Merge remote-tracking branch 'origin/develop' into aosewski/hotloop

CMakeLists.txt

@@ -103,7 +103,7 @@ if(DPP_KERNELS)
 endif()
 option(CK_USE_CODEGEN "Enable codegen library" OFF)
 if(CK_USE_CODEGEN)
-    add_definitions(-DCK_USE_CODEGEN)
+   add_definitions(-DCK_USE_CODEGEN)
 endif()
 
 option(CK_TIME_KERNEL "Enable kernel time tracking" ON)
@@ -196,17 +196,20 @@ if (SUPPORTED_GPU_TARGETS MATCHES "gfx9")
     add_definitions(-DCK_USE_XDL)
     set(CK_USE_XDL "ON")
 endif()
-if (SUPPORTED_GPU_TARGETS MATCHES "gfx94")
+if (SUPPORTED_GPU_TARGETS MATCHES "gfx94" OR SUPPORTED_GPU_TARGETS MATCHES "gfx95")
     message("Enabling FP8 gemms on native architectures")
     add_definitions(-DCK_USE_GFX94)
     set(CK_USE_GFX94 "ON")
 endif()
+if (SUPPORTED_GPU_TARGETS MATCHES "gfx95")
+	add_definitions(-DCK_USE_AMD_MFMA_GFX950)
+endif()
 if (SUPPORTED_GPU_TARGETS MATCHES "gfx11" OR SUPPORTED_GPU_TARGETS MATCHES "gfx12")
     message("Enabling WMMA instances")
     add_definitions(-DCK_USE_WMMA)
     set(CK_USE_WMMA "ON")
 endif()
-if (SUPPORTED_GPU_TARGETS MATCHES "gfx12")
+if (SUPPORTED_GPU_TARGETS MATCHES "gfx12" OR SUPPORTED_GPU_TARGETS MATCHES "gfx950")
     add_definitions(-DCK_USE_OCP_FP8)
     set(CK_USE_OCP_FP8 "ON")
 endif()
@@ -214,6 +217,10 @@ if (SUPPORTED_GPU_TARGETS MATCHES "gfx90a" OR SUPPORTED_GPU_TARGETS MATCHES "gfx
     add_definitions(-DCK_USE_FNUZ_FP8)
     set(CK_USE_FNUZ_FP8 "ON")
 endif()
+if (SUPPORTED_GPU_TARGETS MATCHES "gfx950")
+    add_definitions(-DCK_USE_NATIVE_MX_SUPPORT)
+    set(CK_USE_NATIVE_MX_SUPPORT "ON")
+endif()
 
 option(CK_USE_FP8_ON_UNSUPPORTED_ARCH "Enable FP8 GEMM instances on older architectures" OFF)
 if(CK_USE_FP8_ON_UNSUPPORTED_ARCH AND (SUPPORTED_GPU_TARGETS MATCHES "gfx90a" OR SUPPORTED_GPU_TARGETS MATCHES "gfx908"))

