Downstream libraries aren't migrated to c++20 yet, so replace a use of c++20 concept with equivalent SFINAE logic. The template checks for both the existence and the truthiness of the static member variable.
* base working version for single groupped conv bwd data
* Fix 2d descriptor
* fix groups
* Add 3d support
* fixes
* fixes
* fixes
---------
Co-authored-by: Jakub Piasecki <jakpia21@gmail.com>
* CK Tile Stream K Device Ops
Implementation of CK Tile StreamKHostArgs and StreamKKernel classes. The
StreamKKernel class injects Universal Gemm and includes functions to
facilitate kernel preparation for the GPU.
* Stream K Device Ops Fixes
- Update GetWorkSpaceSize to call TilePartitioner's GetWorkSpaceSize to
ensure we get size needed for accumulation buffers and semaphores.
- Pass in num_sk_blocks into TilePartitioner constructor
- Update documentation
* Add WarpTile dimensions to GetName function in StreamKKernel class
* Fix typos in StreamKHostArgs class description.
Co-authored-by: Christopher Millette <63608002+cgmillette@users.noreply.github.com>
* Apply clang format on updated comment for StreamKHostArgs
* Explicitly specify type for StreamKReductionStrategy enum
* Remove unecessary scopes
* Unify the commenting style to inline comments
* Add explicit casts for occupancy and num_cu in MakeKernelArgs function
Both the static functions Occupancy and NumCU in the StreamKKernel class
use functions from the HIP API that result in the returned occupancy and
num_cu types being type int. The TilePartitioner interface for stream K will
have occupancy and num_cu being type ck_tile::index_t which is int32_t.
Thus, to be safe, this change ensures that both occupancy and num_cu are
cast to int32_t.
* Fix use of kentry due to interface update
PR #2594 updated the interface for the kentry function in
include/ck_tile/host/kernel_launch.hpp. As a result, the static function
Occupancy was updated to work correctly with the new interface.
PR #2594 also changed UniversalGemmKernel's KernelBlockSize static
variable to kBlockSize, so the StreamKKernel class was updated to
reflect this change.
* Switch type of num_sk_blocks from uint32_t to int32_t
This change switches the type of num_sk_blocks to type ck_tile::index_t
which is int32_t. This was done because parallel work for the CK Tile
StreamK TilePartitioner's constructor will have num_sk_blocks as
ck_tile::index_t. Thus, this change will help unify the interfaces to
avoid any type conversion errors.
---------
Co-authored-by: Christopher Millette <63608002+cgmillette@users.noreply.github.com>
* Rename vector to ThreadTile
* more notes on tile encoding
* remove number<> from tuple of make_tile_window
* add script to stress test the copy example
* Remove some duplicate code in fmha_fwd_appendkv_kernel.hpp
* Simplify two templated operator calls by having the templated types deduced automatically
* Simplify two GemmPipeline calls
* Fix GemmPipelineAgBgCrCompV4::GetName
* Refactor use of ArgParser in CK tile GEMM examples
* Update args in README.md to match the implementation in create_args
* Remove some unnecessary include statements
* Rename two variables
* Factor out common code
* Factor out do_verify
* Add and use type aliases for memory operation integral constants
* In gemm_basic.cpp, use kPadM, kPadN, kPadK, and kBlockPerCu from GemmConfig
---------
Co-authored-by: Adam Osewski <19374865+aosewski@users.noreply.github.com>
* Preshuffle AQ matrix in block scale gemm
* turns the output to fp16. Increase the repetition time.
---------
Co-authored-by: ThomasNing <thomas.ning@amd.com>
* Readme for GEMM Multi D
* GEMM Multi D partial Progress
* GEMM Multi D partial Progress!
* CK Tile Engine GEMM Multi D : All Python files generated
* Partial Progress
* Partial Progress
* Partial Progress
* Partial Progress : Incorrect Result
* Partial Progress : Debugging
* Partial Progress : Correct Results
* Partial Progress - Incorrect Results
* Partial Progress - Commenting Passthrough bypass logic
* Changing Passthrough to MultiplyMultiply
* Correct Results!
