//===-- RegAllocSolver.h - Heuristic PBQP Solver for reg alloc --*- C++ -*-===// // // The LLVM Compiler Infrastructure // // This file is distributed under the University of Illinois Open Source // License. See LICENSE.TXT for details. // //===----------------------------------------------------------------------===// // // Heuristic PBQP solver for register allocation problems. This solver uses a // graph reduction approach. Nodes of degree 0, 1 and 2 are eliminated with // optimality-preserving rules (see ReductionRules.h). When no low-degree (<3) // nodes are present, a heuristic derived from Brigg's graph coloring approach // is used. // //===----------------------------------------------------------------------===// #ifndef LLVM_CODEGEN_PBQP_REGALLOCSOLVER_H #define LLVM_CODEGEN_PBQP_REGALLOCSOLVER_H #include "CostAllocator.h" #include "Graph.h" #include "ReductionRules.h" #include "Solution.h" #include "llvm/Support/ErrorHandling.h" #include #include namespace PBQP { namespace RegAlloc { /// \brief Metadata to speed allocatability test. /// /// Keeps track of the number of infinities in each row and column. class MatrixMetadata { private: MatrixMetadata(const MatrixMetadata&); void operator=(const MatrixMetadata&); public: MatrixMetadata(const PBQP::Matrix& M) : WorstRow(0), WorstCol(0), UnsafeRows(new bool[M.getRows() - 1]()), UnsafeCols(new bool[M.getCols() - 1]()) { unsigned* ColCounts = new unsigned[M.getCols() - 1](); for (unsigned i = 1; i < M.getRows(); ++i) { unsigned RowCount = 0; for (unsigned j = 1; j < M.getCols(); ++j) { if (M[i][j] == std::numeric_limits::infinity()) { ++RowCount; ++ColCounts[j - 1]; UnsafeRows[i - 1] = true; UnsafeCols[j - 1] = true; } } WorstRow = std::max(WorstRow, RowCount); } unsigned WorstColCountForCurRow = *std::max_element(ColCounts, ColCounts + M.getCols() - 1); WorstCol = std::max(WorstCol, WorstColCountForCurRow); delete[] ColCounts; } ~MatrixMetadata() { delete[] UnsafeRows; delete[] UnsafeCols; } unsigned getWorstRow() const { return WorstRow; } unsigned getWorstCol() const { return WorstCol; } const bool* getUnsafeRows() const { return UnsafeRows; } const bool* getUnsafeCols() const { return UnsafeCols; } private: unsigned WorstRow, WorstCol; bool* UnsafeRows; bool* UnsafeCols; }; class NodeMetadata { public: typedef enum { Unprocessed, OptimallyReducible, ConservativelyAllocatable, NotProvablyAllocatable } ReductionState; NodeMetadata() : RS(Unprocessed), DeniedOpts(0), OptUnsafeEdges(0) {} ~NodeMetadata() { delete[] OptUnsafeEdges; } void setup(const Vector& Costs) { NumOpts = Costs.getLength() - 1; OptUnsafeEdges = new unsigned[NumOpts](); } ReductionState getReductionState() const { return RS; } void setReductionState(ReductionState RS) { this->RS = RS; } void handleAddEdge(const MatrixMetadata& MD, bool Transpose) { DeniedOpts += Transpose ? MD.getWorstCol() : MD.getWorstRow(); const bool* UnsafeOpts = Transpose ? MD.getUnsafeCols() : MD.getUnsafeRows(); for (unsigned i = 0; i < NumOpts; ++i) OptUnsafeEdges[i] += UnsafeOpts[i]; } void handleRemoveEdge(const MatrixMetadata& MD, bool Transpose) { DeniedOpts -= Transpose ? MD.getWorstCol() : MD.getWorstRow(); const bool* UnsafeOpts = Transpose ? MD.getUnsafeCols() : MD.getUnsafeRows(); for (unsigned i = 0; i < NumOpts; ++i) OptUnsafeEdges[i] -= UnsafeOpts[i]; } bool isConservativelyAllocatable() const { return (DeniedOpts < NumOpts) || (std::find(OptUnsafeEdges, OptUnsafeEdges + NumOpts, 0) != OptUnsafeEdges + NumOpts); } private: ReductionState RS; unsigned NumOpts; unsigned DeniedOpts; unsigned* OptUnsafeEdges; }; class RegAllocSolverImpl { private: typedef PBQP::MDMatrix RAMatrix; public: typedef PBQP::Vector RawVector; typedef PBQP::Matrix RawMatrix; typedef PBQP::Vector Vector; typedef RAMatrix Matrix; typedef PBQP::PoolCostAllocator< Vector, PBQP::VectorComparator, Matrix, PBQP::MatrixComparator> CostAllocator; typedef PBQP::GraphBase::NodeId NodeId; typedef PBQP::GraphBase::EdgeId EdgeId; typedef RegAlloc::NodeMetadata NodeMetadata; struct EdgeMetadata { }; typedef PBQP::Graph Graph; RegAllocSolverImpl(Graph &G) : G(G) {} Solution solve() { G.setSolver(*this); Solution S; setup(); S = backpropagate(G, reduce()); G.unsetSolver(); return S; } void handleAddNode(NodeId NId) { G.getNodeMetadata(NId).setup(G.getNodeCosts(NId)); } void handleRemoveNode(NodeId NId) {} void handleSetNodeCosts(NodeId NId, const Vector& newCosts) {} void handleAddEdge(EdgeId EId) { handleReconnectEdge(EId, G.getEdgeNode1Id(EId)); handleReconnectEdge(EId, G.getEdgeNode2Id(EId)); } void handleRemoveEdge(EdgeId EId) { handleDisconnectEdge(EId, G.getEdgeNode1Id(EId)); handleDisconnectEdge(EId, G.getEdgeNode2Id(EId)); } void handleDisconnectEdge(EdgeId EId, NodeId NId) { NodeMetadata& NMd = G.getNodeMetadata(NId); const MatrixMetadata& MMd = G.getEdgeCosts(EId).getMetadata(); NMd.handleRemoveEdge(MMd, NId == G.getEdgeNode2Id(EId)); if (G.getNodeDegree(NId) == 3) { // This node is becoming optimally reducible. moveToOptimallyReducibleNodes(NId); } else if (NMd.getReductionState() == NodeMetadata::NotProvablyAllocatable && NMd.isConservativelyAllocatable()) { // This node just became conservatively allocatable. moveToConservativelyAllocatableNodes(NId); } } void handleReconnectEdge(EdgeId EId, NodeId NId) { NodeMetadata& NMd = G.getNodeMetadata(NId); const MatrixMetadata& MMd = G.getEdgeCosts(EId).getMetadata(); NMd.handleAddEdge(MMd, NId == G.getEdgeNode2Id(EId)); } void handleSetEdgeCosts(EdgeId EId, const Matrix& NewCosts) { handleRemoveEdge(EId); NodeId N1Id = G.getEdgeNode1Id(EId); NodeId N2Id = G.getEdgeNode2Id(EId); NodeMetadata& N1Md = G.getNodeMetadata(N1Id); NodeMetadata& N2Md = G.getNodeMetadata(N2Id); const MatrixMetadata& MMd = NewCosts.getMetadata(); N1Md.handleAddEdge(MMd, N1Id != G.getEdgeNode1Id(EId)); N2Md.handleAddEdge(MMd, N2Id != G.getEdgeNode1Id(EId)); } private: void removeFromCurrentSet(NodeId NId) { switch (G.getNodeMetadata(NId).getReductionState()) { case NodeMetadata::Unprocessed: break; case NodeMetadata::OptimallyReducible: assert(OptimallyReducibleNodes.find(NId) != OptimallyReducibleNodes.end() && "Node not in optimally reducible set."); OptimallyReducibleNodes.erase(NId); break; case NodeMetadata::ConservativelyAllocatable: assert(ConservativelyAllocatableNodes.find(NId) != ConservativelyAllocatableNodes.end() && "Node not in conservatively allocatable set."); ConservativelyAllocatableNodes.erase(NId); break; case NodeMetadata::NotProvablyAllocatable: assert(NotProvablyAllocatableNodes.find(NId) != NotProvablyAllocatableNodes.end() && "Node not in not-provably-allocatable set."); NotProvablyAllocatableNodes.erase(NId); break; } } void moveToOptimallyReducibleNodes(NodeId