Techniques of optical proximity correction using GPU
First Claim
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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.
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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.
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Citations
7 Claims
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1. A method comprising:
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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. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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Specification