# Changelog for hipBLASLt

Full documentation for hipBLASLt is available at [rocm.docs.amd.com/projects/hipBLASLt](https://rocm.docs.amd.com/projects/hipBLASLt/en/latest/index.html).

## hipBLASLt 1.4.1 for ROCm 7.14

### Added

* Introduced a new API: hipBLASLt-ext::isSolutionSupported(). This API is used by new hipBLASLt integration from rocBLAS to check if a given solution is supported for a certain GPU and Problem Type. 

## hipBLASLt 1.4.0

### Added

* Complex datatype support for gfx942 and gfx950.
* `hipblasLtSetSmCountTarget()` / `hipblasLtGetSmCountTarget()` handle-level
  helpers (the analogue of cuBLAS's `cublasSetSmCountTarget` /
  `cublasGetSmCountTarget`). `int32_t`, default `0` meaning "use all
  compute units"; negative values are rejected with
  `HIPBLAS_STATUS_INVALID_VALUE`.
* `HIPBLASLT_MATMUL_DESC_SM_COUNT_TARGET` matmul-descriptor attribute and
  `HIPBLASLT_MATMUL_PREF_SM_COUNT_TARGET` preference attribute (same
  semantics). When a per-matmul / per-preference value is non-zero it
  takes precedence over the handle-level value. Lets callers convey an
  estimate of how many CUs hipBLASLt should target for kernel selection
  and persistent-grid sizing — useful when another kernel (e.g. RCCL)
  is co-running on the device or when a persistent grid should be sized
  for a known CU budget. (This is a hint, not a CU reservation.)
* `HIPBLASLT_MATMUL_DESC_STREAMK_TILE_SCHEDULING_EXT` and matching ext API
  (`setStreamKTileSchedulingMode()` / `getStreamKTileSchedulingMode()`) accept
  the tri-state `hipblasLtStreamKTileSchedulingMode_t` enum (OFF=0 static SK3,
  ON=1 dynamic SK4, AUTO=2 origami heuristic). Invalid values return
  `HIPBLAS_STATUS_INVALID_VALUE`. `hipblaslt-bench` `--streamk_tile_scheduling`
  and `--sm_count_target` forward into the matmul descriptor
  (see `clients/bench/README.md`).

### Changed

* StreamK=5 tile scheduling default is now `OFF` (`0`, static SK3 sub-path)
  instead of `AUTO` (`2`). Set `HIPBLASLT_MATMUL_DESC_SM_COUNT_TARGET` (or
  `hipblasLtSetSmCountTarget`) to a positive value to engage the origami
  hybrid-mode heuristic per launch even when the mode is `OFF`; use
  `HIPBLASLT_STREAMK_TILE_SCHEDULING_AUTO` (`2`) to always delegate to the
  heuristic regardless of `sm_count_target`.

## hipBLASLt 1.3.0

### Added

* General Batched GEMM support.
* `HIPBLASLT_CHECK_NUMERICS` environment variable: opt-in post-GEMM NaN
  scanner for `hipblasLtMatmul` output (D matrix). Accepts numeric
  (`1`, `2`) or word values (`info`, `warn`, `none`/`off`). Output goes
  to the standard hipBLASLt log sink (or `stderr` if no log sink is
  configured). Per-call cost is one scanner kernel launch only -- no
  `hipStreamSynchronize`, no per-call alloc/free. A persistent 4-byte
  device flag is allocated once in the handle constructor and drained
  once at handle destruction with a single `hipDeviceSynchronize`;
  a teardown log line reports the first matmul call_id at which NaN
  was observed (or that none was, with a sampling caveat when the
  scanner only ran on a subset of calls). Companion env vars allow
  sampling (`HIPBLASLT_CHECK_NUMERICS_SCAN_EVERY`) and a bisect window
  (`HIPBLASLT_CHECK_NUMERICS_SCAN_FROM` / `_SCAN_UNTIL`). A C API
  `hipblasLtCheckNumericsDrain(handle, &first_nan_call_id)` lets
  frameworks drive a drain on demand.

