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https://github.com/c64scene-ar/llvm-6502.git
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git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@212868 91177308-0d34-0410-b5e6-96231b3b80d8
1182 lines
44 KiB
C++
1182 lines
44 KiB
C++
//==- BlockFrequencyInfoImpl.h - Block Frequency Implementation -*- 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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// Shared implementation of BlockFrequency for IR and Machine Instructions.
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// See the documentation below for BlockFrequencyInfoImpl for details.
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//
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//===----------------------------------------------------------------------===//
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#ifndef LLVM_ANALYSIS_BLOCKFREQUENCYINFOIMPL_H
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#define LLVM_ANALYSIS_BLOCKFREQUENCYINFOIMPL_H
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#include "llvm/ADT/DenseMap.h"
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#include "llvm/ADT/PostOrderIterator.h"
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#include "llvm/ADT/iterator_range.h"
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#include "llvm/IR/BasicBlock.h"
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#include "llvm/Support/BlockFrequency.h"
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#include "llvm/Support/BranchProbability.h"
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#include "llvm/Support/Debug.h"
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#include "llvm/Support/ScaledNumber.h"
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#include "llvm/Support/raw_ostream.h"
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#include <deque>
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#include <list>
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#include <string>
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#include <vector>
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#define DEBUG_TYPE "block-freq"
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namespace llvm {
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class BasicBlock;
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class BranchProbabilityInfo;
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class Function;
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class Loop;
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class LoopInfo;
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class MachineBasicBlock;
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class MachineBranchProbabilityInfo;
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class MachineFunction;
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class MachineLoop;
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class MachineLoopInfo;
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namespace bfi_detail {
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struct IrreducibleGraph;
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// This is part of a workaround for a GCC 4.7 crash on lambdas.
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template <class BT> struct BlockEdgesAdder;
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/// \brief Mass of a block.
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///
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/// This class implements a sort of fixed-point fraction always between 0.0 and
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/// 1.0. getMass() == UINT64_MAX indicates a value of 1.0.
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///
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/// Masses can be added and subtracted. Simple saturation arithmetic is used,
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/// so arithmetic operations never overflow or underflow.
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///
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/// Masses can be multiplied. Multiplication treats full mass as 1.0 and uses
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/// an inexpensive floating-point algorithm that's off-by-one (almost, but not
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/// quite, maximum precision).
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///
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/// Masses can be scaled by \a BranchProbability at maximum precision.
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class BlockMass {
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uint64_t Mass;
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public:
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BlockMass() : Mass(0) {}
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explicit BlockMass(uint64_t Mass) : Mass(Mass) {}
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static BlockMass getEmpty() { return BlockMass(); }
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static BlockMass getFull() { return BlockMass(UINT64_MAX); }
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uint64_t getMass() const { return Mass; }
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bool isFull() const { return Mass == UINT64_MAX; }
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bool isEmpty() const { return !Mass; }
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bool operator!() const { return isEmpty(); }
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/// \brief Add another mass.
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///
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/// Adds another mass, saturating at \a isFull() rather than overflowing.
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BlockMass &operator+=(const BlockMass &X) {
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uint64_t Sum = Mass + X.Mass;
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Mass = Sum < Mass ? UINT64_MAX : Sum;
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return *this;
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}
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/// \brief Subtract another mass.
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///
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/// Subtracts another mass, saturating at \a isEmpty() rather than
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/// undeflowing.
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BlockMass &operator-=(const BlockMass &X) {
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uint64_t Diff = Mass - X.Mass;
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Mass = Diff > Mass ? 0 : Diff;
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return *this;
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}
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BlockMass &operator*=(const BranchProbability &P) {
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Mass = P.scale(Mass);
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return *this;
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}
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bool operator==(const BlockMass &X) const { return Mass == X.Mass; }
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bool operator!=(const BlockMass &X) const { return Mass != X.Mass; }
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bool operator<=(const BlockMass &X) const { return Mass <= X.Mass; }
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bool operator>=(const BlockMass &X) const { return Mass >= X.Mass; }
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bool operator<(const BlockMass &X) const { return Mass < X.Mass; }
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bool operator>(const BlockMass &X) const { return Mass > X.Mass; }
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/// \brief Convert to scaled number.
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///
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/// Convert to \a ScaledNumber. \a isFull() gives 1.0, while \a isEmpty()
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/// gives slightly above 0.0.
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ScaledNumber<uint64_t> toScaled() const;
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void dump() const;
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raw_ostream &print(raw_ostream &OS) const;
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};
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inline BlockMass operator+(const BlockMass &L, const BlockMass &R) {
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return BlockMass(L) += R;
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}
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inline BlockMass operator-(const BlockMass &L, const BlockMass &R) {
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return BlockMass(L) -= R;
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}
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inline BlockMass operator*(const BlockMass &L, const BranchProbability &R) {
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return BlockMass(L) *= R;
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}
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inline BlockMass operator*(const BranchProbability &L, const BlockMass &R) {
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return BlockMass(R) *= L;
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}
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inline raw_ostream &operator<<(raw_ostream &OS, const BlockMass &X) {
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return X.print(OS);
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}
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} // end namespace bfi_detail
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template <> struct isPodLike<bfi_detail::BlockMass> {
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static const bool value = true;
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};
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/// \brief Base class for BlockFrequencyInfoImpl
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///
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/// BlockFrequencyInfoImplBase has supporting data structures and some
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/// algorithms for BlockFrequencyInfoImplBase. Only algorithms that depend on
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/// the block type (or that call such algorithms) are skipped here.
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///
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/// Nevertheless, the majority of the overall algorithm documention lives with
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/// BlockFrequencyInfoImpl. See there for details.
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class BlockFrequencyInfoImplBase {
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public:
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typedef ScaledNumber<uint64_t> Scaled64;
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typedef bfi_detail::BlockMass BlockMass;
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/// \brief Representative of a block.
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///
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/// This is a simple wrapper around an index into the reverse-post-order
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/// traversal of the blocks.
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///
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/// Unlike a block pointer, its order has meaning (location in the
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/// topological sort) and it's class is the same regardless of block type.
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struct BlockNode {
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typedef uint32_t IndexType;
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IndexType Index;
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bool operator==(const BlockNode &X) const { return Index == X.Index; }
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bool operator!=(const BlockNode &X) const { return Index != X.Index; }
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bool operator<=(const BlockNode &X) const { return Index <= X.Index; }
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bool operator>=(const BlockNode &X) const { return Index >= X.Index; }
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bool operator<(const BlockNode &X) const { return Index < X.Index; }
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bool operator>(const BlockNode &X) const { return Index > X.Index; }
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BlockNode() : Index(UINT32_MAX) {}
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BlockNode(IndexType Index) : Index(Index) {}
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bool isValid() const { return Index <= getMaxIndex(); }
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static size_t getMaxIndex() { return UINT32_MAX - 1; }
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};
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/// \brief Stats about a block itself.
