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d239b91fd5
* Initial commit * Adding new tile partitioner to flatmm * intermediate changes * debugging kernels * Updating flatmm example to universal gemm example * updated flatmm kernel to run via gemmKernel * update universal gemm to incorporate flatmm * debug * Fix flatmm call * Fixing other kernels and tests for API changes * clang formatted * fixing gemm tests * added test for flatmm and simplify kernel arguments * adding flatmm test * fix test for flatmm * simplify gemm kernel with flatmm * remove flatmm related files * addressing review comments and code clean up * resolving empty file * resolving empty file * clang formatted * addressing review comments * enable persistent kernel for flatmm * reverted the removed files for flatmm * reverted the removed files for flatmm * changed flatmm to weightPReshuffle; removed the _1 added in teh faltmm example * some more renames * clang formatted
FLATMM Matrix Multiplication
This folder contains example for FLATMM using ck_tile tile-programming implementation. 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.
build
# 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>
# 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
example
args:
-b batch size (default:1)
-m m dimension (default:1024)
-n n dimension (default:2048)
-k k dimension (default:64)
-a_layout Tensor A data layout (default: R)
-b_layout Tensor B data layout (default: R)
-c_layout Tensor C data layout (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:2)
-e Absolute error tolerance (default:1e-5)
-prec data type. fp16/bf16/fp8/bf8 (default:fp16)
-warmup number of iterations before benchmark the kernel (default:10)
-repeat number of iterations to benchmark the kernel (default:100)
-timer gpu:gpu timer, cpu:cpu timer (default:gpu)