Perhaps another takeaway from this article is that it'd be nice if more research papers benchmarked with vastly larger data sets.

Many researchers would love to do just that, of course. However, as many researchers will lament, it's not always easy to get 10+-figure node and 11+-figure edge data sets appropriate to a space being explored.

The best research benchmarks I see do compare to a single-core (often multithread or multiprocess) implementation. And they also show benchmark results on datasets of increasing sizes.

I agree with the authors that those sorts of papers aren't common enough, though. And we should strive to do better. Moreover, I agree that in practice in industry, many people over-optimize for horizontal scalability early, and/or do not realize potential savings and benefit by doing vertical optimizations after gaining initial scale.