Abstract
This paper shows that it is possible to use General Purpose Graphic Processing Unit cards for a fast evaluation of different Genetic Programming trees on as few as 32 fitness cases by using the hardware scheduling of NVIDIA cards. Depending on the function set, observed speedup ranges between ×50 and ×250 on one half of an NVidia GTX295 GPGPU card, vs a single core of an Intel Quad core Q8200.
Keywords
- Genetic Program
- Linear Genetic Program
- Cartesian Genetic Programming
- Fitness Case
- General Purpose Graphic Processing Unit
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Maitre, O., Lachiche, N., Collet, P. (2010). Fast Evaluation of GP Trees on GPGPU by Optimizing Hardware Scheduling. In: Esparcia-Alcázar, A.I., Ekárt, A., Silva, S., Dignum, S., Uyar, A.Ş. (eds) Genetic Programming. EuroGP 2010. Lecture Notes in Computer Science, vol 6021. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12148-7_26
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DOI: https://doi.org/10.1007/978-3-642-12148-7_26
Publisher Name: Springer, Berlin, Heidelberg
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