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llvm-mirror/lib/CodeGen/MachineBranchProbabilityInfo.cpp

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4.2 KiB
C++

//===- MachineBranchProbabilityInfo.cpp - Machine Branch Probability Info -===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
//
// This analysis uses probability info stored in Machine Basic Blocks.
//
//===----------------------------------------------------------------------===//
#include "llvm/CodeGen/MachineBranchProbabilityInfo.h"
#include "llvm/CodeGen/MachineBasicBlock.h"
#include "llvm/IR/Instructions.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/raw_ostream.h"
using namespace llvm;
INITIALIZE_PASS_BEGIN(MachineBranchProbabilityInfo, "machine-branch-prob",
"Machine Branch Probability Analysis", false, true)
INITIALIZE_PASS_END(MachineBranchProbabilityInfo, "machine-branch-prob",
"Machine Branch Probability Analysis", false, true)
char MachineBranchProbabilityInfo::ID = 0;
void MachineBranchProbabilityInfo::anchor() { }
uint32_t MachineBranchProbabilityInfo::
getSumForBlock(const MachineBasicBlock *MBB, uint32_t &Scale) const {
// First we compute the sum with 64-bits of precision, ensuring that cannot
// overflow by bounding the number of weights considered. Hopefully no one
// actually needs 2^32 successors.
assert(MBB->succ_size() < UINT32_MAX);
uint64_t Sum = 0;
Scale = 1;
for (MachineBasicBlock::const_succ_iterator I = MBB->succ_begin(),
E = MBB->succ_end(); I != E; ++I) {
uint32_t Weight = getEdgeWeight(MBB, I);
Sum += Weight;
}
// If the computed sum fits in 32-bits, we're done.
if (Sum <= UINT32_MAX)
return Sum;
// Otherwise, compute the scale necessary to cause the weights to fit, and
// re-sum with that scale applied.
assert((Sum / UINT32_MAX) < UINT32_MAX);
Scale = (Sum / UINT32_MAX) + 1;
Sum = 0;
for (MachineBasicBlock::const_succ_iterator I = MBB->succ_begin(),
E = MBB->succ_end(); I != E; ++I) {
uint32_t Weight = getEdgeWeight(MBB, I);
Sum += Weight / Scale;
}
assert(Sum <= UINT32_MAX);
return Sum;
}
uint32_t MachineBranchProbabilityInfo::
getEdgeWeight(const MachineBasicBlock *Src,
MachineBasicBlock::const_succ_iterator Dst) const {
uint32_t Weight = Src->getSuccWeight(Dst);
if (!Weight)
return DEFAULT_WEIGHT;
return Weight;
}
uint32_t MachineBranchProbabilityInfo::
getEdgeWeight(const MachineBasicBlock *Src,
const MachineBasicBlock *Dst) const {
// This is a linear search. Try to use the const_succ_iterator version when
// possible.
return getEdgeWeight(Src, std::find(Src->succ_begin(), Src->succ_end(), Dst));
}
bool
MachineBranchProbabilityInfo::isEdgeHot(const MachineBasicBlock *Src,
const MachineBasicBlock *Dst) const {
// Hot probability is at least 4/5 = 80%
// FIXME: Compare against a static "hot" BranchProbability.
return getEdgeProbability(Src, Dst) > BranchProbability(4, 5);
}
MachineBasicBlock *
MachineBranchProbabilityInfo::getHotSucc(MachineBasicBlock *MBB) const {
uint32_t MaxWeight = 0;
MachineBasicBlock *MaxSucc = nullptr;
for (MachineBasicBlock::const_succ_iterator I = MBB->succ_begin(),
E = MBB->succ_end(); I != E; ++I) {
uint32_t Weight = getEdgeWeight(MBB, I);
if (Weight > MaxWeight) {
MaxWeight = Weight;
MaxSucc = *I;
}
}
if (getEdgeProbability(MBB, MaxSucc) >= BranchProbability(4, 5))
return MaxSucc;
return nullptr;
}
BranchProbability MachineBranchProbabilityInfo::getEdgeProbability(
const MachineBasicBlock *Src, const MachineBasicBlock *Dst) const {
uint32_t Scale = 1;
uint32_t D = getSumForBlock(Src, Scale);
uint32_t N = getEdgeWeight(Src, Dst) / Scale;
return BranchProbability(N, D);
}
raw_ostream &MachineBranchProbabilityInfo::printEdgeProbability(
raw_ostream &OS, const MachineBasicBlock *Src,
const MachineBasicBlock *Dst) const {
const BranchProbability Prob = getEdgeProbability(Src, Dst);
OS << "edge MBB#" << Src->getNumber() << " -> MBB#" << Dst->getNumber()
<< " probability is " << Prob
<< (isEdgeHot(Src, Dst) ? " [HOT edge]\n" : "\n");
return OS;
}