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composable_kernel/CHANGELOG.md
Vijay Krish bad7262507 ck_tile kernel for gemm with groupwise quantized B tensor. (#2663) 
* This change introduces new pipelines with Intrawave scheduler and block gemm primitives that loads the scale tensor to registers to perform dequantization post MFMA on C tensor in registers.

Scale tensor data, BQ is spliced across threads in registers and not stored in LDS.

Current support is for the following combinations, but it should be fairly straightforward to extend support to more formats.

fp8, fp8 -> f32
bf8, bf8 -> f32
fp8, i4 -> f32
bf8, i4 -> f32
Group size can go down to as low as K length of underlying WarpGemm primitive.

* Solve merge conflict

* [CK TILE] Update CHANGELOG.md

---------

Co-authored-by: Vijay Krishnamoorthy <vjkrish@fb.com>
Co-authored-by: ThomasNing <thomas.ning@amd.com>
Co-authored-by: Cong Ma <congma13@amd.com>

[ROCm/composable_kernel commit: 4208e28988]
2025-08-28 23:43:02 -07:00

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Changelog for Composable Kernel

Documentation for Composable Kernel available at https://rocm.docs.amd.com/projects/composable_kernel/en/latest/.

Composable Kernel 1.2.0 for ROCm 7.0.0

Added

  • Added a basic copy kernel example and supporting documentation for new CK Tile developers.
  • 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 support for hdim as a multiple of 32 for FMHA (fwd/fwd_splitkv/bwd)
  • 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 support for elementwise kernel.
  • 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.

Optimized

  • Optimize the gemm multiply multiply preshuffle & lds bypass with Pack of KGroup and better instruction layout. (#2166)
  • Added Vectorize Transpose optimization for CK Tile (#2131)
  • Added the asynchronous copy for gfx950 (#2425)

Fixes

None

Changes

  • 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.
  • Removed BlockSize in make_kernel and CShuffleEpilogueProblem to support Wave32 in CK_TILE (#2594)

Known issues

None

Upcoming changes

  • Non-grouped convolutions are deprecated. All of their functionality is supported by grouped convolution.

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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