1 research outputs found
Towards realistic HPC models of the neuromuscular system
Realistic simulations of detailed, biophysics-based, multi-scale models
require very high resolution and, thus, large-scale compute facilities.
Existing simulation environments, especially for biomedical applications, are
designed to allow for a high flexibility and generality in model development.
Flexibility and model development, however, are often a limiting factor for
large-scale simulations. Therefore, new models are typically tested and run on
small-scale compute facilities. By using a detailed biophysics-based,
chemo-electromechanical skeletal muscle model and the international open-source
software library OpenCMISS as an example, we present an approach to upgrade an
existing muscle simulation framework from a moderately parallel version towards
a massively parallel one that scales both in terms of problem size and in terms
of the number of parallel processes. For this purpose, we investigate different
modeling, algorithmic and implementational aspects. We present improvements
addressing both numerical and parallel scalability. In addition, our approach
includes a novel visualization environment, which is based on the MegaMol
environment capable of handling large amounts of simulated data. It offers a
platform for fast visualization prototyping, distributed rendering, and
advanced visualization techniques. We present results of a variety of scaling
studies at the Tier-1 supercomputer HazelHen at the High Performance Computing
Center Stuttgart (HLRS). We improve the overall runtime by a factor of up to
2.6 and achieved good scalability on up to 768 cores, where the previous
implementation used only 4 cores