potential for GHC benchmarks w.r.t. optimisations being incorrect

Joachim Breitner mail at joachim-breitner.de
Sun May 6 14:59:22 UTC 2018


Hi,

Am Sonntag, den 06.05.2018, 16:41 +0200 schrieb Andreas Klebinger:
> With a high number of NoFibRuns (30+) , disabling frequency scaling,
> stopping background tasks and walking away from the computer
> till it was done I got noise down to differences of about +/-0.2% for
> subsequent runs.
> 
> This doesn't eliminate alignment bias and the like but at least it
> gives fairly reproducible results.

That’s true, but it leaves alignment bias. This bit my in my work on
Call Arity, as I write in my thesis:

   Initially, I attempted to use the actual run time measurements, but it
   turned out to be a mostly pointless endeavour. For example the knights
   benchmark would become 9% slower when enabling Call Arity (i.e. when
   comparing (A) to (B)), a completely unexpected result, given that the
   changes to the GHC Core code were reasonable. Further investigation
   using performance data obtained from the CPU indicated that with the
   changed code, the CPU’s instruction decoder was idling for more cycles,
   hinting at cache effects and/or bad program layout.
   Indeed: When I compiled the code with the compiler flag -g, which
   includes debugging information in the resulting binary, but should otherwise
   not affect the relative performance characteristics much, the unexpected
   difference vanished. I conclude that non-local changes to the
   Haskell or Core code will change the layout of the generated program
   code in unpredictable ways and render such run time measurements
   mostly meaningless.

   This conclusion has been drawn before [MDHS09], and recently, tools
   to mitigate this effect, e.g. by randomising the code layout [CB13], were
   created. Unfortunately, these currently target specific C compilers, so I
   could not use them here.

   In the following measurements, I avoid this problem by not measuring
   program execution time, but simply by counting the number of instructions performed.
   This way, the variability in execution time due to code
   layout does not affect the results. To obtain the instruction counts I employ
   valgrind [NS07], which runs the benchmarks on a virtual CPU and
   thus produces more reliable and reproducible measurements.

Unpleasant experience.

Cheers,
Joachim
-- 
Joachim Breitner
  mail at joachim-breitner.de
  http://www.joachim-breitner.de/
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