Issue No. 05 - September/October (2006 vol. 26)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MM.2006.89
Valentina Salapura , IBM T.J. Watson Research Center
Robert Walkup , IBM T.J. Watson Research Center
Alan Gara , IBM T.J. Watson Research Center
Optimizing future supercomputing applications will depend on delivering the best performance for a given power budget. To determine the effect on efficiency of application-scaling parameters, this article analyzes system power and performance measurement results for real-world applications exploiting thread- and data-level parallelism on the Blue Gene/L system.
computer systems organization, application studies resulting in better multiple-processor systems, super (very large) computers, computer system implementation, architecture, interprocessor communications, processor architectures, parallelism, parallelism, Blue Gene/L system, power optimization
A. Gara, V. Salapura and R. Walkup, "Exploiting Workload Parallelism for Performance and Power Optimization in Blue Gene," in IEEE Micro, vol. 26, no. , pp. 67-81, 2006.