| //===- CodeLayout.cpp - Implementation of code layout algorithms ----------===// |
| // |
| // 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 |
| // |
| //===----------------------------------------------------------------------===// |
| // |
| // ExtTSP - layout of basic blocks with i-cache optimization. |
| // |
| // The algorithm tries to find a layout of nodes (basic blocks) of a given CFG |
| // optimizing jump locality and thus processor I-cache utilization. This is |
| // achieved via increasing the number of fall-through jumps and co-locating |
| // frequently executed nodes together. The name follows the underlying |
| // optimization problem, Extended-TSP, which is a generalization of classical |
| // (maximum) Traveling Salesmen Problem. |
| // |
| // The algorithm is a greedy heuristic that works with chains (ordered lists) |
| // of basic blocks. Initially all chains are isolated basic blocks. On every |
| // iteration, we pick a pair of chains whose merging yields the biggest increase |
| // in the ExtTSP score, which models how i-cache "friendly" a specific chain is. |
| // A pair of chains giving the maximum gain is merged into a new chain. The |
| // procedure stops when there is only one chain left, or when merging does not |
| // increase ExtTSP. In the latter case, the remaining chains are sorted by |
| // density in the decreasing order. |
| // |
| // An important aspect is the way two chains are merged. Unlike earlier |
| // algorithms (e.g., based on the approach of Pettis-Hansen), two |
| // chains, X and Y, are first split into three, X1, X2, and Y. Then we |
| // consider all possible ways of gluing the three chains (e.g., X1YX2, X1X2Y, |
| // X2X1Y, X2YX1, YX1X2, YX2X1) and choose the one producing the largest score. |
| // This improves the quality of the final result (the search space is larger) |
| // while keeping the implementation sufficiently fast. |
| // |
| // Reference: |
| // * A. Newell and S. Pupyrev, Improved Basic Block Reordering, |
| // IEEE Transactions on Computers, 2020 |
| // https://arxiv.org/abs/1809.04676 |
| // |
| //===----------------------------------------------------------------------===// |
| |
| #include "llvm/Transforms/Utils/CodeLayout.h" |
| #include "llvm/Support/CommandLine.h" |
| |
| #include <cmath> |
| |
| using namespace llvm; |
| #define DEBUG_TYPE "code-layout" |
| |
| cl::opt<bool> EnableExtTspBlockPlacement( |
| "enable-ext-tsp-block-placement", cl::Hidden, cl::init(false), |
| cl::desc("Enable machine block placement based on the ext-tsp model, " |
| "optimizing I-cache utilization.")); |
| |
| cl::opt<bool> ApplyExtTspWithoutProfile( |
| "ext-tsp-apply-without-profile", |
| cl::desc("Whether to apply ext-tsp placement for instances w/o profile"), |
| cl::init(true), cl::Hidden); |
| |
| // Algorithm-specific params. The values are tuned for the best performance |
| // of large-scale front-end bound binaries. |
| static cl::opt<double> ForwardWeightCond( |
| "ext-tsp-forward-weight-cond", cl::ReallyHidden, cl::init(0.1), |
| cl::desc("The weight of conditional forward jumps for ExtTSP value")); |
| |
| static cl::opt<double> ForwardWeightUncond( |
| "ext-tsp-forward-weight-uncond", cl::ReallyHidden, cl::init(0.1), |
| cl::desc("The weight of unconditional forward jumps for ExtTSP value")); |
| |
| static cl::opt<double> BackwardWeightCond( |
| "ext-tsp-backward-weight-cond", cl::ReallyHidden, cl::init(0.1), |
| cl::desc("The weight of conditonal backward jumps for ExtTSP value")); |
| |
| static cl::opt<double> BackwardWeightUncond( |
| "ext-tsp-backward-weight-uncond", cl::ReallyHidden, cl::init(0.1), |
| cl::desc("The weight of unconditonal backward jumps for ExtTSP value")); |
| |
| static cl::opt<double> FallthroughWeightCond( |
| "ext-tsp-fallthrough-weight-cond", cl::ReallyHidden, cl::init(1.0), |
| cl::desc("The weight of conditional fallthrough jumps for ExtTSP value")); |
| |
| static cl::opt<double> FallthroughWeightUncond( |
| "ext-tsp-fallthrough-weight-uncond", cl::ReallyHidden, cl::init(1.05), |
| cl::desc("The weight of unconditional fallthrough jumps for ExtTSP value")); |
| |
| static cl::opt<unsigned> ForwardDistance( |
| "ext-tsp-forward-distance", cl::ReallyHidden, cl::init(1024), |
| cl::desc("The maximum distance (in bytes) of a forward jump for ExtTSP")); |
| |
| static cl::opt<unsigned> BackwardDistance( |
| "ext-tsp-backward-distance", cl::ReallyHidden, cl::init(640), |
| cl::desc("The maximum distance (in bytes) of a backward jump for ExtTSP")); |
