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//===- 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/IR/LLVMContext.h"
#include "llvm/ProfileData/InstrProfReader.h"
#include "llvm/ProfileData/InstrProfWriter.h"
#include "llvm/ProfileData/ProfileCommon.h"
#include "llvm/ProfileData/SampleProfReader.h"
#include "llvm/ProfileData/SampleProfWriter.h"
#include "llvm/Support/CommandLine.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 <algorithm>
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 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<InstrProfError>()) {
handleAllErrors(std::move(E), [&](const InstrProfError &IPE) {
instrprof_error instrError = IPE.get();
StringRef Hint = "";
if (instrError == instrprof_error::unrecognized_format) {
// Hint for common error of forgetting --sample for sample profiles.
Hint = "Perhaps you forgot to use the --sample option?";
}
exitWithError(IPE.message(), std::string(Whence), std::string(Hint));
});
}
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 };
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<InstrProfError> 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<MemoryBuffer> File;
DenseMap<StringRef, StringRef> RemappingTable;
public:
/// Build a SymbolRemapper from a file containing a list of old/new symbols.
static std::unique_ptr<SymbolRemapper> create(StringRef InputFile) {
auto BufOrError = MemoryBuffer::getFileOrSTDIN(InputFile);
if (!BufOrError)
exitWithErrorCode(BufOrError.getError(), InputFile);
auto Remapper = std::make_unique<SymbolRemapper>();
Remapper->File = std::move(BufOrError.get());
for (line_iterator LineIt(*Remapper->File, /*SkipBlanks=*/true, '#');
!LineIt.is_at_eof(); ++LineIt) {
std::pair<StringRef, StringRef> 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<WeightedFile, 5> WeightedFileVector;
/// Keep track of merged data and reported errors.
struct WriterContext {
std::mutex Lock;
InstrProfWriter Writer;
std::vector<std::pair<Error, std::string>> Errors;
std::mutex &ErrLock;
SmallSet<instrprof_error, 4> &WriterErrorCodes;
WriterContext(bool IsSparse, std::mutex &ErrLock,
SmallSet<instrprof_error, 4> &WriterErrorCodes)
: Lock(), Writer(IsSparse), Errors(), 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<InstrProfError>(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,
WriterContext *WC) {
std::unique_lock<std::mutex> 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;
auto ReaderOrErr = InstrProfReader::create(Input.Filename);
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<InstrProfError>(IPE), Filename);
return;
}
auto Reader = std::move(ReaderOrErr.get());
bool IsIRProfile = Reader->isIRLevelProfile();
bool HasCSIRProfile = Reader->hasCSIRLevelProfile();
if (WC->Writer.setIsIRLevelProfile(IsIRProfile, HasCSIRProfile)) {
WC->Errors.emplace_back(
make_error<StringError>(
"Merge IR generated profile with Clang generated profile.",
std::error_code()),
Filename);
return;
}
WC->Writer.setInstrEntryBBEnabled(Reader->instrEntryBBEnabled());
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<std::mutex> ErrGuard{WC->ErrLock};
bool firstTime = WC->WriterErrorCodes.insert(IPE).second;
handleMergeWriterError(make_error<InstrProfError>(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<std::mutex> ErrGuard{Dst->ErrLock};
bool firstTime = Dst->WriterErrorCodes.insert(IPE).second;
if (firstTime)
warn(toString(make_error<InstrProfError>(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_Text
: sys::fs::OF_None);
if (EC)
exitWithErrorCode(EC, OutputFilename);
if (OutputFormat == PF_Text) {
if (Error E = Writer.writeText(Output))
exitWithError(std::move(E));
} else {
Writer.write(Output);
}
}
static void mergeInstrProfile(const WeightedFileVector &Inputs,
SymbolRemapper *Remapper,
StringRef OutputFilename,
ProfileFormat OutputFormat, bool OutputSparse,
unsigned NumThreads, FailureMode FailMode) {
if (OutputFilename.compare("-") == 0)
exitWithError("Cannot write indexed profdata format to stdout.");
if (OutputFormat != PF_Binary && OutputFormat != PF_Compact_Binary &&
OutputFormat != PF_Ext_Binary && OutputFormat != PF_Text)
exitWithError("Unknown format is specified.");
std::mutex ErrorLock;
SmallSet<instrprof_error, 4> 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<std::unique_ptr<WriterContext>, 4> Contexts;
for (unsigned I = 0; I < NumThreads; ++I)
Contexts.emplace_back(std::make_unique<WriterContext>(
OutputSparse, ErrorLock, WriterErrorCodes));
if (NumThreads == 1) {
for (const auto &Input : Inputs)
loadInput(Input, Remapper, 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, 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<WriterContext> &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 profiles could 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<InstrProfError>(E)));
});
}
const uint64_t ColdPercentileIdx = 15;
const uint64_t HotPercentileIdx = 11;
/// Adjust the instr profile in \p WC based on the sample profile in
/// \p Reader.
