warp.tile\_scan\_inclusive
==========================

.. currentmodule:: warp._src.lang

.. function:: tile_scan_inclusive(a: Tile[Scalar, tuple[int, ...]]) -> Tile[Scalar, tuple[int, ...]]

   .. wp-function-tags::
      :kernel: true
      :python: false
      :differentiable: false

   Return a new tile containing the inclusive prefix sums of a tile.
   
   This is a cooperative operation: the threads of the block divide the work between
   them, so every thread must reach the call.
   
   Element ``i`` of the result is the sum of input elements ``0`` through ``i``.
   A multi-dimensional tile is scanned over its flattened row-major sequence and the
   result keeps the input shape. On CUDA, this operation reserves a tile's worth of shared
   memory (see :ref:`tile_shared_memory_budget`).
   
   :param a: The input tile. Must be a tile of :class:`warp.float32`, :class:`warp.int32`,
             or :class:`warp.uint32`.
   
   :returns: A register tile with the same shape and dtype as ``a``.
   
   .. rubric:: Example
   
   .. testcode::
   
       @wp.kernel
       def running_totals(x: wp.array[float], out: wp.array[float]):
           t = wp.tile_load(x, shape=4)
           wp.tile_store(out, wp.tile_scan_inclusive(t))
   
       x = wp.array([3.0, 1.0, 4.0, 2.0], dtype=float)
       out = wp.zeros(4, dtype=float)
   
       wp.launch_tiled(running_totals, dim=1, inputs=[x], outputs=[out], block_dim=2)
   
       print(out.numpy())
   
   .. testoutput::
   
       [ 3.  4.  8. 10.]