the the
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/// descendants of \p BB1 in the dominator or post-dominator tree.
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///
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/// A block BB2 will be in the same equivalence class as \p BB1 if
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/// the following holds:
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///
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/// 1- \p BB1 is a descendant of BB2 in the opposite tree. So, if BB2
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/// is a descendant of \p BB1 in the dominator tree, then BB2 should
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/// dominate BB1 in the post-dominator tree.
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///
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/// 2- Both BB2 and \p BB1 must be in the same loop.
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///
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/// For every block BB2 that meets those two requirements, we set BB2's
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/// equivalence class to \p BB1.
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///
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/// \param BB1 Block to check.
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/// \param Descendants Descendants of \p BB1 in either the dom or pdom tree.
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/// \param DomTree Opposite dominator tree. If \p Descendants is filled
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/// with blocks from \p BB1's dominator tree, then
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/// this is the post-dominator tree, and vice versa.
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void SampleProfileLoader::findEquivalencesFor(
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BasicBlock *BB1, SmallVector<BasicBlock *, 8> Descendants,
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DominatorTreeBase<BasicBlock> *DomTree) {
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for (auto *BB2 : Descendants) {
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bool IsDomParent = DomTree->dominates(BB2, BB1);
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bool IsInSameLoop = LI->getLoopFor(BB1) == LI->getLoopFor(BB2);
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if (BB1 != BB2 && VisitedBlocks.insert(BB2).second && IsDomParent &&
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IsInSameLoop) {
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EquivalenceClass[BB2] = BB1;
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// If BB2 is heavier than BB1, make BB2 have the same weight
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// as BB1.
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//
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// Note that we don't worry about the opposite situation here
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// (when BB2 is lighter than BB1). We will deal with this
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// during the propagation phase. Right now, we just want to
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// make sure that BB1 has the largest weight of all the
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// members of its equivalence set.
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unsigned &BB1Weight = BlockWeights[BB1];
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unsigned &BB2Weight = BlockWeights[BB2];
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BB1Weight = std::max(BB1Weight, BB2Weight);
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}
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}
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}
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/// \brief Find equivalence classes.
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///
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/// Since samples may be missing from blocks, we can fill in the gaps by setting
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/// the weights of all the blocks in the same equivalence class to the same
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/// weight. To compute the concept of equivalence, we use dominance and loop
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/// information. Two blocks B1 and B2 are in the same equivalence class if B1
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/// dominates B2, B2 post-dominates B1 and both are in the same loop.
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///
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/// \param F The function to query.
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void SampleProfileLoader::findEquivalenceClasses(Function &F) {
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SmallVector<BasicBlock *, 8> DominatedBBs;
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DEBUG(dbgs() << "\nBlock equivalence classes\n");
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// Find equivalence sets based on dominance and post-dominance information.
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for (auto &BB : F) {
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BasicBlock *BB1 = &BB;
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// Compute BB1's equivalence class once.
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if (EquivalenceClass.count(BB1)) {
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DEBUG(printBlockEquivalence(dbgs(), BB1));
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continue;
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}
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// By default, blocks are in their own equivalence class.
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EquivalenceClass[BB1] = BB1;
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// Traverse all the blocks dominated by BB1. We are looking for
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// every basic block BB2 such that:
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//
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// 1- BB1 dominates BB2.
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// 2- BB2 post-dominates BB1.
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// 3- BB1 and BB2 are in the same loop nest.
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//
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// If all those conditions hold, it means that BB2 is executed
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// as many times as BB1, so they are placed in the same equivalence
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// class by making BB2's equivalence class be BB1.
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DominatedBBs.clear();
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DT->getDescendants(BB1, DominatedBBs);
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findEquivalencesFor(BB1, DominatedBBs, PDT->DT);
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// Repeat the same logic for all the blocks post-dominated by BB1.
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// We are looking for every basic block BB2 such that:
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//
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// 1- BB1 post-dominates BB2.
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// 2- BB2 dominates BB1.
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// 3- BB1 and BB2 are in the same loop nest.
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//
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// If all those conditions hold, BB2's equivalence class is BB1.
