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llvm-project/mlir/lib/Transforms/LoopFusion.cpp

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//===- 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/Pass/Pass.h"
#include "mlir/StandardOps/Ops.h"
#include "mlir/Transforms/LoopFusionUtils.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 <iomanip>
#include <sstream>
#define DEBUG_TYPE "affine-loop-fusion"
using llvm::SetVector;
using namespace mlir;
static llvm::cl::OptionCategory clOptionsCategory(DEBUG_TYPE " options");
/// Disables fusion profitability check and fuses if valid. Ignore any
/// additional (redundant) computation tolerance threshold
/// that would have prevented fusion.
static llvm::cl::opt<bool>
clMaximalLoopFusion("fusion-maximal",
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<double> clFusionAddlComputeTolerance(
"fusion-compute-tolerance",
llvm::cl::desc("Fractional increase in additional "
"computation tolerated while fusing"),
llvm::cl::cat(clOptionsCategory));
static llvm::cl::opt<unsigned> clFusionFastMemorySpace(
"fusion-fast-mem-space",
llvm::cl::desc("Faster memory space number to promote fusion buffers to"),
llvm::cl::cat(clOptionsCategory));
// A local buffer of size less than or equal to this size is automatically
// promoted to fast memory after producer-consumer fusion.
static llvm::cl::opt<unsigned long long> clFusionLocalBufThreshold(
"fusion-local-buf-threshold",
llvm::cl::desc("Threshold size (KiB) for promoting local buffers to fast "
"memory space"),
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> {
LoopFusion(unsigned fastMemorySpace = 0, uint64_t localBufSizeThreshold = 0,
bool maximalFusion = false)
: localBufSizeThreshold(localBufSizeThreshold),
fastMemorySpace(fastMemorySpace), maximalFusion(maximalFusion) {}
void runOnFunction() override;
// Any local buffers smaller than this size (in bytes) will be created in
// `fastMemorySpace` if provided.
uint64_t localBufSizeThreshold;
Optional<unsigned> fastMemorySpace = None;
// If true, ignore any additional (redundant) computation tolerance threshold
// that would have prevented fusion.
bool maximalFusion;
// 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
FunctionPassBase *mlir::createLoopFusionPass(unsigned fastMemorySpace,
uint64_t localBufSizeThreshold,
bool maximalFusion) {
return new LoopFusion(fastMemorySpace, localBufSizeThreshold, maximalFusion);
}
namespace {
// LoopNestStateCollector walks loop nests and collects load and store
// operations, and whether or not an IfInst was encountered in the loop nest.
struct LoopNestStateCollector {
SmallVector<AffineForOp, 4> forOps;
SmallVector<Operation *, 4> loadOpInsts;
SmallVector<Operation *, 4> storeOpInsts;
bool hasNonForRegion = false;
void collect(Operation *opToWalk) {
opToWalk->walk([&](Operation *op) {
if (isa<AffineForOp>(op))
forOps.push_back(cast<AffineForOp>(op));
else if (op->getNumRegions() != 0)
hasNonForRegion = true;
else if (isa<AffineLoadOp>(op))
loadOpInsts.push_back(op);
else if (isa<AffineStoreOp>(op))
storeOpInsts.push_back(op);
});
}
};
// TODO(b/117228571) Replace when this is modeled through side-effects/op traits
static bool isMemRefDereferencingOp(Operation &op) {
if (isa<AffineLoadOp>(op) || isa<AffineStoreOp>(op) ||
isa<AffineDmaStartOp>(op) || isa<AffineDmaWaitOp>(op))
return true;
return false;
}
// MemRefDependenceGraph is a graph data structure where graph nodes are
// top-level operations in a FuncOp 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 statement which is (or contains) a load/store.
Operation *op;
// List of load operations.
SmallVector<Operation *, 4> loads;
// List of store op insts.
SmallVector<Operation *, 4> stores;
Node(unsigned id, Operation *op) : id(id), op(op) {}
// Returns the load op count for 'memref'.
unsigned getLoadOpCount(Value *memref) {
unsigned loadOpCount = 0;
for (auto *loadOpInst : loads) {
if (memref == cast<AffineLoadOp>(loadOpInst).getMemRef())
++loadOpCount;
}
return loadOpCount;
}
// Returns the store op count for 'memref'.
unsigned getStoreOpCount(Value *memref) {
unsigned storeOpCount = 0;
for (auto *storeOpInst : stores) {
if (memref == cast<AffineStoreOp>(storeOpInst).getMemRef())
++storeOpCount;
}
return storeOpCount;
}
// Returns all store ops in 'storeOps' which access 'memref'.
void getStoreOpsForMemref(Value *memref,
SmallVectorImpl<Operation *> *storeOps) {
for (auto *storeOpInst : stores) {
if (memref == cast<AffineStoreOp>(storeOpInst).getMemRef())
storeOps->push_back(storeOpInst);
}
}
// Returns all load ops in 'loadOps' which access 'memref'.
void getLoadOpsForMemref(Value *memref,
SmallVectorImpl<Operation *> *loadOps) {
for (auto *loadOpInst : loads) {
if (memref == cast<AffineLoadOp>(loadOpInst).getMemRef())
loadOps->push_back(loadOpInst);
}
}
// Returns all memrefs in 'loadAndStoreMemrefSet' for which this node
// has at least one load and store operation.
void getLoadAndStoreMemrefSet(DenseSet<Value *> *loadAndStoreMemrefSet) {
llvm::SmallDenseSet<Value *, 2> loadMemrefs;
for (auto *loadOpInst : loads) {
loadMemrefs.insert(cast<AffineLoadOp>(loadOpInst).getMemRef());
}
for (auto *storeOpInst : stores) {
auto *memref = cast<AffineStoreOp>(storeOpInst).getMemRef();
if (loadMemrefs.count(memref) > 0)
loadAndStoreMemrefSet->insert(memref);
}
}
};
// 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 operation defining a value which is used inside a loop
// nest).
Value *value;
};
// 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;
// Map from memref to a count on the dependence edges associated with that
// memref.
DenseMap<Value *, unsigned> 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(FuncOp f);
// Returns the graph node for 'id'.
Node *getNode(unsigned id) {
auto it = nodes.find(id);
assert(it != nodes.end());
return &it->second;
}
// Returns the graph node for 'forOp'.
