Pope Bernard J, Fitch Blake G, Pitman Michael C, Rice John J, Reumann Matthias
Victorian Life Science Computation Initiative, 187 Grattan Street, Carlton, VIC 3010, Australia.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:433-6. doi: 10.1109/IEMBS.2011.6090058.
Future multiscale and multiphysics models must use the power of high performance computing (HPC) systems to enable research into human disease, translational medical science, and treatment. Previously we showed that computationally efficient multiscale models will require the use of sophisticated hybrid programming models, mixing distributed message passing processes (e.g. the message passing interface (MPI)) with multithreading (e.g. OpenMP, POSIX pthreads). The objective of this work is to compare the performance of such hybrid programming models when applied to the simulation of a lightweight multiscale cardiac model. Our results show that the hybrid models do not perform favourably when compared to an implementation using only MPI which is in contrast to our results using complex physiological models. Thus, with regards to lightweight multiscale cardiac models, the user may not need to increase programming complexity by using a hybrid programming approach. However, considering that model complexity will increase as well as the HPC system size in both node count and number of cores per node, it is still foreseeable that we will achieve faster than real time multiscale cardiac simulations on these systems using hybrid programming models.
未来的多尺度和多物理场模型必须借助高性能计算（HPC）系统的能力，以推动对人类疾病、转化医学科学及治疗方法的研究。我们之前表明，计算效率高的多尺度模型将需要使用复杂的混合编程模型，将分布式消息传递进程（如消息传递接口（MPI））与多线程（如OpenMP、POSIX线程）相结合。这项工作的目的是比较此类混合编程模型在应用于轻量级多尺度心脏模型模拟时的性能。我们的结果表明，与仅使用MPI的实现相比，混合模型的表现并不理想，这与我们使用复杂生理模型时的结果相反。因此，对于轻量级多尺度心脏模型，用户可能无需通过使用混合编程方法来增加编程复杂度。然而，考虑到模型复杂度以及HPC系统在节点数量和每个节点核心数量方面的规模都将增加，仍可预见，我们将使用混合编程模型在这些系统上实现比实时更快的多尺度心脏模拟。
