Analog Circuits and Systems Optimization based on Evolutionary Computation Techniques
Barros , M.B.
Analog Circuits and Systems Optimization based on Evolutionary Computation Techniques, Proc International Workshop on Symbolic and Numerical Methods, Modeling and Applications to Circuit Design - SM2ACD , Erfurt, Germany, Vol. , pp. 68 - 73, October, 2008.
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The microelectronics market trends present an ever-increasing level of complexity with special emphasis on the production of complex mixed-signal systems-on-chip. Strict economic and design pressures have driven the development of new methods for automating the analog design process. However, and despite some significant research efforts, the essential act of design at the transistor level is still performed by the trial and error interaction between the designer and the simulator. This paper focus on the development of a new design automation tool based on a modified genetic algorithm kernel, in order to increase efficiency on the analog circuit and system design cycle. It combines a robust optimization with corners, machine learning modeling and distributed processing capability able to deal with multi-objective and highly constrained optimization problems. The resulting optimization tool, simulation capabilities, and extensible architecture are presented and the improvement in design productivity is demonstrated for the design of robust CMOS operational amplifiers.