Hierarchical Network Connectivity and Partitioning for Reconfigurable Large-Scale Neuromorphic Systems
We present an efficient and scalable partitioning method for mapping large-scale neural network models with locally dense and globally sparse connectivity onto reconfigurable neuromorphic hardware. Scalability in computational efficiency, i.e., amount of time spent in actual computation, remains a h...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-01-01
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| Series: | Frontiers in Neuroscience |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fnins.2021.797654/full |