|  | //===- BranchProbabilityInfo.cpp - Branch Probability Analysis ------------===// | 
|  | // | 
|  | // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. | 
|  | // See https://llvm.org/LICENSE.txt for license information. | 
|  | // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception | 
|  | // | 
|  | //===----------------------------------------------------------------------===// | 
|  | // | 
|  | // Loops should be simplified before this analysis. | 
|  | // | 
|  | //===----------------------------------------------------------------------===// | 
|  |  | 
|  | #include "llvm/Analysis/BranchProbabilityInfo.h" | 
|  | #include "llvm/ADT/PostOrderIterator.h" | 
|  | #include "llvm/ADT/SCCIterator.h" | 
|  | #include "llvm/ADT/STLExtras.h" | 
|  | #include "llvm/ADT/SmallVector.h" | 
|  | #include "llvm/Analysis/ConstantFolding.h" | 
|  | #include "llvm/Analysis/LoopInfo.h" | 
|  | #include "llvm/Analysis/PostDominators.h" | 
|  | #include "llvm/Analysis/TargetLibraryInfo.h" | 
|  | #include "llvm/IR/Attributes.h" | 
|  | #include "llvm/IR/BasicBlock.h" | 
|  | #include "llvm/IR/CFG.h" | 
|  | #include "llvm/IR/Constants.h" | 
|  | #include "llvm/IR/Dominators.h" | 
|  | #include "llvm/IR/Function.h" | 
|  | #include "llvm/IR/InstrTypes.h" | 
|  | #include "llvm/IR/Instruction.h" | 
|  | #include "llvm/IR/Instructions.h" | 
|  | #include "llvm/IR/LLVMContext.h" | 
|  | #include "llvm/IR/Metadata.h" | 
|  | #include "llvm/IR/PassManager.h" | 
|  | #include "llvm/IR/ProfDataUtils.h" | 
|  | #include "llvm/IR/Type.h" | 
|  | #include "llvm/IR/Value.h" | 
|  | #include "llvm/InitializePasses.h" | 
|  | #include "llvm/Pass.h" | 
|  | #include "llvm/Support/BranchProbability.h" | 
|  | #include "llvm/Support/Casting.h" | 
|  | #include "llvm/Support/CommandLine.h" | 
|  | #include "llvm/Support/Debug.h" | 
|  | #include "llvm/Support/raw_ostream.h" | 
|  | #include <cassert> | 
|  | #include <cstdint> | 
|  | #include <iterator> | 
|  | #include <map> | 
|  | #include <utility> | 
|  |  | 
|  | using namespace llvm; | 
|  |  | 
|  | #define DEBUG_TYPE "branch-prob" | 
|  |  | 
|  | static cl::opt<bool> PrintBranchProb( | 
|  | "print-bpi", cl::init(false), cl::Hidden, | 
|  | cl::desc("Print the branch probability info.")); | 
|  |  | 
|  | cl::opt<std::string> PrintBranchProbFuncName( | 
|  | "print-bpi-func-name", cl::Hidden, | 
|  | cl::desc("The option to specify the name of the function " | 
|  | "whose branch probability info is printed.")); | 
|  |  | 
|  | INITIALIZE_PASS_BEGIN(BranchProbabilityInfoWrapperPass, "branch-prob", | 
|  | "Branch Probability Analysis", false, true) | 
|  | INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass) | 
|  | INITIALIZE_PASS_DEPENDENCY(TargetLibraryInfoWrapperPass) | 
|  | INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass) | 
|  | INITIALIZE_PASS_DEPENDENCY(PostDominatorTreeWrapperPass) | 
|  | INITIALIZE_PASS_END(BranchProbabilityInfoWrapperPass, "branch-prob", | 
|  | "Branch Probability Analysis", false, true) | 
|  |  | 
|  | BranchProbabilityInfoWrapperPass::BranchProbabilityInfoWrapperPass() | 
|  | : FunctionPass(ID) { | 
|  | initializeBranchProbabilityInfoWrapperPassPass( | 
|  | *PassRegistry::getPassRegistry()); | 
|  | } | 
|  |  | 
|  | char BranchProbabilityInfoWrapperPass::ID = 0; | 
|  |  | 
|  | // Weights are for internal use only. They are used by heuristics to help to | 
|  | // estimate edges' probability. Example: | 
|  | // | 
|  | // Using "Loop Branch Heuristics" we predict weights of edges for the | 
|  | // block BB2. | 
|  | //         ... | 
|  | //          | | 
|  | //          V | 
|  | //         BB1<-+ | 
|  | //          |   | | 
|  | //          |   | (Weight = 124) | 
|  | //          V   | | 
|  | //         BB2--+ | 
|  | //          | | 
|  | //          | (Weight = 4) | 
|  | //          V | 
|  | //         BB3 | 
|  | // | 
|  | // Probability of the edge BB2->BB1 = 124 / (124 + 4) = 0.96875 | 
|  | // Probability of the edge BB2->BB3 = 4 / (124 + 4) = 0.03125 | 
|  | static const uint32_t LBH_TAKEN_WEIGHT = 124; | 
|  | static const uint32_t LBH_NONTAKEN_WEIGHT = 4; | 
|  |  | 
|  | /// Unreachable-terminating branch taken probability. | 
|  | /// | 
|  | /// This is the probability for a branch being taken to a block that terminates | 
|  | /// (eventually) in unreachable. These are predicted as unlikely as possible. | 
|  | /// All reachable probability will proportionally share the remaining part. | 
|  | static const BranchProbability UR_TAKEN_PROB = BranchProbability::getRaw(1); | 
|  |  | 
|  | /// Heuristics and lookup tables for non-loop branches: | 
|  | /// Pointer Heuristics (PH) | 
|  | static const uint32_t PH_TAKEN_WEIGHT = 20; | 
|  | static const uint32_t PH_NONTAKEN_WEIGHT = 12; | 
|  | static const BranchProbability | 
|  | PtrTakenProb(PH_TAKEN_WEIGHT, PH_TAKEN_WEIGHT + PH_NONTAKEN_WEIGHT); | 
|  | static const BranchProbability | 
|  | PtrUntakenProb(PH_NONTAKEN_WEIGHT, PH_TAKEN_WEIGHT + PH_NONTAKEN_WEIGHT); | 
|  |  | 
|  | using ProbabilityList = SmallVector<BranchProbability>; | 
|  | using ProbabilityTable = std::map<CmpInst::Predicate, ProbabilityList>; | 
|  |  | 
|  | /// Pointer comparisons: | 
|  | static const ProbabilityTable PointerTable{ | 
|  | {ICmpInst::ICMP_NE, {PtrTakenProb, PtrUntakenProb}}, /// p != q -> Likely | 
|  | {ICmpInst::ICMP_EQ, {PtrUntakenProb, PtrTakenProb}}, /// p == q -> Unlikely | 
|  | }; | 
|  |  | 
|  | /// Zero Heuristics (ZH) | 
|  | static const uint32_t ZH_TAKEN_WEIGHT = 20; | 
|  | static const uint32_t ZH_NONTAKEN_WEIGHT = 12; | 
|  | static const BranchProbability | 
|  | ZeroTakenProb(ZH_TAKEN_WEIGHT, ZH_TAKEN_WEIGHT + ZH_NONTAKEN_WEIGHT); | 
|  | static const BranchProbability | 
|  | ZeroUntakenProb(ZH_NONTAKEN_WEIGHT, ZH_TAKEN_WEIGHT + ZH_NONTAKEN_WEIGHT); | 
|  |  | 
|  | /// Integer compares with 0: | 
|  | static const ProbabilityTable ICmpWithZeroTable{ | 
|  | {CmpInst::ICMP_EQ, {ZeroUntakenProb, ZeroTakenProb}},  /// X == 0 -> Unlikely | 
|  | {CmpInst::ICMP_NE, {ZeroTakenProb, ZeroUntakenProb}},  /// X != 0 -> Likely | 
|  | {CmpInst::ICMP_SLT, {ZeroUntakenProb, ZeroTakenProb}}, /// X < 0  -> Unlikely | 
|  | {CmpInst::ICMP_SGT, {ZeroTakenProb, ZeroUntakenProb}}, /// X > 0  -> Likely | 
|  | }; | 
|  |  | 
|  | /// Integer compares with -1: | 
|  | static const ProbabilityTable ICmpWithMinusOneTable{ | 
|  | {CmpInst::ICMP_EQ, {ZeroUntakenProb, ZeroTakenProb}},  /// X == -1 -> Unlikely | 
|  | {CmpInst::ICMP_NE, {ZeroTakenProb, ZeroUntakenProb}},  /// X != -1 -> Likely | 
|  | // InstCombine canonicalizes X >= 0 into X > -1 | 
|  | {CmpInst::ICMP_SGT, {ZeroTakenProb, ZeroUntakenProb}}, /// X >= 0  -> Likely | 
|  | }; | 
|  |  | 
|  | /// Integer compares with 1: | 
|  | static const ProbabilityTable ICmpWithOneTable{ | 
|  | // InstCombine canonicalizes X <= 0 into X < 1 | 
|  | {CmpInst::ICMP_SLT, {ZeroUntakenProb, ZeroTakenProb}}, /// X <= 0 -> Unlikely | 
|  | }; | 
|  |  | 
|  | /// strcmp and similar functions return zero, negative, or positive, if the | 
|  | /// first string is equal, less, or greater than the second. We consider it | 
|  | /// likely that the strings are not equal, so a comparison with zero is | 
