A 115.1 TOPS/W, 12.1 TOPS/mm2Computation-in-Memory using Ring-Oscillator based ADC for Edge AI

Abhairaj Singh*, Rajendra Bishnoi, Ali Kaichouhi, Sumit Diware, Rajiv V. Joshi, Said Hamdioui

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

2 Citations (Scopus)
31 Downloads (Pure)

Abstract

Analog computation-in-memory (CIM) architecture alleviates massive data movement between the memory and the processor, thus promising great prospects to accelerate certain computational tasks in an energy-efficient manner. However, data converters involved in these architectures typically achieve the required computing accuracy at the expense of high area and energy footprint which can potentially determine CIM candidacy for low-power and compact edge-AI devices. In this work, we present a memory-periphery co-design to perform accurate A/D conversions of analog matrix-vector-multiplication (MVM) outputs. Here, we introduce a scheme where select-lines and bit-lines in the memory are virtually fixed to improve conversion accuracy and aid a ring-oscillator-based A/D conversion, equipped with component sharing and inter-matching of the reference blocks. In addition, we deploy a self-timed technique to further ensure high robustness addressing global design and cycle-to-cycle variations. Based on measurement results of a 4Kb CIM chip prototype equipped with TSMC 40nm, a relative accuracy of up to 99.71% is achieved with an energy efficiency of 115.1 TOPS/W and computational density of 12.1 TOPS/mm2 for the MNIST dataset. Thus, an improvement of up to 11.3X and 7.5X compared to the state-of-the-art, respectively.

Original languageEnglish
Title of host publicationAICAS 2023 - IEEE International Conference on Artificial Intelligence Circuits and Systems, Proceeding
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages5
ISBN (Electronic)9798350332674
DOIs
Publication statusPublished - 2023
Event5th IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2023 - Hangzhou, China
Duration: 11 Jun 202313 Jun 2023

Publication series

NameAICAS 2023 - IEEE International Conference on Artificial Intelligence Circuits and Systems, Proceeding

Conference

Conference5th IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2023
Country/TerritoryChina
CityHangzhou
Period11/06/2313/06/23

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • analog computing
  • analog-to-digital converters
  • Computation-in-memory
  • ring-oscillator

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