This includes changing methods like LoadDataForInput to PrepareForInput.
It also changed the interface a bit to save a reference to the storage
object. (Maybe it would be better to save a pointer?) These changes also
extend up to the ArrayManagerExecution class, so it can effect device
adapter implementations.
This API change effects both ArrayTransfer and ArrayManagerExecution.
This is in preparation for a future change to make the API more
consistent with ArrayHandle.
The UserPortal in ArrayHandle was used to copy a pointer the user
created into an ArrayHandle to use in VTK-m algorithms. However, this is
only really valid for a basic storage, so the functionality has been
moved there, and you have to construct an ArrayHandle with a storage
instead of an array portal.
Our approach of using the underlying allocator inside thrust was a bad approach,
for some reason it fails to properly allocate uint8's or int8's on the correct
boundaries. I expect that this logic is somewhere else in the code and
instead we should use thrust::system::cuda::vector which does this properly.
Add an Allocate method in ArrayHandle that basically forwards the
alllocate request to the storage object. This allows some measure of
control of the array from the control side. You can allocate the array
and set values (by getting the control array portal) if you so desire.
Previously when ReleaseResourcesExecution was called, the method blindly
deleted the execution array regardless of whether there was a valid copy
in the control environment. This could potentially lose data. What if
someone wanted to conserve memory on the device by clearing the array of
an output array?
There is also now an internal method that blindly deletes the array.
This is good for internal functions that are doing something to
invalidate the execution data anyway.
Fixed a problem where ArrayHandle would cause a crash if you tried to
get the control portal on an uninitialized array (it was supposed to
throw an exception).
Also changed some methods in ArrayHandle so that they work resonably
without error when used with an uninitialized array. Specifically, the
aforementioned behavior was changed to "allocate" an array of size 0
(that is, call Allocate(0) on the storage object) to return an empty
array portal rather than throw an error. Although this use of
ArrayHandle can be considered erroneous, it is convenient the get an
empty array portal when dealing with a potentially unallocated array
rather than create a special condition.
The namespaces need to be different for each test, or else only the first
implementation of the function will be used for all tests that call that
function.
Also updated the test to verify that we can count starting from a non zero
number.
The functors in the ForEach, StaticTransform, and DynamicTransform
methods sometimes can use the index of the parameter that they are
operating on. This can be a helpful diagnostic in compile and run-time
errors. It is also helpful when linking parameters from one
FunctionInterface with those of another.
This new features are now replacing implementations using the Zip
functionality that was removed earlier. The implementation is actually
simplified a bit.
Porting the dax device adapter over to vtkm. Unlike the dax version, doesn't
use the thrust::device_vector, but instead uses thrust::system calls so that
we can support multiple thrust based backends.
Also this has Texture Memory support for input array handles. Some more work
will need to be done to ArrayHandle so that everything works when using an
ArrayHandle inplace with texture memory bindings.
A couple of tests were failing with the Intel compiler due to
imprecision in comparing floating point values.
Also snuck in some minor documentation fixes in a comment for
FunctionInterface.
The unit test for StorageBasic tested the StealArray feature and then
used the delete[] operator on the stolen array to deallocate it. For
many standard libraries the default implementation for delete[] is
the same as (or at least compatible with) std::allocator, but for
the PGI compiler they were not compatible and this resulted in a
run-time error. This change fixes the problem with the test by using
the same allocator as the StorageBasic test.
It's easy to put accidently put something that is not a valid tag in a
ControlSignature or ExecutionSignature. Previously, when you did that
you got a weird error at the end of a very long template instantiation
chain that made it difficult to find the offending worklet.
This adds some type checks when the dispatcher is instantated to check
the signatures. It doesn't point directly to the signature or its
parameter, but it is much closer.
Instead of just checking that a dispatcher's Invoke input is an
ArrayHandle, also check that the ValueType of the ArrayHandle is
compatible with the types of the worklet operator. This is done by
adding a template argument to the ControlSignature tags that is a type
list tag that gets passed to the type check.
The Transport class is responsible for moving data from the control
environment to the execution environment. (Actually, it might be more
accurate to say it gets the execution environment associated with a
given control object.) The Transport class is templated with a tag that
controls the mechanism used for the transport.
Lots of tests have to move values in and out of arrays and check them
against expected values. It is also often the case that these tests are
run on lots of different types. There is some repeated code for
generating known values for particular indices. This change unifies some
of that. This can probably also encourage making more generic tests.
Providing these types tends to "lock in" the precision of the algorithms
used in VTK-m. Since we are using templating anyway, our templates
should be generic enough to handle difference precision in the data.
Usually the appropriate type can be determined by the data provided. In
the case where there is no hint on the precision of data to use (for
example, in the code that provides coordinates for uniform data), there
is a vtkm::FloatDefault.
Before we assumed that we would only use the basic types specified by
the widths of vtkm::Scalar and vtkm::Id. We want to expand this to make
sure the code works on whatever data precision we need.
Since we want our code to generally handle data of different precision
(for example either float or double) expand the types in our list types
to include multiple precision.
Previously we just hand coded base lists up to 4 entries, which was fine
for what we were using it for. However, now that we want to support base
types of different sizes, we are going to need much longer lists.
