Title: Scientific Discovery through Advanced Computing

Abstract:

The Scientific Discovery through Advanced Computing (SciDAC) initiative is a
set of interconnected projects --- science, software development, and research
to directed toward the latter --- designed to support simulation, data
exploration, and collaboration in many thrust areas of the U.S. Department of
Energy, including: climate modeling, fusion energy, chemistry and materials
science, astrophysics, and high energy and particle physics. Lab and
university-based SciDAC participants are creating a new generation of
scientific simulation codes for terascale systems. The software spills over
into many projects not officially in the SciDAC portfolio.

This lecture briefly reviews the sweep of SciDAC and then focuses on some
particular advances in the U.S. magnetic fusion energy program enabled by the
introduction of solver software from the speaker's SciDAC project, Terascale
Optimal PDE Simulations (TOPS, www.tops-scidac.org).

Brief Bio:

David E. Keyes is the Fu Foundation Professor of Applied Mathematics in the
Department of Applied Physics and Applied Mathematics at Columbia University,
an affiliate of the Computational Science Center (CSC) at Brookhaven National
Laboratory, and Acting Director of Institute for Scientific Computing Research
(ISCR) at the Lawrence Livermore National Laboratory.

Keyes graduated summa cum laude with a B.S.E. in Aerospace and Mechanical
Sciences and a Certificate in Engineering Physics from Princeton University in
1978. He received his Ph.D. in Applied Mathematics from Harvard University in
1984. He then post-doc'ed in the Computer Science Department at Yale University
and taught there for eight years, as Assistant and Associate Professor of
Mechanical Engineering, prior to joining Old Dominion University and the
Institute for Computer Applications in Science & Engineering (ICASE) at the
NASA Langley Research Center in 1993. At Old Dominion, Keyes was the Richard F.
Barry Professor of Mathematics & Statistics and founding Director of the Center
for Computational Science.

Keyes is the author or co-author of over 100 publications in computational
science and engineering, numerical analysis, and computer science. He has
co-edited 8 conference proceedings concerned with parallel algorithms and has
delivered over 200 invited presentations at universities, laboratories, and
industrial research centers in over 20 countries and 35 states of the U.S. With
backgrounds in engineering, applied mathematics, and computer science, and
consulting experience with industry and national laboratories, Keyes works at
the algorithmic interface between parallel computing and the numerical analysis
of partial differential equations, across a spectrum of aerodynamic,
geophysical, and chemically reacting flows. Newton-Krylov-Schwarz parallel
implicit methods, introduced in a 1993 paper he co-authored at ICASE, are now
widely used throughout engineering and computational physics, and have been
scaled to thousands of processors.