Code for an IBM-sponsored hackathon which was themed around demonstrating how parallel computing can decrease training time for deep learning models without sacrificing accuracy. I used a data set from UCI's machine learning repository on neutron star signals. I created a neural network for binary classification which I parallelized across multiple GPUs on Virginia Tech's computing clusters.
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Neural network I developed and distributed across multiple remote GPUs
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