Erik Welch
I work on open-source at NVIDIA, including Dask, GraphBLAS and python-graphblas, NetworkX, RAPIDS (cudf, cugraph), toolz, afar, etc.
Sessions
12-02
19:00
30min
100x Faster NetworkX: Dispatching to GraphBLAS
Jim Kitchen, Erik Welch, Mridul Seth
NetworkX is the most popular graph/network library in Python. It is easy to use, well documented, easy to contribute to, extremely flexible, and extremely slow for large graphs.
An upcoming release begins to fix that last issue by calling fast GraphBLAS implementations instead of the native Python implementation.
If you use NetworkX or have ever written a graph algorithm, this talk will be of interest to you as it shows how NetworkX is planning on a path of pluggable algorithm libraries so users can opt-in to faster implementations with minimal code changes.
Talk Track I