forked from OSchip/llvm-project
1360 lines
50 KiB
C++
1360 lines
50 KiB
C++
//===- BranchProbabilityInfo.cpp - Branch Probability Analysis ------------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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//
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// Loops should be simplified before this analysis.
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//
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//===----------------------------------------------------------------------===//
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#include "llvm/Analysis/BranchProbabilityInfo.h"
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#include "llvm/ADT/PostOrderIterator.h"
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#include "llvm/ADT/SCCIterator.h"
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#include "llvm/ADT/STLExtras.h"
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#include "llvm/ADT/SmallVector.h"
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#include "llvm/Analysis/LoopInfo.h"
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#include "llvm/Analysis/PostDominators.h"
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#include "llvm/Analysis/TargetLibraryInfo.h"
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#include "llvm/IR/Attributes.h"
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#include "llvm/IR/BasicBlock.h"
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#include "llvm/IR/CFG.h"
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#include "llvm/IR/Constants.h"
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#include "llvm/IR/Dominators.h"
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#include "llvm/IR/Function.h"
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#include "llvm/IR/InstrTypes.h"
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#include "llvm/IR/Instruction.h"
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#include "llvm/IR/Instructions.h"
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#include "llvm/IR/LLVMContext.h"
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#include "llvm/IR/Metadata.h"
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#include "llvm/IR/PassManager.h"
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#include "llvm/IR/Type.h"
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#include "llvm/IR/Value.h"
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#include "llvm/InitializePasses.h"
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#include "llvm/Pass.h"
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#include "llvm/Support/BranchProbability.h"
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#include "llvm/Support/Casting.h"
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#include "llvm/Support/CommandLine.h"
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#include "llvm/Support/Debug.h"
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#include "llvm/Support/raw_ostream.h"
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#include <cassert>
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#include <cstdint>
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#include <iterator>
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#include <utility>
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using namespace llvm;
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#define DEBUG_TYPE "branch-prob"
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static cl::opt<bool> PrintBranchProb(
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"print-bpi", cl::init(false), cl::Hidden,
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cl::desc("Print the branch probability info."));
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cl::opt<std::string> PrintBranchProbFuncName(
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"print-bpi-func-name", cl::Hidden,
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cl::desc("The option to specify the name of the function "
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"whose branch probability info is printed."));
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INITIALIZE_PASS_BEGIN(BranchProbabilityInfoWrapperPass, "branch-prob",
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"Branch Probability Analysis", false, true)
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INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass)
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INITIALIZE_PASS_DEPENDENCY(TargetLibraryInfoWrapperPass)
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INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass)
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INITIALIZE_PASS_DEPENDENCY(PostDominatorTreeWrapperPass)
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INITIALIZE_PASS_END(BranchProbabilityInfoWrapperPass, "branch-prob",
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"Branch Probability Analysis", false, true)
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BranchProbabilityInfoWrapperPass::BranchProbabilityInfoWrapperPass()
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: FunctionPass(ID) {
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initializeBranchProbabilityInfoWrapperPassPass(
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*PassRegistry::getPassRegistry());
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}
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char BranchProbabilityInfoWrapperPass::ID = 0;
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// Weights are for internal use only. They are used by heuristics to help to
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// estimate edges' probability. Example:
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//
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// Using "Loop Branch Heuristics" we predict weights of edges for the
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// block BB2.
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// ...
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// |
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// V
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// BB1<-+
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// | |
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// | | (Weight = 124)
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// V |
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// BB2--+
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// |
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// | (Weight = 4)
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// V
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// BB3
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//
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// Probability of the edge BB2->BB1 = 124 / (124 + 4) = 0.96875
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// Probability of the edge BB2->BB3 = 4 / (124 + 4) = 0.03125
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static const uint32_t LBH_TAKEN_WEIGHT = 124;
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static const uint32_t LBH_NONTAKEN_WEIGHT = 4;
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/// Unreachable-terminating branch taken probability.
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///
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/// This is the probability for a branch being taken to a block that terminates
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/// (eventually) in unreachable. These are predicted as unlikely as possible.
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/// All reachable probability will proportionally share the remaining part.
