The precompiled `ArrayRangeCompute` function was not following proper fast
paths for special arrays. For example, when computing the range of an
`ArrayHandleUniformPointCoordinates`, the ranges should be taken from the
origin and spacing of the special array. However, the precompiled version
was calling the generic range computation, which was doing an unnecessary
reduction over the entire array. These fast paths have been fixed.
These mistakes in the code were caused by quirks in how templated method
overloading works. To prevent this mistake from happening again in the
precompiled `ArrayRangeCompute` function and elsewhere, all templated forms
of `ArrayRangeCompute` have been deprecated. Most will call
`ArrayRangeCompute` with no issues. For those that need the templated
version, `ArrayRangeComputeTemplate` replaces the old templated
`ArrayRangeCompute`. There is exactly one templated declaration of
`ArrayRangeComputeTemplate` that uses a class, `ArrayRangeComputeImpl`,
with partial specialization to ensure the correct form is used.
What was previously declared as `ArrayHandleNewStyle` is now just the
implementation of `ArrayHandle`. The old implementation of `ArrayHandle`
has been moved to `ArrayHandleDeprecated`, and `ArrayHandle`s still
using this implementation must declare `VTKM_ARRAY_HANDLE_DEPRECATED` to
use it.
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.
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.
The ArrayHandle classes all exclusively work in the control environment.
However, CUDA likes to add __device__ to constructors, destructors, and
assignment operators it automatically adds. This in turn causes warnings
about the __device__ function using host-only classes (like
boost::shared_ptr). Solve this problem by adding explicit methods for
all of these.
Implemented this by wrapping up all these default objects in a macro.
This also solved the problem of other constructors that are necessary
for array handles such as a constructor that takes the base array
handle.
Under CUDA, the default constructors and destructors created are exported
as __host__ and __device__, which causes problems because they used a boost
pointer that only works on the host. The explicit copy constructors and
destructors do the same thing as the default ones except declared to only
work on the host.
