Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7609
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dc.contributor.authorLau, Wai Shingen_US
dc.contributor.authorLi, Gangen_US
dc.contributor.authorLee, Kin Hongen_US
dc.contributor.authorProf. LEUNG Kwong Saken_US
dc.contributor.authorCheang, Sin Manen_US
dc.date.accessioned2023-03-27T04:16:28Z-
dc.date.available2023-03-27T04:16:28Z-
dc.date.issued2005-
dc.identifier.citationLecture Notes in Computer Science, 2005, vol. 3447, pp. 167 - 177en_US
dc.identifier.issn03029743-
dc.identifier.urihttp://hdl.handle.net/20.500.11861/7609-
dc.description.abstractGenetic Parallel Programming (GPP) is a novel Genetic Programming paradigm. GPP Logic Circuit Synthesizer (GPPLCS) is a combinational logic circuit learning system based on GPP. The GPPLCS comprises a Multi-Logic-Unit Processor (MLP) which is a hardware processor built on a Field Programmable Gate Array (FPGA). The MLP is designed to speed up the evaluation of genetic parallel programs that represent combinational logic circuits. Four combinational logic circuit problems are presented to show the performance of the hardware-assisted GPPLCS. Experimental results show that the hardware MLP speeds up evolutions over 10 times. For difficult problems such as the 6-bit priority selector and the 6-bit comparator, the speedup ratio can be up to 22. © Springer-Verlag Berlin Heidelberg 2005.en_US
dc.language.isoenen_US
dc.publisherSpringer Verlagen_US
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.titleMulti-logic-Unit Processor: A combinational logic circuit evaluation engine for genetic parallel programmingen_US
dc.typeConference Paperen_US
dc.identifier.doi10.1007/978-3-540-31989-4_15-
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Applied Data Science-
Appears in Collections:Applied Data Science - Publication
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