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Massively Parallel Evolutionary Computation on GPGPUs pp 369–387Cite as

Using Large-Scale Parallel Systems for Complex Crystallographic Problems in Materials Science

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Abstract

Very recently, the design and understanding of materials synthesis have received a huge effort in which modeling approaches are decisive. Here, we focus on the generation of crystalline inorganic frameworks. Despite the high-throughput (HT) methods that have proved to be useful for the discovery of zeolites, the determination of the new phase’s structure takes up a large part of the entire process. Therefore, we show how graphic processing units or GPUs can be used in order to speed up this mandatory step. We describe GPUs and predictive methods for phase determination. Then, we show all the details that allowed us to reach a stable and robust solution with benchmark analysis and real applications to zeolites.

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Author notes

  1. Laurent A. Baumes

    Present address: ExxonMobil Research and Engineering Co. RDSS - Research Computing, 1545 Route 22 East, Room CC286, Annandale, NJ, 08801, USA

Authors and Affiliations

  1. Insituto de Tecnologia Quimica, UPV-CSIC, Valencia, Spain

    Laurent A. Baumes

  2. ICUBE, University of Strasbourg, Illkirch, France

    Frédéric Krüger & Pierre Collet

Authors
  1. Laurent A. Baumes
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  2. Frédéric Krüger
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  3. Pierre Collet
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Correspondence to Laurent A. Baumes .

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Editors and Affiliations

  1. and Information Science, Hannan University Dept. of Management, Matsubara, Osaka, Japan

    Shigeyoshi Tsutsui

  2. ICube Laboratory UMR CNRS 7357, Université de Strasbourg, Illkirch, France

    Pierre Collet

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Baumes, L.A., Krüger, F., Collet, P. (2013). Using Large-Scale Parallel Systems for Complex Crystallographic Problems in Materials Science. In: Tsutsui, S., Collet, P. (eds) Massively Parallel Evolutionary Computation on GPGPUs. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37959-8_17

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  • DOI: https://doi.org/10.1007/978-3-642-37959-8_17

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