The Impact of Heterogeneous Computing on Workflows for Biomolecular Simulation and Analysis

Abstract

The field of biomolecular simulation has matured to where detailed, accurate, and functionally relevant information that complements experimental data about the structure, dynamics, and interactions of biomolecules can now be routinely discovered. This has been enabled by access to large-scale and heterogeneous high-performance computing resources, including special-purpose hardware. The improved performance of modern simulation methods coupled with hardware advances is shifting the rate-limiting steps of common biomolecular simulations of small to moderately sized systems from the generation of data (for example, via production molecular dynamics simulations that used to take weeks or even months) to the pre- and postprocessing phases of the workflow, namely, simulation setup and data processing, management, and analysis. Because the computational resources that are optimal for generating data aren't necessarily the same as for processing that data, access to heterogeneous computational resources enables a broader exploration of biomolecular structure and dynamics by facilitating distinct aspects of typical biomolecular simulation workflows, which might not be as efficient on a one-size-fits-all computational platform.