| Registration type | Early bird ticket （By November 25th） |
Full fare ticket （After November 25th） |
|
|---|---|---|---|
| General registration attendees are entitled to an additional meal ticket benefit for children under 12 years old. | |||
| International Registration(Accepted papers must use the International registration) | Standard registration including paper publication | US $690.00 | US $760.00 |
| Simple registration including paper publication ( No food and beverage included ) | US $530.00 | US $580.00 | |
| Standard registration not including paper publication | US $490.00 | US $550.00 | |
| Simple registration not including paper publication ( No food and beverage included ) | US $320.00 | US $360.00 | |
| Student registration including paper publication | US $420.00 | US $480.00 | |
| Simple student registration including paper publication (No food and beverage included) | US $260.00 | US $280.00 | |
| Standard student registration not including paper publication | US $280.00 | US $320.00 | |
| Simple student registration not including paper publication ( No food and beverage included ) | US $200.00 | US $230.00 | |
| Group Registration |
Registration method: Please transfer to the following account and send attendees' information (first name, last name, email address, institution) to benchcouncil@bafst.com. Once receiving the registration fees, the registration team will check the information and help finish the group registration. Account Name: HONG KONG AI AND CHIP BENCHMARK RESEARCH LIMITED Account Number: 801-670811-838 Account Address: 6/F Manulife Place, 348 Kwun Tong Road, Kowloon, Hong Kong. Bank Name: The Hongkong and Shanghai Banking Corporation Limited Bank Address: HSBC Main Building, 1 Queen's Road Central, Central, Victoria City, Hong Kong. SWIFT Code: HSBCHKHHHKH |
5 to 10 attendees, 5% discount | |
| 11 to 15 attendees, 10% discount | |||
| 16 to 20 attendees, 15% discount | |||
| Registration Website： | https://eur.cvent.me/5qQEq | ||
| About the refund policy:
1.If canceled by 10/31/2023, the amount refunded would be 100%. 2.If canceled by 11/15/2023, the amount refunded would be 80%. 3.Non-refundable after 11/15/2023. 4.No refund will be provided if the registrant is the only author of an accepted paper who has registered for the conference. Note that multiple papers cannot share the same registration ID. |
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The International Open Benchmark Council (BenchCouncil) is a non-profit international organization dedicated to benchmarks and evaluations.
Since its establishment, BenchCouncil has embraced four core responsibilities: developing the universal sciences and engineering of evaluation across various fields, known as evaluatology and benchmarkology; fostering an open, inclusive, and growing community for benchmarks and evaluations; defining emerging or future multidisciplinary and interdisciplinary challenges through the use of benchmarks; and conducting evaluations of scientific and technological achievements based on evidence.
As a non-profit organization, BenchCouncil relies on your support to sustain its development. You are encouraged to contribute to BenchCouncil's growth by purchasing its commercial tools and services.
Dr. Dhabaleswar K. (DK) Panda is a Professor and Distinguished Scholar of Computer Science at the Ohio State University. He obtained his Ph.D. in computer engineering from the University of Southern California. His research interests include high-performance computing, high-performance networking (InfiniBand), big data analytics (Spark and Hadoop), Deep Learning, cloud computing, Virtualization, GPUs and accelerators, file systems and storage, and exascale computing. He has published over 500 papers in major journals and international conferences related to these research areas. Dr. Panda has served (or serving) as Program Chair/Co-Chair/Vice Chair of many international conferences and workshops including HPCAsia '23, CCGRid '22, SCAsia '22, SCAsia '20, ISC '20, CCGrid '18, ExaComm (15-23), ESPM2 (15-23), HPBDC (15-19), CCGrid '16, PGAS '15, HPBDC '15, HiPC '12, CCGrid '12, HiPC '11, IEEE Cluster (Cluster)'10, Supercomputing (SC)'08, ANCS '07, Hot Interconnect 2007, IPDPS '07, HiPC '07, Hot Interconnect 2006, CAC (2001-04), ICPP '01, CANPC (1997-98) and ICPP '98. He has served as the General Chair/Co-Chair of CCGrid '20, IEEE Micro '19, and ICPP '06. He has served as an Associate Editor of IEEE Transactions on Parallel and Distributed Systems (TPDS), IEEE Transactions on Computers (TC), and Journal of Parallel and Distributed Computing (JPDC). Currently, he is serving as a Co-Editor-in-Chief of CCF Transactions on High-Performance Computing. He has served as Program Committee Member for more than 190 international conferences and workshops. Prof. Panda is a motivated speaker. He has Served as an IEEE Distinguished Visitor and an IEEE Chapters Tutorial Speaker. He has delivered a large number of invited Keynote/Plenary Talks, Tutorials and Presentations Worldwide.
