Copernicus: a new paradigm for parallel adaptive molecular dynamics

  • Authors:

  • Sander Pronk;Per Larsson;Iman Pouya;Gregory R. Bowman;Imran S. Haque;Kyle Beauchamp;Berk Hess;Vijay S. Pande;Peter M. Kasson;Erik Lindahl

  • Affiliations:

  • Royal Institute of Technology, Stockholm, Sweden;University of Virginia, Charlottesville, VA;Royal Institute of Technology, Stockholm, Sweden;Stanford University, Stanford, CA;Stanford University, Stanford, CA;Stanford University, Stanford, CA;Royal Institute of Technology, Stockholm, Sweden;Stanford University, Stanford, CA;University of Virginia, Charlottesville, VA;Royal Institute of Technology, Stockholm, Sweden

  • Venue:
  • Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

Biomolecular simulation is a core application on supercomputers, but it is exceptionally difficult to achieve the strong scaling necessary to reach biologically relevant timescales. Here, we present a new paradigm for parallel adaptive molecular dynamics and a publicly available implementation: Copernicus. This framework combines performance-leading molecular dynamics parallelized on three levels (SIMD, threads, and message-passing) with kinetic clustering, statistical model building and real-time result monitoring. Copernicus enables execution as single parallel jobs with automatic resource allocation. Even for a small protein such as villin (9,864 atoms), Copernicus exhibits near-linear strong scaling from 1 to 5,376 AMD cores. Starting from extended chains we observe structures 0.6 Å from the native state within 30h, and achieve sufficient sampling to predict the native state without a priori knowledge after 80--90h. To match Copernicus' efficiency, a classical simulation would have to exceed 50 microseconds per day, currently infeasible even with custom hardware designed for simulations.