New statistical post processing approach for precise fault and defect localization in TRI database acquired on complex VLSI

Samuel Chef (1) , Philippe Perdu (2) , Guillaume Bascoul , Sabir Jacquir (1) , Kevin Sanchez (2) , Stéphane Binczak (1)

1 Le2i - Laboratoire Electronique, Informatique et Image [UMR6306]
2 CNES - Centre National d'Études Spatiales [Toulouse]

Timing issue, missing or extra state transitions or unusual consumption can be detected and localized by Time Resolved Imaging (TRI) database analysis. Although, long test pattern can challenge this process. The number of photons to process rapidly increases and the acquisition time to have a good signal over noise ratio (SNR) can be prohibitive. As a result, the tracking of the defect emission signature inside a huge database can be quite complicated. In this paper, a method based on data mining techniques is suggested to help the TRI end user to have a good idea about where to start a deeper analysis of the integrated circuit, even with such complex databases.

Mots clés: Clustering; Dynamic Photon Emission; Failure Analysis; VLSI; Time Resolved Imaging

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]; Micro et nanotechnologies/Microélectronique

Samuel Chef, Philippe Perdu, Guillaume Bascoul, Sabir Jacquir, Kevin Sanchez, et al.. New statistical post processing approach for precise fault and defect localization in TRI database acquired on complex VLSI. 20th IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA 2013), Jul 2013, Suzhou, China. pp.140-145. ⟨hal-00860841⟩