Dr. Panda and his research group members have been doing extensive research on modern networking technologies including InfiniBand, Omni-Path, iWARP, AWS EFA, and RoCE. His research group is currently collaborating with National Laboratories and leading InfiniBand, Omni-Path, iWARP and RoCE companies on designing various subsystems of next generation high-end systems. The MVAPICH (High Performance MPI and MPI+PGAS over InfiniBand, iWARP and RoCE with support for GPGPUs and Virtualization) software libraries , developed by his research group, are currently being used by more than 3,300 organizations worldwide (in 90 countries). These software packages have enabled several InfiniBand clusters to get into the latest TOP500 ranking. As of May '23, more than 1.68M downloads of this software have taken place from the project website alone. These software packages are also available with the software stacks for network vendors (InfiniBand, Omni-Path, RoCE, AWS EFA, iWARP, and Slingshot), server vendors, packages (OpenHPC and Spack), and Linux distributors (such as RedHat and SuSE). This software is currently powering the #7 supercomputer in the world.
Multiple software libraries for Big Data processing and management, designed and developed by the group under High-Performance Big Data (HiBD) Project are available. These include: 1) MPI4Dask for data-science applications, 2) MPI4Spark for big data analytics applications; 3) RDMA-enabled Apache Hadoop Software library providing native RDMA (InfiniBand Verbs and RoCE) support for multiple components (HDFS, MapReduce and RPC) of Apache Hadoop; 4) RDMA-enabled Spark Software library providing native RDMA (InfiniBand Verbs and RoCE) support; 5) RDMA-Memcached Software library for providing native RDMA (InfiniBand Verbs and RoCE) support for Memcached used in Web 2.0 environment; and 5) OSU High-performance Big data Benchmarks (OHB). Sample performance numbers and download instructions for these packages are available from the above-mentioned website. These libraries are currently being used by more than 355 organizations worldwide (in 39 countries). As of May '23, more than 47,400 downloads of this software have taken place from the project website alone.
The group has also been focusing on accelerating Deep Learning (DL) Frameworks (TensorFlow and PyTorch) and Machine Learning (ML) Frameworks on modern HPC clusters and supercomputers. MPI-driven approaches to high-performance and scalable versions of the DL/ML frameworks are available from High-Performance Deep Learning (HiDL) Project site.
Dr. Panda leads Network-Based Computing Research Group . Students and staff members of this group are involved in multiple state-of-the-art research projects . Members of his group have obtained a large number of Awards and Recognitions . Dr. Panda's research is supported by funding from US National Science Foundation, US Department of Energy, US Department of Defense, Ohio Board of Regents, Ohio Department of DEvelopment and several industry including AMD, ARM, Broadcom, IBM, Intel, Cisco, Cornelis Networks, Cray, Oracle, SUN, Mellanox, Microsoft, NVIDIA, Pattern Computer, Rockport Networks, QLogic and NetApp.
