31 research outputs found

    Review of Display Technologies Focusing on Power Consumption

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    Producciรณn CientรญficaThis paper provides an overview of the main manufacturing technologies of displays, focusing on those with low and ultra-low levels of power consumption, which make them suitable for current societal needs. Considering the typified value obtained from the manufacturerโ€™s specifications, four technologiesโ€”Liquid Crystal Displays, electronic paper, Organic Light-Emitting Display and Electroluminescent Displaysโ€”were selected in a first iteration. For each of them, several features, including size and brightness, were assessed in order to ascertain possible proportional relationships with the rate of consumption. To normalize the comparison between different display types, relative units such as the surface power density and the display frontal intensity efficiency were proposed. Organic light-emitting display had the best results in terms of power density for small display sizes. For larger sizes, it performs less satisfactorily than Liquid Crystal Displays in terms of energy efficiency.Junta de Castilla y Leรณn (Programa de apoyo a proyectos de investigaciรณn-Ref. VA036U14)Junta de Castilla y Leรณn (programa de apoyo a proyectos de investigaciรณn - Ref. VA013A12-2)Ministerio de Economรญa, Industria y Competitividad (Grant DPI2014-56500-R

    ์œ ๊ธฐ๋ฐœ๊ด‘ ๋‹ค์ด์˜ค๋“œ ํ‘œ์‹œ์žฅ์น˜๋ฅผ ์žฅ์ฐฉํ•œ ์ด๋™ํ˜• ์‹œ์Šคํ…œ์˜ ์ „๋ ฅ ๊ณต๊ธ‰ ์ตœ์ ํ™”

