forked from OSchip/llvm-project
593 lines
18 KiB
C++
593 lines
18 KiB
C++
//===-- HeuristicSolver.h - Heuristic PBQP Solver --------------*- C++ -*-===//
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//
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// The LLVM Compiler Infrastructure
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//
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// This file is distributed under the University of Illinois Open Source
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// License. See LICENSE.TXT for details.
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//
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//===----------------------------------------------------------------------===//
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//
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// Heuristic PBQP solver. This solver is able to perform optimal reductions for
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// nodes of degree 0, 1 or 2. For nodes of degree >2 a plugable heuristic is
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// used to select a node for reduction.
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//
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//===----------------------------------------------------------------------===//
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#ifndef LLVM_CODEGEN_PBQP_HEURISTICSOLVER_H
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#define LLVM_CODEGEN_PBQP_HEURISTICSOLVER_H
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#include "Graph.h"
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#include "Solution.h"
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#include "llvm/Support/raw_ostream.h"
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#include <vector>
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#include <limits>
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namespace PBQP {
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/// \brief Heuristic PBQP solver implementation.
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///
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/// This class should usually be created (and destroyed) indirectly via a call
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/// to HeuristicSolver<HImpl>::solve(Graph&).
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/// See the comments for HeuristicSolver.
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///
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/// HeuristicSolverImpl provides the R0, R1 and R2 reduction rules,
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/// backpropagation phase, and maintains the internal copy of the graph on
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/// which the reduction is carried out (the original being kept to facilitate
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/// backpropagation).
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template <typename HImpl>
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class HeuristicSolverImpl {
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private:
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typedef typename HImpl::NodeData HeuristicNodeData;
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typedef typename HImpl::EdgeData HeuristicEdgeData;
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typedef std::list<Graph::EdgeItr> SolverEdges;
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public:
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/// \brief Iterator type for edges in the solver graph.
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typedef SolverEdges::iterator SolverEdgeItr;
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private:
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class NodeData {
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public:
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NodeData() : solverDegree(0) {}
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HeuristicNodeData& getHeuristicData() { return hData; }
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SolverEdgeItr addSolverEdge(Graph::EdgeItr eItr) {
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++solverDegree;
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return solverEdges.insert(solverEdges.end(), eItr);
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}
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void removeSolverEdge(SolverEdgeItr seItr) {
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--solverDegree;
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solverEdges.erase(seItr);
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}
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SolverEdgeItr solverEdgesBegin() { return solverEdges.begin(); }
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SolverEdgeItr solverEdgesEnd() { return solverEdges.end(); }
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unsigned getSolverDegree() const { return solverDegree; }
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void clearSolverEdges() {
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solverDegree = 0;
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solverEdges.clear();
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}
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private:
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HeuristicNodeData hData;
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unsigned solverDegree;
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SolverEdges solverEdges;
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};
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class EdgeData {
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public:
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HeuristicEdgeData& getHeuristicData() { return hData; }
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void setN1SolverEdgeItr(SolverEdgeItr n1SolverEdgeItr) {
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this->n1SolverEdgeItr = n1SolverEdgeItr;
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}
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SolverEdgeItr getN1SolverEdgeItr() { return n1SolverEdgeItr; }
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void setN2SolverEdgeItr(SolverEdgeItr n2SolverEdgeItr){
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this->n2SolverEdgeItr = n2SolverEdgeItr;
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}
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SolverEdgeItr getN2SolverEdgeItr() { return n2SolverEdgeItr; }
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private:
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HeuristicEdgeData hData;
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SolverEdgeItr n1SolverEdgeItr, n2SolverEdgeItr;
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};
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Graph &g;
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HImpl h;
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Solution s;
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std::vector<Graph::NodeItr> stack;
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typedef std::list<NodeData> NodeDataList;
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NodeDataList nodeDataList;
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typedef std::list<EdgeData> EdgeDataList;
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EdgeDataList edgeDataList;
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public:
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/// \brief Construct a heuristic solver implementation to solve the given
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/// graph.
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/// @param g The graph representing the problem instance to be solved.
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HeuristicSolverImpl(Graph &g) : g(g), h(*this) {}
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/// \brief Get the graph being solved by this solver.
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/// @return The graph representing the problem instance being solved by this
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/// solver.
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Graph& getGraph() { return g; }
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/// \brief Get the heuristic data attached to the given node.
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/// @param nItr Node iterator.
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/// @return The heuristic data attached to the given node.
