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A distributed approach for a COVID-19 fractional time-delay model

    Author

    • Mahdi Movahedian Moghaddam

    Department of Computer and Data Sciences, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran

,

Document Type : Regular paper

10.52547/CMCMA.1.1.95
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Abstract

After the spread of COVID-19, several attempts were made to model it mathematically. Due to the high power of fractional differential equation modeling, a time delay fractional model was presented for the modeling spread of COVID-19. The solution of these models is done by computer systems in several ways, including the fractional predictor-corrector method, which has many challenges. Among these challenges are execution time, scalability, and memory consumption. In previous research, the shared memory approach was presented to reduce the execution time challenge. Still, because of the challenges of scalability and memory consumption, a coarse-grained distributed approach was presented in this research. The results presented in this research have been compared with sequential approaches and shared memory. These results have been implemented based on the data announced by the city of Wuhan in 2019, and a speedup of 1.704 was achieved per execution on 1000 inputs

Keywords

  • grained parallelism
  • distributed computing
  • domain-specific parallelism
  • fractional calculus
  • predictor-corrector method
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Computational Mathematics and Computer Modeling with Applications (CMCMA)
Volume 1, Issue 1 - Serial Number 1
June 2022
Pages 95-104
Files
  • XML
  • PDF 264.43 K
History
  • Receive Date: 27 March 2023
  • Revise Date: 25 June 2023
  • Accept Date: 06 July 2023
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How to cite
  • RIS
  • EndNote
  • Mendeley
  • BibTeX
  • APA
  • MLA
  • HARVARD
  • CHICAGO
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Statistics
  • Article View: 317
  • PDF Download: 169

APA

Movahedian Moghaddam, M. (2022). A distributed approach for a COVID-19 fractional time-delay model. Computational Mathematics and Computer Modeling with Applications (CMCMA), 1(1), 95-104. doi: 10.52547/CMCMA.1.1.95

MLA

Movahedian Moghaddam, M. . "A distributed approach for a COVID-19 fractional time-delay model", Computational Mathematics and Computer Modeling with Applications (CMCMA), 1, 1, 2022, 95-104. doi: 10.52547/CMCMA.1.1.95

HARVARD

Movahedian Moghaddam, M. (2022). 'A distributed approach for a COVID-19 fractional time-delay model', Computational Mathematics and Computer Modeling with Applications (CMCMA), 1(1), pp. 95-104. doi: 10.52547/CMCMA.1.1.95

CHICAGO

M. Movahedian Moghaddam, "A distributed approach for a COVID-19 fractional time-delay model," Computational Mathematics and Computer Modeling with Applications (CMCMA), 1 1 (2022): 95-104, doi: 10.52547/CMCMA.1.1.95

VANCOUVER

Movahedian Moghaddam, M. A distributed approach for a COVID-19 fractional time-delay model. Computational Mathematics and Computer Modeling with Applications (CMCMA), 2022; 1(1): 95-104. doi: 10.52547/CMCMA.1.1.95

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