Statistical timing analysis under process variations.

Statistical timing analysis under process var ...
Khaled R. Heloue, Khaled R. He ...
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December 15, 2009 | History

Statistical timing analysis under process variations.

Integrated circuit design with sub-100nm technology requires closer attention to the effect of process variations and their impact on circuit timing and timing yield. In this work, we introduce a statistical static timing analysis technique that is based on a timing yield model. This technique preserves existing methodology by selecting a "device file setting" or "virtual corner" that takes into account within-die statistical variations. If this corner is used in traditional static timing analysis, and if timing is verified, then the desired yield is met. Using process-specific "generic paths" representing critical paths in a given process technology, and requiring minimum process data, our approach can be used early in the design process, pre-placement. Within-die variations are taken care of using a simple model that assumes their positive correlation, which leads to upper and lower bounds on the timing yield. Our approach also handles both setup and hold timing constraints, and is extended as well to include the effect of statistical clock skew fluctuations resulting from process variations. The end result is a process-specific statistical static timing analysis tool that can be applied either to predict yield, or help in designing chips that meet a specific yield target.

Publish Date
Language
English
Pages
82

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Book Details


Edition Notes

Source: Masters Abstracts International, Volume: 44-02, page: 0990.

Thesis (M.A.Sc.)--University of Toronto, 2005.

Electronic version licensed for access by U. of T. users.

GERSTEIN MICROTEXT copy on microfiche (1 microfiche).

The Physical Object

Pagination
82 leaves.
Number of pages
82

Edition Identifiers

Open Library
OL19216860M
ISBN 10
049407261X

Work Identifiers

Work ID
OL12683502W

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December 15, 2009 Edited by WorkBot link works
October 21, 2008 Created by ImportBot Imported from University of Toronto MARC record