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CCU:GPU Cluster

1,009 bytes added, 6 years ago

→‎Overview

== Overview ==

The CCU provides access to state-of-the-art infrastructure for GPU-based machine learning frameworks based on nVidia GPUs.

This page gives a general overview and links to more in-depth tutorials on how to work with the cluster.

There is some overhead involved when writing code for your projects and you have to stick to a few guidelines,

but there are template projects and scripts provided so that you can get started with minimal knowledge about the

technical background of the GPU cluster.

== What you need ==

* An account for the CCU.

* Ideally, a desktop PC with an nVidia GPU to test your code before pushing it to the cluster (debugging can otherwise be hard).

* Your PC ideally runs a flavor of Linux, all example scripts were tested against Ubuntu 18.04 (should also work on derivatives, such as Mint 19).

* Admin access to your own PC to install lots of stuff (or a friendly administrator).

* More specific needs will be covered in the in-depth tutorials.

== How to get started ==

* Step 1:

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