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2012. 8. ์žฅ๋ž˜ํ˜.์˜ค๋Š˜๋‚  ์Šค๋งˆํŠธํฐ, ํƒœ๋ธ”๋ฆฟ PC ์™€ ๊ฐ™์€ ํœด๋Œ€์šฉ ์ „์ž๊ธฐ๊ธฐ๋Š” ๊ณ ์„ฑ๋Šฅ์˜ ์ค‘์•™์ฒ˜๋ฆฌ์žฅ์น˜ (CPU), ๋Œ€์šฉ๋Ÿ‰ ๋ฉ”๋ชจ๋ฆฌ, ๋Œ€ํ˜• ํ™”๋ฉด, ๊ณ ์†์˜ ๋ฌด์„  ์ธํ„ฐํŽ˜์ด์Šค ๋“ฑ์„ ํƒ‘์žฌํ•จ์—๋”ฐ๋ผ ์ „ ๋ ฅ ์†Œ๋ชจ๋Ÿ‰์ด ๊ธ‰์†ํžˆ ์ฆ๊ฐ€ํ•˜์—ฌ ๊ทธ ์ „๋ ฅ ์†Œ๋ชจ๋Š” ์ด๋ฏธ ์†Œํ˜•์˜ ๋žฉํƒ‘ ์ปดํ“จํ„ฐ ์ˆ˜์ค€์— ์ด๋ฅด๊ณ  ์žˆ๋‹ค. ์„ฑ๋Šฅ๊ณผ ์ „๋ ฅ ์†Œ๋ชจ๋Ÿ‰์˜ ์ธก๋ฉด์—์„œ ํœด๋Œ€์šฉ ์ „์ž๊ธฐ๊ธฐ์™€ ๋žฉํƒ‘ ์ปดํ“จํ„ฐ ์‚ฌ ์ด์˜ ๊ตฌ๋ถ„์ด ์ ์ฐจ ์‚ฌ๋ผ์ง€๊ณ  ์žˆ์Œ์—๋„ ๋ฐฐํ„ฐ๋ฆฌ ๋ฐ ์ „๋ ฅ ๋ณ€ํ™˜ ํšŒ๋กœ๋Š” ๊ธฐ์กด์˜ ์„ค๊ณ„ ์›์น™๋“ค๋งŒ์„ ๋”ฐ๋ผ ์„ค๊ณ„๋˜๊ณ  ์žˆ๋Š” ์‹ค์ •์ด๋‹ค. ์‚ผ์„ฑ์ „์ž์˜ ๊ฐค๋Ÿญ์‹œ ํƒญ ๋ฐ Apple ์‚ฌ์˜ iPad ๋“ฑ ์Šค๋งˆํŠธํฐ ๋ฐ ํƒœ๋ธ”๋ฆฟ PC์˜ ๊ฒฝ์šฐ 1-cell ์ง๋ ฌ ๋ฆฌํŠฌ ์ด์˜จ ์ „์ง€๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ๋ฐ˜ ๋ฉด, ๋žฉํƒ‘ ์ปดํ“จํ„ฐ์˜ ๊ฒฝ์šฐ๋Š” ์ œ์กฐ์‚ฌ์— ๋”ฐ๋ผ 3-cell ์—์„œ 5-cell ์ง๋ ฌ ๋“ฑ์œผ๋กœ ์„ค๊ณ„๋˜๊ณ  ์žˆ๋‹ค. ์ด๋Š” ๋ฐฐํ„ฐ๋ฆฌ ์ถœ๋ ฅ ์ „์••์„ ๋‹ค๋ฅด๊ฒŒ ํ•จ์œผ๋กœ์จ ์ „๋ ฅ ๋ณ€ํ™˜ ํšจ์œจ์— ์˜ํ–ฅ์„ ์ค€๋‹ค. ์ „๋ ฅ ๋ณ€ํ™˜ ํšŒ๋กœ์˜ ํšจ์œจ ๋ฐ ๋ฐฐํ„ฐ๋ฆฌ์˜ ์ˆ˜๋ช…์€ ์ž…์ถœ๋ ฅ ์ „์••/์ „๋ฅ˜๋ฅผ ๋น„๋กฏํ•œ ๋™์ž‘ ํ™˜๊ฒฝ์˜ ์˜ํ–ฅ์„ ๋ฐ›๋Š”๋‹ค. ํœด๋Œ€์šฉ ์ „์ž๊ธฐ๊ธฐ์— ์‚ฌ์šฉ๋˜๋Š” ๊ฐ์ข… ์ „์ž๋ถ€ํ’ˆ์€ ์ „๋ ฅ ์†Œ๋ชจ๋ฅผ ์ค„์ด๊ธฐ ์œ„ํ•œ ๋‹ค์–‘ํ•œ ๊ธฐ๋Šฅ๋“ค์„ ๊ตฌํ˜„ํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ์ค‘์•™์ฒ˜๋ฆฌ์žฅ์น˜์˜ ๋™์  ์ „์••/์ฃผํŒŒ ์ˆ˜ ์กฐ์ ˆ ๊ธฐ๋ฒ• ๋“ฑ ๊ณต๊ธ‰์ „์••์˜ ๋ณ€ํ™”๋ฅผ ์ˆ˜๋ฐ˜ํ•˜๋Š” ๊ธฐ๋ฒ• ์—ญ์‹œ ๋‹ค์–‘ํ•˜๊ฒŒ ์ ์šฉ๋˜๊ณ  ์žˆ๋‹ค. ์ด๋Š” ๊ฐ ์žฅ์น˜์˜ ๊ณต๊ธ‰ ์ „์•• ๋ฐ ์ „๋ฅ˜์˜ ๋ณ€ํ™”๋กœ ์ธํ•œ ์ „๋ ฅ ๋ณ€ํ™˜ ํšŒ๋กœ์˜ ํšจ์œจ์˜ ๋ณ€ํ™” ๋ฅผ ์ดˆ๋ž˜ํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ์ค‘์•™์ฒ˜๋ฆฌ์žฅ์น˜, ๋””์Šคํ”Œ๋ ˆ์ด ๋“ฑ ์ฃผ์š” ์ „๋ ฅ ์†Œ๋น„ ์žฅ์น˜์˜ ์ „๋ ฅ ์ ˆ๊ฐ ๊ธฐ๋ฒ•์„ ๊ฐœ๋ฐœํ•  ๋•Œ์—๋Š” ๊ฐœ๋ณ„ ์žฅ์น˜์˜ ์ „๋ ฅ ์†Œ๋น„๋ฅผ ์ค„์ด๋Š” ๊ฒƒ๊ณผ ๋™์‹œ์— ๊ฐœ๋ณ„ ์žฅ ์น˜์˜ ๋™์ž‘ ํ–‰ํƒœ์— ๋Œ€ํ•œ ์ •ํ™•ํ•œ ๋ถ„์„์— ๊ธฐ๋ฐ˜ํ•˜์—ฌ ๋ฐฐํ„ฐ๋ฆฌ, ์ „๋ ฅ ๋ณ€ํ™˜ํšŒ๋กœ์˜ ์„ค๊ณ„๊ฐ€ ํ•จ๊ป˜์ด๋ฃจ์–ด์ ธ์•ผ ํ•œ๋‹ค. ์„ ํ–‰ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ๋ฐฐํ„ฐ๋ฆฌ์˜ ํŠน์„ฑ์„ ๊ณ ๋ คํ•œ ๋ฐฐํ„ฐ๋ฆฌ ๊ตฌ์„ฑ์˜ ์ตœ์ ํ™” ๊ธฐ๋ฒ•์ด ์ œ์•ˆ๋˜์—ˆ๋‹ค [1]. ์ค‘์•™์ฒ˜๋ฆฌ์žฅ์น˜์˜ ๋™์  ์ „์••/์ฃผํŒŒ์ˆ˜ ์ œ์–ด ๊ธฐ๋ฒ•์— ์ด์–ด ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค์ด์˜ค๋“œ(OLED) ๊ธฐ๋ฐ˜ ๋””์Šคํ”Œ๋ ˆ์ด์˜ ๋™์  ๊ตฌ๋™ํšŒ๋กœ ๊ณต๊ธ‰ ์ „์•• ๊ธฐ๋ฒ•์ด ์ œ์•ˆ๋˜์—ˆ๋‹ค [2]. ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค ์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด๋Š” ์ „๋ ฅ ์†Œ๋ชจ ๋ฐ ์‹œ์•ผ๊ฐ ๋“ฑ ๊ธฐ์กด ์•ก์ • ํ‘œ์‹œ์žฅ์น˜์— ๋น„ํ•ด ์—ฌ๋Ÿฌ ์šฐ์ˆ˜ํ•œ ํŠน์„ฑ์œผ๋กœ ์ธํ•ด ์ฃผ๋ชฉ๋ฐ›๊ณ  ์žˆ๋Š” ์ฐจ์„ธ๋Œ€ ๋””์Šคํ”Œ๋ ˆ์ด ์žฅ์น˜์ด๋‹ค. ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค ์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด์˜ ์ ์€ ์ „๋ ฅ ์†Œ๋ชจ๋Ÿ‰์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ํ™”๋ฉด์˜ ๋Œ€ํ˜•ํ™” ๋ฐ ํ•ด์ƒ๋„์˜ ๊ณ ๋ฐ€๋„ํ™”์— ๋”ฐ๋ผ ์‹œ์Šคํ…œ ์ „๋ ฅ ์†Œ๋ชจ์—์„œ ์—ฌ์ „ํžˆ ํฐ ๋น„์ค‘์„ ์ฐจ์ง€ํ•˜๊ณ  ์žˆ๋‹ค. ์œ ๊ธฐ๋ฐœ ๊ด‘๋‹ค์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด์˜ ๋™์  ๊ตฌ๋™ํšŒ๋กœ ๊ณต๊ธ‰ ์ „์•• ๊ธฐ๋ฒ•(OLED DVS)๋Š” ์ƒ‰์ƒ์˜ ๋ณ€ํ™”์˜ ๊ธฐ์ดˆํ•œ ๊ธฐ์กด์˜ ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด ์ „๋ ฅ ์ ˆ๊ฐ ๊ธฐ๋ฒ•๊ณผ๋Š” ๋‹ฌ๋ฆฌ ์ตœ ์†Œํ•œ์˜ ์ด๋ฏธ์ง€ ์™œ๊ณก๋งŒ์„ ์ˆ˜๋ฐ˜ํ•˜์—ฌ ๋Œ€๋ถ€๋ถ„์˜ ์‚ฌ์ง„, ๋™์˜์ƒ ๋“ฑ์— ์ ์šฉ๊ฐ€๋Šฅํ•œ ์ „๋ ฅ ์ ˆ๊ฐ ๊ธฐ๋ฒ•์ด๋‹ค. ํ•ด๋‹น ๊ธฐ๋ฒ•์€ ๊ณต๊ธ‰ ์ „์••์˜ ๋ณ€ํ™”์‹œํ‚ฌ ํ•„์š”๊ฐ€ ์žˆ์œผ๋ฉฐ, ์ด๋ฅผ ์‹œ์Šคํ…œ์— ์˜ฌ๋ฐ”๋ฅด๊ฒŒ ํ†ตํ•ฉ์‹œํ‚ค๊ธฐ ์œ„ํ•ด์„œ๋Š” ์ „๋ ฅ ๋ณ€ํ™˜ ํšŒ๋กœ ๋ฐ ๋ฐฐํ„ฐ๋ฆฌ ๊ตฌ์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ๊ณ ๋ คํ•ด์•ผ ํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด์˜ ์ „๋ ฅ ์†Œ๋ชจ์™€ ํ•จ๊ป˜ ์ „์ฒด ์‹œ์Šค ํ…œ ํšจ์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ํ•จ๊ป˜ ๊ณ ๋ คํ•˜์—ฌ ์‹œ์Šคํ…œ์„ ์ตœ์ ํ™”ํ•œ๋‹ค. ๋ฐฐํ„ฐ๋ฆฌ ๊ตฌ์„ฑ ์—ญ ์‹œ ๊ธฐ์กด์˜ ์„ค๊ณ„ ํ‘œ์ค€ ๋Œ€์‹  ์ฒด๊ณ„์ ์ธ ์‹œ์Šคํ…œ ๋ถ„์„์— ๊ธฐ๋ฐ˜ํ•œ ์ตœ์ ํ™”๊ฐ€ ์‹œ๋„๋˜์—ˆ๋‹ค. ๊ณต๊ธ‰์ „์••์ด ์กฐ์ ˆ ๊ฐ€๋Šฅํ•œ ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด ํ•˜๋“œ์›จ์–ด ๋ฐ ์ œ์–ด๊ธฐ ์‹œ์Šค ํ…œ-์˜จ-์นฉ (System-on-a-chip, SoC) ๊ฐ€ ์ œ์ž‘๋˜์—ˆ๊ณ , ๊ทธ ๋™์ž‘ ํŠน์„ฑ์ด ๋ถ„์„๋˜์—ˆ๋‹ค. ๊ธฐ์กด ์Šค๋งˆํŠธํฐ ๋ฐ ํƒœ๋ธ”๋ฆฟ PC ๊ฐœ๋ฐœ์šฉ ํ”Œ๋žซํผ์˜ ์ „๋ ฅ ๋ณ€ํ™˜ ํšจ์œจ ๋ฐ ๋™์ž‘ ํŠน์„ฑ ์—ญ์‹œ ๋ถ„์„ ๋˜์—ˆ๋‹ค. ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด์˜ ๋™์  ๊ตฌ๋™ํšŒ๋กœ ๊ณต๊ธ‰ ์ „์•• ๊ธฐ๋ฒ•์˜ ๋™์ž‘ ํŠน์„ฑ ๋ฐ ์Šค๋งˆํŠธํฐ ํ”Œ๋žซํผ์˜ ๋™์ž‘ ํŠน์„ฑ, ๋ฐฐํ„ฐ๋ฆฌ ํŠน์„ฑ์— ๋Œ€ํ•œ ๋ถ„์„์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์‹œ์Šค ํ…œ ์ˆ˜์ค€์—์„œ์˜ ์ „๋ ฅ ๋ณ€ํ™˜ ํšจ์œจ์ด ์ตœ์ ํ™”๋˜์—ˆ๋‹ค.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 DCโ€“DC 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

