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Erschienen in:
2010 | OriginalPaper | Buchkapitel
Speeding Up Matching in Learning Classifier Systems Using CUDA
verfasst von : Pier Luca Lanzi, Daniele Loiacono
Erschienen in: Learning Classifier Systems
Verlag: Springer Berlin Heidelberg
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We investigate the use of NVIDIA’s Compute Unified Device Architecture (CUDA) to speed up matching in classifier systems. We compare CUDA-based matching and CPU-based matching on (i) real inputs using interval-based conditions and on (ii) binary inputs using ternary conditions. Our results show that on small problems, due to the memory transfer overhead introduced by CUDA, matching is faster when performed using the CPU. As the problem size increases, CUDA-based matching can outperform CPU-based matching resulting in a 3-12× speedup when the interval-based representation is applied to match real-valued inputs and a 20-50× speedup for ternary-based representation.