Nov 16, 2023-Dec 15, 2023

Online Registration

Dec 16, 2023-Jan 21, 2024

Preliminary Competition

Apr 9-13, 2024

Final Competition

ASC24 Finalist Participation

  • ASC765 Huazhong University of Science and Technology
  • ASC598 Sun Yat-sen University
  • ASC658 Zhejiang University
  • ASC611 Qinghai University
  • ASC648 Shanghai University
  • ASC663 Fuzhou University
  • ASC709 Lanzhou University
  • ASC751 Shanxi University
  • ASC676 Jinan University
  • ASC628 Southern University of Science and Technology
  • ASC686 Beihang University
  • ASC696 Qilu University of Technology
  • ASC724 NUDT Team
  • ASC673 Shanghai Jiao Tong University
  • ASC592 University of Science and Technology of China
  • ASC703 Harbin Institute of Technology, Shenzhen
  • ASC606 Peking University
  • ASC644 Southwest Petroleum University
  • ASC799 The Chinese University of Hong Kong
  • ASC660 Kasetsart University
  • ASC702 National Tsing Hua University
  • ASC719 The Hong Kong Polytechnic University
  • ASC849 Friedrich-Alexander-University Erlangen- Nuremberg
  • ASC864 National University of Cordoba
  • ASC804 Macau University of Science and Technology

The Second Class Prize Winners

  • ASC712 University of Science and Technology Beijing
  • ASC752 Beijing Normal University
  • ASC837 Tsinghua University
  • ASC675 Fuzhou University
  • ASC649 Shanghai University
  • ASC694 Zhejiang University
  • ASC740 Fuzhou University
  • ASC640 Taiyuan University of Technology
  • ASC627 University of Electronic Science and Technology of China
  • ASC635 Northwestern Polytechnical University
  • ASC636 Southeast University
  • ASC683 Zhejiang University
  • ASC685 Southwest Petroleum University
  • ASC593 Hunan University
  • ASC667 Wuhan University
  • ASC718 Wuhan University
  • ASC684 Fuzhou University
  • ASC743 ShanghaiTech University
  • ASC716 Fuzhou University
  • ASC639 Taiyuan University of Technology
  • ASC750 Shandong University, Weihai
  • ASC622 North China University of Science and Technology
  • ASC618 The Hong Kong University of Science and Technology (Guangzhou)
  • ASC619 The Hong Kong University of Science and Technology (Guangzhou)
  • ASC608 Shandong University of Science and Technology
  • ASC714 Shenzhen University
  • ASC700 Henan Normal University
  • ASC645 Southern University of Science and Technology
  • ASC687 Zhejiang University
  • ASC614 Qinghai University
  • ASC654 South-Central Minzu University
  • ASC725 Tianjin University of Technology and Education
  • ASC679 Yanshan University
  • ASC727 Harbin Institute of Technology
  • ASC607 Shandong Normal University
  • ASC695 Nanjing University
  • ASC604 Wuhan University
  • ASC653 Qilu University of Technology (Shandong Academy of Sciences)
  • ASC677 Fuzhou University
  • ASC713 Nanchang University
  • ASC596 Information Engineering University
  • ASC669 Zhejiang University
  • ASC659 SouthWest Petroleum University
  • ASC772 Harbin Institute of Technology
  • ASC656 South-Central Minzu University
  • ASC710 Harbin Institute of Technology, Shenzhen
  • ASC746 Shandong University, Weihai
  • ASC681 Shanghai Polytechnic University
  • ASC643 Beijing University of Chemical Technology
  • ASC655 South-Central Minzu University
  • ASC646 China University of Mining and Technology
  • ASC793 Ocean University of China
  • ASC786 Southern University of Science and Technology
  • ASC647 Yan Tai University
  • ASC805 Sichuan University
  • ASC802 Jianghan University
  • ASC711 Renmin University of China
  • ASC668 Xi'an Jiaotong University
  • ASC624 North China University of Science and Technology
  • ASC798 Jianghan University
  • ASC801 Jianghan University
  • ASC594 Jianghan University
  • ASC625 The Hong Kong University of Science and Technology (Guangzhou)
  • ASC749 Shandong University, Weihai
  • ASC803 Jianghan University
  • ASC792 Ocean University of China
  • ASC737 Henan Normal University
  • ASC851 China University of Mining and Technology
  • ASC748 Shandong University, Weihai
  • ASC742 Renmin University of China
  • ASC788 Chang'an University
  • ASC794 Chengdu University of Information Technology
  • ASC621 Hangzhou City University
  • ASC800 Jianghan University
  • ASC767 China Pharmaceutical University
  • ASC601 Chang'an University
  • ASC707 Henan Normal University
  • ASC776 Chengdu University of Information Technology
  • ASC758 Chengdu University of Technology
  • ASC863 Kasetsart University
  • ASC600 North China University of Science and Technology
  • ASC616 North China University of Science and Technology
  • ASC829 Southeast University
  • ASC634 North China University of Science and Technology
  • ASC599 North China University of Science and Technology
  • ASC605 North China University of Science and Technology
  • ASC632 North China University of Science and Technology
  • ASC850 Shanghai Business School
  • ASC699 Southern University of Science and Technology

