
Previously dangling samples were represented by INT64_MAX in sample profile while probes never executed were not reported. This was based on an observation that dangling probes were only at a smaller portion than zero-count probes. However, with compiler optimizations, dangling probes end up becoming at large portion of all probes in general and reporting them does not make sense from profile size point of view. This change flips sample reporting by reporting zero-count probes instead. This enabled dangling probe to be represented by none (missing entry in profile). This has a couple benefits: 1. Reducing sample profile size in optimize mode, even when the number of non-executed probes outperform the number of dangling probes, since INT64_MAX takes more space over 0 to encode. 2. Binary size savings. No need to encode dangling probe anymore, since missing probes are treated as dangling in the profile reader. 3. Reducing compiler work to track dangling probes. However, for probes that are real dead and removed, we still need the compiler to identify them so that they can be reported as zero-count, instead of mistreated as dangling probes. 4. Improving counts quality by respecting the counts already collected on the non-dangling copy of a probe. A probe, when duplicated, gets two copies at runtime. If one of them is dangling while the other is not, merging the two probes at profile generation time will cause the real samples collected on the non-dangling one to be discarded. Not reporting the dangling counterpart will keep the real samples. 5. Better readability. 6. Be consistent with non-CS dwarf line number based profile. Zero counts are trusted by the compiler counts inferencer while missing counts will be inferred by the compiler. Note that the current patch does include any work for #3. There will be follow-up changes. For #1, I've seen for a large Facebook service, the text profile is reduced by 7%. For extbinary profile, the size of LBRProfileSection is reduced by 35%. For #4, I have seen general counts quality for SPEC2017 is improved by 10%. Reviewed By: wenlei, wlei, wmi Differential Revision: https://reviews.llvm.org/D104129
638 lines
25 KiB
C++
638 lines
25 KiB
C++
//===-- ProfileGenerator.cpp - Profile Generator ---------------*- C++ -*-===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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#include "ProfileGenerator.h"
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#include "llvm/ProfileData/ProfileCommon.h"
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static cl::opt<std::string> OutputFilename("output", cl::value_desc("output"),
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cl::Required,
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cl::desc("Output profile file"));
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static cl::alias OutputA("o", cl::desc("Alias for --output"),
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cl::aliasopt(OutputFilename));
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static cl::opt<SampleProfileFormat> OutputFormat(
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"format", cl::desc("Format of output profile"), cl::init(SPF_Ext_Binary),
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cl::values(
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clEnumValN(SPF_Binary, "binary", "Binary encoding (default)"),
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clEnumValN(SPF_Compact_Binary, "compbinary", "Compact binary encoding"),
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clEnumValN(SPF_Ext_Binary, "extbinary", "Extensible binary encoding"),
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clEnumValN(SPF_Text, "text", "Text encoding"),
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clEnumValN(SPF_GCC, "gcc",
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"GCC encoding (only meaningful for -sample)")));
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static cl::opt<int32_t, true> RecursionCompression(
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"compress-recursion",
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cl::desc("Compressing recursion by deduplicating adjacent frame "
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"sequences up to the specified size. -1 means no size limit."),
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cl::Hidden,
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cl::location(llvm::sampleprof::CSProfileGenerator::MaxCompressionSize));
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static cl::opt<bool> CSProfMergeColdContext(
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"csprof-merge-cold-context", cl::init(true), cl::ZeroOrMore,
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cl::desc("If the total count of context profile is smaller than "
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"the threshold, it will be merged into context-less base "
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"profile."));
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static cl::opt<bool> CSProfTrimColdContext(
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"csprof-trim-cold-context", cl::init(true), cl::ZeroOrMore,
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cl::desc("If the total count of the profile after all merge is done "
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"is still smaller than threshold, it will be trimmed."));
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static cl::opt<uint32_t> CSProfColdContextFrameDepth(
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"csprof-frame-depth-for-cold-context", cl::init(1), cl::ZeroOrMore,
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cl::desc("Keep the last K frames while merging cold profile. 1 means the "
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"context-less base profile"));
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extern cl::opt<int> ProfileSummaryCutoffCold;
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using namespace llvm;
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using namespace sampleprof;
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namespace llvm {
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namespace sampleprof {
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// Initialize the MaxCompressionSize to -1 which means no size limit
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int32_t CSProfileGenerator::MaxCompressionSize = -1;
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static bool
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usePseudoProbes(const BinarySampleCounterMap &BinarySampleCounters) {
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return BinarySampleCounters.size() &&
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BinarySampleCounters.begin()->first->usePseudoProbes();
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}
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std::unique_ptr<ProfileGenerator>
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ProfileGenerator::create(const BinarySampleCounterMap &BinarySampleCounters,
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enum PerfScriptType SampleType) {
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std::unique_ptr<ProfileGenerator> ProfileGenerator;
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if (SampleType == PERF_LBR_STACK) {
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if (usePseudoProbes(BinarySampleCounters)) {
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ProfileGenerator.reset(
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new PseudoProbeCSProfileGenerator(BinarySampleCounters));
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} else {
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ProfileGenerator.reset(new CSProfileGenerator(BinarySampleCounters));
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}
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} else {
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// TODO:
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llvm_unreachable("Unsupported perfscript!");
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}
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return ProfileGenerator;
