VTK/Threaded Image Algorithms

Review of Streaming Pipeline

The job of a vtkAlgorithm is to perform some operation upon some data (specifically, upon some data encapsulated in a vtkDataObject). One important aspect of VTK's streaming pipeline is that the vtkDataObject that the algorithm operates on might be one part of a larger data set. For example, a vtkImageData object might only contain a few slices of a large stack of image slices.

The portion of a data set that is contained within one vtkImageData object is described by the Extent array, which provides a (first, last) index for each of the three dimensions:

Extent = { first_idx_x, last_idx_x, first_idx_y, last_idx_y, first_idx_z, last_idx_z }

The pipeline tells the algorithm two important pieces of information:

1. How large the entire data set is (the WHOLE_EXTENT).
2. What part of the data set the output vtkImageData object should contain after the algorithm runs (the UPDATE_EXTENT).

Splitting the UPDATE_EXTENT among threads

The algorithm is responsible for producing a vtkImageData object whose size and position within the entire data set described by the UPDATE_EXTENT. But wait, what if we want to divide the work among several threads? Then the UPDATE_EXTENT must be broken into several chunks, each of which is also an extent. For example, let's say that the update extent is { 128, 255, 0, 255, 1, 100 }:

 UPDATE_EXTENT:  { 128, 255, 0, 255, 1, 100 }
 Thread 1 extent:   { 128, 255, 0, 255, 1, 25 }
 Thread 2 extent:   { 128, 255, 0, 255, 26, 50 }
 Thread 3 extent:   { 128, 255, 0, 255, 51, 75 }
 Thread 4 extent:   { 128, 255, 0, 255, 76, 100 }

In this example, the data has been divided along the Z direction.