Recently, both industry and academia have proposed several different neuromorphic
systems to execute machine learning applications that are designed using Spiking Neural …

There is a long-standing challenge to narrow the gap between software engineering
research and industrial practice. This gap is reinforced by a number of challenges, including …

The performance of machine-learning applications heavily relies on the choice of the
underlying hardware architecture, encompassing factors such as computational power …