Performance Assessment of the Cloud for Prototypical Instant Computing Approaches in Geoscientific Hazard Simulations

Abstract

Computing forecasts of hazards, such as tsunamis, requires fast reaction times and high precision, which in turn demands for large computing facilities that are needed only in rare occasions. Cloud computing environments allow to configure largely scalable on-demand computing environments. In this study, we tested two of the major cloud computing environments for parallel scalability for relevant prototypical applications. These applications solve stationary and non-stationary partial differential equations by means of finite differences and finite elements. These test cases demonstrate the capacity of cloud computing environments to provide scalable computing power for typical tasks in geophysical applications. As a proof-of-concept example of an instant computing application for geohazards, we propose a workflow and prototypical implementation for tsunami forecasting in the cloud. We demonstrate that minimal on-site computing resources are necessary for such a forecasting environment. We conclude by outlining the additional steps necessary to implement an operational tsunami forecasting cloud service, considering availability and cost.