SlideShare a Scribd company logo
1 of 18
Distributed Collaborative
Scientific Visualization
GENI, Ignite, and Big Scientific Data
Visualize Big Data
Fast
Any Device
Anywhere
Collaboratively
Size and Speed
Target: 0.15 seconds *
* N. Tolia, D. G. Andersen, and M. Satyanarayanan. Quantifying interactive user experience on thin clients. Computer, 39(3):46–52, 2006.
Conclusion
Same Building is Best
Same “City” (State) is OK
Same Continent Won’t Fly
One Big Server = World Wide Wait
Meaning For Collaboration
Server must be in same location as user
Distributed Collaboration: users can be
anywhere
Means server requirement: servers must be
everywhere
System Setup
< 10 ms, > 100 mb/s
Replicated Databases
Global Picture
Distributed Collaboration Around Big
Data
“A World Where Distance is Eliminated”
Experts Around the World Interacting With Data
Visualizations as Easily as if They Were in the
Same Room
Previously: Expensive Hardware (OptIPortal,
CAVE) over Expensive, Special-Purpose Networks
GENI: Any Device, Anywhere, Anytime, through a
Web browser
Collaboration Around Big Data
All About Size and Speed
- Data Set: 4 million points per month
- 100 MB/month
Too Much Data For Laptop
Way Too Much for Tablet/Phone/Netbook
Need Server Close to User
How Close Depends on Bandwidth
Size and Speed
Task: Draw 30,000 circles in 160 milliseconds
World at 100-km resolution
Quarter-continent at 10-km resolution
Requirement: 160-milliseconds
User studies show dropoff beyond that.
Question. Can we do that from:
Server on campus, Server in city, Server on
continent, Single Server for World?
Size And Speed
Server in
Building
Server in
City
Server on
Continent
Worldwide
Server
Request
Time
1 5 50 250
Fetch Time 20 20 20 20
Transmit
Time
8 30 300 1500
Draw Time 100 100 100 100
Total 129 155 470 1870
Time To Draw 30,000 Points in milliseconds. Goal: 150 ms
Deployment Options
Sparse Interaction/Small
data
Rich Interaction/Big Data
Powerful Client Anything Desktop Application
Any Client Classic Cloud GENI/Ignite Cloud
Size and Speed (30,000 points)
0 150
50 35 41 141
Using GENI
0
50 80 140
240
Size and Speed (10,000 points)
0 150
50 35 41 141
Using GENI
0
50 80 140
240
Size and Speed (30,000 points)
0 150
50 35 41 141
Using GENI
0
50 80
625
525
Using Standard Internet
Size and Speed (10,000 points)
0 150
50 15 20 50
Using GENI
0
50 60
120
170

More Related Content

Viewers also liked

Teori perbandingan politik. presidensial, parlementer, demokrasi.
Teori perbandingan politik. presidensial, parlementer, demokrasi.Teori perbandingan politik. presidensial, parlementer, demokrasi.
Teori perbandingan politik. presidensial, parlementer, demokrasi.
Yudi Prasetya
 
Sistem politik indonesia amandemen uud
Sistem politik indonesia amandemen uudSistem politik indonesia amandemen uud
Sistem politik indonesia amandemen uud
Yudi Prasetya
 

Viewers also liked (6)

Teori perbandingan politik. presidensial, parlementer, demokrasi.
Teori perbandingan politik. presidensial, parlementer, demokrasi.Teori perbandingan politik. presidensial, parlementer, demokrasi.
Teori perbandingan politik. presidensial, parlementer, demokrasi.
 
2015 listing inventory month to month the woodlands copy
2015 listing inventory month to month the woodlands copy2015 listing inventory month to month the woodlands copy
2015 listing inventory month to month the woodlands copy
 
Responsive, Scalable and Liquid Design
Responsive, Scalable and Liquid DesignResponsive, Scalable and Liquid Design
Responsive, Scalable and Liquid Design
 
Sistem politik indonesia amandemen uud
Sistem politik indonesia amandemen uudSistem politik indonesia amandemen uud
Sistem politik indonesia amandemen uud
 
How to recruit more reps into network marketing
How to recruit more reps into network marketingHow to recruit more reps into network marketing
How to recruit more reps into network marketing
 
Función de RRHH
Función de RRHHFunción de RRHH
Función de RRHH
 

Similar to Why geni

Fanug - Pragmatic Windows Phone Developer
Fanug - Pragmatic Windows Phone DeveloperFanug - Pragmatic Windows Phone Developer
Fanug - Pragmatic Windows Phone Developer
Sam Basu
 
TECHNICAL OVERVIEW NVIDIA DEEP LEARNING PLATFORM Giant Leaps in Performance ...
TECHNICAL OVERVIEW NVIDIA DEEP  LEARNING PLATFORM Giant Leaps in Performance ...TECHNICAL OVERVIEW NVIDIA DEEP  LEARNING PLATFORM Giant Leaps in Performance ...
TECHNICAL OVERVIEW NVIDIA DEEP LEARNING PLATFORM Giant Leaps in Performance ...
Willy Marroquin (WillyDevNET)
 
