On Mon, May 12, 2014 at 04:01:26PM -0700, Andi Kleen wrote: > From: Andi Kleen <[email protected]> > > perf stat -rX prints the stddev for multiple measurements. > Just looking at the stddev for judging the quality of the data > is a bit dangerous The simplest sanity check is to just look > at a simple plot. This patchs add a sparkline to the end > of the measurements to make it simple to judge the data. > > The sparkline only uses UTF-8, so should be readable > in all modern tools and terminals. > > The sparkline is between the minimum and maximum of the data, > so it's mainly a indicator of variance. To keep the code > simple and make the output not too wide only the first > 8 values are printed. If more values are there it adds '..' > > The code is inspired by Zach Holman's spark shell script. > > Example output (view in non-proportial font): > > Performance counter stats for 'true' (10 runs): > > 0.175672 task-clock (msec) # 0.555 CPUs utilized > ( +- 1.77% ) █▄▁▁▁▁▁▁.. > 0 context-switches # 0.000 K/sec > 0 cpu-migrations # 0.000 K/sec > 114 page-faults # 0.647 M/sec > ( +- 0.14% ) ▁█▁▁████.. > 520,798 cycles # 2.965 GHz > ( +- 1.75% ) █▄▁▁▁▁▁▁.. > 433,525 instructions # 0.83 insns per cycle > ( +- 0.28% ) ▅▇▅▄▇█▁▆.. > 83,012 branches # 472.537 M/sec > ( +- 0.31% ) ▅▇▆▄▇█▁▆.. > 3,157 branch-misses # 3.80% of all branches > ( +- 2.55% ) ▇█▃▅▁▃▁▂.. > > 0.000316660 seconds time elapsed > ( +- 1.78% ) █▅▁▁▁▁▁▁.. > > As you can see even in the most simple run there are quite interesting > patterns. The time sparkline suggests it would be also useful to have an > option > to throw the first measurement away.
Hmm, my first looking at the spark thingies interpreted them as a histogram. But they're not really. Would it be possible to make it a histogram of -2sigma,2sigma around the avg value? That way you can plot all data and get a good idea of the distribution. I'd suggest using 9 buckets for it.
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