Ignite your...supercomputing 24 jul12_v2


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Presenter - Prof Simon J. Cox from the Computational Engineering Design Research Group (CED) with describe The use of Super Computers for Design optimisation. The CED is a centre of excellence for multi-disciplinary engineering simulation and design which combines together a range of analytical, computational, and experimental techniques.

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Ignite your...supercomputing 24 jul12_v2

  1. 1. Supercomputing & DesignProfessor Simon CoxAssociate Dean, EnterpriseFaculty of Engineering and the Environment24th July 2012sjc@soton.ac.uk
  2. 2. Faculty of EngineeringAeronautics, Astronautics and the Environmentand ComputationalEngineeringProf Keane - Head of AACE UnitProf Simon CoxChair, ComputationalEngineering and Design GroupAssociate Dean, EnterpriseFaculty of Engineering and the Environment
  3. 3. Faculty of Engineering and the EnvironmentAACE Overview• Three research groups (aeronautics & flight mechanics, astronautics and computational engineering & design). Head of Unit: Prof Keane• 30 members of academic staff holding £13m of research grants.• Three major research centres (Airbus Noise Technology Centre, R-R UTC for Computational Engineering, Microsoft Institute for HPC).• Nearly 80 PhD and EngD students under supervision (major partner in DTC for Complexity).• Linked to highly successful undergraduate and MSc teaching programmes (100% student satisfaction in 2008 National Student Survey for Aeronautics-Astronautics course; Royal Academy of Engineering/Exxonmobil Excellence in Engineering Teaching Award). 3
  4. 4. Faculty of Engineering and the EnvironmentDesign ExemplarsComputational Engineeringand Design Research Group
  5. 5. Faculty of Engineering and the EnvironmentRolls-Royce UTC in ComputationalEngineeringPIs: Keane & Scanlan 5 Academic staff, 9 Research fellows, 11 EngD/PhDs, £1.2m per annum external funding (EU/UK Govt/EPSRC) Close integration with Rolls-Royce R&T objectives 5
  6. 6. Typical Design Faculty of EngineeringImprovement Flowchart and the Environment Initial Design Background Geometry Effort Rule Parametric Bases Base Geometry Final CAD Uncertainty Optimiser Models Design Meshing Boundary Search Conditions Results Extraction CFD CSM Post Costs 6 PI: Keane Processing
  7. 7. Faculty of EngineeringMulti-fidelity Optimization and the Environment• 12 geometry variables• 10 full car RANS simulations 15h each• 120 rear wing only RANS simulations 1.5h each 7PI: Keane
  8. 8. Faculty of Engineering and the EnvironmentMulti-scale modelling for nanotechnology • Hans Fangohr • Nanotechnology length scales are close to the atomic lattice spacings. • Need to consider atomistic nature of matter to be accurate • Need to combine atomistic simulations with continuum approaches to make simulations feasible
  9. 9. Faculty of EngineeringMulti-physics modelling and the Environmentfor nanotechnology • Relevant properties • magnetic • thermodynamic • conducting • mechanic • Optical • Crucial for Nanodevices to consider these togetherPI: Fangohr
  10. 10. Faculty of Engineering and the EnvironmentDesign Optimisation of Nanodevices • Magnetic storage, sensors, spintronics • Prototype fabrication expensive vs “cheap” Simulation • Requires – multi-scale simulations – multi-physics simulations • Computational Design Optimisation highly beneficial PI: Fangohr
  11. 11. Multi-objective, multi-disciplinarydesign (coronary stents) Faculty of Engineering and the Environment Balloon expansion: structural integrity Haemodynamics: re-endothelialisation Optimal design: patient specific Flexibility: conformability Systematic design search and optimisation: Recover and maintain healthy blood flow Drug elution: control of restenosis Stress: minimise artery wall damagePI: Bressloff
