An Effective and Efficient Approach for Supporting the Generation of Synthetic Memory Reference Traces via Hierarchical Hidden/Non-Hidden Markov Models

摘要

This paper proposes and experimentally assesses a machine learning approach for supporting the effective and efficient generation of synthetic memory reference traces for a wide range of application scenarios. The proposed approach makes a nice use of extended hierarchical Markov models.