2025

2025 Conference on Advanced Topics and Auto Tuning in High-Performance Scientific Computing

March 21 (Friday) - 22 (Saturday), 2025

National Cheng Kung University

臺南市東區大學路1號
No.1, University Road,Tainan City, Taiwan

機械工程系館 三星講堂

Department of Mechanical Engineering Sanshing Aud.

Aims and Scope

The 2025 Conference on Advanced Topics and Auto Tuning in High-Performance Scientific Computing (ATAT 2025) focuses on the scientific impacts of the latest computer architectures and the approaches to achieve high-performance computing on these leading-edge computers. Advances in many-core architectures, high-end computers, and the integration of AI and deep learning technologies have revealed their significance in scientific discoveries and engineering achievements. These technologies not only enhance computational performance but also enable innovative approaches to solving complex scientific problems through data-driven methodologies. However, the complexity of these newly developed computers, along with the challenges of optimizing AI and deep learning algorithms, leads to contemporary issues in achieving the best efficiency of highly promising computational capabilities. The conference encourages interdisciplinary communications between researchers from applied mathematics, statistics, computer science, physical sciences, engineering, and industry to prompt innovations and breakthroughs in this exciting field. The main themes include, but are not limited to, simulations, numerical methods, applications, hardware, software, and particularly algorithm auto-tuning via statistical methods, AI-driven models and deep learning techniques in high-performance computing.

Forum

The Role of AI in Advancing Computational Education

The Role of AI in Advancing Computational Education will examine how AI is reshaping the design and delivery of computational courses, emphasizing curriculum adaptation and instructional support. With the integration of AI, traditional teaching approaches are evolving to incorporate personalized learning paths, intelligent content recommendations, and real-time feedback. This forum will delve into two core themes:

1. Transforming Computational Curriculum Design:

This discussion will focus on how AI necessitates changes in the content and structure of computational education. Key topics include the balance between coding skills and higher-level computational concepts, the integration of machine learning and data science modules, and the shifting weight of traditional versus modern topics. Participants will explore how to optimize course design to reflect the growing influence of AI-driven tools and practices.

2. AI as an Enabler for Course Delivery:

This segment will investigate how AI can enhance teaching and learning processes through adaptive learning systems, automated grading, and virtual teaching assistants. Real-world examples of AI-powered platforms providing immediate feedback, personalized resources, and scalable instructional support will be highlighted.

By addressing these themes, the forum aims to provide insights into how AI can revolutionize computational education, making it more efficient, inclusive, and aligned with the demands of the modern technological landscape.

Plenary Speakers 

• Stefano De Marchi (University of Padova, Italy)

• Nishiguchi Koji (Nagoya University, Japan)

AI Forum

• Feng-Nan Hwang 黃楓南 (National Central University)

Panelists

• Sun-Yuan Hsieh  謝孫源 (National Cheng Kung University)

• Takahiro Katagiri (Nagoya University)

• Koki Masui (Osaka University)

Invited Speakers

• Te-Yao Chiu 邱德耀 (National Central University)

• Yi-Ju Chou 周𨓜儒  (National Taiwan University)

• Toshiyuki Imamura (RIKEN)

• Heng-Chuan Kan 甘恆全 (National Center for High-performance Computing)

• Takahiro Katagiri (Nagoya University)

• Bing-Ze Lu 呂秉澤 (National Cheng Kung University)

• Koki Masui (Osaka University)

• Kengo Nakajima (The University of Tokyo)

• Yasutaro Nishimura  西村泰太郎 (National Cheng Kung University)

• Torbjörn Nordling 吳馬丁 (National Cheng Kung University)

• Kenji Ono (Kyushu University)

• Katsuhisa Ozaki (Shibaura Institute of Technology)

• Yu-Chen Shu 舒宇宸 (National Cheng Kung University)

• Matthew R. Smith 李汶樺 (National Cheng Kung University)

• Hiroyuki  Takizawa (Takizawa Tohoku University)

• Teruo Tanaka (Kogakuin University)

• Yuki Uchino (RIKEN)

Student Speakers

• Ryota Koda (M2, Tohoku University)

• Makoto Morishita (D3, Nagoya University)

• Shubham (D1, Tohoku University)

• Kanae Shiragami (M1, Kyushu University)

• Hua-Ching Chang 張華倞  (National Chung Hsing University / National Center for High-Performance Computing, Taiwan)

• Yu-Tan Wu 吳雨潭 (M2, National Central University, Taiwan)

Program

Titles and Abstracts

Banquet

Conference Registration

You are welcome to join the conference.  

https://forms.gle/bEqcQi925oy29J1y5

Deadline: March 10th