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Diffstat (limited to 'contrib/llvm/lib/Transforms/Scalar/SampleProfile.cpp')
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diff --git a/contrib/llvm/lib/Transforms/Scalar/SampleProfile.cpp b/contrib/llvm/lib/Transforms/Scalar/SampleProfile.cpp new file mode 100644 index 0000000..73c97ff --- /dev/null +++ b/contrib/llvm/lib/Transforms/Scalar/SampleProfile.cpp @@ -0,0 +1,1101 @@ +//===- 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/Transforms/Scalar.h" +#include "llvm/ADT/DenseMap.h" +#include "llvm/ADT/SmallPtrSet.h" +#include "llvm/ADT/SmallSet.h" +#include "llvm/ADT/StringMap.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/Support/CommandLine.h" +#include "llvm/Support/Debug.h" +#include "llvm/Support/LineIterator.h" +#include "llvm/Support/MemoryBuffer.h" +#include "llvm/Support/Regex.h" +#include "llvm/Support/raw_ostream.h" +#include <cctype> + +using namespace llvm; + +#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<std::string> SampleProfileFile( + "sample-profile-file", cl::init(""), cl::value_desc("filename"), + cl::desc("Profile file loaded by -sample-profile"), cl::Hidden); +static cl::opt<unsigned> 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.")); + +namespace { +/// \brief Represents the relative location of an instruction. +/// +/// Instruction locations are specified by the line offset from the +/// beginning of the function (marked by the line where the function +/// header is) and the discriminator value within that line. +/// +/// The discriminator value is useful to distinguish instructions +/// that are on the same line but belong to different basic blocks +/// (e.g., the two post-increment instructions in "if (p) x++; else y++;"). +struct InstructionLocation { + InstructionLocation(int L, unsigned D) : LineOffset(L), Discriminator(D) {} + int LineOffset; + unsigned Discriminator; +}; +} + +namespace llvm { +template <> struct DenseMapInfo<InstructionLocation> { + typedef DenseMapInfo<int> OffsetInfo; + typedef DenseMapInfo<unsigned> DiscriminatorInfo; + static inline InstructionLocation getEmptyKey() { + return InstructionLocation(OffsetInfo::getEmptyKey(), + DiscriminatorInfo::getEmptyKey()); + } + static inline InstructionLocation getTombstoneKey() { + return InstructionLocation(OffsetInfo::getTombstoneKey(), + DiscriminatorInfo::getTombstoneKey()); + } + static inline unsigned getHashValue(InstructionLocation Val) { + return DenseMapInfo<std::pair<int, unsigned>>::getHashValue( + std::pair<int, unsigned>(Val.LineOffset, Val.Discriminator)); + } + static inline bool isEqual(InstructionLocation LHS, InstructionLocation RHS) { + return LHS.LineOffset == RHS.LineOffset && + LHS.Discriminator == RHS.Discriminator; + } +}; +} + +namespace { +typedef DenseMap<InstructionLocation, unsigned> BodySampleMap; +typedef DenseMap<BasicBlock *, unsigned> BlockWeightMap; +typedef DenseMap<BasicBlock *, BasicBlock *> EquivalenceClassMap; +typedef std::pair<BasicBlock *, BasicBlock *> Edge; +typedef DenseMap<Edge, unsigned> EdgeWeightMap; +typedef DenseMap<BasicBlock *, SmallVector<BasicBlock *, 8>> BlockEdgeMap; + +/// \brief Representation of the runtime profile for a function. +/// +/// This data structure contains the runtime profile for a given +/// function. It contains the total number of samples collected +/// in the function and a map of samples collected in every statement. +class SampleFunctionProfile { +public: + SampleFunctionProfile() + : TotalSamples(0), TotalHeadSamples(0), HeaderLineno(0), DT(nullptr), + PDT(nullptr), LI(nullptr), Ctx(nullptr) {} + + unsigned getFunctionLoc(Function &F); + bool emitAnnotations(Function &F, DominatorTree *DomTree, + PostDominatorTree *PostDomTree, LoopInfo *Loops); + unsigned getInstWeight(Instruction &I); + unsigned getBlockWeight(BasicBlock *B); + void addTotalSamples(unsigned Num) { TotalSamples += Num; } + void addHeadSamples(unsigned Num) { TotalHeadSamples += Num; } + void addBodySamples(int LineOffset, unsigned Discriminator, unsigned Num) { + assert(LineOffset >= 0); + BodySamples[InstructionLocation(LineOffset, Discriminator)] += Num; + } + void