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* create files for xdlops * working on blockwise_gemm_xdlops * add KReduction * add m/n repeats * add 2x2 pipeline * added 128x128 wavegemm * use StaticBuffer of vector_type * break vector type to blk_size * add kpack into xldops_gemm and blockwise_gemm * abroadcast only * add fp32 mfma instructions * adding fp16 mfma * pack half4_t * rename kperwave to kpack * add 32x32x8fp16 * add fp16 mfma * clean code * clean code * V4r4 xdlops kpack (#35) * add kpack with incorrect results * bug fix for make_dynamic_naive_tensor_descriptor_aligned_v2 * add 1x1 kernel * add gridwise_gemm_v2 - single_buffer * enabled dwordx4 for fp16 Co-authored-by: Chao Liu <chao.liu2@amd.com> * refactor fwd-v4r4-xdlops * add v4r4-nhwc-xdlop * improve some perf of nhwc and nchw by tuning parameters, and change scheuduling in gridwise-gemm loop * tweak scheduling in gridwise gemm * add v4r3 with a single output copy * init commit: output with slice win * adding sliceWin * add multiple repeats pattern * starting adding bwd-v4r1-xdlops * use tuple as SrcBuffer * adding bwd-data v4r1 nhwc xdlops * fix bug in make_dynamic_naive_tensor_descriptor_aligned_v2() * fix bug in host bwd-data conv * initial implementation of bwd-data v4r1 nhwc xdlops * add launch bound flags * enable launch bound * add m/nrepeat=4 * tweak bwd-data v4r1 nhwc xdlops * added bwd-data v4r1 nhwc xlops with output A and weight B * add fwd-v4r4 nhwc xdlops, A input, B weight, C output Co-authored-by: Chao Liu <chao.liu2@amd.com>