MPI windows on storage for HPC applications.

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  • Additional Information
    • Author-Supplied Keywords:
      MPI windows on storage
      Out-of-core computation
      Parallel I/O
    • NAICS/Industry Codes:
      334110 Computer and peripheral equipment manufacturing
      334112 Computer Storage Device Manufacturing
    • Abstract:
      Upcoming HPC clusters will feature hybrid memories and storage devices per compute node. In this work, we propose to use the MPI one-sided communication model and MPI windows as unique interface for programming memory and storage. We describe the design and implementation of MPI storage windows, and present its benefits for out-of-core execution, parallel I/O and fault-tolerance. In addition, we explore the integration of heterogeneous window allocations, where memory and storage share a unified virtual address space. When performing large, irregular memory operations, we verify that MPI windows on local storage incurs a 55% performance penalty on average. When using a Lustre parallel file system, “asymmetric” performance is observed with over 90% degradation in writing operations. Nonetheless, experimental results of a Distributed Hash Table, the HACC I/O kernel mini-application, and a novel MapReduce implementation based on the use of MPI one-sided communication, indicate that the overall penalty of MPI windows on storage can be negligible in most cases in real-world applications. [ABSTRACT FROM AUTHOR]
    • Abstract:
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    • Author Affiliations:
      1KTH Royal Institute of Technology, Stockholm 10044, Sweden
      2Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
      3Seagate Systems UK, Havant PO9 1SA, UK
    • ISSN:
      0167-8191
    • Accession Number:
      10.1016/j.parco.2018.05.007
    • Accession Number:
      130689990
  • Citations
    • ABNT:
      RIVAS-GOMEZ, S. et al. MPI windows on storage for HPC applications. Parallel Computing, [s. l.], v. 77, p. 38–56, 2018. DOI 10.1016/j.parco.2018.05.007. Disponível em: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=130689990&custid=s8280428. Acesso em: 11 dez. 2019.
    • AMA:
      Rivas-Gomez S, Gioiosa R, Peng IB, et al. MPI windows on storage for HPC applications. Parallel Computing. 2018;77:38-56. doi:10.1016/j.parco.2018.05.007.
    • APA:
      Rivas-Gomez, S., Gioiosa, R., Peng, I. B., Kestor, G., Narasimhamurthy, S., Laure, E., & Markidis, S. (2018). MPI windows on storage for HPC applications. Parallel Computing, 77, 38–56. https://doi.org/10.1016/j.parco.2018.05.007
    • Chicago/Turabian: Author-Date:
      Rivas-Gomez, Sergio, Roberto Gioiosa, Ivy Bo Peng, Gokcen Kestor, Sai Narasimhamurthy, Erwin Laure, and Stefano Markidis. 2018. “MPI Windows on Storage for HPC Applications.” Parallel Computing 77 (September): 38–56. doi:10.1016/j.parco.2018.05.007.
    • Harvard:
      Rivas-Gomez, S. et al. (2018) ‘MPI windows on storage for HPC applications’, Parallel Computing, 77, pp. 38–56. doi: 10.1016/j.parco.2018.05.007.
    • Harvard: Australian:
      Rivas-Gomez, S, Gioiosa, R, Peng, IB, Kestor, G, Narasimhamurthy, S, Laure, E & Markidis, S 2018, ‘MPI windows on storage for HPC applications’, Parallel Computing, vol. 77, pp. 38–56, viewed 11 December 2019, .
    • MLA:
      Rivas-Gomez, Sergio, et al. “MPI Windows on Storage for HPC Applications.” Parallel Computing, vol. 77, Sept. 2018, pp. 38–56. EBSCOhost, doi:10.1016/j.parco.2018.05.007.
    • Chicago/Turabian: Humanities:
      Rivas-Gomez, Sergio, Roberto Gioiosa, Ivy Bo Peng, Gokcen Kestor, Sai Narasimhamurthy, Erwin Laure, and Stefano Markidis. “MPI Windows on Storage for HPC Applications.” Parallel Computing 77 (September 2018): 38–56. doi:10.1016/j.parco.2018.05.007.
    • Vancouver/ICMJE:
      Rivas-Gomez S, Gioiosa R, Peng IB, Kestor G, Narasimhamurthy S, Laure E, et al. MPI windows on storage for HPC applications. Parallel Computing [Internet]. 2018 Sep [cited 2019 Dec 11];77:38–56. Available from: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=130689990&custid=s8280428