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* Epilogue chainer * epilogue chainer with context to share state in between epilogues * chain-able epilogues for cshuffle * clang-format * rebase related changes - Added separate chainer test - clang format * comment resolutions * clang-format * Policy based chaining - basic Policy structure to control blanket looping and barrier placement. - to be extended for fine grianed control - to be modified to move possible auto-compute values and SFC access count to policy * Refactoring as per spec - Introduced epilogue schedule, graph - modified chainer to function with graph and schedule * minor_changes - made functions to overload in the epilogue_graph file * clang-format * Documentation and Comments - Added comments to files - Noted changes in changelog - Added README to explain the chainer and current status, exact use steps to be added * Comment resolutions - README modified with the suggested changes - Comment fixed accordingly * major refactoring - modified the chainer files to match the new design - updated comments - updated readme - multi-d example shocases use of the chainer * minor cleanup * tensor and rowcol quant chainer epilogue - added scalarepilogue for tensor quant - added schedule for tensorquant - modified quant example to use chainer and appropriate schedules * Refactor epilogue chainer: generalize ops and standardize context interface Address review comments. Changes: - Rename CastToLdsOp to CastAndStoreToLdsOp for clarity - Standardize context member names (working_tile, out_tile, aux_windows) - Update README documentation with correct operation names - Clean up parameter naming in epilogue_chainer.hpp (OutWindow, AccTile, AuxWindows) - common_epilogue_ops.hpp: General-purpose ops (ScaleScalarOp, CastAndStoreToLdsOp, LoadFromLdsOp, ElementwiseOp, StoreOp, MoveWindowsOp) - cshuffle_epilogue_chainer_ops.hpp: CShuffle-specific context and slice operations - epilogue_chainer.hpp: Cleaned up parameter naming for generality - Removed test files that are no longer needed. These were added for intermediate use * update cshuffle chainer ops file w.r.t cshuffle_epilogue.hpp updates & add chainer to quant gemm example * fix compile errors - CI uses c++17 while the code had c++20 features --------- Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com> Co-authored-by: Adam Osewski <19374865+aosewski@users.noreply.github.com>
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/.