Design of a Router for Network on Chip Based on System Level Based on Adaptive Routing Algorithm

WAN Yu-peng; WU Ning

Chinese

您当前的位置：

首页 >

文章列表页 >

Design of a Router for Network on Chip Based on System Level Based on Adaptive Routing Algorithm

更新时间：2026-09-04

- Design of a Router for Network on Chip Based on System Level Based on Adaptive Routing Algorithm
- Vol. 27, Issue 5, Pages: 42-45(2010)
- 作者机构：
  
  南京航空航天大学信息科学与技术学院,江苏,南京,210016
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2010
- 稿件说明：
移动端阅览
万玉鹏, 吴宁. 基于自适应算法的NoC路由单元的系统级设计[J]. 微电子学与计算机, 2010, 27(5): 42-45,49.

WAN Yu-peng, WU Ning. Design of a Router for Network on Chip Based on System Level Based on Adaptive Routing Algorithm[J]. 2010, 27(5): 42-45.
万玉鹏, 吴宁. 基于自适应算法的NoC路由单元的系统级设计[J]. 微电子学与计算机, 2010, 27(5): 42-45,49. DOI：

WAN Yu-peng, WU Ning. Design of a Router for Network on Chip Based on System Level Based on Adaptive Routing Algorithm[J]. 2010, 27(5): 42-45. DOI：

摘要

针对片上网络(NoC)中采用确定性路由算法的路由器的缺点

提出了一种NoC路由单元的系统级模型.该模型采用了自适应路由算法

取代了2DMesh拓扑结构中常用的XY维序路由算法

可以根据当前的通道使用状态动态地分配传输路径

并优先保证GS包的发送.在SystemC平台完成了模型的设计与验证

结果表明

所设计的基于自适应算法的NoC路由单元能够在多包并发时避免路径冲突

提高了网络的并行发送能力

并支持GS服务.

Abstract

For disadvantages of the router which adopts determined routing algorithm

a system-level model of NoC router is proposed. This router adopts adaptive routing algorithm instead of XY ordered routing algorithm which is widely used in 2D Mesh topology. The router chooses the output ports for data transmitting by the states of current output ports and GS packets have higher priority. The router is modeled on the SystemC platform. Verification results show that the designed of router improve the parallel transmitting ability and support guaranteed service.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Implementation and verification of a dual-chain power gating strategy for low power design

A feature-oriented context understanding and slice analysis network for tuberculosis detection

Aerial vehicle detection algorithm based on multi-scale fusion and small-object enhancement

Research on the design of blockchain-based AI-generated content traceability framework

Steganography model guided by attention mechanism and improved dense convolution

Related Author

No data

Related Institution

No data

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