The CCF Distributed Computing Conference (CCF Computility 2024) and the National Conference on Open Distributed and Parallel Computing (DPCS 2024) will be held in Changchun, Jilin Province, China from July 26 to 28, 2024, with an estimated conference size of more than 1,000 people. The theme of this conference is "Computing Network: Distributed System in the Context of New Quality Productivity", which aims to provide the most professional platform for academic discussions, technical exchanges and achievement display for practitioners related to distributed systems and computing power networks. CCF Computility 2024 has prepared 9 keynote reports by academicians and other top experts, and 15 technical forums (80 invited reports), which are definitely not to be missed!
CCF Computility 2024 | 学术盛宴，大咖云集，不容错过！
Keynote speaker of the conference
Background of the Forum
In the era of digital economy, computing resources have become the core productivity of the digital economy and the new engine of digital economic growth. In order to synergize ubiquitous computing resources and build new advantages in the development of the digital economy, a new type of information infrastructure called computing network came into being, aiming to provide efficient and flexible computing services, which is considered to be a key technology to empower future artificial intelligence. However, the computing power network still faces problems such as the imbalance between the supply and demand of computing resources, the linkage between the upstream and downstream of the industrial chain, the lack of deep integration, the rapid growth of computing power energy consumption and the high cost of user use. Therefore, this forum will deeply discuss the development trend and difficult key issues of the computing economy, promote the extensive attention and in-depth research of universities and enterprises on the computing economy, promote the cost reduction, efficiency improvement and income increase of the computing network, and realize the high-quality and sustainable development of the computing network.
| Computing Economy Forum Report Arrangement | ||
| Chair of the Forum | Professor Huang Jianwei, Associate Professor Ma Qian, and Researcher Zhang Meng | |
| Invited Presentation1 | Shan Zhiguang is the director of the Department of Informatization and Industrial Development of the State Information Center | Intelligent Computing and "Computing Network" |
| Invited Presentation 2 | Deng Xiaotie is the director of the Computational Economics Group of CCF and the chair professor of the Center for Frontier Computing Research, School of Computer Science, Peking University | GPU pricing |
| Invited Presentation 3 | Zhao Junhua is a professor at the School of Science and Engineering, Hong Kong Chinese University (Shenzhen). | AI-driven low-carbon energy economics |
| Invited Presentation4 | Qi Qi is the secretary general of the CCF Computational Economics Professional Group and a tenured associate professor at the Hillhouse School of Artificial Intelligence, Renmin University of Chinese | Computing power empowers the computing economy |
| Invited Presentation 5 | Haiming Jin is an associate professor in the Department of Computer Science and Engineering, Shanghai Jiao Tong University | Research on the method of intelligent order distribution of online car-hailing |
| Time: July 28, 2024 afternoon Venue: Anhua Holiday Banquet Center, Changchun City, Jilin Province |
Forum Chair & Introduction
Huang Jianwei
Hong Kong Chinese University (Shenzhen)
Jianwei Huang is Presidential Chair Professor and Associate Vice President of the University of Hong Kong, Chinese Shenzhen, Vice President and Director of the Swarm Intelligence Research Center of Shenzhen Institute of Artificial Intelligence and Robotics, Editor-in-Chief of IEEE Transactions on Network Science and Engineering, Changjiang Scholar Distinguished Professor of the Ministry of Education, IEEE Fellow, and Clarivate Analytics Global Highly Cited Scientist in the field of computer science. His research interests include wireless networks, swarm intelligence, and network economics.
Ma Qian
Sun Yat-sen University
Ma Qian is an associate professor at Sun Yat-sen University. He received his bachelor's and doctoral degrees from Beijing University of Posts and Telecommunications and the Chinese University of Hong Kong, and was a postdoctoral fellow at Chinese University of Hong Kong and Northeastern University, respectively. His research interests include computing power networks, edge computing and cloud computing, distributed artificial intelligence, network optimization, and network economics. He has published more than 30 papers in international high-level journals and conferences such as IEEE/ACM ToN, IEEE TMC, POM, ACM MobiHoc, etc., and has won the IEEE WiOpt 2021 Best Paper Award and the IEEE WiOpt 2015 Best Student Paper Award. He has presided over national longitudinal scientific research projects such as the general project and youth project of the National Natural Science Foundation of China, and the sub-project of the Young Scientist Project of the National Key R&D Program, and participated in the joint fund projects of the National Natural Science Foundation of China and the National Key R&D Program.
