| //==- BlockFrequencyInfoImpl.h - Block Frequency Implementation --*- C++ -*-==// |
| // |
| // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. |
| // See https://llvm.org/LICENSE.txt for license information. |
| // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception |
| // |
| //===----------------------------------------------------------------------===// |
| // |
| // Shared implementation of BlockFrequency for IR and Machine Instructions. |
| // See the documentation below for BlockFrequencyInfoImpl for details. |
| // |
| //===----------------------------------------------------------------------===// |
| |
| #ifndef LLVM_ANALYSIS_BLOCKFREQUENCYINFOIMPL_H |
| #define LLVM_ANALYSIS_BLOCKFREQUENCYINFOIMPL_H |
| |
| #include "llvm/ADT/DenseMap.h" |
| #include "llvm/ADT/DenseSet.h" |
| #include "llvm/ADT/GraphTraits.h" |
| #include "llvm/ADT/Optional.h" |
| #include "llvm/ADT/PostOrderIterator.h" |
| #include "llvm/ADT/SmallVector.h" |
| #include "llvm/ADT/SparseBitVector.h" |
| #include "llvm/ADT/Twine.h" |
| #include "llvm/ADT/iterator_range.h" |
| #include "llvm/IR/BasicBlock.h" |
| #include "llvm/Support/BlockFrequency.h" |
| #include "llvm/Support/BranchProbability.h" |
| #include "llvm/Support/DOTGraphTraits.h" |
| #include "llvm/Support/Debug.h" |
| #include "llvm/Support/ErrorHandling.h" |
| #include "llvm/Support/Format.h" |
| #include "llvm/Support/ScaledNumber.h" |
| #include "llvm/Support/raw_ostream.h" |
| #include <algorithm> |
| #include <cassert> |
| #include <cstddef> |
| #include <cstdint> |
| #include <deque> |
| #include <iterator> |
| #include <limits> |
| #include <list> |
| #include <string> |
| #include <utility> |
| #include <vector> |
| |
| #define DEBUG_TYPE "block-freq" |
| |
| namespace llvm { |
| |
| class BranchProbabilityInfo; |
| class Function; |
| class Loop; |
| class LoopInfo; |
| class MachineBasicBlock; |
| class MachineBranchProbabilityInfo; |
| class MachineFunction; |
| class MachineLoop; |
| class MachineLoopInfo; |
| |
| namespace bfi_detail { |
| |
| struct IrreducibleGraph; |
| |
| // This is part of a workaround for a GCC 4.7 crash on lambdas. |
| template <class BT> struct BlockEdgesAdder; |
| |
| /// Mass of a block. |
| /// |
| /// This class implements a sort of fixed-point fraction always between 0.0 and |
| /// 1.0. getMass() == std::numeric_limits<uint64_t>::max() indicates a value of |
| /// 1.0. |
| /// |
| /// Masses can be added and subtracted. Simple saturation arithmetic is used, |
| /// so arithmetic operations never overflow or underflow. |
| /// |
| /// Masses can be multiplied. Multiplication treats full mass as 1.0 and uses |
| /// an inexpensive floating-point algorithm that's off-by-one (almost, but not |
| /// quite, maximum precision). |
| /// |
| /// Masses can be scaled by \a BranchProbability at maximum precision. |
| class BlockMass { |
| uint64_t Mass = 0; |
| |
| public: |
| BlockMass() = default; |
| explicit BlockMass(uint64_t Mass) : Mass(Mass) {} |
| |
| static BlockMass getEmpty() { return BlockMass(); } |
| |
| static BlockMass getFull() { |
| return BlockMass(std::numeric_limits<uint64_t>::max()); |
| } |
| |
| uint64_t getMass() const { return Mass; } |
| |
| bool isFull() const { return Mass == std::numeric_limits<uint64_t>::max(); } |
| bool isEmpty() const { return !Mass; } |
| |
| bool operator!() const { return isEmpty(); } |
| |
| /// Add another mass. |
| /// |
| /// Adds another mass, saturating at \a isFull() rather than overflowing. |
| BlockMass &operator+=(BlockMass X) { |
| uint64_t Sum = Mass + X.Mass; |
| Mass = Sum < Mass ? std::numeric_limits<uint64_t>::max() : Sum; |
| return *this; |
| } |
| |
| /// Subtract another mass. |
| /// |
| /// Subtracts another mass, saturating at \a isEmpty() rather than |
| /// undeflowing. |
| BlockMass &operator-=(BlockMass X) { |
| uint64_t Diff = Mass - X.Mass; |
| Mass = Diff > Mass ? 0 : Diff; |
| return *this; |
| } |
| |
| BlockMass &operator*=(BranchProbability P) { |
| Mass = P.scale(Mass); |
| return *this; |
| } |
| |
| bool operator==(BlockMass X) const { return Mass == X.Mass; } |
| bool operator!=(BlockMass X) const { return Mass != X.Mass; } |
| bool operator<=(BlockMass X) const { return Mass <= X.Mass; } |
| bool operator>=(BlockMass X) const { return Mass >= X.Mass; } |
