58ceae9561
FuncOp has been moved to the `func` namespace for a little over a month, the using directive can be dropped now.
713 lines
30 KiB
C++
713 lines
30 KiB
C++
//===- TestLinalgTransforms.cpp - Test Linalg transformation patterns -----===//
|
|
//
|
|
// 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 logic for testing Linalg transformations.
|
|
//
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
#include "mlir/Dialect/Affine/IR/AffineOps.h"
|
|
#include "mlir/Dialect/Arithmetic/IR/Arithmetic.h"
|
|
#include "mlir/Dialect/Func/IR/FuncOps.h"
|
|
#include "mlir/Dialect/GPU/GPUDialect.h"
|
|
#include "mlir/Dialect/Linalg/IR/Linalg.h"
|
|
#include "mlir/Dialect/Linalg/Passes.h"
|
|
#include "mlir/Dialect/Linalg/Transforms/HoistPadding.h"
|
|
#include "mlir/Dialect/Linalg/Transforms/Hoisting.h"
|
|
#include "mlir/Dialect/Linalg/Transforms/Transforms.h"
|
|
#include "mlir/Dialect/Linalg/Utils/Utils.h"
|
|
#include "mlir/Dialect/Vector/IR/VectorOps.h"
|
|
#include "mlir/Pass/PassManager.h"
|
|
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
|
|
|
|
#include "llvm/ADT/SetVector.h"
|
|
#include "llvm/ADT/SmallVector.h"
|
|
|
|
using namespace mlir;
|
|
using namespace mlir::linalg;
|
|
|
|
namespace {
|
|
struct TestLinalgTransforms
|
|
: public PassWrapper<TestLinalgTransforms, OperationPass<func::FuncOp>> {
|
|
MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(TestLinalgTransforms)
|
|
|
|
TestLinalgTransforms() = default;
|
|
TestLinalgTransforms(const TestLinalgTransforms &pass) : PassWrapper(pass) {}
|
|
|
|
void getDependentDialects(DialectRegistry ®istry) const override {
|
|
// clang-format off
|
|
registry.insert<AffineDialect,
|
|
memref::MemRefDialect,
|
|
scf::SCFDialect,
|
|
linalg::LinalgDialect,
|
|
vector::VectorDialect,
|
|
gpu::GPUDialect>();
|
|
// clang-format on
|
|
}
|
|
StringRef getArgument() const final {
|
|
return "test-linalg-transform-patterns";
|
|
}
|
|
StringRef getDescription() const final {
|
|
return "Test Linalg transformation patterns by applying them greedily.";
|
|
}
|
|
|
|
void runOnOperation() override;
|
|
|
|
Option<bool> testPatterns{*this, "test-patterns",
|
|
llvm::cl::desc("Test a mixed set of patterns"),
|
|
llvm::cl::init(false)};
|
|
Option<bool> testMatmulToVectorPatterns1dTiling{
|
|
*this, "test-matmul-to-vector-patterns-tile-1d",
|
|
llvm::cl::desc(
|
|
"Test a fused pass that applies patterns from matmul to vectors via "
|
|
"1-d tiling"),
|
|
llvm::cl::init(false)};
|
|
Option<bool> testMatmulToVectorPatterns2dTiling{
|
|
*this, "test-matmul-to-vector-patterns-tile-2d",
|
|
llvm::cl::desc(
|
|
"Test a fused pass that applies patterns from matmul to vectors via "
|
|
"2-d tiling"),
|
|
llvm::cl::init(false)};
|
|
Option<bool> testPromotionOptions{*this, "test-linalg-promotion-options",
|
|
llvm::cl::desc("Test promotion options"),
|
|
llvm::cl::init(false)};
|
|
Option<bool> testTileAndDistributionOptions{
|
|
*this, "test-tile-and-distribute-options",
|
|
llvm::cl::desc("Test tile and distribute options"),
|
|
llvm::cl::init(false)};
|
|
Option<bool> testTileFuseAndDistributionOptions{
|
|
*this, "test-tile-fuse-and-distribute-options",
|
|
llvm::cl::desc("Test tile, fuse and distribute options"),
|
|
llvm::cl::init(false)};
|
|
Option<bool> testVectorTransferForwardingPatterns{
|
|
*this, "test-vector-transfer-forwarding-patterns",
|
|
llvm::cl::desc(
|
|
"Test a fused pass that forwards memref.copy to vector.transfer"),
|
|
llvm::cl::init(false)};
|
|
Option<bool> testGenericToVectorPattern{
|
|
*this, "test-linalg-to-vector-patterns",
|
|
llvm::cl::desc("Test a set of patterns that rewrite a linalg contraction "
|
|
"in vector.contract form"),
|
|
llvm::cl::init(false)};
|
|
Option<bool> testTilePattern{*this, "test-tile-pattern",
|
|
llvm::cl::desc("Test tile pattern"),
