On 2020-06-16 20:28, Mark Shannon wrote:
On 16/06/2020 1:24 pm, Nick Coghlan wrote:
Multiprocessing serialisation overheads are abysmal. With enough OS
support you can attempt to mitigate that via shared memory mechanisms
(which Davin added to the standard library), but it's impossible to
get the overhead of doing that as low as actually using the address
space of one OS process.
What does "multiprocessing serialisation" even mean? I assume you mean
the overhead of serializing objects for communication between processes.
The cost of serializing an object has absolutely nothing to do with
which process the interpreter is running in.
Separate interpreters within a single process will still need to
serialize objects for communication.
The overhead of passing data through shared memory is the same for
threads and processes. It's just memory.
Can we please stick to facts and not throw around terms like "abysmal"
with no data whatsoever to back it up.
I'd like to get back to the facts. Let me quote the original mail from
this thread:
On 2020-06-05 16:32, Mark Shannon wrote:
While I'm in favour of PEP 554, or some similar model for parallelism in
Python, I am opposed to the changes we are currently making to support it.
Which changes?
There are several efforts in this general space. Personally, I also
don't agree with them all. And I think the reason I wasn't able to
formulate too many replies to you is that we don't have a common
understanding of what is being discussed, and of the modivations behind
the changes.
You seem to try convince everyone that multiple processes are better (at
isolation, and at performance) than multiple interpreters in one
process. And I see the point: if you can live with the restriction of
multiple processes, they probably are a better choice!
But I don't think PEPs 554, 489, 573, etc. are about choosing between
multiprocessing and multiple interpreters; they're about making multiple
interpreters better than they currently are.
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