//===- SectionPriorities.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 "SectionPriorities.h" #include "Config.h" #include "InputFiles.h" #include "Symbols.h" #include "Target.h" #include "lld/Common/Args.h" #include "lld/Common/CommonLinkerContext.h" #include "lld/Common/ErrorHandler.h" #include "llvm/ADT/DenseMap.h" #include "llvm/ADT/MapVector.h" #include "llvm/Support/Path.h" #include "llvm/Support/TimeProfiler.h" #include "llvm/Support/raw_ostream.h" #include using namespace llvm; using namespace llvm::MachO; using namespace llvm::sys; using namespace lld; using namespace lld::macho; PriorityBuilder macho::priorityBuilder; namespace { size_t highestAvailablePriority = std::numeric_limits::max(); 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 MapVector &profile); DenseMap run(); private: std::vector clusters; std::vector sections; }; // Maximum amount the combined cluster density can be worse than the original // cluster to consider merging. constexpr int MAX_DENSITY_DEGRADATION = 8; } // end anonymous namespace // Take the edge list in callGraphProfile, resolve symbol names to Symbols, and // generate a graph between InputSections with the provided weights. CallGraphSort::CallGraphSort(const MapVector &profile) { DenseMap secToCluster; auto getOrCreateCluster = [&](const InputSection *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 = c.first.first->canonical(); const auto toSec = c.first.second->canonical(); 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 (fromSec->parent != toSec->parent) continue; int from = getOrCreateCluster(fromSec); int to = getOrCreateCluster(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() { const uint64_t maxClusterSize = target->getPageSize(); // Cluster indices sorted by density. std::vector sorted(clusters.size()); // For union-find. 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); // Already in the same cluster. if (l == predL) continue; Cluster *predC = &clusters[predL]; if (c.size + predC->size > maxClusterSize) 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 decreasing order. Absent sections will have // priority 0 and be placed at the end of sections. // NB: This is opposite from COFF/ELF to be compatible with the existing // order-file code. int curOrder = highestAvailablePriority; for (int leader : sorted) { for (int i = leader;;) { orderMap[sections[i]] = curOrder--; i = clusters[i].next; if (i == leader) break; } } if (!config->printSymbolOrder.empty()) { std::error_code ec; raw_fd_ostream os(config->printSymbolOrder, ec, sys::fs::OF_None); if (ec) { error("cannot open " + config->printSymbolOrder + ": " + ec.message()); return orderMap; } // Print the symbols ordered by C3, in the order of decreasing curOrder // Instead of sorting all the orderMap, just repeat the loops above. for (int leader : sorted) for (int i = leader;;) { const InputSection *isec = sections[i]; // Search all the symbols in the file of the section // and find out a Defined symbol with name that is within the // section. for (Symbol *sym : isec->getFile()->symbols) { if (auto *d = dyn_cast_or_null(sym)) { if (d->isec() == isec) os << sym->getName() << "\n"; } } i = clusters[i].next; if (i == leader) break; } } return orderMap; } std::optional macho::PriorityBuilder::getSymbolPriority(const Defined *sym) { if (sym->isAbsolute()) return std::nullopt; auto it = priorities.find(sym->getName()); if (it == priorities.end()) return std::nullopt; const SymbolPriorityEntry &entry = it->second; const InputFile *f = sym->isec()->getFile(); if (!f) return entry.anyObjectFile; // We don't use toString(InputFile *) here because it returns the full path // for object files, and we only want the basename. StringRef filename; if (f->archiveName.empty()) filename = path::filename(f->getName()); else filename = saver().save(path::filename(f->archiveName) + "(" + path::filename(f->getName()) + ")"); return std::max(entry.objectFiles.lookup(filename), entry.anyObjectFile); } void macho::PriorityBuilder::extractCallGraphProfile() { TimeTraceScope timeScope("Extract call graph profile"); bool hasOrderFile = !priorities.empty(); for (const InputFile *file : inputFiles) { auto *obj = dyn_cast_or_null(file); if (!obj) continue; for (const CallGraphEntry &entry : obj->callGraph) { assert(entry.fromIndex < obj->symbols.size() && entry.toIndex < obj->symbols.size()); auto *fromSym = dyn_cast_or_null(obj->symbols[entry.fromIndex]); auto *toSym = dyn_cast_or_null(obj->symbols[entry.toIndex]); if (fromSym && toSym && (!hasOrderFile || (!getSymbolPriority(fromSym) && !getSymbolPriority(toSym)))) callGraphProfile[{fromSym->isec(), toSym->isec()}] += entry.count; } } } void macho::PriorityBuilder::parseOrderFile(StringRef path) { assert(callGraphProfile.empty() && "Order file must be parsed before call graph profile is processed"); std::optional buffer = readFile(path); if (!buffer) { error("Could not read order file at " + path); return; } MemoryBufferRef mbref = *buffer; for (StringRef line : args::getLines(mbref)) { StringRef objectFile, symbol; line = line.take_until([](char c) { return c == '#'; }); // ignore comments line = line.ltrim(); CPUType cpuType = StringSwitch(line) .StartsWith("i386:", CPU_TYPE_I386) .StartsWith("x86_64:", CPU_TYPE_X86_64) .StartsWith("arm:", CPU_TYPE_ARM) .StartsWith("arm64:", CPU_TYPE_ARM64) .StartsWith("ppc:", CPU_TYPE_POWERPC) .StartsWith("ppc64:", CPU_TYPE_POWERPC64) .Default(CPU_TYPE_ANY); if (cpuType != CPU_TYPE_ANY && cpuType != target->cpuType) continue; // Drop the CPU type as well as the colon if (cpuType != CPU_TYPE_ANY) line = line.drop_until([](char c) { return c == ':'; }).drop_front(); constexpr std::array fileEnds = {".o:", ".o):"}; for (StringRef fileEnd : fileEnds) { size_t pos = line.find(fileEnd); if (pos != StringRef::npos) { // Split the string around the colon objectFile = line.take_front(pos + fileEnd.size() - 1); line = line.drop_front(pos + fileEnd.size()); break; } } symbol = line.trim(); if (!symbol.empty()) { SymbolPriorityEntry &entry = priorities[symbol]; if (!objectFile.empty()) entry.objectFiles.insert( std::make_pair(objectFile, highestAvailablePriority)); else entry.anyObjectFile = std::max(entry.anyObjectFile, highestAvailablePriority); } --highestAvailablePriority; } } DenseMap macho::PriorityBuilder::buildInputSectionPriorities() { DenseMap sectionPriorities; if (config->callGraphProfileSort) { // Sort sections by the profile data provided by __LLVM,__cg_profile // sections. // // 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. TimeTraceScope timeScope("Call graph profile sort"); sectionPriorities = CallGraphSort(callGraphProfile).run(); } if (priorities.empty()) return sectionPriorities; auto addSym = [&](const Defined *sym) { std::optional symbolPriority = getSymbolPriority(sym); if (!symbolPriority) return; size_t &priority = sectionPriorities[sym->isec()]; priority = std::max(priority, *symbolPriority); }; // TODO: Make sure this handles weak symbols correctly. for (const InputFile *file : inputFiles) { if (isa(file)) for (Symbol *sym : file->symbols) if (auto *d = dyn_cast_or_null(sym)) addSym(d); } return sectionPriorities; }