mkdir build
cd build
cmake ..
make
Note: The most recent cuDNN distribution will be obtained automatically by installing PyTorch into the build directory.
Run all tests at once:
cd build
ctest
Run individual test, providing the following arguments:
$ ./bin/benchmark file_name data_type all_formats operation_mode num_repeats [input_tensor_format output_tensor_format kernel_tensor_format]file_name: path to the file with convolution cases (example);output_file_name: path to the output file with benchmark results;data_type: data type used (accepted values arefp16,fp32,fp64,int8,uint8,int32,int8x4,uint8x4,uint8x32);all_formats:1if all input/output/tensor formats should be tested,0to run with specific data formats only;num_repeats: number of repetitions for each convolution algorithm.
If all_formats is set to 0, the following additional arguments must be specified:
input_tensor_format: input tensor data format (accepted values areNCHW,NHWC,NCHW_VECT_C);output_tensor_format: output tensor data format (accepted values areNCHW,NHWC,NCHW_VECT_C);kernel_tensor_format: kernel tensor data format (accepted values areNCHW,NHWC,NCHW_VECT_C).
Examples:
- Test specific data formats:
$ ./bin/benchmark conv_example.txt out_example.csv fp32 0 100 NHWC NHWC NHWC- Test all data formats:
$ ./bin/benchmark conv_example.txt out_example.csv fp32 1 1000Running the benchmark produces a output_file_name file in your working directory.
Example contents for ./bin/benchmark conv_example.txt out_example.txt fp32 0 1 10 NCHW NCHW NCHW:
A value n/a means that the combination of the input tensor dimension, filter tensor dimension and output tensor dimension is not supported for the specified algorithm on your GPU.
A value - means that this convolution not supported for the specified algorithm on your GPU.
input_format output_format filter_format W H C N K S R pad_w pad_h stride_w stride_h out_w out_h input_stride_w input_stride_h filter_stride_w filter_stride_h FWD_GEMM FWD_GEMM WORKSPACE FWD_IMPLICIT_GEMM FWD_IMPLICIT_GEMM WORKSPACE FWD_PRECOMP_GEMM FWD_PRECOMP_GEMM WORKSPACE FWD_DIRECT FWD_DIRECT WROKSPACE FWD_FFT FWD_FFT WORKSPACE FWD_FFT_TILING FWD_FFT_TILING WORKSPACE FWD_WINOGRAD FWD_WINOGRAD WORKSPACE FWD_WINOGRAD_NONFUSED FWD_WINOGRAD_NONFUSED WORKSPACE BWD_FILTER_ALGO_0 BWD_FILTER_ALGO_0 WORKPACE BWD_FILTER_ALGO_1 BWD_FILTER_ALGO_1 WORKSPACE BWD_FILTER_ALGO_3 BWD_FILTER_ALGO_3 WORKSPACE BWD_FILTER_FFT BWD_FILTER_FFT WORKSPACE BWD FILTER FFT_TILING BWD FILTER FFT_TILING WORKSPACE BWD_DATA_ALGO_0 BWD_DATA_ALGO_0 WORKSPACE BWD_DATA_ALGO_1 BWD_DATA_ALGO_1 WORKSPACE BWD_DATA_FFT BWD_DATA_FFT WORKSPACE BWD_DATA_FFT_TILING BWD_DATA_FFT_TILING WORKSPACE BWD_DATA_WINOGRAD BWD_DATA_WINOGRAD WORKSPACE BWD_DATA_WINOGRAD_NONFUSED BWD_DATA_WINOGRAD_NONFUSED WORKSPACE
NCHW NCHW NCHW 1 1 256 32 324 3 3 1 1 1 1 1 1 1 1 1 1 370.914 294912 471.803 0 587.052 9216 n/a 15303.9 212963328 42105.4 441769984 7298.59 8754448 2435.43 14616576 8761.88 0 333.403 6336 8901.35 0 n/a n/a 3661.55 0 1157.1 0 11922.6 217976832 38886.3 441769984 6682.76 8360960 2169.12 14616576
NCHW NCHW NCHW 1 1 256 32 16 3 3 1 1 1 1 1 1 1 1 1 1 231.894 294912 457.18 0 452.277 9216 n/a 2915.1 28459008 9094.39 55730176 562.581 671808 417.447 1843200 369.539 0 43.1993 576 366.571 0 n/a n/a 494.008 0 291.386 0 1501.37 19021824 4851.48 55730176 649.183 410624 398.059 1843200
NCHW NCHW NCHW 3 3 256 32 324 3 3 1 1 1 1 3 3 1 1 1 1 1474.53 2654208 2193.58 0 1353.02 60 n/a 15177.2 212963328 43215.7 441769984 3892.56 8754448 2453.19 14616576 9273.82 0 1711.97 2572 1770.54 2356 13231.9 191476224 n/a 4373.88 0 1019.39 2236 11924.6 217976832 39019.9 441769984 3586.94 8360960 2173.33 14616576
NCHW NCHW NCHW 3 3 256 32 16 3 3 1 1 1 1 3 3 1 1 1 1 348.08 2654208 652.083 0 301.795 60 n/a 2989.4 28459008 9137.38 55730176 421.972 671808 420.687 1843200 423.354 0 139.508 2428 126.237 2356 1967.64 20072448 n/a 965.804 0 123.734 2236 1342.91 19021824 4955.75 55730176 352.066 410624 411.616 1843200
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