Introducing the

1. Introducingthe Prof. MartaKwiatkowska Launched 7th May, 2003 www.MeSC.ac.uk

2. Overview • The Midlands e-Science Centre • Area of ExcellenceModelling 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 ofglobalcomputer • 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 distributedsimulation • 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 mobileprocesses • from concurrency formalisms to modelling particulateprocesses • 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 • 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 Microprocessor Size 7.5x3.5mm Millions of transistors on chip Errors found after manufacture (cf Intel) 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 socialprocesses, modelling and complexorganisations (e.g. hospitals) • uses agent technology and evolutionary computation • real-time disaster management response with the Grid • Research in Natural Computation Group • also includesneural 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 immuneresponse • 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/atmospheric.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 • Modelling and Simulation (DEM) of Particulate Processes • discontinuous, composed of manymillions 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 Pharmaceuticals, foods, powders, aerosols, soils, ... www.eng.bham.ac.uk/chemical/

17. Colliding black holes (courtesy NCSA) Complexity in… the Universe Einstein’s 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. LIGO - Livingston 4km 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. 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.htm,www.phys.warwick.ac.uk/molecularsim/home.html

20. Research examples: Coventry Control methods for improving annealing furnace • Control, optimisation • Industrial collaborators • Corus, Jaguar, Rolls-Royce, TRW, Walsgrave Hospitals NHS Trust, etc • Funding from • EPSRC, DTI and HEFCE

21. Research examples: Wolverhampton Simulation of a new hip and joint replacement. VR simulation of a prototype gear assembly.

22. 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 • IntegrativeBiology (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)

23. 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

24. 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