TheRock/rocm-libraries/projects/composablekernel/example/ck_tile/37_transpose/README.md

Batched Transpose (Block Transpose) with CK Tile

This example demonstrates a high-performance batched block transpose kernel using the CK Tile programming model, with a focus on architectures like gfx950. The kernel is optimized for tiled memory access and is suitable for layout conversions such as NCHW <-> NHWC in deep learning. This transpose load has some constraints in input tile distribution.

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Algorithm and Math

Given a batch of tensors X of shape [N, C, H, W], the block transpose operation rearranges axes to produce Y of shape [N, H, W, C] (NCHW to NHWC) or other permutations.

For each element:

Y_{n, h, w, c} = X_{n, c, h, w}

• Blockwise Transpose: Each thread block processes a tile (block) of the input, reading and writing in a coalesced, tiled fashion for optimal memory throughput.

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Tile Programming Model

• Tiles: Each thread block processes a tile of the input tensor for a given batch.
• Policy: transpose_policy.hpp defines tile/block size and memory access patterns for optimal performance.

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Features

• Optimized for Architecture: Designed for architectures like gfx950 with constraints on input tile distribution.
• Flexible Layouts: Supports NCHW <-> NHWC and other axis permutations.
• Batching: Efficiently transposes multiple tensors in parallel.
• Validation: CPU validation and benchmarking options.

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Build & Run

# in the root of ck_tile
mkdir build && cd build
# you can replace <arch> with the appropriate architecture (for example gfx90a or gfx942) or leave it blank
sh ../script/cmake-ck-dev.sh  ../ <arch>
# Make the transpose executable
make tile_example_transpose -j

This will result in an executable build/bin/tile_example_transpose

Arguments

args:
          -N    input batch size (default:2)
          -C    input channel size. (default:64)
          -H    input height size. (default:1)
          -W    input width size. (default:64)
          -v    whether do CPU validation or not (default: 1)
  -layout_in    input tensor data layout - NCHW by default
 -layout_out    output tensor data layout - NHWC by default
       -seed    seed to be used, -1 means random every time (default:-1)
     -k_name    t to 1 will print kernel name (default:0)

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Source Structure

• Kernel: block_transpose.hpp, batched_transpose_kernel.hpp, transpose_policy.hpp
• Executables: transpose_example.cpp, transpose_api.cpp
• Build: CMakeLists.txt

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Related CK Tile Examples

• 35_batched_transpose: Batched transpose with tiles
• 06_permute: Generic permutation with tiles
• 03_gemm: GEMM with tiles

For tile engine and distribution, see include/ck_tile/tile_engine/ and include/ck_tile/tile_program/tile_distribution/.

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Back to CK Tile Examples