Shuenhoy/vtk-m2
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Kenneth Moreland 434f54195a Fix issue where exports failed when no libraries 
Currently, the only library created is for the rendering package. If
VTKm_BUILD_RENDERING is off, then no libraries are created. If no
libraries are created, then there is nothing that declares a VTKmTargets
export. If there is nothing that creates a VTKmTargets export, the
export command fails.

Aaarg!!!! I can't even find a way to query whether an export is valid
(in the same way you can query whether a target exists). I added a
global variable that recorded whether vtkm_library added a library
(where things are added to the VTKmTargets export). The export command
is called if any libraries were created, a stub is created and installed
otherwise.
2016-09-07 16:48:15 -06:00
CMake Fix issue where exports failed when no libraries 2016-09-07 16:48:15 -06:00
docs Add support to VTK-m to build with C++11 2016-08-03 15:38:38 -04:00
examples Add View to rendering library 2016-09-07 16:48:04 -06:00
vtkm Make font factory arrays static for faster compilation 2016-09-07 16:48:11 -06:00
CMakeLists.txt Fix issue where exports failed when no libraries 2016-09-07 16:48:15 -06:00
CONTRIBUTING.md Add a contributing guide to vtk-m. 2015-07-29 17:33:30 -04:00
CTestConfig.cmake Switch over to uploading by https as that is required by cdash. 2016-02-23 14:03:52 -05:00
CTestCustom.cmake.in Lossen the CTestCustom regexes 2016-03-18 13:46:31 -04:00
LICENSE.txt Fix compile time errors 2015-08-21 11:17:10 -07:00
README.md Update ReadMe to reference gitlab. 2015-05-13 08:45:52 -04:00

README.md

VTK-m

One of the biggest recent changes in high-performance computing is the increasing use of accelerators. Accelerators contain processing cores that independently are inferior to a core in a typical CPU, but these cores are replicated and grouped such that their aggregate execution provides a very high computation rate at a much lower power. Current and future CPU processors also require much more explicit parallelism. Each successive version of the hardware packs more cores into each processor, and technologies like hyperthreading and vector operations require even more parallel processing to leverage each core’s full potential.

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.

Getting VTK-m

The VTK-m repository is located at https://gitlab.kitware.com/vtk/vtk-m

VTK-m dependencies are:

git clone https://gitlab.kitware.com/vtk/vtk-m.git vtkm
mkdir vtkm-build
cd vtkm-build
cmake-gui ../vtkm

A detailed walk-through of installing and building VTK-m can be found on our Contributing page