While network overhead always exists, the goal would be take advantage of the seemingly 10x performance headroom on a GPU as compared to a CPU. Not to mention,

While network overhead always exists, the goal would be take advantage of the seemingly 10x performance headroom on a GPU as compared to a CPU. Not to mention, GPUs are getting more and more HBM capacity. Of course, you're right to wonder about how GPUs behave with more complex structures -- I'm not sure. Research papers seem to get pretty good results for stuff like skip lists and b+trees? The general idea, though, is that GPU compute + bandwidth optimized memory is better/more efficient for high-throughput compute, if you can stomach a couple tens of microseconds. Coincidentally, network latencies force you to stomach that anyway.