Real-time task scheduling on island-based multi-core platforms

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

12 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Article number6714441
Pages (from-to)538-550
Journal / PublicationIEEE Transactions on Parallel and Distributed Systems
Volume26
Issue number2
Online published15 Jan 2014
Publication statusPublished - Feb 2015
Externally publishedYes

Abstract

With the increasing number of cores in a computing system, how to coordinate the computing units and heterogeneous memory resources has soon become extremely critical for real-time systems. This paper explores the joint considerations of memory management and real-time task scheduling over island-based multi-core architecture, where the local memory module of an island offers shorter access time than the global memory module does. The objective of this work is to minimize the number of needed islands to successfully schedule real-time tasks. When the required amount of the local memory space is specified for each task, a scheduling algorithm is proposed to provide an asymptotic 29/9 -Approximation bound. When there is flexibility in determining the needed local memory space for each task, we propose an algorithm with an asymptotic 4 -Approximation bound to jointly manage memory resources and allocate computing cores. In addition to the worst-case approximation analysis, the proposed algorithms are also evaluated with 82 real-life benchmarks with the support of a worst-case execution time analyzer. Moreover, extensive evaluations are conducted to show the capability of the proposed approaches when being used with various computing cores and memory resources.

Research Area(s)

  • heterogeneous memory, memory allocation, multi-core architecture, Real-time system, task scheduling

Citation Format(s)

Real-time task scheduling on island-based multi-core platforms. / Chang, Che-Wei; Chen, Jian-Jia; Kuo, Tei-Wei; Falk, Heiko.

In: IEEE Transactions on Parallel and Distributed Systems, Vol. 26, No. 2, 6714441, 02.2015, p. 538-550.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review