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Issue No.05 - September/October (2006 vol.26)
pp: 67-81
Valentina Salapura , IBM T.J. Watson Research Center
Robert Walkup , IBM T.J. Watson Research Center
Alan Gara , IBM T.J. Watson Research Center
ABSTRACT
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.
INDEX TERMS
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
CITATION
Valentina Salapura, Robert Walkup, Alan Gara, "Exploiting Workload Parallelism for Performance and Power Optimization in Blue Gene", IEEE Micro, vol.26, no. 5, pp. 67-81, September/October 2006, doi:10.1109/MM.2006.89
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