Sustainable Data Centers: HP Labs

Sustainable Data CentersEnabled by Supply and Demand Side Management
Prith Banerjee
Senior Vice President of Research and
Director, Hewlett Packard Laboratories
(Co-authors: Cullen Bash, Chandrakant Patel, Partha Ranganathan)

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HP Labs Research Areas
The next technology challenges and opportunities
Digital Commercial Print
Intelligent Infrastructure
Content Transformation
Sustainability
Immersive Interaction
Cloud
Analytics
Information Management

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The rest of the global economy
IT industry
98%
2%
IT must play a central role in addressing the global sustainability challenge.
Industry Challenge
Create technologies, IT infrastructure and business models for the low-carbon economy
Total carbon emissions
As much as the aviation industry
Projected to double by 2020
IT can play a role in reducing this impact
To do so, IT solutions must take a lifecycle perspective
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Role of the IT EcosystemData Centers at the Hub
Sustainable Data Centers enabled by supply and demand side management of power, cooling and IT resources
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Supply and Demand Side Management
Supply Side:
Design of physical infrastructure with focus on lifecycle engineering and management, and the available energy required to extract, manufacture, operate and reclaim components;
Utilization of local resources to minimize destruction of available energy in transmission, and construction of transmission infrastructure.
Demand Side:
Provisioning data center resources based on the needs and service level agreement of the user through use of flexible building blocks, pervasive sensing, knowledge discovery and policy based control
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IT:SW
IT:HW
Power
Cooling
Autonomous Control
Knowledge Discovery & Visualization
Pervasive Cross-layer Sensing
Flexible, Efficient, & Configurable Building Blocks
Data Center Scale Lifecycle Design
Sustainable Data Center
Key Elements
extraction
operation
manufacturing
End of Life
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Lifecycle Design
extraction
operation
manufacturing
End of Life
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Lifecycle Design through Data Center Synthesis
Automate design of datacenters based on lifecycle considerations
Synthesis Process Flow
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Flexible Building Blocks
From chips, to servers to data centers
Cooling Grid
Qdata center + ∑W
Power Grid – Wensemble
Wblower
Wblower
Wpump
Wcompressor
Wpump
Ground Coupled Loop
Qsystem
Wblower
Wsystem
Qchip
Outside Air
Wchip
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Microblades and Megaservers
The Inefficiencies in the Cloud
Hardware
Power & cooling

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Disaggregation
Efficient building blocks




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2X performance/$

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Pervasive SensingIT & Facilities
Cooling Infrastructure
IT Hardware
External Environment
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Knowledge Discovery in the IT ecosystem
minimizing material and minimizing energy
PCA-based Anomaly detection
Mobile-enabled diagnostics
Collaborative Fault Analytics
Data Center Room Infrastructure
Power Micro-Grid Infrastructure
Cooling Grid Infrastructure
Client Infrastructure
Data Aggregation Pathways
Event/Episode Detection
Model
Creation
Causality
Pre-Process
Raw
Data
Useful Knowledge
Visualization
Expedient Assessment
Early Warning System
Lifetime Estimation
Performance Metrics
Efficiency Metrics
Expert Systems

DAC2009-50-2
Air Mixture Out
Warm Water
Air Mixture In
Air Mixture In
Cooling Tower loop
Wp
QCond
Makeup Water
Return Water
Chiller Refrigerant loop
Wcomp
QEvap
Wp
Chilled Water loop
Data Center CRAC units
Example: Chiller Unit Ensemble
Data center cooling infrastructure
Clustering
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Active Control of Cooling Resources
Conventional Mode
With active control using rack inlet temperature
35% Energy SavingsImproved reliability

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Dynamic Workload Placement based on Cooling Efficiency
8am
10am
3pm
Results
(Thermal Management Margin)j + (AC Margin)j
32% Energy savings over random job placement
 $1M/year in savings (for large DCs)
Improved thermal reliability of IT equipment
Increased uptime
(Hot Air Recirculation)j
(Tset – Tin)i + [(TSAT - TSAT,min)j TCIj]i
(Tin – TSAT)i
Premise:
Hotspots exist that impact efficiency
Use LWPI to place workload in more efficient locations
Test using batch loads in real data center
LWPI = 0.33
LWPI = 3.8
Batch load for tests
LWPI = 4.9
Local Workload Placement Index …
LWPI =
=
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Demonstration at Scale
Software Operations, Bangalore
Consolidation of 14 lab data centers
Facility Building Blocks
IT Building Blocks
Servers
Non-Stop servers
Proliant servers
Blade servers
Custom Enclosures
Storage (XP/EVA)
Multiple Network topologies
SensorNetwork
7500 sensors
Chillers
3 air-cooled
2 water-cooled
Pumps
7 Primary
5 Secondary
CRAC units
55 units
Diesel Generators
5 3MW units
5 floors @14k sq. ft.
900kW cooling per floor
Need based provisioning of compute, power and cooling resources based on available energy consumed (supply side)
Dynamic cooling control implemented
Data Analysis, Visualization and Knowledge Discovery to detect anomalies, improve reliability and minimize redundancy
40% reduction in AHU power
20% reduction in Infrastructure Power
7,500 tons of CO2 prevented annually
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Rack
heterogeneity
X
VM
Enclosure IAM
Server iLO
CPU
CHAOS!! (“Power” Struggle)
X
VM-res.all
Peak thermal power
Peak electrical power
OS-wlm
Average power
Vmotion
OS-gwlm
Local optima
LSF
X
SIM
global optima
X
Power Struggles!
X
X
X
X
X
X
performance
performance
X
X
X
performance
X
X
X
X
X
X
X
X
X

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Cross Layer Monitoring and Management Framework
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It works!

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It works well!
65% savings (OpEx)
20% savings (CapEx)
Similar performance

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Other interesting insights…
No VMC
VMC only
Unified

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Conclusions
Environmental impact of IT is a growing worldwide concern
Governments are beginning to take notice and regulations are increasing
Management of available energy required to run cost effective operation
An integrated, life-cycle approach to data center design and management is necessary to improve efficiency and reduce impact.
Demonstrated results with economic payback

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Sustainable Data Centers: HP Labs

by Hewlett-Packard on Jul 30, 2009

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