Estimating neural networks-based algorithm for adaptive cachereplacement

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.