static void
adjustInstrProfile(std::unique_ptr<WriterContext> &WC,
std::unique_ptr<sampleprof::SampleProfileReader> &Reader,
unsigned SupplMinSizeThreshold, float ZeroCounterThreshold,
unsigned InstrProfColdThreshold) {
// Function to its entry in instr profile.
StringMap<InstrProfileEntry> 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()) {
StringRef FName = PD.getKey();
const sampleprof::FunctionSamples &FS = PD.getValue();
auto It = InstrProfileMap.find(FName);
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);
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<instrprof_error, 4> WriterErrorCodes;
auto WC = std::make_unique<WriterContext>(OutputSparse, ErrorLock,
WriterErrorCodes);
loadInput(Inputs[0], nullptr, 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()) {
Result.addBodySamples(BodySample.first.LineOffset,
BodySample.first.Discriminator,
BodySample.second.getSamples());
for (const auto &Target : BodySample.second.getCallTargets()) {
Result.addCalledTargetSamples(BodySample.first.LineOffset,
BodySample.first.Discriminator,
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<MemoryBuffer>
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<StringRef, 32> SymbolVec;
StringRef Data = Buffer->getBuffer();
Data.split(SymbolVec, '\n', /*MaxSplit=*/-1, /*KeepEmpty=*/false);
for (StringRef symbol : SymbolVec)
PSL.add(symbol);
}
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, FailureMode FailMode) {
using namespace sampleprof;
StringMap<FunctionSamples> ProfileMap;
SmallVector<std::unique_ptr<sampleprof::SampleProfileReader>, 5> Readers;
LLVMContext Context;
sampleprof::ProfileSymbolList WriterList;
Optional<bool> ProfileIsProbeBased;
for (const auto &Input : Inputs) {
auto ReaderOrErr = SampleProfileReader::create(Input.Filename, Context);
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;
}
StringMap<FunctionSamples> &Profiles = Reader->getProfiles();
if (ProfileIsProbeBased &&
ProfileIsProbeBased != FunctionSamples::ProfileIsProbeBased)
exitWithError(
"cannot merge probe-based profile with non-probe-based profile");
ProfileIsProbeBased = FunctionSamples::ProfileIsProbeBased;
for (StringMap<FunctionSamples>::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;
StringRef FName = Samples.getNameWithContext(true);
MergeResult(Result, ProfileMap[FName].merge(Samples, Input.Weight));
if (Result != sampleprof_error::success) {
std::error_code EC = make_error_code(Result);
handleMergeWriterError(errorCodeToError(EC), Input.Filename, FName);
}
}
std::unique_ptr<sampleprof::ProfileSymbolList> ReaderList =
Reader->getProfileSymbolList();
if (ReaderList)
WriterList.merge(*ReaderList);
}
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);
Writer->write(ProfileMap);
}
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<StringRef, 8> 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.find(',') == StringRef::npos)
addWeightedInput(WFV, {std::string(SanitizedEntry), 1});
else
addWeightedInput(WFV, parseWeightedFile(SanitizedEntry));
}
}
static int merge_main(int argc, const char *argv[]) {
cl::list<std::string> InputFilenames(cl::Positional,
cl::desc("<filename...>"));
cl::list<std::string> WeightedInputFilenames("weighted-input",
cl::desc("<weight>,<filename>"));
cl::opt<std::string> InputFilenamesFile(
"input-files", cl::init(""),
cl::desc("Path to file containing newline-separated "
"[<weight>,]<filename> entries"));
cl::alias InputFilenamesFileA("f", cl::desc("Alias for --input-files"),
cl::aliasopt(InputFilenamesFile));
cl::opt<bool> 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<std::string> 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<std::string> OutputFilename("output", cl::value_desc("output"),
cl::init("-"), cl::Required,
cl::desc("Output file"));
cl::alias OutputFilenameA("o", cl::desc("Alias for --output"),
cl::aliasopt(OutputFilename));
