1 //===-- RegAllocSolver.h - Heuristic PBQP Solver for reg alloc --*- C++ -*-===//
3 // The LLVM Compiler Infrastructure
5 // This file is distributed under the University of Illinois Open Source
6 // License. See LICENSE.TXT for details.
8 //===----------------------------------------------------------------------===//
10 // Heuristic PBQP solver for register allocation problems. This solver uses a
11 // graph reduction approach. Nodes of degree 0, 1 and 2 are eliminated with
12 // optimality-preserving rules (see ReductionRules.h). When no low-degree (<3)
13 // nodes are present, a heuristic derived from Brigg's graph coloring approach
16 //===----------------------------------------------------------------------===//
18 #ifndef LLVM_CODEGEN_PBQP_REGALLOCSOLVER_H
19 #define LLVM_CODEGEN_PBQP_REGALLOCSOLVER_H
21 #include "CostAllocator.h"
23 #include "ReductionRules.h"
25 #include "llvm/Support/ErrorHandling.h"
33 /// \brief Metadata to speed allocatability test.
35 /// Keeps track of the number of infinities in each row and column.
36 class MatrixMetadata {
38 MatrixMetadata(const MatrixMetadata&);
39 void operator=(const MatrixMetadata&);
41 MatrixMetadata(const PBQP::Matrix& m)
42 : worstRow(0), worstCol(0),
43 unsafeRows(new bool[m.getRows() - 1]()),
44 unsafeCols(new bool[m.getCols() - 1]()) {
46 unsigned* colCounts = new unsigned[m.getCols() - 1]();
48 for (unsigned i = 1; i < m.getRows(); ++i) {
49 unsigned rowCount = 0;
50 for (unsigned j = 1; j < m.getCols(); ++j) {
51 if (m[i][j] == std::numeric_limits<PBQP::PBQPNum>::infinity()) {
54 unsafeRows[i - 1] = true;
55 unsafeCols[j - 1] = true;
58 worstRow = std::max(worstRow, rowCount);
60 unsigned worstColCountForCurRow =
61 *std::max_element(colCounts, colCounts + m.getCols() - 1);
62 worstCol = std::max(worstCol, worstColCountForCurRow);
71 unsigned getWorstRow() const { return worstRow; }
72 unsigned getWorstCol() const { return worstCol; }
73 const bool* getUnsafeRows() const { return unsafeRows; }
74 const bool* getUnsafeCols() const { return unsafeCols; }
77 unsigned worstRow, worstCol;
84 typedef enum { Unprocessed,
86 ConservativelyAllocatable,
87 NotProvablyAllocatable } ReductionState;
89 NodeMetadata() : rs(Unprocessed), deniedOpts(0), optUnsafeEdges(0) {}
90 ~NodeMetadata() { delete[] optUnsafeEdges; }
92 void setup(const Vector& costs) {
93 numOpts = costs.getLength() - 1;
94 optUnsafeEdges = new unsigned[numOpts]();
97 ReductionState getReductionState() const { return rs; }
98 void setReductionState(ReductionState rs) { this->rs = rs; }
100 void handleAddEdge(const MatrixMetadata& md, bool transpose) {
101 deniedOpts += transpose ? md.getWorstCol() : md.getWorstRow();
102 const bool* unsafeOpts =
103 transpose ? md.getUnsafeCols() : md.getUnsafeRows();
104 for (unsigned i = 0; i < numOpts; ++i)
105 optUnsafeEdges[i] += unsafeOpts[i];
108 void handleRemoveEdge(const MatrixMetadata& md, bool transpose) {
109 deniedOpts -= transpose ? md.getWorstCol() : md.getWorstRow();
110 const bool* unsafeOpts =
111 transpose ? md.getUnsafeCols() : md.getUnsafeRows();
112 for (unsigned i = 0; i < numOpts; ++i)
113 optUnsafeEdges[i] -= unsafeOpts[i];
116 bool isConservativelyAllocatable() const {
117 return (deniedOpts < numOpts) ||
118 (std::find(optUnsafeEdges, optUnsafeEdges + numOpts, 0) !=
