ICT infrastructure for Science:

e-Science developments

Henri Balbal@cs.vu.nl

Vrije Universiteit Amsterdam

Outline

● What is e-Science?● Virtual Laboratory for e-Science (VL-e)● Research infrastructure of VL-e● Some VL-e results● Future developments in the

Netherlands

Science is changing

● System level science● the integration of diverse sources of knowledge about the

constituent parts of a complex system with the goal of obtaining an understanding of the system's properties as a whole [Ian Foster]

● Multidisciplinary research● Each discipline can solve only part of a problem● Collaborations betweens distributed research

groups

● Research driven by (distributed) data● Data explosion, both volume and complexity

Examples

● Functioning of the cell for system biology● Cognition● Cancer research● Cohort studies in medicine (biobanking)● Discovery of biomarkers for drug design● Ecosystems/biodiversity● Studies of water/air pollution● Study black matter

e-Science

● Goal: allow scientists to collaborate in experiments and integration of research● Enable system level science

● Design methods to optimally exploit underlying infrastructure● Hardware (network, computing,

datastorage)● Software (web, grid middleware)

e-Science in context

Sytem levelexperiments

e-Science

Infrastructure

Web/grid software

Virtual Laboratory fore-Science (VL-e)

● 40 M€ BSIK project (2004-2009)● Generic application support

● Application cases are drivers for computer & computational science and engineering research

● Re-use of components via generic solutions

● Rationalization of experimental process● Reproducible & comparable

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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VL-e

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

Virtual Lab.rapid prototyping

(interactive simulation)

Additional Grid Services

(OGSA services)

The VL-e infrastructure

Proof-of-Concept Rapid Prototyping

(DAS-3)

DAS-3 272 nodes(AMD Opterons)

792 cores1TB memoryLAN: Myrinet 10G Gigabit

EthernetWAN: 20-40 Gb/s

OPN

● Applications can dynamically allocate light paths and change the topology of the wide-area network

● Applications: model checking, game tree search, processing CineGrid data (4K video)● Kees Verstoep’s talk (yesterday)

Grid Middleware

SurfnetNetwork Service

(lambda networking)

Virtual Laboratory

VL-E Experimental Environment

VL-E Proof of concept Environment

Rapid prototyping(interactive simulation)

Additional Grid Services

(OGSA services)

Grid Middleware

Surfnet

Virtual Laboratory

Big Grid

BiG Grid

Outline

● What is e-Science?● Virtual Laboratory for e-Science (VL-e)● Research infrastructure of VL-e● Some VL-e results

● Applications● Generic application support

(middleware)

● Future developments in the Netherlands

Functional MRI: Analysis

MR scanner

Brain activation maps

Stimulus System for Cognitive research

fMRI scan Group Activation Map

Intr

o f

MR

I

• Large datasets, many instances• Computation demanding analysis• Distributed resources (scanning, analysis)• Collaboration (data, methodology)

Medical Diagnosis and ImagingProblem Solving Environment

VL-e generic services:• Provides:

– Scientific visualization techniques– SRB– Resource browsing– Workflow management– Job submission– Data querying

• Uses:– V Browser on SRB

– Parallel processing techniques

– VLAM

Application specific services:

• Access to PACS, DICOM

• Interfaces to medical scanners (MRI)

• In-house developed algorithms:– Eddy Current Reduction

– Matched Masked Bone Elimination

• Authentication & authorization

Grid Middleware

Surfnet

Virtual Laboratory

VL-e Environment

… MedicalApplications

…

Grid services:

• Storage facilities

• High Performance Computing platforms

• High Performance Visualization

StimulusSystem

3 Tesla MRI

Dynamicbird behaviour

MODELS

Bird distributionsEnsembles

Calibration andData assimilation

Predictions and on-linewarnings

RADAR

Bird behaviour in relation to weather and landscape

Ibis – Grid programming

● Goal:● drastically simplify grid

programming/deployment

● applications running on many co-allocated resources (``grids as promised’’)

Ibis system

Ibis applications● e-Science (VL-e)

● Brain MEG-imaging● Mass spectroscopy● Grammar learning

● Multimedia content analysis● Other programming systems

● Workflow engine for astronomy (D-grid), grid file system, ProActive, Jylab, …

Multimedia content analysis

● Analyzes video streams to recognize objects

● Extract feature vectors from images● Describe properties (color, shape)● Data-parallel task implemented with C+

+/MPI

● Compute on consecutive images● Task-parallelism on a grid

MMCA

‘Most Visionary Research’ award at AAAI 2007, (Frank Seinstra et al.)

Discussion about infrastructure

● Need well-balanced infrastructure supporting compute/data/network-intensive applications

● Generic software is part of the infrastructure● Key to obtain flexibility

● Organization is important, different roles● Application experiments● Computer Science experiments● Production

● Building infrastructure is research in itself

Next: national e-Science centre?

● Coordinate e-Science research● Software services needed for e-Science● Organize support● Help in developing policies for

infrastructure