Latest MKL API, doesn't handle the dense data to sparse
storage conversion. It expects pointers to rows, cols and
values arrays. It also returns sparse_matrix_t opaque handles
that we don't use inside ArrayFire. Hence, deprecated MKL API
has been removed in favor of our in-house kernels for conversions.

CPU and OpenCL backends have support for mul/div but they
are disabled to have feature parity with CUDA which doesn't
have support for mul/div.
The output of sub/div/mul is not guaranteed to have only
non-zero results of the arithmetic operation. The user has
to take care of pruning the zero results from the output.

- Includes tests to read sparse matrix from mtx file
cmake configure downloads the compressed mtx files, uncompresses
the files and places them under the source tree location
`test/data/matrixmarket` so that clean builds don't redownload
entire data set. Hence, a new change has been added to test/data
git repository to ignore the matrixmarket folder.
If for any reason download fails, MTX tests are disabled.