|  | /// probably false, but also a comparison with any other number is also | 
|  | /// probably false given that what exactly is returned for nonzero values is | 
|  | /// not specified. Any kind of comparison other than equality we know | 
|  | /// nothing about. | 
|  | static const ProbabilityTable ICmpWithLibCallTable{ | 
|  | {CmpInst::ICMP_EQ, {ZeroUntakenProb, ZeroTakenProb}}, | 
|  | {CmpInst::ICMP_NE, {ZeroTakenProb, ZeroUntakenProb}}, | 
|  | }; | 
|  |  | 
|  | // Floating-Point Heuristics (FPH) | 
|  | static const uint32_t FPH_TAKEN_WEIGHT = 20; | 
|  | static const uint32_t FPH_NONTAKEN_WEIGHT = 12; | 
|  |  | 
|  | /// This is the probability for an ordered floating point comparison. | 
|  | static const uint32_t FPH_ORD_WEIGHT = 1024 * 1024 - 1; | 
|  | /// This is the probability for an unordered floating point comparison, it means | 
|  | /// one or two of the operands are NaN. Usually it is used to test for an | 
|  | /// exceptional case, so the result is unlikely. | 
|  | static const uint32_t FPH_UNO_WEIGHT = 1; | 
|  |  | 
|  | static const BranchProbability FPOrdTakenProb(FPH_ORD_WEIGHT, | 
|  | FPH_ORD_WEIGHT + FPH_UNO_WEIGHT); | 
|  | static const BranchProbability | 
|  | FPOrdUntakenProb(FPH_UNO_WEIGHT, FPH_ORD_WEIGHT + FPH_UNO_WEIGHT); | 
|  | static const BranchProbability | 
|  | FPTakenProb(FPH_TAKEN_WEIGHT, FPH_TAKEN_WEIGHT + FPH_NONTAKEN_WEIGHT); | 
|  | static const BranchProbability | 
|  | FPUntakenProb(FPH_NONTAKEN_WEIGHT, FPH_TAKEN_WEIGHT + FPH_NONTAKEN_WEIGHT); | 
|  |  | 
|  | /// Floating-Point compares: | 
|  | static const ProbabilityTable FCmpTable{ | 
|  | {FCmpInst::FCMP_ORD, {FPOrdTakenProb, FPOrdUntakenProb}}, /// !isnan -> Likely | 
|  | {FCmpInst::FCMP_UNO, {FPOrdUntakenProb, FPOrdTakenProb}}, /// isnan -> Unlikely | 
|  | }; | 
|  |  | 
|  | /// Set of dedicated "absolute" execution weights for a block. These weights are | 
|  | /// meaningful relative to each other and their derivatives only. | 
|  | enum class BlockExecWeight : std::uint32_t { | 
|  | /// Special weight used for cases with exact zero probability. | 
|  | ZERO = 0x0, | 
|  | /// Minimal possible non zero weight. | 
|  | LOWEST_NON_ZERO = 0x1, | 
|  | /// Weight to an 'unreachable' block. | 
|  | UNREACHABLE = ZERO, | 
|  | /// Weight to a block containing non returning call. | 
|  | NORETURN = LOWEST_NON_ZERO, | 
|  | /// Weight to 'unwind' block of an invoke instruction. | 
|  | UNWIND = LOWEST_NON_ZERO, | 
|  | /// Weight to a 'cold' block. Cold blocks are the ones containing calls marked | 
|  | /// with attribute 'cold'. | 
|  | COLD = 0xffff, | 
|  | /// Default weight is used in cases when there is no dedicated execution | 
|  | /// weight set. It is not propagated through the domination line either. | 
|  | DEFAULT = 0xfffff | 
|  | }; | 
|  |  | 
|  | BranchProbabilityInfo::SccInfo::SccInfo(const Function &F) { | 
|  | // Record SCC numbers of blocks in the CFG to identify irreducible loops. | 
|  | // FIXME: We could only calculate this if the CFG is known to be irreducible | 
|  | // (perhaps cache this info in LoopInfo if we can easily calculate it there?). | 
|  | int SccNum = 0; | 
|  | for (scc_iterator<const Function *> It = scc_begin(&F); !It.isAtEnd(); | 
|  | ++It, ++SccNum) { | 
|  | // Ignore single-block SCCs since they either aren't loops or LoopInfo will | 
|  | // catch them. | 
|  | const std::vector<const BasicBlock *> &Scc = *It; | 
|  | if (Scc.size() == 1) | 
|  | continue; | 
|  |  | 
|  | LLVM_DEBUG(dbgs() << "BPI: SCC " << SccNum << ":"); | 
|  | for (const auto *BB : Scc) { | 
|  | LLVM_DEBUG(dbgs() << " " << BB->getName()); | 
|  | SccNums[BB] = SccNum; | 
|  | calculateSccBlockType(BB, SccNum); | 
|  | } | 
|  | LLVM_DEBUG(dbgs() << "\n"); | 
|  | } | 
|  | } | 
|  |  | 
|  | int BranchProbabilityInfo::SccInfo::getSCCNum(const BasicBlock *BB) const { | 
|  | auto SccIt = SccNums.find(BB); | 
|  | if (SccIt == SccNums.end()) | 
|  | return -1; | 
|  | return SccIt->second; | 
|  | } | 
|  |  | 
|  | void BranchProbabilityInfo::SccInfo::getSccEnterBlocks( | 
|  | int SccNum, SmallVectorImpl<BasicBlock *> &Enters) const { | 
|  |  | 
|  | for (auto MapIt : SccBlocks[SccNum]) { | 
|  | const auto *BB = MapIt.first; | 
|  | if (isSCCHeader(BB, SccNum)) | 
|  | for (const auto *Pred : predecessors(BB)) | 
|  | if (getSCCNum(Pred) != SccNum) | 
|  | Enters.push_back(const_cast<BasicBlock *>(BB)); | 
|  | } | 
|  | } | 
|  |  | 
|  | void BranchProbabilityInfo::SccInfo::getSccExitBlocks( | 
|  | int SccNum, SmallVectorImpl<BasicBlock *> &Exits) const { | 
|  | for (auto MapIt : SccBlocks[SccNum]) { | 
|  | const auto *BB = MapIt.first; | 
|  | if (isSCCExitingBlock(BB, SccNum)) | 
|  | for (const auto *Succ : successors(BB)) | 
|  | if (getSCCNum(Succ) != SccNum) | 
|  | Exits.push_back(const_cast<BasicBlock *>(Succ)); | 
|  | } | 
|  | } | 
|  |  | 
|  | uint32_t BranchProbabilityInfo::SccInfo::getSccBlockType(const BasicBlock *BB, | 
|  | int SccNum) const { | 
|  | assert(getSCCNum(BB) == SccNum); | 
|  |  | 
|  | assert(SccBlocks.size() > static_cast<unsigned>(SccNum) && "Unknown SCC"); | 
|  | const auto &SccBlockTypes = SccBlocks[SccNum]; | 
|  |  | 
|  | auto It = SccBlockTypes.find(BB); | 
|  | if (It != SccBlockTypes.end()) { | 
|  | return It->second; | 
|  | } | 
|  | return Inner; | 
|  | } | 
|  |  | 
|  | void BranchProbabilityInfo::SccInfo::calculateSccBlockType(const BasicBlock *BB, | 
|  | int SccNum) { | 
|  | assert(getSCCNum(BB) == SccNum); | 
|  | uint32_t BlockType = Inner; | 
|  |  | 
|  | if (llvm::any_of(predecessors(BB), [&](const BasicBlock *Pred) { | 
|  | // Consider any block that is an entry point to the SCC as | 
|  | // a header. | 
|  | return getSCCNum(Pred) != SccNum; | 
|  | })) | 
|  | BlockType |= Header; | 
|  |  | 
|  | if (llvm::any_of(successors(BB), [&](const BasicBlock *Succ) { | 
|  | return getSCCNum(Succ) != SccNum; | 
|  | })) | 
|  | BlockType |= Exiting; | 
|  |  | 
|  | // Lazily compute the set of headers for a given SCC and cache the results | 
|  | // in the SccHeaderMap. | 
|  | if (SccBlocks.size() <= static_cast<unsigned>(SccNum)) | 
|  | SccBlocks.resize(SccNum + 1); | 
|  | auto &SccBlockTypes = SccBlocks[SccNum]; | 
|  |  | 
|  | if (BlockType != Inner) { | 
|  | bool IsInserted; | 
|  | std::tie(std::ignore, IsInserted) = | 
|  | SccBlockTypes.insert(std::make_pair(BB, BlockType)); | 
|  | assert(IsInserted && "Duplicated block in SCC"); | 
|  | } | 
|  | } | 
|  |  | 
|  | BranchProbabilityInfo::LoopBlock::LoopBlock(const BasicBlock *BB, | 
|  | const LoopInfo &LI, | 
|  | const SccInfo &SccI) | 
|  | : BB(BB) { | 
|  | LD.first = LI.getLoopFor(BB); | 
|  | if (!LD.first) { | 
|  | LD.second = SccI.getSCCNum(BB); | 
|  | } | 
|  | } | 
|  |  | 
|  | bool BranchProbabilityInfo::isLoopEnteringEdge(const LoopEdge &Edge) const { | 
|  | const auto &SrcBlock = Edge.first; | 
|  | const auto &DstBlock = Edge.second; | 
|  | return (DstBlock.getLoop() && | 
|  | !DstBlock.getLoop()->contains(SrcBlock.getLoop())) || | 
|  | // Assume that SCCs can't be nested. | 
|  | (DstBlock.getSccNum() != -1 && | 
|  | SrcBlock.getSccNum() != DstBlock.getSccNum()); | 
|  | } | 
|  |  | 
|  | bool BranchProbabilityInfo::isLoopExitingEdge(const LoopEdge &Edge) const { | 
