Import prebuilt clang toolchain for linux.
diff --git a/linux-x64/clang/include/llvm/Analysis/BlockFrequencyInfoImpl.h b/linux-x64/clang/include/llvm/Analysis/BlockFrequencyInfoImpl.h
new file mode 100644
index 0000000..40c40b8
--- /dev/null
+++ b/linux-x64/clang/include/llvm/Analysis/BlockFrequencyInfoImpl.h
@@ -0,0 +1,1473 @@
+//==- BlockFrequencyInfoImpl.h - Block Frequency Implementation --*- C++ -*-==//
+//
+// The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+//
+// 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;
+
+/// \brief 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(); }
+
+ /// \brief 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;
+ }
+
+ /// \brief 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; }
+
+ /// \brief 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
+
+template <> struct isPodLike<bfi_detail::BlockMass> {
+ static const bool value = true;
+};
+
+/// \brief 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;
+
+ /// \brief 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 = std::numeric_limits<uint32_t>::max();
+
+ BlockNode() = default;
+ 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;
+ }
+ };
+
+ /// \brief Stats about a block itself.
+ struct FrequencyData {
+ Scaled64 Scaled;
+ uint64_t Integer;
+ };
+
+ /// \brief 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());
+ }
+ };
+
+ /// \brief 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;
+ }
+
+ /// \brief 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;
+ }
+
+ /// \brief 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;
+ }
+
+ /// \brief Has ContainingLoop been packaged up?
+ bool isPackaged() const { return getResolvedNode() != Node; }
+
+ /// \brief Has Loop been packaged up?
+ bool isAPackage() const { return isLoopHeader() && Loop->IsPackaged; }
+
+ /// \brief Has Loop been packaged up twice?
+ bool isADoublePackage() const {
+ return isDoubleLoopHeader() && Loop->Parent->IsPackaged;
+ }
+ };
+
+ /// \brief 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) {}
+ };
+
+ /// \brief 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);
+ }
+
+ /// \brief 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);
+ };
+
+ /// \brief Data about each block. This is used downstream.
+ std::vector<FrequencyData> Freqs;
+
+ /// \brief Whether each block is an irreducible loop header.
+ /// This is used downstream.
+ SparseBitVector<> IsIrrLoopHeader;
+
+ /// \brief Loop data: see initializeLoops().
+ std::vector<WorkingData> Working;
+
+ /// \brief Indexed information about loops.
+ std::list<LoopData> Loops;
+
+ /// \brief Virtual destructor.
+ ///
+ /// Need a virtual destructor to mask the compiler warning about
+ /// getBlockName().
+ virtual ~BlockFrequencyInfoImplBase() = default;
+
+ /// \brief 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);
+
+ /// \brief 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;
+ }
+
+ /// \brief 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);
+
+ /// \brief 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);
+
+ /// \brief 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);
+
+ /// \brief 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);
+
+ /// \brief Package up a loop.
+ void packageLoop(LoopData &Loop);
+
+ /// \brief Unwrap loops.
+ void unwrapLoops();
+
+ /// \brief Finalize frequency metrics.
+ ///
+ /// Calculates final frequencies and cleans up no-longer-needed data
+ /// structures.
+ void finalizeMetrics();
+
+ /// \brief 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) const;
+ Optional<uint64_t> getProfileCountFromFreq(const Function &F,
+ uint64_t Freq) 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;
+};
+
+/// \brief 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();
+}
+/// \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 {
+ 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;
+
+ /// \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) {
+ 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
+
+/// \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().
+///
+/// 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];
+ }
+
+ /// \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 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:
+ 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) const {
+ return BlockFrequencyInfoImplBase::getBlockProfileCount(F, getNode(BB));
+ }
+
+ Optional<uint64_t> getProfileCountFromFreq(const Function &F,
+ uint64_t Freq) const {
+ return BlockFrequencyInfoImplBase::getProfileCountFromFreq(F, Freq);
+ }
+
+ 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; }
+
+ /// \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>::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.
+ 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");
+
+ 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()) {
+ 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) {
+ DEBUG(dbgs() << "Missing irr loop header metadata on "
+ << getBlockName(HeaderNode) << "\n");
+ HeadersWithoutWeight.insert(H);
+ continue;
+ }
+ 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();
+ 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.
+ 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) {
+ 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) {
+ 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