The development of community-specific user interfaces of a science gateway can be a challenging task for non-IT experts. This contribution proposes an original, easy-to-use solution to tackle this issue based on EasyGateway. EasyGateway is a modern, lightweight solution for the development of science gateway able to interplay with most toolkits. In this paper we present how EasyGateway can “dress” Apache Airavata to manage experiment configurations and job submissions. We discuss the proposed approach considering a real case application represented by the Weather Research and Forecasting Model (WRF), a community model exploited by a large number of users in meteorology and climatology domains. The combined use of EasyGateway and Apache Airavata leads to an improved user experience, enhancing the model configuration phase with support in finding inconsistencies immediately, but also exploiting the possibility of accessing a potentially large set of computational resources to perform model execution.

Using Apache Airavata and EasyGateway for the creation of complex science gateway front-end

D'Agostino D.
2019

Abstract

The development of community-specific user interfaces of a science gateway can be a challenging task for non-IT experts. This contribution proposes an original, easy-to-use solution to tackle this issue based on EasyGateway. EasyGateway is a modern, lightweight solution for the development of science gateway able to interplay with most toolkits. In this paper we present how EasyGateway can “dress” Apache Airavata to manage experiment configurations and job submissions. We discuss the proposed approach considering a real case application represented by the Weather Research and Forecasting Model (WRF), a community model exploited by a large number of users in meteorology and climatology domains. The combined use of EasyGateway and Apache Airavata leads to an improved user experience, enhancing the model configuration phase with support in finding inconsistencies immediately, but also exploiting the possibility of accessing a potentially large set of computational resources to perform model execution.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11567/1087343
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