| |
| // The maximum size of a chain created by the algorithm. The size is bounded |
| // so that the algorithm can efficiently process extremely large instance. |
| static cl::opt<unsigned> |
| MaxChainSize("ext-tsp-max-chain-size", cl::ReallyHidden, cl::init(4096), |
| cl::desc("The maximum size of a chain to create.")); |
| |
| // The maximum size of a chain for splitting. Larger values of the threshold |
| // may yield better quality at the cost of worsen run-time. |
| static cl::opt<unsigned> ChainSplitThreshold( |
| "ext-tsp-chain-split-threshold", cl::ReallyHidden, cl::init(128), |
| cl::desc("The maximum size of a chain to apply splitting")); |
| |
| // The option enables splitting (large) chains along in-coming and out-going |
| // jumps. This typically results in a better quality. |
| static cl::opt<bool> EnableChainSplitAlongJumps( |
| "ext-tsp-enable-chain-split-along-jumps", cl::ReallyHidden, cl::init(true), |
| cl::desc("The maximum size of a chain to apply splitting")); |
| |
| namespace { |
| |
| // Epsilon for comparison of doubles. |
| constexpr double EPS = 1e-8; |
| |
| // Compute the Ext-TSP score for a given jump. |
| double jumpExtTSPScore(uint64_t JumpDist, uint64_t JumpMaxDist, uint64_t Count, |
| double Weight) { |
| if (JumpDist > JumpMaxDist) |
| return 0; |
| double Prob = 1.0 - static_cast<double>(JumpDist) / JumpMaxDist; |
| return Weight * Prob * Count; |
| } |
| |
| // Compute the Ext-TSP score for a jump between a given pair of blocks, |
| // using their sizes, (estimated) addresses and the jump execution count. |
| double extTSPScore(uint64_t SrcAddr, uint64_t SrcSize, uint64_t DstAddr, |
| uint64_t Count, bool IsConditional) { |
| // Fallthrough |
| if (SrcAddr + SrcSize == DstAddr) { |
| return jumpExtTSPScore(0, 1, Count, |
| IsConditional ? FallthroughWeightCond |
| : FallthroughWeightUncond); |
| } |
| // Forward |
| if (SrcAddr + SrcSize < DstAddr) { |
| const uint64_t Dist = DstAddr - (SrcAddr + SrcSize); |
| return jumpExtTSPScore(Dist, ForwardDistance, Count, |
| IsConditional ? ForwardWeightCond |
| : ForwardWeightUncond); |
| } |
| // Backward |
| const uint64_t Dist = SrcAddr + SrcSize - DstAddr; |
| return jumpExtTSPScore(Dist, BackwardDistance, Count, |
| IsConditional ? BackwardWeightCond |
| : BackwardWeightUncond); |
| } |
| |
| /// A type of merging two chains, X and Y. The former chain is split into |
| /// X1 and X2 and then concatenated with Y in the order specified by the type. |
| enum class MergeTypeTy : int { X_Y, X1_Y_X2, Y_X2_X1, X2_X1_Y }; |
| |
| /// The gain of merging two chains, that is, the Ext-TSP score of the merge |
| /// together with the corresponfiding merge 'type' and 'offset'. |
| class MergeGainTy { |
| public: |
| explicit MergeGainTy() = default; |
| explicit MergeGainTy(double Score, size_t MergeOffset, MergeTypeTy MergeType) |
| : Score(Score), MergeOffset(MergeOffset), MergeType(MergeType) {} |
| |
| double score() const { return Score; } |
| |
| size_t mergeOffset() const { return MergeOffset; } |
| |
| MergeTypeTy mergeType() const { return MergeType; } |
| |
| // Returns 'true' iff Other is preferred over this. |
| bool operator<(const MergeGainTy &Other) const { |
| return (Other.Score > EPS && Other.Score > Score + EPS); |
| } |
| |
| // Update the current gain if Other is preferred over this. |
| void updateIfLessThan(const MergeGainTy &Other) { |
| if (*this < Other) |
| *this = Other; |
| } |
| |
| private: |
| double Score{-1.0}; |
| size_t MergeOffset{0}; |
| MergeTypeTy MergeType{MergeTypeTy::X_Y}; |
| }; |
| |
| class Jump; |
| class Chain; |
| class ChainEdge; |
| |
| /// A node in the graph, typically corresponding to a basic block in CFG. |
| class Block { |
| public: |
| Block(const Block &) = delete; |
| Block(Block &&) = default; |
| Block &operator=(const Block &) = delete; |
| Block &operator=(Block &&) = default; |
| |
| // The original index of the block in CFG. |
| size_t Index{0}; |
| // The index of the block in the current chain. |
| size_t CurIndex{0}; |
| // Size of the block in the binary. |
| uint64_t Size{0}; |
| // Execution count of the block in the profile data. |
| uint64_t ExecutionCount{0}; |
| // Current chain of the node. |
| Chain *CurChain{nullptr}; |
| // An offset of the block in the current chain. |
| mutable uint64_t EstimatedAddr{0}; |
| // Forced successor of the block in CFG. |
| Block *ForcedSucc{nullptr}; |
| // Forced predecessor of the block in CFG. |
| Block *ForcedPred{nullptr}; |
| // Outgoing jumps from the block. |
