in
collaboration with
ACM/SIGSIM
March 25 - 29, 2007
Norfolk
Marriott Waterside
Norfolk,
VA
General Chair
Dr.
Maurice J. Ades
Westinghouse Savannah River Company, USA
Vice General Chair
Dr. Hassan Rajaei
Bowling Green State University, USA
Program Chair
Michael J. Chinni
U.S. ARMY -
RDECOM - ARDEC
Exhibits Chair
Steve Branch
SCS
Sponsored by
The Society for Modeling and Simulation International
P.O. Box 17900
San Diego, CA 92177-7900
Tel: 858-277-3888
Fax: 858-277-3930
E-mail: scs@scs.org
http://www.scs.org
in
collaboration with
ACM/SIGSIM
High-Performance Computing Symposium 2007 (HPC'07)
Plenary Keynote Speakers
part of the
Spring
Simulation Multiconference 2007 (SpringSim'07)
 |
Mathematical Software for High-end Computational Science and EngineeringDavid E. KeyesFu Foundation Professor of Applied Mathematics Department of Applied Physics and Applied Mathematics Columbia University New York City, New York |
 |
Multiscale, multirate scientific and engineering applications based
on systems of partial differential equations possess resolution
requirements that are typically inexhaustible and demand execution on
the highest-capability computers available, which will soon reach the
petascale. While the variety of applications is enormous, their needs
for mathematical software infrastructure are surprisingly coincident.
Domains with complex geometry require versatile meshing and
discretization tools. Resolution requirements that evolve with the
solution require dynamic adaptivity. Implicit methods for stable and
accurate integration of transient problems and efficient treatments for
equilibrium problems lead to large, ill-conditioned algebraic systems
that must be solved with an algorithmic complexity that is close to
linear in problem size or storage complexity. Distributed memory
architectures demand efficient means of creating and managing
load-balanced partitions of unstructured objects. These and other
algorithmic challenges that are generic to nearly all mesh- and
particle-based applications are addressed in the SciDAC Institute and
Centers for Enabling Technologies in mathematics, which we briefly
overview in this talk. The chief bottleneck to scalability is often the solver. At their current scalability limits, many applications spend a vast majority of their operations in solvers, due to solver algorithmic complexity that is superlinear in the problem size, whereas other phases scale linearly. Furthermore, the solver may be the phase of the simulation with the poorest parallel scalability, due to intrinsic global dependencies. The Towards Optimal PDE Simulations (TOPS) center focuses on relieving this bottleneck while providing a multilevel programming interface that allows users to advance from initial concerns of correctness and robustness to ultimate concerns of efficiency and performance portability. |
