Research Computing at RCHAU

Shared high-performance computing resources for research and education.

RCHAU provides access to high-performance computing resources for researchers, instructors, students, and collaborators across participating Alabama institutions. The cluster supports a wide range of computational work, including simulations, data analysis, modeling, visualization, and machine learning.

The system is operated as a shared research computing environment. It is designed to support both experienced HPC users and those who are using a computing cluster for the first time.

RCHAU is housed at the University of Alabama in Huntsville and supports a broader network of academic and research partners across the state.

The RCHAU research computing initiative was led by Dr. Vladimir Florinski, whose efforts helped establish a shared high-performance computing resource serving multiple institutions across Alabama.

Getting Started

Users may request an account to access the cluster, submit jobs, use available software, and run research or instructional workloads. New users are encouraged to review the documentation and examples before submitting large jobs.

Request an account to begin the access process.

Account access: Submit an account request and, once approved, use the cluster for eligible research, teaching, or training activities.

Statewide collaboration: RCHAU supports work across participating Alabama universities and partner organizations.

Broad scientific use: The cluster can support many computational workloads, from small test jobs to larger simulations and analysis pipelines.

What You Can Do

Run batch jobs through SLURM on CPU or GPU resources.

Use common research software, compilers, MPI tools, Python environments, CUDA tools, and other installed packages.

Develop and test workflows before scaling to larger jobs.

Learn practical cluster skills, including job scheduling, file management, software environments, and remote access.

Who This Site Is For

This site is intended for both new and experienced users. If you are new to HPC, start with the basic examples and cluster access guides. If you already use clusters regularly, the documentation provides RCHAU-specific details on partitions, software, storage, and job submission.

Ready to Begin?

Review the documentation, request an account, and start with a small test job before running larger workloads. This helps ensure that your environment, scripts, and resource requests are working correctly.