//===- llvm-profdata.cpp - LLVM profile data tool -------------------------===// // // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. // See https://llvm.org/LICENSE.txt for license information. // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception // //===----------------------------------------------------------------------===// // // llvm-profdata merges .profdata files. // //===----------------------------------------------------------------------===// #include "llvm/ADT/SmallSet.h" #include "llvm/ADT/SmallVector.h" #include "llvm/ADT/StringRef.h" #include "llvm/DebugInfo/DWARF/DWARFContext.h" #include "llvm/IR/LLVMContext.h" #include "llvm/Object/Binary.h" #include "llvm/ProfileData/InstrProfCorrelator.h" #include "llvm/ProfileData/InstrProfReader.h" #include "llvm/ProfileData/InstrProfWriter.h" #include "llvm/ProfileData/MemProf.h" #include "llvm/ProfileData/ProfileCommon.h" #include "llvm/ProfileData/RawMemProfReader.h" #include "llvm/ProfileData/SampleProfReader.h" #include "llvm/ProfileData/SampleProfWriter.h" #include "llvm/Support/CommandLine.h" #include "llvm/Support/Discriminator.h" #include "llvm/Support/Errc.h" #include "llvm/Support/FileSystem.h" #include "llvm/Support/Format.h" #include "llvm/Support/FormattedStream.h" #include "llvm/Support/InitLLVM.h" #include "llvm/Support/MemoryBuffer.h" #include "llvm/Support/Path.h" #include "llvm/Support/ThreadPool.h" #include "llvm/Support/Threading.h" #include "llvm/Support/WithColor.h" #include "llvm/Support/raw_ostream.h" #include #include using namespace llvm; enum ProfileFormat { PF_None = 0, PF_Text, PF_Compact_Binary, PF_Ext_Binary, PF_GCC, PF_Binary }; static void warn(Twine Message, std::string Whence = "", std::string Hint = "") { WithColor::warning(); if (!Whence.empty()) errs() << Whence << ": "; errs() << Message << "\n"; if (!Hint.empty()) WithColor::note() << Hint << "\n"; } static void warn(Error E, StringRef Whence = "") { if (E.isA()) { handleAllErrors(std::move(E), [&](const InstrProfError &IPE) { warn(IPE.message(), std::string(Whence), std::string("")); }); } } static void exitWithError(Twine Message, std::string Whence = "", std::string Hint = "") { WithColor::error(); if (!Whence.empty()) errs() << Whence << ": "; errs() << Message << "\n"; if (!Hint.empty()) WithColor::note() << Hint << "\n"; ::exit(1); } static void exitWithError(Error E, StringRef Whence = "") { if (E.isA()) { handleAllErrors(std::move(E), [&](const InstrProfError &IPE) { instrprof_error instrError = IPE.get(); StringRef Hint = ""; if (instrError == instrprof_error::unrecognized_format) { // Hint in case user missed specifying the profile type. Hint = "Perhaps you forgot to use the --sample or --memory option?"; } exitWithError(IPE.message(), std::string(Whence), std::string(Hint)); }); return; } exitWithError(toString(std::move(E)), std::string(Whence)); } static void exitWithErrorCode(std::error_code EC, StringRef Whence = "") { exitWithError(EC.message(), std::string(Whence)); } namespace { enum ProfileKinds { instr, sample, memory }; enum FailureMode { failIfAnyAreInvalid, failIfAllAreInvalid }; } static void warnOrExitGivenError(FailureMode FailMode, std::error_code EC, StringRef Whence = "") { if (FailMode == failIfAnyAreInvalid) exitWithErrorCode(EC, Whence); else warn(EC.message(), std::string(Whence)); } static void handleMergeWriterError(Error E, StringRef WhenceFile = "", StringRef WhenceFunction = "", bool ShowHint = true) { if (!WhenceFile.empty()) errs() << WhenceFile << ": "; if (!WhenceFunction.empty()) errs() << WhenceFunction << ": "; auto IPE = instrprof_error::success; E = handleErrors(std::move(E), [&IPE](std::unique_ptr E) -> Error { IPE = E->get(); return Error(std::move(E)); }); errs() << toString(std::move(E)) << "\n"; if (ShowHint) { StringRef Hint = ""; if (IPE != instrprof_error::success) { switch (IPE) { case instrprof_error::hash_mismatch: case instrprof_error::count_mismatch: case instrprof_error::value_site_count_mismatch: Hint = "Make sure that all profile data to be merged is generated " "from the same binary."; break; default: break; } } if (!Hint.empty()) errs() << Hint << "\n"; } } namespace { /// A remapper from original symbol names to new symbol names based on a file /// containing a list of mappings from old name to new name. class SymbolRemapper { std::unique_ptr File; DenseMap RemappingTable; public: /// Build a SymbolRemapper from a file containing a list of old/new symbols. static std::unique_ptr create(StringRef InputFile) { auto BufOrError = MemoryBuffer::getFileOrSTDIN(InputFile); if (!BufOrError) exitWithErrorCode(BufOrError.getError(), InputFile); auto Remapper = std::make_unique(); Remapper->File = std::move(BufOrError.get()); for (line_iterator LineIt(*Remapper->File, /*SkipBlanks=*/true, '#'); !LineIt.is_at_eof(); ++LineIt) { std::pair Parts = LineIt->split(' '); if (Parts.first.empty() || Parts.second.empty() || Parts.second.count(' ')) { exitWithError("unexpected line in remapping file", (InputFile + ":" + Twine(LineIt.line_number())).str(), "expected 'old_symbol new_symbol'"); } Remapper->RemappingTable.insert(Parts); } return Remapper; } /// Attempt to map the given old symbol into a new symbol. /// /// \return The new symbol, or \p Name if no such symbol was found. StringRef operator()(StringRef Name) { StringRef New = RemappingTable.lookup(Name); return New.empty() ? Name : New; } }; } struct WeightedFile { std::string Filename; uint64_t Weight; }; typedef SmallVector WeightedFileVector; /// Keep track of merged data and reported errors. struct WriterContext { std::mutex Lock; InstrProfWriter Writer; std::vector> Errors; std::mutex &ErrLock; SmallSet &WriterErrorCodes; WriterContext(bool IsSparse, std::mutex &ErrLock, SmallSet &WriterErrorCodes) : Writer(IsSparse), ErrLock(ErrLock), WriterErrorCodes(WriterErrorCodes) { } }; /// Computer the overlap b/w profile BaseFilename and TestFileName, /// and store the program level result to Overlap. static void overlapInput(const std::string &BaseFilename, const std::string &TestFilename, WriterContext *WC, OverlapStats &Overlap, const OverlapFuncFilters &FuncFilter, raw_fd_ostream &OS, bool IsCS) { auto ReaderOrErr = InstrProfReader::create(TestFilename); if (Error E = ReaderOrErr.takeError()) { // Skip the empty profiles by returning sliently. instrprof_error IPE = InstrProfError::take(std::move(E)); if (IPE != instrprof_error::empty_raw_profile) WC->Errors.emplace_back(make_error(IPE), TestFilename); return; } auto Reader = std::move(ReaderOrErr.get()); for (auto &I : *Reader) { OverlapStats FuncOverlap(OverlapStats::FunctionLevel); FuncOverlap.setFuncInfo(I.Name, I.Hash); WC->Writer.overlapRecord(std::move(I), Overlap, FuncOverlap, FuncFilter); FuncOverlap.dump(OS); } } /// Load an input into a writer context. static void loadInput(const WeightedFile &Input, SymbolRemapper *Remapper, const InstrProfCorrelator *Correlator, const StringRef ProfiledBinary, WriterContext *WC) { std::unique_lock CtxGuard{WC->Lock}; // Copy the filename, because llvm::ThreadPool copied the input "const // WeightedFile &" by value, making a reference to the filename within it // invalid outside of this packaged task. std::string Filename = Input.Filename; using ::llvm::memprof::RawMemProfReader; if (RawMemProfReader::hasFormat(Input.Filename)) { auto ReaderOrErr = RawMemProfReader::create(Input.Filename, ProfiledBinary); if (!ReaderOrErr) { exitWithError(ReaderOrErr.takeError(), Input.Filename); } std::unique_ptr Reader = std::move(ReaderOrErr.get()); // Check if the profile types can be merged, e.g. clang frontend profiles // should not be merged with memprof profiles. if (Error E = WC->Writer.mergeProfileKind(Reader->getProfileKind())) { consumeError(std::move(E)); WC->Errors.emplace_back( make_error( "Cannot merge MemProf profile with Clang generated profile.", std::error_code()), Filename); return; } auto MemProfError = [&](Error E) { instrprof_error IPE = InstrProfError::take(std::move(E)); WC->Errors.emplace_back(make_error(IPE), Filename); }; // Add the frame mappings into the writer context. const auto &IdToFrame = Reader->getFrameMapping(); for (const auto &I : IdToFrame) { bool Succeeded = WC->Writer.addMemProfFrame( /*Id=*/I.first, /*Frame=*/I.getSecond(), MemProfError); // If we weren't able to add the frame mappings then it doesn't make sense // to try to add the records from this profile. if (!Succeeded) return; } const auto &FunctionProfileData = Reader->getProfileData(); // Add the memprof records into the writer context. for (const auto &I : FunctionProfileData) { WC->Writer.addMemProfRecord(/*Id=*/I.first, /*Record=*/I.second); } return; } auto ReaderOrErr = InstrProfReader::create(Input.Filename, Correlator); if (Error E = ReaderOrErr.takeError()) { // Skip the empty profiles by returning sliently. instrprof_error IPE = InstrProfError::take(std::move(E)); if (IPE != instrprof_error::empty_raw_profile) WC->Errors.emplace_back(make_error(IPE), Filename); return; } auto Reader = std::move(ReaderOrErr.get()); if (Error E = WC->Writer.mergeProfileKind(Reader->getProfileKind())) { consumeError(std::move(E)); WC->Errors.emplace_back( make_error( "Merge IR generated profile with Clang generated profile.", std::error_code()), Filename); return; } for (auto &I : *Reader) { if (Remapper) I.Name = (*Remapper)(I.Name); const StringRef FuncName = I.Name; bool Reported = false; WC->Writer.addRecord(std::move(I), Input.Weight, [&](Error E) { if (Reported) { consumeError(std::move(E)); return; } Reported = true; // Only show hint the first time an error occurs. instrprof_error IPE = InstrProfError::take(std::move(E)); std::unique_lock ErrGuard{WC->ErrLock}; bool firstTime = WC->WriterErrorCodes.insert(IPE).second; handleMergeWriterError(make_error(IPE), Input.Filename, FuncName, firstTime); }); } if (Reader->hasError()) if (Error E = Reader->getError()) WC->Errors.emplace_back(std::move(E), Filename); } /// Merge the \p Src writer context into \p Dst. static void mergeWriterContexts(WriterContext *Dst, WriterContext *Src) { for (auto &ErrorPair : Src->Errors) Dst->Errors.push_back(std::move(ErrorPair)); Src->Errors.clear(); Dst->Writer.mergeRecordsFromWriter(std::move(Src->Writer), [&](Error E) { instrprof_error IPE = InstrProfError::take(std::move(E)); std::unique_lock ErrGuard{Dst->ErrLock}; bool firstTime = Dst->WriterErrorCodes.insert(IPE).second; if (firstTime) warn(toString(make_error(IPE))); }); } static void writeInstrProfile(StringRef OutputFilename, ProfileFormat OutputFormat, InstrProfWriter &Writer) { std::error_code EC; raw_fd_ostream Output(OutputFilename.data(), EC, OutputFormat == PF_Text ? sys::fs::OF_TextWithCRLF : sys::fs::OF_None); if (EC) exitWithErrorCode(EC, OutputFilename); if (OutputFormat == PF_Text) { if (Error E = Writer.writeText(Output)) warn(std::move(E)); } else { if (Output.is_displayed()) exitWithError("cannot write a non-text format profile to the terminal"); if (Error E = Writer.write(Output)) warn(std::move(E)); } } static void mergeInstrProfile(const WeightedFileVector &Inputs, StringRef DebugInfoFilename, SymbolRemapper *Remapper, StringRef OutputFilename, ProfileFormat OutputFormat, bool OutputSparse, unsigned NumThreads, FailureMode FailMode, const StringRef ProfiledBinary) { if (OutputFormat != PF_Binary && OutputFormat != PF_Compact_Binary && OutputFormat != PF_Ext_Binary && OutputFormat != PF_Text) exitWithError("unknown format is specified"); std::unique_ptr Correlator; if (!DebugInfoFilename.empty()) { if (auto Err = InstrProfCorrelator::get(DebugInfoFilename).moveInto(Correlator)) exitWithError(std::move(Err), DebugInfoFilename); if (auto Err = Correlator->correlateProfileData()) exitWithError(std::move(Err), DebugInfoFilename); } std::mutex ErrorLock; SmallSet WriterErrorCodes; // If NumThreads is not specified, auto-detect a good default. if (NumThreads == 0) NumThreads = std::min(hardware_concurrency().compute_thread_count(), unsigned((Inputs.size() + 1) / 2)); // FIXME: There's a bug here, where setting NumThreads = Inputs.size() fails // the merge_empty_profile.test because the InstrProfWriter.ProfileKind isn't // merged, thus the emitted file ends up with a PF_Unknown kind. // Initialize the writer contexts. SmallVector, 4> Contexts; for (unsigned I = 0; I < NumThreads; ++I) Contexts.emplace_back(std::make_unique( OutputSparse, ErrorLock, WriterErrorCodes)); if (NumThreads == 1) { for (const auto &Input : Inputs) loadInput(Input, Remapper, Correlator.get(), ProfiledBinary, Contexts[0].get()); } else { ThreadPool Pool(hardware_concurrency(NumThreads)); // Load the inputs in parallel (N/NumThreads serial steps). unsigned Ctx = 0; for (const auto &Input : Inputs) { Pool.async(loadInput, Input, Remapper, Correlator.get(), ProfiledBinary, Contexts[Ctx].get()); Ctx = (Ctx + 1) % NumThreads; } Pool.wait(); // Merge the writer contexts together (~ lg(NumThreads) serial steps). unsigned Mid = Contexts.size() / 2; unsigned End = Contexts.size(); assert(Mid > 0 && "Expected more than one context"); do { for (unsigned I = 0; I < Mid; ++I) Pool.async(mergeWriterContexts, Contexts[I].get(), Contexts[I + Mid].get()); Pool.wait(); if (End & 1) { Pool.async(mergeWriterContexts, Contexts[0].get(), Contexts[End - 1].get()); Pool.wait(); } End = Mid; Mid /= 2; } while (Mid > 0); } // Handle deferred errors encountered during merging. If the number of errors // is equal to the number of inputs the merge failed. unsigned NumErrors = 0; for (std::unique_ptr &WC : Contexts) { for (auto &ErrorPair : WC->Errors) { ++NumErrors; warn(toString(std::move(ErrorPair.first)), ErrorPair.second); } } if (NumErrors == Inputs.size() || (NumErrors > 0 && FailMode == failIfAnyAreInvalid)) exitWithError("no profile can be merged"); writeInstrProfile(OutputFilename, OutputFormat, Contexts[0]->Writer); } /// The profile entry for a function in instrumentation profile. struct InstrProfileEntry { uint64_t MaxCount = 0; float ZeroCounterRatio = 0.0; InstrProfRecord *ProfRecord; InstrProfileEntry(InstrProfRecord *Record); InstrProfileEntry() = default; }; InstrProfileEntry::InstrProfileEntry(InstrProfRecord *Record) { ProfRecord = Record; uint64_t CntNum = Record->Counts.size(); uint64_t ZeroCntNum = 0; for (size_t I = 0; I < CntNum; ++I) { MaxCount = std::max(MaxCount, Record->Counts[I]); ZeroCntNum += !Record->Counts[I]; } ZeroCounterRatio = (float)ZeroCntNum / CntNum; } /// Either set all the counters in the instr profile entry \p IFE to -1 /// in order to drop the profile or scale up the counters in \p IFP to /// be above hot threshold. We use the ratio of zero counters in the /// profile of a function to decide the profile is helpful or harmful /// for performance, and to choose whether to scale up or drop it. static void updateInstrProfileEntry(InstrProfileEntry &IFE, uint64_t HotInstrThreshold, float ZeroCounterThreshold) { InstrProfRecord *ProfRecord = IFE.ProfRecord; if (!IFE.MaxCount || IFE.ZeroCounterRatio > ZeroCounterThreshold) { // If all or most of the counters of the function are zero, the // profile is unaccountable and shuld be dropped. Reset all the // counters to be -1 and PGO profile-use will drop the profile. // All counters being -1 also implies that the function is hot so // PGO profile-use will also set the entry count metadata to be // above hot threshold. for (size_t I = 0; I < ProfRecord->Counts.size(); ++I) ProfRecord->Counts[I] = -1; return; } // Scale up the MaxCount to be multiple times above hot threshold. const unsigned MultiplyFactor = 3; uint64_t Numerator = HotInstrThreshold * MultiplyFactor; uint64_t Denominator = IFE.MaxCount; ProfRecord->scale(Numerator, Denominator, [&](instrprof_error E) { warn(toString(make_error(E))); }); } const uint64_t ColdPercentileIdx = 15; const uint64_t HotPercentileIdx = 11; using sampleprof::FSDiscriminatorPass; // Internal options to set FSDiscriminatorPass. Used in merge and show // commands. static cl::opt FSDiscriminatorPassOption( "fs-discriminator-pass", cl::init(PassLast), cl::Hidden, cl::desc("Zero out the discriminator bits for the FS discrimiantor " "pass beyond this value. The enum values are defined in " "Support/Discriminator.h"), cl::values(clEnumVal(Base, "Use base discriminators only"), clEnumVal(Pass1, "Use base and pass 1 discriminators"), clEnumVal(Pass2, "Use base and pass 1-2 discriminators"), clEnumVal(Pass3, "Use base and pass 1-3 discriminators"), clEnumVal(PassLast, "Use all discriminator bits (default)"))); static unsigned getDiscriminatorMask() { return getN1Bits(getFSPassBitEnd(FSDiscriminatorPassOption.getValue())); } /// Adjust the instr profile in \p WC based on the sample profile in /// \p Reader. static void adjustInstrProfile(std::unique_ptr &WC, std::unique_ptr &Reader, unsigned SupplMinSizeThreshold, float ZeroCounterThreshold, unsigned InstrProfColdThreshold) { // Function to its entry in instr profile. StringMap InstrProfileMap; InstrProfSummaryBuilder IPBuilder(ProfileSummaryBuilder::DefaultCutoffs); for (auto &PD : WC->Writer.getProfileData()) { // Populate IPBuilder. for (const auto &PDV : PD.getValue()) { InstrProfRecord Record = PDV.second; IPBuilder.addRecord(Record); } // If a function has multiple entries in instr profile, skip it. if (PD.getValue().size() != 1) continue; // Initialize InstrProfileMap. InstrProfRecord *R = &PD.getValue().begin()->second; InstrProfileMap[PD.getKey()] = InstrProfileEntry(R); } ProfileSummary InstrPS = *IPBuilder.getSummary(); ProfileSummary SamplePS = Reader->getSummary(); // Compute cold thresholds for instr profile and sample profile. uint64_t ColdSampleThreshold = ProfileSummaryBuilder::getEntryForPercentile( SamplePS.getDetailedSummary(), ProfileSummaryBuilder::DefaultCutoffs[ColdPercentileIdx]) .MinCount; uint64_t HotInstrThreshold = ProfileSummaryBuilder::getEntryForPercentile( InstrPS.getDetailedSummary(), ProfileSummaryBuilder::DefaultCutoffs[HotPercentileIdx]) .MinCount; uint64_t ColdInstrThreshold = InstrProfColdThreshold ? InstrProfColdThreshold : ProfileSummaryBuilder::getEntryForPercentile( InstrPS.getDetailedSummary(), ProfileSummaryBuilder::DefaultCutoffs[ColdPercentileIdx]) .MinCount; // Find hot/warm functions in sample profile which is cold in instr profile // and adjust the profiles of those functions in the instr profile. for (const auto &PD : Reader->getProfiles()) { auto &FContext = PD.first; const sampleprof::FunctionSamples &FS = PD.second; auto It = InstrProfileMap.find(FContext.toString()); if (FS.getHeadSamples() > ColdSampleThreshold && It != InstrProfileMap.end() && It->second.MaxCount <= ColdInstrThreshold && FS.getBodySamples().size() >= SupplMinSizeThreshold) { updateInstrProfileEntry(It->second, HotInstrThreshold, ZeroCounterThreshold); } } } /// The main function to supplement instr profile with sample profile. /// \Inputs contains the instr profile. \p SampleFilename specifies the /// sample profile. \p OutputFilename specifies the output profile name. /// \p OutputFormat specifies the output profile format. \p OutputSparse /// specifies whether to generate sparse profile. \p SupplMinSizeThreshold /// specifies the minimal size for the functions whose profile will be /// adjusted. \p ZeroCounterThreshold is the threshold to check whether /// a function contains too many zero counters and whether its profile /// should be dropped. \p InstrProfColdThreshold is the user specified /// cold threshold which will override the cold threshold got from the /// instr profile summary. static void supplementInstrProfile( const WeightedFileVector &Inputs, StringRef SampleFilename, StringRef OutputFilename, ProfileFormat OutputFormat, bool OutputSparse, unsigned SupplMinSizeThreshold, float ZeroCounterThreshold, unsigned InstrProfColdThreshold) { if (OutputFilename.compare("-") == 0) exitWithError("cannot write indexed profdata format to stdout"); if (Inputs.size() != 1) exitWithError("expect one input to be an instr profile"); if (Inputs[0].Weight != 1) exitWithError("expect instr profile doesn't have weight"); StringRef InstrFilename = Inputs[0].Filename; // Read sample profile. LLVMContext Context; auto ReaderOrErr = sampleprof::SampleProfileReader::create( SampleFilename.str(), Context, FSDiscriminatorPassOption); if (std::error_code EC = ReaderOrErr.getError()) exitWithErrorCode(EC, SampleFilename); auto Reader = std::move(ReaderOrErr.get()); if (std::error_code EC = Reader->read()) exitWithErrorCode(EC, SampleFilename); // Read instr profile. std::mutex ErrorLock; SmallSet WriterErrorCodes; auto WC = std::make_unique(OutputSparse, ErrorLock, WriterErrorCodes); loadInput(Inputs[0], nullptr, nullptr, /*ProfiledBinary=*/"", WC.get()); if (WC->Errors.size() > 0) exitWithError(std::move(WC->Errors[0].first), InstrFilename); adjustInstrProfile(WC, Reader, SupplMinSizeThreshold, ZeroCounterThreshold, InstrProfColdThreshold); writeInstrProfile(OutputFilename, OutputFormat, WC->Writer); } /// Make a copy of the given function samples with all symbol names remapped /// by the provided symbol remapper. static sampleprof::FunctionSamples remapSamples(const sampleprof::FunctionSamples &Samples, SymbolRemapper &Remapper, sampleprof_error &Error) { sampleprof::FunctionSamples Result; Result.setName(Remapper(Samples.getName())); Result.addTotalSamples(Samples.getTotalSamples()); Result.addHeadSamples(Samples.getHeadSamples()); for (const auto &BodySample : Samples.getBodySamples()) { uint32_t MaskedDiscriminator = BodySample.first.Discriminator & getDiscriminatorMask(); Result.addBodySamples(BodySample.first.LineOffset, MaskedDiscriminator, BodySample.second.getSamples()); for (const auto &Target : BodySample.second.getCallTargets()) { Result.addCalledTargetSamples(BodySample.first.LineOffset, MaskedDiscriminator, Remapper(Target.first()), Target.second); } } for (const auto &CallsiteSamples : Samples.getCallsiteSamples()) { sampleprof::FunctionSamplesMap &Target = Result.functionSamplesAt(CallsiteSamples.first); for (const auto &Callsite : CallsiteSamples.second) { sampleprof::FunctionSamples Remapped = remapSamples(Callsite.second, Remapper, Error); MergeResult(Error, Target[std::string(Remapped.getName())].merge(Remapped)); } } return Result; } static sampleprof::SampleProfileFormat FormatMap[] = { sampleprof::SPF_None, sampleprof::SPF_Text, sampleprof::SPF_Compact_Binary, sampleprof::SPF_Ext_Binary, sampleprof::SPF_GCC, sampleprof::SPF_Binary}; static std::unique_ptr getInputFileBuf(const StringRef &InputFile) { if (InputFile == "") return {}; auto BufOrError = MemoryBuffer::getFileOrSTDIN(InputFile); if (!BufOrError) exitWithErrorCode(BufOrError.getError(), InputFile); return std::move(*BufOrError); } static void populateProfileSymbolList(MemoryBuffer *Buffer, sampleprof::ProfileSymbolList &PSL) { if (!Buffer) return; SmallVector SymbolVec; StringRef Data = Buffer->getBuffer(); Data.split(SymbolVec, '\n', /*MaxSplit=*/-1, /*KeepEmpty=*/false); for (StringRef SymbolStr : SymbolVec) PSL.add(SymbolStr.trim()); } static void handleExtBinaryWriter(sampleprof::SampleProfileWriter &Writer, ProfileFormat OutputFormat, MemoryBuffer *Buffer, sampleprof::ProfileSymbolList &WriterList, bool CompressAllSections, bool UseMD5, bool GenPartialProfile) { populateProfileSymbolList(Buffer, WriterList); if (WriterList.size() > 0 && OutputFormat != PF_Ext_Binary) warn("Profile Symbol list is not empty but the output format is not " "ExtBinary format. The list will be lost in the output. "); Writer.setProfileSymbolList(&WriterList); if (CompressAllSections) { if (OutputFormat != PF_Ext_Binary) warn("-compress-all-section is ignored. Specify -extbinary to enable it"); else Writer.setToCompressAllSections(); } if (UseMD5) { if (OutputFormat != PF_Ext_Binary) warn("-use-md5 is ignored. Specify -extbinary to enable it"); else Writer.setUseMD5(); } if (GenPartialProfile) { if (OutputFormat != PF_Ext_Binary) warn("-gen-partial-profile is ignored. Specify -extbinary to enable it"); else Writer.setPartialProfile(); } } static void mergeSampleProfile(const WeightedFileVector &Inputs, SymbolRemapper *Remapper, StringRef OutputFilename, ProfileFormat OutputFormat, StringRef ProfileSymbolListFile, bool CompressAllSections, bool UseMD5, bool GenPartialProfile, bool GenCSNestedProfile, bool SampleMergeColdContext, bool SampleTrimColdContext, bool SampleColdContextFrameDepth, FailureMode FailMode) { using namespace sampleprof; SampleProfileMap ProfileMap; SmallVector, 5> Readers; LLVMContext Context; sampleprof::ProfileSymbolList WriterList; Optional ProfileIsProbeBased; Optional ProfileIsCS; for (const auto &Input : Inputs) { auto ReaderOrErr = SampleProfileReader::create(Input.Filename, Context, FSDiscriminatorPassOption); if (std::error_code EC = ReaderOrErr.getError()) { warnOrExitGivenError(FailMode, EC, Input.Filename); continue; } // We need to keep the readers around until after all the files are // read so that we do not lose the function names stored in each // reader's memory. The function names are needed to write out the // merged profile map. Readers.push_back(std::move(ReaderOrErr.get())); const auto Reader = Readers.back().get(); if (std::error_code EC = Reader->read()) { warnOrExitGivenError(FailMode, EC, Input.Filename); Readers.pop_back(); continue; } SampleProfileMap &Profiles = Reader->getProfiles(); if (ProfileIsProbeBased && ProfileIsProbeBased != FunctionSamples::ProfileIsProbeBased) exitWithError( "cannot merge probe-based profile with non-probe-based profile"); ProfileIsProbeBased = FunctionSamples::ProfileIsProbeBased; if (ProfileIsCS && ProfileIsCS != FunctionSamples::ProfileIsCS) exitWithError("cannot merge CS profile with non-CS profile"); ProfileIsCS = FunctionSamples::ProfileIsCS; for (SampleProfileMap::iterator I = Profiles.begin(), E = Profiles.end(); I != E; ++I) { sampleprof_error Result = sampleprof_error::success; FunctionSamples Remapped = Remapper ? remapSamples(I->second, *Remapper, Result) : FunctionSamples(); FunctionSamples &Samples = Remapper ? Remapped : I->second; SampleContext FContext = Samples.getContext(); MergeResult(Result, ProfileMap[FContext].merge(Samples, Input.Weight)); if (Result != sampleprof_error::success) { std::error_code EC = make_error_code(Result); handleMergeWriterError(errorCodeToError(EC), Input.Filename, FContext.toString()); } } std::unique_ptr ReaderList = Reader->getProfileSymbolList(); if (ReaderList) WriterList.merge(*ReaderList); } if (ProfileIsCS && (SampleMergeColdContext || SampleTrimColdContext)) { // Use threshold calculated from profile summary unless specified. SampleProfileSummaryBuilder Builder(ProfileSummaryBuilder::DefaultCutoffs); auto Summary = Builder.computeSummaryForProfiles(ProfileMap); uint64_t SampleProfColdThreshold = ProfileSummaryBuilder::getColdCountThreshold( (Summary->getDetailedSummary())); // Trim and merge cold context profile using cold threshold above; SampleContextTrimmer(ProfileMap) .trimAndMergeColdContextProfiles( SampleProfColdThreshold, SampleTrimColdContext, SampleMergeColdContext, SampleColdContextFrameDepth, false); } if (ProfileIsCS && GenCSNestedProfile) { CSProfileConverter CSConverter(ProfileMap); CSConverter.convertProfiles(); ProfileIsCS = FunctionSamples::ProfileIsCS = false; } auto WriterOrErr = SampleProfileWriter::create(OutputFilename, FormatMap[OutputFormat]); if (std::error_code EC = WriterOrErr.getError()) exitWithErrorCode(EC, OutputFilename); auto Writer = std::move(WriterOrErr.get()); // WriterList will have StringRef refering to string in Buffer. // Make sure Buffer lives as long as WriterList. auto Buffer = getInputFileBuf(ProfileSymbolListFile); handleExtBinaryWriter(*Writer, OutputFormat, Buffer.get(), WriterList, CompressAllSections, UseMD5, GenPartialProfile); if (std::error_code EC = Writer->write(ProfileMap)) exitWithErrorCode(std::move(EC)); } static WeightedFile parseWeightedFile(const StringRef &WeightedFilename) { StringRef WeightStr, FileName; std::tie(WeightStr, FileName) = WeightedFilename.split(','); uint64_t Weight; if (WeightStr.getAsInteger(10, Weight) || Weight < 1) exitWithError("input weight must be a positive integer"); return {std::string(FileName), Weight}; } static void addWeightedInput(WeightedFileVector &WNI, const WeightedFile &WF) { StringRef Filename = WF.Filename; uint64_t Weight = WF.Weight; // If it's STDIN just pass it on. if (Filename == "-") { WNI.push_back({std::string(Filename), Weight}); return; } llvm::sys::fs::file_status Status; llvm::sys::fs::status(Filename, Status); if (!llvm::sys::fs::exists(Status)) exitWithErrorCode(make_error_code(errc::no_such_file_or_directory), Filename); // If it's a source file, collect it. if (llvm::sys::fs::is_regular_file(Status)) { WNI.push_back({std::string(Filename), Weight}); return; } if (llvm::sys::fs::is_directory(Status)) { std::error_code EC; for (llvm::sys::fs::recursive_directory_iterator F(Filename, EC), E; F != E && !EC; F.increment(EC)) { if (llvm::sys::fs::is_regular_file(F->path())) { addWeightedInput(WNI, {F->path(), Weight}); } } if (EC) exitWithErrorCode(EC, Filename); } } static void parseInputFilenamesFile(MemoryBuffer *Buffer, WeightedFileVector &WFV) { if (!Buffer) return; SmallVector Entries; StringRef Data = Buffer->getBuffer(); Data.split(Entries, '\n', /*MaxSplit=*/-1, /*KeepEmpty=*/false); for (const StringRef &FileWeightEntry : Entries) { StringRef SanitizedEntry = FileWeightEntry.trim(" \t\v\f\r"); // Skip comments. if (SanitizedEntry.startswith("#")) continue; // If there's no comma, it's an unweighted profile. else if (!SanitizedEntry.contains(',')) addWeightedInput(WFV, {std::string(SanitizedEntry), 1}); else addWeightedInput(WFV, parseWeightedFile(SanitizedEntry)); } } static int merge_main(int argc, const char *argv[]) { cl::list InputFilenames(cl::Positional, cl::desc("")); cl::list WeightedInputFilenames("weighted-input", cl::desc(",")); cl::opt InputFilenamesFile( "input-files", cl::init(""), cl::desc("Path to file containing newline-separated " "[,] entries")); cl::alias InputFilenamesFileA("f", cl::desc("Alias for --input-files"), cl::aliasopt(InputFilenamesFile)); cl::opt DumpInputFileList( "dump-input-file-list", cl::init(false), cl::Hidden, cl::desc("Dump the list of input files and their weights, then exit")); cl::opt RemappingFile("remapping-file", cl::value_desc("file"), cl::desc("Symbol remapping file")); cl::alias RemappingFileA("r", cl::desc("Alias for --remapping-file"), cl::aliasopt(RemappingFile)); cl::opt OutputFilename("output", cl::value_desc("output"), cl::init("-"), cl::desc("Output file")); cl::alias OutputFilenameA("o", cl::desc("Alias for --output"), cl::aliasopt(OutputFilename)); cl::opt ProfileKind( cl::desc("Profile kind:"), cl::init(instr), cl::values(clEnumVal(instr, "Instrumentation profile (default)"), clEnumVal(sample, "Sample profile"))); cl::opt OutputFormat( cl::desc("Format of output profile"), cl::init(PF_Binary), cl::values( clEnumValN(PF_Binary, "binary", "Binary encoding (default)"), clEnumValN(PF_Compact_Binary, "compbinary", "Compact binary encoding"), clEnumValN(PF_Ext_Binary, "extbinary", "Extensible binary encoding"), clEnumValN(PF_Text, "text", "Text encoding"), clEnumValN(PF_GCC, "gcc", "GCC encoding (only meaningful for -sample)"))); cl::opt FailureMode( "failure-mode", cl::init(failIfAnyAreInvalid), cl::desc("Failure mode:"), cl::values(clEnumValN(failIfAnyAreInvalid, "any", "Fail if any profile is invalid."), clEnumValN(failIfAllAreInvalid, "all", "Fail only if all profiles are invalid."))); cl::opt OutputSparse("sparse", cl::init(false), cl::desc("Generate a sparse profile (only meaningful for -instr)")); cl::opt NumThreads( "num-threads", cl::init(0), cl::desc("Number of merge threads to use (default: autodetect)")); cl::alias NumThreadsA("j", cl::desc("Alias for --num-threads"), cl::aliasopt(NumThreads)); cl::opt ProfileSymbolListFile( "prof-sym-list", cl::init(""), cl::desc("Path to file containing the list of function symbols " "used to populate profile symbol list")); cl::opt CompressAllSections( "compress-all-sections", cl::init(false), cl::Hidden, cl::desc("Compress all sections when writing the profile (only " "meaningful for -extbinary)")); cl::opt UseMD5( "use-md5", cl::init(false), cl::Hidden, cl::desc("Choose to use MD5 to represent string in name table (only " "meaningful for -extbinary)")); cl::opt SampleMergeColdContext( "sample-merge-cold-context", cl::init(false), cl::Hidden, cl::desc( "Merge context sample profiles whose count is below cold threshold")); cl::opt SampleTrimColdContext( "sample-trim-cold-context", cl::init(false), cl::Hidden, cl::desc( "Trim context sample profiles whose count is below cold threshold")); cl::opt SampleColdContextFrameDepth( "sample-frame-depth-for-cold-context", cl::init(1), cl::desc("Keep the last K frames while merging cold profile. 1 means the " "context-less base profile")); cl::opt GenPartialProfile( "gen-partial-profile", cl::init(false), cl::Hidden, cl::desc("Generate a partial profile (only meaningful for -extbinary)")); cl::opt SupplInstrWithSample( "supplement-instr-with-sample", cl::init(""), cl::Hidden, cl::desc("Supplement an instr profile with sample profile, to correct " "the profile unrepresentativeness issue. The sample " "profile is the input of the flag. Output will be in instr " "format (The flag only works with -instr)")); cl::opt ZeroCounterThreshold( "zero-counter-threshold", cl::init(0.7), cl::Hidden, cl::desc("For the function which is cold in instr profile but hot in " "sample profile, if the ratio of the number of zero counters " "divided by the total number of counters is above the " "threshold, the profile of the function will be regarded as " "being harmful for performance and will be dropped.")); cl::opt SupplMinSizeThreshold( "suppl-min-size-threshold", cl::init(10), cl::Hidden, cl::desc("If the size of a function is smaller than the threshold, " "assume it can be inlined by PGO early inliner and it won't " "be adjusted based on sample profile.")); cl::opt InstrProfColdThreshold( "instr-prof-cold-threshold", cl::init(0), cl::Hidden, cl::desc("User specified cold threshold for instr profile which will " "override the cold threshold got from profile summary. ")); cl::opt GenCSNestedProfile( "gen-cs-nested-profile", cl::Hidden, cl::init(false), cl::desc("Generate nested function profiles for CSSPGO")); cl::opt DebugInfoFilename( "debug-info", cl::init(""), cl::desc("Use the provided debug info to correlate the raw profile.")); cl::opt ProfiledBinary( "profiled-binary", cl::init(""), cl::desc("Path to binary from which the profile was collected.")); cl::ParseCommandLineOptions(argc, argv, "LLVM profile data merger\n"); WeightedFileVector WeightedInputs; for (StringRef Filename : InputFilenames) addWeightedInput(WeightedInputs, {std::string(Filename), 1}); for (StringRef WeightedFilename : WeightedInputFilenames) addWeightedInput(WeightedInputs, parseWeightedFile(WeightedFilename)); // Make sure that the file buffer stays alive for the