Comparative Study of the Execution Time of Parallel Heat Equation on CPU and GPU

Parallelization has become a universal technique for computing an intensive scientific simulation to shorten the execution time of complex problems. It consists of bringing together the power of several thousand processors to perform complex calculations at high speed. The choice of the runtime envi...

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Permalink: http://skupnikatalog.nsk.hr/Record/nsk.NSK01001163141/Details
Matična publikacija: Journal of communications software and systems (Online)
17 (2021), 4 ; str. 350-357
Glavni autori: Belhaous, Safa (Author), Chokri, Soumia, Baroud, Sohaib, Mestari, Mohamed
Vrsta građe: e-članak
Jezik: eng
Online pristup: https://doi.org/10.24138/jcomss-2021-0133
Elektronička verzija članka
Elektronička verzija članka
Elektronička verzija članka
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024 7 |2 doi  |a 10.24138/jcomss-2021-0133 
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040 |a HR-ZaNSK  |b hrv  |c HR-ZaNSK  |e ppiak 
041 0 |a eng 
042 |a croatica 
044 |a ci  |c hr 
080 1 |2 2011 
100 1 |a Belhaous, Safa  |4 aut  |9 HR-ZaNSK 
245 1 0 |a Comparative Study of the Execution Time of Parallel Heat Equation on CPU and GPU  |h [Elektronička građa]  |c Safa Belhaous, Soumia Chokri, Sohaib Baroud, Mohamed Mestari. 
300 |b Ilustr. 
504 |a Bibliografija: 
504 |a Summary. 
520 |a Parallelization has become a universal technique for computing an intensive scientific simulation to shorten the execution time of complex problems. It consists of bringing together the power of several thousand processors to perform complex calculations at high speed. The choice of the runtime environment to execute parallel programs significantly influences the execution time. For this reason, this article aims to materialize the impact of computing architectures on the performance of parallel implementations. To better achieve this contribution, we have implemented the heat equation executed on CUDA platform and we have compared the results with those of SkelGIS implementation from the literature. Through the results of the experiments, we demonstrated that the execution time of the CUDA implementation on graphics processing unit (GPU) is almost 100X faster for very large meshes compared to the other implementations. 
700 1 |a Chokri, Soumia  |4 aut  |9 HR-ZaNSK 
700 1 |a Baroud, Sohaib  |4 aut  |9 HR-ZaNSK 
700 1 |a Mestari, Mohamed  |4 aut  |9 HR-ZaNSK 
773 0 |t Journal of communications software and systems (Online)  |x 1846-6079  |g 17 (2021), 4 ; str. 350-357  |w nsk.(HR-ZaNSK)000644741 
981 |b Be2021 
856 4 0 |u https://doi.org/10.24138/jcomss-2021-0133 
856 4 0 |u https://jcoms.fesb.unist.hr/10.24138/jcomss-2021-0133/  |y Elektronička verzija članka 
856 4 0 |u https://jcoms.fesb.unist.hr/pdfs/v17n4_2021-0133_belhaous.pdf  |y Elektronička verzija članka 
856 4 1 |y Digitalna.nsk.hr 
856 4 0 |u https://hrcak.srce.hr/270741  |y Elektronička verzija članka