[mlir][gpu]Add GPUToXeVM lowering pipeline pass. #161216
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mshahneo
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It's the default GPU to XeVM lowering pipeline. It starts by lowering GPU code to the specified compilation target (default is fatbin), then lowers the host code. If XeGPU ops are used, it expects the MLIR code to have XeGPU ops already embedded in gpu code.
XeGPU allows worgroup, subgroup, and workitem level programming. This options lets the pass manager know at which level the XeGPU ops belong to.
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@llvm/pr-subscribers-mlir @llvm/pr-subscribers-mlir-gpu Author: Md Abdullah Shahneous Bari (mshahneo) ChangesIt's the default GPU to XeVM lowering pipeline. It starts by lowering GPU code to the specified compilation target (default is fatbin), then lowers the host code. Patch is 35.92 KiB, truncated to 20.00 KiB below, full version: https://github.com/llvm/llvm-project/pull/161216.diff 7 Files Affected:
diff --git a/mlir/include/mlir/Dialect/GPU/Pipelines/Passes.h b/mlir/include/mlir/Dialect/GPU/Pipelines/Passes.h
index 035235fc7174a..67dc6415008f3 100644
--- a/mlir/include/mlir/Dialect/GPU/Pipelines/Passes.h
+++ b/mlir/include/mlir/Dialect/GPU/Pipelines/Passes.h
@@ -1,4 +1,4 @@
-//===- Passes.h - GPU NVVM pipeline entry points --------------------------===//
+//===- Passes.h - GPU NVVM/XeVM pipeline entry points----------------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
@@ -60,6 +60,53 @@ struct GPUToNVVMPipelineOptions
llvm::cl::init(false)};
};
+// Options for the gpu to xevm pipeline.
+struct GPUToXeVMPipelineOptions
+ : public PassPipelineOptions<GPUToXeVMPipelineOptions> {
+ // XeGPU op granularity selection: workgroup | subgroup | workitem
+ PassOptions::Option<std::string> xegpuOpLevel{
+ *this, "xegpu-op-level",
+ llvm::cl::desc("Granularity of XeGPU operations to target: workgroup | "
+ "subgroup | workitem"),
+ llvm::cl::init("workgroup")};
+ // General lowering controls.
+ PassOptions::Option<bool> use64bitIndex{
+ *this, "use-64bit-index",
+ llvm::cl::desc("Bitwidth of the index type (host & device)"),
+ llvm::cl::init(true)};
+ PassOptions::Option<bool> kernelBarePtrCallConv{
+ *this, "kernel-bare-ptr-calling-convention",
+ llvm::cl::desc("Use bare pointer calling convention for device kernels"),
+ llvm::cl::init(false)};
+ PassOptions::Option<bool> hostBarePtrCallConv{
+ *this, "host-bare-ptr-calling-convention",
+ llvm::cl::desc("Use bare pointer calling convention for host launches"),
+ llvm::cl::init(false)};
+ PassOptions::Option<std::string> binaryFormat{
+ *this, "binary-format",
+ llvm::cl::desc("Final GPU binary emission format (e.g. fatbin)"),
+ llvm::cl::init("fatbin")};
+ // Options mirroring xevm-attach-target (GpuXeVMAttachTarget).
+ PassOptions::Option<std::string> xevmModuleMatcher{
+ *this, "xevm-module-matcher",
+ llvm::cl::desc("Regex to match gpu.module names for XeVM target attach"),
+ llvm::cl::init("")};
+ PassOptions::Option<std::string> zebinTriple{
+ *this, "zebin-triple", llvm::cl::desc("Target triple for XeVM codegen"),
+ llvm::cl::init("spirv64-unknown-unknown")};
+ PassOptions::Option<std::string> zebinChip{
+ *this, "zebin-chip", llvm::cl::desc("Target chip (e.g. pvc, bmg)"),
+ llvm::cl::init("bmg")};
+ PassOptions::Option<unsigned> optLevel{
+ *this, "opt-level",
+ llvm::cl::desc("Optimization level for attached target/codegen"),
+ llvm::cl::init(2)};
+ PassOptions::Option<std::string> cmdOptions{
+ *this, "igc-cmd-options",
+ llvm::cl::desc("Additional downstream compiler command line options"),
+ llvm::cl::init("")};
+};
+
//===----------------------------------------------------------------------===//
// Building and Registering.
