Parallel Nonnegative CP Decomposition of Dense Tensors
Published in 2018 IEEE 25th International Conference on High Performance Computing (HiPC), 2018
Recommended citation: G. Ballard, K. Hayashi and K. Ramakrishnan, "Parallel Nonnegative CP Decomposition of Dense Tensors," 2018 IEEE 25th International Conference on High Performance Computing (HiPC), Bengaluru, India, 2018, pp. 22-31, doi: 10.1109/HiPC.2018.00012. http://hayakb95.github.io/files/NTF_HiPC18.pdf
We present a distributed memory parallel algorithm for computing an approximate nonnegative CP decomposition of dense tensors. The algorithm uses dimensions trees to reduce computation and a tuned communication grid to reduce communication.
Recommended citation: ‘G. Ballard, K. Hayashi and K. Ramakrishnan, “Parallel Nonnegative CP Decomposition of Dense Tensors,” 2018 IEEE 25th International Conference on High Performance Computing (HiPC), Bengaluru, India, 2018, pp. 22-31, doi: 10.1109/HiPC.2018.00012.’ 2018 IEEE 25th International Conference on High Performance Computing (HiPC).