1. 07 Aug, 2023 1 commit
    • Illia Silin's avatar
      Allow building CK for specific data types and split off last remaining DL instances. (#830) · 08eb1769
      Illia Silin authored
      * properly split conv_nd_bwd_data instances
      
      * split conv2d_fwd instance data types
      
      * split the gemm, conv2d_fwd and batched_gemm_softamx_gemm
      
      * split the tests by data types where possible
      
      * filter examples by DTYPES
      
      * split few remaining examples by DTYPES
      
      * filter most instances by DTYPES
      
      * add new lines at end of headers, fix grouped_gemm profiler
      
      * fix syntax
      
      * split the ckprofiler instances by DTYPES
      
      * split the conv2d and quantization DL and XDL instances
      
      * fix the splitting of conv2d DL instances
      
      * split softmax and pool_fwd tests for fp16 and fp32 types
      
      * fix syntax
      
      * fix the dl_int8 quantization instances isolation
      08eb1769
  2. 15 May, 2023 1 commit
    • Illia Silin's avatar
      Update staging branch. (#706) · 72b7ae25
      Illia Silin authored
      
      
      * update daily build from rocm 5.4.3 to 5.5 (#693)
      
      * Fix grouped_gemm_splitk kernels on MI300. (#694)
      
      * replace amd_buffer_atomic_add with hip_atomic_add
      
      * fix grouped_gemm_splitk kernels on mi300
      
      * fix syntax
      
      * revert experimental atomic_add changes
      
      ---------
      Co-authored-by: default avatarJing Zhang <jizhan@amd.com>
      
      * Fix the group of quantization_int8 kernels on MI300. (#695)
      
      * replace amd_buffer_atomic_add with hip_atomic_add
      
      * fix grouped_gemm_splitk kernels on mi300
      
      * fix syntax
      
      * revert experimental atomic_add changes
      
      * fix the group of kernels from ticket 723 on MI300
      
      ---------
      Co-authored-by: default avatarJing Zhang <jizhan@amd.com>
      
      * Optimize bf16 conversion (#664)
      
      * Add TypeConvert class and start refactoring
      
      * Refactor TypeConvert as a struct
      
      * Get back to template functions type_convert
      
      * Add a type_convert_bf16_rtn, set rtz as default
      
      * Clean up
      
      * Add UnaryConvertPrecision struct for high-precision workloads
      
      * Format
      
      * Update type_convert to UnaryConvert on threadwise level
      
      * Update UnaryConvertPrecision
      
      * Format
      
      * Fix chmod
      
      * Add a flag to pick converion method
      
      * Format
      
      * Remove the added flag
      
      * Merge elementwise op with type conversion
      
      * Move type_convert to elemwise op, update the op
      
      * Update type_convert_precision -> bf16_convert_rtn
      
      * Clean up
      
      * Update comments
      
      * Update the CK_WORKAROUND_DENORM_FIX flag handling
      
      * Update the unneeded op to work but warn user
      
      * Remove the message
      
      * Use a PassThrough instead of ConvertBF16RTN to calcaulate reference
      
      * Format
      
      * Add missing include
      
      * Normalization/split k (#615)
      
      * Add contraction profiler and tests (#701)
      
      * Add contraction profiler and tests
      
      * Build and style fixes
      
      * Allow to use any elementwise operator for ref_contraction
      
      * Introduce profile_contraction_scale and profile_contraction_bilinear
      
      * Make ref_contraction generic and extend interface tests
      
      * Stylistic minor fixes
      
      * Extend test_contraction_interface
      
      ---------
      Co-authored-by: default avatarJing Zhang <jizhan@amd.com>
      Co-authored-by: default avatarRostyslav Geyyer <46627076+geyyer@users.noreply.github.com>
      Co-authored-by: default avatarrocking <ChunYu.Lai@amd.com>
      Co-authored-by: default avatarBartłomiej Kocot <bartlomiejkocot98@gmail.com>
      72b7ae25
  3. 11 May, 2023 1 commit
  4. 03 Nov, 2022 1 commit
    • guangzlu's avatar
      Fused elementwise normalization (#492) · 8a4253ba
      guangzlu authored
      * add fused addition lyernorm
      
