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Accurate and analytical statistical spatial correlation modeling for VLSI DFM applications

Authors:

Jui-Hsiang Liu,

Ming-Feng Tsai,

Lumdo Chen,

Charlie Chung-Ping ChenAuthors Info & Claims

DAC '08: Proceedings of the 45th annual Design Automation Conference

Pages 694 - 697

https://doi.org/10.1145/1391469.1391648

Published: 08 June 2008 Publication History

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Abstract

With the significant advancement of statistical timing and yield analysis algorithms, there is a strong need for accurate and analytical spatial correlation models. In this paper, we propose a novel spatial correlation modeling method not only can capture the general spatial correlation relationship but also can generate highly accurate and analytical models. Our method, based on Singular Value Decomposition (SVD), can generate sequences of polynomial weighted by the singular values. Experimental results from foundry measurement data show that our proposed approach is 5X accuracy improvement over several distance based spatial correlation modeling methods.

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Cited By

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Zhang JGupta S(2014)SRAM Array Yield Estimation under Spatially-Correlated Process VariationProceedings of the 2014 IEEE 23rd Asian Test Symposium10.1109/ATS.2014.43(149-155)Online publication date: 16-Nov-2014
https://dl.acm.org/doi/10.1109/ATS.2014.43
Ghavami BRaji MPedram HTahoori M(2013)Design and Analysis of a Robust Carbon Nanotube-Based Asynchronous Primitive CircuitACM Journal on Emerging Technologies in Computing Systems10.1145/2422094.24220989:1(1-27)Online publication date: 1-Feb-2013
https://dl.acm.org/doi/10.1145/2422094.2422098
Dyer EMajzoobi MKoushanfar FStok LDutt NHassoun S(2011)Hybrid modeling of non-stationary process variationsProceedings of the 48th Design Automation Conference10.1145/2024724.2024768(194-199)Online publication date: 5-Jun-2011
https://dl.acm.org/doi/10.1145/2024724.2024768
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Index Terms

Accurate and analytical statistical spatial correlation modeling for VLSI DFM applications
1. Applied computing
  1. Physical sciences and engineering
    1. Engineering

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Published In

DAC '08: Proceedings of the 45th annual Design Automation Conference

June 2008

993 pages

ISBN:9781605581156

DOI:10.1145/1391469

General Chair:
Limor Fix
Intel Research Pittsburgh, Pittsburgh, PA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 08 June 2008

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DAC '08: The 45th Annual Design Automation Conference 2008

June 8 - 13, 2008

California, Anaheim

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Overall Acceptance Rate 1,770 of 5,499 submissions, 32%

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Zhang JGupta S(2014)SRAM Array Yield Estimation under Spatially-Correlated Process VariationProceedings of the 2014 IEEE 23rd Asian Test Symposium10.1109/ATS.2014.43(149-155)Online publication date: 16-Nov-2014
https://dl.acm.org/doi/10.1109/ATS.2014.43
Ghavami BRaji MPedram HTahoori M(2013)Design and Analysis of a Robust Carbon Nanotube-Based Asynchronous Primitive CircuitACM Journal on Emerging Technologies in Computing Systems10.1145/2422094.24220989:1(1-27)Online publication date: 1-Feb-2013
https://dl.acm.org/doi/10.1145/2422094.2422098
Dyer EMajzoobi MKoushanfar FStok LDutt NHassoun S(2011)Hybrid modeling of non-stationary process variationsProceedings of the 48th Design Automation Conference10.1145/2024724.2024768(194-199)Online publication date: 5-Jun-2011
https://dl.acm.org/doi/10.1145/2024724.2024768
Cheng LGupta PHe LLin Y(2010)On confidence in characterization and application of variation modelsProceedings of the 2010 Asia and South Pacific Design Automation Conference10.5555/1899721.1899894(751-756)Online publication date: 18-Jan-2010
https://dl.acm.org/doi/10.5555/1899721.1899894
Liu JTsai MChen LChen C(2010)Accurate and analytical statistical spatial correlation modeling based on singular value decomposition for VLSI DFM applicationsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2010.204289029:4(580-589)Online publication date: 1-Apr-2010
https://dl.acm.org/doi/10.1109/TCAD.2010.2042890
Whi SSu BLee YPan C(2010)Spatial correlation extraction with a limited amount of measurement data2nd Asia Symposium on Quality Electronic Design (ASQED)10.1109/ASQED.2010.5548251(248-254)Online publication date: Aug-2010
https://doi.org/10.1109/ASQED.2010.5548251
Cheng LGupta PHe L(2010)On confidence in characterization and application of variation models2010 15th Asia and South Pacific Design Automation Conference (ASP-DAC)10.1109/ASPDAC.2010.5419790(751-756)Online publication date: Jan-2010
https://doi.org/10.1109/ASPDAC.2010.5419790
Cheng LGupta PSpanos CQian KHe L(2009)Physically justifiable die-level modeling of spatial variation in view of systematic across wafer variabilityProceedings of the 46th Annual Design Automation Conference10.1145/1629911.1629945(104-109)Online publication date: 26-Jul-2009
https://dl.acm.org/doi/10.1145/1629911.1629945

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Accurate and analytical statistical spatial correlation modeling based on singular value decomposition for VLSI DFM applications

Spatial entropy-based clustering for mining data with spatial correlation

Robust extraction of spatial correlation

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