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struct FrequencyData {
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Scaled64 Scaled;
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uint64_t Integer;
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};
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/// \brief Data about a loop.
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///
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/// Contains the data necessary to represent represent a loop as a
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/// pseudo-node once it's packaged.
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struct LoopData {
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typedef SmallVector<std::pair<BlockNode, BlockMass>, 4> ExitMap;
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typedef SmallVector<BlockNode, 4> NodeList;
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LoopData *Parent; ///< The parent loop.
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bool IsPackaged; ///< Whether this has been packaged.
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uint32_t NumHeaders; ///< Number of headers.
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ExitMap Exits; ///< Successor edges (and weights).
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NodeList Nodes; ///< Header and the members of the loop.
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BlockMass BackedgeMass; ///< Mass returned to loop header.
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BlockMass Mass;
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Scaled64 Scale;
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LoopData(LoopData *Parent, const BlockNode &Header)
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: Parent(Parent), IsPackaged(false), NumHeaders(1), Nodes(1, Header) {}
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template <class It1, class It2>
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LoopData(LoopData *Parent, It1 FirstHeader, It1 LastHeader, It2 FirstOther,
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It2 LastOther)
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: Parent(Parent), IsPackaged(false), Nodes(FirstHeader, LastHeader) {
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NumHeaders = Nodes.size();
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Nodes.insert(Nodes.end(), FirstOther, LastOther);
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}
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bool isHeader(const BlockNode &Node) const {
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if (isIrreducible())
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return std::binary_search(Nodes.begin(), Nodes.begin() + NumHeaders,
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Node);
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return Node == Nodes[0];
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}
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BlockNode getHeader() const { return Nodes[0]; }
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bool isIrreducible() const { return NumHeaders > 1; }
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NodeList::const_iterator members_begin() const {
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return Nodes.begin() + NumHeaders;
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}
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NodeList::const_iterator members_end() const { return Nodes.end(); }
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iterator_range<NodeList::const_iterator> members() const {
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return make_range(members_begin(), members_end());
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}
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};
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/// \brief Index of loop information.
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struct WorkingData {
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BlockNode Node; ///< This node.
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LoopData *Loop; ///< The loop this block is inside.
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BlockMass Mass; ///< Mass distribution from the entry block.
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WorkingData(const BlockNode &Node) : Node(Node), Loop(nullptr) {}
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bool isLoopHeader() const { return Loop && Loop->isHeader(Node); }
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bool isDoubleLoopHeader() const {
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return isLoopHeader() && Loop->Parent && Loop->Parent->isIrreducible() &&
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Loop->Parent->isHeader(Node);
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}
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LoopData *getContainingLoop() const {
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if (!isLoopHeader())
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return Loop;
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if (!isDoubleLoopHeader())
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return Loop->Parent;
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return Loop->Parent->Parent;
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}
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/// \brief Resolve a node to its representative.
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///
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/// Get the node currently representing Node, which could be a containing
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/// loop.
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///
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/// This function should only be called when distributing mass. As long as
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/// there are no irreducilbe edges to Node, then it will have complexity
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/// O(1) in this context.
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///
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/// In general, the complexity is O(L), where L is the number of loop
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/// headers Node has been packaged into. Since this method is called in
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/// the context of distributing mass, L will be the number of loop headers
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/// an early exit edge jumps out of.
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BlockNode getResolvedNode() const {
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auto L = getPackagedLoop();
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return L ? L->getHeader() : Node;
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}
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LoopData *getPackagedLoop() const {
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if (!Loop || !Loop->IsPackaged)
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return nullptr;
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auto L = Loop;
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while (L->Parent && L->Parent->IsPackaged)
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L = L->Parent;
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return L;
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}
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/// \brief Get the appropriate mass for a node.
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///
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/// Get appropriate mass for Node. If Node is a loop-header (whose loop
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/// has been packaged), returns the mass of its pseudo-node. If it's a
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/// node inside a packaged loop, it returns the loop's mass.
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BlockMass &getMass() {
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if (!isAPackage())
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return Mass;
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if (!isADoublePackage())
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return Loop->Mass;
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return Loop->Parent->Mass;
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}
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/// \brief Has ContainingLoop been packaged up?
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bool isPackaged() const { return getResolvedNode() != Node; }
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/// \brief Has Loop been packaged up?
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bool isAPackage() const { return isLoopHeader() && Loop->IsPackaged; }
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/// \brief Has Loop been packaged up twice?
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bool isADoublePackage() const {
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return isDoubleLoopHeader() && Loop->Parent->IsPackaged;
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}
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};
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/// \brief Unscaled probability weight.
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///
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/// Probability weight for an edge in the graph (including the
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/// successor/target node).
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///
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/// All edges in the original function are 32-bit. However, exit edges from
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/// loop packages are taken from 64-bit exit masses, so we need 64-bits of
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/// space in general.
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///
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/// In addition to the raw weight amount, Weight stores the type of the edge
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/// in the current context (i.e., the context of the loop being processed).
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/// Is this a local edge within the loop, an exit from the loop, or a
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/// backedge to the loop header?
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struct Weight {
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enum DistType { Local, Exit, Backedge };
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DistType Type;
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BlockNode TargetNode;
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uint64_t Amount;
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Weight() : Type(Local), Amount(0) {}
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Weight(DistType Type, BlockNode TargetNode, uint64_t Amount)
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: Type(Type), TargetNode(TargetNode), Amount(Amount) {}
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};
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/// \brief Distribution of unscaled probability weight.
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///
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/// Distribution of unscaled probability weight to a set of successors.
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///
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/// This class collates the successor edge weights for later processing.
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///
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/// \a DidOverflow indicates whether \a Total did overflow while adding to
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/// the distribution. It should never overflow twice.
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struct Distribution {
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typedef SmallVector<Weight, 4> WeightList;
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WeightList Weights; ///< Individual successor weights.
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uint64_t Total; ///< Sum of all weights.
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bool DidOverflow; ///< Whether \a Total did overflow.
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Distribution() : Total(0), DidOverflow(false) {}
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void addLocal(const BlockNode &Node, uint64_t Amount) {
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add(Node, Amount, Weight::Local);
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}
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void addExit(const BlockNode &Node, uint64_t Amount) {
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add(Node, Amount, Weight::Exit);
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}
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void addBackedge(const BlockNode &Node, uint64_t Amount) {
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add(Node, Amount, Weight::Backedge);
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}
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/// \brief Normalize the distribution.
