
Blockchain technology applied to urban mobility
January 4, 2020
ALLINONE: More energy efficiency in wireless networks
February 1, 2020CoCoUnit is a new processing unit for incorporation into existing processor units (general purpose cores, GPUs, etc.) that will be capable of developing cognitive functions with extremely high energy efficiency. The new unit will make new user experiences that require cognitive functions possible in real time in numerous devices, including mobile devices (such as smart phones and portable devices) and servers in data centres.

This innovative unit, developed by the Architectures and Compilers (ARCO) research group led by Antonio González, will contribute to the development of what is already known as cognitive computing. Through new architectures inspired by the brain, the aim is to expand the capacities of information systems so that they can develop tasks that are traditionally associated with human intelligence such as voice recognition, automatic translation, speech synthesis, image classification or object recognition. In short, the aim is to give computers learning, synthesis and reasoning capacities similar to those developed by the human brain.
Like the brain, the future CoCoUnit will be based on massively parallel architecture with extremely simple units, as it has been found that many simple units are more energy efficient than a few complex units.
The new unit will reduce data movement. The von Neumann architecture that is currently used in processors has enormous energy costs as data have to be moved around the system: all the instructions and operands must be extracted from the memory and sent to the execution units, and the results must be written again in the memory hierarchy. The interconnections for moving the data consume most of the energy of a microprocessor. Reducing these movements could therefore represent considerable energy efficiency benefits.
CoCoUnit will also include specialised hardware for some key functions and will be based on a different computing model, focused on ‘intelligence': learning, rather than ‘imperative programming’ will play a key role in this new approach. In addition, the new unit will explore resilience and approximate computing for greater energy efficiency.
This project has received an Advanced Grant, the highest award given by the European Research Council (ERC) to research projects at the frontiers of knowledge. The project began in September 2019 and will last five years, with funding of 2.5 million euros.
Technology
Topic
You want to know more?
Related Projects
STOR-HY: More flexible, efficient and resilient hydropower storage for the European electricity grid
The Center for Industrial Diagnostics (CDIF) at the Universitat Politècnica de Catalunya - BarcelonaTech (UPC) coordinates the European STOR-HY project, which develops digital tools, monitoring systems and advanced models to optimise the operation of pumped-storage hydropower plants and reduce their investment and maintenance costs.- The Advanced Network Architectures Lab (CRAAX) at the Universitat Politècnica de Catalunya - BarcelonaTech (UPC) is participating in the ACCOMPLISH project, which is developing an innovative AI-based compliance and certification framework to simplify, integrate and automate compliance in operations, assets, solutions and organisational processes related to data and artificial intelligence.
- Un equip de recerca de la UPC, integrat pel CommSensLab-UPC i el Remote Sensing Lab (RSLAB) de la Universitat Politècnica de Catalunya - BarcelonaTech (UPC), juntament amb l’Institut d’Estudis Espacials de Catalunya (IEEC), ha participat en el projecte AI4EO, amb l’objectiu d’impulsar solucions i posar en pràctica eines d’intel·ligència artificial aplicades a dades d’observació de la Terra en diversos casos d’ús sobre el territori català.
- A research team from the Institut de Robòtica i Informàtica Industrial (IRI, CSIC-UPC), together with the Centre de Disseny d'Equips Industrials (CDEI) of the Universitat Politècnica de Catalunya - BarcelonaTech (UPC), are participating in the national CASANDRA project to develop a digital manufacturing solution that will make it possible to establish a bidirectional data flow for continuous digital integration throughout the supply chain across the product life cycle. This integration will be achieved through digital twins and data-based models that are continuously updated thanks to distributed monitoring and control tools.




