llvm/lib/Analysis/BranchProbabilityInfo.cpp
Chandler Carruth b068bbbaec Simplify the design of BranchProbabilityInfo by collapsing it into
a single class. Previously it was split between two classes, one
internal and one external. The concern seemed to center around exposing
the weights used, but those can remain confined to the implementation
file.

Having a single class to maintain the state and analyses in use will
also simplify several of the enhancements I want to make to our static
heuristics.

git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@142783 91177308-0d34-0410-b5e6-96231b3b80d8
2011-10-24 01:40:45 +00:00

514 lines
15 KiB
C++

//===-- BranchProbabilityInfo.cpp - Branch Probability Analysis -*- C++ -*-===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
//
// Loops should be simplified before this analysis.
//
//===----------------------------------------------------------------------===//
#include "llvm/Constants.h"
#include "llvm/Function.h"
#include "llvm/Instructions.h"
#include "llvm/LLVMContext.h"
#include "llvm/Metadata.h"
#include "llvm/Analysis/BranchProbabilityInfo.h"
#include "llvm/Analysis/LoopInfo.h"
#include "llvm/Support/CFG.h"
#include "llvm/Support/Debug.h"
using namespace llvm;
INITIALIZE_PASS_BEGIN(BranchProbabilityInfo, "branch-prob",
"Branch Probability Analysis", false, true)
INITIALIZE_PASS_DEPENDENCY(LoopInfo)
INITIALIZE_PASS_END(BranchProbabilityInfo, "branch-prob",
"Branch Probability Analysis", false, true)
char BranchProbabilityInfo::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;
static const uint32_t RH_TAKEN_WEIGHT = 24;
static const uint32_t RH_NONTAKEN_WEIGHT = 8;
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;
// Standard weight value. Used when none of the heuristics set weight for
// the edge.
static const uint32_t NORMAL_WEIGHT = 16;
// Minimum weight of an edge. Please note, that weight is NEVER 0.
static const uint32_t MIN_WEIGHT = 1;
// Return TRUE if BB leads directly to a Return Instruction.
static bool isReturningBlock(BasicBlock *BB) {
SmallPtrSet<BasicBlock *, 8> Visited;
while (true) {
TerminatorInst *TI = BB->getTerminator();
if (isa<ReturnInst>(TI))
return true;
if (TI->getNumSuccessors() > 1)
break;
// It is unreachable block which we can consider as a return instruction.
if (TI->getNumSuccessors() == 0)
return true;
Visited.insert(BB);
BB = TI->getSuccessor(0);
// Stop if cycle is detected.
if (Visited.count(BB))
return false;
}
return false;
}
static uint32_t getMaxWeightFor(BasicBlock *BB) {
return UINT32_MAX / BB->getTerminator()->getNumSuccessors();
}
// Propagate existing explicit probabilities from either profile data or
// 'expect' intrinsic processing.
bool BranchProbabilityInfo::calcMetadataWeights(BasicBlock *BB) {
TerminatorInst *TI = BB->getTerminator();
if (TI->getNumSuccessors() == 1)
return false;
if (!isa<BranchInst>(TI) && !isa<SwitchInst>(TI))
return false;
MDNode *WeightsNode = TI->getMetadata(LLVMContext::MD_prof);
if (!WeightsNode)
return false;
// 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, but
// don't add them until all weihts are present. Each weight value is clamped
// to [1, getMaxWeightFor(BB)].
uint32_t WeightLimit = getMaxWeightFor(BB);
SmallVector<uint32_t, 2> Weights;
Weights.reserve(TI->getNumSuccessors());
for (unsigned i = 1, e = WeightsNode->getNumOperands(); i != e; ++i) {
ConstantInt *Weight = dyn_cast<ConstantInt>(WeightsNode->getOperand(i));
if (!Weight)
return false;
Weights.push_back(
std::max<uint32_t>(1, Weight->getLimitedValue(WeightLimit)));
}
assert(Weights.size() == TI->getNumSuccessors() && "Checked above");
for (unsigned i = 0, e = TI->getNumSuccessors(); i != e; ++i)
setEdgeWeight(BB, TI->getSuccessor(i), Weights[i]);
return true;
}
// Calculate Edge Weights using "Return Heuristics". Predict a successor which
// leads directly to Return Instruction will not be taken.
