# Fundamentals

What Eugo is, how the pieces fit together, and where your work happens.

Source: https://university.eugo.io/topics/fundamentals

---

## Courses

- [Getting started with Eugo](https://university.eugo.io/courses/getting-started-with-eugo.md): What Eugo is, what problem it solves, and how to run your first workload on a cluster.
- [Eugo 101](https://university.eugo.io/courses/eugo-101.md): A full tour of the platform: sessions, clusters, workspaces, organizations, and how they fit together.
- [EugoIDE essentials](https://university.eugo.io/courses/eugoide-essentials.md): Work fluently in the browser-based notebook environment where your Python actually runs.

## Videos

- [What is Eugo, in 90 seconds](https://university.eugo.io/videos/what-is-eugo-in-90-seconds.md): The shortest useful answer: write ordinary Python, get supercomputer throughput, skip the infrastructure.
- [A tour of EugoIDE](https://university.eugo.io/videos/tour-of-eugoide.md): Every panel in the browser IDE, what it controls, and which parts of your work survive a restart.

## Checklists and guides

- [Workload readiness checklist](https://university.eugo.io/resources/workload-readiness-checklist.md): Verify a workload is worth distributing before you spend cluster time on it.
- [Migrating from cloud VMs](https://university.eugo.io/resources/migrating-from-cloud-vms-checklist.md): Move a workload off hand-managed instances without losing reproducibility.
- [Quick guide: data scientist](https://university.eugo.io/resources/quick-guide-data-scientist.md): The short version of what a data scientist needs on day one: where code runs, where data has to live, and the one habit that keeps a cluster busy.

## Vocabulary

- **High-performance computing (HPC)** — Running work across many machines at once so it finishes far sooner. The technique behind weather models, genomics, and large-scale simulation.
- **HPC as a service (HPCaaS)** — High-performance computing consumed on demand rather than owned: request compute for one run, stop paying when it ends. No hardware, no scheduler to run.
- **Distributed computing** — Splitting one job across several machines that work on it simultaneously. The core technique of HPC, and what the distribute decorator gives you in Python.
- **Job scheduler** — The queueing system on a traditional HPC cluster that decides when a submitted job runs. Eugo has no queue: you launch a cluster and dispatch work to it.
- **Cluster** — A set of machines, one head node and one or more compute nodes, launched together to run distributed work.
- **Compute node** — A machine in a cluster that executes tasks. Compute nodes do the work; the head node coordinates it.
- **EugoIDE** — The browser-based notebook environment where you write and run Python on Eugo. Built on JupyterLab, connected to compute in your workspace.
- **Head node** — The machine in a cluster that coordinates work: it schedules tasks onto compute nodes and tracks their results.
- **Interactive session** — A running EugoIDE instance attached to your workspace. It is where you write code; a cluster is what runs it at scale.
- **Workspace** — An isolated compute environment with its own persistent storage, preinstalled libraries, and resource allocation. Where your sessions and clusters run.
- **Independent work** — Units of work that can each produce their result without needing another unit’s output. A precondition for distributing anything.