| bool operator<(BlockMass X) const { return Mass < X.Mass; } |
| bool operator>(BlockMass X) const { return Mass > X.Mass; } |
| |
| /// Convert to scaled number. |
| /// |
| /// Convert to \a ScaledNumber. \a isFull() gives 1.0, while \a isEmpty() |
| /// gives slightly above 0.0. |
| ScaledNumber<uint64_t> toScaled() const; |
| |
| void dump() const; |
| raw_ostream &print(raw_ostream &OS) const; |
| }; |
| |
| inline BlockMass operator+(BlockMass L, BlockMass R) { |
| return BlockMass(L) += R; |
| } |
| inline BlockMass operator-(BlockMass L, BlockMass R) { |
| return BlockMass(L) -= R; |
| } |
| inline BlockMass operator*(BlockMass L, BranchProbability R) { |
| return BlockMass(L) *= R; |
| } |
| inline BlockMass operator*(BranchProbability L, BlockMass R) { |
| return BlockMass(R) *= L; |
| } |
| |
| inline raw_ostream &operator<<(raw_ostream &OS, BlockMass X) { |
| return X.print(OS); |
| } |
| |
| } // end namespace bfi_detail |
| |
| /// Base class for BlockFrequencyInfoImpl |
| /// |
| /// BlockFrequencyInfoImplBase has supporting data structures and some |
| /// algorithms for BlockFrequencyInfoImplBase. Only algorithms that depend on |
| /// the block type (or that call such algorithms) are skipped here. |
| /// |
| /// Nevertheless, the majority of the overall algorithm documention lives with |
| /// BlockFrequencyInfoImpl. See there for details. |
| class BlockFrequencyInfoImplBase { |
| public: |
| using Scaled64 = ScaledNumber<uint64_t>; |
| using BlockMass = bfi_detail::BlockMass; |
| |
| /// Representative of a block. |
| /// |
| /// This is a simple wrapper around an index into the reverse-post-order |
| /// traversal of the blocks. |
| /// |
| /// Unlike a block pointer, its order has meaning (location in the |
| /// topological sort) and it's class is the same regardless of block type. |
| struct BlockNode { |
| using IndexType = uint32_t; |
| |
| IndexType Index; |
| |
| BlockNode() : Index(std::numeric_limits<uint32_t>::max()) {} |
| BlockNode(IndexType Index) : Index(Index) {} |
| |
| bool operator==(const BlockNode &X) const { return Index == X.Index; } |
| bool operator!=(const BlockNode &X) const { return Index != X.Index; } |
| bool operator<=(const BlockNode &X) const { return Index <= X.Index; } |
| bool operator>=(const BlockNode &X) const { return Index >= X.Index; } |
| bool operator<(const BlockNode &X) const { return Index < X.Index; } |
| bool operator>(const BlockNode &X) const { return Index > X.Index; } |
| |
| bool isValid() const { return Index <= getMaxIndex(); } |
| |
| static size_t getMaxIndex() { |
| return std::numeric_limits<uint32_t>::max() - 1; |
| } |
| }; |
| |
| /// Stats about a block itself. |
| struct FrequencyData { |
| Scaled64 Scaled; |
| uint64_t Integer; |
| }; |
| |
| /// Data about a loop. |
| /// |
| /// Contains the data necessary to represent a loop as a pseudo-node once it's |
| /// packaged. |
| struct LoopData { |
| using ExitMap = SmallVector<std::pair<BlockNode, BlockMass>, 4>; |
| using NodeList = SmallVector<BlockNode, 4>; |
| using HeaderMassList = SmallVector<BlockMass, 1>; |
| |
| LoopData *Parent; ///< The parent loop. |
| bool IsPackaged = false; ///< Whether this has been packaged. |
| uint32_t NumHeaders = 1; ///< Number of headers. |
| ExitMap Exits; ///< Successor edges (and weights). |
| NodeList Nodes; ///< Header and the members of the loop. |
| HeaderMassList BackedgeMass; ///< Mass returned to each loop header. |
| BlockMass Mass; |
| Scaled64 Scale; |
| |
| LoopData(LoopData *Parent, const BlockNode &Header) |
| : Parent(Parent), Nodes(1, Header), BackedgeMass(1) {} |
| |
| template <class It1, class It2> |
| LoopData(LoopData *Parent, It1 FirstHeader, It1 LastHeader, It2 FirstOther, |
| It2 LastOther) |
| : Parent(Parent), Nodes(FirstHeader, LastHeader) { |
| NumHeaders = Nodes.size(); |
| Nodes.insert(Nodes.end(), FirstOther, LastOther); |
| BackedgeMass.resize(NumHeaders); |
| } |
| |
| bool isHeader(const BlockNode &Node) const { |
| if (isIrreducible()) |
| return std::binary_search(Nodes.begin(), Nodes.begin() + NumHeaders, |
| Node); |
| return Node == Nodes[0]; |
| } |
| |
| BlockNode getHeader() const { return Nodes[0]; } |
| bool isIrreducible() const { return NumHeaders > 1; } |
| |
