In this section
@article{Stimberg:2020:10.1038/s41598-019-54957-7,
author = {Stimberg, M and Goodman, D and Nowotny, T},
doi = {10.1038/s41598-019-54957-7},
journal = {Scientific Reports},
pages = {1--12},
title = {Brian2GeNN: accelerating spiking neural network simulations with graphics hardware},
url = {http://dx.doi.org/10.1038/s41598-019-54957-7},
volume = {10},
year = {2020}
}
TY - JOUR
AB - “Brian” is a popular Python-based simulator for spiking neural networks, commonly used in computational neuroscience. GeNNis a C++-based meta-compiler for accelerating spiking neural network simulations using consumer or high performance gradegraphics processing units (GPUs). Here we introduce a new software package, Brian2GeNN, that connects the two systems sothat users can make use of GeNN GPU acceleration when developing their models in Brian, without requiring any technicalknowledge about GPUs, C++ or GeNN. The new Brian2GeNN software uses a pipeline of code generation to translate Brianscripts 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 thatusing Brian2GeNN, two non-trivial models from the literature can run tens to hundreds of times faster than on CPU.
AU - Stimberg,M
AU - Goodman,D
AU - Nowotny,T
DO - 10.1038/s41598-019-54957-7
EP - 12
PY - 2020///
SN - 2045-2322
SP - 1
TI - Brian2GeNN: accelerating spiking neural network simulations with graphics hardware
T2 - Scientific Reports
UR - http://dx.doi.org/10.1038/s41598-019-54957-7
UR - https://www.nature.com/articles/s41598-019-54957-7
UR - http://hdl.handle.net/10044/1/75380
VL - 10
ER -
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