Go to file
Christopher Sewell 735be208e7 Merge topic 'StreamingArray'
f779e8a1 Removing streaming scan inclusive for now
faa69e53 vtkm::internal::Add to vtkm::Add
8a8b409d Merge remote-tracking branch 'upstream/master' into StreamingArray
d7ff8097 Attempt to resolve warnings for streaming device adapter algorithms
9afbdffb Attempt fix warning in streaming
a5a487b3 Attempt 15 to resolve Windows compiler warning with streaming storage
b9d81726 Attempt 14 to resolve Windows compiler warning with streaming storage
93d7956d Attempt 13 to resolve Windows compiler warning with streaming storage
...

Acked-by: Kitware Robot <kwrobot@kitware.com>
Merge-request: !496
2016-11-09 18:53:45 -05:00
CMake Merge remote-tracking branch 'upstream/master' into StreamingArray 2016-11-09 12:15:58 -07:00
docs Add support to VTK-m to build with C++11 2016-08-03 15:38:38 -04:00
examples Get rid of warnings in examples. 2016-11-04 16:29:07 -04:00
vtkm Removing streaming scan inclusive for now 2016-11-09 15:43:57 -07:00
CMakeLists.txt Remove boost CMake logic as VTK-m doesn't require boost now. 2016-10-21 08:41:22 -04:00
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 Update the documentation to reflect we don't require boost. 2016-10-21 08:41:22 -04:00
README.md Update the documentation to reflect we don't require boost. 2016-10-21 08:41:22 -04:00

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 cores 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 required dependencies are:

VTK-m optional 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