  12. 12. Future cath-lab Faculty of Engineering and the Environment (1) Cath Lab (2) Stent Design Tool (a virtual cath. lab) (4) Manufacture (3) The Cloud(1) http://www.everydaychampions.org/hospital/cardiac_cath_lab.php(2) Stent design tool (N.W.Bressloff) PI: Bressloff(3) http://rohitsaxenawrites.wordpress.com/author/rohitklar/(4) http://www.raydiance.com/our-technology
  13. 13. Airbus Noise Technology Centre Faculty of Engineering(AFM Group) and the EnvironmentPI: Zhang• First Airbus-University Technology Centre in the World• Opened November 2008• Focussing on future aircraft technologies for noise reduction• Fifteen academic staff and research students• Computation and experiment
  14. 14. Sample ANTC projects Faculty of Engineering(AFM Group) and the Environment LES of noise generated by interaction of aircraft engine with wing (Zhang/Hu) Aircraft high-lift device noise generation and control (Zhang/Hu) High-speed train aeroacoustics (Hu & Thompson (ISVR) )PI: Zhang
  15. 15. Faculty of Engineering and the EnvironmentUnder the Hood… tools, technologies andplatforms
  16. 16. Microsoft Institute for HPC Faculty of Engineering and the Environment• PI: Cox• Workflow + HPC + Data• Centre for Fluid Mechanics Simulation (CFMS)• Flight simulation HPC• μVis – X-Ray CT Centre workflow and data management• Cloud & Mobile computing – space situational awareness• Institutional and Large Scale Data Management – Materials – Chemistry – Medicine – Archaeology 16 – Engineering HPC Data
  17. 17. Faculty of Engineering and the Environment Engineering Design - from the Desktop to the Enterprise• Engineering design demands integration of complex systems to set-up, execute, monitor, post-process, review, and store computational processes, data and knowledge• Research to tackle new challenges• Applied and customised commodity off- the-shelf Microsoft tools, technologies and platforms Microsoft Institute for HPC @• Collaboration with Rolls-Royce, Airbus, Southampton BAE Systems, MBDA, Microsoft, others: “We demonstrate why, where, and how current and 20 Million Euro UK TSB (DTI) future Microsoft tools and technologies can make the programme engineering design process faster, cheaper and better.” Launched by Bill Gates, Nov 2005 Initial Research 1998 17
  18. 18. TAGtivity Wiki BAE Systems Rolls-Royce Airbus Software + Services Robust, reliable and Organizing thoughts Semantic structure, Orchestration of gas for connecting scalable data and reference search and turbine design engineers and experts intensive material... experience reasoning calculations to users and data collaboration Concept Computation Data Individual review MBDA Data Driven Product Small group review Lifecycle Management Corporate review Data sources Wiki database Task database Workflow templatesTagtivity database Workflow database Conversation database Sharepoint database Workflow trackingFilesystem Knowledge database Workflow tracking Active Directory Filesystem Corporate database Simulation database Technology Windows Server 2008 Windows Workflow Sharepoint Server Microsoft Office 2007 MediaWiki Hyper-V RC0 Foundation Active Directory Windows HPC Server 2008 HP-UX (Interop) SQL Server 2005/ 2008 SQL Server 2008 Windows CCS 2003 Beta2 Windows Windows Presentation D2R Server SQL Server 2008 CTP6 Linux (Interop) Foundation; Matlab ARQ/SPARQL Visual Studio 2005 Communication Office Communication SQL Server 2005 Foundation Server
  19. 19. Exploiting cloud computingfor algorithm developmentN. O’Brien, E. Hart, S. Johnston, K. Djidjeli, S. J. Coxsjc@soton.ac .uk and Neil.OBrien@soton.ac.uk
  20. 20. Case study: photonic crystals• Nanostructures that affect propagation of light Morpho butterfly Wing cross-section Man-made example Opal Peacock’s magnificent Man-made example 20 tail
  21. 21. Strengths of cloud computing• Algorithm development – Time-, data-, compute-intensive• Data dissemination – Sharing large input or output data sets• Burst capability – Testing/parameter sweeping new revisions• Super-scalability – Apply algorithm to big problems 21
