Enabling High‐Performance Cloud Computing for Earth Science Modeling on Over a Thousand Cores: Application to the GEOS‐Chem Atmospheric Chemistry Model
Name
J Adv Model Earth Syst - 2020 - Zhuang - Enabling High‐Performance Cloud Computing for Earth Science Modeling on Over a.pdf
Description
Published version
Size
11.92 MB
Format
Adobe PDF
Checksum (MD5)
21b0a8cabb2e5c1119eb155b34c7bd9c
Author(s)
Zhuang, Jiawei
Jacob, Daniel J
Lin, Haipeng
Lundgren, Elizabeth W
Yantosca, Robert M
Gaya, Judit Flo
Sulprizio, Melissa P
Eastham, Sebastian D
Date Issued
March 25, 2020
Journal
Journal of Advances in Modeling Earth Systems
Publisher
American Geophysical Union
Citation
Zhuang, J., Jacob, D. J., Lin, H., Lundgren, E. W., Yantosca, R. M., Gaya, J. F., et al (2020). Enabling high-performance cloud computing for Earth science modeling on over a thousand cores: Application to the GEOS-Chem atmospheric chemistry model. Journal of Advances in Modeling Earth Systems, 12, e2020MS002064.
Version
Final published version
Abstract
Cloud computing platforms can facilitate the use of Earth science models by providing immediate access to fully configured software, massive computing power, and large input data sets. However, slow internode communication performance has previously discouraged the use of cloud platforms for massively parallel simulations. Here we show that recent advances in the network performance on the Amazon Web Services cloud enable efficient model simulations with over a thousand cores. The choices of Message Passing Interface library configuration and internode communication protocol are critical to this success. Application to the Goddard Earth Observing System (GEOS)‐Chem global 3‐D chemical transport model at 50‐km horizontal resolution shows efficient scaling up to at least 1,152 cores, with performance and cost comparable to the National Aeronautics and Space Administration Pleiades supercomputing cluster.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics. Laboratory for Aviation and the Environment
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1029/2020ms002064
