Escuela Internacional de Verano

Scientific Computing & Visualization

Descripción general del curso

16 05 visual

In the past decade, Scientific Computing has supplemented or replaced traditional scientific workflows to address modeling, design, and optimization problems across a wide range of scientific and engineering domains. Analysis of and insight into the enormous amount of data produced by modern numerical experiments in this context mandates the use of sophisticated visualization and data analysis techniques. 

The present course is aimed at providing students with a solid understanding of, and practical competence in, the area of interactive visual data analysis. In addition to an introduction into the theoretical framework of visualization and ready-to-use tools, a particular focus of study is on the programmatic generation of visualization tailored to specific problems. Last, the course will introduce students to the efficient visualization of large datasets through parallel programming and other techniques.

This course explore the elements of high performance scientific computing and visualization. Students will obtain hands-on experience in:

1) Formulating a mathematical model to describe a physical phenomenon
2) Discretizing the model
3) Designing/analyzing algorithms efficiently on parallel computers
4) Performing a computer experiment by executing the program
5) Visualizing simulation data in an immersive and interactive virtual environment
6) Managing/mining large datasets

Información del curso


Curso: 13 de Junio al 30 de Junio

Workshop:  29 y 30 de Junio





Christoph Garth - Hans Hagen, TU- Kaiserslautern - Germany


Curso: 5:00 p.m. a 9:00 p.m.

 - Lecture: 5:00 p.m. a 7:00 p.m.

- Practice: 7:00 p.m. a 9:00 p.m.

Workshop:  8:00 a.m. a 5:00 p.m.



5:00 p.m. - 9:00 p.m.

* Los estudiantes asistentes al cursos deben asistir al International Workshop on Visual Computing los días 29 y 30 de Junio.


  • Day 1 (Monday, June 13). Introduction to Scientific Computing
    Theoretical: 1) Motivation, 2) Computational Models, 3) The Role of Data Analysis & Visualization, 4) Typical Workflows, 5) Typical Tools (Paraview [, VisIt])
    Practical: Introduction to Paraview
  • Day 2 (Tuesday, June 14). Visualization Fundamentals
    Theoretical: 1) Motivation, 2) Visualization Pipelines, 3) Perception and Color, 4) The Role of Interactive Exploration, 5) Data Representation
    Practical: Getting started with VTK & Python
  • Day 3 (Wednesday, June 15). Visualization Techniques, Scalar Fields I
    Theoretical: 1) Basic Techniques: Color Mapping, etc., 2) Scalar Fields I: Isosurfaces, Level sets (Marching Algorithms)
    Practical: DIY Visualization using VTK/Python: VTK programming model, simple examples, Scalar Techniques, Automation, Movies
  • Day 4 (Thursday, June 16). Scalar Fields II
    Theoretical: 1) Volume Rendering, 2) Radiative Transfer, Levoy Model, 3) Transfer Functions and TF Design, 4) Level Set Topology, 5) Summarization Techniques, 6) Histograms, Scatterplots, etc., 7) Feature-Based Visualization, 8) Applications: CFD, among others
    Practical: Scalar Techniques, Filtering and Basic Interaction
  • Day 5 (Monday, June 20). Visualization Techniques for Vector Fields I
    Theoretical: 1) Mathematical Foundations, 2) Stream-, Path-, Streak-, and Time-Lines, 3) Surface Techniques, 4) Vector Field Topology
    Practical: Flow Visualization: Particles
  • Day 6 (Tuesday, June 21). Visualization Techniques for Vector Fields II, Visualization Techniques for Tensors, Modern Topics and Introduction to Large-Data Visualization
    Theoretical: 1) VT for Vector Fields II: Lagrangian Coherent Structures, Dense Methods (LIC, …) 2) VT for Tensors: Tensor Decomposition & Glyphs, Dense Techniques, Medical Applications, 3) Modern Topics: Pattern Matching, Ensembles and Uncertainty Multi-Filed Techniques, 4) Intro to Large Data Visualization: Challenges and Opportunities, In situ Visualization vs. Post Processing
    Practical: Flow Visualization
  • Day 7 (Wednesday, June 22). Large-DATA & Parallel Visualization
    Theoretical: 1) Basics of Parallel Algorithms, 2) Parallel Decomposition, 3) Setting, 4) Parallel Support in Tools (Paraview Server [, VisIt])
    Practical: Parallel Visualization with VTK & Python
  • Day 8 (Wednesday, June 22). Modern Topics, In Situ Support, Parallel Algorithms in VTK/Python
    Theoretical: 1) Examples of State of the Art Visualization Techniques, 2) In Situ Support: Paraview Cinema, 3) Parallel Algorithms in VTK/Python: Programming Model
    Practical: Building Interactive Tools
  • Day 9 (Monday, June 27). Interaction Principles

