560 lines
21 KiB
C++
560 lines
21 KiB
C++
//===- 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/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/StmtVisitor.h"
|
|
#include "mlir/Pass.h"
|
|
#include "mlir/StandardOps/StandardOps.h"
|
|
#include "mlir/Transforms/LoopUtils.h"
|
|
#include "mlir/Transforms/Passes.h"
|
|
#include "llvm/ADT/DenseMap.h"
|
|
#include "llvm/ADT/DenseSet.h"
|
|
#include "llvm/ADT/SetVector.h"
|
|
#include "llvm/Support/CommandLine.h"
|
|
#include "llvm/Support/raw_ostream.h"
|
|
|
|
using llvm::SetVector;
|
|
|
|
using namespace mlir;
|
|
|
|
// TODO(andydavis) These flags are global for the pass to be used for
|
|
// experimentation. Find a way to provide more fine grained control (i.e.
|
|
// depth per-loop nest, or depth per load/store op) for this pass utilizing a
|
|
// cost model.
|
|
static llvm::cl::opt<unsigned> clSrcLoopDepth(
|
|
"src-loop-depth", llvm::cl::Hidden,
|
|
llvm::cl::desc("Controls the depth of the source loop nest at which "
|
|
"to apply loop iteration slicing before fusion."));
|
|
|
|
static llvm::cl::opt<unsigned> clDstLoopDepth(
|
|
"dst-loop-depth", llvm::cl::Hidden,
|
|
llvm::cl::desc("Controls the depth of the destination loop nest at which "
|
|
"to fuse the source loop nest slice."));
|
|
|
|
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 runOnMLFunction(MLFunction *f) override;
|
|
static char passID;
|
|
};
|
|
|
|
} // end anonymous namespace
|
|
|
|
char LoopFusion::passID = 0;
|
|
|
|
FunctionPass *mlir::createLoopFusionPass() { return new LoopFusion; }
|
|
|
|
static void getSingleMemRefAccess(OperationStmt *loadOrStoreOpStmt,
|
|
MemRefAccess *access) {
|
|
if (auto loadOp = loadOrStoreOpStmt->dyn_cast<LoadOp>()) {
|
|
access->memref = loadOp->getMemRef();
|
|
access->opStmt = loadOrStoreOpStmt;
|
|
auto loadMemrefType = loadOp->getMemRefType();
|
|
access->indices.reserve(loadMemrefType.getRank());
|
|
for (auto *index : loadOp->getIndices()) {
|
|
access->indices.push_back(index);
|
|
}
|
|
} else {
|
|
assert(loadOrStoreOpStmt->isa<StoreOp>());
|
|
auto storeOp = loadOrStoreOpStmt->dyn_cast<StoreOp>();
|
|
access->opStmt = loadOrStoreOpStmt;
|
|
access->memref = storeOp->getMemRef();
|
|
auto storeMemrefType = storeOp->getMemRefType();
|
|
access->indices.reserve(storeMemrefType.getRank());
|
|
for (auto *index : storeOp->getIndices()) {
|
|
access->indices.push_back(index);
|
|
}
|
|
}
|
|
}
|
|
|
|
// FusionCandidate encapsulates source and destination memref access within
|
|
// loop nests which are candidates for loop fusion.
|
|
struct FusionCandidate {
|
|
// Load or store access within src loop nest to be fused into dst loop nest.
|
|
MemRefAccess srcAccess;
|
|
// Load or store access within dst loop nest.
|
|
MemRefAccess dstAccess;
|
|
};
|
|
|
|
static FusionCandidate buildFusionCandidate(OperationStmt *srcStoreOpStmt,
|
|
OperationStmt *dstLoadOpStmt) {
|
|
FusionCandidate candidate;
|
|
// Get store access for src loop nest.
|
|
getSingleMemRefAccess(srcStoreOpStmt, &candidate.srcAccess);
|
|
// Get load access for dst loop nest.
|
|
getSingleMemRefAccess(dstLoadOpStmt, &candidate.dstAccess);
|
|
return candidate;
|
|
}
|
|
|
|
// Returns the loop depth of the loop nest surrounding 'opStmt'.
