cnn_cuda's Introduction
This lab uses the CNN algorithm described in the instructions. The input files consist of a CNN file describing the CNN and an input file containing a number of input matrices. The output files contain the output vectors for each input matrix. To run the code, use: cargo run --release -- <mode> <cnn_file> <input_file> <output_file> where <mode> is either "cpu" "cuda". All the files are pathnames (unlike in the earlier Sudoku example). You would typically use the following commands: cargo run --release -- cpu input/cnn.csv input/in.csv output/out.csv cargo run --release -- cuda input/cnn.csv input/in.csv output/out_cuda.csv The program outputs the time spent doing "actual work", which is the work of converting input matrices to output vectors. This measurement does not include I/O or the overhead of initializing the GPU. As such, the time should be lower for the CUDA version than the CPU version. The repo also includes 2 helper scripts, written in Python: generate.py generates random CNNs and input matrices, defaulting to "input/cnn.csv" and "input/in.csv" compare.py compares 2 output matrices to see if they are "close enough". Used to test the implementations for correctness. Reads output/out.csv and output/out_cuda.csv You can run each of them using the python3 command (e.g. "python3 compare.py").
cnn_cuda's People
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