Node *getForOpNode(AffineForOp forOp) {
for (auto &idAndNode : nodes)
if (idAndNode.second.op == forOp.getOperation())
return &idAndNode.second;
return nullptr;
}
// Adds a node with 'op' to the graph and returns its unique identifier.
unsigned addNode(Operation *op) {
Node node(nextNodeId++, op);
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<Edge, 2> 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<Edge, 2> 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 = cast<AffineStoreOp>(storeOpInst).getMemRef();
auto *op = memref->getDefiningOp();
// Return true if 'memref' is a block argument.
if (!op)
return true;
// Return true if any use of 'memref' escapes the function.
for (auto *user : memref->getUsers())
if (!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, cast<AffineStoreOp>(storeOpInst).getMemRef()) > 0)
return false;
}
return true;
}
// Returns true iff there is an edge from node 'srcId' to node 'dstId' which
// is for 'value' if non-null, or for any value otherwise. Returns false
// otherwise.
bool hasEdge(unsigned srcId, unsigned dstId, Value *value = nullptr) {
if (outEdges.count(srcId) == 0 || inEdges.count(dstId) == 0) {
return false;
}
bool hasOutEdge = llvm::any_of(outEdges[srcId], [=](Edge &edge) {
return edge.id == dstId && (!value || edge.value == value);
});
bool hasInEdge = llvm::any_of(inEdges[dstId], [=](Edge &edge) {
return edge.id == srcId && (!value || 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<MemRefType>())
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<MemRefType>()) {
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 true if there is a path in the dependence graph from node 'srcId'
// to node 'dstId'. Returns false otherwise.
bool hasDependencePath(unsigned srcId, unsigned dstId) {
// Worklist state is: <node-id, next-output-edge-index-to-visit>
SmallVector<std::pair<unsigned, unsigned>, 4> worklist;
worklist.push_back({srcId, 0});
// Run DFS traversal to see if 'dstId' is reachable from 'srcId'.
while (!worklist.empty()) {
auto &idAndIndex = worklist.back();
// Return true if we have reached 'dstId'.
if (idAndIndex.first == dstId)
return true;
// Pop and continue if node has no out edges, or if all out edges have
// already been visited.
if (outEdges.count(idAndIndex.first) == 0 ||
idAndIndex.second == outEdges[idAndIndex.first].size()) {
worklist.pop_back();
continue;
}
// Get graph edge to traverse.
Edge edge = outEdges[idAndIndex.first][idAndIndex.second];
// Increment next output edge index for 'idAndIndex'.
++idAndIndex.second;
// Add node at 'edge.id' to worklist.
worklist.push_back({edge.id, 0});
}
return false;
}
// Returns the input edge count for node 'id' and 'memref' from src nodes
// which access 'memref' with a store operation.
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->getStoreOpCount(memref) > 0)
++inEdgeCount;
}
return inEdgeCount;
}
// Returns the output edge count for node 'id' and 'memref' (if non-null),
// otherwise returns the total output edge count from node 'id'.
unsigned getOutEdgeCount(unsigned id, Value *memref = nullptr) {
unsigned outEdgeCount = 0;
if (outEdges.count(id) > 0)
for (auto &outEdge : outEdges[id])
if (!memref || outEdge.value == memref)
++outEdgeCount;
return outEdgeCount;
}
// Computes and returns an insertion point operation, before which the
// the fused <srcId, dstId> loop nest can be inserted while preserving
// dependences. Returns nullptr if no such insertion point is found.
Operation *getFusedLoopNestInsertionPoint(unsigned srcId, unsigned dstId) {
if (outEdges.count(srcId) == 0)
return getNode(dstId)->op;
// Build set of insts in range (srcId, dstId) which depend on 'srcId'.
SmallPtrSet<Operation *, 2> srcDepInsts;
for (auto &outEdge : outEdges[srcId])
if (outEdge.id != dstId)
srcDepInsts.insert(getNode(outEdge.id)->op);
// Build set of insts in range (srcId, dstId) on which 'dstId' depends.
SmallPtrSet<Operation *, 2> dstDepInsts;
for (auto &inEdge : inEdges[dstId])
if (inEdge.id != srcId)
dstDepInsts.insert(getNode(inEdge.id)->op);
Operation *srcNodeInst = getNode(srcId)->op;
Operation *dstNodeInst = getNode(dstId)->op;
// Computing insertion point:
// *) Walk all operation positions in Block operation list in the
// range (src, dst). For each operation 'op' visited in this search:
// *) Store in 'firstSrcDepPos' the first position where 'op' has a
// dependence edge from 'srcNode'.
// *) Store in 'lastDstDepPost' the last position where 'op' has a
// dependence edge to 'dstNode'.
// *) Compare 'firstSrcDepPos' and 'lastDstDepPost' to determine the
// operation insertion point (or return null pointer if no such
// insertion point exists: 'firstSrcDepPos' <= 'lastDstDepPos').
SmallVector<Operation *, 2> depInsts;
Optional<unsigned> firstSrcDepPos;
Optional<unsigned> lastDstDepPos;
unsigned pos = 0;
for (Block::iterator it = std::next(Block::iterator(srcNodeInst));
it != Block::iterator(dstNodeInst); ++it) {
Operation *op = &(*it);
if (srcDepInsts.count(op) > 0 && firstSrcDepPos == None)
firstSrcDepPos = pos;
if (dstDepInsts.count(op) > 0)
lastDstDepPos = pos;
depInsts.push_back(op);
++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<Edge, 2> 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<Edge, 2> 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<Edge, 2> oldInEdges = inEdges[dstId];
for (auto &inEdge : oldInEdges)
if (inEdge.value == oldMemRef)
removeEdge(inEdge.id, dstId, inEdge.value);
}
}
// Update edge mappings for nodes 'sibId' and 'dstId' to reflect fusion
// of sibling node 'sidId' into node 'dstId'.
void updateEdges(unsigned sibId, unsigned dstId) {
// For each edge in 'inEdges[sibId]':
// *) Add new edge from source node 'inEdge.id' to 'dstNode'.
// *) Remove edge from source node 'inEdge.id' to 'sibNode'.
if (inEdges.count(sibId) > 0) {
SmallVector<Edge, 2> oldInEdges = inEdges[sibId];
for (auto &inEdge : oldInEdges) {
addEdge(inEdge.id, dstId, inEdge.value);
removeEdge(inEdge.id, sibId, inEdge.value);
}
}
// For each edge in 'outEdges[sibId]' to node 'id'
// *) Add new edge from 'dstId' to 'outEdge.id'.
// *) Remove edge from 'sibId' to 'outEdge.id'.
if (outEdges.count(sibId) > 0) {
SmallVector<Edge, 2> oldOutEdges = outEdges[sibId];
for (auto &outEdge : oldOutEdges) {
addEdge(dstId, outEdge.id, outEdge.value);
removeEdge(sibId, outEdge.id, outEdge.value);
}
}
}
// Adds ops in 'loads' and 'stores' to node at 'id'.
void addToNode(unsigned id, const SmallVectorImpl<Operation *> &loads,
const SmallVectorImpl<Operation *> &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();
}
// Calls 'callback' for each input edge incident to node 'id' which carries a
// memref dependence.
void forEachMemRefInputEdge(unsigned id,
const std::function<void(Edge)> &callback) {
if (inEdges.count(id) > 0)
forEachMemRefEdge(inEdges[id], callback);
}
// Calls 'callback' for each output edge from node 'id' which carries a
// memref dependence.
void forEachMemRefOutputEdge(unsigned id,
const std::function<void(Edge)> &callback) {
if (outEdges.count(id) > 0)
forEachMemRefEdge(outEdges[id], callback);
}
// Calls 'callback' for each edge in 'edges' which carries a memref
// dependence.
void forEachMemRefEdge(ArrayRef<Edge> edges,
const std::function<void(Edge)> &callback) {
for (auto &edge : edges) {
// Skip if 'edge' is not a memref dependence edge.
if (!edge.value->getType().isa<MemRefType>())
continue;
assert(nodes.count(edge.id) > 0);
// Skip if 'edge.id' is not a loop nest.
if (!isa<AffineForOp>(getNode(edge.id)->op))
continue;
// Visit current input edge 'edge'.
callback(edge);
}
}
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 operations 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(FuncOp f) {
DenseMap<Value *, SetVector<unsigned>> memrefAccesses;
// TODO: support multi-block functions.
if (f.getBlocks().size() != 1)
return false;
DenseMap<Operation *, unsigned> forToNodeMap;
for (auto &op : f.front()) {
if (auto forOp = dyn_cast<AffineForOp>(op)) {
// Create graph node 'id' to represent top-level 'forOp' and record
// all loads and store accesses it contains.
