Neural networks: a systematic introduction
Neural networks: a systematic introduction
Low power synthesis of dual threshold voltage CMOS VLSI circuits
ISLPED '99 Proceedings of the 1999 international symposium on Low power electronics and design
Proceedings of the 39th annual Design Automation Conference
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Unveiling the ISCAS-85 Benchmarks: A Case Study in Reverse Engineering
IEEE Design & Test
Low-Power, High-Speed CMOS VLSI Design
ICCD '02 Proceedings of the 2002 IEEE International Conference on Computer Design: VLSI in Computers and Processors (ICCD'02)
Statistical optimization of leakage power considering process variations using dual-Vth and sizing
Proceedings of the 41st annual Design Automation Conference
Transistor and Pin Reordering for Gate Oxide Leakage Reduction in Dual T{ox} Circuits
ICCD '04 Proceedings of the IEEE International Conference on Computer Design
VLSI Design Challenges for Gigascale Integration
VLSID '05 Proceedings of the 18th International Conference on VLSI Design held jointly with 4th International Conference on Embedded Systems Design
Reducing Leakage with Mixed-V_th (MVT)
VLSID '05 Proceedings of the 18th International Conference on VLSI Design held jointly with 4th International Conference on Embedded Systems Design
Characterization and modeling of run-time techniques for leakage power reduction
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Nanoelectronic circuits and systems
Enhanced leakage reduction Technique by gate replacement
Proceedings of the 42nd annual Design Automation Conference
Evolutionary computation: comments on the history and current state
IEEE Transactions on Evolutionary Computation
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Designers aim at fast but low-power consuming integrated circuits. Since high processing speed always comes with high energy demands, the literature provides several ways to reduce a circuit's power dissipation. Even though technologically not possible today, this paper hypothesizes that the design would allow for choosing a gate's from a continuous domain in order to explore options for future improvements. That is, the design goal consists in selecting a gate's delay such that both the circuit's delay and its power consumption assumes minimal values. Since the resulting optimization problem is multi-dimensional and might also contain local optima, this paper utilizes genetic algorithms for this task. On a selection of the well-known ISCACS test suite, the genetic algorithms reduced the circuits' leakage values by about 20-50 %; with respect to nonoptimized circuits, the improvement is about 60-80%.