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///
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/// Combines multiple edges to the same \a Weight::TargetNode and scales
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/// down so that \a Total fits into 32-bits.
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///
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/// This is linear in the size of \a Weights. For the vast majority of
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/// cases, adjacent edge weights are combined by sorting WeightList and
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/// combining adjacent weights. However, for very large edge lists an
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/// auxiliary hash table is used.
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void normalize();
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private:
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void add(const BlockNode &Node, uint64_t Amount, Weight::DistType Type);
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};
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/// \brief Data about each block. This is used downstream.
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std::vector<FrequencyData> Freqs;
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/// \brief Loop data: see initializeLoops().
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std::vector<WorkingData> Working;
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/// \brief Indexed information about loops.
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std::list<LoopData> Loops;
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/// \brief Add all edges out of a packaged loop to the distribution.
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///
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/// Adds all edges from LocalLoopHead to Dist. Calls addToDist() to add each
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/// successor edge.
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///
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/// \return \c true unless there's an irreducible backedge.
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bool addLoopSuccessorsToDist(const LoopData *OuterLoop, LoopData &Loop,
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Distribution &Dist);
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/// \brief Add an edge to the distribution.
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///
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/// Adds an edge to Succ to Dist. If \c LoopHead.isValid(), then whether the
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/// edge is local/exit/backedge is in the context of LoopHead. Otherwise,
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/// every edge should be a local edge (since all the loops are packaged up).
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///
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/// \return \c true unless aborted due to an irreducible backedge.
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bool addToDist(Distribution &Dist, const LoopData *OuterLoop,
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const BlockNode &Pred, const BlockNode &Succ, uint64_t Weight);
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LoopData &getLoopPackage(const BlockNode &Head) {
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assert(Head.Index < Working.size());
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assert(Working[Head.Index].isLoopHeader());
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return *Working[Head.Index].Loop;
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}
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/// \brief Analyze irreducible SCCs.
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///
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/// Separate irreducible SCCs from \c G, which is an explict graph of \c
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/// OuterLoop (or the top-level function, if \c OuterLoop is \c nullptr).
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/// Insert them into \a Loops before \c Insert.
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///
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/// \return the \c LoopData nodes representing the irreducible SCCs.
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iterator_range<std::list<LoopData>::iterator>
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analyzeIrreducible(const bfi_detail::IrreducibleGraph &G, LoopData *OuterLoop,
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std::list<LoopData>::iterator Insert);
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/// \brief Update a loop after packaging irreducible SCCs inside of it.
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///
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/// Update \c OuterLoop. Before finding irreducible control flow, it was
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/// partway through \a computeMassInLoop(), so \a LoopData::Exits and \a
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/// LoopData::BackedgeMass need to be reset. Also, nodes that were packaged
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/// up need to be removed from \a OuterLoop::Nodes.
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void updateLoopWithIrreducible(LoopData &OuterLoop);
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/// \brief Distribute mass according to a distribution.
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///
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/// Distributes the mass in Source according to Dist. If LoopHead.isValid(),
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/// backedges and exits are stored in its entry in Loops.
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///
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/// Mass is distributed in parallel from two copies of the source mass.
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void distributeMass(const BlockNode &Source, LoopData *OuterLoop,
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Distribution &Dist);
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/// \brief Compute the loop scale for a loop.
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void computeLoopScale(LoopData &Loop);
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/// \brief Package up a loop.
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void packageLoop(LoopData &Loop);
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/// \brief Unwrap loops.
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void unwrapLoops();
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/// \brief Finalize frequency metrics.
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///
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/// Calculates final frequencies and cleans up no-longer-needed data
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/// structures.
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void finalizeMetrics();
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/// \brief Clear all memory.
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void clear();
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virtual std::string getBlockName(const BlockNode &Node) const;
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std::string getLoopName(const LoopData &Loop) const;
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virtual raw_ostream &print(raw_ostream &OS) const { return OS; }
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void dump() const { print(dbgs()); }
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Scaled64 getFloatingBlockFreq(const BlockNode &Node) const;
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BlockFrequency getBlockFreq(const BlockNode &Node) const;
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raw_ostream &printBlockFreq(raw_ostream &OS, const BlockNode &Node) const;
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raw_ostream &printBlockFreq(raw_ostream &OS,
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const BlockFrequency &Freq) const;
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uint64_t getEntryFreq() const {
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assert(!Freqs.empty());
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return Freqs[0].Integer;
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}
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/// \brief Virtual destructor.
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///
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/// Need a virtual destructor to mask the compiler warning about
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/// getBlockName().
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virtual ~BlockFrequencyInfoImplBase() {}
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};
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namespace bfi_detail {
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template <class BlockT> struct TypeMap {};
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template <> struct TypeMap<BasicBlock> {
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typedef BasicBlock BlockT;
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typedef Function FunctionT;
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typedef BranchProbabilityInfo BranchProbabilityInfoT;
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typedef Loop LoopT;
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typedef LoopInfo LoopInfoT;
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};
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template <> struct TypeMap<MachineBasicBlock> {
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typedef MachineBasicBlock BlockT;
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typedef MachineFunction FunctionT;
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typedef MachineBranchProbabilityInfo BranchProbabilityInfoT;
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typedef MachineLoop LoopT;
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typedef MachineLoopInfo LoopInfoT;
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};
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/// \brief Get the name of a MachineBasicBlock.
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///
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/// Get the name of a MachineBasicBlock. It's templated so that including from
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/// CodeGen is unnecessary (that would be a layering issue).
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///
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/// This is used mainly for debug output. The name is similar to
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/// MachineBasicBlock::getFullName(), but skips the name of the function.
