research-article

AzureBlast: a case study of developing science applications on the cloud

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Roger BargaAuthors Info & Claims

HPDC '10: Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing

Pages 413 - 420

https://doi.org/10.1145/1851476.1851537

Published: 21 June 2010 Publication History

Abstract

Cloud computing has emerged as a new approach to large scale computing and is attracting a lot of attention from the scientific and research computing communities. Despite its growing popularity, it is still unclear just how well the cloud model of computation will serve scientific applications. In this paper we analyze the applicability of cloud to the sciences by investigating an implementation of a well known and computationally intensive algorithm called BLAST. BLAST is a very popular life sciences algorithm used commonly in bioinformatics research. The BLAST algorithm makes an excellent case study because it is both crucial to many life science applications and its characteristics are representative of many applications important to data intensive scientific research. In our paper we introduce a methodology that we use to study the applicability of cloud platforms to scientific computing and analyze the results from our study. In particular we examine the best practices of handling the large scale parallelism and large volumes of data. While we carry out our performance evaluation on Microsoft's Windows Azure the results readily generalize to other cloud platforms.

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AzureBlast: a case study of developing science applications on the cloud

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cover image ACM Conferences

HPDC '10: Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing

June 2010

911 pages

ISBN:9781605589428

DOI:10.1145/1851476

General Chairs:
Salim Hariri
University of Arizona
,
Kate Keahey
University of Chicago

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 21 June 2010

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HPDC '10: The 19th International Symposium on High Performance Distributed Computing

June 21 - 25, 2010

Illinois, Chicago

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