[Mlir-commits] [mlir] [mlir][spirv][gpu] Add conversion for load/store/mad coop matrix ops (PR #66311)
Jakub Kuderski
llvmlistbot at llvm.org
Thu Sep 14 19:13:22 PDT 2023
https://github.com/kuhar updated https://github.com/llvm/llvm-project/pull/66311:
>From cda7d50541e22a0262efff7ee7f17442c8a5d219 Mon Sep 17 00:00:00 2001
From: Jakub Kuderski <jakub at nod-labs.com>
Date: Wed, 13 Sep 2023 16:30:46 -0400
Subject: [PATCH] [mlir][spirv][gpu] Add conversion for load/store/mad coop
matrix ops
This is plugged in as an alternative lowering path in the gpu to spirv
dialect conversion.
The remaining lowering patterns will be added in a future patch.
---
.../mlir/Conversion/GPUToSPIRV/GPUToSPIRV.h | 10 ++
mlir/include/mlir/Conversion/Passes.td | 6 +-
.../SPIRV/IR/SPIRVCooperativeMatrixOps.td | 25 +++
.../Conversion/GPUToSPIRV/GPUToSPIRVPass.cpp | 20 ++-
.../Conversion/GPUToSPIRV/WmmaOpsToSPIRV.cpp | 145 +++++++++++++++++-
.../wmma-ops-to-spirv-khr-coop-matrix.mlir | 80 ++++++++++
.../wmma-ops-to-spirv-nv-coop-matrix.mlir | 3 +-
7 files changed, 278 insertions(+), 11 deletions(-)
create mode 100644 mlir/test/Conversion/GPUToSPIRV/wmma-ops-to-spirv-khr-coop-matrix.mlir
diff --git a/mlir/include/mlir/Conversion/GPUToSPIRV/GPUToSPIRV.h b/mlir/include/mlir/Conversion/GPUToSPIRV/GPUToSPIRV.h
index 6c4643da1884900..c258513ed4878ea 100644
--- a/mlir/include/mlir/Conversion/GPUToSPIRV/GPUToSPIRV.h
+++ b/mlir/include/mlir/Conversion/GPUToSPIRV/GPUToSPIRV.h
@@ -30,11 +30,21 @@ class MMAMatrixType;
void populateGPUToSPIRVPatterns(SPIRVTypeConverter &typeConverter,
RewritePatternSet &patterns);
+/// Collect a set of patterns to convert WMMA ops from GPU dialect to SPIRV,
+/// using the KHR Cooperative Matrix extension.
+void populateGpuWMMAToSPIRVCoopMatrixKHRConversionPatterns(
+ SPIRVTypeConverter &typeConverter, RewritePatternSet &patterns);
+
/// Collect a set of patterns to convert WMMA ops from GPU dialect to SPIRV,
/// using the NV Cooperative Matrix extension.
void populateGpuWMMAToSPIRVCoopMatrixNVConversionPatterns(
SPIRVTypeConverter &typeConverter, RewritePatternSet &patterns);
+/// Returns a KHR cooperative matrix type corresponding to the MMAMatrixType
+/// `type`.
+spirv::CooperativeMatrixType
+convertMMAToSPIRVCoopMatrixType(gpu::MMAMatrixType type);
+
/// Returns an NV cooperative matrix type corresponding to the MMAMatrixType
/// `type`.
