在GPU集群上加速用于电磁场模拟的三维FDTD计算。

Accelerating three-dimensional FDTD calculations on GPU clusters for electromagnetic field simulation.

作者信息

Nagaoka Tomoaki, Watanabe Soichi

机构信息

Electromagnetic Compatibility Laboratory, Applied Electromagnetic Research Institute, National Institute of Information and Communications Technology, Tokyo 184-8795, Japan.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:5691-4. doi: 10.1109/EMBC.2012.6347287.

DOI:10.1109/EMBC.2012.6347287

PMID:23367222

Abstract

Electromagnetic simulation with anatomically realistic computational human model using the finite-difference time domain (FDTD) method has recently been performed in a number of fields in biomedical engineering. To improve the method's calculation speed and realize large-scale computing with the computational human model, we adapt three-dimensional FDTD code to a multi-GPU cluster environment with Compute Unified Device Architecture and Message Passing Interface. Our multi-GPU cluster system consists of three nodes. The seven GPU boards (NVIDIA Tesla C2070) are mounted on each node. We examined the performance of the FDTD calculation on multi-GPU cluster environment. We confirmed that the FDTD calculation on the multi-GPU clusters is faster than that on a multi-GPU (a single workstation), and we also found that the GPU cluster system calculate faster than a vector supercomputer. In addition, our GPU cluster system allowed us to perform the large-scale FDTD calculation because were able to use GPU memory of over 100 GB.

摘要

最近，在生物医学工程的许多领域中，人们使用时域有限差分（FDTD）方法，通过具有逼真解剖结构的计算人体模型进行电磁模拟。为了提高该方法的计算速度，并利用计算人体模型实现大规模计算，我们将三维FDTD代码应用于具有统一计算设备架构（Compute Unified Device Architecture）和消息传递接口（Message Passing Interface）的多GPU集群环境。我们的多GPU集群系统由三个节点组成。每个节点上安装了七块GPU板（NVIDIA Tesla C2070）。我们研究了在多GPU集群环境下FDTD计算的性能。我们证实，多GPU集群上的FDTD计算比多GPU（单个工作站）上的计算速度更快，并且我们还发现GPU集群系统的计算速度比向量超级计算机更快。此外，我们的GPU集群系统使我们能够进行大规模的FDTD计算，因为我们能够使用超过100GB的GPU内存。