DocumentCode :
759854
Title :
Weak Cell Detection in Deep-Submicron SRAMs: A Programmable Detection Technique
Author :
Pavlov, Andrei ; Sachdev, Manoj ; De Gyvez, Jose Pineda
Author_Institution :
Intel Corp., Hillsboro, OR
Volume :
41
Issue :
10
fYear :
2006
Firstpage :
2334
Lastpage :
2343
Abstract :
Embedded SRAM bit count is constantly growing limiting yield in systems-on-chip (SoCs). As technology scales into deep sub-100-nm feature sizes, the increased defect density and process spreads make stability of embedded SRAMs a major concern. This paper introduces a digitally programmable detection technique, which enables detection of SRAM cells with compromised stability [with data retention faults (DRFs) being a subset]. The technique utilizes a set of cells to modify the bitline voltage, which is applied to a cell under test (CUT). The bitline voltage is digitally programmable and can be varied in wide range, modifying the pass/fail threshold of the technique. Programmability of the detection threshold allows tracking process variations and maintaining the optimal tradeoff between test quality and test yield. The measurement results of a test chip presented in the paper demonstrate the effectiveness of the proposed technique
Keywords :
SRAM chips; circuit stability; integrated circuit testing; compromised stability; data retention faults; defect density; design for testability; detection threshold; embedded SRAM; memory fault diagnosis; memory testing; process spreads; programmable bitline; programmable detection; systems-on-chip; test quality; test yield; weak cell detection; Circuit faults; Circuit noise; Fault detection; Fault diagnosis; Random access memory; Semiconductor device measurement; Stability; Testing; Threshold voltage; Working environment noise; Design for testability; SRAM cell stability; memory fault diagnosis; memory testing; weak write test mode;
fLanguage :
English
Journal_Title :
Solid-State Circuits, IEEE Journal of
Publisher :
ieee
ISSN :
0018-9200
Type :
jour
DOI :
10.1109/JSSC.2006.881554
Filename :
1703688
Link To Document :
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