[mlir][linalg] Add padding pass to strategy passes.

Add a strategy pass that pads and hoists after tiling and fusion.

Depends On D112412

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D112480
This commit is contained in:
Tobias Gysi
2021-10-29 15:14:45 +00:00
parent 9668e19e0c
commit 6638112b42
6 changed files with 176 additions and 24 deletions

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@@ -88,6 +88,13 @@ std::unique_ptr<OperationPass<FuncOp>> createLinalgStrategyTilePass(
linalg::LinalgTransformationFilter filter =
linalg::LinalgTransformationFilter());
/// Create a LinalgStrategyPadPass.
std::unique_ptr<OperationPass<FuncOp>> createLinalgStrategyPadPass(
StringRef opName = "",
linalg::LinalgPaddingOptions opt = linalg::LinalgPaddingOptions(),
linalg::LinalgTransformationFilter filter =
linalg::LinalgTransformationFilter());
/// Create a LinalgStrategyPromotePass.
std::unique_ptr<OperationPass<FuncOp>> createLinalgStrategyPromotePass(
StringRef opName = "",

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@@ -248,6 +248,19 @@ def LinalgStrategyTilePass
];
}
def LinalgStrategyPadPass
: FunctionPass<"linalg-strategy-pad-pass"> {
let summary = "Configurable pass to apply padding and hoisting.";
let constructor = "mlir::createLinalgStrategyPadPass()";
let dependentDialects = ["linalg::LinalgDialect"];
let options = [
Option<"anchorFuncName", "anchor-func", "std::string", /*default=*/"",
"Which func op is the anchor to latch on.">,
Option<"anchorOpName", "anchor-op", "std::string", /*default=*/"",
"Which linalg op within the func is the anchor to latch on.">,
];
}
def LinalgStrategyPromotePass
: FunctionPass<"linalg-strategy-promote-pass"> {
let summary = "Configurable pass to apply pattern-based linalg promotion.";

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@@ -46,6 +46,22 @@ private:
linalg::LinalgTilingOptions options;
};
/// Represent one application of LinalgStrategyPadPass.
struct Pad : public Transformation {
Pad(StringRef name, linalg::LinalgPaddingOptions options,
LinalgTransformationFilter::FilterFunction f = nullptr)
: Transformation(f), opName(name), options(options) {}
void addToPassPipeline(OpPassManager &pm,
LinalgTransformationFilter m) const override {
pm.addPass(createLinalgStrategyPadPass(opName, options, m));
}
private:
std::string opName;
linalg::LinalgPaddingOptions options;
};
/// Represent one application of createLinalgStrategyPromotePass.
struct Promote : public Transformation {
Promote(StringRef name, linalg::LinalgPromotionOptions options,
@@ -147,6 +163,21 @@ struct CodegenStrategy {
LinalgTransformationFilter::FilterFunction f = nullptr) {
return b ? tile(opName, options) : *this;
}
/// Append a pattern to pad and hoist the operands of Op `opName` with padding
/// `options`.
CodegenStrategy &pad(StringRef opName, linalg::LinalgPaddingOptions options,
LinalgTransformationFilter::FilterFunction f = nullptr) {
transformationSequence.emplace_back(
std::make_unique<Pad>(opName, options, f));
return *this;
}
/// Conditionally append a pattern to pad and hoist the operands of Op
/// `opName` with padding `options`.
CodegenStrategy &
padIf(bool b, StringRef opName, linalg::LinalgPaddingOptions options,
LinalgTransformationFilter::FilterFunction f = nullptr) {
return b ? pad(opName, options, f) : *this;
}
/// Append a pattern to add a level of promotion for `LinalgOpType` with
/// promotion `options`.
CodegenStrategy &

