Also, to make it more accurate to what multi-threading does, none of those 300 people can see what the others are doing. And the most reliable ways of sending messages to each other involve taking a nap (though it might be brief, you might wake up in an entirely different body and need to fetch your working memory from your old body or worse, from RAM).
Or you can repeatedly write your message until you can be sure that no one else wrote over it since you started writing it. And the more threads you have, the more likely another one wrote over your message to the point where all threads are spending all of their time trying to coordinate and no time working.
I’m not familiar with their implementation but they’ll likely have one of those mechanisms under the hood.
You can only avoid them in very simple cases that don’t really scale up to a large number of threads in most cases. The one exception that does scale well is large amounts of data that can be processed independently of the rest of the data and the results are also independent. 3D rendering is one example, though some effects can create dependencies.
You can’t ask 300 people to build a chair, and expect the chair to be finished 300x faster than if a single person would build it.
Also, to make it more accurate to what multi-threading does, none of those 300 people can see what the others are doing. And the most reliable ways of sending messages to each other involve taking a nap (though it might be brief, you might wake up in an entirely different body and need to fetch your working memory from your old body or worse, from RAM).
Or you can repeatedly write your message until you can be sure that no one else wrote over it since you started writing it. And the more threads you have, the more likely another one wrote over your message to the point where all threads are spending all of their time trying to coordinate and no time working.
Blocking collections?
I’m not familiar with their implementation but they’ll likely have one of those mechanisms under the hood.
You can only avoid them in very simple cases that don’t really scale up to a large number of threads in most cases. The one exception that does scale well is large amounts of data that can be processed independently of the rest of the data and the results are also independent. 3D rendering is one example, though some effects can create dependencies.
So 8 cores is doable but 16 no?