//===- LoopFusion.cpp - Code to perform loop fusion -----------------------===// // // Copyright 2019 The MLIR Authors. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. // ============================================================================= // // This file implements loop fusion. // //===----------------------------------------------------------------------===// #include "mlir/AffineOps/AffineOps.h" #include "mlir/Analysis/AffineAnalysis.h" #include "mlir/Analysis/AffineStructures.h" #include "mlir/Analysis/LoopAnalysis.h" #include "mlir/Analysis/Utils.h" #include "mlir/IR/AffineExpr.h" #include "mlir/IR/AffineMap.h" #include "mlir/IR/Builders.h" #include "mlir/IR/BuiltinOps.h" #include "mlir/IR/InstVisitor.h" #include "mlir/Pass.h" #include "mlir/StandardOps/StandardOps.h" #include "mlir/Transforms/LoopUtils.h" #include "mlir/Transforms/Passes.h" #include "mlir/Transforms/Utils.h" #include "llvm/ADT/DenseMap.h" #include "llvm/ADT/DenseSet.h" #include "llvm/ADT/SetVector.h" #include "llvm/Support/CommandLine.h" #include "llvm/Support/Debug.h" #include "llvm/Support/raw_ostream.h" #include #define DEBUG_TYPE "loop-fusion" using llvm::SetVector; using namespace mlir; static llvm::cl::OptionCategory clOptionsCategory(DEBUG_TYPE " options"); /// Disables fusion profitability check and fuses if valid. static llvm::cl::opt clMaximalLoopFusion("fusion-maximal", llvm::cl::Hidden, llvm::cl::desc("Enables maximal loop fusion"), llvm::cl::cat(clOptionsCategory)); /// A threshold in percent of additional computation allowed when fusing. static llvm::cl::opt clFusionAddlComputeTolerance( "fusion-compute-tolerance", llvm::cl::Hidden, llvm::cl::desc("Fractional increase in additional" " computation tolerated while fusing"), llvm::cl::cat(clOptionsCategory)); namespace { /// Loop fusion pass. This pass currently supports a greedy fusion policy, /// which fuses loop nests with single-writer/single-reader memref dependences /// with the goal of improving locality. // TODO(andydavis) Support fusion of source loop nests which write to multiple // memrefs, where each memref can have multiple users (if profitable). // TODO(andydavis) Extend this pass to check for fusion preventing dependences, // and add support for more general loop fusion algorithms. struct LoopFusion : public FunctionPass { LoopFusion() : FunctionPass(&LoopFusion::passID) {} PassResult runOnFunction(Function *f) override; static char passID; // The amount of additional computation that is tolerated while fusing // pair-wise as a fraction of the total computation. constexpr static double kComputeToleranceThreshold = 0.30f; }; } // end anonymous namespace char LoopFusion::passID = 0; FunctionPass *mlir::createLoopFusionPass() { return new LoopFusion; } namespace { // LoopNestStateCollector walks loop nests and collects load and store // operations, and whether or not an IfInst was encountered in the loop nest. class LoopNestStateCollector : public InstWalker { public: SmallVector forInsts; SmallVector loadOpInsts; SmallVector storeOpInsts; bool hasNonForRegion = false; void visitForInst(ForInst *forInst) { forInsts.push_back(forInst); } void visitOperationInst(OperationInst *opInst) { if (opInst->getNumBlockLists() != 0) hasNonForRegion = true; else if (opInst->isa()) loadOpInsts.push_back(opInst); else if (opInst->isa()) storeOpInsts.push_back(opInst); } }; // TODO(b/117228571) Replace when this is modeled through side-effects/op traits static bool isMemRefDereferencingOp(const OperationInst &op) { if (op.isa() || op.isa() || op.isa() || op.isa()) return true; return false; } // MemRefDependenceGraph is a graph data structure where graph nodes are // top-level instructions in a Function which contain load/store ops, and edges // are memref dependences between the nodes. // TODO(andydavis) Add a more flexible dependece graph representation. // TODO(andydavis) Add a depth parameter to dependence graph construction. struct MemRefDependenceGraph { public: // Node represents a node in the graph. A Node is either an entire loop nest // rooted at the top level which contains loads/stores, or a top level // load/store. struct Node { // The unique identifier of this node in the graph. unsigned id; // The top-level statment which is (or contains) loads/stores. Instruction *inst; // List of load operations. SmallVector loads; // List of store op insts. SmallVector stores; Node(unsigned id, Instruction *inst) : id(id), inst(inst) {} // Returns the load op count for 'memref'. unsigned getLoadOpCount(Value *memref) { unsigned loadOpCount = 0; for (auto *loadOpInst : loads) { if (memref == loadOpInst->cast()->getMemRef()) ++loadOpCount; } return loadOpCount; } // Returns the store op count for 'memref'. unsigned getStoreOpCount(Value *memref) { unsigned storeOpCount = 0; for (auto *storeOpInst : stores) { if (memref == storeOpInst->cast()->getMemRef()) ++storeOpCount; } return storeOpCount; } }; // Edge represents a data dependece between nodes in the graph. struct Edge { // The id of the node at the other end of the edge. // If this edge is stored in Edge = Node.inEdges[i], then // 'Node.inEdges[i].id' is the identifier of the source node of the edge. // If this edge is stored in Edge = Node.outEdges[i], then // 'Node.outEdges[i].id' is the identifier of the dest node of the edge. unsigned id; // The SSA value on which this edge represents a dependence. // If the value is a memref, then the dependence is between graph nodes // which contain accesses to the same memref 'value'. If the value is a // non-memref value, then the dependence is between a graph node which // defines an SSA value and another graph node which uses the SSA value // (e.g. a constant instruction defining a value which is used inside a loop // nest). Value *value; }; // Map from node id to Node. DenseMap nodes; // Map from node id to list of input edges. DenseMap> inEdges; // Map from node id to list of output edges. DenseMap> outEdges; // Map from memref to a count on the dependence edges associated with that // memref. DenseMap memrefEdgeCount; // The next unique identifier to use for newly created graph nodes. unsigned nextNodeId = 0; MemRefDependenceGraph() {} // Initializes the dependence graph based on operations in 'f'. // Returns true on success, false otherwise. bool init(Function *f); // Returns the graph node for 'id'. Node *getNode(unsigned id) { auto it = nodes.find(id); assert(it != nodes.end()); return &it->second; } // Adds a node with 'inst' to the graph and returns its unique