S. Pronk, P. Larson, I. Pouya, G. Bowman, I. Haque, K. Beaucamp, B. Hess, V. S. Pande, P. M. Kasson, E. Lindahl.
Supercomputing 2011, submitted (2011)
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 0.6Å 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 50μs per day, currently infeasible even with custom hardware designed for simulations.