Scaling molecular dynamics beyond 100,000 processor cores for large-scale biophysical simulations.
Jaewoon JungWataru NishimaMarcus DanielsGavin BascomChigusa KobayashiAdetokunbo AdedoyinMichael WallAnna LappalaDominic PhillipsWilliam FischerChang-Shung TungTamar SchlickYuji SugitaKarissa Y SanbonmatsuPublished in: Journal of computational chemistry (2019)
The growing interest in the complexity of biological interactions is continuously driving the need to increase system size in biophysical simulations, requiring not only powerful and advanced hardware but adaptable software that can accommodate a large number of atoms interacting through complex forcefields. To address this, we developed and implemented strategies in the GENESIS molecular dynamics package designed for large numbers of processors. Long-range electrostatic interactions were parallelized by minimizing the number of processes involved in communication. A novel algorithm was implemented for nonbonded interactions to increase single instruction multiple data (SIMD) performance, reducing memory usage for ultra large systems. Memory usage for neighbor searches in real-space nonbonded interactions was reduced by approximately 80%, leading to significant speedup. Using experimental data describing physical 3D chromatin interactions, we constructed the first atomistic model of an entire gene locus (GATA4). Taken together, these developments enabled the first billion-atom simulation of an intact biomolecular complex, achieving scaling to 65,000 processes (130,000 processor cores) with 1 ns/day performance. Published 2019. This article is a U.S. Government work and is in the public domain in the USA.
Keyphrases
- molecular dynamics
- density functional theory
- transcription factor
- mental health
- molecular dynamics simulations
- electronic health record
- gene expression
- machine learning
- genome wide
- big data
- physical activity
- dna damage
- emergency department
- working memory
- high resolution
- copy number
- wastewater treatment
- zika virus
- systematic review
- virtual reality