identifier. unsigned addNode(Instruction *inst) { Node node(nextNodeId++, inst); nodes.insert({node.id, node}); return node.id; } // Remove node 'id' (and its associated edges) from graph. void removeNode(unsigned id) { // Remove each edge in 'inEdges[id]'. if (inEdges.count(id) > 0) { SmallVector oldInEdges = inEdges[id]; for (auto &inEdge : oldInEdges) { removeEdge(inEdge.id, id, inEdge.value); } } // Remove each edge in 'outEdges[id]'. if (outEdges.count(id) > 0) { SmallVector oldOutEdges = outEdges[id]; for (auto &outEdge : oldOutEdges) { removeEdge(id, outEdge.id, outEdge.value); } } // Erase remaining node state. inEdges.erase(id); outEdges.erase(id); nodes.erase(id); } // Returns true if node 'id' writes to any memref which escapes (or is an // argument to) the function/block. Returns false otherwise. bool writesToLiveInOrEscapingMemrefs(unsigned id) { Node *node = getNode(id); for (auto *storeOpInst : node->stores) { auto *memref = storeOpInst->cast()->getMemRef(); auto *inst = memref->getDefiningInst(); auto *opInst = dyn_cast_or_null(inst); // Return false if 'memref' is a function argument. if (opInst == nullptr) return true; // Return false if any use of 'memref' escapes the function. for (auto &use : memref->getUses()) { auto *user = dyn_cast(use.getOwner()); if (!user || !isMemRefDereferencingOp(*user)) return true; } } return false; } // Returns true if node 'id' can be removed from the graph. Returns false // otherwise. A node can be removed from the graph iff the following // conditions are met: // *) The node does not write to any memref which escapes (or is a // function/block argument). // *) The node has no successors in the dependence graph. bool canRemoveNode(unsigned id) { if (writesToLiveInOrEscapingMemrefs(id)) return false; Node *node = getNode(id); for (auto *storeOpInst : node->stores) { // Return false if there exist out edges from 'id' on 'memref'. if (getOutEdgeCount(id, storeOpInst->cast()->getMemRef()) > 0) return false; } return true; } // Returns true iff there is an edge from node 'srcId' to node 'dstId' for // 'value'. Returns false otherwise. bool hasEdge(unsigned srcId, unsigned dstId, Value *value) { if (outEdges.count(srcId) == 0 || inEdges.count(dstId) == 0) { return false; } bool hasOutEdge = llvm::any_of(outEdges[srcId], [=](Edge &edge) { return edge.id == dstId && edge.value == value; }); bool hasInEdge = llvm::any_of(inEdges[dstId], [=](Edge &edge) { return edge.id == srcId && edge.value == value; }); return hasOutEdge && hasInEdge; } // Adds an edge from node 'srcId' to node 'dstId' for 'value'. void addEdge(unsigned srcId, unsigned dstId, Value *value) { if (!hasEdge(srcId, dstId, value)) { outEdges[srcId].push_back({dstId, value}); inEdges[dstId].push_back({srcId, value}); if (value->getType().isa()) memrefEdgeCount[value]++; } } // Removes an edge from node 'srcId' to node 'dstId' for 'value'. void removeEdge(unsigned srcId, unsigned dstId, Value *value) { assert(inEdges.count(dstId) > 0); assert(outEdges.count(srcId) > 0); if (value->getType().isa()) { assert(memrefEdgeCount.count(value) > 0); memrefEdgeCount[value]--; } // Remove 'srcId' from 'inEdges[dstId]'. for (auto it = inEdges[dstId].begin(); it != inEdges[dstId].end(); ++it) { if ((*it).id == srcId && (*it).value == value) { inEdges[dstId].erase(it); break; } } // Remove 'dstId' from 'outEdges[srcId]'. for (auto it = outEdges[srcId].begin(); it != outEdges[srcId].end(); ++it) { if ((*it).id == dstId && (*it).value == value) { outEdges[srcId].erase(it); break; } } } // Returns the input edge count for node 'id' and 'memref' from src nodes // which access 'memref'. unsigned getIncomingMemRefAccesses(unsigned id, Value *memref) { unsigned inEdgeCount = 0; if (inEdges.count(id) > 0) for (auto &inEdge : inEdges[id]) if (inEdge.value == memref) { Node *srcNode = getNode(inEdge.id); // Only count in edges from 'srcNode' if 'srcNode' accesses 'memref' if (srcNode->getLoadOpCount(memref) > 0 || srcNode->getStoreOpCount(memref) > 0) ++inEdgeCount; } return inEdgeCount; } // Returns the output edge count for node 'id' and 'memref'. unsigned getOutEdgeCount(unsigned id, Value *memref) { unsigned outEdgeCount = 0; if (outEdges.count(id) > 0) for (auto &outEdge : outEdges[id]) if (outEdge.value == memref) ++outEdgeCount; return outEdgeCount; } // Computes and returns an insertion point instruction, before which the // the fused loop nest can be inserted while preserving // dependences. Returns nullptr if no such insertion point is found. Instruction *getFusedLoopNestInsertionPoint(unsigned srcId, unsigned dstId, Value *memrefToSkip) { if (outEdges.count(srcId) == 0) return getNode(dstId)->inst; // Build set of insts in range (srcId, dstId) which depend on 'srcId'. SmallPtrSet srcDepInsts; for (auto &outEdge : outEdges[srcId]) if (outEdge.id != dstId && outEdge.value != memrefToSkip) srcDepInsts.insert(getNode(outEdge.id)->inst); // Build set of insts in range (srcId, dstId) on which 'dstId' depends. SmallPtrSet dstDepInsts; for (auto &inEdge : inEdges[dstId]) if (inEdge.id != srcId && inEdge.value != memrefToSkip) dstDepInsts.insert(getNode(inEdge.id)->inst); Instruction *srcNodeInst = getNode(srcId)->inst; Instruction *dstNodeInst = getNode(dstId)->inst; // Computing insertion point: // *) Walk all instruction positions in Block instruction list in the // range (src, dst). For each instruction 'inst' visited in this search: // *) Store in 'firstSrcDepPos' the first position where 'inst' has a // dependence edge from 'srcNode'. // *) Store in 'lastDstDepPost' the last position where 'inst' has a // dependence edge to 'dstNode'. // *) Compare 'firstSrcDepPos' and 'lastDstDepPost' to determine the // instruction insertion point (or return null pointer if no such // insertion point exists: 'firstSrcDepPos' <= 'lastDstDepPos'). SmallVector depInsts; Optional firstSrcDepPos; Optional lastDstDepPos; unsigned pos = 0; for (Block::iterator it = std::next(Block::iterator(srcNodeInst)); it != Block::iterator(dstNodeInst); ++it) { Instruction *inst = &(*it); if (srcDepInsts.count(inst) > 0 && firstSrcDepPos == None) firstSrcDepPos = pos; if (dstDepInsts.count(inst) > 0) lastDstDepPos = pos; depInsts.push_back(inst); ++pos; } if (firstSrcDepPos.hasValue()) { if (lastDstDepPos.hasValue()) { if (firstSrcDepPos.getValue() <= lastDstDepPos.getValue()) { // No valid insertion point exists which preserves dependences. return nullptr; } } // Return the insertion point at 'firstSrcDepPos'. return depInsts[firstSrcDepPos.getValue()]; } // No dependence