Efficient vlsi yield prediction with consideration of partial correlations

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dc.contributor.advisor Hu , Jiang en_US
dc.contributor.committeeMember Bhattacharyya , Shankar en_US
dc.creator Varadan , Sridhar en_US
dc.date.accessioned 2010 -01 -15T00 :06 :29Z
dc.date.accessioned 2014 -02 -19T19 :31 :43Z
dc.date.available 2010 -01 -15T00 :06 :29Z
dc.date.available 2014 -02 -19T19 :31 :43Z
dc.date.created 2007 -12 en_US
dc.date.issued 2009 -05 -15 en_US
dc.identifier.uri http : / /hdl .handle .net /1969 .1 /ETD -TAMU -2503
dc.description.abstract With the emergence of the deep submicron era , process variations have gained importance in issues related to chip design . The impact of process variations is measured using manufacturing /parametric yield . In order to get an accurate estimate of yield , the parameters considered need to be monitored at a large number of locations . Nowadays , intra -die variations are an integral part of the overall process uctuations . This leads to the difficult case where yield prediction has to be done while considering independent and partially correlated variations . The presence of partial correlations adds to the existing trouble caused by the volume of variables . This thesis proposes two techniques for reducing the number of variables and hence the complexity of the yield computation problem namely - Principal Component Analysis (PCA ) and Hierarchical Adaptive Quadrisection (HAQ ) . Systematic process variations are also included in our yield model . The biggest plus in these two methods is reducing the size of the yield prediction problem (thus making it less time complex ) without affecting the accuracy in yield . The efficiency of these two approaches is measured by comparing with the results obtained from Monte Carlo simulations . Compared to previous work , the PCA based method can reduce the error in yield estimation from 17 .1 % - 21 .1 % to 1 .3 % - 2 .8 % with 4 .6x speedup . The HAQ technique can reduce the error to 4 .1 % - 5 .6 % with 6x - 9 .4x speedup . en_US
dc.format.medium electronic en_US
dc.format.mimetype application /pdf en_US
dc.language.iso en _US en_US
dc.subject Yield en_US
dc.title Efficient vlsi yield prediction with consideration of partial correlations en_US
dc.type Book en
dc.type.genre Electronic Thesis en_US
dc.type.material text en_US
dc.format.digitalOrigin born digital en_US

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Efficient vlsi yield prediction with consideration of partial correlations. Available electronically from http : / /hdl .handle .net /1969 .1 /ETD -TAMU -2503 .

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