Dr. Jeremy Kepner
MIT Lincoln Laboratory Fellow
Head, Lincoln Laboratory Supercomputing Center
Monday, October 10, 2016, 12:00 - 1:00 pm
120 Lewis Science Library, Washington Road and Ivy Lane
Big Data volume, velocity, and variety 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 wide 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 MIT Lincoln Laboratory Supercomputing Center (LLSC) and enable the LLSC to deliver leading edge technologies to thousands of scientists and engineers. This talk discusses the rapidly evolving computing landscape and how mathematically rigorous interfaces are the key to exploiting advanced computing capabilities.
Dr. Kepner is Lincoln Laboratory Fellow and leads the MIT Lincoln Laboratory Supercomputing Center (LLSC). His published works span signal processing, data mining, databases, high performance computing, graph algorithms, cyber security, visualization, cloud computing, random matrix theory, abstract algebra, bioinformatics, astronomy, physics, and astrophysics. He has authored two books on parallel computing and graph algorithms. He recently received Lincoln’s highest technical honor “for his leadership and vision in bringing supercomputing to Lincoln Laboratory through the establishment of LLGrid [now LLSC]; his pivotal role in open systems for embedded computing; his creativity in developing a novel database management language and schema; and his contributions to the field of graph analytics." Dr. Kepner is the Chair of the largest computing conference in New England (IEEE High Performance Extreme Computing) and Chair of SIAM Data Mining. Dr. Kepner received his Ph.D. in Astrophysics from Princeton University in 1998.
Organized and sponsored by the Princeton Institute for Computational Science and Engineering (PICSciE). Co-sponsored by the Center for Statistics and Machine Learning (CSML).