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composable_kernel/CHANGELOG.md
Yashvardhan Agarwal 15e81397a4 [CK_TILE] Epilogue chaining (Lwpck 3373) (#2773) 
* 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>
2025-12-18 10:02:02 +01:00

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# Changelog for Composable Kernel
Documentation for Composable Kernel available at [https://rocm.docs.amd.com/projects/composable_kernel/en/latest/](https://rocm.docs.amd.com/projects/composable_kernel/en/latest/).
## (Unreleased) Composable Kernel 1.3.0
### Added
* Added support for explicit GEMM in CK_TILE grouped convolution forward and backward weight.
* Added TF32 convolution support on gfx942 and gfx950 in CK. It could be enabled/disabled via `DTYPES` of "tf32".
* Added attention sink support for FMHA FWD, include qr_ks_vs, qr_async and splitkv pipelines.
* Added support for microscaling (MX) FP8/FP4 mixed data types to Flatmm pipeline
### Changed
### Upcoming changes
## Composable Kernel 1.2.0 for ROCm 7.2.0
### Added
* Added support for fp8 dynamic tensor-wise quantization of fp8 fmha fwd kernel.
* Added support for bf16 data type to grouped_gemm and grouped_gemm_preshuffle.
* Added Col-Col-Row-Col layout support for aquant mode in blockscale GEMM.
* Added support for mixed precision fp8 x bf8 universal GEMM and weight preshuffle GEMM.
* Added a compute async pipeline in the CK Tile universal GEMM on gfx950.
* Added support for B Tensor type `pk_int4_t` in the CK Tile weight preshuffle GEMM.
* Added the new api to load different memory sizes to SGPR.
* Added support for B Tensor preshuffle in CK Tile grouped GEMM.
* Added a basic copy kernel example and supporting documentation for new CK Tile developers.
* Added support for grouped GEMM kernels to perform Multi D elementwise operation.
* Added support for multiple ABD GEMM.
* Added benchmarking support for tile engine GEMM Multi D.
* Added block scaling support in CK Tile GEMM, allowing flexible use of quantization matrices from either A or B operands.
* Added the row-wise column-wise quantization for CK Tile GEMM and CK Tile grouped GEMM.
* Added support for f32 to FMHA (forward and backward).
* Added tensor-wise quantization for CK Tile GEMM.
* Added support for batched contraction kernel.
* Added WMMA (gfx12) support for FMHA.
* Added pooling kernel in CK_TILE
* Added top-k sigmoid kernel in CK_TILE
* Added the blockscale 2D support for CK_TILE GEMM.
* Added Flatmm pipeline for microscaling (MX) FP8/FP4 data types
### Changed
* Removed `BlockSize` in `make_kernel` and `CShuffleEpilogueProblem` to support Wave32 in CK Tile (#2594)
* Added an optional template parameter `Arch` (`gfx9_t`, `gfx12_t` etc.) to `make_kernel` to support linking multiple object files that have the same kernel compiled for different architectures.
* FMHA examples and tests can be built for multiple architectures (gfx9, gfx950, gfx12) at the same time.
### Upcoming changes
* Composable Kernel will be adopting C++20 features in an upcoming ROCm release, updating the minimum compiler requirement to C++20. Ensure that your development environment complies with this requirement to facilitate a seamless transition.
## Composable Kernel 1.1.0 for ROCm 7.1.1
### Upcoming changes
* Composable Kernel will be adopting C++20 features in an upcoming ROCm release, updating the minimum compiler requirement to C++20. Ensure that your development environment complies with this requirement to facilitate a seamless transition.
## Composable Kernel 1.1.0 for ROCm 7.1.0
### Added
* Added support for hdim as a multiple of 32 for FMHA (fwd/fwd_splitkv/bwd)
* Added support for elementwise kernel.
### Upcoming changes
* Non-grouped convolutions are deprecated. Their functionality is supported by grouped convolution.
## Composable Kernel 1.1.0 for ROCm 7.0.0
### Added
* Added support for bf16, f32, and f16 for 2D and 3D NGCHW grouped convolution backward data
* Added a fully asynchronous HOST (CPU) arguments copy flow for CK grouped GEMM kernels.
* Added support GKCYX layout for grouped convolution forward (NGCHW/GKCYX/NGKHW, number of instances in instance factory for NGCHW/GKYXC/NGKHW has been reduced).
* Added support for GKCYX layout for grouped convolution forward (NGCHW/GKCYX/NGKHW).
* Added support for GKCYX layout for grouped convolution backward weight (NGCHW/GKCYX/NGKHW).
