Professor Wang, Cho-Li

BS Nat. Taiwan; MS, PhD S. Calif
BEng(CE) Programme Coordinator; Professor

Tel: (+852) 2857 8458
Fax: (+852) 2559 8447
Email: clwang [AT] cs [DOT] hku [DOT] hk
Homepage: https://www.cs.hku.hkhttps://www.cs.hku.hk/~clwang


Professor Cho-Li Wang received his B.S. degree in Computer Science and Information Engineering from National Taiwan University in 1985. He obtained his M.S. and Ph.D. degrees in Computer Engineering from University of Southern California in 1990 and 1995 respectively. He is currently a professor at the Department of Computer Science. Professor Wang's research interests include parallel architecture,operating system,performance optimization on heterogeneous multicore systems (GPU/AI chips);high-performance software systems for Cloud Computing, and large-scale Distributed Deep Learning system. Professor Wang has published more than 170papers in various peer reviewed journals and conference proceedings. He is/was on the editorial boards of several international journals , including IEEE Transactions on Computers (TC), IEEE Transactions on Cloud Computing, Multiagent and Grid Systems (MGS), Journal of Information Science and Engineering (JISE), International Journal of Pervasive Computing and Communications (JPCC), ICST Transactions on Scalable Information Systems (SIS). He was the program chair for Cluster'03, CCGrid'09, InfoScale'09, and ICPADS'09, ISPA'11, FCST'11, FutureTech'12, and Cluster2012; and the General Chair for IPDPS2012. He has also served as program committee members for numerous international conferences, including IPDPS, CCGrid, Cloud, CloudCom, Grid, HiPC, ICPP, and ICPADS. He is currently a member of China's Supercomputing Innovation Alliance(超级计算创新联盟) andan executivemember of IEEE Technical Committee onParallel Processing (TCPP). He has been invited to give keynote and plenary talk s related to Distributed JVM design and Cloud Computing at various international conferences.

Research Interests

Operating Systems, Virtual Machines and Cloud Computing, Big Data Computing systems, Performance optimization on Manycore,GPU and AI chips, Large-scale Distributed Deep/Machine Learning Systems.

