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Grid Enabled Optimisation and Design Search for Engineering (G EODISE ) Prof Simon Cox Southampton University 3 rd Annual Workshop on Linux Clusters for.

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Presentation on theme: "Grid Enabled Optimisation and Design Search for Engineering (G EODISE ) Prof Simon Cox Southampton University 3 rd Annual Workshop on Linux Clusters for."— Presentation transcript:

1 Grid Enabled Optimisation and Design Search for Engineering (G EODISE ) Prof Simon Cox Southampton University 3 rd Annual Workshop on Linux Clusters for Super Computing National Supercomputer Centre, Linköpings Universitet, Sweden

2 Grid Enabled Optimisation and Design Search for Engineering (G EODISE ) Southampton, Oxford and Manchester Simon Cox- Grid/ W3C Technologies and High Performance Computing Global Grid Forum Apps Working Group Andy Keane- Director of Rolls Royce/ BAE Systems University Technology Partnership in Design Search and Optimisation Mike Giles- Director of Rolls Royce University Technology Centre for Computational Fluid Dynamics Carole Goble- Ontologies and DARPA Agent Markup Language (DAML) / Ontology Inference Language (OIL) Nigel Shadbolt- Director of Advanced Knowledge Technologies (AKT) IRC BAE Systems- Engineering Rolls-Royce- Engineering Fluent- Computational Fluid Dynamics Microsoft- Software/ Web Services Intel- Hardware Compusys- Systems Integration Epistemics- Knowledge Technologies Condor- Grid Middleware

3 The G EODISE Team... F Richard Boardman F Sergio Campobasso F Liming Chen F Mike Chrystall F Simon Cox F Mihai Duta F Clive Emberey F Hakki Eres F Matt Fairman F Carole Goble F Mike Giles F Ian Hartney F Tracey Hunt F Zhuoan Jiao F Andy Keane F Marc Molinari F Juri Papay F Graeme Pound F Nicola Reader F Angus Roberts F Mark Scott F Tony Scurr F Nigel Shadbolt F Paul Smart F Barry Tao F Jasmin Wason F Fenglian Xu F Gang “Luke” Xue

4 Design

5 Structural Optimisation

6 Modern engineering firms are global and distributed “Not just a problem of using HPC” CAD and analysis tools, user interfaces, PSEs, and Visualization Optimisation methods Data archives (e.g. design/ system usage) Knowledge repositories & knowledge capture and reuse tools. Management of distributed compute and data resources How to … ? … improve design environments … cope with legacy code / systems … integrate large-scale systems in a flexible way … produce optimized designs … archive and re-use design history … capture and re-use knowledge Design Challenges

7 The Grid Problem “Flexible and secure sharing of resources among dynamic collections of individuals within and across organisations” F Resources = assets, capabilities, and knowledge v Capabilities (e.g. application codes, analysis tools) v Compute Grids (PC cycles, commodity clusters, HPC) v Data Grids v Experimental Instruments v Knowledge Services v Virtual Organisations v Utility Services Grid middleware mediates between these resources

8 Geodise will provide grid-based seamless access to an intelligent knowledge repository, a state-of-the-art collection of optimisation and search tools, industrial strength analysis codes, and distributed computing & data resources G EODISE

9 (1) Security Infrastructure Authentication & Authorisation (2) Define Geometry to optimise (3) Sample Objective function to build Response Surface Model Nacelle Design Axisymmetric (2D) 3D G EODISE Demo Grid Computing

10 (4) Optimise over Response Surface Model (5) Grid Database Query and Postprocessing of Results G EODISE Demo

11 Grid Computing using (.NET) web services Coming next…

12 Knowledge Portal

13 Knowledge Acquisition

14 Knowledge Technologies a) Annotating Design Optimisation Workflows using OntoMat-Annotizer b) Knowledge Portal Coming next…

15 Workflow Requirements F Flexibility v Customise the workflow and its components initially v Compose a work flow via drag & drop activity node component into an editor panel v Link to knowledge and other services F Monitoring v Interact with the workflow or its components during simulation v Job status v Resource usage F Maintainable v Modify & re-use the workflow either in a GUI or in a human readable file F Usability v Easy to use by engineering users

16 Workflow Tools: IBM

17 Workflow Tools: Microsoft

18 Grid Enabled Optimisation and Design Search for Engineering (G EODISE ) Prof Simon Cox Southampton University

19 Workflow Requirements F Flexibility v Customise the workflow and its components initially v Compose a work flow via drag & drop activity node component into an editor panel v Link to knowledge and other services F Monitoring v Interact with the workflow or its components during simulation v Job status v Resource usage F Maintainable v Modify the workflow either in a GUI or in a human readable file F Usability v Easy to use by engineering users Engineer

20 Matlab F Matlab and toolboxes for mathematical computation, analysis, visualization, and algorithm development: “MATLAB is an intuitive language and a technical computing environment. It provides core mathematics and advanced graphical tools for data analysis, visualization, and algorithm and application development. With more than 600 mathematical, statistical, and engineering functions, engineers and scientists rely on the MATLAB environment for their technical computing needs.” ( ) F Industry usage v Aerospace v Defense v Automotive v Biotech v Pharmaceutical v Medical CROSS PLATFORM/ OS

21 Matlab F Flexibility v Integrated Development Environment v Provides full GUI Support and can integrate code from Fortran, C, Java, & Web/ Grid Services F Monitoring v Command line/ batch mode F Maintainable v Matlab Scripts readable and editable by Engineers F Usability v Already in widespread use by Engineers

22 Grid Computing from Matlab F Globus commands (based on Java CoG v0.9.13) v gd_CreateProxyCertVisual v gd_BatchSubmit v gd_JobStatus v gd_GetFile (GSIftp v0.9.14) v gd_PutFile (GSIftp v0.9.14) F Database commands v gd_archive v gd_query v gd_retrieve

23 Grid-enabled Mesh Generation and Computational Fluid Dynamics Coming next…

24 Database Archive, Query and Retrieve Coming next…

25 The future of design optimisation Design Optimisation needs integrated services F Design improvements driven by CAD tools coupled to advanced analysis codes (CFD, FEA, CEM etc.) F On demand heterogeneous distributed computing and data spread across companies and time zones. F Optimization “for the masses” alongside manual search as part of a problem solving environment. F Knowledge based tools for advice and control of process as well as product. Geodise will provide grid-based seamless access to an intelligent knowledge repository, a state-of-the-art collection of optimisation and search tools, industrial strength analysis codes, and distributed computing and data resources

26 Conclusions F Grid is not just about computing F Grid must be provided to users in a familiar environment F Services need semantics F Workflow is an important issue F … Agnostic about operating system


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