Say hi to
Hopper
Hopper is the high-performance computing environment of the College of Aviation, Science and Technology (CoAST) at Lewis University. It serves research well beyond data science, from AI and large-model development to medical data analysis, machine automation and robotics, and cybersecurity. It runs the projects no laptop can.
Hopper marks the start of the AI era at CoAST and Lewis University, powering multiple federal and international research projects and collaborative research with partner institutions.
Get Started Contact Admin// Find information just for you
For Researchers
Hopper is where the biggest research projects can comfortably run, including federal and international research projects and co-research with multiple partner institutions. Batch and interactive workloads, GPU-accelerated computing, and large-scale storage.
For Students
You don't need any HPC experience to get started. Hopper gives students a manageable environment to learn about advanced computing, from first jobs to capstone projects.
Help When You Need It
Professors and student researchers alike are available to schedule, troubleshoot, and assist, so your work keeps moving.
// Support in the following areas
Programming
All widely used programming languages and toolchains, including Python, GNU C, GNU C++, R, CUDA, NetLogo, Quantum Espresso, and MATLAB with all add-ons, scheduled with Slurm/MPI.
LLM & AI
Opencode with unlimited high-end LLM model access, Claude Code (individual subscription required), and an uncensored open-weight model (OSS 208) for authorized security research.
External Services for Capstone
Limited external services for capstone projects: web hosting, MySQL, and AWS with all features and functions.
Cybersecurity Attack & Simulation
OpenStack-based virtual environments (Debian VMs with VPN access) for cybersecurity attack and defense simulation.
Fusion Multi-Modal AI Development
Development of fusion multi-modal large models: training and fine-tuning models that combine text, image, and sensor data on datacenter-class GPUs.
Data Analytics
Large-scale data analytics across disciplines, including deep analysis of medical data and other data-intensive research domains.
// The Hopper roster
GPU-accelerated computing with NVIDIA datacenter-class GPUs (e.g., H100) for AI and machine learning.
GPU-accelerated computing with NVIDIA datacenter-class GPUs (e.g., H100) for AI and machine learning.
High-performance CPU computing for batch jobs, simulation, and general research workloads.
Hosts cluster applications and services: source control, web tools, and shared research applications.
Hybrid CPU/GPU computing for mixed workloads that pair heavy preprocessing with acceleration.
Hybrid CPU/GPU computing for data analytics, modeling, and interactive research work.
GPU-accelerated training and inference for large-model and deep-learning workloads. Joining the roster in Spring 2027.
OpenStack-based CPU nodes for network simulation, hosting virtual environments for cybersecurity and networking research.
// Get started
- Fill out the access request form. Submit the Hopper access request form to tell us who you are and what you'd like to run. Questions can go to sslab@lewisu.edu.
- Set up your account. We'll follow up with the how-to guide, your credentials, and your first login.
- Schedule your first project. Submit your first jobs, and reach out any time you need help along the way.