💻

Computing Resources

High-performance computing resources for GIS analysis and processing

Featured Service

Available Resources

High-Performance Computing

  • Access to RCC’s Midway Computing Cluster
  • Parallel processing capabilities
  • Large-scale data analysis
  • Multiple CPU cores for parallel processing
  • GPU resources for machine learning and visualization
  • Large memory allocations for big data processing

Storage Solutions

  • Large-scale data storage
  • Backup services
  • Secure data management
  • High-speed access to research data
  • Long-term archiving options

Getting Started

Access Requirements

  • UChicago CNET ID
  • RCC account (request via RCC Support)
  • Basic knowledge of Linux command line (recommended)

Available Software

  • ArcGIS Pro
  • QGIS
  • GDAL/OGR
  • Python with geospatial libraries
  • R with spatial packages

Support and Training

Best Practices

  • Use scratch space for temporary files
  • Request appropriate resources for your jobs
  • Clean up unused data regularly
  • Use version control for your code
  • Document your workflows for reproducibility