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llvm-mirror/lib/Transforms/IPO/SampleProfile.cpp
Wei Mi d9e172d0fb [SampleFDO] Enhance profile remapping support for searching inline instance 
and indirect call promotion candidate.

Profile remapping is a feature to match a function in the module with its
profile in sample profile if the function name and the name in profile look
different but are equivalent using given remapping rules. This is a useful
feature to keep the performance stable by specifying some remapping rules
when sampleFDO targets are going through some large scale function signature
change.

However, currently profile remapping support is only valid for outline
function profile in SampleFDO. It cannot match a callee with an inline
instance profile if they have different but equivalent names. We found
that without the support for inline instance profile, remapping is less
effective for some large scale change.

To add that support, before any remapping lookup happens, all the names
in the profile will be inserted into remapper and the Key to the name
mapping will be recorded in a map called NameMap in the remapper. During
name lookup, a Key will be returned for the given name and it will be used
to extract an equivalent name in the profile from NameMap. So with the help
of the NameMap, we can translate any given name to an equivalent name in
the profile if it exists. Whenever we try to match a name in the module to
a name in the profile, we will try the match with the original name first,
and if it doesn't match, we will use the equivalent name got from remapper
to try the match for another time. In this way, the patch can enhance the
profile remapping support for searching inline instance and searching
indirect call promotion candidate.

In a planned large scale change of int64 type (long long) to int64_t (long),
we found the performance of a google internal benchmark degraded by 2% if
nothing was done. If existing profile remapping was enabled, the performance
degradation dropped to 1.2%. If the profile remapping with the current patch
was enabled, the performance degradation further dropped to 0.14% (Note the
experiment was done before searching indirect call promotion candidate was
added. We hope with the remapping support of searching indirect call promotion
candidate, the degradation can drop to 0% in the end. It will be evaluated
post commit).

Differential Revision: https://reviews.llvm.org/D86332
2020-08-26 11:07:35 -07:00

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//===- SampleProfile.cpp - Incorporate sample profiles into the IR --------===//
//
// 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
//
//===----------------------------------------------------------------------===//
//
// This file implements the SampleProfileLoader transformation. This pass
// reads a profile file generated by a sampling profiler (e.g. Linux Perf -
// http://perf.wiki.kernel.org/) and generates IR metadata to reflect the
// profile information in the given profile.
//
// This pass generates branch weight annotations on the IR:
//
// - prof: Represents branch weights. This annotation is added to branches
// to indicate the weights of each edge coming out of the branch.
// The weight of each edge is the weight of the target block for
// that edge. The weight of a block B is computed as the maximum
// number of samples found in B.
//
//===----------------------------------------------------------------------===//
#include "llvm/Transforms/IPO/SampleProfile.h"
#include "llvm/ADT/ArrayRef.h"
#include "llvm/ADT/DenseMap.h"
#include "llvm/ADT/DenseSet.h"
#include "llvm/ADT/None.h"
#include "llvm/ADT/SCCIterator.h"
#include "llvm/ADT/SmallPtrSet.h"
#include "llvm/ADT/SmallSet.h"
#include "llvm/ADT/SmallVector.h"
#include "llvm/ADT/Statistic.h"
#include "llvm/ADT/StringMap.h"
#include "llvm/ADT/StringRef.h"
#include "llvm/ADT/Twine.h"
#include "llvm/Analysis/AssumptionCache.h"
#include "llvm/Analysis/CallGraph.h"
#include "llvm/Analysis/CallGraphSCCPass.h"
#include "llvm/Analysis/InlineAdvisor.h"
#include "llvm/Analysis/InlineCost.h"
#include "llvm/Analysis/LoopInfo.h"
#include "llvm/Analysis/OptimizationRemarkEmitter.h"
#include "llvm/Analysis/PostDominators.h"
#include "llvm/Analysis/ProfileSummaryInfo.h"
#include "llvm/Analysis/ReplayInlineAdvisor.h"
#include "llvm/Analysis/TargetLibraryInfo.h"
#include "llvm/Analysis/TargetTransformInfo.h"
#include "llvm/IR/BasicBlock.h"
#include "llvm/IR/CFG.h"
#include "llvm/IR/DebugInfoMetadata.h"
#include "llvm/IR/DebugLoc.h"
#include "llvm/IR/DiagnosticInfo.h"
#include "llvm/IR/Dominators.h"
#include "llvm/IR/Function.h"
#include "llvm/IR/GlobalValue.h"
#include "llvm/IR/InstrTypes.h"
#include "llvm/IR/Instruction.h"
#include "llvm/IR/Instructions.h"
#include "llvm/IR/IntrinsicInst.h"
#include "llvm/IR/LLVMContext.h"
#include "llvm/IR/MDBuilder.h"
#include "llvm/IR/Module.h"
#include "llvm/IR/PassManager.h"
#include "llvm/IR/ValueSymbolTable.h"
#include "llvm/InitializePasses.h"
#include "llvm/Pass.h"
#include "llvm/ProfileData/InstrProf.h"
#include "llvm/ProfileData/SampleProf.h"
#include "llvm/ProfileData/SampleProfReader.h"
#include "llvm/Support/Casting.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/ErrorHandling.h"
#include "llvm/Support/ErrorOr.h"
#include "llvm/Support/GenericDomTree.h"
#include "llvm/Support/raw_ostream.h"
#include "llvm/Transforms/IPO.h"
#include "llvm/Transforms/Instrumentation.h"
#include "llvm/Transforms/Utils/CallPromotionUtils.h"
#include "llvm/Transforms/Utils/Cloning.h"
#include "llvm/Transforms/Utils/MisExpect.h"
#include <algorithm>
#include <cassert>
#include <cstdint>
#include <functional>
#include <limits>
#include <map>
#include <memory>
#include <queue>
#include <string>
#include <system_error>
#include <utility>
#include <vector>
using namespace llvm;
using namespace sampleprof;
using ProfileCount = Function::ProfileCount;
#define DEBUG_TYPE "sample-profile"
#define CSINLINE_DEBUG DEBUG_TYPE "-inline"
STATISTIC(NumCSInlined,
"Number of functions inlined with context sensitive profile");
STATISTIC(NumCSNotInlined,
"Number of functions not inlined with context sensitive profile");
// Command line option to specify the file to read samples from. This is
// mainly used for debugging.
static cl::opt<std::string> SampleProfileFile(
"sample-profile-file", cl::init(""), cl::value_desc("filename"),
cl::desc("Profile file loaded by -sample-profile"), cl::Hidden);
// The named file contains a set of transformations that may have been applied
// to the symbol names between the program from which the sample data was
// collected and the current program's symbols.
static cl::opt<std::string> SampleProfileRemappingFile(
"sample-profile-remapping-file", cl::init(""), cl::value_desc("filename"),
cl::desc("Profile remapping file loaded by -sample-profile"), cl::Hidden);
static cl::opt<unsigned> SampleProfileMaxPropagateIterations(
"sample-profile-max-propagate-iterations", cl::init(100),
cl::desc("Maximum number of iterations to go through when propagating "
"sample block/edge weights through the CFG."));
static cl::opt<unsigned> SampleProfileRecordCoverage(
"sample-profile-check-record-coverage", cl::init(0), cl::value_desc("N"),
cl::desc("Emit a warning if less than N% of records in the input profile "
"are matched to the IR."));
static cl::opt<unsigned> SampleProfileSampleCoverage(
"sample-profile-check-sample-coverage", cl::init(0), cl::value_desc("N"),
cl::desc("Emit a warning if less than N% of samples in the input profile "
"are matched to the IR."));
static cl::opt<bool> NoWarnSampleUnused(
"no-warn-sample-unused", cl::init(false), cl::Hidden,
cl::desc("Use this option to turn off/on warnings about function with "
"samples but without debug information to use those samples. "));
static cl::opt<bool> ProfileSampleAccurate(
"profile-sample-accurate", cl::Hidden, cl::init(false),
cl::desc("If the sample profile is accurate, we will mark all un-sampled "
"callsite and function as having 0 samples. Otherwise, treat "
"un-sampled callsites and functions conservatively as unknown. "));
static cl::opt<bool> ProfileAccurateForSymsInList(
"profile-accurate-for-symsinlist", cl::Hidden, cl::ZeroOrMore,
cl::init(true),
cl::desc("For symbols in profile symbol list, regard their profiles to "
"be accurate. It may be overriden by profile-sample-accurate. "));
static cl::opt<bool> ProfileMergeInlinee(
"sample-profile-merge-inlinee", cl::Hidden, cl::init(true),
cl::desc("Merge past inlinee's profile to outline version if sample "
"profile loader decided not to inline a call site. It will "
"only be enabled when top-down order of profile loading is "
"enabled. "));
static cl::opt<bool> ProfileTopDownLoad(
"sample-profile-top-down-load", cl::Hidden, cl::init(true),
cl::desc("Do profile annotation and inlining for functions in top-down "
"order of call graph during sample profile loading. It only "
"works for new pass manager. "));
static cl::opt<bool> ProfileSizeInline(
"sample-profile-inline-size", cl::Hidden, cl::init(false),
cl::desc("Inline cold call sites in profile loader if it's beneficial "
"for code size."));
static cl::opt<int> SampleColdCallSiteThreshold(
"sample-profile-cold-inline-threshold", cl::Hidden, cl::init(45),
cl::desc("Threshold for inlining cold callsites"));
static cl::opt<std::string> ProfileInlineReplayFile(
"sample-profile-inline-replay", cl::init(""), cl::value_desc("filename"),
cl::desc(
"Optimization remarks file containing inline remarks to be replayed "
"by inlining from sample profile loader."),
cl::Hidden);
namespace {
using BlockWeightMap = DenseMap<const BasicBlock *, uint64_t>;
using EquivalenceClassMap = DenseMap<const BasicBlock *, const BasicBlock *>;
using Edge = std::pair<const BasicBlock *, const BasicBlock *>;
using EdgeWeightMap = DenseMap<Edge, uint64_t>;
using BlockEdgeMap =
DenseMap<const BasicBlock *, SmallVector<const BasicBlock *, 8>>;
class SampleProfileLoader;
class SampleCoverageTracker {
public:
SampleCoverageTracker(SampleProfileLoader &SPL) : SPLoader(SPL){};
bool markSamplesUsed(const FunctionSamples *FS, uint32_t LineOffset,
uint32_t Discriminator, uint64_t Samples);
unsigned computeCoverage(unsigned Used, unsigned Total) const;
unsigned countUsedRecords(const FunctionSamples *FS,
ProfileSummaryInfo *PSI) const;
unsigned countBodyRecords(const FunctionSamples *FS,
ProfileSummaryInfo *PSI) const;
uint64_t getTotalUsedSamples() const { return TotalUsedSamples; }
uint64_t countBodySamples(const FunctionSamples *FS,
ProfileSummaryInfo *PSI) const;
void clear() {
SampleCoverage.clear();
TotalUsedSamples = 0;
}
private:
using BodySampleCoverageMap = std::map<LineLocation, unsigned>;
using FunctionSamplesCoverageMap =
DenseMap<const FunctionSamples *, BodySampleCoverageMap>;
/// Coverage map for sampling records.
