Without using vtkm_option, you will run into CMP0077 which means "option() won't honor normal variables". |
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.github | ||
.gitlab/ci | ||
benchmarking | ||
CMake | ||
data | ||
docs | ||
examples | ||
Utilities | ||
vtkm | ||
vtkmstd | ||
.clang-format | ||
.gitattributes | ||
.gitignore | ||
.gitlab-ci-ecp.yml | ||
.gitlab-ci.yml | ||
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.
-
A practical VTK-m Tutorial based in what users want to accomplish with VTK-m:
- Building VTK-m and using existing VTK-m data structures and filters.
- Algorithm development with VTK-m.
- Writing new VTK-m filters.
-
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 5.0+
- XCode 5.0+
- MSVC 2015+
- Intel 17.0.4+
- CMake
- CMake 3.8+
- CMake 3.11+ (for Visual Studio generator)
- CMake 3.12+ (for OpenMP support)
- CMake 3.13+ (for CUDA support)
Optional dependencies are:
- CUDA Device Adapter
- Cuda Toolkit 9.2+
- Note CUDA >= 10.1 is required on Windows
- TBB Device Adapter
- OpenMP Device Adapter
- Requires a compiler that supports OpenMP >= 4.0.
- 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
VTK-m has been tested on the following configurations:c
- On Linux
- GCC 4.8.5, 5.4.0, 6.4.0, 7.3.0, Clang 5.0, 6.0, 7.0, Intel 17.0.4, Intel 19.0.0
- CMake 3.13.3, 3.14.1
- CUDA 9.2.148, 10.0.130, 10.1.105
- TBB 4.4 U2, 2017 U7
- On Windows
- Visual Studio 2015, 2017
- CMake 3.8.2, 3.11.1, 3.12.4
- CUDA 10.1
- TBB 2017 U3, 2018 U2
- On MacOS
- AppleClang 9.1
- CMake 3.12.3
- TBB 2018
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.
The basic procedure for building VTK-m is to unpack the source, create a build directory, run CMake in that build directory (pointing to the source) and then build. Here are some example *nix commands for the process (individual commands may vary).
$ tar xvzf ~/Downloads/vtk-m-v1.4.0.tar.gz
$ mkdir vtkm-build
$ cd vtkm-build
$ cmake-gui ../vtk-m-v1.4.0
$ cmake --build -j . # Runs make (or other build program)
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:
#include <vtkm/Bounds.h>
#include <vtkm/Range.h>
#include <vtkm/cont/ColorTable.h>
#include <vtkm/filter/Contour.h>
#include <vtkm/io/reader/VTKDataSetReader.h>
#include <vtkm/rendering/Actor.h>
#include <vtkm/rendering/Camera.h>
#include <vtkm/rendering/CanvasRayTracer.h>
#include <vtkm/rendering/Color.h>
#include <vtkm/rendering/MapperRayTracer.h>
#include <vtkm/rendering/Scene.h>
#include <vtkm/rendering/View3D.h>
vtkm::io::reader::VTKDataSetReader reader("path/to/vtk_image_file");
vtkm::cont::DataSet inputData = reader.ReadDataSet();
std::string fieldName = "scalars";
vtkm::Range range;
inputData.GetPointField(fieldName).GetRange(&range);
vtkm::Float64 isovalue = range.Center();
// Create an isosurface filter
vtkm::filter::Contour filter;
filter.SetIsoValue(0, isovalue);
filter.SetActiveField(fieldName);
vtkm::cont::DataSet outputData = filter.Execute(inputData);
// compute the bounds and extends of the input data
vtkm::Bounds coordsBounds = inputData.GetCoordinateSystem().GetBounds();
// setup a camera and point it to towards the center of the input data
vtkm::rendering::Camera camera;
camera.ResetToBounds(coordsBounds);
vtkm::cont::ColorTable colorTable("inferno");
// 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
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");
A minimal CMakeLists.txt such as the following one can be used to build this example.
project(example)
set(VTKm_DIR "/somepath/lib/cmake/vtkm-XYZ")
find_package(VTKm REQUIRED)
add_executable(example example.cxx)
target_link_libraries(example vtkm_cont vtkm_rendering)
License
VTK-m is distributed under the OSI-approved BSD 3-clause License. See LICENSE.txt for details.