On 01/08/2020 12:40, Paul A. Clarke wrote:
v4 changes:
   - removed acks from patch because it changed a bit
     with the last fixes:
       perf metric: Collect referenced metrics in struct metric_ref_node
   - fixed runtime metrics [Kajol Jain]
   - increased recursion depth [Paul A. Clarke]
   - changed patches due to dependencies:
       perf metric: Collect referenced metrics in struct metric_ref_node
       perf metric: Add recursion check when processing nested metrics
       perf metric: Rename struct egroup to metric
       perf metric: Rename group_list to metric_list

Also available in here:
   git://git.kernel.org/pub/scm/linux/kernel/git/jolsa/perf.git
   perf/metric
I built and ran from the above git branch, and things seem to work.
Indeed, I was able to apply my changes to exploit the new capabilities
via modifications to tools/perf/pmu-events/arch/powerpc/power9/metrics.json,
as I posted earlier (and will submit once this set gets merged).


Hi Paul,

I was just wondering: Does perf subtest 10.3 work ok for you with the metric reuse?

That's "Parsing of PMU event table metrics" subtest.

Hi Jirka,

If I add something like this:
    {
        "BriefDescription": "dummy test1",
        "MetricExpr": "Bad_Speculation + Frontend_Bound",
        "MetricGroup": "TopdownL1",
        "MetricName": "dummytest",
        "PublicDescription": "dummy test2"
    },

I get "Parse event failed metric 'dummytest' id 'bad_speculation' expr 'bad_speculation + frontend_bound'"

Thanks,
john

Tested-by: Paul A. Clarke<p...@us.ibm.com>

One thing I noted, but which also occurs without these patches, is that
the perf metrics are not computed unless run as root:
--
$ perf stat --metrics br_misprediction_percent command

  Performance counter stats for 'command':

      1,823,530,051      pm_br_pred:u
          2,662,705      pm_br_mpred_cmpl:u

$ /usr/bin/sudo perf stat --metrics br_misprediction_percent command

  Performance counter stats for 'command':

      1,824,655,269      pm_br_pred                #     0.09 
br_misprediction_percent
          1,654,466      pm_br_mpred_cmpl
--

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