
This change enables llvm-profgen to use accurate context-sensitive post-optimization function byte size as a cost proxy to drive global preinline decisions. To do this, BinarySizeContextTracker is introduced to track function byte size under different inline context during disassembling. In preinliner, we can not query context byte size under switch `context-cost-for-preinliner`. The tracker uses a reverse trie to keep size of functions under different context (callee as parent, caller as child), and it can give best/longest possible matching context size for given input context. The new size cost is off by default. There're a few TODOs that needs to addressed: 1) avoid dangling string from `Offset2LocStackMap`, which will be addressed in split context work; 2) using inlinee's entry probe to make sure we have correct zero size for inlinee that's completely optimized away after inlining. Some tuning is also needed. Differential Revision: https://reviews.llvm.org/D108180
246 lines
9.5 KiB
C++
246 lines
9.5 KiB
C++
//===-- CSPreInliner.cpp - Profile guided preinliner -------------- 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 "CSPreInliner.h"
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#include "ProfiledBinary.h"
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#include "llvm/ADT/SCCIterator.h"
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#include <cstdint>
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#include <queue>
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#define DEBUG_TYPE "cs-preinliner"
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using namespace llvm;
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using namespace sampleprof;
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// The switches specify inline thresholds used in SampleProfileLoader inlining.
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// TODO: the actual threshold to be tuned here because the size here is based
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// on machine code not LLVM IR.
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extern cl::opt<int> SampleHotCallSiteThreshold;
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extern cl::opt<int> SampleColdCallSiteThreshold;
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extern cl::opt<int> ProfileInlineGrowthLimit;
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extern cl::opt<int> ProfileInlineLimitMin;
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extern cl::opt<int> ProfileInlineLimitMax;
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cl::opt<bool> EnableCSPreInliner(
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"csspgo-preinliner", cl::Hidden, cl::init(false),
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cl::desc("Run a global pre-inliner to merge context profile based on "
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"estimated global top-down inline decisions"));
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cl::opt<bool> UseContextCostForPreInliner(
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"use-context-cost-for-preinliner", cl::Hidden, cl::init(false),
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cl::desc("Use context-sensitive byte size cost for preinliner decisions"));
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static cl::opt<bool> SamplePreInlineReplay(
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"csspgo-replay-preinline", cl::Hidden, cl::init(false),
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cl::desc(
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"Replay previous inlining and adjust context profile accordingly"));
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CSPreInliner::CSPreInliner(StringMap<FunctionSamples> &Profiles,
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ProfiledBinary &Binary, uint64_t HotThreshold,
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uint64_t ColdThreshold)
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: UseContextCost(UseContextCostForPreInliner), ContextTracker(Profiles),
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ProfileMap(Profiles), Binary(Binary), HotCountThreshold(HotThreshold),
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ColdCountThreshold(ColdThreshold) {}
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std::vector<StringRef> CSPreInliner::buildTopDownOrder() {
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std::vector<StringRef> Order;
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ProfiledCallGraph ProfiledCG(ContextTracker);
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// Now that we have a profiled call graph, construct top-down order
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// by building up SCC and reversing SCC order.
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scc_iterator<ProfiledCallGraph *> I = scc_begin(&ProfiledCG);
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while (!I.isAtEnd()) {
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for (ProfiledCallGraphNode *Node : *I) {
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if (Node != ProfiledCG.getEntryNode())
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Order.push_back(Node->Name);
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}
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++I;
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}
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std::reverse(Order.begin(), Order.end());
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return Order;
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}
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bool CSPreInliner::getInlineCandidates(ProfiledCandidateQueue &CQueue,
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const FunctionSamples *CallerSamples) {
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assert(CallerSamples && "Expect non-null caller samples");
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// Ideally we want to consider everything a function calls, but as far as
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// context profile is concerned, only those frames that are children of
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// current one in the trie is relavent. So we walk the trie instead of call
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// targets from function profile.
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ContextTrieNode *CallerNode =
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ContextTracker.getContextFor(CallerSamples->getContext());
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bool HasNewCandidate = false;
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for (auto &Child : CallerNode->getAllChildContext()) {
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ContextTrieNode *CalleeNode = &Child.second;
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FunctionSamples *CalleeSamples = CalleeNode->getFunctionSamples();
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if (!CalleeSamples)
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continue;
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// Call site count is more reliable, so we look up the corresponding call
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// target profile in caller's context profile to retrieve call site count.
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uint64_t CalleeEntryCount = CalleeSamples->getEntrySamples();
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uint64_t CallsiteCount = 0;
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LineLocation Callsite = CalleeNode->getCallSiteLoc();
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if (auto CallTargets = CallerSamples->findCallTargetMapAt(Callsite)) {
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SampleRecord::CallTargetMap &TargetCounts = CallTargets.get();
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auto It = TargetCounts.find(CalleeSamples->getName());
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if (It != TargetCounts.end())
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CallsiteCount = It->second;
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}
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// TODO: call site and callee entry count should be mostly consistent, add
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// check for that.
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HasNewCandidate = true;
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uint32_t CalleeSize = getFuncSize(*CalleeSamples);
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CQueue.emplace(CalleeSamples, std::max(CallsiteCount, CalleeEntryCount),
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CalleeSize);
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}
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return HasNewCandidate;
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}
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uint32_t CSPreInliner::getFuncSize(const FunctionSamples &FSamples) {
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if (UseContextCost) {
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return Binary.getFuncSizeForContext(FSamples.getContext());
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}
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return FSamples.getBodySamples().size();
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}
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bool CSPreInliner::shouldInline(ProfiledInlineCandidate &Candidate) {
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// If replay inline is requested, simply follow the inline decision of the
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// profiled binary.
