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