1. Department of Computer Technology
Energy Overhead of the Grapical User Interface in Server Operating Systems
Introduction
Experiment
Operating systems reside on nearly every server, controlling systems
resources (Vahdat, Lebeck, & Schlatter Ellis, 2000). Operating systems are
continually designed to provide more features and these features
increasingly include energy savings management. Focusing on server level
operating system software allows us to take advantage of the Cascade Effect
as described by Emerson. The Cascade Effect states that for every watt
saved at the server level 2.84 watts are saved by the data center (Emerson).
In addition if an operating system where chosen that required very little
graphics and no sound additional savings could be achieved. This is because
it would allow the removal or reduction of components. The chart labeled
Watts lost per server provides a rough breakdown of the number of watts
lost broken down by server component (Anderson, 2007). For example PCI
cards, these would include video and audio cards. Exclusion of unnecessary
PCI cards from servers could save 41 watts. Unnecessary components waste
energy even when they are not used(Google). When these savings are
multiplied into the average number of servers in a data center the savings
become very significant. For example, if a PCI card such as video card were
removed for a savings of 41watts from 500 servers in a data center, the
cumulative watts saved would be 58220 watts per year. At an average of
ten cents per kilowatt-hour this results in a savings of $51,035.65 per year.
Watts used by servers are converted to heat, which is expressed in British
Thermal Units(Anayochukwu Ani, Ndubueze Nzeako, & Chigbo Obianuko,
2012). Each watt consumed by a server translates into approximately
3.4129 BTUs per hour (Barielle, 2011). Waste heat must then be removed
from the data center to avoid damaging the servers resulting in additional
energy consumed by cooling units. This is the reasoning behind the Cascade
Effect. This is also the reason that the primary focus of this study is on
reducing the watts consumed at the server level.
Quantitative data was collected to measure the efficiency of server operating
systems. Experimentation and observation were employed at the server and software
levels. The data collected includes observations of watts consumed by the server
with different hardware and operating system software configurations. All energy
readings were collected for a minimum of one hour using the Watts Up? Meter. The
software used for the testing were the following x86 operating systems:
Ubuntu 9.10 (Linux)
Ubuntu 11.10 (Linux)
Windows Server 2008 R2 Datacenter Core
Windows Server 2008 R2 Datacenter GUI
No operating system configuration changes were performed, all were installed using
defaults. The systems were not connected to the Internet and no updates were
performed on the operating systems. Linux based server operating systems ran the
Top command during the observations. Top provides data for on-going processes. A
sample was taken not running Top to serve as a baseline so that the load of running
top can be determined. Top was configured via command line to take readings at
intervals of one second. The results were sent to a file for possible analysis. The
command used was:
Type top -d 1 > /home/testOSName.txt
The Windows based operating systems do not have a direct equivalent to the Linux
Top program. The Windows command line tool called Typeperf was configured to
provide much of the same information. The command used was:
typeperf "MemoryAvailable bytes" "processor(*)% processor time"
"Process(*)Thread Count" > testOSName.csv
This tool was chosen in part because it would run with or without the standard GUI
based Windows operating system. Another advantage to this tool is reduction in the
possibility of creating the energy overhead that might come with a more
sophisticated program. As this study’s focus is on differences in operating systems,
adding another program would unnecessarily complicate the readings. Typeperf
output to file proved to be valuable during the data analysis phase as the data
gathered from the Typeperf tool provided insight into the differences in what was
happening at the operating system level.
Windows 2008 R2 Datacenter
Core
(Non-GUI)
Time
Threads
Watts
(Minutes)
(Mean
(Mean)
Number)
3:16
263
17.1
Windows 2008
R2 Datacenter
(GUI)
Time
Threads
Watts
(Minutes)
(Mean
(Mean)
Number)
9:42
373
18.65
9:43
361
18.6
3:17
263
17
9:44
362
18.65
9:45
360
18.65
3:18
3:19
260
256
17
17.05
9:46
360
18.7
3:20
259
17.05
9:47
368
18.7
3:21
255
17.15
9:48
9:49
364
363
18.6
18.7
3:22
255
17.25
3:23
252
17.1
9:50
362
18.65
3:24
250
17.2
9:51
364
18.7
3:25
254
17.2
9:52
376
18.65
3:26
250
17.25
Findings
The greatest overall variation is the Windows 2008 R2 Datacenter graphical
user interface operating system that varied from 15.30 watts to 24.90 watts with a
difference of 9.60 watts. The data collected provides some insight into the
operating system-power consumption relationship. The data collected indicates a
correlation between increased energy consumption and the presence of a graphical
user interface.
The Comparison of watts consumed by operating system scatter chart shows
that the operating systems that do not run a graphical user interface (GUI) use
roughly 17.5 to 17.6 watts. The two graphical user interface (GUI) based
operating systems tested consumed 18.1 to 18.9 watts roughly. It could be
extrapolated that not using a GUI would save .6 to 1.3 watts per server.
The data collected confirmed the expected difference between GUI based
operating systems and non-GUI. One would assume that there is more energy
overhead in a system that is processing and rendering graphics than one that does
not. The tables above compare the Windows 2008 R2 datacenter thread and watt
consumption for a period of ten minutes
The mean number of threads the GUI version of the OS is running is 365;
the non-GUI mean was 256. This difference of approximately 109 threads may
account for the overall difference in energy consumption. This also indicates that
a reduction of 100 threads can save roughly one watt at the server level.
The server hardware as configured was found to have a mean energy consumption
of 17.42 watts. The Core (non-GUI) installation of Windows 2008 datacenter
increases the power load by .15 watts from the baseline hardware load. The
standard Windows 2008 R2 datacenter installation increases the power load from
the baseline by 1.43 watts. This may not seem like much but this represents an
increase of nearly ten times the load added by the non-GUI version.
The watt readings from the micro server tests combined with the typeperf
data provide insight into why the GUI operating system consumes more energy.
The GUI version of the Windows Server 2008 R2 datacenter runs over 100
threads more than the non-GUI Core version of Windows Server 2008 R2
datacenter. This 100-thread overhead represents approximately one watt of
additional energy consumption at the server level. Allowing for the cascade effect
this would be approximately three watts per server.
References
Anayochukwu Ani, V., Ndubueze Nzeako, A., & Chigbo Obianuko, J. (2012). Energy Optimization at Datacenters in Two Different Locations of Nigeria. International Journal of Energy Engineering,
151-164.
Anderson, N. (2007, 27 2). New industry group looks to cut server room power consumption. Retrieved 11 21, 12, from Ars Technica: http://arstechnica.com/uncategorized/2007/02/8932/
Barielle, S. (2011, 11). Calculating TCO for Energy. Retrieved from IBM Systems Magazine: http://www.ibmsystemsmag.com/mainframe/Business-Strategy/ROI/energy_estimating/
Emerson. (n.d.). Energy Logic: Calculating and Prioritizing your data center IT Efficency Actions. Retrieved 3 13, 2012, from Efficient Data Centers.com:
http://www.efficientdatacenters.com/edc/docs/EnergyLogicMetricPaper.pdf
Google. (n.d.). Efficiency: How we do it. Retrieved 11 21, 12, from Google Data centers: http://www.google.com/about/datacenters/efficiency/internal/#servers
©Heather Brotherton 2011-2013