Neuromorphic Computing for Scientific Applications

Robert Patton; Prasanna Date; Shruti Kulkarni; Chathika Gunaratne; Seung Hwan Lim; Guojing Cong; Steven R. Young; Mark Coletti; Thomas E. Potok; Catherine D. Schuman

doi:10.1109/RSDHA56811.2022.00008

Neuromorphic Computing for Scientific Applications

Robert Patton, Prasanna Date, Shruti Kulkarni, Chathika Gunaratne, Seung Hwan Lim, Guojing Cong, Steven R. Young, Mark Coletti, Thomas E. Potok, Catherine D. Schuman

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

5 Scopus citations

Abstract

Neuromorphic computing technology continues to make strides in the development of new algorithms, devices, and materials. In addition, applications have begun to emerge where neuromorphic computing shows promising results. However, numerous barriers to further development and application remain. In this work, we identify several science areas where neuromorphic computing can either make an immediate impact (within 1 to 3 years) or the societal impact would be extremely high if the technological barriers can be addressed. We identify both opportunities and hurdles to the development of neuromorphic computing technology for these areas. Finally, we discuss future directions that need to be addressed to expand both the development and application of neuromorphic computing.

Original language	English
Title of host publication	Proceedings of RSDHA 2022
Subtitle of host publication	Redefining Scalability for Diversely Heterogeneous Architectures, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	22-28
Number of pages	7
ISBN (Electronic)	9781665475686
DOIs	https://doi.org/10.1109/RSDHA56811.2022.00008
State	Published - 2022
Event	2022 IEEE/ACM Redefining Scalability for Diversely Heterogeneous Architectures, RSDHA 2022 - Dallas, United States Duration: Nov 13 2022 → Nov 18 2022

Publication series

Name	Proceedings of RSDHA 2022: Redefining Scalability for Diversely Heterogeneous Architectures, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis

Conference

Conference	2022 IEEE/ACM Redefining Scalability for Diversely Heterogeneous Architectures, RSDHA 2022
Country/Territory	United States
City	Dallas
Period	11/13/22 → 11/18/22

Funding

This work was funded in part by the DOE Office of Science, High-energy Physics Quantised program. This material is based upon work supported in part by the US Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Robinson Pino, program manager, under contract number DE-AC05-00OR22725 and under award number DE-SC0022566. Notice: This manuscript has been authored in part by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

Keywords

neural simulation
neuromorphic computing
scientific applications
spiking neural networks

Access to Document

10.1109/RSDHA56811.2022.00008

Cite this

Patton, R., Date, P., Kulkarni, S., Gunaratne, C., Lim, S. H., Cong, G., Young, S. R., Coletti, M., Potok, T. E., & Schuman, C. D. (2022). Neuromorphic Computing for Scientific Applications. In Proceedings of RSDHA 2022: Redefining Scalability for Diversely Heterogeneous Architectures, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis (pp. 22-28). (Proceedings of RSDHA 2022: Redefining Scalability for Diversely Heterogeneous Architectures, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RSDHA56811.2022.00008

Patton, Robert ; Date, Prasanna ; Kulkarni, Shruti et al. / Neuromorphic Computing for Scientific Applications. Proceedings of RSDHA 2022: Redefining Scalability for Diversely Heterogeneous Architectures, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 22-28 (Proceedings of RSDHA 2022: Redefining Scalability for Diversely Heterogeneous Architectures, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis).

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abstract = "Neuromorphic computing technology continues to make strides in the development of new algorithms, devices, and materials. In addition, applications have begun to emerge where neuromorphic computing shows promising results. However, numerous barriers to further development and application remain. In this work, we identify several science areas where neuromorphic computing can either make an immediate impact (within 1 to 3 years) or the societal impact would be extremely high if the technological barriers can be addressed. We identify both opportunities and hurdles to the development of neuromorphic computing technology for these areas. Finally, we discuss future directions that need to be addressed to expand both the development and application of neuromorphic computing.",

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author = "Robert Patton and Prasanna Date and Shruti Kulkarni and Chathika Gunaratne and Lim, {Seung Hwan} and Guojing Cong and Young, {Steven R.} and Mark Coletti and Potok, {Thomas E.} and Schuman, {Catherine D.}",

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year = "2022",

doi = "10.1109/RSDHA56811.2022.00008",

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series = "Proceedings of RSDHA 2022: Redefining Scalability for Diversely Heterogeneous Architectures, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis",

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Patton, R , Date, P , Kulkarni, S , Gunaratne, C , Lim, SH, Cong, G, Young, SR , Coletti, M , Potok, TE & Schuman, CD 2022, Neuromorphic Computing for Scientific Applications. in Proceedings of RSDHA 2022: Redefining Scalability for Diversely Heterogeneous Architectures, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis. Proceedings of RSDHA 2022: Redefining Scalability for Diversely Heterogeneous Architectures, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis, Institute of Electrical and Electronics Engineers Inc., pp. 22-28, 2022 IEEE/ACM Redefining Scalability for Diversely Heterogeneous Architectures, RSDHA 2022, Dallas, United States, 11/13/22. https://doi.org/10.1109/RSDHA56811.2022.00008

Neuromorphic Computing for Scientific Applications. / Patton, Robert ; Date, Prasanna ; Kulkarni, Shruti et al.
Proceedings of RSDHA 2022: Redefining Scalability for Diversely Heterogeneous Architectures, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis. Institute of Electrical and Electronics Engineers Inc., 2022. p. 22-28 (Proceedings of RSDHA 2022: Redefining Scalability for Diversely Heterogeneous Architectures, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis).

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

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AU - Kulkarni, Shruti

AU - Gunaratne, Chathika

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AU - Cong, Guojing

AU - Young, Steven R.

AU - Coletti, Mark

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AB - Neuromorphic computing technology continues to make strides in the development of new algorithms, devices, and materials. In addition, applications have begun to emerge where neuromorphic computing shows promising results. However, numerous barriers to further development and application remain. In this work, we identify several science areas where neuromorphic computing can either make an immediate impact (within 1 to 3 years) or the societal impact would be extremely high if the technological barriers can be addressed. We identify both opportunities and hurdles to the development of neuromorphic computing technology for these areas. Finally, we discuss future directions that need to be addressed to expand both the development and application of neuromorphic computing.

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Patton R , Date P , Kulkarni S , Gunaratne C , Lim SH, Cong G et al. Neuromorphic Computing for Scientific Applications. In Proceedings of RSDHA 2022: Redefining Scalability for Diversely Heterogeneous Architectures, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis. Institute of Electrical and Electronics Engineers Inc. 2022. p. 22-28. (Proceedings of RSDHA 2022: Redefining Scalability for Diversely Heterogeneous Architectures, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis). doi: 10.1109/RSDHA56811.2022.00008

Neuromorphic Computing for Scientific Applications

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