| std::vector<Jump *> OutJumps; |
| // Incoming jumps to the block. |
| std::vector<Jump *> InJumps; |
| |
| public: |
| explicit Block(size_t Index, uint64_t Size, uint64_t EC) |
| : Index(Index), Size(Size), ExecutionCount(EC) {} |
| bool isEntry() const { return Index == 0; } |
| }; |
| |
| /// An arc in the graph, typically corresponding to a jump between two blocks. |
| class Jump { |
| public: |
| Jump(const Jump &) = delete; |
| Jump(Jump &&) = default; |
| Jump &operator=(const Jump &) = delete; |
| Jump &operator=(Jump &&) = default; |
| |
| // Source block of the jump. |
| Block *Source; |
| // Target block of the jump. |
| Block *Target; |
| // Execution count of the arc in the profile data. |
| uint64_t ExecutionCount{0}; |
| // Whether the jump corresponds to a conditional branch. |
| bool IsConditional{false}; |
| |
| public: |
| explicit Jump(Block *Source, Block *Target, uint64_t ExecutionCount) |
| : Source(Source), Target(Target), ExecutionCount(ExecutionCount) {} |
| }; |
| |
| /// A chain (ordered sequence) of blocks. |
| class Chain { |
| public: |
| Chain(const Chain &) = delete; |
| Chain(Chain &&) = default; |
| Chain &operator=(const Chain &) = delete; |
| Chain &operator=(Chain &&) = default; |
| |
| explicit Chain(uint64_t Id, Block *Block) |
| : Id(Id), Score(0), Blocks(1, Block) {} |
| |
| uint64_t id() const { return Id; } |
| |
| bool isEntry() const { return Blocks[0]->Index == 0; } |
| |
| bool isCold() const { |
| for (auto *Block : Blocks) { |
| if (Block->ExecutionCount > 0) |
| return false; |
| } |
| return true; |
| } |
| |
| double score() const { return Score; } |
| |
| void setScore(double NewScore) { Score = NewScore; } |
| |
| const std::vector<Block *> &blocks() const { return Blocks; } |
| |
| size_t numBlocks() const { return Blocks.size(); } |
| |
| const std::vector<std::pair<Chain *, ChainEdge *>> &edges() const { |
| return Edges; |
| } |
| |
| ChainEdge *getEdge(Chain *Other) const { |
| for (auto It : Edges) { |
| if (It.first == Other) |
| return It.second; |
| } |
| return nullptr; |
| } |
| |
| void removeEdge(Chain *Other) { |
| auto It = Edges.begin(); |
| while (It != Edges.end()) { |
| if (It->first == Other) { |
| Edges.erase(It); |
| return; |
| } |
| It++; |
| } |
| } |
| |
| void addEdge(Chain *Other, ChainEdge *Edge) { |
| Edges.push_back(std::make_pair(Other, Edge)); |
| } |
| |
| void merge(Chain *Other, const std::vector<Block *> &MergedBlocks) { |
| Blocks = MergedBlocks; |
| // Update the block's chains |
| for (size_t Idx = 0; Idx < Blocks.size(); Idx++) { |
| Blocks[Idx]->CurChain = this; |
| Blocks[Idx]->CurIndex = Idx; |
| } |
| } |
| |
| void mergeEdges(Chain *Other); |
| |
| void clear() { |
| Blocks.clear(); |
| Blocks.shrink_to_fit(); |
| Edges.clear(); |
| Edges.shrink_to_fit(); |
| } |
| |
| private: |
| // Unique chain identifier. |
| uint64_t Id; |
| // Cached ext-tsp score for the chain. |
| double Score; |
| // Blocks of the chain. |
| std::vector<Block *> Blocks; |
| // Adjacent chains and corresponding edges (lists of jumps). |
| std::vector<std::pair<Chain *, ChainEdge *>> Edges; |
| }; |
| |
| /// An edge in CFG representing jumps between two chains. |
| /// When blocks are merged into chains, the edges are combined too so that |
| /// there is always at most one edge between a pair of chains |
| class ChainEdge { |
| public: |
| ChainEdge(const ChainEdge &) = delete; |
| ChainEdge(ChainEdge &&) = default; |
| ChainEdge &operator=(const ChainEdge &) = delete; |
| ChainEdge &operator=(ChainEdge &&) = default; |
| |
| explicit ChainEdge(Jump *Jump) |
| : SrcChain(Jump->Source->CurChain), DstChain(Jump->Target->CurChain), |
| Jumps(1, Jump) {} |
| |
| const std::vector<Jump *> &jumps() const { return Jumps; } |
| |
| void changeEndpoint(Chain *From, Chain *To) { |
| if (From == SrcChain) |
| SrcChain = To; |
| if (From == DstChain) |
| DstChain = To; |
| } |
| |
| void appendJump(Jump *Jump) { Jumps.push_back(Jump); } |
| |
| void moveJumps(ChainEdge *Other) { |
| Jumps.insert(Jumps.end(), Other->Jumps.begin(), Other->Jumps.end()); |
| Other->Jumps.clear(); |
| Other->Jumps.shrink_to_fit(); |
| } |
| |
| bool hasCachedMergeGain(Chain *Src, Chain *Dst) const { |
| return Src == SrcChain ? CacheValidForward : CacheValidBackward; |
| } |
| |
| MergeGainTy getCachedMergeGain(Chain *Src, Chain *Dst) const { |
| return Src == SrcChain ? CachedGainForward : CachedGainBackward; |
| } |
| |
| void setCachedMergeGain(Chain *Src, Chain *Dst, MergeGainTy MergeGain) { |
