Thanks Paul for the hints.
After some tests, reducing portion of my code, I found that simply doing
a naive computation of 'crossprod' in C does NOT give exactly the same
results as calling the Fortran underlying routine (dsyrk) as used in the
R source code.
I will try the double 0.0 to see if it makes a difference.
What do you mean by
"You also need to be careful about
conversion from integer to real, to do double conversion."
?
Where are the trap in this type of conversion?
Thanks.
Renaud
On 10/09/2010 16:07, Paul Gilbert wrote:
With fortran I have always managed to be able to get identical results
on the same computer with the same OS. You will have trouble if you
switch OS or hardware, or try the same hardware and OS with different
math libraries. All the real calculations need to be double, even
intermediate variables. Also, I've had trouble with arrays not being
initialized to double 0.0. If you initialize to single 0.0 the
straggling bits can cause differences. You also need to be careful about
conversion from integer to real, to do double conversion. I'm not sure
about C, but I would guess there are some of the same problems.
Paul
-----Original Message-----
From: r-devel-boun...@r-project.org [mailto:r-devel-boun...@r-
project.org] On Behalf Of Renaud Gaujoux
Sent: September 10, 2010 6:47 AM
To: r-devel@r-project.org
Subject: [Rd] Non identical numerical results from R code vs C/C++
code?
Hi,
suppose you have two versions of the same algorithm: one in pure R, the
other one in C/C++ called via .Call().
Assuming there is no bug in the implementations (i.e. they both do the
same thing), is there any well known reason why the C/C++
implementation
could return numerical results non identical to the one obtained from
the pure R code? (e.g. could it be rounding errors? please explain.)
Has anybody had a similar experience?
By not identical, I mean very small differences (< 2.4 e-14), but
enough
to have identical() returning FALSE. Maybe I should not bother, but I
want to be sure where the differences come from, at least by mere
curiosity.
Briefly the R code perform multiple matrix product; the C code is an
optimization of those specific products via custom for loops, where
entries are not computed in the same order, etc... which improves both
memory usage and speed. The result is theoretically the same.
Thank you,
Renaud
--
Renaud Gaujoux
Computational Biology - University of Cape Town
South Africa
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