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HeuristicNodeData& getHeuristicNodeData(Graph::NodeItr nItr) {
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return getSolverNodeData(nItr).getHeuristicData();
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}
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/// \brief Get the heuristic data attached to the given edge.
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/// @param eItr Edge iterator.
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/// @return The heuristic data attached to the given node.
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HeuristicEdgeData& getHeuristicEdgeData(Graph::EdgeItr eItr) {
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return getSolverEdgeData(eItr).getHeuristicData();
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}
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/// \brief Begin iterator for the set of edges adjacent to the given node in
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/// the solver graph.
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/// @param nItr Node iterator.
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/// @return Begin iterator for the set of edges adjacent to the given node
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/// in the solver graph.
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SolverEdgeItr solverEdgesBegin(Graph::NodeItr nItr) {
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return getSolverNodeData(nItr).solverEdgesBegin();
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}
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/// \brief End iterator for the set of edges adjacent to the given node in
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/// the solver graph.
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/// @param nItr Node iterator.
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/// @return End iterator for the set of edges adjacent to the given node in
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/// the solver graph.
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SolverEdgeItr solverEdgesEnd(Graph::NodeItr nItr) {
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return getSolverNodeData(nItr).solverEdgesEnd();
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}
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/// \brief Remove a node from the solver graph.
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/// @param eItr Edge iterator for edge to be removed.
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///
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/// Does <i>not</i> notify the heuristic of the removal. That should be
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/// done manually if necessary.
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void removeSolverEdge(Graph::EdgeItr eItr) {
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EdgeData &eData = getSolverEdgeData(eItr);
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NodeData &n1Data = getSolverNodeData(g.getEdgeNode1(eItr)),
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&n2Data = getSolverNodeData(g.getEdgeNode2(eItr));
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n1Data.removeSolverEdge(eData.getN1SolverEdgeItr());
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n2Data.removeSolverEdge(eData.getN2SolverEdgeItr());
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}
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/// \brief Compute a solution to the PBQP problem instance with which this
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/// heuristic solver was constructed.
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/// @return A solution to the PBQP problem.
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///
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/// Performs the full PBQP heuristic solver algorithm, including setup,
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/// calls to the heuristic (which will call back to the reduction rules in
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/// this class), and cleanup.
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Solution computeSolution() {
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setup();
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h.setup();
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h.reduce();
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backpropagate();
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h.cleanup();
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cleanup();
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return s;
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}
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/// \brief Add to the end of the stack.
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/// @param nItr Node iterator to add to the reduction stack.
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void pushToStack(Graph::NodeItr nItr) {
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getSolverNodeData(nItr).clearSolverEdges();
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stack.push_back(nItr);
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}
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/// \brief Returns the solver degree of the given node.
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/// @param nItr Node iterator for which degree is requested.
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/// @return Node degree in the <i>solver</i> graph (not the original graph).
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unsigned getSolverDegree(Graph::NodeItr nItr) {
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return getSolverNodeData(nItr).getSolverDegree();
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}
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/// \brief Set the solution of the given node.
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/// @param nItr Node iterator to set solution for.
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/// @param selection Selection for node.
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void setSolution(const Graph::NodeItr &nItr, unsigned selection) {
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s.setSelection(nItr, selection);
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for (Graph::AdjEdgeItr aeItr = g.adjEdgesBegin(nItr),
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aeEnd = g.adjEdgesEnd(nItr);
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aeItr != aeEnd; ++aeItr) {
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Graph::EdgeItr eItr(*aeItr);
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Graph::NodeItr anItr(g.getEdgeOtherNode(eItr, nItr));
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getSolverNodeData(anItr).addSolverEdge(eItr);
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}
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}
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/// \brief Apply rule R0.
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/// @param nItr Node iterator for node to apply R0 to.
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///
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/// Node will be automatically pushed to the solver stack.
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void applyR0(Graph::NodeItr nItr) {
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assert(getSolverNodeData(nItr).getSolverDegree() == 0 &&
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"R0 applied to node with degree != 0.");
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// Nothing to do. Just push the node onto the reduction stack.
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pushToStack(nItr);
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}
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/// \brief Apply rule R1.
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/// @param nItr Node iterator for node to apply R1 to.
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///
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/// Node will be automatically pushed to the solver stack.
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void applyR1(Graph::NodeItr xnItr) {
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NodeData &nd = getSolverNodeData(xnItr);
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assert(nd.getSolverDegree() == 1 &&
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"R1 applied to node with degree != 1.");
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Graph::EdgeItr eItr = *nd.solverEdgesBegin();
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const Matrix &eCosts = g.getEdgeCosts(eItr);
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const Vector &xCosts = g.getNodeCosts(xnItr);
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// Duplicate a little to avoid transposing matrices.
