Welcome to the MCSoC 2021 Special Session on Distributed Computing and Communication Techniques for Emerging AI Applications

Artificial Intelligence (AI), especially the Machine Learning (ML), has demonstrated great potentials to revolutionize our world by improving the efficiency of deployment and management, enhancing security and privacy protection, and enabling various smart applications. The success of AI stems from availability of big training data and massive computation power, which drives academia and industry to build powerful computing and networking infrastructure for data storage, transmission and processing. Evidences have shown that the amount of compute used for training deep learning models has increased 300,000x in the past 6 years. Therefore, the traditional single-machine-based AI systems cannot handle the computing and communication requirements of emerging AI applications, and it is urgent to design and develop distributed computing and communication infrastructure for AI.
Addressing the above challenges needs significant research efforts on theories, algorithms, architecture, and experiences of system deployment and maintenance. Therefore, this special session aims to offer a platform for researchers from both academia and industry to publish recent research findings and to discuss opportunities, challenges and solutions on distributed computing and communication techniques for emerging AI applications. Topics of interests include, but are not limited to:
• Edge/cloud computing for AI
• Federated learning
• Computing and network resource allocation for AI systems
• Energy efficiency of AI systems
• Network management of AI systems
• Modeling and optimization of distributed AI systems
• Incentive mechanisms for distributed AI systems



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