Towards a Design Framework for TNN-Based Neuromorphic Sensory Processing Units

• URL: http://arxiv.org/abs/2205.14248v1
• Date: Fri, 27 May 2022 21:51:05 GMT
• Title: Towards a Design Framework for TNN-Based Neuromorphic Sensory Processing Units
• Authors: Prabhu Vellaisamy and John Paul Shen
• Abstract summary: Temporal Neural Networks (TNNs) are spiking neural networks that exhibit brain-like sensory processing with high energy efficiency. This work presents the ongoing research towards developing a custom design framework for designing efficient application-specific TNN-based Neuromorphic Sensory Processing Units (NSPUs)
• Score: 2.419276285404291
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Temporal Neural Networks (TNNs) are spiking neural networks that exhibit brain-like sensory processing with high energy efficiency. This work presents the ongoing research towards developing a custom design framework for designing efficient application-specific TNN-based Neuromorphic Sensory Processing Units (NSPUs). This paper examines previous works on NSPU designs for UCR time-series clustering and MNIST image classification applications. Current ideas for a custom design framework and tools that enable efficient software-to-hardware design flow for rapid design space exploration of application-specific NSPUs while leveraging EDA tools to obtain post-layout netlist and power-performance-area (PPA) metrics are described. Future research directions are also outlined.

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