|  | return isLoopEnteringEdge({Edge.second, Edge.first}); | 
|  | } | 
|  |  | 
|  | bool BranchProbabilityInfo::isLoopEnteringExitingEdge( | 
|  | const LoopEdge &Edge) const { | 
|  | return isLoopEnteringEdge(Edge) || isLoopExitingEdge(Edge); | 
|  | } | 
|  |  | 
|  | bool BranchProbabilityInfo::isLoopBackEdge(const LoopEdge &Edge) const { | 
|  | const auto &SrcBlock = Edge.first; | 
|  | const auto &DstBlock = Edge.second; | 
|  | return SrcBlock.belongsToSameLoop(DstBlock) && | 
|  | ((DstBlock.getLoop() && | 
|  | DstBlock.getLoop()->getHeader() == DstBlock.getBlock()) || | 
|  | (DstBlock.getSccNum() != -1 && | 
|  | SccI->isSCCHeader(DstBlock.getBlock(), DstBlock.getSccNum()))); | 
|  | } | 
|  |  | 
|  | void BranchProbabilityInfo::getLoopEnterBlocks( | 
|  | const LoopBlock &LB, SmallVectorImpl<BasicBlock *> &Enters) const { | 
|  | if (LB.getLoop()) { | 
|  | auto *Header = LB.getLoop()->getHeader(); | 
|  | Enters.append(pred_begin(Header), pred_end(Header)); | 
|  | } else { | 
|  | assert(LB.getSccNum() != -1 && "LB doesn't belong to any loop?"); | 
|  | SccI->getSccEnterBlocks(LB.getSccNum(), Enters); | 
|  | } | 
|  | } | 
|  |  | 
|  | void BranchProbabilityInfo::getLoopExitBlocks( | 
|  | const LoopBlock &LB, SmallVectorImpl<BasicBlock *> &Exits) const { | 
|  | if (LB.getLoop()) { | 
|  | LB.getLoop()->getExitBlocks(Exits); | 
|  | } else { | 
|  | assert(LB.getSccNum() != -1 && "LB doesn't belong to any loop?"); | 
|  | SccI->getSccExitBlocks(LB.getSccNum(), Exits); | 
|  | } | 
|  | } | 
|  |  | 
|  | // Propagate existing explicit probabilities from either profile data or | 
|  | // 'expect' intrinsic processing. Examine metadata against unreachable | 
|  | // heuristic. The probability of the edge coming to unreachable block is | 
|  | // set to min of metadata and unreachable heuristic. | 
|  | bool BranchProbabilityInfo::calcMetadataWeights(const BasicBlock *BB) { | 
|  | const Instruction *TI = BB->getTerminator(); | 
|  | assert(TI->getNumSuccessors() > 1 && "expected more than one successor!"); | 
|  | if (!(isa<BranchInst>(TI) || isa<SwitchInst>(TI) || isa<IndirectBrInst>(TI) || | 
|  | isa<InvokeInst>(TI) || isa<CallBrInst>(TI))) | 
|  | return false; | 
|  |  | 
|  | MDNode *WeightsNode = getValidBranchWeightMDNode(*TI); | 
|  | if (!WeightsNode) | 
|  | return false; | 
|  |  | 
|  | // Check that the number of successors is manageable. | 
|  | assert(TI->getNumSuccessors() < UINT32_MAX && "Too many successors"); | 
|  |  | 
|  | // Build up the final weights that will be used in a temporary buffer. | 
|  | // Compute the sum of all weights to later decide whether they need to | 
|  | // be scaled to fit in 32 bits. | 
|  | uint64_t WeightSum = 0; | 
|  | SmallVector<uint32_t, 2> Weights; | 
|  | SmallVector<unsigned, 2> UnreachableIdxs; | 
|  | SmallVector<unsigned, 2> ReachableIdxs; | 
|  |  | 
|  | extractBranchWeights(WeightsNode, Weights); | 
|  | for (unsigned I = 0, E = Weights.size(); I != E; ++I) { | 
|  | WeightSum += Weights[I]; | 
|  | const LoopBlock SrcLoopBB = getLoopBlock(BB); | 
|  | const LoopBlock DstLoopBB = getLoopBlock(TI->getSuccessor(I)); | 
|  | auto EstimatedWeight = getEstimatedEdgeWeight({SrcLoopBB, DstLoopBB}); | 
|  | if (EstimatedWeight && | 
|  | *EstimatedWeight <= static_cast<uint32_t>(BlockExecWeight::UNREACHABLE)) | 
|  | UnreachableIdxs.push_back(I); | 
|  | else | 
|  | ReachableIdxs.push_back(I); | 
|  | } | 
|  | assert(Weights.size() == TI->getNumSuccessors() && "Checked above"); | 
|  |  | 
|  | // If the sum of weights does not fit in 32 bits, scale every weight down | 
|  | // accordingly. | 
|  | uint64_t ScalingFactor = | 
|  | (WeightSum > UINT32_MAX) ? WeightSum / UINT32_MAX + 1 : 1; | 
|  |  | 
|  | if (ScalingFactor > 1) { | 
|  | WeightSum = 0; | 
|  | for (unsigned I = 0, E = TI->getNumSuccessors(); I != E; ++I) { | 
|  | Weights[I] /= ScalingFactor; | 
|  | WeightSum += Weights[I]; | 
|  | } | 
|  | } | 
|  | assert(WeightSum <= UINT32_MAX && | 
|  | "Expected weights to scale down to 32 bits"); | 
|  |  | 
|  | if (WeightSum == 0 || ReachableIdxs.size() == 0) { | 
|  | for (unsigned I = 0, E = TI->getNumSuccessors(); I != E; ++I) | 
|  | Weights[I] = 1; | 
|  | WeightSum = TI->getNumSuccessors(); | 
|  | } | 
|  |  | 
|  | // Set the probability. | 
|  | SmallVector<BranchProbability, 2> BP; | 
|  | for (unsigned I = 0, E = TI->getNumSuccessors(); I != E; ++I) | 
|  | BP.push_back({ Weights[I], static_cast<uint32_t>(WeightSum) }); | 
|  |  | 
|  | // Examine the metadata against unreachable heuristic. | 
|  | // If the unreachable heuristic is more strong then we use it for this edge. | 
|  | if (UnreachableIdxs.size() == 0 || ReachableIdxs.size() == 0) { | 
|  | setEdgeProbability(BB, BP); | 
|  | return true; | 
|  | } | 
|  |  | 
|  | auto UnreachableProb = UR_TAKEN_PROB; | 
|  | for (auto I : UnreachableIdxs) | 
|  | if (UnreachableProb < BP[I]) { | 
|  | BP[I] = UnreachableProb; | 
|  | } | 
|  |  | 
|  | // Sum of all edge probabilities must be 1.0. If we modified the probability | 
|  | // of some edges then we must distribute the introduced difference over the | 
|  | // reachable blocks. | 
|  | // | 
|  | // Proportional distribution: the relation between probabilities of the | 
|  | // reachable edges is kept unchanged. That is for any reachable edges i and j: | 
|  | //   newBP[i] / newBP[j] == oldBP[i] / oldBP[j] => | 
|  | //   newBP[i] / oldBP[i] == newBP[j] / oldBP[j] == K | 
|  | // Where K is independent of i,j. | 
|  | //   newBP[i] == oldBP[i] * K | 
|  | // We need to find K. | 
|  | // Make sum of all reachables of the left and right parts: | 
|  | //   sum_of_reachable(newBP) == K * sum_of_reachable(oldBP) | 
|  | // Sum of newBP must be equal to 1.0: | 
|  | //   sum_of_reachable(newBP) + sum_of_unreachable(newBP) == 1.0 => | 
|  | //   sum_of_reachable(newBP) = 1.0 - sum_of_unreachable(newBP) | 
|  | // Where sum_of_unreachable(newBP) is what has been just changed. | 
|  | // Finally: | 
|  | //   K == sum_of_reachable(newBP) / sum_of_reachable(oldBP) => | 
|  | //   K == (1.0 - sum_of_unreachable(newBP)) / sum_of_reachable(oldBP) | 
|  | BranchProbability NewUnreachableSum = BranchProbability::getZero(); | 
|  | for (auto I : UnreachableIdxs) | 
|  | NewUnreachableSum += BP[I]; | 
|  |  | 
|  | BranchProbability NewReachableSum = | 
|  | BranchProbability::getOne() - NewUnreachableSum; | 
|  |  | 
|  | BranchProbability OldReachableSum = BranchProbability::getZero(); | 
|  | for (auto I : ReachableIdxs) | 
|  | OldReachableSum += BP[I]; | 
|  |  | 
|  | if (OldReachableSum != NewReachableSum) { // Anything to dsitribute? | 
|  | if (OldReachableSum.isZero()) { | 
|  | // If all oldBP[i] are zeroes then the proportional distribution results | 
|  | // in all zero probabilities and the error stays big. In this case we | 
|  | // evenly spread NewReachableSum over the reachable edges. | 
|  | BranchProbability PerEdge = NewReachableSum / ReachableIdxs.size(); | 
|  | for (auto I : ReachableIdxs) | 
|  | BP[I] = PerEdge; | 
|  | } else { | 
|  | for (auto I : ReachableIdxs) { | 
|  | // We use uint64_t to avoid double rounding error of the following | 
