parallel output of a time series in hdf5 format

Question

I found that pvd is not well suited for my code. I want to use h5 format to save the solution at each time step in parallel. I want to know the hdf5 equivalent of

# solve for u and save at every time step 
f = File("output.pvd")
while t < T:
    u.vector() = u0.vector()
    solve.solve()    # solve for u
    f << u, t

that paraview can read easily.

Comments

Hi, can you tell us why you think HDF5 format is better?
Thanks

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The main reason was portability. 'pvd' outputs many files (equal to the # of processors used to run the code). And some benchmarks indicate that HDF5 is faster.

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Thanks, I'll take a look at HDF5 too...

Answer 1

f = HDF5File('foo.h5')

But as I know, XDMF format is suited for visualization. (In fact it uses HDF5 as a backend.) So,

f = XDMFFile('foo.xdmf')

Explore f.parameters using

 info(f.parameters, True)

to avoid duplicate mesh storage when appropriate.

Comments

xdmf is really good. Thanks!

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Hi guys, Looking at the xdmffile parameters, 'rewrite_function_mesh' is self explanatory, but what does ' flush_output' mean exactly?
Thanks

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flush_output avoids buffering (at some performance cost) so that files should be consistent and ready for reading at every single time during calculation.

There is also new integer parameter multi_file which can serve to workaround issue 278.

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Thanks. I was playing around with it and found that it helped with the issue 278.