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Reseach Article

Green Computing using Graphical Processing Units

by Y.navneeth Krishnan, Vipin Dwivedi, Chandan N Bhagwat
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 44 - Number 19
Year of Publication: 2012
Authors: Y.navneeth Krishnan, Vipin Dwivedi, Chandan N Bhagwat
10.5120/6368-8641

Y.navneeth Krishnan, Vipin Dwivedi, Chandan N Bhagwat . Green Computing using Graphical Processing Units. International Journal of Computer Applications. 44, 19 ( April 2012), 1-3. DOI=10.5120/6368-8641

@article{ 10.5120/6368-8641,
author = { Y.navneeth Krishnan, Vipin Dwivedi, Chandan N Bhagwat },
title = { Green Computing using Graphical Processing Units },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 44 },
number = { 19 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-3 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume44/number19/6368-8641/ },
doi = { 10.5120/6368-8641 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:35:55.967805+05:30
%A Y.navneeth Krishnan
%A Vipin Dwivedi
%A Chandan N Bhagwat
%T Green Computing using Graphical Processing Units
%J International Journal of Computer Applications
%@ 0975-8887
%V 44
%N 19
%P 1-3
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
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 . In our paper we have tried using the high processing speed of the GPU's to do the computational intensive parts while the sequential parts like storing data is made by the CPU. The GPU has 30-50 times more processing speed than the CPU . 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.

References
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  2. K. Fatahalian, J. Sugerman,,& P. Hanraham, Understanding the efficiency of GPU Algorithm for Matrix-Matrix Multiplication.
  3. NIVIDIA Corp. CUDA Compute Unified Device Architecture. Programming Guide, Version 2. 0, 2008
  4. NVIDIA Corp . GPU programming guide
  5. V. Garcia and E. Debreuve and M. Barlaud. Fast k nearest neighbor search using GPU. In Proceedings of the CVPR Workshop on Computer Vision on GPU, Anchorage, Alaska, USA, June 2008.
  6. www. GPGPU. org
Index Terms

Computer Science
Information Sciences

Keywords

Green Computing Cpu Gpu Power