Breaking the mold: Overcoming the time constraints of molecular dynamics on general-purpose hardware

D Danny Perez (Theoretical Division) A Aidan Thompson (Sandia National Laboratories 2 , Albuquerque, New Mexico 87123,) S Stan Moore (Sandia National Laboratories 2 , Albuquerque, New Mexico 87123,) T Tomas Oppelstrup I Ilya Sharapov (Cerebras Systems 4 , Sunnyvale, California 94085,) K Kylee Santos (Cerebras Systems 4 , Sunnyvale, California 94085,) A Amirali Sharifian (Cerebras Systems 4 , Sunnyvale, California 94085,) D Delyan Z. Kalchev (Cerebras Systems 4 , Sunnyvale, California 94085,) R Robert Schreiber (Cerebras Systems 4 , Sunnyvale, California 94085,) S Scott Pakin (Los Alamos National Laboratory 1 , Los Alamos, New Mexico 87545,) E Edgar A. Leon (Lawrence Livermore National Laboratory 3 , Livermore, California 94550,) J James H. Laros (Sandia National Laboratories 2 , Albuquerque, New Mexico 87123,) M Michael James (Cerebras Systems 4 , Sunnyvale, California 94085,) S Sivasankaran Rajamanickam (Sandia National Laboratories 2 , Albuquerque, New Mexico 87123,)

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

Volume / Issue Vol. 162, Issue 7
Published February 21, 2025
ISSN 0021-9606
Publisher American Institute of Physics

Journal Info

The Journal of Chemical Physics

American Institute of Physics

ISSN: 0021-9606 Physical Sciences

Authors (14)

D

Danny Perez

Theoretical Division

A

Aidan Thompson

Sandia National Laboratories 2 , Albuquerque, New Mexico 87123,

S

Stan Moore

Sandia National Laboratories 2 , Albuquerque, New Mexico 87123,

T

Tomas Oppelstrup

I

Ilya Sharapov

Cerebras Systems 4 , Sunnyvale, California 94085,

K

Kylee Santos

Cerebras Systems 4 , Sunnyvale, California 94085,

A

Amirali Sharifian

Cerebras Systems 4 , Sunnyvale, California 94085,

D

Delyan Z. Kalchev

Cerebras Systems 4 , Sunnyvale, California 94085,

R

Robert Schreiber

Cerebras Systems 4 , Sunnyvale, California 94085,

S

Scott Pakin

Los Alamos National Laboratory 1 , Los Alamos, New Mexico 87545,

E

Edgar A. Leon

Lawrence Livermore National Laboratory 3 , Livermore, California 94550,

J

James H. Laros

Sandia National Laboratories 2 , Albuquerque, New Mexico 87123,

M

Michael James

Cerebras Systems 4 , Sunnyvale, California 94085,

S

Sivasankaran Rajamanickam

Sandia National Laboratories 2 , Albuquerque, New Mexico 87123,