@inproceedings{DBLP:conf/eurogp/HardingB07, author = {Simon Harding and Wolfgang Banzhaf}, title = {Fast Genetic Programming on GPUs}, booktitle = {EuroGP}, year = {2007}, pages = {90-101}, ee = {http://dx.doi.org/10.1007/978-3-540-71605-1_9}, crossref = {DBLP:conf/eurogp/2007}, bibsource = {DBLP, http://dblp.uni-trier.de} } @proceedings{DBLP:conf/eurogp/2007, editor = {Marc Ebner and Michael O'Neill and Anik{\'o} Ek{\'a}rt and Leonardo Vanneschi and Anna Esparcia-Alc{\'a}zar}, title = {Genetic Programming, 10th European Conference, EuroGP 2007, Valencia, Spain, April 11-13, 2007, Proceedings}, booktitle = {EuroGP}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, volume = {4445}, year = {2007}, isbn = {978-3-540-71602-0}, bibsource = {DBLP, http://dblp.uni-trier.de} } @inproceedings{1256286, author = {Simon Harding and Wolfgang Banzhaf}, title = {Fast Genetic Programming and Artificial Developmental Systems on GPUs}, booktitle = {HPCS '07: Proceedings of the 21st International Symposium on High Performance Computing Systems and Applications}, year = {2007}, isbn = {0-7695-2813-9}, pages = {2}, doi = {http://dx.doi.org/10.1109/HPCS.2007.17}, publisher = {IEEE Computer Society}, address = {Washington, DC, USA}, } @InProceedings{langdon:2008:eurogp, author = "W. B. Langdon and W. Banzhaf", title = "A {SIMD} interpreter for Genetic Programming on {GPU} Graphics Cards", booktitle = "EuroGP", year = "2008", series = "LNCS", address = "Naples", month = "26-28 " # mar, publisher = "Springer", note = "Forthcoming", keywords = "genetic algorithms, genetic programming, GPU, parallel computing architecture", URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/langdon_2008_eurogp.pdf", size = "12 pages", abstract = "Mackey-Glass chaotic time series prediction and nuclear protein classification show the feasibility of evaluating genetic programming populations directly on parallel consumer gaming graphics processing units. Using a Linux KDE computer equipped with an nVidia GeForce 8800 GTX graphics processing unit card the C++ SPMD interpretter evolves programs at giga GP operation per second (895 million GPops). We use the RapidMind general processing on GPU (GPGPU) framework to evaluate an entire population of a quarter of a million individual programs on a non-trivial problem in 4 seconds. An efficient reverse polish notation (RPN) tree based GP is given.", notes = "Memorial University Animation http://www.cs.ucl.ac.uk/staff/W.Langdon/pi2_movie.html Code http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/gp-code/gpu_gp_1.tar.gz", size = "12 pages", } @inproceedings{1277274, author = {Darren M. Chitty}, title = {A data parallel approach to genetic programming using programmable graphics hardware}, booktitle = {GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation}, year = {2007}, isbn = {978-1-59593-697-4}, pages = {1566--1573}, location = {London, England}, doi = {http://doi.acm.org/10.1145/1276958.1277274}, publisher = {ACM}, address = {New York, NY, USA}, }