Configuration Reusing in On-Line Task Scheduling for Reconfigurable Computing Systems

Reconfigurable computing systems can be reconfigured at runtime and support partial reconfigurability which makes us able to execute tasks in a true multitasking manner. To manage such systems at runtime, a reconfigurable operating system is needed. The main part of this operating system is resource...

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Bibliographic Details
Published in:Journal of computer science and technology 2011-05, Vol.26 (3), p.463-473
Main Authors: Mansub Bassiri, Maisam, Shahriar Shahhoseini, Hadi
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Computation
Computer Science
Configurations
Data Structures and Information Theory
Design
Information Systems Applications (incl.Internet)
International
Multitasking
On-line systems
Operating systems
Placement
Reconfiguration
Regular Paper
Resource management
Run time (computers)
Scheduling
Software Engineering
Studies
Task scheduling
Tasks
Theory of Computation
World Wide Web
任务调度
可重构计算系统
应用程序
执行时间
操作系统
调度算法
资源管理
配置
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Summary:Reconfigurable computing systems can be reconfigured at runtime and support partial reconfigurability which makes us able to execute tasks in a true multitasking manner. To manage such systems at runtime, a reconfigurable operating system is needed. The main part of this operating system is resource management unit which performs on-line scheduling and placement of hardware tasks at runtime. Reconfiguration overhead is an important obstacle that limits the performance of on-line scheduling algorithms in reconfigurable computing systems and increases the overall execution time. Configuration reusing （task reusing） can decrease reconfiguration overhead considerably, particularly in periodic applications or the applications in which the probability of tasks recurrence is high. In this paper, we present a technique called reusing-based scheduling （RBS）, for on-line scheduling and placement in which configuration reusing is considered as a main characteristic in order to reduce reconfiguration overhead and decrease total execution time of the tasks. Several experiments have been conducted on the proposed algorithm. Obtained results show considerable improvement in overall execution time of the tasks.
ISSN:1000-9000
1860-4749
DOI:10.1007/s11390-011-1147-2