0c61b24337
This is similar to other configuration objects used across MLIR. Rename some fields to better reflect that they are no longer booleans. Reland 04d261101b4f229189463136a794e3e362a793af / #132253.
2253 lines
92 KiB
C++
2253 lines
92 KiB
C++
//===- Tiling.cpp - Implementation of tiling using TilingInterface -------===//
|
|
//
|
|
// 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 tiling using TilingInterface.
|
|
//
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
#include "mlir/Dialect/SCF/Transforms/TileUsingInterface.h"
|
|
|
|
#include "mlir/Analysis/SliceAnalysis.h"
|
|
#include "mlir/Analysis/TopologicalSortUtils.h"
|
|
#include "mlir/Dialect/Affine/IR/AffineOps.h"
|
|
#include "mlir/Dialect/Arith/IR/Arith.h"
|
|
#include "mlir/Dialect/Arith/Utils/Utils.h"
|
|
#include "mlir/Dialect/Func/IR/FuncOps.h"
|
|
#include "mlir/Dialect/SCF/Utils/Utils.h"
|
|
#include "mlir/Dialect/Tensor/IR/Tensor.h"
|
|
#include "mlir/Dialect/Utils/IndexingUtils.h"
|
|
#include "mlir/IR/Dominance.h"
|
|
#include "mlir/IR/Matchers.h"
|
|
#include "mlir/IR/PatternMatch.h"
|
|
#include "mlir/Interfaces/DestinationStyleOpInterface.h"
|
|
#include "mlir/Interfaces/TilingInterface.h"
|
|
#include "mlir/Rewrite/FrozenRewritePatternSet.h"
|
|
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
|
|
#include "llvm/ADT/ScopeExit.h"
|
|
#include "llvm/ADT/TypeSwitch.h"
|
|
#include "llvm/Support/Debug.h"
|
|
#include <optional>
|
|
|
|
#define DEBUG_TYPE "tile-using-interface"
|
|
|
|
using namespace mlir;
|
|
|
|
scf::SCFTilingOptions &
|
|
scf::SCFTilingOptions::setTileSizes(ArrayRef<OpFoldResult> ts) {
|
|
assert(!tileSizeComputationFunction && "tile sizes already set");
|
|
auto tileSizes = llvm::to_vector(ts);
|
|
tileSizeComputationFunction = [tileSizes](OpBuilder &b, Operation *op) {
|
|
return tileSizes;
|
|
};
|
|
return *this;
|
|
}
|
|
|
|
scf::SCFTilingOptions &
|
|
scf::SCFTilingOptions::setNumThreads(ArrayRef<OpFoldResult> nt) {
|
|
assert(!numThreadsComputationFunction && "num tiles already set");
|
|
auto numThreads = llvm::to_vector(nt);
|
|
numThreadsComputationFunction = [numThreads](OpBuilder &b, Operation *op) {
|
|
return numThreads;
|
|
};
|
|
return *this;
|
|
}
|
|
|
|
/// Helper method to adjust the interchange vector to match the iteration
|
|
/// domain.
|
|
static SmallVector<int64_t>
|
|
fillInterchangeVector(ArrayRef<int64_t> interchangeVector,
|
|
size_t iterationDomainSize) {
|
|
SmallVector<int64_t> filledVector = llvm::to_vector(interchangeVector);
|
|
if (filledVector.size() < iterationDomainSize) {
|
|
auto range = llvm::seq<int64_t>(filledVector.size(), iterationDomainSize);
|
|
filledVector.append(range.begin(), range.end());
|
|
}
|
|
if (filledVector.size() > iterationDomainSize)
|
|
filledVector.resize(iterationDomainSize);
|
|
return filledVector;
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// tileUsingSCF implementation.
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
/// Verify the tile size options are set in a consistent manner.
|
|
static LogicalResult
|
|
verifyTileSizeOptions(RewriterBase &rewriter, Location loc,
|
|
const scf::SCFTilingOptions &options) {
|
|
// Specifying number of threads is only supported on `scf.forall` op.
|
|
if (options.numThreadsComputationFunction &&
|
|
options.loopType != scf::SCFTilingOptions::LoopType::ForallOp) {
|
|
return rewriter.notifyMatchFailure(
|
|
loc, "number of threads can only by specified when loop type is "
|
|
"set to use `scf.forall`");
|
|
}
|
|
|
|
// If specified, check that the interchange vector is a permutation.
|
|
if (!options.interchangeVector.empty()) {
|
|
if (!isPermutationVector(options.interchangeVector)) {
|
|
return rewriter.notifyMatchFailure(
|
|
loc, "invalid interchange vector, not a permutation of the entire "
|
|
"iteration space");
|
|
}
|
|
}
|
|
return success();
|
|
}
|
|
|
|
/// Method to instantiate the tile sizes and/or number of threads specified
|
|
/// by the user.
|
|
static std::tuple<SmallVector<OpFoldResult>, SmallVector<OpFoldResult>>
|
|
getUserTileSizesAndNumThreads(RewriterBase &rewriter, TilingInterface op,
|
|
ArrayRef<Range> iterationDomain,
|
|
const scf::SCFTilingOptions &options) {
|
|
OpFoldResult zero = rewriter.getIndexAttr(0);
|
|
SmallVector<OpFoldResult> tileSizes, numThreads;
|
|
size_t numLoops = iterationDomain.size();
|
|
|
|
// Check whether the number of tiles to use is specified.
|
|
if (options.numThreadsComputationFunction) {
|
|
numThreads = options.numThreadsComputationFunction(rewriter, op);
|
|
numThreads.resize(numLoops, zero);
|
|
|
|
// If the number of tiles is also specified, use that.
|
|
if (options.tileSizeComputationFunction) {
|
|
tileSizes = options.tileSizeComputationFunction(rewriter, op);
|
|
tileSizes.resize(numLoops, zero);
|
|
return {tileSizes, numThreads};
|
|
}
|
|
|
|
// Compute the tile sizes from the iteration domain and number
|
|
// of tiles as follows
|
|
// - niters = ceilDiv(ub - lb, step)
|
|
// - tileSize = ceilDiv(niters, numThreads)
|
|
AffineExpr s0, s1, s2;
|
|
bindSymbols(rewriter.getContext(), s0, s1, s2);
|
|
// TODO: The step here is assumed to be 1.
|
|
AffineExpr numItersExpr = (s1 - s0);
|
|
AffineExpr tileSizeExpr = numItersExpr.ceilDiv(s2);
|
|
tileSizes.resize(numLoops, zero);
|
|
for (auto [index, range, nt] :
|
|
llvm::enumerate(iterationDomain, numThreads)) {
|
|
if (isConstantIntValue(nt, 0))
|
|
continue;
|
|
|
|
tileSizes[index] = affine::makeComposedFoldedAffineApply(
|
|
rewriter, op.getLoc(), tileSizeExpr, {range.offset, range.size, nt});
|
|
}
|
|
tileSizes.resize(numLoops, zero);
|
|
return {tileSizes, numThreads};
|
|
}
|
|
|
|
// Enforce the convention that "tiling by zero"
|
|
// skips tiling a particular dimension. This convention is significantly
|
|
// simpler to handle instead of adjusting affine maps to account for missing
|
|
// dimensions.
|
|
assert(options.tileSizeComputationFunction &&
|
|
"expected tile sizes to be specified");
|
|
tileSizes = options.tileSizeComputationFunction(rewriter, op);
|
|
tileSizes.resize(numLoops, zero);
|
|
|
|
return {tileSizes, numThreads};
|
|
}
|
|
|
|
/// Checks if any of the tiled loops are not parallel.
|
|
static void checkSafeToTileToForall(TilingInterface op,
|
|
ArrayRef<OpFoldResult> tileSizes,
|
|
ArrayRef<OpFoldResult> numThreads) {
|
|
auto iterators = op.getLoopIteratorTypes();
|
|
assert(iterators.size() == tileSizes.size() &&
|
|
"expected as many tile size values as number of loops");
|
|
assert((numThreads.empty() || (numThreads.size() == iterators.size())) &&
|
|
"when specified, expected number of threads to use for each loop");
|
|
|
|
for (auto [index, iterator, tileSize] :
|
|
llvm::enumerate(iterators, tileSizes)) {
|
|
// If num threads is specified, check that it is greater than one only for
|
|
// parallel dimensions.
|
|
if (!numThreads.empty()) {
|
|
if (std::optional<int64_t> constNumThreads =
|
|
getConstantIntValue(numThreads[index])) {
|
|
if (constNumThreads.value() > 1 &&
|
|
iterator != utils::IteratorType::parallel) {
|
|
op.emitWarning() << "tiling is not thread safe at axis #" << index;
|
|
}
|
|
}
|
|
continue;
|
|
}
|
|
|
|
if (std::optional<int64_t> constTileSize = getConstantIntValue(tileSize)) {
|
|
if (constTileSize.value() > 0 &&
|
|
iterator != utils::IteratorType::parallel) {
|
|
op.emitWarning() << "tiling is not thread safe at axis #" << index;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
/// Check if `stride` evenly divides the trip count `size - offset`.
|
|
static bool tileDividesIterationDomain(Range loopRange) {
|
|
std::optional<int64_t> offsetAsInt = getConstantIntValue(loopRange.offset);
|
|
if (!offsetAsInt)
|
|
return false;
|
|
std::optional<int64_t> sizeAsInt = getConstantIntValue(loopRange.size);
|
|
if (!sizeAsInt)
|
|
return false;
|
|
std::optional<int64_t> strideAsInt = getConstantIntValue(loopRange.stride);
|
|
if (!strideAsInt)
|
|
return false;
|
|
return ((sizeAsInt.value() - offsetAsInt.value()) % strideAsInt.value() == 0);
|
|
}
|
|
|
|
/// Returns the bounded tile size given the current `offset`, `loopRange` and
|
|
/// `tileSize`, i.e., `min(tileSize, range.end() - offset)`.
|
|
static OpFoldResult getBoundedTileSize(OpBuilder &b, Location loc,
|
|
Range loopRange, OpFoldResult offset,
|
|
OpFoldResult tileSize) {
|
|
std::optional<int64_t> ts = getConstantIntValue(tileSize);
|
|
if (ts && ts.value() == 1)
|
|
return tileSize;
|
|
|
|
if (tileDividesIterationDomain(
|
|
Range{loopRange.offset, loopRange.size, tileSize}))
|
|
return tileSize;
|
|
|
|
// The tile size to use (to avoid out of bounds access) is minimum of
|
|
// `tileSize` and `ub - iv`, where `iv` is the induction variable of the tiled
|
|
// loop.
|
|
AffineExpr s0, s1, d0;
|
|
bindDims(b.getContext(), d0);
|
|
bindSymbols(b.getContext(), s0, s1);
|
|
AffineMap minMap = AffineMap::get(1, 2, {s0 - d0, s1}, b.getContext());
|
|
Value size = getValueOrCreateConstantIndexOp(b, loc, loopRange.size);
|
|
return affine::makeComposedFoldedAffineMin(
|
|
b, loc, minMap, SmallVector<OpFoldResult>{offset, size, tileSize});
|
|
}
|
|
|
|
/// Returns true if the maximum tile offset `tileSize * numThreads-1` is less
|
|
/// than `iterationSize`.
|
|
static bool canOmitTileOffsetInBoundsCheck(OpFoldResult tileSize,
|
|
OpFoldResult numThreads,
|
|
OpFoldResult iterationSize) {
|
|
std::optional<int64_t> tileSizeConst = getConstantIntValue(tileSize);
|
|
std::optional<int64_t> numThreadsConst = getConstantIntValue(numThreads);
|
|
std::optional<int64_t> iterSizeConst = getConstantIntValue(iterationSize);
|
|
if (!tileSizeConst || !numThreadsConst || !iterSizeConst)
|
|
return false;
|
|
return *tileSizeConst * (*numThreadsConst - 1) < *iterSizeConst;
|
|
}
|
|
|
|
/// Compute the `OpFoldResult`s that represents the multi-dimensional
|
|
/// `offset`s and `size`s of the tile of the iteration space that the
|
|
/// innermost loop body of the generated tiled loops corresponds to.
|
|
static std::tuple<SmallVector<OpFoldResult>, SmallVector<OpFoldResult>>
|
|
getTileOffsetAndSizes(RewriterBase &rewriter, Location loc, ValueRange ivs,
|
|
ArrayRef<Range> iterationDomain,
|
|
ArrayRef<OpFoldResult> tileSizes,
|
|
ArrayRef<OpFoldResult> numThreads) {
|
|
SmallVector<OpFoldResult> offsets, sizes;
|
|
int materializedLoopNum = 0;
|
|
|
|
if (!numThreads.empty()) {
|
|
AffineExpr d0, d1, s0, s1;
|
|
AffineExpr offsetExpr, residualTileSizeExpr;
|
|
bindDims(rewriter.getContext(), d0, d1);
|
|
bindSymbols(rewriter.getContext(), s0, s1);
|
|
offsetExpr = d0 + d1 * s0;
|
|
residualTileSizeExpr = s1 - (d0 + d1 * s0);
|
|
|
|
for (auto [nt, tileSize, loopRange] :
|
|
llvm::zip_equal(numThreads, tileSizes, iterationDomain)) {
|
|
|
|
// Non-tiled cases, set the offset and size to the
|
|
// `loopRange.offset/size`.
|
|
if (isConstantIntValue(nt, 0)) {
|
|
offsets.push_back(loopRange.offset);
|
|
sizes.push_back(loopRange.size);
|
|
continue;
|
|
}
|
|
|
|
Value iv = ivs[materializedLoopNum++];
|
|
OpFoldResult offset = affine::makeComposedFoldedAffineApply(
|
|
rewriter, loc, offsetExpr,
|
|
ArrayRef<OpFoldResult>{loopRange.offset, iv, tileSize});
|
|
OpFoldResult residualTileSize = affine::makeComposedFoldedAffineApply(
|
|
rewriter, loc, residualTileSizeExpr,
|
|
{loopRange.offset, nt, tileSize, loopRange.size});
|
|
|
|
OpFoldResult size = tileSize;
|
|
if (!isConstantIntValue(residualTileSize, 0)) {
|
|
OpFoldResult sizeMinusOffsetPerThread =
|
|
affine::makeComposedFoldedAffineApply(rewriter, loc, s0 - d0,
|
|
{offset, loopRange.size});
|
|
size = affine::makeComposedFoldedAffineMin(
|
|
rewriter, loc,
|
|
AffineMap::getMultiDimIdentityMap(2, rewriter.getContext()),
|
|
{sizeMinusOffsetPerThread, tileSize});
|
|
}
|
|
|
|
// Consider the case where the original loop was `[0, 100)`.
