蒙特卡罗方法
加速
静态随机存取存储器
计算机科学
采样(信号处理)
重要性抽样
罕见事件
拒收取样
采用蒙地卡罗积分法
算法
并行计算
混合蒙特卡罗
统计
马尔科夫蒙特卡洛
数学
计算机硬件
计算机视觉
滤波器(信号处理)
作者
Rouwaida Kanj,R. Joshi,Sani R. Nassif
标识
DOI:10.1145/1146909.1146930
摘要
In this paper, we propose a novel methodology for statistical SRAM design and analysis. It relies on an efficient form of importance sampling, mixture importance sampling. The method is comprehensive, computationally efficient and the results are in excellent agreement with those obtained via standard Monte Carlo techniques. All this comes at significant gains in speed and accuracy, with speedup of more than 100X compared to regular Monte Carlo. To the best of our knowledge, this is the first time such a methodology is applied to the analysis of SRAM designs.
科研通智能强力驱动
Strongly Powered by AbleSci AI