Convolutional Neural Network on Embedded Linux System-on-Chip: A Methodology and Performance Benchmark
Space and Naval Warfare Systems Center Pacific San Diego United States
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Deep convolutional neural networks CNNs detect and classify features of interest in sensory input data. There is a need to investigate how best to implement CNNs for Navy and Department of Defense DoD use in platforms with minimal size, weight, and power SWaP capacity, since much academic research focuses solely on achieving the highest performance on a specific dataset with minimal concern of compute resources. This report describes a methodology, configuration, and experimental results of a first step in this studya baseline for comparison of benchmarking metrics. A baseline is important for quantifying any further results and to estimate potential benefits of new and more advanced ideas.