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https://github.com/c64scene-ar/llvm-6502.git
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990ca5517f
The getSumForBlock function was quadratic in the number of successors because getSuccWeight would perform a linear search for an already known iterator. This patch was originally committed as r161460, but reverted again because of assertion failures. Now that duplicate Machine CFG edges have been eliminated, this works properly. git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@162233 91177308-0d34-0410-b5e6-96231b3b80d8
127 lines
4.2 KiB
C++
127 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/Instructions.h"
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#include "llvm/CodeGen/MachineBranchProbabilityInfo.h"
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#include "llvm/CodeGen/MachineBasicBlock.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 MachineBranchProbabilityInfo::
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getSumForBlock(const MachineBasicBlock *MBB, uint32_t &Scale) const {
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// First we compute the sum with 64-bits of precision, ensuring that cannot
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// overflow by bounding the number of weights considered. Hopefully no one
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// actually needs 2^32 successors.
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assert(MBB->succ_size() < UINT32_MAX);
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uint64_t Sum = 0;
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Scale = 1;
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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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Sum += Weight;
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}
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// If the computed sum fits in 32-bits, we're done.
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if (Sum <= UINT32_MAX)
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return Sum;
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// Otherwise, compute the scale necessary to cause the weights to fit, and
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// re-sum with that scale applied.
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assert((Sum / UINT32_MAX) < UINT32_MAX);
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Scale = (Sum / UINT32_MAX) + 1;
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Sum = 0;
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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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Sum += Weight / Scale;
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}
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assert(Sum <= UINT32_MAX);
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return Sum;
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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 MachineBranchProbabilityInfo::isEdgeHot(MachineBasicBlock *Src,
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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 = 0;
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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 0;
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}
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BranchProbability
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MachineBranchProbabilityInfo::getEdgeProbability(MachineBasicBlock *Src,
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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::
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printEdgeProbability(raw_ostream &OS, MachineBasicBlock *Src,
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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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