SCHEDULE: NOV 10-16, 2012
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RAMZzz: Rank-Aware DRAM Power Management with Dynamic Migrations and Demotions
SESSION: DRAM Power and Resiliency Management
EVENT TYPE: Papers
TIME: 3:30PM - 4:00PM
SESSION CHAIR: Nathan Debardeleben
AUTHOR(S):Donghong Wu, Bingsheng He, Xueyan Tang, Jianliang Xu, Minyi Guo
ROOM:355-D
ABSTRACT:
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$^2$ and energy consumption over other power saving techniques.
Chair/Author Details:
Nathan Debardeleben (Chair) - Los Alamos National Laboratory
Donghong Wu - Nanyang Technological University
Bingsheng He - Nanyang Technological University
Xueyan Tang - Nanyang Technological University
Jianliang Xu - Hong Kong Baptist University
Minyi Guo - Shanghai Jiao Tong University
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RAMZzz: Rank-Aware DRAM Power Management with Dynamic Migrations and Demotions
SESSION: DRAM Power and Resiliency Management
EVENT TYPE:
TIME: 3:30PM - 4:00PM
SESSION CHAIR: Nathan Debardeleben
AUTHOR(S):Donghong Wu, Bingsheng He, Xueyan Tang, Jianliang Xu, Minyi Guo
ROOM:355-D
ABSTRACT:
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$^2$ and energy consumption over other power saving techniques.
Chair/Author Details:
Nathan Debardeleben (Chair) - Los Alamos National Laboratory
Donghong Wu - Nanyang Technological University
Bingsheng He - Nanyang Technological University
Xueyan Tang - Nanyang Technological University
Jianliang Xu - Hong Kong Baptist University
Minyi Guo - Shanghai Jiao Tong University
Click here to download .ics calendar file