VTK/GSoC 2015

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Project ideas for the Google Summer of Code 2015

Guidelines

Students

These ideas were contributed by developers and users of VTK and ParaView. If you wish to submit a proposal based on these ideas you should contact the community members identified below to find out more about the idea, get to know the community member that will review your proposal, and receive feedback on your ideas.

The Google Summer of Code program is competitive, and accepted students will usually have thoroughly researched the technologies of their proposed project, been in frequent contact with potential mentors, and ideally have submitted a patch or two to fix bugs in their project (through Gerrit), instructions are here. Kitware makes extensive use of mailing lists, and this would be your best point of initial contact to apply for any of the proposed projects. The mailing lists can be found on the project pages linked in the preceding paragraph. Please see GSoC proposal guidelines for further guidelines on writing your proposal.

Adding Ideas

When adding a new idea to this page, please try to include the following information:

  • A brief explanation of the idea
  • Expected results/feature additions
  • Any prerequisites for working on the project
  • Links to any further information, discussions, bug reports etc
  • Any special mailing lists if not the standard mailing list for VTK
  • Your name and email address for contact (if willing to mentor, or nominated mentor)

If you are not a developer for the project concerned, please contact a developer about the idea before adding it here.

Project Ideas

Project page, mailing lists, dashboard.

Project: Templated Input Generator for VTK

Brief explanation: Build up an infrastructure that makes it trivial to bring new scientific data formats into VTK and ParaView. The infrastructure will handle the complexities of temporal support, parallel processing, composite data structures, ghost levels and the like, and provide easy to use entry points that bring data from the file or other source and populate VTK arrays.

Expected Results: Code that can take an input specification and produce vtk data objects correctly and relatively efficiently. The input specification should be sufficiently abstracted from VTKs data types that users who understand the input format well won't have to understand VTK's complexities in order to use it.

Prerequisites: C++, Python, or maybe Lua.

References: http://www.paraview.org/Wiki/Writing_ParaView_Readers

Mentor(s): dave.demarle and/or Robert Maynard and/or Andy Bauer

CAD Model and Simulation Spline Visualization

Brief explanation: While spline curves and surfaces have been used for many years to describe CAD models, these flexible representations have often been discarded during the meshing and simulation process that is used to estimate the behavior of CAD-modeled parts in a particular environment or during a particular event. Recently, a group of techniques called IsoGeometric Analysis (IGA) has evolved in order to reduce the amount of work required to prepare simulations and to improve their accuracy. This project would develop support for arbitrary-dimensional, rational spline patches in VTK so that these simulations can be visualized properly. This may involve conversion to handle the variety of spline formats (T-Splines, NURBS, Catmull-Clark surfaces, etc.).

Expected results: The result would be a new mesh representation class, a reader, and a suite of 2-3 filters for contouring, cutting, and rendering these meshes.

Prerequisites: C/C++ experience, knowledge of rational splines and techniques for processing them (degree elevation, knot insertion/removal), and preferably some experience with VTK

Mentor(s): David Thompson (david dot thompson ta kitware dot com) and/or Bob O'Bara (bob dot obara ta kitware dot com)

Shared Memory Parallelism in VTK

Brief explanation: Development of multi-threaded algorithms in VTK. Multiple R&D efforts are leading the creation of an infrastructure to support next generation multi-threaded parallel algorithm development in VTK. These efforts are based on modern parallel libraries such as Intel TBB and Inria KAAPI. The main goal of this project will be the development of algorithms that leverage this infrastructure. The focus will be on upgrading existing core algorithms such as iso-surfacing, clipping, cutting, warping etc. to be parallel.

Expected results: A number of algorithms that execute in parallel using shared memory. Scalability of new algorithms will have to be measured and documented. Development of regression tests and examples will be also expected.

Prerequisites: Experience in C++ and multi-threaded code development. Understanding of core visualization algorithms and data structures. Some experience in VTK ideally but not necessary.

Mentor: Berk Geveci (berk dot geveci at kitware dot com)

Half Baked Ideas

  • make concave polydata "just work" (i.e. render correctly) with minimal impact on common case speed
  • add on framework for keeping track of units
  • lua wrapping, lua programmable filters
  • Switch android version of KiwiViewer from VES rendering to VTK rendering - Brad Davis
  • advanced rendering algorithms with OpenGL2 back end - Ambient occlusion, Shadows, Reflection, etc etc.
  • interface to high quality rendering engines