Ph.D. Defense of Dissertation Announcement

Title: High-Performance Algorithms and Software for Large-Scale Molecular
Simulation

Xing Liu
School of Computational Science and Engineering
College of Computing
Georgia Institute of Technology

Date: Wednesday, December 10, 2014
Time: 10:00am - 12:00pm EST
Location: KACB 1212


Committee:
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Prof. Edmond Chow (Advisor, School of Computational Science and
Engineering, Georgia Tech)
Prof. David A. Bader (School of Computational Science and Engineering,
Georgia Tech)
Prof. David Sherrill (School of Chemistry and Biochemistry, Georgia Tech)
Prof. Jeffrey Skolnick (Center for the Study of Systems Biology; School of
Biology, Georgia Tech)
Prof. Richard Vuduc (School of Computational Science and Engineering,
Georgia Tech)


Abstract:
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Molecular simulation is an indispensable tool in many different
disciplines such as physics, biology, chemical engineering, materials
science, drug design, and others. Performing large-scale molecular
simulation is of great interest to biologists and chemists, because many
important biological and pharmaceutical phenomena can only be observed in
very large molecule systems and after sufficiently long time dynamics. On
the other hand, molecular simulation methods usually have very steep
computational costs, which limits current molecular simulation studies to
relatively small systems. The gap between the scale of molecular
simulation that existing techniques can handle and the scale of interest
has become a major barrier for applying molecular simulation to study
real-world problems.

In order to study large-scale molecular systems using molecular
simulation, it requires developing highly parallel simulation algorithms
and constantly adapting the algorithms to rapidly changing high
performance computing architectures. However, many existing algorithms and
codes for molecular simulation are from more than a decade ago, which were
designed for sequential computers or early parallel architectures. They
may not scale efficiently and do not fully exploit features of today's
hardware. Given the rapid evolution in computer architectures, the time
has come to revisit these molecular
simulation algorithms and codes.

In this thesis, we demonstrate our approach to addressing the
computational challenges of large-scale molecular simulation by presenting
both the high-performance algorithms and software for two important
molecular simulation applications: Hartree-Fock (HF) calculations and
hydrodynamics simulations, on highly parallel computer architectures. The
algorithms and software presented in this thesis have been used by
biologists and chemists to study some problems that were unable to solve
using existing codes. The parallel techniques and methods developed in
this work can be also applied to other molecular simulation applications.