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Developing Efficient Discrete Simulations on Multicore and GPU Architectures

1
Department of Computer Architecture and Technology, Universidad de Sevilla, Avenida Reina Mercedes s/n, 41012 Sevilla, Spain
2
Department of Condensed Matter Physics, Universidad de Sevilla, Avenida Reina Mercedes s/n, 41012 Sevilla, Spain
*
Author to whom correspondence should be addressed.
Electronics 2020, 9(1), 189; https://doi.org/10.3390/electronics9010189
Received: 16 December 2019 / Revised: 10 January 2020 / Accepted: 12 January 2020 / Published: 19 January 2020
(This article belongs to the Section Computer Science & Engineering)
In this paper we show how to efficiently implement parallel discrete simulations on multicore and GPU architectures through a real example of an application: a cellular automata model of laser dynamics. We describe the techniques employed to build and optimize the implementations using OpenMP and CUDA frameworks. We have evaluated the performance on two different hardware platforms that represent different target market segments: high-end platforms for scientific computing, using an Intel Xeon Platinum 8259CL server with 48 cores, and also an NVIDIA Tesla V100 GPU, both running on Amazon Web Server (AWS) Cloud; and on a consumer-oriented platform, using an Intel Core i9 9900k CPU and an NVIDIA GeForce GTX 1050 TI GPU. Performance results were compared and analyzed in detail. We show that excellent performance and scalability can be obtained in both platforms, and we extract some important issues that imply a performance degradation for them. We also found that current multicore CPUs with large core numbers can bring a performance very near to that of GPUs, and even identical in some cases. View Full-Text
Keywords: laser dynamics; parallel computing; cellular automata; GPUs and multi-core processors performance laser dynamics; parallel computing; cellular automata; GPUs and multi-core processors performance
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  • Externally hosted supplementary file 1
    Link: https://github.com/dcagigas/Laser-Cellular-Automata
    Description: The source code of the different implementations and the results achieved are available at https: //github.com/dcagigas/Laser-Cellular-Automata.
MDPI and ACS Style

Cagigas-Muñiz, D.; Diaz-del-Rio, F.; López-Torres, M.R.; Jiménez-Morales, F.; Guisado, J.L. Developing Efficient Discrete Simulations on Multicore and GPU Architectures. Electronics 2020, 9, 189. https://doi.org/10.3390/electronics9010189

AMA Style

Cagigas-Muñiz D, Diaz-del-Rio F, López-Torres MR, Jiménez-Morales F, Guisado JL. Developing Efficient Discrete Simulations on Multicore and GPU Architectures. Electronics. 2020; 9(1):189. https://doi.org/10.3390/electronics9010189

Chicago/Turabian Style

Cagigas-Muñiz, Daniel, Fernando Diaz-del-Rio, Manuel R. López-Torres, Francisco Jiménez-Morales, and José L. Guisado 2020. "Developing Efficient Discrete Simulations on Multicore and GPU Architectures" Electronics 9, no. 1: 189. https://doi.org/10.3390/electronics9010189

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