May 15, 2017
Conference Paper

Designing Scalable Distributed Memory Models: A Case Study

Abstract

Supercomputers complexity continue to rapidly increase, requiring novel software solutions to aid in addressing the extreme abundance of parallelism, restrictive power constraints, and fault tolerance requirements. While industrial standards like MPI and OpenMP have undergone extensive efforts to prepare for future systems [1, 2], ne grain asynchronous runtimes have demonstrated an innate agility in extracting performance which is otherwise arduous to attain with current execution models

Revised: June 4, 2018 | Published: May 15, 2017

Citation

Landwehr J.B., J.D. Suetterlein, J.B. Manzano Franco, A. Marquez, K.J. Barker, and G.R. Gao. 2017. Designing Scalable Distributed Memory Models: A Case Study. In Proceedings of the Computing Frontiers Conference (CF 2017), May 15-17, 2017, Siena, Italy, 174-182. New York, New York:ACM. PNNL-SA-124960. doi:10.1145/3075564.3077425