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static const BranchProbability UR_TAKEN_PROB = BranchProbability::getRaw(1);
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static const uint32_t PH_TAKEN_WEIGHT = 20;
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static const uint32_t PH_NONTAKEN_WEIGHT = 12;
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static const uint32_t ZH_TAKEN_WEIGHT = 20;
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static const uint32_t ZH_NONTAKEN_WEIGHT = 12;
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static const uint32_t FPH_TAKEN_WEIGHT = 20;
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static const uint32_t FPH_NONTAKEN_WEIGHT = 12;
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/// This is the probability for an ordered floating point comparison.
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static const uint32_t FPH_ORD_WEIGHT = 1024 * 1024 - 1;
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/// This is the probability for an unordered floating point comparison, it means
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/// one or two of the operands are NaN. Usually it is used to test for an
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/// exceptional case, so the result is unlikely.
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static const uint32_t FPH_UNO_WEIGHT = 1;
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/// Set of dedicated "absolute" execution weights for a block. These weights are
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/// meaningful relative to each other and their derivatives only.
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enum class BlockExecWeight : std::uint32_t {
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/// Special weight used for cases with exact zero probability.
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ZERO = 0x0,
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/// Minimal possible non zero weight.
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LOWEST_NON_ZERO = 0x1,
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/// Weight to an 'unreachable' block.
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UNREACHABLE = ZERO,
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/// Weight to a block containing non returning call.
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NORETURN = LOWEST_NON_ZERO,
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/// Weight to 'unwind' block of an invoke instruction.
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UNWIND = LOWEST_NON_ZERO,
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/// Weight to a 'cold' block. Cold blocks are the ones containing calls marked
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/// with attribute 'cold'.
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COLD = 0xffff,
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/// Default weight is used in cases when there is no dedicated execution
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/// weight set. It is not propagated through the domination line either.
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DEFAULT = 0xfffff
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};
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BranchProbabilityInfo::SccInfo::SccInfo(const Function &F) {
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// Record SCC numbers of blocks in the CFG to identify irreducible loops.
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// FIXME: We could only calculate this if the CFG is known to be irreducible
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// (perhaps cache this info in LoopInfo if we can easily calculate it there?).
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int SccNum = 0;
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for (scc_iterator<const Function *> It = scc_begin(&F); !It.isAtEnd();
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++It, ++SccNum) {
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// Ignore single-block SCCs since they either aren't loops or LoopInfo will
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// catch them.
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const std::vector<const BasicBlock *> &Scc = *It;
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if (Scc.size() == 1)
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continue;
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LLVM_DEBUG(dbgs() << "BPI: SCC " << SccNum << ":");
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for (const auto *BB : Scc) {
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LLVM_DEBUG(dbgs() << " " << BB->getName());
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SccNums[BB] = SccNum;
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calculateSccBlockType(BB, SccNum);
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}
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LLVM_DEBUG(dbgs() << "\n");
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}
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}
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int BranchProbabilityInfo::SccInfo::getSCCNum(const BasicBlock *BB) const {
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auto SccIt = SccNums.find(BB);
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if (SccIt == SccNums.end())
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return -1;
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return SccIt->second;
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}
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void BranchProbabilityInfo::SccInfo::getSccEnterBlocks(
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int SccNum, SmallVectorImpl<BasicBlock *> &Enters) const {
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for (auto MapIt : SccBlocks[SccNum]) {
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const auto *BB = MapIt.first;
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if (isSCCHeader(BB, SccNum))
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for (const auto *Pred : predecessors(BB))
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if (getSCCNum(Pred) != SccNum)
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Enters.push_back(const_cast<BasicBlock *>(BB));
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}
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}
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void BranchProbabilityInfo::SccInfo::getSccExitBlocks(
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int SccNum, SmallVectorImpl<BasicBlock *> &Exits) const {
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for (auto MapIt : SccBlocks[SccNum]) {
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const auto *BB = MapIt.first;
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if (isSCCExitingBlock(BB, SccNum))
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for (const auto *Succ : successors(BB))
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if (getSCCNum(Succ) != SccNum)
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Exits.push_back(const_cast<BasicBlock *>(BB));
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}
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}
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uint32_t BranchProbabilityInfo::SccInfo::getSccBlockType(const BasicBlock *BB,
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int SccNum) const {
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assert(getSCCNum(BB) == SccNum);
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assert(SccBlocks.size() > static_cast<unsigned>(SccNum) && "Unknown SCC");
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const auto &SccBlockTypes = SccBlocks[SccNum];
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auto It = SccBlockTypes.find(BB);
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if (It != SccBlockTypes.end()) {
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return It->second;
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}
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return Inner;
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}
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void BranchProbabilityInfo::SccInfo::calculateSccBlockType(const BasicBlock *BB,
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int SccNum) {
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assert(getSCCNum(BB) == SccNum);
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uint32_t BlockType = Inner;
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if (llvm::any_of(predecessors(BB), [&](const BasicBlock *Pred) {
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// Consider any block that is an entry point to the SCC as
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// a header.
