Record whether the weights on out-edges from a MBB are normalized.

1. Create a utility function normalizeEdgeWeights() in MachineBranchProbabilityInfo that normalizes a list of edge weights so that the sum of then can fit in uint32_t.
2. Provide an interface in MachineBasicBlock to normalize its successors' weights.
3. Add a flag in MachineBasicBlock that tracks whether its successors' weights are normalized.
4. Provide an overload of getSumForBlock that accepts a non-const pointer to a MBB so that it can force normalizing this MBB's successors' weights.
5. Update several uses of getSumForBlock() by eliminating the once needed weight scale.

Differential Revision: http://reviews.llvm.org/D11442

llvm-svn: 244154
This commit is contained in:
Cong Hou 2015-08-05 22:01:20 +00:00
parent 758f3f542a
commit 36e7e52aa4
6 changed files with 106 additions and 42 deletions

View File

@ -65,6 +65,10 @@ class MachineBasicBlock : public ilist_node<MachineBasicBlock> {
Instructions Insts;
const BasicBlock *BB;
int Number;
/// A flag tracking whether the weights of all successors are normalized.
bool AreSuccWeightsNormalized;
MachineFunction *xParent;
/// Keep track of the predecessor / successor basicblocks.
@ -129,6 +133,9 @@ public:
const MachineFunction *getParent() const { return xParent; }
MachineFunction *getParent() { return xParent; }
/// Return whether all weights of successors are normalized.
bool areSuccWeightsNormalized() const { return AreSuccWeightsNormalized; }
/// MachineBasicBlock iterator that automatically skips over MIs that are
/// inside bundles (i.e. walk top level MIs only).
template<typename Ty, typename IterTy>
@ -384,6 +391,12 @@ public:
/// Set successor weight of a given iterator.
void setSuccWeight(succ_iterator I, uint32_t weight);
/// Normalize all succesor weights so that the sum of them does not exceed
/// UINT32_MAX. Return true if the weights are modified and false otherwise.
/// Note that weights that are modified after calling this function are not
/// guaranteed to be normalized.
bool normalizeSuccWeights();
/// Remove successor from the successors list of this MachineBasicBlock. The
/// Predecessors list of succ is automatically updated.
void removeSuccessor(MachineBasicBlock *succ);

View File

@ -59,6 +59,10 @@ public:
// adjustment. Any edge weights used with the sum should be divided by Scale.
uint32_t getSumForBlock(const MachineBasicBlock *MBB, uint32_t &Scale) const;
// Get sum of the block successors' weights, and force normalizing the
// successors' weights of MBB so that their sum fit within 32-bits.
uint32_t getSumForBlock(MachineBasicBlock *MBB) const;
// A 'Hot' edge is an edge which probability is >= 80%.
bool isEdgeHot(const MachineBasicBlock *Src,
const MachineBasicBlock *Dst) const;
@ -82,8 +86,34 @@ public:
raw_ostream &printEdgeProbability(raw_ostream &OS,
const MachineBasicBlock *Src,
const MachineBasicBlock *Dst) const;
// Normalize a list of weights by scaling them down so that the sum of them
// doesn't exceed UINT32_MAX. Return the scale.
template <class WeightList>
static uint32_t normalizeEdgeWeights(WeightList &Weights);
};
template <class WeightList>
uint32_t
MachineBranchProbabilityInfo::normalizeEdgeWeights(WeightList &Weights) {
assert(Weights.size() < UINT32_MAX && "Too many weights in the list!");
// First we compute the sum with 64-bits of precision.
uint64_t Sum = std::accumulate(Weights.begin(), Weights.end(), uint64_t(0));
// If the computed sum fits in 32-bits, we're done.
if (Sum <= UINT32_MAX)
return 1;
// Otherwise, compute the scale necessary to cause the weights to fit, and
// re-sum with that scale applied.
assert((Sum / UINT32_MAX) < UINT32_MAX &&
"The sum of weights exceeds UINT32_MAX^2!");
uint32_t Scale = (Sum / UINT32_MAX) + 1;
for (auto &W : Weights)
W /= Scale;
return Scale;
}
}

