verilator/src/V3OrderParallel.cpp
Geza Lore 2247e1e345
Cleanup/simplify V3OrderParallel (#4959)
No functional change.
2024-03-10 18:15:45 +00:00

2551 lines
111 KiB
C++

// -*- mode: C++; c-file-style: "cc-mode" -*-
//*************************************************************************
// DESCRIPTION: Verilator: Multi-threaded code partitioning and ordering
//
// Code available from: https://verilator.org
//
//*************************************************************************
//
// Copyright 2003-2024 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 "V3File.h"
#include "V3Graph.h"
#include "V3GraphStream.h"
#include "V3InstrCount.h"
#include "V3List.h"
#include "V3OrderCFuncEmitter.h"
#include "V3OrderInternal.h"
#include "V3OrderMoveGraphBuilder.h"
#include "V3Os.h"
#include "V3PairingHeap.h"
#include "V3PartitionGraph.h"
#include "V3Scoreboard.h"
#include "V3Stats.h"
#include <array>
#include <list>
#include <memory>
#include <type_traits>
#include <unordered_map>
#include <unordered_set>
#include <vector>
VL_DEFINE_DEBUG_FUNCTIONS;
class MTaskEdge;
class MergeCandidate;
class SiblingMC;
// Similar to OrderMoveVertex, but modified for threaded code generation.
class MTaskMoveVertex final : public V3GraphVertex {
VL_RTTI_IMPL(MTaskMoveVertex, V3GraphVertex)
OrderLogicVertex* const m_logicp; // Logic represented by this vertex, or nullptr if variable
const AstSenTree* const m_domainp;
public:
MTaskMoveVertex(V3Graph& graph, OrderLogicVertex* logicp,
const AstSenTree* domainp) VL_MT_DISABLED : V3GraphVertex{&graph},
m_logicp{logicp},
m_domainp{domainp} {}
~MTaskMoveVertex() override = default;
// ACCESSORS
OrderLogicVertex* logicp() const { return m_logicp; }
const AstScope* scopep() const { return m_logicp ? m_logicp->scopep() : nullptr; }
const AstSenTree* domainp() const { return m_domainp; }
string dotColor() const override { return logicp() ? logicp()->dotColor() : "yellow"; }
string name() const override {
std::string nm;
if (!logicp()) {
nm = "var";
} else {
nm = logicp()->name() + "\\n";
nm += "MV:";
nm += +" d=" + cvtToHex(logicp()->domainp());
nm += +" s=" + cvtToHex(logicp()->scopep());
}
nm += "\nt=" + std::to_string(color()); // "color()" represents the mtask ID.
return nm;
}
};
// ######################################################################
// 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<EdgeKey>;
//=============================================================================
// LogicMTask
class LogicMTask final : public V3GraphVertex {
VL_RTTI_IMPL(LogicMTask, V3GraphVertex)
template <GraphWay::en T_Way>
friend class PropagateCp;
public:
// TYPES
using VxList = std::list<MTaskMoveVertex*>;
struct CmpLogicMTask final {
bool operator()(const LogicMTask* ap, const LogicMTask* bp) const {
return ap->id() < bp->id();
}
};
private:
// MEMBERS
// Set of MTaskMoveVertex's assigned to this mtask. LogicMTask does not
// own the MTaskMoveVertex objects, we merely keep pointers to them
// here.
VxList 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<uint32_t, GraphWay::NUM_WAYS> m_critPathCost;
uint32_t m_serialId; // Unique MTask ID number
// 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<LogicMTask*> m_edgeSet;
// Store the outgoing and incoming edges in a heap sorted by the critical path length
std::array<EdgeHeap, GraphWay::NUM_WAYS> m_edgeHeap;
// MTasks for which a SiblingMC exists with 'this' as the higher ID MTask (m_ap in SiblingMC)
std::set<LogicMTask*> m_siblings;
// List of SiblingMCs for which this is the higher ID MTask (m_ap in SiblingMC)
V3List<SiblingMC*> m_aSiblingMCs;
// List of SiblingMCs for which this is the lower ID MTask (m_bp in SiblingMC)
V3List<SiblingMC*> m_bSiblingMCs;
public:
// CONSTRUCTORS
LogicMTask(V3Graph* graphp, MTaskMoveVertex* mtmvVxp)
: V3GraphVertex{graphp} {
for (uint32_t& item : m_critPathCost) item = 0;
if (mtmvVxp) { // Else null for test
m_mvertices.push_back(mtmvVxp);
if (const OrderLogicVertex* const olvp = mtmvVxp->logicp()) {
m_cost += V3InstrCount::count(olvp->nodep(), true);
}
}
// Start at 1, so that 0 indicates no mtask ID.
