[ExternalEmail] Pearson Correlation Speed

I'm trying to calculate Pearson correlation coefficients for a large
matrix of size 18563 x 18563. The following function takes about XX
minutes to complete, and I'd like to do this calculation about 15 times
and so speed is some what of an issue.

Does anyone have any suggestions on ways to speed this up? I'd wondered
if using C++ code to do the calculations might speed things up, but I've
never written any C/C++ code or attempted to use any within R.

I've seen some C++ code here:
http://www.alglib.net/statistics/correlation.php

I wondered if anyone might be able to help me get this so it can run in
R? I've tried the following:
1) download and unzipped
http://www.alglib.net/translator/dl/statistics.correlation.cpp.zip
2) moved the contents of the libs dir into the parent dir alongside
correlation.cpp (didn't know how to tell R where to look for C libraries)
3) Tried: "R CMD SHLIB correlation.cpp" and got the following as output:
-- start output --
icpc -I/tools/R/2.7.1/lib/R/include  -I/usr/local/include  -mp  -fpic
-g -O2 -c correlation.cpp -o correlation.o
ap.h(163): warning #858: type qualifier on return type is meaningless
  const bool operator==(const complex& lhs, const complex& rhs);
             ^

ap.h(164): warning #858: type qualifier on return type is meaningless
  const bool operator!=(const complex& lhs, const complex& rhs);
             ^

ap.h(179): warning #858: type qualifier on return type is meaningless
  const double abscomplex(const complex &z);
               ^

icpc -shared -L/usr/local/lib -o correlation.so correlation.o
-- end output --
4) Now this doesn't look brilliant! Any thoughts? Also, I'm assuming I
need to do some other work with the C++ code in order to allow me to use
it from within my R scripts - any pointers on that?

Thanks for any input - I hope I just need a hand over the initial
hurdles and then I can get onto that up-hill learning curve!!

Nathan