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@@ -68,6 +68,39 @@ struct LinalgStrategyTilePass
LinalgTransformationFilter filter;
};
/// Configurable pass to apply hoisting and padding.
struct LinalgStrategyPadPass
: public LinalgStrategyPadPassBase<LinalgStrategyPadPass> {
LinalgStrategyPadPass() = default;
LinalgStrategyPadPass(StringRef opName, LinalgPaddingOptions opt,
LinalgTransformationFilter filt)
: options(opt), filter(filt) {
this->anchorOpName.setValue(opName.str());
}
void runOnFunction() override {
auto funcOp = getFunction();
if (!anchorFuncName.empty() && funcOp.getName() != anchorFuncName)
return;
RewritePatternSet paddingPattern(funcOp.getContext());
if (!anchorOpName.empty()) {
paddingPattern.add<LinalgPaddingPattern>(
anchorOpName, funcOp.getContext(), options, filter);
} else {
paddingPattern.add<LinalgPaddingPattern>(funcOp.getContext(), options,
filter);
}
if (failed(applyPatternsAndFoldGreedily(funcOp, std::move(paddingPattern))))
signalPassFailure();
}
LinalgPaddingOptions options;
LinalgTransformationFilter filter;
};
/// Configurable pass to apply pattern-based linalg generalization.
struct LinalgStrategyGeneralizePass
: public LinalgStrategyGeneralizePassBase<LinalgStrategyGeneralizePass> {
@@ -332,6 +365,13 @@ mlir::createLinalgStrategyTilePass(StringRef opName, LinalgTilingOptions opt,
return std::make_unique<LinalgStrategyTilePass>(opName, opt, filter);
}
/// Create a LinalgStrategyPadPass.
std::unique_ptr<OperationPass<FuncOp>>
mlir::createLinalgStrategyPadPass(StringRef opName, LinalgPaddingOptions opt,
LinalgTransformationFilter filter) {
return std::make_unique<LinalgStrategyPadPass>(opName, opt, filter);
}
/// Create a LinalgStrategyPromotePass.
std::unique_ptr<OperationPass<FuncOp>>
mlir::createLinalgStrategyPromotePass(StringRef opName,

