skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Parallel Computing for Module-Based Computational Experiment

Abstract

Large-scale scientific code plays an important role in scientific researches. In order to facilitate module and element evaluation in scientific applications, we introduce a unit testing framework and describe the demand for module-based experiment customization. We then develop a parallel version of the unit testing framework to handle long-term simulations with a large amount of data. Specifically, we apply message passing based parallelization and I/O behavior optimization to improve the performance of the unit testing framework and use profiling result to guide the parallel process implementation. Finally, we present a case study on litter decomposition experiment using a standalone module from a large-scale Earth System Model. This case study is also a good demonstration on the scalability, portability, and high-efficiency of the framework.

Authors:
 [1]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [2];  [3]
  1. University of Tennessee, Knoxville (UTK)
  2. ORNL
  3. Jilin University, China
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1542200
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Journal Volume: 11537; Conference: International Conference on Computational Sciences - Faro, , Portugal - 6/12/2019 4:00:00 AM-6/14/2019 4:00:00 AM
Country of Publication:
United States
Language:
English

Citation Formats

Yao, Zhuo, Wang, Dali, Ricciuto, Daniel M., Yuan, Fengming, and Fang, Chunsheng. Parallel Computing for Module-Based Computational Experiment. United States: N. p., 2019. Web. doi:10.1007/978-3-030-22741-8_27.
Yao, Zhuo, Wang, Dali, Ricciuto, Daniel M., Yuan, Fengming, & Fang, Chunsheng. Parallel Computing for Module-Based Computational Experiment. United States. doi:10.1007/978-3-030-22741-8_27.
Yao, Zhuo, Wang, Dali, Ricciuto, Daniel M., Yuan, Fengming, and Fang, Chunsheng. Sat . "Parallel Computing for Module-Based Computational Experiment". United States. doi:10.1007/978-3-030-22741-8_27. https://www.osti.gov/servlets/purl/1542200.
@article{osti_1542200,
title = {Parallel Computing for Module-Based Computational Experiment},
author = {Yao, Zhuo and Wang, Dali and Ricciuto, Daniel M. and Yuan, Fengming and Fang, Chunsheng},
abstractNote = {Large-scale scientific code plays an important role in scientific researches. In order to facilitate module and element evaluation in scientific applications, we introduce a unit testing framework and describe the demand for module-based experiment customization. We then develop a parallel version of the unit testing framework to handle long-term simulations with a large amount of data. Specifically, we apply message passing based parallelization and I/O behavior optimization to improve the performance of the unit testing framework and use profiling result to guide the parallel process implementation. Finally, we present a case study on litter decomposition experiment using a standalone module from a large-scale Earth System Model. This case study is also a good demonstration on the scalability, portability, and high-efficiency of the framework.},
doi = {10.1007/978-3-030-22741-8_27},
journal = {},
issn = {0302--9743},
number = ,
volume = 11537,
place = {United States},
year = {2019},
month = {6}
}

Conference:
Other availability
Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

Save / Share: