Abisko: Deep codesign of an architecture for spiking neural networks using novel neuromorphic materials

• Published in: The International Journal of High Performance Computing Applications
• Main Authors: Vetter, Jeffrey S., Date, Prasanna, Fahim, Farah, Kulkarni, Shruti R., Maksymovych, Petro, Talin, A. Alec, Tallada, Marc Gonzalez, Vanna-iampikul, Pruek, Young, Aaron R., Brooks, David, Cao, Yu, Gu-Yeon, Wei, Lim, Sung Kyu, Liu, Frank, Marinella, Matthew, Sumpter, Bobby, Miniskar, Narasinga Rao
• Other Authors: DOE Office of Science Research Program
• Format: Article in Journal/Newspaper
• Language: English
• Published: SAGE Publications 2023
• Subjects: Abisko
• Online Access: http://dx.doi.org/10.1177/10943420231178537; http://journals.sagepub.com/doi/pdf/10.1177/10943420231178537; http://journals.sagepub.com/doi/full-xml/10.1177/10943420231178537

The Abisko project aims to develop an energy-efficient spiking neural network (SNN) computing architecture and software system capable of autonomous learning and operation. The SNN architecture explores novel neuromorphic devices that are based on resistive-switching materials, such as memristors an...