Zhang Meng
Zhejiang University
Meng Zhang, a researcher and tenured assistant professor at Zhejiang University of Illinois at Urbana-Champaign (ZJUI), was selected into the National High-level Young Talents Program. Adjunct Assistant Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. He graduated from the Department of Information Engineering of the University of Hong Kong Chinese in 2019 with a Ph.D., and worked as a Postdoctoral Fellow in the Department of Electrical and Computer Engineering at Northwestern University from 2020 to 2022, and joined ZJUI in January 2022. In 2018-2019, he was a visiting scholar at the Department of Electrical Engineering, Princeton University. His main research interests are wireless and computer networks, intelligent network optimization, edge intelligence and distributed machine learning, and he has made a series of research achievements in cutting-edge topics such as multi-real-time communication and computing, real-time data privacy protection, and network and data economics. In 2021, he won the IEEE/IFIP WiOpt Best Paper Award. Academic part-time: TPC: INFOCOM, ICC, WCNC, WiOPT Top journal reviewers: IEEE/ACM ToN, IEEE TMC, IEEE JSAC, IEEE TWC, IEEE INFOCOM, WiOpt, etc.
Presentation of the guests and the presentation
Shan Zhiguang
State Information Center of the People's Republic of China
Shan Zhiguang, Director of the Department of Informatization and Industrial Development of the State Information Center, Second-level Researcher, Director of the China Smart City Development Research Center, Director of the Smart City Development Research Center, and Director of the Future Industry and Platform Economy Research Center. Chairman of the Digital Economy Forum, Secretary-General of the Secretariat of the Inter-ministerial Coordination Working Group for the Construction of New Smart Cities, Secretary-General of the National Expert Advisory Committee for Big Data Development, and Chairman of the Blockchain Service Network (BSN) Development Alliance. He is a national-level candidate for the New Century Millions of Talents Project and enjoys the special government allowance of the State Council.
Title: Intelligent Computing and "Computing Network"
Abstract: This paper introduces the development trend and application requirements of intelligent computing, expounds the concept, effect analysis, necessity and practical significance of the construction of the intelligent computing center, analyzes the overall architecture, technology evolution path, construction architecture and technical route of the intelligent computing center, discusses the necessity, main characteristics, service architecture, service content, service ecology and promotion strategy of public intelligent services, puts forward the misunderstandings and deviations in the construction of the national integrated computing power system, and analyzes the open challenges still faced at the practical level. Suggestions for scientifically promoting the integrated computing power network are put forward.
Deng Xiaotie
Peking university
Deng Xiaotie is the director of the Computational Economics Group of CCF, the chair professor of the Center for Frontier Computing Research of the School of Computer Science of Peking University, the executive director of the Center for Frontier Computing of Peking University, and the director of the Center for Multi-agent of the Institute of AI. He has taught at Shanghai Jiao Tong University, the University of Liverpool, the City University of Hong Kong and the University of York. His research interests include algorithmic game theory, blockchain, Internet economy, online algorithms and parallel computing. In 2008, he was elected an ACM Fellow for his contributions to the field of algorithmic game theory. In 2019, he was elected as an IEEE Fellow for his contributions to the fields of incomplete information computing and interactive environment computing. In 2020, he was elected as a Foreign Member of the European Academy of Sciences; In 2021, he was elected as a Fellow of the Chinese Society of Industrial and Applied Mathematics (CSIAM Fellow); In 2021, he was appointed as a member of the Board of Directors of the Game Theory Society (GTS); In 2021, he was appointed as an honorary director of the Game Theory Branch of the Operations Research Society of China; In 2021, he won the CCF Society for Artificial Intelligence Multi-agent and Multi-agent System Research Achievement Award; In 2022, he won the "Test of Time Award" from ACM Computational Economics. As a project leader, he has undertaken dozens of research projects in Canada, Hong Kong, the United Kingdom and the National Foundation of China, and served on the editorial boards of various international journals. Deng Xiaotie has served as the chairman of several international academic conferences, and initiated the International Conference on Web and Internet Economics (WINE) and the International Joint Conference on Theoretical Computer Science (IJTCS), which are held by Asia, Europe and the United States. He has won the FOCS Best Paper Award of the IEEE Theoretical Computer Science Conference; His work "Research on Several Classical Problems of Graph and Combinatorial Optimization" won the second prize of the 2015 Outstanding Scientific Research Output Award (Natural Science) of Colleges and Universities.