Performance analysis and modeling is of critical importance to computer systems and architecture research and development. We must design and build our simulators, benchmarks, and analysis tools correctly, and we must measure and analyze our performance results rigorously, otherwise experimental research and development may lead to incorrect and misleading conclusions and ineffective optimizations. These tools are critical to our understanding of both the problems and the solutions. In this talk, I will revisit the importance of rigorous performance evaluation, and decompose the performance evaluation challenge into two sub-problems, experimental design and data analysis. I will discuss some of the (not so obvious) pitfalls in both experimental design and data analysis, and argue for potential solutions. I will also emphasize the importance of picking the right level of abstraction for steering performance analysis tool as there no one size fits all.
Lieven Eeckhout (PhD 2002) is a Senior Full Professor at Ghent University, Belgium, in the Department of Electronics and Information Systems (ELIS). His research interests include computer architecture, with specific emphasis on performance evaluation and modeling, dynamic resource management, CPU/GPU microarchitecture, and sustainability. He is the recipient of the 2017 ACM SIGARCH Maurice Wilkes Award and the 2017 OOPSLA Most Influential Paper Award, and he was elevated to IEEE Fellow in 2018 and ACM Fellow in 2021. Other awards include three IEEE Micro Top Pick selections (2007, 2010 and 2022), the ISPASS 2013 and MICRO 2023 Best Paper Awards, and Best Paper Nominations at PACT 2014, ISPASS 2012, ISPASS 2014, ISPASS 2015, ISPASS 2016, MICRO 2019, MICRO 2021 and ISCA 2023. He served as the Program Chair for ISCA 2020, HPCA 2015, CGO 2013 and ISPASS 2009, and has served or serves as General Chair for ISPASS 2010, IISWC 2023 and ASPLOS 2025. He served as the Chair of the IEEE Computer So
General Co-Chairs:
Weiping Li, Civil Aviation Flight University of China, China
Tao Tang, BNU-HKBU United International College, China
Frank Werner, Institute of Mathematical Optimization, Otto-von-Guericke-University, German
IC 2023 Program Co-Chairs:
Christophe Cruz, Université de Bourgogne, France
Yanchun Zhang, Victoria University, Australia
Wanling Gao, ICT, Chinese Academy of Sciences, China
Program chairs:
Christophe Cruz, University de Bourgogne, France
Yanchun Zhang, Victoria University, Australia
Wanling Gao, ICT, Chinese Academy of Sciences, China
Program vice-chairs:
Jungang Xu, University of Chinese Academy of Sciences, China
Yucong Duan, Hainan University, China
IC 2023 Area Chairs
AI Algorithms
Hideyuki Takahashi, Department of Data Science, Faculty of Informatics, Tohoku Gakuin University, Japan
Faraz Hussain, Clarkson University, USA
Chunjie Luo, University of Chinese Academy of Science, China
AI Systems
Pengfei Chen, SUN YAT-SEN UNIVERSITY, China
Jason Jia, Amazon, USA
Xiaoguang Wang, University of Illinois Chicago, USA
AI for Ocean Science and Engineering
Guoqiang Zhong, Ocean University of China, China
Hui Yu, University of Portsmouth, UK
AI in Finance
Co-chairs：
Changyun Wang, Renmin University of China, China
Michael Guo, Durham University, UK
Program Co-Chairs：
Zhigang Qiu, Renmin University of China, China
Shinan Cao, University of International Business and Economics, China
AI for Education
John Impagliazzo, Hofstra University, USA
Xuesong Lu, East China Normal University, China
Stéphane Bressan, National University of Singapore, Singapore
AI for Law
Minghui Xiong, ZJU Law & AI Laboratory, Zhejiang University, China
Bart Verheij, Department of Artificial Intelligence, University of Groningen, the Netherlands
AI for Materials Science and Engineering
