// -*- mode: C++; c-file-style: "cc-mode" -*- //************************************************************************* // DESCRIPTION: Verilator: Multi-threaded code partitioning and ordering // // Code available from: https://verilator.org // //************************************************************************* // // Copyright 2003-2025 by Wilson Snyder. This program is free software; you // can redistribute it and/or modify it under the terms of either the GNU // Lesser General Public License Version 3 or the Perl Artistic License // Version 2.0. // SPDX-License-Identifier: LGPL-3.0-only OR Artistic-2.0 // //************************************************************************* // // Parallel code ordering // //************************************************************************* #include "V3PchAstNoMT.h" // VL_MT_DISABLED_CODE_UNIT #include "V3Config.h" #include "V3ExecGraph.h" #include "V3File.h" #include "V3Graph.h" #include "V3GraphStream.h" #include "V3InstrCount.h" #include "V3List.h" #include "V3OrderCFuncEmitter.h" #include "V3OrderInternal.h" #include "V3OrderMoveGraph.h" #include "V3Os.h" #include "V3PairingHeap.h" #include "V3Scoreboard.h" #include "V3Stats.h" #include #include #include #include #include #include VL_DEFINE_DEBUG_FUNCTIONS; class LogicMTask; class MTaskEdge; class MergeCandidate; class SiblingMC; // ###################################################################### // Partitioner tunable settings: // // Before describing these settings, a bit of background: // // Early during the development of the partitioner, V3Split was failing to // split large always blocks (with ~100K assignments) so we had to handle // very large vertices with ~100K incoming and outgoing edges. // // The partitioner attempts to deal with such densely connected // graphs. Some of the tuning parameters below reference "huge vertices", // that's what they're talking about, vertices with tens of thousands of // edges in and out. Whereas most graphs have only tens of edges in and out // of most vertices. // // V3Split has since been fixed to more reliably split large always // blocks. It's kind of an open question whether the partitioner must // handle huge nodes gracefully. Maybe not! But it still can, given // appropriate tuning. // PART_SIBLING_EDGE_LIMIT (integer) // // Arbitrarily limit the number of edges on a single vertex that will be // considered when enumerating siblings, to the given value. This protects // the partitioner runtime in the presence of huge vertices. // // The sibling-merge is less important than the edge merge. (You can // totally disable the sibling merge and get halfway decent partitions; you // can't disable edge merges, those are fundamental to the process.) So, // skipping the enumeration of some siblings on a few vertices does not // have a large impact on the result of the partitioner. // // If your vertices are small, the limit (at 26) approaches a no-op. Hence // there's basically no cost to applying this limit even when we don't // expect huge vertices. // // If you don't care about partitioner runtime and you want the most // aggressive partition, set the limit very high. If you have huge // vertices, leave this as is. constexpr unsigned PART_SIBLING_EDGE_LIMIT = 26; // PART_STEPPED_COST (defined/undef) // // When computing critical path costs, use a step function on the actual // underlying vertex cost. // // If there are huge vertices, when a tiny vertex merges into a huge // vertex, we can often avoid increasing the huge vertex's stepped cost. // If the stepped cost hasn't increased, and the critical path into the huge // vertex hasn't increased, we can avoid propagating a new critical path to // vertices past the huge vertex. Since huge vertices tend to have huge lists // of children and parents, this can be a substantial savings. // // Does not seem to reduce the quality of the partitioner's output. // // If you have huge vertices, leave this 'true', it is the major setting // that allows the partitioner to handle such difficult graphs on anything // like a human time scale. // // If you don't have huge vertices, the 'true' value doesn't help much but // should cost almost nothing in terms of partitioner quality. // // If you want the most aggressive possible partition, set it "false" and // be prepared to be disappointed when the improvement in the partition is // negligible / in the noise. // // Q) Why retain the control, if there is really no downside? // // A) Cost stepping can lead to corner cases. A developer may wish to // disable cost stepping to rule it out as the cause of unexpected // behavior. #define PART_STEPPED_COST true // Don't produce more than a certain maximum number of MTasks. This helps // the TSP variable sort not to blow up (a concern for some of the tests) // and we probably don't want a huge number of mTaskGraphp in practice anyway // (50 to 100 is typical.) // // If the user doesn't give one with '--threads-max-mTaskGraphp', we'll set the // maximum # of MTasks to // (# of threads * PART_DEFAULT_MAX_MTASKS_PER_THREAD) constexpr unsigned PART_DEFAULT_MAX_MTASKS_PER_THREAD = 50; // end tunables. //###################################################################### // Misc graph and assertion utilities static void partCheckCachedScoreVsActual(uint32_t cached, uint32_t actual) { #if PART_STEPPED_COST // Cached CP might be a little bigger than actual, due to stepped CPs. // Example: // Let's say we have a parent with stepped_cost 40 and a grandparent // with stepped_cost 27. Our forward-cp is 67. Then our parent and // grandparent get merged, the merged node has stepped cost 66. We // won't propagate that new CP to children as it hasn't grown. So, // children may continue to think that the CP coming through this path // is a little higher than it really is; permit that. UASSERT((((cached * 10) <= (actual * 11)) && (cached * 11) >= (actual * 10)), "Calculation error in scoring (approximate, may need tweak)"); #else UASSERT(cached == actual, "Calculation error in scoring"); #endif } //============================================================================= // We keep MTaskEdge graph edges in a PairingHeap, sorted by score and id struct EdgeKey final { // Node: Structure layout chosen to minimize padding in PairingHeao<*>::Node uint64_t m_id; // Unique ID part of edge score uint32_t m_score; // Score part of ID void increase(uint32_t score) { UDEBUGONLY(UASSERT(score >= m_score, "Must increase");); m_score = score; } bool operator<(const EdgeKey& other) const { // First by Score then by ID return m_score < other.m_score || (m_score == other.m_score && m_id < other.m_id); } }; using EdgeHeap = PairingHeap; //###################################################################### // MTask utility classes struct MergeCandidateKey final { // Note: Structure layout chosen to minimize padding in PairingHeao<*>::Node uint64_t m_id; // Unique ID part of edge score uint32_t m_score; // Score part of ID bool operator<(const MergeCandidateKey& other) const { // First by Score then by ID, but notice that we want minimums using a max-heap, so reverse return m_score > other.m_score || (m_score == other.m_score && m_id > other.m_id); } }; using MergeCandidateScoreboard = V3Scoreboard; // Information associated with scoreboarding a merge candidate class MergeCandidate VL_NOT_FINAL : public MergeCandidateScoreboard::Node { // Only the known subclasses can create or delete one of these friend class SiblingMC; friend class MTaskEdge; // This structure is extremely hot. To save 8 bytes we pack // one bit indicating removedFromSb with the id. To save another // 8 bytes by not having a virtual function table, we implement the // few polymorphic methods over the two known subclasses explicitly, // using another bit of the id to denote the actual subtype. // By using the bottom bits for flags, we can still use < to compare IDs without masking. // <63:1> Serial number for ordering, <0> subtype (SiblingMC) static constexpr uint64_t IS_SIBLING_MASK = 1ULL << 0; static constexpr uint64_t ID_INCREMENT = 1ULL << 1; bool isSiblingMC() const { return m_key.m_id & IS_SIBLING_MASK; } // CONSTRUCTORS explicit MergeCandidate(bool isSiblingMC) { static uint64_t serial = 0; serial += ID_INCREMENT; // +ID_INCREMENT so doesn't set the special bottom bits m_key.m_id = serial | (isSiblingMC * IS_SIBLING_MASK); } ~MergeCandidate() = default; public: // METHODS SiblingMC* toSiblingMC(); // Instead of cast<>/as<> MTaskEdge* toMTaskEdge(); // Instead of cast<>/as<> bool mergeWouldCreateCycle() const; // Instead of virtual method inline void rescore(); uint32_t score() const { return m_key.m_score; } static MergeCandidate* heapNodeToElem(MergeCandidateScoreboard::Node* nodep) { return static_cast(nodep); } }; static_assert(sizeof(MergeCandidate) == sizeof(MergeCandidateScoreboard::Node), "Should not have a vtable"); // A pair of associated LogicMTask's that are merge candidates for sibling // contraction class SiblingMC final : public MergeCandidate { LogicMTask* const m_ap; LogicMTask* const m_bp; V3ListLinks m_aLinks; // List links to store instances of this class V3ListLinks m_bLinks; // List links to store instances of this class V3ListLinks& aLinks() { return m_aLinks; } V3ListLinks& bLinks() { return m_bLinks; } public: // List type to store instances of this class using AList = V3List; using BList = V3List; // CONSTRUCTORS SiblingMC(LogicMTask* ap, LogicMTask* bp); ~SiblingMC() = default; // METHODS void unlinkA(); void unlinkB(); LogicMTask* ap() const { return m_ap; } LogicMTask* bp() const { return m_bp; } bool mergeWouldCreateCycle() const; }; static_assert(!std::is_polymorphic::value, "Should not have a vtable"); // GraphEdge for the MTask graph class MTaskEdge final : public V3GraphEdge, public MergeCandidate { VL_RTTI_IMPL(MTaskEdge, V3GraphEdge) friend class LogicMTask; template friend class PropagateCp; // MEMBERS // This edge can be in 2 EdgeHeaps, one forward and one reverse. We allocate the heap nodes // directly within the edge as they are always required and this makes association cheap. std::array m_edgeHeapNode; public: // CONSTRUCTORS MTaskEdge(V3Graph* graphp, LogicMTask* fromp, LogicMTask* top, int weight); // METHODS template inline LogicMTask* furtherMTaskp() const; inline LogicMTask* fromMTaskp() const; inline LogicMTask* toMTaskp() const; bool mergeWouldCreateCycle() const; // Following initial assignment of critical paths, clear this MTaskEdge // out of the edge-map for each node and reinsert at a new location // with updated critical path. void resetCriticalPaths(); uint32_t cachedCp(GraphWay way) const { return m_edgeHeapNode[way].key().m_score; } // Convert from the address of the m_edgeHeapNode[way] in an MTaskEdge back to the MTaskEdge static const MTaskEdge* toMTaskEdge(GraphWay way, const EdgeHeap::Node* nodep) { const size_t offset = VL_OFFSETOF(MTaskEdge, m_edgeHeapNode[way]); return reinterpret_cast(reinterpret_cast(nodep) - offset); } private: VL_UNCOPYABLE(MTaskEdge); }; //============================================================================= // LogicMTask class LogicMTask