Back Midas Rome Roody Rootana
  Midas DAQ System  Not logged in ELOG logo
Entry  05 Sep 2024, Jack Carlton, Forum, Python frontend rate limitations? frontend.pyfrontend.cxx
    Reply  05 Sep 2024, Ben Smith, Forum, Python frontend rate limitations? 
       Reply  05 Sep 2024, Stefan Ritt, Forum, Python frontend rate limitations? 
          Reply  06 Sep 2024, Jack Carlton, Forum, Python frontend rate limitations? 
          Reply  11 Sep 2024, Konstantin Olchanski, Forum, Python frontend rate limitations? 
       Reply  27 Sep 2024, Ben Smith, Forum, Python frontend rate limitations? 
    Reply  11 Sep 2024, Konstantin Olchanski, Forum, Python frontend rate limitations? 
       Reply  11 Sep 2024, Konstantin Olchanski, Forum, Python frontend rate limitations? 
Message ID: 2829     Entry time: 06 Sep 2024     In reply to: 2828
Author: Jack Carlton 
Topic: Forum 
Subject: Python frontend rate limitations? 
Thanks for the responses, they were very helpful.

>First the general advice: if you reduce the "period" of your equipment, then your function will get called more frequently. You can set it to 0 and we'll 
call it as often as possible.

Thanks, this solves the event rate limitation I described. I didn't think to change this because the "period" did not affect the observed rate in C (and now 
I know why thanks to Stefan).

A couple more questions:

1. 
For me, 
python -m timeit -s "import struct;import ctypes;arr = [0]*1250001;buf = ctypes.create_string_buffer(10000000);fmt = \">1250000d\"" "struct.pack_into(fmt, 
buf, *arr)"
10 loops, best of 3: 43.7 msec per loop

which suggests my maximum data rate is about 1.25 MB * 1000/43.7 Hz = 23 MB/s (?). But I see data rates up to 60 MB/s with a python frontend. Am I 
misinterpreting the meaning of this result?


2. I can effectively bypass the rate limitations in python by running two concurrent frontends. For example, with one python frontend at best I can generate 
60 MB/s of data (setting "period" to 0 now); but with two frontends I can double this to 120 MB/s. This implies one python frontend is not bottlenecked by 
hardware limitations in my case.

Am I doing something wrong to artificially bottleneck my frontends? Perhaps there's a multi-threading solution I can implement to avoid needing multiple 
frontends?


Thanks,
Jack
ELOG V3.1.4-2e1708b5