电源网络分析是深亚微米集成电路设计的关键因素之一.针对高性能芯片采用IBMC4封装和网状结构片上网络的特点,首先通过随机游走模型推导出电源网络的三个性质,接着基于这些性质给出了深亚微米电源网络的分析框架,最后提出了基于马尔可夫-蒙特卡洛采样的电源网络求解算法.仿真实验表明,与随机采样求解电源网络方程相比,马尔可夫-蒙特卡洛采样在不降低计算精度的前提下,运算速度提高了近两个数量级.
With continuously shrinking of ICs device feature sizes, power supply noise has induced pressing challenges for circuit design in deep sub-micron. A random-walk based framework is presented for power network analysis. Based on this framework, Markov Chain Monte Carlo (MCMC) sampling is proposed to solve the problem of power network analysis. Simulation results on power network analysis show that MCMC sampling improves the running speed by two orders of magnitudes than random sampling without accuracy degradation.