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}
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void ProfileGenerator::write(std::unique_ptr<SampleProfileWriter> Writer,
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StringMap<FunctionSamples> &ProfileMap) {
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if (std::error_code EC = Writer->write(ProfileMap))
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exitWithError(std::move(EC));
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}
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void ProfileGenerator::write() {
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auto WriterOrErr = SampleProfileWriter::create(OutputFilename, OutputFormat);
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if (std::error_code EC = WriterOrErr.getError())
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exitWithError(EC, OutputFilename);
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write(std::move(WriterOrErr.get()), ProfileMap);
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}
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void ProfileGenerator::findDisjointRanges(RangeSample &DisjointRanges,
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const RangeSample &Ranges) {
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/*
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Regions may overlap with each other. Using the boundary info, find all
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disjoint ranges and their sample count. BoundaryPoint contains the count
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multiple samples begin/end at this points.
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|<--100-->| Sample1
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|<------200------>| Sample2
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A B C
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In the example above,
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Sample1 begins at A, ends at B, its value is 100.
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Sample2 beings at A, ends at C, its value is 200.
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For A, BeginCount is the sum of sample begins at A, which is 300 and no
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samples ends at A, so EndCount is 0.
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Then boundary points A, B, and C with begin/end counts are:
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A: (300, 0)
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B: (0, 100)
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C: (0, 200)
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*/
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struct BoundaryPoint {
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// Sum of sample counts beginning at this point
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uint64_t BeginCount;
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// Sum of sample counts ending at this point
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uint64_t EndCount;
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BoundaryPoint() : BeginCount(0), EndCount(0){};
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void addBeginCount(uint64_t Count) { BeginCount += Count; }
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void addEndCount(uint64_t Count) { EndCount += Count; }
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};
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/*
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For the above example. With boundary points, follwing logic finds two
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disjoint region of
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[A,B]: 300
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[B+1,C]: 200
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If there is a boundary point that both begin and end, the point itself
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becomes a separate disjoint region. For example, if we have original
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ranges of
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|<--- 100 --->|
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|<--- 200 --->|
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A B C
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there are three boundary points with their begin/end counts of
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A: (100, 0)
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B: (200, 100)
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C: (0, 200)
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the disjoint ranges would be
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[A, B-1]: 100
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[B, B]: 300
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[B+1, C]: 200.
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*/
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std::map<uint64_t, BoundaryPoint> Boundaries;
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for (auto Item : Ranges) {
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uint64_t Begin = Item.first.first;
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uint64_t End = Item.first.second;
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uint64_t Count = Item.second;
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if (Boundaries.find(Begin) == Boundaries.end())
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Boundaries[Begin] = BoundaryPoint();
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Boundaries[Begin].addBeginCount(Count);
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if (Boundaries.find(End) == Boundaries.end())
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Boundaries[End] = BoundaryPoint();
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Boundaries[End].addEndCount(Count);
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}
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uint64_t BeginAddress = 0;
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int Count = 0;
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for (auto Item : Boundaries) {
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uint64_t Address = Item.first;
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BoundaryPoint &Point = Item.second;
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if (Point.BeginCount) {
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if (BeginAddress)
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DisjointRanges[{BeginAddress, Address - 1}] = Count;
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Count += Point.BeginCount;
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BeginAddress = Address;
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}
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if (Point.EndCount) {
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assert(BeginAddress && "First boundary point cannot be 'end' point");
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DisjointRanges[{BeginAddress, Address}] = Count;
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Count -= Point.EndCount;
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BeginAddress = Address + 1;
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}
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}
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}
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FunctionSamples &
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CSProfileGenerator::getFunctionProfileForContext(StringRef ContextStr,
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bool WasLeafInlined) {
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auto Ret = ProfileMap.try_emplace(ContextStr, FunctionSamples());
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if (Ret.second) {
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// Make a copy of the underlying context string in string table
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// before StringRef wrapper is used for context.
