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Parallel optimization of transistor level circuits using cartesian genetic programming

Published:15 July 2017Publication History

ABSTRACT

The aim of the paper is to introduce a new parallel approach to evolutionary optimization of digital circuits described on transistor level. The evolutionary optimization is guided by the fitness function employing a simulator of candidate circuits. A new discrete simulator was introduced to achieve a good trade-off between precision and cost of circuit evaluations. The simulator is based on event-driven simulation. Precise numeric SPICE simulator is regularly called to validate simulation results. To increase the speed of evolution, three parallel approaches were proposed: (i) thread level parallelism, (ii) multiple computing nodes which collectively communicate and distribute the best solution, and (iii) client-server architecture eliminating a limited count of SPICE simulator instances.

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          cover image ACM Conferences
          GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference Companion
          July 2017
          1934 pages
          ISBN:9781450349390
          DOI:10.1145/3067695

          Copyright © 2017 ACM

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          • Published: 15 July 2017

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