Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Parallel MPI image reconstructions in GPU using CUDA

Published

Author(s)

Klaus Natorf Quelhas, Mark-Alexander Henn, Ricardo Cordeiro de 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

Keywords

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

Citation

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], https://doi.org/10.18416/IJMPI.2023.2303043, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=936159 (Accessed April 20, 2024)
Created March 19, 2023, Updated March 23, 2023