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AMBEATion - Analog/Mixed Signal Back End Design Automation based on Machine Learning and Artificial Intelligence Techniques

Durata:
48 mesi (2025)
Responsabile scientifico:
Tipo di progetto:
Ricerca UE - H2020 - Excellent Science - Marie Curie
Ente finanziatore:
COMMISSIONE EUROPEA
Codice identificativo progetto:
Ruolo PoliTo:
Coordinatore

Abstract

In the field of the Electronic Integrated circuit design, the analog-mixed-signal (AMS) physical design of all analog blocks and of whole integrated circuits (IC) based on the Analog-on-Top approach still uses a handmade flow. The Electronic Design Automation (EDA) industry has been working since several years in the application of techniques to make better design and verification tools ranging from synthesis to place & route, timing analysis, analog design and circuit simulations. The AMBEATion consortium will utilize a holistic approach which applies these enhanced tools to categories of designs (i.e. Smart Systems) and drives them through scriptware and methodologies which will further enhance the productivity of designers in the design automation of these complex low power devices. Essential strategy of the ambitious multidisciplinary program is the Transfer of Knowledge between the partners and the training of a focused team of researchers on the algorithm developments and their application to the industrial state of the art AMS Back End design flow. The main outcomes of this AMBEATion project will be: i) highly increase designers productivity in the area of mixed signal designs (primarily AMS Backend) addressing the needs of industrial users, ii) possibly reduce the silicon products costs as a consequence increase the European industry competitiveness, iii) provide the academies with new advanced training topics aligned with high tech employers needs, iv) set the basis of a long lasting technical partnership between European research and design centers.

Strutture coinvolte

Partner

  • CESKE VYSOKE UCENI TECHNICKE V PRAZE
  • POLITECNICO DI TORINO - Coordinatore
  • SNPS PORTUGAL UNIPESSOAL LDA
  • STMICROELECTRONICS DESIGN AND APPLICATION SRO
  • STMICROELECTRONICS SRL
  • Synopsys Armenia CJSC
  • SYNOPSYS NETHERLANDS BV
  • UNIVERSITA DEGLI STUDI DI CATANIA
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Parole chiave

Settori ERC

PE7_3 - Simulation engineering and modelling
PE6_7 - Artificial intelligence, intelligent systems, multi agent systems
PE7_2 - Electrical engineering: power components and/or systems
PE6_11 - Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)

Budget

Costo totale progetto: € 257.600,00
Contributo totale progetto: € 257.600,00
Costo totale PoliTo: € 124.200,00
Contributo PoliTo: € 124.200,00

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