Tutorials

Description:

Installing and managing software packages often poses a challange to HPC users on Linux systems without root permission. This two-part mini series is aiming at introducing helpful tools to remedy that.

This part will feature container technology and the software Singularity (a.k.a. Apptainer), a popular implementation of containers on HPC. Containers are gaining increasing popularities for its flexibility and portability. More and more developers now start to release their software packages as working containers for users' convenience. In this training, we will discuss how to use Singularity to run container images on our clusters, acquire more container images, and build your own container images. We will also showcase the usage of containerized popular packages such as Tensorflow and PyTorch.

Prerequisites:

Basic knowledge of HPC environment and Linux is preferred but not required.

Description:

Installing and managing software packages often poses a challange to HPC users on Linux systems without root permission. This two-part mini series is aiming at introducing helpful tools to remedy that.

This part will feature virtual environments and the software Conda, a popular tool working with virtual environments. In this training, we will discuss how to use Conda and virtual environments to install and manage software packages on our clusters, including frequently requested packages such as Tensorflow and PyTorch. We will also share useful tips, such as sharing virtual environment with group members and using Conda to manage software packages beyond Python (e.g., R / Perl).

Prerequisites:

Basic knowledge of HPC environment and Linux is preferred but not required.

Description:

In scientific computing disciplines such as bioinformatics, computational biology, and other data-intensive fields, many tools and workflows remain serial in nature. Running a large number of these independent jobs efficiently on a multi-core HPC platform can be challenging.

This training will introduce two powerful approaches for handling such workloads namely GNU Parallel and SLURM Job Arrays. This training session covers efficient execution and management of large collections of independent or parameter-sweep tasks using GNU Parallel and SLURM Job Arrays, leveraging both single-node and multi-node HPC environments for scalable, high-throughput processing. Through hands-on, real-world examples, we will demonstrate how to launch, monitor, and optimize massive batches of serial or lightweight jobs using GNU Parallel and SLURM Job Arrays, highlighting their similarities, differences, and best-use scenarios.

Prerequisites:

Basic knowledge of HPC environment and Linux is preferred but not required.

Description:

Molecular dynamics simulation (MD) is a computational technique that is used to study the dynamics of molecules and atoms over time. The tutorial will discuss the essentials of the classical molecular dynamics simulations. The basic system setup, initialization, and analysis for widely used simulation packages such as LAMMPS, GROMACS, AMBER and NAMD on LONI and LSU HPC clusters will be reviewed.

Prerequisites:

Basic knowledge of HPC environment and Linux is preferred but not required.