Workshop on Scalable Data Analytics in Scientific Computing (SDASC)

Contents:

• Call for Papers
• Topics of Interest
• Submission guidelines
• Important dates
• Organizers (alphabetical)
• Scope
• Topics of Interest
• Contributing
• Committees
• Program

With increasing importance of statistical inference methods and their use at large cloud and warehouse-scale computing industry, we propose a workshop called Scalable Data Analytics in Scientific Computing (SDASC). It will feature automated data analysis efforts on the convergence of computational science, HPC, and large scale data analytics and inference. The workshop will focus on integration of the HPC techniques and statistical learning and related tasks into modern computational software stack.

The half-day workshop will gather experts from the computational science, HPC, and machine learning. The committee members are recognized in their respective fields as experts of note and will assure fulfilment of the goals of the workshop outlined below.

This workshop could also be considered as a complementary event to the Machine Learning Learning Day slated to take place at ISC 2019.

The workshop aims to establish a forum of discourse and exchange of ideas about current practices for HPC and data analytics integration. The outcomes will include discussion about contemporary methods and implementation techniques that unify modern statistical inference, latest software stacks for Machine Learning deployed on supercomputing machines with hardware accelerators.