//===----------------------------------------------------------------------===//
@@ -70,8 +117,15 @@ struct GPUToNVVMPipelineOptions
void buildLowerToNVVMPassPipeline(OpPassManager &pm,
const GPUToNVVMPipelineOptions &options);
+/// Adds the GPU to XeVM pipeline to the given pass manager. Transforms main
+/// dialects into XeVM targets. Begins with GPU code regions, then handles host
+/// code.
+void buildLowerToXeVMPassPipeline(OpPassManager &pm,
+ const GPUToXeVMPipelineOptions &options);
+
/// Register all pipeleines for the `gpu` dialect.
void registerGPUToNVVMPipeline();
+void registerGPUToXeVMPipeline();
} // namespace gpu
} // namespace mlir
diff --git a/mlir/lib/Dialect/GPU/Pipelines/CMakeLists.txt b/mlir/lib/Dialect/GPU/Pipelines/CMakeLists.txt
index 70a9c77a6d796..f231eebe6d82b 100644
--- a/mlir/lib/Dialect/GPU/Pipelines/CMakeLists.txt
+++ b/mlir/lib/Dialect/GPU/Pipelines/CMakeLists.txt
@@ -1,5 +1,6 @@
add_mlir_dialect_library(MLIRGPUPipelines
GPUToNVVMPipeline.cpp
+ GPUToXeVMPipeline.cpp
ADDITIONAL_HEADER_DIRS
${MLIR_MAIN_INCLUDE_DIR}/mlir/Dialect/GPU
@@ -12,6 +13,7 @@ add_mlir_dialect_library(MLIRGPUPipelines
MLIRLinalgTransforms
MLIRAffineToStandard
MLIRGPUToNVVMTransforms
+ MLIRXeGPUToXeVM
MLIRIndexToLLVM
MLIRMathToLLVM
MLIRNVGPUToNVVM
@@ -19,4 +21,7 @@ add_mlir_dialect_library(MLIRGPUPipelines
MLIRReconcileUnrealizedCasts
MLIRSCFToControlFlow
MLIRVectorToSCF
+ MLIRXeGPUTransforms
+ MLIRXeGPUToXeVM
+ MLIRXeVMToLLVM
)
diff --git a/mlir/lib/Dialect/GPU/Pipelines/GPUToXeVMPipeline.cpp b/mlir/lib/Dialect/GPU/Pipelines/GPUToXeVMPipeline.cpp
new file mode 100644
index 0000000000000..e3e1bab3e12d1
--- /dev/null
+++ b/mlir/lib/Dialect/GPU/Pipelines/GPUToXeVMPipeline.cpp
@@ -0,0 +1,145 @@
+//===- GPUToXeVMPipeline.cpp - Lowering pipeline to XeVM/LLVM -------------===//
+//
+// 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 a pass for testing the lowering to XeVM as a generally
+// usable sink pass. If XeGPU ops are used, it expects the MLIR code to have
+// XeGPU ops already embedded in gpu code.
+//
+//===----------------------------------------------------------------------===//
+
+#include "mlir/Conversion/AffineToStandard/AffineToStandard.h"
+#include "mlir/Conversion/ArithToLLVM/ArithToLLVM.h"
+#include "mlir/Conversion/ControlFlowToLLVM/ControlFlowToLLVM.h"
+#include "mlir/Conversion/FuncToLLVM/ConvertFuncToLLVMPass.h"
+#include "mlir/Conversion/IndexToLLVM/IndexToLLVM.h"
+#include "mlir/Conversion/MathToLLVM/MathToLLVM.h"
+#include "mlir/Conversion/MemRefToLLVM/MemRefToLLVM.h"
+#include "mlir/Conversion/Passes.h"
+#include "mlir/Conversion/SCFToControlFlow/SCFToControlFlow.h"
+#include "mlir/Conversion/VectorToSCF/VectorToSCF.h"
+#include "mlir/Conversion/XeGPUToXeVM/XeGPUToXeVM.h"
+#include "mlir/Conversion/XeVMToLLVM/XeVMToLLVM.h"
+#include "mlir/Dialect/Func/IR/FuncOps.h"
+#include "mlir/Dialect/GPU/IR/GPUDialect.h"
+#include "mlir/Dialect/GPU/Pipelines/Passes.h"
+#include "mlir/Dialect/GPU/Transforms/Passes.h"
+#include "mlir/Dialect/LLVMIR/Transforms/RequestCWrappers.h"
+#include "mlir/Dialect/MemRef/Transforms/Passes.h"
