Johannes Schemmel has been the head of the “Electronic Visions” research group at Heidelberg University since 2000. Since 2008, he has also led the ASIC-Laboratory of the University. Following the untimely passing of Prof. Karlheinz Meier in 2018, he served as the acting chair. Since 2024, he has held the chair of “Neuromorphic Computing Architectures” at Heidelberg University. His research focuses on highly parallel mixed-signal circuits for information processing. In recent years, the analog implementation of biologically inspired neural networks has been his primary research direction. The most prominent example of this work is the Heidelberg neuromorphic BrainScaleS system, which is part of the European EBRAINS research infrastructure for Neuroscience.

Abstract:  BrainScaleS – Networks of Analog Neuromorphic Processors

Brain-inspired event-based neuromorphic computing is a promising technology for energy-efficient bio-inspired AI. It also enables continuous learning based on local learning algorithms. For maximum energy efficiency, a brain-like in-memory realization is desirable. The Heidelberg BrainScaleS platform is an example of a neuromorphic architecture that combines true in-memory computing with hardware support for continuous local learning. In addition, its analog implementation of the core neuronal operations enables complex neuron models without an energy or area penalty.

For real-world applications as well as neuroscience, certain minimum network sizes are required. To realize the necessary upscaling, BrainScaleS pioneered wafer-scale integration. For future generations of BrainScaleS, this will not be feasible due to the high mask costs of modern semiconductor processes. This talk presents alternative solutions and how they can be utilized by the current BrainScaleS platform in EBRAINS. EBRAINS is a European research infrastructure for neuroscience. Its BrainScaleS neuromorphic service democratizes access to analog neuromorphic computing.