9
votes

I've been using the gprof profiler in conjunction with g++.

I have a function in my code which encapsulates several sections of behaviour which are related enough to the primary function that it would not make sense to split them off into their own functions.

I'd like to know how much time is spent in each of these areas of code.

So, if you imagine the code looks like

function(){
    A
    A
    A
    B
    B
    B
    C
    C
    C
}

where A, B, and C represent particular sections of code I'm interested in, is there a way to get gprof to tell me how much time is spent working on those particular sections?

3
If you are trying to make the program run faster, you can do better than gprof.Mike Dunlavey
@MikeDunlavey Too bad that the question was deleted.user202729
And that answer had 192 upvotes. GrrrRichard

3 Answers

9
votes

I know it's a old question, but I have found a interesting answer. As Sam say, the -l option is only for old gcc compiler. But I have found that if you compile and link with -pg -fprofile-arcs -ftest-coverage, run the program, the result of gprof -l is very interesting.

Flat profile:

Each sample counts as 0.01 seconds.
  %   cumulative   self              self     total           
 time   seconds   seconds    calls  Ts/call  Ts/call  name    
 13.86      0.26     0.26                             main (ComAnalyste.c:450 @ 804b315)
 10.87      0.46     0.20                             main (ComAnalyste.c:386 @ 804b151)
  7.07      0.59     0.13                             main (ComAnalyste.c:437 @ 804b211)
  6.25      0.70     0.12                             main (ComAnalyste.c:436 @ 804b425)
  4.89      0.79     0.09                             main (ComAnalyste.c:283 @ 804a3f4)
  4.89      0.88     0.09                             main (ComAnalyste.c:436 @ 804b1e9)
  4.08      0.96     0.08                             main (ComAnalyste.c:388 @ 804ad95)
  3.81      1.03     0.07                             main (ComAnalyste.c:293 @ 804a510)
  3.53      1.09     0.07                             main (ComAnalyste.c:401 @ 804af04)
  3.26      1.15     0.06                             main (ComAnalyste.c:293 @ 804a4bf)
  2.72      1.20     0.05                             main (ComAnalyste.c:278 @ 804a48d)
  2.72      1.25     0.05                             main (ComAnalyste.c:389 @ 804adae)
  2.72      1.30     0.05                             main (ComAnalyste.c:406 @ 804aecb)
  2.45      1.35     0.05                             main (ComAnalyste.c:386 @ 804ad6d)
  2.45      1.39     0.05                             main (ComAnalyste.c:443 @ 804b248)
  2.45      1.44     0.05                             main (ComAnalyste.c:446 @ 804b2f4)
  2.17      1.48     0.04                             main (ComAnalyste.c:294 @ 804a4e4)
  2.17      1.52     0.04                             main (ComAnalyste.c:459 @ 804b43b)
  1.63      1.55     0.03                             main (ComAnalyste.c:442 @ 804b22d)
  1.63      1.58     0.03                             main (ComAnalyste.c:304 @ 804a56d)
  1.09      1.60     0.02                             main (ComAnalyste.c:278 @ 804a3b3)
  1.09      1.62     0.02                             main (ComAnalyste.c:285 @ 804a450)
  1.09      1.64     0.02                             main (ComAnalyste.c:286 @ 804a470)
  1.09      1.66     0.02                             main (ComAnalyste.c:302 @ 804acdf)
  0.82      1.67     0.02                             main (ComAnalyste.c:435 @ 804b1d2)
  0.54      1.68     0.01                             main (ComAnalyste.c:282 @ 804a3db)
  0.54      1.69     0.01                             main (ComAnalyste.c:302 @ 804a545)
  0.54      1.70     0.01                             main (ComAnalyste.c:307 @ 804a586)
  0.54      1.71     0.01                             main (ComAnalyste.c:367 @ 804ac1a)
  0.54      1.72     0.01                             main (ComAnalyste.c:395 @ 804ade6)
  0.54      1.73     0.01                             main (ComAnalyste.c:411 @ 804aff8)
  0.54      1.74     0.01                             main (ComAnalyste.c:425 @ 804b12a)
  0.54      1.75     0.01                             main (ComAnalyste.c:429 @ 804b19f)
  0.54      1.76     0.01                             main (ComAnalyste.c:444 @ 804b26f)
  0.54      1.77     0.01                             main (ComAnalyste.c:464 @ 804b4a1)
  0.54      1.78     0.01                             main (ComAnalyste.c:469 @ 804b570)
  0.54      1.79     0.01                             main (ComAnalyste.c:472 @ 804b5b9)
  0.27      1.80     0.01                             main (ComAnalyste.c:308 @ 804a5a3)
  0.27      1.80     0.01                             main (ComAnalyste.c:309 @ 804a5a9)
  0.27      1.81     0.01                             main (ComAnalyste.c:349 @ 804a974)
  0.27      1.81     0.01                             main (ComAnalyste.c:350 @ 804a99c)
  0.27      1.82     0.01                             main (ComAnalyste.c:402 @ 804af1d)
  0.27      1.82     0.01                             main (ComAnalyste.c:416 @ 804b073)
  0.27      1.83     0.01                             main (ComAnalyste.c:417 @ 804b0a1)
  0.27      1.83     0.01                             main (ComAnalyste.c:454 @ 804b3ec)
  0.27      1.84     0.01                             main (ComAnalyste.c:461 @ 804b44a)
  0.27      1.84     0.01                             main (ComAnalyste.c:462 @ 804b458)

It's say the time spent per line. It's very interesting result. I don't know the accuracy or the validity of that, but it's quite interesting. Hope it's help

3
votes

Here's a useful resource for you: gprof line by line profiling.

With older versions of the gcc compiler, the gprof -l argument specified line by line profiling.

However, newer versions of gcc use the gcov tool instead of gprof to display line by line profiling information.

2
votes

If you are using linux, then you can use linux perf instead of gprof, as described here:

http://code.google.com/p/jrfonseca/wiki/Gprof2Dot#linux_perf

Typing perf report and selecting a function will allow you to get line-by-line information about where the CPU time is spent inside the function.