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Please use this identifier to cite or link to this item: http://10.10.120.238:8080/xmlui/handle/123456789/941
Title: Adaptive distribution of control messages for improving bandwidth utilization in multiple NoC
Authors: Yadav S.
Laxmi V.
Kapoor H.
Gaur M.S.
Kumar A.
Keywords: Adaptive traffic distribution
Control messages
Data messages
Multiple networks-on-chip
Static traffic distribution
Issue Date: 2023
Publisher: Springer
Abstract: The advancement of networks-on-chip (NoCs) is noteworthy as the number of cores increases. The bandwidth demand has grown steadily as network traffic has increased owing to high-workload applications. The NoC traffic broadly divided into control messages and data messages in which data messages are bigger in size. As NoC channel bandwidth sets in proportion to the size of the data messages, the NoC bandwidth remains underutilized during control messages transmission. This adversely affects NoC power and performance efficiency. In modern NoC architectures, multiple NoC is popular to efficiently utilize NoC bandwidth because it offers more than one physical channel for traffic communication. The conventional multiple-NoC architectures statically distribute traffic between the NoCs. This significantly affects the power-performance metrics. We have observed up to fivefold variation in energy efficiency during the analysis of static traffic distribution for multiple NoC. In this paper, we propose an adaptive distribution of control messages for multiple NoC to improve bandwidth utilization. The traversal of control messages switch between the NoC networks according to the runtime utilization of networks. The proposed adaptive distribution of control messages improves energy efficiency up to 72.7 % and 66.9 % on average over single-NoC and static traffic distribution in multiple NoC, respectively. The link utilization also improves by 1.37 × and 40 % on average over single-NoC and conventional static traffic distribution, respectively. Thus, the proposed adaptive distribution overcomes the implications of static traffic distribution. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
URI: https://dx.doi.org/10.1007/s11227-023-05208-0
http://localhost:8080/xmlui/handle/123456789/941
ISSN: 0920-8542
Appears in Collections:Journal Article

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