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

Published in: Innovation in Education and Inclusion : Proceedings of the 16th LACCEI International Multi-Conference for Engineering, Education and Technology
Date of Conference: July 18-20, 2018
Location of Conference: Lima, Perú
Authors: José Sulla-Torres (Universidad Nacional de San Agustín, PE)
Milagros Mayta (Universidad Nacional de San Agustín, PE)
Henry Talavera (Universidad Nacional de San Agustín, PE)
Gonzalo Quispe (Universidad Nacional de San Agustín, PE)
Full Paper: #44

Abstract:

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.