A Low-Cost FSM-based Bit-Stream Generator for Low-Discrepancy Stochastic Computing

2021 
Low-discrepancy (LD) bit-streams have been proposed to improve the accuracy and computation speed of stochastic computing (SC) circuits. These bit-streams are conventionally generated by using a quasi-random number generator such as a Sobol sequence generator and a comparator. The high hardware cost of such number generators makes the current comparator-based generators expensive in terms of area and power cost. The hardware cost issue further aggravates when increasing the number of inputs and the precision of data. A finite state machine (FSM)-based LD bit-stream generator was proposed recently to mitigate this hardware cost. The proposed generator, however, can only generate a specific LD pattern and hence, cannot be used where multiple independent LD bit-streams are needed. In this work, we propose a low-cost FSM-based LD bit-stream generator that supports generation of any number of independent LD bit-streams. The proposed generator reduces the hardware area and the area-delay product up to 80 % compared to those of the state-of-the-art comparator-based LD bit-stream generator while generating accurate bit-streams. We develop a parallel design of the proposed generator and show that the 8 × parallel implementation reduces the hardware cost on average more than 82 percent compared to the cost of the state-of-the-art parallel LD generator. Taking advantage of the provided area saving we improve the fault tolerance of the bit-stream generation unit, a vulnerable component in SC systems, by orders of magnitude. We show the effectiveness of using the proposed generator in SC-based design of convolution function as the case study.
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