Arithmetic Circuits in Unipolar Format for Stochastic Computing (SC)

Stochastic Computing (SC) is a computational technique that executes arithmetic operations on a random bitstream basis. Traditionally, stochastic arithmetic circuits are found according to probability equations, however not all arithmetic operations can directly be generated using this technique. This paper introduces a sequential processing technique to design SC arithmetic circuits in unipolar encoding format. The proposed technique processes each bit of data in the input bitstream by considering the previous information. The output bitstream can then easily be generated. A SC adder, a SC subtractor, a SC comparator, a SC absolute subtractor, a SC multiplier by integer, and a SC divider by integer are proposed. The proposed technique provides many advantages over the traditional methods such as ease of design, flexibility, reductions in limitations when generating arithmetic functions, and efficient circuits. Moreover, the value of the output signal can be read without the need to multiply the result. The impact of each parameter in the proposed SC arithmetic circuits is studied to assess the accuracy of the proposed SC circuit; then, a comparison between the proposed and other SC circuits is presented. The results in this paper show that the proposed designs are significantly better than other SC arithmetic circuits in terms of accuracy, correlation between input signals to the output data, and cross-correlation to input signals, area, delay, power dissipation, and power delay product (PDP). For example, in the proposed SC adder circuit, its accuracy is improved by 64.67% while its delay, power dissipation, area, and PDP are improved by 45.79%, 85.86%, 85.60%, and 92.33% respectively.