Abstract
Genetic Parallel Programming (GPP) is a novel Genetic Programming paradigm. The GPP Accelerating Phenomenon, i.e. parallel programs are easier to be evolved than sequential programs, opens up a new approach to evolve solution programs in parallel forms. Based on the GPP paradigm, we developed a combinational digital circuit learning system, the GPP+MLP system. An optimal Multiple Logic Unit Processor (MLP) is designed to evaluate genetic parallel programs. To show the effectiveness of the proposed GPP+MLP system, four multi-output Binary arithmetic circuits are used. Experimental results show that both the gate counts and the propagation gate delays of the evolved circuits are less than conventional designs. For example, in a 3-bit multiplier experiment, we obtained a combinational digital circuit with 26 two-input logic gates in 6 gate levels. It utilizes 4 gates less than a conventional design.
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Cheang, S.M., Lee, K.H., Leung, K.S. (2004). Designing Optimal Combinational Digital Circuits Using a Multiple Logic Unit Processor. In: Keijzer, M., O’Reilly, UM., Lucas, S., Costa, E., Soule, T. (eds) Genetic Programming. EuroGP 2004. Lecture Notes in Computer Science, vol 3003. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24650-3_3
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DOI: https://doi.org/10.1007/978-3-540-24650-3_3
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