Saving 200kW and $200 K/year by power-aware job/machine scheduling

  title={Saving 200kW and \$200 K/year by power-aware job/machine scheduling},
  author={Junichi Hikita and Akio Hirano and Hiroshi Nakashima},
  journal={2008 IEEE International Symposium on Parallel and Distributed Processing},
This paper reports our 3.75-year empirical study on power-aware operations of Kyoto University's supercomputer system. The supercomputer system of 10 TFlops had required about 540 kW on average in its first fiscal year 2004. After that and one-year try-and-error of power efficient operation, we implemented a simple but effective scheduler of jobs and machine powering to improve the per- load power efficiency by up to 39 % and to save 200 kW and $200,000 electric charge in the fiscal year 2006… CONTINUE READING
Highly Cited
This paper has 34 citations. REVIEW CITATIONS
20 Citations
10 References
Similar Papers


Publications citing this paper.
Showing 1-10 of 20 extracted citations


Publications referenced by this paper.
Showing 1-10 of 10 references

An experimental study of NQS parameter tuning method for improvement of the system usage efficiency

  • R. Ito
  • In Proc. Intl. WS. Automatic Performance Tuning,
  • 2007
1 Excerpt

Autonomic power and performance management for large scale data centers

  • B. Khargharia
  • In Proc. Next Generation SoftwareWS. (in Proc…
  • 2007
1 Excerpt

An overview of the BlueGene/L supercomputer

  • N. R. Adiga
  • In Proc. Supercomputing 2002,
  • 2002
1 Excerpt

Similar Papers

Loading similar papers…