diff --git a/mlir/include/mlir/Dialect/GPU/Pipelines/Passes.h b/mlir/include/mlir/Dialect/GPU/Pipelines/Passes.h
index 035235fc7174a..c545517ec7739 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 | lane
+  PassOptions::Option<std::string> xegpuOpLevel{
+      *this, "xegpu-op-level",
+      llvm::cl::desc("Granularity of XeGPU operations to target: workgroup | "
+                     "subgroup | lane"),
+      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/LANE/simple_gemm.mlir b/mlir/test/Integration/Dialect/XeGPU/LANE/simple_gemm.mlir
new file mode 100644
index 0000000000000..ffe29ef35a5c9
--- /dev/null
+++ b/mlir/test/Integration/Dialect/XeGPU/LANE/simple_gemm.mlir
@@ -0,0 +1,121 @@
+// RUN: mlir-opt %s --gpu-lower-to-xevm-pipeline="xegpu-op-level=lane" \
+// 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<8xf32>
+      %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<8xf32>) {
+        %a_val = xegpu.load_nd %a_tdesc[%x_block_offset, %k] : !xegpu.tensor_desc<8x16xf16> -> vector<8xf16>
+        %b_val = xegpu.load_nd %b_tdesc[%k, %y_block_offset] : !xegpu.tensor_desc<16x16xf16> -> vector<16xf16>
+        %dpas = xegpu.dpas %a_val, %b_val, %arg_c : vector<8xf16>, vector<16xf16>, vector<8xf32> -> vector<8xf32>
+        scf.yield %dpas : vector<8xf32>
+      }
+      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<8xf32>, !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
+
+    // Initialize 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>
+        }
+      }
+    }
+
+    // Initialize 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 version.
+    %2 = call @test(%A, %B, %C) : (memref<256x256xf16>, memref<256x256xf16>, memref<256x256xf32>) -> memref<256x256xf32>
+    %gpu_result_cast = 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(%gpu_result_cast) : (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/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/WG/simple_gemm.mlir b/mlir/test/Integration/Dialect/XeGPU/WG/simple_gemm.mlir
new file mode 100644
index 0000000000000..fdc24c02f9d98
--- /dev/null
+++ b/mlir/test/Integration/Dialect/XeGPU/WG/simple_gemm.mlir
@@ -0,0 +1,149 @@
+// RUN: mlir-opt %s --gpu-lower-to-xevm-pipeline="xegpu-op-level=workgroup" \
+// RUN: | mlir-runner \
+// RUN:   --shared-libs=%mlir_levelzero_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
+// RUN:   --entry-point-result=void \
+// RUN: | FileCheck %s
+
+#a = #xegpu.layout<sg_layout = [8, 4], sg_data = [32, 32], inst_data = [8, 16]>
+#b = #xegpu.layout<sg_layout = [8, 4], sg_data = [32, 64], inst_data = [16, 16]>
+#c = #xegpu.layout<sg_layout = [8, 4], sg_data = [32, 64], inst_data = [8, 16]>
+#a_prefetch = #xegpu.layout<sg_layout = [32, 1], sg_data = [8, 32], inst_data = [8, 16]>
+#b_prefetch = #xegpu.layout<sg_layout = [4, 8], sg_data = [8, 32], inst_data = [8, 16]>
+module @gemm attributes {gpu.container_module} {
+  func.func @test(%A: memref<256x256xf16>, %B: memref<256x256xf16>, %C: memref<256x256xf32>) -> memref<256x256xf32> attributes {llvm.emit_c_interface} {
+    %c1 = arith.constant 1 : index
+    %c4 = arith.constant 4 : index
+    %c8 = arith.constant 8 : index
+    %c16 = arith.constant 16 : index
+    %c32 = arith.constant 32 : index
+    %c64 = arith.constant 64 : index
+    %c128 = arith.constant 128 : index
+    %c512 = arith.constant 512 : index
+    %A_gpu = gpu.alloc () : memref<256x256xf16>
+    gpu.memcpy %A_gpu, %A : memref<256x256xf16>, memref<256x256xf16>
+    %B_gpu = gpu.alloc () : memref<256x256xf16>
+    gpu.memcpy %B_gpu, %B : memref<256x256xf16>, memref<256x256xf16>
+    %C_gpu = gpu.alloc () : memref<256x256xf32>
+    gpu.memcpy %C_gpu, %C : memref<256x256xf32>, memref<256x256xf32>
+    // NOTE: Here we can't use [8, 64] wi threads following the SG thread layout of [8, 4]. Because runtime will linearize the x dimension first (we need y dimension to be linearized first).
+    // So just use linearized thread layout of [512, 1] wi threads.
+    gpu.launch_func  @test_kernel::@test_kernel blocks in (%c1, %c1, %c1) threads in (%c512, %c1, %c1) args(%A_gpu : memref<256x256xf16>, %B_gpu : memref<256x256xf16>, %C_gpu : memref<256x256xf32>)
+    gpu.wait // Wait for the kernel to finish.