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auto It = ContextStrings.insert(ContextStr.str());
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SampleContext FContext(*It.first, RawContext);
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if (WasLeafInlined)
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FContext.setAttribute(ContextWasInlined);
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FunctionSamples &FProfile = Ret.first->second;
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FProfile.setContext(FContext);
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FProfile.setName(FContext.getNameWithoutContext());
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}
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return Ret.first->second;
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}
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void CSProfileGenerator::generateProfile() {
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FunctionSamples::ProfileIsCS = true;
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for (const auto &BI : BinarySampleCounters) {
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ProfiledBinary *Binary = BI.first;
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for (const auto &CI : BI.second) {
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const StringBasedCtxKey *CtxKey =
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dyn_cast<StringBasedCtxKey>(CI.first.getPtr());
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StringRef ContextId(CtxKey->Context);
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// Get or create function profile for the range
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FunctionSamples &FunctionProfile =
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getFunctionProfileForContext(ContextId, CtxKey->WasLeafInlined);
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// Fill in function body samples
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populateFunctionBodySamples(FunctionProfile, CI.second.RangeCounter,
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Binary);
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// Fill in boundary sample counts as well as call site samples for calls
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populateFunctionBoundarySamples(ContextId, FunctionProfile,
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CI.second.BranchCounter, Binary);
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}
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}
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// Fill in call site value sample for inlined calls and also use context to
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// infer missing samples. Since we don't have call count for inlined
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// functions, we estimate it from inlinee's profile using the entry of the
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// body sample.
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populateInferredFunctionSamples();
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postProcessProfiles();
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}
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void CSProfileGenerator::updateBodySamplesforFunctionProfile(
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FunctionSamples &FunctionProfile, const FrameLocation &LeafLoc,
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uint64_t Count) {
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// Filter out invalid negative(int type) lineOffset
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if (LeafLoc.second.LineOffset & 0x80000000)
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return;
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// Use the maximum count of samples with same line location
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ErrorOr<uint64_t> R = FunctionProfile.findSamplesAt(
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LeafLoc.second.LineOffset, LeafLoc.second.Discriminator);
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uint64_t PreviousCount = R ? R.get() : 0;
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if (PreviousCount < Count) {
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FunctionProfile.addBodySamples(LeafLoc.second.LineOffset,
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LeafLoc.second.Discriminator,
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Count - PreviousCount);
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}
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}
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void CSProfileGenerator::populateFunctionBodySamples(
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FunctionSamples &FunctionProfile, const RangeSample &RangeCounter,
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ProfiledBinary *Binary) {
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// Compute disjoint ranges first, so we can use MAX
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// for calculating count for each location.
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RangeSample Ranges;
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findDisjointRanges(Ranges, RangeCounter);
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for (auto Range : Ranges) {
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uint64_t RangeBegin = Binary->offsetToVirtualAddr(Range.first.first);
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uint64_t RangeEnd = Binary->offsetToVirtualAddr(Range.first.second);
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uint64_t Count = Range.second;
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// Disjoint ranges have introduce zero-filled gap that
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// doesn't belong to current context, filter them out.
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if (Count == 0)
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continue;
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InstructionPointer IP(Binary, RangeBegin, true);
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// Disjoint ranges may have range in the middle of two instr,
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// e.g. If Instr1 at Addr1, and Instr2 at Addr2, disjoint range
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// can be Addr1+1 to Addr2-1. We should ignore such range.
