Paper Info
Title
Power measurement techniques for energy-efficient computing: reconciling scalability, resolution, and accuracy
Abstract
The rising concern for power consumption of large-scale computer systems puts a research focus on the respective measurement methods. Varying workload patterns and energy efficiency optimizations cause highly dynamic power consumption on today’s compute nodes—a challenge for every measurement infrastructure. We identify five partly contradictory requirements that characterize such infrastructures: temporal granularity, spatial granularity, well-defined accuracy, scalability, and cost. In two projects we push the boundaries for these criteria: a scalable measurement solution for hundreds of nodes at millisecond granularity that is tightly integrated into the HPC system, and a sophisticated single-node instrumentation to measure the power consumption of application events in the microsecond range. Both measurement solutions are calibrated and their accuracy is carefully studied. We discuss scalable processing of the measurements for global monitoring in large-scale systems and use this data for energy efficiency analyses in combination with contextual information such as application performance trace data.
Year
DOI
Venue
2019
10.1007/s00450-018-0392-9
Computer Science - Research and Development
Keywords
Field
DocType
HAEC, HDEEM, Power measurement, Verification, Energy efficiency
Contextual information,Efficient energy use,Computer science,Workload,Real-time computing,Millisecond,Dynamic demand,Granularity,Scalability,Instrumentation
Journal
Volume
Issue
ISSN
34
1
2524-8529
Citations 
PageRank 
References 
1
0.40
12
Authors
7
Name
Order
Citations
PageRank
Thomas Ilsche117214.92
Robert Schöne223519.27
Joseph Schuchart31109.49
Daniel Hackenberg440028.07
Marc Simon5161.29
Yiannis Georgiou61319.76
Wolfgang E. Nagel71800167.93