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

Project description

Machine learning could speed up analogue and mixed-signal design

Mixed-signal integrated circuits have both analogue and digital circuits on a single semiconductor die. For analogue-centric designs, which integrate small to medium amounts of digital logic, physical designers often use analogue-on-top methodologies that rely on handmade flows. The electronic design automation industry is actively working on developing better design and verification methods ranging from integrated circuit synthesis to place and route, timing analysis, analogue design and simulation tools. The EU-funded AMBEATion project will use a holistic approach involving artificial intelligence techniques that should enhance the physical design automation of complex low-power integrated circuits. The project's activities will help increase designers' productivity in mixed-signal designs and reduce device production costs.

Objective

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 employer’s needs, iv) set the basis of a long lasting technical partnership between European research and design centers.

Fields of science (EuroSciVoc)

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

MSCA-RISE - Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE)

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Call for proposal

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(opens in new window) H2020-MSCA-RISE-2020

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Coordinator

POLITECNICO DI TORINO
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 124 200,00
Address
CORSO DUCA DEGLI ABRUZZI 24
10129 Torino
Italy

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Region
Nord-Ovest Piemonte Torino
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 124 200,00

Participants (7)

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