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if (SamplePreInlineReplay)
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return Candidate.CalleeSamples->getContext().hasAttribute(
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ContextWasInlined);
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// Adjust threshold based on call site hotness, only do this for callsite
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// prioritized inliner because otherwise cost-benefit check is done earlier.
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unsigned int SampleThreshold = SampleColdCallSiteThreshold;
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if (Candidate.CallsiteCount > HotCountThreshold)
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SampleThreshold = SampleHotCallSiteThreshold;
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// TODO: for small cold functions, we may inlined them and we need to keep
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// context profile accordingly.
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if (Candidate.CallsiteCount < ColdCountThreshold)
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SampleThreshold = SampleColdCallSiteThreshold;
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return (Candidate.SizeCost < SampleThreshold);
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}
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void CSPreInliner::processFunction(const StringRef Name) {
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FunctionSamples *FSamples = ContextTracker.getBaseSamplesFor(Name);
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if (!FSamples)
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return;
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unsigned FuncSize = getFuncSize(*FSamples);
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unsigned FuncFinalSize = FuncSize;
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unsigned SizeLimit = FuncSize * ProfileInlineGrowthLimit;
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SizeLimit = std::min(SizeLimit, (unsigned)ProfileInlineLimitMax);
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SizeLimit = std::max(SizeLimit, (unsigned)ProfileInlineLimitMin);
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LLVM_DEBUG(dbgs() << "Process " << Name
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<< " for context-sensitive pre-inlining (pre-inline size: "
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<< FuncSize << ", size limit: " << SizeLimit << ")\n");
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ProfiledCandidateQueue CQueue;
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getInlineCandidates(CQueue, FSamples);
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while (!CQueue.empty() && FuncFinalSize < SizeLimit) {
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ProfiledInlineCandidate Candidate = CQueue.top();
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CQueue.pop();
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bool ShouldInline = false;
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if ((ShouldInline = shouldInline(Candidate))) {
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// We mark context as inlined as the corresponding context profile
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// won't be merged into that function's base profile.
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ContextTracker.markContextSamplesInlined(Candidate.CalleeSamples);
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Candidate.CalleeSamples->getContext().setAttribute(
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ContextShouldBeInlined);
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FuncFinalSize += Candidate.SizeCost;
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getInlineCandidates(CQueue, Candidate.CalleeSamples);
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}
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LLVM_DEBUG(dbgs() << (ShouldInline ? " Inlined" : " Outlined")
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<< " context profile for: "
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<< Candidate.CalleeSamples->getNameWithContext()
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<< " (callee size: " << Candidate.SizeCost
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<< ", call count:" << Candidate.CallsiteCount << ")\n");
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}
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LLVM_DEBUG({
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if (!CQueue.empty())
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dbgs() << " Inline candidates ignored due to size limit (inliner "
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"original size: "
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<< FuncSize << ", inliner final size: " << FuncFinalSize
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<< ", size limit: " << SizeLimit << ")\n";
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while (!CQueue.empty()) {
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ProfiledInlineCandidate Candidate = CQueue.top();
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CQueue.pop();
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bool WasInlined =
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Candidate.CalleeSamples->getContext().hasAttribute(ContextWasInlined);
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dbgs() << " " << Candidate.CalleeSamples->getNameWithContext()
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<< " (candidate size:" << Candidate.SizeCost
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<< ", call count: " << Candidate.CallsiteCount << ", previously "
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<< (WasInlined ? "inlined)\n" : "not inlined)\n");
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}
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});
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}
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void CSPreInliner::run() {
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#ifndef NDEBUG
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auto printProfileNames = [](StringMap<FunctionSamples> &Profiles,
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bool IsInput) {
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dbgs() << (IsInput ? "Input" : "Output") << " context-sensitive profiles ("
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<< Profiles.size() << " total):\n";
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for (auto &It : Profiles) {
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const FunctionSamples &Samples = It.second;
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dbgs() << " [" << Samples.getNameWithContext() << "] "
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<< Samples.getTotalSamples() << ":" << Samples.getHeadSamples()
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<< "\n";
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}
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};
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#endif
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LLVM_DEBUG(printProfileNames(ProfileMap, true));
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// Execute global pre-inliner to estimate a global top-down inline
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// decision and merge profiles accordingly. This helps with profile
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// merge for ThinLTO otherwise we won't be able to merge profiles back
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// to base profile across module/thin-backend boundaries.
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// It also helps better compress context profile to control profile
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// size, as we now only need context profile for functions going to
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// be inlined.
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for (StringRef FuncName : buildTopDownOrder()) {
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processFunction(FuncName);
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}
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// Not inlined context profiles are merged into its base, so we can
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// trim out such profiles from the output.
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std::vector<StringRef> ProfilesToBeRemoved;
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for (auto &It : ProfileMap) {
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SampleContext Context = It.second.getContext();
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if (!Context.isBaseContext() && !Context.hasState(InlinedContext)) {
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assert(Context.hasState(MergedContext) &&
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"Not inlined context profile should be merged already");
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ProfilesToBeRemoved.push_back(It.first());
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}
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}
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for (StringRef ContextName : ProfilesToBeRemoved) {
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ProfileMap.erase(ContextName);
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}
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// Make sure ProfileMap's key is consistent with FunctionSamples' name.
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SampleContextTrimmer(ProfileMap).canonicalizeContextProfiles();
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LLVM_DEBUG(printProfileNames(ProfileMap, false));
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}
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