final : public V3GraphVertex { VL_RTTI_IMPL(LogicMTask, V3GraphVertex) template friend class PropagateCp; public: // TYPES struct CmpLogicMTask final { bool operator()(const LogicMTask* ap, const LogicMTask* bp) const { return ap->id() < bp->id(); } }; private: // MEMBERS // List of OrderMoveVertex's assigned to this mtask. LogicMTask does not // own the OrderMoveVertex objects, we merely keep them in a list here. OrderMoveVertex::List m_mVertices; // Cost estimate for this LogicMTask, derived from V3InstrCount. // In abstract time units. uint32_t m_cost = 0; // Cost of critical paths going FORWARD from graph-start to the start // of this vertex, and also going REVERSE from the end of the graph to // the end of the vertex. Same units as m_cost. std::array m_critPathCost; const uint32_t m_id; // Unique LogicMTask ID number static uint32_t s_nextId; // Next ID number to use // Count "generations" which are just operations that scan through the // graph. We'll mark each node with the last generation that scanned // it. We can use this to avoid recursing through the same node twice // while searching for a path. uint64_t m_generation = 0; // Store a set of forward relatives so we can quickly check if we have a given child std::unordered_set m_edgeSet; // Store the outgoing and incoming edges in a heap sorted by the critical path length std::array m_edgeHeap; // MTasks for which a SiblingMC exists with 'this' as the higher ID MTask (m_ap in SiblingMC) std::set m_siblings; // List of SiblingMCs for which this is the higher ID MTask (m_ap in SiblingMC) SiblingMC::AList m_aSiblingMCs; // List of SiblingMCs for which this is the lower ID MTask (m_bp in SiblingMC) SiblingMC::BList m_bSiblingMCs; public: // CONSTRUCTORS LogicMTask(V3Graph* graphp, OrderMoveVertex* mVtxp) : V3GraphVertex{graphp} , m_id{s_nextId++} { UASSERT(s_nextId < 0xFFFFFFFFUL, "Too many mTaskGraphp"); for (uint32_t& item : m_critPathCost) item = 0; if (mVtxp) { m_mVertices.linkBack(mVtxp); if (const OrderLogicVertex* const olvp = mVtxp->logicp()) { m_cost += V3InstrCount::count(olvp->nodep(), true); } } } // METHODS std::set& siblings() { return m_siblings; }; SiblingMC::AList& aSiblingMCs() { return m_aSiblingMCs; }; SiblingMC::BList& bSiblingMCs() { return m_bSiblingMCs; }; OrderMoveVertex::List& vertexList() { return m_mVertices; } const OrderMoveVertex::List& vertexList() const { return m_mVertices; } void moveAllVerticesFrom(LogicMTask* otherp) { m_mVertices.splice(m_mVertices.end(), otherp->vertexList()); m_cost += otherp->m_cost; } static uint64_t incGeneration() { static uint64_t s_generation = 0; ++s_generation; return s_generation; } // Use this instead of pointer-compares to compare LogicMTasks. Avoids // nondeterministic output. Also name mTaskGraphp based on this number in // the final C++ output. uint32_t id() const { return m_id; } // Abstract cost of every logic mtask uint32_t cost() const VL_MT_SAFE { return m_cost; } void setCost(uint32_t cost) { m_cost = cost; } // For tests only uint32_t stepCost() const { return stepCost(m_cost); } static uint32_t stepCost(uint32_t cost) { #if PART_STEPPED_COST // Round cost up to the nearest 5%. Use this when computing all // critical paths. The idea is that critical path changes don't // need to propagate when they don't exceed the next step, saving a // lot of recursion. if (cost == 0) return 0; double logcost = log(cost); // log(1.05) is about 0.05 // So, round logcost up to the next 0.05 boundary logcost *= 20.0; logcost = ceil(logcost); logcost = logcost / 20.0; const uint32_t stepCost = static_cast(exp(logcost)); UDEBUGONLY(UASSERT_STATIC(stepCost >= cost, "stepped cost error exceeded");); UDEBUGONLY(UASSERT_STATIC(stepCost <= ((cost * 11 / 10)), "stepped cost error exceeded");); return stepCost; #else return cost; #endif } template void addRelativeEdge(MTaskEdge* edgep) { constexpr GraphWay way{N_Way}; constexpr GraphWay inv = way.invert(); // Add to the edge heap LogicMTask* const relativep = edgep->furtherMTaskp(); // Value is !way cp to this edge const uint32_t cp = relativep->stepCost() + relativep->critPathCost(inv); // m_edgeHeap[way].insert(&edgep->m_edgeHeapNode[way], {relativep->id(), cp}); } template void stealRelativeEdge(MTaskEdge* edgep) { constexpr GraphWay way{N_Way}; // Make heap node insertable, ruining the heap it is currently in. edgep->m_edgeHeapNode[way].yank(); // Add the edge as new addRelativeEdge(edgep); } template void removeRelativeEdge(MTaskEdge* edgep) { constexpr GraphWay way{N_Way}; // Remove from the edge heap m_edgeHeap[way].remove(&edgep->m_edgeHeapNode[way]); } void addRelativeMTask(LogicMTask* relativep) { // Add the relative to connecting edge map const bool exits = !m_edgeSet.emplace(relativep).second; UDEBUGONLY(UASSERT(!exits, "Adding existing relative");); } void removeRelativeMTask(LogicMTask* relativep) { const size_t removed = m_edgeSet.erase(relativep); UDEBUGONLY(UASSERT(removed, "Relative should have been in set");); } bool hasRelativeMTask(LogicMTask* relativep) const { return m_edgeSet.count(relativep); } template void checkRelativesCp() const { constexpr GraphWay way{N_Way}; for (const V3GraphEdge& edge : edges()) { const LogicMTask* const relativep = static_cast(edge.furtherp()); const uint32_t cachedCp = static_cast(edge).cachedCp(way); const uint32_t cp = relativep->critPathCost(way.invert()) + relativep->stepCost(); partCheckCachedScoreVsActual(cachedCp, cp); } } string name() const override VL_MT_STABLE { // Display forward and reverse critical path costs. This gives a quick // read on whether graph partitioning looks reasonable or bad. std::ostringstream out; out << "mt" << m_id << "." << this << " [b" << m_critPathCost[GraphWay::FORWARD] << " a" << m_critPathCost[GraphWay::REVERSE] << " c" << cost(); return out.str(); } void setCritPathCost(GraphWay way, uint32_t cost) { m_critPathCost[way] = cost; } uint32_t critPathCost(GraphWay way) const { return m_critPathCost[way]; } template uint32_t critPathCostWithout(const V3GraphEdge* withoutp) const { const GraphWay way{N_Way}; const GraphWay inv = way.invert(); // Compute the critical path cost wayward to this node, without considering edge // 'withoutp'. We need to look at two edges at most, the critical path if that is not via // 'withoutp', or the second-worst path, if the critical path is via 'withoutp'. UDEBUGONLY(UASSERT(withoutp->furtherp() == this, "In critPathCostWithout(), edge 'withoutp' must further to 'this'");); const EdgeHeap& edgeHeap = m_edgeHeap[inv]; const EdgeHeap::Node* const maxp = edgeHeap.max(); if (!maxp) return 0; if (MTaskEdge::toMTaskEdge(inv, maxp) != withoutp) return maxp->key().m_score; const EdgeHeap::Node* const secp = edgeHeap.secondMax(); if (!secp) return 0; return secp->key().m_score; } private: static bool pathExistsFromInternal(LogicMTask* fromp, LogicMTask* top, const V3GraphEdge* excludedEdgep, uint64_t generation) { // Q) Why does this take LogicMTask instead of generic V3GraphVertex? // A) We'll use the critical paths known to LogicMTask to prune the // recursion for speed. Also store 'generation' in // LogicMTask::m_generation so we can prune the search and avoid // recursing through the same node more than once in a single // search. if (fromp->m_generation == generation) { // Already looked at this node in the current search. // Since we're back again, we must not have found a path on the // first go. return false; } fromp->m_generation = generation; // Base case: we found a path. if (fromp == top) return true; // Base case: fromp is too late, cannot possibly be a prereq for top. if (fromp->critPathCost(GraphWay::REVERSE) < (top->critPathCost(GraphWay::REVERSE) + top->stepCost())) { return false; } if ((fromp->critPathCost(GraphWay::FORWARD) + fromp->stepCost()) > top->critPathCost(GraphWay::FORWARD)) { return false; } // Recursively look for a path for (const V3GraphEdge& follow : fromp->outEdges()) { if (&follow == excludedEdgep) continue; LogicMTask* const nextp = static_cast(follow.top()); if (pathExistsFromInternal(nextp, top, nullptr, generation)) return true; } return false; } // True if there's a path from 'fromp' to 'top' excluding // 'excludedEdgep', false otherwise. // // 'excludedEdgep' may be nullptr in which case no edge is excluded. If // 'excludedEdgep' is non-nullptr it must connect fromp and top. // // TODO: consider changing this API to the 'isTransitiveEdge' API // used by GraphPathChecker public: static bool pathExistsFrom(LogicMTask* fromp, LogicMTask* top, const V3GraphEdge* excludedEdgep) { return pathExistsFromInternal(fromp, top, excludedEdgep, incGeneration()); } static void dumpCpFilePrefixed(const V3Graph& graph, const string& nameComment) { const string filename = v3Global.debugFilename(nameComment) + ".txt"; UINFO(1, "Writing " << filename << endl); const std::unique_ptr ofp{V3File::new_ofstream(filename)}; std::ostream* const osp = &(*ofp); // &* needed to deref unique_ptr if (osp->fail()) v3fatalStatic("Can't write " << filename); // Find start vertex with longest CP const LogicMTask* startp = nullptr; for (const V3GraphVertex& vtx : graph.vertices()) { const LogicMTask& mtask = static_cast(vtx); if (!startp) { startp = &mtask; continue; } if (mtask.cost() + mtask.critPathCost(GraphWay::REVERSE) > startp->cost() + startp->critPathCost(GraphWay::REVERSE)) { startp = &mtask; } } // Follow the entire critical path std::vector path; uint32_t totalCost = 0; for (const LogicMTask* nextp = startp; nextp;) { path.push_back(nextp); totalCost += nextp->cost(); if (EdgeHeap::Node* const maxp = nextp->m_edgeHeap[GraphWay::FORWARD].max()) { nextp = MTaskEdge::toMTaskEdge(GraphWay::FORWARD, maxp)->toMTaskp(); } else { nextp = nullptr; } } *osp << "totalCost = " << totalCost << " (should match the computed critical path cost (CP) for the graph)\n"; // Dump for (const LogicMTask* mtaskp : path) { *osp << "begin mtask with cost " << mtaskp->cost() << '\n'; for (const OrderMoveVertex& mVtx : mtaskp->vertexList()) { const OrderLogicVertex* const logicp = mVtx.logicp(); if (!logicp) continue; // Show nodes with hierarchical costs V3InstrCount::count(logicp->nodep(), false, osp); } } } private: VL_UNCOPYABLE(LogicMTask); }; // Start at 1, so that 0 indicates no mtask. uint32_t LogicMTask::s_nextId = 1; // Instead of dynamic cast SiblingMC* MergeCandidate::toSiblingMC() { return isSiblingMC() ? static_cast(this) : nullptr; } MTaskEdge* MergeCandidate::toMTaskEdge() { return isSiblingMC() ? nullptr : static_cast(this); } // Normally this would be a virtual function, but we save space by not having a vtable, // and we know we only have 2 possible subclasses. bool MergeCandidate::mergeWouldCreateCycle() const { return isSiblingMC() ? static_cast(this)->mergeWouldCreateCycle() : static_cast(this)->mergeWouldCreateCycle(); } static uint32_t siblingScore(const SiblingMC* sibsp) { const LogicMTask* const ap = sibsp->ap(); const LogicMTask* const bp = sibsp->bp(); const uint32_t mergedCpCostFwd = std::max(ap->critPathCost(GraphWay::FORWARD), bp->critPathCost(GraphWay::FORWARD)); const uint32_t mergedCpCostRev = std::max(ap->critPathCost(GraphWay::REVERSE), bp->critPathCost(GraphWay::REVERSE)); return