NId) { removeFromCurrentSet(NId); OptimallyReducibleNodes.insert(NId); G.getNodeMetadata(NId).setReductionState( NodeMetadata::OptimallyReducible); } void moveToConservativelyAllocatableNodes(NodeId NId) { removeFromCurrentSet(NId); ConservativelyAllocatableNodes.insert(NId); G.getNodeMetadata(NId).setReductionState( NodeMetadata::ConservativelyAllocatable); } void moveToNotProvablyAllocatableNodes(NodeId NId) { removeFromCurrentSet(NId); NotProvablyAllocatableNodes.insert(NId); G.getNodeMetadata(NId).setReductionState( NodeMetadata::NotProvablyAllocatable); } void setup() { // Set up worklists. for (auto NId : G.nodeIds()) { if (G.getNodeDegree(NId) < 3) moveToOptimallyReducibleNodes(NId); else if (G.getNodeMetadata(NId).isConservativelyAllocatable()) moveToConservativelyAllocatableNodes(NId); else moveToNotProvablyAllocatableNodes(NId); } } // Compute a reduction order for the graph by iteratively applying PBQP // reduction rules. Locally optimal rules are applied whenever possible (R0, // R1, R2). If no locally-optimal rules apply then any conservatively // allocatable node is reduced. Finally, if no conservatively allocatable // node exists then the node with the lowest spill-cost:degree ratio is // selected. std::vector reduce() { assert(!G.empty() && "Cannot reduce empty graph."); typedef GraphBase::NodeId NodeId; std::vector NodeStack; // Consume worklists. while (true) { if (!OptimallyReducibleNodes.empty()) { NodeSet::iterator NItr = OptimallyReducibleNodes.begin(); NodeId NId = *NItr; OptimallyReducibleNodes.erase(NItr); NodeStack.push_back(NId); switch (G.getNodeDegree(NId)) { case 0: break; case 1: applyR1(G, NId); break; case 2: applyR2(G, NId); break; default: llvm_unreachable("Not an optimally reducible node."); } } else if (!ConservativelyAllocatableNodes.empty()) { // Conservatively allocatable nodes will never spill. For now just // take the first node in the set and push it on the stack. When we // start optimizing more heavily for register preferencing, it may // would be better to push nodes with lower 'expected' or worst-case // register costs first (since early nodes are the most // constrained). NodeSet::iterator NItr = ConservativelyAllocatableNodes.begin(); NodeId NId = *NItr; ConservativelyAllocatableNodes.erase(NItr); NodeStack.push_back(NId); G.disconnectAllNeighborsFromNode(NId); } else if (!NotProvablyAllocatableNodes.empty()) { NodeSet::iterator NItr = std::min_element(NotProvablyAllocatableNodes.begin(), NotProvablyAllocatableNodes.end(), SpillCostComparator(G)); NodeId NId = *NItr; NotProvablyAllocatableNodes.erase(NItr); NodeStack.push_back(NId); G.disconnectAllNeighborsFromNode(NId); } else break; } return NodeStack; } class SpillCostComparator { public: SpillCostComparator(const Graph& G) : G(G) {} bool operator()(NodeId N1Id, NodeId N2Id) { PBQPNum N1SC = G.getNodeCosts(N1Id)[0] / G.getNodeDegree(N1Id); PBQPNum N2SC = G.getNodeCosts(N2Id)[0] / G.getNodeDegree(N2Id); return N1SC < N2SC; } private: const Graph& G; }; Graph& G; typedef std::set NodeSet; NodeSet OptimallyReducibleNodes; NodeSet ConservativelyAllocatableNodes; NodeSet NotProvablyAllocatableNodes; }; typedef Graph Graph; Solution solve(Graph& G) { if (G.empty()) return Solution(); RegAllocSolverImpl RegAllocSolver(G); return RegAllocSolver.solve(); } } } #endif // LLVM_CODEGEN_PBQP_REGALLOCSOLVER_H