[Rcpp-devel] Segfault error during simulation in Rcpp

Sorry yesterday evening by mistake I sent a message only to Dirk:

Thanks, you are right I'll try cxxfunction and/or I'll see whether I can
move avoid doing so many calls to C++.

For the sake of minimality: this code is enough to have a segfault or to
make R stall
(at least on my computer):

library(Rcpp)
myFun <- cppFunction('NumericMatrix myFun(NumericMatrix input){ return
input; }')

n <- 10
x <- 1:n^2
N <- 1e6
b <- 0
A <- matrix(x, n, n)
for (j in 1:N) {
    res <- myFun(A)
    a <- res[1,1]
    b <- b + a
}

cat(sprintf("Done, b is %d\n", b))

Thanks a lot to everybody for the help!


On Fri, May 17, 2013 at 4:17 AM, Ivan Popivanov <ivan.popivanov at gmail.com>wrote:

Ignore my previous mail ...


On Thu, May 16, 2013 at 11:12 PM, Ivan Popivanov <
ivan.popivanov at gmail.com> wrote:

How is this code supposed to work? If n=1e6, then the matrix has 1e12
elements, right? That's in the terabyte range - the memory manager is going
to blow up or overflow and the results would be unpredictable. Or am I
missing something?

Regards,
Ivan


On Thu, May 16, 2013 at 7:14 PM, Jonathan Olmsted <jpolmsted at gmail.com>wrote:

Matteo,

The other obvious of course is that you are not forced to control a
loop over
10^6 elements from R either:  pass N=10^6 down to C++ code, and run
your N
loops there.  You will also get a considerable speed boost.

^ I could have been more explicit. This is what I meant. You might may
or may not be able to do this in the sourceCpp() framework, though. How you
do this is much more obvious if you go the route of making an Rcpp package.
For as much as the convenience functions are a blessing, I've always found
it hard to think about how I'd do more complex things with them. It could
be possible, I just don't see it. I find the package approach to be a nice
balance between abstracting away from some details but keeping some in the
forefront of your mind. If you email me off the list and I can send you a
very small package that using Rcpp. Multiple C++ functions are created,
only some are exposed to R.

It seems like you'd probably do something similar.

-Jonathan

 | On Thu, May 16, 2013 at 8:11 PM, Dirk Eddelbuettel <edd at debian.org>
wrote:
|
|
|     On 16 May 2013 at 14:49, Jonathan Olmsted wrote:
|     | Several things.
|     |
|     | Xiao, Dirk's code gives me a segfault immediately and reliably.
|     |
|     | All, when I do this whole song and dance using the "old"
Rcpp/inline/
|     | cxxfunction approach, I don't have any issues. One obvious
difference you
|     can
|     | see (like was mentioned) in the generated code (visibile using
verbose=
|     TRUE) is
|     | the declaration of an RNGScope object.
|     |
|     | But, if the memory issue crops up when you call a C++
function (syncing
|     with
|     | R's RNG state) 1e6 times AND you are already writing C++ maybe
this is
|     an
|     | opportunity to just put one more layer of the code into C++
and create
|     only one
|     | such RNGScope object?
|
|     Beautiful. So we get to blame R Core after all?  ;-)
|
|     Dirk
|
|     --
|     Dirk Eddelbuettel | edd at debian.org |
http://dirk.eddelbuettel.com
|     _______________________________________________
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--
Dirk Eddelbuettel | edd at debian.org | http://dirk.eddelbuettel.com