GPUs for Genetic and Evolutionary Computation
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The Goal This competition focuses on the applications of genetic and evolutionary computation that can maximally exploit the parallelism provided by low-cost consumer graphical cards. The competition will award the best applications both in terms of degree of parallelism obtained, in terms of overall speed-up, and in terms of programming style. The Competition We had 4 excellent submissions that have now been reviewed by our panel. During the competition slot, the entrants will be given time to present their work. The winner will be announced on Sunday. |
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The Submissions
Winning Entry
Nicholas A. Sinnott-Armstrong , Delaney Granizo-Mackenzie, Jason H. Moore - High Performance Parallel Disease Detection: an Artificial Immune System for GPUs
Other Entries
The Van Luong, Nouredine Melab, El-Ghazali Talbi - GPU-based Parallel Hybrid Genetic Algorithms
Marķa A. Franco, Natalio Krasnogor, Jaume Bacardit - Speeding up the BioHEL evolutionary learning system using GPGPUs
Jason Normore, Simon Harding, Wolfgang Banzhaf - Computational Fluid Dynamics on GPUS for Genetic Programming Fitness Evaluation
On behalf of the organisers, I would like to offer a big thank you to all those who entered. (Simon Harding)