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.<\/p>\n","protected":false},"excerpt":{"rendered":"

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. 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