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Big data meets big science

Published:01 July 2014Publication History
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Abstract

Next-generation scientific instruments are forcing researchers to question the limits of massively parallel computing.

References

  1. Francesco De Carlo Doga Gürsoy et al., Scientific Data Exchange: A schema for HDF5-based storage of raw and analyzed data. Submitted to J. Synchrotron Radiation.Google ScholarGoogle Scholar
  2. Rachel Mak, Mirna Lerotic, Holger Fleckenstein, Stefan Vogt, Stefan M. Wild, Sven Leyffer, Yefim Sheynkin, and Chris Jacobsen. Non-negative matrix analysis for effective feature extraction in X-ray spectromicroscopy. Submitted to the Royal Society of Chemistry for a Faraday Discussion meeting. DOI: 10.1039/c000000x.Google ScholarGoogle Scholar
  3. Michael Stonebraker, Paul Brown, Donghui Zhang and Jacek Becla. SciDB: A database management system for applications with complex analytics. Computing in Science & Engineering, 15, 54-62 (2013), DOI:http://dx.doi.org/10.1109/MCSE.2013.19. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Big data meets big science

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          • Published in

            cover image Communications of the ACM
            Communications of the ACM  Volume 57, Issue 7
            July 2014
            98 pages
            ISSN:0001-0782
            EISSN:1557-7317
            DOI:10.1145/2622628
            • Editor:
            • Moshe Y. Vardi
            Issue’s Table of Contents

            Copyright © 2014 ACM

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            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 1 July 2014

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