公开(公告)号：US09483602B2

公开(公告)日：2016-11-01

申请号：US13881866

申请日：2011-10-27

申请人： Trent Lorne McConaghy ,  Joel Cooper ,  Jeffrey Dyck ,  Kyle Fisher

发明人： Trent Lorne McConaghy ,  Joel Cooper ,  Jeffrey Dyck ,  Kyle Fisher

IPC分类号： G06F17/50 ,  G06G7/62

CPC分类号： G06F17/5081 ,  G06F17/5009 ,  G06F17/5022 ,  G06F17/5036 ,  G06F2217/10

摘要： A method and system to estimate failure rates in designs. N Monte Carlo samples are drawn from the random distribution that describes process variation in the design. A subset of these samples is selected, and that subset of Ninit samples are simulated (with a circuit simulator) to measure a performance value for each sample. A model is constructed, using the values of the Ninit process points as training inputs, and the corresponding Ninit performance values as training outputs. The candidate Monte Carlo samples are from the N Monte Carlo samples that have not yet been simulated. Each candidate is simulated on the model to get predicted performance values, and the samples are ordered in ascending (or descending) order of the predicted performance values. Simulation of candidates samples is then begun, in that order. The sampling and simulation will stops once there is sufficient confidence that all failures are found.

摘要翻译： 一种估计设计失败率的方法和系统。 N蒙特卡洛样本是从设计中描述过程变化的随机分布中得出的。 选择这些样本的子集，并且模拟Ninit样本的子集（使用电路模拟器）来测量每个样本的性能值。 使用Ninit过程点的值作为训练输入，并将相应的Ninit性能值作为训练输出构建一个模型。 候选蒙特卡洛样本来自尚未模拟的N蒙特卡罗样本。 在模型上模拟每个候选人以获得预测的性能值，并且以预测的性能值的升序（或降序）顺序排列样本。 然后按照顺序开始模拟候选样本。 一旦有足够的信心发现所有故障，采样和仿真将停止。

公开(公告)号：US20130226544A1

公开(公告)日：2013-08-29

申请号：US13881866

申请日：2011-10-27

申请人： Trent Lorne Mcconaghy ,  Joel Cooper ,  Jeffrey Dyvk ,  Kyle Fisher

发明人： Trent Lorne Mcconaghy ,  Joel Cooper ,  Jeffrey Dyvk ,  Kyle Fisher

IPC分类号： G06F17/50

CPC分类号： G06F17/5081 ,  G06F17/5009 ,  G06F17/5022 ,  G06F17/5036 ,  G06F2217/10

摘要： A method and system to estimate failure rates in designs. N Monte Carlo samples are drawn from the random distribution that describes process variation in the design. A subset of these samples is selected, and that subset of Ninit samples are simulated (with a circuit simulator) to measure a performance value for each sample. A model is constructed, using the values of the Ninit process points as training inputs, and the corresponding Ninit performance values as training outputs. The candidate Monte Carlo samples are from the N Monte Carlo samples that have not yet been simulated. Each candidate is simulated on the model to get predicted performance values, and the samples are ordered in ascending (or descending) order of the predicted performance values. Simulation of candidates samples is then begun, in that order. The sampling and simulation will stops once there is sufficient confidence that all failures are found.

摘要翻译： 一种估计设计失败率的方法和系统。 N蒙特卡洛样本是从设计中描述过程变化的随机分布中得出的。 选择这些样本的子集，并且模拟Ninit样本的子集（使用电路模拟器）来测量每个样本的性能值。 使用Ninit过程点的值作为训练输入，并将相应的Ninit性能值作为训练输出构建一个模型。 候选蒙特卡洛样本来自尚未模拟的N蒙特卡罗样本。 在模型上模拟每个候选人以获得预测的性能值，并且以预测的性能值的升序（或降序）顺序排列样本。 然后按照顺序开始模拟候选样本。 一旦有足够的信心发现所有故障，采样和仿真将停止。