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Fusion Conv+Bias+ReLU(+Add) (#62)
* fix relu * clean up * clean up * adding 1x1 conv * adding 1x1 conv * added 1x1 conv * refactor * refactor * refactor * added profiler for conv+bias+relu+add * clean up * adding conv+bias+relu * adding conv+bias+relu * added conv+bias+relu * Update README.md * update cpu verification * adding c shuffle * update static_tensor for dealing with invalid element * adding c shuffle * debugging * fix bug * convert to fp16 before shuffle * shuffle more than one M/NRepeat * clean up * remove coordinate step hack from GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v3r1 * clean up * remove coordinate step hack from all gridwise gemm xdl * clean up coordinate step hack * clean up coordinate step hack * ThreadwiseTensorSliceTransfer_v3r2 support pointwise op on both src and dst * adding output shuffle in conv+bias+relu+add * update * added conv+bias+relu+add with c shuffle * added conv+bias+relu+add with c shuffle * fix forward_sweep bugs in threadwise copy * clean up * refactor * clean up * clean up * added conv_c_shuffle+bias_relu * clean up * added conv+bias+relu+atomic_add * clean up * clean up * clean up * clean up * clean up * clean up * misc fixes; add 1x1 specialization * clean up * delete unused device op * clean up * add support for odd C value
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example/4_conv2d_fwd_xdl/README.md
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example/4_conv2d_fwd_xdl/README.md
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# Instructions for ```conv2d_fwd_xdl``` Example
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## Docker script
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```bash
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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 ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \
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rocm/tensorflow:rocm4.3.1-tf2.6-dev \
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/bin/bash
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```
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## Build ```conv2d_fwd_xdl```
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```bash
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mkdir build && cd build
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```
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```bash
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# Need to specify target ID, example below is gfx908
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cmake \
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-D BUILD_DEV=OFF \
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-D CMAKE_BUILD_TYPE=Release \
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-D CMAKE_CXX_FLAGS="-DCK_AMD_GPU_GFX908 --amdgpu-target=gfx908 -O3 " \
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-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \
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-D CMAKE_PREFIX_PATH=/opt/rocm \
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..
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```
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```bash
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make -j conv2d_fwd_xdl
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```
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## Run ```conv2d_fwd_xdl```
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```bash
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#arg1: verification (0=no, 1=yes)
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#arg2: initialization (0=no init, 1=integer value, 2=decimal value)
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#arg3: run kernel # of times (>1)
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#arg4 to 18: N, K, C, Y, X, Hi, Wi, Sy, Sx, Dy, Dx, LeftPy, LeftPx, RightPy, RightPx
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./example/conv2d_fwd_xdl 0 1 5
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```
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Result (MI100 @ 1087Mhz, 133.5TFlops peak FP16)
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```
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in_n_c_hi_wi: dim 4, lengths {128, 192, 71, 71}, strides {967872, 1, 13632, 192}
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wei_k_c_y_x: dim 4, lengths {256, 192, 3, 3}, strides {1728, 1, 576, 192}
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out_n_k_ho_wo: dim 4, lengths {128, 256, 36, 36}, strides {331776, 1, 9216, 256}
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arg.a_grid_desc_k0_m_k1_{216, 165888, 8}
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arg.b_grid_desc_k0_n_k1_{216, 256, 8}
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arg.c_grid_desc_m_n_{ 165888, 256}
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launch_and_time_kernel: grid_dim {1296, 1, 1}, block_dim {256, 1, 1}
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Warm up
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Start running 5 times...
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Perf: 1.43206 ms, 102.486 TFlops, 232.947 GB/s
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```
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