A CA based scheme of cache zone prediction for data migration In CMPs

Abstract

This work proposes an efficient scheme for identification of L2 cache module zone (low level cache) for data migration in Chip Multiprocessors (CMPs), during program execution, exploiting the benefits of Non-Uniform Cache Architecture (NUCA). Selection of an exact cache module for migration is always not realizable. A more efficient scheme can be the prediction of cache zone for migration. The proposed scheme is developed around the modelling tool of periodic boundary cellular automata (CA) to satisfy the requirement. The CA employed performs density classification of the instances of data request generated by different processor cores and predicts the best placement for data (up to an acceptable level) in the low level NUCA cache.