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Title: TUE, a New Energy-Efficiency Metric Applied at ORNL’s Jaguar. In: ISC 2013: Supercomputing. Lecture Notes in Computer Science

Conference ·
 [1];  [2];  [2];  [3];  [4];  [4];  [5];  [6]
  1. Intel Corporation, Dupont, WA (United States). Intel Architecture Group; Energy Efficient HPC Working Group, Anderson Island, WA (United States)
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Energy Efficient HPC Working Group, Anderson Island, WA (United States)
  3. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  4. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Energy Efficient HPC Working Group, Anderson Island, WA (United States)
  5. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Energy Efficient HPC Working Group, Anderson Island, WA (United States)
  6. Energy Efficient HPC Working Group, Anderson Island, WA (United States)
+ Show Author Affiliations

The metric, Power Usage Effectiveness (PUE), has been successful in improving energy efficiency of data centers, but it is not perfect. One challenge is that PUE does not account for the power distribution and cooling losses inside IT equipment. This is particularly problematic in the HPC (high performance computing) space where system suppliers are moving cooling and power subsystems into or out of the cluster. This paper proposes two new metrics: ITUE (IT-power usage effectiveness), similar to PUE but “inside” the IT and TUE (total-power usage effectiveness), which combines the two for a total efficiency picture. We conclude with a demonstration of the method, and a case study of measurements at ORNL’s Jaguar system. TUE provides a ratio of total energy, (internal and external support energy uses) and the specific energy used in the HPC. TUE can also be a means for comparing HPC site to HPC site.

Research Organization:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Organization:
USDOE Office of Science (SC)
OSTI ID:
1567530
Resource Relation:
Conference: International Supercomputing Conference
Country of Publication:
United States
Language:
English

References (1)

Measuring power consumption on IBM Blue Gene/P journal August 2011

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Related Subjects

HPC
energy-efficiency
metrics
data center