Firedrake meeting 2022 09 21

Date and time 2022-09-21 15:00UTC (16:00BST)

Action Items

1. Pick Chair and Minuter (SV pick)
2. ALL: (ongoing) triage the open issues and confirm if they are indeed still open (and perhaps provide labels)
3. JB: Look into updating the @parallel test marker (ongoing)
4. DH: talk to Jemma about Firedrake 2022 (nearly done! Abstracts open next week hopefully)
5. JB: SIAM CSE23 Minisymposium/minisymposterium

Minutes

Present:

Apologies:

DH: Minisymposterium at CSE

Koki to organise via slack

TK: Firedrake Overheads

See #general for discussion on strong scaling - TK managed to get impressive strong scaling

• Overheads in assign, assembly and parloops which TK has coded around
• Able to get to 80% scaling efficiency with 200 MPI processes
• Good argument for switching assign to only allow numpy assignments (quick win)

CW has some thoughts given he's rewriting pyop2 (too quick to minute!)

TK not sure if issues are to do with checks and function calls at runtime in python

• DH says certainly some python overhead due to manipulation of Args

DH: LinearSolver being faster than LinearVariationalSolver sounds like a bug.

• Either there is a significant difference we haven't thought of, or we're doing something dumb.

TK: Could make a special version of LinearVariationalSolver that has his optimisations.

• DH: Better would be to rewrite assemble as necessary which ought to be possible.

DH: Parloop caching?

• CW: Fact we're using python makes a big difference vs C

IDEA: wrap cached assignments/interpolations in Expression.

JB: Status of PETSc/petsc4py GC MR

Post rebase memory leaks fixed. Code reorganisation has been requested I will try and get this done this week.

JB: Anyone running PETSc main?

JB getting segfaults since change of C style guide

• Not that we can tell...

Daiane Dolci: Pyadjoint Questions to do with time steppers recreating blocks for every time step

DH: If you know your timestep loop structure you can improve memory usage. At the moment we leak solve blocks - pyadjoint doesn't know about what's repeated (e.g. loops in your code like a time step...)

• Can try writing an explicit continuous adjoint that knows about your time stepper
• Can also try to debug why storing solutions on the tape is causing so much memory usage (e.g. interpolate)
  • Daiane will report back next time

Merge PRs

Irksome: https://github.com/firedrakeproject/Irksome/pull/53

Date of next meeting

1600 UTC 2022-09-28