print(raw_ostream &OS); + void printEdgeWeight(raw_ostream &OS, Edge E); + void printBlockWeight(raw_ostream &OS, BasicBlock *BB); + void printBlockEquivalence(raw_ostream &OS, BasicBlock *BB); + bool computeBlockWeights(Function &F); + void findEquivalenceClasses(Function &F); + void findEquivalencesFor(BasicBlock *BB1, + SmallVector<BasicBlock *, 8> Descendants, + DominatorTreeBase<BasicBlock> *DomTree); + void propagateWeights(Function &F); + unsigned visitEdge(Edge E, unsigned *NumUnknownEdges, Edge *UnknownEdge); + void buildEdges(Function &F); + bool propagateThroughEdges(Function &F); + bool empty() { return BodySamples.empty(); } + +protected: + /// \brief Total number of samples collected inside this function. + /// + /// Samples are cumulative, they include all the samples collected + /// inside this function and all its inlined callees. + unsigned TotalSamples; + + /// \brief Total number of samples collected at the head of the function. + /// FIXME: Use head samples to estimate a cold/hot attribute for the function. + unsigned TotalHeadSamples; + + /// \brief Line number for the function header. Used to compute relative + /// line numbers from the absolute line LOCs found in instruction locations. + /// The relative line numbers are needed to address the samples from the + /// profile file. + unsigned HeaderLineno; + + /// \brief Map line offsets to collected samples. + /// + /// Each entry in this map contains the number of samples + /// collected at the corresponding line offset. All line locations + /// are an offset from the start of the function. + BodySampleMap BodySamples; + + /// \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<BasicBlock *, 128> VisitedBlocks; + + /// \brief Set of visited edges during propagation. + SmallSet<Edge, 128> 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. + DominatorTree *DT; + PostDominatorTree *PDT; + LoopInfo *LI; + + /// \brief Predecessors for each basic block in the CFG. + BlockEdgeMap Predecessors; + + /// \brief Successors for each basic block in the CFG. + BlockEdgeMap Successors; + + /// \brief LLVM context holding the debug data we need. + LLVMContext *Ctx; +}; + +/// \brief Sample-based profile reader. +/// +/// Each profile contains sample counts for all the functions +/// executed. Inside each function, statements are annotated with the +/// collected samples on all the instructions associated with that +/// statement. +/// +/// For this to produce meaningful data, the program needs to be +/// compiled with some debug information (at minimum, line numbers: +/// -gline-tables-only). Otherwise, it will be impossible to match IR +/// instructions to the line numbers collected by the profiler. +/// +/// From the profile file, we are interested in collecting the +/// following information: +/// +/// * A list of functions included in the profile (mangled names). +/// +/// * For each function F: +/// 1. The total number of samples collected in F. +/// +/// 2. The samples collected at each line in F. To provide some +/// protection against source code shuffling, line numbers should +/// be relative to the start of the function. +class SampleModuleProfile { +public: + SampleModuleProfile(const Module &M, StringRef F) + : Profiles(0), Filename(F), M(M) {} + + void dump(); + bool loadText(); + void loadNative() { llvm_unreachable("not implemented"); } + void printFunctionProfile(raw_ostream &OS, StringRef FName); + void dumpFunctionProfile(StringRef FName); + SampleFunctionProfile &getProfile(const Function &F) { + return Profiles[F.getName()]; + } + + /// \brief Report a parse error message. + void reportParseError(int64_t LineNumber, Twine Msg) const { + DiagnosticInfoSampleProfile Diag(Filename.data(), LineNumber, Msg); + M.getContext().diagnose(Diag); + } + +protected: + /// \brief Map every function to its associated profile. + /// + /// The profile of every function executed at runtime is collected + /// in the structure SampleFunctionProfile. This maps function objects + /// to their corresponding profiles. + StringMap<SampleFunctionProfile> Profiles; + + /// \brief Path name to the file holding the profile data. + /// + /// The