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return getSCCNum(Pred) != SccNum;
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}))
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BlockType |= Header;
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if (llvm::any_of(successors(BB), [&](const BasicBlock *Succ) {
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return getSCCNum(Succ) != SccNum;
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}))
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BlockType |= Exiting;
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// Lazily compute the set of headers for a given SCC and cache the results
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// in the SccHeaderMap.
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if (SccBlocks.size() <= static_cast<unsigned>(SccNum))
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SccBlocks.resize(SccNum + 1);
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auto &SccBlockTypes = SccBlocks[SccNum];
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if (BlockType != Inner) {
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bool IsInserted;
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std::tie(std::ignore, IsInserted) =
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SccBlockTypes.insert(std::make_pair(BB, BlockType));
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assert(IsInserted && "Duplicated block in SCC");
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}
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}
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BranchProbabilityInfo::LoopBlock::LoopBlock(const BasicBlock *BB,
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const LoopInfo &LI,
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const SccInfo &SccI)
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: BB(BB) {
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LD.first = LI.getLoopFor(BB);
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if (!LD.first) {
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LD.second = SccI.getSCCNum(BB);
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}
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}
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bool BranchProbabilityInfo::isLoopEnteringEdge(const LoopEdge &Edge) const {
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const auto &SrcBlock = Edge.first;
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const auto &DstBlock = Edge.second;
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return (DstBlock.getLoop() &&
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!DstBlock.getLoop()->contains(SrcBlock.getLoop())) ||
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// Assume that SCCs can't be nested.
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(DstBlock.getSccNum() != -1 &&
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SrcBlock.getSccNum() != DstBlock.getSccNum());
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}
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bool BranchProbabilityInfo::isLoopExitingEdge(const LoopEdge &Edge) const {
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return isLoopEnteringEdge({Edge.second, Edge.first});
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}
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bool BranchProbabilityInfo::isLoopEnteringExitingEdge(
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const LoopEdge &Edge) const {
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return isLoopEnteringEdge(Edge) || isLoopExitingEdge(Edge);
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}
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bool BranchProbabilityInfo::isLoopBackEdge(const LoopEdge &Edge) const {
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const auto &SrcBlock = Edge.first;
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const auto &DstBlock = Edge.second;
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return SrcBlock.belongsToSameLoop(DstBlock) &&
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((DstBlock.getLoop() &&
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DstBlock.getLoop()->getHeader() == DstBlock.getBlock()) ||
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(DstBlock.getSccNum() != -1 &&
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SccI->isSCCHeader(DstBlock.getBlock(), DstBlock.getSccNum())));
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}
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void BranchProbabilityInfo::getLoopEnterBlocks(
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const LoopBlock &LB, SmallVectorImpl<BasicBlock *> &Enters) const {
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if (LB.getLoop()) {
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auto *Header = LB.getLoop()->getHeader();
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Enters.append(pred_begin(Header), pred_end(Header));
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} else {
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assert(LB.getSccNum() != -1 && "LB doesn't belong to any loop?");
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SccI->getSccEnterBlocks(LB.getSccNum(), Enters);
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}
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}
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void BranchProbabilityInfo::getLoopExitBlocks(
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const LoopBlock &LB, SmallVectorImpl<BasicBlock *> &Exits) const {
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if (LB.getLoop()) {
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LB.getLoop()->getExitBlocks(Exits);
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} else {
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assert(LB.getSccNum() != -1 && "LB doesn't belong to any loop?");
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SccI->getSccExitBlocks(LB.getSccNum(), Exits);
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}
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}
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// Propagate existing explicit probabilities from either profile data or
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// 'expect' intrinsic processing. Examine metadata against unreachable
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// heuristic. The probability of the edge coming to unreachable block is
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// set to min of metadata and unreachable heuristic.
