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Original commit message from CVS: * docs/design/draft-klass.txt: Add example that needs more thinking. * docs/design/draft-missing-plugins.txt: More thoughts about wtrapper plugins. * docs/random/ensonic/embedded.txt: * docs/random/ensonic/profiling.txt: More design work.
98 lines
3.1 KiB
Text
98 lines
3.1 KiB
Text
$Id$
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= profiling =
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== what information is interesting? ==
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* pipeline throughoutput
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if we know the cpu-load for a given datastream, we could extrapolate what the
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system can handle
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-> qos profiling
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* load distribution
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which element causes which cpu load/memory usage
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= qos profiling =
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* what data is needed ?
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* (streamtime,propotion) pairs from sinks
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draw a graph with gnuplot or similar
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* number of frames in total
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* number of frames dropped from each element that support QOS
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elements that don't support QOS wont have this information anyway
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* needs to be media type specific:
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* video: full frames
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* audio: partial buffers can be dropped in the sink, count number of dropped
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audio frames
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* idea2: query data (e.g. via. gst-launch)
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* add -r, --report option to gst-launch
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* send duration to get total number of frames (GST_FORMAT_DEFAULT for video is frames)
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* during playing we need to capture QOS-events to record 'streamtime,proportion' pairs
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gst_pad_add_event_probe(video_sink->sink_pad,handler,data)
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* during playback we like to know when an elemnt drops frames
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what about elements sending a qos_action message?
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* after EOS, send qos-queries to each element in the pipeline
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* qos-query will return:
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number of frames rendered
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number of frames dropped
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* print a nice table with the results
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* QOS stats first
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* list of 'streamtime,proportion' pairs
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+ robust
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+ also available to application
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- changes in core
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= core profiling =
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* scheduler keeps a list of usecs the process function of each element was
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running
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* process functions are: loop, chain, get, they are driven by gst_pad_push() and
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gst_pad_pull_range()
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* scheduler keeps a sum of all times
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* each gst-element has a profile_percentage field
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* when going to play
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* scheduler sets sum and all usecs in the list to 0
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* when handling an element
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* remember old usecs t_old
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* take time t1
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* call elements processing function
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* take time t2
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* t_new=t2-t1
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* sum+=(t_new-t_old)
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* profile_percentage=t_new/sum;
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* should the percentage be averaged?
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* profile_percentage=(profile_percentage+(t_new/sum))/2.0;
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* the profile_percentage shows how much CPU time the element uses in relation
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to the whole pipeline
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== rusage + pad-probes =
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* check get_rusage() based cpu usage detection in buzztard
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this together with pad_probes could gives us decent application level profiles
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* different elements
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* 1:1 elements are easy to handle
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* 0:1 elements need a start timer
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* 1:0 elements need a end timer
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* n:1, 1:m and n:m type elemnts are tricky
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adapter based elements might have a fluctuating usage in addition
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// result data
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struct {
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beg_min,beg_max;
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end_min,end_max;
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} profile_data;
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// install probes
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gst_bin_iterate_elements(pipeline)
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gst_element_iterate_pads(element)
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if (gst_pad_get_direction(pad)==GST_PAD_SRC)
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gst_pad_add_buffer_probe(pad,end_timer,profile_data)
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else
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gst_pad_add_buffer_probe(pad,beg_timer,profile_data)
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// listen to bus state-change messages to
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// * reset counters on NULL_TO_READY
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// * print results on READY_TO_NULL
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