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vrije Universiteit. Virtual Laboratory for e-Science (VL-e). Henri Bal Department of Computer Science Vrije Universiteit Amsterdam [email protected] e-Science. Web is about exchanging information Grid is about sharing resources Computers, data bases, instruments, services

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Virtual laboratory for e science vl e

vrije Universiteit

Virtual Laboratory fore-Science (VL-e)

Henri Bal

Department of Computer ScienceVrije Universiteit Amsterdam

[email protected]


E science

e-Science

  • Web is about exchanging information

  • Grid is about sharing resources

    • Computers, data bases, instruments, services

  • e-Science supports experimental science by providing a virtual laboratory on top of Grids


Virtual laboratory for e science vl e

Grid

Harness multi-domain distributed resources

Virtual Laboratories

Distributed computing

Application

Specific

Part

Application

Specific

Part

Application

Specific

Part

Visualization & collaboration

Potential Generic

part

Potential Generic

part

Potential Generic

part

Management

of comm. &

computing

Virtual Laboratory

Application oriented services

Management

of comm. &

computing

Management

of comm. &

computing

Knowledge

Data & information


Virtual laboratory for e science

User Interfaces &

Virtual reality

based visualization

Virtual Laboratory for e-Science

Bio-diversity

Telescience

Food Informatics

Bio-Informatics

Data Intensive

Science

Medical diagnosis &

imaging

Interactive

PSE

Adaptive

information

disclosure

Virtual lab. &

System integration

Collaborative

information

Management

High-performancedistributed computing

Security & Generic

AAA

Optical Networking


The vl e project

vrije Universiteit

The VL-e project

  • 20 partners

  • Academic - Industrial

  • 40 M€ (20 M€ BSIK funding)

  • 2004 - 2008


Virtual laboratory for e science vl e

VL-e environments

Application

specific

service

Medical

Application

Telescience

Bio ASP

Application

Potential

Generic service

&

Virtual

Lab. services

Virtual Lab.

rapid prototyping

(interactive simulation)

Virtual Laboratory

Additional

Grid Services

(OGSA services)

Grid Middleware

Grid

&

Network

Services

Network Service

(lambda networking)

Gigaport

VL-E Proof of concept Environment

VL-E Experimental Environment


Vl e workshop

Belleman

Marshall, Breit

Konijnenburg

Visualization

Jansen

Bouwhuis

demo

VL-e workshop

Telescience

Food

Bio-Inf

Medical imaging

Data Intensie

Bio-div

P4: Scaling up

i PSE

A.I.D.

Virtual lab

CIM

High-performancedistributed computing

Security

Optical Networking


Interactive problem solving environments

ui (VRE)

MRI, PET

Monolith, Cluster

Cave, Wall, PC, PDA

From Medical Image Acquisition to Interactive Virtual Visualization…

Simulated blood flow

MR image

Patient at MRI scanner

MR image

Segmentation

Shear stress, velocities

GVK

LB Solver

Medical Data

MD login and Grid Proxy creation

Bypass creation

LB mesh

generation

Job submission

ce (e.g., Bratislava)

ce (e.g., Valencia)

se (e.g., Leiden)

  • P.M.A. Sloot, A.G. Hoekstra, R.G. Belleman, A. Tirado-Ramos, E.V. Zudilova, D.P. Shamonin, R.M. Shulakov, A.M. Artoli , L. Abrahamyan

Interactive Problem Solving Environments

Virtual Node navigation

Job monitoring

Simulated Blood Flow

VRE


Virtual laboratory for e science vl e

Visualization on the Grid


Virtual laboratory for e science vl e

Visualization on the Grid


Virtual laboratory for e science vl e

Visualization on the Grid


Virtual laboratory for e science vl e

Visualization on the Grid


Virtual laboratory for e science vl e

Visualization on the Grid


High performance distributed computing

High-PerformanceDistributed Computing

  • Ibis: a Java-centric grid programming environment

    • Remote Method Invocation (RMI), group communication, divide&conquer parallelism, object migration (ProActive)

  • Written in pure Java, runs on heterogeneous grids

    • “Write once, run everywhere ”

    • Use bytecode rewriting for optimizations (e.g. serialization)

    • Use native code as special-case optimization (e.g. Myrinet)


Experiences with ibis

Experiences with Ibis

  • Distributed supercomputing applications

    • Electromagnetic simulation (Jem3D)

    • Automated protein identification (AMOLF)

    • N-body simulations, SAT-solver, raytracer

  • Successful grid experiments

    • On DAS-2 (homogeneous Dutch grid)

    • On GridLab (European grid)

  • Need co-allocation mechanisms

More info + distribution at www.cs.vu.nl/ibis


Optical networking

CPU’s

R

CPU’s

R

CPU’s

R

NOC

CPU’s

R

CPU’s

R

Optical networking

  • Formally part of GigaPort-NG BSIK project

  • Studies optical networking technology in a grid context (e.g., bandwidth-on-demand)

  • Useful for many VL-e applications

    • Data-intensive sciences, visualization,HPDC, etc.


Workshop program

Workshop program

  • 14:15 - 14:45 Workflow and data integration in e-bioscience: Some user requirements (Scot Marshall)

  • 14:45 - 15:15 The Knowledge Grid and Adaptive Information Disclosure (Machiel Jansen)

  • 15:15 - 15:45 Data management in the Proof-of-Concept environment of VL-e (Maurice Bouwhuis)

  • 15:45 - 16:00 Presentation of the Demos

  • 16:00 - 16:30 Break & Demo at the LightHouse (SARA+UvA)

  • 16:30 - 17:00 Medical Application (Robert Belleman)

  • 17:00 - 17:30 Bioinformatics (Timo Breit)

  • 17:30 - 18:00 Dutch Tele-science Lab (Marco Konijnenburg)


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