Hardware-software collaborative thermal sensing in optical network-on-chip–based manycore systems
Continuous technology scaling in manycore systems leads to severe overheating issues. To guarantee system reliability, it is critical to accurately yet efficiently monitor runtime temperature distribution for effective chip thermal management. As an emerging communication architecture for new-genera...
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sg-ntu-dr.10356-1452952023-12-15T03:56:55Z Hardware-software collaborative thermal sensing in optical network-on-chip–based manycore systems Li, Mengquan Liu, Weichen Guan, Nan Xie, Yiyuan Ye, Yaoyao School of Computer Science and Engineering Engineering::Computer science and engineering Manyscore Systems Optical Network-On-Chip Continuous technology scaling in manycore systems leads to severe overheating issues. To guarantee system reliability, it is critical to accurately yet efficiently monitor runtime temperature distribution for effective chip thermal management. As an emerging communication architecture for new-generation manycore systems, optical network-on-chip (ONoC) satisfies the communication bandwidth and latency requirements with low power dissipation. Moreover, observation shows that it can be leveraged for runtime thermal sensing. In this article, we propose a brand-new on-chip thermal sensing approach for ONoC-based manycore systems by utilizing the intrinsic thermal sensitivity of optical devices and the inter-processor communications in ONoCs. It requires no extra hardware but utilizes existing optical devices in ONoCs and combines them with lightweight software computation in a hardware-software collaborative manner. The effectiveness of the our approach is validated both at the device level and the system level through professional photonic simulations. Evaluation results based on synthetic communication traces and realistic benchmarks show that our approach achieves an average temperature inaccuracy of only 0.6648 K compared to ground-truth values and is scalable to be applied for large-size ONoCs. Nanyang Technological University This work is partially supported by NSFC 61772094, China, and NAP M4082282 and SUG M4082087 from Nanyang Technological University, Singapore. 2020-12-16T09:12:18Z 2020-12-16T09:12:18Z 2019 Journal Article Li, M., Liu, W., Guan, N., Xie, Y., & Ye, Y. (2019). Hardware-software collaborative thermal sensing in optical network-on-chip–based manycore systems. ACM Transactions on Embedded Computing Systems, 18(6), 118:1-118:24. doi:10.1145/3362099 1539-9087 https://hdl.handle.net/10356/145295 10.1145/3362099 6 18 118:1 118:24 en ACM Transactions on Embedded Computing Systems 10.21979/N9/9EKPP2 © 2019 Association for Computing Machinery (ACM). All rights reserved. This paper was published in ACM Transactions on Embedded Computing Systems and is made available with permission of Association for Computing Machinery (ACM). application/pdf |
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Engineering::Computer science and engineering Manyscore Systems Optical Network-On-Chip Li, Mengquan Liu, Weichen Guan, Nan Xie, Yiyuan Ye, Yaoyao Hardware-software collaborative thermal sensing in optical network-on-chip–based manycore systems |
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Continuous technology scaling in manycore systems leads to severe overheating issues. To guarantee system reliability, it is critical to accurately yet efficiently monitor runtime temperature distribution for effective chip thermal management. As an emerging communication architecture for new-generation manycore systems, optical network-on-chip (ONoC) satisfies the communication bandwidth and latency requirements with low power dissipation. Moreover, observation shows that it can be leveraged for runtime thermal sensing. In this article, we propose a brand-new on-chip thermal sensing approach for ONoC-based manycore systems by utilizing the intrinsic thermal sensitivity of optical devices and the inter-processor communications in ONoCs. It requires no extra hardware but utilizes existing optical devices in ONoCs and combines them with lightweight software computation in a hardware-software collaborative manner. The effectiveness of the our approach is validated both at the device level and the system level through professional photonic simulations. Evaluation results based on synthetic communication traces and realistic benchmarks show that our approach achieves an average temperature inaccuracy of only 0.6648 K compared to ground-truth values and is scalable to be applied for large-size ONoCs. |
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School of Computer Science and Engineering |
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School of Computer Science and Engineering Li, Mengquan Liu, Weichen Guan, Nan Xie, Yiyuan Ye, Yaoyao |
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Article |
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Li, Mengquan Liu, Weichen Guan, Nan Xie, Yiyuan Ye, Yaoyao |
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Li, Mengquan |
title |
Hardware-software collaborative thermal sensing in optical network-on-chip–based manycore systems |
title_short |
Hardware-software collaborative thermal sensing in optical network-on-chip–based manycore systems |
title_full |
Hardware-software collaborative thermal sensing in optical network-on-chip–based manycore systems |
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Hardware-software collaborative thermal sensing in optical network-on-chip–based manycore systems |
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Hardware-software collaborative thermal sensing in optical network-on-chip–based manycore systems |
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hardware-software collaborative thermal sensing in optical network-on-chip–based manycore systems |
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2020 |
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https://hdl.handle.net/10356/145295 |
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1787136708464082944 |