//===- SampleProfile.cpp - Incorporate sample profiles into the IR --------===// // // The LLVM Compiler Infrastructure // // This file is distributed under the University of Illinois Open Source // License. See LICENSE.TXT for details. // //===----------------------------------------------------------------------===// // // This file implements the SampleProfileLoader transformation. This pass // reads a profile file generated by a sampling profiler (e.g. Linux Perf - // http://perf.wiki.kernel.org/) and generates IR metadata to reflect the // profile information in the given profile. // // This pass generates branch weight annotations on the IR: // // - prof: Represents branch weights. This annotation is added to branches // to indicate the weights of each edge coming out of the branch. // The weight of each edge is the weight of the target block for // that edge. The weight of a block B is computed as the maximum // number of samples found in B. // //===----------------------------------------------------------------------===// #include "llvm/ADT/DenseMap.h" #include "llvm/ADT/SmallPtrSet.h" #include "llvm/ADT/SmallSet.h" #include "llvm/ADT/StringRef.h" #include "llvm/Analysis/LoopInfo.h" #include "llvm/Analysis/PostDominators.h" #include "llvm/IR/Constants.h" #include "llvm/IR/DebugInfo.h" #include "llvm/IR/DiagnosticInfo.h" #include "llvm/IR/Dominators.h" #include "llvm/IR/Function.h" #include "llvm/IR/InstIterator.h" #include "llvm/IR/Instructions.h" #include "llvm/IR/LLVMContext.h" #include "llvm/IR/MDBuilder.h" #include "llvm/IR/Metadata.h" #include "llvm/IR/Module.h" #include "llvm/Pass.h" #include "llvm/ProfileData/SampleProfReader.h" #include "llvm/Support/CommandLine.h" #include "llvm/Support/Debug.h" #include "llvm/Support/ErrorOr.h" #include "llvm/Support/raw_ostream.h" #include "llvm/Transforms/IPO.h" #include "llvm/Transforms/Utils/Cloning.h" #include using namespace llvm; using namespace sampleprof; #define DEBUG_TYPE "sample-profile" // Command line option to specify the file to read samples from. This is // mainly used for debugging. static cl::opt SampleProfileFile( "sample-profile-file", cl::init(""), cl::value_desc("filename"), cl::desc("Profile file loaded by -sample-profile"), cl::Hidden); static cl::opt SampleProfileMaxPropagateIterations( "sample-profile-max-propagate-iterations", cl::init(100), cl::desc("Maximum number of iterations to go through when propagating " "sample block/edge weights through the CFG.")); static cl::opt SampleProfileCoverage( "sample-profile-check-coverage", cl::init(0), cl::value_desc("N"), cl::desc("Emit a warning if less than N% of samples in the input profile " "are matched to the IR.")); namespace { typedef DenseMap BlockWeightMap; typedef DenseMap EquivalenceClassMap; typedef std::pair Edge; typedef DenseMap EdgeWeightMap; typedef DenseMap> BlockEdgeMap; /// \brief Sample profile pass. /// /// This pass reads profile data from the file specified by /// -sample-profile-file and annotates every affected function with the /// profile information found in that file. class SampleProfileLoader : public ModulePass { public: // Class identification, replacement for typeinfo static char ID; SampleProfileLoader(StringRef Name = SampleProfileFile) : ModulePass(ID), DT(nullptr), PDT(nullptr), LI(nullptr), Reader(), Samples(nullptr), Filename(Name), ProfileIsValid(false) { initializeSampleProfileLoaderPass(*PassRegistry::getPassRegistry()); } bool doInitialization(Module &M) override; void dump() { Reader->dump(); } const char *getPassName() const override { return "Sample profile pass"; } bool runOnModule(Module &M) override; void getAnalysisUsage(AnalysisUsage &AU) const override { AU.setPreservesCFG(); } protected: bool runOnFunction(Function &F); unsigned getFunctionLoc(Function &F); bool emitAnnotations(Function &F); ErrorOr getInstWeight(const Instruction &I) const; ErrorOr getBlockWeight(const BasicBlock *BB) const; const FunctionSamples *findCalleeFunctionSamples(const CallInst &I) const; const FunctionSamples *findFunctionSamples(const Instruction &I) const; bool inlineHotFunctions(Function &F); void printEdgeWeight(raw_ostream &OS, Edge E); void printBlockWeight(raw_ostream &OS, const BasicBlock *BB) const; void printBlockEquivalence(raw_ostream &OS, const BasicBlock *BB); bool computeBlockWeights(Function &F); void findEquivalenceClasses(Function &F); void findEquivalencesFor(BasicBlock *BB1, SmallVector Descendants, DominatorTreeBase *DomTree); void propagateWeights(Function &F); uint64_t visitEdge(Edge E, unsigned *NumUnknownEdges, Edge *UnknownEdge); void buildEdges(Function &F); bool propagateThroughEdges(Function &F); void computeDominanceAndLoopInfo(Function &F); unsigned getOffset(unsigned L, unsigned H) const; void clearFunctionData(); /// \brief Map basic blocks to their computed weights. /// /// The weight of a basic block is defined to be the maximum /// of all the instruction weights in that block. BlockWeightMap BlockWeights; /// \brief Map edges to their computed weights. /// /// Edge weights are computed by propagating