| if (Src == SrcChain) { |
| CachedGainForward = MergeGain; |
| CacheValidForward = true; |
| } else { |
| CachedGainBackward = MergeGain; |
| CacheValidBackward = true; |
| } |
| } |
| |
| void invalidateCache() { |
| CacheValidForward = false; |
| CacheValidBackward = false; |
| } |
| |
| private: |
| // Source chain. |
| Chain *SrcChain{nullptr}; |
| // Destination chain. |
| Chain *DstChain{nullptr}; |
| // Original jumps in the binary with correspinding execution counts. |
| std::vector<Jump *> Jumps; |
| // Cached ext-tsp value for merging the pair of chains. |
| // Since the gain of merging (Src, Dst) and (Dst, Src) might be different, |
| // we store both values here. |
| MergeGainTy CachedGainForward; |
| MergeGainTy CachedGainBackward; |
| // Whether the cached value must be recomputed. |
| bool CacheValidForward{false}; |
| bool CacheValidBackward{false}; |
| }; |
| |
| void Chain::mergeEdges(Chain *Other) { |
| assert(this != Other && "cannot merge a chain with itself"); |
| |
| // Update edges adjacent to chain Other |
| for (auto EdgeIt : Other->Edges) { |
| Chain *DstChain = EdgeIt.first; |
| ChainEdge *DstEdge = EdgeIt.second; |
| Chain *TargetChain = DstChain == Other ? this : DstChain; |
| ChainEdge *CurEdge = getEdge(TargetChain); |
| if (CurEdge == nullptr) { |
| DstEdge->changeEndpoint(Other, this); |
| this->addEdge(TargetChain, DstEdge); |
| if (DstChain != this && DstChain != Other) { |
| DstChain->addEdge(this, DstEdge); |
| } |
| } else { |
| CurEdge->moveJumps(DstEdge); |
| } |
| // Cleanup leftover edge |
| if (DstChain != Other) { |
| DstChain->removeEdge(Other); |
| } |
| } |
| } |
| |
| using BlockIter = std::vector<Block *>::const_iterator; |
| |
| /// A wrapper around three chains of blocks; it is used to avoid extra |
| /// instantiation of the vectors. |
| class MergedChain { |
| public: |
| MergedChain(BlockIter Begin1, BlockIter End1, BlockIter Begin2 = BlockIter(), |
| BlockIter End2 = BlockIter(), BlockIter Begin3 = BlockIter(), |
| BlockIter End3 = BlockIter()) |
| : Begin1(Begin1), End1(End1), Begin2(Begin2), End2(End2), Begin3(Begin3), |
| End3(End3) {} |
| |
| template <typename F> void forEach(const F &Func) const { |
| for (auto It = Begin1; It != End1; It++) |
| Func(*It); |
| for (auto It = Begin2; It != End2; It++) |
| Func(*It); |
| for (auto It = Begin3; It != End3; It++) |
| Func(*It); |
| } |
| |
| std::vector<Block *> getBlocks() const { |
| std::vector<Block *> Result; |
| Result.reserve(std::distance(Begin1, End1) + std::distance(Begin2, End2) + |
| std::distance(Begin3, End3)); |
| Result.insert(Result.end(), Begin1, End1); |
| Result.insert(Result.end(), Begin2, End2); |
| Result.insert(Result.end(), Begin3, End3); |
| return Result; |
| } |
| |
| const Block *getFirstBlock() const { return *Begin1; } |
| |
| private: |
| BlockIter Begin1; |
| BlockIter End1; |
| BlockIter Begin2; |
| BlockIter End2; |
| BlockIter Begin3; |
| BlockIter End3; |
| }; |
| |
| /// The implementation of the ExtTSP algorithm. |
| class ExtTSPImpl { |
| using EdgeT = std::pair<uint64_t, uint64_t>; |
| using EdgeCountMap = std::vector<std::pair<EdgeT, uint64_t>>; |
| |
| public: |
| ExtTSPImpl(size_t NumNodes, const std::vector<uint64_t> &NodeSizes, |
| const std::vector<uint64_t> &NodeCounts, |
| const EdgeCountMap &EdgeCounts) |
| : NumNodes(NumNodes) { |
| initialize(NodeSizes, NodeCounts, EdgeCounts); |
| } |
| |
| /// Run the algorithm and return an optimized ordering of blocks. |
| void run(std::vector<uint64_t> &Result) { |
| // Pass 1: Merge blocks with their mutually forced successors |
| mergeForcedPairs(); |
| |
| // Pass 2: Merge pairs of chains while improving the ExtTSP objective |
| mergeChainPairs(); |
| |
| // Pass 3: Merge cold blocks to reduce code size |
| mergeColdChains(); |
| |
| // Collect blocks from all chains |
| concatChains(Result); |
| } |
| |
| private: |
| /// Initialize the algorithm's data structures. |
| void initialize(const std::vector<uint64_t> &NodeSizes, |
| const std::vector<uint64_t> &NodeCounts, |
| const EdgeCountMap &EdgeCounts) { |
| // Initialize blocks |
| AllBlocks.reserve(NumNodes); |
| for (uint64_t Node = 0; Node < NumNodes; Node++) { |
| uint64_t Size = std::max<uint64_t>(NodeSizes[Node], 1ULL); |
| uint64_t ExecutionCount = NodeCounts[Node]; |
| // The execution count of the entry block is set to at least 1 |
| if (Node == 0 && ExecutionCount == 0) |
| ExecutionCount = 1; |
| AllBlocks.emplace_back(Node, Size, ExecutionCount); |
| } |
| |
| // Initialize jumps between blocks |
