Award Number1933342
Funding AgencyNational Science Foundation
Effective Date2020-01-01
Expiration Date2020-12-31
Funding Amount$36,636

Abstract

This award provides support for the NSF-CBMS Conference on Parallel Time Integration to be held on June 1-5, 2020, at Michigan Technological University. The primary focus of the conference is to educate and inspire researchers and students in new and innovative numerical techniques for the parallel-in-time solution of large-scale evolution problems on modern supercomputing architectures, and to stimulate further studies in their analysis and applications. It aligns with the National Strategic Computing Initiative (NSCI) objective: "increase coherence between technology for modeling/simulation and data analytics". Computational simulations are a key part of scientific research for government, industry, and academia, complementing laboratory experimentation and theory. Changes in computer architectures are leading to future supercomputers that will have billions of processors, as opposed to millions today. However, each individual processor will be no faster than individual processors today. Thus, these next generation machines will no longer automatically provide a speedup to existing computational simulations, and new mathematical algorithms must be developed and deployed that can utilize this unprecedented number of processors. Parallel-in-time methods provide one such class of mathematical algorithms. They add a new dimension (time) of parallelism and thus allow existing computer models to be extended to next generation supercomputers. The range of potential applications is vast: computational molecular dynamics such as protein and DNA folding, computational biology (e.g., heart modeling), computational fluid dynamics (e.g., combustion, climate, and weather), and machine learning.

The conference will feature ten lectures by Professor Gander, an expert in parallel time integration. Using appropriate mathematical methodologies from the theory of partial differential equations in a functional analytic setting, numerical discretizations, integration techniques, and convergence analyses of these iterative methods, conference participants will be exposed to the numerical analysis of parallel-in-time methodologies and their implementations. The proposed topics include multiple shooting type methods, waveform relaxation methods, time-multigrid methods, and direct time-parallel methods. These lectures will be accessible to a wide audience from a broad range of disciplines, including mathematics, computer science and engineering. The conference website is at- http://conferences.math.mtu.edu/cbms2020/

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.