UQ: Uncertainty Quantification for High-Performance Computing, May 2-4, 2012

Workshop Information

May 2, 2012 - 8:30am - May 4, 2012 - 3:00pm
Oak Ridge National Laboratory

Location: Oak Ridge, TN

Organizers: Rick Archibald (ORNL) and Clayton Webster (ORNL), Directorate Liaison: Pierre Gremaud (SAMSI)

The workshop was co-sponsored by the Oak Ridge National Laboratory and by SAMSI. It was held on location at Oak Ridge National Laboratory and included practical workshop guidance in the use of resources from the Oak Ridge National Computing Facility.

Motivation and Goals

The future designs of large peta and exascale supercomputing systems will require a paradigm shift in the development of mathematical algorithms and theory. The field of computational uncertainty quantification will have a unique role to play in maximizing the knowledge that can be gained through the full utilization of these supercomputing systems. Key drivers to developing effective mathematical methods for these systems will be achieved through algorithms and theory that expose hierarchies of parallel work while minimizing the power cost of data movement and communication.

Speakers addressed both theoretical and computation issues involved with UQ in high performance computing (HPC). Specific topics included Scalable algorithms for UQ, Calibration, estimation and identification, and Data-driven reduced order models for UQ.

Format

Participation was open for a limited number of external registrants. The expected outcome of this workshop was to foster new links between people that have strengths in UQ science with people that have strengths in HPC.

Schedule

Wednesday, May 2, 2012
Oak Ridge National Laboratory

8:30-8:55 a.m. Registration and Continental Breakfast
8:55-9:00 Introduction and Welcome
Pierre Gremaud, SAMSI
  Scalable Algorithms for UQ
9:00-9:45 Max Gunzburger, Florida State University
9:45-10:30 Dongbin Xiu, Purdue University
Practical Stochastic Computation Algorithms For Large-Scale Systems
10:30-11:00 Break
11:00-11:45 Eric Phipps, Sandia National Laboratories
Exploring Embedded UQ Approaches for Improved Scalability and Efficiency
11:45-12:30 Mihai Anitescu, ANL
Scalable Gaussian Process Analysis
12:30-2:00 Lunch
2:00-2:45 Daniel Tartakovsky, University of California-San Diego
Uncertainty Quantification for Nonlinear Parabolic & Hyperbolic Conservation Laws
2:45-3:30 Habib Najm, Sandia National Laboratories
Bayesian Parameter Estimation with Partial Information
3:30-4:00 Break
4:00-4:45 John Burkardt, Florida State University
Extending the Power of Sparse Collocation

Thursday, May 3, 2012
Oak Ridge National Laboratory

8:30-9:00 a.m. Registration and Continental Breakfast
  Application, Software, and Data-driven Reduced Order Models
9:00-9:45 Kate Evans, Oak Ridge National Laboratory
Scalable Algorithms for Climate Modeling
9:45-10:30 Serge Guillas, University College, London
Bayesian Calibration and Emulation of Geophysical Computer Models Using High Performance Computing
10:30-11:00 Break
11:00-11:45 Ernesto Prudencio and Karl W. Schulz, University of Texas
HPC Challenges Related to UQ Algorithms
11:45-12:30 Karl Schulz, University of Texas
12:30-2:00 Lunch
2:00-2:45 Marta D'Elia, Florida State University
Data Assimilation in Hemodynamics,Bayesian Inversion and Model Reduction
  Resources and Opportunities at ORNL and the DOE
2:45-3:30 Karen Pao, ASCR - DOE
Uncertainty Quantification and the March to Exascale
3:30-4:00 Break
4:00-4:30 Poster Advertisements
4:30-4:45 Jeff Nichols, Oak Ridge National Laboratory
4:45-8:00 Poster Session and Reception

SAMSI will provide poster presentation boards and tape. The board dimensions are 4 ft. wide by 3 ft. high. They are tri-fold with each side being 1 ft. wide and the center 2 ft. wide. Please make sure your poster fits the board. The boards can accommodate up to 16 pages of paper measuring 8.5 inches by 11 inches.

Friday, May 4, 2012
Oak Ridge National Laboratory

8:30-9:00 a.m. Registration and Continental Breakfast
  Calibration, Estimation and Identification
9:00-9:45 Don Estep, Colorado State University
Stochastic Inverse Problems for Parameter Determination
9:45-10:30 Youssef Marsouk, MIT
Large-scale Bayesian inference without MCMC
10:30-11:00 Break
11:00-11:45 Omar Ghattas, University of Texas
Extreme-scale UQ for inverse problems with applications to global seismic inversion
11:45-12:30 Guannan Zhang, Florida State University
Stochastic Model Calibration with Sparse-grid Bayesian Method for Computationally Expensive Simulations
12:30-3:00 Working Lunch & Optional Laboratory Tour
  1. National Center for Computing Sciences
  2. Spallation Neutron Source
  3. High Flux Isotope Reactor
  4. Graphite Reactor
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