### Changed

* Replaced `install.sh` with an invoke-based task runner (`tasks.py`) to support cross-platform builds including Windows (ROCm 7.0+).
* gtest and msgpack-cxx are now fetched automatically via CMake FetchContent if not found on the system.
* Greatly improved MXFP4 GEMM performance when using HIPBLASLT_MATMUL_MATRIX_SCALE_BLK32_UE8M0_32_8_EXT

## hipBLASLt 1.2.2 for ROCm 7.2.1

### Added

* Support for AMD SMI.

### Changed

* Migrate `HIPBLASLT_ENABLE_LLVM` to `HIPBLASLT_ENABLE_YAML` and synchronize with tensilelite's build library format.

### Deprecation

* ROCm SMI is deprecated and dependencies are removed.

## hipBLASLt 1.2.1 for ROCm 7.2.1

### Resolved issues

* Fix issue where users might encounter a `HIPBLAS_STATUS_INTERNAL_ERROR` with various sizes in CPX mode.

## hipBLASLt 1.2.0 for ROCm 7.2.0

### Added

* Support for 'BF16' input with 'FP32' output data type for gfx90a.
* Support for hipBLASLtExt operation APIs on gfx11XX and gfx12XX.
* Added ``HIPBLASLT_MATMUL_MATRIX_SCALE_BLK32_UE8M0_32_8_EXT`` to support pre-swizzled block scaling data.

## hipBLASLt 1.1.0 for ROCm 7.1.0

### Added

* Fused Clamp GEMM for ``HIPBLASLT_EPILOGUE_CLAMP_EXT`` and ``HIPBLASLT_EPILOGUE_CLAMP_BIAS_EXT``. This feature requires the minimum (``HIPBLASLT_MATMUL_DESC_EPILOGUE_ACT_ARG0_EXT``) and maximum (``HIPBLASLT_MATMUL_DESC_EPILOGUE_ACT_ARG1_EXT``) to be set.
* Support for ReLU/Clamp activation functions with auxiliary output for the `f16` and `bf16` data types for gfx942 to capture intermediate results. This feature is enabled for ``HIPBLASLT_EPILOGUE_RELU_AUX``, ``HIPBLASLT_EPILOGUE_RELU_AUX_BIAS``, ``HIPBLASLT_EPILOGUE_CLAMP_AUX_EXT``, and ``HIPBLASLT_EPILOGUE_CLAMP_AUX_BIAS_EXT``.
* Support for `HIPBLAS_COMPUTE_32F_FAST_16BF` for FP32 data type for gfx950 only.
* Added the CPP extension APIs ``setMaxWorkspaceBytes`` and ``getMaxWorkspaceBytes``.
* Added the ability to print logs (using ``HIPBLASLT_LOG_MASK=32``) for Grouped GEMM.
* Support for swizzleA by using the hipblaslt-ext cpp API.
* Support for hipBLASLt extop for gfx11xx and gfx12xx.

### Changed

* ``hipblasLtMatmul()`` now returns an error when the workspace size is insufficient, rather than causing a segmentation fault.

### Resolved issues

* Fix incorrect results when using ldd and ldc with some solutions

## hipBLASLt 1.0.0 for ROCm 7.0.0

### Added

* Stream-K GEMM support has been enabled for the `FP32`, `FP16`, `BF16`, `FP8`, and `BF8` data types on the MI300A APU. To activate this feature, set the `TENSILE_SOLUTION_SELECTION_METHOD` environment variable to `2`, for example, `export TENSILE_SOLUTION_SELECTION_METHOD=2`.
* Fused Swish/SiLU GEMM in hipBLASLt (enabled by ``HIPBLASLT_EPILOGUE_SWISH_EXT`` and ``HIPBLASLT_EPILOGUE_SWISH_BIAS_EXT``)
* Added support for ``HIPBLASLT_EPILOGUE_GELU_AUX_BIAS`` for gfx942
* Added `HIPBLASLT_TUNING_USER_MAX_WORKSPACE` to constrain max workspace size for user offline tuning
* Added ``HIPBLASLT_ORDER_COL16_4R16`` and ``HIPBLASLT_ORDER_COL16_4R8`` to ``hipblasLtOrder_t`` to support FP16/BF16 swizzle GEMM and FP8/BF8 swizzle GEMM respectively.
* Added TF32 emulation on gfx950

