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Adaptive inter-router links for low-power, area-efficient and reliable Network-on-Chip (NoC) architectures
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Asia and South Pacific Design Automation Conference archive
Proceedings of the 2009 Asia and South Pacific Design Automation Conference table of contents
Yokohama, Japan
SESSION: On-chip communication architectures table of contents
Pages 1-6  
Year of Publication: 2009
ISBN:978-1-4244-2748-2
Authors
Avinash Karanth Kodi  Ohio University, Athens, OH
Ashwini Sarathy  University of Arizona, Tucson, AZ
Ahmed Louri  University of Arizona, Tucson, AZ
Janet Wang  University of Arizona, Tucson, AZ
Sponsors
: IEEE Circuits and Systems Society
SIGDA: ACM Special Interest Group on Design Automation
IEICE ESS : Institute of Electronics, Information and Communication Engineers - Engineering Sciences Society
IPSJ SIGSLDM : Information Processing Society of Japan - SIG System LSI Design Methodology
Publisher
IEEE Press  Piscataway, NJ, USA
Bibliometrics
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ABSTRACT

The increasing wire delay constraints in deep sub-micron VLSI designs have led to the emergence of scalable and modular Network-on-Chip (NoC) architectures. As the power consumption, area overhead and performance of the entire NoC is influenced by the router buffers, research efforts have targeted optimized router buffer design. In this paper, we propose iDEAL - inter-router, dual-function energy and area-efficient links capable of data transmission as well as data storage when required. iDEAL enables a reduction in the router buffer size by controlling the repeaters along the links to adaptively function as link buffers during congestion, thereby achieving nearly 30% savings in overall network power and 35% reduction in area with only a marginal 1 -- 3% drop in performance. In addition, aggressive speculative flow control further improves the performance of iDEAL. Moreover, the significant reduction in power consumption and area provides sufficient headroom for monitoring Negative Bias Temperature Instability (NBTI) effects in order to improve circuit reliability at reduced feature sizes.


REFERENCES

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Collaborative Colleagues:
Avinash Karanth Kodi: colleagues
Ashwini Sarathy: colleagues
Ahmed Louri: colleagues
Janet Wang: colleagues