Is Profiling Useless in Today's World?

rngadam writes "gprof doesn't work in Linux multithreaded programs without a workaround that doesn't work that well. It seems that if you want to use profiling, you have to look for alternatives or agree with RedHat's Ulrich Drepper that "gprof is useless in today's world"... Is profiling useless? How do you profile your programs? Is the lack of good profiling tools under Linux leading us in a world of bloated applications and killing Linux adoption by the embedded developers? Or will the adoption of a LinuxThreads replacement solve our problems?"

Comments

OProfile

[mmontour]

Take a look at OProfile. It's quite a nice tool, although it's not a direct replacement for gprof. From their 'About' page:

OProfile is a system-wide profiler for Linux x86 systems, capable of profiling all running code at low overhead. OProfile is released under the GNU GPL.

It consists of a kernel module and a daemon for collecting sample data, and several post-profiling tools for turning data into information.

OProfile leverages the hardware performance counters of the CPU to enable profiling of a wide variety of interesting statistics, which can also be used for basic time-spent profiling. All code is profiled: hardware and software interrupt handlers, kernel modules, the kernel, shared libraries, and applications (the only exception being the oprofile interrupt handler itself).

Profiling will always be useful

[Wesley Everest]

I work as a game developer, and we have to make sure that everything that is done for each frame takes less than 33ms. So we're always profiling our code to cram more functionality into a limited amount of time.

But even if you aren't doing something that is speed intensive like games, you always have tradeoffs when you choose your data structures and algorithms. Generally you first code up the easiest algorithm that you think will use an acceptable amount of memory and CPU time. Then, later, if something is too slow, you have to identify where the problem is. If could be that you chose an O(N^2) algorithm not realizing that N might be 1,000 instead of the max of 100 you were counting on, forcing you to switch to an O(NlogN) algorithm that is more complex.

Now, if it is a small application, you might have enough familiarity with the code to be able to guess where the problem is -- then you fix it and see if it is still slow. If that works, then you're set and profiling isn't necessary. But if the fix doesn't speed it up enough, then you're stuck. You have to profile it somehow.

You might try simple tricks like changing the code to loop on a suspected bit of code 100 times and see how much longer it takes. Or maybe throw in some printf's that spit out the current time at different points. Or maybe create your own profiling code that you manually call in functions you want to time. Or, you might use an actual profiler without modifications to the code. But lacking a profiler doesn't mean you can't or won't profile your code.

And even with CPU speed doubling every couple of years or so, that doesn't mean speed is no longer an issue. You can easily choose the wrong algorithm and have something take 1000s of times longer to run than the proper algorithm.

Re:Profiling is Useful

[anonymous_wombat]

In single threaded programs, just one type of profiling needs to be done, the kind that standard profiling tools measure. In multi-threaded programs, the relative execution times of the various threads may be more important. The first thing to do is to figure out which threads are using most of the resources. After this is done, and any optimizations made, the old-style profiling and optimizing of slow methods is just as important as ever. If your program is spending 80% of its time sorting, then optimize your sorting code.

Of course, for many applications, multi-threading achieves the vast majority of the speed increase, and profiling will only be of marginal utility. The profiler is just one tool of many, and is not a silver bullet.