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Thursday, March 16 • 8:45am - 9:30am
Keynote: "Algorithmic Adaptations to Extreme Scale" David Keyes, King Abdullah University

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Algorithmic adaptations to use next-generation computers closer to their potential are underway in Oil & Gas and many other fields. Instead of squeezing out flops – the traditional goal of algorithmic optimality, which once served as a reasonable proxy for all associated costs – algorithms must now squeeze synchronizations, memory, and data transfers, while extra flops on locally cached data represent only small costs in time and energy. After decades of programming model stability with bulk synchronous processing, new programming models and new algorithmic capabilities (to make forays into, e.g., inverse problems, data assimilation, and uncertainty quantification) must be co-designed with the hardware. We briefly recap the architectural constraints, then concentrate on two kernels that each occupy a large portion of all scientific computing cycles: large dense symmetric/Hermitian systems (covariances, Hamiltonians, Hessians, Schur complements) and large sparse Poisson/Helmholtz systems (solids, fluids, electromagnetism, radiation diffusion, gravitation).  We examine progress in porting solvers for these kernels (e.g., fast multipole, hierarchically low rank matrices, multigrid) to the hybrid distributed-shared programming environment, including the GPU and the MIC architectures.

avatar for David Keyes

David Keyes

Director, Extreme Computing Research Center, King Abdullah University of Science and Technology
David Keyes is the director of the Extreme Computing Research Center at King Abdullah University of Science and Technology, where he was a founding dean in 2009, and an adjoint professor of applied mathematics at Columbia University. Keyes earned his BSE in Aerospace and Mechanical Engineering from Princeton and his PhD in Applied Mathematics from Harvard. He works at the algorithmic interface between parallel computing and the... Read More →

Thursday March 16, 2017 8:45am - 9:30am
Room 103 BRC

Attendees (11)