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bool BranchProbabilityInfo::calcMetadataWeights(const BasicBlock *BB) {
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const Instruction *TI = BB->getTerminator();
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assert(TI->getNumSuccessors() > 1 && "expected more than one successor!");
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if (!(isa<BranchInst>(TI) || isa<SwitchInst>(TI) || isa<IndirectBrInst>(TI) ||
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isa<InvokeInst>(TI)))
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return false;
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MDNode *WeightsNode = TI->getMetadata(LLVMContext::MD_prof);
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if (!WeightsNode)
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return false;
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// Check that the number of successors is manageable.
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assert(TI->getNumSuccessors() < UINT32_MAX && "Too many successors");
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// Ensure there are weights for all of the successors. Note that the first
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// operand to the metadata node is a name, not a weight.
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if (WeightsNode->getNumOperands() != TI->getNumSuccessors() + 1)
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return false;
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// Build up the final weights that will be used in a temporary buffer.
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// Compute the sum of all weights to later decide whether they need to
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// be scaled to fit in 32 bits.
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uint64_t WeightSum = 0;
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SmallVector<uint32_t, 2> Weights;
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SmallVector<unsigned, 2> UnreachableIdxs;
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SmallVector<unsigned, 2> ReachableIdxs;
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Weights.reserve(TI->getNumSuccessors());
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for (unsigned I = 1, E = WeightsNode->getNumOperands(); I != E; ++I) {
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ConstantInt *Weight =
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mdconst::dyn_extract<ConstantInt>(WeightsNode->getOperand(I));
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if (!Weight)
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return false;
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assert(Weight->getValue().getActiveBits() <= 32 &&
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"Too many bits for uint32_t");
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Weights.push_back(Weight->getZExtValue());
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WeightSum += Weights.back();
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const LoopBlock SrcLoopBB = getLoopBlock(BB);
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const LoopBlock DstLoopBB = getLoopBlock(TI->getSuccessor(I - 1));
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auto EstimatedWeight = getEstimatedEdgeWeight({SrcLoopBB, DstLoopBB});
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if (EstimatedWeight &&
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EstimatedWeight.getValue() <=
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static_cast<uint32_t>(BlockExecWeight::UNREACHABLE))
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UnreachableIdxs.push_back(I - 1);
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else
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ReachableIdxs.push_back(I - 1);
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}
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assert(Weights.size() == TI->getNumSuccessors() && "Checked above");
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// If the sum of weights does not fit in 32 bits, scale every weight down
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// accordingly.
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uint64_t ScalingFactor =
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(WeightSum > UINT32_MAX) ? WeightSum / UINT32_MAX + 1 : 1;
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if (ScalingFactor > 1) {
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WeightSum = 0;
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for (unsigned I = 0, E = TI->getNumSuccessors(); I != E; ++I) {
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Weights[I] /= ScalingFactor;
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WeightSum += Weights[I];
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}
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}
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assert(WeightSum <= UINT32_MAX &&
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"Expected weights to scale down to 32 bits");
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if (WeightSum == 0 || ReachableIdxs.size() == 0) {
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for (unsigned I = 0, E = TI->getNumSuccessors(); I != E; ++I)
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Weights[I] = 1;
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WeightSum = TI->getNumSuccessors();
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}
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// Set the probability.
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SmallVector<BranchProbability, 2> BP;
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for (unsigned I = 0, E = TI->getNumSuccessors(); I != E; ++I)
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BP.push_back({ Weights[I], static_cast<uint32_t>(WeightSum) });
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// Examine the metadata against unreachable heuristic.
