Purpose and Overview
Miami University offers High Performance Computing (HPC) services, frequently called the RedHawk Research Cluster, to support research. teaching, and data-intensive projects that require advanced computing power beyond what a typical desktop or laptop can provide. HPC enables users to run large-scale simulations, analyze big data sets, and process complex scientific calculations efficiently and securely.
Features and Benefits
Features:
- Centralized: Access to Redhawk, Miami’s centralized HPC cluster.
- Managed: Job scheduling and resource allocation using SLURM.
- Versatile: Software modules for scientific computing, including MATLAB, R, Python, and more.
- Secure: Remote access to the cluster via SSH.
- Scalable: Data storage for active projects.
- High-Performance: Supports GPU and multi-node computing.
Benefits:
- Accelerated: Reduces compute time for complex jobs, speeding up research.
- Educational: Supports teaching in data science, modeling, and computational courses.
- Collaborative: Enables interdisciplinary teamwork in a shared computing environment.
- Efficient: Improves performance for repetitive, simulation-heavy, and data-intensive tasks.
- Secure: Ensures compliance and protection through centralized data and access management.
Service Boundaries and Constraints
- Use is limited to Miami University academic, research, and instructional purposes.
- Users must request an account and agree to acceptable use and data storage policies.
- Long-term storage and backup are not included; users are responsible for managing their own data.
- Intensive jobs may require queue times depending on demand and system availability.
Eligibility and Audience
- Faculty conducting research or integrating HPC into curriculum.
- Graduate and undergraduate students working on approved research or coursework.
- Staff and research support personnel assisting in data analysis and computing workflows.
- Use must be associated with university-sponsored activities.
Getting Started and Support
Contact rescomp@miamioh.edu for questions and support of specific modules on the cluster