* (2/5) bilinear gemm pass, perf bug: skip a lds has lower performance than skip b lds
* (3/5) batched gemm pass, perf bug: skip a lds has lower performance than skip b lds
* (4/5) grouped conv pass
* (5/5) attention pass, todo: debug lds perf bug
* AIT Attention API refactor (#8)
* sanity pass
* sanity pass 2
* confirm significant performance regression.
* turn on all instances
* turn off instance format
* Fix bug & tunning & format
* DML meta, self_attn+cross_attn
* sanity pass
* remove useless flag
* update tile and problem size used in AIT attention
* bug fix in grouped conv supporting check
* deprecate inline asm wmma
* Bug fix: double lds skip
* clang-format
* Fix errors in
1. example, fmha
2. gridwise pipeline
3. deviceop, fmha, change some containers from vector to array
* part2 of previous commit
* clang format
* API fix of gridwisegemmpipeline
* separate array base and vector base attention tensor transformation
* fix gemm
* clang format
* add gemm fp16 instances
* Temp save
* fpAintB kernel compile pass
* Sanity pass.
* Temp save
* debug code enabled
* Fp16AInt8B_GEMM sanity
* MQA implementation
* GQA-4 example
* tempsave
* Compile pass
* New implementation of fp16Aint8B Gemm, Acheieve similar math throughput with native fp16 Gemm
* Bump rocm-docs-core from 0.24.0 to 0.29.0 in /docs/sphinx
Bumps [rocm-docs-core](https://github.com/RadeonOpenCompute/rocm-docs-core) from 0.24.0 to 0.29.0.
- [Release notes](https://github.com/RadeonOpenCompute/rocm-docs-core/releases)
- [Changelog](https://github.com/RadeonOpenCompute/rocm-docs-core/blob/develop/CHANGELOG.md)
- [Commits](https://github.com/RadeonOpenCompute/rocm-docs-core/compare/v0.24.0...v0.29.0)
---
updated-dependencies:
- dependency-name: rocm-docs-core
dependency-type: direct:production
update-type: version-update:semver-minor
...
Signed-off-by: dependabot[bot] <support@github.com>
* initial enablement of gfx950
* fix clang format
* disable examples 31 and 41 int8 on gfx950
* initial navi4x enablement
* remove extra endif
* enabled dl_gemm
* update s_barrier and s_waitcnt for gfx12
* fix the gfx12 assembly syntax
* fixed block_sync_lds
* add support for more dl kernels on navi4
* add wmma
* format
* Todo: fix gemm_bilinear_wmma instances compilation bug
* Solve a bug when K1=16
* remove unnecessary changes
* Remove tensor layout limitation to LDS usage in tesnor contraction
* fixed block_sync_lds
* merge navi3_ref
* update self-attention and cross-attention
* fix a typo of name
* fixed layout
* debugging
* Add arch limiter for fp8 gemm
* fixed wmma
* enable fp8 gemm_xdl for all gfx9 targets
* temporarily disable gemm_xdl_fp16_fp8 on MI100/200
* fix the cmake logic for gemm_xdl_fp16_fp8
* fixed c_output
* re-enable the gemm_xdl_fp16_fp8 on MI100/200
* fixed gfx12
* fixed
* fixed
* seperate gfx12 blockwise_gemm
* fixed
* enable fwd conv on navi4x
* enable gridwise
* enabled gemm
* fixed merge
* remove empty example fold
* fixed conflicts
* some small changes
* Update cmake-ck-dev.sh
* Update cmake-ck-dev.sh
* enabled other types
* fixed register loads
* test fa
* enable gfx12
* clean up
* enable some instances on gfx12
* add gfx1201 macro in amd_wmma header
* fix clang format
* enable batched_gemm_softmax_gemm_perm_wmma for gfx12
* disable instances with blocksize=256 in attention examples
* debuggging
* debug
* fixed lds_enabled
* debugging
* Fix and add limit to skiplds feature
* Enable skipLds feature and fix compilation bugs
* add ck_tile definitions for gfx12
* fix clang format and test/wmma_op
* updage instances cmake for gfx12
* disable the test_wmma_op on gfx12
* fix the builds for gfx950
* add gfx12 and gfx950 to default target list
* clean-up cmake file
* Initial introduction of OFP8 data types.
