Low‐cost regional‐based congestion‐aware routing algorithm for 2D mesh NoC. (1st October 2022)

• Record Type: Journal Article
• Authors: Vazifedunn, Seena; Reza, Akram; Reshadi, Midia
• Other Names: Hsu Ching‐Hsien guestEditor.
• Is Part Of: International journal of communication systems. Volume 36:Number 1(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-10-01
• Subjects: adaptive routing -- clustering -- congestion‐aware -- network‐on‐chip -- path diversity; Telecommunication systems -- Periodicals; 621.382
• DOI: 10.1002/dac.5360
• Languages: English
• ISSNs: 1074-5351

Abstract

Summary: Given the advantages of network‐on‐chips (NoCs), they are rapidly improving to replace other forms of System‐on‐Chip (SoC) designs. Although various factors improve the NoC's performance, many challenges should be addressed when designing an NoC, one of which is congestion and its impacts on performance and efficiency. Hence, numerous routing algorithms have been proposed that contemplate the congestion influences to deal with its complexities. Nevertheless, given the significant impacts of overheads on performance and efficiency, it is crucial to consider them when designing an enhanced NoC. The proposed routing algorithm employs regional traffic information within multiple clusters and has a decent view of the traffic condition when choosing the path to the destination. Each node generates one bit of traffic information and propagates it only when the node is congested, thus preventing the information overhead. Finally, the path diversity parameter is utilized to identify the best route from the source to the destination. The proposed algorithm's results show that the number of received packets, average latency, average throughput, maximum latency, and energy consumption while using different traffic patterns are improved by 10.9%, 35.3%, 15.8%, 43%, and 15.3%, respectively. Abstract : Gathering the congestion information of the network while considering the port direction eliminates the impractical information and results in more accurate information to specify the output port. Moreover, this information can be accumulated in multiple stages in different clusters, providing a better vision of the network. Therefore, the congestion information collected coupled with the path diversity of each path can be employed to specify the best path with the least congestion and the most path diversity toward the destination.