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Resources Hub

Welcome to Our Resources Hub

Whether you're new to high-performance computing (HPC) or looking to expand your skills, this page provides essential guides, training, and connections to help you succeed. Explore the sections below to get started and make the most of TAMUSA's research computing resources.

HPC Cluster User Guide

Step-by-step instructions on accessing, logging in, and navigating our CAMSA HPC cluster. Learn to submit jobs, monitor progress, and manage your environment effectively.

View Policies

Account Request & Access Policies

Details on how to request an account, eligibility criteria, security requirements, and responsible usage guidelines to keep our resources safe and efficient.

Account Access

Job Submission & Scheduling Guide

Learn about job schedulers, queue systems, and best practices for optimizing run times and resource allocation. This guide helps you maximize efficiency and minimize wait times.

Job Guide

Data Storage & Transfer Guidelines

Understand options for data storage, moving large files, and backing up your research data. Includes tips for secure transfers and using high-speed connections.

Storage Guide

Upcoming HPC Workshops
Join hands-on training sessions designed for both beginners and advanced users. Topics include Linux basics, parallel computing, data analysis, and GPU programming
Computer Lab

CAMSA Cluster Technical Details

Cluster Overview

CAMSA delivers 3.6 PF peak performance and 40 TB of high-performance storage. It supports diverse workloads from AI and data science to large-scale simulations, leveraging cutting-edge accelerators and high-speed networking.

Node & Processor Details

CAMSA includes 49 CPUs and 968 cores, built on Intel Xeon Gold processors. Node types include:

  • Head Nodes (PowerEdge R650)

  • Login Nodes (PowerEdge R650)

  • Compute Nodes (PowerEdge R420 & C6420)

  • GPU Nodes (PowerEdge R750)

  • Storage Nodes (PowerEdge R650 NFS)

Accelerators & GPUs

CAMSA features a rich accelerator testbed with Intel MAX GPUs, Intel FPGAs, NVIDIA GPUs, and Graphcore IPUs, enabling advanced research in AI, ML, and data-intensive computing.

Networking & Interconnect

The cluster uses Mellanox HDR InfiniBand switches for ultra-fast, low-latency interconnects, alongside Dell S3048-ON Ethernet switches providing flexible connectivity options.

Storage & Rack Information

Storage nodes provide 1.92 TB SSDs per node and a total of 40 TB high-performance storage. The cluster is housed in Chatsworth racks with AP8865 PDUs to ensure reliable power and cooling.

Software & Scheduler

CAMSA runs Red Hat Enterprise Linux for HPC on head nodes, managed with Bright Cluster Manager and SLURM scheduler. Available software includes Python3, Jupyter, GPU-compute images, Singularity containers, and MPI libraries.

Available Software Modules


Pre-installed software includes Python3, Jupyter, GPU libraries, MPI, and various scientific computing packages. Check the full list to see available tools for your research.

Requesting New Software


Need a specific package? Submit a request to have new software or library modules installed on the CAMSA cluster.

Visualization Tools


Recommendations for visualization and analysis tools, such as ParaView, Matplotlib, and other open-source platforms compatible with CAMSA.