* Renamed FP8 and BF8 tests into FP8_FNUZ and BF8_FNUZ.
* Implementation of ConvertFP32Nearest in test_fp8_ocp.
* Remove dependence on possibly undeclared alias.
* Implement FP8OCP test for stochastic rounding mode.
* Implement FP8OCP tests for half_t type conversions.
* enable bf16 atomic add on gfx950
* Implement ConvertFP32Nearest test.
* Implement ConvertFP32Stochastic test.
* Implement ConvertFP16Nearest and ConvertFP16Stochastic tests.
* Refactoring. Move FP8 definitions into a separate header file.
* Enable easy switching between architectures.
* Fix compilation error for gfx942 architecture.
* only builf gfx950 branch for gfx950 target by default
* Enable OCP build of example_gemm_xdl_fp8.
* Fix formatting.
* fix the build logic for gfx950
* Improve GEMM example verbosity.
* Add constexpr where applicable.
* fix the logic of enabling XDL and WMMA instances
* Improve GEMM example verbosity.
* Enable build of example_gemm_xdl_fp8_bf8 test.
* Fix tests for gfx1101 architecture.
* Build DPP examples only on gfx103 and gfx11 architectures.
* Optionaly run either CPU or GPU verifications with GEMM examples.
* Extend GeneratorTensor_Sequential to produce values of prescribed data types.
* Add missing constructor.
* Improve infrastructure for OFP8 data type support.
* BUGFIX. Should not use FP8 as Compute/Accum data type.
* Add custom target for grouped_convnd_bwd_weight tests.
* Can build `tests` target on gfx950.
* Bugfixes on gfx1101 architecture.
* Fix dependencies.
* Provide single point of truth for FP8 INF and NAN checks
* Prevent instantiation of operators that are not supported by FP8 data types
* Add FP8 type selection into client_axample CMakeLists.txt
* Prevent sccache server from shutting down during build
* Fix test success reporting logic
* Change default verification method to CPU.
GPU verification takes too much time to complete on the emulator.
* Make sure all tests and examples are built for gfx950
* Facilitate testing of FP8 data types on the emulator
* Introduce two new tensor generators
* Enable instances built for gfx94 to be built on gfx950
* Verify 35_splitk_gemm on floating point numbers.
splitk gemm appears to be losing precision VS reference implementation when FP numbers are involved.
* Verify 04_gemm_add_add_fastgelu on floating point numbers
* Verify 20_grouped_conv_bwd_weight on floating point numbers
* Verify 38_grouped_conv_bwd_data_multiple_d on floating point numbers
* Verify more tests on floating point data
* Fix data types and improve testing verbocity.
* Upgrade to NPI 573 build docker.
* Skip on gemm_universal tests.
The tests take too long to complete on the emulator.
Need to see if it is possible to reduce the scope of the testing to just FP8 data types.
* Fix gfx1101 build
* Document test availability
* Re-enable fp8 gemms for gfx94/95
* Cherry-pick GEMM Universal tests for FP8 data types
* Cleanup
* CK_USE_GFX94 has already been set on this branch
* Address formatting issues and leftovers
* Make fail/pass logic consistent within 01_gemm folder
Removed multiple negations in fail/pass logic to propagate `true` as the success indicator.
* Fix GPU verification reporting logic.
* Update year in copyright notice.
* Cleanup
* Use `enum class` instead of `enum`
* Remove set_property for FP8 tests
* Narrowing the scope of PR to OCP FP8 enablement only
* Add tests for OCP FP8 vector_type storage
* Enable gemm kernel on all gfx9 architectures (#227)
* clean-up
* Implement `non_native_vector_base` with `ext_vector_type` array. (#232)
* Enable support of 1, 2, 4, and 8-byte custom types in CK.
