llvm-6502/lib/Analysis/BranchProbabilityInfo.cpp
Chandler Carruth 0b8c9a80f2 Move all of the header files which are involved in modelling the LLVM IR
into their new header subdirectory: include/llvm/IR. This matches the
directory structure of lib, and begins to correct a long standing point
of file layout clutter in LLVM.

There are still more header files to move here, but I wanted to handle
them in separate commits to make tracking what files make sense at each
layer easier.

The only really questionable files here are the target intrinsic
tablegen files. But that's a battle I'd rather not fight today.

I've updated both CMake and Makefile build systems (I think, and my
tests think, but I may have missed something).

I've also re-sorted the includes throughout the project. I'll be
committing updates to Clang, DragonEgg, and Polly momentarily.

git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@171366 91177308-0d34-0410-b5e6-96231b3b80d8
2013-01-02 11:36:10 +00:00

559 lines
18 KiB
C++

//===-- BranchProbabilityInfo.cpp - Branch Probability Analysis -----------===//
//
// 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/Analysis/BranchProbabilityInfo.h"
#include "llvm/ADT/PostOrderIterator.h"
#include "llvm/Analysis/LoopInfo.h"
#include "llvm/IR/Constants.h"
#include "llvm/IR/Function.h"
#include "llvm/IR/Instructions.h"
#include "llvm/IR/LLVMContext.h"
#include "llvm/IR/Metadata.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;
/// \brief Unreachable-terminating branch taken weight.
///
/// This is the weight for a branch being taken to a block that terminates
/// (eventually) in unreachable. These are predicted as unlikely as possible.
static const uint32_t UR_TAKEN_WEIGHT = 1;
/// \brief Unreachable-terminating branch not-taken weight.
///
/// This is the weight for a branch not being taken toward a block that
/// terminates (eventually) in unreachable. Such a branch is essentially never
/// taken. Set the weight to an absurdly high value so that nested loops don't
/// easily subsume it.
static const uint32_t UR_NONTAKEN_WEIGHT = 1024*1024 - 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;
/// \brief Invoke-terminating normal branch taken weight
///
/// This is the weight for branching to the normal destination of an invoke
/// instruction. We expect this to happen most of the time. Set the weight to an
/// absurdly high value so that nested loops subsume it.
static const uint32_t IH_TAKEN_WEIGHT = 1024 * 1024 - 1;
/// \brief Invoke-terminating normal branch not-taken weight.
///
/// This is the weight for branching to the unwind destination of an invoke
/// instruction. This is essentially never taken.
static const uint32_t IH_NONTAKEN_WEIGHT = 1;
// 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;
static uint32_t getMaxWeightFor(BasicBlock *BB) {
return UINT32_MAX / BB->getTerminator()->getNumSuccessors();
}
/// \brief Calculate edge weights for successors lead to unreachable.
///
/// Predict that a successor which leads necessarily to an
/// unreachable-terminated block as extremely unlikely.
bool BranchProbabilityInfo::calcUnreachableHeuristics(BasicBlock *BB) {
TerminatorInst *TI = BB->getTerminator();
if (TI->getNumSuccessors() == 0) {
if (isa<UnreachableInst>(TI))
PostDominatedByUnreachable.insert(BB);
return false;
}
SmallVector<unsigned, 4> UnreachableEdges;
