问题
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?
回答1:
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
回答2:
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.
回答3:
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.
来源：https://stackoverflow.com/questions/9608949/gprof-time-spent-in-particular-lines-of-code