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if (xnItr == g.getEdgeNode1(eItr)) {
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Graph::NodeItr ynItr = g.getEdgeNode2(eItr);
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Vector &yCosts = g.getNodeCosts(ynItr);
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for (unsigned j = 0; j < yCosts.getLength(); ++j) {
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PBQPNum min = eCosts[0][j] + xCosts[0];
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for (unsigned i = 1; i < xCosts.getLength(); ++i) {
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PBQPNum c = eCosts[i][j] + xCosts[i];
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if (c < min)
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min = c;
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}
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yCosts[j] += min;
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}
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h.handleRemoveEdge(eItr, ynItr);
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} else {
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Graph::NodeItr ynItr = g.getEdgeNode1(eItr);
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Vector &yCosts = g.getNodeCosts(ynItr);
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for (unsigned i = 0; i < yCosts.getLength(); ++i) {
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PBQPNum min = eCosts[i][0] + xCosts[0];
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for (unsigned j = 1; j < xCosts.getLength(); ++j) {
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PBQPNum c = eCosts[i][j] + xCosts[j];
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if (c < min)
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min = c;
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}
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yCosts[i] += min;
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}
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h.handleRemoveEdge(eItr, ynItr);
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}
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removeSolverEdge(eItr);
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assert(nd.getSolverDegree() == 0 &&
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"Degree 1 with edge removed should be 0.");
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pushToStack(xnItr);
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}
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/// \brief Apply rule R2.
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/// @param nItr Node iterator for node to apply R2 to.
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///
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/// Node will be automatically pushed to the solver stack.
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void applyR2(Graph::NodeItr xnItr) {
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assert(getSolverNodeData(xnItr).getSolverDegree() == 2 &&
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"R2 applied to node with degree != 2.");
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NodeData &nd = getSolverNodeData(xnItr);
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const Vector &xCosts = g.getNodeCosts(xnItr);
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SolverEdgeItr aeItr = nd.solverEdgesBegin();
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Graph::EdgeItr yxeItr = *aeItr,
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zxeItr = *(++aeItr);
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Graph::NodeItr ynItr = g.getEdgeOtherNode(yxeItr, xnItr),
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znItr = g.getEdgeOtherNode(zxeItr, xnItr);
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bool flipEdge1 = (g.getEdgeNode1(yxeItr) == xnItr),
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flipEdge2 = (g.getEdgeNode1(zxeItr) == xnItr);
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const Matrix *yxeCosts = flipEdge1 ?
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new Matrix(g.getEdgeCosts(yxeItr).transpose()) :
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&g.getEdgeCosts(yxeItr);
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const Matrix *zxeCosts = flipEdge2 ?
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new Matrix(g.getEdgeCosts(zxeItr).transpose()) :
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&g.getEdgeCosts(zxeItr);
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unsigned xLen = xCosts.getLength(),
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yLen = yxeCosts->getRows(),
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zLen = zxeCosts->getRows();
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Matrix delta(yLen, zLen);
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for (unsigned i = 0; i < yLen; ++i) {
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for (unsigned j = 0; j < zLen; ++j) {
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PBQPNum min = (*yxeCosts)[i][0] + (*zxeCosts)[j][0] + xCosts[0];
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for (unsigned k = 1; k < xLen; ++k) {
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PBQPNum c = (*yxeCosts)[i][k] + (*zxeCosts)[j][k] + xCosts[k];
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if (c < min) {
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min = c;
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}
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}
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delta[i][j] = min;
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}
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}
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if (flipEdge1)
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delete yxeCosts;
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if (flipEdge2)
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delete zxeCosts;
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Graph::EdgeItr yzeItr = g.findEdge(ynItr, znItr);
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bool addedEdge = false;
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if (yzeItr == g.edgesEnd()) {
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yzeItr = g.addEdge(ynItr, znItr, delta);
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addedEdge = true;
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} else {
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Matrix &yzeCosts = g.getEdgeCosts(yzeItr);
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h.preUpdateEdgeCosts(yzeItr);
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if (ynItr == g.getEdgeNode1(yzeItr)) {
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yzeCosts += delta;
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} else {
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yzeCosts += delta.transpose();
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}
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}
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bool nullCostEdge = tryNormaliseEdgeMatrix(yzeItr);
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if (!addedEdge) {
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// If we modified the edge costs let the heuristic know.
