Poster: hybrid parallelization of a realistic heart model
Dorian Krause, Mark Potse, Thomas Dickopf, Rolf Krause, Angelo Auricchio, and Frits W. Prinzen
Proceedings of SC11; the 2011 Conference for High Performance Computing, Networking, Storage and Analysis

links

poster

A more extensive description of the findings presented in this poster is given in a proceedings paper from another conference. This paper is available as a book chapter:

In: Rainer Keller, David Kramer, Jan-Philipp Weiss, editors: Facing the Multicore - Challenge II; Aspects of New Paradigms and Technologies in Parallel Computing. Lecture Notes in Computer Science, Volume 7174, 2012. ISBN 978-3-642-30396-8 (print), 978-3-642-30397-5 (online).

abstract

The simulation of the electrophysiology of the heart is challenging due to its multiscale nature requiring the use of high spatial resolutions. Hence, it is important to efficiently utilize large parallel machines. In this article, we present a code designed to meet these scalability challenges. It is based on a well-established model originally designed for sharedmemory systems. To improve scalability and extend support to distributed-memory architectures, we developed a hybrid OpenMP-MPI code. The new code shows excellent scalability up to 8448 cores with both explicit and implicit time discretizations. Our results prove that hybrid parallelization can be advantageous for this type of application. We describe our approach to a fully parallel workflow allowing for simulation sizes exceeding 1.5 billion mesh nodes, which opens new possibilities for computational electrophysiological studies. Finally, we present an in-depth analysis of the scalability and performance of different preconditioners

funding

Computational resources were provided by the Universitá della Svizzera italiana (USI), the Swiss National Supercomputing Centre (CSCS), and the Réseau québécois de calcul de haute performance (RQCHP). This work was supported by the project "A High Performance Approach to Cardiac Resynchronization Therapy" within the context of the "Iniziativa Ticino in Rete" and the "Swiss High Performance and Productivity Computing" (HP2C) Initiative