Apparently this has been reported before as a problem with PETSc/HDF5
integration:  
https://lists.mcs.anl.gov/pipermail/petsc-users/2012-January/011980.html

On Thu, Nov 9, 2017 at 8:37 AM, Michael K. Edwards
<m.k.edwa...@gmail.com> wrote:
> Thank you for the validation, and for the suggestion to use
> H5Sselect_none().  That is probably the right thing for the dataspace.
> Not quite sure what to do about the memspace, though; the comment is
> correct that we crash if any of the dimensions is zero.
>
> On Thu, Nov 9, 2017 at 8:34 AM, Jordan Henderson
> <jhender...@hdfgroup.org> wrote:
>> It seems you're discovering the issues right as I'm typing this!
>>
>>
>> I'm glad you were able to solve the issue with the hanging. I was starting
>> to suspect an issue with the MPI implementation but it's usually the last
>> thing on the list after inspecting the code itself.
>>
>>
>> As you've seen, it seems that PETSc is creating a NULL dataspace for the
>> ranks which are not contributing, instead of creating a Scalar/Simple
>> dataspace on all ranks and calling H5Sselect_none() for those that don't
>> participate. This would most likely explain the reason you saw the assertion
>> failure in the non-filtered case, as the legacy code probably was not
>> expecting to receive a NULL dataspace. On top of that, the NULL dataspace
>> seems like it is causing the parallel operation to break collective mode,
>> which is not allowed when filters are involved. I would need to do some
>> research as to why this happens before deciding whether it's more
>> appropriate to modify this in HDF5 or to have PETSc not use NULL dataspaces.
>>
>>
>> Avoiding deadlock from the final sort has been an issue I had to re-tackle a
>> few different times due to the nature of the code's complexity, but I will
>> investigate using the chunk offset as a secondary sort key and see if it
>> will run into problems in any other cases. Ideally, the chunk redistribution
>> might be updated in the future to involve all ranks in the operation instead
>> of just rank 0, also allowing for improvements to the redistribution
>> algorithm that may solve these problems, but for the time being this may be
>> sufficient.

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