bool BranchProbabilityInfo::calcReturnHeuristics(BasicBlock *BB){
if (BB->getTerminator()->getNumSuccessors() == 1)
return false;
SmallPtrSet<BasicBlock *, 4> ReturningEdges;
SmallPtrSet<BasicBlock *, 4> StayEdges;
for (succ_iterator I = succ_begin(BB), E = succ_end(BB); I != E; ++I) {
BasicBlock *Succ = *I;
if (isReturningBlock(Succ))
ReturningEdges.insert(Succ);
else
StayEdges.insert(Succ);
}
if (uint32_t numStayEdges = StayEdges.size()) {
uint32_t stayWeight = RH_TAKEN_WEIGHT / numStayEdges;
if (stayWeight < NORMAL_WEIGHT)
stayWeight = NORMAL_WEIGHT;
for (SmallPtrSet<BasicBlock *, 4>::iterator I = StayEdges.begin(),
E = StayEdges.end(); I != E; ++I)
setEdgeWeight(BB, *I, stayWeight);
}
if (uint32_t numRetEdges = ReturningEdges.size()) {
uint32_t retWeight = RH_NONTAKEN_WEIGHT / numRetEdges;
if (retWeight < MIN_WEIGHT)
retWeight = MIN_WEIGHT;
for (SmallPtrSet<BasicBlock *, 4>::iterator I = ReturningEdges.begin(),
E = ReturningEdges.end(); I != E; ++I) {
setEdgeWeight(BB, *I, retWeight);
}
}
return ReturningEdges.size() > 0;
}
// Calculate Edge Weights using "Pointer Heuristics". Predict a comparsion
// between two pointer or pointer and NULL will fail.
bool BranchProbabilityInfo::calcPointerHeuristics(BasicBlock *BB) {
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());
BasicBlock *Taken = BI->getSuccessor(0);
BasicBlock *NonTaken = BI->getSuccessor(1);
// 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(Taken, NonTaken);
setEdgeWeight(BB, Taken, PH_TAKEN_WEIGHT);
setEdgeWeight(BB, NonTaken, PH_NONTAKEN_WEIGHT);
return true;
}
// Calculate Edge Weights using "Loop Branch Heuristics". Predict backedges
// as taken, exiting edges as not-taken.
bool BranchProbabilityInfo::calcLoopBranchHeuristics(BasicBlock *BB) {
uint32_t numSuccs = BB->getTerminator()->getNumSuccessors();
Loop *L = LI->getLoopFor(BB);
if (!L)
return false;
SmallPtrSet<BasicBlock *, 8> BackEdges;
SmallPtrSet<BasicBlock *, 8> ExitingEdges;
SmallPtrSet<BasicBlock *, 8> InEdges; // Edges from header to the loop.
bool isHeader = BB == L->getHeader();
for (succ_iterator I = succ_begin(BB), E = succ_end(BB); I != E; ++I) {
BasicBlock *Succ = *I;
Loop *SuccL = LI->getLoopFor(Succ);
if (SuccL != L)
ExitingEdges.insert(Succ);
else if (Succ == L->getHeader())
BackEdges.insert(Succ);
else if (isHeader)
InEdges.insert(Succ);
}
if (uint32_t numBackEdges = BackEdges.size()) {
uint32_t backWeight = LBH_TAKEN_WEIGHT / numBackEdges;
if (backWeight < NORMAL_WEIGHT)
backWeight = NORMAL_WEIGHT;
for (SmallPtrSet<BasicBlock *, 8>::iterator EI = BackEdges.begin(),
EE = BackEdges.end(); EI != EE; ++EI) {
BasicBlock *Back = *EI;
setEdgeWeight(BB, Back, backWeight);
}
}
if (uint32_t numInEdges = InEdges.size()) {
uint32_t inWeight = LBH_TAKEN_WEIGHT / numInEdges;
if (inWeight < NORMAL_WEIGHT)
inWeight = NORMAL_WEIGHT;
for (SmallPtrSet<BasicBlock *, 8>::iterator EI = InEdges.begin(),
EE = InEdges.end(); EI != EE; ++EI) {
BasicBlock *Back = *EI;
setEdgeWeight(BB, Back, inWeight);
}
}
uint32_t numExitingEdges = ExitingEdges.size();
if (uint32_t numNonExitingEdges = numSuccs - numExitingEdges) {
uint32_t exitWeight = LBH_NONTAKEN_WEIGHT / numNonExitingEdges;
if (exitWeight < MIN_WEIGHT)
exitWeight = MIN_WEIGHT;
for (SmallPtrSet<BasicBlock *, 8>::iterator EI = ExitingEdges.begin(),
EE = ExitingEdges.end(); EI != EE; ++EI) {
BasicBlock *Exiting = *EI;
setEdgeWeight(BB, Exiting, exitWeight);
}
}
return true;
}
bool BranchProbabilityInfo::calcZeroHeuristics(BasicBlock *BB) {
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;
Value *RHS = CI->getOperand(1);
ConstantInt *CV = dyn_cast<ConstantInt>(RHS);
if (!CV)
return false;
bool isProb;
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->isAllOnesValue() && CI->getPredicate() == CmpInst::ICMP_SGT) {
// InstCombine canonicalizes X >= 0 into X > -1.
