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Benchmarking neuromorphic systems with Nengo
Nengo is a software package for designing and simulating large-scale neural models. Nengo is architected such that the same Nengo model can be simulated on any of several Nengo backends with few to no modifications. Backends translate a model to specific platforms, which include GPUs and neuromorphi...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4609756/ https://www.ncbi.nlm.nih.gov/pubmed/26539076 http://dx.doi.org/10.3389/fnins.2015.00380 |
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author | Bekolay, Trevor Stewart, Terrence C. Eliasmith, Chris |
author_facet | Bekolay, Trevor Stewart, Terrence C. Eliasmith, Chris |
author_sort | Bekolay, Trevor |
collection | PubMed |
description | Nengo is a software package for designing and simulating large-scale neural models. Nengo is architected such that the same Nengo model can be simulated on any of several Nengo backends with few to no modifications. Backends translate a model to specific platforms, which include GPUs and neuromorphic hardware. Nengo also contains a large test suite that can be run with any backend and focuses primarily on functional performance. We propose that Nengo's large test suite can be used to benchmark neuromorphic hardware's functional performance and simulation speed in an efficient, unbiased, and future-proof manner. We implement four benchmark models and show that Nengo can collect metrics across five different backends that identify situations in which some backends perform more accurately or quickly. |
format | Online Article Text |
id | pubmed-4609756 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-46097562015-11-04 Benchmarking neuromorphic systems with Nengo Bekolay, Trevor Stewart, Terrence C. Eliasmith, Chris Front Neurosci Neuroscience Nengo is a software package for designing and simulating large-scale neural models. Nengo is architected such that the same Nengo model can be simulated on any of several Nengo backends with few to no modifications. Backends translate a model to specific platforms, which include GPUs and neuromorphic hardware. Nengo also contains a large test suite that can be run with any backend and focuses primarily on functional performance. We propose that Nengo's large test suite can be used to benchmark neuromorphic hardware's functional performance and simulation speed in an efficient, unbiased, and future-proof manner. We implement four benchmark models and show that Nengo can collect metrics across five different backends that identify situations in which some backends perform more accurately or quickly. Frontiers Media S.A. 2015-10-19 /pmc/articles/PMC4609756/ /pubmed/26539076 http://dx.doi.org/10.3389/fnins.2015.00380 Text en Copyright © 2015 Bekolay, Stewart and Eliasmith. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Bekolay, Trevor Stewart, Terrence C. Eliasmith, Chris Benchmarking neuromorphic systems with Nengo |
title | Benchmarking neuromorphic systems with Nengo |
title_full | Benchmarking neuromorphic systems with Nengo |
title_fullStr | Benchmarking neuromorphic systems with Nengo |
title_full_unstemmed | Benchmarking neuromorphic systems with Nengo |
title_short | Benchmarking neuromorphic systems with Nengo |
title_sort | benchmarking neuromorphic systems with nengo |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4609756/ https://www.ncbi.nlm.nih.gov/pubmed/26539076 http://dx.doi.org/10.3389/fnins.2015.00380 |
work_keys_str_mv | AT bekolaytrevor benchmarkingneuromorphicsystemswithnengo AT stewartterrencec benchmarkingneuromorphicsystemswithnengo AT eliasmithchris benchmarkingneuromorphicsystemswithnengo |