| //===- CallGraphSort.cpp --------------------------------------------------===// | |
| // | |
| // 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 | |
| // | |
| //===----------------------------------------------------------------------===// | |
| /// | |
| /// This is based on the ELF port, see ELF/CallGraphSort.cpp for the details | |
| /// about the algorithm. | |
| /// | |
| //===----------------------------------------------------------------------===// | |
| #include "CallGraphSort.h" | |
| #include "COFFLinkerContext.h" | |
| #include "InputFiles.h" | |
| #include "SymbolTable.h" | |
| #include "Symbols.h" | |
| #include <numeric> | |
| using namespace llvm; | |
| using namespace lld; | |
| using namespace lld::coff; | |
| namespace { | |
| struct Edge { | |
| int from; | |
| uint64_t weight; | |
| }; | |
| struct Cluster { | |
| Cluster(int sec, size_t s) : next(sec), prev(sec), size(s) {} | |
| double getDensity() const { | |
| if (size == 0) | |
| return 0; | |
| return double(weight) / double(size); | |
| } | |
| int next; | |
| int prev; | |
| uint64_t size; | |
| uint64_t weight = 0; | |
| uint64_t initialWeight = 0; | |
| Edge bestPred = {-1, 0}; | |
| }; | |
| class CallGraphSort { | |
| public: | |
| CallGraphSort(COFFLinkerContext &ctx); | |
| DenseMap<const SectionChunk *, int> run(); | |
| private: | |
| std::vector<Cluster> clusters; | |
| std::vector<const SectionChunk *> sections; | |
| COFFLinkerContext &ctx; | |
| }; | |
| // Maximum amount the combined cluster density can be worse than the original | |
| // cluster to consider merging. | |
| constexpr int MAX_DENSITY_DEGRADATION = 8; | |
| // Maximum cluster size in bytes. | |
| constexpr uint64_t MAX_CLUSTER_SIZE = 1024 * 1024; | |
| } // end anonymous namespace | |
| using SectionPair = std::pair<const SectionChunk *, const SectionChunk *>; | |
| // Take the edge list in Config->CallGraphProfile, resolve symbol names to | |
| // Symbols, and generate a graph between InputSections with the provided | |
| // weights. | |
| CallGraphSort::CallGraphSort(COFFLinkerContext &ctx) : ctx(ctx) { | |
| const MapVector<SectionPair, uint64_t> &profile = ctx.config.callGraphProfile; | |
| DenseMap<const SectionChunk *, int> secToCluster; | |
| auto getOrCreateNode = [&](const SectionChunk *isec) -> int { | |
| auto res = secToCluster.try_emplace(isec, clusters.size()); | |
| if (res.second) { | |
| sections.push_back(isec); | |
| clusters.emplace_back(clusters.size(), isec->getSize()); | |
| } | |
| return res.first->second; | |
| }; | |
| // Create the graph. | |
| for (const std::pair<SectionPair, uint64_t> &c : profile) { | |
| const auto *fromSec = cast<SectionChunk>(c.first.first->repl); | |
| const auto *toSec = cast<SectionChunk>(c.first.second->repl); | |
| uint64_t weight = c.second; | |
| // Ignore edges between input sections belonging to different output | |
| // sections. This is done because otherwise we would end up with clusters | |
| // containing input sections that can't actually be placed adjacently in the | |
| // output. This messes with the cluster size and density calculations. We | |
| // would also end up moving input sections in other output sections without | |
| // moving them closer to what calls them. | |
| if (ctx.getOutputSection(fromSec) != ctx.getOutputSection(toSec)) | |
| continue; | |
| int from = getOrCreateNode(fromSec); | |
| int to = getOrCreateNode(toSec); | |
| clusters[to].weight += weight; | |
| if (from == to) | |
| continue; | |
| // Remember the best edge. | |
| Cluster &toC = clusters[to]; | |
| if (toC.bestPred.from == -1 || toC.bestPred.weight < weight) { | |
| toC.bestPred.from = from; | |
| toC.bestPred.weight = weight; | |
| } | |
| } | |
| for (Cluster &c : clusters) | |
| c.initialWeight = c.weight; | |
| } | |
| // It's bad to merge clusters which would degrade the density too much. | |
| static bool isNewDensityBad(Cluster &a, Cluster &b) { | |
| double newDensity = double(a.weight + b.weight) / double(a.size + b.size); | |
| return newDensity < a.getDensity() / MAX_DENSITY_DEGRADATION; | |
| } | |
| // Find the leader of V's belonged cluster (represented as an equivalence | |