|
|
// If number of threads are `7`, the tile size would be computed as
|
|
// `ceilDiv(100, 7) = 15`. For the last thread (thread_id = 6)
|
|
// - `offset = 0 + 6 * 15 = 105`
|
|
// - `tileSize = min(15, 100 - 105) = -5`
|
|
// To avoid negative tile sizes, we need to do a further
|
|
// `nonNegativeTileSize = affine.max(0, tileSize)`.
|
|
// This `max` can be avoided if
|
|
// `offset + tileSize * (numThreads - 1) < (ub - lb)`
|
|
if (!canOmitTileOffsetInBoundsCheck(tileSize, nt, loopRange.size)) {
|
|
AffineMap maxMap =
|
|
AffineMap::getMultiDimIdentityMap(2, rewriter.getContext());
|
|
size = affine::makeComposedFoldedAffineMax(
|
|
rewriter, loc, maxMap, {rewriter.getIndexAttr(0), size});
|
|
}
|
|
|
|
offsets.push_back(offset);
|
|
sizes.push_back(size);
|
|
}
|
|
return {offsets, sizes};
|
|
} else {
|
|
for (auto [tileSize, loopRange] :
|
|
llvm::zip_equal(tileSizes, iterationDomain)) {
|
|
|
|
// Non-tiled cases, set the offset and size to the
|
|
// `loopRange.offset/size`.
|
|
if (isConstantIntValue(tileSize, 0)) {
|
|
offsets.push_back(loopRange.offset);
|
|
sizes.push_back(loopRange.size);
|
|
continue;
|
|
}
|
|
|
|
Value iv = ivs[materializedLoopNum++];
|
|
OpFoldResult offset = getAsOpFoldResult(iv);
|
|
offsets.push_back(offset);
|
|
OpFoldResult size =
|
|
getBoundedTileSize(rewriter, loc, loopRange, offset, tileSize);
|
|
sizes.push_back(size);
|
|
}
|
|
return {offsets, sizes};
|
|
}
|
|
}
|
|
|
|
/// Function to return the bounds of the loops to be generated.
|
|
static std::tuple<SmallVector<OpFoldResult>, SmallVector<OpFoldResult>,
|
|
SmallVector<OpFoldResult>>
|
|
getLoopBounds(RewriterBase &rewriter, Location loc, ArrayRef<Range> loopRanges,
|
|
ArrayRef<OpFoldResult> tileSizes) {
|
|
SmallVector<OpFoldResult> lbs, ubs, steps;
|
|
for (auto [loopRange, tileSize] : llvm::zip_equal(loopRanges, tileSizes)) {
|
|
// No loop if the tile size is 0.
|
|
if (isConstantIntValue(tileSize, 0))
|
|
continue;
|
|
lbs.push_back(loopRange.offset);
|
|
ubs.push_back(loopRange.size);
|
|
steps.push_back(tileSize);
|
|
}
|
|
return {lbs, ubs, steps};
|
|
}
|
|
|
|
/// A function that allows returning additional yielded values during
|
|
/// `yieldTiledValuesAndReplace`.
|
|
/// - `ivs` induction variable for the loop.
|
|
/// - `newBbArgs` basic block arguments corresponding to newly added iter_args.
|
|
/// - `tiledValues` the tiled values to return. Must be of same size as
|
|
/// `newbbArgs`, each element of this array is inserted into the corresponding
|
|
/// element in `newbbArgs`.
|
|
/// - `resultOffsets` is of the same size as `tiledValues` and represents
|
|
/// the offsets to use when inserting corresponding element from `tiledValues`
|
|
/// into the element from `newBbArgs`.
|
|
/// - `resultSizes` is of the same size as `tiledValues` and represents
|
|
/// the size of the corresponding element from `tiledValues` inserted into
|
|
/// the element from `newBbArgs`.
|
|
/// In case the method needs to return `failure()` the method is expected
|
|
/// to clean up any inserted operations.
|
|
using YieldTiledValuesFn = std::function<LogicalResult(
|
|
RewriterBase &rewriter, Location loc, ValueRange ivs, ValueRange newBbArgs,
|
|
SmallVector<Value> &tiledValues,
|
|
SmallVector<SmallVector<OpFoldResult>> &resultOffsets,
|
|
SmallVector<SmallVector<OpFoldResult>> &resultSizes)>;
|
|
|
|
/// Clones the operation and updates the destination if the operation
|
|
/// implements the `DestinationStyleOpInterface`.
|
|
static Operation *cloneOpAndUpdateDestinationArgs(RewriterBase &rewriter,
|
|
Operation *op,
|
|
ValueRange newDestArgs) {
|
|
Operation *clonedOp = rewriter.clone(*op);
|
|
if (newDestArgs.empty())
|
|
return clonedOp;
|
|
if (auto destinationStyleOp = dyn_cast<DestinationStyleOpInterface>(clonedOp))
|
|
destinationStyleOp.getDpsInitsMutable().assign(newDestArgs);
|
|
return clonedOp;
|
|
}
|
|
|
|
/// Generate the tile-loop nest using `scf.for` operation.
|
|
/// - `loopRanges` specifies the lb, ub and step of the untiled iteration space.
|
|
/// - `tileSizes` is the tile sizes to use. Zero represent untiled loops.
|
|
/// - `destinationTensors` are the init values to use for the outer most loop.
|
|
/// - `yieldTiledValuesFn` is called to generated the loop body of the inner
|
|
/// most
|
|
/// loop.
|
|
/// - `loops` is an in-out parameter into which the generated loops are
|
|
/// populated.
|
|
static LogicalResult generateLoopNestUsingForOp(
|
|
RewriterBase &rewriter, Location loc, ArrayRef<Range> loopRanges,
|
|
ArrayRef<OpFoldResult> tileSizes, ValueRange destinationTensors,
|
|
YieldTiledValuesFn yieldTiledValuesFn,
|
|
SmallVector<LoopLikeOpInterface> &loops) {
|
|
assert(!loopRanges.empty() && "unexpected empty loop ranges");
|
|
assert(loopRanges.size() == tileSizes.size() &&
|
|
"expected as many tile sizes as loop ranges");
|
|
OpBuilder::InsertionGuard guard(rewriter);
|
|
|
|
SmallVector<OpFoldResult> lbs, ubs, steps;
|
|
std::tie(lbs, ubs, steps) =
|
|
getLoopBounds(rewriter, loc, loopRanges, tileSizes);
|
|
SmallVector<Value> lbVals =
|
|
getValueOrCreateConstantIndexOp(rewriter, loc, lbs);
|
|
SmallVector<Value> ubVals =
|
|
getValueOrCreateConstantIndexOp(rewriter, loc, ubs);
|
|
SmallVector<Value> stepVals =
|
|
getValueOrCreateConstantIndexOp(rewriter, loc, steps);
|
|
|
|
SmallVector<Value> ivs;
|
|
for (auto [lb, ub, step] : llvm::zip_equal(lbVals, ubVals, stepVals)) {
|
|
auto loop =
|
|
rewriter.create<scf::ForOp>(loc, lb, ub, step, destinationTensors,
|
|
[](OpBuilder &bodyBuilder, Location bodyLoc,
|
|
Value iv, ValueRange /*iterArgs*/) {});
|
|
loops.push_back(loop);
|
|
ivs.push_back(loop.getInductionVar());
|
|
rewriter.setInsertionPointToEnd(loop.getBody());
|
|
destinationTensors = loop.getRegionIterArgs();
|
|
}
|
|
|
|
SmallVector<Value> tiledResults;
|
|
SmallVector<SmallVector<OpFoldResult>> resultOffsets, resultSizes;
|
|
if (failed(yieldTiledValuesFn(rewriter, loc, ivs, destinationTensors,
|
|
tiledResults, resultOffsets, resultSizes))) {
|
|
return rewriter.notifyMatchFailure(
|
|
loc, "failed to generate inner tile loop body");
|
|
}
|
|
if (loops.empty())
|
|
return success();
|
|
|
|
assert(tiledResults.size() == destinationTensors.size() &&
|
|
"Number of results of body should be equal to number of iter args");
|
|
|
|
// 6. Yield all the results of the tiled operation.
|
|
SmallVector<Value> yieldedValues;
|
|
for (auto [tiledValue, destinationTensor, resultOffset, resultSize] :
|
|
llvm::zip_equal(tiledResults, destinationTensors, resultOffsets,
|
|
resultSizes)) {
|
|
SmallVector<OpFoldResult> resultStride(resultOffset.size(),
|
|
rewriter.getIndexAttr(1));
|
|
auto insertSlice = rewriter.create<tensor::InsertSliceOp>(
|
|
loc, tiledValue, destinationTensor, resultOffset, resultSize,
|
|
resultStride);
|
|
yieldedValues.push_back(insertSlice);
|
|
}
|
|
rewriter.create<scf::YieldOp>(loc, yieldedValues);
|
|
|
|
// Add the scf.yield operations for all the outer loops.
|
|
for (auto [outerLoop, innerLoop] :
|
|
llvm::zip_equal(MutableArrayRef(loops).drop_back(),
|
|
MutableArrayRef(loops).drop_front())) {
|
|
rewriter.setInsertionPointToEnd(
|
|
cast<scf::ForOp>(outerLoop.getOperation()).getBody());
|
|
rewriter.create<scf::YieldOp>(outerLoop.getLoc(), innerLoop->getResults());
|
|
}
|
|
return success();
|
|
}
|
|
|
|
/// Generate the tile-loop nest using `scf.forall` operation.
|
|
/// - `loopRanges` specifies the lb, ub and step of the untiled iteration space.
|
|
/// - `tileSizes` is the tile sizes to use. Zero represent untiled loops.
|
|
/// - `destinationTensors` are the init values to use for the outer most loop.
|
|
/// - `mappingVector` is the mapping attributes to use for loop construction.
|
|
/// Can be empty.
|
|
/// - `yieldTiledValuesFn` is called to generated the loop body of the inner
|
|
/// most
|
|
/// loop.
|
|
/// - `loops` is an in-out parameter into which the generated loops are
|
|
/// populated.
|
|
static LogicalResult generateLoopNestUsingForallOp(
|
|
RewriterBase &rewriter, Location loc, ArrayRef<Range> loopRanges,
|
|
ArrayRef<OpFoldResult> tileSizes, ArrayRef<OpFoldResult> numThreads,
|
|
ArrayRef<Attribute> mappingVector, ValueRange destinationTensors,
|
|
YieldTiledValuesFn tiledBodyFn, SmallVector<LoopLikeOpInterface> &loops) {
|
|
assert(!loopRanges.empty() && "unexpected empty loop ranges");
|
|
assert(loopRanges.size() == tileSizes.size() &&
|
|
"expected as many tile sizes as loop ranges");
|
|
OpBuilder::InsertionGuard guard(rewriter);
|
|
SmallVector<OpFoldResult> offsets(loopRanges.size()),
|
|
sizes(loopRanges.size());
|
|
|
|
std::optional<ArrayAttr> mappingAttr;
|
|
if (!mappingVector.empty())
|
|
mappingAttr = rewriter.getArrayAttr(mappingVector);
|
|
|
|
scf::ForallOp forallOp;
|
|
bool useNumThreads = !numThreads.empty();
|
|
|
|
if (useNumThreads) {
|
|
// Prune the zero numthreads.
|
|
SmallVector<OpFoldResult> nonZeroNumThreads;
|
|
for (auto nt : numThreads) {
|
|
if (isConstantIntValue(nt, 0))
|
|
continue;
|
|
nonZeroNumThreads.push_back(nt);
|
|
}
|
|
forallOp = rewriter.create<scf::ForallOp>(loc, nonZeroNumThreads,
|
|
destinationTensors, mappingAttr);
|
|
} else {
|
|
SmallVector<OpFoldResult> lbs, ubs, steps;
|
|
std::tie(lbs, ubs, steps) =
|
|
getLoopBounds(rewriter, loc, loopRanges, tileSizes);
|
|
forallOp = rewriter.create<scf::ForallOp>(loc, lbs, ubs, steps,
|
|
destinationTensors, mappingAttr);
|
|
}
|
|
loops.push_back(forallOp);
|
|
|
|
rewriter.setInsertionPoint(forallOp.getTerminator());
|
|
destinationTensors = forallOp.getRegionOutArgs();
|
|
|
|
SmallVector<Value> tiledResults;
|
|
SmallVector<SmallVector<OpFoldResult>> resultOffsets, resultSizes;
|
|
if (failed(tiledBodyFn(rewriter, loc, forallOp.getInductionVars(),
|
|
destinationTensors, tiledResults, resultOffsets,
|
|
resultSizes)))
|
|
return rewriter.notifyMatchFailure(loc, "failed to generate loop body");
|
|
|
|
rewriter.setInsertionPointToEnd(forallOp.getTerminator().getBody());
|
|
for (auto [tiledValue, destinationTensor, resultOffset, resultSize] :
|
|
llvm::zip_equal(tiledResults, destinationTensors, resultOffsets,
|
|
resultSizes)) {
|
|
SmallVector<OpFoldResult> resultStride(resultOffset.size(),
|
|
rewriter.getIndexAttr(1));
|
|
|
|
rewriter.create<tensor::ParallelInsertSliceOp>(
|
|
loc, tiledValue, destinationTensor, resultOffset, resultSize,
|
|
resultStride);
|
|
}
|
|
return success();
|
|
}
|
|
|
|
/// Generate the tile-loop nest using the loop construct specifed in `options`.
|
|
/// - `options`: Tiling options specified.
|
|
/// - `loopRanges` specifies the lb, ub and step of the untiled iteration space.
|
|
/// - `tileSizes` is the tile sizes to use. Zero represent untiled loops.
|
|
/// - `destinationTensors` are the init values to use for the outer most loop.
|
|
/// - `yieldTiledValuesFn` is called to generated the loop body of the inner
|
|
/// most
|
|
/// loop.
|
|
/// - `loops` is an in-out parameter into which the generated loops are
|
|
/// populated.
