A Test Methodology for Neural Computing Unit

Minho Cheong, Ingeol Lee, Sungho Kang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As convolutional neural networks (CNN) has been widely employed in deep learning applications, the accelerator for CNN has been proposed. Neural computing unit (NCU), which is an accelerator for CNN, includes thousands of identical cores named multiplier and accumulate (MAC), so testing NCU with the conventional methods are inefficient. This paper proposes a novel method to test NCU by applying test patterns for a MAC to all MACs in NCU. The experimental results indicate that the new method reduces test time to 1.38% and test data volume to 0.03%.

Original languageEnglish
Title of host publicationProceedings - International SoC Design Conference 2018, ISOCC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages11-12
Number of pages2
ISBN (Electronic)9781538679609
DOIs
Publication statusPublished - 2019 Feb 22
Event15th International SoC Design Conference, ISOCC 2018 - Daegu, Korea, Republic of
Duration: 2018 Nov 122018 Nov 15

Publication series

NameProceedings - International SoC Design Conference 2018, ISOCC 2018

Conference

Conference15th International SoC Design Conference, ISOCC 2018
CountryKorea, Republic of
CityDaegu
Period18/11/1218/11/15

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All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials

Cite this

Cheong, M., Lee, I., & Kang, S. (2019). A Test Methodology for Neural Computing Unit. In Proceedings - International SoC Design Conference 2018, ISOCC 2018 (pp. 11-12). [8649896] (Proceedings - International SoC Design Conference 2018, ISOCC 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISOCC.2018.8649896