A new wave of intelligent computing, driven by recent advances in machine learning and cognitive algorithms coupled with process technology and new design methodologies, has the potential to usher unprecedented disruption in the way conventional computing solutions are designed and deployed. These new and innovative approaches often provide an attractive and efficient alternative not only in terms of performance but also power, energy, and area.
A key class of these intelligent solutions is providing real-time, on-device cognition at the edge to enable many novel applications including vision and image processing, language translation, autonomous driving, malware detection, and gesture recognition. Naturally, these applications have diverse requirements for performance, energy, reliability, accuracy, and security that demand a holistic approach to designing the hardware, software, and intelligence algorithms to achieve the best power, performance, and area (PPA).
The goal of this workshop is to provide a forum for researchers who are exploring novel ideas in the field of energy efficient machine learning and artificial intelligence for embedded applications. We also hope to provide a solid platform for forging relationships and exchange of ideas between the industry and the academic world through discussions and active collaborations.
To be held in conjunction with the 23rd ACM Intl. Conf. on Architectural Support for Programming Languages and Operating Systems (ASPLOS 2018)