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Brian2GeNN: accelerating spiking neural network simulations with graphics hardware
“Brian” is a popular Python-based simulator for spiking neural networks, commonly used in computational neuroscience. GeNN is a C++-based meta-compiler for accelerating spiking neural network simulations using consumer or high performance grade graphics processing units (GPUs). Here we introduce a n...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6962409/ https://www.ncbi.nlm.nih.gov/pubmed/31941893 http://dx.doi.org/10.1038/s41598-019-54957-7 |
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author | Stimberg, Marcel Goodman, Dan F. M. Nowotny, Thomas |
author_facet | Stimberg, Marcel Goodman, Dan F. M. Nowotny, Thomas |
author_sort | Stimberg, Marcel |
collection | PubMed |
description | “Brian” is a popular Python-based simulator for spiking neural networks, commonly used in computational neuroscience. GeNN is a C++-based meta-compiler for accelerating spiking neural network simulations using consumer or high performance grade graphics processing units (GPUs). Here we introduce a new software package, Brian2GeNN, that connects the two systems so that users can make use of GeNN GPU acceleration when developing their models in Brian, without requiring any technical knowledge about GPUs, C++ or GeNN. The new Brian2GeNN software uses a pipeline of code generation to translate Brian scripts into C++ code that can be used as input to GeNN, and subsequently can be run on suitable NVIDIA GPU accelerators. From the user’s perspective, the entire pipeline is invoked by adding two simple lines to their Brian scripts. We have shown that using Brian2GeNN, two non-trivial models from the literature can run tens to hundreds of times faster than on CPU. |
format | Online Article Text |
id | pubmed-6962409 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-69624092020-01-23 Brian2GeNN: accelerating spiking neural network simulations with graphics hardware Stimberg, Marcel Goodman, Dan F. M. Nowotny, Thomas Sci Rep Article “Brian” is a popular Python-based simulator for spiking neural networks, commonly used in computational neuroscience. GeNN is a C++-based meta-compiler for accelerating spiking neural network simulations using consumer or high performance grade graphics processing units (GPUs). Here we introduce a new software package, Brian2GeNN, that connects the two systems so that users can make use of GeNN GPU acceleration when developing their models in Brian, without requiring any technical knowledge about GPUs, C++ or GeNN. The new Brian2GeNN software uses a pipeline of code generation to translate Brian scripts into C++ code that can be used as input to GeNN, and subsequently can be run on suitable NVIDIA GPU accelerators. From the user’s perspective, the entire pipeline is invoked by adding two simple lines to their Brian scripts. We have shown that using Brian2GeNN, two non-trivial models from the literature can run tens to hundreds of times faster than on CPU. Nature Publishing Group UK 2020-01-15 /pmc/articles/PMC6962409/ /pubmed/31941893 http://dx.doi.org/10.1038/s41598-019-54957-7 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Stimberg, Marcel Goodman, Dan F. M. Nowotny, Thomas Brian2GeNN: accelerating spiking neural network simulations with graphics hardware |
title | Brian2GeNN: accelerating spiking neural network simulations with graphics hardware |
title_full | Brian2GeNN: accelerating spiking neural network simulations with graphics hardware |
title_fullStr | Brian2GeNN: accelerating spiking neural network simulations with graphics hardware |
title_full_unstemmed | Brian2GeNN: accelerating spiking neural network simulations with graphics hardware |
title_short | Brian2GeNN: accelerating spiking neural network simulations with graphics hardware |
title_sort | brian2genn: accelerating spiking neural network simulations with graphics hardware |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6962409/ https://www.ncbi.nlm.nih.gov/pubmed/31941893 http://dx.doi.org/10.1038/s41598-019-54957-7 |
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