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Evolved Synthesis of Digital Circuits

Evolved Synthesis of Digital Circuits
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Author(s): Laurentiu Ionescu (University of Pitesti, Romania), Alin Mazare (University of Pitesti, Romania), Gheorghe Serban (University of Pitesti, Romania)and Emil Sofron (University of Pitesti, Romania)
Copyright: 2009
Pages: 9
Source title: Encyclopedia of Artificial Intelligence
Source Author(s)/Editor(s): Juan Ramón Rabuñal Dopico (University of A Coruña, Spain), Julian Dorado (University of A Coruña, Spain)and Alejandro Pazos (University of A Coruña, Spain)
DOI: 10.4018/978-1-59904-849-9.ch093

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Abstract

Traditionally physical systems have been designed by engineers using complex collections of rules and principles. The design process is top-down in nature and begins with a precise specification. This contrasts very strongly with the mechanisms which have produced the extraordinary diversity and sophistication of living creatures. In this case the ‘‘designs’’ are evolved by a process of natural selection. The design starts as a set of instructions encoded in the DNA whose coding regions are first transcribed into RNA in the cell nucleus and then later translated into proteins in the cell cytoplasm. The DNA carries the instructions for building molecules using sequences of amino acids. Eventually after a number of extraordinarily complex and subtle biochemical reactions an entire living organism is created. The survivability of the organism can be seen as a process of assembling a larger system from a number of component parts and then testing the organism in the environment in which it finds itself (Miller, 2000). The main target of the evolvable hardware is to build a digital circuit using bio inspired methods like genetic algorithms. Here the potential solutions are coded like configuration vectors which command interconnection between logical cells inside the reconfigurable circuit. All configuration vectors represent the genotype and one single configuration vector is the individual with its own characteristics (like chromosome). The individuals are generated by genetic operators like crossover or mutation. One individual give one solution circuit which is tested in evaluation module. The circuit obtained from the individual consist the phenotype. The circuit behavior is compared with target functions, which we desire to implement. The result is fitness: if the circuit approximates the behavior of the target function, we have a good fitness for the individual which generate the circuit. Then each individual whit its fitness gets into selection module where the future parents in crossover and mutation are decided. Finally we have a circuit solution which implements the target function. We have an evolved synthesis of digital circuit – a method like assemble and test. This method can be useful because explore the design space beyond the limits imposed by traditional design methods. Two research directions are developed in evolvable hardware. In extrinsic evolvable hardware the individuals are obtained from software implementation on computer and phenotype consist in high level abstract circuits like SPICE object files or FPGA configuration files (.bit). The intrinsic evolution, on the other hand, supposes that entire evolution process is inside one or more chips (FPGA): the hardware implementation of evolved hardware. The challenge is to design an intrinsic evolution because can be used for applications like robots control system. But this involves implementation of the software based algorithms in hardware modules.

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