trixi-framework / Trixi.jl

Trixi.jl: Adaptive high-order numerical simulations of conservation laws in Julia
https://trixi-framework.github.io/Trixi.jl
MIT License
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Set TreeMesh capacity attribute also when using MPI #1862

Closed benegee closed 4 months ago

benegee commented 4 months ago

Resolves #1861

github-actions[bot] commented 4 months ago

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codecov[bot] commented 4 months ago

Codecov Report

Attention: Patch coverage is 0% with 1 lines in your changes are missing coverage. Please review.

Project coverage is 89.44%. Comparing base (b11bc10) to head (485355a). Report is 1 commits behind head on main.

Files Patch % Lines
src/meshes/mesh_io.jl 0.00% 1 Missing :warning:
Additional details and impacted files ```diff @@ Coverage Diff @@ ## main #1862 +/- ## ========================================== - Coverage 89.45% 89.44% -0.00% ========================================== Files 438 438 Lines 35592 35593 +1 ========================================== Hits 31836 31836 - Misses 3756 3757 +1 ``` | [Flag](https://app.codecov.io/gh/trixi-framework/Trixi.jl/pull/1862/flags?src=pr&el=flags&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=trixi-framework) | Coverage Δ | | |---|---|---| | [unittests](https://app.codecov.io/gh/trixi-framework/Trixi.jl/pull/1862/flags?src=pr&el=flag&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=trixi-framework) | `89.44% <0.00%> (-<0.01%)` | :arrow_down: | Flags with carried forward coverage won't be shown. [Click here](https://docs.codecov.io/docs/carryforward-flags?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=trixi-framework#carryforward-flags-in-the-pull-request-comment) to find out more.

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sloede commented 4 months ago

Thanks! Did you check whether loading a mesh in serial works when you save it in parallel with a small capacity? I don't remember right now whether the capacity is a local one or needs to be big enough to store the data from all MPI ranks in parallel. That's why I'm asking.

The capacity is always global. Since the TreeMesh is parallelized by keeping a full copy on each rank and just syncing it between the processes, a "local" capacity does not make much sense anyways

benegee commented 4 months ago

Thanks for the explanation. I would not have known.

I only tested running the simulation in parallel and reading the results in serial via Trixi2Vtk.