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CSE5304—Project Proposal Parallel Matrix Multiplication

CSE5304—Project Proposal Parallel Matrix Multiplication. Tian Mi. An naive version with MPI. Result:. P 1 . P 2 . …. P i . …. P N . An naive version with MPI. P i .  P i. An naive version with MPI. Processor0 reads input file Processor0 distributes one matrix

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CSE5304—Project Proposal Parallel Matrix Multiplication

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  1. CSE5304—Project ProposalParallel Matrix Multiplication Tian Mi

  2. An naive version with MPI Result: P1 P2 … Pi … PN

  3. An naive version with MPI Pi  Pi

  4. An naive version with MPI • Processor0 reads input file • Processor0 distributes one matrix • Processor0 broadcasts the other matrix • All processors in parallel • Do the multiplication of each piece of data • Processor0 gathers the result • Processor0 writes result to output file

  5. MPI_Scatter

  6. MPI_Scatter

  7. MPI_Bcast

  8. MPI_Bcast

  9. MPI_Gather

  10. MPI_Gather

  11. Data generation • Data generation in R with package “igraph” • Integer in range of [-1000, 1000] • Matrix size:

  12. Result • Data size: 1024*1024

  13. Result • Data size: 1024*1024

  14. Result • Data size: 1024*1024

  15. Result • Data size: 2048*2048

  16. Result • Data size: 2048*2048

  17. Result • Data size: 2048*2048

  18. Result • Data size: 4096*4096

  19. Analysis • To see the superlinear speedup • increase the computation, which is not dominant enough • larger matrix and larger integer • However, larger matrix or long integer will also increase the communication time (broadcast, scatter, gather)

  20. Cannon's algorithm--Example • http://www.vampire.vanderbilt.edu/education-outreach/me343_fall2008/notes/parallelMM_10_09.pdf

  21. Cannon's algorithm • Still Implementing and debugging • No result to share at present

  22. Thank you • Questions & Comments?

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