The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
May. 08, 2012

Filed:

Dec. 24, 2008
Applicants:

Xin Wang, Pasadena, CA (US);

Charles C. Chiang, SanJose, CA (US);

Jamil Kawa, Campbell, CA (US);

Inventors:

Xin Wang, Pasadena, CA (US);

Charles C. Chiang, SanJose, CA (US);

Jamil Kawa, Campbell, CA (US);

Assignee:

Synopsys, Inc., Mountain View, CA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 17/50 (2006.01);
U.S. Cl.
CPC ...
Abstract

One embodiment of the present invention provides a system that computes dummy feature density for a CMP (Chemical-Mechanical Polishing) process. Note that the dummy feature density is used to add dummy features to a layout to reduce the post-CMP topography variation. During operation, the system discretizes a layout of an integrated circuit into a plurality of panels. Next, the system computes a feature density and a slack density for the plurality of panels. The system then computes a dummy feature density for the plurality of panels by, iteratively, (a) calculating an effective feature density for the plurality of panels using the feature density and a function that models the CMP process, (b) calculating a filling amount for a set of panels in the plurality of panels using a target feature density, the effective feature density, and the slack density, and (c) updating the feature density, the slack density, and the dummy feature density for the set of panels using the filling amount. In one embodiment of the present invention, the iterative process is guided by a variance-minimizing heuristic to efficiently select the set of panels and assign/remove dummy density to the set of panels to decrease the effective feature density variation.


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