Fast Deployment of Alternate Analog Test Using Bayesian Model Fusion
| Autor: | John Liaperdos, Haralampos-G. Stratigopoulos, Louay Abdallah, Yiorgos Tsiatouhas, Angela Arapoyanni, Xin Li |
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| Přispěvatelé: | Torella, Lucie, Department of Computer Engineering and Informatics [Patras], University of Patras [Patras], Techniques de l'Informatique et de la Microélectronique pour l'Architecture des systèmes intégrés (TIMA), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), Department of Informatics & Telecommunications, University of Athens, Techniques of Informatics and Microelectronics for integrated systems Architecture (TIMA), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA) |
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
PACS 8542
[SPI.NANO] Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics 020208 electrical & electronic engineering 0202 electrical engineering electronic engineering information engineering 02 engineering and technology [SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics 020202 computer hardware & architecture |
| Zdroj: | Design, Automation and Test in Europe Conference (DATE'15) Design, Automation and Test in Europe Conference (DATE'15), Mar 2015, Grenoble, France |
| Popis: | International audience; n this paper, we address the problem of limited training sets for learning the regression functions in alternate analog test. Typically, a large volume of real data needs to be collected from different wafers and lots over a long period of time to be able to train the regression functions with accuracy across the whole design space and apply alternate test with high confidence. To avoid this delay and achieve a fast deployment of alternate test, we propose to use the Bayesian model fusion technique that leverages prior knowledge from simulation data and fuses this information with data from few real circuits to draw accurate regression functions across the whole design space. The technique is demonstrated for an alternate test designed for RF low noise amplifiers. |
| Databáze: | OpenAIRE |
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