|
|
llvm::cl::init(false)};
|
|
Option<bool> testTileScalarizeDynamicDims{
|
|
*this, "test-tile-scalarize-dynamic-dims",
|
|
llvm::cl::desc("Test tiling of dynamic dims by 1"),
|
|
llvm::cl::init(false)};
|
|
Option<bool> testTransformPadTensor{
|
|
*this, "test-transform-pad-tensor",
|
|
llvm::cl::desc("Test transform pad tensor by copying with generic ops"),
|
|
llvm::cl::init(false)};
|
|
Option<bool> testGeneralizePadTensor{
|
|
*this, "test-generalize-pad-tensor",
|
|
llvm::cl::desc("Test transform pad tensor by copying with generic ops"),
|
|
llvm::cl::init(false)};
|
|
Option<bool> testSwapSubTensorPadTensor{
|
|
*this, "test-swap-subtensor-padtensor",
|
|
llvm::cl::desc("Test rewrite of subtensor(pad_tensor) into "
|
|
"pad_tensor(subtensor)"),
|
|
llvm::cl::init(false)};
|
|
Option<bool> testSplitReduction{
|
|
*this, "test-split-reduction",
|
|
llvm::cl::desc("Test split reduction transformation"),
|
|
llvm::cl::init(false)};
|
|
ListOption<int64_t> peeledLoops{
|
|
*this, "peeled-loops",
|
|
llvm::cl::desc("Loops to be peeled when test-tile-pattern"),
|
|
llvm::cl::ZeroOrMore};
|
|
ListOption<int64_t> tileSizes{
|
|
*this, "tile-sizes",
|
|
llvm::cl::desc("Linalg tile sizes for test-tile-pattern"),
|
|
llvm::cl::ZeroOrMore};
|
|
Option<bool> skipPartial{
|
|
*this, "skip-partial",
|
|
llvm::cl::desc("Skip loops inside partial iterations during peeling"),
|
|
llvm::cl::init(false)};
|
|
Option<std::string> loopType{
|
|
*this, "loop-type",
|
|
llvm::cl::desc("Specify the type of loops to generate: for, parallel or "
|
|
"tiled_loop"),
|
|
llvm::cl::init("for")};
|
|
Option<bool> testBubbleUpExtractSliceOpPattern{
|
|
*this, "test-bubble-up-extract-slice-op-pattern",
|
|
llvm::cl::desc("Test rewrite of linalgOp + extract_slice into "
|
|
"extract_slice + linalgOp"),
|
|
llvm::cl::init(false)};
|
|
};
|
|
} // namespace
|
|
|
|
static void applyPatterns(func::FuncOp funcOp) {
|
|
MLIRContext *ctx = funcOp.getContext();
|
|
RewritePatternSet patterns(ctx);
|
|
|
|
//===--------------------------------------------------------------------===//
|
|
// Linalg tiling patterns.
|
|
//===--------------------------------------------------------------------===//
|
|
patterns.add<LinalgTilingPattern>(
|
|
MatmulOp::getOperationName(), ctx,
|
|
LinalgTilingOptions().setTileSizes({2000, 3000, 4000}),
|
|
LinalgTransformationFilter(StringAttr::get(ctx, "MEM"),
|
|
StringAttr::get(ctx, "L3")));
|
|
patterns.add<LinalgTilingPattern>(
|
|
MatmulOp::getOperationName(), ctx,
|
|
LinalgTilingOptions().setTileSizes({200, 300, 400}),
|
|
LinalgTransformationFilter(StringAttr::get(ctx, "L3"),
|
|
StringAttr::get(ctx, "L2")));
|
|
patterns.add<LinalgTilingPattern>(
|
|
MatmulOp::getOperationName(), ctx,
|
|
LinalgTilingOptions().setTileSizes({20, 30, 40}),
|
|
LinalgTransformationFilter(StringAttr::get(ctx, "L2"),
|
|
StringAttr::get(ctx, "L1")));
|
|
patterns.add<LinalgTilingPattern>(
|
|
MatmulOp::getOperationName(), ctx,
|
|
LinalgTilingOptions().setTileSizes({2, 3, 4}),
|
|
LinalgTransformationFilter(StringAttr::get(ctx, "L1"),
|
|
StringAttr::get(ctx, "REG")));
|
|
|
|
patterns.add<LinalgTilingPattern>(
|
|
MatvecOp::getOperationName(), ctx,
|
|
LinalgTilingOptions().setTileSizes({5, 6}).setLoopType(
|
|
LinalgTilingLoopType::ParallelLoops),
|
|
LinalgTransformationFilter(ArrayRef<StringAttr>{},
|
|
StringAttr::get(ctx, "L1")));
|
|
|
|
patterns.add<LinalgTilingPattern>(
|
|
DotOp::getOperationName(), ctx, LinalgTilingOptions().setTileSizes(8000),
|
|
LinalgTransformationFilter(
|
|
ArrayRef<StringAttr>{StringAttr::get(ctx, "MEM"),
|
|
StringAttr::get(ctx, "L3"),
|
|
StringAttr::get(ctx, "L2")},
|
|
StringAttr::get(ctx, "REG")));
|
|
|
|
//===--------------------------------------------------------------------===//
|
|
// Linalg tiling and permutation patterns.
