A Model-Based Process for Evaluating Cluster Building Blocks
Traditional servers account for more than 1.5% of the US electricity use though spend their lives largely underutilized or idle. Because a large portion of power in a data center is due directly or indirectly to servers, power savings in a data center environment can be achieved simply by using lower power hardware in place of these traditional servers. However, deciding which hardware to use in place of servers is complicated because lower power typically equates to lower performance and because different cluster owners use different metrics of success in quantifying cluster performance. The paper presents measurements from several single-machine and system benchmarks for both interactive and batch jobs and develop predictive models for power and performance within a cluster.