LoopNestStateCollector collector;
collector.collect(&op);
// Return false if a non 'affine.for' region was found (not currently
// supported).
if (collector.hasNonForRegion)
return false;
Node node(nextNodeId++, &op);
for (auto *opInst : collector.loadOpInsts) {
node.loads.push_back(opInst);
auto *memref = cast<AffineLoadOp>(opInst).getMemRef();
memrefAccesses[memref].insert(node.id);
}
for (auto *opInst : collector.storeOpInsts) {
node.stores.push_back(opInst);
auto *memref = cast<AffineStoreOp>(opInst).getMemRef();
memrefAccesses[memref].insert(node.id);
}
forToNodeMap[&op] = node.id;
nodes.insert({node.id, node});
} else if (auto loadOp = dyn_cast<AffineLoadOp>(op)) {
// Create graph node for top-level load op.
Node node(nextNodeId++, &op);
node.loads.push_back(&op);
auto *memref = cast<AffineLoadOp>(op).getMemRef();
memrefAccesses[memref].insert(node.id);
nodes.insert({node.id, node});
} else if (auto storeOp = dyn_cast<AffineStoreOp>(op)) {
// Create graph node for top-level store op.
Node node(nextNodeId++, &op);
node.stores.push_back(&op);
auto *memref = cast<AffineStoreOp>(op).getMemRef();
memrefAccesses[memref].insert(node.id);
nodes.insert({node.id, node});
} else if (op.getNumRegions() != 0) {
// Return false if another region is found (not currently supported).
return false;
} else if (op.getNumResults() > 0 && !op.use_empty()) {
// Create graph node for top-level producer of SSA values, which
// could be used by loop nest nodes.
Node node(nextNodeId++, &op);
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 = node.op;
for (auto *value : opInst->getResults()) {
for (auto *user : value->getUsers()) {
SmallVector<AffineForOp, 4> loops;
getLoopIVs(*user, &loops);
if (loops.empty())
continue;
assert(forToNodeMap.count(loops[0].getOperation()) > 0);
unsigned userLoopNestId = forToNodeMap[loops[0].getOperation()];
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;
}
// Removes load operations from 'srcLoads' which operate on 'memref', and
// adds them to 'dstLoads'.
static void moveLoadsAccessingMemrefTo(Value *memref,
SmallVectorImpl<Operation *> *srcLoads,
SmallVectorImpl<Operation *> *dstLoads) {
dstLoads->clear();
SmallVector<Operation *, 4> srcLoadsToKeep;
for (auto *load : *srcLoads) {
if (cast<AffineLoadOp>(load).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<Operation *> ops) {
unsigned numOps = ops.size();
assert(numOps > 0);
std::vector<SmallVector<AffineForOp, 4>> loops(numOps);
unsigned loopDepthLimit = std::numeric_limits<unsigned>::max();
for (unsigned i = 0; i < numOps; ++i) {
getLoopIVs(*ops[i], &loops[i]);
loopDepthLimit =
std::min(loopDepthLimit, static_cast<unsigned>(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<Operation *> loadOpInsts,
ArrayRef<Operation *> storeOpInsts) {
// Merge loads and stores into the same array.
SmallVector<Operation *, 2> 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.
DependenceResult result = checkMemrefAccessDependence(
srcAccess, dstAccess, d, &dependenceConstraints,
/*dependenceComponents=*/nullptr);
if (hasDependence(result)) {
// 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;
}
// Sinks all sequential loops to the innermost levels (while preserving
// relative order among them) and moves all parallel loops to the
// outermost (while again preserving relative order among them).
// This can increase the loop depth at which we can fuse a slice, since we are
// pushing loop carried dependence to a greater depth in the loop nest.
static void sinkSequentialLoops(MemRefDependenceGraph::Node *node) {
assert(isa<AffineForOp>(node->op));
AffineForOp newRootForOp = sinkSequentialLoops(cast<AffineForOp>(node->op));
node->op = newRootForOp.getOperation();
}
// TODO(mlir-team): improve/complete this when we have target data.
unsigned getMemRefEltSizeInBytes(MemRefType memRefType) {
auto elementType = memRefType.getElementType();
unsigned sizeInBits;
if (elementType.isIntOrFloat()) {
sizeInBits = elementType.getIntOrFloatBitWidth();
} else {
auto vectorType = elementType.cast<VectorType>();
sizeInBits =
vectorType.getElementTypeBitWidth() * vectorType.getNumElements();
}
return llvm::divideCeil(sizeInBits, 8);
}
// Creates and returns a private (single-user) memref for fused loop rooted
// at 'forOp', 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(AffineForOp forOp, Operation *srcStoreOpInst,
unsigned dstLoopDepth,
Optional<unsigned> fastMemorySpace,
uint64_t localBufSizeThreshold) {
auto *forInst = forOp.getOperation();
// Create builder to insert alloc op just before 'forOp'.
OpBuilder b(forInst);
// Builder to create constants at the top level.
OpBuilder top(forInst->getParentOfType<FuncOp>().getBody());
// Create new memref type based on slice bounds.
auto *oldMemRef = cast<AffineStoreOp>(srcStoreOpInst).getMemRef();
auto oldMemRefType = oldMemRef->getType().cast<MemRefType>();
unsigned rank = oldMemRefType.getRank();
// Compute MemRefRegion for 'srcStoreOpInst' at depth 'dstLoopDepth'.
MemRefRegion region(srcStoreOpInst->getLoc());
bool validRegion = succeeded(region.compute(srcStoreOpInst, dstLoopDepth));
(void)validRegion;
assert(validRegion && "unexpected memref region failure");
SmallVector<int64_t, 4> newShape;
std::vector<SmallVector<int64_t, 4>> lbs;
SmallVector<int64_t, 8> lbDivisors;
lbs.reserve(rank);
// Query 'region' for 'newShape' and lower bounds of MemRefRegion accessed
// by 'srcStoreOpInst' at depth 'dstLoopDepth'.
