* memory op changes
* memory op changes
* Fixing TILE_ENGINE_BASIC in Tile Engine
* Removing gfx90a from Tile Engine Run
* [CK TILE ENGINE] increasing ci configs for BASIC case
* Setting RUN_TILE_ENGINE_BASIC_TESTS to ON by default
---------
Co-authored-by: Max Podkorytov <4273004+tenpercent@users.noreply.github.com>
* solve compiler issue
* solve the gfx950 mfma shuffle regression
* refactor jenkinsfile to handle arch name better
* [CK TILE] set divisor to count of thread along k dimension
* fix the compiler error
* solve degradation
* Finish the multiplies fix
* fix the scales
* solve compilation error
* solve the composes
* solve the error of tile sweeper
* fix the test and example
* fix for gfx950
---------
Co-authored-by: Max Podkorytov <4273004+tenpercent@users.noreply.github.com>
Co-authored-by: illsilin_amdeng <Illia.Silin@amd.com>
Co-authored-by: Cong Ma <congma13@amd.com>
* Add placeholder test.
* Initial conv bwd weight factory.
* Conv builder test refactoring.
* Add missing pieces to bwd weight factory.
* Improve compile time erros message when no matching factory is found.
* Use amcro to ensure automatic macthing between concepts are their string representations.
* Improve compile time diagnostics.
* Small improvements.
* Improve missing member/wrong type compile-time errors.
* Improve compile time diagnostics.
* Concept bug fixes.
* Remove debug assert.
* Update algorithm signature diagnostics.
* Factory bug fixes.
* First functional version of bwd weight conv factory.
* Refactor handing of GEMM-K batch template parameter in conv bwd weight factory.
* Concept improvements.
* Improve concept diagnostics.
* Introduve a common size type for concepts.
* Update compiletime diagnostics to use the size type.
* Update conv specialization enum.
* Fix fwd conv builder tests.
* Fix smoke tests.
* Separate bwd weigth and bwd data tests into separate targets.
* Clean-up CK Tile builder tests.
* Add bwd weight XDL CShuffle V3 factory.
* Build conv bwd weigth v3 instances successfully.
* Add instance traits for DeviceGroupedConvBwdWeight_Xdl_CShuffleV3.
* Test fix.
* Add instance traits for bwd weight algorithms.
* Add unit tests for instance strings.
* Build new instance traits unit tests but exclude WMMA for now.
* Added factory for DeviceGroupedConvBwdWeightTwoStage_Xdl_CShuffle.
* Conv bwd weight DL factory.
* Final implementation for bwd weight DL factory.
* Add test for creating DeviceGroupedConvBwdWeightMultipleD_Xdl_CShuffle instance.
* Add factory for DeviceGroupedConvBwdWeightMultipleD_Xdl_CShuffle
* Treat ref algorithm the same way as real algorithms in the dispatcher.
* Refactor large tensor support and WMMA configuration.
* Add factory and tests for DeviceGroupedConvBwdWeight_Wmma_CShuffleV3.
* Update Readme.
* Fix WMMA bwd weight tests.
* Added factory and tests for DeviceGroupedConvBwdWeightTwoStage_Wmma_CShuffleV3.
* Factory and tests for DeviceGroupedConvBwdWeight_Wmma_CShuffle.
* Dispatching for DeviceGroupedConvBwdWeightMultipleD_Wmma_CShuffle.
* Add factory for DeviceGroupedConvBwdWeightMultipleD_Wmma_CShuffleV3
* Fix DeviceGroupedConvBwdWeightMultipleD_Wmma_CShuffleV3 factory and compute types for input and output tensor in bwd weigth convs.
* Fix fwd factories after refactoring.
* clang-format
* Move compile-time diagnostics to a separate branch.
* Fix ref algorithm dispatching.
* Fix smoke tests.
* clang-format
* Fix factory for regular WMMA conv bwd weight.
* Clarify builder Readme.
* Remove obsolete test file.
* Fix test after merge.
* clang-format
* Remove the C++26 extensions.
* Unify conv elementwise ops and layout definitions for fwd and bwd directions.
* Remove old layout and elementwise ops.
* Unify handling of conv tensor types between fwd and bwd directions.
* Unify block transfer for fwd and bwd directions. Rename ThreadSliceDim to ThreadClusterRank.
