Parareal Method for Anisotropic Diffusion Denoising

Conference Paper (2023)
Author(s)

X. Shan (TU Delft - Numerical Analysis)

MB Van Gijzen (TU Delft - Numerical Analysis)

Research Group
Numerical Analysis
Copyright
© 2023 X. Shan, M.B. van Gijzen
DOI related publication
https://doi.org/10.1007/978-3-031-30445-3_26
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 X. Shan, M.B. van Gijzen
Research Group
Numerical Analysis
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. @en
Pages (from-to)
313-322
ISBN (print)
9783031304446
Reuse Rights

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Abstract

This paper studies time-domain parallelisation using Parareal to speed up the computations of anisotropic diffusion filtering. We consider both explicit and implicit Euler based method for the propagation in time for Parareal. The Preconditioned Conjugate Gradient (PCG) method is used to solve the systems that arise in the implicit based method. The estimation of the iteration numbers of PCG allows us to predict the running time of Parareal calculation, which further guides us in the experimental stage. Parallelisation of the method is implemented using Coarray Fortran. We illustrate the experimental results on 3D low-field MRI images using up to 960 cores. The computational improvement in time is achieved.

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