Among the algorithmic adaptations advocated to migrate today's successful bulk synchronous parallel scientific software base to the anticipated exascale environment are: (1) reducing synchronization scope and frequency, (2) reducing memory traffic per core, (3) exploiting more SIMD-style concurrency, (4) building more fault-tolerance into algorithms. We briefly recap the architectural constraints and map some current trends in algorithmic research being pursued at KAUST onto these directions.
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 popularize. Before joining KAUST as a founding dean in 2009, he led 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..