* Fix and debug the pass through feature
* Sample commit
* Correct Results : MultiplyMultiply
* Code Cleanup
* Removing Failed Instances
* Working code before Unary element support
* Custom Elementwise Function support and working implementation for Mul and Add
* Updating README
* Working for Passthrough
* Review Comments : Minor Fixes
* Review Comments : Minor Fixes
* Readme Updated
* Partial Changes after Rebase
* Working Code : Changes after Rebase
* Updating Jenkins file
* Removing default value changed while testing
* Configuration changes in config files
* Tile Handler changes in GEMM Multi D Tile Engine
* Tile Handler changes in GEMM Multi D Example
* Change log for Gemm Multi D in CK Tile Engine
* Configuration changes in config files
---------
Co-authored-by: ThomasNing <thomasning@amd.com>
* add failing tests
* swap out and reference
* add constraint assert to transpose input distribution
* test both pipelines with rectangular block tile
* print mismatched indices
* add a smaller failing test for old pipeline
* print grid and block
* fill output before operating on it
* swap m/n tile sizes and make one test pass
* add device syncs
* add one more flipped test case
* flip block tile at host arg init
* fix tiles for lds pipeline
* clang-format
* rename tests
* roll back error check
* remove device syncs
* reduce large test case's size
* Add more printing to core cktile
* Revert other changes in static encoding pattern
* Refactor to using a free print() function
* Remove loops and print just the containers
* Print tuple with better formatting, fix sequence compilation
* Add some tests for print utility
* Add print utility header
* Print for static_encoding_pattern
* add buffer_view printing
* Align vector_traits
* Fix formatting
* Lower-case enum strings
Co-authored-by: Christopher Millette <63608002+cgmillette@users.noreply.github.com>
* Remove empty comment lines
* Fix test with lower-case too
* Reduce repeated code in print tests, move helper function closer to type definition, test X&Y
* Add test_print_common.hpp
* add print.hpp in core.hpp
---------
Co-authored-by: Aviral Goel <aviral.goel@amd.com>
Co-authored-by: Christopher Millette <63608002+cgmillette@users.noreply.github.com>
Co-authored-by: Adam Osewski <19374865+aosewski@users.noreply.github.com>
* General 2D Reduction Kernel
* Move the reduction kernel from the example
* Split the code and add the necessary policy, problem, shape files as
per ck_tile convention
* Add/modify the headers
* Modified the example to work with the 'new' kernel
* Added tests for the kernel
* N-D refernce reduce
* Added support for N-D input with transform to 2D
* Added padding to support various input sized tensors
* Bug fix in the thread buffer constructor
* Some comments to explain the reduce2d block kernel
* comments resolution
* clang-format
* comments resolution
* clang-format
* clang-format
* comments resolution
* clang-format
* enable the persistent kernel for CompV4
* polish the example and clang format
* fix the non-persistent kernel error
---------
Co-authored-by: ThomasNing <thomasning@amd.com>
Resolves R_X86_64_32 relocation out of range errors in grouped conv2d instances
by splitting debug information into separate .dwo files.
Add explicit cast to avoid signed/unsigned comparison warning.
* something khushbu can help with
* v1 v2 works with flatmm develop
* v0 v1 v2 numerical error gone
* Fixing numerical error, and interchange preshuffle configs to match with flatmm
* Refactor GEMM pipeline configurations and integrate preshuffle support
- Updated preshuffle pipeline definitions to include multiple versions (V1, V2, V3).
- Changed the pipeline constant from CK_TILE_PIPELINE_PRESHUFFLE to CK_TILE_PIPELINE_PRESHUFFLE_V3 in relevant configurations.
- Removed obsolete code and comments
* clang format
* fix vectorloadsize bug
* add the Preshuffle3
* update kwarp calculation in gemm utils
* update vector size A and B correctly in V2 pipeline; Added few more changes to align with dteng's branch
* fix: add CK_GFX950_SUPPORT macro for gfx950 detection
* default disable rotating buffer
* docs(CHANGELOG): update changelog for rocm 7.0
* Revert "docs(CHANGELOG): update changelog for rocm 7.0"
This reverts commit 2bc16fff84.
* Remove unused Preshuffle V3 pipeline and related code; update gemm function to use Preshuffle V2; clean up comments and formatting in various files.
