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TERATEC 2016 Forum
Plenary sessions
Tuesday, June 28, 2016

Solver software infrastructure for exascale applications

David KEYES
Professor, Applied Mathematics and Computational Science Director, Extreme Computing Research Center King Abdullah University of Science and Technology & Adjunct Professor, Applied Mathematics and Applied Physics Columbia University

Abstract : At the heart of the G-8’s International Exascale Software Project (launched in 2009) is the belief that a vast array of applications share a core of tasks that can be abstracted and layered in such a way as to be served by a common software infrastructure, more efficiently than if each community develops their own independently. This philosophy is embedded in the “DNA” of the speaker’s institution, KAUST (also launched in 2009), especially with respect to solver software, represented by the speaker’s Extreme Computing Research Center (ECRC). What is general enough to be leveraged over many applications, however, needs to be tuned to specific hardware. Without co-design of software and hardware, performance of future applications may never exceed today’s few Petaflop/s.  The algorithmic adaptations required to migrate today’s successful “bulk synchronous” open source parallel scientific software base to the exascale environment include: (1) reducing synchronization scope and frequency, (2) reducing memory traffic per core, (3) exploiting more instruction-uniform concurrency, and (4) relying more on algorithms for fault tolerance than expensive hardware redundancy. For solvers, attention can be confined to a handful of algorithms that possess optimal complexity: lin-log scaling in problem size. Otherwise weak scaling to a billion cores is not practical.  We illustrate with examples from ongoing ECRC research.

Bio : David Keyes directs the Extreme Computing Research Center at KAUST. He earned a BSE in Aerospace and Mechanical Sciences from Princeton in 1978 and PhD in Applied Mathematics from Harvard in 1984. Keyes works at the interface between parallel computing and the numerical analysis of PDEs, with a focus on scalable implicit solvers. Newton-Krylov-Schwarz (NKS), Additive Schwarz Preconditioned Inexact Newton (ASPIN), and Algebraic Fast Multipole (AFM) methods are methods he helped name and is helping to popularize.  Before joining KAUST as a founding dean in 2009, he led multi-institutional scalable solver software projects in the SciDAC and ASCI programs of the US DOE, ran university collaboration programs at LLNL’s ISCR and NASA’s ICASE, and taught at Columbia, Old Dominion, and Yale Universities.  He is a Fellow of SIAM and AMS, and has been awarded the ACM Gordon Bell Prize, the IEEE Sidney Fernbach Award, and the SIAM Prize for Distinguished Service to the Profession.

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