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David E. Keyes

  • Ph.D. Applied Mathematics, Harvard University, 1984
  • M.S. Applied Mathematics, Harvard University, 1979
  • B.S. Engineering, Aerospace and Mechanical Sciences, Summa Cum Laude, Princeton University, 1978
  • Certificate, Program in Engineering Physics, Princeton University, 1978

Other Program Affiliations

Research Interests

David Keyes is Professor of Applied Mathematics and Computational Science and the Director of the Extreme Computing Research Center, having served as the Dean of the Division of Mathematical and Computer Sciences and Engineering at KAUST for its first 3.5 years. Also an Adjunct Professor and former Fu Foundation Chair Professor in Applied Physics and Applied Mathematics at Columbia University, and an affiliate of several laboratories of the U.S. Department of Energy, Keyes graduated in Aerospace and Mechanical Sciences from Princeton in 1978 and earned a doctorate in Applied Mathematics from Harvard in 1984. Before joining KAUST among the founding faculty, he led scalable solver software projects in the ASCI and SciDAC programs of the U.S. Department of Energy.

Keyes works at the algorithmic interface between parallel computing and the numerical analysis of partial differential equations, with a focus on implicit scalable solvers for emerging architectures and their use in the many large-scale applications in energy and environment governed by conservation laws that demand high performance because of high resolution, high dimension, high fidelity physical models, or the "multi-solve" requirements of optimization, control, sensitivity analysis, inverse problems, data assimilation, or uncertainty quantification.

He has named and contributed to Newton-Krylov-Schwarz (NKS), Additive Schwarz Preconditioned Inexact Newton (ASPIN), and Algebraic Fast Multipole (AFM) methods for large sparse linear and nonlinear systems arising from PDEs. Through the ECRC, he now works on meeting the requirements of drastic reductions in communication and synchronization, increases in concurrency for cores sharing memory locally, local load redistribution, and algorithm-based fault tolerance for these and other algorithms.

Selected Publications

  • R. Yokota, G. Turkiyyah & D. Keyes, "Communication Complexity of the Fast Multipole Method and its Algebraic Variants", Supercomput. Front. and Innov., 1:62–83, 2014.
  • D. Keyes et al. "Multiphysics Simulations: Challenges and Opportunities", Int. J. High Performance Computing Applications 27:5–83, 2013.
  • D. E. Keyes. "Exaflop/s – the Why and the How", Comptes Rendus 339:70–77, 2011.
  • D. A. Knoll & D. E. Keyes. "Jacobian-Free Newton-Krylov Methods: A Survey of Approaches and Applications", J. Comput. Phys., 193:357–397, 2004.
  • X.-C. Cai & D. E. Keyes. "Nonlinear Preconditioned Inexact Newton Algorithms", SIAM J. Sci. Comp. 24:183–200, 2002.