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Re: [Xen-devel] Operf and Opreport outputs


I tried the perf-hello.c file and found the results as you explained. It is very helpful to me. Now, for PERF_COUNT_HW_BRANCH_MISSES, I am getting varying values every time unlike PERF_COUNT_HW_INSTRUCTIONS.  

To get count for only defined process, I am trying to set perf_event_attr structure variables sample_type as PERF_SAMPLE_BRANCH_STACK and branch_sample_type as PERF_SAMPLE_BRANCH_USER. By doing so, I am getting error no. 5 by perf_event_open. What may be the problem?

Dhara Buch

On Mon, Jun 19, 2017 at 5:51 PM, Michael Petlan <mpetlan@xxxxxxxxxx> wrote:
On Mon, 19 Jun 2017, dhara buch wrote:
> Hello,
> Thanks a lot for the detailed explanation. I could understand the working of operf and opreport.
> Unlike operf, ocount counts each occurrence of the monitored event. In such a case, why ocount also gives varying values of CPU_CLK_UNHALTED even when the monitored code doesn't get
> changed. Is it because of background processes? If so, then can we get event count for only monitored command?

Hi Dhara,

it is kind of because of the background processes, but not in the way that ocount
would count also their CPU consumption. If you don't use '-s' option, ocount will
count only what your command does.

However, it counts either kernelspace, userspace or both (default if you are root).
This can be configured by the event's flags:


Only kernelspace (used by the command, i.e. syscalls, etc):

Only userspace (i.e. syscalls are excluded):

(the format is (ocount): event:umask:kernelspace:userspace,
for operf it is: event:umask:sample_rate:kernelspace:userspace)

The numbers are slightly different each run because the process does not live in
vacuum. It is usually dynamically linked, it calls libraries, kernel switches
contexts, etc. All these things cause the differences. Also, the CPU optimizes
the execution with floating success, depending on what else runs there with it.
If the process is interrupted many times, the CPU consumption will be higher.

I have a sample code which I linked dynamically and statically. While the dyn.
linked executable always takes around 670,260 cycles, the statically linked one
takes around 380,202 and seems to be more steady. Since it is very simple code,
you can see that the linker-related stuff took more than 40% of the CPU cycles).

Executing a binary is so complex problem that there is no surprise that those
measurements give different values every time.



You can use either papi library or the built-in kernel support for counting
just a particular part of code, e.g. a function. I have attached one example
which uses perfevents kernel background. I have two functions for factorial
counting, one is slightly less effective than the other. I count cycles and
instructions for both. When executing repeatedly, you can see, that the inst.
count is the same all the time (at least on my laptop), but the cycles count
differs even for just the stuff in the functions which are very simple.

