A dynamic disk spin-down technique for mobile computing
MobiCom '96 Proceedings of the 2nd annual international conference on Mobile computing and networking
Processor design for portable systems
Journal of VLSI Signal Processing Systems - Special issue on technologies for wireless computing
High-performance computing in chemistry: NW Chem
Future Generation Computer Systems - Special issue: parallel computing applications
Voltage scheduling problem for dynamically variable voltage processors
ISLPED '98 Proceedings of the 1998 international symposium on Low power electronics and design
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
Parallel Computation in Biological Sequence Analysis
IEEE Transactions on Parallel and Distributed Systems
A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Performance Comparison of Dynamic Voltage Scaling Algorithms for Hard Real-Time Systems
RTAS '02 Proceedings of the Eighth IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS'02)
RTSS '01 Proceedings of the 22nd IEEE Real-Time Systems Symposium
Voltage-Clock-Scaling Adaptive Scheduling Techniques for Low Power in Hard Real-Time Systems
IEEE Transactions on Computers
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
Dynamic voltage scaling for multitasking real-time systems with uncertain execution time
GLSVLSI '06 Proceedings of the 16th ACM Great Lakes symposium on VLSI
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)
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
A Hierarchy Energy Driven Architecture for Wireless Sensor Networks
WAINA '10 Proceedings of the 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
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
Modeling Overall Energy Consumption in Wireless Sensor Networks
PDCAT '10 Proceedings of the 2010 International Conference on Parallel and Distributed Computing, Applications and Technologies
A unified approach to variable voltage scheduling for nonideal DVS processors
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Journal of Systems and Software
Energy-Aware Scheduling on Multicore Heterogeneous Grid Computing Systems
Journal of Grid Computing
A study on combinational effects of job and resource characteristics on energy consumption
Multiagent and Grid Systems
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In recent years, the issue of energy consumption in parallel and distributed computing systems has attracted a great deal of attention. In response to this, many energy-aware scheduling algorithms have been developed primarily using the dynamic voltage-frequency scaling (DVFS) capability which has been incorporated into recent commodity processors. Majority of these algorithms involve two passes: schedule generation and slack reclamation. The former pass involves the redistribution of tasks among DVFS-enabled processors based on a given cost function that includes makespan and energy consumption, while the latter pass is typically achieved by executing individual tasks with slacks at a lower processor frequency. In this paper, a new slack reclamation algorithm is proposed by approaching the energy reduction problem from a different angle. Firstly, the problem of task slack reclamation by using combinations of processors' frequencies is formulated. Secondly, several proofs are provided to show that (1) if the working frequency set of processor is assumed to be continues, the optimal energy will be always achieved by using only one frequency, (2) for real processors with a discrete set of working frequencies, the optimal energy is always achieved by using at most two frequencies, and (3) these two frequencies are adjacent/neighbouring when processor energy consumption is a convex function of frequency. Thirdly, a novel algorithm to find the best combination of frequencies to result the optimal energy is presented. The presented algorithm has been evaluated based on results obtained from experiments with three different sets of task graphs: 3000 randomly generated task graphs, and 600 task graphs for two popular applications (Gauss-Jordan and LU decomposition). The results show the superiority of the proposed algorithm in comparison with other techniques.