When:
November 29, 2021 @ 1:00 pm – 2:00 pm
2021-11-29T13:00:00-06:00
2021-11-29T14:00:00-06:00

APS Scientific Computation Seminar

Speaker: Valerio Pascucci
John R. Parks Endowed Chair, University of Utah Professor, School of Computing
Faculty, Scientific Computing, and Imaging Institute
Director, Center for Extreme Data Management Analysis and Visualization (CEDMAV)

Title:    The National Science Data Fabric: Democratizing Data Access for Science and Society

Date: Monday, November 29, 2021

Time:   1:00 p.m. (Central Time)
Location:
Microsoft Teams meeting

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Phone Conference ID: 707 344 060#

Speaker:

Valerio Pascucci

John R. Parks Endowed Chair, University of Utah

Professor, School of Computing
Faculty, Scientific Computing, and Imaging Institute
Director, Center for Extreme Data Management Analysis and Visualization (CEDMAV)

 

Title:

The National Science Data Fabric: Democratizing Data Access for Science and Society

Abstract:

Effective use of data management techniques for the analysis and visualization of massive scientific data is a crucial ingredient for the success of any experimental facility, supercomputing center, or cyberinfrastructure that supports data-intensive scientific investigations. Data movements have become a central component that can enable or stifle innovation in the progress towards high-resolution experimental data acquisition (e.g., APS, SLAC, NSLS II). However, universal data delivery remains elusive, limiting the scientific impacts of these facilities. This is particularly true for high-volume/high-velocity datasets and resource-constrained institutions. This talk will present the National Science Data Fabric (NSDF) testbed, which introduces a novel trans-disciplinary data fabric integrating access to and use of shared storage, networking, computing, and educational resources. The NSDF technology addresses the key data management challenges involved in constructing complex streaming workflows that take advantage of any data processing opportunities that arise while the data is in motion. This technology finds practical use in many research and industrial applications, including materials science, precision agriculture, ecology, and telemedicine. This NSDF overview will include several techniques that allow building a scalable data movement infrastructure for fast I/O while organizing the data in a way that makes it immediately accessible for analytics and visualization. For example, I will present a use case for the real-time data acquisition from an APS beamline to allow remote users to monitor the progress of an experiment.