Koji Inoue

Kyushu University, Japan

Toward Edge-Cloud Energy Efficient AI Accelerations

Abstract

This talk shares our recent two research activities regarding AI accelerations. The first one targets single-flux quantum (SFQ) devices for AI inference and training. Thanks to the ultra-fast, ultra-low-power features of SFQ logic, we can expect significant power/performance improvements. The other research topic is to support edge-cloud cooperative executions. We have implemented such an execution framework on an IoT platform called My-IoT Platform. With this framework, we can easily install edge-cloud cooperative computing services such as cyber-physical systems and distributed AI inferences.

Biography

Koji Inoue received the B.E. and M.E. degrees in computer science from Kyushu Institute of Technology, Japan in 1994 and 1996, respectively. He received a Ph.D. degree in the Department of Computer Science and Communication Engineering, Graduate School of Information Science and Electrical Engineering, Kyushu University, Japan in 2001. In 1999, he joined Halo LSI Design& Technology, Inc., NY, as a circuit designer. He is currently a professor of the Department of Advanced Information Technology, Kyushu University. His research interests include power-aware computing, high-performance computing, secure computer systems, 3D microprocessor architectures, multi/many-core architectures, nano-photonic computing, superconducting computing, and quantum computing.