|
|
static LogicalResult generateLoopNest(
|
|
RewriterBase &rewriter, Location loc, const scf::SCFTilingOptions &options,
|
|
ArrayRef<Range> loopRanges, ArrayRef<OpFoldResult> tileSizes,
|
|
ArrayRef<OpFoldResult> numThreads, ValueRange destinationTensors,
|
|
YieldTiledValuesFn tiledBodyFn, SmallVector<LoopLikeOpInterface> &loops) {
|
|
// If the tile sizes are all zero, no loops are generated. Just call the
|
|
// callback function to handle untiled case.
|
|
if (llvm::all_of(tileSizes, isZeroIndex)) {
|
|
SmallVector<Value> tiledResults;
|
|
SmallVector<SmallVector<OpFoldResult>> resultOffsets, resultSizes;
|
|
return tiledBodyFn(rewriter, loc, ValueRange{}, destinationTensors,
|
|
tiledResults, resultOffsets, resultSizes);
|
|
}
|
|
if (options.loopType == scf::SCFTilingOptions::LoopType::ForOp) {
|
|
return generateLoopNestUsingForOp(rewriter, loc, loopRanges, tileSizes,
|
|
destinationTensors, tiledBodyFn, loops);
|
|
}
|
|
if (options.loopType == scf::SCFTilingOptions::LoopType::ForallOp) {
|
|
return generateLoopNestUsingForallOp(
|
|
rewriter, loc, loopRanges, tileSizes, numThreads, options.mappingVector,
|
|
destinationTensors, tiledBodyFn, loops);
|
|
}
|
|
return rewriter.notifyMatchFailure(loc, "unhandled loop type");
|
|
}
|
|
|
|
static FailureOr<SmallVector<Value>>
|
|
createInitialTensorsForTiling(RewriterBase &rewriter, TilingInterface op,
|
|
ArrayRef<OpFoldResult> tileSizes,
|
|
const scf::SCFTilingOptions &options) {
|
|
SmallVector<Value> initTensors;
|
|
Location loc = op->getLoc();
|
|
switch (options.reductionStrategy) {
|
|
case scf::SCFTilingOptions::ReductionTilingStrategy::FullReduction:
|
|
if (failed(tensor::getOrCreateDestinations(rewriter, loc, op, initTensors)))
|
|
return failure();
|
|
return initTensors;
|
|
case scf::SCFTilingOptions::ReductionTilingStrategy::
|
|
PartialReductionOuterReduction: {
|
|
auto redOp = dyn_cast<PartialReductionOpInterface>(op.getOperation());
|
|
if (!redOp) {
|
|
return rewriter.notifyMatchFailure(
|
|
op, "PartialReductionOuterReduction tiling strategy is only supported"
|
|
"for operations implementing PartialReductionOpInterface");
|
|
}
|
|
// Get reduction dimensions.
|
|
// TODO: PartialReductionOpInterface should really query TilingInterface
|
|
// itself and find reduction dimensions.
|
|
SmallVector<int> reductionDims;
|
|
for (auto [idx, iteratorType] :
|
|
llvm::enumerate(op.getLoopIteratorTypes())) {
|
|
if (iteratorType == utils::IteratorType::reduction)
|
|
reductionDims.push_back(idx);
|
|
}
|
|
return redOp.generateInitialTensorForPartialReduction(
|
|
rewriter, loc, tileSizes, reductionDims);
|
|
}
|
|
default:
|
|
return rewriter.notifyMatchFailure(op,
|
|
"unhandled reduction tiling strategy");
|
|
}
|
|
}
|
|
|
|
static FailureOr<TilingResult>
|
|
getTiledImplementation(RewriterBase &rewriter, TilingInterface op,
|
|
ValueRange regionIterArg, ArrayRef<OpFoldResult> offsets,
|
|
ArrayRef<OpFoldResult> sizes,
|
|
const scf::SCFTilingOptions &options) {
|
|
switch (options.reductionStrategy) {
|
|
case scf::SCFTilingOptions::ReductionTilingStrategy::FullReduction:
|
|
return op.getTiledImplementation(rewriter, offsets, sizes);
|
|
case scf::SCFTilingOptions::ReductionTilingStrategy::
|
|
PartialReductionOuterReduction: {
|
|
auto redOp = dyn_cast<PartialReductionOpInterface>(op.getOperation());
|
|
if (!redOp) {
|
|
return rewriter.notifyMatchFailure(
|
|
op, "PartialReductionOuterReduction tiling strategy is only "
|
|
"supported for operations "
|
|
"implementing PartialReductionOpInterface");
|
|
}
|
|
// Get reduction dimensions.
|
|
// TODO: PartialReductionOpInterface should really query TilingInterface
|
|
// itself and find reduction dimensions.
|
|
SmallVector<int> reductionDims;
|
|
for (auto [idx, iteratorType] :
|
|
llvm::enumerate(op.getLoopIteratorTypes())) {
|
|
if (iteratorType == utils::IteratorType::reduction)
|
|
reductionDims.push_back(idx);
|
|
}
|
|
return redOp.tileToPartialReduction(rewriter, op.getLoc(), regionIterArg,
|
|
offsets, sizes, reductionDims);
|
|
}
|
|
default:
|
|
return rewriter.notifyMatchFailure(op,
|
|
"unhandled reduction tiling strategy");
|
|
}
|
|
}
|
|
|
|
static LogicalResult
|
|
getResultTilePosition(RewriterBase &rewriter, int64_t index, Value tiledResult,
|
|
TilingInterface op, ArrayRef<OpFoldResult> offsets,
|
|
ArrayRef<OpFoldResult> sizes,
|
|
SmallVector<OpFoldResult> &resultOffset,
|
|
SmallVector<OpFoldResult> &resultSize,
|
|
const scf::SCFTilingOptions &options) {
|
|
|
|
switch (options.reductionStrategy) {
|
|
case scf::SCFTilingOptions::ReductionTilingStrategy::FullReduction:
|
|
return op.getResultTilePosition(rewriter, index, offsets, sizes,
|
|
resultOffset, resultSize);
|
|
case scf::SCFTilingOptions::ReductionTilingStrategy::
|
|
PartialReductionOuterReduction: {
|
|
auto redOp = dyn_cast<PartialReductionOpInterface>(op.getOperation());
|
|
if (!redOp) {
|
|
return rewriter.notifyMatchFailure(
|
|
op, "PartialReductionOuterReduction tiling strategy is only supported"
|
|
"for operations implementing PartialReductionOpInterface");
|
|
}
|
|
// Get reduction dimensions.
|
|
// TODO: PartialReductionOpInterface should really query TilingInterface
|
|
// itself and find reduction dimensions.
|
|
SmallVector<int> reductionDims;
|
|
for (auto [idx, iteratorType] :
|
|
llvm::enumerate(op.getLoopIteratorTypes())) {
|
|
if (iteratorType == utils::IteratorType::reduction)
|
|
reductionDims.push_back(idx);
|
|
}
|
|
return redOp.getPartialResultTilePosition(rewriter, index, offsets, sizes,
|
|
resultOffset, resultSize,
|
|
reductionDims);
|
|
}
|
|
default:
|
|
return rewriter.notifyMatchFailure(op,
|
|
"unhandled reduction tiling strategy");
|
|
}
|
|
}
|
|
|
|
static FailureOr<MergeResult>
|
|
mergeTilingResults(RewriterBase &rewriter, TilingInterface op,
|
|
ValueRange partialResults,
|
|
const scf::SCFTilingOptions &options) {
|
|
switch (options.reductionStrategy) {
|
|
case scf::SCFTilingOptions::ReductionTilingStrategy::FullReduction:
|
|
// No need to merge results for reduction tiling strategy.
|
|
return MergeResult{{}, partialResults};
|
|
case scf::SCFTilingOptions::ReductionTilingStrategy::
|
|
PartialReductionOuterReduction: {
|
|
auto redOp = dyn_cast<PartialReductionOpInterface>(op.getOperation());
|
|
if (!redOp) {
|
|
return rewriter.notifyMatchFailure(
|
|
op, "PartialReductionOuterReduction tiling strategy is only "
|
|
"supported for operations "
|
|
"implementing PartialReductionOpInterface");
|
|
}
|
|
// Get reduction dimensions.
|
|
// TODO: PartialReductionOpInterface should really query TilingInterface
|
|
// itself and find reduction dimensions.
|
|
SmallVector<int> reductionDims;
|
|
for (auto [idx, iteratorType] :
|
|
llvm::enumerate(op.getLoopIteratorTypes())) {
|
|
if (iteratorType == utils::IteratorType::reduction)
|
|
reductionDims.push_back(idx);
|
|
}
|
|
return redOp.mergeReductions(rewriter, op.getLoc(), partialResults,
|
|
reductionDims);
|
|
}
|
|
default:
|
|
return rewriter.notifyMatchFailure(op,
|
|
"unhandled reduction tiling strategy");
|
|
}
|
|
}
|
|
|
|
/// Append the specified additional `newInitOperands` operands to the
|
|
/// loops existing `init` operands (or similar), and replace `loopOp` with
|
|
/// the new loop that has the additional init operands. The loop body of
|
|
/// this loop is moved over to the new loop. `yieldTiledValuesFn`
|
|
/// is called to get the new tiled values returned, and the offset
|
|
/// and sizes at which the tiled value is inserted into the
|
|
/// new region iter_args that correspond to the newly added init operands.
|
|
template <typename LoopType>
|
|
FailureOr<LoopLikeOpInterface>
|
|
yieldTiledValuesAndReplaceLoop(LoopType loopOp, RewriterBase &rewriter,
|
|
ValueRange newInitOperands,
|
|
YieldTiledValuesFn yieldTiledValuesFn) {
|
|
return rewriter.notifyMatchFailure(loopOp, "unhandled loop type");
|
|
}
|
|
|
|
/// Implementation of `yieldTiledValuesAndReplaceLoop` for `scf.for`.
|
|
template <>
|
|
FailureOr<LoopLikeOpInterface> yieldTiledValuesAndReplaceLoop<scf::ForOp>(
|
|
scf::ForOp loopOp, RewriterBase &rewriter, ValueRange newInitOperands,
|
|
YieldTiledValuesFn yieldTiledValuesFn) {
|
|
OpBuilder::InsertionGuard g(rewriter);
|
|
Location loc = loopOp.getLoc();
|
|
rewriter.setInsertionPoint(loopOp);
|
|
|
|
auto inits = llvm::to_vector(loopOp.getInitArgs());
|
|
inits.append(newInitOperands.begin(), newInitOperands.end());
|
|
auto newLoop = rewriter.create<scf::ForOp>(
|
|
loc, loopOp.getLowerBound(), loopOp.getUpperBound(), loopOp.getStep(),
|
|
inits, [](OpBuilder &, Location, Value, ValueRange) {});
|
|
|
|
// Move the loop body to the new op.
|
|
Block *loopBody = loopOp.getBody();
|
|
Block *newLoopBody = newLoop.getBody();
|
|
rewriter.mergeBlocks(
|
|
loopBody, newLoopBody,
|
|
newLoopBody->getArguments().take_front(loopBody->getNumArguments()));
|
|
|
|
auto yieldOp = cast<scf::YieldOp>(newLoopBody->getTerminator());
|
|
rewriter.setInsertionPoint(yieldOp);
|
|
|
|
SmallVector<Value> tiledValues;
|
|
SmallVector<SmallVector<OpFoldResult>> resultOffsets, resultSizes;
|
|
ValueRange newRegionIterArgs =
|
|
newLoop.getRegionIterArgs().take_back(newInitOperands.size());
|
|
if (failed(yieldTiledValuesFn(rewriter, loc, newLoop.getInductionVar(),
|
|
newRegionIterArgs, tiledValues, resultOffsets,
|
|
resultSizes))) {
|
|
rewriter.eraseOp(newLoop);
|
|
return rewriter.notifyMatchFailure(loopOp, "failed to get tiled values");
|
|
}
|
|
|
|
SmallVector<Value> newYieldValues = llvm::to_vector(yieldOp.getOperands());
|
|
for (auto [tiledValue, regionIterArg, resultOffset, resultSize] :
|
|
llvm::zip_equal(tiledValues, newRegionIterArgs, resultOffsets,
|
|
resultSizes)) {
|
|
SmallVector<OpFoldResult> resultStride(resultOffset.size(),
|
|
rewriter.getIndexAttr(1));
|
|
Value insert = rewriter.create<tensor::InsertSliceOp>(
|
|
yieldOp->getLoc(), tiledValue, regionIterArg, resultOffset, resultSize,
|
|
resultStride);
|
|
newYieldValues.push_back(insert);
|
|
}
|
|
|
|
rewriter.replaceOpWithNewOp<scf::YieldOp>(yieldOp, newYieldValues);
|
|
rewriter.replaceOp(loopOp,
|
|
newLoop->getResults().take_front(loopOp.getNumResults()));
|
|
return cast<LoopLikeOpInterface>(newLoop.getOperation());
|
|
}
|
|
|
|
/// Implementation of `yieldTiledValuesAndReplaceLoop` for `scf.forall`
|
|
template <>
|
|
FailureOr<LoopLikeOpInterface> yieldTiledValuesAndReplaceLoop<scf::ForallOp>(
|
|
scf::ForallOp loopOp, RewriterBase &rewriter, ValueRange newInitOperands,
|
|
YieldTiledValuesFn yieldTiledValuesFn) {
|
|
OpBuilder::InsertionGuard g(rewriter);
|
|
Location loc = loopOp.getLoc();
|
|
rewriter.setInsertionPoint(loopOp);
|
|
auto inits = llvm::to_vector(loopOp.getOutputs());
|
|
inits.append(newInitOperands.begin(), newInitOperands.end());
|
|
auto newLoop = rewriter.create<scf::ForallOp>(
|
|
loc, loopOp.getMixedLowerBound(), loopOp.getMixedUpperBound(),
|
|
loopOp.getMixedStep(), inits, loopOp.getMapping(),
|
|
[](OpBuilder &, Location, ValueRange) {});
|
|
|
|
// Move the region of the current block to the newly created op.