119 optUnsafeEdges + numOpts);
126 unsigned* optUnsafeEdges;
129 class RegAllocSolverImpl {
131 typedef PBQP::MDMatrix<MatrixMetadata> RAMatrix;
133 typedef PBQP::Vector RawVector;
134 typedef PBQP::Matrix RawMatrix;
135 typedef PBQP::Vector Vector;
136 typedef RAMatrix Matrix;
137 typedef PBQP::PoolCostAllocator<
138 Vector, PBQP::VectorComparator,
139 Matrix, PBQP::MatrixComparator> CostAllocator;
141 typedef PBQP::GraphBase::NodeId NodeId;
142 typedef PBQP::GraphBase::EdgeId EdgeId;
144 typedef RegAlloc::NodeMetadata NodeMetadata;
146 struct EdgeMetadata { };
148 typedef PBQP::Graph<RegAllocSolverImpl> Graph;
150 RegAllocSolverImpl(Graph &G) : G(G) {}
156 S = backpropagate(G, reduce());
161 void handleAddNode(NodeId NId) {
162 G.getNodeMetadata(NId).setup(G.getNodeCosts(NId));
164 void handleRemoveNode(NodeId NId) {}
165 void handleSetNodeCosts(NodeId NId, const Vector& newCosts) {}
167 void handleAddEdge(EdgeId EId) {
168 handleReconnectEdge(EId, G.getEdgeNode1Id(EId));
169 handleReconnectEdge(EId, G.getEdgeNode2Id(EId));
172 void handleRemoveEdge(EdgeId EId) {
173 handleDisconnectEdge(EId, G.getEdgeNode1Id(EId));
174 handleDisconnectEdge(EId, G.getEdgeNode2Id(EId));
177 void handleDisconnectEdge(EdgeId EId, NodeId NId) {
178 NodeMetadata& nMd = G.getNodeMetadata(NId);
179 const MatrixMetadata& mMd = G.getEdgeCosts(EId).getMetadata();
180 nMd.handleRemoveEdge(mMd, NId == G.getEdgeNode2Id(EId));
181 if (G.getNodeDegree(NId) == 3) {
182 // This node is becoming optimally reducible.
183 moveToOptimallyReducibleNodes(NId);
184 } else if (nMd.getReductionState() ==
185 NodeMetadata::NotProvablyAllocatable &&
186 nMd.isConservativelyAllocatable()) {
187 // This node just became conservatively allocatable.
188 moveToConservativelyAllocatableNodes(NId);
192 void handleReconnectEdge(EdgeId EId, NodeId NId) {
193 NodeMetadata& nMd = G.getNodeMetadata(NId);
194 const MatrixMetadata& mMd = G.getEdgeCosts(EId).getMetadata();
195 nMd.handleAddEdge(mMd, NId == G.getEdgeNode2Id(EId));
198 void handleSetEdgeCosts(EdgeId EId, const Matrix& NewCosts) {
199 handleRemoveEdge(EId);
201 NodeId n1Id = G.getEdgeNode1Id(EId);
202 NodeId n2Id = G.getEdgeNode2Id(EId);
203 NodeMetadata& n1Md = G.getNodeMetadata(n1Id);
204 NodeMetadata& n2Md = G.getNodeMetadata(n2Id);
205 const MatrixMetadata& mMd = NewCosts.getMetadata();
206 n1Md.handleAddEdge(mMd, n1Id != G.getEdgeNode1Id(EId));
207 n2Md.handleAddEdge(mMd, n2Id != G.getEdgeNode1Id(EId));
212 void removeFromCurrentSet(NodeId NId) {
213 switch (G.getNodeMetadata(NId).getReductionState()) {
214 case NodeMetadata::Unprocessed: break;
215 case NodeMetadata::OptimallyReducible:
216 assert(OptimallyReducibleNodes.find(NId) !=
217 OptimallyReducibleNodes.end() &&
218 "Node not in optimally reducible set.");
219 OptimallyReducibleNodes.erase(NId);
221 case NodeMetadata::ConservativelyAllocatable:
222 assert(ConservativelyAllocatableNodes.find(NId) !=
223 ConservativelyAllocatableNodes.end() &&
224 "Node not in conservatively allocatable set.");
225 ConservativelyAllocatableNodes.erase(NId);
227 case NodeMetadata::NotProvablyAllocatable:
228 assert(NotProvablyAllocatableNodes.find(NId) !=
229 NotProvablyAllocatableNodes.end() &&
230 "Node not in not-provably-allocatable set.");
231 NotProvablyAllocatableNodes.erase(NId);
236 void moveToOptimallyReducibleNodes(NodeId NId) {
