mirror of
https://gitlab.kitware.com/vtk/vtk-m
synced 2024-10-05 01:49:02 +00:00
Use Markdown readme as mainpage for doxygen.
This commit is contained in:
Robert Maynard
parent
c09e88d214
commit
3f42642d24
@ -138,7 +138,11 @@ WARN_LOGFILE =
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# configuration options related to the input files
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#---------------------------------------------------------------------------
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INPUT = @VTKm_SOURCE_DIR@/vtkm
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INPUT = @VTKm_SOURCE_DIR@/README.md
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INPUT += @VTKm_SOURCE_DIR@/docs/CodingConventions.md
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INPUT += @VTKm_SOURCE_DIR@/vtkm
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USE_MDFILE_AS_MAINPAGE = README.md
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FILE_PATTERNS = *.cxx *.h *.cu
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192
README.md
192
README.md
@ -1,106 +1,20 @@
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## VTK-m ##
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VTK-m is a toolkit of scientific visualization algorithms for emerging processor architectures. VTK-msupports 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.
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VTK-m is a toolkit of scientific visualization algorithms for emerging processor
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architectures. VTK-m supports the fine-grained concurrency for data analysis and
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visualization algorithms required to drive extreme scale computing by providing
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abstract models for data and execution that can be applied to a variety of
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algorithms across many different processor architectures.
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You can find out more about the design of VTK-m on our [wiki][]
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Dependencies
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============
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VTK-m Requires:
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+ C++11 Compiler. VTK-m has been confirmed to work with the following
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+ GCC 4.8+
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+ Clang 3.3+
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+ XCode 5.0+
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+ MSVC 2013+
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+ [CMake 3.3](http://www.cmake.org/download/)
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Optional dependencies are:
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+ CUDA Device Adapter
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+ [Cuda Toolkit 7+](https://developer.nvidia.com/cuda-toolkit)
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+ TBB Device Adapter
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+ [TBB](https://www.threadingbuildingblocks.org/)
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+ Rendering Module
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+ The rendering module requires that you have a extension binding library and one rendering library. A windowing library is not needed expect for some optional tests.
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+ Extension Binding
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+ [GLEW](http://glew.sourceforge.net/)
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+ Rendering Canvas
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+ OpenGL Driver (See your GPU/iGPU vendor)
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+ EGL (See your GPU/iGPU vendor)
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+ [OSMesa](https://www.mesa3d.org/osmesa.html)
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+ Windowing/Contexts
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+ EGL (See your GPU/iGPU vendor)
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+ [GLFW](http://www.glfw.org/)
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+ [GLUT](http://freeglut.sourceforge.net/)
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Building
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========
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VTK-m supports all majors platforms ( Windows, Linux, OSX ), and uses CMake
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to generate all the build rules for the project.
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```
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$ git clone https://gitlab.kitware.com/vtk/vtk-m.git
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$ mkdir vtkm-build
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$ cd vtkm-build
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$ cmake-gui ../vtk-m
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$ make -j<N>
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$ make test
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```
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The VTK-m CMake configuration supports several options, including what specific
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device adapters ( e.g. CUDA, TBB ) that you wish to enable. Here are some
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relevant options
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| Variable | Description |
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|-----------------------------|-----------------------------|
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| BUILD_SHARED_LIBS | Enabled by default. Build all VTK-m libraries as shared libraries. |
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| CMAKE_BUILD_TYPE | This statically specifies what build type (configuration) will be built in this build tree. Possible values are empty, Debug, Release, RelWithDebInfo and MinSizeRel. This variable is only meaningful to single-configuration generators (such as make and Ninja). |
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| CMAKE_INSTALL_PREFIX | Directory to install VTK-m into. |
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| VTKm_ENABLE_EXAMPLES | Disabled by default. Turn on building of simple examples of using VTK-m. |
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| VTKm_ENABLE_BENCHMARKS | Disabled by default. Turn on additional timing tests. |
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| VTKm_ENABLE_CUDA | Disabled by default. Enable CUDA backend. |
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| VTKm_CUDA_Architecture | Defaults to native. Specify what GPU architecture(s) to build CUDA code for, options include native, fermi, kepler, maxwell, and pascal. |
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| VTKm_ENABLE_TBB | Disabled by default. Enable Intel Threading Building Blocks backend. |
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| VTKm_ENABLE_TESTING | Enabled by default. Turn on header, unit, worklet, and filter tests. |
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| VTKm_ENABLE_RENDERING | Enabled by default. Turn on the rendering module. |
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| VTKm_USE_64BIT_IDS | Enabled by default. This is the size of integers used to index arrays, points, cells, etc. Use 64 bit precision when on, 32 bit precision when off. |
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| VTKm_USE_DOUBLE_PRECISION | Disabled by default. Precision to use in floating point numbers when no other precision can be inferred. Use 64 bit precision when on, 32 bit precision when off. |
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Learning
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========
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VTK-m offers numerous different ways to learn how to use the provided components.
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If you are interested in a high level overview of VTK-m a good place to start
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is with the IEEE Vis talk ["VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures"](http://m.vtk.org/images/2/29/VTKmVis2016.pptx) or the older and more technical
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presentation
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["VTK-m Overview for Intel Design Review"](http://m.vtk.org/images/a/a4/VTKmIntelMeet.pptx).
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If you are interested in learning how to use the existing VTK-m codebase,
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or how to integrate into your own project, we recommend reading "Part 1: Getting Started"
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and "Part 2: Using VTK-m" of the [VTK-m Users Guide][].
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If you want to contribute to VTK-m we recommend reading the following sections
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of the [VTK-m Users Guide][].
