Towards a Machine that Works Like the Brain: Neuromorphic Computer
ORAL · Invited
Abstract
At present time new hardware concepts, based on transformative scientific concepts, are needed. This includes reevaluation of data manipulation concepts for software and systems and by necessity will require development of novel hardware including new device and materials concepts. I will describe some of the first steps by a large group of researchers to implement the grand challenge to “develop a machine that works like the brain”.
*This research was supported as part of the Quantum Materials for Energy Efficient Neuromorphic Computing (Q-MEEN-C), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science under Award # DE-SC0019273.
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Publication: See for instance
1) Quantum materials for energy-efficient neuromorphic computing
Axel Hoffmann, Shriram Ramanathan, Julie Grollier, Andrew D. Kent, Marcelo Rozenberg, Ivan K. Schuller, Oleg Shpyrko, Robert Dynes, Yeshaiahu Fainman, Alex Frano, Eric E. Fullerton, Giulia Galli, Vitaliy Lomakin, Shyue Ping Ong, Amanda K. Petford-Long, Jonathan A. Schuller, Mark D. Stiles, Yayoi Takamura, Yimei Zhu, APL Materials 10, 070904 (2022)
2) Thermal Management in Neuromorphic Materials, Devices, and Networks, Felipe Torres, Ali C. Basaran, Ivan K. Schuller, Advanced Materials, 35, e2205098 (2022)
Presenters
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Ivan K Schuller
- University of California, San Diego