|
|
//===--------------------------------------------------------------------===//
|
|
patterns.add<LinalgTilingPattern>(
|
|
MatmulOp::getOperationName(), ctx,
|
|
LinalgTilingOptions()
|
|
.setTileSizes({2000, 3000, 4000})
|
|
.setInterchange({1, 2, 0}),
|
|
LinalgTransformationFilter(StringAttr::get(ctx, "__with_perm__"),
|
|
StringAttr::get(ctx, "L2__with_perm__")));
|
|
patterns.add<LinalgTilingPattern>(
|
|
MatmulOp::getOperationName(), ctx,
|
|
LinalgTilingOptions()
|
|
.setTileSizes({200, 300, 400})
|
|
.setInterchange({1, 0, 2}),
|
|
LinalgTransformationFilter(StringAttr::get(ctx, "L2__with_perm__"),
|
|
StringAttr::get(ctx, "L1__with_perm__")));
|
|
patterns.add<LinalgTilingPattern>(
|
|
MatmulOp::getOperationName(), ctx,
|
|
LinalgTilingOptions().setTileSizes({20, 30, 40}),
|
|
LinalgTransformationFilter(StringAttr::get(ctx, "L1__with_perm__"),
|
|
StringAttr::get(ctx, "REG__with_perm__")));
|
|
|
|
patterns.add<LinalgTilingPattern>(
|
|
MatvecOp::getOperationName(), ctx,
|
|
LinalgTilingOptions().setTileSizes({5, 6}).setInterchange({1, 0}),
|
|
LinalgTransformationFilter(StringAttr::get(ctx, "__with_perm__"),
|
|
StringAttr::get(ctx, "L1__with_perm__")));
|
|
|
|
patterns.add<LinalgTilingPattern>(
|
|
MatmulOp::getOperationName(), ctx,
|
|
LinalgTilingOptions()
|
|
.setTileSizes({16, 8, 4})
|
|
.setInterchange({1, 2, 0})
|
|
.setLoopType(LinalgTilingLoopType::ParallelLoops),
|
|
LinalgTransformationFilter(
|
|
StringAttr::get(ctx, "par__with_perm__"),
|
|
StringAttr::get(ctx, "after_par__with_perm__")));
|
|
|
|
//===--------------------------------------------------------------------===//
|
|
// Linalg to loops patterns.
|
|
//===--------------------------------------------------------------------===//
|
|
patterns.add<LinalgLoweringPattern<DotOp>>(
|
|
ctx,
|
|
/*loweringType=*/LinalgLoweringType::Loops,
|
|
LinalgTransformationFilter(StringAttr::get(ctx, "REG")));
|
|
|
|
//===--------------------------------------------------------------------===//
|
|
// Linalg distribution patterns.
|
|
//===--------------------------------------------------------------------===//
|
|
LinalgLoopDistributionOptions distributionOptions;
|
|
|
|
//===--------------------------------------------------------------------===//
|
|
// Linalg to vector contraction patterns.
|
|
//===--------------------------------------------------------------------===//
|
|
patterns.add<LinalgVectorizationPattern>(
|
|
ctx, LinalgTransformationFilter(StringAttr::get(ctx, "VECTORIZE"))
|
|
.addOpFilter<MatmulOp, FillOp, GenericOp>());
|
|
patterns.add<CopyVectorizationPattern>(ctx);
|
|
|
|
//===--------------------------------------------------------------------===//
|
|
// Linalg generic interchange pattern.
|
|
//===--------------------------------------------------------------------===//
|
|
patterns.add<GenericOpInterchangePattern>(
|
|
ctx,
|
|
/*interchangeVector=*/ArrayRef<unsigned>{1, 2, 0},
|
|
LinalgTransformationFilter(ArrayRef<StringAttr>{},
|
|
StringAttr::get(ctx, "PERMUTED")));
|
|
|
|
//===--------------------------------------------------------------------===//
|
|
// Linalg subview operands promotion.
