Also, I'm excited by the new opportunities for parallel programming and development offered by the IPython parallel programming extensions ( http://ipython.org/ipython-doc/dev/parallel/index.html), but have not had a chance to try them out. If you get a chance to use them for development, please let us know if you find them to be useful.
A On Tue, May 8, 2012 at 5:21 PM, Aron Ahmadia <aron.ahmadia at kaust.edu.sa>wrote: > b) In MATLAB, arrays are used everywhere, also for small collections, >> where one would use tuples or lists in Python (e.g. multiple return values >> from a function). When I encounter an array in the original MATLAB code, I >> have to decide whether a tuple, a list, a numpy.ndarray or a >> PETSc.Vec/PETSc.Mat is appropriate. > > > ndarray for numerical data, Python dicts and lists for more flexibility, > PETSc Vecs and Mats if you need the PETSc API. Conversion between ndarray > and PETSc Vecs is practically free, so I would keep them as numpy arrays > for as long as possible (this is the strategy in pyclaw). > > >> One approach would be to use PETSc wherever the array can be larger than >> a typical tuple. Is there a performance penalty associated with using PETSc >> Vec/Mat for rather small arrays? >> > > I agree with Matt, no performance penalty here. > > A > -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.mcs.anl.gov/pipermail/petsc-users/attachments/20120508/3c9b71fc/attachment.htm>