报告题目：GPU pricing
Report Summary: High-performance GPUs are essential to accelerate large AI model tasks, but their allocation and pricing are complex due to resource scarcity and high demand. In such a proprietary computing system, resource allocation strategies for various factors, workloads, user needs, and system utilization, as well as job scheduling and resource pooling techniques all play a role in improving efficiency. A cost, market, and value-based pricing model to ensure that the price reflects the technical and performance advantages of GPUs is a key scientific challenge in current research to provide decision support for optimal use of resources and cost-effectiveness.
Zhao Junhua
Hong Kong Chinese University (Shenzhen)
Dr. Zhao Junhua is a professor at the School of Science and Engineering of the University of Chinese Hong Kong, Shenzhen, the director of the New Energy Science and Engineering Program, the director of the Energy Market and Energy Finance Laboratory of the Shenzhen Finance Institute, the executive director of the China-Singapore Joint Research Center for Smart Energy Storage, and the co-director of the Taurus Asset Management Research Center of the Shenzhen Institute of Data Economy. He has long been engaged in research in the fields of smart grid, energy economy, low-carbon transition, and artificial intelligence. In 2023, he was elected as a Fellow of the Institution of Engineering and Technology (IET), and from 2021 to 2022, he was consecutively selected as "China Highly Cited Researcher" by Elsevier. From 2020 to 2022, he was consecutively selected as one of the "Top 2% Scientists in the World" by Stanford University. In 2017, he was awarded the Young Scientist of the Future by the ADC Forum in Australia. He has won the Hunan Provincial Science and Technology Progress Award twice, the Zhejiang Natural Science Award once, the "Electric Power Science and Technology Innovation Award" of the China Electricity Council once, and the Most Influential Paper of the Year Award of the International Journal Energy Conversion and Economics in 2020. He has published more than 300 research papers, including one in Joule, one in Patterns, two in Scientific Data, and more than 60 in IEEE Transactions. Google Scholar has been cited more than 15,000 times, and the Google h-factor is 61.
Title: AI-Driven Low-Carbon Energy Economics
Report Summary: Controlling carbon emissions and delaying climate change is a major issue related to the fate of mankind. The energy sector is the single largest source of greenhouse gas emissions. How to use economic means to achieve the low-carbon transformation of the energy industry is a research topic of great significance. This lecture preliminarily discusses how to solve several key problems in the low-carbon transformation of energy and power systems based on artificial intelligence technology, including user behavior understanding, real-time emission measurement of enterprises, and simulation of market transaction behavior.
祁琦
Chinese People's University
Qi Qi, Secretary General of CCF Computational Economics Professional Group, tenured associate professor and doctoral supervisor of Hillhouse School of Artificial Intelligence, Chinese University, national overseas high-level young talents, Secretary General of Computational Economics of CCF China Computer Federation. He received his Ph.D. from Stanford University under the supervision of Professor Ye Yinyu. He was an assistant professor at the Hong Kong University of Science and Technology. His main research interests are algorithmic game theory, large model autonomous agents, mechanism design, multi-agent and optimization. He has published more than 50 papers in world-class computer, artificial intelligence, and management journals and conferences, including OR, MOR, GEB and other journals, as well as STOC, WINE, CCC, NeurIPS, KDD and other computer conferences. He has presided over the National High-level Talent Scheme and a number of research projects of the Science Foundation of Hong Kong. He is a senior program committee member and co-chair of several international conferences in the field of artificial intelligence, Internet and gaming. Two U.S. patents were granted for the research and application of Internet advertising.