spirv::CooperativeMatrixNVType
diff --git a/mlir/include/mlir/Conversion/Passes.td b/mlir/include/mlir/Conversion/Passes.td
index 3218760931b8cb0..11008baa0160efe 100644
--- a/mlir/include/mlir/Conversion/Passes.td
+++ b/mlir/include/mlir/Conversion/Passes.td
@@ -567,7 +567,11 @@ def ConvertGPUToSPIRV : Pass<"convert-gpu-to-spirv", "ModuleOp"> {
let options = [
Option<"use64bitIndex", "use-64bit-index",
"bool", /*default=*/"false",
- "Use 64-bit integers to convert index types">
+ "Use 64-bit integers to convert index types">,
+ Option<"useCoopMatrixNV", "use-coop-matrix-nv",
+ "bool", /*default=*/"true",
+ "Use the NV cooperative matrix extension insted of the KHR extension"
+ " to lower GPU WMMA ops">,
];
}
diff --git a/mlir/include/mlir/Dialect/SPIRV/IR/SPIRVCooperativeMatrixOps.td b/mlir/include/mlir/Dialect/SPIRV/IR/SPIRVCooperativeMatrixOps.td
index b5ea0774f589d16..34c76c5e9382302 100644
--- a/mlir/include/mlir/Dialect/SPIRV/IR/SPIRVCooperativeMatrixOps.td
+++ b/mlir/include/mlir/Dialect/SPIRV/IR/SPIRVCooperativeMatrixOps.td
@@ -146,6 +146,15 @@ def SPIRV_KHRCooperativeMatrixLoadOp : SPIRV_KhrVendorOp<"CooperativeMatrixLoad"
let results = (outs
SPIRV_AnyCooperativeMatrix:$result
);
+
+ let builders = [
+ OpBuilder<(ins "Type":$result, "Value":$pointer,
+ "spirv::ConstantOp":$stride,
+ "spirv::CooperativeMatrixLayoutKHR":$layout), [{
+ build($_builder, $_state, result, pointer, layout, stride,
+ spirv::MemoryAccessAttr{});
+ }]>
+ ];
}
// -----
@@ -226,6 +235,15 @@ def SPIRV_KHRCooperativeMatrixStoreOp : SPIRV_KhrVendorOp<"CooperativeMatrixStor
);
let results = (outs);
+
+ let builders = [
+ OpBuilder<(ins "Value":$pointer, "Value":$object,
+ "spirv::ConstantOp":$stride,
+ "spirv::CooperativeMatrixLayoutKHR":$layout), [{
+ build($_builder, $_state, pointer, object, layout, stride,
+ spirv::MemoryAccessAttr{});
+ }]>
+ ];
}
// -----
@@ -332,6 +350,13 @@ def SPIRV_KHRCooperativeMatrixMulAddOp : SPIRV_KhrVendorOp<"CooperativeMatrixMul
let results = (outs
SPIRV_AnyCooperativeMatrix:$result
);
+
+ let builders = [
+ OpBuilder<(ins "Value":$a, "Value":$b, "Value":$c), [{
+ build($_builder, $_state, a, b, c,
+ spirv::CooperativeMatrixOperandsKHRAttr{});
+ }]>
+ ];
}
//===----------------------------------------------------------------------===//
diff --git a/mlir/lib/Conversion/GPUToSPIRV/GPUToSPIRVPass.cpp b/mlir/lib/Conversion/GPUToSPIRV/GPUToSPIRVPass.cpp
index d0ce58597f980d4..5b05c45bf602509 100644
--- a/mlir/lib/Conversion/GPUToSPIRV/GPUToSPIRVPass.cpp
+++ b/mlir/lib/Conversion/GPUToSPIRV/GPUToSPIRVPass.cpp
@@ -86,13 +86,25 @@ void GPUToSPIRVPass::runOnOperation() {
SPIRVConversionOptions options;
options.use64bitIndex = this->use64bitIndex;
SPIRVTypeConverter typeConverter(targetAttr, options);
- typeConverter.addConversion([&](gpu::MMAMatrixType type) -> Type {
- return convertMMAToSPIRVCoopMatrixNVType(type);
+
+ typeConverter.addConversion([useNV = this->useCoopMatrixNV.getValue()](
+ gpu::MMAMatrixType type) -> Type {
+ if (useNV)
+ return convertMMAToSPIRVCoopMatrixNVType(type);
+
+ return convertMMAToSPIRVCoopMatrixType(type);
});
+
RewritePatternSet patterns(context);
populateGPUToSPIRVPatterns(typeConverter, patterns);
- populateGpuWMMAToSPIRVCoopMatrixNVConversionPatterns(typeConverter,
- patterns);
+ if (this->useCoopMatrixNV) {
+ populateGpuWMMAToSPIRVCoopMatrixNVConversionPatterns(typeConverter,
+ patterns);
+ } else {
+ populateGpuWMMAToSPIRVCoopMatrixKHRConversionPatterns(typeConverter,
+ patterns);
+ }
+
// TODO: Change SPIR-V conversion to be progressive and remove the following
// patterns.