duration of the // weighted input vector's lifetime. auto Buffer = getInputFileBuf(InputFilenamesFile); parseInputFilenamesFile(Buffer.get(), WeightedInputs); if (WeightedInputs.empty()) exitWithError("no input files specified. See " + sys::path::filename(argv[0]) + " -help"); if (DumpInputFileList) { for (auto &WF : WeightedInputs) outs() << WF.Weight << "," << WF.Filename << "\n"; return 0; } std::unique_ptr Remapper; if (!RemappingFile.empty()) Remapper = SymbolRemapper::create(RemappingFile); if (!SupplInstrWithSample.empty()) { if (ProfileKind != instr) exitWithError( "-supplement-instr-with-sample can only work with -instr. "); supplementInstrProfile(WeightedInputs, SupplInstrWithSample, OutputFilename, OutputFormat, OutputSparse, SupplMinSizeThreshold, ZeroCounterThreshold, InstrProfColdThreshold); return 0; } if (ProfileKind == instr) mergeInstrProfile(WeightedInputs, DebugInfoFilename, Remapper.get(), OutputFilename, OutputFormat, OutputSparse, NumThreads, FailureMode, ProfiledBinary); else mergeSampleProfile(WeightedInputs, Remapper.get(), OutputFilename, OutputFormat, ProfileSymbolListFile, CompressAllSections, UseMD5, GenPartialProfile, GenCSNestedProfile, SampleMergeColdContext, SampleTrimColdContext, SampleColdContextFrameDepth, FailureMode); return 0; } /// Computer the overlap b/w profile BaseFilename and profile TestFilename. static void overlapInstrProfile(const std::string &BaseFilename, const std::string &TestFilename, const OverlapFuncFilters &FuncFilter, raw_fd_ostream &OS, bool IsCS) { std::mutex ErrorLock; SmallSet WriterErrorCodes; WriterContext Context(false, ErrorLock, WriterErrorCodes); WeightedFile WeightedInput{BaseFilename, 1}; OverlapStats Overlap; Error E = Overlap.accumulateCounts(BaseFilename, TestFilename, IsCS); if (E) exitWithError(std::move(E), "error in getting profile count sums"); if (Overlap.Base.CountSum < 1.0f) { OS << "Sum of edge counts for profile " << BaseFilename << " is 0.\n"; exit(0); } if (Overlap.Test.CountSum < 1.0f) { OS << "Sum of edge counts for profile " << TestFilename << " is 0.\n"; exit(0); } loadInput(WeightedInput, nullptr, nullptr, /*ProfiledBinary=*/"", &Context); overlapInput(BaseFilename, TestFilename, &Context, Overlap, FuncFilter, OS, IsCS); Overlap.dump(OS); } namespace { struct SampleOverlapStats { SampleContext BaseName; SampleContext TestName; // Number of overlap units uint64_t OverlapCount; // Total samples of overlap units uint64_t OverlapSample; // Number of and total samples of units that only present in base or test // profile uint64_t BaseUniqueCount; uint64_t BaseUniqueSample; uint64_t TestUniqueCount; uint64_t TestUniqueSample; // Number of units and total samples in base or test profile uint64_t BaseCount; uint64_t BaseSample; uint64_t TestCount; uint64_t TestSample; // Number of and total samples of units that present in at least one profile uint64_t UnionCount; uint64_t UnionSample; // Weighted similarity double Similarity; // For SampleOverlapStats instances representing functions, weights of the // function in base and test profiles double BaseWeight; double TestWeight; SampleOverlapStats() : OverlapCount(0), OverlapSample(0), BaseUniqueCount(0), BaseUniqueSample(0), TestUniqueCount(0), TestUniqueSample(0), BaseCount(0), BaseSample(0), TestCount(0), TestSample(0), UnionCount(0), UnionSample(0), Similarity(0.0), BaseWeight(0.0), TestWeight(0.0) {} }; } // end anonymous namespace namespace { struct FuncSampleStats { uint64_t SampleSum; uint64_t MaxSample; uint64_t HotBlockCount; FuncSampleStats() : SampleSum(0), MaxSample(0), HotBlockCount(0) {} FuncSampleStats(uint64_t SampleSum, uint64_t MaxSample, uint64_t HotBlockCount) : SampleSum(SampleSum), MaxSample(MaxSample), HotBlockCount(HotBlockCount) {} }; } // end anonymous namespace namespace { enum MatchStatus { MS_Match, MS_FirstUnique, MS_SecondUnique, MS_None }; // Class for updating merging steps for two sorted maps. The class should be // instantiated with a map iterator type. template class MatchStep { public: MatchStep() = delete; MatchStep(T FirstIter, T FirstEnd, T SecondIter, T SecondEnd) : FirstIter(FirstIter), FirstEnd(FirstEnd), SecondIter(SecondIter), SecondEnd(SecondEnd), Status(MS_None) {} bool areBothFinished() const { return (FirstIter == FirstEnd && SecondIter == SecondEnd); } bool isFirstFinished() const { return FirstIter == FirstEnd; } bool isSecondFinished() const { return SecondIter == SecondEnd; } /// Advance one step based on the previous match status unless the previous /// status is MS_None. Then update Status based on the comparison between two /// container iterators at the current step. If the previous status is /// MS_None, it means two iterators are at the beginning and no comparison has /// been made, so we simply update Status without advancing the iterators. void updateOneStep(); T getFirstIter() const { return FirstIter; } T getSecondIter() const { return SecondIter; } MatchStatus getMatchStatus() const { return Status; } private: // Current iterator and end iterator of the first container. T FirstIter; T FirstEnd; // Current iterator and end iterator of the second container. T SecondIter; T SecondEnd; // Match status of the current step. MatchStatus Status; }; } // end anonymous namespace template void MatchStep::updateOneStep() { switch (Status) { case MS_Match: ++FirstIter; ++SecondIter; break; case MS_FirstUnique: ++FirstIter; break; case MS_SecondUnique: ++SecondIter; break; case MS_None: break; } // Update Status according to iterators at the current step. if (areBothFinished()) return; if (FirstIter != FirstEnd && (SecondIter == SecondEnd || FirstIter->first < SecondIter->first)) Status = MS_FirstUnique; else if (SecondIter != SecondEnd && (FirstIter == FirstEnd || SecondIter->first < FirstIter->first)) Status = MS_SecondUnique; else Status = MS_Match; } // Return the sum of line/block samples, the max line/block sample, and the // number of line/block samples above the given threshold in a function // including its inlinees. static void getFuncSampleStats(const sampleprof::FunctionSamples &Func, FuncSampleStats &FuncStats, uint64_t HotThreshold) { for (const auto &L : Func.getBodySamples()) { uint64_t Sample = L.second.getSamples(); FuncStats.SampleSum += Sample; FuncStats.MaxSample = std::max(FuncStats.MaxSample, Sample); if (Sample >= HotThreshold) ++FuncStats.HotBlockCount; } for (const auto &C : Func.getCallsiteSamples()) { for (const auto &F : C.second) getFuncSampleStats(F.second, FuncStats, HotThreshold); } } /// Predicate that determines if a function is hot with a given threshold. We /// keep it separate from its callsites for possible extension in the future. static bool isFunctionHot(const FuncSampleStats &FuncStats, uint64_t HotThreshold) { // We intentionally compare the maximum sample count in a function with the // HotThreshold to get an approximate determination on hot functions. return (FuncStats.MaxSample >= HotThreshold); } namespace { class SampleOverlapAggregator { public: SampleOverlapAggregator(const std::string &BaseFilename, const std::string &TestFilename, double LowSimilarityThreshold, double Epsilon, const OverlapFuncFilters &FuncFilter) : BaseFilename(BaseFilename), TestFilename(TestFilename), LowSimilarityThreshold(LowSimilarityThreshold), Epsilon(Epsilon), FuncFilter(FuncFilter) {} /// Detect 0-sample input profile and report to output stream. This interface /// should be called after loadProfiles(). bool detectZeroSampleProfile(raw_fd_ostream &OS) const; /// Write out function-level similarity statistics for functions specified by /// options --function, --value-cutoff, and --similarity-cutoff. void dumpFuncSimilarity(raw_fd_ostream &OS) const; /// Write out program-level similarity and overlap statistics. void dumpProgramSummary(raw_fd_ostream &OS) const; /// Write out hot-function and hot-block statistics for base_profile, /// test_profile, and their overlap. For both cases, the overlap HO is /// calculated as follows: /// Given the number of functions (or blocks) that are hot in both profiles /// HCommon and the number of functions (or blocks) that are hot in at /// least one profile HUnion, HO = HCommon / HUnion. void dumpHotFuncAndBlockOverlap(raw_fd_ostream &OS) const; /// This function tries matching functions in base and test profiles. For each /// pair of matched functions, it aggregates the function-level /// similarity into a profile-level similarity. It also dump function-level /// similarity information of functions specified by --function, /// --value-cutoff, and --similarity-cutoff options. The program-level /// similarity PS is computed as follows: /// Given function-level similarity FS(A) for all function A, the /// weight of function A in base profile WB(A), and the weight of function /// A in test profile WT(A), compute PS(base_profile, test_profile) = /// sum_A(FS(A) * avg(WB(A), WT(A))) ranging in [0.0f to 1.0f] with 0.0 /// meaning no-overlap. void computeSampleProfileOverlap(raw_fd_ostream &OS); /// Initialize ProfOverlap with the sum of samples in base and test /// profiles. This function also computes and keeps the sum of samples and /// max sample counts of each function in BaseStats and TestStats for later /// use to avoid re-computations. void initializeSampleProfileOverlap(); /// Load profiles specified by BaseFilename and TestFilename. std::error_code loadProfiles(); using FuncSampleStatsMap = std::unordered_map; private: SampleOverlapStats ProfOverlap; SampleOverlapStats HotFuncOverlap; SampleOverlapStats HotBlockOverlap; std::string BaseFilename; std::string TestFilename; std::unique_ptr BaseReader; std::unique_ptr TestReader; // BaseStats and TestStats hold FuncSampleStats for each function, with // function name as the key. FuncSampleStatsMap BaseStats; FuncSampleStatsMap TestStats; // Low similarity threshold in floating point number double LowSimilarityThreshold; // Block samples above BaseHotThreshold or TestHotThreshold are considered hot // for tracking hot blocks. uint64_t BaseHotThreshold; uint64_t TestHotThreshold; // A small threshold used to round the results of floating point accumulations // to resolve imprecision. const double Epsilon; std::multimap> FuncSimilarityDump; // FuncFilter carries specifications in options --value-cutoff and // --function. OverlapFuncFilters FuncFilter; // Column offsets for printing the function-level details table. static const unsigned int TestWeightCol = 15; static const unsigned int SimilarityCol = 30; static const unsigned int OverlapCol = 43; static const unsigned int BaseUniqueCol = 53; static const unsigned int TestUniqueCol = 67; static const unsigned int BaseSampleCol = 81; static const unsigned int TestSampleCol = 96; static const unsigned int FuncNameCol = 111; /// Return a similarity of two line/block sample counters in the same /// function in base and test profiles. The line/block-similarity BS(i) is /// computed as follows: /// For an offsets i, given the sample count at i in base profile BB(i), /// the sample count at i in test profile BT(i), the sum of sample counts /// in this function in base profile SB, and the sum of sample counts in /// this function in test profile ST, compute BS(i) = 1.0 - fabs(BB(i)/SB - /// BT(i)/ST), ranging in [0.0f to 1.0f] with 0.0 meaning no-overlap. double computeBlockSimilarity(uint64_t BaseSample, uint64_t TestSample, const SampleOverlapStats &FuncOverlap) const; void updateHotBlockOverlap(uint64_t BaseSample, uint64_t TestSample, uint64_t HotBlockCount); void getHotFunctions(const FuncSampleStatsMap &ProfStats, FuncSampleStatsMap &HotFunc, uint64_t HotThreshold) const; void