|
|
//===--------------------------------------------------------------------===//
|
|
patterns.add<LinalgPromotionPattern<MatmulOp>>(
|
|
ctx, LinalgPromotionOptions().setUseFullTileBuffersByDefault(true),
|
|
LinalgTransformationFilter(StringAttr::get(ctx, "_promote_views_"),
|
|
StringAttr::get(ctx, "_views_promoted_")));
|
|
patterns.add<LinalgPromotionPattern<MatmulOp>>(
|
|
ctx,
|
|
LinalgPromotionOptions()
|
|
.setOperandsToPromote({0})
|
|
.setUseFullTileBuffersByDefault(true),
|
|
LinalgTransformationFilter(
|
|
StringAttr::get(ctx, "_promote_first_view_"),
|
|
StringAttr::get(ctx, "_first_view_promoted_")));
|
|
patterns.add<LinalgPromotionPattern<FillOp>>(
|
|
ctx,
|
|
LinalgPromotionOptions()
|
|
.setOperandsToPromote({1})
|
|
.setUseFullTileBuffers({false, true})
|
|
.setAlignment(32),
|
|
LinalgTransformationFilter(
|
|
StringAttr::get(ctx, "_promote_views_aligned_"),
|
|
StringAttr::get(ctx, "_views_aligned_promoted_")));
|
|
|
|
(void)applyPatternsAndFoldGreedily(funcOp, std::move(patterns));
|
|
|
|
// Drop the marker.
|
|
funcOp.walk([](LinalgOp op) {
|
|
op->removeAttr(LinalgTransforms::kLinalgTransformMarker);
|
|
});
|
|
}
|
|
|
|
static void fillL1TilingAndMatmulToVectorPatterns(
|
|
func::FuncOp funcOp, StringRef startMarker,
|
|
SmallVectorImpl<RewritePatternSet> &patternsVector) {
|
|
MLIRContext *ctx = funcOp.getContext();
|
|
patternsVector.emplace_back(
|
|
ctx, std::make_unique<LinalgTilingPattern>(
|
|
MatmulOp::getOperationName(), ctx,
|
|
LinalgTilingOptions()
|
|
.setTileSizes({8, 12, 16})
|
|
.setInterchange({1, 0, 2}),
|
|
LinalgTransformationFilter(StringAttr::get(ctx, startMarker),
|
|
StringAttr::get(ctx, "L1"))));
|
|
|
|
patternsVector.emplace_back(
|
|
ctx,
|
|
std::make_unique<LinalgPromotionPattern<MatmulOp>>(
|
|
ctx, LinalgPromotionOptions().setUseFullTileBuffersByDefault(true),
|
|
LinalgTransformationFilter(StringAttr::get(ctx, "L1"),
|
|
StringAttr::get(ctx, "VEC"))));
|
|
|
|
patternsVector.emplace_back(
|
|
ctx, std::make_unique<LinalgVectorizationPattern>(
|
|
MatmulOp::getOperationName(), ctx, LinalgVectorizationOptions(),
|
|
LinalgTransformationFilter(StringAttr::get(ctx, "VEC"))));
|
|
patternsVector.back().add<LinalgVectorizationPattern>(
|
|
ctx, LinalgTransformationFilter().addOpFilter<FillOp>());
|
|
patternsVector.back().add<CopyVectorizationPattern>(ctx);
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// Test promotion callbacks
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
// Allocation call back
|
|
static Optional<Value> allocCallBackFn(OpBuilder &b, memref::SubViewOp subView,
|
|
ArrayRef<Value> boundingSubViewSize,
|
|
DataLayout &layout) {
|
|
SmallVector<int64_t, 4> shape(boundingSubViewSize.size(), -1);
|
|
return b
|
|
.create<memref::AllocOp>(
|
|
subView.getLoc(),
|
|
MemRefType::get(shape, subView.getType().getElementType(),
|
|
/*affineMapComposition =*/{}, 3),
|
|
boundingSubViewSize)
|
|
.getResult();
|
|
}
|
|
|
|
// Deallocation callback
|
|
static LogicalResult deallocCallBackFn(OpBuilder &b, Value buffer) {
|
|
b.create<memref::DeallocOp>(buffer.getLoc(), buffer);
|
|
return success();
|
|
}
|
|
|
|
// Copy in call back
|
|
static LogicalResult copyCallBackFn(OpBuilder &b, Value src, Value dst,
|
|
bool isOutput) {
|
|
auto floatType = src.getType().cast<MemRefType>().getElementType();
|
|
if (!floatType.isa<FloatType>())
|
|
return failure();
|
|
if (!isOutput) {
|
|
Value cst = b.create<arith::ConstantOp>(src.getLoc(),
|
|
FloatAttr::get(floatType, 42.0));
|
|
b.create<FillOp>(src.getLoc(), cst, dst);
|
|
}
|
|
b.create<memref::CopyOp>(src.getLoc(), src, dst);
|
|
return success();