Optional<int64_t> numElements =
region.getConstantBoundingSizeAndShape(&newShape, &lbs, &lbDivisors);
assert(numElements.hasValue() &&
"non-constant number of elts in local buffer");
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<Value *, 8> outerIVs;
cst->getIdValues(rank, cst->getNumIds(), &outerIVs);
// Build 'rank' AffineExprs from MemRefRegion 'lbs'
SmallVector<AffineExpr, 4> 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'.
uint64_t bufSize =
getMemRefEltSizeInBytes(oldMemRefType) * numElements.getValue();
unsigned newMemSpace;
if (bufSize <= localBufSizeThreshold && fastMemorySpace.hasValue()) {
newMemSpace = fastMemorySpace.getValue();
} else {
newMemSpace = oldMemRefType.getMemorySpace();
}
auto newMemRefType = top.getMemRefType(
newShape, oldMemRefType.getElementType(), {}, newMemSpace);
// Gather alloc operands for the dynamic dimensions of the memref.
SmallVector<Value *, 4> allocOperands;
unsigned dynamicDimCount = 0;
for (auto dimSize : oldMemRefType.getShape()) {
if (dimSize == -1)
allocOperands.push_back(
top.create<DimOp>(forOp.getLoc(), oldMemRef, dynamicDimCount++));
}
// Create new private memref for fused loop 'forOp'.
// 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<AllocOp>(forOp.getLoc(), newMemRefType, allocOperands);
// Build an AffineMap to remap access functions based on lower bound offsets.
SmallVector<AffineExpr, 4> remapExprs;
remapExprs.reserve(rank);
unsigned zeroOffsetCount = 0;
for (unsigned i = 0; i < rank; i++) {
if (auto constExpr = offsets[i].dyn_cast<AffineConstantExpr>())
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=*/&*forOp.getBody()->begin());
assert(ret && "replaceAllMemrefUsesWith should always succeed here");
(void)ret;
return newMemRef;
}
// Checks if node 'srcId' (which writes to a live out memref), can be safely
// fused into node 'dstId'. Returns true if the following conditions are met:
// *) 'srcNode' only writes to live out 'memref'.
// *) 'srcNode' has exactly one output edge on 'memref' (which is to 'dstId').
// *) 'dstNode's read/write region to 'memref' is a super set of 'srcNode's
// write region to 'memref'.
// TODO(andydavis) Generalize this to handle more live in/out cases.
static bool canFuseSrcWhichWritesToLiveOut(unsigned srcId, unsigned dstId,
Value *memref,
MemRefDependenceGraph *mdg) {
auto *srcNode = mdg->getNode(srcId);
auto *dstNode = mdg->getNode(dstId);
// Gather all memrefs from 'srcNode' store ops.
DenseSet<Value *> storeMemrefs;
for (auto *storeOpInst : srcNode->stores) {
storeMemrefs.insert(cast<AffineStoreOp>(storeOpInst).getMemRef());
}
// Return false if any of the following are true:
// *) 'srcNode' writes to a live in/out memref other than 'memref'.
// *) 'srcNode' has more than one output edge on 'memref'.
// Check that all stores are to the same memref.
if (storeMemrefs.size() != 1 ||
mdg->getOutEdgeCount(srcNode->id, memref) != 1)
return false;
// Compute MemRefRegion 'srcWriteRegion' for 'srcStoreOpInst' on 'memref'.
auto *srcStoreOpInst = srcNode->stores.front();
MemRefRegion srcWriteRegion(srcStoreOpInst->getLoc());
if (failed(srcWriteRegion.compute(srcStoreOpInst, /*loopDepth=*/0))) {
LLVM_DEBUG(llvm::dbgs()
<< "Unable to compute MemRefRegion for source operation\n.");
return false;
}
SmallVector<int64_t, 4> srcShape;
// Query 'srcWriteRegion' for 'srcShape' and 'srcNumElements'.
// by 'srcStoreOpInst' at depth 'dstLoopDepth'.
Optional<int64_t> srcNumElements =
srcWriteRegion.getConstantBoundingSizeAndShape(&srcShape);
if (!srcNumElements.hasValue())
return false;
// Compute MemRefRegion 'dstRegion' for 'dstStore/LoadOpInst' on 'memref'.
// TODO(andydavis) Compute 'unionboundingbox' of all write regions (one for
// each store op in 'dstStoreOps').
SmallVector<Operation *, 2> dstStoreOps;
dstNode->getStoreOpsForMemref(memref, &dstStoreOps);
SmallVector<Operation *, 2> dstLoadOps;
dstNode->getLoadOpsForMemref(memref, &dstLoadOps);
auto *dstOpInst = dstStoreOps.empty() ? dstLoadOps[0] : dstStoreOps[0];
MemRefRegion dstRegion(dstOpInst->getLoc());
if (failed(dstRegion.compute(dstOpInst, /*loopDepth=*/0))) {
LLVM_DEBUG(llvm::dbgs()
<< "Unable to compute MemRefRegion for dest operation\n.");
return false;
}
SmallVector<int64_t, 4> dstShape;
// Query 'dstRegion' for 'dstShape' and 'dstNumElements'.
// by 'dstOpInst' at depth 'dstLoopDepth'.
Optional<int64_t> dstNumElements =
dstRegion.getConstantBoundingSizeAndShape(&dstShape);
if (!dstNumElements.hasValue())
return false;
// Return false if write region is not a superset of 'srcNodes' write
// region to 'memref'.
// TODO(andydavis) Check the shape and lower bounds here too.
if (srcNumElements != dstNumElements)
return false;
return true;
}
// Checks the profitability of fusing a backwards slice of the loop nest
// surrounding 'srcOpInst' into the loop nest surrounding 'dstLoadOpInsts'.
// The argument 'srcStoreOpInst' is used to calculate the storage reduction on
// the memref being produced and consumed, which is an input to the cost model.
// For producer-constumer fusion, 'srcStoreOpInst' will be the same as
// 'srcOpInst', as we are slicing w.r.t to that producer.
// For input-reuse fusion, 'srcOpInst' will be the src loop nest LoadOp which
// reads from the same memref as dst loop nest load ops, and 'srcStoreOpInst'
// will be the unique store op in the src node, which will be used to check
// that the write region is the same after input-reuse fusion.
// 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(Operation *srcOpInst, Operation *srcStoreOpInst,
ArrayRef<Operation *> dstLoadOpInsts,
ArrayRef<Operation *> dstStoreOpInsts,
ComputationSliceState *sliceState,
unsigned *dstLoopDepth, bool maximalFusion) {
LLVM_DEBUG({
llvm::dbgs() << "Checking whether fusion is profitable between:\n";
llvm::dbgs() << " " << *srcOpInst << " and \n";
for (auto dstOpInst : dstLoadOpInsts) {
llvm::dbgs() << " " << *dstOpInst << "\n";
};
});
// Compute cost of sliced and unsliced src loop nest.
SmallVector<AffineForOp, 4> srcLoopIVs;
getLoopIVs(*srcOpInst, &srcLoopIVs);
unsigned numSrcLoopIVs = srcLoopIVs.size();
// Walk src loop nest and collect stats.
LoopNestStats srcLoopNestStats;
if (!getLoopNestStats(srcLoopIVs[0], &srcLoopNestStats))
return false;
// Compute cost of dst loop nest.
