The power wall has become a dominant impeding factor in the realm of exascale system design. It is therefore important to understand how to most effectively create software to minimize its power usage while maintaining satisfactory levels of performance. This work uses existing software and hardware facilities to tune applications to minimize for several combinations of power and performance. The tuning is done with respect to software level performance-related tunables and for processor clock frequency. These tunable parameters are explored via an offline search to find the parameter combinations that are optimal with respect to performance (or delay, D), energy (E), energy×delay (E×D) and energy×delay×delay (E×D 2). These searches are employed on a parallel application that solves Poisson's equation using stencils. We show that the parameter configuration that minimizes energy consumption can save, on average, 5.4% energy with a performance loss of 4% when compared to the configuration that minimizes runtime. © 2012 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Tiwari, A., Laurenzano, M. A., Carrington, L., & Snavely, A. (2012). Auto-tuning for energy usage in scientific applications. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7156 LNCS, pp. 178–187). Springer Verlag. https://doi.org/10.1007/978-3-642-29740-3_21
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