|90/10 rule... source? firstname.lastname@example.org (Jens Troeger) (2004-01-09)|
|Re: 90/10 rule... source? email@example.com (2004-01-12)|
|Re: 90/10 rule... source? firstname.lastname@example.org (Derek M Jones) (2004-01-12)|
|Re: 90/10 rule... source? email@example.com (2004-01-16)|
|Re: 90/10 rule... source? firstname.lastname@example.org (Mike Kent) (2004-01-16)|
|Re: 90/10 rule... source? email@example.com (Derek M Jones) (2004-01-17)|
|Re: 90/10 rule... source? firstname.lastname@example.org (James Cownie) (2004-01-22)|
|Re: 90/10 rule... source? email@example.com (2004-01-22)|
|Re: 90/10 rule... source? firstname.lastname@example.org (Derek M Jones) (2004-01-31)|
|From:||email@example.com (Nick Maclaren)|
|Date:||16 Jan 2004 22:25:25 -0500|
|Organization:||University of Cambridge, England|
|Posted-Date:||16 Jan 2004 22:25:24 EST|
Derek M Jones <firstname.lastname@example.org> wrote:
>> I am looking for a (the) original paper on the 90/10 rule of program
>> execution. So far I found this reference
>I think the 90/10 rule might qualify as an urban legend.
>Example 8 of Knuth's paper quotes a 90% figure, but many of the
>other examples are around the 50% mark (a few 70%'s).
Yes and no. I think that the rule is real, but it has been made into
a pseudo law of nature, which it isn't.
>[I think the 90/10 rule comes from databases, where long before there
>were computerized files it was well known that in most record systems,
>a small set of records got most of the lookups. -John]
Could well be.
I first came across it (in the late 1960s) in the form that you get
90% of the benefit for 10% of the effort; in that form, it is a pretty
good rule of thumb. But, even so, it makes no sense if interpreted
too much like a formula.
Since then, I found evidence of it in previous centuries, in such
forms as maintaining discipline: 90% of the trouble comes from 10% of
the people. I don't know how old it is in that form, and can no
longer remember where I saw it.
As far as program tuning an optimisation is concerned, the lowest I
have seen is in things like statistical packages, where it is common
for the time to be spent in a large proportion of the code. In such
cases, cleaning up code and using a good, general, optimiser gives the
The highest I have seen is in a few HPC codes run on specialist
systems, such as one where 98% of the time was spent in two, 99.99%
vectorisable loops. The loops were hundreds of lines long with lots
of calculations, but every cycle could be done in parallel, and the
loop count was fixed at about 30,000!
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