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Evalua&ng Green Compu&ng Techniques with Dense, Longterm Power Sensing Maria Kazandjieva, Brandon Heller, David Gal, Philip Levis, Christos Kozyrakis, and Nick McKeown Nov 30, 2010
Evalua&ng Green Compu&ng Techniques with Dense, Long-‐term Power Sensing
Maria Kazandjieva, Brandon Heller, David Gal,
Philip Levis, Christos Kozyrakis, and Nick McKeown
Nov 30, 2010
What can we do to create a more energy-‐
efficient building compu&ng infrastructure?
We don’t know much about energy waste, but what if we did?
We Could
Use current equipment more efficiently
Buy the right equipment next &me around
Enact policies that reduce waste
Educate building occupants
The Bill
300 megawaU-‐hours = 300 U.S. homes
Data Every 15 Minutes
Wired Power Meters
WaUsUp .Net
Ethernet-‐enabled Sampling rate: 1 Hz Closed soZware ~1.8 W power draw $250
Three ‘Easy’ Steps to Deployment
1. Obtaining all necessary materials 2. Getting permission 3. Collecting the data
"I started looking at some stats and found that new machine 'powernet' is number 1 in gates with ~7% of all flows."
"The 70 current meters now account for 20% of the total daily recorded flows"
"more than half of all DNS lookups emanating from Gates/Packard Allen to the campus servers"
A Single Power Meter
System Design
CPU
Wired Wireless
connections: AC power
Wireless Meters
Wired Meters
Database
Front End traffic
CPU
A Single Power Meter
30’’ Dell Monitor
&me (minutes)
10 20 30 40 50
120
90
60
30
150
0
power (w
aUs)
black
white
screen blanking
brightness 14
brightness 11
120
90
60
30
150
0
Impact
&me (hours)
noon
80
60
40
20
100
0
2pm 4pm 6pm 8pm 10am 10pm
power (w
aUs)
April May
Meters. More Meters.
What if we had 10 or 50 meters?
1) Differences between device classes
125 W
&me
10 20 30 40 50
120
80
40
0
power (w
aUs)
data rate (Mbps)
HP Switch, 23 ac&ve ports
NEC Switch, 47 ac&ve ports
NEC Switch, 23 ac&ve ports
2) Varia&ons within a class
Hundreds of Meters
A picture begins to emerge
The Big Picture
The Big Picture
Are We There Yet?
(under) U&liza&on
Percentile CPU
Machine Type 5th 50th 95th
Dell Optiplex 745 1% 9% 58%
High-end custom-built 0% 1% 57%
Dell Precision T3400 0% 4% 29%
HP Pavillion Elite m9250f 0% 0% 25%
Dell Precision T3400 0% 1% 13%
Dell Inspiron 530 1% 1% 8%
Dell Precision T4300 0% 1% 7%
10 20 30 40 50
120
80
40
0
power (w
aUs)
data rate (Mbps)
HP Switch, 23 ac&ve ports
NEC Switch, 47 ac&ve ports
NEC Switch, 23 ac&ve ports
Network U&liza&on
Network U&liza&on
So Far We’ve Learned That
Compu&ng systems account for >55% of Gates' electricity use;
Much of the compu&ng infrastructure is
heavily underu&lized.
Can We Do BeUer?
The Network
When is wireless good enough?
Does a more &ered wired infrastructure reduce waste?
Tradi&onal Desktop Compu&ng
Ul&mate example of waste -‐ high idle baseline power
-‐ low CPU u&liza&on
-‐ almost no diurnal paUerns
Tradi&onal Desktop Compu&ng
Network proxies
Virtual Machine Migra&on
Thin Clients
Laptops
Approach Ac&ve Power Idle Power Per-‐Host Avg Savings
Network Proxy 123 W 5 W 27.3 W 69%
VM Migra&on 127.3 W 9.8 W 30.7 W 65%
Thin Clients 29 W 14 W 13.4 W 85%
Laptops 26 W 26 W 26 W 76.5%
Laptops + Proxy 26 W 5 W 7.9 W 90%
Assume: Active workday of 9 hours; no user activity on weekends
Going Forward
Collect data from different setups: -‐ Office of Research Administra&on: VM migra&on
-‐ University of Erlangen-‐Nuremberg: Thin Clients
Redesign part of the Gates building compu&ng infrastructure & evaluate it
Summary
Dense (250+ sensing points),
long-‐term (over 1 year) power and u&liza&on sensing can reveal waste.
It provides a microcosm for evalua&ng energy saving techniques,
from simple policy changes to completely new infrastructures.
Thank You
hUp://powernet.stanford.edu
Extra Slides
Not the Whole Story
Considera&ons other than pure energy savings:
-‐ total cost of ownership
-‐ maintenance difficulty
-‐ remote accessibility
-‐ support for custom SW and HW
