Abstract
The Approximate Computing for Power and Energy Optimisation ETN will train 15 ESRs to tackle the challenges of future embedded and high-performance computing energy efficiency by using disruptive methodologies. 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 datacenters. To make things worse, Internet-of-Things will soon connect up to 50 billion devices through wireless networks to the cloud. APROPOS aims at decreasing energy consumption in both distributed computing and communications for cloudbased cyber-physical systems. We propose adaptive Approximate Computing to optimize energy-accuracy tradeoffs. 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. By introducing a new dimension, accuracy, to the design optimization, the energy efficiency can even be improved by a factor of 10x-50x. We 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 addressing approximate computing, is to a large extent done by researching energy-accuracy trade-offs on circuit, architecture, software, and system-level solutions, bringing together world leading experts from European organizations to train the ESR fellows.
Project details
Unibo Team Leader: Luca Benini
Unibo involved Department/s:
Dipartimento di Ingegneria dell'Energia Elettrica e dell'Informazione "Guglielmo Marconi"
Coordinator:
Tampereen Korkeakoulusaatio Sr(Finland)
Other Participants:
KUNGL. TEKNISKA HOGSKOLAN - Royal Institute of Technology
(Sweden)
Turun Yliopisto - University Of Turku
(Finland)
ALMA MATER STUDIORUM - Università di Bologna
(Italy)
The Queen'S University Of Belfast
(United Kingdom)
Technische Universität Wien
(Austria)
Ecole Centrale De Lyon
(France)
Universiteit Van Amsterdam
(Netherlands)
Ibm Research Gmbh
(Switzerland)
Politecnico di TORINO
(Italy)
Technische Universiteit Delft - Delft University Of Technology
(Netherlands)
Universitat Politècnica de València
(Spain)
Wirepas Oy
(Finland)
Politecnico di MILANO
(Italy)
Total Eu Contribution: Euro (EUR) 4.095.308,16
Project Duration in months: 48
Start Date:
01/11/2020
End Date:
31/10/2024
This project contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 956090