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Issue No.06 - Nov.-Dec. (2011 vol.13)
pp: 14-24
James Ahrens , Los Alamos National Laboratory
Bruce Hendrickson , Sandia National Labs
Gabrielle Long , Argonne National Laboratory
Steve Miller , Oak Ridge National Laboratory
Rob Ross , Argonne National Laboratory
Dean Williams , Lawrence Livermore National Laboratory
ABSTRACT
<p>Given its leading role in high-performance computing for modeling and simulation and its many experimental facilities, the US Department of Energy has a tremendous need for data-intensive science. Locating the challenges and commonalities among three case studies illuminates, in detail, the technical challenges involved in realizing data-intensive science.</p>
INDEX TERMS
Data-intensive science, high-performance computing, data management, scientific computing
CITATION
James Ahrens, Bruce Hendrickson, Gabrielle Long, Steve Miller, Rob Ross, Dean Williams, "Data-Intensive Science in the US DOE: Case Studies and Future Challenges", Computing in Science & Engineering, vol.13, no. 6, pp. 14-24, Nov.-Dec. 2011, doi:10.1109/MCSE.2011.77
REFERENCES
1. S. Solomon et al., eds., Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, 2007, Cambridge Univ. Press, www.ipcc.ch/publications_and_data/ar4/wg1/ encontents.html.
2. W. Washington et al., Scientific Grand Challenges: Challenges in Climate Change Science and the Role of Computing at the Extreme Scale, US Dept. Energy, 2008; www.er.doe.gov/ascr/ProgramDocuments/Docs ClimateReport.pdf.
3. B. Allcock et al., ASCR Science Requirements, report, US Office of Advanced Scientific Computing Research Network Requirements Workshop, 2009; www.es.net/assets/Papers-and-Publications ASCR-Net-Req-Workshop-2009-Final-Report.pdf .
4. B. Fultz, K. Herwig, and G. Long, Computational Scattering Science 2010, Argonne Nat'l Lab., 2010, www.its.caltech.edu/~matsci/PublishCompScatWkshp_2010.html .
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