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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
ISBN978-3-031-42477-9
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
DOIhttps://doi.org/10.1007/978-3-031-42478-6_13
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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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