E. Hodgess. International Journal of Computational Science and Information Technology (IJCSITY), 10 (1):
01-05(February 2022)
DOI: 10.5121/ijcsity.2022.10101
Abstract
We considered building high performance tools on the Raspberry Pi 4. We implemented OpenMP and OpenCoarrays Fortran in conjunction with the statistical language R. We found that the OpenCoarrays is more effective when working with vectors, while OpenMP is better in the arena with large matrices in a geostatistics application. These results can be very useful for researchers with limited access to high performance tools or limited funding.
%0 Journal Article
%1 noauthororeditor
%A Hodgess, Erin M.
%D 2022
%J International Journal of Computational Science and Information Technology (IJCSITY)
%K Computing
%N 1
%P 01-05
%R 10.5121/ijcsity.2022.10101
%T HIGH PERFORMANCE COMPUTING ON THE RASPBERRY PI
%U https://aircconline.com/ijcsity/V10N1/10122ijcsity01.pdf
%V 10
%X We considered building high performance tools on the Raspberry Pi 4. We implemented OpenMP and OpenCoarrays Fortran in conjunction with the statistical language R. We found that the OpenCoarrays is more effective when working with vectors, while OpenMP is better in the arena with large matrices in a geostatistics application. These results can be very useful for researchers with limited access to high performance tools or limited funding.
@article{noauthororeditor,
abstract = {We considered building high performance tools on the Raspberry Pi 4. We implemented OpenMP and OpenCoarrays Fortran in conjunction with the statistical language R. We found that the OpenCoarrays is more effective when working with vectors, while OpenMP is better in the arena with large matrices in a geostatistics application. These results can be very useful for researchers with limited access to high performance tools or limited funding.},
added-at = {2022-03-10T06:04:43.000+0100},
author = {Hodgess, Erin M.},
biburl = {https://www.bibsonomy.org/bibtex/21e50ab3692a3264cb3abd16ab3187cc7/claure},
doi = {10.5121/ijcsity.2022.10101},
interhash = {7e800d1a31b3f95f14517a6f02e074d6},
intrahash = {1e50ab3692a3264cb3abd16ab3187cc7},
issn = {ISSN : 2320-7442 (Online) ; 2320 - 8457 (Print)},
journal = {International Journal of Computational Science and Information Technology (IJCSITY)},
keywords = {Computing},
language = {English},
month = {February},
number = 1,
pages = {01-05},
timestamp = {2022-03-10T06:04:43.000+0100},
title = {HIGH PERFORMANCE COMPUTING ON THE RASPBERRY PI},
url = {https://aircconline.com/ijcsity/V10N1/10122ijcsity01.pdf},
volume = 10,
year = 2022
}