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This change replaces pipeline macros like CK_TILE_PIPELINE_COMPUTE_V3, CK_TILE_PIPELINE_MEMORY, etc in the CK Tile examples with a common enum called GemmPipeline to reduce code duplication.
Multiple D GEMM with CK Tile
This example demonstrates GEMM with multiple D tensors (multi-output GEMM) using the CK Tile programming model. This is useful for fused operations where the GEMM output is combined with multiple side inputs (e.g., bias, residual, or other elementwise sources).
Algorithm and Math
Given:
A:[M, K]B:[K, N]D_0, D_1, ..., D_n:[M, N](multiple side inputs)E:[M, N](output)
The operation:
E = f(A \times B, D_0, D_1, ..., D_n)
where f is a fused elementwise function (e.g., add, multiply, activation).
- Tilewise Multi-D GEMM: Each thread block processes a tile of
E, loading corresponding tiles fromA,B, and allD_i, performing blockwise GEMM and fused elementwise operations.
Tile Programming Model
- Tiles: Each thread block processes a tile of
E. - Pipeline: Modular, supports different memory/computation pipelines and multi-D fusion.
Features
- Multiple D Inputs: Supports arbitrary number of side inputs for fusion.
- Flexible Layouts: Supports row/column-major and custom strides for all tensors.
- SplitK: Supports K-batching for large K dimensions.
- Validation: GPU validation and benchmarking options.
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
../script/cmake-ck-dev.sh ../ <arch>
#The basic pipeline method on the gemm calculation
make tile_example_gemm_multi_d_fp16 -j
This will result in an executable build/bin/tile_example_gemm_multi_d_fp16
Arguments
args:
-m m dimension (default:3840)
-n n dimension (default:4096)
-k k dimension (default:4096)
-a_layout A tensor data layout - Row by default (default:R)
-b_layout B tensor data layout - Col by default (default:C)
-ds_layout Ds tensor data layout - Row by default (default:R)
-e_layout E tensor data layout - Row by default (default:R)
-stride_a Tensor A stride (default:0)
-stride_b Tensor B stride (default:0)
-stride_ds Tensor Ds stride (default:0)
-stride_e Tensor E stride (default:0)
-v 0. No validation, 1. Validation on GPU (default:1)
-warmup number of iterations before benchmark the kernel (default:50)
-repeat number of iterations to benchmark the kernel (default:100)
-kbatch kbatch for SplitK (default:1)
-json 0: No Json, 1: Dump Results in Json format (default:0)
-jsonfile json file name to dump results (default:cktile_gemm_multi_d_fp16.json)
Source Structure
- Kernel:
gemm_multi_d_fp16.hpp(tile-programming kernel template) - Executable:
gemm_multi_d_fp16.cpp - Utils:
utils.hpp - Build:
CMakeLists.txt,run_gemm_multi_d_fp16_example.inc
Related CK Tile Examples
- 03_gemm: Single GEMM with tiles
- 16_batched_gemm: Batched GEMM with tiles
- 17_grouped_gemm: Grouped GEMM with tiles
For distribution, see include/ck_tile/tile_engine/ and include/ck_tile/tile_program/tile_distribution/.