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GPU accelerated Monte Carlo simulation of pulsed-field gradient NMR experiments

Waudby, CA; Christodoulou, J; (2011) GPU accelerated Monte Carlo simulation of pulsed-field gradient NMR experiments. Journal of Magnetic Resonance , 211 (1) 67 - 73. 10.1016/j.jmr.2011.04.004.

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Abstract

The simulation of diffusion by Monte Carlo methods is often essential to describing NMR measurements of diffusion in porous media. However, simulation timescales must often span hundreds of milliseconds, with large numbers of trajectories required to ensure statistical convergence. Here we demonstrate that by parallelising code to run on graphics processing units (GPUs), these calculations may be accelerated by over three orders of magnitude, opening new frontiers in experimental design and analysis. As such cards are commonly installed on most desktop computers, we expect that this will prove useful in many cases where simple analytical descriptions are not available or appropriate, e.g. in complex geometries or where short gradient pulse approximations do not hold, or for the analysis of diffusion-weighted MRI in complex tissues such as the lungs and brain. (C) 2011 Elsevier Inc. All rights reserved.

Type: Article
Title: GPU accelerated Monte Carlo simulation of pulsed-field gradient NMR experiments
DOI: 10.1016/j.jmr.2011.04.004
Publisher version: http://dx.doi.org/10.1016/j.jmr.2011.04.004
Language: English
Keywords: CUDA, GPGPU, Parallel processing, Restricted diffusion, PGSE, Restricted diffusion, Self-diffusion, Spin-echo, Laplacian Eigenfunctions, Length scales, Approximation, Spectroscopy, Time, Diffusometry, Attenuation
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Structural and Molecular Biology
URI: https://discovery.ucl.ac.uk/id/eprint/1307844
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