Parallel and Distributed Computing: Theory and Applications

Dear Colleagues,

With the recent vigorous development of emerging technologies such as big data, artificial intelligence, and the metaverse, various intelligent systems and applications have become commonplace in daily life. It is difficult for traditional centralized computing power to support the computing needs of such applications. The simultaneous growth of complex intelligent algorithms, massive multi-modal data, and various large-scale applications has put unprecedented pressure on computing architecture. The development of parallel and distributed computing is essential for overcoming the limited computing power of traditional centralized computing, and its social and economic impacts are considerable.

Parallel and distributed computing occur in many areas of computer science, including algorithms, computer architecture, networking, operating systems, and software engineering. With the emergence of new infrastructures and computing architectures (e.g., cloud computing, edge computing, smart cities, and the Internet of Vehicles), the current parallel and distributed computing techniques have become challenging, and there is still much room for improvement in their research. Therefore, the development of powerful and effective parallel computing capabilities to ensure computing efficiency and security across various intelligent applications is increasingly urgent in both academia and industry. In addition, the implementation of parallel and distributed computing technology for practical application in various fields is another key issue.

The purpose of this Special Issue is to present current developments, share theoretical and technical knowledge, and discuss emerging challenges and trends in the field of parallel and distributed computing. Original research and review articles are welcome.

Topics of interest include, but are not limited to:

• The theory of parallel and distributed computing;
• Architectures, algorithms, and models of parallel and distributed computing;
• High-performance computing architectures for big data, artificial intelligence, and the metaverse;
• Parallel and distributed computing for machine learning/data mining;
• Novel algorithms and applications in all fields of parallel and distributed computing;
• The management and analytics of parallel or distributed computing-based applications.

Dr. Jianguo Chen
Dr. Jinyu Tian
Dr. Ji Wang
Guest Editors

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