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llvm-for-llvmta/lib/Analysis/BranchProbabilityInfo.cpp

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2022-04-25 10:02:23 +02:00
//===- 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/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/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 <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);
static const uint32_t PH_TAKEN_WEIGHT = 20;
static const uint32_t PH_NONTAKEN_WEIGHT = 12;
static const uint32_t ZH_TAKEN_WEIGHT = 20;
static const uint32_t ZH_NONTAKEN_WEIGHT = 12;
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;
/// 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 *>(BB));
}
}
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)))
return false;
MDNode *WeightsNode = TI->getMetadata(LLVMContext::MD_prof);
if (!WeightsNode)
return false;
// Check that the number of successors is manageable.
assert(TI->getNumSuccessors() < UINT32_MAX && "Too many successors");
// Ensure there are weights for all of the successors. Note that the first
// operand to the metadata node is a name, not a weight.
if (WeightsNode->getNumOperands() != TI->getNumSuccessors() + 1)
return false;
// 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;
Weights.reserve(TI->getNumSuccessors());
for (unsigned I = 1, E = WeightsNode->getNumOperands(); I != E; ++I) {
ConstantInt *Weight =
mdconst::dyn_extract<ConstantInt>(WeightsNode->getOperand(I));
if (!Weight)
return false;
assert(Weight->getValue().getActiveBits() <= 32 &&
"Too many bits for uint32_t");
Weights.push_back(Weight->getZExtValue());
WeightSum += Weights.back();
const LoopBlock SrcLoopBB = getLoopBlock(BB);
const LoopBlock DstLoopBB = getLoopBlock(TI->getSuccessor(I - 1));
auto EstimatedWeight = getEstimatedEdgeWeight({SrcLoopBB, DstLoopBB});
if (EstimatedWeight &&
EstimatedWeight.getValue() <=
static_cast<uint32_t>(BlockExecWeight::UNREACHABLE))
UnreachableIdxs.push_back(I - 1);
else
ReachableIdxs.push_back(I - 1);
}
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());
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.back();
WorkList.pop_back();
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_succ_iterator I = succ_begin(BB), E = succ_end(BB); I != E; ++I) {
const BasicBlock *SuccBB = *I;
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_succ_iterator SI = succ_begin(&BI), SE = succ_end(&BI); SI != SE;
++SI) {
printEdgeProbability(OS << " ", &BI, *SI);
}
}
}
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 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();
}