pyop3

[connorjward]

Replace PyOP2 with pyop3.

Thesis link

Summary

Data structures for unstructured meshes are much more complicated than N-dimensional arrays. Firedrake therefore does an awful lot of very involved bookkeeping to make sure that things work.

The key contribution of pyop3 is a new abstraction for describing data layouts, called axis trees. Axis trees are able to describe mesh data layouts completely from a high-level specification. This has the dual set of benefits of: (a) being able to delete a lot of complex Firedrake code, and (b) we can now express a whole suite of algorithms that would otherwise be very difficult to write.

You can think of pyop3 as 'a JIT-compiled numpy for unstructured mesh data'.

pyop3

Core concepts

Expected benefits

API changes visible in Firedrake

function.dat.data now always returns a flat array

This means that coordinates.dat.data gives back an array with shape (nverts*gdim,) instead of (nverts, gdim).

Explanation

Now that data layouts are much more flexible than before it no longer makes sense to apply multi-dimensional shape to dats. For example, consider a mixed function space with both scalar and vector subspaces. mixed_function.dat.data cannot straightforwardly have multi-dimensional shape.

Similarly, since we can now permute data layouts freely, it is valid for coordinates to be stored with effective layout (gdim, nverts).

To avoid all this confusion dat.data always returns something flat. The axis tree (dat.axes) provides the information needed to interpret it.

Drop support for variable layer extruded meshes

Users should use a cell submesh instead to get the right behaviour.

Explanation

The functionality appeared not to be used by the community (e.g. thetisproject/thetis#405) and porting the functionality would have been a large amount of work.

.sub() expects a tuple instead of integer for tensor spaces.

function.dat.vec is now a function not a property.

This allows one to pass block size to the generated Vec.