MinSC: An Exact Synthesis-Based Method for Minimal-Area Stochastic Circuits under Relaxed Error Bound

Stochastic computing (SC) operates on stochastic bit streams, which can realize complex arithmetic functions with simple circuits. A previous work shows that by introducing a little approximation error for the target function, the cost of SC circuits can be dramatically reduced. However, the previous heuristic method only explores a limited subset of the solution space, so the optimality of the results cannot be guaranteed. In this paper, we propose MinSC, an exact synthesis-based method for minimal-area stochastic circuits under relaxed error bound. First, a novel search method is proposed to find the best approximation polynomial for a target function. Then, considering gates with different fanin numbers and areas, an exact SC synthesis method using satisfiability modulo theories is designed to obtain an area-optimal SC circuit realizing the best approximation polynomial. The experimental results show that compared with the state-of-the-art method, given an error ratio 0.05, MinSC on average reduces the gate number, area, delay, and area-delay-product of the SC circuits by 60.24%, 47.24%, 7.10%, 57.07%, respectively.