285 lines
12 KiB
C++
285 lines
12 KiB
C++
//===- Fusion.cpp - Implementation of linalg Fusion -----------------------===//
|
|
//
|
|
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
|
|
// See https://llvm.org/LICENSE.txt for license information.
|
|
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
|
|
//
|
|
//===----------------------------------------------------------------------===//
|
|
//
|
|
// This file implements the linalg dialect Fusion pass.
|
|
//
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
#include "mlir/Dialect/Affine/IR/AffineOps.h"
|
|
#include "mlir/Dialect/Arith/IR/Arith.h"
|
|
#include "mlir/Dialect/Linalg/IR/Linalg.h"
|
|
#include "mlir/Dialect/Linalg/Passes.h"
|
|
#include "mlir/Dialect/Linalg/Transforms/Transforms.h"
|
|
#include "mlir/Dialect/Linalg/Utils/Utils.h"
|
|
#include "mlir/Dialect/MemRef/IR/MemRef.h"
|
|
#include "mlir/Dialect/Tensor/IR/Tensor.h"
|
|
#include "mlir/IR/AffineExpr.h"
|
|
#include "mlir/IR/AffineMap.h"
|
|
#include "mlir/IR/Dominance.h"
|
|
#include "mlir/Support/LLVM.h"
|
|
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
|
|
#include "mlir/Transforms/RegionUtils.h"
|
|
#include "llvm/ADT/MapVector.h"
|
|
#include "llvm/ADT/ScopeExit.h"
|
|
#include "llvm/Support/CommandLine.h"
|
|
#include "llvm/Support/Debug.h"
|
|
|
|
#include <optional>
|
|
#include <set>
|
|
|
|
#define DEBUG_TYPE "linalg-fusion"
|
|
|
|
using namespace mlir;
|
|
using namespace mlir::linalg;
|
|
|
|
/// Implements a simple high-level fusion pass on linalg structured operations.
|
|
///
|
|
/// In each block, linalg ops are processed in reverse textual order.
|
|
/// Given a linalg op `O`, fusion occurs by:
|
|
/// 1. inspecting the linalg ops that write into the views read by `O`. There
|
|
/// are 2 cases:
|
|
/// a) buffer case: use the SSA value of the views and a simple alias
|
|
/// analysis on subview ops to determine producer-consumer dependences;
|
|
/// b) tensor case: use SSA use-def chains on extract_slice ops;
|
|
/// 2. greedily fuse the linalg ops that produce the subview/extract_slice.
|
|
/// 3. inspect the fused ops and determine whether they have other remaining
|
|
/// LinalgOp uses. If not, then erase the original producing linalg op.
|
|
///
|
|
/// More advanced use cases, analyses as well as profitability heuristics are
|
|
/// left for future work.
|
|
|
|
struct ShapeDimension {
|
|
Value shape;
|
|
unsigned dimension;
|
|
};
|
|
|
|
// Given an `op`, returns the first (`shape`, `dimension`) pair that identifies
|
|
// the loop range at `loopDepth`. The semantics of the loopToOperandRangesMaps
|
|
// guarantees at least one such dimension is found. If multiple candidates exist
|
|
// they must agree by construction (i.e. have the same size) and we just return
|
|
// the first one.
|
|
static ShapeDimension
|
|
getShapeDefiningLoopRange(LinalgOp op, unsigned loopDepth,
|
|
bool fromSubViewOpOnly = false) {
|
|
// Iterate over the inputs and outputs in order.
|
|
// Extract the subranges from the linearized ranges.
|
|
for (OpOperand &opOperand : op->getOpOperands()) {
|
|
// The method `getRangeFromOperandShape` requires using SubViewOp or
|
|
// ExtractSliceOps. If the value isn't defined from there continue.
|
|
// todo: The method should be adapted to get the values from
|
|
// `ViewInterface`. The interface needs a `getOrCreateRanges` method which
|
|
// currently returns a `linalg.range`. The fix here is to move this op to
|
|
// `std` dialect and add the method to `ViewInterface`.
