Parallel programming of an ionic floating-gate memory array for scalable neuromorphic computing
Sandia National Laboratories California · Stanford University · +3 more institutions
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Abstract
Neuromorphic computers could overcome efficiency bottlenecks inherent to conventional computing through parallel programming and readout of artificial neural network weights in a crossbar memory array. However, selective and linear weight updates and 1 billion write-read operations and support >1-megahertz write-read frequencies.
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12Topics & keywords
Topics
Keywords
- Neuromorphic engineering
- Scalability
- Computer science
- Crossbar switch
- Transistor
- Parallel computing
- Voltage
- Artificial neural network
UN Sustainable Development Goals
- Affordable and clean energy
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