Publication | Closed Access
Wimpy node clusters
77
Citations
25
References
2010
Year
Unknown Venue
Cluster ComputingEngineeringEnergy EfficiencyConstant ScaleupComputer ArchitectureNetwork AnalysisCluster TechnologyStructural Graph TheoryParallel ComputingCombinatorial OptimizationHigh CostComputer EngineeringWimpy Node ClustersComputer ScienceComplex QueriesScalable ComputingPerformance ScalabilityNetwork ScienceGraph TheoryNetwork AlgorithmEdge ComputingCloud ComputingParallel ProgrammingPower-efficient ComputingBig Data
The high cost associated with powering servers has introduced new challenges in improving the energy efficiency of clusters running data processing jobs. Traditional high-performance servers are largely energy inefficient due to various factors such as the over-provisioning of resources. The increasing trend to replace traditional high-performance server nodes with low-power low-end nodes in clusters has recently been touted as a solution to the cluster energy problem. However, the key tacit assumption that drives such a solution is that the proportional scale-out of such low-power cluster nodes results in constant scaleup in performance. This paper studies the validity of such an assumption using measured price and performance results from a low-power Atom-based node and a traditional Xeon-based server and a number of published parallel scaleup results. Our results show that in most cases, computationally complex queries exhibit disproportionate scaleup characteristics which potentially makes scale-out with low-end nodes an expensive and lower performance solution.
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