+#include "mlir/Dialect/XeGPU/Transforms/Passes.h"
+#include "mlir/Pass/PassManager.h"
+#include "mlir/Pass/PassOptions.h"
+#include "mlir/Target/LLVM/XeVM/Target.h"
+#include "mlir/Transforms/Passes.h"
+
+using namespace mlir;
+
+namespace {
+//===----------------------------------------------------------------------===//
+// Common pipeline
+//===----------------------------------------------------------------------===//
+void buildCommonPassPipeline(
+ OpPassManager &pm, const mlir::gpu::GPUToXeVMPipelineOptions &options) {
+ // builtin.module scope passes
+ pm.addPass(createCSEPass());
+ {
+ GpuXeVMAttachTargetOptions xevmTargetOptions;
+ xevmTargetOptions.moduleMatcher = options.xevmModuleMatcher;
+ xevmTargetOptions.triple = options.zebinTriple;
+ xevmTargetOptions.chip = options.zebinChip;
+ xevmTargetOptions.optLevel = options.optLevel;
+ xevmTargetOptions.cmdOptions = options.cmdOptions;
+ pm.addPass(createGpuXeVMAttachTarget(xevmTargetOptions));
+ }
+}
+
+//===----------------------------------------------------------------------===//
+// GPUModule-specific stuff.
+//===----------------------------------------------------------------------===//
+void buildGpuPassPipeline(OpPassManager &pm,
+ const mlir::gpu::GPUToXeVMPipelineOptions &options) {
+ if (options.xegpuOpLevel == "workgroup") {
+ pm.addNestedPass<gpu::GPUModuleOp>(xegpu::createXeGPUWgToSgDistribute());
+ pm.addNestedPass<gpu::GPUModuleOp>(createCSEPass());
+ pm.addNestedPass<gpu::GPUModuleOp>(createLowerAffinePass());
+ pm.addNestedPass<gpu::GPUModuleOp>(xegpu::createXeGPUBlocking());
+ pm.addNestedPass<gpu::GPUModuleOp>(createCanonicalizerPass());
+ pm.addNestedPass<gpu::GPUModuleOp>(createCSEPass());
+ }
+ if (options.xegpuOpLevel == "subgroup" ||
+ options.xegpuOpLevel == "workgroup") {
+ pm.addNestedPass<gpu::GPUModuleOp>(xegpu::createXeGPUPropagateLayout());
+ pm.addNestedPass<gpu::GPUModuleOp>(xegpu::createXeGPUSubgroupDistribute());
+ pm.addNestedPass<gpu::GPUModuleOp>(createCanonicalizerPass());
+ pm.addNestedPass<gpu::GPUModuleOp>(createCSEPass());
+ pm.addNestedPass<gpu::GPUModuleOp>(createLoopInvariantCodeMotionPass());
+ pm.addNestedPass<gpu::GPUModuleOp>(createCSEPass());
+ pm.addNestedPass<gpu::GPUModuleOp>(xegpu::createXeGPUVectorLinearize());
+ }
+ pm.addNestedPass<gpu::GPUModuleOp>(createConvertXeGPUToXeVMPass());
+ {
+ ConvertGpuOpsToLLVMSPVOpsOptions gpuToLLVMSPVOptions;
+ gpuToLLVMSPVOptions.use64bitIndex = options.use64bitIndex;
+ pm.addNestedPass<gpu::GPUModuleOp>(
+ createConvertGpuOpsToLLVMSPVOps(gpuToLLVMSPVOptions));
+ }
+ pm.addNestedPass<gpu::GPUModuleOp>(createConvertXeVMToLLVMPass());
+ pm.addNestedPass<gpu::GPUModuleOp>(createCSEPass());
+}
+
+//===----------------------------------------------------------------------===//
+// Host Post-GPU pipeline
+//===----------------------------------------------------------------------===//
+void buildHostPostPipeline(OpPassManager &pm,
+ const mlir::gpu::GPUToXeVMPipelineOptions &options) {
+ pm.addNestedPass<func::FuncOp>(LLVM::createLLVMRequestCWrappersPass());
+ pm.addNestedPass<func::FuncOp>(createGpuAsyncRegionPass());
