Donghwa Shin

Accurate modeling and calculation of delay and energy overheads of dynamic voltage scaling in modern high-performance microprocessors

Dynamic voltage and frequency scaling (DVS) has been studied for well over a decade, and even commercial systems widely support DVS nowadays. Nevertheless, existing DVS transition overhead models do not accurately reflect modern DVS architectures including modern DC-DC converters, PLL (Phase Lock Loop), and voltage and frequency change policies. Incorrect DVS overhead models prevent one from achieving the maximum energy gain, by misleading the DVS control policies. This paper introduces an accurate DVS overhead model, in terms of both energy consumption and time penalty, through detailed observation of modern DVS setups and voltage and frequency change guidelines from vendors. We introduce new major contributors to the DVS overhead including the performance underdrive loss of the DVS-enabled microprocessor, additional inductor IR loss, and so on, as well as consideration of power efficiency from discontinuous-mode DC-DC conversion. Our DVS overhead model enhances the DVS overhead model accuracy from 86% to 238% for Intel Core2 Duo E6850 and LTC3733.

Dynamic voltage scaling of OLED displays

Unlike liquid crystal display (LCD) panels that require high-intensity backlight, organic LED (OLED) display panels naturally consume low power and provide high image quality thanks to their self-illuminating characteristic. In spite of this fact, the OLED display panel is still the dominant power consumer in battery-operated devices. As a result, there have been many attempts to reduce the OLED power consumption. Since power consumption of any pixel of the OLED display depends on the color that it displays, previous power saving methods change the pixel color subject to a tolerance level on the color distortion specified by the users. In practice, the OLED power saving techniques cannot be used on common user applications such as photo viewers and movie players. This paper introduces the first OLED power saving technique that does not result in a significant degradation in the color and luminance values of the displayed image. The proposed technique is based on dynamic (driving) voltage scaling (DVS) of the OLED panel. Although the proposed DVS technique may degrade luminance of the panel, the panel luminance can be restored with appropriate image compensation. Consequently, power is saved on the OLED display panel with only minor changes in the color and luminance of the image. This technique is similar to dynamic backlight scaling of LCDs, but is based on the unique characteristics of the OLED drivers. The proposed method saves wasted power in the driver transistor and the internal resistance with an amplitude modulation driver, and in the internal resistance with a pulse width modulation driver, respectively. Experimental results show that the proposed OLED DVS with image compensation technique saves up to 52.5% of the OLED power while keeping the same human-perceived image quality for the Lena image.

Battery-supercapacitor hybrid system for high-rate pulsed load applications

Modern batteries (e.g., Li-ion batteries) provide high discharge efficiency, but the rate capacity effect in these batteries drastically decreases the discharge efficiency as the load current increases. Electric double layer capacitors, or simply supercapacitors, have extremely low internal resistance, and a battery-supercapacitor hybrid may mitigate the rate capacity effect for high pulsed discharging current. However, a hybrid architecture comprising a simple parallel connection does not perform well when the supercapacitor capacity is small, which is a typical situation because of the low energy density and high cost of supercapacitors. This paper presents a new battery-supercapacitor hybrid system that employs a constant-current charger. The constant-current charger isolates the battery from supercapacitor to improve the end-to-end efficiency for energy from the battery to the load while accounting for the rate capacity effect of Li-ion batteries and the conversion efficiencies of the converters.

Accurate Modeling of the Delay and Energy Overhead of Dynamic Voltage and Frequency Scaling in Modern Microprocessors

Dynamic voltage and frequency scaling (DVFS) has been studied for well over a decade. Nevertheless, existing DVFS transition overhead models suffer from significant inaccuracies; for example, by incorrectly accounting for the effect of DC-DC converters, frequency synthesizers, voltage, and frequency change policies on energy losses incurred during mode transitions. Incorrect and/or inaccurate DVFS transition overhead models prevent one from determining the precise break-even time and thus forfeit some of the energy saving that is ideally achievable. This paper introduces accurate DVFS transition overhead models for both energy consumption and delay. In particular, we redefine the DVFS transition overhead including the underclocking-related losses in a DVFS-enabled microprocessor, additional inductor IR losses, and power losses due to discontinuous-mode DC-DC conversion. We report the transition overheads for a desktop, a mobile and a low-power representative processor. We also present DVFS transition overhead macromodel for use by high-level DVFS schedulers.

State of health aware charge management in hybrid electrical energy storage systems

This paper is the first to present an efficient charge management algorithm focusing on extending the cycle life of battery elements in hybrid electrical energy storage (HEES) systems while simultaneously improving the overall cycle efficiency. In particular, it proposes to apply a crossover filter to the power source and load profiles. The goal of this filtering technique is to allow the battery banks to stably (i.e., with low variation) receive energy from the power source and/or provide energy to the load device, while leaving the spiky (i.e., with high variation) power supply or demand to be dealt with by the supercapacitor banks. To maximize the HEES system cycle efficiency, a mathematical problem is formulated and solved to determine the optimal charging/discharging current profiles and charge transfer interconnect voltage, taking into account the power loss of the EES elements and power converters. To minimize the state of health (SoH) degradation of the battery array in the HEES system, we make use of two facts: the SoH of battery is better maintained if (i) the SoC swing is smaller, and (ii) the same SoC swing occurs at lower average SoC. Now then using the supercapacitor bank to deal with the high-frequency component of the power supply or demand, we can reduce the SoC swing for the battery array and lower the SoC of the array. A secondary helpful effect is that, for fixed and given amount of energy delivered to the load device, an improvement in the overall charge cycle efficiency of the HEES system translates into a further reduction in both the average SoC and the SoC swing of the battery array. The proposed charge management algorithm for a Li-ion battery - supercapacitor bank HEES system is simulated and compared to a homogeneous EES system comprised of Li-ion batteries only. Experimental results show significant performance enhancements for the HEES system, an increase of up to 21.9% and 4.82x in terms of the cycle efficiency and cycle life, respectively.