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// If the unreachable heuristic is more strong then we use it for this edge.
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if (UnreachableIdxs.size() == 0 || ReachableIdxs.size() == 0) {
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setEdgeProbability(BB, BP);
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return true;
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}
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auto UnreachableProb = UR_TAKEN_PROB;
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for (auto I : UnreachableIdxs)
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if (UnreachableProb < BP[I]) {
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BP[I] = UnreachableProb;
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}
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// Sum of all edge probabilities must be 1.0. If we modified the probability
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// of some edges then we must distribute the introduced difference over the
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// reachable blocks.
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//
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// Proportional distribution: the relation between probabilities of the
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// reachable edges is kept unchanged. That is for any reachable edges i and j:
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// newBP[i] / newBP[j] == oldBP[i] / oldBP[j] =>
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// newBP[i] / oldBP[i] == newBP[j] / oldBP[j] == K
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// Where K is independent of i,j.
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// newBP[i] == oldBP[i] * K
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// We need to find K.
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// Make sum of all reachables of the left and right parts:
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// sum_of_reachable(newBP) == K * sum_of_reachable(oldBP)
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// Sum of newBP must be equal to 1.0:
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// sum_of_reachable(newBP) + sum_of_unreachable(newBP) == 1.0 =>
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// sum_of_reachable(newBP) = 1.0 - sum_of_unreachable(newBP)
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// Where sum_of_unreachable(newBP) is what has been just changed.
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// Finally:
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// K == sum_of_reachable(newBP) / sum_of_reachable(oldBP) =>
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// K == (1.0 - sum_of_unreachable(newBP)) / sum_of_reachable(oldBP)
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BranchProbability NewUnreachableSum = BranchProbability::getZero();
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for (auto I : UnreachableIdxs)
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NewUnreachableSum += BP[I];
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BranchProbability NewReachableSum =
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BranchProbability::getOne() - NewUnreachableSum;
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BranchProbability OldReachableSum = BranchProbability::getZero();
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for (auto I : ReachableIdxs)
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OldReachableSum += BP[I];
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if (OldReachableSum != NewReachableSum) { // Anything to dsitribute?
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if (OldReachableSum.isZero()) {
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// If all oldBP[i] are zeroes then the proportional distribution results
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// in all zero probabilities and the error stays big. In this case we
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// evenly spread NewReachableSum over the reachable edges.
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BranchProbability PerEdge = NewReachableSum / ReachableIdxs.size();
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for (auto I : ReachableIdxs)
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BP[I] = PerEdge;
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} else {
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for (auto I : ReachableIdxs) {
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// We use uint64_t to avoid double rounding error of the following
