* 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
* 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>
* 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
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_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>
* 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