Energy-Optimal Dynamic Thermal Management: Computation and Cooling Power Co-Optimization

Conventional dynamic thermal management (DTM) assumes that the thermal resistance of a heat-sink is a given constant determined at design time. However, the thermal resistance of a common forced-convection heat sink is inversely proportional to the flow rate of the air or coolant at the expense of the cooling power consumption. The die temperature of the silicon devices strongly affects its leakage power consumption and reliability, and it can be changed by adjusting the thermal resistance of the cooling devices. Different from conventional DTM which aims to avoid the thermal emergency, our proposed DTM regards the thermal resistance of a forced-convection heat sink as a control variable, and minimize the total power consumption both for computation and cooling. We control the cooling power consumption together with the microprocessor clock frequency and supply voltage, and track the energy-optimal die temperature. Consequently, we reduce a significant amount of the temperature-dependent leakage power consumption of the microprocessor while spending a bit higher cooling power than conventional DTM, and eventually consume less total power. Experimental results show the proposed DTM saves up to 8.2% of the total energy compared with a baseline DTM approach. Our proposed DTM also enhances the Failures in Time (FIT) up to 80% in terms of the electromigration lifetime reliability.

Energy-optimal dynamic thermal management for green computing

Existing thermal management systems for microprocessors assume that the thermal resistance of the heat-sink is constant and that the objective of the cooling system is simply to avoid thermal emergencies. But in fact the thermal resistance of the usual forced-convection heat-sink is inversely proportional to the fan speed, and a more rational objective is to minimize the total power consumption of both processor and cooling system. Our new method of dynamic thermal management uses both the fan speed and the voltage/frequency of the microprocessor as control variables. Experiments show that tracking the energy-optimal steady-state temperature can saves up to 17.6% of the overall energy, when compared with a conventional approach that merely avoids overheating.

Near-optimal, dynamic module reconfiguration in a photovoltaic system to combat partial shading effects

Partial shading is a serious obstacle to effective utilization of photovoltaic (PV) systems since it can result in significant output power degradation for the system. A PV system is organized as a series connection of PV modules, each module comprising of a number of series-parallel connected cells. This paper presents modified PV cell structures with integrated switches, imbalanced cell connection topologies for PV modules, and a dynamic programming algorithm to produce near-optimal reconfigurations of each PV module with the goal of maximizing the system output power level under any partial shading patterns. Through simulations, we have demonstrated up to a factor of 2.3X improvement in the output power level of a PV system comprised of 3 PV modules with 60 PV cells per module.

Charge replacement in hybrid electrical energy storage systems

Hybrid electrical energy storage (HEES) systems are composed of multiple banks of heterogeneous electrical energy storage (EES) elements with distinctive properties. Charge replacement in a HEES system (i.e., dynamic assignment of load demands to EES banks) is one of the key operations in the system. This paper formally describes the global charge replacement (GCR) optimization problem and provides an algorithm to find the near-optimal GCR control policy. The optimization problem is formulated as a mixed-integer nonlinear programming problem, where the objective function is the charge replacement efficiency. The constraints account for the energy conservation law, efficiency of the charger/converter, the rate capacity effect, and self-discharge rates plus internal resistances of the EES element arrays. The near-optimal solution to this problem is obtained while considering the state of charges (SoCs) of the EES element arrays, characteristics of the load devices, and estimates of energy contributions by the EES element arrays. Experimental results demonstrate significant improvements in the charge replacement efficiency in an example HEES system comprised of banks of battery and supercapacitor elements with a high-power pulsed military radio transceiver as the load device.

An automated framework for generating variable-accuracy battery models from datasheet information

Models based on an electrical circuit equivalent have become the most popular choice for modeling the behavior of batteries, thanks to their ease of co-simulation with other parts of a digital system. Such circuit models are actually model templates: the specific values of their electrical elements must be derived by the analysis of the specific battery devices to be modeled. This process requires either to measure the battery characteristics or to derive them from the datasheet. In the latter case, however, very often not all information are available and the model fitting becomes then unfeasible. In this paper we present a methodology for deriving, in a semi-automatic way, circuit equivalent battery models solely from data available in a battery datasheet. In order to account for the different amount of information available, we introduce the concept of “level” of a model, so that models with different accuracy can be derived depending on the available data. The methodology requires only minimal intervention by the designer and it automatically generates MATLAB models once the required data for the corresponding model level are transcribed from the datasheet. Simulation results show that our methodology allows to accurately reconstruct the information reported in the datasheet as well as to derive missing ones.