NetworkX & NVIDIA co-developed a GPU-accelerated backend powered by NVIDIA cuGraph, to accelerate popular graph algorithms like betweenness centrality, Louvain, and PageRank. Depending on the algorithm and graph size, users can expect to see significant performance gains on NetworkX workflows - up to 50x, even 500x over NetworkX on CPU.

With zero code changes developers can run NetworkX powered by cuGraph on NVIDIA GPUs for larger graphs and faster performance.

Check it out : https://youtu.be/3EsbU1gcH5c

Check out this amazing blog : https://developer.nvidia.com/blog/networkx-introduces-zero-code-change-acceleration-using-nvidia-cugraph/?ncid=ref-inor-830854-vt27

Overview: NetworkX accelerated by cuGraph
1. NetworkX is an open source high performance graph analytics library that is now GPU-accelerated with NVIDIA's cuGraph library.
2. The NetworkX GPU engine powered by NVIDIA nx-cuGraph is now available for general access.
3. With zero code changes developers can run NetworkX accelerated by cuGraph for NVIDIA GPUs.
4. NetworkX powered by cuGraph can achieve a range of speed ups from 63x up to 487x over CPU depending on the NetworkX algorithm used.

YouTube

Achieve up to 500x Faster NetworkX with Zero Code Changes Using NVIDIA cuGraph

NetworkX, a popular Python graph analytics library, now includes an in-memory GPU backend powered by cuGraph for popular graph algorithms such as Louvain, betweenness centrality, PageRank, and others.

NVIDIA cuGraph creates speedups of 50x to 500x on large…