Re: Some event modifiers missing from output and desire option to compute value based on measurements

[William Cohen <wcohen@redhat.com>]

On 03/13/2014 01:30 PM, Andi Kleen wrote:
> William Cohen <wcohen@redhat.com> writes:
> 
>> When experimenting with perf I wanted to have separate counts for events in userspace and the kernel.  I used:
>>
>> $ perf stat   -e instructions:u -e instructions:k -e cycles:u -e cycles:k -e cache-misses:u -e cache-misses:k make
>>
>> The associated  output below includes the event modifiers for all the events, but the 3.06 and 0.37 insns per cycles look off.  Shouldn't that instructions:u/cycles:u and instructions:k/cycles:k be the values reported for "insns per cycle"?
> 
> Yes the event match code currently assumes there's only a single event
> each and always uses the last.
> 
>> It appears that the output is listing the measurements in the same
>> order they are specified on the command line, but it would be nice if
>> the output was clearer on the events being measured.  If I am reading
>> the output correctly, the L1-icache-load-misses per instruction is
>> pretty poor for kernel-space.  Much of the time I am looking at ratios
>> of events and it would be nice if "perf stat" had a way to have it
>> compute the ratios directly. Maybe a "-m, --math" option allowing
>> algebraic expressions where you could do:

Hi Andi,

So the missing event modifier is still a problem.  The events begins passed into the perf are not going to match the names on the output.  Also a script using the output perf is not going to be able to distinguish between the same event with different modifiers.

> 
> Most people just use -x, and load the result into a spread sheet or
> other script that does the compuations. At some point you usually want
> to plot the data or do other more complex manipulations than your
> simple facility would provide.
> 
> You may also find this script useful
> 
> https://github.com/andikleen/pmu-tools/blob/master/interval-normalize.py
> 
> -Andi
> 

Thanks for the pointer to the interval-normalize.py script.

Yes, many people are probably using other more sophisticated tools such as spread sheets to analyze the data from perf.  However, something like a "-m, --math" option would give a bit more insight than the basic "perf stat" without having to resort to more sophisticated tools.  "perf stat" is already generating all sorts of derived numbers such as IPC, events/second, and perccent of cache misses it seems like a small step to provide some flexibility for the user to specify exactly what to compute.


-Will