Using AWS EC2 as Test-Bed infrastructure in the I/O system configuration for HPC applications

By: Contributor(s): Material type: ArticleArticlePublication details: : , 2016Description: 1 archivo (1,2 MB)Subject(s): Online resources: Summary: In recent years, the use of public cloud platforms as infrastructure has been gaining popularity in many scientific areas and High Performance Computing (HPC) is no exception. These kinds of platforms can be used by system administrators as Test-Bed systems for evaluating and detecting performance inefficiencies in the I/O subsystem, and for taking decisions about the configuration parameters that have influence on the performance of an application, without compromising the performance of the production HPC system. In this paper, we propose a methodology to evaluate parallel applications by using virtual clusters as a test system. Our experimental validation indicates that virtual clusters are a quick and easy solution for system administrators, for analyzing the impact of the I/O system on the I/O kernels of the parallel applications and for taking performance decisions in a controlled environment.
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Formato de archivo PDF. -- Este documento es producción intelectual de la Facultad de Informática - UNLP (Colección BIPA/Biblioteca)

In recent years, the use of public cloud platforms as infrastructure has been gaining popularity in many scientific areas and High Performance Computing (HPC) is no exception. These kinds of platforms can be used by system administrators as Test-Bed systems for evaluating and detecting performance inefficiencies in the I/O subsystem, and for taking decisions about the configuration parameters that have influence on the performance of an application, without compromising the performance of the production HPC system. In this paper, we propose a methodology to evaluate parallel applications by using virtual clusters as a test system. Our experimental validation indicates that virtual clusters are a quick and easy solution for system administrators, for analyzing the impact of the I/O system on the I/O kernels of the parallel applications and for taking performance decisions in a controlled environment.

Journal of Computer Science & Technology, 16(2), pp. 65-75.

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