      * add fused addition lyernorm
      
      * changed CMakelist
      
      * removed annotates
      
      * modified descriptor of C
      
      * fixed bug in gridwise add layernorm
      
      * format the files
      
      * modified name from add&layernorm into elementwise&layernorm
      
      * created fused elementwise layernorm branch
      
      * change input into tuple type
      
      * add sweep once to reduce load & read of C from global memory
      
      * modified Argument api
      
      * modified way to malloc c in global memory
      
      * changed gamma and beta to m_k_desc
      
      * fixed bug when sweep once and move CDataType when define device level struct
      
      * add src dim for gamma and beta
      
      * implement optimization for coalesced
      
      * delete a annotation line
      
      * fixed some bug to meet the requirements of ck
      
      * add bandwidth computing in example, and fixed the time unit
      
      * move device_elementwise_layernorm_impl.hpp into device/impl
      
      * fixed bug in device_elementwise_layernorm_impl.hpp
      
      * changed name from layernorm into normalization
      
      * clang-format the changed files
      
      * changed the names
      
      * moved immidiate results into lds, it become faster in non-sweeponce cases
      
      * changed naming of C into X to make the defination more clear
      
      * changed naming in example
      
      * add tests for elementwise normalization
      
      * move example_elementwise_layernorm_blockwise into folder 44_elementwise_normalization
      
      * move test_elementwise_layernorm_fp16 into new folder
      
      * move elementwise_normalization_instances into a new folder
      
      * add more tests in test_elementwise_layernorm_fp16.cpp
      
      * added some corner cases in test
      
      * fixed method to compute lds size for matrix X
      
      * changed name of 44_elementwise_normalization into 45_elementwise_normalization
      
      * modified some comments
      
      * modified some other confused comments
      
      * reduce redundant tests in test_elementwise_layernorm_fp16.cpp
      8a4253ba
  5. 25 Oct, 2022 2 commits
    • guangzlu's avatar
      Revert "Fused elementwise layernorm (#468)" (#491) · 6ea9257e
      guangzlu authored
      This reverts commit efbcc6ed.
      6ea9257e
    • guangzlu's avatar
      Fused elementwise layernorm (#468) · efbcc6ed
      guangzlu authored
      * add fused addition lyernorm
      
      * add fused addition lyernorm
      
      * changed CMakelist
      
      * removed annotates
      
      * modified descriptor of C
      
      * fixed bug in gridwise add layernorm
      
      * format the files
      
      * modified name from add&layernorm into elementwise&layernorm
      
      * created fused elementwise layernorm branch
      
      * change input into tuple type
      
      * add sweep once to reduce load & read of C from global memory
      
      * modified Argument api
      
      * modified way to malloc c in global memory
      
      * changed gamma and beta to m_k_desc
      
      * fixed bug when sweep once and move CDataType when define device level struct
      
      * add src dim for gamma and beta
      
      * implement optimization for coalesced
      
      * delete a annotation line
      
      * fixed some bug to meet the requirements of ck
      
      * add bandwidth computing in example, and fixed the time unit
      
      * move device_elementwise_layernorm_impl.hpp into device/impl
      
      * fixed bug in device_elementwise_layernorm_impl.hpp
      
      * changed name from layernorm into normalization
      
      * clang-format the changed files
      
      * changed the names
      
      * moved immidiate results into lds, it become faster in non-sweeponce cases
      
      * changed naming of C into X to make the defination more clear
      
      * changed naming in example
      
      * add tests for elementwise normalization
      
      * move example_elementwise_layernorm_blockwise into folder 44_elementwise_normalization
      
      * move test_elementwise_layernorm_fp16 into new folder
      
      * move elementwise_normalization_instances into a new folder
      
      * add more tests in test_elementwise_layernorm_fp16.cpp
      
      * added some corner cases in test
      
      * fixed method to compute lds size for matrix X
      
      * changed name of 44_elementwise_normalization into 45_elementwise_normalization
      
      * modified some comments
      
      * modified some other confused comments
      
      * reduce redundant tests in test_elementwise_layernorm_fp16.cpp
      efbcc6ed
  6. 13 Jul, 2022 1 commit
    • rocking5566's avatar
      Standalone layernorm (#315) · 7f216620
      rocking5566 authored
      
      
      * Implement layernorm kernel and deviceOp
      
      * verify gpu kernel with host code
      
      * 1. Separate gamma aand beta from affine
      2. Check if argument is valid
      
      * clean
      
      * Sync the naming
      
      * Support sweep once mode if we can put k dimension data inside one block
      
      * [What] Get length from upper length.
      [Why] if we get length directly, we may get length after padding.
      
      * We only use one block in K dimension.
      Hence, we can simplify the indexing of global R/W.
      
      * Use 1d descriptor for gamma and beta
      
      * Add accElementwiseOp
      
      * Extract layernorm host code
      
      * Support different YVectorDim in GridwiseLayernorm
      
      * Rename XSrcVectorDim to XYSrcVectorDim. Because we use same parameter in deviceOp
      
      * Gamma and beta can share the VGPR.
      
      * Add test for fp32 and fp16
      
      * Fix bug of concurrency and add test case which may fail orignally
      
      * Propagate NaN for layernorm
      Co-authored-by: default avatarChao Liu <chao.liu2@amd.com>
      7f216620