105 research outputs found
Producing green computing images to optimize power consumption in OLED-based displays
Energy consumption in Organic Light Emitting
Diode (OLED) depends on the displayed contents. The power
consumed by an OLED-based display is directly proportional to
the luminance of the image pixels. In this paper, a novel idea
is proposed to generate energy-efficient images, which consume
less power when shown on an OLED-based display. The Blue
color component of an image pixel is the most power-hungry
i.e. it consumes more power as compared to the Red and Green
color components. The main idea is to reduce the intensity of
the blue color to the best possible level so that the overall power
consumption is reduced while maintaining the perceptual quality
of an image. The idea is inspired by the famous βLand Effectβ,
which demonstrates that it is possible to generate a full-color
image by using only two color components instead of three.
experiments are performed on the Kodak image database. The
results show that the proposed method is able to reduce the power
consumption by 18% on average and the modified images do not
lose the perceptual quality. Social media platform, where users
scroll over many images, is an ideal application for the proposed
method since it will greatly reduce the power consumption in
mobile phones during surfing social networking applications
LAPSE: Low-Overhead Adaptive Power Saving and Contrast Enhancement for OLEDs
Organic Light Emitting Diode (OLED) display panels are becoming increasingly popular especially in mobile devices; one of the key characteristics of these panels is that their power consumption strongly depends on the displayed image. In this paper we propose LAPSE, a new methodology to concurrently reduce the energy consumed by an OLED display and enhance the contrast of the displayed image, that relies on image-specific pixel-by-pixel transformations. Unlike previous approaches, LAPSE focuses specifically on reducing the overheads required to implement the transformation at runtime. To this end, we propose a transformation that can be executed in real time, either in software, with low time overhead, or in a hardware accelerator with a small area and low energy budget. Despite the significant reduction in complexity, we obtain comparable results to those achieved with more complex approaches in terms of power saving and image quality. Moreover, our method allows to easily explore the full quality-versus-power tradeoff by acting on a few basic parameters; thus, it enables the runtime selection among multiple display quality settings, according to the status of the system
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μμ€μμμ μ λ ₯ λ³ν ν¨μ¨μ΄ μ΅μ νλμλ€.Modern mobile devices such as smartphone or tablet PC are typically equipped a high-performance CPU, memory, wireless interface, and display. As a result, their power consumption is as high as a small-size laptop computer. The boundary between the mobile devices and laptop computer is becoming unclear from the perspective of the performance and power. However, their battery and related power conversion architecture are only designed according to the legacy design so far. Smartphone and tablet PCs from major vendors such as iPad from Apple or Galaxy-tab from Samsung uses 1-cell Li-ion battery. The laptop PC typically has 3-cell Li-ion battery. The output voltage of the battery affect system-level power conversion efficiency.
Furthermore, traditional power conversion architecture in the mobile computing system is designed only considering the fixed condition where the system-level low-power techniques such as DVFS are becoming mandatory. Such a low-power techniques applied to the major components result in not only load demand fluctuation but also supply voltage changing. It has an effect on the battery lifetime as well as the system-level power delivery efficiency. The efficiency is affected by the operating condition including input voltage, output voltage, and output current. We should consider the operating condition of the major power consumer such as a display to enhance the system-level power delivery efficiency. Therefore, we need to design the system not only from the perspective of the power consumption but also energy storage design. The optimization of battery setup considering battery characteristics was presented in [1].
Beside the DVFS of microprocessor, a power saving technique based on the supply voltage scaling of the OLED driver circuit was recently introduced [2]. An organic light emitting diode (OLED) is a promising display device which has a lot of advantages compared with conventional LCD, but it still consumes significant amount of power consumption due to the size and resolution increasing. The OLED dynamic voltage scaling (OLED DVS) technique is the first OLED display power saving technique that induces only minimal color change to accommodate display of natural images where the existing OLED low-power techniques are based on the color change. The OLED DVS incurs supply voltage change. Therefore we need to consider the system-level power delivery efficiency and battery setup to properly integrate the DVS-enabled OLED display to the system.
In this dissertation, we not only optimize the power consumption of the OLED display but also consider its effect on the whole system power efficiency. We perform the optimization of the battery setup by a systematic method instead of the legacy design rule. At first, we develop an algorithm for the OLED DVS for the still images and a histogram-based online method for the image sequence with a hardware board and a SoC. We characterize the behavior of the OLED DVS. Next, we analyze the characteristics of the smartphone and tablet-PC platforms by using the development platforms. We profile the power consumption of each components in the smartphone and power conversion efficiency of the boost converter which is used in the tablet-PC for the display devices. We optimize not only the power consuming components or the conversion system but also the energy storage system based on the battery model and system-level power delivery efficiency analysis.1 Introduction
1.1 Supply Voltage Scaling for OLED Display
1.2 Power Conversion Efficiency in MobileSystems
1.3 Research Motivation
2 Related Work
2.1 Low-Power Techniques for Display Devices
2.1.1 Light Source Control-Based Approaches
2.1.2 User Behavior-Based Approaches
2.1.3 Low-Power Techniques for Controller and Framebuffer
2.1.4 Pre-ChargingforOLED
2.1.5 ColorRemapping
2.2 Battery discharging efficiency aware low-power techniques
2.2.1 Parallel Connection
2.2.2 Constant-Current Regulator-Based Architecture
2.3 System-level power analysis techniques
3 Preliminary 38
3.1 Organic Light Emitting Diode (OLED) Display
3.1.1 OLED Cell Architecture
3.1.2 OLED Panel Architecture
3.1.3 OLED Driver Circuits
3.2 Effect of VDD scaling on driver circuits
3.2.1 VDD scaling for AM drivers
3.2.2 VDD scaling for PWM drivers
4 Supply Voltage Scaling and Image Compensation of OLED displays
4.1 Image quality and power models of OLED panels
4.2 OLED display characterization
4.3 VDD scaling and image compensation
5 OLED DVS implementation
5.1 Hardware prototype implementation
5.2 OLED DVS System-on-Chip implementation
5.3 Optimization of OLED DVS SoC
5.4 VDD transition overhead
6 Power conversion efficiency and delivery architecture in mobile Systems
6.1 Power conversion efficiency model of switching-Mode DCβDC converters
6.2 Power conversion efficiency model of linear regulator power loss model
6.3 Rate Capacity Effect of Li-ion Batteries
7 Power conversion efficiency-aware battery setup optimization with DVS- enabled OLED display
7.1 System-level power efficiency model
7.2 Power conversion efficiency analysis of smartphone platform
7.3 Power conversion efficiency for OLED power supply
7.4 Li-ion battery model
7.4.1 Battery model parameter extraction
7.5 Battery setup optimization
8 Experiments
8.1 Simulation result for OLED display with AM driver
8.2 Measurement result for OLED display with PWM driver
8.3 Design space exploration of battery setup with OLED displays
9 Conclusion
10 Future WorkDocto
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