| HeaderMassList::difference_type getHeaderIndex(const BlockNode &B) { |
| assert(isHeader(B) && "this is only valid on loop header blocks"); |
| if (isIrreducible()) |
| return std::lower_bound(Nodes.begin(), Nodes.begin() + NumHeaders, B) - |
| Nodes.begin(); |
| return 0; |
| } |
| |
| NodeList::const_iterator members_begin() const { |
| return Nodes.begin() + NumHeaders; |
| } |
| |
| NodeList::const_iterator members_end() const { return Nodes.end(); } |
| iterator_range<NodeList::const_iterator> members() const { |
| return make_range(members_begin(), members_end()); |
| } |
| }; |
| |
| /// Index of loop information. |
| struct WorkingData { |
| BlockNode Node; ///< This node. |
| LoopData *Loop = nullptr; ///< The loop this block is inside. |
| BlockMass Mass; ///< Mass distribution from the entry block. |
| |
| WorkingData(const BlockNode &Node) : Node(Node) {} |
| |
| bool isLoopHeader() const { return Loop && Loop->isHeader(Node); } |
| |
| bool isDoubleLoopHeader() const { |
| return isLoopHeader() && Loop->Parent && Loop->Parent->isIrreducible() && |
| Loop->Parent->isHeader(Node); |
| } |
| |
| LoopData *getContainingLoop() const { |
| if (!isLoopHeader()) |
| return Loop; |
| if (!isDoubleLoopHeader()) |
| return Loop->Parent; |
| return Loop->Parent->Parent; |
| } |
| |
| /// Resolve a node to its representative. |
| /// |
| /// Get the node currently representing Node, which could be a containing |
| /// loop. |
| /// |
| /// This function should only be called when distributing mass. As long as |
| /// there are no irreducible edges to Node, then it will have complexity |
| /// O(1) in this context. |
| /// |
| /// In general, the complexity is O(L), where L is the number of loop |
| /// headers Node has been packaged into. Since this method is called in |
| /// the context of distributing mass, L will be the number of loop headers |
| /// an early exit edge jumps out of. |
| BlockNode getResolvedNode() const { |
| auto L = getPackagedLoop(); |
| return L ? L->getHeader() : Node; |
| } |
| |
| LoopData *getPackagedLoop() const { |
| if (!Loop || !Loop->IsPackaged) |
| return nullptr; |
| auto L = Loop; |
| while (L->Parent && L->Parent->IsPackaged) |
| L = L->Parent; |
| return L; |
| } |
| |
| /// Get the appropriate mass for a node. |
| /// |
| /// Get appropriate mass for Node. If Node is a loop-header (whose loop |
| /// has been packaged), returns the mass of its pseudo-node. If it's a |
| /// node inside a packaged loop, it returns the loop's mass. |
| BlockMass &getMass() { |
| if (!isAPackage()) |
| return Mass; |
| if (!isADoublePackage()) |
| return Loop->Mass; |
| return Loop->Parent->Mass; |
| } |
| |
| /// Has ContainingLoop been packaged up? |
| bool isPackaged() const { return getResolvedNode() != Node; } |
| |
| /// Has Loop been packaged up? |
| bool isAPackage() const { return isLoopHeader() && Loop->IsPackaged; } |
| |
| /// Has Loop been packaged up twice? |
| bool isADoublePackage() const { |
| return isDoubleLoopHeader() && Loop->Parent->IsPackaged; |
| } |
| }; |
| |
| /// Unscaled probability weight. |
| /// |
| /// Probability weight for an edge in the graph (including the |
| /// successor/target node). |
| /// |
| /// All edges in the original function are 32-bit. However, exit edges from |
| /// loop packages are taken from 64-bit exit masses, so we need 64-bits of |
| /// space in general. |
| /// |
| /// In addition to the raw weight amount, Weight stores the type of the edge |
| /// in the current context (i.e., the context of the loop being processed). |
| /// Is this a local edge within the loop, an exit from the loop, or a |
| /// backedge to the loop header? |
| struct Weight { |
| enum DistType { Local, Exit, Backedge }; |
| DistType Type = Local; |
| BlockNode TargetNode; |
| uint64_t Amount = 0; |
| |
| Weight() = default; |
| Weight(DistType Type, BlockNode TargetNode, uint64_t Amount) |
| : Type(Type), TargetNode(TargetNode), Amount(Amount) {} |
| }; |
| |
| /// Distribution of unscaled probability weight. |
| /// |
| /// Distribution of unscaled probability weight to a set of successors. |
| /// |
| /// This class collates the successor edge weights for later processing. |
| /// |
| /// \a DidOverflow indicates whether \a Total did overflow while adding to |