format of this file is defined by each profiler + /// independently. If possible, the profiler should have a text + /// version of the profile format to be used in constructing test + /// cases and debugging. + StringRef Filename; + + /// \brief Module being compiled. Used mainly to access the current + /// LLVM context for diagnostics. + const Module &M; +}; + +/// \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 FunctionPass { +public: + // Class identification, replacement for typeinfo + static char ID; + + SampleProfileLoader(StringRef Name = SampleProfileFile) + : FunctionPass(ID), Profiler(), Filename(Name), ProfileIsValid(false) { + initializeSampleProfileLoaderPass(*PassRegistry::getPassRegistry()); + } + + bool doInitialization(Module &M) override; + + void dump() { Profiler->dump(); } + + const char *getPassName() const override { return "Sample profile pass"; } + + bool runOnFunction(Function &F) override; + + void getAnalysisUsage(AnalysisUsage &AU) const override { + AU.setPreservesCFG(); + AU.addRequired<LoopInfo>(); + AU.addRequired<DominatorTreeWrapperPass>(); + AU.addRequired<PostDominatorTree>(); + } + +protected: + /// \brief Profile reader object. + std::unique_ptr<SampleModuleProfile> Profiler; + + /// \brief Name of the profile file to load. + StringRef Filename; + + /// \brief Flag indicating whether the profile input loaded successfully. + bool ProfileIsValid; +}; +} + +/// \brief Print this function profile on stream \p OS. +/// +/// \param OS Stream to emit the output to. +void SampleFunctionProfile::print(raw_ostream &OS) { + OS << TotalSamples << ", " << TotalHeadSamples << ", " << BodySamples.size() + << " sampled lines\n"; + for (BodySampleMap::const_iterator SI = BodySamples.begin(), + SE = BodySamples.end(); + SI != SE; ++SI) + OS << "\tline offset: " << SI->first.LineOffset + << ", discriminator: " << SI->first.Discriminator + << ", number of samples: " << SI->second << "\n"; + OS << "\n"; +} + +/// \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 SampleFunctionProfile::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 SampleFunctionProfile::printBlockEquivalence(raw_ostream &OS, + BasicBlock *BB) { + 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 SampleFunctionProfile::printBlockWeight(raw_ostream &OS, BasicBlock *BB) { + OS << "weight[" << BB->getName() << "]: " << BlockWeights[BB] << "\n"; +} + +/// \brief Print the function profile for \p FName on stream \p OS. +/// +/// \param OS Stream to emit the output to. +/// \param FName Name of the function to print. +void SampleModuleProfile::printFunctionProfile(raw_ostream &OS, + StringRef FName) { + OS << "Function: " << FName << ":\n"; + Profiles[FName].print(OS); +} + +/// \brief Dump the function profile for \p FName. +/// +/// \param FName Name of the function to print. +void SampleModuleProfile::dumpFunctionProfile(StringRef FName) { + printFunctionProfile(dbgs(), FName); +} + +/// \brief Dump all the function profiles found. +void SampleModuleProfile::dump() { + for (StringMap<SampleFunctionProfile>::const_iterator I = Profiles.begin(), + E = Profiles.end(); + I != E; ++I) + dumpFunctionProfile(I->getKey()); +} + +/// \brief Load samples from a text file. +/// +/// The file contains a list of samples for every function executed at +/// runtime. Each function profile has the following format: +/// +/// function1:total_samples:total_head_samples +/// offset1[.discriminator]: number_of_samples [fn1:num fn2:num ... ] +/// offset2[.discriminator]: number_of_samples [fn3:num fn4:num ... ] +/// ... +/// offsetN[.discriminator]: number_of_samples [fn5:num fn6:num ... ] +/// +/// Function names must be mangled in order for the profile loader to +/// match them in the current translation unit. The two numbers in the +/// function header specify how many total samples were accumulated in +/// the function (first number), and the total number of samples accumulated +/// at the prologue of the function (second number). This head sample +/// count provides an indicator of how frequent is the function invoked. +/// +/// Each sampled line may contain several items. Some are optional +/// (marked