MSPA-MCS: Data-Driven Parallelization of Time in Molecular Dynamics Simulations

Conventional parallelization strategies do not scale

well when the computational effort arises from the

need to simulate to long time spans, rather than from

large state space. Molecular Dynamics simulations

constitute an important class of applications where

this proves to be a bottleneck. The investigators

develop a new approach to parallelization of Molecular

Dynamics, which is based on the observation that

simulations typically occur in a context rich in data

from other related simulations. They use such data to

parallelize the time domain, which yields a more

scalable algorithm. This approach is based on the

observation that long time-spans are often encountered

in simulations with multiple time scales. The fine

scales are responsible for the large computational

effort. However, the important contribution of the

fine-scales is often to the effect they have on the

coarse scale. The investigators use reduced order

modeling to identify important coarse scale effects.

They use clustering and machine learning to

dynamically determine the relationship between the

simulation being performed and prior data. They use

ODE and controls theory for stability analysis,

uncertainty estimation, and system identification.

The investigators validate their techniques using a

variety of realistic applications in nano and bio-nano

materials. The importance of the applications chosen

arises from the fact that materials have historically

played a pivotal role in human progress. An indication

of their importance lies in the fact that eras of

human progress, such as the iron age and the bronze

age, are named after the materials that contributed to

such progress. Nano and bio-nano materials, designed

based on fundamental understanding at the atomic

scale, promise yet another revolution, leading to

products such as fuel efficient cars, disaster

resistant structures, and new ways of treating

diseases. The investigators' techniques remove an

important impediment to such developments.

Furthermore, the students involved obtain training in

interdisciplinary research. Inclusion of a

collaborator with a joint appointment at an HBCU

ensures that under-represented students too benefit

from this work.