Neuromórfico EG - Neuromorphic systems for processing in EdGe Computing - ITCL

Neuromórfico-EG – Research in the design and development of Neuromorphic systems for processing in EdGe Computing in general purpose systems, capital equipment, healthcare systems and cybersecurity in IDS.

Regional Project


The general objectives of the Neuromorphic-EG project are:

  • The investigation of all issues related to hardware architectures.
  • Neuron-based algorithms for dynamic series processing
  • Hardware designs
  • Algorithm designs realized in classical computation.
  • The transformation of the algorithms to neuromorphic computing
  • The deployment of a complete neuromorphic hardware system for processing in Egde Computing (EC).

The project will also incorporate optimization data transmission. All this, implemented on hardware architectures that optimize performance and allow the implementation of networks of a high number of neurons.

For this puropose it is proposed, as a result of the planned research, the implementation of a practical mixed analog-digital neural engine based on an innovative architecture and a hardware platform based on SoC for large-scale ANN, while the implementation of the entire algorithm is developed on digital systems operating in the EC machine.

This industrial research project will promote enabling technological solutions for Industry 4.0 that make sense of neuromorphic systems and edge computing at the industrial level. It will be about solutions and strategies with a high technological content that achieve intelligent tools that enable companies in Castilla y León to access the transfer of research results quickly from the research with the project’s demonstrator prototypes.

    Duration time:  August 2020 – Dececember 2022

    It is a project funded by the Junta de Castilla y León, through the ICE JCYL grant program for the implementation of R & D projects of regional interest aimed at excellence and competitive improvement of the Technology Centers of Castilla y León co-financed with ERDF 2014 – 2020.