//===- 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 "lld/Common/ErrorHandler.h" #include 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(const COFFLinkerContext &ctx); DenseMap run(); private: std::vector clusters; std::vector sections; const 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; // Take the edge list in Config->CallGraphProfile, resolve symbol names to // Symbols, and generate a graph between InputSections with the provided // weights. CallGraphSort::CallGraphSort(const COFFLinkerContext &ctx) : ctx(ctx) { const MapVector &profile = ctx.config.callGraphProfile; DenseMap 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 &c : profile) { const auto *fromSec = cast(c.first.first->repl); const auto *toSec = cast(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 &leaders, int v) { while (leaders[v] != v) { leaders[v] = leaders[leaders[v]]; v = leaders[v]; } return v; } static void mergeClusters(std::vector &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 CallGraphSort::run() { std::vector sorted(clusters.size()); std::vector 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 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) { error("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(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 coff::computeCallGraphProfileOrder(const COFFLinkerContext &ctx) { return CallGraphSort(ctx).run(); }