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@@ -1,28 +1,53 @@
// Test that both anchor-op name and MatmulOp-based codegen strategy produce the same result.
// RUN: mlir-opt %s -test-linalg-codegen-strategy="anchor-func=matmul anchor-op=linalg.matmul tile-sizes=2,4,8 vectorize vectorize-contraction-to=matrixintrinsics unroll-vector-transfers=true" | FileCheck %s
// RUN: mlir-opt %s -test-linalg-codegen-strategy="anchor-func=matmul anchor-op=linalg.matmul tile-sizes=2,4,8 tile-interchange=1,2,0 vectorize vectorize-contraction-to=matrixintrinsics unroll-vector-transfers=true" | FileCheck %s
// RUN: mlir-opt %s -test-linalg-codegen-strategy="anchor-func=matmul anchor-op=linalg.matmul tile-sizes=16,32,64 promote promote-full-tile-pad register-tile-sizes=2,4,8 vectorize vectorize-contraction-to=outerproduct split-transfers=true unroll-vector-transfers=false" | FileCheck %s --check-prefix=OUTER
// RUN: mlir-opt %s -test-linalg-codegen-strategy="anchor-func=matmul anchor-op=linalg.matmul tile-sizes=2,4,8 vectorize vectorize-contraction-to=matrixintrinsics unroll-vector-transfers=true" | FileCheck %s
// RUN: mlir-opt %s -test-linalg-codegen-strategy="anchor-func=matmul anchor-op=linalg.matmul tile-sizes=16,32,64 promote promote-full-tile-pad register-tile-sizes=2,4,8 vectorize vectorize-contraction-to=outerproduct split-transfers=true unroll-vector-transfers=false" | FileCheck %s --check-prefix=OUTER
// RUN: mlir-opt %s -test-linalg-codegen-strategy="anchor-func=matmul anchor-op=linalg.matmul tile-sizes=16,32,64 generalize iterator-interchange=0,2,1" | FileCheck %s --check-prefix=GENER
// RUN: mlir-opt %s -test-linalg-codegen-strategy="anchor-func=matmul anchor-op=linalg.matmul tile-sizes=2,4,8 vectorize vectorize-contraction-to=matrixintrinsics unroll-vector-transfers=true" -split-input-file | FileCheck %s --check-prefix=CHECK-INTRINSIC
// RUN: mlir-opt %s -test-linalg-codegen-strategy="anchor-func=matmul anchor-op=linalg.matmul tile-sizes=16,32,64 promote promote-full-tile-pad register-tile-sizes=2,4,8 vectorize vectorize-contraction-to=outerproduct split-transfers=true unroll-vector-transfers=false" -split-input-file | FileCheck %s --check-prefix=CHECK-OUTER
// RUN: mlir-opt %s -test-linalg-codegen-strategy="anchor-func=matmul anchor-op=linalg.matmul tile-sizes=16,32,64 tile-interchange=1,2,0 generalize iterator-interchange=0,2,1" -split-input-file | FileCheck %s --check-prefix=CHECK-INTERCHANGE
// RUN: mlir-opt %s -test-linalg-codegen-strategy="anchor-func=matmul anchor-op=linalg.matmul tile-sizes=16,32,64 pad pack-paddings=1,1,0 hoist-paddings=3,3,0" -split-input-file | FileCheck %s --check-prefix=CHECK-PAD
// CHECK-INTRINSIC: func @matmul(
// CHECK-OUTER: func @matmul(
func @matmul(%arg0: memref<72x72xf32>, %arg1: memref<72x72xf32>, %arg2: memref<72x72xf32>) {
// CHECK-LABEL: func @matmul(
// OUTER-LABEL: func @matmul(
// GENER-LABEL: func @matmul(
func @matmul(%A: memref<1584x1584xf32>, %B: memref<1584x1584xf32>, %C: memref<1584x1584xf32>) {
linalg.matmul
ins(%A, %B: memref<1584x1584xf32>, memref<1584x1584xf32>)
outs(%C: memref<1584x1584xf32>)
// Check the matrix intrinsic lowering is triggered.
// CHECK-INTRINSIC: vector.matrix_multiply
// CHECK-INTRINSIC-SAME: {lhs_columns = 8 : i32, lhs_rows = 2 : i32, rhs_columns = 4 : i32}
// CHECK-INTRINSIC-SAME: (vector<16xf32>, vector<32xf32>) -> vector<8xf32>
// CHECK: vector.matrix_multiply
// CHECK-SAME: {lhs_columns = 8 : i32, lhs_rows = 2 : i32, rhs_columns = 4 : i32}
// CHECK-SAME: (vector<16xf32>, vector<32xf32>) -> vector<8xf32>
// OUTER: vector.outerproduct {{.*}} : vector<2xf32>, vector<4xf32>
// GENER: linalg.generic
// GENER-SAME: iterator_types = ["parallel", "reduction", "parallel"]
// Check the outer product lowering is triggered.
// CHECK-OUTER: vector.outerproduct {{.*}} : vector<2xf32>, vector<4xf32>
linalg.matmul ins(%arg0, %arg1: memref<72x72xf32>, memref<72x72xf32>) outs(%arg2: memref<72x72xf32>)
return
}
// -----
// CHECK-INTERCHANGE: func @matmul(
func @matmul(%arg0: tensor<72x72xf32>, %arg1: tensor<72x72xf32>, %arg2: tensor<72x72xf32>) -> tensor<72x72xf32> {
// CHECK-INTERCHANGE-DAG: %[[C16:.*]] = arith.constant 16
// CHECK-INTERCHANGE-DAG: %[[C32:.*]] = arith.constant 32
// CHECK-INTERCHANGE-DAG: %[[C64:.*]] = arith.constant 64
// Check the tile loops are interchanged.
// CHECK-INTERCHANGE: scf.for {{.*}} step %[[C32]]
// CHECK-INTERCHANGE: scf.for {{.*}} step %[[C64]]
// CHECK-INTERCHANGE: scf.for {{.*}} step %[[C16]]
// Check the operation has been generalized and interchanged.
// CHECK-INTERCHANGE: linalg.generic
// CHECK-INTERCHANGE-SAME: iterator_types = ["parallel", "reduction", "parallel"]
%0 = linalg.matmul ins(%arg0, %arg1: tensor<72x72xf32>, tensor<72x72xf32>) outs(%arg2: tensor<72x72xf32>) -> tensor<72x72xf32>
return %0 : tensor<72x72xf32>
}
// -----
// CHECK-PAD: func @matmul(
func @matmul(%arg0: tensor<72x72xf32>, %arg1: tensor<72x72xf32>, %arg2: tensor<72x72xf32>) -> tensor<72x72xf32> {
// Check the padding of the input operands has been hoisted out of the tile loop nest.
// CHECK-PAD-COUNT=2: linalg.pad_tensor %{{.*}} nofold
// CHECK-PAD-COUNT=3: scf.for
// CHECK-PAD: linalg.matmul
%0 = linalg.matmul ins(%arg0, %arg1: tensor<72x72xf32>, tensor<72x72xf32>) outs(%arg2: tensor<72x72xf32>) -> tensor<72x72xf32>
return %0 : tensor<72x72xf32>
}

