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827301d95a
* Use thread cluster descriptor and explicit M_K 2d descriptor to simply Blockwise Reduction * Change by replacing ReduceDims by NumReduceDims as Device Reduce interface template parameter * Rename the folder name for the pool2d and reduce examples * Update to reduction test scripts * Add Readme for pool2d_fwd and reduce_blockwise examples * Tiny fix in reduce profiler and tiny update in reduce testing scripts * Tiny fix in testing script profile_reduce_no_index.sh * Tiny change in script/profile_reduce_with_index.sh * Renaming and refining in Reduction profiler/device layer/examples * Renaming and refining in Reduction profiler/device layer/examples * Renaming all NumReduceDims to NumReduceDim
Instructions for pool2d_fwd Example
Docker script
docker run \
-it \
--rm \
--privileged \
--group-add sudo \
-w /root/workspace \
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \
rocm/tensorflow:rocm4.3.1-tf2.6-dev \
/bin/bash
Build pool2d_fwd
mkdir build && cd build
# Need to specify target ID, example below is gfx908
cmake \
-D BUILD_DEV=OFF \
-D CMAKE_BUILD_TYPE=Release \
-D CMAKE_CXX_FLAGS="-DCK_AMD_GPU_GFX908 --amdgpu-target=gfx908 -O3 " \
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \
-D CMAKE_PREFIX_PATH=/opt/rocm \
..
make -j pool2d_fwd
Run pool2d_fwd
#arg1: verification (0=no, 1=yes)
#arg2: initialization (0=no init, 1=integer value, 2=decimal value)
#arg3: run kernel # of times (>1)
#arg4 to 15: N, C, Y, X, Hi, Wi, Sy, Sx, LeftPy, LeftPx, RightPy, RightPx
./example/pool2d_fwd 1 1 10
Result
in_n_c_hi_wi: dim 4, lengths {128, 192, 71, 71}, strides {967872, 1, 13632, 192}
out_n_c_ho_wo: dim 4, lengths {128, 192, 36, 36}, strides {248832, 1, 6912, 192}
launch_and_time_kernel: grid_dim {124416, 1, 1}, block_dim {64, 1, 1}
Warm up
Start running 10 times...
Perf: 0.415453 ms, 1.37996 TFlops, 749.726 GB/s
error: 0
max_diff: 0, 1, 1