APROPOS aims at decreasing energy consumption in both distributed computing and communications for cloud-based cyber-physical systems. Through optimizing the design by introducing a new dimension, accuracy, the energy efficiency can even be improved by a factor of 10x-50x. Fifteen PhD students will be trained to tackle the challenges of future embedded and high-performance computing energy efficiency by using disruptive methodologies.

More electricity

Following the current trend, by 2040 computers will need more electricity than the world energy resources can generate. On the communications side, energy consumption in mobile broadband networks is comparable to datacentres. To make things worse, Internet-of-Things will soon connect up to 50 billion devices through wireless networks to the cloud.
APROPOS proposes adaptive Approximate Computing to optimize energy-accuracy trade-offs.

‘Acceptable’ accuracy

Luckily, in many parts of the global data acquisition, transfer, computation, and storage systems there exists the possibility to trade off accuracy to less power and less time consumed. As examples, numerous sensors are measuring noisy or inexact inputs; the algorithms processing the acquired signals can be stochastic; the applications using the data may be satisfied with an ‘acceptable’ accuracy instead of exact and absolutely correct results; the system may be resilient against occasional errors; and a coarse classification may be enough for a data mining system.

Training

World leading experts from European organizations will train the spearheads of the future generation to cope with the technologies, methodologies, and tools for successfully applying Approximate Computing to power and energy saving. The training, in this first ever ITN project addressing approximate computing, is to a large extent done by researching energy-accuracy trade-offs on circuit, architecture, software, and system-level solutions.

APROPOS is collaboration of fourteen partners and will receive 4M€ from the EU H2020 programme. The UvA will receive 265K€.