| SuccNodes.resize(NumNodes); |
| PredNodes.resize(NumNodes); |
| std::vector<uint64_t> OutDegree(NumNodes, 0); |
| AllJumps.reserve(EdgeCounts.size()); |
| for (auto It : EdgeCounts) { |
| auto Pred = It.first.first; |
| auto Succ = It.first.second; |
| OutDegree[Pred]++; |
| // Ignore self-edges |
| if (Pred == Succ) |
| continue; |
| |
| SuccNodes[Pred].push_back(Succ); |
| PredNodes[Succ].push_back(Pred); |
| auto ExecutionCount = It.second; |
| if (ExecutionCount > 0) { |
| auto &Block = AllBlocks[Pred]; |
| auto &SuccBlock = AllBlocks[Succ]; |
| AllJumps.emplace_back(&Block, &SuccBlock, ExecutionCount); |
| SuccBlock.InJumps.push_back(&AllJumps.back()); |
| Block.OutJumps.push_back(&AllJumps.back()); |
| } |
| } |
| for (auto &Jump : AllJumps) { |
| assert(OutDegree[Jump.Source->Index] > 0); |
| Jump.IsConditional = OutDegree[Jump.Source->Index] > 1; |
| } |
| |
| // Initialize chains |
| AllChains.reserve(NumNodes); |
| HotChains.reserve(NumNodes); |
| for (Block &Block : AllBlocks) { |
| AllChains.emplace_back(Block.Index, &Block); |
| Block.CurChain = &AllChains.back(); |
| if (Block.ExecutionCount > 0) { |
| HotChains.push_back(&AllChains.back()); |
| } |
| } |
| |
| // Initialize chain edges |
| AllEdges.reserve(AllJumps.size()); |
| for (Block &Block : AllBlocks) { |
| for (auto &Jump : Block.OutJumps) { |
| auto SuccBlock = Jump->Target; |
| ChainEdge *CurEdge = Block.CurChain->getEdge(SuccBlock->CurChain); |
| // this edge is already present in the graph |
| if (CurEdge != nullptr) { |
| assert(SuccBlock->CurChain->getEdge(Block.CurChain) != nullptr); |
| CurEdge->appendJump(Jump); |
| continue; |
| } |
| // this is a new edge |
| AllEdges.emplace_back(Jump); |
| Block.CurChain->addEdge(SuccBlock->CurChain, &AllEdges.back()); |
| SuccBlock->CurChain->addEdge(Block.CurChain, &AllEdges.back()); |
| } |
| } |
| } |
| |
| /// For a pair of blocks, A and B, block B is the forced successor of A, |
| /// if (i) all jumps (based on profile) from A goes to B and (ii) all jumps |
| /// to B are from A. Such blocks should be adjacent in the optimal ordering; |
| /// the method finds and merges such pairs of blocks. |
| void mergeForcedPairs() { |
| // Find fallthroughs based on edge weights |
| for (auto &Block : AllBlocks) { |
| if (SuccNodes[Block.Index].size() == 1 && |
| PredNodes[SuccNodes[Block.Index][0]].size() == 1 && |
| SuccNodes[Block.Index][0] != 0) { |
| size_t SuccIndex = SuccNodes[Block.Index][0]; |
| Block.ForcedSucc = &AllBlocks[SuccIndex]; |
| AllBlocks[SuccIndex].ForcedPred = &Block; |
| } |
| } |
| |
| // There might be 'cycles' in the forced dependencies, since profile |
| // data isn't 100% accurate. Typically this is observed in loops, when the |
| // loop edges are the hottest successors for the basic blocks of the loop. |
| // Break the cycles by choosing the block with the smallest index as the |
| // head. This helps to keep the original order of the loops, which likely |
| // have already been rotated in the optimized manner. |
| for (auto &Block : AllBlocks) { |
| if (Block.ForcedSucc == nullptr || Block.ForcedPred == nullptr) |
| continue; |
| |
| auto SuccBlock = Block.ForcedSucc; |
| while (SuccBlock != nullptr && SuccBlock != &Block) { |
| SuccBlock = SuccBlock->ForcedSucc; |
| } |
| if (SuccBlock == nullptr) |
| continue; |
| // Break the cycle |
| AllBlocks[Block.ForcedPred->Index].ForcedSucc = nullptr; |
| Block.ForcedPred = nullptr; |
| } |
| |
| // Merge blocks with their fallthrough successors |
| for (auto &Block : AllBlocks) { |
| if (Block.ForcedPred == nullptr && Block.ForcedSucc != nullptr) { |
| auto CurBlock = &Block; |
| while (CurBlock->ForcedSucc != nullptr) { |
| const auto NextBlock = CurBlock->ForcedSucc; |
| mergeChains(Block.CurChain, NextBlock->CurChain, 0, MergeTypeTy::X_Y); |
| CurBlock = NextBlock; |
| } |
| } |
| } |
| } |
| |
| /// Merge pairs of chains while improving the ExtTSP objective. |
| void mergeChainPairs() { |
| /// Deterministically compare pairs of chains |
| auto compareChainPairs = [](const Chain *A1, const Chain *B1, |
| const Chain *A2, const Chain *B2) { |
| if (A1 != A2) |
| return A1->id() < A2->id(); |
| return B1->id() < B2->id(); |
| }; |
| |
| while (HotChains.size() > 1) { |
| Chain *BestChainPred = nullptr; |
| Chain *BestChainSucc = nullptr; |
| auto BestGain = MergeGainTy(); |
| // Iterate over all pairs of chains |
| for (Chain *ChainPred : HotChains) { |
| // Get candidates for merging with the current chain |
| for (auto EdgeIter : ChainPred->edges()) { |
