- author = "Gopinath Chennupati and R. Muhammad Atif Azad and Conor Ryan",
- title = "On the Automatic Generation of Efficient Parallel Iterative Sorting Algorithms",
- booktitle = "GECCO Companion '15: Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation",
- year = "2015",
- editor = "Sara Silva and Anna I Esparcia-Alcazar and Manuel Lopez-Ibanez and Sanaz Mostaghim and Jon Timmis and Christine Zarges and Luis Correia and Terence Soule and Mario Giacobini and Ryan Urbanowicz and Youhei Akimoto and Tobias Glasmachers and Francisco {Fernandez de Vega} and Amy Hoover and Pedro Larranaga and Marta Soto and Carlos Cotta and Francisco B. Pereira and Julia Handl and Jan Koutnik and Antonio Gaspar-Cunha and Heike Trautmann and Jean-Baptiste Mouret and Sebastian Risi and Ernesto Costa and Oliver Schuetze and Krzysztof Krawiec and Alberto Moraglio and Julian F. Miller and Pawel Widera and Stefano Cagnoni and JJ Merelo and Emma Hart and Leonardo Trujillo and Marouane Kessentini and Gabriela Ochoa and Francisco Chicano and Carola Doerr",
- isbn13 = "978-1-4503-3488-4",
- keywords = "genetic algorithms, genetic programming, grammatical evolution: Poster",
- pages = "1369--1370",
- month = "11-15 " # jul,
- organisation = "SIGEVO",
- address = "Madrid, Spain",
-
URL = "
http://doi.acm.org/10.1145/2739482.2764695",
-
DOI = "
doi:10.1145/2739482.2764695",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
-
abstract = "Increasing availability of multiple processing
elements on the recent desktop and personal computers
poses unavoidable challenges in realizing their
processing power. The challenges include programming
these high processing elements. Parallel programming is
an apt solution for such a realization of the
computational capacity. However, it has many
difficulties in developing the parallel programs.
We present Multi-core Grammatical Evolution for Parallel Sorting (MCGE-PS) that automatically produces native parallel sorting programs. These programs are of iterative nature that also exploit the processing power of the multi-core processors efficiently. The performance of the resultant programs is measured in terms of the execution time. The results indicate a significant improvement over the state-of-the-art implementations. Finally, we conduct an empirical analysis on computational complexity of the evolving parallel programs. The results are competitive with that of the state-of-the-art evolutionary attempts.",
- notes = "Also known as \cite{2764695} Distributed at GECCO-2015.",
