Algorithms and Infrastructure for Molecular Dynamics Simulations

Ananth Grama
University Scholar and Professor of Computer Sciences
Purdue University.


Molecular dynamics (MD) approaches are at the core of diverse problems in
biophysical simulations, materials engineering, and chemical modeling,
among others. Over the past several years, with collaborators in various
application domains, we have investigated fast algorithms, mathematical
formalisms, software infrastructure, and more recently, application-specific
coarse-graining techniques and novel molecular dynamics techniques that further
augment traditional approches with information abstracted from quantum-scale
modeling.

In this talk, we describe our results in the development of
(i) fast algorithms for long-range potentials, (ii) error analysis and
acceleration techniques for multipole approximations, (iii) parallelism and
scaling properties, and (iv) applications of our techniques to sparse and
dense linear system solvers. In spite of various algorithmic and hardware
advances, molecular dynamics remains highly limited in its spatial and
temporal scales. For this reason, it is important to develop coarse-grained
models capable of fundamentally extending space and time scales, while
maintaining the fidelity and predictive properties of simulations. We
describe our work on the development of these models for the simulation of
biophysical membranes. Traditional molecular dynamics approaches do not
extend to reactive systems, since bonds are static through the simulation.
We conclude with a discussion of our more recent work on simulation of
reactive systems.


--
Various parts of this work are in collaboration with Eric Jakobsson,
Vipin Kumar, Sagar Pandit, Ahmed Sameh, Vivek Sarin, H. Larry Scott,
Shankar Subramaniam, Priya Vashishtha.
