* updates to support int8 in 03_gemm example
* added comments, using aliases, helper functions
* test(gemm_universal): add test cases for int8 gemm pipeline
* fix(test_gemm): fix for failing test unit test for int8
* test(ck_tile): add int8 unit test for gemm universal
* refactor(gemm_universal): GPU reference verification for GEMM code improved
* style(gemm_universal): removed extra comments and did clang format
* merging recent changes to universal gemm to tile_engine
* ck tile engine integration work
* feat(tile_engine): add int8 support to tile engine ops/gemm
* feat(tile_engine): added 32 32 16 mfma instances to tile engine for int8
* style: Format code with clang-format-12
* refactor(tile_engine): address review comments
* style: removed unhelpful comments & unused variables.
* build: tile engine uses default config
* feat: add int8 support for CK_TILE GEMM
* style: added trailing commas to codegen_utils.py
* refactor: tile engine
* refactor: formatting and code review
* refactor: code formatting for python files
* fix: suppress build warning
* add support for gfx950
* refactor:KWarpTile size in gemms util
* Fix the branch and wrap up the k warp tile
* Add bf8 integration
* refactor: clang format and rebase
---------
Co-authored-by: zjli2013 <leezhengjiang@gmail.com>
Co-authored-by: AviralGoelAMD <aviral.goel@amd.com>
Co-authored-by: Khushbu Agarwal <khuagarw@amd.com>
* [CK_TILE] Refine fp8 in flatmm
1. Replace USING_MFMA_16x16x32 & USING_MFMA_16x16x32 with constexpr
2. Add an additional const check to avoid build error in HotLoopScheduler
3. Refine shuffleb to support both tile 32x32 and 16x16
4. Support command option -init
5. Move Gemm warp defintion to a separate struct
* fix clang format
* fix clang format
* keep default bhavior unchanged (warp tile = 16x16)
* fix tile engine build error
* fix a typo in codegen_utils.py
* address review comments
* address review comments
---------
Co-authored-by: Thomas Ning <Thomas.Ning@amd.com>
* Avoid passing indices (std::vector) by value to host tensor's operator()
Each access requires 2 allocations and copies of the vector.
* Remove 1 unneeded vector copy from the slowest part of fmha_bwd's verification
* Compute ds_hp_host_ref in parallel
This sequntial ForEach is the slowest part of validation and it benefits
from parallel computation.
* Do not use ForEach for simple copy and conversion of large tensors
These tensors all have the same shape {nhead, real_seqlen_q, real_seqlen_k} and
can be copied/converted without complex computations of linear indices.
* add transpose load; no real logic
* fix some compile errors
* fix some issues
* update transpose load logic
* add some fixes
* fix a distribution issue
* update some codes
* add some fix
* can pass; but no logic
* transpose load enable
* update tile transpose
* miss output tile distribution mapping
* hack for transpose 16x16
* update output tensor distribution
* delete unused variables
* fix transpose related codes
* update transpose load example
* exchange the iteration order
* fix 16x16 related dimension transpose
* fix a transpose index issue
* fix a transpose index issue
* fix clang format check
* update load tile transpose related codes
* fix compile errors and pass 16x16 tests
* fix a typo
* update logic
* check other data types
* add transpose load api
* update transpose load api
* fix clang format check
* change file name
* refactor codes
* update code name
* delete some unused codes
* delete the unused oob flag for transpose load
* update tensor view api for transpose load
* update for testing
* fix a typo error
* move transpose ops to example directory
* update transpose api
* update include file
* fix for pr review
* fix compile errors
* add transpose load; no real logic
* fix some compile errors
* fix some issues
* update transpose load logic
* add some fixes
* fix a distribution issue
* update some codes
* add some fix
* can pass; but no logic
* transpose load enable
* update tile transpose
* miss output tile distribution mapping
* hack for transpose 16x16
* update output tensor distribution
* delete unused variables
* fix transpose related codes
* update transpose load example
* exchange the iteration order
* fix 16x16 related dimension transpose
* fix a transpose index issue
* fix a transpose index issue
* fix clang format check
* update load tile transpose related codes
* fix compile errors and pass 16x16 tests
* fix a typo
* update logic
* check other data types
* add transpose load api
* update transpose load api
* fix clang format check
* change file name
* refactor codes
* update code name
* delete some unused codes
* delete the unused oob flag for transpose load
* update tensor view api for transpose load
* update for testing
* fix a typo error
* move transpose ops to example directory
* update transpose api
* update include file
* fix for pr review
* fix compile errors
* change directory name
* delete the duplicated directory
* update cmakelists file
* delete the unused codes
* update function names
* update transpose policy
* update code after remod.py
* update codes
* add some comment
* Polish the instr infrastructure
* build up the fixed instr
* redesign the transpose api, currently it has numerical error
* add the bf16 transpose
* fix some issues
* add some comments
* update document
* Finished the refactor of API and pass through the verification
* fix the merging issue
---------
Co-authored-by: ThomasNing <thomas.ning@amd.com>
* [CK_TILE] Support multi-config in tile_example_gemm_universal
Add GemmConfig in run_gemm_example to support multiple tile config.
- It is useful when use you need compare gemm perf with different tile/pipeline config
- we also can use it simplify the code for wmma support in the furture.
* [CK_TILE] Support multi-config in tile_example_gemm_universal
Address review comments
* rebase code and fix clang format.
* fix clang format
* support pipeline v5.
* fix merge conflict
* address review comment
* add missing file
* address review comment v2
* fix build error
* Do not use warpSize as compile time constant as it is removed
* Update tile_image_to_column_shape.hpp
update warpSize usage.
* clean-up all use of warpSize, make sure code builds
* fix
---------
Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>
Co-authored-by: illsilin <Illia.Silin@amd.com>
Co-authored-by: Bartlomiej Kocot <barkocot@amd.com>
* Multiple d, initial commit
* Check Ds Layout
* Readme and clang format
* Update branch & conflicts
* Multiple D - fix clang-formatter
* Rename elemetwise_op
* Fix CI
* Code review part1
* Remove printf
* Remove unnecessary comment
* Add new tests with Col layout
* Review part 2
* Added support for Multiple D GEMM
* Update comment
* Remove maybe_unused
* Clang-format
* Review part 3
* Add comment to function
* Add comment to function: another
* Take number of params for a refrence function
* Remove additional d param for 0 tensor
* Change name of function
* Fix CI fails
* - elevate important build messages to log level STATUS
- comment out the rest (temporarily)
* - marked all low importance build messages as log_level=DEBUG
* Add TailHandler for V3, V4 and Mem pipelines
* Adapt examples and tests to use TailHandler
* move tail-handling logic to pipeline in persistent grouped gemm
* Fix Mem pipeline dispatching, add CompV4 dispatching
* Use a macro for handling the many tails of Mem pipeline
* Fix formatting again
* Use const-ref RunFunction, remove unnecessary try_run
* Add constraint on traits/tile/pipeline
* Use kM0=128 if max_seqlen_q == 8192
* Re-format codegen script
* Remove redundant attr name postix
* Fix import error: default field in dataclass
* Use kK0=64 & kK1=64 to hide latency
* Use CU utilization to decide tile size