client_example/01_gemm/README.md

+[Back to supported operations](../../../include/ck/README.md)
+# Composable Kernel GEMM
+
+## GEMM
+General matrix multiplications operation. In CK GEMM operation is called as `DeviceGemm` and requires following types as template parameters:
+
+* **ALayout** - A matrix layout (RowMajor/ColumnMajor).
+* **BLayout** - B matrix layout (RowMajor/ColumnMajor).
+* **CLayout** - B matrix layout (RowMajor/ColumnMajor).
+* **ADataType** - A matrix data type.
+* **BDataType** - B matrix data type.
+* **CDataType** - B matrix data type.
+* **AElementwiseOperation** - Fused operation on tensor A before GEMM.
+* **BElementwiseOperation** - Fused operation on tensor B before GEMM.
+* **CElementwiseOperation** - Fused operation on tensor C after GEMM.
+
+For matrices with large K dimension `DeviceGemmSplitK` implementation is available. This implementation allows user to split K dimension between work groups. This implementation uses `AtomicAdd` operation on global memory, thus need to zero-out output buffer for correct results.
+
+For fused operations with additional tensor there are `DeviceGemmMultipleABD` or `DeviceGemmMultipleD` operation which require following parameters:
+* **DsLayout** - layouts for additional tensors for fused operations.
+* **DsDataType** - data types for additional tensors for fused operations.
+
+For `DeviceGemmMultipleABD` **ALayout**, **BLayout**, **ADataType** and **BDataType** user should pass a tuple.
+
+List of the device operations in CK:
+
+* **DeviceGemmDl** - Device operation with DL instructions.
+* **DeviceGemmDpp** - Device operation with DL instructions with DPP instructions during data load.
+* **DeviceGemmWmma_CShuffle** - Device operation with WMMA instructions with CShuffle optimization for more optimized data store.
+* **DeviceGemm_Xdl_CShuffle_LdsDirectLoad** - Device operation with XDL instructions and CShuffle optimization for more optimized data store and direct load from global memory to shared memory.
+* **DeviceGemm_Xdl_CShuffle** - Device operation with XDL instructions with CShuffle optimization for more optimized data store.
+* **DeviceGemm_Xdl_CShuffleV2** - Device operation with XDL instructions with CShuffle optimization for more optimized data store. GEMM pipeline has been optimized compared to **DeviceGemm_Xdl_CShuffle**.
+* **DeviceGemmXdlSkipBLds** - Device operation with XDL instructions. Load to shared memory has been skiped for B matrix.
+* **DeviceGemm_Xdl_WaveletModel_CShuffle** - Device operation with XDL instructions with CShuffle optimization for more optimized data store. Producer and consumer scheme cooperation between waves in workgroup.
+* **DeviceGemmXdl** - Device operation with XDL instructions.
+
+Table of supported cases by instance factory with XDL instruction for Row/Row/Row, Row/Column/Row, Column/Row/Row or Column/Column/Row:
+
+|       |Is supported|
+|-------|---|
+|bf16|✓|
+|fp16|✓|
+|fp32|✓|
+|int8|✓|
+|fp8 |✓|
+
+Table of supported cases by instance factory with WMMA instruction for Row/Row/Row, Row/Column/Row, Column/Row/Row or Column/Column/Row:
+
+|       |Is supported|
+|-------|---|
+|bf16|✓|
+|fp16|✓|
+|fp32|✗|
+|int8|✓|
+|fp8 |✗|
+
+Table of supported cases by instance factory with DL instruction for Row/Row/Row, Row/Column/Row, Column/Row/Row or Column/Column/Row:
+
+|       |Is supported|
+|-------|---|
+|bf16|✗|
+|fp16|✓|
+|fp32|✓|
+|int8|✓|
+|fp8 |✗|
+
+Table of supported cases by instance factory with fused output elementwise operation:
+
+* **B Matrix Multiply + Add + Gelu** - bf16 (int8 for B matrix)
+* **B Matrix Multiply + Add** - bf16 (int8 for B matrix)
+* **B Matrix Multiply + Gelu** - bf16 (int8 for B matrix)
+* **B Matrix Multiply** - bf16 (int8 for B matrix)
+
+* **Add + Add + Gelu** - fp16
+* **Add + Gelu** - fp16, bf16 (int8 for B matrix) for Row/Column/Row
+* **Multiply** - fp16
+* **Add + Multiply** - fp16
+* **Add + Relu** - fp16 (int8 for B matrix)  for Row/Column/Row, bf16 (int8 for B matrix) for Row/Column/Row
+* **Add + Silu** - fp16 (int8 for B matrix)  for Row/Column/Row, bf16 (int8 for B matrix) for Row/Column/Row
+* **Add** - fp16 (int8 for B matrix)  for Row/Column/Row, bf16 (int8 for B matrix) for Row/Column/Row
+* **Bilinear** - fp16, int8
+* **Gelu** - fp16
+* **Multiply + Add** - fp16 for Row/Column/Row and Row/Row/Row, fp16 (int8 for B matrix, fp32 for Bias) for Row/Column/Row and Row/Row/Row, 
+* **Quantization** - int8
+
+## GEMM V2 (Universal GEMM)
+General matrix multiplications operation optimized for MI300 series. Operation is called as `DeviceGemmV2` and requires following types as template parameters:
+
+* **ALayout** - A matrix layout (RowMajor/ColumnMajor).
+* **BLayout** - B matrix layout (RowMajor/ColumnMajor).
+* **CLayout** - B matrix layout (RowMajor/ColumnMajor).
+* **ADataType** - A matrix data type.
+* **BDataType** - B matrix data type.
+* **CDataType** - B matrix data type.
+* **AElementwiseOperation** - Fused operation on tensor A before GEMM.
+* **BElementwiseOperation** - Fused operation on tensor B before GEMM.
+* **CElementwiseOperation** - Fused operation on tensor C after GEMM.
+
+This implementation allows user to split K dimension between work groups. This implementation requires AtomicAdd operation on global memory (output buffer must be set to zeroes if splitK parameter is larger than one).
+
+List of the device operations for in CK:
+
+* **DeviceGemm_Xdl_CShuffleV3** - Device operation with XDL instructions with CShuffle optimization for more optimized data store.
+* **DeviceGemm_Xdl_CShuffleV3R1** - Device operation with XDL instructions with CShuffle optimization for more optimized data store. This implementation perform reduction on splitted K dimension after GEMM instead of AtomicAdd instruction. 
+
+Table of supported cases by instance factory with XDL instruction for Row/Row/Row, Row/Column/Row, Column/Row/Row or Column/Column/Row:
+
+|       |Is supported|
+|-------|---|
+|bf16|✓|
+|fp16|✓|
+|fp32|✗|
+|int8|✗|
+|fp8 (C bf16)|✓|
+|fp16 (A fp8)|✓|
+|fp16 (B fp8)|✓|
+
+## Others
+
+* **DeviceGemm_dequantB** - GEMM with dequantization (implemented with WMMA instructions).
+* **DeviceGemmMultipleD_ABScale** - GEMM with scale for A and B matrix.
+* **DeviceGemmMultipleDLayernorm** - GEMM fused with layernorm.
+* **DeviceGemmMultipleDMultipleR** - GEMM fused with reductions and custom global reductions operators.
+* **DeviceGemmReduce** - GEMM fused with reduction.
+* **DeviceGemm_Streamk_V2** - GEMM stream K implementation. Implementation allows to use reduction instead of AtomicAdd.
+* **DeviceGemmStreamK** - GEMM stream K implementation using AtomicAdd.