So Long Computer Overlords
So Long Computer OverlordsSo Long Computer Overlords
So Long Computer Overlords
Ian Foster
 
10 zig combined presentation deck v3
10 zig combined presentation deck v310 zig combined presentation deck v3
10 zig combined presentation deck v3
Jennifer Phillips
 

Similar to Why geni (20)

Energy Efficient Mobile Applications with Mobile Cloud Computing ( MCC )
Energy Efficient Mobile Applications with Mobile Cloud Computing ( MCC )Energy Efficient Mobile Applications with Mobile Cloud Computing ( MCC )
Energy Efficient Mobile Applications with Mobile Cloud Computing ( MCC )
 
New Framework for Improving Bigdata Analaysis Using Mobile Agent
New Framework for Improving Bigdata Analaysis Using Mobile AgentNew Framework for Improving Bigdata Analaysis Using Mobile Agent
New Framework for Improving Bigdata Analaysis Using Mobile Agent
 
EDGE COMPUTING
EDGE COMPUTINGEDGE COMPUTING
EDGE COMPUTING
 
Blewis Session 1 Fy10 Q3 Azure
Blewis  Session 1 Fy10 Q3 AzureBlewis  Session 1 Fy10 Q3 Azure
Blewis Session 1 Fy10 Q3 Azure
 
ThinClient
ThinClientThinClient
ThinClient
 
RTI Data-Distribution Service (DDS) Master Class 2011
RTI Data-Distribution Service (DDS) Master Class 2011RTI Data-Distribution Service (DDS) Master Class 2011
RTI Data-Distribution Service (DDS) Master Class 2011
 
IoT Story: From Edge to HDP
IoT Story: From Edge to HDPIoT Story: From Edge to HDP
IoT Story: From Edge to HDP
 
Welcome To The Mobile World
Welcome To The Mobile WorldWelcome To The Mobile World
Welcome To The Mobile World
 
Fanug - Pragmatic Windows Phone Developer
Fanug - Pragmatic Windows Phone DeveloperFanug - Pragmatic Windows Phone Developer
Fanug - Pragmatic Windows Phone Developer
 
Business impact of cloud computing
Business impact of cloud computingBusiness impact of cloud computing
Business impact of cloud computing
 
Cloud Basics.pptx
Cloud Basics.pptxCloud Basics.pptx
Cloud Basics.pptx
 
1. GRID COMPUTING
1. GRID COMPUTING1. GRID COMPUTING
1. GRID COMPUTING
 
Fog computing
Fog computingFog computing
Fog computing
 
TECHNICAL OVERVIEW NVIDIA DEEP LEARNING PLATFORM Giant Leaps in Performance ...
TECHNICAL OVERVIEW NVIDIA DEEP  LEARNING PLATFORM Giant Leaps in Performance ...TECHNICAL OVERVIEW NVIDIA DEEP  LEARNING PLATFORM Giant Leaps in Performance ...
TECHNICAL OVERVIEW NVIDIA DEEP LEARNING PLATFORM Giant Leaps in Performance ...
 
Classrooms - Anywhere, Anytime! - Geoff Green, MCPc
Classrooms - Anywhere, Anytime! - Geoff Green, MCPcClassrooms - Anywhere, Anytime! - Geoff Green, MCPc
Classrooms - Anywhere, Anytime! - Geoff Green, MCPc
 
So Long Computer Overlords
So Long Computer OverlordsSo Long Computer Overlords
So Long Computer Overlords
 
10 zig combined presentation deck v3
10 zig combined presentation deck v310 zig combined presentation deck v3
10 zig combined presentation deck v3
 
Introduction to Cloud computing
Introduction to Cloud computingIntroduction to Cloud computing
Introduction to Cloud computing
 
WEB APPLICATIONS 1.pdf
WEB APPLICATIONS 1.pdfWEB APPLICATIONS 1.pdf
WEB APPLICATIONS 1.pdf
 
Introduction to Azure DocumentDB
Introduction to Azure DocumentDBIntroduction to Azure DocumentDB
Introduction to Azure DocumentDB
 

More from David Lary

More from David Lary (10)

The West Africa-America Chamber of Commerce & Industries presents: Big Data &...
The West Africa-America Chamber of Commerce & Industries presents: Big Data &...The West Africa-America Chamber of Commerce & Industries presents: Big Data &...
The West Africa-America Chamber of Commerce & Industries presents: Big Data &...
 
The West Africa-America Chamber of Commerce & Industries presents: Sub sahara...
The West Africa-America Chamber of Commerce & Industries presents: Sub sahara...The West Africa-America Chamber of Commerce & Industries presents: Sub sahara...
The West Africa-America Chamber of Commerce & Industries presents: Sub sahara...
 
