Presentation Open Access

Scalable, Data Driven Plasma Simulations with PIConGPU

Huebl, Axel; Widera, René; Garten, Marco; Pausch, Richard; Steiniger, Klaus; Bastrakov, Sergei; Meyer, Felix; Bastrakova, Ksenia; Debus, Alexander; Kluge, Thomas; Ehrig, Simeon; Werner, Matthias; Worpitz, Benjamin; Matthes, Alexander; Rudat, Sophie; Starke, Sebastian; Bussmann, Michael

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  <titles>
    <title>Scalable, Data Driven Plasma Simulations with PIConGPU</title>
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  <publisher>Rodare</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>LPA</subject>
    <subject>laser-plasma</subject>
    <subject>particle-in-cell</subject>
    <subject>HPC</subject>
    <subject>manycore</subject>
    <subject>GPU</subject>
    <subject>simulation</subject>
    <subject>interactive</subject>
    <subject>big data</subject>
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  <dates>
    <date dateType="Issued">2019-06-13</date>
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  <language>en</language>
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    <description descriptionType="Abstract">&lt;p&gt;PIConGPU is an open source, multi-platform particle-in-cell code scaling to the fastest supercomputers in the TOP500 list. We present the architecture, novel developments, and workflows that enable high-precision, fast turn-around computations on Exascale-machines. Furthermore, we present our strategies to handle extreme data flows from thousands of GPUs for analysis with in situ processing and open data formats (openPMD). PIConGPU is since recently furthermore natively controlled by a Python Jupyter interface and we research just-in-time kernel generation for C++ with our Cling-CUDA extensions.&lt;/p&gt;</description>
    <description descriptionType="Other">Invited minisymposium talk at the Platform for Advanced Scientific Computing (PASC) Conference (PASC19) at ETH Zurich (Zurich, Switzerland).</description>
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Publication date:
June 13, 2019
DOI:
10.14278/rodare.131

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Keyword(s):
LPA laser-plasma particle-in-cell HPC manycore GPU simulation interactive big data
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