Workshops

The program opens with four days of tutorials that will provide an introduction to major themes of the entire program and the four workshops.  The goal is to build a foundation for the participants of this program who have diverse scientific backgrounds.  The topics covered during the tutorials will include the following:

Large-scale data analytics

• An overview of typical challenges and approaches
• Statistical foundations of modern data analytics
• A primer on machine learning
• Deep learning: Recent successes and next steps
• Hardware aspects of large-scale data analytics

Large-scale simulation

• An overview of typical challenges and approaches
• Scalable algorithms for HPC
• Multi-fidelity approaches and model-order reduction
• Uncertainty quantification and predictive computational science
• Hardware aspects of large-scale simulation

Large-scale data management

• An overview of typical challenges and approaches
• Handling BD: Efficient data representation and compression
• Hardware aspects of large-scale data management

Big Data and HPC Visualization

Please note: there are no activities on Saturday and Sunday, Sept. 15-16.  For those participating in the long program, please plan to attend Opening Day on Wednesday, Sept. 12, as well.  Others may participate in Opening Day by invitation from the organizing committee.

Organizing Committee

Joachim Buhmann (ETH Zürich)
Hans-Joachim Bungartz (Technical University Munich (TUM))
Emmanuel Candes (Stanford University)
Jeffrey Hittinger (Lawrence Livermore National Laboratory)
Frank Jenko (Max Planck Institute for Plasma Physics and UCLA)
David Keyes (King Abdullah Univ. of Science and Technology (KAUST))
Alan Lee (AMD)
Tandy Warnow (University of Illinois at Urbana-Champaign)