• Journal of Electrical Engineering and Technology
• /
• v.13 no.1
• /
• pp.181-191
• /
• 2018

Rapid development of information technology makes our environment become smarter and massive high performance computers are providing powerful computing for that. Graphics Processing Unit (GPU) as a typical high performance component is being widely used for both graphics and general-purpose applications. Although it can greatly improve computing power, it also delivers significant power consumption and need sufficient power supplies. To make high performance computing more sustainable, the important step is to measure it. Current power technologies for GPU have some drawbacks, such as they are not applicable for power estimation at the early stage. In this article, we present a novel power technology to correlate power consumption and the characteristics at the programmer perspective, and then to estimate power consumption of source program without prerunning. We conduct experiments on Nvidia's GT740 platform; the results show that our power model is more accurately than regression model and has an average error of 2.34% and the maximum error of 9.65%.

• Journal of Communications and Networks
• /
• v.18 no.4
• /
• pp.649-657
• /
• 2016

In this paper, we investigate energy efficiency (EE) of the traditional co-located and the distributed massive multiple-input multiple-output (MIMO) systems. First, we derive an approximate EE expression for both the idealistic and the realistic power consumption models. Then an optimal energy-efficient remote access unit (RAU) selection algorithm based on the distance between the mobile stations (MSs) and the RAUs are developed to maximize the EE for the downlink distributed massive MIMO systems under the realistic power consumption model. Numerical results show that the EE of the distributed massive MIMO systems is larger than the co-located massive MIMO systems under both the idealistic and realistic power consumption models, and the optimal EE can be obtained by the developed energy-efficient RAU selection algorithm.

• Proceedings of the IEEK Conference
• /
• 2000.11b
• /
• pp.329-332
• /
• 2000

This paper proposed resource allocation algorithm for the minimum power consumption of functional unit in high level synthesis process as like DSP which is circuit to give many functional unit. In this paper, the proposed method though high level simulation find switching activity in circuit each functional unit exchange for binary sequence length and value bit are logic one value. To used the switching activity find the allocation with minimal power consumption, the proposed method visits all control steps one by one and determines the allocation with minimal power consumption at each control step.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.5
• /
• pp.442-446
• /
• 2015

As electricity consumption is increasing rapidly these days, an urgent. need exists to minimize consumption through smart and intelligent ways in order to prevent a future energy crisis. For this purpose, development of an intelligent peak power management system should be required. As the number of appliances and consumer electrical devices increase, power consumption in unit business tends to grow. Generally, electricity consumption can be minimized using a peak power management system capable of. effectively controlling the load power by continuously monitoring the power. In this work, a peak power management system which consists of arduino microprocessor equipped with ethernet and Zigbee shield is presented. To verify the feasibility of the proposed scheme, laboratory-scale experiments are carried out.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.9B
• /
• pp.1322-1329
• /
• 2010

As body sensor network (BSN) research becomes mature, the need for managing power consumption of sensor nodes has become evident since most of the applications are designed for continuous monitoring. Real time Electrocardiograph (ECG) analysis on sensor nodes is proposed as an optimal choice for saving power consumption by reducing data transmission overhead. Smart sensor nodes with the ability to categorize lately detected ECG cycles communicate with base station only when ECG cycles are classified as abnormal. In this paper, ECG classification algorithms are described, which categorize detected ECG cycles as normal or abnormal, or even more specific cardiac diseases. Our Euclidean distance (ED) based classification method is validated to be most power efficient and very accurate in determining normal or abnormal ECG cycles. A close comparison of power efficiency and classification accuracy between our ED classification algorithm and generalized linear model (GLM) based classification algorithm is provided. Through experiments we show that, CPU cycle power consumption of ED based classification algorithm can be reduced by 31.21% and overall power consumption can be reduced by 13.63% at most when compared with GLM based method. The accuracy of detecting NSR, APC, PVC, SVT, VT, and VF using GLM based method range from 55% to 99% meanwhile, we show that the accuracy of detecting normal and abnormal ECG cycles using our ED based method is higher than 86%.

• Journal of Digital Contents Society
• /
• v.10 no.4
• /
• pp.633-637
• /
• 2009

In this paper, we present the reuse module library generating algorithm and register-transfer (RT) library generating algorithm considering the power consumption of reuse module for field-programmable gate array (FPGA) technology mapping in order to implement into the circuit for calculating power consumption. To realize the circuit of calculation of power consumption, the FPGA is selected. Considering lookup table (LUT) conditions of selected FPGA, technology mapping process is conducted to minimize the total power consumption. With these information, the circuit is realized using suitable given power consumption among allocated results of modules.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
• /
• v.10 no.4
• /
• pp.135-142
• /
• 2011

This paper proposes a performance evaluation method for power consumption of set-top box (STB) stand-by mode transition schemes. A stand-by mode transition scheme characterizes the timing of mode transition. The timing of mode transition affects the duration of stand-by mode operation, and the power consumptions of STB as well. Recently a fast stand-by mode transition scheme (FMT) has been proposed based on user input for selecting the device to be connected to TV. In this paper, we evaluate power consumption of FMT and a conventional mode transition scheme. For the computation of the duration of stand-by mode operation, the user input events are modeled as Poisson process. Simulation results based on the modeling reveals that the proposed scheme is more effective in power saving than the conventional scheme by up to 30%.

• ETRI Journal
• /
• v.34 no.5
• /
• pp.727-733
• /
• 2012

This paper demonstrates a new driving scheme that allows reducing the supply voltage of data drivers for low-power active matrix organic light-emitting diode (AMOLED) displays. The proposed technique drives down the data voltage range by 50%, which subsequently diminishes in the peak power consumption of data drivers at the full white pattern by 75%. Because the gate voltage of a driving thin film transistor covers the same range as a conventional driving scheme by means of a level-shifting scheme, the low-data supply scheme achieves the equivalent dynamic range of OLED currents. The average power consumption of data drivers is reduced by 60% over 24 test images, and power consumption is kept below 25%.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.6B
• /
• pp.641-647
• /
• 2009

This paper proposes an improved predictive dynamic power management (DPM) scheme and a task scheduling algorithm to reduce unnecessary power consumption in embedded systems. The proposed algorithm performs pre-scheduling to minimize unnecessary power consumption. The proposed predictive DPM utilizes a scheduling library provided by the system to reduce computation overhead. Experimental results show that the proposed algorithm can reduce power consumption by 22.3% on the average comparing with the LLF algorithm for DPM-enable system scheduling.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2011.05a
• /
• pp.382-385
• /
• 2011

The sensor network technology for core technology of ubiquitous computing is in the spotlight recently, the research on sensor network is proceeding actively which is composed many different sensor node. One of the important condition for design of sensor node is to extend for network life which is to minimize power-consumption under the limited resources of sensor network. This study suggest routing protocol that was used second level cluster structure to reduce power-consumption of sensor node. the first level use the previous routing protocol under the LEACH, second level decide to transmit or not by comparision of data value for Effective Usage, reduce the unnecessary power-consumption.