|
|
Block *loopBody = loopOp.getBody();
|
|
Block *newLoopBody = newLoop.getBody();
|
|
rewriter.mergeBlocks(
|
|
loopBody, newLoopBody,
|
|
newLoopBody->getArguments().take_front(loopBody->getNumArguments()));
|
|
|
|
auto terminator = cast<scf::InParallelOp>(newLoopBody->getTerminator());
|
|
rewriter.setInsertionPoint(terminator);
|
|
SmallVector<Value> tiledValues;
|
|
SmallVector<SmallVector<OpFoldResult>> resultOffsets, resultSizes;
|
|
ValueRange regionIterArgs =
|
|
newLoop.getRegionIterArgs().take_back(newInitOperands.size());
|
|
if (failed(yieldTiledValuesFn(rewriter, loc, newLoop.getInductionVars(),
|
|
regionIterArgs, tiledValues, resultOffsets,
|
|
resultSizes))) {
|
|
rewriter.eraseOp(newLoop);
|
|
return rewriter.notifyMatchFailure(loopOp,
|
|
"failed to get yielded tiled values");
|
|
}
|
|
|
|
// Update the terminator.
|
|
rewriter.setInsertionPointToEnd(terminator.getBody());
|
|
|
|
for (auto [tiledValue, iterArg, resultOffset, resultSize] : llvm::zip_equal(
|
|
tiledValues, regionIterArgs, resultOffsets, resultSizes)) {
|
|
SmallVector<OpFoldResult> resultStride(resultOffset.size(),
|
|
rewriter.getIndexAttr(1));
|
|
rewriter.create<tensor::ParallelInsertSliceOp>(
|
|
terminator.getLoc(), tiledValue, iterArg, resultOffset, resultSize,
|
|
resultStride);
|
|
}
|
|
|
|
rewriter.replaceOp(loopOp,
|
|
newLoop->getResults().take_front(loopOp.getNumResults()));
|
|
return cast<LoopLikeOpInterface>(newLoop.getOperation());
|
|
}
|
|
|
|
/// Implementation of `yieldTiledValuesAndReplaceLoop` for
|
|
/// `LoopLikeOpInterface`, that just dispatches to the implementation for each
|
|
/// supported loop type.
|
|
FailureOr<LoopLikeOpInterface> yieldTiledValuesAndReplaceLoop(
|
|
LoopLikeOpInterface loopLikeOp, RewriterBase &rewriter,
|
|
ValueRange newInitOperands, YieldTiledValuesFn yieldTiledValuesFn) {
|
|
return TypeSwitch<Operation *, FailureOr<LoopLikeOpInterface>>(
|
|
loopLikeOp.getOperation())
|
|
.Case<scf::ForOp, scf::ForallOp>(
|
|
[&](auto loopOp) -> FailureOr<LoopLikeOpInterface> {
|
|
return yieldTiledValuesAndReplaceLoop(
|
|
loopOp, rewriter, newInitOperands, yieldTiledValuesFn);
|
|
})
|
|
.Default([&](auto loopOp) -> FailureOr<LoopLikeOpInterface> {
|
|
return rewriter.notifyMatchFailure(loopOp, "unhandled loop type");
|
|
});
|
|
}
|
|
|
|
/// Method to add new init values to a loop nest. Updates `loops` in-place
|
|
/// with new loops that use the `newInitValues`. The outer-loops are updated
|
|
/// to yield the new result values of the inner loop. For the innermost loop,
|
|
/// the call back `getNewYields` is invoked to get the additional values to
|
|
/// yield form the innermost loop.
|
|
static LogicalResult addInitOperandsToLoopNest(
|
|
RewriterBase &rewriter, MutableArrayRef<LoopLikeOpInterface> loops,
|
|
ValueRange newInitValues, YieldTiledValuesFn getNewTiledYieldsFn) {
|
|
SmallVector<scf::ForOp> newLoops;
|
|
if (loops.empty())
|
|
return success();
|
|
OpBuilder::InsertionGuard g(rewriter);
|
|
rewriter.setInsertionPoint(loops.front());
|
|
|
|
SmallVector<Value> ivs;
|
|
for (auto &loop : loops.drop_back()) {
|
|
rewriter.setInsertionPoint(loop);
|
|
|
|
// if loops.size() > 1 we assume that scf.for is used for the loops.
|
|
auto forLoop = cast<scf::ForOp>(loop.getOperation());
|
|
|
|
// Create a new loop with the new init values for this loop.
|
|
SmallVector<Value> newInits = llvm::to_vector(forLoop.getInitArgs());
|
|
newInits.append(newInitValues.begin(), newInitValues.end());
|
|
auto newLoop = rewriter.create<scf::ForOp>(
|
|
forLoop.getLoc(), forLoop.getLowerBound(), forLoop.getUpperBound(),
|
|
forLoop.getStep(), newInits,
|
|
[&](OpBuilder &b, Location loc, Value iv, ValueRange iterArgs) {});
|
|
|
|
// Merge the body of the new loop with the body of the old loops.
|
|
SmallVector<Value> sourceBlockArgs;
|
|
sourceBlockArgs.push_back(newLoop.getInductionVar());
|
|
auto newRegionIterArgs = newLoop.getRegionIterArgs();
|
|
sourceBlockArgs.append(
|
|
newRegionIterArgs.begin(),
|
|
std::next(newRegionIterArgs.begin(), forLoop.getNumResults()));
|
|
rewriter.mergeBlocks(forLoop.getBody(), newLoop.getBody(), sourceBlockArgs);
|
|
rewriter.replaceOp(
|
|
forLoop, newLoop.getResults().take_front(forLoop.getNumResults()));
|
|
loop = newLoop;
|
|
ivs.push_back(newLoop.getInductionVar());
|
|
newInitValues = newLoop.getRegionIterArgs().take_back(newInitValues.size());
|
|
}
|
|
|
|
// Update the loop body of the innermost loop to get new yield values.
|
|
LoopLikeOpInterface innerMostLoop = loops.back();
|
|
FailureOr<LoopLikeOpInterface> newInnerMostLoop =
|
|
yieldTiledValuesAndReplaceLoop(innerMostLoop, rewriter, newInitValues,
|
|
getNewTiledYieldsFn);
|
|
|
|
if (failed(newInnerMostLoop))
|
|
return innerMostLoop.emitOpError("failed to return additional yields");
|
|
loops.back() = newInnerMostLoop.value();
|
|
|
|
// Make all other loops except the innermost loops yield the values returned
|
|
// by the inner loop.
|
|
for (auto [outerLoop, innerLoop] :
|
|
llvm::zip_equal(loops.drop_back(), loops.drop_front())) {
|
|
// Again assume that all the outer loops are scf.for operations.
|
|
auto outerForLoop = cast<scf::ForOp>(outerLoop);
|
|
auto outerLoopYield =
|
|
cast<scf::YieldOp>(outerForLoop.getBody()->getTerminator());
|
|
SmallVector<Value> newYields =
|
|
llvm::to_vector(outerLoopYield.getOperands());
|
|
ValueRange additionalYields =
|
|
innerLoop->getResults().take_back(newInitValues.size());
|
|
newYields.append(additionalYields.begin(), additionalYields.end());
|
|
rewriter.setInsertionPoint(outerLoopYield);
|
|
rewriter.replaceOpWithNewOp<scf::YieldOp>(outerLoopYield, newYields);
|
|
}
|
|
return success();
|
|
}
|
|
|
|
/// Implementation of tiling transformation of `op` that implements the
|
|
/// `TilingInterface` using `scf.for` to iterate over the tiles.
|
|
FailureOr<scf::SCFTilingResult>
|
|
mlir::scf::tileUsingSCF(RewriterBase &rewriter, TilingInterface op,
|
|
const scf::SCFTilingOptions &options) {
|
|
if (failed(verifyTileSizeOptions(rewriter, op.getLoc(), options))) {
|
|
return failure();
|
|
}
|
|
|
|
OpBuilder::InsertionGuard guard(rewriter);
|
|
rewriter.setInsertionPointAfter(op);
|
|
|
|
// 1. Get the range of the loops that are represented by the operation.
|
|
SmallVector<Range> iterationDomain = op.getIterationDomain(rewriter);
|
|
|
|
// 2. Materialize the tile sizes and/or number of threads;
|
|
SmallVector<OpFoldResult> tileSizes, numThreads;
|
|
std::tie(tileSizes, numThreads) =
|
|
getUserTileSizesAndNumThreads(rewriter, op, iterationDomain, options);
|
|
|
|
// Check if it is safe to tile. This is hold over from previous iterations
|
|
// of tile to for-all. Consider dropping it.
|
|
if (options.loopType == scf::SCFTilingOptions::LoopType::ForallOp) {
|
|
checkSafeToTileToForall(op, tileSizes, numThreads);
|
|
}
|
|
|
|
// 3. If there is an interchange specified, permute the iteration domain and
|
|
// the tile sizes.
|
|
SmallVector<int64_t> interchangeVector;
|
|
if (!options.interchangeVector.empty()) {
|
|
interchangeVector = fillInterchangeVector(options.interchangeVector,
|
|
iterationDomain.size());
|
|
assert(isPermutationVector(interchangeVector) &&
|
|
"expected interchange vector to be a permutation");
|
|
|
|
applyPermutationToVector(iterationDomain, interchangeVector);
|
|
applyPermutationToVector(tileSizes, interchangeVector);
|
|
if (!numThreads.empty())
|
|
applyPermutationToVector(numThreads, interchangeVector);
|
|
}
|
|
|
|
FailureOr<TilingResult> tilingResult;
|
|
// 4. Define the lambda function used later to generate the body of the
|
|
// innermost tiled loop.
|
|
YieldTiledValuesFn innerYieldTiledValuesFn =
|
|
[&](RewriterBase &rewriter, Location loc, ValueRange ivs,
|
|
ValueRange regionIterArgs, SmallVector<Value> &tiledResults,
|
|
SmallVector<SmallVector<OpFoldResult>> &resultOffsets,
|
|
SmallVector<SmallVector<OpFoldResult>> &resultSizes)
|
|
-> LogicalResult {
|
|
// 4a. Compute the `offsets` and `sizes` to use for tiling.
|
|
SmallVector<OpFoldResult> offsets, sizes;
|
|
std::tie(offsets, sizes) = getTileOffsetAndSizes(
|
|
rewriter, loc, ivs, iterationDomain, tileSizes, numThreads);
|
|
|
|
// 4b. If interchange was provided, apply inverse of the interchange
|
|
// to get back the offsets/sizes in the order to be specified.
|
|
if (!interchangeVector.empty()) {
|
|
auto inversePermutation = invertPermutationVector(interchangeVector);
|
|
applyPermutationToVector(offsets, inversePermutation);
|
|
applyPermutationToVector(sizes, inversePermutation);
|
|
}
|
|
|
|
// 5. Generate the tiled implementation within the inner most loop.
|
|
|
|
// 5a. Clone the operation within the loop body.
|
|
auto clonedOp = cast<TilingInterface>(
|
|
cloneOpAndUpdateDestinationArgs(rewriter, op, regionIterArgs));
|
|
|
|
// 5b. Early return cloned op if tiling is not happening. We can not
|
|
// return the original op because it could lead to `rewriter.replaceOp(op,
|
|
// op->getResults())` and users would get crash.
|
|
if (llvm::all_of(tileSizes, isZeroIndex)) {
|
|
tiledResults.append(clonedOp->result_begin(), clonedOp->result_end());
|
|
tilingResult =
|
|
TilingResult{/*tiledOps=*/{clonedOp}, clonedOp->getResults(),
|
|
/*generatedSlices=*/{}};
|
|
return success();
|
|
}
|
|
|
|
// 5c. Tile the cloned operation.
|
|
tilingResult = getTiledImplementation(rewriter, clonedOp, regionIterArgs,
|
|
offsets, sizes, options);
|
|
if (failed(tilingResult)) {
|
|
rewriter.eraseOp(clonedOp);
|
|
return op.emitOpError("faild to tile operation");
|
|
}
|
|
|
|
// 5d. Delete the cloned operation.
|
|
rewriter.eraseOp(clonedOp);
|
|
|
|
// 5e. Compute the offsets at which the result values are to be inserted
|
|
// back into its destinations.
|
|
for (auto [index, tiledValue] :
|
|
llvm::enumerate(tilingResult->tiledValues)) {
|
|
tiledResults.push_back(tiledValue);
|
|
SmallVector<OpFoldResult> resultOffset, resultSize;
|
|
if (failed(getResultTilePosition(rewriter, index, tiledValue, op, offsets,
|
|
sizes, resultOffset, resultSize,
|
|
options))) {
|
|
for (auto op : tilingResult->tiledOps) {
|
|
rewriter.eraseOp(op);
|
|
}
|
|
return rewriter.notifyMatchFailure(
|
|
op, "failed to get slice of result produced");
|
|
}
|
|
resultOffsets.emplace_back(std::move(resultOffset));
|
|
resultSizes.emplace_back(std::move(resultSize));
|
|
}
|
|
|
|
return success();
|
|
};
|
|
|
|
// 6. Find the destination tensors to use for the operation.
|
|
FailureOr<SmallVector<Value>> maybeInits =
|
|
createInitialTensorsForTiling(rewriter, op, tileSizes, options);
|
|
if (failed(maybeInits)) {
|
|
return rewriter.notifyMatchFailure(
|
|
op, "unable to create initial tensors for tiling");
|
|
}
|
|
SmallVector<Value> &initTensors = maybeInits.value();
|
|
|
|
// 7. Generate the tiled loops nest using the callback defined above.
|
|
SmallVector<LoopLikeOpInterface> loops;
|
|
if (failed(generateLoopNest(rewriter, op.getLoc(), options, iterationDomain,
|
|
tileSizes, numThreads, initTensors,
|
|
innerYieldTiledValuesFn, loops)))
|
|
return op.emitOpError("failed to generate tiling loops");
|
|
assert(succeeded(tilingResult) &&
|
|
"expected tiling result to be computed after loop generation");
|
|
|
|
SmallVector<Value> partialResults;
|
|
if (loops.empty()) {
|
|
// If loops are empty, the tiled op is used as the replacement for the
|
|
// untiled op.
|
|
partialResults = tilingResult->tiledValues;
|
|
} else {
|
|
partialResults = llvm::map_to_vector(loops.front()->getResults(),
|
|
[](OpResult r) -> Value { return r; });
|
|
}
|
|
|
|
FailureOr<MergeResult> mergeResult =
|
|
mergeTilingResults(rewriter, op, partialResults, options);
|
|
if (failed(mergeResult)) {
|
|
return rewriter.notifyMatchFailure(
|
|
op, "Failed to merge partial results from tiling");
|
|
}
|
|
|
|
return scf::SCFTilingResult{tilingResult->tiledOps, initTensors, loops,
|
|
mergeResult.value(),
|
|
tilingResult->generatedSlices};
|
|
}
|
|
|
|
FailureOr<scf::SCFTilingResult>
|
|
mlir::scf::tileReductionUsingScf(RewriterBase &b,
|
|
PartialReductionOpInterface op,
|
|
ArrayRef<OpFoldResult> tileSizes) {
|
|
SCFTilingOptions options;
|
|
options.setLoopType(SCFTilingOptions::LoopType::ForOp);
|
|
options.setReductionTilingStrategy(SCFTilingOptions::ReductionTilingStrategy::
|
|
PartialReductionOuterReduction);
|
|
options.setTileSizes(tileSizes);
|
|
|
|
TilingInterface tilingInterfaceOp =
|
|
dyn_cast<TilingInterface>(op.getOperation());
|
|
if (!tilingInterfaceOp) {
|
|
return b.notifyMatchFailure(
|
|
op,
|
|
"Operation implementing PartialReductionOpInterface should implement "
|
|
"TilingInterface");
|
|
}
|
|
|
|
return tileUsingSCF(b, tilingInterfaceOp, options);
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// tileConsumerAndFuseProducersUsingSCF implementation.