static uint32_t s_nextId = 1;
m_serialId = s_nextId++;
UASSERT(s_nextId < 0xFFFFFFFFUL, "Too many mTaskGraphp");
}
// METHODS
std::set<LogicMTask*>& siblings() { return m_siblings; };
V3List<SiblingMC*>& aSiblingMCs() { return m_aSiblingMCs; };
V3List<SiblingMC*>& bSiblingMCs() { return m_bSiblingMCs; };
void moveAllVerticesFrom(LogicMTask* otherp) {
// splice() is constant time
m_mvertices.splice(m_mvertices.end(), otherp->m_mvertices);
m_cost += otherp->m_cost;
}
const VxList& vertexList() const { return m_mvertices; }
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_serialId; }
void id(uint32_t id) { m_serialId = 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<uint32_t>(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 <GraphWay::en T_Way>
void addRelativeEdge(MTaskEdge* edgep);
template <GraphWay::en T_Way>
void stealRelativeEdge(MTaskEdge* edgep);
template <GraphWay::en T_Way>
void removeRelativeEdge(MTaskEdge* edgep);
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); }
void checkRelativesCp(GraphWay way) const;
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_serialId << "." << 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]; }
uint32_t critPathCostWithout(GraphWay way, const V3GraphEdge* withoutp) const;
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* followp = fromp->outBeginp(); followp;
followp = followp->outNextp()) {
if (followp == excludedEdgep) continue;
LogicMTask* const nextp = static_cast<LogicMTask*>(followp->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);
private:
VL_UNCOPYABLE(LogicMTask);
};
//######################################################################
// 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<MergeCandidate, MergeCandidateKey>;
// 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<MergeCandidate*>(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;
V3ListEnt<SiblingMC*> m_aEnt; // List entry for m_ap->aSiblingMCs()
V3ListEnt<SiblingMC*> m_bEnt; // List entry for m_bp->bSiblingMCs()
public:
// CONSTRUCTORS
SiblingMC() = delete;
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_aEnt.pushBack(m_ap->aSiblingMCs(), this);
m_bEnt.pushBack(m_bp->bSiblingMCs(), this);
}
~SiblingMC() = default;
// METHODS
SiblingMC* aNextp() const { return m_aEnt.nextp(); }
SiblingMC* bNextp() const { return m_bEnt.nextp(); }
void 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_aEnt.unlink(m_ap->aSiblingMCs(), this);
}
void unlinkB() { m_bEnt.unlink(m_bp->bSiblingMCs(), this); }
LogicMTask* ap() const { return m_ap; }
LogicMTask* bp() const { return m_bp; }
bool mergeWouldCreateCycle() const {
return (LogicMTask::pathExistsFrom(m_ap, m_bp, nullptr)
|| LogicMTask::pathExistsFrom(m_bp, m_ap, nullptr));
}
};
static_assert(!std::is_polymorphic<SiblingMC>::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 <GraphWay::en T_Way>
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<EdgeHeap::Node, GraphWay::NUM_WAYS> m_edgeHeapNode;
public:
// CONSTRUCTORS
MTaskEdge(V3Graph* graphp, LogicMTask* fromp, LogicMTask* top, int weight)
: V3GraphEdge{graphp, fromp, top, weight}
, MergeCandidate{/* isSiblingMC: */ false} {
fromp->addRelativeMTask(top);
fromp->addRelativeEdge<GraphWay::FORWARD>(this);
top->addRelativeEdge<GraphWay::REVERSE>(this);
}
// METHODS
LogicMTask* furtherMTaskp(GraphWay way) const {
return static_cast<LogicMTask*>(this->furtherp(way));
}
LogicMTask* fromMTaskp() const { return static_cast<LogicMTask*>(fromp()); }
LogicMTask* toMTaskp() const { return static_cast<LogicMTask*>(top()); }
bool 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 resetCriticalPaths() {
LogicMTask* const fromp = fromMTaskp();
LogicMTask* const top = toMTaskp();
fromp->removeRelativeEdge<GraphWay::FORWARD>(this);
top->removeRelativeEdge<GraphWay::REVERSE>(this);
fromp->addRelativeEdge<GraphWay::FORWARD>(this);
top->addRelativeEdge<GraphWay::REVERSE>(this);
}
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<const MTaskEdge*>(reinterpret_cast<uintptr_t>(nodep) - offset);
}
private:
VL_UNCOPYABLE(MTaskEdge);
};
template <GraphWay::en T_Way>
void LogicMTask::addRelativeEdge(MTaskEdge* edgep) {
constexpr GraphWay way{T_Way};
constexpr GraphWay inv = way.invert();
// Add to the edge heap
LogicMTask* const relativep = edgep->furtherMTaskp(way);
// 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 <GraphWay::en T_Way>
void LogicMTask::stealRelativeEdge(MTaskEdge* edgep) {
constexpr GraphWay way{T_Way};
// Make heap node insertable, ruining the heap it is currently in.
