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台灣工業與應用數學會,其宗旨為促進台灣數學界與工業界、科技界更密切地交流與合作,謀求工業與應用數學之發展,及科學與技術之提昇與普及。

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【學會活動】2025 TWSIAM年會 早鳥報名優惠倒數中!

Category: 最新消息

Twsiam2025海報

 機會難得~~ TWSIAM年會早鳥報名優惠倒數中!

「第十三屆台灣工業與應用數學會年會」早鳥優惠到4/30(三)23:55!還沒報名的朋友趕快把握機會!

主題:AI與應用數學

時間:2025年6月7日(六)~6月8日(日)

地點:國立清華大學 旺宏館、綜合三館

精彩論壇+業界交流+水漾湖韻中餐廳晚宴

報名傳送門:https://www.accupass.com/event/2502260306252032934583

更多年會資訊:https://www.math.nthu.edu.tw/~twsiam2025

       早鳥價(即日起~04/30 23:55):一般與會者$3,500|學生 $700(含晚宴、紀念品)

       一般報名 (05/01~05/20 23:55):一般與會者 $4,000|學生 $1,000(含晚宴、紀念品)

歡迎各位先進們、學生們一起來參與!

 

台灣工業與應用數學會113年度 第二屆會士獲選名單

Category: 分類 (zh-tw)

TWSIAM 第二屆會士名單公告

TWSIAM_謹賀2025新年快樂

Category: 最新消息

【活動訊息】2025 ATAT Conference

Category: 最新消息
2025 Conference on Advanced Topics and Auto Tuning in High-Performance Scientific Computing

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

Location: National Cheng Kung University  機械工程系館 三星講堂

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.

More Information: ATAT in HPSC

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