* revert example/ck_tile/flatmm to its original state
* remove comment added by second author
* switch to xor ALDSDescriptor
* modify the MakeALdsDescriptor()
* temporary profiling script
* getting rid of line marker compiler error
* UniversalWeightPreshufflePipelineAgBgCrPolicy now derives from UniversalGemmBasePolicy
* add a minor fix for the config
* typo fix
* Fix formatting in lambda function for WeightPreshufflePipelineAGmemBGmemCRegV2
* revert change in include/ck_tile/ops/flatmm/pipeline/flatmm_pipeline_agmem_bgmem_creg_v1.hpp
* revert change in include/ck_tile/core/arch/amd_buffer_addressing.hpp
* reenable the GemmSpatiallyLocalTilePartitioner
* make GemmConfigPreshuffle_1 for v1 pipeline, GemmConfigPreshuffle_2 for v2 pipeline
* remove hardcoded true for preshuffle bool template argument
* rename script
* remove gemm_profilie.sh script
* merge conflict resolve
* clang formatted
* typo fix
* Remove duplicate include of block_gemm_areg_bsmem_creg_v2r1.hpp in gemm.hpp
* Remove commented-out code in UniversalWeightPreshufflePipelineAgBgCrPolicy
* Fix missing newline at end of file in run_gemm_example.inc
* Remove unused barrier call in BlockWeightPreshuffleASmemBSmemCRegV1
* addressing review comments
* removing debug code
* addressing review comments
* Revert "addressing review comments"
This reverts commit 29c45192ba.
* updating tile_engine code
* addressing review comments
---------
Co-authored-by: amd-khushbu <khuagarw@amd.com>
Co-authored-by: ThomasNing <thomas.ning@amd.com>
* Add tests for host convesion f32/f16 to f8
* Add tests for host convesion from f8 to f32/f16
* Fix UB and corner cases in f32/f16 to/from f8 conversion
* There are UBs when very small values are converted to f8: bitshifts
can be larger that type width. Using unsigned long long does not help
because exponent_diff >= 64 in such cases. This causes that values
like 2.117582368e-22 are converted to non-zero f8 in host validation
of FMHA tests, test_f8 crashes with segfault in completely irrelevant
code like GTest internals or produces non-deterministic results etc.
* Fix FNUZ conversion to return NaN for NaN inputs.
* Fix compilation error (due to uint8_t << 8) in OCP e5m2 to f16
conversion.
* Replace some magic numbers with values from numeric_traits
* Build tests only on devices supporting the type
* update gpu_timer for rotating buffer as hipblasLt's implementation
* timing fix
* Updating gpu timer for old ck as well
* Revert "Updating gpu timer for old ck as well"
This reverts commit 958cd1bc99.
* code clean up with runtime argument; function rename
* code cleanup
* general timer fixes
* bug fix
* clang formatted
* addressing reveiew comments
* clang formatted
* Addressing review comments
* CI fix
---------
Co-authored-by: Po Yen Chen <PoYen.Chen@amd.com>
* Expand the bandwidth of direct_global_to_lds for gfx950
* clang-format
* fix the remod.py and script for clang format
---------
Co-authored-by: Max Podkorytov <4273004+tenpercent@users.noreply.github.com>
* unify pipeline signature with existing example
* iwyu
* move stuff around in load-tile-transpose
* cleanups in batched transpose pipeline
* comments
* use same inputs size
* cleaner printf
* print host args
* use 64 block sides in the 37_transpose example
* roll back grid dimension size adjustment for 37_transpose example
* transpose grid for 37_transpose to unify with 35_batched_transpose
* unify grid computation logic
* make policy methods device only (since they are used only on device from the pipeline)
* more host/device attribute cleanups
* copy over problem
* move over pipeline and policy
* add switch to batched transpose api
* make the lds problem more similar to original problem
* factor out logic into traits
* factor out conditional compilation into trait parameter
* propagate pipeline to args
* unhardcode pipeline dispatch parameter
* refactor vector size
* put warp tile out of dispatch
* rename template parameter for trait
* rewrite vector size in terms of problem
* mark policy-internal struct variable as device
* factor out input distribution and thread access pattern from policies
* reword vector size
* use datatype across batched transpose pipelines, problems and kernel
* remove transpose traits from lds pipeline
* add padding to the lds pipeline *interface*
* add comment
* remove ck_tile example #37
* update cmakelists
* add test for new pipeline
* update batched transpose test
* roll back load_tile_transpose changes
* remove comments
* pack dispatch parameters into a config
* padM can be enabled
* adjust lds vector size to enable padding along N
* update test
* clean up logic
* swap m/n input vector size
* adjust perf test script
* sweep over C/W in perf test
* count both read and written bytes into bandwidth (x2 the number)
* clang-format
* widen size range for perf test
* remove 64k x 64k case; it's too large for index
* remove thread tile from dispatch
* Solve merge conflict
* fix compile
* modify the transpose
* solve the test error and clang format
* Add v3 support for Groupd fwd conv+bias+clamp & ckProfiler (#2463)
* Add logging to IsSupported.
* Less casting in AddClamp
* Conv+bias+clamp instances & profiler BF16
* Fix 3D instances & run just 1x for verification.
* :Run just once for verification conv fwd.
* ckProfiler conv fwd clampwq
* Remove exec bit & formatting
* Add support for MultiD for grouped conv fwd v3.
