Abstract
This paper presents for the first time the application of Cartesian Genetic Programming to the evolution of machine code for a simple implementation of a MOVE processor. The effectiveness of the algorithm is demonstrated by evolving machine code for a 4-bit multiplier with three different levels of parallelism. The results show that 100% successful solutions were found by CGP and by further optimising the size of the solutions, it is possible to find efficient implementations of the 4-bit multiplier that have the potential to be ”human competitive”. Further analysis of the results revealed that the structure of some solutions followed a known general design methodology.
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Walker, J.A., Liu, Y., Tempesti, G., Tyrrell, A.M. (2010). Automatic Code Generation on a MOVE Processor Using Cartesian Genetic Programming. In: Tempesti, G., Tyrrell, A.M., Miller, J.F. (eds) Evolvable Systems: From Biology to Hardware. ICES 2010. Lecture Notes in Computer Science, vol 6274. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15323-5_21
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DOI: https://doi.org/10.1007/978-3-642-15323-5_21
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