Profiling Hedge [Edit]

Once you have implemented a testcase which is running and doing what you want, the computation might still take longer than you expected. A program to visualize profile data of your code's run is KCachegrind, which can be installed on a Ubuntu system by

sudo apt-get install kcachegrind

Profiling a whole computation [Edit]

To profile the whole computation, start your testcase with

python -m lsprofcalltree your_testcase.py

and get a log file called your_testcase.py.log. Open this file with KCachegrind by

kcachegrind your_testcase.py.log

and analyze the graphs to get an idea of where the most time is spent in your computation.

Profiling a single method [Edit]

To profile a single method of your testcase, you have to add some lines to your code. The following lines shall serve you as an example for profiling a method called profiled_method with the arguments arguments.

   1 from cProfile import Profile
   2 prof = Profile()
   3 try:
   4     prof.runcall(lambda: profiled_method(arguments))
   5 finally:
   6     from lsprofcalltree import KCacheGrind
   7     kg = KCacheGrind(prof)
   8     import sys
   9     kg.output(open(
  10         "your_testcase_profiled_method.log",
  11         "w"))
  12 

You would get a log file called your_testcase_profiled_method.log which you can analyze with KCachegrind. In experiments/hedge/maxwell/maxwell-cuda.py you can find an example for that.

Plotting the computation time data [Edit]

If you want to plot the computation time data, have look at the part of this Wiki that explains plotting graphs with matplotlib.