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1. Create a utility function normalizeEdgeWeights() in MachineBranchProbabilityInfo that normalizes a list of edge weights so that the sum of then can fit in uint32_t. 2. Provide an interface in MachineBasicBlock to normalize its successors' weights. 3. Add a flag in MachineBasicBlock that tracks whether its successors' weights are normalized. 4. Provide an overload of getSumForBlock that accepts a non-const pointer to a MBB so that it can force normalizing this MBB's successors' weights. 5. Update several uses of getSumForBlock() by eliminating the once needed weight scale. Differential Revision: http://reviews.llvm.org/D11442 llvm-svn: 244154
126 lines
4.2 KiB
C++
126 lines
4.2 KiB
C++
//===- MachineBranchProbabilityInfo.cpp - Machine Branch Probability Info -===//
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//
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// The LLVM Compiler Infrastructure
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//
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// This file is distributed under the University of Illinois Open Source
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// License. See LICENSE.TXT for details.
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//
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//===----------------------------------------------------------------------===//
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//
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// This analysis uses probability info stored in Machine Basic Blocks.
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//
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//===----------------------------------------------------------------------===//
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#include "llvm/CodeGen/MachineBranchProbabilityInfo.h"
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#include "llvm/CodeGen/MachineBasicBlock.h"
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#include "llvm/IR/Instructions.h"
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#include "llvm/Support/Debug.h"
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#include "llvm/Support/raw_ostream.h"
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using namespace llvm;
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INITIALIZE_PASS_BEGIN(MachineBranchProbabilityInfo, "machine-branch-prob",
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"Machine Branch Probability Analysis", false, true)
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INITIALIZE_PASS_END(MachineBranchProbabilityInfo, "machine-branch-prob",
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"Machine Branch Probability Analysis", false, true)
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char MachineBranchProbabilityInfo::ID = 0;
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void MachineBranchProbabilityInfo::anchor() { }
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uint32_t
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MachineBranchProbabilityInfo::getSumForBlock(MachineBasicBlock *MBB) const {
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// Normalize the weights of MBB's all successors so that the sum is guaranteed
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// to be no greater than UINT32_MAX.
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MBB->normalizeSuccWeights();
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SmallVector<uint32_t, 8> Weights;
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for (MachineBasicBlock::const_succ_iterator I = MBB->succ_begin(),
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E = MBB->succ_end();
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I != E; ++I)
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Weights.push_back(getEdgeWeight(MBB, I));
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return std::accumulate(Weights.begin(), Weights.end(), 0u);
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}
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uint32_t
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MachineBranchProbabilityInfo::getSumForBlock(const MachineBasicBlock *MBB,
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uint32_t &Scale) const {
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SmallVector<uint32_t, 8> Weights;
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for (MachineBasicBlock::const_succ_iterator I = MBB->succ_begin(),
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E = MBB->succ_end();
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I != E; ++I)
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Weights.push_back(getEdgeWeight(MBB, I));
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if (MBB->areSuccWeightsNormalized())
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Scale = 1;
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else
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Scale = MachineBranchProbabilityInfo::normalizeEdgeWeights(Weights);
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return std::accumulate(Weights.begin(), Weights.end(), 0u);
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}
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uint32_t MachineBranchProbabilityInfo::
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getEdgeWeight(const MachineBasicBlock *Src,
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MachineBasicBlock::const_succ_iterator Dst) const {
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uint32_t Weight = Src->getSuccWeight(Dst);
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if (!Weight)
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return DEFAULT_WEIGHT;
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return Weight;
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}
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uint32_t MachineBranchProbabilityInfo::
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getEdgeWeight(const MachineBasicBlock *Src,
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const MachineBasicBlock *Dst) const {
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// This is a linear search. Try to use the const_succ_iterator version when
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// possible.
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return getEdgeWeight(Src, std::find(Src->succ_begin(), Src->succ_end(), Dst));
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}
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bool
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MachineBranchProbabilityInfo::isEdgeHot(const MachineBasicBlock *Src,
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const MachineBasicBlock *Dst) const {
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// Hot probability is at least 4/5 = 80%
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// FIXME: Compare against a static "hot" BranchProbability.
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return getEdgeProbability(Src, Dst) > BranchProbability(4, 5);
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}
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MachineBasicBlock *
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MachineBranchProbabilityInfo::getHotSucc(MachineBasicBlock *MBB) const {
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uint32_t MaxWeight = 0;
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MachineBasicBlock *MaxSucc = nullptr;
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for (MachineBasicBlock::const_succ_iterator I = MBB->succ_begin(),
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E = MBB->succ_end(); I != E; ++I) {
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uint32_t Weight = getEdgeWeight(MBB, I);
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if (Weight > MaxWeight) {
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MaxWeight = Weight;
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MaxSucc = *I;
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}
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}
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if (getEdgeProbability(MBB, MaxSucc) >= BranchProbability(4, 5))
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return MaxSucc;
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return nullptr;
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}
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BranchProbability MachineBranchProbabilityInfo::getEdgeProbability(
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const MachineBasicBlock *Src, const MachineBasicBlock *Dst) const {
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uint32_t Scale = 1;
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uint32_t D = getSumForBlock(Src, Scale);
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uint32_t N = getEdgeWeight(Src, Dst) / Scale;
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return BranchProbability(N, D);
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}
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raw_ostream &MachineBranchProbabilityInfo::printEdgeProbability(
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raw_ostream &OS, const MachineBasicBlock *Src,
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const MachineBasicBlock *Dst) const {
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const BranchProbability Prob = getEdgeProbability(Src, Dst);
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OS << "edge MBB#" << Src->getNumber() << " -> MBB#" << Dst->getNumber()
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<< " probability is " << Prob
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<< (isEdgeHot(Src, Dst) ? " [HOT edge]\n" : "\n");
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return OS;
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}
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