Preprints
https://doi.org/10.5194/egusphere-2025-1558
https://doi.org/10.5194/egusphere-2025-1558
21 May 2025
 | 21 May 2025
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

Configuring parallel use of custom ArcGIS toolboxes in a Linux high-performance computing environment

Jeremy Baynes, Jacob Tafrate, Donald Ebert, and Steven Lennartz

Abstract. High performance computing (HPC) clusters offer an abundance of processors, memory, and data storage that can help meet growing computational demands for large geospatial analyses. Esri’s proprietary ArcGIS toolboxes are a common way to develop, document, and share geospatial code; however, these toolboxes are typically developed for use in Esri’s ArcGIS Pro for Windows which limits their use in Linux, the dominant HPC operating system. Esri’s support of Linux for their server software opens the possibility of using ArcGIS toolboxes in an HPC environment, but use of this software proved problematic for concurrent, parallel processing offering little benefit over a single workstation. We developed a solution using container technology allowing us to run hundreds of concurrent tasks that use ArcGIS toolboxes. This approach is designed to take advantage of the many existing ArcGIS toolboxes and use them in parallel for workflows that can be reasonably divided into independent sub-tasks. With careful setup and use of an HPC job scheduler, we reduced total processing time for one analysis 95.6 % by dividing the analysis into 202 sub-tasks. This solution allows other HPC users to take advantage of parallel use of ArcGIS Toolboxes, avoid the effort of translating existing workflows to Linux native software, and establish a bridge between desktop GIS and HPC systems.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Share
Jeremy Baynes, Jacob Tafrate, Donald Ebert, and Steven Lennartz

Status: open (until 16 Jul 2025)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2025-1558', Anonymous Referee #1, 21 May 2025 reply
    • AC1: 'Reply on RC1', Jeremy Baynes, 21 May 2025 reply
Jeremy Baynes, Jacob Tafrate, Donald Ebert, and Steven Lennartz

Model code and software

hpc-apptainer-arcgis US EPA https://doi.org/10.5281/zenodo.15066385

Jeremy Baynes, Jacob Tafrate, Donald Ebert, and Steven Lennartz

Viewed

Total article views: 161 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
132 19 10 161 4 6
  • HTML: 132
  • PDF: 19
  • XML: 10
  • Total: 161
  • BibTeX: 4
  • EndNote: 6
Views and downloads (calculated since 21 May 2025)
Cumulative views and downloads (calculated since 21 May 2025)

Viewed (geographical distribution)

Total article views: 154 (including HTML, PDF, and XML) Thereof 154 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 16 Jun 2025
Download
Short summary
This work describes our efforts of using Esri ArcGIS Toolboxes for large-scale geospatial processing in a high-performance computing (HPC) environment. Our custom ArcGIS toolbox was useful for automating workflows and our Agency’s HPC system offered massive parallel processing. However, these two products were not immediately compatible. Here we describe our solution and demonstrate its utility by performing an assessment of riparian land cover proportions across the conterminous United States.
Share