[chrisseaton]

Think outside of web workloads! Not everyone is writing a web app.

Think about something like Delaunay triangulation or mesh refinement. These are critical path bottlenecks for a great many applications and in practice very parallel, but they're irregular so we cannot easily distribute the data structure. The best results we have are for shared memory thread models. We don't know how to do it any other way!

[skosch]

That's why the post you just replied to suggested that Node may not be the right tool for those kind of tasks.

[kelnos]

The problem is that I see a lot of projects written in languages with single-threaded runtimes (python more often than node) that become difficult/expensive to scale and extend down the road. I loathe the idea of a rewrite, but sometimes the initial language choice lacked forethought to the point where it makes sense to rewrite in something that actually can make use of all of a machine's processing resources.

Things like greenlet and gevent (and likely napa.js) are band-aids over the underlying problem.

[grawlinson]

For these workloads, I would consider a compiled language with great parallelism/concurrency. e.g Rust or GoLang.