Evaluating Data Prefetching Methods and Proposing an Energy-aware First Level Cache for Cloud Workloads, Ph.D. Dissertation Sharif University of Technology ; Sarbazi Azad, Hamid (Supervisor)
Abstract
Data generation rate is far more than the technology scaling rate in a way that there will be a 40x gap between the data generation rate and the technology scaling rate in 2020. On one hand, unlike traditional HPC clusters, processors in data centers are not fully utilized and on the other hand, unlike traditional embedded processors, they are not idle most of the time. Therefore, energy consumption of such processors is an important issue; otherwise dealing with a huge volume of data will be problematic in the near future. In this dissertation, we will show that while first level data cache encounters high miss rate, traditional approaches such as data prefetching, which were efficient for...
Cataloging briefEvaluating Data Prefetching Methods and Proposing an Energy-aware First Level Cache for Cloud Workloads, Ph.D. Dissertation Sharif University of Technology ; Sarbazi Azad, Hamid (Supervisor)
Abstract
Data generation rate is far more than the technology scaling rate in a way that there will be a 40x gap between the data generation rate and the technology scaling rate in 2020. On one hand, unlike traditional HPC clusters, processors in data centers are not fully utilized and on the other hand, unlike traditional embedded processors, they are not idle most of the time. Therefore, energy consumption of such processors is an important issue; otherwise dealing with a huge volume of data will be problematic in the near future. In this dissertation, we will show that while first level data cache encounters high miss rate, traditional approaches such as data prefetching, which were efficient for...
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