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if (IP.Address > RangeEnd)
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continue;
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while (IP.Address <= RangeEnd) {
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uint64_t Offset = Binary->virtualAddrToOffset(IP.Address);
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auto LeafLoc = Binary->getInlineLeafFrameLoc(Offset);
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if (LeafLoc.hasValue()) {
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// Recording body sample for this specific context
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updateBodySamplesforFunctionProfile(FunctionProfile, *LeafLoc, Count);
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}
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// Accumulate total sample count even it's a line with invalid debug info
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FunctionProfile.addTotalSamples(Count);
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// Move to next IP within the range
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IP.advance();
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}
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}
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}
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void CSProfileGenerator::populateFunctionBoundarySamples(
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StringRef ContextId, FunctionSamples &FunctionProfile,
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const BranchSample &BranchCounters, ProfiledBinary *Binary) {
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for (auto Entry : BranchCounters) {
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uint64_t SourceOffset = Entry.first.first;
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uint64_t TargetOffset = Entry.first.second;
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uint64_t Count = Entry.second;
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// Get the callee name by branch target if it's a call branch
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StringRef CalleeName = FunctionSamples::getCanonicalFnName(
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Binary->getFuncFromStartOffset(TargetOffset));
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if (CalleeName.size() == 0)
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continue;
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// Record called target sample and its count
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auto LeafLoc = Binary->getInlineLeafFrameLoc(SourceOffset);
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if (!LeafLoc.hasValue())
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continue;
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FunctionProfile.addCalledTargetSamples(LeafLoc->second.LineOffset,
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LeafLoc->second.Discriminator,
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CalleeName, Count);
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// Record head sample for called target(callee)
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std::ostringstream OCalleeCtxStr;
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if (ContextId.find(" @ ") != StringRef::npos) {
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OCalleeCtxStr << ContextId.rsplit(" @ ").first.str();
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OCalleeCtxStr << " @ ";
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}
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OCalleeCtxStr << getCallSite(*LeafLoc) << " @ " << CalleeName.str();
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FunctionSamples &CalleeProfile =
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getFunctionProfileForContext(OCalleeCtxStr.str());
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assert(Count != 0 && "Unexpected zero weight branch");
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CalleeProfile.addHeadSamples(Count);
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}
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}
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static FrameLocation getCallerContext(StringRef CalleeContext,
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StringRef &CallerNameWithContext) {
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StringRef CallerContext = CalleeContext.rsplit(" @ ").first;
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CallerNameWithContext = CallerContext.rsplit(':').first;
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auto ContextSplit = CallerContext.rsplit(" @ ");
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StringRef CallerFrameStr = ContextSplit.second.size() == 0
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? ContextSplit.first
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: ContextSplit.second;
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FrameLocation LeafFrameLoc = {"", {0, 0}};
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StringRef Funcname;
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SampleContext::decodeContextString(CallerFrameStr, Funcname,
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LeafFrameLoc.second);
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LeafFrameLoc.first = Funcname.str();
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return LeafFrameLoc;
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}
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void CSProfileGenerator::populateInferredFunctionSamples() {
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for (const auto &Item : ProfileMap) {
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const StringRef CalleeContext = Item.first();
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const FunctionSamples &CalleeProfile = Item.second;
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// If we already have head sample counts, we must have value profile
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// for call sites added already. Skip to avoid double counting.
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if (CalleeProfile.getHeadSamples())
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continue;
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// If we don't have context, nothing to do for caller's call site.
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// This could happen for entry point function.
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if (CalleeContext.find(" @ ") == StringRef::npos)
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continue;
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// Infer Caller's frame loc and context ID through string splitting
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StringRef CallerContextId;
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FrameLocation &&CallerLeafFrameLoc =
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getCallerContext(CalleeContext, CallerContextId);
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// It's possible that we haven't seen any sample directly in the caller,
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// in which case CallerProfile will not exist. But we can't modify
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// ProfileMap while iterating it.
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// TODO: created function profile for those callers too
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if (ProfileMap.find(CallerContextId) == ProfileMap.end())
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continue;
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FunctionSamples &CallerProfile = ProfileMap[CallerContextId];
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// Since we don't have call count for inlined functions, we
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// estimate it from inlinee's profile using entry body sample.
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uint64_t EstimatedCallCount = CalleeProfile.getEntrySamples();
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// If we don't have samples with location, use 1 to indicate live.
