In recent years, the development of Systems on Chip (SoCs) is facing increasing challenges, which are starting to expose the limitations of current design philosophies. In spite of many conservative measures, often at the expense of computational efficiency, realising a functional SoC has come to require tens of Millions USD. Such a tendency threatens to hinder innovation and keeps away applications that require the efficiency of ASIC. Among them, a prime example are Artificial Neural Networks (ANNs), which have become one of the most popular research topics and already see many commercial applications in countless fields. The increasing complexity of ANNs makes them quite demanding in terms of computational power, so the inefficient approach of modern SoCs is quickly becoming unsuited for them.