client_example/07_grouped_convnd_fwd/README.md

+[Back to supported operations](../../../include/ck/README.md)
+# Composable Kernel Grouped Convolution
+
+## Grouped Convolution Forward
+Grouped convolution operation for 1D, 2D or 3D spatial dimensions. Convolution utilizes GEMM kernel after tensor coordinate transform. In CK Grouped Convolution Forward operation is called as `DeviceGroupedConvFwdMultipleABD` and requires following types as template parameters:
+
+* **NumDimSpatial** - number of spatial dimensions (1D, 2D, 3D).
+* **InLayout** - input layout (NHWGC, GNHWC, NGCHW).
+* **WeiLayout** - weight layout (GKYXC).
+* **DsLayout** - layouts for additional tensors for fused operations.
+* **OutLayout** - output layout (NHWGK, GNHWK, NGKHW).
+* **ADataType** - input data type. Pass tuple if there is fused operation with input.
+* **BDataType** - weight data type. Pass tuple if there is fused operation with weight.
+* **DsDataType** - data types for additional tensors for fused operations.
+* **EDataType** - Output data type.
+* **AElementwiseOperation** - fused operation on tensor A (input).
+* **BElementwiseOperation** - fused operation on tensor B (weight).
+* **CDEElementwiseOperation** - fused operation on tensor C (output).
+* **AComputeType** - compute data type of tensor A for mfma instruction (ADataType by default).
+* **BComputeType** - compute data type of tensor B for mfma instruction (AComputeType by default).
+
+Grouped convolution forward support tensors larger than 2GB.
+
+List of the device operations for grouped convolution forward in CK:
+
+* **DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle_V3** - Device operation with XDL instructions. Optimized for AMD Instinct MI300 series.
+* **DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle** - Device operation with XDL instructions and support of fused operations to input, weight and output.
+* **DeviceGroupedConvFwdMultipleD_Wmma_CShuffle** - Device operation with WMMA instructions.
+* **DeviceGroupedConvFwdDlMultipleD_NHWC_KYXC_NHWK** - Device operation with DL instructions.
+
+Table of supported cases by instance factory with XDL instruction:
+
+|       |NHWGC/GKYXC/NHWGK|NGCHW/GKYXC/NGKHW|GNHWC/GKYXC/GNHWK|
+|-------|---|---|---|
+|bf16 |2D, 3D|2D|1D, 2D, 3D|
+|fp16 |2D, 3D|2D|1D, 2D, 3D|
+|fp32 |2D, 3D|2D|1D, 2D, 3D|
+|int8 |2D, 3D|2D|1D, 3D|
+|fp8  |3D|✗|✗|
+|bf8  |3D|✗|✗|
+
+Table of supported cases by instance factory with WMMA instruction:
+
+|       |NHWGC/GKYXC/NHWGK|NGCHW/GKYXC/NGKHW|GNHWC/GKYXC/GNHWK|
+|-------|---|---|---|
+|fp16 |2D, 3D|✗|2D, 3D|
+|int8 |2D, 3D|✗|2D, 3D|
+
+Table of supported cases by instance factory with DL instruction:
+
+|       |NHWGC/GKYXC/NHWGK|NGCHW/GKYXC/NGKHW|GNHWC/GKYXC/GNHWK|
+|-------|---|---|---|
+|bf16 |✗|✗|2D|
+|fp16 |✗|✗|2D|
+|fp32 |✗|✗|2D|
+|int8 |✗|✗|2D|
+
+Table of supported cases by instance factory with fused elementwise operation:
+
+* **Dynamic elementwise operation** - 2D/3D, NHWGC, bf16/fp16/fp32/int8
+* **Bilinear** - 3D, NHWGC, bf16/fp16/fp32/int8
+* **ConvInvScale** - 3D, NHWGC, fp8
+* **ConvScale** - 3D, NHWGC, fp8/bf8
+* **ConvScale + Add** - 3D, NHWGC, fp8
+* **ConvScale + Relu** - 3D, NHWGC, fp8
+* **Scale** - 3D, NHWGC, bf16/fp16/fp32/int8
+* **Scale + Add (for A and B)** - 3D, NHWGC, bf16/fp16/fp32/int8
+* **Scale + Add + Scale + Add + Relu** - 3D, NHWGC, bf16/fp16/fp32/int8

client_example/10_grouped_convnd_bwd_data/README.md

+[Back to supported operations](../../../include/ck/README.md)
+# Composable Kernel Grouped Convolution
+
+## Grouped Convolution Backward Data
+
+Grouped convolution operation for 1D, 2D or 3D spatial dimensions. Convolution utilizes GEMM kernel after tensor coordinate transform. In CK Grouped Convolution Backward Data operation is called as `DeviceGroupedConvBwdDataMultipleD` and requires following types as template parameters:
+
+* **NumDimSpatial** - number of spatial dimensions (1D, 2D, 3D).
+* **ALayout** - output layout (NHWGK, GNHWK, NGKHW).
+* **BLayout** - weight layout (GKYXC).
+* **DsLayout** - layouts for additional tensors for fused operations.
+* **ELayout** - input layout (NHWGC, GNHWC, NGCHW).
+* **ADataType** - output data type.
+* **BDataType** - weight data type.
+* **DsDataType** - data types for additional tensors for fused operations.
+* **EDataType** - input data type.
+* **AElementwiseOperation** - fused operation on tensor A (output).
+* **BElementwiseOperation** - fused operation on tensor B (weight).
+* **CDEElementwiseOperation** - fused operation on tensor C (input).
+* **AComputeType** - compute data type of tensor A for mfma instruction (ADataType by default).
+* **BComputeType** - compute data type of tensor B for mfma instruction (AComputeType by default).
+
+Grouped convolution backward data supports tensors larger than 2GB (except when image is larger than 2GB).
+
+List of the device operations for grouped convolution backward data in CK:
+
+* **DeviceGroupedConvBwdDataMultipleD_Xdl_CShuffle_v1** - Device operation with XDL instructions and support of fused operations to input.
+* **DeviceGroupedConvBwdDataMultipleD_Wmma_CShuffle** - Device operation with WMMA instructions.
+
+Table of supported cases by instance factory with XDL instruction:
+
+|       |NHWGC/GKYXC/NHWGK|NGCHW/GKYXC/NGKHW|GNHWC/GKYXC/GNHWK|
+|-------|---|---|---|
+|bf16|2D, 3D|✗|2D, 3D|
+|fp16 |2D, 3D|✗|2D, 3D|
+|fp32  |2D, 3D|✗|2D, 3D|
+
+Table of supported cases by instance factory with WMMA instruction:
+
+|       |NHWGC/GKYXC/NHWGK|NGCHW/GKYXC/NGKHW|GNHWC/GKYXC/GNHWK|
+|-------|---|---|---|
+|fp16 |2D, 3D|✗|2D, 3D|
+|int8 |2D, 3D|✗|2D, 3D|
+
+Table of supported cases by instance factory with fused elementwise operation:
+
+* **Bilinear** - 3D, NHWGC, bf16/fp16/fp32
+* **Scale** - 3D, NHWGC, bf16/fp16/fp32

