//===- 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(MachineBasicBlock *Src, 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 = 0; 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 0; } BranchProbability MachineBranchProbabilityInfo::getEdgeProbability(MachineBasicBlock *Src, 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, MachineBasicBlock *Src, 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; }