In-Stream Correlation-Based Division and Bit-Inserting Square Root in Stochastic Computing
In-Stream Correlation-Based Division and Bit-Inserting Square Root in Stochastic Computing
复制标题
随机计算中基于流内相关性的除法和位插入平方根
DOI：
10.1109/mdat.2021.3050716
复制
发表时间：
2021
影响因子：
2
通讯作者：
Miguel, Joshua San
中科院分区：
文献类型：
--
作者：
Wu, Di;Yin, Ruokai;Miguel, Joshua San
编者按：本文介绍了用于除法和平方根运算的改进的随机计算原语。两者都是非线性函数，不能简化为加法和乘法。作者利用的相关性，通常被认为是不可取的随机计算，其控制注入到计算导致收敛时间和面积要求之间的良好妥协。- 钱卫康，上海交通大学
Editor’s notes:This article presents improved stochastic computing primitives for division and square root operations. Both are nonlinear functions that cannot be reduced to additions and multiplications. The authors make use of the very correlations that are usually considered undesirable in stochastic computing; their controlled injection into computations leads to good compromises between convergence time and area requirements. —Weikang Qian, Shanghai Jiao Tong University
DOI：
10.1109/tcad.2018.2858338
发表时间：
2018
影响因子：
2.9
作者：
Vincent T. Lee;Armin Alaghi;Rajesh Pamula;V. Sathe;L. Ceze;M. Oskin
通讯作者：
M. Oskin