This workshop teaches beginners on how to utilize the ASU Research Computing supercomputer. This workshop will cover the supercomputer's configuration, batch and interactive access, and available software packages. Access has been greatly simplified with the web portal, a browser-based interface to the supercomputer which supports command-line shell, drag and drop file transfer, job submission, and MATLAB, RStudio, Jupyter, and other applications.

This workshop will focus on best practices, profiling, and benchmarking in R. This workshop will also introduce how to submit R jobs to ASU’s supercomputers through the use of batch submissions, parameter sweeps, and SLURM job arrays.

This workshop will describe different low and high level approaches to accelerating existing or developing research codes through the use of Graphical Processing Units (GPUs) on the ASU High Performance Computing supercomputer.

Join Research Computing for: Data Transfers with ASU Research Computing.

The ASU Research Computing supercomputer hosts a high-speed scratch filesystem to quickly compute results in addition to 100 GB of storage in users' own personal home directories. When these filesystems become full, the performance of the supercomputer is impacted which can potentially cause system outages. Using Globus and other data transfer tools, this workshop will interactively teach users how to transfer data from their scratch or home directories.

This workshop covers more advanced topics for conducting research on ASU's high-performance computing cluster, mostly focusing on batch submission processes and benchmarking jobs through the command line.

Introduction to managing Python environments on the ASU High Performance Computing supercomputer. This workshop will cover the basics of creating, activating, and managing Python environments using Mamba, a package manager for Python that is designed to be fast, scalable, and easy to use.

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