It is very easy to cause ODR violations with DeviceAdapterTagCuda.
If you include that header from a C++ file and a CUDA file inside
the same program we an ODR violation. The reasons is that the C++
versions will say the tag is invalid, and the CUDA will say the
tag is valid.
The solution to this is that any compilation unit that includes
DeviceAdapterTagCuda from a version of VTK-m that has CUDA enabled
must be invoked by the cuda compiler.
This adds an ExecutionSignature tag named Device that passes the
DeviceAdapterTag as an argument to the worklet's operator(). This allows
worklets to specialize their code based on the device.
Mask objects allow you to specify which output values should be
generated when a worklet is run. That is, the Mask allows you to skip
the invocation of a worklet for any number of outputs.
`vtkm::cont::testing` now initializes with logging enabled and support
for device being passed on the command line, `vtkm::testing` only
enables logging.
There was a direct edit to WorkletInvokeFunctorDetail.h that was not
reflected in WorkletInvokeFunctorDetail.h.in. This makes the two files
consistent so that future edits will not loose the changes.
While making changes to how execution objects work, we had agreed to
name the base object ExecutionObjectBase instead of its original name of
ExecutionObjectFactoryBase. Somehow that change did not make it through.
In order to make the change from the current way execution obejcts are utilized to the new proposed executionObjectFactory process type checks now has to look for the new execution object factory class to check against.
This allows for easier host side logic when determining grid and block
sizes, and allows for a smaller library side by moving some logic
into compiled in functions.
1. Add a 'FastVec' class that copies input vector types to an efficient
Vec type on the stack. Specializations avoid copies of already efficient
types.
2. Update 'WorldCoordinatesToParametricCoordinates' functions to utilize the
'FastVec' class. This should improve performance when the passed in
vectors are of slow types like 'vtkm::VecFromPortalPermute'.
3. Since most input Vec types will convert to the same 'FastVec' type this
also reduces the code generations. Some code refactoring was required for
this.
Sandia National Laboratories recently changed management from the
Sandia Corporation to the National Technology & Engineering Solutions
of Sandia, LLC (NTESS). The copyright statements need to be updated
accordingly.
Redesigns the TBB and Serial backends and the vtkm::exec::Task concept so that
we can re-use the same launching logic for all Worklets, instead of generating
per worlet code. To keep the performance the same the TilingTask now is past
a range of indices to work on, rather than a single index.
Binary size reduction:
WorkletTests_SERIAL old - 19MB
WorkletTests_SERIAL new - 18MB
WorkletTests_TBB old - 39MB
WorkletTests_TBB new - 18MB
libvtkAcceleratorsVTKm old - 48MB
libvtkAcceleratorsVTKm new - 19MB
Previously WorkletInvokeFunctor inherited from vtkm::exec::FunctorBase,
which is also the base class for all users Worklets and for all functors
based to DeviceAdapter::Schedule.
This is done for a few reasons. The first is that we reduce the
minimum size of user worklets. Previously the users worklet would hold
a reference to the error message, and so would the wrapper class added
when calling DeviceAdapter::Schedule. Now we only have the users worklet
holding a reference.
Second, by refactoring to have two base classes we can better improve
the documentation on what responsibilities FunctorBase.h has, compared
to TaskBase.
Change the VTKM_CONT_EXPORT to VTKM_CONT. (Likewise for EXEC and
EXEC_CONT.) Remove the inline from these macros so that they can be
applied to everything, including implementations in a library.
Because inline is not declared in these modifies, you have to add the
keyword to functions and methods where the implementation is not inlined
in the class.
