‘Doorbraken op komst voor energiezuinige dataopslag’
‘Doorbraken op komst voor energiezuinige dataopslag’

Brain-inspired computing

To make data storage and data processing energy efficient and faster

Neuromorphic (brain-inspired) hardware can perform scientific computations faster and more energy-efficiently than conventional computing systems. Potentially, it can even perform calculations that are not yet possible with current computer systems. This is evident from the first results of the project "Neuromorphic computational and data science: toward disruptively green computing" by IBM, SURF and multiple research institutes within Radboud University.

The limits of conventional computer systems are becoming increasingly apparent. Current computer systems consume enormous amounts of energy, about seven per cent of global energy production, and is expected to increase exponential over the next decade.

Within computational science, the demand for new energy-efficient hardware is growing; hardware that should lead to a faster, more economical and scalable technology for scientific calculations. In the project' Neuromorphic computational and data Science: towards disruptively green computing', IBM, SURF and Radboud University investigate how neuromorphic hardware can meet this need.