Large-scale experimental evaluation of GPU strategies for evolutionary machine learning
We exhaustively evaluate two GPU strategies for evolutionary machine learning systems. We use synthetic datasets to thoroughly explore the space of problem characteristics. The findings of the evaluation on synthetic datasets translate to real-world problems. Our findings help avoiding a blind trial-and-error calibration of GPU data mining code.
evolutionary machine learning large-scale data mining graphics processing units