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https://github.com/ROCm/composable_kernel.git
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67dcc552b6
* 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>
[ROCm/composable_kernel commit: 3835318cc3]
15 lines
755 B
Bash
Executable File
15 lines
755 B
Bash
Executable File
WORKSPACE=$1
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echo "workspace: " $WORKSPACE
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docker run \
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-it \
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--rm \
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--privileged \
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--group-add sudo \
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-w /root/workspace \
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-v $WORKSPACE:/root/workspace \
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rocm/tensorflow:rocm4.1-tf1.15-dev \
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/bin/bash
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#--network host \
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