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GPU Cloud Architectures for Bioinformatic Applications

  • Conference paper
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Bioinformatics and Biomedical Engineering (IWBBIO 2023)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 13919))

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Abstract

The world of computing is constantly evolving. The trends that are sha** today’s applications are Cloud computing and GPU computing. These technologies allow bringing high performance computations to low power devices, when using a computing outsourcing architecture. Following the trend, bioinformatic applications are looking to take advantage of these paradigms, but there are challenges that have to be solved. Data that these applications work with is usually sensible and has to be protected. Also, GPU usage in Cloud architectures currently presents inefficiencies. This paper makes a review of the characteristics of Cloud computing outsourcing architectures, including the security aspects, and GPU usage for these applications. The proposed architecture includes GPU devices and tries to make efficient use of them. The experiments show that it has the opportunity to increase parallelism and reduce context switching costs when running different applications concurrently on the GPU.

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Notes

  1. 1.

    Galaxy is an open-source web-based framework for performing computational analyses in fields such as bioinformatics, genomics, proteomics, and others. It has an easy-to-use interface for running complex workflows and supports a variety of tools for genome assembly, annotation, and visualization, among other things.

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Acknowledgments

This work was supported by the Spanish Research Agency (AEI) under project HPC4Industry PID2020-120213RB-I00.

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Authors and Affiliations

  1. University of Alicante, Alicante, Spain

    Antonio Maciá-Lillo, Tamai Ramírez, Higinio Mora, Antonio Jimeno-Morenilla & José-Luis Sánchez-Romero

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  1. Antonio Maciá-Lillo
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  2. Tamai Ramírez
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  3. Higinio Mora
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Correspondence to Antonio Maciá-Lillo .

Editor information

Editors and Affiliations

  1. University of Granada, Granada, Spain

    Ignacio Rojas

  2. University of Granada, Granada, Spain

    Olga Valenzuela

  3. University of Granada, Granada, Spain

    Fernando Rojas Ruiz

  4. University of Granada, Granada, Spain

    Luis Javier Herrera

  5. University of Granada, Granada, Spain

    Francisco Ortuño

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Maciá-Lillo, A., Ramírez, T., Mora, H., Jimeno-Morenilla, A., Sánchez-Romero, JL. (2023). GPU Cloud Architectures for Bioinformatic Applications. In: Rojas, I., Valenzuela, O., Rojas Ruiz, F., Herrera, L.J., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2023. Lecture Notes in Computer Science(), vol 13919. Springer, Cham. https://doi.org/10.1007/978-3-031-34953-9_6

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  • DOI: https://doi.org/10.1007/978-3-031-34953-9_6

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