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|
template <class BlockT> std::string getBlockName(const BlockT *BB) {
|
|
assert(BB && "Unexpected nullptr");
|
|
auto MachineName = "BB" + Twine(BB->getNumber());
|
|
if (BB->getBasicBlock())
|
|
return (MachineName + "[" + BB->getName() + "]").str();
|
|
return MachineName.str();
|
|
}
|
|
/// \brief Get the name of a BasicBlock.
|
|
template <> inline std::string getBlockName(const BasicBlock *BB) {
|
|
assert(BB && "Unexpected nullptr");
|
|
return BB->getName().str();
|
|
}
|
|
|
|
/// \brief Graph of irreducible control flow.
|
|
///
|
|
/// This graph is used for determining the SCCs in a loop (or top-level
|
|
/// function) that has irreducible control flow.
|
|
///
|
|
/// During the block frequency algorithm, the local graphs are defined in a
|
|
/// light-weight way, deferring to the \a BasicBlock or \a MachineBasicBlock
|
|
/// graphs for most edges, but getting others from \a LoopData::ExitMap. The
|
|
/// latter only has successor information.
|
|
///
|
|
/// \a IrreducibleGraph makes this graph explicit. It's in a form that can use
|
|
/// \a GraphTraits (so that \a analyzeIrreducible() can use \a scc_iterator),
|
|
/// and it explicitly lists predecessors and successors. The initialization
|
|
/// that relies on \c MachineBasicBlock is defined in the header.
|
|
struct IrreducibleGraph {
|
|
typedef BlockFrequencyInfoImplBase BFIBase;
|
|
|
|
BFIBase &BFI;
|
|
|
|
typedef BFIBase::BlockNode BlockNode;
|
|
struct IrrNode {
|
|
BlockNode Node;
|
|
unsigned NumIn;
|
|
std::deque<const IrrNode *> Edges;
|
|
IrrNode(const BlockNode &Node) : Node(Node), NumIn(0) {}
|
|
|
|
typedef std::deque<const IrrNode *>::const_iterator iterator;
|
|
iterator pred_begin() const { return Edges.begin(); }
|
|
iterator succ_begin() const { return Edges.begin() + NumIn; }
|
|
iterator pred_end() const { return succ_begin(); }
|
|
iterator succ_end() const { return Edges.end(); }
|
|
};
|
|
BlockNode Start;
|
|
const IrrNode *StartIrr;
|
|
std::vector<IrrNode> Nodes;
|
|
SmallDenseMap<uint32_t, IrrNode *, 4> Lookup;
|
|
|
|
/// \brief Construct an explicit graph containing irreducible control flow.
|
|
///
|
|
/// Construct an explicit graph of the control flow in \c OuterLoop (or the
|
|
/// top-level function, if \c OuterLoop is \c nullptr). Uses \c
|
|
/// addBlockEdges to add block successors that have not been packaged into
|
|
/// loops.
|
|
///
|
|
/// \a BlockFrequencyInfoImpl::computeIrreducibleMass() is the only expected
|
|
/// user of this.
|
|
template <class BlockEdgesAdder>
|
|
IrreducibleGraph(BFIBase &BFI, const BFIBase::LoopData *OuterLoop,
|
|
BlockEdgesAdder addBlockEdges)
|
|
: BFI(BFI), StartIrr(nullptr) {
|
|
initialize(OuterLoop, addBlockEdges);
|
|
}
|
|
|
|
template <class BlockEdgesAdder>
|
|
void initialize(const BFIBase::LoopData *OuterLoop,
|
|
BlockEdgesAdder addBlockEdges);
|
|
void addNodesInLoop(const BFIBase::LoopData &OuterLoop);
|
|
void addNodesInFunction();
|
|
void addNode(const BlockNode &Node) {
|
|
Nodes.emplace_back(Node);
|
|
BFI.Working[Node.Index].getMass() = BlockMass::getEmpty();
|
|
}
|
|
void indexNodes();
|
|
template <class BlockEdgesAdder>
|
|
void addEdges(const BlockNode &Node, const BFIBase::LoopData *OuterLoop,
|
|
BlockEdgesAdder addBlockEdges);
|
|
void addEdge(IrrNode &Irr, const BlockNode &Succ,
|
|
const BFIBase::LoopData *OuterLoop);
|
|
};
|
|
template <class BlockEdgesAdder>
|
|
void IrreducibleGraph::initialize(const BFIBase::LoopData *OuterLoop,
|
|
BlockEdgesAdder addBlockEdges) {
|
|
if (OuterLoop) {
|
|
addNodesInLoop(*OuterLoop);
|
|
for (auto N : OuterLoop->Nodes)
|
|
addEdges(N, OuterLoop, addBlockEdges);
|
|
} else {
|
|
addNodesInFunction();
|
|
for (uint32_t Index = 0; Index < BFI.Working.size(); ++Index)
|
|
addEdges(Index, OuterLoop, addBlockEdges);
|
|
}
|
|
StartIrr = Lookup[Start.Index];
|
|
}
|
|
template <class BlockEdgesAdder>
|
|
void IrreducibleGraph::addEdges(const BlockNode &Node,
|
|
const BFIBase::LoopData *OuterLoop,
|
|
BlockEdgesAdder addBlockEdges) {
|
|
auto L = Lookup.find(Node.Index);
|
|
if (L == Lookup.end())
|
|
return;
|
|
IrrNode &Irr = *L->second;
|
|
const auto &Working = BFI.Working[Node.Index];
|
|
|
|
if (Working.isAPackage())
|
|
for (const auto &I : Working.Loop->Exits)
|
|
addEdge(Irr, I.first, OuterLoop);
|
|
else
|
|
addBlockEdges(*this, Irr, OuterLoop);
|
|
}
|
|
}
|
|
|
|
/// \brief Shared implementation for block frequency analysis.
|
|
///
|
|
/// This is a shared implementation of BlockFrequencyInfo and
|
|
/// MachineBlockFrequencyInfo, and calculates the relative frequencies of
|
|
/// blocks.
|
|
///
|
|
/// LoopInfo defines a loop as a "non-trivial" SCC dominated by a single block,
|
|
/// which is called the header. A given loop, L, can have sub-loops, which are
|
|
/// loops within the subgraph of L that exclude its header. (A "trivial" SCC
|
|
/// consists of a single block that does not have a self-edge.)
|
|
///
|
|
/// In addition to loops, this algorithm has limited support for irreducible
|
|
/// SCCs, which are SCCs with multiple entry blocks. Irreducible SCCs are
|
|
/// discovered on they fly, and modelled as loops with multiple headers.
|
|
///
|
|
/// The headers of irreducible sub-SCCs consist of its entry blocks and all
|
|
/// nodes that are targets of a backedge within it (excluding backedges within
|
|
/// true sub-loops). Block frequency calculations act as if a block is
|
|
/// inserted that intercepts all the edges to the headers. All backedges and
|
|
/// entries point to this block. Its successors are the headers, which split
|
|
/// the frequency evenly.
|
|
///
|
|
/// This algorithm leverages BlockMass and ScaledNumber to maintain precision,
|
|
/// separates mass distribution from loop scaling, and dithers to eliminate
|
|
/// probability mass loss.
|
|
///
|
|
/// The implementation is split between BlockFrequencyInfoImpl, which knows the
|
|
/// type of graph being modelled (BasicBlock vs. MachineBasicBlock), and
|
|
/// BlockFrequencyInfoImplBase, which doesn't. The base class uses \a
|
|
/// BlockNode, a wrapper around a uint32_t. BlockNode is numbered from 0 in
|
|
/// reverse-post order. This gives two advantages: it's easy to compare the
|
|
/// relative ordering of two nodes, and maps keyed on BlockT can be represented
|
|
/// by vectors.
