Instead, always use precompiled versions of range computing. This means
you won't be able to specify the type. Currently, types are limited to
scalars vecs up to size 4.
The main motivation for this change is to allow you to include Field.h
with a non-device compiler. This is an important feature for our
customers.
I plan in the future to implement a mechanism to pull out a component of
most ArrayHandle's as a single array. This would enable us to support a
precompiled version that can compute the range of arbitrarily sized
Vecs.
- It fixes a lingering error triggered with BenchContour
- It reenables BenchContour
Signed-off-by: Vicente Adolfo Bolea Sanchez <vicente.bolea@kitware.com>
The old atomic compare and swap operations (`vtkm::AtomicCompareAndSwap`
and `vtkm::exec::AtomicArrayExecutionObject::CompareAndSwap`) had an
order of arguments that was confusing. The order of the arguments was
shared pointer (or index), desired value, expected value. Most people
probably assume expected value comes before desired value. And this
order conflicts with the order in the `std` methods, GCC atomics, and
Kokkos.
Change the interface of atomic operations to be patterned off the
`std::atomic_compare_exchange` and `std::atomic<T>::compare_exchange`
methods. First, these methods have a more intuitive order of parameters
(shared pointer, expected, desired). Second, rather than take a value
for the expected and return the actual old value, they take a pointer to
the expected value (or reference in `AtomicArrayExecutionObject`) and
modify this value in the case that it does not match the actual value.
This makes it harder to mix up the expected and desired parameters.
Also, because the methods return a bool indicating whether the value was
changed, there is an additional benefit that compare-exchange loops are
implemented easier.
For example, consider you want to apply the function `MyOp` on a
`sharedValue` atomically. With the old interface, you would have to do
something like this.
```cpp
T oldValue;
T newValue;
do
{
oldValue = *sharedValue;
newValue = MyOp(oldValue);
} while (vtkm::AtomicCompareAndSwap(sharedValue, newValue, oldValue) != oldValue);
```
With the new interface, this is simplfied to this.
```cpp
T oldValue = *sharedValue;
while (!vtkm::AtomicCompareExchange(sharedValue, &oldValue, MyOp(oldValue));
```
When you invoke a worklet, a scoped performance log is automatically
generated. The previous version gave the name of the worklet, which is
technically everything you need to know. However, it is also convenient
to know what type of worklet it is (e.g. a field map worklet or a
topology map worklet). This can be determined by looking at the
definition of the worklet in the source code, but that is not practical
if, for example, you want to perform automated analysis.
This change prints out the type of the dispatcher instead of the
worklet. The full type of the dispatcher includes the worklet as a
template parameter, so you get both the dispatcher/worklet type and the
worklet itself. So previously you would get log lines like
```
Invoking Worklet: 'vtkm::worklet::vtkm::worklet::ExternalFaces::NumFacesPerCell'
```
They now look like this:
```
Invoking Worklet: 'vtkm::worklet::DispatcherMapTopology<vtkm::worklet::ExternalFaces::NumFacesPerCell>'
```
Previously, the `TransferFunction` worklet required you to call
`PrepareForExecution` on the `ColorTable` and give that to the
constructor. Bad things can happen if the `ColorTable` used in the
constructor does not match the device the worklet actually gets invoked
on. Change this to make the `ColorTable` a worklet argument of type
`ExecObj`. The dispatcher will automatically call
`ColorTable::PrepareForInput` and guarantee that the devices match.
Virtual methods are being deprecated, so remove their use from the
ColorTable classes. Instead of using a virtual method to look up a value
in the ColorTable, we essentially use a switch statement. This change
also simplified the code quite a bit.
The execution object used to use pointers to handle the virtual objects.
That is no longer necessary, so a simple `vtkm::exec::ColorTable` is
returned for execution objects. (Note that this `ColorTable` contains
pointers that are specific for the particular device.) This is a non-
backward compabible change. However, the only place (outside of the
`ColorTable` implementation itself) was a single worklet for converting
scalars to colors (`vtkm::worklet::colorconversion::TransferFunction`).
This is unlikely to affect anyone.
I also "fixed" some names in enum structs. There has been some
inconsistencies in VTK-m on whether items in an enum struct are
capitolized or camel case. We seem to moving toward camel case, so
deprecate some old names.
e706880d7 Fix unnecessary deprecation warnings in visual studio
f7cc03107 Fix deprecated warnings
b27e4c7ea Ignore files for deprecated virtual classes for SourceInInstall test
284774cf4 Turn on "no virtual" option on some CI builds
cd08fd499 Add changelog for removing virtual methods
63ef84ed7 Optionally remove all use of ArrayHandleVirtual
e11f612ad Deprecate ArrayHandleVirtual
Acked-by: Kitware Robot <kwrobot@kitware.com>
Acked-by: Robert Maynard <robert.maynard@kitware.com>
Merge-request: !2256
As we remove more and more virtual methods from VTK-m, I expect several
users will be interested in completely removing them from the build for
several reasons.
1. They may be compiling for hardware that does not support virtual
methods.
