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Smash: A Compression Benchmark with AI Datasets from Remote GPU Virtualization Systems

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Hybrid Artificial Intelligent Systems (HAIS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13469))

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Abstract

Remote GPU virtualization is a mechanism that allows GPU-accelerated applications to be executed in computers without GPUs. Instead, GPUs from remote computers are used. Applications are not aware of using a remote GPU. However, overall performance depends on the throughput of the underlying network connecting the application to the remote GPUs. One way to increase this bandwidth is to compress transmissions made within the remote GPU virtualization middleware between the application side and the GPU side.

In this paper we make a two-fold contribution. On the one hand, we present a new compression benchmark with more than 40 compression libraries. On the other hand, we have gathered the internal transmissions of a remote GPU virtualization middleware while executing 4 popular artificial intelligence applications. With these data we have created a new dataset for testing compression libraries in this specific domain. Both, the new compression benchmark and the new dataset are publicly available.

This work was supported by the project “AI in Secure Privacy-Preserving Computing Continuum (AI-SPRINT)” through the European Union’s Horizon 2020 Research and Innovation Programme under Grant 101016577.

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Author information

Authors and Affiliations

  1. Universitat Politècnica de València, Valencia, Spain

    Cristian Peñaranda & Federico Silla

  2. Universitat de València, Valencia, Spain

    Carlos Reaño

Authors
  1. Cristian Peñaranda
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  2. Carlos Reaño
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  3. Federico Silla
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Corresponding author

Correspondence to Cristian Peñaranda .

Editor information

Editors and Affiliations

  1. University of Deusto, Bilbao, Spain

    Pablo García Bringas

  2. University of León, León, Spain

    Hilde Pérez García

  3. University of La Rioja, Logroño, La Rioja, Spain

    Francisco Javier Martínez de Pisón

  4. University of Oviedo, Oviedo, Spain

    José Ramón Villar Flecha

  5. Data Science and Big Data Analytics Lab, Pablo de Olavide University, Sevilla, Spain

    Alicia Troncoso Lora

  6. Department of Computer Science, University of Oviedo, Oviedo, Spain

    Enrique A. de la Cal

  7. Applied Computational Intelligence, University of Burgos, Burgos, Burgos, Spain

    Álvaro Herrero

  8. Universidad Pablo de Olavide, Seville, Spain

    Francisco Martínez Álvarez

  9. DIGIP, University of Bergamo, Dalmine, Bergamo, Italy

    Giuseppe Psaila

  10. Department of Industrial Engineering, University of A Coruña, Ferrol, Spain

    Héctor Quintián

  11. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Peñaranda, C., Reaño, C., Silla, F. (2022). Smash: A Compression Benchmark with AI Datasets from Remote GPU Virtualization Systems. In: García Bringas, P., et al. Hybrid Artificial Intelligent Systems. HAIS 2022. Lecture Notes in Computer Science(), vol 13469. Springer, Cham. https://doi.org/10.1007/978-3-031-15471-3_21

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  • DOI: https://doi.org/10.1007/978-3-031-15471-3_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-15470-6

  • Online ISBN: 978-3-031-15471-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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