Abstract
Neuromorphic computing is one promising post-Moore's law era technology. In order to develop and use neuromorphic systems, traditional von Neumann-based computers must be able to communicate with neuromorphic hardware to support functionality such as monitoring the state of the network, optimizing the array to better perform the task, and input/output data processing. In this paper, we describe our use of a separate neuromorphic array communications controller to support highthroughput, low-latency communication between a traditional computer and our implementations of neuromorphic systems. The goal of the communications controller is to provide enough performance to facilitate the desired interaction between the systems and to enable scaling of the neuromorphic systems to larger sizes.
Original language | English |
---|---|
Title of host publication | 2018 International Joint Conference on Neural Networks, IJCNN 2018 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781509060146 |
DOIs | |
State | Published - Oct 10 2018 |
Externally published | Yes |
Event | 2018 International Joint Conference on Neural Networks, IJCNN 2018 - Rio de Janeiro, Brazil Duration: Jul 8 2018 → Jul 13 2018 |
Publication series
Name | Proceedings of the International Joint Conference on Neural Networks |
---|---|
Volume | 2018-July |
Conference
Conference | 2018 International Joint Conference on Neural Networks, IJCNN 2018 |
---|---|
Country/Territory | Brazil |
City | Rio de Janeiro |
Period | 07/8/18 → 07/13/18 |
Funding
Notice: This material is based on research sponsored by the Air Force Research Laboratory under agreement number FA8750-16-1-0065. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the Air Force Research Laboratory or the U.S. Government. This manuscript has been authored in part by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). Research sponsored by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the U.S. Department of Energy.