Building next-generation AI systems: Co-optimization of algorithms, architectures, and nanoscale memristive devices

Bipin Rajendran; Abu Sebastian; Evangelos Eleftheriou

doi:10.1109/IMW.2019.8739740

Building next-generation AI systems: Co-optimization of algorithms, architectures, and nanoscale memristive devices

Bipin Rajendran, Abu Sebastian, Evangelos Eleftheriou

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

Computing systems inspired by the architecture of the human brain is poised to revolutionize the engines for information processing and data analytics. However, the efficiency and performance of these platforms pale in comparison with the human brain, especially when benchmarked in terms of metrics such as intelligence per Watt per square mm. In this paper, we review some recent progress and future prospects of building artificial intelligence systems that target the efficiency of the brain, leveraging the unique properties of nanoscale memristive device technologies.

Original language	English (US)
Title of host publication	2019 IEEE 11th International Memory Workshop, IMW 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728109817
DOIs	https://doi.org/10.1109/IMW.2019.8739740
State	Published - May 2019
Event	11th IEEE International Memory Workshop, IMW 2019 - Montterey, United States Duration: May 12 2019 → May 15 2019

Publication series

Name	2019 IEEE 11th International Memory Workshop, IMW 2019

Conference

Conference	11th IEEE International Memory Workshop, IMW 2019
Country/Territory	United States
City	Montterey
Period	5/12/19 → 5/15/19

All Science Journal Classification (ASJC) codes

Hardware and Architecture
Electrical and Electronic Engineering

Keywords

Spiking neural network
crossbar array
in-memory computing
memristive devices
on-chip learning

Access to Document

10.1109/IMW.2019.8739740

Cite this

Rajendran, B., Sebastian, A., & Eleftheriou, E. (2019). Building next-generation AI systems: Co-optimization of algorithms, architectures, and nanoscale memristive devices. In 2019 IEEE 11th International Memory Workshop, IMW 2019 Article 8739740 (2019 IEEE 11th International Memory Workshop, IMW 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IMW.2019.8739740

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abstract = "Computing systems inspired by the architecture of the human brain is poised to revolutionize the engines for information processing and data analytics. However, the efficiency and performance of these platforms pale in comparison with the human brain, especially when benchmarked in terms of metrics such as intelligence per Watt per square mm. In this paper, we review some recent progress and future prospects of building artificial intelligence systems that target the efficiency of the brain, leveraging the unique properties of nanoscale memristive device technologies.",

keywords = "Spiking neural network, crossbar array, in-memory computing, memristive devices, on-chip learning",

author = "Bipin Rajendran and Abu Sebastian and Evangelos Eleftheriou",

year = "2019",

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doi = "10.1109/IMW.2019.8739740",

language = "English (US)",

series = "2019 IEEE 11th International Memory Workshop, IMW 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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note = "11th IEEE International Memory Workshop, IMW 2019 ; Conference date: 12-05-2019 Through 15-05-2019",

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Rajendran, B, Sebastian, A & Eleftheriou, E 2019, Building next-generation AI systems: Co-optimization of algorithms, architectures, and nanoscale memristive devices. in 2019 IEEE 11th International Memory Workshop, IMW 2019., 8739740, 2019 IEEE 11th International Memory Workshop, IMW 2019, Institute of Electrical and Electronics Engineers Inc., 11th IEEE International Memory Workshop, IMW 2019, Montterey, United States, 5/12/19. https://doi.org/10.1109/IMW.2019.8739740

Building next-generation AI systems: Co-optimization of algorithms, architectures, and nanoscale memristive devices. / Rajendran, Bipin; Sebastian, Abu; Eleftheriou, Evangelos.
2019 IEEE 11th International Memory Workshop, IMW 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8739740 (2019 IEEE 11th International Memory Workshop, IMW 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - Computing systems inspired by the architecture of the human brain is poised to revolutionize the engines for information processing and data analytics. However, the efficiency and performance of these platforms pale in comparison with the human brain, especially when benchmarked in terms of metrics such as intelligence per Watt per square mm. In this paper, we review some recent progress and future prospects of building artificial intelligence systems that target the efficiency of the brain, leveraging the unique properties of nanoscale memristive device technologies.

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M3 - Conference contribution

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BT - 2019 IEEE 11th International Memory Workshop, IMW 2019

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 12 May 2019 through 15 May 2019

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Rajendran B, Sebastian A, Eleftheriou E. Building next-generation AI systems: Co-optimization of algorithms, architectures, and nanoscale memristive devices. In 2019 IEEE 11th International Memory Workshop, IMW 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8739740. (2019 IEEE 11th International Memory Workshop, IMW 2019). doi: 10.1109/IMW.2019.8739740

Building next-generation AI systems: Co-optimization of algorithms, architectures, and nanoscale memristive devices

Abstract

Publication series

Conference

All Science Journal Classification (ASJC) codes

Keywords

Access to Document

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