yen-ting yu iris hui-ru jiang yumin zhang charles chiang drc-based hotspot detection considering...

Yen-Ting Yu

Iris Hui-Ru Jiang

Yumin Zhang

Charles Chiang

DRC-Based Hotspot Detection Considering Edge Tolerance and Incomplete Specification

ICCAD’14

Outline

Introduction Preliminaries Hotspot Detection Framework Experimental Result Conclusion

Introduction

In modern manufacturing processes, certain layout configurations are susceptible to lithographic process

Patterns with similar layouts could become process-hotspots

Represent these similar patterns by a representative pattern with edge tolerances and incomplete specified regions

String-matching-based Each pattern and layout window are encoded by

strings

Overview

The key features of this work Redefine MTCG and the extraction rules to

reflect the impacts of don’t care regions and edge tolerances

DRC searching space reduction technique Longest common subsequence on strings to

handle the impact of don’t care regions

Preliminaries

Design Rule Checking (DRC) Design rules are a set of parameters to ensure

the manufacturability of a layout Fundamental rules include the minimum width,

minimum spacing, and minimum enclosure rules

Modified Transitive Closure Graph (MTCG)

Problem Formulation

Given Hotspot pattern with edge tolerances and

incompletely specified regions (don’t care regions)

A layout Report

All hotspot locations considering eight possible orientations in the layout

Hotspot Detection Framework

Pattern Enumeration

Edge tolerances within a given pattern may lead to different pattern topologies

Extend the idea of All-Pair Min-Range Path (APMRP) algorithm to form pattern enumeration algorithm

APMRP m and n denote the minimum and maximum

distance between two edges minimize the (n – m) value If m < 0 and n > 0

(m, n) set contains three subsets: {(m, −1), (0, 0), (1, n)}

If m < 0 and n = 0 (m, n) set contains two subsets: {(m, −1), (0, 0)}

If m = 0 and n > 0 (m, n) set contains two subsets: {(0, 0), (1, n)}

Else only one subset {(m, n)}

MTCG with Don’t Care Regions and Critical DRC Rule Extraction

To use the aid of DRC to realize hotspot detection

Interpret all edge constraints to design rules Redefine five types of rules in [1] All rules can be extracted only from Ch,h and

Cv,v, Ch,v and Cv,h are serve for boundary checking

Rule 1(internal rule)–the width and height of a block tile find the dimension of each block tile that does

not touch the window boundary

Rule 2(external rule)–the distance between two adjacent block tiles find the dimensions of all space tiles that do not

touch the window boundary and are located in between block tiles

Rule 3(diagonal rule)–the diagonal relations between two convex corners of block (space) tiles find the diagonal relations between any two

convex corners of block (space) tiles

Rule 4(longedge rule)–the space or block tile with one edge touching the window boundary

Rule 5(segment rule)–the space tile with two or three adjacent edges touching the window boundary or space tiles

The dimensions of each extracted rule can be represented by a rule rectangle

The height and width of a rule rectangle are defined by its corresponding edge constraints

Define two types of don’t care regions Don’t region with two or three adjacent edges

fully facing the window boundaries

Don’t region in between two facing edges of polygons

Rule 6––the space tile with one edge or two opposite edges touching the boundary tiles

Searching Space Reduction

A pattern may have eight possible orientations Divide these eight orientations into two sets Generate a runset file for each set and run DRC

twice to obtain the locations that hit any generated rule

The region AND technique

Rule Ordering

Even a simple range pattern may generate tons of different pattern topologies after pattern enumeration

With the region AND technique, how to cover the whole pattern topologies during DRC with fewest DRC rules becomes an issue

The topology covering problem is NP-hard U = {1, 2, 3, 4, 5}

four subsets S = {{1, 2, 3}, {2, 4}, {3, 4}, {4, 5}}

subsets{1, 2, 3} {4, 5} A greedy heuristic can be applied to this

problem

Rules priority {internal rule, external rule, diagonal rule}

v

{longedge rule, sixth rule}

v

{segment rule}

Candidate Identification

Each generated pattern topology is represented by a set of DRC rules

Encoding rule rectangles to two strings, one in the vertical, one in the horizontal

To identify the potential hotspot locations in the layout, based on DRC results and rule priorities

Finalization

Some locations contain extra polygons that are not related to any of our extracted DRC rules and are not within the don’t care regions

Experimental Result

Implemented in the C programming language on a Linux platform

Hotspot patterns

Integrate a state-of-the-art industrial DRC engine into our framework

Conclusion

Proposed an accurate and efficient hotspot detection framework to handle hotspot patterns with edge tolerances and incompletely specified regions

Compared with the state-of-the-art work, our approach can reach promising success rate with significant speedups