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Computing Resources
High-performance computing resources for GIS analysis and processing
Featured ServiceAvailable 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
- Weekly office hours
- Email support at gis-help@rcc.uchicago.edu
- Online documentation and tutorials
- Workshops on HPC for GIS
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