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基于预配置和配置重用的粗粒度动态可重构系统任务调度技术

戴紫彬 曲彤洲

戴紫彬, 曲彤洲. 基于预配置和配置重用的粗粒度动态可重构系统任务调度技术[J]. 电子与信息学报, 2019, 41(6): 1458-1465. doi: 10.11999/JEIT180831
引用本文: 戴紫彬, 曲彤洲. 基于预配置和配置重用的粗粒度动态可重构系统任务调度技术[J]. 电子与信息学报, 2019, 41(6): 1458-1465. doi: 10.11999/JEIT180831
Zibin DAI, Tongzhou QU. Task Scheduling Technology for Coarse-grained Dynamic Reconfigurable System Based on Configuration Prefetching and Reuse[J]. Journal of Electronics & Information Technology, 2019, 41(6): 1458-1465. doi: 10.11999/JEIT180831
Citation: Zibin DAI, Tongzhou QU. Task Scheduling Technology for Coarse-grained Dynamic Reconfigurable System Based on Configuration Prefetching and Reuse[J]. Journal of Electronics & Information Technology, 2019, 41(6): 1458-1465. doi: 10.11999/JEIT180831

基于预配置和配置重用的粗粒度动态可重构系统任务调度技术

doi: 10.11999/JEIT180831
详细信息
    作者简介:

    戴紫彬:男,1966年生,教授,博士生导师,研究方向为可重构计算与安全专用芯片设计

    曲彤洲:男,1994年生,硕士生,研究方向为可重构计算与信息安全

    通讯作者:

    曲彤洲 qutongzhou@outlook.com

  • 中图分类号: TP309.7; TN492

Task Scheduling Technology for Coarse-grained Dynamic Reconfigurable System Based on Configuration Prefetching and Reuse

  • 摘要: 配置时间过长是制约可重构系统整体性能提升的重要因素,而合理的任务调度技术可有效降低系统配置时间。该文针对粗粒度动态可重构系统(CGDRS)和具有数据依赖关系的流应用,提出了一种3维任务调度模型。首先基于该模型,设计了一种基于预配置策略的任务调度算法(CPSA);然后根据任务间的配置重用性,提出了间隔配置重用与连续配置重用策略,并据此对CPSA算法进行改进。实验结果证明,CPSA算法能够有效解决调度死锁问题、降低流应用执行时间并提高调度成功率。与其它调度算法相比,对流应用执行时间的平均优化比例达到6.13%~19.53%。
  • 图  1  CGDRS整体结构示意

    图  2  CGDRS任务配置与计算过程

    图  3  预配置机制对任务执行时序的影响

    图  4  CPSA算法下任务在各个队列中的转换示意图

    图  5  可重用配置信息示意

    图  6  改进后的CPSA调度算法流程图

    图  7  调度成功率对比图

    图  8  CPSA调度算法与其它算法调度结果对比

    表  1  CPSA调度算法相较于其它调度算法对应用执行时间的优化比例(%)

    应用O(Pre)O(CCF)O(RCP)O(BULB)
    J20&L512.304.386.5019.79
    J20&L1010.325.878.0615.73
    J20&L159.667.3311.4818.18
    J30&L512.065.026.3515.28
    J40&L1520.758.6316.1020.90
    J30&L108.575.5913.8118.26
    J30&L1516.957.5511.9321.63
    J40&L521.575.1117.2826.02
    J40&L1010.895.6815.7219.97
    平均值13.676.1311.9119.53
    下载: 导出CSV
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出版历程
  • 收稿日期:  2018-08-24
  • 修回日期:  2019-02-02
  • 网络出版日期:  2019-02-26
  • 刊出日期:  2019-06-01

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