Title: Computing Power Empowers the Computing Economy
Report Summary: With the advent of the era of large models, computing power has become the core force to promote changes in various fields. Powerful computing power provides a solid foundation for the construction and analysis of complex economic models, enabling us to understand and predict economic phenomena more deeply. Through efficient computing power, we can process massive economic data, mine potential laws and trends, and provide a more scientific and accurate basis for policy formulation and enterprise intelligent decision-making. This report will discuss the role of computing power in computational economics, with a particular focus on its application in the advertising auction mechanism and the optimal allocation of social resources. In the field of advertising auctions, powerful computing power can quickly process and analyze large amounts of data, accurately evaluate the value of advertisements and participants' behaviors, so as to optimize the auction process and improve the efficiency and effectiveness of advertising. In terms of resource allocation, computing power enables us to simulate and calculate complex scenarios in real time through agent-based model methods, helping to achieve optimal allocation of resources and improve resource utilization efficiency. Through the empowerment of computing power, the advertising auction mechanism and resource allocation mechanism have been continuously improved and innovated, providing strong support for the orderly development of economic activities and the rational use of resources, and promoting computational economics to achieve more significant results and progress in these specific application scenarios.
Kim Hae-myung
Shanghai Jiao Tong University
Jin Haiming is currently an associate professor in the Department of Computer Science and Engineering at Shanghai Jiao Tong University, deputy director of the John Hopcroft Computer Science Center, and doctoral supervisor. Jin Haiming has been engaged in research in the direction of Internet of Things and mobile computing for a long time, and has published and accepted more than 60 academic papers in well-known international journals such as TON, TMC, JSAC, and well-known international conferences such as SenSys, INFOCOM, UbiComp, and MobiHoc. He has won the CCF-Didi Gaia Young Scholars Research Fund Outstanding Project Award, the INFOCOM Outstanding Program Member Award, the Best Report Award of the China-Japan-Korea A3 Prospective Project Forum, the Best Paper Nomination of the CCF Class A Conference INFOCOM, and was selected into the list of the world's top 2% scientists in 2023.
Title: Research on the intelligent order distribution method of online car-hailing
Report Summary: Ride-hailing is a new type of transportation based on Internet technology, which is very popular around the world because of its advantages such as high matching efficiency and good passenger experience. This report will introduce the four work of this research group with the theme of intelligent order distribution of online car-hailing. In the first work, we propose an adaptive order distribution method for order distribution, and design a spatiotemporal hierarchical adaptive order sharing framework to solve the problem of poor aggregation effect of existing multiplication orders. We prove that there is no deterministic or random online algorithm for the problem of adaptive order splitting interval, and the experimental results show that the proposed method significantly improves the return of platform multiplication and single splitting. In the second work, we propose a single-order sharing method to ensure the fairness of drivers, and design a constraint-based multi-agent reinforcement learning framework to solve the problem of unfairness of the existing single-sharing methods. We prove that the algorithm converges to a stable point at a sublinear rate, and the experimental results show that the proposed method can improve the long-term revenue of the platform while reducing the revenue gap of drivers. In the third work, we propose a configurable single-sharing method with platform preference, and design a multi-objective multi-agent reinforcement learning framework to solve the problem of conflicting goals between multiple single-sharing objectives. We demonstrate the convergence and sample complexity of the algorithm, and the experimental results show that the Pareto plane constructed by the proposed method is better than the existing baseline method. In the fourth work, we propose a generalizable order division method for platform scenarios, and design a multi-scenario multi-agent reinforcement learning framework for the diversification of supply and demand distribution in different scenarios. We theoretically analyze the optimality gap and constraint violation degree of the strategy in the new scenario, and the experimental results show that the strategy obtained by the proposed method has a good generalization ability for the new scenario.
How to register for the conference
1. Registration Criteria
| Ticket type: | Participant Identity | 6.1~7.28 |
| Conference registration fee | Professional Member of CCF | ￥2700 |
| CCF Student Member | ￥1700 | |
| Non-Member Professionals | ￥3200 | |
| Non-member students | ￥2200 |
2. How to register
| Conference registration QR code | QR code for the homepage of the conference |
Note: The conference is paid through the CCF conference management system, and the refund shall comply with the "CCF Regulations on the Refund of Conference Registration Fees".
For the specific arrangements of the above forums, please pay attention to the official website of the conference. In addition to the keynote speeches and this forum, CCF Computility 2024 will also organize 14 unique thematic forums, each of which will be chaired by top experts to bring you the most cutting-edge academic discussions and technical exchanges.
At present, the preparatory work of the conference is nearing the end, and scholars in the field of distributed computing are welcome to come to Changchun to witness and promote technological innovation.