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if (!EstimatedCallCount && !CalleeProfile.getBodySamples().size())
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EstimatedCallCount = 1;
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CallerProfile.addCalledTargetSamples(
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CallerLeafFrameLoc.second.LineOffset,
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CallerLeafFrameLoc.second.Discriminator,
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CalleeProfile.getContext().getNameWithoutContext(), EstimatedCallCount);
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CallerProfile.addBodySamples(CallerLeafFrameLoc.second.LineOffset,
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CallerLeafFrameLoc.second.Discriminator,
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EstimatedCallCount);
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CallerProfile.addTotalSamples(EstimatedCallCount);
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}
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}
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void CSProfileGenerator::postProcessProfiles() {
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// Compute hot/cold threshold based on profile. This will be used for cold
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// context profile merging/trimming.
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computeSummaryAndThreshold();
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// Run global pre-inliner to adjust/merge context profile based on estimated
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// inline decisions.
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CSPreInliner(ProfileMap, HotCountThreshold, ColdCountThreshold).run();
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// Trim and merge cold context profile using cold threshold above;
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SampleContextTrimmer(ProfileMap)
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.trimAndMergeColdContextProfiles(
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ColdCountThreshold, CSProfTrimColdContext, CSProfMergeColdContext,
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CSProfColdContextFrameDepth);
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}
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void CSProfileGenerator::computeSummaryAndThreshold() {
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// Update the default value of cold cutoff for llvm-profgen.
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// Do it here because we don't want to change the global default,
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// which would lead CS profile size too large.
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if (!ProfileSummaryCutoffCold.getNumOccurrences())
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ProfileSummaryCutoffCold = 999000;
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SampleProfileSummaryBuilder Builder(ProfileSummaryBuilder::DefaultCutoffs);
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auto Summary = Builder.computeSummaryForProfiles(ProfileMap);
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HotCountThreshold = ProfileSummaryBuilder::getHotCountThreshold(
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(Summary->getDetailedSummary()));
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ColdCountThreshold = ProfileSummaryBuilder::getColdCountThreshold(
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(Summary->getDetailedSummary()));
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}
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void CSProfileGenerator::write(std::unique_ptr<SampleProfileWriter> Writer,
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StringMap<FunctionSamples> &ProfileMap) {
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if (std::error_code EC = Writer->write(ProfileMap))
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exitWithError(std::move(EC));
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}
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// Helper function to extract context prefix string stack
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// Extract context stack for reusing, leaf context stack will
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// be added compressed while looking up function profile
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static void
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extractPrefixContextStack(SmallVectorImpl<std::string> &ContextStrStack,
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const SmallVectorImpl<const PseudoProbe *> &Probes,
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ProfiledBinary *Binary) {
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for (const auto *P : Probes) {
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Binary->getInlineContextForProbe(P, ContextStrStack, true);
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}
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}
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void PseudoProbeCSProfileGenerator::generateProfile() {
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// Enable pseudo probe functionalities in SampleProf
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FunctionSamples::ProfileIsProbeBased = true;
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FunctionSamples::ProfileIsCS = true;
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for (const auto &BI : BinarySampleCounters) {
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ProfiledBinary *Binary = BI.first;
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for (const auto &CI : BI.second) {
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const ProbeBasedCtxKey *CtxKey =
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dyn_cast<ProbeBasedCtxKey>(CI.first.getPtr());
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SmallVector<std::string, 16> ContextStrStack;
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extractPrefixContextStack(ContextStrStack, CtxKey->Probes, Binary);
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// Fill in function body samples from probes, also infer caller's samples
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// from callee's probe
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populateBodySamplesWithProbes(CI.second.RangeCounter, ContextStrStack,
|
|
Binary);
|
|
// Fill in boundary samples for a call probe
|
|
populateBoundarySamplesWithProbes(CI.second.BranchCounter,
|
|
ContextStrStack, Binary);
|
|
}
|
|
}
|
|
|
|
postProcessProfiles();
|
|
}
|
|
|
|
void PseudoProbeCSProfileGenerator::extractProbesFromRange(
|
|
const RangeSample &RangeCounter, ProbeCounterMap &ProbeCounter,
|
|
ProfiledBinary *Binary) {
|
|
RangeSample Ranges;
|
|
findDisjointRanges(Ranges, RangeCounter);
|
|
for (const auto &Range : Ranges) {
|
|
uint64_t RangeBegin = Binary->offsetToVirtualAddr(Range.first.first);
|
|
uint64_t RangeEnd = Binary->offsetToVirtualAddr(Range.first.second);
|
|
uint64_t Count = Range.second;
|
|
// Disjoint ranges have introduce zero-filled gap that
|
|
// doesn't belong to current context, filter them out.