|  | // calculation: BP[i] = BP[i] * NewReachableSum / OldReachableSum | 
|  | // The formula is taken from the private constructor | 
|  | // BranchProbability(uint32_t Numerator, uint32_t Denominator) | 
|  | uint64_t Mul = static_cast<uint64_t>(NewReachableSum.getNumerator()) * | 
|  | BP[I].getNumerator(); | 
|  | uint32_t Div = static_cast<uint32_t>( | 
|  | divideNearest(Mul, OldReachableSum.getNumerator())); | 
|  | BP[I] = BranchProbability::getRaw(Div); | 
|  | } | 
|  | } | 
|  | } | 
|  |  | 
|  | setEdgeProbability(BB, BP); | 
|  |  | 
|  | return true; | 
|  | } | 
|  |  | 
|  | // Calculate Edge Weights using "Pointer Heuristics". Predict a comparison | 
|  | // between two pointer or pointer and NULL will fail. | 
|  | bool BranchProbabilityInfo::calcPointerHeuristics(const BasicBlock *BB) { | 
|  | const BranchInst *BI = dyn_cast<BranchInst>(BB->getTerminator()); | 
|  | if (!BI || !BI->isConditional()) | 
|  | return false; | 
|  |  | 
|  | Value *Cond = BI->getCondition(); | 
|  | ICmpInst *CI = dyn_cast<ICmpInst>(Cond); | 
|  | if (!CI || !CI->isEquality()) | 
|  | return false; | 
|  |  | 
|  | Value *LHS = CI->getOperand(0); | 
|  |  | 
|  | if (!LHS->getType()->isPointerTy()) | 
|  | return false; | 
|  |  | 
|  | assert(CI->getOperand(1)->getType()->isPointerTy()); | 
|  |  | 
|  | auto Search = PointerTable.find(CI->getPredicate()); | 
|  | if (Search == PointerTable.end()) | 
|  | return false; | 
|  | setEdgeProbability(BB, Search->second); | 
|  | return true; | 
|  | } | 
|  |  | 
|  | // Compute the unlikely successors to the block BB in the loop L, specifically | 
|  | // those that are unlikely because this is a loop, and add them to the | 
|  | // UnlikelyBlocks set. | 
|  | static void | 
|  | computeUnlikelySuccessors(const BasicBlock *BB, Loop *L, | 
|  | SmallPtrSetImpl<const BasicBlock*> &UnlikelyBlocks) { | 
|  | // Sometimes in a loop we have a branch whose condition is made false by | 
|  | // taking it. This is typically something like | 
|  | //  int n = 0; | 
|  | //  while (...) { | 
|  | //    if (++n >= MAX) { | 
|  | //      n = 0; | 
|  | //    } | 
|  | //  } | 
|  | // In this sort of situation taking the branch means that at the very least it | 
|  | // won't be taken again in the next iteration of the loop, so we should | 
|  | // consider it less likely than a typical branch. | 
|  | // | 
|  | // We detect this by looking back through the graph of PHI nodes that sets the | 
|  | // value that the condition depends on, and seeing if we can reach a successor | 
|  | // block which can be determined to make the condition false. | 
|  | // | 
|  | // FIXME: We currently consider unlikely blocks to be half as likely as other | 
|  | // blocks, but if we consider the example above the likelyhood is actually | 
|  | // 1/MAX. We could therefore be more precise in how unlikely we consider | 
|  | // blocks to be, but it would require more careful examination of the form | 
|  | // of the comparison expression. | 
|  | const BranchInst *BI = dyn_cast<BranchInst>(BB->getTerminator()); | 
|  | if (!BI || !BI->isConditional()) | 
|  | return; | 
|  |  | 
|  | // Check if the branch is based on an instruction compared with a constant | 
|  | CmpInst *CI = dyn_cast<CmpInst>(BI->getCondition()); | 
|  | if (!CI || !isa<Instruction>(CI->getOperand(0)) || | 
|  | !isa<Constant>(CI->getOperand(1))) | 
|  | return; | 
|  |  | 
|  | // Either the instruction must be a PHI, or a chain of operations involving | 
|  | // constants that ends in a PHI which we can then collapse into a single value | 
|  | // if the PHI value is known. | 
|  | Instruction *CmpLHS = dyn_cast<Instruction>(CI->getOperand(0)); | 
|  | PHINode *CmpPHI = dyn_cast<PHINode>(CmpLHS); | 
|  | Constant *CmpConst = dyn_cast<Constant>(CI->getOperand(1)); | 
|  | // Collect the instructions until we hit a PHI | 
|  | SmallVector<BinaryOperator *, 1> InstChain; | 
|  | while (!CmpPHI && CmpLHS && isa<BinaryOperator>(CmpLHS) && | 
|  | isa<Constant>(CmpLHS->getOperand(1))) { | 
|  | // Stop if the chain extends outside of the loop | 
|  | if (!L->contains(CmpLHS)) | 
|  | return; | 
|  | InstChain.push_back(cast<BinaryOperator>(CmpLHS)); | 
|  | CmpLHS = dyn_cast<Instruction>(CmpLHS->getOperand(0)); | 
|  | if (CmpLHS) | 
|  | CmpPHI = dyn_cast<PHINode>(CmpLHS); | 
|  | } | 
|  | if (!CmpPHI || !L->contains(CmpPHI)) | 
|  | return; | 
|  |  | 
|  | // Trace the phi node to find all values that come from successors of BB | 
|  | SmallPtrSet<PHINode*, 8> VisitedInsts; | 
|  | SmallVector<PHINode*, 8> WorkList; | 
|  | WorkList.push_back(CmpPHI); | 
|  | VisitedInsts.insert(CmpPHI); | 
|  | while (!WorkList.empty()) { | 
|  | PHINode *P = WorkList.pop_back_val(); | 
|  | for (BasicBlock *B : P->blocks()) { | 
|  | // Skip blocks that aren't part of the loop | 
|  | if (!L->contains(B)) | 
|  | continue; | 
|  | Value *V = P->getIncomingValueForBlock(B); | 
|  | // If the source is a PHI add it to the work list if we haven't | 
|  | // already visited it. | 
|  | if (PHINode *PN = dyn_cast<PHINode>(V)) { | 
|  | if (VisitedInsts.insert(PN).second) | 
|  | WorkList.push_back(PN); | 
|  | continue; | 
|  | } | 
|  | // If this incoming value is a constant and B is a successor of BB, then | 
|  | // we can constant-evaluate the compare to see if it makes the branch be | 
|  | // taken or not. | 
|  | Constant *CmpLHSConst = dyn_cast<Constant>(V); | 
|  | if (!CmpLHSConst || !llvm::is_contained(successors(BB), B)) | 
|  | continue; | 
|  | // First collapse InstChain | 
|  | const DataLayout &DL = BB->getModule()->getDataLayout(); | 
|  | for (Instruction *I : llvm::reverse(InstChain)) { | 
|  | CmpLHSConst = ConstantFoldBinaryOpOperands( | 
|  | I->getOpcode(), CmpLHSConst, cast<Constant>(I->getOperand(1)), DL); | 
|  | if (!CmpLHSConst) | 
|  | break; | 
|  | } | 
|  | if (!CmpLHSConst) | 
|  | continue; | 
|  | // Now constant-evaluate the compare | 
|  | Constant *Result = ConstantExpr::getCompare(CI->getPredicate(), | 
|  | CmpLHSConst, CmpConst, true); | 
|  | // If the result means we don't branch to the block then that block is | 
|  | // unlikely. | 
|  | if (Result && | 
|  | ((Result->isZeroValue() && B == BI->getSuccessor(0)) || | 
|  | (Result->isOneValue() && B == BI->getSuccessor(1)))) | 
|  | UnlikelyBlocks.insert(B); | 
|  | } | 
|  | } | 
|  | } | 
|  |  | 
|  | std::optional<uint32_t> | 
|  | BranchProbabilityInfo::getEstimatedBlockWeight(const BasicBlock *BB) const { | 
|  | auto WeightIt = EstimatedBlockWeight.find(BB); | 
|  | if (WeightIt == EstimatedBlockWeight.end()) | 
|  | return std::nullopt; | 
|  | return WeightIt->second; | 
|  | } | 
|  |  | 
|  | std::optional<uint32_t> | 
|  | BranchProbabilityInfo::getEstimatedLoopWeight(const LoopData &L) const { | 
|  | auto WeightIt = EstimatedLoopWeight.find(L); | 
|  | if (WeightIt == EstimatedLoopWeight.end()) | 
|  | return std::nullopt; | 
|  | return WeightIt->second; | 
|  | } | 
|  |  | 
|  | std::optional<uint32_t> | 
|  | BranchProbabilityInfo::getEstimatedEdgeWeight(const LoopEdge &Edge) const { | 
|  | // For edges entering a loop take weight of a loop rather than an individual | 
|  | // block in the loop. | 
|  | return isLoopEnteringEdge(Edge) | 
|  | ? getEstimatedLoopWeight(Edge.second.getLoopData()) | 