  22. 22. Case study: photonic crystal modelling• Photonic crystals are periodic dielectric structures, we assume periodicity in 𝑥 and 𝑦 directions and infinite extent in 𝑧 22
  23. 23. Maxwell’s Equations• Maxwell’s equations give the allowed modes of propagation for TM, TE modes, after applying standard simplifications 1 − ∆𝜓 = 𝜆𝜓 𝜀 1 −𝛻 ⋅ 𝛻𝜓 = 𝜆𝜓 𝜀• When the dielectric 𝜀 varies, no analytical solution exists 23
  24. 24. Algorithms for Photonic Crystal Modelling• Plane Wave Methods Gibbs Phenomenon – Scale poorly + Gibbs Phenomenon• Finite Difference Method – Simple to code FD Stencil – Requires fine mesh for accuracy » Large and Sparse Matrices• Finite Element Method – Large amounts of code FE Mesh – Requires fine (complicated) mesh for accuracy » Large and Sparse Matrices• Meshless Method – Simple to code & data parallel Radial Basis Function – Improved geometry handling » Small and Dense Matrices 24
  25. 25. Meshless Method Formulation• Maxwell’s equations for 2D problem TE  .        i k .   i k  u   u 1 1   TM 1       1   i k   i k  u   u .  • Simplifying, the 2D elliptic Helmholtz equation takes the form:• Introducing the following notation:• Then use the Standard RBF approximation of a function to write the Helmholtz equation as a generalized eigenvalue problem: 25
  26. 26. Cloud application• Verification by checking a high-resolution run against existing software – Developer workstation free to run other tasks – Institutional cluster queue time avoided• Parameter sweeps through high dimensional spaces – Wall-time bounded below by (provisioning time + longest simulation time)• Application of the new algorithm to novel shapes, bandgap engineering and optimisation 26
  27. 27. Results• Comparison of band diagrams 27
  28. 28. Concluding remarks• Cloud paradigm demonstrated – Accelerated development cycle – Parts of a traditionally-serial workflow ran on Windows Azure in parallel – Enhanced collaboration opportunities – Modularity of design• New meshless algorithm demonstrated – Solves Maxwell equations successfully – Applicable for bio-inspired photonic materials 28
  29. 29. Azure+Windows Phone 7Atmospheric ScienceProfessor Simon Cox and Dr Steven Johnston with:ASTRA: Dr András Sóbester, Prof Jim Scanlan, and Neil O’BrienMicrosoft Institute for High Performance Computing @ Southamptonsjc@soton.ac.uk & sjj698@zepler.org
  30. 30. Atmospheric ScienceThrough Robotic Aircraft• Monitoring the atmosphere – Weather, pollution – Volcanic ash…• Low cost metrological balloons – High altitude• Instrument retrieval using WP7 + GPS• Predicting the landing location with Azure
  31. 31. ASTRA architecture Meteorological Windows Logging and weather balloon Azure data storage Blob storage Windows Device Phone 7 Windows registration and Phone 7 GPS logging GSM notifications notifications Internet Flight University of Followers prediction Southampton algorithms Tracker using and trajectory Bing maps updates on WP7
  32. 32. ASTRA flights usingWP7 and Windows Azure• ASTRA 7 – 18,237 meters (59,832 feet) – Top speed 145 km/h (90mph) – 1hr 16’• ASTRA 8 – 21,600 meters (71,000 feet) – Top speed 82 km/h (51mph) – 2hr 30’
  33. 33. Take Off….. 33
  34. 34. Windows Phone 7 on the edge of Space 34
  35. 35. Windows Phone trajectory 35
  36. 36. Windows Phone at -58 degrees C 36
  37. 37. ThanksWe acknowledge and thank Microsoft and Microsoft Research for supportProf Simon Coxsjc@soton.ac.uk
  38. 38. Further information• Atmospheric Science Through Robotic Aircraft (ASTRA) http://www.soton.ac.uk/~astra/ (Main page) http://segoz.co.uk/Stratosphericflight.aspx (WP7 application) http://www.soton.ac.uk/~astra/diary.html http://www.microsoft.com/showcase/en/us/details/da17789f-7914-4131- b7cb-91937be3d20a (Video)
  39. 39. Faculty of Engineering and the EnvironmentSummary