* Make BlockTransferDescriptor concept parametrized. Introduce a common TileTransferParameters concept for conv algorithms.
* clang-format
---------
Co-authored-by: Ville Pietilä <>
* feat: grouped gemm tile loop support for RDNA4
* fix: removed extra parameter from grouped gemm example instance
* fix: FP8 check incorrectly enabling FP8 on RDNA3
This commit addresses numerical stability issues in the BlockFmhaPipelineQRKSVS pipeline when bias has -inf masking values:
1. Explicitly handle the case where the accumulated exponential sum (l) is zero. In this case, the LSE is now correctly set to negative infinity, preventing log(0) errors.
2. Extend the zero-check protection in the normalization step to cover the ELEMENTWISE_BIAS case, preventing potential division by zero.
- Enable page_size=1 support in batch prefill codegen (linear layout only).
- Implement per-token page lookup in `kv_offset_array_transform` for page_size=1 to handle 3D input tensors correctly.
- Relax `kPageBlockSize` alignment assertion for the page_size=1 case.
* refactor: remove Default scheduler implementation as it not used anymore
* refactor: remove dead code from gemm universal kernel
* chore: add descriptive comments about amd intrinsic hardware sync instructions
* fix: label existing memory pipeline for aquant as intrawave
This adds some utilities to automatically generate UniqueInputs,
UniqueOutputs, alloc_inputs, alloc_outputs, and validate, based
on a Inputs::reflect() and Outputs::reflect().
* nt on fp8 blockscale
* some improve and tests needs to be fixed
* update
* fix format
* revert useless change
* revert any change in amd_buffer_coherence
* WIP
* Add Unit tests for the Multi Reduction Kernel
* clang format
* Rename multiblock to threadwise
* Multiblock WIP
* Fix multi reduce multi block unit tests
* Multi Reduce Tile Engine: WIP
* refactoring + try addressing precision error
* Fix multiops examples
* Cleanup
* Clean up tile engine's reduce op
* Update changelog
* Fix remod/clang
* Fix dates
* Fix documentation & missing file
* Fix comments
* Use the update_tile api in the multi-block kernel
* Unify threadwise/multiblock into a single kernel + default multiblock output to float in tests
* Add TileParitioner
* Cleanup
* Add warning when no data to process, in the example
* Refactoring Reduce kernel Tile Partioner + cleanup
* Move the tile partioner to its own file
* Add missing includes
* Fix copyright header with update_amd_copyright_headers.py
* Fix change of interface in Reduce2dProblem
---------
Co-authored-by: Damien Lejeune <damien.lejeune@amd.com>
Co-authored-by: Adam Osewski <19374865+aosewski@users.noreply.github.com>
* ck-builder: make toString to_string
We are using snake case for CK-Builder
* ck-builder: add debug.hpp with tensor descriptor printing function
This adds some initial functionality to debug.hpp, a header which will
be used to house some debug utilities.
* ck-builder: abstract nd-iteration
Abstracting this makes it easier to test, clearer, and allows us to
use it elsewhere (such as in debug.hpp soon)
* ck-builder: tensor printing
* ck-builder: rename INT32 to I32
This makes it more in line with the other data type definitions.
* Take split_k into account when checking 2GB tensor limit.
* Revert "Take split_k into account when checking 2GB tensor limit."
This reverts commit adf35c91be.
* Optimize grouped conv bwd wei split_k off calc
(cherry picked from commit 6f61dd56c5)
* Update gridwise_gemm_xdl_cshuffle_conv_v3.hpp
(cherry picked from commit b33877c10f)
* Fix tensor descriptors and stride calculations
* Don't miss half of the elements
* Fix buffer size calculations
* Disable hack if stride not divisible by k_batch
* Clean up comments
* Disallow hack in non-contiguous edge cases
* Index -> Dim
* Fix broken test
* Refactor applicability checks into separate function
* fix missed variable name
* Fix variable name in info print
* update V3 2GB check
* No more regression, use templates instead
* Code deduplication
* Regression fix for cshuffle
* arch-guarded atomic_add implementations for gfx11
* Similar for half(4|8)_t as well
* Only use both offset hacks at the same time
* Revert "arch-guarded atomic_add implementations for gfx11"
This reverts commit 3883fe6935.
This reverts commit 5311ec608d.
