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FEAT: sparse-sparse add/sub support #2312

Merged
merged 4 commits into from Dec 19, 2018
Merged

FEAT: sparse-sparse add/sub support #2312

merged 4 commits into from Dec 19, 2018

Commits on Nov 30, 2018

  1. Remove MKL usage from sparse to sparse/dense conversions 

    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.
    @9prady9
    9prady9 committed Nov 30, 2018
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  2. FEAT: sparse-sparse add/sub support 

    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.
    @9prady9
    9prady9 committed Nov 30, 2018
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  3. Changes to download and use mtx files 

    - 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.
    @9prady9
    9prady9 committed Nov 30, 2018
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  4. Sparse-Sparse arithmetic tests using MTX files

    @9prady9
    9prady9 committed Nov 30, 2018
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