There are tremendous efforts on the research and development of neuromorphic computing beyond the von Neumann architecture. By mimicking the operations of brains and integrating the memory and processing units in proximity, a modular, parallel, distributed and scalable computing system may be realized with lower power consumptions and large bandwidth. Neuromorphic computing is revolutionary and excels at computing complex spatial-temporal dynamics with plasticity and fault-tolerance. Marching towards the realization of neuromorphic computing has a natural reference from the mature development ecosystem for von Neumann computers with the CMOS technology. The fundamental devices, the circuit and system designs and the electronic design automation algorithms form a stable and mutual supportive ecosystem which is believed to play an important role in the technology developments.
This Research Topic aims to archive the most recent advancements in the devices, circuits and system, as well as the electronic design automations (EDA) for the neuromorphic computing. While there are many research and development activities in the fields, the efforts reported in literature are mostly quite scattered. By collecting recent advances in the areas from devices to circuit designs and EDA, this Research Topic will be a comprehensive platform to discuss different aspects of the neuromorphic computing ecosystem, to identify the challenges facing by the community in its further development, and hopefully to figure out the next milestones for the maturity of the exciting technology.
The scope of the Research Topic includes the neuromorphic circuits (based on integrations of CMOS technology or emerging device technologies for functional, brain-like systems), and the EDA algorithms and tools (for the hierarchical implementations of the neuromorphic computing blocks). The term of 'neuromorphic' here specially means 'brain-like', which uses the hardwares to emulate the synaptic and neural dynamics in the event-driven manner with spikes.
Topics of interests include, but are not limited to:
-Hardware circuits for spiking neural network (SNN)
-Algorithm-hardware co-design for SNN circuits
-Design and simulation of neuromorphic circuits
-Synthesis and verification of neuromorphic systems
-System technology co-optimization for neuromorphic systems
Note that pure device papers without or with only simply mentioned applications in neuromorphic circuits and systems are not in the scope of this Research Topic. Circuits and systems of the real-valued computation in the deep-learning paradigm are also out of the scope.
There are tremendous efforts on the research and development of neuromorphic computing beyond the von Neumann architecture. By mimicking the operations of brains and integrating the memory and processing units in proximity, a modular, parallel, distributed and scalable computing system may be realized with lower power consumptions and large bandwidth. Neuromorphic computing is revolutionary and excels at computing complex spatial-temporal dynamics with plasticity and fault-tolerance. Marching towards the realization of neuromorphic computing has a natural reference from the mature development ecosystem for von Neumann computers with the CMOS technology. The fundamental devices, the circuit and system designs and the electronic design automation algorithms form a stable and mutual supportive ecosystem which is believed to play an important role in the technology developments.
This Research Topic aims to archive the most recent advancements in the devices, circuits and system, as well as the electronic design automations (EDA) for the neuromorphic computing. While there are many research and development activities in the fields, the efforts reported in literature are mostly quite scattered. By collecting recent advances in the areas from devices to circuit designs and EDA, this Research Topic will be a comprehensive platform to discuss different aspects of the neuromorphic computing ecosystem, to identify the challenges facing by the community in its further development, and hopefully to figure out the next milestones for the maturity of the exciting technology.
The scope of the Research Topic includes the neuromorphic circuits (based on integrations of CMOS technology or emerging device technologies for functional, brain-like systems), and the EDA algorithms and tools (for the hierarchical implementations of the neuromorphic computing blocks). The term of 'neuromorphic' here specially means 'brain-like', which uses the hardwares to emulate the synaptic and neural dynamics in the event-driven manner with spikes.
Topics of interests include, but are not limited to:
-Hardware circuits for spiking neural network (SNN)
-Algorithm-hardware co-design for SNN circuits
-Design and simulation of neuromorphic circuits
-Synthesis and verification of neuromorphic systems
-System technology co-optimization for neuromorphic systems
Note that pure device papers without or with only simply mentioned applications in neuromorphic circuits and systems are not in the scope of this Research Topic. Circuits and systems of the real-valued computation in the deep-learning paradigm are also out of the scope.
