Cortical-inspired placement and routing: minimizing the memory resources in multi-core neuromorphic processors

• URL: http://arxiv.org/abs/2208.13587v1
• Date: Mon, 29 Aug 2022 13:28:02 GMT
• Title: Cortical-inspired placement and routing: minimizing the memory resources in multi-core neuromorphic processors
• Authors: Vanessa R. C. Leite, Zhe Su, Adrian M. Whatley, Giacomo Indiveri
• Abstract summary: We propose a network design approach inspired by biological neural networks. We use this approach to design a new routing scheme optimized for small-world networks. We present a hardware-aware placement algorithm that optimize the allocation of resources for small-world network models.
• Score: 5.391889175209394
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Brain-inspired event-based neuromorphic processing systems have emerged as a promising technology in particular for bio-medical circuits and systems. However, both neuromorphic and biological implementations of neural networks have critical energy and memory constraints. To minimize the use of memory resources in multi-core neuromorphic processors, we propose a network design approach inspired by biological neural networks. We use this approach to design a new routing scheme optimized for small-world networks and, at the same time, to present a hardware-aware placement algorithm that optimizes the allocation of resources for small-world 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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