Parallelizing Massively Independent Tasks - GNU Parallel and Job Arrays

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.