|
|
if (fromSubViewOpOnly &&
|
|
!isa_and_nonnull<memref::SubViewOp, tensor::ExtractSliceOp>(
|
|
opOperand.get().getDefiningOp()))
|
|
continue;
|
|
|
|
AffineMap map = op.getMatchingIndexingMap(&opOperand);
|
|
LLVM_DEBUG(llvm::dbgs() << "getShapeDefiningLoopRange I/O idx: "
|
|
<< opOperand.getOperandNumber() << "\n");
|
|
LLVM_DEBUG(llvm::dbgs()
|
|
<< "getShapeDefiningLoopRange map: " << map << "\n");
|
|
SmallVector<Value, 8> shapeRanges(map.getNumResults(), nullptr);
|
|
for (const auto &en : llvm::enumerate(map.getResults())) {
|
|
auto dimExpr = dyn_cast<AffineDimExpr>(en.value());
|
|
if (!dimExpr)
|
|
continue;
|
|
if (loopDepth == cast<AffineDimExpr>(en.value()).getPosition()) {
|
|
LLVM_DEBUG(llvm::dbgs() << "getShapeDefiningLoopRange loopDepth: "
|
|
<< loopDepth << "\n");
|
|
LLVM_DEBUG(llvm::dbgs() << "getShapeDefiningLoopRange shape: "
|
|
<< opOperand.get() << "\n");
|
|
return ShapeDimension{opOperand.get(),
|
|
static_cast<unsigned>(en.index())};
|
|
}
|
|
}
|
|
}
|
|
llvm_unreachable("Expect to be able to extract a shape defining loop range");
|
|
}
|
|
|
|
static SmallVector<Value> getTiledOperands(LinalgOp producer) {
|
|
return producer->getOperands();
|
|
}
|
|
|
|
/// Fuses the producer by cloning the `producer`. The `fusedLoopsAndRanges`
|
|
/// provides the loop range information for the fused loops. The rest are
|
|
/// obtained from the producer itself, since they are not tiled + fused.
|
|
static LinalgOp fuse(OpBuilder &b, LinalgOp producer,
|
|
const DenseMap<unsigned, Range> &fusedLoopsAndRanges) {
|
|
SmallVector<OpFoldResult> ivs, tileSizes, sizeBounds;
|
|
SmallVector<Range> loopRanges;
|
|
Location loc = producer.getLoc();
|
|
|
|
for (unsigned i = 0, e = producer.getNumLoops(); i < e; ++i) {
|
|
auto shapeDim = getShapeDefiningLoopRange(producer, i);
|
|
OpFoldResult dim =
|
|
createFoldedDimOp(b, loc, shapeDim.shape, shapeDim.dimension);
|
|
sizeBounds.push_back(dim);
|
|
auto it = fusedLoopsAndRanges.find(i);
|
|
if (it != fusedLoopsAndRanges.end()) {
|
|
ivs.push_back(it->second.offset);
|
|
tileSizes.push_back(it->second.size);
|
|
loopRanges.push_back(it->second);
|
|
LLVM_DEBUG(llvm::dbgs() << "tiled loop#" << i << " with LoopRange "
|
|
<< loopRanges.back() << "\n");
|
|
} else {
|
|
tileSizes.push_back(b.getIndexAttr(0));
|
|
loopRanges.push_back(Range{b.getIndexAttr(0), dim, b.getIndexAttr(1)});
|
|
LLVM_DEBUG(llvm::dbgs() << "full loop#" << i << " with LoopRange "
|
|
<< loopRanges.back() << "\n");
|
|
}
|
|
}
|
|
|
|
SmallVector<Value, 8> clonedShapes;
|
|
clonedShapes.reserve(producer->getNumOperands());
|
|
|
|
// Compute subranges for all tensor input/output operands.
