The aggregate power use of computing hardware is an important cost factor in scientific cluster and distributed computing systems. The Worldwide LHC Computing Grid (WLCG) is a major example of such a distributed computing system, used primarily for high throughput computing (HTC) applications. It has a computing capacity and power consumption rivaling that of the largest supercomputers. The computing capacity required from this system is also expected to grow over the next decade. Optimizing the power utilization and cost of such systems is thus of great interest. A number of trends currently underway will provide new opportunities for power-aware optimizations. We discuss how power-aware software applications and scheduling might be used to reduce power consumption, both as autonomous entities and as part of a (globally) distributed system. As concrete examples of computing centers we provide information on the large HEP-focused Tier-1 at FNAL, and the Tigress High Performance Computing Center at Princeton University, which provides HPC resources in a university context.
Cite
@article{arxiv.1404.6929,
title = {Power-aware applications for scientific cluster and distributed computing},
author = {David Abdurachmanov and Peter Elmer and Giulio Eulisse and Paola Grosso and Curtis Hillegas and Burt Holzman and Ruben L. Janssen and Sander Klous and Robert Knight and Shahzad Muzaffar},
journal= {arXiv preprint arXiv:1404.6929},
year = {2014}
}
Comments
Submitted to proceedings of International Symposium on Grids and Clouds (ISGC) 2014, 23-28 March 2014, Academia Sinica, Taipei, Taiwan