Mejora de rendimiento en tiempo de ejecución de los Algoritmos de Compresión en CPU y GPU utilizando CUDA

Milagros Mayta-Rosas; Henry Talavera-Díaz; Gonzalo Quispe-Huanca; José Sulla-Torres

doi:10.18687/LACCEI2018.1.1.44

Mejora de rendimiento en tiempo de ejecución de los Algoritmos de Compresión en CPU y GPU utilizando CUDA

Milagros Mayta-Rosas, Henry Talavera-Díaz, Gonzalo Quispe-Huanca, José Sulla-Torres

Universidad Nacional de San Agustín

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

Resumen

Currently users handle large amounts of data that are increasing, consequently the compression of these introduces an additional overhead and the performance of the hardware can be reduced, therefore must take into account the execution time as a key element to choose properly the algorithm perform this action. In this paper we present a parallel implementation of Lempel-Ziv (LZ78) and Run Length Encoding (RLE) algorithms, originally sequential, using the parallel programming model and Compute Unified Device Architecture (CUDA), on a NVIDIA-branded GPU device. It presents a comparison between the execution time of the algorithms in CPU and in GPU demonstrating a significant improvement in the execution time of the process of data compression on the GPU in comparison with the implementation based on the CPU in both algorithms.

Título traducido de la contribución	Improved runtime performance of compression algorithms on CPU and GPU using CUDA
Idioma original	Español
Título de la publicación alojada	Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Editorial	Latin American and Caribbean Consortium of Engineering Institutions
ISBN (versión digital)	9780999344316
DOI	https://doi.org/10.18687/LACCEI2018.1.1.44
Estado	Publicada - 2018
Publicado de forma externa	Sí
Evento	16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology - Lima, Perú Duración: 18 jul. 2018 → 20 jul. 2018

Serie de la publicación

Nombre	Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volumen	2018-July
ISSN (versión digital)	2414-6390

Conferencia

Conferencia	16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology
País/Territorio	Perú
Ciudad	Lima
Período	18/07/18 → 20/07/18

Palabras clave

CUDA
GPU
LZ78
Lossless compression algorithms
Run Length Encoding

Acceder al documento

10.18687/LACCEI2018.1.1.44

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Mayta-Rosas, M., Talavera-Díaz, H., Quispe-Huanca, G., & Sulla-Torres, J. (2018). Mejora de rendimiento en tiempo de ejecución de los Algoritmos de Compresión en CPU y GPU utilizando CUDA. En Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology; Vol. 2018-July). Latin American and Caribbean Consortium of Engineering Institutions. https://doi.org/10.18687/LACCEI2018.1.1.44

Mayta-Rosas, Milagros ; Talavera-Díaz, Henry ; Quispe-Huanca, Gonzalo et al. / Mejora de rendimiento en tiempo de ejecución de los Algoritmos de Compresión en CPU y GPU utilizando CUDA. Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology. Latin American and Caribbean Consortium of Engineering Institutions, 2018. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology).

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abstract = "Currently users handle large amounts of data that are increasing, consequently the compression of these introduces an additional overhead and the performance of the hardware can be reduced, therefore must take into account the execution time as a key element to choose properly the algorithm perform this action. In this paper we present a parallel implementation of Lempel-Ziv (LZ78) and Run Length Encoding (RLE) algorithms, originally sequential, using the parallel programming model and Compute Unified Device Architecture (CUDA), on a NVIDIA-branded GPU device. It presents a comparison between the execution time of the algorithms in CPU and in GPU demonstrating a significant improvement in the execution time of the process of data compression on the GPU in comparison with the implementation based on the CPU in both algorithms.",

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author = "Milagros Mayta-Rosas and Henry Talavera-D{\'i}az and Gonzalo Quispe-Huanca and Jos{\'e} Sulla-Torres",

note = "Publisher Copyright: {\textcopyright} 2018 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.; 16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology ; Conference date: 18-07-2018 Through 20-07-2018",

year = "2018",

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Mayta-Rosas, M, Talavera-Díaz, H, Quispe-Huanca, G & Sulla-Torres, J 2018, Mejora de rendimiento en tiempo de ejecución de los Algoritmos de Compresión en CPU y GPU utilizando CUDA. En Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology. Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology, vol. 2018-July, Latin American and Caribbean Consortium of Engineering Institutions, 16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology, Lima, Perú, 18/07/18. https://doi.org/10.18687/LACCEI2018.1.1.44

Mejora de rendimiento en tiempo de ejecución de los Algoritmos de Compresión en CPU y GPU utilizando CUDA. / Mayta-Rosas, Milagros; Talavera-Díaz, Henry; Quispe-Huanca, Gonzalo et al.
Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology. Latin American and Caribbean Consortium of Engineering Institutions, 2018. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology; Vol. 2018-July).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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AB - Currently users handle large amounts of data that are increasing, consequently the compression of these introduces an additional overhead and the performance of the hardware can be reduced, therefore must take into account the execution time as a key element to choose properly the algorithm perform this action. In this paper we present a parallel implementation of Lempel-Ziv (LZ78) and Run Length Encoding (RLE) algorithms, originally sequential, using the parallel programming model and Compute Unified Device Architecture (CUDA), on a NVIDIA-branded GPU device. It presents a comparison between the execution time of the algorithms in CPU and in GPU demonstrating a significant improvement in the execution time of the process of data compression on the GPU in comparison with the implementation based on the CPU in both algorithms.

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Mayta-Rosas M, Talavera-Díaz H, Quispe-Huanca G, Sulla-Torres J. Mejora de rendimiento en tiempo de ejecución de los Algoritmos de Compresión en CPU y GPU utilizando CUDA. En Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology. Latin American and Caribbean Consortium of Engineering Institutions. 2018. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology). doi: 10.18687/LACCEI2018.1.1.44

Mejora de rendimiento en tiempo de ejecución de los Algoritmos de Compresión en CPU y GPU utilizando CUDA

Resumen

Serie de la publicación

Conferencia

Palabras clave

Acceder al documento

Otros archivos y enlaces

Huella

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