    Quality-Based Backlight Optimization for Video Playback on Handheld Devices

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    For a typical handheld device, the backlight accounts for a significant percentage of the total energy consumption (e.g., around 30% for a Compaq iPAQ 3650). Substantial energy savings can be achieved by dynamically adapting backlight intensity levels on such low-power portable devices. In this paper, we analyze the characteristics of video streaming services and propose a cross-layer optimization scheme called quality adapted backlight scaling (QABS) to achieve backlight energy savings for video playback applications on handheld devices. Specifically, we present a fast algorithm to optimize backlight dimming while keeping the degradation in image quality to a minimum so that the overall service quality is close to a specified threshold. Additionally, we propose two effective techniques to prevent frequent backlight switching, which negatively affects user perception of video. Our initial experimental results indicate that the energy used for backlight is significantly reduced, while the desired quality is satisfied. The proposed algorithms can be realized in real time

    Producing green computing images to optimize power consumption in OLED-based displays

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    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 โ€œLand Effectโ€, 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

    Adaptive display power management for mobile games

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    Ministry of Education, Singapore under its Academic Research Funding Tier

    LAPSE: Low-Overhead Adaptive Power Saving and Contrast Enhancement for OLEDs

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    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

    Low-Overhead Adaptive Brightness Scaling for Energy Reduction in OLED Displays

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    Organic Light Emitting Diode (OLED) is rapidly emerging as the mainstream mobile display technology. This is posing new challenges on the design of energy-saving solutions for OLED displays, specifically intended for interactive devices such as smartphones, smartwatches and tablets. To this date, the standard solution is brightness scaling. However, the amount of the scaling is typically set statically (either by the user, through a setting knob, or by the system in response to predefined events such as low-battery status) and independently of the displayed image. In this work we describe a smart computing technique called Low-Overhead Adaptive Brightness Scaling (LABS), that overcomes these limitations. In LABS, the optimal content-dependent brightness scaling factor is determined automatically for each displayed image, on a frame-by-frame basis, with a low computational cost that allows real-time usage. The basic form of LABS achieves more than 35% power reduction on average, when applied to different image datasets, while maintaining the Mean Structural Similarity Index (MSSIM) between the original and transformed images above 97%

    Dynamic power management: from portable devices to high performance computing

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    Electronic applications are nowadays converging under the umbrella of the cloud computing vision. The future ecosystem of information and communication technology is going to integrate clouds of portable clients and embedded devices exchanging information, through the internet layer, with processing clusters of servers, data-centers and high performance computing systems. Even thus the whole society is waiting to embrace this revolution, there is a backside of the story. Portable devices require battery to work far from the power plugs and their storage capacity does not scale as the increasing power requirement does. At the other end processing clusters, such as data-centers and server farms, are build upon the integration of thousands multiprocessors. For each of them during the last decade the technology scaling has produced a dramatic increase in power density with significant spatial and temporal variability. This leads to power and temperature hot-spots, which may cause non-uniform ageing and accelerated chip failure. Nonetheless all the heat removed from the silicon translates in high cooling costs. Moreover trend in ICT carbon footprint shows that run-time power consumption of the all spectrum of devices accounts for a significant slice of entire world carbon emissions. This thesis work embrace the full ICT ecosystem and dynamic power consumption concerns by describing a set of new and promising system levels resource management techniques to reduce the power consumption and related issues for two corner cases: Mobile Devices and High Performance Computing

    FINE-GRAINED DYNAMIC VOLTAGE SCALING ON OLED DISPLAY

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    Organic Light Emitting Diode (OLED) has emerged as a new generation of display techniques for mobile devices. Emitting light with organic fluorescent materials OLED display panels are thinner, brighter, lighter, cheaper and more power efficient, compared to other display technologies such as Liquid Crystal Displays (LCD). In present mobile devices, due to the battery capacity limitation and increasing daily usage, the power efficiency significantly affect the general performance and user experience. However, display panel even built with OLEDs is still the biggest contributor to a mobile deviceโ€™s total power consumption. In this thesis, a fine-grained dynamic voltage scaling (FDVS) technique is proposed to reduce the OLED display power consumption. In bottom level, based on dynamic voltage scaling (DVS) power optimization, a DVS-friendly AMOLED driver design is proposed to enhance the color accuracy of the OLED pixels under scaled down supply voltage. Correspondingly, the OLED panel is partitioned into multiple display sections and each sectionโ€™s supply voltage is adaptively adjusted to implement fine-grained DVS with display content. When applied to display image, some optimization algorithm and methods are developed to select suitable scaled voltage and maintain display quality with Structural Similarity Index (SSIM), which is an image distortion evaluation criteria based on human vision system (HVS). Experimental results show that, the FDVS technique can achieve 28.44%~39.24% more power saving on images. Further analysis shows FDVS technology can also effectively reduce the color remapping cost when color compensation is required to improve the image quality of an OLED panel working at a scaled supplied voltage
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