|
|
///
|
|
/// This algorithm is O(V+E), unless there is irreducible control flow, in
|
|
/// which case it's O(V*E) in the worst case.
|
|
///
|
|
/// These are the main stages:
|
|
///
|
|
/// 0. Reverse post-order traversal (\a initializeRPOT()).
|
|
///
|
|
/// Run a single post-order traversal and save it (in reverse) in RPOT.
|
|
/// All other stages make use of this ordering. Save a lookup from BlockT
|
|
/// to BlockNode (the index into RPOT) in Nodes.
|
|
///
|
|
/// 1. Loop initialization (\a initializeLoops()).
|
|
///
|
|
/// Translate LoopInfo/MachineLoopInfo into a form suitable for the rest of
|
|
/// the algorithm. In particular, store the immediate members of each loop
|
|
/// in reverse post-order.
|
|
///
|
|
/// 2. Calculate mass and scale in loops (\a computeMassInLoops()).
|
|
///
|
|
/// For each loop (bottom-up), distribute mass through the DAG resulting
|
|
/// from ignoring backedges and treating sub-loops as a single pseudo-node.
|
|
/// Track the backedge mass distributed to the loop header, and use it to
|
|
/// calculate the loop scale (number of loop iterations). Immediate
|
|
/// members that represent sub-loops will already have been visited and
|
|
/// packaged into a pseudo-node.
|
|
///
|
|
/// Distributing mass in a loop is a reverse-post-order traversal through
|
|
/// the loop. Start by assigning full mass to the Loop header. For each
|
|
/// node in the loop:
|
|
///
|
|
/// - Fetch and categorize the weight distribution for its successors.
|
|
/// If this is a packaged-subloop, the weight distribution is stored
|
|
/// in \a LoopData::Exits. Otherwise, fetch it from
|
|
/// BranchProbabilityInfo.
|
|
///
|
|
/// - Each successor is categorized as \a Weight::Local, a local edge
|
|
/// within the current loop, \a Weight::Backedge, a backedge to the
|
|
/// loop header, or \a Weight::Exit, any successor outside the loop.
|
|
/// The weight, the successor, and its category are stored in \a
|
|
/// Distribution. There can be multiple edges to each successor.
|
|
///
|
|
/// - If there's a backedge to a non-header, there's an irreducible SCC.
|
|
/// The usual flow is temporarily aborted. \a
|
|
/// computeIrreducibleMass() finds the irreducible SCCs within the
|
|
/// loop, packages them up, and restarts the flow.
|
|
///
|
|
/// - Normalize the distribution: scale weights down so that their sum
|
|
/// is 32-bits, and coalesce multiple edges to the same node.
|
|
///
|
|
/// - Distribute the mass accordingly, dithering to minimize mass loss,
|
|
/// as described in \a distributeMass().
|
|
///
|
|
/// Finally, calculate the loop scale from the accumulated backedge mass.
|
|
///
|
|
/// 3. Distribute mass in the function (\a computeMassInFunction()).
|
|
///
|
|
/// Finally, distribute mass through the DAG resulting from packaging all
|
|
/// loops in the function. This uses the same algorithm as distributing
|
|
/// mass in a loop, except that there are no exit or backedge edges.
|
|
///
|
|
/// 4. Unpackage loops (\a unwrapLoops()).
|
|
///
|
|
/// Initialize each block's frequency to a floating point representation of
|
|
/// its mass.
|
|
///
|
|
/// Visit loops top-down, scaling the frequencies of its immediate members
|
|
/// by the loop's pseudo-node's frequency.
|
|
///
|
|
/// 5. Convert frequencies to a 64-bit range (\a finalizeMetrics()).
|
|
///
|
|
/// Using the min and max frequencies as a guide, translate floating point
|
|
/// frequencies to an appropriate range in uint64_t.
|
|
///
|
|
/// It has some known flaws.
|
|
///
|
|
/// - Loop scale is limited to 4096 per loop (2^12) to avoid exhausting
|
|
/// BlockFrequency's 64-bit integer precision.
|
|
///
|
|
/// - The model of irreducible control flow is a rough approximation.
|
|
///
|
|
/// Modelling irreducible control flow exactly involves setting up and
|
|
/// solving a group of infinite geometric series. Such precision is
|
|
/// unlikely to be worthwhile, since most of our algorithms give up on
|
|
/// irreducible control flow anyway.
|
|
///
|
|
/// Nevertheless, we might find that we need to get closer. Here's a sort
|
|
/// of TODO list for the model with diminishing returns, to be completed as
|
|
/// necessary.
|
|
///
|
|
/// - The headers for the \a LoopData representing an irreducible SCC
|
|
/// include non-entry blocks. When these extra blocks exist, they
|
|
/// indicate a self-contained irreducible sub-SCC. We could treat them
|
|
/// as sub-loops, rather than arbitrarily shoving the problematic
|
|
/// blocks into the headers of the main irreducible SCC.
|
|
///
|
|
/// - Backedge frequencies are assumed to be evenly split between the
|
|
/// headers of a given irreducible SCC. Instead, we could track the
|
|
/// backedge mass separately for each header, and adjust their relative
|
|
/// frequencies.
|
|
///
|
|
/// - Entry frequencies are assumed to be evenly split between the
|
|
/// headers of a given irreducible SCC, which is the only option if we
|
|
/// need to compute mass in the SCC before its parent loop. Instead,
|
|
/// we could partially compute mass in the parent loop, and stop when
|
|
/// we get to the SCC. Here, we have the correct ratio of entry
|
|
/// masses, which we can use to adjust their relative frequencies.
|
|
/// Compute mass in the SCC, and then continue propagation in the
|
|
/// parent.
|
|
///
|
|
/// - We can propagate mass iteratively through the SCC, for some fixed
|
|
/// number of iterations. Each iteration starts by assigning the entry
|
|
/// blocks their backedge mass from the prior iteration. The final
|
|
/// mass for each block (and each exit, and the total backedge mass
|
|
/// used for computing loop scale) is the sum of all iterations.
|
|
/// (Running this until fixed point would "solve" the geometric
|
|
/// series by simulation.)
