Computer simulation of action potential propagation on cardiac tissues: An efficient and scalable parallel approach

J.M. Alonso, JM Ferrero, V. Hernández, G. Moltó, M. Montserrat, and J Saiz. Computer simulation of action potential propagation on cardiac tissues: An efficient and scalable parallel approach. In Parallel Computing: Software Technology, Algorithms, Architectures and Applications, Advances in Parallel Computing, pp. 339–346, 13, 2004.

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Abstract

The simulation of action potential propagation on cardiac tissues has become a very time consuming task with large memory requirements. Realistic ionic models combined with the ever-increasing need to simulate larger tissues during longer time, demand the use of very large-scale computational resources. This paper presents a complete parallel computing implementation for the electrical activity simulation in a two-dimensional monodomain cardiac tissue using a cost-effective beowulf cluster. High performance computing techniques have reduced the simulation time by a factor of nearly the number of processors, reaching a 94% of efficiency when using 32 processes. Moreover, the application of stable numerical ODE integration methods has allowed the use of larger timesteps, reducing the whole simulation time.

BibTeX Entry

@inproceedings{Molto2004csa,
   abstract = {The simulation of action potential propagation on cardiac tissues has become a very time consuming task with large memory requirements. Realistic ionic models combined with the ever-increasing need to simulate larger tissues during longer time, demand the use of very large-scale computational resources. This paper presents a complete parallel computing implementation for the electrical activity simulation in a two-dimensional monodomain cardiac tissue using a cost-effective beowulf cluster. High performance computing techniques have reduced the simulation time by a factor of nearly the number of processors, reaching a 94% of efficiency when using 32 processes. Moreover, the application of stable numerical ODE integration methods has allowed the use of larger timesteps, reducing the whole simulation time.},
   author = {J.M. Alonso and JM Ferrero and V. Hernández and G. Moltó and M. Montserrat and J Saiz},
   booktitle = {Parallel Computing: Software Technology, Algorithms, Architectures and Applications, Advances in Parallel Computing},
   pages = {339–346},
   title = {Computer simulation of action potential propagation on cardiac tissues: An efficient and scalable parallel approach},
   volume = {13},
   url = {http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:Computer+simulation+of+action+potential+propagation+on+cardiac+tissues:+An+efficient+and+scalable+parallel+approach,+in:+Parallel+Computing:#0},
   year = {2004}
}