Reliability Modeling and Management of Nanophotonic On-Chip Networks

Authors:
Zheng Li;Moustafa Mohamed;Xi Chen;Eric Dudley;Ke Meng;Li Shang;Alan R. Mickelson;Russ Joseph;Manish Vachharajani;Brian Schwartz;Yihe Sun
Affiliations:
Institute of Microelectronics, Tsinghua University, Beijing, China;Department of Electrical, Computer, and Energy Engineering, University of Colorado at Boulder, Boulder, U.S.A.;Department of Electrical, Computer, and Energy Engineering, University of Colorado at Boulder, Boulder, U.S.A.;Department of Electrical, Computer, and Energy Engineering, University of Colorado at Boulder, Boulder, U.S.A.;Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, U.S.A.;Department of Electrical, Computer, and Energy Engineering, University of Colorado at Boulder, Boulder, U.S.A.;Department of Electrical, Computer, and Energy Engineering, University of Colorado at Boulder, Boulder, U.S.A.;Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, U.S.A.;Department of Electrical, Computer, and Energy Engineering, University of Colorado at Boulder, Boulder, U.S.A.;Tech-X Corporation, Boulder, U.S.A.;Institute of Microelectronics, Tsinghua University, Beijing, China
Venue:
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Year:
2012

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Abstract

While transistor performance and energy efficiency have dramatically improved in recent years, electrical interconnect improvements has failed to keep pace. Recent advances in nanophotonic fabrication have made on-chip optics an attractive alternative. However, system integration challenges remain. In particular, the parameters of on-chip nanophotonic structures are sensitive to fabrication-induced process variation and run-time spatial thermal variation across the die. This work addresses the performance and reliability challenges that arise from this sensitivity to variation. The paper first presents a model predicting the system-level effects of thermal and process variation in nanophotonic networks. It then shows how to optimize many-core system performance and reliability by using run-time techniques to compensate for the thermal and process variation effects.