Clustered voltage scaling technique for low-power design
ISLPED '95 Proceedings of the 1995 international symposium on Low power design
ISLPED '95 Proceedings of the 1995 international symposium on Low power design
Scheduling techniques for variable voltage low power designs
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Energy minimization using multiple supply voltages
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special issue on low power electronics and design
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
High-Level Power Analysis and Optimization
High-Level Power Analysis and Optimization
Low Power Digital CMOS Design
VLSI and Modern Signal Processing
VLSI and Modern Signal Processing
On two-pronged power-aware voltage scheduling for multi-processor real-time systems
PATMOS'07 Proceedings of the 17th international conference on Integrated Circuit and System Design: power and timing modeling, optimization and simulation
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This paper presents an efficient search method for a scheduling and module selection problem using multiple supply voltages so as to minimize dynamic energy consumption under time and area constraints. The proposed algorithm is based on a genetic algorithm so that it can find near-optimal solutions in a short time for large-size problems. n efficient search can be achieved by crossover that prevents generating nonvalid individuals and a local search is also utilized in the algorithm. Experimental results for large-size problems with 1,000 operations demonstrate that the proposed method can achieve significant energy reduction up to 50 percent and can find a near-optimal solution (within 2.8 percent from the lower bound of optimal solutions) in 10 minutes. On the other hand, the ILP-based method cannot find any feasible solution in one hour for the large-size problem, even if a state-of-art mathematical programming solver is used.