Performance analysis of HPC applications in the cloud

被引:70
作者
Exposito, Roberto R. [1 ]
Taboada, Guillermo L. [1 ]
Ramos, Sabela [1 ]
Tourino, Juan [1 ]
Doallo, Ramon [1 ]
机构
[1] Univ A Coruna, Comp Architecture Grp, La Coruna 15071, Spain
来源
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE | 2013年 / 29卷 / 01期
关键词
Cloud computing; High Performance Computing; Amazon EC2 Cluster Compute platform; MPI; OpenMP; MPJ;
D O I
10.1016/j.future.2012.06.009
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The scalability of High Performance Computing (HPC) applications depends heavily on the efficient support of network communications in virtualized environments. However, Infrastructure as a Service (IaaS) providers are more focused on deploying systems with higher computational power interconnected via high-speed networks rather than improving the scalability of the communication middleware. This paper analyzes the main performance bottlenecks in HPC application scalability on the Amazon EC2 Cluster Compute platform: (1) evaluating the communication performance on shared memory and a virtualized 10 Gigabit Ethernet network; (2) assessing the scalability of representative HPC codes, the NAS Parallel Benchmarks, using an important number of cores, up to 512; (3) analyzing the new cluster instances (CC2), both in terms of single instance performance, scalability and cost-efficiency of its use; (4) suggesting techniques for reducing the impact of the virtualization overhead in the scalability of communication-intensive HPC codes, such as the direct access of the Virtual Machine to the network and reducing the number of processes per instance; and (5) proposing the combination of message-passing with multithreading as the most scalable and cost-effective option for running HPC applications on the Amazon EC2 Cluster Compute platform. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:218 / 229
页数:12
相关论文
共 37 条
[1]  
Abramson D., 2006, Intel Technol. J, V10, P3, DOI DOI 10.1535/ITJ.1003.02
[2]  
Amazon Web Services LLC, AM EL COMP CLOUD AM
[3]  
Amazon Web Services LLC, HIGH PERF COMP US AM
[4]  
[Anonymous], 2008, Benchmarking Amazon EC2 for High-Performance Scientific Computing
[5]  
[Anonymous], 2003, ACM SIGOPS OPERATING
[6]  
[Anonymous], 2010, Performance analysis of high performance computing applications on the amazon web services cloud
[7]  
[Anonymous], P 17 INT C ARCH SUPP
[8]  
[Anonymous], 2002, Tech. Rep. 02-02-01
[9]   THE NAS PARALLEL BENCHMARKS [J].
BAILEY, DH ;
BARSZCZ, E ;
BARTON, JT ;
BROWNING, DS ;
CARTER, RL ;
DAGUM, L ;
FATOOHI, RA ;
FREDERICKSON, PO ;
LASINSKI, TA ;
SCHREIBER, RS ;
SIMON, HD ;
VENKATAKRISHNAN, V ;
WEERATUNGA, SK .
INTERNATIONAL JOURNAL OF SUPERCOMPUTER APPLICATIONS AND HIGH PERFORMANCE COMPUTING, 1991, 5 (03) :63-73
[10]  
Baker M, 2000, LECT NOTES COMPUT SC, V1800, P552