Efficient SDS Simulations on Multi-GPU Nodes of XSEDE High-end Clusters
Computer and Information Sciences, University of Delaware, Newark, DE 19716
Eighth IEEE International Conference on e-Science and Grid Technologies (eScience), 2013
@article{schlachter2013efficient,
title={Efficient SDS Simulations on Multi-GPU Nodes of XSEDE High-end Clusters},
author={Schlachter, Samuel and Herbein, Stephen and Taufer, Michela and Ou, Shuching and Patel, Sandeep and Logan, Jeremy S},
year={2013}
}
Efficiently studying Sodium Dodecyl Sulfate (SDS) molecules’ formations in the presence of different molar concentrations on high-end GPU clusters whose nodes share accelerators exposes us to several challenges, including the need to dynamically adapt the job lengths. Neither virtualization nor lightweight OS solutions can easily support generality, portability, and maintainability in concert. Our solution complements rather than rewrites existing workflow and resource managers with a companion module that complements functions of the workflow manager and a wrapper module that extends functions of the resource managers. Results on the Keeneland cluster show how, by using our modules, accelerated SDS simulations more efficiently use the cluster’s GPUs while leading to relevant scientific observations.
October 25, 2013 by hgpu
