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Faster Segmented Sort on GPUs

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Euro-Par 2023: Parallel Processing (Euro-Par 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14100))

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Abstract

Efficient parallel implementations of various sorting algorithms on modern hardware platforms are essential to numerous application areas. In this paper, we first measure the performance of the leading segmented sort implementation on CUDA-enabled GPUs and determine optimal setups using the resulting runtimes. Subsequently, we propose a number of changes that improve efficiency for segments of specific lengths. Furthermore, an alternative key-only version is introduced, that is specifically optimized to just sort keys instead of key-value pairs, which allows for further optimization. Performance is evaluated by comparing runtimes of the original algorithm with our improved version for segments of different lengths resulting in average speedups between 1.26 and 1.35 on four GPUs of different generations (Pascal, Volta, Ampere, Ada Lovelace). Furthermore, comparison to alternative segmented sort implementations from CUB and ModernGPU results in average speedups of at least 2.2 and 2.5, respectively, across all tested architectures. To illustrate how our improved sorting algorithm can be beneficial in a practical application, we have integrated it into the MetaCache-GPU pipeline for metagenomic DNA classification resulting in speedups of up to 25.6% for the sorting step. Code is publicly available at

https://gitlab.rlp.net/pararch/faster-segmented-sort-on-gpus.

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Notes

  1. 1.

    https://gitlab.rlp.net/pararch/faster-segmented-sort-on-gpus.

  2. 2.

    https://nvlabs.github.io/cub/struct_device_segmented_sort.html.

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Author information

Authors and Affiliations

  1. Institute of Computer Science, Johannes Gutenberg University, 55128, Mainz, Germany

    Robin Kobus, Johannes Nelgen, Valentin Henkys & Bertil Schmidt

Authors
  1. Robin Kobus
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  2. Johannes Nelgen
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  3. Valentin Henkys
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  4. Bertil Schmidt
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Corresponding author

Correspondence to Bertil Schmidt .

Editor information

Editors and Affiliations

  1. University of Glasgow, Glasgow, UK

    José Cano

  2. University of Cyprus, Nicosia, Cyprus

    Marios D. Dikaiakos

  3. University of Cyprus, Nicosia, Cyprus

    George A. Papadopoulos

  4. Chalmers University of Technology, Gothenburg, Sweden

    Miquel Pericàs

  5. University of Manchester, Manchester, UK

    Rizos Sakellariou

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Kobus, R., Nelgen, J., Henkys, V., Schmidt, B. (2023). Faster Segmented Sort on GPUs. In: Cano, J., Dikaiakos, M.D., Papadopoulos, G.A., Pericàs, M., Sakellariou, R. (eds) Euro-Par 2023: Parallel Processing. Euro-Par 2023. Lecture Notes in Computer Science, vol 14100. Springer, Cham. https://doi.org/10.1007/978-3-031-39698-4_45

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  • DOI: https://doi.org/10.1007/978-3-031-39698-4_45

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-39697-7

  • Online ISBN: 978-3-031-39698-4

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