基于SSA-RF的功耗预测  

Power consumption prediction based on SSA-RF

作　　者：谢东东 张立军[1] 严雨灵 柴永剑 马利军 XIE Dongdong;ZHANG Lijun;YAN Yuling;CHAI Yongjian;MA Lijun(Soochow University,Suzhou 215000,Jiangsu,China)

机构地区：[1]苏州大学,江苏苏州215000

出　　处：《微电子学与计算机》2023年第6期109-116,共8页Microelectronics & Computer

基　　金：国家自然科学基金(61272105)。

摘　　要：随机森林具有训练速度快、不容易过拟合、易于实现等优点成功应用于各种领域.针对在芯片设计后仿阶段需要对不同存储存储单元大小、电压、温度等情况进行功耗测试,并且测试一次的时间很长的问题,提出了一种基于麻雀搜索算法(SSA)与随机森林(RF)相结合的功耗预测方法.首先,对14 nmSRAM后仿的单元库进行表征,找出合适的特征变量,得到特征数据后构建训练测试集;然后对特征变量进行特征重要性分析,按照特征重要性排序;最后使用随机森林模型进行回归预测,并引入了麻雀搜索算法以寻找出均方根误差最小时的模型参数.与线性回归模型、支持向量回归模型等相比,SSA-RF收敛精度高并且训练速度快,SSA-RF模型的R2值为0.97左右.此外,在数据量较少的情况下其R2的值也能达到0.95左右,构建了一个较好的预测模型,为减少功耗测试时间提供了一种可行的方案,可以为设计人员留下更多的时间去优化电路.Random forest has been successfully applied in various fields due to its advantages of fast training speed,difficult over fitting and easy realization.In order to solve the problem that the power consumption test of different memory unit sizes,voltages and temperatures is needed in the post simulation stage of chip design,and the test time is very long,a power prediction method based on the combination of Sparrow Search Algorithm(SSA)and Random Forest(RF)is proposed.Firstly,the unit library after 14 nm SRAM is characterized to find out the appropriate feature variables and obtain the feature data to build the training test set.Secondly,the characteristic variables are analyzed by the characteristic importance,and sorted according to the characteristic importance.Finally,the random forest model is used for regression prediction,and the sparrow search algorithm is introduced to find the model parameters with the smallest root mean square error.Compared with linear regression model,support vector regression model and other models,SSA-RF has higher convergence accuracy,faster training speed.The R2 value of SSA-RF model is about 0.97.In addition,in the case of less data,the R2 value can also reach about 0.95.A better prediction model is constructed,which provides a feasible scheme for reducing the power consumption test time,and can leave more time for designers to optimize the circuit.

关 键 词：功耗 麻雀搜索算法 随机森林 

分 类 号：TN407[电子电信—微电子学与固体电子学]