Managing energy and server resources in hosting centers
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Benchmarks and Standards for the Evaluation of Parallel Job Schedulers
IPPS/SPDP '99/JSSPP '99 Proceedings of the Job Scheduling Strategies for Parallel Processing
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Energy conservation policies for web servers
USITS'03 Proceedings of the 4th conference on USENIX Symposium on Internet Technologies and Systems - Volume 4
Thermal vs Energy Optimization for DVFS-Enabled Processors in Embedded Systems
ISQED '07 Proceedings of the 8th International Symposium on Quality Electronic Design
Analyzing the Energy-Time Trade-Off in High-Performance Computing Applications
IEEE Transactions on Parallel and Distributed Systems
Energy-aware scheduling for real-time multiprocessor systems with uncertain task execution time
Proceedings of the 44th annual Design Automation Conference
Green Supercomputing Comes of Age
IT Professional
Chasing Gaps between Bursts: Towards Energy Efficient Large Scale Experimental Grids
PDCAT '08 Proceedings of the 2008 Ninth International Conference on Parallel and Distributed Computing, Applications and Technologies
Adagio: making DVS practical for complex HPC applications
Proceedings of the 23rd international conference on Supercomputing
Communications of the ACM
EnergySaving cluster roll: power saving system for clusters
ARCS'10 Proceedings of the 23rd international conference on Architecture of Computing Systems
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In recent years power consumption of high performance computing (HPC) clusters has become a growing problem due, e.g., to the economic cost of electricity, the emission of carbon dioxide (with negative impact on the environment), and the generation of heat (which reduces hardware reliability). In past work, we developed EnergySaving cluster, a software package that regulates the number of active nodes in an HPC facility to match the user's current demands. In this paper, we extend this work by presenting a simulator for this tool that allows the evaluation and analysis of the benefits of applying different energy-saving strategies and rules, under realistic workloads, to different cluster configurations.