1. Utility-Function-Driven Energy- Efficient Cooling in Data Centers Authors: Rajarshi Das, Jeffrey Kephart, Jonathan Lenchner, Hendrik Hamamn IBM Thomas J. Watson Research Center Presented by: Shivashis Saha University of Nebraska-Lincoln

2. Outline Introduction Related Work Data Center Energy Balance Utility Functions – Multiplicative utility functions – Additive utility functions Experiments Conclusion 2

3. Introduction Data center energy management – “50% of existing data centers will have insufficient power and cooling within two years” – “Power is the second-highest operating cost in 70% of all data centers” – “Data centers are responsible for the tens of millions of metric tons of carbon dioxide emissions annually --- more than 5% of the total global emissions” 3

4. Introduction Why use autonomic computing? – Large, difficult to manage, complex – Management problem is both qualitatively similar to and quantitatively harder than that of managing IT alone. 4

5. Contributions Apply utility functions to save energy – Tradeoff between energy and temperature – Control parameters: Fan speed On/off states of individual Computer Room Air Conditioning (CRAC) Proposed model show 12% reduction in energy without violating temperature contraints 5

6. Related Work Saving more energy is not good if administrator does not want that! – Proposed model is flexible Apply computational fluid dynamics modeling to complex data center environments Temperature aware workload placement based on inlet temperature or heat recirculation 6

7. Data Center Energy Balance P DC, power to run data center is split using switch gear equipment into: – Path to power the IT equipments – Path to power the supporting equipments 7

8. Data Center Energy Balance The support path may include – Power for pumping coolant to and from CRACs to the chiller and to and from the chiller to the cooling tower Power path for IT equipments include – Conversion loss due to the uninterruptible power supply (UPS) systems – Losses associated with the power distribution P PDU – The UPS systems are located outside the raised floor area 8

9. The total power on the floor: P IT is the power consumed by the IT equipments Total CRAC fan power and CDU pump power: The relation between fan power P CRACi and relative fan speed Θ i Data Center Energy Balance 9

10. Under steady state condition, the total raised floor power equal to the total cooling power – The reduced fan speed reduces the air flow: 10

11. Data Center Energy Balance All raised floor power needs to be cooled by the chilling system, which required power for refrigeration – COP: the coefficient of performance of the chiller system (assume, average COP = 4.5) 11

12. Data Center Energy Balance Reducing CRAC fan speeds, the fan power is reduced This reduces both the raised floor power and the power needed from chiller system However, reducing fan speed also increases the server inlet temperature  A tradeoff between energy consumption and the temperature!!! 12

13. Utility Functions Data center operators responsible for the physical environment tend not to be concerned about application level performance, e.g. performance, availability, or security They are more concerned about cost, energy, temperature, and hardware lifetimes There are two CRAC units, whose fan speeds are Θ 1 and Θ 2 13

14. Utility Functions Multiplicative utility functions 14

15. Utility Functions  The previous utility function is very harsh! 15

16. Utility Functions Additive utility functions 16

17. Experiments 17

18. Experiments 18

19. Experiments 19

20. Experiments 20 Each CRAC was: 1.Turned off 2.Turned on at lowest speed (60%) 3.Turned on at max speed (100%)

21. Experiments 21

22. Experiments Snorkels were placed 22

23. Experiments 23

24. Conclusion Use of utility functions in data centers Total reduction of energy consumption by 14% Dynamic aspects of utility functions are not yet considered Investigation of techniques combining dynamic workload scheduling with dynamic workload migration 24

25. Thanks!