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Using the High-Level Based Program Interface to Facilitate the Large Scale Scientific Computing

This paper is to make further research on facilitating the large-scale scientific computing on the grid and the desktop grid platform. The related issues include the programming method, the overhead of the high-level program interface based middleware, and the data anticipate migration. The block ba...

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Detalles Bibliográficos
Autores principales: Shang, Yizi, Shang, Ling, Gao, Chuanchang, Lu, Guiming, Ye, Yuntao, Jia, Dongdong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3916069/
https://www.ncbi.nlm.nih.gov/pubmed/24574931
http://dx.doi.org/10.1155/2014/914514
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author Shang, Yizi
Shang, Ling
Gao, Chuanchang
Lu, Guiming
Ye, Yuntao
Jia, Dongdong
author_facet Shang, Yizi
Shang, Ling
Gao, Chuanchang
Lu, Guiming
Ye, Yuntao
Jia, Dongdong
author_sort Shang, Yizi
collection PubMed
description This paper is to make further research on facilitating the large-scale scientific computing on the grid and the desktop grid platform. The related issues include the programming method, the overhead of the high-level program interface based middleware, and the data anticipate migration. The block based Gauss Jordan algorithm as a real example of large-scale scientific computing is used to evaluate those issues presented above. The results show that the high-level based program interface makes the complex scientific applications on large-scale scientific platform easier, though a little overhead is unavoidable. Also, the data anticipation migration mechanism can improve the efficiency of the platform which needs to process big data based scientific applications.
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spelling pubmed-39160692014-02-26 Using the High-Level Based Program Interface to Facilitate the Large Scale Scientific Computing Shang, Yizi Shang, Ling Gao, Chuanchang Lu, Guiming Ye, Yuntao Jia, Dongdong ScientificWorldJournal Research Article This paper is to make further research on facilitating the large-scale scientific computing on the grid and the desktop grid platform. The related issues include the programming method, the overhead of the high-level program interface based middleware, and the data anticipate migration. The block based Gauss Jordan algorithm as a real example of large-scale scientific computing is used to evaluate those issues presented above. The results show that the high-level based program interface makes the complex scientific applications on large-scale scientific platform easier, though a little overhead is unavoidable. Also, the data anticipation migration mechanism can improve the efficiency of the platform which needs to process big data based scientific applications. Hindawi Publishing Corporation 2014-01-19 /pmc/articles/PMC3916069/ /pubmed/24574931 http://dx.doi.org/10.1155/2014/914514 Text en Copyright © 2014 Yizi Shang et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Shang, Yizi
Shang, Ling
Gao, Chuanchang
Lu, Guiming
Ye, Yuntao
Jia, Dongdong
Using the High-Level Based Program Interface to Facilitate the Large Scale Scientific Computing
title Using the High-Level Based Program Interface to Facilitate the Large Scale Scientific Computing
title_full Using the High-Level Based Program Interface to Facilitate the Large Scale Scientific Computing
title_fullStr Using the High-Level Based Program Interface to Facilitate the Large Scale Scientific Computing
title_full_unstemmed Using the High-Level Based Program Interface to Facilitate the Large Scale Scientific Computing
title_short Using the High-Level Based Program Interface to Facilitate the Large Scale Scientific Computing
title_sort using the high-level based program interface to facilitate the large scale scientific computing
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3916069/
https://www.ncbi.nlm.nih.gov/pubmed/24574931
http://dx.doi.org/10.1155/2014/914514
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