DANNA: A neuromorphic software ecosystem

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• 作者：Adam Disney^a ; ^{adisney1@vols.utk.edu" class="auth_mail" title="E-mail the corresponding author} ; John Reynolds^a ; ^{jreyno40@vols.utk.edu" class="auth_mail" title="E-mail the corresponding author} ; Catherine D. Schuman^b ; ^{schumancd@ornl.gov" class="auth_mail" title="E-mail the corresponding author} ; Aleksander Klibisz^a ; ^{aklibisz@vols.utk.edu" class="auth_mail" title="E-mail the corresponding author} ; Aaron Young^a ; ^{ayoung48@vols.utk.edu" class="auth_mail" title="E-mail the corresponding author} ; James S. Plank^a ; ^{jplank@vols.utk.edu" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Neuromorphic computing ; Genetic algorithms ; Visualization
• 刊名：Biologically Inspired Cognitive Architectures
• 出版年：2016
• 出版时间：July 2016
• 年：2016
• 卷：17
• 期：Complete
• 页码：49-56
• 全文大小：1295 K

文摘

Architectures for neuromorphic computing have evolved to the point where a significant amount of software design and implementation is necessary for leveraging these architectures to solve real problems. In this paper, we describe the software ecosystem for the DANNA neuromorphic computing model. This ecosystem is composed of four pieces: a simulator, commander, evolutionary optimizer, and visualizer. The ecosystem facilitates developing applications for DANNA, and in turn will help DANNA evolve into a more effective neuromorphic computing model. We describe how we use the software components to perform digit classification using the MNIST dataset.