Abstract
The aim of this work is to report on a parallel implementation of methods for tolerance analysis in the framework of a micro-electronics design center. The methods were designed to run parallelly on different platforms which could have different computational performances. In order to distribute the computations over a network of work-stations, the algorithm was designed not by using a parallel compiler, but by using a RPC multi-server network. We have used essentially two methods. The first is the Monte Carlo approach, the second is based on an approximation by numerical integration or quadrature technique [1, 2, 3, 4], which requires far less function evaluations than the Monte Carlo method. These two approaches have been implemented in a parallel algorithm to be used on a cluster of multivendor workstations.
Chapter PDF
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
David H. Evans An Application of Numerical Integration Techniques to Statistical Tolerancing Tecnometrics Vol. 9, No. 3 August 1967.
David H. Evans An Application of Numerical Integration Techniques to Statistical Tolerancing, II-A Note on the Error Tecnometrics Vol. 13, No. 2 May 1971
David H. Evans An Application of Numerical Integration Techniques to Statistical Tolerancing, III-General Distribution Tecnometrics Vol. 13, No. 2 May 1971
David H. Evans Statistical Tolerancing: The State of the Art. Part II. Methods for Estimating Moments Journal of Quality Technology, Vol. 7, No. 1, January 1975
Lombardo, S.; Pinto, A.; Raineri, V.; Ward, P.; La Rosa, G. Privitera, G.; Campisano, S.U. Si/Ge/SUB X/Si/SUB 1-X/ Heterojunction Bipolar Transistors with the Ge/SUB X/Si/SUB 1-X/ Base Formed IEEE Electron Device Letters, Vol. 17, Issue:10, Oct. 1996
Swami D. Nigam and Joshua U. Turner Review of Statistical approaches to tolerance analysis Computer-Aided Design. Vol. 27, No 1, pp. 6–15, 1995
B. Flury, A First Course in Multivariate Statistic, Springer, 1997
John Bloomer. Power Programming with RPC O’Reilly & Associates, Inc., (1992)
Rinaudo, S.; Privitera, G.; Ferla, G.; Galluzzo, A. Small-Signal and Noise Modeling of Submicrometer Self Aligned Bipolar Transistor Radio and Wireless Conference, 1998. RAWCON 98. 1998 IEEE (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1999 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rinaudo, S., Moschella, F., Anile, M.A. (1999). Parallel Implementation in a Industrial Framework of Statistical Tolerancing Analysis in Microelectronics. In: Amestoy, P., et al. Euro-Par’99 Parallel Processing. Euro-Par 1999. Lecture Notes in Computer Science, vol 1685. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48311-X_93
Download citation
DOI: https://doi.org/10.1007/3-540-48311-X_93
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-66443-7
Online ISBN: 978-3-540-48311-3
eBook Packages: Springer Book Archive