This advanced session focuses on improving the efficiency, scalability, and reproducibility of your research workflows on the Hoffman2 Cluster. Topics include job arrays, resource monitoring, environment management (e.g., python, conda), and best practices for data and storage usage. Ideal for users ready to streamline and scale their computational research.
This workshop introduces participants to running batch jobs on the Hoffman2 Cluster using the job scheduler. Attendees will learn how to write and submit batch scripts, request computing resources, monitor job status, and manage output files. This session is essential for researchers aiming to run larger or automated workloads efficiently.
This workshop guides researchers through running Jupyter Notebooks on the Hoffman2 Cluster for interactive data analysis and computing. Participants will learn how to launch Jupyter via the job scheduler, connect securely through SSH tunneling, and manage computing resources effectively. Ideal for users familiar with Jupyter who want to scale their workflows using the Hoffman2 Cluster.