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Published byAnnis Marshall Modified over 8 years ago
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Visualization in Scientific Computing (or Scientific Visualization) Multiresolution,...
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Scientific Computing w use of computers to simulate physical processes or systems: development of mathematical model (equation) development of a numerical algorithm implementation in a computer software numerical simulation representation of the result in a comprehens. form interpretation and validation
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Example: crash simulation of a car equation for shear stress (deformation)
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w geometrical model w finite element model (FEM)
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w resolve the equation for each element of the model w data: geometry (3D coordinates) results: scalar values (stress) vector values (deformation)
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w our model (8 MB): 289 parts 32.000 nodes 28.000 elements 13 time steps Q: how can we interpret this data?
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… try to understand the numerical information not a good solution (~400.000 scalar & 400.000 vector values)
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… computer graphics and animation “we are better at understanding this kind of information”
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Scientific Visualization w is the use of computer graphics to create visual images that aid in the understanding of complex numerical representation of scientific concepts or results w utilize the pattern-recognition capability of the human visual system
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* astrophysics (Big bang)
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* molecular biology
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* visual arts
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* computational fluid dynamics
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* gas model of the sun
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Problems w unprecedented growth in the amount of data w our capability to manipulate, explore and understand large data sets growth more slowly Possible solutions w multiresolution methods w automatic feature extraction
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Q: How large is large?
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Accelerated Strategic Computing Initiative (ASCI) - DOE
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* 4640 compute nodes * 16/74/20 service/disk/network nodes * 9536 Pentium Pro processors * 2500 square feet footprint * 606 GBytes RAM memory * 1.8 TFlops system peak performance ASCI Red TFLOPS Supercomputer
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100 % 10 % 50 % Multiresolution representation * at different levels of detail
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Feature extraction
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Questions & Answers
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