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+ "Part 2: Using VTK-m"
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- Covers the core fundamental components of VTK-m including data model, worklets, and filters.
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- "Part 3: Developing with VTK-m"
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- Covers how to develop new worklets and filters.
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- "Part 4: Advanced Development"
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- Covers topics such as new worklet tags, opengl interop and custom device adapters .
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Example
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=======
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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.
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The VTK-m source distribution includes a number of examples. The goal of the
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VTK-m examples is to illustrate specific VTK-m concepts in a consistent and
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simple format. However, these examples only cover a small part of the
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capabilities of VTK-m.
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Below is a simple example of using VTK-m to load a VTK image file, run the
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Marching Cubes algorithm on it, and render the results to an image:
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@ -156,6 +70,28 @@ view.Paint();
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view.SaveAs("demo_output.pnm");
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```
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Learning
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========
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VTK-m offers numerous different ways to learn how to use the provided components.
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If you are interested in a high level overview of VTK-m a good place to start
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is with the IEEE Vis talk ["VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures"](http://m.vtk.org/images/2/29/VTKmVis2016.pptx) or the older and more technical presentation
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["VTK-m Overview for Intel Design Review"](http://m.vtk.org/images/a/a4/VTKmIntelMeet.pptx).
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If you are interested in learning how to use the existing VTK-m codebase,
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or how to integrate into your own project, we recommend reading "Part 1: Getting Started"
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and "Part 2: Using VTK-m" of the [VTK-m Users Guide][].
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If you want to contribute to VTK-m we recommend reading the following sections
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of the [VTK-m Users Guide][].
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+ "Part 2: Using VTK-m"
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- Covers the core fundamental components of VTK-m including data model, worklets, and filters.
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- "Part 3: Developing with VTK-m"
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- Covers how to develop new worklets and filters.
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- "Part 4: Advanced Development"
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- Covers topics such as new worklet tags, opengl interop and custom device adapters .
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Contributing
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============
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@ -168,7 +104,73 @@ There are many ways to contribute to [VTK-m][], with varying levels of effort.
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a Pull Request.
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++ Submit an Issue or Pull Request for the [VTK-m User's Guide](http://m.vtk.org/images/c/c8/VTKmUsersGuide.pdf)
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Dependencies
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============
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VTK-m Requires:
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+ C++11 Compiler. VTK-m has been confirmed to work with the following
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+ GCC 4.8+
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+ Clang 3.3+
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+ XCode 5.0+
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+ MSVC 2013+
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+ [CMake 3.3](http://www.cmake.org/download/)
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Optional dependencies are:
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+ CUDA Device Adapter
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+ [Cuda Toolkit 7+](https://developer.nvidia.com/cuda-toolkit)
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+ TBB Device Adapter
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+ [TBB](https://www.threadingbuildingblocks.org/)
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+ Rendering Module
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+ The rendering module requires that you have a extension binding library
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and one rendering library. A windowing library is not needed expect
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for some optional tests.
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+ Extension Binding
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+ [GLEW](http://glew.sourceforge.net/)
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+ Rendering Canvas
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+ OpenGL Driver (See your GPU/iGPU vendor)
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+ EGL (See your GPU/iGPU vendor)
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+ [OSMesa](https://www.mesa3d.org/osmesa.html)
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+ Windowing/Contexts
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+ EGL (See your GPU/iGPU vendor)
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+ [GLFW](http://www.glfw.org/)
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+ [GLUT](http://freeglut.sourceforge.net/)
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Building
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========
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VTK-m supports all majors platforms ( Windows, Linux, OSX ), and uses CMake
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to generate all the build rules for the project.
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```
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$ git clone https://gitlab.kitware.com/vtk/vtk-m.git
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$ mkdir vtkm-build
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$ cd vtkm-build
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$ cmake-gui ../vtk-m
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$ make -j<N>
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$ make test
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```
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The VTK-m CMake configuration supports several options, including what specific
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device adapters ( e.g. CUDA, TBB ) that you wish to enable. Here are some
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relevant options
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| Variable | Description |
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|-----------------------------|-----------------------------|
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| BUILD_SHARED_LIBS | Enabled by default. Build all VTK-m libraries as shared libraries. |
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| CMAKE_BUILD_TYPE | This statically specifies what build type (configuration) will be built in this build tree. Possible values are empty, Debug, Release, RelWithDebInfo and MinSizeRel. This variable is only meaningful to single-configuration generators (such as make and Ninja). |
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| CMAKE_INSTALL_PREFIX | Directory to install VTK-m into. |
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| VTKm_ENABLE_EXAMPLES | Disabled by default. Turn on building of simple examples of using VTK-m. |
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| VTKm_ENABLE_BENCHMARKS | Disabled by default. Turn on additional timing tests. |
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| VTKm_ENABLE_CUDA | Disabled by default. Enable CUDA backend. |
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| VTKm_CUDA_Architecture | Defaults to native. Specify what GPU architecture(s) to build CUDA code for, options include native, fermi, kepler, maxwell, and pascal. |
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| VTKm_ENABLE_TBB | Disabled by default. Enable Intel Threading Building Blocks backend. |
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| VTKm_ENABLE_TESTING | Enabled by default. Turn on header, unit, worklet, and filter tests. |
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| VTKm_ENABLE_RENDERING | Enabled by default. Turn on the rendering module. |
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| VTKm_USE_64BIT_IDS | Enabled by default. This is the size of integers used to index arrays, points, cells, etc. Use 64 bit precision when on, 32 bit precision when off. |
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| VTKm_USE_DOUBLE_PRECISION | Disabled by default. Precision to use in floating point numbers when no other precision can be inferred. Use 64 bit precision when on, 32 bit precision when off. |
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License
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||||
=======
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