Breaking the mold: Overcoming the time constraints of molecular dynamics on general-purpose hardware
Abstract
The evolution of molecular dynamics (MD) simulations has been intimately linked to that of computing hardware. For decades following the creation of MD, simulations have improved with computing power along the three principal dimensions of accuracy, atom count (spatial scale), and duration (temporal scale). Since the mid-2000s, computer platforms have, however, failed to provide strong scaling for MD, as scale-out central processing unit (CPU) and graphics processing unit (GPU) platforms that provide substantial increases to spatial scale do not lead to proportional increases in temporal scale. Important scientific problems therefore remained inaccessible to direct simulation, prompting the development of increasingly sophisticated algorithms that present significant complexity, accuracy, and efficiency challenges. While bespoke MD-only hardware solutions have provided a path to longer timescales for specific physical systems, their impact on the broader community has been mitigated by their limited adaptability to new methods and potentials. In this work, we show that a novel computing architecture, the Cerebras wafer scale engine, completely alters the scaling path by delivering unprecedentedly high simulation rates up to 1.144 M steps/s for 200 000 atoms whose interactions are described by an embedded atom method potential. This enables direct simulations of the evolution of materials using general-purpose programmable hardware over millisecond timescales, dramatically increasing the space of direct MD simulations that can be carried out. In this paper, we provide an overview of advances in MD over the last 60 years and present our recent result in the context of historical MD performance trends.
Article Details
Journal Info
The Journal of Chemical Physics
American Institute of Physics
Authors (14)
Danny Perez
Theoretical Division
Aidan Thompson
Sandia National Laboratories 2 , Albuquerque, New Mexico 87123,
Stan Moore
Sandia National Laboratories 2 , Albuquerque, New Mexico 87123,
Tomas Oppelstrup
Ilya Sharapov
Cerebras Systems 4 , Sunnyvale, California 94085,
Kylee Santos
Cerebras Systems 4 , Sunnyvale, California 94085,
Amirali Sharifian
Cerebras Systems 4 , Sunnyvale, California 94085,
Delyan Z. Kalchev
Cerebras Systems 4 , Sunnyvale, California 94085,
Robert Schreiber
Cerebras Systems 4 , Sunnyvale, California 94085,
Scott Pakin
Los Alamos National Laboratory 1 , Los Alamos, New Mexico 87545,
Edgar A. Leon
Lawrence Livermore National Laboratory 3 , Livermore, California 94550,
James H. Laros
Sandia National Laboratories 2 , Albuquerque, New Mexico 87123,
Michael James
Cerebras Systems 4 , Sunnyvale, California 94085,
Sivasankaran Rajamanickam
Sandia National Laboratories 2 , Albuquerque, New Mexico 87123,