computeHotFuncOverlap(); /// This function updates statistics in FuncOverlap, HotBlockOverlap, and /// Difference for two sample units in a matched function according to the /// given match status. void updateOverlapStatsForFunction(uint64_t BaseSample, uint64_t TestSample, uint64_t HotBlockCount, SampleOverlapStats &FuncOverlap, double &Difference, MatchStatus Status); /// This function updates statistics in FuncOverlap, HotBlockOverlap, and /// Difference for unmatched callees that only present in one profile in a /// matched caller function. void updateForUnmatchedCallee(const sampleprof::FunctionSamples &Func, SampleOverlapStats &FuncOverlap, double &Difference, MatchStatus Status); /// This function updates sample overlap statistics of an overlap function in /// base and test profile. It also calculates a function-internal similarity /// FIS as follows: /// For offsets i that have samples in at least one profile in this /// function A, given BS(i) returned by computeBlockSimilarity(), compute /// FIS(A) = (2.0 - sum_i(1.0 - BS(i))) / 2, ranging in [0.0f to 1.0f] with /// 0.0 meaning no overlap. double computeSampleFunctionInternalOverlap( const sampleprof::FunctionSamples &BaseFunc, const sampleprof::FunctionSamples &TestFunc, SampleOverlapStats &FuncOverlap); /// Function-level similarity (FS) is a weighted value over function internal /// similarity (FIS). This function computes a function's FS from its FIS by /// applying the weight. double weightForFuncSimilarity(double FuncSimilarity, uint64_t BaseFuncSample, uint64_t TestFuncSample) const; /// The function-level similarity FS(A) for a function A is computed as /// follows: /// Compute a function-internal similarity FIS(A) by /// computeSampleFunctionInternalOverlap(). Then, with the weight of /// function A in base profile WB(A), and the weight of function A in test /// profile WT(A), compute FS(A) = FIS(A) * (1.0 - fabs(WB(A) - WT(A))) /// ranging in [0.0f to 1.0f] with 0.0 meaning no overlap. double computeSampleFunctionOverlap(const sampleprof::FunctionSamples *BaseFunc, const sampleprof::FunctionSamples *TestFunc, SampleOverlapStats *FuncOverlap, uint64_t BaseFuncSample, uint64_t TestFuncSample); /// Profile-level similarity (PS) is a weighted aggregate over function-level /// similarities (FS). This method weights the FS value by the function /// weights in the base and test profiles for the aggregation. double weightByImportance(double FuncSimilarity, uint64_t BaseFuncSample, uint64_t TestFuncSample) const; }; } // end anonymous namespace bool SampleOverlapAggregator::detectZeroSampleProfile( raw_fd_ostream &OS) const { bool HaveZeroSample = false; if (ProfOverlap.BaseSample == 0) { OS << "Sum of sample counts for profile " << BaseFilename << " is 0.\n"; HaveZeroSample = true; } if (ProfOverlap.TestSample == 0) { OS << "Sum of sample counts for profile " << TestFilename << " is 0.\n"; HaveZeroSample = true; } return HaveZeroSample; } double SampleOverlapAggregator::computeBlockSimilarity( uint64_t BaseSample, uint64_t TestSample, const SampleOverlapStats &FuncOverlap) const { double BaseFrac = 0.0; double TestFrac = 0.0; if (FuncOverlap.BaseSample > 0) BaseFrac = static_cast(BaseSample) / FuncOverlap.BaseSample; if (FuncOverlap.TestSample > 0) TestFrac = static_cast(TestSample) / FuncOverlap.TestSample; return 1.0 - std::fabs(BaseFrac - TestFrac); } void SampleOverlapAggregator::updateHotBlockOverlap(uint64_t BaseSample, uint64_t TestSample, uint64_t HotBlockCount) { bool IsBaseHot = (BaseSample >= BaseHotThreshold); bool IsTestHot = (TestSample >= TestHotThreshold); if (!IsBaseHot && !IsTestHot) return; HotBlockOverlap.UnionCount += HotBlockCount; if (IsBaseHot) HotBlockOverlap.BaseCount += HotBlockCount; if (IsTestHot) HotBlockOverlap.TestCount += HotBlockCount; if (IsBaseHot && IsTestHot) HotBlockOverlap.OverlapCount += HotBlockCount; } void SampleOverlapAggregator::getHotFunctions( const FuncSampleStatsMap &ProfStats, FuncSampleStatsMap &HotFunc, uint64_t HotThreshold) const { for (const auto &F : ProfStats) { if (isFunctionHot(F.second, HotThreshold)) HotFunc.emplace(F.first, F.second); } } void SampleOverlapAggregator::computeHotFuncOverlap() { FuncSampleStatsMap BaseHotFunc; getHotFunctions(BaseStats, BaseHotFunc, BaseHotThreshold); HotFuncOverlap.BaseCount = BaseHotFunc.size(); FuncSampleStatsMap TestHotFunc; getHotFunctions(TestStats, TestHotFunc, TestHotThreshold); HotFuncOverlap.TestCount = TestHotFunc.size(); HotFuncOverlap.UnionCount = HotFuncOverlap.TestCount; for (const auto &F : BaseHotFunc) { if (TestHotFunc.count(F.first)) ++HotFuncOverlap.OverlapCount; else ++HotFuncOverlap.UnionCount; } } void SampleOverlapAggregator::updateOverlapStatsForFunction( uint64_t BaseSample, uint64_t TestSample, uint64_t HotBlockCount, SampleOverlapStats &FuncOverlap, double &Difference, MatchStatus Status) { assert(Status != MS_None && "Match status should be updated before updating overlap statistics"); if (Status == MS_FirstUnique) { TestSample = 0; FuncOverlap.BaseUniqueSample += BaseSample; } else if (Status == MS_SecondUnique) { BaseSample = 0; FuncOverlap.TestUniqueSample += TestSample; } else { ++FuncOverlap.OverlapCount; } FuncOverlap.UnionSample += std::max(BaseSample, TestSample); FuncOverlap.OverlapSample += std::min(BaseSample, TestSample); Difference += 1.0 - computeBlockSimilarity(BaseSample, TestSample, FuncOverlap); updateHotBlockOverlap(BaseSample, TestSample, HotBlockCount); } void SampleOverlapAggregator::updateForUnmatchedCallee( const sampleprof::FunctionSamples &Func, SampleOverlapStats &FuncOverlap, double &Difference, MatchStatus Status) { assert((Status == MS_FirstUnique || Status == MS_SecondUnique) && "Status must be either of the two unmatched cases"); FuncSampleStats FuncStats; if (Status == MS_FirstUnique) { getFuncSampleStats(Func, FuncStats, BaseHotThreshold); updateOverlapStatsForFunction(FuncStats.SampleSum, 0, FuncStats.HotBlockCount, FuncOverlap, Difference, Status); } else { getFuncSampleStats(Func, FuncStats, TestHotThreshold); updateOverlapStatsForFunction(0, FuncStats.SampleSum, FuncStats.HotBlockCount, FuncOverlap, Difference, Status); } } double SampleOverlapAggregator::computeSampleFunctionInternalOverlap( const sampleprof::FunctionSamples &BaseFunc, const sampleprof::FunctionSamples &TestFunc, SampleOverlapStats &FuncOverlap) { using namespace sampleprof; double Difference = 0; // Accumulate Difference for regular line/block samples in the function. // We match them through sort-merge join algorithm because // FunctionSamples::getBodySamples() returns a map of sample counters ordered // by their offsets. MatchStep BlockIterStep( BaseFunc.getBodySamples().cbegin(), BaseFunc.getBodySamples().cend(), TestFunc.getBodySamples().cbegin(), TestFunc.getBodySamples().cend()); BlockIterStep.updateOneStep(); while (!BlockIterStep.areBothFinished()) { uint64_t BaseSample = BlockIterStep.isFirstFinished() ? 0 : BlockIterStep.getFirstIter()->second.getSamples(); uint64_t TestSample = BlockIterStep.isSecondFinished() ? 0 : BlockIterStep.getSecondIter()->second.getSamples(); updateOverlapStatsForFunction(BaseSample, TestSample, 1, FuncOverlap, Difference, BlockIterStep.getMatchStatus()); BlockIterStep.updateOneStep(); } // Accumulate Difference for callsite lines in the function. We match // them through sort-merge algorithm because // FunctionSamples::getCallsiteSamples() returns a map of callsite records // ordered by their offsets. MatchStep CallsiteIterStep( BaseFunc.getCallsiteSamples().cbegin(), BaseFunc.getCallsiteSamples().cend(), TestFunc.getCallsiteSamples().cbegin(), TestFunc.getCallsiteSamples().cend()); CallsiteIterStep.updateOneStep(); while (!CallsiteIterStep.areBothFinished()) { MatchStatus CallsiteStepStatus = CallsiteIterStep.getMatchStatus(); assert(CallsiteStepStatus != MS_None && "Match status should be updated before entering loop body"); if (CallsiteStepStatus != MS_Match) { auto Callsite = (CallsiteStepStatus == MS_FirstUnique) ? CallsiteIterStep.getFirstIter() : CallsiteIterStep.getSecondIter(); for (const auto &F : Callsite->second) updateForUnmatchedCallee(F.second, FuncOverlap, Difference, CallsiteStepStatus); } else { // There may be multiple inlinees at the same offset, so we need to try // matching all of them. This match is implemented through sort-merge // algorithm because callsite records at the same offset are ordered by // function names. MatchStep CalleeIterStep( CallsiteIterStep.getFirstIter()->second.cbegin(), CallsiteIterStep.getFirstIter()->second.cend(), CallsiteIterStep.getSecondIter()->second.cbegin(), CallsiteIterStep.getSecondIter()->second.cend()); CalleeIterStep.updateOneStep(); while (!CalleeIterStep.areBothFinished()) { MatchStatus CalleeStepStatus = CalleeIterStep.getMatchStatus(); if (CalleeStepStatus != MS_Match) { auto Callee = (CalleeStepStatus == MS_FirstUnique) ? CalleeIterStep.getFirstIter() : CalleeIterStep.getSecondIter(); updateForUnmatchedCallee(Callee->second, FuncOverlap, Difference, CalleeStepStatus); } else { // An inlined function can contain other inlinees inside, so compute // the Difference recursively. Difference += 2.0 - 2 * computeSampleFunctionInternalOverlap( CalleeIterStep.getFirstIter()->second, CalleeIterStep.getSecondIter()->second, FuncOverlap); } CalleeIterStep.updateOneStep(); } } CallsiteIterStep.updateOneStep(); } // Difference reflects the total differences of line/block samples in this // function and ranges in [0.0f to 2.0f]. Take (2.0 - Difference) / 2 to // reflect the similarity between function profiles in [0.0f to 1.0f]. return (2.0 - Difference) / 2; } double SampleOverlapAggregator::weightForFuncSimilarity( double FuncInternalSimilarity, uint64_t BaseFuncSample, uint64_t TestFuncSample) const { // Compute the weight as the distance between the function weights in two // profiles. double BaseFrac = 0.0; double TestFrac = 0.0; assert(ProfOverlap.BaseSample > 0 && "Total samples in base profile should be greater than 0"); BaseFrac = static_cast(BaseFuncSample) / ProfOverlap.BaseSample; assert(ProfOverlap.TestSample > 0 && "Total samples in test profile should be greater than 0"); TestFrac = static_cast(TestFuncSample) / ProfOverlap.TestSample; double WeightDistance = std::fabs(BaseFrac - TestFrac); // Take WeightDistance into the similarity. return FuncInternalSimilarity * (1 - WeightDistance); } double SampleOverlapAggregator::weightByImportance(double FuncSimilarity, uint64_t BaseFuncSample, uint64_t TestFuncSample) const { double BaseFrac = 0.0; double TestFrac = 0.0; assert(ProfOverlap.BaseSample > 0 && "Total samples in base profile should be greater than 0"); BaseFrac = static_cast(BaseFuncSample) / ProfOverlap.BaseSample / 2.0; assert(ProfOverlap.TestSample > 0 && "Total samples in test profile should be greater than 0"); TestFrac = static_cast(TestFuncSample) / ProfOverlap.TestSample / 2.0; return FuncSimilarity * (BaseFrac + TestFrac); } double SampleOverlapAggregator::computeSampleFunctionOverlap( const sampleprof::FunctionSamples *BaseFunc, const sampleprof::FunctionSamples *TestFunc, SampleOverlapStats *FuncOverlap, uint64_t BaseFuncSample, uint64_t TestFuncSample) { // Default function internal similarity before weighted, meaning two functions // has no overlap. const double DefaultFuncInternalSimilarity = 0; double FuncSimilarity; double FuncInternalSimilarity; // If BaseFunc or TestFunc is nullptr, it means the functions do not overlap. // In this case, we use DefaultFuncInternalSimilarity as the function internal // similarity. if (!BaseFunc || !TestFunc) { FuncInternalSimilarity = DefaultFuncInternalSimilarity; } else { assert(FuncOverlap != nullptr && "FuncOverlap should be provided in this case"); FuncInternalSimilarity = computeSampleFunctionInternalOverlap( *BaseFunc, *TestFunc, *FuncOverlap); // Now, FuncInternalSimilarity may be a little less than 0 due to // imprecision of floating point accumulations. Make it zero if the // difference is below Epsilon. FuncInternalSimilarity = (std::fabs(FuncInternalSimilarity - 0) < Epsilon) ? 