DAEBI: A Tool for Data Flow and Architecture Explorations of Binary Neural Network Accelerators

Mikail Yayla, Cecilia Latotzke, Robert Huber, Somar Iskif, Tobias Gemmeke, Jian-Jia Chen. DAEBI: A Tool for Data Flow and Architecture Explorations of Binary Neural Network Accelerators. In Cristina Silvano, Christian Pilato, Marc Reichenbach, editors, Embedded Computer Systems: Architectures, Modeling, and Simulation - 23rd International Conference, SAMOS 2023, Samos, Greece, July 2-6, 2023, Proceedings. Volume 14385 of Lecture Notes in Computer Science, pages 107-122, Springer, 2023. [doi]

Abstract

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