Had any exposure to r=2 hypergraph implementations on the GPU? Ideally with an efficient way to determine if the graph is acyclic?
(The CPU algos for doing this work great on CPUs but are woeful on GPUs.)
(The CPU algos for doing this work great on CPUs but are woeful on GPUs.)
For the 'easy' way we do in gfql, which is basically vector ops on bulk wavefronts, we can do massive cypher traversals like you're asking, like 100M edges touched in a result substep, and on a tiny GPU. There are other such bulk patterns we want to add such as Pregel style, which open other algorithms here. In practice we can often just call cudf/cugraph as building blocks so haven't had the pressure to do so yet.
The weak spot I find is more like small OLTP lookups. Ex: Imagine a taxi routing traffic service pinging for one car to do a couple hops out, where you just want a KV store in cheap RAM. But if you are batching those queries, like in a heavy city, and going deeper on them, maybe more interesting.