SmallVector<unsigned, 4> ReachableEdges;
for (succ_iterator I = succ_begin(BB), E = succ_end(BB); I != E; ++I) {
if (PostDominatedByUnreachable.count(*I))
UnreachableEdges.push_back(I.getSuccessorIndex());
else
ReachableEdges.push_back(I.getSuccessorIndex());
}
// If all successors are in the set of blocks post-dominated by unreachable,
// this block is too.
if (UnreachableEdges.size() == TI->getNumSuccessors())
PostDominatedByUnreachable.insert(BB);
// Skip probabilities if this block has a single successor or if all were
// reachable.
if (TI->getNumSuccessors() == 1 || UnreachableEdges.empty())
return false;
uint32_t UnreachableWeight =
std::max(UR_TAKEN_WEIGHT / (unsigned)UnreachableEdges.size(), MIN_WEIGHT);
for (SmallVector<unsigned, 4>::iterator I = UnreachableEdges.begin(),
E = UnreachableEdges.end();
I != E; ++I)
setEdgeWeight(BB, *I, UnreachableWeight);
if (ReachableEdges.empty())
return true;
uint32_t ReachableWeight =
std::max(UR_NONTAKEN_WEIGHT / (unsigned)ReachableEdges.size(),
NORMAL_WEIGHT);
for (SmallVector<unsigned, 4>::iterator I = ReachableEdges.begin(),
E = ReachableEdges.end();
I != E; ++I)
setEdgeWeight(BB, *I, ReachableWeight);
return true;
}
// 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, i, Weights[i]);
return true;
}
// 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());
// p != 0 -> isProb = true
// p == 0 -> isProb = false
// p != q -> isProb = true
// p == q -> isProb = false;
unsigned TakenIdx = 0, NonTakenIdx = 1;
bool isProb = CI->getPredicate() == ICmpInst::ICMP_NE;
if (!isProb)
std::swap(TakenIdx, NonTakenIdx);
setEdgeWeight(BB, TakenIdx, PH_TAKEN_WEIGHT);
setEdgeWeight(BB, NonTakenIdx, 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) {
Loop *L = LI->getLoopFor(BB);
if (!L)
return false;
SmallVector<unsigned, 8> BackEdges;
SmallVector<unsigned, 8> ExitingEdges;
SmallVector<unsigned, 8> InEdges; // Edges from header to the loop.
for (succ_iterator I = succ_begin(BB), E = succ_end(BB); I != E; ++I) {
if (!L->contains(*I))
ExitingEdges.push_back(I.getSuccessorIndex());
else if (L->getHeader() == *I)
BackEdges.push_back(I.getSuccessorIndex());
else
InEdges.push_back(I.getSuccessorIndex());
}
if (uint32_t numBackEdges = BackEdges.size()) {
uint32_t backWeight = LBH_TAKEN_WEIGHT / numBackEdges;
if (backWeight < NORMAL_WEIGHT)
backWeight = NORMAL_WEIGHT;
for (SmallVector<unsigned, 8>::iterator EI = BackEdges.begin(),
EE = BackEdges.end(); EI != EE; ++EI) {
setEdgeWeight(BB, *EI, backWeight);
}
}
if (uint32_t numInEdges = InEdges.size()) {
uint32_t inWeight = LBH_TAKEN_WEIGHT / numInEdges;
if (inWeight < NORMAL_WEIGHT)
inWeight = NORMAL_WEIGHT;
for (SmallVector<unsigned, 8>::iterator EI = InEdges.begin(),
EE = InEdges.end(); EI != EE; ++EI) {
setEdgeWeight(BB, *EI, inWeight);
}
}
if (uint32_t numExitingEdges = ExitingEdges.size()) {
uint32_t exitWeight = LBH_NONTAKEN_WEIGHT / numExitingEdges;
if (exitWeight < MIN_WEIGHT)
exitWeight = MIN_WEIGHT;
for (SmallVector<unsigned, 8>::iterator EI = ExitingEdges.begin(),
EE = ExitingEdges.end(); EI != EE; ++EI) {
setEdgeWeight(BB, *EI, 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;
}
unsigned TakenIdx = 0, NonTakenIdx = 1;
if (!isProb)
std::swap(TakenIdx, NonTakenIdx);
setEdgeWeight(BB, TakenIdx, ZH_TAKEN_WEIGHT);
setEdgeWeight(BB, NonTakenIdx, 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;
}
