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High Performance Computing with Java Streams

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Euro-Par 2021: Parallel Processing Workshops (Euro-Par 2021)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13098))

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Abstract

Java streams enable an easy-to-use functional-like programming style that transparently supports parallel execution. This paper presents an approach that improves the performance of stream-based Java applications. The approach enables the effective usage of Java for HPC applications, due to data locality improvements (i.e., support for efficient data layouts), without losing the object-oriented view of data in the code. The approach extends the Java collections API to hide additional details concerning the data layout, enabling the transparent use of more memory-friendly data layouts. The enhanced Java Collection API enables an easy adaptation of existing Java codes making those Java codes suitable for HPC. Performance results show that improving the data locality can provide a two-fold performance gain in sequential stream applications, which translated into a similar gain over parallel stream implementations. Moreover, the performance is comparable to similar C implementations using OpenMP.

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Notes

  1. 1.

    The use of a single collection for both x and y elements is mandatory, since streams require a single iterator for accessing all the elements (i.e., for internal iteration).

  2. 2.

    Vectorisation was confirmed by inspection of the assembly generated.

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Acknowledgements

This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. The evaluation used the computing infra-structure of the project Search-ON2: Revitalization of HPC infrastructure of UMinho, (NORTE-07-0162-FEDER-000086), co-funded by the North Portugal Regional Operational Programme (ON.2-O Novo Norte), under the National Strategic Reference Framework (NSRF), through the European Regional Development Fund (ERDF).

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Authors and Affiliations

  1. Centro Algoritmi, Universidade do Minho, Braga, Portugal

    Rui Silva & João L. Sobral

Authors
  1. Rui Silva
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  2. João L. Sobral
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Corresponding author

Correspondence to João L. Sobral .

Editor information

Editors and Affiliations

  1. University of Lisbon, Lisbon, Portugal

    Ricardo Chaves

  2. Department of Computer Engineering, CiTIUS, University of Santiago de Compostela, Santiago de Compostela, La Coruña, Spain

    Dora B. Heras

  3. University of Lisbon, Lisbon, Portugal

    Aleksandar Ilic

  4. Koç University, Istanbul, Turkey

    Didem Unat

  5. Barcelona Supercomputing Center, Barcelona, Spain

    Rosa M. Badia

  6. University of Stirling, Stirling, UK

    Andrea Bracciali

  7. Louisiana State University, Baton Rouge, USA

    Patrick Diehl

  8. Mathematics and Computer Science, Argonne National Laboratory, Lemont, IL, USA

    Anshu Dubey

  9. Ajou University, Suwon, Korea (Republic of)

    Oh Sangyoon

  10. Tennessee Technological University, Cookeville, TN, USA

    Stephen L. Scott

  11. University of Pisa, Pisa, Italy

    Laura Ricci

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Silva, R., Sobral, J.L. (2022). High Performance Computing with Java Streams. In: Chaves, R., et al. Euro-Par 2021: Parallel Processing Workshops. Euro-Par 2021. Lecture Notes in Computer Science, vol 13098. Springer, Cham. https://doi.org/10.1007/978-3-031-06156-1_2

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  • DOI: https://doi.org/10.1007/978-3-031-06156-1_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06155-4

  • Online ISBN: 978-3-031-06156-1

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