basic block weights in /// SampleProfile::propagateWeights. EdgeWeightMap EdgeWeights; /// \brief Set of visited blocks during propagation. SmallPtrSet VisitedBlocks; /// \brief Set of visited edges during propagation. SmallSet VisitedEdges; /// \brief Equivalence classes for block weights. /// /// Two blocks BB1 and BB2 are in the same equivalence class if they /// dominate and post-dominate each other, and they are in the same loop /// nest. When this happens, the two blocks are guaranteed to execute /// the same number of times. EquivalenceClassMap EquivalenceClass; /// \brief Dominance, post-dominance and loop information. std::unique_ptr DT; std::unique_ptr> PDT; std::unique_ptr LI; /// \brief Predecessors for each basic block in the CFG. BlockEdgeMap Predecessors; /// \brief Successors for each basic block in the CFG. BlockEdgeMap Successors; /// \brief Profile reader object. std::unique_ptr Reader; /// \brief Samples collected for the body of this function. FunctionSamples *Samples; /// \brief Name of the profile file to load. StringRef Filename; /// \brief Flag indicating whether the profile input loaded successfully. bool ProfileIsValid; }; class SampleCoverageTracker { public: SampleCoverageTracker() : SampleCoverage() {} bool markSamplesUsed(const FunctionSamples *Samples, uint32_t LineOffset, uint32_t Discriminator); unsigned computeCoverage(unsigned Used, unsigned Total) const; unsigned countUsedSamples(const FunctionSamples *Samples) const; unsigned countBodySamples(const FunctionSamples *Samples) const; private: typedef DenseMap BodySampleCoverageMap; typedef DenseMap FunctionSamplesCoverageMap; /// Coverage map for sampling records. /// /// This map keeps a record of sampling records that have been matched to /// an IR instruction. This is used to detect some form of staleness in /// profiles (see flag -sample-profile-check-coverage). /// /// Each entry in the map corresponds to a FunctionSamples instance. This is /// another map that counts how many times the sample record at the /// given location has been used. FunctionSamplesCoverageMap SampleCoverage; }; SampleCoverageTracker CoverageTracker; } /// Mark as used the sample record for the given function samples at /// (LineOffset, Discriminator). /// /// \returns true if this is the first time we mark the given record. bool SampleCoverageTracker::markSamplesUsed(const FunctionSamples *Samples, uint32_t LineOffset, uint32_t Discriminator) { LineLocation Loc(LineOffset, Discriminator); unsigned &Count = SampleCoverage[Samples][Loc]; return ++Count == 1; } /// Return the number of sample records that were applied from this profile. unsigned SampleCoverageTracker::countUsedSamples(const FunctionSamples *Samples) const { auto I = SampleCoverage.find(Samples); unsigned Count = (I != SampleCoverage.end()) ? I->second.size() : 0; for (const auto &I : Samples->getCallsiteSamples()) Count += countUsedSamples(&I.second); return Count; } /// Return the number of sample records in the body of this profile. /// /// The count includes all the samples in inlined callees. unsigned SampleCoverageTracker::countBodySamples(const FunctionSamples *Samples) const { unsigned Count = Samples->getBodySamples().size(); for (const auto &I : Samples->getCallsiteSamples()) Count += countBodySamples(&I.second); return Count; } /// Return the fraction of sample records used in this profile. /// /// The returned value is an unsigned integer in the range 0-100 indicating /// the percentage of sample records that were used while applying this /// profile to the associated function. unsigned SampleCoverageTracker::computeCoverage(unsigned Used, unsigned Total) const { assert(Used <= Total && "number of used records cannot exceed the total number of records"); return Total > 0 ? Used * 100 / Total : 100; } /// Clear all the per-function data used to load samples and propagate weights. void SampleProfileLoader::clearFunctionData() { BlockWeights.clear(); EdgeWeights.clear(); VisitedBlocks.clear(); VisitedEdges.clear(); EquivalenceClass.clear(); DT = nullptr; PDT = nullptr; LI = nullptr; Predecessors.clear(); Successors.clear(); } /// \brief Returns the offset of lineno \p L to head_lineno \p H /// /// \param L Lineno /// \param H Header lineno of the function /// /// \returns offset to the header lineno. 16 bits are used to represent offset. /// We assume that a single function will not exceed 65535 LOC. unsigned SampleProfileLoader::getOffset(unsigned L, unsigned H) const { return (L - H) & 0xffff; } /// \brief Print the weight of edge \p E on stream \p OS. /// /// \param OS Stream to emit the output to. /// \param E Edge to print. void SampleProfileLoader::printEdgeWeight(raw_ostream &OS, Edge E) { OS << "weight[" << E.first->getName() << "->" << E.second->getName() << "]: " << EdgeWeights[E] << "\n"; } /// \brief Print the equivalence class of block \p BB on stream \p OS. /// /// \param OS Stream to emit the output to. /// \param BB Block to print. void SampleProfileLoader::printBlockEquivalence(raw_ostream &OS, const BasicBlock *BB) { const BasicBlock *Equiv = EquivalenceClass[BB]; OS << "equivalence[" << BB->getName() << "]: " << ((Equiv) ? EquivalenceClass[BB]->getName() : "NONE") << "\n"; } /// \brief Print the weight of block \p BB on stream \p OS. /// /// \param OS Stream to emit the output to. /// \param BB Block to print. void SampleProfileLoader::printBlockWeight(raw_ostream &OS, const BasicBlock *BB) const { const auto &I = BlockWeights.find(BB); uint64_t W = (I == BlockWeights.end() ? 