= Analyzing the PJMEDIA Tone Generator Algorithms Performance =
This article presents the performance analysis of various back-end algorithms of the tone generator that are implemented in PJMEDIA. We will measure the performance in both speed and accuracy terms.
== The Algorithms ==
The tone generator (tonegen.c) supports several algorithms, and since version 1.0-rc3, the use of these algorithms is controlled by {{{PJMEDIA_TONEGEN_ALG}}} setting:
- {{{PJMEDIA_TONEGEN_SINE}}}: The good-old generation using math's sine(), floating point. This has very good precision but it's the slowest and requires floating point support and linking with the math library.
- {{{PJMEDIA_TONEGEN_FLOATING_POINT}}}: Floating point approximation of sine(). This has relatively good precision and much faster than plain sine(), but it requires floating-point support and linking with the math library.
- {{{PJMEDIA_TONEGEN_FIXED_POINT_CORDIC}}} (new in 1.0-rc3): Fixed point using sine signal generated by Cordic algorithm. This algorithm can be tuned to provide balance between precision and performance by tuning the {{{PJMEDIA_TONEGEN_FIXED_POINT_CORDIC_LOOP}}} setting, and may be suitable for platforms that lack floating-point support. The default setting for {{{PJMEDIA_TONEGEN_FIXED_POINT_CORDIC_LOOP}}} is 8.
- {{{PJMEDIA_TONEGEN_FAST_FIXED_POINT}}}: Fast fixed point using some approximation to generate sine waves. The tone generated by this algorithm is not very precise, however the algorithm is very fast.
== Accuracy ==
For the accuracy test, we setup the tone generator to generate digit A from [http://en.wikipedia.org/wiki/DTMF DTMF], with frequencies of 697 and 1209. We then saved the tone to a WAV file and analyzed the frequency using !CoolEdit (now becomes [http://www.adobe.com/special/products/audition/syntrillium.html Adobe Audition]).
This is simple to do with [http://www.pjsip.org/pjsua.htm pjsua] really:
{{{
pjsua --play-tone 697,1209,200,2000 --rec-file tone.wav
}}}
then issue these commands:
{{{
cc 1 2
sleep 5000
cd 1 2
q
}}}
And here is the graphics from the frequency analysis.
|| PJMEDIA_TONEGEN_SINE:[[BR]] [[Image(sine.JPG)]] || PJMEDIA_TONEGEN_FLOATING_POINT:[[BR]] [[Image(float.JPG)]] ||
|| PJMEDIA_TONEGEN_FIXED_POINT_CORDIC with 10 iterations:[[BR]] [[Image(cordic10.JPG)]] || PJMEDIA_TONEGEN_FIXED_POINT_CORDIC with 8 iterations (default):[[BR]][[Image(cordic8.JPG)]] ||
|| PJMEDIA_TONEGEN_FIXED_POINT_CORDIC with 7 iterations:[[BR]] [[Image(cordic7.JPG)]] || PJMEDIA_TONEGEN_FAST_FIXED_POINT: [[BR]][[Image(fast-fixed-point.JPG)]] ||
== Performance ==
Below is the time measurements of the algorithms. The test measures the generation of 1 second worth of dual-tone at 8KHz sampling rate. For single-tone, just divide the results by two, and for 16KHz dual-tone, just multiply the results by two.
The MIPS value uses the same convention as in [PJMEDIA-MIPS PJMEDIA Performance Measurement] page.
=== Linux, ARM9 (ARM926EJ-S), gcc ===
On this platform we use {{{-O3 -msoft-float -DNDEBUG -DPJ_HAS_FLOATING_POINT=0}}} flags.
|| || time (usec) || CPU (%) || MIPS ||
|| PJMEDIA_TONEGEN_SINE || 506,535 || 50.653 || 100.29 ||
|| PJMEDIA_TONEGEN_FLOATING_POINT || 18,037 || 1.804 || 3.57 ||
|| PJMEDIA_TONEGEN_FIXED_POINT_CORDIC with 10 iterations || 11,662 || 1.166 || 2.31 ||
|| PJMEDIA_TONEGEN_FIXED_POINT_CORDIC with 8 iterations (default) || 9,872 || 0.987 || 1.95 ||
|| PJMEDIA_TONEGEN_FIXED_POINT_CORDIC with 7 iterations || 8,943 || 0.894 || 1.77 ||
|| PJMEDIA_TONEGEN_FAST_FIXED_POINT || 1,449 || 0.145 || 0.29 ||