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Allow parallel I/O for hydro and particle reading #4730

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@cphyc cphyc commented Nov 3, 2023

PR Summary

This allows parallel I/O for the RAMSES dataset. Reading a RAMSES dataset has three steps:

  • read in the AMR structure
  • read the hydro files
  • read the particle files

The strategy I have adopted is to parallelize on the first one, such that each MPI task is now in charge of a few domains and only reads those (incl. hydro + particles).

@@ -1157,9 +1199,9 @@ def alltoallv_array(self, send, total_size, offsets, sizes):
dtr = send.dtype.itemsize / tmp_send.dtype.itemsize # > 1
roff = [off * dtr for off in offsets]
rsize = [siz * dtr for siz in sizes]
tmp_recv = recv.view(self.__tocast)
tmp_recv = recv.view(transport_dtype)
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The motivation for getting rid of the cast to CHAR is so that we do not hit the limit imposed by MPI of 2**31 elements when communicating arrays as quickly.

Comment on lines +1153 to +1158
self.comm.send(
(arr.dtype.str, arr.shape, transport_dtype) + unit_metadata,
dest=dest,
tag=tag,
)
self.comm.Send([arr, mpi_type], dest=dest, tag=tag)
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Isn't there a bug here? I think this should be

Suggested change
self.comm.send(
(arr.dtype.str, arr.shape, transport_dtype) + unit_metadata,
dest=dest,
tag=tag,
)
self.comm.Send([arr, mpi_type], dest=dest, tag=tag)
self.comm.send(
(arr.dtype.str, arr.shape, transport_dtype) + unit_metadata,
dest=dest,
tag=tag,
)
self.comm.Send([tmp, mpi_type], dest=dest, tag=tag)

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I think it should be tmp, yeah, but since it has been working I think it's possible that mpi4py was fixing it implicitly.

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cphyc commented Nov 3, 2023

@yt-fido test this please

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2 participants