///
/// This map keeps a record of sampling records that have been matched to
/// an IR instruction. This is used to detect some form of staleness in
/// profiles (see flag -sample-profile-check-coverage).
///
/// Each entry in the map corresponds to a FunctionSamples instance. This is
/// another map that counts how many times the sample record at the
/// given location has been used.
FunctionSamplesCoverageMap SampleCoverage;
/// Number of samples used from the profile.
///
/// When a sampling record is used for the first time, the samples from
/// that record are added to this accumulator. Coverage is later computed
/// based on the total number of samples available in this function and
/// its callsites.
///
/// Note that this accumulator tracks samples used from a single function
/// and all the inlined callsites. Strictly, we should have a map of counters
/// keyed by FunctionSamples pointers, but these stats are cleared after
/// every function, so we just need to keep a single counter.
uint64_t TotalUsedSamples = 0;
SampleProfileLoader &SPLoader;
};
class GUIDToFuncNameMapper {
public:
GUIDToFuncNameMapper(Module &M, SampleProfileReader &Reader,
DenseMap<uint64_t, StringRef> &GUIDToFuncNameMap)
: CurrentReader(Reader), CurrentModule(M),
CurrentGUIDToFuncNameMap(GUIDToFuncNameMap) {
if (!CurrentReader.useMD5())
return;
for (const auto &F : CurrentModule) {
StringRef OrigName = F.getName();
CurrentGUIDToFuncNameMap.insert(
{Function::getGUID(OrigName), OrigName});
// Local to global var promotion used by optimization like thinlto
// will rename the var and add suffix like ".llvm.xxx" to the
// original local name. In sample profile, the suffixes of function
// names are all stripped. Since it is possible that the mapper is
// built in post-thin-link phase and var promotion has been done,
// we need to add the substring of function name without the suffix
// into the GUIDToFuncNameMap.
StringRef CanonName = FunctionSamples::getCanonicalFnName(F);
if (CanonName != OrigName)
CurrentGUIDToFuncNameMap.insert(
{Function::getGUID(CanonName), CanonName});
}
// Update GUIDToFuncNameMap for each function including inlinees.
SetGUIDToFuncNameMapForAll(&CurrentGUIDToFuncNameMap);
}
~GUIDToFuncNameMapper() {
if (!CurrentReader.useMD5())
return;
CurrentGUIDToFuncNameMap.clear();
// Reset GUIDToFuncNameMap for of each function as they're no
// longer valid at this point.
SetGUIDToFuncNameMapForAll(nullptr);
}
private:
void SetGUIDToFuncNameMapForAll(DenseMap<uint64_t, StringRef> *Map) {
std::queue<FunctionSamples *> FSToUpdate;
for (auto &IFS : CurrentReader.getProfiles()) {
FSToUpdate.push(&IFS.second);
}
while (!FSToUpdate.empty()) {
FunctionSamples *FS = FSToUpdate.front();
FSToUpdate.pop();
FS->GUIDToFuncNameMap = Map;
for (const auto &ICS : FS->getCallsiteSamples()) {
const FunctionSamplesMap &FSMap = ICS.second;
for (auto &IFS : FSMap) {
FunctionSamples &FS = const_cast<FunctionSamples &>(IFS.second);
FSToUpdate.push(&FS);
}
}
}
}
SampleProfileReader &CurrentReader;
Module &CurrentModule;
DenseMap<uint64_t, StringRef> &CurrentGUIDToFuncNameMap;
};
/// Sample profile pass.
///
/// This pass reads profile data from the file specified by
/// -sample-profile-file and annotates every affected function with the
/// profile information found in that file.
class SampleProfileLoader {
public:
SampleProfileLoader(
StringRef Name, StringRef RemapName, bool IsThinLTOPreLink,
std::function<AssumptionCache &(Function &)> GetAssumptionCache,
std::function<TargetTransformInfo &(Function &)> GetTargetTransformInfo,
std::function<const TargetLibraryInfo &(Function &)> GetTLI)
: GetAC(std::move(GetAssumptionCache)),
GetTTI(std::move(GetTargetTransformInfo)), GetTLI(std::move(GetTLI)),
CoverageTracker(*this), Filename(std::string(Name)),
RemappingFilename(std::string(RemapName)),
IsThinLTOPreLink(IsThinLTOPreLink) {}
bool doInitialization(Module &M, FunctionAnalysisManager *FAM = nullptr);
bool runOnModule(Module &M, ModuleAnalysisManager *AM,
ProfileSummaryInfo *_PSI, CallGraph *CG);
void dump() { Reader->dump(); }
protected:
friend class SampleCoverageTracker;
bool runOnFunction(Function &F, ModuleAnalysisManager *AM);
unsigned getFunctionLoc(Function &F);
bool emitAnnotations(Function &F);
ErrorOr<uint64_t> getInstWeight(const Instruction &I);
ErrorOr<uint64_t> getBlockWeight(const BasicBlock *BB);
const FunctionSamples *findCalleeFunctionSamples(const CallBase &I) const;
std::vector<const FunctionSamples *>
findIndirectCallFunctionSamples(const Instruction &I, uint64_t &Sum) const;
mutable DenseMap<const DILocation *, const FunctionSamples *> DILocation2SampleMap;
const FunctionSamples *findFunctionSamples(const Instruction &I) const;
bool inlineCallInstruction(CallBase &CB);
bool inlineHotFunctions(Function &F,
DenseSet<GlobalValue::GUID> &InlinedGUIDs);
// Inline cold/small functions in addition to hot ones
bool shouldInlineColdCallee(CallBase &CallInst);
void emitOptimizationRemarksForInlineCandidates(
const SmallVectorImpl<CallBase *> &Candidates, const Function &F,
bool Hot);
void printEdgeWeight(raw_ostream &OS, Edge E);
void printBlockWeight(raw_ostream &OS, const BasicBlock *BB) const;
void printBlockEquivalence(raw_ostream &OS, const BasicBlock *BB);
bool computeBlockWeights(Function &F);
void findEquivalenceClasses(Function &F);
template <bool IsPostDom>
void findEquivalencesFor(BasicBlock *BB1, ArrayRef<BasicBlock *> Descendants,
DominatorTreeBase<BasicBlock, IsPostDom> *DomTree);
void propagateWeights(Function &F);
uint64_t visitEdge(Edge E, unsigned *NumUnknownEdges, Edge *UnknownEdge);
void buildEdges(Function &F);
std::vector<Function *> buildFunctionOrder(Module &M, CallGraph *CG);
bool propagateThroughEdges(Function &F, bool UpdateBlockCount);
void computeDominanceAndLoopInfo(Function &F);
void clearFunctionData();
bool callsiteIsHot(const FunctionSamples *CallsiteFS,
ProfileSummaryInfo *PSI);
/// Map basic blocks to their computed weights.
///
/// The weight of a basic block is defined to be the maximum
/// of all the instruction weights in that block.
BlockWeightMap BlockWeights;
/// Map edges to their computed weights.
///
/// Edge weights are computed by propagating basic block weights in
/// SampleProfile::propagateWeights.
EdgeWeightMap EdgeWeights;
/// Set of visited blocks during propagation.
SmallPtrSet<const BasicBlock *, 32> VisitedBlocks;
/// Set of visited edges during propagation.
SmallSet<Edge, 32> VisitedEdges;
/// Equivalence classes for block weights.
///
/// Two blocks BB1 and BB2 are in the same equivalence class if they
/// dominate and post-dominate each other, and they are in the same loop
/// nest. When this happens, the two blocks are guaranteed to execute
/// the same number of times.
EquivalenceClassMap EquivalenceClass;
/// Map from function name to Function *. Used to find the function from
/// the function name. If the function name contains suffix, additional
/// entry is added to map from the stripped name to the function if there
/// is one-to-one mapping.
StringMap<Function *> SymbolMap;
/// Dominance, post-dominance and loop information.
std::unique_ptr<DominatorTree> DT;
std::unique_ptr<PostDominatorTree> PDT;
std::unique_ptr<LoopInfo> LI;
std::function<AssumptionCache &(Function &)> GetAC;
std::function<TargetTransformInfo &(Function &)> GetTTI;
std::function<const TargetLibraryInfo &(Function &)> GetTLI;
/// Predecessors for each basic block in the CFG.
BlockEdgeMap Predecessors;
/// Successors for each basic block in the CFG.
BlockEdgeMap Successors;
SampleCoverageTracker CoverageTracker;
/// Profile reader object.
std::unique_ptr<SampleProfileReader> Reader;
/// Samples collected for the body of this function.
FunctionSamples *Samples = nullptr;
/// Name of the profile file to load.
std::string Filename;
/// Name of the profile remapping file to load.
std::string RemappingFilename;
/// Flag indicating whether the profile input loaded successfully.
bool ProfileIsValid = false;
/// Flag indicating if the pass is invoked in ThinLTO compile phase.
///
/// In this phase, in annotation, we should not promote indirect calls.
/// Instead, we will mark GUIDs that needs to be annotated to the function.
bool IsThinLTOPreLink;
/// Profile Summary Info computed from sample profile.
ProfileSummaryInfo *PSI = nullptr;
/// Profle Symbol list tells whether a function name appears in the binary
/// used to generate the current profile.
std::unique_ptr<ProfileSymbolList> PSL;
/// Total number of samples collected in this profile.