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DominatedBBs.clear();
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PDT->getDescendants(BB1, DominatedBBs);
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findEquivalencesFor(BB1, DominatedBBs, DT);
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DEBUG(printBlockEquivalence(dbgs(), BB1));
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}
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// Assign weights to equivalence classes.
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//
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// All the basic blocks in the same equivalence class will execute
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// the same number of times. Since we know that the head block in
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// each equivalence class has the largest weight, assign that weight
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// to all the blocks in that equivalence class.
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DEBUG(dbgs() << "\nAssign the same weight to all blocks in the same class\n");
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for (auto &BI : F) {
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BasicBlock *BB = &BI;
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BasicBlock *EquivBB = EquivalenceClass[BB];
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if (BB != EquivBB)
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BlockWeights[BB] = BlockWeights[EquivBB];
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DEBUG(printBlockWeight(dbgs(), BB));
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}
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}
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/// \brief Visit the given edge to decide if it has a valid weight.
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///
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/// If \p E has not been visited before, we copy to \p UnknownEdge
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/// and increment the count of unknown edges.
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///
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/// \param E Edge to visit.
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/// \param NumUnknownEdges Current number of unknown edges.
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/// \param UnknownEdge Set if E has not been visited before.
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///
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/// \returns E's weight, if known. Otherwise, return 0.
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unsigned SampleProfileLoader::visitEdge(Edge E, unsigned *NumUnknownEdges,
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Edge *UnknownEdge) {
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if (!VisitedEdges.count(E)) {
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(*NumUnknownEdges)++;
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*UnknownEdge = E;
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return 0;
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}
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return EdgeWeights[E];
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}
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/// \brief Propagate weights through incoming/outgoing edges.
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///
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/// If the weight of a basic block is known, and there is only one edge
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/// with an unknown weight, we can calculate the weight of that edge.
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///
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/// Similarly, if all the edges have a known count, we can calculate the
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/// count of the basic block, if needed.
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///
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/// \param F Function to process.
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///
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/// \returns True if new weights were assigned to edges or blocks.
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bool SampleProfileLoader::propagateThroughEdges(Function &F) {
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bool Changed = false;
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DEBUG(dbgs() << "\nPropagation through edges\n");
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for (auto &BI : F) {
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BasicBlock *BB = &BI;
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// Visit all the predecessor and successor edges to determine
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// which ones have a weight assigned already. Note that it doesn't
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// matter that we only keep track of a single unknown edge. The
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// only case we are interested in handling is when only a single
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// edge is unknown (see setEdgeOrBlockWeight).
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for (unsigned i = 0; i < 2; i++) {
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unsigned TotalWeight = 0;
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unsigned NumUnknownEdges = 0;
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Edge UnknownEdge, SelfReferentialEdge;
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if (i == 0) {
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// First, visit all predecessor edges.
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for (auto *Pred : Predecessors[BB]) {
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Edge E = std::make_pair(Pred, BB);
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TotalWeight += visitEdge(E, &NumUnknownEdges, &UnknownEdge);
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if (E.first == E.second)
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SelfReferentialEdge = E;
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}
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} else {
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// On the second round, visit all successor edges.
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for (auto *Succ : Successors[BB]) {
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Edge E = std::make_pair(BB, Succ);
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TotalWeight += visitEdge(E, &NumUnknownEdges, &UnknownEdge);
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}
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}
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// After visiting all the edges, there are three cases that we
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// can handle immediately:
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//
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// - All the edge weights are known (i.e., NumUnknownEdges == 0).
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// In this case, we simply check that the sum of all the edges
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// is the same as BB's weight. If not, we change BB's weight
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// to match. Additionally, if BB had not been visited before,
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// we mark it visited.
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//
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// - Only one edge is unknown and BB has already been visited.