cl::opt<ProfileKinds> ProfileKind(
cl::desc("Profile kind:"), cl::init(instr),
cl::values(clEnumVal(instr, "Instrumentation profile (default)"),
clEnumVal(sample, "Sample profile")));
cl::opt<ProfileFormat> 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> 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<bool> OutputSparse("sparse", cl::init(false),
cl::desc("Generate a sparse profile (only meaningful for -instr)"));
cl::opt<unsigned> 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<std::string> 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<bool> CompressAllSections(
"compress-all-sections", cl::init(false), cl::Hidden,
cl::desc("Compress all sections when writing the profile (only "
"meaningful for -extbinary)"));
cl::opt<bool> 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<bool> GenPartialProfile(
"gen-partial-profile", cl::init(false), cl::Hidden,
cl::desc("Generate a partial profile (only meaningful for -extbinary)"));
cl::opt<std::string> 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<float> 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 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<unsigned> 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<unsigned> 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::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<SymbolRemapper> 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, Remapper.get(), OutputFilename,
OutputFormat, OutputSparse, NumThreads, FailureMode);
else
mergeSampleProfile(WeightedInputs, Remapper.get(), OutputFilename,
OutputFormat, ProfileSymbolListFile, CompressAllSections,
UseMD5, GenPartialProfile, 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<instrprof_error, 4> 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, &Context);
overlapInput(BaseFilename, TestFilename, &Context, Overlap, FuncFilter, OS,
IsCS);
Overlap.dump(OS);
}
namespace {
struct SampleOverlapStats {
StringRef BaseName;
StringRef 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 T> 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 <class T> void MatchStep<T>::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();
private:
SampleOverlapStats ProfOverlap;
SampleOverlapStats HotFuncOverlap;
SampleOverlapStats HotBlockOverlap;
std::string BaseFilename;
std::string TestFilename;
std::unique_ptr<sampleprof::SampleProfileReader> BaseReader;
std::unique_ptr<sampleprof::SampleProfileReader> TestReader;
// BaseStats and TestStats hold FuncSampleStats for each function, with
// function name as the key.
StringMap<FuncSampleStats> BaseStats;
StringMap<FuncSampleStats> 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<double, SampleOverlapStats, std::greater<double>>
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 StringMap<FuncSampleStats> &ProfStats,
StringMap<FuncSampleStats> &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<double>(BaseSample) / FuncOverlap.BaseSample;
if (FuncOverlap.TestSample > 0)
TestFrac = static_cast<double>(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 StringMap<FuncSampleStats> &ProfStats,
StringMap<FuncSampleStats> &HotFunc, uint64_t HotThreshold) const {
for (const auto &F : ProfStats) {
if (isFunctionHot(F.second, HotThreshold))
HotFunc.try_emplace(F.first(), F.second);
}
}
void SampleOverlapAggregator::computeHotFuncOverlap() {
StringMap<FuncSampleStats> BaseHotFunc;
getHotFunctions(BaseStats, BaseHotFunc, BaseHotThreshold);
HotFuncOverlap.BaseCount = BaseHotFunc.size();
StringMap<FuncSampleStats> 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<BodySampleMap::const_iterator> 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<CallsiteSampleMap::const_iterator> 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<FunctionSamplesMap::const_iterator> 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<double>(BaseFuncSample) / ProfOverlap.BaseSample;
