Trying to assess the impact of the Ragel state machine generator on software, I’ve been trying to come down with a quick way to seriously benchmark some simple testcases, making sure that the results are as objective as possible. Unfortunately, I’m not a profiling expert; to keep with the alliteration in the post’s title, I’m not proficient with profilers.
Profiling can be done either internally to the software (manually or with GCC’s help), externally with a profiling software, or in the kernel with a sampling profiler. Respectively, you’d be found using the rdtsc instruction (on x86/amd64), the gprof command, valgrind and one of either sysprof or oprofile. Turns out that almost all these options don’t give you anything useful in truth, and you have to decide whether to get theoretical data, or practical timing, and in both cases, you don’t have a very useful result.
Of that list of profiling software, the one that looked more promising was actually oProfile; especially more interesting since the AMD Family 10h (Barcelona) CPUs supposedly have a way to have accurate reporting of instruction executed, which should combine the precise timing reported by oProfile with the invariant execution profile that valgrind provides. Unfortunately oprofile’s documentation is quite lacking, and I could find nothing to get that “IBS” feature working.
Since oprofile is a sampling profiler, it has a few important points to be noted: it requires kernel support (which in my case required a kernel rebuild because I had profiling support disabled), it requires root to set up and start profiling, through a daemon process, by default it profiles everything running in the system, which on a busy system running a tinderbox might actually be _too_ much. Support for oprofile in Gentoo also doesn’t seem to be perfect, for instance there is no standardised way to start/stop/restart the daemon, which might not sound that bad for most people, but is actually useful because sometimes you forget to have the daemon running and you try to start it time and time again and it doesn’t seem to work as you expect. Also, for some reason it stores the data in /var/lib instead of /var/cache; this wouldn’t be a problem if it wasn’t that if you don’t pay enough attention you can easily see your /var/lib filesystem filling up (remember: it runs at root so it bypasses the root-reserved space).
More worrisome, you’ll never get proper profiling on Gentoo yet, at least for AMD64 systems. The problem is that all sampling profilers (so the same holds true for sysprof too) require frame pointer information; the well-known -fomit-frame-pointer flag, that allows to save precious registers on x86, and used to break debug support, can become a problem, as Mart pointed out to me. The tricky issue is that since a few GCC and GDB versions, the frame pointer is no longer needed to be able to get complete backtraces of processes being debugged; this meant that, for instance on AMD64, the flag is now automatically enabled by -O2 and higher. On some architecture, this is still not a problem to sample-based profiling, but on AMD64 it is. Now, the testcases I had to profile are quite simple and minimal and only call into the C library (and that barely calls the kernel to read the input files), so I only needed to have the C library built with frame pointers to break down the functions; unfortunately this wasn’t as easy as I hoped.
The first problem is that the Gentoo ebuild for glibc does have a glibc-omitfp USE flag; but does not seem to explicitly disable frame pointer omitting, just explicitly enable it. Changing that, thus, didn’t help; adding -fno-omit-frame-pointer also does not work properly because flags are (somewhat obviously) filtered down; adding that flag to the whitelist in flag-o-matic does not help either. I have yet to see it working as it’s supposed to, so for now oprofile is just accumulating dust.
My second choice was to use gprof together with GCC’s profiling support, but that only seems to provide a breakdown in percentage of execution time, which is also not what I was aiming for. The final option was to fall back to valgrind, in particular the callgrind tool. Unfortunately the output of that tool is not human-readable, and you usually end up using software like KCacheGrind to be able to parse it; but since this system is KDE-free I couldn’t rely on that; and also KCacheGrind does not provide an easy way to extract data out of it to compile benchmark tables and tests.
On the other hand, the callgrind_annotate script does provide the needed information, although still in a not exactly software-parsable fashion; indeed to find the actual information I had to look at the main() calltrace and then select the function I’m interested in profiling, that provided me with the instruction count of execution. Unfortunately this does not really help me as much as I was hoping, since it tells me nothing on how much time will it take for the CPU to execute the instruction (which is related to the amount of cache and other stuff like that), but it’s at least something to start with.
I’ll be providing the complete script, benchmark and hopefully results once I can actually have a way to correlate them to real-life situations.