Design For Test Technique for Leakage Power Reduction in Nanoscale Static Random Access Memory

Abstract

Problem statement: As technology scales down, the integration density of transistors increases and most of the power is dissipated as leakage. Leakage power reduction is achieved in Static Random Access Memory (SRAM) cells by increasing the source voltage (source biasing) of the SRAM array. Another promising issue in nanoscaled devices is the process parameter variations. Due to these variations, higher source voltage causes the data stored in the cells of the SRAM array to flip (weak cell) in the standby mode resulting in hold failure. The weak cells identified are replaced using redundant columns. Maximum source voltage that can be applied to reduce the leakage power without any failure depends on the number of redundant columns available to repair the weak cells. Approach: This study proposes a novel Design For Test (DFT) technique to reduce the number of March tests, thus reducing the test time using a source bias (V_SB) predictor. In the proposed method, V_SB predictor predicts the initial source bias voltage to be applied to the SRAM array. The proposed DFT verified by designing an 8×16 SRAM array in 90 nm technology. March algorithm was used to identify the weak cells and predict the maximum source voltage from '0' mV. This process was run large number of March tests consuming more test time. Results and discussion: The predicted V_SB helps to make a fast convergence of maximum V_SB to be applied, which will improve the speed performance of the adaptive source bias and saves the test time by 60 %.