Register Based Genetic Programming on FPGA Computing Platforms
Proceedings of the European Conference on Genetic Programming
IEEE Micro
Parallel multi-objective evolutionary algorithms on graphics processing units
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
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
Highly scalable multi objective test suite minimisation using graphics cards
SSBSE'11 Proceedings of the Third international conference on Search based software engineering
A Map-Reduce Based Framework for Heterogeneous Processing Element Cluster Environments
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
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A widely available and economic means of increasing the computing power applied to a problem is to use modern graphics processing units (GPUs) for parallel processing. We present a new, optimized general methodology for deploying genetic programming (GP) to the PC, Xbox 360 video game console, and Zune portable media device. This work describes, for the first time, the implementation considerations necessary to maximize available CPU and GPU (where available) usage on the three separate hardware platforms. We demonstrate the first instance of GP using portable digital media device hardware. The work also presents, for the first time, an Xbox 360 implementation that uses the GPU for fitness evaluation. Implementations on each platform are also benchmarked on the basis of execution time for an established GP regression benchmark.