Hi Michele,
This is really interesting. I am a co-author of the xtensor project and one
thing that could be interesting is to wrap the various sparse matrix data
structures in the form of xtensor expressions. A byproduct of doing so is
that it would simplify creating bindings for multiple scientific computing
languages (Python, Julia, R, and more coming). You can see the blog post
http://quantstack.net/c++/2017/05/30/polyglot-scientific-computing-with-
xtensor.html for reference...
Also, one quick question: is the LGPL license a deliberate choice or is it
not important to you? Most projects in the Python scientific stack are BSD
licensed. So the LGPL choice makes it unlikely that a higher-level project
adopts it as a dependency. If you are the only copyright holder, you would
still have the possibility to license it under a more permissive license
such as BSD or MIT...
Congratulations on the release!
Sylvain
On Wed, Jun 21, 2017 at 11:51 AM, Michele Martone
Hi.
I'm the author of the high performance multithreaded sparse matrix library `librsb' (mostly C, LGPLv3): http://librsb.sourceforge.net/
I'm *not* a user of SciPy/NumPy/Python, but using Cython I have written a proof-of-concept interface to librsb, named `PyRSB': https://github.com/michelemartone/pyrsb
PyRSB is in a prototypal state; e.g. still lacks good error handling. Its interface is trivial, as it mimicks that of SciPy's 'csr_matrix'. Advantages over csr_matrix are in fast multithreaded multiplication of huge sparse matrices. Intended application area is iterative solution of linear systems; particularly fast if with symmetric matrices and many rhs.
With this email I am looking for prospective: - users/testers - developers (any interest to collaborate/adopt/include the project?)
Looking forward for your feedback, Michele
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