Building next-generation AI systems: Co-optimization of algorithms, architectures, and nanoscale memristive devices
Document Type
Conference Proceeding
Publication Date
5-1-2019
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.
Identifier
85068311624 (Scopus)
ISBN
[9781728109817]
Publication Title
2019 IEEE 11th International Memory Workshop Imw 2019
External Full Text Location
https://doi.org/10.1109/IMW.2019.8739740
Grant
1710009
Fund Ref
National Science Foundation
Recommended Citation
Rajendran, Bipin; Sebastian, Abu; and Eleftheriou, Evangelos, "Building next-generation AI systems: Co-optimization of algorithms, architectures, and nanoscale memristive devices" (2019). Faculty Publications. 7623.
https://digitalcommons.njit.edu/fac_pubs/7623
