Enabling High-Performance Cloud Computing for Earth Science Modeling on Over a Thousand Cores: Application to the GEOS-Chem Atmospheric Chemistry Model

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.