Middleware alternatives for storm surge predictions in Windows Azure
Proceedings of the 3rd workshop on Scientific Cloud Computing Date
An Analysis of Provisioning and Allocation Policies for Infrastructure-as-a-Service Clouds
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
Stochastic Tail-Phase Optimization for Bag-of-Tasks Execution in Clouds
UCC '12 Proceedings of the 2012 IEEE/ACM Fifth International Conference on Utility and Cloud Computing
A vision for personalized service level agreements in the cloud
Proceedings of the Second Workshop on Data Analytics in the Cloud
Storm surge simulation and load balancing in Azure cloud
Proceedings of the High Performance Computing Symposium
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Carrying out science at extreme scale is the next generational challenge facing the broad field of scientific research. Cloud computing offers to potential for an increasing number of researchers to have ready access to the large scale compute resources required to tackle new challenges in their field. Unfortunately barriers of complexity remain for researchers untrained in cloud programming. In this paper we examine how cloud based architectures can be used to solve large scale research experiments in a manner that is easily accessible for researchers with limited programming experience, using their existing computational tools. We examine the top challenges identified in our own large-scale science experiments running on the Windows Azure platform and then describe a Cloud-based parameter sweep prototype (dubbed Cirrus) which provides a framework of solutions for each challenge.