Important Dates

Special Session

30 June, 2022

Paper Submission

September 01, 2022
September 20, 2022

Author Notification

September 24, 2022
October 24, 2022

Final Manuscript Due

10 November, 2022

Conference Date

18-20 December, 2022
18-21 December, 2022


Keynote Speakers

Coming soon

Depei Qian

Building China’s next generation computing infrastructure


ABSTRACT: This talk begins with a brief review of HPC development in China in the past decades and a discussion on the role of computing in enabling problem-solving. The new demands and challenges raised by big data (BD) and artificial intelligence (AI) applications to computing are presented. Some critical issues in establishing the computing the next computing infrastructure under the circumstance of “East-west Computing transfer” strategic project are discussed. Finally, the task of building CNGrid-NG, the next generation supercomputing infrastructure of China is proposed.

BIO: Qian Depei, professor of Beihang University, fellow of CCF, academician of Chinese Academy of Sciences. He has served as a member of the expert group of the National High-tech R&D Program (the 863 program) and the National Key R&D Program in information technology since 1996 and led several key national projects on high performance computing.

He has been working on computer architecture and computer networks for many years. His current research interests include high performance computer architecture and implementation technologies, distributed systems, network computing, and multicore/manycore programing. He has published more than 400 papers in journals and conferences.

Minyi Guo

On the Three Layers of Sustainable Computing: Challenges and Opportunities


ABSTRACT: Climate change and energy crisis are two of the biggest global issues of our time. It is critical to develop computing techniques that do not compromise the wellbeing of future generations. To reduce IT carbon footprint, and to support emerging data-analytic workloads that tend to scale well with large number of compute nodes, there is a heightening demand for green high-performance computing and communication systems. In this talk we would like to share our views on the design methodologies for sustainable computing. We divide sustainable computing system design into three layers and present the opportunities that each layer faces. We also discuss the deep challenges that must be addressed in the sustainable computing era. First, a new resource management abstraction for gaining visibility into the underlying infrastructure is needed. In addition, a framework that synergistically combines various software/hardware tuning knobs at each layer is necessary. Finally, it is time to develop appropriate autonomic control schemes to handle the dynamicity and complexity of the cloud. The above methodology constitutes the initial idea of a “Energy-Architecture-Workload” co-designed approach, which will lead to a more environmentally friendly digital infrastructure, as required by the ongoing shift in computing paradigm.

BIO: Prof. Minyi Guo is currently a Zhiyuan Chair Professor at the Department of Computer Science and Engineering of Shanghai Jiao Tong University (SJTU), China, and was the department head from 2009 to 2019. His research spans parallel/distributed computing, computer architecture, compiler optimization, cloud computing, and big data. He received the National Science Fund for Distinguished Young Scholars from NSFC in 2007, and he was appointed as the Chief Scientist of the prestigious 973 Program in 2014. He is the Editor-in-Chief of IEEE Transactions on Sustainable Computing (TSUSC), and he has served as General/Program Chair of many well-established IEEE conferences. Prof. Guo has published 8 books and 500+ publications in premier journals/conferences and a dozen of best paper awards. Prof. Guo has received numerous prestigious government/industry awards, including the Chinese National Award for Technological Invention, and the IEEE TCSC Technical Achievement Award for Excellence in Scalable Computing, etc. He is a foreign member of the Academia Europaea, a Fellow of IEEE and CCF, and an ACM Distinguished Scientist.

Kenli Li

Parallel intelligent processing and application in ultrasonic images


ABSTRACT: Ultrasound (US) imaging is a widely used screening tool for defects examination and prenatal diagnosis. Accurate acquisition of fetal standard planes with key anatomical structures is crucial for substantial biometric measurement and diagnosis. However, the standard plane acquisition is a labour-intensive task and requires operators equipped with a thorough knowledge of fetal anatomy, which leads to a high rate of misdiagnosis in diagnosing fetal malformations. To improve the accuracy and real-time of AI-based systems for automatic ultrasound image detection and quality assessment, various deep learning models are proposed to improve the corresponding accuracy of standard plane interpretation. And different parallel computing models, including pipeline, data parallelism and communication optimization methods, are used to achieve real-time standard plane detection. In addition, we create a novel end-edge-cloud collaborative architecture for ultrasound image interpretation and auxiliary diagnosis to alleviate the workload and boost examination efficiency.

