HPC at SCU utilizes a powerful cluster environment to support research, coursework, and advanced computational projects across disciplines. Users can submit and monitor SLURM jobs, request GPUs and memory, manage software environments with Conda, and run tools like MATLAB, C/C++, Jupyter, and machine learning workflows through Open OnDemand. These resources enable efficient, scalable computing while simplifying access to high-performance infrastructure.
We offer tutorials for:
- Video and Camino Courses – Basic introductory videos and detailed course guides for specific topics.
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SLURM Job Submission – Essential for submitting, scheduling, and managing jobs on the cluster so resources are used efficiently.
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Command Line Terminal – Provides the foundational skills needed to navigate the system, transfer files, and run programs.
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Conda – Helps users manage software environments and dependencies for reproducible research and coding workflows.
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Machine Learning – Guides users on leveraging GPUs and cluster resources for training and running ML models at scale.
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C/C++ Programs – Supports compiling and running high-performance compiled code for simulations and compute-heavy tasks.
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MATLAB – Enables users to run MATLAB workloads on HPC hardware for faster processing and larger datasets.
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Open OnDemand – Offers a web-based interface for accessing the cluster, launching apps, managing files, and monitoring jobs without heavy command-line use.
- SSH Key Generation – Generate and use SSH keys to securely authenticate and access remote systems without needing a password.