SmallVector<AffineForOp, 4> dstLoopIVs;
getLoopIVs(*dstLoadOpInsts[0], &dstLoopIVs);
LoopNestStats dstLoopNestStats;
if (!getLoopNestStats(dstLoopIVs[0], &dstLoopNestStats))
return false;
// Compute the maximum loop depth at which we can can insert the src slice
// and still satisfy dest loop nest dependences, for producer-consumer fusion.
unsigned maxDstLoopDepth =
(srcOpInst == srcStoreOpInst)
? getMaxLoopDepth(dstLoadOpInsts, dstStoreOpInsts)
: dstLoopIVs.size();
if (maxDstLoopDepth == 0) {
LLVM_DEBUG(llvm::dbgs() << "Can't fuse: maxDstLoopDepth == 0 .\n");
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<uint64_t>::max();
double maxStorageReduction = 0.0;
Optional<uint64_t> sliceMemEstimate = None;
SmallVector<ComputationSliceState, 4> sliceStates;
sliceStates.resize(maxDstLoopDepth);
// The best loop depth at which to materialize the slice.
Optional<unsigned> bestDstLoopDepth = None;
// Compute op instance count for the src loop nest without iteration slicing.
uint64_t srcLoopNestCost = getComputeCost(srcLoopIVs[0], srcLoopNestStats);
// Compute src loop nest write region size.
MemRefRegion srcWriteRegion(srcStoreOpInst->getLoc());
if (failed(srcWriteRegion.compute(srcStoreOpInst, /*loopDepth=*/0))) {
LLVM_DEBUG(llvm::dbgs()
<< "Unable to compute MemRefRegion for source operation\n.");
return false;
}
Optional<int64_t> maybeSrcWriteRegionSizeBytes =
srcWriteRegion.getRegionSize();
if (!maybeSrcWriteRegionSizeBytes.hasValue())
return false;
int64_t srcWriteRegionSizeBytes = maybeSrcWriteRegionSizeBytes.getValue();
// Compute op instance count for the src loop nest.
uint64_t dstLoopNestCost = getComputeCost(dstLoopIVs[0], dstLoopNestStats);
// Evaluate all depth choices for materializing the slice in the destination
// loop nest.
for (unsigned i = maxDstLoopDepth; i >= 1; --i) {
// Compute the union of slice bounds of all ops in 'dstLoadOpInsts'.
if (failed(mlir::computeSliceUnion({srcOpInst}, dstLoadOpInsts,
/*loopDepth=*/i,
/*numCommonLoops=*/0,
/*isBackwardSlice=*/true,
&sliceStates[i - 1]))) {
LLVM_DEBUG(llvm::dbgs()
<< "computeSliceUnion failed for loopDepth: " << i << "\n");
continue;
}
int64_t fusedLoopNestComputeCost;
if (!getFusionComputeCost(srcLoopIVs[0], srcLoopNestStats, dstLoopIVs[0],
dstLoopNestStats, &sliceStates[i - 1],
&fusedLoopNestComputeCost)) {
LLVM_DEBUG(llvm::dbgs() << "Unable to compute fusion compute cost.\n.");
continue;
}
double additionalComputeFraction =
fusedLoopNestComputeCost /
(static_cast<double>(srcLoopNestCost) + dstLoopNestCost) -
1;
// Determine what the slice write MemRefRegion would be, if the src loop
// nest slice 'sliceStates[i - 1]' were to be inserted into the dst loop
// nest at loop depth 'i'
MemRefRegion sliceWriteRegion(srcStoreOpInst->getLoc());
if (failed(sliceWriteRegion.compute(srcStoreOpInst, /*loopDepth=*/0,
&sliceStates[i - 1]))) {
LLVM_DEBUG(llvm::dbgs()
<< "Failed to compute slice write region at loopDepth: " << i
<< "\n");
continue;
}
Optional<int64_t> maybeSliceWriteRegionSizeBytes =
sliceWriteRegion.getRegionSize();
if (!maybeSliceWriteRegionSizeBytes.hasValue() ||
maybeSliceWriteRegionSizeBytes.getValue() == 0) {
LLVM_DEBUG(llvm::dbgs()
<< "Failed to get slice write region size at loopDepth: " << i
<< "\n");
continue;
}
int64_t sliceWriteRegionSizeBytes =
maybeSliceWriteRegionSizeBytes.getValue();
// If we are fusing for reuse, check that write regions remain the same.
// TODO(andydavis) Write region check should check sizes and offsets in
// each dimension, so that we are sure they are covering the same memref
// region. Also, move this out to a isMemRefRegionSuperSet helper function.
if (srcOpInst != srcStoreOpInst &&
sliceWriteRegionSizeBytes != srcWriteRegionSizeBytes)
continue;
double storageReduction = static_cast<double>(srcWriteRegionSizeBytes) /
static_cast<double>(sliceWriteRegionSizeBytes);
LLVM_DEBUG({
std::stringstream msg;
msg << " evaluating fusion profitability at depth : " << i << "\n"
<< std::fixed << std::setprecision(2)
<< " additional compute fraction: "
<< 100.0 * additionalComputeFraction << "%\n"
<< " storage reduction factor: " << storageReduction << "x\n"
<< " fused nest cost: " << fusedLoopNestComputeCost << "\n"
<< " src write region size: " << srcWriteRegionSizeBytes << "\n"
<< " slice write region size: " << sliceWriteRegionSizeBytes
<< "\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) &&
(maximalFusion ||
(additionalComputeFraction < computeToleranceThreshold))) {
maxStorageReduction = storageReduction;
bestDstLoopDepth = i;
minFusedLoopNestComputeCost = fusedLoopNestComputeCost;
sliceMemEstimate = sliceWriteRegionSizeBytes;
}
}
// A simple cost model: fuse if it reduces the memory footprint. If
// -maximal-fusion is set, fuse nevertheless.
if (!maximalFusion && !bestDstLoopDepth.hasValue()) {
LLVM_DEBUG(
llvm::dbgs()
<< "All fusion choices involve more than the threshold amount of "
"redundant computation; NOT fusing.\n");
return false;
}
if (!bestDstLoopDepth.hasValue()) {
LLVM_DEBUG(llvm::dbgs() << "no fusion depth could be evaluated.\n");
return false;
}
// 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<double> storageReduction = None;
if (!maximalFusion) {
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");
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 (static_cast<long>(fusedMem) > srcMemSizeVal + dstMemSizeVal) {
LLVM_DEBUG(llvm::dbgs() << "Fusion is not profitable; NOT fusing.\n");
return false;
}
storageReduction =
100.0 *
(1.0 - fusedMem / (static_cast<double>(srcMemSizeVal) + dstMemSizeVal));
}
double additionalComputeFraction =
100.0 * (minFusedLoopNestComputeCost /
(static_cast<double>(srcLoopNestCost) + dstLoopNestCost) -
1);
(void)additionalComputeFraction;
LLVM_DEBUG({
std::stringstream msg;
msg << " fusion is most profitable at depth " << *dstLoopDepth << " with "
<< std::setprecision(2) << additionalComputeFraction
<< "% redundant computation and a ";
msg << (storageReduction.hasValue()
? std::to_string(storageReduction.getValue())
: "<unknown>");
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 or
// input-reuse relationship on a memref, with the goal of improving locality.
