2n RRR: Improved Stochastic Number Duplicator Based on Bit Re-Arrangement

In the fields of machine learning and image processing, cost-less circuits with low energy are required instead of extreme precision, and stochastic computing (SC), a type of approximate computing, is attracting attention. In SC, stochastic numbers (SNs), bit streams with values of the appearance rates of 1`s, are used. SC enables calculations with simple circuits. To make the calculation results correct, duplication of an SN (gener-ating an SN with the same value) is required when using the SN with the same value. The conventional SN duplicator composed of a flip-flop (FF) has a problem that the output SN only depends on the input SN. Therefore, if the FF-based duplicator is used in a circuit with re-convergence paths, the output SN becomes erroneous. This paper proposes an SN duplicator, 2
ⁿ
RRR, that can output more independent output by its improved flexibility of bit re-arrangement. With this duplicator, the errors of the hyperbolic tangent function are reduced by up to 50% compared to the duplicator that we proposed previously. Also, up to more than 99.9% of the circuit area is reduced compared to the implementation of binary computing.