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
/// Return the untiled producer whose slice is used in a tiled consumer. The
|
|
/// method traverses the tile loop nest (`loops`) if needed, and returns the
|
|
/// `iter_args` of the outer most that is encountered. Traversing the
|
|
/// iter_args indicates that this is a destination operand of the consumer. If
|
|
/// there was no loop traversal needed, the second value of the returned tuple
|
|
/// is empty.
|
|
static std::tuple<OpResult, std::optional<OpOperand *>>
|
|
getUntiledProducerFromSliceSource(OpOperand *source,
|
|
ArrayRef<LoopLikeOpInterface> loops) {
|
|
std::optional<OpOperand *> destinationIterArg;
|
|
assert(!loops.empty() && "expected non empty loops container");
|
|
auto loopIt = loops.rbegin();
|
|
while (loopIt != loops.rend() && isa<BlockArgument>(source->get())) {
|
|
auto iterArg = cast<BlockArgument>(source->get());
|
|
auto loop = *loopIt;
|
|
if (iterArg.getOwner()->getParentOp() != loop)
|
|
break;
|
|
source = loop.getTiedLoopInit(iterArg);
|
|
loopIt++;
|
|
}
|
|
if (loopIt == loops.rend())
|
|
destinationIterArg = source;
|
|
return {dyn_cast<OpResult>(source->get()), destinationIterArg};
|
|
}
|
|
|
|
/// Implementation of fusing producer of a single slice by computing the
|
|
/// slice of the producer in-place.
|
|
std::optional<scf::SCFFuseProducerOfSliceResult>
|
|
mlir::scf::tileAndFuseProducerOfSlice(
|
|
RewriterBase &rewriter, tensor::ExtractSliceOp candidateSliceOp,
|
|
MutableArrayRef<LoopLikeOpInterface> loops) {
|
|
// 1. Get the producer of the source (potentially walking through
|
|
// `iter_args` of nested `scf.for`)
|
|
auto [fusableProducer, destinationInitArg] =
|
|
getUntiledProducerFromSliceSource(&candidateSliceOp.getSourceMutable(),
|
|
loops);
|
|
if (!fusableProducer)
|
|
return std::nullopt;
|
|
unsigned resultNumber = fusableProducer.getResultNumber();
|
|
|
|
OpBuilder::InsertionGuard g(rewriter);
|
|
rewriter.setInsertionPoint(candidateSliceOp);
|
|
|
|
// 2. Clone the fused producer
|
|
// 2a. Compute the destination operands to use for the cloned operation.
|
|
SmallVector<Value> origDestinationTensors, clonedOpDestinationTensors;
|
|
Operation *fusableProducerOp = fusableProducer.getOwner();
|
|
if (isa<DestinationStyleOpInterface>(fusableProducerOp) &&
|
|
failed(tensor::getOrCreateDestinations(
|
|
rewriter, fusableProducerOp->getLoc(), fusableProducerOp,
|
|
origDestinationTensors)))
|
|
return std::nullopt;
|
|
|
|
clonedOpDestinationTensors = origDestinationTensors;
|
|
if (destinationInitArg &&
|
|
isa<DestinationStyleOpInterface>(fusableProducerOp)) {
|
|
// 2b. If the producer is also destination style, then to maintain the
|
|
// destination passing style, update the destination of the producer to be
|
|
// the source of the slice.
|
|
clonedOpDestinationTensors[resultNumber] = candidateSliceOp.getSource();
|
|
}
|
|
// 2c. Clone the fused producer.
|
|
Operation *clonedProducerOp = cloneOpAndUpdateDestinationArgs(
|
|
rewriter, fusableProducerOp, clonedOpDestinationTensors);
|
|
// 2d. Update the source of the candidateSlice to be the cloned producer.
|
|
// Easier to just clone the slice with different source since
|
|
// replacements and DCE of cloned ops becomes easier
|
|
SmallVector<Value> candidateSliceOpOperands =
|
|
llvm::to_vector(candidateSliceOp->getOperands());
|
|
candidateSliceOpOperands[0] = clonedProducerOp->getResult(resultNumber);
|
|
tensor::ExtractSliceOp clonedCandidateSliceOp =
|
|
mlir::clone(rewriter, candidateSliceOp,
|
|
candidateSliceOp->getResultTypes(), candidateSliceOpOperands);
|
|
|
|
// 3. Generate the tiled implementation of the producer of the source
|
|
FailureOr<TilingResult> tileAndFuseResult =
|
|
tensor::replaceExtractSliceWithTiledProducer(
|
|
rewriter, clonedCandidateSliceOp,
|
|
clonedProducerOp->getResult(resultNumber));
|
|
if (failed(tileAndFuseResult))
|
|
return std::nullopt;
|
|
// Note: Do not delete the candidateSliceOp, since its passed in from the
|
|
// caller.
|
|
rewriter.replaceAllUsesWith(candidateSliceOp,
|
|
tileAndFuseResult->tiledValues[0]);
|
|
rewriter.eraseOp(clonedCandidateSliceOp);
|
|
rewriter.eraseOp(clonedProducerOp);
|
|
|
|
// 3. If the slice is for a destination operand, for example,
|
|
//
|
|
// ```mlir
|
|
// %0 = linalg.init
|
|
// %1 = linalg.fill .. outs(%0 : )
|
|
// %2 = scf.for .. iter_args(%arg0 = %1) {
|
|
// %3 = scf.for .. iter_args(%arg1 = %arg0) {
|
|
// %4 = tensor.extract_slice %arg1 [..]
|
|
// .. = linalg.matmul .. outs(%4 : )
|
|
// }
|
|
// }
|
|
// ```
|
|
//
|
|
// the IR is currently
|
|
//
|
|
// ```
|
|
// %0 = linalg.init
|
|
// %1 = linalg.fill
|
|
// %2 = scf.for .. iter_args(%arg0 = %1 /* incorrect value */ ) {
|
|
// %3 = scf.for .. iter_args(%arg1 = %arg0) {
|
|
// %4 = tensor.extract_slice %arg1[..]
|
|
// %5 = linalg.fill .. outs(%4 : )
|
|
// .. = linalg.matmul .. outs(%5 : )
|
|
// }
|
|
// }
|
|
// ```
|
|
//
|
|
// The untiled `linalg.fill` is still used as the `init_value` since it
|
|
// was originally a destination operand of the untiled `linalg.matmul`.
|
|
// When fusing an operand that is a destination operand, the iter_arg of
|
|
// the outer most loop should be changed to use the destination of the
|
|
// fused operation. With this the IR will be.
|
|
//
|
|
// ```
|
|
// %0 = linalg.init
|
|
// %1 = scf.for .. iter_args(%arg0 = %0 /* corrected value */ ) {
|
|
// %2 = scf.for .. iter_args(%arg1 = %arg0) {
|
|
// %3 = tensor.extract_slice %arg1[..]
|
|
// %4 = linalg.fill .. outs(%3 : )
|
|
// .. = linalg.matmul .. outs(%4 : )
|
|
// }
|
|
// }
|
|
// ```
|
|
if (destinationInitArg &&
|
|
isa<DestinationStyleOpInterface>(fusableProducerOp) && !loops.empty()) {
|
|
loops.front()
|
|
->getOpOperands()[destinationInitArg.value()->getOperandNumber()]
|
|
.set(origDestinationTensors[resultNumber]);
|
|
}
|
|
return scf::SCFFuseProducerOfSliceResult{
|
|
fusableProducer, tileAndFuseResult->tiledValues[0],
|
|
tileAndFuseResult->tiledOps, tileAndFuseResult->generatedSlices};
|
|
}
|
|
|
|
/// Reconstruct the fused producer from within the tiled-and-fused code.
|
|
FailureOr<SmallVector<Operation *>> mlir::scf::yieldReplacementForFusedProducer(
|
|
RewriterBase &rewriter, tensor::ExtractSliceOp sliceOp,
|
|
scf::SCFFuseProducerOfSliceResult fusedProducerInfo,
|
|
MutableArrayRef<LoopLikeOpInterface> loops,
|
|
ArrayRef<unsigned> yieldResultNumber) {
|
|
if (loops.empty())
|
|
return success();
|
|
|
|
Operation *originalOwner = fusedProducerInfo.origProducer.getOwner(),
|
|
*tiledOwner = fusedProducerInfo.tiledOps[0];
|
|
|
|
Location loc = originalOwner->getLoc();
|
|
// a. collect all init Value to be appended
|
|
SmallVector<unsigned> initNumberList =
|
|
yieldResultNumber.empty() ? llvm::to_vector(llvm::seq<unsigned>(
|
|
0, originalOwner->getNumResults()))
|
|
: llvm::to_vector(yieldResultNumber);
|
|
SmallVector<Value> initValueList;
|
|
for (const auto &resultNumber : initNumberList) {
|
|
FailureOr<Value> initValue = tensor::getOrCreateDestination(
|
|
rewriter, loc, originalOwner->getResult(resultNumber));
|
|
if (succeeded(initValue)) {
|
|
initValueList.push_back(initValue.value());
|
|
} else {
|
|
return failure();
|
|
}
|
|
}
|
|
|
|
SmallVector<Operation *> generatedSlices;
|
|
YieldTiledValuesFn newYieldValuesFn =
|
|
[&](RewriterBase &innerRewriter, Location loc, ValueRange /*ivs*/,
|
|
ValueRange newRegionIterArgs, SmallVector<Value> &tiledResult,
|
|
SmallVector<SmallVector<OpFoldResult>> &tiledOffset,
|
|
SmallVector<SmallVector<OpFoldResult>> &tiledSizes) -> LogicalResult {
|
|
OpBuilder::InsertionGuard g(innerRewriter);
|
|
|
|
// get sliceOp tile information
|
|
SmallVector<OpFoldResult> sliceOffset = sliceOp.getMixedOffsets(),
|
|
sliceSizes = sliceOp.getMixedSizes();
|
|
|
|
// expect all strides of sliceOp being 1
|
|
if (llvm::any_of(sliceOp.getMixedStrides(), [](OpFoldResult ofr) {
|
|
return !isConstantIntValue(ofr, 1);
|
|
}))
|
|
return failure();
|
|
|
|
unsigned sliceResultNumber =
|
|
fusedProducerInfo.origProducer.getResultNumber();
|
|
|
|
auto tilableOp = cast<TilingInterface>(originalOwner);
|
|
// b. get iterDomain Offset and Sizes based on sliceOp tile
|
|
SmallVector<OpFoldResult> iterDomainOffset, iterDomainSizes;
|
|
// skip tensor.pack/unpack/pad, which expects single opResult
|
|
if (tilableOp->getNumResults() > 1 &&
|
|
failed(tilableOp.getIterationDomainTileFromResultTile(
|
|
rewriter, sliceResultNumber, sliceOffset, sliceSizes,
|
|
iterDomainOffset, iterDomainSizes))) {
|
|
// In theory, it is unnecessary to raise an error here. Actually
|
|
// although it fails to reconstruct the result tensor, it should not
|
|
// broke current fusion anyway. The reason why we must return failure
|
|
// currently is that the callback function `newYieldValuesFn` will be
|
|
// called after new init operand(s) has already been appended. It will
|
|
// take more refactoring to make sure the init operands are added
|
|
// consistently in the future. For more details, please refer to:
|
|
// https://github.com/llvm/llvm-project/pull/93144#discussion_r1643760814
|
|
return failure();
|
|
}
|
|
|
|
// c. calculate offsets and sizes info of all OpResults respectively based
|
|
// on iteration Domain Tile
|
|
SmallVector<SmallVector<OpFoldResult>> offsetList, sizesList;
|
|
for (const auto &resultNumber : initNumberList) {
|
|
if (resultNumber == sliceResultNumber) {
|
|
offsetList.push_back(sliceOffset);
|
|
sizesList.push_back(sliceSizes);
|
|
} else {
|
|
assert(!iterDomainOffset.empty() && !iterDomainSizes.empty());
|
|
// infer result tile according to the iteration domain tile
|
|
SmallVector<OpFoldResult> offset, sizes;
|
|
if (failed(tilableOp.getResultTilePosition(
|
|
rewriter, resultNumber, iterDomainOffset, iterDomainSizes,
|
|
offset, sizes))) {
|
|
return failure();
|
|
}
|
|
offsetList.push_back(offset);
|
|
sizesList.push_back(sizes);
|
|
}
|
|
}
|
|
|
|
// d. create `extract_slice` for `iter_args` for DPS operation if
|
|
// necessary
|
|
if (auto tiledDestStyleOp =
|
|
dyn_cast<DestinationStyleOpInterface>(tiledOwner)) {
|
|
rewriter.setInsertionPoint(tiledDestStyleOp);
|
|
for (const auto &&[index, newRegionArg] :
|
|
llvm::enumerate(newRegionIterArgs)) {
|
|
auto destSlice = rewriter.create<tensor::ExtractSliceOp>(
|
|
loc, newRegionArg, offsetList[index], sizesList[index],
|
|
SmallVector<OpFoldResult>(offsetList[index].size(),
|
|
rewriter.getIndexAttr(1)));
|
|
generatedSlices.push_back(destSlice);
|
|
unsigned resultNumber = initNumberList[index];
|
|
rewriter.modifyOpInPlace(tiledDestStyleOp, [&]() {
|
|
tiledDestStyleOp.getDpsInitsMutable()[resultNumber].set(destSlice);
|
|
});
|
|
}
|
|
}
|
|
|
|
// e. prepare tiled offset and sizes for later `insert_slice` creation by
|
|
// caller
|
|
Block *block = rewriter.getInsertionPoint()->getBlock();
|
|
rewriter.setInsertionPoint(block->getTerminator());
|
|
for (const auto &&[index, resultNumber] : llvm::enumerate(initNumberList)) {
|
|
tiledResult.push_back(tiledOwner->getResult(resultNumber));
|
|
tiledOffset.emplace_back(offsetList[index]);
|
|
tiledSizes.emplace_back(sizesList[index]);
|
|
}
|
|
return success();
|
|
};
|
|
|
|
if (failed(addInitOperandsToLoopNest(rewriter, loops, initValueList,
|
|
newYieldValuesFn))) {
|
|
return failure();
|
|
}
|
|
return generatedSlices;
|
|
}
|
|
|
|
namespace {
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// SliceTrackingListener
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
/// This class is a listener for tracking the insertion and removal of
|
|
/// `tensor.extract_slice` ops in a worklist. This can be used in a greedy
|
|
/// fusion algorithm to apply cleanup patterns in between fusion steps.
