By Topic

Estimating neural networks-based algorithm for adaptive cache replacement

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
M. S. Obaidat ; Dept. of Comput. Sci., Monmouth Univ., West Long Branch, NJ, USA ; H. Khalid

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

Published in:

IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)  (Volume:28 ,  Issue: 4 )