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// calculation: BP[i] = BP[i] * NewReachableSum / OldReachableSum
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// The formula is taken from the private constructor
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// BranchProbability(uint32_t Numerator, uint32_t Denominator)
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uint64_t Mul = static_cast<uint64_t>(NewReachableSum.getNumerator()) *
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BP[I].getNumerator();
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uint32_t Div = static_cast<uint32_t>(
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divideNearest(Mul, OldReachableSum.getNumerator()));
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BP[I] = BranchProbability::getRaw(Div);
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}
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}
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}
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|
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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());
|
|
|
|
BranchProbability TakenProb(PH_TAKEN_WEIGHT,
|
|
PH_TAKEN_WEIGHT + PH_NONTAKEN_WEIGHT);
|
|
BranchProbability UntakenProb(PH_NONTAKEN_WEIGHT,
|
|
PH_TAKEN_WEIGHT + PH_NONTAKEN_WEIGHT);
|
|
|
|
// p != 0 -> isProb = true
|
|
// p == 0 -> isProb = false
|
|
// p != q -> isProb = true
|
|
// p == q -> isProb = false;
|
|
bool isProb = CI->getPredicate() == ICmpInst::ICMP_NE;
|
|
if (!isProb)
|
|
std::swap(TakenProb, UntakenProb);
|
|
|
|
setEdgeProbability(
|
|
BB, SmallVector<BranchProbability, 2>({TakenProb, UntakenProb}));
|
|
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
|
|
for (Instruction *I : llvm::reverse(InstChain)) {
|
|
CmpLHSConst = ConstantExpr::get(I->getOpcode(), CmpLHSConst,
|
|
cast<Constant>(I->getOperand(1)), true);
|
|
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);
|
|
}
|
|
}
|
|
}
|
|
|
|
Optional<uint32_t>
|
|
BranchProbabilityInfo::getEstimatedBlockWeight(const BasicBlock *BB) const {
|
|
auto WeightIt = EstimatedBlockWeight.find(BB);
|
|
if (WeightIt == EstimatedBlockWeight.end())
|
|
return None;
|
|
return WeightIt->second;
|
|
}
|
|
|
|
Optional<uint32_t>
|
|
BranchProbabilityInfo::getEstimatedLoopWeight(const LoopData &L) const {
|
|
auto WeightIt = EstimatedLoopWeight.find(L);
|
|
if (WeightIt == EstimatedLoopWeight.end())
|
|
return None;
|
|
return WeightIt->second;
|
|
}
|
|
|
|
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>
|
|
Optional<uint32_t> BranchProbabilityInfo::getMaxEstimatedEdgeWeight(
|
|
const LoopBlock &SrcLoopBB, iterator_range<IterT> Successors) const {
|
|
SmallVector<uint32_t, 4> Weights;
|
|
Optional<uint32_t> MaxWeight;
|
|
for (const BasicBlock *DstBB : Successors) {
|
|
const LoopBlock DstLoopBB = getLoopBlock(DstBB);
|
|
auto Weight = getEstimatedEdgeWeight({SrcLoopBB, DstLoopBB});
|
|
|
|
if (!Weight)
|
|
return None;
|
|
|
|
if (!MaxWeight || MaxWeight.getValue() < Weight.getValue())
|
|
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);
|
|
}
|
|
}
|
|
}
|
|
|
|
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 None;
|
|
}
|
|
|
|
// 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.getValue(), 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.getValue()});
|
|
// 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.getValue(),
|
|
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)) {
|
|
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.getValueOr(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.getValueOr(static_cast<uint32_t>(BlockExecWeight::DEFAULT)) /
|
|
2);
|
|
}
|
|
|
|
if (Weight)
|
|
FoundEstimatedWeight = true;
|
|
|
|
auto WeightVal =
|
|
Weight.getValueOr(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);
|
|
|
|
bool isProb;
|
|
if (Func == LibFunc_strcasecmp ||
|
|
Func == LibFunc_strcmp ||
|
|
Func == LibFunc_strncasecmp ||
|
|
Func == LibFunc_strncmp ||
|
|
Func == LibFunc_memcmp ||
|
|
Func == LibFunc_bcmp) {
|
|
// 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.
|
|
switch (CI->getPredicate()) {
|
|
case CmpInst::ICMP_EQ:
|
|
isProb = false;
|
|
break;
|
|
case CmpInst::ICMP_NE:
|
|
isProb = true;
|
|
break;
|
|
default:
|
|
return false;
|
|
}
|
|
} else if (CV->isZero()) {
|
|
switch (CI->getPredicate()) {
|
|
case CmpInst::ICMP_EQ:
|
|
// X == 0 -> Unlikely
|
|
isProb = false;
|
|
break;
|
|
case CmpInst::ICMP_NE:
|
|
// X != 0 -> Likely
|
|
isProb = true;
|
|
break;
|
|
case CmpInst::ICMP_SLT:
|
|
// X < 0 -> Unlikely
|
|
isProb = false;
|
|
break;
|
|
case CmpInst::ICMP_SGT:
|
|
// X > 0 -> Likely
|
|
isProb = true;
|
|
break;
|
|
default:
|
|
return false;
|
|
}
|
|
} else if (CV->isOne() && CI->getPredicate() == CmpInst::ICMP_SLT) {
|
|
// InstCombine canonicalizes X <= 0 into X < 1.
