Messages in this thread | | | Date | Thu, 13 Aug 2009 10:35:24 +0200 | From | Ingo Molnar <> | Subject | Re: [UPDATED][PATCH][mmotm] Help Root Memory Cgroup Resource Counters Scale Better (v5) |
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* Balbir Singh <balbir@linux.vnet.ibm.com> wrote:
> Without Patch > > Performance counter stats for '/home/balbir/parallel_pagefault': > > 5826093739340 cycles # 809.989 M/sec > 408883496292 instructions # 0.070 IPC > 7057079452 cache-references # 0.981 M/sec > 3036086243 cache-misses # 0.422 M/sec
> With this patch applied > > Performance counter stats for '/home/balbir/parallel_pagefault': > > 5957054385619 cycles # 828.333 M/sec > 1058117350365 instructions # 0.178 IPC > 9161776218 cache-references # 1.274 M/sec > 1920494280 cache-misses # 0.267 M/sec
Nice how the instruction count and the IPC value incraesed, and the cache-miss count decreased.
Btw., a 'perf stat' suggestion: you can also make use of built-in error bars via repeating parallel_pagefault N times:
aldebaran:~> perf stat --repeat 3 /bin/ls
Performance counter stats for '/bin/ls' (3 runs):
1.108886 task-clock-msecs # 0.875 CPUs ( +- 4.316% ) 0 context-switches # 0.000 M/sec ( +- 0.000% ) 0 CPU-migrations # 0.000 M/sec ( +- 0.000% ) 254 page-faults # 0.229 M/sec ( +- 0.000% ) 3461896 cycles # 3121.958 M/sec ( +- 3.508% ) 3044445 instructions # 0.879 IPC ( +- 0.134% ) 21213 cache-references # 19.130 M/sec ( +- 1.612% ) 2610 cache-misses # 2.354 M/sec ( +- 39.640% )
0.001267355 seconds time elapsed ( +- 4.762% )
that way even small changes in metrics can be identified as positive effects of a patch, if the improvement is beyond the error percentage that perf reports.
For example in the /bin/ls numbers i cited above, the 'instructions' value can be trusted up to 99.8% (with a ~0.13% noise), while say the cache-misses value can not really be trusted, as it has 40% of noise. (Increasing the repeat count will drive down the noise level - at the cost of longer measurement time.)
For your patch the improvement is so drastic that this isnt needed - but the error estimations can be quite useful for more borderline improvements. (and they are also useful in finding and proving small performance regressions)
Ingo
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