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arXiv · 2203.00655

A hardware-software co-design approach to minimize the use of memory resources in multi-core neuromorphic processors

Vanessa R. C. Leite·Zhe Su·Adrian M. Whatley·Giacomo Indiveri
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Abstract

Both in electronics and biology, physical implementations of neural networks have severe energy and memory constraints. We propose a hardware-software co-design approach for minimizing the use of memory resources in multi-core neuromorphic processors, by taking inspiration from biological neural networks. We use this approach to design new routing schemes optimized for small-world networks and to provide guidelines for designing novel application-specific multi-core neuromorphic chips. Starting from the hierarchical routing scheme proposed, we present a hardware-aware placement algorithm that optimizes the allocation of resources for arbitrary network models. We validate the algorithm with a canonical small-world network and present preliminary results for other networks derived from it.

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Vanessa R. C. Leite, Zhe Su, Adrian M. Whatley, Giacomo Indiveri. 2022-03-01. A hardware-software co-design approach to minimize the use of memory resources in multi-core neuromorphic processors. https://arxiv.org/abs/2203.00655

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