A photonic accelerator for large-scale artificial neural networks
- Resource Type
- Authors
- Sean Pang; Guifang Li
- Source
- AI and Optical Data Sciences II.
- Subject
- Quantitative Biology::Neurons and Cognition
Artificial neural network
Orders of magnitude (temperature)
Computer science
business.industry
Computer Science::Neural and Evolutionary Computation
Analog computer
Optical computing
Power (physics)
law.invention
ComputingMethodologies_PATTERNRECOGNITION
law
Scalability
Electronic engineering
Photonics
business
Efficient energy use
- Language
In the post-Moore’s law era, dedicated digital accelerators have played an indispensable role in the success of artificial neural networks (ANNs) and their applications in artificial intelligence (AI). As the complexity of ANNS grows, analog electrical and optical computing are being considered as alternatives for achieving sustainable scalability and energy efficiency. In this talk we will present photonic accelerators that can potentially provide orders of magnitude increases in scalability and energy efficiency towards brain-like AI with hundred billion-neuron neural processing power.