1. Presenter: Sabine Roller [roller@hlrs.de] Coordinator: Hubert Hérenger [herenger@hlrs.de] High Performance Computing Center Stuttgart (HLRS) Business Experiment 06 - Groundwater Modelling Providing better forecast possibilities in groundwater modelling using optimization and grid technologies

2. Business Experiments in GRID 2 Project Data Sheet Type of project: Integrated Project Project coordinator: Mr. Santi Ristol santi.ristol@atosorigin.com (ATOS ORIGIN) Project start date: 1st June 2006 Duration: 42 months (Nov 2008) Budget: 24.7 M Euros Max EC contribution: 15.7 M Euros (63%) Consortium: 75 partners Effort: 2713 PM (226 PY,65 P,360.000h) The mission of BEINGRID is to Exploit European Grid middleware by creating a toolset repository of Grid services from across the Grid research domain and to use these services to deliver a set of successful business experiments that stimulate the early adoption of Grid technologies across the European Union.

3. Business Experiments in GRID 3 Business Experiment 06 BE06 Goals: –Large scale multidisciplinary compute grid –Improved prediction via Grid technologies –Business models for license management –Designing, implementing and validating solution BE Details: –Duration: 20 months –Economic sector: SMEs providing services for groundwater modelling –Grid middleware: Globus Toolkit 4, Unicore/GS

4. Business Experiments in GRID 4 Decision problems related to groundwater important resource for water supply important component of aquatic environment endangered world-wide by depletion due to overexploitation pollution by industry, land-use, hazardous wastes, etc. Problem: Large time gap between cause and consequences of system changes!

5. Business Experiments in GRID 5 Decision problems related to groundwater Example: Pollution within the catchment areas of water works lack of information on exact position of contamination sources limited knowledge on effects of pollution (spatial-temporal distribution) Many effects are notified first, if large quantities of water are polluted and remediation measures become expensive and cumbersome. -> there is an urgent need to gain information on the potential risk from polluted sites as early as possible, to forecast possible risk and to design remediation strategies!

6. Business Experiments in GRID 6 Groundwater models Complex groundwater models finite element models/simulation (FE-models) 3D Transient (non stationary) coupled flow and mass transport high computational effort –some 100.000 elements –some 1.000 time steps Standard method for decision support  scenario analysis

7. Business Experiments in GRID 7 Sensitivity analysis The sensitivity analysis is carried out to analyze uncertain parameters by several parameter variations and therefore to estimate the model uncertainty Current problems by performing sensitivity analysis no (semi-)automatic implementation available thus it requires a lot of manual work very long runtimes due to a large number of simulations  sensitivity analysis is often disregarded during modeling

8. Business Experiments in GRID 8 Model based optimization Background of model based optimization non-linear correlation of flow- and transport processes therefore complex analysis are required to get the optimum system configuration optimization algorithms are powerful instruments to get optimum model setting with respect to constraints Disadvantages of optimization algorithms are hugh amount of time and computational power due to a very large number of model runs often model and/or optimization software must be adapted manually Off 1 On 1 Off 3 Pumping station Switch level Groundwater level Off 2 On 2 On 3 Off 4 On 4 Constraint

9. Business Experiments in GRID 9 Customer requirements Groundwater models are often used by small engineering companies, public authorities, water suppliers and without own informatics section  Model design is often a service delivery  Model usage must require non or at most a minimum of informatics knowledge

10. Business Experiments in GRID 10 Customer requirements So model calibration, sensitivity analysis and optimization can be provided as supply of services or as a “toolkit” providing –groundwater relevant “easy to use” graphical interface, –applicable runtime behavior, –evaluation methods and –without need of informatics or programming skills

11. Business Experiments in GRID 11 The status quo: distributed optimization FEFLOW 2. Simulation run 1. Start simulation Return simulation 3. Return simulationresults Interface Management Middleware Cluster of workstations Optimization

12. Business Experiments in GRID 12 The status quo: distributed optimization The distributed optimization provides an essential speedup of optimization and so enables the optimization of groundwater problems even in complex cases nevertheless, mathematical correct optimization of complex problems (transient, mass transport) are still hard to hand but: optimization (even with simplified assumptions) provides a better screening of rational scenarios for water quantity problems (e.g. optimization of groundwater lowering) the method is practicable already  Using the present distributed optimization requires modeling and development skills, so optimization requires at least a modeler and a computer scientist

13. Business Experiments in GRID 13 The goals: providing a grid toolkit The goal of the “grid toolkit” is to provide a “FEFLOW ® grid toolkit” including –a FEFLOW ® grid service to simulate FE-models, –grid services to enable distributed model calibration, sensitivity analysis and/or optimization –graphical “easy to use” user interfaces to integrate the toolkit into a grid framework (e.g. GT4, Unicore/GS) design of a portal solution to access the services (e.g. GridSphere/GridPortlets) and/or to access grid resources by the actual FEFLOW ® application and/or standalone client.

14. Business Experiments in GRID 14 The goals: providing a grid toolkit To succeed with a grid toolkit basic features have to be: “easy to use” user interfaces, a secure and reliable environment, access to new resources (thus performance gain) without specific knowledge, problem oriented predefined scenarios (to be easily adapted to different models) and a efficient business plan (accounting, billing).

15. Business Experiments in GRID 15 The goals: providing suitable business models A key aspect of BEinGRID is bringing new grid technologies out of the lab into the real world. Currently loads of technologies developed in different EU projects wait for adoption Obstacles to adoption are: –smaller technological gaps resulting from many projects being very domain specifc (these will be closed in the BEs and other workpackages) –lacking business models To succeed with a grid solution appropriate business models are required: –suitable for service consumers, e.g. end users from different sectors (SMEs, governmental) … –suitable for service providers and ISVs, e.g. WASY

16. Thank You.