The Who, What, Why, and How of High Performance Computing in the Cloud

被引:30
作者
Gupta, Abhishek [1 ]
Kale, Laxmikant V. [1 ]
Gioachin, Filippo [2 ]
March, Verdi [2 ]
Suen, Chun Hui [2 ]
Lee, Bu-Sung [2 ]
Faraboschi, Paolo [3 ]
Kaufmann, Richard [3 ]
Milojicic, Dejan [3 ]
机构
[1] Univ Illinois, Urbana, IL 61801 USA
[2] HP Labs, Singapore, Singapore
[3] HP Labs, Palo Alto, CA USA
来源
2013 IEEE FIFTH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING TECHNOLOGY AND SCIENCE (CLOUDCOM), VOL 1 | 2013年
关键词
HPC; Cloud; Performance Analysis; Economics;
D O I
10.1109/CloudCom.2013.47
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cloud computing is emerging as an alternative to supercomputers for some of the high-performance computing (HPC) applications that do not require a fully dedicated machine. With cloud as an additional deployment option, HPC users are faced with the challenges of dealing with highly heterogeneous resources, where the variability spans across a wide range of processor configurations, interconnections, virtualization environments, and pricing rates and models. In this paper, we take a holistic viewpoint to answer the question - why and who should choose cloud for HPC, for what applications, and how should cloud be used for HPC? To this end, we perform a comprehensive performance evaluation and analysis of a set of benchmarks and complex HPC applications on a range of platforms, varying from supercomputers to clouds. Further, we demonstrate HPC performance improvements in cloud using alternative lightweight virtualization mechanisms - thin VMs and OS-level containers, and hypervisor- and application-level CPU affinity. Next, we analyze the economic aspects and business models for HPC in clouds. We believe that is an important area that has not been sufficiently addressed by past research. Overall results indicate that current public clouds are cost-effective only at small scale for the chosen HPC applications, when considered in isolation, but can complement supercomputers using business models such as cloud burst and application-aware mapping.
引用
收藏
页码:306 / 314
页数:9
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