CUDA-Specific Types

.. note::

This page is about types specific to CUDA targets. Many other types are also
available in the CUDA target - see :ref:`cuda-built-in-types`.

Vector Types

[CUDA Vector Types](https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#built-in-vector-types)
are usable in kernels. There are two important distinctions from vector types in CUDA C/C++:

First, the recommended names for vector types in Numba CUDA is formatted as ``<base_type>x<N>``,
where ``base_type`` is the base type of the vector, and ``N`` is the number of elements in the vector.
Examples include ``int64x3``, ``uint16x4``, ``float32x4``, etc. For new Numba CUDA kernels,
this is the recommended way to instantiate vector types.

For convenience, users adapting existing kernels from CUDA C/C++ to Python may use
aliases consistent with the C/C++ namings. For example, ``float3`` aliases ``float32x3``,
``long3`` aliases ``int32x3`` or ``int64x3`` (depending on the platform), etc. 

Second, unlike CUDA C/C++ where factory functions are used, vector types are constructed directly
with their constructor. For example, to construct a ``float32x3``:

.. code-block:: python3

    from numba.cuda import float32x3

    # In kernel
    f3 = float32x3(0.0, -1.0, 1.0)

Additionally, vector types can be constructed from a combination of vector and
primitive types, as long as the total number of components matches the result
vector type. For example, all of the following constructions are valid:

.. code-block:: python3

    zero = uint32(0)
    u2 = uint32x2(1, 2)
    # Construct a 3-component vector with primitive type and a 2-component vector
    u3 = uint32x3(zero, u2)
    # Construct a 4-component vector with 2 2-component vectors
    u4 = uint32x4(u2, u2)

The 1st, 2nd, 3rd and 4th component of the vector type can be accessed through fields 
``x``, ``y``, ``z``, and ``w`` respectively. The components are immutable after
construction in the present version of Numba; it is expected that support for
mutating vector components will be added in a future release.

.. code-block:: python3

    v1 = float32x2(1.0, 1.0)
    v2 = float32x2(1.0, -1.0)
    dotprod = v1.x * v2.x + v1.y * v2.y