edgep->m_edgeHeapNode[way].yank();
// Add the edge as new
addRelativeEdge<T_Way>(edgep);
}
template <GraphWay::en T_Way>
void LogicMTask::removeRelativeEdge(MTaskEdge* edgep) {
constexpr GraphWay way{T_Way};
// Remove from the edge heap
m_edgeHeap[way].remove(&edgep->m_edgeHeapNode[way]);
}
void LogicMTask::checkRelativesCp(GraphWay way) const {
for (V3GraphEdge* edgep = beginp(way); edgep; edgep = edgep->nextp(way)) {
const LogicMTask* const relativep = static_cast<const LogicMTask*>(edgep->furtherp(way));
const uint32_t cachedCp = static_cast<MTaskEdge*>(edgep)->cachedCp(way);
const uint32_t cp = relativep->critPathCost(way.invert()) + relativep->stepCost();
partCheckCachedScoreVsActual(cachedCp, cp);
}
}
uint32_t LogicMTask::critPathCostWithout(GraphWay way, const V3GraphEdge* withoutp) const {
// 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(way) == this,
"In critPathCostWithout(), edge 'withoutp' must further to 'this'"););
const GraphWay inv = way.invert();
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;
}
void LogicMTask::dumpCpFilePrefixed(const V3Graph& graph, const string& nameComment) {
const string filename = v3Global.debugFilename(nameComment) + ".txt";
UINFO(1, "Writing " << filename << endl);
const std::unique_ptr<std::ofstream> 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
LogicMTask* startp = nullptr;
for (V3GraphVertex* vxp = graph.verticesBeginp(); vxp; vxp = vxp->verticesNextp()) {
LogicMTask* const mtaskp = static_cast<LogicMTask*>(vxp);
if (!startp) {
startp = mtaskp;
continue;
}
if (mtaskp->cost() + mtaskp->critPathCost(GraphWay::REVERSE)
> startp->cost() + startp->critPathCost(GraphWay::REVERSE)) {
startp = mtaskp;
}
}
// Follow the entire critical path
std::vector<const LogicMTask*> path;
uint32_t totalCost = 0;
for (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 (MTaskMoveVertex* const mVtxp : mtaskp->vertexList()) {
const OrderLogicVertex* const logicp = mVtxp->logicp();
if (!logicp) continue;
// Show nodes with hierarchical costs
V3InstrCount::count(logicp->nodep(), false, osp);
}
}
}
// Instead of dynamic cast
SiblingMC* MergeCandidate::toSiblingMC() {
return isSiblingMC() ? static_cast<SiblingMC*>(this) : nullptr;
}
MTaskEdge* MergeCandidate::toMTaskEdge() {
return isSiblingMC() ? nullptr : static_cast<MTaskEdge*>(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<const SiblingMC*>(this)->mergeWouldCreateCycle()
: static_cast<const MTaskEdge*>(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(GraphWay::FORWARD, edgep));
const uint32_t mergedCpCostRev = std::max(fromp->critPathCostWithout(GraphWay::REVERSE, 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<const MTaskEdge*>(this));
}
}
//######################################################################
// Look at vertex costs (in one way) to form critical paths for each
// vertex.
static void partInitHalfCriticalPaths(GraphWay way, V3Graph& mTaskGraph, bool checkOnly) {
GraphStreamUnordered order{&mTaskGraph, way};
const GraphWay rev = way.invert();
for (const V3GraphVertex* vertexp; (vertexp = order.nextp());) {
const LogicMTask* const mtaskcp = static_cast<const LogicMTask*>(vertexp);
LogicMTask* const mtaskp = const_cast<LogicMTask*>(mtaskcp);
uint32_t cpCost = 0;
#if VL_DEBUG
std::unordered_set<V3GraphVertex*> relatives;
#endif
for (V3GraphEdge* edgep = vertexp->beginp(rev); edgep; edgep = edgep->nextp(rev)) {
#if VL_DEBUG
// Run a few asserts on the initial mtask graph,
// while we're iterating through...
UASSERT_OBJ(edgep->weight() != 0, mtaskp,
"Should be no cut edges in mTaskGraphp graph");
UASSERT_OBJ(relatives.find(edgep->furtherp(rev)) == relatives.end(), mtaskp,
"Should be no redundant edges in mTaskGraphp graph");
relatives.insert(edgep->furtherp(rev));
#endif
const LogicMTask* const relativep = static_cast<LogicMTask*>(edgep->furtherp(rev));
cpCost = std::max(cpCost, (relativep->critPathCost(way)
+ static_cast<uint32_t>(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(GraphWay::FORWARD, mTaskGraph, false);
partInitHalfCriticalPaths(GraphWay::REVERSE, 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* vxp = mTaskGraph.verticesBeginp(); vxp; vxp = vxp->verticesNextp()) {
for (V3GraphEdge* edgep = vxp->outBeginp(); edgep; edgep = edgep->outNextp()) {
MTaskEdge* const mtedgep = edgep->as<MTaskEdge>();
mtedgep->resetCriticalPaths();
}
}
}
// Do an EXPENSIVE check to make sure that all incremental CP updates have
// gone correctly.
