Proceedings of the European Conference on Genetic Programming
Fast Genetic Programming and Artificial Developmental Systems on GPUs
HPCS '07 Proceedings of the 21st International Symposium on High Performance Computing Systems and Applications
A data parallel approach to genetic programming using programmable graphics hardware
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Genetic programming on graphics processing units
Genetic Programming and Evolvable Machines
Fast genetic programming on GPUs
EuroGP'07 Proceedings of the 10th European conference on Genetic programming
Deployment of parallel linear genetic programming using GPUs on PC and video game console platforms
Genetic Programming and Evolvable Machines
SMCGP2: self modifying cartesian genetic programming in two dimensions
Proceedings of the 13th annual conference on Genetic and evolutionary computation
A many threaded CUDA interpreter for genetic programming
EuroGP'10 Proceedings of the 13th European conference on Genetic Programming
Efficient phenotype evaluation in cartesian genetic programming
EuroGP'12 Proceedings of the 15th European conference on Genetic Programming
Accelerated parallel genetic programming tree evaluation with OpenCL
Journal of Parallel and Distributed Computing
On GPU based fitness evaluation with decoupled training partition cardinality
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
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This paper investigates the use of a new Graphics Processing Unit (GPU) programming tool called 'GPU.NET' for implementing a Genetic Programming fitness evaluator. We find that the tool is able to help write software that accelerates fitness evaluation. For the first time, Cartesian Genetic Programming (CGP) was used with a GPU-based interpreter. With its code reuse and compact representation, implementing CGP efficiently on the GPU required several innovations. Further, we tested the system on a very large data set, and showed that CGP is also suitable for use as a classifier.