Solid state electronic devices (4th ed.)
Solid state electronic devices (4th ed.)
The effect of polysilicon grain boundaries on MOS based devices
INFOS'99 Proceedings of the 11th biennial conference on on Insulating films on semiconductors
Principles in the Evolutionary Design of Digital Circuits—Part I
Genetic Programming and Evolvable Machines
Parameter variations and impact on circuits and microarchitecture
Proceedings of the 40th annual Design Automation Conference
Power Dissipation Reductions with Genetic Algorithms
EH '03 Proceedings of the 2003 NASA/DoD Conference on Evolvable Hardware
Design methodology for IC manufacturability based on regular logic-bricks
Proceedings of the 42nd annual Design Automation Conference
High-performance CMOS variability in the 65-nm regime and beyond
IBM Journal of Research and Development - Advanced silicon technology
Introduction to Evolvable Hardware: A Practical Guide for Designing Self-Adaptive Systems (IEEE Press Series on Computational Intelligence)
High-speed, low-leakage integrated circuits: An evolutionary algorithm perspective
Journal of Systems Architecture: the EUROMICRO Journal
Adaptive Optical Proximity Correction Using an Optimization Method
CIT '07 Proceedings of the 7th IEEE International Conference on Computer and Information Technology
Human-competitive evolved antennas
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Evolving Variability-Tolerant CMOS Designs
ICES '08 Proceedings of the 8th international conference on Evolvable Systems: From Biology to Hardware
Towards evolving industry-feasible intrinsic variability tolerant CMOS designs
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Optimising variability tolerant standard cell libraries
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
The route to a defect tolerant LUT through artificial evolution
Genetic Programming and Evolvable Machines
Promises and challenges of evolvable hardware
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
IEEE Spectrum
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Evolvable Hardware has been a discipline for over 15 years. Its application has ranged from simple circuit design to antenna design. However, research in the field has often been criticised for not addressing real world problems. Intrinsic variability has been recognised as one of the major challenges facing the semiconductor industry. This paper describes an approach that optimises designs within a standard cell library by altering the transistor dimensions. The proposed approach uses a Multi-objective Genetic Algorithm to optimise the device widths within a standard cell. The designs are analysed using statistically enhanced transistor models (based on 3D-atomistic simulations) and statistical Spice simulations. The goal is to extract high-speed and low-power designs, which are more tolerant to the random fluctuations present in current and future technology nodes. The results show improvements in both the speed and power of the optimised standard cells and that the impact of threshold voltage variation is reduced.