The remarkable language understanding, generation, and knowledge reasoning capabilities of ChatGPT have demonstrated the incredible outcomes that result from the integration of massive data and powerful computational resources. However, most current computing systems rely on silicon-based chips, which are approaching their performance limits. Thus, improving the efficiency of programs through parallel computing has become a crucial path for enhancing performance.
To help university faculty and students better grasp the techniques of parallel computing, Huazhong University of Science and Technology (HUST) will hold the "2024 HUST - USYD Summer School & Parallel Programming Hands-on Workshop" from July 8 to 26, 2024. The workshop will be conducted online, focusing on using OpenMP and MPI to program and optimize shared and distributed memory parallel computer systems. Participants will learn the basic methods of parallel programming and engage in a series of hands-on experiments to deepen their understanding of parallel computing and optimization concepts. By the end of the workshop, participants will have developed parallel thinking skills and gained foundational abilities in parallel programming, enabling them to address parallelization problems in various environments and scenarios.
The EduCoder and the Mechanical Industry Press co-host the workshop.
1.Eligibility and Requirements
The workshop is open to all faculty and students of HUST, as well as those from other universities across the country who are interested in learning parallel programming. Applicants must have a programming background, particularly in C language.
2.Registration Period
From now until July 1.
3.Registration Process
Scan the QR code below to join the project’s QQ group (Group ID: 183973772) and fill out the "2024 HUST - USYD Summer School & Parallel Programming Hands-on Workshop Registration Form" in the group announcement. The teaching team will select participants based on their eligibility for the workshop, and successful applicants will be notified via SMS.
4.Teaching Method
The workshop will be conducted entirely online, with the EduCoder platform serving as the practical platform for the workshop. Instructions on how to use the platform will be provided during the class. Participants who complete the workshop requirements will receive a certificate of completion.
。
5. Teaching Team
Lecturers:
Professor Zhou Bingbing, Associate Professor at the School of Information Technology, University of Sydney, graduated from Nanjing Institute of Technology (now Southeast University) in 1982 with a degree in Electronic Engineering and received his PhD in Computer Science from the Australian National University in 1989. He has been a postdoctoral researcher at ANU (1992-2000) and a senior lecturer at Deakin University (2000-2003). His research focuses on distributed and parallel computing, algorithm design and analysis, cloud computing, and bioinformatics. He has published over 100 papers in international journals and conferences and is a reviewer for numerous international publications and conferences. At the University of Sydney, he teaches various computer science workshops, including "Parallel and Distributed Computing," "Operating System Kernel," and "Computer and Network Organization."
Dr Lu Feng is an Associate Professor at the School of Computer Science and Technology, HUST, and Deputy Director of the Institute of Parallel Computing. She is a member of the Big Data Committee, Artificial Intelligence and Pattern Recognition Committee, and Distributed Computing and Systems Committee of the China Computer Federation (CCF). She has been involved in over ten research projects, including the National Natural Science Foundation, doctoral funding projects, and national 863 programs. She has published more than 20 academic papers in top international journals and conferences, with over 300 citations on Google Scholar (highest citation per paper: 45). She has won several awards, including a second prize in the National College Green Computing Competition and a second prize in the National Software Engineering Teaching Case Competition.
Teaching Assistants:
Zheng Haibo (Master’s student, School of Computer Science and Technology, HUST)
Hou Yuxiang (Master’s student, School of Computer Science and Technology, HUST)
Wang Xiying (Master’s student, School of Computer Science and Technology, HUST)
Jiang Shan (Master’s student, School of Computer Science and Technology, HUST)
Hou Xuzhe (Undergraduate, Electrical and Computer Engineering, University of Illinois)
Zhang Xunjiang (Doctoral student, School of Life Science and Technology, HUST)
Luo Wenxi (Doctoral student, School of Life Science and Technology, HUST)
