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STTAR: A Traffic- and Thermal-Aware Adaptive Routing for 3D Network-on-Chip Systems

Juan Fang1,*, Yunfei Mao1, Min Cai1, Li’ang Zhao1, Huijie Chen1, Wei Xiang2,3

1 Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
2 La Trobe University, Melbourne, VIC 3086, Australia
3 James Cook University, Cains, QLD 4878, Australia

* Corresponding Author: Juan Fang. Email: email

Computers, Materials & Continua 2022, 72(3), 5531-5545. https://doi.org/10.32604/cmc.2022.027177

Abstract

Since the three-dimensional Network on Chip (3D NoC) uses through-silicon via technology to connect the chips, each silicon layer is conducted through heterogeneous thermal, and 3D NoC system suffers from thermal problems. To alleviate the seriousness of the thermal problem, the distribution of data packets usually relies on traffic information or historical temperature information. However, thermal problems in 3D NoC cannot be solved only based on traffic or temperature information. Therefore, we propose a Score-Based Traffic- and Thermal-Aware Adaptive Routing (STTAR) that applies traffic load and temperature information to routing. First, the STTAR dynamically adjusts the input and output buffer lengths of each router with traffic load information to limit routing resources in overheated areas and control the rate of temperature rise. Second, STTAR adopts a scoring strategy based on temperature and the number of free slots in the buffer to avoid data packets being transmitted to high-temperature areas and congested areas and to improve the rationality of selecting routing output nodes. In our experiments, the proposed scoring Score-Based Traffic- and Thermal-Aware Adaptive Routing (STTAR) scheme can increase the throughput by about 14.98% to 47.90% and reduce the delay by about 10.80% to 35.36% compared with the previous works.

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Cite This Article

J. Fang, Y. Mao, M. Cai, L. Zhao, H. Chen et al., "Sttar: a traffic- and thermal-aware adaptive routing for 3d network-on-chip systems," Computers, Materials & Continua, vol. 72, no.3, pp. 5531–5545, 2022.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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