mergedCpCostRev + mergedCpCostFwd + LogicMTask::stepCost(ap->cost() + bp->cost()); } static uint32_t edgeScore(const MTaskEdge* edgep) { // Score this edge. Lower is better. The score is the new local CP // length if we merge these mTaskGraphp. ("Local" means the longest // critical path running through the merged node.) const LogicMTask* const top = edgep->toMTaskp(); const LogicMTask* const fromp = edgep->fromMTaskp(); const uint32_t mergedCpCostFwd = std::max(fromp->critPathCost(GraphWay::FORWARD), top->critPathCostWithout(edgep)); const uint32_t mergedCpCostRev = std::max(fromp->critPathCostWithout(edgep), top->critPathCost(GraphWay::REVERSE)); return mergedCpCostRev + mergedCpCostFwd + LogicMTask::stepCost(fromp->cost() + top->cost()); } void MergeCandidate::rescore() { if (const SiblingMC* const sibp = toSiblingMC()) { m_key.m_score = siblingScore(sibp); } else { // The '1 +' favors merging a SiblingMC over an otherwise- // equal-scoring MTaskEdge. The comment on selfTest() talks // about why. m_key.m_score = 1 + edgeScore(static_cast(this)); } } SiblingMC::SiblingMC(LogicMTask* ap, LogicMTask* bp) : MergeCandidate{/* isSiblingMC: */ true} , m_ap{ap} , m_bp{bp} { // Storage management depends on this UASSERT(ap->id() > bp->id(), "Should be ordered"); UDEBUGONLY(UASSERT(ap->siblings().count(bp), "Should be in sibling map");); m_ap->aSiblingMCs().linkBack(this); m_bp->bSiblingMCs().linkBack(this); } void SiblingMC::unlinkA() { VL_ATTR_UNUSED const size_t removed = m_ap->siblings().erase(m_bp); UDEBUGONLY(UASSERT(removed == 1, "Should have been in sibling set");); m_ap->aSiblingMCs().unlink(this); } void SiblingMC::unlinkB() { m_bp->bSiblingMCs().unlink(this); } bool SiblingMC::mergeWouldCreateCycle() const { return (LogicMTask::pathExistsFrom(m_ap, m_bp, nullptr) || LogicMTask::pathExistsFrom(m_bp, m_ap, nullptr)); } MTaskEdge::MTaskEdge(V3Graph* graphp, LogicMTask* fromp, LogicMTask* top, int weight) : V3GraphEdge{graphp, fromp, top, weight} , MergeCandidate{/* isSiblingMC: */ false} { fromp->addRelativeMTask(top); fromp->addRelativeEdge(this); top->addRelativeEdge(this); } template LogicMTask* MTaskEdge::furtherMTaskp() const { return static_cast(this->furtherp()); } LogicMTask* MTaskEdge::fromMTaskp() const { return static_cast(fromp()); } LogicMTask* MTaskEdge::toMTaskp() const { return static_cast(top()); } bool MTaskEdge::mergeWouldCreateCycle() const { return LogicMTask::pathExistsFrom(fromMTaskp(), toMTaskp(), this); } // Following initial assignment of critical paths, clear this MTaskEdge // out of the edge-map for each node and reinsert at a new location // with updated critical path. void MTaskEdge::resetCriticalPaths() { LogicMTask* const fromp = fromMTaskp(); LogicMTask* const top = toMTaskp(); fromp->removeRelativeEdge(this); top->removeRelativeEdge(this); fromp->addRelativeEdge(this); top->addRelativeEdge(this); } //###################################################################### // Look at vertex costs (in one way) to form critical paths for each // vertex. template static void partInitHalfCriticalPaths(V3Graph& mTaskGraph, bool checkOnly) { constexpr GraphWay way{N_Way}; constexpr GraphWay rev = way.invert(); GraphStreamUnordered order{&mTaskGraph, way}; for (const V3GraphVertex* vertexp; (vertexp = order.nextp());) { const LogicMTask* const mtaskcp = static_cast(vertexp); LogicMTask* const mtaskp = const_cast(mtaskcp); uint32_t cpCost = 0; #if VL_DEBUG std::unordered_set relatives; #endif for (const V3GraphEdge& edge : vertexp->edges()) { #if VL_DEBUG // Run a few asserts on the initial mtask graph, // while we're iterating through... UASSERT_OBJ(edge.weight() != 0, mtaskp, "Should be no cut edges in mTaskGraphp graph"); UASSERT_OBJ(relatives.find(edge.furtherp()) == relatives.end(), mtaskp, "Should be no redundant edges in mTaskGraphp graph"); relatives.insert(edge.furtherp()); #endif const LogicMTask* const relativep = static_cast(edge.furtherp()); cpCost = std::max(cpCost, (relativep->critPathCost(way) + static_cast(relativep->stepCost()))); } if (checkOnly) { partCheckCachedScoreVsActual(mtaskp->critPathCost(way), cpCost); } else { mtaskp->setCritPathCost(way, cpCost); } } } // Look at vertex costs to form critical paths for each vertex. static void partInitCriticalPaths(V3Graph& mTaskGraph) { partInitHalfCriticalPaths(mTaskGraph, false); partInitHalfCriticalPaths(mTaskGraph, false); // Reset all MTaskEdges so that 'm_edges' will show correct CP numbers. // They would have been all zeroes on initial creation of the MTaskEdges. for (V3GraphVertex& vtx : mTaskGraph.vertices()) { for (V3GraphEdge& edge : vtx.outEdges()) edge.as()->resetCriticalPaths(); } } // Do an EXPENSIVE check to make sure that all incremental CP updates have // gone correctly. static void partCheckCriticalPaths(V3Graph& mTaskGraph) { partInitHalfCriticalPaths(mTaskGraph, true); partInitHalfCriticalPaths(mTaskGraph, true); for (const V3GraphVertex& vtx : mTaskGraph.vertices()) { const LogicMTask& mtask = static_cast(vtx); mtask.checkRelativesCp(); mtask.checkRelativesCp(); } } // ###################################################################### // PropagateCp template class PropagateCp final { // Propagate increasing critical path (CP) costs through a graph. // // Usage: // * Client increases the cost and/or CP at a node or small set of nodes // (often a pair in practice, eg. edge contraction.) // * Client calls PropagateCp::cpHasIncreased() one or more times. // Each call indicates that the inclusive CP of some "seed" vertex // has increased to a given value. // * NOTE: PropagateCp will neither read nor modify the cost // or CPs at the seed vertices, it only accesses and modifies // vertices wayward from the seeds. // * Client calls PropagateCp::go(). Internally, this iteratively // propagates the new CPs wayward through the graph. // // TYPES // We keep pending vertices in a heap during critical path propagation struct PendingKey final { LogicMTask* m_mtaskp; // The vertex in the heap uint32_t m_score; // The score of this entry void increase(uint32_t score) { UDEBUGONLY(UASSERT(score >= m_score, "Must increase");); m_score = score; } bool operator<(const PendingKey& other) const { if (m_score != other.m_score) return m_score < other.m_score; return LogicMTask::CmpLogicMTask{}(m_mtaskp, other.m_mtaskp); } }; using PendingHeap = PairingHeap; using PendingHeapNode = typename PendingHeap::Node; // MEMBERS PendingHeap m_pendingHeap; // Heap of pending rescores // We allocate this many heap nodes at once static constexpr size_t ALLOC_CHUNK_SIZE = 128; PendingHeapNode* m_freep = nullptr; // List of free heap nodes std::vector> m_allocated; // Allocated heap nodes const bool m_slowAsserts; // Enable nontrivial asserts // Used only with slow asserts to check mTaskGraphp visited only once std::set m_seen; public: // CONSTRUCTORS explicit PropagateCp(bool slowAsserts) : m_slowAsserts{slowAsserts} {} // METHODS private: // Allocate a HeapNode for the given element PendingHeapNode* allocNode() { // If no free nodes available, then make some if (!m_freep) { // Allocate in chunks for efficiency m_allocated.emplace_back(new PendingHeapNode[ALLOC_CHUNK_SIZE]); // Set up free list pointer m_freep = m_allocated.back().get(); // Set up free list chain for (size_t i = 1; i < ALLOC_CHUNK_SIZE; ++i) { m_freep[i - 1].m_next.m_ptr = &m_freep[i]; } // Clear the next pointer of the last entry m_freep[ALLOC_CHUNK_SIZE - 1].m_next.m_ptr = nullptr; } // Free nodes are available, pick up the first one PendingHeapNode* const resultp = m_freep; m_freep = resultp->m_next.m_ptr; resultp->m_next.m_ptr = nullptr; return resultp; } // Release a heap node (make it available for future allocation) void freeNode(PendingHeapNode* nodep) { // Re-use the existing link pointers and simply prepend it to the free list nodep->m_next.m_ptr = m_freep; m_freep = nodep; } public: void cpHasIncreased(V3GraphVertex* vxp, uint32_t newInclusiveCp) { constexpr GraphWay way{N_Way}; constexpr GraphWay inv{way.invert()}; // For *vxp, whose CP-inclusive has just increased to // newInclusiveCp, iterate to all wayward nodes, update the edges // of each, and add each to m_pending if its overall CP has grown. for (V3GraphEdge& graphEdge : vxp->edges()) { MTaskEdge& edge = static_cast(graphEdge); LogicMTask* const relativep = edge.furtherMTaskp(); EdgeHeap::Node& edgeHeapNode = edge.m_edgeHeapNode[inv]; if (newInclusiveCp > edgeHeapNode.key().m_score) { relativep->m_edgeHeap[inv].increaseKey(&edgeHeapNode, newInclusiveCp); } const uint32_t critPathCost = relativep->critPathCost(way); if (critPathCost >= newInclusiveCp) continue; // relativep's critPathCost() is out of step with its longest !wayward edge. // Schedule that to be resolved. const uint32_t newVal = newInclusiveCp - critPathCost; if (PendingHeapNode* const nodep = static_cast(relativep->userp())) { // Already in heap. Increase score if needed. if (newVal > nodep->key().m_score) m_pendingHeap.increaseKey(nodep, newVal); continue; } // Add to heap PendingHeapNode* const nodep = allocNode(); relativep->userp(nodep); m_pendingHeap.insert(nodep, {relativep, newVal}); } } void go() { constexpr GraphWay way{N_Way}; constexpr GraphWay inv{way.invert()}; // m_pending maps each pending vertex to the amount that it wayward // CP will grow. // // We can iterate over the pending set in reverse order, always // choosing the nodes with the largest pending CP-growth. // // The intuition is: if the original seed node had its CP grow by // 50, the most any wayward node can possibly grow is also 50. So // for anything pending to grow by 50, we know we can process it // once and we won't have to grow its CP again on the current pass. // After we're done with all the grow-by-50s, nothing else will // grow by 50 again on the current pass, and we can process the // grow-by-49s and we know we'll only have to process each one // once. And so on. // // This generalizes to multiple seed nodes also. while (!m_pendingHeap.empty()) { // Pop max element from heap PendingHeapNode* const maxp = m_pendingHeap.max(); m_pendingHeap.remove(maxp); // Pick up values LogicMTask* const mtaskp = maxp->key().m_mtaskp; const uint32_t cpGrowBy = maxp->key().m_score; // Free the heap node, we are done with it freeNode(maxp); mtaskp->userp(nullptr); // Update the critPathCost of mtaskp, that was out-of-date with respect to its edges const uint32_t startCp = mtaskp->critPathCost(way); const uint32_t newCp = startCp + cpGrowBy; if (VL_UNLIKELY(m_slowAsserts)) { // Check that CP matches that of the longest edge wayward of vxp. const uint32_t edgeCp = mtaskp->m_edgeHeap[inv].max()->key().m_score; UASSERT_OBJ(edgeCp == newCp, mtaskp, "CP doesn't match longest wayward edge"); // Confirm that we only set each node's CP once. That's an // important property of PropagateCp which allows it to be far // faster than a recursive algorithm on some graphs. const bool first = m_seen.insert(mtaskp).second; UASSERT_OBJ(first, mtaskp, "Set CP on node twice"); } mtaskp->setCritPathCost(way, newCp); cpHasIncreased(mtaskp, newCp + mtaskp->stepCost()); } if (VL_UNLIKELY(m_slowAsserts)) m_seen.clear(); } private: