PI: Jeremy P. Bos, DataS, ECE
Sponsor: Department of Defense
Award: $459,894 | 3 Years
Awarded: April 2017
Abstract: This project will explore the nature of imaging in conditions characterized by extreme
anisoplanatism. Under these conditions each point in an image may be affected by
a locally unique blurring kernel implying a violation of the linear shift invariance.
Bos and his students will use a combination analysis and extensive experimental data
to develop new models and new understanding of this phenomenon. Bos has also proposed
using angular diversity as a means of mitigating the effects of extreme anisoplanatism
on imaging and beam control problems.
PI: Timothy C. Havens, DataS, Computing
Sponsor: Department of Defense
Award: $96,643 | 1 Years
Awarded: February 2019
PI: Benjamin Ong, DataS, Math
Sponsor: National Science Foundation
Award: $36,636 | 1 Years
Awarded: October 2019
Abstract: 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.
PI: Weihua Zhou, DataS, CMH
Sponsor: Department of Health and Human Services (FPT-Tulane University)
Award: $24,497 | 1 Years
Awarded: November 2019
PI: Hairong Wei
Sponsor: NSF (Kansas State University)
Amount Funded: $79,765
Date Awarded: August 2021
PI: Sidike M. Paheding
Co-PI: Samantha L. Smith
Sponsor: NSF
Amount Funded: $69,711
Date Awarded: August 2021
PI: Snehamoy Chatterjee
Sponsor: DHHS
Amount Funded: $288,343
Date Awarded: August 2021
PI: Snehamoy Chatterjee
Sponsor: Newmont Mining Corp
Amount Funded: $25,000
Date Awarded: June 2021
PI: Timothy C. Havens
Co-PI: Tony J. Pinar
Sponsor: Restricted
Amount Funded: $428,707
Date Awarded: August 2020
PI: Xiaoyong (Brian) Yuan
Co-PI: Lan (Emily) Zhang
Sponsor: NSF
Amount Funded: $309,170
Date Awarded: July 2021
PI: Xiaoyong (Brian) Yuan
Sponsor: Oak Ridge Associated Universities
Amount Funded: $5,000
Date Awarded: June 2022