[Rd] the incredible lightness of crossprod
pgilbert at bank-banque-canada.ca
Thu Jan 27 22:55:24 CET 2005
Prof Brian Ripley wrote:
> On Thu, 27 Jan 2005, Paul Gilbert wrote:
>> A few weeks ago I noticed
>>> z <- matrix(rnorm(20000),10000,2)
>>> system.time(for (i in 1:1000) apply(z,2,sum))
>>  13.44 0.48 14.08 0.00 0.00
>>> system.time(for (i in 1:1000) rep(1,10000) %*% z)
>>  6.46 0.11 6.84 0.00 0.00
> So both run in a few milliseconds for rather large problems.
>> which seemed completely contrary to all my childhood teachings. Now
>>> system.time(for (i in 1:1000) crossprod(rep(1,10000), z))
>>  1.90 0.12 2.24 0.00 0.00
>> makes sense because it is suppose to be faster than %*% , but why is
>> apply so slow?
> `so slow' sic: what are you going to do in the 7ms you saved?
Yes, I think I've spent more time checking this than I will ever save.
>> (And should I go back and change apply in my code everywhere or is
>> this likely to reverse again?)
> It's not likely. apply is an R-level loop, and %*% is a C-level one.
> However, %*% is not supposed to be much slower than crossprod, and
> the devil is in the details of how the BLAS is implemented: the code
> is very similar.
> That %*% was faster than apply has been true in all my (17 years) of
> S/R experience. Your childhood may predate S3, of course.
I didn't say the teachings were correct. I clearly should have
questioned some things sooner.
> I still think one should use row/colSums for clarity with acceptable
> efficiency. It must be very unusual for these operations to be a
> dominant part of a calculation, so let's not lose proportion here.
Agreed. I think I like the clarity reason best.
Thanks for the explanation.
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