static void partCheckCriticalPaths(V3Graph& mTaskGraph) {
partInitHalfCriticalPaths(GraphWay::FORWARD, mTaskGraph, true);
partInitHalfCriticalPaths(GraphWay::REVERSE, mTaskGraph, true);
for (V3GraphVertex* vxp = mTaskGraph.verticesBeginp(); vxp; vxp = vxp->verticesNextp()) {
const LogicMTask* const mtaskp = static_cast<LogicMTask*>(vxp);
mtaskp->checkRelativesCp(GraphWay::FORWARD);
mtaskp->checkRelativesCp(GraphWay::REVERSE);
}
}
// ######################################################################
// PropagateCp
template <GraphWay::en T_Way>
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<PendingKey>;
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<std::unique_ptr<PendingHeapNode[]>> 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<LogicMTask*> 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{T_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 (MTaskEdge *edgep = static_cast<MTaskEdge*>(vxp->beginp(way)), *nextp; edgep;
edgep = nextp) {
// Fetch early as likely cache miss
nextp = static_cast<MTaskEdge*>(edgep->nextp(way));
LogicMTask* const relativep = edgep->furtherMTaskp(way);
EdgeHeap::Node& edgeHeapNode = edgep->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<PendingHeapNode*>(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{T_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<LogicMTask*, 50> vx; // All vertices within the graph
// Generate a pseudo-random graph
std::array<uint64_t, 2> 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<T_Way> 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->inBeginp()) 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
MTaskEdge* outNextp = static_cast<MTaskEdge*>(donorp->outBeginp());
while (outNextp) {
MTaskEdge* const edgep = outNextp;
LogicMTask* const relativep = outNextp->toMTaskp();
outNextp = static_cast<MTaskEdge*>(outNextp->outNextp());
relativep->removeRelativeEdge<GraphWay::REVERSE>(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<MTaskEdge*>(
recipientp->findConnectingEdgep(GraphWay::FORWARD, 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<GraphWay::FORWARD>(edgep);
relativep->addRelativeEdge<GraphWay::REVERSE>(edgep);
if (sbp) {
if (!sbp->contains(edgep)) {
sbp->add(edgep);
} else {
sbp->hintScoreChanged(edgep);
}
}
}
}
// Process incoming edges
MTaskEdge* inNextp = static_cast<MTaskEdge*>(donorp->inBeginp());
while (inNextp) {
MTaskEdge* const edgep = inNextp;
LogicMTask* const relativep = inNextp->fromMTaskp();
inNextp = static_cast<MTaskEdge*>(inNextp->inNextp());
relativep->removeRelativeMTask(donorp);
relativep->removeRelativeEdge<GraphWay::FORWARD>(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<MTaskEdge*>(
recipientp->findConnectingEdgep(GraphWay::REVERSE, 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<GraphWay::FORWARD>(edgep);
recipientp->stealRelativeEdge<GraphWay::REVERSE>(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<GraphWay::FORWARD> m_forwardPropagator{m_slowAsserts}; // Forward propagator
PropagateCp<GraphWay::REVERSE> 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* itp = m_mTaskGraph.verticesBeginp(); itp;
itp = itp->verticesNextp()) {
std::unordered_set<const V3GraphVertex*> neighbors;
for (V3GraphEdge* edgep = itp->outBeginp(); edgep; edgep = edgep->outNextp()) {
const bool first = neighbors.insert(edgep->top()).second;
UASSERT_OBJ(first, itp, "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* itp = m_mTaskGraph.verticesBeginp(); itp; itp = itp->verticesNextp()) {
itp->userp(nullptr); // Reset user value while we are here. Used by PropagateCp.
for (V3GraphEdge* edgep = itp->outBeginp(); edgep; edgep = edgep->outNextp()) {
m_sb.add(static_cast<MTaskEdge*>(edgep));
}
siblingPairFromRelatives<GraphWay::REVERSE, true>(itp);
siblingPairFromRelatives<GraphWay::FORWARD, true>(itp);
}
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...
