What causes the CPU overload in such a case
It looks like the for loop that loops over connections to send the message is the main source of the load. The biggest problem is not the CPU however. When the process takes more than 70% of the CPU (as displayed by top), python seems to start skipping garbage collection, and the memory size of the process just keeps growing. We have no control over this.
I doubt I'll be running 4 heavy cpu-bound processes on a 4-core system
Running 4 servers on a 4-core box seems fine, it leaves plenty of resources for system tasks and logging, as long as as long as they are not at 99% CPU each, but I doubt you will get them to run at 99% because of the said memory problem.
-----Original Message----- From: twisted-python-bounces@twistedmatrix.com [mailto:twisted-python- bounces@twistedmatrix.com] On Behalf Of Atilla Sent: Thursday, November 29, 2007 10:47 AM To: Twisted general discussion Subject: Re: [Twisted-Python] Advise for heavy concurrency
I doubt I'll be running 4 heavy cpu-bound processes on a 4-core system, I'd prefer to leave 1 core "free" for all the rest of monitoring/logging tasks.
What causes the CPU overload in such a case? Currently I keep a custom many-to-many like structure, which has O(1) access time and need to forward the same message to N clients that are returned from that structure, for each incoming packet, at worst. I could potentially pre-pack the exact network message to avoid generating it for each of them, which at this point is the largest overhead. Although I'm not sure how much I can save like that.
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