how did any of this work?
match other CellSet file layouts.
???
compile in CUDA.
unit tests.
also only serial.
make error message accurate
Well, this compiles and works now.
Did it ever?
use CellShapeTagGeneric
UnitTest matches previous changes.
whoops
Fix linking problems.
Need the same interface
as other ThreadIndices.
add filter test
okay, let's try duplicating CellSetStructure.
okay
inching...
change to wedge in CellSetListTag
Means changing these to support it.
switch back to wedge from generic
compiles and runs
remove ExtrudedType
need vtkm_worklet
vtkm_worklet needs to be included
fix segment count for wedge specialization
need to actually save the index
for the other constructor.
specialize on Explicit
clean up warning
angled brackets not quotes.
formatting
401b12bd6 Merge branch 'master' of https://gitlab.kitware.com/vtk/vtk-m into add_polyLine
fea18190f Specialized cases for cell-edge functions on polylines.
d310ec3aa return type is void. Call vertex/line methods, then just return.
d6898b805 Fix cell deriv for polylines and remove print statements.
9157004ac Merge branch 'master' of https://gitlab.kitware.com/vtk/vtk-m into add_polyLine
d6e2e9588 Remove debugging print statements.
b9d109ab3 Fix for CellEdgeFace test. Case is identical to polygon.
d7e793861 Fix compiler warnings. Comment out std::cout usage for testing with cuda.
...
Acked-by: Kitware Robot <kwrobot@kitware.com>
Acked-by: Kenneth Moreland <kmorel@sandia.gov>
Merge-request: !1677
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.
CUDA devices have problems with recursive algorithms that have no well-
defined depth because the stack on a CUDA device tends to be pretty
short. Fix the problem for BoundingIntervalHierarchyExec by changing to
a state-machine based algorithm that follows the hierarchy up and down.
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.
The ArrayPortalValueReference is supposed to behave just like the value
it encapsulates and does so by automatically converting to the base type
when necessary. However, when it is possible to convert that to
something else, it is possible to get errors about ambiguous overloads.
To avoid these, add specialized versions of the operators to specify
which ones should be used.
Also consolidated the CUDA version of an ArrayPortalValueReference to the
standard one. The two implementations were equivalent and we would like
changes to apply to both.
