Changes between Version 4 and Version 5 of Profiling

Timestamp:

01/07/13 11:47:12 (8 years ago)

Author:

Antoine Martin

Comment:

--

Profiling

@@ -42 +42 @@
 * focus on one thread at a time - there is not much overlap/impact between different threads
 * choose an application to test which will stress the desired portion of the code (ie: if testing the network or encoding thread, an application that generates a high frames-per-second is more appropriate than what may ultimately be the target application for the system)
-* choose an application whose behaviour is predictable: preferably not using the network or relying on any external resources
+* choose an application whose behaviour is predictable: preferably not using the network or relying on any external resources. So the whole thing can be scripted, run repeatedly/reliably for comparing with previous runs.
 * start with most groups enabled
 * most groups can usually be disabled early - unless they are being profiled specifically
 * some [../Debugging Debugging] environment variables may be useful
+* save useful graphs with all the information relating to the version used, modifications, environment, etc. So these can be reproduced later.
+
+
+== Fixing Bottlenecks ==
+First, write a test to measure/isolate the problematic part of the code.
+[[BR]]
+There are no magic solutions to apply, some common solutions:
+* threading (we already have too many threads though..)
+* re-writing in C or Cython
+* better algorithms
+
+
+== Examples ==
+
+=== maths.py re-written in Cython ===
+Merged in r2462
+
+[[BR]]
+
+* Before:
+{{{
+$ XPRA_CYTHON_MATH=0 ./tests/xpra/test_maths.py 
+calculate_time_weighted_average(100000 records)=(0.5129547191923681, 0.529864013016996)
+elapsed time: 72.6ms
+test_calculate_timesize_weighted_average(100000 records)=(70109.42497899215, 22337.16293859974)
+elapsed time: 204.9ms
+}}}
+* After:
+{{{
+$ XPRA_CYTHON_MATH=1 ./tests/xpra/test_maths.py 
+calculate_time_weighted_average(100000 records)=(0.5226684212684631, 0.5245391130447388)
+elapsed time: 4.0ms
+test_calculate_timesize_weighted_average(100000 records)=(180154.15625, 35980.69140625)
+elapsed time: 19.7ms
+}}}
+Which is 10 to 20 times faster.