Automatic Machine Code Generation for a Transport Triggered Architecture using Cartesian Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@Article{journals/ijaras/WalkerLTTT12,

• author = "James Alfred Walker and Yang Liu and Gianluca Tempesti and Jon Timmis and Andy M. Tyrrell",
• title = "Automatic Machine Code Generation for a Transport Triggered Architecture using Cartesian Genetic Programming",
• journal = "International Journal of Adaptive, Resilient and Autonomic Systems",
• year = "2012",
• volume = "3",
• number = "4",
• pages = "32--50",
• keywords = "genetic algorithms, genetic programming, Cartesian Genetic Programming",
• ISSN = "1947-9220",
• DOI = "doi:10.4018/jaras.2012100103",
• bibdate = "2013-03-06",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/journals/ijaras/ijaras3.html#WalkerLTTT12",
• abstract = "Transport triggered architectures are used for implementing bio-inspired systems due to their simplicity, modularity and fault-tolerance. However, producing efficient, optimised machine code for such architectures is extremely difficult, since computational complexity has moved from the hardware-level to the software-level. Presented is the application of Cartesian Genetic Programming (CGP) to the evolution of machine code for a simple implementation of transport triggered architecture. 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 100percent 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. Further analysis of the solutions showed that use of loops within the CGP function set could be beneficial and was demonstrated by repeating the earlier 4-bit multiplier experiment with the addition of a loop function.",

}

Genetic Programming entries for James Alfred Walker Yang Liu Gianluca Tempesti Jon Timmis Andrew M Tyrrell

Citations