dolfin team mailing list archive

[Joachim Haga <jobh@xxxxxxxxx>]

Aha, not so simple then. I don't quite get the multiple backend use
case, but if it's supported then it's supported.

I didn't quite understand your suggestion. Do you mean to make
down_cast() a method on Matrix et al instead of a global method? That
sounds nice...

Anyhow: I'm away for six weeks, starting tomorrow, and don't know how
much I'll be able to communicate when away. Feel free to leave this bug
(and others, don't know if I have time now to report more) unresolved.
Unless you want to fix them, of course :)

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https://bugs.launchpad.net/bugs/747297

Title:
  Python: Cache tensor types

Status in DOLFIN:
  New

Bug description:
  In a matrix-multiplication heavy Python workload, I see something like
  5-10% of the time being spent in get_tensor_type(). The attached patch
  memoizes the result, per type. Seems to work fine, but should be
  sanity checked (is per-type result ok?).