BIO: Kenli Li, Vice President of Hunan University, Member of CCF, the Principal of the High Performance Computing Discipline Innovation Intelligence Introduction Base of the Ministry of Education, the Director of the Engineering Research Center of the Ministry of Education for High Performance Computing Application Software Technology, Vice Chairman of the National Supercomputing Innovation Alliance, Member of the Expert Committee of the New Generation Artificial Intelligence Industry Technology Innovation Alliance, Member of the General Expert Group of the National Key Research and Development Program of High Performance Computing, Chairman of CCF Changsha, Vice Chairman of Hunan Computer Society, Associate Editor of IEEE-TC/TSUSC/TII, editorial board member of "Computer Research and Development". He hosted more than 30 national, provincial and ministerial projects, including the national key research and development plans, and key projects of the Fund Committee. He won the First Prize of National Science & Technology Progress Award for Innovation Team (ranked 13th). His main research areas are parallel and distributed processing, supercomputing and cloud computing, high-performance computing for big data and artificial intelligence, etc.

Zhiwei Xu

Information Superbahn Planet-Scale Low-Entropy High-Goodput Computing Utility


ABSTRACT: The idea of utility computing was proposed 60 years ago by John McCarthy, but now is poised to become a mainstream reality. This talk presents Information Superbahn, a perspective on computing utility, built on experiences of grid computing, services computing, and cloud computing. According to the Information Superbahn perspective, future computing utility should provide worldwide subscribers with four distinct features: (1) pay-per-use services, (2) planet-scale culture, (3) low-entropy systems, and (4) high-goodput utility. Preliminary evidence is provided to reveal the potential of Information Superbahn.

BIO: Zhiwei Xu is a professor at the Institute of Computing Technology, Chinese Academy of Sciences. His research areas include computer architecture and distributed systems. He has led over a dozen priority research projects in supercomputers, distributed systems, and energy-efficient AI processors. Professor Xu holds a PhD degree from University of Southern California.

Xiangyang Li

Industrial Internet of Things: A First Look at Intelligent Sensing, Edge Computing, and Security


ABSTRACT: Industrial Internet is a new generation of intelligent network formed by the deep integration of industrial production system and Internet, and its core is the deep integration application of information and physical system with the integration of perception, communication, analysis, decision-making and control. As a next-generation industrial infrastructure, the Industrial Internet will reshape the entire industrial production and manufacturing system, and form a new intelligent manufacturing system with equipment online, enterprises in the cloud and remote control, which contribute to the digitalization, networking and intellectualization of industrial production. As one of the core supports of Industrial Internet, intelligent IoT has been profoundly changing every aspect of industrial production. The core tasks of IoT are ubiquitous low-power depth perception, wireless-based interconnection of all things, and intelligent data sharing and computing. In this presentation, I will share some challenges of the Industrial Internet, especially the challenges of architecture, intelligent sensing, edge computing, and security. Meanwhile I will share our team's research work in intelligent IoT, including low-power and passive based intelligent sensing, large-scale passive low-power networks, intelligent edge computing, and secure privacy protection for intelligent IoT.

BIO: Xiangyang Li, Professor, Executive Dean of School of Computer Science and Technology, University of Science and Technology of China, ACM Fellow, IEEE Fellow, ACM Distinguished Scientist, former Co-Chair of ACM China, Executive Director of ACM Council, New Venture Chair Professor, Distinguished Young Fund recipient of Foundation Committee, Chief Scientist of National Key R&D Program for IoT Security Project, He has served as Assistant Professor, Associate Professor and Professor at Illinois Institute of Technology, EMC Chair Professor at Tsinghua University, and Visiting Professor at Microsoft Research Asia. He received his master's degree and PhD in computer science from the University of Illinois, and a double degree in computer science and business administration from Tsinghua University. Prof. Xiangyang Li has been engaged in research on Smart IoT, IoT and data security privacy, data sharing and trade.


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