Files
clang-p2996/llvm/tools/llvm-profgen/CSPreInliner.cpp
Hongtao Yu a4190037fa [CSSPGO][Preinliner] Use linear threshold to drive inline decision.
The per-callsite size threshold used today to drive preinline decision is based on hotness/coldness cutoff. The default setup is for callsites with a sample count above the hotness cutoff (99%), a 1500 size threshold is used. Any callsite below 99.99% coldness cutoff uses a zero threshold. This has a couple issues:

1. While both cutoffs and size thoresholds are configurable, different applications may need different setups, making a universal setup impractical.

2. The callsites between hotness cutoff and coldness cutoff are not considered as inline candidates, which could be a missing opportunity.

3. Hot callsites always use the same threshold. In reality we may want a bigger threshold for hotter callsites.

In this change we are introducing a linear threshold regardless of hot/cold cutoffs. Given a sample space, a threshold is computed for a callsite based on the position of that callsite sample in the whole space. With that we no longer need to define what's hot or cold. Callsites with different hotness will get a different threshold. This should overcome the above three issues.

I have seen good results with a universal default setup for two of our internal services.

For one service, 0.2% to 0.5% perf improvement over a baseline with a previous default setup, on-par code size.
For the second service, 0.5% to 0.8% perf improvement over a baseline with a previous default setup, 0.2% code size increase; on-par performance and code size with a baseline that is with a carefully tuned cutoff to cover enough hot functions.

Reviewed By: wenlei

Differential Revision: https://reviews.llvm.org/D125023
2022-05-08 22:07:58 -07:00