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// In this case, we can compute the weight of the edge by
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// subtracting the total block weight from all the known
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// edge weights. If the edges weight more than BB, then the
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// 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) {
|
|
unsigned &BBWeight = BlockWeights[BB];
|
|
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(BB).second)
|
|
Changed = true;
|
|
} else if (NumUnknownEdges == 1 && VisitedBlocks.count(BB)) {
|
|
// 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(BB)) {
|
|
unsigned &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;
|
|
|
|
// 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");
|
|
MDBuilder MDB(F.getContext());
|
|
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<unsigned, 4> Weights;
|
|
bool AllWeightsZero = true;
|
|
for (unsigned I = 0; I < TI->getNumSuccessors(); ++I) {
|
|
BasicBlock *Succ = TI->getSuccessor(I);
|
|
Edge E = std::make_pair(BB, Succ);
|
|
unsigned Weight = EdgeWeights[E];
|
|
DEBUG(dbgs() << "\t"; printEdgeWeight(dbgs(), E));
|
|
Weights.push_back(Weight);
|
|
if (Weight != 0)
|
|
AllWeightsZero = false;
|
|
}
|
|
|
|
// Only set weights if there is at least one non-zero weight.
|
|
// In any other case, let the analyzer set weights.
|
|
if (!AllWeightsZero) {
|
|
DEBUG(dbgs() << "SUCCESS. Found non-zero weights.\n");
|
|
TI->setMetadata(llvm::LLVMContext::MD_prof,
|
|
MDB.createBranchWeights(Weights));
|
|
} 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 = getDISubprogram(&F))
|
|
return S.getLineNumber();
|
|
|
|
// If could not find the start of \p F, 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;
|
|
}
|
|
|
|
/// \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;
|
|
|
|
// Initialize invariants used during computation and propagation.
|
|
HeaderLineno = getFunctionLoc(F);
|
|
if (HeaderLineno == 0)
|
|
return false;
|
|
|
|
DEBUG(dbgs() << "Line number for the first instruction in " << F.getName()
|
|
<< ": " << HeaderLineno << "\n");
|
|
|
|
// Compute basic block weights.
|
|
Changed |= computeBlockWeights(F);
|
|
|
|
if (Changed) {
|
|
// Find equivalence classes.
|
|
findEquivalenceClasses(F);
|
|
|
|
// Propagate weights to all edges.
|
|
propagateWeights(F);
|
|
}
|
|
|
|
return Changed;
|
|
}
|
|
|
|
char SampleProfileLoader::ID = 0;
|
|
INITIALIZE_PASS_BEGIN(SampleProfileLoader, "sample-profile",
|
|
"Sample Profile loader", false, false)
|
|
INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass)
|
|
INITIALIZE_PASS_DEPENDENCY(PostDominatorTree)
|
|
INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass)
|
|
INITIALIZE_PASS_DEPENDENCY(AddDiscriminators)
|
|
INITIALIZE_PASS_END(SampleProfileLoader, "sample-profile",
|
|
"Sample Profile loader", false, false)
|
|
|
|
bool SampleProfileLoader::doInitialization(Module &M) {
|
|
auto ReaderOrErr = SampleProfileReader::create(Filename, M.getContext());
|
|
if (std::error_code EC = ReaderOrErr.getError()) {
|
|
std::string Msg = "Could not open profile: " + EC.message();
|
|
M.getContext().diagnose(DiagnosticInfoSampleProfile(Filename.data(), Msg));
|
|
return false;
|
|
}
|
|
Reader = std::move(ReaderOrErr.get());
|
|
ProfileIsValid = (Reader->read() == sampleprof_error::success);
|
|
return true;
|
|
}
|
|
|
|
FunctionPass *llvm::createSampleProfileLoaderPass() {
|
|
return new SampleProfileLoader(SampleProfileFile);
|
|
}
|
|
|
|
FunctionPass *llvm::createSampleProfileLoaderPass(StringRef Name) {
|
|
return new SampleProfileLoader(Name);
|
|
}
|
|
|
|
bool SampleProfileLoader::runOnFunction(Function &F) {
|
|
if (!ProfileIsValid)
|
|
return false;
|
|
|
|
DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree();
|
|
PDT = &getAnalysis<PostDominatorTree>();
|
|
LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
|
|
Ctx = &F.getParent()->getContext();
|
|
Samples = Reader->getSamplesFor(F);
|
|
if (!Samples->empty())
|
|
return emitAnnotations(F);
|
|
return false;
|
|
}
|