GeNN: a code generation framework for accelerated brain simulations
- Submitting institution
-
University of Sussex
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 206151_59372
- Type
- D - Journal article
- DOI
-
10.1038/srep18854
- Title of journal
- Scientific Reports
- Article number
- a18854
- First page
- -
- Volume
- 6
- Issue
- -
- ISSN
- 2045-2322
- Open access status
- Out of scope for open access requirements
- Month of publication
- May
- Year of publication
- 2015
- URL
-
http://dx.doi.org/10.1038/srep18854
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
2
- Research group(s)
-
-
- Citation count
- 37
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- "This is the primary publication for the GeNN software [1] for GPU accelerated spiking neural network simulations. GeNN was instrumental for our participation in large projects (Green Brain, EPSRC, £660,561 [2], Brains on Board, EPSRC, £4,816,675 [3], ActiveAI, £953,584 [4], contacts: james.marshall@sheffield.ac.uk, andrewop@sussex.ac.uk). It also underpinned work with Huawei (contact: guoqinghai@huawei.com) and has led to several follow-on publications [5-7]. The paper has an accelerating citation profile and is typically cited by competitors seeing GeNN as the gold standard to beat (e.g. [8]).
[1] https://github.com/genn-team/genn
[2] https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/J019534/1
[3] https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/P006094/1
[4] https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/S030964/1
[5] https://doi.org/10.3389/fnins.2018.00941
[6] https://doi.org/10.1038/s41598-019-54957-7
[7] https://doi.org/10.1038/s43588-020-00022-7
[8] https://doi.org/10.1016/j.neucom.2018.04.007"
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -