Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/153571
Title: Efficient and reconfigurable reservoir computing to realize alphabet pronunciation recognition based on processing-in-memory
Authors: Liu, Shuang
Wu, Yuancong
Xiong, Canlong
Liu, Yihe
Yang, Jing
Yu, Q.
Hu, S. G.
Chen, Tupei
Liu, Y.
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2021
Source: Liu, S., Wu, Y., Xiong, C., Liu, Y., Yang, J., Yu, Q., Hu, S. G., Chen, T. & Liu, Y. (2021). Efficient and reconfigurable reservoir computing to realize alphabet pronunciation recognition based on processing-in-memory. Applied Physics Letters, 119(10), 102103-. https://dx.doi.org/10.1063/5.0057132
Journal: Applied Physics Letters
Abstract: With its high energy efficiency and ultra-high speed, processing-in-memory (PIM) technology is promising to enable high performance in Reservoir Computing (RC) systems. In this work, we demonstrate an RC system based on an as-fabricated PIM chip platform. The RC system extracts input into a high-dimensional space through the nonlinear characteristic and randomly connected reservoir states inside the PIM-based RC. To examine the system, nonlinear dynamic system predictions, including nonlinear auto-regressive moving average equation of order 10 driven time series, isolated spoken digit recognition task, and recognition of alphabet pronunciation, are carried out. The system saves about 50% energy and requires much fewer operations as compared with the RC system implemented with digital logic. This paves a pathway for the RC algorithm application in PIM with lower power consumption and less hardware resource required.
URI: https://hdl.handle.net/10356/153571
ISSN: 0003-6951
DOI: 10.1063/5.0057132
Rights: © 2021 Author(s). All rights reserved. This paper was published by AIP Publishing in Applied Physics Letters and is made available with permission of Author(s).
Fulltext Permission: embargo_20220916
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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