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

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 net...

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Bibliographic Details
Published inarXiv.org
Main Authors Leite, Vanessa R C, Su, Zhe, Whatley, Adrian M, Indiveri, Giacomo
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 01.03.2022
Subjects
Algorithms
Co-design
Design optimization
Hardware
Microprocessors
Neural networks
Processors
Software
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Summary: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.
ISSN:2331-8422