With the major revision 2.0 of VTK-m, many items previously marked as
deprecated were removed. If updating to a new version of VTK-m, it is
recommended to first update to VTK-m 1.9, which will include the deprecated
features but provide warnings (with the right compiler) that will point to
the replacement code. Once the deprecations have been fixed, updating to
2.0 should be smoother.
This mechanism sets up CMake variables that allow a user to select which
modules/libraries to create. Dependencies will be tracked down to ensure
that all of a module's dependencies are also enabled.
The modules are also arranged into groups.
Groups allow you to set the enable flag for a group of modules at once.
Thus, if you have several modules that are likely to be used together,
you can create a group for them.
This can be handy in converting user-friendly CMake options (such as
`VTKm_ENABLE_RENDERING`) to the modules that enable that by pointing to
the appropriate group.
The enumerations in `vtkm::cont::Field::Association` were renamed in the
previous commit. The old names still exist, but are deprecated. Change
the rest of the code to use the new names.
Consumers of VTK-m when enabling of dropping of unused functions
will see VTK-m functions dropped. Previously this didn't happen
as VTK-m didn't build object files with the correct flags for this.
By allowing the linker to remove unused symbols we see a significant
saving the file size of VTK-m tests, examples, and benchmarks.
An OpenMP build of the tests and benchmarks goes from 168MB to
141MB which is roughly a 16% filesize reduction.
Initially I had presumed that these changes would increase link times.
But in measurements the total wall time for compilation of VTK-m has
stayed about the same ( seeing a decrease of 1.5% ). Presumably the
increased computation is offset by the reduction in file writing.
This is a library that contains parts of worklets that can be
precompiled into a library.
Currently, this library contains the implementation of ScatterCounting.
The oscillator is a simple analytical source of time-varying data.
It provides a function value at each point that is computed as a
sum of Gaussian kernels -- each with a specified position, amplitude,
frequency, and phase.