client_example/11_grouped_conv_bwd_weight/README.md

+[Back to supported operations](../../../include/ck/README.md)
+# Composable Kernel Grouped Convolution
+
+## Grouped Convolution Backward Weight
+
+Grouped convolution operation for 1D, 2D or 3D spatial dimensions. Convolution utilizes GEMM kernel after tensor coordinate transform. Backward weight version uses splitK feature (due to large GEMM K dimension). In CK Grouped Convolution Backward Weight operation is called as `DeviceGroupedConvBwdWeight` and requires following types as template parameters:
+
+* **NumDimSpatial** - number of spatial dimensions (1D, 2D, 3D).
+* **InLayout** - input layout (NHWGC, GNHWC, NGCHW).
+* **WeiLayout** - weight layout (GKYXC).
+* **OutLayout** - output layout (NHWGK, GNHWK, NGKHW).
+* **InDataType** - input data type.
+* **WeiDataType** - weight data type.
+* **OutDataType** - output data type.
+* **InElementwiseOperation** - fused operation on tensor input.
+* **WeiElementwiseOperation** - fused operation on tensor weight.
+* **OutElementwiseOperation** - fused operation on tensor output.
+* **ComputeTypeA** - compute data type of tensor A for mfma instruction (ADataType by default).
+* **ComputeTypeB** - compute data type of tensor B for mfma instruction (ComputeTypeA by default).
+
+For fused operations with additional tensor there is `DeviceGroupedConvBwdWeightMultipleD` operation which requires following parameters:
+* **DsLayout** - layouts for additional tensors for fused operations.
+* **DsDataType** - data types for additional tensors for fused operations.
+
+Grouped convolution backward weight doesn't supports tensors larger than 2GB.
+
+List of the device operations for grouped convolution backward weight in CK:
+
+* **DeviceGroupedConvBwdWeight_Xdl_CShuffle** - Device operation with XDL instructions.
+* **DeviceGroupedConvBwdWeightTwoStage_Xdl_CShuffle** - Device operation with XDL instructions. Optimized for small C or K.
+* **DeviceGroupedConvBwdWeight_Wmma_CShuffle** - Device operation with WMMA instructions.
+* **DeviceGroupedConvBwdWeightMultipleD_Xdl_CShuffle** - Device operation with XDL instructions and support of fused operations to output.
+* **DeviceGroupedConvBwdWeight_Dl** - Device operation with DL instructions.
+
+Table of supported cases by instance factory with XDL instruction:
+
+|       |NHWGC/GKYXC/NHWGK|NGCHW/GKYXC/NGKHW|GNHWC/GKYXC/GNHWK|
+|-------|---|---|---|
+|bf16|2D, 3D|✗|✗|
+|bf16(fp32 for weight)|2D, 3D|✗|1D, 2D, 3D|
+|fp16 |2D, 3D|✗|1D, 2D, 3D|
+|fp32  |2D, 3D|✗|1D, 2D, 3D|
+
+Table of supported cases by instance factory with WMMA instruction:
+
+|       |NHWGC/GKYXC/NHWGK|NGCHW/GKYXC/NGKHW|GNHWC/GKYXC/GNHWK|
+|-------|---|---|---|
+|fp16 |3D|✗|3D|
+|int8 |3D|✗|3D|
+
+Table of supported cases by instance factory with DL instruction:
+
+|       |NHWGC/GKYXC/NHWGK|NGCHW/GKYXC/NGKHW|GNHWC/GKYXC/GNHWK|
+|-------|---|---|---|
+|bf16(fp32 for weight)|1D, 2D, 3D|✗|1D, 2D, 3D|
+|fp16 |1D, 2D, 3D|✗|1D, 2D, 3D|
+|fp32  |1D, 2D, 3D|✗|1D, 2D, 3D|
+
+Table of supported cases by instance factory with fused elementwise operation:
+
+* **Bilinear** - 3D, NHWGC, bf16(fp32 for weight)/fp16/fp32
+* **Scale** - 3D, NHWGC, bf16(fp32 for weight)/fp16/fp32

