Introduction to Brian: A Simulator for Spiking Neural Networks

Brian is a simulator designed for spiking neural networks, focusing on ease of use, flexibility, performance, and reliability. It allows runtime code generation, C++ conversion, and GPU support for enhanced performance. Despite limitations in large-scale simulations, Brian is ideal for small networks. Meet the Brian team and explore the potential of this powerful tool.

• Brian Simulator
• Spiking Neural Networks
• Performance
• GPU Support
• Neural Science

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1. Dan Goodman, Marcel Stimberg, Romain Brette, http://briansimulator.org

2. What is Brian? Simulator for spiking neural networks Install: conda install c conda-forge brian2 Focus on Easy to learn and use Flexibility Performance Reliability Documentation: https://brian2.readthedocs.io https://tinyurl.com/Brian2Demo Try a demo of Brian in the browser while you listen to the talk: https://tinyurl.com/Brian2Demo

3. Demo A live demo? Surely nothing could go wrong? https://tinyurl.com/Brian2Demo Try a demo of Brian in the browser while you listen to the talk: https://tinyurl.com/Brian2Demo

4. Performance Runtime code generation Brian model converted to C++ Allows code specialised for model Heterogeneous: Similar to NEST (3x faster for large) 8x faster than NEURON Homogeneous: 12x faster than NEST, even with 1 thread 27x faster than NEURON Stimberg, Brette, Goodman (2020) eLife https://tinyurl.com/Brian2Demo Try a demo of Brian in the browser while you listen to the talk: https://tinyurl.com/Brian2Demo

5. GPU support via Brian2GeNN GeNN A GPU simulator for SNNs Thomas Nowotny (Sussex) and team Brian2GeNN Brian code on GPU using GeNN backend Simply add the lines import brian2genn set_device( genn ) Up to 400x faster than single CPU Most models supported Stimberg, Goodman, Nowotny (2020) Sci. Rep. https://tinyurl.com/Brian2Demo Try a demo of Brian in the browser while you listen to the talk: https://tinyurl.com/Brian2Demo

6. Limitations Single machine No support for large, distributed simulations on supercomputers. We think there s plenty of work to do on small networks (e.g. up to 10M neuron). If you need this, try NEST. Focus on single compartment neurons Some support for multi-compartmental neurons. For simple things, can use Brian. If this is your main focus, try NEURON. https://tinyurl.com/Brian2Demo Try a demo of Brian in the browser while you listen to the talk: https://tinyurl.com/Brian2Demo

7. Thanks! Any questions? Brian team GeNN team Marcel Stimberg Romain Brette James Knight James Turner Esin Yavuz Thomas Nowotny Cyrille Rossant, Victor Benichoux, Pierre Yger, Werner Beroux, Konrad Wartke, Daniel Bliss, Jan-Hendrik Schleimer, Moritz Augustin, Romain Caz , Dominik Krzemi ski, Martino Sorbaro, Benjamin Evans, Meng Dong, Alex Seeholzer, Daan Sprenkels, Edward Betts, Thomas McColgan, Charlee Fletterman, Mihir Vaidya, Teo Stocco, Dylan Richard Muir, Adrien F. Vincent, Kapil Kumar, Matthieu Recugnat, Paul Brodersen, Guillaume Dumas, Aleksandra Teska, Vigneswaran Chandrasekaran and all the Brian users https://tinyurl.com/Brian2Demo Try a demo of Brian in the browser while you listen to the talk: https://tinyurl.com/Brian2Demo