* Fix pool tests for OCP FP8 data type
* fix jenkins file
* restore cron trigger
---------
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: aska-0096 <haocwang@amd.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Jing Zhang <jizhan@amd.com>
Co-authored-by: zjing14 <zhangjing14@gmail.com>
Co-authored-by: Jun Liu <Liu.Jun@amd.com>
Co-authored-by: Andriy Roshchenko <andriy.roshchenko@amd.com>
Co-authored-by: Andriy Roshchenko <107577548+andriy-ca@users.noreply.github.com>
* 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.
* 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
* Calculate generic relative threshold pool3dfwd
* Calculate absolute error threshold pool3d fwd
* Generic threshold calculation take max input for relative error pool3dfwd
* Remove max possible value for error calculation at runtime
* Remove debug print in pool3dfwd
* Pool3d fwd adjusted types in generic threshold calculation
* Generic threshold calculation take into account number of accumulations and accdatatype
* Generic threshold fix final error formula
* Generic threshold calculation - num of accs fix
* Generic threshold calculation - adjust absolute error
* Generic threshold calculation - OutDataType in absolute error
* Add a gpu gemm reference kernel
* Switch to gpu reference in gemm examples
* Remove redundant arguments
* Update all related examples
* Update more examples
* Try less threads per block
* Try even less threads per block
* Add support for all matrix layouts
* Increase block size
* Clean up
* Remove hardcoded strides
* Clean up
* Try a column-major case
* Revert back to row-major
* Run both CPU and GPU veriffication
---------
Co-authored-by: Po Yen Chen <PoYen.Chen@amd.com>
* revert ckprofiler change
* temp save
* Add test and test pass
* test pass
* Fix bug inside rotating buffer when tensor is not packed
* bug fix
* clang format
---------
Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>
* Enable CMakePresets build
* Verify Convolution, Scaling and ReLU algorithms.
* Add tensor element-wise scale and type cast operation.
* Reduction implemented but does not work.
* Exploration of Reduction functionality.
* Completed example for Convolution scaled with ReLu activation and AMAX reduction.
* WIP: Add required instances for convolution.
* WIP: Create client example. Implement convolution stage.
* Add elementwise instances.
* Add elementwise scale + convert example.
* Add reduction instances.
* WIP: Client example for AMAX reduction.
* WIP: Add instances for multistage reduction.
* WIP: Implementation of multistage reduction.
* Refactoring.
* Clean up.
* Add CMakePresets.json
* Guard off FP8 instances when the data type is not available.
* Add example for Scaled FP8 Convolution with AMAX reduction.
* Refactor CombConvScaleRelu instances.
* Add CombConvScale instances.
* Add client example for Scaled FP8 Convolution with AMAX reduction.
* Cleanup.
* Set RNE fp8 conversion as a default
* Update f8 tests
* Disable failing test on gfx11
* Update bf8 tests
* Add a flag
* Fix the flag
* Raise flag for gfx10 as well
* Temp commit for tolerance testing
* Update tolerances
This fixes 2 issues when compiled with libc++.
First issue is attempt to call std::numeric_limits<ranges::range_value_t<_Float16>>::min().
_Float16 is extension of libstdc++, it does not exist in C++ standard[2].
Luckily, there is NumericLimits class in composable_kernel, which does everything needed.
Second issue with call to 'check_err' is ambiguous: there are 2 candidates.
It happens because composable_kernel relies on idea that f8_t (defined as _BitInt(8)) does not pass is_integral trait.
However, libc++ treats _BitInt(N) as integral (per standard "any implementation-defined extended integer types" can be integral).
