Design space issues for intrinsic evolvable hardware
- 13 November 2004
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
This paper discusses the problem of increased programming time for intrinsic evolvable hardware (EHW) as the complexity of the circuit grows. We develop equations for the size of the population, n, and the number of generations required for the population to converge, ngen, based on L, the length of the programming string. We show that the processing time of the computer becomes negligible for intrinsic EHW since the selection/crossover/mutation steps are only done once per generation, suggesting there is room for use of more complex evolutionary algorithms in intrinsic EHW. Finally, we review the state of the practice and discuss the notion of a system design approach for intrinsic EHW.Keywords
This publication has 8 references indexed in Scilit:
- Evolutionary fault recovery in a Virtex FPGA using a representation that incorporates routingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2004
- An experiment on nonlinear synthesis using evolutionary techniques based only on CMOS transistorsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Intrinsic evolution of quasi DC solutions for transistor level analog electronic circuits using a CMOS FPTA chipPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Evolving circuits in seconds: experiments with a stand-alone board-level evolvable systemPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Reducing hardware evolution's dependency on FPGAsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Towards evolving electronic circuits for autonomous space applicationsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Scalability problems of digital circuit evolution evolvability and efficient designsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- The Gambler's Ruin Problem, Genetic Algorithms, and the Sizing of PopulationsEvolutionary Computation, 1999