Optimized Gate Diffusion Input Method-Based Reversible Magnitude Arithmetic Unit Using Non-dominated Sorting Genetic Algorithm II.

Gate diffusion input (GDI) method using a simple cell makes it possible to design low-power logic gates with reduced chip area and less complexity. In this work, a novel design of single-bit optimized reversible logic-based magnitude arithmetic unit (RMAU) circuit, using appropriate standard reversible gates with carbon nanotube (CNT) field-effect transistors (CNTFETs), based on modified-GDI (m-GDI) method for nanoscales is presented. In order to optimize the performance of the proposed circuit, and to achieve minimum power consumption and propagation delay, transistor sizes are adjusted using the non-dominated sorting genetic algorithm II (NSGA-II) in MATLAB tool. The simulation results show improvement in evaluating the figure of merits in worst-case delay and power consumption of the proposed optimized arithmetic unit, in comparison with a non-optimized RMAU circuit using a similar design method but counterpart structures. The effects of different process parameters (such as the diameter of CNTs) and voltage and temperature (PVT) variations are extensively evaluated by the Monte Carlo procedure in standard 32 nm technology utilizing the Synopsys HSPICE simulator. According to the outcomes obtained, the proposed optimized RMAU circuit is robust against PVT variations and noise-tolerable criterions, compared to those competitors with similar design in non-optimized conditions. The proposed optimized and non-optimized circuits were used in image processing as real environment assessments, and results depicted their excellent ability in being implemented in various large reversible-based applications, such as future generations of FPGA chips and CNTFET-based computers. [ABSTRACT FROM AUTHOR]