Siqi Shi, School of Materials Science and Engineering, Shanghai University, China
Turab Lookma, AiMaterials Research LLC, Santa Fe, USA
Yue Liu, School of Computer Engineering and Science, Shanghai University, China
AI for Sciences
Tao Zhou, Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences, China
Weile Jia, Institute of Computing Technology, Chinese Academy of Sciences, China
AI for Civil Aviation
Lin Zou, Civil Aviation Flight University of China, China
AI for Medicine
Co-chairs：
Zhenchang Wang, Beijing Friendship Hospital, Capital Medical University, China
Jie Lu, Xuanwu Hospital, Capital Medical University, China
Jinlyu Sun, Peking Union Medical College Hospital, China
Vice-Chair：
Zhifei Zhang, Capital Medical University, China
AI for Space Science and Engineering
Ziming Zou, National Space Science Center, Chinese Academy of Sciences, China
Liming Song, Institute of High Energy Physics, Chinese Academy of Sciences, China
AI for High Energy Physics
Co-chairs：
Yaodong Cheng, Institute of High Energy Physics, Chinese Academy of Sciences, China
Yaquan Fang, Institute of High Energy Physics, Chinese Academy of Sciences, China
Program Co-Chairs：
Xinchou Lou, University of Texas at Dallas, Dallas & Institute of High Energy Physics (IHEP), China
AI and Security
Bo Luo, University of Kansas, US
Yu Wen, Institute of Information Engineering, Chinese Academy of Sciences, China
Publicity Chairs
Fei Teng, Southwest Jiaotong University, China
Zheng Yuan, Lecturer, King's College London, UK
Roy Lee, Singapore University of Technology and Design, Singapore
Ming Gao, East China Normal University, China
Yuan Cheng, Fudan University, China
Juan Li, Central South University, China
Tianwen Xu, Zhejiang University, China
Yicheng Liao, Zhejiang University, China
Xiao Chi, Zhejiang University, China
Zhengwei Yang, School of Computer Engineering and Science, Shanghai University, Shanghai, China
Han Lv, Beijing Friendship Hospital, Capital Medical University, China
Xiaoyan Hu, National Space Science Center, Chinese Academy of Sciences, China
Yanjie Fu, University of Central Florida, USA
Weiwei Tang, National Space Science Center, Chinese Academy of Sciences, China
Pengyang Wang, University of Macau, China
Haijun Yang, Shanghai Jiao Tong University (SJTU), Shanghai, China
Xingtao Huang, Shandong University (SDU), Qingdao, China
Huilin Qu, the European Organization for Nuclear Research (CERN), Geneva
TPC Members
AI Algorithms
Diego Oliva, University of Guadalajara, Guadalajara, Mexico
Yogendra Arya, J.C. Bose University of Science and Technology, India
Nazar Khan, Punjab University, Pakistan
Yingjie Shi, Beijing Institute of Fashion Technology, China
Sansanee Auephanwiriyakul, Chiang Mai University, Thailand
Xiexue Zhou, Max Planck Institute of Biochemistry, Germany
Zihan Jiang, Huawei, China
AI Systems
Xiaoguang Wang, University of Illinois Chicago, USA
Pengfei Zheng, Huawei Ltd., China
Yushan Su, Princeton University, USA
Runan Wang, Imperial College London, UK
Jindal, Anshul, Technical University of Munich, Germany
Hui Dou, Anhui University, China
Saiyu Qi, Xi’an Jiaotong University, China
Wuxia Jin, Xi’an Jiaotong University, China
Chuan Chen, Sun Yat-sen University, China
Shajulin Benedict, Indian Institute of Information Technology, India
Vishvak Murahari, Princeton University, USA
AI for Ocean Science and Engineering
Partha Pratim Roy, Institute of Technology Roorkee, India
Rachid Hedjam, Sultan Qaboos University, Oman
Xin Li, China University of Petroleum (East China), China
Zhimin Wang, Ocean University of China, China
Chi Zhang, Ocean University of China, China
AI in Finance
George Alexandridis，Reading University, UK
Haoyu Gao, Renmin University of China
Yi Huang, Fudan University, China
Fuwei Jiang, Central University of Finance and Economics, China
Dimitris Petmezas，Durham University, UK
