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arXiv · 2603.03723

A New Class of Geometric Analog Error Correction Codes for Crossbar Based In-Memory Computing

Ziyuan Zhu·Changcheng Yuan·Ron M. Roth·Paul H. Siegel·Anxiao Jiang
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Abstract

Analog error correction codes have been proposed for analog in-memory computing on resistive crossbars, which can accelerate vector-matrix multiplication for machine learning. Unlike traditional communication or storage channels, this setting involves a mixed noise model with small perturbations and outlier errors. A number of analog codes have been proposed for handling a single outlier, and several constructions have also been developed to address multiple outliers. However, the set of available code families remains limited, covering only a narrow range of code lengths and dimensions. In this paper, we study a recently proposed family of geometric codes capable of handling multiple outliers, and develop a geometric analysis that characterizes their m-height profiles.

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Ziyuan Zhu, Changcheng Yuan, Ron M. Roth, Paul H. Siegel, Anxiao Jiang. 2026-03-04. A New Class of Geometric Analog Error Correction Codes for Crossbar Based In-Memory Computing. https://arxiv.org/abs/2603.03723

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