no code implementations • 8 Aug 2019 • Dalton Lunga, Jonathan Gerrand, Hsiuhan Lexie Yang, Christopher Layton, Robert Stewart
By taking advantage of Apache Spark, Nvidia DGX1, and DGX2 computing platforms, we demonstrate unprecedented compute speed-ups for deep learning inference on pixel labeling workloads; processing 21, 028~Terrabytes of imagery data and delivering an output maps at area rate of 5. 245sq. km/sec, amounting to 453, 168 sq. km/day - reducing a 28 day workload to 21~hours.