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GTX: the MARCO GSRC technology extrapolation system
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Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 37th Annual Design Automation Conference table of contents
Los Angeles, California, United States
Pages: 693 - 698  
Year of Publication: 2000
ISBN:1-58113-187-9
Authors
Andrew E. Caldwell  UCLA CS Dept.,
Yu Cao  UC Berkeley EECS Dept.,
Andrew B. Kahng  UCLA CS Dept.,
Farinaz Koushanfar  UCLA CS Dept.,
Hua Lu  UCLA EE Dept.,
Igor L. Markov  UCLA CS Dept.,
Michael Oliver  UCLA CS Dept.,
Dirk Stroobandt  Ghent University ELIS Dept., Belgium
Dennis Sylvester  Synopsys, Inc.,
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
EDAC : Electronic Design Automation Consortium
IEEE-CAS : Circuits & Systems
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 4,   Downloads (12 Months): 21,   Citation Count: 16
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ABSTRACT

Technology extrapolation — the calibration and prediction of achievable design in future technology generations — drives the evolution of VLSI system architectures, design methodologies, and design tools. This paper describes initial experiences with development and use of GTX, the MARCO GSRC Technology Extrapolation system. GTX provides a robust, portable framework for interactive specification and comparison of modeling choices, e.g., for predicting system cycle time, die size and power dissipation. We use GTX to reveal surprising levels of uncertainty (modeling and parameter sensitivity) in widely-cited cycle-time models that drive recent roadmaps. We also describe new SOI and bulk device models that have been developed for GTX, as well as studies of power dissipation and delay uncertainty under various implementation assumptions for global interconnects.


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.

 
1
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3
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4
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8
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9
 
10
MARCO GSRC Technology Extrapolation Initiative, http ://vlsicad. cs. ucla. edu/GSRC/GTX/
 
11
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20
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CITED BY  16

Collaborative Colleagues:
Andrew E. Caldwell: colleagues
Yu Cao: colleagues
Andrew B. Kahng: colleagues
Farinaz Koushanfar: colleagues
Hua Lu: colleagues
Igor L. Markov: colleagues
Michael Oliver: colleagues
Dirk Stroobandt: colleagues
Dennis Sylvester: colleagues