targets in range (or only dst deps in range), return // 'dstNodInst' insertion point. return dstNodeInst; } // Updates edge mappings from node 'srcId' to node 'dstId' after 'oldMemRef' // has been replaced in node at 'dstId' by a private memref. void updateEdges(unsigned srcId, unsigned dstId, Value *oldMemRef) { // For each edge in 'inEdges[srcId]': add new edge remaping to 'dstId'. if (inEdges.count(srcId) > 0) { SmallVector oldInEdges = inEdges[srcId]; for (auto &inEdge : oldInEdges) { // Add edge from 'inEdge.id' to 'dstId' if not for 'oldMemRef'. if (inEdge.value != oldMemRef) addEdge(inEdge.id, dstId, inEdge.value); } } // For each edge in 'outEdges[srcId]': remove edge from 'srcId' to 'dstId'. if (outEdges.count(srcId) > 0) { SmallVector oldOutEdges = outEdges[srcId]; for (auto &outEdge : oldOutEdges) { // Remove any out edges from 'srcId' to 'dstId' across memrefs. if (outEdge.id == dstId) removeEdge(srcId, outEdge.id, outEdge.value); } } // Remove any edges in 'inEdges[dstId]' on 'oldMemRef' (which is being // replaced by a private memref). These edges could come from nodes // other than 'srcId' which were removed in the previous step. if (inEdges.count(dstId) > 0) { SmallVector oldInEdges = inEdges[dstId]; for (auto &inEdge : oldInEdges) if (inEdge.value == oldMemRef) removeEdge(inEdge.id, dstId, inEdge.value); } } // Adds ops in 'loads' and 'stores' to node at 'id'. void addToNode(unsigned id, const SmallVectorImpl &loads, const SmallVectorImpl &stores) { Node *node = getNode(id); for (auto *loadOpInst : loads) node->loads.push_back(loadOpInst); for (auto *storeOpInst : stores) node->stores.push_back(storeOpInst); } void clearNodeLoadAndStores(unsigned id) { Node *node = getNode(id); node->loads.clear(); node->stores.clear(); } void print(raw_ostream &os) const { os << "\nMemRefDependenceGraph\n"; os << "\nNodes:\n"; for (auto &idAndNode : nodes) { os << "Node: " << idAndNode.first << "\n"; auto it = inEdges.find(idAndNode.first); if (it != inEdges.end()) { for (const auto &e : it->second) os << " InEdge: " << e.id << " " << e.value << "\n"; } it = outEdges.find(idAndNode.first); if (it != outEdges.end()) { for (const auto &e : it->second) os << " OutEdge: " << e.id << " " << e.value << "\n"; } } } void dump() const { print(llvm::errs()); } }; // Intializes the data dependence graph by walking instructions in 'f'. // Assigns each node in the graph a node id based on program order in 'f'. // TODO(andydavis) Add support for taking a Block arg to construct the // dependence graph at a different depth. bool MemRefDependenceGraph::init(Function *f) { DenseMap> memrefAccesses; // TODO: support multi-block functions. if (f->getBlocks().size() != 1) return false; DenseMap forToNodeMap; for (auto &inst : f->front()) { if (auto *forInst = dyn_cast(&inst)) { // Create graph node 'id' to represent top-level 'forInst' and record // all loads and store accesses it contains. LoopNestStateCollector collector; collector.walkForInst(forInst); // Return false if IfInsts are found (not currently supported). if (collector.hasNonForRegion) return false; Node node(nextNodeId++, &inst); for (auto *opInst : collector.loadOpInsts) { node.loads.push_back(opInst); auto *memref = opInst->cast()->getMemRef(); memrefAccesses[memref].insert(node.id); } for (auto *opInst : collector.storeOpInsts) { node.stores.push_back(opInst); auto *memref = opInst->cast()->getMemRef(); memrefAccesses[memref].insert(node.id); } forToNodeMap[forInst] = node.id; nodes.insert({node.id, node}); } if (auto *opInst = dyn_cast(&inst)) { if (auto loadOp = opInst->dyn_cast()) { // Create graph node for top-level load op. Node node(nextNodeId++, &inst); node.loads.push_back(opInst); auto *memref = opInst->cast()->getMemRef(); memrefAccesses[memref].insert(node.id); nodes.insert({node.id, node}); } else if (auto storeOp = opInst->dyn_cast()) { // Create graph node for top-level store op. Node node(nextNodeId++, &inst); node.stores.push_back(opInst); auto *memref = opInst->cast()->getMemRef(); memrefAccesses[memref].insert(node.id); nodes.insert({node.id, node}); } else if (opInst->getNumBlockLists() != 0) { // Return false if another region is found (not currently supported). return false; } else if (opInst->getNumResults() > 0 && !opInst->use_empty()) { // Create graph node for top-level producer of SSA values, which // could be used by loop nest nodes. Node node(nextNodeId++, &inst); nodes.insert({node.id, node}); } } } // Add dependence edges between nodes which produce SSA values and their // users. for (auto &idAndNode : nodes) { const Node &node = idAndNode.second; if (!node.loads.empty() || !node.stores.empty()) continue; auto *opInst = cast(node.inst); for (auto *value : opInst->getResults()) { for (auto &use : value->getUses()) { auto *userOpInst = cast(use.getOwner()); SmallVector loops; getLoopIVs(*userOpInst, &loops); if (loops.empty()) continue; assert(forToNodeMap.count(loops[0]) > 0); unsigned userLoopNestId = forToNodeMap[loops[0]]; addEdge(node.id, userLoopNestId, value); } } } // Walk memref access lists and add graph edges between dependent nodes. for (auto &memrefAndList : memrefAccesses) { unsigned n = memrefAndList.second.size(); for (unsigned i = 0; i < n; ++i) { unsigned srcId = memrefAndList.second[i]; bool srcHasStore = getNode(srcId)->getStoreOpCount(memrefAndList.first) > 0; for (unsigned j = i + 1; j < n; ++j) { unsigned dstId = memrefAndList.second[j]; bool dstHasStore = getNode(dstId)->getStoreOpCount(memrefAndList.first) > 0; if (srcHasStore || dstHasStore) addEdge(srcId, dstId, memrefAndList.first); } } } return true; } namespace { // LoopNestStats aggregates various per-loop statistics (eg. loop trip count // and operation count) for a loop nest up until the innermost loop body. struct LoopNestStats { // Map from ForInst to immediate child ForInsts in its loop body. DenseMap> loopMap; // Map from ForInst to count of operations in its loop body. DenseMap opCountMap; // Map from ForInst to its constant trip count. DenseMap tripCountMap; }; // LoopNestStatsCollector walks a single loop nest and gathers per-loop // trip count and operation count statistics and records them in 'stats'. class LoopNestStatsCollector : public InstWalker { public: LoopNestStats *stats; bool hasLoopWithNonConstTripCount = false; LoopNestStatsCollector(LoopNestStats *stats) : stats(stats) {} void visitForInst(ForInst *forInst) { auto *parentInst = forInst->getParentInst(); if (parentInst != nullptr) { assert(isa(parentInst) && "Expected parent ForInst"); // Add