论文标题
迈向基于TNN的神经形态感官处理单元的设计框架
Towards a Design Framework for TNN-Based Neuromorphic Sensory Processing Units
论文作者
论文摘要
时间神经网络（TNNS）是尖峰神经网络，具有高能量效率表现出类似脑的感觉处理。这项工作介绍了正在进行的研究，以开发一个定制设计框架，用于设计有效的基于特定于TNN的神经形态感官处理单元（NSPU）。本文研究了有关UCR时间序列聚类和MNIST图像分类应用程序的NSPU设计的先前作品。定制设计框架和工具的当前想法可以使高效的软件到硬件设计流程进行快速设计空间探索应用特定的NSPU，同时利用EDA工具获得了Layout Netlist和Power-Performance-arrea（PPA）指标。还概述了未来的研究方向。
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.
