A Survey on Green Computing using GPU in Image Processing

Pooja Handa,Rajesh Sachdeva,Meenu Kalra

doi:10.24297/ijct.v14i10.1834

Pooja Handa, Rajesh Sachdeva + Show 1 more

Open Access

https://doi.org/10.24297/ijct.v14i10.1834

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Abstract

Green computing is the process of reducing the power consumed by a computer and thereby reducing carbon emissions. The total power consumed by the computer excluding the monitor at its fully computative load is equal to the sum of the power consumed by the GPU in its idle state and the CPU at its full state. Recently, there have been tremendous interests in the acceleration of general computing applications using a Graphics Processing Unit (GPU). Now the GPU provides the computing powers not only for fast processing of graphics applications, but also for general computationally complex data intensive applications. On the other hand, power and energy consumptions are also becoming important design criteria. Consequently, software designs have to consider the power/energy consumptions together with performance when they are developing software.The GPU therefore does the 100% of the CPU work in its idle state .Hence the power consumed by the GPU will be low. Also when the GPU is doing all the work the CPU will remain at a load less than its idle load. Hence the power consumed will be equal to the power consumed by the CPU at a load less than its idle load plus the power consumed by a GPU.Â Â

Highlights

Green computing refers to those practices adopted in the IT industry so as to reduce carbon emissions [1]
There is more research in the coding part than in hardware be it with making the webpage of websites black so as to reduce power consumption to making shorter codes,it all accounts for green computing [2,3,4]
This paper presents a performance based evaluation of the DCT image compression technique on both the CPU and graphics processing unit (GPU) using CUDA

Summary

Introduction

Green computing refers to those practices adopted in the IT industry so as to reduce carbon emissions [1]. The graphics processing unit (GPU) has become an essential part of today’s conventional computing systems. There has been a marked raise in the performance and capabilities of GPUs. Graphics Processing Units is powerful, programmable, and highly parallel computing, which are increasingly targeting for general-purpose computing applications.

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