mapping to 'forInst' from its parent ForInst. stats->loopMap[cast(parentInst)].push_back(forInst); } // Record the number of op instructions in the body of 'forInst'. unsigned count = 0; stats->opCountMap[forInst] = 0; for (auto &inst : *forInst->getBody()) { if (isa(&inst)) ++count; } stats->opCountMap[forInst] = count; // Record trip count for 'forInst'. Set flag if trip count is not constant. Optional maybeConstTripCount = getConstantTripCount(*forInst); if (!maybeConstTripCount.hasValue()) { hasLoopWithNonConstTripCount = true; return; } stats->tripCountMap[forInst] = maybeConstTripCount.getValue(); } }; // Computes the total cost of the loop nest rooted at 'forInst'. // Currently, the total cost is computed by counting the total operation // instance count (i.e. total number of operations in the loop bodyloop // operation count * loop trip count) for the entire loop nest. // If 'tripCountOverrideMap' is non-null, overrides the trip count for loops // specified in the map when computing the total op instance count. // NOTE: this is used to compute the cost of computation slices, which are // sliced along the iteration dimension, and thus reduce the trip count. // If 'computeCostMap' is non-null, the total op count for forInsts specified // in the map is increased (not overridden) by adding the op count from the // map to the existing op count for the for loop. This is done before // multiplying by the loop's trip count, and is used to model the cost of // inserting a sliced loop nest of known cost into the loop's body. // NOTE: this is used to compute the cost of fusing a slice of some loop nest // within another loop. static int64_t getComputeCost( ForInst *forInst, LoopNestStats *stats, llvm::SmallDenseMap *tripCountOverrideMap, DenseMap *computeCostMap) { // 'opCount' is the total number operations in one iteration of 'forInst' body int64_t opCount = stats->opCountMap[forInst]; if (stats->loopMap.count(forInst) > 0) { for (auto *childForInst : stats->loopMap[forInst]) { opCount += getComputeCost(childForInst, stats, tripCountOverrideMap, computeCostMap); } } // Add in additional op instances from slice (if specified in map). if (computeCostMap != nullptr) { auto it = computeCostMap->find(forInst); if (it != computeCostMap->end()) { opCount += it->second; } } // Override trip count (if specified in map). int64_t tripCount = stats->tripCountMap[forInst]; if (tripCountOverrideMap != nullptr) { auto it = tripCountOverrideMap->find(forInst); if (it != tripCountOverrideMap->end()) { tripCount = it->second; } } // Returns the total number of dynamic instances of operations in loop body. return tripCount * opCount; } } // end anonymous namespace static Optional getConstDifference(AffineMap lbMap, AffineMap ubMap) { assert(lbMap.getNumResults() == 1 && "expected single result bound map"); assert(ubMap.getNumResults() == 1 && "expected single result bound map"); assert(lbMap.getNumDims() == ubMap.getNumDims()); assert(lbMap.getNumSymbols() == ubMap.getNumSymbols()); // TODO(andydavis) Merge this code with 'mlir::getTripCountExpr'. // ub_expr - lb_expr AffineExpr lbExpr(lbMap.getResult(0)); AffineExpr ubExpr(ubMap.getResult(0)); auto loopSpanExpr = simplifyAffineExpr(ubExpr - lbExpr, lbMap.getNumDims(), lbMap.getNumSymbols()); auto cExpr = loopSpanExpr.dyn_cast(); if (!cExpr) return None; return cExpr.getValue(); } // Builds a map 'tripCountMap' from ForInst to constant trip count for loop // nest surrounding 'srcAccess' utilizing slice loop bounds in 'sliceState'. // Returns true on success, false otherwise (if a non-constant trip count // was encountered). // TODO(andydavis) Make this work with non-unit step loops. static bool buildSliceTripCountMap( OperationInst *srcOpInst, ComputationSliceState *sliceState, llvm::SmallDenseMap *tripCountMap) { SmallVector srcLoopIVs; getLoopIVs(*srcOpInst, &srcLoopIVs); unsigned numSrcLoopIVs = srcLoopIVs.size(); // Populate map from ForInst -> trip count for (unsigned i = 0; i < numSrcLoopIVs; ++i) { AffineMap lbMap = sliceState->lbs[i]; AffineMap ubMap = sliceState->ubs[i]; if (lbMap == AffineMap() || ubMap == AffineMap()) { // The iteration of src loop IV 'i' was not sliced. Use full loop bounds. if (srcLoopIVs[i]->hasConstantLowerBound() && srcLoopIVs[i]->hasConstantUpperBound()) { (*tripCountMap)[srcLoopIVs[i]] = srcLoopIVs[i]->getConstantUpperBound() - srcLoopIVs[i]->getConstantLowerBound(); continue; } return false; } Optional tripCount = getConstDifference(lbMap, ubMap); if (!tripCount.hasValue()) return false; (*tripCountMap)[srcLoopIVs[i]] = tripCount.getValue(); } return true; } // Removes load operations from 'srcLoads' which operate on 'memref', and // adds them to 'dstLoads'. static void moveLoadsAccessingMemrefTo(Value *memref, SmallVectorImpl *srcLoads, SmallVectorImpl *dstLoads) { dstLoads->clear(); SmallVector srcLoadsToKeep; for (auto *load : *srcLoads) { if (load->cast()->getMemRef() == memref) dstLoads->push_back(load); else srcLoadsToKeep.push_back(load); } srcLoads->swap(srcLoadsToKeep); } // Returns the innermost common loop depth for the set of operations in 'ops'. static unsigned getInnermostCommonLoopDepth(ArrayRef ops) { unsigned numOps = ops.size(); assert(numOps > 0); std::vector> loops(numOps); unsigned loopDepthLimit = std::numeric_limits::max(); for (unsigned i = 0; i < numOps; ++i) { getLoopIVs(*ops[i], &loops[i]); loopDepthLimit = std::min(loopDepthLimit, static_cast(loops[i].size())); } unsigned loopDepth = 0; for (unsigned d = 0; d < loopDepthLimit; ++d) { unsigned i; for (i = 1; i < numOps; ++i) { if (loops[i - 1][d] != loops[i][d]) { break; } } if (i != numOps) break; ++loopDepth; } return loopDepth; } // Returns the maximum loop depth at which no dependences between 'loadOpInsts' // and 'storeOpInsts' are satisfied. static unsigned getMaxLoopDepth(ArrayRef loadOpInsts, ArrayRef storeOpInsts) { // Merge loads and stores into the same array. SmallVector ops(loadOpInsts.begin(), loadOpInsts.end()); ops.append(storeOpInsts.begin(), storeOpInsts.end()); // Compute the innermost common loop depth for loads and stores. unsigned loopDepth = getInnermostCommonLoopDepth(ops); // Return common loop depth for loads if there are no store ops. if (storeOpInsts.empty()) return loopDepth; // Check dependences on all pairs of ops in 'ops' and store the minimum // loop depth at which a dependence is satisfied. for (unsigned i = 0, e = ops.size(); i < e; ++i) { auto *srcOpInst = ops[i]; MemRefAccess srcAccess(srcOpInst); for (unsigned j = 0; j < e; ++j) { auto *dstOpInst = ops[j]; MemRefAccess dstAccess(dstOpInst); unsigned numCommonLoops = getNumCommonSurroundingLoops(*srcOpInst, *dstOpInst); for (unsigned d = 1; d <= numCommonLoops + 1; ++d) { FlatAffineConstraints dependenceConstraints; // TODO(andydavis) Cache dependence analysis results, check cache here. if (checkMemrefAccessDependence(srcAccess, dstAccess, d, &dependenceConstraints, /*dependenceComponents=*/nullptr)) { // Store minimum loop depth and break because we want the min 'd' at // which there is a dependence. loopDepth = std::min(loopDepth, d - 1); break; } } } } return loopDepth; } // Returns the slice union of 'sliceStateA' and 'sliceStateB' in 'sliceStateB' // using a rectangular bounding box. // TODO(andydavis) This function assumes that lower bounds for 'sliceStateA' // and 'sliceStateB' are aligned. // Specifically, when taking the union of overlapping intervals, it assumes // that both intervals start at zero. Support needs to be added to take into // account interval start offset when computing the union. // TODO(andydavis) Move this function to an analysis library. static bool getSliceUnion(const ComputationSliceState &sliceStateA, ComputationSliceState *sliceStateB) { assert(sliceStateA.lbs.size() == sliceStateB->lbs.size()); assert(sliceStateA.ubs.size() == sliceStateB->ubs.size()); for (unsigned i = 0, e = sliceStateA.lbs.size(); i < e; ++i) { AffineMap lbMapA = sliceStateA.lbs[i]; AffineMap ubMapA = sliceStateA.ubs[i]; if (lbMapA == AffineMap()) { assert(ubMapA == AffineMap()); continue; } assert(ubMapA && "expected non-null ub map"); AffineMap lbMapB = sliceStateB->lbs[i]; AffineMap ubMapB = sliceStateB->ubs[i]; if (lbMapB == AffineMap()) { assert(ubMapB == AffineMap()); // Union 'sliceStateB' does not have a bound for 'i' so copy from A. sliceStateB->lbs[i] = lbMapA; sliceStateB->ubs[i] = ubMapA; continue; } // TODO(andydavis) Change this code to take the min across all lower bounds // and max across all upper bounds for each dimension. This code can for // cases where a unique min or max could not be statically determined. // Assumption: both lower bounds are the same. if (lbMapA != lbMapB) return false; // Add bound with the largest trip count to union. Optional tripCountA = getConstDifference(lbMapA, ubMapA); Optional tripCountB = getConstDifference(lbMapB, ubMapB); if (!tripCountA.hasValue() || !tripCountB.hasValue()) return false; if (tripCountA.getValue() > tripCountB.getValue()) { sliceStateB->lbs[i] = lbMapA; sliceStateB->ubs[i] = ubMapA; } } return true; } // Creates and returns a private (single-user) memref for fused loop rooted // at 'forInst', with (potentially reduced) memref size based on the // MemRefRegion written to by 'srcStoreOpInst' at depth 'dstLoopDepth'. // TODO(bondhugula): consider refactoring the common code from generateDma and // this one. static Value *createPrivateMemRef(ForInst *forInst, OperationInst *srcStoreOpInst, unsigned dstLoopDepth) { // Create builder to insert alloc op just before 'forInst'. FuncBuilder b(forInst); // Builder to create constants at the top level. FuncBuilder top(forInst->getFunction()); // Create new memref type based on slice bounds. auto *oldMemRef = srcStoreOpInst->cast()->getMemRef(); auto oldMemRefType = oldMemRef->getType().cast(); unsigned rank = oldMemRefType.getRank(); // Compute MemRefRegion for 'srcStoreOpInst' at depth 'dstLoopDepth'. MemRefRegion region; getMemRefRegion(srcStoreOpInst, dstLoopDepth, ®ion); SmallVector newShape; std::vector> lbs; SmallVector lbDivisors; lbs.reserve(rank); // Query 'region' for 'newShape' and lower bounds of MemRefRegion accessed // by 'srcStoreOpInst' at depth 'dstLoopDepth'. Optional numElements = region.getConstantBoundingSizeAndShape(&newShape, &lbs, &lbDivisors); assert(numElements.hasValue()); const FlatAffineConstraints *cst = region.getConstraints(); // 'outerIVs' holds the values that this memory region is symbolic/paramteric // on; this would correspond to loop IVs surrounding the level at which the // slice is being materialized. SmallVector outerIVs; cst->getIdValues(rank, cst->getNumIds(), &outerIVs); // Build 'rank' AffineExprs from MemRefRegion 'lbs' SmallVector offsets; offsets.reserve(rank); for (unsigned d = 0; d < rank; ++d) { assert(lbs[d].size() == cst->getNumCols() - rank && "incorrect bound size"); AffineExpr offset = top.getAffineConstantExpr(0); for (unsigned j = 0, e = cst->getNumCols() - rank - 1; j < e; j++) { offset = offset + lbs[d][j] * top.getAffineDimExpr(j); } assert(lbDivisors[d] > 0); offset = (offset + lbs[d][cst->getNumCols() - 1 - rank]).floorDiv(lbDivisors[d]); offsets.push_back(offset); } // Create 'newMemRefType' using 'newShape' from MemRefRegion accessed // by 'srcStoreOpInst'. auto newMemRefType = top.getMemRefType(newShape, oldMemRefType.getElementType(), {}, oldMemRefType.getMemorySpace()); // Gather alloc operands for the dynamic dimensions of the memref. SmallVector allocOperands; unsigned dynamicDimCount = 0; for (auto dimSize : oldMemRefType.getShape()) { if (dimSize == -1) allocOperands.push_back( top.create(forInst->getLoc(), oldMemRef, dynamicDimCount++)); } // Create new private memref for fused loop 'forInst'. // TODO(andydavis) Create/move alloc ops for private memrefs closer to their // consumer loop nests to reduce their live range. Currently they are added // at the beginning of the function, because loop nests can be reordered // during the fusion pass. Value *newMemRef = top.create(forInst->getLoc(), newMemRefType, allocOperands); // Build an AffineMap to remap access functions based on lower bound offsets. SmallVector remapExprs; remapExprs.reserve(rank); unsigned zeroOffsetCount = 0; for (unsigned i = 0; i < rank; i++) { if (auto constExpr = offsets[i].dyn_cast()) if (constExpr.getValue() == 0) ++zeroOffsetCount; auto dimExpr = b.getAffineDimExpr(outerIVs.size() + i); auto remapExpr = simplifyAffineExpr(dimExpr - offsets[i], outerIVs.size() + rank, 0); remapExprs.push_back(remapExpr); } auto indexRemap = zeroOffsetCount == rank ? AffineMap() : b.getAffineMap(outerIVs.size() + rank, 0, remapExprs, {}); // Replace all users of 'oldMemRef' with 'newMemRef'. bool ret = replaceAllMemRefUsesWith(oldMemRef, newMemRef, {}, indexRemap, /*extraOperands=*/outerIVs, /*domInstFilter=*/&*forInst->getBody()->begin()); assert(ret && "replaceAllMemrefUsesWith should always succeed here"); (void)ret; return newMemRef; } // Does the slice have a single iteration? static uint64_t getSliceIterationCount( const llvm::SmallDenseMap &sliceTripCountMap) { uint64_t