For instance, does fork() copy the page of memory containing the array? I believe it's Copy-on-Write semantics, right? What happens when the parent process changes the array?
Then, how do Pipe and Queue send the array across processes? Do they also pickle and unpickle it? Use shared memory?
As you’ve pointed out fork() isn’t ideal for a number of reasons and in general it’s preferred to use torch tensors directly instead of numpy arrays so that you are not forced into using fork()
There’s also this write up which I found to be quite useful for details: https://ppwwyyxx.com/blog/2022/Demystify-RAM-Usage-in-Multip...
Yes and you just answered your question.
In this case, I am the parent python process, you are the child processes started with the `multiprocessing` module, and the data is the numpy array.
The implication is that the changes made by the parent process to the numpy array post fork() won't be visible to the child processes.