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Diffstat (limited to 'contrib/llvm/lib/CodeGen/PBQP/HeuristicBase.h')
| -rw-r--r-- | contrib/llvm/lib/CodeGen/PBQP/HeuristicBase.h | 242 |
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diff --git a/contrib/llvm/lib/CodeGen/PBQP/HeuristicBase.h b/contrib/llvm/lib/CodeGen/PBQP/HeuristicBase.h new file mode 100644 index 0000000..3bb24e1 --- /dev/null +++ b/contrib/llvm/lib/CodeGen/PBQP/HeuristicBase.h @@ -0,0 +1,242 @@ +//===-- HeuristcBase.h --- Heuristic base class for PBQP --------*- C++ -*-===// +// +// The LLVM Compiler Infrastructure +// +// This file is distributed under the University of Illinois Open Source +// License. See LICENSE.TXT for details. +// +//===----------------------------------------------------------------------===// + +#ifndef LLVM_CODEGEN_PBQP_HEURISTICBASE_H +#define LLVM_CODEGEN_PBQP_HEURISTICBASE_H + +#include "HeuristicSolver.h" + +namespace PBQP { + + /// \brief Abstract base class for heuristic implementations. + /// + /// This class provides a handy base for heuristic implementations with common + /// solver behaviour implemented for a number of methods. + /// + /// To implement your own heuristic using this class as a base you'll have to + /// implement, as a minimum, the following methods: + /// <ul> + /// <li> void addToHeuristicList(Graph::NodeItr) : Add a node to the + /// heuristic reduction list. + /// <li> void heuristicReduce() : Perform a single heuristic reduction. + /// <li> void preUpdateEdgeCosts(Graph::EdgeItr) : Handle the (imminent) + /// change to the cost matrix on the given edge (by R2). + /// <li> void postUpdateEdgeCostts(Graph::EdgeItr) : Handle the new + /// costs on the given edge. + /// <li> void handleAddEdge(Graph::EdgeItr) : Handle the addition of a new + /// edge into the PBQP graph (by R2). + /// <li> void handleRemoveEdge(Graph::EdgeItr, Graph::NodeItr) : Handle the + /// disconnection of the given edge from the given node. + /// <li> A constructor for your derived class : to pass back a reference to + /// the solver which is using this heuristic. + /// </ul> + /// + /// These methods are implemented in this class for documentation purposes, + /// but will assert if called. + /// + /// Note that this class uses the curiously recursive template idiom to + /// forward calls to the derived class. These methods need not be made + /// virtual, and indeed probably shouldn't for performance reasons. + /// + /// You'll also need to provide NodeData and EdgeData structs in your class. + /// These can be used to attach data relevant to your heuristic to each + /// node/edge in the PBQP graph. + + template <typename HImpl> + class HeuristicBase { + private: + + typedef std::list<Graph::NodeItr> OptimalList; + + HeuristicSolverImpl<HImpl> &s; + Graph &g; + OptimalList optimalList; + + // Return a reference to the derived heuristic. + HImpl& impl() { return static_cast<HImpl&>(*this); } + + // Add the given node to the optimal reductions list. Keep an iterator to + // its location for fast removal. + void addToOptimalReductionList(Graph::NodeItr nItr) { + optimalList.insert(optimalList.end(), nItr); + } + + public: + + /// \brief Construct an instance with a reference to the given solver. + /// @param solver The solver which is using this heuristic instance. + HeuristicBase(HeuristicSolverImpl<HImpl> &solver) + : s(solver), g(s.getGraph()) { } + + /// \brief Get the solver which is using this heuristic instance. + /// @return The solver which is using this heuristic instance. + /// + /// You can use this method to get access to the solver in your derived + /// heuristic implementation. + HeuristicSolverImpl<HImpl>& getSolver() { return s; } + + /// \brief Get the graph representing the problem to be solved. + /// @return The graph representing the problem to be solved. + Graph& getGraph() { return g; } + + /// \brief Tell the solver to simplify the graph before the reduction phase. + /// @return Whether or not the solver should run a simplification phase + /// prior to the main setup and reduction. + /// + /// HeuristicBase returns true from this method as it's a sensible default, + /// however you can over-ride it in your derived class if you want different + /// behaviour. + bool solverRunSimplify() const { return true; } + + /// \brief Decide whether a node should be optimally or heuristically + /// reduced. + /// @return Whether or not the given node should be listed for optimal + /// reduction (via R0, R1 or R2). + /// + /// HeuristicBase returns true for any node with degree less than 3. This is + /// sane and sensible for many situations, but not all. You can over-ride + /// this