Accelerating Data Acquisition, Reduction, and Analysis at the Spallation Neutron Source

Autor: Mathieu Doucet, David A. Dillow, Russel Taylor, Thomas Proffen, Stuart I. Campbell, Garrett E. Granroth, Jim Kohl, Ross Miller, Dale Stansberry, Galen M. Shipman
Rok vydání: 2014
Předmět:
Zdroj: eScience
Popis: ORNL operates the world's brightest neutron source, the Spallation Neutron Source (SNS). Funded by the US DOE Office of Basic Energy Science, this national user facility hosts hundreds of scientists from around the world, providing a platform to enable break-through research in materials science, sustainable energy, and basic science. While the SNS provides scientists with advanced experimental instruments, the deluge of data generated from these instruments represents both a big data challenge and a big data opportunity. For example, instruments at the SNS can now generate multiple millions of neutron events per second providing unprecedented experiment fidelity but leaving the user with a dataset that cannot be processed and analyzed in a timely fashion using legacy techniques. To address this big data challenge, ORNL has developed a near real-time streaming data reduction and analysis infrastructure. The Accelerating Data Acquisition, Reduction, and Analysis (ADARA) system provides a live streaming data infrastructure based on a high-performance publish subscribe system, in situ data reduction, visualization, and analysis tools, and integration with a high-performance computing and data storage infrastructure. ADARA allows users of the SNS instruments to analyze their experiment as it is run and make changes to the experiment in real-time and visualize the results of these changes. In this paper we describe ADARA, provide a high-level architectural overview of the system, and present a set of use-cases and real-world demonstrations of the technology.
Databáze: OpenAIRE