Extensible and Scalable Adaptive Sampling on Supercomputers

Autor:	Hruska, Eugen, Balasubramanian, Vivekanandan, Lee, Hyungro, Jha, Shantenu, Clementi, Cecilia
Rok vydání:	2019
Předmět:	Quantitative Biology - Quantitative Methods Physics - Computational Physics
Druh dokumentu:	Working Paper
Popis:	The accurate sampling of protein dynamics is an ongoing challenge despite the utilization of High-Performance Computers (HPC) systems. Utilizing only "brute force" MD simulations requires an unacceptably long time to solution. Adaptive sampling methods allow a more effective sampling of protein dynamics than standard MD simulations. Depending on the restarting strategy the speed up can be more than one order of magnitude. One challenge limiting the utilization of adaptive sampling by domain experts is the relatively high complexity of efficiently running adaptive sampling on HPC systems. We discuss how the ExTASY framework can set up new adaptive sampling strategies, and reliably execute resulting workflows at scale on HPC platforms. Here the folding dynamics of four proteins are predicted with no a priori information. Comment: 17 pages, 9 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1907.06954 Zobrazit plný text záznamu View this record from Arxiv