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APROPOS - Approximate Computing for Power and Energy Optimisation

Durata:
48 mesi (2020 - 2024)
Responsabile scientifico:
Tipo di progetto:
Ricerca UE - H2020 - Excellent Science - Marie Curie
Ente finanziatore:
COMMISSIONE EUROPEA
Codice identificativo progetto:
Ruolo PoliTo:
Partner

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 cloud-based cyber-physical systems. We propose adaptive Approximate Computing to optimize energy-accuracy trade-offs. 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.

Persone coinvolte

Dipartimenti coinvolti

Partner

  • ALMA MATER STUDIORUM UNIVERSITA' DI BOLOGNA
  • Catena Holding BV
  • ECOLE CENTRALE DE LYON
  • IBM RESEARCH GMBH - ZURICH RESEARCH LABORATORY
  • KTH - KUNGLIGA TEKNISKA HOGSKOLAN
  • POLITECNICO DI MILANO
  • POLITECNICO DI TORINO
  • TAMPERE UNIVERSITY FOUNDATION SR - Coordinatore
  • TECHNISCHE UNIVERSITAET WIEN
  • TECHNISCHE UNIVERSITEIT DELFT (TUD)
  • THE QUEEN'S UNIVERSITY OF BELFAST
  • TURUN YLIOPISTO
  • UNIVERSITAT POLITECNICA DE VALENCIA
  • UNIVERSITY OF TURKU
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Parole chiave

Settori ERC

PE6_1 - Computer architecture, pervasive computing, ubiquitous computing
PE6_2 - Computer systems, parallel/distributed systems, sensor networks, embedded systems, cyber-physical systems
PE6_11 - Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)

Obiettivi di Sviluppo Sostenibile (Sustainable Development Goals)

Obiettivo 4. Fornire un’educazione di qualità, equa ed inclusiva, e opportunità di apprendimento per tutti|Obiettivo 7. Assicurare a tutti l’accesso a sistemi di energia economici, affidabili, sostenibili e moderni

Budget

Costo totale progetto: € 4.080.122,28
Contributo totale progetto: € 4.080.122,28
Costo totale PoliTo: € 261.499,68
Contributo PoliTo: € 261.499,68

Attività di comunicazione