Efficient Process-Hotspot Detection Using Range Pattern Matching

Abstract

In current manufacturing processes, certain layout configurations are likely to have reduced yield and/or reliability due to increased susceptibility to stress effects or poor tolerance to certain processes like lithography. These problematic layout configurations need to be efficiently detected and eliminated from a design layout to enable better yield. In this paper, such layout configurations are called processhotspots and an efficient and scalable algorithm is proposed to detect such process-hotspots in a given layout.The concept of a range pattern is introduced and used to accurately and compactly represent these process-hotspots. This representation is flexible and can incorporate information about the deficiencies of available modeling and/or subsequent correction (for instance, mask synthesis) techniques. Each range pattern can also be associated with a scoring mechanism to score the problem regions according to yield impact. A library of range patterns is being developed in collaboration with a fab. The proposed process-hotspot detection system assumes that process-hotspots are specified as a library of range patterns and determines all occurrences of any of these range patterns in a layout. It is fast and accurate and can be applied to large industrial layouts. Unlike previous work, the proposed scheme can identify problems that cannot be efficiently modeled or corrected by subsequent mask synthesis techniques and can thereby complement existing work in that area. Experimental results are quite promising and show that all locations that match a range pattern in a given layout can be found in a matter of minutes.

EPIC: Efficient prediction of IC manufacturing hotspots with a unified meta-classification formulation

“…Figure 5: Example patterns in PM base classifiers We explored the current state-of-the-art methods [14][15][16] and came up with several major classes (each with hundreds of specific hotspot structures) of pattern matching base classifiers to cover various types of lithography hotspots, relating to special line-ends, corners, jogs, contact patterns, etc.…”

“…(2) Machine learning techniques [7][8][9][10][11][12][13] with good noise suppression capability are still in need of further accuracy improvement. (3) Pattern matching techniques [14][15][16][17] that are very good at detecting pre-characterized hotspot patterns lack the capability to predict never-before-seen hotspots. This is especially problematic when new types of designs are involved after the original pattern library is built.…”

Threatened Plants in China’s Sanjiang Plain: Hotspot Distributions and Gap Analysis

“…A hotspot is defined as a condition indicating some form of clustering in a spatial distribution that can separate clusters of high value from clusters of low value [41]. Hotspot detection is one of the methods for testing global aggregation, which not only can measure the degree of local correlation and analyze the characteristics of spatial distribution, but also can identify the clustering characteristics of high-or low-value species richness [42,43].…”

SAT based multi-net rip-up-and-reroute for manufacturing hotspot removal

“…This concern is largely addressed by the range pattern technique proposed in [4]. Range pattern provides a compact form for representing variants of patterns which share the same topological structure.…”

“…Although it is still based on rip-up-and-reroute, it has two key differences from the existing approaches. First, the hotspot patterns are stored in a library and instances of the hotspots in a routing are identified by pattern matching with the library [4]. One can see that no lithography or other manufacturing simulations are involved within the rerouting.…”