Comparative Analysis of Open and Short Defects in embedded SRAM using Parasitic Extraction Method for Deep Submicron Technology.

Abstract

The technology advances from the micron level to the Nanometer level. This striking change in the technology with so many factors might influence the embedded device design and its performance. In the fast-growing technology, it is very difficult to find suitable algorithms to test embedded SRAM. It is noticed that while going to deep sub-nano technologies, the existing test methods may not fully satisfy the test results due to the increased number of faults and defects. Scale-down technologies have an impact on the parasitic effects, creating an additional source of faulty behavior, and making the existing test techniques less effective in detecting them. In this paper we propose a new method, taking the parasitic effect into the consideration, which gives the fault information along with its location. In the proposed method we have considered node-to-node open and short defects for different technologies (45nm, 32nm, and 7nm). It is observed that the proposed test method gives 100% fault coverage which is independent of technology variation.