Files
composable_kernel/example/ck_tile/18_flatmm
yadaish dae85ead64 [CK_TILE] support split-k a16w4 gemm1 (#3389)
* initial version to support moe gemm1 split-k

* add missing args

* fix build warning

* update reference

* for split-k disable bias and weight

* remove debug log

* fix format

* fix div by zero errors

* fix cmake config

* update

* resolve conflicts

* remove useless changes

* reformat

* fix

* remove useless changes

* fix ci

---------

Co-authored-by: lalala-sh <Jiaxing.Wen@amd.com>
Co-authored-by: root <root@smci355-ccs-aus-m01-25.cs-aus.dcgpu>
2025-12-29 23:05:35 +08:00
..

FLATMM Matrix Multiplication with CK Tile

This example demonstrates FLATMM (flattened matrix multiplication) using the CK Tile programming model. FLATMM is a variant of GEMM optimized for certain memory layouts and batch processing patterns. Currently, it only supports the basic feature of the CK Tile FLATMM, but creates the placeholders for the future support on different FLATMM pipeline and different FLATMM modules. In the near future, we will gradually migrate all the FLATMM features from old CK to CK Tile.


Algorithm and Math

Given:

  • A: [\text{batch}, M, K]
  • B: [\text{batch}, K, N]
  • C: [\text{batch}, M, N]

For each batch b:


C^{(b)} = A^{(b)} \times B^{(b)}
  • FLATMM: An alternative solution as the Preshuffled GEMM in /03_gemm

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 flatmm calculation
make tile_example_flatmm_basic -j

This will result in an executable build/bin/tile_example_flatmm_basic

Arguments

args:
          -m    m dimension (default:256)
          -n    n dimension (default:256)
          -k    k dimension (default:128)
   -a_layout    A tensor data layout - Row by default (default:R)
   -b_layout    B tensor data layout - Row by default (default:C)
   -c_layout    C tensor data layout - Row by default (default:R)
   -stride_a    Tensor A stride (default:0)
   -stride_b    Tensor B stride (default:0)
   -stride_c    Tensor C stride (default:0)
          -v    0. No validation, 1. Validation on CPU, 2. Validation on GPU (default:1)
       -prec    data type. fp16/bf16/fp8/bf8 (default:fp16)
     -warmup    number of iterations before benchmark the kernel (default:50)
     -repeat    number of iterations to benchmark the kernel (default:100)
      -timer    gpu:gpu timer, cpu:cpu timer (default:gpu)
    -split_k    splitK value (default:1)
       -init    0:random, 1:linear, 2:constant(1) (default:0)
  -warp_tile    0: 16x16, 1: 32x32, 2: 16x16x128 (950 only), 3: 32x32x64 (950 only) (default:0)
       -json    0: No Json, 1: Dump Results in Json format (default:0)
   -jsonfile    json file name to dump results (default:flatmm_basic.json)

Source Structure


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


Back to CK Tile Examples