1. Leveraging Renewable Energy in Data Centers Ricardo Bianchini on tour 2012

2. New Outline (remove) Datacenters consume a lot of power – Huge datacenters, however, a lot of small and medium datacenters – Mainly brown sources: CO2, cost Bringing green energy to datacenters – Why renewable is good? – Why distributed generation? – Why solar and wind? – Variability challenge Green µDatacenter – Construction and operation: timeline – Lessons learned Green Systems – GreenSlot – GreenHadoop

3. Old Outline (remove) Viability – Why renewable is good? – Renewable approaches – Why distributed generation? – Why solar and wind? – Challenges Green µDatacenter – Construction and operation: timeline – Lessons learned Green Systems – GreenSlot – GreenHadoop

4. Motivation Datacenters consume large amounts of energy Energy cost is not the only problem – Brown sources: coal, natural gas… Lots of small and medium datacenters Use renewable sources for datacenters – Solar panels, wind turbines… – “Green" datacenters

5. Renewable sources has lower environmental impact Wastes last thousands of years

6. Motivation Datacenters consume large amounts of energy Energy cost is not the only problem – Brown sources: coal, natural gas… Lots of small and medium datacenters Use renewable sources for datacenters – Solar panels, wind turbines… – “Green" datacenters

7. Renewable approaches for “green” datacenters Centralized generation – Utilities install renewable power plants – Green pricing: users pay for a green percentage Compensation systems – CO 2 offsets – Renewable Electricity Credits (RECs) Distributed generation – Connect to close renewable power plants – Self-generation

8. Why distributed generation? Energy independence – Stable costs – Resilient to external failures Reduce transmission and conversion losses – From 41% to 30% losses (even <5%) Long lifetime – Installations can be reused Allow local energy management – Control which energy to use and when

9. Why solar and wind? Medium/high availability Suitable for small/medium installations – Initial cost/W is lower – No wastes – Easy to install – Easy to maintain

10. Why solar? Solar PV cost scalability is linear – Small installations have similar $/W as large – Better for distributed generation Solar availability is higher than wind WindSolar

11. Price of PV energy is decreasing PV energy already cheaper than utility in some locations [1]

12. Problems and challenges Require large extensions of land – Bad for large datacenters Low/medium efficiency – Efficiency lower than 40% – Increasing every year Variability – Batteries: losses, economic and environmental cost – Net metering: losses, limited availability – Smarter management

13. Parasol (remove) Construction – Structure – Solar panels Installation – Servers: software Lessons learned – Not as easy as it seems – Hard to deal with facilities crowd – Setting it on the roof has extra cost – Easier to just put solar panels in the roof and use a regular room – Flexibility for research purposes is hard – Metering everywhere: temperature, power

14. Parasol We are building a µDatacenter Powered by – PV panels – Electricity grid – Batteries Research framework – Manage solar-powered datacenter – Software to exploit renewable energy – Free cooling

15. Parasol description Installed on the roof Steel structure – Container to host the IT – 10 PV panels: 3 kW Backup energy systems – Batteries: 32 kWh – Power grid IT equipment – 2 42U racks – 64 Atom servers (so far) – 2 switches Cooling system – Free cooling – Air conditioner – Heater

16. Structure craning and assembling

17. Container and solar panels

18. Electrical and cooling

19. IT equipment

20. Green systems Handle renewable energy variability – Smart energy management GreenSlot [SC‘11] – Schedule batch jobs (SLURM) GreenHadoop [EUROSYS’12] – Schedule data-processing jobs (MapReduce)

21. Green systems approach Predict green energy availability – Weather forecast Schedule jobs – Maximize green energy use – If green not available, consume cheap brown May delay jobs but must meet deadlines Manage data availability Send to sleep (S3) idle servers to save energy

22. J1 GreenSlot behavior J2 Time J1 J2 Now Nodes Power J1 J2 Schedule: Brown electricity price Job deadline Scheduling window J1, J2

23. J1 J3 J4 GreenSlot behavior J2 Time J1 J2 J4 J3 Nodes Power J3 J4 Schedule: Now J3, J4 Brown electricity price Job deadline Scheduling window

24. J1 J4 J3 GreenSlot behavior J2 Time J2 J1 J3 Nodes Power J4 Schedule: J4Weather prediction was wrong Now Brown electricity price Job deadline Scheduling window

25. J1 J4 J5J3 GreenSlot behavior J2 Time J2 J1 J3J5 Nodes Power J4 J5 Schedule: Now J5 Brown electricity price Job deadline Scheduling window

26. Future directions Collect data of the data center – Real workloads – Temperatures ???

27. Leveraging Renewable Energy in Data Centers Ricardo Bianchini on tour 2012