DocumentCode
652581
Title
Electrical energy aware parallel computing with MPI and CUDA
Author
Igumenov, Aleksandr ; Ilinskas, Julius
Author_Institution
Inst. of Math. & Inf., Vilnius Univ., Vilnius, Lithuania
fYear
2013
fDate
28-30 Oct. 2013
Firstpage
531
Lastpage
536
Abstract
The object of research of the article is environment-friendly technologies that can minimize electrical energy consumption of parallel and distributed computers. The study revealed that even without computations computer clusters consume considerable amount of electrical power. A technique to save electrical energy is proposed to automatically shut down compute nodes when they are not needed for computation, leaving only network cards on waiting for the tasks. When the tasks are assigned, electrical power consumption increases, but not evenly for each core - each next core increases consumption of power less than the previous one. Therefore for efficient use of electricity computer´s cores must be loaded as much as possible, rather than parallel tasks divided among several computers. Graphics processing units consume a lot of electrical power. However their high computational performance makes computing electrical energy efficient when they are used with care.
Keywords
application program interfaces; graphics processing units; message passing; parallel architectures; power aware computing; CUDA; MPI; automatic compute node shut down; computational performance; computer clusters; computer core; distributed computers; electrical energy aware computing; electrical energy consumption minimization; electrical energy efficient computing; electrical energy saving; electrical power consumption; environment-friendly technologies; graphics processing units; network cards; parallel computers; parallel task division; task assignment; Electricity; Energy consumption; Graphics processing units; Green products; Multicore processing; Supercomputers; CUDA technologies; GPU; energy aware parallel computing;
fLanguage
English
Publisher
ieee
Conference_Titel
P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 2013 Eighth International Conference on
Conference_Location
Compiegne
Type
conf
DOI
10.1109/3PGCIC.2013.91
Filename
6681285
Link To Document