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h.postUpdateEdgeCosts(yzeItr);
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}
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if (nullCostEdge) {
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// If this edge ended up null remove it.
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if (!addedEdge) {
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// We didn't just add it, so we need to notify the heuristic
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// and remove it from the solver.
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h.handleRemoveEdge(yzeItr, ynItr);
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h.handleRemoveEdge(yzeItr, znItr);
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removeSolverEdge(yzeItr);
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}
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g.removeEdge(yzeItr);
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} else if (addedEdge) {
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// If the edge was added, and non-null, finish setting it up, add it to
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// the solver & notify heuristic.
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edgeDataList.push_back(EdgeData());
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g.setEdgeData(yzeItr, &edgeDataList.back());
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addSolverEdge(yzeItr);
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h.handleAddEdge(yzeItr);
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}
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h.handleRemoveEdge(yxeItr, ynItr);
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removeSolverEdge(yxeItr);
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h.handleRemoveEdge(zxeItr, znItr);
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removeSolverEdge(zxeItr);
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pushToStack(xnItr);
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}
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private:
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NodeData& getSolverNodeData(Graph::NodeItr nItr) {
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return *static_cast<NodeData*>(g.getNodeData(nItr));
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}
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EdgeData& getSolverEdgeData(Graph::EdgeItr eItr) {
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return *static_cast<EdgeData*>(g.getEdgeData(eItr));
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}
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void addSolverEdge(Graph::EdgeItr eItr) {
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EdgeData &eData = getSolverEdgeData(eItr);
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NodeData &n1Data = getSolverNodeData(g.getEdgeNode1(eItr)),
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&n2Data = getSolverNodeData(g.getEdgeNode2(eItr));
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eData.setN1SolverEdgeItr(n1Data.addSolverEdge(eItr));
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eData.setN2SolverEdgeItr(n2Data.addSolverEdge(eItr));
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}
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void setup() {
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if (h.solverRunSimplify()) {
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simplify();
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}
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// Create node data objects.
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for (Graph::NodeItr nItr = g.nodesBegin(), nEnd = g.nodesEnd();
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nItr != nEnd; ++nItr) {
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nodeDataList.push_back(NodeData());
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g.setNodeData(nItr, &nodeDataList.back());
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}
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// Create edge data objects.
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for (Graph::EdgeItr eItr = g.edgesBegin(), eEnd = g.edgesEnd();
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eItr != eEnd; ++eItr) {
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edgeDataList.push_back(EdgeData());
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g.setEdgeData(eItr, &edgeDataList.back());
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addSolverEdge(eItr);
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}
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}
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void simplify() {
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disconnectTrivialNodes();
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eliminateIndependentEdges();
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}
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// Eliminate trivial nodes.
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void disconnectTrivialNodes() {
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unsigned numDisconnected = 0;
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for (Graph::NodeItr nItr = g.nodesBegin(), nEnd = g.nodesEnd();
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nItr != nEnd; ++nItr) {
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if (g.getNodeCosts(nItr).getLength() == 1) {
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std::vector<Graph::EdgeItr> edgesToRemove;
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for (Graph::AdjEdgeItr aeItr = g.adjEdgesBegin(nItr),
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aeEnd = g.adjEdgesEnd(nItr);
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aeItr != aeEnd; ++aeItr) {
