Author: Danilo

Slurm nodes and partitions are among the first components I check when monitoring or troubleshooting an HPC cluster. Commands such as sinfo and scontrol provide immediate visibility into node states, partition availability, and potential issues that can affect job scheduling and cluster performance. If you’re getting started with Slurm administration, understanding how to inspect nodes and partitions is an essential skill. In my experience, these commands are invaluable for identifying unavailable nodes, reviewing partition status, and quickly determining why resources are not accepting new jobs. In this guide, I demonstrate how to view information about Slurm nodes and partitions using…

Slurm job submission is a fundamental task for users working with High Performance Computing (HPC) clusters. In this guide, I will demonstrate the basic commands used to submit jobs, including srun for interactive execution and sbatch for batch processing. When working with a Slurm-managed cluster, users do not usually execute workloads directly on compute nodes. Instead, they request resources from the scheduler, which allocates nodes, CPUs, and execution time according to the job requirements. This article provides practical examples of job submission in a Slurm environment, showing how to run commands interactively, submit scripts, inspect the queue, and understand the…

The Slurm invalid account error can occur when a user tries to submit jobs without a valid association in the Slurm database. In this guide, I will demonstrate a real troubleshooting scenario where a job submission fails with an account or account/partition combination error. While testing a Slurm cluster, I received this error when submitting a job using the srun command. The issue was related to the user configuration in Slurm accounting rather than the operating system user or home directory configuration. This article explains how to identify the cause of the problem, verify users and accounts with sacctmgr, and…

Creating a Simple Python Project Using a Virtual Environment demonstrates, in practice, how to use a virtual environment. First and foremost, we’ve written an article to explain how to install Python on Windows. Click here to access this article. Additionally, if you’re not familiar with Python virtual environment (venv), there is an article to explain it a bit. Click here to access this article. Let’s Get Started: The Python Directory After installing Python (on Windows, Linux, or any operating system), a good practice is to create a directory to store your Python projects. In our case, for instance, since we’re…

A Python virtual environment on Windows allows developers to create isolated environments for different projects, keeping Python packages and dependencies separated. In this guide, I will show how to create, activate, use, and manage a virtual environment using the built-in Python venv module. When working with Python projects, managing different library versions can become a challenge. A virtual environment provides a clean and organized way to install project-specific packages without affecting the global Python installation on Windows. I created this practical guide to demonstrate how Python virtual environments work in a Windows environment, including common tasks such as installing modules,…

Installing Python on Windows shows how to install Python step-by-step. I’ve been using Python on Linux, and I’d like to run it on Windows. So, I decided to create this simple article showing all the necessary steps to install Python on Windows. In this case, I’m running Windows 11 (I did not test it on previous Windows releases). Downloading Python Installer The first step is to download the Python installer: In my case, I’m using the 64-bit version (choose the best version for you): Installing Python on Windows Installing Python on Windows is straightforward. Double-click the Python installer and follow…