2. They may need to compile for CUDA but need shared libraries.
3. It should go a bit faster.
To enable this, a CMake option named `VTKm_NO_DEPRECATED_VIRTUAL` is
added. It defaults to `OFF`. But when it is `ON`, none of the code that
both uses virtuals and is deprecated will be built.
Currently, only `ArrayHandleVirtual` is deprecated, so the rest of the
virtual classes will still be built. As we move forward, more will be
removed until all virtual method functionality is removed.
The parallel sorts in the device adapter are documented to not be
stable. Up until recently, the sorts for all the supported devices
happened to be stable (or at least provided a stable sort where needed).
However, the recent Kokkos adapter provides a sort that is no stable.
This broke some tests that relied on stable sorts when they should not
have.
Fix the tests that relied on stable sort to check the results.
The testing helper class provided a method named `GetTestDataBasePath`
that returned the base path to all the data files stored in the VTK-m
repo. This is fine, but it was a little cumbersome to build filenames.
To make things easier, there is now a new method named `DataPath` that
takes a string of the filename (or, rather, subpath) to the file in that
directory and automatically builds the path to it.
We have made several improvements to adding data into an `ArrayHandle`.
## Moving data from an `std::vector`
For numerous reasons, it is convenient to define data in a `std::vector`
and then wrap that into an `ArrayHandle`. It is often the case that an
`std::vector` is filled and then becomes unused once it is converted to an
`ArrayHandle`. In this case, what we really want is to pass the data off to
the `ArrayHandle` so that the `ArrayHandle` is now managing the data and
not the `std::vector`.
C++11 has a mechanism to do this: move semantics. You can now pass
variables to functions as an "rvalue" (right-hand value). When something is
passed as an rvalue, it can pull state out of that variable and move it
somewhere else. `std::vector` implements this movement so that an rvalue
can be moved to another `std::vector` without actually copying the data.
`make_ArrayHandle` now also takes advantage of this feature to move rvalue
`std::vector`s.
There is a special form of `make_ArrayHandle` named `make_ArrayHandleMove`
that takes an rvalue. There is also a special overload of
`make_ArrayHandle` itself that handles an rvalue `vector`. (However, using
the explicit move version is better if you want to make sure the data is
actually moved.)
## Make `ArrayHandle` from initalizer list
A common use case for using `std::vector` (particularly in our unit tests)
is to quickly add an initalizer list into an `ArrayHandle`. Now you can
by simply passing an initializer list to `make_ArrayHandle`.
## Deprecated `make_ArrayHandle` with default shallow copy
For historical reasons, passing an `std::vector` or a pointer to
`make_ArrayHandle` does a shallow copy (i.e. `CopyFlag` defaults to `Off`).
Although more efficient, this mode is inherintly unsafe, and making it the
default is asking for trouble.
To combat this, calling `make_ArrayHandle` without a copy flag is
deprecated. In this way, if you wish to do the faster but more unsafe
creation of an `ArrayHandle` you should explicitly express that.
This requried quite a few changes through the VTK-m source (particularly in
the tests).
## Similar changes to `Field`
`vtkm::cont::Field` has a `make_Field` helper function that is similar to
`make_ArrayHandle`. It also features the ability to create fields from
`std::vector`s and C arrays. It also likewise had the same unsafe behavior
by default of not copying from the source of the arrays.
That behavior has similarly been depreciated. You now have to specify a
copy flag.
The ability to construct a `Field` from an initializer list of values has
also been added.
`CoordinateSystem` differed from `Field` in that its `GetData`
method returned an `ArrayHandleVirtualCoordinates` instead of
a `VariantArrayHandle`. This is probably confusing since
`CoordianteSystem` inherits `Field` and has a pretty dramatic
difference in this behavior.
In preparation to deprecate `ArrayHandleVirtualCoordinates`, this
changes `CoordiantSystem` to be much more like `Field`. (In the
future, we may change the `CoordinateSystem` to point to a `Field`
rather than be a special `Field`.)
A method named `GetDataAsMultiplexer` has been added to
`CoordinateSystem`. This method allows you to get data from
`CoordinateSystem` as a single array type without worrying
about creating functors to handle different types and without
needing virtual methods.
For some reason, `UnitTestContourTreeUniformAugmentedFilterCUDA` was
deadlocking on some of the dashboards when `VTKM_ASSERT` was changed to
be empty when compiling CUDA kernels (for compiler performance reasons).
Fix this by calling `assert` directly in this case.
For the life of me, I cannot figure out why this would be an issue.
Clearly the `assert` is never actually called or else the test would
error out (unless a special condition in CUDA is causing it to be
hidden). But if you take out the code, something changes to lock up the
kernel.
0a4317709 Fix issues of calling __host__ from __device__
dd4d88cd5 Fix warnings about comparing floating point values
cd4b59059 Fix warnings about data type conversion
Acked-by: Kitware Robot <kwrobot@kitware.com>
Acked-by: Robert Maynard <robert.maynard@kitware.com>
Merge-request: !2146
df0881631 minor coding style improvment
68c18f154 remove redundant #include
ba35520b1 use condition number for error tolerance
ee422b7f2 move data member initialization to constructors
e0c4db209 add VTKM_EXEC_CONT to constructor
c25f0b4bb Rename StatisticalMoments. more unit tests
5eeeb4791 Change StatState's API to better conform to VTKm's coding standard
794db28ad Merge branch 'master' into stats_by_key
...