|
|
template <class BT> class BlockFrequencyInfoImpl : BlockFrequencyInfoImplBase {
|
|
typedef typename bfi_detail::TypeMap<BT>::BlockT BlockT;
|
|
typedef typename bfi_detail::TypeMap<BT>::FunctionT FunctionT;
|
|
typedef typename bfi_detail::TypeMap<BT>::BranchProbabilityInfoT
|
|
BranchProbabilityInfoT;
|
|
typedef typename bfi_detail::TypeMap<BT>::LoopT LoopT;
|
|
typedef typename bfi_detail::TypeMap<BT>::LoopInfoT LoopInfoT;
|
|
|
|
// This is part of a workaround for a GCC 4.7 crash on lambdas.
|
|
friend struct bfi_detail::BlockEdgesAdder<BT>;
|
|
|
|
typedef GraphTraits<const BlockT *> Successor;
|
|
typedef GraphTraits<Inverse<const BlockT *>> Predecessor;
|
|
|
|
const BranchProbabilityInfoT *BPI;
|
|
const LoopInfoT *LI;
|
|
const FunctionT *F;
|
|
|
|
// All blocks in reverse postorder.
|
|
std::vector<const BlockT *> RPOT;
|
|
DenseMap<const BlockT *, BlockNode> Nodes;
|
|
|
|
typedef typename std::vector<const BlockT *>::const_iterator rpot_iterator;
|
|
|
|
rpot_iterator rpot_begin() const { return RPOT.begin(); }
|
|
rpot_iterator rpot_end() const { return RPOT.end(); }
|
|
|
|
size_t getIndex(const rpot_iterator &I) const { return I - rpot_begin(); }
|
|
|
|
BlockNode getNode(const rpot_iterator &I) const {
|
|
return BlockNode(getIndex(I));
|
|
}
|
|
BlockNode getNode(const BlockT *BB) const { return Nodes.lookup(BB); }
|
|
|
|
const BlockT *getBlock(const BlockNode &Node) const {
|
|
assert(Node.Index < RPOT.size());
|
|
return RPOT[Node.Index];
|
|
}
|
|
|
|
/// \brief Run (and save) a post-order traversal.
|
|
///
|
|
/// Saves a reverse post-order traversal of all the nodes in \a F.
|
|
void initializeRPOT();
|
|
|
|
/// \brief Initialize loop data.
|
|
///
|
|
/// Build up \a Loops using \a LoopInfo. \a LoopInfo gives us a mapping from
|
|
/// each block to the deepest loop it's in, but we need the inverse. For each
|
|
/// loop, we store in reverse post-order its "immediate" members, defined as
|
|
/// the header, the headers of immediate sub-loops, and all other blocks in
|
|
/// the loop that are not in sub-loops.
|
|
void initializeLoops();
|
|
|
|
/// \brief Propagate to a block's successors.
|
|
///
|
|
/// In the context of distributing mass through \c OuterLoop, divide the mass
|
|
/// currently assigned to \c Node between its successors.
|
|
///
|
|
/// \return \c true unless there's an irreducible backedge.
|
|
bool propagateMassToSuccessors(LoopData *OuterLoop, const BlockNode &Node);
|
|
|
|
/// \brief Compute mass in a particular loop.
|
|
///
|
|
/// Assign mass to \c Loop's header, and then for each block in \c Loop in
|
|
/// reverse post-order, distribute mass to its successors. Only visits nodes
|
|
/// that have not been packaged into sub-loops.
|
|
///
|
|
/// \pre \a computeMassInLoop() has been called for each subloop of \c Loop.
|
|
/// \return \c true unless there's an irreducible backedge.
|
|
bool computeMassInLoop(LoopData &Loop);
|
|
|
|
/// \brief Try to compute mass in the top-level function.
|
|
///
|
|
/// Assign mass to the entry block, and then for each block in reverse
|
|
/// post-order, distribute mass to its successors. Skips nodes that have
|
|
/// been packaged into loops.
|
|
///
|
|
/// \pre \a computeMassInLoops() has been called.
|
|
/// \return \c true unless there's an irreducible backedge.
|
|
bool tryToComputeMassInFunction();
|
|
|
|
/// \brief Compute mass in (and package up) irreducible SCCs.
|
|
///
|
|
/// Find the irreducible SCCs in \c OuterLoop, add them to \a Loops (in front
|
|
/// of \c Insert), and call \a computeMassInLoop() on each of them.
|
|
///
|
|
/// If \c OuterLoop is \c nullptr, it refers to the top-level function.
|
|
///
|
|
/// \pre \a computeMassInLoop() has been called for each subloop of \c
|
|
/// OuterLoop.
|
|
/// \pre \c Insert points at the the last loop successfully processed by \a
|
|
/// computeMassInLoop().
|
|
/// \pre \c OuterLoop has irreducible SCCs.
|
|
void computeIrreducibleMass(LoopData *OuterLoop,
|
|
std::list<LoopData>::iterator Insert);
|
|
|
|
/// \brief Compute mass in all loops.
|
|
///
|
|
/// For each loop bottom-up, call \a computeMassInLoop().
|
|
///
|
|
/// \a computeMassInLoop() aborts (and returns \c false) on loops that
|
|
/// contain a irreducible sub-SCCs. Use \a computeIrreducibleMass() and then
|
|
/// re-enter \a computeMassInLoop().
|
|
///
|
|
/// \post \a computeMassInLoop() has returned \c true for every loop.
|
|
void computeMassInLoops();
|
|
|
|
/// \brief Compute mass in the top-level function.
|
|
///
|
|
/// Uses \a tryToComputeMassInFunction() and \a computeIrreducibleMass() to
|
|
/// compute mass in the top-level function.
|
|
///
|
|
/// \post \a tryToComputeMassInFunction() has returned \c true.
|
|
void computeMassInFunction();
|
|
|
|
std::string getBlockName(const BlockNode &Node) const override {
|
|
return bfi_detail::getBlockName(getBlock(Node));
|
|
}
|
|
|
|
public:
|
|
const FunctionT *getFunction() const { return F; }
|
|
|
|
void doFunction(const FunctionT *F, const BranchProbabilityInfoT *BPI,
|
|
const LoopInfoT *LI);
|
|
BlockFrequencyInfoImpl() : BPI(nullptr), LI(nullptr), F(nullptr) {}
|
|
|
|
using BlockFrequencyInfoImplBase::getEntryFreq;
|
|
BlockFrequency getBlockFreq(const BlockT *BB) const {
|
|
return BlockFrequencyInfoImplBase::getBlockFreq(getNode(BB));
|
|
}
|
|
Scaled64 getFloatingBlockFreq(const BlockT *BB) const {
|
|
return BlockFrequencyInfoImplBase::getFloatingBlockFreq(getNode(BB));
|
|
}
|
|
|
|
/// \brief Print the frequencies for the current function.
|
|
///
|
|
/// Prints the frequencies for the blocks in the current function.
