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122 lines
4.8 KiB
C++
122 lines
4.8 KiB
C++
//=- MachineBranchProbabilityInfo.h - Branch Probability Analysis -*- C++ -*-=//
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//
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// The LLVM Compiler Infrastructure
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//
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// This file is distributed under the University of Illinois Open Source
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// License. See LICENSE.TXT for details.
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//
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//===----------------------------------------------------------------------===//
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//
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// This pass is used to evaluate branch probabilties on machine basic blocks.
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//
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//===----------------------------------------------------------------------===//
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#ifndef LLVM_CODEGEN_MACHINEBRANCHPROBABILITYINFO_H
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#define LLVM_CODEGEN_MACHINEBRANCHPROBABILITYINFO_H
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#include "llvm/CodeGen/MachineBasicBlock.h"
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#include "llvm/Pass.h"
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#include "llvm/Support/BranchProbability.h"
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#include <climits>
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#include <numeric>
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namespace llvm {
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class MachineBranchProbabilityInfo : public ImmutablePass {
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virtual void anchor();
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// Default weight value. Used when we don't have information about the edge.
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// TODO: DEFAULT_WEIGHT makes sense during static predication, when none of
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// the successors have a weight yet. But it doesn't make sense when providing
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// weight to an edge that may have siblings with non-zero weights. This can
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// be handled various ways, but it's probably fine for an edge with unknown
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// weight to just "inherit" the non-zero weight of an adjacent successor.
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static const uint32_t DEFAULT_WEIGHT = 16;
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public:
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static char ID;
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MachineBranchProbabilityInfo() : ImmutablePass(ID) {
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PassRegistry &Registry = *PassRegistry::getPassRegistry();
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initializeMachineBranchProbabilityInfoPass(Registry);
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}
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void getAnalysisUsage(AnalysisUsage &AU) const override {
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AU.setPreservesAll();
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}
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// Return edge weight. If we don't have any informations about it - return
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// DEFAULT_WEIGHT.
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uint32_t getEdgeWeight(const MachineBasicBlock *Src,
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const MachineBasicBlock *Dst) const;
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// Same thing, but using a const_succ_iterator from Src. This is faster when
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// the iterator is already available.
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uint32_t getEdgeWeight(const MachineBasicBlock *Src,
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MachineBasicBlock::const_succ_iterator Dst) const;
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// Get sum of the block successors' weights, potentially scaling them to fit
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// within 32-bits. If scaling is required, sets Scale based on the necessary
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// adjustment. Any edge weights used with the sum should be divided by Scale.
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uint32_t getSumForBlock(const MachineBasicBlock *MBB, uint32_t &Scale) const;
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// Get sum of the block successors' weights, and force normalizing the
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// successors' weights of MBB so that their sum fit within 32-bits.
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uint32_t getSumForBlock(MachineBasicBlock *MBB) const;
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// A 'Hot' edge is an edge which probability is >= 80%.
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bool isEdgeHot(const MachineBasicBlock *Src,
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const MachineBasicBlock *Dst) const;
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// Return a hot successor for the block BB or null if there isn't one.
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// NB: This routine's complexity is linear on the number of successors.
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MachineBasicBlock *getHotSucc(MachineBasicBlock *MBB) const;
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// Return a probability as a fraction between 0 (0% probability) and
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// 1 (100% probability), however the value is never equal to 0, and can be 1
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// only iff SRC block has only one successor.
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// NB: This routine's complexity is linear on the number of successors of
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// Src. Querying sequentially for each successor's probability is a quadratic
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// query pattern.
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BranchProbability getEdgeProbability(const MachineBasicBlock *Src,
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const MachineBasicBlock *Dst) const;
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// Print value between 0 (0% probability) and 1 (100% probability),
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// however the value is never equal to 0, and can be 1 only iff SRC block
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// has only one successor.
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raw_ostream &printEdgeProbability(raw_ostream &OS,
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const MachineBasicBlock *Src,
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const MachineBasicBlock *Dst) const;
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// Normalize a list of weights by scaling them down so that the sum of them
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// doesn't exceed UINT32_MAX. Return the scale.
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template <class WeightList>
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static uint32_t normalizeEdgeWeights(WeightList &Weights);
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};
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template <class WeightList>
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uint32_t
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MachineBranchProbabilityInfo::normalizeEdgeWeights(WeightList &Weights) {
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assert(Weights.size() < UINT32_MAX && "Too many weights in the list!");
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// First we compute the sum with 64-bits of precision.
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uint64_t Sum = std::accumulate(Weights.begin(), Weights.end(), uint64_t(0));
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// If the computed sum fits in 32-bits, we're done.
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if (Sum <= UINT32_MAX)
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return 1;
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// Otherwise, compute the scale necessary to cause the weights to fit, and
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// re-sum with that scale applied.
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assert((Sum / UINT32_MAX) < UINT32_MAX &&
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"The sum of weights exceeds UINT32_MAX^2!");
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uint32_t Scale = (Sum / UINT32_MAX) + 1;
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for (auto &W : Weights)
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W /= Scale;
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return Scale;
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}
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}
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#endif
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