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

 |  Login

Show simple item record

dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.advisor Ou, Zhonghong
dc.contributor.advisor Niemi, Tapio Pestana, Goncalo Marques 2016-10-12T11:37:33Z 2016-10-12T11:37:33Z 2016-09-26
dc.description.abstract The 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.extent 72
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.title Energy Efficiency in High Throughput Computing Tools, techniques and experi- ments en
dc.type G2 Pro gradu, diplomityö fi Perustieteiden korkeakoulu fi
dc.subject.keyword energy efficiency en
dc.subject.keyword scientific computing en
dc.subject.keyword ARM en
dc.subject.keyword Intel en
dc.subject.keyword RAPL en
dc.identifier.urn URN:NBN:fi:aalto-201610124915
dc.programme.major Data Communication Software en
dc.programme.mcode T3005 fi
dc.type.ontasot Master's thesis en
dc.type.ontasot Diplomityö fi
dc.contributor.supervisor Nurminen, Jukka
dc.programme Master's Programme in Mobile Computing - Services and Security fi

Files in this item

This item appears in the following Collection(s)

Show simple item record

Search archive

Advanced Search

article-iconSubmit a publication


My Account