Georgios Sermpinis，Glasgow University, UK
Yanmei Sun, University of International Business and Economics, China
Evangelos Vagenas-Nanos, Glasgow University, UK
Quan Wen, Georgetown University, USA
Ke Wu, Renmin University of China, China
Teng Zhong, University of International Business and Economics, China
Dexin Zhou, CUNY Baruch College, USA
Xiaoneng Zhu, Shanghai University of Finance and Economics, China
Yifeng Zhu, Central University of Finance and Economics, China
AI for Education
Yunshi Lan, East China Normal University, China
Shenggen Ju, Sichuan University, China
Zhenya Huang, University of Science and Technology of China, China
Tiancheng Zhang, Northeastern University, China
Zheng Yuan, King’s College London, UK
Thomas Heinis, Imperial College London, UK
Roy Lee, Singapore University of Technology and Design, Singapore
Sadegh Nobari, Chief Information Officer, Startbahn, Japan
Alison Clear, Eastern Institute of Technology, New Zealand
Tony Clear, Auckland University of Technology, New Zealand
Judith Gal-Ezer, Open University of Israel, Israel
Natalie Kiesler, DIPF | Leibniz-Institute, German
AI for Law
Michal Araszkiewiz, Jagiellonian University, Poland
Wenjing Du, East China University of Political Science and Law, China
Juan Li, Central South University, China
Reka Markovich, University of Luxemburg, Luxemburg
Matthias Grabmair, Technical University of Munich, Germany
Monica Palmirani, University of Bologna, Italy
Bin Wei, Zhejiang University, China
Heng Zheng, University of Illinois Urbana-Champaign, USA
AI for Materials Science and Engineering
Dezhen Xue, State Key Laboratory for Mechanical Behavior of Materials, Xi’an Jiaotong University, China
Jinjin Li,Department of Micro/Nano Electronics, Shanghai Jiao Tong University, China
Lei Li, Department of Materials Science and Engineering, Southern University of Science and Technology, China
Maxim Avdeev, Australian Nuclear Science and Technology Organization, School of Chemistry, The University of Sydney, Australia
Yanjing Su, Beijing Advanced Innovation Center for Materials Genome Engineering, University of Science and Technology Beijing, China
Zhi Wei Seh, Institute of Materials Research and Engineering, A*STAR, Singapore
Zhijun Fang, School of Computer Science and Technology, Donghua University, China
Zijian Hong, School of Materials Science and Engineering, Zhejiang University, China
AI for Sciences
Guihua Shan, Computer Network Information Center, Chinese Academy of Sciences, China
Zhiqin Xu, Shanghai Jiao Tong University, China
Chi Zhou, Shenzhen University, China
Lijun Liu, Osaka University, Osaka, Japan
Di Fang, University of California, Berkeley, US
Xiaojie Wu, Bytedance Inc. US
Tong Zhao, Institute of Computing Technology, Chinese Academy of Sciences, China
AI for Civil Aviation
Michael Schultz, Institute of Flight Systems, Bundeswehr University Munich, 85577 Neubiberg, Germany
Paolo Tortora, Dipartimento di Ingegneria Industriale, Alma Mater Studiorum Università di Bologna, Bologna, Italy
Carlos E.S. Cesnik, Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC 27708, USA
Michael I. Friswell, Faculty of Science and Engineering, Swansea University, Swansea SA1 8EN, UK
Song Fu, School of Aerospace Engineering, Tsinghua University, Beijing 100084, China
Jae-Hung Han, Department of Aerospace Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea
Jacques Periaux , Full Research Professor on Numerical Methods in Engineering at CIMNE/UPC, Barcelona, Spain
Domenico Accardo, DII—Department of Industrial Engineering, University of Naples Federico II, Piazzale Vincenzo Tecchio, 80, Naples, Italy
Rafic M. Ajaj, Department of Aerospace Engineering, Khalifa University, Abu Dhabi 127788, United Arab Emirate
