问题
short version:
Is there a good time based sampling profiler for Linux?
long version:
I generally use OProfile to optimize my applications. I recently found a shortcoming that has me wondering.
The problem was a tight loop, spawning c++filt to demangle a c++ name. I only stumbled upon the code by accident while chasing down another bottleneck. The OProfile didn't show anything unusual about the code so I almost ignored it but my code sense told me to optimize the call and see what happened. I changed the popen of c++filt to abi::__cxa_demangle. The runtime went from more than a minute to a little over a second. About a x60 speed up.
Is there a way I could have configured OProfile to flag the popen call? As the profile data sits now OProfile thinks the bottle neck was the heap and std::string calls (which BTW once optimized dropped the runtime to less than a second, more than x2 speed up).
Here is my OProfile configuration:
$ sudo opcontrol --status
Daemon not running
Event 0: CPU_CLK_UNHALTED:90000:0:1:1
Separate options: library
vmlinux file: none
Image filter: /path/to/executable
Call-graph depth: 7
Buffer size: 65536
Is there another profiler for Linux that could have found the bottleneck?
I suspect the issue is that OProfile only logs its samples to the currently running process. I'd like it to always log its samples to the process I'm profiling. So if the process is currently switched out (blocking on IO or a popen call) OProfile would just place its sample at the blocked call.
If I can't fix this, OProfile will only be useful when the executable is pushing near 100% CPU. It can't help with executables that have inefficient blocking calls.
回答1:
Glad you asked. I believe OProfile can be made to do what I consider the right thing, which is to take stack samples on wall-clock time when the program is being slow and, if it won't let you examine individual stack samples, at least summarize for each line of code that appears on samples, the percent of samples the line appears on. That is a direct measure of what would be saved if that line were not there. Here's one discussion. Here's another, and another. And, as Paul said, Zoom should do it.
If your time went from 60 sec to 1 sec, that implies every single stack sample would have had a 59/60 probability of showing you the problem.
回答2:
Try Zoom - I believe it will let you profile all processes - it would be interesting to know if it highlights your problem in this case.
回答3:
I wrote this a long time ago, only because I couldn't find anything better: https://github.com/dicej/profile
I just found this, too, though I haven't tried it: https://github.com/oliver/ptrace-sampler
回答4:
Quickly hacked up trivial sampling profiler for linux: http://vi-server.org/vi/simple_sampling_profiler.html
It appends backtrace(3) to a file on SIGUSR1, and then converts it to annotated source.
回答5:
After trying everything suggested here (except for the now-defunct Zoom, which is still available as huge file from dropbox), I found that NOTHING does what Mr. Dunlavey recommends. The "quick hacks" listed above in some of the answers wouldn't build for me, or didn't work for me either. Spent all day trying stuff... and nothing could find fseek as a hotspot in an otherwise simple test program that was I/O bound.
So I coded up yet another profiler, this time with no build dependencies, based on GDB, so it should "just work" for almost any debuggable code. A single CPP file.
https://github.com/jasonrohrer/wallClockProfiler
It automates the manual process suggested by Mr. Dunlavey, interrupting the target process with GDB periodically and harvesting a stack trace, and then printing a report at the end about which stack traces are the most common. Those are your true wall-clock hotspots. And it actually works.
来源：https://stackoverflow.com/questions/2449159/linux-time-sample-based-profiler