mlir::arith::populateArithToSPIRVPatterns(typeConverter, patterns);
diff --git a/mlir/lib/Conversion/GPUToSPIRV/WmmaOpsToSPIRV.cpp b/mlir/lib/Conversion/GPUToSPIRV/WmmaOpsToSPIRV.cpp
index bf3fff027fe384a..d73cd5686d66e92 100644
--- a/mlir/lib/Conversion/GPUToSPIRV/WmmaOpsToSPIRV.cpp
+++ b/mlir/lib/Conversion/GPUToSPIRV/WmmaOpsToSPIRV.cpp
@@ -18,22 +18,28 @@
#include "mlir/Dialect/SPIRV/IR/SPIRVDialect.h"
#include "mlir/Dialect/SPIRV/IR/SPIRVEnums.h"
#include "mlir/Dialect/SPIRV/IR/SPIRVOps.h"
+#include "mlir/Dialect/SPIRV/IR/SPIRVTypes.h"
#include "mlir/Dialect/SPIRV/IR/TargetAndABI.h"
#include "mlir/Dialect/SPIRV/Transforms/SPIRVConversion.h"
+#include "mlir/IR/BuiltinAttributes.h"
+#include "mlir/IR/BuiltinTypes.h"
#include "mlir/IR/TypeUtilities.h"
+#include "llvm/ADT/StringSwitch.h"
-namespace mlir::nv {
-namespace {
+#include <cassert>
+namespace mlir {
/// Creates a SPIR-V op to replace the given GPU subgroup mma elementwise op
/// when the elementwise op directly supports with cooperative matrix type.
/// Returns false if cannot.
///
/// See SPV_NV_cooperative_matrix for supported elementwise ops.
static bool createElementwiseOp(ConversionPatternRewriter &builder,
- gpu::SubgroupMmaElementwiseOp op,
- spirv::CooperativeMatrixNVType coopType,
+ gpu::SubgroupMmaElementwiseOp op, Type coopType,
ValueRange operands) {
+ assert((isa<spirv::CooperativeMatrixType, spirv::CooperativeMatrixNVType>(
+ coopType)));
+
switch (op.getOpType()) {
case gpu::MMAElementwiseOp::ADDF:
builder.replaceOpWithNewOp<spirv::FAddOp>(op, coopType, operands);
@@ -71,6 +77,110 @@ static bool createElementwiseOp(ConversionPatternRewriter &builder,
return false;
}
+//===----------------------------------------------------------------------===//
+// SPV_KHR_cooperative_matrix
+//===----------------------------------------------------------------------===//
+
+namespace khr {
+namespace {
+
+/// Converts the GPU MMA loadOp to KHRCooperativeMatrixLoad op in the SPIRV
+/// dialect.
+struct WmmaLoadOpToSPIRVLowering final
+ : OpConversionPattern<gpu::SubgroupMmaLoadMatrixOp> {
+ using OpConversionPattern::OpConversionPattern;
+
+ LogicalResult
+ matchAndRewrite(gpu::SubgroupMmaLoadMatrixOp op, OpAdaptor adaptor,
+ ConversionPatternRewriter &rewriter) const override {
+ const auto &typeConverter = *getTypeConverter<SPIRVTypeConverter>();
+ Location loc = op->getLoc();
+
+ auto retType = cast<gpu::MMAMatrixType>(op.getRes().getType());
+ MemRefType memrefType = op.getSrcMemref().getType();
+ Value bufferPtr =
+ spirv::getElementPtr(typeConverter, memrefType, adaptor.getSrcMemref(),
+ adaptor.getIndices(), loc, rewriter);
+
+ auto coopType =
+ typeConverter.convertType<spirv::CooperativeMatrixType>(retType);
+ if (!coopType)
+ return rewriter.notifyMatchFailure(op, "type conversion failed");
+
+ int64_t stride = op.getLeadDimension().getSExtValue();
+ IntegerType i32Type = rewriter.getI32Type();
+ auto strideValue = rewriter.create<spirv::ConstantOp>(
+ loc, i32Type, IntegerAttr::get(i32Type, stride));
+
+ bool isColMajor = op.getTranspose().value_or(false);
+ auto layout = isColMajor ? spirv::CooperativeMatrixLayoutKHR::ColumnMajor
+ : spirv::CooperativeMatrixLayoutKHR::RowMajor;
+
+ rewriter.replaceOpWithNewOp<spirv::KHRCooperativeMatrixLoadOp>(
+ op, coopType, bufferPtr, strideValue, layout);
+ return success();
+ }
+};
+
+/// Converts the GPU MMA StoreOp to KHRCooperativeMatrixStore op in the SPIRV
+/// dialect.
