MKL library behaving differently in mex-files and in standalone C++ - c++

Question

I am trying to get GPc (https://github.com/SheffieldML/GPc) working in Matlab, using mex-files. I got the examples working, I took the bit I'm currently being interested in out as a standalone C++ program, that works just fine. However, when I try to do the same in a mex and run it through Matlab, I'm getting some errors, in particular:
MKL ERROR: Parameter 4 was incorrect on entry to DPOTRF.
or
** On entry to DPOTRF parameter number 4 had an illegal value
depending on whether I use the system version of MKL or the one Matlab carries along. The call to dpotrf is:
dpotrf_(type, nrows, vals, nrows, info);
with all variables valid (type="U", nrows=40, vals = double[40*40]) and with the interface:
extern "C" void dpotrf_(
const char* t, // whether upper or lower triangluar 'U' or 'L'
const int &n, // (input)
double *a, // a[n][lda] (input/output)
const int &lda, // (input)
int &info // (output)
);
(both are taken from GPc). LDA was originally supplied as ncols (which I believe is incorrect, but I didn't inquiry the library author about it yet), but it shouldn't make a difference, because this is called on a square matrix.
I feared that there might be problem with the references, so I changed the interface header to accept int* (like in http://www.netlib.org/clapack/clapack-3.2.1-CMAKE/SRC/dpotrf.c), but that started giving me segfaults, so it made me thinking the references there are right.
Does anybody have an idea what might be wrong?

Answer 1

I've tried to reproduce with an example on my end, but I'm not seeing any errors. In fact the result is identical to MATLAB's.
mex_chol.cpp
#include "mex.h"
#include "lapack.h"
void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[])
{
// verify arguments
if (nrhs != 1 || nlhs > 1) {
mexErrMsgTxt("Wrong number of arguments.");
}
if (!mxIsDouble(prhs[0]) || mxIsComplex(prhs[0])) {
mexErrMsgTxt("Input must be a real double matrix.");
}
if (mxGetM(prhs[0]) != mxGetN(prhs[0])) {
mexErrMsgTxt("Input must be a symmetric positive-definite matrix.");
}
// copy input matrix to output (its contents will be overwritten)
plhs[0] = mxDuplicateArray(prhs[0]);
// pointer to data
double *A = mxGetPr(plhs[0]);
mwSignedIndex n = mxGetN(plhs[0]);
// perform matrix factorization
mwSignedIndex info = 0;
dpotrf("U", &n, A, &n, &info);
// check if call was successful
if (info < 0) {
mexErrMsgTxt("Parameters had an illegal value.");
} else if (info > 0) {
mexErrMsgTxt("Matrix is not positive-definite.");
}
}
Note that MATLAB already ships with BLAS/LAPCK headers and libraries (Intel MKL implementation). In fact this is what $MATLABROOT\extern\include\lapack.h has as function prototype for dpotrf:
#define dpotrf FORTRAN_WRAPPER(dpotrf)
extern void dpotrf(
char *uplo,
ptrdiff_t *n,
double *a,
ptrdiff_t *lda,
ptrdiff_t *info
);
Here is how you compile the above C++ code:
>> mex -largeArrayDims mex_chol.cpp libmwblas.lib libmwlapack.lib
Finally let's test the MEX function:
% some random symmetric positive semidefinite matrix
A = gallery('randcorr',10);
% our MEX-version of Cholesky decomposition
chol2 = #(A) triu(mex_chol(A));
% compare
norm(chol(A) - chol2(A)) % I get 0
(Note that the MEX code returns the working matrix as is, where the LAPACK routine only overwrites half of the matrix. So I used TRIU to zero-out the other half and extract the upper part).