+ pm.addPass(createReconcileUnrealizedCastsPass());
+ pm.addPass(createConvertVectorToSCFPass());
+ pm.addPass(createSCFToControlFlowPass());
+ pm.addPass(memref::createExpandStridedMetadataPass());
+ pm.addPass(createFinalizeMemRefToLLVMConversionPass());
+ {
+ GpuToLLVMConversionPassOptions gpuToLLVMOptions;
+ gpuToLLVMOptions.hostBarePtrCallConv = options.hostBarePtrCallConv;
+ gpuToLLVMOptions.kernelBarePtrCallConv = options.kernelBarePtrCallConv;
+ pm.addPass(createGpuToLLVMConversionPass(gpuToLLVMOptions));
+ }
+ pm.addPass(createConvertToLLVMPass());
+ pm.addPass(createLowerAffinePass());
+ pm.addPass(createReconcileUnrealizedCastsPass());
+ // gpu-module-to-binary
+ {
+ GpuModuleToBinaryPassOptions gpuToModuleBinOptions;
+ gpuToModuleBinOptions.compilationTarget = options.binaryFormat;
+ gpuToModuleBinOptions.cmdOptions = options.cmdOptions;
+ pm.addPass(createGpuModuleToBinaryPass(gpuToModuleBinOptions));
+ }
+}
+} // namespace
+
+void mlir::gpu::buildLowerToXeVMPassPipeline(
+ OpPassManager &pm, const GPUToXeVMPipelineOptions &options) {
+ // Common pipelines
+ buildCommonPassPipeline(pm, options);
+
+ // GPUModule-specific stuff
+ buildGpuPassPipeline(pm, options);
+
+ // Host post-GPUModule-specific stuff
+ buildHostPostPipeline(pm, options);
+}
+
+void mlir::gpu::registerGPUToXeVMPipeline() {
+ PassPipelineRegistration<GPUToXeVMPipelineOptions>(
+ "gpu-lower-to-xevm-pipeline",
+ "The default GPU to XeVM lowering pipeline. It starts by lowering GPU "
+ "code to the "
+ "specified compilation target (default is fatbin) then lowers the host "
+ "code.",
+ buildLowerToXeVMPassPipeline);
+}
diff --git a/mlir/lib/RegisterAllPasses.cpp b/mlir/lib/RegisterAllPasses.cpp
index c67b24226ae45..dd413d2de8710 100644
--- a/mlir/lib/RegisterAllPasses.cpp
+++ b/mlir/lib/RegisterAllPasses.cpp
@@ -98,4 +98,5 @@ void mlir::registerAllPasses() {
sparse_tensor::registerSparseTensorPipelines();
tosa::registerTosaToLinalgPipelines();
gpu::registerGPUToNVVMPipeline();
+ gpu::registerGPUToXeVMPipeline();
}
diff --git a/mlir/test/Integration/Dialect/XeGPU/SG/simple_gemm.mlir b/mlir/test/Integration/Dialect/XeGPU/SG/simple_gemm.mlir
new file mode 100644
index 0000000000000..877edf47fcd15
--- /dev/null
+++ b/mlir/test/Integration/Dialect/XeGPU/SG/simple_gemm.mlir
@@ -0,0 +1,120 @@
+// RUN: mlir-opt %s --gpu-lower-to-xevm-pipeline="xegpu-op-level=subgroup" \
+// RUN: | mlir-runner \
+// RUN: --shared-libs=%mlir_levelzero_runtime \
+// RUN: --shared-libs=%mlir_runner_utils \
+// RUN: --entry-point-result=void \
+// RUN: | FileCheck %s
+
+module @gemm attributes {gpu.container_module} {
+ gpu.module @kernel {
+ gpu.func @simple_gemm(%a: memref<256x256xf16>, %b: memref<256x256xf16>, %c: memref<256x256xf32>) kernel {
+ %c0 = arith.constant 0 : index
+ %c1 = arith.constant 1 : index
+ %c8 = arith.constant 8 : index
+ %c16 = arith.constant 16 : index
+ %c32 = arith.constant 32 : index
+ %c256 = arith.constant 256 : index
+ %block_x = gpu.block_id x
+ %block_y = gpu.block_id y
+ %x_block_offset = arith.muli %block_x, %c8 : index
+ %y_block_offset = arith.muli %block_y, %c16 : index
+