### Changed

* ``HIPBLASLT_MATMUL_DESC_A_SCALE_POINTER_VEC_EXT`` and ``HIPBLASLT_MATMUL_DESC_B_SCALE_POINTER_VEC_EXT`` are removed. Use the ``HIPBLASLT_MATMUL_DESC_A_SCALE_MODE`` and ``HIPBLASLT_MATMUL_DESC_B_SCALE_MODE`` attributes to set scalar (``HIPBLASLT_MATMUL_MATRIX_SCALE_SCALAR_32F``) or vector (``HIPBLASLT_MATMUL_MATRIX_SCALE_OUTER_VEC_32F``).
* The non-V2 APIs (``GemmPreference``, ``GemmProblemType``, ``GemmEpilogue``, ``GemmTuning``, ``GemmInputs``) in the Cpp header are now the same as the V2 APIs (``GemmPreferenceV2``, ``GemmProblemTypeV2``, ``GemmEpilogueV2``, ``GemmTuningV2``, ``GemmInputsV2``). The original non-V2 APIs are removed.
* `hipblasltExtAMaxWithScale` API is removed.

### Optimized

* Improved performance for 8-bit (FP8/BF8/I8) NN/NT cases by adding ``s_delay_alu`` to reduce stalls from dependent ALU operations on gfx12+.
* Improved performance for 8-bit and 16-bit (FP16/BF16) TN cases by enabling software dependency check (Expert Scheduling Mode) under certain restrictions to reduce redundant hardware dependency checks on gfx12+.
* Improved performance for 8-bit, 16-bit, and 32-bit batched GEMM with a better heuristic search algorithm for gfx942.

### Upcoming changes

* V2 APIs (``GemmPreferenceV2``, ``GemmProblemTypeV2``, ``GemmEpilogueV2``, ``GemmTuningV2``, ``GemmInputsV2``) are deprecated.

## hipBLASLt 0.12.1 for ROCm 6.4.2

### Added

* Support for gfx1151

## hipBLASLt 0.12.1 for ROCm 6.4.1

### Resolved issues

* Fixed an accuracy issue that occurred for some solutions using an `FP32` or `TF32` data type with a TT transpose.

## hipBLASLt 0.12.0 for ROCm 6.4.0

### Added

* Support roctx if `HIPBLASLT_ENABLE_MARKER=1` is set
* Output the profile logging if `HIPBLASLT_LOG_MASK=64` is set
* Support FP16 compute type
* Add memory bandwidth information in hipblaslt-bench output
* Support user offline tuning mechanism
* Add more samples

### Changed

* Output the bench command along with solution index if `HIPBLASLT_LOG_MASK=32` is set

### Optimized

* Improve the overall performance of XF32/FP16/BF16/FP8/BF8 data type
* Reduce library size

### Resolved issues

* Fix multi-threads bug
* Fix multi-streams bug

## hipBLASLt 0.10.0 for ROCm 6.3.0

### Added

* Support the V2 CPP extension API for backward compatibility
* Support for data type Int8 in with Int8 out
* Support for data type FP32/FP64 for gfx110x
* Add the Extension API `hipblaslt_ext::matmulIsTuned`
* Output atol and rtol for hipblaslt-bench validation
* Output the bench command for hipblaslt CPP ext API path if `HIPBLASLT_LOG_MASK=32` is set
* Support odd sizes for FP8/BF8 GEMM

### Changed

* Reorganize and add more sample code
* Add a dependency with the hipblas-common package and remove the dependency with the hipblas package

