Neural Mini-Apps as a Tool for Neuromorphic Computing Insight

Craig M. Vineyard, Suma Cardwell, Frances S. Chance, Srideep Musuvathy, Fred Rothganger, William Severa, John Darby Smith, Corinne Teeter, Felix Wang, James B. Aimone

Abstract: Neuromorphic computing (NMC) is an exciting paradigm seeking to incorporate principles from biological brains to enable advanced computing capabilities. Not only does this encompass algorithms, such as neural networks, but also the consideration of how to structure the enabling computational architectures for executing such workloads. Assessing the merits of NMC is more nuanced than simply comparing singular, historical performance metrics from traditional approaches versus that of NMC. The novel computational architectures require new algorithms to make use of their differing computational approaches. And neural algorithms themselves are emerging across increasing application domains. Accordingly, we propose following the example high performance computing has employed using context capturing mini-apps and abstraction tools to explore the merits of computational architectures. Here we present Neural Mini-Apps in a neural circuit tool called Fugu as a means of NMC insight.