|
|
class SliceTrackingListener : public RewriterBase::Listener {
|
|
public:
|
|
explicit SliceTrackingListener(
|
|
std::optional<FrozenRewritePatternSet> patterns);
|
|
SliceTrackingListener() = default;
|
|
|
|
/// Adds the given list of operations to the worklist, and if present,
|
|
/// applies the list of `patterns` to the newly added operations. This only
|
|
/// processes the given operations and any newly inserted ones by the
|
|
/// pattern set.
|
|
LogicalResult insertAndApplyPatterns(ArrayRef<Operation *> newOps);
|
|
|
|
/// Add to the new operation worklist if it is an extract_slice.
|
|
void notifyOperationInserted(Operation *op,
|
|
OpBuilder::InsertPoint previous) override;
|
|
|
|
/// Shared helper for operation removal from the worklist.
|
|
void removeOp(Operation *op);
|
|
|
|
/// Remove the operation from the worklist.
|
|
void notifyOperationErased(Operation *op) override;
|
|
|
|
/// Remove the operation from the worklist.
|
|
void notifyOperationReplaced(Operation *op, ValueRange replacement) override;
|
|
|
|
/// The worklist for this transformation keeps track of the slices to visit
|
|
/// next for fusion.
|
|
std::deque<tensor::ExtractSliceOp> worklist;
|
|
|
|
private:
|
|
/// Optional pattern set to apply when adding new operations to the
|
|
/// worklist.
|
|
std::optional<FrozenRewritePatternSet> patterns = std::nullopt;
|
|
};
|
|
|
|
SliceTrackingListener::SliceTrackingListener(
|
|
std::optional<FrozenRewritePatternSet> p) {
|
|
patterns = std::move(p);
|
|
}
|
|
|
|
LogicalResult
|
|
SliceTrackingListener::insertAndApplyPatterns(ArrayRef<Operation *> ops) {
|
|
for (Operation *op : ops) {
|
|
if (auto slice = dyn_cast<tensor::ExtractSliceOp>(op))
|
|
worklist.push_back(slice);
|
|
}
|
|
|
|
if (!patterns)
|
|
return success();
|
|
|
|
return applyOpPatternsGreedily(
|
|
ops, patterns.value(),
|
|
GreedyRewriteConfig().setListener(this).setStrictness(
|
|
GreedyRewriteStrictness::ExistingAndNewOps));
|
|
}
|
|
|
|
void SliceTrackingListener::notifyOperationInserted(
|
|
Operation *op, OpBuilder::InsertPoint previous) {
|
|
auto slice = dyn_cast<tensor::ExtractSliceOp>(op);
|
|
if (!slice)
|
|
return;
|
|
worklist.push_back(slice);
|
|
}
|
|
|
|
// Scan the worklist for the given op and remove it if present. The
|
|
// expectation is for the worklist to be small and for removal to be
|
|
// relatively rare.
|
|
void SliceTrackingListener::removeOp(Operation *op) {
|
|
if (!isa<tensor::ExtractSliceOp>(op))
|
|
return;
|
|
auto iter = worklist.begin();
|
|
while (iter != worklist.end()) {
|
|
if (*iter == op)
|
|
break;
|
|
iter++;
|
|
}
|
|
if (iter == worklist.end())
|
|
return;
|
|
|
|
worklist.erase(iter);
|
|
}
|
|
|
|
void SliceTrackingListener::notifyOperationErased(Operation *op) {
|
|
removeOp(op);
|
|
}
|
|
|
|
void SliceTrackingListener::notifyOperationReplaced(Operation *op,
|
|
ValueRange replacement) {
|
|
removeOp(op);
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// ReplacementListener
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
/// Listener that tracks updates replacements for values which can be mutated.
|
|
/// This listener runs on top of the existing listener for the rewriter,
|
|
/// to make sure external users can still run listeners.
|
|
class ReplacementListener : public RewriterBase::ForwardingListener {
|
|
public:
|
|
ReplacementListener(DenseMap<Value, Value> &replacements,
|
|
OpBuilder::Listener *listener)
|
|
: ForwardingListener(listener), replacements(replacements) {}
|
|
|
|
void updateReplacementValues(ValueRange origValues,
|
|
ValueRange replaceValues) {
|
|
// This can probably be written better, but just iterates over the map
|
|
// and the new replacements for now.
|
|
for (auto &[key, val] : replacements) {
|
|
for (auto [orig, replace] : llvm::zip_equal(origValues, replaceValues)) {
|
|
if (val == orig) {
|
|
val = replace;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
void notifyOperationReplaced(Operation *op, Operation *newOp) override {
|
|
ForwardingListener::notifyOperationReplaced(op, newOp);
|
|
updateReplacementValues(op->getResults(), newOp->getResults());
|
|
}
|
|
|
|
void notifyOperationReplaced(Operation *op, ValueRange values) override {
|
|
ForwardingListener::notifyOperationReplaced(op, values);
|
|
updateReplacementValues(op->getResults(), values);
|
|
}
|
|
|
|
private:
|
|
DenseMap<Value, Value> &replacements;
|
|
};
|
|
|
|
} // namespace
|
|
|
|
/// Implementation of tile consumer and fuse producer greedily.
|
|
FailureOr<scf::SCFTileAndFuseResult>
|
|
mlir::scf::tileConsumerAndFuseProducersUsingSCF(
|
|
RewriterBase &rewriter, TilingInterface consumer,
|
|
const scf::SCFTileAndFuseOptions &options) {
|
|
// This transformation is only valid for ops that return values (i.e. not
|
|
// valid to use with operations that have memref operands).
|
|
if (!consumer->getNumResults()) {
|
|
return rewriter.notifyMatchFailure(
|
|
consumer, "invalid pattern for op with no results");
|
|
}
|
|
|
|
// 1. First tile the consumer.
|
|
SetVector<Operation *> fusedProducers, tiledAndFusedOps;
|
|
llvm::SmallDenseMap<Value, size_t> origProducerToLoopResultNum;
|
|
|
|
FailureOr<scf::SCFTilingResult> tilingResult =
|
|
tileUsingSCF(rewriter, consumer, options.tilingOptions);
|
|
|
|
if (failed(tilingResult))
|
|
return rewriter.notifyMatchFailure(consumer, "failed to tile consumer");
|
|
tiledAndFusedOps.insert_range(tilingResult->tiledOps);
|
|
|
|
DenseMap<Value, Value> replacements;
|
|
for (auto [origVal, replacement] : llvm::zip_equal(
|
|
consumer->getResults(), tilingResult->mergeResult.replacements)) {
|
|
replacements[origVal] = replacement;
|
|
}
|
|
|
|
// If there are no loops generated, fusion is immaterial.
|
|
auto &loops = tilingResult->loops;
|
|
if (loops.empty()) {
|
|
return scf::SCFTileAndFuseResult{fusedProducers, tiledAndFusedOps, loops,
|
|
replacements};
|
|
}
|
|
|
|
// Since the loop gets potentially replaced during fusion, we need to track
|
|
// the mutation of replacement values. To do this, we attach a listener to
|
|
// update the replacements as they happen.
|
|
OpBuilder::Listener *previousListener = rewriter.getListener();
|
|
auto resetListener =
|
|
llvm::make_scope_exit([&]() { rewriter.setListener(previousListener); });
|
|
ReplacementListener replaceListener(replacements, previousListener);
|
|
rewriter.setListener(&replaceListener);
|
|
|
|
// 2. Typically, the operands of the tiled operation are slices of the
|
|
// operands of the untiled operation. These are expressed in IR using
|
|
// `tensor.extract_slice` operations with source being the operands of
|
|
// the untiled operation. Create a worklist of these
|
|
// `tensor.extract_slice` operations. If the producers of the source of
|
|
// the `tensor.extract_slice` can be tiled such that the tiled value is
|
|
// generated in-place, that effectively tiles + fuses the operations.
|
|
struct WorklistItem {
|
|
tensor::ExtractSliceOp candidateSlice;
|
|
SCFTileAndFuseOptions::ControlFnResult controlFnResult;
|
|
};
|
|
|
|
SliceTrackingListener sliceTracker =
|
|
SliceTrackingListener(options.cleanupPatterns);
|
|
|
|
if (failed(
|
|
sliceTracker.insertAndApplyPatterns(tilingResult->generatedSlices))) {
|
|
return rewriter.notifyMatchFailure(consumer, "cleanup patterns failed");
|
|
}
|
|
OpBuilder::InsertionGuard g(rewriter);
|
|
while (!sliceTracker.worklist.empty()) {
|
|
auto candidateSlice = sliceTracker.worklist.front();
|
|
sliceTracker.worklist.pop_front();
|
|
|
|
auto [fusableProducer, destinationInitArg] =
|
|
getUntiledProducerFromSliceSource(&candidateSlice.getSourceMutable(),
|
|
loops);
|
|
if (!fusableProducer)
|
|
continue;
|
|
|
|
std::optional<SCFTileAndFuseOptions::ControlFnResult> controlFnResult =
|
|
options.fusionControlFn(candidateSlice, fusableProducer,
|
|
destinationInitArg.has_value());
|
|
if (!controlFnResult)
|
|
continue;
|
|
|
|
WorklistItem worklistItem = {candidateSlice, controlFnResult.value()};
|
|
|
|
// The operands of the fused producer might themselved be slices of
|
|
// values produced by operations that implement the `TilingInterface`.
|
|
// Add these operations to the worklist.
|
|
std::optional<scf::SCFFuseProducerOfSliceResult> fusedResult =
|
|
tileAndFuseProducerOfSlice(rewriter, worklistItem.candidateSlice,
|
|
loops);
|
|
if (!fusedResult)
|
|
continue;
|
|
|
|
SmallVector<Operation *> worklistCandidates = fusedResult->generatedSlices;
|
|
|
|
if (worklistItem.controlFnResult.yieldProducerReplacement) {
|
|
// Reconstruct and yield all opResult of fusableProducerOp by default.
|
|
// The caller can specific which one to yield by designating optional
|
|
// argument named `yieldResultNumber` of
|
|
// `yieldReplacementForFusedProducer`.
|
|
Operation *fusableProducerOp = fusedResult->origProducer.getOwner();
|
|
FailureOr<SmallVector<Operation *>> newSlices =
|
|
yieldReplacementForFusedProducer(rewriter,
|
|
worklistItem.candidateSlice,
|
|
fusedResult.value(), loops);
|
|
if (failed(newSlices)) {
|
|
return rewriter.notifyMatchFailure(
|
|
fusableProducerOp, "failed to replacement value for this "
|
|
"operation from within the tiled loop");
|
|
}
|
|
worklistCandidates.append(newSlices.value());
|
|
for (auto [index, result] :
|
|
llvm::enumerate(fusableProducerOp->getResults())) {
|
|
replacements[result] = loops.front()->getResult(
|
|
loops.front()->getNumResults() -
|
|
fusableProducerOp->getNumResults() + index);
|
|
}
|
|
}
|
|
if (Operation *tiledAndFusedOp =
|
|
fusedResult->tiledAndFusedProducer.getDefiningOp()) {
|
|
fusedProducers.insert(fusedResult->origProducer.getDefiningOp());
|
|
tiledAndFusedOps.insert(tiledAndFusedOp);
|
|
}
|
|
|
|
if (failed(sliceTracker.insertAndApplyPatterns(worklistCandidates))) {
|
|
return rewriter.notifyMatchFailure(consumer, "cleanup patterns failed");
|
|
}
|
|
}
|
|
|
|
return scf::SCFTileAndFuseResult{fusedProducers, tiledAndFusedOps, loops,
|
|
replacements};
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// tileAndFuseConsumerUsingSCF implementation.
