NDLI: Acceleration of the Dual-Field Domain Decomposition Algorithm Using MPI

Content Provider	IEEE Xplore Digital Library
Author	Huan-Ting Meng Jian-Ming Jin
Copyright Year	1963
Abstract	It is well known that graphics processing units (GPUs) are able to accelerate highly parallelizable algorithms with a high speedup. However, for less-parallelizable algorithms such as the finite element method, novel schemes are needed to achieve a high speedup. In this paper, the dual-field domain decomposition (DFDD) method based on element-level decomposition (DFDD-ELD) is accelerated on a large GPU cluster. By using element-level subdomains, the DFDD-ELD computation can be easily mapped onto GPU's granular processors and is thus highly parallelizable. Various electromagnetic problems are simulated to demonstrate the speedup and scalability of DFDD-ELD on a GPU cluster. With a careful GPU memory arrangement and thread allocation, we are able to achieve a significant speedup by utilizing GPUs in a message-passing interface (MPI)-based cluster environment. The same acceleration strategy can be applied to the acceleration of the discontinuous Galerkin time-domain (DGTD) algorithms.
Sponsorship	IEEE Antennas and Propagation Society
Starting Page	4706
Ending Page	4715
Page Count	10
File Size	1680791
File Format	PDF
ISSN	0018926X
Volume Number	62
Issue Number	9
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Graphics processing units Finite element analysis Acceleration Vectors Instruction sets Algorithm design and analysis Computer architecture time-domain analysis Circuit analysis compute unified device architecture (CUDA) finite-element analysis graphics processing unit (GPU) GPU cluster high-performance computing message-passing interface (MPI) multi-GPU parallel programming radar cross section
Content Type	Text
Resource Type	Article
Subject	Condensed Matter Physics Electrical and Electronic Engineering

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