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Scalable design methodology and online algorithm for TSV-cluster defects recovery in highly reliable 3D-NoC systems

Dang, Nam Khanh and Ahmed, Akram Ben and Okuyama, Yuichi and Abdallah, Abderazek Ben (2017) Scalable design methodology and online algorithm for TSV-cluster defects recovery in highly reliable 3D-NoC systems. IEEE Transactions on Emerging Topics in Computing . ISSN 2168-6750

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3D-Network-on-Chips exploit the benefits of Network-on-Chips and 3D-Integrated Circuits allowing them to be considered as one of the most advanced and auspicious communication methodologies. On the other hand, the reliability of 3D-NoCs, due to the vulnerability of Through Silicon Vias, still remains as a major problem. Most of the existing techniques rely on correcting the TSV defects by using redundancies or employing routing algorithms. Nevertheless, they are not suitable for TSV-cluster defects as they can either lead to costly area and power consumption overheads or they may result in non-minimal routing paths; thus, posing serious threats to the system reliability and overall performance. In this work, we present a scalable and low-overhead TSV usage and design method for 3D-NoC systems where the TSVs of a router can be utilized by its neighbors to deal with the cluster open defects. An adaptive online algorithm is also introduced to assist the proposed system to immediately work around the newly detected defects without using redundancies. The experimental results show the proposal ensure less than 2% of the routers being disabled, even with 50% of the TSV clusters defects. The performance evaluations also demonstrate unchanged performances for real applications under 5% of cluster defects.

Item Type: Article
Subjects: Electronics and Communications
Electronics and Communications > Electronics and Computer Engineering
Information Technology (IT)
Scopus-indexed journals
ISI-indexed journals
Divisions: Key Laboratory for Smart Integrated Systems (SISLAB)
Depositing User: Khanh N. Dang
Date Deposited: 28 Mar 2020 11:47
Last Modified: 28 Mar 2020 11:47

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