Previously ArrayHandleBasicImpl had no support for OpenMP since
we forgot to update the implementation. This version will
work when adding new devices without any changes.
14824bd42 Make sure people always treat DeviceAdapterId as a proper type
Acked-by: Kitware Robot <kwrobot@kitware.com>
Acked-by: Sujin Philip <sujin.philip@kitware.com>
Merge-request: !1332
2c6ca906f Enable building the worklets when OpenMP is enabled.
d595abf90 WrappedBinaryOperator now supports std::vector<bool>::reference
Acked-by: Kitware Robot <kwrobot@kitware.com>
Acked-by: Allison Vacanti <allison.vacanti@kitware.com>
Merge-request: !1327
96ae94420 Simplified execution object creation for atomic array
0bd197af9 moved TwoLevelUniformGridExecutionObject to vtkm/exec/internal
6ce895be8 simplified how atomic arrays create execution objects
f1ee5b92a fix a rebase error
25d140361 fix bad rabse for wireframer
f892695f1 fixing so wierd merging issue
9bb00ec66 moved the execution object for TwoLevelUniform grid to vrkm::exec
db1c9bfee Change the namespacing of atomic array
...
Acked-by: Kitware Robot <kwrobot@kitware.com>
Acked-by: Robert Maynard <robert.maynard@kitware.com>
Merge-request: !1243
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.
Benchmarking in VTK showed significant overhead in the computation
of the reverse connectivity calculation in
ConnectivityExplicitInternals::ComputeCellToPointConnectivity.
This patch adds a ReverseConnectivityBuilder that reduces the amount of
time and memory needed to build the table by using an atomic histogram
approach that avoids a costly radix SortByKey.
Key operations in the new helper class are templated to allow this
approach to be reused by VTK-specific cell array converters.
There is no real reason why you cannot construct an
ArrayPortalFromIterators on a device, so go ahead and let that happen.
(This removes some CUDA warnings about calling __host__ from
__device__.)
Having VTKM_EXEC on algorithms for CPU devices was problematic because
the algorithms were specific to the CPU, but during a CUDA compile it
would try to compile device code (for no reasons since it was never
called on a device).
Remove these identifiers for the idea that a device implementation knows
specifically what function modifiers to use and does not need the VTK-m
defined catch-alls.
By making is_base_of part of PrepareArgForExec, we can shorten not only
the C++ code but also the code that is generated by it.
Also, return && instead of by value when passing through the argument.
Changes thanks to Robert Maynard.
This commit adds a worklet as well as a filter that modify point coordinates by moving points
along point normals by the scalar amount times the scalar factor.
It's a simpified version of the vtkWarpScalar class in VTK. Additionally the filter doesn't
modify the point coordinates, but creates a new point coordinates that have been warped.
This commit adds a worklet as well as a filter that modify point coordinates by moving points
along a vector by a certain scalar amount.
It's a simpified version of the vtkWarpVector in VTK.
It doesn't modify the point coordinates, but creates a new point coordinates that have been warped.
The original design of invoke and the transport infrastructure
relied on the implementation behavior of vtkm::cont types
such as ArrayHandle that used an internal shared_ptr to managed
state. This allowed passing by value instead of passing by
non-const ref when needing to transfer information to the device.
As VTK-m adds support for classes that use virtuals the ability
to pass by base pointer type allows for us to invoke worklets
using a base type without the risk of type slicing.
Additional by moving over to a non-const ref Invocation we
can update all transports that have 'output' to now be
by ref and therefore support types that can't be copied while
being 'more' correct.
The invocation parameters need to be non const as we want to
be able to call non-const methods like `PrepareForOutput` on them
from a transport function.
The original implementation abused the fact that everything
could be copied by value and have that work properly. But
when we start introducing virtual classes copying by value of
a base type can cause type slicing.
Most of the arguments given to device adapter algorithms are actually
control-side arguments that get converted to execution objects internally
(usually a `vtkm::cont::ArrayHandle`). However, some of the algorithms,
take an argument that is passed directly to the execution environment, such
as the predicate argument of `Sort`. If the argument is a plain-old-data
(POD) type, which is common enough, then you can just pass the object
straight through. However, if the object has any special elements that have
to be transferred to the execution environment, such as internal arrays,
passing this to the `vtkm::cont::Algorithm` functions becomes
problematic.
To cover this use case, all the `vtkm::cont::Algorithm` functions now
support automatically transferring objects that support the `ExecObject`
worklet convention. If any argument to any of the `vtkm::cont::Algorithm`
functions inherits from `vtkm::cont::ExecutionObjectBase`, then the
`PrepareForExecution` method is called with the device the algorithm is
running on, which allows these device-specific objects to be used without
the hassle of creating a `TryExecute`.
