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Call for Papers: Special Issue on Advanced Parallel HPC for AI Applications

Elsevier publishers have launched their Call for Papers on their Special Issue on Advances on Parallel and High Performance Computing for AI Applications.

Most of the AI/ML technologies and applications require heavy use of high performance computers and accelerators. Consequently, High Performance Computing 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 Novel HPC architecture for AI/ML

Research articles must not have been published or submitted for publication elsewhere. All articles will be peer reviewed and accepted based on quality, originality, novelty, and relevance to the special issue.

The Submission deadline is Nov 30, 2018.

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