Guest Editorial Energy-Quality Scalable Circuits and Systems for Sensing and Computing: From Approximate to Communication-Inspired and Learning-Based

Sustained energy efficiency improvements have been instrumental for the vertiginous evolution of electronic systems with computing, sensing, communication and storage capabilities. Energy efficiency improvements are indeed crucial for continued increase in the performance under a limited power budget, reduced operating cost, as well as for untethering traditionally wired systems. This is indeed true for high-performance systems subject to heat removal limitations (e.g., server blades), as well as for operational cost considerations when the cost of electricity is a major fraction of the total cost, as in the case of datacenters[1], or the more recent crypto-currency mining endeavors[2]. Energy reductions are also critical in portable electronics, due to the limited thermal budget and battery energy availability. Similarly, energy reductions are essential in miniaturized energy-autonomous systems such as sensor nodes, hearables, wearables and others, due to their tightly constrained energy source[3]. Overall, energy efficiency improvements have historically permitted the continuous size down-scaling and lifetime extension of electronic systems (see,[4]).