Artificial Neural Network (ANN) is a type of information processing system based on mimicking the principles of biological brains.
It has been broadly applied in application domains such as pattern recognition, automatic control, signal processing, decision support system and artificial intelligence.
Spiking Neural Network (SNN) is a type of biologically-inspired ANN that perform information processing based on discrete-time spikes.
It is more biologically realistic than classic ANNs, and can potentially achieve much better performance-power ratio.
Now, the researchers from Zhejiang University and Hangzhou Dianzi University in Hangzhou, China, have successfully developed the "Darwin" Neural Processing Unit (NPU), a neuromorphic hardware co-processor based on Spiking Neural Networks, fabricated by standard CMOS technology.
The research group led by Dr De Ma from Hangzhou Dianzi university and Dr Xiaolei Zhu from Zhejiang university developed a co-processor named as "Darwin".
The Darwin NPU aims to provide hardware acceleration of intelligent algorithms, with target application domain of resource-constrained, low-power small embedded devices.
The successful development of "Darwin" demonstrates the feasibility of real-time execution of Spiking Neural Networks in resource-constrained embedded systems.
It supports flexible configuration of a multitude of parameters of the neural network, hence it can be used to implement different functionalities as configured by the user.
"Since it uses spikes for information processing and transmission,similar to biological neural networks, it may be suitable for analysis and processing of biological spiking neural signals, and building brain-computer interface systems by interfacing with animal or human brains," the authors explained.
Its potential applications include intelligent hardware systems, robotics, brain-computer interfaces and others, said a paper that appeared in the journal Science China Press.