The Convergence of Machine Learning, Big Data, and Supercomputing
Machine learning, big data and simulation challenges have led to a proliferation of computing hardware and software solutions. Hyperscale data centers, accelerators and programmable logic can deliver enormous performance via a range of analytic environments and data-storage technologies. Effectively exploiting these capabilities for science and engineering requires mathematically rigorous interfaces that allow scientists and engineers to focus on their research and avoid rewriting software each time computing technology changes. Mathematically rigorous interfaces are at the core of the MIT Lincoln Laboratory Supercomputing Center and let it deliver leading-edge technologies to thousands of scientists and engineers. This talk discusses the rapidly evolving computing landscape and how mathematically rigorous interfaces are key to exploiting advanced computing capabilities.
Dr. Jeremy Kepner is a MIT Lincoln Laboratory Fellow. He founded the Lincoln Laboratory Supercomputing Center and pioneered the establishment of the Massachusetts Green High Performance Computing Center. He has developed novel big data and parallel computing software used by thousands of scientists and engineers worldwide. He has led several embedded computing efforts, which earned him a 2011 R&D 100 Award. Dr. Kepner has chaired SIAM Data Mining, the IEEE Big Data conference, and the IEEE High Performance Extreme Computing conference. Dr. Kepner is the author of two bestselling books, Parallel MATLAB for Multicore and Multinode Computers and Graph Algorithms in the Language of Linear Algebra. His peer-reviewed publications include works on abstract algebra, astronomy, astrophysics, cloud computing, cybersecurity, data mining, databases, graph algorithms, health sciences, plasma physics, signal processing, and 3D visualization. In 2014, he received Lincoln Laboratory's Technical Excellence Award.
Dr. Kepner holds a BA degree in astrophysics from Pomona College and a PhD degree in astrophysics from Princeton University.
Sponsored by the Department of Computer Science and the Center for Scientific Computing