method in your derived class if you want a different selection + /// criteria. Note however that your criteria for selecting optimal nodes + /// should be <i>at least</i> as strong as this. I.e. Nodes of degree 3 or + /// higher should not be selected under any circumstances. + bool shouldOptimallyReduce(Graph::NodeItr nItr) { + if (g.getNodeDegree(nItr) < 3) + return true; + // else + return false; + } + + /// \brief Add the given node to the list of nodes to be optimally reduced. + /// @return nItr Node iterator to be added. + /// + /// You probably don't want to over-ride this, except perhaps to record + /// statistics before calling this implementation. HeuristicBase relies on + /// its behaviour. + void addToOptimalReduceList(Graph::NodeItr nItr) { + optimalList.push_back(nItr); + } + + /// \brief Initialise the heuristic. + /// + /// HeuristicBase iterates over all nodes in the problem and adds them to + /// the appropriate list using addToOptimalReduceList or + /// addToHeuristicReduceList based on the result of shouldOptimallyReduce. + /// + /// This behaviour should be fine for most situations. + void setup() { + for (Graph::NodeItr nItr = g.nodesBegin(), nEnd = g.nodesEnd(); + nItr != nEnd; ++nItr) { + if (impl().shouldOptimallyReduce(nItr)) { + addToOptimalReduceList(nItr); + } else { + impl().addToHeuristicReduceList(nItr); + } + } + } + + /// \brief Optimally reduce one of the nodes in the optimal reduce list. + /// @return True if a reduction takes place, false if the optimal reduce + /// list is empty. + /// + /// Selects a node from the optimal reduce list and removes it, applying + /// R0, R1 or R2 as appropriate based on the selected node's degree. + bool optimalReduce() { + if (optimalList.empty()) + return false; + + Graph::NodeItr nItr = optimalList.front(); + optimalList.pop_front(); + + switch (s.getSolverDegree(nItr)) { + case 0: s.applyR0(nItr); break; + case 1: s.applyR1(nItr); break; + case 2: s.applyR2(nItr); break; + default: assert(false && + "Optimal reductions of degree > 2 nodes is invalid."); + } + + return true; + } + + /// \brief Perform the PBQP reduction process. + /// + /// Reduces the problem to the empty graph by repeated application of the + /// reduction rules R0, R1, R2 and RN. + /// R0, R1 or R2 are always applied if possible before RN is used. + void reduce() { + bool finished = false; + + while (!finished) { + if (!optimalReduce()) + if (!impl().heuristicReduce()) + finished = true; + } + } + + /// \brief Add a node to the heuristic reduce list. + /// @param nItr Node iterator to add to the heuristic reduce list. + void addToHeuristicList(Graph::NodeItr nItr) { + assert(false && "Must be implemented in derived class."); + } + + /// \brief Heuristically reduce one of the nodes in the heuristic + /// reduce list. + /// @return True if a reduction takes place, false if the heuristic reduce + /// list is empty. + void heuristicReduce() { + assert(false && "Must be implemented in derived class."); + } + + /// \brief Prepare a change in the costs on the given edge. + /// @param eItr Edge iterator. + void preUpdateEdgeCosts(Graph::EdgeItr eItr) { + assert(false && "Must be implemented in derived class."); + } + + /// \brief Handle the change in the costs on the given edge. + /// @param eItr Edge iterator. + void postUpdateEdgeCostts(Graph::EdgeItr eItr) { + assert(false && "Must be implemented in derived class."); + } + + /// \brief Handle the addition of a new edge into the PBQP graph. + /// @param eItr Edge iterator for the added edge. + void handleAddEdge(Graph::EdgeItr eItr) { + assert(false && "Must be implemented in derived class."); + } + + /// \brief Handle disconnection of an edge from a node. + /// @param eItr Edge iterator for edge being disconnected. + /// @param nItr Node iterator for the node being disconnected from. + /// + /// Edges are frequently removed due to the removal of a node. This + /// method allows for the effect to be computed only for the remaining + /// node in the graph. + void handleRemoveEdge(Graph::EdgeItr eItr, Graph::NodeItr nItr) { + assert(false && "Must be implemented in derived class."); + } + + /// \brief Clean up any structures used by HeuristicBase. + /// + /// At present this just performs a sanity check: that the optimal reduce + /// list is empty now that reduction has completed. + /// + /// If your derived class has more complex structures which need tearing + /// down you should over-ride this method but include a call back to this + /// implementation. + void cleanup() { + assert(optimalList.empty() && "Nodes left over in optimal reduce list?"); + } + + }; + +} + + +#endif // LLVM_CODEGEN_PBQP_HEURISTICBASE_H |
