Automatic generation of user-defined test algorithm description file for memory BIST implementation

Memory built-in self-test (BIST) is a widely used technique to allow the self-test and self-checking of the embedded memories on chips after the fabrication process. It can be used by implementing a standard testing algorithm available in the EDA tool library or a user-defined algorithm (UDA). This paper presents the development of software that automatically generates a description file of a UDA to be deployed for memory BIST circuit implementation using Tessent memory BIST software. It comprises the test setup and also the microprogram coding for each instruction to be executed when performing tests on embedded memories. The proposed automation software was tested by using March SR as the input algorithm and the results obtained from the simulations show that the output test patterns generated by the implemented memory BIST match the expected patterns and passed all the tests, which validated the correct functionality of the UDA description file generation. The proposed automation software also fast generation the UDA description file, which was completed in less than 500 ms

Memory built-in self-repair and correction for improving yield: a review

Nanometer memories are highly prone to defects due to dense structure, necessitating memory built-in self-repair as a must-have feature to improve yield. Today’s system-on-chips contain memories occupying an area as high as 90% of the chip area. Shrinking technology uses stricter design rules for memories, making them more prone to manufacturing defects. Further, using 3D-stacked memories makes the system vulnerable to newer defects such as those coming from through-silicon-vias (TSV) and micro bumps. The increased memory size is also resulting in an increase in soft errors during system operation. Multiple memory repair techniques based on redundancy and correction codes have been presented to recover from such defects and prevent system failures. This paper reviews recently published memory repair methodologies, including various built-in self-repair (BISR) architectures, repair analysis algorithms, in-system repair, and soft repair handling using error correcting codes (ECC). It provides a classification of these techniques based on method and usage. Finally, it reviews evaluation methods used to determine the effectiveness of the repair algorithms. The paper aims to present a survey of these methodologies and prepare a platform for developing repair methods for upcoming-generation memories