| // class). We apply union-find path-halving technique (simple to implement) in | |
| // the meantime as it decreases depths and the time complexity. | |
| static int getLeader(std::vector<int> &leaders, int v) { | |
| while (leaders[v] != v) { | |
| leaders[v] = leaders[leaders[v]]; | |
| v = leaders[v]; | |
| } | |
| return v; | |
| } | |
| static void mergeClusters(std::vector<Cluster> &cs, Cluster &into, int intoIdx, | |
| Cluster &from, int fromIdx) { | |
| int tail1 = into.prev, tail2 = from.prev; | |
| into.prev = tail2; | |
| cs[tail2].next = intoIdx; | |
| from.prev = tail1; | |
| cs[tail1].next = fromIdx; | |
| into.size += from.size; | |
| into.weight += from.weight; | |
| from.size = 0; | |
| from.weight = 0; | |
| } | |
| // Group InputSections into clusters using the Call-Chain Clustering heuristic | |
| // then sort the clusters by density. | |
| DenseMap<const SectionChunk *, int> CallGraphSort::run() { | |
| std::vector<int> sorted(clusters.size()); | |
| std::vector<int> leaders(clusters.size()); | |
| std::iota(leaders.begin(), leaders.end(), 0); | |
| std::iota(sorted.begin(), sorted.end(), 0); | |
| llvm::stable_sort(sorted, [&](int a, int b) { | |
| return clusters[a].getDensity() > clusters[b].getDensity(); | |
| }); | |
| for (int l : sorted) { | |
| // The cluster index is the same as the index of its leader here because | |
| // clusters[L] has not been merged into another cluster yet. | |
| Cluster &c = clusters[l]; | |
| // Don't consider merging if the edge is unlikely. | |
| if (c.bestPred.from == -1 || c.bestPred.weight * 10 <= c.initialWeight) | |
| continue; | |
| int predL = getLeader(leaders, c.bestPred.from); | |
| if (l == predL) | |
| continue; | |
| Cluster *predC = &clusters[predL]; | |
| if (c.size + predC->size > MAX_CLUSTER_SIZE) | |
| continue; | |
| if (isNewDensityBad(*predC, c)) | |
| continue; | |
| leaders[l] = predL; | |
| mergeClusters(clusters, *predC, predL, c, l); | |
| } | |
| // Sort remaining non-empty clusters by density. | |
| sorted.clear(); | |
| for (int i = 0, e = (int)clusters.size(); i != e; ++i) | |
| if (clusters[i].size > 0) | |
| sorted.push_back(i); | |
| llvm::stable_sort(sorted, [&](int a, int b) { | |
| return clusters[a].getDensity() > clusters[b].getDensity(); | |
| }); | |
| DenseMap<const SectionChunk *, int> orderMap; | |
| // Sections will be sorted by increasing order. Absent sections will have | |
| // priority 0 and be placed at the end of sections. | |
| int curOrder = INT_MIN; | |
| for (int leader : sorted) { | |
| for (int i = leader;;) { | |
| orderMap[sections[i]] = curOrder++; | |
| i = clusters[i].next; | |
| if (i == leader) | |
| break; | |
| } | |
| } | |
| if (!ctx.config.printSymbolOrder.empty()) { | |
| std::error_code ec; | |
| raw_fd_ostream os(ctx.config.printSymbolOrder, ec, sys::fs::OF_None); | |
| if (ec) { | |
| Err(ctx) << "cannot open " << ctx.config.printSymbolOrder << ": " | |
| << ec.message(); | |
| return orderMap; | |
| } | |
| // Print the symbols ordered by C3, in the order of increasing curOrder | |
| // Instead of sorting all the orderMap, just repeat the loops above. | |
| for (int leader : sorted) | |
| for (int i = leader;;) { | |
| const SectionChunk *sc = sections[i]; | |
| // Search all the symbols in the file of the section | |
| // and find out a DefinedCOFF symbol with name that is within the | |
| // section. | |
| for (Symbol *sym : sc->file->getSymbols()) | |
| if (auto *d = dyn_cast_or_null<DefinedCOFF>(sym)) | |
| // Filter out non-COMDAT symbols and section symbols. | |
| if (d->isCOMDAT && !d->getCOFFSymbol().isSection() && | |
| sc == d->getChunk()) | |
| os << sym->getName() << "\n"; | |
| i = clusters[i].next; | |
| if (i == leader) | |
| break; | |
| } | |
| } | |
| return orderMap; | |
| } | |
| // Sort sections by the profile data provided by /call-graph-ordering-file | |
| // | |
| // This first builds a call graph based on the profile data then merges sections | |
| // according to the C³ heuristic. All clusters are then sorted by a density | |
| // metric to further improve locality. | |
| DenseMap<const SectionChunk *, int> | |
| coff::computeCallGraphProfileOrder(COFFLinkerContext &ctx) { | |
| return CallGraphSort(ctx).run(); | |
| } |