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ShanghaiTech University Knowledge Management System
Characterizing Stochastic Number Generators for Accurate Stochastic Computing | |
2023-08 | |
来源专著 | Design and Applications of Emerging Computer Systems |
出版地 | Springer, Cham |
出版者 | Weiqiang Liu, Jie Han, Fabrizio Lombardi |
ISBN | 978-3-031-42477-9 |
页码 | 331–349 |
摘要 | Since the advent of the post-Moore era, the challenges of increasing power have been raised. Stochastic computing, where stochastic numbers or binary bit streams are used to convey information, adopts encoding method that is different from the conventional multi-bit binary radix representation. This encoding method enables low arithmetic hardware cost, reduced energy consumption, and improved reliability. Despite the aforementioned advantages, the accuracy of a stochastic computing system is largely affected by the stochastic number generators (SNGs), which converts binary numbers into their stochastic representation. This paper reviews recent developments in SNGs and their implementations. The accuracy of the computation results produced by these SNGs is evaluated and compared. |
关键词 | Stochastic computing Quasi-random numbers Sobol sequences Stochastic number generator Low discrepancy sequences |
DOI | https://doi.org/10.1007/978-3-031-42478-6_13 |
URL | 查看原文 |
收录类别 | 其他 |
学科门类 | 电子科学与技术 |
语种 | 英语 |
文献类型 | 专著章节 |
条目标识符 | https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/517734 |
专题 | 信息科学与技术学院_硕士生 信息科学与技术学院_PI研究组_刘思廷组 |
作者单位 | 上海科技大学 |
第一作者单位 | 上海科技大学 |
推荐引用方式 GB/T 7714 | Gong YT,Shi H,Liu ST. Characterizing Stochastic Number Generators for Accurate Stochastic Computing. Springer, Cham:Weiqiang Liu, Jie Han, Fabrizio Lombardi,2023:331–349. |
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