0 : FuncInternalSimilarity; } FuncSimilarity = weightForFuncSimilarity(FuncInternalSimilarity, BaseFuncSample, TestFuncSample); return FuncSimilarity; } void SampleOverlapAggregator::computeSampleProfileOverlap(raw_fd_ostream &OS) { using namespace sampleprof; std::unordered_map BaseFuncProf; const auto &BaseProfiles = BaseReader->getProfiles(); for (const auto &BaseFunc : BaseProfiles) { BaseFuncProf.emplace(BaseFunc.second.getContext(), &(BaseFunc.second)); } ProfOverlap.UnionCount = BaseFuncProf.size(); const auto &TestProfiles = TestReader->getProfiles(); for (const auto &TestFunc : TestProfiles) { SampleOverlapStats FuncOverlap; FuncOverlap.TestName = TestFunc.second.getContext(); assert(TestStats.count(FuncOverlap.TestName) && "TestStats should have records for all functions in test profile " "except inlinees"); FuncOverlap.TestSample = TestStats[FuncOverlap.TestName].SampleSum; bool Matched = false; const auto Match = BaseFuncProf.find(FuncOverlap.TestName); if (Match == BaseFuncProf.end()) { const FuncSampleStats &FuncStats = TestStats[FuncOverlap.TestName]; ++ProfOverlap.TestUniqueCount; ProfOverlap.TestUniqueSample += FuncStats.SampleSum; FuncOverlap.TestUniqueSample = FuncStats.SampleSum; updateHotBlockOverlap(0, FuncStats.SampleSum, FuncStats.HotBlockCount); double FuncSimilarity = computeSampleFunctionOverlap( nullptr, nullptr, nullptr, 0, FuncStats.SampleSum); ProfOverlap.Similarity += weightByImportance(FuncSimilarity, 0, FuncStats.SampleSum); ++ProfOverlap.UnionCount; ProfOverlap.UnionSample += FuncStats.SampleSum; } else { ++ProfOverlap.OverlapCount; // Two functions match with each other. Compute function-level overlap and // aggregate them into profile-level overlap. FuncOverlap.BaseName = Match->second->getContext(); assert(BaseStats.count(FuncOverlap.BaseName) && "BaseStats should have records for all functions in base profile " "except inlinees"); FuncOverlap.BaseSample = BaseStats[FuncOverlap.BaseName].SampleSum; FuncOverlap.Similarity = computeSampleFunctionOverlap( Match->second, &TestFunc.second, &FuncOverlap, FuncOverlap.BaseSample, FuncOverlap.TestSample); ProfOverlap.Similarity += weightByImportance(FuncOverlap.Similarity, FuncOverlap.BaseSample, FuncOverlap.TestSample); ProfOverlap.OverlapSample += FuncOverlap.OverlapSample; ProfOverlap.UnionSample += FuncOverlap.UnionSample; // Accumulate the percentage of base unique and test unique samples into // ProfOverlap. ProfOverlap.BaseUniqueSample += FuncOverlap.BaseUniqueSample; ProfOverlap.TestUniqueSample += FuncOverlap.TestUniqueSample; // Remove matched base functions for later reporting functions not found // in test profile. BaseFuncProf.erase(Match); Matched = true; } // Print function-level similarity information if specified by options. assert(TestStats.count(FuncOverlap.TestName) && "TestStats should have records for all functions in test profile " "except inlinees"); if (TestStats[FuncOverlap.TestName].MaxSample >= FuncFilter.ValueCutoff || (Matched && FuncOverlap.Similarity < LowSimilarityThreshold) || (Matched && !FuncFilter.NameFilter.empty() && FuncOverlap.BaseName.toString().find(FuncFilter.NameFilter) != std::string::npos)) { assert(ProfOverlap.BaseSample > 0 && "Total samples in base profile should be greater than 0"); FuncOverlap.BaseWeight = static_cast(FuncOverlap.BaseSample) / ProfOverlap.BaseSample; assert(ProfOverlap.TestSample > 0 && "Total samples in test profile should be greater than 0"); FuncOverlap.TestWeight = static_cast(FuncOverlap.TestSample) / ProfOverlap.TestSample; FuncSimilarityDump.emplace(FuncOverlap.BaseWeight, FuncOverlap); } } // Traverse through functions in base profile but not in test profile. for (const auto &F : BaseFuncProf) { assert(BaseStats.count(F.second->getContext()) && "BaseStats should have records for all functions in base profile " "except inlinees"); const FuncSampleStats &FuncStats = BaseStats[F.second->getContext()]; ++ProfOverlap.BaseUniqueCount; ProfOverlap.BaseUniqueSample += FuncStats.SampleSum; updateHotBlockOverlap(FuncStats.SampleSum, 0, FuncStats.HotBlockCount); double FuncSimilarity = computeSampleFunctionOverlap( nullptr, nullptr, nullptr, FuncStats.SampleSum, 0); ProfOverlap.Similarity += weightByImportance(FuncSimilarity, FuncStats.SampleSum, 0); ProfOverlap.UnionSample += FuncStats.SampleSum; } // Now, ProfSimilarity may be a little greater than 1 due to imprecision // of floating point accumulations. Make it 1.0 if the difference is below // Epsilon. ProfOverlap.Similarity = (std::fabs(ProfOverlap.Similarity - 1) < Epsilon) ? 1 : ProfOverlap.Similarity; computeHotFuncOverlap(); } void SampleOverlapAggregator::initializeSampleProfileOverlap() { const auto &BaseProf = BaseReader->getProfiles(); for (const auto &I : BaseProf) { ++ProfOverlap.BaseCount; FuncSampleStats FuncStats; getFuncSampleStats(I.second, FuncStats, BaseHotThreshold); ProfOverlap.BaseSample += FuncStats.SampleSum; BaseStats.emplace(I.second.getContext(), FuncStats); } const auto &TestProf = TestReader->getProfiles(); for (const auto &I : TestProf) { ++ProfOverlap.TestCount; FuncSampleStats FuncStats; getFuncSampleStats(I.second, FuncStats, TestHotThreshold); ProfOverlap.TestSample += FuncStats.SampleSum; TestStats.emplace(I.second.getContext(), FuncStats); } ProfOverlap.BaseName = StringRef(BaseFilename); ProfOverlap.TestName = StringRef(TestFilename); } void SampleOverlapAggregator::dumpFuncSimilarity(raw_fd_ostream &OS) const { using namespace sampleprof; if (FuncSimilarityDump.empty()) return; formatted_raw_ostream FOS(OS); FOS << "Function-level details:\n"; FOS << "Base weight"; FOS.PadToColumn(TestWeightCol); FOS << "Test weight"; FOS.PadToColumn(SimilarityCol); FOS << "Similarity"; FOS.PadToColumn(OverlapCol); FOS << "Overlap"; FOS.PadToColumn(BaseUniqueCol); FOS << "Base unique"; FOS.PadToColumn(TestUniqueCol); FOS << "Test unique"; FOS.PadToColumn(BaseSampleCol); FOS << "Base samples"; FOS.PadToColumn(TestSampleCol); FOS << "Test samples"; FOS.PadToColumn(FuncNameCol); FOS << "Function name\n"; for (const auto &F : FuncSimilarityDump) { double OverlapPercent = F.second.UnionSample > 0 ? static_cast(F.second.OverlapSample) / F.second.UnionSample : 0; double BaseUniquePercent = F.second.BaseSample > 0 ? static_cast(F.second.BaseUniqueSample) / F.second.BaseSample : 0; double TestUniquePercent = F.second.TestSample > 0 ? static_cast(F.second.TestUniqueSample) / F.second.TestSample : 0; FOS << format("%.2f%%", F.second.BaseWeight * 100); FOS.PadToColumn(TestWeightCol); FOS << format("%.2f%%", F.second.TestWeight * 100); FOS.PadToColumn(SimilarityCol); FOS << format("%.2f%%", F.second.Similarity * 100); FOS.PadToColumn(OverlapCol); FOS << format("%.2f%%", OverlapPercent * 100); FOS.PadToColumn(BaseUniqueCol); FOS << format("%.2f%%", BaseUniquePercent * 100); FOS.PadToColumn(TestUniqueCol); FOS << format("%.2f%%", TestUniquePercent * 100); FOS.PadToColumn(BaseSampleCol); FOS << F.second.BaseSample; FOS.PadToColumn(TestSampleCol); FOS << F.second.TestSample; FOS.PadToColumn(FuncNameCol); FOS << F.second.TestName.toString() << "\n"; } } void SampleOverlapAggregator::dumpProgramSummary(raw_fd_ostream &OS) const { OS << "Profile overlap infomation for base_profile: " << ProfOverlap.BaseName.toString() << " and test_profile: " << ProfOverlap.TestName.toString() << "\nProgram level:\n"; OS << " Whole program profile similarity: " << format("%.3f%%", ProfOverlap.Similarity * 100) << "\n"; assert(ProfOverlap.UnionSample > 0 && "Total samples in two profile should be greater than 0"); double OverlapPercent = static_cast(ProfOverlap.OverlapSample) / ProfOverlap.UnionSample; assert(ProfOverlap.BaseSample > 0 && "Total samples in base profile should be greater than 0"); double BaseUniquePercent = static_cast(ProfOverlap.BaseUniqueSample) / ProfOverlap.BaseSample; assert(ProfOverlap.TestSample > 0 && "Total samples in test profile should be greater than 0"); double TestUniquePercent = static_cast(ProfOverlap.TestUniqueSample) / ProfOverlap.TestSample; OS << " Whole program sample overlap: " << format("%.3f%%", OverlapPercent * 100) << "\n"; OS << " percentage of samples unique in base profile: " << format("%.3f%%", BaseUniquePercent * 100) << "\n"; OS << " percentage of samples unique in test profile: " << format("%.3f%%", TestUniquePercent * 100) << "\n"; OS << " total samples in base profile: " << ProfOverlap.BaseSample << "\n" << " total samples in test profile: " << ProfOverlap.TestSample << "\n"; assert(ProfOverlap.UnionCount > 0 && "There should be at least one function in two input profiles"); double FuncOverlapPercent = static_cast(ProfOverlap.OverlapCount) / ProfOverlap.UnionCount; OS << " Function overlap: " << format("%.3f%%", FuncOverlapPercent * 100) << "\n"; OS << " overlap functions: " << ProfOverlap.OverlapCount << "\n"; OS << " functions unique in base profile: " << ProfOverlap.BaseUniqueCount << "\n"; OS << " functions unique in test profile: " << ProfOverlap.TestUniqueCount << "\n"; } void SampleOverlapAggregator::dumpHotFuncAndBlockOverlap( raw_fd_ostream &OS) const { assert(HotFuncOverlap.UnionCount > 0 && "There should be at least one hot function in two input profiles"); OS << " Hot-function overlap: " << format("%.3f%%", static_cast(HotFuncOverlap.OverlapCount) / HotFuncOverlap.UnionCount * 100) << "\n"; OS << " overlap hot functions: " << HotFuncOverlap.OverlapCount << "\n"; OS << " hot functions unique in base profile: " << HotFuncOverlap.BaseCount - HotFuncOverlap.OverlapCount << "\n"; OS << " hot functions unique in test profile: " << HotFuncOverlap.TestCount - HotFuncOverlap.OverlapCount << "\n"; assert(HotBlockOverlap.UnionCount > 0 && "There should be at least one hot block in two input profiles"); OS << " Hot-block overlap: " << format("%.3f%%", static_cast(HotBlockOverlap.OverlapCount) / HotBlockOverlap.UnionCount * 100) << "\n"; OS << " overlap hot blocks: " << HotBlockOverlap.OverlapCount << "\n"; OS << " hot blocks unique in base profile: " << HotBlockOverlap.BaseCount - HotBlockOverlap.OverlapCount << "\n"; OS << " hot blocks unique in test profile: " << HotBlockOverlap.TestCount - HotBlockOverlap.OverlapCount << "\n"; } std::error_code SampleOverlapAggregator::loadProfiles() { using namespace sampleprof; LLVMContext Context; auto BaseReaderOrErr = SampleProfileReader::create(BaseFilename, Context, FSDiscriminatorPassOption); if (std::error_code EC = BaseReaderOrErr.getError()) exitWithErrorCode(EC, BaseFilename); auto TestReaderOrErr = SampleProfileReader::create(TestFilename, Context, FSDiscriminatorPassOption); if (std::error_code EC = TestReaderOrErr.getError()) exitWithErrorCode(EC, TestFilename); BaseReader = std::move(BaseReaderOrErr.get()); TestReader = std::move(TestReaderOrErr.get()); if (std::error_code EC = BaseReader->read()) exitWithErrorCode(EC, BaseFilename); if (std::error_code EC = TestReader->read()) exitWithErrorCode(EC, TestFilename); if (BaseReader->profileIsProbeBased() != TestReader->profileIsProbeBased()) exitWithError( "cannot compare probe-based profile with non-probe-based profile"); if (BaseReader->profileIsCS() != TestReader->profileIsCS()) exitWithError("cannot compare CS profile with non-CS profile"); // Load BaseHotThreshold and TestHotThreshold as 99-percentile