Tackling exascale software challenges in molecular dynamics simulations with 
GROMACS.

Páll, S.; Abraham, M. J.; Kutzner, C.; Hess, B.; Lindahl, E.

doi:10.1007/978-3-319-15976-8_1

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Tackling exascale software challenges in molecular dynamics simulations with GROMACS.

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Kutzner, C.
Department of Theoretical and Computational Biophysics, MPI for biophysical chemistry, Max Planck Society;

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http://link.springer.com/book/10.1007%2F978-3-319-15976-8
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Citation

Páll, S., Abraham, M. J., Kutzner, C., Hess, B., & Lindahl, E. (2015). Tackling exascale software challenges in molecular dynamics simulations with GROMACS. In S. Markidis, & E. Laure (Eds.), Solving Software Challenges for Exascale: International Conference on Exascale Applications and Software, EASC 2014, Stockholm, Sweden, April 2-3, 2014, Revised Selected Papers (pp. 3-27). Cham: Springer. doi:10.1007/978-3-319-15976-8_1.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0025-72AB-E

Abstract

GROMACS is a widely used package for biomolecular sim- ulation, and over the last two decades it has evolved from small-scale efficiency to advanced heterogeneous acceleration and multi-level paral- lelism targeting some of the largest supercomputers in the world. Here, we describe some of the ways we have been able to realize this through the use of parallelization on all levels, combined with a constant focus on absolute performance. Release 4.6 of GROMACS uses SIMD acceleration on a wide range of architectures, GPU offloading acceleration, and both OpenMP and MPI parallelism within and between nodes, respectively. The recent work on acceleration made it necessary to revisit the fun- damental algorithms of molecular simulation, including the concept of neighborsearching, and we discuss the present and future challenges we see for exascale simulation - in particular a very fine-grained task paral- lelism. We also discuss the software management, code peer review and continuous integration testing required for a project of this complexity.