Use of graphics processing units for automatic synthesis of programs

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@Article{daSilva:2015:CEE,

• author = "Cleomar Pereira {da Silva} and Douglas {Mota Dias} and Cristiana Bentes and Marco Aurelio Cavalcanti Pacheco",
• title = "Use of graphics processing units for automatic synthesis of programs",
• journal = "Computer \& Electrical Engineering",
• volume = "46",
• pages = "112--122",
• year = "2015",
• ISSN = "0045-7906",
• DOI = "doi:10.1016/j.compeleceng.2015.04.006",
• URL = "http://www.sciencedirect.com/science/article/pii/S0045790615001342",
• abstract = "Genetic programming (GP) is an evolutionary method that allows computers to solve problems automatically. However, the computational power required for the evaluation of billions of programs imposes a serious limitation on the problem size. This work focuses on accelerating GP to support the synthesis of large problems. This is done by completely exploiting the highly parallel environment of graphics processing units (GPUs). Here, we propose a new quantum-inspired linear GP approach that implements all the GP steps in the GPU and provides the following: (1) significant performance improvements in the GP steps, (2) elimination of the overhead of copying the fitness results from the GPU to the CPU, and (3) incorporation of a new selection mechanism to recognize the programs with the best evaluations. The proposed approach outperforms the previous approach for large-scale synthetic and real-world problems. Further, it provides a remarkable speedup over the CPU execution.",
• keywords = "genetic algorithms, genetic programming, GPU acceleration, Machine code, Quantum-inspired algorithms, Massive parallelism",

}

Genetic Programming entries for Cleomar Pereira da Silva Douglas Mota Dias Cristiana Bentes Marco Aurelio Cavalcanti Pacheco

Citations