Parallel resolution of the 3D Helmholtz equation based on multi‐graphics processing unit clusters. (5th February 2014)

• Record Type: Journal Article
• Authors: Ortega, Gloria; Lobera, Julia; García, Inmaculada; Pilar Arroyo, M.; Garzón, Ester M.; Limet, Sébastien; Smari, Waleed W.; Spalazzi, Luca; Hu, Jia; Gao, Jianliang
• Is Part Of: Concurrency and computation. Volume 27:Number 13(2015:Sep.)
• Page Start: 3205
• Page End: 3219
• Publication Date: 2014-02-05
• Subjects: Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.3212
• Languages: English
• ISSNs: 1532-0626

Abstract

<abstract abstract-type="main" id="cpe3212-abs-0001"> <title>Summary</title> <p id="cpe3212-para-0001">The resolution of the 3D Helmholtz equation is required in the development of models related to a wide range of scientific and technological applications. For solving this equation in complex arithmetic, the biconjugate gradient (BCG) method is one of the most relevant solvers. However, this iterative method has a high computational cost because of the large sparse matrix and the vector operations involved. In this paper, a specific BCG method, adapted for the regularities of the Helmholtz equation is presented. This BCG is based on the implementation of a novel format (named 'Regular Format') that allows the storage of the large sparse matrix involved in the sparse matrix vector product in a compact form. The contribution of this work is twofold: (1) decreasing the memory requirements of the 3D Helmholtz equation using the 'Regular Format' and (2) speeding up the resolution of the equation using high performance computing resources. A hybrid Message Passing Interface (MPI)‐graphics processing unit CUDA GPU parallelization that is capable of solving complex problems in short time has carried out (Fast‐Helmholtz). Fast‐Helmholtz combines optimizations at Message Passing Interface and GPU levels to reduce communications costs and to improve the exploitation of GPU architecture. This strategy makes it possible to extend the dimension of the Helmholtz problem to be solved, thanks to the relevant reduction of memory requirements and runtime. Copyright © 2014 John Wiley & Sons, Ltd.</p> </abstract>