| Chain *ChainSucc = EdgeIter.first; |
| class ChainEdge *ChainEdge = EdgeIter.second; |
| // Ignore loop edges |
| if (ChainPred == ChainSucc) |
| continue; |
| |
| // Stop early if the combined chain violates the maximum allowed size |
| if (ChainPred->numBlocks() + ChainSucc->numBlocks() >= MaxChainSize) |
| continue; |
| |
| // Compute the gain of merging the two chains |
| MergeGainTy CurGain = |
| getBestMergeGain(ChainPred, ChainSucc, ChainEdge); |
| if (CurGain.score() <= EPS) |
| continue; |
| |
| if (BestGain < CurGain || |
| (std::abs(CurGain.score() - BestGain.score()) < EPS && |
| compareChainPairs(ChainPred, ChainSucc, BestChainPred, |
| BestChainSucc))) { |
| BestGain = CurGain; |
| BestChainPred = ChainPred; |
| BestChainSucc = ChainSucc; |
| } |
| } |
| } |
| |
| // Stop merging when there is no improvement |
| if (BestGain.score() <= EPS) |
| break; |
| |
| // Merge the best pair of chains |
| mergeChains(BestChainPred, BestChainSucc, BestGain.mergeOffset(), |
| BestGain.mergeType()); |
| } |
| } |
| |
| /// Merge remaining blocks into chains w/o taking jump counts into |
| /// consideration. This allows to maintain the original block order in the |
| /// absense of profile data |
| void mergeColdChains() { |
| for (size_t SrcBB = 0; SrcBB < NumNodes; SrcBB++) { |
| // Iterating in reverse order to make sure original fallthrough jumps are |
| // merged first; this might be beneficial for code size. |
| size_t NumSuccs = SuccNodes[SrcBB].size(); |
| for (size_t Idx = 0; Idx < NumSuccs; Idx++) { |
| auto DstBB = SuccNodes[SrcBB][NumSuccs - Idx - 1]; |
| auto SrcChain = AllBlocks[SrcBB].CurChain; |
| auto DstChain = AllBlocks[DstBB].CurChain; |
| if (SrcChain != DstChain && !DstChain->isEntry() && |
| SrcChain->blocks().back()->Index == SrcBB && |
| DstChain->blocks().front()->Index == DstBB && |
| SrcChain->isCold() == DstChain->isCold()) { |
| mergeChains(SrcChain, DstChain, 0, MergeTypeTy::X_Y); |
| } |
| } |
| } |
| } |
| |
| /// Compute the Ext-TSP score for a given block order and a list of jumps. |
| double extTSPScore(const MergedChain &MergedBlocks, |
| const std::vector<Jump *> &Jumps) const { |
| if (Jumps.empty()) |
| return 0.0; |
| uint64_t CurAddr = 0; |
| MergedBlocks.forEach([&](const Block *BB) { |
| BB->EstimatedAddr = CurAddr; |
| CurAddr += BB->Size; |
| }); |
| |
| double Score = 0; |
| for (auto &Jump : Jumps) { |
| const Block *SrcBlock = Jump->Source; |
| const Block *DstBlock = Jump->Target; |
| Score += ::extTSPScore(SrcBlock->EstimatedAddr, SrcBlock->Size, |
| DstBlock->EstimatedAddr, Jump->ExecutionCount, |
| Jump->IsConditional); |
| } |
| return Score; |
| } |
| |
| /// Compute the gain of merging two chains. |
| /// |
| /// The function considers all possible ways of merging two chains and |
| /// computes the one having the largest increase in ExtTSP objective. The |
| /// result is a pair with the first element being the gain and the second |
| /// element being the corresponding merging type. |
| MergeGainTy getBestMergeGain(Chain *ChainPred, Chain *ChainSucc, |
| ChainEdge *Edge) const { |
| if (Edge->hasCachedMergeGain(ChainPred, ChainSucc)) { |
| return Edge->getCachedMergeGain(ChainPred, ChainSucc); |
| } |
| |
| // Precompute jumps between ChainPred and ChainSucc |
| auto Jumps = Edge->jumps(); |
| ChainEdge *EdgePP = ChainPred->getEdge(ChainPred); |
| if (EdgePP != nullptr) { |
| Jumps.insert(Jumps.end(), EdgePP->jumps().begin(), EdgePP->jumps().end()); |
| } |
| assert(!Jumps.empty() && "trying to merge chains w/o jumps"); |
| |
| // The object holds the best currently chosen gain of merging the two chains |
| MergeGainTy Gain = MergeGainTy(); |
| |
| /// Given a merge offset and a list of merge types, try to merge two chains |
| /// and update Gain with a better alternative |
| auto tryChainMerging = [&](size_t Offset, |
| const std::vector<MergeTypeTy> &MergeTypes) { |
| // Skip merging corresponding to concatenation w/o splitting |
| if (Offset == 0 || Offset == ChainPred->blocks().size()) |
| return; |
| // Skip merging if it breaks Forced successors |
| auto BB = ChainPred->blocks()[Offset - 1]; |
| if (BB->ForcedSucc != nullptr) |
| return; |
| // Apply the merge, compute the corresponding gain, and update the best |
| // value, if the merge is beneficial |
| for (const auto &MergeType : MergeTypes) { |
| Gain.updateIfLessThan( |
| computeMergeGain(ChainPred, ChainSucc, Jumps, Offset, MergeType)); |
| } |
| }; |
| |
| // Try to concatenate two chains w/o splitting |
| Gain.updateIfLessThan( |