///
/// This is the sum of all the samples collected in all the functions executed
/// at runtime.
uint64_t TotalCollectedSamples = 0;
/// Optimization Remark Emitter used to emit diagnostic remarks.
OptimizationRemarkEmitter *ORE = nullptr;
// Information recorded when we declined to inline a call site
// because we have determined it is too cold is accumulated for
// each callee function. Initially this is just the entry count.
struct NotInlinedProfileInfo {
uint64_t entryCount;
};
DenseMap<Function *, NotInlinedProfileInfo> notInlinedCallInfo;
// GUIDToFuncNameMap saves the mapping from GUID to the symbol name, for
// all the function symbols defined or declared in current module.
DenseMap<uint64_t, StringRef> GUIDToFuncNameMap;
// All the Names used in FunctionSamples including outline function
// names, inline instance names and call target names.
StringSet<> NamesInProfile;
// For symbol in profile symbol list, whether to regard their profiles
// to be accurate. It is mainly decided by existance of profile symbol
// list and -profile-accurate-for-symsinlist flag, but it can be
// overriden by -profile-sample-accurate or profile-sample-accurate
// attribute.
bool ProfAccForSymsInList;
// External inline advisor used to replay inline decision from remarks.
std::unique_ptr<ReplayInlineAdvisor> ExternalInlineAdvisor;
};
class SampleProfileLoaderLegacyPass : public ModulePass {
public:
// Class identification, replacement for typeinfo
static char ID;
SampleProfileLoaderLegacyPass(StringRef Name = SampleProfileFile,
bool IsThinLTOPreLink = false)
: ModulePass(ID), SampleLoader(
Name, SampleProfileRemappingFile, IsThinLTOPreLink,
[&](Function &F) -> AssumptionCache & {
return ACT->getAssumptionCache(F);
},
[&](Function &F) -> TargetTransformInfo & {
return TTIWP->getTTI(F);
},
[&](Function &F) -> TargetLibraryInfo & {
return TLIWP->getTLI(F);
}) {
initializeSampleProfileLoaderLegacyPassPass(
*PassRegistry::getPassRegistry());
}
void dump() { SampleLoader.dump(); }
bool doInitialization(Module &M) override {
return SampleLoader.doInitialization(M);
}
StringRef getPassName() const override { return "Sample profile pass"; }
bool runOnModule(Module &M) override;
void getAnalysisUsage(AnalysisUsage &AU) const override {
AU.addRequired<AssumptionCacheTracker>();
AU.addRequired<TargetTransformInfoWrapperPass>();
AU.addRequired<TargetLibraryInfoWrapperPass>();
AU.addRequired<ProfileSummaryInfoWrapperPass>();
}
private:
SampleProfileLoader SampleLoader;
AssumptionCacheTracker *ACT = nullptr;
TargetTransformInfoWrapperPass *TTIWP = nullptr;
TargetLibraryInfoWrapperPass *TLIWP = nullptr;
};
} // end anonymous namespace
/// Return true if the given callsite is hot wrt to hot cutoff threshold.
///
/// Functions that were inlined in the original binary will be represented
/// in the inline stack in the sample profile. If the profile shows that
/// the original inline decision was "good" (i.e., the callsite is executed
/// frequently), then we will recreate the inline decision and apply the
/// profile from the inlined callsite.
///
/// To decide whether an inlined callsite is hot, we compare the callsite
/// sample count with the hot cutoff computed by ProfileSummaryInfo, it is
/// regarded as hot if the count is above the cutoff value.
///
/// When ProfileAccurateForSymsInList is enabled and profile symbol list
/// is present, functions in the profile symbol list but without profile will
/// be regarded as cold and much less inlining will happen in CGSCC inlining
/// pass, so we tend to lower the hot criteria here to allow more early
/// inlining to happen for warm callsites and it is helpful for performance.
bool SampleProfileLoader::callsiteIsHot(const FunctionSamples *CallsiteFS,
ProfileSummaryInfo *PSI) {
if (!CallsiteFS)
return false; // The callsite was not inlined in the original binary.
assert(PSI && "PSI is expected to be non null");
uint64_t CallsiteTotalSamples = CallsiteFS->getTotalSamples();
if (ProfAccForSymsInList)
return !PSI->isColdCount(CallsiteTotalSamples);
else
return PSI->isHotCount(CallsiteTotalSamples);
}
/// Mark as used the sample record for the given function samples at
/// (LineOffset, Discriminator).
///
/// \returns true if this is the first time we mark the given record.
bool SampleCoverageTracker::markSamplesUsed(const FunctionSamples *FS,
uint32_t LineOffset,
uint32_t Discriminator,
uint64_t Samples) {
LineLocation Loc(LineOffset, Discriminator);
unsigned &Count = SampleCoverage[FS][Loc];
bool FirstTime = (++Count == 1);
if (FirstTime)
TotalUsedSamples += Samples;
return FirstTime;
}
/// Return the number of sample records that were applied from this profile.
///
/// This count does not include records from cold inlined callsites.
unsigned
SampleCoverageTracker::countUsedRecords(const FunctionSamples *FS,
ProfileSummaryInfo *PSI) const {
auto I = SampleCoverage.find(FS);
// The size of the coverage map for FS represents the number of records
// that were marked used at least once.
unsigned Count = (I != SampleCoverage.end()) ? I->second.size() : 0;
// If there are inlined callsites in this function, count the samples found
// in the respective bodies. However, do not bother counting callees with 0
// total samples, these are callees that were never invoked at runtime.
for (const auto &I : FS->getCallsiteSamples())
for (const auto &J : I.second) {
const FunctionSamples *CalleeSamples = &J.second;
if (SPLoader.callsiteIsHot(CalleeSamples, PSI))
Count += countUsedRecords(CalleeSamples, PSI);
}
return Count;
}
/// Return the number of sample records in the body of this profile.
///
/// This count does not include records from cold inlined callsites.
unsigned
SampleCoverageTracker::countBodyRecords(const FunctionSamples *FS,
ProfileSummaryInfo *PSI) const {
unsigned Count = FS->getBodySamples().size();
// Only count records in hot callsites.
for (const auto &I : FS->getCallsiteSamples())
for (const auto &J : I.second) {
const FunctionSamples *CalleeSamples = &J.second;
if (SPLoader.callsiteIsHot(CalleeSamples, PSI))
Count += countBodyRecords(CalleeSamples, PSI);
}
return Count;
}
/// Return the number of samples collected in the body of this profile.
///
/// This count does not include samples from cold inlined callsites.
uint64_t
SampleCoverageTracker::countBodySamples(const FunctionSamples *FS,
ProfileSummaryInfo *PSI) const {
uint64_t Total = 0;
for (const auto &I : FS->getBodySamples())
Total += I.second.getSamples();
// Only count samples in hot callsites.
for (const auto &I : FS->getCallsiteSamples())
for (const auto &J : I.second) {
const FunctionSamples *CalleeSamples = &J.second;
if (SPLoader.callsiteIsHot(CalleeSamples, PSI))
Total += countBodySamples(CalleeSamples, PSI);
}
return Total;
}
/// Return the fraction of sample records used in this profile.
///
/// The returned value is an unsigned integer in the range 0-100 indicating
/// the percentage of sample records that were used while applying this
/// profile to the associated function.
unsigned SampleCoverageTracker::computeCoverage(unsigned Used,
unsigned Total) const {
assert(Used <= Total &&
"number of used records cannot exceed the total number of records");
return Total > 0 ? Used * 100 / Total : 100;
}
/// Clear all the per-function data used to load samples and propagate weights.
void SampleProfileLoader::clearFunctionData() {
BlockWeights.clear();
EdgeWeights.clear();
VisitedBlocks.clear();
VisitedEdges.clear();
EquivalenceClass.clear();
DT = nullptr;
PDT = nullptr;
LI = nullptr;
Predecessors.clear();
Successors.clear();
CoverageTracker.clear();
}
#ifndef NDEBUG
/// Print the weight of edge \p E on stream \p OS.
///
/// \param OS Stream to emit the output to.
/// \param E Edge to print.
void SampleProfileLoader::printEdgeWeight(raw_ostream &OS, Edge E) {
OS << "weight[" << E.first->getName() << "->" << E.second->getName()
<< "]: " << EdgeWeights[E] << "\n";
}
/// Print the equivalence class of block \p BB on stream \p OS.
///
/// \param OS Stream to emit the output to.
/// \param BB Block to print.
void SampleProfileLoader::printBlockEquivalence(raw_ostream &OS,
const BasicBlock *BB) {
const BasicBlock *Equiv = EquivalenceClass[BB];
OS << "equivalence[" << BB->getName()
<< "]: " << ((Equiv) ? EquivalenceClass[BB]->getName() : "NONE") << "\n";
}
/// Print the weight of block \p BB on stream \p OS.
///
/// \param OS Stream to emit the output to.
/// \param BB Block to print.
void SampleProfileLoader::printBlockWeight(raw_ostream &OS,
const BasicBlock *BB) const {
const auto &I = BlockWeights.find(BB);
uint64_t W = (I == BlockWeights.end() ? 0 : I->second);
OS << "weight[" << BB->getName() << "]: " << W << "\n";
}
#endif
/// Get the weight for an instruction.
///
/// The "weight" of an instruction \p Inst is the number of samples
/// collected on that instruction at runtime. To retrieve it, we
/// need to compute the line number of \p Inst relative to the start of its
/// function. We use HeaderLineno to compute the offset. We then
/// look up the samples collected for \p Inst using BodySamples.
///
/// \param Inst Instruction to query.
///
/// \returns the weight of \p Inst.
ErrorOr<uint64_t> SampleProfileLoader::getInstWeight(const Instruction &Inst) {
const DebugLoc &DLoc = Inst.getDebugLoc();
if (!DLoc)
return std::error_code();
const FunctionSamples *FS = findFunctionSamples(Inst);
if (!FS)
return std::error_code();
// Ignore all intrinsics, phinodes and branch instructions.
