Performing Large Science Experiments on Azure: Pitfalls and Solutions

  • Wei Lu ,
  • Jared Jackson ,
  • Jaliya Ekanayake ,
  • Roger S. Barga ,
  • Nelson Araujo

Proceedings of the 2nd IEEE Int'l Conference on Cloud Computing Technology and Science |

Published by IEEE Computer Society

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.

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NCBI BLAST on Windows Azure

July 25, 2011

A parallel BLAST engine that runs on the Windows Azure cloud fabric, NCBI BLAST on Windows Azure can scale up to hundreds of compute nodes. This cloud-based implementation of the National Center for Biotechnology Information (NCBI) Basic Local Alignment Search Tool (BLAST) searches all available sequence databases for similarities between a protein or DNA query and known sequences. BLAST on Windows Azure enables researchers to take advantage of the scalability of the Windows Azure platform to execute BLAST jobs on demand in the cloud.