threshold in // profile summary. ProfileSummary &BasePS = BaseReader->getSummary(); ProfileSummary &TestPS = TestReader->getSummary(); BaseHotThreshold = ProfileSummaryBuilder::getHotCountThreshold(BasePS.getDetailedSummary()); TestHotThreshold = ProfileSummaryBuilder::getHotCountThreshold(TestPS.getDetailedSummary()); return std::error_code(); } void overlapSampleProfile(const std::string &BaseFilename, const std::string &TestFilename, const OverlapFuncFilters &FuncFilter, uint64_t SimilarityCutoff, raw_fd_ostream &OS) { using namespace sampleprof; // We use 0.000005 to initialize OverlapAggr.Epsilon because the final metrics // report 2--3 places after decimal point in percentage numbers. SampleOverlapAggregator OverlapAggr( BaseFilename, TestFilename, static_cast(SimilarityCutoff) / 1000000, 0.000005, FuncFilter); if (std::error_code EC = OverlapAggr.loadProfiles()) exitWithErrorCode(EC); OverlapAggr.initializeSampleProfileOverlap(); if (OverlapAggr.detectZeroSampleProfile(OS)) return; OverlapAggr.computeSampleProfileOverlap(OS); OverlapAggr.dumpProgramSummary(OS); OverlapAggr.dumpHotFuncAndBlockOverlap(OS); OverlapAggr.dumpFuncSimilarity(OS); } static int overlap_main(int argc, const char *argv[]) { cl::opt BaseFilename(cl::Positional, cl::Required, cl::desc("")); cl::opt TestFilename(cl::Positional, cl::Required, cl::desc("")); cl::opt Output("output", cl::value_desc("output"), cl::init("-"), cl::desc("Output file")); cl::alias OutputA("o", cl::desc("Alias for --output"), cl::aliasopt(Output)); cl::opt IsCS( "cs", cl::init(false), cl::desc("For context sensitive PGO counts. Does not work with CSSPGO.")); cl::opt ValueCutoff( "value-cutoff", cl::init(-1), cl::desc( "Function level overlap information for every function (with calling " "context for csspgo) in test " "profile with max count value greater then the parameter value")); cl::opt FuncNameFilter( "function", cl::desc("Function level overlap information for matching functions. For " "CSSPGO this takes a a function name with calling context")); cl::opt SimilarityCutoff( "similarity-cutoff", cl::init(0), cl::desc("For sample profiles, list function names (with calling context " "for csspgo) for overlapped functions " "with similarities below the cutoff (percentage times 10000).")); cl::opt ProfileKind( cl::desc("Profile kind:"), cl::init(instr), cl::values(clEnumVal(instr, "Instrumentation profile (default)"), clEnumVal(sample, "Sample profile"))); cl::ParseCommandLineOptions(argc, argv, "LLVM profile data overlap tool\n"); std::error_code EC; raw_fd_ostream OS(Output.data(), EC, sys::fs::OF_TextWithCRLF); if (EC) exitWithErrorCode(EC, Output); if (ProfileKind == instr) overlapInstrProfile(BaseFilename, TestFilename, OverlapFuncFilters{ValueCutoff, FuncNameFilter}, OS, IsCS); else overlapSampleProfile(BaseFilename, TestFilename, OverlapFuncFilters{ValueCutoff, FuncNameFilter}, SimilarityCutoff, OS); return 0; } namespace { struct ValueSitesStats { ValueSitesStats() : TotalNumValueSites(0), TotalNumValueSitesWithValueProfile(0), TotalNumValues(0) {} uint64_t TotalNumValueSites; uint64_t TotalNumValueSitesWithValueProfile; uint64_t TotalNumValues; std::vector ValueSitesHistogram; }; } // namespace static void traverseAllValueSites(const InstrProfRecord &Func, uint32_t VK, ValueSitesStats &Stats, raw_fd_ostream &OS, InstrProfSymtab *Symtab) { uint32_t NS = Func.getNumValueSites(VK); Stats.TotalNumValueSites += NS; for (size_t I = 0; I < NS; ++I) { uint32_t NV = Func.getNumValueDataForSite(VK, I); std::unique_ptr VD = Func.getValueForSite(VK, I); Stats.TotalNumValues += NV; if (NV) { Stats.TotalNumValueSitesWithValueProfile++; if (NV > Stats.ValueSitesHistogram.size()) Stats.ValueSitesHistogram.resize(NV, 0); Stats.ValueSitesHistogram[NV - 1]++; } uint64_t SiteSum = 0; for (uint32_t V = 0; V < NV; V++) SiteSum += VD[V].Count; if (SiteSum == 0) SiteSum = 1; for (uint32_t V = 0; V < NV; V++) { OS << "\t[ " << format("%2u", I) << ", "; if (Symtab == nullptr) OS << format("%4" PRIu64, VD[V].Value); else OS << Symtab->getFuncName(VD[V].Value); OS << ", " << format("%10" PRId64, VD[V].Count) << " ] (" << format("%.2f%%", (VD[V].Count * 100.0 / SiteSum)) << ")\n"; } } } static void showValueSitesStats(raw_fd_ostream &OS, uint32_t VK, ValueSitesStats &Stats) { OS << " Total number of sites: " << Stats.TotalNumValueSites << "\n"; OS << " Total number of sites with values: " << Stats.TotalNumValueSitesWithValueProfile << "\n"; OS << " Total number of profiled values: " << Stats.TotalNumValues << "\n"; OS << " Value sites histogram:\n\tNumTargets, SiteCount\n"; for (unsigned I = 0; I < Stats.ValueSitesHistogram.size(); I++) { if (Stats.ValueSitesHistogram[I] > 0) OS << "\t" << I + 1 << ", " << Stats.ValueSitesHistogram[I] << "\n"; } } static int showInstrProfile(const std::string &Filename, bool ShowCounts, uint32_t TopN, bool ShowIndirectCallTargets, bool ShowMemOPSizes, bool ShowDetailedSummary, std::vector DetailedSummaryCutoffs, bool ShowAllFunctions, bool ShowCS, uint64_t ValueCutoff, bool OnlyListBelow, const std::string &ShowFunction, bool TextFormat, bool ShowBinaryIds, bool ShowCovered, raw_fd_ostream &OS) { auto ReaderOrErr = InstrProfReader::create(Filename); std::vector Cutoffs = std::move(DetailedSummaryCutoffs); if (ShowDetailedSummary && Cutoffs.empty()) { Cutoffs = ProfileSummaryBuilder::DefaultCutoffs; } InstrProfSummaryBuilder Builder(std::move(Cutoffs)); if (Error E = ReaderOrErr.takeError()) exitWithError(std::move(E), Filename); auto Reader = std::move(ReaderOrErr.get()); bool IsIRInstr = Reader->isIRLevelProfile(); size_t ShownFunctions = 0; size_t BelowCutoffFunctions = 0; int NumVPKind = IPVK_Last - IPVK_First + 1; std::vector VPStats(NumVPKind); auto MinCmp = [](const std::pair &v1, const std::pair &v2) { return v1.second > v2.second; }; std::priority_queue, std::vector>, decltype(MinCmp)> HottestFuncs(MinCmp); if (!TextFormat && OnlyListBelow) { OS << "The list of functions with the maximum counter less than " << ValueCutoff << ":\n"; } // Add marker so that IR-level instrumentation round-trips properly. if (TextFormat && IsIRInstr) OS << ":ir\n"; for (const auto &Func : *Reader) { if (Reader->isIRLevelProfile()) { bool FuncIsCS = NamedInstrProfRecord::hasCSFlagInHash(Func.Hash); if (FuncIsCS != ShowCS) continue; } bool Show = ShowAllFunctions || (!ShowFunction.empty() && Func.Name.contains(ShowFunction)); bool doTextFormatDump = (Show && TextFormat); if (doTextFormatDump) { InstrProfSymtab &Symtab = Reader->getSymtab(); InstrProfWriter::writeRecordInText(Func.Name, Func.Hash, Func, Symtab, OS); continue; } assert(Func.Counts.size() > 0 && "function missing entry counter"); Builder.addRecord(Func); if (ShowCovered) { if (llvm::any_of(Func.Counts, [](uint64_t C) { return C; })) OS << Func.Name << "\n"; continue; } uint64_t FuncMax = 0; uint64_t FuncSum = 0; for (size_t I = 0, E = Func.Counts.size(); I < E; ++I) { if (Func.Counts[I] == (uint64_t)-1) continue; FuncMax = std::max(FuncMax, Func.Counts[I]); FuncSum += Func.Counts[I]; } if (FuncMax < ValueCutoff) { ++BelowCutoffFunctions; if (OnlyListBelow) { OS << " " << Func.Name << ": (Max = " << FuncMax << " Sum = " << FuncSum << ")\n"; } continue; } else if (OnlyListBelow) continue; if (TopN) { if (HottestFuncs.size() == TopN) { if (HottestFuncs.top().second < FuncMax) { HottestFuncs.pop(); HottestFuncs.emplace(std::make_pair(std::string(Func.Name), FuncMax)); } } else HottestFuncs.emplace(std::make_pair(std::string(Func.Name), FuncMax)); } if (Show) { if (!ShownFunctions) OS << "Counters:\n"; ++ShownFunctions; OS << " " << Func.Name << ":\n" << " Hash: " << format("0x%016" PRIx64, Func.Hash) << "\n" << " Counters: " << Func.Counts.size() << "\n"; if (!IsIRInstr) OS << " Function count: " << Func.Counts[0] << "\n"; if (ShowIndirectCallTargets) OS << " Indirect Call Site Count: " << Func.getNumValueSites(IPVK_IndirectCallTarget) << "\n"; uint32_t NumMemOPCalls = Func.getNumValueSites(IPVK_MemOPSize); if (ShowMemOPSizes && NumMemOPCalls > 0) OS << " Number of Memory Intrinsics Calls: " << NumMemOPCalls << "\n"; if (ShowCounts) { OS << " Block counts: ["; size_t Start = (IsIRInstr ? 0 : 1); for (size_t I = Start, E = Func.Counts.size(); I < E; ++I) { OS << (I == Start ? "" : ", ") << Func.Counts[I]; } OS << "]\n"; } if (ShowIndirectCallTargets) { OS << " Indirect Target Results:\n"; traverseAllValueSites(Func, IPVK_IndirectCallTarget, VPStats[IPVK_IndirectCallTarget], OS, &(Reader->getSymtab())); } if (ShowMemOPSizes && NumMemOPCalls > 0) { OS << " Memory Intrinsic Size Results:\n"; traverseAllValueSites(Func, IPVK_MemOPSize, VPStats[IPVK_MemOPSize], OS, nullptr); } } } if (Reader->hasError()) exitWithError(Reader->getError(), Filename); if (TextFormat || ShowCovered) return 0; std::unique_ptr PS(Builder.getSummary()); bool IsIR = Reader->isIRLevelProfile(); OS << "Instrumentation level: " << (IsIR ? "IR" : "Front-end"); if (IsIR) OS << " entry_first = " << Reader->instrEntryBBEnabled(); OS << "\n"; if (ShowAllFunctions || !ShowFunction.empty()) OS << "Functions shown: " << ShownFunctions << "\n"; OS << "Total functions: " << PS->getNumFunctions() << "\n"; if (ValueCutoff > 0) { OS << "Number of functions with maximum count (< " << ValueCutoff << "): " << BelowCutoffFunctions << "\n"; OS << "Number of functions with maximum count (>= " << ValueCutoff << "): " << PS->getNumFunctions() - BelowCutoffFunctions << "\n"; } OS << "Maximum function count: " << PS->getMaxFunctionCount() << "\n"; OS << "Maximum internal block count: " << PS->getMaxInternalCount() << "\n"; if (TopN) { std::vector> SortedHottestFuncs; while (!HottestFuncs.empty()) { SortedHottestFuncs.emplace_back(HottestFuncs.top()); HottestFuncs.pop(); } OS << "Top " << TopN << " functions with the largest internal block counts: \n"; for (auto &hotfunc : llvm::reverse(SortedHottestFuncs)) OS << " " << hotfunc.first << ", max count = " << hotfunc.second << "\n"; } if (ShownFunctions && ShowIndirectCallTargets) { OS << "Statistics for indirect call sites profile:\n"; showValueSitesStats(OS, IPVK_IndirectCallTarget, VPStats[IPVK_IndirectCallTarget]); } if (ShownFunctions && ShowMemOPSizes) { OS << "Statistics for memory intrinsic calls sizes profile:\n"; showValueSitesStats(OS, IPVK_MemOPSize, VPStats[IPVK_MemOPSize]); } if (ShowDetailedSummary) { OS << "Total number of blocks: " << PS->getNumCounts() << "\n"; OS << "Total count: " << PS->getTotalCount() << "\n"; PS->printDetailedSummary(OS); } if (ShowBinaryIds) if (Error E = Reader->printBinaryIds(OS)) exitWithError(std::move(E), Filename); return 0; } static void showSectionInfo(sampleprof::SampleProfileReader *Reader, raw_fd_ostream &OS) { if (!Reader->dumpSectionInfo(OS)) { WithColor::warning() << "-show-sec-info-only is only supported for " << "sample profile in extbinary format and is " << "ignored for other formats.