Dongarra Gives Deep-Learning a Python Interface With RaPyDLI

An NSF-funded project called “Rapid Python Deep Learning Infrastructure”, or RaPyDLI received nearly $1 million in NSF grants. The project led by supercomputing luminaries Jack Dongarra (University of Tennessee) and Geoffrey Fox (Indiana University) along with Andrew Ng (Stanford, Baidu and Coursera) will allow users to program deep learning models in Python and port them to supercomputers and scale-out to cloud systems. Specifically, “RaPyDLI will be built as a set of open source modules that can be accessed from a Python user interface but executed interoperably in a C/C++ or Java environment on the largest supercomputers or clouds with interactive analysis and visualization. RaPyDLI will support GPU accelerators and Intel Phi coprocessors and a broad range of storage approaches including files, NoSQL, HDFS and databases.”

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