* 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.
* 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
* 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.
* 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
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>
* Add a scale op
* Update the element op
* Add instances
* Add an example
* Add a client example
* Add a flag check
* Revert flag check addition
* Fix flag check
* Update d strides in example
* Update d strides in client example
* Apply suggestions from code review
Update copyright header
Co-authored-by: Bartłomiej Kocot <barkocot@amd.com>
* Move the example
* Move the client example
* Update element op
* Update example with the new element op
* Add scalar layout
* Update example
* Update kernel for scalar Ds
* Revert kernel changes
* Update element op
* Update example to use scales' pointers
* Format
* Update instances
* Update client example
* Move element op to unary elements
* Update element op to work with values instead of pointers
* Update instances to take element op as an argument
* Update examples to use random scale values
---------
Co-authored-by: Bartłomiej Kocot <barkocot@amd.com>
* Overload output stream operator for LoopScheduler and PiplineVersion
* Add Run overload accepting grid descriptors MK.
* Add __device__ keyword for CalculateGridSize
* Create device op GroupedGemmMultipleD
* Add GroupedGemm MultipleD Tile Loop implementation.
* Add an example for GroupedGemm MultipleD tile loop.
* Device Op GroupedGEMMTileLoop.
* Bunch of small changes in exmaple.
* CkProfiler
* Remove unused tparam.
* changed the copy function to v7r2
* adding multi_abd
* in-progress
* add post-load oob check
* Fix include statement.
* Fix output stream overloads.
* Do not make descriptors and check validity untill we find group.
* Fix gemm desc initialization.
* debugging
* adjust instances
* add run_lds
* add elemntwise_op
* replace multi_abd_device with v3
* clean up
* clean
* clean
* Revert device op
* Fix compilation for DTYPES=FP16
* Validate tensor transfers paramters.
* Added LDSType
* profiling
* adjust oobcheck
* add missing file
* Validate on host only NK dims if M is not known.
* add
* clean
* refactor
* clean
* add examples
* add fuse
* add fusion and client example
* Fix bug.
* A convenient debug func for selecting threads.
* Fix has main k block loop bug.
* Make sure that b2c has up to date tile offset.
* Output stream operator for Sequence type.
* Cmake file formatting.
* clean
---------
Co-authored-by: Adam Osewski <Adam.Osewski@amd.com>
* Refactor elementwise kernels
* Instances fixes
* Fix cmake
* Fix max pool bwd test
* Update two stage gemm split k
* Restore elementwise scale for hiptensor backward compatiblity
* Fix Acc data type check in conv fwd multiple abd
* Disable conv fp64 fwd example
* Update grouped conv weight multi d
* Update device op api to support BComputeType
* Add example
* Add instances
* Add profiler mode
* Add client example
* Update copyright year
* Add BComputeType check
* Fix compute types
* parse examples inside the add_example_executable function
* fix the example 64 cmake file
* add xdl flag to the gemm_bias_softmax_gemm_permute example
* add filtering of tests based on architecture type
* enable test_grouped_gemm for gfx9 only
* enable test_transpose only for gfx9
* only linnk test_transpose if it gets built
* split the gemm instances by architectures
* split gemm_bilinear,grouped_conv_bwd_weight instances by targets
* split instances by architecture
* split grouped_conv instances by architecture
* fix clang format
* fix the if-else logic in group_conv headers
* small fix for grouped convolution instances
* fix the grouped conv bwd weight dl instances
* fix client examples
* only enable client examples 3 and 4 on gfx9
* set the gfx9 macro
* make sure the architecture macros are set by cmake
* use separate set of xdl/wmma flags for host code
* sinmplify the main cmake file
* add conv_fwd_bf8 instance declaration
* rename folder
* Add type string
* Remove typo
* Add deviceOp to backward x
* Add comment to describe the behavior of backward normalization