|  | : getEstimatedBlockWeight(Edge.second.getBlock()); | 
|  | } | 
|  |  | 
|  | template <class IterT> | 
|  | std::optional<uint32_t> BranchProbabilityInfo::getMaxEstimatedEdgeWeight( | 
|  | const LoopBlock &SrcLoopBB, iterator_range<IterT> Successors) const { | 
|  | SmallVector<uint32_t, 4> Weights; | 
|  | std::optional<uint32_t> MaxWeight; | 
|  | for (const BasicBlock *DstBB : Successors) { | 
|  | const LoopBlock DstLoopBB = getLoopBlock(DstBB); | 
|  | auto Weight = getEstimatedEdgeWeight({SrcLoopBB, DstLoopBB}); | 
|  |  | 
|  | if (!Weight) | 
|  | return std::nullopt; | 
|  |  | 
|  | if (!MaxWeight || *MaxWeight < *Weight) | 
|  | MaxWeight = Weight; | 
|  | } | 
|  |  | 
|  | return MaxWeight; | 
|  | } | 
|  |  | 
|  | // Updates \p LoopBB's weight and returns true. If \p LoopBB has already | 
|  | // an associated weight it is unchanged and false is returned. | 
|  | // | 
|  | // Please note by the algorithm the weight is not expected to change once set | 
|  | // thus 'false' status is used to track visited blocks. | 
|  | bool BranchProbabilityInfo::updateEstimatedBlockWeight( | 
|  | LoopBlock &LoopBB, uint32_t BBWeight, | 
|  | SmallVectorImpl<BasicBlock *> &BlockWorkList, | 
|  | SmallVectorImpl<LoopBlock> &LoopWorkList) { | 
|  | BasicBlock *BB = LoopBB.getBlock(); | 
|  |  | 
|  | // In general, weight is assigned to a block when it has final value and | 
|  | // can't/shouldn't be changed.  However, there are cases when a block | 
|  | // inherently has several (possibly "contradicting") weights. For example, | 
|  | // "unwind" block may also contain "cold" call. In that case the first | 
|  | // set weight is favored and all consequent weights are ignored. | 
|  | if (!EstimatedBlockWeight.insert({BB, BBWeight}).second) | 
|  | return false; | 
|  |  | 
|  | for (BasicBlock *PredBlock : predecessors(BB)) { | 
|  | LoopBlock PredLoop = getLoopBlock(PredBlock); | 
|  | // Add affected block/loop to a working list. | 
|  | if (isLoopExitingEdge({PredLoop, LoopBB})) { | 
|  | if (!EstimatedLoopWeight.count(PredLoop.getLoopData())) | 
|  | LoopWorkList.push_back(PredLoop); | 
|  | } else if (!EstimatedBlockWeight.count(PredBlock)) | 
|  | BlockWorkList.push_back(PredBlock); | 
|  | } | 
|  | return true; | 
|  | } | 
|  |  | 
|  | // Starting from \p BB traverse through dominator blocks and assign \p BBWeight | 
|  | // to all such blocks that are post dominated by \BB. In other words to all | 
|  | // blocks that the one is executed if and only if another one is executed. | 
|  | // Importantly, we skip loops here for two reasons. First weights of blocks in | 
|  | // a loop should be scaled by trip count (yet possibly unknown). Second there is | 
|  | // no any value in doing that because that doesn't give any additional | 
|  | // information regarding distribution of probabilities inside the loop. | 
|  | // Exception is loop 'enter' and 'exit' edges that are handled in a special way | 
|  | // at calcEstimatedHeuristics. | 
|  | // | 
|  | // In addition, \p WorkList is populated with basic blocks if at leas one | 
|  | // successor has updated estimated weight. | 
|  | void BranchProbabilityInfo::propagateEstimatedBlockWeight( | 
|  | const LoopBlock &LoopBB, DominatorTree *DT, PostDominatorTree *PDT, | 
|  | uint32_t BBWeight, SmallVectorImpl<BasicBlock *> &BlockWorkList, | 
|  | SmallVectorImpl<LoopBlock> &LoopWorkList) { | 
|  | const BasicBlock *BB = LoopBB.getBlock(); | 
|  | const auto *DTStartNode = DT->getNode(BB); | 
|  | const auto *PDTStartNode = PDT->getNode(BB); | 
|  |  | 
|  | // TODO: Consider propagating weight down the domination line as well. | 
|  | for (const auto *DTNode = DTStartNode; DTNode != nullptr; | 
|  | DTNode = DTNode->getIDom()) { | 
|  | auto *DomBB = DTNode->getBlock(); | 
|  | // Consider blocks which lie on one 'line'. | 
|  | if (!PDT->dominates(PDTStartNode, PDT->getNode(DomBB))) | 
|  | // If BB doesn't post dominate DomBB it will not post dominate dominators | 
|  | // of DomBB as well. | 
|  | break; | 
|  |  | 
|  | LoopBlock DomLoopBB = getLoopBlock(DomBB); | 
|  | const LoopEdge Edge{DomLoopBB, LoopBB}; | 
|  | // Don't propagate weight to blocks belonging to different loops. | 
|  | if (!isLoopEnteringExitingEdge(Edge)) { | 
|  | if (!updateEstimatedBlockWeight(DomLoopBB, BBWeight, BlockWorkList, | 
|  | LoopWorkList)) | 
|  | // If DomBB has weight set then all it's predecessors are already | 
|  | // processed (since we propagate weight up to the top of IR each time). | 
|  | break; | 
|  | } else if (isLoopExitingEdge(Edge)) { | 
|  | LoopWorkList.push_back(DomLoopBB); | 
|  | } | 
|  | } | 
|  | } | 
|  |  | 
|  | std::optional<uint32_t> | 
|  | BranchProbabilityInfo::getInitialEstimatedBlockWeight(const BasicBlock *BB) { | 
|  | // Returns true if \p BB has call marked with "NoReturn" attribute. | 
|  | auto hasNoReturn = [&](const BasicBlock *BB) { | 
|  | for (const auto &I : reverse(*BB)) | 
|  | if (const CallInst *CI = dyn_cast<CallInst>(&I)) | 
|  | if (CI->hasFnAttr(Attribute::NoReturn)) | 
|  | return true; | 
|  |  | 
|  | return false; | 
|  | }; | 
|  |  | 
|  | // Important note regarding the order of checks. They are ordered by weight | 
|  | // from lowest to highest. Doing that allows to avoid "unstable" results | 
|  | // when several conditions heuristics can be applied simultaneously. | 
|  | if (isa<UnreachableInst>(BB->getTerminator()) || | 
|  | // If this block is terminated by a call to | 
|  | // @llvm.experimental.deoptimize then treat it like an unreachable | 
|  | // since it is expected to practically never execute. | 
|  | // TODO: Should we actually treat as never returning call? | 
|  | BB->getTerminatingDeoptimizeCall()) | 
|  | return hasNoReturn(BB) | 
|  | ? static_cast<uint32_t>(BlockExecWeight::NORETURN) | 
|  | : static_cast<uint32_t>(BlockExecWeight::UNREACHABLE); | 
|  |  | 
|  | // Check if the block is 'unwind' handler of  some invoke instruction. | 
|  | for (const auto *Pred : predecessors(BB)) | 
|  | if (Pred) | 
|  | if (const auto *II = dyn_cast<InvokeInst>(Pred->getTerminator())) | 
|  | if (II->getUnwindDest() == BB) | 
|  | return static_cast<uint32_t>(BlockExecWeight::UNWIND); | 
|  |  | 
|  | // Check if the block contains 'cold' call. | 
|  | for (const auto &I : *BB) | 
|  | if (const CallInst *CI = dyn_cast<CallInst>(&I)) | 
|  | if (CI->hasFnAttr(Attribute::Cold)) | 
|  | return static_cast<uint32_t>(BlockExecWeight::COLD); | 
|  |  | 
|  | return std::nullopt; | 
|  | } | 
|  |  | 
|  | // Does RPO traversal over all blocks in \p F and assigns weights to | 
|  | // 'unreachable', 'noreturn', 'cold', 'unwind' blocks. In addition it does its | 
|  | // best to propagate the weight to up/down the IR. | 
|  | void BranchProbabilityInfo::computeEestimateBlockWeight( | 
|  | const Function &F, DominatorTree *DT, PostDominatorTree *PDT) { | 
|  | SmallVector<BasicBlock *, 8> BlockWorkList; | 
|  | SmallVector<LoopBlock, 8> LoopWorkList; | 
|  |  | 
|  | // By doing RPO we make sure that all predecessors already have weights | 
|  | // calculated before visiting theirs successors. | 
|  | ReversePostOrderTraversal<const Function *> RPOT(&F); | 
|  | for (const auto *BB : RPOT) | 
