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[mlir][spirv] Add integration tests for vector.interleave and vector.shuffle #93858

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Jun 3, 2024
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[mlir][spirv] Add integration tests for vector.interleave and vector.shuffle #93858

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[mlir][spirv] Add integration tests for vector.interleave and vector.…
angelz913 May 30, 2024
c7fb113
Add CMake dependency
angelz913 May 31, 2024
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1 change: 1 addition & 0 deletions mlir/lib/Conversion/GPUToSPIRV/CMakeLists.txt
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Expand Up @@ -13,6 +13,7 @@ add_mlir_conversion_library(MLIRGPUToSPIRV
MLIRIR
MLIRPass
MLIRSCFToSPIRV
MLIRVectorToSPIRV
MLIRSPIRVDialect
MLIRSPIRVConversion
MLIRSupport
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2 changes: 2 additions & 0 deletions mlir/lib/Conversion/GPUToSPIRV/GPUToSPIRVPass.cpp
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Expand Up @@ -18,6 +18,7 @@
#include "mlir/Conversion/GPUToSPIRV/GPUToSPIRV.h"
#include "mlir/Conversion/MemRefToSPIRV/MemRefToSPIRV.h"
#include "mlir/Conversion/SCFToSPIRV/SCFToSPIRV.h"
#include "mlir/Conversion/VectorToSPIRV/VectorToSPIRV.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"
#include "mlir/Dialect/GPU/IR/GPUDialect.h"
#include "mlir/Dialect/SPIRV/IR/SPIRVDialect.h"
Expand Down Expand Up @@ -132,6 +133,7 @@ void GPUToSPIRVPass::runOnOperation() {
mlir::arith::populateArithToSPIRVPatterns(typeConverter, patterns);
populateMemRefToSPIRVPatterns(typeConverter, patterns);
populateFuncToSPIRVPatterns(typeConverter, patterns);
populateVectorToSPIRVPatterns(typeConverter, patterns);

if (failed(applyFullConversion(gpuModule, *target, std::move(patterns))))
return signalPassFailure();
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79 changes: 79 additions & 0 deletions mlir/test/mlir-vulkan-runner/vector-interleave.mlir
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@@ -0,0 +1,79 @@
// RUN: mlir-vulkan-runner %s \
// RUN: --shared-libs=%vulkan-runtime-wrappers,%mlir_runner_utils \
// RUN: --entry-point-result=void | FileCheck %s

// CHECK: [0, 2, 1, 3]
module attributes {
gpu.container_module,
spirv.target_env = #spirv.target_env<
#spirv.vce<v1.0, [Shader], [SPV_KHR_storage_buffer_storage_class]>, #spirv.resource_limits<>>
} {
gpu.module @kernels {
gpu.func @kernel_vector_interleave(%arg0 : memref<2xi32>, %arg1 : memref<2xi32>, %arg2 : memref<4xi32>)
kernel attributes { spirv.entry_point_abi = #spirv.entry_point_abi<workgroup_size = [1, 1, 1]>} {
%idx0 = arith.constant 0 : index
%idx1 = arith.constant 1 : index
%idx2 = arith.constant 2 : index
%idx3 = arith.constant 3 : index
%idx4 = arith.constant 4 : index

%lhs = arith.constant dense<[0, 0]> : vector<2xi32>
%rhs = arith.constant dense<[0, 0]> : vector<2xi32>

%val0 = memref.load %arg0[%idx0] : memref<2xi32>
%val1 = memref.load %arg0[%idx1] : memref<2xi32>
%val2 = memref.load %arg1[%idx0] : memref<2xi32>
%val3 = memref.load %arg1[%idx1] : memref<2xi32>

%lhs0 = vector.insertelement %val0, %lhs[%idx0 : index] : vector<2xi32>
%lhs1 = vector.insertelement %val1, %lhs0[%idx1 : index] : vector<2xi32>
%rhs0 = vector.insertelement %val2, %rhs[%idx0 : index] : vector<2xi32>
%rhs1 = vector.insertelement %val3, %rhs0[%idx1 : index] : vector<2xi32>

%interleave = vector.interleave %lhs1, %rhs1 : vector<2xi32> -> vector<4xi32>

%res0 = vector.extractelement %interleave[%idx0 : index] : vector<4xi32>
%res1 = vector.extractelement %interleave[%idx1 : index] : vector<4xi32>
%res2 = vector.extractelement %interleave[%idx2 : index] : vector<4xi32>
%res3 = vector.extractelement %interleave[%idx3 : index] : vector<4xi32>

memref.store %res0, %arg2[%idx0]: memref<4xi32>
memref.store %res1, %arg2[%idx1]: memref<4xi32>
memref.store %res2, %arg2[%idx2]: memref<4xi32>
memref.store %res3, %arg2[%idx3]: memref<4xi32>

gpu.return
}
}

func.func @main() {
// Allocate 3 buffers.
%buf0 = memref.alloc() : memref<2xi32>
%buf1 = memref.alloc() : memref<2xi32>
%buf2 = memref.alloc() : memref<4xi32>

%idx0 = arith.constant 0 : index
%idx1 = arith.constant 1 : index
%idx4 = arith.constant 4 : index

// Initialize input buffer.
%buf0_vals = arith.constant dense<[0, 1]> : vector<2xi32>
%buf1_vals = arith.constant dense<[2, 3]> : vector<2xi32>
vector.store %buf0_vals, %buf0[%idx0] : memref<2xi32>, vector<2xi32>
vector.store %buf1_vals, %buf1[%idx0] : memref<2xi32>, vector<2xi32>

