Yang Hu

Dr. Yang Hu is currently an Associate Professor in the School of Integrated Circuits at Tsinghua University. He receives his BS degree from Tianjin University in 2007, and his MS degree from Tsinghua University in 2011, and his Ph.D. degree from the University of Florida in 2017. He was a tenure-track assistant professor in the ECE department at University of Texas at Dallas from 2017 to 2021. His research mainly focused on the network-oriented domain-specific architecture, co-optimization of memory/computing system for AI, and hardware security of heterogeneous system. The research projects had been funded by more than 1 million dollars. Dr. Hu now works on high-performance AI chip architecture and compilation tools.


Dr. Hu is an NSF CAREER Awardee. He has published more than 40 papers in computer architecture conferences and journals such as ISCA, HPCA, ASPLOS, MICRO, SC, DAC, ICS, RTAS, ICPP, ICCD, IEEE-TCAD, IEEE-TC, and IEEE-TPDS. His research work has won Best Paper Nomination of HPCA in 2017 and 2018. He received the Best of IEEE Computer Architecture Letters Award in 2015. He is an Associate Editor of Elsevier Chip Journal. He served as TPC track chair of DAC, and TPC member of HPCA, DAC, IWQoS, ISPASS, ICPP, ICDCS, IPDPS, and etc.. He served as NSF panelists and external reviewer of Hongkong Research Grant Council. He also served as session chair of HPCA 2022 and registration chair of ICS 2018.


5G-enabled applications pose diverse processing requirements to the network infrastructure. We examine the service function chain consolidation on heterogeneous server platform by looking into the detailed element-level CPU and GPU mapping. We summarize critical overheads and we propose NFCompass, which exploits two core techniques to minimize the performance overheads caused by SFC consolidation on the heterogeneous server platform.