Detail publikace
Using a GPU to Accelerate Electrical Impedance Tomography Algorithms
DUŠEK, J. MIKULKA, J.
Originální název
Using a GPU to Accelerate Electrical Impedance Tomography Algorithms
Anglický název
Using a GPU to Accelerate Electrical Impedance Tomography Algorithms
Jazyk
en
Originální abstrakt
This paper discusses parallelizing an algorithm for image reconstruction in EIT. A GPU NVIDIA platform with CUDA kernel was used for data processing. Introductory section comprises description of EIT and relevant practical applications. The following chapter outlines objective function with Tikhonov regularization and possibility of mathematical extension to increase image resolution. Besides we also characterize the modification of reconstruction algorithm with respect to computional speed. The achieved results are discussed with a survey of the achieved algorithm acceleration and related problems.
Anglický abstrakt
This paper discusses parallelizing an algorithm for image reconstruction in EIT. A GPU NVIDIA platform with CUDA kernel was used for data processing. Introductory section comprises description of EIT and relevant practical applications. The following chapter outlines objective function with Tikhonov regularization and possibility of mathematical extension to increase image resolution. Besides we also characterize the modification of reconstruction algorithm with respect to computional speed. The achieved results are discussed with a survey of the achieved algorithm acceleration and related problems.
Dokumenty
BibTex
@inproceedings{BUT139897,
author="Jan {Dušek} and Jan {Mikulka}",
title="Using a GPU to Accelerate Electrical Impedance Tomography Algorithms",
annote="This paper discusses parallelizing an algorithm for image reconstruction in EIT. A GPU NVIDIA platform with CUDA kernel was used for data processing. Introductory section comprises description of EIT and relevant practical applications. The following chapter outlines objective function with Tikhonov regularization and possibility of mathematical extension to increase image resolution. Besides we also characterize the modification of reconstruction algorithm with respect to computional speed. The achieved results are discussed with a survey of the achieved algorithm acceleration and related problems.",
booktitle="Proceedings of IIPhDW 2017 in Lodz",
chapter="139897",
howpublished="online",
year="2017",
month="september",
pages="59--63",
type="conference paper"
}