4 ms·
I'm curious what makes it for embedding large graphs - afaict the core is a spring model implemented as O(n^2) in nodes and single-threaded? Wasn't sure of the
by lmeyerov 4y ago
I'm curious what makes it for embedding large graphs - afaict the core is a spring model implemented as O(n^2) in nodes and single-threaded? Wasn't sure of the _size param for the nested loop, maybe I'm misreading. Was hoping there'd be something fun to solve the asymptotic scaling limit via fast multipole, NN's, etc :)
- h4kor 4y agoMain benefit over alternative (e.g. networkx): Use all cores of your machine + lower memory footprint. I had problems working with a 24k node graph, which is why I created this library. For speed I want to try two things in the future: Barnes–Hut simulation and doing the computation on the GPU.
- lmeyerov 4y agoAh yeah, I'd still fix the asymptotics first before doing multicore: 10X multicore speedup on a problem means little when haven't done the 100X+ speedup :) we do 500k+ node graphs on frontend, and million/billion on backend.. but after the core is sane