//
// The steps of the producer-consumer fusion algorithm are as follows:
//
// *) A worklist is initialized with node ids from the dependence graph.
// *) For each node id in the worklist:
// *) Pop an AffineForOp of the worklist. This 'dstAffineForOp' will be a
// candidate destination AffineForOp into which fusion will be attempted.
// *) Add each LoadOp currently in 'dstAffineForOp' into list 'dstLoadOps'.
// *) For each LoadOp in 'dstLoadOps' do:
// *) Look up dependent loop nests which have a single store op to the same
// memref.
// *) Check if dependences would be violated by the fusion.
// *) 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',
// at a loop depth determined by the cost model in 'isFusionProfitable'.
// *) Add the newly fused load/store operations to the state,
// and also add newly fused load ops to 'dstLoopOps' to be considered
// as fusion dst load ops in another iteration.
// *) Remove old src loop nest and its associated state.
//
// The steps of the input-reuse fusion algorithm are as follows:
//
// *) Initialize 'worklist' with node ids from the dependence graph.
// *) For each 'dstNode' in the worklist:
// *) Find a candidate sibling node 'sibNode' to fuse with 'dstNode' which
// loads from the same memref, but which has no dependence paths to/from.
// *) Get a computation slice of 'sibLoopNest', which adjusts its loop
// bounds to be functions of 'dstLoopNest' IVs and symbols.
// *) Fuse the 'sibLoopNest' computation slice into the 'dstLoopNest',
// at a loop depth determined by the cost model in 'isFusionProfitable'.
// This function also checks that the memref write region of 'sibLoopNest',
// is preserved in the fused loop nest.
// *) Update graph state to reflect the fusion of 'sibNode' into 'dstNode'.
//
// Given a graph where top-level operations 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.
struct GreedyFusion {
public:
// The data dependence graph to traverse during fusion.
MemRefDependenceGraph *mdg;
// Worklist of graph nodes visited during the fusion pass.
SmallVector<unsigned, 8> worklist;
// Set of graph nodes which are present on the worklist.
llvm::SmallDenseSet<unsigned, 16> worklistSet;
// Parameter for local buffer size threshold.
unsigned localBufSizeThreshold;
// Parameter for fast memory space.
Optional<unsigned> fastMemorySpace;
// If true, ignore any additional (redundant) computation tolerance threshold
// that would have prevented fusion.
bool maximalFusion;
using Node = MemRefDependenceGraph::Node;
GreedyFusion(MemRefDependenceGraph *mdg, unsigned localBufSizeThreshold,
Optional<unsigned> fastMemorySpace, bool maximalFusion)
: mdg(mdg), localBufSizeThreshold(localBufSizeThreshold),
fastMemorySpace(fastMemorySpace), maximalFusion(maximalFusion) {}
// Initializes 'worklist' with nodes from 'mdg'
void init() {
// TODO(andydavis) Add a priority queue for prioritizing nodes by different
// metrics (e.g. arithmetic intensity/flops-to-bytes ratio).
worklist.clear();
worklistSet.clear();
for (auto &idAndNode : mdg->nodes) {
const Node &node = idAndNode.second;
worklist.push_back(node.id);
worklistSet.insert(node.id);
}
}
// Run the GreedyFusion pass.
// *) First pass through the nodes fuses single-use producer nodes into their
// unique consumer.
// *) Second pass fuses sibling nodes which share no dependence edges.
// *) Third pass fuses any remaining producer nodes into their users.
void run() {
// TODO(andydavis) Run this repeatedly until a fixed-point is reached.
fuseProducerConsumerNodes(/*maxSrcUserCount=*/1);
fuseSiblingNodes();
fuseProducerConsumerNodes(
/*maxSrcUserCount=*/std::numeric_limits<unsigned>::max());
eraseUnusedMemRefAllocations();
}
void fuseProducerConsumerNodes(unsigned maxSrcUserCount) {
init();
while (!worklist.empty()) {
unsigned dstId = worklist.back();
worklist.pop_back();
worklistSet.erase(dstId);
// 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<AffineForOp>(dstNode->op))
continue;
// Sink sequential loops in 'dstNode' (and thus raise parallel loops)
// while preserving relative order. This can increase the maximum loop
// depth at which we can fuse a slice of a producer loop nest into a
// consumer loop nest.
sinkSequentialLoops(dstNode);
SmallVector<Operation *, 4> loads = dstNode->loads;
SmallVector<Operation *, 4> dstLoadOpInsts;
DenseSet<Value *> visitedMemrefs;
while (!loads.empty()) {
// Get memref of load on top of the stack.
auto *memref = cast<AffineLoadOp>(loads.back()).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<unsigned, 2> 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<AffineForOp>(srcNode->op))
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 if 'srcNode' writes to any live in or escaping memrefs,
// and cannot be fused.
bool writesToLiveInOrOut =
mdg->writesToLiveInOrEscapingMemrefs(srcNode->id);
if (writesToLiveInOrOut &&
!canFuseSrcWhichWritesToLiveOut(srcId, dstId, memref, mdg))
continue;
// Skip if 'srcNode' out edge count on 'memref' > 'maxSrcUserCount'.
if (mdg->getOutEdgeCount(srcNode->id, memref) > maxSrcUserCount)
continue;
// Compute an operation list insertion point for the fused loop
// nest which preserves dependences.
Operation *insertPointInst =
mdg->getFusedLoopNestInsertionPoint(srcNode->id, dstNode->id);
if (insertPointInst == nullptr)
continue;
// Get unique 'srcNode' store op.
auto *srcStoreOpInst = srcNode->stores.front();
// Gather 'dstNode' store ops to 'memref'.
SmallVector<Operation *, 2> dstStoreOpInsts;
for (auto *storeOpInst : dstNode->stores)
if (cast<AffineStoreOp>(storeOpInst).getMemRef() == memref)
dstStoreOpInsts.push_back(storeOpInst);
unsigned bestDstLoopDepth;
mlir::ComputationSliceState sliceState;
// Check if fusion would be profitable.
if (!isFusionProfitable(srcStoreOpInst, srcStoreOpInst,
dstLoadOpInsts, dstStoreOpInsts, &sliceState,
&bestDstLoopDepth, maximalFusion))
continue;
// TODO(andydavis) Remove the following test code when canFuseLoops
// is fully functional.
mlir::ComputationSliceState sliceUnion;
if (!maximalFusion) {
FusionResult result = mlir::canFuseLoops(
cast<AffineForOp>(srcNode->op), cast<AffineForOp>(dstNode->op),
bestDstLoopDepth, &sliceUnion);
assert(result.value == FusionResult::Success);
(void)result;
}
// Fuse computation slice of 'srcLoopNest' into 'dstLoopNest'.
auto sliceLoopNest = mlir::insertBackwardComputationSlice(
srcStoreOpInst, dstLoadOpInsts[0], bestDstLoopDepth, &sliceState);
if (sliceLoopNest) {
LLVM_DEBUG(llvm::dbgs() << "\tslice loop nest:\n"
<< *sliceLoopNest.getOperation() << "\n");
// Move 'dstAffineForOp' before 'insertPointInst' if needed.
auto dstAffineForOp = cast<AffineForOp>(dstNode->op);
if (insertPointInst != dstAffineForOp.getOperation()) {
dstAffineForOp.getOperation()->moveBefore(insertPointInst);
}
// Update edges between 'srcNode' and 'dstNode'.
mdg->updateEdges(srcNode->id, dstNode->id, memref);
// Collect slice loop stats.
