pygraphblas

> They can absolutely have meanings assigned outside the usual "when multiplied by a vector" type of calculations. For example the "adjacency matrix" representation of a graph is very often never multiplied by a vector even in academic algorithm descriptions. Not disputing your basic point, but I'm not sure "very often never" is entirely accurate. In the GraphBLAS API vector/matrix and matrix/vector multiplication is key for almost all algorithms that depend on breadth first search, this is because matrix/vector multiplication is a single step in a BFS which is the core operation of the GraphBLAS. The vector is typically used to hold the current frontier (and mask). See the "Shortest Path Lengths" example here: https://github.com/michelp/pygraphblas/blob/master/pygraphbl... (disclosure, I am the pygraphblas author). > Purist test: aren'

Numba is indeed a great library for speeding up Python and also doing other useful things when interacting when external libraries. For example the "jit compile a single function" feature is gold when you need to pass a function callback pointer into a C library. This is how pygraphblas compiles Python functions into semiring operators that are then passed to the library which has no idea that the pointer is to jit compiled python function: https://github.com/michelp/pygraphblas/blob/master/tests/tes...

SuiteSparse doesn't support GPUs just yet, but when it does, you can do this with pygraphblas: https://github.com/michelp/pygraphblas (I am the pygraphblas author)

It's so early in this work that you might be the first person asking those specific questions. I'm no expert but I take it by VLSI you mean doing circuit routing and simulation and optimizing that topology. My gut tells me those would be good fits for the GraphBLAS. If the base types don't suit your needs, you can always make your own. Tim Davis has talked about how he's made new types that are small nxn matrices as elements of a larger matrix. You can have complex, quaternion, or complex bags of stuff as matrix elements as long as you define the operators you need to work on those types. Here's an example of using User Defined Types for a shortest path algorithm that also stores backlinks along the shortest path so the shortest path tree is materialized. in Python: https://github.com/michelp/pygraphblas/blob/master/pygraphbl...

There is also a Python wrapper: https://github.com/michelp/pygraphblas

Here are two different PageRank approaches with pygraphblas: https://github.com/michelp/pygraphblas/blob/master/pygraphbl...

pygraphblas author here, here is a good notebook introduction to the very basics of GraphBLAS with Python. The concepts carry naturally to the C API as well: https://github.com/michelp/pygraphblas/blob/master/pygraphbl... I also made a quick introduction video for a paper submission you can see here: https://www.youtube.com/watch?v=JUbXW_f03W0