iterCount = 1; for (const auto &count : sliceTripCountMap) { iterCount *= count.second; } return iterCount; } // Checks the profitability of fusing a backwards slice of the loop nest // surrounding 'srcOpInst' into the loop nest surrounding 'dstLoadOpInsts'. // Returns true if it is profitable to fuse the candidate loop nests. Returns // false otherwise. `dstLoopDepth` is set to the most profitable depth at which // to materialize the source loop nest slice. // The profitability model executes the following steps: // *) Computes the backward computation slice at 'srcOpInst'. This // computation slice of the loop nest surrounding 'srcOpInst' is // represented by modified src loop bounds in 'sliceState', which are // functions of loop IVs in the loop nest surrounding 'srcOpInst'. // *) Computes the cost of unfused src/dst loop nests (currently the cost of a // loop nest is the total number of dynamic operation instances in the loop // nest). // *) Computes the cost of fusing a slice of the src loop nest into the dst // loop nest at various values of dst loop depth, attempting to fuse // the largest compution slice at the maximal dst loop depth (closest to the // load) to minimize reuse distance and potentially enable subsequent // load/store forwarding. // NOTE: If the dst loop nest includes multiple loads in 'dstLoadOpInsts' for // the same memref as is written by 'srcOpInst', then the union of slice // loop bounds is used to compute the slice and associated slice cost. // NOTE: 'dstLoopDepth' refers to the loop depth within the destination loop // nest, at which the src computation slice is inserted/fused. // NOTE: We attempt to maximize the dst loop depth, but there are cases // where a particular setting for 'dstLoopNest' might fuse an unsliced // loop (within the src computation slice) at a depth which results in // execessive recomputation (see unit tests for examples). // *) Compares the total cost of the unfused loop nests to the min cost fused // loop nest computed in the previous step, and returns true if the latter // is lower. static bool isFusionProfitable(OperationInst *srcOpInst, ArrayRef dstLoadOpInsts, ArrayRef dstStoreOpInsts, ComputationSliceState *sliceState, unsigned *dstLoopDepth) { LLVM_DEBUG({ llvm::dbgs() << "Checking whether fusion is profitable between:\n"; llvm::dbgs() << " "; srcOpInst->dump(); llvm::dbgs() << " and \n"; for (auto dstOpInst : dstLoadOpInsts) { llvm::dbgs() << " "; dstOpInst->dump(); }; }); // Compute cost of sliced and unsliced src loop nest. SmallVector srcLoopIVs; getLoopIVs(*srcOpInst, &srcLoopIVs); unsigned numSrcLoopIVs = srcLoopIVs.size(); // Walk src loop nest and collect stats. LoopNestStats srcLoopNestStats; LoopNestStatsCollector srcStatsCollector(&srcLoopNestStats); srcStatsCollector.walk(srcLoopIVs[0]); // Currently only constant trip count loop nests are supported. if (srcStatsCollector.hasLoopWithNonConstTripCount) return false; // Compute cost of dst loop nest. SmallVector dstLoopIVs; getLoopIVs(*dstLoadOpInsts[0], &dstLoopIVs); LoopNestStats dstLoopNestStats; LoopNestStatsCollector dstStatsCollector(&dstLoopNestStats); dstStatsCollector.walk(dstLoopIVs[0]); // Currently only constant trip count loop nests are supported. if (dstStatsCollector.hasLoopWithNonConstTripCount) return false; // Compute the maximum loop depth at which we can can insert the src slice // and still satisfy dest loop nest dependences. unsigned maxDstLoopDepth = getMaxLoopDepth(dstLoadOpInsts, dstStoreOpInsts); if (maxDstLoopDepth == 0) return false; // Search for min cost value for 'dstLoopDepth'. At each value of // 'dstLoopDepth' from 'maxDstLoopDepth' to '1', compute computation slice // bounds between 'srcOpInst' and each op in 'dstOpinsts' (taking the union // of these bounds). Next the union slice bounds are used to calculate // the cost of the slice and the cost of the slice inserted into the dst // loop nest at 'dstLoopDepth'. uint64_t minFusedLoopNestComputeCost = std::numeric_limits::max(); uint64_t maxStorageReduction = 0; Optional sliceMemEstimate = None; SmallVector sliceStates; sliceStates.resize(maxDstLoopDepth); // The best loop depth at which to materialize the slice. Optional bestDstLoopDepth = None; // Compute op instance count for the src loop nest without iteration slicing. uint64_t srcLoopNestCost = getComputeCost(srcLoopIVs[0], &srcLoopNestStats, /*tripCountOverrideMap=*/nullptr, /*computeCostMap=*/nullptr); // Compute op instance count for the src loop nest. uint64_t dstLoopNestCost = getComputeCost(dstLoopIVs[0], &dstLoopNestStats, /*tripCountOverrideMap=*/nullptr, /*computeCostMap=*/nullptr); llvm::SmallDenseMap sliceTripCountMap; DenseMap computeCostMap; for (unsigned i = maxDstLoopDepth; i >= 1; --i) { MemRefAccess srcAccess(srcOpInst); // Handle the common case of one dst load without a copy. if (!mlir::getBackwardComputationSliceState( srcAccess, MemRefAccess(dstLoadOpInsts[0]), i, &sliceStates[i - 1])) return false; // Compute the union of slice bound of all ops in 'dstLoadOpInsts'. for (int j = 1, e = dstLoadOpInsts.size(); j < e; ++j) { MemRefAccess dstAccess(dstLoadOpInsts[j]); ComputationSliceState tmpSliceState; if (!mlir::getBackwardComputationSliceState(srcAccess, dstAccess, i, &tmpSliceState)) return false; // Compute slice boun dunion of 'tmpSliceState' and 'sliceStates[i - 1]'. getSliceUnion(tmpSliceState, &sliceStates[i - 1]); } // Build trip count map for computation slice. We'll skip cases where the // trip count was non-constant. sliceTripCountMap.clear(); if (!buildSliceTripCountMap(srcOpInst, &sliceStates[i - 1], &sliceTripCountMap)) continue; // Checks whether a store to load forwarding will happen. int64_t sliceIterationCount = getSliceIterationCount(sliceTripCountMap); assert(sliceIterationCount > 0); bool storeLoadFwdGuaranteed = (sliceIterationCount == 1); // Compute cost of fusion for this dest loop depth. computeCostMap.clear(); // The store and loads to this memref will disappear. if (storeLoadFwdGuaranteed) { // A single store disappears: -1 for that. computeCostMap[srcLoopIVs[numSrcLoopIVs - 1]] = -1; for (auto *loadOp : dstLoadOpInsts) { if (auto *loadLoop = dyn_cast_or_null(loadOp->getParentInst())) computeCostMap[loadLoop] = -1; } } // Compute op instance count for the src loop nest with iteration slicing. int64_t sliceComputeCost = getComputeCost(srcLoopIVs[0], &srcLoopNestStats, /*tripCountOverrideMap=*/&sliceTripCountMap, /*computeCostMap=*/&computeCostMap); // Compute cost of fusion for this depth. computeCostMap[dstLoopIVs[i - 1]] = sliceComputeCost; int64_t fusedLoopNestComputeCost = getComputeCost(dstLoopIVs[0], &dstLoopNestStats, /*tripCountOverrideMap=*/nullptr, &computeCostMap); double additionalComputeFraction = fusedLoopNestComputeCost / (static_cast(srcLoopNestCost) + dstLoopNestCost) - 1; // TODO(bondhugula): This is an ugly approximation. Fix this by finding a // good way to calculate the footprint of the memref in the slice and // divide it by the total memory footprint of the fused computation. double storageReduction = static_cast(srcLoopNestCost) / sliceIterationCount; LLVM_DEBUG({ std::stringstream msg; msg << " evaluating fusion profitability at depth : " << i << "\n" << std::setprecision(2) << " additional compute fraction: " << 100.0 * additionalComputeFraction << "%\n" << " storage reduction factor: " << storageReduction << "x\n" << " fused nest cost: " << fusedLoopNestComputeCost << "\n" << " slice iteration count: " << sliceIterationCount << "\n"; llvm::dbgs() << msg.str(); }); double computeToleranceThreshold = clFusionAddlComputeTolerance.getNumOccurrences() > 0 ? clFusionAddlComputeTolerance : LoopFusion::kComputeToleranceThreshold; // TODO(b/123247369): This is a placeholder cost model. // Among all choices that add an acceptable amount of redundant computation // (as per computeToleranceThreshold), we will simply pick the one that // reduces the intermediary size the most. if ((storageReduction > maxStorageReduction) && (clMaximalLoopFusion || (additionalComputeFraction < computeToleranceThreshold))) { maxStorageReduction = storageReduction; bestDstLoopDepth = i; minFusedLoopNestComputeCost = fusedLoopNestComputeCost; // TODO(bondhugula,andydavis): find a good way to compute the memory // footprint of the materialized slice. // Approximating this to the compute cost of the slice. This could be an // under-approximation or an overapproximation, but in many cases // accurate. sliceMemEstimate = sliceIterationCount; } } // A simple cost model: fuse if it reduces the memory footprint. If // -maximal-fusion is set, fuse nevertheless. if (!clMaximalLoopFusion && !bestDstLoopDepth.hasValue()) { LLVM_DEBUG(llvm::dbgs() << "All fusion choices involve more than the threshold amount of" "redundant computation; NOT fusing.\n"); return false; } assert(bestDstLoopDepth.hasValue() && "expected to have a value per logic above"); // Set dstLoopDepth based on best values from search. *dstLoopDepth = bestDstLoopDepth.getValue(); LLVM_DEBUG( llvm::dbgs() << " LoopFusion fusion stats:" << "\n best loop depth: " << bestDstLoopDepth << "\n src loop nest compute cost: " << srcLoopNestCost << "\n dst loop nest compute cost: " << dstLoopNestCost << "\n fused loop nest compute cost: " << minFusedLoopNestComputeCost << "\n"); auto dstMemSize = getMemoryFootprintBytes(*dstLoopIVs[0]); auto srcMemSize = getMemoryFootprintBytes(*srcLoopIVs[0]); Optional storageReduction = None; if (!clMaximalLoopFusion) { if (!dstMemSize.hasValue() || !srcMemSize.hasValue()) { LLVM_DEBUG( llvm::dbgs() << " fusion memory benefit cannot be evaluated; NOT fusing.\n"); return false; } auto srcMemSizeVal = srcMemSize.getValue(); auto dstMemSizeVal = dstMemSize.getValue(); assert(sliceMemEstimate.hasValue() && "expected value"); // This is an inaccurate estimate since sliceMemEstimate is isaccurate. auto fusedMem = dstMemSizeVal + sliceMemEstimate.getValue(); LLVM_DEBUG(llvm::dbgs() << " src mem: " << srcMemSizeVal << "\n" << " dst mem: " << dstMemSizeVal << "\n" << " fused mem: " << fusedMem << "\n" << " slice mem: " << sliceMemEstimate << "\n"); if (fusedMem > srcMemSizeVal + dstMemSizeVal) { LLVM_DEBUG(llvm::dbgs() << "Fusion is not profitable; NOT fusing.\n"); return false; } storageReduction = 100.0 * (1.0 - fusedMem / (static_cast(srcMemSizeVal) + dstMemSizeVal)); } double additionalComputeFraction = 100.0 * (minFusedLoopNestComputeCost / (static_cast(srcLoopNestCost) + dstLoopNestCost) - 1); (void)additionalComputeFraction; LLVM_DEBUG({ std::stringstream msg; msg << " fusion is most profitable at depth " << *dstLoopDepth << " with " << setprecision(2) << additionalComputeFraction << "% redundant computation and a "; msg << (storageReduction.hasValue() ? std::to_string(storageReduction.getValue()) : ""); msg << "% storage reduction.\n"; llvm::dbgs() << msg.str(); }); // Update return parameter 'sliceState' with 'bestSliceState'. ComputationSliceState *bestSliceState = &sliceStates[*dstLoopDepth - 1]; sliceState->lbs = bestSliceState->lbs; sliceState->ubs = bestSliceState->ubs; sliceState->lbOperands = bestSliceState->lbOperands; sliceState->ubOperands = bestSliceState->ubOperands; // Canonicalize slice bound affine maps. for (unsigned i = 0; i < numSrcLoopIVs; ++i) { if (sliceState->lbs[i] != AffineMap()) { canonicalizeMapAndOperands(&sliceState->lbs[i], &sliceState->lbOperands[i]); } if (sliceState->ubs[i] != AffineMap()) { canonicalizeMapAndOperands(&sliceState->ubs[i], &sliceState->ubOperands[i]); } } return true; } // GreedyFusion greedily fuses loop nests which have a producer/consumer // relationship on a memref, with the goal of improving locality. Currently, // this the producer/consumer relationship is required to be unique in the // Function (there are TODOs to relax this constraint in the future). // // The steps of the algorithm are as follows: // // *) A worklist is initialized with node ids from the dependence graph. // *) For each node id in the worklist: // *) Pop a ForInst of the worklist. This 'dstForInst' will be a candidate // destination ForInst into which fusion will be attempted. // *) Add each LoadOp currently in 'dstForInst' into list 'dstLoadOps'. // *) For each LoadOp in 'dstLoadOps' do: // *) Lookup dependent loop nests at earlier positions in the Function // which have a single store op to the same memref. // *) Check if dependences would be violated by the fusion. For example, // the src loop nest may load from memrefs which are different than // the producer-consumer memref between src and dest loop nests. // *) Get a computation slice of 'srcLoopNest', which adjusts its loop // bounds to be functions of 'dstLoopNest' IVs and symbols. // *) Fuse the 'srcLoopNest' computation slice into the 'dstLoopNest', // just before the dst load op user. // *) Add the newly fused load/store operation instructions to the state, // and also add newly fuse load ops to 'dstLoopOps' to be considered // as fusion dst load ops in another iteration. // *) Remove old src loop nest and its associated state. // // Given a graph where top-level