+struct WmmaStoreOpToSPIRVLowering final
+ : OpConversionPattern<gpu::SubgroupMmaStoreMatrixOp> {
+ using OpConversionPattern::OpConversionPattern;
+
+ LogicalResult
+ matchAndRewrite(gpu::SubgroupMmaStoreMatrixOp op, OpAdaptor adaptor,
+ ConversionPatternRewriter &rewriter) const override {
+ const auto &typeConverter = *getTypeConverter<SPIRVTypeConverter>();
+ Location loc = op->getLoc();
+
+ auto memrefType = cast<MemRefType>(op.getDstMemref().getType());
+ Value bufferPtr =
+ spirv::getElementPtr(typeConverter, memrefType, adaptor.getDstMemref(),
+ adaptor.getIndices(), loc, rewriter);
+
+ int64_t stride = op.getLeadDimension().getSExtValue();
+ IntegerType i32Type = rewriter.getI32Type();
+ auto strideValue = rewriter.create<spirv::ConstantOp>(
+ loc, i32Type, IntegerAttr::get(i32Type, stride));
+
+ bool isColMajor = op.getTranspose().value_or(false);
+ auto layout = isColMajor ? spirv::CooperativeMatrixLayoutKHR::ColumnMajor
+ : spirv::CooperativeMatrixLayoutKHR::RowMajor;
+
+ rewriter.replaceOpWithNewOp<spirv::KHRCooperativeMatrixStoreOp>(
+ op, bufferPtr, adaptor.getSrc(), strideValue, layout);
+ return success();
+ }
+};
+
+/// Converts GPU MMA Compute to KHRCooperativeMatrixMulAdd op in the SPIRV
+/// dialect.
+struct WmmaMmaOpToSPIRVLowering final
+ : OpConversionPattern<gpu::SubgroupMmaComputeOp> {
+ using OpConversionPattern::OpConversionPattern;
+
+ LogicalResult
+ matchAndRewrite(gpu::SubgroupMmaComputeOp subgroupMmaComputeOp,
+ OpAdaptor adaptor,
+ ConversionPatternRewriter &rewriter) const override {
+ rewriter.replaceOpWithNewOp<spirv::KHRCooperativeMatrixMulAddOp>(
+ subgroupMmaComputeOp, adaptor.getOpA(), adaptor.getOpB(),
+ adaptor.getOpC());
+ return success();
+ }
+};
+
+} // namespace
+} // namespace khr
+
+//===----------------------------------------------------------------------===//
+// SPV_NV_cooperative_matrix
+//===----------------------------------------------------------------------===//
+
+namespace nv {
+namespace {
+
/// Converts the GPU MMA loadOp to NVCooperativeMatrixLoad op in the SPIRV
/// dialect.
struct WmmaLoadOpToSPIRVLowering final
@@ -247,7 +357,8 @@ struct WmmaElementwiseOpToSPIRVScalarMulLowering final
};
} // namespace
-} // namespace mlir::nv
+} // namespace nv
+} // namespace mlir
mlir::spirv::CooperativeMatrixNVType
mlir::convertMMAToSPIRVCoopMatrixNVType(gpu::MMAMatrixType type) {
@@ -257,6 +368,30 @@ mlir::convertMMAToSPIRVCoopMatrixNVType(gpu::MMAMatrixType type) {
elementType, spirv::Scope::Subgroup, retTypeShape[0], retTypeShape[1]);
}
+mlir::spirv::CooperativeMatrixType
+mlir::convertMMAToSPIRVCoopMatrixType(gpu::MMAMatrixType type) {
+ ArrayRef<int64_t> retTypeShape = type.getShape();
+ Type elementType = type.getElementType();
+
+ auto use =
+ llvm::StringSwitch<spirv::CooperativeMatrixUseKHR>(type.getOperand())
+ .Case("AOp", spirv::CooperativeMatrixUseKHR::MatrixA)
+ .Case("BOp", spirv::CooperativeMatrixUseKHR::MatrixB)
+ .Default(spirv::CooperativeMatrixUseKHR::MatrixAcc);
+