|
|
}
|
|
|
|
static void fillPromotionCallBackPatterns(MLIRContext *ctx,
|
|
RewritePatternSet &patterns) {
|
|
patterns.add<LinalgTilingPattern>(
|
|
MatmulOp::getOperationName(), ctx,
|
|
LinalgTilingOptions().setTileSizes({16, 16, 16}),
|
|
LinalgTransformationFilter(StringAttr::get(ctx, "START"),
|
|
StringAttr::get(ctx, "PROMOTE")));
|
|
patterns.add<LinalgPromotionPattern<MatmulOp>>(
|
|
ctx,
|
|
LinalgPromotionOptions()
|
|
.setOperandsToPromote({0, 2})
|
|
.setUseFullTileBuffers({false, false})
|
|
.setAllocationDeallocationFns(allocCallBackFn, deallocCallBackFn)
|
|
.setCopyInOutFns(
|
|
[](OpBuilder &b, Value src, Value dst) -> LogicalResult {
|
|
return copyCallBackFn(b, src, dst, false);
|
|
},
|
|
[](OpBuilder &b, Value src, Value dst) -> LogicalResult {
|
|
return copyCallBackFn(b, src, dst, true);
|
|
}),
|
|
LinalgTransformationFilter(StringAttr::get(ctx, "PROMOTE")));
|
|
}
|
|
|
|
template <typename IdOp, typename NProcsOp>
|
|
static SmallVector<ProcInfo, 2>
|
|
getGpuProcIds(OpBuilder &b, Location loc, ArrayRef<Range> parallelLoopRanges) {
|
|
size_t count = std::min<size_t>(3, parallelLoopRanges.size());
|
|
SmallVector<ProcInfo, 2> procInfo(count);
|
|
Type indexType = b.getIndexType();
|
|
for (unsigned i = 0; i < count; ++i) {
|
|
gpu::Dimension dim = *gpu::symbolizeDimension(i);
|
|
procInfo[count - 1 - i] = {b.create<IdOp>(loc, indexType, dim),
|
|
b.create<NProcsOp>(loc, indexType, dim)};
|
|
}
|
|
return procInfo;
|
|
}
|
|
|
|
static void fillTileAndDistributePatterns(MLIRContext *context,
|
|
RewritePatternSet &patterns) {
|
|
{
|
|
LinalgLoopDistributionOptions cyclicNprocsEqNiters;
|
|
cyclicNprocsEqNiters.distributionMethod.resize(
|
|
2, DistributionMethod::CyclicNumProcsEqNumIters);
|
|
cyclicNprocsEqNiters.procInfo =
|
|
getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>;
|
|
patterns.add<LinalgTilingPattern>(
|
|
MatmulOp::getOperationName(), context,
|
|
LinalgTilingOptions()
|
|
.setTileSizes({8, 8, 4})
|
|
.setLoopType(LinalgTilingLoopType::ParallelLoops)
|
|
.setDistributionOptions(cyclicNprocsEqNiters),
|
|
LinalgTransformationFilter(
|
|
StringAttr::get(context, "distribute1"),
|
|
StringAttr::get(context, "after_distribute1")));
|
|
}
|
|
|
|
{
|
|
LinalgLoopDistributionOptions cyclicNprocsGeNiters;
|
|
cyclicNprocsGeNiters.distributionMethod.resize(
|
|
2, DistributionMethod::CyclicNumProcsGeNumIters);
|
|
cyclicNprocsGeNiters.procInfo =
|
|
getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>;
|
|
patterns.add<LinalgTilingPattern>(
|
|
MatmulOp::getOperationName(), context,
|
|
LinalgTilingOptions()
|
|
.setTileSizes({8, 8, 4})
|
|
.setLoopType(LinalgTilingLoopType::ParallelLoops)
|
|
.setDistributionOptions(cyclicNprocsGeNiters),
|
|
LinalgTransformationFilter(
|
|
StringAttr::get(context, "distribute2"),
|
|
StringAttr::get(context, "after_distribute2")));
|
|
}
|
|
|
|
{
|
|
LinalgLoopDistributionOptions cyclicNprocsDefault;
|
|
cyclicNprocsDefault.distributionMethod.resize(2,
|
|
DistributionMethod::Cyclic);
|
|
cyclicNprocsDefault.procInfo =
|
|
getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>;
|
|
patterns.add<LinalgTilingPattern>(
|
|
MatmulOp::getOperationName(), context,
|
|
LinalgTilingOptions()
|
|
.setTileSizes({8, 8, 4})
|
|
.setLoopType(LinalgTilingLoopType::ParallelLoops)
|
|
.setDistributionOptions(cyclicNprocsDefault),
|
|
LinalgTransformationFilter(
|
|
StringAttr::get(context, "distribute3"),
|
|
StringAttr::get(context, "after_distribute3")));
|
|
}
|
|
|
|
{
|
|
LinalgLoopDistributionOptions cyclicNprocsMixed1;
|
|
cyclicNprocsMixed1.distributionMethod = {
|
|
