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* Wrap ck host utitlies in CK namespace. The CK and CK-Tile source code bases are incompatible because CK is not properly using namespaces everywhere. In particular, we need to put hip_check_error in the ck namespace. Move all functions in include/ck_/host_utility that were in global namespace into the ck namespace. There may be additional namespace problems like this, and it's possible we'll have namespace clashes. But it is good design to properly guard our to code bases (CK and CKTile) so that they can both coexist. Moreover, estabilishing this compatiblity is essential if we are going to allow the builder to instantiate kernels from either template library. * Add using declarations to test code. After moving some of the untils into the ck namespace, most examples and a few tests had to be updated to recognize the new namespace declarations. We add using declarations to individual compute units for functions that were previously in the global namespace. * Add using declarations to client examples.
Elementwise Operation with Permutation Fusion
Theory
This example demonstrates elementwise operations fused with tensor permutation. This pattern is used in deep learning for applying activation functions or scaling while simultaneously reordering tensor dimensions (e.g., NCHW to NHWC).
Mathematical Formulation:
- Elementwise:
Z = f(X)orZ = f(X, Y) - Permute:
Y_{i_{p_0}, i_{p_1}, ..., i_{p_{n-1}}} = Z_{i_0, i_1, ..., i_{n-1}}P = [p_0, p_1, ..., p_{n-1}]is the permutation pattern
Algorithmic Background:
- The elementwise operation and permutation are fused in a single kernel.
- Intermediate results are kept in registers, not written to global memory.
- Used for layout conversion with activation, attention head reshaping, and more.
How to Run
Prerequisites
Please follow the instructions in the main Build Guide section as a prerequisite to building and running this example.
Build and run
cd composable_kernel/example/44_elementwise_permute
mkdir build && cd build
cmake -DCMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc ..
make -j
# Example run (ReLU + NCHW to NHWC)
./elementwise_permute_xdl --input_shape=32,128,56,56 --permutation=0,2,3,1 --operation=relu --verify=1 --time=1
Source Code Structure
Directory Layout
example/44_elementwise_permute/
├── elementwise_permute_xdl.cpp # Main example: sets up, runs, and verifies elementwise+permute
include/ck/tensor_operation/gpu/device/
│ └── device_elementwise_permute.hpp # Device-level API for fused elementwise+permute
include/ck/tensor_operation/gpu/device/impl/
│ └── device_elementwise_permute_impl.hpp # Implementation
include/ck/tensor_operation/gpu/grid/
│ └── gridwise_elementwise_permute.hpp # Grid-level kernel
include/ck/tensor_operation/gpu/element/
└── element_wise_operation.hpp # Elementwise operation definitions
Key Classes and Functions
- DeviceElementwisePermute (in
device_elementwise_permute.hpp):
Device API for fused elementwise and permutation. - gridwise_elementwise_permute (in
gridwise_elementwise_permute.hpp):
Implements the tiled/blocking elementwise+permute kernel. - element_wise_operation (in
element_wise_operation.hpp):
Defines elementwise operations (e.g., relu, scale).
This example demonstrates how Composable Kernel supports efficient fusion of elementwise operations and tensor permutation for deep learning and data layout transformations.