instructions are vertices in the set 'V' and // edges in the set 'E' are dependences between vertices, this algorithm // takes O(V) time for initialization, and has runtime O(V + E). // // This greedy algorithm is not 'maximal' due to the current restriction of // fusing along single producer consumer edges, but there is a TODO to fix this. // // TODO(andydavis) Experiment with other fusion policies. // TODO(andydavis) Add support for fusing for input reuse (perhaps by // constructing a graph with edges which represent loads from the same memref // in two different loop nests. struct GreedyFusion { public: MemRefDependenceGraph *mdg; SmallVector worklist; GreedyFusion(MemRefDependenceGraph *mdg) : mdg(mdg) { // Initialize worklist with nodes from 'mdg'. worklist.resize(mdg->nodes.size()); std::iota(worklist.begin(), worklist.end(), 0); } void run() { while (!worklist.empty()) { unsigned dstId = worklist.back(); worklist.pop_back(); // Skip if this node was removed (fused into another node). if (mdg->nodes.count(dstId) == 0) continue; // Get 'dstNode' into which to attempt fusion. auto *dstNode = mdg->getNode(dstId); // Skip if 'dstNode' is not a loop nest. if (!isa(dstNode->inst)) continue; SmallVector loads = dstNode->loads; SmallVector dstLoadOpInsts; DenseSet visitedMemrefs; while (!loads.empty()) { // Get memref of load on top of the stack. auto *memref = loads.back()->cast()->getMemRef(); if (visitedMemrefs.count(memref) > 0) continue; visitedMemrefs.insert(memref); // Move all loads in 'loads' accessing 'memref' to 'dstLoadOpInsts'. moveLoadsAccessingMemrefTo(memref, &loads, &dstLoadOpInsts); // Skip if no input edges along which to fuse. if (mdg->inEdges.count(dstId) == 0) continue; // Iterate through in edges for 'dstId' and src node id for any // edges on 'memref'. SmallVector srcNodeIds; for (auto &srcEdge : mdg->inEdges[dstId]) { // Skip 'srcEdge' if not for 'memref'. if (srcEdge.value != memref) continue; srcNodeIds.push_back(srcEdge.id); } for (unsigned srcId : srcNodeIds) { // Skip if this node was removed (fused into another node). if (mdg->nodes.count(srcId) == 0) continue; // Get 'srcNode' from which to attempt fusion into 'dstNode'. auto *srcNode = mdg->getNode(srcId); // Skip if 'srcNode' is not a loop nest. if (!isa(srcNode->inst)) continue; // Skip if 'srcNode' has more than one store to any memref. // TODO(andydavis) Support fusing multi-output src loop nests. if (srcNode->stores.size() != 1) continue; // Skip 'srcNode' if it has in edges on 'memref'. // TODO(andydavis) Track dependence type with edges, and just check // for WAW dependence edge here. Note that this check is overly // conservative and will be removed in the future. if (mdg->getIncomingMemRefAccesses(srcNode->id, memref) != 0) continue; // Skip if 'srcNode' writes to any live in or escaping memrefs. if (mdg->writesToLiveInOrEscapingMemrefs(srcNode->id)) continue; // Compute an instruction list insertion point for the fused loop // nest which preserves dependences. Instruction *insertPointInst = mdg->getFusedLoopNestInsertionPoint( srcNode->id, dstNode->id, memref); if (insertPointInst == nullptr) continue; // Get unique 'srcNode' store op. auto *srcStoreOpInst = srcNode->stores.front(); // Gather 'dstNode' store ops to 'memref'. SmallVector dstStoreOpInsts; for (auto *storeOpInst : dstNode->stores) if (storeOpInst->cast()->getMemRef() == memref) dstStoreOpInsts.push_back(storeOpInst); unsigned bestDstLoopDepth; mlir::ComputationSliceState sliceState; // Check if fusion would be profitable. if (!isFusionProfitable(srcStoreOpInst, dstLoadOpInsts, dstStoreOpInsts, &sliceState, &bestDstLoopDepth)) continue; // Fuse computation slice of 'srcLoopNest' into 'dstLoopNest'. auto *sliceLoopNest = mlir::insertBackwardComputationSlice( srcStoreOpInst, dstLoadOpInsts[0], bestDstLoopDepth, &sliceState); if (sliceLoopNest != nullptr) { // Move 'dstForInst' before 'insertPointInst' if needed. auto *dstForInst = cast(dstNode->inst); if (insertPointInst != dstForInst) { dstForInst->moveBefore(insertPointInst); } // Update edges between 'srcNode' and 'dstNode'. mdg->updateEdges(srcNode->id, dstNode->id, memref); // Collect slice loop stats. LoopNestStateCollector sliceCollector; sliceCollector.walkForInst(sliceLoopNest); // Promote single iteration slice loops to single IV value. for (auto *forInst : sliceCollector.forInsts) { promoteIfSingleIteration(forInst); } // Create private memref for 'memref' in 'dstForInst'. SmallVector storesForMemref; for (auto *storeOpInst : sliceCollector.storeOpInsts) { if (storeOpInst->cast()->getMemRef() == memref) storesForMemref.push_back(storeOpInst); } assert(storesForMemref.size() == 1); auto *newMemRef = createPrivateMemRef( dstForInst, storesForMemref[0], bestDstLoopDepth); visitedMemrefs.insert(newMemRef); // Create new node in dependence graph for 'newMemRef' alloc op. unsigned newMemRefNodeId = mdg->addNode(newMemRef->getDefiningInst()); // Add edge from 'newMemRef' node to dstNode. mdg->addEdge(newMemRefNodeId, dstId, newMemRef); // Collect dst loop stats after memref privatizaton transformation. LoopNestStateCollector dstLoopCollector; dstLoopCollector.walkForInst(dstForInst); // Add new load ops to current Node load op list 'loads' to // continue fusing based on new operands. for (auto *loadOpInst : dstLoopCollector.loadOpInsts) { auto *loadMemRef = loadOpInst->cast()->getMemRef(); if (visitedMemrefs.count(loadMemRef) == 0) loads.push_back(loadOpInst); } // Clear and add back loads and stores mdg->clearNodeLoadAndStores(dstNode->id); mdg->addToNode(dstId, dstLoopCollector.loadOpInsts, dstLoopCollector.storeOpInsts); // Remove old src loop nest if it no longer has outgoing dependence // edges, and it does not write to a memref which escapes the // function. if (mdg->canRemoveNode(srcNode->id)) { mdg->removeNode(srcNode->id); cast(srcNode->inst)->erase(); } } } } } // Clean up any allocs with no users. for (auto &pair : mdg->memrefEdgeCount) { if (pair.second > 0) continue; auto *memref = pair.first; // Skip if there exist other uses (return instruction or function calls). if (!memref->use_empty()) continue; // Use list expected to match the dep graph info. auto *inst = memref->getDefiningInst(); auto *opInst = dyn_cast_or_null(inst); if (opInst && opInst->isa()) opInst->erase(); } } }; } // end anonymous namespace PassResult LoopFusion::runOnFunction(Function *f) { MemRefDependenceGraph g; if (g.init(f)) GreedyFusion(&g).run(); return success(); } static PassRegistration pass("loop-fusion", "Fuse loop nests");