DistributionMethod::CyclicNumProcsEqNumIters,
|
|
DistributionMethod::CyclicNumProcsGeNumIters};
|
|
cyclicNprocsMixed1.procInfo = getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>;
|
|
patterns.add<LinalgTilingPattern>(
|
|
MatmulOp::getOperationName(), context,
|
|
LinalgTilingOptions()
|
|
.setTileSizes({8, 8, 4})
|
|
.setLoopType(LinalgTilingLoopType::ParallelLoops)
|
|
.setDistributionOptions(cyclicNprocsMixed1),
|
|
LinalgTransformationFilter(
|
|
StringAttr::get(context, "distribute4"),
|
|
StringAttr::get(context, "after_distribute4")));
|
|
}
|
|
|
|
{
|
|
LinalgLoopDistributionOptions cyclicNprocsMixed2;
|
|
cyclicNprocsMixed2.distributionMethod = {
|
|
DistributionMethod::CyclicNumProcsGeNumIters,
|
|
DistributionMethod::Cyclic};
|
|
cyclicNprocsMixed2.procInfo = getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>;
|
|
patterns.add<LinalgTilingPattern>(
|
|
MatmulOp::getOperationName(), context,
|
|
LinalgTilingOptions()
|
|
.setTileSizes({8, 8, 4})
|
|
.setLoopType(LinalgTilingLoopType::ParallelLoops)
|
|
.setDistributionOptions(cyclicNprocsMixed2),
|
|
LinalgTransformationFilter(
|
|
StringAttr::get(context, "distribute5"),
|
|
StringAttr::get(context, "after_distribute5")));
|
|
}
|
|
|
|
{
|
|
LinalgLoopDistributionOptions cyclicNprocsMixed3;
|
|
cyclicNprocsMixed3.distributionMethod = {
|
|
DistributionMethod::Cyclic,
|
|
DistributionMethod::CyclicNumProcsEqNumIters};
|
|
cyclicNprocsMixed3.procInfo = getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>;
|
|
|
|
patterns.add<LinalgTilingPattern>(
|
|
MatmulOp::getOperationName(), context,
|
|
LinalgTilingOptions()
|
|
.setTileSizes({8, 8, 4})
|
|
.setLoopType(LinalgTilingLoopType::ParallelLoops)
|
|
.setDistributionOptions(cyclicNprocsMixed3),
|
|
LinalgTransformationFilter(
|
|
StringAttr::get(context, "distribute6"),
|
|
StringAttr::get(context, "after_distribute6")));
|
|
}
|
|
|
|
{
|
|
LinalgLoopDistributionOptions cyclicNprocsEqNiters;
|
|
cyclicNprocsEqNiters.distributionMethod.resize(2,
|
|
DistributionMethod::Cyclic);
|
|
cyclicNprocsEqNiters.procInfo =
|
|
getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>;
|
|
patterns.add<LinalgTilingPattern>(
|
|
MatmulOp::getOperationName(), context,
|
|
LinalgTilingOptions()
|
|
.setTileSizes({8, 8, 4})
|
|
.setLoopType(LinalgTilingLoopType::Loops)
|
|
.setDistributionOptions(cyclicNprocsEqNiters),
|
|
LinalgTransformationFilter(
|
|
StringAttr::get(context, "tensors_distribute1"),
|
|
StringAttr::get(context, "tensors_after_distribute1")));
|
|
}
|
|
}
|
|
|
|
static void fillTileFuseAndDistributePatterns(MLIRContext *context,
|
|
RewritePatternSet &patterns) {
|
|
LinalgLoopDistributionOptions cyclicNprocsEqNiters;
|
|
cyclicNprocsEqNiters.distributionMethod.resize(2, DistributionMethod::Cyclic);
|
|
cyclicNprocsEqNiters.procInfo = getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>;
|
|
patterns.add<LinalgTileAndFuseTensorOpsPattern>(
|
|
MatmulOp::getOperationName(), context,
|
|
LinalgTilingAndFusionOptions()
|
|
.setTileSizes({8, 8, 4})
|
|
.setDistributionOptions(cyclicNprocsEqNiters),
|
|
LinalgTransformationFilter(
|
|
StringAttr::get(context, "tensors_fuse_distribute1"),
|
|
StringAttr::get(context, "tensors_after_fuse_distribute1")));
|
|
}
|
|
|
|
static void
|
|
applyMatmulToVectorPatterns(func::FuncOp funcOp,
|
|
bool testMatmulToVectorPatterns1dTiling,
|
|
bool testMatmulToVectorPatterns2dTiling) {
|
|
MLIRContext *ctx = funcOp.getContext();
|
|
SmallVector<RewritePatternSet, 4> stage1Patterns;
|
|
if (testMatmulToVectorPatterns1dTiling) {
|
|
fillL1TilingAndMatmulToVectorPatterns(funcOp, "START", stage1Patterns);
|
|
