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By Alberto Bosio, Luigi Dilillo, Patrick Girard, Serge Pravossoudovitch, Arnaud Virazel

Advanced attempt equipment for SRAMs: powerful strategies for Dynamic Fault Detection in Nanoscaled Technologies


Alberto Bosio

Luigi Dilillo

Patrick Girard

Serge Pravossoudovitch

Arnaud Virazel

Modern electronics is determined by nanoscaled applied sciences that current new demanding situations when it comes to trying out and prognosis. stories are quite liable to defects when you consider that they take advantage of the know-how limits to get the top density. This e-book is a useful advisor to the checking out and prognosis of the most recent iteration of SRAM, probably the most commonplace kind of stories. Classical equipment for checking out reminiscence are designed to deal with the so-called "static faults", yet those try out strategies usually are not enough for faults which are rising within the most recent Very Deep Sub-Micron (VDSM) applied sciences. those new faults, known as "dynamic faults", should not lined via classical algorithms and require the committed attempt and prognosis ideas awarded during this book.

  • First ebook to offer entire, cutting-edge assurance of dynamic fault trying out for SRAM memories;
  • Presents content material utilizing a "bottom-up" technique, from the research of motives of malfunctions as much as the iteration of shrewdpermanent try recommendations;
  • Includes case stories protecting all reminiscence elements (core-cells, deal with decoders, write drivers, experience amplifiers, etc.);
  • Proposes an exhaustive research of resistive-open defects in every one reminiscence part and the ensuing dynamic fault modeling.

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Extra resources for Advanced Test Methods for SRAMs: Effective Solutions for Dynamic Fault Detection in Nanoscaled Technologies

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4 Fault model extraction: simulation results with any parameters Technology Df1 130 nm 90 nm 65 nm 45 nm TF Df2 DRDF, RDF, dDRF TF DRDF, RDF, dDRF, dRDF TF, dRDF DRDF, dDRDF TF RDF, DRDF Df3 Df4 Df5 Df6 DRDF, RDF, dDRF DRDF, RDF, dDRF, dRDF DRDF, dDRDF RDF, DRDF, dRDF dRDF, DRF, dDRF dRDF, DRF, DDRF dRDF RDF, DRDF IRF, TF TF IRF, TF TF TF, dRDF TF, dRDF TF TF In the majority of cases, each defect involves the same fault models in all technologies. Moreover, a visible trend of increased occurrence of dynamic faults in more scaled technologies is evident with the exception of the 45 nm technology.

In these elements, the read operations, useful for the observation phase, also contribute to the sensitization phase. Both ⇑ and ⇓ addressing orders are operated allowing a good sensitization for all the core-cells. The modification, which makes March C- able to detect dRDFs, consists in the use of the particular address sequence word line after word line. 4), this modification does not change the capability of March C- to detect the former targeted faults. The efficiency of the modified March C- can be evaluated considering a given SRAM architecture (Dilillo et al.

The fault F is injected into the memory and the March test is applied. The values of the read operations of the simulated March tests are used to monitor the memory behavior in the presence of F. By this way, the fault coverage achieved by the simulated March test is computed for the injected fault F. This procedure is applied for the entire fault list. 3) where F is the number of faults in the fault list and MTL is the length of the March test. The fault number is strictly related to the size of the considered memory.

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