Deep neural networks (DNNs), as a subset of machine learning (ML) techniques, entail that real-world data can be learned, and decisions made in real time. However, their wide adoption is hindered by number software hardware limitations. The existing general-purpose platforms used to accelerate DNNs are facing new challenges associated with the growing amount exponentially increasing complexity ...

Resistive memories are outstanding electron devices that have displayed a large potential in plethora of applications such as nonvolatile data storage, neuromorphic computing, hardware cryptography, etc. Their fabrication control and performance been notably improved the last few years to cope with requirements massive industrial production. However, most important hurdle progress their develop...