|
|
if (Count == 0)
|
|
continue;
|
|
|
|
InstructionPointer IP(Binary, RangeBegin, true);
|
|
|
|
// Disjoint ranges may have range in the middle of two instr,
|
|
// e.g. If Instr1 at Addr1, and Instr2 at Addr2, disjoint range
|
|
// can be Addr1+1 to Addr2-1. We should ignore such range.
|
|
if (IP.Address > RangeEnd)
|
|
continue;
|
|
|
|
while (IP.Address <= RangeEnd) {
|
|
const AddressProbesMap &Address2ProbesMap =
|
|
Binary->getAddress2ProbesMap();
|
|
auto It = Address2ProbesMap.find(IP.Address);
|
|
if (It != Address2ProbesMap.end()) {
|
|
for (const auto &Probe : It->second) {
|
|
if (!Probe.isBlock())
|
|
continue;
|
|
ProbeCounter[&Probe] += Count;
|
|
}
|
|
}
|
|
|
|
IP.advance();
|
|
}
|
|
}
|
|
}
|
|
|
|
void PseudoProbeCSProfileGenerator::populateBodySamplesWithProbes(
|
|
const RangeSample &RangeCounter,
|
|
SmallVectorImpl<std::string> &ContextStrStack, ProfiledBinary *Binary) {
|
|
ProbeCounterMap ProbeCounter;
|
|
// Extract the top frame probes by looking up each address among the range in
|
|
// the Address2ProbeMap
|
|
extractProbesFromRange(RangeCounter, ProbeCounter, Binary);
|
|
std::unordered_map<PseudoProbeInlineTree *, FunctionSamples *> FrameSamples;
|
|
for (auto PI : ProbeCounter) {
|
|
const PseudoProbe *Probe = PI.first;
|
|
uint64_t Count = PI.second;
|
|
// Ignore dangling probes since they will be reported later if needed.
|
|
if (Probe->isDangling())
|
|
continue;
|
|
FunctionSamples &FunctionProfile =
|
|
getFunctionProfileForLeafProbe(ContextStrStack, Probe, Binary);
|
|
// Record the current frame and FunctionProfile whenever samples are
|
|
// collected for non-danglie probes. This is for reporting all of the
|
|
// dangling probes of the frame later.
|
|
FrameSamples[Probe->getInlineTreeNode()] = &FunctionProfile;
|
|
FunctionProfile.addBodySamplesForProbe(Probe->Index, Count);
|
|
FunctionProfile.addTotalSamples(Count);
|
|
if (Probe->isEntry()) {
|
|
FunctionProfile.addHeadSamples(Count);
|
|
// Look up for the caller's function profile
|
|
const auto *InlinerDesc = Binary->getInlinerDescForProbe(Probe);
|
|
if (InlinerDesc != nullptr) {
|
|
// Since the context id will be compressed, we have to use callee's
|
|
// context id to infer caller's context id to ensure they share the
|
|
// same context prefix.
|
|
StringRef CalleeContextId =
|
|
FunctionProfile.getContext().getNameWithContext();
|
|
StringRef CallerContextId;
|
|
FrameLocation &&CallerLeafFrameLoc =
|
|
getCallerContext(CalleeContextId, CallerContextId);
|
|
uint64_t CallerIndex = CallerLeafFrameLoc.second.LineOffset;
|
|
assert(CallerIndex &&
|
|
"Inferred caller's location index shouldn't be zero!");
|
|
FunctionSamples &CallerProfile =
|
|
getFunctionProfileForContext(CallerContextId);
|
|
CallerProfile.setFunctionHash(InlinerDesc->FuncHash);
|
|
CallerProfile.addBodySamples(CallerIndex, 0, Count);
|
|
CallerProfile.addTotalSamples(Count);
|
|
CallerProfile.addCalledTargetSamples(
|
|
CallerIndex, 0,
|
|
FunctionProfile.getContext().getNameWithoutContext(), Count);
|
|
}
|
|
}
|
|
|
|
// Assign zero count for remaining probes without sample hits to
|
|
// differentiate from probes optimized away, of which the counts are unknown
|
|
// and will be inferred by the compiler.