} else if (testMatmulToVectorPatterns2dTiling) {
|
|
stage1Patterns.emplace_back(
|
|
ctx, std::make_unique<LinalgTilingPattern>(
|
|
MatmulOp::getOperationName(), ctx,
|
|
LinalgTilingOptions()
|
|
.setTileSizes({768, 264, 768})
|
|
.setInterchange({1, 2, 0}),
|
|
LinalgTransformationFilter(StringAttr::get(ctx, "START"),
|
|
StringAttr::get(ctx, "L2"))));
|
|
fillL1TilingAndMatmulToVectorPatterns(funcOp, "L2", stage1Patterns);
|
|
}
|
|
{
|
|
// Canonicalization patterns
|
|
RewritePatternSet canonicalizationPatterns(funcOp.getContext());
|
|
vector::populateVectorTransferPermutationMapLoweringPatterns(
|
|
canonicalizationPatterns);
|
|
vector::populateVectorReductionToContractPatterns(canonicalizationPatterns);
|
|
stage1Patterns.push_back(std::move(canonicalizationPatterns));
|
|
}
|
|
SmallVector<FrozenRewritePatternSet, 4> frozenStage1Patterns;
|
|
llvm::move(stage1Patterns, std::back_inserter(frozenStage1Patterns));
|
|
FrozenRewritePatternSet stage2Patterns =
|
|
getLinalgTilingCanonicalizationPatterns(ctx);
|
|
(void)applyStagedPatterns(funcOp, frozenStage1Patterns, stage2Patterns);
|
|
}
|
|
|
|
static void applyVectorTransferForwardingPatterns(func::FuncOp funcOp) {
|
|
RewritePatternSet forwardPattern(funcOp.getContext());
|
|
forwardPattern.add<LinalgCopyVTRForwardingPattern>(funcOp.getContext());
|
|
forwardPattern.add<LinalgCopyVTWForwardingPattern>(funcOp.getContext());
|
|
(void)applyPatternsAndFoldGreedily(funcOp, std::move(forwardPattern));
|
|
}
|
|
|
|
static void applyLinalgToVectorPatterns(func::FuncOp funcOp) {
|
|
RewritePatternSet patterns(funcOp.getContext());
|
|
auto *ctx = funcOp.getContext();
|
|
patterns.add<LinalgVectorizationPattern>(
|
|
ctx, LinalgTransformationFilter()
|
|
.addOpFilter<ContractionOpInterface, FillOp, GenericOp>());
|
|
patterns.add<CopyVectorizationPattern>(ctx);
|
|
populatePadOpVectorizationPatterns(patterns);
|
|
populateConvolutionVectorizationPatterns(patterns);
|
|
(void)applyPatternsAndFoldGreedily(funcOp, std::move(patterns));
|
|
}
|
|
|
|
static void applyPadTensorToGenericPatterns(func::FuncOp funcOp) {
|
|
RewritePatternSet patterns(funcOp.getContext());
|
|
patterns.add<PadOpTransformationPattern>(funcOp.getContext());
|
|
(void)applyPatternsAndFoldGreedily(funcOp, std::move(patterns));
|
|
}
|
|
|
|
static void applyGeneralizePadTensorPatterns(func::FuncOp funcOp) {
|
|
RewritePatternSet patterns(funcOp.getContext());
|
|
patterns.add<GeneralizePadOpPattern>(funcOp.getContext());
|
|
(void)applyPatternsAndFoldGreedily(funcOp, std::move(patterns));
|
|
}
|
|
|
|
static void applyExtractSliceOfPadTensorSwapPattern(func::FuncOp funcOp) {
|
|
RewritePatternSet patterns(funcOp.getContext());
|
|
patterns.add<ExtractSliceOfPadTensorSwapPattern>(funcOp.getContext());
|
|
(void)applyPatternsAndFoldGreedily(funcOp, std::move(patterns));
|
|
}
|
|
|
|
static void applyTilePattern(func::FuncOp funcOp, const std::string &loopType,
|
|
ArrayRef<int64_t> tileSizes,
|
|
ArrayRef<int64_t> peeledLoops,
|
|
bool scalarizeDynamicDims) {
|
|
MLIRContext *context = funcOp.getContext();
|
|
RewritePatternSet tilingPattern(context);
|
|
LinalgTilingLoopType type =
|
|
llvm::StringSwitch<LinalgTilingLoopType>(loopType)
|
|
.Case("for", LinalgTilingLoopType::Loops)
|
|
.Case("affine", LinalgTilingLoopType::AffineLoops)
|
|
.Case("parallel", LinalgTilingLoopType::ParallelLoops);
|
|
auto linalgTilingOptions = linalg::LinalgTilingOptions()
|
|
.setPeeledLoops(peeledLoops)
|
|
.setLoopType(type);
|
|
if (scalarizeDynamicDims) {
|
|
linalgTilingOptions.scalarizeDynamicDims();
|
|
assert(tileSizes.empty() &&
|
|