Gang Chen, State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace Engineering, Xi'an Jiaotong University, Xi'an 710049, China
Mou Chen, College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Wing Chiu, Department of Mechanical and Aerospace Engineering, Monash University, Room G27A, 17 College Walk (Building 31), Clayton Campus, Wellington Road, Clayton, VIC 3800, Australia
AI for Medicine
Han Lv, Beijing Friendship Hospital, Capital Medical University, China
Peng Wang, Beijing Ditan Hospital, Capital Medical University, China
Chaodong Wang, Xuanwu Hospital, Capital Medical University, China
Longxin Xiong, Nanchang Ninth Hospital, China
Mingzhu Zhang, Beijing Tongren Hospital, Capital Medical University, China
Yi Li, Peking Union Medical College Hospital, China
Shenhai Wei, The First Hospital of Tsinghua University, China
Hongxu Yang, GE Healthcare, Netherlands
Xiaohong Liu, Shanghai Jiao Tong University, China
Bingbin Yu, German Research Center for Artificial Intelligence-Robotic Innovation Center, Germany
Menghan Hu, East China Normal University, China
Shuo Li, Case Western Reserve University, USA
Tao Tan, Faculty of Applied Sciences, Macao Polytechnic University
Yue Wu, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, China
Siuly Siuly, Victoria University, Australia
Enamul Kabir, University of Southern Queensland, Australia
Muhammad Tariq Sadiq, University of Brighton, UK
Smith K. Khare, Aarhus University, Denmark
Mohammed Diykh, University of Thi-Qar, College of Education for Pure Science, Iraq
Supriya Angra, Torrens University, Australia
Abdulkadir ŞENGÜR, Firat University, Turkey
Varun Bajaj, PDPM-Indian Institute of Technology, Design and Manufacturing, India
Ömer Faruk ALÇİN, Malatya Turgut Ozal University, Turkey
K. Venkatachalam, University of Hradec Králové, Hradec Králové, Czech Republic
Ivan Lee, TheUniversity of South Australia, Australia
Feng Xia, RMIT University, Australia
Zhiguo Gong, The University of Macau, China
Hong Yang, Guangzhou University, China
Qian Zhou, Nanjing Univerrsity of Posts and Telecommunications, China
Wenjun Tan, Northeastern University, China
AI for Space Science and Engineering
Zongcheng Ling, Shandong University, China
Yanjie Fu, University of Central Florida, USA
Jiajia Liu, University of Science and Technology of China, China
Xiaoxi He, University of Macau, China
AI for High Energy Physics
Xinchou Lou, University of Texas at Dallas, Dallas & Institute of High Energy Physics (IHEP), Beijing, China
Haijun Yang, Shanghai Jiao Tong University (SJTU), Shanghai, China
Xingtao Huang, Shandong University (SDU), Qingdao, China
Huilin Qu, the European Organization for Nuclear Research (CERN), Geneva
Bruce Mellado, University of the Witwatersrand (WIS), Johannesburg
Fabio Hernandez, Computing Centre, National institute of nuclear and particle physics (IN2P3), Lyon
AI and Security
Yanwei Liu, Institute of Information Engineering, Chinese Academy of Sciences
Hongjia Li, Institute of Information Engineering, Chinese Academy of Sciences
Zhiqiang Xu, Jiangxi University of Science and Technology
Liwei Chen, Institute of Information Engineering, Chinese Academy of Sciences
Yanni Han, Institute of Information Engineering, Chinese Academy of Sciences
Duohe Ma, Institute of Information Engineering, Chinese Academy of Sciences
Sanya, also known as "China's Hawaii," is a breathtaking destination renowned for its stunning natural scenery, pleasant climate, and pristine air quality. Located on the southern coast of Hainan Island, Sanya boasts a perfect combination of picturesque landscapes and a tropical paradise. The climate in Sanya is pleasant, with a perpetual spring-like atmosphere, and one can escape the cold winter elsewhere and indulge in the warm sunshine, pristine beaches, crystal-clear waters, delectable cuisine, and lush tropical landscapes.