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@@ -54,6 +54,7 @@ struct TestLinalgCodegenStrategy
void runStrategy(LinalgTilingOptions tilingOptions,
LinalgTilingOptions registerTilingOptions,
LinalgPaddingOptions paddingOptions,
vector::VectorContractLowering vectorContractLowering,
vector::VectorTransferSplit vectorTransferSplit);
@@ -86,6 +87,16 @@ struct TestLinalgCodegenStrategy
*this, "register-promote-full-tile-pad",
llvm::cl::desc("Pad the small aligned memory buffer to the tile sizes."),
llvm::cl::init(false)};
Option<bool> pad{*this, "pad", llvm::cl::desc("Pad the operands."),
llvm::cl::init(false)};
ListOption<int64_t> packPaddings{
*this, "pack-paddings",
llvm::cl::desc("Operand packing flags when test-pad-pattern"),
llvm::cl::ZeroOrMore, llvm::cl::MiscFlags::CommaSeparated};
ListOption<int64_t> hoistPaddings{
*this, "hoist-paddings",
llvm::cl::desc("Operand hoisting depths when test-pad-pattern"),
llvm::cl::ZeroOrMore, llvm::cl::MiscFlags::CommaSeparated};
Option<bool> generalize{*this, "generalize",
llvm::cl::desc("Generalize named operations."),
llvm::cl::init(false)};
@@ -132,9 +143,18 @@ struct TestLinalgCodegenStrategy
llvm::cl::init("")};
};
// For now, just assume it is the zero of type.
// In the future, it should be the zero of type + op.
static Value getNeutralOfLinalgOp(OpBuilder &b, OpOperand &op) {
auto t = getElementTypeOrSelf(op.get());
return b.create<arith::ConstantOp>(op.getOwner()->getLoc(), t,
b.getZeroAttr(t));
}
void TestLinalgCodegenStrategy::runStrategy(
LinalgTilingOptions tilingOptions,
LinalgTilingOptions registerTilingOptions,
LinalgPaddingOptions paddingOptions,
vector::VectorContractLowering vectorContractLowering,
vector::VectorTransferSplit vectorTransferSplit) {
assert(!anchorOpName.empty());
@@ -150,6 +170,7 @@ void TestLinalgCodegenStrategy::runStrategy(
LinalgPromotionOptions()
.setAlignment(16)
.setUseFullTileBuffersByDefault(registerPromoteFullTile))
.padIf(pad, anchorOpName, paddingOptions)
.generalizeIf(generalize, anchorOpName)
.interchangeIf(!iteratorInterchange.empty(), iteratorInterchange)
.vectorizeIf(vectorize, generalize ? genericOpName : anchorOpName)
@@ -191,6 +212,21 @@ void TestLinalgCodegenStrategy::runOnFunction() {
registerTilingOptions =
registerTilingOptions.setTileSizes(registerTileSizes);
LinalgPaddingOptions paddingOptions;
auto packFunc = [&](OpOperand &opOperand) {
return opOperand.getOperandNumber() < packPaddings.size()
? packPaddings[opOperand.getOperandNumber()]
: false;
};
auto hoistingFunc = [&](OpOperand &opOperand) {
return opOperand.getOperandNumber() < hoistPaddings.size()
? hoistPaddings[opOperand.getOperandNumber()]
: 0;
};
paddingOptions.setPaddingValueComputationFunction(getNeutralOfLinalgOp);
paddingOptions.setPaddingNoFoldComputationFunction(packFunc);
paddingOptions.setPaddingHoistComputationFunction(hoistingFunc);
vector::VectorContractLowering vectorContractLowering =
llvm::StringSwitch<vector::VectorContractLowering>(
vectorizeContractionTo.getValue())
@@ -206,8 +242,8 @@ void TestLinalgCodegenStrategy::runOnFunction() {
.Case("vector-transfers", vector::VectorTransferSplit::VectorTransfer)
.Default(vector::VectorTransferSplit::None);
runStrategy(tilingOptions, registerTilingOptions, vectorContractLowering,
vectorTransferSplit);
runStrategy(tilingOptions, registerTilingOptions, paddingOptions,
vectorContractLowering, vectorTransferSplit);
}
namespace mlir {