As discussed in this chapter, the cooling equipment in WSCs can themselves consume a lot of energy. Cooling costs can be lowered by proactively managing temperature. Temperature-aware workload placement is one optimization that has been proposed to manage temperature to reduce cooling costs. The idea is to identify the cooling profile of a given room and map the hotter systems to the cooler spots, so that at the WSC level the requirements for overall cooling are reduced.

a. The coefficient of performance (COP) of a computer room air conditioning unit (CRAC) is a measure of its efficiency, and is defined as the ratio of heat removed (Q) to the amount of work necessary (W) to remove that heat. The COP of a CRAC unit increases with the temperature of the air the CRAC unit pushes into the plenum. If air returns to the CRAC unit at 20°C and we remove 10KWof heat with a COP of 1.9, how much energy do we expend in the CRAC unit? If it takes a COP of 3.1 to cool the same volume of air, but the air is returned at 25°C, how much energy do we now expend in the CRAC unit?

b. Assume a workload distribution algorithm is able to match the hot workloads well with the cool spots to allow the computer room air-conditioning (CRAC) unit to be run at a higher temperature to improve cooling efficiencies like in the exercise above. What is the power savings between the two cases described above?

c. Given the scale of WSC systems, power management can be a complex, multifaceted problem. Optimizations to improve energy efficiency can be implemented in hardware and in software, at the system level, and at the cluster level for the IT equipment or the cooling equipment, etc. It is important to consider these interactions when designing an overall energy-efficiency solution for the WSC. Consider a consolidation algorithm that looks at server utilization and consolidates different workload classes on the same server to increase server utilization (this can potentially have the server operating at a higher energy efficiency if the system is not energy-proportional). How would this optimization interact with a concurrent algorithm that tried to use different power states (see ACPI, Advanced Configuration Power Interface, for some examples)? What other examples can you think of where multiple optimizations can potentially conflict with one another in a WSC? How would you solve this problem?