+ %c_tdesc = xegpu.create_nd_tdesc %c : memref<256x256xf32> -> !xegpu.tensor_desc<8x16xf32>
+ %c_init_value = xegpu.load_nd %c_tdesc[%x_block_offset, %y_block_offset] : !xegpu.tensor_desc<8x16xf32> -> vector<8x16xf32>
+ %a_tdesc = xegpu.create_nd_tdesc %a : memref<256x256xf16> -> !xegpu.tensor_desc<8x16xf16>
+ %b_tdesc = xegpu.create_nd_tdesc %b : memref<256x256xf16> -> !xegpu.tensor_desc<16x16xf16>
+
+ %r = scf.for %k = %c0 to %c256 step %c16 iter_args(%arg_c = %c_init_value) -> (vector<8x16xf32>) {
+ %a_val = xegpu.load_nd %a_tdesc[%x_block_offset, %k] : !xegpu.tensor_desc<8x16xf16> -> vector<8x16xf16>
+ %b_val = xegpu.load_nd %b_tdesc[%k, %y_block_offset] : !xegpu.tensor_desc<16x16xf16> -> vector<16x16xf16>
+ %dpas = xegpu.dpas %a_val, %b_val, %arg_c : vector<8x16xf16>, vector<16x16xf16>, vector<8x16xf32> -> vector<8x16xf32>
+ scf.yield %dpas : vector<8x16xf32>
+ }
+ xegpu.store_nd %r, %c_tdesc[%x_block_offset, %y_block_offset] <{l1_hint = #xegpu.cache_hint<write_back>, l2_hint = #xegpu.cache_hint<uncached>}>: vector<8x16xf32>, !xegpu.tensor_desc<8x16xf32>
+ gpu.return
+ }
+ }
+
+ func.func @test(%a : memref<256x256xf16>, %b : memref<256x256xf16>, %c : memref<256x256xf32>) -> memref<256x256xf32> attributes {llvm.emit_c_interface} {
+ %c1 = arith.constant 1 : index
+ %c16 = arith.constant 16 : index
+ %c32 = arith.constant 32 : index
+ %memref_a = gpu.alloc () : memref<256x256xf16>
+ gpu.memcpy %memref_a, %a : memref<256x256xf16>, memref<256x256xf16>
+ %memref_b = gpu.alloc () : memref<256x256xf16>
+ gpu.memcpy %memref_b, %b : memref<256x256xf16>, memref<256x256xf16>
+ %memref_c = gpu.alloc () : memref<256x256xf32>
+ gpu.memcpy %memref_c, %c : memref<256x256xf32>, memref<256x256xf32>
+ gpu.launch_func @kernel::@simple_gemm blocks in (%c32, %c16, %c1) threads in (%c16, %c1, %c1) args(%memref_a : memref<256x256xf16>, %memref_b : memref<256x256xf16>, %memref_c : memref<256x256xf32>)
+ gpu.wait // Wait for the kernel to finish.
+ gpu.memcpy %c, %memref_c : memref<256x256xf32>, memref<256x256xf32>
+ gpu.dealloc %memref_a : memref<256x256xf16>
+ gpu.dealloc %memref_b : memref<256x256xf16>
+ gpu.dealloc %memref_c : memref<256x256xf32>
+ return %c : memref<256x256xf32>
+ }
+
+
+ func.func @main() attributes {llvm.emit_c_interface} {
+ %c0 = arith.constant 0 : index
+ %c1 = arith.constant 1 : index
+ %c1_f16 = arith.constant 1.0 : f16
+ %c2_f16 = arith.constant 2.0 : f16
+ %c256 = arith.constant 256 : index
+ %cf_0 = arith.constant 0.0 : f16
+ %cf_1 = arith.constant 1.0 : f16
+ %A = memref.alloc() : memref<256x256xf16>
+ %B = memref.alloc() : memref<256x256xf16>
+ %C = memref.alloc() : memref<256x256xf32>
+ %C_ref = memref.alloc() : memref<256x256xf32>
+ %c_gen_int = arith.constant 0 : i1
+ %cf_lower = arith.constant -0.5 : f32
+ %cf_upper = arith.constant 0.5 : f32
+ // Option 1: intialize matrix A ; A[i, j] = j
+ scf.for %i = %c0 to %c256 step %c1 {
+ scf.for %j = %c0 to %c256 step %c1 {
+ %t = index.castu %j : index to i16
+ %val = arith.uitofp %t : i16 to f16
+ memref.store %val, %A[%i, %j] : memref<256x256xf16>
+ }
+ }
+
+ // Initialize the B matrix
+ // Make matrix B an identity matrix
