* 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
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 <>
* 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.
---------
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>