| /// the distribution. It should never overflow twice. |
| struct Distribution { |
| using WeightList = SmallVector<Weight, 4>; |
| |
| WeightList Weights; ///< Individual successor weights. |
| uint64_t Total = 0; ///< Sum of all weights. |
| bool DidOverflow = false; ///< Whether \a Total did overflow. |
| |
| Distribution() = default; |
| |
| void addLocal(const BlockNode &Node, uint64_t Amount) { |
| add(Node, Amount, Weight::Local); |
| } |
| |
| void addExit(const BlockNode &Node, uint64_t Amount) { |
| add(Node, Amount, Weight::Exit); |
| } |
| |
| void addBackedge(const BlockNode &Node, uint64_t Amount) { |
| add(Node, Amount, Weight::Backedge); |
| } |
| |
| /// Normalize the distribution. |
| /// |
| /// Combines multiple edges to the same \a Weight::TargetNode and scales |
| /// down so that \a Total fits into 32-bits. |
| /// |
| /// This is linear in the size of \a Weights. For the vast majority of |
| /// cases, adjacent edge weights are combined by sorting WeightList and |
| /// combining adjacent weights. However, for very large edge lists an |
| /// auxiliary hash table is used. |
| void normalize(); |
| |
| private: |
| void add(const BlockNode &Node, uint64_t Amount, Weight::DistType Type); |
| }; |
| |
| /// Data about each block. This is used downstream. |
| std::vector<FrequencyData> Freqs; |
| |
| /// Whether each block is an irreducible loop header. |
| /// This is used downstream. |
| SparseBitVector<> IsIrrLoopHeader; |
| |
| /// Loop data: see initializeLoops(). |
| std::vector<WorkingData> Working; |
| |
| /// Indexed information about loops. |
| std::list<LoopData> Loops; |
| |
| /// Virtual destructor. |
| /// |
| /// Need a virtual destructor to mask the compiler warning about |
| /// getBlockName(). |
| virtual ~BlockFrequencyInfoImplBase() = default; |
| |
| /// Add all edges out of a packaged loop to the distribution. |
| /// |
| /// Adds all edges from LocalLoopHead to Dist. Calls addToDist() to add each |
| /// successor edge. |
| /// |
| /// \return \c true unless there's an irreducible backedge. |
| bool addLoopSuccessorsToDist(const LoopData *OuterLoop, LoopData &Loop, |
| Distribution &Dist); |
| |
| /// Add an edge to the distribution. |
| /// |
| /// Adds an edge to Succ to Dist. If \c LoopHead.isValid(), then whether the |
| /// edge is local/exit/backedge is in the context of LoopHead. Otherwise, |
| /// every edge should be a local edge (since all the loops are packaged up). |
| /// |
| /// \return \c true unless aborted due to an irreducible backedge. |
| bool addToDist(Distribution &Dist, const LoopData *OuterLoop, |
| const BlockNode &Pred, const BlockNode &Succ, uint64_t Weight); |
| |
| LoopData &getLoopPackage(const BlockNode &Head) { |
| assert(Head.Index < Working.size()); |
| assert(Working[Head.Index].isLoopHeader()); |
| return *Working[Head.Index].Loop; |
| } |
| |
| /// Analyze irreducible SCCs. |
| /// |
| /// Separate irreducible SCCs from \c G, which is an explict graph of \c |
| /// OuterLoop (or the top-level function, if \c OuterLoop is \c nullptr). |
| /// Insert them into \a Loops before \c Insert. |
| /// |
| /// \return the \c LoopData nodes representing the irreducible SCCs. |
| iterator_range<std::list<LoopData>::iterator> |
| analyzeIrreducible(const bfi_detail::IrreducibleGraph &G, LoopData *OuterLoop, |
| std::list<LoopData>::iterator Insert); |
| |
| /// Update a loop after packaging irreducible SCCs inside of it. |
| /// |
| /// Update \c OuterLoop. Before finding irreducible control flow, it was |
| /// partway through \a computeMassInLoop(), so \a LoopData::Exits and \a |
| /// LoopData::BackedgeMass need to be reset. Also, nodes that were packaged |
| /// up need to be removed from \a OuterLoop::Nodes. |
| void updateLoopWithIrreducible(LoopData &OuterLoop); |
| |
| /// Distribute mass according to a distribution. |
| /// |
| /// Distributes the mass in Source according to Dist. If LoopHead.isValid(), |
| /// backedges and exits are stored in its entry in Loops. |
| /// |
| /// Mass is distributed in parallel from two copies of the source mass. |
| void distributeMass(const BlockNode &Source, LoopData *OuterLoop, |
| Distribution &Dist); |
| |
| /// Compute the loop scale for a loop. |
| void computeLoopScale(LoopData &Loop); |
| |
