Using Lightweight Virtual Machines to Run High Performance Computing Applications: The Case of the Weather Research and Forecasting Model - Archive ouverte HAL
Communication Dans Un Congrès Année : 2011

Using Lightweight Virtual Machines to Run High Performance Computing Applications: The Case of the Weather Research and Forecasting Model

Résumé

There are many scientific applications that have high performance computing demands. Such demands are traditionally supported by cluster- or Grid-based systems. Cloud computing, which has experienced a tremendous growth, emerged as an approach to provide on-demand access to computing resources. The cloud computing paradigm offers a number of advantages over other distributed platforms. For example, the access to resources is flexible and cost-effective since it is not necessary to invest a large amount of money on a computing infrastructure nor pay salaries for maintenance functions. Therefore, the possibility of using cloud computing for running high performance computing applications is attractive. However, it has been shown elsewhere that current cloud computing platforms are not suitable for running this kind of applications since the performance offered is very poor. The reason is mainly the overhead from virtualisation which is extensively used by most cloud computing platforms as a means to optimise resource usage. In this paper, we present a lightweight virtualisation approach applied to WRF, a challenging communication-intensive, high performance computing application. Our experimental results show that lightweight virtualisation imposes about 5% overhead and it substantially outperforms traditional heavy-weight virtualisation such as VMware
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Dates et versions

hal-00625910 , version 1 (22-09-2011)

Identifiants

  • HAL Id : hal-00625910 , version 1

Citer

Hector Duran-Limon, Nikos Parlavantzas, Ming Zhao, Luis Silva-Bañuelos, Victor Tellez-Valdez. Using Lightweight Virtual Machines to Run High Performance Computing Applications: The Case of the Weather Research and Forecasting Model. 4th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2011), Dec 2011, Melbourne, Australia. ⟨hal-00625910⟩
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