Processor design for portable systems
Journal of VLSI Signal Processing Systems - Special issue on technologies for wireless computing
Dynamic voltage scaling and power management for portable systems
Proceedings of the 38th annual Design Automation Conference
Dynamic Power Management: Design Techniques and CAD Tools
Dynamic Power Management: Design Techniques and CAD Tools
An Incremental Genetic Algorithm Approach to Multiprocessor Scheduling
IEEE Transactions on Parallel and Distributed Systems
Just In Time Dynamic Voltage Scaling: Exploiting Inter-Node Slack to Save Energy in MPI Programs
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Minimizing execution time in MPI programs on an energy-constrained, power-scalable cluster
Proceedings of the eleventh ACM SIGPLAN symposium on Principles and practice of parallel programming
Energy management of DVS-DPM enabled embedded systems powered by fuel cell-battery hybrid source
ISLPED '07 Proceedings of the 2007 international symposium on Low power electronics and design
Energy-Efficient Real-Time Task Scheduling in Multiprocessor DVS Systems
ASP-DAC '07 Proceedings of the 2007 Asia and South Pacific Design Automation Conference
Energy-efficient dynamic task scheduling algorithms for DVS systems
ACM Transactions on Embedded Computing Systems (TECS)
Bounding energy consumption in large-scale MPI programs
Proceedings of the 2007 ACM/IEEE conference on Supercomputing
Expected energy consumption minimization in DVS systems with discrete frequencies
Proceedings of the 2008 ACM symposium on Applied computing
An Effective Iterative Compilation Search Algorithm for High Performance Computing Applications
HPCC '08 Proceedings of the 2008 10th IEEE International Conference on High Performance Computing and Communications
High Performance Computing and the Progress of Weather and Climate Forecasting
High Performance Computing for Computational Science - VECPAR 2008
Koala: a platform for OS-level power management
Proceedings of the 4th ACM European conference on Computer systems
Minimizing Energy Consumption for Precedence-Constrained Applications Using Dynamic Voltage Scaling
CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
DSD '09 Proceedings of the 2009 12th Euromicro Conference on Digital System Design, Architectures, Methods and Tools
Trade-offs between voltage scaling and processor shutdown for low-energy embedded multiprocessors
SAMOS'07 Proceedings of the 7th international conference on Embedded computer systems: architectures, modeling, and simulation
Profile-based optimization of power performance by using dynamic voltage scaling on a PC cluster
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Green Task Scheduling Algorithms with Speeds Optimization on Heterogeneous Cloud Servers
GREENCOM-CPSCOM '10 Proceedings of the 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing
Some observations on optimal frequency selection in DVFS-based energy consumption minimization
Journal of Parallel and Distributed Computing
Review: Energy-aware performance analysis methodologies for HPC architectures-An exploratory study
Journal of Network and Computer Applications
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The energy consumption issue in distributed computing systems has become quite critical due to environmental concerns. In response to this, many energy-aware scheduling algorithms have been developed primarily by using the dynamic voltage-frequency scaling (DVFS) capability incorporated in recent commodity processors. The majority of these algorithms involve two passes: schedule generation and slack reclamation. The latter is typically achieved by lowering processor frequency for tasks with slacks. In this paper, we revisit this energy reduction technique from a different perspective and propose a new slack reclamation algorithm which uses a linear combination of the maximum and minimum processor frequencies to decrease energy consumption. This algorithm has been evaluated based on results obtained from experiments with three different sets of task graphs: 1,500 randomly generated task graphs, and 300 task graphs of each of two real-world applications (Gauss-Jordan and LU decomposition). The results show that the amount of energy saved in the proposed algorithm is 13.5%, 25.5% and 0.11% for random, LU decomposition and Gauss-Jordan task graphs, respectively, these percentages for the reference DVFSbased algorithm are 12.4%, 24.6% and 0.1%, respectively.