\n"; return; } } namespace { struct HotFuncInfo { std::string FuncName; uint64_t TotalCount; double TotalCountPercent; uint64_t MaxCount; uint64_t EntryCount; HotFuncInfo() : TotalCount(0), TotalCountPercent(0.0f), MaxCount(0), EntryCount(0) {} HotFuncInfo(StringRef FN, uint64_t TS, double TSP, uint64_t MS, uint64_t ES) : FuncName(FN.begin(), FN.end()), TotalCount(TS), TotalCountPercent(TSP), MaxCount(MS), EntryCount(ES) {} }; } // namespace // Print out detailed information about hot functions in PrintValues vector. // Users specify titles and offset of every columns through ColumnTitle and // ColumnOffset. The size of ColumnTitle and ColumnOffset need to be the same // and at least 4. Besides, users can optionally give a HotFuncMetric string to // print out or let it be an empty string. static void dumpHotFunctionList(const std::vector &ColumnTitle, const std::vector &ColumnOffset, const std::vector &PrintValues, uint64_t HotFuncCount, uint64_t TotalFuncCount, uint64_t HotProfCount, uint64_t TotalProfCount, const std::string &HotFuncMetric, uint32_t TopNFunctions, raw_fd_ostream &OS) { assert(ColumnOffset.size() == ColumnTitle.size() && "ColumnOffset and ColumnTitle should have the same size"); assert(ColumnTitle.size() >= 4 && "ColumnTitle should have at least 4 elements"); assert(TotalFuncCount > 0 && "There should be at least one function in the profile"); double TotalProfPercent = 0; if (TotalProfCount > 0) TotalProfPercent = static_cast(HotProfCount) / TotalProfCount * 100; formatted_raw_ostream FOS(OS); FOS << HotFuncCount << " out of " << TotalFuncCount << " functions with profile (" << format("%.2f%%", (static_cast(HotFuncCount) / TotalFuncCount * 100)) << ") are considered hot functions"; if (!HotFuncMetric.empty()) FOS << " (" << HotFuncMetric << ")"; FOS << ".\n"; FOS << HotProfCount << " out of " << TotalProfCount << " profile counts (" << format("%.2f%%", TotalProfPercent) << ") are from hot functions.\n"; for (size_t I = 0; I < ColumnTitle.size(); ++I) { FOS.PadToColumn(ColumnOffset[I]); FOS << ColumnTitle[I]; } FOS << "\n"; uint32_t Count = 0; for (const auto &R : PrintValues) { if (TopNFunctions && (Count++ == TopNFunctions)) break; FOS.PadToColumn(ColumnOffset[0]); FOS << R.TotalCount << " (" << format("%.2f%%", R.TotalCountPercent) << ")"; FOS.PadToColumn(ColumnOffset[1]); FOS << R.MaxCount; FOS.PadToColumn(ColumnOffset[2]); FOS << R.EntryCount; FOS.PadToColumn(ColumnOffset[3]); FOS << R.FuncName << "\n"; } } static int showHotFunctionList(const sampleprof::SampleProfileMap &Profiles, ProfileSummary &PS, uint32_t TopN, raw_fd_ostream &OS) { using namespace sampleprof; const uint32_t HotFuncCutoff = 990000; auto &SummaryVector = PS.getDetailedSummary(); uint64_t MinCountThreshold = 0; for (const ProfileSummaryEntry &SummaryEntry : SummaryVector) { if (SummaryEntry.Cutoff == HotFuncCutoff) { MinCountThreshold = SummaryEntry.MinCount; break; } } // Traverse all functions in the profile and keep only hot functions. // The following loop also calculates the sum of total samples of all // functions. std::multimap, std::greater> HotFunc; uint64_t ProfileTotalSample = 0; uint64_t HotFuncSample = 0; uint64_t HotFuncCount = 0; for (const auto &I : Profiles) { FuncSampleStats FuncStats; const FunctionSamples &FuncProf = I.second; ProfileTotalSample += FuncProf.getTotalSamples(); getFuncSampleStats(FuncProf, FuncStats, MinCountThreshold); if (isFunctionHot(FuncStats, MinCountThreshold)) { HotFunc.emplace(FuncProf.getTotalSamples(), std::make_pair(&(I.second), FuncStats.MaxSample)); HotFuncSample += FuncProf.getTotalSamples(); ++HotFuncCount; } } std::vector ColumnTitle{"Total sample (%)", "Max sample", "Entry sample", "Function name"}; std::vector ColumnOffset{0, 24, 42, 58}; std::string Metric = std::string("max sample >= ") + std::to_string(MinCountThreshold); std::vector PrintValues; for (const auto &FuncPair : HotFunc) { const FunctionSamples &Func = *FuncPair.second.first; double TotalSamplePercent = (ProfileTotalSample > 0) ? (Func.getTotalSamples() * 100.0) / ProfileTotalSample : 0; PrintValues.emplace_back( HotFuncInfo(Func.getContext().toString(), Func.getTotalSamples(), TotalSamplePercent, FuncPair.second.second, Func.getHeadSamplesEstimate())); } dumpHotFunctionList(ColumnTitle, ColumnOffset, PrintValues, HotFuncCount, Profiles.size(), HotFuncSample, ProfileTotalSample, Metric, TopN, OS); return 0; } static int showSampleProfile(const std::string &Filename, bool ShowCounts, uint32_t TopN, bool ShowAllFunctions, bool ShowDetailedSummary, const std::string &ShowFunction, bool ShowProfileSymbolList, bool ShowSectionInfoOnly, bool ShowHotFuncList, raw_fd_ostream &OS) { using namespace sampleprof; LLVMContext Context; auto ReaderOrErr = SampleProfileReader::create(Filename, Context, FSDiscriminatorPassOption); if (std::error_code EC = ReaderOrErr.getError()) exitWithErrorCode(EC, Filename); auto Reader = std::move(ReaderOrErr.get()); if (ShowSectionInfoOnly) { showSectionInfo(Reader.get(), OS); return 0; } if (std::error_code EC = Reader->read()) exitWithErrorCode(EC, Filename); if (ShowAllFunctions || ShowFunction.empty()) Reader->dump(OS); else // TODO: parse context string to support filtering by contexts. Reader->dumpFunctionProfile(StringRef(ShowFunction), OS); if (ShowProfileSymbolList) { std::unique_ptr ReaderList = Reader->getProfileSymbolList(); ReaderList->dump(OS); } if (ShowDetailedSummary) { auto &PS = Reader->getSummary(); PS.printSummary(OS); PS.printDetailedSummary(OS); } if (ShowHotFuncList || TopN) showHotFunctionList(Reader->getProfiles(), Reader->getSummary(), TopN, OS); return 0; } static int showMemProfProfile(const std::string &Filename, const std::string &ProfiledBinary, raw_fd_ostream &OS) { auto ReaderOr = llvm::memprof::RawMemProfReader::create( Filename, ProfiledBinary, /*KeepNames=*/true); if (Error E = ReaderOr.takeError()) // Since the error can be related to the profile or the binary we do not // pass whence. Instead additional context is provided where necessary in // the error message. exitWithError(std::move(E), /*Whence*/ ""); std::unique_ptr Reader( ReaderOr.get().release()); Reader->printYAML(OS); return 0; } static int showDebugInfoCorrelation(const std::string &Filename, bool ShowDetailedSummary, bool ShowProfileSymbolList, raw_fd_ostream &OS) { std::unique_ptr Correlator; if (auto Err = InstrProfCorrelator::get(Filename).moveInto(Correlator)) exitWithError(std::move(Err), Filename); if (auto Err = Correlator->correlateProfileData()) exitWithError(std::move(Err), Filename); InstrProfSymtab Symtab; if (auto Err = Symtab.create( StringRef(Correlator->getNamesPointer(), Correlator->getNamesSize()))) exitWithError(std::move(Err), Filename); if (ShowProfileSymbolList) Symtab.dumpNames(OS); // TODO: Read "Profile Data Type" from debug info to compute and show how many // counters the section holds. if (ShowDetailedSummary) OS << "Counters section size: 0x" << Twine::utohexstr(Correlator->getCountersSectionSize()) << " bytes\n"; OS << "Found " << Correlator->getDataSize() << " functions\n"; return 0; } static int show_main(int argc, const char *argv[]) { cl::opt Filename(cl::Positional, cl::desc("")); cl::opt ShowCounts("counts", cl::init(false), cl::desc("Show counter values for shown functions")); cl::opt TextFormat( "text", cl::init(false), cl::desc("Show instr profile data in text dump format")); cl::opt ShowIndirectCallTargets( "ic-targets", cl::init(false), cl::desc("Show indirect call site target values for shown functions")); cl::opt ShowMemOPSizes( "memop-sizes", cl::init(false), cl::desc("Show the profiled sizes of the memory intrinsic calls " "for shown functions")); cl::opt ShowDetailedSummary("detailed-summary", cl::init(false), cl::desc("Show detailed profile summary")); cl::list DetailedSummaryCutoffs( cl::CommaSeparated, "detailed-summary-cutoffs", cl::desc( "Cutoff percentages (times 10000) for generating detailed summary"), cl::value_desc("800000,901000,999999")); cl::opt ShowHotFuncList( "hot-func-list", cl::init(false), cl::desc("Show profile summary of a list of hot functions")); cl::opt ShowAllFunctions("all-functions", cl::init(false), cl::desc("Details for every function")); cl::opt ShowCS("showcs", cl::init(false), cl::desc("Show context sensitive counts")); cl::opt ShowFunction("function", cl::desc("Details for matching functions")); cl::opt OutputFilename("output", cl::value_desc("output"), cl::init("-"), cl::desc("Output file")); cl::alias OutputFilenameA("o", cl::desc("Alias for --output"), cl::aliasopt(OutputFilename)); cl::opt ProfileKind( cl::desc("Profile kind:"), cl::init(instr), cl::values(clEnumVal(instr, "Instrumentation profile (default)"), clEnumVal(sample, "Sample profile"), clEnumVal(memory, "MemProf memory access profile"))); cl::opt TopNFunctions( "topn", cl::init(0), cl::desc("Show the list of functions with the largest internal counts")); cl::opt ValueCutoff( "value-cutoff", cl::init(0), cl::desc("Set the count value cutoff. Functions with the maximum count " "less than this value will not be printed out. (Default is 0)")); cl::opt OnlyListBelow( "list-below-cutoff", cl::init(false), cl::desc("Only output names of functions whose max count values are " "below the cutoff value")); cl::opt ShowProfileSymbolList( "show-prof-sym-list", cl::init(false), cl::desc("Show profile symbol list if it exists in the profile. ")); cl::opt ShowSectionInfoOnly( "show-sec-info-only", cl::init(false), cl::desc("Show the information of each section in the sample profile. " "The flag is only usable when the sample profile is in " "extbinary format")); cl::opt ShowBinaryIds("binary-ids", cl::init(false), cl::desc("Show binary ids in the profile. ")); cl::opt DebugInfoFilename( "debug-info", cl::init(""), cl::desc("Read and extract profile metadata from debug info and show " "the functions it found.")); cl::opt ShowCovered( "covered", cl::init(false), cl::desc("Show only the functions that have been executed.")); cl::opt ProfiledBinary( "profiled-binary", cl::init(""), cl::desc("Path to binary from which the profile was collected.")); cl::ParseCommandLineOptions(argc, argv, "LLVM profile data summary\n"); if (Filename.empty() && DebugInfoFilename.empty()) exitWithError( "the positional argument '' is required unless '--" + DebugInfoFilename.ArgStr + "' is provided"); if (Filename == OutputFilename) { errs() << sys::path::filename(argv[0]) << ": Input file name cannot be the same as the output file name!\n"; return 1; } std::error_code EC; raw_fd_ostream OS(OutputFilename.data(), EC, sys::fs::OF_TextWithCRLF); if (EC) exitWithErrorCode(EC, OutputFilename); if (ShowAllFunctions && !ShowFunction.empty()) WithColor::warning() << "-function argument ignored: showing all functions\n"; if (!DebugInfoFilename.empty()) return showDebugInfoCorrelation(DebugInfoFilename, ShowDetailedSummary, ShowProfileSymbolList, OS); if (ProfileKind == instr) return showInstrProfile( Filename, ShowCounts, TopNFunctions, ShowIndirectCallTargets, ShowMemOPSizes, ShowDetailedSummary, DetailedSummaryCutoffs, ShowAllFunctions, ShowCS, ValueCutoff, OnlyListBelow, ShowFunction, TextFormat, ShowBinaryIds, ShowCovered, OS); if (ProfileKind == sample) return showSampleProfile(Filename, ShowCounts, TopNFunctions, ShowAllFunctions, ShowDetailedSummary, ShowFunction, ShowProfileSymbolList, ShowSectionInfoOnly, ShowHotFuncList, OS); return showMemProfProfile(Filename, ProfiledBinary, OS); } int main(int argc, const char *argv[]) { InitLLVM X(argc, argv); StringRef ProgName(sys::path::filename(argv[0])); if (argc > 1) { int (*func)(int, const char *[]) = nullptr; if (strcmp(argv[1], "merge") == 0) func = merge_main; else if (strcmp(argv[1], "show") == 0) func = show_main; else if (strcmp(argv[1], "overlap") == 0) func = overlap_main; if (func) { std::string Invocation(ProgName.str() + " " + argv[1]); argv[1] = Invocation.c_str(); return func(argc - 1, argv + 1); } if (strcmp(argv[1], "-h") == 0 || strcmp(argv[1], "-help") == 0 || strcmp(argv[1], "--help") == 0) { errs() << "OVERVIEW: LLVM profile data tools\n\n" << "USAGE: " << ProgName << " [args...]\n" << "USAGE: " << ProgName << " -help\n\n" << "See each individual command --help for more details.\n" << "Available commands: merge, show, overlap\n"; return 0; } } if (argc < 2) errs() << ProgName << ": No command specified!\n"; else errs() << ProgName << ": Unknown command!\n"; errs() << "USAGE: " << ProgName << " [args...]\n"; return 1; }