Design of Experiments Implementation towards Optimization of Power Distribution Networks

Modern computer servers require cutting edge technologies to meet their expected high performance. Among several relevant disciplines, power delivery (PD) is a key player in this regard. Efficient and reliable statistical methods to reduce cost while keeping adequate server’s performance are highly demanded from the PD perspective. This paper addresses a feasible statistical methodology based on design of experiments (DoE) for evaluating platform’s power delivery ingredients. Our methodology explores voltage regulator’s intrinsic parameters, compensation networks, non-linear compensation parameters, and the amount of bulk capacitors. Our statistical approach aims at identifying those variables with the largest impact on computer server’s PD performance, as well as optimizing them at the system level while achieving cost reduction

Surrogate-based Analysis and Design Optimization of Power Delivery Networks

As microprocessor architectures continue to increase computing performance under low-energy consumption, the combination of signal integrity, electromagnetic interference, and power delivery is becoming crucial in the computer industry. In this context, power delivery engineers make use of complex and computationally expensive models that impose time-consuming industrial practices to reach an adequate power delivery design. In this paper, we propose a general surrogate-based methodology for fast and reliable analysis and design optimization of power delivery 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 4th generation server CPU motherboard. We next propose a black box PDN surrogate modeling methodology for efficient and reliable power delivery 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 with dual power rail remote sensing intended for communications and storage applications, by finding optimal sensing resistors and loading conditions; and a multiphase voltage regulator from a 6th generation Intel® server motherboard, by finding optimal compensation settings to reduce the number of bulk capacitors without losing CPU performance.ITESO, A.C

Power Delivery Network Impedance Profile and Voltage Droop Optimization

The design process of power delivery networks (PDN) in modern computer platforms is becoming more relevant and complex due to its relationship with high-frequency effects on signal integrity. When circuits start operating, the changing current flowing through the PDN produces fluctuations creating voltage noise. Unsuccessful noise control can compromise data integrity. A suitable PDN design approach is the use of decoupling capacitors to lower the impedance profile and mitigate current surges, ensuring a small variation in the power supply voltage under significant transient current loads. An optimization approach to determine the number of decoupling capacitors in a PDN is presented in this paper, aiming at decreasing the amount of decoupling capacitors without violating the PDN design specifications, looking at both the impedance profile in the frequency domain and the resulting voltage droop in the transient time-domain.ITESO, A.C

Selecting Surrogate-Based Modeling Techniques for Power Integrity Analysis

In recent years, extensive usage of simulated power integrity (PI) models to predict the behavior of power delivery networks (PDN) on a chip has become more relevant. Predicting adequate performance against power consumption can yield to either cheap or costly design solutions. Since PI simulations including high-frequency effects are becoming more and more computationally complex and expensive, it is critical to develop reliable and fast models to understand system’s behavior to accelerate decision making during design stages. Hence, metamodeling techniques can help to overcome this challenge. In this work, a comparative study between different surrogate modeling techniques as applied to PI analysis is described. We model and analyze a PDN that includes two different power domains and a combination of remote sense resistors for communication and storage CPU applications. We aim at developing reliable and fast coarse models to make trade off decisions while complying with voltage levels and power consumption requirements

Optimizing a buck voltage regulator and the number of decoupling capacitors for a PDN application

An optimization methodology to determine the best values of the compensation elements of a buck voltage regulator (VR) as well as the optimal number of decoupling capacitors in a power delivery network (PDN) application is proposed. A state average equivalent circuit model of the buck converter is employed. The proposed optimization methodology gradually finds the best compensation parameter values of a buck converter VR to meet some stability criteria in a PDN application. Additionally, the number of parallel decoupling capacitors in the PDN is minimized to simultaneously meet a frequency-domain impedance profile specification and a time-domain voltage droop requirement.ITESO, A.C

Optimizing Phase Settings of High-Frequency Voltage Regulators for Power Delivery Applications

Every new computer server introduced to the market aims at delivering the best tradeoff between performance and power consumption. This goal is crucial in the case of servers for cloud computing hardware infrastructure. In this context, power delivery (PD) experts are adopting higher frequency switching voltage regulators (VR) to reduce platform’s cost as well as total cost of ownership (TCO). Because of this fact, the real estate of components, such as voltage regulators and output inductors, is shrinking as VR frequency increases. As a consequence, achieving the best performance of the VR implies looking into phase shedding schemes, as well as EM coupled inductor design, among other techniques, to mitigate power losses. This paper focuses on the study of the best angle arrangement possible for high frequency VR applications, by exploring angle settings under light load scenarios, aiming to minimize VR’s power loss and output’s voltage ripple

Design Optimization of a Planar Spiral Inductor Using Space Mapping

This paper addresses the implementation of a computationally efficient optimization technique for designing structures simulated in 3D electromagnetic field solvers. A probe of concept is done by the EM-based optimization of a planar spiral inductor for high-power applications. The optimization technique employed is based on space mapping (SM) methods, more specifically on the Broyden-based input space mapping algorithm. Our optimization results confirm the efficiency of the proposed approach

Design Optimization of a Planar Spiral Inductor Using Space Mapping (poster)

This paper addresses the implementation of a computationally efficient optimization technique for designing structures simulated in 3D electromagnetic field solvers. A probe of concept is done by the EM-based optimization of a planar spiral inductor for high-power applications. The optimization technique employed is based on space mapping (SM) methods, more specifically on the Broyden-based input space mapping algorithm. Our optimization results confirm the efficiency of the proposed approach

Industry-Oriented Research Projects on Computer-Aided Design of High-Frequency Circuits and Systems at ITESO Mexico

The Mexican Federal Government, through its National Council of Science and Technology (CONACYT, for its initials in Spanish), recently started a new initiative for encouraging the creation of high-quality industry-oriented graduate programs. In line to this initiative, ITESO – the Jesuit University of Guadalajara, Mexico, opened in 2013 an industry-oriented doctoral program in engineering sciences. In this paper, we briefly describe the main research production of this doctoral program in the area of computer-aided design techniques for RF and microwave modeling, design, and optimization of circuits and systems in industrial settings. We summarize the main recent contributions involving surrogate-based modeling and optimization as applied to post-silicon validation of high-speed computer interfaces, signal-integrity testing, power integrity enhancement, and low-cost high-speed interconnect multi-physical characterization. Research contributions validated on realistic industrial platforms in collaboration with high-tech companies are emphasized