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Column-Segmented Sparse Matrix-Matrix Multiplication on Multicore CPUs

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CSeg

CSeg (Column-Segmented Sparse Matrix-Matrix Multiplication on Multicore CPUs) is a OpenMP based SpGEMM, Sparse Matrix-Matrix Multiplication, implementation.

💻 Source Code: [http://github.com/GT-TDAlab/CSeg]

CSeg is developed by the members of GT-TDAlab.

License

CSeg is distributed under BSD License. For details, see LICENSE.

The PIGO library is included as an external program. See PIGO LICENSE for details.

Contributors

Contact

For questions or supports open an issue or contact contributors via [email protected].

Citation

Citation for the CSeg (BibTeX):

    @inproceedings{An21-HiPC,
        title = {Column-Segmented Sparse Matrix-Matrix Multiplication},
        author = {Xiaojing An and \"Umit V. \c{C}ataly\"{u}rek},
        year = {2021},
        month = {Dec},
        booktitle = {HiPC21: 28th IEEE International Conference on High Performance Computing, Data, & Analytics},
        keywords = {SpGEMM}
    }

Compilers tested

  • icpc version 2021.2.0 (gcc version 9.2.0 compatibility)
  • gcc version 9.2.0 (GCC)

How to build

Run make from current folder:

make

How to run

You can use main executable to run CSeg from command line. We are using PIGO for parallel input, and currently support mtx inputs only.

Use main -h to see all options. An usage example, multiplying the matrices in ./exampleData

./main -A ./exampleData/gre_185_left.mtx -B ./exampleData/gre_185_right.mtx -t -w 1 -e 2
-> Loading inputs.
-> Matrix A at ./exampleData/gre_185_left.mtx statistics
                             Num of rows :        186
                             Num of cols :        201
                        Num of non-zeros :       1005
                              Max degree :          7
-> Matrix B at ./exampleData/gre_185_right.mtx statistics
                             Num of rows :        201
                             Num of cols :        211
                        Num of non-zeros :       1005
                              Max degree :          7

-> Warmup runs of SpGEMM
                   Statistics for SpGEMM :
                    Number of bits in Bh :          8
                    Number of bits in Bl :          0
                    Compression Ratio is :   0.483582, and compression is applied.
                         S has non-zeros :       1005, direct merging on dense array will be applied
   Construct S and get upperbound (secs) :   0.014287
                           max_widthComp :         26
                              max_widthH :         47
                               max_width :         47
                         max_collisionsH :         40
                                max_degA :          7
                                   flops :       5609
                        MallocPtr (secs) :   0.000001
                         Symbolic (secs) :   0.006328
                 MallocColIndices (secs) :   0.000008
                          Numeric (secs) :   0.006927
           Total runtime (warmup) (secs) :   0.027652


-> Perf runs of SpGEMM
   Construct S and get upperbound (secs) :   0.012966
                        MallocPtr (secs) :   0.000000
                         Symbolic (secs) :   0.010833
                 MallocColIndices (secs) :   0.000000
                          Numeric (secs) :   0.008451
                    Total runtime (secs) :   0.032293

   Construct S and get upperbound (secs) :   0.010876
                        MallocPtr (secs) :   0.000000
                         Symbolic (secs) :   0.011075
                 MallocColIndices (secs) :   0.000001
                          Numeric (secs) :   0.006498
                    Total runtime (secs) :   0.028485


-> Matrix C statistics
                             Num of rows :        186
                             Num of cols :        211
                        Num of non-zeros :       3093
                              Max degree :         24

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