Energy-awareness and Big Data Management in Information Systems
@EnBIS2016
Monica VitaliPolitecnico di Milano
Marina ZapaterUniversidad Complutense de Madrid
Motivation
Towards cloud services: increment in the size and kind of information to be stored, processed, and analysed
Question: Is it sustainable?
Focus: Energy-awareness of cloud-based business activities, from the application to the resource management
Challenges: Internet of Things and Big Data
2
Data Center energy consumption trends
7
500.000 DCs in the world
Total Energy > 200 000 000 000 € / year
Data Center energy consumption trends
8
1.3% Worldwide energy production in 2010
1 Data Center =
2012: Data Center power demand grew 63% to 38GW2013: Further rise of 17% to 43GW
Responsible for 2% CO2 emissions
Jonathan Koomey, 2011. Growth in Data Center electricity use 2005 to 2010
Sustainability and CO2
ICT Power Consumption Distribution
9Greenpeace report “Clicking Green: A Guide to Building the Green Internet”, 2015
Green IT Taxonomy
13M. Vitali and B. Pernici, “A Survey on Energy Efficiency in Information Systems,” IJCIS 2014
Green IT ApproachesSeveral layers, complementary approaches
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Chip Server Rack Room Data Center Federated DCs IoT
Application
Scheduling &Allocation
OS
Compiler/VM
Architecture
Technology
SoA started by covering largest chunk of power consumption
Green IT ApproachesSeveral layers, complementary approaches
● Savings by applying only best practices● Impact of savings increases with level of abstraction
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Traditional power breakdown in DCs● Traditionally, cooling costs have been an important part of overall energy
16IT
ManagementCooling
Management
Traditional cooling techniques● Raised-floor air-cooled DCs● Both industry and academic devoted efforts to reduce DC cooling costs
○ Google reports PUE of 1.11 and 1.12 → Data Centers in very cold areas● When power density increases, this techniques cannot be used anymore
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Enabling high-density computation● In order to achieve exascale
computing, we need higherpower densities
○ More efficient cooling○ But also more efficient servers
18kw/Rack
Trad
ition
al H
VA
C
refri
gera
tion
Hot/cold aisle contain-ment
Component-based(liquid cooling)
Close-coupled chilled water cooling(in-row or in-rack)
Higher rack density
Warmer water temperature
Green IT ApproachesSeveral layers, complementary approaches
19
Chip Server Rack Room Data Center Federated DCs IoT
Scheduling &Allocation
Application
OS
Compiler/VM
Architecture
Technology
Goal: Holistic approach to energy efficiency and GreenIT(i.e: “Filling all the cells in the table”)
Chip-level techniques: 3D architectures
20
Chip Server Rack Room Data Center Federated DCs IoT
Scheduling &Allocation
Application
OS
Compiler/VM
Architecture
Technology
New transistor technologies: FD-SoI● Dramatically impacts the trade-offs at upper abstraction layers
21
Chip Server Rack Room Data Center Federated DCs IoT
Scheduling &Allocation
Application
OS
Compiler/VM
Architecture
Technology
Heterogeneity: putting it all together● Move towards heterogeneous chips, servers, rooms, data centers
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Chip Server Rack Room Data Center Federated DCs IoT
Scheduling &Allocation
Application
OS
Compiler/VM
Architecture
Technology
FDSoIConventional CMOS
Heterogeneous Servers, Racks...:
2D, 2.5D, 3D Chips...
EnBIS 2016
GOAL Look at Green IT from a new perspective
Face new challenges and new opportunities of Green IT
Promote cooperation between research groups towards an holistic approach
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EnBIS 2016 Papers Selection
6 Full Paper submitted
3 Papers Accepted for presentation
50% Acceptance Rate
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EnBIS 2016 Schedule
SESSION 1 (9:00 - 10:30)Opening Presentation. Sustainable Data Centers (1 presentation)
SESSION 2 (11:00 - 12:30)Panel Discussion: Enhancing multi-disciplinary collaboration between research groups
SESSION 3 (14:00 - 15:30)Smart Buildings (2 presentations)
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Energy-awareness and Big Data Management in Information Systems
@EnBIS2016
Monica VitaliPolitecnico di Milano
Marina ZapaterUniversidad Complutense de Madrid
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