|
|
///
|
|
/// Blocks are printed in the natural iteration order of the function, rather
|
|
/// than reverse post-order. This provides two advantages: writing -analyze
|
|
/// tests is easier (since blocks come out in source order), and even
|
|
/// unreachable blocks are printed.
|
|
///
|
|
/// \a BlockFrequencyInfoImplBase::print() only knows reverse post-order, so
|
|
/// we need to override it here.
|
|
raw_ostream &print(raw_ostream &OS) const override;
|
|
using BlockFrequencyInfoImplBase::dump;
|
|
|
|
using BlockFrequencyInfoImplBase::printBlockFreq;
|
|
raw_ostream &printBlockFreq(raw_ostream &OS, const BlockT *BB) const {
|
|
return BlockFrequencyInfoImplBase::printBlockFreq(OS, getNode(BB));
|
|
}
|
|
};
|
|
|
|
template <class BT>
|
|
void BlockFrequencyInfoImpl<BT>::doFunction(const FunctionT *F,
|
|
const BranchProbabilityInfoT *BPI,
|
|
const LoopInfoT *LI) {
|
|
// Save the parameters.
|
|
this->BPI = BPI;
|
|
this->LI = LI;
|
|
this->F = F;
|
|
|
|
// Clean up left-over data structures.
|
|
BlockFrequencyInfoImplBase::clear();
|
|
RPOT.clear();
|
|
Nodes.clear();
|
|
|
|
// Initialize.
|
|
DEBUG(dbgs() << "\nblock-frequency: " << F->getName() << "\n================="
|
|
<< std::string(F->getName().size(), '=') << "\n");
|
|
initializeRPOT();
|
|
initializeLoops();
|
|
|
|
// Visit loops in post-order to find thelocal mass distribution, and then do
|
|
// the full function.
|
|
computeMassInLoops();
|
|
computeMassInFunction();
|
|
unwrapLoops();
|
|
finalizeMetrics();
|
|
}
|
|
|
|
template <class BT> void BlockFrequencyInfoImpl<BT>::initializeRPOT() {
|
|
const BlockT *Entry = F->begin();
|
|
RPOT.reserve(F->size());
|
|
std::copy(po_begin(Entry), po_end(Entry), std::back_inserter(RPOT));
|
|
std::reverse(RPOT.begin(), RPOT.end());
|
|
|
|
assert(RPOT.size() - 1 <= BlockNode::getMaxIndex() &&
|
|
"More nodes in function than Block Frequency Info supports");
|
|
|
|
DEBUG(dbgs() << "reverse-post-order-traversal\n");
|
|
for (rpot_iterator I = rpot_begin(), E = rpot_end(); I != E; ++I) {
|
|
BlockNode Node = getNode(I);
|
|
DEBUG(dbgs() << " - " << getIndex(I) << ": " << getBlockName(Node) << "\n");
|
|
Nodes[*I] = Node;
|
|
}
|
|
|
|
Working.reserve(RPOT.size());
|
|
for (size_t Index = 0; Index < RPOT.size(); ++Index)
|
|
Working.emplace_back(Index);
|
|
Freqs.resize(RPOT.size());
|
|
}
|
|
|
|
template <class BT> void BlockFrequencyInfoImpl<BT>::initializeLoops() {
|
|
DEBUG(dbgs() << "loop-detection\n");
|
|
if (LI->empty())
|
|
return;
|
|
|
|
// Visit loops top down and assign them an index.
|
|
std::deque<std::pair<const LoopT *, LoopData *>> Q;
|
|
for (const LoopT *L : *LI)
|
|
Q.emplace_back(L, nullptr);
|
|
while (!Q.empty()) {
|
|
const LoopT *Loop = Q.front().first;
|
|
LoopData *Parent = Q.front().second;
|
|
Q.pop_front();
|
|
|
|
BlockNode Header = getNode(Loop->getHeader());
|
|
assert(Header.isValid());
|
|
|
|
Loops.emplace_back(Parent, Header);
|
|
Working[Header.Index].Loop = &Loops.back();
|
|
DEBUG(dbgs() << " - loop = " << getBlockName(Header) << "\n");
|
|
|
|
for (const LoopT *L : *Loop)
|
|
Q.emplace_back(L, &Loops.back());
|
|
}
|
|
|
|
// Visit nodes in reverse post-order and add them to their deepest containing
|
|
// loop.
|
|
for (size_t Index = 0; Index < RPOT.size(); ++Index) {
|
|
// Loop headers have already been mostly mapped.
|
|
if (Working[Index].isLoopHeader()) {
|
|
LoopData *ContainingLoop = Working[Index].getContainingLoop();
|
|
if (ContainingLoop)
|
|
ContainingLoop->Nodes.push_back(Index);
|
|
continue;
|
|
}
|
|
|
|
const LoopT *Loop = LI->getLoopFor(RPOT[Index]);
|
|
if (!Loop)
|
|
continue;
|
|
|
|
// Add this node to its containing loop's member list.
|
|
BlockNode Header = getNode(Loop->getHeader());
|
|
assert(Header.isValid());
|
|
const auto &HeaderData = Working[Header.Index];
|
|
assert(HeaderData.isLoopHeader());
|
|
|
|
Working[Index].Loop = HeaderData.Loop;
|
|
HeaderData.Loop->Nodes.push_back(Index);
|
|
DEBUG(dbgs() << " - loop = " << getBlockName(Header)
|
|
<< ": member = " << getBlockName(Index) << "\n");
|
|
}
|
|
}
|
|
|
|
template <class BT> void BlockFrequencyInfoImpl<BT>::computeMassInLoops() {
|
|
// Visit loops with the deepest first, and the top-level loops last.
|
|
for (auto L = Loops.rbegin(), E = Loops.rend(); L != E; ++L) {
|
|
if (computeMassInLoop(*L))
|
|
continue;
|
|
auto Next = std::next(L);
|
|
computeIrreducibleMass(&*L, L.base());
|
|
L = std::prev(Next);
|
|
if (computeMassInLoop(*L))
|
|
continue;
|
|
llvm_unreachable("unhandled irreducible control flow");
|
|
}
|
|
}
|
|
|
|
template <class BT>
|
|
bool BlockFrequencyInfoImpl<BT>::computeMassInLoop(LoopData &Loop) {
|
|
// Compute mass in loop.