Closes: #1460
Signed-off-by: Sv. Lockal <lockalsash@gmail.com>
* Support 64 bit indexing
* Add new grouped conv fwd kernel for large tensors
* Add instances large tensor
* Fixes for transform conv to gemm
* Fixes
* fixes
* Remove not needed instances
* examples fixes
* Remove not need ds arrays
* Fix tests
* Add 2GB check in gridwise dl
* Fixes
* add ab_scale init support
* enabled interwave
* add scale type; update isSupport
* adjust example
* clean
* enable f8 pure gemm rcr ckprofiler
* Add gemm_multiply_multiply instances
* clang format
* Optimize for ScaleBlockMNK=128
* enable abscale f8 gemm ck profiler
* Add pure f8 gemm test suite
* Reverting to the state of project at f60fd77
* update copyright
* clang format
* update copyright
---------
Co-authored-by: root <jizhan@amd.com>
* init for reduce_threadwise multi_d
* add reduce_threadwise_multi_d
* add reduce_multi_d
* clean
* start add an other splitk device op
* add reduce template parameter to SplitKBatchOffset
* add reduce c matrix
* clean up code
* change example data type to bf16
* add bf16Ai8B example
* remove reduce template parameter
* add splitk atomic status to v4
* example add multi d parameters
* device op add multi-d parameters
* add multi-d to reduce
* fix kbach=1 bug
* change B layout to col in bf16Ai8B example
* remove float adding struct
* change multi-d interface
* change file and class name
* remove multi-d of bf16Ai8B example
* change IsReduce function to IsReduceAdd
* change example layout to RRR from RCR
* according layout to set ds stride
* reset parameter layout
* add gemm universal reduce instance
* add reduce factory
* add profile_gemm_universal_reduce
* add reduce to profiler
* fix reduce instance
* fix profiler reduce compiling bug
* format
* format library instance code
* add mem instance for reduce library
* fix call instance names
* add workspace for reduce in ckProfiler
* format
* add mnpading to reduce library instance
* add fp16 instance to reduce of profiler
* change copyright time
* restore profiler cmake file
* add reduce text to instances
* add DsLayout and DsDataType to instances template parameter
* fixed gemm_reduce_multi_d
* add an example without multi_d
* Update common.hpp
* Update gtest.cmake
* Update gemm_xdl_splitk_reduce_bf16.cpp
* clean
* Update gtest.cmake
* format
* fixe api
* format
* default parameter change to RRR
* add vector_len for multi_d
* format
* Update gtest.cmake
* fix bf16A iBB elementwiseop
* add ReduceDataType
* move ReduceDataType to end position
* format
* remove googletest git method address
* fix copyright time
* update init data
---------
Co-authored-by: root <jizhan@amd.com>
Co-authored-by: letaoqin <letaoqin@amd.com>
Co-authored-by: Jing Zhang <jizhan@meta.com>
Co-authored-by: zjing14 <zhangjing14@gmail.com>
* Add CMakePresets configurations.
* Add ConvScale+ReLU Functor and an Example
* Account for ReLU FLOPs.
* Add instances of 3D convolutions with ConvscaleRelu operation.
* Implement Client Example
* Cleanup
* universal streamk with atomics with ckprofiler support. grid_size and streamk strategy are tunable. grid_size of -1 leads to #WGs = maximum occupancy X num_CUs. implementation supports many different streamk policies: 1-tile, 2-tile, 3-tile and 4-tile. streamk strategy of -1 leads to default streamk policy (4-tile).
* Update README.md
* fixing clang-format issues
* removed conflicts in struct members between streamk and universal streamk
* corrected arg parsing for streamk and universal streamk
* added stream-k policies for 3 tile and 4 tile
* fixed argument type issue with parsing cmd args
* changes suggested in PR review are made- removing comments and correcting copyright
* file permissions updated
* added default value support for grid_size and streamk-policy selection set to -1
* print messages for arguments
* print messages for arguments
* print messages for arguments1
We are adding more instances of grouped convolution 3d forward with a ConvScale element-wise operation.
This commit handles bf8@bf8->fp8 data types combination.
* Included an example.
* Added instances.
* Added a client example.
---------
Co-authored-by: Rostyslav Geyyer <rosty.geyyer@amd.com>
Co-authored-by: Bartłomiej Kocot <barkocot@amd.com>
* Update the element op
* Add an example
* Add instances
* Add a client example
* make sure new instances only build on gfx9
* Update element op and its handling
* Format
* Update instances to take element op as an argument
* Update examples to use random scale values
* Format
* Update client example with random scales
* Format
---------
Co-authored-by: illsilin <Illia.Silin@amd.com>
