An MPI+OpenMP hybrid implementation of Gustavson's Sparse Matrix Multiplication for Boolean CSR matrices
Only final/ and Matlab/ are intended for use, old/ has some old code that is there for archiving purposes.
Go to final/ and do make
For performance testing the algorithm:
mpirun/srun -n number_of_tasks SpGEMM_mpi_omp path_to_matrix block_size number_of_threads times_to_run
number_of_tasks*path_to_matrix*block_size needs to equal the input's size n.
It can easily be extended to support matrices of any size by adding one row of the remaining workload to each thread but that was out of the scope of this assignment.
It prints in order:
tasks, threads, total_cpus/threads, blocksize, matrix path, input size n, input nnz, output nnz, mean time, median time, fastest time
For testing the validity of the algorithm, use Matlab/test_SpGEMM(n,d) where n is the size of the n*n random input sparse matrix and d is aproximately
the non zero elements per row that the matrix will have.
For testing the validity of the Hybrid MPI+OpenMP implementation, do make test in final/. It will run both the Hybrid and serial code on a test matrix
in Matlab/ and print either a confirm message if it they produce the same matrix or an error message otherwise.
old/ has the code of the serial implementation + previous implementations that used blocking but were much slower.