| computeMergeGain(ChainPred, ChainSucc, Jumps, 0, MergeTypeTy::X_Y)); |
| |
| if (EnableChainSplitAlongJumps) { |
| // Attach (a part of) ChainPred before the first block of ChainSucc |
| for (auto &Jump : ChainSucc->blocks().front()->InJumps) { |
| const auto SrcBlock = Jump->Source; |
| if (SrcBlock->CurChain != ChainPred) |
| continue; |
| size_t Offset = SrcBlock->CurIndex + 1; |
| tryChainMerging(Offset, {MergeTypeTy::X1_Y_X2, MergeTypeTy::X2_X1_Y}); |
| } |
| |
| // Attach (a part of) ChainPred after the last block of ChainSucc |
| for (auto &Jump : ChainSucc->blocks().back()->OutJumps) { |
| const auto DstBlock = Jump->Source; |
| if (DstBlock->CurChain != ChainPred) |
| continue; |
| size_t Offset = DstBlock->CurIndex; |
| tryChainMerging(Offset, {MergeTypeTy::X1_Y_X2, MergeTypeTy::Y_X2_X1}); |
| } |
| } |
| |
| // Try to break ChainPred in various ways and concatenate with ChainSucc |
| if (ChainPred->blocks().size() <= ChainSplitThreshold) { |
| for (size_t Offset = 1; Offset < ChainPred->blocks().size(); Offset++) { |
| // Try to split the chain in different ways. In practice, applying |
| // X2_Y_X1 merging is almost never provides benefits; thus, we exclude |
| // it from consideration to reduce the search space |
| tryChainMerging(Offset, {MergeTypeTy::X1_Y_X2, MergeTypeTy::Y_X2_X1, |
| MergeTypeTy::X2_X1_Y}); |
| } |
| } |
| Edge->setCachedMergeGain(ChainPred, ChainSucc, Gain); |
| return Gain; |
| } |
| |
| /// Compute the score gain of merging two chains, respecting a given |
| /// merge 'type' and 'offset'. |
| /// |
| /// The two chains are not modified in the method. |
| MergeGainTy computeMergeGain(const Chain *ChainPred, const Chain *ChainSucc, |
| const std::vector<Jump *> &Jumps, |
| size_t MergeOffset, |
| MergeTypeTy MergeType) const { |
| auto MergedBlocks = mergeBlocks(ChainPred->blocks(), ChainSucc->blocks(), |
| MergeOffset, MergeType); |
| |
| // Do not allow a merge that does not preserve the original entry block |
| if ((ChainPred->isEntry() || ChainSucc->isEntry()) && |
| !MergedBlocks.getFirstBlock()->isEntry()) |
| return MergeGainTy(); |
| |
| // The gain for the new chain |
| auto NewGainScore = extTSPScore(MergedBlocks, Jumps) - ChainPred->score(); |
| return MergeGainTy(NewGainScore, MergeOffset, MergeType); |
| } |
| |
| /// Merge two chains of blocks respecting a given merge 'type' and 'offset'. |
| /// |
| /// If MergeType == 0, then the result is a concatenation of two chains. |
| /// Otherwise, the first chain is cut into two sub-chains at the offset, |
| /// and merged using all possible ways of concatenating three chains. |
| MergedChain mergeBlocks(const std::vector<Block *> &X, |
| const std::vector<Block *> &Y, size_t MergeOffset, |
| MergeTypeTy MergeType) const { |
| // Split the first chain, X, into X1 and X2 |
| BlockIter BeginX1 = X.begin(); |
| BlockIter EndX1 = X.begin() + MergeOffset; |
| BlockIter BeginX2 = X.begin() + MergeOffset; |
| BlockIter EndX2 = X.end(); |
| BlockIter BeginY = Y.begin(); |
| BlockIter EndY = Y.end(); |
| |
| // Construct a new chain from the three existing ones |
| switch (MergeType) { |
| case MergeTypeTy::X_Y: |
| return MergedChain(BeginX1, EndX2, BeginY, EndY); |
| case MergeTypeTy::X1_Y_X2: |
| return MergedChain(BeginX1, EndX1, BeginY, EndY, BeginX2, EndX2); |
| case MergeTypeTy::Y_X2_X1: |
| return MergedChain(BeginY, EndY, BeginX2, EndX2, BeginX1, EndX1); |
| case MergeTypeTy::X2_X1_Y: |
| return MergedChain(BeginX2, EndX2, BeginX1, EndX1, BeginY, EndY); |
| } |
| llvm_unreachable("unexpected chain merge type"); |
| } |
| |
| /// Merge chain From into chain Into, update the list of active chains, |
| /// adjacency information, and the corresponding cached values. |
| void mergeChains(Chain *Into, Chain *From, size_t MergeOffset, |
| MergeTypeTy MergeType) { |
| assert(Into != From && "a chain cannot be merged with itself"); |
| |
| // Merge the blocks |
| MergedChain MergedBlocks = |
| mergeBlocks(Into->blocks(), From->blocks(), MergeOffset, MergeType); |
| Into->merge(From, MergedBlocks.getBlocks()); |
| Into->mergeEdges(From); |
| From->clear(); |
| |
| // Update cached ext-tsp score for the new chain |
| ChainEdge *SelfEdge = Into->getEdge(Into); |
| if (SelfEdge != nullptr) { |
| MergedBlocks = MergedChain(Into->blocks().begin(), Into->blocks().end()); |
| Into->setScore(extTSPScore(MergedBlocks, SelfEdge->jumps())); |
| } |
| |
| // Remove chain From from the list of active chains |
| llvm::erase_value(HotChains, From); |
| |
| // Invalidate caches |
