1. RealityGrid Peter Coveney 1 and John Brooke 2 1. Centre for Computational Science, Department of Chemistry, Queen Mary, University of London 2. Manchester Research Centre for Computational Science, University of Manchester

2. 2 The Problem Simulation time: days. Analysis time: months Ability to generate data outstrips our ability to understand it by several orders of magnitude

3. 3 RealityGrid Aim Using grid technology to closely couple high performance computing, high throughput experiment and visualization, RealityGrid will move the bottleneck out of the hardware and back into the human mind.

4. 4 E-Science Framework Code meta Verification, Optimisation & Scheduling Visual Programming Environment Code Distributed Component Repository Globus Execution Environment Meta-data: Software interface and component performance Performance feedback through GrADS & APART into meta-data

5. Layered Architecture Applications / Problem Solving Environments Grid Services HBMGASS Grid Fabric LSF MPI NQE Application Toolkits GlobusView Solaris GSI-FTPMDS Grid Resources Linux PBS GSIGRAM DUROCMPICH-Gglobusrun ManchesterImperial College EPCCOxford QMLoughborough Manchester QM-LUSI/XMT UNICOSIRIXTru64 SRB LUSI PortalComponent RepositoryVisualization & SteeringComputational PSE Component FrameworkVIPAR

6. 6 Integrated experiments Scientific discovery can be enhanced by closely coupling computation and experiment RealityGrid includes two such experimental components: –X-ray microtomography : produces 3D X-ray attenuation maps of specimens at a microscopic level –London University Search Instrument (LUSI) a materials combinatorial science laboratory for study of ceramic materials

7. 7 X-ray Microtomography Simulation, visualization and data gathering coupled via RealityGrid Expensive synchrotron beam time resources optimally used to obtain sufficient resolution for simulation Local testbed providing grid enablement model for European synchrotron facility

8. 8 LUSI firsts Almost all drug design is now done in a combinatorial manner LUSI is the first instrument to apply this technique to materials science problems. LUSI provides high volume experimental data directly to the high performance analysis tools enabled by the grid. Grid enabling LUSI will allow researchers from other institutions to add to and mine from its unique database.