Update Blockwise and Gridwise files to support both wave32 & wave64.
1. Calculate WaveSize from template parameter, instead of hard code it to 64, some "64" is also replace with WaveSize
2. Move BN0Shuffled and BK0Shuffled to device side. we can't get correct mfma inst info in host side.
3. Update b_thread_offset_n and b_thread_offset_k in gridwise_gemm_xdl_cshuffle_v3_b_scale.hpp for gfx11. in gfx11, input data is duplicated for each 16 threads, it is different with all of others.
4. Modify a1_threadwise_copy in gridwise_batched_*gemm*gemm for gfx11. for gfx11, we need duplicate input and swizzle A if transposeC isn't enabled.
* initial commit for skeleton code
* replaced skeleton code with old streamk b2c map functions from old CK, still need to clean up the code
* fixed up code to match CK Tile convention: data type changes, naming changes, etc.
* change for num_sk_blocks data type
* formatting fix
* minor fixes
* moved reduction argument to template
* resolved comments from PR review: standardizing naming, pruning unneeded code
* resolve errors from merge of device op PR: moved enum to common file
* switching to uint32_t due to implementation constraints: divmod only takes uint32_t and mixing signed and unsigned types causes problems
* unsigned type fix
* add const qualifier
* added documentation for template parameters
* documentation edit
* Adding RapidJson Library
* Adding Json Dumps in all CK_Tile Examples
Not verified yet
* Adding json to cktile Batched Transpose
* adding json dumps to layernorm2d_fwd
* Adding json dump to flatmm_basic
* Adding RapidJson Library
* Adding Json Dumps in all CK_Tile Examples
Not verified yet
* Adding json to cktile Batched Transpose
* adding json dumps to layernorm2d_fwd
* Adding json dump to flatmm_basic
* Adding json in 03_gemm
* Add json dump to 16_batched_gemm
* Add json dump to gemm_multi_d_fp16
* Add json dump to grouped_gemm
* fix fmha_bwd/fwd
* Fix clang-format errors
exclude include/rapidjson in jenkins as its a third-party library
* Saparating function and defination.
* Update Documentation of 03_gemm
* Refactoring as per code review
* Disable fp8 instances on unsupported targets (#2592)
* Restrict building of gemm_universal_preshuffle_f8 instances to specific targets in CMakeLists.txt
* Add condition to skip gemm_xdl_universal_preshuffle_f8 instances for unsupported targets in CMakeLists.txt
* Add conditions to skip unsupported targets for gemm_universal_preshuffle_f8 and gemm_xdl_universal_preshuffle_f8 instances in CMakeLists.txt
* Refine conditions to exclude gemm_universal_preshuffle_f8 instances for unsupported targets in CMakeLists.txt
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Co-authored-by: AviralGoelAMD <aviralgoel@amd.com>
* fix clang format
* remove duplicate lines of code from library/src/tensor_operation_instance/gpu/CMakeLists.txt
* Fixing Readme and unifying jsondumps
* adding moe_smoothquant
* adding fused_moe
* Fixing Readme for batched_gemm
* Fixing Readme for grouped_gemm
* adding flatmm
* adding gemm_multi_d_fp16
* adding elementwise
* adding File name when json is dumped
* Fixing Reduce after merge
* adding batched_transpose
* Adding Warptile in Gemm
* Fixing Clang Format
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Co-authored-by: Aviral Goel <aviral.goel@amd.com>
Co-authored-by: AviralGoelAMD <aviralgoel@amd.com>
Co-authored-by: illsilin_amdeng <Illia.Silin@amd.com>
* Adding fix for the gfx908 to the GEMM MFMA implementaitons of WarpGemmMfmaBf16Bf16F32M4N64K16 WarpGemmMfmaBf16Bf16F32M64N4K16
* Adding support for offload target gfx9-4-generic
* This duplication here isn't ideal
* This change introduces new pipelines with Intrawave scheduler and block gemm primitives that loads the scale tensor to registers to perform dequantization post MFMA on C tensor in registers.
Scale tensor data, BQ is spliced across threads in registers and not stored in LDS.
Current support is for the following combinations, but it should be fairly straightforward to extend support to more formats.
fp8, fp8 -> f32
bf8, bf8 -> f32
fp8, i4 -> f32
bf8, i4 -> f32
Group size can go down to as low as K length of underlying WarpGemm primitive.
* Solve merge conflict
* [CK TILE] Update CHANGELOG.md
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Co-authored-by: Vijay Krishnamoorthy <vjkrish@fb.com>
Co-authored-by: ThomasNing <thomas.ning@amd.com>
Co-authored-by: Cong Ma <congma13@amd.com>
The performance of Aquant has increased after enabling transposed C.
Do not need to exchange AQ elements among lanes after enabling
transposed C as one thread only holds data from one row.
* feat(check_err): add a variable to adjust number of incorrect values to print
* feat(host_tensor): add printing capability for fp8 bf8 int8 int4
* fix(gemm_utils): update acceptable data type
* fix(host_tensor): print both 4 bit ints in pk_int4_t
* refactor(HostTensor): define pk_int4_t_to_int8x2_t and fix typo in vector_type.hpp
* feat(host_tensor): add print first n elements functions
