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Massively parallelized interpolated factored Green function method

Bauinger, Christoph and Bruno, Oscar P. (2023) Massively parallelized interpolated factored Green function method. Journal of Computational Physics, 475 . Art. No. 111837. ISSN 0021-9991. doi:10.1016/j.jcp.2022.111837. https://resolver.caltech.edu/CaltechAUTHORS:20230213-460790900.1

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Abstract

This paper presents the first parallel implementation of the novel "Interpolated Factored Green Function" (IFGF) method introduced recently for the accelerated evaluation of discrete integral operators arising in wave scattering and other areas (Bauinger and Bruno, Jour. Computat. Phys., 2021). On the basis of the hierarchical IFGF interpolation strategy, the proposed (hybrid MPI-OpenMP) parallel implementation results in efficient data communication, and it scales up to large numbers of cores—without any hard limitations on the number of cores efficiently employed. Moreover, on any given number of cores, the proposed parallel approach preserves the O(N log N) computing cost inherent in the sequential version of the IFGF algorithm. Unlike other approaches, the IFGF method does not utilize the Fast Fourier Transform (FFT), and it is thus better suited for efficient parallelization in distributed-memory computer systems. In particular, the IFGF method relies on a “peer-to-peer” strategy wherein, at every level, field propagation is directly enacted via “exchanges” between “peer” polynomials of constant degree, without data accumulation in large-scale “telephone-central” mathematical constructs such as those used in the Fast Multipole Method (FMM) and pure FFT-based approaches. A variety of numerical results presented in this paper illustrate the character of the proposed parallel algorithm, in particular demonstrating scaling from 1 to all 1,680 cores available in the High Performance Computing cluster used, and for problems of up to 4,096 wavelengths in acoustic size.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1016/j.jcp.2022.111837DOIArticle
ORCID:
AuthorORCID
Bruno, Oscar P.0000-0001-8369-3014
Additional Information:This work was supported by NSF, DARPA and AFOSR through contracts DMS-2109831 and HR00111720035, FA9550-19-1-0173 and FA9550-21-1-0373, and by the NSSEFF Vannevar Bush Fellowship under contract number N00014-16-1-2808.
Funders:
Funding AgencyGrant Number
NSFDMS-2109831
Defense Advanced Research Projects Agency (DARPA)HR00111720035
Air Force Office of Scientific Research (AFOSR)FA9550-19-1-0173
Air Force Office of Scientific Research (AFOSR)FA9550-21-1-0373
National Security Science and Engineering Faculty FellowshipN00014-16-1-2808
DOI:10.1016/j.jcp.2022.111837
Record Number:CaltechAUTHORS:20230213-460790900.1
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20230213-460790900.1
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:119233
Collection:CaltechAUTHORS
Deposited By: Research Services Depository
Deposited On:22 Mar 2023 16:12
Last Modified:22 Mar 2023 16:12

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