+ return spirv::CooperativeMatrixType::get(elementType, retTypeShape[0],
+ retTypeShape[1],
+ spirv::Scope::Subgroup, use);
+}
+
+void mlir::populateGpuWMMAToSPIRVCoopMatrixKHRConversionPatterns(
+ SPIRVTypeConverter &converter, RewritePatternSet &patterns) {
+ using namespace mlir;
+ MLIRContext *context = patterns.getContext();
+ patterns.add<khr::WmmaLoadOpToSPIRVLowering, khr::WmmaMmaOpToSPIRVLowering,
+ khr::WmmaStoreOpToSPIRVLowering>(converter, context);
+}
+
void mlir::populateGpuWMMAToSPIRVCoopMatrixNVConversionPatterns(
SPIRVTypeConverter &converter, RewritePatternSet &patterns) {
using namespace mlir;
diff --git a/mlir/test/Conversion/GPUToSPIRV/wmma-ops-to-spirv-khr-coop-matrix.mlir b/mlir/test/Conversion/GPUToSPIRV/wmma-ops-to-spirv-khr-coop-matrix.mlir
new file mode 100644
index 000000000000000..0818791b98471da
--- /dev/null
+++ b/mlir/test/Conversion/GPUToSPIRV/wmma-ops-to-spirv-khr-coop-matrix.mlir
@@ -0,0 +1,80 @@
+// RUN: mlir-opt --convert-gpu-to-spirv="use-coop-matrix-nv=false" --cse \
+// RUN: --split-input-file --verify-diagnostics %s | FileCheck %s
+
+module attributes {
+ gpu.container_module,
+ spirv.target_env = #spirv.target_env<#spirv.vce<v1.6,
+ [Shader, CooperativeMatrixKHR, Float16],
+ [SPV_KHR_storage_buffer_storage_class, SPV_KHR_cooperative_matrix]>,
+ #spirv.resource_limits<>>} {
+
+ gpu.module @kernels {
+ // CHECK-LABEL: spirv.func @gpu_wmma_load_op
+ // CHECK-SAME: !spirv.ptr<!spirv.struct<(!spirv.array<512 x f32, stride=4> [0])>, StorageBuffer>
+ gpu.func @gpu_wmma_load_op(%arg0 : memref<32x32xf16, #spirv.storage_class<StorageBuffer>>) kernel
+ attributes {spirv.entry_point_abi = #spirv.entry_point_abi<workgroup_size = [32, 4, 1]>} {
+ %i = arith.constant 16 : index
+ %j = arith.constant 16 : index
+ // CHECK: %[[STRIDE:.+]] = spirv.Constant 32 : i32
+ // CHECK: spirv.KHR.CooperativeMatrixLoad {{%.*}}, %[[STRIDE]], <RowMajor> :
+ // CHECK-SAME: !spirv.ptr<f32, StorageBuffer>, i32 -> !spirv.coopmatrix<16x16xf16, Subgroup, MatrixAcc>
+ %0 = gpu.subgroup_mma_load_matrix %arg0[%i, %j] {leadDimension = 32 : index} :
+ memref<32x32xf16, #spirv.storage_class<StorageBuffer>> -> !gpu.mma_matrix<16x16xf16, "COp">
+
+ // CHECK: spirv.KHR.CooperativeMatrixLoad {{%.*}}, %[[STRIDE]], <ColumnMajor> :
+ // CHECK-SAME: !spirv.ptr<f32, StorageBuffer>, i32 -> !spirv.coopmatrix<16x16xf16, Subgroup, MatrixAcc>
+ %1 = gpu.subgroup_mma_load_matrix %arg0[%i, %j] {leadDimension = 32 : index, transpose} :
+ memref<32x32xf16, #spirv.storage_class<StorageBuffer>> -> !gpu.mma_matrix<16x16xf16, "COp">
+ // CHECK: spirv.Return
+ gpu.return
+ }
+
+ // CHECK-LABEL: spirv.func @gpu_wmma_store_op
+ // CHECK-SAME: !spirv.ptr<!spirv.struct<(!spirv.array<512 x f32, stride=4> [0])>, StorageBuffer>
+ // CHECK-SAME: !spirv.coopmatrix<16x16xf16, Subgroup, MatrixAcc>
+ gpu.func @gpu_wmma_store_op(%arg0: memref<32x32xf16, #spirv.storage_class<StorageBuffer>>,
+ %arg1: !gpu.mma_matrix<16x16xf16, "COp">) kernel
