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Current approach doesn't work well in cases when multiple paths are predicted to be "cold". By "cold" paths I mean those containing "unreachable" instruction, call marked with 'cold' attribute and 'unwind' handler of 'invoke' instruction. The issue is that heuristics are applied one by one until the first match and essentially ignores relative hotness/coldness of other paths. New approach unifies processing of "cold" paths by assigning predefined absolute weight to each block estimated to be "cold". Then we propagate these weights up/down IR similarly to existing approach. And finally set up edge probabilities based on estimated block weights. One important difference is how we propagate weight up. Existing approach propagates the same weight to all blocks that are post-dominated by a block with some "known" weight. This is useless at least because it always gives 50\50 distribution which is assumed by default anyway. Worse, it causes the algorithm to skip further heuristics and can miss setting more accurate probability. New algorithm propagates the weight up only to the blocks that dominates and post-dominated by a block with some "known" weight. In other words, those blocks that are either always executed or not executed together. In addition new approach processes loops in an uniform way as well. Essentially loop exit edges are estimated as "cold" paths relative to back edges and should be considered uniformly with other coldness/hotness markers. Reviewed By: yrouban Differential Revision: https://reviews.llvm.org/D79485
124 lines
4.2 KiB
C++
124 lines
4.2 KiB
C++
//===- LazyBranchProbabilityInfo.h - Lazy Branch Probability ----*- 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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//
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// This is an alternative analysis pass to BranchProbabilityInfoWrapperPass.
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// The difference is that with this pass the branch probabilities are not
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// computed when the analysis pass is executed but rather when the BPI results
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// is explicitly requested by the analysis client.
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//
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//===----------------------------------------------------------------------===//
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#ifndef LLVM_ANALYSIS_LAZYBRANCHPROBABILITYINFO_H
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#define LLVM_ANALYSIS_LAZYBRANCHPROBABILITYINFO_H
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#include "llvm/Analysis/BranchProbabilityInfo.h"
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#include "llvm/Pass.h"
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namespace llvm {
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class AnalysisUsage;
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class Function;
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class LoopInfo;
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class TargetLibraryInfo;
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/// This is an alternative analysis pass to
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/// BranchProbabilityInfoWrapperPass. The difference is that with this pass the
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/// branch probabilities are not computed when the analysis pass is executed but
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/// rather when the BPI results is explicitly requested by the analysis client.
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///
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/// There are some additional requirements for any client pass that wants to use
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/// the analysis:
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///
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/// 1. The pass needs to initialize dependent passes with:
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///
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/// INITIALIZE_PASS_DEPENDENCY(LazyBPIPass)
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///
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/// 2. Similarly, getAnalysisUsage should call:
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///
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/// LazyBranchProbabilityInfoPass::getLazyBPIAnalysisUsage(AU)
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///
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/// 3. The computed BPI should be requested with
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/// getAnalysis<LazyBranchProbabilityInfoPass>().getBPI() before LoopInfo
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/// could be invalidated for example by changing the CFG.
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///
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/// Note that it is expected that we wouldn't need this functionality for the
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/// new PM since with the new PM, analyses are executed on demand.
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class LazyBranchProbabilityInfoPass : public FunctionPass {
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/// Wraps a BPI to allow lazy computation of the branch probabilities.
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///
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/// A pass that only conditionally uses BPI can uncondtionally require the
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/// analysis without paying for the overhead if BPI doesn't end up being used.
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class LazyBranchProbabilityInfo {
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public:
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LazyBranchProbabilityInfo(const Function *F, const LoopInfo *LI,
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const TargetLibraryInfo *TLI)
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: Calculated(false), F(F), LI(LI), TLI(TLI) {}
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/// Retrieve the BPI with the branch probabilities computed.
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BranchProbabilityInfo &getCalculated() {
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if (!Calculated) {
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assert(F && LI && "call setAnalysis");
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BPI.calculate(*F, *LI, TLI, nullptr, nullptr);
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Calculated = true;
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}
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return BPI;
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}
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const BranchProbabilityInfo &getCalculated() const {
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return const_cast<LazyBranchProbabilityInfo *>(this)->getCalculated();
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}
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private:
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BranchProbabilityInfo BPI;
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bool Calculated;
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const Function *F;
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const LoopInfo *LI;
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const TargetLibraryInfo *TLI;
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};
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std::unique_ptr<LazyBranchProbabilityInfo> LBPI;
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public:
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static char ID;
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LazyBranchProbabilityInfoPass();
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/// Compute and return the branch probabilities.
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BranchProbabilityInfo &getBPI() { return LBPI->getCalculated(); }
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/// Compute and return the branch probabilities.
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const BranchProbabilityInfo &getBPI() const { return LBPI->getCalculated(); }
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void getAnalysisUsage(AnalysisUsage &AU) const override;
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/// Helper for client passes to set up the analysis usage on behalf of this
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/// pass.
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static void getLazyBPIAnalysisUsage(AnalysisUsage &AU);
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bool runOnFunction(Function &F) override;
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void releaseMemory() override;
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void print(raw_ostream &OS, const Module *M) const override;
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};
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/// Helper for client passes to initialize dependent passes for LBPI.
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void initializeLazyBPIPassPass(PassRegistry &Registry);
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/// Simple trait class that provides a mapping between BPI passes and the
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/// corresponding BPInfo.
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template <typename PassT> struct BPIPassTrait {
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static PassT &getBPI(PassT *P) { return *P; }
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};
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template <> struct BPIPassTrait<LazyBranchProbabilityInfoPass> {
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static BranchProbabilityInfo &getBPI(LazyBranchProbabilityInfoPass *P) {
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return P->getBPI();
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}
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};
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}
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#endif
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