|
|
static unsigned getLoopDepth(OperationStmt *opStmt) {
|
|
unsigned loopDepth = 0;
|
|
auto *currStmt = opStmt->getParentStmt();
|
|
ForStmt *currForStmt;
|
|
while (currStmt && (currForStmt = dyn_cast<ForStmt>(currStmt))) {
|
|
++loopDepth;
|
|
currStmt = currStmt->getParentStmt();
|
|
}
|
|
return loopDepth;
|
|
}
|
|
|
|
namespace {
|
|
|
|
// LoopNestStateCollector walks loop nests and collects load and store
|
|
// operations, and whether or not an IfStmt was encountered in the loop nest.
|
|
class LoopNestStateCollector : public StmtWalker<LoopNestStateCollector> {
|
|
public:
|
|
SmallVector<ForStmt *, 4> forStmts;
|
|
SmallVector<OperationStmt *, 4> loadOpStmts;
|
|
SmallVector<OperationStmt *, 4> storeOpStmts;
|
|
bool hasIfStmt = false;
|
|
|
|
void visitForStmt(ForStmt *forStmt) { forStmts.push_back(forStmt); }
|
|
|
|
void visitIfStmt(IfStmt *ifStmt) { hasIfStmt = true; }
|
|
|
|
void visitOperationStmt(OperationStmt *opStmt) {
|
|
if (opStmt->isa<LoadOp>())
|
|
loadOpStmts.push_back(opStmt);
|
|
if (opStmt->isa<StoreOp>())
|
|
storeOpStmts.push_back(opStmt);
|
|
}
|
|
};
|
|
|
|
// MemRefDependenceGraph is a graph data structure where graph nodes are
|
|
// top-level statements in an MLFunction which contain load/store ops, and edges
|
|
// are memref dependences between the nodes.
|
|
// 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.
|
|
Statement *stmt;
|
|
// List of load op stmts.
|
|
SmallVector<OperationStmt *, 4> loads;
|
|
// List of store op stmts.
|
|
SmallVector<OperationStmt *, 4> stores;
|
|
Node(unsigned id, Statement *stmt) : id(id), stmt(stmt) {}
|
|
|
|
// Returns the load op count for 'memref'.
|
|
unsigned getLoadOpCount(Value *memref) {
|
|
unsigned loadOpCount = 0;
|
|
for (auto *loadOpStmt : loads) {
|
|
if (memref == loadOpStmt->cast<LoadOp>()->getMemRef())
|
|
++loadOpCount;
|
|
}
|
|
return loadOpCount;
|
|
}
|
|
|
|
// Returns the store op count for 'memref'.
|
|
unsigned getStoreOpCount(Value *memref) {
|
|
unsigned storeOpCount = 0;
|
|
for (auto *storeOpStmt : stores) {
|
|
if (memref == storeOpStmt->cast<StoreOp>()->getMemRef())
|
|
++storeOpCount;
|
|
}
|
|
return storeOpCount;
|
|
}
|
|
};
|
|
|
|
// Edge represents a memref data dependece between nodes in the graph.
|
|
struct Edge {
|
|
// The id of the node at the other end of the edge.
|
|
unsigned id;
|
|
// The memref on which this edge represents a dependence.
|
|
Value *memref;
|
|
};
|
|
|
|
// Map from node id to Node.
|
|
DenseMap<unsigned, Node> nodes;
|
|
// Map from node id to list of input edges.
|
|
DenseMap<unsigned, SmallVector<Edge, 2>> inEdges;
|
|
// Map from node id to list of output edges.
|
|
DenseMap<unsigned, SmallVector<Edge, 2>> outEdges;
|
|
|
|
MemRefDependenceGraph() {}
|
|
|
|
// Initializes the dependence graph based on operations in 'f'.
|
|
// Returns true on success, false otherwise.
|
|
bool init(MLFunction *f);
|
|
|
|
// Returns the graph node for 'id'.
|
|
Node *getNode(unsigned id) {
|
|
auto it = nodes.find(id);
|
|
assert(it != nodes.end());
|
|
return &it->second;
|
|
}
|
|
|
|
// Adds an edge from node 'srcId' to node 'dstId' for 'memref'.
