Efficient Spatial Variation Characterization via Matrix Completion

TL;DR

This paper introduces a matrix completion-based method for efficiently estimating spatial variations on wafers or dies using minimal sampling points, with high accuracy and broad applicability.

Contribution

It presents a novel approach leveraging matrix completion to accurately characterize spatial variations with fewer samples than traditional methods.

Findings

Achieves high accuracy with fewer sampling points.

Generalizes to mixed spatial and device type estimation.

Offers a practical solution for wafer and die analysis.

Abstract

In this paper, we propose a novel method to estimate and characterize spatial variations on dies or wafers. This new technique exploits recent developments in matrix completion, enabling estimation of spatial variation across wafers or dies with a small number of randomly picked sampling points while still achieving fairly high accuracy. This new approach can be easily generalized, including for estimation of mixed spatial and structure or device type information.