Brian2Loihi: An emulator for the neuromorphic chip Loihi using the spiking neural network simulator Brian
Developing intelligent neuromorphic solutions remains a challenging endeavor. It requires a solid conceptual understanding of the hardware's fundamental building blocks. Beyond this, accessible and user-friendly prototyping is crucial to speed up the design pipeline. We developed an open source...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-11-01
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| Series: | Frontiers in Neuroinformatics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fninf.2022.1015624/full |
| _version_ | 1811231301274959872 |
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| author | Carlo Michaelis Carlo Michaelis Andrew B. Lehr Andrew B. Lehr Winfried Oed Winfried Oed Christian Tetzlaff Christian Tetzlaff |
| author_facet | Carlo Michaelis Carlo Michaelis Andrew B. Lehr Andrew B. Lehr Winfried Oed Winfried Oed Christian Tetzlaff Christian Tetzlaff |
| author_sort | Carlo Michaelis |
| collection | DOAJ |
| description | Developing intelligent neuromorphic solutions remains a challenging endeavor. It requires a solid conceptual understanding of the hardware's fundamental building blocks. Beyond this, accessible and user-friendly prototyping is crucial to speed up the design pipeline. We developed an open source Loihi emulator based on the neural network simulator Brian that can easily be incorporated into existing simulation workflows. We demonstrate errorless Loihi emulation in software for a single neuron and for a recurrently connected spiking neural network. On-chip learning is also reviewed and implemented, with reasonable discrepancy due to stochastic rounding. This work provides a coherent presentation of Loihi's computational unit and introduces a new, easy-to-use Loihi prototyping package with the aim to help streamline conceptualization and deployment of new algorithms. |
| first_indexed | 2024-04-12T10:42:26Z |
| format | Article |
| id | doaj.art-47a4df511e53499fb435efe68c5447f2 |
| institution | Directory Open Access Journal |
| issn | 1662-5196 |
| language | English |
| last_indexed | 2024-04-12T10:42:26Z |
| publishDate | 2022-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroinformatics |
| spelling | doaj.art-47a4df511e53499fb435efe68c5447f22022-12-22T03:36:33ZengFrontiers Media S.A.Frontiers in Neuroinformatics1662-51962022-11-011610.3389/fninf.2022.10156241015624Brian2Loihi: An emulator for the neuromorphic chip Loihi using the spiking neural network simulator BrianCarlo Michaelis0Carlo Michaelis1Andrew B. Lehr2Andrew B. Lehr3Winfried Oed4Winfried Oed5Christian Tetzlaff6Christian Tetzlaff7Department of Computational Neuroscience, University of Göttingen, Göttingen, GermanyBernstein Center for Computational Neuroscience, University of Göttingen, Göttingen, GermanyDepartment of Computational Neuroscience, University of Göttingen, Göttingen, GermanyBernstein Center for Computational Neuroscience, University of Göttingen, Göttingen, GermanyDepartment of Computational Neuroscience, University of Göttingen, Göttingen, GermanyBernstein Center for Computational Neuroscience, University of Göttingen, Göttingen, GermanyDepartment of Computational Neuroscience, University of Göttingen, Göttingen, GermanyBernstein Center for Computational Neuroscience, University of Göttingen, Göttingen, GermanyDeveloping intelligent neuromorphic solutions remains a challenging endeavor. It requires a solid conceptual understanding of the hardware's fundamental building blocks. Beyond this, accessible and user-friendly prototyping is crucial to speed up the design pipeline. We developed an open source Loihi emulator based on the neural network simulator Brian that can easily be incorporated into existing simulation workflows. We demonstrate errorless Loihi emulation in software for a single neuron and for a recurrently connected spiking neural network. On-chip learning is also reviewed and implemented, with reasonable discrepancy due to stochastic rounding. This work provides a coherent presentation of Loihi's computational unit and introduces a new, easy-to-use Loihi prototyping package with the aim to help streamline conceptualization and deployment of new algorithms.https://www.frontiersin.org/articles/10.3389/fninf.2022.1015624/fullneuromorphic computingLoihiBrian2emulatorspiking neural networkopen source |
| spellingShingle | Carlo Michaelis Carlo Michaelis Andrew B. Lehr Andrew B. Lehr Winfried Oed Winfried Oed Christian Tetzlaff Christian Tetzlaff Brian2Loihi: An emulator for the neuromorphic chip Loihi using the spiking neural network simulator Brian Frontiers in Neuroinformatics neuromorphic computing Loihi Brian2 emulator spiking neural network open source |
| title | Brian2Loihi: An emulator for the neuromorphic chip Loihi using the spiking neural network simulator Brian |
| title_full | Brian2Loihi: An emulator for the neuromorphic chip Loihi using the spiking neural network simulator Brian |
| title_fullStr | Brian2Loihi: An emulator for the neuromorphic chip Loihi using the spiking neural network simulator Brian |
| title_full_unstemmed | Brian2Loihi: An emulator for the neuromorphic chip Loihi using the spiking neural network simulator Brian |
| title_short | Brian2Loihi: An emulator for the neuromorphic chip Loihi using the spiking neural network simulator Brian |
| title_sort | brian2loihi an emulator for the neuromorphic chip loihi using the spiking neural network simulator brian |
| topic | neuromorphic computing Loihi Brian2 emulator spiking neural network open source |
| url | https://www.frontiersin.org/articles/10.3389/fninf.2022.1015624/full |
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