pygraphistry

We do millions of edges in the browser fine via webgl (graphistry.com / https://github.com/graphistry/pygraphistry ) . For forceatlas and other interactive & iterative analytics algs (t-sne, ...), it's hard to keep 100K+ nodes interactive via webgl. Most webgl attempts go naive all-to-all O(n^2), so the graph size quickly hits a ceiling. We rewrote to use GPUs end-to-end in the server so we can do trickier opencl/cuda algs that achieve O(nlogn) and O(n). Funny enough, users don't notice round trip costs -- or get even faster perf -- as our 2.0 engine does live streaming between client/cloud to hit ~20fps, similar to how streaming movies keep up frame rate. Our problem is now that JS only supports pointers up to 2GB :)

Yep -- at https://github.com/graphistry/pygraphistry, we started by making millions of nodes/edges interactive. If you use notebooks, can signup on our site and get going. The trick is we connect GPUs in the browser to GPUs in the cloud, and encapsulate it enough that you can stick to writing standard SQL/pandas/etc. We've been curious about server-side static tile rendering for larger graphs, but has been on the back-burner. (We already connect to GPUs on the server, so not rocket science.) Currently, we're actively increasing how much can be ingested + computed on, such as for finding influencers, communities & rings, etc. However, visualizing that hasn't been an operational priority for our users. More useful to generate the communities, and then either inspect individual ones, or see how communities stitch together: quickly run out of