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Interconnect prediction for programmable logic devices
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Source International Workshop on System-Level Interconnect Prediction archive
Proceedings of the 2001 international workshop on System-level interconnect prediction table of contents
Sonoma, California, United States
Pages: 125 - 131  
Year of Publication: 2001
ISBN:1-58113-315-4
Author
Michael Hutton  Altera Corporation, San Jose, CA
Sponsor
SIGDA: ACM Special Interest Group on Design Automation
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 2,   Downloads (12 Months): 12,   Citation Count: 5
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ABSTRACT

Classical interconnect prediction would seem to be a perfect fit for the design of programmable logic architectures (PLDs). Yet theoretical models such as those based on Rent's Rule are usually only used for rough estimates in the early stages of an architecture development. In practice, empirical methods (evaluation via many test designs) dominate the evaluation of fitting and performance for PLD architectures.The primary reasons for this gap between theory and practice are that the models are difficult to extend to fixed architectures with hierarchy and heterogeneous resources and that many of the cost metrics are different between gate-arrays and PLDs.In this paper and the accompanying talk I will survey some of the issues with line-count estimation for the design of PLDs. I will point out some of the inherent differences between the way interconnect is used in PLDs and gate arrays which lead to new opportunities in the development of the theory. Some previous results will show how interconnect is typically researched in the PLD community. For an idealized PLD architecture, I will attempt to define a simple line-count estimation model using the classical theory and compare it to results in practice. I will also present some empirical and anecdotal data useful for understanding the issues and pitfalls involved in architecture evaluation.The primary goal of this work is to motivate new directions in the theory of interconnect prediction and interconnect prediction specifically for PLDs.


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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