VL_UNCOPYABLE(PropagateCp); public: static void selfTest() { V3Graph graph; // A graph std::array vx; // All vertices within the graph // Generate a pseudo-random graph std::array rngState = {{0x12345678ULL, 0x9abcdef0ULL}}; // GCC 3.8.0 wants {{}} // Create 50 vertices for (auto& i : vx) { i = new LogicMTask{&graph, nullptr}; i->setCost(1); } // Create 250 edges at random. Edges must go from // lower-to-higher index vertices, so we get a DAG. for (unsigned i = 0; i < 250; ++i) { const unsigned idx1 = V3Os::rand64(rngState) % 50; const unsigned idx2 = V3Os::rand64(rngState) % 50; if (idx1 > idx2) { if (!vx[idx2]->hasRelativeMTask(vx[idx1])) { new MTaskEdge{&graph, vx[idx2], vx[idx1], 1}; } } else if (idx2 > idx1) { if (!vx[idx1]->hasRelativeMTask(vx[idx2])) { new MTaskEdge{&graph, vx[idx1], vx[idx2], 1}; } } } partInitCriticalPaths(graph); PropagateCp prop{true}; // Seed the propagator with every input node; // This should result in the complete graph getting all CP's assigned. for (const auto& i : vx) { if (i->inEmpty()) prop.cpHasIncreased(i, 1 /* inclusive CP starts at 1 */); } // Run the propagator. prop.go(); // Finally, confirm that the entire graph appears to have correct CPs. partCheckCriticalPaths(graph); } }; // Merge edges from a LogicMtask. static void partRedirectEdgesFrom(V3Graph& graph, LogicMTask* recipientp, LogicMTask* donorp, MergeCandidateScoreboard* sbp) { // This code removes adjacent edges. When this occurs, mark it in need // of a rescore, in case its score has fallen and we need to move it up // toward the front of the scoreboard. // // Wait, what? Shouldn't the scores only increase as we merge nodes? Well // that's almost true. But there is one exception. // // Suppose we have A->B, B->C, and A->C. // // The A->C edge is a "transitive" edge. It's ineligible to be merged, as // the merge would create a cycle. We score it on the scoreboard like any // other edge. // // However, our "score" estimate for A->C is bogus, because the forward // critical path to C and the reverse critical path to A both contain the // same node (B) so we overestimate the score of A->C. At first this // doesn't matter, since transitive edges aren't eligible to merge anyway. // // Later, suppose the edge contractor decides to merge the B->C edge, with // B donating all its incoming edges into C, say. (So we reach this // function.) // // With B going away, the A->C edge will no longer be transitive and it // will become eligible to merge. But if we don't mark it for rescore, // it'll stay in the scoreboard with its old (overestimate) score. We'll // merge it too late due to the bogus score. When we finally merge it, we // fail the assert in the main edge contraction loop which checks that the // actual score did not fall below the scoreboard's score. // // Another way of stating this: this code ensures that scores of // non-transitive edges only ever increase. // Process outgoing edges while (MTaskEdge* const edgep = static_cast(donorp->outEdges().frontp())) { LogicMTask* const relativep = edgep->toMTaskp(); relativep->removeRelativeEdge(edgep); if (recipientp->hasRelativeMTask(relativep)) { // An edge already exists between recipient and relative of donor. // Mark it in need of a rescore if (sbp) { if (sbp->contains(edgep)) sbp->remove(edgep); MTaskEdge* const existMTaskEdgep = static_cast( recipientp->findConnectingEdgep(relativep)); UDEBUGONLY(UASSERT(existMTaskEdgep, "findConnectingEdge didn't find edge");); if (sbp->contains(existMTaskEdgep)) sbp->hintScoreChanged(existMTaskEdgep); } VL_DO_DANGLING(edgep->unlinkDelete(), edgep); } else { // No existing edge between recipient and relative of donor. // Redirect the edge from donor<->relative to recipient<->relative. edgep->relinkFromp(recipientp); recipientp->addRelativeMTask(relativep); recipientp->stealRelativeEdge(edgep); relativep->addRelativeEdge(edgep); if (sbp) { if (!sbp->contains(edgep)) { sbp->add(edgep); } else { sbp->hintScoreChanged(edgep); } } } } // Process incoming edges while (MTaskEdge* const edgep = static_cast(donorp->inEdges().frontp())) { LogicMTask* const relativep = edgep->fromMTaskp(); relativep->removeRelativeMTask(donorp); relativep->removeRelativeEdge(edgep); if (relativep->hasRelativeMTask(recipientp)) { // An edge already exists between recipient and relative of donor. // Mark it in need of a rescore if (sbp) { if (sbp->contains(edgep)) sbp->remove(edgep); MTaskEdge* const existMTaskEdgep = static_cast( recipientp->findConnectingEdgep(relativep)); UDEBUGONLY(UASSERT(existMTaskEdgep, "findConnectingEdge didn't find edge");); if (sbp->contains(existMTaskEdgep)) sbp->hintScoreChanged(existMTaskEdgep); } VL_DO_DANGLING(edgep->unlinkDelete(), edgep); } else { // No existing edge between recipient and relative of donor. // Redirect the edge from donor<->relative to recipient<->relative. edgep->relinkTop(recipientp); relativep->addRelativeMTask(recipientp); relativep->addRelativeEdge(edgep); recipientp->stealRelativeEdge(edgep); if (sbp) { if (!sbp->contains(edgep)) { sbp->add(edgep); } else { sbp->hintScoreChanged(edgep); } } } } // Remove donorp from the graph VL_DO_DANGLING(donorp->unlinkDelete(&graph), donorp); } //###################################################################### // Contraction // Perform edge or sibling contraction on the partition graph class Contraction final { // TYPES // New CP information for mtaskp reflecting an upcoming merge struct NewCp final { uint32_t cp; uint32_t propagateCp; bool propagate; }; // MEMBERS V3Graph& m_mTaskGraph; // The Mtask graph uint32_t m_scoreLimit; // Sloppy score allowed when picking merges uint32_t m_scoreLimitBeforeRescore = 0xffffffff; // Next score rescore at unsigned m_mergesSinceRescore = 0; // Merges since last rescore const bool m_slowAsserts; // Take extra time to validate algorithm MergeCandidateScoreboard m_sb; // Scoreboard PropagateCp m_forwardPropagator{m_slowAsserts}; // Forward propagator PropagateCp m_reversePropagator{m_slowAsserts}; // Reverse propagator LogicMTask* const m_entryMTaskp; // Singular source vertex of the dependency graph LogicMTask* const m_exitMTaskp; // Singular sink vertex of the dependency graph public: // CONSTRUCTORS Contraction(V3Graph& mTaskGraph, uint32_t scoreLimit, LogicMTask* entryMTaskp, LogicMTask* exitMTaskp, bool slowAsserts) : m_mTaskGraph{mTaskGraph} , m_scoreLimit{scoreLimit} , m_slowAsserts{slowAsserts} , m_entryMTaskp{entryMTaskp} , m_exitMTaskp{exitMTaskp} { if (m_slowAsserts) { // Check there are no redundant edges for (V3GraphVertex& vtx : m_mTaskGraph.vertices()) { std::unordered_set neighbors; for (V3GraphEdge& edge : vtx.outEdges()) { const bool first = neighbors.insert(edge.top()).second; UASSERT_OBJ(first, &vtx, "Redundant edge found in input to Contraction()"); } } } unsigned maxMTasks = v3Global.opt.threadsMaxMTasks(); if (maxMTasks == 0) { // Unspecified so estimate if (v3Global.opt.threads() > 1) { maxMTasks = (PART_DEFAULT_MAX_MTASKS_PER_THREAD * v3Global.opt.threads()); } else { // Running Contraction with --threads <= 1 means self-test maxMTasks = 500; } } // OPTIMIZATION PASS: Edge contraction and sibling contraction. // - Score each pair of mTaskGraphp which is a candidate to merge. // * Each edge defines such a candidate pair // * Two mTaskGraphp that are prereqs or postreqs of a common third // vertex are "siblings", these are also a candidate pair. // - Build a list of MergeCandidates, sorted by score. // - Merge the best pair. // - Incrementally recompute critical paths near the merged mtask. for (V3GraphVertex& vtx : m_mTaskGraph.vertices()) { vtx.userp(nullptr); // Reset user value while we are here. Used by PropagateCp. for (V3GraphEdge& edge : vtx.outEdges()) m_sb.add(static_cast(&edge)); siblingPairFromRelatives(&vtx); siblingPairFromRelatives(&vtx); } doRescore(); // Set initial scores in scoreboard while (true) { // This is the best edge to merge, with the lowest // score (shortest local critical path) MergeCandidate* const mergeCanp = m_sb.best(); if (!mergeCanp) { // Scoreboard found no eligible merges. Maybe a rescore // will produce some merge-able pairs? if (m_sb.needsRescore()) { doRescore(); continue; } break; } if (m_slowAsserts) { UASSERT(!m_sb.needsRescore(mergeCanp), "Need-rescore items should not be returned by bestp"); } const uint32_t cachedScore = mergeCanp->score(); mergeCanp->rescore(); const uint32_t actualScore = mergeCanp->score(); if (actualScore > cachedScore) { // Cached score is out-of-date. // Mark this elem as in need of a rescore and continue. m_sb.hintScoreChanged(mergeCanp); continue; } // ... we'll also confirm that actualScore hasn't shrunk relative // to cached score, after the mergeWouldCreateCycle() check. if (actualScore > m_scoreLimit) { // Our best option isn't good enough if (m_sb.needsRescore()) { // Some pairs need a rescore, maybe those will be // eligible to merge afterward. doRescore(); continue; } else { // We've exhausted everything below m_scoreLimit; stop. // Except, if we have too many mTaskGraphp, raise the score // limit and keep going... const unsigned mtaskCount = m_mTaskGraph.vertices().size(); if (mtaskCount > maxMTasks) { const uint32_t oldLimit = m_scoreLimit; m_scoreLimit = (m_scoreLimit * 120) / 100; v3Global.rootp()->fileline()->v3warn( UNOPTTHREADS, "Thread scheduler is unable to provide requested " "parallelism; suggest asking for fewer threads."); UINFO(1, "Critical path limit was=" << oldLimit << " now=" << m_scoreLimit << endl); continue; } // Really stop break; } } if (actualScore > m_scoreLimitBeforeRescore) { // Time to rescore, that will result in a higher // scoreLimitBeforeRescore, and possibly lower-scoring // elements returned from bestp(). doRescore(); continue; } // Avoid merging the entry/exit nodes. This would create serialization, by forcing the // merged MTask to run before/after everything else. Empirically this helps // performance in a modest way by allowing other MTasks to start earlier. if (MTaskEdge* const edgep = mergeCanp->toMTaskEdge()) { if (edgep->fromp() == m_entryMTaskp || edgep->top() == m_exitMTaskp) { m_sb.remove(mergeCanp); continue; } } // Avoid merging any edge that would create a cycle. // // For example suppose we begin with vertices A, B, C and edges // A->B, B->C, A->C. // // Suppose we want to merge A->C into a single vertex. // New edges would be AC->B and B->AC which is not a DAG. // Do not allow this. if (mergeCanp->mergeWouldCreateCycle()) { // Remove this candidate from scoreboard so we don't keep // reconsidering it on every loop. m_sb.remove(mergeCanp); if (SiblingMC* const smcp = mergeCanp->toSiblingMC()) { smcp->unlinkA(); smcp->unlinkB(); VL_DO_DANGLING(delete smcp, smcp); } continue; } partCheckCachedScoreVsActual(cachedScore, actualScore); // Finally there's no cycle risk, no need to rescore, we're // within m_scoreLimit and m_scoreLimitBeforeRescore. // This is the edge to merge. // // Bookkeeping: if this is the first edge we'll merge since // the last rescore, compute the new m_scoreLimitBeforeRescore // to be somewhat higher than this edge's score. if (m_mergesSinceRescore == 0) { #if PART_STEPPED_RESCORELIMIT