unsigned mtaskCount = 0;
for (V3GraphVertex* vxp = m_mTaskGraph.verticesBeginp(); vxp;
vxp = vxp->verticesNextp()) {
++mtaskCount;
}
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();
delete 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);
}
}
private:
template <GraphWay::en T_Way>
NewCp newCp(LogicMTask* mtaskp, LogicMTask* otherp, MTaskEdge* mergeEdgep) {
constexpr GraphWay way{T_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(way)) {
newCp = std::max(otherp->critPathCost(way),
mtaskp->critPathCostWithout(way, mergeEdgep));
} else {
newCp = std::max(mtaskp->critPathCost(way),
otherp->critPathCostWithout(way, 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) {
for (SiblingMC *smcp = mtaskp->aSiblingMCs().begin(), *nextp; // lintok-begin-on-ref
smcp; smcp = nextp) {
nextp = smcp->aNextp();
m_sb.remove(smcp);
smcp->unlinkB();
delete smcp;
}
for (SiblingMC *smcp = mtaskp->bSiblingMCs().begin(), *nextp; // lintok-begin-on-ref
smcp; smcp = nextp) {
nextp = smcp->bNextp();
m_sb.remove(smcp);
smcp->unlinkA();
delete 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();
recipientp->aSiblingMCs().reset();
recipientp->bSiblingMCs().reset();
}
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<GraphWay::FORWARD>(recipientp, donorp, mergeEdgep);
const NewCp donorNewCpFwd = newCp<GraphWay::FORWARD>(donorp, recipientp, mergeEdgep);
const NewCp recipientNewCpRev = newCp<GraphWay::REVERSE>(recipientp, donorp, mergeEdgep);
const NewCp donorNewCpRev = newCp<GraphWay::REVERSE>(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<GraphWay::FORWARD>(mergeEdgep);
mergeEdgep->toMTaskp()->removeRelativeEdge<GraphWay::REVERSE>(mergeEdgep);
VL_DO_DANGLING(mergeEdgep->unlinkDelete(), mergeEdgep);
} else {
// Remove the siblingMC
mergeSibsp->unlinkA();
mergeSibsp->unlinkB();
VL_DO_DANGLING(delete mergeEdgep, mergeEdgep);
}
// 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<GraphWay::REVERSE, true>(recipientp);
siblingPairFromRelatives<GraphWay::FORWARD, true>(recipientp);
unsigned edges = 0;
for (V3GraphEdge* edgep = recipientp->outBeginp(); edgep; edgep = edgep->outNextp()) {
LogicMTask* const postreqp = static_cast<LogicMTask*>(edgep->top());
siblingPairFromRelatives<GraphWay::REVERSE, false>(postreqp);
++edges;
if (edges >= PART_SIBLING_EDGE_LIMIT) break;
}
edges = 0;
for (V3GraphEdge* edgep = recipientp->inBeginp(); edgep; edgep = edgep->inNextp()) {
LogicMTask* const prereqp = static_cast<LogicMTask*>(edgep->fromp());
siblingPairFromRelatives<GraphWay::FORWARD, false>(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* smcp = ap->aSiblingMCs().begin(); // lintok-begin-on-ref
smcp; smcp = smcp->aNextp()) {
UASSERT_OBJ(smcp->ap() == ap, ap, "Inconsistent SiblingMC");
UASSERT_OBJ(m_sb.contains(smcp), ap, "Must be on the scoreboard");
if (smcp->bp() == bp) found = true;
}
UASSERT_OBJ(found, ap, "Sibling not found");
}
}
template <GraphWay::en T_Way, bool Exhaustive>
void siblingPairFromRelatives(V3GraphVertex* mtaskp) {
constexpr GraphWay way{T_Way};
// Need at least 2 edges
if (!mtaskp->beginp(way) || !mtaskp->beginp(way)->nextp(way)) return;
std::array<LogicMTask*, PART_SIBLING_EDGE_LIMIT> 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<uint8_t>::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<SortingRecord, PART_SIBLING_EDGE_LIMIT> sortRecs;
size_t n = 0;
// Populate the buffers
for (V3GraphEdge *edgep = mtaskp->beginp(way), *nextp; edgep; edgep = nextp) {
nextp = edgep->nextp(way); // Fetch next first as likely cache miss
LogicMTask* const otherp = static_cast<LogicMTask*>(edgep->furtherp(way));
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 (Exhaustive || n <= 2 * MAX_NONEXHAUSTIVE_PAIRS) {
const size_t end = n & ~static_cast<size_t>(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.verticesBeginp() && !mTaskGraph.verticesBeginp()->verticesNextp(),
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<const LogicMTask>()->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(uint32_t, report.criticalPathCost(), 19);
UASSERT_SELFTEST(uint32_t, report.totalGraphCost(), 101);
UASSERT_SELFTEST(uint32_t, report.vertexCount(), 14);
UASSERT_SELFTEST(uint32_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<uint32_t /*rank*/, std::set<LogicMTask*, MTaskIdLessThan>>;
// 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<LogicMTask*>(static_cast<const LogicMTask*>(serialize.nextp()))) {
// Compute and assign rank
uint32_t rank = 0;
for (V3GraphEdge* edgep = mtaskp->inBeginp(); edgep; edgep = edgep->inNextp()) {
rank = std::max(edgep->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 MTaskMoveVertex in each MTask at this stage
UASSERT_OBJ(mtaskp->vertexList().size() == 1, mtaskp, "Multiple MTaskMoveVertex");
const MTaskMoveVertex* const moveVtxp = mtaskp->vertexList().front();
// Set up mapping back to the MTask from the OrderLogicVertex
if (OrderLogicVertex* const lvtxp = moveVtxp->logicp()) lvtxp->userp(mtaskp);
}
}
// Gather all variables. SystemC vars will be handled slightly specially, so keep separate.
std::vector<const OrderVarStdVertex*> regularVars;
std::vector<const OrderVarStdVertex*> systemCVars;
for (V3GraphVertex *vtxp = orderGraph.verticesBeginp(), *nextp; vtxp; vtxp = nextp) {
nextp = vtxp->verticesNextp();
// Only consider OrderVarStdVertex which reflects
// an actual lvalue assignment; the others do not.