* Reapply "arch-guarded atomic_add implementations for gfx11"
This reverts commit 1972adeddc.
* Only remove float4 atomic_add
* Refactor to single flag
* Consolidate template parameters
* Consolidate flag in transformers
---------
Co-authored-by: Bartlomiej Kocot <barkocot@amd.com>
* Implement grouped gemm fastgelu for RDNA4
* chore: some cleanup and minor inconsistencies in grouped gemm profiler
* chore: clarified logic and reporting of supported instance warnings
Our concept-base conversions are fragile and too complex. We want to refactor to straightforward functions
for each intance trace class template. This change adds unit test coverage to make that refactoring safer.
Refactor function amd_buffer_load_invalid_element_return_zero to avoid
the inefficient ASM code generated by compiler.
Compiler generates suboptimal assembly for ternary operator, causing excessive VGPR usage
Tested compilers:
- Rocm 7.0.1
- Rocm 7.1.1
Co-authored-by: Thomas Ning <Thomas.Ning@amd.com>
* update grouped_gemm blockwise kernel
* update config
* update kernel
* update examples
* remove test code for now
* sync test files with origin/develop
* update example
* fix code lint
* fix code-lint
* update test code
* run clang format
* run pre-commit
* update api
* ck-builder: explicitly delete forward declarations
Before, these functions were seen as a forward declaration for an existing function.
If no actual implementation overload could be found, these would be selected and
a linker error or warning would be generated. By marking these functions as explicitly
deleted, they incorrect invocations are generated as compile error instead.
* ck-builder: ckt::run plumbing for reference conv
This implements the ckt::run plumbing for the reference convolution
implementation and sets up the first complete end-to-end test.
* ck-builder: make validation system check for all-zeros
When both the actual and reference output are both all zero bits,
there is probably something wrong in the test framework.
* ck-builder: proper implementation+tests for TensorDescriptor::is_packed
* ck-builder: fix typos
* [CK_TILE] unify double and single lds implementation (#108)
Unify LDS buffer management API for single and double buffering modes
This change consolidates the Local Data Store (LDS) buffer management by:
Merging single and double LDS buffer APIs into a unified interface
Implementing ping-pong address calculation in pipeline when double LDS is enabled
Computing pong buffer addresses dynamically using base address offsets
---------
Co-authored-by: joye <joye@amd.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* update wp_pipeline
* fix a c++17 issue
* update for ci errors
* fix ci issues
* include a header to fix ci errors
* fix some rebase issues
* update with rebase
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
This pull request builds on #3267 by proving the "validation" infrastructure, the means to compare a set of `Outputs`.
The design of the validation infrastructure is relatively straight forward:
- Each SIGNATURE should come with a `validate()` implementation, which should be implemented in a similar way that the other functions/types from `testing.hpp` are implemented.
- `validate()` returns a `ValidationReport`, which is a structure that keeps all relevant information about comparing the tensors from two `Outputs`. Note that crucially, `validate()` should not do any reporting by itself. Rather, glue logic should be implemented by the user to turn `ValidationReport` into a relevant error message.
- You can see this clue code for CK-Builder itself in `testing_utils.hpp`, its `MatchesReference()`. This functionality is relatively barebones right now, it will be expanded upon in a different PR to keep the scope of this one down.
The comparison is done on the GPU (using an atomic for now), to keep tests relatively quick. Some notable items from this PR:
- To help compare the tensors and with writing tests, I've written a generic function `tensor_foreach` which invokes a callback on every element of a tensor.
- For that it was useful that the `TensorDescriptor` has a rank which is known at compile-time, so I've changed the implementation of `TensorDescriptor` for that. I felt like it was a better approach than keeping it dynamic, for multiple reasons:
- This is C++ and we should use static typing where possible and useful. This way, we don't have to implement runtime assertions about the tensor rank.
- We know already know the rank of tensors statically, as it can be derived from the SIGNATURE.
- It simpifies the implementation of `tensor_foreach` and other comparison code.
- There are a lot of new tests for validating the validation implementation, validating validation validation tests (Only 3 recursive levels though...). For a few of those functions, I felt like it would be useful to expose them to the user.
- Doc comments everywhere.
