Stochastic computing (SC) presents high error tolerance and low hardware cost, and has great potential in applications such as neural networks and image processing. However, the bitstream generator, which converts a binary number to bitstreams, occupies a large area and energy consumption, thus weakening the superiority of SC. In this paper, we propose a novel technique for generating bitstreams in parallel, which needs only one clock for conversion and significantly reduces the hardware cost. Synthesis results demonstrate that the proposed parallel bitstream generator improves 2.5x area and 712x energy consumption.
@article{arxiv.1904.09554,
title = {A Parallel Bitstream Generator for Stochastic Computing},
author = {Yawen Zhang and Runsheng Wang and Xinyue Zhang and Zherui Zhang and Jiahao Song and Zuodong Zhang and Yuan Wang and Ru Huang},
journal= {arXiv preprint arXiv:1904.09554},
year = {2019}
}