unsigned TakenIdx = 0, NonTakenIdx = 1;
if (!isProb)
std::swap(TakenIdx, NonTakenIdx);
setEdgeWeight(BB, TakenIdx, FPH_TAKEN_WEIGHT);
setEdgeWeight(BB, NonTakenIdx, FPH_NONTAKEN_WEIGHT);
return true;
}
bool BranchProbabilityInfo::calcInvokeHeuristics(BasicBlock *BB) {
InvokeInst *II = dyn_cast<InvokeInst>(BB->getTerminator());
if (!II)
return false;
setEdgeWeight(BB, 0/*Index for Normal*/, IH_TAKEN_WEIGHT);
setEdgeWeight(BB, 1/*Index for Unwind*/, IH_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>();
assert(PostDominatedByUnreachable.empty());
// Walk the basic blocks in post-order so that we can build up state about
// the successors of a block iteratively.
for (po_iterator<BasicBlock *> I = po_begin(&F.getEntryBlock()),
E = po_end(&F.getEntryBlock());
I != E; ++I) {
DEBUG(dbgs() << "Computing probabilities for " << I->getName() << "\n");
if (calcUnreachableHeuristics(*I))
continue;
if (calcMetadataWeights(*I))
continue;
if (calcLoopBranchHeuristics(*I))
continue;
if (calcPointerHeuristics(*I))
continue;
if (calcZeroHeuristics(*I))
continue;
if (calcFloatingPointHeuristics(*I))
continue;
calcInvokeHeuristics(*I);
}
PostDominatedByUnreachable.clear();
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) {
uint32_t Weight = getEdgeWeight(BB, I.getSuccessorIndex());
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;
}
/// Get the raw edge weight for the edge. If can't find it, return
/// DEFAULT_WEIGHT value. Here an edge is specified using PredBlock and an index
/// to the successors.
uint32_t BranchProbabilityInfo::
getEdgeWeight(const BasicBlock *Src, unsigned IndexInSuccessors) const {
DenseMap<Edge, uint32_t>::const_iterator I =
Weights.find(std::make_pair(Src, IndexInSuccessors));
if (I != Weights.end())
return I->second;
return DEFAULT_WEIGHT;
}
/// Get the raw edge weight calculated for the block pair. This returns the sum
/// of all raw edge weights from Src to Dst.
uint32_t BranchProbabilityInfo::
getEdgeWeight(const BasicBlock *Src, const BasicBlock *Dst) const {
uint32_t Weight = 0;
DenseMap<Edge, uint32_t>::const_iterator MapI;
for (succ_const_iterator I = succ_begin(Src), E = succ_end(Src); I != E; ++I)
if (*I == Dst) {
MapI = Weights.find(std::make_pair(Src, I.getSuccessorIndex()));
if (MapI != Weights.end())
Weight += MapI->second;
}
return (Weight == 0) ? DEFAULT_WEIGHT : Weight;
}
/// Set the edge weight for a given edge specified by PredBlock and an index
/// to the successors.
void BranchProbabilityInfo::
setEdgeWeight(const BasicBlock *Src, unsigned IndexInSuccessors,
uint32_t Weight) {
Weights[std::make_pair(Src, IndexInSuccessors)] = Weight;
DEBUG(dbgs() << "set edge " << Src->getName() << " -> "
<< IndexInSuccessors << " successor weight to "
<< Weight << "\n");
}
/// Get an edge's probability, relative to other out-edges from Src.
BranchProbability BranchProbabilityInfo::
getEdgeProbability(const BasicBlock *Src, unsigned IndexInSuccessors) const {
uint32_t N = getEdgeWeight(Src, IndexInSuccessors);
uint32_t D = getSumForBlock(Src);
return BranchProbability(N, D);
}
/// Get the probability of going from Src to Dst. It returns the sum of all
/// probabilities for edges from Src to Dst.
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->getName() << " -> " << Dst->getName()
<< " probability is " << Prob
<< (isEdgeHot(Src, Dst) ? " [HOT edge]\n" : "\n");
return OS;
}