* Add kernel function, prepare to implement
* implement generic kernel
* Check vector size
* Add sweep once pipeline for small reduce size
* Fix bug of KRaw_ error
* Fix bug of dx stride
* sanity check for mean and rstd
* backward x for groupnorm
* Add bwd x instance
* add layernorm 2d bwd gamma beta instances
* Change save mean var type from f32 to f16 in f16 mode
* Change the example to f16
* Add groupnorm bwd gamma beta instance
* Add groupnorm bwd x instance
* Fix naming
* Add layernorm bwd x ckprofiler
* Add groupnorm bwd x profiler
* clang format
* Rename bwd x to bwd data
* Fix bug of verification in profiler
* Add test of layernorm and groupnorm bwd data
* Add missing cmake
* Add layernorm2d bwd data
* rename fwd example
* Add groupnorm client example
* Fix typo. replace Invarient with Invariant
* Add checking before running the best instance
* spolit the static library into several
* update lib paths and fix client example
* do not use device_mha_operarions for client examples
* use appropriate libs to link to client examples
* remove the gpu/transpose path from the list
* try fixing clinet examples 3,4,9
* add necessary libs for client examples
* fix the layernorm client example
* fix the client examples 23 and 24
* fix typo
* add interface library and refresh clang format
* Introduce multiABD api and deprecate multiD
* Replace multiD with multiABD
* Mark structures as deprecated
* Change doxygen deprecated to note to avoid warnings
* Support multi AB for grouped conv fwd xdl
* Add instances
* Add client example
* Add example
* Add interface test
* Minor fixes
Minor fixes
Minor fixes
* Comment fixes
* Fixes
* Reference fix
* Test xdl fixes
* Improve multi_ab interface test
* added working example for 5D input using 1D kernel
* example with 5D input tensor and 2d kernel - not working: issues with arguments
* added updated version of 3d device op - changed descriptors/dims
* added example file to check kernel
* fixed descriptor and isSupportedArgument stride problem
* added and modified kernel for 3d - updated tids/loop
* adding some more 5d example files
* fixed some issues
* changes made for testing
* working version: fixed error in stride for A, still a bit inefficient
* cleaned up formatting/comments
* updating formatting
* more formatting fixes
* fixing cmake, adding back gpu targets in cmake script
* adding client example
* added instances for client example
* fixed errors in client example
* implemented client ex with device_elementwise.hpp and device_elementwise_3d_impl.hpp
* removed extra files
* minor formatting and naming fixes
* adding test files and profiler
* fixing minor error
* minor fix
* removed unneccesary comments, renamed files
* updated instance list for client example, added different layout example
* removing instances
* fixed error in instance generation
* remove comments
* update profiler and client example tensor layouts
* fixed errors in test/profiler
* updated vector dim access to enable vector load
* updated test/profiler files
* updated example with 1d kernel
* updating profiler
* renamed files
---------
Co-authored-by: Jing Zhang <jizha@amd.com>
* Rename folder
* Add layernorm 4d fwd example
* Rename original layernorm example
* Add layernorm 4d f16 test
* Add layernorm4d_fwd client example
* Support layernorm4D in ckProfiler
* Rename groupnorm to groupnorm fwd in example
* Rename layernorm and group fwd in test
* Rename normalization to normalization_fwd (instances)
* Add fwd to DeviceNormalization
* Rename external api header
* Rename folder, because we can also add bwd in this folder
* Add fwd in layernorm and groupnorm (profiler
* Fix compile error
---------
Co-authored-by: Po Yen Chen <PoYen.Chen@amd.com>
* save mean and inverse std in normalization
* Save mean and inverse std in splitK
* Vector save mean and inv std
* Modify instance for save mean and std
* simplify the layernorm example
* Save mean and std in groupnorm example
* Save mean and inv std in ckProfiler and test
* Remove compute data type from base class
* Save mean and inv std in client example
* Add changelog
* clang format
* Fix compile error
* Refine naming
* Avoid error in bf16
* revert changelog