assert(ProfOverlap.TestSample > 0 &&
"Total samples in test profile should be greater than 0");
TestFrac = static_cast<double>(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<double>(BaseFuncSample) / ProfOverlap.BaseSample / 2.0;
assert(ProfOverlap.TestSample > 0 &&
"Total samples in test profile should be greater than 0");
TestFrac = static_cast<double>(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;
StringMap<const FunctionSamples *> BaseFuncProf;
const auto &BaseProfiles = BaseReader->getProfiles();
for (const auto &BaseFunc : BaseProfiles) {
BaseFuncProf.try_emplace(BaseFunc.second.getName(), &(BaseFunc.second));
}
ProfOverlap.UnionCount = BaseFuncProf.size();
const auto &TestProfiles = TestReader->getProfiles();
for (const auto &TestFunc : TestProfiles) {
SampleOverlapStats FuncOverlap;
FuncOverlap.TestName = TestFunc.second.getName();
assert(TestStats.count(FuncOverlap.TestName) &&
"TestStats should have records for all functions in test profile "
"except inlinees");
FuncOverlap.TestSample = TestStats[FuncOverlap.TestName].SampleSum;
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->getName();
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);
}
// 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 ||
(Match != BaseFuncProf.end() &&
FuncOverlap.Similarity < LowSimilarityThreshold) ||
(Match != BaseFuncProf.end() && !FuncFilter.NameFilter.empty() &&
FuncOverlap.BaseName.find(FuncFilter.NameFilter) !=
FuncOverlap.BaseName.npos)) {
assert(ProfOverlap.BaseSample > 0 &&
"Total samples in base profile should be greater than 0");
FuncOverlap.BaseWeight =
static_cast<double>(FuncOverlap.BaseSample) / ProfOverlap.BaseSample;
assert(ProfOverlap.TestSample > 0 &&
"Total samples in test profile should be greater than 0");
FuncOverlap.TestWeight =
static_cast<double>(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->getName()) &&
"BaseStats should have records for all functions in base profile "
"except inlinees");
const FuncSampleStats &FuncStats = BaseStats[F.second->getName()];
++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.try_emplace(I.second.getName(), 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.try_emplace(I.second.getName(), 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<double>(F.second.OverlapSample) / F.second.UnionSample
: 0;
double BaseUniquePercent =
F.second.BaseSample > 0
? static_cast<double>(F.second.BaseUniqueSample) /
F.second.BaseSample
: 0;
double TestUniquePercent =
F.second.TestSample > 0
? static_cast<double>(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 << "\n";
}
}
void SampleOverlapAggregator::dumpProgramSummary(raw_fd_ostream &OS) const {
OS << "Profile overlap infomation for base_profile: " << ProfOverlap.BaseName
<< " and test_profile: " << ProfOverlap.TestName << "\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<double>(ProfOverlap.OverlapSample) / ProfOverlap.UnionSample;
assert(ProfOverlap.BaseSample > 0 &&
"Total samples in base profile should be greater than 0");
double BaseUniquePercent = static_cast<double>(ProfOverlap.BaseUniqueSample) /
ProfOverlap.BaseSample;
assert(ProfOverlap.TestSample > 0 &&
"Total samples in test profile should be greater than 0");
double TestUniquePercent = static_cast<double>(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<double>(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<double>(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<double>(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);
if (std::error_code EC = BaseReaderOrErr.getError())
exitWithErrorCode(EC, BaseFilename);
auto TestReaderOrErr = SampleProfileReader::create(TestFilename, Context);
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");
// Load BaseHotThreshold and TestHotThreshold as 99-percentile threshold in
// profile summary.
