High Performance Computing on the Raspberry PI

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 geo statistics application. These results can be very useful for researchers with limited access to high performance tools or limited funding.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-13
DOI
https://doi.org/10.5281/zenodo.16841567
Primary Topic
Data Analysis with R
Type
article
Field-Weighted Citation Impact
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article

High Performance Computing on the Raspberry PI

Zenodo (CERN European Organization for Nuclear Research)
Data Analysis with R
article

High Performance Computing on the Raspberry PI

article en

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 geo statistics application. These results can be very useful for researchers with limited access to high performance tools or limited funding.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 75%
Data Analysis with R
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High Performance Computing on the Raspberry PI · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS