研討會主題:
1. 人工智慧與量子計算在高能物理中的進展
探討機器學習、深度學習及量子演算法於粒子物理數據分析中的應用。
2. 分散式數據管理與大數據處理
高能物理實驗中，處理地理分散數據集的挑戰與解決方案。
3. 系統優化：效能分析與調整
分析系統效能並優化大規模實驗計算資源的策略。
4. 高效數據處理的工作負載調度
創新工作負載調度技術，應對大規模及動態計算任務的需求。
5. 科學研究中的虛擬合作
從 COVID-19 疫情期間的虛擬組織與合作管理中汲取的經驗教訓。
6. 處理大型數據集的計算模式演進
探討處理大規模、全球分佈數據集的計算模式的進展與洞察。
7. 邁向碳中和的永續計算
探索計算運作實現永續發展與減少碳足跡的趨勢與策略。
Topic of Interests:
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Advancements in AI and Quantum Computing for High-Energy Physics
Exploring applications of machine learning, deep learning, and quantum algorithms in particle physics data analysis. -
Distributed Data Management and Big Data Processing
Challenges and solutions for managing geographically distributed datasets in high-energy physics experiments. -
System Optimization: Performance Analysis and Tuning
Strategies for analyzing system performance and optimizing computing resources for large-scale experiments. -
Workload Scheduling for Efficient Data Processing
Innovations in workload scheduling to handle large-scale and dynamic computing tasks effectively. -
Virtual Collaboration in Scientific Research
Lessons learned from managing virtual organizations and collaborations during the COVID-19 pandemic. -
Evolving Computing Models for Large-Scale Datasets
Insights into computing model advancements for handling extensive and globally distributed datasets. -
Sustainable Computing: Moving Towards Carbon Neutrality
Examining trends and strategies in computing operations to achieve sustainability and reduce carbon footprints.
