- author = "Gopinath Chennupati and R. Muhammad Atif Azad and Conor Ryan",
- title = "Synthesis of Parallel Iterative Sorts with Multi-Core Grammatical Evolution",
- booktitle = "GECCO 2015 5th Workshop on Evolutionary Computation for the Automated Design of Algorithms (ECADA'15)",
- year = "2015",
- editor = "John Woodward and Daniel Tauritz and Manuel Lopez-Ibanez",
- isbn13 = "978-1-4503-3488-4",
- keywords = "genetic algorithms, genetic programming, grammatical evolution",
- pages = "1059--1066",
- month = "11-15 " # jul,
- organisation = "SIGEVO",
- address = "Madrid, Spain",
-
URL = "
http://doi.acm.org/10.1145/2739482.2768458",
-
DOI = "
doi:10.1145/2739482.2768458",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
-
abstract = "Writing parallel programs is a challenging but
unavoidable proposition to take true advantage of
multi-core processors.
In this paper, we extend Multi-core Grammatical Evolution for Parallel Sorting (MCGE-PS) to evolve parallel iterative sorting algorithms while also optimizing their degree of parallelism. We use evolution to optimize the performance of these parallel programs in terms of their execution time, and our results demonstrate a significant optimization of 11.03 in performance when compared with various MCGE-PS variations as well as the GNU GCC compiler optimizations that reduce the execution time through code minimization.
We then analyse the evolutionary (code growth) and non-evolutionary (thread scheduling) factors that cause performance implications. We address them to further optimize the performance and report it as 12.52.",
- notes = "Also known as \cite{2768458} Distributed at GECCO-2015.",
