Taylor Geospatial Institute Regional AI Learning System (TGI RAILS) User Guide
System status, planned outages, and maintenance information:
Introduction
TGI RAILS is a regional computing system funded by the NSF Campus Cyberinfrastructure program for primary use by the TGI consortium for geospatial related research. RAILS provides a highly capable GPU-focused compute environment for GPU and CPU workloads.
RAILS has three CPU-only nodes and three 8-way NVIDIA H100-based GPU nodes. Every RAILS node has high-performance node-local SSD storage (1.92 TB for CPU nodes, 3.5 TB for GPU nodes), and is connected to the 1 PB VAST filesystem via the high-speed interconnect. The RAILS resource uses the SLURM workload manager for job scheduling.
Contents
- TGI RAILS Status Updates
- System Architecture
- Allocation and Account Administration
- Accessing The System
- Good Cluster Citizenship
- Data Management
- Accessing and Transferring Files
- Programming Environment (Building Software)
- Running Jobs
- Installed Software
- Visualization
- Containers
- Services
- Debugging And Performance Analysis
- Protected Data
- Acknowledging TGI Rails
- Getting Help