* Initial adding of generic reduction
* Initial adding of generic reduction ...
* Updates to make compiling done
* clang-format all files
* clang-format some files again
* Renaming in profiler/include/profile_reduce.hpp
* Updates and make BlockWise cases passed
* Updates and make ThreadWise and MultiBlockTwoCall cases passed
* Remove the support for MUL and NORM1 reduceOp from the profiler and the device instances
* Change to replace the dim0_max_vector_size/dim1_max_vector_size template argument in the device reduce classes
* format
* adding pooling
* added max and average pooling
* comment out cout and kernel timing
* Tiny simplification in profiler/reduce_profiler.cpp
* Add example for reduce_blockwise
* Tiny updates
* Change to pass the ElementWiseOp from device layer to kernel
* Fix the vectorDim and vectorSize in Device layer
* Enable vector load on both dim0 and dim1 for Threadwise method
* Tiny updates
* Change to let the user to pass the preUnaryOp and posUnaryOp
* Make pooling example work
* split device_reduce_instance into two libraries
* Tiny update
* Replace nanPropaOpt enum by boolean propagate_nan
* Simplification in DeviceReduce layer codes
* update build
* Change to clarify the difference between ck::half_t and half_float::half
* Renaming in all the reduction codes
* Add VectorSize as template parameter for device layer
* Add BetaIsZero as kernel template and as AccDataType for alpha
* print
* Small updates for pooling
* Updates for host_generic_reduction for reference
* Update to make AVG pooling pass
* Update to make MAX pooling with indices output pass
* fix
* add OutDst vector store to threadwise reduction and pooling
* tweak
* turn off check_indices that caused build issue
* refactor pooling
* clean up
* turn off check_indices for building issue for php-compiler
* add more tile size for odd C
* tweak conv for odd C
* update script
* clean up elementwise op
* add hack in reduction_operator.hpp to avoid compile error. To fix it, need to use element_wise_op in reduction op
* Add OutVectorSize as device and kernel tunable, also update to Elementwise Operations
* Move reduce operator mapping to host layer file reduction_operator_mapping.hpp from reduction_operator.hpp
* Change to the unary operators
* Move the definitions of unary operations to element_wise_operation.hpp
* re-org files
* Refine in device interfaces and multiblock kernels
* Split the reduction configurations into instances for specific methods
* Update in getTypeString() of device pool2d
* Renaming in host and kernel
* Tiny update in profiler/src/profiler.cpp
* Uncomment in device_operation/CMakeLists.txt to enable the building of all operations
* Make check_indices a templated function to remove some linking issue
* Renaming in the profiler reduce module
* Add support for double Reduction (but disable MultiblockAtomicAdd for double)
* Tiny correction of literal string
* Rename DevicePoolFwd to DevicePool2dFwd
* Split device_reduce_instance_xxx.cpp files according to the data types to speed up compiling
* Add comments for lists of configurations, lists of instances and references of add_reduce_instances_xxx
* Remove un-used header file gridwise_generic_reduction_wrapper_common.hpp
* Renaming and refining in the Reduction codes
* Tiny change in the unary operators
* Renaming symbols and files
* Renaming symbols in the kernels
* Move kernel kernel_set_buffer_value to separate file
* Add IndexDataType template parameter for kernels and use int32_t as index data type in device layer
* Tiny update in the kernels
* Remove definition of sqrtf()/isnan()/abs() for half_t due to some ADL issue
* Simplify a helper function in device layer
* Tiny adjustment in testing data initialization
* Renaming in kernel/device/host
* Add two testing scripts for reduction
* Refine the Unary operators in element_wise_operation.hpp
* Update in the reduce profiler module
* Update to the reduction testing scripts
* reduce compile parallelism
* change CI docker to rocm5.0
* remove unused variables
* fix build
Co-authored-by: Chao Liu <chao.liu2@amd.com>
* tweak conv for odd C
* update script
* clean up elementwise op
* fix build
* clean up
* added example for gemm+bias+relu+add
* added example for gemm+bias+relu
* add profiler for gemm_s_shuffle; re-org files
* add profiler
* fix build
* clean up
* clean up
* clean up
* fix build
* [What]
1. Add DeviceGemmXdl_C_Shuffle
2. Revise example of gemm_xdl
[Why] Prepare to add shuffle version of D = alpha * (A * B) + beta * C
[How] Imitate DeviceGemmXdl and device_conv2d_fwd_xdl_c_shuffle_nhwc_kyxc_nhwk.hpp
* Add online-compiling facility
* Synchronize from fwd-v4r5 and implement host interfaces to call conv-fwd v4r4/v4r5 using on-line compiling method
* Tiny adjustment to time reporting
* Use object assignment to replace explicit bytes copying in the first kernel of v4r4/v4r5
* Use single thread to assign descriptor object to device memory
* Adjust to the workload assignment of the two kernels of v4r4 (experimental)
* Revert "Adjust to the workload assignment of the two kernels of v4r4 (experimental)"
This reverts commit eb38461456bb0c82b6c0d32cdd616e181907e20c.
* Update to make constexpr for generating descriptor types in kernel 2 of dynamic conv-fwd v4r4
* Update to dynamic conv-fwd v4r4 online-compiling
* Update to dynamic conv-fwd v4r5 online-compiling (result not accurate)
* Tiny update to driver/CMakeLists.txt
* clang-format
* Tiny comments change
* Add env OLC_DUMP_SAVE_TMP_DIR to support saving of temperary dir
* Fwd v4r5 olc perf (#39)
* added hip-clang flags that fix perf issue of online compilation
* fix bug for olc fwd-v4r5-nchw
* Move constexpr and type reference statements out of the function body in conv-fwd v4r4/v4r5 kernel wrapper
* Remove printing in hip_build_utils.cpp
* Update to root CMakeLists.txt
* Revert "Move constexpr and type reference statements out of the function body in conv-fwd v4r4/v4r5 kernel wrapper"
This reverts commit 3d2c5d8ecdd8298b72d127110500ed5b38d9835c.
Co-authored-by: Chao Liu <chao.liu2@amd.com>
Co-authored-by: Chao Liu <lc.roy86@gmail.com>
Co-authored-by: root <root@dc-smc-18.amd.com>
* Use DynamicBuffer to hold raw pointer (to global and LDS memory)
* add workaround for compiler issue (inefficient ISA) of ds_write for int8x4, int8x8, int8x16
* Replace most raw index calculation to coordinate transformation
* Overhaul blockwise and threadwise GEMM
* Overhaul driver for gridwies GEMM kernel
Co-authored-by: Jing Zhang <jizhan@amd.com>
* Added bwd data v3r1: breaking down compute into a series of load balanced GEMM, and launch in a single kernel
* Added bwd data v4r1: like v3r1, but launch GEMMs in multiple kernels
* Tweaked v1r1 and v1r2 (atomic) on AMD GPU
* enabled atomic add in tensor copy
* added gridwise GEMM
* added backward data conv using GEMM + atomic
* added backward data conv using GEMM, no atomic
