Advances of HPC for AI Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".
Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 475
Special Issue Editors
Interests: resource allocation and job scheduling; optimization for deep learning applications; cloud computing; supercomputing
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Special Issue Information
Dear Colleagues,
Artificial intelligence (AI) is a cross-disciplinary technology based on mathematics, computer science, linguistics, psychology, and many more domains. It allows machines to simulate human behaviour or to solve problems intelligently by training AI models using vast volumes of application data. As more and more AI applications such as personalized shopping, autonomous vehicles, facial recognition, recommendation system, and voice assistant are available in our daily lives, a significant amount of computation and storage space are needed to improve AI applications. To better serve AI applications, there is a significant amount of inter-domain studies in the High-Performance Computing (HPC) and AI communities that aim to 1) improve AI with the help of HPC techniques (i.e., “HPC for AI”) and 2) improve HPC through the use of AI techniques (i.e., “AI for HPC”). In this Special Issue, we would like to see all inter-domain research work between HPC and AI.
Dr. Shanjiang Tang
Dr. Yusen Li
Guest Editors
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Keywords
- AI for HPC and HPC for AI
- efficient data storage and parallelism for AI
- resource management and job scheduling for AI applications
- programming models for AI
- performance modelling for AI applications
- accuracy and efficiency optimization for AI model training and inference
- efficient hardware and software systems for AI
- fault Tolerance, High Availability, and Reliability for AI
- I/O optimization for AI applications
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