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PUBLICATIONS

Parallel MPI image reconstructions in GPU using CUDA

Published

Author(s)

Klaus Natorf Quelhas, Mark-Alexander Henn, Ricardo Farias, Weston L. Tew, Solomon I. Woods

Abstract

This work shows that it is possible to obtain faster MPI image reconstructions by implementing the algorithms in parallel in Graphics Processing Units (GPUs) using NVIDIA's CUDA (Compute Unified Device Architecture). While the parallel Kaczmarz's algorithm was slower than its serial version running in the Central Processing Unit (CPU), the parallel version of the Conjugate Gradient Normal Residual (CGNR) algorithm was about 58 times faster than its serial implementation, and about 10 times faster than the serial implementation of Kaczmarz's.
Citation
International Journal on Magnetic Particle Imaging
Volume
9
Issue
1 Suppl 1
Pub Type
Journals

Download Paper

https://doi.org/10.18416/IJMPI.2023.2303043
Local Download

Keywords

Magnetic Particle Imaging, MPI, Graphics Processing Unit, GPU, Parallel computing, CUDA, Image reconstruction
Numerical methods and software, Nanomaterials, Magnetics and Image and signal processing

Citation

Natorf Quelhas, K. , Henn, M. , Farias, R. , Tew, W. and Woods, S. (2023), Parallel MPI image reconstructions in GPU using CUDA, International Journal on Magnetic Particle Imaging, [online], https://doi.org/10.18416/IJMPI.2023.2303043, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=936159 (Accessed December 9, 2024)

Issues

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Created March 19, 2023, Updated July 31, 2024