View File

@ -1232,15 +1232,17 @@ bool IfConverter::IfConvertTriangle(BBInfo &BBI, IfcvtKind Kind) {
bool HasEarlyExit = CvtBBI->FalseBB != nullptr;
uint64_t CvtNext = 0, CvtFalse = 0, BBNext = 0, BBCvt = 0, SumWeight = 0;
uint32_t WeightScale = 0;
if (HasEarlyExit) {
// Get weights before modifying CvtBBI->BB and BBI.BB.
// Explictly normalize the weights of all edges from CvtBBI->BB so that we
// are aware that the edge weights obtained below are normalized.
CvtBBI->BB->normalizeSuccWeights();
CvtNext = MBPI->getEdgeWeight(CvtBBI->BB, NextBBI->BB);
CvtFalse = MBPI->getEdgeWeight(CvtBBI->BB, CvtBBI->FalseBB);
BBNext = MBPI->getEdgeWeight(BBI.BB, NextBBI->BB);
BBCvt = MBPI->getEdgeWeight(BBI.BB, CvtBBI->BB);
SumWeight = MBPI->getSumForBlock(CvtBBI->BB, WeightScale);
SumWeight = MBPI->getSumForBlock(CvtBBI->BB);
}
if (CvtBBI->BB->pred_size() > 1) {
@ -1277,8 +1279,8 @@ bool IfConverter::IfConvertTriangle(BBInfo &BBI, IfcvtKind Kind) {
// New_Weight(BBI.BB, CvtBBI->FalseBB) =
// Weight(BBI.BB, CvtBBI->BB) * Weight(CvtBBI->BB, CvtBBI->FalseBB)
uint64_t NewNext = BBNext * SumWeight + (BBCvt * CvtNext) / WeightScale;
uint64_t NewFalse = (BBCvt * CvtFalse) / WeightScale;
uint64_t NewNext = BBNext * SumWeight + BBCvt * CvtNext;
uint64_t NewFalse = BBCvt * CvtFalse;
// We need to scale down all weights of BBI.BB to fit uint32_t.
// Here BBI.BB is connected to CvtBBI->FalseBB and will fall through to
// the next block.

View File

@ -16,6 +16,7 @@
#include "llvm/ADT/SmallString.h"
#include "llvm/CodeGen/LiveIntervalAnalysis.h"
#include "llvm/CodeGen/LiveVariables.h"
#include "llvm/CodeGen/MachineBranchProbabilityInfo.h"
#include "llvm/CodeGen/MachineDominators.h"
#include "llvm/CodeGen/MachineFunction.h"
#include "llvm/CodeGen/MachineInstrBuilder.h"
@ -39,8 +40,9 @@ using namespace llvm;
#define DEBUG_TYPE "codegen"
MachineBasicBlock::MachineBasicBlock(MachineFunction &mf, const BasicBlock *bb)
: BB(bb), Number(-1), xParent(&mf), Alignment(0), IsLandingPad(false),
AddressTaken(false), CachedMCSymbol(nullptr) {
: BB(bb), Number(-1), AreSuccWeightsNormalized(false), xParent(&mf),
Alignment(0), IsLandingPad(false), AddressTaken(false),
CachedMCSymbol(nullptr) {
Insts.Parent = this;
}
@ -481,8 +483,10 @@ void MachineBasicBlock::addSuccessor(MachineBasicBlock *succ, uint32_t weight) {
if (weight != 0 && Weights.empty())
Weights.resize(Successors.size());
if (weight != 0 || !Weights.empty())
if (weight != 0 || !Weights.empty()) {
Weights.push_back(weight);
AreSuccWeightsNormalized = false;
}
Successors.push_back(succ);
succ->addPredecessor(this);
@ -1096,7 +1100,25 @@ uint32_t MachineBasicBlock::getSuccWeight(const_succ_iterator Succ) const {
void MachineBasicBlock::setSuccWeight(succ_iterator I, uint32_t weight) {
if (Weights.empty())
return;
*getWeightIterator(I) = weight;
auto WeightIter = getWeightIterator(I);
uint32_t OldWeight = *WeightIter;
*WeightIter = weight;
if (weight > OldWeight)
AreSuccWeightsNormalized = false;
}
/// Normalize all succesor weights so that the sum of them does not exceed
/// UINT32_MAX. Return true if the weights are modified and false otherwise.
/// Note that weights that are modified after calling this function are not
/// guaranteed to be normalized.
bool MachineBasicBlock::normalizeSuccWeights() {
if (!AreSuccWeightsNormalized) {
uint32_t Scale =
MachineBranchProbabilityInfo::normalizeEdgeWeights(Weights);
AreSuccWeightsNormalized = true;
return Scale != 1;
}
return false;
}
/// getWeightIterator - Return wight iterator corresonding to the I successor

