On Optimizing Distributed Tucker Decomposition for Sparse Tensors

@article{Chakaravarthy2018OnOD,
  title={On Optimizing Distributed Tucker Decomposition for Sparse Tensors},
  author={Venkatesan T. Chakaravarthy and J. Choi and D. Joseph and P. Murali and Y. Sabharwal and S. S. Pandian and D. Sreedhar},
  journal={Proceedings of the 2018 International Conference on Supercomputing},
  year={2018}
}
  • Venkatesan T. Chakaravarthy, J. Choi, +4 authors D. Sreedhar
  • Published 2018
  • Computer Science
  • Proceedings of the 2018 International Conference on Supercomputing
  • The Tucker decomposition generalizes the notion of Singular Value Decomposition (SVD) to tensors, the higher dimensional analogues of matrices. We study the problem of constructing the Tucker decomposition of sparse tensors on distributed memory systems via the HOOI procedure, a popular iterative method. The scheme used for distributing the input tensor among the processors (MPI ranks) critically influences the HOOI execution time. Prior work has proposed different distribution schemes: an… CONTINUE READING
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