From braunm at MIT.EDU  Sat May 26 01:12:56 2007
From: braunm at MIT.EDU (Michael Braun)
Date: Fri, 25 May 2007 19:12:56 -0400
Subject: [Rd] R scripts slowing down after repeated called to compiled code
Message-ID: <1180134776.6736.15.camel@braunm1>

Thanks in advance to anyone that might be able to help me with this
problem.  I have not been able to find a reference to it in the
documentation on online sources, so I am turning to this group.

I am running R 2.4.1 under Red Hat Enterprise Linux 4, on an x86_64
platform (multi-core Intel Xeon processors, 3.6Ghx, 8GB of RAM).  I have
some rather complicated code (so I won't attach it here), but it is an
iterative algorithm that takes data in the form of an R list, passes the
entire list to some compiled C code, converts list items to GSL matrices
and vectors, performs its various operations, and sends back the result
to R.  That result is then sent back to the compiled code until some
kind of convergence (I won't bore the group with more details).

The problem is that every .Call to the compiled code runs slower (I
print the iteration time using Sys.time() and difftime() ).  There is no
logical reason for this (i.e., it's not a feature of the algorithm
itself).  I am using about 20% of my machine's available RAM (it's a
large dataset and a memory-intensive algorithm), but there does not
appear to be any swapping of memory to disk.  I am sure that I am
UNPROTECTING the SEXP's that I created, and I am freeing all of the GSL
objects at the end of each function.  The total RAM used does seem to
increase, slowly but steadily, but the speed decrease occurs well before
I start coming close to running out of RAM.

Also, it is not just the compiled call that slows down.  EVERYTHING
slows down, even those that consist only of standard R functions.  The
time for each of these function calls is roughly proportional to the
time of the .Call to the C function.

Another observation is that when I terminate the algorithm, do a rm
(list=ls()), and then a gc(), not all of the memory is returned to the
OS.  It is not until I terminate the R session that I get all of the
memory back.  In my C code, I am not doing anything to de-allocate the
SEXP's I create, relying on the PROTECT/UNPROTECT mechanism instead (is
this right?).

I spent most of the day thinking I have a memory leak, but that no
longer appears to be the case.  I tried using Rprof(), but that only
gives me the aggregated relative time spent in each function (more than
80% of the time, it's in the .Call).

So I'm stuck.  Can anyone help?

Thanks,

Michael





-- 
Michael Braun
Assistant Professor of Marketing
MIT Sloan School of Management
One Amherst St., E40-169
Cambridge, MA 02142
(617) 253-3436
braunm at mit.edu



[Rd] R scripts slowing down after repeated called to compiled code
Michael Braun