| /// Adjust the mass of all headers in an irreducible loop. |
| /// |
| /// Initially, irreducible loops are assumed to distribute their mass |
| /// equally among its headers. This can lead to wrong frequency estimates |
| /// since some headers may be executed more frequently than others. |
| /// |
| /// This adjusts header mass distribution so it matches the weights of |
| /// the backedges going into each of the loop headers. |
| void adjustLoopHeaderMass(LoopData &Loop); |
| |
| void distributeIrrLoopHeaderMass(Distribution &Dist); |
| |
| /// Package up a loop. |
| void packageLoop(LoopData &Loop); |
| |
| /// Unwrap loops. |
| void unwrapLoops(); |
| |
| /// Finalize frequency metrics. |
| /// |
| /// Calculates final frequencies and cleans up no-longer-needed data |
| /// structures. |
| void finalizeMetrics(); |
| |
| /// Clear all memory. |
| void clear(); |
| |
| virtual std::string getBlockName(const BlockNode &Node) const; |
| std::string getLoopName(const LoopData &Loop) const; |
| |
| virtual raw_ostream &print(raw_ostream &OS) const { return OS; } |
| void dump() const { print(dbgs()); } |
| |
| Scaled64 getFloatingBlockFreq(const BlockNode &Node) const; |
| |
| BlockFrequency getBlockFreq(const BlockNode &Node) const; |
| Optional<uint64_t> getBlockProfileCount(const Function &F, |
| const BlockNode &Node, |
| bool AllowSynthetic = false) const; |
| Optional<uint64_t> getProfileCountFromFreq(const Function &F, |
| uint64_t Freq, |
| bool AllowSynthetic = false) const; |
| bool isIrrLoopHeader(const BlockNode &Node); |
| |
| void setBlockFreq(const BlockNode &Node, uint64_t Freq); |
| |
| raw_ostream &printBlockFreq(raw_ostream &OS, const BlockNode &Node) const; |
| raw_ostream &printBlockFreq(raw_ostream &OS, |
| const BlockFrequency &Freq) const; |
| |
| uint64_t getEntryFreq() const { |
| assert(!Freqs.empty()); |
| return Freqs[0].Integer; |
| } |
| }; |
| |
| namespace bfi_detail { |
| |
| template <class BlockT> struct TypeMap {}; |
| template <> struct TypeMap<BasicBlock> { |
| using BlockT = BasicBlock; |
| using FunctionT = Function; |
| using BranchProbabilityInfoT = BranchProbabilityInfo; |
| using LoopT = Loop; |
| using LoopInfoT = LoopInfo; |
| }; |
| template <> struct TypeMap<MachineBasicBlock> { |
| using BlockT = MachineBasicBlock; |
| using FunctionT = MachineFunction; |
| using BranchProbabilityInfoT = MachineBranchProbabilityInfo; |
| using LoopT = MachineLoop; |
| using LoopInfoT = MachineLoopInfo; |
| }; |
| |
| /// Get the name of a MachineBasicBlock. |
| /// |
| /// Get the name of a MachineBasicBlock. It's templated so that including from |
| /// CodeGen is unnecessary (that would be a layering issue). |
| /// |
| /// This is used mainly for debug output. The name is similar to |
| /// MachineBasicBlock::getFullName(), but skips the name of the function. |
| 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(); |
| } |
| /// Get the name of a BasicBlock. |
| template <> inline std::string getBlockName(const BasicBlock *BB) { |
| assert(BB && "Unexpected nullptr"); |
| return BB->getName().str(); |
| } |
| |
| /// 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 { |
| using BFIBase = BlockFrequencyInfoImplBase; |
| |
| BFIBase &BFI; |
| |
| using BlockNode = BFIBase::BlockNode; |
| struct IrrNode { |
| BlockNode Node; |
| unsigned NumIn = 0; |
| std::deque<const IrrNode *> Edges; |
| |
| IrrNode(const BlockNode &Node) : Node(Node) {} |
| |
| using iterator = std::deque<const IrrNode *>::const_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 = nullptr; |
| std::vector<IrrNode> Nodes; |
| SmallDenseMap<uint32_t, IrrNode *, 4> Lookup; |
| |
| /// 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) { |
| 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); |
| } |
| |
| } // end namespace bfi_detail |
| |
| /// 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(). |
| /// |
| /// In the case of irreducible loops, instead of a single loop header, |
| /// there will be several. The computation of backedge masses is similar |
| /// but instead of having a single backedge mass, there will be one |
| /// backedge per loop header. In these cases, each backedge will carry |
| /// a mass proportional to the edge weights along the corresponding |
| /// path. |
| /// |
