Department of Computer Science
RAMZzz: Rank-aware DRAM power management with dynamic migrations and demotions
Main memory is a significant energy consumer which may contribute to over 40% of the total system power, and will become more significant for server machines with more main memory. In this paper, we propose a novel memory system design named RAMZzz with rank-aware energy saving optimizations. Specifically, we rely on a memory controller to monitor the memory access locality, and group the pages with similar access locality into the same rank. We further develop dynamic page migrations to adapt to data access patterns, and a prediction model to estimate the demotion time for accurate control on power state transitions. We experimentally compare our algorithm with other energy saving policies with cycle-accurate simulation. Experiments with benchmark workloads show that RAMZzz achieves significant improvement on energy-delay and energy consumption over other power saving techniques. © 2012 IEEE.
Source Publication Title
2012 International Conference for High Performance Computing, Networking, Storage and Analysis (SC).
Salt Lake City, Utah
Wu, Donghong, Bingsheng He, Xueyan Tang, Jianliang Xu, and Minyi Guo. "RAMZzz: Rank-aware DRAM power management with dynamic migrations and demotions." 2012 International Conference for High Performance Computing, Networking, Storage and Analysis (SC). (2012): 1-11.