Workshop II: HPC and Data Science for Scientific Discovery

October 15 - 19, 2018

Schedule


Monday, October 15, 2018

9:00 - 9:50
10:15 - 11:05
Peter Benner (Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg)

Low-rank tensor methods for simulation, optimization and uncertainty quantification of parametric PDEs
PDF Presentation

 
11:30 - 12:20
Alexander Szalay (John Hopkins University)

Streaming Algorithms for Halo Finders in Cosmology

 
2:30 - 3:20
Peter Lindstrom (Lawrence Livermore National Laboratory)

Alternatives to IEEE: NextGen Number Formats for Scientific Computing
PDF Presentation

 
4:00 - 4:50
Franck Cappello (Argonne National Laboratory)

Three Frontiers of Lossy Compression for Scientific Data

 

Tuesday, October 16, 2018

9:00 - 9:50
10:15 - 11:05
Begüm Demir (Technische Universität Berlin)

Accurate and Scalable Processing of Big Data in Earth Observation

 
11:30 - 12:20
 
2:30 - 3:20
4:00 - 4:50

Wednesday, October 17, 2018

9:00 - 9:50
Frank Jenko (Max Planck Institute for Plasma Physics and UCLA)

Combining computing and learning for physics
PDF Presentation

 
10:15 - 11:05
11:30 - 12:20
Michael Eldred (Sandia National Laboratories)

Multilevel-Multifidelity Sampling and Emulation for Forward UQ
PDF Presentation

 
2:30 - 3:20
4:00 - 4:50

Thursday, October 18, 2018

9:00 - 9:50
George Biros (University of Texas at Austin)

Scalable kernel methods
PDF Presentation

 
10:15 - 11:05
11:30 - 12:20
2:30 - 3:20
James Demmel (University of California, Berkeley (UC Berkeley))

Communication-Avoiding Algorithms for Linear Algebra, Machine Learning, and Beyond
PDF Presentation

 
4:00 - 4:50

Friday, October 19, 2018

9:00 - 9:50
Claudia Draxl (Humboldt-Universität)

How FAIR are data repositories in materials science?
PDF Presentation

 
10:15 - 11:05
Matthias Scheffler (Fritz-Haber-Institut der Max-Planck-Gesellschaft)

When More Data Do Not Provide A Better Description

 
11:30 - 12:20
Robert Martin (Air Force Research Laboratory)

Efficient Adaptive Hybrid Kinetic Simulation: Computing the Signal in the Noise

 
2:30 - 3:20
Victoria Stodden (University of Illinois at Urbana-Champaign)

Enabling Reproducibility in Computational and Data-enabled Science
PDF Presentation

 
4:00 - 4:50