* Few small fixes.
* New GroupedGemm instances (BF16)
* Unify and refactor GroupedGEMM device API.
* Adapt changes to new API.
* Adapt grouped gemm profiler.
* Accept multiple kbatches for grouped gemm profiler.
- delete obsolete two stage as it is now covered by grouped gemm
* Update unit test for grouped gemm.
* Fix thresholds for BF16 and F8. Unblock tests.
* Fix few instances.
* Multiple small fixes.
* Adapt to new API, check dynamic casting.
* Uncomment few data types in grouped gemm profiler.
* Fix call to SetDeviceArgs.
* Fix profile grouped gemm multiply tile loop.
* Fix grouped gemm tile loop kernel args in client examples.
* Review comments.
* Block universal gemm.
* Universal block gemm with interwave scheduler - draft.
* Refactoring
* Move a/b_warp_tiles into BlockGemmImpl
* set BlockGemmImpl as a class member
* Change tile size for more suitable to memory bound cases.
* Introduce kKPerThread to WarpGemm
* Add documentation comment.
* Fix Interwave scheduler block gemm.
* Add compute/memory friendly tile configuration.
* Clean
* New tile configurations in gemm mem example.
* Add more static checks and fix loop order in block gemm.
* Add more static checks and use warp gemm mfma dispatcher.
* Add default scheduler block gemm.
* Remove logging in example.
* Change in fwd-splitkv kernel to support num_splits=1 case
* Update in codegen fwd-splitkv to make num_splits > 1 cases pass
* Specify instance traits in dispatch
* Fix link error for fp8 kernels
---------
Co-authored-by: Po Yen Chen <PoYen.Chen@amd.com>
* Add overloads for MakeKargs
Overload MakeKargs to accept std::tuple<uint64_t, uint64_t> and std::tuple<void*, void*> to preserve functionality of code currently passing in list initializers or tuples.
* Add overloads for MakeKargs
Overload MakeKargs to accept std::tuple<uint64_t, uint64_t> and std::tuple<void*, void*> to preserve functionality of code currently passing in list initializers or tuples.
* Re-format files using ck_tile remod.py
---------
Co-authored-by: Po Yen Chen <PoYen.Chen@amd.com>
* Generate group mode paged-attn kernel
* Enable paged-kvcache + group mode support
* Add missing header: fused_moe.hpp
* Add comment to explain kernel arg usage
* Make error message more clear
* Add comment for confusing data member names
* Add more comment for confusing variable names
* Fix typo in option description
* reduce the docker image size and layers
* clean up docker file
* fix linker error for client example 24
* install CK into the default /opt/rocm/ path
* restore installing CK to alternative path in CI
* add linking for utility lib
* add bf16 gemms for gfx11/gfx12
* reduce the input values in test_gemm
* add int8 wmma gemm instances for gfx11/gfx12
* add example gemm_wmma_int8
* fix bug in gemm_wmma_int8 test
* increase bf16 gemm test tolerance
* update the dates and clean-up commented-out instances
* Improve test verbosity.
* BUGFIX: Add missing initialization for reduction buffer
* Change default initialization method
Performance may be affected for fp32 and int8 examples.
* Improve test verbosity
* Cleanup
* [CK_TILE] add more stride for layernorm to support un-continuous Tensor
* align CK coding style
* extend strides to layernrom expample
* clang-format...
* optimze small N case using vec io and using rcp div
* [Ck_tile] layernorm, add param to control fastdiv; change generate codes and test pass
* [Ck_tile] fix blockSize compute in Generic2dBlockShape
* [Ck_tile]fix kfastfdiv template style
* [Ck_tile] layernorm, fix stype in review
---------
Co-authored-by: dummycoderfe <noplydummmycoder@163.com>
Before, generate.py appended the list at the end of the output file.
When running the cmake configuration steps multiple times on the
examples, the blob list (such as fwd_blob_list.txt) would grow at every
configuration.
`library/src/tensor_operation_instance/gpu/mha/CMakeLists.txt` worked around
this issue by removing the output file if it exists.
Now, generate.py overrides the content of the output file.
There is no need for the workaround in the CMakeLists.txt;
and the issue is solved for the example projects too.
