virtual laboratory for e-science (vl-e)
DESCRIPTION
vrije Universiteit. Virtual Laboratory for e-Science (VL-e). Henri Bal Department of Computer Science Vrije Universiteit Amsterdam [email protected]. Outline. e-Science and virtual laboratories The VL-e project VL-e and networking Case studies: Visualization - PowerPoint PPT PresentationTRANSCRIPT
Virtual Laboratory fore-Science (VL-e)
Henri Bal
Department of Computer ScienceVrije Universiteit Amsterdam
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
PU
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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