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
/// A utility function that checks whether the only use of the result of a
|
|
/// tensor.insert_slice op is in a scf.yield op.
|
|
static LogicalResult
|
|
checkAssumptionForFusingConsumer(tensor::InsertSliceOp candidateSliceOp) {
|
|
Value result = candidateSliceOp.getResult();
|
|
Value::use_range uses = result.getUses();
|
|
if (!llvm::hasSingleElement(uses)) {
|
|
LLVM_DEBUG(llvm::dbgs() << "Too many uses of the candidate slice op\n");
|
|
return failure();
|
|
}
|
|
OpOperand &operandUse = (*uses.begin());
|
|
Operation *userOp = operandUse.getOwner();
|
|
if (!isa<scf::YieldOp>(userOp)) {
|
|
LLVM_DEBUG(llvm::dbgs()
|
|
<< "Expected scf.yield to be the only user, but got -> "
|
|
<< (*userOp));
|
|
return failure();
|
|
}
|
|
if (result.getDefiningOp()->getBlock() != userOp->getBlock()) {
|
|
LLVM_DEBUG(llvm::dbgs() << "Expected tensor.insert_slice and scf.yield to "
|
|
"be in the same block\n");
|
|
return failure();
|
|
}
|
|
return success();
|
|
}
|
|
|
|
/// An utility to get the first user of the given loopOp. If any of user stay
|
|
/// in different block of loopOp, return failure.
|
|
static FailureOr<Operation *> getFirstUserOfLoop(Operation *loopOp) {
|
|
if (!isa<LoopLikeOpInterface>(loopOp))
|
|
return failure();
|
|
Operation *firstUserOfLoop = nullptr;
|
|
for (Operation *userOp : loopOp->getUsers()) {
|
|
// `ParallelInsertSlice` located inside `InParallelOp` has no same parent
|
|
// block with any other types of operation. Thus, just redirecting to its
|
|
// parent `InParallelOp`. E.g.
|
|
//
|
|
// ```
|
|
// %1 = scf.for {
|
|
// ...
|
|
// }
|
|
// %2 = consumerOp ins(%1, ...)
|
|
// scf.forall.in_parallel {
|
|
// tensor.parallel_insert_slice %1
|
|
// }
|
|
// ```
|
|
// where `InParallelOp` but not `ParallelInsertSlice` stays in the same
|
|
// same block with `consumerOp`.
|
|
if (isa<tensor::ParallelInsertSliceOp>(userOp))
|
|
userOp = userOp->getParentOfType<scf::InParallelOp>();
|
|
|
|
if (loopOp->getBlock() != userOp->getBlock())
|
|
return failure();
|
|
|
|
if (!firstUserOfLoop || userOp->isBeforeInBlock(firstUserOfLoop))
|
|
firstUserOfLoop = userOp;
|
|
}
|
|
return firstUserOfLoop;
|
|
}
|
|
|
|
/// This utility currently checks whether the first userOp of loop is NOT
|
|
/// before the last defineOp of consumer operand. Because that we need to move
|
|
/// the whole loop structure right before the `firstUserOfLoop`. This utility
|
|
/// thus helps ensuring that no invalid IR is formed, i.e. no backward slice
|
|
/// of consumerOp is dominated by the `firstUserOfLoop`. Saying that:
|
|
///
|
|
/// ```
|
|
/// %0 = scf.for() {
|
|
/// ...
|
|
/// }
|
|
/// ...
|
|
/// %1 = firstUserOfLoop(%0)
|
|
/// ...
|
|
/// %2 = lastDefOfConsumerOperand
|
|
/// ...
|
|
/// %3 = consumerOp(%2)
|
|
/// ```
|
|
///
|
|
/// If the `firstUserOfLoop` is before `lastDefOfConsumerOperand`, then it
|
|
/// would be invalid to move the `loopOp` right before the `firstUserOfLoop`,
|
|
/// a.k.a. use-def chain violation:
|
|
///
|
|
/// ```
|
|
/// %0:2 = scf.for() {
|
|
/// // use before define error
|
|
/// %3 = tiledConsumerOp(%2)
|
|
/// }
|
|
/// %1 = firstUserOfLoop(%0)
|
|
/// ...
|
|
/// %2 = lastDefOfConsumerOperand
|
|
/// ```
|
|
///
|
|
/// @param loopOp: loop operation
|
|
/// @param consumerOp: consumer operation
|
|
/// @param reorderOperations: the flag controls whether to reorder the
|
|
/// backward slice w.r.t. the defineOp of `consumerOp` operands.
|
|
/// @return: computed backward slice of consumerOp, but excluding those
|
|
/// already dominates `firstUserOfLoop`.
|
|
static FailureOr<llvm::SetVector<Operation *>>
|
|
checkAssumptionForLoop(Operation *loopOp, Operation *consumerOp,
|
|
bool reorderOperations) {
|
|
FailureOr<Operation *> firstUserOfLoop = getFirstUserOfLoop(loopOp);
|
|
if (failed(firstUserOfLoop))
|
|
return failure();
|
|
|
|
BackwardSliceOptions options;
|
|
DominanceInfo dominanceInfo;
|
|
options.inclusive = true;
|
|
options.omitBlockArguments = true;
|
|
bool includeLoopOp = false;
|
|
options.filter = [&](Operation *op) {
|
|
if (op == loopOp) {
|
|
includeLoopOp = true;
|
|
return false;
|
|
}
|
|
// Cut off the slice to not include any operation that already dominates
|
|
// firstUserOfLoop.
|
|
return !dominanceInfo.properlyDominates(op, *firstUserOfLoop);
|
|
};
|
|
llvm::SetVector<Operation *> slice;
|
|
for (auto operand : consumerOp->getOperands()) {
|
|
getBackwardSlice(operand, &slice, options);
|
|
}
|
|
|
|
if (!slice.empty()) {
|
|
// If consumerOp has one producer, which is also the user of loopOp.
|
|
// E.g.
|
|
// ```
|
|
// %0 = %loopOp
|
|
// %1 = consumerOp1 ins(%0)
|
|
// %2 = consumerOp2 ins(%0, %1)
|
|
// ```
|
|
// We can not fuse consumerOp2 into loopOp due to UD chain, unless
|
|
// consumerOp1 has already been fused into loopOp before.
|
|
if (includeLoopOp || !reorderOperations)
|
|
return failure();
|
|
}
|
|
|
|
return slice;
|
|
}
|
|
|
|
/// Fetches the OpOperand of the first valid user (and use) of the value `val`
|
|
/// which implements `TilingInterface` and `DestinationStyleOpInterface`.
|
|
/// Returns failure otherwise.
|
|
static FailureOr<OpOperand *> getConsumerFromLoopUses(RewriterBase &rewriter,
|
|
Operation *loopOp,
|
|
unsigned resultNumber) {
|
|
if (!isa<LoopLikeOpInterface>(loopOp))
|
|
return failure();
|
|
Value val = loopOp->getResult(resultNumber);
|
|
Block *loopBlock = loopOp->getBlock();
|
|
for (OpOperand &opOperand : val.getUses()) {
|
|
Operation *consumerOp = opOperand.getOwner();
|
|
// Step 1. Check if the user is tilable.
|
|
if (!isa<TilingInterface>(consumerOp) ||
|
|
!isa<DestinationStyleOpInterface>(consumerOp)) {
|
|
// TODO: We have to init result of consumer before scf.for, use
|
|
// DestinationStyleOpInterface to get result shape from init for now.
|
|
// Add support for other op such as op has InferTypeOpInterface.
|
|
continue;
|
|
}
|
|
// Step 2. Check if user stay in the same block.
|
|
if (loopBlock != consumerOp->getBlock())
|
|
continue;
|
|
// Step 3. Check if user has succeeding user. Otherwise, it usually
|
|
// represents already tiled.
|
|
if (consumerOp->use_empty())
|
|
continue;
|
|
// Step 4. Check assumption for loop with `reorderOperations` enabled.
|
|
FailureOr<llvm::SetVector<Operation *>> slice =
|
|
checkAssumptionForLoop(loopOp, consumerOp, true);
|
|
if (failed(slice))
|
|
continue;
|
|
// Step 5. If backward sice is not empty, move them before
|
|
// firstUserOfLoop.
|
|
if (!slice->empty()) {
|
|
mlir::topologicalSort(*slice);
|
|
FailureOr<Operation *> firstUserOfLoop = getFirstUserOfLoop(loopOp);
|
|
assert(succeeded(firstUserOfLoop) && "First user of loop is not found");
|
|
for (auto op : *slice) {
|
|
rewriter.moveOpBefore(op, *firstUserOfLoop);
|
|
}
|
|
}
|
|
return &opOperand;
|
|
}
|
|
return failure();
|
|
}
|
|
|
|
/// Check that the loop is perfectly nested.
|
|
/// The loops are expected to be ordered from outer most to inner most.
|
|
/// For example:
|
|
/// ```
|
|
/// %0 = scf.for()
|
|
/// %1 = scf.for()
|
|
/// %2 = scf.for()
|
|
/// %3 = ...
|
|
/// yield %3
|
|
/// yield %2
|
|
/// yield %1
|
|
/// ```
|
|
/// Here loops should be [%0, %1].
|
|
static bool
|
|
isPerfectlyNestedForLoops(MutableArrayRef<LoopLikeOpInterface> loops) {
|
|
assert(!loops.empty() && "unexpected empty loop nest");
|
|
if (loops.size() == 1) {
|
|
return isa_and_nonnull<scf::ForOp>(loops.front().getOperation());
|
|
}
|
|
for (auto [outerLoop, innerLoop] :
|
|
llvm::zip_equal(loops.drop_back(), loops.drop_front())) {
|
|
auto outerFor = dyn_cast_or_null<scf::ForOp>(outerLoop.getOperation());
|
|
auto innerFor = dyn_cast_or_null<scf::ForOp>(innerLoop.getOperation());
|
|
if (!outerFor || !innerFor) {
|
|
return false;
|
|
}
|
|
auto outerBBArgs = outerFor.getRegionIterArgs();
|
|
auto innerIterArgs = innerFor.getInitArgs();
|
|
if (outerBBArgs.size() != innerIterArgs.size()) {
|
|
return false;
|
|
}
|
|
|
|
for (auto [outerBBArg, innerIterArg] :
|
|
llvm::zip_equal(outerBBArgs, innerIterArgs)) {
|
|
if (!llvm::hasSingleElement(outerBBArg.getUses()) ||
|
|
innerIterArg != outerBBArg) {
|
|
return false;
|
|
}
|
|
}
|
|
|
|
ValueRange outerYields =
|
|
cast<scf::YieldOp>(outerFor.getBody()->getTerminator())->getOperands();
|
|
ValueRange innerResults = innerFor.getResults();
|
|
if (outerYields.size() != innerResults.size()) {
|
|
return false;
|
|
}
|
|
for (auto [outerYield, innerResult] :
|
|
llvm::zip_equal(outerYields, innerResults)) {
|
|
if (!llvm::hasSingleElement(innerResult.getUses()) ||
|
|
outerYield != innerResult) {
|
|
return false;
|
|
}
|
|
}
|
|
}
|
|
return true;
|
|
}
|
|
|
|
/// Fetch the untiled consumer of the outermost scf.for's result which is
|
|
/// yielded by a tensor.insert_slice from the innermost scf.for. This function
|
|
/// makes the following assumptions :
|
|
/// 1. tensor.insert_slice has scf.yield as its only user.
|
|
/// 2. scf.for's corresponding result has only one use.
|
|
/// 3. The `loops` passed in are perfectly nested `scf.for` operations.
|
|
static FailureOr<OpOperand *>
|
|
getUntiledConsumerFromSlice(RewriterBase &rewriter,
|
|
tensor::InsertSliceOp candidateSliceOp,
|
|
MutableArrayRef<LoopLikeOpInterface> loops) {
|
|
assert(!loops.empty() && "unexpected loops to be empty");
|
|
// 1. Expect slice to be part of the body of the inner most loop.
|
|
Operation *containingOp = candidateSliceOp->getParentOp();
|
|
if (containingOp != loops.back()) {
|
|
return rewriter.notifyMatchFailure(
|
|
candidateSliceOp,
|
|
"expected slice to be within body of inner-most loop");
|
|
}
|
|
|
|
// 2. Check that the loop is perfectly nested.
|
|
if (!isPerfectlyNestedForLoops(loops)) {
|
|
return rewriter.notifyMatchFailure(
|
|
candidateSliceOp, "expected passed loops to be perfectly nested.");
|
|
}
|
|
|
|
if (failed(checkAssumptionForFusingConsumer(candidateSliceOp)))
|
|
return failure();
|
|
Value sliceResult = candidateSliceOp.getResult();
|
|
|
|
// 3. Fetch the corresponding output.
|
|
OpOperand &yieldOpOperand = (*sliceResult.getUses().begin());
|
|
unsigned resultNumber = yieldOpOperand.getOperandNumber();
|
|
|
|
scf::ForOp topLevelForOp = cast<scf::ForOp>(loops.front().getOperation());
|
|
|
|
return getConsumerFromLoopUses(rewriter, topLevelForOp, resultNumber);
|
|
}
|
|
|
|
/// Fetch the first untiled consumer of a scf.forall's result which is yielded
|
|
/// by a tensor.parallel_insert_slice.
|
|
static FailureOr<OpOperand *>
|
|
getUntiledConsumerFromSlice(RewriterBase &rewriter,
|
|
tensor::ParallelInsertSliceOp candidateSliceOp,
|
|
MutableArrayRef<LoopLikeOpInterface> loops) {
|
|
assert(!loops.empty() && "unexpected loops to be empty");
|
|
// 1. Check that the surrounding loop is a single scf.forall loop.
|
|
if (loops.size() != 1) {
|
|
return rewriter.notifyMatchFailure(
|
|
candidateSliceOp, "expected single surrounding scf.forall");
|
|
}
|
|
auto forallOp = dyn_cast<scf::ForallOp>(loops.front().getOperation());
|
|
if (!forallOp) {
|
|
return rewriter.notifyMatchFailure(
|
|
candidateSliceOp, "expected single surrounding scf.forall");
|
|
}
|
|
|
|
// 2. Fetch the corresponding output
|
|
Value sliceDest = candidateSliceOp.getDest();
|
|
auto iterArg = dyn_cast<BlockArgument>(sliceDest);
|
|
if (!iterArg)
|
|
return failure();
|
|
if (iterArg.getOwner()->getParentOp() != forallOp)
|
|
return failure();
|
|
|
|
unsigned resultNumber =
|
|
forallOp.getTiedOpResult(forallOp.getTiedOpOperand(iterArg))
|
|
.getResultNumber();
|
|
|
|
return getConsumerFromLoopUses(rewriter, forallOp, resultNumber);
|
|
}
|
|
|
|
/// A utility to fetch an untiled consumer of
|
|
/// tensor.insert_slice/tensor.parallel_insert_slice.
|
|
static FailureOr<OpOperand *>
|
|
getUntiledConsumerFromSlice(RewriterBase &rewriter, Operation *sliceOp,
|
|
MutableArrayRef<LoopLikeOpInterface> loops) {
|
|
assert(!loops.empty() && "unexpected empty loops");
|
|
if (auto insertSlice = dyn_cast<tensor::InsertSliceOp>(sliceOp)) {
|
|
return getUntiledConsumerFromSlice(rewriter, insertSlice, loops);
|
|
} else if (auto parallelInsertSlice =
|
|
dyn_cast<tensor::ParallelInsertSliceOp>(sliceOp)) {
|
|
return getUntiledConsumerFromSlice(rewriter, parallelInsertSlice, loops);
|
|
} else {
|
|
return failure();
|
|
}
|
|
}
|
|
|
|
/// Implementation of fusing consumer of a single slice by computing the
|
|
/// slice of the consumer in-place for scf loop.
