Some Joules Are M ore P recious T han O thers: Managing Renewable Energy in the Datacenter

1. Some Joules Are More Precious Than Others: Managing Renewable Energy in the Datacenter Published on: HotPower ‘09 Presentation By: Liang Hao Tuesday, August 03, 2010

2. Author • Christopher Stewart from The Ohio State University • Kai Shenfrom University of Rochester • Publications: • Of Christopher Stewart • Of Kai Shen

3. Motivation • To reduce datacenters’ dependence on costly and less clean energy from the grid • Hence to maximize the use of renewable energies • To explore the possibility of evaluating the request-level power consumption

4. Problems • Applications in the datacenter must be available 24x7 • But wind and solar energy are intermittent • Datacenters powered by renewable energy need backups • Primary options: Grid, generator, battery • Alternatives are either dirty and/or costly • Renewables are precious! • renewable = joule converted from solar/wind • The preferred energy source • Available only sometimes and costly to store

5. Opportunities • Capacity planning • Compute power should fluctuate with intermittent outages—i.e., turn machines off • Load balancing • Route requests to datacenters with unused renewables • Migrate services to datacenters with renewables

6. Intermittency1.Datacenter Modeling

7. Intermittency1.Datacenter Modeling • Automatic transfer switch (ATS) • Input 2 power sources, outputs 1 power source • Monitors power from the primary source • When power from primary dips below threshold, ATS switches to secondary • When primary exhibits power of threshold, ATS switches back to secondary

8. Intermittency1.Datacenter Modeling • Key parameters related to the ATS • to ensure dependability or reliability, threshold equals peak consumption • to make full use of renewable energies, scale down the threshold

9. Intermittency2.Wind Intermittency • Battery backup too costly • But if we apply renewable-aware management, there is enough supply from other datacenters

10. Intermittency3.Renewable Utility • when threshold set to peak power, the utility of wind turbine power production drops 65% compared to when threshold set to zero.

11. Intermittency3.Renewable Utility • Economical feasibility (metric: cost per KW-hour) • Average price for commercial electricity $0.10 KW-hour • $2.4M to erect a wind turbine that is connected (directly) to a datacenter [European Wind Energy Assc.] • $1.6M installation • 2% annual maintenance fees • Lifetime of turbine: 20 years • Datacenter at CA or MT could use 24M KWh • Either high power consumption or zero threshold • Wind-powered datacenter in MT: $0.04 KWh

12. Request-level Event Profiling • To estimate the power consumption of individual requests • With quantized statistics, scheduler could possibly route some requests to datacenters with unused renewables

13. Request-level Event Profiling • Tracing the route that a request go through, including CPU usage and other hardware events. • We configured the performance counters to assemble three predictor metrics for our power model: • L2cache requests per CPU cycle (Ccache), • memory transactions per CPU cycle (Cmem), • and the ratio of non-halt CPU cycles (Cnonhalt).

14. Request-level Event Profiling • Power consumption is calculated according to the expression below • where P’s are coefficient parameters for the linear model. are constants that approximate ceiling values for the predictor metrics.

15. Request-level Event Profilingmicro benchmarks • 1) idle • 2) CPU spinning with no access to cache or memory • 3/4) Apache web server with either short requests (no more than 1KB files) or long requests (files of 100 KB– 1 MB) • 5/6) OpenSSL RSA encryption/decryption using either a small key or a large key. We also use four full server workloads • 7) TPC-C running on the MySQL database • 8) TPC-H running on the MySQL database • 9) RUBiS • 10) WeBWorK .

16. Request-level Event Profiling • Request workloads executed in isolation • WattsUp power meter measures watts and joules • Processor was not adjusted during tests

17. Vision

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