Special Issue on Advances on Parallel and High Performance Computing for AI Applications
• 大类 : 工程技术 - 3区
• 小类 : 计算机：理论方法 - 3区
Artificial Intelligence (AI) and Machine Learning (ML) have grown substantially in popularity in recent years. Much research has been done in both academia and industry, with applications in many areas. For example, deep learning has achieved superhuman performance in image classification. AI/ML have been used to play games such as Chess, Go, Atari and Jeopardy very successfully. In addition, many companies have being using AI and ML in areas such as health care, natural resource management and advertisement.
Most of the AI/ML technologies and applications require heavy use of high performance computers and accelerators. Consequently, High Performance Computing (HPC) is a key component of these systems. Clusters of computers and accelerators (e.g. GPUs) are routinely used to train and run models, both in research and production. On the other hand, ML and AI have also become a "killer application" for HPC and, consequently, have driven much of research in this area. For example, tailored computer architecture has been devised and new parallel programming frameworks developed to accelerate AI/ML models. The objective of this special issue is to bring together the HPC and AI/ML communities to present their applications and solutions to performance issues, and also to present how AI/ML can be used to solve HPC problems.
This is an open call for contributions. Authors are invited to submit papers to this special issue on themes related to the interplay of HPC and AI/ML. A selection of papers from the High Performance Machine Learning Workshop (HPML2018) will be invited to submit extended versions with at least 40% of new material to be considered for this special issue.
Topics of interest include, but are not limited to:
- Machine learning (including deep learning) models
- Large-scale machine learning applications
- Statistical models
- Large-scale data analytics
- Machine learning applied to HPC
- Accelerated Machine Learning
- HPC applied to Machine Learning
- Benchmarking, performance measurements, and analysis of ML models
- Hardware acceleration for ML and AI
- Parallel ML and AI models
- HPC infrastructure and resource management for ML