In this paper, we propose an adap-tive squish representation for multilayer layouts, which is storage eficient, lossless and compatible with deep neural networks. We conduct experiments on 14nm industrial designs with a metal layer and its two adjacent via …

Jan 21, 2019 · In this paper, we propose an adaptive squish representation for multilayer layouts, which is storage efficient, lossless and compatible with deep neural networks. We conduct experiments on 14nm...

We propose a novel two-stage generative learning-based pattern generation framework including pattern topology generation and legalization, which has the capability of learn-ing inherent distributions of two-dimensional layouts and generate realistic patterns with little manual guidance.

1)We develop a novel layout pattern generation method based on discrete denoising for synthesizing layout topology. 2)We propose a lossless layout pattern representation strategy, Deep Squish Pattern, which accelerates pixel-based layout pattern generation schemes. 3)We utilize a nonlinear system for pattern assessment where

1. Systematically window across entire design 2. In every fixed window, centered on the corner or center of anchor layer shape, identify every pattern that exists in that design and target layer(s) (with dimensions) 3. Store a full catalog of all patterns with dimensions! Anchoring Classify Pattern Capture Pattern Library Pattern Cataloging

The classic squish pattern 11 is a lossless layout representation that consists of layout topology and geometric information. 9 As shown in Figure1, a layout design is converted into clips for pattern analysis.

In this paper, we propose an adaptive squish representation for multilayer layouts, which is storage efficient, lossless and compatible with deep neural networks. We conduct experiments on 14nm industrial designs with a metal layer and its two adjacent via …

In this study, we investigate the potential of generative machine learning models for creating design rule legal metal layout patterns. Our results demonstrate that the proposed model can generate legal patterns in complex design rule settings and achieves a high diversity score.

Jan 21, 2019 · In this paper, we propose an adaptive squish representation for multilayer layouts, which is storage efficient, lossless and compatible with deep neural networks. We conduct experiments on 14 nm industrial designs with a metal layer and its two adjacent via layers that contain metal-to-via hotspots.

processing to yield a legal layout pattern. Squish Pattern Representation. A layout pattern, comprising a series of non-overlapping polygons, can be effectively modeled using a squish pattern. The squish pattern is a compact representation of layout pattern that encodes layout topology and geometry into a matrix and vectors , 𝑦. It divides ...