.C(..., DUP=FALSE) memory costs depending on input size?

Hello,

I'm trying to create my own C code for use within R. While optimizing the
code I've noticed that even while only using pointers to get my data to C
the time needed still depends on data (vector) size.

To test this, I've created an empty C function to which I've send vectors
containing various sizes of elements. The time needed for each call is
measured and plotted. I would expect a flat line (a little above y=0) since
the only thing send are pointers. What I do not expect is to see a linear
climbing line when the vector size increases. Initializing the vectors isn't
being measured, only the '.C' call to an empty C function, see below.

Is there anything I'm missing that can explain this input-size dependent
latency? The only reason I can think of is that these vectors are being
copied along the way.

What follows is both the R and C code which I use only for testing and a
plot of both measurements with DUP=TRUE and DUP=FALSE:

(RED: DUP=FALSE, GREEN: DUP=TRUE)
http://www.nabble.com/file/p20368695/CandR.png


R code:
----------
# sequence from 512 to 2^23 with 2^17 stepsize
a <- seq(512, 2^23, 2^17)
# storage for wall time
h <- length(a); j <- length(a)
for (i in 1:length(a)) {
       x <- as.double(1:a[i])
       y <- as.double(x)
       # system.time()[3] is (actual) wall time
       h[i] <- system.time(.C("commTest", x, y, DUP=FALSE))[3]
       j[i] <- system.time(.C("commTest", x, y, DUP=TRUE))[3]
       x <- 0
       y <- 0
}
# plot:
plot(a, h, type="l", col="red", xlab="Vector Size -->", ylab="Time in
Seconds -->"); lines(a, j, col="green")


C code:
-----------
#include<R.h>
extern "C" {
       void commTest(double* a, double* b);
}

/*
* Empty function
* Just testing communication costs between R --> C
*/
void commTest(double* a, double* b) {
 /* Do ab-so-lute-ly-nothing.. */
}

System Details:
---------------------
Linux gpu 2.6.18-6-amd64 #1 SMP Thu May 8 06:49:39 UTC 2008 x86_64 GNU/Linux
R version 2.7.1 (2008-06-23)
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