237 removeFromCurrentSet(NId);
238 OptimallyReducibleNodes.insert(NId);
239 G.getNodeMetadata(NId).setReductionState(
240 NodeMetadata::OptimallyReducible);
243 void moveToConservativelyAllocatableNodes(NodeId NId) {
244 removeFromCurrentSet(NId);
245 ConservativelyAllocatableNodes.insert(NId);
246 G.getNodeMetadata(NId).setReductionState(
247 NodeMetadata::ConservativelyAllocatable);
250 void moveToNotProvablyAllocatableNodes(NodeId NId) {
251 removeFromCurrentSet(NId);
252 NotProvablyAllocatableNodes.insert(NId);
253 G.getNodeMetadata(NId).setReductionState(
254 NodeMetadata::NotProvablyAllocatable);
259 for (auto NId : G.nodeIds()) {
260 if (G.getNodeDegree(NId) < 3)
261 moveToOptimallyReducibleNodes(NId);
262 else if (G.getNodeMetadata(NId).isConservativelyAllocatable())
263 moveToConservativelyAllocatableNodes(NId);
265 moveToNotProvablyAllocatableNodes(NId);
269 // Compute a reduction order for the graph by iteratively applying PBQP
270 // reduction rules. Locally optimal rules are applied whenever possible (R0,
271 // R1, R2). If no locally-optimal rules apply then any conservatively
272 // allocatable node is reduced. Finally, if no conservatively allocatable
273 // node exists then the node with the lowest spill-cost:degree ratio is
275 std::vector<GraphBase::NodeId> reduce() {
276 assert(!G.empty() && "Cannot reduce empty graph.");
278 typedef GraphBase::NodeId NodeId;
279 std::vector<NodeId> NodeStack;
281 // Consume worklists.
283 if (!OptimallyReducibleNodes.empty()) {
284 NodeSet::iterator nItr = OptimallyReducibleNodes.begin();
286 OptimallyReducibleNodes.erase(nItr);
287 NodeStack.push_back(NId);
288 switch (G.getNodeDegree(NId)) {
297 default: llvm_unreachable("Not an optimally reducible node.");
299 } else if (!ConservativelyAllocatableNodes.empty()) {
300 // Conservatively allocatable nodes will never spill. For now just
301 // take the first node in the set and push it on the stack. When we
302 // start optimizing more heavily for register preferencing, it may
303 // would be better to push nodes with lower 'expected' or worst-case
304 // register costs first (since early nodes are the most
306 NodeSet::iterator nItr = ConservativelyAllocatableNodes.begin();
308 ConservativelyAllocatableNodes.erase(nItr);
309 NodeStack.push_back(NId);
310 G.disconnectAllNeighborsFromNode(NId);
312 } else if (!NotProvablyAllocatableNodes.empty()) {
313 NodeSet::iterator nItr =
314 std::min_element(NotProvablyAllocatableNodes.begin(),
315 NotProvablyAllocatableNodes.end(),
316 SpillCostComparator(G));
318 NotProvablyAllocatableNodes.erase(nItr);
319 NodeStack.push_back(NId);
320 G.disconnectAllNeighborsFromNode(NId);
328 class SpillCostComparator {
330 SpillCostComparator(const Graph& G) : G(G) {}
331 bool operator()(NodeId N1Id, NodeId N2Id) {
332 PBQPNum N1SC = G.getNodeCosts(N1Id)[0] / G.getNodeDegree(N1Id);
333 PBQPNum N2SC = G.getNodeCosts(N2Id)[0] / G.getNodeDegree(N2Id);
341 typedef std::set<NodeId> NodeSet;
342 NodeSet OptimallyReducibleNodes;
343 NodeSet ConservativelyAllocatableNodes;
344 NodeSet NotProvablyAllocatableNodes;
347 typedef Graph<RegAllocSolverImpl> Graph;
349 Solution solve(Graph& G) {
352 RegAllocSolverImpl RegAllocSolver(G);
353 return RegAllocSolver.solve();
359 #endif // LLVM_CODEGEN_PBQP_REGALLOCSOLVER_H