DocumentCode :
2673541
Title :
A quantitative analysis of high performance computing with Amazon´s EC2 infrastructure: The death of the local cluster?
Author :
Hill, Zach ; Humphrey, Marty
Author_Institution :
Dept. of Comput. Sci., Univ. of Virginia, Charlottesville, VA, USA
fYear :
2009
fDate :
13-15 Oct. 2009
Firstpage :
26
Lastpage :
33
Abstract :
The introduction of affordable infrastructure on demand, specifically Amazon´s Elastic Compute Cloud (EC2), has had a significant impact in the business IT community and provides reasonable and attractive alternatives to locally-owned infrastructure. For scientific computation however, the viability of EC2 has come into question due to its use of virtualization and network shaping and the performance impacts of both. Several works have shown that EC2 cannot compete with a dedicated HPC cluster utilizing high-performance interconnects, but how does EC2 compare with smaller departmental and lab-sized commodity clusters that are often the primary computational resource for scientists? To answer that question we have run MPI and memory bandwidth benchmarks on EC2 clusters with each of the 64-bit instance types to compare the performance of a 16 node cluster of each to a dedicated locally-owned commodity cluster based on Gigabit Ethernet. Our results show that while EC2 does experience reduced performance, it is still viable for smaller-scale applications.
Keywords :
parallel processing; software performance evaluation; EC2 infrastructure; HPC cluster; business IT community; elastic compute cloud; high performance computing; network shaping; performance impact; quantitative analysis; scientific computation; Bandwidth; Cloud computing; Computer networks; Computer science; Debugging; Delay; High performance computing; Performance analysis; Resource virtualization; Scientific computing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Grid Computing, 2009 10th IEEE/ACM International Conference on
Conference_Location :
Banff, AB
Print_ISBN :
978-1-4244-5148-7
Electronic_ISBN :
978-1-4244-5149-4
Type :
conf
DOI :
10.1109/GRID.2009.5353067
Filename :
5353067
Link To Document :
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