It is now common for data center managers to question the impact on server energy usage of two recent impact factors: (1) the rise in the data center inlet air temperature to servers per 2008 ASHRAE guidelines, and (2) the fan speed increase from the use of rack level heat exchangers such as Rear Door Heat Exchangers. To help acquire a deeper understanding of the relevant issues, a system floor thermal test was built on the IBM New York data center benchmark floor which consisted of a standard 19 rack filled with 39 3.0 GHz 1U servers that dissipated between 10–17 kW depending on extent of server utilization. Fan speed, chip temperature metrics, and server power data was collected using product debug codes and server level programs. A simulated air heat load was installed right in front of this server rack to allow the manipulation of air inlet temperature into the servers from 20 °C to 32 °C. Two different rack level configurations were considered for the experiments: (i) a perforated front door and no door at the rear, and (ii) a perforated front door and a Rear Door Heat Exchanger at the rear. An exerciser program was used to vary the CPU utilization from Idle to 70% which represented a typical data center work load. Data was collected for 19 servers of the 39 servers (remaining were in use by Benchmark Lab) for the two rack configurations, for 4 inlet server air temperatures, and for two chip exerciser settings, i.e. 16 experiments. For the 70% exerciser setting (typical operation) and the base line rack configuration without rack level heat exchangers, the rise in server power for an increase in inlet air temperature was 5.2% for the 20 °C to 27 °C change and was 17% for the 20 °C to 31 °C change. For the 70% exerciser setting (typical), the increase in server power from the use of rack level heat exchangers (Rear Door Heat Exchanger) was less than 1.3% for all the conditions. Given the broad range of fan speed algorithms and cooling hardware in server products on the market and their change over each generation, significant further study will be required to characterize each category of systems for these conditions. However, the present study provides a template for quantifying server energy usage in a context that data center managers can understand and use.

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