# Double Patterning Layout Decomposition for Simultaneous Conflict and Stitch Minimization - PowerPoint PPT Presentation

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Double Patterning Layout Decomposition for Simultaneous Conflict and Stitch Minimization. K.Yuan, J.Yang and D.Pan ECE Dept. Univ. of Texas at Austin. ISPD 2009. Outline. Introduction Preliminaries and Motivation Problem Formulation Algorithm Basic ILP Formulation Speed-Up Techniques

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Double Patterning Layout Decomposition for Simultaneous Conflict and Stitch Minimization

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## Double Patterning Layout Decomposition for Simultaneous Conflict and Stitch Minimization

K.Yuan, J.Yang and D.Pan

ECE Dept. Univ. of Texas at Austin

ISPD 2009

### Outline

• Introduction

• Preliminaries and Motivation

• Problem Formulation

• Algorithm

• Basic ILP Formulation

• Speed-Up Techniques

• Solution Mergence

• Experimental Result

• Conclusion

### Introduction

• As the minimum feature size decreases, semiconductor industry is facing the limitation of patterning sub-32nm.

• Double patterning lithography (DPL) is considered as a most likely solution for 32nm/22nm technology.

• In DPL, a single layout is decomposed into two masks and manufactured through two exposure steps.

### Introduction

• As a benefit, the pitch size is doubled, which enhances the resolution.

### Introduction

• Decomposition is a process that assigns opposite colors if the distance between two features is less than the minimum coloring spacing.

• A feature may be split into two parts and colored differently to resolve the conflicts, which generates stitches.

• Stitches cause yield loss due to overlay error and they also increase manufacturing cost.

### Preliminaries and Motivation

• Layout Decomposition Considerations

• Coloring Conflict: If the distance between two separate features in the same mask is less than mincs, they should be assigned to different colors. Otherwise, there will be a coloring conflict.

### Preliminaries and Motivation

• Layout Decomposition Considerations

• Splitting Stitch: The stitch exists when two touched features are assigned to different masks.

### Preliminaries and Motivation

• Simultaneous Optimization

### Preliminaries and Motivation

• Simultaneous Optimization

### Problem Formulation

• Different stitch candidates can lead to different solution qualities.

### Problem Formulation

• The difficulty of predicting where the splitting is needed.

### Problem Formulation

• The difficulty of predicting where the splitting is needed.

### Problem Formulation

• Grid Layout Model

• Map the whole layout into grids.

• Each grid is either empty or fully occupied by the pattern.

• Each occupied grid will be assigned one color.

• Minimum coloring spacing mincs is taken as two-grid size.

### Problem Formulation

• Terms

• Occupied grid (OG): The grid filled by the layout.

• Blocking path (BP): Given two OG1 and OG2, a BP is a path when

• It is fully composed of the OGs and connects OG1 and OG2.

• OG1 and OG2 are touching its two ending grids, respectively.

• This path is within the bounding box of OG1 and OG2.

### Problem Formulation

• Terms

• Potential conflict grid pair (PCGP) and potential stitch grid pair (PSGP): Given two OG1 and OG2,

• If the distance between OG1 and OG2 is less than mincs and the two grids are not touching, they form a PCGP.

• If OG1 and OG2 are touching, they form a PSGP.

• Stitch grid pair (SGP): If the grids of a PSGP are assigned different colors, it is a SGP.

• Conflict grid pair (CGP): If a PCGP is in the identical color, and there is no BP connecting them in the same mask, it is a CGP.

### Problem Formulation

• Problem formulation:

• Given a grid layout, color it into two parts (GRAY and BLACK). The primary objective is to minimize the number of CGPs and the second objective is to minimize the number of SGPs.

### Algorithm

• The overall layout decomposition flow.

### Algorithm

• Basic ILP Formulation

### Algorithm

• Basic ILP Formulation

• (1) is to minimize the weighted summation of SGPs and CGPs.

• (2) and (3) are used to identify SGP from PSGP.

• (4)-(9) is to determine whether a PCGP forms a CGP.

• (8) and (9) evaluates the conditions for CGP.

### Algorithm

• Speed-Up techniques

• Independent component computation

• Many isolated occupied grid clusters, there are no PSGPs or PCGPs formed between them.

• Apply basic ILP formulation for each one.

### Algorithm

• Speed-Up techniques

• Layout partition

• Divide a big component into several small connected partitions and perform ILP approach for each one.

• Different from the independent component computation, there will be some PSGPs/PCGPs between different partitions.

### Algorithm

• Solution Mergence

• After solving the solution for each component/partition, need to merge the coloring assignment as a whole.

### Algorithm

• Solution Mergence

• SGPe/CGPe: external conflicts/stitiches crossing the boundary of different partitions.

• Coloring flip optimization: Given a number of partitions and their coloring solutions for one independent component, choose the best flipping scheme to minimize total cost of SGPe and CGPe.

### Algorithm

• Solution Mergence

• Coloring flip optimization

### Conclusion

• This paper has developed a double patterning aware layout decomposition flow for simultaneous conflict and stitch minimization.

• The approach is featured by grid layout model and integer linear programming.