摘要
随机计算(Stochastic Computing,SC)是一种以概率编码数值的新型技术,可以有效减小电路功耗和面积,但其所固有的随机特性会导致计算精度损失,从而限制了其应用范围.为提高随机计算的准确性,提出了基于误差补偿原理的高精度随机计算加法运算单元,设计了一种计算随机序列最大值的SC-MAX单元.仿真结果显示:与同类设计相比,两种计算单元的计算精度明显提高,其中同等SC序列长度下加法单元的相对误差降低了80%以上,SC-MAX计算单元的相对误差减小了90%,且LUT与FF开销减小了10%以上.将两种计算单元运用于神经网络,在MNIST及CIFAR10数据集上的推理结果显示:精度损失跟浮点数相比分别可低至0.04%和0.86%.
Stochastic Computing(SC)is a new technology that encodes numerical value by probability,which can effectively reduce the power consumption and area of the circuit.However,the loss of calculation accuracy caused by its inherent random characteristics limits its application.In order to improve the accuracy of Stochastic Computing,a high-precision Stochastic Computing addition unit based on error compensation principle is proposed,and a SC-MAX element is designed to calculate the maximum value of SC sequence.The simulation results show that,compared with the similar design,the calculation accuracy of the two calculation units is significantly improved.The relative error of the addition unit is reduced by more than 80%under the same SC length,and the relative error of the SC-MAX calculation unit is reduced by 90%compared with the similar design,and the LUT and FF overhead is significantly reduced by more than 10%.The two kinds of calculation units are applied to neural network.The reasoning results on MNIST and CIFAR10 data sets show that the precision loss is less than 0.04%and 0.86%respectively comparedto float point results.
作者
周游
李杰
贺光辉
ZHOU You;LI Jie;HE Guanghui(Department of Micro Nano Electronics,Shanghai Jiao Tong University,Shanghai 200240,China;Shanghai Aerospace Measurement and Control CommunicationInstitute,Shanghai 200092,China)
出处
《微电子学与计算机》
2021年第7期1-6,共6页
Microelectronics & Computer
基金
国家重点研发计划项目(2020YFB2205500)
上海航天联合基金(USCAST2019-28)
国家自然科学基金项目(61674103,62074097)。
