Remodelling correlation: A fault resilient technique of correlation sensitive stochastic designs

Abstract

Major sources of error in stochastic circuits are correlation errors, soft errors, and random fluctuation errors, which impact the circuit’s accuracy and reliability. The soft error has the effect of modifying the correlation status, which in turn modifies the probability of the output. This has serious implications for security and medical systems that require highly precise systems. To address this issue, we employ a fault-tolerant technique of correlation-sensitive stochastic logic circuits. To ensure reliable operation, we have developed a Remodelling Correlation ( ReCo ) framework for correlation-sensitive stochastic logic elements (SLEs). Using two intriguing case studies, we present two variants of ReCo model for combinational circuits with contradictory requirements. To achieve faster convergence to the desired Mean-Squared Error (MSE) value with less hardware area, the proposed method prioritizes the selection of logic elements and the placement of correction blocks. It is shown that the overall reliability of the circuit is unaffected by this method. To demonstrate the usefulness of the proposed framework, the contrast stretch operation on images of CEED2016, a standard contrast enhancement dataset, is investigated in a noisy setting. The average Multiscale structural similarity index (MS-SSIM) of the output images using the proposed method is observed as 0 . 91 ± 0 . 02 , which is significantly higher than the original images with error, i.e., 0 . 75 ± 0 . 12 .