Introducing the

1
Introducing the

• Prof. Marta Kwiatkowska
• Launched 7th May, 2003
• www.MeSC.ac.uk

2
Overview

• The Midlands e-Science Centre
• Area of Excellence Modelling and Analysis of
  Large Complex Systems
• Applications focus, rather than Grid middleware
• Hope to work with Grid middleware developers
• Partner institutions
• University of Birmingham
• University of Warwick, Centre for Scientific
  Computation
• University of Coventry
• University of Wolverhampton
• Infrastructure and resources
• Projects
• Next steps

3
Complex systems

• New field of science - study how parts of a
  system give rise to the collective behaviours,
  and how it interacts with its environment.
• Social science, medicine, weather, engineering,
  economy, management...

4
Meeting the complexity challenge

• Why study and analyse?
• knowledge, discovery, prediction
• Sources of complexity
• millions of components
• huge data sets
• interaction, motion in space
• unpredictability
• Solutions
• mathematical modelling
• computational modelling, simulation
• high-performance visualisation
• collaboration
• Delivery via e-Science
• harness the power of global computer
• answers in real-time

Model ? Simulate ? Predict ? Control ? Avoid
disaster
5
The Midlands e-Science Centre

• Virtual Centre
• open, possible still to join
• University of Birmingham
• home Computer Science
• Physics and Astronomy
• Chemical Sciences
• Biosciences
• Engineering
• Geography, Earth and Env. Sci.
• Mathematics and Statistics
• Medical School
• Information Services
• University of Warwick
• Centre for Scientific Computing
• University of Coventry
• University of Wolverhampton

6
MeSC objectives

• Connect the Midlands
• provide accessibility and connectivity for the
  Grid for the Midlands region
• Excellence in Complex Systems
• focus on modelling of very large complex systems
• act as source of relevant expertise for industry
• Enable long-term research
• numerical algorithms
• simulation techniques for the Grid
• Foster collaboration
• different disciplines in science and engineering
• academics and industry

7
Research at MeSC

• Research themes
• Simulation of evolving systems of interacting
  components
• Large-scale Grid-enabled distributed simulation
• Mathematical solutions of large complex systems
• Data mining and large-scale visualisation
• Hope to stimulate crossover of techniques
• from evolutionary techniques to organisation
  management
• from physics motion models to understanding
  mobile processes
• from concurrency formalisms to modelling
  particulate processes
• from algorithms research to bioinformatics
• etc

8
People at MeSC

• Management Board
• Marta Kwiatkowska, CS, Director
• Peter Watkins, Phys
• Peter Knowles, Chem
• Georgios Theodoropoulos, CS
• Andrew Chan, Eng
• John Owen, IS
• Peter Taylor, CSC, Warwick
• Keith Burnham, Eng, Coventry
• Richard Hall, Eng, Wolverhampton
• Technical/User Support
• Paul Hatton, IS
• Steve Jarvis, CS, Warwick
• PDRA (offer made)
• Many more existing/potential collaborators

9
Infrastructure

• Networking
• High-speed campus network, multi-million pound
  investment (SRIF and University)
• midMAN
• Computing facilities
• SRIF-2 funding, 200K, currently considering
  future strategy
• About to purchase dedicated cluster for e-Science
  Centre
• HPC facility at Birmingham, and various clusters
• Access Grid Node
• at Birmingham (2x), Warwick and Wolverhampton
• for virtual meetings and and collaboration
• VISTA
• State-of-the-art visualisation centre

10
Visual and Spatial Technology Centre

• Set up in partnership with HP
• 4M investment
• Association with several industrial partners
  (AVS, CFX, Fakespace, etc)
• Scientific visualisation
• geodata, medical imaging
• Information visualisation
• knowledge discovery
• Data representation
• understanding complex data
• Immersive environments

Part of the internal structure of a hydrogen
atom.
Image fusion of a series of MRI scans.
www.vista.bham.ac.uk/index.htm
11
Complexity in Hardware Design
Microprocessor Size 7.5x3.5mm Millions of
transistors on chip Errors found after
manufacture (cf Intel)

• Research in Modelling and Analysis of Systems
  Group
• distributed simulation to assess performance
• automatic verification to ensure no design errors
• also can find errors in software (security
  protocols, etc)
• funding from EPSRC, DTI, QinetiQ, BT, EU
• The Grid technology enables
• larger models, faster analysis, improved
  reliability
• reduced costs time to manufacture

www.cs.bham.ac.uk/research/systems/,
www.cs.bham.ac.uk/gkt/Research/par-lard/
12
Complexity in Social Science

• Managing complex social scenarios
• develop new ways of thinking about social
  processes, modelling and complex organisations
  (e.g. hospitals)
• uses agent technology and evolutionary
  computation
• real-time disaster management response with the
  Grid
• Research in Natural Computation Group
• also includes neural networks, evolvable
  hardware, self-organising systems, ...
• funding from EPSRC, EU, Advantage West Midlands,
  Marconi, Honda

Real situation ? Model ? Agent-based simulation
www.irit.fr/COSI/, www.cs.bham.ac.uk/research/NC/
13
Complexity in the Human Genome

• Modelling of biology of immune response
• large-scale genomics
• data mining, computationally intensive
• modelling physiology of the immune response
• understanding molecular basis
• Research in ImmunoGenomics Group
• gene expression profiling, infection modelling
• Cancer Research
• childhood cancer

Components of a probabilistic model describing a
lymphocyte in a chronic inflammatory disease
www.irit.fr/COSI/, www.cs.bham.ac.uk/research/NC/
14
Complexity in Urban Pollution Control