### Optimized

* Support fused kernel for HIPBLASLT_MATMUL_DESC_AMAX_D_POINTER for FP8/BF8 data type
* Improve the library loading time
* Improve the overall performance of first returned solution

### Upcoming changes

*  The V1 CPP extension API will be deprecated in a future release of hipBLASLt

## hipBLASLt 0.8.0

### Added

* Extension APIs:
  * `hipblasltExtAMaxWithScale`
* `GemmTuning` extension parameter to set wgm by user
* Support HIPBLASLT_MATMUL_DESC_AMAX_D_POINTER for the FP8/BF8 data types
* Support for FP8/BF8 input, FP32/FP16/BF16/F8/BF8 output (only for the gfx94x architectures)
* Support HIPBLASLT_MATMUL_DESC_COMPUTE_INPUT_TYPE_A_EXT and HIPBLASLT_MATMUL_DESC_COMPUTE_INPUT_TYPE_B_EXT for FP16 input data type to use FP8/BF8 mfma
* Support for the gfx110x architecture

### Optimized

* Improve the library loading time

## hipBLASLt 0.7.0

### Additions

* Extension APIs:
  * `hipblasltExtSoftmax`
  * `hipblasltExtLayerNorm`
  * `hipblasltExtAMax`
* `GemmTuning` extension parameter to set split-k by user
* Support for mixed-precision datatype: FP16/FP8 in with FP16 out
* Add CMake support for documentation

### Deprecations

* algoGetHeuristic() ext API for GroupGemm will be deprecated in a future release of hipBLASLt

## hipBLASLt 0.6.0

### Additions

* New `UserArguments` variable for `GroupedGemm`
* Support for datatype: FP16 in with FP32 out
* Support for datatype: Int8 in Int32 out
* Support for gfx94x platform
* Support for FP8/BF8 datatype (only for gfx94x platform)
* Support scalar A,B,C,D for FP8/BF8 datatype
* Added samples

### Changes

* Replaced `hipblasDatatype_t` with `hipDataType`
* Replaced `hipblasLtComputeType_t` with `hipblasComputeType_t`

### Removals

* Deprecated `HIPBLASLT_MATMUL_DESC_D_SCALE_VECTOR_POINTER`

## hipBLASLt 0.3.0

### Additions

* Added `getAllAlgos` extension APIs
* TensileLite support for new epilogues: gradient gelu, gradient D, gradient A/B, aux
* Added a sample package that includes three sample apps
* Added a new C++ GEMM class in the hipBLASLt extension

### Changes

* Refactored GroupGemm APIs as C++ class in the hipBLASLt extension
* Changed the scaleD vector enum to `HIPBLASLT_MATMUL_DESC_D_SCALE_VECTOR_POINTER`

### Fixes

* Enabled norm check validation for CI

### Optimizations

* GSU kernel: wider memory, PGR N
* Updated logic yaml to improve some FP16 NN sizes
* GroupGemm support for GSU kernel
* Added grouped GEMM tuning for aldebaran

## hipBLASLt 0.2.0

### Additions

* Added CI tests for TensileLite
* Initialized extension group GEMM APIs (FP16 only)
* Added a group GEMM sample app: `example_hipblaslt_groupedgemm`

### Fixes

* Fixed incorrect results for the ScaleD kernel

### Optimizations

* Tuned equality sizes for the HHS data type
* Reduced host-side overhead for `hipblasLtMatmul()`
* Removed unused kernel arguments
* Schedule values setup before first `s_waitcnt`
* Refactored TensileLite host codes
* Optimized build time

## hipBLASLt 0.1.0

### Additions

* Enabled hipBLASLt APIs
* Support for gfx90a
* Support for problem type: FP32, FP16, BF16
* Support activation: relu, gelu
* Support for bias vectors
* Integrated with TensileLite kernel generator
* Added Gtest: `hipblaslt-test`
* Added the full function tool `hipblaslt-bench`
* Added the sample app `example_hipblaslt_preference`

### Optimizations

* gridBase solution search algorithm for untuned size
* Tuned 10k sizes for each problem type