Selected Publications

Zhaorui Zhang, Cho-LiWang, ``SaPus: Self-Adaptive Parameter Update Strategy for DNN Training on Multi-GPU Clusters,'' IEEE Transactions on Parallel and Distributed Systems (TPDS), Vol. 33, No. 7, July 2022, pp. 1569-1580. (Link)
Zhaorui Zhang, Zhuoran Ji, Cho-LiWang, ``Momentum-Driven Adaptive Synchronization Model for Distributed DNN Training on HPC Clusters,'' Journal of Parallel and Distributed Computing (JPDC),Vol. 159, January 2022, Pages 65-84. (Link).
Zhuoran Ji and Cho-Li Wang, "CTXBack: Enabling Low Latency GPU Context Switching via Context Flashback", 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS’21), 17-21 May 2021. (Link)
Zhuoran Ji and Cho-Li Wang, "Accelerating DBSCAN Algorithm with AI Chips for Large Datasets", 50th International Conference on Parallel Processing (ICPP’21), Aug. 9-12, 2021, Chicago, Illinois, USA. (Link)
Zhuoran Ji and Cho-Li Wang, "Collaborative GPU Preemption via Spatial Multitasking for Efficient GPU Sharing", 27th International European Conference on Parallel and Distributed Computing (Euro-Par'21), 30 Aug. – 3 Sept. 2021.
Xin Yao and Cho-Li Wang, Probabilistic Consistency Guarantee in Partial Quorum-based Data Store, IEEE Transactions on Parallel and Distributed Systems (TPDS), Volume 31, Issue 8, Aug. 2020, Page 1815 – 1827.
Huanxin Lin, Cho-Li Wang. On-GPU Thread-Data Remapping for Nested Branch Divergence, Journal of Parallel and Distributed Computing, Volume 139, May 2020, Pages 75-86.
Hao Wu, Weizhi Liu, Huanxin Lin, and Cho-Li Wang, A Model-Based Software Solution for Simultaneous Multiple Kernels on GPUs, ACM Transactions on Architecture and Code Optimization (TACO), Volume 17, Issue 1, March 2020.
Huanxin Lin, Cho-Li Wang, Efficient Low-Latency Packet Processing Using On-GPU Thread-Data Remapping, Journal of Parallel and Distributed Computing (JPDC), Volume 133, November 2019, Pages 51-62.
Xin Yao, Xueyu Wu, Cho-Li Wang, "FluentPS: A Parameter Server Design with Low-frequency Synchronization for Distributed Deep Learning", 2019 IEEE International Conference on Cluster Computing (Cluster 2019),Sept 23-26. 2019,Albuquerque, NM, USA.
Xin Yao, Mingzhe Zhang, Cho-Li Wang, EC-Shuffle: Dynamic Erasure Coding Optimization for Efficient and Reliable Shuffle in Spark, The 19th Annual IEEE/ACM International Symposium in Cluster, Cloud, and Grid Computing (CCGrid 2019), Larnaca, Cyprus, May 14-17, 2019.
Huanxin Lin, Cho-Li Wang, Hongyuan Liu, “On-GPU Thread-Data Remapping for Branch Divergence Reduction,” ACM Transactions on Architecture and Code Optimization (TACO), Vol. 15, No. 3, Oct. 2018.
Mingzhe Zhang, King Tin Lam, Xin Yao, Cho-Li Wang, SIMPO: A Scalable In-Memory Persistent Object Framework Using NVRAM for Reliable Big Data Computing, ACM Transactions on Architecture and Code Optimization (TACO), Volume 15 Issue 1, April 2018.
Hongyuan Liu, King Tin Lam, Huanxin Lin, Cho-Li Wang, Junchao Ma, Lightweight Dependency Checking for Parallelizing Loops with Non-Deterministic Dependency on GPU, The 22nd IEEE International Conference on Parallel and Distributed Systems (ICPADS 2016), Dec. 13-16, 2016, Wuhan, China. [Best Paper Awards]
Zhiquan Lai, King Tin Lam, Cho-Li Wang, and Jinshu Su, PoweRock: Power Modelling and Flexible Dynamic Power Management for Many-core Architectures, IEEE Systems Journal, Issue: 99, pp. 1-13, 20 January 2016.
Sheng Di, Cho-Li Wang, Franck Cappello, Adaptive Algorithm for Minimizing Cloud Task Length with Prediction Errors, , IEEE Transactions on Cloud Computing, Vol.2, No.2, pp 194 - 207, April-June 2014
S. Di and C.L. Wang, Dynamic Optimization of Multi-Attribute Resource Allocation in Self-Organizing Clouds, IEEE Transactions on Parallel and Distributed Systems (TPDS), 14 May 2012
S. Di and C.L. Wang, Decentralized Proactive Resource Allocation for Maximizing Throughput of P2P Grid, Journal of Parallel and Distributed Computing (JPDC), Vol. 72, No. 2, February 2012, pp. 308–321

Recent Research Grants

Co-PI: Hong Kong RGCResearch Impact Fund (RIF) project entitled “Edge Learning: the Enabling Technology for Distributed Big Data Analytics in Cloud-Edge Environment” (Ref: R5060-19), led by Prof. Guo Songfrom PolyU. Project period: May 01, 2020 to April 30, 2025.
Co-PI: CRF Equipment Fund 2019/20,“X-GPU: An Extreme GPU Cluster for Interdisciplinary Research on Molecular Dynamics Simulations and Genomics Studies”, led by Dr. Xuhui Huang from HKUST.
Co-PI: Hong Kong RGC Collaborative Research Fund (C5026-18G) entitled ``Multi-stage Big Data Analytics on Complex Systems: Methodologies and Applications', led by Prof. Jiannong Caofrom PolyU. Period: June 28, 2019 to June 27, 2022.
RGC's General Research Fund (2016-2019): Big-Little Heterogeneous Computing with Polymorphic GPU Kernels
RGC's General Research Fund (2015-2018): Software Architecture for Fault-Tolerant Multicore Computing with Hybridized Non-Volatile Memories
Huawei research grant (2015-2017): Big Data Acceleration on GPU-based Heterogeneous Architecture
RGC's General Research Fund (2012-2015): Scalable Cloud-on-Chip Runtime Support with Software Coherence for Future 1000-Core Tiled Architectures.
Huawei research grant (2012-2013): A New Multikernel OS for High Throughput Computing on Manycore Systems
RGC's General Research Fund (2011-2013): Transparent Runtime and Memory Coherence Support for GPU Based Heterogeneous Many-Core Architecture.
China 863 Project (2006-2010): 香港大学网格自适应服务技术研究 (CNGrid HKU Grid Point).