| /// At the end of propagation, the full mass assigned to the loop will be |
| /// distributed among the loop headers proportionally according to the |
| /// mass flowing through their backedges. |
| /// |
| /// 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. |
| /// |
| /// - 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. |
| /// |
| /// - 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 { |
| // This is part of a workaround for a GCC 4.7 crash on lambdas. |
| friend struct bfi_detail::BlockEdgesAdder<BT>; |
| |
| using BlockT = typename bfi_detail::TypeMap<BT>::BlockT; |
| using FunctionT = typename bfi_detail::TypeMap<BT>::FunctionT; |
| using BranchProbabilityInfoT = |
| typename bfi_detail::TypeMap<BT>::BranchProbabilityInfoT; |
| using LoopT = typename bfi_detail::TypeMap<BT>::LoopT; |
| using LoopInfoT = typename bfi_detail::TypeMap<BT>::LoopInfoT; |
| using Successor = GraphTraits<const BlockT *>; |
| using Predecessor = GraphTraits<Inverse<const BlockT *>>; |
| |
| const BranchProbabilityInfoT *BPI = nullptr; |
| const LoopInfoT *LI = nullptr; |
| const FunctionT *F = nullptr; |
| |
| // All blocks in reverse postorder. |
| std::vector<const BlockT *> RPOT; |
| DenseMap<const BlockT *, BlockNode> Nodes; |
| |
| using rpot_iterator = typename std::vector<const BlockT *>::const_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]; |
| } |
| |
| /// Run (and save) a post-order traversal. |
| /// |
| /// Saves a reverse post-order traversal of all the nodes in \a F. |
| void initializeRPOT(); |
| |
| /// 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(); |
| |
| /// 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); |
| |
| /// 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); |
| |
| /// 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(); |
| |
| /// 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 last loop successfully processed by \a |
| /// computeMassInLoop(). |
| /// \pre \c OuterLoop has irreducible SCCs. |
| void computeIrreducibleMass(LoopData *OuterLoop, |
| std::list<LoopData>::iterator Insert); |
| |
| /// 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(); |
| |
| /// 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: |
| BlockFrequencyInfoImpl() = default; |
| |
| const FunctionT *getFunction() const { return F; } |
| |
| void calculate(const FunctionT &F, const BranchProbabilityInfoT &BPI, |
| const LoopInfoT &LI); |
| |
| using BlockFrequencyInfoImplBase::getEntryFreq; |
| |
| BlockFrequency getBlockFreq(const BlockT *BB) const { |
| return BlockFrequencyInfoImplBase::getBlockFreq(getNode(BB)); |
| } |
| |
| Optional<uint64_t> getBlockProfileCount(const Function &F, |
| const BlockT *BB, |
| bool AllowSynthetic = false) const { |
| return BlockFrequencyInfoImplBase::getBlockProfileCount(F, getNode(BB), |
| AllowSynthetic); |
| } |
| |
| Optional<uint64_t> getProfileCountFromFreq(const Function &F, |
| uint64_t Freq, |
| bool AllowSynthetic = false) const { |
| return BlockFrequencyInfoImplBase::getProfileCountFromFreq(F, Freq, |
| AllowSynthetic); |
| } |
| |
| bool isIrrLoopHeader(const BlockT *BB) { |
| return BlockFrequencyInfoImplBase::isIrrLoopHeader(getNode(BB)); |
| } |
| |
| void setBlockFreq(const BlockT *BB, uint64_t Freq); |
| |
| Scaled64 getFloatingBlockFreq(const BlockT *BB) const { |
| return BlockFrequencyInfoImplBase::getFloatingBlockFreq(getNode(BB)); |
| } |
| |
| const BranchProbabilityInfoT &getBPI() const { return *BPI; } |
| |
| /// 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>::calculate(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. |
| LLVM_DEBUG(dbgs() << "\nblock-frequency: " << F.getName() |
| << "\n=================" |
| << std::string(F.getName().size(), '=') << "\n"); |
| initializeRPOT(); |
| initializeLoops(); |
| |
| // Visit loops in post-order to find the local mass distribution, and then do |
| // the full function. |
| computeMassInLoops(); |
| computeMassInFunction(); |
| unwrapLoops(); |
| finalizeMetrics(); |
| } |
| |
| template <class BT> |
| void BlockFrequencyInfoImpl<BT>::setBlockFreq(const BlockT *BB, uint64_t Freq) { |
| if (Nodes.count(BB)) |
| BlockFrequencyInfoImplBase::setBlockFreq(getNode(BB), Freq); |
| else { |
| // If BB is a newly added block after BFI is done, we need to create a new |
