Re: [boost] [xpressive] Performance Tuning?

Subject: Re: [boost] [xpressive] Performance Tuning?
From: Edward Grace (ej.grace_at_[hidden])
Date: 2009-07-28 17:19:37

>>
>> 42 	// operation to at least update the L1 cache.  *** Note: This
>> 43 	// concern is specific to the particular application at which
>> 44 	// we're targeting the test. ***
>>
>> that seems quite important but a little opaque out of context.
>
> It means the application we were going to use this technique on was
> going to update a long series of accumulators, which will certainly  
> not
> fit in a few registers.  We wanted to force the test to reflect that
> reality.

Ah, I did some hunting and found things for the iterative calculation  
of the mean - presumably this is an embodiment of the original  
application.

How various caches interact is not something I've given a great deal  
of thought to.  In practice it can presumably make or break the real  
'speed' of something.  I can see that there's a great difference in  
timing a large bunch of iterations of the same thing one after  
another and the actual typical execution characteristics of the same  
function in a different context.

This kind of thing is something I have to shrug my shoulders at  - I  
can see it's a potential issue but don't know enough to comment.

>> One thing I take exception to is the (effective) use of the mean as a
>> measurement of central tendency
>
> Why?

The mean is not a robust measure of central tendency.  Robust, in  
this context, means that a single arbitrarily large observation can  
shift the estimator (the mean in this case) arbitrarily far.

The median on the other hand is robust, a single arbitrarily large  
observation may not move the median at all.

Technically the 'breakdown point' of the mean is zero. For the  
obligatory Wikipedia overview see:

   http://tinyurl.com/l4vldr

>> - perhaps their trickery has eliminated the heavy tail.
>
> Why would one assume there is a heavy tail in the first place?

Informally speaking one may expect the OS to very-very occasionally  
interrupt a running function that nominally takes (say) 100 cycles  
and run of to do some disk IO.  That delay may will run into hundreds  
of millions of clock cycles.  Consequently that observation may  
differ from all the others by (say) six orders of magnitude.

Most probably of course that will not occur; that's a long tail -  
very rare events of extreme magnitude.  A bit like returns in stock  
market crashes only less frequent. ;-)

Less informally I've measured it!  On a log-log histogram plot of  
~10^7 measurements even trivial functions display a definite hint of  
Pareto-like [ http://tinyurl.com/ngnyk2 ] behaviour in the wings.

-ed

------------------------------------------------
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