* Added support for GKCYX layout for grouped convolution backward data (NGCHW/GKCYX/NGKHW).
* Added support for Stream-K version of mixed fp8/bf16 GEMM
* Added support for Multiple D GEMM
* Added GEMM pipeline for microscaling (MX) FP8/FP6/FP4 data types
* Added support for FP16 2:4 structured sparsity to universal GEMM.
* Added support for Split K for grouped convolution backward data.
* Added logit soft-capping support for fMHA forward kernels.
* Added support for hdim as a multiple of 32 for FMHA (fwd/fwd_splitkv)
* Added benchmarking support for tile engine GEMM.
* Added Ping-pong scheduler support for GEMM operation along the K dimension.
* Added rotating buffer feature for CK_Tile GEMM.
* Added int8 support for CK_TILE GEMM.
* Added CK Tile Epilogue Chainer framework for composable epilogue sequences in GEMM operations
### Optimized
* Optimize the gemm multiply multiply preshuffle & lds bypass with Pack of KGroup and better instruction layout.
* Added Vectorize Transpose optimization for CK Tile
* Added the asynchronous copy for gfx950
### Changed
* Removed support for gfx940 and gfx941 targets (#1944)
* Replaced the raw buffer load/store intrinsics with Clang20 built-ins (#1876)
* DL and DPP kernels are now enabled by default.
* Number of instances in instance factory for grouped convolution forward NGCHW/GKYXC/NGKHW has been reduced.
* Number of instances in instance factory for grouped convolution backward weight NGCHW/GKYXC/NGKHW has been reduced.
* Number of instances in instance factory for grouped convolution backward data NGCHW/GKYXC/NGKHW has been reduced.
## Composable Kernel 1.1.0 for ROCm 6.1.0
### Additions
* Added generic instances for GEMM XDL operations (#1161)
* Added gamma and beta parameters for the layernorm and groupnorm bwd operations (#1133)
* Introduced wrapper sublibrary (limited functionality). (#1071, #1098, #1108, #1126)
* Added an option to vary the number of warm-up cycles and iterations for ckProfiler (#1124)
### Optimizations
* New performance optimizations for GEMM operations on MI200 and MI300 architectures (#1135)
### Fixes
* Reduced the build time for most GPU architectures (#1084)
* Fixed some conversion issues for fp8 data type (#1099)
### Changes
None
### Known issues
None
## Composable Kernel 1.1.0 for ROCm 6.0.0
### Fixes
* Fixed a hazard associated with inline v_dot (#808)
* Fixed two bugs in grouped convolution backward data without K padding (#848 #876)
### Optimizations
None
### Additions
* Added an image to a column kernel (#867)
* Added a column to an image kernel (#930)
* Support for 3D grouped convolution on RDNA 3 GPUs (#935, #950, #985)
* Grouped convolution support for small K and C (#822 #879 #897)
* Support for NHWGC (2D and 3D) grouped convolution backward weight (#769 #804)
* Support for bf16/f32/f16 and NHWGC (2D and 3D) grouped convolution backward data (#757 #799)
* Support for Batched GEMM DL (#732)
### Changes
* Changed the grouped convolution API to maintain consistency with other convolution kernels (#817)
## Composable Kernel 0.2.0 for ROCm 5.7.0
### Fixes
* Fixed a bug in 6-dimensional kernels (#555)
* Fixed a test case failure with grouped convolution backward weight (#524)
### Optimizations
* Improved the performance of the normalization kernel
### Additions
* New CMake flags:
* "DL_KERNELS"-* Must be set to "ON" in order to build the GEMM DL and batched_gemm_multi_d_dl instances
* "DTYPES" -- Can be set to any subset of "fp64;fp32;fp16;fp8;bf16;int8" to build an instance of the specified data types
* "INSTANCES_ONLY" -- Only builds CK library and instances without tests, examples, or profiler
* New feature: if GPU_TARGETS is not set in the CMake command line, CK will be built for all targets supported by the compiler
* Support for MI300A/MI300X
* Support for AMD RDNA 3
* New user tutorial (#563)
* Additional instances for irregular GEMM sizes (#560)
* New inter-wave consumer-producer programming model for GEMM kernels (#310)
* GEMM with support multiple elementwise fusions (multi-D) (#534)
* Multi-embeddings support (#542)
* AMD RDNA 3 blockwise GEMM and real GEMM support (#541)
* AMD RDNA grouped convolution backward weight support (#505)
* MaxPool and AvgPool forward (#815); MaxPool backward (#750)
### Changes
None
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