m_scoreLimitBeforeRescore = (actualScore * 105) / 100; #else m_scoreLimitBeforeRescore = actualScore; #endif // This print can serve as a progress indicator, as it // increases from low numbers up toward cpLimit. It may be // helpful to see progress during slow partitions. Maybe // display something by default even? UINFO(6, "New scoreLimitBeforeRescore: " << m_scoreLimitBeforeRescore << endl); } // Finally merge this candidate. contract(mergeCanp); } // Free remaining SiblingMCs while (MergeCandidate* const mergeCanp = m_sb.best()) { m_sb.remove(mergeCanp); if (SiblingMC* const smcp = mergeCanp->toSiblingMC()) { smcp->unlinkA(); smcp->unlinkB(); VL_DO_DANGLING(delete smcp, smcp); } } } private: template NewCp newCp(LogicMTask* mtaskp, LogicMTask* otherp, MTaskEdge* mergeEdgep) { constexpr GraphWay way{N_Way}; // Return new wayward-CP for mtaskp reflecting its upcoming merge // with otherp. Set 'result.propagate' if mtaskp's wayward // relatives will see a new wayward CP from this merge. uint32_t newCp; if (mergeEdgep) { if (mtaskp == mergeEdgep->furtherp()) { newCp = std::max(otherp->critPathCost(way), mtaskp->critPathCostWithout(mergeEdgep)); } else { newCp = std::max(mtaskp->critPathCost(way), otherp->critPathCostWithout(mergeEdgep)); } } else { newCp = std::max(otherp->critPathCost(way), mtaskp->critPathCost(way)); } const uint32_t origRelativesCp = mtaskp->critPathCost(way) + mtaskp->stepCost(); const uint32_t newRelativesCp = newCp + LogicMTask::stepCost(mtaskp->cost() + otherp->cost()); NewCp result; result.cp = newCp; result.propagate = (newRelativesCp > origRelativesCp); result.propagateCp = newRelativesCp; return result; } void removeSiblingMCsWith(LogicMTask* mtaskp) { while (SiblingMC* const smcp = mtaskp->aSiblingMCs().unlinkFront()) { m_sb.remove(smcp); smcp->unlinkB(); VL_DO_DANGLING(delete smcp, smcp); } while (SiblingMC* const smcp = mtaskp->bSiblingMCs().unlinkFront()) { m_sb.remove(smcp); smcp->unlinkA(); VL_DO_DANGLING(delete smcp, smcp); } } void removeSiblingMCs(LogicMTask* recipientp, LogicMTask* donorp) { // The lists here should be disjoint (there should be only one SiblingMC involving these // two MTasks, and we removed that elsewhere), so no need for unlinking from the lists we // are clearing. removeSiblingMCsWith(recipientp); removeSiblingMCsWith(donorp); // Clear the sibling map of the recipient. The donor will be deleted anyway, so we can // leave that in a corrupt for efficiency. recipientp->siblings().clear(); } void contract(MergeCandidate* mergeCanp) { LogicMTask* top = nullptr; LogicMTask* fromp = nullptr; MTaskEdge* const mergeEdgep = mergeCanp->toMTaskEdge(); SiblingMC* const mergeSibsp = mergeCanp->toSiblingMC(); if (mergeEdgep) { top = mergeEdgep->toMTaskp(); fromp = mergeEdgep->fromMTaskp(); } else { top = mergeSibsp->ap(); fromp = mergeSibsp->bp(); } // Merge the smaller mtask into the larger mtask. If one of them // is much larger, this will save time in partRedirectEdgesFrom(). // Assume the more costly mtask has more edges. // // [TODO: now that we have edge maps, we could count the edges // exactly without a linear search.] LogicMTask* recipientp; LogicMTask* donorp; if (fromp->cost() > top->cost()) { recipientp = fromp; donorp = top; } else { donorp = fromp; recipientp = top; } VL_DANGLING(fromp); VL_DANGLING(top); // Use donorp and recipientp now instead // Recursively update forward and reverse CP numbers. // // Doing this before merging the mTaskGraphp lets us often avoid // recursing through either incoming or outgoing edges on one or // both mTaskGraphp. // // These 'NewCp' objects carry a bit indicating whether we must // propagate CP for each of the four cases: const NewCp recipientNewCpFwd = newCp(recipientp, donorp, mergeEdgep); const NewCp donorNewCpFwd = newCp(donorp, recipientp, mergeEdgep); const NewCp recipientNewCpRev = newCp(recipientp, donorp, mergeEdgep); const NewCp donorNewCpRev = newCp(donorp, recipientp, mergeEdgep); m_sb.remove(mergeCanp); if (mergeEdgep) { // Remove and free the connecting edge. Must do this before propagating CP's below. mergeEdgep->fromMTaskp()->removeRelativeMTask(mergeEdgep->toMTaskp()); mergeEdgep->fromMTaskp()->removeRelativeEdge(mergeEdgep); mergeEdgep->toMTaskp()->removeRelativeEdge(mergeEdgep); VL_DO_DANGLING(mergeEdgep->unlinkDelete(), mergeEdgep); } else { // Remove the siblingMC mergeSibsp->unlinkA(); mergeSibsp->unlinkB(); VL_DO_DANGLING(delete mergeSibsp, mergeSibsp); } // This also updates cost and stepCost on recipientp recipientp->moveAllVerticesFrom(donorp); UINFO(9, "recipient = " << recipientp->id() << ", donor = " << donorp->id() << ", mergeEdgep = " << mergeEdgep << "\n" << "recipientNewCpFwd = " << recipientNewCpFwd.cp << (recipientNewCpFwd.propagate ? " true " : " false ") << recipientNewCpFwd.propagateCp << "\n" << "donorNewCpFwd = " << donorNewCpFwd.cp << (donorNewCpFwd.propagate ? " true " : " false ") << donorNewCpFwd.propagateCp << endl); recipientp->setCritPathCost(GraphWay::FORWARD, recipientNewCpFwd.cp); if (recipientNewCpFwd.propagate) { m_forwardPropagator.cpHasIncreased(recipientp, recipientNewCpFwd.propagateCp); } recipientp->setCritPathCost(GraphWay::REVERSE, recipientNewCpRev.cp); if (recipientNewCpRev.propagate) { m_reversePropagator.cpHasIncreased(recipientp, recipientNewCpRev.propagateCp); } if (donorNewCpFwd.propagate) { m_forwardPropagator.cpHasIncreased(donorp, donorNewCpFwd.propagateCp); } if (donorNewCpRev.propagate) { m_reversePropagator.cpHasIncreased(donorp, donorNewCpRev.propagateCp); } m_forwardPropagator.go(); m_reversePropagator.go(); // Remove all other SiblingMCs that include recipientp or donorp. We remove all siblingMCs // of recipientp so we do not get huge numbers of SiblingMCs. We'll recreate them below, up // to a bounded number. removeSiblingMCs(recipientp, donorp); // Redirect all edges, delete donorp partRedirectEdgesFrom(m_mTaskGraph, recipientp, donorp, &m_sb); ++m_mergesSinceRescore; // Do an expensive check, confirm we haven't botched the CP // updates. if (m_slowAsserts) partCheckCriticalPaths(m_mTaskGraph); // Finally, make new sibling pairs as needed: // - prereqs and postreqs of recipientp // - prereqs of recipientp's postreqs // - postreqs of recipientp's prereqs // Note that this depends on the updated critical paths (above). siblingPairFromRelatives(recipientp); siblingPairFromRelatives(recipientp); unsigned edges = 0; for (V3GraphEdge& edge : recipientp->outEdges()) { LogicMTask* const postreqp = static_cast(edge.top()); siblingPairFromRelatives(postreqp); ++edges; if (edges >= PART_SIBLING_EDGE_LIMIT) break; } edges = 0; for (V3GraphEdge& edge : recipientp->inEdges()) { LogicMTask* const prereqp = static_cast(edge.fromp()); siblingPairFromRelatives(prereqp); ++edges; if (edges >= PART_SIBLING_EDGE_LIMIT) break; } } void doRescore() { // During rescore, we know that graph isn't changing, so allow // the critPathCost*Without() routines to cache some data in // each LogicMTask. This is just an optimization, things should // behave identically without the caching (just slower) m_sb.rescore(); UINFO(6, "Did rescore. Merges since previous = " << m_mergesSinceRescore << endl); m_mergesSinceRescore = 0; m_scoreLimitBeforeRescore = 0xffffffff; } void makeSiblingMC(LogicMTask* ap, LogicMTask* bp) { if (ap->id() < bp->id()) std::swap(ap, bp); // The higher id vertex owns the association set const auto first = ap->siblings().insert(bp).second; if (first) { m_sb.add(new SiblingMC{ap, bp}); } else if (VL_UNLIKELY(m_slowAsserts)) { // It's fine if we already have this SiblingMC, we may have // created it earlier. Just confirm that we have associated data. bool found = false; for (const SiblingMC& smc : ap->aSiblingMCs()) { UASSERT_OBJ(smc.ap() == ap, ap, "Inconsistent SiblingMC"); UASSERT_OBJ(m_sb.contains(&smc), ap, "Must be on the scoreboard"); if (smc.bp() == bp) found = true; } UASSERT_OBJ(found, ap, "Sibling not found"); } } template void siblingPairFromRelatives(V3GraphVertex* mtaskp) { constexpr GraphWay way{N_Way}; // Need at least 2 edges auto& edges = mtaskp->edges(); if (!edges.hasMultipleElements()) return; std::array neighbors; // This is a hot method, so we want so sort as efficiently as possible. We pre-load // all data (critical path cost and id) required for determining ordering into an aligned // structure. There is not enough space next to these to keep a whole pointer within 16 // bytes, so we store an index into the neighbors buffer instead. We can then compare // and swap these sorting records very efficiently. With this the standard library sorting // functions are efficient enough and using more optimized methods (e.g.: sorting networks) // has no measurable benefit. struct alignas(16) SortingRecord final { uint64_t m_id; uint32_t m_cp; uint8_t m_idx; static_assert(PART_SIBLING_EDGE_LIMIT <= std::numeric_limits::max(), "m_idx must fit all indices into 'neighbors'"); bool operator<(const SortingRecord& that) const { return m_cp < that.m_cp || (m_cp == that.m_cp && m_id < that.m_id); } }; static_assert(sizeof(SortingRecord) <= 16, "How could this be padded to more than 16?"); std::array sortRecs; size_t n = 0; // Populate the buffers for (V3GraphEdge& edge : mtaskp->edges()) { LogicMTask* const otherp = static_cast(edge.furtherp()); neighbors[n] = otherp; sortRecs[n].m_id = otherp->id(); sortRecs[n].m_cp = otherp->critPathCost(way) + otherp->cost(); sortRecs[n].m_idx = n; ++n; // Prevent nodes with huge numbers of edges from massively slowing down us down if (n >= PART_SIBLING_EDGE_LIMIT) break; } // Don't make all possible pairs of siblings when not requested (non-exhaustive). // Just make a few pairs. constexpr size_t MAX_NONEXHAUSTIVE_PAIRS = 3; if (N_Exhaustive || n <= 2 * MAX_NONEXHAUSTIVE_PAIRS) { const size_t end = n & ~static_cast(1); // Round down to even, (we want pairs) std::sort(sortRecs.begin(), sortRecs.begin() + n); for (size_t i = 0; i < end; i += 2) { makeSiblingMC(neighbors[sortRecs[i].m_idx], neighbors[sortRecs[i + 1].m_idx]); } } else { constexpr size_t end = 2 * MAX_NONEXHAUSTIVE_PAIRS; std::partial_sort(sortRecs.begin(), sortRecs.begin() + end, sortRecs.begin() + n); for (size_t i = 0; i < end; i += 2) { makeSiblingMC(neighbors[sortRecs[i].m_idx], neighbors[sortRecs[i + 1].m_idx]); } } } // SELF TESTS // This is a performance test, its intent is to demonstrate that the // partitioner doesn't run on this chain in N^2 time or worse. Overall // runtime should be N*log(N) for a chain-shaped graph. // static void selfTestChain() { const uint64_t usecsSmall = partitionChainUsecs(5); const uint64_t usecsLarge = partitionChainUsecs(500); // Large input is 50x bigger than small input. // Its runtime should be about 10x longer -- not about 2500x longer // or worse which would suggest N^2 scaling or worse. UASSERT(usecsLarge < (usecsSmall * 1500), "selfTestChain() took longer than expected. Small input runtime = " << usecsSmall << ", large input runtime = " << usecsLarge); } static uint64_t partitionChainUsecs(unsigned chain_len) { // NOTE: To get a dot file run with --debugi-Partitioner 4 or more. const uint64_t startUsecs = V3Os::timeUsecs(); V3Graph mTaskGraph; LogicMTask* lastp = nullptr; for (unsigned i = 0; i < chain_len; ++i) { LogicMTask* const mtp = new LogicMTask{&mTaskGraph, nullptr}; mtp->setCost(1); if (lastp) new MTaskEdge{&mTaskGraph, lastp, mtp, 1}; lastp = mtp; } partInitCriticalPaths(mTaskGraph); // Since slowAsserts mode is *expected* to cause N^2 runtime, and the // intent of this test is to demonstrate better-than-N^2 runtime, disable // slowAsserts. Contraction::apply(mTaskGraph, // Any CP limit >chain_len should work: chain_len * 2, nullptr, nullptr, /* slowAsserts: */ false); // All vertices should merge into one UASSERT_SELFTEST(bool, mTaskGraph.vertices().hasSingleElement(), true); const uint64_t endUsecs = V3Os::timeUsecs(); const uint64_t elapsedUsecs = endUsecs - startUsecs; return elapsedUsecs; } // This test defends against a particular failure mode that the // partitioner exhibited during development: // // At one time, the partitioner consistently favored edge-merges over // equal-scoring sibling merges. Every edge and sibling merge in this // test starts out with an equal score. If you only do edge-merges, all // possible merges will continue to have equal score as the center node // grows and grows. Soon the critical path budget is exhausted by a // large center node, and we still have many small leaf nodes -- it's // literally the worst partition possible. // // Now, instead, the partitioner gives slight favoritism to sibling // merges in the event that scores are tied. This is better for the // test and also real designs. static void selfTestX() { // NOTE: To get a dot file run with --debugi-Partitioner 4 or more. V3Graph mTaskGraph; LogicMTask* const centerp = new LogicMTask{&mTaskGraph, nullptr}; centerp->setCost(1); unsigned i; for (i = 0; i < 50; ++i) { LogicMTask* const mtp = new LogicMTask{&mTaskGraph, nullptr}; mtp->setCost(1); // Edge from every input -> centerp new MTaskEdge{&mTaskGraph, mtp, centerp, 1}; } for (i = 0; i < 50; ++i) { LogicMTask* const mtp = new LogicMTask{&mTaskGraph, nullptr}; mtp->setCost(1); // Edge from centerp -> every output new MTaskEdge{&mTaskGraph, centerp, mtp, 1}; } partInitCriticalPaths(mTaskGraph); Contraction::apply(mTaskGraph, 20, nullptr, nullptr, true); const auto report = mTaskGraph.parallelismReport( [](const V3GraphVertex* vtxp) { return vtxp->as()->cost(); }); // Checking exact values here is maybe overly precise. What we're // mostly looking for is a healthy reduction in the number of mTaskGraphp. UASSERT_SELFTEST(uint64_t, report.criticalPathCost(), 19); UASSERT_SELFTEST(uint64_t, report.totalGraphCost(), 101); UASSERT_SELFTEST(uint64_t, report.vertexCount(), 14); UASSERT_SELFTEST(uint64_t, report.edgeCount(), 13); } public: static void selfTest() { selfTestX(); selfTestChain(); } static void apply(V3Graph& mTaskGraph, uint32_t scoreLimit, LogicMTask* entryMTaskp, LogicMTask* exitMTaskp, bool slowAsserts) { Contraction{mTaskGraph, scoreLimit, entryMTaskp, exitMTaskp, slowAsserts}; } }; //###################################################################### // DpiImportCallVisitor // Scan node, indicate whether it contains a call to a DPI imported // routine. class DpiImportCallVisitor final : public VNVisitor { bool m_hasDpiHazard = false; // Found a DPI import call. bool m_tracingCall = false; // Iterating into a CCall to a CFunc // METHODS void visit(AstCFunc* nodep) override { if (!m_tracingCall) return; m_tracingCall = false; if (nodep->dpiImportWrapper()) { if (nodep->dpiPure() ? !v3Global.opt.threadsDpiPure() : !v3Global.opt.threadsDpiUnpure()) { m_hasDpiHazard = true; } } iterateChildren(nodep); } void visit(AstNodeCCall* nodep) override { iterateChildren(nodep); // Enter the function and trace it m_tracingCall = true; iterate(nodep->funcp()); } void visit(AstNode* nodep) override { iterateChildren(nodep); } public: // CONSTRUCTORS explicit DpiImportCallVisitor(AstNode* nodep) { iterate(nodep); } bool hasDpiHazard() const { return m_hasDpiHazard; } ~DpiImportCallVisitor() override = default; private: VL_UNCOPYABLE(DpiImportCallVisitor); }; //###################################################################### // FixDataHazards class FixDataHazards final { // // Fix data hazards in the MTask graph. // // The fine-grained graph from V3Order may contain data hazards which are // not a problem for serial mode, but which would be a problem in parallel // mode. // // There are basically two classes: unordered pairs of writes, and // unordered write-read pairs. We fix both here, with a combination of // MTask-merges and new edges to ensure no such unordered pairs remain. // // ABOUT UNORDERED WRITE-WRITE PAIRS // // The V3Order dependency graph treats these as unordered events: // // a) sig[15:8] = stuff; // ... // b) sig[7:0] = other_stuff; // // Seems OK right? They are writes to disjoint bits of the same // signal. They can run in either order, in serial mode, and the result // will be the same. // // The resulting C code for each of this isn't a pure write, it's // actually an R-M-W sequence: // // a) sig = (sig & 0xff) | (0xff00 & (stuff << 8)); // ... // b) sig = (sig & 0xff00) | (0xff & other_stuff); // // In serial mode, order doesn't matter so long as these run serially. // In parallel mode, we must serialize these RMW's to avoid a race. // // We don't actually check here if each write would involve an R-M-W, we // just assume that it would. If this routine ever causes a drastic // increase in critical path, it could be optimized to make a better // prediction (with all the risk that word implies!) about whether a // given write is likely to turn into an R-M-W. // // ABOUT UNORDERED WRITE-READ PAIRS // // If we don't put unordered write-read pairs into some order at Verilation // time, we risk a runtime race. // // How do such unordered writer/reader pairs happen? Here's a partial list // of scenarios: // // Case 1: Circular logic // // If the design has circular logic, V3Order has by now generated some // dependency cycles, and also cut some of the edges to make it // acyclic. // // For serial mode, that was fine. We can break logic circles at an // arbitrary point. At runtime, we'll repeat the _eval() until no // changes are detected, which papers over the discarded dependency. // // For parallel mode, this situation can lead to unordered reads and // writes of the same variable, causing a data race. For example if the // original code is this: // // assign b = b | a << 2; // assign out = b; // // ... there's originally a dependency edge which records that 'b' // depends on the first assign. V3Order may cut this edge, making the // statements unordered. In serial mode that's fine, they can run in // either order. In parallel mode it's a reader/writer race. // // Case 2: Race Condition in Verilog Sources // // If the input has races, eg. blocking assignments in always blocks // that share variables, the graph at this point will contain unordered // writes and reads (or unordered write-write pairs) reflecting that. // // Case 3: Interesting V3Order Behavior // // There's code in V3Order that explicitly avoids making a dependency // edge from a clock-gater signal to the logic node that produces the // clock signal. This leads to unordered reader/writer pairs in // parallel mode. // // TYPES // Sort LogicMTask objects into deterministic order by calling id() // which is a unique and stable serial number. struct MTaskIdLessThan final { bool operator()(const LogicMTask* lhsp, const LogicMTask* rhsp) const { return lhsp->id() < rhsp->id(); } }; using TasksByRank = std::map>; // MEMBERS V3Graph& m_mTaskGraph; // The Mtask graph // CONSTRUCTORs FixDataHazards(const OrderGraph& orderGraph, V3Graph& mTaskGraph) : m_mTaskGraph{mTaskGraph} { // Rank the graph. DGS is faster than V3GraphAlg's recursive rank, and also allows us to // set up the OrderLogicVertex -> LogicMTask map at the same time. { GraphStreamUnordered serialize{&m_mTaskGraph}; while (LogicMTask* const mtaskp = const_cast(static_cast(serialize.nextp()))) { // Compute and assign rank uint32_t rank = 0; for (V3GraphEdge& edge : mtaskp->inEdges()) { rank = std::max(edge.fromp()->rank() + 1, rank); } mtaskp->rank(rank); // Set up the OrderLogicVertex -> LogicMTask map // Entry and exit MTasks have no MTaskMoveVertices under them, so move on if (mtaskp->vertexList().empty()) continue; // Otherwise there should be only one OrderMoveVertex in each MTask at this stage const OrderMoveVertex::List& vertexList = mtaskp->vertexList(); UASSERT_OBJ(vertexList.hasSingleElement(), mtaskp, "Multiple OrderMoveVertex"); const OrderMoveVertex* const mVtxp = vertexList.frontp(); // Set up mapping back to the MTask from the OrderLogicVertex if (OrderLogicVertex* const lvtxp = mVtxp->logicp()) lvtxp->userp(mtaskp); } } // Gather all variables. SystemC vars will be handled slightly specially, so keep separate. std::vector regularVars; std::vector systemCVars; for (const V3GraphVertex& vtx : orderGraph.vertices()) { // Only consider OrderVarStdVertex which reflects // an actual lvalue assignment; the others do not. if (const OrderVarStdVertex* const vvtxp = vtx.cast()) { if (vvtxp->vscp()->varp()->isSc()) { systemCVars.push_back(vvtxp); } else { regularVars.push_back(vvtxp); } } } // For each OrderVarVertex, look at its writer and reader mTaskGraphp. // // If there's a set of writers and readers at the same rank, we // know these are unordered with respect to one another, so merge // those mTaskGraphp all together. // // At this point, we have at most one merged mtask per rank (for a // given OVV.) Create edges across these remaining mTaskGraphp to ensure // they run in serial order (going along with the existing ranks.) // // NOTE: we don't update the CP's stored in the LogicMTasks to // reflect the changes we make to the graph. That's OK, as we // haven't yet initialized CPs when we call this routine. for (const OrderVarStdVertex* const varVtxp : regularVars) { // Build a set of mTaskGraphp, per rank, which access this var. // Within a rank, sort by MTaskID to avoid nondeterminism. TasksByRank tasksByRank; // Find all reader and writer tasks for this variable, add to // tasksByRank. findAdjacentTasks(varVtxp, tasksByRank); // Merge all writer and reader tasks from same rank together. // // NOTE: Strictly speaking, we don't need to merge all the // readers together. That may lead to extra serialization. The // least amount of ordering we could impose here would be to // merge all writers at a given rank together; then make edges // from the merged writer node to each reader node at the same // rank; and then from each reader node to the merged writer at // the next rank. // // Whereas, merging all readers and writers at the same rank // together is "the simplest thing that could possibly work" // and it seems to. It also creates fairly few edges. We don't // want to create tons of edges here, doing so is not nice to // the main edge contraction pass. mergeSameRankTasks(tasksByRank); } // Handle SystemC vars just a little differently. Instead of // treating each var as an independent entity, and serializing // writes to that one var, we treat ALL systemC vars as a single // entity and serialize writes (and, conservatively, reads) across // all of them. // // Reasoning: writing a systemC var actually turns into a call to a // var.write() method, which under the hood is accessing some data // structure that's shared by many SC vars. It's not thread safe. // // Hopefully we only have a few SC vars -- top level ports, probably. { TasksByRank tasksByRank; for (const OrderVarStdVertex* const varVtxp : systemCVars) { findAdjacentTasks(varVtxp, tasksByRank); } mergeSameRankTasks(tasksByRank); } // Handle nodes containing DPI calls, we want to serialize those // by default unless user gave --threads-dpi-concurrent. // Same basic strategy as above to serialize access to SC vars. if (!v3Global.opt.threadsDpiPure() || !v3Global.opt.threadsDpiUnpure()) { TasksByRank tasksByRank; for (V3GraphVertex& vtx : m_mTaskGraph.vertices()) { LogicMTask& mtask = static_cast(vtx); if (hasDpiHazard(&mtask)) tasksByRank[mtask.rank()].insert(&mtask); } mergeSameRankTasks(tasksByRank); } } // METHODS void findAdjacentTasks(const OrderVarStdVertex* varVtxp, TasksByRank& tasksByRank) { // Find all writer tasks for this variable, group by rank. for (const V3GraphEdge& edge : varVtxp->inEdges()) { if (const auto* const logicVtxp = edge.fromp()->cast()) { LogicMTask* const writerMtaskp = static_cast(logicVtxp->userp()); tasksByRank[writerMtaskp->rank()].insert(writerMtaskp); } } // Not: Find all reader tasks for this variable, group by rank. // There was "broken" code here to find readers, but fixing it to // work properly harmed performance on some tests, see issue #3360. } void mergeSameRankTasks(const TasksByRank& tasksByRank) { LogicMTask* lastRecipientp = nullptr; for (const auto& pair : tasksByRank) { // Find the largest node at this rank, merge into it. (If we // happen to find a huge node, this saves time in // partRedirectEdgesFrom() versus merging into an arbitrary node.) LogicMTask* recipientp = nullptr; for (LogicMTask* const mtaskp : pair.second) { if (!recipientp || (recipientp->cost() < mtaskp->cost())) recipientp = mtaskp; } UASSERT_OBJ(!lastRecipientp || (lastRecipientp->rank() < recipientp->rank()), recipientp, "Merging must be on lower rank"); for (LogicMTask* const donorp : pair.second) { // Merge donor into recipient. if (donorp == recipientp) continue; // Fix up the map, so donor's OLVs map to recipientp for (const OrderMoveVertex& vtx : donorp->vertexList()) { vtx.logicp()->userp(recipientp); } // Move all vertices from donorp to recipientp recipientp->moveAllVerticesFrom(donorp); // Redirect edges from donorp to recipientp, delete donorp partRedirectEdgesFrom(m_mTaskGraph, recipientp, donorp, nullptr); } if (lastRecipientp && !lastRecipientp->hasRelativeMTask(recipientp)) { new MTaskEdge{&m_mTaskGraph, lastRecipientp, recipientp, 1}; } lastRecipientp = recipientp; } } bool hasDpiHazard(LogicMTask* mtaskp) { for (const OrderMoveVertex& mVtx : mtaskp->vertexList()) { if (OrderLogicVertex* const lvtxp = mVtx.logicp()) { // NOTE: We don't handle DPI exports. If testbench code calls a // DPI-exported function at any time during eval() we may have // a data hazard. (Likewise in non-threaded mode if an export // messes with an ordered variable we're broken.) // Find all calls to DPI-imported functions, we can put those // into a serial order at least. That should solve the most // likely DPI-related data hazards. if (DpiImportCallVisitor{lvtxp->nodep()}.hasDpiHazard()) return true; } } return false; } VL_UNCOPYABLE(FixDataHazards); public: static void apply(const OrderGraph& orderGraph, V3Graph& mTaskGraph) { FixDataHazards(orderGraph, mTaskGraph); } }; //###################################################################### // Partitioner implementation // Print debug stats about graphp whose nodes must be LogicMTask's. static void debugMTaskGraphStats(V3Graph& graph, const string& stage) { if (!debug() && !dumpLevel() && !dumpGraphLevel()) return; UINFO(4, "\n"); UINFO(4, " Stats for " << stage << endl); uint32_t mtaskCount = 0; uint32_t totalCost = 0; std::array mtaskCostHist; mtaskCostHist.fill(0); for (const V3GraphVertex& mtask : graph.vertices()) { ++mtaskCount; uint32_t mtaskCost = mtask.as()->cost(); totalCost += mtaskCost; unsigned log2Cost = 0; while (mtaskCost >>= 1) ++log2Cost; UASSERT(log2Cost < 32, "log2Cost overflow in debugMTaskGraphStats"); ++mtaskCostHist[log2Cost]; } UINFO(4, " Total mtask cost = " << totalCost << "\n"); UINFO(4, " Mtask count = " << mtaskCount << "\n"); UINFO(4, " Avg cost / mtask = " << ((mtaskCount > 0) ? cvtToStr(totalCost / mtaskCount) : "INF!") << "\n"); UINFO(4, " Histogram of mtask costs:\n"); for (unsigned i = 0; i < 32; ++i) { if (mtaskCostHist[i]) { UINFO(4, " 2^" << i << ": " << mtaskCostHist[i] << endl); V3Stats::addStat("MTask graph, " + stage + ", mtask cost 2^" + (i < 10 ? " " : "") + cvtToStr(i), mtaskCostHist[i]); } } if (mtaskCount < 1000) { string filePrefix("ordermv_"); filePrefix += stage; if (dumpGraphLevel() >= 4) graph.dumpDotFilePrefixedAlways(filePrefix); } // Look only at the cost of each mtask, neglect communication cost. // This will show us how much parallelism we expect, assuming cache-miss // costs are minor and the cost of running logic is the dominant cost. const auto report = graph.parallelismReport( [](const V3GraphVertex* vtxp) { return vtxp->as()->cost(); }); V3Stats::addStat("MTask graph, " + stage + ", critical path cost", report.criticalPathCost()); V3Stats::addStat("MTask graph, " + stage + ", total graph cost", report.totalGraphCost()); V3Stats::addStat("MTask graph, " + stage + ", mtask count", report.vertexCount()); V3Stats::addStat("MTask graph, " + stage + ", edge count", report.edgeCount()); V3Stats::addStat("MTask graph, " + stage + ", parallelism factor", report.parallelismFactor()); if (debug() >= 4) { UINFO(0, "\n"); UINFO(0, " MTask Parallelism estimate based costs at stage" << stage << ":\n"); UINFO(0, " Critical path cost = " << report.criticalPathCost() << "\n"); UINFO(0, " Total graph cost = " << report.totalGraphCost() << "\n"); UINFO(0, " MTask vertex count = " << report.vertexCount() << "\n"); UINFO(0, " Edge count = " << report.edgeCount() << "\n"); UINFO(0, " Parallelism factor = " << report.parallelismFactor() << "\n"); } } // Print a hash of the shape of graphp. If you are battling // nondeterminism, this can help to pinpoint where in the pipeline it's // creeping in. static void hashGraphDebug(const V3Graph& graph, const char* debugName) { // Disabled when there are no nondeterminism issues in flight. if (!v3Global.opt.debugNondeterminism()) return; std::unordered_map vx2Id; unsigned id = 0; for (const V3GraphVertex& vtx : graph.vertices()) vx2Id[&vtx] = id++; unsigned hash = 0; for (const V3GraphVertex& vtx : graph.vertices()) { for (const V3GraphEdge& edge : vtx.outEdges()) { hash = vx2Id[edge.top()] + 31U * hash; // The K&R hash function } } UINFO(0, "Hash of shape (not contents) of " << debugName << " = " << cvtToStr(hash) << endl); } //************************************************************************* // Partitioner takes the fine-grained logic graph from V3Order and // collapses it into a coarse-grained graph of LogicMTask's, each // of which contains of set of the logic nodes from the fine-grained // graph. class Partitioner final { // MEMBERS OrderMoveGraph& m_moveGraph; // Fine-grained dependency graph std::unique_ptr m_mTaskGraphp{new V3Graph{}}; // The resulting MTask graph LogicMTask* m_entryMTaskp = nullptr; // Singular source vertex of the dependency graph LogicMTask* m_exitMTaskp = nullptr; // Singular sink vertex of the dependency graph // METHODS // Predicate function to determine what OrderMoveVertex to bypass when constructing the MTask // graph. The fine-grained dependency graph of OrderMoveVertex vertices is a bipartite graph // of: // - 1. OrderMoveVertex instances containing logic via OrderLogicVertex // (OrderMoveVertex::logicp() != nullptr) // - 2. OrderMoveVertex instances containing an (OrderVarVertex, domain) pair // Our goal is to order the logic vertices. The second type of variable/domain vertices only // carry dependencies and are eventually discarded. In order to reduce the working set size of // Contraction, we 'bypass' and not create LogicMTask vertices for the variable vertices, // and instead add the transitive dependencies directly, but only if adding the transitive // edges directly does not require more dependency edges than keeping the intermediate vertex. // That is, we bypass a variable vertex if fanIn * fanOut <= fanIn + fanOut. This can only be // true if fanIn or fanOut are 1, or if they are both 2. This can cause significant reduction // in working set size. static bool bypassOk(OrderMoveVertex* mvtxp) { // Need to keep all logic vertices if (mvtxp->logicp()) return false; // Count fan-in, up to 3 unsigned fanIn = 0; auto& inEdges = mvtxp->inEdges(); for (auto it = inEdges.begin(); it != inEdges.end(); ++it) { if (++fanIn == 3) break; } UDEBUGONLY(UASSERT_OBJ(fanIn <= 3, mvtxp, "Should have stopped counting fanIn");); // If fanInn no more than one, bypass if (fanIn <= 1) return true; // Count fan-out, up to 3 unsigned fanOut = 0; auto& outEdges = mvtxp->outEdges(); for (auto it = outEdges.begin(); it != outEdges.end(); ++it) { if (++fanOut == 3) break; } UDEBUGONLY(UASSERT_OBJ(fanOut <= 3, mvtxp, "Should have stopped counting fanOut");); // If fan-out no more than one, bypass if (fanOut <= 1) return true; // They can only be (2, 2), (2, 3), (3, 2), (3, 3) at this point, bypass if (2, 2) return fanIn + fanOut == 4; } uint32_t setupMTaskDeps() VL_MT_DISABLED { uint32_t totalGraphCost = 0; // Artificial single entry point vertex in the MTask graph to allow sibling merges. // This is required as otherwise disjoint sub-graphs could not be merged, but the // coarsening algorithm assumes that the graph is connected. m_entryMTaskp = new LogicMTask{m_mTaskGraphp.get(), nullptr}; // The V3InstrCount within LogicMTask will set user1 on each AST // node, to assert that we never count any node twice. const VNUser1InUse user1inUse; // Create the LogicMTasks for each OrderMoveVertex for (V3GraphVertex& vtx : m_moveGraph.vertices()) { OrderMoveVertex& mVtx = static_cast(vtx); if (bypassOk(&mVtx)) { mVtx.userp(nullptr); // Set to nullptr to mark as bypassed } else { LogicMTask* const mtaskp = new LogicMTask{m_mTaskGraphp.get(), &mVtx}; mVtx.userp(mtaskp); totalGraphCost += mtaskp->cost(); } } // Artificial single exit point vertex in the MTask graph to allow sibling merges. // this enables merging MTasks with no downstream dependents if that is the ideal merge. m_exitMTaskp = new LogicMTask{m_mTaskGraphp.get(), nullptr}; // Create the mtask->mtask dependency edges based on the dependencies between // OrderMoveVertex vertices. for (V3GraphVertex& vtx : m_mTaskGraphp->vertices()) { LogicMTask& mtask = static_cast(vtx); // Entry and exit vertices handled separately if (VL_UNLIKELY((&mtask == m_entryMTaskp) || (&mtask == m_exitMTaskp))) continue; OrderMoveVertex::List& vertexList = mtask.vertexList(); // At this point, there should only be one OrderMoveVertex per LogicMTask UASSERT_OBJ(vertexList.hasSingleElement(), &mtask, "Multiple