ASC24 Final

Rules of the final stage

1.The use of optimization methods specific to certain parameters or input data sets is strictly forbidden.

2.If any changes are made to the algorithm, the revised version must maintain mathematical equivalence to the original.

3.Violation of any rule mentioned above will result in a zero score being assigned for the corresponding task.

4.Properly constructing the cluster is essential. Any damage to the server may incur a penalty of up to 20 points for the team, as determined by the ASC24 Committee.

Performance Optimization

I. HPL performance optimization:

1.Platform requirement: The runtime power consumption must remain under 3 KW. Failure to comply will result in the invalidation of the current task.

2.Goal: Obtain the correct results while achieving the highest performance.

3.Software download: http://www.netlib.org/benchmark/hpl/

II. Performance optimization of HPCG:

1.Platform requirement: The runtime power consumption must remain under 3 KW. Failure to comply will result in the invalidation of the current task.

2.About run time: The runtime of HPCG (version 3.0) must be a minimum of 1800 seconds (30 minutes), as reported in the output file. The Quick Path option is not permitted.

3.Software download: https://github.com/hpcg-benchmark/hpcg

III. Performance optimization of OpenCAEPoro:

1.Platform requirement: The power restriction of the test platform is 3 KW. If the power consumption exceeds 3 KW, the results of the current task will be invalid.

2.Goal: The OpenCAEPoro challenge shares a similar objective with the preliminary round. The ASC24 committee will announce several OpenCAEPoro workloads during the finals. Each workload's results must pass correctness checking, and the objective is to minimize OBJECT TIME. It's important to note that modifying any code related to the method parameters is prohibited, and all parameters in the input files must remain unchanged.

3.Software download: https://github.com/OpenCAEPlus/OpenCAEPoro_ASC2024

IV. Performance optimization of GoMars:

1.Platform requirement: The power restriction of the test platform is 3 KW. If the power consumption exceeds 3 KW, the results of the current task will be invalid.

2.Goal: GoMars is a novel global open planetary atmospheric model designed for Mars. It offers insights into Martian meteorological conditions crucial for landing operations. The ASC24 committee will introduce various GoMars workloads during the finals. The results of each workload must undergo correctness checking, and the objective is to minimize the runtime of the GoMars application. Please note that the provided link only contains the dynamic core of GoMars, whereas additional codes for physical processes may be included in the final version.

3.Software download: https://gitee.com/dongli85/GMCORE

V. Performance optimization of the Mystery Application:

1.Platform requirement: The power restriction of the test platform is 3 KW. If the power consumption exceeds 3 KW, the results of current task will be invalid.

2.Goal: The ASC24 committee will announce several Mystery Application workloads during the finals. The results of each workload must pass correctness checking, and the objective is to minimize runtime.

VI. Performance optimization of LLM inference:

1.Platform requirement: The power limit for the test platform is 3 KW. Any power consumption exceeding this threshold during the contest will result in the invalidation of the current task's results.

2.Goal: The LLM inference challenge shares a similar goal with the preliminary round. AquilaChat2-34B will be used in the final round and the datasets used for evaluation will be disclosed on site. Besides, it is required to utilize 4bit or less quantization for inference acceleration during the final and the baseline quantization method is 4bit bitsandbytes. Moreover, the overall accuracy rather than only output length of dataset results will be taken into account, which should be controlled within a maximum error of 1.5% compared to the BF16 precision baseline.

3.Download: Model weight and the baseline code for bitsandbytes download link https://huggingface.co/BAAI/AquilaChat2-34B/

Team Presentation

1.Each team is required to present their results using PowerPoint (PPT) slides. The presentation order for each team will be determined by a draw. English must be used in both the PPT slides and in the presentations delivered by up to two student speakers.

2.The presentation must not exceed 7 minutes in duration. Any additional time will result in a reduction of your score accordingly. Following the presentation, judges will have approximately 3 minutes to ask questions.

3.The evaluation committee will assess the presentation of each team.

4.The team advisor is welcome to observe her/his team's presentation session.