* add page_block_size parameter
* add is_sglang_layout to parameters
* add kv_offset_array_transform to batch async for page size 16
* add kv_last_page_lens to kernel
* change kv layout to [num_total_pages, page_block_size, hdim]
* format
* - enable codegen of batch_prefill kernels
- create new problem struct BlockFmhaBatchPrefillPipelineProblem for
batch prefill kernels
- generate different page sizes of batch prefill kernels (1, 16)
* 1. fix wrong calculation of page id in kv_offset_array_transform in gfx950
2. support page size 1024
* fix python format
* change kv cache layout to [num_blocks, num_kv_heads, head_size/x,
block_size, x] and [num_blocks, num_kv_heads, block_size/X, head_size, X]
* 1. Introduced `kVectorSize` in BlockFmhaBatchPrefillPipelineProblem instead of using hardcode values
2. Makes batch prefill kernel traits structures inherent from fmha fwd
traits
3. Add some static check for Page size, vector size, hdim, ..., etc.
* [Refactor] Replace is_sglang_layout with Enums for KV cache configuration
Refactored `fmha_batch_prefill` to use `BlockAttentionKVCacheMemoryLayoutEnum` (VECTORIZED/LINEAR) and `BlockAttentionKVCacheLookupTableEnum` (SGLANG_1D/VLLM_2D) instead of a single
boolean.
**Changes:**
* Added Enum definitions in `block_attention_kvcache_layout_enum.hpp`.
* Updated Kernel, Pipeline, and Traits to template on these Enums.
* Implemented `kv_offset_array_transform` logic based on `kKVMemoryLayout`.
* Refactored `PageBlockTableKargs` to adapt to `kKVLookupTable`.
* Updated CodeGen scripts to support new parameters.
This decouples memory layout from the paging mechanism, enabling flexible KV cache configurations.
* 1. remove batch prefill pipeline with sk_pad=false
2. correct some comments
3. add static assert to make sure v offsets is in same page within a tile.
* fix vgpr spill count
* remove unnecessary t2s functions
* add fp8 support for receipt 200 and 600 in fmha_bath_prefill.py
* support linear kv cache layout
* Remove block_table_ptr from fwd_batch_prefill_args. Instead, reuse
kv_page_indices as a pointer of the lookup table.
* 1. merge multiple transforms into single transform.
2. add static check to make sure vlayout is row-major.
* move FmhaFwdCommonKargs::seqlen_k_ptr to VllmPageTableKargs.
* update changelog
---------
Co-authored-by: ltqin <letaoqin@amd.com>
Co-authored-by: PoYen, Chen <PoYen.Chen@amd.com>
* initial poc
* factor out common parts in operator()
* cv4
* rest of the universal gemm pipelines
* fix test
* remove boilerplate from tile engine
* fix example
* fix example
* format
* fix tests build for gemm
* remove base pipeline codegen from gemm instance builder
* unify v3 logic with the rest of universal gemm pipelines
* fix build for multi abd test
* fix test gemm multi d
* fix build for weight preshuffle
* fix grouped gemm test
* fix grouped gemm multi d test
* fix grouped gemm preshuffle
* fix grouped gemm example except for quant
* fix gemm preshuffle
* fix splitk 2 stage example
* fix batched gemm example
* fix multid example
* fix multiabd example
* fix batched gemm test
* fixup
* fix examples build
* fix grouped gemm test build
* fix smoke builder
* hacky poc
* fix tile engine
* kill the lambda
* maybe fix test build
* more fixes
* clang-format
* save temp
* clang-format
* mostly fix examples
* clang-format
* remove dead code
* more cleanup
* fix fmha bwd build (default epilogue set/add appears to be broken)
* fix default epilogue tests but not correctness
* clang-format
* fix bquant
* clang-format
* cleanup dead code
* rearrange make windows for readability
* restore changes to IsSupportedArgument
* fix smoke-builder
* clang-format
* fixup rename class
* build fixes
* clang-format
* fix builder
* fixup
* remove set from builder tests
* fix test
* clang-format
* re-refactor the kernels
* clang-format
* fix header license
* remove memory operation from conv bwd test
* clang-format
* clang-format example,include
* clang-format test
* build fixes
* clang-format
* solve compilation error
* fix the CI
* solve compilation error
* clang format
* solve merge conflict
* solve merge conflict
* solve the gfx11 error
* solve test error
* moar build fixes
* remove AtomicAddRequiresKBatchGreaterThanOne test since the property is removed from the kernel scope
---------
Co-authored-by: Thomas Ning <Thomas.Ning@amd.com>
Previously, the code used unsigned long for literals and format specifiers to represent 64-bit unsigned values. While this worked on Linux, it caused compatibility issues on Windows.