Acked-by: Kitware Robot <kwrobot@kitware.com>
Merge-request: !2128
This merge request is Phase 1 of several to implement the distributed parallel
contour tree in VTKm. This merge requests adds the base outline for the
algorithm. The implementation of the details of the algorithm in the
BoundaryRestrictedAugmentedContourTree.h is currently still missing.
However, these will require a substantial (~3000) lines of additional code.
The goal is to stage the integration process across merge requests to make
the review process simpler.
Initially, the probe filter would simply not set a value if a sample was
outside the input `DataSet`. This is not great as the memory could be
left uninitalized and lead to unpredictable results. The testing
compared these invalid results to 0, which seemed to work but is
probably unstable.
This was partially fixed by a previous change that consolidated to
mapping of cell data with a general routine that permuted data. However,
the fix did not extend to point data in the input, and it was not
possible to specify a particular invalid value.
This change specifically updates the probe filter so that invalid values
are set to a user-specified value.
930c3d2fb reproduce_ci_env better detects which stage a job is for
71d9d4311 Doxygen is now generated by gitlab and done on each master merge
a652f7fe1 Update vtk-m doxygen to generate less warnings
97a2408fc Correct warnings for using TBB 2020 deprecated functions
Acked-by: Kitware Robot <kwrobot@kitware.com>
Merge-request: !2117
This fixes a bug introduced in commit
93d87e06fd7a0ef479a324e5cd2453c1c7ece0ee
Part of the commit moved fromusing a `BoundaryState` object to keeping
boundary flags in a `vtkm::Vec<bool,3>`. However, the meaning of the
flag got inverted. The `BoundaryState::IsRadiusIn?Boundary` methods
returned true if the current location was inside the bounds (i.e. _not_
on the boundary), but the new flags are true if the current location is
on the boundary (the inverse).
The updating of the code for the `StructuredPointGradient::Jacobian`
method got the flag somewhat wrong and scaled the wrong case.
e9fd545b0 Merge branch 'master' of gitlab.kitware.com:vtk/vtk-m into euler_integrator_fix
23126bbec Integrator status fix for consistant behavior
3e18f105e Fixing Integrator Status Behavior
ff112e424 Integrator status behavior check
343f2d577 Merge branch 'master' of gitlab.kitware.com:vtk/vtk-m into euler_integrator_fix
82cfba27c Rectify testing code
8ddecbb43 Fixing test issues
6274b1657 Updating Euler Integrator to work
Acked-by: Kitware Robot <kwrobot@kitware.com>
Merge-request: !2023
We now use SumYAxis when executing with CUDA for better memory patterns.
Instead of using the heavy Pass4/Pass4WithNormals, CUDA now uses a
2 pass approach with the second pass outputting the normals and
coordinates using with significantly less warp divergence
First the Pass1 now uses WorkletVisitPointsWithCells as it is
faster since it doesn't compute some implicit boundary / neighborhood
info.
Second we reworked the logic around using `Fill` and a conditional
write of the edge case. The requirements of SMP when on a NUMA
machine is the complete opposite of what works great with CUDA.
The only reason Keys has a template is so that it can hold a UniqueKeys
array and provide the key for each group. If that is not needed and you
want to implement a library function that takes a keys object, you can
now grab the Keys superclass KeysBase. KeysBase is not templated, so you
can pass it to a standard method in a library.
-- Setting the Spatial and OK bit both to 1 for Euler integrator
similar to RK4
-- After discussion w/ Dave, the Spatial/Temporal bit will be the
status of the particle and not the OK bit.
The version of `Filter::Execute` that takes a policy as an argument is now
deprecated. Filters are now able to specify their own fields and types,
which is often why you want to customize the policy for an execution. The
other reason is that you are compiling VTK-m into some other source that
uses a particular types of storage. However, there is now a mechanism in
the CMake configuration to allow you to provide a header that customizes
the "default" types used in filters. This is a much more convenient way to
compile filters for specific types.
One thing that filters were not able to do was to customize what cell sets
they allowed using. This allows filters to self-select what types of cell
sets they support (beyond simply just structured or unstructured). To
support this, the lists `SupportedCellSets`, `SupportedStructuredCellSets`,
and `SupportedUnstructuredCellSets` have been added to `Filter`. When you
apply a policy to a cell set, you now have to also provide the filter.
This commit splits ThreadIndicesTopologyMap into two
different specializations which can be instanciated with the
tags: DefaultScatterAndMaskTag and CustomScatterAndMaskTag.
These specialization will allow ThreadIndicesTopologyMap
instances to avoid holding in memory InputIndex, OutputIndex and ThreadIndex
variables when Mask = MaskNone and Scatter = ScatterIdentity which in this case
are not needed since no transformation are done.
Signed-off-by: Vicente Adolfo Bolea Sanchez <vicente.bolea@kitware.com>