* Enable 2Lds.
* clean
* align instances
* align instances
* profiler fixes
* Fixes
* fix
* fix
---------
Co-authored-by: Adam Osewski <root@quanta-ccs-aus-f01-19.cs-aus.dcgpu>
Co-authored-by: Bartłomiej Kocot <barkocot@amd.com>
* Fixing 0ms and inf GB/s issue in img2col (#2565)
issue :
====
``` sh
$ bin/tile_example_img2col
Perf: 0 ms, inf GB/s
```
solution :
======
Problem occured because config.time_kernel is false by default.
if false, then no need to calculate perf, just print proper message
`image_to_coloumn: pass, No Perf generated due to config.time_kernel=0`
* merge with develop
* solve clang format
---------
Co-authored-by: ThomasNing <thomas.ning@amd.com>
Co-authored-by: Adam Osewski <19374865+aosewski@users.noreply.github.com>
Co-authored-by: Adam Osewski <root@quanta-ccs-aus-f01-19.cs-aus.dcgpu>
Co-authored-by: Bartłomiej Kocot <barkocot@amd.com>
Co-authored-by: rahjain-amd <Rahul.Jain@amd.com>
* Elementwise kernel implementation
Co-authored-by: Sami Aario <samaario@amd.com>
Co-authored-by: Mohsen Saffari <mohsen.saffari@amd.com>
Co-authored-by: yashagar <yashagar@amd.com>
* Elementwise with generalized nDims
* Adding the n-ary input tensor feature
* Generalize dimensions on top of inputs
* Add TFLOPS + remove std usage for tuples
* 1D basecase optimization
* Cleanup code + refactoring to a common interface
* Generalize to unary and add an example
* Cleanup, refactoring and commenting
* Suggestions for LWPCK-3170: elementwise kernel improvements
* Clang-format: remod.py
* Replace InputTensorType with XDataType as the type of input_tensors
* Add Tuple::apply and use it in ElementWiseKernel::operator to call operation with the exact number of arguments in xs
* Move examples to folder 19_elementwise
* Add missing copyright headers and fix some existing ones
* Replace an assert with throw std::runtime_error in elementwise example
* Avoid reading the output by using make_static_distributed_tensor for y_tile
* Removed two unused includes
* No need to move windows to the next block when each workgroup processes a single tile
* Only copy input tensors to the device
* Use get_warp_size to obtain warp size, and use ceiling division for grid size also for the unary example
* Adding output strides to the kernel, transposition example and update the other examples
* Changes made by remod.py
* Use default template parameter values for memory operation and coherence in a call to make_naive_tensor_view
* Move binary operations to include/ck_tile/ops/elementwise/binary_elementwise_operation.hpp
* Reuse generic reference binary/unary operation in examples + refactoring the transpose reference
* Fix comments in elementwise_example.cpp
- Refer to AMD terminology except when suggesting NVIDIA alternatives in parentheses
- ElementWiseTraits was renamed to ElementWiseShape
- Adopt suggestions made by Copilot when prompted to check for factual or typographical errors
* Simplify CMakeLists.txt and remove the unused variables this uncovers
* Rename a file and fix some copyright statements
* Changes made by script/clang-format-overwrite.sh
* Add basic unit test for ElementWiseKernel
* Remove left-over uninformative comment in apply unit test
* Changes made by clang-format-overwrite.sh
* fixup! Use default template parameter values for memory operation and coherence in a call to make_naive_tensor_view
* Clean up test_tuple_apply.cpp and test_elementwise_1d.cpp
* Use make_uniform_array_with_factory to define h_xs and d_xs_mems_owner as type std::array
* Use a DeviceMem constructor that calls get_element_space_size_in_bytes internally
* Move examples to folder 20_elementwise
* Reduced register pressure on the CK tile elementwise kernel + add 4d input example to be able benchmark against old CK
* Fix CLang formating
* Bump up the elementwise example folder number
* Elementwise: add padding + minor cleanup
* Add Vector Size inference + fix issue with wrong vectorization due to missing GuaranteedLastDimensionVectorStride setting in make_naive_tensor_view
* Add isSupportedArg to Elementwise kernel + addapt example and unit tests
* Fix clang-format on the unit test file
---------
Co-authored-by: Damien Lejeune <damien.lejeune@amd.com>
Co-authored-by: Sami Aario <samaario@amd.com>
Co-authored-by: Mohsen Saffari <mohsen.saffari@amd.com>
Co-authored-by: Aviral Goel <aviral.goel@amd.com>
