Kyushu University, Japan
Toward Edge-Cloud Energy Efficient AI Accelerations
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.
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.
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