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International Conference on Algorithms and Architectures for Parallel Processing

ICA3PP 2016: Algorithms and Architectures for Parallel Processing pp 118–125Cite as

Enabling Android-Based Devices to High-End GPGPUs

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10048))

Abstract

The success of Android is based on its unified Java programming model that allows to write platform-independent programs for a variety of different target platforms. In this paper we describe the first, to the best of our knowledge, offloading platform that enables Android devices with no GPU support to run Nvidia CUDA kernels by migrating their execution on high-end GPGPU servers. The framework is highly modular and exposes a rich Application Programming Interface (API) to the developers, making it highly transparent and hiding the complexity of the network layer. We present the first preliminary results, showing that not only GPGPU offloading is possible but it is also promising in terms of performance.

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Notes

  1. 1.

    http://www.dell.com/en-uk/work/learn/mobility-byod.

  2. 2.

    http://docs.nvidia.com/cuda/cuda-runtime-api/.

  3. 3.

    https://devblogs.nvidia.com/parallelforall/easy-introduction-cuda-c-and-c/.

  4. 4.

    http://docs.nvidia.com/cuda/cuda-samples/.

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Acknowledgments

This research has been supported by the Grant Agreement number: 644312 - RAPID - H2020-ICT-2014/H2020-ICT-2014-1 “Heterogeneous Secure Multi-level Remote Acceleration Service for Low-Power Integrated Systems and Devices”.

Author information

Authors and Affiliations

  1. Department of Science and Technologies, University of Napoli Parthenope, Naples, Italy

    Raffaele Montella, Carmine Ferraro, Valentina Pelliccia & Giulio Giunta

  2. Computation Institute, University of Chicago, Chicago, USA

    Raffaele Montella

  3. Sapienza University of Rome, Rome, Italy

    Sokol Kosta

  4. CMI, Aalborg University Copenhagen, Copenhagen, Denmark

    Sokol Kosta

Authors
  1. Raffaele Montella
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  2. Carmine Ferraro
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  3. Sokol Kosta
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  4. Valentina Pelliccia
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  5. Giulio Giunta
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Corresponding author

Correspondence to Giulio Giunta .

Editor information

Editors and Affiliations

  1. University Carlos III of Madrid, Leganes, Spain

    Jesus Carretero

  2. Carlos III University of Madrid, Leganes, Madrid, Spain

    Javier Garcia-Blas

  3. The University of Waikato, Hamilton, New Zealand

    Ryan K.L. Ko

  4. IBM Zurich Research Laboratory, Rüschlikon, Switzerland

    Peter Mueller

  5. Hiroshima University, Higashi-Hiroshima, Japan

    Koji Nakano

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© 2016 Springer International Publishing AG

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Montella, R., Ferraro, C., Kosta, S., Pelliccia, V., Giunta, G. (2016). Enabling Android-Based Devices to High-End GPGPUs. In: Carretero, J., Garcia-Blas, J., Ko, R., Mueller, P., Nakano, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2016. Lecture Notes in Computer Science(), vol 10048. Springer, Cham. https://doi.org/10.1007/978-3-319-49583-5_9

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  • DOI: https://doi.org/10.1007/978-3-319-49583-5_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49582-8

  • Online ISBN: 978-3-319-49583-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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