// Branch and phinodes instruction usually contains debug info from sources outside of
// the residing basic block, thus we ignore them during annotation.
if (isa<BranchInst>(Inst) || isa<IntrinsicInst>(Inst) || isa<PHINode>(Inst))
return std::error_code();
// If a direct call/invoke instruction is inlined in profile
// (findCalleeFunctionSamples returns non-empty result), but not inlined here,
// it means that the inlined callsite has no sample, thus the call
// instruction should have 0 count.
if (auto *CB = dyn_cast<CallBase>(&Inst))
if (!CB->isIndirectCall() && findCalleeFunctionSamples(*CB))
return 0;
const DILocation *DIL = DLoc;
uint32_t LineOffset = FunctionSamples::getOffset(DIL);
uint32_t Discriminator = DIL->getBaseDiscriminator();
ErrorOr<uint64_t> R = FS->findSamplesAt(LineOffset, Discriminator);
if (R) {
bool FirstMark =
CoverageTracker.markSamplesUsed(FS, LineOffset, Discriminator, R.get());
if (FirstMark) {
ORE->emit([&]() {
OptimizationRemarkAnalysis Remark(DEBUG_TYPE, "AppliedSamples", &Inst);
Remark << "Applied " << ore::NV("NumSamples", *R);
Remark << " samples from profile (offset: ";
Remark << ore::NV("LineOffset", LineOffset);
if (Discriminator) {
Remark << ".";
Remark << ore::NV("Discriminator", Discriminator);
}
Remark << ")";
return Remark;
});
}
LLVM_DEBUG(dbgs() << " " << DLoc.getLine() << "."
<< DIL->getBaseDiscriminator() << ":" << Inst
<< " (line offset: " << LineOffset << "."
<< DIL->getBaseDiscriminator() << " - weight: " << R.get()
<< ")\n");
}
return R;
}
/// Compute the weight of a basic block.
///
/// The weight of basic block \p BB is the maximum weight of all the
/// instructions in BB.
///
/// \param BB The basic block to query.
///
/// \returns the weight for \p BB.
ErrorOr<uint64_t> SampleProfileLoader::getBlockWeight(const BasicBlock *BB) {
uint64_t Max = 0;
bool HasWeight = false;
for (auto &I : BB->getInstList()) {
const ErrorOr<uint64_t> &R = getInstWeight(I);
if (R) {
Max = std::max(Max, R.get());
HasWeight = true;
}
}
return HasWeight ? ErrorOr<uint64_t>(Max) : std::error_code();
}
/// Compute and store the weights of every basic block.
///
/// This populates the BlockWeights map by computing
/// the weights of every basic block in the CFG.
///
/// \param F The function to query.
bool SampleProfileLoader::computeBlockWeights(Function &F) {
bool Changed = false;
LLVM_DEBUG(dbgs() << "Block weights\n");
for (const auto &BB : F) {
ErrorOr<uint64_t> Weight = getBlockWeight(&BB);
if (Weight) {
BlockWeights[&BB] = Weight.get();
VisitedBlocks.insert(&BB);
Changed = true;
}
LLVM_DEBUG(printBlockWeight(dbgs(), &BB));
}
return Changed;
}
/// Get the FunctionSamples for a call instruction.
///
/// The FunctionSamples of a call/invoke instruction \p Inst is the inlined
/// instance in which that call instruction is calling to. It contains
/// all samples that resides in the inlined instance. We first find the
/// inlined instance in which the call instruction is from, then we
/// traverse its children to find the callsite with the matching
/// location.
///
/// \param Inst Call/Invoke instruction to query.
///
/// \returns The FunctionSamples pointer to the inlined instance.
const FunctionSamples *
SampleProfileLoader::findCalleeFunctionSamples(const CallBase &Inst) const {
const DILocation *DIL = Inst.getDebugLoc();
if (!DIL) {
return nullptr;
}
StringRef CalleeName;
if (Function *Callee = Inst.getCalledFunction())
CalleeName = Callee->getName();
const FunctionSamples *FS = findFunctionSamples(Inst);
if (FS == nullptr)
return nullptr;
return FS->findFunctionSamplesAt(LineLocation(FunctionSamples::getOffset(DIL),
DIL->getBaseDiscriminator()),
CalleeName, Reader->getRemapper());
}
/// Returns a vector of FunctionSamples that are the indirect call targets
/// of \p Inst. The vector is sorted by the total number of samples. Stores
/// the total call count of the indirect call in \p Sum.
std::vector<const FunctionSamples *>
SampleProfileLoader::findIndirectCallFunctionSamples(
const Instruction &Inst, uint64_t &Sum) const {
const DILocation *DIL = Inst.getDebugLoc();
std::vector<const FunctionSamples *> R;
if (!DIL) {
return R;
}
const FunctionSamples *FS = findFunctionSamples(Inst);
if (FS == nullptr)
return R;
uint32_t LineOffset = FunctionSamples::getOffset(DIL);
uint32_t Discriminator = DIL->getBaseDiscriminator();
auto T = FS->findCallTargetMapAt(LineOffset, Discriminator);
Sum = 0;
if (T)
for (const auto &T_C : T.get())
Sum += T_C.second;
if (const FunctionSamplesMap *M = FS->findFunctionSamplesMapAt(LineLocation(
FunctionSamples::getOffset(DIL), DIL->getBaseDiscriminator()))) {
if (M->empty())
return R;
for (const auto &NameFS : *M) {
Sum += NameFS.second.getEntrySamples();
R.push_back(&NameFS.second);
}
llvm::sort(R, [](const FunctionSamples *L, const FunctionSamples *R) {
if (L->getEntrySamples() != R->getEntrySamples())
return L->getEntrySamples() > R->getEntrySamples();
return FunctionSamples::getGUID(L->getName()) <
FunctionSamples::getGUID(R->getName());
});
}
return R;
}
/// Get the FunctionSamples for an instruction.
///
/// The FunctionSamples of an instruction \p Inst is the inlined instance
/// in which that instruction is coming from. We traverse the inline stack
/// of that instruction, and match it with the tree nodes in the profile.
///
/// \param Inst Instruction to query.
///
/// \returns the FunctionSamples pointer to the inlined instance.
const FunctionSamples *
SampleProfileLoader::findFunctionSamples(const Instruction &Inst) const {
const DILocation *DIL = Inst.getDebugLoc();
if (!DIL)
return Samples;
auto it = DILocation2SampleMap.try_emplace(DIL,nullptr);
if (it.second)
it.first->second = Samples->findFunctionSamples(DIL, Reader->getRemapper());
return it.first->second;
}
bool SampleProfileLoader::inlineCallInstruction(CallBase &CB) {
if (ExternalInlineAdvisor) {
auto Advice = ExternalInlineAdvisor->getAdvice(CB);
if (!Advice->isInliningRecommended()) {
Advice->recordUnattemptedInlining();
return false;
}
// Dummy record, we don't use it for replay.
Advice->recordInlining();
}
Function *CalledFunction = CB.getCalledFunction();
assert(CalledFunction);
DebugLoc DLoc = CB.getDebugLoc();
BasicBlock *BB = CB.getParent();
InlineParams Params = getInlineParams();
Params.ComputeFullInlineCost = true;
// Checks if there is anything in the reachable portion of the callee at
// this callsite that makes this inlining potentially illegal. Need to
// set ComputeFullInlineCost, otherwise getInlineCost may return early
// when cost exceeds threshold without checking all IRs in the callee.
// The acutal cost does not matter because we only checks isNever() to
// see if it is legal to inline the callsite.
InlineCost Cost =
getInlineCost(CB, Params, GetTTI(*CalledFunction), GetAC, GetTLI);
if (Cost.isNever()) {
ORE->emit(OptimizationRemarkAnalysis(CSINLINE_DEBUG, "InlineFail", DLoc, BB)
<< "incompatible inlining");
return false;
}
InlineFunctionInfo IFI(nullptr, GetAC);
if (InlineFunction(CB, IFI).isSuccess()) {
// The call to InlineFunction erases I, so we can't pass it here.
emitInlinedInto(*ORE, DLoc, BB, *CalledFunction, *BB->getParent(), Cost,
true, CSINLINE_DEBUG);
return true;
}
return false;
}
bool SampleProfileLoader::shouldInlineColdCallee(CallBase &CallInst) {
if (!ProfileSizeInline)
return false;
Function *Callee = CallInst.getCalledFunction();
if (Callee == nullptr)
return false;
InlineCost Cost = getInlineCost(CallInst, getInlineParams(), GetTTI(*Callee),
GetAC, GetTLI);
return Cost.getCost() <= SampleColdCallSiteThreshold;
}
void SampleProfileLoader::emitOptimizationRemarksForInlineCandidates(
const SmallVectorImpl<CallBase *> &Candidates, const Function &F,
bool Hot) {
for (auto I : Candidates) {
Function *CalledFunction = I->getCalledFunction();
if (CalledFunction) {
ORE->emit(OptimizationRemarkAnalysis(CSINLINE_DEBUG, "InlineAttempt",
I->getDebugLoc(), I->getParent())
<< "previous inlining reattempted for "
<< (Hot ? "hotness: '" : "size: '")
<< ore::NV("Callee", CalledFunction) << "' into '"
<< ore::NV("Caller", &F) << "'");
}
}
}
/// Iteratively inline hot callsites of a function.
///
/// Iteratively traverse all callsites of the function \p F, and find if
/// the corresponding inlined instance exists and is hot in profile. If
/// it is hot enough, inline the callsites and adds new callsites of the
/// callee into the caller. If the call is an indirect call, first promote
/// it to direct call. Each indirect call is limited with a single target.
///
/// \param F function to perform iterative inlining.
/// \param InlinedGUIDs a set to be updated to include all GUIDs that are
/// inlined in the profiled binary.
