Peter Bodik, Michael Paul Armbrust, Kevin Canini, Armando Fox, Michael Jordan and David A. Patterson
EECS Department
University of California, Berkeley
Technical Report No. UCB/EECS-2008-127
September 26, 2008
http://www2.eecs.berkeley.edu/Pubs/TechRpts/2008/EECS-2008-127.pdf
Although there is prior work on energy conservation in datacenters, we identify a new approach based on the synergy between virtual machines and statistical machine learning, and we observe that constrained energy conservation can improve hardware reliability. We give initial results on a cluster that reduces energy costs by a factor of 5, reduces integrated circuit failures by a factor of 1.6, and disk failures by a factor of 5. We propose research milestones to generalize our results and compare them with recent related work.
BibTeX citation:
@techreport{Bodik:EECS-2008-127, Author = {Bodik, Peter and Armbrust, Michael Paul and Canini, Kevin and Fox, Armando and Jordan, Michael and Patterson, David A.}, Title = {A Case For Adaptive Datacenters To Conserve Energy and Improve Reliability}, Institution = {EECS Department, University of California, Berkeley}, Year = {2008}, Month = {Sep}, URL = {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2008/EECS-2008-127.html}, Number = {UCB/EECS-2008-127}, Abstract = {Although there is prior work on energy conservation in datacenters, we identify a new approach based on the synergy between virtual machines and statistical machine learning, and we observe that constrained energy conservation can improve hardware reliability. We give initial results on a cluster that reduces energy costs by a factor of 5, reduces integrated circuit failures by a factor of 1.6, and disk failures by a factor of 5. We propose research milestones to generalize our results and compare them with recent related work.} }
EndNote citation:
%0 Report %A Bodik, Peter %A Armbrust, Michael Paul %A Canini, Kevin %A Fox, Armando %A Jordan, Michael %A Patterson, David A. %T A Case For Adaptive Datacenters To Conserve Energy and Improve Reliability %I EECS Department, University of California, Berkeley %D 2008 %8 September 26 %@ UCB/EECS-2008-127 %U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2008/EECS-2008-127.html %F Bodik:EECS-2008-127