June 1-5, 2020: Conference postponed to Summer 2022 due to COVID-19. Dates TBD.
Computational simulations are a key part of scientific research for government, industry, and academia, complementing laboratory experimentation and theory. However changes in computer architectures are leading to future supercomputers that will have billions of processors, as opposed to millions today. Further, 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. One such class of mathematical algorithms, parallel-in-time methods, is the subject of this workshop. In particular, parallel-in-time methods 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 for parallel-in-time to dramatically speed-up is vast, e.g., computational molecular dynamics (e.g., protein and DNA folding), computational biology (e.g., heart modeling), computational fluid dynamics (e.g., combustion, climate, and weather), and machine learning.
The primary focus of the proposed parallel-in-time workshop 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. This workshop aligns with the National Strategic Computing Initiative (NSCI) objective: “increase coherence between technology for modeling/simulation and data analytics”. 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.