///
/// \returns True if there is any inline happened.
bool SampleProfileLoader::inlineHotFunctions(
Function &F, DenseSet<GlobalValue::GUID> &InlinedGUIDs) {
DenseSet<Instruction *> PromotedInsns;
// ProfAccForSymsInList is used in callsiteIsHot. The assertion makes sure
// Profile symbol list is ignored when profile-sample-accurate is on.
assert((!ProfAccForSymsInList ||
(!ProfileSampleAccurate &&
!F.hasFnAttribute("profile-sample-accurate"))) &&
"ProfAccForSymsInList should be false when profile-sample-accurate "
"is enabled");
DenseMap<CallBase *, const FunctionSamples *> localNotInlinedCallSites;
bool Changed = false;
while (true) {
bool LocalChanged = false;
SmallVector<CallBase *, 10> CIS;
for (auto &BB : F) {
bool Hot = false;
SmallVector<CallBase *, 10> AllCandidates;
SmallVector<CallBase *, 10> ColdCandidates;
for (auto &I : BB.getInstList()) {
const FunctionSamples *FS = nullptr;
if (auto *CB = dyn_cast<CallBase>(&I)) {
if (!isa<IntrinsicInst>(I) && (FS = findCalleeFunctionSamples(*CB))) {
assert((!FunctionSamples::UseMD5 || FS->GUIDToFuncNameMap) &&
"GUIDToFuncNameMap has to be populated");
AllCandidates.push_back(CB);
if (FS->getEntrySamples() > 0)
localNotInlinedCallSites.try_emplace(CB, FS);
if (callsiteIsHot(FS, PSI))
Hot = true;
else if (shouldInlineColdCallee(*CB))
ColdCandidates.push_back(CB);
}
}
}
if (Hot || ExternalInlineAdvisor) {
CIS.insert(CIS.begin(), AllCandidates.begin(), AllCandidates.end());
emitOptimizationRemarksForInlineCandidates(AllCandidates, F, true);
} else {
CIS.insert(CIS.begin(), ColdCandidates.begin(), ColdCandidates.end());
emitOptimizationRemarksForInlineCandidates(ColdCandidates, F, false);
}
}
for (CallBase *I : CIS) {
Function *CalledFunction = I->getCalledFunction();
// Do not inline recursive calls.
if (CalledFunction == &F)
continue;
if (I->isIndirectCall()) {
if (PromotedInsns.count(I))
continue;
uint64_t Sum;
for (const auto *FS : findIndirectCallFunctionSamples(*I, Sum)) {
if (IsThinLTOPreLink) {
FS->findInlinedFunctions(InlinedGUIDs, F.getParent(),
PSI->getOrCompHotCountThreshold());
continue;
}
if (!callsiteIsHot(FS, PSI))
continue;
const char *Reason = "Callee function not available";
// R->getValue() != &F is to prevent promoting a recursive call.
// If it is a recursive call, we do not inline it as it could bloat
// the code exponentially. There is way to better handle this, e.g.
// clone the caller first, and inline the cloned caller if it is
// recursive. As llvm does not inline recursive calls, we will
// simply ignore it instead of handling it explicitly.
auto CalleeFunctionName = FS->getFuncName();
auto R = SymbolMap.find(CalleeFunctionName);
if (R != SymbolMap.end() && R->getValue() &&
!R->getValue()->isDeclaration() &&
R->getValue()->getSubprogram() &&
R->getValue()->hasFnAttribute("use-sample-profile") &&
R->getValue() != &F &&
isLegalToPromote(*I, R->getValue(), &Reason)) {
uint64_t C = FS->getEntrySamples();
auto &DI =
pgo::promoteIndirectCall(*I, R->getValue(), C, Sum, false, ORE);
Sum -= C;
PromotedInsns.insert(I);
// If profile mismatches, we should not attempt to inline DI.
if ((isa<CallInst>(DI) || isa<InvokeInst>(DI)) &&
inlineCallInstruction(cast<CallBase>(DI))) {
localNotInlinedCallSites.erase(I);
LocalChanged = true;
++NumCSInlined;
}
} else {
LLVM_DEBUG(dbgs()
<< "\nFailed to promote indirect call to "
<< CalleeFunctionName << " because " << Reason << "\n");
}
}
} else if (CalledFunction && CalledFunction->getSubprogram() &&
!CalledFunction->isDeclaration()) {
if (inlineCallInstruction(*I)) {
localNotInlinedCallSites.erase(I);
LocalChanged = true;
++NumCSInlined;
}
} else if (IsThinLTOPreLink) {
findCalleeFunctionSamples(*I)->findInlinedFunctions(
InlinedGUIDs, F.getParent(), PSI->getOrCompHotCountThreshold());
}
}
if (LocalChanged) {
Changed = true;
} else {
break;
}
}
// Accumulate not inlined callsite information into notInlinedSamples
for (const auto &Pair : localNotInlinedCallSites) {
CallBase *I = Pair.getFirst();
Function *Callee = I->getCalledFunction();
if (!Callee || Callee->isDeclaration())
continue;
ORE->emit(OptimizationRemarkAnalysis(CSINLINE_DEBUG, "NotInline",
I->getDebugLoc(), I->getParent())
<< "previous inlining not repeated: '"
<< ore::NV("Callee", Callee) << "' into '"
<< ore::NV("Caller", &F) << "'");
++NumCSNotInlined;
const FunctionSamples *FS = Pair.getSecond();
if (FS->getTotalSamples() == 0 && FS->getEntrySamples() == 0) {
continue;
}
if (ProfileMergeInlinee) {
// A function call can be replicated by optimizations like callsite
// splitting or jump threading and the replicates end up sharing the
// sample nested callee profile instead of slicing the original inlinee's
// profile. We want to do merge exactly once by filtering out callee
// profiles with a non-zero head sample count.
if (FS->getHeadSamples() == 0) {
// Use entry samples as head samples during the merge, as inlinees
// don't have head samples.
const_cast<FunctionSamples *>(FS)->addHeadSamples(
FS->getEntrySamples());
// Note that we have to do the merge right after processing function.
// This allows OutlineFS's profile to be used for annotation during
// top-down processing of functions' annotation.
FunctionSamples *OutlineFS = Reader->getOrCreateSamplesFor(*Callee);
OutlineFS->merge(*FS);
} else
assert(FS->getHeadSamples() == FS->getEntrySamples() &&
"Expect same head and entry sample counts for profiles already "
"merged.");
} else {
auto pair =
notInlinedCallInfo.try_emplace(Callee, NotInlinedProfileInfo{0});
pair.first->second.entryCount += FS->getEntrySamples();
}
}
return Changed;
}
/// Find equivalence classes for the given block.
///
/// This finds all the blocks that are guaranteed to execute the same
/// number of times as \p BB1. To do this, it traverses all the
/// descendants of \p BB1 in the dominator or post-dominator tree.
///
/// A block BB2 will be in the same equivalence class as \p BB1 if
/// the following holds:
///
/// 1- \p BB1 is a descendant of BB2 in the opposite tree. So, if BB2
/// is a descendant of \p BB1 in the dominator tree, then BB2 should
/// dominate BB1 in the post-dominator tree.
///
/// 2- Both BB2 and \p BB1 must be in the same loop.
///
/// For every block BB2 that meets those two requirements, we set BB2's
/// equivalence class to \p BB1.
///
/// \param BB1 Block to check.
/// \param Descendants Descendants of \p BB1 in either the dom or pdom tree.
/// \param DomTree Opposite dominator tree. If \p Descendants is filled
/// with blocks from \p BB1's dominator tree, then
/// this is the post-dominator tree, and vice versa.
template <bool IsPostDom>
void SampleProfileLoader::findEquivalencesFor(
BasicBlock *BB1, ArrayRef<BasicBlock *> Descendants,
DominatorTreeBase<BasicBlock, IsPostDom> *DomTree) {
const BasicBlock *EC = EquivalenceClass[BB1];
uint64_t Weight = BlockWeights[EC];
for (const auto *BB2 : Descendants) {
bool IsDomParent = DomTree->dominates(BB2, BB1);
bool IsInSameLoop = LI->getLoopFor(BB1) == LI->getLoopFor(BB2);
if (BB1 != BB2 && IsDomParent && IsInSameLoop) {
EquivalenceClass[BB2] = EC;
// If BB2 is visited, then the entire EC should be marked as visited.
if (VisitedBlocks.count(BB2)) {
VisitedBlocks.insert(EC);
}
// If BB2 is heavier than BB1, make BB2 have the same weight
// as BB1.
//
// Note that we don't worry about the opposite situation here
// (when BB2 is lighter than BB1). We will deal with this
// during the propagation phase. Right now, we just want to
// make sure that BB1 has the largest weight of all the
// members of its equivalence set.
Weight = std::max(Weight, BlockWeights[BB2]);
}
}
if (EC == &EC->getParent()->getEntryBlock()) {
BlockWeights[EC] = Samples->getHeadSamples() + 1;
} else {
BlockWeights[EC] = Weight;
}
}
/// Find equivalence classes.
///
/// Since samples may be missing from blocks, we can fill in the gaps by setting
/// the weights of all the blocks in the same equivalence class to the same
/// weight. To compute the concept of equivalence, we use dominance and loop
/// information. Two blocks B1 and B2 are in the same equivalence class if B1
/// dominates B2, B2 post-dominates B1 and both are in the same loop.
///
/// \param F The function to query.
void SampleProfileLoader::findEquivalenceClasses(Function &F) {
SmallVector<BasicBlock *, 8> DominatedBBs;
LLVM_DEBUG(dbgs() << "\nBlock equivalence classes\n");
// Find equivalence sets based on dominance and post-dominance information.
for (auto &BB : F) {
BasicBlock *BB1 = &BB;
// Compute BB1's equivalence class once.
if (EquivalenceClass.count(BB1)) {
LLVM_DEBUG(printBlockEquivalence(dbgs(), BB1));
continue;
}
// By default, blocks are in their own equivalence class.
EquivalenceClass[BB1] = BB1;
// Traverse all the blocks dominated by BB1. We are looking for
// every basic block BB2 such that:
//
// 1- BB1 dominates BB2.
// 2- BB2 post-dominates BB1.
// 3- BB1 and BB2 are in the same loop nest.
//
// If all those conditions hold, it means that BB2 is executed
// as many times as BB1, so they are placed in the same equivalence
// class by making BB2's equivalence class be BB1.
DominatedBBs.clear();
DT->getDescendants(BB1, DominatedBBs);
findEquivalencesFor(BB1, DominatedBBs, PDT.get());
LLVM_DEBUG(printBlockEquivalence(dbgs(), BB1));
}
// Assign weights to equivalence classes.
//
// All the basic blocks in the same equivalence class will execute
// the same number of times. Since we know that the head block in
// each equivalence class has the largest weight, assign that weight
// to all the blocks in that equivalence class.
