BOOK-CHAPTER

Power Consumption Aware Cluster Resource Management

Simon KiertscherBettina SchnorJörg Zinke

Year: 2013 Advances in environmental engineering and green technologies book series Pages: 20-37   Publisher: IGI Global

Abstract

In 2007, the Green500 list was introduced, which compares supercomputers by performance-per-watt. Since supercomputers consist of thousands of nodes, energy-saving is a growing demand. Compute clusters are often managed by a so-called Resource Management Systems (RMS), which have load information about the whole system. For clusters with changing compute demands, this can be used to switch on/off nodes according to the current load situation and save energy this way. Here, the authors present energy-saving techniques that work on the management level and measurements that show that speed scaling is not a good means for energy saving. Further, they give an overview of some important standards and specifications related to energy saving, like ACPI and IPMI. Finally, the authors present their energy-saving daemon called CHERUB. Due to its modular design, it can operate with different Resource Management Systems. Their experimental results show that CHERUB’s scheduling algorithm works well, i.e. it will save energy, if possible, and avoids state flapping.

Keywords:
Daemon Computer science Modular design Energy management Scheduling (production processes) Power saving Distributed computing Energy consumption Resource Management System Resource (disambiguation) Energy (signal processing) Power (physics) Operating system Resource allocation Computer network Electrical engineering Engineering Operations management

Metrics

1
Cited By
0.58
FWCI (Field Weighted Citation Impact)
19
Refs
0.72
Citation Normalized Percentile
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Citation History

Topics

Cloud Computing and Resource Management
Physical Sciences →  Computer Science →  Information Systems
Distributed and Parallel Computing Systems
Physical Sciences →  Computer Science →  Computer Networks and Communications
Parallel Computing and Optimization Techniques
Physical Sciences →  Computer Science →  Hardware and Architecture
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