OrderMoveVertex"); OrderMoveVertex* const mVtxp = vertexList.frontp(); UASSERT_OBJ(mVtxp->userp(), &mtask, "Bypassed OrderMoveVertex should not have MTask"); // Function to add a edge to a dependent from 'mtaskp' const auto addEdge = [this, &mtask](LogicMTask* otherp) { UASSERT_OBJ(otherp != &mtask, &mtask, "Would create a cycle edge"); if (mtask.hasRelativeMTask(otherp)) return; // Don't create redundant edges. new MTaskEdge{m_mTaskGraphp.get(), &mtask, otherp, 1}; }; // Iterate downstream direct dependents for (V3GraphEdge& dEdge : mVtxp->outEdges()) { V3GraphVertex* const top = dEdge.top(); if (LogicMTask* const otherp = static_cast(top->userp())) { // The opposite end of the edge is not a bypassed vertex, add as direct // dependent addEdge(otherp); } else { // The opposite end of the edge is a bypassed vertex, add transitive dependents for (V3GraphEdge& tEdge : top->outEdges()) { LogicMTask* const transp = static_cast(tEdge.top()->userp()); // The Move graph is bipartite (logic <-> var), and logic is never // bypassed, hence 'transp' must be non nullptr. UASSERT_OBJ(transp, mVtxp, "This cannot be a bypassed vertex"); addEdge(transp); } } } } // Create Dependencies to/from the entry/exit vertices. for (V3GraphVertex& vtx : m_mTaskGraphp->vertices()) { LogicMTask& mtask = static_cast(vtx); if (VL_UNLIKELY((&mtask == m_entryMTaskp) || (&mtask == m_exitMTaskp))) continue; // Add the entry/exit edges if (mtask.inEmpty()) new MTaskEdge{m_mTaskGraphp.get(), m_entryMTaskp, &mtask, 1}; if (mtask.outEmpty()) new MTaskEdge{m_mTaskGraphp.get(), &mtask, m_exitMTaskp, 1}; } return totalGraphCost; } // CONSTRUCTORS Partitioner(const OrderGraph& orderGraph, OrderMoveGraph& moveGraph) : m_moveGraph{moveGraph} { // Fill in the m_mTaskGraphp with LogicMTask's and their interdependencies. // Called by V3Order hashGraphDebug(m_moveGraph, "v3partition initial fine-grained deps"); // Create the first MTasks. Initially, each MTask just wraps one // OrderMoveVertex. Over time, we'll merge MTasks together and // eventually each MTask will wrap a large number of MTaskMoveVertices // (and the logic nodes therein.) const uint32_t totalGraphCost = setupMTaskDeps(); debugMTaskGraphStats(*m_mTaskGraphp, "initial"); // For debug: print out the longest critical path. This allows us to // verify that the costs look reasonable, that we aren't combining // nodes that should probably be split, etc. if (dumpLevel() >= 3) LogicMTask::dumpCpFilePrefixed(*m_mTaskGraphp, "cp"); // Merge nodes that could present data hazards; see comment within. FixDataHazards::apply(orderGraph, *m_mTaskGraphp); debugMTaskGraphStats(*m_mTaskGraphp, "hazards"); hashGraphDebug(*m_mTaskGraphp, "mTaskGraphpp after fixDataHazards()"); // Setup the critical path into and out of each node. partInitCriticalPaths(*m_mTaskGraphp); hashGraphDebug(*m_mTaskGraphp, "after partInitCriticalPaths()"); // Order the graph. We know it's already ranked from fixDataHazards() // so we don't need to rank it again. // // On at least some models, ordering the graph here seems to help // performance. (Why? Is it just triggering noise in a lucky direction? // Is it just as likely to harm results?) // // More diversity of models that can build with --threads will // eventually tell us. For now keep the order() so we don't forget // about it, in case it actually helps. TODO: get more data and maybe // remove this later if it doesn't really help. m_mTaskGraphp->orderPreRanked(); // Merge MTask nodes together, repeatedly, until the CP budget is // reached. Coarsens the graph, usually by several orders of // magnitude. // // Some tests disable this, hence the test on threadsCoarsen(). // Coarsening is always enabled in production. if (v3Global.opt.threadsCoarsen()) { const int targetParFactor = v3Global.opt.threads(); UASSERT(targetParFactor >= 2, "Should not reach Partitioner when --threads <= 1"); // Set cpLimit to roughly totalGraphCost / nThreads // // Actually set it a bit lower, by a hardcoded fudge factor. This // results in more smaller mTaskGraphp, which helps reduce fragmentation // when scheduling them. const unsigned fudgeNumerator = 3; const unsigned fudgeDenominator = 5; const uint32_t cpLimit = ((totalGraphCost * fudgeNumerator) / (targetParFactor * fudgeDenominator)); UINFO(4, "Partitioner set cpLimit = " << cpLimit << endl); Contraction::apply(*m_mTaskGraphp, cpLimit, m_entryMTaskp, m_exitMTaskp, // --debugPartition is used by tests // to enable slow assertions. v3Global.opt.debugPartition()); debugMTaskGraphStats(*m_mTaskGraphp, "contraction"); } m_mTaskGraphp->removeTransitiveEdges(); debugMTaskGraphStats(*m_mTaskGraphp, "transitive1"); // Remove MTasks that have no logic in it rerouting the edges. Set user to indicate the // mtask on every underlying OrderMoveVertex. Clear vertex lists (used later). m_moveGraph.userClearVertices(); for (V3GraphVertex* const vtxp : m_mTaskGraphp->vertices().unlinkable()) { LogicMTask* const mtaskp = vtxp->as(); OrderMoveVertex::List& vertexList = mtaskp->vertexList(); // Check if MTask is empty bool empty = true; for (OrderMoveVertex& mVtx : vertexList) { if (mVtx.logicp()) { empty = false; break; } } // If empty remove it now if (empty) { mtaskp->rerouteEdges(m_mTaskGraphp.get()); VL_DO_DANGLING(mtaskp->unlinkDelete(m_mTaskGraphp.get()), mtaskp); continue; } // Annotate the underlying OrderMoveVertex vertices and unlink them while (OrderMoveVertex* const mVtxp = vertexList.unlinkFront()) mVtxp->userp(mtaskp); } m_mTaskGraphp->removeRedundantEdgesSum(&V3GraphEdge::followAlwaysTrue); } ~Partitioner() = default; VL_UNCOPYABLE(Partitioner); VL_UNMOVABLE(Partitioner); public: static std::unique_ptr apply(const OrderGraph& orderGraph, OrderMoveGraph& moveGraph) { return std::move(Partitioner{orderGraph, moveGraph}.m_mTaskGraphp); } }; // Sort LogicMTask vertices by their serial IDs. struct MTaskVxIdLessThan final { bool operator()(const V3GraphVertex* lhsp, const V3GraphVertex* rhsp) const { return lhsp->as()->id() < rhsp->as()->id(); } }; AstExecGraph* V3Order::createParallel(OrderGraph& orderGraph, const std::string& tag, const TrigToSenMap& trigToSen, bool slow) { UINFO(2, " Constructing parallel code for '" + tag + "'"); // For nondeterminism debug: hashGraphDebug(orderGraph, "V3OrderParallel's input OrderGraph"); // Build the move graph OrderMoveDomScope::clear(); const std::unique_ptr moveGraphp = OrderMoveGraph::build(orderGraph, trigToSen); if (dumpGraphLevel() >= 9) moveGraphp->dumpDotFilePrefixed(tag + "_ordermv"); // Partition moveGraphp into LogicMTask's. The partitioner will set userp() on each logic // vertex in the moveGraphp to the MTask it belongs to. const std::unique_ptr mTaskGraphp = Partitioner::apply(orderGraph, *moveGraphp); if (dumpGraphLevel() >= 9) moveGraphp->dumpDotFilePrefixed(tag + "_ordermv_mtasks"); // Some variable OrderMoveVertices are not assigned to an MTask. Reroute and delete these. for (V3GraphVertex* const vtxp : moveGraphp->vertices().unlinkable()) { OrderMoveVertex* const mVtxp = vtxp->as(); if (!mVtxp->userp()) { UASSERT_OBJ(!mVtxp->logicp(), mVtxp, "Logic OrderMoveVertex not assigned to mtask"); mVtxp->rerouteEdges(moveGraphp.get()); VL_DO_DANGLING(mVtxp->unlinkDelete(moveGraphp.get()), mVtxp); } } // Remove all edges from the move graph that cross between MTasks. Add logic to MTask lists. for (V3GraphVertex& vtx : moveGraphp->vertices()) { OrderMoveVertex* const mVtxp = vtx.as(); LogicMTask* const mtaskp = static_cast(mVtxp->userp()); // Add to list in MTask, in MoveGraph order. This should not be necessary, but see #4993. mtaskp->vertexList().linkBack(mVtxp); // Remove edges crossing between MTasks for (V3GraphEdge* const edgep : mVtxp->outEdges().unlinkable()) { const OrderMoveVertex* const toMVtxp = edgep->top()->as(); if (mtaskp != toMVtxp->userp()) VL_DO_DANGLING(edgep->unlinkDelete(), edgep); } } if (dumpGraphLevel() >= 9) moveGraphp->dumpDotFilePrefixed(tag + "_ordermv_pruned"); // Create the AstExecGraph node which represents the execution of the MTask graph. FileLine* const rootFlp = v3Global.rootp()->fileline(); AstExecGraph* const execGraphp = new AstExecGraph{rootFlp, tag}; V3Graph* const depGraphp = execGraphp->depGraphp(); // Translate the LogicMTask graph into the corresponding ExecMTask graph, // which will outlive ordering. std::unordered_map logicMTaskToExecMTask; OrderMoveGraphSerializer serializer{*moveGraphp}; V3OrderCFuncEmitter emitter{tag, slow}; GraphStream mtaskStream{mTaskGraphp.get()}; while (const V3GraphVertex* const vtxp = mtaskStream.nextp()) { const LogicMTask* const cMTaskp = vtxp->as(); LogicMTask* const mTaskp = const_cast(cMTaskp); // Add initially ready vertices within this MTask to the serializer as seeds, // and unlink them from the vertex list in the MTask as we go. (The serializer // uses the list links in the vertex, so must unlink it here.) while (OrderMoveVertex* const mVtxp = mTaskp->vertexList().unlinkFront()) { if (mVtxp->inEmpty()) serializer.addSeed(mVtxp); } // Emit all logic within the MTask as they become ready OrderMoveDomScope* prevDomScopep = nullptr; while (OrderMoveVertex* const mVtxp = serializer.getNext()) { // We only really care about logic vertices if (OrderLogicVertex* const logicp = mVtxp->logicp()) { // Force a new function if the domain or scope changed, for better combining. OrderMoveDomScope* const domScopep = &mVtxp->domScope(); if (domScopep != prevDomScopep) emitter.forceNewFunction(); prevDomScopep = domScopep; // Emit the logic under this vertex emitter.emitLogic(logicp); } // Can delete the vertex now VL_DO_DANGLING(mVtxp->unlinkDelete(moveGraphp.get()), mVtxp); } // We have 2 objects, because AstMTaskBody is an AstNode, and ExecMTask is a GraphVertex. // To combine them would involve multiple inheritance. // Construct the actual MTaskBody AstMTaskBody* const bodyp = new AstMTaskBody{rootFlp}; execGraphp->addMTaskBodiesp(bodyp); for (AstActive* const activep : emitter.getAndClearActiveps()) bodyp->addStmtsp(activep); UASSERT_OBJ(bodyp->stmtsp(), bodyp, "Should not try to create empty MTask"); // Create the ExecMTask ExecMTask* const execMTaskp = new ExecMTask{depGraphp, bodyp}; const bool newEntry = logicMTaskToExecMTask.emplace(mTaskp, execMTaskp).second; UASSERT_OBJ(newEntry, mTaskp, "LogicMTasks should be processed in dependencyorder"); UINFO(3, "Final '" << tag << "' LogicMTask " << mTaskp->id() << " maps to ExecMTask" << execMTaskp->id() << std::endl); // Add the dependency edges between ExecMTasks for (const V3GraphEdge& edge : mTaskp->inEdges()) { const V3GraphVertex* fromVxp = edge.fromp(); const LogicMTask* const fromp = fromVxp->as(); new V3GraphEdge{depGraphp, logicMTaskToExecMTask.at(fromp), execMTaskp, 1}; } } // Delete the remaining variable vertices for (V3GraphVertex* const vtxp : moveGraphp->vertices().unlinkable()) { if (!vtxp->as()->logicp()) { VL_DO_DANGLING(vtxp->unlinkDelete(moveGraphp.get()), vtxp); } } UASSERT(moveGraphp->empty(), "Waiting vertices remain, but none are ready"); OrderMoveDomScope::clear(); return execGraphp; } void V3Order::selfTestParallel() { UINFO(2, __FUNCTION__ << ": " << endl); PropagateCp::selfTest(); PropagateCp::selfTest(); Contraction::selfTest(); }