// Initialize output buffer.
%value0 = arith.constant 0 : i32
%buf3 = memref.cast %buf2 : memref<4xi32> to memref<?xi32>
call @fillResource1DInt(%buf3, %value0) : (memref<?xi32>, i32) -> ()

gpu.launch_func @kernels::@kernel_vector_interleave
blocks in (%idx4, %idx1, %idx1) threads in (%idx1, %idx1, %idx1)
args(%buf0 : memref<2xi32>, %buf1 : memref<2xi32>, %buf2 : memref<4xi32>)
%buf4 = memref.cast %buf3 : memref<?xi32> to memref<*xi32>
call @printMemrefI32(%buf4) : (memref<*xi32>) -> ()
return
}
func.func private @fillResource1DInt(%0 : memref<?xi32>, %1 : i32)
func.func private @printMemrefI32(%ptr : memref<*xi32>)
}
79 changes: 79 additions & 0 deletions mlir/test/mlir-vulkan-runner/vector-shuffle.mlir
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// RUN: mlir-vulkan-runner %s \
// RUN: --shared-libs=%vulkan-runtime-wrappers,%mlir_runner_utils \
// RUN: --entry-point-result=void | FileCheck %s

// CHECK: [2, 1, 3, 3]
module attributes {
gpu.container_module,
spirv.target_env = #spirv.target_env<
#spirv.vce<v1.0, [Shader], [SPV_KHR_storage_buffer_storage_class]>, #spirv.resource_limits<>>
} {
gpu.module @kernels {
gpu.func @kernel_vector_shuffle(%arg0 : memref<2xi32>, %arg1 : memref<2xi32>, %arg2 : memref<4xi32>)
kernel attributes { spirv.entry_point_abi = #spirv.entry_point_abi<workgroup_size = [1, 1, 1]>} {
%idx0 = arith.constant 0 : index
%idx1 = arith.constant 1 : index
%idx2 = arith.constant 2 : index
%idx3 = arith.constant 3 : index
%idx4 = arith.constant 4 : index

%lhs = arith.constant dense<[0, 0]> : vector<2xi32>
%rhs = arith.constant dense<[0, 0]> : vector<2xi32>

%val0 = memref.load %arg0[%idx0] : memref<2xi32>
%val1 = memref.load %arg0[%idx1] : memref<2xi32>
%val2 = memref.load %arg1[%idx0] : memref<2xi32>
%val3 = memref.load %arg1[%idx1] : memref<2xi32>

%lhs0 = vector.insertelement %val0, %lhs[%idx0 : index] : vector<2xi32>
%lhs1 = vector.insertelement %val1, %lhs0[%idx1 : index] : vector<2xi32>
%rhs0 = vector.insertelement %val2, %rhs[%idx0 : index] : vector<2xi32>
%rhs1 = vector.insertelement %val3, %rhs0[%idx1 : index] : vector<2xi32>

%shuffle = vector.shuffle %lhs1, %rhs1[2, 1, 3, 3] : vector<2xi32>, vector<2xi32>

%res0 = vector.extractelement %shuffle[%idx0 : index] : vector<4xi32>
%res1 = vector.extractelement %shuffle[%idx1 : index] : vector<4xi32>
%res2 = vector.extractelement %shuffle[%idx2 : index] : vector<4xi32>
%res3 = vector.extractelement %shuffle[%idx3 : index] : vector<4xi32>

memref.store %res0, %arg2[%idx0]: memref<4xi32>
memref.store %res1, %arg2[%idx1]: memref<4xi32>
memref.store %res2, %arg2[%idx2]: memref<4xi32>
memref.store %res3, %arg2[%idx3]: memref<4xi32>

gpu.return
}
}

func.func @main() {
// Allocate 3 buffers.
%buf0 = memref.alloc() : memref<2xi32>
%buf1 = memref.alloc() : memref<2xi32>
%buf2 = memref.alloc() : memref<4xi32>

%idx0 = arith.constant 0 : index
%idx1 = arith.constant 1 : index
%idx4 = arith.constant 4 : index

// Initialize input buffer.
%buf0_vals = arith.constant dense<[0, 1]> : vector<2xi32>
%buf1_vals = arith.constant dense<[2, 3]> : vector<2xi32>
vector.store %buf0_vals, %buf0[%idx0] : memref<2xi32>, vector<2xi32>
vector.store %buf1_vals, %buf1[%idx0] : memref<2xi32>, vector<2xi32>

// Initialize output buffer.
%value0 = arith.constant 0 : i32
%buf3 = memref.cast %buf2 : memref<4xi32> to memref<?xi32>
call @fillResource1DInt(%buf3, %value0) : (memref<?xi32>, i32) -> ()

gpu.launch_func @kernels::@kernel_vector_shuffle
blocks in (%idx4, %idx1, %idx1) threads in (%idx1, %idx1, %idx1)
args(%buf0 : memref<2xi32>, %buf1 : memref<2xi32>, %buf2 : memref<4xi32>)
%buf4 = memref.cast %buf3 : memref<?xi32> to memref<*xi32>
call @printMemrefI32(%buf4) : (memref<*xi32>) -> ()
return
}
func.func private @fillResource1DInt(%0 : memref<?xi32>, %1 : i32)
func.func private @printMemrefI32(%ptr : memref<*xi32>)
}
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