Abstract
The use of FPGA based custom computing platforms is proposed for implementing linearly structured Genetic Programs. Such a context enables consideration of micro architectural and instruction design issues not normally possible when using classical Von Neumann machines. More importantly, the desirability of minimising memory management overheads results in the imposition of additional constraints to the crossover operator. Specifically, individuals are described in terms of the number of pages and page length, where the page length is common across individuals of the population. Pairwise crossover therefore results in the swapping of equal length pages, hence minimising memory overheads. Simulation of the approach demonstrates that the method warrants further study.
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Heywood, M.I., Zincir-Heywood, A.N. (2000). Register Based Genetic Programming on FPGA Computing Platforms. In: Poli, R., Banzhaf, W., Langdon, W.B., Miller, J., Nordin, P., Fogarty, T.C. (eds) Genetic Programming. EuroGP 2000. Lecture Notes in Computer Science, vol 1802. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-46239-2_4
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