Publication | Closed Access
Copernicus
48
Citations
19
References
2011
Year
Unknown Venue
Cluster ComputingEngineeringMolecular BiologyComputer ArchitectureHigh Performance ComputingMolecular DynamicsMolecular ComputingKinetic ClusteringParallel ComputingBiophysicsMassively-parallel ComputingPerformance-leading Molecular DynamicsLarge-scale SimulationBiomolecular DynamicsBiomolecular SimulationComputational BiologyParallel ProgrammingSystems BiologyComputational Biophysics
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.
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