LoopNestStateCollector sliceCollector;
sliceCollector.collect(sliceLoopNest.getOperation());
// Promote single iteration slice loops to single IV value.
for (auto forOp : sliceCollector.forOps) {
promoteIfSingleIteration(forOp);
}
if (!writesToLiveInOrOut) {
// Create private memref for 'memref' in 'dstAffineForOp'.
SmallVector<Operation *, 4> storesForMemref;
for (auto *storeOpInst : sliceCollector.storeOpInsts) {
if (cast<AffineStoreOp>(storeOpInst).getMemRef() == memref)
storesForMemref.push_back(storeOpInst);
}
assert(storesForMemref.size() == 1);
auto *newMemRef = createPrivateMemRef(
dstAffineForOp, storesForMemref[0], bestDstLoopDepth,
fastMemorySpace, localBufSizeThreshold);
visitedMemrefs.insert(newMemRef);
// Create new node in dependence graph for 'newMemRef' alloc op.
unsigned newMemRefNodeId =
mdg->addNode(newMemRef->getDefiningOp());
// Add edge from 'newMemRef' node to dstNode.
mdg->addEdge(newMemRefNodeId, dstId, newMemRef);
}
// Collect dst loop stats after memref privatizaton transformation.
LoopNestStateCollector dstLoopCollector;
dstLoopCollector.collect(dstAffineForOp.getOperation());
// 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 = cast<AffineLoadOp>(loadOpInst).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 if it does not write to a memref which escapes the
// function. If 'writesToLiveInOrOut' is true, then 'srcNode' has
// been fused into 'dstNode' and write region of 'dstNode' covers
// the write region of 'srcNode', and 'srcNode' has no other users
// so it is safe to remove.
if (writesToLiveInOrOut || mdg->canRemoveNode(srcNode->id)) {
mdg->removeNode(srcNode->id);
srcNode->op->erase();
} else {
// Add remaining users of 'oldMemRef' back on the worklist (if not
// already there), as its replacement with a local/private memref
// has reduced dependences on 'oldMemRef' which may have created
// new fusion opportunities.
if (mdg->outEdges.count(srcNode->id) > 0) {
SmallVector<MemRefDependenceGraph::Edge, 2> oldOutEdges =
mdg->outEdges[srcNode->id];
for (auto &outEdge : oldOutEdges) {
if (outEdge.value == memref &&
worklistSet.count(outEdge.id) == 0) {
worklist.push_back(outEdge.id);
worklistSet.insert(outEdge.id);
}
}
}
}
}
}
}
}
}
// Visits each node in the graph, and for each node, attempts to fuse it with
// its sibling nodes (nodes which share a parent, but no dependence edges).
void fuseSiblingNodes() {
init();
while (!worklist.empty()) {
unsigned dstId = worklist.back();
worklist.pop_back();
worklistSet.erase(dstId);
// 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<AffineForOp>(dstNode->op))
continue;
// Attempt to fuse 'dstNode' with its sibling nodes in the graph.
fuseWithSiblingNodes(dstNode);
}
}
// Attempt to fuse 'dstNode' with sibling nodes in the graph.
void fuseWithSiblingNodes(Node *dstNode) {
DenseSet<unsigned> visitedSibNodeIds;
std::pair<unsigned, Value *> idAndMemref;
while (findSiblingNodeToFuse(dstNode, &visitedSibNodeIds, &idAndMemref)) {
unsigned sibId = idAndMemref.first;
Value *memref = idAndMemref.second;
// TODO(andydavis) Check that 'sibStoreOpInst' post-dominates all other
// stores to the same memref in 'sibNode' loop nest.
auto *sibNode = mdg->getNode(sibId);
// Compute an operation list insertion point for the fused loop
// nest which preserves dependences.
assert(sibNode->op->getBlock() == dstNode->op->getBlock());
Operation *insertPointInst =
sibNode->op->isBeforeInBlock(dstNode->op)
? mdg->getFusedLoopNestInsertionPoint(sibNode->id, dstNode->id)
: mdg->getFusedLoopNestInsertionPoint(dstNode->id, sibNode->id);
if (insertPointInst == nullptr)
continue;
// Check if fusion would be profitable and at what depth.
// Get unique 'sibNode' load op to 'memref'.
SmallVector<Operation *, 2> sibLoadOpInsts;
sibNode->getLoadOpsForMemref(memref, &sibLoadOpInsts);
// Currently findSiblingNodeToFuse searches for siblings with one load.
assert(sibLoadOpInsts.size() == 1);
Operation *sibLoadOpInst = sibLoadOpInsts[0];
assert(!sibNode->stores.empty());
// TODO(andydavis) Choose the store which postdominates all other stores.
auto *sibStoreOpInst = sibNode->stores.back();
// Gather 'dstNode' load ops to 'memref'.
SmallVector<Operation *, 2> dstLoadOpInsts;
dstNode->getLoadOpsForMemref(memref, &dstLoadOpInsts);
// Gather 'dstNode' store ops to 'memref'.
SmallVector<Operation *, 2> dstStoreOpInsts;
dstNode->getStoreOpsForMemref(memref, &dstStoreOpInsts);
unsigned bestDstLoopDepth;
mlir::ComputationSliceState sliceState;
// Check if fusion would be profitable.
if (!isFusionProfitable(sibLoadOpInst, sibStoreOpInst, dstLoadOpInsts,
dstStoreOpInsts, &sliceState, &bestDstLoopDepth,
maximalFusion))
continue;
// Fuse computation slice of 'sibLoopNest' into 'dstLoopNest'.
auto sliceLoopNest = mlir::insertBackwardComputationSlice(
sibLoadOpInst, dstLoadOpInsts[0], bestDstLoopDepth, &sliceState);
if (sliceLoopNest != nullptr) {
auto dstForInst = cast<AffineForOp>(dstNode->op);
// Update operation position of fused loop nest (if needed).
if (insertPointInst != dstForInst.getOperation()) {
dstForInst.getOperation()->moveBefore(insertPointInst);
}
// Update data dependence graph state post fusion.
updateStateAfterSiblingFusion(sliceLoopNest, sibNode, dstNode);
}
}
}
// Searches function argument uses and the graph from 'dstNode' looking for a
// fusion candidate sibling node which shares no dependences with 'dstNode'
// but which loads from the same memref. Returns true and sets
// 'idAndMemrefToFuse' on success. Returns false otherwise.
bool findSiblingNodeToFuse(Node *dstNode,
DenseSet<unsigned> *visitedSibNodeIds,
std::pair<unsigned, Value *> *idAndMemrefToFuse) {
// Returns true if 'sibNode' can be fused with 'dstNode' for input reuse
// on 'memref'.
auto canFuseWithSibNode = [&](Node *sibNode, Value *memref) {
// Skip if 'outEdge' is not a read-after-write dependence.