  • Day 10 (Tuesday, June 28). Interaction Lab Visit

  • Day 11 (Wednesday, June 29). International Seminar in Visual Computing and Visualization

  • Day 12 (Thursday, June 30). International Seminar in Visual Computing and Visualization

Válido como:

Estudiantes MISIS:

Curso del perfil PCAP

Estudiantes otras maestrías:

Curso electivo

Estudiantes ISIS:

Electiva profesional


Christoph Garth

 Christoph Garth

Institución: TU-Kaiserslautern

Hoja de vida

Research Interests

  • Lagrangian and topological analysis of vector and tensor fields
  • Visual exploration and analysis of large-scale data
  • Parallel and scalable visualization algorithms
  • Feature extraction in Computational Fluid Dynamics problems
  • Topological methods in visualization
  • Query-Driven Visualization
  • Material interface reconstruction
  • Scientific Visualization
  • Computer Graphics


  • Oct. 2007: Dr. rer. nat. (Ph. D.) in Computer Science (summa cum laude), University of Kaiserslautern
  • Jan. 2003: Diplom (M. Sc.), Mathemathics & Computer Science, University of Kaiserslautern

Professional Experience

  • Since 2011: Juniorprofessor in Computational Topology, University of Kaiserslautern
  • 2007–2011: Postdoctoral Researcher, University of California, Davis
  • 2003–2007: Research Assistant, Dept. of Computer Science, University of Kaiserslautern 

Some Journal Publications

  • W. Schlei, K. C. Howell, X. Tricoche, C. Garth. Enhanced Visualization and Autonomous Ex- traction of Poincaré Map Topology. Journal of Astronautical Sciences AAS 13-903, 2015.
  • M. W. Wöllhaf, K. G. Hansen, C. Garth, J. M. Herrmann. Import of ribosomal proteins into yeast mitochondria. Biochemistry and Cell Biology, 92(6): 489-498, 2014.
  • L. Hüttenberger, C. Heine, C. Garth. Decomposition and Segmentation of Multivariate Data using Pareto Sets. IEEE Transactions on Visualization and Computer Graphics 20(12):2684– 2693, 2014.
  • M. Hummel, H. Obermaier, C. Garth, K. I. Joy. Comparative Visual Analysis of Lagrangian Transport in CFD Ensembles. IEEE Transactions on Visualization and Computer Graphics, 19(12):2743–2752, Dec. 2013.
  • D. Camp, H. Krishnan, D. Pugmire, E. W. Bethel, K. I. Joy, H. Childs, I. Johnson. GPU Acceleration of Particle Advection Workloads in a Parallel, Distributed Memory Setting. In Proc. Eurographics Symposium on Parallel Graphics and Visualization (EGPGV), pp. 1–8, Girona,Spain, May 2013
  • I. Pirlepov, H. Obermaier, E. Deines, C. Garth, K. I. Joy. Cubic Gradient-Based Material Interfaces. IEEE Transactions on Visualization and Computer Graphics 19(10):1687–1699, Oct. 2013.

Con la colaboración de: 


Kathrin Häb 

Más información AQÚI  

ext hans hagen

 Hans Hagen

Institución: TU-Kaiserslautern

Hoja de vida

  • Ph.D. (mathematics) University of Dortmund. March 1982
  • IEEE Career Award 2009
  • Full professor at the University of Kaiserslautern since February 1988
  • Adj. Prof. UC Davis
  • Before moving to Kaiserslautern Prof. Hagen held faculty positions at TU Braunschweig and at the Arizona State University
  • Several visiting positions and consulting experience of over 20 years

Former editor in chief of IEEE Transactions on Visualization and Computer Graphics Associated editor of:

  • Computer Aided Geometric Design
  • Computing
  • Surveys on Mathematics in Industry
  • Mathematical Engineering in IndustryFormer editor of  "Computer Aided Design"


 Jose Tiberio Hernandez

Institución: Universidad de los Andes

Hoja de vida

Profesor Asociado
Ph.D. en Informática, ENSTA-Paris VI, Francia

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