Automation of optimal metal density filling for deep sub micron technology designs

The locally adopted technique of Chemical-mechanical polishing (CMP) along with various other steps taken in design for manufacturing procedures employed for the fabrication of nano ICs, results in adverse impact on interconnecting wire parameters as well as device features. In order to enhance the...

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Bibliographic Details
Published inMaterials today : proceedings Vol. 74; pp. 207 - 212
Main Authors Khursheed, Afreen, Khare, Kavita, Haque, Fozia Z.
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 2023
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ISSN2214-7853
2214-7853
DOI10.1016/j.matpr.2022.08.050

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Summary:The locally adopted technique of Chemical-mechanical polishing (CMP) along with various other steps taken in design for manufacturing procedures employed for the fabrication of nano ICs, results in adverse impact on interconnecting wire parameters as well as device features. In order to enhance the manufacturability yield, performance predictability and also for getting the uniform chip layout a propos to prescribed density criteria; dummy fill insertion into layout is a mandatory step of contemporary manufacturing process. Full chip dummy fill is an iterative process which is time consuming and exponentially increases size of GDS. This paper discusses an algorithm which suggests a more sophisticated dummy-fill technique such that it optimizes the total number of metal fill by keeping a tradeoff between the fill requirement and need of design. The proposed algorithm will iterate automatically till a target density is reached with marginal increase to the size of the GDS. MENTOR GRAPHICS SVRF Calibre commands are used to develop the algorithm. PERL scripting is used to run the job automatically. The simulated experimental results points out that the proposed method renders a more balanced metal density distribution while using lesser dummy metal features. Besides this it shows an acceptable timing overhead.
ISSN:2214-7853
2214-7853
DOI:10.1016/j.matpr.2022.08.050