Why should you not miss the opportunity to exchange ideas with global top tech entrepreneurs? Here are ten reasons to participate in the conference:
The 2023 BenchCouncil International Conference on Intelligent Computing and Chip (FICC 2023) will be held in Sanya from December 3rd to 6th. As an important event in this field, FICC 2023 provides a unique opportunity for companies to showcase their technologies, share their experiences, and engage in in-depth discussions with top global experts and entrepreneurs.
Here are ten reasons for you to attend FICC 2023 and deliver a presentation at the conference:
Participating in FICC 2023 will bring tremendous opportunities and benefits to your company. I sincerely invite you to attend this grand event and deliver a keynote speech. Please confirm your intention to attend as soon as possible so that we can provide you with more detailed information.
The application process to participate in the Sanya International Conference on Intelligent Computing and Chip Union is as follows:
Please provide clear and detailed information in the email to help the evaluators fully understand your company and the content of your presentation. We wish you success in your application!
The Travel Grant is a compensatory award that is available to applicants who have registered for the conference. The conference will be held Dec.3 – Dec.6 in Sanya, Hainan, China, all registers are eligible to apply. Since the total grant is a fixed amount, the amount that can be awarded to each register will depend on the number of awardees and will cover only a portion of your expenses.
There are two levels of Travel Grant: 2100 RMB (300 USD) for up to 20 people, and 700 RMB (100 USD) for up to 100 people. The final list of recipients of the Travel Grant will be announced during the conference banquet. Please note that individuals who have already applied for the family meal ticket are not eligible to apply for the Travel Grant.
Important information about travel grants:
If you wish to apply for the grant, please contact student.travel.grant.bench@gmail.com.
Use the subject line "FICC 2023 Travel Grant Application." The travel grant application (a single consolidated pdf file) should include:
BenchCouncil has launched the Top100 initiative, which aims to recognize the top 100 achievements in the fields of chips, AI, open source, evaluations, and benchmarks. These achievements are known as Chip100, AI100, Open100, and Bench100. As a result, we have compiled both annual and centennial versions of four rankings, which can be accessed publicly at https://www.benchcouncil.org/evaluation/. These rankings have generated significant interest, comments, and suggestions from academic and industry practitioners worldwide.
For those that have been selected into annual version of the BenchCouncil Top 100 achievements ranking list (AI100, Chip100, Open100, Bench100)
Academia complimentary Service:
Industry complimentary Service:
Free registration: https://eur.cvent.me/eAxmP
Furthermore, we offer upgrade services for academic or industrial institutions that have been selected for the Top 100 achievements ranking list (AI100, Chip100, Open100, Bench100). Institutions that register for the upgraded service can enjoy additional benefits at the FICC 2023 conference. The number of registrations, duration of plenary session speech, and exhibition space will vary depending on whether you are from academia or industry. We can also provide customized services upon request.
If you need to register for upgrade service, please transfer the cash to the following bank account.
Meanwhile, please send an email to benchcouncil.evaluation@gmail.com. Also, you can upgrade services through the registration link https://eur.cvent.me/eAxmP.
Academia Upgrade Service:
Industry Upgrade Service:
To avoid missing important achievements, BenchCouncil calls for the submission of achievements in the fields of AI, Chips, Open source, benchmarks, and evaluations. After the preliminary evaluation, the submitters of the achievements will have the opportunity to present or showcase their work at the FICC 2023 conference and have a chance to be included in the final rankings.
Ten benefits
1. The submitted achievements will be included in the annual achievement report of the BenchCouncil and will be cited. The submitters need to provide valid citation formats, including paper publications, code repositories, etc. The compiled annual achievement report will be officially published in BenchCouncil Transactions.
