Daehyeok Kim
Keeping Up with AI’s Increasingly Complex Networking Demands

09/24/2024 - The job of building computer networks that train and run large AI models is becoming increasingly complicated because traditional network designs can’t operate at the higher speeds that the AI workloads require and need to be tuned to a variety of communication endpoints (such as CPUs, graphics processing units and AI accelerators) that have widely different characteristics, including data generation speeds. Moreover, AI workloads require advanced network monitoring capabilities to quickly diagnose and resolve performance bottlenecks.
NSF Funded Expedition Project Uses AI to Rethink Computer Operating Systems

05/23/2024 - Aditya Akella leads the project that aims to boost performance of OSes and help enable assistant robots, autonomous vehicles and smart cities.