Machine Learning Support for Cell-aware Diagnosis - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier
Book Sections Year : 2023

Machine Learning Support for Cell-aware Diagnosis

Abstract

This chapter will provide an overview of the various machine learning approaches and techniques proposed to support cell-aware generation, test, and diagnosis. The chapter will focus on the generation of the cell-aware models and their usage for diagnosis. After some backgrounds on conventional approaches to generate and diagnose cell-aware defects, the chapter will present a learning-based solution to generate cell-aware models. Then, the chapter will present a ML-based cell-aware diagnosis technique. Effectiveness of existing techniques will be shown through industrial case studies and corresponding diagnosis results in terms of accuracy and resolution. The chapter will conclude by a discussion on the future directions in this field.
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Dates and versions

lirmm-03989878 , version 1 (15-02-2023)

Identifiers

  • HAL Id : lirmm-03989878 , version 1

Cite

Aymen Ladhar, Arnaud Virazel. Machine Learning Support for Cell-aware Diagnosis. Machine Learning Support for Fault Diagnosis of System-on-Chip, pp.173-204, 2023, ISBN 978-3-031-19638-6 ISBN 978-3-031-19639-3 (eBook). ⟨lirmm-03989878⟩

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