|
|
clonedShapes.append(makeTiledShapes(
|
|
b, loc, producer, getTiledOperands(producer), ivs, tileSizes, sizeBounds,
|
|
/**omitPartialTileCheck=*/false));
|
|
|
|
// Take result types from the tiled init operands.
|
|
MutableOperandRange producerDpsInits = producer.getDpsInitsMutable();
|
|
SmallVector<Type, 4> resultTypes;
|
|
resultTypes.reserve(producer->getNumResults());
|
|
int64_t firstInitOperandIdx =
|
|
static_cast<OperandRange>(producerDpsInits).getBeginOperandIndex();
|
|
for (int64_t i = 0, e = producer->getNumResults(); i < e; ++i) {
|
|
resultTypes.push_back(clonedShapes[firstInitOperandIdx + i].getType());
|
|
}
|
|
|
|
// Clone the producer with new operands and result types.
|
|
LinalgOp clonedOp = clone(b, producer, resultTypes, clonedShapes);
|
|
|
|
// Shift all IndexOp results by the tile offset.
|
|
SmallVector<OpFoldResult> allIvs = llvm::to_vector(
|
|
llvm::map_range(loopRanges, [&](Range range) { return range.offset; }));
|
|
offsetIndices(b, clonedOp, allIvs);
|
|
|
|
return clonedOp;
|
|
}
|
|
|
|
/// Get the loop range for a dimension `dim` based on the `shapedOperand`. It is
|
|
/// expected to be defined by a subview op or an extract_slice op.
|
|
static Range getRangeFromOperandShape(OpBuilder &b, Location loc,
|
|
Value shapedOperand, unsigned dim) {
|
|
Operation *shapeProducingOp = shapedOperand.getDefiningOp();
|
|
if (auto subViewOp = dyn_cast<memref::SubViewOp>(shapeProducingOp))
|
|
return subViewOp.getOrCreateRanges(b, loc)[dim];
|
|
if (auto sliceOp = dyn_cast<tensor::ExtractSliceOp>(shapeProducingOp))
|
|
return sliceOp.getOrCreateRanges(b, loc)[dim];
|
|
llvm_unreachable("SubviewOp or ExtractSliceOp expected");
|
|
}
|
|
|
|
/// Fuses the producer into the loop immediately enclosing the consumer.
|
|
/// This is achieved by "recomputing" the producer at the time it
|
|
/// is needed just before the consumer.
|
|
static LinalgOp fuse(OpBuilder &b, LinalgOp producerOp, AffineMap producerMap,
|
|
OpOperand &consumerOpOperand) {
|
|
LLVM_DEBUG(llvm::dbgs() << "Producer map: " << producerMap << "\n");
|
|
DenseMap<unsigned, Range> fusedLoopsAndRanges;
|
|
Value shapedOperand = consumerOpOperand.get();
|
|
for (const auto &en : llvm::enumerate(producerMap.getResults())) {
|
|
unsigned posInProducerLoop = cast<AffineDimExpr>(en.value()).getPosition();
|
|
fusedLoopsAndRanges[posInProducerLoop] = getRangeFromOperandShape(
|
|
b, consumerOpOperand.getOwner()->getLoc(), shapedOperand, en.index());
|
|
}
|
|
return fuse(b, producerOp, fusedLoopsAndRanges);
|
|
}
|
|
|
|
/// Walk back use-def chain through scf::For yields.
|
|
/// Sets `producer` and `outputIndex` if it finds a producer LinalgOp
|
|
|
|
// TODO(ravishankarm, ntv): This can be moved into the dependence graphs
|
|
// dependence tracking since the dependence tracking is similar to what is done
|
|
// w.r.t to buffers.