if (const OrderVarStdVertex* const vvtxp = vtxp->cast<OrderVarStdVertex>()) {
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 *vtxp = m_mTaskGraph.verticesBeginp(), *nextp; vtxp; vtxp = nextp) {
nextp = vtxp->verticesNextp();
LogicMTask* const mtaskp = static_cast<LogicMTask*>(vtxp);
if (hasDpiHazard(mtaskp)) tasksByRank[mtaskp->rank()].insert(mtaskp);
}
mergeSameRankTasks(tasksByRank);
}
}
// METHODS
void findAdjacentTasks(const OrderVarStdVertex* varVtxp, TasksByRank& tasksByRank) {
// Find all writer tasks for this variable, group by rank.
for (V3GraphEdge* edgep = varVtxp->inBeginp(); edgep; edgep = edgep->inNextp()) {
if (const auto* const logicVtxp = edgep->fromp()->cast<OrderLogicVertex>()) {
LogicMTask* const writerMtaskp = static_cast<LogicMTask*>(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 MTaskMoveVertex* const tmvp : donorp->vertexList()) {
tmvp->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 MTaskMoveVertex* const moveVtxp : mtaskp->vertexList()) {
if (OrderLogicVertex* const lvtxp = moveVtxp->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(const 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<uint32_t, 32> mtaskCostHist;
mtaskCostHist.fill(0);
for (const V3GraphVertex* mtaskp = graph.verticesBeginp(); mtaskp;
mtaskp = mtaskp->verticesNextp()) {
++mtaskCount;
uint32_t mtaskCost = mtaskp->as<const LogicMTask>()->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<const LogicMTask>()->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<const V3GraphVertex*, uint32_t> vx2Id;
unsigned id = 0;
for (const V3GraphVertex* vxp = graph.verticesBeginp(); vxp; vxp = vxp->verticesNextp()) {
vx2Id[vxp] = id++;
}
unsigned hash = 0;
for (const V3GraphVertex* vxp = graph.verticesBeginp(); vxp; vxp = vxp->verticesNextp()) {
for (const V3GraphEdge* edgep = vxp->outBeginp(); edgep; edgep = edgep->outNextp()) {
const V3GraphVertex* const top = edgep->top();
hash = vx2Id[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
const V3Graph& m_fineDepsGraph; // Fine-grained dependency graph
std::unique_ptr<V3Graph> 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 MTaskMoveVertex to bypass when constructing the MTask
// graph. The fine-grained dependency graph of MTaskMoveVertex vertices is a bipartite graph
// of:
// - 1. MTaskMoveVertex instances containing logic via OrderLogicVertex
// (MTaskMoveVertex::logicp() != nullptr)
// - 2. MTaskMoveVertex 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(MTaskMoveVertex* mvtxp) {
// Need to keep all logic vertices
if (mvtxp->logicp()) return false;
// Count fan-in, up to 3
unsigned fanIn = 0;
for (V3GraphEdge* edgep = mvtxp->inBeginp(); edgep; edgep = edgep->inNextp()) {
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;
for (V3GraphEdge* edgep = mvtxp->outBeginp(); edgep; edgep = edgep->outNextp()) {
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 MTaskMoveVertex
for (V3GraphVertex *vtxp = m_fineDepsGraph.verticesBeginp(), *nextp; vtxp; vtxp = nextp) {
nextp = vtxp->verticesNextp();
MTaskMoveVertex* const mVtxp = static_cast<MTaskMoveVertex*>(vtxp);
if (bypassOk(mVtxp)) {
mVtxp->userp(nullptr); // Set to nullptr to mark as bypassed
} else {
LogicMTask* const mtaskp = new LogicMTask{m_mTaskGraphp.get(), mVtxp};
mVtxp->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
// MTaskMoveVertex vertices.
for (V3GraphVertex *vtxp = m_mTaskGraphp->verticesBeginp(), *nextp; vtxp; vtxp = nextp) {
nextp = vtxp->verticesNextp();
LogicMTask* const mtaskp = static_cast<LogicMTask*>(vtxp);
// Entry and exit vertices handled separately
if (VL_UNLIKELY((mtaskp == m_entryMTaskp) || (mtaskp == m_exitMTaskp))) continue;
// At this point, there should only be one MTaskMoveVertex per LogicMTask
UASSERT_OBJ(mtaskp->vertexList().size() == 1, mtaskp, "Multiple MTaskMoveVertex");
MTaskMoveVertex* const mvtxp = mtaskp->vertexList().front();
UASSERT_OBJ(mvtxp->userp(), mtaskp, "Bypassed MTaskMoveVertex should not have MTask");
// Function to add a edge to a dependent from 'mtaskp'
const auto addEdge = [this, mtaskp](LogicMTask* otherp) {
UASSERT_OBJ(otherp != mtaskp, mtaskp, "Would create a cycle edge");
if (mtaskp->hasRelativeMTask(otherp)) return; // Don't create redundant edges.
