A hierarchical run-time adaptive resource allocation framework for large-scale MPSoC systems

Wei Quan*, Andy D. Pimentel

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

In the embedded computer system domain, MPSoC systems have become increasingly popular due to the ever-increasing performance demands of modern embedded applications. The number of processing elements in these MPSoCs also steadily increases. Whereas current MPSoCs still contain a limited number of processing elements, future MPSoCs will feature tens up to hundreds of (heterogeneous) processing elements that are all integrated on a single chip. On these future large-scale MPSoC systems, the mapping of applications onto the hardware resources plays an important role to fully explore the parallelism of applications. In this article, a hierarchical run-time adaptive resource allocation framework which uses an intelligent task remapping approach is proposed to improve the system performance for large-scale MPSoCs.

Original languageEnglish
Pages (from-to)311-339
Number of pages29
JournalDesign Automation for Embedded Systems
Volume20
Issue number4
DOIs
Publication statusPublished - 1 Dec 2016
Externally publishedYes

Keywords

  • Embedded systems
  • KPN
  • MPSoC
  • Simulation
  • Task mapping

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