Magnetic diagnostics are essential for the operation and understanding of a magnetic confinement fusion (MCF) device, for example, by providing in real-time, the axisymmetric measurements needed for plasma equilibrium reconstructions or magnetohydrodynamic instabilities control. In this paper, we present a fast and robust implementation on GPU architecture of an accurate algorithm suitable for the computation of synthetic magnetic measurements used both in real time applications and off-line reconstruction procedures. The proposed procedure is first applied to benchmark problems, to validate the compute unified device architecture implementation, and then to cases of practical interests in MCF.

Fast and Efficient Algorithms for Computational Electromagnetics on GPU Architecture

Manduchi Gabriele;
2017

Abstract

Magnetic diagnostics are essential for the operation and understanding of a magnetic confinement fusion (MCF) device, for example, by providing in real-time, the axisymmetric measurements needed for plasma equilibrium reconstructions or magnetohydrodynamic instabilities control. In this paper, we present a fast and robust implementation on GPU architecture of an accurate algorithm suitable for the computation of synthetic magnetic measurements used both in real time applications and off-line reconstruction procedures. The proposed procedure is first applied to benchmark problems, to validate the compute unified device architecture implementation, and then to cases of practical interests in MCF.
2017
Istituto gas ionizzati - IGI - Sede Padova
Inglese
64
7
1983
1987
5
http://ieeexplore.ieee.org/document/7944666/
Sì, ma tipo non specificato
Computational electromagnetics
GPU
magnetic confinement fusion (MCF)
synthetic magnetic measurements
Electronic ISSN: 1558-1578;
4
info:eu-repo/semantics/article
262
Maceina, Tautvydas; Bettini, Paolo; Manduchi, Gabriele; Passarotto, Mauro
01 Contributo su Rivista::01.01 Articolo in rivista
none
   Implementation of activities described in the Roadmap to Fusion during Horizon 2020 through a Joint programme of the members of the EUROfusion consortium
   EUROfusion
   H2020
   633053
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/335804
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