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In recent years, Artificial Intelligence (AI) has been widely deployed in a variety of business sectors and industries, yielding numbers of revolutionary applications and services that are primarily driven by high-performance computation and storage facilities in the cloud. On the other hand, embedding intelligence into edge devices is highly demanded by emerging applications such as autonomous systems, human-machine interactions, and the Internet of Things (IoT). In these applications, it is advantageous to process data near or at the source of data to improve energy & spectrum efficiency and security, and decrease latency. Although the computation capability of edge devices has increased tremendously during the past decade, it is still challenging to perform sophisticated AI algorithms in these resource-constrained edge devices, which calls for not only low-power chips for energy efficient processing at the edge …