A survey of design techniques for system-level dynamic power management
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special section on low-power electronics and design
Making a Case for Efficient Supercomputing
Queue - Power Management
MegaProto: A Low-Power and Compact Cluster for High-Performance Computing
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 11 - Volume 12
Reducing Energy Consumption of Disk Storage Using Power-Aware Cache Management
HPCA '04 Proceedings of the 10th International Symposium on High Performance Computer Architecture
PARSE: A Tool for Parallel Application Run Time Sensitivity Evaluation
ICPADS '06 Proceedings of the 12th International Conference on Parallel and Distributed Systems - Volume 1
A network performance sensitivity metric for parallel applications
ISPA'07 Proceedings of the 5th international conference on Parallel and Distributed Processing and Applications
Energy-efficient deadline scheduling for heterogeneous systems
Journal of Parallel and Distributed Computing
Optimal DPM and DVFS for frame-based real-time systems
ACM Transactions on Architecture and Code Optimization (TACO) - Special Issue on High-Performance Embedded Architectures and Compilers
Adaptive workload driven dynamic power management for high performance computing clusters
Computers and Electrical Engineering
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Beowulf clusters are now deployed worldwide, chiefly in support of scientific computing. Beowulf clusters yield high computing performance, yet they also pose several challenges: (1) heat-induced hardware failure makes large scale commodity clusters fail quite frequently and (2) cost effectiveness of the Beowulf cluster is challenged by the fact that it lacks means of adapting its power state according to varying work load. This paper addresses these issues by developing a Power and Environment Awareness Module (PEAM) for a Beowulf cluster. The busty nature of computation load in an academic environment inspired the implementation and analysis of a fixed timeout Dynamic Power Management (DPM) policy. Today it is common that many Beowulf clusters in academic environment are composed of older, recycled nodes that may lack of out-of-band management technologies, thus Advanced Configuration and Power Interface (ACPI) and Wake-on-LAN (WOL) technology is exploited to control the power state of cluster nodes. A data center environment monitoring system that uses Wireless Sensor Networks (WSN) technology is developed and deployed to realize environment awareness of the cluster. Our PEAM module has been implemented on our cluster at Purdue University, reducing the operational cost and increasing the reliability of the cluster by reducing heat generation and optimizing workload distribution in an environment aware manner.