|
|
FailureOr<scf::SCFFuseConsumerOfSliceResult>
|
|
mlir::scf::tileAndFuseConsumerOfSlice(
|
|
RewriterBase &rewriter, Operation *candidateSliceOp,
|
|
MutableArrayRef<LoopLikeOpInterface> loops) {
|
|
// Return if `loops` is empty, return an error for now. Caller is expected
|
|
// to handle this case.
|
|
if (loops.empty()) {
|
|
return candidateSliceOp->emitOpError(
|
|
"cannot call tile and fuse consumer with an empty loop nest");
|
|
}
|
|
if (!isa<tensor::InsertSliceOp, tensor::ParallelInsertSliceOp>(
|
|
candidateSliceOp))
|
|
return failure();
|
|
|
|
// 1. Get the consumer of scf.for for the result yielded by
|
|
// tensor.insert_slice/parallel_insert_slice.
|
|
FailureOr<OpOperand *> maybeConsumerOpOperand =
|
|
getUntiledConsumerFromSlice(rewriter, candidateSliceOp, loops);
|
|
if (failed(maybeConsumerOpOperand)) {
|
|
return rewriter.notifyMatchFailure(candidateSliceOp,
|
|
"could not fetch consumer to fuse");
|
|
}
|
|
OpOperand *consumerOpOperand = *maybeConsumerOpOperand;
|
|
Operation *consumerOp = consumerOpOperand->getOwner();
|
|
unsigned operandNumber = consumerOpOperand->getOperandNumber();
|
|
unsigned resultNumber = 0;
|
|
if (auto producerResult = dyn_cast<OpResult>(consumerOpOperand->get())) {
|
|
resultNumber = producerResult.getResultNumber();
|
|
} else {
|
|
return rewriter.notifyMatchFailure(
|
|
consumerOp, "consumer op's operand doesn't seem to be an OpResult");
|
|
}
|
|
|
|
LoopLikeOpInterface outerMostLoop = loops.front();
|
|
LoopLikeOpInterface innerMostLoop = loops.back();
|
|
|
|
// Check assumption for loop with `reorderOperations` disabled.
|
|
if (failed(checkAssumptionForLoop(outerMostLoop, consumerOp, false))) {
|
|
return rewriter.notifyMatchFailure(
|
|
outerMostLoop, "the first user of loop should not dominate any define "
|
|
"of consumer operand(s)");
|
|
}
|
|
|
|
OpBuilder::InsertionGuard g(rewriter);
|
|
|
|
// 2. Check consumer is not using scf loop's output as init.
|
|
auto dstOp = dyn_cast<DestinationStyleOpInterface>(consumerOp);
|
|
if (!dstOp)
|
|
return rewriter.notifyMatchFailure(consumerOp,
|
|
"consumer op is not DPS operation");
|
|
SmallVector<Value> dpsInits =
|
|
llvm::map_to_vector(dstOp.getDpsInits(), [](Value v) { return v; });
|
|
if (llvm::is_contained(dpsInits, outerMostLoop->getResult(resultNumber))) {
|
|
return rewriter.notifyMatchFailure(
|
|
consumerOp,
|
|
"consumer op taking the result of scf.for as init is not supported");
|
|
}
|
|
SmallVector<Value> newInits = dpsInits;
|
|
|
|
Location loc = outerMostLoop->getLoc();
|
|
|
|
// 3. Move the whole loop structure right before firstUserOfLoop, the
|
|
// dominance should be already ensured by `checkAssumptionForLoop`.
|
|
FailureOr<Operation *> firstUserOfLoop = getFirstUserOfLoop(outerMostLoop);
|
|
if (failed(firstUserOfLoop)) {
|
|
return rewriter.notifyMatchFailure(
|
|
outerMostLoop, "could not find the first user of outer most loop");
|
|
}
|
|
rewriter.moveOpBefore(outerMostLoop, *firstUserOfLoop);
|
|
|
|
// 4. Set insertion point before terminator op of the loop and create a new
|
|
// tensor.insert_slice. In the scf.for case this is a clone of the
|
|
// candidateSliceOp whereas in the scf.forall case this is created from the
|
|
// operands of tensor.parallel_insert_slice.
|
|
tensor::InsertSliceOp clonedInsertSliceOp;
|
|
if (auto sliceOp =
|
|
dyn_cast<tensor::ParallelInsertSliceOp>(candidateSliceOp)) {
|
|
auto newForallOp = cast<scf::ForallOp>(innerMostLoop.getOperation());
|
|
rewriter.setInsertionPoint(newForallOp.getTerminator());
|
|
clonedInsertSliceOp = rewriter.create<tensor::InsertSliceOp>(
|
|
loc, sliceOp.getSource(), sliceOp.getDest(), sliceOp.getMixedOffsets(),
|
|
sliceOp.getMixedSizes(), sliceOp.getMixedStrides());
|
|
} else {
|
|
rewriter.setInsertionPoint(candidateSliceOp);
|
|
clonedInsertSliceOp =
|
|
cast<tensor::InsertSliceOp>(rewriter.clone(*candidateSliceOp));
|
|
}
|
|
|
|
// 5.a. Clone consumer op.
|
|
auto clonedConsumerOp = cast<TilingInterface>(rewriter.clone(*consumerOp));
|
|
|
|
// 5.b. Replace all uses of the loop result with the result of the cloned
|
|
// tensor.insert_slice.
|
|
OpOperand &operandToReplace = clonedConsumerOp->getOpOperand(operandNumber);
|
|
rewriter.modifyOpInPlace(clonedConsumerOp, [&]() {
|
|
operandToReplace.set(clonedInsertSliceOp.getResult());
|
|
});
|
|
|
|
// 6. Perform tiling of the cloned consumer and replace the operand at
|
|
// `operandNumber` with the source of the cloned tensor.insert_slice op.
|
|
auto ossSliceOp =
|
|
cast<OffsetSizeAndStrideOpInterface>(clonedInsertSliceOp.getOperation());
|
|
FailureOr<TilingResult> tileAndFuseResult =
|
|
tensor::replaceInsertSliceWithTiledConsumer(
|
|
rewriter, ossSliceOp, clonedConsumerOp->getOpOperand(operandNumber));
|
|
if (failed(tileAndFuseResult)) {
|
|
return failure();
|
|
}
|
|
auto tiledConsumerOp = cast<TilingInterface>(tileAndFuseResult->tiledOps[0]);
|
|
rewriter.replaceAllUsesWith(tiledConsumerOp->getOperand(operandNumber),
|
|
clonedInsertSliceOp.getSource());
|
|
|
|
// 7. Reconstruct [nested] loop with new inits.
|
|
YieldTiledValuesFn newYieldValuesFn =
|
|
[&](RewriterBase &innerRewriter, Location loc, ValueRange /*ivs*/,
|
|
ValueRange newRegionIterArgs, SmallVector<Value> &tiledResult,
|
|
SmallVector<SmallVector<OpFoldResult>> &tiledOffset,
|
|
SmallVector<SmallVector<OpFoldResult>> &tiledSizes) -> LogicalResult {
|
|
OpBuilder::InsertionGuard g(innerRewriter);
|
|
// 8. Set inner insertPoint right before tiled consumer op.
|
|
innerRewriter.setInsertionPoint(tiledConsumerOp);
|
|
|
|
SmallVector<OpFoldResult> offsets = ossSliceOp.getMixedOffsets();
|
|
SmallVector<OpFoldResult> sizes = ossSliceOp.getMixedSizes();
|
|
SmallVector<OpFoldResult> strides = ossSliceOp.getMixedStrides();
|
|
|
|
// 9. Check all insert stride is 1.
|
|
if (llvm::any_of(strides, [](OpFoldResult stride) {
|
|
return !isConstantIntValue(stride, 1);
|
|
})) {
|
|
return rewriter.notifyMatchFailure(
|
|
candidateSliceOp, "containingOp's result yield with stride");
|
|
}
|
|
|
|
// 10. Try to get iter domain position from input position. Use
|
|
// clonedConsumerOp instead of tiledConsumerOp, because the iteration
|
|
// domain may require index computation based on the result size. The
|
|
// sizes and offsets should be the same either way, but using
|
|
// tiledConsumerOp could lead to some chained unnecessary extra index
|
|
// computation.
|
|
SmallVector<OpFoldResult> iterDomainOffsets, iterDomainSizes;
|
|
if (failed(clonedConsumerOp.getIterationDomainTileFromOperandTile(
|
|
rewriter, operandNumber, offsets, sizes, iterDomainOffsets,
|
|
iterDomainSizes))) {
|
|
return rewriter.notifyMatchFailure(
|
|
clonedConsumerOp,
|
|
"can't get iter domain position from input position");
|
|
}
|
|
|
|
// 11. Try to fetch the offset and size for all results of the cloned
|
|
// consumer. This would then be used to form the corresponding
|
|
// tensor.insert_slice/parallel_insert_slice later.
|
|
unsigned totalNumResultsOfConsumer = tiledConsumerOp->getNumResults();
|
|
SmallVector<SmallVector<OpFoldResult>> resultOffsets(
|
|
totalNumResultsOfConsumer);
|
|
SmallVector<SmallVector<OpFoldResult>> resultSizes(
|
|
totalNumResultsOfConsumer);
|
|
for (auto [idx, v] : llvm::enumerate(tiledConsumerOp->getResults())) {
|
|
if (failed(tiledConsumerOp.getResultTilePosition(
|
|
rewriter, idx, iterDomainOffsets, iterDomainSizes,
|
|
resultOffsets[idx], resultSizes[idx]))) {
|
|
return rewriter.notifyMatchFailure(
|
|
tiledConsumerOp,
|
|
"can't get result domain position from iter domain position");
|
|
}
|
|
}
|
|
|
|
// 12. Create `extract_slice` for `iter_args` for DPS operation if
|
|
// necessary.
|
|
if (auto tiledDestStyleOp = dyn_cast<DestinationStyleOpInterface>(
|
|
tiledConsumerOp.getOperation())) {
|
|
rewriter.setInsertionPoint(tiledDestStyleOp);
|
|
for (const auto &&[index, newRegionArg] :
|
|
llvm::enumerate(newRegionIterArgs)) {
|
|
auto destSlice = rewriter.create<tensor::ExtractSliceOp>(
|
|
loc, newRegionArg, resultOffsets[index], resultSizes[index],
|
|
SmallVector<OpFoldResult>(resultOffsets[index].size(),
|
|
rewriter.getIndexAttr(1)));
|
|
// Make a copy of index to avoid a capturing structured binding, which
|
|
// is a C++20 extension.
|
|
auto dstNumber = index;
|
|
rewriter.modifyOpInPlace(tiledDestStyleOp, [&]() {
|
|
tiledDestStyleOp.getDpsInitsMutable()[dstNumber].set(destSlice);
|
|
});
|
|
}
|
|
}
|
|
|
|
// 13. Prepare tiled offset and sizes for later `insert_slice` creation by
|
|
// caller.
|
|
Block *block = rewriter.getInsertionPoint()->getBlock();
|
|
rewriter.setInsertionPoint(block->getTerminator());
|
|
for (const auto &&[index, result] :
|
|
llvm::enumerate(tiledConsumerOp->getResults())) {
|
|
tiledResult.push_back(result);
|
|
tiledOffset.emplace_back(resultOffsets[index]);
|
|
tiledSizes.emplace_back(resultSizes[index]);
|
|
}
|
|
return success();
|
|
};
|
|
// 14. Add new inits to [nested] loops.
|
|
if (failed(addInitOperandsToLoopNest(rewriter, loops, newInits,
|
|
newYieldValuesFn))) {
|
|
return rewriter.notifyMatchFailure(tiledConsumerOp,
|
|
"unable to add new inits to nest loop");
|
|
}
|
|
|
|
// 15. Replace the result of scf loop and consumer op with new loop's
|
|
// results.
|
|
|
|
for (auto &&[oldResult, newResult] :
|
|
llvm::zip(consumerOp->getResults(),
|
|
loops.front()->getResults().take_back(newInits.size()))) {
|
|
rewriter.replaceAllUsesWith(oldResult, newResult);
|
|
}
|
|
|
|
// 16. Need to erase the old scf loop and the cloned consumer op.
|
|
rewriter.eraseOp(clonedConsumerOp);
|
|
|
|
return scf::SCFFuseConsumerOfSliceResult{
|
|
consumerOpOperand,
|
|
&(tileAndFuseResult->tiledOps[0]->getOpOperand(operandNumber)),
|
|
tileAndFuseResult->tiledOps};
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// lowerToLoopsUsingSCFForOp implementation.
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
FailureOr<SmallVector<scf::ForOp>>
|
|
mlir::scf::lowerToLoopsUsingSCFForOp(RewriterBase &rewriter,
|
|
TilingInterface op) {
|
|
// TODO: Handle cases where the op has results if needed.
|
|
if (op->getNumResults() > 0) {
|
|
return rewriter.notifyMatchFailure(
|
|
op, "unable to lower to loops operations with return values");
|
|
}
|
|
|
|
SmallVector<Range> domain = op.getIterationDomain(rewriter);
|
|
SmallVector<Value> ivs;
|
|
SmallVector<scf::ForOp> loops;
|
|
Location loc = op.getLoc();
|
|
for (auto loopRange : domain) {
|
|
Value offsetVal =
|
|
getValueOrCreateConstantIndexOp(rewriter, loc, loopRange.offset);
|
|
Value sizeVal =
|
|
getValueOrCreateConstantIndexOp(rewriter, loc, loopRange.size);
|
|
Value strideVal =
|
|
getValueOrCreateConstantIndexOp(rewriter, loc, loopRange.stride);
|
|
auto loop = rewriter.create<scf::ForOp>(op.getLoc(), offsetVal, sizeVal,
|
|
strideVal, ValueRange{});
|
|
loops.push_back(loop);
|
|
ivs.push_back(loop.getInductionVar());
|
|
rewriter.setInsertionPoint(loop.getBody()->getTerminator());
|
|
}
|
|
if (failed(op.generateScalarImplementation(rewriter, op.getLoc(), ivs))) {
|
|
return failure();
|
|
}
|
|
return loops;
|
|
}
|