|
|
void addEdge(unsigned srcId, unsigned dstId, Value *memref) {
|
|
outEdges[srcId].push_back({dstId, memref});
|
|
inEdges[dstId].push_back({srcId, memref});
|
|
}
|
|
|
|
// Removes an edge from node 'srcId' to node 'dstId' for 'memref'.
|
|
void removeEdge(unsigned srcId, unsigned dstId, Value *memref) {
|
|
assert(inEdges.count(dstId) > 0);
|
|
assert(outEdges.count(srcId) > 0);
|
|
// Remove 'srcId' from 'inEdges[dstId]'.
|
|
for (auto it = inEdges[dstId].begin(); it != inEdges[dstId].end(); ++it) {
|
|
if ((*it).id == srcId && (*it).memref == memref) {
|
|
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).memref == memref) {
|
|
outEdges[srcId].erase(it);
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
|
|
// Returns the input edge count for node 'id' and 'memref'.
|
|
unsigned getInEdgeCount(unsigned id, Value *memref) {
|
|
unsigned inEdgeCount = 0;
|
|
if (inEdges.count(id) > 0)
|
|
for (auto &inEdge : inEdges[id])
|
|
if (inEdge.memref == memref)
|
|
++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.memref == memref)
|
|
++outEdgeCount;
|
|
return outEdgeCount;
|
|
}
|
|
|
|
// Returns the min node id of all output edges from node 'id'.
|
|
unsigned getMinOutEdgeNodeId(unsigned id) {
|
|
unsigned minId = std::numeric_limits<unsigned>::max();
|
|
if (outEdges.count(id) > 0)
|
|
for (auto &outEdge : outEdges[id])
|
|
minId = std::min(minId, outEdge.id);
|
|
return minId;
|
|
}
|
|
|
|
// Updates edge mappings from node 'srcId' to node 'dstId' and removes
|
|
// state associated with node 'srcId'.
|
|
void updateEdgesAndRemoveSrcNode(unsigned srcId, unsigned dstId) {
|
|
// For each edge in 'inEdges[srcId]': add new edge remaping to 'dstId'.
|
|
if (inEdges.count(srcId) > 0) {
|
|
SmallVector<Edge, 2> oldInEdges = inEdges[srcId];
|
|
for (auto &inEdge : oldInEdges) {
|
|
// Remove edge from 'inEdge.id' to 'srcId'.
|
|
removeEdge(inEdge.id, srcId, inEdge.memref);
|
|
// Add edge from 'inEdge.id' to 'dstId'.
|
|
addEdge(inEdge.id, dstId, inEdge.memref);
|
|
}
|
|
}
|
|
// For each edge in 'outEdges[srcId]': add new edge remaping to 'dstId'.
|
|
if (outEdges.count(srcId) > 0) {
|
|
SmallVector<Edge, 2> oldOutEdges = outEdges[srcId];
|
|
for (auto &outEdge : oldOutEdges) {
|
|
// Remove edge from 'srcId' to 'outEdge.id'.
|
|
removeEdge(srcId, outEdge.id, outEdge.memref);
|
|
// Add edge from 'dstId' to 'outEdge.id' (if 'outEdge.id' != 'dstId').
|
|
if (outEdge.id != dstId)
|
|
addEdge(dstId, outEdge.id, outEdge.memref);
|
|
}
|
|
}
|
|
// Remove 'srcId' from graph state.
|
|
inEdges.erase(srcId);
|
|
outEdges.erase(srcId);
|
|
nodes.erase(srcId);
|
|
}
|
|
|
|
// Adds ops in 'loads' and 'stores' to node at 'id'.
|
|
void addToNode(unsigned id, const SmallVectorImpl<OperationStmt *> &loads,
|
|
const SmallVectorImpl<OperationStmt *> &stores) {
|
|
Node *node = getNode(id);
|
|
for (auto *loadOpStmt : loads)
|
|
node->loads.push_back(loadOpStmt);
|
|
for (auto *storeOpStmt : stores)
|
|
node->stores.push_back(storeOpStmt);
|
|
}
|
|
|
|
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.memref << "\n";
|
|
}
|
|
it = outEdges.find(idAndNode.first);
|
|
if (it != outEdges.end()) {
|
|
for (const auto &e : it->second)
|
|
os << " OutEdge: " << e.id << " " << e.memref << "\n";
|
|
}
|
|
}
|
|
}
|
|
void dump() const { print(llvm::errs()); }
|
|
};
|
|
|
|
// Intializes the data dependence graph by walking statements in 'f'.
