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Cloud Computing for Scientific Simulation and High Performance Computing

Cloud Computing for Scientific Simulation and High Performance Computing

Adrian Jackson, Michèle Weiland
Copyright: © 2013 |Pages: 20
ISBN13: 9781466628540|ISBN10: 1466628545|EISBN13: 9781466628557
DOI: 10.4018/978-1-4666-2854-0.ch003
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MLA

Jackson, Adrian, and Michèle Weiland. "Cloud Computing for Scientific Simulation and High Performance Computing." Principles, Methodologies, and Service-Oriented Approaches for Cloud Computing, edited by Xiaoyu Yang and Lu Liu, IGI Global, 2013, pp. 51-70. https://doi.org/10.4018/978-1-4666-2854-0.ch003

APA

Jackson, A. & Weiland, M. (2013). Cloud Computing for Scientific Simulation and High Performance Computing. In X. Yang & L. Liu (Eds.), Principles, Methodologies, and Service-Oriented Approaches for Cloud Computing (pp. 51-70). IGI Global. https://doi.org/10.4018/978-1-4666-2854-0.ch003

Chicago

Jackson, Adrian, and Michèle Weiland. "Cloud Computing for Scientific Simulation and High Performance Computing." In Principles, Methodologies, and Service-Oriented Approaches for Cloud Computing, edited by Xiaoyu Yang and Lu Liu, 51-70. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2854-0.ch003

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Abstract

This chapter describes experiences using Cloud infrastructures for scientific computing, both for serial and parallel computing. Amazon’s High Performance Computing (HPC) Cloud computing resources were compared to traditional HPC resources to quantify performance as well as assessing the complexity and cost of using the Cloud. Furthermore, a shared Cloud infrastructure is compared to standard desktop resources for scientific simulations. Whilst this is only a small scale evaluation these Cloud offerings, it does allow some conclusions to be drawn, particularly that the Cloud can currently not match the parallel performance of dedicated HPC machines for large scale parallel programs but can match the serial performance of standard computing resources for serial and small scale parallel programs. Also, the shared Cloud infrastructure cannot match dedicated computing resources for low level benchmarks, although for an actual scientific code, performance is comparable.

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