Very interesting, didn't know about graphblas!
Does anybody here know about the advantages with respect to scipy.sparse ? Does scipy.sparse use graphblas internally?
Does anybody here know about the advantages with respect to scipy.sparse ? Does scipy.sparse use graphblas internally?
graphblas provides a different bag of tools oriented toward solving graph problems, primarily around semirings and custom graph element operation. I don't think scipy.sparse, for example, provides a means for plugging in different semiring operations for computing shortest paths or max flow. On the other hand, graphblas does not provide decomposition or solving algorithms like scipy.sparse does.
It is my goal to make it so that scipy.sparse matrices, dense numpy matrices, and networkX graphs can be interchangeable used with pygraphblas in the most reasonably efficient way. This way we get all the tools in both bags. Would love to chat with more scipy developers to see where there can be unification.
UPDATE: it looks like there is some support for graph solving with scipy.sparse.csgraph, would be interesting to see how these compare to GraphBLAS based approaches!
[1] Tim Davis Research http://faculty.cse.tamu.edu/davis/research.html