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As the heterogeneous system based on CPU-GPU architecture has a strong performance advantages, so that it has been widely used in many fields especially image recognition, in order to enhance the transmission efficiency on HSA (Heterogeneous System Architecture) Platform. In this paper, we design a naive Bayesian image classification algorithm on the APU, which supports the HSA standard, and design a set of resource dynamic scheduling strategy for the eigenvalue extraction of the algorithm. The experimental results show that this strategy can save 29.56% execution time on average.

A Scheduling Strategy of Naive Bayesian image classification on HSA Platform