Workload- based power management for parallel computer systems

Authors:
D. J. Bradley;R. E. Harper;S. W. Hunter
Affiliations:
IBM Systems Group, Research Triangle Park, P.O. Box 12195, Durham, North Carolina 27709;IBM Systems Group, Research Triangle Park, P.O. Box 12195, Durham, North Carolina 27709;IBM Systems Group, Research Triangle Park, P.O. Box 12195, Durham, North Carolina 27709
Venue:
IBM Journal of Research and Development
Year:
2003

Citing 8
Cited 9

Adaptive algorithms for managing a distributed data processing workload

IBM Systems Journal
Managing energy and server resources in hosting centers

SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Every joule is precious: the case for revisiting operating system design for energy efficiency

EW 9 Proceedings of the 9th workshop on ACM SIGOPS European workshop: beyond the PC: new challenges for the operating system
High-Performance Web Site Design Techniques

IEEE Internet Computing
Power: A First-Class Architectural Design Constraint

Computer
The case for power management in web servers

Power aware computing
The Case for Higher-Level Power Management

HOTOS '99 Proceedings of the The Seventh Workshop on Hot Topics in Operating Systems
Energy Management for Server Clusters

HOTOS '01 Proceedings of the Eighth Workshop on Hot Topics in Operating Systems

BladeCenter networking

IBM Journal of Research and Development - IBM BladeCenter systems
BladeCenter thermal diagnostics

IBM Journal of Research and Development - IBM BladeCenter systems
Making scheduling "cool": temperature-aware workload placement in data centers

ATEC '05 Proceedings of the annual conference on USENIX Annual Technical Conference
On temperature-aware scheduling for single-processor systems

HiPC'07 Proceedings of the 14th international conference on High performance computing
Environment-conscious scheduling of HPC applications on distributed Cloud-oriented data centers

Journal of Parallel and Distributed Computing
Safe overprovisioning: using power limits to increase aggregate throughput

PACS'04 Proceedings of the 4th international conference on Power-Aware Computer Systems
Temperature management in data centers: why some (might) like it hot
Evolutionary multiobjective optimization for green clouds

Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Energy usage and carbon emission optimization mechanism for federated data centers

E2DC'12 Proceedings of the First international conference on Energy Efficient Data Centers

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes and evaluates predictive power management algorithms that we have developed to minimize energy consumption and unmet demand in parallel computer systems. The algorithms are evaluated using workload data obtained from production servers from several applications, showing that energy savings of 20% or more can readily be achieved, with a small degree of unmet demand and acceptable reliability, availability, and serviceability (RAS) impact. The implementation of these algorithms in IBM system management software and the possibilities for future work are discussed.