CBMS Conference – Parallel Time Integration

June 1-5, 2020:   Conference tentatively rescheduled to June 7-11, 2021due to COVID-19.

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.