| // BlockNode for it assigned with a new index. The index can be determined |
| // by the size of Freqs. |
| BlockNode NewNode(Freqs.size()); |
| Nodes[BB] = NewNode; |
| Freqs.emplace_back(); |
| BlockFrequencyInfoImplBase::setBlockFreq(NewNode, Freq); |
| } |
| } |
| |
| template <class BT> void BlockFrequencyInfoImpl<BT>::initializeRPOT() { |
| const BlockT *Entry = &F->front(); |
| 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"); |
| |
| LLVM_DEBUG(dbgs() << "reverse-post-order-traversal\n"); |
| for (rpot_iterator I = rpot_begin(), E = rpot_end(); I != E; ++I) { |
| BlockNode Node = getNode(I); |
| LLVM_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() { |
| LLVM_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(); |
| LLVM_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); |
| LLVM_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. |
| LLVM_DEBUG(dbgs() << "compute-mass-in-loop: " << getLoopName(Loop) << "\n"); |
| |
| if (Loop.isIrreducible()) { |
| LLVM_DEBUG(dbgs() << "isIrreducible = true\n"); |
| Distribution Dist; |
| unsigned NumHeadersWithWeight = 0; |
| Optional<uint64_t> MinHeaderWeight; |
| DenseSet<uint32_t> HeadersWithoutWeight; |
| HeadersWithoutWeight.reserve(Loop.NumHeaders); |
| for (uint32_t H = 0; H < Loop.NumHeaders; ++H) { |
| auto &HeaderNode = Loop.Nodes[H]; |
| const BlockT *Block = getBlock(HeaderNode); |
| IsIrrLoopHeader.set(Loop.Nodes[H].Index); |
| Optional<uint64_t> HeaderWeight = Block->getIrrLoopHeaderWeight(); |
| if (!HeaderWeight) { |
| LLVM_DEBUG(dbgs() << "Missing irr loop header metadata on " |
| << getBlockName(HeaderNode) << "\n"); |
| HeadersWithoutWeight.insert(H); |
| continue; |
| } |
| LLVM_DEBUG(dbgs() << getBlockName(HeaderNode) |
| << " has irr loop header weight " |
| << HeaderWeight.getValue() << "\n"); |
| NumHeadersWithWeight++; |
| uint64_t HeaderWeightValue = HeaderWeight.getValue(); |
| if (!MinHeaderWeight || HeaderWeightValue < MinHeaderWeight) |
| MinHeaderWeight = HeaderWeightValue; |
| if (HeaderWeightValue) { |
| Dist.addLocal(HeaderNode, HeaderWeightValue); |
| } |
| } |
| // As a heuristic, if some headers don't have a weight, give them the |
| // minimium weight seen (not to disrupt the existing trends too much by |
| // using a weight that's in the general range of the other headers' weights, |
| // and the minimum seems to perform better than the average.) |
| // FIXME: better update in the passes that drop the header weight. |
| // If no headers have a weight, give them even weight (use weight 1). |
| if (!MinHeaderWeight) |
| MinHeaderWeight = 1; |
| for (uint32_t H : HeadersWithoutWeight) { |
| auto &HeaderNode = Loop.Nodes[H]; |
| assert(!getBlock(HeaderNode)->getIrrLoopHeaderWeight() && |
| "Shouldn't have a weight metadata"); |
| uint64_t MinWeight = MinHeaderWeight.getValue(); |
| LLVM_DEBUG(dbgs() << "Giving weight " << MinWeight << " to " |
| << getBlockName(HeaderNode) << "\n"); |
| if (MinWeight) |
| Dist.addLocal(HeaderNode, MinWeight); |
| } |
| distributeIrrLoopHeaderMass(Dist); |
| for (const BlockNode &M : Loop.Nodes) |
| if (!propagateMassToSuccessors(&Loop, M)) |
| llvm_unreachable("unhandled irreducible control flow"); |
| if (NumHeadersWithWeight == 0) |
| // No headers have a metadata. Adjust header mass. |
| adjustLoopHeaderMass(Loop); |
| } 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. |
| LLVM_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 { |
| using BlockT = BT; |
| using LoopData = BlockFrequencyInfoImplBase::LoopData; |
| using Successor = GraphTraits<const BlockT *>; |
| |
| 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 (const auto Succ : children<const BlockT *>(BB)) |
| G.addEdge(Irr, BFI.getNode(Succ), OuterLoop); |
| } |
| }; |
| |
| } // end namespace bfi_detail |
| |
| template <class BT> |
| void BlockFrequencyInfoImpl<BT>::computeIrreducibleMass( |
| LoopData *OuterLoop, std::list<LoopData>::iterator Insert) { |
| LLVM_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); |
| } |
| |
| // A helper function that converts a branch probability into weight. |
| inline uint32_t getWeightFromBranchProb(const BranchProbability Prob) { |
| return Prob.getNumerator(); |
| } |
| |
| template <class BT> |
| bool |
| BlockFrequencyInfoImpl<BT>::propagateMassToSuccessors(LoopData *OuterLoop, |
