e28309f09b
If a global static array is declared with VTKM_EXEC_CONSTANT and the code is compiled by nvcc (for multibackend code) then the array is only accesible on the GPU. If for some reason a worklet fails on the cuda backend and it is re-executed on any of the CPU backends, it will continue to fail. We couldn't find a simple way to declare the array once and have it available on both CPU and GPU. The approach we are using here is to declare the arrays as static inside some "Get" function which is marked as VTKM_EXEC_CONT. |
||
---|---|---|
CMake | ||
data | ||
docs | ||
examples | ||
Utilities | ||
vtkm | ||
.clang-format | ||
.gitattributes | ||
CMakeLists.txt | ||
CONTRIBUTING.md | ||
CTestConfig.cmake | ||
CTestCustom.cmake.in | ||
LICENSE.txt | ||
README.md | ||
version.txt |
VTK-m
VTK-m is a toolkit of scientific visualization algorithms for emerging processor architectures. VTK-m supports the fine-grained concurrency for data analysis and visualization algorithms required to drive extreme scale computing by providing abstract models for data and execution that can be applied to a variety of algorithms across many different processor architectures.
You can find out more about the design of VTK-m on the VTK-m Wiki.
Learning Resources
-
A high-level overview is given in the IEEE Vis talk "VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures."
-
The VTK-m Users Guide provides extensive documentation. It is broken into multiple parts for learning and references at multiple different levels.
- "Part 1: Getting Started" provides the introductory instruction for building VTK-m and using its high-level features.
- "Part 2: Using VTK-m" covers the core fundamental components of VTK-m including data model, worklets, and filters.
- "Part 3: Developing with VTK-m" covers how to develop new worklets and filters.
- "Part 4: Advanced Development" covers topics such as new worklet types and custom device adapters.
-
Community discussion takes place on the VTK-m users email list.
-
Doxygen-generated nightly reference documentation is available online.
Contributing
There are many ways to contribute to VTK-m, with varying levels of effort.
-
Ask a question on the VTK-m users email list.
-
Submit new or add to discussions of a feature requests or bugs on the VTK-m Issue Tracker.
-
Submit a Pull Request to improve VTK-m
- See CONTRIBUTING.md for detailed instructions on how to create a Pull Request.
- See the VTK-m Coding Conventions that must be followed for contributed code.
-
Submit an Issue or Pull Request for the VTK-m Users Guide
Dependencies
VTK-m Requires:
- C++11 Compiler. VTK-m has been confirmed to work with the following
- GCC 4.8+
- Clang 3.3+
- XCode 5.0+
- MSVC 2013+
- CMake
- CMake 3.3+ (for any build)
- CMake 3.9+ (for CUDA build)
Optional dependencies are:
- CUDA Device Adapter
- TBB Device Adapter
- OpenGL Rendering
- The rendering module contains multiple rendering implementations including standalone rendering code. The rendering module also includes (optionally built) OpenGL rendering classes.
- The OpenGL rendering classes require that you have a extension binding library and one rendering library. A windowing library is not needed except for some optional tests.
- Extension Binding
- On Screen Rendering
- OpenGL Driver
- Mesa Driver
- On Screen Rendering Tests
- Headless Rendering
- OS Mesa
- EGL Driver
Building
VTK-m supports all majors platforms (Windows, Linux, OSX), and uses CMake to generate all the build rules for the project. The VTK-m source code is available from the VTK-m download page or by directly cloning the VTK-m git repository.
$ git clone https://gitlab.kitware.com/vtk/vtk-m.git
$ mkdir vtkm-build
$ cd vtkm-build
$ cmake-gui ../vtk-m
$ make -j<N>
$ make test
A more detailed description of building VTK-m is available in the VTK-m Users Guide.
Example##
The VTK-m source distribution includes a number of examples. The goal of the VTK-m examples is to illustrate specific VTK-m concepts in a consistent and simple format. However, these examples only cover a small part of the capabilities of VTK-m.
Below is a simple example of using VTK-m to load a VTK image file, run the Marching Cubes algorithm on it, and render the results to an image:
vtkm::io::reader::VTKDataSetReader reader("path/to/vtk_image_file");
inputData = reader.ReadDataSet();
vtkm::Float64 isovalue = 100.0f;
std::string fieldName = "pointvar";
// Create an isosurface filter
vtkm::filter::MarchingCubes filter;
filter.SetIsoValue(0, isovalue);
vtkm::filter::Result result = filter.Execute( inputData,
inputData.GetField(fieldName) );
filter.MapFieldOntoOutput(result, inputData.GetField(fieldName));
// compute the bounds and extends of the input data
vtkm::Bounds coordsBounds = inputData.GetCoordinateSystem().GetBounds();
vtkm::Vec<vtkm::Float64,3> totalExtent( coordsBounds.X.Length(),
coordsBounds.Y.Length(),
coordsBounds.Z.Length() );
vtkm::Float64 mag = vtkm::Magnitude(totalExtent);
vtkm::Normalize(totalExtent);
// setup a camera and point it to towards the center of the input data
vtkm::rendering::Camera camera;
camera.ResetToBounds(coordsBounds);
camera.SetLookAt(totalExtent*(mag * .5f));
camera.SetViewUp(vtkm::make_Vec(0.f, 1.f, 0.f));
camera.SetClippingRange(1.f, 100.f);
camera.SetFieldOfView(60.f);
camera.SetPosition(totalExtent*(mag * 2.f));
vtkm::rendering::ColorTable colorTable("thermal");
// Create a mapper, canvas and view that will be used to render the scene
vtkm::rendering::Scene scene;
vtkm::rendering::MapperRayTracer mapper;
vtkm::rendering::CanvasRayTracer canvas(512, 512);
vtkm::rendering::Color bg(0.2f, 0.2f, 0.2f, 1.0f);
// Render an image of the output isosurface
vtkm::cont::DataSet& outputData = result.GetDataSet();
scene.AddActor(vtkm::rendering::Actor(outputData.GetCellSet(),
outputData.GetCoordinateSystem(),
outputData.GetField(fieldName),
colorTable));
vtkm::rendering::View3D view(scene, mapper, canvas, camera, bg);
view.Initialize();
view.Paint();
view.SaveAs("demo_output.pnm");
License
VTK-m is distributed under the OSI-approved BSD 3-clause License. See LICENSE.txt for details.