Design of Radix-8 Based Approximate Booth Squarer for Error Tolerant Computing - Shetkar, Lakshmikant; Hegde, Ganapathi (2023 International Conference on Next Generation Electronics (NEleX), 2023)
To explore the benefits of approximate computing, this project proposes an approximate partial product generator for squarer (APPGS). Using APPGS, three designs of approximate radix-8 Booth squarer's (ABS1, ABS2, and ABS3) are proposed. APPGS produces approximate partial products in number of least significant columns of the partial product matrix. ABS2 and ABS3 utilize approximate adders and compressors with a novel input signal rearrangement method for the accumulation of approximate partial products. Moreover, the ABS3 features an error recovery module at k number of most significant columns of the approximate partial products. The proposed squarer's with different values of rand k are simulated and synthesized using 45-nm CMOS technology. The results indicate that the proposed squarer's achieve optimized performance for both hardware and accuracy metrics. The results indicate that the proposed radix-8 squarer's achieve optimized performance for both hardware and accuracy metrics as compared existing radix-4 squarer. After synthesis of the proposed design that helps to reducing area and power of the overall design.