PSoC-Based Real-Time Data Acquisition for a Scalable Spiking Neural Network Hardware Architecture
Journal
2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018
Date Issued
2018
Author(s)
Balaji U.K.
Madrenas J.
Type
Conference Paper
Abstract
Data acquisition for monitoring the spiky activity of large-scale SNN hardware architectures are a challenge due to their time constraints, complexity, large logic size, and so on. This paper presents a versatile PSoC-Based Data Acquisition prototype, where a specialized Master Device is used for this purpose. It benefits from the heterogeneous nature of SoC platforms that allows it to host programmable logic together with a hard-core ARM processor integrating memory and a variety of peripherals in a single chip. The presented design enables monitoring the performance of a multi-chip neural network through a single Ethernet interface in a hardware and software co-design, which is combined with an application developed in Python that allows the visualization on the PC of a dynamic raster plot of neural activity. In addition, an example of full platform functionality is shown. © 2018 IEEE.
Subjects