new MTaskEdge{m_mTaskGraphp.get(), mtaskp, otherp, 1};
};
// Iterate downstream direct dependents
for (V3GraphEdge *dEdgep = mvtxp->outBeginp(), *dNextp; dEdgep; dEdgep = dNextp) {
dNextp = dEdgep->outNextp();
V3GraphVertex* const top = dEdgep->top();
if (LogicMTask* const otherp = static_cast<LogicMTask*>(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 *tEdgep = top->outBeginp(), *tNextp; tEdgep;
tEdgep = tNextp) {
tNextp = tEdgep->outNextp();
LogicMTask* const transp
= static_cast<LogicMTask*>(tEdgep->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 *vtxp = m_mTaskGraphp->verticesBeginp(), *nextp; vtxp; vtxp = nextp) {
nextp = vtxp->verticesNextp();
LogicMTask* const mtaskp = static_cast<LogicMTask*>(vtxp);
if (VL_UNLIKELY((mtaskp == m_entryMTaskp) || (mtaskp == m_exitMTaskp))) continue;
// Add the entry/exit edges
if (mtaskp->inEmpty()) new MTaskEdge{m_mTaskGraphp.get(), m_entryMTaskp, mtaskp, 1};
if (mtaskp->outEmpty()) new MTaskEdge{m_mTaskGraphp.get(), mtaskp, m_exitMTaskp, 1};
}
return totalGraphCost;
}
// CONSTRUCTORS
Partitioner(const OrderGraph& orderGraph, const V3Graph& fineDepsGraph)
: m_fineDepsGraph{fineDepsGraph} {
// Fill in the m_mTaskGraphp with LogicMTask's and their interdependencies.
// Called by V3Order
hashGraphDebug(m_fineDepsGraph, "v3partition initial fine-grained deps");
// Create the first MTasks. Initially, each MTask just wraps one
// MTaskMoveVertex. 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");
// Reassign MTask IDs onto smaller numbers, which should be more stable
// across small logic changes. Keep MTask IDs in the same relative
// order though, otherwise we break CmpLogicMTask for still-existing
// EdgeSet's that haven't destructed yet.
{
using SortedMTaskSet = std::set<LogicMTask*, LogicMTask::CmpLogicMTask>;
SortedMTaskSet sorted;
for (V3GraphVertex* itp = m_mTaskGraphp->verticesBeginp(); itp;
itp = itp->verticesNextp()) {
LogicMTask* const mtaskp = static_cast<LogicMTask*>(itp);
sorted.insert(mtaskp);
}
for (auto it = sorted.begin(); it != sorted.end(); ++it) {
// We shouldn't perturb the sort order of the set, despite
// changing the IDs, they should all just remain in the same
// relative order. Confirm that:
const uint32_t nextId = v3Global.rootp()->allocNextMTaskID();
UASSERT(nextId <= (*it)->id(), "Should only shrink MTaskIDs here");
UINFO(4, "Reassigning MTask id " << (*it)->id() << " to id " << nextId << "\n");
(*it)->id(nextId);
}
}
// Set color to indicate an mtaskId on every underlying MTaskMoveVertex.
for (V3GraphVertex* itp = m_mTaskGraphp->verticesBeginp(); itp;
itp = itp->verticesNextp()) {
const LogicMTask* const mtaskp = static_cast<LogicMTask*>(itp);
for (MTaskMoveVertex* const mvertexp : mtaskp->vertexList()) {
mvertexp->color(mtaskp->id());
}
}
}
~Partitioner() = default;
VL_UNCOPYABLE(Partitioner);
VL_UNMOVABLE(Partitioner);
public:
static std::unique_ptr<V3Graph> apply(const OrderGraph& orderGraph,
const V3Graph& fineDepsGraph) {
return std::move(Partitioner{orderGraph, fineDepsGraph}.m_mTaskGraphp);
}
};
// Sort MTaskMoveVertex vertices by domain, then by scope, based on teh order they are encountered
class OrderVerticesByDomainThenScope final {
mutable uint64_t m_nextId = 0; // Next id to use
mutable std::unordered_map<const void*, uint64_t> m_id; // Map from ptr to id
// Map a pointer into an id, for deterministic results
uint64_t findId(const void* ptrp) const {
const auto pair = m_id.emplace(ptrp, m_nextId);
if (pair.second) ++m_nextId;
return pair.first->second;
}
public:
bool operator()(const V3GraphVertex* lhsp, const V3GraphVertex* rhsp) const {
const MTaskMoveVertex* const l_vxp = lhsp->as<MTaskMoveVertex>();
const MTaskMoveVertex* const r_vxp = rhsp->as<MTaskMoveVertex>();
const uint64_t l_id = findId(l_vxp->domainp());
const uint64_t r_id = findId(r_vxp->domainp());
if (l_id != r_id) return l_id < r_id;
return findId(l_vxp->scopep()) < findId(r_vxp->scopep());
}
};
// Sort LogicMTask vertices by their serial IDs.
struct MTaskVxIdLessThan final {
bool operator()(const V3GraphVertex* lhsp, const V3GraphVertex* rhsp) const {
return lhsp->as<LogicMTask>()->id() < rhsp->as<LogicMTask>()->id();
}
};
AstExecGraph* V3Order::createParallel(const 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");
// Starting from the orderGraph, make a slightly-coarsened graph representing
// only logic, and discarding edges we know we can ignore.