const uint64_t HotCutoff = 990000;
ProfileSummary &BasePS = BaseReader->getSummary();
for (const auto &SummaryEntry : BasePS.getDetailedSummary()) {
if (SummaryEntry.Cutoff == HotCutoff) {
BaseHotThreshold = SummaryEntry.MinCount;
break;
}
}
ProfileSummary &TestPS = TestReader->getSummary();
for (const auto &SummaryEntry : TestPS.getDetailedSummary()) {
if (SummaryEntry.Cutoff == HotCutoff) {
TestHotThreshold = SummaryEntry.MinCount;
break;
}
}
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<double>(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<std::string> BaseFilename(cl::Positional, cl::Required,
cl::desc("<base profile file>"));
cl::opt<std::string> TestFilename(cl::Positional, cl::Required,
cl::desc("<test profile file>"));
cl::opt<std::string> 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<bool> IsCS("cs", cl::init(false),
cl::desc("For context sensitive counts"));
cl::opt<unsigned long long> ValueCutoff(
"value-cutoff", cl::init(-1),
cl::desc(
"Function level overlap information for every function in test "
"profile with max count value greater then the parameter value"));
cl::opt<std::string> FuncNameFilter(
"function",
cl::desc("Function level overlap information for matching functions"));
cl::opt<unsigned long long> SimilarityCutoff(
"similarity-cutoff", cl::init(0),
cl::desc(
"For sample profiles, list function names for overlapped functions "
"with similarities below the cutoff (percentage times 10000)."));
cl::opt<ProfileKinds> 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_Text);
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;
}
typedef struct ValueSitesStats {
ValueSitesStats()
: TotalNumValueSites(0), TotalNumValueSitesWithValueProfile(0),
TotalNumValues(0) {}
uint64_t TotalNumValueSites;
uint64_t TotalNumValueSitesWithValueProfile;
uint64_t TotalNumValues;
std::vector<unsigned> ValueSitesHistogram;
} ValueSitesStats;
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<InstrProfValueData[]> 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<uint32_t> DetailedSummaryCutoffs,
bool ShowAllFunctions, bool ShowCS,
uint64_t ValueCutoff, bool OnlyListBelow,
const std::string &ShowFunction, bool TextFormat,
raw_fd_ostream &OS) {
auto ReaderOrErr = InstrProfReader::create(Filename);
std::vector<uint32_t> Cutoffs = std::move(DetailedSummaryCutoffs);
if (ShowDetailedSummary && Cutoffs.empty()) {
Cutoffs = {800000, 900000, 950000, 990000, 999000, 999900, 999990};
}
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<ValueSitesStats> VPStats(NumVPKind);
auto MinCmp = [](const std::pair<std::string, uint64_t> &v1,
const std::pair<std::string, uint64_t> &v2) {
return v1.second > v2.second;
};
std::priority_queue<std::pair<std::string, uint64_t>,
std::vector<std::pair<std::string, uint64_t>>,
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.find(ShowFunction) != Func.Name.npos);
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);
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)
return 0;
std::unique_ptr<ProfileSummary> 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<std::pair<std::string, uint64_t>> 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);
}
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 {
StringRef FuncName;
uint64_t TotalCount;
double TotalCountPercent;
uint64_t MaxCount;
uint64_t EntryCount;
HotFuncInfo()
: FuncName(), 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), 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<std::string> &ColumnTitle,
const std::vector<int> &ColumnOffset,
const std::vector<HotFuncInfo> &PrintValues,
uint64_t HotFuncCount, uint64_t TotalFuncCount,
uint64_t HotProfCount, uint64_t TotalProfCount,
const std::string &HotFuncMetric,
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<double>(HotProfCount) / TotalProfCount * 100;
formatted_raw_ostream FOS(OS);
FOS << HotFuncCount << " out of " << TotalFuncCount
<< " functions with profile ("
<< format("%.2f%%",
(static_cast<double>(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";
for (const HotFuncInfo &R : PrintValues) {
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 StringMap<sampleprof::FunctionSamples> &Profiles,
ProfileSummary &PS, 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<uint64_t, std::pair<const FunctionSamples *, const uint64_t>,
std::greater<uint64_t>>
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<std::string> ColumnTitle{"Total sample (%)", "Max sample",
"Entry sample", "Function name"};
std::vector<int> ColumnOffset{0, 24, 42, 58};
std::string Metric =
std::string("max sample >= ") + std::to_string(MinCountThreshold);
std::vector<HotFuncInfo> 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.getName(), Func.getTotalSamples(), TotalSamplePercent,
FuncPair.second.second, Func.getEntrySamples()));
}
dumpHotFunctionList(ColumnTitle, ColumnOffset, PrintValues, HotFuncCount,
Profiles.size(), HotFuncSample, ProfileTotalSample,
Metric, OS);
return 0;
}
static int showSampleProfile(const std::string &Filename, bool ShowCounts,
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);
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
Reader->dumpFunctionProfile(ShowFunction, OS);
if (ShowProfileSymbolList) {
std::unique_ptr<sampleprof::ProfileSymbolList> ReaderList =