client_example/CMakeLists.txt

@@ -56,7 +56,7 @@ if (GPU_TARGETS)
         add_definitions(-DCK_USE_WMMA)
         set(CK_USE_WMMA "ON")
     endif()
-    if (GPU_TARGETS MATCHES "gfx12")
+    if (GPU_TARGETS MATCHES "gfx12" OR GPU_TARGETS MATCHES "gfx950")
         add_definitions(-DCK_USE_OCP_FP8)
         set(CK_USE_OCP_FP8 "ON")
     endif()

codegen/driver/main.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
 
 #include <functional>
 #include <iostream>

codegen/src/headers.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
+
 #include "ck/host/headers.hpp"
 #include "ck_headers.hpp"
 

codegen/src/types.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
+
 #include "ck/host/types.hpp"
 #include "ck/host/stringutils.hpp"
 #include <algorithm>

codegen/test/gemm_multiple_d.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
+
 #include "ck/host/device_gemm_multiple_d/problem.hpp"
 #include "ck/host/device_gemm_multiple_d/operation.hpp"
 #include "ck/host/headers.hpp"

codegen/test/grouped_conv_fwd_multiple_d_v1.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
+
 #include "ck/host/device_grouped_conv_fwd_multiple_d/conv_fwd_op.hpp"
 #include "ck/host/device_grouped_conv_fwd_multiple_d/conv_fwd_problem.hpp"
 #include "ck/host/headers.hpp"

codegen/test/grouped_conv_fwd_multiple_d_v2.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
+
 #include "ck/host/device_grouped_conv_fwd_multiple_d/conv_fwd_op.hpp"
 #include "ck/host/device_grouped_conv_fwd_multiple_d/conv_fwd_problem.hpp"
 #include "ck/host/headers.hpp"

codegen/test/grouped_conv_fwd_multiple_d_v3.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
+
 #include "ck/host/device_grouped_conv_fwd_multiple_d/conv_fwd_op.hpp"
 #include "ck/host/device_grouped_conv_fwd_multiple_d/conv_fwd_problem.hpp"
 #include "ck/host/headers.hpp"

codegen/test/grouped_conv_fwd_multiple_d_v4.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
+
 #include "ck/host/device_grouped_conv_fwd_multiple_d/conv_fwd_op.hpp"
 #include "ck/host/device_grouped_conv_fwd_multiple_d/conv_fwd_problem.hpp"
 #include "ck/host/headers.hpp"

codegen/test/include/common.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
+
 #pragma once
 #include <algorithm>
 #include <cmath>

codegen/test/rtc/include/rtc/compile_kernel.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
+
 #ifndef GUARD_HOST_TEST_RTC_INCLUDE_RTC_COMPILE_KERNEL
 #define GUARD_HOST_TEST_RTC_INCLUDE_RTC_COMPILE_KERNEL
 

codegen/test/rtc/include/rtc/hip.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
+
 #ifndef GUARD_HOST_TEST_RTC_INCLUDE_RTC_HIP
 #define GUARD_HOST_TEST_RTC_INCLUDE_RTC_HIP
 
 #include <hip/hip_runtime_api.h>
 #include <memory>
-#include <string>
 #include <stdexcept>
+#include <string>
 
 namespace rtc {
 

codegen/test/rtc/include/rtc/kernel.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
+
 #ifndef GUARD_HOST_TEST_RTC_INCLUDE_RTC_KERNEL
 #define GUARD_HOST_TEST_RTC_INCLUDE_RTC_KERNEL
 

codegen/test/rtc/include/rtc/manage_ptr.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
+
 #ifndef GUARD_HOST_TEST_RTC_INCLUDE_RTC_MANAGE_POINTER
 #define GUARD_HOST_TEST_RTC_INCLUDE_RTC_MANAGE_POINTER
 

codegen/test/rtc/include/rtc/tmp_dir.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
+
 #ifndef GUARD_HOST_TEST_RTC_INCLUDE_RTC_TMP_DIR
 #define GUARD_HOST_TEST_RTC_INCLUDE_RTC_TMP_DIR