The C++ standard does not guarantee that long is 64 bits. On LP64 systems (e.g., Linux), long maps to 64-bit values, but on LLP64 systems (e.g., Windows), long maps to 32-bit values. This discrepancy led to incorrect behavior when assuming unsigned long was always 64-bit.
This commit updates all relevant literals and format specifiers to explicitly use 64-bit unsigned types, ensuring consistent behavior across platforms.
Remove the dependency from device_tensor_generator.hpp and fix a typo from a previous force push. The changes replace standard library math functions with their ck::math equivalents and define PI as a local constant instead of computing it using std::acos.
Key changes:
* Removed #include header dependency
* Replaced std::acos(-1.0) with hardcoded PI constant 3.141592653f
* Replaced std::sqrt, std::cos, and std::sin with ck::math equivalents
Added instance traits for the following bwd weight conv algorithms
DeviceGroupedConvBwdWeight_Xdl_CShuffleV3
DeviceGroupedConvBwdWeight_Wmma_CShuffleV3
DeviceGroupedConvBwdWeight_Wmma_CShuffle
DeviceGroupedConvBwdWeight_TwoStage_Xdl_CShuffle
DeviceGroupedConvBwdWeight_TwoStage_Wmma_CShuffleV3
DeviceGroupedConvBwdWeight_DL
DeviceGroupedConvBwdWeightMultipleD_Xdl_CShuffle
DeviceGroupedConvBwdWeightMultipleD_Wmma_CShuffleV3
Added also unit tests for instance traits of those bwd weigth algorithms that are currently exposed by the narrow CK build for MIOpen.
---------
Co-authored-by: Ville Pietilä <>
## Proposed changes
This source file won't build for gfx1101 on Windows. It builds successfully on other gfx110X architectures, and also builds successfully on gfx1101 on Linux.
This is the compile error:
```
[composable_kernel] FAILED: library/src/tensor_operation_instance/gpu/grouped_conv3d_bwd_weight_bilinear/CMakeFiles/device_grouped_conv3d_bwd_weight_bilinear_instance.dir/wmma/device_grouped_conv3d_bwd_weight_wmma_bilinear_ndhwgc_gkzyxc_ndhwgk_f16_instance.cpp.obj
[composable_kernel] ccache B:\build\core\clr\dist\lib\llvm\bin\clang++.exe -DCK_ENABLE_BF16 -DCK_ENABLE_BF8 -DCK_ENABLE_FP16 -DCK_ENABLE_FP32 -DCK_ENABLE_FP64 -DCK_ENABLE_FP8 -DCK_ENABLE_INT8 -DCK_TILE_USE_WMMA=1 -DCK_TIME_KERNEL=1 -DCK_USE_WMMA -DCK_USE_XDL -DDPP_KERNELS -DLLVM_MAIN_REVISION=524190 -DUSE_PROF_API=1 -D__HIP_PLATFORM_AMD__=1 -D__HIP_PLATFORM_HCC__=1 -IC:/home/runner/_work/TheRock/TheRock/ml-libs/composable_kernel/library/include -IC:/home/runner/_work/TheRock/TheRock/ml-libs/composable_kernel/include -IB:/build/ml-libs/composable_kernel/build/include -IB:/build/base/half/stage/include -isystem B:/build/core/clr/dist/include -DWIN32 -DWIN32_LEAN_AND_MEAN -D_CRT_SECURE_NO_WARNINGS -DNOMINMAX -fms-extensions -fms-compatibility -D_ENABLE_EXTENDED_ALIGNED_STORAGE -Wno-documentation-unknown-command -Wno-documentation-pedantic -Wno-unused-command-line-argument -Wno-explicit-specialization-storage-class -Wno-ignored-attributes -Wno-unknown-attributes -Wno-duplicate-decl-specifier --hip-path=B:/build/core/clr/dist --hip-device-lib-path=B:/build/core/clr/dist/lib/llvm/amdgcn/bitcode -O3 -DNDEBUG -D_DLL -D_MT -Xclang --dependent-lib=msvcrt -std=c++20 -Wall -Wextra -Wcomment -Wendif-labels -Wformat -Winit-self -Wreturn-type -Wsequence-point -Wswitch -Wtrigraphs -Wundef -Wuninitialized -Wunreachable-code -Wunused -Wno-reserved-identifier -Wno-option-ignored -Wsign-compare -Wno-extra-semi-stmt -Wno-unused-template -Wno-missing-field-initializers -Wno-error=deprecated-declarations -Wall -Wextra -Wcomment -Wendif-labels -Wformat -Winit-self -Wreturn-type -Wsequence-point -Wswitch -Wtrigraphs -Wundef -Wuninitialized -Wunreachable-code -Wunused -Wno-reserved-identifier -Wno-option-ignored -Wsign-compare -Wno-extra-semi-stmt -Wno-unused-template -Weverything -Wno-c++98-compat -Wno-c++98-compat-pedantic -Wno-conversion -Wno-double-promotion -Wno-exit-time-destructors -Wno-extra-semi -Wno-float-conversion -Wno-gnu-anonymous-struct -Wno-gnu-zero-variadic-macro-arguments -Wno-missing-prototypes -Wno-nested-anon-types -Wno-padded -Wno-return-std-move-in-c++11 -Wno-shorten-64-to-32 -Wno-sign-conversion -Wno-unknown-warning-option -Wno-unused-command-line-argument -Wno-weak-vtables -Wno-covered-switch-default -Wno-unsafe-buffer-usage -Wno-unused-lambda-capture -Wno-nvcc-compat -Wno-c++20-compat -Wno-bit-int-extension -Wno-pass-failed -Wno-switch-default -Wno-unique-object-duplication -Wno-nrvo -Werror -Weverything -fcolor-diagnostics -x hip --offload-arch=gfx1100 --offload-arch=gfx1101 --offload-arch=gfx1102 --offload-arch=gfx1103 --offload-arch=gfx1100 --offload-arch=gfx1101 --offload-arch=gfx1102 --offload-arch=gfx1103 -MD -MT library/src/tensor_operation_instance/gpu/grouped_conv3d_bwd_weight_bilinear/CMakeFiles/device_grouped_conv3d_bwd_weight_bilinear_instance.dir/wmma/device_grouped_conv3d_bwd_weight_wmma_bilinear_ndhwgc_gkzyxc_ndhwgk_f16_instance.cpp.obj -MF library\src\tensor_operation_instance\gpu\grouped_conv3d_bwd_weight_bilinear\CMakeFiles\device_grouped_conv3d_bwd_weight_bilinear_instance.dir\wmma\device_grouped_conv3d_bwd_weight_wmma_bilinear_ndhwgc_gkzyxc_ndhwgk_f16_instance.cpp.obj.d -o library/src/tensor_operation_instance/gpu/grouped_conv3d_bwd_weight_bilinear/CMakeFiles/device_grouped_conv3d_bwd_weight_bilinear_instance.dir/wmma/device_grouped_conv3d_bwd_weight_wmma_bilinear_ndhwgc_gkzyxc_ndhwgk_f16_instance.cpp.obj -c C:/home/runner/_work/TheRock/TheRock/ml-libs/composable_kernel/library/src/tensor_operation_instance/gpu/grouped_conv3d_bwd_weight_bilinear/wmma/device_grouped_conv3d_bwd_weight_wmma_bilinear_ndhwgc_gkzyxc_ndhwgk_f16_instance.cpp
[composable_kernel] error: Illegal instruction detected: Operand has incorrect register class.
[composable_kernel] V_CMP_NE_U32_e32 0, $src_private_base, implicit-def $vcc, implicit $exec
[composable_kernel] 1 error generated when compiling for gfx1101.
```
This appears to be a compiler bug and we'll follow up to get a proper fix landed, but for the purposes of landing some work to enable gfx1151 support in TheRock we'd like to disable building of these kernels on this architecture temporarily.
## Checklist
Please put an `x` into the boxes that apply. You can also fill these out after creating the PR. If you're not sure, please don't hesitate to ask.
- [X] I have added tests relevant to the introduced functionality, and the unit tests are passing locally
- [X] I have added the test to REGRESSION_TESTS list defined at the top of CMakeLists.txt in tests/CMakeLists.txt, **IF** the test takes more than 30 seconds to run.
