GitLab

* (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>

Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>

* Add transpose scale amax example

* fixes

* Tune reduce instance

* Introduce combined elementwise ops

* Introduce refrence elementwise

* Extend available elementwise operations with conv examples

* Fixes

* Remove not needed convert

* Update CMakeFile and dir name

* Rename file. Prepare to support another activation

* Add comment for quantization

* Extract out_elementop

* Add tanh example

* Add conv + bias + tanh quantization instance

* Add missing parameter

* Refine cmake

* Add external api and client example

* Extract variable in example

* Fix the comment

---------
Co-authored-by: zjing14 <zhangjing14@gmail.com>

* Sync the order of type string with template parameter

* Add more instances

* Check the vector size and remove redundant var

* Extract var to static, prepare to separate sweep once kernel

* Separate sweeponce flow and optimize the flow

* 1. Rename AccDatatype in normalization to computeData
2. Rename AccElementwiseOperation to YElementwiseOperation in normalization

* Remove useless code

* Update naive variance kernel

* Refine string

* Fix typo

* Support naive variance for device_normalization

* Check the blocksize

* Share the VGPR of x and y

* Share the VGPR of gamma and beta

* Add more instances

* Support fp16 sqrt for experiment

* Add CHANGELOG

* Fix typo

* clang-format

* Add gemm + layernorm instance

* Add ckProfiler

* Add test

* Add client example

* Detect if user forger to set the workrspace

* Use literal in the example

* [What] use builtin function for sqrt
[Why] compiler will not use v_sqrt_f64_e64 if we use ::sqrt()

* check gemm vaildity in IsSupportedArgument

* Add more testcases

* Merge duplicated folder in client example

* Print more infomation

* Use better kernel parameter for MS problem size

* clang format

* Add constexpr for if condition and remove redundant include

* Remove cstdlib and add constexpr

* Let cmath included when compiling host codes in math_v2.hpp

* Remove including of cmath in device_base.hpp and device_permute.hpp

Co-authored-by: Chao Liu <chao.liu2@amd.com>

* Introduce int4 data type.

* Add unit-tests for int4

* Compile int4 UT only when int4 enabled.

* clang-format
Co-authored-by: Adam Osewski <aosewski@amd.com>

* ad gelu and fast_gelu

* added GeLU and fast GeLU

* clean up

* add gemm+fastgelu example

* add gemm+gelu instances

* update profiler

* clean up

* clean up

* adding gemm+bias+activation

* clean

* adding bias

* clean

* adding gemm multiple d

* debugging

* add gemm bias add fastgelu

* rename, clean

* refactoring; add readme

* refactor

* refactor

* refactor

* refactor

* refactor

* refactor

* fix

* fix

* update example

* update example

* rename

* update example

* add ckProfiler

* clean

* clean

* clean

* clean

* add client app example

* update readme

* delete obselete files

* remove old client app

* delete old file

* cleaning

* clean

* remove half

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path for all examples

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path

* revert client app example

* clean build

* fix build

* temporary disable client test on Jenkins

* clean

* clean

* clean

* Use the unified naming for math functions on host and HIP kernel

* Corresponding change/simplification in reduction host/profiler/examples due to unified math functions renaming

* Renaming GetReductionZeroVal() to GetIdentityValue()

* Tiny renaming in profile_reduce_impl.hpp

* More renaming in profile_reduce_impl.hpp

* Replace zeroVal by identiyVal

* Remove ck_ prefix in the naming of ck::math provided functions

* Add math functions for host

* Change to host reduction to use ck::math:

* Remove the using of half_float::half and half.hpp from reduction example/profiler/ctest

* delete obselete files

* move files

* build

* update cmake

* update cmake

* fix build

* reorg examples

* update cmake for example and test

* Initial adding of generic reduction

* Initial adding of generic reduction ...

* Updates to make compiling done

* clang-format all files

* clang-format some files again

* Renaming in profiler/include/profile_reduce.hpp

* Updates and make BlockWise cases passed

* Updates and make ThreadWise and MultiBlockTwoCall cases passed

* Remove the support for MUL and NORM1 reduceOp from the profiler and the device instances

* Change to replace the dim0_max_vector_size/dim1_max_vector_size template argument in the device reduce classes

* format

* adding pooling

* added max and average pooling

* comment out cout and kernel timing

* Tiny simplification in profiler/reduce_profiler.cpp

* Add example for reduce_blockwise

* Tiny updates

* Change to pass the ElementWiseOp from device layer to kernel

* Fix the vectorDim and vectorSize in Device layer

* Enable vector load on both dim0 and dim1 for Threadwise method

* Tiny updates

* Change to let the user to pass the preUnaryOp and posUnaryOp

* Make pooling example work

* split device_reduce_instance into two libraries

* Tiny update

* Replace nanPropaOpt enum by boolean propagate_nan

* Simplification in DeviceReduce layer codes

* update build

* Change to clarify the difference between ck::half_t and half_float::half

* Renaming in all the reduction codes

* Add VectorSize as template parameter for device layer

* Add BetaIsZero as kernel template and as AccDataType for alpha

* print

* Small updates for pooling

* Updates for host_generic_reduction for reference

* Update to make AVG pooling pass

* Update to make MAX pooling with indices output pass

* fix

* add OutDst vector store to threadwise reduction and pooling

* tweak

* turn off check_indices that caused build issue

* refactor pooling

* clean up

* turn off check_indices for building issue for php-compiler

* add more tile size for odd C

* tweak conv for odd C

* update script

* clean up elementwise op

* add hack in reduction_operator.hpp to avoid compile error. To fix it, need to use element_wise_op in reduction op

* Add OutVectorSize as device and kernel tunable, also update to Elementwise Operations

* Move reduce operator mapping to host layer file reduction_operator_mapping.hpp from reduction_operator.hpp

* Change to the unary operators

* Move the definitions of unary operations to element_wise_operation.hpp

* re-org files

* Refine in device interfaces and multiblock kernels

* Split the reduction configurations into instances for specific methods

* Update in getTypeString() of device pool2d

* Renaming in host and kernel

* Tiny update in profiler/src/profiler.cpp

* Uncomment in device_operation/CMakeLists.txt to enable the building of all operations

* Make check_indices a templated function to remove some linking issue

* Renaming in the profiler reduce module

* Add support for double Reduction (but disable MultiblockAtomicAdd for double)

* Tiny correction of literal string

* Rename DevicePoolFwd to DevicePool2dFwd

* Split device_reduce_instance_xxx.cpp files according to the data types to speed up compiling

* Add comments for lists of configurations, lists of instances and references of add_reduce_instances_xxx

* Remove un-used header file gridwise_generic_reduction_wrapper_common.hpp

* Renaming and refining in the Reduction codes

* Tiny change in the unary operators

* Renaming symbols and files

* Renaming symbols in the kernels

* Move kernel kernel_set_buffer_value to separate file

* Add IndexDataType template parameter for kernels and use int32_t as index data type in device layer

* Tiny update in the kernels

* Remove definition of sqrtf()/isnan()/abs() for half_t due to some ADL issue

* Simplify a helper function in device layer

* Tiny adjustment in testing data initialization

* Renaming in kernel/device/host

* Add two testing scripts for reduction

* Refine the Unary operators in element_wise_operation.hpp

* Update in the reduce profiler module

* Update to the reduction testing scripts

* reduce compile parallelism

* change CI docker to rocm5.0

* remove unused variables

* fix build
Co-authored-by: Chao Liu <chao.liu2@amd.com>