Victorian Life Science Computation Initiative, Carlton, VIC 3010, Australia.
IEEE Trans Biomed Eng. 2011 Oct;58(10):2965-9. doi: 10.1109/TBME.2011.2161580. Epub 2011 Jul 14.
Future multiscale and multiphysics models that support research into human disease, translational medical science, and treatment can utilize the power of high-performance computing (HPC) systems. We anticipate 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, Pthreads). The objective of this study is to compare the performance of such hybrid programming models when applied to the simulation of a realistic physiological multiscale model of the heart. Our results show that the hybrid models perform favorably when compared to an implementation using only the MPI and, furthermore, that OpenMP in combination with the MPI provides a satisfactory compromise between performance and code complexity. Having the ability to use threads within MPI processes enables the sophisticated use of all processor cores for both computation and communication phases. Considering that HPC systems in 2012 will have two orders of magnitude more cores than what was used in this study, we believe that faster than real-time multiscale cardiac simulations can be achieved on these systems.
未来支持人类疾病研究、转化医学和治疗的多尺度和多物理模型可以利用高性能计算 (HPC) 系统的强大功能。我们预计，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（例如，消息传递接口 (MPI)）与多线程（例如，OpenMP、Pthreads）混合使用。本研究的目的是比较这些混合编程模型在模拟真实生理多尺度心脏模型时的性能。我们的结果表明，与仅使用 MPI 的实现相比，混合模型的性能良好，并且 OpenMP 与 MPI 结合使用在性能和代码复杂性之间提供了令人满意的折衷。在 MPI 进程中使用线程的能力使能够在计算和通信阶段都能够巧妙地使用所有处理器核心。考虑到 2012 年的 HPC 系统将拥有比本研究中使用的系统多两个数量级的核心，我们相信可以在这些系统上实现比实时更快的多尺度心脏模拟。