+ attributes {spirv.entry_point_abi = #spirv.entry_point_abi<workgroup_size = [32, 4, 1]>} {
+ %i = arith.constant 16 : index
+ %j = arith.constant 16 : index
+ // CHECK: %[[STRIDE:.+]] = spirv.Constant 32 : i32
+ // CHECK: spirv.KHR.CooperativeMatrixStore {{%.*}}, {{%.*}}, %[[STRIDE]], <RowMajor> :
+ // CHECK-SAME: !spirv.ptr<f32, StorageBuffer>, !spirv.coopmatrix<16x16xf16, Subgroup, MatrixAcc>
+ gpu.subgroup_mma_store_matrix %arg1, %arg0[%i,%j] {leadDimension = 32 : index} :
+ !gpu.mma_matrix<16x16xf16, "COp">, memref<32x32xf16, #spirv.storage_class<StorageBuffer>>
+
+ // CHECK: spirv.KHR.CooperativeMatrixStore {{%.*}}, {{%.*}}, %[[STRIDE]], <ColumnMajor> :
+ // CHECK-SAME: !spirv.ptr<f32, StorageBuffer>, !spirv.coopmatrix<16x16xf16, Subgroup, MatrixAcc>
+ gpu.subgroup_mma_store_matrix %arg1, %arg0[%i,%j] {leadDimension = 32 : index, transpose} :
+ !gpu.mma_matrix<16x16xf16, "COp">, memref<32x32xf16, #spirv.storage_class<StorageBuffer>>
+ // CHECK: spirv.Return
+ gpu.return
+ }
+
+ // CHECK-LABEL: spirv.func @gpu_wmma_mma_op
+ // CHECK-SAME: !spirv.coopmatrix<16x16xf16, Subgroup, MatrixA>
+ // CHECK-SAME: !spirv.coopmatrix<16x16xf16, Subgroup, MatrixB>
+ // CHECK-SAME: !spirv.coopmatrix<16x16xf16, Subgroup, MatrixAcc>
+ gpu.func @gpu_wmma_mma_op(%A: !gpu.mma_matrix<16x16xf16, "AOp">,
+ %B: !gpu.mma_matrix<16x16xf16, "BOp">,
+ %C: !gpu.mma_matrix<16x16xf16, "COp">,
+ %ptr: memref<16x16xf16, #spirv.storage_class<StorageBuffer>>) kernel
+ attributes {spirv.entry_point_abi = #spirv.entry_point_abi<workgroup_size = [32, 4, 1]>} {
+ // CHECK: %[[MAD:.*]] = spirv.KHR.CooperativeMatrixMulAdd {{%.*}}, {{%.*}}, {{%.*}} :
+ // CHECK-SAME: !spirv.coopmatrix<16x16xf16, Subgroup, MatrixA>,
+ // CHECK-SAME: !spirv.coopmatrix<16x16xf16, Subgroup, MatrixB>
+ // CHECK-SAME: -> !spirv.coopmatrix<16x16xf16, Subgroup, MatrixAcc>
+ %D = gpu.subgroup_mma_compute %A, %B, %C : !gpu.mma_matrix<16x16xf16, "AOp">,
+ !gpu.mma_matrix<16x16xf16, "BOp">
+ -> !gpu.mma_matrix<16x16xf16, "COp">
+
+ %i = arith.constant 0 : index
+ // CHECK: spirv.KHR.CooperativeMatrixStore {{%.+}}, %[[MAD]], %{{.+}}, <RowMajor>
+ gpu.subgroup_mma_store_matrix %D, %ptr[%i,%i] {leadDimension = 32 : index} :
+ !gpu.mma_matrix<16x16xf16, "COp">, memref<16x16xf16, #spirv.storage_class<StorageBuffer>>
+ // CHECK: spirv.Return
+ gpu.return
+ }
+
+ }
+}
diff --git a/mlir/test/Conversion/GPUToSPIRV/wmma-ops-to-spirv-nv-coop-matrix.mlir b/mlir/test/Conversion/GPUToSPIRV/wmma-ops-to-spirv-nv-coop-matrix.mlir
index 5811c791f308d1e..ec7da92704c07c2 100644
--- a/mlir/test/Conversion/GPUToSPIRV/wmma-ops-to-spirv-nv-coop-matrix.mlir
+++ b/mlir/test/Conversion/GPUToSPIRV/wmma-ops-to-spirv-nv-coop-matrix.mlir
@@ -1,4 +1,5 @@
-// RUN: mlir-opt --convert-gpu-to-spirv --split-input-file --verify-diagnostics %s | FileCheck %s
+// RUN: mlir-opt --convert-gpu-to-spirv="use-coop-matrix-nv=true" \
+// RUN: --split-input-file --verify-diagnostics %s | FileCheck %s
module attributes {
gpu.container_module,
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