Dr. Johannes Schemmel, KIP, Heidelberg University, Germany
Brain Inspired Computing
Brain Inspired or Neuromorphic Computing, as a realization of Non-Turing, in-memory, event-based computing, will allow us to overcome the power wall our CPU-centric CMOS technology is facing. But that does not mean that the era of Turing-based computing will come to an end soon, or that Turing-based computing does not have its place in the neuromorphic world. This talk will summarize how the Heidelberg BrainScaleS-2 accelerated analog neuromorphic architecture balances Turing and Non-Turing computing to combine power efficiency with the necessary flexibility and programmability, thereby reducing the resource requirements of AI and extending it by recent insights from neuroscience. These bio-inspired AI technologies may be beneficial for the data challenges the next generation of science instrumentation is facing. Possible applications of the BrainScaleS technology in the area of edge computing will be presented.
Dr. Johannes Schemmel is head of the Electronic Vision(s) research group at Heidelberg University. Since 2018 he acts as interim professor at the chair of neuromorphic computing. His core research interests are massively parallel analog, in-memory, neuromorphic computing technologies for brain-inspired artificial intelligence.
He is the lead architect of the BrainScaleS neuromorphic system.