Carbon Efficiency of Natural Organic Honey-Memristor Based Neuromorphic Computing

Harshvardhan Uppaluru; Zoe Templin; Shah Zayed Riam; Feng Zhao; Jinhui Wang

doi:10.1145/3716368.3735268

Carbon Efficiency of Natural Organic Honey-Memristor Based Neuromorphic Computing

Harshvardhan Uppaluru
, Zoe Templin
, Shah Zayed Riam
, Feng Zhao
, Jinhui Wang

University of South Alabama
Washington State University Vancouver

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

Original language	English
Title of host publication	GLSVLSI 2025 - Proceedings of the Great Lakes Symposium on VLSI 2025
Publisher	Association for Computing Machinery
Pages	245-251
Number of pages	7
ISBN (Electronic)	9798400714962
DOIs	https://doi.org/10.1145/3716368.3735268
State	Published - Jun 29 2025
Externally published	Yes
Event	35th Edition of the Great Lakes Symposium on VLSI 2025, GLSVLSI 2025 - New Orleans, United States Duration: Jun 30 2025 → Jul 2 2025

Publication series

Name	Proceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI

Conference

Conference	35th Edition of the Great Lakes Symposium on VLSI 2025, GLSVLSI 2025
Country/Territory	United States
City	New Orleans
Period	6/30/25 → 7/2/25

ASJC Scopus Subject Areas

General Engineering

Keywords

Emerging non-volatile devices
Memristor
Neuromorphic Computing

Access to Document

10.1145/3716368.3735268

Cite this

Uppaluru, H., Templin, Z., Riam, S. Z., Zhao, F., & Wang, J. (2025). Carbon Efficiency of Natural Organic Honey-Memristor Based Neuromorphic Computing. In GLSVLSI 2025 - Proceedings of the Great Lakes Symposium on VLSI 2025 (pp. 245-251). (Proceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI). Association for Computing Machinery. https://doi.org/10.1145/3716368.3735268

Carbon Efficiency of Natural Organic Honey-Memristor Based Neuromorphic Computing. / Uppaluru, Harshvardhan; Templin, Zoe; Riam, Shah Zayed et al.
GLSVLSI 2025 - Proceedings of the Great Lakes Symposium on VLSI 2025. Association for Computing Machinery, 2025. p. 245-251 (Proceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI).

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

Uppaluru, H, Templin, Z, Riam, SZ, Zhao, F & Wang, J 2025, Carbon Efficiency of Natural Organic Honey-Memristor Based Neuromorphic Computing. in GLSVLSI 2025 - Proceedings of the Great Lakes Symposium on VLSI 2025. Proceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI, Association for Computing Machinery, pp. 245-251, 35th Edition of the Great Lakes Symposium on VLSI 2025, GLSVLSI 2025, New Orleans, United States, 6/30/25. https://doi.org/10.1145/3716368.3735268

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keywords = "Emerging non-volatile devices, Memristor, Neuromorphic Computing",

author = "Harshvardhan Uppaluru and Zoe Templin and Riam, \{Shah Zayed\} and Feng Zhao and Jinhui Wang",

note = "Publisher Copyright: {\textcopyright} 2025 Copyright held by the owner/author(s).; 35th Edition of the Great Lakes Symposium on VLSI 2025, GLSVLSI 2025 ; Conference date: 30-06-2025 Through 02-07-2025",

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BT - GLSVLSI 2025 - Proceedings of the Great Lakes Symposium on VLSI 2025

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Carbon Efficiency of Natural Organic Honey-Memristor Based Neuromorphic Computing

Publication series

Conference

ASJC Scopus Subject Areas

Keywords

Access to Document

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Cite this