Energy Efficiency in High Throughput Computing Tools, techniques and experi- ments

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.advisorOu, Zhonghong
dc.contributor.advisorNiemi, Tapio
dc.contributor.authorPestana, Goncalo Marques
dc.contributor.schoolPerustieteiden korkeakoulufi
dc.contributor.supervisorNurminen, Jukka
dc.date.accessioned2016-10-12T11:37:33Z
dc.date.available2016-10-12T11:37:33Z
dc.date.issued2016-09-26
dc.description.abstractThe volume of data to process and store in high throughput computing (HTC) and scientific computing continues increasing many-fold every year. Consequently, the energy consumption of data centers and similar facilities is raising economical and environmental concerns. Thus, it is of paramount importance to improve energy efficiency in such environments. This thesis focuses on understanding how to improve energy efficiency in scientific computing and HTC. For this purpose we conducted research on tools and techniques to measure power consumption. We also conducted experiments to understand if low-energy processing architectures are suitable for HTC and compared the energy efficiency of ARM and Intel ar- chitectures under authentic scientific workloads. Finally, we used the results to develop an algorithm that schedules tasks among ARM and Intel machines in a dynamic electricity pricing market in order to optimally lower the overall electric- ity bill. Our contributions are three-fold: The results of the study indicate that ARM has potential for being used in scientific and HTC from an energy efficiency perspective; We also outlined a set of tools and techniques to accurately measure energy consumption at the different levels of the computing systems; In addiciton, the developed scheduling algorithm shows potential savings in the electrical bill when applied to heterogeneous data centers working under a dynamic electricity pricing market.en
dc.format.extent72
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/22815
dc.identifier.urnURN:NBN:fi:aalto-201610124915
dc.language.isoenen
dc.programmeMaster's Programme in Mobile Computing - Services and Securityfi
dc.programme.majorData Communication Softwareen
dc.programme.mcodeT3005fi
dc.rights.accesslevelopenAccess
dc.subject.keywordenergy efficiencyen
dc.subject.keywordscientific computingen
dc.subject.keywordARMen
dc.subject.keywordIntelen
dc.subject.keywordRAPLen
dc.titleEnergy Efficiency in High Throughput Computing Tools, techniques and experi- mentsen
dc.typeG2 Pro gradu, diplomityöfi
dc.type.okmG2 Pro gradu, diplomityö
dc.type.ontasotMaster's thesisen
dc.type.ontasotDiplomityöfi
dc.type.publicationmasterThesis
local.aalto.idinssi54647
local.aalto.openaccessyes
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
master_Pestana_Goncalo_Marques_2016.pdf
Size:
2.34 MB
Format:
Adobe Portable Document Format