LLVM_DEBUG(
dbgs() << "\nAssign the same weight to all blocks in the same class\n");
for (auto &BI : F) {
const BasicBlock *BB = &BI;
const BasicBlock *EquivBB = EquivalenceClass[BB];
if (BB != EquivBB)
BlockWeights[BB] = BlockWeights[EquivBB];
LLVM_DEBUG(printBlockWeight(dbgs(), BB));
}
}
/// Visit the given edge to decide if it has a valid weight.
///
/// If \p E has not been visited before, we copy to \p UnknownEdge
/// and increment the count of unknown edges.
///
/// \param E Edge to visit.
/// \param NumUnknownEdges Current number of unknown edges.
/// \param UnknownEdge Set if E has not been visited before.
///
/// \returns E's weight, if known. Otherwise, return 0.
uint64_t SampleProfileLoader::visitEdge(Edge E, unsigned *NumUnknownEdges,
Edge *UnknownEdge) {
if (!VisitedEdges.count(E)) {
(*NumUnknownEdges)++;
*UnknownEdge = E;
return 0;
}
return EdgeWeights[E];
}
/// Propagate weights through incoming/outgoing edges.
///
/// If the weight of a basic block is known, and there is only one edge
/// with an unknown weight, we can calculate the weight of that edge.
///
/// Similarly, if all the edges have a known count, we can calculate the
/// count of the basic block, if needed.
///
/// \param F Function to process.
/// \param UpdateBlockCount Whether we should update basic block counts that
/// has already been annotated.
///
/// \returns True if new weights were assigned to edges or blocks.
bool SampleProfileLoader::propagateThroughEdges(Function &F,
bool UpdateBlockCount) {
bool Changed = false;
LLVM_DEBUG(dbgs() << "\nPropagation through edges\n");
for (const auto &BI : F) {
const BasicBlock *BB = &BI;
const BasicBlock *EC = EquivalenceClass[BB];
// Visit all the predecessor and successor edges to determine
// which ones have a weight assigned already. Note that it doesn't
// matter that we only keep track of a single unknown edge. The
// only case we are interested in handling is when only a single
// edge is unknown (see setEdgeOrBlockWeight).
for (unsigned i = 0; i < 2; i++) {
uint64_t TotalWeight = 0;
unsigned NumUnknownEdges = 0, NumTotalEdges = 0;
Edge UnknownEdge, SelfReferentialEdge, SingleEdge;
if (i == 0) {
// First, visit all predecessor edges.
NumTotalEdges = Predecessors[BB].size();
for (auto *Pred : Predecessors[BB]) {
Edge E = std::make_pair(Pred, BB);
TotalWeight += visitEdge(E, &NumUnknownEdges, &UnknownEdge);
if (E.first == E.second)
SelfReferentialEdge = E;
}
if (NumTotalEdges == 1) {
SingleEdge = std::make_pair(Predecessors[BB][0], BB);
}
} else {
// On the second round, visit all successor edges.
NumTotalEdges = Successors[BB].size();
for (auto *Succ : Successors[BB]) {
Edge E = std::make_pair(BB, Succ);
TotalWeight += visitEdge(E, &NumUnknownEdges, &UnknownEdge);
}
if (NumTotalEdges == 1) {
SingleEdge = std::make_pair(BB, Successors[BB][0]);
}
}
// After visiting all the edges, there are three cases that we
// can handle immediately:
//
// - All the edge weights are known (i.e., NumUnknownEdges == 0).
// In this case, we simply check that the sum of all the edges
// is the same as BB's weight. If not, we change BB's weight
// to match. Additionally, if BB had not been visited before,
// we mark it visited.
//
// - Only one edge is unknown and BB has already been visited.
// In this case, we can compute the weight of the edge by
// subtracting the total block weight from all the known
// edge weights. If the edges weight more than BB, then the
// edge of the last remaining edge is set to zero.
//
// - There exists a self-referential edge and the weight of BB is
// known. In this case, this edge can be based on BB's weight.
// We add up all the other known edges and set the weight on
// the self-referential edge as we did in the previous case.
//
// In any other case, we must continue iterating. Eventually,
// all edges will get a weight, or iteration will stop when
// it reaches SampleProfileMaxPropagateIterations.
if (NumUnknownEdges <= 1) {
uint64_t &BBWeight = BlockWeights[EC];
if (NumUnknownEdges == 0) {
if (!VisitedBlocks.count(EC)) {
// If we already know the weight of all edges, the weight of the
// basic block can be computed. It should be no larger than the sum
// of all edge weights.
if (TotalWeight > BBWeight) {
BBWeight = TotalWeight;
Changed = true;
LLVM_DEBUG(dbgs() << "All edge weights for " << BB->getName()
<< " known. Set weight for block: ";
printBlockWeight(dbgs(), BB););
}
} else if (NumTotalEdges == 1 &&
EdgeWeights[SingleEdge] < BlockWeights[EC]) {
// If there is only one edge for the visited basic block, use the
// block weight to adjust edge weight if edge weight is smaller.
EdgeWeights[SingleEdge] = BlockWeights[EC];
Changed = true;
}
} else if (NumUnknownEdges == 1 && VisitedBlocks.count(EC)) {
// If there is a single unknown edge and the block has been
// visited, then we can compute E's weight.
if (BBWeight >= TotalWeight)
EdgeWeights[UnknownEdge] = BBWeight - TotalWeight;
else
EdgeWeights[UnknownEdge] = 0;
const BasicBlock *OtherEC;
if (i == 0)
OtherEC = EquivalenceClass[UnknownEdge.first];
else
OtherEC = EquivalenceClass[UnknownEdge.second];
// Edge weights should never exceed the BB weights it connects.
if (VisitedBlocks.count(OtherEC) &&
EdgeWeights[UnknownEdge] > BlockWeights[OtherEC])
EdgeWeights[UnknownEdge] = BlockWeights[OtherEC];
VisitedEdges.insert(UnknownEdge);
Changed = true;
LLVM_DEBUG(dbgs() << "Set weight for edge: ";
printEdgeWeight(dbgs(), UnknownEdge));
}
} else if (VisitedBlocks.count(EC) && BlockWeights[EC] == 0) {
// If a block Weights 0, all its in/out edges should weight 0.
if (i == 0) {
for (auto *Pred : Predecessors[BB]) {
Edge E = std::make_pair(Pred, BB);
EdgeWeights[E] = 0;
VisitedEdges.insert(E);
}
} else {
for (auto *Succ : Successors[BB]) {
Edge E = std::make_pair(BB, Succ);
EdgeWeights[E] = 0;
VisitedEdges.insert(E);
}
}
} else if (SelfReferentialEdge.first && VisitedBlocks.count(EC)) {
uint64_t &BBWeight = BlockWeights[BB];
// We have a self-referential edge and the weight of BB is known.
if (BBWeight >= TotalWeight)
EdgeWeights[SelfReferentialEdge] = BBWeight - TotalWeight;
else
EdgeWeights[SelfReferentialEdge] = 0;
VisitedEdges.insert(SelfReferentialEdge);
Changed = true;
LLVM_DEBUG(dbgs() << "Set self-referential edge weight to: ";
printEdgeWeight(dbgs(), SelfReferentialEdge));
}
if (UpdateBlockCount && !VisitedBlocks.count(EC) && TotalWeight > 0) {
BlockWeights[EC] = TotalWeight;
VisitedBlocks.insert(EC);
Changed = true;
}
}
}
return Changed;
}
/// Build in/out edge lists for each basic block in the CFG.
///
/// We are interested in unique edges. If a block B1 has multiple
/// edges to another block B2, we only add a single B1->B2 edge.
void SampleProfileLoader::buildEdges(Function &F) {
for (auto &BI : F) {
BasicBlock *B1 = &BI;
// Add predecessors for B1.
SmallPtrSet<BasicBlock *, 16> Visited;
if (!Predecessors[B1].empty())
llvm_unreachable("Found a stale predecessors list in a basic block.");
for (pred_iterator PI = pred_begin(B1), PE = pred_end(B1); PI != PE; ++PI) {
BasicBlock *B2 = *PI;
if (Visited.insert(B2).second)
Predecessors[B1].push_back(B2);
}
// Add successors for B1.
Visited.clear();
if (!Successors[B1].empty())
llvm_unreachable("Found a stale successors list in a basic block.");
for (succ_iterator SI = succ_begin(B1), SE = succ_end(B1); SI != SE; ++SI) {
BasicBlock *B2 = *SI;
if (Visited.insert(B2).second)
Successors[B1].push_back(B2);
}
}
}
/// Returns the sorted CallTargetMap \p M by count in descending order.
static SmallVector<InstrProfValueData, 2> GetSortedValueDataFromCallTargets(
const SampleRecord::CallTargetMap & M) {
SmallVector<InstrProfValueData, 2> R;
for (const auto &I : SampleRecord::SortCallTargets(M)) {
R.emplace_back(InstrProfValueData{FunctionSamples::getGUID(I.first), I.second});
}
return R;
}
/// Propagate weights into edges
///
/// The following rules are applied to every block BB in the CFG:
///
/// - If BB has a single predecessor/successor, then the weight
/// of that edge is the weight of the block.
///
/// - If all incoming or outgoing edges are known except one, and the
/// weight of the block is already known, the weight of the unknown
/// edge will be the weight of the block minus the sum of all the known
/// edges. If the sum of all the known edges is larger than BB's weight,
/// we set the unknown edge weight to zero.
///
/// - If there is a self-referential edge, and the weight of the block is
/// known, the weight for that edge is set to the weight of the block
/// minus the weight of the other incoming edges to that block (if
/// known).
void SampleProfileLoader::propagateWeights(Function &F) {
bool Changed = true;
unsigned I = 0;
// If BB weight is larger than its corresponding loop's header BB weight,
// use the BB weight to replace the loop header BB weight.
for (auto &BI : F) {
BasicBlock *BB = &BI;
Loop *L = LI->getLoopFor(BB);
if (!L) {
continue;
}
BasicBlock *Header = L->getHeader();
if (Header && BlockWeights[BB] > BlockWeights[Header]) {
BlockWeights[Header] = BlockWeights[BB];
}
}
// Before propagation starts, build, for each block, a list of
// unique predecessors and successors. This is necessary to handle
// identical edges in multiway branches. Since we visit all blocks and all
// edges of the CFG, it is cleaner to build these lists once at the start
// of the pass.
buildEdges(F);
// Propagate until we converge or we go past the iteration limit.
while (Changed && I++ < SampleProfileMaxPropagateIterations) {
Changed = propagateThroughEdges(F, false);
}
// The first propagation propagates BB counts from annotated BBs to unknown
// BBs. The 2nd propagation pass resets edges weights, and use all BB weights
// to propagate edge weights.
