Virtual Laboratory fore-Science (VL-e)

Henri Bal

Department of Computer ScienceVrije Universiteit Amsterdam

bal@cs.vu.nl

vrije Universiteit

Outline

• e-Science and virtual laboratories• The VL-e project• VL-e and networking• Case studies:

o Visualizationo Interactive problem solving environments o Distributed supercomputing

• Computing/networking infrastructure

e-Science

• Web is about exchanging information

• Grid is about sharing resourceso Computers, data bases, instruments, services

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

Managementof comm. & computing

Managementof comm. & computing

Managementof comm. & computing

Potential Genericpart Potential Generic

partPotential Generic

part

ApplicationSpecific

Part

ApplicationSpecific

Part

ApplicationSpecific

Part

Virtual Laboratory Application oriented services

GridHarness multi-domain distributed resources

Virtual LaboratoriesDistributed computing

Visualization & collaboration

Knowledge

Data & information

Optical NetworkingHigh-performance

distributed computingSecurity & Generic

AAA

Virtual lab. &System integration

Interactive PSE

Collaborative information Management

Adaptive information

disclosure

User Interfaces & Virtual reality

based visualization

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Virtual Laboratory for e-Science

The VL-e project• 40 M€ (20 M€ BSIK funding)• 2004 - 2008

vrije Universiteit

• 20 partners• Academic - Industrial

VL-e and networking

• e-Science applications generate much (distributed) datao High-resolution imagingo Bio-informatics querieso Particle physics:

o Currently: 1 PByte per yearo LHC (2007): 10-30 PByte per year

• Virtual laboratories need high-speed networks foro Remote visualization o Interactive problem solving environmentso Distributed supercomputing

VL-e and networking

Optical NetworkingHigh-performance

distributed computingSecurity

Virtual labi PSE CIMA.I.D. Visualization

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Visualization on the Grid

Visualization on the Grid

Visualization on the Grid

Visualization on the Grid

Visualization on the Grid

MRI, PET Monolith, Cluster Cave, Wall, PC, PDA

From Medical Image Acquisition to Interactive Virtual Visualization…

MD login and Grid Proxy creation

Bypass creation LB mesh generation

Job submission Job monitoring

Virtual Node navigation Simulated

Blood Flow

Patient at MRI scanner

MR image MR image Segmentation

Shear stress, velocitiesSimulated blood flow

se (e.g., Leiden)ce (e.g., Valencia) ce (e.g., Bratislava)

ui (VRE)

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

Distributed supercomputing (parallel computing on grids)

VU (72 nodes) UvA (32)

Leiden (32) Delft (32)

GigaPort

Utrecht (32)

DAS-2

Distributed ASCI Supercomputer 2

Distributed supercomputing (parallel computing on grids)

• Can grids be used for High-Performance Computing applications that are not trivially parallel?

• Key: grids usually are hierarchicalo Collections of clusters, supercomputerso Fast local links, slow wide-area links

• Can optimize algorithms to exploit this hierarchyo Message combining + latency hiding on wide-area linkso Optimized collective communication operations (broadcast etc.)o Often gives latency-insensitive, throughput-bound algorithms

HPC on a grid?

Ibis: a Java-centric grid programming environment

• Written in pure Java, runs on heterogeneous gridso “Write once, run everywhere ”

• Many applications:o Electromagnetic simulation (Jem3D)o Automated protein identification

(VL-e application from AMOLF)o N-body simulationso SAT-solvero Raytracer

Jem3D (see SC’04)

Available from www.cs.vu.nl/ibis

Networking demands

• Low latency is needed foro Interactive visualizationo Interactive Problem Solving Environmentso Synchronous, latency-sensitive parallel algorithms

• High throughput is needed foro Data-intensive e-Science applicationso Visualization of large data setso Asynchronous, throughput-bound parallel algorithms

• Efficient collective (group) communication foro Collaborative visualization between multiple siteso Collective operations in parallel algorithms

Outline

• e-Science and virtual laboratories• The VL-e project• VL-e and networking• Examples:

o Visualizationo Interactive Problem Solving Environments o Distributed supercomputing

• Computing/networking infrastructure

Grid Middleware

Gigaport Network Service (lambda networking)

Application specificservice

Application Potential

Generic service &

Virtual Lab. services

Grid &

NetworkServices

Virtual Laboratory

VL-E Experimental Environment

VL-E Proof of concept Environment

Telescience Medical Application Bio ASP

Virtual Lab.rapid prototyping

(interactive simulation)

Additional Grid Services

(OGSA services)

VL-e environments

DAS-3

• Proposed next generation grid in the Netherlands• Partners:

o ASCI research school (VU, UvA, TU Delft, Leiden)o Gigaport-NG/SURFnet: DWDM computer backplane

(dedicated optical group of 8 lambdas)o VL-e and MultimediaN BSIK projects

• Topology controlled by applications through the Network Operations Center

DAS-3C

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Summary

• VL-e (Virtual Laboratory for e-Science) studies entire e-Science chain, including applications, middleware and grids

• High networking demands from applications and generic methods

• New state-of-the-art Grid infrastructure planned for 2006 using optical networking