|
|
for (auto &I : FrameSamples) {
|
|
auto *FunctionProfile = I.second;
|
|
for (auto *Probe : I.first->getProbes()) {
|
|
if (!Probe->isDangling())
|
|
FunctionProfile->addBodySamplesForProbe(Probe->Index, 0);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
void PseudoProbeCSProfileGenerator::populateBoundarySamplesWithProbes(
|
|
const BranchSample &BranchCounter,
|
|
SmallVectorImpl<std::string> &ContextStrStack, ProfiledBinary *Binary) {
|
|
for (auto BI : BranchCounter) {
|
|
uint64_t SourceOffset = BI.first.first;
|
|
uint64_t TargetOffset = BI.first.second;
|
|
uint64_t Count = BI.second;
|
|
uint64_t SourceAddress = Binary->offsetToVirtualAddr(SourceOffset);
|
|
const PseudoProbe *CallProbe = Binary->getCallProbeForAddr(SourceAddress);
|
|
if (CallProbe == nullptr)
|
|
continue;
|
|
FunctionSamples &FunctionProfile =
|
|
getFunctionProfileForLeafProbe(ContextStrStack, CallProbe, Binary);
|
|
FunctionProfile.addBodySamples(CallProbe->Index, 0, Count);
|
|
FunctionProfile.addTotalSamples(Count);
|
|
StringRef CalleeName = FunctionSamples::getCanonicalFnName(
|
|
Binary->getFuncFromStartOffset(TargetOffset));
|
|
if (CalleeName.size() == 0)
|
|
continue;
|
|
FunctionProfile.addCalledTargetSamples(CallProbe->Index, 0, CalleeName,
|
|
Count);
|
|
}
|
|
}
|
|
|
|
FunctionSamples &PseudoProbeCSProfileGenerator::getFunctionProfileForLeafProbe(
|
|
SmallVectorImpl<std::string> &ContextStrStack,
|
|
const PseudoProbeFuncDesc *LeafFuncDesc, bool WasLeafInlined) {
|
|
assert(ContextStrStack.size() && "Profile context must have the leaf frame");
|
|
// Compress the context string except for the leaf frame
|
|
std::string LeafFrame = ContextStrStack.back();
|
|
ContextStrStack.pop_back();
|
|
CSProfileGenerator::compressRecursionContext(ContextStrStack);
|
|
|
|
std::ostringstream OContextStr;
|
|
for (uint32_t I = 0; I < ContextStrStack.size(); I++) {
|
|
if (OContextStr.str().size())
|
|
OContextStr << " @ ";
|
|
OContextStr << ContextStrStack[I];
|
|
}
|
|
// For leaf inlined context with the top frame, we should strip off the top
|
|
// frame's probe id, like:
|
|
// Inlined stack: [foo:1, bar:2], the ContextId will be "foo:1 @ bar"
|
|
if (OContextStr.str().size())
|
|
OContextStr << " @ ";
|
|
OContextStr << StringRef(LeafFrame).split(":").first.str();
|
|
|
|
FunctionSamples &FunctionProile =
|
|
getFunctionProfileForContext(OContextStr.str(), WasLeafInlined);
|
|
FunctionProile.setFunctionHash(LeafFuncDesc->FuncHash);
|
|
return FunctionProile;
|
|
}
|
|
|
|
FunctionSamples &PseudoProbeCSProfileGenerator::getFunctionProfileForLeafProbe(
|
|
SmallVectorImpl<std::string> &ContextStrStack, const PseudoProbe *LeafProbe,
|
|
ProfiledBinary *Binary) {
|
|
// Explicitly copy the context for appending the leaf context
|
|
SmallVector<std::string, 16> ContextStrStackCopy(ContextStrStack.begin(),
|
|
ContextStrStack.end());
|
|
Binary->getInlineContextForProbe(LeafProbe, ContextStrStackCopy, true);
|
|
const auto *FuncDesc = Binary->getFuncDescForGUID(LeafProbe->GUID);
|
|
bool WasLeafInlined = LeafProbe->InlineTree->hasInlineSite();
|
|
return getFunctionProfileForLeafProbe(ContextStrStackCopy, FuncDesc,
|
|
WasLeafInlined);
|
|
}
|
|
|
|
} // end namespace sampleprof
|
|
} // end namespace llvm
|