The West Africa-America Chamber of Commerce & Industries presents:
The West Africa-America Chamber of Commerce & Industries presents: The West Africa-America Chamber of Commerce & Industries presents:
The West Africa-America Chamber of Commerce & Industries presents:
 
West Africa-America Chamber of Commerce & Industries: E mist
West Africa-America Chamber of Commerce & Industries: E mistWest Africa-America Chamber of Commerce & Industries: E mist
West Africa-America Chamber of Commerce & Industries: E mist
 
Big Data & Machine Learning for Societal Benefit
Big Data & Machine Learning for Societal BenefitBig Data & Machine Learning for Societal Benefit
Big Data & Machine Learning for Societal Benefit
 
THRIVE: Pollution Viewer
THRIVE: Pollution ViewerTHRIVE: Pollution Viewer
THRIVE: Pollution Viewer
 
Machine Learning for Societal Applications
Machine Learning for Societal ApplicationsMachine Learning for Societal Applications
Machine Learning for Societal Applications
 
Machine Learning for Scientific Applications
Machine Learning for Scientific ApplicationsMachine Learning for Scientific Applications
Machine Learning for Scientific Applications
 
Aerial Vehicles, Machine Learning, Remote Sensing, and Optimized System Design
Aerial Vehicles, Machine Learning, Remote Sensing, and Optimized System DesignAerial Vehicles, Machine Learning, Remote Sensing, and Optimized System Design
Aerial Vehicles, Machine Learning, Remote Sensing, and Optimized System Design
 
Requirements for next generation of Cloud Computing: Case study with multiple...
Requirements for next generation of Cloud Computing: Case study with multiple...Requirements for next generation of Cloud Computing: Case study with multiple...
Requirements for next generation of Cloud Computing: Case study with multiple...
 

Recently uploaded

Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Victor Rentea
 

Recently uploaded (20)

MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024
 
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodPolkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
 
CNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In PakistanCNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In Pakistan
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
 
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 AmsterdamDEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor Presentation
 
Platformless Horizons for Digital Adaptability
Platformless Horizons for Digital AdaptabilityPlatformless Horizons for Digital Adaptability
Platformless Horizons for Digital Adaptability
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...
 
Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of Terraform
 

Why geni

  • 2. Visualize Big Data Fast Any Device Anywhere Collaboratively
  • 3. Size and Speed Target: 0.15 seconds * * N. Tolia, D. G. Andersen, and M. Satyanarayanan. Quantifying interactive user experience on thin clients. Computer, 39(3):46–52, 2006.
  • 4.
  • 5.
  • 6. Conclusion Same Building is Best Same “City” (State) is OK Same Continent Won’t Fly One Big Server = World Wide Wait
  • 7. Meaning For Collaboration Server must be in same location as user Distributed Collaboration: users can be anywhere Means server requirement: servers must be everywhere
  • 8. System Setup < 10 ms, > 100 mb/s Replicated Databases
  • 10. Distributed Collaboration Around Big Data “A World Where Distance is Eliminated” Experts Around the World Interacting With Data Visualizations as Easily as if They Were in the Same Room Previously: Expensive Hardware (OptIPortal, CAVE) over Expensive, Special-Purpose Networks GENI: Any Device, Anywhere, Anytime, through a Web browser
  • 11. Collaboration Around Big Data All About Size and Speed - Data Set: 4 million points per month - 100 MB/month Too Much Data For Laptop Way Too Much for Tablet/Phone/Netbook Need Server Close to User How Close Depends on Bandwidth
  • 12. Size and Speed Task: Draw 30,000 circles in 160 milliseconds World at 100-km resolution Quarter-continent at 10-km resolution Requirement: 160-milliseconds User studies show dropoff beyond that. Question. Can we do that from: Server on campus, Server in city, Server on continent, Single Server for World?
  • 13. Size And Speed Server in Building Server in City Server on Continent Worldwide Server Request Time 1 5 50 250 Fetch Time 20 20 20 20 Transmit Time 8 30 300 1500 Draw Time 100 100 100 100 Total 129 155 470 1870 Time To Draw 30,000 Points in milliseconds. Goal: 150 ms
  • 14. Deployment Options Sparse Interaction/Small data Rich Interaction/Big Data Powerful Client Anything Desktop Application Any Client Classic Cloud GENI/Ignite Cloud
  • 15. Size and Speed (30,000 points) 0 150 50 35 41 141 Using GENI 0 50 80 140 240
  • 16. Size and Speed (10,000 points) 0 150 50 35 41 141 Using GENI 0 50 80 140 240
  • 17. Size and Speed (30,000 points) 0 150 50 35 41 141 Using GENI 0 50 80 625 525 Using Standard Internet
  • 18. Size and Speed (10,000 points) 0 150 50 15 20 50 Using GENI 0 50 60 120 170