TY - JOUR
T1 - Minimizing energy on homogeneous processors with shared memory
AU - CHAU, Vincent
AU - FONG, Chi Kit Ken
AU - LIU, Shengxin
AU - WANG, Yinling Elaine
AU - ZHANG, Yong
N1 - A preliminary version of this paper appeared in Proceedings of FAW'2020, LNCS 12340, p 83–95
PY - 2021/4/18
Y1 - 2021/4/18
N2 - Energy efficiency is a crucial desideratum in the design of computer systems, from small-sized mobile devices with limited battery to large scale data centers. In such computing systems, processors and memory are considered as two major power consumers among all the system components. One recent trend to reduce power consumption is using shared memory in multi-core systems, such architecture has become ubiquitous nowadays. However, implementing the energy-efficient methods to the multi-core processor and the shared memory separately is not trivial. In this work, we consider the energy-efficient task scheduling problem, which coordinates the power consumption of both the multi-core processor and the shared memory, especially focus on the general situation in which the number of tasks is more than the number of cores. We devise an approximation algorithm with guaranteed performance in the multiple cores system. We tackle the problem by first presenting an optimal algorithm when the assignment of tasks to cores is given. Then we propose an approximation assignment for the general task scheduling.
AB - Energy efficiency is a crucial desideratum in the design of computer systems, from small-sized mobile devices with limited battery to large scale data centers. In such computing systems, processors and memory are considered as two major power consumers among all the system components. One recent trend to reduce power consumption is using shared memory in multi-core systems, such architecture has become ubiquitous nowadays. However, implementing the energy-efficient methods to the multi-core processor and the shared memory separately is not trivial. In this work, we consider the energy-efficient task scheduling problem, which coordinates the power consumption of both the multi-core processor and the shared memory, especially focus on the general situation in which the number of tasks is more than the number of cores. We devise an approximation algorithm with guaranteed performance in the multiple cores system. We tackle the problem by first presenting an optimal algorithm when the assignment of tasks to cores is given. Then we propose an approximation assignment for the general task scheduling.
KW - Approximation algorithm
KW - Energy
KW - Scheduling
KW - Shared memory
UR - http://www.scopus.com/inward/record.url?scp=85103317800&partnerID=8YFLogxK
U2 - 10.1016/j.tcs.2021.03.030
DO - 10.1016/j.tcs.2021.03.030
M3 - Journal Article (refereed)
SN - 0304-3975
VL - 866
SP - 160
EP - 170
JO - Theoretical Computer Science
JF - Theoretical Computer Science
ER -