|  | if (auto BBWeight = getInitialEstimatedBlockWeight(BB)) | 
|  | // If we were able to find estimated weight for the block set it to this | 
|  | // block and propagate up the IR. | 
|  | propagateEstimatedBlockWeight(getLoopBlock(BB), DT, PDT, *BBWeight, | 
|  | BlockWorkList, LoopWorkList); | 
|  |  | 
|  | // BlockWorklist/LoopWorkList contains blocks/loops with at least one | 
|  | // successor/exit having estimated weight. Try to propagate weight to such | 
|  | // blocks/loops from successors/exits. | 
|  | // Process loops and blocks. Order is not important. | 
|  | do { | 
|  | while (!LoopWorkList.empty()) { | 
|  | const LoopBlock LoopBB = LoopWorkList.pop_back_val(); | 
|  |  | 
|  | if (EstimatedLoopWeight.count(LoopBB.getLoopData())) | 
|  | continue; | 
|  |  | 
|  | SmallVector<BasicBlock *, 4> Exits; | 
|  | getLoopExitBlocks(LoopBB, Exits); | 
|  | auto LoopWeight = getMaxEstimatedEdgeWeight( | 
|  | LoopBB, make_range(Exits.begin(), Exits.end())); | 
|  |  | 
|  | if (LoopWeight) { | 
|  | // If we never exit the loop then we can enter it once at maximum. | 
|  | if (LoopWeight <= static_cast<uint32_t>(BlockExecWeight::UNREACHABLE)) | 
|  | LoopWeight = static_cast<uint32_t>(BlockExecWeight::LOWEST_NON_ZERO); | 
|  |  | 
|  | EstimatedLoopWeight.insert({LoopBB.getLoopData(), *LoopWeight}); | 
|  | // Add all blocks entering the loop into working list. | 
|  | getLoopEnterBlocks(LoopBB, BlockWorkList); | 
|  | } | 
|  | } | 
|  |  | 
|  | while (!BlockWorkList.empty()) { | 
|  | // We can reach here only if BlockWorkList is not empty. | 
|  | const BasicBlock *BB = BlockWorkList.pop_back_val(); | 
|  | if (EstimatedBlockWeight.count(BB)) | 
|  | continue; | 
|  |  | 
|  | // We take maximum over all weights of successors. In other words we take | 
|  | // weight of "hot" path. In theory we can probably find a better function | 
|  | // which gives higher accuracy results (comparing to "maximum") but I | 
|  | // can't | 
|  | // think of any right now. And I doubt it will make any difference in | 
|  | // practice. | 
|  | const LoopBlock LoopBB = getLoopBlock(BB); | 
|  | auto MaxWeight = getMaxEstimatedEdgeWeight(LoopBB, successors(BB)); | 
|  |  | 
|  | if (MaxWeight) | 
|  | propagateEstimatedBlockWeight(LoopBB, DT, PDT, *MaxWeight, | 
|  | BlockWorkList, LoopWorkList); | 
|  | } | 
|  | } while (!BlockWorkList.empty() || !LoopWorkList.empty()); | 
|  | } | 
|  |  | 
|  | // Calculate edge probabilities based on block's estimated weight. | 
|  | // Note that gathered weights were not scaled for loops. Thus edges entering | 
|  | // and exiting loops requires special processing. | 
|  | bool BranchProbabilityInfo::calcEstimatedHeuristics(const BasicBlock *BB) { | 
|  | assert(BB->getTerminator()->getNumSuccessors() > 1 && | 
|  | "expected more than one successor!"); | 
|  |  | 
|  | const LoopBlock LoopBB = getLoopBlock(BB); | 
|  |  | 
|  | SmallPtrSet<const BasicBlock *, 8> UnlikelyBlocks; | 
|  | uint32_t TC = LBH_TAKEN_WEIGHT / LBH_NONTAKEN_WEIGHT; | 
|  | if (LoopBB.getLoop()) | 
|  | computeUnlikelySuccessors(BB, LoopBB.getLoop(), UnlikelyBlocks); | 
|  |  | 
|  | // Changed to 'true' if at least one successor has estimated weight. | 
|  | bool FoundEstimatedWeight = false; | 
|  | SmallVector<uint32_t, 4> SuccWeights; | 
|  | uint64_t TotalWeight = 0; | 
|  | // Go over all successors of BB and put their weights into SuccWeights. | 
|  | for (const BasicBlock *SuccBB : successors(BB)) { | 
|  | std::optional<uint32_t> Weight; | 
|  | const LoopBlock SuccLoopBB = getLoopBlock(SuccBB); | 
|  | const LoopEdge Edge{LoopBB, SuccLoopBB}; | 
|  |  | 
|  | Weight = getEstimatedEdgeWeight(Edge); | 
|  |  | 
|  | if (isLoopExitingEdge(Edge) && | 
|  | // Avoid adjustment of ZERO weight since it should remain unchanged. | 
|  | Weight != static_cast<uint32_t>(BlockExecWeight::ZERO)) { | 
|  | // Scale down loop exiting weight by trip count. | 
|  | Weight = std::max( | 
|  | static_cast<uint32_t>(BlockExecWeight::LOWEST_NON_ZERO), | 
|  | Weight.value_or(static_cast<uint32_t>(BlockExecWeight::DEFAULT)) / | 
|  | TC); | 
|  | } | 
|  | bool IsUnlikelyEdge = LoopBB.getLoop() && UnlikelyBlocks.contains(SuccBB); | 
|  | if (IsUnlikelyEdge && | 
|  | // Avoid adjustment of ZERO weight since it should remain unchanged. | 
|  | Weight != static_cast<uint32_t>(BlockExecWeight::ZERO)) { | 
|  | // 'Unlikely' blocks have twice lower weight. | 
|  | Weight = std::max( | 
|  | static_cast<uint32_t>(BlockExecWeight::LOWEST_NON_ZERO), | 
|  | Weight.value_or(static_cast<uint32_t>(BlockExecWeight::DEFAULT)) / 2); | 
|  | } | 
|  |  | 
|  | if (Weight) | 
|  | FoundEstimatedWeight = true; | 
|  |  | 
|  | auto WeightVal = | 
|  | Weight.value_or(static_cast<uint32_t>(BlockExecWeight::DEFAULT)); | 
|  | TotalWeight += WeightVal; | 
|  | SuccWeights.push_back(WeightVal); | 
|  | } | 
|  |  | 
|  | // If non of blocks have estimated weight bail out. | 
|  | // If TotalWeight is 0 that means weight of each successor is 0 as well and | 
|  | // equally likely. Bail out early to not deal with devision by zero. | 
|  | if (!FoundEstimatedWeight || TotalWeight == 0) | 
|  | return false; | 
|  |  | 
|  | assert(SuccWeights.size() == succ_size(BB) && "Missed successor?"); | 
|  | const unsigned SuccCount = SuccWeights.size(); | 
|  |  | 
|  | // If the sum of weights does not fit in 32 bits, scale every weight down | 
|  | // accordingly. | 
|  | if (TotalWeight > UINT32_MAX) { | 
|  | uint64_t ScalingFactor = TotalWeight / UINT32_MAX + 1; | 
|  | TotalWeight = 0; | 
|  | for (unsigned Idx = 0; Idx < SuccCount; ++Idx) { | 
|  | SuccWeights[Idx] /= ScalingFactor; | 
|  | if (SuccWeights[Idx] == static_cast<uint32_t>(BlockExecWeight::ZERO)) | 
|  | SuccWeights[Idx] = | 
|  | static_cast<uint32_t>(BlockExecWeight::LOWEST_NON_ZERO); | 
|  | TotalWeight += SuccWeights[Idx]; | 
|  | } | 
|  | assert(TotalWeight <= UINT32_MAX && "Total weight overflows"); | 
|  | } | 
|  |  | 
|  | // Finally set probabilities to edges according to estimated block weights. | 
|  | SmallVector<BranchProbability, 4> EdgeProbabilities( | 
|  | SuccCount, BranchProbability::getUnknown()); | 
|  |  | 
|  | for (unsigned Idx = 0; Idx < SuccCount; ++Idx) { | 
|  | EdgeProbabilities[Idx] = | 
|  | BranchProbability(SuccWeights[Idx], (uint32_t)TotalWeight); | 
|  | } | 
|  | setEdgeProbability(BB, EdgeProbabilities); | 
|  | return true; | 
|  | } | 
|  |  | 
|  | bool BranchProbabilityInfo::calcZeroHeuristics(const BasicBlock *BB, | 
|  | const TargetLibraryInfo *TLI) { | 
|  | const BranchInst *BI = dyn_cast<BranchInst>(BB->getTerminator()); | 
|  | if (!BI || !BI->isConditional()) | 
|  | return false; | 
|  |  | 
|  | Value *Cond = BI->getCondition(); | 
|  | ICmpInst *CI = dyn_cast<ICmpInst>(Cond); | 
|  | if (!CI) | 
|  | return false; | 
|  |  | 
|  | auto GetConstantInt = [](Value *V) { | 
|  | if (auto *I = dyn_cast<BitCastInst>(V)) | 
|  | return dyn_cast<ConstantInt>(I->getOperand(0)); | 
|  | return dyn_cast<ConstantInt>(V); | 
|  | }; | 
|  |  | 
|  | Value *RHS = CI->getOperand(1); | 
|  | ConstantInt *CV = GetConstantInt(RHS); | 
|  | if (!CV) | 
|  | return false; | 
|  |  | 
|  | // If the LHS is the result of AND'ing a value with a single bit bitmask, | 
