Shuenhoy/vtk-m2
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Kenneth Moreland 0769b96bf3 Remove Width and Height from Camera 
The width and height are maintained out of necessity by the canvas. A
second copy was maintained by the camera, which was only used for
computing the aspect ratio and similar metrics for projections.

Having to maintain the width/height in two places is a bit of a hassle
and provides the opportunity for bugs if they get out of sync. Instead,
have the width/height managed in one place (the canvas) and pass them as
parameters as necessary.
2016-06-09 12:07:56 -06:00
CMake Auto-detection of cuda version requires usage of a working directory. 2016-06-03 13:10:44 -04:00
docs The Copyright statement now has all the periods in the correct location. 2015-05-21 10:30:11 -04:00
examples Remove Width and Height from Camera 2016-06-09 12:07:56 -06:00
vtkm Remove Width and Height from Camera 2016-06-09 12:07:56 -06:00
CMakeLists.txt Add test to check that all source files are part of the build system 2016-06-02 10:23:37 -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