- [x] I have added inline documentation which enables the maintainers with understanding the motivation
- [X] I have removed the stale documentation which is no longer relevant after this pull request
- [X] (If this change is user-facing) I have added release notes which provide the end users with a brief summary of the improvement from this pull request
- [X] I have run `clang-format` on all changed files
- [X] Any dependent changes have been merged
* Added device level implementation for bwd_data_wmma_v3.
* Added first instance of bwd_data_wmma_v3(f16).
* Add support for bwd data in gridwise implementation
Some changes are general for convolution and some are specific for bwd
data. We need to generalize them once we have fwd, bwd data and bwd
weight
* Initial device implementation of bwd data
* Remove unused template parameters in device impl
* Add one instance for different layout
initial check of device implementation
* Add tests for splitk and for different layouts
* Appended more instances to wmma_v3_f16.
* Added conv_2d bf16 wmma_v3 instances.
* Added conv_3d_bf16 wmma_v3_instances.
* Added conv_3d_f16_wmma_v3_instances.
* Added SplitN test cases for wmma.
* Conv3d_bwd_data_scale_wmma_v3 instances.
* Conv3d_bwd_data_bilinear_wmma_v3_instances
* Renaming the device level instances file to common name , since it is defined for different DataTypes.
* Renaming the instances and fixing typo
* Added the test cases to regression test list
* NCHW support for wmma_v3
* Examples for bf16 and f16 bwd_data_wmma_v3
* Added transpose conditons for device impl
* fixing bugs
* Added the gemm_args array implmentation
* WIP debug conv bwd
* fix splitk
* Grouped gemm fix
* Update CmakeLists with EOF
* Added more instances for tests
* Fixed the run time error in examples and removed 3d conv examples.
* Fixed a typo.
* Updated CmakeLists to removed the 3d convultion deleted files
* Added print error statements for unsupoorted argument
* Added the merge conflict related changes
* Fixed compilation error
* Fixed the InstanceFactory duplication error.
* Removed the print statements and added logs to Arg function
* All the merge conflict related errors resolved
* Added d_tensor tests.
* Added the missing example types of wmm_v3
* Merge error fix
* Corrected the instance name
* Reverted the bias relu change
* Revereted the transpose load local change
* Updated the regression test list with bwd_data_scale
* Revert "Revereted the transpose load local change"
This reverts commit 0b7281edb2bf008e407006690a00621174d9d19b.
* Revert "Merge error fix"
This reverts commit f3c85daa474b1b83d10c8a3ce077354e71d91a2b.
* Reverting the local change
* Added merge error fix
* Build error fix due to merge conflicts
* Added bias_relu example for wmma_v3
* Modified the main method in dtensor tests
* Updated the dtensor tests to pick all the shapes
* Updated the dtensor test shapes.
* Updated the mem operations in tests.
* Added reference func
* Fixed typos in device impl
* Added new header file and modified the include file for 3d tests
* Renamed the test file and added reference func call.
* clang format fix
* Added ignore params
* Modified device impl and tests
* Removed debug print statements and updated dtensor test shapes
* Fixing merge conflicts
* Fixing more merge conflicts
* Fixed copyrights
* Updated the tuned instances to bilinear and scale.
* Adding tuned instances to vanilla wmma_v3
* Removed all unused instances and modified test layouts.
* Cleaned up all instances , reverted back fwd fp16 instances and updated tuned fp16 instances.
* Fix clang format
* Updated tuned f16/-genric instances
* Formatting the instances file
* Fixed copyrights and clang issues
* Nonsense commit to force git to force
* Removed the transpose instances
* Added verified genric instances
* Fixing namespace errors
* Added todo for failing shapes
* Formatting instance file
* Fix instance list formatting
* Removing unnecessary formats
* Renamed the common file
* Unification of xdl and wmma bwd_data tests
* Updated Cmake
* Added all layout types and deleted code.
* Updated Cmake to add the condition to all tests.
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Co-authored-by: Enrico Degregori <enrico@streamhpc.com>
Co-authored-by: Anton Gorenko <anton@streamhpc.com>
Co-authored-by: kiefer <kiefer.van.teutem@streamhpc.com>
