ConSil: Low-Cost Thermal Mapping of Data Centers Export

@inproceedings{citeulike:2931462, author = {Moore, J. and Chase, J. and Ranganathan, P.}, citeulike-article-id = {2931462}, citeulike-linkout-0 = {http://www.cs.duke.edu/~justin/papers/sysml06consil.pdf}, comment = { * motivation is that sensors are very expensive to deploy in data center. * solution is to sample at key areas and inlet server temperature of servers * use a machine learning method to calculate the entire map. * Results show that 80\% of the simulations fall within 1 deg. Celsius of the experimental/measured value. * better integration with existing thermal control loops. external sensors have problems of synchronizing ambient temperature readings with equivalent server workload measurements. Used FANN neural network library}, journal = {Proceedings of SysML}, keywords = {datacenter, energy, power}, month = {June}, posted-at = {2008-06-26 18:10:31}, priority = {2}, title = {ConSil: Low-Cost Thermal Mapping of Data Centers}, url = {http://www.cs.duke.edu/~justin/papers/sysml06consil.pdf}, year = {2006} }

TY - CONF ID - citeulike:2931462 L3 - citeulike-article-id:2931462 JF - Proceedings of SysML TI - ConSil: Low-Cost Thermal Mapping of Data Centers KW - datacenter KW - energy KW - power N1 - * motivation is that sensors are very expensive to deploy in data center. * solution is to sample at key areas and inlet server temperature of servers * use a machine learning method to calculate the entire map. * Results show that 80% of the simulations fall within 1 deg. Celsius of the experimental/measured value. * better integration with existing thermal control loops. external sensors have problems of synchronizing ambient temperature readings with equivalent server workload measurements. Used FANN neural network library AU - Moore, J AU - Chase, J AU - Ranganathan, P PY - 2006/06// UR - http://www.cs.duke.edu/~justin/papers/sysml06consil.pdf ER -