|
|
static void getProducerOfTensor(Value tensor, OpResult &opResult) {
|
|
if (!isa<RankedTensorType>(tensor.getType()))
|
|
return;
|
|
|
|
while (true) {
|
|
LLVM_DEBUG(llvm::dbgs() << "\ngetProducerOfTensor: " << tensor);
|
|
if (auto linalgOp = tensor.getDefiningOp<LinalgOp>()) {
|
|
opResult = cast<OpResult>(tensor);
|
|
return;
|
|
}
|
|
if (auto sliceOp = tensor.getDefiningOp<tensor::ExtractSliceOp>()) {
|
|
tensor = sliceOp.getSource();
|
|
continue;
|
|
}
|
|
if (auto blockArg = dyn_cast<BlockArgument>(tensor)) {
|
|
if (auto forOp = blockArg.getDefiningOp<scf::ForOp>()) {
|
|
tensor = forOp.getInitArgs()[blockArg.getArgNumber()];
|
|
continue;
|
|
}
|
|
}
|
|
return;
|
|
}
|
|
}
|
|
|
|
FailureOr<FusionInfo>
|
|
mlir::linalg::fuseProducerOfTensor(OpBuilder &b, OpOperand &consumerOpOperand) {
|
|
Value inputTensor = consumerOpOperand.get();
|
|
OpResult producerOpResult;
|
|
getProducerOfTensor(inputTensor, producerOpResult);
|
|
if (!producerOpResult) {
|
|
LLVM_DEBUG(llvm::dbgs() << "\nUnable to find producer");
|
|
return failure();
|
|
}
|
|
return fuseProducerOfTensor(b, producerOpResult, consumerOpOperand);
|
|
}
|
|
|
|
FailureOr<FusionInfo>
|
|
mlir::linalg::fuseProducerOfTensor(OpBuilder &b, OpResult producerOpResult,
|
|
OpOperand &consumerOpOperand) {
|
|
auto producerOp = dyn_cast<LinalgOp>(producerOpResult.getOwner());
|
|
if (!producerOp)
|
|
return failure();
|
|
|
|
LinalgOp consumerOp = dyn_cast<LinalgOp>(consumerOpOperand.getOwner());
|
|
if (!consumerOp)
|
|
return failure();
|
|
|
|
Value inputTensor = consumerOpOperand.get();
|
|
|
|
// Must be an extract_slice op to guarantee there are loops we can fuse into.
|
|
auto sliceOp = inputTensor.getDefiningOp<tensor::ExtractSliceOp>();
|
|
if (!sliceOp) {
|
|
LLVM_DEBUG(llvm::dbgs()
|
|
<< "\nNot fusable, not an extract_slice op: " << inputTensor);
|
|
return failure();
|
|
}
|
|
|
|
// If producer is already in the same block as consumer, we are done.
|
|
if (consumerOpOperand.get().getParentBlock() ==
|
|
producerOpResult.getParentBlock())
|
|
return failure();
|
|
|
|
// Insert fused `producer` just before `consumer`.
|
|
OpBuilder::InsertionGuard g(b);
|
|
b.setInsertionPoint(consumerOp);
|
|
LLVM_DEBUG(llvm::dbgs() << "Fuse into consumer: " << *consumerOp << "\n");
|
|
OpOperand *opOperand =
|
|
producerOp.getDpsInitOperand(producerOpResult.getResultNumber());
|
|
LinalgOp fusedProducer =
|
|
fuse(b, producerOp, producerOp.getMatchingIndexingMap(opOperand),
|
|
consumerOpOperand);
|
|
|
|
// Replace use.
|
|
// Canonicalizations are not guaranteed to have happened before constructing
|
|
// `fusedProducer`. In the tensor case this can result in temporary type
|
|
// mismatches. Insert a `tensor.cast` op to propagate the transformation
|
|
// invariant that types are compatible.
|
|
Value def = fusedProducer->getResult(producerOpResult.getResultNumber());
|
|
Type consumerType = consumerOpOperand.get().getType();
|
|
if (consumerType != def.getType())
|
|
def = b.create<tensor::CastOp>(fusedProducer.getLoc(), consumerType, def);
|
|
consumerOpOperand.set(def);
|
|
return FusionInfo{cast<LinalgOp>(producerOpResult.getOwner()), fusedProducer};
|
|
}
|