"tileSizes and scalarizeDynamicDims is mutually exclusive");
|
|
} else {
|
|
linalgTilingOptions.setTileSizes(tileSizes);
|
|
}
|
|
linalg::LinalgTransformationFilter f(StringAttr::get(context, "tile"));
|
|
TilingPatterns<linalg::MatmulOp, linalg::GenericOp>::insert(
|
|
tilingPattern, linalgTilingOptions, f);
|
|
(void)applyPatternsAndFoldGreedily(funcOp, std::move(tilingPattern));
|
|
}
|
|
|
|
static void applySplitReduction(func::FuncOp funcOp) {
|
|
RewritePatternSet patterns(funcOp.getContext());
|
|
linalg::populateSplitReductionPattern(
|
|
patterns,
|
|
[](LinalgOp op) {
|
|
unsigned insertDimIndex = op.getNumLoops() - 1;
|
|
return std::make_pair(4, insertDimIndex);
|
|
},
|
|
LinalgTransformationFilter(
|
|
ArrayRef<StringAttr>{},
|
|
StringAttr::get(funcOp.getContext(), "SPLIT")));
|
|
(void)applyPatternsAndFoldGreedily(funcOp, std::move(patterns));
|
|
}
|
|
|
|
static void applyBubbleUpExtractSliceOpPattern(func::FuncOp funcOp) {
|
|
RewritePatternSet patterns(funcOp.getContext());
|
|
populateBubbleUpExtractSliceOpPatterns(patterns);
|
|
(void)applyPatternsAndFoldGreedily(funcOp, std::move(patterns));
|
|
}
|
|
|
|
/// Apply transformations specified as patterns.
|
|
void TestLinalgTransforms::runOnOperation() {
|
|
auto lambda = [&](void *) {
|
|
getOperation().walk([](LinalgOp op) {
|
|
op->removeAttr(LinalgTransforms::kLinalgTransformMarker);
|
|
});
|
|
};
|
|
std::unique_ptr<void, decltype(lambda)> cleanupGuard{(void *)1, lambda};
|
|
|
|
if (testPromotionOptions) {
|
|
RewritePatternSet patterns(&getContext());
|
|
fillPromotionCallBackPatterns(&getContext(), patterns);
|
|
(void)applyPatternsAndFoldGreedily(getOperation(), std::move(patterns));
|
|
return;
|
|
}
|
|
if (testTileAndDistributionOptions) {
|
|
RewritePatternSet patterns(&getContext());
|
|
fillTileAndDistributePatterns(&getContext(), patterns);
|
|
(void)applyPatternsAndFoldGreedily(getOperation(), std::move(patterns));
|
|
return;
|
|
}
|
|
if (testTileFuseAndDistributionOptions) {
|
|
RewritePatternSet patterns(&getContext());
|
|
fillTileFuseAndDistributePatterns(&getContext(), patterns);
|
|
(void)applyPatternsAndFoldGreedily(getOperation(), std::move(patterns));
|
|
return;
|
|
}
|
|
if (testPatterns)
|
|
return applyPatterns(getOperation());
|
|
if (testMatmulToVectorPatterns1dTiling || testMatmulToVectorPatterns2dTiling)
|
|
return applyMatmulToVectorPatterns(getOperation(),
|
|
testMatmulToVectorPatterns1dTiling,
|
|
testMatmulToVectorPatterns2dTiling);
|
|
if (testVectorTransferForwardingPatterns)
|
|
return applyVectorTransferForwardingPatterns(getOperation());
|
|
if (testGenericToVectorPattern)
|
|
return applyLinalgToVectorPatterns(getOperation());
|
|
if (testTransformPadTensor)
|
|
return applyPadTensorToGenericPatterns(getOperation());
|
|
if (testGeneralizePadTensor)
|
|
return applyGeneralizePadTensorPatterns(getOperation());
|
|
if (testSwapSubTensorPadTensor)
|
|
return applyExtractSliceOfPadTensorSwapPattern(getOperation());
|
|
if (testTilePattern)
|
|
return applyTilePattern(getOperation(), loopType, tileSizes, peeledLoops,
|
|
/*scalarizeDynamicDims=*/false);
|
|
if (testTileScalarizeDynamicDims)
|
|
return applyTilePattern(getOperation(), loopType, tileSizes,
|
|
/*peeledLoops=*/{}, /*scalarizeDynamicDims=*/true);
|
|
if (testSplitReduction)
|
|
return applySplitReduction(getOperation());
|
|
if (testBubbleUpExtractSliceOpPattern)
|
|
return applyBubbleUpExtractSliceOpPattern(getOperation());
|
|
}
|
|
|
|
namespace mlir {
|
|
namespace test {
|
|
void registerTestLinalgTransforms() {
|
|
PassRegistration<TestLinalgTransforms>();
|
|
}
|
|
} // namespace test
|
|
} // namespace mlir
|