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Dynamic Adaptive Neural Network Arrays: A Neuromorphic Architecture

Catherine D. Schuman, Adam Disney, and John Reynolds.

November, 2015

Supercomputing, 2015: Machine Learning in High Performance Computing Environments Workshop.

http://ornlcda.github.io/MLHPC2015/program.html

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Abstract

Dynamic Adaptive Neural Network Array (DANNA) is a neuromorphic hardware implementation. It differs from most other neuromorphic projects in that it allows for programmability of structure, and it is trained or designed using evolutionary optimization. This paper describes the DANNA structure, how DANNA is trained using evolutionary optimization, and an application of DANNA to a very simple classification task.

Citation Information

Text


.inproceedings  sdr:15:d
author          C. D. Schuman and A. Disney and J. Reynolds
title           Dynamic Adaptive Neural Network Arrays: A Neuromorphic Architecture
booktitle       Workshop on Machine Learning in HPC Environments, Supercomputing
year            2015
address         Austin, TX

Bibtex


@INPROCEEDINGS{sdr:15:d,
  author = "C. D. Schuman and A. Disney and J. Reynolds",
  title = "Dynamic Adaptive Neural Network Arrays: A Neuromorphic Architecture",
  booktitle = "Workshop on Machine Learning in HPC Environments, Supercomputing",
  year = "2015",
  address = "Austin, TX"
}