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Minimizing energy on homogeneous processors with shared memory

  • Vincent Chau
  • , Chi Kit Ken Fong
  • , Shengxin Liu*
  • , Elaine Yinling Wang
  • , Yong Zhang
  • *Corresponding author for this work
  • Southeast University, Nanjing
  • Hong Kong Chu Hai College
  • School of Computer Science and Technology, Harbin Institute of Technology
  • Shenzhen Institute of Advanced Technology
  • Dalian University of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)160-170
Number of pages11
JournalTheoretical Computer Science
Volume866
DOIs
StatePublished - 18 Apr 2021
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Approximation algorithm
  • Energy
  • Scheduling
  • Shared memory

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