// TODO(andydavis) Remove restrict to single load op restriction.
if (sibNode->getLoadOpCount(memref) != 1)
return false;
// Skip if there exists a path of dependent edges between
// 'sibNode' and 'dstNode'.
if (mdg->hasDependencePath(sibNode->id, dstNode->id) ||
mdg->hasDependencePath(dstNode->id, sibNode->id))
return false;
// Skip sib node if it loads to (and stores from) the same memref on
// which it also has an input dependence edge.
DenseSet<Value *> loadAndStoreMemrefSet;
sibNode->getLoadAndStoreMemrefSet(&loadAndStoreMemrefSet);
if (llvm::any_of(loadAndStoreMemrefSet, [=](Value *memref) {
return mdg->getIncomingMemRefAccesses(sibNode->id, memref) > 0;
}))
return false;
// Check that all stores are to the same memref.
DenseSet<Value *> storeMemrefs;
for (auto *storeOpInst : sibNode->stores) {
storeMemrefs.insert(cast<AffineStoreOp>(storeOpInst).getMemRef());
}
if (storeMemrefs.size() != 1)
return false;
return true;
};
// Search for siblings which load the same memref function argument.
auto fn = dstNode->op->getParentOfType<FuncOp>();
for (unsigned i = 0, e = fn.getNumArguments(); i != e; ++i) {
for (auto *user : fn.getArgument(i)->getUsers()) {
if (auto loadOp = dyn_cast<AffineLoadOp>(user)) {
// Gather loops surrounding 'use'.
SmallVector<AffineForOp, 4> loops;
getLoopIVs(*user, &loops);
// Skip 'use' if it is not within a loop nest.
if (loops.empty())
continue;
Node *sibNode = mdg->getForOpNode(loops[0]);
assert(sibNode != nullptr);
// Skip 'use' if it not a sibling to 'dstNode'.
if (sibNode->id == dstNode->id)
continue;
// Skip 'use' if it has been visited.
if (visitedSibNodeIds->count(sibNode->id) > 0)
continue;
// Skip 'use' if it does not load from the same memref as 'dstNode'.
auto *memref = loadOp.getMemRef();
if (dstNode->getLoadOpCount(memref) == 0)
continue;
// Check if 'sibNode/dstNode' can be input-reuse fused on 'memref'.
if (canFuseWithSibNode(sibNode, memref)) {
visitedSibNodeIds->insert(sibNode->id);
idAndMemrefToFuse->first = sibNode->id;
idAndMemrefToFuse->second = memref;
return true;
}
}
}
}
// Search for siblings by following edges through an intermediate src node.
// Collect candidate 'dstNode' input edges in 'inEdges'.
SmallVector<MemRefDependenceGraph::Edge, 2> inEdges;
mdg->forEachMemRefInputEdge(
dstNode->id, [&](MemRefDependenceGraph::Edge inEdge) {
// Add 'inEdge' if it is a read-after-write dependence.
if (dstNode->getLoadOpCount(inEdge.value) > 0 &&
mdg->getNode(inEdge.id)->getStoreOpCount(inEdge.value) > 0)
inEdges.push_back(inEdge);
});
// Search for sibling nodes to fuse by visiting output edges from each input
// edge in 'inEdges'.
for (auto &inEdge : inEdges) {
// Collect candidate output edges from each node 'inEdge.id' in 'inEdges'.
SmallVector<MemRefDependenceGraph::Edge, 2> outEdges;
mdg->forEachMemRefOutputEdge(
inEdge.id, [&](MemRefDependenceGraph::Edge outEdge) {
unsigned sibNodeId = outEdge.id;
if (visitedSibNodeIds->count(sibNodeId) > 0)
return;
// Skip output edge if not a sibling using the same memref.
if (outEdge.id == dstNode->id || outEdge.value != inEdge.value)
return;
auto *sibNode = mdg->getNode(sibNodeId);
if (!isa<AffineForOp>(sibNode->op))
return;
// Check if 'sibNode/dstNode' can be input-reuse fused on 'memref'.
if (canFuseWithSibNode(sibNode, outEdge.value)) {
// Add candidate 'outEdge' to sibling node.
outEdges.push_back(outEdge);
}
});
// Add first candidate if any were returned.
if (!outEdges.empty()) {
visitedSibNodeIds->insert(outEdges[0].id);
idAndMemrefToFuse->first = outEdges[0].id;
idAndMemrefToFuse->second = outEdges[0].value;
return true;
}
}
return false;
}
void updateStateAfterSiblingFusion(AffineForOp sliceLoopNest, Node *sibNode,
Node *dstNode) {
// Update 'sibNode' and 'dstNode' input/output edges to reflect fusion.
mdg->updateEdges(sibNode->id, dstNode->id);
// Collect slice loop stats.
LoopNestStateCollector sliceCollector;
sliceCollector.collect(sliceLoopNest.getOperation());
// Promote single iteration slice loops to single IV value.
for (auto forOp : sliceCollector.forOps) {
promoteIfSingleIteration(forOp);
}
// Collect dst loop stats after memref privatizaton transformation.
auto dstForInst = cast<AffineForOp>(dstNode->op);
LoopNestStateCollector dstLoopCollector;
dstLoopCollector.collect(dstForInst.getOperation());
// Clear and add back loads and stores
mdg->clearNodeLoadAndStores(dstNode->id);
mdg->addToNode(dstNode->id, dstLoopCollector.loadOpInsts,
dstLoopCollector.storeOpInsts);
// Remove old sibling loop nest if it no longer has outgoing dependence
// edges, and it does not write to a memref which escapes the
// function.
if (mdg->getOutEdgeCount(sibNode->id) == 0) {
mdg->removeNode(sibNode->id);
sibNode->op->erase();
}
}
// Clean up any allocs with no users.
void eraseUnusedMemRefAllocations() {
for (auto &pair : mdg->memrefEdgeCount) {
if (pair.second > 0)
continue;
auto *memref = pair.first;
// Skip if there exist other uses (return operation or function calls).
if (!memref->use_empty())
continue;
// Use list expected to match the dep graph info.
auto *op = memref->getDefiningOp();
if (isa_and_nonnull<AllocOp>(op))
op->erase();
}
}
};
} // end anonymous namespace
void LoopFusion::runOnFunction() {
// Override if a command line argument was provided.
if (clFusionFastMemorySpace.getNumOccurrences() > 0) {
fastMemorySpace = clFusionFastMemorySpace.getValue();
}
// Override if a command line argument was provided.
if (clFusionLocalBufThreshold.getNumOccurrences() > 0) {
localBufSizeThreshold = clFusionLocalBufThreshold * 1024;
}
if (clMaximalLoopFusion.getNumOccurrences() > 0)
maximalFusion = clMaximalLoopFusion;
MemRefDependenceGraph g;
if (g.init(getFunction()))
GreedyFusion(&g, localBufSizeThreshold, fastMemorySpace, maximalFusion)
.run();
}
static PassRegistration<LoopFusion> pass("affine-loop-fusion",
"Fuse loop nests");
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