The counterpoint would be:
Kamailio may not wait a lot for outside I/O, but even a pure in-memory config's code path largely rakes any incoming request over a bunch of kernel and system call interactions, which are in effect wait.
That doesn't have much in common with a truly pure-computational workload.
-- Alex
On May 29, 2025, at 1:06 PM, Alex Balashov abalashov@evaristesys.com wrote:
I don't have a great deal of empirical experience with this. However, proceeding from first principles in a rather general way, hyperthreading probably does more harm than good to more pure CPU-bound workloads, and is more beneficial in I/O-bound workloads where there is more of the kind of waiting on external responses that you ascribe to the "old" system.
The basic idea of hyperthreading, as best as I understand it, is a kind of oversubscription of a physical core across two logical threads. That means all the core's resources are shared (e.g. caches, memory bandwidth) and the OS has to manage more threads on the same physical core, increasing scheduler overhead.
I imagine this means that hyperthreading works best in cases where there are execution or memory access patterns that naturally "yield" to the other thread on the same core a lot, with I/O waiting of course coming to mind first and foremost. The "hyper" part I guess comes from the idea that the physical cores aren't sitting idle as much as when a single thread of execution waits on something. If there's not much of that kind of waiting, HyperThreading probably isn't of much help, and may even hurt.
The real unknown is whether a seemingly compute-bound Kamailio config has the kinds of execution patterns that create a lot of natural yielding on the given architecture. It's hard to say, under the hood, if htable lookups and dispatcher leaves a lot of these yield "gaps". My guess is they don't; it doesn't seem to me to map onto stuff like complex arithmetic, wildly varying memory allocations, cache misses and branch mispredictions and other things that could lead a thread of execution to stall. However, without forensically combing through the underlying machine code--which I of course cannot do--it's so hard to say. There are attempts throughout Kamailio's core code to modulate branch prediction to the compiler, e.g. through lots of use of unlikely()[1]:
/* likely/unlikely */ #if __GNUC__ >= 3
#define likely(expr) __builtin_expect(!!(expr), 1) #define unlikely(expr) __builtin_expect(!!(expr), 0)
I don't know how you'd profile the real-world effects of this, though.
My guess is that this is, like most things of the kind, splitting very thin hairs, and doesn't have much effect on your ability to process 2500 CPS one way or another.
-- Alex
[1] https://stackoverflow.com/questions/7346929/what-is-the-advantage-of-gccs-bu...
On May 29, 2025, at 11:57 AM, Brooks Bridges via sr-users sr-users@lists.kamailio.org wrote:
So, I have a platform that handles in the order of around 2500 or more call attempts per second. There are 2 servers that are built that handle this traffic, "old" and "new". The "old" design is a bit heavy, has multiple redis calls to external IO, does a lot of "work" on each invite before passing it along, etc. The "new" design is extremely lightweight, only a couple of htable comparisons and a dispatcher check on each invite before passing it along. The 2 servers are running different versions of Kamailio, however they're both in the 5.x train and I've found nothing in the changelogs that I believe would explain a significant difference in how child process CPU scheduling is performed, especially a detrimental change. I'm more than happy to be proven wrong about that though!
The "old" system is running 5.4.8: This system is running 4 x 8 core CPUs (32 cores) with no hyperthreading (4 x E5-4627 v2 to be exact) and has multiple external IO interactions with things like redis, lots of "work" being done on each invite checking various things before allowing it to proceed. This is currently running 32 child processes and again, has no issues handling the requests whatsoever and has been running at this level and higher for literal years.
The "new" system is running 5.8.3: This system is running 2 x 8 core CPUs (16 cores) *with* hyperthreading (2 x E5-2667 v4 to be exact) and has no external IO interactions with anything, and only does a couple of checks against some hash table values and dispatcher before allowing it to proceed. This is also currently running 32 child processes, however I am experiencing spikes in context switching and odd memory access issues (e.g. backtraces show things like "<error: Cannot access memory at address 0x14944ec60>" in udp_rvc_loop) with similar loads.
What I'm looking for here is empirical knowledge about things specifically like context switching and if hyperthreading is detrimental in cases where I'm doing very high volume, low latency (e.g. no waiting on external replies, etc) work. Is it possible there are additional issues with the way hyperthreading works and the concepts behind it if the individual calls for CPU resources are so "quick" as to overwhelm the scheduler and cause congestion in the CPU's thread scheduler itself?
Have you run into anything like this? Have you discovered that very low latency call processing can incur more hyperthreading overhead than the benefit you get from it? Do you have additional data I may be missing to help me justify to the C suite to change out the system architecture to provide a higher physical core count? Can you share it?
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-- Alex Balashov Principal Consultant Evariste Systems LLC Web: https://evaristesys.com Tel: +1-706-510-6800