VisitedEdges.clear();
Changed = true;
while (Changed && I++ < SampleProfileMaxPropagateIterations) {
Changed = propagateThroughEdges(F, false);
}
// The 3rd propagation pass allows adjust annotated BB weights that are
// obviously wrong.
Changed = true;
while (Changed && I++ < SampleProfileMaxPropagateIterations) {
Changed = propagateThroughEdges(F, true);
}
// Generate MD_prof metadata for every branch instruction using the
// edge weights computed during propagation.
LLVM_DEBUG(dbgs() << "\nPropagation complete. Setting branch weights\n");
LLVMContext &Ctx = F.getContext();
MDBuilder MDB(Ctx);
for (auto &BI : F) {
BasicBlock *BB = &BI;
if (BlockWeights[BB]) {
for (auto &I : BB->getInstList()) {
if (!isa<CallInst>(I) && !isa<InvokeInst>(I))
continue;
if (!cast<CallBase>(I).getCalledFunction()) {
const DebugLoc &DLoc = I.getDebugLoc();
if (!DLoc)
continue;
const DILocation *DIL = DLoc;
uint32_t LineOffset = FunctionSamples::getOffset(DIL);
uint32_t Discriminator = DIL->getBaseDiscriminator();
const FunctionSamples *FS = findFunctionSamples(I);
if (!FS)
continue;
auto T = FS->findCallTargetMapAt(LineOffset, Discriminator);
if (!T || T.get().empty())
continue;
SmallVector<InstrProfValueData, 2> SortedCallTargets =
GetSortedValueDataFromCallTargets(T.get());
uint64_t Sum;
findIndirectCallFunctionSamples(I, Sum);
annotateValueSite(*I.getParent()->getParent()->getParent(), I,
SortedCallTargets, Sum, IPVK_IndirectCallTarget,
SortedCallTargets.size());
} else if (!isa<IntrinsicInst>(&I)) {
I.setMetadata(LLVMContext::MD_prof,
MDB.createBranchWeights(
{static_cast<uint32_t>(BlockWeights[BB])}));
}
}
}
Instruction *TI = BB->getTerminator();
if (TI->getNumSuccessors() == 1)
continue;
if (!isa<BranchInst>(TI) && !isa<SwitchInst>(TI))
continue;
DebugLoc BranchLoc = TI->getDebugLoc();
LLVM_DEBUG(dbgs() << "\nGetting weights for branch at line "
<< ((BranchLoc) ? Twine(BranchLoc.getLine())
: Twine("<UNKNOWN LOCATION>"))
<< ".\n");
SmallVector<uint32_t, 4> Weights;
uint32_t MaxWeight = 0;
Instruction *MaxDestInst;
for (unsigned I = 0; I < TI->getNumSuccessors(); ++I) {
BasicBlock *Succ = TI->getSuccessor(I);
Edge E = std::make_pair(BB, Succ);
uint64_t Weight = EdgeWeights[E];
LLVM_DEBUG(dbgs() << "\t"; printEdgeWeight(dbgs(), E));
// Use uint32_t saturated arithmetic to adjust the incoming weights,
// if needed. Sample counts in profiles are 64-bit unsigned values,
// but internally branch weights are expressed as 32-bit values.
if (Weight > std::numeric_limits<uint32_t>::max()) {
LLVM_DEBUG(dbgs() << " (saturated due to uint32_t overflow)");
Weight = std::numeric_limits<uint32_t>::max();
}
// Weight is added by one to avoid propagation errors introduced by
// 0 weights.
Weights.push_back(static_cast<uint32_t>(Weight + 1));
if (Weight != 0) {
if (Weight > MaxWeight) {
MaxWeight = Weight;
MaxDestInst = Succ->getFirstNonPHIOrDbgOrLifetime();
}
}
}
misexpect::verifyMisExpect(TI, Weights, TI->getContext());
uint64_t TempWeight;
// Only set weights if there is at least one non-zero weight.
// In any other case, let the analyzer set weights.
// Do not set weights if the weights are present. In ThinLTO, the profile
// annotation is done twice. If the first annotation already set the
// weights, the second pass does not need to set it.
if (MaxWeight > 0 && !TI->extractProfTotalWeight(TempWeight)) {
LLVM_DEBUG(dbgs() << "SUCCESS. Found non-zero weights.\n");
TI->setMetadata(LLVMContext::MD_prof,
MDB.createBranchWeights(Weights));
ORE->emit([&]() {
return OptimizationRemark(DEBUG_TYPE, "PopularDest", MaxDestInst)
<< "most popular destination for conditional branches at "
<< ore::NV("CondBranchesLoc", BranchLoc);
});
} else {
LLVM_DEBUG(dbgs() << "SKIPPED. All branch weights are zero.\n");
}
}
}
/// Get the line number for the function header.
///
/// This looks up function \p F in the current compilation unit and
/// retrieves the line number where the function is defined. This is
/// line 0 for all the samples read from the profile file. Every line
/// number is relative to this line.
///
/// \param F Function object to query.
///
/// \returns the line number where \p F is defined. If it returns 0,
/// it means that there is no debug information available for \p F.
unsigned SampleProfileLoader::getFunctionLoc(Function &F) {
if (DISubprogram *S = F.getSubprogram())
return S->getLine();
if (NoWarnSampleUnused)
return 0;
// If the start of \p F is missing, emit a diagnostic to inform the user
// about the missed opportunity.
F.getContext().diagnose(DiagnosticInfoSampleProfile(
"No debug information found in function " + F.getName() +
": Function profile not used",
DS_Warning));
return 0;
}
void SampleProfileLoader::computeDominanceAndLoopInfo(Function &F) {
DT.reset(new DominatorTree);
DT->recalculate(F);
PDT.reset(new PostDominatorTree(F));
LI.reset(new LoopInfo);
LI->analyze(*DT);
}
/// Generate branch weight metadata for all branches in \p F.
///
/// Branch weights are computed out of instruction samples using a
/// propagation heuristic. Propagation proceeds in 3 phases:
///
/// 1- Assignment of block weights. All the basic blocks in the function
/// are initial assigned the same weight as their most frequently
/// executed instruction.
///
/// 2- Creation of equivalence classes. Since samples may be missing from
/// blocks, we can fill in the gaps by setting the weights of all the
/// blocks in the same equivalence class to the same weight. To compute
/// the concept of equivalence, we use dominance and loop information.
/// Two blocks B1 and B2 are in the same equivalence class if B1
/// dominates B2, B2 post-dominates B1 and both are in the same loop.
///
/// 3- Propagation of block weights into edges. This uses a simple
/// propagation heuristic. The following rules are applied to every
/// block BB in the CFG:
///
/// - If BB has a single predecessor/successor, then the weight
/// of that edge is the weight of the block.
///
/// - If all the edges are known except one, and the weight of the
/// block is already known, the weight of the unknown edge will
/// be the weight of the block minus the sum of all the known
/// edges. If the sum of all the known edges is larger than BB's weight,
/// we set the unknown edge weight to zero.
///
/// - If there is a self-referential edge, and the weight of the block is
/// known, the weight for that edge is set to the weight of the block
/// minus the weight of the other incoming edges to that block (if
/// known).
///
/// Since this propagation is not guaranteed to finalize for every CFG, we
/// only allow it to proceed for a limited number of iterations (controlled
/// by -sample-profile-max-propagate-iterations).
///
/// FIXME: Try to replace this propagation heuristic with a scheme
/// that is guaranteed to finalize. A work-list approach similar to
/// the standard value propagation algorithm used by SSA-CCP might
/// work here.
///
/// Once all the branch weights are computed, we emit the MD_prof
/// metadata on BB using the computed values for each of its branches.
///
/// \param F The function to query.
///
/// \returns true if \p F was modified. Returns false, otherwise.
bool SampleProfileLoader::emitAnnotations(Function &F) {
bool Changed = false;
if (getFunctionLoc(F) == 0)
return false;
LLVM_DEBUG(dbgs() << "Line number for the first instruction in "
<< F.getName() << ": " << getFunctionLoc(F) << "\n");
DenseSet<GlobalValue::GUID> InlinedGUIDs;
Changed |= inlineHotFunctions(F, InlinedGUIDs);
// Compute basic block weights.
Changed |= computeBlockWeights(F);
if (Changed) {
// Add an entry count to the function using the samples gathered at the
// function entry.
// Sets the GUIDs that are inlined in the profiled binary. This is used
// for ThinLink to make correct liveness analysis, and also make the IR
// match the profiled binary before annotation.
F.setEntryCount(
ProfileCount(Samples->getHeadSamples() + 1, Function::PCT_Real),
&InlinedGUIDs);
// Compute dominance and loop info needed for propagation.
computeDominanceAndLoopInfo(F);
// Find equivalence classes.
findEquivalenceClasses(F);
// Propagate weights to all edges.
propagateWeights(F);
}
// If coverage checking was requested, compute it now.
if (SampleProfileRecordCoverage) {
unsigned Used = CoverageTracker.countUsedRecords(Samples, PSI);
unsigned Total = CoverageTracker.countBodyRecords(Samples, PSI);
unsigned Coverage = CoverageTracker.computeCoverage(Used, Total);
if (Coverage < SampleProfileRecordCoverage) {
F.getContext().diagnose(DiagnosticInfoSampleProfile(
F.getSubprogram()->getFilename(), getFunctionLoc(F),
Twine(Used) + " of " + Twine(Total) + " available profile records (" +
Twine(Coverage) + "%) were applied",
DS_Warning));
}
}
if (SampleProfileSampleCoverage) {
uint64_t Used = CoverageTracker.getTotalUsedSamples();
uint64_t Total = CoverageTracker.countBodySamples(Samples, PSI);
unsigned Coverage = CoverageTracker.computeCoverage(Used, Total);
if (Coverage < SampleProfileSampleCoverage) {
F.getContext().diagnose(DiagnosticInfoSampleProfile(
F.getSubprogram()->getFilename(), getFunctionLoc(F),
Twine(Used) + " of " + Twine(Total) + " available profile samples (" +
Twine(Coverage) + "%) were applied",
DS_Warning));
}
}
return Changed;
}
char SampleProfileLoaderLegacyPass::ID = 0;
INITIALIZE_PASS_BEGIN(SampleProfileLoaderLegacyPass, "sample-profile",
"Sample Profile loader", false, false)
INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker)
INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass)
INITIALIZE_PASS_DEPENDENCY(TargetLibraryInfoWrapperPass)
INITIALIZE_PASS_DEPENDENCY(ProfileSummaryInfoWrapperPass)
INITIALIZE_PASS_END(SampleProfileLoaderLegacyPass, "sample-profile",
"Sample Profile loader", false, false)
std::vector<Function *>
SampleProfileLoader::buildFunctionOrder(Module &M, CallGraph *CG) {
std::vector<Function *> FunctionOrderList;
FunctionOrderList.reserve(M.size());
if (!ProfileTopDownLoad || CG == nullptr) {
if (ProfileMergeInlinee) {
// Disable ProfileMergeInlinee if profile is not loaded in top down order,
// because the profile for a function may be used for the profile
// annotation of its outline copy before the profile merging of its
// non-inlined inline instances, and that is not the way how
// ProfileMergeInlinee is supposed to work.
