Arbor: a multi-compartment neural network simulation library

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OCNS 2021

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At the 2021 edition of the CNS conference, Arbor is present with a tutorial. We have a 3-hour timeslot with an introduction and a hands-on session on July 1st. Starting time: 06:00 Los Angeles, 09:00 New York, 15:00 Berlin, 23:00 Sydney.

Join the Arbor workshop session at at this URL.

Get the workshop slides and materials here.

See here for an overview of the whole program: CNS 2021 tutorials

Tutorial description

Arbor is a performance portable library designed to handle very large and computationally intensive simulations of networks of multi-compartment neurons. At the same time, Arbor is designed to be easy to use and understand, so that also beginners to computational neuroscience can get up to speed quickly. Furthermore, Arbor aims to prepare computational neuroscientists to take advantage of HPC architectures. Whether your model is large or small, Arbor is able to optimize and compute your result on almost any current and future hardware.

In this session, we’ll first introduce the Arbor simulator library. We will go into questions such as:

After the introduction, it is time for a hands-on session where Arbor is used to:

Participating in the tutorial assumes that attendees are comfortable using the Python programming language. No prior knowledge of Arbor or constructing neuroscientific simulations is required. ​


Although preparation is not required, having a look through the Arbor documentation beforehand can help you get the most out of this tutorial. If you wish to run the tutorial on your own machine, make sure you have Python installed (v3.6 or higher) and have installed the arbor and seaborn packages through pip, e.g. pip install arbor seaborn.

Note: Windows users are supported through WSL and WSL only at this time.