|
|
// Assigns each node in the graph a node id based on program order in 'f'.
|
|
// TODO(andydavis) Add support for taking a StmtBlock arg to construct the
|
|
// dependence graph at a different depth.
|
|
bool MemRefDependenceGraph::init(MLFunction *f) {
|
|
unsigned id = 0;
|
|
DenseMap<Value *, SetVector<unsigned>> memrefAccesses;
|
|
for (auto &stmt : *f->getBody()) {
|
|
if (auto *forStmt = dyn_cast<ForStmt>(&stmt)) {
|
|
// Create graph node 'id' to represent top-level 'forStmt' and record
|
|
// all loads and store accesses it contains.
|
|
LoopNestStateCollector collector;
|
|
collector.walkForStmt(forStmt);
|
|
// Return false if IfStmts are found (not currently supported).
|
|
if (collector.hasIfStmt)
|
|
return false;
|
|
Node node(id++, &stmt);
|
|
for (auto *opStmt : collector.loadOpStmts) {
|
|
node.loads.push_back(opStmt);
|
|
auto *memref = opStmt->cast<LoadOp>()->getMemRef();
|
|
memrefAccesses[memref].insert(node.id);
|
|
}
|
|
for (auto *opStmt : collector.storeOpStmts) {
|
|
node.stores.push_back(opStmt);
|
|
auto *memref = opStmt->cast<StoreOp>()->getMemRef();
|
|
memrefAccesses[memref].insert(node.id);
|
|
}
|
|
nodes.insert({node.id, node});
|
|
}
|
|
if (auto *opStmt = dyn_cast<OperationStmt>(&stmt)) {
|
|
if (auto loadOp = opStmt->dyn_cast<LoadOp>()) {
|
|
// Create graph node for top-level load op.
|
|
Node node(id++, &stmt);
|
|
node.loads.push_back(opStmt);
|
|
auto *memref = opStmt->cast<LoadOp>()->getMemRef();
|
|
memrefAccesses[memref].insert(node.id);
|
|
nodes.insert({node.id, node});
|
|
}
|
|
if (auto storeOp = opStmt->dyn_cast<StoreOp>()) {
|
|
// Create graph node for top-level store op.
|
|
Node node(id++, &stmt);
|
|
node.stores.push_back(opStmt);
|
|
auto *memref = opStmt->cast<StoreOp>()->getMemRef();
|
|
memrefAccesses[memref].insert(node.id);
|
|
nodes.insert({node.id, node});
|
|
}
|
|
}
|
|
// Return false if IfStmts are found (not currently supported).
|
|
if (isa<IfStmt>(&stmt))
|
|
return false;
|
|
}
|
|
|
|
// 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;
|
|
}
|
|
|
|
// 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
|
|
// MLFunction (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 ForStmt of the worklist. This 'dstForStmt' will be a candidate
|
|
// destination ForStmt into which fusion will be attempted.
|
|
// *) Add each LoadOp currently in 'dstForStmt' into list 'dstLoadOps'.
|
|
// *) For each LoadOp in 'dstLoadOps' do:
|
|
// *) Lookup dependent loop nests at earlier positions in the MLFunction
|
|
// 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 statements 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 statements 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 nestst.
|
|
struct GreedyFusion {
|
|
public:
|
|
MemRefDependenceGraph *mdg;
|
|
SmallVector<unsigned, 4> 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<ForStmt>(dstNode->stmt))
|
|
continue;
|
|
|
|
SmallVector<OperationStmt *, 4> loads = dstNode->loads;
|
|
while (!loads.empty()) {
|
|
auto *dstLoadOpStmt = loads.pop_back_val();
|
|
auto *memref = dstLoadOpStmt->cast<LoadOp>()->getMemRef();
|
|
// Skip 'dstLoadOpStmt' if multiple loads to 'memref' in 'dstNode'.