+    gpu.memcpy %C, %C_gpu : memref<256x256xf32>, memref<256x256xf32>
+    gpu.dealloc %A_gpu : memref<256x256xf16>
+    gpu.dealloc %B_gpu : memref<256x256xf16>
+    gpu.dealloc %C_gpu : memref<256x256xf32>
+    return %C : memref<256x256xf32>
+  }
+
+  gpu.module @test_kernel   {
+    gpu.func @test_kernel(%A: memref<256x256xf16>, %B: memref<256x256xf16>, %C: memref<256x256xf32>) kernel  {
+      %c0 = arith.constant 0 : index
+      %c1 = arith.constant 1 : index
+      %c32 = arith.constant 32 : index
+      %c64 = arith.constant 64 : index
+      %c96 = arith.constant 96 : index
+      %c256 = arith.constant 256 : index
+      %c4096 = arith.constant 4096 : index
+      %block_id_x = gpu.block_id x
+      %block_id_y = gpu.block_id y
+      %m = arith.muli %block_id_x, %c256 : index
+      %n = arith.muli %block_id_y, %c256 : index
+      %c_tdesc = xegpu.create_nd_tdesc %C : memref<256x256xf32> -> !xegpu.tensor_desc<256x256xf32, #c>
+      %c_init_value = xegpu.load_nd %c_tdesc[%m, %n] : !xegpu.tensor_desc<256x256xf32, #c> -> vector<256x256xf32>
+      %a_tdesc = xegpu.create_nd_tdesc %A : memref<256x256xf16> -> !xegpu.tensor_desc<256x32xf16, #a>
+      %b_tdesc = xegpu.create_nd_tdesc %B : memref<256x256xf16> -> !xegpu.tensor_desc<32x256xf16, #b>
+      // Prefetch A 3 times.
+      %a_prefetch_tdesc = xegpu.create_nd_tdesc %A : memref<256x256xf16> -> !xegpu.tensor_desc<256x32xf16, #a_prefetch>
+      xegpu.prefetch_nd %a_prefetch_tdesc[%m, %c0] : !xegpu.tensor_desc<256x32xf16, #a_prefetch>
+      xegpu.prefetch_nd %a_prefetch_tdesc[%m, %c32] : !xegpu.tensor_desc<256x32xf16, #a_prefetch>
+      xegpu.prefetch_nd %a_prefetch_tdesc[%m, %c64] : !xegpu.tensor_desc<256x32xf16, #a_prefetch>
+       // Prefetch B 3 times.
+      %b_prefetch_tdesc = xegpu.create_nd_tdesc %B : memref<256x256xf16> -> !xegpu.tensor_desc<32x256xf16, #b_prefetch>
+      xegpu.prefetch_nd %b_prefetch_tdesc[%c0, %n] : !xegpu.tensor_desc<32x256xf16, #b_prefetch>
+      xegpu.prefetch_nd %b_prefetch_tdesc[%c32, %n] : !xegpu.tensor_desc<32x256xf16, #b_prefetch>
+      xegpu.prefetch_nd %b_prefetch_tdesc[%c64, %n] : !xegpu.tensor_desc<32x256xf16, #b_prefetch>
+
+      %out = scf.for %k = %c0 to %c256 step %c32
+        iter_args(%c_value = %c_init_value)
+        -> (vector<256x256xf32>) {
+        %a_value = xegpu.load_nd %a_tdesc[%m, %k]  : !xegpu.tensor_desc<256x32xf16, #a> -> vector<256x32xf16>
+        %b_value = xegpu.load_nd %b_tdesc[%k, %n] : !xegpu.tensor_desc<32x256xf16, #b> -> vector<32x256xf16>
+        // Prefetch next tiles.
+        %prefetch_offset = arith.addi %k, %c96 : index
+        xegpu.prefetch_nd %a_prefetch_tdesc[%m, %prefetch_offset] : !xegpu.tensor_desc<256x32xf16, #a_prefetch>
+        xegpu.prefetch_nd %b_prefetch_tdesc[%prefetch_offset, %n] : !xegpu.tensor_desc<32x256xf16, #b_prefetch>
+        %c_new_value = xegpu.dpas %a_value, %b_value, %c_value {layout_result_0 = #c}
+          : vector<256x32xf16>, vector<32x256xf16>, vector<256x256xf32> -> vector<256x256xf32>
+        scf.yield %c_new_value : vector<256x256xf32>
+      }
+      xegpu.store_nd %out, %c_tdesc[%m, %n] : vector<256x256xf32>, !xegpu.tensor_desc<256x256xf32, #c>
+      gpu.return
+    }
+  }
+
+  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
+    // 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>
+        }
+      }
+    }
+
+    // Initialize 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 version.
+    %2 = call @test(%A, %B, %C) : (memref<256x256xf16>, memref<256x256xf16>, memref<256x256xf32>) -> memref<256x256xf32>
+    %gpu_result_cast = 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(%gpu_result_cast) : (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}
+}