On 13/11/08 2:38 AM, Jon Olav Vik wrote:
David Nickerson <[EMAIL PROTECTED]> writes:
As a side note, I am envisioning that in the long term such simulation
data would ideally be stored using FieldML (http://www.fieldml.org)
which underneath is likely to provide several options for the high
performance persistent storage (with HDF5 being one of the options
that crops up quite frequently). Unfortunately, I'm unsure what sort
of time frame a fieldML based solution might become available...
To me, HDF5 looks like a fairly round wheel, which I'd be happy to use while
FieldML decides whether to invent its own.
One feature that would often be useful is parallel writing, for instance for
trivially parallel simulation of multiple parameter scenarios, writing results
for one scenario without blocking output from the others. HDF5 has this (http://
www.hdfgroup.org/HDF5/PHDF5/) but e.g. the Python interface (www.pytables.org)
does not yet support it.
Although PyTables provides an easy to use and efficient interface
between Python and HDF5 files, it also imposes it's own metadata model
on HDF5 files. If a general HDF5 solution, able to be used with
PyTables, were to be designed to hold CellML simulation results then the
HDF5 structure would have to allow for PyTable specific groups.
Another approach would be to specify a generic HDF5 framework for CellML
simulations and to implement this layer in C/C++, and then, if using
Python, access it via a possible PyCellML wrapper (which could also
provide access to the CellML API).
Regards,
Dave Brooks
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