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Parallel MPI image reconstructions in GPU using CUDA



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


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.
International Journal on Magnetic Particle Imaging
1 Suppl 1


Magnetic Particle Imaging, MPI, Graphics Processing Unit, GPU, Parallel computing, CUDA, Image reconstruction


Natorf Quelhas, K. , Henn, M. , Cordeiro de Farias, R. , Tew, W. and Woods, S. (2023), Parallel MPI image reconstructions in GPU using CUDA, International Journal on Magnetic Particle Imaging, [online],, (Accessed April 20, 2024)
Created March 19, 2023, Updated March 23, 2023