%0 Journal Article %1 MAIER2024102291 %A Maier, Benjamin %A Göddeke, Dominik %A Huber, Felix %A Klotz, Thomas %A Röhrle, Oliver %A Schulte, Miriam %D 2024 %J Journal of Computational Science %K hpc-computing neuromuscular simulation tool %P 102291 %R https://doi.org/10.1016/j.jocs.2024.102291 %T OpenDiHu: An efficient and scalable framework for biophysical simulations of the neuromuscular system %U https://www.sciencedirect.com/science/article/pii/S187775032400084X %V 79 %X The versatile neuromuscular system, consisting of skeletal muscles and the nervous system, enables human to perform crucial everyday tasks. To investigate its functioning and dysfunctioning with computer simulations, highly resolved, multi-scale models are favorable, whose numerical solutions demand for high performance computing. We present OpenDiHu, a versatile, high-performance computing, open source software framework for detailed, systemic simulations of skeletal muscles and their recruitment mechanisms. OpenDiHu allows to solve a variety of multi-scale models, including 3D muscle mechanics, measurable electromyographic signals, action potential propagation in the muscle tissue, subcellular bio-chemo-electrical processes, and the neural drive to the muscle. All these components can be combined with a wide range of numerical solution schemes into comprehensive simulation setups for the entire system. Experiments on up to almost 27000 cores demonstrate the efficiency and parallel scalability of OpenDiHu. This enables in silico experiments at very high spatial and temporal resolutions.

@article{MAIER2024102291, abstract = {The versatile neuromuscular system, consisting of skeletal muscles and the nervous system, enables human to perform crucial everyday tasks. To investigate its functioning and dysfunctioning with computer simulations, highly resolved, multi-scale models are favorable, whose numerical solutions demand for high performance computing. We present OpenDiHu, a versatile, high-performance computing, open source software framework for detailed, systemic simulations of skeletal muscles and their recruitment mechanisms. OpenDiHu allows to solve a variety of multi-scale models, including 3D muscle mechanics, measurable electromyographic signals, action potential propagation in the muscle tissue, subcellular bio-chemo-electrical processes, and the neural drive to the muscle. All these components can be combined with a wide range of numerical solution schemes into comprehensive simulation setups for the entire system. Experiments on up to almost 27000 cores demonstrate the efficiency and parallel scalability of OpenDiHu. This enables in silico experiments at very high spatial and temporal resolutions.}, added-at = {2024-12-05T14:42:20.000+0100}, author = {Maier, Benjamin and Göddeke, Dominik and Huber, Felix and Klotz, Thomas and Röhrle, Oliver and Schulte, Miriam}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/24297669772239848ef5163a19989129e/diglezakis}, doi = {https://doi.org/10.1016/j.jocs.2024.102291}, interhash = {59bf2fc78694127b4507b54213450ee5}, intrahash = {4297669772239848ef5163a19989129e}, issn = {1877-7503}, journal = {Journal of Computational Science}, keywords = {hpc-computing neuromuscular simulation tool}, pages = 102291, timestamp = {2024-12-05T14:42:20.000+0100}, title = {OpenDiHu: An efficient and scalable framework for biophysical simulations of the neuromuscular system}, url = {https://www.sciencedirect.com/science/article/pii/S187775032400084X}, volume = 79, year = 2024 }