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Title: A CAD System for Exploring Neuromorphic Computing with Emerging Technologies

Authors:
 [1];  [1];  [1];  [2]
  1. University of Tennessee (UT)
  2. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Laboratory Directed Research and Development (LDRD) Program
OSTI Identifier:
1361337
DOE Contract Number:
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: Government Microcircuit Applications & Critical Technology (GOMACTech) Conference, Reno, NV, USA, 20170320, 20170320
Country of Publication:
United States
Language:
English

Citation Formats

Plank, James, Rose, Garrett, Dean, Mark, and Schuman, Catherine D. A CAD System for Exploring Neuromorphic Computing with Emerging Technologies. United States: N. p., 2017. Web.
Plank, James, Rose, Garrett, Dean, Mark, & Schuman, Catherine D. A CAD System for Exploring Neuromorphic Computing with Emerging Technologies. United States.
Plank, James, Rose, Garrett, Dean, Mark, and Schuman, Catherine D. Sun . "A CAD System for Exploring Neuromorphic Computing with Emerging Technologies". United States. doi:.
@article{osti_1361337,
title = {A CAD System for Exploring Neuromorphic Computing with Emerging Technologies},
author = {Plank, James and Rose, Garrett and Dean, Mark and Schuman, Catherine D},
abstractNote = {},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Jan 01 00:00:00 EST 2017},
month = {Sun Jan 01 00:00:00 EST 2017}
}

Conference:
Other availability
Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

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  • Abstract not provided.
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  • Dynamic Adaptive Neural Network Arrays (DANNAs) are neuromorphic computing systems developed as a hardware based approach to the implementation of neural networks. They feature highly adaptive and programmable structural elements, which model arti cial neural networks with spiking behavior. We design them to solve problems using evolutionary optimization. In this paper, we highlight the current hardware and software implementations of DANNA, including their features, functionalities and performance. We then describe the development of an Application Development Platform (ADP) to support efficient application implementation and testing of DANNA based solutions. We conclude with future directions.
  • We describe our approach to post-Moore's law computing with three neuromorphic computing models that share a RISC philosophy, featuring simple components combined with a flexible and programmable structure. We envision these to be leveraged as co-processors, or as data filters to provide in situ data analysis in supercomputing environments.
  • Abstract not provided.