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Accelerating Cardiac Bidomain Simulations Using Graphics Processing Units

Neic, A.; Liebmann, M.; Hoetzl, E.; Mitchell, L.; Vigmond, E.J.; Haase, G.; Plank, G.

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Authors

A. Neic

M. Liebmann

E. Hoetzl

L. Mitchell

E.J. Vigmond

G. Haase

G. Plank



Abstract

Anatomically realistic and biophysically detailed multiscale computer models of the heart are playing an increasingly important role in advancing our understanding of integrated cardiac function in health and disease. Such detailed simulations, however, are computationally vastly demanding, which is a limiting factor for a wider adoption of in-silico modeling. While current trends in high-performance computing (HPC) hardware promise to alleviate this problem, exploiting the potential of such architectures remains challenging since strongly scalable algorithms are necessitated to reduce execution times. Alternatively, acceleration technologies such as graphics processing units (GPUs) are being considered. While the potential of GPUs has been demonstrated in various applications, benefits in the context of bidomain simulations where large sparse linear systems have to be solved in parallel with advanced numerical techniques are less clear. In this study, the feasibility of multi-GPU bidomain simulations is demonstrated by running strong scalability benchmarks using a state-of-the-art model of rabbit ventricles. The model is spatially discretized using the finite element methods (FEM) on fully unstructured grids. The GPU code is directly derived from a large pre-existing code, the Cardiac Arrhythmia Research Package (CARP), with very minor perturbation of the code base. Overall, bidomain simulations were sped up by a factor of 11.8 to 16.3 in benchmarks running on 6-20 GPUs compared to the same number of CPU cores. To match the fastest GPU simulation which engaged 20 GPUs, 476 CPU cores were required on a national supercomputing facility.

Citation

Neic, A., Liebmann, M., Hoetzl, E., Mitchell, L., Vigmond, E., Haase, G., & Plank, G. (2012). Accelerating Cardiac Bidomain Simulations Using Graphics Processing Units. IEEE Transactions on Biomedical Engineering, 59(8), 2281-2290. https://doi.org/10.1109/tbme.2012.2202661

Journal Article Type Article
Acceptance Date May 25, 2012
Online Publication Date Jun 5, 2012
Publication Date Aug 1, 2012
Deposit Date Aug 1, 2018
Publicly Available Date Mar 29, 2024
Journal IEEE Transactions on Biomedical Engineering
Print ISSN 0018-9294
Electronic ISSN 1558-2531
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 59
Issue 8
Pages 2281-2290
DOI https://doi.org/10.1109/tbme.2012.2202661
Related Public URLs https://www.ncbi.nlm.nih.gov/pubmed/22692867

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Copyright Statement
© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.




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