| const BlockNode &Node) { |
| LLVM_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 = GraphTraits<const BlockT *>::child_begin(BB), |
| SE = GraphTraits<const BlockT *>::child_end(BB); |
| SI != SE; ++SI) |
| if (!addToDist( |
| Dist, OuterLoop, Node, getNode(*SI), |
| getWeightFromBranchProb(BPI->getEdgeProbability(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).print(OS, 5) |
| << ", int = " << getBlockFreq(&BB).getFrequency(); |
| if (Optional<uint64_t> ProfileCount = |
| BlockFrequencyInfoImplBase::getBlockProfileCount( |
| F->getFunction(), getNode(&BB))) |
| OS << ", count = " << ProfileCount.getValue(); |
| if (Optional<uint64_t> IrrLoopHeaderWeight = |
| BB.getIrrLoopHeaderWeight()) |
| OS << ", irr_loop_header_weight = " << IrrLoopHeaderWeight.getValue(); |
| OS << "\n"; |
| } |
| |
| // Add an extra newline for readability. |
| OS << "\n"; |
| return OS; |
| } |
| |
| // Graph trait base class for block frequency information graph |
| // viewer. |
| |
| enum GVDAGType { GVDT_None, GVDT_Fraction, GVDT_Integer, GVDT_Count }; |
| |
| template <class BlockFrequencyInfoT, class BranchProbabilityInfoT> |
| struct BFIDOTGraphTraitsBase : public DefaultDOTGraphTraits { |
| using GTraits = GraphTraits<BlockFrequencyInfoT *>; |
| using NodeRef = typename GTraits::NodeRef; |
| using EdgeIter = typename GTraits::ChildIteratorType; |
| using NodeIter = typename GTraits::nodes_iterator; |
| |
| uint64_t MaxFrequency = 0; |
| |
| explicit BFIDOTGraphTraitsBase(bool isSimple = false) |
| : DefaultDOTGraphTraits(isSimple) {} |
| |
| static std::string getGraphName(const BlockFrequencyInfoT *G) { |
| return G->getFunction()->getName(); |
| } |
| |
| std::string getNodeAttributes(NodeRef Node, const BlockFrequencyInfoT *Graph, |
| unsigned HotPercentThreshold = 0) { |
| std::string Result; |
| if (!HotPercentThreshold) |
| return Result; |
| |
| // Compute MaxFrequency on the fly: |
| if (!MaxFrequency) { |
| for (NodeIter I = GTraits::nodes_begin(Graph), |
| E = GTraits::nodes_end(Graph); |
| I != E; ++I) { |
| NodeRef N = *I; |
| MaxFrequency = |
| std::max(MaxFrequency, Graph->getBlockFreq(N).getFrequency()); |
| } |
| } |
| BlockFrequency Freq = Graph->getBlockFreq(Node); |
| BlockFrequency HotFreq = |
| (BlockFrequency(MaxFrequency) * |
| BranchProbability::getBranchProbability(HotPercentThreshold, 100)); |
| |
| if (Freq < HotFreq) |
| return Result; |
| |
| raw_string_ostream OS(Result); |
| OS << "color=\"red\""; |
| OS.flush(); |
| return Result; |
| } |
| |
| std::string getNodeLabel(NodeRef Node, const BlockFrequencyInfoT *Graph, |
| GVDAGType GType, int layout_order = -1) { |
| std::string Result; |
| raw_string_ostream OS(Result); |
| |
| if (layout_order != -1) |
| OS << Node->getName() << "[" << layout_order << "] : "; |
| else |
| OS << Node->getName() << " : "; |
| switch (GType) { |
| case GVDT_Fraction: |
| Graph->printBlockFreq(OS, Node); |
| break; |
| case GVDT_Integer: |
| OS << Graph->getBlockFreq(Node).getFrequency(); |
| break; |
| case GVDT_Count: { |
| auto Count = Graph->getBlockProfileCount(Node); |
| if (Count) |
| OS << Count.getValue(); |
| else |
| OS << "Unknown"; |
| break; |
| } |
| case GVDT_None: |
| llvm_unreachable("If we are not supposed to render a graph we should " |
| "never reach this point."); |
| } |
| return Result; |
| } |
| |
| std::string getEdgeAttributes(NodeRef Node, EdgeIter EI, |
| const BlockFrequencyInfoT *BFI, |
| const BranchProbabilityInfoT *BPI, |
| unsigned HotPercentThreshold = 0) { |
| std::string Str; |
| if (!BPI) |
| return Str; |
| |
| BranchProbability BP = BPI->getEdgeProbability(Node, EI); |
| uint32_t N = BP.getNumerator(); |
| uint32_t D = BP.getDenominator(); |
| double Percent = 100.0 * N / D; |
| raw_string_ostream OS(Str); |
| OS << format("label=\"%.1f%%\"", Percent); |
| |
| if (HotPercentThreshold) { |
| BlockFrequency EFreq = BFI->getBlockFreq(Node) * BP; |
| BlockFrequency HotFreq = BlockFrequency(MaxFrequency) * |
| BranchProbability(HotPercentThreshold, 100); |
| |
| if (EFreq >= HotFreq) { |
| OS << ",color=\"red\""; |
| } |
| } |
| |
| OS.flush(); |
| return Str; |
| } |
| }; |
| |
| } // end namespace llvm |
| |
| #undef DEBUG_TYPE |
| |
| #endif // LLVM_ANALYSIS_BLOCKFREQUENCYINFOIMPL_H |