Asynchronous Neuromorphic Optimization with Lava
Fuente:
arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866913330295209984 |
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| author | Snyder, Shay Risbud, Sumedh R. Parsa, Maryam |
| author_facet | Snyder, Shay Risbud, Sumedh R. Parsa, Maryam |
| contents | Performing optimization with event-based asynchronous neuromorphic systems presents significant challenges. Intel's neuromorphic computing framework, Lava, offers an abstract application programming interface designed for constructing event-based computational graphs. In this study, we introduce a novel framework tailored for asynchronous Bayesian optimization that is also compatible with Loihi 2. We showcase the capability of our asynchronous optimization framework by connecting it with a graph-based satellite scheduling problem running on physical Loihi 2 hardware. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_17052 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Asynchronous Neuromorphic Optimization with Lava Snyder, Shay Risbud, Sumedh R. Parsa, Maryam Emerging Technologies Performing optimization with event-based asynchronous neuromorphic systems presents significant challenges. Intel's neuromorphic computing framework, Lava, offers an abstract application programming interface designed for constructing event-based computational graphs. In this study, we introduce a novel framework tailored for asynchronous Bayesian optimization that is also compatible with Loihi 2. We showcase the capability of our asynchronous optimization framework by connecting it with a graph-based satellite scheduling problem running on physical Loihi 2 hardware. |
| title | Asynchronous Neuromorphic Optimization with Lava |
| topic | Emerging Technologies |
| url | https://arxiv.org/abs/2404.17052 |