As microprocessor architectures continue to increase computing performance under low-energy consumption, the combination of signal integrity, electromagnetic interference, and power delivery (PD) is becoming crucial in the computer industry. In that context, PD engineers make use of complex and computationally expensive models that impose time-consuming industrial practices to reach an adequate PD design. In this article, we propose a general surrogate-based methodology for fast and reliable analysis and design optimization of PD networks (PDN). We first formulate a generic surrogate model methodology exploiting passive lumped models optimized by parameter extraction to fit PDN impedance profiles. This PDN modeling formulation is illustrated with industrial laboratory measurements of a fourth generation server CPU motherboard. We next propose a black box PDN surrogate modeling methodology for efficient and reliable PD design optimization. To build our black box PDN surrogate, we compare four metamodeling techniques: support vector machines, polynomial surrogate modeling, generalized regression neural networks, and Kriging. The resultant best metamodel is then used to enable fast and accurate optimization of the PDN performance. Two examples validate our surrogate-based optimization approach: a voltage regulator (VR) with dual power rail remote sensing intended for communications and storage applications, by finding optimal sensing resistors and loading conditions; and a multiphase VR from a fifth-generation Intel server motherboard, by finding optimal compensation settings to reduce the number of bulk capacitors without losing CPU performance.

中文翻译：

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基于代理的供电网络分析和设计优化

随着微处理器架构在低能耗下不断提高计算性能，信号完整性、电磁干扰和功率传输 (PD) 的组合在计算机行业变得至关重要。在这种情况下，PD 工程师使用复杂且计算成本高的模型，这些模型强加了耗时的工业实践来实现适当的 PD 设计。在本文中，我们提出了一种通用的基于代理的方法，用于对 PD 网络 (PDN) 进行快速可靠的分析和设计优化。我们首先制定通用代理模型方法，利用通过参数提取优化的无源集总模型来拟合 PDN 阻抗曲线。此 PDN 建模公式通过对第四代服务器 CPU 主板的工业实验室测量进行说明。我们接下来提出了一种用于高效可靠的 PD 设计优化的黑盒 PDN 代理建模方法。为了构建我们的黑盒 PDN 代理，我们比较了四种元建模技术：支持向量机、多项式代理建模、广义回归神经网络和克里金法。然后使用得到的最佳元模型来快速准确地优化 PDN 性能。两个示例验证了我们基于代理的优化方法：通过寻找最佳传感电阻器和负载条件，具有双电源轨遥感的电压调节器 (VR)，用于通信和存储应用；以及来自第五代英特尔服务器主板的多相 VR，通过寻找最佳补偿设置来减少大容量电容器的数量，而不会降低 CPU 性能。