• Difficult to model
• air movement in street
• effect of road dust
• The Grid technology
• better accuracy
• feasibility of response on regional/national
  scale

Concentration of pollutants in street lanes

• Research in Climate and Atmospheric Research and
  Wind Engineering Groups
• various project concerning the effect of wind,
  turbulence, dispersion of particles, etc
• large eddy simulation
• funding from NERC, EPSRC, industry

www.ges.bham.ac.uk/research/physical/Atmospheric/a
tmospheric.htm, www.eng.bham.ac.uk/civil/
15
Complexity in Fluids and Flows

• Modelling bubble formation
• relevant for laser surgery, bubble contrast
  agents in ultrasound imaging, underwater
  explosions, water waves, ship bow waves, etc
• computationally demanding, would benefit from the
  Grid
• Research in Applied Mathematics Group
• also detonation and flame processes (Fuel Cells,
  to be displayed at Royal Society)
• cancer modelling
• funding from EPSRC, Kodak, Unilever, Nestle,
  Pilkingtons, etc

Laser-generated bubble near boundary
www.mat.bham.ac.uk/research/applied/applied1.htm
16
Complexity in Granular Substances

• Pharmaceuticals,
• foods,
• powders,
• aerosols,
• soils, ...

• Modelling and Simulation (DEM) of Particulate
  Processes
• discontinuous, composed of many millions of
  particles
• particles interact in various ways
• aim to calculate properties of substance
  elasticity, texture, feel
• Grid technology needed because of sheer scale of
  models
• Research in Chemical and Civil Engineering
• funding from EPSRC, Cadbury, Unilever, BNFL

www.eng.bham.ac.uk/chemical/
17
Complexity in the Universe

• Einsteins Theory of General Relativity
• Mass-energy produces space-time warpage
• Black hole collisions, Supernovae,
• The Big Bang, ...
• Gravitational waves are time dependent
  gravitational fields produced by the acceleration
  of masses.

18
Gravitational Waves and e-Science

• Measure the stretch and squeeze of space with
  light beams, approx. 10-16 cm
• Signals drastically dominated by noise
• Extract signals from the noise while keeping up
  with the data flow (approx. a few Mb/sec)

• Research in Gravitational Waves Group
• partners in LIGO and LISA international
  scientific collaborations
• funding from PPARC
• Grid technology the only solution

www.sr.bham.ac.uk/research/gravity/,
www.ligo.caltech.edu/, http//lisa.jpl.nasa.gov/
19
Complexity in the Atom

• Collide heavy nuclei (e.g. Gold)
• Achieve temperatures that are a million times
  hotter than the centre of the sun - as in the
  early universe
• Aim to discover the plasma phase of nuclear matter

459 collaborators
49 institutions
12 countries
Birmingham is the only UK institution
The STAR collaboration
20
Relativistic Heavy Ion Collider (RHIC)

• RHIC at the Brookhaven National Laboratory, NY,
  USA.

PHOBOS
BRAHMS
RHIC
PHENIX
STAR
New York 50 miles
AGS
Birmingham 2500 miles
TANDEMS
21
Nuclear Physics and e-Science
A digital picture of a collision.

• Grid technology essential
• international collaboration
• computationally intensive tasks
• High-speed networks essential
• data volume 1 TB/day for approx. 20 wks/yr(1
  TB 1,000,000,000,000 bytes approx.)
• data mining necessary
• distribution of datasets for detailed analysis

Run 1186017, Event 32
end view
www.np.ph.bham.ac.uk, www.star.bnl.gov,
www.bnl.gov/rhic
22
Research examples Warwick

• New methods for quantum-chemical calculations
  (Chemistry/Maths)
• Monte Carlo simulation of condensed matter
  (Physics/Statistics)
• Analysis of turbulence simulations distributed
  data visualisation via the Grid
  (Eng/Maths/Com-puter Science)

Studying molecular properties of aromatic
systems with DALTON.
Simulation of molecular structures and
interactions.
http//qcwizards.warwick.ac.uk/taylor/research.ht
m, www.phys.warwick.ac.uk/molecularsim/home.html
23
Research examples Coventry

• Control, optimisation
• Industrial collaborators
• Corus, Jaguar, Rolls-Royce, TRW, Walsgrave
  Hospitals NHS Trust, etc
• Funding from
• EPSRC, DTI and HEFCE

• Control methods for improving annealing furnace

24
Research examples Wolverhampton
Simulation of a new hip and joint replacement.
VR simulation of a prototype gear assembly.
25
Projects

• At Birmingham
• GridPP
• LIGO LISA (GW) and STAR (Nuclear Physics)
• Grid-enabled distributed simulation and numerical
  solutions
• COSI (Complexity in Social Sciences, EU)
• BioSimGrid
• Integrative Biology (cancer modelling, fluid
  dynamics)
• e-TUMOUR (EU FP6 IP)
• Bioinformatics (Bioinformatics Regional
  Institute)
• Randomised trials (Primary Care, national
  network)
• Pollution modelling and control (Geography and
  Env. Science)

26
Projects continued

• At Warwick
• PACE, Performance Analysis and Characterisation
  Environment
• Molecular modelling
• Turbulence
• At Coventry
• Biomedical engineering
• Industrial control, optimisation
• At Wolverhampton
• VR
• Simulation for manufacturing, SMEs

27
Next steps

• Infrastructure improvements
• AGN rooms, dedicated cluster, etc
• Application areas
• medical applications
• bioinformatics
• pervasive e-Science? (sensor networks, mobile
  wearable computing)
• industrial solutions
• etc
• Collaborate and build on collaborations
• with other e-Science centres
• collaborate with e-Science ontology, workflow and
  visualisation tool developers