FEAT: sparse-sparse add/sub support #2312
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I have a pending issue on CPU backend that I am currently debugging but the other two backends work as expected. It is probably some typo, will get it soon. Update - Resolved: It was a mistake on my end mixing up custom code with MKL upstream calls that caused the segfaults. |
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Update: There are some additional changes I need to make to sparse array creation when MKL upstream is used in CPU backend. It involves replacing deprecated API with newest. |
umar456
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Oct 16, 2018
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I will look into the windows compiler errors tomorrow. |
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I have fixed windows compilation problems. 🤞 |
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umar456
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Nov 1, 2018
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Requires arrayfire/arrayfire-data#12 |
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umar456
reviewed
Nov 25, 2018
umar456
previously requested changes
Nov 25, 2018
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Addressed feedback, review again pls
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.
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umar456
reviewed
Dec 3, 2018
umar456
approved these changes
Dec 19, 2018
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CPU backend:
CUDA backend sparse-sparse add/sub
OpenCL backend sparse-sparse add/sub/div/mul
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.
Support for div/mul isn't exposed to the user yet as it is not uniform across all backends or even within CPU backend at the moment.
Also moved mkl interface defs in CPU backend into single source file