|
|
DEBUG(dbgs() << "compute-mass-in-loop: " << getLoopName(Loop) << "\n");
|
|
|
|
if (Loop.isIrreducible()) {
|
|
BlockMass Remaining = BlockMass::getFull();
|
|
for (uint32_t H = 0; H < Loop.NumHeaders; ++H) {
|
|
auto &Mass = Working[Loop.Nodes[H].Index].getMass();
|
|
Mass = Remaining * BranchProbability(1, Loop.NumHeaders - H);
|
|
Remaining -= Mass;
|
|
}
|
|
for (const BlockNode &M : Loop.Nodes)
|
|
if (!propagateMassToSuccessors(&Loop, M))
|
|
llvm_unreachable("unhandled irreducible control flow");
|
|
} else {
|
|
Working[Loop.getHeader().Index].getMass() = BlockMass::getFull();
|
|
if (!propagateMassToSuccessors(&Loop, Loop.getHeader()))
|
|
llvm_unreachable("irreducible control flow to loop header!?");
|
|
for (const BlockNode &M : Loop.members())
|
|
if (!propagateMassToSuccessors(&Loop, M))
|
|
// Irreducible backedge.
|
|
return false;
|
|
}
|
|
|
|
computeLoopScale(Loop);
|
|
packageLoop(Loop);
|
|
return true;
|
|
}
|
|
|
|
template <class BT>
|
|
bool BlockFrequencyInfoImpl<BT>::tryToComputeMassInFunction() {
|
|
// Compute mass in function.
|
|
DEBUG(dbgs() << "compute-mass-in-function\n");
|
|
assert(!Working.empty() && "no blocks in function");
|
|
assert(!Working[0].isLoopHeader() && "entry block is a loop header");
|
|
|
|
Working[0].getMass() = BlockMass::getFull();
|
|
for (rpot_iterator I = rpot_begin(), IE = rpot_end(); I != IE; ++I) {
|
|
// Check for nodes that have been packaged.
|
|
BlockNode Node = getNode(I);
|
|
if (Working[Node.Index].isPackaged())
|
|
continue;
|
|
|
|
if (!propagateMassToSuccessors(nullptr, Node))
|
|
return false;
|
|
}
|
|
return true;
|
|
}
|
|
|
|
template <class BT> void BlockFrequencyInfoImpl<BT>::computeMassInFunction() {
|
|
if (tryToComputeMassInFunction())
|
|
return;
|
|
computeIrreducibleMass(nullptr, Loops.begin());
|
|
if (tryToComputeMassInFunction())
|
|
return;
|
|
llvm_unreachable("unhandled irreducible control flow");
|
|
}
|
|
|
|
/// \note This should be a lambda, but that crashes GCC 4.7.
|
|
namespace bfi_detail {
|
|
template <class BT> struct BlockEdgesAdder {
|
|
typedef BT BlockT;
|
|
typedef BlockFrequencyInfoImplBase::LoopData LoopData;
|
|
typedef GraphTraits<const BlockT *> Successor;
|
|
|
|
const BlockFrequencyInfoImpl<BT> &BFI;
|
|
explicit BlockEdgesAdder(const BlockFrequencyInfoImpl<BT> &BFI)
|
|
: BFI(BFI) {}
|
|
void operator()(IrreducibleGraph &G, IrreducibleGraph::IrrNode &Irr,
|
|
const LoopData *OuterLoop) {
|
|
const BlockT *BB = BFI.RPOT[Irr.Node.Index];
|
|
for (auto I = Successor::child_begin(BB), E = Successor::child_end(BB);
|
|
I != E; ++I)
|
|
G.addEdge(Irr, BFI.getNode(*I), OuterLoop);
|
|
}
|
|
};
|
|
}
|
|
template <class BT>
|
|
void BlockFrequencyInfoImpl<BT>::computeIrreducibleMass(
|
|
LoopData *OuterLoop, std::list<LoopData>::iterator Insert) {
|
|
DEBUG(dbgs() << "analyze-irreducible-in-";
|
|
if (OuterLoop) dbgs() << "loop: " << getLoopName(*OuterLoop) << "\n";
|
|
else dbgs() << "function\n");
|
|
|
|
using namespace bfi_detail;
|
|
// Ideally, addBlockEdges() would be declared here as a lambda, but that
|
|
// crashes GCC 4.7.
|
|
BlockEdgesAdder<BT> addBlockEdges(*this);
|
|
IrreducibleGraph G(*this, OuterLoop, addBlockEdges);
|
|
|
|
for (auto &L : analyzeIrreducible(G, OuterLoop, Insert))
|
|
computeMassInLoop(L);
|
|
|
|
if (!OuterLoop)
|
|
return;
|
|
updateLoopWithIrreducible(*OuterLoop);
|
|
}
|
|
|
|
template <class BT>
|
|
bool
|
|
BlockFrequencyInfoImpl<BT>::propagateMassToSuccessors(LoopData *OuterLoop,
|
|
const BlockNode &Node) {
|
|
DEBUG(dbgs() << " - node: " << getBlockName(Node) << "\n");
|
|
// Calculate probability for successors.
|
|
Distribution Dist;
|
|
if (auto *Loop = Working[Node.Index].getPackagedLoop()) {
|
|
assert(Loop != OuterLoop && "Cannot propagate mass in a packaged loop");
|
|
if (!addLoopSuccessorsToDist(OuterLoop, *Loop, Dist))
|
|
// Irreducible backedge.
|
|
return false;
|
|
} else {
|
|
const BlockT *BB = getBlock(Node);
|
|
for (auto SI = Successor::child_begin(BB), SE = Successor::child_end(BB);
|
|
SI != SE; ++SI)
|
|
// Do not dereference SI, or getEdgeWeight() is linear in the number of
|
|
// successors.
|
|
if (!addToDist(Dist, OuterLoop, Node, getNode(*SI),
|
|
BPI->getEdgeWeight(BB, SI)))
|
|
// Irreducible backedge.
|
|
return false;
|
|
}
|
|
|
|
// Distribute mass to successors, saving exit and backedge data in the
|
|
// loop header.
|
|
distributeMass(Node, OuterLoop, Dist);
|
|
return true;
|
|
}
|
|
|
|
template <class BT>
|
|
raw_ostream &BlockFrequencyInfoImpl<BT>::print(raw_ostream &OS) const {
|
|
if (!F)
|
|
return OS;
|
|
OS << "block-frequency-info: " << F->getName() << "\n";
|
|
for (const BlockT &BB : *F)
|
|
OS << " - " << bfi_detail::getBlockName(&BB)
|
|
<< ": float = " << getFloatingBlockFreq(&BB)
|
|
<< ", int = " << getBlockFreq(&BB).getFrequency() << "\n";
|
|
|
|
// Add an extra newline for readability.
|
|
OS << "\n";
|
|
return OS;
|
|
}
|
|
|
|
} // end namespace llvm
|
|
|
|
#undef DEBUG_TYPE
|
|
|
|
#endif
|