composable_kernel/example/ck_tile/05_reduce

Reduction with CK Tile

This example demonstrates parallel reduction (sum, max, etc.) using the CK Tile programming model, a core operation for normalization, statistics, and aggregation in deep learning.

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Algorithm and Math

Given a tensor X and a reduction axis, compute:

• Sum: Y = \sum_i X_i

• Max: Y = \max_i X_i

• Mean: Y = \frac{1}{N} \sum_i X_i

• Tilewise Reduction: Each thread block reduces a tile (block) of the input, using shared memory and register accumulation for efficiency.

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Tile Programming Model

• Tiles: Each thread block processes a tile (block) of the input tensor.
• Pipeline: Modular, can be extended for fused reductions or post-processing.

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Build & Run

mkdir build && cd build
sh ../script/cmake-ck-dev.sh ../ <arch>
make tile_example_reduce -j
./bin/tile_example_reduce -?

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Source Structure

• Kernel: reduce.hpp (tile-programming kernel template)
• Executable: reduce.cpp (argument parsing, kernel launch)
• Build: CMakeLists.txt

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Related CK Tile Examples

• 03_gemm: GEMM with tiles
• 04_img2col: im2col transformation
• 06_permute: Permutation with tiles

For distribution, see include/ck_tile/tile_program/tile_distribution/.

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Back to CK Tile Examples