|  | // we don't have information about probabilities. | 
|  | if (Instruction *LHS = dyn_cast<Instruction>(CI->getOperand(0))) | 
|  | if (LHS->getOpcode() == Instruction::And) | 
|  | if (ConstantInt *AndRHS = GetConstantInt(LHS->getOperand(1))) | 
|  | if (AndRHS->getValue().isPowerOf2()) | 
|  | return false; | 
|  |  | 
|  | // Check if the LHS is the return value of a library function | 
|  | LibFunc Func = NumLibFuncs; | 
|  | if (TLI) | 
|  | if (CallInst *Call = dyn_cast<CallInst>(CI->getOperand(0))) | 
|  | if (Function *CalledFn = Call->getCalledFunction()) | 
|  | TLI->getLibFunc(*CalledFn, Func); | 
|  |  | 
|  | ProbabilityTable::const_iterator Search; | 
|  | if (Func == LibFunc_strcasecmp || | 
|  | Func == LibFunc_strcmp || | 
|  | Func == LibFunc_strncasecmp || | 
|  | Func == LibFunc_strncmp || | 
|  | Func == LibFunc_memcmp || | 
|  | Func == LibFunc_bcmp) { | 
|  | Search = ICmpWithLibCallTable.find(CI->getPredicate()); | 
|  | if (Search == ICmpWithLibCallTable.end()) | 
|  | return false; | 
|  | } else if (CV->isZero()) { | 
|  | Search = ICmpWithZeroTable.find(CI->getPredicate()); | 
|  | if (Search == ICmpWithZeroTable.end()) | 
|  | return false; | 
|  | } else if (CV->isOne()) { | 
|  | Search = ICmpWithOneTable.find(CI->getPredicate()); | 
|  | if (Search == ICmpWithOneTable.end()) | 
|  | return false; | 
|  | } else if (CV->isMinusOne()) { | 
|  | Search = ICmpWithMinusOneTable.find(CI->getPredicate()); | 
|  | if (Search == ICmpWithMinusOneTable.end()) | 
|  | return false; | 
|  | } else { | 
|  | return false; | 
|  | } | 
|  |  | 
|  | setEdgeProbability(BB, Search->second); | 
|  | return true; | 
|  | } | 
|  |  | 
|  | bool BranchProbabilityInfo::calcFloatingPointHeuristics(const BasicBlock *BB) { | 
|  | const BranchInst *BI = dyn_cast<BranchInst>(BB->getTerminator()); | 
|  | if (!BI || !BI->isConditional()) | 
|  | return false; | 
|  |  | 
|  | Value *Cond = BI->getCondition(); | 
|  | FCmpInst *FCmp = dyn_cast<FCmpInst>(Cond); | 
|  | if (!FCmp) | 
|  | return false; | 
|  |  | 
|  | ProbabilityList ProbList; | 
|  | if (FCmp->isEquality()) { | 
|  | ProbList = !FCmp->isTrueWhenEqual() ? | 
|  | // f1 == f2 -> Unlikely | 
|  | ProbabilityList({FPTakenProb, FPUntakenProb}) : | 
|  | // f1 != f2 -> Likely | 
|  | ProbabilityList({FPUntakenProb, FPTakenProb}); | 
|  | } else { | 
|  | auto Search = FCmpTable.find(FCmp->getPredicate()); | 
|  | if (Search == FCmpTable.end()) | 
|  | return false; | 
|  | ProbList = Search->second; | 
|  | } | 
|  |  | 
|  | setEdgeProbability(BB, ProbList); | 
|  | return true; | 
|  | } | 
|  |  | 
|  | void BranchProbabilityInfo::releaseMemory() { | 
|  | Probs.clear(); | 
|  | Handles.clear(); | 
|  | } | 
|  |  | 
|  | bool BranchProbabilityInfo::invalidate(Function &, const PreservedAnalyses &PA, | 
|  | FunctionAnalysisManager::Invalidator &) { | 
|  | // Check whether the analysis, all analyses on functions, or the function's | 
|  | // CFG have been preserved. | 
|  | auto PAC = PA.getChecker<BranchProbabilityAnalysis>(); | 
|  | return !(PAC.preserved() || PAC.preservedSet<AllAnalysesOn<Function>>() || | 
|  | PAC.preservedSet<CFGAnalyses>()); | 
|  | } | 
|  |  | 
|  | void BranchProbabilityInfo::print(raw_ostream &OS) const { | 
|  | OS << "---- Branch Probabilities ----\n"; | 
|  | // We print the probabilities from the last function the analysis ran over, | 
|  | // or the function it is currently running over. | 
|  | assert(LastF && "Cannot print prior to running over a function"); | 
|  | for (const auto &BI : *LastF) { | 
|  | for (const BasicBlock *Succ : successors(&BI)) | 
|  | printEdgeProbability(OS << "  ", &BI, Succ); | 
|  | } | 
|  | } | 
|  |  | 
|  | bool BranchProbabilityInfo:: | 
|  | isEdgeHot(const BasicBlock *Src, const BasicBlock *Dst) const { | 
|  | // Hot probability is at least 4/5 = 80% | 
|  | // FIXME: Compare against a static "hot" BranchProbability. | 
|  | return getEdgeProbability(Src, Dst) > BranchProbability(4, 5); | 
|  | } | 
|  |  | 
|  | /// Get the raw edge probability for the edge. If can't find it, return a | 
|  | /// default probability 1/N where N is the number of successors. Here an edge is | 
|  | /// specified using PredBlock and an | 
|  | /// index to the successors. | 
|  | BranchProbability | 
|  | BranchProbabilityInfo::getEdgeProbability(const BasicBlock *Src, | 
|  | unsigned IndexInSuccessors) const { | 
|  | auto I = Probs.find(std::make_pair(Src, IndexInSuccessors)); | 
|  | assert((Probs.end() == Probs.find(std::make_pair(Src, 0))) == | 
|  | (Probs.end() == I) && | 
|  | "Probability for I-th successor must always be defined along with the " | 
|  | "probability for the first successor"); | 
|  |  | 
|  | if (I != Probs.end()) | 
|  | return I->second; | 
|  |  | 
|  | return {1, static_cast<uint32_t>(succ_size(Src))}; | 
|  | } | 
|  |  | 
|  | BranchProbability | 
|  | BranchProbabilityInfo::getEdgeProbability(const BasicBlock *Src, | 
|  | const_succ_iterator Dst) const { | 
|  | return getEdgeProbability(Src, Dst.getSuccessorIndex()); | 
|  | } | 
|  |  | 
|  | /// Get the raw edge probability calculated for the block pair. This returns the | 
|  | /// sum of all raw edge probabilities from Src to Dst. | 
|  | BranchProbability | 
|  | BranchProbabilityInfo::getEdgeProbability(const BasicBlock *Src, | 
|  | const BasicBlock *Dst) const { | 
|  | if (!Probs.count(std::make_pair(Src, 0))) | 
|  | return BranchProbability(llvm::count(successors(Src), Dst), succ_size(Src)); | 
|  |  | 
|  | auto Prob = BranchProbability::getZero(); | 
|  | for (const_succ_iterator I = succ_begin(Src), E = succ_end(Src); I != E; ++I) | 
|  | if (*I == Dst) | 
|  | Prob += Probs.find(std::make_pair(Src, I.getSuccessorIndex()))->second; | 
|  |  | 
|  | return Prob; | 
|  | } | 
|  |  | 
|  | /// Set the edge probability for all edges at once. | 
|  | void BranchProbabilityInfo::setEdgeProbability( | 
|  | const BasicBlock *Src, const SmallVectorImpl<BranchProbability> &Probs) { | 
|  | assert(Src->getTerminator()->getNumSuccessors() == Probs.size()); | 
|  | eraseBlock(Src); // Erase stale data if any. | 
|  | if (Probs.size() == 0) | 
|  | return; // Nothing to set. | 
|  |  | 
|  | Handles.insert(BasicBlockCallbackVH(Src, this)); | 
|  | uint64_t TotalNumerator = 0; | 
|  | for (unsigned SuccIdx = 0; SuccIdx < Probs.size(); ++SuccIdx) { | 
|  | this->Probs[std::make_pair(Src, SuccIdx)] = Probs[SuccIdx]; | 
|  | LLVM_DEBUG(dbgs() << "set edge " << Src->getName() << " -> " << SuccIdx | 
|  | << " successor probability to " << Probs[SuccIdx] | 
|  | << "\n"); | 
|  | TotalNumerator += Probs[SuccIdx].getNumerator(); | 
|  | } | 
|  |  | 
|  | // Because of rounding errors the total probability cannot be checked to be | 
|  | // 1.0 exactly. That is TotalNumerator == BranchProbability::getDenominator. | 
|  | // Instead, every single probability in Probs must be as accurate as possible. | 
|  | // This results in error 1/denominator at most, thus the total absolute error | 
|  | // should be within Probs.size / BranchProbability::getDenominator. | 
|  | assert(TotalNumerator <= BranchProbability::getDenominator() + Probs.size()); | 
