Title :
Memory Affinity: Balancing Performance, Power, Thermal and Fairness for Multi-core Systems
Author :
Jia, Gangyong ; Li, Xi ; Wang, Chao ; Zhou, Xuehai ; Zhu, Zongwei
Author_Institution :
Dept. of Comput. Sci. & Technol., Univ. of Sci. & Technol. of China (USTC), Hefei, China
Abstract :
Main memory is expected to grow significantly in both speed and capacity for it is a major shared resource among cores in a multi-core system, which will lead to increasing power consumption. Therefore, it is critical to address the power issue without seriously decreasing performance in the memory subsystem. In this paper, we firstly propose memory affinity which retains the active and low power memory ranks as long as possible to avoid frequently switching between active and low power status, and then present a memory affinity aware scheduling (MAS) to balance performance, power, thermal and fairness for multi-core systems. Experimental results demonstrate our memory affinity aware scheduling algorithms well adapt to system loading to maximize power saving and avoid memory hotspot at the same time while sustaining the system bandwidth demand and preserving fairness among threads.
Keywords :
multiprocessing systems; power consumption; resource allocation; scheduling; storage management; MAS; active memory ranks; fairness balancing; fairness preservation; low power memory ranks; memory affinity aware scheduling; memory hotspot avoidance; memory subsystem; multicore systems; performance balancing; power balancing; power consumption; power saving maximization; shared resource; system bandwidth demand; thermal balancing; Instruction sets; Memory management; Multicore processing; Random access memory; Switches; Thermal management; Memory system; fairness; memory affinity; performance; power;
Conference_Titel :
Cluster Computing (CLUSTER), 2012 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-2422-9
DOI :
10.1109/CLUSTER.2012.33