index.rst

Arbor

Arbor is a high-performance library for computational neuroscience simulations with morphologically-detailed cells, from single cell models to very large networks.

The development team is from HPC centers, aiming to help neuroscientists effectively use contemporary and future HPC systems to meet their simulation needs.

Arbor is designed from the ground up for many core architectures:

• Written in modern C++ and CUDA;
• Distributed parallelism using MPI;
• Multithreading with TBB and C++11 threads;
• Open source and open development;
• Sound development practices: unit testing, continuous Integration, and validation.

Citing Arbor

@INPROCEEDINGS{
    paper:arbor2019,
    author={N. A. {Akar} and B. {Cumming} and V. {Karakasis} and A. {Küsters} and W. {Klijn} and A. {Peyser} and S. {Yates}},
    booktitle={2019 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)},
    title={{Arbor --- A Morphologically-Detailed Neural Network Simulation Library for Contemporary High-Performance Computing Architectures}},
    year={2019}, month={feb}, volume={}, number={},
    pages={274--282},
    doi={10.1109/EMPDP.2019.8671560},
    ISSN={2377-5750}}

Alternative citation formats for the paper can be downloaded here, and a preprint is available at arXiv.