NDLI: Interconnect modeling for improved system-level design optimization

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Interconnect modeling for improved system-level design optimization

Content Provider	ACM Digital Library
Author	Samadi, Kambiz Carloni, Luca Pinto, Alessandro Muddu, Swamy Kahng, Andrew B. Sharma, Puneet
Abstract	Accurate modeling of delay, power, and area of interconnections early in the design phase is crucial for effective system-level optimization. Models presently used in system-level optimizations, such as network-on-chip (NoC) synthesis, are inaccurate in the presence of deep-submicron effects. In this paper, we propose new, highly accurate models for delay and power in buffered interconnects; these models are usable by system-level designers for existing and future technologies. We present a general and transferable methodology to construct our models from a wide variety of reliable sources (Liberty, LEF/ITF, ITRS, PTM, etc.). The modeling infrastructure, and a number of characterized technologies, are available as open source. Our models comprehend key interconnect circuit and layout design styles, and a power-efficient buffering technique that overcomes unrealities of previous delay-driven buffering techniques. We show that our models are significantly more accurate than previous models for global and intermediate buffered interconnects in 90nm and 65nm foundry processes - essentially matching signoff analyses. We also integrate our models in the COSI-OCC synthesis tool and show that the more accurate modeling significantly affects optimal/achievable architectures that are synthesized by the tool. The increased accuracy provided by our models enables system-level designers to obtain better assessments of the achievable performance/power/area tradeoffs for (communication-centric aspects of) system design, with negligible setup and overhead burdens.
Starting Page	258
Ending Page	264
Page Count	7
File Format	PDF
ISBN	9781424419227
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2008-01-21
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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