
Tracking the Performance Evolution of Blue Gene Systems
2013; Springer Science+Business Media; Linguagem: Inglês
10.1007/978-3-642-38750-0_24
ISSN1611-3349
AutoresDarren J. Kerbyson, Kevin Barker, Diego Gallo, Dong Chen, José R. Brunheroto, Kyung Dong Ryu, George L. Chiu, Adolfy Hoisie,
Tópico(s)Advanced Data Storage Technologies
ResumoIBM’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.
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