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  5. Analytical Approach to Statistical Logic Cell Delay Analysis and its Extension to a Timing Graph
 
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Analytical Approach to Statistical Logic Cell Delay Analysis and its Extension to a Timing Graph

Author(s)
Mishagli, Dimitri  
Blokhina, Elena  
Brazil, Thomas J.  
Hollands, Steve  
Uri
http://hdl.handle.net/10197/9831
Date Issued
2018-03-16
Date Available
2019-04-08T09:11:15Z
Abstract
In this paper we propose a new methodology to determine the delay of combinational circuits within the framework of statistical static timing analysis (SSTA). The methodology is based on exact analytical solutions for the probability density functions of logic gate delays. Assuming initial delays of the input arrival times and operation time of gates to be normally distributed, the non-Gaussian distribution of the resulting delay of a gate is obtained, as well as its first two moments. This allowed us to propose a novel closed-loop algorithm for the calculation of delay propagation in combinational circuits. Possible extensions and future steps are discussed.
Sponsorship
European Commission - European Regional Development Fund
Science Foundation Ireland
Other Sponsorship
Synopsys, Ireland
Type of Material
Conference Publication
Publisher
ACM
Subjects

Combinational circuit...

Statistical static ti...

Digital integrated ci...

Gaussian distribution...

Web versions
http://www.tauworkshop.com/2018/
Language
English
Status of Item
Peer reviewed
Journal
ACM International Workshop on Timing Issues in the Specification and Synthesis of Digital Systems (TAU 2018), in Monterey, California, US
Conference Details
The 2018 ACM International Workshop on Timing Issues in the Specification and Synthesis of Digital Systems, Monterey, California, 15-16 March 2018
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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mishagli_tau18.pdf

Size

398.29 KB

Format

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Checksum (MD5)

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Owning collection
Electrical and Electronic Engineering Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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