Abstract-This paper provides an overview of the Apache Airavata software system for science gateways. Gateways use Airavata to manage application and workflow executions on a range of backend resources (grids, computing clouds, and local clusters). Airavata's design goal is to provide component abstractions for major tasks required to provide gateway application management. Components are not directly accessed but are instead exposed through a client Application Programming Interface. This design allows gateway developers to take full advantage of Airavata's capabilities, and Airavata developers (including those interested in middleware research) to modify Airavata's implementations and behavior. This is particularly important as Airavata evolves to become a scalable, elastic "platform as a service" for science gateways. We illustrate the capabilities of Airavata through the discussion of usage vignettes. As an Apache Software Foundation project, Airavata's open community governance model is as important as its software base. We discuss how this works within Airavata and how it may be applicable to other distributed computing infrastructure and cyberinfrastructure efforts.
Cloud computing is a resource of significant value to computational science, but has proven itself to be not immediately realizable by the researcher. The cloud providers that offer a Platform-as-a-Service (PaaS) platform should, in theory, offer a sound alternative to infrastructure-as-aservice as it could be easier to take advantage of for computational science kinds of problems. The objective of our study is to assess how well the Azure platform as a service can serve a particular class of computational science application. We conduct a performance evaluation using three approaches to executing a high-throughput storm surge application: using Sigiri, a large scale resource abstraction tool, Windows Azure HPC scheduler, and Daytona, an Iterative Map-reduce runtime for Azure. The differences in the approaches including early performance measures for up to 500 instances are discussed.
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