View File

@ -361,8 +361,7 @@ MachineBlockPlacement::selectBestSuccessor(MachineBasicBlock *BB,
// improve the MBPI interface to efficiently support query patterns such as
// this.
uint32_t BestWeight = 0;
uint32_t WeightScale = 0;
uint32_t SumWeight = MBPI->getSumForBlock(BB, WeightScale);
uint32_t SumWeight = MBPI->getSumForBlock(BB);
DEBUG(dbgs() << "Attempting merge from: " << getBlockName(BB) << "\n");
for (MachineBasicBlock *Succ : BB->successors()) {
if (BlockFilter && !BlockFilter->count(Succ))
@ -378,7 +377,7 @@ MachineBlockPlacement::selectBestSuccessor(MachineBasicBlock *BB,
}
uint32_t SuccWeight = MBPI->getEdgeWeight(BB, Succ);
BranchProbability SuccProb(SuccWeight / WeightScale, SumWeight);
BranchProbability SuccProb(SuccWeight, SumWeight);
// If we outline optional branches, look whether Succ is unavoidable, i.e.
// dominates all terminators of the MachineFunction. If it does, other
@ -675,8 +674,7 @@ MachineBlockPlacement::findBestLoopExit(MachineFunction &F, MachineLoop &L,
// FIXME: Due to the performance of the probability and weight routines in
// the MBPI analysis, we use the internal weights and manually compute the
// probabilities to avoid quadratic behavior.
uint32_t WeightScale = 0;
uint32_t SumWeight = MBPI->getSumForBlock(MBB, WeightScale);
uint32_t SumWeight = MBPI->getSumForBlock(MBB);
for (MachineBasicBlock *Succ : MBB->successors()) {
if (Succ->isLandingPad())
continue;
@ -705,7 +703,7 @@ MachineBlockPlacement::findBestLoopExit(MachineFunction &F, MachineLoop &L,
BlocksExitingToOuterLoop.insert(MBB);
}
BranchProbability SuccProb(SuccWeight / WeightScale, SumWeight);
BranchProbability SuccProb(SuccWeight, SumWeight);
BlockFrequency ExitEdgeFreq = MBFI->getBlockFreq(MBB) * SuccProb;
DEBUG(dbgs() << " exiting: " << getBlockName(MBB) << " -> "
<< getBlockName(Succ) << " [L:" << SuccLoopDepth << "] (";

View File

@ -28,36 +28,35 @@ char MachineBranchProbabilityInfo::ID = 0;
void MachineBranchProbabilityInfo::anchor() { }
uint32_t MachineBranchProbabilityInfo::
getSumForBlock(const MachineBasicBlock *MBB, uint32_t &Scale) const {
// First we compute the sum with 64-bits of precision, ensuring that cannot
// overflow by bounding the number of weights considered. Hopefully no one
// actually needs 2^32 successors.
assert(MBB->succ_size() < UINT32_MAX);
uint64_t Sum = 0;
uint32_t
MachineBranchProbabilityInfo::getSumForBlock(MachineBasicBlock *MBB) const {
// Normalize the weights of MBB's all successors so that the sum is guaranteed
// to be no greater than UINT32_MAX.
MBB->normalizeSuccWeights();
SmallVector<uint32_t, 8> Weights;
for (MachineBasicBlock::const_succ_iterator I = MBB->succ_begin(),
E = MBB->succ_end();
I != E; ++I)
Weights.push_back(getEdgeWeight(MBB, I));
return std::accumulate(Weights.begin(), Weights.end(), 0u);
}
uint32_t
MachineBranchProbabilityInfo::getSumForBlock(const MachineBasicBlock *MBB,
uint32_t &Scale) const {
SmallVector<uint32_t, 8> Weights;
for (MachineBasicBlock::const_succ_iterator I = MBB->succ_begin(),
E = MBB->succ_end();
I != E; ++I)
Weights.push_back(getEdgeWeight(MBB, I));
if (MBB->areSuccWeightsNormalized())
Scale = 1;
for (MachineBasicBlock::const_succ_iterator I = MBB->succ_begin(),
E = MBB->succ_end(); I != E; ++I) {
uint32_t Weight = getEdgeWeight(MBB, I);
Sum += Weight;
}
// If the computed sum fits in 32-bits, we're done.
if (Sum <= UINT32_MAX)
return Sum;
// Otherwise, compute the scale necessary to cause the weights to fit, and
// re-sum with that scale applied.
assert((Sum / UINT32_MAX) < UINT32_MAX);
Scale = (Sum / UINT32_MAX) + 1;
Sum = 0;
for (MachineBasicBlock::const_succ_iterator I = MBB->succ_begin(),
E = MBB->succ_end(); I != E; ++I) {
uint32_t Weight = getEdgeWeight(MBB, I);
Sum += Weight / Scale;
}
assert(Sum <= UINT32_MAX);
return Sum;
else
Scale = MachineBranchProbabilityInfo::normalizeEdgeWeights(Weights);
return std::accumulate(Weights.begin(), Weights.end(), 0u);
}
uint32_t MachineBranchProbabilityInfo::