@Article{AlmeidaBaueFaze:2016:MiMaVi,
author = "Almeida, Eug{\^e}nio Sper de and Bauer, Michael Anthony and
Fazenda, Alvaro Luiz",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Western
University} and {Universidade Federal de S{\~a}o Paulo
(UNIFESP)}",
title = "Numerical weather model BRAMS evaluation on many-core
architectures: a micro and macro vision",
journal = "International Journal of Computational Science and Engineering",
year = "2016",
volume = "12",
number = "4",
pages = "330--340",
keywords = "performance, regional atmospheric modelling system, BRAMS,
numerical weather prediction model, high performance computing,
HPC, meteorology, parallel processing, multicore architecture.",
abstract = "This paper investigates the performance of a weather forecasting
application (Brazilian developments on the regional atmospheric
modelling system BRAMS) on high performance computing (HPC)
clusters with a multi-core architecture. We simulated atmosphere
conditions over South America for 24 hours ahead using the BRAMS,
aiming to understand the impact of different architectural
configurations on performance and scalability. Our analyses
consider execution in intra-node and inter-node configurations of
a cluster with 24 cores per node. Results reveal differences in
the BRAMS performance caused by interconnection. The BRAMS may get
better performance by using a newer version of MPI library
implementation (one-copy schema) and improving spatial
resolution.",
doi = "10.1504/ijcse.2016.076940",
url = "http://dx.doi.org/10.1504/ijcse.2016.076940",
issn = "1742-7193",
label = "lattes: 0676191681641372 1 AlmeidaBaueFaze:2016:MiMaVi",
language = "en",
targetfile = "almeida_numerical.pdf",
urlaccessdate = "09 maio 2024"
}