305 lines
12 KiB
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//===-- CSPreInliner.cpp - Profile guided preinliner -------------- C++ -*-===//
//
// 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
//
//===----------------------------------------------------------------------===//
#include "CSPreInliner.h"
#include "ProfiledBinary.h"
#include "llvm/ADT/SCCIterator.h"
#include "llvm/ADT/Statistic.h"
#include "llvm/DebugInfo/Symbolize/SymbolizableModule.h"
#include <cstdint>
#include <queue>
#define DEBUG_TYPE "cs-preinliner"
using namespace llvm;
using namespace sampleprof;
STATISTIC(PreInlNumCSInlined,
"Number of functions inlined with context sensitive profile");
STATISTIC(PreInlNumCSNotInlined,
"Number of functions not inlined with context sensitive profile");
STATISTIC(PreInlNumCSInlinedHitMinLimit,
"Number of functions with FDO inline stopped due to min size limit");
STATISTIC(PreInlNumCSInlinedHitMaxLimit,
"Number of functions with FDO inline stopped due to max size limit");
STATISTIC(
PreInlNumCSInlinedHitGrowthLimit,
"Number of functions with FDO inline stopped due to growth size limit");
// The switches specify inline thresholds used in SampleProfileLoader inlining.
// TODO: the actual threshold to be tuned here because the size here is based
// on machine code not LLVM IR.
extern cl::opt<int> SampleHotCallSiteThreshold;
extern cl::opt<int> SampleColdCallSiteThreshold;
extern cl::opt<int> ProfileInlineGrowthLimit;
extern cl::opt<int> ProfileInlineLimitMin;
extern cl::opt<int> ProfileInlineLimitMax;
extern cl::opt<bool> SortProfiledSCC;
cl::opt<bool> EnableCSPreInliner(
"csspgo-preinliner", cl::Hidden, cl::init(true),
cl::desc("Run a global pre-inliner to merge context profile based on "
"estimated global top-down inline decisions"));
cl::opt<bool> UseContextCostForPreInliner(
"use-context-cost-for-preinliner", cl::Hidden, cl::init(true),
cl::desc("Use context-sensitive byte size cost for preinliner decisions"));
static cl::opt<bool> SamplePreInlineReplay(
"csspgo-replay-preinline", cl::Hidden, cl::init(false),
cl::desc(
"Replay previous inlining and adjust context profile accordingly"));
CSPreInliner::CSPreInliner(SampleProfileMap &Profiles, ProfiledBinary &Binary,
ProfileSummary *Summary)
: UseContextCost(UseContextCostForPreInliner),
// TODO: Pass in a guid-to-name map in order for
// ContextTracker.getFuncNameFor to work, if `Profiles` can have md5 codes
// as their profile context.
ContextTracker(Profiles, nullptr), ProfileMap(Profiles), Binary(Binary),
Summary(Summary) {
// Set default preinliner hot/cold call site threshold tuned with CSSPGO.
// for good performance with reasonable profile size.
if (!SampleHotCallSiteThreshold.getNumOccurrences())
SampleHotCallSiteThreshold = 1500;
if (!SampleColdCallSiteThreshold.getNumOccurrences())
SampleColdCallSiteThreshold = 0;
}
std::vector<StringRef> CSPreInliner::buildTopDownOrder() {
std::vector<StringRef> Order;
ProfiledCallGraph ProfiledCG(ContextTracker);
// Now that we have a profiled call graph, construct top-down order
// by building up SCC and reversing SCC order.
scc_iterator<ProfiledCallGraph *> I = scc_begin(&ProfiledCG);
while (!I.isAtEnd()) {
auto Range = *I;
if (SortProfiledSCC) {
// Sort nodes in one SCC based on callsite hotness.
scc_member_iterator<ProfiledCallGraph *> SI(*I);
Range = *SI;
}
for (auto *Node : Range) {
if (Node != ProfiledCG.getEntryNode())
Order.push_back(Node->Name);
}
++I;
}
std::reverse(Order.begin(), Order.end());
return Order;
}
bool CSPreInliner::getInlineCandidates(ProfiledCandidateQueue &CQueue,
const FunctionSamples *CallerSamples) {
assert(CallerSamples && "Expect non-null caller samples");
// Ideally we want to consider everything a function calls, but as far as
// context profile is concerned, only those frames that are children of
// current one in the trie is relavent. So we walk the trie instead of call
// targets from function profile.
ContextTrieNode *CallerNode =
ContextTracker.getContextFor(CallerSamples->getContext());
bool HasNewCandidate = false;
for (auto &Child : CallerNode->getAllChildContext()) {
ContextTrieNode *CalleeNode = &Child.second;
FunctionSamples *CalleeSamples = CalleeNode->getFunctionSamples();
if (!CalleeSamples)
continue;
// Call site count is more reliable, so we look up the corresponding call
// target profile in caller's context profile to retrieve call site count.
uint64_t CalleeEntryCount = CalleeSamples->getEntrySamples();
uint64_t CallsiteCount = 0;
LineLocation Callsite = CalleeNode->getCallSiteLoc();
if (auto CallTargets = CallerSamples->findCallTargetMapAt(Callsite)) {
SampleRecord::CallTargetMap &TargetCounts = CallTargets.get();
auto It = TargetCounts.find(CalleeSamples->getName());
if (It != TargetCounts.end())
CallsiteCount = It->second;
}
// TODO: call site and callee entry count should be mostly consistent, add
// check for that.
HasNewCandidate = true;
uint32_t CalleeSize = getFuncSize(*CalleeSamples);
CQueue.emplace(CalleeSamples, std::max(CallsiteCount, CalleeEntryCount),
CalleeSize);
}
return HasNewCandidate;
}
uint32_t CSPreInliner::getFuncSize(const FunctionSamples &FSamples) {
if (UseContextCost) {
return Binary.getFuncSizeForContext(FSamples.getContext());
}
return FSamples.getBodySamples().size();
}
bool CSPreInliner::shouldInline(ProfiledInlineCandidate &Candidate) {
// If replay inline is requested, simply follow the inline decision of the
// profiled binary.
if (SamplePreInlineReplay)
return Candidate.CalleeSamples->getContext().hasAttribute(
ContextWasInlined);
unsigned int SampleThreshold = SampleColdCallSiteThreshold;
uint64_t ColdCountThreshold = ProfileSummaryBuilder::getColdCountThreshold(
(Summary->getDetailedSummary()));
if (Candidate.CallsiteCount <= ColdCountThreshold)
SampleThreshold = SampleColdCallSiteThreshold;
else {
// Linearly adjust threshold based on normalized hotness, i.e, a value in
// [0,1]. Use 10% cutoff instead of the max count as the normalization
// upperbound for stability.
double NormalizationUpperBound =
ProfileSummaryBuilder::getEntryForPercentile(
Summary->getDetailedSummary(), 100000 /* 10% */)
.MinCount;
double NormalizationLowerBound = ColdCountThreshold;
double NormalizedHotness =
(Candidate.CallsiteCount - NormalizationLowerBound) /
(NormalizationUpperBound - NormalizationLowerBound);
if (NormalizedHotness > 1.0)
NormalizedHotness = 1.0;
// Add 1 to to ensure hot callsites get a non-zero threshold, which could
// happen when SampleColdCallSiteThreshold is 0. This is when we do not
// want any inlining for cold callsites.
SampleThreshold = SampleHotCallSiteThreshold * NormalizedHotness * 100 +
SampleColdCallSiteThreshold + 1;
}
return (Candidate.SizeCost < SampleThreshold);
}
void CSPreInliner::processFunction(const StringRef Name) {
FunctionSamples *FSamples = ContextTracker.getBaseSamplesFor(Name);
if (!FSamples)
return;
unsigned FuncSize = getFuncSize(*FSamples);
unsigned FuncFinalSize = FuncSize;
unsigned SizeLimit = FuncSize * ProfileInlineGrowthLimit;
SizeLimit = std::min(SizeLimit, (unsigned)ProfileInlineLimitMax);
SizeLimit = std::max(SizeLimit, (unsigned)ProfileInlineLimitMin);
LLVM_DEBUG(dbgs() << "Process " << Name
<< " for context-sensitive pre-inlining (pre-inline size: "
<< FuncSize << ", size limit: " << SizeLimit << ")\n");
ProfiledCandidateQueue CQueue;
getInlineCandidates(CQueue, FSamples);
while (!CQueue.empty() && FuncFinalSize < SizeLimit) {
ProfiledInlineCandidate Candidate = CQueue.top();
CQueue.pop();
bool ShouldInline = false;
if ((ShouldInline = shouldInline(Candidate))) {
// We mark context as inlined as the corresponding context profile
// won't be merged into that function's base profile.
++PreInlNumCSInlined;
ContextTracker.markContextSamplesInlined(Candidate.CalleeSamples);
Candidate.CalleeSamples->getContext().setAttribute(
ContextShouldBeInlined);
FuncFinalSize += Candidate.SizeCost;
getInlineCandidates(CQueue, Candidate.CalleeSamples);
} else {
++PreInlNumCSNotInlined;
}
LLVM_DEBUG(dbgs() << (ShouldInline ? " Inlined" : " Outlined")
<< " context profile for: "
<< Candidate.CalleeSamples->getContext().toString()
<< " (callee size: " << Candidate.SizeCost
<< ", call count:" << Candidate.CallsiteCount << ")\n");
}
if (!CQueue.empty()) {
if (SizeLimit == (unsigned)ProfileInlineLimitMax)
++PreInlNumCSInlinedHitMaxLimit;
else if (SizeLimit == (unsigned)ProfileInlineLimitMin)
++PreInlNumCSInlinedHitMinLimit;
else
++PreInlNumCSInlinedHitGrowthLimit;
}
LLVM_DEBUG({
if (!CQueue.empty())
dbgs() << " Inline candidates ignored due to size limit (inliner "
"original size: "
<< FuncSize << ", inliner final size: " << FuncFinalSize
<< ", size limit: " << SizeLimit << ")\n";
while (!CQueue.empty()) {
ProfiledInlineCandidate Candidate = CQueue.top();
CQueue.pop();
bool WasInlined =
Candidate.CalleeSamples->getContext().hasAttribute(ContextWasInlined);
dbgs() << " " << Candidate.CalleeSamples->getContext().toString()
<< " (candidate size:" << Candidate.SizeCost
<< ", call count: " << Candidate.CallsiteCount << ", previously "
<< (WasInlined ? "inlined)\n" : "not inlined)\n");
}
});
}
void CSPreInliner::run() {
#ifndef NDEBUG
auto printProfileNames = [](SampleProfileMap &Profiles, bool IsInput) {
dbgs() << (IsInput ? "Input" : "Output") << " context-sensitive profiles ("
<< Profiles.size() << " total):\n";
for (auto &It : Profiles) {
const FunctionSamples &Samples = It.second;
dbgs() << " [" << Samples.getContext().toString() << "] "
<< Samples.getTotalSamples() << ":" << Samples.getHeadSamples()
<< "\n";
}
};
#endif
LLVM_DEBUG(printProfileNames(ProfileMap, true));
// Execute global pre-inliner to estimate a global top-down inline
// decision and merge profiles accordingly. This helps with profile
// merge for ThinLTO otherwise we won't be able to merge profiles back
// to base profile across module/thin-backend boundaries.
// It also helps better compress context profile to control profile
// size, as we now only need context profile for functions going to
// be inlined.
for (StringRef FuncName : buildTopDownOrder()) {
processFunction(FuncName);
}
// Not inlined context profiles are merged into its base, so we can
// trim out such profiles from the output.
std::vector<SampleContext> ProfilesToBeRemoved;
for (auto &It : ProfileMap) {
SampleContext &Context = It.second.getContext();
if (!Context.isBaseContext() && !Context.hasState(InlinedContext)) {
assert(Context.hasState(MergedContext) &&
"Not inlined context profile should be merged already");
ProfilesToBeRemoved.push_back(It.first);
}
}
for (auto &ContextName : ProfilesToBeRemoved) {
ProfileMap.erase(ContextName);
}
// Make sure ProfileMap's key is consistent with FunctionSamples' name.
SampleContextTrimmer(ProfileMap).canonicalizeContextProfiles();
FunctionSamples::ProfileIsPreInlined = true;
LLVM_DEBUG(printProfileNames(ProfileMap, false));
}