# Problems with DSS routine

I am beginner of MKL. I just want to use the DSS routine to solve a large sparse matrix equation. I revised the DSS example according to the manual. But it could not work with the error message "forrtl: severe (157): Program Exception -access violation".

I wonder if DSS routine has a size limitation for the solving sparse matrix.

Could someone tell me how to fix this problem? Please find my code attached.

Your help would be fully appreciated.

# Symmetric sparse matrix - dense matrix multiplication

I need to multiply a symmetric sparse matrix A with a dense matrix X (Y = A*X) using multi-thread/core. The matrices I'm using are the adjacency matrix of graphs, with large number of nodes (up to 2 million nodes).

I have tried two approaches:

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# Function to solve the linear "less-equality"-constrained least squares (LSE)

`Hi, I know there is ?gglse that solves the linear equality-constrained least squares problem using a generalized RQ factorization`
```      minimize ||c - A*x||2 subject to B*x = d

However I would like to solve particular case:
```
`     minimize ||c - A*x||2 subject to B*x <= d`
`Is this possible, I have searched documentation but had no luck`

# Compiling R 3.0.2 with MKL

I'm not sure if R compiled correctly with MKL:

When I do ldd on R I don't see any reference to MKL

# Is there a problem with hemm() ?

If I multiply two complex diagonal 2x2 matrices, with chemm(), I don't get a diagonal matrix !

Here is the code for C=A.B

Matrix A is stored as an upper triangle hermitian matrix.

#include <cstdlib>
#include <iostream>
#include <cstdio>
#include <complex>
#include <math.h>

# misunderstanding of dss_create Direct Sparse Solver (DSS) Interface Routines

I need to use dss interface in c++ program.

From Intel® Math Kernel Library Reference Manual MKL 11.1, Page 2973:

The default value of the parameter opt is MKL_DSS_MSG_LVL_WARNING + MKL_DSS_TERM_LVL_ERROR.