8338

A PCG Implementation of an Elliptic Kernel in an Ocean Global Circulation Model Based on GPU Libraries

Salvatore Cuomo, Pasquale De Michele, Raffaele Farina, Marta Chinnici
University of Naples "Federico II" – Dept. of Mathematics and Applications
arXiv:1210.1878 [math.NA] (5 Oct 2012)
@article{2012arXiv1210.1878C,

   author={Cuomo}, S. and {De Michele}, P. and {Farina}, R. and {Chinnici}, M.},

   title={"{A PCG Implementation of an Elliptic Kernel in an Ocean Global Circulation Model Based on GPU Libraries}"},

   journal={ArXiv e-prints},

   archivePrefix={"arXiv"},

   eprint={1210.1878},

   primaryClass={"math.NA"},

   keywords={Mathematics – Numerical Analysis, 65Y5, 65Y10, 65F08, 65F35, 37N10},

   year={2012},

   month={oct},

   adsurl={http://adsabs.harvard.edu/abs/2012arXiv1210.1878C},

   adsnote={Provided by the SAO/NASA Astrophysics Data System}

}

Download Download (PDF)   View View   Source Source   

587

views

In this paper an inverse preconditioner for the numerical solution of an elliptic Laplace prob- lem of a global circulation ocean model is presented. The inverse preconditiong technique is adopted in order to efficiently compute the numerical solution of the elliptic kernel by using the Conjugate Gradient (CG) method. We show how the performance and the rate of convergence of the solver are linked to the discretized grid resolution and to the Laplace coefficients of the oceanic model. Finally, we describe an easy-to-implement version of the solver on the Graphical Processing Units (GPUs) by means of scientific computing libraries and we discuss its performance.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

TwitterAPIExchange Object
(
    [oauth_access_token:TwitterAPIExchange:private] => 301967669-yDz6MrfyJFFsH1DVvrw5Xb9phx2d0DSOFuLehBGh
    [oauth_access_token_secret:TwitterAPIExchange:private] => o29ji3VLVmB6jASMqY8G7QZDCrdFmoTvCDNNUlb7s
    [consumer_key:TwitterAPIExchange:private] => TdQb63pho0ak9VevwMWpEgXAE
    [consumer_secret:TwitterAPIExchange:private] => Uq4rWz7nUnH1y6ab6uQ9xMk0KLcDrmckneEMdlq6G5E0jlQCFx
    [postfields:TwitterAPIExchange:private] => 
    [getfield:TwitterAPIExchange:private] => ?cursor=-1&screen_name=hgpu&skip_status=true&include_user_entities=false
    [oauth:protected] => Array
        (
            [oauth_consumer_key] => TdQb63pho0ak9VevwMWpEgXAE
            [oauth_nonce] => 1481003851
            [oauth_signature_method] => HMAC-SHA1
            [oauth_token] => 301967669-yDz6MrfyJFFsH1DVvrw5Xb9phx2d0DSOFuLehBGh
            [oauth_timestamp] => 1481003851
            [oauth_version] => 1.0
            [cursor] => -1
            [screen_name] => hgpu
            [skip_status] => true
            [include_user_entities] => false
            [oauth_signature] => dOAuaplcel5BqhEy3ITM67bOVtQ=
        )

    [url] => https://api.twitter.com/1.1/users/show.json
)
Follow us on Facebook
Follow us on Twitter

HGPU group

2079 peoples are following HGPU @twitter

HGPU group © 2010-2016 hgpu.org

All rights belong to the respective authors

Contact us: