Tracking the Performance Evolution of Blue Gene Systems

被引:0
|
作者
Kerbyson, Darren J. [1 ]
Barker, Kevin J. [1 ]
Gallo, Diego S. [2 ,3 ]
Chen, Dong [3 ]
Brunheroto, Jose R. [3 ]
Ryu, Kyung Dong [3 ]
Chiu, George L. [3 ]
Hoisie, Adolfy [1 ]
机构
[1] Pacific Northwest Natl Lab, Richland, WA 99352 USA
[2] IBM Res Brazil, BR-04007900 Sao Paulo, SP, Brazil
[3] IBM TJ Watson Res Ctr, Yorktown Hts, NY 10598 USA
来源
SUPERCOMPUTING (ISC 2013) | 2013年 / 7905卷
关键词
High Performance Computing; Performance Evaluation; Performance Modeling; Massively Parallel Processing; COMPUTER;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
IBM's Blue Gene supercomputer has evolved through three generations from the original Blue Gene/L to P to Q. A higher level of integration has enabled greater single-core performance, and a larger concurrency per compute node. Although these changes have brought with them a higher overall system peak-performance, no study has examined in detail the evolution of performance across system generations. In this work we make two significant contributions - that of providing a comparative performance analysis across Blue Gene generations using a consistent set of tests, and also in providing a validated performance model of the NEK-Bone proxy application. The combination of empirical analysis and the predictive performance model enable us to not only directly compare measured performance but also allow for a comparison of system configurations that cannot currently be measured. We provide insights into how the changing characteristics of Blue Gene have impacted on the application performance, as well as what future systems may be able to achieve.
引用
收藏
页码:317 / 329
页数:13
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