Fault-tolerant networks-on-chip routing with coarse and fine-grained look-ahead

Liu, Junxiu, Harkin, Jim, Li, Yuhua ORCID: https://orcid.org/0000-0003-2913-4478 and Maguire, Liam P. 2016. Fault-tolerant networks-on-chip routing with coarse and fine-grained look-ahead. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 35 (2) , pp. 260-273. 10.1109/TCAD.2015.2459050

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Abstract

Fault tolerance and adaptive capabilities are challenges for modern networks-on-chip (NoC) due to the increase in physical defects in advanced manufacturing processes. Two novel adaptive routing algorithms, namely coarse and fine-grained (FG) look-ahead algorithms, are proposed in this paper to enhance 2-D mesh/torus NoC system fault-tolerant capabilities. These strategies use fault flag codes from neighboring nodes to obtain the status or conditions of real-time traffic in an NoC region, then calculate the path weights and choose the route to forward packets. This approach enables the router to minimize congestion for the adjacent connected channels and also to bypass a path with faulty channels by looking ahead at distant neighboring router paths. The novelty of the proposed routing algorithms is the weighted path selection strategies, which make near-optimal routing decisions to maintain the NoC system performance under high fault rates. Results show that the proposed routing algorithms can achieve performance improvement compared to other state of the art works under various traffic loads and high fault rates. The routing algorithm with FG look-ahead capability achieves a higher throughput compared with the coarse-grained approach under complex fault patterns. The hardware area/power overheads of both routing approaches are relatively low which does not prohibit scalability for large-scale NoC implementations.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics Data Innovation Research Institute (DIURI)
Publisher:	IEEE
ISSN:	0278-0070
Date of First Compliant Deposit:	7 March 2018
Date of Acceptance:	10 July 2015
Last Modified:	06 Dec 2024 18:45
URI:	https://orca.cardiff.ac.uk/id/eprint/109719

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