// This is quite similar to the 'm_pomGraph' of the serial code gen:
const std::unique_ptr<V3Graph> logicGraphp
= V3OrderMoveGraphBuilder<MTaskMoveVertex>::apply(orderGraph, trigToSen);
// Needed? We do this for m_pomGraph in serial mode, so do it here too:
logicGraphp->removeRedundantEdgesMax(&V3GraphEdge::followAlwaysTrue);
// Partition logicGraph into LogicMTask's. The partitioner will annotate
// each vertex in logicGraph with a 'color' which is really an mtask ID
// in this context.
const std::unique_ptr<V3Graph> mTaskGraphp = Partitioner::apply(orderGraph, *logicGraphp);
struct MTaskState final {
AstMTaskBody* m_mtaskBodyp = nullptr;
std::vector<const OrderLogicVertex*> m_logics;
ExecMTask* m_execMTaskp = nullptr;
};
std::unordered_map<uint32_t /*mtask id*/, MTaskState> mtaskStates;
// Iterate through the entire logicGraph. For each logic node,
// attach it to a per-MTask ordered list of logic nodes.
// This is the order we'll execute logic nodes within the MTask.
//
// MTasks may span scopes and domains, so sort by both here:
GraphStream<OrderVerticesByDomainThenScope> logicStream{logicGraphp.get()};
while (const V3GraphVertex* const vtxp = logicStream.nextp()) {
const MTaskMoveVertex* const movep = vtxp->as<MTaskMoveVertex>();
// Only care about logic vertices
if (!movep->logicp()) continue;
const unsigned mtaskId = movep->color();
UASSERT(mtaskId > 0, "Every MTaskMoveVertex should have an mtask assignment >0");
// Add this logic to the per-mtask order
mtaskStates[mtaskId].m_logics.push_back(movep->logicp());
// Since we happen to be iterating over every logic node,
// take this opportunity to annotate each AstVar with the id's
// of mTaskGraphp that consume it and produce it. We'll use this
// information in V3EmitC when we lay out var's in memory.
const OrderLogicVertex* const logicp = movep->logicp();
for (const V3GraphEdge* edgep = logicp->inBeginp(); edgep; edgep = edgep->inNextp()) {
const OrderVarVertex* const vVtxp = edgep->fromp()->cast<const OrderVarVertex>();
if (!vVtxp) continue;
vVtxp->vscp()->varp()->addMTaskId(mtaskId);
}
for (const V3GraphEdge* edgep = logicp->outBeginp(); edgep; edgep = edgep->outNextp()) {
const OrderVarVertex* const vVtxp = edgep->top()->cast<const OrderVarVertex>();
if (!vVtxp) continue;
vVtxp->vscp()->varp()->addMTaskId(mtaskId);
}
}
// 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();
// Create CFuncs and bodies for each MTask.
V3OrderCFuncEmitter emitter{tag, slow};
GraphStream<MTaskVxIdLessThan> mtaskStream{mTaskGraphp.get()};
while (const V3GraphVertex* const vtxp = mtaskStream.nextp()) {
const LogicMTask* const mtaskp = vtxp->as<LogicMTask>();
// Create a body for this mtask
AstMTaskBody* const bodyp = new AstMTaskBody{rootFlp};
MTaskState& state = mtaskStates[mtaskp->id()];
state.m_mtaskBodyp = bodyp;
// Emit functions with this MTaks's logic, and call them in the body.
for (const OrderLogicVertex* lVtxp : state.m_logics) emitter.emitLogic(lVtxp);
for (AstActive* const activep : emitter.getAndClearActiveps()) bodyp->addStmtsp(activep);
// Translate the LogicMTask graph into the corresponding ExecMTask
// graph, which will outlive V3Order and persist for the remainder
// of verilator's processing.
// - The LogicMTask graph points to MTaskMoveVertex's
// and OrderLogicVertex's which are ephemeral to V3Order.
// - The ExecMTask graph and the AstMTaskBody's produced here
// persist until code generation time.
state.m_execMTaskp = new ExecMTask{depGraphp, bodyp, mtaskp->id()};
// Cross-link each ExecMTask and MTaskBody
// Q: Why even have two objects?
// A: One is an AstNode, the other is a GraphVertex,
// to combine them would involve multiple inheritance...
state.m_mtaskBodyp->execMTaskp(state.m_execMTaskp);
for (V3GraphEdge* inp = mtaskp->inBeginp(); inp; inp = inp->inNextp()) {
const V3GraphVertex* fromVxp = inp->fromp();
const LogicMTask* const fromp = fromVxp->as<const LogicMTask>();
const MTaskState& fromState = mtaskStates[fromp->id()];
new V3GraphEdge{depGraphp, fromState.m_execMTaskp, state.m_execMTaskp, 1};
}
execGraphp->addMTaskBodiesp(bodyp);
}
return execGraphp;
}
void V3Order::selfTestParallel() {
UINFO(2, __FUNCTION__ << ": " << endl);
PropagateCp<GraphWay::FORWARD>::selfTest();
PropagateCp<GraphWay::REVERSE>::selfTest();
Contraction::selfTest();
}