|
|
// X <= 0 -> Unlikely
|
|
isProb = false;
|
|
} else if (CV->isMinusOne()) {
|
|
switch (CI->getPredicate()) {
|
|
case CmpInst::ICMP_EQ:
|
|
// X == -1 -> Unlikely
|
|
isProb = false;
|
|
break;
|
|
case CmpInst::ICMP_NE:
|
|
// X != -1 -> Likely
|
|
isProb = true;
|
|
break;
|
|
case CmpInst::ICMP_SGT:
|
|
// InstCombine canonicalizes X >= 0 into X > -1.
|
|
// X >= 0 -> Likely
|
|
isProb = true;
|
|
break;
|
|
default:
|
|
return false;
|
|
}
|
|
} else {
|
|
return false;
|
|
}
|
|
|
|
BranchProbability TakenProb(ZH_TAKEN_WEIGHT,
|
|
ZH_TAKEN_WEIGHT + ZH_NONTAKEN_WEIGHT);
|
|
BranchProbability UntakenProb(ZH_NONTAKEN_WEIGHT,
|
|
ZH_TAKEN_WEIGHT + ZH_NONTAKEN_WEIGHT);
|
|
if (!isProb)
|
|
std::swap(TakenProb, UntakenProb);
|
|
|
|
setEdgeProbability(
|
|
BB, SmallVector<BranchProbability, 2>({TakenProb, UntakenProb}));
|
|
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;
|
|
|
|
uint32_t TakenWeight = FPH_TAKEN_WEIGHT;
|
|
uint32_t NontakenWeight = FPH_NONTAKEN_WEIGHT;
|
|
bool isProb;
|
|
if (FCmp->isEquality()) {
|
|
// f1 == f2 -> Unlikely
|
|
// f1 != f2 -> Likely
|
|
isProb = !FCmp->isTrueWhenEqual();
|
|
} else if (FCmp->getPredicate() == FCmpInst::FCMP_ORD) {
|
|
// !isnan -> Likely
|
|
isProb = true;
|
|
TakenWeight = FPH_ORD_WEIGHT;
|
|
NontakenWeight = FPH_UNO_WEIGHT;
|
|
} else if (FCmp->getPredicate() == FCmpInst::FCMP_UNO) {
|
|
// isnan -> Unlikely
|
|
isProb = false;
|
|
TakenWeight = FPH_ORD_WEIGHT;
|
|
NontakenWeight = FPH_UNO_WEIGHT;
|
|
} else {
|
|
return false;
|
|
}
|
|
|
|
BranchProbability TakenProb(TakenWeight, TakenWeight + NontakenWeight);
|
|
BranchProbability UntakenProb(NontakenWeight, TakenWeight + NontakenWeight);
|
|
if (!isProb)
|
|
std::swap(TakenProb, UntakenProb);
|
|
|
|
setEdgeProbability(
|
|
BB, SmallVector<BranchProbability, 2>({TakenProb, UntakenProb}));
|
|
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);
|
|
}
|
|
|
|
const BasicBlock *
|
|
BranchProbabilityInfo::getHotSucc(const BasicBlock *BB) const {
|
|
auto MaxProb = BranchProbability::getZero();
|
|
const BasicBlock *MaxSucc = nullptr;
|
|
|
|
for (const auto *Succ : successors(BB)) {
|
|
auto Prob = getEdgeProbability(BB, Succ);
|
|
if (Prob > MaxProb) {
|
|
MaxProb = Prob;
|
|
MaxSucc = Succ;
|
|
}
|
|
}
|
|
|
|
// Hot probability is at least 4/5 = 80%
|
|
if (MaxProb > BranchProbability(4, 5))
|
|
return MaxSucc;
|
|
|
|
return nullptr;
|
|
}
|
|
|
|
/// 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.find(std::make_pair(Src, 0)) == this->Probs.end())
|
|
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");
|
|
}
|
|
}
|
|
|
|
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 (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) {
|
|
BranchProbabilityInfo BPI;
|
|
BPI.calculate(F, AM.getResult<LoopAnalysis>(F),
|
|
&AM.getResult<TargetLibraryAnalysis>(F),
|
|
&AM.getResult<DominatorTreeAnalysis>(F),
|
|
&AM.getResult<PostDominatorTreeAnalysis>(F));
|
|
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();
|
|
}
|