Lee B. Baker

Works (5)

Updated: July 5th, 2023 15:32

2021 article

A Scalable Cluster-based Hierarchical Hardware Accelerator for a Cortically Inspired Algorithm

Dey, S., Baker, L., Schabel, J., Li, W., & Franzon, P. D. (2021, June 30). ACM Journal on Emerging Technologies in Computing Systems, Vol. 10.

By: S. Dey n, L. Baker n, J. Schabel  n, W. Li n & P. Franzon n 

author keywords: Neuromorphic computing; accelerator; cortical processor; hierarchical temporal memory; sparse distributed memory
topics (OpenAlex): Advanced Memory and Neural Computing; Advanced Neural Network Applications; Stochastic Gradient Optimization Techniques
TL;DR: A scalable, configurable and cluster-based hierarchical hardware accelerator through custom hardware architecture for Sparsey, a cortical learning algorithm inspired by the operation of the human cortex that uses a Sparse Distributed Representation to enable unsupervised learning and inference in the same algorithm. (via Semantic Scholar)
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7. Affordable and Clean Energy (OpenAlex)
Sources: Web Of Science, NC State University Libraries
Added: February 28, 2022

2021 article proceedings

Design for 3D Stacked Circuits

By: P. Franzon n , W. Davis n, E. Rotenberg n , J. Stevens n, S. Lipa n, T. Nigussie n, H. Pan  n, L. Baker n ...

topics (OpenAlex): 3D IC and TSV technologies; Semiconductor materials and devices; Interconnection Networks and Systems
TL;DR: 2.5D and 3D technologies can give rise to a node equivalent of scaling due to improved connectivity because of improved connectivity, but design issues that need to be addressed in pursuing such exploitations include thermal management, design for test and computer aided design. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries, Crossref
Added: July 11, 2022

2021 article

Multi-ANN embedded system based on a custom 3D-DRAM

Baker, L. B., Patti, R., & Franzon, P. (2021, October 1). 2021 IEEE INTERNATIONAL 3D SYSTEMS INTEGRATION CONFERENCE (3DIC).

By: L. Baker n, R. Patti & P. Franzon n 

author keywords: machine learning; embedded system; Deep Neural Networks (DNNs); CNN; neural network; LSTM; MLP
topics (OpenAlex): Advanced Memory and Neural Computing; Advanced Neural Network Applications; CCD and CMOS Imaging Sensors
TL;DR: This work demon-strates how a customized 3D-DRAM with a very wide databus can be combined with application-specific layers to produce a system meeting the requirements of embedded systems employing multiple instances of disparate ANNs. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: May 2, 2022

2017 journal article

Appliance Identification Algorithm for a Non-Intrusive Home Energy Monitor Using Cogent Confabulation

IEEE Transactions on Smart Grid, 10(1), 714–721.

By: S. Park *, L. Baker n & P. Franzon n 

author keywords: Appliance identification; cogent confabulation; monitoring; neural network applications; non-intrusive; energy monitor
topics (OpenAlex): Smart Grid Energy Management; Building Energy and Comfort Optimization; Energy Efficiency and Management; IoT-based Smart Home Systems
TL;DR: This paper presents an appliance identification algorithm for use with a non-intrusive home energy monitor based on a cogent confabulation neural network that showed better performance than the combinatorial optimization and artificial neural network approaches. (via Semantic Scholar)
UN Sustainable Development Goals Color Wheel
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy (Web of Science; OpenAlex)
Sources: Web Of Science, NC State University Libraries
Added: January 28, 2019

conference paper

Processor-in-memory support for artificial neural networks

Schabel, J., Baker, L., Dey, S., Li, W. F., & Franzon, P. D. 2016 IEEE International Conference on Rebooting Computing (icrc).

By: J. Schabel, L. Baker, S. Dey, W. Li & P. Franzon 

Source: NC State University Libraries
Added: August 6, 2018

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