1. Green Computing

2. Green Computing Data centers extremely wasteful
Need energy to power
Need energy to cool
1000 racks, 25,000 sq ft, 10MW for computing, 5MW to dissipate heat
Need a system more efficient, less expensive strategy with immediate impact on energy consumption

4. Data Centers -2006/7
Focus by green computing movement on data centers (SUVs of the tech world)
DOE Study started in 2006 (Bush years?)
Don’t know how many data centers in US
61B kWh of energy
Cost: $4.5 B (more than used by all color TVs in US)
In 2007, DOE reported data centers 1.5% of all electricity in US
Greenhouse gas emission projected to more than double from 2007 to 2020

6. Goal
Within a few years, cost of power for data center was expected to exceed cost of original capital investment
Fed. Gov. wanted data center energy consumption to be reduced by at least 10%
Same as energy consumed by 1M average US households

7. Servers - 2007 One focus Servers Rarely completely idle
Optimized at maximum utilization
Seldom operate at maximum
10-50% of max utilization levels
100% utilization not acceptable for meeting throughput, etc. – no slack time

10. Servers - 2007 Completely idle server waste of capital
Difficult to idle subset of servers
But Servers need to be available
Perform background tasks
Move data around
Can help recovery of crash
Applications can be restructured to create idle intervals
Difficult, hard to maintain
Devices with highest energy savings, highest wake-up penalty, e.g disk spin up

11. Disks: Inactive/active - 2007
Penalty for transition to active from inactive state makes it less useful
Disk penalty 1000 higher for spin up than regular access latency
Only useful if idle for several minutes (rarely occurs)
More beneficial to have smaller penalty even if higher energy levels
Active energy savings schemes are useful even if higher penalty to transition because in low energy mode for longer periods

12. Suggested Solutions
Mismatch between servers’ high-energy efficiency characteristics and behavior
Design machines that consume energy in proportion to amount of work performed
No power when idle (easy)
Nearly no power when little work (harder)
More as activity increases (even harder)

13. Suggested Solutions
Sources of computing power in remote server warehouses
Located near renewable energy sources – wind, solar
Usage shifts across globe depending on where energy most abundant

14. Actualized Solutions Processors close to energy-proportional
Consume < 1/3 power at low activity (70% of peak)
Power range less for other components
< 50% for DRAM, 25% for disk drives, 15% for network switches
Some “low hanging fruit” approaches
Orient racks of servers to exhaust in a uniform direction
Higher fruit - Microsoft
Built near hydroelectric power in WA
Built in Ireland - can air cool, 50% more energy efficient
Countries with favorable climates: Canada, Finland, Sweden and Switzerland

15. More Solutions Google – trying to reduce carbon footprint
Carbon footprint includes direct fuel use, purchased electricity and business travel, employee commuting, construction, server manufacturing
According to Google, its data centers use ½ industry’s average amount of power
How? Ultra efficient evaporative cooling (customized)
Green Grid consortium
Dell, IBM, Sun VM-Wear AMD
Green500 – 500 most green supercomputers

16. More Solutions US government
EPA has phase-one of Energy Star standards for servers
Measure server power supply efficiency and energy consumption while idle
Must also measure energy use at peak demand

17. Data Center Product Specification Completion – Energy Star
2009
Servers v1.0
2011
Data Center Buildings Program
2012
UPS v1.0 (uninterruptable power supply)
2013
Servers 2.0
Storage v1.0
2014
Large Network Equipment v1.0
2015
Data Center Cooling Equipment v1.0

18. Where are we today?

19. 2016 DOE Report DOE 2008 report to Congress
First time data center use for the entire country was quantified in some way
2016 report – surprised by how energy use curve flattened between 2008 and 2016
Demand for data center capacity grew tremendously over last 5 years
Total data center energy grew only slightly

20. 2016 DOEReport 2000-2005 data center energy consumption grew by 90%
4% increase
US data centers consume 70B kilo-watt hours in 2014 – 2% of total energy consumption, same consumed by 6.4 M avg. US homes

21. Why? Why? Amount of servers not growing as quickly
Use virtualization and 2008 crash slowed growth
3% annual increase in server shipments going to hyperscale data centers – cloud giants
Cloud giants created a science out of maximizing server utilization and data center efficiency
data center providers improvements in efficiency of facilities infrastructure, power, cooling equipment

22. Why? Companies deploying fewer servers
Amount of power each server needs not growing as quickly
Power requirements static since 2005
Servers better at reducing power when idle or at lower utilization
Data center power and cooling more efficient
Storage devices and networking hardware also significant efficiency improvements

23. One Solution - Energy proportional servers

24. Efficiency improvements –
If at 2010 levels, data centers consume 40B kWh more

25. Where are the data centers?
Enterprises host 71% of IT assets
20% hosted by data center providers
9% hosted in the cloud
Small data center: fewer than 40 enclosures
Medium: as many as 200 enclosures
Hyperscale – millions of servers

27. Current State Power Usage Effectiveness PUE
PUE = Total facility power/IT equipment power
Data Center infrastructure Efficiency metric DCiE
1/PUE
When first introduced, the US avg PUE was >2.4
For every Watt going to a server, 1.4 Watts used in facility or by AC
Today, datacenters Google, Microsoft, etc. have PUE <1.2. Some even less today ~ 1.0 (

28. Current State
Data center used to just keep up with demand, not keep energy bill low
Now, data center want to make as efficient and productive as possible
BUT – huge center of existing software still runs in highly inefficient data centers
Hyperscale cloud data centers (Google, etc.) represent < 5% of US data centers
Small, medium, corporate, multitenant data centers still squander huge amounts of energy

29. Put everything into the cloud?
Lowest hanging fruit – efficiency of really small data centers (together millions of servers)
Make more efficient or
Replace with hyperscale facilities
Still a limit on efficiency
Still a new field of discovery

30. Current state (2014)- The Negative
Key findings from the NRDC-Anthesis report include:
Up to 30 percent of servers are “comatose” and no longer needed because projects have ended or business processes changed, but are still plugged in and consuming electricity.
Much of the energy consumed by U.S. data centers powers servers operating at 12 to 18 percent of capacity. Even sitting virtually idle, servers use significant amounts of power 24/7. 
In 80 percent of organizations, the department responsible for data center management is separate from the one paying the electric bills. This “split incentive” reduces the likelihood of implementation of commonsense efficiency measures.

31. Current State – The Bad
The average desktop PC wastes half of the energy it consumes.
typical PC is in use only 4 hours each workday and sits idle for more than 5 hours. (
Computers and monitors represent 66% of the electrical load in the average office.
Most new PCs are ENERGY STAR rated but only 5% of PCs have features activated. (Energy Star)
PCs use about 10% more electricity than data centers. (California Energy Commission)

32. Current approaches
Replace old computers with new more energy-efficient
But manufacturing through day-to-day uses energy
Dell , IBM, Cicso, Adobe, Apple listed as Green
What is “Greenest computer ever” ?
Is MacBook air (pro) greenest?

33. Goals for Future Consider energy to manufacture, operate, dispose of
Sense and optimize world around us
Predict and respond to future events by modeling behavior (grown in performance)
Benefit of digital alternative to physical activities
E-newspapers, online shopping
Personal energy meter??