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Graph::EdgeItr eItr = *aeItr;
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if (g.getEdgeNode1(eItr) == nItr) {
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Graph::NodeItr otherNodeItr = g.getEdgeNode2(eItr);
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g.getNodeCosts(otherNodeItr) +=
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g.getEdgeCosts(eItr).getRowAsVector(0);
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}
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else {
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Graph::NodeItr otherNodeItr = g.getEdgeNode1(eItr);
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g.getNodeCosts(otherNodeItr) +=
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g.getEdgeCosts(eItr).getColAsVector(0);
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}
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edgesToRemove.push_back(eItr);
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}
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if (!edgesToRemove.empty())
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++numDisconnected;
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while (!edgesToRemove.empty()) {
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g.removeEdge(edgesToRemove.back());
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edgesToRemove.pop_back();
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}
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}
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}
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}
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void eliminateIndependentEdges() {
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std::vector<Graph::EdgeItr> edgesToProcess;
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unsigned numEliminated = 0;
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for (Graph::EdgeItr eItr = g.edgesBegin(), eEnd = g.edgesEnd();
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eItr != eEnd; ++eItr) {
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edgesToProcess.push_back(eItr);
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}
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while (!edgesToProcess.empty()) {
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if (tryToEliminateEdge(edgesToProcess.back()))
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++numEliminated;
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edgesToProcess.pop_back();
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}
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}
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bool tryToEliminateEdge(Graph::EdgeItr eItr) {
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if (tryNormaliseEdgeMatrix(eItr)) {
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g.removeEdge(eItr);
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return true;
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}
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return false;
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}
|
|
|
|
bool tryNormaliseEdgeMatrix(Graph::EdgeItr &eItr) {
|
|
|
|
Matrix &edgeCosts = g.getEdgeCosts(eItr);
|
|
Vector &uCosts = g.getNodeCosts(g.getEdgeNode1(eItr)),
|
|
&vCosts = g.getNodeCosts(g.getEdgeNode2(eItr));
|
|
|
|
for (unsigned r = 0; r < edgeCosts.getRows(); ++r) {
|
|
PBQPNum rowMin = edgeCosts.getRowMin(r);
|
|
uCosts[r] += rowMin;
|
|
if (rowMin != std::numeric_limits<PBQPNum>::infinity()) {
|
|
edgeCosts.subFromRow(r, rowMin);
|
|
}
|
|
else {
|
|
edgeCosts.setRow(r, 0);
|
|
}
|
|
}
|
|
|
|
for (unsigned c = 0; c < edgeCosts.getCols(); ++c) {
|
|
PBQPNum colMin = edgeCosts.getColMin(c);
|
|
vCosts[c] += colMin;
|
|
if (colMin != std::numeric_limits<PBQPNum>::infinity()) {
|
|
edgeCosts.subFromCol(c, colMin);
|
|
}
|
|
else {
|
|
edgeCosts.setCol(c, 0);
|
|
}
|
|
}
|
|
|
|
return edgeCosts.isZero();
|
|
}
|
|
|
|
void backpropagate() {
|
|
while (!stack.empty()) {
|
|
computeSolution(stack.back());
|
|
stack.pop_back();
|
|
}
|
|
}
|
|
|
|
void computeSolution(Graph::NodeItr nItr) {
|
|
|
|
NodeData &nodeData = getSolverNodeData(nItr);
|
|
|
|
Vector v(g.getNodeCosts(nItr));
|
|
|
|
// Solve based on existing solved edges.
|
|
for (SolverEdgeItr solvedEdgeItr = nodeData.solverEdgesBegin(),
|
|
solvedEdgeEnd = nodeData.solverEdgesEnd();
|
|
solvedEdgeItr != solvedEdgeEnd; ++solvedEdgeItr) {
|
|
|
|
Graph::EdgeItr eItr(*solvedEdgeItr);
|
|
Matrix &edgeCosts = g.getEdgeCosts(eItr);
|
|
|
|
if (nItr == g.getEdgeNode1(eItr)) {
|
|
Graph::NodeItr adjNode(g.getEdgeNode2(eItr));
|
|
unsigned adjSolution = s.getSelection(adjNode);
|
|
v += edgeCosts.getColAsVector(adjSolution);
|
|
}
|
|
else {
|
|
Graph::NodeItr adjNode(g.getEdgeNode1(eItr));
|
|
unsigned adjSolution = s.getSelection(adjNode);
|
|
v += edgeCosts.getRowAsVector(adjSolution);
|
|
}
|
|
|
|
}
|
|
|
|
setSolution(nItr, v.minIndex());
|
|
}
|
|
|
|
void cleanup() {
|
|
h.cleanup();
|
|
nodeDataList.clear();
|
|
edgeDataList.clear();
|
|
}
|
|
};
|
|
|
|
/// \brief PBQP heuristic solver class.
|
|
///
|
|
/// Given a PBQP Graph g representing a PBQP problem, you can find a solution
|
|
/// by calling
|
|
/// <tt>Solution s = HeuristicSolver<H>::solve(g);</tt>
|
|
///
|
|
/// The choice of heuristic for the H parameter will affect both the solver
|
|
/// speed and solution quality. The heuristic should be chosen based on the
|
|
/// nature of the problem being solved.
|
|
/// Currently the only solver included with LLVM is the Briggs heuristic for
|
|
/// register allocation.
|
|
template <typename HImpl>
|
|
class HeuristicSolver {
|
|
public:
|
|
static Solution solve(Graph &g) {
|
|
HeuristicSolverImpl<HImpl> hs(g);
|
|
return hs.computeSolution();
|
|
}
|
|
};
|
|
|
|
}
|
|
|
|
#endif // LLVM_CODEGEN_PBQP_HEURISTICSOLVER_H
|