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A probabilistic analysis of pipelined global interconnect under process variations
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Source Asia and South Pacific Design Automation Conference archive
Proceedings of the 2006 Asia and South Pacific Design Automation Conference table of contents
Yokohama, Japan
SESSION: Statistical and yield analysis table of contents
Pages: 724 - 729  
Year of Publication: 2006
ISBN:0-7803-9451-8
Authors
Navneeth Kankani  The University of Arizona, Tucson, AZ
Vineet Agarwal  The University of Arizona, Tucson, AZ
Janet Wang  The 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 SIG-SLDM : Information Processing Society of Japan, SIG System LSI Design Methodology
Publisher
IEEE Press  Piscataway, NJ, USA
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ABSTRACT

The main thesis of this paper is to perform a reliability based performance analysis for a shared latch inserted global interconnect under uncertainty. We first put forward a novel delay metric named DMA for estimation of interconnect delay probability density function considering process variations. Without considerable loss in accuracy, DMA can achieve high computational efficiency even in a large space of random variables. We then propose a comprehensive probabilistic methodology for sampling transfers, on a shared latch inserted global interconnect, that highly improves the reliability of the interconnect. Improvements up to 125% are observed in the reliability when compared to deterministic sampling approach. It is also shown that dual phase clocking scheme for pipelined global interconnect is able to meet more stringent timing constraints due to its lower latency.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Collaborative Colleagues:
Navneeth Kankani: colleagues
Vineet Agarwal: colleagues
Janet Wang: colleagues