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The specialization for SerializableTypeString for ArrayHandleCast tried to get the serialization for the base type and the storage tag. This is wrong since the storage tag itself is not seralizable nor has a type string. Instead, just record the type name for the sub ArrayHandle itself. |
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.github | ||
.gitlab/ci | ||
benchmarking | ||
CMake | ||
data | ||
docs | ||
examples | ||
Utilities | ||
vtkm | ||
vtkmstd | ||
.clang-format | ||
.gitattributes | ||
.gitignore | ||
.gitlab-ci.yml | ||
.hooks-config | ||
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 3.12+
- CMake 3.13+ (for CUDA support)
Optional dependencies are:
- CUDA Device Adapter
- Cuda Toolkit 9.2, >= 10.2
- Note CUDA >= 10.2 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, 6.5, 7.4, 8.2, 9.2; Clang 5, 8; Intel 17.0.4; 19.0.0
- CMake 3.12, 3.13, 3.16, 3.17
- CUDA 9.2, 10.2, 11.0, 11.1
- TBB 4.4 U2, 2017 U7
- On Windows
- Visual Studio 2015, 2017
- CMake 3.12, 3.17
- CUDA 10.2
- TBB 2017 U3, 2018 U2
- On MacOS
- AppleClang 9.1
- CMake 3.12
- 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/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::VTKDataSetReader reader("path/to/vtk_image_file.vtk");
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.Paint();
view.SaveAs("demo_output.png");
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.