|
|
if (dstNode->getLoadOpCount(memref) != 1)
|
|
continue;
|
|
// Skip if no input edges along which to fuse.
|
|
if (mdg->inEdges.count(dstId) == 0)
|
|
continue;
|
|
// Iterate through in edges for 'dstId'.
|
|
for (auto &srcEdge : mdg->inEdges[dstId]) {
|
|
// Skip 'srcEdge' if not for 'memref'.
|
|
if (srcEdge.memref != memref)
|
|
continue;
|
|
auto *srcNode = mdg->getNode(srcEdge.id);
|
|
// Skip if 'srcNode' is not a loop nest.
|
|
if (!isa<ForStmt>(srcNode->stmt))
|
|
continue;
|
|
// Skip if 'srcNode' has more than one store to 'memref'.
|
|
if (srcNode->getStoreOpCount(memref) != 1)
|
|
continue;
|
|
// Skip 'srcNode' if it has out edges on 'memref' other than 'dstId'.
|
|
if (mdg->getOutEdgeCount(srcNode->id, memref) != 1)
|
|
continue;
|
|
// Skip 'srcNode' if it has in dependence edges. NOTE: This is overly
|
|
// TODO(andydavis) Track dependence type with edges, and just check
|
|
// for WAW dependence edge here.
|
|
if (mdg->getInEdgeCount(srcNode->id, memref) != 0)
|
|
continue;
|
|
// Skip if 'srcNode' has out edges to other memrefs after 'dstId'.
|
|
if (mdg->getMinOutEdgeNodeId(srcNode->id) != dstId)
|
|
continue;
|
|
// Get unique 'srcNode' store op.
|
|
auto *srcStoreOpStmt = srcNode->stores.front();
|
|
// Build fusion candidate out of 'srcStoreOpStmt' and 'dstLoadOpStmt'.
|
|
FusionCandidate candidate =
|
|
buildFusionCandidate(srcStoreOpStmt, dstLoadOpStmt);
|
|
// Fuse computation slice of 'srcLoopNest' into 'dstLoopNest'.
|
|
unsigned srcLoopDepth = clSrcLoopDepth.getNumOccurrences() > 0
|
|
? clSrcLoopDepth
|
|
: getLoopDepth(srcStoreOpStmt);
|
|
unsigned dstLoopDepth = clDstLoopDepth.getNumOccurrences() > 0
|
|
? clDstLoopDepth
|
|
: getLoopDepth(dstLoadOpStmt);
|
|
auto *sliceLoopNest = mlir::insertBackwardComputationSlice(
|
|
&candidate.srcAccess, &candidate.dstAccess, srcLoopDepth,
|
|
dstLoopDepth);
|
|
if (sliceLoopNest != nullptr) {
|
|
// Remove edges between 'srcNode' and 'dstNode' and remove 'srcNode'
|
|
mdg->updateEdgesAndRemoveSrcNode(srcNode->id, dstNode->id);
|
|
// Record all load/store accesses in 'sliceLoopNest' at 'dstPos'.
|
|
LoopNestStateCollector collector;
|
|
collector.walkForStmt(sliceLoopNest);
|
|
mdg->addToNode(dstId, collector.loadOpStmts,
|
|
collector.storeOpStmts);
|
|
// Add new load ops to current Node load op list 'loads' to
|
|
// continue fusing based on new operands.
|
|
for (auto *loadOpStmt : collector.loadOpStmts)
|
|
loads.push_back(loadOpStmt);
|
|
// Promote single iteration loops to single IV value.
|
|
for (auto *forStmt : collector.forStmts) {
|
|
promoteIfSingleIteration(forStmt);
|
|
}
|
|
// Remove old src loop nest.
|
|
cast<ForStmt>(srcNode->stmt)->erase();
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
};
|
|
|
|
} // end anonymous namespace
|
|
|
|
PassResult LoopFusion::runOnMLFunction(MLFunction *f) {
|
|
MemRefDependenceGraph g;
|
|
if (g.init(f))
|
|
GreedyFusion(&g).run();
|
|
return success();
|
|
}
|
|
|
|
static PassRegistration<LoopFusion> pass("loop-fusion", "Fuse loop nests");
|