Shared-Memory Parallelization of MTTKRP for Dense Tensors
Published in PPoPP "18: Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (Short Paper), 2018
Recommended citation: Hayashi, Koby. (2018). "Shared-Memory Parallelization of MTTKRP for Dense Tensors." Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. http://hayakb95.github.io/files/Sharmed_Mem_MTTKRP_Full.pdf
Matricized Tensor Times Khatri-Rao Product (MTTKRP) is the main computational kernel when computing a CP Decomposition of tensors. This paper describes parallelization strategies for efficiently computing MTTKRP for dense tensors.
Recommended citation: ‘Koby Hayashi, Grey Ballard, Yujie Jiang, and Michael J. Tobia. 2018. Shared-memory parallelization of MTTKRP for dense tensors. SIGPLAN Not. 53, 1 (January 2018), 393–394. https://doi.org/10.1145/3200691.3178522’ Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming.