CCG Crucible Computing Group Home

Exploiting Uniform Spatial Distribution to Design Efficient Random Number Source for Stochastic Computing

Kuncai Zhong, Zexi Li, Haoran Jin, Weikang Qian
Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design (2022)

DOI: 10.1145/3508352.3549396

Abstract

Stochastic computing (SC) generally suffers from long latency. One solution is to apply proper random number sources (RNSs). Nevertheless, current RNS designs either have high hardware cost or low accuracy. To address the issue, motivated by that the uniform spatial distribution generally leads to a high accuracy for an SC circuit, we propose a basic architecture to generate the uniform spatial distribution and a further detailed implementation of it. For the implementation, we further propose a method to optimize its hardware cost and a method to optimize its accuracy. The method for hardware cost optimization can optimize the hardware cost without affecting the accuracy. The experimental results show that our proposed implementation can achieve both low hardware cost and high accuracy. Compared to the state-of-the-art stochastic number generator design, the proposed design can reduce 88% area with close accuracy.

Cite this paper

@inproceedings{zhong2022exploiting,
  title = {Exploiting Uniform Spatial Distribution to Design Efficient Random Number Source for Stochastic Computing},
  author = {Kuncai Zhong and Zexi Li and Haoran Jin and Weikang Qian},
  year = {2022},
  booktitle = {Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design},
  doi = {10.1145/3508352.3549396},
  url = {https://crucible.eecs.umich.edu/papers/exploiting-uniform-spatial-distribution-to-design-efficient-random-number-15}
}

← All publications