+ scf.for %i = %c0 to %c256 step %c1 {
+ scf.for %j = %c0 to %c256 step %c1 {
+ %i_i32 = index.castu %i : index to i32
+ %j_i32 = index.castu %j : index to i32
+ %i_j_same = arith.cmpi eq, %i_i32, %j_i32 : i32
+
+ scf.if %i_j_same {
+ memref.store %cf_1, %B[%i, %j] : memref<256x256xf16>
+ } else {
+ memref.store %cf_0, %B[%i, %j] : memref<256x256xf16>
+ }
+ }
+ }
+ // intialize matrix C and C_ref ; C[i, j] = 0
+ %c0_f32 = arith.constant 0.0 : f32
+ scf.for %i = %c0 to %c256 step %c1 {
+ scf.for %j = %c0 to %c256 step %c1 {
+ memref.store %c0_f32, %C[%i, %j] : memref<256x256xf32>
+ memref.store %c0_f32, %C_ref[%i, %j] : memref<256x256xf32>
+ }
+ }
+
+ // Run GPU.
+ %2 = call @test(%A, %B, %C) : (memref<256x256xf16>, memref<256x256xf16>, memref<256x256xf32>) -> memref<256x256xf32>
+ %cast_C = memref.cast %2 : memref<256x256xf32> to memref<*xf32>
+ // CHECK: Unranked Memref base@ = 0x{{[0-9a-f]+}}
+ // CHECK-COUNT-256: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255]
+ call @printMemrefF32(%cast_C) : (memref<*xf32>) -> ()
+
+ memref.dealloc %A : memref<256x256xf16>
+ memref.dealloc %B : memref<256x256xf16>
+ memref.dealloc %C : memref<256x256xf32>
+ memref.dealloc %C_ref : memref<256x256xf32>
+ return
+ }
+ func.func private @printMemrefF32(memref<*xf32>) attributes {llvm.emit_c_interface}
+}
diff --git a/mlir/test/Integration/Dialect/XeGPU/SIMT/simple_gemm.mlir b/mlir/test/Integration/Dialect/XeGPU/SIMT/simple_gemm.mlir
new file mode 100644
index 0000000000000..36b04791ee2dd
--- /dev/null
+++ b/mlir/test/Integration/Dialect/XeGPU/SIMT/simple_gemm.mlir
@@ -0,0 +1,121 @@
+// RUN: mlir-opt %s --gpu-lower-to-xevm-pipeline="xegpu-op-level=workitem" \
+// RUN: | mlir-runner \
+// RUN: --shared-libs=%mlir_levelzero_runtime \
+// RUN: --shared-libs=%mlir_runner_utils \
+// RUN: --entry-point-result=void \
+// RUN: | FileCheck %s
+
+module @gemm attributes {gpu.container_module} {
+ gpu.module @kernel {
+ gpu.func @simple_gemm(%a: memref<256x256xf16>, %b: memref<256x256xf16>, %c: memref<256x256xf32>) kernel {
+ %c0 = arith.constant 0 : index
+ %c1 = arith.constant 1 : index
+ %c8 = arith.constant 8 : index
+ %c16 = arith.constant 16 : index
+ %c32 = arith.constant 32 : index
+ %c256 = arith.constant 256 : index
+ %b...
[truncated]
|
Jianhui-Li
reviewed
Oct 1, 2025
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| // RUN: mlir-opt %s --gpu-lower-to-xevm-pipeline="xegpu-op-level=workitem" \ | |||
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Please change the directory and pipeline parameter to "lane", instead of SIMT and workitem, to be consistent with XeGPU layout definition.
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Thanks a lot, Jianhui. Changed it now.
Change `workitem` to `lane`.
Rename `SIMT` test folder to `LANE`.
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It's the default GPU to XeVM lowering pipeline. It starts by lowering GPU code to the specified compilation target (default is fatbin), then lowers the host code.
If XeGPU ops are used, it expects the MLIR code to have XeGPU ops already embedded in gpu code.