Comparing neuromorphic solutions in action: implementing a bio-inspired solution to a benchmark classification task on three parallel-computing platforms
- Submitting institution
-
University of Sussex
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 206151_59469
- Type
- D - Journal article
- DOI
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10.3389/fnins.2015.00491
- Title of journal
- Frontiers in Neuroscience
- Article number
- -
- First page
- 1
- Volume
- 9
- Issue
- a491
- ISSN
- 1662-4548
- Open access status
- Out of scope for open access requirements
- Month of publication
- January
- Year of publication
- 2016
- URL
-
https://doi.org/10.3389/fnins.2015.00491
- 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
- 21
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper has had significant impacts on the design of software stacks for neuromorphic computers. After the paper demonstrated the costs of model preparation in terms of energy and time on a supporting classical computer there was a clear shift to on-device initialisation in both the SpiNNaker (contact: Prof Steve Furber, steve.furber@manchester.ac.uk) and BrainsScaleS (contact: Dr Johannes Schemmel, schemmel@asic.uni-heidelberg.de) teams, as well as in our own GeNN software.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -