User-level threads do not solve the problem of synchronization and data movement. That is, with a “thread-per-core” model, you eliminate most needs to synchronize between multiple CPU cores, and, therefore, eliminate the overhead of acquiring and releasing a lock and allow the out-of-order CPU cores run at full speed. Furthermore, “thread-per-core” model ensures that memory accesses are always CPU local, which eliminates the need to move data between CPU caches, which eliminates the expensive CPU cache consistency protocol (that makes scaling to multiple cores more difficult).
That said, I am not claiming thread-per-core is _the solution_ either, just saying that if you can partition data at application-level, you can make things run plenty fast. Of course, you’re also exposing yourself to other issues, like “hot shards” where some CPUs get disproportionately more work than others. However, as we scale to more and more cores, it seems inevitable that we must partition our systems at some level.