|  | assert(TotalNumerator >= BranchProbability::getDenominator() - Probs.size()); | 
|  | (void)TotalNumerator; | 
|  | } | 
|  |  | 
|  | void BranchProbabilityInfo::copyEdgeProbabilities(BasicBlock *Src, | 
|  | BasicBlock *Dst) { | 
|  | eraseBlock(Dst); // Erase stale data if any. | 
|  | unsigned NumSuccessors = Src->getTerminator()->getNumSuccessors(); | 
|  | assert(NumSuccessors == Dst->getTerminator()->getNumSuccessors()); | 
|  | if (NumSuccessors == 0) | 
|  | return; // Nothing to set. | 
|  | if (!this->Probs.contains(std::make_pair(Src, 0))) | 
|  | return; // No probability is set for edges from Src. Keep the same for Dst. | 
|  |  | 
|  | Handles.insert(BasicBlockCallbackVH(Dst, this)); | 
|  | for (unsigned SuccIdx = 0; SuccIdx < NumSuccessors; ++SuccIdx) { | 
|  | auto Prob = this->Probs[std::make_pair(Src, SuccIdx)]; | 
|  | this->Probs[std::make_pair(Dst, SuccIdx)] = Prob; | 
|  | LLVM_DEBUG(dbgs() << "set edge " << Dst->getName() << " -> " << SuccIdx | 
|  | << " successor probability to " << Prob << "\n"); | 
|  | } | 
|  | } | 
|  |  | 
|  | void BranchProbabilityInfo::swapSuccEdgesProbabilities(const BasicBlock *Src) { | 
|  | assert(Src->getTerminator()->getNumSuccessors() == 2); | 
|  | if (!Probs.contains(std::make_pair(Src, 0))) | 
|  | return; // No probability is set for edges from Src | 
|  | assert(Probs.contains(std::make_pair(Src, 1))); | 
|  | std::swap(Probs[std::make_pair(Src, 0)], Probs[std::make_pair(Src, 1)]); | 
|  | } | 
|  |  | 
|  | raw_ostream & | 
|  | BranchProbabilityInfo::printEdgeProbability(raw_ostream &OS, | 
|  | const BasicBlock *Src, | 
|  | const BasicBlock *Dst) const { | 
|  | const BranchProbability Prob = getEdgeProbability(Src, Dst); | 
|  | OS << "edge " << Src->getName() << " -> " << Dst->getName() | 
|  | << " probability is " << Prob | 
|  | << (isEdgeHot(Src, Dst) ? " [HOT edge]\n" : "\n"); | 
|  |  | 
|  | return OS; | 
|  | } | 
|  |  | 
|  | void BranchProbabilityInfo::eraseBlock(const BasicBlock *BB) { | 
|  | LLVM_DEBUG(dbgs() << "eraseBlock " << BB->getName() << "\n"); | 
|  |  | 
|  | // Note that we cannot use successors of BB because the terminator of BB may | 
|  | // have changed when eraseBlock is called as a BasicBlockCallbackVH callback. | 
|  | // Instead we remove prob data for the block by iterating successors by their | 
|  | // indices from 0 till the last which exists. There could not be prob data for | 
|  | // a pair (BB, N) if there is no data for (BB, N-1) because the data is always | 
|  | // set for all successors from 0 to M at once by the method | 
|  | // setEdgeProbability(). | 
|  | Handles.erase(BasicBlockCallbackVH(BB, this)); | 
|  | for (unsigned I = 0;; ++I) { | 
|  | auto MapI = Probs.find(std::make_pair(BB, I)); | 
|  | if (MapI == Probs.end()) { | 
|  | assert(Probs.count(std::make_pair(BB, I + 1)) == 0 && | 
|  | "Must be no more successors"); | 
|  | return; | 
|  | } | 
|  | Probs.erase(MapI); | 
|  | } | 
|  | } | 
|  |  | 
|  | void BranchProbabilityInfo::calculate(const Function &F, const LoopInfo &LoopI, | 
|  | const TargetLibraryInfo *TLI, | 
|  | DominatorTree *DT, | 
|  | PostDominatorTree *PDT) { | 
|  | LLVM_DEBUG(dbgs() << "---- Branch Probability Info : " << F.getName() | 
|  | << " ----\n\n"); | 
|  | LastF = &F; // Store the last function we ran on for printing. | 
|  | LI = &LoopI; | 
|  |  | 
|  | SccI = std::make_unique<SccInfo>(F); | 
|  |  | 
|  | assert(EstimatedBlockWeight.empty()); | 
|  | assert(EstimatedLoopWeight.empty()); | 
|  |  | 
|  | std::unique_ptr<DominatorTree> DTPtr; | 
|  | std::unique_ptr<PostDominatorTree> PDTPtr; | 
|  |  | 
|  | if (!DT) { | 
|  | DTPtr = std::make_unique<DominatorTree>(const_cast<Function &>(F)); | 
|  | DT = DTPtr.get(); | 
|  | } | 
|  |  | 
|  | if (!PDT) { | 
|  | PDTPtr = std::make_unique<PostDominatorTree>(const_cast<Function &>(F)); | 
|  | PDT = PDTPtr.get(); | 
|  | } | 
|  |  | 
|  | computeEestimateBlockWeight(F, DT, PDT); | 
|  |  | 
|  | // Walk the basic blocks in post-order so that we can build up state about | 
|  | // the successors of a block iteratively. | 
|  | for (const auto *BB : post_order(&F.getEntryBlock())) { | 
|  | LLVM_DEBUG(dbgs() << "Computing probabilities for " << BB->getName() | 
|  | << "\n"); | 
|  | // If there is no at least two successors, no sense to set probability. | 
|  | if (BB->getTerminator()->getNumSuccessors() < 2) | 
|  | continue; | 
|  | if (calcMetadataWeights(BB)) | 
|  | continue; | 
|  | if (calcEstimatedHeuristics(BB)) | 
|  | continue; | 
|  | if (calcPointerHeuristics(BB)) | 
|  | continue; | 
|  | if (calcZeroHeuristics(BB, TLI)) | 
|  | continue; | 
|  | if (calcFloatingPointHeuristics(BB)) | 
|  | continue; | 
|  | } | 
|  |  | 
|  | EstimatedLoopWeight.clear(); | 
|  | EstimatedBlockWeight.clear(); | 
|  | SccI.reset(); | 
|  |  | 
|  | if (PrintBranchProb && | 
|  | (PrintBranchProbFuncName.empty() || | 
|  | F.getName().equals(PrintBranchProbFuncName))) { | 
|  | print(dbgs()); | 
|  | } | 
|  | } | 
|  |  | 
|  | void BranchProbabilityInfoWrapperPass::getAnalysisUsage( | 
|  | AnalysisUsage &AU) const { | 
|  | // We require DT so it's available when LI is available. The LI updating code | 
|  | // asserts that DT is also present so if we don't make sure that we have DT | 
|  | // here, that assert will trigger. | 
|  | AU.addRequired<DominatorTreeWrapperPass>(); | 
|  | AU.addRequired<LoopInfoWrapperPass>(); | 
|  | AU.addRequired<TargetLibraryInfoWrapperPass>(); | 
|  | AU.addRequired<DominatorTreeWrapperPass>(); | 
|  | AU.addRequired<PostDominatorTreeWrapperPass>(); | 
|  | AU.setPreservesAll(); | 
|  | } | 
|  |  | 
|  | bool BranchProbabilityInfoWrapperPass::runOnFunction(Function &F) { | 
|  | const LoopInfo &LI = getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); | 
|  | const TargetLibraryInfo &TLI = | 
|  | getAnalysis<TargetLibraryInfoWrapperPass>().getTLI(F); | 
|  | DominatorTree &DT = getAnalysis<DominatorTreeWrapperPass>().getDomTree(); | 
|  | PostDominatorTree &PDT = | 
|  | getAnalysis<PostDominatorTreeWrapperPass>().getPostDomTree(); | 
|  | BPI.calculate(F, LI, &TLI, &DT, &PDT); | 
|  | return false; | 
|  | } | 
|  |  | 
|  | void BranchProbabilityInfoWrapperPass::releaseMemory() { BPI.releaseMemory(); } | 
|  |  | 
|  | void BranchProbabilityInfoWrapperPass::print(raw_ostream &OS, | 
|  | const Module *) const { | 
|  | BPI.print(OS); | 
|  | } | 
|  |  | 
|  | AnalysisKey BranchProbabilityAnalysis::Key; | 
|  | BranchProbabilityInfo | 
|  | BranchProbabilityAnalysis::run(Function &F, FunctionAnalysisManager &AM) { | 
|  | auto &LI = AM.getResult<LoopAnalysis>(F); | 
|  | auto &TLI = AM.getResult<TargetLibraryAnalysis>(F); | 
|  | auto &DT = AM.getResult<DominatorTreeAnalysis>(F); | 
|  | auto &PDT = AM.getResult<PostDominatorTreeAnalysis>(F); | 
|  | BranchProbabilityInfo BPI; | 
|  | BPI.calculate(F, LI, &TLI, &DT, &PDT); | 
|  | return BPI; | 
|  | } | 
|  |  | 
|  | PreservedAnalyses | 
|  | BranchProbabilityPrinterPass::run(Function &F, FunctionAnalysisManager &AM) { | 
|  | OS << "Printing analysis results of BPI for function " | 
|  | << "'" << F.getName() << "':" | 
|  | << "\n"; | 
|  | AM.getResult<BranchProbabilityAnalysis>(F).print(OS); | 
|  | return PreservedAnalyses::all(); | 
|  | } |