2. The submitters of the achievements will receive the certificate of annual achievement Selection. For example, the certificate for the Chip category will be named "the certificate of 2023 BenchCouncil Chip achievement selection." The certificate will display the individual and institutional names.
3. The achievements will be featured on the official English webpages of the BenchCouncil's achievement evaluation (https://www.benchcouncil.org/evaluation/).
4. The official English webpages of the BenchCouncil will provide links to the achievements. The submitters should ensure that the linked content is authentic, non-deceptive, and accurate.
5. The submitters will have the opportunity to attend all four conferences: Chips 2023, OpenCS 2023, Bench 2023, and IC 2023. They will have the chance to engage in extensive exchanges with international peers.
6. The selected achievements will be showcased at the conference venue. The specific time period (generally not exceeding one day) and location need to be coordinated with the conference organizers.
7. The submitters of the achievements have the opportunity to present their work at the conference, subject to further evaluation and arrangement by the conference organizers.
8. Outstanding achievements invited to present at the conference may have the chance to be included in the annual version of the Top 100 achievements ranking (final version) after evaluation by the committee and recognition from peers. The committee has reserved 20 slots for selecting achievements from the submissions.
9. Exemplary achievements that have stood the test of time have the chance to be included in the annual version of the Top 100 achievements ranking (request for comments).
10. The submitters of the achievements can apply for travel funding.
Scope of achievements:
In the field of chips, including but not limited to as follows:
system design, logic design, physical design, timing design, verification and simulation, emulators, auxiliary design tools, emerging chips such as superconducting and quantum chips, emerging accelerators, semiconductor materials, lithography technology, circuits, packaging technology.
In the field of artificial intelligence, including but not limited to as follows:
machine learning, reinforcement learning, natural language processing, image analysis, video analysis, data mining, recommendation systems, knowledge representation and reasoning, medical image processing, multimodal information fusion, collective intelligence, intelligent robots and systems, intelligent control, intelligent healthcare, artificial intelligence and astronomy, artificial intelligence and high-energy physics, artificial intelligence and space science, artificial intelligence and transportation, artificial intelligence and oceanography, artificial intelligence and security, artificial intelligence and law, artificial intelligence and finance, artificial intelligence and traditional industries, ethics and governance of artificial intelligence, artificial intelligence and big data, artificial intelligence and materials, artificial intelligence and civil aviation applications, artificial intelligence and business management.
In the field of open source, including but not limited to as follows:
chips, operating systems, containerization and virtualization, compilers, data management, networks, programming languages and compilers, systems and frameworks, basic libraries, monitoring and optimization tools, big data, AI, cloud computing, HPC, blockchain, LLM, autonomous driving, digital twins, Internet of Things, privacy and security, datasets, education.
In the field of benchmark and evaluation, including but not limited to as follows:
econometrics, clinical medical evaluation, drug evaluation, business and financial benchmarks, AI evaluation, HPC benchmarks, database benchmarks, memory benchmarks, network benchmarks, hardware and disk benchmarks, graph benchmarks, human resource evaluation, education evaluation, indicator and index systems.
Process of submitting achievements:
Evaluation criteria:
After being selected, you must register the conference.
please transfer the cash to the following bank account.
Also, You can pay using your credit card with following registration link https://eur.cvent.me/5qQEq
1. 1 standard registration for FICC 2023.
Furthermore, we offer upgrade services (the registration link is: https://eur.cvent.me/k85BK) for academic or industrial institutions that have been selected for the Top 100 achievements ranking list (AI100, Chip100, Open100, Bench100). Institutions that register for the upgraded service can enjoy additional benefits at the FICC 2023 conference. The number of registrations, duration of plenary session speech, and exhibition space will vary depending on whether you are from academia or industry. Also, we provide customized services upon request.
Academia Upgrade Service:
Industry Upgrade Service: