Introducing the Prof. Marta Kwiatkowska Launched 7th May, 2003 www.MeSC.ac.uk 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 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... 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 – – – – mathematical modelling computational modelling, simulation high-performance visualisation collaboration • Solutions • Delivery via e-Science – harness the power of global computer – answers in real-time Model ⇓ Simulate ⇓ Predict ⇓ Control ⇓ Avoid disaster 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 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 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 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 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 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 www.vista.bham.ac.uk/index.htm Part of the internal structure of a hydrogen atom. Image fusion of a series of MRI scans. 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/ 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 www.irit.fr/COSI/, www.cs.bham.ac.uk/research/NC/ Real situation ⇓ Model ⇓ Agent-based simulation Complexity in… the Human Genome • Modelling of biology of immune response – large-scale genomics Integrin PS1 Filamin – data mining, computationally intensive Paxillin PS2 Profilin – modelling physiology of the immune response IL-2 – understanding molecular basis Calmodulin • Research in ImmunoGenomics Group – gene expression profiling, infection modelling Cancer Research – childhood cancer Notch 4 Connexin Calcineurin Adenosine A2B Receptor Components of a probabilistic model describing a lymphocyte in a chronic inflammatory disease www.irit.fr/COSI/, www.cs.bham.ac.uk/research/NC/ 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/ 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 www.mat.bham.ac.uk/research/applied/applied1.htm Laser-generated bubble near boundary 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/ 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. Colliding black holes (courtesy NCSA) 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) LIGO - Livingston 4km • 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/ 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 Relativistic Heavy Ion Collider (RHIC) • RHIC at the Brookhaven National Laboratory, NY, USA. PHOBOS PHENIX RHIC BRAHMS STAR New York 50 miles AGS Birmingham 2500 miles TANDEMS Nuclear Physics and e-Science A “digital picture” of a collision. • Grid technology essential – international collaboration – computationally intensive tasks Run: 1186017, Event 32 • 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 www.np.ph.bham.ac.uk, www.star.bnl.gov, www.bnl.gov/rhic end view 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/Computer 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 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 Research examples: Wolverhampton Simulation of a new hip and joint replacement. VR simulation of a prototype gear assembly. 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) 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 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