计算机应用 ›› 2016, Vol. 36 ›› Issue (5): 1206-1211.DOI: 10.11772/j.issn.1001-9081.2016.05.1206

• 网络与通信 • 上一篇    下一篇

基于Rent规则的片上网络局部化特性流量生成算法

周玉瀚, 韩国栋, 沈剑良, 姜奎   

  1. 国家数字交换系统工程技术研究中心, 郑州 450002
  • 收稿日期:2015-11-02 修回日期:2015-12-21 出版日期:2016-05-10 发布日期:2016-05-09
  • 通讯作者: 周玉瀚
  • 作者简介:周玉瀚(1990-),男,河北廊坊人,硕士研究生,主要研究方向:层次化结构、自适应路由算法;韩国栋(1964-),男,山东烟台人,副教授,博士,主要研究方向:嵌入式系统、交换芯片设计;沈剑良(1982-),男,河南郑州人,讲师,博士,主要研究方向:层次化结构、容错路由;姜奎(1991-),男,山东潍坊人,硕士研究生,主要研究方向:FPGA可重构计算、层次化结构。
  • 基金资助:
    国家863计划项目(2014AA01A704);国家自然科学基金创新群体项目(61521003);国家自然科学基金面上项目(61572520)。

Rent's rule-based localized traffic generation algorithm for network on chip

ZHOU Yuhan, HAN Guodong, SHEN Jianliang, JIANG Kui   

  1. National Digital Switching System Engineering & Technological R & D Center, Zhengzhou Henan 450002, China
  • Received:2015-11-02 Revised:2015-12-21 Online:2016-05-10 Published:2016-05-09
  • Supported by:
    This work is partially supported by the National High Technology Research and Development Program (863 Program) of China(2014AA01A704), the Innovation Group Project of the National Natural Science Foundation of China (61521003), the Surface Program of National Natural Science Foundation of China (61572520).

摘要: 针对传统片上网络(NoC)流量模型的空间分布不符合实际应用中通信局部化特性、网络带宽开销大的问题,提出一种基于Rent规则的NoC局部化特性流量生成算法。该算法通过建立有限Mesh结构的通信概率分布模型,并利用通信概率矩阵对各节点匀速发包获得合成流量,实现通信局部化。实验模拟了不同局部化程度、不同网络尺寸的合成流量;仿真结果表明,与Random Uniform、Bit Complement、Reversal、Transpose、Butterfly等5种传统合成流量相比,该算法合成流量的局部化程特性更好、网络带宽开销更低,接近实际通信流量。

关键词: 片上网络, Rent规则, 流量生成算法, 流量模型, 通信局部化

Abstract: In view of the problems that the spatial distribution of traffic model in traditional Network on Chip (NoC) was not consistent with the communication locality in practical applications and the overhead of network bandwidth is large, a novel algorithm for flow generation with NoC localized characteristic based on Rent rule was proposed. By establishing the communication probability distribution model with finite Mesh structure, the communication probability matrix was used to send packets to each node uniformly and obtain synthesis flows, and the locality was realized. The experiment simulated on flow with different locality degree and different network size. The results show that the proposed algorithm has better performance in flow locality, which is more close to the actual flows compared with five algorithms including Random Uniform, Bit Complement, Reversal, Transpose and Butterfly. In addition, the overhead of network bandwidth is lower.

Key words: Network on Chip (NoC), Rent rule, traffic generation algorithm, flow model, communication locality

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