below): +/// +/// a- Source line offset. This number represents the line number +/// in the function where the sample was collected. The line number +/// is always relative to the line where symbol of the function +/// is defined. So, if the function has its header at line 280, +/// the offset 13 is at line 293 in the file. +/// +/// b- [OPTIONAL] Discriminator. This is used if the sampled program +/// was compiled with DWARF discriminator support +/// (http://wiki.dwarfstd.org/index.php?title=Path_Discriminators) +/// +/// c- Number of samples. This is the number of samples collected by +/// the profiler at this source location. +/// +/// d- [OPTIONAL] Potential call targets and samples. If present, this +/// line contains a call instruction. This models both direct and +/// indirect calls. Each called target is listed together with the +/// number of samples. For example, +/// +/// 130: 7 foo:3 bar:2 baz:7 +/// +/// The above means that at relative line offset 130 there is a +/// call instruction that calls one of foo(), bar() and baz(). With +/// baz() being the relatively more frequent call target. +/// +/// FIXME: This is currently unhandled, but it has a lot of +/// potential for aiding the inliner. +/// +/// +/// Since this is a flat profile, a function that shows up more than +/// once gets all its samples aggregated across all its instances. +/// +/// FIXME: flat profiles are too imprecise to provide good optimization +/// opportunities. Convert them to context-sensitive profile. +/// +/// This textual representation is useful to generate unit tests and +/// for debugging purposes, but it should not be used to generate +/// profiles for large programs, as the representation is extremely +/// inefficient. +/// +/// \returns true if the file was loaded successfully, false otherwise. +bool SampleModuleProfile::loadText() { + ErrorOr<std::unique_ptr<MemoryBuffer>> BufferOrErr = + MemoryBuffer::getFile(Filename); + if (std::error_code EC = BufferOrErr.getError()) { + std::string Msg(EC.message()); + M.getContext().diagnose(DiagnosticInfoSampleProfile(Filename.data(), Msg)); + return false; + } + std::unique_ptr<MemoryBuffer> Buffer = std::move(BufferOrErr.get()); + line_iterator LineIt(*Buffer, '#'); + + // Read the profile of each function. Since each function may be + // mentioned more than once, and we are collecting flat profiles, + // accumulate samples as we parse them. + Regex HeadRE("^([^0-9].*):([0-9]+):([0-9]+)$"); + Regex LineSample("^([0-9]+)\\.?([0-9]+)?: ([0-9]+)(.*)$"); + while (!LineIt.is_at_eof()) { + // Read the header of each function. + // + // Note that for function identifiers we are actually expecting + // mangled names, but we may not always get them. This happens when + // the compiler decides not to emit the function (e.g., it was inlined + // and removed). In this case, the binary will not have the linkage + // name for the function, so the profiler will emit the function's + // unmangled name, which may contain characters like ':' and '>' in its + // name (member functions, templates, etc). + // + // The only requirement we place on the identifier, then, is that it + // should not begin with a number. + SmallVector<StringRef, 3> Matches; + if (!HeadRE.match(*LineIt, &Matches)) { + reportParseError(LineIt.line_number(), + "Expected 'mangled_name:NUM:NUM', found " + *LineIt); + return false; + } + assert(Matches.size() == 4); + StringRef FName = Matches[1]; + unsigned NumSamples, NumHeadSamples; + Matches[2].getAsInteger(10, NumSamples); + Matches[3].getAsInteger(10, NumHeadSamples); + Profiles[FName] = SampleFunctionProfile(); + SampleFunctionProfile &FProfile = Profiles[FName]; + FProfile.addTotalSamples(NumSamples); + FProfile.addHeadSamples(NumHeadSamples); + ++LineIt; + + // Now read the body. The body of the function ends when we reach + // EOF or when we see the start of the next function. + while (!LineIt.is_at_eof() && isdigit((*LineIt)[0])) { + if (!LineSample.match(*LineIt, &Matches)) { + reportParseError( + LineIt.line_number(), + "Expected 'NUM[.NUM]: NUM[ mangled_name:NUM]*', found " + *LineIt); + return false; + } + assert(Matches.size() == 5); + unsigned