Reduced Precision Redundancy Systems by Approximation (RPA): Design and Analysis

This paper proposes new designs for Reduced Precision Redundancy (RPR) systems using Approximation (RPAs). Reduced redundancy is accomplished by utilizing approximate modules, hence requiring substantially different designs for the decision hardware for generating an output. The proposed schemes deal with a single erroneous data word generated by a module (in the presence of single and multiple bit errors) using three modules as inputs to the decision hardware of the RPA. Different from RPRs found in the technical literature, the proposed RPAs operate using only logic operations (so no involved as decision hardware). The probability of providing an exact data word at the output of the RPA under the above error conditions is analytically found; the provided simulation results show that the difference between simulated and analytical probabilities is at most 5%. Circuit based metrics (such as delay, power dissipation, and area) of the proposed designs are simulated and compared with RPR; the proposed designs outperform RPR in all metrics.