cc -o perf-hello perf-hello.c myperf.c

Ineffective method:
        PERF_COUNT_HW_CPU_CYCLES = 32192

More effective method:
        PERF_COUNT_HW_CPU_CYCLES = 15931



> Thank you,
> On Fri, Jun 16, 2017 at 4:52 PM, Michael Petlan <mpetlan@xxxxxxxxxx> wrote:
>       On Fri, 16 Jun 2017, dhara buch wrote:
>       > Hello,
>       >
>       > Many days ago you had helped me a lot in using Oprofile in Virtual Machine. That time, I also had a query regarding
>       > getting information from 'opreport --symbols --debuginfo' command.
>       Hello,
>       yeah, I remember...
>       >
>       > Actually, I am profiling a file1.c file with the following commands...
>       >
>       > 1. gcc -g file1.c -o file1
>       >
>       > 2. operf ./file1 --events=CPU_CLK_UNHALTED
>       >
>       > 3. opreport --symbols --debuginfo
>       >
>       > the output contains various lines where one line look follows:
>       >
>       > samples  %        linenr info                 image name               symbol name
>       >
>       > 2       12.5000  rsaimp.c:16                 rsaimp                   MM
>       > 2        12.5000  rsaimp.c:34                 rsaimp                   main
>       >
>       > When I execute commands 2 and 3 multiple times, each time I gwt the output for symbole name MM (which is UDF in the
>       > program) but I don't get output for main every time.
>       >
>       This is kind of random, see below.
>       > Additionally,'' the sample % also vary every time I file operf command. I do not understand the working of operf that
>       > how it gives different outputs for the same program.
>       >
>       How _counting_ works:
>       Each time an event happens in CPU (in our case -- CPU_CLK_UNHALTED -- one
>       CPU tick), its counter is incremented by one. This way, you can get the
>       whole number of how many times the event happened:
>       $ ocount ls
>       Events were actively counted for 1863267 nanoseconds.
>       Event counts (actual) for /bin/ls:
>                 Event                    Count                    % time counted
>                 CPU_CLK_UNHALTED         2,672,309                100.00
>       This means that there were 2.672 million CPU ticks necessary to execute
>       `ls`.
>       The tool for counting is *ocount*.
>       How _profiling_ works:
>       For profiling, events are counted the same way as when counting, but only
>       once per N event occurrences a "sample" is taken. A sample is a piece of
>       information about where in the code it happened, what was the context and
>       potentially call-stack, etc. This sample is saved into the oprofile_data
>       dir structure. When you finish profiling, opreport generates some overview
>       from the samples recorded.
>       Of course, taking sample causes some overhead. Thus, you cannot take it
>       each time the event counter increments. For this purpose, there is "sample
>       rate" value which divides the event counter and takes a sample only once
>       per "sample rate" occurrences. Thus, it is pretty random, which event
>       occurrence is picked for a sample.
>       Of course, your main() consumes CPU ticks and the counter is incremented,
>       but sometimes, one of these incrementations produces sample, sometimes not,
>       thus the function is missing.
>       You have 2 samples on each of the line in the report. That is really a low
>       number, so it is very probable that sometimes the samples hit main() and
>       sometimes not.
>       $ operf ls
>       Profiling done.
>       $ opreport
>       Using /root/oprofile_data/samples/ for samples directory.
>       CPU: Core 2, speed 2267 MHz (estimated)
>       Counted CPU_CLK_UNHALTED events (Clock cycles when not halted) with a unit mask of 0x00 (Unhalted core cycles) count 100000
>       CPU_CLK_UNHALT...|
>         samples|      %|
>       ------------------
>        -->   37 100.000 ls
>              CPU_CLK_UNHALT...|
>                samples|      %|
>                        ------------------
>                     27 72.9730 kallsyms
>                      5 13.5135 libc-2.19.so
>                      2  5.4054 ld-2.19.so
>                      1  2.7027 ls
>                      1  2.7027 ext4
>                      1  2.7027 libattr.so.1.1.0
>       You see that out of (estimated) 2.5-3.5 mil of event occurrences (which is
>       the scale `ls` usually needs on my PC), I got only 37 samples.
>       The sample rate for each event are in `ophelp` as "min count".
>       Why did I get 37 samples? My default setting of default event is:
>       $ ophelp -d
>       CPU_CLK_UNHALTED:100000:0:1:1
>       -------------------^^
>       This means that there is 1 sample per 100000 event occurrences.
>       You can tweak this value a bit, but note that oprofile won't let you set
>       the value to be too low, due to the overhead reasons.
>       Let's try 10000 (sampling 10 times more often):
>       $ operf -e CPU_CLK_UNHALTED:10000 ls
>       WARNING: Lost samples detected! See /root/oprofile_data/samples/operf.log for details.
>       Lowering the sampling rate may reduce or eliminate lost samples.
>       See the '--events' option description in the operf man page for help.
>       Profiling done.
>       $ opreport
>       Using /root/oprofile_data/samples/ for samples directory.
>       WARNING: Lost samples detected! See /root/oprofile_data/samples/operf.log for details.
>       CPU: Core 2, speed 2267 MHz (estimated)
>       Counted CPU_CLK_UNHALTED events (Clock cycles when not halted) with a unit mask of 0x00 (Unhalted core cycles) count 10000
>       CPU_CLK_UNHALT...|
>         samples|      %|
>       ------------------
>             429 100.000 ls
>             CPU_CLK_UNHALT...|
>               samples|      %|
>               ------------------
>                     313 72.9604 kallsyms
>                      55 12.8205 ld-2.19.so
>                      34  7.9254 libc-2.19.so
>                      17  3.9627 ls
>                       8  1.8648 ext4
>                       2  0.4662 binfmt_misc
>       You see that both operf and opreport warned about lost samples which means
>       that the overhead in kernel was too high and some samples were lost. But
>       probably not that many, since you see that I got 429 samples instead of
>       37 which is very roughly 10 times more.
>       Profiling is not for exact measurement of how many CPU ticks happened in
>       a function, it is rather designed for relative comparison across your code.
>       If you are getting too few samples, try to decrease the sample rate as I
>       did in the example. Have a look at `ophelp` what is the lowest value for
>       your event.
>       Also please note that the min sample rates are rough and depend on the load,
>       so under low load, lower rates can be used without issues. When you profile
>       systemwide on all CPUs, it's very high chance that you'll run into an overhead
>       and lose many samples...
>       I hope I explained it a bit.
>       Cheers,
>       Michael
>       > Thanks,
>       >
>       > Dhara Buch
>       >
>       >

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