// X >= 0 -> Likely
isProb = true;
} else {
return false;
}
BasicBlock *Taken = BI->getSuccessor(0);
BasicBlock *NonTaken = BI->getSuccessor(1);
if (!isProb)
std::swap(Taken, NonTaken);
setEdgeWeight(BB, Taken, ZH_TAKEN_WEIGHT);
setEdgeWeight(BB, NonTaken, ZH_NONTAKEN_WEIGHT);
return true;
}
bool BranchProbabilityInfo::calcFloatingPointHeuristics(BasicBlock *BB) {
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;
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;
} else if (FCmp->getPredicate() == FCmpInst::FCMP_UNO) {
// isnan -> Unlikely
isProb = false;
} else {
return false;
}
BasicBlock *Taken = BI->getSuccessor(0);
BasicBlock *NonTaken = BI->getSuccessor(1);
if (!isProb)
std::swap(Taken, NonTaken);
setEdgeWeight(BB, Taken, FPH_TAKEN_WEIGHT);
setEdgeWeight(BB, NonTaken, FPH_NONTAKEN_WEIGHT);
return true;
}
void BranchProbabilityInfo::getAnalysisUsage(AnalysisUsage &AU) const {
AU.addRequired<LoopInfo>();
AU.setPreservesAll();
}
bool BranchProbabilityInfo::runOnFunction(Function &F) {
LastF = &F; // Store the last function we ran on for printing.
LI = &getAnalysis<LoopInfo>();
for (Function::iterator I = F.begin(), E = F.end(); I != E; ++I) {
if (calcMetadataWeights(I))
continue;
if (calcLoopBranchHeuristics(I))
continue;
if (calcReturnHeuristics(I))
continue;
if (calcPointerHeuristics(I))
continue;
if (calcZeroHeuristics(I))
continue;
calcFloatingPointHeuristics(I);
}
return false;
}
void BranchProbabilityInfo::print(raw_ostream &OS, const Module *) 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 (Function::const_iterator BI = LastF->begin(), BE = LastF->end();
BI != BE; ++BI) {
for (succ_const_iterator SI = succ_begin(BI), SE = succ_end(BI);
SI != SE; ++SI) {
printEdgeProbability(OS << " ", BI, *SI);
}
}
}
uint32_t BranchProbabilityInfo::getSumForBlock(const BasicBlock *BB) const {
uint32_t Sum = 0;
for (succ_const_iterator I = succ_begin(BB), E = succ_end(BB); I != E; ++I) {
const BasicBlock *Succ = *I;
uint32_t Weight = getEdgeWeight(BB, Succ);
uint32_t PrevSum = Sum;
Sum += Weight;
assert(Sum > PrevSum); (void) PrevSum;
}
return Sum;
}
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);
}
BasicBlock *BranchProbabilityInfo::getHotSucc(BasicBlock *BB) const {
uint32_t Sum = 0;
uint32_t MaxWeight = 0;
BasicBlock *MaxSucc = 0;
for (succ_iterator I = succ_begin(BB), E = succ_end(BB); I != E; ++I) {
BasicBlock *Succ = *I;
uint32_t Weight = getEdgeWeight(BB, Succ);
uint32_t PrevSum = Sum;
Sum += Weight;
assert(Sum > PrevSum); (void) PrevSum;
if (Weight > MaxWeight) {
MaxWeight = Weight;
MaxSucc = Succ;
}
}
// Hot probability is at least 4/5 = 80%
if (BranchProbability(MaxWeight, Sum) > BranchProbability(4, 5))
return MaxSucc;
return 0;
}
// Return edge's weight. If can't find it, return DEFAULT_WEIGHT value.
uint32_t BranchProbabilityInfo::
getEdgeWeight(const BasicBlock *Src, const BasicBlock *Dst) const {
Edge E(Src, Dst);
DenseMap<Edge, uint32_t>::const_iterator I = Weights.find(E);
if (I != Weights.end())
return I->second;
return DEFAULT_WEIGHT;
}
void BranchProbabilityInfo::
setEdgeWeight(const BasicBlock *Src, const BasicBlock *Dst, uint32_t Weight) {
Weights[std::make_pair(Src, Dst)] = Weight;
DEBUG(dbgs() << "set edge " << Src->getNameStr() << " -> "
<< Dst->getNameStr() << " weight to " << Weight
<< (isEdgeHot(Src, Dst) ? " [is HOT now]\n" : "\n"));
}
BranchProbability BranchProbabilityInfo::
getEdgeProbability(const BasicBlock *Src, const BasicBlock *Dst) const {
uint32_t N = getEdgeWeight(Src, Dst);
uint32_t D = getSumForBlock(Src);
return BranchProbability(N, D);
}
raw_ostream &
BranchProbabilityInfo::printEdgeProbability(raw_ostream &OS,
const BasicBlock *Src,
const BasicBlock *Dst) const {
const BranchProbability Prob = getEdgeProbability(Src, Dst);
OS << "edge " << Src->getNameStr() << " -> " << Dst->getNameStr()
<< " probability is " << Prob
<< (isEdgeHot(Src, Dst) ? " [HOT edge]\n" : "\n");
return OS;
}