LineOffset, NumSamples, Discriminator = 0; + Matches[1].getAsInteger(10, LineOffset); + if (Matches[2] != "") + Matches[2].getAsInteger(10, Discriminator); + Matches[3].getAsInteger(10, NumSamples); + + // FIXME: Handle called targets (in Matches[4]). + + // When dealing with instruction weights, we use the value + // zero to indicate the absence of a sample. If we read an + // actual zero from the profile file, return it as 1 to + // avoid the confusion later on. + if (NumSamples == 0) + NumSamples = 1; + FProfile.addBodySamples(LineOffset, Discriminator, NumSamples); + ++LineIt; + } + } + + return true; +} + +/// \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 profiled weight of I. +unsigned SampleFunctionProfile::getInstWeight(Instruction &Inst) { + DebugLoc DLoc = Inst.getDebugLoc(); + unsigned Lineno = DLoc.getLine(); + if (Lineno < HeaderLineno) + return 0; + + DILocation DIL(DLoc.getAsMDNode(*Ctx)); + int LOffset = Lineno - HeaderLineno; + unsigned Discriminator = DIL.getDiscriminator(); + unsigned Weight = + BodySamples.lookup(InstructionLocation(LOffset, Discriminator)); + DEBUG(dbgs() << " " << Lineno << "." << Discriminator << ":" << Inst + << " (line offset: " << LOffset << "." << Discriminator + << " - weight: " << Weight << ")\n"); + return Weight; +} + +/// \brief Compute the weight of a basic block. +/// +/// The weight of basic block \p B is the maximum weight of all the +/// instructions in B. The weight of \p B is computed and cached in +/// the BlockWeights map. +/// +/// \param B The basic block to query. +/// +/// \returns The computed weight of B. +unsigned SampleFunctionProfile::getBlockWeight(BasicBlock *B) { + // If we've computed B's weight before, return it. + std::pair<BlockWeightMap::iterator, bool> Entry = + BlockWeights.insert(std::make_pair(B, 0)); + if (!Entry.second) + return Entry.first->second; + + // Otherwise, compute and cache B's weight. + unsigned Weight = 0; + for (BasicBlock::iterator I = B->begin(), E = B->end(); I != E; ++I) { + unsigned InstWeight = getInstWeight(*I); + if (InstWeight > Weight) + Weight = InstWeight; + } + Entry.first->second = Weight; + return Weight; +} + +/// \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 SampleFunctionProfile::computeBlockWeights(Function &F) { + bool Changed = false; + DEBUG(dbgs() << "Block weights\n"); + for (Function::iterator B = F.begin(), E = F.end(); B != E; ++B) { + unsigned Weight = getBlockWeight(B); + Changed |= (Weight > 0); + DEBUG(printBlockWeight(dbgs(), B)); + } + + 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 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 SampleFunctionProfile::findEquivalencesFor( + BasicBlock *BB1, SmallVector<BasicBlock *, 8> Descendants, + DominatorTreeBase<BasicBlock> *DomTree) { + for (SmallVectorImpl<BasicBlock *>::iterator I = Descendants.begin(), + E = Descendants.end(); + I != E; ++I) { + BasicBlock *BB2 = *I; + bool IsDomParent = DomTree->dominates(BB2, BB1); + bool IsInSameLoop = LI->getLoopFor(BB1) == LI->getLoopFor(BB2); + if (BB1 != BB2 && VisitedBlocks.insert(BB2) && IsDomParent && + IsInSameLoop) { + EquivalenceClass[BB2] = BB1; + + // 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. + unsigned &BB1Weight = BlockWeights[BB1]; + unsigned &BB2Weight = BlockWeights[BB2]; + BB1Weight = std::max(BB1Weight, BB2Weight); + } + } +} + +/// \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 SampleFunctionProfile::findEquivalenceClasses(Function &F) { + SmallVector<BasicBlock *, 8> DominatedBBs; + DEBUG(dbgs() << "\nBlock equivalence classes\n"); + // Find equivalence sets based on dominance and post-dominance information. + for (Function::iterator B = F.begin(), E = F.end(); B != E; ++B) { + BasicBlock *BB1 = B; + + // 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->DT); + + // Repeat the same logic for all the blocks post-dominated by BB1. + // We are looking for every basic block BB2 such that: + // + // 1- BB1 post-dominates BB2. + // 2- BB2 dominates BB1. + // 3- BB1 and BB2 are in the same loop nest. + // + // If all those conditions hold, BB2's equivalence class is