Estimating neural networks-based algorithm for adaptive cache replacement

In this paper, we propose an adaptive cache replacement scheme based on the estimating type of neural networks (NN´s). The statistical prediction property of such NN´s is used in our work to develop a neural network based replacement policy which can effectively identify and eliminate inactive cache lines. This would provide larger free space for a cache to retain actively referenced lines. The proposed strategy may, therefore, yield better cache performance as compared to the conventional schemes. Simulation results for a wide spectrum of cache configurations indicate that the estimating neural network based replacement scheme provides significant performance advantage over existing policies