Memory devices and applications for in-memory computing
Traditional von Neumann computing systems involve separate processing and memory
units. However, data movement is costly in terms of time and energy and this problem is …
units. However, data movement is costly in terms of time and energy and this problem is …
In-memory computing with resistive switching devices
Modern computers are based on the von Neumann architecture in which computation and
storage are physically separated: data are fetched from the memory unit, shuttled to the …
storage are physically separated: data are fetched from the memory unit, shuttled to the …
A survey of deep neural network architectures and their applications
Since the proposal of a fast learning algorithm for deep belief networks in 2006, the deep
learning techniques have drawn ever-increasing research interests because of their …
learning techniques have drawn ever-increasing research interests because of their …
2022 roadmap on neuromorphic computing and engineering
DV Christensen, R Dittmann… - Neuromorphic …, 2022 - iopscience.iop.org
Modern computation based on von Neumann architecture is now a mature cutting-edge
science. In the von Neumann architecture, processing and memory units are implemented …
science. In the von Neumann architecture, processing and memory units are implemented …
Neuromorphic computing using non-volatile memory
Dense crossbar arrays of non-volatile memory (NVM) devices represent one possible path
for implementing massively-parallel and highly energy-efficient neuromorphic computing …
for implementing massively-parallel and highly energy-efficient neuromorphic computing …
[HTML][HTML] Deep learning with spiking neurons: opportunities and challenges
M Pfeiffer, T Pfeil - Frontiers in neuroscience, 2018 - frontiersin.org
Spiking neural networks (SNNs) are inspired by information processing in biology, where
sparse and asynchronous binary signals are communicated and processed in a massively …
sparse and asynchronous binary signals are communicated and processed in a massively …
Embodied neuromorphic intelligence
The design of robots that interact autonomously with the environment and exhibit complex
behaviours is an open challenge that can benefit from understanding what makes living …
behaviours is an open challenge that can benefit from understanding what makes living …
Neuromorphic photonic networks using silicon photonic weight banks
Photonic systems for high-performance information processing have attracted renewed
interest. Neuromorphic silicon photonics has the potential to integrate processing functions …
interest. Neuromorphic silicon photonics has the potential to integrate processing functions …
A scalable multicore architecture with heterogeneous memory structures for dynamic neuromorphic asynchronous processors (DYNAPs)
Neuromorphic computing systems comprise networks of neurons that use asynchronous
events for both computation and communication. This type of representation offers several …
events for both computation and communication. This type of representation offers several …
In-memory mechanical computing
Mechanical computing requires matter to adapt behavior according to retained knowledge,
often through integrated sensing, actuation, and control of deformation. However, inefficient …
often through integrated sensing, actuation, and control of deformation. However, inefficient …