BB1. + DominatedBBs.clear(); + PDT->getDescendants(BB1, DominatedBBs); + findEquivalencesFor(BB1, DominatedBBs, DT); + + 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 (Function::iterator B = F.begin(), E = F.end(); B != E; ++B) { + BasicBlock *BB = B; + 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. +unsigned SampleFunctionProfile::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 SampleFunctionProfile::propagateThroughEdges(Function &F) { + bool Changed = false; + DEBUG(dbgs() << "\nPropagation through edges\n"); + for (Function::iterator BI = F.begin(), EI = F.end(); BI != EI; ++BI) { + BasicBlock *BB = BI; + + // 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++) { + unsigned TotalWeight = 0; + unsigned NumUnknownEdges = 0; + Edge UnknownEdge, SelfReferentialEdge; + + if (i == 0) { + // First, visit all predecessor edges. + for (size_t I = 0; I < Predecessors[BB].size(); I++) { + Edge E = std::make_pair(Predecessors[BB][I], BB); + TotalWeight += visitEdge(E, &NumUnknownEdges, &UnknownEdge); + if (E.first == E.second) + SelfReferentialEdge = E; + } + } else { + // On the second round, visit all successor edges. + for (size_t I = 0; I < Successors[BB].size(); I++) { + Edge E = std::make_pair(BB, Successors[BB][I]); + 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) { + 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)) + 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 SampleFunctionProfile::buildEdges(Function &F) { + for (Function::iterator I = F.begin(), E = F.end(); I != E; ++I) { + BasicBlock *B1 = I; + + // 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)) + 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)) + Successors[B1].push_back(B2); + } + } +} + +/// \brief Propagate weights into edges +/// +/// The following rules are applied to every block B in the CFG: +/// +/// - If B 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 B'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 SampleFunctionProfile::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 (Function::iterator I = F.begin(), E = F.end(); I != E; ++I) { + BasicBlock *B = I; + TerminatorInst *TI = B->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(B, 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 SampleFunctionProfile::getFunctionLoc(Function &F) { + NamedMDNode *CUNodes = F.getParent()->getNamedMetadata("llvm.dbg.cu"); + if (CUNodes) { + for (unsigned I = 0, E1 = CUNodes->getNumOperands(); I != E1; ++I) { + DICompileUnit CU(CUNodes->getOperand(I)); + DIArray Subprograms = CU.getSubprograms(); + for (unsigned J = 0, E2 = Subprograms.getNumElements(); J != E2; ++J) { + DISubprogram Subprogram(Subprograms.getElement(J)); + if (Subprogram.describes(&F)) + return Subprogram.getLineNumber(); + } + } + } + + F.getContext().diagnose(DiagnosticInfoSampleProfile( + "No debug information found in function " + F.getName())); + 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 B in the CFG: +/// +/// - If B 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 B'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 B 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 SampleFunctionProfile::emitAnnotations(Function &F, DominatorTree *DomTree, + PostDominatorTree *PostDomTree, + LoopInfo *Loops) { + 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"); + DT = DomTree; + PDT = PostDomTree; + LI = Loops; + Ctx = &F.getParent()->getContext(); + + // 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(LoopInfo) +INITIALIZE_PASS_DEPENDENCY(AddDiscriminators) +INITIALIZE_PASS_END(SampleProfileLoader, "sample-profile", + "Sample Profile loader", false, false) + +bool SampleProfileLoader::doInitialization(Module &M) { + Profiler.reset(new SampleModuleProfile(M, Filename)); + ProfileIsValid = Profiler->loadText(); + 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; + DominatorTree *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); + PostDominatorTree *PDT = &getAnalysis<PostDominatorTree>(); + LoopInfo *LI = &getAnalysis<LoopInfo>(); + SampleFunctionProfile &FunctionProfile = Profiler->getProfile(F); + if (!FunctionProfile.empty()) + return FunctionProfile.emitAnnotations(F, DT, PDT, LI); + return false; +} |