ProfileMergeInlinee = false;
}
for (Function &F : M)
if (!F.isDeclaration() && F.hasFnAttribute("use-sample-profile"))
FunctionOrderList.push_back(&F);
return FunctionOrderList;
}
assert(&CG->getModule() == &M);
scc_iterator<CallGraph *> CGI = scc_begin(CG);
while (!CGI.isAtEnd()) {
for (CallGraphNode *node : *CGI) {
auto F = node->getFunction();
if (F && !F->isDeclaration() && F->hasFnAttribute("use-sample-profile"))
FunctionOrderList.push_back(F);
}
++CGI;
}
std::reverse(FunctionOrderList.begin(), FunctionOrderList.end());
return FunctionOrderList;
}
bool SampleProfileLoader::doInitialization(Module &M,
FunctionAnalysisManager *FAM) {
auto &Ctx = M.getContext();
auto ReaderOrErr =
SampleProfileReader::create(Filename, Ctx, RemappingFilename);
if (std::error_code EC = ReaderOrErr.getError()) {
std::string Msg = "Could not open profile: " + EC.message();
Ctx.diagnose(DiagnosticInfoSampleProfile(Filename, Msg));
return false;
}
Reader = std::move(ReaderOrErr.get());
Reader->collectFuncsFrom(M);
ProfileIsValid = (Reader->read() == sampleprof_error::success);
PSL = Reader->getProfileSymbolList();
// While profile-sample-accurate is on, ignore symbol list.
ProfAccForSymsInList =
ProfileAccurateForSymsInList && PSL && !ProfileSampleAccurate;
if (ProfAccForSymsInList) {
NamesInProfile.clear();
if (auto NameTable = Reader->getNameTable())
NamesInProfile.insert(NameTable->begin(), NameTable->end());
}
if (FAM && !ProfileInlineReplayFile.empty()) {
ExternalInlineAdvisor = std::make_unique<ReplayInlineAdvisor>(
*FAM, Ctx, ProfileInlineReplayFile);
if (!ExternalInlineAdvisor->areReplayRemarksLoaded())
ExternalInlineAdvisor.reset();
}
return true;
}
ModulePass *llvm::createSampleProfileLoaderPass() {
return new SampleProfileLoaderLegacyPass();
}
ModulePass *llvm::createSampleProfileLoaderPass(StringRef Name) {
return new SampleProfileLoaderLegacyPass(Name);
}
bool SampleProfileLoader::runOnModule(Module &M, ModuleAnalysisManager *AM,
ProfileSummaryInfo *_PSI, CallGraph *CG) {
if (!ProfileIsValid)
return false;
GUIDToFuncNameMapper Mapper(M, *Reader, GUIDToFuncNameMap);
PSI = _PSI;
if (M.getProfileSummary(/* IsCS */ false) == nullptr) {
M.setProfileSummary(Reader->getSummary().getMD(M.getContext()),
ProfileSummary::PSK_Sample);
PSI->refresh();
}
// Compute the total number of samples collected in this profile.
for (const auto &I : Reader->getProfiles())
TotalCollectedSamples += I.second.getTotalSamples();
auto Remapper = Reader->getRemapper();
// Populate the symbol map.
for (const auto &N_F : M.getValueSymbolTable()) {
StringRef OrigName = N_F.getKey();
Function *F = dyn_cast<Function>(N_F.getValue());
if (F == nullptr)
continue;
SymbolMap[OrigName] = F;
auto pos = OrigName.find('.');
if (pos != StringRef::npos) {
StringRef NewName = OrigName.substr(0, pos);
auto r = SymbolMap.insert(std::make_pair(NewName, F));
// Failiing to insert means there is already an entry in SymbolMap,
// thus there are multiple functions that are mapped to the same
// stripped name. In this case of name conflicting, set the value
// to nullptr to avoid confusion.
if (!r.second)
r.first->second = nullptr;
OrigName = NewName;
}
// Insert the remapped names into SymbolMap.
if (Remapper) {
if (auto MapName = Remapper->lookUpNameInProfile(OrigName)) {
if (*MapName == OrigName)
continue;
SymbolMap.insert(std::make_pair(*MapName, F));
}
}
}
bool retval = false;
for (auto F : buildFunctionOrder(M, CG)) {
assert(!F->isDeclaration());
clearFunctionData();
retval |= runOnFunction(*F, AM);
}
// Account for cold calls not inlined....
for (const std::pair<Function *, NotInlinedProfileInfo> &pair :
notInlinedCallInfo)
updateProfileCallee(pair.first, pair.second.entryCount);
return retval;
}
bool SampleProfileLoaderLegacyPass::runOnModule(Module &M) {
ACT = &getAnalysis<AssumptionCacheTracker>();
TTIWP = &getAnalysis<TargetTransformInfoWrapperPass>();
TLIWP = &getAnalysis<TargetLibraryInfoWrapperPass>();
ProfileSummaryInfo *PSI =
&getAnalysis<ProfileSummaryInfoWrapperPass>().getPSI();
return SampleLoader.runOnModule(M, nullptr, PSI, nullptr);
}
bool SampleProfileLoader::runOnFunction(Function &F, ModuleAnalysisManager *AM) {
DILocation2SampleMap.clear();
// By default the entry count is initialized to -1, which will be treated
// conservatively by getEntryCount as the same as unknown (None). This is
// to avoid newly added code to be treated as cold. If we have samples
// this will be overwritten in emitAnnotations.
uint64_t initialEntryCount = -1;
ProfAccForSymsInList = ProfileAccurateForSymsInList && PSL;
if (ProfileSampleAccurate || F.hasFnAttribute("profile-sample-accurate")) {
// initialize all the function entry counts to 0. It means all the
// functions without profile will be regarded as cold.
initialEntryCount = 0;
// profile-sample-accurate is a user assertion which has a higher precedence
// than symbol list. When profile-sample-accurate is on, ignore symbol list.
ProfAccForSymsInList = false;
}
// PSL -- profile symbol list include all the symbols in sampled binary.
// If ProfileAccurateForSymsInList is enabled, PSL is used to treat
// old functions without samples being cold, without having to worry
// about new and hot functions being mistakenly treated as cold.
if (ProfAccForSymsInList) {
// Initialize the entry count to 0 for functions in the list.
if (PSL->contains(F.getName()))
initialEntryCount = 0;
// Function in the symbol list but without sample will be regarded as
// cold. To minimize the potential negative performance impact it could
// have, we want to be a little conservative here saying if a function
// shows up in the profile, no matter as outline function, inline instance
// or call targets, treat the function as not being cold. This will handle
// the cases such as most callsites of a function are inlined in sampled
// binary but not inlined in current build (because of source code drift,
// imprecise debug information, or the callsites are all cold individually
// but not cold accumulatively...), so the outline function showing up as
// cold in sampled binary will actually not be cold after current build.
StringRef CanonName = FunctionSamples::getCanonicalFnName(F);
if (NamesInProfile.count(CanonName))
initialEntryCount = -1;
}
F.setEntryCount(ProfileCount(initialEntryCount, Function::PCT_Real));
std::unique_ptr<OptimizationRemarkEmitter> OwnedORE;
if (AM) {
auto &FAM =
AM->getResult<FunctionAnalysisManagerModuleProxy>(*F.getParent())
.getManager();
ORE = &FAM.getResult<OptimizationRemarkEmitterAnalysis>(F);
} else {
OwnedORE = std::make_unique<OptimizationRemarkEmitter>(&F);
ORE = OwnedORE.get();
}
Samples = Reader->getSamplesFor(F);
if (Samples && !Samples->empty())
return emitAnnotations(F);
return false;
}
PreservedAnalyses SampleProfileLoaderPass::run(Module &M,
ModuleAnalysisManager &AM) {
FunctionAnalysisManager &FAM =
AM.getResult<FunctionAnalysisManagerModuleProxy>(M).getManager();
auto GetAssumptionCache = [&](Function &F) -> AssumptionCache & {
return FAM.getResult<AssumptionAnalysis>(F);
};
auto GetTTI = [&](Function &F) -> TargetTransformInfo & {
return FAM.getResult<TargetIRAnalysis>(F);
};
auto GetTLI = [&](Function &F) -> const TargetLibraryInfo & {
return FAM.getResult<TargetLibraryAnalysis>(F);
};
SampleProfileLoader SampleLoader(
ProfileFileName.empty() ? SampleProfileFile : ProfileFileName,
ProfileRemappingFileName.empty() ? SampleProfileRemappingFile
: ProfileRemappingFileName,
IsThinLTOPreLink, GetAssumptionCache, GetTTI, GetTLI);
if (!SampleLoader.doInitialization(M, &FAM))
return PreservedAnalyses::all();
ProfileSummaryInfo *PSI = &AM.getResult<ProfileSummaryAnalysis>(M);
CallGraph &CG = AM.getResult<CallGraphAnalysis>(M);
if (!SampleLoader.runOnModule(M, &AM, PSI, &CG))
return PreservedAnalyses::all();
return PreservedAnalyses::none();
}
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