Techniques of optical proximity correction using GPU

• US 8,938,696 B1
• Filed: 07/15/2013
• Issued: 01/20/2015
• Est. Priority Date: 07/08/2010
• Status: Active Grant

• Current Assignee: D2S, Inc.
• Original Assignee: D2S, Inc.
• Inventors: Torunoglu, Ilhami H., Karakas, Ahmet, Elsen, Erich E.
• Primary Examiner(s): Do, Thuan
• Assistant Examiner(s): Alam, Mohammed
• Application Number:
  US13/942,395
• Time in Patent Office: 554 Days
• Field of Search: 716/53
• US Class Current: 716/53
• CPC Class Codes: G03F 7/70441 Optical proximity correction [OPC]
• CPC Class Codes: G06F 2119/18 Manufacturability analysis or optimisation for manufacturability
• CPC Class Codes: G06F 30/00 Computer-aided design [CAD]
• CPC Class Codes: G06F 30/39 Circuit design at the physical level physical level design for reconfigurable circuits G06F30/347
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

Computationally intensive electronic design automation operations are accelerated with algorithms utilizing one or more graphics processing units. The optical proximity correction (OPC) process calculates, improves, and optimizes one or more features on an exposure mask (used in semiconductor or other processing) so that a resulting structure realized on an integrated circuit or chip meets desired design and performance requirements. When a chip has billions of transistors or more, each with many fine structures, the computational requirements for OPC can be very large. This processing can be accelerated using one or more graphics processing units.

Claims

1. A method comprising:

creating an initial fragmentation of a mask data pattern, wherein the initial fragmentation comprises a plurality of fragments, and wherein each fragment in the plurality of fragments comprises a length and a position;

calculating an objective function at a sample point in each fragment in the plurality of fragments, wherein the calculating is performed using a computer;

moving a fragment in the plurality of fragments, based on the objective function calculation;

inserting a new fragment between a first pair of consecutive fragments in the plurality of fragments when the movement of the first pair of fragments is larger than a pre-determined maximum value;

merging a second pair of consecutive fragments in the plurality of fragments when the movement of the second pair of fragments is smaller than a pre-determined minimum value; and

iteratively performing the calculating, moving, inserting, and merging until movement of each pair of fragments is below the pre-determined maximum value and above the pre-determined minimum value.

2. The method of claim 1 wherein the initial fragmentation comprises:

calculating the objective function along an edge of the mask data pattern;

calculating a slope of the calculated objective function;

determining a plurality of inflection points, wherein an inflection point occurs wherever the slope of the objective function changes sign; and

inserting a fragment boundary between each pair of consecutive inflection points.

3. The method of claim 1 wherein the creating is distributed over a plurality of computers.

4. The method of claim 1 wherein at least one of calculating, moving, inserting and merging is distributed over a plurality of computers.

5. The method of claim 4 wherein at least one of calculating, moving, inserting and merging are performed using a graphical processing unit (GPU).

6. The method of claim 1 wherein the objective function comprises edge placement error (EPE).

7. The method of claim 1 wherein the sample point is selected to be at a location where a slope of the objective function is zero.