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© 2009 Hewlett-Packard Development Company, L.P.The information contained herein is subject to change without notice
Unified Thermal and Power Management in Server Enclosures
Niraj Tolia, Zhikui Wang, Manish Marwah, Cullen Bash, Parthasarathy Ranganathan, Xiaoyun Zhu*
*Now at VMware
2005: $26.5 Billion
“The cost of power and cooling is likely to exceed that of hardware…”
- Luiz Barosso, Google
“In the data center, power and cooling costs more than the IT equipment it supports.”
- Christian L. Belady, Microsoft (former HP)
Zephyr• Unified Power and Cooling Management
Contributions• Demonstrate how to do per-blade cooling• Save both cooling (21--30%) + system power (23--29%)
• Without impacting performance
Compact DesignDense Compute and Storage
Blade Servers:
Workloads are Virtualized
Compact DesignDense Compute and Storage
Blade Servers:
Workloads are Virtualized
Web ServerOS
Hardware
Virtualization:
VM MonitorHardware
Virtual Machine
WebServerOS
Virtualization:
Virtual Machine
WebServerOS
OSVM MonitorHardware
VM MonitorHardware
Virtual Machine
App ServerOS
Virtualization:
Virtual Machine
WebServerOS
OSVM MonitorHardware
VM MonitorHardware
Virtual Machine
App ServerOS
Virtualization:
Virtual Machine
WebServerOS
OSVM MonitorHardware
VM MonitorHardware
Virtual Machine
App ServerOS
Virtualization:
CPU P-states BladeEnclosure
PowerUtil
Temp.Zephyr
Min.Power
Tref
Utilref
Models
Fan Speed
VM Migr.Blade On/Off
Power ModelsTemperature Models
0
50
100
150
200
250
0 20 40 60 80 100
Pow
er (
W)
Utilization
Power - P0Power - P4Power Model - P0Power Model - P4
Power Model: Single Blade
Power Model: Single Fan
0 6000 12000 180000
50
100
150
200
Speed (RPM)
Pow
er (W
)
Measured Fan PowerFan Power Model
Unfortunately, temperature models are significantly more complex.
Models don’t existsMany things affect temperatureInsufficient sensors in servers
Zonal Variations
Fan No.
Blad
e N
o.
1 2 3 4 5 6 7 8 9 10
123456789
10111213141516
Zonal Variation: Fan Influence
Temperature Models• Steady State Model−Assumes workloads, ambient environment is constant
• Transient Model−Finer-grained control in real-world environments
Temperature Models• Steady State Model−Assumes workloads, ambient environment is constant
• Transient Model−Finer-grained control in real-world environments
ZephyrBlade
Enclosure
PowerUtil
Temp.
Min.Power
Tref
Utilref
Models
Fan SpeedCPU P-statesVM Migr.
Blade On/Off
ZephyrBlade
Enclosure
PowerUtil
Temp.
Min.Power
Tref
Utilref
Models
Fan SpeedCPU P-statesVM Migr.
Blade On/Off
FC
ECGC
Group Controller (GC)• Goal: Minimize Power(Enclosure)
• Changes state every 10 minutes• Monitors Utilization, Inlet Temperature• Uses two-step optimization−Simulated Annealing for space search−Convex Optimization for Fan Cost + Blade Power Model
Experimental Setup
Storage Array
Controller
Temp and Util. DataVM Migration
Fan Speed Control
16 Blades (4 cores)5 P-States
10 Fans, 64 Xen VMs
0
50
100
150
200
250
300
IT
Pow
er (W
)Static Integral Predictive Zephyr Zephyr + On/Off
Cooling Power Savings
626
System Power Savings
0
500
1000
1500
2000
2500
3000
3500
4000
IT
Pow
er (W
)Static Integral Predictive Zephyr Zephyr + On/Off
Simulated Servers
239
34
68
102
136
170
204
120
154
190
222
256
290
0
50
100
150
200
250
300
0 20 40 60 80 100
Power Usage (W
)
Utilization
Real
EnergyProportional
PracticalNext-Gen
Simulation: Tamb+15C &13 servers types
Conclusions• Zephyr combines:−Concepts from Heat Transfer Theory with Systems
• Unified power and cooling management can save:−30% Cooling Power−29% Enclosure Power
Full Length Papers:www.hpl.hp.com/personal/Niraj_Tolia/