Fix distributed remapping bug #2169
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It looks like that my earlier tests passed just by luck :( |
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I think the best path forward with this is to boil down the reproducer (even if it means putting a flaky reproducer inside a loop). It's a bit of work, but it's often the best path to ensure progress is made on identifying the issue. |
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vchuravy
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Feb 7, 2025
| @@ -777,38 +754,26 @@ function _collect_interpolated_values!( | |||
| if only_one_field | |||
| ClimaComms.reduce!( | |||
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Where is the synchronization of the CUDA stream?
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I spent many hours tracking down #2108 and could not find the root issue. I decided to take a different approach and simplify redefine `interpolate` in terms of `interpolate!`.
As suggested in JuliaParallel/MPI.jl#892 ``` remapper._interpolated_values[remapper.colons..., begin] ``` allocates a new copy, which can trip up CUDA's synchronization.
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#2108 partially describes the odissey I went through to understand and fix this bug.
After discussing this with folks at MPI.jl (JuliaParallel/MPI.jl#892), a potential problem was identified:
in the
ClimaComms.reduce!call allocates a new copy. This can mess up CUDA's synchronization, so that the correct data is not sent over. The simple solution is to useviewinstead of slices.In addition to this, this PR changes
interpolateto useinterpoalte!, which leads much simpler code (the reason it was not done this way originally is becauseinterpolate!is a more recent addition and behaved slightly differently).Closes #2108
Closes #2132