| for (auto EdgeIter : Into->edges()) { |
| EdgeIter.second->invalidateCache(); |
| } |
| } |
| |
| /// Concatenate all chains into a final order of blocks. |
| void concatChains(std::vector<uint64_t> &Order) { |
| // Collect chains and calculate some stats for their sorting |
| std::vector<Chain *> SortedChains; |
| DenseMap<const Chain *, double> ChainDensity; |
| for (auto &Chain : AllChains) { |
| if (!Chain.blocks().empty()) { |
| SortedChains.push_back(&Chain); |
| // Using doubles to avoid overflow of ExecutionCount |
| double Size = 0; |
| double ExecutionCount = 0; |
| for (auto *Block : Chain.blocks()) { |
| Size += static_cast<double>(Block->Size); |
| ExecutionCount += static_cast<double>(Block->ExecutionCount); |
| } |
| assert(Size > 0 && "a chain of zero size"); |
| ChainDensity[&Chain] = ExecutionCount / Size; |
| } |
| } |
| |
| // Sorting chains by density in the decreasing order |
| std::stable_sort(SortedChains.begin(), SortedChains.end(), |
| [&](const Chain *C1, const Chain *C2) { |
| // Make sure the original entry block is at the |
| // beginning of the order |
| if (C1->isEntry() != C2->isEntry()) { |
| return C1->isEntry(); |
| } |
| |
| const double D1 = ChainDensity[C1]; |
| const double D2 = ChainDensity[C2]; |
| // Compare by density and break ties by chain identifiers |
| return (D1 != D2) ? (D1 > D2) : (C1->id() < C2->id()); |
| }); |
| |
| // Collect the blocks in the order specified by their chains |
| Order.reserve(NumNodes); |
| for (Chain *Chain : SortedChains) { |
| for (Block *Block : Chain->blocks()) { |
| Order.push_back(Block->Index); |
| } |
| } |
| } |
| |
| private: |
| /// The number of nodes in the graph. |
| const size_t NumNodes; |
| |
| /// Successors of each node. |
| std::vector<std::vector<uint64_t>> SuccNodes; |
| |
| /// Predecessors of each node. |
| std::vector<std::vector<uint64_t>> PredNodes; |
| |
| /// All basic blocks. |
| std::vector<Block> AllBlocks; |
| |
| /// All jumps between blocks. |
| std::vector<Jump> AllJumps; |
| |
| /// All chains of basic blocks. |
| std::vector<Chain> AllChains; |
| |
| /// All edges between chains. |
| std::vector<ChainEdge> AllEdges; |
| |
| /// Active chains. The vector gets updated at runtime when chains are merged. |
| std::vector<Chain *> HotChains; |
| }; |
| |
| } // end of anonymous namespace |
| |
| std::vector<uint64_t> llvm::applyExtTspLayout( |
| const std::vector<uint64_t> &NodeSizes, |
| const std::vector<uint64_t> &NodeCounts, |
| const std::vector<std::pair<EdgeT, uint64_t>> &EdgeCounts) { |
| size_t NumNodes = NodeSizes.size(); |
| |
| // Verify correctness of the input data. |
| assert(NodeCounts.size() == NodeSizes.size() && "Incorrect input"); |
| assert(NumNodes > 2 && "Incorrect input"); |
| |
| // Apply the reordering algorithm. |
| auto Alg = ExtTSPImpl(NumNodes, NodeSizes, NodeCounts, EdgeCounts); |
| std::vector<uint64_t> Result; |
| Alg.run(Result); |
| |
| // Verify correctness of the output. |
| assert(Result.front() == 0 && "Original entry point is not preserved"); |
| assert(Result.size() == NumNodes && "Incorrect size of reordered layout"); |
| return Result; |
| } |
| |
| double llvm::calcExtTspScore( |
| const std::vector<uint64_t> &Order, const std::vector<uint64_t> &NodeSizes, |
| const std::vector<uint64_t> &NodeCounts, |
| const std::vector<std::pair<EdgeT, uint64_t>> &EdgeCounts) { |
| // Estimate addresses of the blocks in memory |
| std::vector<uint64_t> Addr(NodeSizes.size(), 0); |
| for (size_t Idx = 1; Idx < Order.size(); Idx++) { |
| Addr[Order[Idx]] = Addr[Order[Idx - 1]] + NodeSizes[Order[Idx - 1]]; |
| } |
| std::vector<uint64_t> OutDegree(NodeSizes.size(), 0); |
| for (auto It : EdgeCounts) { |
| auto Pred = It.first.first; |
| OutDegree[Pred]++; |
| } |
| |
| // Increase the score for each jump |
| double Score = 0; |
| for (auto It : EdgeCounts) { |
| auto Pred = It.first.first; |
| auto Succ = It.first.second; |
| uint64_t Count = It.second; |
| bool IsConditional = OutDegree[Pred] > 1; |
| Score += ::extTSPScore(Addr[Pred], NodeSizes[Pred], Addr[Succ], Count, |
| IsConditional); |
| } |
| return Score; |
| } |
| |
| double llvm::calcExtTspScore( |
| const std::vector<uint64_t> &NodeSizes, |
| const std::vector<uint64_t> &NodeCounts, |
| const std::vector<std::pair<EdgeT, uint64_t>> &EdgeCounts) { |
| std::vector<uint64_t> Order(NodeSizes.size()); |
| for (size_t Idx = 0; Idx < NodeSizes.size(); Idx++) { |
| Order[Idx] = Idx; |
| } |
| return calcExtTspScore(Order, NodeSizes, NodeCounts, EdgeCounts); |
| } |