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Teaching Accelerated Computing and Deep Learning at a Large-Scale with the NVIDIA Deep Learning Institute

Workshop: Ninth SC Workshop on Best Practices for HPC Training and Education

Authors: Bálint Pál Gyires-Tóth (Budapest University of Technology and Economics); Işıl Öz (Izmir Institute of Technology, Turkey); and Joe Bungo (NVIDIA Corporation, Deep Learning Institute)

Abstract: Researchers and developers in a variety of fields have benefited from the massively parallel processing paradigm. Numerous tasks are facilitated by the use of accelerated computing, such as graphics, simulations, visualizations, cryptography, data science, and machine learning. Over the past years, machine learning and in particular deep learning have received much attention. The development of such solutions requires a different level of expertise and insight than that required for traditional software engineering. Therefore, there is a need for novel approaches to teaching people about these topics.

This presentation outlines the primary challenges of accelerated computing and deep learning education, discusses the methodology and content of the NVIDIA Deep Learning Institute, presents the results of a quantitative survey conducted after full-day workshops, and demonstrates a sample adoption of DLI teaching kits for teaching heterogeneous parallel computing.

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