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Title: BEAM: A Computational Workflow System for Managing and Modeling Material Characterization Data in HPC Environments

Abstract

Improvements in scientific instrumentation allow imaging at mesoscopic to atomic length scales, many spectroscopic modes, and now—with the rise of multimodal acquisition systems and the associated processing capability—the era of multidimensional, informationally dense data sets has arrived. Technical issues in these combinatorial scientific fields are exacerbated by computational challenges best summarized as a necessity for drastic improvement in the capability to transfer, store, and analyze large volumes of data. The Bellerophon Environment for Analysis of Materials (BEAM) platform provides material scientists the capability to directly leverage the integrated computational and analytical power of High Performance Computing (HPC) to perform scalable data analysis and simulation via an intuitive, cross-platform client user interface. This framework delivers authenticated, “push-button” execution of complex user workflows that deploy data analysis algorithms and computational simulations utilizing the converged compute-and-data infrastructure at Oak Ridge National Laboratory's (ORNL) Compute and Data Environment for Science (CADES) and HPC environments like Titan at the Oak Ridge Leadership Computing Facility (OLCF). In this work we address the underlying HPC needs for characterization in the material science community, elaborate how BEAM's design and infrastructure tackle those needs, and present a small sub-set of user cases where scientists utilized BEAM across a broadmore » range of analytical techniques and analysis modes.« less

Authors:
 [1];  [1];  [1];  [2];  [1];  [1];  [1];  [1];  [1];  [1];  [1];  [1];  [1];  [1]
+ Show Author Affiliations
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  2. Vanderbilt Univ., Nashville, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities Division
OSTI Identifier:
1567545
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Procedia Computer Science
Additional Journal Information:
Journal Volume: 80; Journal Issue: C; Journal ID: ISSN 1877-0509
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 96 KNOWLEDGE MANAGEMENT AND PRESERVATION; computational workflows; HPC workflows; data management; materials science; materials modeling; scalable data analysis; user experience design; multi-tier architectures

Citation Formats

Lingerfelt, E. J., Belianinov, A., Endeve, E., Ovchinnikov, Oleg, Somnath, S., Borreguero, J. M., Grodowitz, N., Park, B., Archibald, R. K., Symons, C. T., Kalinin, S. V., Messer, O. E. B., Shankar, M., and Jesse, S. BEAM: A Computational Workflow System for Managing and Modeling Material Characterization Data in HPC Environments. United States: N. p., 2016. Web. doi:10.1016/j.procs.2016.05.410.
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Lingerfelt, E. J., Belianinov, A., Endeve, E., Ovchinnikov, Oleg, Somnath, S., Borreguero, J. M., Grodowitz, N., Park, B., Archibald, R. K., Symons, C. T., Kalinin, S. V., Messer, O. E. B., Shankar, M., & Jesse, S. BEAM: A Computational Workflow System for Managing and Modeling Material Characterization Data in HPC Environments. United States. https://doi.org/10.1016/j.procs.2016.05.410
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Lingerfelt, E. J., Belianinov, A., Endeve, E., Ovchinnikov, Oleg, Somnath, S., Borreguero, J. M., Grodowitz, N., Park, B., Archibald, R. K., Symons, C. T., Kalinin, S. V., Messer, O. E. B., Shankar, M., and Jesse, S. Wed . "BEAM: A Computational Workflow System for Managing and Modeling Material Characterization Data in HPC Environments". United States. https://doi.org/10.1016/j.procs.2016.05.410. https://www.osti.gov/servlets/purl/1567545.
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@article{osti_1567545,
title = {BEAM: A Computational Workflow System for Managing and Modeling Material Characterization Data in HPC Environments},
author = {Lingerfelt, E. J. and Belianinov, A. and Endeve, E. and Ovchinnikov, Oleg and Somnath, S. and Borreguero, J. M. and Grodowitz, N. and Park, B. and Archibald, R. K. and Symons, C. T. and Kalinin, S. V. and Messer, O. E. B. and Shankar, M. and Jesse, S.},
abstractNote = {Improvements in scientific instrumentation allow imaging at mesoscopic to atomic length scales, many spectroscopic modes, and now—with the rise of multimodal acquisition systems and the associated processing capability—the era of multidimensional, informationally dense data sets has arrived. Technical issues in these combinatorial scientific fields are exacerbated by computational challenges best summarized as a necessity for drastic improvement in the capability to transfer, store, and analyze large volumes of data. The Bellerophon Environment for Analysis of Materials (BEAM) platform provides material scientists the capability to directly leverage the integrated computational and analytical power of High Performance Computing (HPC) to perform scalable data analysis and simulation via an intuitive, cross-platform client user interface. This framework delivers authenticated, “push-button” execution of complex user workflows that deploy data analysis algorithms and computational simulations utilizing the converged compute-and-data infrastructure at Oak Ridge National Laboratory's (ORNL) Compute and Data Environment for Science (CADES) and HPC environments like Titan at the Oak Ridge Leadership Computing Facility (OLCF). In this work we address the underlying HPC needs for characterization in the material science community, elaborate how BEAM's design and infrastructure tackle those needs, and present a small sub-set of user cases where scientists utilized BEAM across a broad range of analytical techniques and analysis modes.},
doi = {10.1016/j.procs.2016.05.410},
journal = {Procedia Computer Science},
number = C,
volume = 80,
place = {United States},
year = {Wed Jun 01 00:00:00 EDT 2016},
month = {Wed Jun 01 00:00:00 EDT 2016}
}
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https://doi.org/10.1016/j.procs.2016.05.410
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Works referenced in this record:

Near Real-time Data Analysis of Core-collapse Supernova Simulations with Bellerophon
journal, January 2014

Band Excitation in Scanning Probe Microscopy: Recognition and Functional Imaging
journal, April 2014

Identification of phases, symmetries and defects through local crystallography
journal, July 2015

  • Belianinov, Alex; He, Qian; Kravchenko, Mikhail
  • Nature Communications, Vol. 6, Issue 1
  • DOI: 10.1038/ncomms8801

Molecular Dynamics Force-Field Refinement against Quasi-Elastic Neutron Scattering Data
journal, December 2015

  • Borreguero, Jose M.; Lynch, Vickie E.
  • Journal of Chemical Theory and Computation, Vol. 12, Issue 1
  • DOI: 10.1021/acs.jctc.5b00878

Scalable molecular dynamics with NAMD
journal, January 2005

  • Phillips, James C.; Braun, Rosemary; Wang, Wei
  • Journal of Computational Chemistry, Vol. 26, Issue 16, p. 1781-1802
  • DOI: 10.1002/jcc.20289

Sassena — X-ray and neutron scattering calculated from molecular dynamics trajectories using massively parallel computers
journal, July 2012

Mantid—Data analysis and visualization package for neutron scattering and μ SR experiments
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  • Arnold, O.; Bilheux, J. C.; Borreguero, J. M.
  • Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 764
  • DOI: 10.1016/j.nima.2014.07.029
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