0 : I->second); OS << "weight[" << BB->getName() << "]: " << W << "\n"; } /// \brief Get the weight for an instruction. /// /// The "weight" of an instruction \p Inst is the number of samples /// collected on that instruction at runtime. To retrieve it, we /// need to compute the line number of \p Inst relative to the start of its /// function. We use HeaderLineno to compute the offset. We then /// look up the samples collected for \p Inst using BodySamples. /// /// \param Inst Instruction to query. /// /// \returns the weight of \p Inst. ErrorOr SampleProfileLoader::getInstWeight(const Instruction &Inst) const { DebugLoc DLoc = Inst.getDebugLoc(); if (!DLoc) return std::error_code(); const FunctionSamples *FS = findFunctionSamples(Inst); if (!FS) return std::error_code(); const DILocation *DIL = DLoc; unsigned Lineno = DLoc.getLine(); unsigned HeaderLineno = DIL->getScope()->getSubprogram()->getLine(); uint32_t LineOffset = getOffset(Lineno, HeaderLineno); uint32_t Discriminator = DIL->getDiscriminator(); ErrorOr R = FS->findSamplesAt(LineOffset, Discriminator); if (R) { bool FirstMark = CoverageTracker.markSamplesUsed(FS, LineOffset, Discriminator); if (FirstMark) { const Function *F = Inst.getParent()->getParent(); LLVMContext &Ctx = F->getContext(); emitOptimizationRemark(Ctx, DEBUG_TYPE, *F, DLoc, Twine("Applied ") + Twine(*R) + " samples from profile"); } DEBUG(dbgs() << " " << Lineno << "." << DIL->getDiscriminator() << ":" << Inst << " (line offset: " << Lineno - HeaderLineno << "." << DIL->getDiscriminator() << " - weight: " << R.get() << ")\n"); } 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 SampleProfileLoader::getBlockWeight(const BasicBlock *BB) const { bool Found = false; uint64_t Weight = 0; for (auto &I : BB->getInstList()) { const ErrorOr &R = getInstWeight(I); if (R && R.get() >= Weight) { Weight = R.get(); Found = true; } } if (Found) return Weight; else return std::error_code(); } /// \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 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; Function *CalleeFunc = Inst.getCalledFunction(); if (!CalleeFunc) { return nullptr; } StringRef CalleeName = CalleeFunc->getName(); const FunctionSamples *FS = findFunctionSamples(Inst); if (FS == nullptr) return nullptr; return FS->findFunctionSamplesAt( CallsiteLocation(getOffset(DIL->getLine(), SP->getLine()), DIL->getDiscriminator(), CalleeName)); } /// \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 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(CallsiteLocation(getOffset(DIL->getLine(), SP->getLine()), DIL->getDiscriminator(), CalleeName)); } 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 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 CIS; for (auto &BB : F) { for (auto &I : BB.getInstList()) { CallInst *CI = dyn_cast(&I); if (CI) { const FunctionSamples *FS = findCalleeFunctionSamples(*CI); if (FS && FS->getTotalSamples() > 0) { 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, SmallVector Descendants, DominatorTreeBase *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 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 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(TI) && !isa(TI)) continue; DEBUG(dbgs() << "\nGetting weights for branch at line " << TI->getDebugLoc().getLine() << ".\n"); SmallVector 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::max()) { DEBUG(dbgs() << " (saturated due to uint32_t overflow)"); Weight = std::numeric_limits::max(); } Weights.push_back(static_cast(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(""))); } 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->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(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 |= 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 (SampleProfileCoverage) { unsigned Used = CoverageTracker.countUsedSamples(Samples); unsigned Total = CoverageTracker.countBodySamples(Samples); unsigned Coverage = CoverageTracker.computeCoverage(Used, Total); if (Coverage < SampleProfileCoverage) { F.getContext().diagnose(DiagnosticInfoSampleProfile( getDISubprogram(&F)->getFilename(), getFunctionLoc(F), Twine(Used) + " of " + Twine(Total) + " available profile records (" + 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_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; bool retval = false; for (auto &F : M) if (!F.isDeclaration()) { clearFunctionData(); retval |= runOnFunction(F); } return retval; } bool SampleProfileLoader::runOnFunction(Function &F) { Samples = Reader->getSamplesFor(F); if (!Samples->empty()) return emitAnnotations(F); return false; }